From a21e31698afdd73084bbbe3afd850a76478a3feb Mon Sep 17 00:00:00 2001 From: Danila Date: Fri, 8 May 2026 04:55:37 +0300 Subject: [PATCH] Complete the work with scikit --- requirements.txt | 6 + venv/.gitignore | 28 + venv/README.md | 18 + week4_scikit_learn.ipynb | 1805 ++++++++++++++++++++++++++++++++++++++ 4 files changed, 1857 insertions(+) create mode 100644 requirements.txt create mode 100644 venv/.gitignore create mode 100644 venv/README.md create mode 100644 week4_scikit_learn.ipynb diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..51107da --- /dev/null +++ b/requirements.txt @@ -0,0 +1,6 @@ +scikit-learn==1.8.0 +matplotlib==3.7.2 +pandas==2.0.3 +openml==0.14.0 +jupyterlab==4.5.7 +numpy==1.24.3 \ No newline at end of file diff --git a/venv/.gitignore b/venv/.gitignore new file mode 100644 index 0000000..80a538e --- /dev/null +++ b/venv/.gitignore @@ -0,0 +1,28 @@ +venv/ +__pycache__/ +*.pyc +.DS_Store +.ipynb_checkpoints/ +*.egg-info/ +dist/ +build/ +* +env/ +ENV/ + +*.ipynb_checkpoints + +*.py[cod] +*.so +.Python + +*.csv +*.pkl +*.h5 +data/ + +.idea/ +.vscode/ +*.swp + +Thumbs.db \ No newline at end of file diff --git a/venv/README.md b/venv/README.md new file mode 100644 index 0000000..88d20d8 --- /dev/null +++ b/venv/README.md @@ -0,0 +1,18 @@ +# Самостоятельное задание: Model Selection - Multiclass ROC + +## Информация +- **Раздел:** Model Selection +- **Пример:** Multiclass Receiver Operating Characteristic (ROC) + +## Содержание +1. Часть 1: Работа с датасетом Iris (встроенный) +2. Часть 2: Работа с внешним датасетом (Wine Quality) + +## Результаты +- Iris: ROC AUC (macro) = 0.78 +- Wine Quality: ROC AUC (macro) = [результат] + +## Запуск +```bash +pip install -r requirements.txt +jupyter lab \ No newline at end of file diff --git a/week4_scikit_learn.ipynb b/week4_scikit_learn.ipynb new file mode 100644 index 0000000..55b0a13 --- /dev/null +++ b/week4_scikit_learn.ipynb @@ -0,0 +1,1805 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "f63c8744-c58c-4b0d-a8db-ad9e910d2461", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "# КОД ИЗ МЕТОДИЧКИ" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "4c3e103f-575f-499f-96ed-cd536f6af5e2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 1.00 1.00 1.00 11\n", + " 1 1.00 1.00 1.00 9\n", + " 2 1.00 1.00 1.00 10\n", + "\n", + " accuracy 1.00 30\n", + " macro avg 1.00 1.00 1.00 30\n", + "weighted avg 1.00 1.00 1.00 30\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\USER\\PycharmProjects\\Practice4\\venv\\Lib\\site-packages\\sklearn\\neural_network\\_multilayer_perceptron.py:785: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (500) reached and the optimization hasn't converged yet.\n", + " warnings.warn(\n" + ] + } + ], + "source": [ + "from sklearn.datasets import load_iris\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.neural_network import MLPClassifier\n", + "from sklearn.metrics import classification_report\n", + "\n", + "# Загрузка и разбиение данных\n", + "X, y = load_iris(return_X_y=True)\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n", + "\n", + "# Модель MLP — многослойный перцептрон\n", + "clf = MLPClassifier(hidden_layer_sizes=(10,), activation='relu', max_iter=500)\n", + "clf.fit(X_train, y_train)\n", + "\n", + "# Отчёт о точности\n", + "print(classification_report(y_test, clf.predict(X_test)))" + ] + }, + { + "cell_type": "markdown", + "id": "3bfe56c7-95ba-48c6-b77f-75ed92c98298", + "metadata": {}, + "source": [ + "# Пример с https://scikit-learn.org/stable/auto_examples/neural_networks/plot_mnist_filters.html" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "c7d55251-fcde-45df-8a0c-1889bc1badb2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration 1, loss = 0.44139186\n", + "Iteration 2, loss = 0.19174891\n", + "Iteration 3, loss = 0.13983521\n", + "Iteration 4, loss = 0.11378556\n", + "Iteration 5, loss = 0.09443967\n", + "Iteration 6, loss = 0.07846529\n", + "Iteration 7, loss = 0.06506307\n", + "Iteration 8, loss = 0.05534985\n", + "Training set score: 0.986429\n", + "Test set score: 0.953061\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import warnings\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from sklearn.datasets import fetch_openml\n", + "from sklearn.exceptions import ConvergenceWarning\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.neural_network import MLPClassifier\n", + "\n", + "# Load data from https://www.openml.org/d/554\n", + "X, y = fetch_openml(\"mnist_784\", version=1, return_X_y=True, as_frame=False)\n", + "X = X / 255.0\n", + "\n", + "# Split data into train partition and test partition\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0, test_size=0.7)\n", + "\n", + "mlp = MLPClassifier(\n", + " hidden_layer_sizes=(40,),\n", + " max_iter=8,\n", + " alpha=1e-4,\n", + " solver=\"sgd\",\n", + " verbose=10,\n", + " random_state=1,\n", + " learning_rate_init=0.2,\n", + ")\n", + "\n", + "# this example won't converge because of resource usage constraints on\n", + "# our Continuous Integration infrastructure, so we catch the warning and\n", + "# ignore it here\n", + "with warnings.catch_warnings():\n", + " warnings.filterwarnings(\"ignore\", category=ConvergenceWarning, module=\"sklearn\")\n", + " mlp.fit(X_train, y_train)\n", + "\n", + "print(\"Training set score: %f\" % mlp.score(X_train, y_train))\n", + "print(\"Test set score: %f\" % mlp.score(X_test, y_test))\n", + "\n", + "fig, axes = plt.subplots(4, 4)\n", + "# use global min / max to ensure all weights are shown on the same scale\n", + "vmin, vmax = mlp.coefs_[0].min(), mlp.coefs_[0].max()\n", + "for coef, ax in zip(mlp.coefs_[0].T, axes.ravel()):\n", + " ax.matshow(coef.reshape(28, 28), cmap=plt.cm.gray, vmin=0.5 * vmin, vmax=0.5 * vmax)\n", + " ax.set_xticks(())\n", + " ax.set_yticks(())\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "bc0a9278-f49b-40ef-9ca5-affa8f9dbc8e", + "metadata": {}, + "source": [ + "# ВЫПОЛНЕНИЕ САМОСТОЯТЕЛЬНОГО ЗАДАНИЯ" + ] + }, + { + "cell_type": "markdown", + "id": "7df8f048-1d56-4464-97fa-847ea9149e0d", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## Искусственные нейронные сети\n", + "\n", + "### Описание проекта\n", + "Проект по изучению базовых принципов построения и обучения искусственных нейронных сетей на Python с использованием библиотеки scikit-learn.\n", + "\n", + "### Цели задачи\n", + "- Освоить базовые принципы работы MLP (многослойного перцептрона)\n", + "- Научиться использовать MLPClassifier из scikit-learn\n", + "- Применить нейронные сети к реальным задачам классификации\n", + "- Визуализировать и интерпретировать результаты" + ] + }, + { + "cell_type": "markdown", + "id": "b201551f-39a6-4794-86c3-421003dffa5d", + "metadata": {}, + "source": [ + "### Датасет Iris" + ] + }, + { + "cell_type": "markdown", + "id": "99061866-3cb8-43cf-85e7-b2a85f728973", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Импорт библиотек" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "84ffeb8b-ed0b-498b-b892-be814aa68f09", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Все библиотеки импортированы\n" + ] + } + ], + "source": [ + "# Импорт всех необходимых библиотек\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from itertools import cycle\n", + "\n", + "# Scikit-learn модули\n", + "from sklearn.datasets import load_iris\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.preprocessing import LabelBinarizer\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.metrics import RocCurveDisplay, roc_curve, auc, roc_auc_score\n", + "\n", + "# Настройка визуализации\n", + "plt.style.use('seaborn-v0_8-darkgrid')\n", + "np.random.seed(42)\n", + "\n", + "print(\"Все библиотеки импортированы\")" + ] + }, + { + "cell_type": "markdown", + "id": "66d4e587-f86e-4da1-848b-f230adf5a4bd", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Подготовка данных" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "bf33c40f-6e14-4f9b-bb2f-ceb7928f1fa2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Исходные данные:\n", + " Размер X: (150, 4)\n", + " Классы: ['setosa' 'versicolor' 'virginica']\n", + " Распределение классов: (array(['setosa', 'versicolor', 'virginica'], dtype='" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Выбираем класс для анализа (например, virginica)\n", + "class_of_interest = \"virginica\"\n", + "class_id = np.flatnonzero(label_binarizer.classes_ == class_of_interest)[0]\n", + "\n", + "print(f\"Анализируем класс: {class_of_interest} (ID: {class_id})\")\n", + "\n", + "# Построение ROC-кривой\n", + "display = RocCurveDisplay.from_predictions(\n", + " y_onehot_test[:, class_id],\n", + " y_score[:, class_id],\n", + " name=f\"{class_of_interest} vs the rest\",\n", + " color=\"orange\",\n", + " plot_chance_level=True, # показывает диагональную линию (AUC=0.5)\n", + ")\n", + "\n", + "display.ax_.set(\n", + " xlabel=\"False Positive Rate (FPR)\",\n", + " ylabel=\"True Positive Rate (TPR)\",\n", + " title=\"ROC-кривая: Virginica против всех остальных\",\n", + ")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "2c825c70-45ac-4a77-9cb3-63f30792ec13", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "##### Интерпретация\n", + "\n", + "На графике показано, насколько хорошо модель отличает цветки **Virginica** от **Setosa** и **Versicolor**.\n", + "\n", + "- **Кривая находится выше диагонали** — модель работает лучше случайного угадывания.\n", + "- **Изгиб кривой** показывает, что можно найти порог с хорошим балансом TPR и FPR.\n", + "- **AUC** (площадь под кривой) = 0.77 (выводится на графике)." + ] + }, + { + "cell_type": "markdown", + "id": "36d48f00-cb2b-44fe-a688-6390364b7e38", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Микро-усреднение" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "93a74aa5-d376-469a-bee0-1ba66fc8b929", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\USER\\PycharmProjects\\Practice4\\venv\\Lib\\site-packages\\sklearn\\utils\\_plotting.py:176: FutureWarning: `**kwargs` is deprecated and will be removed in 1.9. Pass all matplotlib arguments to `curve_kwargs` as a dictionary instead.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Micro-averaged ROC AUC score: 0.7699\n", + "Ручной расчет AUC: 0.7699\n" + ] + } + ], + "source": [ + "# Микро-усреднение через ravel()\n", + "display = RocCurveDisplay.from_predictions(\n", + " y_onehot_test.ravel(),\n", + " y_score.ravel(),\n", + " name=\"micro-average OvR\",\n", + " color=\"orange\",\n", + " plot_chance_level=True,\n", + ")\n", + "display.ax_.set(\n", + " xlabel=\"False Positive Rate\",\n", + " ylabel=\"True Positive Rate\",\n", + " title=\"Микро-усредненная ROC-кривая (One-vs-Rest)\",\n", + ")\n", + "plt.show()\n", + "\n", + "# Альтернативный расчет AUC через roc_auc_score\n", + "micro_roc_auc_ovr = roc_auc_score(\n", + " y_test, y_score, multi_class=\"ovr\", average=\"micro\"\n", + ")\n", + "print(f\"Micro-averaged ROC AUC score: {micro_roc_auc_ovr:.4f}\")\n", + "\n", + "# Ручной расчет через roc_curve и auc\n", + "fpr_micro, tpr_micro, _ = roc_curve(y_onehot_test.ravel(), y_score.ravel())\n", + "roc_auc_micro = auc(fpr_micro, tpr_micro)\n", + "print(f\"Ручной расчет AUC: {roc_auc_micro:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "1b558ce9-f1ab-45d6-b953-9936fa5f9ae8", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "##### Интерпретация микро-усреднения\n", + "\n", + "**Микро-усреднение** объединяет все классы вместе:\n", + "- Каждый образец (не класс) вносит вклад в общую метрику\n", + "- TPR и FPR вычисляются глобально по всем классам\n", + "- AUC = 0.77 означает, что в 77% случаев модель правильно ранжирует пары (положительный, отрицательный)\n", + "\n", + "**Когда использовать:** При дисбалансе классов — микро-усреднение показывает общую производительность на всех образцах." + ] + }, + { + "cell_type": "markdown", + "id": "af15222a-ab61-462c-9203-a24ef4be0c73", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Макро усреднение" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "ad1ab35d-45a4-4c3e-8375-677c144b0587", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Macro-averaged ROC AUC score: 0.7762\n", + "Проверка через roc_auc_score: 0.7760\n" + ] + } + ], + "source": [ + "# Хранение кривых для каждого класса\n", + "fpr, tpr, roc_auc = {}, {}, {}\n", + "\n", + "# Расчет ROC для каждого класса\n", + "for i in range(n_classes):\n", + " fpr[i], tpr[i], _ = roc_curve(y_onehot_test[:, i], y_score[:, i])\n", + " roc_auc[i] = auc(fpr[i], tpr[i])\n", + "\n", + "# Создание сетки точек для интерполяции\n", + "fpr_grid = np.linspace(0.0, 1.0, 1000)\n", + "\n", + "# Интерполяция всех кривых для усреднения\n", + "mean_tpr = np.zeros_like(fpr_grid)\n", + "for i in range(n_classes):\n", + " mean_tpr += np.interp(fpr_grid, fpr[i], tpr[i])\n", + "\n", + "mean_tpr /= n_classes\n", + "roc_auc_macro = auc(fpr_grid, mean_tpr)\n", + "\n", + "print(f\"Macro-averaged ROC AUC score: {roc_auc_macro:.4f}\")\n", + "\n", + "# Эквивалентный расчет через roc_auc_score\n", + "macro_roc_auc_ovr = roc_auc_score(\n", + " y_test, y_score, multi_class=\"ovr\", average=\"macro\"\n", + ")\n", + "print(f\"Проверка через roc_auc_score: {macro_roc_auc_ovr:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "f67ef939-b647-4279-81bf-98aff0cc2e63", + "metadata": {}, + "source": [ + "##### Интерпретация макро-усреднения\n", + "\n", + "**Макро-усреднение** сначала вычисляет AUC для каждого класса отдельно, затем усредняет:\n", + "\n", + "- Класс Setosa: AUC ≈ 1.00 (идеально)\n", + "- Класс Versicolor: AUC ≈ 0.70\n", + "- Класс Virginica: AUC ≈ 0.77\n", + "- **Итоговое макро-AUC = 0.78**\n", + "\n", + "**Когда использовать:** Когда важна производительность на каждом классе, особенно на малочисленных." + ] + }, + { + "cell_type": "markdown", + "id": "b091d701-da07-4f14-8830-f866367c7cb0", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Все OvR кривые вместе" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "f94a2b7f-02e8-4fb8-a1e5-0fcde855832a", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\USER\\PycharmProjects\\Practice4\\venv\\Lib\\site-packages\\sklearn\\utils\\_plotting.py:176: FutureWarning: `**kwargs` is deprecated and will be removed in 1.9. Pass all matplotlib arguments to `curve_kwargs` as a dictionary instead.\n", + " warnings.warn(\n", + "C:\\Users\\USER\\PycharmProjects\\Practice4\\venv\\Lib\\site-packages\\sklearn\\utils\\_plotting.py:176: FutureWarning: `**kwargs` is deprecated and will be removed in 1.9. Pass all matplotlib arguments to `curve_kwargs` as a dictionary instead.\n", + " warnings.warn(\n", + "C:\\Users\\USER\\PycharmProjects\\Practice4\\venv\\Lib\\site-packages\\sklearn\\utils\\_plotting.py:176: FutureWarning: `**kwargs` is deprecated and will be removed in 1.9. Pass all matplotlib arguments to `curve_kwargs` as a dictionary instead.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Построение всех кривых на одном графике\n", + "fig, ax = plt.subplots(figsize=(8, 6))\n", + "\n", + "# Микро-усреднение\n", + "plt.plot(\n", + " fpr_micro, tpr_micro,\n", + " label=f\"micro-average (AUC = {roc_auc_micro:.2f})\",\n", + " color=\"pink\", linestyle=\":\", linewidth=4,\n", + ")\n", + "\n", + "# Макро-усреднение\n", + "plt.plot(\n", + " fpr_grid, mean_tpr,\n", + " label=f\"macro-average (AUC = {roc_auc_macro:.2f})\",\n", + " color=\"green\", linestyle=\":\", linewidth=4,\n", + ")\n", + "\n", + "# Кривые для каждого класса\n", + "colors = cycle([\"black\", \"red\", \"blue\"])\n", + "for class_id, color in zip(range(n_classes), colors):\n", + " RocCurveDisplay.from_predictions(\n", + " y_onehot_test[:, class_id],\n", + " y_score[:, class_id],\n", + " name=f\"ROC curve for {target_names[class_id]}\",\n", + " color=color,\n", + " ax=ax,\n", + " plot_chance_level=(class_id == 2),\n", + " )\n", + "\n", + "ax.set(\n", + " xlabel=\"False Positive Rate\",\n", + " ylabel=\"True Positive Rate\",\n", + " title=\"ROC-кривые для стратегии One-vs-Rest\",\n", + ")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "d771445d-aa24-489e-a9ee-367b799d23cd", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "##### Интерпретация общего графика OvR\n", + "\n", + "График наглядно демонстрирует:\n", + "\n", + "1. **Setosa (черная кривая)** — идеально отделяется от других классов (кривая в левом верхнем углу)\n", + "2. **Versicolor (красная)** и **Virginica (синяя)** — отделяются хуже, их кривые проходят ближе к диагонали\n", + "3. **Микро-усреднение (розовый пунктир)** — показывает общее качество на всех образцах\n", + "4. **Макро-усреднение (зеленый пунктир)** — среднее между тремя кривыми\n", + "\n", + "**Вывод:** Основная сложность для модели — различить классы Versicolor и Virginica." + ] + }, + { + "cell_type": "markdown", + "id": "910bc75c-866c-43f6-b951-c86d74c07e56", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Стратегия One-vs-One" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "a1793d2a-04ea-4e66-b962-b69ad29fcc0f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Пары классов для OvO:\n", + " setosa vs versicolor\n", + " setosa vs virginica\n", + " versicolor vs virginica\n" + ] + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhIAAAIcCAYAAACjN0fPAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjksIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvJkbTWQAAAAlwSFlzAAAPYQAAD2EBqD+naQAAouFJREFUeJztnQd4FFUXhg8pkITQktCRXqUIgvTeOwQI0kFQQaRLrwLSmxRRiiBVBSkivakgShHpPyBIEQQEQicJpOz/fDfOsi19k23f+zxD2Nkpd+7Mzv3uOefek0qn0+mEEEIIISQRuCVmJ0IIIYQQCglCCCGEJAlaJAghhBCSaCgkCCGEEJJoKCQIIYQQkmgoJAghhBCSaCgkCCGEEJJoKCQIIYQQkmgoJAghKQrnwCPEuaCQIDajc+fOUqRIEaOlaNGi8uabb0qrVq3k+++/t7jf/v375d1335UKFSpIqVKlpEGDBjJlyhS5fft2jOfatWuX9OjRQypXriylS5eWpk2bysKFC+XZs2fJeIXElOPHj8v777/PiklG8DuaP3++VY9Zu3ZtGT58uFWPSZwHD1sXgLg2r7/+uowbN07/OTIyUu7cuSNfffWVDB06VDJmzCg1atTQfz9+/HhZu3atNGnSRCZOnCjp06eXy5cvy6pVq2TTpk0yb948qVixon77qKgoGTJkiOzcuVNat24t7du3l7Rp08rJkyflyy+/lL1796pz4Tgk+Vm/fr389ddfrOpk5Ntvv5Vs2bKxjkmKQSFBbIqvr6+yEJhSvXp1qVSpkmzcuFEvJNasWaNExNSpUyUwMFC/LYRDy5Yt5b333pMBAwbI1q1bJSAgQH23dOlS9XnBggVSr149/T44dvny5aVjx47y2WefyYgRI1LkeglJbiz9nghJTujaIHZJmjRpJHXq1JIqVSq9peLzzz+XqlWrGokIQ0HyySefyMOHD5XgAOHh4bJs2TIlSgxFhEbZsmWlX79+UrBgwVjLApMuTLsaOGaZMmXkm2++kSNHjihT8i+//KJECVwt9evXV4InNnMz4gTatWun1t+8eVN/HkM3DxoEbHPu3DkjdxCW+JYVwOoCV1HJkiWlSpUqqp5CQkL03+P88TGHr1ixQho2bKiOU61aNfn444+NXEOw/ixevFjVdYkSJZTLCZYiw7LBavTPP/+o80EkgqdPnyrXVN26ddWx4Xb67rvvjM599uxZ6dq1q7pnqPtu3bopq5KptQPXiXrDfWjRooXs2LEjxuv54osvVDkfP35stB4WquLFi0twcLC6pjlz5qg6xbb4O2vWLPVsWeKPP/5Q1/bjjz8arT9//rxav2fPHvX5xYsXMn36dCWScdxmzZrJ9u3bjfbBuSZPnqyuG9czatSoeN0H03t59+5dGTZsmBLPqLtOnTrJiRMn9N+jLBDT2jHx/OI+4tpjIj73LKbyE+eDFgliU9CgRkRE6D9DMKChwYvt+fPnqjHQXsT37t2TDz74IMZjFShQQMVY7Nu3T/r3768aYAiLWrVqxbhP7969E1Tef//9V2bPni0TJkxQjQDcKmDgwIHKKtKrVy91frhgQIcOHSweB/Efhi9zjcyZMyvrCV7icPGgHvr06aOO6eaWcN3/ww8/yODBg1VDBWsN6hYNI8q9fPlyJdSyZMkSpzkcVp0ZM2aoBgkN1ZUrV2TatGkSGhqq/gI0aBAHPXv2VA3WsWPHVEPy5MkT+fDDD1VdP3jwQP73v/+pa8ydO7eEhYWpOkKjDVGXM2dOJXzQ6Ny/f1/VJxpJxMTA8oQG8uXLl0pUIublp59+knTp0inxCIHUt29fJTYgDpYsWaKuHWWxdG2ok08//VR2794tQUFB+vXbtm1TgtXf318WLVokX3/9tbru1157TU6dOqXqz9PTU5XXFMT34LpwDMPnDvWnuenwzKM+IDpwDDy3EBh4hnBteI40cF3vvPOOsrbBJRef+2AIfkNw5+F3BRdf1qxZlRDu3r27EnV58uRRdQxRhucMvx+IY9TLjRs3lPvQlPjcs5jKT5wTCgliU9DYoPdnCBq3woULy9y5c/UvY63XnitXrliPhxfjoUOH1P+14Mu49kkIsELgZYueL9CEBHrhWo8LvUT0AhHMiZe4ZlUxfLnPnDlTXbehtQHACmNomkbDi5c5/mrumviCBgvnQXnwVyNv3ryqR//zzz9LzZo1zc5piaNHj6p6hNUFggZuIR8fH31v/urVq7Ju3ToZNGiQPpgSjTGuHY0xGh40sH5+fkbng+Xmzz//VPWKBl+rP4hL1B8sMteuXVOCsEuXLqqhBvnz51fiB3UJIYFGD8LCUBiigcN9QoAnYmpMwfdvvfWWapw1IfH333/L6dOnlVjQrhsWA8TXAFy3t7e3OmdMNG/eXDXWaHC9vLzUfYC1AT1+XDuez4MHD6pzNG7cWH/NEAO4T+jde3hEv5pz5MihxJAGGv/Y7oMpmgUIf4sVK6bWoQ4hVvDbu379uvz6669KHGt1BKsVyo3fH+q8UKFCRseEWIzrnkE0WSo/cU7o2iA2BY0pTKJY8BKCgEBDhx4RXrymQwa1F2xMuLu7m20bm4nWEPTa8DLUFnw2BL0/NHyWXAum7haYh2FBQQNrCq4zU6ZMSmRYAueG6RxCCA0QGjw0wKZWnLiuC+WFVQMmZsPrQuMJV5AmuOIDrAG4FjTMsCacOXNG9ei1ujh8+LAql+m58BmmczTmlkBDjevTGiTDxhj7wQKAhgzXj57u2LFjVe8dogo9bM3SALcJGixYP9C7hsVHc3Ghlx8TOA8aVNwrAEsC6kZzD2FkEOoJQgjxNhCOcA1olrKYjgnXkebegOXh1q1b+n1+++03JbBgnTCtK5Tj0qVL+mNpjX9874MpqHcID8PjQAhhFBPEE+ofvxPD35p2Ddr9Scw9i6n8xDmhRYLYFJg74WPVeOONN9QLCaZX9Hy0BhQvLoDeVWygZ6pti95QXPugp4+GAz1F9NINX5zo7Wk+fhyjUaNGykJiqRGBydgQmMWBaU8RvWv4uNEooXExBecxtdAguNTQrWFoxYEgQY8ZZmlTq8KjR4/UX7hZNFeLIbCaxBf0nCFcIKQghOBiQD2j8cZ32rks9fw1l5AlUD9w55iiWV8gDPCMQBTAnYGYB1gi0GPGfRg9erS6d7AkQGSgkYbbARYLWI7imrcCDSgsPjguet8QEojtwPEBXCo4/4YNG5S1AG4FCBuc13B0kKlVDI0sjoVnBn9hjdGsKagrlEn7bOm+aA0wrA0JuQ+m4FzasxhT/eMZggA3RLsniIVIzD3TMC0/cU4oJIhdgZcRGgTEOEyaNEkFtgE0lvDlYxhn27ZtYxQR8L/DHwvwMsbxDhw4oEzBlkCDgB4sfO1obGEq1zD06eLFCbM9YiMQtwAftyEwvaOx0ID/GJi+xBEzUKdOHdUIacGGhuA8aDAByrJ69WoVe4Dts2fPrtZDRKCsaIzQUKxcuVL5oU2D9bQhrRhGC1FkSoYMGSQhwOSOBY0LgksRgwCrAGIStHNBJFnyhWuizlIZYF43RbMQoJEDEAZoxGElgusBFgfELqDOITrhToGAgGUL9x29bFgPYpqLRAMuClgCICRQx7AGjBkzRv89BByeHSy4p3AHIUgTsRiwVEDEWAJiGMGIqCs8s4bWJ5wTDSzuW0xCJLH3wVTQ4lyaW9AQWElQ91jw7KJeDcWEJjK1+k/MPSOuA10bxO5ALxE+V/iuNQsBXujodePljQbEFPijR44cqV6cWoAj9oGVASIBk1iZAnM8GgbNd43GCtYRbcFnDXwPczJe2DAp40VsCILNDEHjgZ6iobiAoEEgGwLlYgLn0c6Phg3BbLg2wxEKmhUHkfAYkYLeKEzpGNlgCMoPIYOGxPC60NhAoEF0xRcEamriCXWMnjbiEWCSR6NTrlw59R0aJcNzweIDX7tmsTANGIWbBVYY08DTLVu2KGGAa0Rdoi7QUKGxQ28f4griBVYdnBPm/jZt2qhzai4t1DeIywUEywbqF88VBI+h6IK/H0GcAHWJZwCiAr3u2CYzg3UAQg/XDgGiuQoAjo/7he8N6wpxBxCphsHHCb0PpuC+QGAbukvgfoAQguhCWbAv6ti0/gHEiSnxuWfEtaBFgtglEAV4+eIljkAxNCBvv/22mswIjQjM+3hZo3eEWAD0hNHQILbCsFcGIYFt8eKEJQN+aTRmWAe3BXqvH330UbzLhZ4lygPLBMzdGhgBgSGrcC9gFAD845o1RQM9aQiDmHrnmj9fEw1oqHAO+NMR2a+B9dgGvUhEyaMBhN8blgqM7tBAnWEkACw8+D/cMmgAYRKHq0Fzj+CcEBWIN4hp5AYackwchpEBEC84DgQV4lngQkADgvuF3jwaGViQ0LgjoBA+emwH0PijzBBwqHs0zDDTo3FE3WBbiD5cN4QjtocLAGIA28DyACEFCwJ65IhFQQMP0Qb3B8qPfRDMqPX4EcQYGxCtCA6EywSuDMPgWDSaCJyEZQsCBvWGe40G2DBuxRRthAauDfsZWhmwHseFAMCCe4tnA5OpoSyxHTeu+2AK6hfPOUY7oX5hLUC9IAYHghv1jTgQWOZwbTgGxDusHIj7sTQ0Oj73jLgYOkJsRKdOndQSE1OnTtUVLlxYt2rVKqP1Bw4c0PXs2VNXpUoVXcmSJXX169fXTZ48WffPP/9YPE54eLhu9erVuqCgIF358uV1pUuX1jVr1ky3aNEi3fPnz+Ms57Bhw3S1atXSfz579qyuWLFiuhUrVugOHz6syrhmzRpdmzZtdCVKlNA1b95ct3PnTqNjYJvatWvrwsLC9Os2bNig1t+4cUN/HnzWFhyrUaNGajvDOjPcply5crr27durclgqK9i2bZsuMDBQHQ/X36tXL92FCxf03+P8ONa8efNirYeVK1fqGjdurCtVqpQ6Tv/+/XU3b940qucFCxbo6tSpoytevLiuevXqunHjxukePnyo3+bixYu6hg0bqu9R/yA4OFg3cuRIXcWKFfX1t379eqNznzp1Ste9e3d1XtzzVq1a6Xbv3q3//vz586pucG+xTYcOHdRzgnP169dPFxcTJ05UdXDp0iWj9bgm1EvdunVV2SpVqqQbNWqU7sGDB3Eec9euXeqYePZMwXOHZxZ1hLrAszFr1iyj5wP3EfczoffB9F7euXNHN2jQIPWsvPnmm6oeUV8aISEh6rdWrVo1VZYGDRroli5dqouMjIyxLPG5ZzGVnzgfqfCPrcUMIY4KXBUI0kMvDz07QghxNRgjQQghhJBEQyFBCCGEkERD1wYhhBBCEg0tEoQQQghJNBQShBBCCEk0FBKEEEIIcWwhgQlxMOUrhtLFBCbMQZIZ5GJAJj7TWfwIIYQQ4oIzW2K6VswsaDiFqymYThYz2iHLHRIYYSa/nj17qiyAMSWFuXfPONmMn19aefDgVR4FknywrlMG1nPKwbpmXbvCM505czrHExJIqgMREdecWEhGhOmHkXwI09eOGjVKzaOP+eExXWtcYMZbd3c39ZfTbyUvrOuUgfWccrCuWdcxMXXvJXkcGm60rkT29NKxXK5YK+3OkzCZ+/MVs/WBpbJL+TyxJz07+FewbP+feTbdYXUKSUYfz1j3XXb4b7l0LzpHzODGxSTAI5VV2kSbCgnM6Y7ZAJEPwDQFsiHIb4/kMdoc+PiL+feRbyA+QoIQQkgygtYoIvacJvECr/iXbiLhISJ2MOcyOrlhUWExfn/0r6ty//lLo3VuUX4SWsI71uM+ehoihy6ZC4nyOURCs8aeZO76vdty6NI1s/WPK2SUNG5pYt33zI2/5fiN6AR63Z7kkwC/2MvpEEJCy9IYF0jGZJo8Bol6YnOHAC33julfknywrlMG1nPKwbqOA51OMmwMFM87v1utzgPE9kDHdMmeVU56xdI4v2beiP4mIk3Mkw2b4WGeY03m/xu9JGbfd+JT/Wmj9w1/GC6fHZgm81v8LKlSuTl+jER8QPY+pFc2BJ8RpBmb/wfuDEP8/RPn/yEJh3WdMrCeUw7WdQy8fC5iRRFhL4SmShW7iHBgPDJ6yOPrYeqZTuXmIkIC8RGmogGfvby8YtwHQSSGPQlUWHDwU8ZIJDOs65SB9ZxysK7jIDxEb0EI7n5SdJ4+SatrP18JfvDM5u/qULhq9jdT/99YY714uZu3Nx1XHpd7z4zbpmoF/GRMgyKxHvv6gxB575tTZusH1cwvDV/PGuu+3526LYsPmbs2Vnd+U7Kki1n4REVFyfDNZ+XknegAy5Hv1JEHD58b1XNAgAMGW8aXrFmzyv37943W4XOWLFli3c/0QcRnWz+crgLrmvXsbPCZjqliXv03ysNHBEtiQecvdVrReUTZ9F296fRtOXXrnv7zd2dDxN/bTQVDGpLWJ0DCdMZCIq2Pn3h5+cd6/DRe3pIurbkDx8s7IM59fbxfSrq00QGThnh7+4tXDBYUiIihQwfJoRPnJUvgKHHzTC1pUntY7Zl2CCGBuSOWLFmiAl8QaIm/f/zxh/Tq1cvWRSOEEOJkICBx18W7ku6/WIRFh65LhjQ+ZkJiZac3E3X8vH4+sq1nxUTt26pUdrXEF01ErFy5TLWfs8ZESK1a1ZX14f5942kSHHpCqpgCLMPCoqNlGzZsKE+ePJFJkyapIaP4i7iJRo0a2bqYhBBCnIznLyPN1qVN7S6ORpSJiFiwYJHUrFnb6uexWyFRtWpVNX8E8PX1lUWLFsnx48fVcE8MB128eHGMk1ERQgghiSU03FxI+KR2CAN+rCIiKKidJAd2UzMXL16M9XOpUqVk06ZNKVwqQgghzsDXf/wjf903nsnRP21q+aBKXrNtQyxYJHwcyCIRlYIiwq6EBCGEEJJc/Hb1gfx27aHRurx+3haFRBoPN/HxdHdYIXHt2lXZuHF9iogIQCFBCCGEGLCkXWk1/LPJ7ujPG3uUEy9368wCmRLkz19A1q3bJNevX5PWrdsm+/koJAghhJBYCEibRrw90ti9O+PmzRuSO3ce9blcufJqSQnsNtiSEEIIIfGPiahbt5qcPn1SUhoKCUIIIU6PFvdguHh5OE7cQ3wCKx8/fiyXL8eegyo5oGuDEEKI0zOjRXFxNqIsjM5o1SooxctBiwQhhBDiYESl8BDP2KBFghBCiFPQZfUf8uxFhJo8CsM1MRtl2dcySqdyucSZiLIjEQEoJAghhNgVB/4KluN/PzZb369GPnHT0jpb4J/HYfIkLMJoXbo0ztfMvXz5Uq5cuWwXIgI4Xw0TQgiJG6R9RKrsJJIqPMTqtX3ixmNZc/ym2fq+1fNFZwi1AJI5vsqRoUPB1P9Se0ZEpwRPIGGRSa+b5MLLy0tWr14nhw8fktq164mtoZAghBBXQ6eTjBsDxfPO7+IshEfqJKh0Djn69wO5k3a2uPtcV+v3h4vs/29iKUd3Z+zevVMaNGikLBHINWUPIgIw2JIQQlyNiFCri4jw7G+JeNhu9kdP91QyqGZ+SSXhehFhDUpkKiVe7l5iDzERXbq0k2nTJom9QYsEIYS4MPffOSk6TytkUoaIiCV+IblBL92UsL/GyKoOFSRHhsQLHIgIS8e2VWBlgQIFxd6gkCCEEBdGiQhrCAk7ZGqTN6SAv584KlF2NjojJigkCCGE2BV9a+STPgisNCE+doEvO5SWZnui//9W7kziqEQ5iIgAFBKEEELsCgzx1CVhX2dg2LCPHEJEAAZbEkIIIXZGiRIlxd3d3e5FBKBFghBCSKK5/+yF/Hr1odx99sJofWCp7OKfNnWs++6/dF+u3H+u/1y3SGYJCEjHuyEiXbt2l2rVakj+/AXsvj4oJAghhCSKP+8+k97rT8tjk9kkQfUC/nELiT/vya4L99T/G7+eRbKmS6MmlnJFoqKiZN682dK58zvi7++v1jmCiAAUEoQQQhLFsiN/WxQRiWH7/+6qBSEOSPE9tE5Bafx6VpcREUOGDJRVq5bLli2bZffun8TDw3GaZ8ZIEEIISRT/u/PU6jUHgwSmuoaYcDURkSpVKvnggz4OJSKAY5WWEEKI3dCqVHaVJCtSp5OISJ2sO3nLKseFiCiXO6O4mohY4ACBlZagkCCEEJIoulXIrf4irmHhL9esUouFs/rKsNoFxNcJs3Y6o4gAzn2nCCGEJDsIj+z8Vi61aPikjrt5GVmvsIqF0PBwTyV5cmSS+/efKheHMzNt2idOISIAYyQIIYQkrSFJlUrSe3kaLR5ucU8M5ZPa3WiftPEQH85C+/adJXfuPA4vIoDr3DVCCCHETsibN58cPHhUvL1tlzHVWtAiQQghhKRATMSIEYNl587t+nXOICIALRKEOCJwIL98LhIeEu2gJskHLPQv3ZyqrlPhWuwQBG2GhIdIaERoomMkwiJDxZ4TcK1Zs1KOHTstWbNmE2eBQoIQR0OnkwwbA0Xu/C4Bti6LC8G6Tn4R0e9wLzn38Iw4E1EmWTxnzZrnVCIC0LVBiKMRESqed363dSmIExCe/S0RD/swr4dFhllVRJTIVEq83L3ElkQ5UCrwpECLBCEOTHD3kxLl4WPrYjg1mLI5wN9X7gc/c74hiRARiUy7HREZJb9ceSDubqnU4vHf35wZvCRb+qQ14BvrbpU0bkkTOBARaLxtRZSLiAhAIUGIA6Pz9BGhkEhe0BalTiviGeU0MRLWICQ8UoZs+Z/Z+vcr55H3KuVJ0rG93L3V4shs2LDOJUQEoJAghBCSYCKiLKuq+Mwf4Qq0bt1WfvvtkFSqVMWpRQSgkCCEEJJgIikkLLozoqKiVNItNzc3mT17vks8WQy2JIQQYjUhgTgJVyTqv5iIPn3el4gI66RWdxQoJAghhCQYujYsB1Zu2rRBjh074lJPFF0bhBBCEkxA2tSy6O1SKn040ojDQoH/F8yc1qVqM8rC6AzERbgSFBKEEEISjJenu7yZK6NL15wrDfGMDbo2CCGEkARCEfEKCglCCCEkgVy8eEG+/XaNS1siNOjaIIQQQhJIsWKvy8qV38j9+/dcWkQACglCCCEknu6Mu3f/lWzZsqvPtWrVYb3RtUEIIYTEP7Cybt3qcvnyJVaZAYyRIIQQQuIZWHnv3l05e/Y068sAujYIIcQFeRkRJefuPJXHoeFG6zN6e0rpXBli3fdFRJT8dvWB/nOJHOnVvBKuMjqjZcvWti6WXUEhQZwb5H2OCBVnIlV4iK2LQBycy/efS9/vzsj95y/Nviv3Wgb5vO0bse7/7EWEUebPtqWzi7t7uJoeu2nxrJIjQ8Izd4ZF2t/vlEM84weFBHFedDrJuDFQPO/8buuSEGJXTN932aKISBw62fpwrLj7XFefvneS2aEpIuIPYySI8xIR6twi4rWKIh4J7/kR1wY5Mq4Fh1gvuVaqcL2IsAZlspQRL3cvsTUhISFy+vQJzhMRD2iRIC7B/XdOis7TR5yFVKlEArJlEQl+hg4hIfHGwy2V7O5dSXQ6nYRH6iTkZaSsOHZDVv9+M+m1eH2cfN+jmjpHYp/rXFkzS3DwM+WVtCW+vr6ybt1mOXLksDRo0Mi2hbFzKCSIS6BEhBMJCUn131uXkMQ+QqlSSWqPVPLNH/9YR0SIyCeN3pB0qRP/O8MjjXLZ0p1x8ODPUqNGLfU5Y8ZMFBHxgEKCEEJceORGiRzpVBZPDd/UcTcL6b089Pu8iAqTUWej15eJY7SHPQMRMWTIQFm1arlMnDhFevb80NZFchgoJAghxEVJ7eGWqAyenu6v9gvFqKj/hIQziAhYRPz8/G1dJIeCwZaEEEJcFlMR4eoJuBIDLRKEELvi7tMX8vfDUCkYkFYy+njGuu3NR6Fy58kLs/VvvpZB3OLwtWMyptCXkUbr0qXxkCJZfWPdLzwySk7988Rsfc6MXpI9feyjDTDkEiMmTCmWzVfSxuFSuBL8XB48N548CkGNcU0eBU7efKxGaxjil9ZT8vunFVeGIsI6UEgQQuwCNNDjdlyUPRfvqc8zWxSXGgVjNzFvPnNHVhy9Ybb+UP+qKpAwNqbsuSQX7z4zWvdmrgyy6O24J2P6YL35FMm9q+aVdyrkjnXfo9cfqms0ZVWnMlI0a7pY911+5IbsPH/XbBbKPb0rSVxg8qhHJjNYNiqWRSY0LiquCkat0BJhHejaIITYBRAFmoggJLmBGyN37tzi5uZGd0YSoUWCEGIXHPv7kcXev28avqZI8tC//0fSoEFjKVq0GKs4CdAiQQixC56EGZvebzwKlTHbL9isPMQ5YyI+/3yBPHv2VL+OIiLpUEgQQuwCzLBoyNyfr8iTsAiblYc4F1rujHHjRkqHDkHqM7EOtBkSQuyC5yZCAvikdo91nyavZ5VSOdKbrY9PHolBtfLLsxfG58zgFfcrMW1qD5nVsrjZ+rx+cc/oWPa1jBb3zRmPbJkdy+aUekUyG63zdI/fLJATGhdR02EbksXXOdN+xycBV+fO3VRsBLEOFBKEELugSBZfNfwSlonnLyMkJDxSfY6NfP4+akkMiZmISZvEqXqBxE1YlDVdGrUkBozqKJo1UbtKpbx+4qowi2fyQyFBCLELJjdlwBuxLhQRKQOFBCEuzp0nYWqOAW9Pd8kTh3kekxpdvmc89wII8E0jAWljN5U/Dg2X20/CLLoEvDxjd2EQkhgmTRqvd2dwxsrkg0KCEBcl+PlLGfz9OTl7+6k+4dLiuCZjCouQzqtPJGoypl+vPZCx280nY1rZqYwUi2MyJkISQ5s2b8u3366VceMmctrrZIRCgtgnOp0IkgElgVTh5lMRk1fM3H9ZLyIIcUaKFXtdDh8+Ib6+sU97TpIGhQSxP3Q6ybgxUDzv/G7rkjg1v117aLYuLDySbgbi0DERGN7ZqFFTqVy5qlpHEZH8cPwLsT8iQq0qIsKzvyXiEffwOlciIjLKbLjliZuP5SsLeSsIcaTAykWLFkqnTm9LcHCwrYvkMtAiQeya+++cFJ1n4ob36YGIiCMTpKuBoZWWiMf0C4TY/eiMadNmib9/4obokoRDIUHsGiUikiokSJyzSGr4xJHK2ju1u4xvVMRsfeEscfugMXGUpX3jSr1NSGxwiKftoZAgxAXJ7JtGdn1Q8b/JnyIlFH/DIyVPpthdQGk83KTx64mbFQmzN8ZnBkdC4gtFhH1AIUGIC4IppP18Uks8ZnUmxG5ZvXoF54mwAygkCHFibj0OkygMpTUAE0/5xzF5FCGOQLt2HeXnn3+Uhg0bc54IG0IhQYgT887aE/IgxDg9d4OimeWTJpyOmjiuOwMBlVhSp04tS5euUP8ntoPDPwkhhDiMiBgyZKAMGzZIdP9Z2igibA8tEoQQQhxGRKxatVyJh7Zt20u5cuVtXSxCIUGI4yXYmrTnkqRN7S5+6bzEXRelYh5qFwpQaaYJcQURgQRcFBH2Ay0ShDgQD0PD5bCFqa3zZPKhkCAuIyKCgtrZuljEAAoJQpxiIinLabg/rJpPwiKM93ktjrkiCLEXKCIcAwoJQpxYSDQvmS2ZS0RI8nHq1AlZu3YlLRF2jk1Hbbx48UJGjhwp5cqVk6pVq8qyZcti3HbPnj3SqFEjKVOmjLRv317OnTuXomUlxJ6FBGImCHE2ypQpK1988SXdGXaOTS0S06dPl7Nnz8qKFSvk1q1bMmzYMMmRI4c0bNjQaLtLly7JRx99JBMmTJA333xTvvrqK+nZs6cSF97eNNMS5+DZiwiJiDSePMrNTSS9l6f+s6eHm+TO5C2h4ZESGh4lz19EiC4WiwQhjujOQOZOP7/opFstWrSydZGIvQqJkJAQWb9+vSxZskSKFy+uFgiGNWvWmAmJQ4cOScGCBaVly5bq86BBg9R2ly9flpIlS9roCgixLkO3/E+O/f3IaF3BgLTyddey+s8YnYEF8+8EBKSTu/eeSOjLKJUDgxBnEBG9e/eWXbt2yaZN2yVnzly2LhKxZyFx4cIFiYiIUK4KjbJlYcb6Qj1MbuiK/UfGjBmVaDh+/LjafuPGjeLr6yu5c+e2UentCEzKEhEqdgMmmHvpJhIeIqqrnJhDYF8SL9xSpXI6awQmGgqLDBN7AaItJNxdQiNC1c+NGBMWaZ33D977mGhqxYroVOB//HGcQsJBsJmQuHfvnmTKlElNcaoREBCg4iYePXokfn5++vWNGzeW/fv3S4cOHcTd3V2JjEWLFkmGDBliPYc2a6rpX6dBp5MMGwPF887vYm8EWOk46p45232LgZgu09Jz66zPNEREv8O95NzDM7YuCkkEeB4T80yaiojPPlskzZu34D1IJqz9/rCZkAgNDTUSEUD7/PLlS6P1Dx8+VMJj7Nix8sYbb8jXX38tI0aMkE2bNom/f7QfzRQ/v7Ti7m5s7vX3d7IJe14+F7FDEWE1XqsoAdmyOF9rGQOeFiwLHh5uyoURE872TIeEh1BEOChlspSRXFkzJ3jKas2doYmIlStXSqdOnZKtnMT67w+bCYk0adKYCQbts5eXl9H6mTNnSuHChaVjx47q88SJE9UIjg0bNsj7779v8fgPHjw3Ul2osODgp85lmgwP0ff8g7ufFJ2n7XNCq7r285XgB8+SXtce3iLBz8RVCLcwIiMiIkru339qtt5Zn2m4DzQ21t0qXu62D6ZGXfv5+coDazzTToyXu5cEJ/D3ChExdKixJQIiwtmea3sjpvdHbJ0WuxQSWbNmVZYGxEl4eEQXA1YHiIj06dMbbYuhnp07d9Z/hmujaNGiaqRHbJg+iPjsVA+nwbVEefiIYLE1EG+p04rOI8o6de1M9ysOmpbIKmVfy2i0LpOPZ6z16GzPtOG1pHHzthsh4ePpIyHukU5V18lBQuvn8ePH8uuvv5jNE+Fsz7W9Yq16tpmQKFasmBIQJ0+eVPNIAARTYhSGYaAlyJIli/z1119G665evcoRG8Rh+PnyfZm855J4uruJp3sq8XSL/vtxoyJSKLOv2qZRsay2LiYhKUrGjJlk48at8vvvx6RJk2asfQfFZmPGMP8DhnN+/PHHcvr0adm7d6+akKpLly5660RYWHTkdtu2bWXdunWyefNmuX79unJ1wBoRGBhoq+ITkiCev4yUByHh8u/TF3LzUZhcfRAif957LhFR7HYR1wLujGPHjug/Z82ajSLCwbHp4HMETGL+iK5du8r48eOlb9++Ur9+ffUdZrrcvn27ftTGmDFj1EgNiI8//vhDTWIVU6AlIfaG6URTGrBMEOIqaDERTZvWl2+/XWvr4hBnmNkSVolp06apxZSLFy8afQ4KClILIY5IeFSUxfVwbxDiSiJi5crowEpTFzZxXHgnCUkBXsZkkTAZokyIK4gIpgJ3Lpj9k5AUIHdGb6lfJLOER+kkPDLqv0UnPp7ONSslIaZQRDg/FBKEpABV8vuphRBXgiLCNaBdlRBCSLIANwbyItGd4dzQIkEIISRZgIAYN26iBAa2ljfeeJWgkTgXtEgQQgixqjtj2bIl+nmAICYoIpwbCglCCCFWjYkYPvwjeffdLiqbK3F+KCQIIYRYPbCyRYtWCc4EShwTxkgQl6Dewt8kNNw4u2bzEtlkaJ2Cse53+tYT6b3+tNn6TxoXlZqFtNyrlln623X56ugNs/W7P6gkPhZShhPiqHB0hmtDIWErYPIzSJmcGFKFh1itOM7Oi4hIeRFhPLsk5nKIC5hmTfcDUfEw2SKPhqV97Q1cY1hktD/b1oRFJu03QVIeighCIWELdDrJuDFQPO/8zieQ2FxE9DvcS849PMM7QRLFxx+P5oyVLg5jJGxBRKhVRUR49rdEPLytdjziOsASYY8iokSmUuLl7mXrYpB40Lx5S8mQISOnvXZhaJGwMfffOSk6T5+kHQQigkFNJIlsqLNVvNztQ5BCRDBQzzEoV668HDt2SjJmzGTrohAbQSFhY5SISKqQIHGCwMqXJjERpXNmiHM/P5/UElgqm9n6HBni7i0Xy5rO4r7ubvYZyQ4R4U3LFolHTMT48WOkdesgKVWqtFpHEeHaUEgQl2Bw7dhHZ8TEa5m8ZWS9wonat0ZBf7UQ4kwiYsiQgbJq1XL59ts1cvToKUmfPm5BTpwbxkgQQghJkIiA22nixKkUEURBIUEIISRBImLBgkUSFNSOtUYUFBKEEEJihCKCxAWFBCGEkBhZuvQLWiJIrDDYkjglH++8KP+7/VQ83VOJp7ubpHZPpQInxzQoYuuiEeJQdOrUTXbv3iVvv92e7gxiEQoJ4pTcehwmVx8YTyH+/KVxrg1CiGW0rJ2Ih/Dx8ZH16zdzXg8SI3RtEKckwkIejdQefNwJiW9MxLRpnxgJCkJighYJ4pS8jDRPquVppxNBEWKvCbiaNGkhJUuWsnWxiJ3DLhpxSixl9kSsBCEk/lk8KSJIfKBFgjglb+RML1l800h4VJS8jNBJRFSU5M5kH3kkCLE3mAqcJAUKCeKUJHZaa0JcDYoIklQoJIhDMnHXRTl964nRulwZvWVOYAmblYkQR+TIkd+M3BmcsZIkFAoJ4pD8+/SFXHsQarTOzQEiyxEFHxYZluTj4FJDwt0lNCJU/gusTxRhkcZ1SFyPSpWqyIwZn6phnhQRJDFQSBCSgiKi3+Fecu7hGdY5sbk749mzp/qkW127ducdIYmGYeyEpBCwRNiriCiRqZR4uXvZuhgkBWMimjVrKMHBwaxzkmRokSB2xe0nYQIHhU9qd/FJ7SEeTjr3w4Y6W8XL3TtJrg1/f18JDn6WJNeGBkQEJx1yvcDKo0cPS6NGTWxdLOLgUEgQu2LU1vNy5vZT/WfkyCiTK4MsaGM8Kc7r2dKZxURkT+84PWqICG+PpAkJH08fCfGItIqQIK45OoMiglgDCgliV5jmw8AMlRYmqZTeVfOlXKEIcXA4xJMkJ4yRIHZFiIXEWmk93W1SFkKcAYoIktxQSBC7IiTcXEggXoIQkjgQULl//x7OE0GSDbo2SLLz9R//yO4Ld83WL+9Qxmx4pKVU3xQShCSezJkzy6ZN2+TUqRPSvHkgq5JYHQoJkuzceRImZw0CKGMCoRBD6xRU7o2QlxFKVOD/pXNGj3UnhMTfnXHu3Fl90q08efKqhZDkgEKC2A0YhdGqVHZbF4MQp4iJ+PrrVfLll6ukYcPGti4ScXIoJAghxEkDK58+Nc5HQ0hywGBLQghxAjg6g9gKWiRIsoOJokpmT8+aJiSZoIggtoRCgiQ77d7MqRZCiPWhiCC2hkKCWIWfLt2XKJ1OUnu4if+DMAl9Hib+Pqklj58Pa5iQZCY8/CXniSA2g0KCWIVJey7Jo9Bwo3UNi2WRiY2LsoYJSUbc3NxkzpwF0qFDF6lQoSLrmqQ4DLYkViE8MspsnaeTZu4kxB7cGWvXrpKIiAi9mKCIILaCQoIkm5CAm4MQYn0RMWTIQBkw4EPp27eXmhGWEFvCNz1JMniRIUunKR60SBCSLCJi1arlKiaidu266i8htoRCgiSZyCjLPaLU7ny8CEkuEbFgwSIJCmrHCiY2h8GWJMm4uaWSrzqUVlaJiKgo8U7rJcEPn0vODN6sXUKsAEUEsWcoJIhVcmQU/2/CKVhZAwLSyf37T4WuW0Ksw+jRw2iJIHYLbc+EEGLn1KvXUHx8fOjOIHYJLRKEEGLn1KpVR44dOyOZM2e2dVEIMYMWCUIIscOYiEmTxsvly5f06ygiiL1CiwSREzcfy74/70nw85dSu3BmqVck9l7PmVtPZO3xm2bre1bJK/n8OSU2IdbKnbFu3dfy66/HJW3atKxUYrdQSLg4yJEx/If/iTYNRF7kxohDSNx99kL2/nnfbD0TcxFi3QRco0d/TBFB7B66NlwcWBYszCVFCElhmMWTOCoUEi7OleAQo8+YC2L3hbs2Kw8hrghFBHFkKCRcHNNJKVceuyG/Xntoq+IQ4pJ89tk8vTuDM1YSR4MxEi5OlIVZo9zjmLo/jYebZPFNbbbek1NiE5IoOnfuKtu3b5Hu3d/ntNfE4aCQcHEsCQnMVBkbVfP7y7ae/slYKkJcI9mdlnArY8ZMsnXrHnF3d7d1sQhJMBQSLs7Pfaso9wYEBZJv4f9M2klIysREFCpUSHr2/FCto4ggjgqFhIuDHhFcGe6SSjzZGSIkRQMr3dzcpHbtelKoUGHWPHFYGGxJCCE2Gp0xf/4XFBHE4aFFgji9HzosMkzsgbDIUFsXgdgQDvEkzgqFBHFqEdHvcC859/CMrYtCXByKCOLM0LVBnBZYIuxRRJTIVEq83L1sXQySgvz00z7OE0GcFlokiEuwoc5W8XL3FnsAIkIb9kdcAwRUjh49XrJnz855IojTQSFBXAKICG8P+xASxHXcGWFhYeLjE50Rt1+/gbYuEiHJAl0bhBCSTDERQUEt5Nmzp6xf4tTQIuHCPAoNl/e/OSVubtGzWXq4pVJ/g0rnkCbFs9q6eIQ4RWDl4cO/St26DWxdLEKSDQoJFyYiMkquPjDO/glqP39pk/IQ4oyjMygiiLND14YLE2meZkPhxjmyCUkwHOJJXBUKCRcGuTUsQR1BSMKgiCCuDIWEC2Mp8ydw59BEQhLE7du3VBpwzZ0RFNSONUhchkTFSDx9+lS2bNkiV69eld69e8upU6ekQIECkjt3buuXkCQbqd3dpGKeTBKp0+mzf0ZGiWT2Tc1aJyQB5MyZSzZs2CoXLvxPAgPbsO6IS5FgIfHnn39K165d1cQq2v93794tO3fulEWLFkn58uWTp6TE6mRJl0bmtynJmiUkke6My5cvSeHCRdTnYsVeVwshrkaCXRuffPKJtG/fXjZu3Cienp5q3ZQpU6RDhw4yffr05CgjIYTYnYgYMmSg1K9fQw4dOmjr4hDiWELizJkz0rJlS7P17dq1k8uXL1urXIQQYtciYtWq5RIaGiq3bv1j6yIR4lhCws/PT8VGmPLHH3+Iv7+/tcpFCCF2LSIYWElIIoXEe++9J6NHj5Y1a9aoNM2HDx+WefPmyfjx4+Wdd95J0LFevHghI0eOlHLlyknVqlVl2bJlMW578eJF5VIpVaqUNGvWTJ2XEEJSCooIQqwUbAkXRpYsWeTLL78ULy8vFReRL18+FTvRuHHjBB0L+549e1ZWrFght27dkmHDhkmOHDmkYcOGZqNEunfvLrVr15apU6fK999/L3369JFdu3bRCkIISXYoIgixopA4duyYVK9eXTXqhrx8+VL27t0rdevWjddxQkJCZP369bJkyRIpXry4Wi5duqQsHaZCYtOmTSqD3scffyzu7u7Sr18/+fnnn5UIqVGjRkIvgSQjsFKFhIdIaESoxDBNRYoRFhlq2wIQpyEyMlKCg+/TnUGINYREly5d5NChQypWwhCIgEGDBsnp06fjdZwLFy5IRESElClTRr+ubNmy8sUXXyj174ZMUv9x9OhRqVOnjhIRGhs2bIjzHNq8SqZ/bY5BOVSZ7KVcVhAR/X7rJWcfnhF7A/VsN/ffCtjdM+3EoI4xQm3JkuVy+PBvUq0aOy/JWdeGf4lj1HO8hMTatWtlwoQJSo2jsahSpYrF7SpXrhzvE9+7d08yZcokqVO/mvwoICBAxU08evTISKjcuHFDxUaMGTNG9u/fLzlz5lRuEAiPmPDzSyvu7sYhIP7+6cQuePmqXAH+viKp09qkGGHhkfLg+Utx/y/rJ/5iSZvaXTxM6i4+wBJhjyKiTJYykitrZvX8Oht280w7IejQrFu3Ttq2bas+Z8/uL4GBTW1dLJeAz7Vj1XO8hATmiChUqJD6YWECKgRXZsiQQf89XtDe3t5SuHDheJ8Yw6YMRQTQPsNNYuoGWbx4sbKGwBWybds26dGjh+zYsUNNjGWJBw+eG6kuVFhw8FObm9sV4SES8N9/7wc/E/GMskkxDl97IH2+O2u2fm6rElIlv7HFKT7AnaGxqd5WSePmLfaAl7uXBKOenQi7e6adNHfGihXLZO/e/bJ06WLWdQrA59q29RwQkC55XRtvvfWW+rtv3z4VEJnU3l2aNGnMBIP2GUGchsClUaxYMRUbAV5//XXlXkHQZa9evWI8h+kLFp/t4qVrUAZVHhuVKSIG/YKkXYmpJ8N9ICK83O1DSAC7uO/JgN08006cgKts2eh3H+s65WBdO1Y9JzhGAi4HjLLA5FMIQDIUAf/73/+UlSA+ZM2aVR4+fKjiJDw8PPTuDoiI9OnTG22bOXNmyZ8/v9G6vHnzyu3btxNafGJAVIzZP53PBUBIfGAWT0ISToId4ZhDAm4GuCaQuCs8PFyJCrgbmjRpEu/jwMIAAXHy5En9uuPHj0vJkiWNAi1B6dKl1TwShly5ckXFShDrpxFHnAQhrgZFBCEpJCQOHDggM2fOlFmzZqmMn926dVPDOPEXIzfiC2IqMNU2hnRipAeGjmJCKsRBaNaJsLAw/dwVEBLz58+X69evy9y5c1UAZosWLRJafGIA04gT8oqRI4fo3RlMBU5IMro2MKoCbgWAAEzM5VCiRAl5++23pVOnTgk61ogRI5SQQACnr6+v9O3bV+rXr6++w0yXSAbWqlUrZXlYunSpTJo0SVlDIGDwF+4RYpmLd5/JiZuPzdY3LZ5VfNNE3/aCmX1lQI38+hTiMFDgb7b0aVitxOWoVKmKrF69QubMWSBBQe1sXRxCnFdIoBH/9ddfpU2bNkpIwB0BiwFmn4TISAiwSkybNk0tppi6MjDUExlHSfz44+Zjmf3jX2braxT01wuJ3Jm8pWO5XKxSQkSkRYtWUq5cecmZk78JQpJVSGBq6v79+yt/IlwLiIvAyAk0/LAiEEKII4B32MyZU6Vjxy568UARQUgKCAnMMImRGfgRYg4HTFaFYZhvvvmmPr6BEEIcJbBy48b18vPPh9WQdEJICggJ8Nprr+n/X7RoUbVgxktMWw2XByGEOMrojI8+GkYRQUhyj9rAXA8LFy5UgY9BQUEq8yeEgwZGXWAaWUxhTQgh9gqHeBJiI4sEUndjznnERGAa60WLFqmhmYiNwHerV69WQZgYvkmSn7tPX8i+S/clrae7+KT+b/F0l/wBPpLey1Nt06x4VqlRwN9s38y+NN8S14QighAbColdu3appF2Y9wFgiObQoUPVpFBIooX/Iz7CMDsnST6uPQixOCJjVsviUv0/8YCRGdroDEKIyJw5MzhPBCHJQLxaGkxlXb58ef3nChUqSHBwsEoFjtktDWMmSPIT8vLV1OSGIGsnIcQynTp1ky1bNkmfPgM4TwQhKS0kECNhGtHs6ekpY8eOpYiwAvefvZDD1x+arX8rdybJms7cFRESbllIeHtSSBASE5jAbu/eg+rdRQixHkmyfSMLqEuBAFODVNmJJVV4iNHnK8EhMn7nn2bbzQksblFIPI/BIoFYCULIq5iI4cM/Utk73367g1pHEUGIDYXEnTt3zGau/Pfff83iIpxWXOh0knFjoHje+d3WJZFQujYIiXdgJaa9xvTXuXPnYa0RYkshYTo/BIZ/IrcGxmFrn/H/8+fPi1MSEWp1ERGe/S0RD29kMEnQfm1K55DahQMkNDxSxUvAQoG/Gf4bsUGIK2M6OmPu3IUUEYTYWkjs27cvOcvgcNx/56ToPH2SfiCIiP+EWEKIHvIJAUIIMYRDPAmxUyGB7JvkFUpEWENIEEKsBkUEIbaBEw3YAcWzp5M1nd80W58jg5dNykOII7J9+1bOE0GIDaCQsAPSpvaQwll8bV0MQhyaJk2aqTkiihV7nfNEEJKCUEgQQhzanREeHq7muUFg5dixE2xdJEJcjkQLiWfPnsnff/8tBQsWlJcvX4qvL3vUcXHzUais/v2mILwSLz23/+Ism5XIJkVokSAkwSJiyJCB8s8/N+Srr9aKlxddgYQ4hJDAXBITJ06UjRs36vNwTJs2TUJDQ2X27NmSIUOG5CinUxD8/KVsOHXbbH2ZXBkoJAhJhIhYtWq5EuWHD/8qNWvWZh0SYq9pxA2ZMWOGXL58WTZt2qSfNrtv374qH8cnn3ySHGV0GgwyrxuR8AGghLgupiJiwYJFFBGEOJKQ2L17t4waNUqKFCmiX4f/w0px4MABa5fPqYhBR+gn9SKEJFxEBAW1Y7UR4khC4vnz5+Lt7W3xBx4ZaTkHBPmvjmIwSVBGEBI3FBGEOImQqF27tsyZM0cFW2rcuHFDuTVq1Khh7fI5FTA8eLqnEg+3VOLuFh1sGR14aeuSEWL/XLt2VTZt+o6WCEIcPdgSqcNHjhwp5cuXVz2E1q1by9OnT6Vq1aoyZsyY5Cmlk/Bmrozy64Bqti4GIQ5J/vwFZN26TXL9+jVp3bqtrYtDCEmskEiXLp3Mnz9fDf28cuWKRERESL58+aRAgQIJPRQhhMQKOis3bvwtefLkVZ/LlSuvFkKIA7s2unfvLhs2bJCMGTNKzZo1pW7duhQRhJBky51Rt251OXXqBGuYEGcREiVKlJAlS5ZIlSpVpFevXrJlyxYVgEkIIcmRgOvJk8fy11+XWbmEOIuQGDRokOzcuVO+++47KV68uBIVlStXln79+qn1hBBi7SyerVoFsVIJcbYpsjF3BJZu3brJ119/LV988YXs2bNHGjZsKHYHhl2+fC4SHhLzZA5xkAr7OjE6nU7CIsOSdIywyFCrlYe4JkwFToiLCIkHDx7Ivn371ORUhw8fVvk24OZo0qSJ2B06nWTYGChy53cJsHVZ7FhE9DvcS849PGProhAXhiKCEBcREp07d5Y//vhD8uTJI40bN5YRI0ZI/vz5xW6JCBXPO79b7XDh2d8S8TCfkMuRgSXCmiKiTJYy4uXOBEokYSD535UrlzlPBCHOLiRKly6tpsguWrSoOBrB3U9KlIdP0g4CEeHEM0htqLNVvNwTL5RQNbmyZpbg4Gcx5hYhxBLI3rl69To5fPiQ1K5dj5VEiDMJiVu3bkn27NlVT6F9+/b6dZbIkSOH2Cs6Tx+RpAqJJHDk+kOZvOeSwYyWqdTf8Y2KSPHs6cUegIjw9kiakGDuEJIQd8bu3TulQYNG6rnx8fGhiCDEGYUEpsU+dOiQ+Pv7q//jBw+/umGDoX0+f/58cpbXoQl9GSm3HpsHNIZFRNmkPITYS0zEoEFDZfjw0bwhhDirkEBgZaZMmfT/J4kjJku/mxO7SgiJT2BlgQIFWVGEOPM8Ejlz5hQ3t+hNEVyJabKxznBBRtC+ffsmd3kdGlhtLEEZQVwJjs4gxAUtEgcOHJDTp0+r/x87dkzNGQFfpiHXr1+Xf/75J3lK6eQWCRokiKtAEUGIiwoJJOVaunSp6lFjwfBPT09P/fdakNSkSZOSs6wOT0Da1FK9gH90Pf43T1aUTifpvBI9LxghDsWwYR8ZzVgZFNTO1kUihCSReLVgr732mqxcuVLv2sDwT19f36Se2+V4I2cGmZUzg62LQYjNKFXqDXF3d5d58z6niCDEVYd/Ig7iyZMnanG04Z+EENvSuXM3qVq1uuTLZ8eT2BFCUm74pykc/kkIMY2JmDdvtnTu/I56fwCKCEJcdPinn5+f/v+EEJKQwMotWzbL7t0/iYcH44EIcdnhn9rkU/g/hn8GBASo/z99+lR27Nghf//9t/pMCCGmozM++KAPRQQhriwkDNm7d69Ur15djh8/roZ8duzYUTZt2iS9e/eW1atXJ08pCSEOA4d4EuJaJFhIfPrpp9KvXz+pXLmyrF+/XgVhbtu2TWbPni3Lli1LnlISQhwCighCXI8ECwm4MBo1aqSPl6hXLzpLX6FCheTBgwfWLyEhxGGYPn0S54kgxMVIcOQThnceOXJEsmbNKlevXlWjOMAPP/wgefPmTY4yOg3PXkTIg5Bwlf1Ty7GB0BNMVOXpnmBNR4jd0b59Z/nuu/UybNhIzhNBiIuQYCEBt8bQoUMlMjJSatasKSVLlpRp06bJN998IwsWLEieUjoJey/ek0l7Lpmt/6ZrWSkQkNYmZSLEmuTJk1d++eWoeHl5sWIJcRESLCQaN24sFStWlH///VeKFSum1gUFBUmPHj3USA4SM8z+SZwxJmLkyCFSo0ZtadSoiVpHEUGIa5GoQd3Iq3HmzBnZvHmzskwgFwcEBokdZv8kziYihgwZKKtWLZe1a1fJ0aOnJFu27LYuFiEkhUmwY/7PP/+U+vXry+eff66mzsayePFiJSQuX76cPKV0cosE84gTRxYRmCdi1qx5FBGEuCgJtkggw2eVKlVk4sSJ+glmwsPDZcyYMTJ58mQOAY0FC7OK64MuCXFUEcEsnoS4NgkWEidPnpRx48YZzVKHlOLvvfeetGnTxtrlcypK58ogQ+sU/C8de7SFAmnEM3m/SslOiD1DEUEISbKQyJw5s5pLIn9+4+x9WJc2LUcexEbBgLRqIcRR+e67b2mJIIQkTUi0a9dORo8eLf3795dSpUqpdadOnZJ58+ap0RuEEOelTZu35fDhX6VSpSqcJ4IQkjghgWGeoaGhMnPmTHn8+LFah2Gf3bp1k+7duyf0cIQQB3BnYIE7083NTWbPnm/rIhFC7IgECwkEV/Xt21ctwcHBkiZNGvH19U2e0hFC7CJ3xpMnj2ThwqXM4EkISbyQ+P7772XPnj0qsLJu3brSpEkT8ff3j+/uhBAHT8DVrdu7UrlyVVsXixDiiPNIrFixQkaOHClhYWHKrTFs2DCV7ZMQ4jpZPCkiCCGJtkggjwbmj2jZsqX6vHv3bhkxYoQMHDhQvWQIIc4DU4ETQqxukbhx44ZUqlRJ/xkZP2GZuHv3boJORgixbygiCCHJYpGIiIgwCrLC/xFk+fLlywSf0JU5/+9TOXPrqUodDjuOSieeKpU0LpZFvDzdbV08QuTixQvy7bdrOGMlISR5k3aRxHH42kNZ+Ms1s/W1CvpTSBC7oFix12Xlym/k/v17nCeCEGJdIbFjxw6jYZ4wgWIUh5+fn9F2WhwFiX+ujVTM2kVsCH7Ld+/+q0+6VatWHd4PQoh1hUSOHDnMknFh6Ofq1auN1iHwkkIiZnQx5f9kvCqxcUzEzp3bZPPm7VKwYCHeC0KI9YXE/v37E3ZUksDsn6wwYvvAyrNnT1NIEEKSZ9QGsQ50bRB7Hp3RsmVrWxeLEOKAMNgyBXn7zRzS6PUsEoUU4gapxH1Sc8QGSTk4xJMQYk0oJFKQ9F6eaiHEVlBEEEKsDV0bhLgQISEhcubMSc4TQQixrUUiMjJSDh48KNeuXZNWrVrJ1atXJX/+/JIuXTrrlYwQYnUwhHvdus1y5MhvUr9+I9YwISTlLRK3b9+WZs2aqSReM2bMkMePH8vSpUulUaNGcvHixaSXiBBidXfGgQM/6T9nyJCRIoIQYjshMWHCBClbtqyySKROnVqtQybQypUryyeffGK9khFCrBYT0aZNc1m06DPWKCHE9kLi999/l+7du4u7+6uRBp6entK7d285e/astctHCLFSYKWfnz/rkhBieyHh5eUlwcHBZusRJ2E4hTYhxHZwdAYhxG6FRLt27WTs2LHy008/6QXEhg0bZMyYMdKmTZvkKCMhJAFQRBBC7HrUxocffijp06eXjz/+WEJDQ+X9999XeTe6desmPXr0SJ5SOgnfn7ktP18OVmZmbVps/H9qs2LihtzihCQRTHRmOmNlUFA71ishxL6Gf3bu3FktGJOOoaAc9hk//rofIgevPDBbTwlBrAXEQ+7cucXNzU3mz/+CIoIQYn9CYvPmzbF+z+yfMaOL5eVPiLXo12+QGt5ZtGgxViohxP6ExLx584w+wyKB4EsPDw8pVapUgoTEixcvZPz48bJ7924VxInRIFhi4+bNm2oeiy+++EIqVKggjmZ2NoUSglgjJmLRooXSuXNX8fWNnhSOIoIQYrdCwlJK8efPn6sAzCJFiiToWNOnT1dDRlesWCG3bt2SYcOGSY4cOaRhw4Yx7oPYDLhUnCX7J40RxFqBlTt2bJXNm7crtwYhhDhU0q60adNK3759pX379ir4Mj5ADKxfv16WLFkixYsXV8ulS5dkzZo1MQqJLVu2KNHiqGT09pRcGb1U9k+oCvzVgi4JSerojM6du1FEEEIcN/vnhQsX1IstIdtHRERImTJl9OswYyZcFjiOaa/q4cOHakruZcuWSdOmTcURea9yHrUQklTwG8EkcCtWcHQGIcTBhARGa5gGB8JKgDwbGAIaX+7duyeZMmXST7MNAgICVNzEo0ePxM/Pz2j7qVOnSmBgoBQqVCje51DFTBXzZ2JQLwb/T4q7RduXLpvkt0RoIuKzzzjEMznhM51ysK4ds54TLCQsBThCDAwePFgqVaoU7+NgDgpDEaEdB7x8+dJo/a+//irHjx+XrVu3xvv4fn5pxd3dTeTlK8uGv5+vSOq08T6GqxAS/mq6c39/X/Hx9EnyMf39mQk2uRg+fLheRKxcuVI6deqUbOcir+AznXKwrh2rnhMsJGAt6NKlixqrnhTSpEljJhi0zxjBoREWFqYCOceNG2e0Pi4ePHgerbbCQyTgv3XBD56JziP+7hdXITQiVP//4OBnEuIRmehjoc7xcAYHP7UYXEqSTpMmgbJ8+Vcya9ZMadSohdy//5TVmozwmU45WNe2reeAgHQpIyQQ8JgQF0ZMZM2aVcU9IE4CQ0c1dwfEAmbO1Dh9+rTcuHFD+vXrZ7T/e++9p4aaIhtpTKgK0hl/ZuMWQz1ZuY5Y18lH0aKvy5EjJyRv3uxKRPCZThn4TKccrGvHqucECwmICMz9gL8YqgnLgiFYFx+KFSumBMTJkyelXLlyah3cFyVLljQKtMTcFJhnwpD69eurlOVVqlRJaPEJcciYiLFjR0ijRk2lSpVqah0T5BFCHH5CqoMHD6q/WuAlJlvC/8+fPx+v43h7eyuLAuaFmDx5sty9e1eNyJgyZYreOoGpt2GhyJMnj0WLBnJ8EOIqQzzXrFklv/9+hs89IcTxhMSxY8fUME1YEPbt22e1k48YMUIJia5dMSOfr5qLAtYGULVqVSUqWrVqZbXzEeLI80RMnz6bIoIQ4phCAsGVv/zyi3qJ5cyZ02onh1Vi2rRpajEFw0ljIrbvkouHIS9l0a/X5fStJxIeaRywObhWQamQN1Os+3/9xz+y8dQt9f83c2WUoXUKijtnoyIxwFTghBCnEhKWckS4EpFROvlg/WmVvdMSIeFxj3J4FPJSrj2IHh2Bv9v+969+tsut7ztWzhCSvFBEEEKcMkbClTNUXvj3aYwiIrG8iIi2aoTFQ4QQ12L16hV6d8aCBZxsihDiJEKidevW8ZrH35oxFPYCXBCBpbJJRKROInU6ZaHYe/GeRFrBUJPXL+mTPxHnol27jvLzzz9Kw4aNJSiona2LQwgh1hES77zzjhpF4YoUzZpORtZ7de0QEViSCmw8bcvEb7gscW60PDUQ65jhdenSFS5tBSSEOJmQwAutSZMmjBgXkesPQlR8Q/k8r4Ir/Xw846zD1zJ5SyWDgMyAtKmlXtHMUimvcU4R4poiYsiQgWpK96lTZykxQRFBCHEUGGyZQPL4+cicwBIJruimxbOphRBLImLVquVKPLRt217KlSvPSiKEOAxxBz2IqKybpjNYEkKsKyIQWEkRQQhxSouENtskIST5RAQDKwkhTmuRIIRYD4oIQohL59og1gGTfIVFhtlFdYZFvkojTpKfU6dOyNq1K2mJIIQ4BRQSNhIR/Q73knMPz9ji9MTGlClTVhYtWiZhYWF0ZxBCHB4KiXhw+0mY/PvkhZqYCovHf38xmVRi8mXAEmGPIqJEplLi5e5l62I4JXBnPHz4UD+EunnzQFsXiRBCrAKFRDz44ewdWfLb32brf+xTWXzTJK0KN9TZKl7u3mIPQERw/oLky53x88/7ZfPm7ZIzZ65kOAshhNgGCol4gCmxLWGN7J0QEd4e9iEkSPIn4Prjj+MUEoQQp4KjNuJBRAxCAi4OQhKSxbNZsxasMEKIU0EhkQQhYQ2LBHFOmAqcEOIqUEgk0rUBCeHGpErEAhQRhBBXgjES8aBFyWzy5msZJSIySp9G/L9kjYSY8eTJYzl8+BDniSCEuAQUEvGgUGZftRASHzJmzCQbNmyV338/Kk2aNGOlEUKcGro2CLGSO+PYsSP6z1mzZqWIIIS4BBQShFgpJqJp0/ry7bdrWZ+EEJeCQoIQKwVWqh+UG39ShBDXgm89QhIJR2cQQgiFBCGJgiKCEEKioUWCkARCEUEIIa+gkCAkgWC6a19fX84TQQghrjaPxNht5+Wl26sEWRm9PWVY3UJx7vfWrAPqb7o0HtL5rVziniqV+KdNLU2KZ03W8hL7FRLjxk2UwMDW8sYbZWxdHEIIsSkuJSR+vBwsoeKl/5w9fZoE7f/0RYQs/OWa+n/hzGkpJFzMnbF8+VLp2LGLeHlFp1uniCCEELo2Eo2HO71CrhYTMWLEYOnevZPodJaTuBFCiCvC1jAepPEwr6YsvqmT434QOw+sDAxso/4SQgiJhkIiHlhqNhoVyxKfXYkDw9EZhBASNy4VI5E5bWoJS/XKkoCAyXjt55taXkREp/vMkcFLAktll9qFMydbOYntoYgghJD44VJCYuO75UXn4ZPw/XqUT5byEPvl449H690ZCxYskqCgdrYuEiGE2CV0bRBigebNW0qGDBkpIgghJA5cyiJBSHwpV668HDt2SjJmzMRKI4SQWKBFgpD/YiLGjRslp06d0NcHRQQhhMQNhQRxeSAihgwZKJ9/Pl/efjtQnjx57PJ1Qggh8YVCgrg0mohYtWq5CqycOHGqpE+fwdbFIoQQh4FCgrgspiKCozMIISThUEgQl4QighBCrAOFBHFJli79gpYIQgixAhz+SVySTp26yZ49u6Rt2/acbIoQQpIAhQRxGbSsnYiH8PHxkXXrNjMBFyGEJBG6NohLxURMm/aJkaAghBCSNGiRIC6XgKtJkxZSsmQpWxeLEEKcAlokiMtl8aSIIIQQ60EhQZwWpgInhJDkh0KCOCUUEYQQkjJQSBCn5OjRw0bujKCgdrYuEiGEOCUMtiROScWKlWXWrHni5eVFEUEIIckIhQRxKnfGs2dP9Um3OnfuZusiEUKI00PXBnGqmIhmzRpKcHCwrYtDCCEuA4UEcarAygsX/qfiIwghhKQMFBLE6UZnNGrUxNbFIoQQl4FCgjgsHOJJCCG2h0KCOCQUEYQQYh9QSBCHBAGV+/fv4TwRhBBiYzj8kzgkmTNnlk2btsmpUyekefNAWxeHEEJcFgoJ4lDujHPnzkjJkm+oz3ny5FULIYQQ20HXBnGomIgGDWrJjh3bbF0cQggh/0GLBHG4wErMXkkIIcQ+oEWC2DUcnUEIIfYNhQSxWygiCCHE/qGQIHYJRQQhhDgGFBLEbgkPf8l5IgghxM5hsCWxS9zc3GTOnAXSoUMXqVChoq2LQwghJAZokSB25c5Yu3aVRERE6MUERQQhhNg3FBLEbkTEkCEDZcCAD6VPn56i0+lsXSRCCCHxgEKC2I2IWLVquYqJqFOnnvpLCCHE/qGQIHYlIhYsWCRBQe14VwghxEGgkCA2gyKCEEIcHwoJYjNGjx5GSwQhhDg4FBLEZtSr11B8fNLSnUEIIQ4M55EgNqNWrTpy7NhpyZw5M+8CIYQ4KLRIkBSNiZg0abxcvnxJv44ighBCHBsKCZKiuTPmzp0lrVs3k+fPn7PmCSHECaCQICmegGv06I8lbdq0rHlCCHECKCRIssIsnoQQ4txQSJBkgyKCEEKcH5sKiRcvXsjIkSOlXLlyUrVqVVm2bFmM2/7000/SokULKVOmjDRr1kz27duXomUlCWfhwvl6dwZnrCSEEOfEpkJi+vTpcvbsWVmxYoWMGzdOFixYIDt37jTb7sKFC9KnTx9p3bq1bN68Wdq1ayf9+/dX64n90rlzVylb9i2KCEIIcWJsNo9ESEiIrF+/XpYsWSLFixdXy6VLl2TNmjXSsGFDo223bt0qFStWlC5duqjPefLkkf3798uOHTukaNGiKVZmZKQMiwxL8nHCIkPFWTHM2pkhQ0bZunW3uLu727RMhBBCnFBIwJoQERGhXBUaZcuWlS+++EL51t3cXhlLAgMDJTw83OwYT58+jfUcKoFkqpg/J7SB7He4l5x7eEasCcrkLIkutZiI0qVLSufOPdQ6Dw+KiORAe2ac5dmxZ1jXrGtnI5WV3x82ExL37t2TTJkySerUqfXrAgICVNzEo0ePxM/PT7++QIECRvvCcvHbb78pF0dM+PmlFXd3N5GXrwSJv5+vSOrEDTsMCQ+xuogok6WM5Mqa2SlSZkNE9O7dW1asWCarVrkpq1JKWotcFX//dLYugsvAumZdOxv+Vnp/2ExIhIaGGokIoH1++fJljPs9ePBA+vbtK2+++abUqVMnlu2eR6ut8BAJ+G9d8INnovOISlx5I165IzbW3Spe7t6SVLzcvSQ4+Jk4iyUCIgKiCDEvmTPnlPv3Y7cYkcSDZxsvgeDgp2LgTSLJAOs65WBd27aeAwLSOZaQSJMmjZlg0D57eXlZ3Of+/fvyzjvvKDfDvHnzjNwfllAVpDP+nNiXruF+ady8rSIkTI/rDEM8P/tskXTq1EmJCEe/NkcgKc80YV3bK3yuHauebTZqI2vWrPLw4UMVJ2Ho7oCISJ8+vdn2//77r3Ts2FGJjZUrVxq5Poht4DwRhBBCbCYkihUrJh4eHnLy5En9uuPHj0vJkiXNLA0Y4fHuu++q9atXr1YihNien37ax3kiCCHExbGZa8Pb21tatmwpH3/8sUyePFnu3r2rJqSaMmWK3jqRLl06ZaFYtGiR/P3337Jq1Sr9dwDfYRtiG2rXriejR4+X7NmzS1BQzIGvhBBCnBebCQkwYsQIJSS6du0qvr6+Koiyfv366jvMdAlR0apVK9m1a5eEhYVJUFCQ0f4YFjp16lQbld513RkIlNWSbvXrN9DWRSKEEOKqM1vCKjFt2jQ5ceKEHDx4ULp166b/7uLFi0pEAMx2ic+mC0WEbWIigoJayNOnT1L47MTaVK2KqenLyZ07d8y+27z5O/Xdl18ucqiKf/jwgezfv9fWxbB7+vR53yr3Fs/IH3/8LtZk9uzZsmXLZqN1OAfOtWTJ52bb4zpwPfEt386d2+S997pKvXrVpEWLhvLJJ+Pk33/NfwNJYd26tdKyZSOpV6+6TJkyQXWELYGya79DwwXvWMPytm/fSurXryEjRgyW4OD7+u8mTBgjx44dFlvDpF0kwYGVx48fk8OHf2XNOQGIUzp06Gez9QcO/OSQ85t8/vl8+e23X2xdDLtn8uQZ0r59Z7E3rl+/Jnv27JHGjZsard+7d5fkzJlLdu/eYTR7bkKZP3+2Wpo3D5Tly9fK5MkzVcPcp09PFfxvrdixZcsWy5AhI2XevM/l3LmzsnDhXIvb4h58//1O/bJmzXeSPn0Gvav4yJHflBBp0+ZtWbJkhfj4eMvgwf3U+xh07/6+zJ07y+KEjSkJhQRJ1OiMevWMpzEn5nRfe8Js+fqPf+KsqjO3nljcF+utzRtvvCm//HLAaN3z58/k7NkzUqhQEXE0ktLIuBJorHx8fMTeWLNmhXJZQ+BqYGTfTz/tl65deyjLwYkTxxN17FOnTsq6dV/L5MmzpFmzlpIr12tSvHgJmTJllkRGRigrgjVYv/4bCQpqL1WqVJNixYorQbFt2xaLVgncA3//AP3y7bdrJF++/HohsWHDt+pd27r125InT14ZOnSUGsF47NgR9T2uIWvW7LJv326xJRQSJFY4xDPxnLn91Gy58yTuXC3PXkZY3BfrrU21atXl5Mk/lHjQ+PXXX+SNN0qbNTSbN2+QoKDmyiQMU/Jff13Wf3fv3l0ZPXqoNGxYS2rVqiTdu3eU06ejR2Tdvn1LmWt//nm/tG3bQmrXrixDhw6QJ08eWywTpr4fNWqINGxYUx0P5lvD8sVUDpiJd+zYqpY2bZqpdU+ePJFp0yZJs2b1pUGDGjJx4hi1TmPRos+kRYsGUrt2FXWsK1f+0n/3ww+bpUOH1lKjRkWpUKGCzJo1TSIjI83KC+tcnTpVjBqKo0cPK1P0ixdhcunSn9KrV3e1Dczdy5cvidGaYmqiR/n69++trxeUH8eFSX7OnOnq+ADme1zzzJlT1HWuXv2VclkNHPihqqemTeup7bXh9qaujW++Wa32x7aDBvWRW7f+0f/+165dqUztqKO+fXsa3XdDMCvxwoXzpFWrJlK3blUZNmyg3mWgPQNffbVU3dPZs6dZvO979+42m2gQdYn7X7VqDdXww9SfGHbu3KoadjzbhiBof+rUWaqxtgTqxZL7YdKkj822jYyMlPPn/yelS7+pX4cyo94vX/4z1vL9/fd12b79B+nTZ4DeGoj78PrrJfTbpEnjpSwzZ8+e1q+rWrW6+k3YEgoJEiMUEc5P/vwFJSAgixw+/JuRW6NatZpG28FqsXz5YhkwYIgsW7ZG3nijjPTr11PfKKOxj4yMkkWLlqvvM2fOIrNmGQdCr1y5XD7+eJLMn79YvWy//nq1xTKhgXvwIFgWLvxS5s//Qi5duigrVnwZZzlgJsZIIixLlqxU248cOVguX74o06fPkTlzPpNr167J5MnRDcDPP/8oW7ZslAkTpsmqVd+Kv7+/TJkyXn2HXu+nn86Qnj0/lG++2Sjjx4+XrVu/l19+MXcDlStXXsV7HT58yMi8jRc8XvzwwcO6s2rVOhk+fIzqdVtyv9StW1+JL8R5GB4H68HUqRPk2bNn8vnnX8qUKTNVHc6ePV2/7Z07t9U8O19+uVrq1m0on346Xby9fZQJH9vjWFu2bDI7LxohiJsPPuir6tTHJ62MGTNcfYf1uE/9+w+SZctWS7Zs2eWjj/qqgGtTIGIOHPhRjeT64ovlEhERKSNGfKQ3w4PTp0/Jl1+uUj12U06ePK4S/ZmmRNi3b5eULPmGml8IYuLHH/dZPH9coCEvVux1i98VLlxUpWiwBJ4lQ/eDtvTvP9hs22fPnsrLly8kICCzfh2sK7AAYWRibHz99SopW7a8EjsamTL5KZGugbq8f/+ePH78SL/urbcqyP/+dzbO3FPJCYUEiRH0IrZv36J3Z3CIp3MCq8ShQ9HuDTRECN6qVq2G0TbolXbu/I4y1772Wm55770PlEl19+7typ0A4TFw4BBlfoVptlWrtnL16hWjY/To0VP1rtBDq1+/oVy48D+L5blz55ZqAHPkyKka4E8+mS6NGzePsxywoGDGXCzI43P58iVlbRkzZqJ6OePcY8dOVGLk77+vqfN4eHhK1qzZVC9vwICh0qfPIHUenB+Nfo0atSV79hwqdwzKYnpNWkOB7WB+13qlBw/+rASNdj0ZMmRQjXDFipXl008XqobLFBwf1wQhB9Dzx2+wRo1a8s8/N9UxcS0FChRU1zJs2GhlfYG40OjYsasyd2fLlk1u376tRsPhvGiIZ8yYK5UqVTE7L8RU27YdpE6d+ur8gwYNlTffLKesHRs2rJN33+2lGvC8efOpc2I+n127thsdA0IO6wYNGqb2LViwkIwbN1H1sjUzPGjbtr2qa5zHlD//vKieH0NQhoMHD+ifR9RzaGiIsm4llKdPn0natL4J3g/PkqH7QVtQt6aE/WeV8vT0NFqPz+HhMad+CAl5ruJAEAthSJ069ZTQgwUCVg24lyGyw8NfWSfxO8EzCMHtksM/iX2DH/yGDVvVCz8wsI2ti0OSCTQSo0cPUy+q48ePKisFekKGXL9+VRYunK9M7RoQHTdu/K2EJp4PvAjxwkPA3MWLF4x6ogANnAZ6vYaz2hqC3urw4R9J06Z1VW+/Zs06+pic2MphCrb19U0nuXPn0a9DQ5UuXXplmahbt4FqKNu2bS7Fi5dUYqhp0+ho+aJFiylBAuvI1at/ybVrV+T69etSvnxFi2VGI4zeN4Lezpw5pf5WqFBJfQfhg/J+//1GqVy5qjRo0Fg1RJaA+IClpEWLVsqCgN4merNnzpxW9RkY2Mhoe6y7efOG/jNEg0bHjl1k8uTxykpQoUJlVUZLAgaNfffuxfSf/fz85cMP+6sGC+4nQ9M6GqyiRV9X99gQ1D/KYrgtyo26x33Q7gFEWUwg2DFjxoxG6w4d+kU1spqFDM8QhNSOHdukYcMm+jJZio3Rnj8t3gJiLjG99k6d2sq//942W1+/fiMV/2BI6tRp1F/T4Ed8jin1A4BFENYr7ZnRaNYsUP766y/58MP31OeaNWsrMagNvwcQdphPyVrBoomBQoKY/fjQkytcODrQDqbAmMyBJHZKZjefLC1b+phfJhq+qT0s7ov1yUGpUtE+Y5jVDxz4WapXN3ZraL3sfv0GqYbdELzQ8MzAF4+XNHpQVapUVy9OxDkYYtpLiykwsmzZt2Tjxm3KjYB4jenTJys/OawJsZXDFNOkgBpRUZFqQWO+du0Gdexffz2oTMs//LBJuQJOnTqhhto1bNhYWREGDRogo0ePjbEO4ROHFQO97yNHflV1qF1vp07dlEBAg37o0EHp3/8DFTSHgD9TIG5WrVqu6hK9bm1kBa4bPeClS6Mn5TMkc+bMamQAgPgxbOhQlwcP/qTqccyYYcpi8f770TEXGoaBjcb1lybW+otPXcPdhSWu7QAEqeG2AOIUYPjjq/NHSapUV1T8BaxJEIuGVhlDNwPA96BIkaJy4cJ5i+dGECaEU69efcy+mzlzrkXRa+mZy5Ahg6o3jATRrCvYF4IsJvEI8MzAymY6q7O7u7t89NEwJezgMoE4e++9LkpgGhIVpRM3N9uNsqJrgxg8jFEyZMhANfYZLzySNJZ1KGO2tH8zZ5z7lcyR3uK+WJ8coCFBLwfujV9/PSDVq9cy2+a11/IoXy16hNoCM+u5c2dUbx0uBJjsu3Tprnrd2lj3xIyiQOT6xYvnpVGjpjJx4lQZOXKs3m0QWzmA4ZDV3LnzqsYEbgwNuCaeP3+ueshoXBFQifIOHjxCvvpqrepZw6UAQdGkSXN9gw+/PdwLMYEGoFatuuqYcEFAEGgBiJ9+OlOJinbtOsn8+YvU0EPtekxB45M3b35lzoalQRN1KC8aS1yfdt049mefzZWXLy0P/YMVBNmSW7ZsI9OnfyrvvvuBRZdArly5jQIB4X+HNQhzxcA6odWt1ijC2mRo5dGsl2j0DLfFcW7e/Nts25hA/iTDAFwEWCKQFUJs+fI1+mXevC/U95p7BW4U3GPDIFoAcQUrgHZ+CKvz58/pg4ANUzBgxIapODK08hg+b9piarXTngN0vAzPgTpxd/eQggULS0wgxgHuJ0u/hVWrvvovB1UGlbgSLqAyZcoavbdRb35+MQuV5IZCghiJCPSG4OeDb5a4DvBB//DD95Ipk7/yuZrSrl1H1WtDxDwaVETn79+/R/Lkyad6fHiBIigOAX8//rhXli2LHhFgmuE3PiAoDSMMMAQVDTtM/JqFLLZyALxw8exCbKBRhjVh4sRxqgHByxqR9rAewH2DZ/6zzz5VroToeKAf1P7w3+OlffbsKSUqMJJj+PDhShzFdj1wHaBxwzaIE9AsBGhU5syZoRo7uAlh7dCuJ6bjQBzBHaH59BGfgM/jx49W14LGHNeCeIGY0gTgfKhHWBhxDQgGtTSkF3551CksF3BzzJgxRbkgsLz9dgfl3kFcybVrV2XatE9Uz7h27egAUA3Ep8AMj/NhBAnOOWHCWMmSJatZ7zkmUDbDESGIFcGwTMRm4X5pCxpRuAAQHwLQAOfLV0AFiEI84LmAYMLIEIzE0CwuJUqUkqZNWyq3GQJnsR2CajEvA55fWGusQWBgG2XdQvlxrxCE2rx5S71rA42+oQUF4gz1DgFpSvbsOVVwLuoU93DMmKFK+KIeNHBfQMGCr9alNHRtECMRoQVWmgb9EOemfPlK6oVmGmRp2Lihd7t06RfqLwIqp02bow+a++ij4WpoH3rBsBogoh2jFRAAFptJ1xIIoERvdPjwQaqhLF26rHJrxKccDRo0kZEjP5Ju3drL1q17ZfToCapxwxBKNBa4vr59owMqMaqiR49eaoIimLVhwcCcAhgd0L17TzW6o2fPbqoxr1WrpmogYgtoK1GipPLxo5EzdBdMmDBFNWrvvttV9dpr164r3br1iPE4GKWxaNEC/WgNjTFjXl0LjoPzIMA1JmBlwcgZDPWEa6Ry5SpqtIspiNmA8MLwVtQ7GuqJE6NHg8CKAgvO9OmT1HclSryhrCoIQDQFwxYXLPhUxdvAtQX3E6xUsbkzDIH4ggXp6tWrki5dgOzZs0tZyiw9P7CyYHgpxCbqfdas+fL55/PUvYdbCKOGYPkxFQdDhoyQfPnyKQsERuUgXgZCZ/z4yWrEiDWoW7eBCnSdMWOyCrBEgOgHH/TTfz9y5BAl0kaN+lgvLHB/0qc3F4SwSCHGBAISFih8HjDAeLQIhCrEVGICSa1FKp2TzuBy795/QTXhIZJ5cbRJ6X7PP0XnkbhJWEIjQqXJ7ujxzdvq7xNvD29xVhGRlNEZsCwHBKST+/efWiXPPWE92xo+0ykHrCwFC+aTdu268v0RTzC3B4KEIQiT+kxnzpy4JJh0bbgw1hYRhBCSFDDSZMuWLTGO6CHGYPQMgk5hqbMlFBIuDMxp8PtSRBBC7AG4qurVq6emlCZxg5wemLsjppE3KQVjJFwYRJIvWfKVSgwDfzEhhNiaIUOG0DUaTxDbYQ/QIuGC7oxNm77TT9YCMUERQQghJLFQSLhg7oyePburyGFCCCEkqVBIuGgCLsx4RwghhCQVCgkXgFk8CSGEJBcUEk4ORQQhhJDkhELCyUEshObO4DwRhBBCrA2FhJODjHKYopYiglgLTIa7ceN6VmgMMzNisVRPht+lFFWrllN5GlIapExfvHih0bpbt/5R5Zk4cYzZ9shz0qZNM4vHwnp8bwiSo2FGxwYNaqgEY8jUioRs1mTPnp3Stm0LqVOnijr+o0ePYtz233/vyNChA6R+/RqqvJiC2xDkc+nYsY3Uq1dNPvigh8qVojFhwhg5duywODIUEk4OMhcePXqKM1YSq4FMn8gdQcxBjhEslurJ8DtnBlk/V6/+Sp8CXWPfvt0qSyiSWSHjZmJBgrGxY4dL5crVZPHiFTJnzkKVEOvDD99Tya+sARK8TZ06Ud555z1ZtOgrlQkVuVdiYuzYEeLt7S1ffrlK+vf/SIkoiAeAZFvIlYEspl999bUUKlRYhg7tr5Ijgu7d35e5c2ep/CSOCoWEE8ZETJ8+2SjlsaVsjoQkFidNz2MVfH191WKpngy/c2ZghSlfvqJZVtK9e3f9l43TU2V0TQx4ryE515AhI6V9+04qwysaZiQ0y5kzpyxfvsQq17BhwzqpXbueSmWPNOU4/m+/HVJWFVOePHmiUoV37dpDJY+rVq2mSqh2/PhR9T2sDZixE8eCkOrVq48EBwfLtWvRFhSkJM+aNbsSWo4KhYQTBlbOnDlVWrduprLFERuBRiQ8JHmXl8+NPyewgV+//htp3bqp1K5dWXr06CynTp3Uf3flymVlOq5du4q0b99Kb6JHuu1+/XqZmc1heobpFtvjWOiNaxw/fky6deugzhMU1EI2b96g/w7m6EGD+ki9etXV9717v6tPi2yJH37YLB06tJaaNStKkyZ1VMZKTPUO7ty5IwMHfqjMx02b1lOZMmPK2aCZn7t2bSd161aVIUP6q+niNVCGQYP6KlN1ixaNZMGCBfpJ3JBdctSoIdKwYU1p2LCWMk0jM6ah+8JSPWnfIYU0rtXQ5RAS8lyt0+4BerOdOgUps/p773VR6a5jIjQ0VGXnbNy4jlqmTZtk8bePDJ+jRw9VZa5Vq5J0795RZY6Mz/OArK4tWjRQ9xfZRNHLtgTqCG4NNKaG4D4jRTgyfCK1u5YCPKFAjCDFe716DY3WI7PrqFHjVeZYS6DMuA+mC9ZbAunI33ijjP5z1qzZ1ALBYEqaNGmURWTbth/+Swl+Tc6cOa1PFY/y4vpR16gfbJc2bVrJkSOX/hiYFNDwd+FocIpsJx2d8dFHw9QDTmyATicZNwaK553k900bJlgOz/6WPArcGJ3aLw7+/POCLFw4VyZNmqF6S+vXw1w8TDZt2qFSHw8e3F/1oIYOHaUSA6Gh8vHxUS/wSZOmy6hRQ+X773eqlyREBBptzPlfvHgJ9aJEw7x27Qbx8/OXMWOGy9tvd5D69RvJmTOnVHpxvKTRm0QqaKRxRhpyNLBwBaDHidTgpqAxRepnpBQvXLioXLjwP5k4cayUK/eWStX86afTxdvbR5YvXysPHz5QjWaePPmkVasgi3Xw5ZeLVJkLFiysjovtP/98mfKFf/jhu1KlSnVZvPgruXnzumqc8bp8++2Oaj+kHV+48EuJjIxQQmLFii+ld+/++mNnyZLVrJ60xhNWCfRYf/55v2pYwaFDByVjxkxSqtQbcunSn0pwIA34668XVz3hwYP7yYoV36jeqykwwaORnjp1lqRJ46ViEJYs+Vyl9TYE5fT1TSeLFi1X74svvpiv0ozjuLE9DwcP/ixbtmyUyZNnSUBAgCxe/JlMmTJelixZaVYWlAN1r12XoQDIli276t1XrVpDPv54pNy5c1utSwiXL1+SIkWKKeFgSt68+WLcb/LkGRZdB5jZ1xIQlQEBmY3WZcrkp8SYKWnSpFHPEX4D3333jRK2jRs3k6ZNW6rvkVDr0KEDSiQj/TvezzNmfKrS1WvgN4D9IVJNLTmOAIWEE8AhnnZIPBpzW3L79m31QsuWLZtkz55D3nuvt/I541lCkBkaNa13B3PtnTu3lG+6YcMmki5d9AvQ3z9axuDl2aZNOyU8wAcf9FUWCZiHO3ToLE+ePFaCAufBghc09kWvuWXL1hIYGKT8ywDHWLvWvIECEAnDh49RogHgWN98s0b19rAO11SkSFHVOKHBnTFjrr6slmjSpLk+9fKIEWNVYB0sMceP/64aZIgoJEPKly+fhIU9k/nz5yshgbpAWeAyRE/0k0+mm7kx0GCY1pMhaFw++2yuDBgwRN0HmPpr1aqr/v/NN6tUbFP9+tG9bmTkPXnyuJravm/fgWZmdew7Z85nUqpUabUOZv9Lly4abYfywUpQs2ZtJXJAq1ZtleCL63nA9cIdgR45vh8wYGiMsQgQJNmz51QB3obAbA8BASpVqiKenqll585t0q3bu5IQnj17qhr0hAIhlxBevAgzuwZ8fvnypcXtr127quoL7hZYa+bMmSHlypVX4hnPP1wZAwcOleLFS8rmzd/J5MkTZNmy1fprwbOEZw33zVSEOQIUEg4ORYQdkipVtGUgIjQ5TyEB/r5yP/jZK4+Gh3e8BQx6xPnzF5QuXdopEyxe8s2bB6qX2bVr1+Svvy4pF4FGZGSUahwtge0RlGZIiRIl5fr1q+oF3rJlG5k27RP56qulahRRkyYt9L0xfIcGBdYFmIQvXrwofn6WG4qiRYup3h8sAlev/qV6vzdv3lD+eC0F9eTJ4+XAgR+lQoXKqrGG5SImSpZ8Q/9/vMhRVlwLyo1er2FGxTJlyqjGAD3GoKD2Mnz4R2q0ABqLmjXrmJna4wLWDlgSYEJHLx2J8+bPX6SvzytX9iorgAZ60+XLVzI7zj//3FA9YNSNBqw9hmZ5AJEQGNhGWQbOnj2trEwYOaC5a2J7HurWbaBEYdu2zVVDCEHStGkLi9f16NFDyZgxo9G68+fPqftUvXq0uwOWrbfeKm8kJHAerSymYL12L3CPEPiYUD76qJ+cPn3CbH2pUmVk1qx5ZustiQZ8hnA05fffj8rWrd/Lpk3blAAtWvR1ZbmAlQpCAha2AgUKSuvWbdX2EKhwAyLDKQIwASwssEQ8fPhQHBGXEBJ4z4amSiWhEaGik8T1FMMik69RSApQvpwnwg5Bg+7pk4zHx9surYhnVPQDnkDwQoTZHpYDmF3hnoCPFlHnaJgwhTrMtfHBtOemCQ8sYPDg4cq9cPDgT8pMDh/61KmzVWMH/3+GDBmVjxgNFsTE11+vtngeNLYYhtewYWPlZ3/nnfeVaV4DL22UG+fB8MAxY4ZJx45d5f33e1s8nmnq5aioSHFzS2XxerRGDtvgHBs3bpNffvlZnQfBzUePHlYul/gCCwxEFdwb9+/fVRabYsWK/1d3karcsP4YYslVGd/00Sg/4kcghOrUqaeEDMQJYj3ieh4yZ86i3FS4xl9/PShff71Kfvhhk3IhmTasECxazIoGxAvA+Q3LAysJ4gZgSYHLRYszMQXr8T2AwPv229VqX5zLkH379siRI7/KyJHjzI4xfPhoi3EjMbl/AwKyKPeVIfhsybp08eJ5ZQGDiNCAGMN7Ofr7C9Kmzdv67yAa4E5DTI8hUVE69fw5Ik4vJPDAdcmeVU56pRHZb3mcsiMDRbtlyyblD4UJlJD4gF4pgiARaQ5Tas+efaR58/rqxZ47dx7VSMLErVkhdu3aLufP/08GDBhs9gLH9uhZGwbYISgNQgG+5q+++lKZ5HEuLAhiRGOFxuT+/XvKR681iIhwj2lUCBovuCMQ/wMQ2IYofi1vDAICEWkPKweWVau+kp07t8YoJBCLoJUZPWbEaBQoUEj1qn/6ab86vlauEydOKHcPesTffrtGbQc3DBY0lDBVmwoJ03oypU6dBire4MGD+8p6Ylift2//YxQPgfiF117Lo1wehsCSgnt06dIleeONaNcGhBRGLyxbtka/HUYIQCT88MMeyZQpk1qnBdCivnG/Ynoe4MbBPAmwaFSuXFVZn1q0aKgsQoiJMQSmepjyNXCP9+/fq1xIsBhpQGwg0HHHjm1KSKDH/vz5c+WmCgh4w8hlgPUYmQFq164rS5YslD17duldP9rxvvlmdYwxFxBDCQHXhWtHrAPA9d+9+6+yyJgSEJBZWYYgzLSYC1h84OIB/v6ZzQKI4Rpq0OB1o3qKdgGaCxVHwOlHbYRFhUWLCCtRIlMp8XI3N2/ZiqxZs8revQcpIkiCQE8MjQ1GQWCEAXzYiP5HA9mgQSM1xn3GjMnqhfjbb7/Ip5/O1DdAWjzDhQvnVS8PcQMbNnyrTNV4QX7++XzlGkGjh4b3wIH9Mm/ebNXoozG7fPlPKVSoiGTIkEGdEw0fyoCywIQe03h6HOvs2VOqAYMfGm4MCBXNBA1rBgLWEJCH7w8fPqTOExMYpQDBhO2nTJmgAt4QDwLLBsqAAFM0ACgf4iPQkEIc3L17V53n7NkzcuPG3ypGQYvQN8S0nkyBVQVC6sCBn5UA0mjbtoPs3btblQ91htEl3367VpXNlLRpfZXlYu7cGWruA7iIFi1aKGXLljfaDj169IT37dulghx//HGvLFsW7UpB/cX2PKCR++yzT9VIEnwHawUsEZbKA1cSttHmiTh16oQy86OTA9eJtuC+1K/fWH78cY+qG8RfVKtWQ823cOTIEXUMWEA+/niUsqBoQgBCAUIGbiEIOtQ/rhuBsqgrDK20BrjXEM9bt25WzwcChCGitKH0EJ2aYKpSpboSnCgTnv9ffjkgq1Yt11shmjdvKVu2bFa/DwhW/D7+/fe2PqYIaEKjYMGC4oik0jnpoPB7956qv6FhwdLkP0vExhrrJU2ahAfqGAIREVdPIznBjxr+WfQa2rXrKPaG8t0HpJP7958mdDQiSeF6xosScQvobeFF3qNHT+Ve0Myx8+bNUv5tNODwiWPiHDRGaHgw2gKi4OOPJ6lARzR6eLHD/Auzbe/e/aR06TfVsXAMTLgDAeHjk1ZZFRDIiWMtW7ZY9YxxTPRKcR68kOE6MO1F3r9/X00KhJ4iGlAE7SEI8NatmzJ79gI1WgCujt9/P6Z6qJUrV5GBA4eZ+ey14Z81atSSI0cOq5d6pUpV1SgJLXYDQYMoM8oOS0SHDu2ldesOkiqVmxJZGOWBBiM0NERKly6rrCRoZLSZK0eN+tisnrC99p0GtkdDuGbNd0blg5UDdYMGFXMPdO+Oobh1Ld5HDB2F0IObBD1iiJI+fQYqFw2GOM6b94V6X8ClhPuNgEVYNxAYiAbys8+WSIkSpWJ9HuBugljE/c2dO698+GF/JbwsERjYWAWvInYFYhSCa8WKr822Q2ArYjJQNzgPhAssNBBuiEeBdQOWmnff7WXmgkCj/N1336qGG99htEvPnh+qslkLCKalS79QMRlvvVVRhg0bpdxwQBviu2DBYvUZlpS5c2fqnxfEQyCWRmsrIEhQhxChsK5gYjIEBmvAjYR7rh3PVu+PzJkTN2LEpYTE9tpQ0v7iDIGVUMC//faHGkJnT1BIsJ4dAQgJCCPNdB0bfKYTBoJhIUYsxSqwri2DOVsgorVRRI4mJJzeteGsozPmzl1odyKCEEIwe+WxY0eMYiVIzMB9COFlGCfjaFBIOAAc4kkIcRTgSurSpXuMo2+IMXBhYYRUfEfg2COOW3IXgSKCEOvz3XfG2SSJdUGwIokf48dPFkeHFgk7Z/v2rZwnghBCiN1Ci4Sd06RJMzVHRLFir3OIJyGEELuDQsJO3RkYx45hTQisHDt2gq2LRAghhFiErg07FBFDhgxU46sxXp0QQgixZygk7FBEYFY0TNF7+PCvti4SIYQQEisUEnYoIuDOWLBgkUr5SwghhNgzFBJ2KiKYgIs40yySmG44KWA6Ykz3jL+uAq73jz9+V//H9N9IfmXpu5QA9w/3MaXBxMtI7oVJm0xnz0QdIIW3Kdge35uC+sI+hiDPB+ZxaN++ldSuXUXatm2h9n3xwnpu5RcvXqhcLg0b1pQWLRrEOr8Gyo4ymi7IK6OB3CstWzaSevWqq+NqLnDE1XXv3lE9KykNgy1tDEUEcXaWLFkpPj7RCaxI/Pn++50qzwlAoic0qlq+DcPvnJkdO7aqRF2ms/giLwVykCDnRrlyxgnK4gsa3n79eqmGuG/fQZI3bz6VPAs5M5BrZvr0OVa5hoUL56rEbXPnfqESpiFPR7Zs2aRWLfPcKZMnzzBKWoc8LGPHjpBWrYLUZySIg/AZM2ai+Pn5yaRJ49XxMaEV8qxgVtGFC+cZ5XNJCWiRsDF4cJGwhZYI4qwga2iaNPaTMddR8PcP0KelNk2JZPids4JrXrHiS5US3hA08sj0iZTnSFSmZRpNKGvXrpRbt/6R+fO/0Gf2xN9Jk2aojLdIaZ9UQkND5Ycfvpf+/T9SSbqQKK5Dh84qy60lIA5xb7Eg+RcyuXbo0EWKFo1OOY7keEgGVqVKNSlWrLgMGTJStm3bordKIHMtksNBsKQkFBI2Jn/+AvLttxvls88W053hZC/B0IjQZF1CwkOMPick/964cSNU5kdDkLIZmTcB5v5H5so6daookzZ6QcioqZm5P/igu4wYMVgaNKghu3fvkEuX/pRevbqr7WF2RUpqS66NiIgIWbToM2Xixb6jRw+Tx48f6U3A6E21atVE6tatqs6PcljiyZMnMm3aJGnWrL46zsSJY9Q6zYSNc86cOUV9t3r1V2b7P3/+TJmLmzatJzVrVpQOHVrLgQM/6b9HGu1oc3dl6dgxSPbufeVWMATnQrZLvOAbN66jyoPGzxBce8eObZTpvEePziobqMbx48ekW7cO6jxBQS1Up8LUfQFTO3rmWDT3gvbd5s3fmbkckOWzXbtA9X9kIEVm0CZN6qhlwoQxsebAQPbKDz7ooe5ju3atVM/fEki//s470eWGyX7cuJH6Bv3p06cyatQQtb5hw1rqnKhvcOfOHRk48EOpV6+aqnukY8czYQmkEUcDWbx4CaP1KFPBgoWkZs06al+IicSA+kTSNlPLDo6NLJzFi5eK0cVmadluwX2HjLeRkRFSsuQb+nWlSpWW//3vnLJGx16+H+Tp08fSsWNX9Rm/v/Pn/6fPqgtQN6gDnAdAXCIrK56BlISuDRuAB+jGjb/15jqY5hJrniP2Bxr0fod7ybmHZ1L0vCUylZK5FT+PV5r7OnUaKP8qXkKY4x8Nzq+//iKTJk1X5R81aqh6oS5fvkal70Y6aKT97tbtXbX/mTOnVT4FpG5Gz6l//w/UC3Ls2IkqtfPo0UOlaNFiKj23IUjLDHP0iBHjVKpqNPY49iefTFf/P3PmlIwePV693GHOHzHiI1m6dJVZ+UeOHKz82DA/o7yzZk1TKcanTp2tvkePDNf05ZerVapxU5Ai/MaN6zJnzgLx8vJWvdNp0yaq1ORIsz1x4lgZOnSUSr/94497ZdCgQbJ583ZJl87cnYDU2rimOXM+U8Jn0qRxKgV28+aBqnFBYwnTM17627b9IEOG9Je1azeIn5+/jBkzXN5+u4PqSeLaIe7eeKOM5MuXX3/89u0762MEBg4canTumjXrypw5M5TpHPUN0LAilTiAaLtw4X8yY8ZcZRXCZ5xz7tzPza4DvnU08ijLiBFjVPpvmOHz5MlntB2sARCAuCY0WniXTZgwWrZsgYDppIQP6mThwi9VIwohAXHVu3d/+fTT6eLt7SPLl69V58NzguNrpntDjhz5VcqVe8voeca9hshDKnofHx8pW/YtJQgaNWoqCQEC5ebNG2qiP0vgHlgiS5asyq1kCV9fX7N1wcH3VepxQ+sR7vvLly/k8ePHylpnCVzn6tUrlfUB1wnwXGK/gIDM+u3w28VvBenJNXBPNm1ar36bKQWFhI1yZ0Axfvfd9zE+sMSxSSVxN+a2pGLFyqLTRalebfnyFVXvDxOgoeFELxkN8eLFXynxkDt3XvnwwwGqB68JCbzcu3btrndZ3LlzS6pVq6H82TARf/rpQsmePYfZy/GHHzapY+H8YPDgEbJ//x5lTdi1a7vMnDlPlQGMGzdRWSeQSTJ37jz641y+fEn16tEYa+shYNDr//vvV0F56MnlyvWaxetHr65du46SP39B9bl9+07yww+bVQMICwkEVubMWdT14Ls33ywlqVOnsXgs9BSHDx8jhQoVVubrS5c6qN83hMR3330jbdq00zd0H3zQV5Udpm2YuGEdQMOCusKCRgJmbUPQkODeANOGBwmyypYtr8QDhATqEfcUdYzGcuPGdUqIFSgQfZ1jxkxQlom//rqsX6exd+9uJZQGDBiiv+8oHyxFpu8wbIPrAyg3ynD16hX9swCxgOfAy8tLiUTNWnb79m1VR6hX3BsInHTp0lus1z//vKieTUNOnz4ld+/+q541UKNGbZk+fZJ6XnHM+IJGGaRNa974x4a7u7vZ/YkN3ANTF5T2OTz8ZYz7nThxXO7d+1dfx9qxDPc3PJ7hsRDrgd8InkuUNyWgkLBhAi78mCkknA+V5r3i5xIWmXwTiqGT5u/vK8HBz0TzaHi5e8XLGgFSp04t1arVVA0QXtb4C1MxXjzXr19VDQjcAobPLhoUzQ2BHrdh3EPnzu+o3i4aUPiZGzRobPbCffTokeqFFSkS3XMG6Hn36NFTzp07q87x+uuvzNjoaUEooDyGQgKffX3TGa2DdQ8N0rVr1/Q9w9galoYNm8jBgz/Jli2bVG8ffnftOgsVKqKuAb1znAONVpcuHVWjaMl7hEYTIkID1/f119FWFJTnnXfeM9q+RImS6hpwffD/T5v2iXz11VLl927SpIWkT2+5YY2JunXrK/cNeqBwOeTKlVuJhCtXLqvAvV693rFgEb1uJiRgSSpcuLASERqwMER/90qgvfZabvH0TK2sDFeu/CXXrl1RIgL3HKAXPXz4R9K0aV1lacVzVa9eQ/Vdx45dlCA9cOBHqVChskqdXbhwUYvX9ejRQ9WbN3Vr4L5q+1StWkNZtGAR0kQueumW3HxYpzWsmniBGyYhwDXTubO59QQgXgHWHEMgPg2DJ4H2Gc9TTPz44z4ltg3dLpqQtXQ8w2NlyJBB3WP8hvE7TQkoJGyYxdOSOY84B7jH3h7JN1IBesHH00dCPCItNm7xAS9xvNT79x+sArSmTJmp1qMng97o1KmzzPbRenAQIoZ06tRNmdPRQBw6dFC5OuAaaNaspX6b2NIkmx5PIzIySi3x2TYqKlItGlov3hJwIcA907BhY9WYQ/RoDS7u3fTpn6qIedQLrmnTpu/ks8+WKJFhimmvD7/1VKncYiyr4TUNHjxcvQcgag4e/FkJMbhn4GKJL9Wr11JuITTqmMiuTp1ot4YW07Jw4VIldgxBxL8p8U1jjXiY3r3flapVq+stO+vWfa3/Hu6GjRu3KVEDd9n06ZOVxQtWIzS0+B7Xi+/GjBmmLEfvv9/bwplSGcUR4HrgZoKYrVGjgn49ttm5c7teSEBkPnsWHZNhaoVIly6d/tmAiL148bx+JIwhcPtBBGkCSCMgIEC5ZSzhZ6FOM2fOrLdwafULqxfOj3LGBNw63bu/b7QOAgFiAu4SzS2O40IwGIr2qKjoF4L2DKYEDLZMAZgKnNgjeFGi4f322zWqR6NZx157LY/y9SP2AeZnLLdv/6N835YsHrBUIKAPJlb0YOfPX6RMsmjUDMFLHKZ4LTAMXLp0UQUr5syZUzXI5869iivBC/jmzb+NLA8AIgeNgmEvGT3i58+fm21rCQT+7dmzUyZMmKysIYikR1Cb1muFhWLBgk+VdQQN3OrV6yR79uxy9OhvFo+HshjOb4GYhIIFo3v7KA+sLYbgGrEeDQJiO1C/GIGwdOlK5SI4dOiA2TliszTBAlOhQiXVyGJeBQhEgOGRqFNYgbT7mDZtWpk3b7Y8eGA+1wC+h5XUsDePoYeIHzEELqjSpcvIuHGfqHThGD2A+6Tth+cJDTTcORMnTpWRI8fqnwVYrXBuiDeItXff/SDGYEk0zJoFDMDlBivFJ59MU7E72oKkhjg/YkwAYnvOnTttdjzcB0MhWL9+YxXDYmqVgFBC3IWlmAeIAa0uTRcfn7Rm2+N87u4eRs/A6dMnVZ0ZWn5MLXcYTWIYoAmwPWI6sP+razqjjl+w4CuLGOoM9x3CI6WgkEhmKCKIvYKXInzMK1cul1q16ugbK7g6MM4dQXJoWE6dOqF6lRAblnyu6F3h5YagPzTuaEixT+HC5r13xAsg4BJ+fPSgEfRYvHhJ9RJu1ixQBSbiO/h4J0wYq4LbEDxmCHpjMPtOnDhOjTKA5QBBgegdazEPsYFeHQIs0bhBABw58pvMnj1DbyZGA4LREHA34IWOnvM///wjhQpZNsEDuCfgSsA4/++++1YCA9uq9W+/3VE2bPhWmd7hOkAA6V9/XVKWGpitDxzYrxp2BDAidgIiy5LVA3WPst679yqozhCIh2++WSN58uTRi6noOm0pM2dOVXUKsYU6++efG2bxKwDWAogOjJxBACUaWVgVTOsfDRSeC9Q7rmn+/DlqNIHmp0fgH+4jgjVxHNSJ9izg+cB3uL+4/4cPH7J4vQDrcR5DtwasCHhmcZ+1JTAwSNUlGn+AkRhwKUHcYng9hCFG1SAAsW3bDvrjtW3bTvXk+/btKb/9dkjdA0z6hdFCVapUl4oV428Vignct0aNmsjMmZPVs4qRQXB7GU44CEFpOAEWniM8o4gxMQXCDfvjODgeLFHNm7c0cm2gblHf8XVzWgO6NpIZRI7jB8x5Iog9ggYI5nSM4tCAWIB5/dNPZ8j773dVZnFMntOnT/8YjzNhwhSZPXuavPtuV7U/zMXduvUw2w4uEPQAx44drsyylStXU4F7AD1LWAIwIgANOiwmCNq05B4YPXqCapD69++temqIY8CkQvEBlhNk1MW5EAyZPXtOFTi6ZMnn8uefF5Q5G3MJoNGHyEKAI0ZtVKhQMUY3EoQNzP2oq549e0v9+tEmcbgZYMqGeMJf9Bxnz16gN02jniGmunZtpxp+jEYwdAdpNGjQREaO/Ei6dWsvW7eaD0VFw6fTTdRbIzT69Bmor1PUNywJCHC0JAhhMZox41NVHtQLGjJYHdCgo5duKAYRCDlgwIfq3uCYiAPRhoq+994HyuozfPggCQ0NkdKlyyq3hhZcO2vWVDWDI1wVlStX0d9/8zqtpCZcgqUDzwNcTKbxJpqQhXjYuhXzNQxW4hNWscWLF6ohyRER4ZI3b371zBi6jBDjM2/e57J8+VL17AYHB6t9Uf8IhLVWQ9y37yDV4GPyK7gGo61gr9IftGjRUEaOHKeuAWA0S7p0vhbPX7duAxWwirgQCDcc54MP+hltA1FvDRGUEFLpEjL43IG4dy/aXBUaFixN9kffoO21fxAvL/8ULwvGVyMBlyVfnLOBZz8gIJ3cv/800b57wnp2lGcaPX00EL/8knLTVbtKXUdERKq5PNDIGs6dQGKfACswEPO4rLVodYrrmc6cOea4jdigayMZ0IJ/NI2G4VuuICIIIcRawGoCC1ZKT67kyOzevUNZ+WITEckBhUQyxUR06dJOzbxHCCEkcTRt2kLNEYFYBxI7cP9s3LhePvwwZhdkcsEYiWQMrDQdp00IcS4weRbdGskH4l8+/9x4ynESc+zPihWvhuGmJLRIWAmOziCEEOKKUEhYAYoIQgghrgqFhBUYNuwjoxkrDccIE0IIIc4MhYQVKFXqDRVhTBFBCCHE1WCwpRXo3LmbmnfeMPUvIYQQ4grQIpHImAhMB3z//n39OooIQgghrgiFRCIDK6dMmShBQS3UtLOEOCpPnjxRuRKCgppLnTpVpGPHNrJu3VqjrItVq5ZTMzjaMygfypncIKcHlthAYqoffthssXyYhtsUJEPDlNGWsFT3yNvx3ntdpV69amp6ZWQyRZI1a4JnoGXLRlKvXnWVCTMs7FUuCFOQpAvlNFwwLTdAmnbUB3FuKCSSMDqjd+++8U69S4i9gSyByKWBTI3Dh4+RVavWqdTFyC8xd250SnGSMJCUCjkhkPnSEOShQDZOzDyYlKwE8+fPVguyq2Ia5MmTZ6qkT3369JSHDx9a5XYhydayZYtlyJCRKhcFMlcuXDg3xu0xWRQSZ33//U790r17dE4M5I9AfSC5F3FeKCTiCYd4Emfjiy8WqElsZs2aL2XLvqWSNCHpE0QFZsjjyz/hrF69Qho2bGrUwYDVEplGkSocloMTJ44n6n6dOnVS1q37WiZPnqUSSyF1dfHiJWTKlFkSGRmhrAjWAJkyg4LaS5Uq1VS6awiKbdu2xGiVgJBA6m5k0tQWLaU26gGias2aFVYpG7FP2J2OBxQRJDE8f/48xu8wyscw9W9s22J2P29vb6NtkXTH29tN/V/r4KZNG/3yjm9W2r17d8uHH/ZT2RMNQQMyd+7nki1bdqOMgsgGevPmDXn99RIyevR4/fdINQ3zPNI1IxtkhQqVZdiw0SrHDNZjH5Rt9+6d6vv27TtJx45d9Y0sttm+PbqheuutijJkyAjJkCGjKiNSWu/Zs0Nti+MOGDBYpYyOCzTYyOj4++9HJVMmP9UzRkMOS2KrVk1Uhkpk2gSwEGBdr159pEGDxioFOlJ7I2tvrly5lJUmKMg8I6cpyGq6b99uWbZsjdH6o0cPq2yYVavWkOLFNynXBGbETCg7d25VDfsbb5Q2Wo/naOrUWeLnF2BxvzZtmqlppk1BAz9qlLGbBhk5kRIc16wBsYL7hBTnJUqUMjsO7vtrr+WOsdy47h49OqlMpMgwSpwPCol4MH36JM4TQRJMvnyvGmJT6tatL2vXfqf/XLx4AZUl1hKVK1eVzZu36z+XK1dCpTw25e7dJ/Eu2z//3FQpnosWLW72HRpb04YOvm6IBzTwEyaMls8/nyfjx09Rx0GK6kGDhslbb1WQGzf+Vt9v2bJR2rXrpPb98ce90qpVkCxbtlqZuSEOqlWrKblz51HptdGwjhgxTrJmzabSLSNF8iefTFe+9QsX/qfSXiPlMz6PGTNciZzYgDAYNWqo6iUvX75GBUXjmBBk3bq9q1Ki//zzj3ohce7cGXn8+LFKRQ43wdChA+T993sr4YLvkMo6X75ckjdvkVjPe/LkcVU/WopwjX37dknJkm9I+vTpVaP61VdfysCBQ43EYXxAQw4RZ4nChYvGuN+SJSslKirSbD3q1JRnz57Ky5cvJCAgs34drAoQb3fv3jXbHqnRnzx5LDt2bJXJk8crUdqkSQslFrU02Hnz5lP7nzr1h7p+4nzQtREP2rfvLLlz5+U8EcRpQIMBfH1947U9evMQF8gfg4bi8uVLemvdgAFDlM8eGQfLl68oZcuWV715jQwZMsiHHw5QpvgOHbqoRuXChfOqwf/hh02q0a5YsbIa+TR48AjJl6+Ask5s3LhOmdXReOK8Y8ZMUG6Bv/66HGtZjx8/pnrgQ4eOUr9blBvnh1sAwH3z++9HJCQk2gr044/7pFKlysocD5dOuXLlpXXrt1V5YaFo0SJQVqyI2zT/558XzUTEixdhcvDgASVSQI0atZWA+/nn/ZJQnj59JmnTxu9+GZIpUyYjt4O2WLr3mvsCLi9D8Dk8/KVFa0T0Ofxk2rQ5KlvnypVfmrlZICYuXryQ4LITx4AWiXiAl8Mvvxw1MkUTEhdXr5qbkw1dG4acO/dXjNuiJ23I77+fVa6NgIB0cv/+U71rIyGgcQdPn8bPioFAQQ00QHA7AJi0PT1Ty4oVX8qVK3/JtWtXlIhAA6yRPXtOo+uFywM+/UePHilLQJEixfTfQUz06NFTrly5rLIZ9ur1jlE5IFxu3Lgea0K869evql5ygwY1jPZ78eKFCjAtUaKkakh//fUXqVu3gbKSfPBBP/2+hw4dVCMiNGDWz5cvX5x1hGBHWCQMOXToFyVYYIEBECco+44d26Rhwyb6Hr+lAExt5IwWb4F7BvdJQunUqa38+6/5s1i/fiMl1AxJnTrazYW6NwSfLb3/ypQpK9u27dVfN64N93XTpg3y9tsd9dtBPForGJTYHxQSFsAPeOTIIar30KhR9I+dIoIklITELCR0WwgJ/A0NjUqUkMiRI5cSBBixAb+7KcOHD1K9crgrLIkZreG7dOlP6d37XTUhW+nSb0q7dh31PX8NSyObsH9sI57gqwcLFy4Vb28fo+/8/PxivTbsC0sE4gZM0Xr0tWvXUwGQuXLllkePHir3kbYvGtguXbrr90FdZ84cd1wGTPmGw2a10RqgfftW+nXYJlWqKyqOA+4cX9908uzZs1isRtFxBUWKFFWWHEugzuFmQJyHKTNnzrU4TN3SMwexAjEBF49mXcG+EGYQX5YwFU958+aV+/fvmt1vN7doVwdxPujaMAE/8iFDBsqyZUvk/fe7WQxSIsTRQSMOE/+GDevMep+//HJALYZ+8pjYtWu7lC5dRsaN+0QCA9soUXLz5t/xGuKIwLuMGTMq37/GpUsXJTCwsbKAwIoBiwV68VjQ8CEI8sGDB7Ee97XX8qhGOmPGTPp9b9/+RwV1an57xKgcO3ZYDXWsUqW6vqOAfREcqu2H5eDBn+WHH36I83ogcFBeDQRYHj78qzL3I1ZDW+bN+0JfdwCxHBg2ijk9DMGwS5QLsSQAAuf8+XMq8NUQxNZEz/1hHgcBEBRreD3aAneEKRCMxYq9bnQOxIm4u3tIwYKFzbbHfBkQSYb3G+ISQs4QWIL8/PzjqEHiqFBIWBARq1YtVy+c2bPnG0WuE+JMIDIfoz4GDeqjYg8QOLl162Y14RKG/8Vntlb0YBGz8L//nVXDRTG5FaL+LfnTLdGmTTsVcIlJl+AamTt3lhQvXlLFK2CI48yZU9V3cJdMnDhO/vnnhorFiA3EaWTLlk0mTBijyoZRGNOnT1aNsuZiKVSoiBJKEFJ16tTT74ugUPT6Fy9eqAJHMdIEQZ45csR+Tu2YcMloHDjwk3LhIIlf/vwF9QvcARUqVFIBigCBmIgLQSApxAPuA2IoMOoEViHNcoMRE02btpThwz+SrVu/V9vhvg0e3E8JAG0kTFKBIPz661Wq/BAuCIBt3rylXmzBOqFZUGCxQuAvJqCCAIMFBkM9TcuC+wCLCnFO6NqIQUQwARdxdmCq/vzzL9XkQ2h00ZvOmTOnvPtuT2nZsk28hQCCDAcM+FAN7YR14p133tOb9OMCvXX4/ceOHa5M6JUrV1PBmwDDBdFAYVQIvsOxMYLDNL7EFHw/depsNVwVE27BNYKRGn369DfaDu6N9eu/VqMzNNBxmDZttnz++XzVmAYEZJE+fQZI8+bNVTxKbCCoE+4ICCpYEfbs2SWVKlWx6BJA/Q4bNlDOnj2jYjYwlwdGwowc+ZGqj8yZs6gAVtMGGUNjEa8BCwSuL1269KoxHz9+spmLIbEgbuT27dtqpAsEIVy8WgwJgNsXYg5DR1FfuCeYsGrz5u+U1eGDD/oaiTNYW2A1KVMm+WceJbYhlS4p06zZMffuRf/oQ8OCpcn+Zur/22v/IF5e5uY1igjrkdQgQMJ6duRnGtYcTOwFMUWigVC9e/dfNdGZNeuaJJ6Y6jlz5sTN80HXhogyb9ISQQhJKhjeitgH5uCJBvWA+sAQeuK80LUhIq1bt1VBURjLDn8mIYQkBsSVVK9eS00p3aLFq5EargpiOWrWrGM2vwZxLlxWSMCdgQWBTAhUmjVrnq2LRAhxAnr3fhVP4Oq0bNna1kUgKYCbK+fOwPh3miAJIYQQBxUSmGlu5MiRUq4ccthXlWXLlsW47f/+9z8JCgqSN954Q1q3bi1nz55NcgKu77/fpBLqEEIIIcQBhcT06dOVIMA89uPGjZMFCxbIzp07zbbD0KH3339fCY6NGzdKmTJlpGfPnjEmOUpIFk9tRjtCCCGEOJCQgAhYv369jBo1SooXLy716tWTd999V9asMU7BC7Zv366yyg0dOlQKFCig9sEsd5ZER0zoopARcAyzeBJCCCHOICQuXLig4hNgXdAoW7asnDp1ymy+eqzDd9r0ttFpjt+UkyeNp4qNTUTcWnlL1qxZy8mmCCGEEGcYtXHv3j2V3haz4WkEBASouAlkjzNMzINtCxY0zvbn7+8vly5FpzKOCegOSI8Xt1/Io0OPlIj47LNFHOKZjPyn9fR/CevZ0eEzzbp2NlJZ+T1tMyERGhpqJCKA9llLURzXtqbbGeLnl1bc3d1EF5VWKuVIL3n6F5CuJcdI5y5drHodxDL+/ombIY0kDNZzysG6Zl07G/5Wek/bTEgg5sFUCGifTVN2x7RtbKm9Hzx4rldbs5vsF/8u6eTBw+dxzpdPkgbqHA9ncDCnuE1OWM8pB+uade0qz3RAQDrHEhJZs2aVhw8fqjgJLbsdXBgQB+nTpzfb9v79+0br8DlLliyxnkOroFSp3CSVm5v6zPnbUwbWNevZ2eAzzbp2NnRWahNtFmxZrFgxJSAMAyaPHz8uJUuWVDNNGoK5I06cOKHPeY+/f/zxh1pPCCGEENthMyHh7e0tLVu2lI8//lhOnz4te/fuVRNSdfkvhgHWibCwMPX/hg0bypMnT2TSpEly+fJl9RdxE40aNbJV8QkhhBBi6zTiEAMQErt37xZfX1/p0aOHdOvWTX1XpEgRmTJlirRqFZ34BmIDk1b99ddf6rvx48fL66+/zptICCGEuKqQIIQQQohj45JJuwghhBBiHSgkCCGEEJJoKCQIIYQQkmicRkjYIiW5q5KQuv7pp5+kRYsWKqdKs2bNZN++fSlaVlepZ42bN2+quj5y5EiKlNEV6/rixYvSvn17KVWqlHqmDx8+nKJldaW63rNnjxqdh2cadX7u3LkULasz8PLlS2natGms74Qkt4k6J2HChAm6Zs2a6c6ePavbvXu3rkyZMrodO3aYbff8+XNdlSpVdFOnTtVdvnxZN3HiRF3lypXVemLduj5//ryuePHiuhUrVuiuXbumW716tfqM9cR69WxIjx49dIULF9YdPnyYVZwMdf3kyRP1vhg9erR6pufOnasrW7as7v79+6xvK9f1n3/+qStZsqRu06ZNuuvXr+vGjx+v3t0hISGs63gSFham+/DDD2N9J1ijTXQKIYELxgNnWFGfffaZrlOnTmbbrl+/Xle7dm1dVFSU+oy/9erV023YsCFFy+wKdT1jxgzVsBnSvXt33ezZs1OkrK5Szxrff/+9rl27dhQSyVjXEMV169bVRURE6Ne1atVK99NPPyX0tC5JQup6+fLlusDAQP3np0+fqmf79OnTKVZeR+bSpUu65s2bK9EWm5CwRpvoFK6NlExJ7uokpK4DAwNl8ODBZsd4+pT5TqxZzwDTzc+YMUMmTJiQiLvq2iSkro8ePSp16tQRd3d3/boNGzZIjRo1UrTMrlDXGTNmVBMQYsZjfLdx40Y131Du3LltUHLH4+jRo1KhQgX59ttvY93OGm2izXJtOFpKcpLwui5QoIBRtaGOf/vtN2nXrh2r04rPNJg6daoSboUKFWLdJmNd37hxQ8VGjBkzRvbv3y85c+aUYcOGqRcxsW5dN27cWNVxhw4dlHBD6oRFixZJhgwZWNXxAPUWH6zRJjqFRSK5U5KTxNW1IQ8ePJC+ffsqpYseHbFePf/666+q19a7d29WazLXdUhIiCxevFgyZ84sS5YskbfeekvNyHv79m3WvZXrGlY2NHJjx46VdevWqaDtESNGSHBwMOvailijTXQKIZHcKclJ4uraMFNr165dVbK1efPmmSVlI4l/ppGPBi9aTB/PZzj5n2n0jJFwsF+/fmqK/iFDhkjevHnl+++/52Ns5bqeOXOmFC5cWDp27CglSpSQiRMnqhxNcCUR62GNNtEp3uiGKck1rJ2SnCS8rsG///6rXgR4MFeuXGlmkidJe6aRgwbmdjRs8Dtrvuf33ntPCQxi3Wcaloj8+fMbrYOQoEXC+nWNoZ5FixbVf0YHBJ9v3brFx9qKWKNNdAohwZTk9lnXMAO/++67av3q1avVA0usW8/w1yPp3ebNm/UL+OSTT6R///6sbis/06VLl1bzSBhy5coVFStBrFvXaMiQpNGQq1evSq5cuVjVVgRzR5w4cUJZjAH+/vHHH2p9vNE5CWPGjNE1adJEd+rUKd2ePXt0b775pm7Xrl3qu7t37+pCQ0P1Q4gqVqyoxspieAz+Ygwt55Gwfl1jmGepUqXUdlivLRiLT6xXz6ZwHonkq+ubN2/qSpcurZs3b56aR+LTTz9Vn+/cucNH2sp1vW3bNv08EqhrDCfnnB2Jw/SdYO020WmEBCYpGTp0qPpRV61aVY1BNqxEwzGxeIBbtmypHtI2bdrozp07Z6NSO3ddN2jQQH02XYYNG2bD0jvnM20IhUTy1vXvv/+u5jcoUaKErkWLFrqjR48m4oyuS0Lqet26dbqGDRuqbdu3b68msSIJx/SdYO02kWnECSGEEJJonCJGghBCCCG2gUKCEEIIIYmGQoIQQgghiYZCghBCCCGJhkKCEEIIIYmGQoIQQgghiYZCghBCCCGJhkKCEEIIIYmGQoIQO6B27dpSpEgRs6V9+/bx2h/bHjlyxKplunnzpll5kNsDZfr555+TfPyNGzeq69b47bff9LkVTL+zFjiu6TUhz0ODBg1k7dq18T7Os2fP9HlNCHF1PGxdAEJINCNHjpTGjRsbVYenp6fNq2f9+vWSPXt2fdryFStWyIcffijbt2+X3LlzJ/q4uNaaNWvqP3fr1k1liC1QoIDZd9YkW7Zs8t133+k/P336VH0eP368FCxYUMqXLx/nMb766isl3Fq2bJksZSTEkaBFghA7IV26dCpNteGSMWNGWxdLpX7XyvPaa6/JsGHDJHXq1LJ///4kHRepo2NKKx/bd0nF3d3dqI6RFnzo0KGSJ08e2bt3b7yOoWVKJIRQSBDiEMCUPmLECKlUqZKUKFFCGjZsGGOjBxdBixYtlMm+Tp068s033+i/e/LkiQwZMkTefPNNqVq1qkycOFFZGRIC0kAbWkseP34sY8aMkcqVK0vZsmXV8bFOY/bs2epccIt07txZLl26ZOa+0P526dJF5s+fb/Rd27ZtZd68eUZlaNeunSxcuFD9/88//1THxfHholizZo0kBogjiAxNKHzxxReqDKhvlH/BggX6cuP/R48eVa4R8PLlS5W6vUKFCmoZPHiwPHr0KFHlIMTRoEWCEAdg0qRJcvXqVVm2bJls3bpVypUrJ6NGjVINmCGRkZEyYMAAJTR27Ngh/fv3Vyb7y5cvq++xD0z5X3/9tWqIz5w5IxMmTIh3OZ4/fy5z5syR8PBwqVatmlrXp08fOX/+vGp4ly9fruIchg8frr7bs2ePfPvtt/Lpp5+qcgcEBChBZIrmaoCI6N69u9F3cHPgOBr//vuvnDx5Upo0aaJE0HvvvacEzJYtW5S1BNeVkPgF1CHEB+qofv36ah32hwsH9b5z507lykHZzp07p8qDMpYpU0Z++eUXvVg6e/asLFmyRLlnIPxQ94S4AoyRIMROGDdunLIQGHLo0CHx8fGRt956S9555x0pXLiwWo+GDLELwcHB+vgFAJGAnjAa7Fy5cqklS5YsyoT/999/KysGetJwowCcD35+NO7aOlOaNm0qqVKlUr300NBQyZo1q0yZMkXFR1y4cEEdD41tvnz51PYzZsxQje2VK1fkn3/+UZaLHDlyqAWWC6w3RXNjZMiQQdKmTWv0XaNGjWTatGly7do1yZs3r+zevVtef/115YpAHfj7+yvxBPA9zonGPKb4hVu3bikRoAExAvcGBJK2HnWKa4QFCCDA9LPPPlPWlOLFi6t7gutCvaJOVq9eLRs2bNBbKKZPn64sExcvXtSvI8RZoZAgxE7o16+fvkes4e3trf6iUYQIWLdunWqI0TPWLBCGIKYCjd7o0aNVz7xWrVrSunVr1UD/8ccfEhUVJdWrVzfaB+uuX7+uTPiWWLx4sRIPEBNoQCFSNFCW9OnT60UEQLAkzofvYDVAIwsXS+nSpaVu3brSpk2bBNULzg0LDATE+++/r/5qQak4B8SMoTBAnWguCktAWK1atUoJo1OnTsnkyZNVHUGwaFSsWFF9N2vWLGVhgcXl3r17qq5MuXHjhrLQwN1iCLaF+KGQIM4OhQQhdgJ61uhlWwLBgCdOnFCxDxAK6Am//fbbFrf9+OOPpWPHjkp4YIFrAaICDSysDug5W2qsYwKWBFg2YoorsATOhQXlhIsFlpUff/xRvvzySyWGEjp0EsIB7g80+BBEU6dOVesjIiKU1WDs2LEJivHQ6hkWDHweNGiQukZNyMHSAYERFBSk1sFlgviNmK4VYPgohJbpPSXE2WGMBCF2DvztiC+A6R1Wi3r16umDGU1HD6DXjJgINJQffPCBEg3oXWOEBawGcH3AsoDvscCsDzO8aaxFfMExEcBp6K5ArAHKjO9++ukn1ShjKCfK9f3336teOgIkEwKCKOEmwLEQRJozZ079+RE7AhGgXRPiJ2BxiC+wmsByg/Kh3AAxJIiLwJBcWIMyZcqk3EhafaMONTCSBRYQuJS0Mvj6+irXCPYhxNmhkCDEzkGvHy4OmPQxSdTBgwf1AZKmAgAuBQQmojeNmIhjx44p0z9iCuByQIAkRhScPn1auUcQGxESEqLcE4kBx4SrBD12HBML/o+YDsRzwLwPoYIyoewY8YBrgSXAFPTmEYMAsWMphgIxB4sWLTJyQTRv3lyJIVgk4ILARFkIkEyoJQBBqBBE2sgMCAeMfoFIQRDlwIEDlftCq29cw927d9U1QTTAcgFLEOaWgJCCBQnuopgsOYQ4ExQShDiAkEAA465du1TvGWZ9WBvgNoDv3nRbuDEgHtDIIggRMQlo6AAadTRumPwJwZvo0WPEQVJAICR65Thmjx49pFChQiowEWD4JKwo6J1DAGASK5QPgscUDOFE+TA6whLaKA1DIYFGHCMlYOWA5QCxIXDr9OzZM0HXgPKj7IjngCCBJQLWCbiS+vbtq+IcYAnS6hv/h0hCmWB1wCgVuFhwrRiuCncJYktii9UgxFlIpePMKoQQQghJJLRIEEIIISTRUEgQQgghJNFQSBBCCCEk0VBIEEIIISTRUEgQQgghJNFQSBBCCCEk0VBIEEIIISTRUEgQQgghJNFQSBBCCCEk0VBIEEIIISTRUEgQQgghRBLL/wG78ODWO76RtQAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Macro-averaged One-vs-One ROC AUC score: 0.7761\n" + ] + } + ], + "source": [ + "# Создание всех пар классов\n", + "from itertools import combinations\n", + "\n", + "pair_list = list(combinations(label_binarizer.classes_, 2))\n", + "print(\"Пары классов для OvO:\")\n", + "for pair in pair_list:\n", + " print(f\" {pair[0]} vs {pair[1]}\")\n", + "\n", + "# Расчет OvO кривых\n", + "pair_scores = []\n", + "fpr_grid = np.linspace(0.0, 1.0, 1000)\n", + "mean_tpr_ovo = {}\n", + "\n", + "for ix, (label_a, label_b) in enumerate(pair_list):\n", + " # Маски для текущей пары\n", + " a_mask = y_test == label_a\n", + " b_mask = y_test == label_b\n", + " ab_mask = np.logical_or(a_mask, b_mask)\n", + " \n", + " # Истинные метки для пары\n", + " a_true = a_mask[ab_mask]\n", + " b_true = b_mask[ab_mask]\n", + " \n", + " # Индексы классов\n", + " idx_a = np.flatnonzero(label_binarizer.classes_ == label_a)[0]\n", + " idx_b = np.flatnonzero(label_binarizer.classes_ == label_b)[0]\n", + " \n", + " # ROC кривые\n", + " fpr_a, tpr_a, _ = roc_curve(a_true, y_score[ab_mask, idx_a])\n", + " fpr_b, tpr_b, _ = roc_curve(b_true, y_score[ab_mask, idx_b])\n", + " \n", + " # Усреднение TPR для пары\n", + " mean_tpr_ovo[ix] = np.zeros_like(fpr_grid)\n", + " mean_tpr_ovo[ix] += np.interp(fpr_grid, fpr_a, tpr_a)\n", + " mean_tpr_ovo[ix] += np.interp(fpr_grid, fpr_b, tpr_b)\n", + " mean_tpr_ovo[ix] /= 2\n", + " mean_score = auc(fpr_grid, mean_tpr_ovo[ix])\n", + " pair_scores.append(mean_score)\n", + " \n", + " # Визуализация для пары\n", + " fig, ax = plt.subplots(figsize=(6, 6))\n", + " plt.plot(\n", + " fpr_grid, mean_tpr_ovo[ix],\n", + " label=f\"Mean {label_a} vs {label_b} (AUC = {mean_score:.2f})\",\n", + " linestyle=\":\", linewidth=4,\n", + " )\n", + " RocCurveDisplay.from_predictions(\n", + " a_true, y_score[ab_mask, idx_a],\n", + " ax=ax, name=f\"{label_a} as positive class\",\n", + " )\n", + " RocCurveDisplay.from_predictions(\n", + " b_true, y_score[ab_mask, idx_b],\n", + " ax=ax, name=f\"{label_b} as positive class\",\n", + " plot_chance_level=True,\n", + " )\n", + " ax.set_title(f\"ROC-кривые: {label_a} vs {label_b}\")\n", + " ax.set_xlabel(\"False Positive Rate\")\n", + " ax.set_ylabel(\"True Positive Rate\")\n", + " plt.show()\n", + "\n", + "print(f\"\\nMacro-averaged One-vs-One ROC AUC score: {np.mean(pair_scores):.4f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "d381d526-7cc4-4259-a392-2abe0f8424c1", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "##### Интерпретация стратегии One-vs-One\n", + "\n", + "OvO анализ дает дополнительную информацию:\n", + "\n", + "| Пара классов | AUC | Интерпретация |\n", + "|--------------|-----|----------------|\n", + "| Setosa vs Versicolor | ~1.00 | Идеальное разделение |\n", + "| Setosa vs Virginica | ~0.90 | Очень хорошее разделение |\n", + "| **Versicolor vs Virginica** | **~0.64** | **Плохое разделение (основная проблема)** |\n", + "\n", + "**Вывод:** Модель отличает Setosa от других, но путает Versicolor и Virginica. Это соответствует известной особенности датасета Iris — эти два класса имеют перекрывающиеся признаки." + ] + }, + { + "cell_type": "markdown", + "id": "1501b21a-eea4-4ae2-ad25-6050eb02bb6b", + "metadata": {}, + "source": [ + "#### Итоговые выводы (Датасет Iris)\n", + "\n", + "##### Что мы узнали:\n", + "\n", + "1. **ROC-кривые и AUC** — эффективные инструменты для оценки многоклассовых классификаторов\n", + "2. **One-vs-Rest (OvR)** — показывает, как модель отличает каждый класс от всех остальных\n", + "3. **One-vs-One (OvO)** — выявляет проблемные пары классов\n", + "4. **Микро-усреднение (AUC = 0.77)** — характеризует общую производительность на всех образцах\n", + "5. **Макро-усреднение (AUC = 0.78)** — показывает среднюю производительность по классам\n", + "\n", + "##### Ключевое наблюдение:\n", + "Модель справляется с классом Setosa (AUC ≈ 1.0), но плохо различает Versicolor и Virginica (AUC ≈ 0.64 для пары)." + ] + }, + { + "cell_type": "markdown", + "id": "da77e871-0c60-4027-a832-89d72719cefc", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "### Работа с внешним датасетом openml.org" + ] + }, + { + "cell_type": "markdown", + "id": "da4454dc-ad21-4b5d-beac-52d1f88763c5", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Внешний датасет — Breast Cancer Wisconsin\n", + "\n", + "##### Источник данных\n", + "- **Название:** Wisconsin-breast-cancer-cytology-features\n", + "- **OpenML ID:** 43611 (оригинал: UCI)\n", + "- **Ссылка:** https://www.openml.org/d/43611\n", + "\n", + "##### Описание задачи\n", + "**Цель:** Классификация опухолей молочной железы на злокачественные (malignant) и доброкачественные (benign) на основе характеристик клеточных ядер.\n", + "\n", + "**Характеристики датасета:**\n", + "- 569 образцов\n", + "- 30 признаков (радиус, текстура, периметр, площадь, гладкость и др.)\n", + "- 2 класса: malignant (злокачественная) — 212 образцов, benign (доброкачественная) — 357 образцов" + ] + }, + { + "cell_type": "markdown", + "id": "ba17852d-0b95-413f-bca0-95fadb170786", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Импорт библиотек" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "667d3d9b-8d7d-4fc4-9a11-fa23e19be96d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Библиотеки импортированы\n" + ] + } + ], + "source": [ + "# ИМПОРТ БИБЛИОТЕК\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.datasets import fetch_openml\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.preprocessing import StandardScaler, LabelBinarizer\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.metrics import (\n", + " roc_auc_score, roc_curve, auc, \n", + " classification_report, confusion_matrix,\n", + " RocCurveDisplay\n", + ")\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "# Настройка графиков\n", + "plt.style.use('seaborn-v0_8-darkgrid')\n", + "np.random.seed(42)\n", + "\n", + "print(\"Библиотеки импортированы\")" + ] + }, + { + "cell_type": "markdown", + "id": "052f7a50-6e4b-40da-b67c-4a339be36a21", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Загрузка данных" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "74ffb3a6-3271-44b6-bc97-6e25ca7e4729", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "======================================================================\n", + "ЗАГРУЗКА ДАТАСЕТА BREAST CANCER (через URL)\n", + "======================================================================\n", + "\n", + " Датасет загружен!\n", + " Источник: https://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data\n", + " Размер X: (569, 30)\n", + " Размер y: 569\n", + " Количество признаков: 30\n", + " Количество образцов: 569\n", + "\n", + "Целевая переменная (диагноз):\n", + " Уникальные значения: ['B' 'M']\n", + " Распределение:\n", + " B (доброкачественная): 357 (62.7%)\n", + " M (злокачественная): 212 (37.3%)\n" + ] + } + ], + "source": [ + "# ЗАГРУЗКА ДАННЫХ\n", + "print(\"=\" * 70)\n", + "print(\"ЗАГРУЗКА ДАТАСЕТА BREAST CANCER (через URL)\")\n", + "print(\"=\" * 70)\n", + "\n", + "# Прямая ссылка на датасет Breast Cancer Wisconsin (UCI)\n", + "url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data\"\n", + "\n", + "# Названия столбцов\n", + "columns = [\n", + " 'id', 'diagnosis', \n", + " 'radius_mean', 'texture_mean', 'perimeter_mean', 'area_mean', 'smoothness_mean',\n", + " 'compactness_mean', 'concavity_mean', 'concave_points_mean', 'symmetry_mean', 'fractal_dimension_mean',\n", + " 'radius_se', 'texture_se', 'perimeter_se', 'area_se', 'smoothness_se',\n", + " 'compactness_se', 'concavity_se', 'concave_points_se', 'symmetry_se', 'fractal_dimension_se',\n", + " 'radius_worst', 'texture_worst', 'perimeter_worst', 'area_worst', 'smoothness_worst',\n", + " 'compactness_worst', 'concavity_worst', 'concave_points_worst', 'symmetry_worst', 'fractal_dimension_worst'\n", + "]\n", + "\n", + "# Загрузка данных\n", + "df = pd.read_csv(url, header=None, names=columns)\n", + "\n", + "# Разделение на признаки и целевую переменную\n", + "X = df.drop(['id', 'diagnosis'], axis=1)\n", + "y_raw = df['diagnosis'] # 'M' = malignant, 'B' = benign\n", + "\n", + "print(f\"\\n Датасет загружен!\")\n", + "print(f\" Источник: {url}\")\n", + "print(f\" Размер X: {X.shape}\")\n", + "print(f\" Размер y: {len(y_raw)}\")\n", + "print(f\" Количество признаков: {X.shape[1]}\")\n", + "print(f\" Количество образцов: {X.shape[0]}\")\n", + "\n", + "print(f\"\\nЦелевая переменная (диагноз):\")\n", + "print(f\" Уникальные значения: {np.unique(y_raw)}\")\n", + "print(f\" Распределение:\")\n", + "for diagnosis in np.unique(y_raw):\n", + " count = np.sum(y_raw == diagnosis)\n", + " print(f\" {diagnosis} ({'злокачественная' if diagnosis == 'M' else 'доброкачественная'}): {count} ({count/len(y_raw)*100:.1f}%)\")" + ] + }, + { + "cell_type": "markdown", + "id": "ef476200-644d-42ea-b0a4-2831c7fa933e", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Первичный анализ данных" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "fb16e6fa-523b-4324-bc97-a7b358de8dc7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "======================================================================\n", + "ИССЛЕДОВАНИЕ ДАННЫХ\n", + "======================================================================\n", + "\n", + "Первые 5 строк данных:\n", + " radius_mean texture_mean perimeter_mean area_mean smoothness_mean \\\n", + "0 17.99 10.38 122.80 1001.0 0.11840 \n", + "1 20.57 17.77 132.90 1326.0 0.08474 \n", + "2 19.69 21.25 130.00 1203.0 0.10960 \n", + "3 11.42 20.38 77.58 386.1 0.14250 \n", + "4 20.29 14.34 135.10 1297.0 0.10030 \n", + "\n", + " compactness_mean concavity_mean concave_points_mean symmetry_mean \\\n", + "0 0.27760 0.3001 0.14710 0.2419 \n", + "1 0.07864 0.0869 0.07017 0.1812 \n", + "2 0.15990 0.1974 0.12790 0.2069 \n", + "3 0.28390 0.2414 0.10520 0.2597 \n", + "4 0.13280 0.1980 0.10430 0.1809 \n", + "\n", + " fractal_dimension_mean ... radius_worst texture_worst perimeter_worst \\\n", + "0 0.07871 ... 25.38 17.33 184.60 \n", + "1 0.05667 ... 24.99 23.41 158.80 \n", + "2 0.05999 ... 23.57 25.53 152.50 \n", + "3 0.09744 ... 14.91 26.50 98.87 \n", + "4 0.05883 ... 22.54 16.67 152.20 \n", + "\n", + " area_worst smoothness_worst compactness_worst concavity_worst \\\n", + "0 2019.0 0.1622 0.6656 0.7119 \n", + "1 1956.0 0.1238 0.1866 0.2416 \n", + "2 1709.0 0.1444 0.4245 0.4504 \n", + "3 567.7 0.2098 0.8663 0.6869 \n", + "4 1575.0 0.1374 0.2050 0.4000 \n", + "\n", + " concave_points_worst symmetry_worst fractal_dimension_worst \n", + "0 0.2654 0.4601 0.11890 \n", + "1 0.1860 0.2750 0.08902 \n", + "2 0.2430 0.3613 0.08758 \n", + "3 0.2575 0.6638 0.17300 \n", + "4 0.1625 0.2364 0.07678 \n", + "\n", + "[5 rows x 30 columns]\n", + "\n", + "Типы данных:\n", + "float64 30\n", + "Name: count, dtype: int64\n", + "\n", + "Статистика по первым 5 признакам:\n", + " radius_mean texture_mean perimeter_mean area_mean smoothness_mean\n", + "count 569.000000 569.000000 569.000000 569.000000 569.000000\n", + "mean 14.127292 19.289649 91.969033 654.889104 0.096360\n", + "std 3.524049 4.301036 24.298981 351.914129 0.014064\n", + "min 6.981000 9.710000 43.790000 143.500000 0.052630\n", + "25% 11.700000 16.170000 75.170000 420.300000 0.086370\n", + "50% 13.370000 18.840000 86.240000 551.100000 0.095870\n", + "75% 15.780000 21.800000 104.100000 782.700000 0.105300\n", + "max 28.110000 39.280000 188.500000 2501.000000 0.163400\n", + "\n", + "Целевая переменная:\n", + " Уникальные значения: ['B' 'M']\n", + " Распределение:\n", + " B: 357 образцов (62.7%)\n", + " M: 212 образцов (37.3%)\n" + ] + } + ], + "source": [ + "# ПЕРВИЧНЫЙ АНАЛИЗ ДАННЫХ\n", + "print(\"=\" * 70)\n", + "print(\"ИССЛЕДОВАНИЕ ДАННЫХ\")\n", + "print(\"=\" * 70)\n", + "\n", + "# Первые строки данных\n", + "print(\"\\nПервые 5 строк данных:\")\n", + "print(X.head())\n", + "\n", + "# Типы данных\n", + "print(\"\\nТипы данных:\")\n", + "print(X.dtypes.value_counts())\n", + "\n", + "# Статистика по первым 5 признакам\n", + "print(\"\\nСтатистика по первым 5 признакам:\")\n", + "print(X.iloc[:, :5].describe())\n", + "\n", + "# Анализ целевой переменной\n", + "print(\"\\nЦелевая переменная:\")\n", + "print(f\" Уникальные значения: {np.unique(y_raw)}\")\n", + "print(f\" Распределение:\")\n", + "for class_name in np.unique(y_raw):\n", + " count = np.sum(y_raw == class_name)\n", + " print(f\" {class_name}: {count} образцов ({count/len(y_raw)*100:.1f}%)\")" + ] + }, + { + "cell_type": "markdown", + "id": "ad2cc9e3-79bc-4702-bf2e-ca0bab2e403b", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Визуализация распределения классов" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "a1c9099c-834e-432f-9591-105bbb3de840", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# ВИЗУАЛИЗАЦИЯ РАСПРЕДЕЛЕНИЯ КЛАССОВ\n", + "plt.figure(figsize=(8, 5))\n", + "colors = ['green', 'red']\n", + "class_counts = y_raw.value_counts()\n", + "bars = plt.bar(class_counts.index, class_counts.values, color=colors, edgecolor='black')\n", + "plt.title('Распределение классов в датасете Breast Cancer', fontsize=14)\n", + "plt.xlabel('Диагноз', fontsize=12)\n", + "plt.ylabel('Количество образцов', fontsize=12)\n", + "\n", + "# Добавление подписей на столбцы\n", + "for bar, count in zip(bars, class_counts.values):\n", + " plt.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 5, \n", + " f'{count} ({count/len(y_raw)*100:.1f}%)', \n", + " ha='center', fontsize=11)\n", + "\n", + "plt.xticks(rotation=0)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "1db3c1dd-436d-43db-b67b-daf060b0a2d3", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Визуализация признаков" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "5034d014-8418-4648-8b0a-b8fdfe97c727", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# ВИЗУАЛИЗАЦИЯ РАСПРЕДЕЛЕНИЯ ПРИЗНАКОВ\n", + "plt.figure(figsize=(12, 5))\n", + "\n", + "# Признак 1: clump_thickness\n", + "plt.subplot(1, 2, 1)\n", + "for class_name, color in zip(np.unique(y_raw), colors):\n", + " subset = X[y_raw == class_name]\n", + " plt.hist(subset.iloc[:, 0], bins=15, alpha=0.7, color=color, \n", + " label=f'{class_name}', edgecolor='black')\n", + "plt.title(f'Распределение: {X.columns[0]}', fontsize=12)\n", + "plt.xlabel('Значение')\n", + "plt.ylabel('Частота')\n", + "plt.legend()\n", + "\n", + "# Признак 2: uniformity_cell_size\n", + "plt.subplot(1, 2, 2)\n", + "for class_name, color in zip(np.unique(y_raw), colors):\n", + " subset = X[y_raw == class_name]\n", + " plt.hist(subset.iloc[:, 1], bins=15, alpha=0.7, color=color,\n", + " label=f'{class_name}', edgecolor='black')\n", + "plt.title(f'Распределение: {X.columns[1]}', fontsize=12)\n", + "plt.xlabel('Значение')\n", + "plt.ylabel('Частота')\n", + "plt.legend()\n", + "\n", + "plt.suptitle('Распределение ключевых признаков по классам', fontsize=14)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "52fd06e0-af94-4705-bdfc-28cc4d9095d8", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Предобработка данных" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "4eeed08b-312b-4cc6-88e3-645b5e05f00d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "======================================================================\n", + "ПРЕДОБРАБОТКА ДАННЫХ\n", + "======================================================================\n", + "Преобразование меток:\n", + " benign (доброкачественная) -> 0\n", + " malignant (злокачественная) -> 1\n", + " Распределение после преобразования: [569]\n", + "\n", + "Масштабирование выполнено:\n", + " Среднее после масштабирования: -0.00000000\n", + " Стандартное отклонение: 1.00000000\n" + ] + } + ], + "source": [ + "# ПРЕДОБРАБОТКА ДАННЫХ\n", + "print(\"=\" * 70)\n", + "print(\"ПРЕДОБРАБОТКА ДАННЫХ\")\n", + "print(\"=\" * 70)\n", + "\n", + "# Преобразование целевой переменной в числовой формат\n", + "# 'benign' -> 0, 'malignant' -> 1 (для ROC анализа)\n", + "y_numeric = (y_raw == 'malignant').astype(int)\n", + "y_str = y_raw # сохраняем строки для совместимости\n", + "\n", + "print(\"Преобразование меток:\")\n", + "print(f\" benign (доброкачественная) -> 0\")\n", + "print(f\" malignant (злокачественная) -> 1\")\n", + "print(f\" Распределение после преобразования: {np.bincount(y_numeric)}\")\n", + "\n", + "# Стандартизация признаков\n", + "scaler = StandardScaler()\n", + "X_scaled = scaler.fit_transform(X)\n", + "\n", + "print(f\"\\nМасштабирование выполнено:\")\n", + "print(f\" Среднее после масштабирования: {X_scaled.mean():.8f}\")\n", + "print(f\" Стандартное отклонение: {X_scaled.std():.8f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "0c6e09a2-e590-4bdf-8f1a-ebe750894a10", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Разделение на train/test" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "61deb698-6d39-4835-8d91-0087922d9a5f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Размер выборок:\n", + " Обучающая: 398 образцов\n", + " Тестовая: 171 образцов\n", + "\n", + "Распределение классов в выборках:\n", + " Обучающая:\n", + " B: 250 (62.8%)\n", + " M: 148 (37.2%)\n", + " Тестовая:\n", + " B: 107 (62.6%)\n", + " M: 64 (37.4%)\n" + ] + } + ], + "source": [ + "# РАЗДЕЛЕНИЕ НА ОБУЧАЮЩУЮ И ТЕСТОВУЮ ВЫБОРКИ\n", + "X_train, X_test, y_train, y_test = train_test_split(\n", + " X_scaled, y_str, # используем строковые метки\n", + " test_size=0.3, # 30% в тестовую выборку\n", + " random_state=42, # фиксация случайности\n", + " stratify=y_str # сохранение пропорций классов\n", + ")\n", + "\n", + "print(f\"Размер выборок:\")\n", + "print(f\" Обучающая: {X_train.shape[0]} образцов\")\n", + "print(f\" Тестовая: {X_test.shape[0]} образцов\")\n", + "\n", + "# Проверка распределения в выборках\n", + "print(f\"\\nРаспределение классов в выборках:\")\n", + "print(f\" Обучающая:\")\n", + "for class_name in np.unique(y_train):\n", + " count = np.sum(y_train == class_name)\n", + " print(f\" {class_name}: {count} ({count/len(y_train)*100:.1f}%)\")\n", + "print(f\" Тестовая:\")\n", + "for class_name in np.unique(y_test):\n", + " count = np.sum(y_test == class_name)\n", + " print(f\" {class_name}: {count} ({count/len(y_test)*100:.1f}%)\")" + ] + }, + { + "cell_type": "markdown", + "id": "2d5ae399-3236-493d-b0c8-806930af1f2d", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Обучение модели" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "9742fe9e-b21b-4f94-9d44-5a827d068a97", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "======================================================================\n", + "ОБУЧЕНИЕ МОДЕЛИ\n", + "======================================================================\n", + "Модель обучена\n", + " Количество итераций: 19\n", + " Коэффициенты модели (первые 5): [0.2996 0.5055 0.3002 0.4126 0.3856]\n", + " Intercept: -0.4677\n", + "======================================================================\n", + "ОЦЕНКА КАЧЕСТВА МОДЕЛИ\n", + "======================================================================\n", + "Accuracy (точность): 0.9708 (97.08%)\n", + "\n", + "Classification Report:\n", + " precision recall f1-score support\n", + "\n", + " benign (0) 0.96 0.99 0.98 107\n", + "malignant (1) 0.98 0.94 0.96 64\n", + "\n", + " accuracy 0.97 171\n", + " macro avg 0.97 0.96 0.97 171\n", + " weighted avg 0.97 0.97 0.97 171\n", + "\n", + "\n", + "Confusion Matrix:\n", + " Предсказано\n", + " benign malignant\n", + " benign 106 1\n", + " malignant 4 60\n" + ] + } + ], + "source": [ + "# ОБУЧЕНИЕ МОДЕЛИ ЛОГИСТИЧЕСКОЙ РЕГРЕССИИ\n", + "print(\"=\" * 70)\n", + "print(\"ОБУЧЕНИЕ МОДЕЛИ\")\n", + "print(\"=\" * 70)\n", + "\n", + "# Создание и обучение классификатора\n", + "classifier = LogisticRegression(\n", + " max_iter=1000, # достаточно для сходимости\n", + " random_state=42,\n", + " C=1.0 # параметр регуляризации\n", + ")\n", + "\n", + "classifier.fit(X_train, y_train)\n", + "\n", + "# Получение вероятностей для тестовой выборки\n", + "# (берем вероятность второго класса - malignant)\n", + "y_score = classifier.predict_proba(X_test)[:, 1]\n", + "y_pred = classifier.predict(X_test)\n", + "\n", + "print(f\"Модель обучена\")\n", + "print(f\" Количество итераций: {classifier.n_iter_[0]}\")\n", + "print(f\" Коэффициенты модели (первые 5): {classifier.coef_[0][:5].round(4)}\")\n", + "print(f\" Intercept: {classifier.intercept_[0]:.4f}\")\n", + "# ОЦЕНКА КАЧЕСТВА МОДЕЛИ\n", + "print(\"=\" * 70)\n", + "print(\"ОЦЕНКА КАЧЕСТВА МОДЕЛИ\")\n", + "print(\"=\" * 70)\n", + "\n", + "# Точность\n", + "accuracy = classifier.score(X_test, y_test)\n", + "print(f\"Accuracy (точность): {accuracy:.4f} ({accuracy*100:.2f}%)\")\n", + "\n", + "# Подробный отчет\n", + "print(\"\\nClassification Report:\")\n", + "print(classification_report(y_test, y_pred, \n", + " target_names=['benign (0)', 'malignant (1)']))\n", + "\n", + "# Матрица ошибок\n", + "cm = confusion_matrix(y_test, y_pred)\n", + "print(\"\\nConfusion Matrix:\")\n", + "print(\" Предсказано\")\n", + "print(\" benign malignant\")\n", + "print(f\" benign {cm[0,0]:3d} {cm[0,1]:3d}\")\n", + "print(f\" malignant {cm[1,0]:3d} {cm[1,1]:3d}\")" + ] + }, + { + "cell_type": "markdown", + "id": "49e244f2-96d7-467d-8fd4-c8dd280eb2f3", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### ROC-анализ" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "19df41bb-2f00-444f-88f1-cf301c94b6ad", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "======================================================================\n", + "ROC-АНАЛИЗ\n", + "======================================================================\n", + "Уникальные классы в y_test: ['B' 'M']\n", + "Количество классов: 2\n", + "Форма после бинаризации: (171, 1)\n", + "Взяли первый столбец (единственный класс)\n", + "\n", + "ROC AUC Score: 0.9975 (99.75%)\n", + "\n", + "Интерпретация AUC:\n", + " Отличное качество (AUC >= 0.9)\n", + "\n", + "Оптимальный порог (критерий Юдена): 0.2352\n", + " TPR (Чувствительность) при этом пороге: 0.9844\n", + " FPR (1 - Специфичность) при этом пороге: 0.0187\n" + ] + } + ], + "source": [ + "# ROC-АНАЛИЗ\n", + "print(\"=\" * 70)\n", + "print(\"ROC-АНАЛИЗ\")\n", + "print(\"=\" * 70)\n", + "unique_classes = np.unique(y_test)\n", + "print(f\"Уникальные классы в y_test: {unique_classes}\")\n", + "print(f\"Количество классов: {len(unique_classes)}\")\n", + "\n", + "# Бинаризация для ROC\n", + "label_binarizer = LabelBinarizer().fit(y_train)\n", + "y_test_binarized = label_binarizer.transform(y_test)\n", + "\n", + "print(f\"Форма после бинаризации: {y_test_binarized.shape}\")\n", + "\n", + "# Проверка: если классов 2, берем второй столбец (индекс 1)\n", + "# Если класс 1, берем первый столбец (индекс 0)\n", + "if y_test_binarized.shape[1] == 2:\n", + " y_test_binary = y_test_binarized[:, 1] # берем класс malignant (второй)\n", + " print(\"Взяли второй столбец (malignant)\")\n", + "elif y_test_binarized.shape[1] == 1:\n", + " y_test_binary = y_test_binarized[:, 0] # берем единственный класс\n", + " print(\"Взяли первый столбец (единственный класс)\")\n", + "else:\n", + " y_test_binary = y_test_binarized[:, 1] # по умолчанию\n", + "\n", + "# Расчет ROC кривой и AUC\n", + "fpr, tpr, thresholds = roc_curve(y_test_binary, y_score)\n", + "roc_auc = auc(fpr, tpr)\n", + "\n", + "print(f\"\\nROC AUC Score: {roc_auc:.4f} ({roc_auc*100:.2f}%)\")\n", + "print(f\"\\nИнтерпретация AUC:\")\n", + "if roc_auc >= 0.9:\n", + " print(\" Отличное качество (AUC >= 0.9)\")\n", + "elif roc_auc >= 0.8:\n", + " print(\" Хорошее качество (0.8 <= AUC < 0.9)\")\n", + "elif roc_auc >= 0.7:\n", + " print(\" Удовлетворительное качество (0.7 <= AUC < 0.8)\")\n", + "else:\n", + " print(\" Низкое качество (AUC < 0.7)\")\n", + "\n", + "# Нахождение оптимального порога (критерий Юдена)\n", + "optimal_idx = np.argmax(tpr - fpr)\n", + "optimal_threshold = thresholds[optimal_idx]\n", + "print(f\"\\nОптимальный порог (критерий Юдена): {optimal_threshold:.4f}\")\n", + "print(f\" TPR (Чувствительность) при этом пороге: {tpr[optimal_idx]:.4f}\")\n", + "print(f\" FPR (1 - Специфичность) при этом пороге: {fpr[optimal_idx]:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "1402e9e8-3b03-4367-8ca2-e44912b57738", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Визуализация ROC-кривой" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "739753ff-ca56-4597-b3b6-30e80163cdd8", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxYAAAKyCAYAAABIREjrAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjksIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvJkbTWQAAAAlwSFlzAAAPYQAAD2EBqD+naQAAzG5JREFUeJzs3QV0VEcXB/B/PIEgIQR3d6dAseKUAsWKu0uQEtxdExyKuxUtxd0KFCtapLhLsBBIQvQ7d/h22ShR1v6/c3KS93azO/v2ZTP3zb0zFiEhISEgIiIiIiKKA8u4/DIREREREREDCyIiIiIiihccsSAiIiIiojhjYEFERERERHHGwIKIiIiIiOKMgQUREREREcUZAwsiIiIiIoozBhZERERERBRnDCyIiIiIiCjOrOP+EEQUHbNnz8acOXMivC1x4sRIkyYNKlasiB49esDR0THC+/3999/4/fff8c8//+DNmzdIliwZsmbNirp166ovOzu7SJ//+vXr6nflMZ4/fw4LCwvkyJEDtWvXRrNmzWBra8s3kkzS9OnTMX/+fKxcuRKlSpXSd3OIiEwWAwuib6xJkyYoXrx4qH0vXrzA3r17sXTpUly6dAmrVq2ClZWV9nZ/f3+MHDkSW7ZsQYYMGfDzzz8jY8aMePv2Lf766y8MGzZMdZokcMmcOXO455w7d676SpEihQpAMmXKBG9vbxw+fBgTJkxQz71o0SIV4BARERHFBgMLom+sSJEiKjAIq2PHjmjbti1Onz6tOvxVq1bV3jZ27FgVVLRs2RKDBg2CjY2N9rbOnTvjwIED6NevH9q1a4dt27YhSZIk2tvXrFmDWbNmoUqVKurKre6oRqdOnTBjxgz89ttvGDJkCGbOnJmgr52IiIhMF2ssiAyEpaUlGjdurH4+d+6cdr+MYGzYsAHly5fH8OHDQwUVGhKE9O/fH0+ePFGBgsb79+8xZcoUpEqVKlxQodG7d2+VTnXw4EH1+0RERESxwcCCyIAkSpQo3D4JKkSHDh2i/N2mTZvCyckJ27dvV6lTQlKc/Pz8VPpVZPUXUmshaVBSe5E+ffqvtrFy5cqoUKGCdvv+/fto2LAh8uXLhytXrqiRldy5c+P48eMYPXq0ymkvVqwYWrVqpZ5Dl4y+yH0fPHgQar+khMl++R0N+Vn2ab7k+UqXLo3u3bvj0aNHoX7/33//Rd++fVU7CxQooJ5fjs+uXbtC3S8gIEC99h9//BEFCxYM9fjytXHjxq8eD3n9YX9P86V7nITm2ET2JcdD4+PHj3B3d0e1atXUawh735MnT0bZLs3xCgwMVNtSk9OmTRv1WHv27FH7Hj9+HGV75L2OzXEVDx8+VK9HAuLChQurYyx1DppzU+PUqVNqtE7OE0kRlOBa9/FkBE/aIoGxrqdPn6Jo0aLqNnkdGvI6JcguWbKkat/gwYPh4+OjbVOXLl1Ue77//nuMGzdOe1tMn0vzXuqeI/PmzVOvoWvXrqHOj6FDh6pjKcdMRizr1aunRhLD1mBF9L7K30bYcyOi5xaXL19G3rx51W1fe1z5bIjoPQ5Lc0zkOWVEs1y5cuo1NGrUSD1GWNF9vWH/9uVzqlevXihUqJD6+9c9P7p166ber/z586v3Vc7jr53/uq897JeM6kb3c0rOH7mfHNuwNJ9T0kZx4sSJSP+WpI4tNu8fkbFhKhSRAZFRAyH/kDVk9ELqLeSfXlTkPmXKlFGdshs3bqh/0DLaIcLWdIQl9RqxNWLECHh5eal/zvI4t27dUvulJkQTEAUHB2P16tVo3769qgOJqjPz7Nkz1SGIzOTJk1UwJB0Rea61a9fi7t272L17t9p/8eJFlTKWLl069V2CLekMrl+/Hr/++qtKE5POrpDRncWLF6NSpUpo3bq1NrA7f/68KnSPDl9fX/VdOlNSTK8xceLESH9HOmXfffeddvv169fqdemSx5PXJGlzkrKmCQz379+vvmJq6tSp6ryQehw5N3RJp1m34yPGjx8fajsmx/W///5TjyfvuwQeUvdz9uxZ1WGXNmhG1bZu3ao6bvKY0lmU4/fnn3+qx3v37h2aN28e6euR9EDdoEBI0CLnmDx/ixYtVKC8efNm3LlzR90+atQo1cYBAwbgwoULqpZJgtIFCxZEeewieq6w5PVJx1s6ppo0Rnlsea/t7e3VcUidOjVevnyJTZs2YcyYMepvVvbHh6CgIPU3J8f8az58+BDu/f0a+buVYFfee6nFkgseEgjI378c67i+Xvk7PHTokErp1JxHErjIiKpcRJCUT3le+ZuXDrn8Tfzxxx/ImTPnV9suvysTVWjIZ6m8X9H5nJKLJhIISDAS9u9Gzl85x+QCh+azQEaeJ02aFOp+cr7F5/tHZMgYWBB9Y9JBkauqGvKPxNPTU400SCdIrsrJ1V0N+ccsHa6oZnzSkJmlNMXgmt8VkgqVEORqpnxJh7FWrVrhOnnymqQDKuSqpbwu6aT98MMP6h9wROR2mRUrso6czGJlbf3lo0s6t1KTIsfU2dlZdVAkwJBOo3RsdDsT0sGQ+2o6LtJZSJs2rSps1y2Wl3/yMQ0spF1SHK8hnUzNaMHX6mzkqq1uYCGPKZ0q6fBLKpsuueoe08BCHl867NJJi6hjp5kQQJeHh0eo7ZgcV+m0fvr0SXUo8+TJo/bJ88rMY9JJkyv6MoGAvNcSdMh5r5kJ7ZdfflHninTsNKmBYUlNkXRC5bzWnONCHkdmP5MRCxkFEfK6JHCUYyojFVJPJK9DOsMSSMr7LBMgyJX4mDxXWFLHJJ1XCQjl8YV0UmWShOXLl4e6WFCjRg389NNP6pjFV2Ah78vNmzeRMmVKvHr1Ksr7yrkpwUVMJmuQ4FfOIc3kEPLe1KlTR42qyYQQEljG9vVKyuaKFStUJ17qzDRkhEtejzyu7miutEEClWPHjkUrsJALLjLioUsTWHztc6pEiRLIkiULdu7cGaq+7dq1ayqAdXV11b7fco5JUBX2byk6gUVM3j8iQ8ZUKKJvTP5hyT86zVfZsmXVP7N169apTtWSJUtCdXJDQkJCdaSjovk9+R3d7fi+CiaPJ1cOJZUkV65cqFmzZrj7yAiA5p+1JuiRf7iSVnL16tVIO3EyaiNX1SMjV7IliJBOnnT45Mqz1Ihonks6eEeOHAnV+ZUOvuYYSIdKd78EbLrHO6Zk6t7I0thiS9oqX/HxmBJUyJVQOT5RjQB8TXSPq8xUdubMGdVR1wQVGnI1Wjqn2bJlU2kjcgVc0vR0p1eW4EM6//L3ENH7Ir8j552MCoSdOlbOHyGPqSGvW/7GNMGfphMoNJ1czUhhTJ4rbKdYXnPPnj1DPb50ROV16nay5XhpAk7dczEu5EKCBAsymiABW1QknU3SkiTIjGxa64jI367ujHPyu3I+yQUASSeK7euVvx8JEiQtUQJUXTIyIeeL7t+BBAKaixLxcfyi8zklAY+c1xLI6I5WyHstn926ryU2f7Mxef+IDB1HLIi+MRlyl06XdP5lpEJzpUo6JTIEH5b8o5OiavnHG1HhdkSdXM3IhaYTKM8TnSt7GnL/sGTURLPWhdwunTR5fOkARjT6IAFHWNKh1Fx1D5tWIB0UudIts1fJV2Q0nUQNeW5J89G0Qb5LapbkP8txlWMnKRqazo1ukCUBkbRfRgvq16+vRjyks/C1tJewHffkyZOrK5XxRa4kSx2DdNhkpEBSMuQ5dEdIoktGkqQTKNMRx6QjGVZ0j6vsl58l2AtLjq98CU1djOac0BXRlMkakiYn7ZDgM+yoioxeyXHSnRVNyKiUkJSrsCM1um2JyXNpaEaUpA4gbIAt55IcHxl9kU6qHBs592U0Jz4Dfgl+kiZNqlKTJEUoMvJ8EmRKwCedWLmIEV0R5f1r3jvN8YvN65WOvXyuyahh2BovuaAiHXypXZF0Nnk8eY81jxMfxy86n1MSPEj6noxwymeTfBbv2LFDpTPqppHKZ4Fu4B3f7x+RMWBgQfSNSbqE7rC8dPzkSp10bqXDPnDgwFD3lyulkscui+JFtbiXpO/I8L4EAJorxfKPTzrOUqcRNhVAl+RLS3qNBDYyihJRWoju4mJyhU8CIUmDkKuU0kEJu8BeRAvuSRtFRCMw0omT0QiZ+Soq8lzSyZXHkkBKOiRubm7qH70m0JF6D0kpkPZqim7lNsn/1iVtlwBPXr9uwWhMSOpNQlxllA6rXMmV4yKBU2xJsCadIjmvJKVEE6DEVHSPqybQ0L1yH5Ho3k+X1GfIeSipJZpgQZecFxE9niYgD3tORjVS9bXn0pCUKunsSgAonVDd+iEZCenTp48KOuXvSkY+JMCXmqewhf2xJaNI+/btU535rwWOUo8kIxZyvsd0lC46f8+xeb1SYyOfbxK8Sft0O+oSzC1cuFAFgJKSJI+pmZBAJm2ID9F5XZIGJ+2XVC4ZoZLPWRk1bdCgQZw/C2Ly/hEZAwYWRHom/9ik4yfD79K5lRoLGQ3QkPQoyQOXfGMJFCLriMnQvHS0pXhU889S/hnK1VvJPZcrYQ4ODhH+E5XUCOlIyarfYtmyZeHup5vWIo8vHSrppMosQTKML3ntuu7duxcumJEiaxH2arZcAZdOnDyGdOIiq00QUiipG5hIKpP8nsx0JKkt0iGXzokcD91/1FKQHZZ0gKSDImld0imQK4YS+MksL9G5mitXLiX1I7JagLiQ4E3ej9u3b6uca+mwyRVdSQ2RK6fRJVdb5QqsvF9SvKw7HbHG1zr3csU5usdVMwog739Ycpzl6rMEIrr3kxXndUk+u4zWSPCqS662h50tTJe0T84x6fzJFWANTc1R2JE4TRsj6gx+7bk0ZBYfCVAlXUaCN2m7pqZJinjlb0V3n2574kpGryT4lGBGZg+LiqQOynsv54HMgBZTEb2fYf+eY/N6pf5F2i91GpIqJ0GGnI8yUiEztkkNj6Sa6QYA8jcQX6L7OSXvrwQWkn4pM1LJqKLUjmjIuSVBm4x8JsT7R2QsWGNBZACkg66Z7UiuCmtSmoTkK8vCd/LPTG6TzmxYR48eVVempeMpudMa0gGUzrI8nlx51aQkaEgqgcxeJEGF/HOTomIh/2jDfunOeKQhBZnS0Zd//Jp/xhqS4iUzN2nIVV3pEEjqQdi0CmmD7P9aJy4imnoSzUxRksYkKS+6nV8JVDQjEpqrkZp8bUlhkdEgGX2R4ywFyLozyERFghnJ844qdUuX5rm/ltImZPRGCpBl+k6ZtUjqBmQkKTYzeEnnTDo8MsuUZmpM3fZ8rYYnJsdVRjRkNEMKojWzMWnIiInMWibBrqS0ST66XD3XTT2T90Rer9RLuLi4aPfLuSPTcWpmF4qskyp0p/GUOglNDYB0DHVppkAN26mLznPpkk6vzI4kAY2cRxqSly8F/bqvQ0iHWfeYxZZcAJDn+Noon5DgX463BKixIRcndCedkNcq76duDUtsX68EdnLhQ2Yek+cRkoImf9vSudcNKqQzLp8tUT1eTET3c0oKuSWNT/7m5fNWRpp1L9RIu+UzSO6XEO8fkbHgiAWRgZAOunSs5cq9rIItV8w1V5LlSp4EATLbilwhlw69XPGVTq104KTjJP8IpfMQNr9ccqnln6V0/qUDJVcG5R+5XMGUIXgZLZDZcqKaHjUq0lbptMrvazoQQq44ymiLXOmTdkonTl6PdNbCksBH2h6dTpykPGlyueU55AqndDykcyPBj8xzL/PQy9VjSZ+QDrrM+iKBj6TKSIdIQzqBcpVRpjqNbnCgIR1fmQ1LgkLJ/Q67uKB0luU9k/vJ8ZX3TXOlNTp52JIaIlPvyvENW48SGzKyJJ2iCRMmqGk65ThqRhu+1p6YHlfpZMt5JyM5coVcAhIpbpYr2XJOaF6PvDbpVMn5I+eJdHzlGMk5Kelfuh1Kea/l7yOqq+3yGDITlfyu5MdLGo6M7mjappmSWF6L/N1I6o5cdZYUG13Rea6w5DGlxkLaL69Z3nM5p+RYS/CqmZlK/uYkkJXXpnvMNCTw0x1ZkdmYNHUMcg7p1hhJO2W0JGztSETkvpJWF9t0G2m7jDTJqKAcQxlFlU6x7sKbsXm9urVn0jmXx5PjKMG91NrI48l5IZ18+cySETPN8Ynq8aIrup9TcjFAM6osdNOgpI3y2SezR8nfVESjoxKUxeX9IzIWDCyIDIgEENLhkX9A8g9OOmdCOtySiyxXySQPWa76SmdcgghJc5GZpuSfXkRT0kqnTzpw8o9eOuEyjan8g5b9EoxIJ1Cuhkd35qmw5B++dCAlB1+u5Om+Fkl9kdxh+UctaVwyehJREajMLhPdzrNuDYp06qXzKB2Z7Nmzq32S7iG52XIc5TjJ1VMZ9ZFUHkkFkk6OXMWWuhMJ4uQYSFtjSjrommAiqukk5X4ymiQdCLnCKR0Y3TUsIiLHUmpeZIRCilvjg4wkyHGSYErOAzln5D2XIEGzDkFUontcJUVE1h2QUQN572VEQjqYEsxqzjUN6dBJUCOdMpkJSs5zSbmTegXN1LUaklrztavt0nmVq8ASWEgQIYGP5PlLO+XvRoIYCa6kzdLBlqvkck6GFZ3nioicB5IzL++3dLzl9co5Kp1r+ZuWq/lyvsl5J7dLoCUBg+4olNQURETOV0mH1O2YShpWdM8P+fuvXr06YkuCb/k7lo61jCpJ4CSpT3L+aMTm9eqmJcrfoaxhIulycizlPJDzVc43OZ/kfZHnkxRBOWflOWRUIyZ1OmHF5HNKAit5/RJA6K4rpPlMksAkss8CGXmMy/tHZDRCiIji0ebNm0Ny5coVsmHDBpM+rpUqVQqZNWtWlPeR2+V+pF/Tpk1T5+Tff/9ttG/FwIEDQ1q2bPnNn1eOmRw7OYbm/jl1+/Zt9TsLFy4MtV/2yeMZ4vtH9K2xxoKIiIjoKyQVVUaFZdSRiCLGVCgioliQFJuI0iV0ye1yP6K4koL4qNb3oIQh6X2ShippTpJ6JVNyS4qXLlmB/GvTzPL9I3PBwIKIKBakbuVrJKc9LnntRBq6tSn07UjNkEwmIHVpMlIhNSBh6c4EFhm+f2QuLCQfSt+NICIiIiIi48YaCyIiIiIiijMGFkREREREFGcMLIiIjJDUbkhxeGT53bIYmty+ZcuWSB9DbpP7yH0jWztB5uWXhRVlnRFZQ0DWVpHfk8X/viVZNVsWZ5P1A0qVKqXWH9Bdof5rDh06pPLcZf0FWUle1qmQ9QvCktWcZXFKWaRNFsiTFeknT56sFgQMSwp6ZZ0SWSNC1sqoUKGCWh/E29s7zq+XiMgYMbAgIjIysor1gwcP1IrE0smXBcviU0BAAEaPHq0WIbtw4YJamFFWAu/YsSO8vLzULDnSMZfVz78FWehOFveTdvXu3VsFN5pAQbMy9dcWHJTfl8XZZFE8eR1SkCu/L8GTrv79+6sF9GQxQzc3N7XwpCzOJkGN7nPJa2/Xrp1a0b5IkSIYOnSoCixkIT5ZtfvTp08JciyIiAzaN185g4iI4mTAgAEhefPmDZk9e7ZanGvHjh0RLs73tYW7NIuEhV3ob/LkyWr/qFGjQgIDA0PdFhwcrJ5fbpf7JbSPHz+GlCpVKqROnTohfn5+2v1nz55VbRg5cmSUv//69euQQoUKhZQsWTLk6dOn2v0fPnwIqVKlSkj16tVD/P391b5Dhw6px2zatGnIp0+ftPe9fv16SL58+dQiZxq7d+9W9x06dGiEx33dunXx8vqJiIwJRyyIiIyIpN/s3btXpenI1XSxfv36eHv8u3fvYunSpcifPz9GjhwJKyurULdbWFio/cmSJcOmTZvUPP8J6ciRI3j79i2aNWumFifTkLQsWRtARjOiGrE5duwY/Pz81ChC2rRpQ00jKvvu37+Pv//+W+3bv3+/+i6jMba2ttr75smTBz/88AN27Nihjr+QESMh+3VVqVJFfb927Vo8HQEiIuPBwIKIyIjs2rULvr6+KFu2LDJmzKhqHyQ16s6dO/Hy+Nu2bZORbNXpjoykYG3YsEF12qWDHpnTp0+rGo6vfUXl0qVL6rukG4Ul9RLS0ZdgKDKaOgwJDsLKkiWL+n716tWv3lcWp5NULEmhEtmzZ1ffb9++Hep+EqiINGnSRPm6iIhMERfIIyIyIps3b1bfpe5B/PTTT7h8+bKqI5A6iLiSx9KMCERF0ymPinS+pV4hLjSd/Yg66pp9jx8/jjAY0ARBQjPSoEtGQoSnp2e4+8qITFT3laLuGjVqYMGCBaodJUuWVEHHxIkT1fYvv/wSh1dNRGScGFgQERkJGZW4ePEicuXKhRw5cqh9P/74o5q1SEYapNhYio7jQlYYFqlSpYpze1OmTKlN14otTUAQ0ciIvb29+i4jOJEpXry4+i5pTPXr1w912+7du9V3SZXS3FfSoeS+Xbp00d5P0r2OHz8e6r6Wlpbo3r27GrEYOHCg9r4uLi4qlUy+ExGZG6ZCEREZCalpELVr19buS506tRpdeP/+PXbu3Bmrx5W6CQ1NTYVMuxpXkjr05s2br35FRdKyvnabdPIjI7UiMrrw119/qdmsbty4oYKBMWPGqCBNWFt/vsbWqFEjVYch0+8uWrRI1VHIrFhdu3ZVr0XY2Nho07waN26MZ8+ewdXVFXPnzlWPL8dPZpAKO9sUEZE54IgFEZERkOlN//zzT21tgaT/aMi6DlJnIUXc0jkWmkLnqAIEzW26RdESqEhKj6T8SF1BXPzzzz9o3br1V++nqVuIiGakQkYldAuqdUcPkiRJEuXjy1ofI0aMwNatW7Xrekjx+4wZM9C2bVskT55c+zjLly9XIz/yO/IlQYuMCknq2ahRo7QpUtOnT1dF46tWrVJpUBqSmla3bl01be2+ffu0gQgRkTlgYEFEZARkdqRXr16pn9u0aRPhfa5cuYJ///1XXaXXdJajWqxNs+ibbj2BdJKlKFuuuEcVWMyZM0dd/Zer9ZHVN8j+ZcuWIS4yZMigrbUIW/egqb/Qne0psuDEw8NDpSw9fPhQpWhJjYiMOohMmTJp7yv7pY5FCsJlNEWOgaQ1aRYR1BwTCYbkvrpBhZD7ysxQsvaFpK5FdmyIiEwRAwsiIiMq2pbF3WSa1bDkSvzBgwfVqIWs/qzp0ErnPzLXr19X3/PmzavdJ1fnZ86cqRZ6a9CgQag0KQ0fHx9VLC6BiSwMFxkJBGSV67iQWa80ReVhZ5CSfTLKoKk3iYgEVlI3IfeRx9KtHTl69Kj6/t1332lndJKRH5lCNlu2bOpL977p0qVTM3EJGT2JbPVxzUhQVGlcRESmiDUWREQGTkYqZBQhadKkaoSgatWq4b5kRWqhWWuhQIEC6mr/nj17IgwupM5AAhHpPOfLl0+7XzrOsrK1TME6bty4cJ1nSf8ZNGiQapOsLfG10YK4kk6+BCirV68OtV6FjKhI/UO9evUiDH40JBVJVhGX2al0O/oymiBT5sqx04xYSOH68OHDVdCkS46pjAZJ2pRuu6QGQ46hrqdPn+LAgQMqgJEieyIic2Ihq+TpuxFERBS5xYsXY+rUqSoFasiQIZHer127djh58qSqJ2jRogXOnj2rCo8lOJDZmTQjExJoyCxS0umWImXNqICGdOAHDBigZk2SdB+pG5ApVKXTLAvSSX1HpUqVMGvWrHB1DwlBRmOkMFqCJakhef36tUqxknQvCQ6cnZ2195XXJXRno5I0JkndkjbLlwRFK1euVNPLSsCSPn16dT85TnIMJWiRAmwZ9ZGUJxm9KV26NObPn699vRKENGnSRNWiyMiO1Gw8efJEBSUyi5QUc1esWDHBjw0RkSFhYEFEZOCkcFhy/qWjnzVr1kjvJ+k6nTt3VlfKJQAQUlMgnWiZLlUzlawUaEunVwIVSe+JiFxzkqvxUitw69Yt9bsyvauMbkjnvk6dOlGOFMQ3GXlZuHChaosmxapv377h1rfQpEvpFoRLwCApYtLpf/TokQpIKlSogB49eqhjETZ1at68earwWgIQOT4yKiKjFbpF7kJqMCSAOHTokDo+jo6Oaoaubt26qSCIiMjcMLAgIiIiIqI4Y40FERERERHFGQMLIiIiIiKKMwYWREREREQUZwwsiIiIiIgozhhYEBERERFRnDGwICIiIiKiOGNgQUREREREcWYNE+bp6a3vJsDGxgoBAUH6bgYZCJ4PxPOB+NlA/F9BxtZ3cHFJEq37ccQigX3DhWnJCPB8IJ4PxM8G4v8KMtW+AwMLIiIiIiKKMwYWREREREQUZwwsiIiIiIgozhhYEBERERFRnDGwICIiIiKiOGNgQUREREREccbAgoiIiIiI4oyBBRERERERxRkDCyIiIiIiijMGFkREREREFGcMLIiIiIiIKM4YWBARERERUZwxsCAiIiIiojhjYEFERERERHHGwIKIiIiIiOKMgQUREREREcUZAwsiIiIiIoozBhZERERERBRnDCyIiIiIiMh0Agt/f3/Url0bp0+fjvQ+165dwy+//ILChQujYcOGuHr16jdtIxERERERGXBg8enTJ/Tt2xe3bt2K9D4+Pj7o3LkzSpQogS1btqBo0aLo0qWL2k9ERERERGYeWNy+fRuNGzfGw4cPo7zfrl27YGdnhwEDBiB79uwYOnQoEidOjD179nyzthIRERERkYEGFmfOnEGpUqXw+++/R3m/S5cuoXjx4rCwsFDb8r1YsWK4ePHiN2opERERERFFxhp61rx582jdz9PTEzly5Ai1z9nZOcr0KSIiIiIiYxQUFAQfn49wdnaCsdB7YBFdvr6+sLW1DbVPtqXom4yb7YutSHx7LCwCP8DUyUhbSEiIvptBBoLnA/FcIH42UES8Pgaj7SwvePsGY9/YzEDuEfBPXQ+GzmgCC6mvCBtEyLa9vX2kv2NjY4X/Z07pjbW1VfTuGBICizevgQ8fAcfECEnhLL0OmAPHO+Ng5XNb380gIiIi0rubT4GfpwE3n33e7r/wNqb3nAFkbAhDZzSBRerUqfHq1atQ+2Q7VapUkf5OQEAQDIG/f+TtsPB6B/vf18Jh8QJY3b+n3R+UJSt8O3aBX5PmCEmWHCYtwFt9C4EFQqxM/LVKrMgBC+L5QPxsIP6voAjs/CcALWd/wHvfz9spHC1Qt1Qy+GToHGV/0lAYTWAha1csWrRIpZFo0gf++ecfdO3aFcbK5tABJGvfCvANP2Wu5YP7SDx8MBJPGAuvpasQULkqTJ0EFd4558OUWVtbIjAwWN/NIAPB84F4LhA/G0hIv3basj8wbt7vksSi5MuRCWun9EDONHbwcfkJxkDvs0J9rWDbz89P/VyzZk28f/8e48ePV1PUynepu/jxxx9htEFFi18AP19YSLAUJu9eu8/PV91P7k9EREREpuWjrx/aD56JsXPXa+sw61YphX3LxiJL+sgzcwyRQQcW5cqVU+tXCEdHRyxYsADnz59HgwYN1PSzCxcuRKJEiWBsJP1JjVRI8BAc9dVrdXtIiLq//B4RERERmY52A2dg6/5T2u2h3RpjxeRf4Zgo8jpiQ2VQqVA3b96McrtQoULYunUrjJ3UVEj6U9hRiqiCixBfH9hvWAffTt0SvH1ERERE9G0M7NwIR89eha2NNRaMdUWtiiWM9tAbVGBhFkJCVKF2bDgsmg/fjl3NZrYoIiIiIlNXvEAOLBzXE7mzpkeebBlgzBhYfGMWb96Emv0p2r8XEqJ+L8XOnEASg85gizFL/5f6bgIRERFRgvvkH4Clm/ajc5OasLL60p/7uUopkzj6DCy+MYuPcVsEzur9S8AOJinE0vhyCYmIiIii47nnW7Tq74GzV27hxat3GNWruckdOAYW31hIYsc4/X5w4mSAToRrSkGFn0tTfTeDiIiIKN6du3JLBRXPPN+q7QXrd6Nj4+rIkCalSR1tBhbfWEiKFGrxO1mnIrrF2+r3LCwQnD4VPhSdyRoLIiIiIiOx5s8j+HXCIvgHBKrtDKmdsdqjn8kFFcL0Ln0bOgsLtaJ2bPg3/ZFBBREREZERCAwMwiD35egx+jdtUFGmaB4cXj0RRfJmgyliYKEHfk2aAw6JEGIZvcMfYmkB2NvCv3aFBG8bEREREcXNm3feaOA6AfPX7dbu69CoGrb9NhwuKZKZ7OFlYKEHIcmSw2vpKjX68LXgQlKgAAv4THUDkiT+Zm0kIiIiopi79+g5KrUegmNnr6ptG2srzBzaGR6DO6q1KkwZAws9CahcFV5rNgL2Dip4+BxAfKHdZ28Ln1mDEFimsL6aSkRERETRlDqlE5I5JlI/p3JOhu0LRqBNgypmcfwYWOg5uHh96To+jpuE4MxZQt0mhdp+bm3wfvd8BhVERERERiKRgx3WePRH9bJFcXjVRJQukgfmwiIkJAZTExkZT09vfTcBtrZW8PcPCr3vxVYkvj0WFoE6a1qEhMDyzUtY+IWoKWW9iy5gobYJsra2RGBgsL6bQQaC5wPxXCB+Nhi/9x984OXtg4xpE2CWp0Af2AR5wSdTQ4TY6q82w8UlSbTuZ9qJXgZKggprn9vhb5D3LAkQYpOIQQURERGRgbv94ClauLnD0tIC+5aNQ5LEDjBnTIXSA81IRQgsEGzlFOoryCYtF4ojIiIiMnAHTl5E5dZDcfPeE1y/8xgDpiyDueOIhR6FWCWHd875+mwCEREREcWAVBHMWvknRs1ep34WebNnwICODcz+ODKwICIiIiKKBh/fT+g1dgE27T2h3Ve7Ukn8NrqH2adBCQYWRERERERf8ejZK7Rwm4rLN+9r9w3u8gv6d2wAy2guemzqGFgQEREREUXhxD/X0GbAdLx6+15tOyayx/wxrmq0gr5gYEFEREREFIUT569rg4qsGVJj7bT+yJs9I49ZGAwsiIiIiIii0K9DfVy+eU/VWCyZ0BtOyRx5vCLAwIKIiIiISId/QCBsbb50k6WGYuHYnmqftbUVj1UkWGlCRERERPR/F67dQcmGv6q6Cl2JHOwYVHwFAwsiIiIiIgDrdx5DzQ4j8eDJS1WsLTNBUfQxFYqIiIiIzFpgYBBGzlqDuWt2avflyJQ2VDoUfR2PFhERERGZrbdeH9B+8EwcPn1Zu69tgyqYMqA9A4sYYmBBRERERGbp2u2HaN7XHfefvFDb1lZWmDKgHdo3qqbvphklBhZEREREZHb+PHQa3UbMxUffT2o7pVNSrJjyK8oWy6fvphktBhZEREREZFY833ih6/C58PH7HFQUzpMVq937IWPalPpumlHjrFBEREREZFZcUiTDnJFd1c+NapTF7sWjGVTEA45YEBEREZHZaVD9e6ROmRzfF80LCwsLfTfHJHDEgoiIiIhM2qFTlzBu3u/h9ks9BYOK+MMRCyIiIiIySSEhIZizagdGzl6D4OAQZMmQCi3rVtJ3s0wWRyyIiIiIyOT4+vmjy/A5GD5ztQoqxIETF1WwQQmDIxZEREREZFIePXuFlv3ccenGPe2+/h0bYnCXRkx9SkAMLIiIiIjIZJy8cB1tBkxXU8qKxA52+G1MD9StXErfTTN5DCyIiIiIyCQs3bQfA6YsQ2BQkNrOnD4V1nr0R/6cmfTdNLPAwCIB2b7YCsc744AA71D7Lf1fJuTTEhEREZmdOat3YNj0Vdrtit8VwLKJfZAieRK9tsucsHg7ASW+PRZWH2/Byv95qC8LBKvbQyztE/LpiYiIiMxGwxrfI01KJ/Vz9xY/YfPsIQwqvjGOWCQgi8AP6nsILBBilTzUbRJU+Lk0TcinJyIiIjIbaV1SYLW7G/67/xTN61TUd3PMEgOLb0CCCu+c87/FUxERERGZhe2HzqB8yfxIniSxdl+JgjnVF+kHU6GIiIiIyGgEBQVj+IzVaNXfA52HzlbbZBgYWBARERGRUXj3/gMa956E2au2q+19Jy5gx5Gz+m4W/R9ToYiIiIjI4N24+xjN+07F3UfP1ba1lRUm9WuDupW/03fT6P8YWBARERGRQdt55Cy6DJ+DDz5+ats5eRKsmNIX5Yrn03fTSAcDCyIiIiIySMHBwZi6eAsmLtio3Vcwdxas8eiHTGld9No2Co+BBREREREZnE/+Aeg4dJaa/UmjQfUymDOiGxI52Om1bRQxBhZEREREZHBsbaxhZ2OjfrawsMBI12bo3aau+pkMEwMLIiIiIjI4EkDMGt4FL16/Q89WdVC9XFF9N4m+goEFEREREeldSEgIHj1/Fap2QlKe/pw/nKMURoLrWBARERGRXvl98ke3kfNQoflA3Pv/dLIaTH0yHgwsiIiIiEhvnr58g1qdRmH9zmN49/4jWvTzQEBAIN8RI8RUKCIiIiLSi9OXbqJ1/2mqjkIksrfDwE4NYWPDLqox4rtGRERERN/cyq0H4TZpCQICg9R2pnQuan2Kgrmy8N0wUgwsiIiIiOibkTSnwR4rsHjjPu2+8iXyY/mkPnB2Ssp3wogxsCAiIiKib8LzjRfaDJyOk/9c1+7r0vRHjOvTkulPJoCBBRERERF9E+ev3tYGFbIA3rQhHdGybiUefRPBWaGIiIiI6JuoWaE4BnVphDQpnbBz0UgGFSaGIxZERERElCCCg4NhaRn6OvaAjg3R8ZcaSMl6CpPDEQsiIiIiinfvvD+iSZ/JWLppf+jOp6UlgwoTxRELIiIiIopXN+89RvO+7rjz8BkO/30FebJnwPdF8/IomzgGFkREREQUb3YfO4/Ow2bD+6Ov2k7i6ICgoGAeYTPAwIKIiIiI4iwkJATuS7ZgwvyN6meRP2cmrPHojyzpU/EImwEGFkREREQUJx98/NB91Dz8efC0dl+9qqUxd1Q3JHaw59E1EwwsiIiIiCjW7j95ieZ9p+La7Ydq28LCAsO6N0HfdvXUz2Q+GFgQERERUaxIylObAdO0QUWSxA5YNK6nWq+CzA+nmyUiIiKiWJERiZnDOsPBzhY5MqfFwRXjGVSYMY5YEBEREVGsFcmbDetnDEThvFmRPEliHkkzxhELIiIiIoqWZ55vMGTaSgQGBoXaX/G7AgwqiCMWRERERPR1Zy7/h1b9PPDi9TtVWzHRrQ0PG4XCEQsiIiIiitKqbYdRu/NoFVSI7YfO4N37DzxqFAprLIiIiIgoQgEBgRgyfSUW/b5Xu69s8XxYMflXJE/qyKNGoTCwICIiIqJwXr99jzYDp+Ov89e0+zo1qYEJv7aGjQ27kBQezwoiIiIiCuXyzfto4eaOR8881baNtRU8BndE63qVeaQoUgwsiIiIiEjr3JVbqNt1LHz8Pqnt1M7JscrdDd8VysWjRFFi8TYRERERaRXMnQX5cmRUPxfLnx2HV09kUEHRwhELIiIiItKys7VRIxSzVm7HSNdmsLez5dGhaGFgQURERGTGbt1/qr7nzJJOuy+tSwquU0ExxlQoIiIiIjO1768LqNJ6CJr1nYJ33h/13RwycgwsiIiIiMyMrJw9fdkfaNJnMt5/9MXtB88wcf5GfTeLjBxToYiIiIjMiI/vJ7iO+Q1b9p3S7qtbpRSG92iq13aR8WNgQURERGQmHj7zVOtTXLl5X7tvSNfG6NehPiwtmchCccPAgoiIiMgMHD/3L9oOnI7X77zVdpLEDlgw1hW1KpbQd9PIRDCwICIiIjJxizfsxUD35QgKClbb2TKmwdpp/ZEnWwZ9N41MCAMLIiIiIhP3wcdPG1RUKVMYSyb0QvKkjvpuFpkYBhZEREREJq53m7q4+t8DpEudAiNdm8PKivUUFP8YWBARERGZmNdv38PZKal228LCAgvHubJAmxIUw1UiIiIiE7J2+1EUquOKI6cvh9rPWZ8ooTGwICIiIjIBgYFBGOyxAt1HzcNH309oO2iGml6WyGgCiw8fPqBHjx4oWbIkunfvjnfv3sVPy4iIiIgoWt6880bDnhPw29pd2n0Nq3+PNCmdeATJeAKLWbNm4cKFC2jQoIH6Pm3atPhpGRERERF91b+3HqJS6yE4euaq2raxtsLMoZ3hMbgjbG1YTkvfTpzPtgMHDmDgwIH4+eefkSlTJixatCh+WkZEREREUdp28DS6j5yrUp9EKudkWDmlL0oXycMjR8YXWLx8+RJZs2ZVP+fIkQOenszlIyIiIkpIwcHBmLhgE6Yu3qzdVzRfNqx274f0qZ158Mn4AougoCAEBgbCyspKbdvb26sTnYiIiIgSzsOnnpi3Zod2u3Gt8ir9ycHeloedjCew+OOPP7Q/SxAh8yIfOXIEt27dwsOHD+O7fUREREQURpYMqTF/jCvaDZqBUb2ao0eLn1SfjEifLEJCQkJi8gt58kSdsycn9fXr12EIPD299fr8KY7mgpX/cwRbOcE753y9toUMg7W1JQIDOapHPB+Inw0U8/8V0mULGzzcf/ISWdKn4uE0VYE+sAnygk+mhgixTaa3Zri4JEmYEYuDBw/Gpj1EREREFAsSUMxa+ScePXsF90EdQt3GoIIMSYwDi61bt+KXX35B6tSp46UBnz59wujRo7Fv3z5Vo9G+fXv1FZH9+/er6WyfP3+uRk6GDRuG/Pnzx0s7iIiIiAyNj+8n9Bq7AJv2nlDb+XNmQruG1fTdLKL4Wcdi7ty5ePHiBeLLlClTcPXqVaxYsQIjR47EnDlzsGfPnnD3kxoONzc3dOnSBdu2bUPevHnVz76+vvHWFiIiIiJDISMUNTuM0AYV4tXb93ptE1G8BhYxLMmIko+PDzZu3IihQ4eqkYdq1aqhY8eOWLNmTbj7njhxQk1nW69ePbVeRt++fdXUtrdv34639hAREREZghP/XEOlVoNx+eZ9tZ3YwQ6rprqhf8eG+m4aUfxONztq1Cg4OjpGeJsUFcnoQ3TcuHFDTVdbtGhR7b7ixYtj/vz5asYpS8svcU/y5MlVEHH+/Hl1/y1btqg2SJBBREREZArkAu6iDXvRf9IyBAYFqX1Z0qfG2mn9kC8H+zxkoutYRDZyEZMRDRlxcHJygq3tlzmXU6ZMqeou3r17hxQpUmj316pVC4cOHULz5s3VuhkSdCxYsADJkumvQp6IiIgovvgHBKL/5KVYsfXLRDmVShXC0om94ZQs4gu6RCYxYlGoUKE4P7nUR+gGFUKz7e/vH2r/27dvVSAyYsQIFC5cGOvWrcPgwYNVMbmzM1eYJCIiIuM2ctaaUEGFrE0xulcLWFt/XoiYyKRX3o4rOzu7cAGEZltmiNLl7u6OXLlyoUWLFmp77Nix+PHHH7F582Z07tw5wse3sbGCPteK0c41bfF5TmoiKyueB/QFzwfiuUC6+ndsgO2HTsPzzXvMGdEFzepU5AEydyEWsIIlbGytAPkytcDC1dU13FSzQUFBKj0ppuRxZCRC6iysrT83RUYlJKhImjRpqPv++++/aNWqlXZbUqFkytmnT59G+vgBAZ9zE/VFmxYWAi6KRlpcII908XwgngukkSJZEqzx6K86DoXzZOPnAwFBIbAICkaAfxBCoN9+bXRYxiawkOledUcJzp07h3LlymH16tUxeiyZMlYCiosXL2r3SXF2wYIFQxVui1SpUuHOnTuh9t27dw8ZMmSI6UsgIiIi0qvAwCC4L9mCN++8Q+0vnCcrihfIobd2EX3TwGLp0qWYMWMGsmTJot0nMzPVrFkTkyZNUtPHRpeDg4OaPlZqNi5fvowDBw6ox2/durV29MLPz0/93LhxY2zYsAF//PEHHjx4oFKjZLSifv36MX0JRERERHrz1usDfuk1CePm/Y52g2eoIIPIFMQ4FWr9+vXo06dPqBGLtGnTqlWwZUan5cuXq5W5o0sKsCWwaNOmjZo+tmfPnqhevbq6TUZBJk6ciAYNGqhZoT5+/KhmgpKVt2W0Q6a1ZeE2ERERGYtrtx+ieV933H/yebHhE+ev49zVWyhdJI++m0YUZxYhMVzxTmZkknUmypQpE+62U6dOoWvXrrh06RIMgadn6OHFby3F0Vyw8n+OYCsneOecr9e2kGGQIn7m1BPPB+Jng3nafugMuo6Yg4++n9R2SqekWDHlV5Qtli/U/fi/grQCfWAT5AWfTA0RYqu/JRZcXJIkTCpU+vTpVQARkbNnzyJNmjQxfUgiIiIikyWL/k6YvwGt+ntogwqppTi8amK4oILIrFKhpNZh6tSpCAgIQNWqVVUq0ps3b3D48GEsW7YMbm5uCdNSIiIiIiPj/dEXXYbPwa6j57T7GtUoi1nDuyCRg51e20ak98Cibdu2ePHiBVatWqXqKYRkU8nsTlIn0a5du3hvJBEREZGxeef9ETXbj8CNu4+161uN7tUcPVvV+bLWFZG5L5A3cOBAdO/eXU0T++7dO7XmhKzE7eTkFP8tJCIiIjJCyRwToVj+7CqwSOqYCEsn9kbV74vou1lEhrfytoxSyJesN2FjY6O+iIiIiOgzGZWYNrgjgoKD0b9DA+TInI6HhkxarAKLhQsXYt68efj06ZN2dWlbW1t06dIFPXr0iO82EhERERk8Xz9/3Lz3GEXyZtPus7ezxYIxrnptF5HBBhabN2/GtGnT0KhRI9StW1etXSEL2clq3HPmzEG6dOm4aB0RERGZlcfPX6FlPw/cffgMB1dOQM4sHJ0g8xPjwEIKtps1a4aRI0dq92XLlg2lSpWCvb09Vq5cycCCiIiIzMapCzfQesA0eL7xUtudhs3G4VUTWKBNZifG61g8ePBATTMbkSpVquDu3bvx0S4iIiIig7d8ywHU7TpGG1RkTp8Kc0d2Y1BBZinGIxapU6fG06dPI7zt8ePHcHR0jI92ERERERks/4BADJq6HEs379fuq/hdASyb2AcpkkdvlWIimPuIReXKlTFz5kxcvnw51P5Lly5h9uzZ6nYiIiIiUyWjEz93GxsqqOje4idsnj2EQQWZtRiPWPTs2RMnT55EkyZNkD59elW8/erVKzx58gTZs2fnyttERERksi5ev4uWbu54/OK12raztcGMoZ3QrHZFfTeNyPgCC0l12rRpk5od6uzZs/Dy8kLBggXRvn17NGjQQBVwExEREZmil6+98OTlG/VzWhcnrHbvh+IFcui7WUQGwSJEsxCFCfL09Nbr86c4mgtW/s8RbOUE75zz9doWMgzW1pYIDAzWdzPIQPB8IJ4Lxmn6sj+w+9h5rJzSF2lcnOL98fnZQFqBPrAJ8oJPpoYIsU0GfXFxSZIwIxaDBw/+6iqTEyZMiOnDEhERERmcDz5+SOxgF2qWpz5tf0aPlrVhaxOrdYaJTFaM/yJOnz4davvZs2eqzsLGxkZt6/7hERERERmrG3cfo3nfqejUuAa6Na+l3S99HQYVRPEQWBw6dEj7c2BgIAoUKID58+cjf/78MX0oIiIiIoO06+g5dBk+B94ffTFsxirky5ERFb8rqO9mERm0OI3hcXSCiIiITElwcDDcl2zFhPkbtPvy5ciErBnT6LVdRMaAyYFERERE/6+n6D5qHv48+CXtu0H1MpgzohsSOdjxGBHFd2Chu+p2UFCQ+i7rWOjuT5cuXUwfloiIiEhv7j9+geZu7rh2+6E2K2NEj6aqUJsZGkQJFFjIytph/8C6du0aavv69esxfVgiIiIivThy+jLaDZ6Jt14f1HZSx0RYPL4XqpcryneEKCEDC5lKlpE7ERERmYKAgED0m7xUG1TkzJwOa6f1R84szL4gSvDAQlbXJiIiIjIFNjbWaqG7am2HoVzx/Fg4rieSJUmk72YRmWfx9ocPHzBw4ECcOXMGJUuWVCMayZMnj5/WERERESUwmfVp37JxyJMtA6ysLHm8iWIpzn89s2bNwoULF9RIhnyfNm1aXB+SiIiIKEGcvnQTbQZMg39AYKj9+XNmYlBBpO8RiwMHDqgRi59//hmZMmXCokWL4vqQRERERPFu5daDcJu0BAGBQXBOvhzThnTkUSYypMDi5cuXyJo1q/o5R44c8PT0jI92EREREcVbgfaQaSuxaMNe7b7/7j+B3yd/2NvZ8igTGUJgIetYBAYGwsrKSm3b29urFSuJiIiIDMGrt+/RZuB0nDh/Tbuvc5OaGP9rK1W4TUTxJ8Z/UX/88Yf2ZwkiZOrZI0eO4NatW3j48POiMkRERET6dunGPbRwc8fj56/Utq2NtUp/alm3kr6bRmSSYhxYDBo0KNy+2bNna3/mGhdERESkb5v3noDr6Pnw/eSvttOkdMIq974oWTCXvptGZLJiHFgcPHgwYVpCREREFA92HjmLDkNmabdLFMiBVe5uSOuSgseXyJACi/Tp0ydMS4iIiIjiQbWyRVGmSB6cungDzetUxLTBHVmkTWSIgcXgwYOjvF1SoWSRPCIiIiJ9kFqKFVN+xa6j59CmfhWmaRMZamCxdetWpEyZEra2EU/PxhoLIiIi+pb2HDuPjGld1CJ3Gqmck6Ntg6p8I4i+oVjNszZv3jwUKlQo/ltDREREFE0hISHwWLoV43/bgMzpUuHwqglwSubI40ekJ5b6emIiIiKi2Prg44e2A6dj3LzfVYBx/8kLLNu8nweUSI+4MgwREREZlftPXqKF21T8e+uhNg17WPcm+LVdPX03jcisxSqwOHr0KO7evRtqn6y+nTRpUpQpUybS+gsiIiKiuDh65iraDZqBN17eajtJYgcsGtcTNSsU54ElMsbAYu7cuRHulysG5cuXx8KFC+PaLiIiIiItSXdasH4Phk5fiaCgYLUvR+a0WOvRH7mycip8IpNaIC84OFjd5u7uHh/tIiIiItIGFX3GL8KKrV/6INXKFsGi8b2QPEliHiUiU1wgT0Yrjh8/Htc2EREREYXKiMid7Uv/49e2P2NY96awsuIcNERGnwr15s0bLFmyBCdPnoSnpycWL16MAwcOIE+ePGo/ERERUXzq1qwW7jx4hu+L5UXDGmV5cIkMUIxD/UePHqFu3brYsGEDUqdOjdevXyMoKAj37t1Dr169cOTIkYRpKREREZmNa7c/z/ikO2rhMbgjgwoiUwosJk+eDGdnZ1VPMWfOHJX3KDw8PFC5cmXMnz8/IdpJREREZiAgIBADpy5H2aYDsO+vC/puDhElZGBx6tQpdO/eXU0tK1cPdDVp0gS3bt2K6UMSERER4fXb92jgOgEL1u9WFy47Dp0FzzdePDJEplxjYW0d8a/5+/uHCzaIiIiIvubqrQdo3ncqHj71VNs21lYY16clXFIk48EjMtURixIlSmDBggXw8fHR7pNgQqabXbduHYoVKxbfbSQiIiIT9sf+U6jedrg2qEjlnAw7Fo5E6/pV9N00IkrIEQs3Nzc0a9YM1atXR6lSpVRQITNB3blzBw8ePMDatWtj+pBERERkhuSi5PjfNsBj6VbtvmL5s2PVVDekT+2s17YR0TcYsciVKxc2b96sgorTp0/DyspKTTubKVMmrF+/Hnnz5o1FM4iIiMiceHn7oFnfqaGCiqY/VcCuRaMYVBCZy4jF2bNnkS9fPjULFBEREVFseL55h1P/XFc/W1paYNyvrdRaFazVJDKjEYvWrVurtCciIiKi2MqROR0Wje8F5+RJsGXOEHRv/hODCiJzG7HQrFtBREREFJP+Q2BgEGxsvnQ9apQvhot/zkaSxA48kETmOt3spk2bcOzYsQhvkyHMHj16xLVdREREZCJ8fD/BdcxvsLezxdyR3UKNTDCoIDLzwGLDhg2R3sbAgoiIiDQePvNECzd3XLl5X20Xyp0VXZv9yANEZIJiHVgUKlQo/ltDREREJuOv89fQZsA0vH7nrbYdE9kjY9qU+m4WERlSYEFEREQUVT3F4o37MNh9BQKDgtS+bBnTYO20/siTLQMPHJGJinFgUbJkSSROnDhhWkNERERG7ZN/APpNWoJV2w5r91UuXQhLJ/ZG8qSOem0bERlYYLFq1aqEaQkREREZteeeb9F6wDScufyfdl+v1nUw0rU5rKxiPMM9EZl6YFGlSpUob5fi7QMHDsSlTURERGSERsxaow0q7O1sMGtYFzSuVV7fzSIiQw0svLy88OHDB7X6du7cuROmVURERGR0Jrm1welLN9V6FWs8+qFI3mz6bhIRGXJgsW/fPri7u+PPP/9E4cKF0adPHyRLlixhWkdERERGI0XyJNgwcyCckjoilXNyfTeHiL6xGCc8pkiRAhMmTMC6detw/fp11KhRA+vXr+eK3ERERGbkzTtvdB0xF55vvELtz501A4MKIjMV60qqggULqoBi4MCBmDNnDho0aIDz58/Hb+uIiIjI4Px76yEqtR6C9TuPoc3A6QgICNR3k4jIGAOLs2fPhvrKkCEDxo4dCxsbG7Rs2RL9+vVLmJYSERGR3m07eBrV2w3Dgycv1fat+09x//8/E5F5i3GNRatWrdTMT5oFcHR/Fjt37lQ1GERERGQ6goODMXHBJkxdvFm7T4qzV7u7IUMarqZNRLEILFauXMnjRkREZEbef/BBlxFzsfvoOe0+mUZ25tDOcLC31WvbiMiIA4vvvvsuYVpCREREBufOw2do3ncqbt57orYtLS0wulcLuLasrc1aICKKVWAhNm3ahH///VcVcNeuXRtTpkzB6dOnkTNnTgwZMgQpU3JIlIiIyNg9efEalVsPhZf3R7WdLEliLJvYG5XLFNZ304jIFIq3p06dimHDhmH37t3qu8wGtWXLFmTNmhUnTpzA+PHjE6alRERE9E2lT+2MBtXLqJ/zZMuAw6smMKggovgbsZCF8Tp37oy+ffti+/bt6N+/PyZNmoR69eph69atKvAgIiIi0zC5fzukdEqGXq3rIEliB303h4hMacTizZs3KFu2rPq5evXq6nu2bNnU90yZMuHt27fx3UYiIiL6Bh49e4XDf18Otc/WxhpDuzVmUEFE8R9YBAUFwcHh8xULa+vPAx5WVlahtomIiMi4nLxwHZVaDUbLfu64dvuhvptDREYoVpHA0aNHcffuXTWntcwIceTIEdy6dQsPH/KDiIiIyNgs3bQfA6YsQ2BQkNoeNn0Vtswdqu9mEZE5BBZz584NtT179mztz5x6joiIyDj4BwRiwJSlWL7loHZfpVKFsGRCb722i4jMJLA4ePDLhw8REREZp5ev36F1/2n4+9JN7b4eLX5Sa1RYW39OcSYiStDAQmZ++uWXX5A6deqY/ioREREZgAvX7qBlPw+1ToWws7XBzGGd0fSnCvpuGhGZU/G2pEG9ePEiYVpDRERECWrLvpP4seNIbVCRLlUK7F48ikEFEX37EYuQkJC4PysRERHpRYpkjqq2QpQqnAsrp7ghdcrkfDeISD/F26NGjYKjo2OEt0nx9ooVK+LaLiIiIkoAP5QqhLF9WuG/e08wZUA7lQZFRBQfYr3wRGQjFxzRICIiMqxF7zKkcQ41a2P35rXUd87kSEQGMWJRqFCheG0IERERxa8dh8+i64g56N+xAXq3+Vm7nwEFERlE8TYREREZNlnAdtLCjWoV7Q8+fhg1ex2Onb2q72YRkYmL8YiFq6truKlmg4KCYGXFOa+JiIj0zfujL7qOmIudR85q9zWs/j1KFMip13YRkemzjE1gsW3bNnTu3Fm779y5cyhXrhxWr14d3+0jIiKiaLr36DmqtxumDSok5WlM7xZYNL4nEjnY8TgSkWEFFkuXLsWMGTOQJUsW7b5MmTKhZs2amDRpEjZu3BjfbSQiIqKvOPz3ZVRqPQTX7zxW20kdE2HjrEHo1bouayqIyDBTodavX48+ffqEGrFImzYthg0bhpQpU2L58uVqZW4iIiJKeDIb49w1OzFi5moEB3+esTF31vRYO60/smdKy7eAiAx3xEJW3S5YsGCEtxUuXBiPH3++UkJEREQJz8fvE5ZvOaANKmpWKI79y8cxqCAiww8s0qdPj1OnTkV429mzZ5EmTZr4aBcRERFFQ2IHe6z16K9Sn/p3bIi1Hv3Uz0REBp8K1bhxY0ydOhUBAQGoWrUqnJ2d8ebNGxw+fBjLli2Dm5tbwrSUiIiItNPJWlp+uTaYK2t6nN86Ay4pkvEIEZHxBBZt27ZV6VCrVq1S9RSa/E5ra2u0adMG7dq1S4h2EhEREaDSnjbs/gtb5w6Fna2N9pgwqCAifbMIkaggFry9vXHhwgV4eXkhadKkaiVuJycnGBJPT2+9Pn+Ko7lg5f8cwVZO8M45X69tIcNgbW2JwMBgfTeDDATPB4rJueAfEIhBU5dj6eb9artF3R8wZ0RXzvhkgvjZQFqBPrAJ8oJPpoYIsdXfiKSLS5KEGbHQkFSoChUqqJ9lBOPMmTPInj07cuTIEduHJCIiogh4vvFC6wHTcOrCDe2+JIkdVMG2lZUFjxkRGYQYBxbXrl1Ti+Q9e/ZMFXLLz6NHj4avr6/K95wwYQLq1auXMK0lIiIyMxev30VLN3c8fvFabdvaWGP6kE5qxIKIyKhnhRozZgwSJUqk1q1IlSoVBg8ejPLly2P79u2oUaMGFi9enDAtJSIiMjOb9pxAzQ4jtEFFmpRO2LVoFIMKIjKNwOLmzZtqlKJFixbw8PBQhdstW7ZEzpw50bBhQzx69ChhWkpERGQmgoKC1YJ3HYfOgt+nALWvZMGcOLx6AkoUzKnv5hERxU9gISlPmrUqXFxc1PfEiROr70mSJIG/v3+MHu/Tp08YMmQISpQogXLlymHp0qVRBjXNmjVTheJ16tTB33//HdPmExERGbyVfxzErJXbtdstf66EHQtHIq1LCr22i4goXgML9Uv/nzvbwsIi1PfYmDJlCq5evYoVK1Zg5MiRmDNnDvbs2RPhLFTt27dXxeGSdlWtWjU1cvL69efhYSIiIlPR6ufKqFCyAKysLDFlQDvMHt4l1NSyRESGKFazQvXo0QO2trba7a5du8LGxibGoxU+Pj7YuHEjFi1ahPz586uvW7duYc2aNahZs2ao+27dulXVdowaNQpWVlbo1asXjh49qoKSihUrxuZlEBERGSRrayssn9QH1+8+Qtli+fTdHCKihAksZManuIxQ6Lpx4wYCAwNRtGhR7b7ixYtj/vz54VYVlelsq1SpooIKjc2bN8dLO4iIiPRF/t9NXfwHKpUqhCJ5s2n3p0iehEEFEZl2YDFp0qR4e3JPT0+1qJ7u6EfKlClV3cW7d++QIsWXXFIpCpfaiuHDh+PQoUNqqtuBAweqQISIiMgYffDxQ/dR8/DnwdNYsnE/Dq+awBW0ich8AgtJUWrQoIEauZDpZuNCCsF1gwqh2Q6bViVpUwsXLkTr1q1V6tTOnTvRoUMH7N69G2nTpo3w8W1srBBPgyuxoh3Zsfi8iiaR5EsTafB8MG/3Hr9A0z5T8O+th2r7yYvXOH7+XzT+sZy+m0Z6xs8G0gqxgBUsYWNrBciXqQUWMkIgHfyZM2eiTJkyaopZSVEKGyBEh52dXbgAQrNtb28far+kQOXNm1fVVoh8+fLhxIkT2LZtm6rxiEhAQBD0Sabi/fwDEBgYrNe2kOHguUA8H+jI6ctoN3gm3np9UAcjqaMDFo3rhRrli/Ezgvi/gr4ICoFFUDAC/IMQAv32a6MjxpdPx48frzr0khIlHWc3Nze1QJ6svn3lypUYPVbq1Knx9u1bVWehmx4lQUXSpElD3Vemts2W7UvuqciSJYtaAZyIiMgYyP/NuWt2ooHrBG1QkTNzOhxZM1EFFURExixWeRky0iDrSCxZsgSHDx9Ws0T9+++/aNy4sdq/evVqlbr0NTICYW1tjYsXL2r3nT9/HgULFgxVuC2KFCmi1rHQdffuXVVrQUREZOj8Pvmj28h5GDptJYKDP49o1yhXDAdWjEeuLPxfRkTGL04J31JkLbM1yUJ10umXBfKyZs2K2bNno2rVqjh9+nSUv+/g4KBqNWQK2cuXL+PAgQNqgTypo9CMXvj5+amfmzZtqp5DHvvBgwcqFUsKun/++ee4vAQiIqJvMvNTvW7jsH7nMe0+t/b1sXZafyRLkojvABGZBIsQbSFA9EkgIbUN+/btUyMT3333HRo1aoQaNWqoWgsJBmQxu5cvX6pg4WsF3BJYyGM5Ojqqguy2bduq23Lnzo2JEyeqYnHNaIakYslaF9mzZ8fQoUNRsmTJSB/b09Mb+pTiaC5Y+T9HsJUTvHPO12tbyDBIET9rLIjng3lasnEf3CYtQSJ7O8wd2Q31q5fR3sbPBtLF84G0An1gE+QFn0wNEWKbDPri4pIkYQILWYxOAgapj6hfv77q9GfMmDHc/WQF7VWrVn111CIhMbAgQ8N/FsTzwXzJv9uJCzaidqXvUCh3llC38bOBeD6QKQQWMZ4VSmodZHSiXLlyUS6UJwGH3I+IiMjcBAQE4siZK6hW9ssCsPI/c0jXxnptFxFRQopxYCG1DdGRLl262LSHiIjIqL16+x5tBk7HifPXsNq9H2pXijxll4jI7AKLwYMHR/sB5YrMhAkT4tImIiIio3T55n007zsVj5+/Utu9xi7AD6UKwjFR6LWZiIjMNrCIrE5Cs+aEzAalEVV6FBERkanasu8keoz6Db6fPi/0mialE1a592VQQURmI1qBxaFDhyLcP3z4cHh7e2PGjBnx3S4iIiKjEBQUjPG//Y5py/7Q7itRIAdWubshrUsKvbaNiMho1rGoVq2aXmd9IiIi0icvbx80+3VKqKCieZ2K2LFwJIMKIjI7MS7e1pUzZ068e/cOr1+/hrOzc/y1ioiIyMDdfvAUzX6dilsPnqptKytLjP+1Nbo0rcm0YCIyS3EKLJImTarm5X779i0DCyIiMitWlpbwfOulfnZK5ojlk35Fxe8K6LtZRETGmQp17tw5dVUmZcqU8dciIiIiI5A1Yxosm9hHLXZ3eNVEBhVEZPaiNWLx9OnnYV6Njx8/4sqVK6pou2zZskiePLnZH0giIjJtH339YAELJHKw0+6rVLqQCigsLeN0nY6IyHwCi8qVK4fLF5UUqLx582LixIkJ1TYiIiKD8ODpS7Rwc0eerBmwaHzPUP8TGVQQEcUgsJAF7zQfovI9UaJEyJQpE3Lnzs0CNSIiMmnHz/2LNgOm442XN67+9wBF8mWDa8va+m4WEZFxBhYNGjRI+JYQEREZEBmZX/j7HgyZtlKtVSFyZE6L6mWL6rtpRESmNysUERGRKfrkHwC3SUuwetth7b5qZYtg0fheSJ4ksV7bRkRkqBhYEBER6Xjm+Qat+0/D2Su3tPv6tPkZw3s0VWtVEBFRxBhYEBER/d+5K7fQsp8Hnr96q7Yd7Gwxe0RXNKpZlseIiOgr4nzp5ezZs/Dx8YnrwxAREendjBXbtEFFhjQpsWfpGAYVRETfIrAICgpC69atce/evbg8DBERkUGYM7KbKtD+vlheHF41AYXzZNV3k4iIzCcVSmbNICIiMkbyP0x3TQopzN7223CkSpEMNjbMFiYiiglWoRERkVm6eusBfuwwUhVr60qf2plBBRFRLDCwICIis/PH/lOo3nY4/r50U80AJdPLEhFR3HCcl4iIzEZwcDAmzN8A9yVbtfsCg4Lw/oMPXFIk02vbiIiMHQMLIiIyC17ePug8fDb2Hv9Hu6/JT+UxY0hnONjb6rVtRESmgIEFERGZvFv3n6J536m49eCp2ra0tMDYPq3QvXmtUMXbREQUewwsiIjIpO376wI6DpmJ9x991XbypImxbGIfVCpdSN9NIyIyKQwsiIjIZF27/RBN+kzWTo2eN3sGrPXoj6wZ0+i7aUREJoezQhERkcnKlyMTOjepqX6uXakk9i0bx6CCiCiBcMSCiIhM2rg+LVEodxY0q10Blpa8nkZElFD4CUtERCbjr/PX8Oeh06H2yQraLer+wKCCiCiBccSCiIiMntRQLN64D4PdV8DG2gpZlqVWoxRERPTtcMSCiIiMmqya3WvsAvSfvFQtduf7yR+Lft+j72YREZkdjlgQEZHReu75Fq0HTMOZy/9p9/VqXQcjXZvrtV1EROaIgQURERml81dvo2U/dzzzfKu27e1sMGtYFzSuVV7fTSMiMktxCiysrKwwceJEZMiQIf5aRERE9BXrdhxFn/GLVBqUSJ/aGWs8+qFI3mw8dkRExjpiUb9+/fhpCRERUTRMXrgJExds1G6XKZIHK6b8ilTOyXn8iIj0iMXbRERkVMqVyAdrKyv1c/uG1bBt/nAGFUREBoA1FkREZFTKFsuHqQPbqZ/bNaym7+YQEdH/MbAgIiKDdvrSTZQsmDPUAncMKIiITCiwuHv3Lh4/fowPHz7AyckJ6dKlQ+bMmeO3dUREZLaCg4MxaeEmTFm0GUO6NsaATg313SQiIoqvwOLVq1dYtmwZduzYgZcvX6qVTjUsLCzU7FA//vgjWrdujZQpU8bkoYmIiLS8P/qiy/A52HX0nNqeMH8Dqn5fGMXy5+BRIiIy5sAiKCgIc+fOxeLFi9XIhMwEVbBgQaRPnx6JEiWCl5cXXrx4gfPnz+PQoUNYuXIl2rRpA1dXV9jY2CT8qyAiIpNx99FzNO87FTfuPlbblpYWGN2zBYrmy67vphERURQsQnSHHSJRr149NRrRtWtXFChQ4Gt3x7lz51QQ8vz5c/zxxx/QF09Pb+hTiqO5YOX/HMFWTvDOOV+vbSHDYG1ticDAYH03gwwEz4fwDp68iPZDZsHL+6PaTpYkMZZO6IUq3xeBKeO5QDwfKEKBPrAJ8oJPpoYIsU0GfXFxSRJ/IxaDBg1C6dKlo/3kJUqUUF+nTp2K9u8QEZH5kmtcc1btwMjZaxAc/Pl6V55sGbB2Wn9ky5hG380jIqL4CixiElRIHYamvqJMmTLR/j0iIjJPvn7+6DV2PjbuOaHdV6tiCSwY64okiR302jYiIkqABfL8/f1x7NgxHD9+HL6+vhHWYSxZsgQ1a9aMwdMTEZG5CwwKwtVbD7TbMvvTanc3BhVERKY4YnH//n20b98ez549U9tSb7F8+XJVvC1OnjyJcePGqSlopbibiIgoumRUYq1Hf9TpOhYT3FqjbuVSPHhERKY6YuHh4QFvb2+MHDkS7u7uam7xyZMnq++jR49Ghw4d8OTJE3Tv3h27du1K+FYTEZFR++DjF2o7a8Y0OL91BoMKIiJTH7G4cOECunXrhqZNm6rt5MmTo2fPnhg1ahQ2bNiAH374AcOHD9eOYBAREUXEPyAQA6cuwz//3sHuxaORyMFOe5udLacnJyIy+cDi3bt3yJ8/v3a7cOHC8PHxwbZt2zBx4kS1rgUREVFUXr5+hzYDpuPUxRtqu/e4BVg4rqdaYJWIiMwksAgMDISDw5eZOTQ/9+nTh0EFERF91YVrd9CynweevHitHZ2QtSkYVBARmVlgERlZq4KIiCgqG3YdR69xC+D3KUBtp0uVQs36VCx/Dh44IiITEqfAwtIy2rPVEhGRmQkKCsao2Wsxe9V27b5ShXNh5RQ3pE6ZXK9tIyIiPQYWR48eVdPJCpkNSoavjxw5glu3boW7b7169eK3lUREZFTevf+A9oNn4tDfl7X72tSvgikD2rFIm4jI3AOLuXPnhts3e/bscPsk4GBgQURk3lZsPagNKqytrDC5f1u0b1SNNRVEROYeWBw8eDDhW0JERCbDtWUd/HX+Gi5cu4sVU35F2WL59N0kIiIyhMCC61MQEVFMWFlZYtH4XvD+4IuMaVPy4BERmYFoV18fP34cnTp1wk8//aQWyztx4kTCtoyIiIyC90dfdBgyE+ev3g61P3mSxAwqiIjMSLQCi8OHD6Nz5864ePEiEidOjEuXLqFjx45Ys2ZNwreQiIgM1r1Hz1G93TBs3nsSLfu547nnW303iYiIDDmwWLhwIUqVKqVmgdqwYYOaIapWrVr47bffEr6FRERkkA7/fRmVWg/B9TuP1fZH30+4+/i5vptFRESGHFj8999/aNeunRqtEDY2NujevTtev36NZ8+eJXQbiYjIgISEhGDO6h1o2HMC3r3/qPblypIOh1aOx/dF8+q7eUREZMjF2z4+PkiePPRiRhkyZFD/XLy8vJA2bdqEah8RERkQXz9/9B6/UK2mrVGzQnEsHOuKpI6J9No2IiIygsBCAghZnyLUL1p//tWgoKCEaRkRERmUJy9eqzoKmUJWo1+HBhjS9RdYWkZ7LhAiIjL3BfKIiMh8+X3yR432I/D4+Su1ncjeDr+N7o6fq5bWd9OIiMjYAotr167h06dP2m0ZqZBRDNkvqVK6SpYsGb+tJCIivbK3s8XAzo3Qc8x8ZErngrXT+qNAzsx8V4iIKOaBxejRoyNMkRo+fLg2TUqTMnX9+vXoPiwRERmJVj9Xgr9/AOpVLQ1np6T6bg4RERljYLFy5cqEbwkRERkMzzde2H3sPFrXqxxqf4dfquutTUREZAKBhcwA5eLioqaZJSIi03bx+l20dHPH4xevkSSRA+pXL6PvJhERkRGI1jQeVapUYXoTEZEZ2LTnBH7sMFIFFWLsvPUICAjUd7OIiMiUppslIiLTFRQUjDFz12Hmij+1+0oWzImVU/vCxoYTCBIR0dfxvwURkZl79/4DOg6djQMnL2r3tfy5EjwGdYCdLVNgiYgogaebjQqnmyUiMg437j5G875TcffRc7VtZWWJiW5t0KlxjXALoxIRESXYdLNhcbpZIiLjcfTMVbWStvdHX7WdIlkSLJ/cBxVKFtB304iIyJQDC1mvIkeOHAnbGiIi+mayZkwN2//XT+TPmUktepc5XSq+A0RElLCBRYECBVCoUKHYPQsRERmcTGldsGJKX6zYcgAzhnVGYgd7fTeJiIiMGIu3iYjMxIOnL+GcPCkcE30JIMoVz6e+iIiIvsk6FkREZNyOnrmCH1oORvdR8xAcHKzv5hARkbkGFitXrkS2bNkSvjVERBSvZFKN39buQgPXCXjr9QF/HjyNRRv28igTEZF+AotTp07BxiZmc5n7+Phg+vTpsW0XERHFkd8nf3Qf9RsGe6xQC+CJGuWKoelPFXlsiYhIP4GFt7c3atSogeXLl+Ply5dR3tfT0xPz5s1T93///n18tZOIiGLgmecb/NRpNNbtOKrd59a+vpr5KVmSRDyWRESkn+LtYcOGoUqVKpg0aRKmTJmCwoULqxmiMmTIAAcHBxV4PHv2DOfPn8fNmzeRPXt2TJgwAeXLl4//FhMRUZTOXP4Prfp54MXrd2o7kb0d5o7shvrVy/DIERGR/meFKlOmDLZt24YjR45g+/bt2LFjB16/fq29PWXKlChXrhxcXV1RqVKlhGovERFFYdW2w3CbuBj+AYFqO2NaF6zx6IdCubPwuBERkWFNN/vDDz+oL+Hr66tGK5InTw5bW9uEaB8REcWgUHvPsfPaoEKmkV0++VekdErKY0hERIY93aykQaVKlYpBBRGRAbCwsMD8MT2QJ1sGdG5SE1vnDmVQQURE3wwXyCMiMmIyOmFr8+WjPEliB+xfPk59JyIi+pa4QB4RkZHauu8USjb8FY+fvwq1n0EFERHpAwMLIiIjI2tSjJmzDu0Gz8CDJy/Rws0dvn7++m4WERGZOaZCEREZES9vH3QeNht7//pHuy9/zkywsNBrs4iIiGIfWNy5cwcnTpxQC+a1atUKjx49Qp48eeDo6MjDSkSUAG7df4rmfafi1oOnatvKyhLjf22NLk1rqsJtIiIiowosgoODMWLECGzevFlNbSj/zH788Ue12vbDhw+xevVqpEmTJmFaS0RkpvYe/wedhs7C+4++atspmSOWT/oVFb8roO+mERERxa7GQgIIWSBv3LhxasRCggvRv39/FXRMnz49pg9JRESRkM9Yj6Vb0fTXKdqgIl+OTDi8aiKDCiIiMu7AQkYqevXqhYYNG6qF8TTy5s2r9kuwQURE8ePUxRsYO3e99iJO3SqlsG/ZWGRJn4qHmIiIjDuwePXqlQoiIpI6dWq8f/8+PtpFREQAvi+aF73b1FXHYmi3xlgx+Vc4JrLnsSEiIuOvscicOTOOHj2K77//PtxtZ86cUbcTEVH8GdGjGX6sUByli+ThYSUiItMJLNq0aaOKtwMCAlCpUiVVvP3gwQOcPn0aS5cuxaBBgxKmpUREJk7SnRb+vgfJkiRG058qaPfL7E8MKoiIyOQCi19++QVv3rzBb7/9hnXr1ql/hH379oWNjQ06duyIZs2aJUxLiYhM2Cf/ALhNWoLV2w7DztYGubKkQ7H8OfTdLCIiooRdx6JLly5o0aIFLly4gHfv3iFp0qQoXLhwqGLu6Pr06RNGjx6Nffv2wd7eHu3bt1dfUXn8+DHq1KmD+fPno1SpUrF5CUREBuO551u06u+Bs1duaYOM4+f+ZWBBRESmHVgMHjwY3bt3R8aMGVG+fPlQt929exdTpkxRHf7okvtfvXoVK1aswNOnTzFw4ECkS5cONWvWjPR3Ro0aBR8fn5g2nYjI4Jy7cgst+3ng+au3atvezgZzRnRDo5pl9d00IiKi+A8spMOv8ccff6Bq1aqwsrIKd79jx47h5MmT0X5yCQ42btyIRYsWIX/+/Orr1q1bWLNmTaSBxZ9//omPHz9G+zmIiAzVqj8Oo/e4hfAPCFTbGVI7Y7VHPxTJm03fTSMiIkqYwEJSlSRo0HB1dY3wflJvUbZs9K+y3bhxA4GBgShatKh2X/HixdWIhyy2Z2kZejbct2/fYurUqapIvHbt2tF+HiIiQxIQEIhhM1Zjwfrd2n1liubByil94ZIimV7bRkRElKCBxZgxY9RIhAQOQ4YMQbdu3ZApU6ZQ95EgQGotYlLz4OnpCScnJ9ja2mr3pUyZUtVdSO1GihQpQt1/0qRJqF+/PnLmzBnt5yAiMjTdR83Dxj1fFhPt0KgaJvZrC1ubWJW9ERERGYRo/ReThe+kQy9ketmKFSuG6/THhq+vb6igQmi2/f39Q+2XwOb8+fPYsWNHtB/fxsYKFhbQGzlWn38ArK1jvBYhmSCZNpSoa/Mfse3gachi2tOGdEC7hlV5UMwcPxuI5wNFKMQCVrCEja0VIF8GLsaXxyTAkBGFy5cvq86/jGIISV2SQOHcuXPo169ftB7Lzs4uXACh2ZYZojT8/PzU2hkjR44Mtf9rAgKCoE+aY4MQIDAwWK9tIcPBc4GK58+JuSO7IUuGVChZMBfPCeJnA/F/BUUsKAQWQcEI8A9CCPTbr02QwEIWwuvduze8vLwivD1x4sTRDixkJETqJqTOwtraWpseJcGDpFVpSBDz6NEj9OrVK9Tvd+rUCfXq1VOpWkREhkguuvy+6zga/1g+1FXpX34sp0YyGWgSEZGpiHFgMX36dFUXMXbsWDVDk9RWNGjQQBV3y4J5MsNTdOXNm1cFFBcvXkSJEiXUPkl3KliwYKjC7UKFCql1LnRVr14d48aNi1GxOBHRt+Tl7YPOw2dj7/F/cPvBMwzv0ZRvABERmawYJ3zfvHlTzQpVrVo1VKpUCc+ePVM1F8OHD0ejRo3UitzR5eDgoEYcZF0KGZU4cOCAmvGpdevW2tELSYOSEYzMmTOH+tKMeDg7O8f0JRARJbjbD56iWtuhKqgQM1Zsw91Hz3nkiYjIZFnGZlhfOvRCOviy7oRGjRo1cO3atRgvuCfrV7Rp00ZNa9uzZ081GiHKlSuHXbt2xbSJRER6tf/EBVRuPRT/3f+8BlDypImxadZgZMuYhu8MERGZrBinQsk0szJqIalLWbNmVQXbsuJ2tmzZVK1ETBevk1GLyZMnq6+w5HkiE9VtRET6mrBh5oo/MXrOOu3kDXmzZ8Baj/7IyqCCiIhMXIwDizp16sDd3V3902zZsiUKFCig6i1atWqlFrbLkSNHwrSUiMiA+fh+Qs+x87F570ntvtqVSuK30T2QJLGDXttGRERkkKlQHTt2RNOmTXHp0iW1LVPAXr9+Hd27d1cjFwMGDEiIdhIRGaznnm9Rs8OIUEHF4C6/qJW0GVQQEZG5iPGIhczWNHDgQO22zOAkRdeadChHR8f4biMRkUFL6phIlqtRHBPZY/4YVzVaQUREZE7iZRlgCSZkSlhvb2+1xgURkTlJ5GCHNR79ULJgTuxfPo5BBRERmaVojVgEBQVhxowZ2LJlCywsLNQUsb/++iusrKy0q2XL+hWLFy9W08MSEZky/4BAvHnnjTQuTtp9mdK6YN+yseozkoiIyBxFa8Ri1qxZKnDImDEj8uTJgyVLlmgXwpMF7WrXro3Zs2cjVapUqoCbiMhUvXj1DnW6jEYD1wn44BP6QgqDCiIiMmfRGrHYu3evmg1q6tSpaluCClllO3fu3GrdCRsbG7i5uaFt27bqZyIiU3Th2h20cHPH05dv1HbfCYuwcFxPfTeLiIjIeEYsXrx4oUYlNOrWrYunT5+qGaCKFy+OnTt3olOnTgwqiMhkrd95DDU7jNQGFelTO6N7i5/03SwiIiLjGrGQRfCcnL7kEqdIkUJ9L1WqlEqB4vA/EZmqwMAgjJy1BnPX7NTuK104N1ZO7YtUzsn12jYiIiKjnm5WM+WskNQnBhVEZKreen1A+8Ezcfj0Ze2+dg2rYnL/drC1idXHJxERkcmK039GBweuJktEpuna7Ydo3tcd95+8UNvWVlaYMqAd2jeqpu+mERERmV5gwdEKIjJV2w+d0QYVKZ2SqtSn74vm1XeziIiIjD+waNKkSbh9DRs2jDDYuHbtWtxbRkSkR/07NsDFG/fw9MVrrHbvh4xpU/L9ICIiimtg4erqGp27EREZreDgYG39mJCfF451hZWlpVpZm4iIiKLGwIKIzN7dR8/RZuB0TOnfDmWK5tEejySJWUdGREQUr+tYEBGZqoMnL6JSqyG4cvM+Wg+YhsfPX+m7SUREREaJ8yUSkVkKCQnBnFU7MHL2GgQHh6h9zsmTICAgUN9NIyIiMkoMLIjI7Pj6+aP3uAXYsPsv7b5aFUtgwVhXpj8RERHFEgMLIjIrj569Qst+7rh0455234BODTGoc6NQxdtEREQUMwwsiMhsnLxwHW0GTIfnGy+1ndjBDr+N6YG6lUvpu2lERETmGVi8efMGS5YswcmTJ+Hp6YnFixfjwIEDyJMnD6pWrRr/rSQiiqN33h/RtPdkvP/oq7Yzp0+FtR79kT9nJh5bIiKieBDjcf9Hjx6hbt262LBhA1KnTo3Xr18jKCgI9+7dQ69evXDkyJH4aBcRUbxKniQx3Ad1UD9X/K4ADq+cwKCCiIhInyMWkydPhrOzM1atWoVEiRKhQIECar+Hhwc+ffqE+fPn44cffojPNhIRxYvGtcojiWMiVPu+CKytrXhUiYiI9DlicerUKXTv3h1JkyaFhYVFqNuaNGmCW7duxWf7iIhi5eL1u5i2dGu4/T9WKM6ggoiIyFBqLKytI/41f3//cMEGEdG3tmHXcfQatwB+nwKQLrUzmv5UgW8CERGRoY1YlChRAgsWLICPj492nwQTwcHBWLduHYoVKxbfbSQiipagoGAMn7EanYfPUUGFWLv9qFoMj4iIiAxsxMLNzQ3NmjVD9erVUapUKRVUyAxRd+7cwYMHD7B27dqEaSkRURTevf+A9oNn4tDfl7X7WterjKkD23MklYiIyBBHLHLlyoVNmzapoOL06dOwsrJS085mypQJ69evR968eROmpUREkbh+5xEqtRqiDSqsrazgPrA9Zg7rDDtbGx43IiIiQxyxkKlls2bNqmaBIiLSt51HzqLL8Dn44OOntp2TJ8GKKX1Rrng+fTeNiIjIrMR4xKJcuXIYN24crly5kjAtIiKKptV/HkYLN3dtUFEwdxYcXj2RQQUREZExBBa1a9fG3r170bhxY9SsWVOtW/HkyZOEaR0RURQqly6M1M7J1c8NqpfB3iVjkCmtC48ZERGRHliExGK6FPmVv//+Gzt37sT+/fvh7e2tZoP6+eefVbCRJEkSGAJPT2+9Pn+Ko7lg5f8cwVZO8M45X69tIcNgbW2JwMBgfTfDpJy+dBN/X7yBXq3rGl2RNs8H4rlA/GygKAX6wCbICz6ZGiLENhn0xcUlScIFFroCAgJw4sQJFWTs3r1brXFx8eJFGAIGFmRo2JGMm7/OX0PBXFmQLEkimAKeD8RzgfjZQKYUWMQ4FUpXYGAg/vrrL+zatQvHjh1T+8qUKROXhyQiCkeuf8xdsxN1u45B5+Gz1bo5REREZOSzQoVNg/Ly8kKhQoXQq1cv1KpVC05OTgnTUiIyS75+/ugzYSF+33lcbe89/g9+33UczWpX1HfTiIiIKC6BRfny5fH69WukS5cOzZs3V3UVWbJkienDEBF91ZMXr9GynzsuXLur3devQ300qVWeR4+IiMjYA4vKlSujbt26KFGiRMK0iIgIUAXZrQdMw8vXXup4JLK3w7xR3VCvGtMtiYiITCKwGDNmTMK0hIjo/1ZsOYh+k5cgIDBIbWdK54I1Hv1U4TYREREZcWBRpUoVzJ07F3ny5FE/R0Wmezxw4EB8tY+IzEhgYBAGuS/H4o37tPvKl8iP5ZP6wNkpqV7bRkRERPEQWHz33XdInDix+rlkyZJGN1c8ERkHKytLvH73Zf2ZLk1/xLg+LWFjE+PBVSIiIvrG4ryORVhBQUGwsrKCIeA6FmRouG7B13309cPPXceibcOqaFm3EkwZzwfiuUD8bCCzXsdCUqFu3LgR4W2XL1/G999/H9OHJCIz9vrt+1DbiR3ssW/ZWJMPKoiIiExNtPILduzYoRbDE0+ePMG+ffsiDC5OnTqlVuImIvqaoKBgjJ27Hqu2HcLBlROQJX0q7W2WlnFau5OIiIgMNbC4cuUKVqxYoX6W+op58+ZFet927drFX+uIyCS98/6ITkNnYf+Ji2q7ed+pOLRyPOztbPXdNCIiIkrIwMLNzQ2tW7dWq25XrVoVc+bMQd68eUPdR+oqHB0d1RcRUWRu3nuM5n3dcefhs/9/dliibYMqsLO14UEjIiIy9cDC1tYW6dOnVz8fPHgQqVKlgo0NOwFEFDO7j51H52Gz4f3RV22nSJYEyyf3QYWSBXgoiYiIzCGwkBGKX375BalTp8bWrVujvK+kSvXo0SO+2kdEJkBGOz2WbsX43zaon0X+nJmwdlp/ZE73pbaCiIiIzCCwqFChggos5OeoMLAgIl0ffPzQY9Q8bDt4WruvXtXSmDuqm5oBioiIiMwosNCdASqyqWaJiCJy6sJ1bVAhFx6Gd2+CX9vV40KbREREJiZe5nT09PTEv//+qxbHIyLSVa1sUfTv2BBJEztg/fQB6Nu+PoMKIiIiExTjwOLDhw8YPHgw1qxZo7Z3796NSpUqoVGjRqhduzaePfs80wsRmSdNDYWuwV0a4a/fp6JG+WJ6aRMREREZYGDh4eGBvXv3Ilmyz8uKu7u7I0+ePKr2wtraWm0TkXny++SP7qN+w4otB0PtlwXvMqV10Vu7iIiIyEBqLHTJdLODBg1SoxNXr15VK3EPGDAAVapUUatzjxw5MmFaSkQG7ZnnG7R088D5f29j056/kDtbepQukkffzSIiIiJDDSzevXuHbNmyqZ+PHj2qRinKli2rtmUU49OnT/HfSiIyaGcu/4dW/Tzw4vU7tW1tZQXPN+/13SwiIiIy5FQoWSjv5s2b6ucDBw6gSJEi2tW2JdDIkCFD/LeSiAzWqm2HUbvzaG1QkTGtC/YuG4s6lb/Td9OIiIjIkAOLpk2bYtKkSahVqxauX7+O5s2bq/2urq5Yvny5up2ITF9AQCD6T1mKnmPmwz8gUO0rWzwfDq+agEK5s+i7eURERGToqVBt2rSBs7Mzzp49q4IJCTCEjY0NRo0ahSZNmiREO4nIgLx++x5tBk7HX+evafd1alIDE35tDRubGH+sEBERkQmwCIlobkgT4enprdfnT3E0F6z8nyPYygneOefrtS1kGKytLREYGAxjJh8ZtTqNwqkLnxfLtLG2gsfgjmhdr7K+m2Z0TOF8oPjBc4F4PlCEAn1gE+QFn0wNEWL7eUZWfXBxSZJwC+Tdu3cPv/76qyraLliwICpUqIC+ffvizp07sXk4IjIisnr2hL6tYW9ng1TOybBj4UgGFURERBTzVKjbt2+rOgorKytUrlwZKVOmVCtvHz58GEeOHMHGjRuRPXt2HloiE1Y0X3asnOKG/DkzIX1qZ303h4iIiIwxsJAF8GTmp1WrViFJki/DIt7e3qr+Yvr06WqxPCIyDV7ePvht3U70a98A1tZW2v3VyxXVa7uIiIjIsMQ4FUqKtrt27RoqqBCy3blzZ3U7EZmGW/efomqboZi0YBNGzV6r7+YQERGRKQUWsiCenZ1dhLfZ2trC398/PtpFRHq2768LqNJ6CG49eKq212w/As83XvpuFhEREZlKYCHF2mvXrlUzw+iS7TVr1qBAgQLx2T4i+sbkb3na0q1o0mcy3n/0VfvyZc+IwysnwCWF/makICIiIhOrsejduzeaNWuGunXrombNmnBxcVHF23v27FGzRS1btixhWkpECe6jrx9cR8/H1v2ntPvqVimFeaO6wzGRPd8BIiIiir/AQkYsFi9eDA8PD1WkLVc3ZfpJGalYtGgRSpYsGdOHJCID8ODpS7Rwc8fV/x5o9w3p2hj9OtSHpWWsZqYmIiIiMxKrJXJLly6tppX19fXF+/fvkTRpUjg4OMR/64jom/j31kPU6TIGb7w+LyqZJLEDFox1Ra2KJfgOEBERUfwGFq9fv8aWLVvw9OlTZM6cGXXq1IGzszMDCiITkC1jGmTJkEoFFvLz2mn9kSdbBn03i4iIiEwtsJBF8Vq0aAEvry8zwsybNw9z585l6hORCXCwt8Vq934YPWctJvdri+RJHfXdJCIiIjIy0UqcnjFjBhwdHbF69WpcunQJW7duVYvkjR07NuFbSETx7rnnW9x79DzUvnSpUmDBGFcGFURERJRwgcW5c+fQt29flChRQq1hkTdvXgwZMgS3bt3CmzdvYvfMRKQX567cQqVWgz9PJ/vBh+8CERERfbvAwtvbG+nSpQu1L0+ePGpGqFevXsVPS4gowa358whqdRqFZ55v8d/9pxg+YzWPOhEREX27GougoCBYWVmF2qeZBSogICB+WkJECSYwMAjDZqzC/HW7tfvKFM2DYd2b8KgTERGR/qabJSLj8eadN9oNnoGjZ65q93VoVA0T+7WFrQ0/AoiIiCh+xLlXIYvjEZHhrk/R3G0qHjx5qbZtrK3gPrAD2jSoou+mERERkbkGFk2aRJwy0bBhw3CBxrVr1+LeMiKKk20HT6P7yLn46PtJbadyToaVU/qidJE8PLJERESkn8DC1dU1/p+ZiBLU7QdPtUFF0XzZ1DoV6VM786gTERFRgmBgQWSi+rarhys378PW1gYzh3ZWi+ARERERJRRWbhKZiA8+fnBMZB8qLXHhuJ6qroK1UERERGQQ61gQkWE7cPIiCtdxxbGzX2Z+EjLrE4MKIiIi+hYYWBAZMVmkctbKP9G49yS8fueNtgNn4MHTzzNAEREREX1LTIUiMlI+vp/Qa+wCbNp7Qrvv+2J5kCJZEr22i4iIiMwTAwsiI/To2Su0cJuKyzfva/cN7vIL+ndsAEtLDkQSERGRkQQWb968wZIlS3Dy5El4enpi8eLFOHDgAPLkyYOqVavGfyuJSOvEP9fQZsB0vHr7Xm1Lwfb8Ma6oXakkjxIRERHpTYwvbT569Ah169bFhg0bkDp1arx+/RpBQUG4d+8eevXqhSNHjiRMS4nMnNRTLNm4Dz93HacNKrJmSI39y8cxqCAiIiLjG7GYPHkynJ2dsWrVKiRKlAgFChRQ+z08PPDp0yfMnz8fP/zwQ0K0lcisPX35BsNnrEZgUJDarlSqEJZO7A2nZI76bhoRERFRzEcsTp06he7duyNp0qThprFs0qQJbt26xcNKlABk1ezfxvRQP7u2rI2NswYxqCAiIiLjrrGwto741/z9/TlnPlEC+rlKKfy1fgoK5MzM40xERETGPWJRokQJLFiwAD4+Ptp9MnIRHByMdevWoVixYvHdRiKz9Puu4xg2fVW4/QwqiIiIyCRGLNzc3NCsWTNUr14dpUqVUkGFzBB1584dPHjwAGvXrk2YlhKZicDAIIyctQZz1+xU27mypkfrepX13SwiIiKi+B2xyJUrFzZv3qyCitOnT8PKykpNO5spUyasX78eefPmjelDEtH/vfX6gF96TdIGFeLKf1/WqiAiIiIyqRqLLFmyqFmgiCj+XLv9EM37uuP+kxdq29rKClMGtEP7RtV4mImIiMj0AounT59+9T7p0qWLbXuIzNKfh06j24i5+Oj7SW2ndEqKFVN+Rdli+fTdNCIiIqKECSwqV6781Zmfrl+/HtOHJTJLMunBpIWbMGXRZu2+wnmyYrV7P2RMm1KvbSMiIiJK0MBiwoQJ4QILmSHq3LlzquZCbiei6Jm4YBOmLv4SVDSqURazhndBIgc7HkIiIiIy7cCiQYMGEe5v0aIFJk6ciO3bt8do5W1ZrXv06NHYt28f7O3t0b59e/UVkSNHjmD69Ol4+PAhMmTIgD59+qBKlSoxfQlEBqPjL9Wx5s/DeOb5FqN7NUfPVnW4FgwRERGZT/F2VGlSsip3TEyZMgVXr17FihUrVP3GwIEDVY1GzZo1Q93vxo0bcHV1xYABA1CxYkX89ddf6N27NzZt2oQ8efLE58sg+mZSp0yONR798PqdN6p+X4RHnoiIiIxWvAYWly5dinRV7ohICtXGjRuxaNEi5M+fX33dunULa9asCRdY7NixA6VLl0br1q3VdubMmXHo0CHs3r2bgQUZhZCQECzZuB91K5eCUzJH7f6i+bLrtV1EREREegksBg8eHGEB6vPnz3H27Fk0atQo2o8loxCBgYEoWrSodl/x4sUxf/589ZiWll+W2ahfvz4CAgLCPYa3t3dMXwLRN+fr54/e4xZgw+6/sO3A39gwcxCsra34ThAREZH5BhZSoB2WFHM7OjqiU6dO6Nq1a7Qfy9PTE05OTrC1tdXuS5kypaq7ePfuHVKkSKHdnz176Ku6MrJx6tQpNG3aNKYvgeibevz8FVr288DF63fV9qG/L+PomSuowtQnIiIiMufAQtKWwnbyY8vX1zdUUCE02/7+/pH+3ps3b9CzZ08UK1YsyuJtGxsrfGVm3ASlnT3LArC2jvEi52QCTv5zHS3cPOD5xkttJ3awx8JxrqhRoZi+m0YGwMqKnwvEc4H42UBRCLGAFSxhY2sFyJepBRbNmzdX6VD16tWL85Pb2dmFCyA02zJDVERevXqFdu3aqXz1WbNmhUqXCisgIAj6JG38/AMQGBis17bQt7ds834MmLIMAYGfz8PM6VPh95kDkCdrRp4PpMXPBuK5QBHhZwMpQSGwCApGgH8QQqDffm2CBBY2NjYqfSk+pE6dGm/fvlV1Fpqib0mPkqAiadKk4e7/4sULbfH2ypUrQ6VKERkK/4BADJq6HEs379fuq/hdASyb2AepUibjPwsiIiIySTEOLGSKV5kiVoqmZZrXRIkShbuPTBcbHXnz5lUBxcWLF1GiRAm17/z58yhYsGC4kQiZQapjx45qvwQVLi4uMW06UYL76OuHRq4TceriDe2+7i1+wpheLVisTURERCYtxoHFqFGjEBQUhP79+0d6n+vXr0frsRwcHFRKlTymrNj98uVLLF26VC20pxm9SJIkiRrBWLBggVoYb9WqVdrbhNwm9yEyBIns7ZAxnYsKLOxsbTBjaCc0q11R380iIiIiMrzAYty4cfHaAKnXkMCiTZs2amYpKcquXr26uq1cuXIqyJDVvvfu3Qs/Pz/88ssvoX5fpqGdNGlSvLaJKC4F+zOHdsaHj75wa18fxQvk4MEkIiIis2ARoq0wjpzUNYwcOTLeZoP6Vjw99bvGRYqjuWDl/xzBVk7wzjlfr22hhBEUFIxbD54iT7YM0bq/zA7Ggjzi+UD8bCD+r6BoCfSBTZAXfDI1RIhtMuiLi0v0soOiNdfhmTNn8PHjx7i2icikvHv/AY17T0L1dsNx5+EzfTeHiIiISK84iTpRLNy4+xiVWw/FwVOX8P6DD1oPmKZGL4iIiIjMVYxrLIjM3c4jZ9Fl+Bx88PFT287Jk2BSv7Zc7IyIiIjMWrQDix49eoRbJTuy4tUDBw7EtV1EBic4OBhTF2/BxAUbtfsK5s6CNR79kCktpz8mIiIi8xbtwCJfvnxckI7MloxOdBs5F9sPndHua1C9DOaM6IZEDnZ6bRsRERGR0Y1YFCpUKGFbQ2SA7j9+geZ9p+LanUfaUbkRPZqiT9uf1c9ERERExBoLomgVal+/+1j9nNQxERaP74Xq5YryyBERERHp4KxQRF9Rs0JxDO3WGDkzp8PBFeMZVBARERHFNhVKVrd2cnKKzl2JjJ5/QCBsrK1CpTnJKtpdm9WCYyJ7vbaNiIiIyKhHLCZOnIiMGTMmfGuI9Ozpyzeo2WEEFm3YG2q/BBkMKoiIiIgix3UsiP7v9KWbaN1/Gl68fodLN+4hb/aMKF8iP48PERERUTQwsCACsHLrQbhNWoKAwCB1PNKndkbypIl5bIiIiIiiiYEFmbWAgEAMmbYyVOqTjFIsn9QHzk5J9do2IiIiImPCwILM1qu379Fm4HScOH9Nu69L0x8xrk9L2NjwT4OIiIgoJth7IrMkNRQt3Nzx+PkrtW1rY41pQzqiZd1K+m4aERERkVFiYEFmJzg4GF2Gz9EGFWlSOmGVe1+ULJhL300jIiIiMlpcII/MjqWlJRaN74lE9nYoUSAHDq+ewKCCiIiIKI44YkFmqWCuLPhz/nAUyJUZ9na2+m4OERERkdHjiAWZvJv3HsN1zHw1A5SuEgVzMqggIiIiiiccsSCTtvvYeXQeNhveH33hYG+LqQPa67tJRERERCaJgQWZpJCQEHgs3Yrxv21QP4uT/1zHBx8/OCay13fziIiIiEwOAwsyORI89Bg1D9sOntbuq1e1NOaO6obEDgwqiIiIiBICAwsyKfefvEQLt6n499ZDtW1hYYFh3Zugb7t66mciIiIiShgMLMhkHD1zFe0GzcAbL2+1nSSxAxaN64maFYrru2lEREREJo+BBZlMUNHAdTyCgoLVdo7MabHWoz9yZU2v76YRERERmQVON0smoXSR3GqxO1GtbBEcWDGeQQURERHRN8QRCzIJdrY2WDnFDau2HcKvbevByooxMxEREdG3xN4XGaWzV/7DjbuPQ+1LnTI5+nVowKCCiIiISA8YWJDRWf3nYfzUaTSa952Kd+8/6Ls5RERERMTAgoxJQEAgBkxZBtfR8+EfEIi7j55j1srt+m4WEREREbHGgozF67fv0XbQDBw/9692X6fGNTC4yy96bRcRERERfcbibTJ4l2/eRws3dzx65qm2bayt4DGoA1rXr6LvphERERHR/zGwIIO2dd8p9Bj9G3z8PqntVM7JsGqqG0oVzq3vphERERGRDgYWZLDG/7YBUxdv1m4Xy59dBRXpUzvrtV1EREREFB4DCzJYSR0dtD83/akCZgztBHs7W722iYiIiIgixsCCDJZry9q4dvsRCubOjG7NasHCwkLfTSIiIiKiSDCwIIPx8JknMqV10W5LIDFvVDcGFERERERGgAvkkd6FhIRg+rI/UOzn3jh48mKo2zhKQURERGQcGFiQXvn4fkKHITMxes46BAYFof2QWXjy4jXfFSIiIiIjw1Qo0mvqk6xPceXmfe2+Hi1+QloXJ74rREREREaGgQXpxV/nr6HNgGl4/c5bbSdJ7IAFY11Rq2IJviNERERERoiBBX3zeorFG/dhsPsKlfoksmVMg7XT+iNPtgx8N4iIiIiMFAML+mY++Qeg36QlWLXtsHZflTKFsWRCLyRP6sh3goiIiMiIMbCgb+bx81f448Df2u1eretgpGtzWFlxDgEiIiIiY8ceHX0z2TOlVXUUieztsGhcT4zp3ZJBBREREZGJ4IgFJajg4GBYWn6JX6U4+9L22XBJkYxHnoiIiMiEcMSCEkRgYBAGe6xAn/GLVMG2LgYVRERERKaHIxYU796880a7wTNw9MxVtV0wdxZ0alyDR5qIiIjIhDGwoHj1762HaO42FQ+evFTbNtZWsLPhaUZERERk6tjjo3iz7eBpdB85Fx99P6ntVM7JsHJKX5QukodHmYiIiMjEMbCgeCnQnrhgE6Yu3qzdVzRfNqx274f0qZ15hImIiIjMAAMLipP3H3zQZcRc7D56Truvca3ymDm0MxzsbXl0iYiIiMwEAwuKk+EzVmuDCktLC7U2RY8WP8HCwoJHloiIiMiMMLCgOBnRoykO/X1ZjVwsm9gblcsU5hElIiIiMkMMLChOnJ2S4vcZA2BvZ4tsGdPwaBIRERGZKQYWFG0+vp8wdt56uLWvj5ROSbX78+XIxKNIRGQCuo5Zgn+u3w+1T6YNT5HMERWK50HP5tXVhSRd+05exub9Z/Hfg2cIDg5BxjQp8GP5ImhcoxRsrEN3MwKDgrBp3xnsOn4RD5+9gq2NNXJnSYs2P1dAifzZYG7keHQcuQgD29dB3mzptfs/+PihWqdJSGxvix1z+8Pa2irU743+bQueeb7F/BEdwj3mwk2HsPPoBWyb7RZq/w7Zd/g87jx6obazZ0yFZj9+j8ql8sf763rq+RZTl+3AxRsPYG9ng58rFUenRpVhZRn5usy7j1/Eyu3H8eTlW2TPkBpdG1dBqUI5tLc/fPYa01fuwqX/HiKRvS3q/lAM7Rv8AGurL8fm9z2n8Puev/HqnTeypHNBl1+qoGzRXOq2m/eeYuKSP7F4dKdQv0Pxi4EFRcujZ6/Qwm0qLt+8jys372Pr3KGw4foUREQmp2rpAujbppZ229fPH6cv38a0lbtV4DCwQx3tbRMWbcOeE5fQrl5FtV86bP9cv4dFmw7h4Ol/MWdIGySyt1P3/eQfANcJK/Di9Tt0blQFhXJlUvu2H/kHruOXY1SPhqhZ1rzSaVdv/wtZ06cKFVSIvScuI0XSxHjt9QGHz15DtTIFY/0cISEhGDLzd5z79x46NaqEwR3rQsogD5+5hqGzNqBrkypoU7cC4ktgYBB6TVyBjGmcVSf+0fPXGLfwD1haWKDzL1Ui/B15vaN+24Iuv1RGldIFcPbKHfRzX4MZg1qjeL6seP/BF51HL0aWdCkxb1g7+H0KwIRFf+DFm/cY3qW+eowdR//BvPUHMKJbfeTJkg47jl1Af4+1WD6+C3JlTovcWdOpY71q+1/qfKWEwcCCvurkheto3X8aXr19r7YvXLuDa3ceoXCerDx6REQmxs7WBimTJwm1TzqJ1+8+xf5TV7SBhVwBl6Bg3vB2KJoni/a+mdI6o0zhnGgxaC5mrt6rOrJiwcZDuP3wOdZP7YnUzsm095cgRtY/8li+S42KaAIRUyejEiv+PK4632FtO/wPyhTJieev3mHLgbNxCiw27z+DI2evY9m4LsiTNZ12f9b6qVSguGDDIdT4vhDSpEyO+CAB5fNXXlg6pguSOjoge8bUePv+I2at2Yu29SqqUaqwZKSiaun8aF//B7WdOW1K3Lz/DIs3H1aBxc5jF1SAO6lPUyRPmljdZ2jneug0ajE6NPgB6VyccOTcdZQunANVShVQt8toxca9p3H26l0VWIiWtcuqEaJfqpeCYyL7eHm9FBoDC4ryKsfSTfsxcOpyNVwrsqRPjbXT+jH9iYjIzEiH0NrKMlTayfdFcoYKKjQkcJA0m2V/HP2cPmVrgz+PnEedisVCBRUakvbSsFpJFdRElqKV1sUJI7s1UCkxv05ZheRJEmHJmM74rtlw9G9XW6XS/PfguUrF6ta4KiqUyBthapD8b+s8egku3XyAM+vGqn3yGBpWVpaqjV0aVVYpXULSh+as24fL/z2Er18AUjknxS/VSqFF7bLqdun0uq/Yib/+uak60RrF8maJMF1JbD14DqlSJFUdb133nrzE1VuP0Kp2Wbz/6IfxC//Ag2evVGc7NjYfOIOyxXKFCio0mv5YBsXzZ4Vzcsdop8ZpdGxYCZ0bVQ63X9KfJL1NggoNSXOT4FHS5QrkyBjud2RUo17lEqH2yWNIypz0P+T2LOldtEGF5nZx4fp9FVikSOqII2ev4daD58iRKTUO/H1VBW/5sn8ZDZJjLe+tHPtWdcpFcsQoLhhYUIT8AwLRf/JSrNh6ULuvUqlCWDqxN5ySRfwBREREpkc6dn9fuo3df11E/Sol1T4//wDViY/qSnrJAtmwYONBXLvzBKmdk6p0lkK5I67Jc0mRVH1Fx6y1e1SHvUfTatp9c9ftQ49m1TGyWzZsP3oBA6atw8JRHVW6VVjSWZWgIqy+rWuhapkCKkhYv/uUSt+R4MTK0gKuE5ajVMEcanTBytIK2w6fw8w1e9RrzJUlLZZvO4bj529gXM/GqgMs069PW7ELb7w+RPo6jp67jrJFc4fbL6NAUkNQpkgulSo2ecl2NWrxa6sfEVPy+3cevUSt8kUjvF2u2kcUGGpM7tsMAYGfLyyGJW2MyMs3XuGCRxenzyNgL157RRhYyO0yOqPrqec79dwfPvohpVMSlTURFBysrdOQ24UmkJMgR4IyGSmT+wSHhKjalbCvr1yx3Dh2/joDiwTCwILCefHqHVoP8MDpS/9p98naFKN7tQhXQEZERJH8g31/CvavNsAi2E8vhyjE0h5+KZsgMGnpGP2e1EwcOv1vqM5pGpfkaFm7HNrW+5yL7/3BV135T5YkUaSPkzxJYm3HTwp4RdLEX65ix8bfl2/jzJU72DytT6ir1z9VKKrSW4Rrs+r459o9bNjzd7jAQq5gz167T9WRyBVtXY6J7FQKmLyuFMkSq6J1OxtrePv4qSv78viaNC3pxEqu/u1HL1Rg8d/9Zypl57uC2bWPF9noiwgODsa/dx6jQdXPgZpuELfr+CVULJFXjfLIl6T3SCpQ9yZVo3zMiHh//HzuJUkcu7SfZI6Rv7+RkaDTMczzadKf/P0DI/ydH8sVweodf6mRDTmGMgohAZaQ4KJq6YJYuvUoZqzaje5NqsHHzx8eK3aq0SVN4PPoxWsEBYdgdPeGyJYhlapNmbZyF9K6JFepeRrZM6TC2p0n1XtgGUUxOcUOAwsKxfONFyq1GoynL9+obfkQmzmsM5r+FH+FXURE5sDuzXZY+T/VextiGlhInYN0zkNCgGt3HsNjxS58VyC7Cio0s+lImosshCod9ch4f/RV352SJlZfwuuDT6xfi6Q6SQdb0qHCjm6UyB+65q9grkyq4DyshRsPoWDOjCqFK2xgMWnJdkxdtlN1VKWDL/n4cjFN2t6oWilVYCx5/4+fv8Gth8/V70jnVOTJlk6l10iAkTNzmq8uEuv1wRdBQcHa46Jx8sJ/apSjetkvI0HVvy+oUqykdqHW/1OzJCVNrshHRAIja+vPHeZkST6/T7E97r0nrVSpTRGR8yGiImjpNwQEBIXLghD2kYxytPm5vApA3aauUcdUAoPWdctj9tq9alRF3u+JvZtg4uI/Vd2Eg73t5xGKx57qdhllGuCxDr+2/lGbvibF2s8836kUNt3AQgJSeX/lPQh7/CnuGFhQKDKNbJUyhbFq22GkS5UCq93dUCz/l+neiIgoej6lqAuLV7/rdcTiU4ovMzhFl1yVl2JtTSG2pKHIrE2SXqIp3JbOY75s6XHhxn20+OlznUFY56/dU1eq82ZLh8QOdmrK2ks3H0aYPiUpLJI61KfVj+FqDjTKFc+NTGmcMXvNXnVlWzfdJuz0oZ+vRofu3Evh+Paj/2DtZFecv3Y33ONLR7XSd/lUYCGjItNX7Ual7/KrK94dhi+EU7LEKF8sj5oCVV57HVd37e+2rlNedWI7jlqkft/W2hr+gYEoHEEqltAEHlI8rUvSuES/qWvD/Y6kQ2kCiySJHVSKUEQk5Sxp4s8jDTLdrxz/yzcfRhr8SdpYp4aVUCxf+AlZpEBaRqwioltDoSt1imRqJEeX51tv9T2VzlT1uqSdUifTp1VNeHn7qnNu077T6pyRIEKUL55Hfb16660CpsDAYMxYvQcZUqXAvSeeKniS90VXgZwZ1ciFLs0x/1rwR7HDwIJCkT8090Ed4GBvp9arSB1Ps0QQEZkbGSn4EM3RArnCLB0lQySd+OY/lVWpKjKaIbMVCSlcHjZrgwogJA1Il3T+1u46qTrC0gkWdSsVU1ebpWg2bA6+pBVdu/tEFeFGJkkiB/RsXgMXrj9QaTBT+jbX3ia/K51Ojcv/PQpXrDxl2Q6VziWBQkQk/UkTUMkVcyk8l5Scy/9Z4v1HX2ye3kebDixBitAMGkjnV47NXxduokfT6ihdKDvm/X4AXt4RjxRI4bmkWukWestIxYkL/6kC91Z1y6kRDQ05lpIaJEXkEnhJsCB1IPL7Ya+6X7z5AEVyZ9Zu16tUApOXbseNe0/DHRN5DBmRSJcq4uMuxeUxVTRvZuw8fkGNZmlmXjr3710VXObKEvFCur/9fgB2ttZqVigJKsShM9dQqtDn1DJpo9TrzB7SRnv7/lMXVapYwVwZVfqVkJEkqXHRkPdJglFdb99/UAGvvAcU/5hcZubeen3AqQs3Qu2TK1FTBrRjUEFERIqsLyCd7klL/oSP3ye1T+oUpPZAZmhase2YGnWQxc2kOLrDiIVImzK5ugKt0b5eRfUYnUYtUvd5/OKNSrUaO38rdh27iCGdftZenY7q4pc8pkyfqjtbkXSQpTZEZk+auXqPmhlIZqXSePbqHV6/846yYPeDzye1sJoUEe/56xLeefuodRMkCJJUmwOnr6rbpM5D1n/QTfGR2Y5GzN2ERtW+Q5OapZE5nctXp83Nlz0Dbt7/kiq3+69Lqji5dd1yalYjCSA0X5JyJOtAyKiFkBoMmf3KbepqNZ2qjJZcufUII+duwtOXb9Gs1pfXLgGd1GnIqJOMAsisWtJemf51yZYj6NmiRrxNNatpm9SqyDGS90GK1Oeu34/mtb7XLpgo55Aca430qZyw8s/jOP7PTTx58UaNXsm5IeeMkPdBHmvW6r3qHJPHdF++U6VjSfAizycpY9NX7saxc9fVY8isZX8e+Qft6odO17px71momaIofnHEwoxdu/0Qzfu64/W799i/fBzyZMug7yYREZEBkgtOQzv9jG7jlqmry25tflL7JXVJRitktePVO06ojrakTzWuURqNa4ZeeVtW7F4wooMa+ZBARNY6kKJumTb0txHto5ydSFfh3JnVatGz1uzBsrFd1D6ZrWrdrlPqin7OTGnUlW2pddDVr03tCNdQ0JBCX/mSDrxcFe9Qv6KaFUpqFm7UKYcZq/aoKVPTuSRH3UrFcezcDTVSUsvPX43cyGiArC4dXT+UyIsdxz4XKGsWePuuQDYVlISVIXUKVCyZVwUfUv8iAZgcy982HMSY+VvUaEeSRPYonCezmrlK7q8hBcpT3Zpjw97T+OPQOdXJl7S2bBlTYUrfZtppeeOLqs0c1BpTlm5H++ELVMqUFL7LehMacq7IGhWa6X7leMprkN+RVC4ZkZGF8DTHQuoipg1oqYq3t/Y/h5TJHVX6lm4ANaxLfSyTAu/Ve/D63QdkTpcS43s2DreyuKTB1a5QLF5fM31hESJ/MSbK0/NLNKwPKY7mgpX/cwRbOcE753wYku2HzqDriDnqQ1KUKpwLe5aMYc5hAjPkdAf69ng+EM+FuJM1KEZ0rY/aFY2rsyg1AfV6TcPcoe3CXUHnZ0PCkKmPe4xfhj9m9Y3VjFd6EegDmyAv+GRqiBDb8GvAfCsuLqEXzYwMU6HMjBS0TVywEa36e2iDCllBe/H43gwqiIiIvhHp2Ep60LrdJ3nMvxE51nLMjSaoMEIMLMyIzP7Qqv80TF64SbuvUY2y2L14NDLGckVPIiIiih2pEXjw9JWqJ6CEJcXrcqwjmiKX4g9TocwkFeruo+do4TYV1///4SUFcKN7NUfPVnU4UvENcXibeD4QPxuI/yvIVFOhWLxtBo6cvow2A2fAy/vztHZJHRNh6cTeqPr95/mwiYiIiIjiioGFGZDFYLw/fp5LO3fW9Fg7rT+yZ0qr72YRERERkQlhYGEGKpcpjNE9W+DEhetYONZVjVgQEREREcUnBhYm6PXb90iRPEmo2gnXVrXRo+VPaj5rIiIiIqL4xl6mifn74g2UadIPc1bvCLVfggwGFURERESUUBhYmJAVWw6iTpcxePnaCyNnrcHRM1f03SQiIiIiMhNMhTIB/gGBGOy+HEs27dfuK18iPwrmyqLXdhERERGR+WBgYeQ833ihzcDpOPnPde2+bs1rYWzvlrC2ttJr24iIyPgEBgVh074z2HX8Ih4+ewVbG2vkzpIWbX6ugBL5s8HQtB7yG/q2roX8OdKj79Q1aFyjNMoXy63vZlECO3L2GnYcvQD3fi1C7Z/3+34s/+OYOiea/lgm1G1PPd+iXq9p+G14exTPlzXcY37XbDhGdK2P2hWLafc9efkWq7Yfx6mLt/Da6wOckzuiXNHcaFe/IlImj97aDjGxcd9prNl5Aq/feiNPtvTo17IyCmR0iPT+ly9fRPfuHcPtnzVrPooVK4ENG9bh6dMn6NOnH74FBhZG7OL1u2jp5o7HL16rbTtbG0wf0gnN63BVSSIiirlP/gFwnbACL16/Q+dGVVAoVya1b/uRf+A6fjlG9WiImmULG9Sh7dq4CvpMXolPAYH4rkB2fF8kp76bRAns/QdfuC/fqQIEXcHBwdh17CIyp0uJrQfPhgssYurSzQf4dcpqFMubBSO6NUBal+R49Ow15q7fj04jF2HRqE5I6RR/wcWOoxcwa81eDO30M3JlSYsVfx6D6+T12DqxKewi+Z07d24jffoMmDdvcaj9SZN+XkyvQYNf0KpVY1y6dBGFCyf8+mWssTBSm/acQM0OI7RBRVoXJ+xaNIpBBRERxdqCjYdw++Fz1WGqXbEoMqV1Rs7MadC3TS38VKEoPJbvgo/fJ4M6wt8XyYW9CwZhx5z+mDmoNaw4+6HJW7/7JArkzIiMaZxD7T99+Q5evnmPns2q494TT/xz/X6c0syHzd6IEvmzYqpbczXCkc7FCaUK5cCcIW3h7eOHRZsPIT4t33YUjWuUQs1yhZEtQyoM71If9nY22HL0WqS/I4FF1qzZ4OycMtSXjY2Nut3a2hqNGjXBwoVz8S1wxMII+X3yx8QFG+H3KUBtlyyYE6umuiGNi5O+m0ZEREYqMDAIfx45jzoViyG18+ernWFHBhpWK6lGx8WOo/9gzPyt4e6XNmVybJvthv4ea/HBxy/UVeUHTz3xi9ssrJviimYD5oRLO9FNRZGO3fwNB3Dw9L/wfOONRPa2KFkgGwa0rwOnpInDpbVIu/44eA4TFm/TPsbo37bgmedbzB/RQfscYffde/ISc9buw6X/HiIoKBilCmZH75Y/qqvTIiQkBKu2/4UtB8/i9bsPKthqVbuc6vxFZNrKXTh+/ga2zuyr3SfH4ceukzGxT1O88/4Y7rgtGdNZpaAt3HgIN+49Va89fSontKtXET+WLxIuzSesM+vGRvjadIU9XnLfnccuaGeOTJLIHuWK5cbgjnXVsYzp8Y/oObqOWaIufI7s1kDd/vb9RzTqOwM5M6UJdfxnrt6DC9cfIJGDrUq3692yZqRpRjKCtnHfGQzsUCfcbduP/oMcGVOjfPE86hzecuCMGm2Ijb/+uYkXr73g0a9FqOn7RVJHB8wa1BrOkbTx/LV76DZ2aaSPrXm/dL3x+oCHz16jZIHs2n3WVlYomjsj/rn5DM0ieaw7d26hUKGoRyIqVaqKWbOm4fr1f5E3b34kJAYWRsjezhZrPPqhapuhqF+tDNwHddB+0BMREcXGk5dvVIpJodyZIrzdJUVS9RXWrt8GaH9es+MEDp3+V/1cp2JR9J+2TnXONIHKzmMXkS97emTPmPqr7Zm9di+O/3MTI7tKCoqTGkkZPX8Llm09qkZQwvL64KM63jHxzPMdOoxYhO8KZsdvw9rjU0CA6uR2GbMYaye7wjGRPX77/QD2nryM/m1rI0t6F1y4fh+Tl25XwUKj6qXCPaYEZut3n8LFGw9QJE9mtW//qStIktgBZYrkxO7jF8Mdt4CAIDTuN0tdrR7S6WcVzCzdehTjFv6B7wrmUHn9ws8vAG3qlkeT/6f4HDh1VQUysVUwZ0ZM7ttMBVS3HjzHwOnrVPpbg6olY3z8o0MCOO+Pftptzzfv0XnUEtQsVwh9Wv4I30/+WLjpEDqMWIj1U3rCwd423GPIcfX+6Bsu5U3e/2Pnb6BdvQoqEKhaugA27P0b795/RPKkiWPc1ut3n8DBzlaN2EUkX/YMkf5uoVwZQ72/0SEjLSK1c+i/sZTJHXHrwbNIf+/evTtInjw5OnRoBU/Pl8iWLTs6d+6OfPkKaO+TIoUzcufOi+PHjzKwoM/kQ0Y3Ys6TLQP+Wj8VmdO5hIukiYjIMMiaQvPW7Pzq/YrkzYq100J3RJr+OgWXb9z76u92b/ETXFvW1m5Lp6tUo77h9n+N1wdf9T1p4sgLRSOie2VZtyP4fdFcSJEssepIt61X8XP+u/z8cwXt83z0jTytKl+29KhcKj+K5vl8xVlGEGQ04fajFxHeXwIAudp94O+r0W77pv2n1ZX4MT0aqSJ1IaMK9XtNw56/Lqn0r3W7TmJsz1/U1XyRIXUKNSogoxgRBRbSEc2TNR12/3VRG1hIQCUjHLppWrrH7fGLN+jcqDJa1i6r/qdbW1uq46QK6J+/0gYWH3z9kDplau3vOiaKLPM+emysrbSPJSluVlaW2seM6fH/miu3HuHIuWsoXSiHGg0Rmw+cQSrnpHBr85P2fhN7N0G1zpNw8PTVUKNZGldvP1JtSWQf+rXvPXFZPW61MoXUdvXvC6oi6O1HL6BVnXIxbu/7j75Iktg+Vn0sG2vrGBd2a7JQbK1DX/O3s7XWHq+wXrx4jg8fPsDHx1cVZ1taWmHLlt/h6toF/2vvLMCjuL42fkIgkKDBixd310LRosUpFgotEqy4luIUd3cLUIpb+QOllEJLKVDcg3uB4BIkIfs97803y+xkNyTZhE2y7+95lrCzd2fvzNydPe+RexctWq5SpDQgOM6cifplCBixiAFs23tYFq/7TUUp9JGJLOlTO7RfhBBCQgdG/p37jz54mjIYcsXBw8fPwvRefIbREYX3Gbd/CKS3aJ7fyABpHDXLFZbt+04oYXH4zFV58txfqn0WbPjl+vQTVaxatUwBlVqCFCA9SAE6dOqyzPx5p5qd6vqd4IdmrBu9yzv3n5JVE7qGEBbwcFf49n3qydvAQCmUMzgqc/nmPcmdNZ1ZVAAYhJnSpVQGNNJ0UBQ+eOY6iaMzMN8FBSlj7/XbAElgJWOgbsWiMmfNLmUwI2Jz8sINGdi+ns1zBbGCCM/qHQfU596+90gu/L+XOijIZG53+95jFV0JDe14IU5SeSaRyiXzqvMfWtsgk0mlGMFg/7xo7nCd/x5jl5kX4DXJ+77qgaicsGSreDeqLL7X/lPCDPhe/U+u3LxvcX0Azi1qJKyBdDTPpMFCSw8mGICgQ6oayJM1varB2LT73/eCzdU1xDnV9xFobZIlTqjEttGxGxaOnb8mPcYut/n63qWDQ2yDgNDGp543bwNVnYU10qRJK9u3/yHu7u6qlgLkyZNXfH19Zf361dKnzwBz22TJPOX0aQoLpwaDfOKijTJ67hr1vO+4xTJtUHtGKAghJIaA9Jd0qZN/sF1Kz5ApRik8k4TpvfgMPTCC8D7j9g+BnP7kSRPJCd8bytg3AiN7ss826dGyZphSmTQDe8XWfcrwh8AoXyy3EhGgX+va0m/yz1Kz03hltBtn1xmzcIvyWiNqgPflbPiJ2peWMqIBww9GK+oRUltJ1YKBOaLLV+bnMJSfPg8WTybrdrCYgkzKwITBDUZ3bypZ0qUM0c7NxrTu1csWVClVyNOHUMiXLYN8Gooz8Mqt+9J+2EJlGEM4fFE6n4rofDtonoVNcPnWPclkRYRaO17UbFy780AmLN4qz16+Fq8vP7PZFofp9/iZjJizQab9tEO+b1s3zOd/YPv6ki97BnNqU0crtQUbdv2r+tO4eikZOW/T+2MymVRxNOo2jKDmwxoY35oI0IAIg2DBa2VaDLXYP8YHBBKKrpMkDN7nC/+QohtpgEAbn0gJW7Jpr9ovrouRZVv+UjUlOFfWzuuKsZ0lPGjpgn6Pn1uMlQdPXkhqT9upXIkTW35vIPKyZPlU7t+/b7E9KOidxIkT9RkujFhEU5C72XnYbNny+0HdtlequC6ezrNCCCEk+oJUpLCkI8G7HBhoaSytmhK+HG0NCIqz2+eE+30wSOpWKiprfz2oUkeMBdxI/Tl75baaGQfAGNV78a2BmgTk8SOK8OeRczKySxPza0jlRYThwePn4uYWV5Im8lDF2wCRDUwXOqpbEwuRA0MZee9GTzVSqprbmFoUnmD97EFIodGERfZMaVTKEzzkWtQCHvGbdx9Ko6olJUu6VCo96N6DJxZrY6ze8Y9cueWnCp1tXYMKJfKotRYuXL8rja2kTBkNb6SNzRz4rXk8/HEweCYgGMbg9KVbqhYC05CGhv54YaCeOH9dGdbWhIW+LTz9VUrnl7+P+Ybr/KPuRtsHzpURFKvPXfu7mlnJOGNXtoypVaQJY007/4iYDZu9Xlp8WdbquikQoCgCN44BCMG5Q9pIQvf3KVIYFyiixrFAWKBGFQLx2PnrUqmkZRHzMd/rSphoIqJkgaySLrWnLN64R8b1bG7h1EWh9cpt+22ul5LALV6IGas+BEQ9psk9evaqmjYZQIwd870pTSrltfqeAwf2y+DB/cXHZ5WkS5c++D2BgXLp0gWpUKGyRdvHjx9LypSpJKrhdLPRkGu37km11oPNogKDeVhXL1k0ujtFBSGEkCijTf0KyiDyHrZA5fcj9//s5Vvy49yNan0AFBajjgKG3bU7flaLa43UqVhU1vx6UBlbJQtapvHg9w2GKUSFnkTu8VXh9N7D55SRj8Lh0Qs2q3SpAEOqyI6/T0qfb2tHaFFYiAf/129l6Kx1qnj5zKVbMmDaKkma2EPl6KMPDauUkLlrfle1IkhR2vLHEZmxcqcqqg2NuhWLyR//nlPvwb5CA4b1vYfPZP/xC6qgHDMxoUBcK+yGs9Fn859SoXgeZfQ/ePJcPV74B9eo6A3tgMB36rW7D57IgZOX5I9/z0qebMFGpxGtLSINuM4HTlxUxm14zv+H+PvYBSlbJKe5VkNPo6qllPE/ZOZaFXXAY+C0NXLu8m2bUTFER+4+eGpO2UN/duw7KZVL5VVRBrxPe+A5Uu/2HjmvjhO0qlteLQCJ83ldpXj5qbGOyA6uNQx8rU5iUPv66hz2nbxSTV2LxfIgFiFWErq7SaemX0hk0qJWWfnpf/tViiCiWD/O26hS1BpUyGNu8/DhA/H3Dz72ggULqRSnkSOHyvnz59TUs/j/06dPpWlTL4t9X7hw3qKgO6qg6zuasefgSWk9YJo8fvpCPU+SyEMWjuom1coVcXTXCCGExHLg0Z03pK1KeYHhBQMO+d1YeXvOkDZm4xCz9iBlo1UYimLh8Z609H9S6/PCYV5jAiIBRbxIJ/LqN1Olp2D60s5NvxCfLX+padc1kDaEaVAjAqIvcwe3UUKhzZD54hbPVUoVyK6KubVUsp6taqr6E3jdEV2BCECh9YcKgtGnZIk9VD3Hh9LSmtYorYTakFnrVGYCogcwWjFD0tkrt2TnP6fUDE0ARrCRbwfOVVP8akXStTqNV6INUZAyhXJI9xY1VOG3Ea0tgJAolCuTqgsJz/n/ENhvN68aNtPvcP5nqgXnFqqIB87X7MFtzDU/RjB9LNKkjpy5qorL/zriq0QGVly3hletz9S0upt3H5G2DSuq9VncE8RTM3ct3fynBL4LUv1AhKR5LcuoFyImC4d7y7LNfynxA1GXyjOxqkP5tn55swiJLOpXKa6uE6b5RX1HnqzpZGb/5uKZOIFolU/16tWQ1q29pW3bDuLhkVCmTp0tc+ZMl969u8ibN2/U1LOzZs1XM0HpoxVXr16RAQPep4lFFS4mLcYWC/HzC1anjiL53pzi+vauBLl6yvMcc0Nti8swe+U2GTx1ubmoKGeWdLJycl/Jnjlkbh+JmVhLdyDOC8cDcYaxAC9vox5TZM2k7ubCWmcAsyzBaB/fy+uDBdcfGg9YcwKF1RA01tZMQG2EJiycAUwrjAjTlH4tJdYT6C/x3j0V/0yNxOQWcn2ZsLBy5XLZt29viNW5w0OqVGGb5YqpUNGENdv3ycDJy8yionq5ovLb0lEUFYQQQmIkmA0Ja1qMmr9Jec2dRVSgCBjHjSLltCmTRTiaogdTwGJaXFtTxkZknYaYDKILSJe6ZmPmKPKegIAA2bRpnbRr11E+BhQW0YSGVctIuWLBxTm92zRQkQrkeBJCCCExESxMNmLuBjXtrbVZf2IrmIoWC9v5Xrsjwzs3ipSZHJGe9HVt66lXqCPwGfVxjMboAmpy+rSuLdNX/urorkR7NmxYI6VLfyZFixb/KJ/HVKhokgoFHjx+JgeO+0rtSiWislvEgcTmdAcSfjgeCMcC4b2BRHUqVGTAVKhozvLNf8ipC9dCzGNOUUEIIYQQQmIinBXqIxMQECg/TF4mC9b8KpnSpZI/lo1WiyARQgghhBASk3F4jQWmxvrhhx+kePHiUq5cOVm8OOSKjRpnz56Vxo0bS6FChaRRo0Zy+vRpiUkg1an+d6OUqAA37vjJpl0HHN0tQgghhBBCYr6wGD9+vBIIPj4+MnToUJk5c6bs2LEjRDssBtK+fXslQDZs2CBFihSRDh06mBcJie6c9L0mFb8eIH8fCV5JEytMzhzaUdo2ruborhFCCCGEEBKzhQVEwdq1a2XgwIGSL18+qVq1qrRr105++umnEG23bdsm8ePHl379+km2bNnUexImTGhVhEQ3Vu9/K9VbD5Zbdx+o52lTesr/FgyVr+tWcnTXCCGERDdMJnF5/Exc7txXf/GcEEJiAg6tsTh//rwEBgaq6INGsWLFZO7cuRIUFCRxdCt0njhxQr2mTduGv0WLFpXjx49Lw4YNJTry7p1JBq0SGfvLS/O24vmzy/KJveWTVMkd2jdCCCHRjOcvxe2XveK2eoe43rpn3vwuQxp527SGvK1TQSSxc61XQAiJWTg0YuHn5yeenp7i5vZ+0ZeUKVOquosnT56EaJs6dWqLbSlSpJC7d+9KdAQraTee9ETG/vJ+m1edCrJ1/lCKCkIIIRa4/n1cktTsJAkmL5M4t+9bvIbn2I7X4+4/zjNHCIm2ODRi8erVKwtRAbTnb9++DVNbY7voAiIqVQq4yZZ/34hrHJFRPbykQ5MvxMUlUCQw0NHdI47C5CLyjmkNhOOBvCfugVMSv+fU4BQoK2lP2jbT67fi0X2c+E/pIYGlC0TpAm8bdx+XrX+dlKu3H4iraxz5NF1KqVexkNQpXzBSFnwjIi/8X0uz7xfKilFtJCjIJC0HL5bVY70lkUcCp/6t2HXwnCzY8Jfc8XsqmdOlkG7NK0vJfFlstn/64pXMXrtX/j52SV6+eiPZM6WW75pUlMK5MprbrN55WNbsPCz3Hj2T9Kk95etapdRY1jhx4ZZ4/7g8xL7n/OAlxfJkFkfi8u61xCQcKixQM2EUBtrzBAkShKmtsZ2eePFcxZH3v8510siNu8+lRvFk8lmNkiJBzxzXGRItcJU44vKOC+QRjgfy/zz3F/fvZ9oUFXrwOlp4fD9TXm0aJpLYI9JPY0DgO+k7fbucvnpfOtQrIWXyV1JCY/+pmzL1p12y78g5mdi1urjqUpVJxPCML9KwYm6p1XWGynJoX6+EeMZ/I/LujdP+Vvx77rYMmfOL9Gz2mZTJl1E2/XlOek1cIz+PaCxZ01lPIR88c4s8fOovYzpWkRRJPeTn305Kt/Gr5OfhjSXLJ56yfs8ZmbX6bxnSuqIUzJ5WDp65JaMXbRNP9yCpVPRTtY8r169LxtRJZPEPlqn1SRPFV4vTOZo47kklXvz4IvFcJbrjUGGRJk0aefz4saqziBs3rjnlCWIhSZIkIdo+eBBc/KyB58b0KD0BAe/EoWQfImM7TRX/DO3FP9WXju0LiRbEc3OVgLcOHpck2sDxQBIsXCTyOuCDosJCXLwOkKADAfK6baNIP4GLfZbJ0UsPZOHsuZI503uPb8PSIvkrXpT2XbrKwv2B0tKrOS9eJNCyayNp0PqF+n+iRInE38nvDQtn9pfyn5eX+m0Hq+cdSoscvdFVlu1/Lv16eYdof+v2bTlwZrbMmT5NcufPr7Z1LWGSfS1byeazruJdqpE8cguUju3zS4X/r8etUUxk1b5bsu96PClVP/g7dP7JLcmcPb94FGxpsf+A/384mnhwrpsSiMSAMeFQYZEnTx4lKFCAjWlkwZEjR6RAgQIWhdsAa1csWLBAqXqEYfH36NGj0rFjR4muvE1TXyRjI3kbAwYC+Ui4uYpJOB4IxwMJnv3JfalPhE6F+5Kl8qpjD+TdRtqpxKQp6zZtklq16kim7PlVdERPjnzFpXr1WrJu02bxatVe7t27K40b17W6r7Vrt8jixfNl+/atIV4rXLiozJw5X8qVKy4//DBUfR74998D0rNnF2nd2lvatu0gixbNkyVLFkiuXHlk0aL3aSpHjx6Wbt06Stq0n8i6dcGFjCdOHFPtz58/JwEBbyVduvTSqlUb1V8NfJ41pk+fK0WLFpcuXdrLJ5+kk4EDh1ltZ+11/bZt236R0aOHy759h62+/6uv6kjNmrXVsenbJkyeVL0+bPgg+e23HercZc6cMcRvxahRw6yeT+xT69Pp0ydl/vzZ4ut7TtlXZcuWl+++6y5JkyYz96F27Xpy8uRxOX78mKRKlUpatvxWateub95fWPZx9+5/5vYlS5aRyZNnWPTpv//u2BwbAMeI82Ycf6fOnJEuXXqKyS34nICixUvL3r27LbZpJEkZRyZMmCq58pcQky5d3iWOqzz3f6veg7EKMJ7hyMa+rt+4Ia3bdDTv89LV61KwYGGrnxEtiOcaI0SFw4WFu7u71K9fX4YNGyajR4+W+/fvqwXyxowZY45eJE6cWEUwatSoIZMmTZJRo0ZJs2bNZNWqVaruombNmo48BEIIISRCuDx6JK7Xrob/fSaTep/L40diSp4i0s7+zZs35OnTp1KgQGGbbYoVKyFbt26WO3dui6trcFrGqFHjJX/+gmajdODAfur/3bv3kY4du8j9+/fE2/sbc7t48eKF2C8MvilTJoTYnjhxErl8+aKaqCVt2rRqG4xvN7f45jZ+fvelV68u0qhRU+nXb6AEBATITz/5yNixP0qJEqUkue4cdevWW6pUqar+r/UrOnD8+FF1XB8C5w/nUUM71+Ds2dPStWsHqVu3gfTq1V8ePXookyePU2JtwQIf8/Xy8VkkLVu2lh49+sg///wt48ePFnd3D6lSpVqY99Gs2dfSvPnX6v/x4lnWv4LUqdPI5s22jydZMs8Q2168eK7sOrxXT8qUqdS1sgZsxDJlylls27Pnd7l166a61nogPnFsEDBffllXPv+8gvm1q1cvS7JkyaRt25ZqPGXNmk3at+8sefMGR0FI2HF4kuSAAQPUGhbffPONDB8+XLp27SrVqgUvGoeVuLF+hRYinDdvnopoYHpZTD87f/588fCI/BxTQgghJKpxefnCvve/sO/9Rp49C84lT5rUttcWxhd48uSxhfGfIkVK9cD/NfC7jW2aEam1S5Ik5P5XrVqhXk+TJlg8aGC9KkQT/vprj3oO0bBnz24pW/Zzi3pLRAE6deoqGTJklE8/zaoMZ7SFWNKj9UnfL0cDUQXjvXLlYMETGoggaP3HQ0sjB6tW/STZsuWQnj37SZYsn6rzNnToKLlw4bwcOvSPuV2JEqWlTZv2kilTFmnatIVUqlRF1qz5OVz7gGNY64MxdR1AgOj7aXxoAkXP69fBRcr2TNRz6tQJGT16hFSoUEk++8xScGTKlFkWLVoh338/SHbv3iVz5gRHWRB5e/Hihfj7v1Jia8yYSWrW0S5dOsjVq1fC9LkkmkQstME5btw49TDi6+tr8bxgwYKycePGj9g7QgghJGowJUxk3/sT2fd+I1qqy8tQBM+zZ8/V38g0yuGNXr58iUyfPk8GDuwb4vXy5SvJ77/vlMaNm8mBA3+ryAWM3nPnzqjX06fPILVq1ZW1a1fJlSuXlLf60qWL6rV378KXPrJz53bl8YYxC5FTo8aX0rhxc/NMWNrrGpge35jSU7Xq5+LiEkeSJ0+u0mvatesYwguvZ8OGNcrrX69eQ9m9+zeJKDh2iAY9OXLkVGLq8uVLZs9+0aLFLNrkz19I9u/fF659fAhEmFq2bGzz9eXL15ojUPpJekB4J+rRgPgcPnyQFChQSIYMGRnidU/P5OqB40F9L9LsvL07qeu8ffsfyh7VhFqePHmVDbp+/Wrp02dAmI6ZRBNhQQghhDgjpuTJ5V2WTyXO9WthLt5W73NxkaDMWcTkGbkLrcJAhzcZufcVKlS22ubYsSOqDYxpW+kp4WXGjClSrVotyZUrt9XXy5evKFOnTlDrW/32269StWoNlTKjAa9y587t1PuR+gRvNYRPRNKcypUrL506dVPG7MWLvjJx4hiVOoPUH/3rGjBkjSxZslK95+HDB7JgwRzp27e7+Pissvp5aLN48QKZNGmGvHlj37SiqD21tV0f2dD/HwQFvTPXtYZ1Hx8Ca5LhPIT2uhFEsmDcP3zoZ7H9wQM/SZXK9kQ9AAJg2rRJKvoyaNAIi3S7Awf2K/GASJYGojK4xkj9Q1+QUqUH5wPiFSn6JIalQhFCCCFOiYuLvGrXIUJvfeXdMVILtwHSU5o29ZKtWzfJNSu1H1euXJYdO7ZKo0ZNrKayRIQjRw4psQLPsS1QI5EvXwFVg/DPP/vkiy+qW7y+efN6FR2YOnW2tGjxjfKqP3z40KKNZjAbJ4Yx4uGRUKVTIccehd8lS5ZW/TO+rj00L7sebEfaTZEixcTLq5Xy9GtpZkZmz54mFStWlnz57M/lh7GMomw9Fy9ekJcvX0qWLO+N6nPnzlq0OXXqpOTMmTtc+/gQECH682R8WBMpiAqhvkd/vrVi/UKFitj8rI0b16n6nIYNm8iwYaND1PBA3C1dutBiG2pJkPKHcQPhgSgT6oY0kJ526dIFCzFCwgaFBSGEEOIgXjf1EnH3EFMY14VQ7dw95HWTqJnuFZ750qXLSpcu3rJhw1qVVoQH/t+1a3tVvA3jPbL49dftqsDbWp6+HkQhFi6cI7lz5w2RVoTniJ6gEBmzFWHWn0mTxqrX4JVGdMPX97x6jiLl0EBqE6IImNUI+zl69IjkyZMvXMeE96MAGMYrzhsiQdbqSgCM2o4du0pkgHoJGMNTpoxXwhAG+YgRgyRnzlxSvHhJc7tdu36V9evXqPqTlSuXyZ9//qEEUHj2EVU0a9ZCdu3aqWpurl+/poQXIkdNmniZ2yCNCTUR4MaN6zJt2kSVLofZrVBsjvOPh9bGy6ulSjFDVANjecuWjbJy5XJVZwKhWbBgIRXhGjlyqJpVDEIQ/0c0A0KbhA+mQhFCCCEOwpQ0mTxdvFyStmisRINLUFDoosLFRZ4uWaHeFxXA0Prxx7FqWlMYYPPnz1LefnjwURz95Zf1InXlbUQiMEPPhyhfvrJMnz5ZpUEZ+eqrZsoI/fHHIapgO2PGjGpGH0x3e/78WfXA/zHDD4qRQwMGKB44D5iNqFat2majO6zUqxfcR9QlQAiNGTPRZltEarSCeHtB1AMpVfDQt2nTQkVXPv+8onTq1MUiQoDpff/8c4/MmjVVRQ9GjBgjZcqUDdc+ogpEiAYMGKIiDPPnz1HpSOPHT5XMmd+vvO3t3UpFgzDFLupdEF2AOMLD2jS8mO0KbVasWCqzZk1TaVE9e/aVOnWCp9jFMSLaNWfOdOndu4sSl6iNmTVrvsWMYiRsuJhsJdTFAvz8govMHImbmyvXsSAcD4T3BxIqHn/tFo+WLUReBS+Rpq+5QE2Fwt1DiYqASlV4NmM5UWU76NfSIDEHt2hgS6ZKZVmHYgumQhFCCCEOJrBKVXl44py8HDlWFWbrwXNsf3jyPEUFISRaw1QoQgghJBqA9KZX3p3kVbuOavE7rFOBKWXV7E+RXKhNCCFRAVOhnCB8RaIPHA+E44Hw3kD4W0Fimu3AVChCCCGEEELIR4M1FoQQQgghhBC7obAghBBCCCGE2A2FBSGEEEIIIcRuKCwIIYQQQgghdkNhQQghhBBCCLEbCgtCCCGEEEKI3VBYEEIIIYQQQuyGwoIQQgghhBBiNxQWhBBCCCGEELuhsCCEEEIIIYTYDYUFIYQQQgghxG4oLAghhBBCCCF242IymUz274YQQgghhBDizDBiQQghhBBCCLEbCgtCCCGEEEKI3VBYEEIIIYQQQuyGwsJO3rx5Iz/88IMUL15cypUrJ4sXL7bZ9uzZs9K4cWMpVKiQNGrUSE6fPm3vx5MYPB727Nkj9erVkyJFikidOnXk999//6h9JdFrPGjcunVLjYmDBw/yEjnpWPD19ZXmzZtLwYIF1b3hwIEDH7WvJHqNh99++01q1qyp7gsYF2fOnOEliqW8fftWateuHer9P7rbkhQWdjJ+/Hh1UX18fGTo0KEyc+ZM2bFjR4h2/v7+0r59e3UT2bBhg7pBdOjQQW0nzjcezp8/L126dFE3hU2bNkmzZs2ke/fuajtxvvGgZ9iwYbwvOPFYeP78ubRp00ayZ88uv/zyi1StWlXdKx4+fOiQfhPHjoeLFy9K7969lb2wefNmyZMnj/r/q1eveGliodjs1auXuua2iBG2JGaFIhHj5cuXpgIFCpgOHDhg3jZr1izT119/HaLt2rVrTZUrVzYFBQWp5/hbtWpV0/r163n6nXA8TJgwwdS2bVuLbW3atDFNnjz5o/SVRK/xoLF582ZTs2bNTDlz5rR4H3GeseDj42P64osvTIGBgeZtDRs2NO3Zs+ej9ZdEn/GwZMkSU4MGDczPnz9/ru4PJ0+e5GWKRVy8eNFUt25dU506dUK9/8cEW5IRCzuAdzkwMFApRo1ixYrJiRMnJCgoyKIttuE1FxcX9Rx/ixYtKsePH7enCySGjocGDRpInz59rHorifONB/D48WOZMGGCjBgx4iP3lESnsXDo0CGpUqWKuLq6mretX79eKlSowAvlhOMhWbJkcunSJTly5Ih6DV7qRIkSSaZMmRzQcxJVHDp0SEqVKiWrV68OtV1MsCXjOroDMRk/Pz/x9PQUNzc387aUKVOqcNaTJ08kefLkFm0R2taTIkWKUENeJPaOh2zZslm8F+Pgn3/+USlRxPnGAxg7dqwSnDly5HBAb0l0GQs3b95UtRWDBw+W3bt3S/r06aV///7KmCDONx5q1aqlxoGXl5cSm3HixJF58+ZJ0qRJHdR7EhV4eXmFqV1MsCUZsbAD5DjqbwxAe44CnLC0NbYjzjEe9Dx69Ei6du2qvA7wVBLnGw/79+9XHsnOnTt/1D6S6DcWkCs9f/58SZUqlSxYsEBKlCghbdu2lf/++4+XywnHAyKZMCaHDBkia9asURN+DBgwgDU3TsqrGGBLUljYQfz48UNcTO15ggQJwtTW2I44x3jQePDggXzzzTeodZLp06crbxRxrvHw+vVrZTSggJP3g9hJeO4N8EqjQLdbt26SN29e6du3r2TJkkUV7hLnGw8TJ06UnDlzSosWLSR//vzy448/iru7u0qPI85H/BhgS9KKsYM0adIobwJyJTXgWcAFTpIkSYi2MCL14Hnq1Knt6QKJoeMB3Lt3T/1Y4KawbNmyEKkxxDnGw8mTJ1X6CwxJ5Fxredfe3t5KcBDnujcgUpE1a1aLbRAWjFg453jA1LK5c+c2P4fzCc/v3LnzUftMogdpYoAtSWFhB/AqxY0b16JoBukMBQoUCOF5xnzDx44dU55pgL9Hjx5V24nzjQekO7Rr105tX7FihbpZEOccD8in37lzp5p2WHuAkSNHqimIiXPdGwoXLqzWsdBz5coVVWtBnG88wGC8fPmyxbarV69KhgwZPlp/SfShUAywJSks7ADhyPr166t55+F13LVrl1rkplWrVmYPBNIcQI0aNeTZs2cyatQoNcMD/iJXDoveEOcbDyi+u3HjhowbN878Gh6cFcr5xgO8lJkzZ7Z4AIhNFOUR57o3YAIHCIsZM2bI9evXZdq0aSqihdx64nzjoUmTJqq2Ag4HjAekRiFagYkeiHPgF9NsSUfPdxvT8ff3N/Xr189UuHBhU7ly5dSc0xqYi1g/t/CJEydM9evXV/NXf/XVV6YzZ844qNfE0eOhevXq6rnx0b9/f14cJ70/6OE6Fs49Fg4fPqzWLsifP7+pXr16pkOHDjmo1yQ6jIc1a9aYatSoodo2b97cdPr0aV6YWExOwzoWMc2WdME/jhY3hBBCCCGEkJgNU6EIIYQQQgghdkNhQQghhBBCCLEbCgtCCCGEEEKI3VBYEEIIIYQQQuyGwoIQQgghhBBiNxQWhBBCCCGEELuhsCCEEEIIIYTYDYUFIcQpiE1L9sSmYyGEEBJ7oLAgJAbx/fffS65cuWw+duzYEa59Va5cOUr7q32OsZ/58uWTcuXKSd++feW///6L1M+7deuW+owNGzao58+ePZN+/frJ4cOHzW1atmypHo66XkWKFJE6derIkiVLwr3PixcvSvPmzSO1nx07dpS1a9eq/+O8hTbGRowYYbNdnjx5pESJEtKmTRs5cuSIef8HDx60uq/8+fNL+fLl1fXx8/Mzt1+3bp20b99eogO7d+9WfY0Kfv31V2nbtq189tlnUrhwYaldu7bMnj1bXrx4ITER3E8w5gkhzktcR3eAEBI+UqVKJTNnzrT6WpYsWWJEnwMDA+Xq1asyceJEOXbsmGzdulUSJEgQKZ+VOnVqWb16tWTKlEk9P3funGzevFkaNWpkbjN06FBx1LEj2vDgwQNZtWqVjB07VuLHjy9eXl5h3h/EI85ZZAGBcO/ePYvzA9Bn9N1IypQpbbYLCgpSxzZr1iz55ptvlEDInTu3ue2QIUOUqNR4+fKlEiDz589X40ETN+jLTz/9pN7/1VdfiaOAIOrdu3ek7xfnCaIa1xLHCqGYMGFCOX78uCxatEh27dolS5culSRJkkT6ZxNCSFRCYUFIDMPNzU15N2N6n4sXLy7x4sWT/v37y++//y5ffvlllH2WkezZs0fKZ9nTn4oVK8oXX3yhDPvwCIvI5PXr10rcQWjFiWMZwEb0IUOGDB/ch7V2efPmlapVq8rKlSvNEQ7tvBvPRdmyZeXt27eyYMECuXTpkmrj4uIiHTp0UO+FFz+yRGdYQcQA/cEjceLE4u/vH6n7X7hwoRLTEGU4TxplypSRkiVLSosWLZQ4GzBgQKR+LiGERDVMhSIkFvLu3TvlBYZRVrBgQWXMNWvWTA4cOGDzPadPn1Ze5mLFiqlUnW+//VZ5UPUgnejrr7+WQoUKKQMIouDRo0cR7meBAgXU39u3b5u3/f3338rQRj9KlSqlPMb6dCl4e6dMmaLSLpBKg7+TJk2SgICAEKlQ8Di3atVKbcdfLf1JnwqFtJ2GDRuG6Fvnzp2lbt26UXbsEFXu7u7KiNYb+jiWatWqqWMrWrSotG7dWkVdwIwZM8zRDxwjnmvnBNcbRireV716dVm+fPkH+7B+/Xp58+aNVKpUSSITCA1PT0+5c+dOmNprnnn9uUCf0Df08WODSMmaNWtUhAXXPDLBOF28eLFKAdOLCg2M+27dupnFrzaerT306XxhGQPWUgC1NDX8tfYcPHz4UDkC9KmTEIPDhw9XqW/4nmpjEVEoRGNwz6lQoYKKPNlKUwS4xlWqVDGnm2kpdmhrK83K2n6spXfiPojPR9oh7oMQ8xDS+Ew9e/fuVfdH9BkpmrjuSKG0lcKnP/dM/yLEEkYsCImBIJXIiKurq9kww4/nzz//rIxy/Agi1QUe0O7du8uePXuUQWv00LZr105Kly6tDAQYDXPmzFH532gPr+2///6rjFy0mTp1qjx9+lSmTZumDHYYYhHxKiP9BWhpS5s2bVIGOwQRPNaPHz+W6dOnS9OmTWXjxo2SIkUK5UXGsaFdxowZ5cSJE0powFCHQaYHaTcwEuD5xl8YQEYgHrCv69evS+bMmdU2GBV//vmn9OzZUz2399j11wsG4P3795XRh+NHvzS0WpBevXqpc4I+4XNwHf/3v/9J48aN5e7du+ozke6VNm1a9b5hw4YpIwvnDKIQ/R09erQ6ju+++85mv7Zs2aKMLURVjKCfxnGGqIYxsmENXDc8tOtqa58Yd4cOHVLpPzD8Pv30U/NrSBGDuPjll1+UB/9jAmMRYw7fE81gjizOnDmjzk1oYg6i1kinTp3UtdKAUa8nomMgLEDsPn/+3CI1a8KECUr0YcxiHOI7CAcBHjVq1FDfW3yH8N3D6xAPtqI3RhERWeC7hTRIb29vJYzOnj2r7oMQ6vhc3C//+OMPdW7RP3y3nzx5IuPHj1fHge8evmcAaXra9w4kSpQoSvpMSEyHwoKQGAZ+8PR56howPrWCVxiuMIr13kkYal27dhVfX98Q6ShIQYGxA0MZXnKQNWtW9SMKDySEBYwLGH7z5s1TIgbAe48UJhgYHzL+jAblqVOnZMyYMcq7DYMJRicEETyG+CwN9KdWrVrK+IQRA0MUHlmtJgDRAxiA6KMR/Phrnl/8tZYChegAjDSkpmgG2M6dO5W3EwIH2HPstq4X6mGQgqQVYkPM4VwPGjRIHa92bDhXqMVA7QIMNE1MaNcQ4gTedYgR7frjHMJoQn8R/UH0wIh2DWrWrGm139a86dgvroMtsQBP8LVr19R1hACBca4HUTAjSZMmVUYdvNxG0YKI1rZt21RfP6YhZxREkYkWfQtLmpmxT/rvrf58RHQMhAWMERjnSHmDSAG4V+DegM/SIjqovcH1TpYsmbr+EPqIyly4cEH1wZqwwLmAowDfDwguoI0BfP/sAfc0CAH9fRFpd6jBwn0EogcRFQhHHBsigZpjBkIbogIRRO2c//XXX+pvTEtDJeRjQ2FBSAwDhbKIJhjRDE6gGeZI1bly5YryfMMzpxmwRnLkyCHJkydXswPB2/j555+rH2EYe+DVq1cqMoAIBoqPNUMSEYNs2bKp9KWIGNcwzuHRhMf/8uXLamYgY7EsDCp4YCEoAKIOOD4YS/AsQ5TYk67i4eGhah1gwGrCAtEB5LunSZPG7mPXXy8YZpj158aNG0os4Lg0YMxoRjsiTDAWYaSHdt0A0tvQL5wLvXjDc3wuiqNxfNaMOhhvtgxcvNdYvG1NvFkTIOnTp1cebeNsShBwGAcQI6irgdcY4heC1xrYD/qIKI1RFGIfeNhD3LiR9xOIfuqnAbYV3dE+096+R8YY+BDY58iRI1UBPUSj9h2EcwLPcZ/QgMEN5wUiTxAVGhA4MNKtCYVx48apSALuA5qwQFQS4JprEURbGCNg+vOv9dVYu4XnqF1BmhPuJYhiYPzp0/Ag7DVxH9bzhH6ENaJHSGyGwoKQGAYMUK02ITQvI4w4/IU3H0ZZunTpbK6BgBlpkIsMI2T79u3KGwljv169esqDDoMYP+JaQasRGBThEUM4BggheKs1kIJgbdYhbRsMAICULfQXkQJ4RmHAQhihn0hVigg4TqQFnT9/Xn0WjA6kkQB7j914vRCBQbQF6RlIr9Cn/8Aris+FGMQxYkYlCJ/Q1q7Qzput4neIFGsgtQVo+zeSM2fOMHnV9QIEBiU84xBk1sCxaucCxiTaw1OMc2htelmtb1pf9SClxdbsaGEF4ia8kQNbQGDpa4UaNGigxKMR7Xuob2sEDgFEJKylqEXmGPgQSE2EuJ07d64SARra1MDGKAi+z4hY6EH6FIxuRDn0wPDH7Ff43kHIa0BsYz8QI0hJwhg4evSo1TEwcOBA9TCKUYB0RWAUxxB26Df2hzb4XmliJqLgPOEBcYJ9oU4GaadwPBDibFBYEBLL0Ool4C3GDzZSmuBFQ4Ei5s23BdrBSIdn8eTJkyr9AbUMiBigsBE/mkhlsWa8GGs2IiKGNIMEKT9GYMhoRgyOBRECPFBUiuOC4QOvI6IHEQHRCRggEFX4C0MXKVIABr49x26tPQxOpI3Ac4pzjP0jioGICTzLSB1BRATbIfi0NAxraHnvPj4+qq+2DFkj2vnU0lsiSlgFiDWQ2w7jEvn4iDxhX3o049BaGk+TJk0sag4iAtJiIgsILH1UyVbqEdJuIF6RimMr0gWRjIkTUN8UFiI6BkIDaXmIDKJuyXgs2udB0OjTxnDvMRZG4zuqCU4tDQz3GERCkHqJ+44eCCrUayBdSUufwr0BkUMjXbp0sRgDEJtIvQKa0wL3Dk1saMXzEDnoDz4L3zHjJAw4BkSBIH6NQskaqJfBdxciBZ+H+xEmwsDY/tgzmhHiaCgsCIllwNuNH3z8aOvTR2DI2ErBwHz6KP5EoSwMa3gN8YAwwcw++AHGFKLYt14gIAcZhgdyle2dwhXebHw2ah3g7dW4efOmMrK02Z0gclBjAeML3kHM6ATvIzz91hYW02oiQgNtMHMM0o5gNMG417zlUXHsSBeBYYy1LODpxPFiVi4YNPDc6401TVRoEQtjqgVSSQCMJX3EBoILBeIQL9Y8sogq4LiRcuIo4D3GuEOdCQzNZcuWhfC0o4/WIiDYZisy4gjCuogerh9EKqJtWHzPuEglDFpcOwjPsEYsIjoGPiSU8B5834xo6U779u1T/9dqGjAtLyKLGKtaahG+U/i+6r+HqAeBMW+tSB0gDRPvQwonhDiEgbUaDWzXfyf1IgD1SQD3MH00DM8hbBBVgAiD0MNn6fuCeyVEC+6HYREWaKPvB44fQgP3DNw7CHEmKCwIiWXAQIcxDK8ZDDc8EKlAISOw5vlDeg4EB34M8SOMH1x472Gwa557rTAUNRCYSQk/zpg2E/UHtgyE8ACDC58BI0j7DBhKSHeB9xGzMgFMb4nPhdcX4gfGJ1awhiGBOhHjmgNaXQC8v9iPfsE2YzoU9ot+GFOeouLYe/Tooc4xvMJIo0HtAa4VokaYAhfeb8zyo3mttePSvMUQYPCowqBFnwYPHqzSa2DEoT4DXl9EEmwtmgjhhOuO/HtrRdUfC1xD9B8RMpwPfTE5+gajObxRoegOzjdmbUKUDQIT4hTjDtsgBGDshmdhvvCMAYhv/TTSEATaX33ND6KWK1assCrM4e1HjRPqheCRR8qPlpYGRwDSk1CjACMe6ZiopdGDfSO1KrSCfIgqpDhGFIh9CHZEw3DPw30Ds0Ghn6it0OpD4BxA5Azf8fr166uI6eTJk5VzwRhBswVEEs4pUr4QlcH9CPen6LpgKSFRCYUFIbEMGNL4wUd+MvJ8Na8cjATk9WM6U6OXFCkh+PFHXjOMAvwQ40cdM6ZoHlBtRiD8MOPHGB5LGMP4EY2smVIQfUB/kQoEkQPDAwYAfvS1XGkcE4wO1Fgg9QHHi+OxZYjhODC7k5ZSBIPcGhAcMCQgZpAapScqjh3GGY4Fxes4Dkx5C5GBz4ChAxGEfcPQRIEzrhsMSAg9GOGYsx9FtfD4Y3YtnDNEQBCBgKcZhh3ES2gRG6x1gGuMSMmHakWikj59+qi0EYxZpLZASKBPqHXBMcQ2MH7wHUUtE64lJg6AkET6G4QqJiOwVftii7COAUQUjLN1AYxDCBwNpP3BGLcFxiu+h/hMHA8iG0gDwvcI6XUQTRjjiCTqi7wBBAyEfFQzatQoVQCOewWcBbjPIfKJc6xF/pDGBCcMvne458A5geilrQkFrIHIEB4Axwxhh+MO7zUkJDbgYrJVEUgIISRWAwEJzyxm/4K3NjqBFDGkCzFPPerBOhJINbK3mB0CH5FDa0XrhBDngPOiEUKIk4LIADyziMbYu25AZIK0PKSaIc+dxa+EEBJzoLAghBAnBiksmPoXU99GF5C6gtQ3a4XDJPJBShPqdcJaLE4IIbZgKhQhhBBCCCHEbhixIIQQQgghhNgNhQUhhBBCCCHEbigsCCGEEEIIIXZDYUEIIYQQQgixGwoLQgghhBBCiN1QWBBCCCGEEELshsKCEEIIIYQQYjcUFoQQQgghhBC7obAghBBCCCGEiL38H8yBVpOjudsJAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# ВИЗУАЛИЗАЦИЯ ROC-КРИВОЙ\n", + "fig, ax = plt.subplots(figsize=(8, 7))\n", + "\n", + "# ROC кривая\n", + "ax.plot(fpr, tpr, color='orange', lw=2, \n", + " label=f'ROC кривая (AUC = {roc_auc:.3f})')\n", + "\n", + "# Опорная линия (случайное угадывание)\n", + "ax.plot([0, 1], [0, 1], 'k--', lw=2, label='Случайное угадывание (AUC = 0.5)')\n", + "\n", + "# Точка оптимального порога\n", + "ax.plot(fpr[optimal_idx], tpr[optimal_idx], 'ro', markersize=10, \n", + " label=f'Оптимальный порог = {optimal_threshold:.3f}')\n", + "\n", + "# Заполнение области под кривой\n", + "ax.fill_between(fpr, tpr, alpha=0.3, color='darkorange')\n", + "\n", + "# Настройки графика\n", + "ax.set_xlim([-0.05, 1.05])\n", + "ax.set_ylim([-0.05, 1.05])\n", + "ax.set_xlabel('False Positive Rate (FPR) — 1 - Специфичность', fontsize=12)\n", + "ax.set_ylabel('True Positive Rate (TPR) — Чувствительность', fontsize=12)\n", + "ax.set_title(f'ROC-кривая для классификации рака груди\\nAUC = {roc_auc:.3f}', fontsize=14)\n", + "ax.legend(loc='lower right', fontsize=11)\n", + "ax.grid(alpha=0.3)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "9fa3aa46-450e-41a1-bccd-7b90c7639545", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Дополнительная визуализация" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "79f4797b-4939-42bb-b34e-7f47907081f3", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# ДОПОЛНИТЕЛЬНАЯ ВИЗУАЛИЗАЦИЯ\n", + "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 5))\n", + "\n", + "# График 1: Распределение предсказанных вероятностей\n", + "benign_mask = y_test == 'benign'\n", + "malignant_mask = y_test == 'malignant'\n", + "\n", + "ax1.hist(y_score[benign_mask], bins=25, alpha=0.7, label='Benign (доброкачественная)', \n", + " color='red', edgecolor='black')\n", + "ax1.hist(y_score[malignant_mask], bins=25, alpha=0.7, label='Malignant (злокачественная)', \n", + " color='blue', edgecolor='black')\n", + "ax1.axvline(x=optimal_threshold, color='red', linestyle='--', linewidth=2, \n", + " label=f'Оптимальный порог = {optimal_threshold:.3f}')\n", + "ax1.set_xlabel('Вероятность принадлежности к классу malignant', fontsize=11)\n", + "ax1.set_ylabel('Частота', fontsize=11)\n", + "ax1.set_title('Распределение предсказанных вероятностей', fontsize=12)\n", + "ax1.legend(fontsize=10)\n", + "\n", + "# График 2: TPR и FPR в зависимости от порога\n", + "thresholds_subset = thresholds[1:-1:5] # разреживаем для читаемости\n", + "tpr_subset = tpr[1:-1:5]\n", + "fpr_subset = fpr[1:-1:5]\n", + "\n", + "ax2.plot(thresholds_subset, tpr_subset, 'b-o', label='TPR (Чувствительность)', linewidth=2)\n", + "ax2.plot(thresholds_subset, fpr_subset, 'r-s', label='FPR (1 - Специфичность)', linewidth=2)\n", + "ax2.axvline(x=optimal_threshold, color='green', linestyle='--', linewidth=2,\n", + " label=f'Оптимальный порог = {optimal_threshold:.3f}')\n", + "ax2.set_xlabel('Порог принятия решения', fontsize=11)\n", + "ax2.set_ylabel('Значение метрики', fontsize=11)\n", + "ax2.set_title('Зависимость TPR и FPR от порога', fontsize=12)\n", + "ax2.legend(fontsize=10)\n", + "ax2.grid(alpha=0.3)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "b6a95a99-3c26-421a-bd53-ed6f35773167", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "#### Сравнение с Iris" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "ca77eed5-b077-4510-92d3-76c768b3a1ab", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "======================================================================\n", + "СРАВНЕНИЕ С ДАТАСЕТОМ IRIS\n", + "======================================================================\n", + "\n", + "┌────────────────────────────────┬──────────────┬─────────────────┐\n", + "│ Показатель │ Iris │ Breast Cancer │\n", + "├────────────────────────────────┼──────────────┼─────────────────┤\n", + "│ Тип задачи │ Многоклассовая│ Бинарная │\n", + "│ Количество классов │ 3 │ 2 │\n", + "│ Количество признаков │ 4 │ 30 │\n", + "│ Размер выборки │ 150 │ 569 │\n", + "│ Macro / ROC AUC │ 0.780 │ 0.998 │\n", + "│ Micro / Accuracy │ 0.770 │ 0.971 │\n", + "└────────────────────────────────┴──────────────┴─────────────────┘\n", + "\n", + "\n", + " **Сравнительный анализ:**\n", + "\n", + "**Breast Cancer показывает более высокую производительность потому что:**\n", + " 1. Задача бинарной классификации (проще, чем 3 класса Iris)\n", + " 2. Признаки более информативны (30 медицинских показателей)\n", + " 3. Классы хорошо разделимы (AUC = 0.998 > 0.95 говорит об отличном качестве)\n", + "**Почему это важно:**\n", + " - Модель может использоваться как инструмент поддержки принятия решений врача\n", + " - Высокая чувствительность (TPR) важна для обнаружения злокачественных опухолей\n", + "\n" + ] + } + ], + "source": [ + "# СРАВНЕНИЕ С ДАТАСЕТОМ IRIS\n", + "print(\"=\" * 70)\n", + "print(\"СРАВНЕНИЕ С ДАТАСЕТОМ IRIS\")\n", + "print(\"=\" * 70)\n", + "\n", + "iris_macro_auc = 0.78\n", + "iris_micro_auc = 0.77 \n", + "\n", + "print(f\"\"\"\n", + "┌────────────────────────────────┬──────────────┬─────────────────┐\n", + "│ Показатель │ Iris │ Breast Cancer │\n", + "├────────────────────────────────┼──────────────┼─────────────────┤\n", + "│ Тип задачи │ Многоклассовая│ Бинарная │\n", + "│ Количество классов │ 3 │ 2 │\n", + "│ Количество признаков │ 4 │ 30 │\n", + "│ Размер выборки │ 150 │ 569 │\n", + "│ Macro / ROC AUC │ {iris_macro_auc:.3f} │ {roc_auc:.3f} │\n", + "│ Micro / Accuracy │ {iris_micro_auc:.3f} │ {accuracy:.3f} │\n", + "└────────────────────────────────┴──────────────┴─────────────────┘\n", + "\"\"\")\n", + "\n", + "print(\"\\n **Сравнительный анализ:**\")\n", + "print(f\"\"\"\n", + "**Breast Cancer показывает более высокую производительность потому что:**\n", + " 1. Задача бинарной классификации (проще, чем 3 класса Iris)\n", + " 2. Признаки более информативны (30 медицинских показателей)\n", + " 3. Классы хорошо разделимы (AUC = {roc_auc:.3f} > 0.95 говорит об отличном качестве)\n", + "**Почему это важно:**\n", + " - Модель может использоваться как инструмент поддержки принятия решений врача\n", + " - Высокая чувствительность (TPR) важна для обнаружения злокачественных опухолей\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "id": "1c2394a1-9bab-47df-bc7e-ba3a11bae1f2", + "metadata": {}, + "source": [ + "### Результаты\n", + "\n", + "### Ключевые выводы\n", + "\n", + "1. **Качество модели:**\n", + " - ROC AUC = **0.99+** — отличный результат (модель правильно ранжирует пары)\n", + " - Accuracy = **97%+** — высокий процент правильных предсказаний\n", + "\n", + "2. **Медицинская значимость:**\n", + " - True Positive Rate (TPR) — чувствительность: правильно определяет злокачественные опухоли\n", + " - False Positive Rate (FPR) — доля ложных срабатываний: низкая\n", + " - Модель правильно определяет ~98% злокачественных опухолей\n", + "\n", + "3. **Практическое применение:**\n", + " - Можно использовать для скрининга (при низком пороге)\n", + " - Можно настроить порог в зависимости от стоимости ошибок\n", + " - AUC > 0.99 говорит о почти идеальном разделении классов\n", + "\n", + "4. **Ограничения:**\n", + " - Данные могут быть не репрезентативны для всех групп населения\n", + " - Модель не заменяет биопсию, а только помогает врачу" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "79400e44-fa36-4e74-b599-cee63eef9e55", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.14.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}