From 499760f2e6491dd3fd567ee0e5ce809ab8fcaab4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=D0=A1=D1=83=D1=85=D0=BE=D0=B2=D0=B0=20=D0=97=D0=BB=D0=B0?= =?UTF-8?q?=D1=82=D0=B0=20=D0=91=D0=BE=D1=80=D0=B8=D1=81=D0=BE=D0=B2=D0=BD?= =?UTF-8?q?=D0=B0?= Date: Wed, 14 May 2025 21:51:30 +0300 Subject: [PATCH] =?UTF-8?q?=D0=A0=D0=B0=D0=B1=D0=BE=D1=82=D0=B0=20=D0=B7?= =?UTF-8?q?=D0=B0=D0=B2=D0=B5=D1=80=D1=88=D0=B5=D0=BD=D0=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .ipynb_checkpoints/Untitled-checkpoint.ipynb | 6 + .../week4_scikit_learn-checkpoint.ipynb | 502 ++++++++++++++++++ Untitled.ipynb | 198 +++++++ week4_scikit_learn.ipynb | 502 ++++++++++++++++++ ~$чет по работе.docx | Bin 162 -> 0 bytes Отчет по работе.docx | Bin 32081 -> 186044 bytes 6 files changed, 1208 insertions(+) create mode 100644 .ipynb_checkpoints/Untitled-checkpoint.ipynb create mode 100644 .ipynb_checkpoints/week4_scikit_learn-checkpoint.ipynb create mode 100644 Untitled.ipynb create mode 100644 week4_scikit_learn.ipynb delete mode 100644 ~$чет по работе.docx diff --git a/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/.ipynb_checkpoints/Untitled-checkpoint.ipynb new file mode 100644 index 0000000..363fcab --- /dev/null +++ b/.ipynb_checkpoints/Untitled-checkpoint.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/.ipynb_checkpoints/week4_scikit_learn-checkpoint.ipynb b/.ipynb_checkpoints/week4_scikit_learn-checkpoint.ipynb new file mode 100644 index 0000000..794fc25 --- /dev/null +++ b/.ipynb_checkpoints/week4_scikit_learn-checkpoint.ipynb @@ -0,0 +1,502 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "c7951e95-0bd8-4b23-863d-528051c0dc85", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 1.00 1.00 1.00 8\n", + " 1 1.00 0.14 0.25 14\n", + " 2 0.40 1.00 0.57 8\n", + "\n", + " accuracy 0.60 30\n", + " macro avg 0.80 0.71 0.61 30\n", + "weighted avg 0.84 0.60 0.54 30\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "D:\\Practice4\\.venv\\Lib\\site-packages\\sklearn\\neural_network\\_multilayer_perceptron.py:691: 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)))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0aab83de-75f3-4e00-ad79-f011f2195366", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 1.00 1.00 1.00 8\n", + " 1 0.82 0.75 0.78 12\n", + " 2 0.73 0.80 0.76 10\n", + "\n", + " accuracy 0.83 30\n", + " macro avg 0.85 0.85 0.85 30\n", + "weighted avg 0.84 0.83 0.83 30\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "D:\\Practice4\\.venv\\Lib\\site-packages\\sklearn\\neural_network\\_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) 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=100)\n", + "clf.fit(X_train, y_train)\n", + "\n", + "# Отчёт о точности\n", + "print(classification_report(y_test, clf.predict(X_test)))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "c5b95df2-6d00-440c-b7a5-9bd3360c9f70", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 1.00 1.00 1.00 9\n", + " 1 1.00 1.00 1.00 12\n", + " 2 1.00 1.00 1.00 9\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" + ] + } + ], + "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=2500)\n", + "clf.fit(X_train, y_train)\n", + "\n", + "# Отчёт о точности\n", + "print(classification_report(y_test, clf.predict(X_test)))\n" + ] + }, + { + "cell_type": "markdown", + "id": "c4687a52-9dc6-4fca-9bb5-f433acddca90", + "metadata": {}, + "source": [ + "# 1. **Часть 1: DBSCAN на синтетическом датасете make_blobs**" + ] + }, + { + "cell_type": "markdown", + "id": "5027127f-d121-4544-9432-dc6c6d6ef670", + "metadata": {}, + "source": [ + "#**Цель-Продемонстрировать работу алгоритма кластеризации DBSCAN на синтетических данных с тремя кластерами.**" + ] + }, + { + "cell_type": "markdown", + "id": "518c3a5c-5f80-4ae7-9637-f810b1e577aa", + "metadata": {}, + "source": [ + "**Импорт библиотек**" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "43634fe1-67dd-4b63-a730-00e7ccbc07c7", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.datasets import make_blobs\n", + "from sklearn.cluster import DBSCAN\n", + "from sklearn.preprocessing import StandardScaler" + ] + }, + { + "cell_type": "markdown", + "id": "1b51a387-bfea-418e-8a0f-79b02b6024a0", + "metadata": {}, + "source": [ + " **Генерация данных**" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0b08cf7d-0761-45b0-8a2e-2817ce2d5e4a", + "metadata": {}, + "outputs": [], + "source": [ + "X, y_true = make_blobs(n_samples=300, centers=3, cluster_std=0.5, random_state=0)\n", + "X = StandardScaler().fit_transform(X)\n" + ] + }, + { + "cell_type": "markdown", + "id": "3d43f16d-aae5-4e39-81cc-f876cbe76068", + "metadata": {}, + "source": [ + "**Визуализация исходных данных**" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "bc586730-b430-44a2-a5b7-852f25ce19c5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8, 6))\n", + "plt.scatter(X[:, 0], X[:, 1], c=y_true, cmap='viridis', s=50)\n", + "plt.title(\"Синтетические данные с тремя кластерами\")\n", + "plt.xlabel(\"Признак 1\")\n", + "plt.ylabel(\"Признак 2\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "6dbcd759-c02f-41ca-b7df-c36a78f8ac49", + "metadata": {}, + "source": [ + "**Применение DBSCAN**" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "a765ae38-a2f1-4b5d-b81a-ebd63485c5a5", + "metadata": {}, + "outputs": [], + "source": [ + "dbscan = DBSCAN(eps=0.3, min_samples=5)\n", + "labels = dbscan.fit_predict(X)\n" + ] + }, + { + "cell_type": "markdown", + "id": "c4a3b09b-2600-4974-b584-449f5d8c3592", + "metadata": {}, + "source": [ + "**Визуализация результатов кластеризации**" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "fa83a1e9-6ab3-4406-bae4-30dd881cccde", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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IK9mKUbEdLZkaQV/Ovggq5b5SqgPtk6Kr4UDPkaK9ZLtG21I+JglMsgszE/UKBn3xk8jypTpQ4R956JYEWtKngkA6jxRdI29digZTWgZZcxkVTtFzpdeMxAYJano9KapGEW9/KGJPtmLjx48XwpOi6fT6U6cuis4FK7AryXvJB0VmyQOW3iN07nwXSoVTJWh1wJeSEAx6jN5T9FwprYNy2emigS4i6PUmyOOW9kPnk+zW6DWnMbRy4Ytk+kNFX4Uj97SCQdD9FOn3t/wi0Ukizwj67NB5CJYSYgRdQPhSB2h1gDq30Xmn/G2KqpKdX2FI4Pu2oe0pt5feT5QzT4LdJ3zp/NEqCuUBUwoDXbDQBQqlbVCKEK3mEPT5o88SRdWpwJUuekj00/2Ut0wRXsp3J2FM7zu66Aj2eaULBRLJdDFM78NQub6UkkIrKqHSfBimzClzHwmGYYplteUjMzNTWGg1b95ct9lses2aNfW+ffsK+yGn0ynG/Pzzz3qPHj1EZyeyJKKxDz74oLBKC8SoUaPE8RcvXlzg/kWLFoltn3vuuSLWYsHszPwtmKpWrSps0ApbphV+3oFsrsie65VXXhFWVWTrRZZMU6dOLWKZFa6dme9G546eG1lC+Z5bcezMfJw4cUJPTU3VL7roIvF7z5499csuu0zfsmVLke0D2ZnR61O3bl3xetE5W7JkScD5kMXXk08+qTdp0kR01apTp45+6aWX6jt37gzrfJh9L/le5zfeeEN/66239LS0NPF69O/fX1+7dm2B/dFrQ2Pvu+++kK8z2Zyde+65wq6Pjkv7vPLKK/V169YV2G7KlCnCXi8uLk5v3Lix/vrrr+dbuvm/Z+j9EMgCzP/msynznZMLL7wwoC1XYTszuu+dd94J67wWPh++G3VOo+dxySWXiM9oYQs7/2P6bpIk6dWrVxcWYf5WZdSNjazyxo4dm/8Zof3T54Req8KfV58dIL3fO3ToIMbSeW3fvr14Dxw+fFi85vSa0GsbCnrv0XEK25kVxnee2M6MiSYk+qfs5TbDMNEERdko0keV2wzjD0V+qakGFUGWNDJeXlAeLS3Pm+nKxzBMxYZzfBmmkkPLxmQRFk5XJ4ZhGIaJRTjHl2EqKZQzSzmOlGtJuX6UR8kwFRHKwQ7V0pdhmMoDC1+GqaT8/fffopiKrKLI+iiSFesME00Ux66OYZiKCef4MgzDMAzDMJUCzvFlGIZhGIZhKgUsfBmGYRiGYZhKAef4mujqRB1qkpOTi7QiZRiGYRiGYcofytylLoT16tWDLAeP67LwNYBEL3XEYRiGYRiGYaIbahXfoEGDoI+z8DWAIr2+E5mSklLe02EYhmEYhmEKkZGRIQKVPt0WDBa+BvjSG0j0svBlGIZhGIaJXozSUrm4jWEYhmEYhqkUsPBlGIZhGIZhKgUsfBmGYRiGYZhKAQtfhmEYhmEYplLAwpdhGIZhGIapFLDwZRiGYRiGYSoFLHwZhmEYhmGYSgELX4ZhGIZhGKZSwMKXYRiGYRiGqRSw8GUYhmEYhmEqBSx8GYZhGIZhmEoBC1+GYRiGYRimUmAp7wkwDMMw4aPrOo4tP4ZNX27BsWXHoENHaueaaHNDa9TtVxeSJEXuOCuPY8/UPXBmOBFfKx7NL26Gqi2roixx57nhTHfCmmSFNdFapsdmGKbiIOn0V40JSkZGBqpUqYL09HSkpKSU93QYhmGguTUsfHARtk/cAUmRoKueP+O+nxuNaoTBHw6EYldKdJzM/VmYffMcnFx3EpLFK6R1iGOkDW+AQR8MhC3FFnIfucdzcWjhYai5biQ1TELdvnUhyeZF+fHVx7H+ow3YM3Wv53lKQIPB9dH+jvaoP6BeiZ4fwzCVT6+x8DWAhS/DMNHG0ueWYcPHG4UIDYgMtLisOQb8u3+xj0GCddK5U5B7LDdfWPtDIrtmxxoY9dtIWOKKLh7mnsjDP88sxe7Juwtsn1gvEd0e7YIWV7QwnMOOn3di/v/NB6Sz4t53bPq9+5Pd0OnejsV+jkxoTqw/ic1fbMbhhYehuXVUa1MVba5vjQZDG0BWOFOSiU29xu9chmGYGCLvZB42fropuOglNGD7jzuQuS+z2MdZ+/76oKKXoPuPrz6Bnb/uCjjH30dPLSJ6iexD2Zh/30Ks+2B9yOOf3HgK8/9vAXTNc6zCxyZWvLwS+2ftL8azY0JB8bDlL6/A5OFTvO+jLPG6HZx3CDOvm40/Lp4BZ6azvKfJMMWChS/DMEwMsfO3XUHFqD+UTkCpEMXNp9323Tbj48jAJhLhhSDRlLU/K+T2y19agTM70oM+LsS9iW+oObfPw67Ju40HMqah1YR173kuTHT32dfQ93oeW3EMc26ZKwQyw8QaLHwZhmFiCMq7lS0m/nRLQNaBrGIdg0SrK8tlPFADTm0+DV07K4AcZxzY8dNOQ9FMwnzzl5sDPkaCahcJfD/RFQx3thtzb5+HZS8uN54vY+qiZ807a0OOodf24N+HRMSfYWINdnVgGIaJISzxiulImxIg99YUJXCEoGig5tIMx5F4OjDnYMDHNKcGNU8N67jrP9iA1M6paDKmcVjb0Vz3Tt+LLd9sRfrODFEQmDasAVpf3xpVm1dBZWP/zAPCPcMIKnbcNmEbanVNLZN5MUyk4IgvwzBMDJE2pIGpSCiNSRvaoFjHSE5Lgi3FhGWYDNToUKOAS4PqNBa9Z8cGFreyTYYSF54jBc1hw8cbwi7gm3ze75hz2zwcXnRE5LFm7M7Aps8345f+v3oKCCsZWfszRfGgmfdXSXLIGaa8YOHLMAwTQ9TqUQvVWlcNKU7oMXJPaDC0frGOQVHPVte0MhZAGtD2pjYF7kppkmzqGLTvYBFV8iBudnHTsxZqJqB0i2Mrjgsxa4a8dAemjf0Dpzefzt8+f1+UpqEDS59dhh2/7ERlQom3FDgXQZFo9YEXjZnYg4UvwzBMDEGicPDHg0UTh0DClO5TbAqGfja4RJZTHe/ugMS6CUHFL0VYa/eqJQSqP9XbVEfNTjUMv11IXLa+rnXQx9vd0ja0c0UQqMlGKHKO5mDRI4vxffsfRGqDkchb9foqc0KwgkAeyabOuw6kDUsrgxkxTGRh4cswDBNjVGtVFRf+OQYNz02D5P9XXALqD6qPMX+cj9QuJcu9jKsRh9G/n49a3Tz7oegrFdUJISwBjUc3wogJ5wqRXZjuT3TziKcgAVvhAdyphph/MKq3rY6B7/UP71tK8sw7GLQ0T97EW7/bZioP2bNNFo4uO4rKQkrjFNQfXD90tF+G6KBX+KKHYWIBbmBhADewYBgmmsk+koOT608KoVmtTTWRnxtpTm44iT3T9oqiJ2pZ3OyipkhuFDqlYeekXcKHl7rMUUqEf+OJ1K41ce43w0OKVB8n1p7A3Dv/RsaujJDjaN8NhtQX+w3GlJG/48S6k6bs4PwZ8F5/0RCkspB9OBtTRk0N6OMs8rlliPMsosMME2N6jRN0GIZhYpjEOgniVprUaF9D3MKh2dimqNevLrb9sB37/toPd45b5P+2uroV6g+sZ7ptcc1ONTH862H4bfAkj4gOolkpHaHDXR2C7uf4mhPFtt+qbLmsiXUTceGMMcKPeddvuwtEx2v3ri0i+rW71yrXOTJMceGIrwEc8WUYhil/9s3cj9k3zRECt0j7Yk1H/7f6oeVVLYNuv/L1VVj7n3VhR3tlq4xxa69AXHXj6HRFJO9Unrhg0FUNVZpXQZWmlc/ijYkNOOLLMAzDRDWa6ongmmnI0XB4Gi7+eyw2f7EF2yduhzPDJSKxTcY2Qbub2xhGpKnFLkWZwxG+JKopj7Wyil6CnntxbfEYJhph4cswDMOUGbRsThZhm7/YLPJtSfhWaZaCNje2QctxLYRbRTAo2tj7xV7iRqI5HNeKxDqJYYvelCYp6PVcT9PbMAwT/bCrA8MwDFMmUJ7vjCv/xIL7F+KEtyCPSN+VgX+eXorfz5+K3BN5pvYVrlWbx4HAnPClBhqtrm6JMVPPh72aPazjMAwT3XDEl2EYhikTFj++BEeWeK3B/N3EvHr0zPZ0zL5lDkZPGhXxY1NDj+aXNcf2n3YUPLY/ElCrey2M+G44bCm2iM8hlnGcceDI0qOilXRywyTU7FxTeEqHC13wbP1mK85sOwPZrqDeOXXRclxLxNesvOkkTNnCwpdhGIYpE9u1HT/tDNkMglIRjv5zFMdXHy+xD3Eg+r7eR3R2OzDnYL61GiFyfzUddXrXwbnfDstPt8jcnyVE2qGFh0WKRvU21dDqulbC27g4oi9WBe+yF1dgx087oPm1o67aogq6Pd4NjUc1MrUfd54b8+9dgN2/7xGe0L6224cWHMKqf61Gv9f7hCxOZJhIwcKXYRiGKXV2T94N3USqAYminb/uKhXha4mzYPg3w7Bvxj5s+myzsDgjarSvLlovNx7dOL/Qbv1/1wvB518Qd2rTKWz/cQcajWyIQf8dWOFtzkj0/j56GjJ2ZxTJjz6zI124bPT7V5+QHfh8/H3PAuz5Y4/42Sd6BWTzrGlYMH4RrMk2NBnTOPJPhGH8qNifWoZhGCYqyD2RK/JySeSERANyjuWW2jxoDo3PbyxuwaDObsteWCF+9hd8vp/3/blfNOcY8slgVGRI+AcSvQLvXYsf+wf1B9YP2dCELjD2TN1jfLwXlqPx+Y1MezwzTHHg4jaGYRim1KGcWVOuCjJgr1J++bWU0rDilZUhx1BaBC3ZUwS4ouJId4j0BsPXTAK2fLs15JCt320VkXwjsvZn4fCiw+FOlWHCgoUvwzAMU+pQLmio/F4ftAxensvd+2fvR95JY2cJyhHe+u02OE47kLEnQ6QFVCSOLj1WIKc3GCSMqTNfKM5sPVMwvSEYkqfA0Z+TG09h7XvrsOqN1dj2/XY4s1zG+2GYEHCqA8MwDFPqVGlWBQ2G1MfBvw8FjSKSmKzSNAV1z6mL8iJjV0aBwrdg0OM7ft2JTZ9v9twhAQ0G1UeHu9uj3jn1EOuoeW7zY3PdhvZwptDPjqWLib/vmY9jK46L14NqCTW3jiVPLEHHezui8/2dOCWCqfgR3/nz52PMmDGoV6+eqKidNGlSyPHz5s0T4wrfjhw5UmZzZhiGYTwMfG+AaAoRSLCQuImrbsfwr4eVq2OCbFNMRaYJ5xnn2V904OD8Q5h+6Z/Y9NkmxDqhcnaLNPpoGrw9LFG3X13TIpWcNchN4/dRU0WrZN9FBolewp2rChcI8n1mmAovfLOzs9GpUyd88MEHYW23detWHD58OP9Wq1atUpsjwzAME5i4GnG44I/R6HRfR9irn20MYU2you3NbTB21oVCGJcn9frXM9vnogi+KPGSJ5fi6DKvX3GMUqNjDVRtWVVEso2ec6trWoUcQ81AjPZDArpuvzqo2rwKlr+4HI50Z8iou78rB8NU2FSHkSNHilu4kNCtWrVqqcyJYRiGCa/IrdujXdFlfGdkHcwS0VVqLkFWY+GQdSBLRAR1VUO1NtVRrVVk/sbTfmr3qo1jK46F1eK4sIjb8L+NqN2zNmIVirp3e7wrZt84J/gYRUK11tXQaETDkPtKqJWAvq/2xqJHlgTdD1389PtXX+Qcy8GeaXsNzz1ts/mrLUjtfI7JZ8QwMSh8i0vnzp3hcDjQvn17PPfcc+jXr1/QsTSObj4yMjLKaJYMwzCVB9kqI6Vx+NFdstf655ml2D/rQIHIbK3uqej5XE/U7l7yFb3+7/TDlFFT4cp0FUv80jZ7p+8TDhH0PKMFat5BTg1UQEbzqtOnjig6VOxKwPGNRzZCvzf7YjEJVulsRNuXA02i97wfzjX1HMnrl3x6ybIs53DO2QiwDnGhcc4bfUUeOBXKmTnnNOYIO0AwxaBCC9+6devio48+Qvfu3YWY/fTTTzFo0CAsXboUXbt2DbjNq6++iueff77M58owDMOE5sz2M6Khgosq+wtpo+OrTuCPi6bj3O+Go/6AkhWXVWlaBRfOGIPFj/+Dg/MOFiv1gYSZK9sFe9WzKR3lBUXVyRVh7X/WQdf1/HzbLV9vhb2aHQPf64+0YWkBt219TSvh07v1261ClLpz3SIdpfU1LdFwRMP8hh9maHZRUzS5oDEOLTiM9B0e8V23bx1UbXE2Wk/zM4tmMhebYfyR9HDeZVG2DPPbb79h7NixYW03cOBANGzYEN98843piG9aWhrS09ORklK+uWcMwzCVmckjpuDkhlPBI4LCA9iOcWuuCBrFDJfMvZk4suwodJeGpIZJmHH5X6aK30jUXb/72rCEYWmx7MXlWP/BhsAPSp6WzSO+P7fEFwyRgNwcfur9i+E4ijo3PDcNw74YWibzYqIf0mtVqlQx1GsVOuIbiJ49e2LhwoVBH7fb7eLGMAzDFA93jht7/tiL9J3pQoBS0VKt7rVK5NZwfPVxnFh7MvQgDcJXd/fUPWh+STNEyt3A3+Eg7dw07J8ZejmeRFnTsU2iQvSSkFz/3yCil9A9UdYljy/BJQsvLldHDYLSX8jO7siSIyHPMT3W5gbjVskMg8oufNesWSNSIBiGYZjIQgJq46ebsOr11SIdgYQf3ae/RvmgVTHwg4Go0a56sfZNVmFm/HVpzMG5ByMmfAvT8a722PfnPsNx7W5rh2iAmmxQRDfkedOA9J0ZOLr0qLATK296PNUdUy+Y5hHlAaLr9HzqD6znceBgmDAp/8vRMMjKyhLClW7E7t27xc/79nn+CD3++OO47rrr8se/++67mDx5Mnbs2IENGzbg/vvvx5w5c3D33XeX23NgGIapCGhuDSfWn8SRpUeFwwKx5p21WPr0Mk8OrneMT3BRQdXUMdNwanPx2vyqeaqpaCQJbdWhorQgp4Zz3uznSRFQCs6H2vLSfQPfH4CaHWogGjix7oTpVtGURhINpHauifN+GAFbVU/ranGe/c53o5ENMfSzIdzAgqn4Ed8VK1Zg8ODB+b+PHz9e/H/99dfjyy+/FB69PhFMOJ1OPPjggzh48CASEhLQsWNHzJo1q8A+GIZhGPOoThXrP9yATZ9uQu7xs619U7ul4vjK40G3I/FFgnTxY/9g9ORRYR83uWGyENJGkDg223yhuJAvbfW21UR0e/eUPR73BpuMZpc0Q7tb2hY7ql0qmE1diLJqHyp6G7f6CpEys3/2AdEdLiktCS3HtYyYdR1TOYnZ4rZoS5ZmGIap6JBw/euamTi08HBRoUT6yuS3ySXzL/I0RwgDckiY0P4H4SpgxKWLLhbWWGUBLcXTnCzxlqiMQK58fRXW/nudqYK8MX+MRq2uqWUyL4YpL70WU6kODMMwTNkUp2XszUT24ewC9lJr3l2LQ+SdGkhDhRFCoeYQ4WJNtKLzA51CjpFkoNmlzUpN9FIr3e0Tt2PLt1txeNFhISZJ7NLcolH0+qLTRvEtOm+Ug53apWaZzYthyouYSnVgGIZhSo/0XelY98EG7Px5Z36ebErTFLF83+Ly5tj0xWZRCFVSirvO2PHeDnCccQiXAv9CN9/PjUY2Qv+3gjcoKi6Uw7z4sSViyd1f4NPSe8+nu6PJBU0QrSQ1SELXh7tg1b9WBx4g0/mT0e+NvuXu6FBS6EKNXityEqnepnpUNQ9hogdOdTCAUx0YhqkMHF1xDDMu/1MI3gLFUF4tVLNzTZxYfSIixyrpkvqpzaex5astOEyWV5qOGh1qoM31rVG7Z8ks0wJBQmrKyN+Rd8oRtEiMuptRo4dwcGa5sH/WfjhO5sFePQ5pQxuIds6lAX3Nb/hwg2hi4c5Tz7ptuHUk1k8UxXh1+5S/m0NxObr8KFa/tQYH/z6Uf2ESVyMObW9qgw53tw+7HTZTsfUaC18DWPgyDFPRIRE2sduPcGU6oUcgohsUCaIw6aK5Y2MmuvjXtTNxYM5BQ9/eK1ddjoTaCaaKA1e+ukpEz8mpwpcbrcQpaH1dK/R4snvEmm8Eep13TdqF9O3pwoGibt+6aDC4fqmnaZCXMHWJOzD3IDSniiotqorOb/UH14eslCwqS8Vvc26dK34u8hrJQO0etUVbZcrBZio23MCCYRiGMcXOX3bCme4s3YN4O4T1frFXzIheyundP6tgekNAdI9fbpcHO4ccRq4Us2+eU3Cf3v9JBJNLxJmtZ3Dut8NLZZnelmQNOzJdUjb8byOWPrusgJdwxp5M7JuxT0Toh38zTHTbKw45x3Iw9455nsK9QK+RBhxbfkykefR8tkcJnwlTUeAEGIZhmErOrt925ac0RArhuSryRz07tiZZMeyLITHVdIC6h5kp2iPhdXD+QcNxO37aif0zQwhpzdOoY+uEbagI7Ph5J5Y+s8zTiMIvGuv7+djK45h1/WzD4rtgbP1um0jXCPUa0Wuz5estomCTYQiO+DIMw1Ry8k47IuLjSiI3PjUeI74/F7sm70LGzgzIdgX1+tZB07FNYUkom68ciqyS0KHjlaRtMKUlmB5LaQsGbPxskyfcZJBOsu799aLxxLEVx0UlYGqXVJHDnBpDVmMkOFe8sjL0GFXHkX+OCoeMeueEf0G05/c9pmzaXNluHPnnCBoMaRD2MZiKBwtfhmGYSk5CrXic2X6mZI4NEhBXMw4jfxwhPHqrt+mGsubE2hNiad3XVILyWJuMboz2t7Urlmis0iTFtOA38iUmH+JTZjqj6UAW2ab9sCM/MkrthLdP3CGcNc55u1+JxHxZQWI2+1C2qXNHaSLFEb6Us2wWXzdBhon+Tw/DMAxTqjS/rHmJRG98rXj0eq5nsRpTRAry1yX3hV2TdgvRS9Ay+O7f92DK+VOF92641OlTB8mNkgzHkUBtfW3o3FnNGd4JDpQasP2nHSJfNhbI3OdpY20EPbf0XRnFOkZSvUTTKiahrnHhIVM5YOHLMAxTyWlyQWMk1Cm+MOjxZDe0v71dsYuUSsrx1cex4IGFwpGicGW/+F0HFj28GEeXHQ1rv1SQ1eOpHoZjyJ2gVo9aIcfZqthgr1bC86MDm7/YguwjOYh2wnGmsMQXz8Wi5bgWpi7YkhomoVa30K8PU3lg4cswDFPJIZ/Tfq/3Kfb25Z17SukNMHCKIIG6/qONYe+7yZjGOOetfmJJ3t/2y1e0V29gPQz5ZJBY2l/+0goseeofbPhkI/JO5hU5PtmV+bYraXQ72qnbr47oCGeIDKQNTSvWMahxSFKDRMNz2uWBzlHbWY8pezjHl2EYhhFuAj5PWbOQmKDuZdTKmLar0b46WlzRQjQPCBeq7D+86IjI0yVqdqrpEU8GgpYK0CidIZTPrti/qgsLLcq1pRbD4bb9TRvWQLgIUJMEavJRtUUVtLqmlYhWTj73d2TsyhA5xTRfKq5b/sIKEQXv9njXfK/atje3EftwnA7eDMMQGcjcm4loJ7FuIhqNaoS90/eFfK50bkTkthiQN+/In87DH5fMEF3bBN5D+br5dXmoc7H3z1RMuIGFAdzAgmEqL2S8v+2H7cg6kA1LnIIGQxug4fC0mCguCpdv206A45TD/AZ+IllE3KgTmFfIdHu0q+iYZdavl0T3okcWI3NPZn70jkRLcuNkEYmuP7B+0G0psvpdu+9NT/vK1ZcLURYJTm85LfKHydEhoLiTIHJ/+/2rb/5dZ7adwYxxfyH7YLbH21bTRWTUbOMQEte0z76vBo7Q01f6sRXHsP3HHcg5kgNrkg2NRqQJEarYSqcxRiif3Skjp4p5FDk/3rfGwPcGoPmlzUp0HGemUxT/kW0Z5RZTmkXDc9PQ5sY2JeoQyMQW3LktQrDwZZjKhzvPjYUPLcbOn3eeXUYlbefWRS7s0M+HVLgv1C/SvsovCosEPZ/pjg53dTAcd2DOAfx17SyPl6sWuOnF8K+HiZa+gaDo61dNvjFla0X7u27HNWFFfA8vPoJNn2/CwXmHRHQ5pXEyWl/XGi2ubIE5N8/BoYWHDaO3F/45RkSw8+fsVEUkdOdvO5F7PE9EyKu3qYa1/15nak7DvhqKRiMaBrwImHXjbBxddiw/4un7nwoQh381VFijlbX4XfbccuyastvjueulWptqIjc8bVjx0hwYpjAsfCMEC1+GqVzQn8RZN8zGvpn7AxbOkBCTbTIu+GM0qretjorC951+QM7RXFNjJasE3RX6q4PO0VXrroS9avCCLhLa33eeiLxTecFTLGQgrlocxq25Img3s1k3zcG+P0MvqZMArD+oPkZ8Nxxm3wdLn1uOjR9vzBePnh15/qMLoJzDxkVmtG2LK5qj/9vnGB7v536/ijSGYM+DIsPxtRNwxYrLirT6pYu130dPw+nNpwNuT/OgtsgXzhiDqi3K3nkj93guji4/JkQ/2cTV6FgjZjr4MRVLr1W89TqGYZgScGjBYez7M7DoJSiySIKNCpkqEpSba6bwKi41zlD0EnSOqHNXKPZO3+spAgu1O80Tydw7Y1/QIZRLaybHt8Od7WAWah9Mote37dkdeW45R805K9C2JPiMIBE4+KOBYpk+0OtA98lWBUP+N6iI6CV2/bZb+AQHOw90P6VkrHlnLcoDamzSeFQjNBvbVES/WfQy5QULX4ZhGD82f7nFUACSiDgw9yAy95vzKo0FWl/fypMDaqBHKMUjWOTVHzqHpzYVbdjgzHCKvOk1/16LTV9sFjmrhvuySDiy9EjQx+v0qo0+L/fKP27heRA9n+1hukkCiXbDtINwskJMrqvW7FgTY6aNRt2+dYo8VrtXbYz+fRRq96gdcNvNX2w2/Ean9y2lHIgIO8NUUtjVgWEYxg9yFTBVca9DLCsnpxk3OIgFkuonYfjXQ0W+LQk//3PgW+rv/mQ34UhwYPYBU/v0t5Aip4MVr67Eps82i8gjiVn/nM+Q+4Hx2LY3t0XVVtWw4aMN2E/zo+ESUG9APXS4sz3qDzDfGYzydvNOREYc0rlL7Xo2v9cIyvUlpwIqrDyxxuNwUb19DVRtXiXkdqe3meu8R+cxY08m4qqH77zBMBUBFr4MwzB+hLMEa8qnNIao178eLv77Imz6bBO2fb8drkyXEKiNRjZCu1vaisjqnml7sN6EYCWB5WsaQPmrf989X0QbfdFPs6KX0FTNVEe4eufUFTeq8necccJexQZbig3hQi4EkYIuGNrc0Cbs7VIap4ibWWRFghrGWIaprLDwZRiG8aN2r1rCE9Qo6kuRPCrQiSaOrzoubKxo/uRcQJZO4dpYpTRKRu8XeqHX8z2FY4LIOfW7GGg4oiHiU+OQSxHRYKdIgjh+0wubiF/3z9yPXZN3F/t50fzDsbyyJdvErbhYk8Lw+SXnCcljSxbosWaXNENqF/MR3+JCqRDkMWz0vqXnVl5tpRkmGmDhyzAM40ebG1pj5y+7DEVvo5ENkVCr+G1+I4njjAOzb5mLwwsP56cQ0Bx3/rpLiNR+b/TF8dUnsO+v/XDnuoW4peYLjc5rGDRfl8QcdXQrDHkY93/nHMy8bpZH9wbSWTrEMS0Jnu0pvaGAM0KYUBOC4kRujaBI9JElR0UuMqVl1OqWKgqv6g2oKwQ/Cf+QSEC7W9tiz+97kH0452y+skg50NH6+tbo/WKvMinkantTGxyYczD0dBVJNOOgxg8MU1lhOzMD2M6MYSoX9Cdx4YOLsG3C9qDiwZpsxYV/XiAEZHlD9lDTLvwDJ9adDNpEwdNZ4mxBlk+EVmtdFedNHIGE2uEL+P2z9mPhw4uFpZdP8JHgjqsZh76v9BbtZH182fhrkdcbDr78YBK9nR/oFBHx6Eh3iIj43ml7kXUoG3nHc+HOVc8W9FH3uY41RMOJ7T9sx5avtwb3B5Y9rZ6pIQZFUQ/MPoiD8w4KW7HkRslocXlzU40ySFzv+WOvyEtWc91IapAkPIIp1zccfOkkO3/bFfBihF7z5IZJuOCPMbBXC24xxzCxCvv4RggWvgxT+aCc0pWvrsKGjzeKoiyKcpIAIrFYo0N1DPpwkGGxUVmx89edmHfX/GJtS2KIWu9e+NcFxerqReeJoownVp8QwqtGhxqis50ry4Vt32/D1gnbRb4s/R7Okr2tig2pnWqi5VUtItZl7cC8g5h90xwR8Q7lskCCm4Q8Cc8Ta08GHqNIYty53w4L2VXOiMNLjogmGHmnHJ6LEdHFzXNRQisKA98fEFazDXqvrnx9FTZ+sulsASEJdx1IG54mvITja3JRG1MxYeEbIVj4MkzlhRwMdk7ahaz9WWJ5mLqHpUZZx7bfx0zD8ZXHzXUuCwL5xzYd2zQi8zm54SSmX/6nOHdmbbx8UNrFVetDN70orlMHNXcgoR6WDVkQSFAO+nAgmo45G9UOBn3FBopWn1jnmRNFyQO9diSA6/WvixHfn1vAHcMMVNy3Z9peb8tiq7gYoSg0w1RkzOo1TvRhGIYJAi0Jt70x/Ir8suT0ltMlEr0kqrZ8uy0iwpcaTZDodaY7wxa9FPFsOrZJxEUvseqtNZ5zFKGOzCRWFz6wCKkdawYUlCT+N362WeT+urJdwjqsxZXNhbuDz/5u+UsrRWQ32GtH91OxGvlFF27XTPs/uvQoNLeOqq2qCqs2f3FMhX0tr2xxdl+6jqMrjiF9R7q4uCB3DkqpYJjKCAtfhmGYGCbcaGAggZWxOyMic9k6YZsotAtXYJLopYg65fJGmpxjOcJVIlwhbgQJ2lVvrcbA/wwocP+Wb7Zi0SOL81MWfBcEGz7aiM2fb8Hwb4YiOS0Zh+YfMnVeNn+5OV/4UhEe5Z9ToaK/m0Ri/UT0eq4nmoxpXGQf1Hp72fPLheg9u2MgbVgD9HmlT4XxoWYYs1QwF0qGYZjKRZ3etU21Gg6FJc6T35t7PFfkNf/z9FIsf3kFjvxzREQLzbL1u21hiV7fvKkgbtQv56FK08jnTWfuy4q46BXonjbBIqXDy6EFh4TopccKFxrS726HWzQIObTosLlDqDpObvB0vzu58ZRIjaAiRt/xfdHi7IPZmHPrXFG4Vzj/m9w30nf6iV7vtpSbPeW835G5L7NYT59hYhWO+DIMw8QwZGO178/9xd6exGfasDQhdjd9vlkIXVmRxf/r3lsvPF+H/G8QqrWuFtHGD7W6pyIpLRmNRzYUDTLMtEEuDkop7ZegDndntp9B7Z6eNsJr/7OuQKS36AaA5tRMd77zvzhY8MBC4QARyhJu4UOLhHczpYtQW+L59y8MKvppPxSdX/TwYuHswTCVBY74MgzDxDDUkpess4oLCaDMvZnY+Okmj6gicUYti72d1ShaSAV06bsKRQ0D4PPtNUPf1/ti8IcDhe1ZaYleggS7rWrkPYDzkc6mVBxacNjQq5gep5bIZqL0NKZu3zqiOO9kMLs6P+h12z7RE/UlOzb63WgulEccqVQXhokFWPgyDMPEMJTnec47/dDp/zpC8aYsCF9d2U+MBvpL79Vd1IBh74x9ISOD7hy3KMYyovGoRmebOIQgoW6C8BAuC6gRRZvrW5c4FzoQsk3O74KWezzP9HZU/NfkgsaG4tfX7phsz8zOn9JTiAN/HzKd4kFCnGEqC5zqwDAME+NQakL3J7qh470dsGfqXmQfyYY1wdOy2F7djhUvrxSRQP9OZFWaVUG3R7tiz7Q9+d3eQgmwfTNovzlIrJMQMu1C5PmGQgLa39ZOzDmilnMH/CznuhS0nKOLAnJHOLXxVLG7xxWGRCu1UbZX8bhQ2JLN++3SPHs81V1EiGn+webU5sbWqNU1FYcpJ9iM7qWAvTfKa7phiORposEwlQUWvgzDMBUEYWM17qyNlQ/qRNb9yW7CAouit8kNk1GzS00RLV76/LKQoteHrgEn158MKXyrt62OPi/1wpInl3pyXQtbdUkQYpyizCWFPHlXvLoSGz/eVKDJyOo316BmxxoY9NHA/GI5agIx6teRWPbcMlEARnm2PihKHnZXOUUSVnddH+qSf19SWhKqtamG01tPhyzwo20p2ptUPwkXTBuNv++dj6PLjnkaWJBypUZyFsmbomHHsVXHRLMUM4Kd9lHF21iF/j+24pjxdjqQ0oQ96pnKAzewMIAbWDAMU5H5oduPwhXADMO/GSaaIRix7699WP3OWtHRzUdCnQS0u6Ut2t/RTojUEreVHr8I274P3laaur9dOGOMEPn+UEEX5bWSHRmJ+Lrn1MVvgychfVeG6dQA6t435NMhRVpWb5+4HfPvWxh6YwliXjU71cy/69TmU6KQcO/0vZ4WyoWw17BDc2imOuBduuhiEc0/vuo4poyaajieXpcrVl4WsQg8w5QX3MCCYRiGMSS1c03hxmAYGZQoomvs7EA0PLehuFFBXM5hT/ew6u2rR0xcHVt+LKjoJei5UB4tWbIN+XhwgcfI8aDphQU7rrW7rR0WP7bE8Ljkk9v+zvZI9UbLC9P88uY4tuo4tny11ZNX7Rf5FRFdVUffV/sUEL3Ema1nsPPXXUGP6zh51jItFI1GNRKil6CIftq5aTgw60DIBifdH+/KopepVLDwZRiGqcRQHim1tw0FibYGQ+ojsV4iDi8+IhwDyP+VBG3a8DQ0u6QZbElnc1wpF3jbhG1iCV/XNJECQWN9oiwQYvFRN9eQY9MXm/OFZND9qTp2/74HuS/lIj41PuT+Wl3TEgfnHQxZ5Nf25jbo/VKvgILXBz3W97U+Ii93/YcbcHrLmQJ+y5RrXH9g/QLbuHPdWPjw4pDzK3gQT3pCoPv3/bkPuybtEl34aC7kmjHntnnCPs3/fImfNR29nu+JFlcUTY1hmIoMpzoYwKkODMNUZOgrYM4tc7Hnj70BBRWJJHJGOO+Hc7H8pRVn81FJRHlFGInaIZ8ORoNB9bH+ow1Y/uKKAg0WfONJPPZ6oWd+hJGOve+v/dj02WYcXuyxAqPUBBLjra5qCVuKrUiaAs1z6bPL4Mo0XvYn6HhUTGcE5QmTD+/GTzYVaEpBqQCd7u2ANje1CSl6C0PPLWtfFhwZTiTUikdC7cC50dt/2oH59y5ApKBzfeGfY1CjfY38edBrtuXrLUKIKzZZWOC1vrYVty1mKqVeY+FrAAtfhmEqOlTVv/jxJSJ9QERcvfqOit6oaGvwR4Ow5Ml/RHFbwCir7HGWaHd7W6x/f0PwA0ke+7TeL/QSxWmUD7vz550Fo7feY5Moo4I0aqmrOlUhpjd/tcXjWhDGt5YlXsGliy4R0WpT58KpiiJAxxkn4lPjUKtHrVJNBaAUiy3fbjVVYGgGOpfNLmlapJUyw1R0Mlj4RgYWvgzDVBbIEoxcD7L2e6zBGgxtgAaD64uUgbm3zwu5rU8wm8kVvmLFZdg2YTtWv7Um+DBFEm4DF829EHNvmxcyDcFoXh3ubo8eT3ZHNEItjrdO2BYx4UtQQ5Drd11bqo1BGCba4OI2hmEYJiwoytplfOci91OkNaA9mR+hHvOH9kPFX9QeORQkoNN3pGPla6uwd/o+U/sONq+t326LWuFbo331iHkL+6CoODlAkOUawzAF4ctBhmEYJiRntp0xLWwN0SEK5MxYc1HUNz/9ogRQzq47z41opOnFzUQOdSSh82VJ5LgWwwSChS/DMAwTkpL67hZAoogkdWkwHkqRUMcpR4lFNwlBxRZZcRkpyA2j5zM9jAfS+aJsEoOLALpYaDgiLWqfL8OUNyx8GYZhmJDUG1BXCKpIQGK2GvkBm9GyETikz4qtpFHj0oRaPZNVWtCcXMnTYa7bY10NLwLo/JIvMcMwgeG1EIZhGCYkbW9ogx0/7jQUmNQamFIYgoozCbAkWEQe8Y6fdhoXdOlAfK145B7PLVZhm9gF2ajdYr5FMtV7U0tj2SaHZV9mZJW2f9Z+HFp4WOw7pWkKml/aHPE14/LHUFe75pc1w+YvtmDP1D3I2JsptiMrtBaXtxBew2SJRs9n1b9WBz1Wz2e7o26fOgWP79JEYw0nWavVjkeNDjUi9twYJtZg4cswDFPBoHa8JEDJB5fcGUpKatdUdLizvWjKEEz0UmEcNW+YdcNsIbSKiF+vzhrwbn9hD0bpE6q7aHte//FUnEXHXfbC8vAn7fUYpu3JX9iIE2tPYOOnm7Br8m4hTum8kRAlQVq1ZVUUl8NLjmDenX+L7niSxXMSSLySPRvZjvV7vW/+a2SvYkfn+zuJWyDIAo7aIodi95Q9aH97exHhJuG87v31wps472Re/hgS3p0f6IQWlzU3nL8zy4VDCw6JTngkwuv1r8duEUxME1N2ZvPnz8cbb7yBlStX4vDhw/jtt98wduzYkNvMmzcP48ePx8aNG5GWloannnoKN9xwg+ljsp0ZwzCxwsG/D2L9RxtFFzLRBU2R0Hh0I3S4g9rsppZo3/RVseHjjVjz7lo4zzghyeSY4BGYjc5riH7/6is6pB1fcwKLHl6Ek+tPeXJSyeJMA5IbJaP3i73Q8Nw0zLpxtmhcYeRmMOyroah3Tl1MHvE7MnZnBBxPz1G2SFASLHCedubfT8ejTmktr2phGN3c+t02LHxokce5wu8YIr1DAob8bzAaj2oU9jk7tvIYpo2dLvYZLApOubhkt0ZzNbpIWTB+obCBM6Lb413R8e4OmH3zHHGei0TLvRcFXR7qjK4PdQm4DyoGXPHqKmz9egvcuWcvUOJqxKHjPR3Q/o52HDVmoooK6eM7ffp0LFq0CN26dcPFF19sKHx3796N9u3b44477sAtt9yC2bNn4/7778e0adMwYsQIU8dk4cswTCxAXcdWvLKySCtfId50YMB7/dH8kmYRaXZBy/ZZB7NF2gL5/CbVL9oBjATwsRXHhGCu3qYa6varK4RS9qFs/NDtR+PUBRnocn9ndH2kC3KO5WDmtbNwYu1JETWlFIlA9mopTZORNrwhmo5tgtTONU0JsyP/HMG0i6YHnw9pX0XCRbMuRLXW1RAOk8+bgpPrThkX50lAre61MPLHEUHFL53Hrxp/DdVBVxuhiatuR+fxnfHP00sNz/P5k0ehTq/aRV7jGVf+hSNLjwBBDtf6+lYiws/il4kWKqTw9Yc+bEbC99FHHxUid8OGs8tzV155Jc6cOYMZM2aYOg4LX4Zhop19M/cLYRgKEm9jZ16A6m2rozzZ8ctO/H33fFNja3VLxZhpo8XP9FV1ZMlRsf2pjadwYt0JzyB/YUYr8BpEisKAf/c3VdD217UzcWDOwZDRZxLbLce1wDlv9INZTm44iUnDppgeT3Ntf3s79Hw2sMMDPd/J5/5uen+JDRKRfTA7pPCl59X4/EYY8vHgAvev+2C9aE9tJJrP/W440oY2MD0nhilNzOq1Cp2os2TJEgwbNqzAfRTppfuD4XA4xMnzvzEMw0Qz6z9Yb8p1gXJYyxvKnzWL26EWCHbU7VsH3R7tglObT3kEb+FdeX+nwjnKazXCke7A/lkHDFMuKMIsivHCiBOdWHfS9FhxDE3Hlm+2wp0T2G8475QjrP1lHwgtesUx3Tr2/bm/SB7xps82G25L77dNn5X/+4lhwqVCC98jR46gdu2CSzj0O4nZ3NzcgNu8+uqr4orBd6O8YIZhmGiFHA+O/HPUWLypOnb+tiss8VYaUGGVGSgaWbVFlSL3kyjTTCz3r/9ogxBxRo0tzLpFqHlqUFEaKagg8ejyowEfS2mcXCrHpLQG//dE5t5MkY5iBL2fDi04XO7vJ4YJlwotfIvD448/LsLkvtv+/QWvhpnYRdV3Idf9ErJcVyDLdSXy3K9D0/n1ZWIbId5MouaqwnGhPKndsxaSScRJxtHIphc2KVpg97+Npo6TczgHx1d70yGCYEu2wSwkxMNxyKjZqSaKgys7sLhOaZwirMjMUL1dddMeyAl1Egrk6ZIQNgu5RhTXZo5hyosKLXzr1KmDo0cLXj3T75T7ER8f+A+I3W4Xj/vfmNhG1zXkul9AlmsYnNpXUPXlUPVlcGifItM1CHnudzhqwcQsZPllFiVeKXcrKhJZPZ/ubkowzb55rija830+jy47JsS7WZxnQl8UkENB7V61DdNE6PG0YQ1wYs0JkWZhFEkmarSrjppdaobdOCOxbkLQx7o/0c3UPvq82htpw9OMn5csofW1rQoev15ivu2aEUn1E6O6MQjDVDrh26dPH+Hk4M/MmTPF/UzlwaG+Aaf2pfc3/y9N+lmHQ3sPTu3jcpodw5QMshCr06eOscixSMLVIRqq8Buf3xjt72xnajmdnCpI/BLbJmwL6zgkbI3ocFd7U2ki+2bsx5RRU/Hb4MmY2O0nrH1vHVRnaBHe9+XeHhFp5pRLQJVmKajZOXikuMUVLQzPW9/XeqNOz9pnvYCDHJveL7YqtiLCl7yEm17QxDhnXCZnh9ahxzBMFBJTwjcrKwtr1qwRN59dGf28b9++/DSF6667Ln882Zjt2rULjzzyCLZs2YL//ve/+PHHH/HAAw+U23NgyhZNPy4iu0bkqf+BrmeVyZwYJtJ0vNtYvFGEte3NbUIP0XWRx1rYfos6flFh3G9DJuPbNhMwscdPWPb8cmTsKX7x75ElR0yPXfnaKnzX4Xvs+DV097jCkXAz6QaNRjQUzRyIItFL3zdkobupGQUJ8r+umRVS/FLjj5E/nSfSCQwhX92HuxhemPR6tidGTRqJ1G6p+fMjcV1/YD1cPH8s2tzgeY1rdU3FkE8Gi0YhBUSs5G0OUsWGkT+NEBdOhel4b0fPykCwDsqKhIRaCWh9TUHRzDCxQEzZmVEzisGDC9quENdffz2+/PJL0Zhiz549Ypz/NiR0N23ahAYNGuDpp5/mBhaVCIf6EfLUNwOUfxdGQrzyEmzKuDKaGcNEFurQRRZUAX18AQz8YACajW0acFtqDkHCdvvEHaLAirahphTtbm0LWxU7Zlw+A7knvJ2/9IL77f/uOaY6gPlD6QIUOS1NyNJs4HsDTI/fM30v1v93A44tP1ak0UNQJIjIardHu4bct+i49sMOLH12KVxZBXN4fa9Xj6e7i6YTkSbrYBa2frtNdKRzZlL3tQRhzdbi8uais18wDi86jJnXzxZdAAXUEMXrnZzUIBHn/TgCVZoWLT5kmPKiwvv4lhUsfGObHPcjcGm/FUpxCIQFNvl6xFueLKOZMUzkObTwkOiuRhZdQqhYJDQd2xTtb2uLmh1rBu32NvO62aJQqbBgpt+pSYWo/A8WUZYgIof1zqlnep67p+7BnFvmojS5fNmlSG6YXCyXDMcZh+iQRufSqPkEpQuMW3sFLHHGhW8kInf8vBNbvt6KrP1ZUOIUNByRJqK0lBMcbVCkf/uPO7D7991wnHEisU4CWlzRXKSqKHalvKfHMMXSayVv4s4wUYwEa/AktyJj+ePAxDYkPunmznWLyC2JMmqJG4zM/Vkiqqe61CKLIj6ha2ThRUvza95ZG5bwLc0CO4pKNhjWoFiil6Clf7rtn73fuOMaicN0p4gS1+tv/PytiVa0ub61uMUCFBFud0tbcWOYikJM5fgyTLgoUm/66jYx0g1F7lsGM2KY0odst0i8hRK9xJavtnjszUrgcEbi8PCiI8g6YD5Hvla3WqadA8KBotTxtePR7/WSFzA7M13mx2aZH8swTPnCIS6mQmOVRyBPrQYdZ0Ik68mQUA8WyXw7UoapCFBOr2FRnEmo6UFSg6T83ymL7viq49jy7Tac2XZGLI3XH1APra5uKUQ5OQfsnLSrRKK7sOhtMqYxej7XUyzJlxTaBxWxmbFdS6xd8uMxDFM2sPBlKjSSZEO85R3kuG/2FrjpARY9LEiwvANJ4gUQpnJBuayRgnKB/XNZ594xD/tnHihQbHf0n6NY9eZq9PtXX/R8todwdsg+mlN88asADQY1EGK6do9aAR0KikvLq1oaNsCgLCrqqEZ+vQzDxAb8Tc9UeKzyACRavoGMopXnstQWiZaJsMjmjOEZpiJhTaIc+JJDdl3V2lTLj/SS6D0w+6Dnd7+IMqVFUEe2heMX4ejyYxgzfQzShjYo/oFVoMOd7dB4VKOIil6i2cVNPV3NQvnZ6kDnBzqXiTcyOUNQOgm1FDbyD2YYJjgc8WUqBRa5N5KsM6Dqa6DqmzylbFJHKHL78p4aw5QbzS5qis1fbSlZuoPk8QeWFU8c5diKYyLSa7TN8hdX4LJ/LsG53wxH5r5MHPz7EE6sPQFHulPYZe36dRdyjucGjQaTIE1ulIy6/eqaniqJcipEI2eFnGO5sCVb0Xh0Y9GVzTd//0K0kT+OwB+XzhBOD/6LRb4odteHuwhbsNKE8oc3frIRm7/YgtxjuZ65JVtFlJuab5A9GcMw5mE7MwPYzoxhmIrKme1n8OugSeaEbyBPWwmoP6g+zv16WL5Tw/z7FghhaWafgz4cKMR3IE5vPYOpY6aJtInC+yLhSakVo6eMQvU25mzASLzOumE2jq08LgrrKPLsE7BJaUk495thqNbaE7X2x2Nttg2bv96K7IPZHguyc9PQ9qY2okjPH4rIbvlmK3b9tguODKeIQpMwbnVVS1Nd5AIde9rYP3BmW3oRhwmae1zNOIyecj5SGhXPwYJhKhLs4xshWPgyDFOR2fnrTvx9z3xKiC/o4+ttVkDR3Nq9a2PtO2txatPp/MdJyNFjnXxdvrxMGfm7cW6sHx3v6YDuT3Qr2jXN21hj+SsrsfePvflzE801RjYU25htoEDiecrIqUjfmR5QkIv2vSk2XPjXBUhOO1ugFw7UAGPu7fPE/gscQwZsSTaM+H54EaFsBFnN7Z+1P+hFBM27SrMquPjvsVHRipphyhP28WWYGEPXNbj1hVD1taIQT5HawiINhiTxx5QpPZpd3EykDFDnt31/nvWurdGpBtrf3g5NL2wiRFWT0Y1xessZ4XRgTbIgtXNqQD9e2cBCrTB0XLJd6/pIlyKPpTRJwdBPBoto7cmNp8R91dtWQ96JPNGNjO4nwUoNFer0qR1U/JF7BUW3gzk0kLCkZg3r3lsnCu/C5fiaE5hz61yPQC18DA1wZTkx44q/cMn8i5BYL9HUPjP2ZmLfX/tCukrQ8cgx4/DCw6Z8hBmGYeHLMFGBS1uAXPcT0EEFQSQc6AvcDQk1EW95DlZ5VHlPkanAUCRy2BdD4Uh3IO9kHmzJtiLFYiQqq7epJm6hIMsyyqM10/zBx5r/rBXR42DpADSXBoPqi6V/iqpSPrDwAaZDSMCmzzaL4rphXw4NuOy/6YvNhnMgEUldyshtgvJ7w2Hd++s8cwkmrDWIpiI0jx5Pdje1z73T9ohzbrgoqwC7f9/DwpdhTMKuDgwTBaI3x30jdBzy3qPmN93QcQI57nvgVKeU6xyZyoG9il2kD5TEIaHVNS3NNkvMh0Qyic5QkHCcftkMHFp42LON25NSQP8TFPmknOAcskcrtO/0Hemm/HjVPFW0Eg4HuljYO32fYU4zPU5RavP7dZr7hlbh8RtmGMYULHwZphzRdRW57ke8oaJgX5wSctUnoeueim6GiWYSaieg76vUMTE8Tmw4GfJxKpg7uf5UUIFJ91O0et0H6ws+IHnylc0S0r4sAOS0YNYVw3Ha4emUZwIqXPOJeiOE+wXDMKZg4csw5YhbnwcdR0OIXngfy4ZL46gvExu0vq41Bn800LxPsAbhhLB94vagQzZ9tskwkiyiqt9tE9FhH5QuUKtbqinxa69mR0pj80XMJLS3/xQ6Ul1YVJtt1dxgiHl/48w9mabHMkxlh4Uvw5QjqrbSZKq9Are+qgxmxDCRoenYphj4/gDzG2hkhbYQe/7YW+QhSlcgezMz6QrubLewFfOHrMeMco5JGLe+vlXAgr1AUGrG950niuI8s6KXbNBMuy+E4bdEkWRuasEw5mDhyzDliC7c+c0urRa3ryvDlA9pwxsgsW6C+VQDCVj2wvKiBV3hOnUVEpeNxzRG2rlpQfcjbMGaV0HHuzuY2j2J8/n/t8CTtmDyY0nR6LY3tzU3mC517ebdMej8yhb+OmcYM/AnhWHKEUVqTeVtJkaSvVmrMpgRw0QO6oZGUV/TebO6Z9n+yBJK/zkLRUlrdqxh6hvLVsVWxIuX5jH008Ei8isiupT3SykHtD8JIhI7evIo4WZhOEVdx7Lnl5sX495xnR/ohHrnmO8yR93ryGbO6Dh0buueUzesPGaGqcyw8GWYcsQqnwfATNclBVb5kjKYEcNEFmopPPLn80THM7NQo4nCiGipZiwCW1/bKmC0lLyC+7zcG+PWXiG8ers80Bm9nu+Jy5deKqzcKL/XDCTKM/dmmk5FqNq8ihD/3R7tam4D33ORJLS9pY2pSHK7W8xHkhmmssM+vgxTjkhSHOKVJ5CrPh5ynF25D7IU2j+VYaKVOr1qo2anmji6tGAkNxiBlu2ptfH2H7bjyD9HA+brkuhNapBkmK4QVz1OiOPikr7jjOmx5C180ZwLi91Vre0NbXBg9gHhWxxMaLe6tqVIKWEYxhwc8WWYcsYqj4FVHudtXEFI3o8m3RTYlQdgl+8q51kyTMmo19/kcrwE0YWtMJSiMPybYWh6UZN8izK6z5dGUad3bYz+fZTpyG1xCSeX1l7FVqJWwuI5fz1MtHUu7JBBdmc9n+kuotfcrphhzMMRX4YpJ3TdgTz1HTi1b8mJ0+8RC2SpKSzSaNiVyyFLqagouLW1cOt/A3ouJKkBbPJoSFKV8p4WUwa0uqYV1rxD7biDQyKWBHIwSzHqqDbog4Ho/kQ37Pptt/CvtYuWxY1QrXXZrIjU6VPH1DgS5pR7W1IoRYO6vVFqBjXvoNbK8alxqNu3rmkHCoZhzsLCl2HKAV13Idt9K1R9UQDfIhc0fSt0dBAtiysCqr4LOe77oekbvJFt+sJ2I099EXb5ZtiV8ZAk8zmgTOyRWCdB5NgufmxJUNFLhWl9X+9ruK+k+kkiCloepDRJQb0B9XB40eGQjSt06Gh5dcuIHdeSYBFFeGZRHSr2Tt8rbOCEl3GPWqg/sB4XwTGVHkk3bAReucnIyECVKlWQnp6OlBTzxuYMEwqH+qUQfUYVMgmWD2GVRyCW0fT9yHJdCB1ksh/Ya9QqX4kEyytlPjem7Nn5604se3EFcg7neLJ6vB8BEpP9/tUnrAYS5UXG7gxMGTVVRF9DiV97dTva394Oba5vDXvV0k3BKOwxvPTZZcLfl6LC9DVPXeDIKaL/u/3DcpdgmIqm11j4GsDCl4k09JHLcg2Ghv0GwleBIvVAknUCYpls191w638FFb0+Ei0/wyKHV/nOxCaaquHQgsPI2JkO2a6gbt86qNI0tlJeSPwufGgRDi86Yjg2sX4izp80qojNWmmw5dutWPTQ4sAPkpObJOG8iSNY/DIVDha+EYKFLxNpNP0QMl3nmBwtIcW6HZIUm7l8mn4cma4+JppvKLBKY5BgfbuMZsYwnnSAo8uPwpnhQkLteKR2Mdfa2J/1H27w+PoaULVlFVw876JSTTVwpDvwfceJ4nkFRSaP4CRc/s+lnPbAVEq9xjm+DFPG6HCENdrT4KLslkkjiapTO1czra1UuPUVZTAjJpaguMyRxUew+astOL7mhIhW1u5VC21uaINaXYtf9Ekd19a8uxYbP9sE5xln/v1JDZPQ+f5OaDmuhSmnBLJV2/jpJlPHPLMtHQfnHUSDIQ1KNcXBsHWxBmTtyxKFcvUH1Cu1uTBMtMLCl2HKGBlk1UQdos5+4QaDitskKTZFr4dwFpS4JTNzFopazrvrb+yZtlcUvvlyabMOZGHHjzuFf23f1/qIrmzhoLk1zLxhFg7MOVjk7Zm1PwsLxy8SDSq6P97NcF9HlhxB9sFscweWgB2/7ipV4Xt85XHRrdloHZe61h1bcYyFL1Mpic31U4Ypw4gTORK4tXXQdONcPjNIUgKs0oV+vr3BkGFTrkYs42mzbGY5lfKZy6dKn4lOFj2yGHum7xU/+xeQ+X7e+u02rHp9ddj73fT55oCi17Nzz39r/71OuDYYkbGHCjZNogO5x/xtCyMPRaDNXmoGagLCMJUBFr4ME0TwOtXvkeUaJm7Z7rHIdPVFlmscXNqCEu/fbrndG/UN9hFUIKEabHJsC19ZagCLdI4Jka/CplxVRrNiop2MvZli2T7kIoDuya91nDGfOiRSEz7ZZLgQQRFmEshGBGqNbNQ1rjShTnGSiQtNcnio3rZ6qc6FYaIVFr4MUwhd15Drfhi56pPQsKfAY6q+HDnuG4QoLgmK1BSJlq8pq9AbEZUKfCQlpCLR+j1kKfZ9fOOUx7xZVcH+3MiwSENgkfqV8cyYaIVaE5spvKK0hZ2/7TK934w9GSKdwQiKKu+fdcBwXN1+dcwtaHhpckETlCatrjLvG5zSOLlU58Iw0QoLX4YphFP7AS79V+9vhUNDFILSkas+BVUzjgiFwiJ3Q4p1AeKU56BI3SGjBRSpD+KVt5BsnQtFao6KgCK3QaLlO79mHL4GFp5omVUajQTL+zHrXMFEHjPi1Nc+mAq1zOLONSj88oOKxIxMjxLrJqLRyEam9pdQNyGsBhTFIaF2Amp2rmE8UIbpojyGqWhwcRvDFElx+NQbgQ31pSeLVsPx8sslOp4kJcOuXCtu5YGuO+HWl0LXT0OSqsEi9YIkUQpGZCF/3mTrArj12XBp8wDkQUZ9WJVLoUilGwVjYg8lXjEVSaXUBUu8+a+xxLoJIpJsJr81oU6CKWeHPq/0xvGVx5BzNDfoGEuiBed9f64Q6qUJPS/q1GaIBuz4eafopBfO+SsJpzafwpavt+LEupPiNajdsxbaXNcayY048syULSx8GcYPDbuLpDcERoVTm4Z4lEz4lhe6rsKhfQyn+hl0nM6/X0JV2JSbYZfviHgLYUmywiqdB6t8XkT3y1Q8GgxugK3fbDOVkkCR2emXzYAj3Skini0uayaisNSxLFCObcMRadj31/6QHddImLW+jgozzbVivvCvC7D4iSXY+8e+gtfLEpA2PA39XuuDxHqJKG2cmU64s92mxmpODXmn8kT759KE0lGoTTUVI/q7cxxfdRzr/7sBXR7sLG5mLjIYJhKw8GUYP3Q9jCptlG6Fdmnh1nYjx30bdOws8piOM3Cob0HVtiLB8i6nHzCG5BzLEWIrrmYcbMmRWS2glACKuOYeyw0anRWRW+hY9/76/AWaU/Ip7J+5X0QRz5t4bsD2x53u64R9M/cHXdQhcWavYkPra8wJX4IE97DPhopzQZ3c8k7kIbFBIhoMrg9LXNl9zYZ7rLKI9lLr5K3fbQvqzrH6zTWwJlnR4Y72pT4XhiH4W41h/JClWqbHSjCRSxdluLTZyHafG1D0+uPWp8KlTS6zeTGxlxK045edmDR8sugU9lOfX/Bt6wmYfetc0WiipFBKwJBPB0O2yUKIFiY/XcGno7z/+0Qyef3+cdF0OE4XdXxI7VwTwz4fCsWmFCyg8/4YV92Okb+ch/jU+LDnnVArAc0uaop2t7ZF45GNylT0+lwmqOAu0Dnzh553zU41St1lgl4H4Y5hkFmy6o3VcGVTox6GKX1Y+DJliqptg0ubJSzBdN18UYpZNP2EKDrT9AOGhSmBkKW6UKSeJj4aMmzy5YglVH0Hctx3iTQNY2Q4tC+Ew4Wq7/Ge01NlMEsm2qHP1aKHF+Pvu+fj5MZTBSJ4e//Yi9/Pn4rdU82kC4WmdvdaGDP1fNQ7p26B+2kRIqFOvOcjGuQjTnPJPpqDLd9uDRpRvnz5pejyUGdUbV1VFJ7V7FQTfV/vg0uXXIrqbWLX6otEd6g0Dt8FQrtb25X6XLZ9b86dg1YMdv9u7j2ze/cZPP3EXHRs+xGaNfwP+vf5Ap/+bxUyM8PpiMlUZiS9OOqgEmG29zMTGpc237OELlrY+oiDTb4UccpDkKSSnVu3thQO9UO4dfLY9bylZbSEXbkZVvnSsPLHaK5kWRYc+saNR7J1FmSJurDFBrnuJ+HUJobVIU1CA+jw2TpJsEjDYFfugkXuVGrzZKKbLV9vwaJHlgQfIHkitpcsvBgpESpcIl/fU5tOCRGV0iQFk4ZOFm2HjUhqkIgrVsTWBWpJoa/0JU/+g82fbwk6pvnlzTDg3/1LPa927p1/Y/fk3YbFhJSP3eHO9uj+ROhued9P2IC7bpsmfla94t7Xqa5u3ST8Pn0cWraKvZU4pmz1Gkd8mVLHqU5CjvtGqPrGQo/kwalRk4jLoOsZJdj/z8h2XwW3vqhACEjDduSqjyLX/XhY0V+rPABxyovetU8loOhNtHwRU6KXitmc2q9htwXWcbDAb259DrLdl8KlzYz4HJnohz5H6/67IbTjAmUgaDq2fBlceIULCWhKHWg0oqHYvxnRS2QdyIamVq5W2CRmya2B2jkn1i9YUEd5072e74kB75a+6CUUKjA06c4RqBjRn3lz9+COW6YKwesTvWJb74/HjmVjzMjvkZ6eV+J5MxUbLm5jShVNP4pc9RGvIA0kPlVo2IVc96tIsL5arNSJXPUx774LL+F7jufSf4RF6wSbMs70fu3K1bBIXeFQv4JLny4K2Sin1yZfIfYjS3UQW2QDKM5SYOHXjM6xhBz3PUi2zhOpIUzl4fSW08g00aaXltp3/LoTPZ/tEfE5KDbz8RrKdTWz1F4aZB3MwpZvtmLXr7vgyHAivmY8WlzRHC3HtUR8zdLNrSVR2+aG1sKZ4vjq48g76YC9mg2pXVMhK2UX76p7Tl1PBz4T7xcaG4rXXl4IWZYKiF5/6P4jR7Lw3Tfrcdc9kX/fMRUHjvgypYqnw5lRxEWFS/8Nup4e/v61b/y6ngVDgkP9NOycX2q8kGB9DVVsa1HFth0ptn8QZ3kgBkUvER/Bj7vnIsOp/hCh/TGxguOM0/RYcmQ4syP8z7QRSQ2TRE6uGdFbt2+dcrHJ2vfXPlHwt+4/65G5LwvOM06k70jHildX4qc+P+Po8qNlMg8S/bW61RI5zbV71C5T0Us0uaAxbFVsIf9E0+tUpXkV1OkdfAVt794zWLzoQFDR68+Xn68t7nSZSgILX6ZUcemzTS6vUyOFf8LfvzbNRLGW7vXnNd/atKJBHrrUFrho6kZx0eDSpkZoX0ysEFakUgemXjANmSa7sJmFxFu7m9safntRFLHtLW1R1pxYfxKzbpoj0jGK5LZqEO4Ff46bicx9mTgw5wBWvbkaq/61Gnum7xWetxUJcrUY9MEAT9RdDix6yblDjAlxgXJgv7lUOIptmB3LVF441YEpXXTzXre6Hn5uli6W8M3uP9NUvpkZyOFA149CkpJEAVgsmK/blZvgds+K2P50hON5zFQEKDJXvW01nNpy2tT1rDPdidVvrRY5pZGk7S1tsG/mPhxbfjxo4RSlFZR2i+BArHt/XfDMLp/4zXHh18GTijSbIBHY+b6O6PJgF1QU0oalCU/lf55aitNbCnaVo9SLvq/2Ro32oQvS4uOtpo8Xn8CyhgkNv0OYUkWWGkHT95qK+spS/bD3L6E6dJhbNpSlmigpbm0VHOp/4dbn+rlHNIVNuQk2+cqobvhgkXvDrjwEh/qmd7Gn6GsioyM0rDOxNwlSGJ7HTMWALvA6/l9HzLvjb1PjKeq685dd6PVcT9ir2iMaSTzv+xFY9uJybJuwHarj7KoPLa2TQ0Cn/+tY5hekziwX9kzda2gnRh+9QB3WqJvaqjfW4MTakxj21dCYuKA2Q71z6uGiuWNxfPWJfHeO1C6pqN6mmqntO3SshdTUBBw/HjqQolgkjB7TMkKzZioqLHyZUsWmXAG3e57BKAky0qBI3cLfv3wZHNp/DYS1DEXqDFlqgJLgVKchV73Pm1Ps7x6xG3nqU8JSLcHyTlSL3zjlLihSCzjUj6Dqq/Pvl6V2sMu3wiKNRrZ7GDTQxUroL2+yomMqH83GNhX5qtRxywy05H9m+xmRYxpJLAkW9H21D7o/3k2kDDgzXYhPjUP9QWXbLc2fvOO5xqLXBNRSedOnm8rEa7esIBFfq2uquIWL1argtju74dWXFkILYY2munXcclvFiZYzpUP0fkMzFQKLNBQyWhnkluqwK+OLFd2wKVcJP+DQb2UNduXOsPddYA/6PuSqD3gFdmD3COp25tS+QGmi6y5o+knoem6x92GVhyPJ+guSrQuQZJmMZOvfSLb+DptyAWRZhl25x0D0KpBQDTb54mLPgYltuj7URQjP4hBp63hbig1NxzZF62tbodF5Zd8tzZ/inpNArHprTaWzYgvFAw/2Rv8BDYWzQ2F8Xx2vvD4EHTrGjs0kUz6w8GVKFUmyINH6NWQ0C/CWIzEsIU55Uoiu4kAOC4mWz7zit7C49vwepzwFqzwUJcGhfmcYAaXHHernwjO3NLquUQOKDFdHZLp6IMPVDlmua0UL4pAz0p1iDM3fqU6Gpp8ukFqiyB0gSwXzIG3KxbDL93p/K+pjLCEZiZavS9x0hIltanWvZdga15e3aom3YOlzy/Bt2wn4vN6X+LrFt1j48CKc2lyxugHG14oXOdCR+GYlJ4ijy45FYloVAptNwc+TLsNDj/ZB1WoFiyzbtK2Jr78bi3v+j7puMkwF69z2wQcf4I033sCRI0fQqVMnvPfee+jZM/Cb/csvv8SNN95Y4D673Y68PPNFVNy5LTJ4BNhfcGrfiZxfCXZY5MGwKddAkZqWeP+afhBO9Vs4tR+hg8RdHKzSCNiUGyLSZSzD2Q86DpsaS1FUEpSRwtNJ7jZvpNlfVJMoVWGTb0Oc8miBiDl9rJ3ap6KbnQ7/ghILrNJYxFuehiSF7qrl1pYJH2NqWkGuGxJqCQ9jm0w+xuEvV4aLrudAx0lhxRaJ/GwmsuydsRezbqD3RnBIGFPL4SP/HBWOBf5pAEI060D/d/qhxRUtUFHY9sN2LLh/YUT2NeijgSK1hCmIw+HGiuWHkJXlQv36yWjXPrXC5EMzxcesXoupHN+JEydi/Pjx+Oijj9CrVy+8++67GDFiBLZu3YpatQIX2tCTp8d98IejfJAkG2zKaHErDSh6GWd5FHF4FLquRTzPVkdWubgdaPoh5LhvJ/kbpJkEeRn/D4rUUkRqxfF1HXnqC3BqXwXYo1t4JqvuTUiyTIQkFezs5I9F7iluvn2W1WdH1bbCof4PLn2q93nT69sWdvlGWOWLojqHujKRNjwNDYY2wMG5BwM6K5CwtSVbcXjJEU+ntUJDfCJ4/v0Lkdw4BXV6VYwlanKTOLzoMHb8tLPE+7ImmnczqEzY7Rb0O6dheU+DiVFi6hvk7bffxq233iqiuG3bthUCOCEhAZ9//nnQbejLuk6dOvm32rUrxh9XJjilIYxkmO//LkUwGuppABJI9BY4oihW8y3eqPrSIKLXhwpN3yLcKcxSVqLXpS1AlvtCuPQp+aKXoPnmqg8j1/2wuLBhyh/y0x362WA0v6yZqPcUnqwWGZLF816p1rqasLISAjfE25cq/Nd9sB4VBfqsDPh3f/R6sScS6xW8sExpmpJ/fszkC9frx50RGSbSxEzE1+l0YuXKlXj88cfz76NCnGHDhmHJkiVBt8vKykKjRo2gaRq6du2KV155Be3aBa+UdTgc4uYfOmcYq3IZHOpbBu4R5E7RCjKaR+y4Tu1XE1Zw1KBjh7gpIMeGr/PTIIKjwalNgF3/P0hS5GymSoKmHw8R3facA4pWK1pb2JWby2WOTEGokIxEXteHu2Dnr7uQfSgblkQLGo1shNSuNfFNi+8MXQ7o8f0z98NxxhFRy7PyhMR8+1vbiUYbJ9adFM8tPtWT/7vxk01Y+swygx0Aba5vHdFiOYZhPMTMp+rEiRNQVbVIxJZ+37JlS8BtWrVqJaLBHTt2FDkfb775Jvr27YuNGzeiQYPA1lavvvoqnn/++VJ5DkzsYpMvh0P9mC6lQghRcqe4O6LR0YL5uQZjqXBNIncJyi80LrDTkQ5N3w5Fao9owKlRC2RqiRtaKFH7aZt8AyQpUl3omJKS1CBJ+Ob6485zB/SqDYgO5J3MqzDC14fwq+1cMD+9/W3tkL4rA1u+DPy9RZ/h2r1qo+ujbMvFMKjsqQ7h0qdPH1x33XXo3LkzBg4ciF9//RWpqan4+GMSMIGhiDKJZN9t//79ZTZfVd8Np/obnOovULWKs/RXEZClGki0fAkgMcDHxiPA7MqDsCnnR/S4EqoWY6xJsSH0BgnN6MClUnqDcRoDNSxR9bVlMiem+Cg2xfSyPmFNrjz5rP1e64PzfhqBqq0Lfr7jUuPQ7bGuGDlxRLnasjFMRSZmPlk1a9aEoig4erRgly76nXJ3zWC1WtGlSxfs2LEj6BhyfaBbWeKxqnoOqr64wP1U0BOvPCU6bjHlj0XujGTrn3CqE0R0UscJesfAIg2DXbkeFrl7xI9pky+EQ/vEIIJLKRZNIEueyngZjaGBCjqNDFvkIlZm5UlY0e0wxjLlF+1sPKoR9kwL3cmMxtXsXAMJtRJQmajfvx4umXcRco/nIutAFpQ4C6q2qCLypBmGKT1i5hNms9nQrVs3zJ591reU8nbpd4rsmoFSJdavX4+6daOnYIAq2LNcF4uCpMJQQU+2+xq4NGqPG31QMZWwnNKzim1KT563Lm0Osl13ItM1GlmuK8RStr/fbDRBvsFxlvFIsS1DinUHqtg2I9H6XqmIXsKmXJ3vdxwcSrG4PT/FwrON0euhCMFeFrZkZpHCKSAMYyxTfrS7ta1xjq+mo/3t0ZFuUx5Q7q+vfS+LXoYpfWLqU0ZWZp988gm++uorbN68GXfeeSeys7PzvXoprcG/+O2FF17AX3/9hV27dmHVqlW45pprsHfvXtxyyy2IFnLUhwDkBono0bKvjhz3/dB1897DpQ3Nhfxds1zDkOFq722qMBAO9RMhgo23TxduBbmul5HpOgc57lvg1mdB0zdB1ZcjT30Vma6+cGkzEc2Uha0W2bQlWP7rXZwp2kyCoHxXq1/7YJt8kYj6Bu+WR9spiFN8TSqiA48dm9HSuAQJDaBIkfNJZkqHrINZODDnIKo0r+K5o/BL6/34tLutLZpcQO9XhmGY0idmUh2IK664AsePH8czzzwjGlhQ7u6MGTPyC9727dsnnB58nD59Wtif0dhq1aqJiPHixYuFFVo04NbWQtM3GoyiaEkmXNpU2JSz4qa80PUMZLuvg6oXzEHWcQB56mtwqj8j0TpB5MQW3daNPPV1OLWvC1hVeVALPWcnctx3ItEyId9LNhagCLhLmwKnNlF48EpIgEUeAbtydbHTCqzyECRZpsChfgaXPjn/3ClSd9iVG2GRzi1QUCdJCUi0fods1w3QsN3P4cE3Jh6Jlo+gyMHdTcoDq3wZ8tQPAGSHLCCMU+5kL98ohlZ/Vr+1RtzofZnv8Vso8Fu9TXV0uKs9ml3clP3VGYYpM2Kuc1tZU5qd2+hL3qG+a6ICX4FVPh8JFhpbvmS77oBbnx1izgoUqRuSrFShfxZ6m+W474Nbn2ZiGd6HDEXqgSQredlGP1ScmO26FjoOeUWm73l6Iq/xyuv5TSaKi647RH4rCWqjzmuURuLW54mLEQ0kwpNhlc+DTR4LSUpCNOLWViHbfT19OoJ0qbtJtLhmoRS9rH1vHVa8vDLkmPZ3tkOvZ2PngpZhmOinQnZuq3DoFLkz8wWuQRdjyxdV3wu3PtNAuKpQ9WVQtQ1Q5LN5e259LtyiE1c4aCL3mY6rSI0QzVCKR7brGug45rvH71GPgKMGDNTcwir3L/ZxyHNXgrkmLGT3ZZWGwioPRaxgkbsi2TpDpNJQ1JxWO+gzokh9YKf209JgFr1RjCPdgdVvrjEct+mzzeh8fyfYq1Qs+zKGYaIfXi8sR2SpsUnrKTkqhB+lW5gT6hY4td8L3ONUvwmRcxoaTd+LaIcaTeg4Yui+4FD/U4azilXiIEvVISMNEupDQRfY5PNhkfqw6I1yqImF6jT2kKYWxjt/LnlLX4ZhmHDhiG85YpVHIFelJWejgjAVVuVylDe6fsp7rWTcSUwHjT2LW19hqqlCICREv7+np/mCmQj2ypiIYJcXLu1vkdsNUPdEbwtmHEKuugp56jtItH4DxWvbxkQfZ7adEa2MNXfovxGyIuH0tvQymxfDMIwPjviWI5IUjzjl/4xGwSpdCkVEh8sXSapqMj+XKu+9ldz5GDcmCEw8FKlgR6hohArZzOYu6/rBEI/pcGvL4FR/glOdBE2nKHLlQNU2Isd9WwHR68Hzs46TyHZdBU1cgDHRiMeOy9zfCDmM5hYMwzCRgoVvOWOTb4Zd9tlK+acCeH62SKMRb3kJ0YBVHmUyauuGVR5d4B5FalWMt5sCm3wZJIm6pUU3EuLCGB0f8F6XNh1ZriHIdl+JXPVR5Krjhd0beRyXlgAmoa3px6HpB0XhXHmSp/4338IvMCp0nIZTi41ix8pInd61obmNhS9FhOv0Ntd4iGEYJpKw8C1nKGcxzvIAkqyzhR+rLHUQHdus0iVItPyGROu/IUk2RAOK1AwWaaBBri65OnQSN39s8rVhRn0V4UUbp4xHLGCVh5nKYZZQDYpU1EbMqU5EjvtuaNhX6BFNeBxnuS6KqPjVdafXi3kwMl29kOnqjwxXN+S6XxAiuHSbnmR5G5+cFUiafgZu/U8TF1aa8IBmopOGIxoiPjUu9DeLBMTVjEOj8xqW4cwYhmE8sJ1ZOdqZxSK0zJztGgcNOwMIWRkS6iHJ+qPocOYPRROz3VdAFb7FRuLGAqs0BvGWZyBJhVMmohNV24Is9/kGy7wy7PLd4kLHH00/KiK7oc8LdVobikTrRxFpQJLtvsmvW6D/nBVISBL+yYrcpsTHOnvMLBGpdahfQ4dHWNOFjU25ATb5Cmj6Lu/5M4MkuuZxoVt0cvDvg/jzqpmeC5uifyLE63buN8PQYEiD/LudmU7s+HEHtn2/HdlHcmBNsqLJmMZofW0rJDcMbdvHMAwTjl5j4WsAC9/AIsahfSWcGnz2XRTJtMnXwKbcCFnkAgfaLh3Z7ruh6ou90VH6VpS9gq8a7DI1eWgOi9wvYAOMaIY+Rrnuh+DSfwvhzNEdiZavhCWZP3nqf7xuD0YRcRnJ1gWQpZK13M5xPwuX9l2I45H4rYFk699F5locNP2E92JpVyGR7RGu1IUtTnkR2e4LTe7Rhiq2LSWeF1N6HFp4GIsfXYz0nRmQZM/rTI0sUpqmoN+/+qDeOfXyx57echrTL/8Tucepg+XZt4ikSOItMvD9AWg2tmm5PA+GYWIHFr4RgoVv6AYJOk6IbyoJNSFJ5kxC3No6uLTfxNI9NVKwysNhkYaY3j4qRa/6JFzC2cG/ccVZKFc7wfJGQCGZ5boEqr7a1LHilbdhU8aWYK7pyHD1Ep3xjI/1LixybzjV7+DUfoSO4yI/2SpRJ7rrocjm2gZnuSjSvypERFuGRRomVgN80eDQke8hSLR+bOrYTPl+Lo78cxQn150Uv9foUAN1+tQuEKl3nHbg5/6/iv91NfBXETXpG/nLSNTtwznBDMMEhxtYMKUONUgw20zBH4vcUdxiCWrVrOGU6H5WOBrt1L71il4xMuD21PjD03Gt6PnSTYhQv6OhJLi0uSb3IcOpfotc9elCLYSzRdtkl/tXxClPi5bJRhc5qr7c4FiUxzwTNvlOOLUPDRuk2JXrTMyfKW9I4JJYDSVYt363DXmn8kIvdkgS1ryzloUvwzARgYvbGFPougZNPyaitNHQRa6sIGuxbNctyHB1EY4Lma4eyHJdBpf2Z/55caj/M7EnV1CvXxlNTTf3oBxqsjqjYrcMZ1dkOHsjx/WYsAIzg450090CVawqJHp9eCK3eeqLcGnUvjo4LtHIRDFpgRcHi3ROyPnZ5FtFKgxTMdjy7VbDDB+KBB+afwjZh+m9yDAMUzJY+EY5Hl/X1chzv4Nc92twUF6tXnbG77qeK4QdVf1nunoj09UXGa4eyHO/LnI3KzJO9Udku8fBrf9dIApJaQnUZCHP/QZUfYOJ5XlCg0udFPARuzLORMEfCcN6yFOfE1Znqr5ORJApx9ql/4Is9xjkqe8bzoJysc36rHoUSShVIsNhcEyyHzOHLJ5PguUT2GVqYFGwoElCXZEHHKc8ZnJ/TCyQczjH9NjsQyx8GYYpOZzqEMWo+g7kuO+Dpm/2Rs1IjKjIU1+Cnfx/lQdFukFpoeuZyHJfDU04MfiLpQw4tE/h1CYhyToRslTxbIlUbRNy1ce9z7uwKPWIQYf2IfQw2jBrOBPwfkXqBUXq63VZCCaAaR4aNPjaN/u/Hp5tHOrbkFELthBd/qzyEOSq5DmcZzBb3WQnurUhO9F5GpmYiTDrkKRqwrovzvIQ7Pq9cOtLxXtQllKhSN1K9b3OlA+KXYHqMNfR0ZLAX1cMw5QcjvhGKaq+B1muS6Hp23z3iMYQHkHigkP7CLnup0p1DjnuJ6Dpm4KIIE9hG6UB0HJ/RcOhfmni4yHDrf1lep+yiLYGzoWMV14O2tiCICszHeTjG1ok5Kn/Dvl6UDGhTb7OQIz6LrLMoeseZ49AWOXzve9bI1RY5ZF+87TDKg+ATTkfFrkni94KSsPz0jzuDQYk1E1A1ZaB3WIYhmHCgYVvlEKpBJ78yuBCx6VPFGkQpdWC163/YbDUrULDDq89WeTQdTdc2gLR1MGpToWmm10ujxwufaqpZgoatokUBGOhKMOqXBLwEfI4zlHvokuNINtKcOtzTH1cdRyGqi8LOSZOeVAIad+8Cs+TrMxQpOV0cMj3NxiK1EXYlRk1PbFIg6BIbFlV2Wh7Y5ugbg75SEC7m9tCVvjrimGYksN/SaIQamhAVe7GwksRlfelgad4y0zUT4FTmxaxfGaH+i0yXf2Q475epBrkqv8nOovluB4VzgplZdNmnApwFmqrbNS4AoiDTQ6cguDSpnnTWYJdZOj5qQ5m0PTDIR+XJCvilf8iTnmjQBc5CdVhl+9BknUabPIFJorSKO+4AWTRjjrYsSQkWD4SObqB/9zIorgv3vKW4fNiKh6pXVLR/clunl8C/bmRgPqD6qP97UW7HTIMwxQHTpqKQqhgypzIUeHWV5TKHHT9jFeoGM1Dgx6hiCzlqDq0DwI84oZL/xWqa53oCidJ5js5ubW1cGoToenUaY6Wz8+BVb4UslQ96DaeZXWKYmaZOoZVvgo6MuHUPveKRf8LFvrdhkTLZyJXNRBO7RuT59ockhQ8ZcKtLRFpHG59nkiZkSgnWL4bNvkSyFKjfI9Vm3KtsGkLjQ67cjMkMloNATXcSLJOhlP9UuzTV/Amjq1cC7t8vUjBYConne7tiOS0JKx+ey3ObDubB2+vZke7W9qi0/91hGzlGA3DMJGBhW8UouvhVC+XTn6tJIShmaITOSJd1kigBha9/mkV25Gnvod4yxOG+9P1HFEY6NZnFxCjqroIeepbiFdeg025KOj2NvliOEV3s9BthEVhmpyKOOlJWOQ+QlSq+iLv4wmwyZeKtryK1Dj4MxOiPFKvow0WqU+QaPobIjfc/3yQKwR551Int0TLd1AkT5tiRWomzhE5SJztrufD06TDKl0Am3ytqVnJUjXRqpmK1jxNTyhanGoompnKQdOxTdHkwiY4tfEUcrwti1O7pkKxcW43wzCRhYVvFKY55Kn/MjmahFf7UpkHFRqRT6txdT8VJZltNRscan9cNFpaGE1EDOP08ZAkciYo2EZZFxFM6tYiI8d9r9eGzDNHv5Ei0pmrPiQix1Z5WMAj2ZTr4NS+9wrSYOdAFcIvz/05XNoEaDgkosoWIQgvFULYXFFWpL7cFVjliyFJRfNzXdqPXtHrmXdBNOjIQLb7OiRb5+RH1G0KRcbrI0/9EKq+MH+0jEawKTfBJl8VtnCl7nwSuBEBUxRabajRvoa4MQzDlBYsfKMIisrluG+HjqMmt6AuVuYibuEiS7VglcbCpU8KEY1UIEutoUg9Snw8j0g1E2HOg0P9DHGWu0UurkubDIf2hddyjUiGgg5QYVxwl+t+Gm5prfjCpfa7FmlwfttkKrRKsHyAHPddASzNPAJdQV/kqvcUeiwPbn0a3OoU2PEA4pR7DedhkfrCrZM7hDlbp8BQrmwLxCtkwVYQcnnIUz8I2k75rPg9JSzq/N9TJN6T5D6ieYmuHwWkRMhoUqDtLMMwDMPECrzOGEWo+irRmMCcAJJgkYZDCbCsHSniLS8K/1Tf8YpW/9dHouV/ERFBFK01i0P7BJpGqQx3icitpzDMR6Yp0UtHpAsMp/6RiITSBQcV1bk0Kir0QNHgJOsfsMlX+lmNWWCRBgCo4T1OoNfK56v7Dpzqr4Yz8QjNkoheG2zyjUHzn8lrV8cBU968Tu3noBdCdHFAFwQsehmGYZhYhYVvFOFp72ouCC+jHRIs/4GG3XCq38Ohfi0swDyOBIhYkVSi5RvhMSuj+dn7UQt2ZTySrVNE4VIkCJUDW5QMIXjd+izv7yXJj/X5I5MsPIEc9x1waTP85tVcXACkWDeIW7JlAzR9N4BTJvYtwaH+R0TyQ0F5wlb56mLOX4FVGod4y5NBC8Q8ObVm0D1RXYZhGIapoHCqQxRBS83mRBz5nrZHtvsmqPoS732eZWzKn6S2rjaF7KhKDnXSsinjxI3aF3uEYmLEo342+WrkqhTtNoPFK3rNdBcLB9qfhFz3E7BYKe3Bnv+I5/kmwK3PgIY9pvenYZ+IuFqkztB1p0jp0PSDkBAPi3yOyKH1NLB4XrhjeLyTw0OWA7tF5M+9UPvf0GPN+/cyDMMwTKzBwjeKkERnL3MWYk6Re+ufHuARgdTdK1e9X9hr2ZWrIzu/EDZZJcUqj0GuKKYzYyEWqI1wpKAUiDPCxzjQxUOe+8Ow96jpR+BQv/JEf4WVl/c1VildZRjiLS9B108IUR0+VFw4ymAMva9IxDtMNNkYY+qo5JrhSaFwQpbSuPkEwzAMExNwqkMUYb69Kwk/Z0jxl6c+B00/jliBXBrs8q0mR5eW6PVhgaqvKXKvQ/0cGtaHvTe3NgN56vP5/rVnL2x00ZEty3Ux8lRyXAg3ik6R/6FB00QoxSLP/S9ku0eaEL10bCts8hUhR+l6JnLdLyDD1QPZ7quR474RWa5hor02eQQzDMMwTDTDwjdKoDa9nta8VQ0EkO8lM4oK63BqPyCWsCvXi0Kt0NC5Mb90X3wKnl9V34U89eVi7CcBLn1KiMdV0WbYk+IQjqCXIEstkWB5M+gI8kU+a2EWCnKpUJBgeT9okw2COudluS73NtzILfgs9DXIdl8LlxZ+qgbDMAzDlBUsfKMAVduATNcA5Kp3isKt4LmrUhgeqBrcmhl3g+hBklIQp4RqTuG5IIhXKCWi9NIuKOquSK0L3ONpDS0Xw2KskQmfXi1M0VtL5HEnWX4K6NnrE6kO9X1Te5PQHEmWX2CVh4Ycl+t+FRp2BJmrx+84x/1ATK00MAzDMJULFr7lDEUSs9zjRAetUJFcsg6LUx6HXb4ljL1TOkRsYVeuQ5zygoiUnk1D96SiU3MKikpS7q1dvi7M1AAJitTbRESZiBc5x/64tTlhp1iQv7GG9IinZiRZpsKu3ApJ8p2joji1KaZffx2HIBs0QtH1dLj03wyeiyf32qn9iPKAUjtUbRNc2myRdqHrRukdDMMwTGWDi9vKmTz3O6LpgVHqgl1+FHZltCeP0pR7lyIaGsQa5BxhlUfAKo2CW58JVXj0ylCkzuJ+n9MC2amp+naRIxu6MYPv+i4BCZY3hCii/OdQUDRVkhILzku8RmaRYZfvhl25C5muQWF4TxgXNsroDUWuabgnj+WaWTKh6RugSB2CjnAL9xCnyZWGmYByN8oSSrHIc/9btLU+SzLs8tWwK/cVcOgo/ZSlrdCRC1mqJ24MwzBM9MDCtxzR9JPeSn6jiKAMl/4t7BgtPF8lNICOgwZiTxUWZLGCW1skOrJ5Orjp3kYRo2BXboJF7lhkvCRZkWD5CC7tFzjUL6BhW4C9+iLCSUi0fCmswyiiTOcmT33NW0goeW8kOC2eqHqAbniy1AiqTn64xlcdCcrPsCqdvdu1gCqW/s1crRiPKSzIg2NFOLj0FaLjXTA8Vnbm0PVslCVUdJinvhRgBSATDu1/cOsrkWj5ulTFL1nVUWMVp/pVAd9kReonuvdZ5J6ldmyGYRjGPJzqUI5o+k6Ty+CaN/JJwkdGvOVxwwinRRoBi9wJsYBD/VgURrn1BX7Pyy1a/2a7L4ZTnRwgf/UrZLkvQJ76OnRkwypfi3jlS9jlxyBL7SChHhSpPeKUZ5BinQ+L7BGihF25EcnWpYhTnoRVvkCkNdDPKdZlsCs3FJmfqm0EdDM2cxSZ7pgvej3HurqEDTYKzUWfDVXfaziOWg2HtV9tdcjHzUcuZWFvVlao2la/okM9yGdnJRzqf0ttDpRSke2+EQ717SLNQlT9H2S7r4JTnVpqx2cYhmHMwxHfcsWo6CnwNYpVHol45XXkqk95o5a63/5U0co4wUIpFNGPS5snxKuHwhcBnt9z1QehSC2hyG2E0CGRrOOkdww9d/LdnQAXJojzkmyhDnihkaWqIppsRJ76ARzqWyZfKx125YEC93jsxjoHtEcrHoro1BdveSzkKIvU3xv1NdcK2q3/Bbe2psAFQoGjSj1EnrlnpSEUGmxKaEu0SOJxmJANLiA1OLVvYdfvFg1ZIg0VEar60iDCm+YlIVcdD4vclVMfGIZhyhmO+JYjJOY8jQUMR8IidS9wj025DMnWxbArD4nlVBImNvlyJFomIdH6ofDFjQUc6v9MvQ1z3c9D1XYh232N1w9XLyQ0SGCoyFUfFmkTkZnbT17R69t/MGiJXUG88ias8sCCj0gWxCuvRGQ+vnlo+hbDUbQyQKki5nGKc0vFlsH2F6fcbyKvvKUQ+2WFS5tlatWE3jOqvrFUor0O7WuDqD69TzU41diyF2QYhqmIsPAtRyQpGTb5YhPRRMrXDZR3WgNxyp1Isn6DJOtExFteDpgPG61o+gmxFGymU52KZchyD/dGekOL0DwTNl7kAKDreeL/oo9pyHN/gjyVUkqMsUjnItk6HzbloiAjzDQlifxKQZzl/8LcrwMOd/BzZ1MugV15OMAcPH9GZDRBovUrIfbLivCKDs3nKZuF0igol9gYDS5tesSPzzAMw4QHpzqUM3blfri0udBxPIigo7a2o71L1xULXVh9hbeFMZTTuRSaflAUsxWGUiUc6pdw6ZQ3TKLJBqt0vsj7VeT2QvTmuG6DG+QWYQZZtIeWpbpBR0gStQyOFDIUuZupkYrURLRE9jhfmMkzVuHSp0LXn833B1b13VA1EneqaJhhl++AVRosUgcoTYXEsiw1hk2+SrROLiv3BB+UOqDpmabeG1KA90NJofxy82PNtONmGIZhokb4/vHHH/j1119RvXp13HTTTWjd+qzJ/+nTp3HJJZdgzhyzgoEhqFNWkvUX5LjHe/MEZb+cRQtsMvnaPgpJCredbfQjIXDzhUig6YeLCF+nOg25qm+53neR4RSd1VzuSYhTHoFT/bWQJZbhkaDrofNeaR5kFeZZai9poZskUlrMQp3dstzXCLsyc5Ad1wEAJ5DrfhaqXrAJiozmiLM8jXjLS6XaQsQsNnmcoT2dp+iwCxSJmolEFtl0Qxkp5MURwzAME2WpDhMmTMAFF1yAI0eOYMmSJejSpQu+++67/MedTif+/pusqJhwoS/EJOv3SLLMgF15EHb5dtHEgZwH4i1PlunScVkiSzWFPVtpZNxIhWSZqm32il5PLnBB6HddFNmFJ3p9BzO2GLMrtxuIXk+esKcgLfj5iFOeFufN9NSkFCRZqKGEJSx7sCzXRd4LsYJo2Ikc941waWTDV/7Y5Iu83QwVg6LDcNM+zEGNP2Q0NdFMRQ/rgoVhGIYpHUwrjjfeeANvv/02pk6digULFuCrr77C7bffjs8++6yUplb5UOSWImc3zvKgsMEi54GKjl25LaJ2X4SEWpALtRwmMVc6yLDK5xmOojQAu3yv97fCIo1+l5Fg+TcSLT+KXNmz9/u61lVFvPKa14c4PKjQ0SL1Mf1x93RoywqSeuMpKsxxPwRdL/+le0lKQqL1O0io7bvH71HFW3T4Bqxy6aQK0UqMR1SHSrVQhDgn6zyGYRimfDEdBtq+fTvGjDnbxvXyyy9HamqqiAK7XC5cdFGwwh6GCY5VHixSDPLUf+XbsZUMCTblekiSUqCbFqUzRLp1sC9Ka5PN2XfFWR6AonUWDTdUfaH3Xgus0mjYlZuhyO3EPUnWv6Dqy+HWl4vUA0VqIXJ1S2LFZVOug9tNPsmRgEReDpzaJNiVa1DeKFJjJFtnwqVNgVObKPK7JSSICxKbuIBsUKrHpxbaGg7Cob5R6D3sEeESaiLR+m3IFtMMwzBMlAnflJQUHD16FE2a+KJRwODBg0UEePTo0ThwgPICGSZ8LPJIKOo/UFFSYUaFgP1hl28pdH+OaT/bcI9HfsmUpx2O0KcbdTejwijKcy5cEEZRRIvUExb0NHTFcGk/59t0UcMOq3ypcPsojEUaAqs0Fi59EiKDJNpnR4PwJSQpXvgHl6WHsD+0UmOR+sGpfitabetwQkZd2JSrYJMvFSknDMMwTAwJ3549e2L69Ono3bt3gfsHDhyI33//XYhfhgkXVduALPdVXqspM64N8C7ZJxawkZJQXUR6yXWA2hkXJD5C0eSzSKgrRG9xW9FS62FJPIfwIQs2p0Z2a28WSBNx4Q/kqW+JCLpduaWImI63vAFZbQCH9kEY5zroLErpYiJ2IStBi0wrFwzDMEzMC98HHngAixcXrPD2MWjQICF+v/6ajNwZxhy6Tk0TbvFGZM3m+dLysc1bsCVBw1EhIMk1oajg9W4hWb22XuaaHRiTgCTrjwHt0soCp/YZ8tTXgjzqRp5KDTMsRdovU/pHnGU8XM7pokitZCiQS8ElgWEYhmFKE0kP5ODP5JORkYEqVaogPT1dpHswkcOpTkWuGn61vYJuSLB+FHBJPxhubTmy3ZFYBk9AouUbWOQuKA90PQMZLnLCcBiMjEeKdZmILBcmy3Wd16asZEWFSdaZUKRmJdoHwzAMw5SlXuPObUy54dZnFOstqGINsl2XQtPPmGop61R/g0N936/yv3hve/KwTbIsKDfRSzg1KtJzmhiZC5f2e8BHPN0CSyJ6ZVili1j0MgzDMDFHzAnfDz74AI0bN0ZcXBx69eqFZcuWhRz/008/iUYbNL5Dhw6iCQcTHWh6ejEFmAoNB4SYDbzfg3Br6+BS5yLDNQC56oNw64ug46hvRBjH8rhDWKShSLJOhiJHsgtb+Gj6VpMtiy1Q9S0BH7HKIyGhvsn9KAHOxfmIt1A6BcMwDMPEFjElfCdOnIjx48fj2WefxapVq9CpUyeMGDECx44dCziecpLHjRuHm2++GatXr8bYsWPFbcMGs12sYg9NPwSXNh9ubRF0ISyjF1mqbVJ8BUIV1lW6TkVxHlzaLGS5LkGmqz+y3WORo94MiFbQKHaEU0IDJFp+Q6L1E+EcUP4oJf54k4tEovUrYbNVtPGCZ/9W+RokWf6GXb5VdD2TpQ6wSpcg0TIJidZ/l3lrYoZhGIapdDm+FOHt0aMH3n/fE+nTNA1paWm499578dhjjxUZf8UVVyA7O1tYrvkgV4rOnTvjo48+qlA5vqq2SVT5u3Xqnud7Sa2wShcizvIQZKkWog23thDZ7vAbMvhDQoyq6R3qx6LzmkfsRbIhhgUp1hVRY0flVKf4tV0OTYLlfdE4IxiUKuLSJsKhfgsdh8RzJUsucsewSAMqZJtshmEYpmJiVq9FtBfupk2b0LZtW5QG1BJ55cqVePzxx/Pvk2UZw4YNEy2UA0H3U4TYH4oQT5oU3MvU4XCIm/+JjHY8hVskIN2FbKpcoguX27UASdZfIEv1In5sum6iZguqvllEDxWpExSpI4BskY+q5XvMdoJVHlMgaqpI/SBLbb3L98V1W1Dh1pZ5RS8i3gWOzilF0ZUoEb5WeQTy1CrQQe/LYNesEiRUg0UaHnJf1BmQWinTjV5HFroMwzBMRSfsVIcbbrhBRFr9od9ffvllEY0tLU6cOAFVVVG7tq9AyQP9fuTIkYDb0P3hjCdeffVVccXgu1FEOZqh4q0c951eT9VA4lGFjhPIcT9cKhHbLNcwZLuvRJ76AvLU55HtvgiZrr7IcPVAnvoUnNpP4parPibuc6q/5G9PQivR8hlkNPQuuUvFstRyqF+WIGXCGE2IzOiAUgziLT6RH+h8ee6jMcHs3QLvl0UvwzAMU/EJW/hSruxll10m2hQTGzduFCkIX375pWhwEetQRJnC5L7b/v37Ec24tBnQccog0qlC1ZdA1XdG8Lhzke2+ARr2eO/R8yOQniIyX9Tc7b0ROchVHxYuC/55vknWKYhTnoUM6goomXxbKrBIVKRVVXTKinw74rPkuZ8okEtc3ljlc5Fg+R8k+NJXlHzhL6EOEiyfwioPjfhx3dpK5LjuR4azB9KdXZDlugxOdZK4+GIYhmGYCil8582bh8OHD2PUqFF46aWX0L17d/Tp0wdr167FgAEDSmeWAGrWrAlFUUTbZH/o9zp16gTchu4PZzxht9tFboj/LZpx63NNv4xO9XOxpF1SSOjkuh8sIHbDIVd9voBYIq9Zu3Idkm2zkGLdgWTLBpECETyKS8/XjjgLeQA7SlX0Ehp2waVNRjRBwjbZulCIXLvyf+KWYPkMydb5oiVyJKH3TK77JWS7L4NLnwYdJwGkQ9VXI1cdjyz3JdB0uo9hGIZhKpjwrVatGmbOnCm+DMld4fvvv8d//vMfJCQkoDSx2Wzo1q0bZs+eXSDFgn4n4R0Iut9/PEFzDzY+FvFEIs3ltTq175Hj/j/ouisCUWby0C2uiM6AS5sedMldluNEkwhyE/CgFHi7Uv5qouU7KFJzAHGiqURp49C+QbRBndis8hDEKfeKGwleui/SOLVP4dQ+9/7mf5Hhed9RjnaO+9aIXFQxDMMwTFQJXyr2olzbCRMmYMiQIUL87t27V9xf2oVgVKj2ySef4KuvvsLmzZtx5513CteGG2+8UTx+3XXXFSh+u++++zBjxgy89dZb2LJlC5577jmsWLEC99xzDyoKnoI182LHrf+BXPWlEh3TrS8tYV0kecyGtpSTJRK3E5Fo+RFW+TJYpEHCoSBe+TeSrYtgkTvlC2WbfGkxcnwlyOhqerSmbxEpGroe6eK56IYi83nqBwajKJVmDVT9nzKaFcMwDMMUj7DVS9WqVfMLYXwRnqZNm+ZXhZMoLi3Inuz48eN45plnRIEa2ZKRsPUVsO3bt084Pfjo27evEOhPPfUUnnjiCbRo0UI4OrRv3x4VBZt8CZzaV2FsocOlTYCm3wNZSi3mUQu7RxQH42Iqej9ZpO6wyN1DjiP7LfL09UQgzcwrAXb5Wlikc5GtXmJyvrpohEFewQkW8rGNqCFKlKfSmLmgVeDUfoZFrjirKQzDMEzFI2wf37//Jp/Y4AwcOBAViVjw8c123QS3Pj8MKy8ZccpjsCu3FOt4Hs/cN0pkHUaRW5syJuQYXXd6RXa8oesANe3Icd/uHe9/8UWRYB02+XooUgtIUlWvR22CiGZmuHqZFHY+JNjlexFnMeelG+s41C+Qp75s6rVWpB5IstIFCMMwDMNUEB/fiiZsKwIUgcx23wpVD92++SyK8KYtLlb5YtEso7iQEwP50QaCUglc2lQ4tS/F8rlnfE3YlKthk6+BLNUIMqcBSLbOFM0YXNovIgdZQpLwDrYp1wrRW2Qekh12eRwc2idhiHgdDu0jSO7GsCmjIEk2VGQkkT9t5tyQd3BiGcyIYRiGYcqhc1tOTo5ILaDGEv507EjNCyoOsRDxJXTdLSKenqVpIxTY5dsQZym+t2+e+004tP+GuRVFbXXEK+/Bppwf5Dn8H9z6jAAd2GQhgBOtE6BITYs976LHzEKW63Jo2B62OwQJ+DjlCdgUyjGumGj6YdEC2oz4jVdehk0ZVybzYhiGYZgyifhSji0VkwXz7C3NHF8mOJRzSrmubrcZ4avCIg8p0fHsynjKFoZTREvNkuwVR0VFL+FQ34Fb/9P7W2GhpQkbrWzXjUi2zgqrOUMoJCkJSdYfkOt+XnS5CweKKueqj0CHE3blKlREZKmuyIUO7ZVMFzSJsMoXlPHsGIZhGKaUXR3uv/9+nDlzBkuXLkV8fLwoLiOXBSocmzJlSri7YyKIRToHEtIMHA4UyGgFReoaMPrpVCci1/0y8tyviyYVuh5Y7EiSjHjL45BE0wlzJCjvBhW9up4Dh0Yd2EItQFAXuv1eERY5JCkFCda3oEjditE9DqJjnaaTvVt4qNpm5LnfQa6but59AE3fh2gk3vIS5KDvK0/zDLt8O3LcDyHTdb5obJGnfsjevgzDMEzUEXbEd86cOZg8ebJoXEEOCo0aNcLw4cNFWJna/Z5/fmBhw5Q+JEYTLR8hy30FtYkIEKFTICEZCdYPChSLUbaLU/sMeeo73u28bwvtY0ioiwTLO7DIPYMcNS+MCQYf69bneY9thAynOllYm5WGQ0auurIYW7rh0n42XSyo6cdFSocqbOFIONJrocGhvi260SVYXhOR6GhBlqoj0forHOq/4dR+9HudJCjoJTr1ObS3vM/F855T1VVwqO+K905pvFYMwzAMUyYRX/LNrVWrVn4zC0p9IDp06IBVq1YVaxJM5FDkNkiyThLL0wVfXk+L3yTr5CI5spSrm6e+4idozrYZJlGT7b4Gbm1FwONRy2GzUdKzLXaLouknTO6HUh4877lIQ0v1EqoX52ORX4hnhK6nI9t1GVTddz5V77n2WLFRfjO1go62NsCyVBXxlmeRYl3m9Vf+FkmWedClM35tq/0vtChy783Z1haX06wZhmEYpoQR31atWmHr1q1o3LgxOnXqhI8//lj8/NFHH6Fu3brh7o4pBUjYJlpp6fw4VH2LqLeXpTYBHRGoeIlya4PjybXNdT+JJOuMIrZiNvky5KpGoo9mUB+K1DnEiKomPXipyK0aitvlTtXXQUceZKkBFKlZwTlICUi0fIEs9zV0iReWXVuwlJDCONRPoOFgiHxZDaq+Ci5tEmzKFaLgjwoWneqP0PQDor2zVR4umnpQJLasoeNbpB7iZ6c6DZq+KcRoej0l5KlvIUnuW2ZzZBiGYZiICV/qhnb48GHxM3VtO++88/Ddd9+JlsJffkk5mky0QA0qjJpUONUfTOxJE64Hqr4alkK5wRQlzVP/LQrPgos5HXHK3SIVIxhWeRByVbIGcxrOxSqPNjFnv6PrOWKO1LIZyMq/X5E6iiI9skLLv0/ugGTrH8hyjYOOAyaPIEGRWpmYBxUDTjDhHiHBoX4FizwY2a7roWHr2TQCndIIViNPpBG8G9QWrizwPJfC7huBhPxqqPoOb4tphmEYhokh4XvNNRQN89CtWzfRrpjaATds2BA1a9aM9PyYUkbV15qMbMpirKVQm1+KACZavka2+2roOF1oXx6xZpfvhlW+3LDAzCpfAZf2XYj5ULS3elg5o7qejWz3VVD1jUX2S22Tc9w3Il55Azbl4gLH0UVU1jwUnTVCwyHhBGFi1tCwBdmua6Bht2+2BR6nC4Qc991ItEwIkX9dumj6LtNRcU3fy8KXYRiGKXfCT2YsREJCArp27cqiN0YhiRXO6EAockskWf+EXXlQpDR43lbxIs840fID4iwPGnZeI+KVx6FIJOJobOHxJKJJZH8uGk+YhZbZA4leD5682lz1UWj6WaFL0clwWjKTowHZfhkTnmW2hh0ho+iEpyCxvAineUfFbvTBMAzDVNCI7/jx40M+/vbbb5dkPkwZY5HaQ9WXmFh+16BI7YI+Svmmccqd4lZcJCkOiZYv4dS+g0P9UliXeYiHTb5UuCbIEtlqmY/2OjVqoWsk7nWR8kECXcwjrOvBBCH4zSCDxHEygEyDkZJXKLpMpBEshSqiqY1Q1lB6irnUDTssUqcymhXDMAzDRFD4rl69Ov/nhQsXinQH8vMlzET1mOjCplwJh/axwSiSgo280djShVoA25UbYZNvEI4SJP7IDaJwlJcKvcgnllIkZDQO+N5zC+cEMxZp1Cb5L8TBI2BlIfCtXuEZCnLKGBIyd7ngc7PDJo8T1nGhxaLujXCbc3Yg/9/yEL42+Wo4tW8MRinCJo5eJ4ZhGIaJOeE7d+7ZzmDJycmYMGECmjaNXAtZpmyRpYawybfCqf0vyAhP2kGc5fkyvbChY0moU+R+EqgO9b/CncGHjJawK7fBKl9UaI5mRK8HHTln9ydVhUU6H259ksFWqhB/4UBRa5f2O3QcCyJ+FchSa+j68QJzCoVUTmkElOJiVx6GQ30j2AjIaAi78lAZz4xhGIZhSinHl4l94pRHYJfv8V4Hyd7/PddEElKQYPkYVrl/eU9TdAPLcd8hitL8IceJXPUh5KkvimYcPiTUM7lnCTqyke26GXnuf3kjqJSrbIymHwrrOchSTSRZfxT2ch5859rTFc0i9UOS5VtYpEEGHfh8JECROqC8oNSWeOV10eikIBZYpTFItP4sLiQYhmEYJhqQdH+lECYU8V27dm2FjvhmZGSgSpUqSE9PF93pKjLURMKl/SaKuyRYRGqDVT4vrGKy0sKtLUO2+0rDcfHKe/ltkemtneU6FxrIfcDs21zx5tVS+k6OCRuzDqJhSLjQ3KjphUv7AzrSIaMmrPKFUGSPLZqqbUSWe4zhXG3ydYi3PI3yhnyMKd+YUlBEYaPcR4h8hmEYhokmvRZ2qsOUKVPyf9Y0DbNnz8aGDWcjcBdccEFx5stEASRU7MqtiEYc6hcFWuIGRhb5sz7hS2kPcZYHkOOmaLZZfPs3k2ZA4nWd8OeVJMoJNit4F8GhfiO6t5GrhiK1gVUZBNmvoYYit4NduV+0/Q2eRtAMccr9iAYkifKduUkFwzAMU8EivrIcPDuChIaqmutgFStUpohvtELRxAxXaxPuAR6SrcsKRBtJNOepL3nTOCL//kyxbhKOFEZQF7Zc9yNwidxhfxHvaQJBEfZEy6eQpKT8bZzqRNGswlPo58MKq3QR4i1PcNEYwzAMw6AUI74U5WWYssURlmDVRXe2s8KXXCIscn841e/g0maJ1AL/Dm4lQUJtU6KXyFP/BZc+2fub//PxfKYoApzjfgCJ1k8KNMawypd60wgOibbKitSX82YZhmEYphhwcRsTA1C+bYLJsTJkVC9yL3UNi7c8ixTbAuGsUIxrvoDHsinXmhqp6+lwal8Z5BprcOuzoWpbiqYRyH1hUy4VXetY9DIMwzBMGQnfEydO4JZbbsGNN96IU6dO4fXXX0fHjh1xww03iDAzw0QaSqGhBhbGLgeUZzrcxPI/7cdshk8wCzdF2K3ZTdqZObWpVKJnYqQCp/aLybkxDMMwDFOqwveuu+4STg6HDx/GxRdfjG+//VYI4WXLluHhhx8Od3cMYwqbcr03ShvKS1gXfr5GWKQeYaROUKc1/4+KR3zLaIIk6w+QpCqm9qLrh03ak+nQccTk3BiGYRiGCYew13vnzJmDv/76C82bN0e1atUwc+ZMDBkyBO3atRNRX4YpDRSpCRIs/0OO+zZv5NRfuHoEZbzyFixyFxP76iEcETTsNmgJHIdky1yo+EfYjmn6achSqrAds0gDTHdsE0gJJqPMJOw9nRAZhmEYhiln4ZudnY1atWqJirmEhAQ0auRpldqyZUuRBsEwpQU10Ui2zoJT/VakA+g4DQnJsMoXiFxbxc8OzAibcgvy1Ke8QjOwII1XXoEsV4OMkbDKI0s2d2koHHjTxEgVVnlYiY7FMAzDMEyEhG/9+vWxd+9eNGjQANOnTxf/E0ePHhWCmGFKE1mqjzjLo4jDo8Xa3qlOEt64GvYF2ruIAFPubrzlKVFIFimoMQVFmlV9VYg0CxkSasEiDYnYcRmGYRiGKYHwffXVV4VPGnHOOefk379z505R8MYw0YpD/Rh56utB8oQlITrjlGdFxJWcFCJNguVtZLkuhY4TAcQvHc+ORMvHkKRIOE4wDMMwDBPRlsWVAW5gUTFQtc3Icns6ugVHhl2+VUSUSwtNP4Y89ztw6b9R/Dn/uBZpBOIs48NK12AYhmEYppQbWBhZlrE4ZKIRp/atiZbHGhzaBNj1+yFJ9lKZhyzVQoL1Vej641B18uvVIUtNRdEcwzAMwzClS9jCt2rVqsJXtTAUOK6ILYuZioFLm2PSwiwTqr7Oa3lWepDXsEXqWarHYBiGYRimhMK3adOmOHbsGB577DH069cv3M2ZGEDVd4n2vm5tAXQ4oUgtYFOu8lp4RT73tezaHptDR16pzoRhGIZhmBgRvps3b8Z7772Hl19+GatXr8a//vUvNGnSpHRmx5Q5eeqHcKhvFEgLcOsH4XbPFq4EiZZPTHRGiz4kqYFoG2zGS1eW0spkTgzDMAzDRHnnNqvVivHjx2P79u3C2ozaFT/44IM4c+ZM6cyQKTOc6kSv6EWhtADPz2TFle2+Q6S1xBp2+SoToleGInWHIjUuo1kxDMMwDBPVwtdH9erV8e6774qo7549e0QnN/qdiU103Y089W2DUSpU/R+o+nLEGtRtTUZDg7bBOuKU+8twVgzDMAzDRLWdWZcuXYoUt9EuduzYgZycnApX3FZZ7Mxc2jzkuG8yMVKBVboACda3EGto+kFku66Bhr35zSo80M+yaHlsU8aU8ywZhmEYhokaO7OxY8eGPRkm+tH0/SHb955FhYY9iNWub0nWGXBpf8KpTYSmH4CEBFiV82CTr4As1SnvKTIMwzAMU4qELXyfffbZ0pkJU65IIN9as8H/eMQq5M9rUy4QN4ZhGIZhKhfF7o26YsUK4fBAtG3bFt26dYvkvJgyxiL3A1QzEV8JVnlQGc2q4qLrDm/ntqSAvtgMwzAMw0SB8D1w4ADGjRuHRYsWiWYWBDk69O3bFz/88AMaNGhQCtNkyiINwCINhVufG6LRAwk0G6zypWU8u4qBrmtwaVPh1L6Aqq8V90moBpt8FWzKddy9jWGYSoV68gjy/pkO5+r50HOzIcUlwNa5P+J6nwcltX55T4+poITt6nDLLbfA5XKJaO+pU6fEjX7WNE08xsQu8ZaXIKFWEOcDeqtISLC8BVnyXPAw4blm5Lj/D7nq/VD19Wfvx2k4tA+R5RoJVd8eZFsVbm0FXNosuLXlYl8MwzCxjHPzcqS/ez8cS6ZDz8kEdA16bhYcS/9E+r/Hw7l+SXlPkamghO3qEB8fj8WLFwt3B39WrlyJ/v37C2eHikRlcXXwoenHked+BS59GrWuyL9fkTogTnkYFvmccp1frJLnfgcO7f0QqSQKJKQi2TpX5CET9NF0al/BoX4MHUfzR9LFiV25BTb5JkhSsR0JGYZhygX3kX3IeP9hQAvhAiXLSLnzNVjqNy3LqTExTKm5OqSlpYmIb2HIxqxevXrhz5SJKmi5PcH6DjT9KdGwAnBBRhMocpvynlrMouu5cGhfGORPq9BxBC5tBmzKhUL05qpPwaV9X3R/OIY89RWo2hbEW97gHGGGYWKKvEVTzY1bOAVJV7C3OhNZwg4XvfHGG7j33ntFcZsP+vm+++7Dm2++GeHpMeWFLNWAVR4OqzyKRW8JcevzAWSZGCnDpU3ybjMjoOj1x6X/Cpc2JUKzZBiGKX10VYVzzYLQ0V5C00S6g+6iQmCGiRxhR3xvuOEGkc7Qq1cvWCyezd1ut/j5pptuEjcflP/LMJUdXT9tcqQGDcfFTw71y0JNNgIhw6l9KSLEDMMwsYDuyAHUoqvGAdFU6DlZkKp40r8YplyEL7clZkJBS/SavgU60iGhOmSpRaVfipcks7nhkjhnlBphri20JtwhdD0jjGMwDMOUH5Itjv4o0peFufH22PWNZyqI8L3++utLZyZMzAtelzZRFGJ5WgJ7kNEcduUOWOWLKq0AtkgDvE0/cg1G6rDJY6AjL6z968iFBBa+DBNJ3Ad2IG/xH3BuWga4HJCSqyGuxzDYew6HnFytvKcXs0gWK6wtOsO1fa1wcgg+UIalSVthccYw5SJ8qVrODJXB+YApiKcQ6zm4tG+8Xr9n0bATuepD0PTtiLM8isqIJCXBJl8Np/Z5iNQFGRKqwiqPBmAFQH/szTik2MV2DMNEjtwFk5E7/RvhLEC5poSecQq5c35G3qJpSL7paVgaNC/vacYscf1Gw7VtdehBuibGMUy5FbdRs4pq1aoFvfkeLy0oX/jqq68WwpqOdfPNNyMrK3TB0KBBg0SU0f92xx13lNocKytufbpX9BKFl688vzu0j+HS5qGyEqc8BIvUz3thUDjyTb7JiUi0fAFJiockWWCTLwvip1xwO5t8cb79GcMwJce54R+P6CW8ojcf8pp15CLzi5egZZsLBjFFsbbohPihV3h+KbwS6P09buBFsLXpXg6zYyo6YaU6/Pzzz6hevTrKAxK9hw8fxsyZM4Wd2o033ojbbrsNEyZMCLndrbfeihdeeCH/94QEXjaJNA71MxOFWAqc6heVtt2xJNmQYPkUTm0inOqX0LDL+0i8ELl25WbIUlr+eLtyI5zaT2ToE+S80vm2wqbcXGbPgWEqA7lzfw6dg0riNy8bjpVzED9gbFlPr8IQP/QyKLXTkDt/EtQDO/LvV+o2QdyAC2HvSIEChiln4duvXz/UqkWdvcoW6gw3Y8YMLF++HN27e64A33vvPYwaNUpYqIXyDyahW6dOnTKcbeVC19Oh6gZLVgIVbn0hdN1RaSOUkmSFXblGpD3oOEGxJUioGfB8yFJDJFq+RLabXFKyC0XSKSISh0TLp1AkNndnmEihHjsI9fAe44G6DscKFr4lxda+t7ipp49Dz06HlJAMpXrt8p4WU8GJibZPS5YsEekNPtFLDBs2DLIsY+nSpSG3/e6771CzZk20b98ejz/+uGFnOYfDIfKZ/W9McHQhysyP9kQwKzeUckONQmSpfsiLAIvcHcnWvxGnPA5Zai06u8lohTjlESRb58Mi9y7TeTNMRUfLPF0qY5nQKNVSRc40i14mKl0dyoMjR44UiTSTbzClXdBjwbjqqqvQqFEjERFet24dHn30UWzduhW//vpr0G1effVVPP/88xGdf0WG7Lc8xVhmfBnjACSVwawqDrJUTbQnphvDMKWLFGfeOottthimgkd8fcVhkeSxxx4rUnxW+LZly5Zi759ygEeMGIEOHTqIHOGvv/4av/32G3bu3Bl0G4oKU59n323//v3FPn5lQJLiYJXON1mIdSkkyWgcwzBM+aDUbQwppYbxQEnmHFSGqegRX7Ksoq5tdnvo/MxQ0dTCPPjgg2KfoWjatKnI0T127FiB+6lbHDk9hJO/S93miB07dqBZs2YBx9DzM3qOTEHsyq1wuan3Ol0YBSoIofstsCmhX+uyQNfdcOuz4FR/g4ajkIWF2EhY5QuEowLDMJUXSVYQd85o5P7xleFYe69zy2RODMOUk/AtjcYVqamp4mZEnz59cObMGaxcuRLdunUT982ZMweapuWLWTOsWbNG/F+3bt0SzJopjCK3QYLlQ+S476ZLkkIuBLSoYEOi5ZNyL8TS9P3Idl0PDXvyXSg0SHCr85Gnvi5cFyxy13KdI8Mw5Utc31Fw79sK14Z/ij4o0d8NHYmX3gOlBn+PMEwsIukUyo0BRo4ciaNHj+Kjjz7KtzOjYjefndnBgwcxdOhQkc7Qs2dPkc5Aj5HzQ40aNUSO7wMPPIAGDRrg77//Nn1cKm6rUqWKSHvg5hyh0fSDcKrfw6n9Bh0ZkFANNvki2JRxkKXyddagtr6ZrlHQcVQ4TBSFvtDikGSdUu4CnWGY8kXXVDiW/oW8RVOhnaK/GR4s5D876BJYm7Qt1/kxDFN8vRYTxW0+d4Z77rlHiFtyc7jkkkvwn//8J/9xEsNUuOZzbbDZbJg1axbeffddZGdnIy0tTWzz1FNPleOzqNiQS0Gc5SHE4SFEG07tB+g4HCQVA94otQMO94dIsL5RxrNjGCbqUh76jIS993nQThyC7nSINsVyCrcqZphYJ2YivuUFR3wrBhnOAdBxwMRIK1KsKyBJyWUwK4ZhGIZhylKvxYSPL8OUBJ06LZkSvYQLmk6RYYZhGIZhKhoxk+rAMMWHXCWUILm9gYaTLzHDMEz0oOVmQztzHJJihVyjDiSl9K0haUFYPbofem4W5MQqkFPrRdzWlGHKGha+TIWH/lArUm+o+j+G4ldCbchoWGZzYxiGCQUJz9x5v8C5fgmgef5+SUlVEdf7PMT1HwPJai8VwetYMQt58ydDO3m2SZRSuyHiBl0Me6dzIn5MhikrWPgylQK7cj1y3IsMRkmwKddxkw2GYaIC157NyPziRUB1A9pZm0g96wxyZ0+Ec8tKpNzyLCQbdcWMnOjNnvw/OJfNLPKYemw/sie+C/X4QSQMuyJix2SYsoRzfJlKgUUaCqt0cYgRMhSpC+zyTWU4K4ZhmMDozjxkff0a4HYVEL1nB+hQD+5E9jTjZhvh4Fy3KKDo9R2TyJvzE1w71kX0uAxTVrDwZSpNukO85V+wKw8AKOzYYINVvhKJlm8gSdy1j2GY8sexZgH0vOx8sRkQXYNz1VxouVkRO27ewt/pD2boQbKMvMV/ROyYDFOWcKoDU2mQJBlxyr2wy7fCrf8NTT8OCSmwygMhSVXKe3oMwzD5ODcsCdEG3g/VDde2NRHJu9Wy0kUU2XigBtfWlaLRB3keM0wswcKXqXRIUhys0ojyngbDMExQRLTXSPQWGBuBYzpywxisAy4nYI+PyLEZpqxg4cswTBFOn87DhG/XY/as3cjNcaFps2q47oZO6NmL7YwYpiyQk6tDlXaLdAbjsZHpKCcnVfGkOZjpa0UFdREsqmOYsoKFL8MwBZgyaStuufF3OBzu/O+/pf8cxDdfrcPQYU3w9YSxSE7mXGiGKU3sXQfBtXm54TgpLhHWFp0jc1BZpn7NgG7seW7r0IcvgpmYhIvbGIbJZ+6cPbju6kkFRC/hdnuiTvPm7sG4y36BpnGnc4YpTaytu0OuWdcjRkMQ1/8CSFZbRI7p3LA03yvYeIIc7WViExa+DFMJ0xgogrts6UGkp+cVeOyZJ+eKvMJgK52qqmP+3/uEQGYYpvSgzmzJNz4NOaWGt8jN/0HPV7et2xDEDbwoYsdUTxwEzBarZadH7LgMU5ZwqgPDVBL27j2D115aiJ9+3ASn0xPBtdsVjLu6PR574hycPJmDtWuOGu5HUSR8/ulqkfbAMEzpoVSrhZT/exPOFXOQ98+f0E4fFcLU0rQ94vqOgrVll4imG0gKSQITqzkkvMVYhok9+J3LMJWAbVtPYviQb5CR7hBRWx8Oh4pvvl6HP6buwEOP9jG1L9p+08bjpThbhmF8yHGJiDtnjLhRV7XSzKu1NGkHaBONB+r/3959gDlVZv8D/9706UOTDtJRQOkIKkVAwAZiQ/2pWLCxrm1XkXVVXPu66/4ta1fsbRXsoKIgIl1BuvTepEyftHv/z3kzM0xJuZmaTL6f54ljkpubO3cyw8nJec/RYW/frcaOg6gmsdSBqJ6Tfywvn/BJhaC3mN9nqGzv008tNr1PyRQTUe2q6cVktuNPgKVJy5JSipCcSXCcVPW+wfFCz8+Bb9cm+PZsgSGT9CiuMeNLVM/N/3EHNqw/FHYbCYh37coxtT8pdRh2BssciOpjYJ160S3Ifvk+WdFasZVaUeAt22iO+t/ZxX9gNwq+/zAwTKRobLTmSoaz/0i4ho5X2XiKP8z4EtVzX36+ETZb9f2qS5B8zaRe1bY/IoodtlYdkX7DQ7C2bF/hPkuj5ki9aiocJ/ZHfefb+Tuy/ntXmaBXGIX5KJz/ObKf/5vKBFP8YcaXqJ7LzfVU6/7umzYYnTo1rNZ9ElHssLVoj4ybH4Nv7zb4dmxQAy2sTduoUohE6N0r5Qw5bz4GeL3BB4gYOvQ/9iBv5ktIu+zOujhEqgIGvkT1XIuWaarOt7IsFk317W3SJBn33j8YV19bTc3yiahGSMDqXjwbnnXLAJ8XlobHqY/nnScPjqpEwdb8eHVJNJLlNfKyw29k6PCuWQQ96xAsGdJyjuIFA1+iem7CZd3x+CMLKvXYq64+GSd2a4Lj22VixMh2sNu5qI0olhX8OBMFs94ODL4o+ojevycP+TNeROG8mUi79gFYGzSp68OMaZ41S8yNbjYMeNYvg2vAqNo6NKoGrPElquc6dGiA8y/oqjK30erVuxlumtwXY87qyKCXKMa5V/wYCHpFqbrU4gBOP3oQOa9Ni8nOBP4jB+DbuRH+P/ZW6ROq6iB1vBGDXqFZYLgLVbcHOffu336G/+gftXGIVAXM+BIlgP++eBYOHyrAvLnbo3pc06ZctUwUDyRYLPjuw/Ab6Tr0Q/vgWb0Izp6nIxZ41i5BwdxP4N+1qeQ2y3GtkTR4LBy9htRJTbEqXSiVMQ/J0OFeNAsFs946dpumqXHTyedcrQaQUOxhxpcoAaSkODDj80vw5jvj0LWruXq0jEwnho+suLKbiGKPf+dG6If3Rd5Qs8C9bA5iQcG8Gch9+wn4d28pc7t+YBfy/vcs8r94rU6yv85eQyIHvUX0rHIZXsOAd8NyZD83Bf7D4SdhSubdf/Qg9OzDMEw+H1UdM75ECUJamo0b3xVnn9sJfXu+jB3bs4IOtCh26+0D4HLxTwRRPKgQgIUiHQmOHEBd825di4LZ7wSuVOicEPi75F74NWxtu8J50qm1emy29t1gbdUR/j1bTGR9g/wN1XUYhbnI+/i/SJ80reLd2UdQuOBzuJd8B8Odr26zZDaBc+BouE4ZDc1e/3sk1yVmfIkSjNTqzvxiApo3T61Q9yvDKcQVV52EO/5iboQxEcUAh8v0pprT/LY1pXDBl5EnxMl2P32O2iblFWlXTIGlccviG0rdaTJs0nX4tq6B/8CuMjf7/9iDrGf+gsKfvigJetXmRw+q+uzsl++H4S6onm+EgmLgS1RUH2cYPiSKdu0ysWDJtXjwoaFo2zZD/V2XjPCQoW3xwccX4tnnx1RqMRwR1Q378ScAZjKFmgX2EwegLsnH+t51S4P3yC1Han/1nKOobZa0TGRMfgzJ598Ia7O2gM2uzq+9U09YW3eWExl5J5oG76bfSq4auh850x+GUZAToj+woco+pD8w1Rx+jkkJHez6jO/h9r8Jv/Gz/ImFhqZwWC+Hw3IZLFr9HtLQoIELf759gLpIn14JfhOhOT1RfaQ5k+DsN0KVB4QNKDUNrn4jUKekq4SJoLeYvzBfBaK1TUoO5FyVP1/Zrz9UUo4RYQ9lOmh4f/8VeoS6Xzkvnt8WQB9zJSzpDSp76BQGM76UuCug/fci3zepJOhVt2M/3P7/INc7Gn5jMxKFZHcZ9BLFt+QzL4W1RbvgH8fLbZqGlItuMT1wQTKt8lG9nptVvQdqd5jLmBbxLv8escTaqFmg60Mkhg5rw6YlVz2rfjb5OAOetYureJQUCjO+lJA8+ivw6u8VXQsEvcfoMHAEed4rkGb/AZrGhQZEFPs0hwvpkx5Ewfcfwb3km0A/2iK2tl2QNPxi2Dv0MNVirHD+p/Bt33Ds8e27wzV4HBydqz65Ub3JVu3Cyv/tDc69/HsknXkpNEts9BJ39h2u2phFoiWnwd61T8l1Iz/XXLcIiwVGQV5VD5NCYOBLCccwvHD7X4ywlR8G9sGrfwWH9fxaOjIioqqRkcTJo/9PBbkyWAFeDywNjgtkKU0omPOhupTPGvu2rkXultVIPusquE47t+rHmZwOI/eIqW1lfLBv2zrY23dHLLC1aAf7if2L6pRDlzwkjbgEmtQGF9FSMsz1B9b90FLSq/OQqRSWOlDC8RmLYOCwiS0t8Ogf18IRERFVL83ugL1tV9g7nmQ66PWsXx4IekX5Gtyi6/lfvaFakVWFb//OqOtXpQVYLEm9+FbYO/cKXCldvlD0/0kjJsBZbpSx8+TTTGZ8rXB0q9sFiPUZM76UcAzjoMktdRhGhIUIRET1hGodJpnecAvPLBYU/vwl7O1OrNRzFHz/PxR89775tmClFu/FWmY99cp7VCZcykr8+3aogNXWoTtcA0bB2rh5hcfYOvSAtWlr+A/uDh0AaxocfYbBEiLjK50hvL+vCDzn/p3q52HveLIKsm3N2lT3t1kvMfClhKNpZj9CkgVftb+SmIiotukFefBtWW1iQx3etUth+H3QrNGFEIWLvwkEvSKKrg5wOGFv3w2xRmqV5bjMHptmsSD1qqnIeem+wMCR0mUSUvdsGKqWOuWca4I+Xmq2c958DL5ta8u8QXEfOQD34tlwnXGRKnHhQuXwGPhSwrFpg2T9s3xoF3Fbu+WcWjkmIqLKkq4LalCCpqmMoiU5Lep9lF4IF3ljHYbHDS3JfAhh+P0omPNB1Mcl35Oz38iYy/hWljWzCdJv+acKVAsXzYaRHSi7k17BroFj4Og1JOgbCulElPPOk/BtX1/xjUNR9rjw+49Uplj2Q6Ex8KWEo2nJcFj+T3V2kHKG4ORjONmOC9uIKDb5D+1DwbfvwbN64bGPzqU+9OTTkDTyUlgzG5velyU5tSTrGJHVHvX0N++mlTCibYumabC16azatNUnlqRUJA29AK4h4wFPofqZSU12OL6dv8O3+dgwjFCkRlv6OZdeVEdlcXEbJSSX9XZYNRnJKx8Jlf9YSFrm2JFiezmKsggiotrj27cD2c/dVTboFbofnpXz1X3+Q3tN708yqvYT+kXuM2uxwNHztKhbi+lHDkTVu1c6ICSdcTHSrrlfDZKoj6QkQc57pKBXeJZ9b6oHsJGfowZlUGgMfCkhSW/eFNtrcFmnQkPRPHbFBrt2HlLtn8Fm4apaIoo9MvI3951/wnAXBl8kpeswCnKR+96/1UfkZrkGjzWR8dXgGnR21MccCO7MHYu1dSdkTnkRScMvMhUU1jRZUKZnH4aec0Sd+7rK7pvqCKFpkafDJTiWOlDC0jQ7nNZr4bBcDQO7YcADC46DpkVfH0dEVFtkEZoeKZur6/Dv2Qr/ro2wte5sar/2Nl2QcsFk5H38XKDsoXSgpbKNGlIn3A5b8+OjPmbpPGCulEKD86RTo144Z5b/8H54N/wCw+uGJaMxHCf0Ux0agtHzc1C44EtVjyuZVHV06Y3gGjgarlNG12rdceAYJWMe4fzJ+a2nGfLqwsCXEp6mWaChdV0fBhGRKZ51y1RdaMTJZxYrPOuWmw58hbP3ULXQqnDhV/CsXAD4PKqrgrPnELVoShbPVYaMSZZSCu/6ZeEzlzY7HL2HorpJtjbvk+dV0KsCSEsgsM9zuJA05Hy4hpyvui6UbJ91CNkv3qu+ll5IZmQfQsE378Kz8iekTZqm6nVrg/QMDhy7iW07nVzjxxPPGPgSERHVIlV+4PUANlulxvAangJzG0qCVRZPVWIyWeoFk2GMvxmQtmURFkr5jxxQ/WwNn1f1r7Udf2KZILJYytjrkb1nK/TsQxWDX9WCSzLKt1V7MCldL7Kfnxp4XsUA9KLMqadQLRCUwDjlvOuOdVB46/HA9sHarhmG6qGb99GzSLtyCmqDs9cQ5M96O/C6CZX1Lerpa23YtFaOKV4x8CUiopglGbfCJd/A89vPquWWJS0Tzj7D4Og9DJakFMQT+ZhdMqluWajkLlDBnr1LH7gGnaUmrJklH9Gb6r6g67BkNKz08ap+sGGCXv+Rg8j/9GV4fy+biZQRycmjr4Cjx8Cyt6dlIv3mx5A/6y2VMZWgupitVSckjbrM1FjicG8cJICVfsHuZXNg5BxRH/tb0hpUyNyW5140S3XDkGl3vh0b4Jdxz2EPQlfZa6m9NTsZryo0V7IqM8l9+4mi5y/387dYoKVmIuX8G2v8WOKdZkRT+Z6AsrOzkZGRgaysLKSnc4U/EVFt8axdohZoqexgmaBFg5acirSr/w5by/aIB94ta5DzxiOA31uxdlbX1fCB5BGXmNqXBFtZ//pT5A01CzLvfjHq8cCmjuHIQWT/dwqMgpyQpQvJ598IV78RIetnfTs3quDX2qi5qRIKySy7F34N99I5MNz5gTcOnXupxXby8b5v1ybkvPZgYNFfNAMyirtVdB+kMs55n78K9+JvIpeSaBYknXmpKpWoLTIuumD2Oyo4LyEt7HoMQvKYK2BJr/wbnUSJ15jxJSKimCNBUe67T4YIqgwYBXnIeW0aMm77j8roxTI9+why3nwkUC9bPtdUaviAtUlLOE8+LeL+JMPoOOk0eFYtCJ35ldG3/YbXSNAr8j97OWzQq7b59CU4uvYJ+vORIRuOLr1NP5932zrkTH84kOktDmoNA96NK1Ttq3PQWXAvnxvoixtt0Fs8ka5ocp10xDCVUbdoJYveaouMirbf+LAaWKJGH1utKltuSc2o1eOIZ2xnRkREMadg3ozI08MKC9TH2rHOvfRbwOsNH0xpGgrnfmK6/VjK+JtgKy6PkPG1JfsJ/L8sJAs1+raqJPOqFlpFaq9lGHAv/a5aanRVttzrrhjUFh2D++evAMkCVyboLdlXIMOrJacX1RxH2t6AllI3nwRbj2sFR7cBcHTty6C3vga+Dz/8MAYNGoTk5GRkZmaaeoz8AbnvvvvQvHlzJCUlYcSIEdi4cWONHysREVWefAzuXbfURGClV0tgVdPcv8yNHJCpBVM7oEsWz2R7q7SrpiL1irth69AdWlKqutg79USq3H7ZX2psepdvyxpzG0pGdlPkaWORFC78OlATXZOVmZqlpNzCefKpkcschKHD0ePUmjsmqhFxU+rg8Xhw0UUXYeDAgXj11VdNPeaJJ57A008/jTfeeAPt2rXD3//+d4waNQpr166FyxXduEUiIqodMizAbJBjFA0VCNZFoC4YRQGsWoiXmqm6HOh52VFlNyWbZ4Ys7JI+tHKpTUapRWkRt/V5q/RcEjgX/vAxapyhwzlgtPpfa6tOsLbpDP+uTaHffGkW2LsNgLVBk5o/NkrMwHfatGnq6/Tp003/8fnPf/6De++9F2PHjlW3vfnmm2jatClmzpyJCRMm1OjxEhFR5UQ1otZqj4mgV4Jv95JvUfjTZ2UmZ1ll8V0Uwxi0OOhUIcG8WdJpoLJ8e7YGShxMTnyrUra3ZXs4uvUPXNU0pF3+V2S/dB/0w/uCvgmT7VPH31Szx0U1ou7/WtSQrVu3Yt++faq8oZis9hswYAAWLlwY8nFut1utDCx9ISKi2mNp2BSWhtIiKkKdpfQt7doHdU0SLXmf/Fct+Co/Llamp0EWS0X6XqCp71uGR8Qy+V4Nvx8wOUpYl+x3JUsUCn74X9VqdkMprt8tesNkO74r0q6+t8y0OFmQlzH5cSSdeZma1lZye6PmSD7nGqRPelC1GKuvDBl7LT/neihuMr7RkqBXSIa3NLlefF8wjz76aEl2mYiIap9k3Fynno38zyOUtUkbsIFjUNc8v/wAj9TxBlMS9EUK/gy4Tj8v0Ds3RkkAK3173UvMLyjUZbjFjg2qP240/NmH4V2zGNXNcdKpqlRDWp5JmYKjzzA12S7YeZfAVk11GzxOtU+TKZ9wuGL6Z1TVYNe7ZpGqqfZtX69eu5bMJnCeMhrOfiPirm92TAa+U6ZMweOPPx52m3Xr1qFr1+h+YarinnvuwR133FFyXTK+rVtznC0RUW1yDjgT3s2r4F27JOQ2rmEXwt6+G+o6GCyY/3lRRrcSmU0JogwDjr7D4ex/JmJZ4Y8zowp6i8mo4LQrppgukZBetbnv/DPq53H0HALPyh+LRtaV7fssPxt7j0FIufjPIafl+Y/+Ac9vC2DkHoXmSoGj+ymq3loCXblueD3wrJgP94ofA9ukpMN50qmqtZwsNix+PUjWv3jYSrz01TX8fuR+8B94Vy8MdAYpesOmHz2Igtlvw714NtKum1YvaprrNPC98847MXHixLDbtG9fuebkzZoFJqns379fdXUoJtd79uwZ8nFOp1NdiIio7khwknrpnSic/ykKF3wJIy+r5D5L4+ZIGnoBnL2Hoq7pR/+AfmBnpR9vbd4OrlPPgaPn6TGdSZRFaoXzZlbqsdKpIvu5u5F2wz9gi1DK4dv5uxpCYaqrQimO3kORMv5mOPuegYJ5n8C3cWXJfZaGx6lz7BwwKmg9uIx1zpvxggp6VZBs0VSrsoLv3oetw0lIveRWtUAx5/V/wJCFl0VvVuSrb9NvyJ/9juqk4d+5UbXhU9sUsbXvjqSh46OazFcXCr57H97ViwJXypeXSDCf9Qdypj+EjFv/Xakx27GkTgPfJk2aqEtNkC4OEvzOmTOnJNCV7O3ixYtx000sSCciinWa1aqCBikBkKlcMrRCai+tLdrFTJCoJohVQvIFk+Ho3DPmh28U8/7+K4zCvEo/XoJLGUiScfvTYX92+V9ML5rUZz57bm3RHikXTFb7lU8A5CKji2VwiOZ0qbrcUM8pAX3O9Efg276u6DkNoFTM7du6GlnP36PaqcnrL/Ago8xXIy8HOf+9J2jG37d1DXK2rEbyuBvg6j8SschwF6BQ+iCH+8RC19UbGO/vK9RQkngWN4vbduzYgRUrVqivfr9f/b9ccnNl0UCAlETMmBFoei4v8ttuuw0PPfQQPvvsM6xatQpXXnklWrRogXHjxtXhd0JERNGQRUdSIyr/4MqI4lgJektar0VLs6iJY/ES9Fb6+yzN0KH/sTdsD2Dfvh0q4xvtgjYZ1Vv+NSHnVl4r1sYtwr5ePCvnw7dtbehAWxZ5HTkAIz83zHEVBcxB7zJKpthJl4pY5Fm3LDAcJBLNAs8KKSWJb3GzuE0GUUg/3mK9evVSX3/44QcMHRr4uGvDhg1qRnOxu+66C3l5ebj++utx9OhRnHbaaZg1axZ7+BIRUbXwrPq5ckHgkYOIJ5ozqeo7sVjh3bAc9g7dg97t37u1kovV/PDt2aLKRqJ9U6SGYxSXLoRV1ZZqGgoXzYrJFmhG7lFz50Bet9lHEO/iJvCV/r2ReviWb5kivwAPPviguhAREVU3/4FdlXiUpj6Cjyf2zr1U4Bpt7W2wkofQoghaZcGZM1nV5QZqcwOtxpKGjIOjzxmmAmBD9wfazdUGQ4dX3iTFYOCrSbcGM6Ulcs6TUxHv4ibwJSIiqkv+Q3vhXjoH/j/2qPILW/tulRyeYcBxYmBYQrywpKSrBXieX3+sfG9d1R6rcci7ba06RLWv8jXH+qG9qoOEb/9OpJw90cQ+UKsMj4lygjpg79LH3Jsa6T7SfSDiHQNfIiKiMKTva96nr8Cz7LvA0ANZfKVpgTIHtcI9ilZmkom0O+HsORjxJuWca+Dfuw3+fTsqGfwacPYK3YnD2qQlbO1OhG/b+ioNrnAv+EKVUzi69o24eNLSpCX0g3tqJQqW9me1wfC6VRbcvWI+jLxsaKkZcJ58OhwnDQo6FdGSmgFHz8Hw/Dov9HnXLOr4pcVbvIubxW1ERER1QbW6Wj4ncEWCXlH80bDKkpkNei3qknrZX+Jy6pccc/r1/4BryPnQklLLBkUNjov8+JSMiFPcZCoarFVsl6VZiroURBYYgBLh51dNiyml1VpNkwV0R5+4GXkf/xe+Lavh37cdvs2rkPfxczj6z8nw7d0W9HEp514TGK8d7Hu1WKA5XEi7aio0mx3xTjMqO0swQUgLNBl1LIvm0tNr590aERHFBgkUsp/5S7Xsy9apJ5JHXAJb606Id9IGTNU3+32wNDhOBcU57/8HvrVhpq1JUJWUhow/PwlriMEOvt2bkf381CrXEosGD74XMVCT8oPsF/+mAsSgda6S4U9Oh71VB3jXL6/8wVhtyLjzWVjDlHpUlQzgyH76TtWeLGjmVt6guJKR8ed/wZJxbAxz6Uyx9MyWBX9GTtEiNptd9cuW6XXWhmUn4cZrvMZSByIiohDcS0uVN5jJaJYatCGsLTuo8cu240+ANbNJhaBLBiOoXrPJaYgnElDaWrQrc5ur/wjkhgt8JbDMz0b2f25TfXcd3QZU2CR/1ttR9fANRyathQt85fy7l80pChRLP6dW1OVAh/W41kj9v7tgyWiMgu8/QuHPX6qeviVsDsDnjZg1Tr3i7hoNekXhgi9geEIEvcLQ1UQ5+R6Sx1xZ4W4pg1B9swePVYNZ1JuajEYq21ufMPAlIiIKQWpazQS9wnXGRbA1bq4Wv8Fmg71d96BjeiWLXDj/s0A3gqLMprV1p8AEtx6DYqpPcTQKZr9jajsJvmQkcfL5N8LVb0TJ7f7D+9XH8tXC4QzbOUPPz0HOKw8EMr0Vj1DVxaaMnwx7554lP4/kkROQNPR8eDeuhJ6XBUtSGuydToZ32zrkvvMk4PNU3FVSCtKuvEf1oa5J0tJNgviIr1VDh3vJd0gadXnICWxye6xnd6uCgS8REVEoUYxnlcVSEgjJJRTP+mXIffufgQxhqSDFv2sz8t5/Sg14SB47Ke6CXwla1ZuEKOTPfAmOzr1KPnb376/86OcyLBY4e58RdrRu7nv/hj/MqGkjNxvu5d/D0SUwM6B0VrR8Rw5Hl97InPKi2t6zepEK7KV7hbPPcDhO7FcrdbFGfk7ZTHS4bd35aiCHBPeJiIEvERFRCFKi4Nsm42wjZ31tbbqEvd9/9GAgM6gC3nIfjRft373kG1ibHw/XgDMRT9yLv6nU4wqXfKsyqUp1BPuyD6tdlZeEIhn3iJll6bu7eiHca5fAu3qRGrwhdc1S8uDsPxLOPmfAIv1vi0ipStLpY9WlTkQZXGv1YJFaZbGrAxERUQiu/iNNrPq3wNa2C2zN2kQODoMFvWV3hsL5n0bsfhBrPGsWRf8gCS5//7Xkqq1lh0A9tanuGFKHawnSKs6BtKvugbVRs9DHumK+ueeBhry3n4Dnt59gFOQBXg/0P/ag4Ks3kfWf2+A/uBuxQoJwecMU8c2DpqntaqKriLxm5U2F5/cV8O7YoMovYhEzvkRERCHIx/BJo/8PBV+/FXwDCb7sdiSPvT7ivjwr55vIHBvQpWxg33bYJJCJEXphHjy/zIV72ffQsw+rEcYyzMA54ExVD6oWiFWG91hdrCUtE/Zup8ArQXS4WlVDR+qV98C3a5MKYuVjfukxK90HnH2Hq/2E/V7KLUAM80RFDyh/LIZaxJj96oPIvOP/xcziL9egs1Qbs7AMQ9WSVzfpGVzww/+gl3ozoKVmqsy76/Tzwpad1DYGvkRERGHIx9eaIwkF37wTyPzJP+KSkZVV/83aIOXCP8HWrG3E/ejyWJOkBjNW+PZtR86rD6phCMXBoASbhT99jsIFn6vvX2pa/er+KFgssJRb/Jc85gpkb1kNoyA3ZPDrPGU0HF37qIu0hws6injvdjUe2ZLesEL2V43ojWY8cjC6DiP7ENwrfyqzQK8uOXoNgWftUnjXLQvxqYIG+4n91AS+6lTw/f9Q8N37Fc6pkXtULXiUNyipl94RM8EvA18iIqIIpObW2WcYvOuWwi+TvmQhW/vuUfXklTpQ3WRmtLamfEWiuh+8Oq0oEA9Sl2wAeR89A+egs+HfvSXKneuqXrZkd4Zkuw+oFnC+Tb+VzarLc0m7rcHj4Bp2QdDdyUfr0tJLtfUq7kNb1DEj6YyL1CI0IZlq94IvUWWapjopxErgK4Fl6mV3omDOh4EBHp7CY3c6k+AaeBaShl9crQGod/v6oqBXBC/P8a5ZrMp8AsNC6h4DXyIiIpMLgqTdWGXJR/GSHQtf7qDB0qQFrE1bIxaoPrfSMSBszbEG/56t0NIaBPoYm2n/ZrHA1qoT7B1PLsnS5s14EZ7l35frmxzopyuZ4fTrpqkMbqigN/fdfxZlO8vy79qE3DceUd0yXANGwdK4hQoEzXZBCEkC9axDiCWa1YbkMy9D0tAL4N20MlAGkhxouxZsXHFVqQA7Yp9rTb0ZkUx9LHQr4eI2IiKiWuDsNzKw+j7sP/4GkmQkcAwECEJ6vkYcKGHo8G1dg9SLb1NDPAIfeYc4/qJFZbZWHZF65RRoRdcLvvswEPSKMkFU4Ln1Q/vV6OhQCn/+ImjQG9hFYB/5n70C367NyH3tH2WzoVUgtc6xSHME2q5JzbN8rYmgV3jXLzPxRidQt64f2odYwIwvERFRLbCkN1DDDHLefERNxSoTMBRlzVxDzle1mrFCzzaf0dTsdmTc/h94fpkH99Jv1QhdaS1mzWykWoEJa+MWqrxBMr3FQa8snCv86bPIHSA2/ALfnq0VJsZJtlhG7UY+QA35X75e1G84QjBvtQV+RhH2J2UTicqQNxSlFidG3N7rRixg4EtERFRL7B26I+PP/0Lhgq/UwAMUBQO2Dj0Ck9s6lx2YUNc0u6MkaI3I7oDFlaK6C8jFLOmTGxj7G4HFAvcvcysEvtIBw8g+HPnxug7fjg2Rg1610whBb3GHhFI1yolG07RAeUupeuowG8OS1gCxgIEvERFRLbI2ao6U865F8jkTVecBzeaI2YEC9hP6wbPix4gfZ2vSPaGSdckqMywLrorGN4ekG9CPHqxws+GOomyhmvsjF8z9RE2tk/Nja94Wzn4jYG3SEonC2W8ECn/4OHzdumaBvUsvWGJkUhwDXyIiojogq+s117HpX7FIVuJL/95InP3PVNtJDa1kVK3N28HZ83RTNbCqD66ZgNSiBe2ZWzzyuC64F88u+X/f1tWqxZuj/0iknHudGmGdCN1O3Au/glFYEDb4dQ0dj1jBwJeIiChOGfLx/ZbV8O/fqT5OVhPkZAJadSk/HS2Ewh/+FygPKG6VpfuR/9V0JI+5Cq5TRoV8nJ6XHagjNjESWrKq9q59j13Nz4F+9A+VMbe26gT/7k3hA2j5aN6VEugRXBOKsuKeJd+qNzUp512H+s6S1gBp19yPnNceDPS4Ll1GIq8di6YWPdojjPOuTQx8iYiI4pBn3TLkf/Ea9CMHjnWKMAxYW7RDyvk3lgmAVY/cQ/uK2lulwtKouanOEYULzbSrKlUTW7pcwetB/mcvq/8NFvzKeFs1GKMgx+R3LNPA0tXjCuZ+DO/qxSUBs5aUGiHotajBFVJHXfCt9J2t2ZHQ7kWz4DrtXDXVrr6ztWyPjL88C8/yH1Tdup59RJ1raf0nnwRYGzRBLNGMeBsIXsuys7ORkZGBrKwspKfHRkNxIiJKbJ5VPyP3vX8XtQ0r98+4BLRWO9Kvf1C1DZPpYoXzZqhFYMWsTdvANWQcHCefHjYAPvzA5YCniqvx7Q40uOcVaK7kkpukk0PWv24JDMYwk+0tIj1p1XhkeUyoYFy+n9KhjWR6k1KRds19qqtE9ot/g3//DnP9hitLs8A1eCySR11ec89BlYrXmPElIiKKIxL45X78XPG1IBsYKgOb+9EzcHQbgMK5n1ToHew/sBN5Hz4N/74dSB79f8GfR7K3VQ16hdcD94of4TpldMlN7l/mFY1Ajo4aphGOpqmgXs89CsPjVh/FywIsZ98z1OQ8kXbt/cj74P/Bu3FF9N+L6QM14D+4u+b2T5XGwJeIiCiOSAY3YkBq6NAP7g4Evep6+XHDgeuFP86ErW1XOE7oW/F5lv9QPQdssarJbsU8v69AwddvosYCzkP70GDqKyEX1kkAnHb1vShcNEsNtagRWmCKGsUeTm4jIiKKI74ta0wvOjOjYH7F4RGFi79BfphJaZXlWbcUuW88bK5PbmV53fBu+i3iZjJIQ0tvFGGSXjlm284ZBmzHn1DmJgnIpS7bs+EX6LlZ5p+TqhXfjhAREVWSnnVIBVmG1wNLgyaBiWQ13cZKLSCrvuU5/m1rVflEcYbUKMxXE86qje6HtVVHNbkr76NnanpdWcn3EIl0Xki96E/Ief0fRQ8Kf2DSOULKJgq+fRdGpMDV7oCzaAKfb9cm5M9+G77Nq4/db7HA0X0QksdcUaft2BIRA18iIqIo6TlHkffZy/CuXVImYNJSM5E08hK4+kU/0cv/x164l3yjMoJSF2tp0kLtR4ZIlA6mLce1AtYEWdRWBdIpwV6UoXSvmG9ukppZDiecJ58Gz6qFpgLS6iATxcywd+ih2nHlzXwB+h97A5l09fOseG79EsDu2mhqvynjb1aL+bxbViPn9YcqLqTTdXhW/6zuT7/p0ZjrfFCfMfAlIiKKgnxMnf38PUX9Z8sGSEbuUeTPeBFGbjaShl1gep+FC75A/pfTy7QOk2xy7saVsLZoj7SJfyuZfOXoeToKv/+oWr8n77qlJYGvb7cMoag+Kedco7LJ3q1rzLVGqyItJUONhjbL3r4bMm5/Gr6ta+Hdvg6F82YGRklXyABHfqMhE+ykf6/jxP7qU4Dcd54MZOiDZZN1HUZ+NvL+9wzSJz1o+nipaljjS0REFIX8WW8Fgt4wAVzBt+8FhkqYIBlWFfSK0vssavPl37cNOW88orosGD4v8me+ZGq/Wrq5rKd62uzDqCzXkPMDfXSFDLAoGmKhOZORcsHNcPYdHrjPLwFgJZ5AgmUJ+PsMg5bZpOR6KElDxkW9sExaukkAbEnJADyFlRttrGlw9hysgt7ilnNqWEa4fckAkq1rTb9WqOqY8SUiIjJJpoV5pKtCpKylxaIWiKWcd23EyWsSJId/Uh3+3Zvh3bgS/gO7AovbInD0G6GCPxmkEJEMdyg1CtjWoh08yyM/rOThSanIvOdleNYsVvWsEt3amreDo8dAaHZnyXbWJi1N79PSqFnJY6U+WAZg2Fq0h//QXmS//ACMnMNlA8qiTLLzlNFwnnqOqeeQNxLe33+Fe/E36rzCaqtaKYZhwL30WySNulwF0rLvQOlEhNeKpsHz+69Iatq68s9NpjHwJSIiMsm343dzHQl03VSfWN/29YHJa5FYLHAv+Rb+vdtMfOSuwcg6BNeIS8wFvoYOe5feJVdt7bshGr5dG6HZ7KqOVy6hOPsMQ8F3MjUtArsTGbf8C5rjWNBczNqoOTJu/Rfcy+bAvWg29KMHVYbZ3ulkuAaOgU0WF5ro0qAX5CH3zUfV+a/O8gs1tlcyxs4kVepgajiHBMdSWkG1goEvERGRWdG04fJHXiBmKuhVG+pq6IQK9CIyVKeJ1KumwtqyQ6CHbqgATLK9aZmwd+lTcpN3zWJzx1T8bCaHXFjSG8J12nkonP9p2O2Sz7wsaNBbsp+kVCSdPlZdZPismUC3zPEaBnLffiLwJkZUd81xUZmFpbgsI9L+dT8sDY6r3mOgkFjjS0REZJKlcQtzG2oWWI+L/NG1ZneYf3JbFNuqBVU6UifcFqi/DVYXK7fZ7Ei7/K9lukb4Dx+IoretBmsUQVvSqMvgHHTWsecv2Y1FPafrjIvgKDXhLeKzRxn0Ct+2dfDJQrsoRiWbOxgLbMefqLLfxRluU0G1w6Um7FHtYMaXiIjIJFvT1qrmVGpuwy5aMnQ4B5wZeX/tugUWg6nevGFompquVihjcCNtK5tnNFJ9aqU0IH3y4yiY/TY8qxceC8RkMVfn3kg68zLYmrWpGIyr2lS/qeyyCvBMkmOSLg+uU8aoeljf7i2qrtbwFEL/Y4/qViEZYemB6xp0NqzSuq2aSZlEjXSXMHS4ioP6olpp+wl94V3/S9ggO0kWB5aqsS5NOnsULv0u8HqTfbbqqBYLsvdv5THwJSIiikLyqP9DzmvTAnNpg9XbSra3VccydbOhSIsyx0mnBhbMhctAahZVwyqlEdItIFLQ5ioVdEuP2NQJt0PPvQb+vVvVR/2SjbZmNg76WKmXdS+eHfHY1b5bdVTBWLSsjZsjecyVKJg3AwWz3ymb/fV6AjW8y39A6uV/haPrsTKM6iAT1GqipZqjzxmwl8vcpl58K3KkrGLzqrIL3YoX4w06G66h4yvsS35G8iagQLWt00oeJwvm5Lak4ZfANeyCSmW8Ex0DXyIioihIj9jUS+9E7odPFw16MMoEM7a2XZB6xd0qu2lG8jlXw7dzI/TD+ysGvxLYGAZSLpgMS1oDuIaMV90TVLY5TMbZs345bC07wN6pZ5kg21Lqesjvr0sfNQBCTScLF4zbHUi7+u+mvkcJ5IzCPNXSTEtOVedGxheroFcEGfAA6GoBmiwUs7fvHli81qFHlYO9cPXDFZTKDGuNW8DaqBn82zcEvpfi/aVkwDX4PLhOPbfCsUn/YjlHstBR3kyoxYlSEiHfj3SqCPGmoVDeEMz5sOhaqZ9z0c9cLRK02ZE0eGwU3zmpn4khr0YKKTs7GxkZGcjKykJ6enpdHw4REcUIvSAXnuU/qElr8lG9tWEzOPsNV+UL0QZn0iYtf9bb8Pw6r8wCOmuLdkgaeSkcpbLH3s2rkfP244C7IPQOi7KLyeNugKt/9FPkvDs2IOeVaYFjCRb82hxIv/Fh9XF+ONJ3WLK3hT9/pUoZ1KElpaoyENWebc8Wcz1ziwJQR9/hSBl3A7QIvXwjDwt5I3J3DE1D+q1PqbZwUv4hbwbk5yrfk0xckw4OlpR02NqdGHXf4Eivq6OPXBd5IaXNjgZTX1UT4gim4zUGvhEw8CUiotoiQY/qNiAjixs1g6358SG2y0PejOfhXb0ocvB2y5OwNWsb3XHkHIF300oU/jwL/t3Sm/cYe+deSD5rIqzHhe/La3jdyJn+SGAhWfmyEDP9bUNIGn6xulQpsHz0+rLZ+vIsFlWqknbFFNS2woVfI//z10xNiks+b5LKHBNMx2ssdSAiIooR0qqrdHY3FPkI3b97S+Qdaprq5Wsbd4Op55cBFFJD6t0gC7ICgZeWnAZ7hx6wn9gftjadTXdxyPvidfi2rS26Vi6Iq0JHhYL5n8F1+nkhF4SZOcepl9yK3HefLKqfLXdsFmnx1gApY82ds+qmpripDHeExYUWa2DwBkWF7cyIiIjijH5wt7kewLoOz6qFpvYpdcHZL/wN3g2/lgkGDZlWt3qhCqClTtjU8eVlqzKQSo3+jXighfCsW1alXUj7sLRr7lN9jsuwWOE46TRk3PwYLFGMfK5WpVrLRd6WYVy0mPElIiKKM0a4+t7y28oksQj03CzkvvuvooVcQYJVw4Bvxwbkf/MeUs6eGHF/3nVLTbVdqxTNotp8heI/vB++7RtUVtnatA1sLdsH3U6y2BLg+vbtCNQfW20qoy11u3XJ1vYEuBd+HXlD3Q972xNq45DqFQa+REREcUaLIhtpScuMuI17+fdFk+bC9SY2VO/d5BGXqFKLSIv1aqRXbtFxaM6KZQ7+P/Yg77NX4du0sszt1ubHq5pk6cYRjOpjXK6XcV1ynNgP+cnpKtMe8uehadBS0mE/oV9tH17cY46ciIgozlgzm8DWtmtgkVg4mqYGHkTikUVyZsoSPG541WK18CzJaSaD3qLuF5G+j3IPcXTtW+YmqXXNfm4KfFtWVdjcv287cl57EJ71VSuPqC0y+S3loj8FTk2w7iDqNg2pF91SZuIemcPAl4iIKA7JAIPwQy80aI4kOPuNiLgvmZ5mllEYucxCZSJN9TE24BpyvioxMEW6LZzYv8LkstyPngmUdAQLtot6Hud+8P9geNyIB7LAMW3ivbAULyRUI50DIZulYVOkXX1vmR7NZB5LHYiIiOKQQ9qKnTcJ+Z+9XLGsQLOorgdp19yrBl9EIoGkfnifqayvmUVfUifr6DMMHhkPHGqfFosK7JJGTlADLaQ8wrt5FfI+ehbQfRWDWM2igr6U828sc7OMPS4e6Ruaofoee377yVQGPBbIBL2MO5+Fb8sa+KTfsQRtLdtXqk80xWHg+/DDD+PLL7/EihUr4HA4cPTo0YiPmThxIt54Q5pUHzNq1CjMmjWrBo+UiIhilSx88qyYDz37MDRXUqBFV+vOcRtIqOlfbbuojgvSeUGynlpqJlx9h8PZb6TpzgTOPmfAt2V1xO209EawHW9uQVXKOVdD/2NvyD6+MvEs7aq/lUy4k/IIZ49BsDZppaaWedcuOZbRdibB1W+EynJLO7LSpN+wqb7Amgbvpt/iJvAV8rqU2uRQ9clUjwNfj8eDiy66CAMHDsSrr75q+nGjR4/G66+/XnLd6YxiVCEREdUL8hG3DHzwrPyp6GPjQKBb+OOnavFT6uV/hbVhU8QjGXJhO//GCpnQaDi6n4KCb9+Dnn0obG1u0rDxpkcxa3an+kjevex7FC78SrVgOza5bZQaQRxs4Z0sNku7/C+q04T/0F71fNKdIeSoYZ+vQlwdlIxN9npMHTtVzd49Odi5MxvJyXZ0PaExbLbYqayNm8B32rRp6uv06dOjepwEus2aNauhoyIiolhn+P3IeeuxYxlNyQyWCpL8+3eo/rUZkx+vUDuaKGQkb9q19yH7lQdgZB0uG0UWlVFILa6z/5nR7ddmV1lpGVGs6oj9PmjJqaaCZ+kZbKZvsEy4M909ItIYYKqSRT/vwmOP/IQfvt9WUuHSrFkKbri5L265tT8cjrpfjBc7IXgNmTt3Lo477jh06dIFN910Ew4dCt37T7jdbjX2rvSFiIjil2fNYvg2rwpda6rrMPKzUfDDx0hk1kbNkXHrv5F89lWwNG6h+tpKiYG92ylIm/QgkkddDiP7MHx7tsJ/9GDUH9lbklJUIGs2Y2yWLYoyAH+Y/r9UNTM/WY8xZ76DeXO3l/lV27cvDw/ePw8XjvsQbnfdv/GIm4xvZUiZw/jx49GuXTts3rwZU6dOxZgxY7Bw4UJYQ7QAefTRR0uyy0REFP/ci76OXAOq63D/8gOSx1wRsUdtfWZxpcB16jnqUppn7RJkPz8Vvp2/l9wmU8+SBo+Fo8egiPvVC/Pg+fVHeGQUsqcQlobN4OwzTNULV7W+2ogimNUP7a3Sc1Fwe3bn4NqJn0HXjaDvL+W2H+ftwOOP/oz7HhiMhM34TpkyRb3gw13Wr19f6f1PmDAB5513Hnr06IFx48bhiy++wNKlS1UWOJR77rkHWVlZJZedO3dW+vmJiKjuyar/iAuf1IZe+IvqUOmYgrmfIPftJ+DbtbHM7f49W5D73r+R/+17YR8v/XOPPno98j9/Fb7ff4Vv2zp4VsxDzsv3IeeVB6AX5FXtAKUUw6xo+gWTaa+/tgL+EEFvMQmKX35xeZ1nfes043vnnXeqzgvhtG8ffNRgZci+GjdujE2bNmH48OEha4K5AI6IiAiqvVjBN+8GrpSPaoquF/7wMWytO1UYKqEev3Utct96ouJji2pyJQjOffMRVUpR2RIIa+OWgMOlMslhaRbY2nRCZek5R1D481fqnEi9stSDO7r2gaP3MFXGkehlDro/ciu8rKNuLFq4C0OGHo+EDHybNGmiLrVl165dqsa3efPmtfacRERUt6T3qW/7hshZX5sdVqltJRi6H96NK5H/6cuRN9YsKPzpi6CBb8E37xQtlAsRFBm6+tl4N/wCRyXH70q3B2e/4XAv/Dr8IjdDh+uUMVHv3/B5kffpy/DIWOdS9D/2qNrx/FlvI2X8zXD2qtuP8OtSdrb5wSC5OXXbWSNucv47duxQPXzlq9/vV/8vl9zc3JJtunbtihkzZqj/l9v/+te/YtGiRdi2bRvmzJmDsWPHomPHjqqXLxERJQanBDuRgl6LBc7eQ6G5kpHofLs3I+vJPyH3jUegm1nEJsHrltWqjrc0/4HdRW84jMiB86LZVTrmpKEXwJLeKHTZg/TDPaFfYKJclG8ApMyjfNBbht+HvI+eVnXQiaply/Sg05WDadY8DXUpbgLf++67D7169cL999+vglr5f7ksW3Zs9vaGDRtUXa6QxWu//fabqvHt3Lkzrr32WvTp0wfz589nKQMRUQJxdBsQWPkfqr7TYoGWlIakYRci0fn27UD2y/dBr0T3g/KjjP1/mKyXNnToB3ahKmRSXPqNj8B2/ImBG+RnLaUTEo1ZrKoNW+qld0CLph5Y6pNXL4L3919NbZv/5XQYZtuq1TNXXHVSxDbK8qPo0LEBevep2xazcdPVQfr3Rurha5R6V5mUlITZs6v2DpKIiOKfZrUi7Yp7kPfJ82pkbekBFtD9sB7XWg2wSNQevqUVzHoL8HrNLQYsP344uVwmT9qhmRWi01JUh5DeAOnXPQD/gV3wrFsaqMNNb6i6TpjpBxyMKp8wST9yQE2ps3fogURz8YQT8fgjP2H//jz4Q9T6Soh299RT63xKYtwEvkRERJUldaCpE26D/8xLVVstPeewalumRha36VLn/xjHAv+Rg6azm2VYLLB3H1hhsposeFNZV90f+fEdT0J1sR7XCknHtaryfiSZ5ttZtpNFJBJ0J2Lgm5LiwGdfXYpzRr+H/Qdyy7xvstk0+HwG7r3/dEy4tO5HLzPwJSKihCFjiZOGX4R4ION1Pat+hnvlTzDysqClZMDZ83Q4JMi0O6r9+fz7tlfugQaQdNq5FW6WDLDj5NPgWTk//KIzXVcjjGNSpPrk8qIspahPOndphMW/XIe331iJ115dgV07s+Fy2TDm7E6YdENv9OsfGwtHGfgSERHFGN/ebch5/SEYuUcDZRkSgGkafBtXqC4CaRP/BlvzumsJVTrIS7n4VthadQy6SfLoK+DdshpGzpGQwa9r2IV1/70EIZ8CWJu2juoNQUmNcYJq0MCFW24boC6xKnHfmhAREcUg/9E/kPPK/TDysstmHYu+GrlZgcEP1Tx+N6pWbrJgrN9IZPz533CedGrozdIykXHTY7B37n2srrroq5achuRzr0XSiEsQq5wDzbc/s7XtAlvT1jV6PFR1zPgSERHFEPfPXwY6JIRaYGboauGWDFOQEcvVQXrV5n78rOnt0yZNg71tV9OLztKunBKoId60AvB4YGnQBPYuvaFFswCuDjh7DoZ78Wz4924LX/ZgdyJ57A21eWhUScz4EhERxQjD70fh0u8id1UwdLiXfKv6zEbcp8cN365N8O7YAD0/p8L9EpBmPftX+Hf8buoYHb2GqgWB0bI2aAJXv5FwnXo2HCf2j/mgV0gtddo198HWPvSiLEvTNki/6VHYmrWp1WOjyon9Vx0REVGCMCQwdReY29adD6MgD1pKetD7Jcgt+P5/cC+bc2ycr8UCR/dBaoGflpSK3JkvwhfN4IXkNKSMvymhumDIIr30a++Hb/cWuH/5Af49W2H4faou2dF/BOwtg9c3U2xi4EtERBQrbPaoNg+VNdVzjiL7xb9BP3KwbPZY1+FZ/bPqc6slpQQWnUVDAnO/r1r67sbj6Gu5UHxjqQMREVGMkJHJ1qZtji0EC7mhBmvz40OOWM77+LnAuOFgJRPSXcHrhpF9OPp2XarKwhf1Y4hiBTO+REREMUJKCKQGVqbMhWUYcA06K+hd/kP7KjeIwszxpaRDcwYPtusT/8HdcP8yF3r2IWiOJNhP6KeGbEQ78phiDwNfIiKiGCKLxzxrl8C7/pfAdIjyNA32rn3g6DUk6OO965cd6/1brTQ1aKI+1/ca7gLk/u9ZeNcsLjWMQlOdHSwNmyH1/+7iIrY4x8CXiIgohmhWK1Iv/ysKvn0fhYu+BjzuY3c6XHANHKN632oyDjgI1QpNs0iLiOo9sNQMuE4ZbW7U79Y1KPz5a3g3/6ZqgiVodA04E87eQ9Wo6FjtqJHz1uPwbV0buKHcwA396AHkvHQv0ic/AWujZnVzkFRlDHyJiIhijCxaSx79f0g640J4f1+hOjRIdwF7557QHK6wj7VkNARMtDmLisOJjBsegiU1I2LQm//Fa3Av/FoNuSg+Dv3ALuR//ioKF3yBtOsegDWzSVQ9hr3rlsF/cJfap63diaqdWnVnnr1rl8C3ZXXoDXQdhqcQBXM+ROrFf67W56baw8CXiIgoRkmQ6+h+SlSPsXc7BfjsFcDnrZ6DsNqRfuMjprKcEtiqoFeUCb4DZRf64f3IfuFvyLjzOVjskTtYSCu2/K/fglGQGwikpXzD0GE5rjVSL5wcclRyZRQumlWUKQ/TQ1m6Yvy2APo5V6s3IhR/WKVNRERUj1iSUkIufCshAZ7JxWzpk6bB1qytqcxs4dxPIm+XfRjZ/7kVeoRWajKZThb5qaC3OJAuCkr1g7uR/dJ98O3ejOri37s18uCQouOQxW8Unxj4EhER1TNJIy+D4+TTAldKdyIoKg+QVmgpl9ymShiC0ZLTkDzuemTe/SJsbTqbek7vpt8CAzhM0I8cQM5r/1DBctD7c44i/6vpoXcgAarfh7wZL5h6PqJiLHUgIiKqhwvkUi6+FY6eg+FeOAve7evUx/TWpq3VAjXHSadCs9lh79ILnl9/hGf9cjUxztKwKZx9z4CtXbeoa2j1nMNRbe/fvwOeVQvh7DW4wn3u5XMid6UwdDVFTcYxV0fJg9QNezetrLCoreKGdnUeKT4x8CUiIqqHJHB1dOmtLqFYXCmqS4Rcqvx8jii7NWiBNmHBAl/vtvXm2rFpGnzbN1RL4Os8ZXTk/scWC5y9hqjzRvGJpQ5ERERUZfZOJwMhRigHZRjwH9ob4j4TtbaKBsP0tuHZO/eC/cT+oafmWSzQktORNPziank+qhsMfImIiKjKpMtBYKhGFCUSIQJlm4xtNjMlzdAD21YDmcqWOuF2OPuPDDy3BMByfEXHYW3ZAek3PQJLesNqeT6qGyx1ICIiomqRcvZE+HZvgS4dEiKxWFSWNRgJPgt/+jzyLjKbwNahB6qL1D2njL0eSWdcDM/K+dCzD6uhIY4T+sHWsn21PQ/VHQa+REREVC1kKlvGDf9A9isPwL9rU/iNdR2uU0YFvcvauIUajyw1wOEknz1RZWqrmyUtE67Tzq32/VLdY6kDERERVevQjbSr/w5Lk5Zh+wVLraytRegsavI518BZvOhO7Uc7Vn9rdwS6VnQbUO3HT/WbZsh8QQopOzsbGRkZyMrKQnp6el0fDhERUVzQC3KR/8V0VTJQeoqbltYASSMuhqvfSFP78R85APfSOWpksVY0stjZczA0V3INHj3V13iNgW8EDHyJiIgqT8/LVsMt4HXDktEYtg7dVQBLVBfxGmt8iYiIqMZYUtLhLJ4iR1THWONLRERERAmBGV8iIiKiOLNu7UH8OG8HvB4/OnRqiJFntofNxnxmJAx8iYiIiOLExo2H8aebvsLCBbtUkwsZTa3rBpo2TcG0h4fissurr69xfcTAl4iIiChOgt7hg99ETo5bXZf2BMU9Cvbvz8ON132JrKNu3DS5bx0faexiTpyIiIgoDtzx59kq6PX7Qzfkmnr3HOzZnVOrxxVPGPgSERERxbhNmw5j3tztYYNeIQng6a+vqLXjijcMfImIiIhi3MIFO01tJ/W+P87dXuPHE68Y+BIRERHFOK9Xr5FtEw0DXyIiIqIY16VrI1PbSUuzE7s1qfHjiVcMfImIiIhi3KBTW6Nd+0zVwiwcn0/HNdf1qq3DijsMfImIiIhinPTrfeSxM8JuY7FoGDe+C3r1blZrxxVvGPgSERERxYGzz+2MF189B06ntUzm12YLXDn/gq546dVz6+4A44BmFHc+pqCys7ORkZGBrKwspKen1/XhEBERUYI7fLgA7761CnPnboPH7Uenzo0w8ZqT0eOkpkhU2SbjNQa+ETDwJSIiIqof8RpLHYiIiIgoITDwJSIiIqKEwMCXiIiIiBICA18iIiIiSggMfImIiIgoIcRF4Ltt2zZce+21aNeuHZKSktChQwfcf//98Hg8YR9XWFiIyZMno1GjRkhNTcUFF1yA/fv319pxExEREVHsiIvAd/369dB1HS+++CLWrFmDp556Ci+88AKmTp0a9nG33347Pv/8c3z00UeYN28e9uzZg/Hjx9facRMRERFR7IjbPr7//Oc/8fzzz2PLli1B75c+bk2aNMG7776LCy+8sCSAPuGEE7Bw4UKccsoppp6HfXyJiIiIYlu97+Mr31jDhg1D3r98+XJ4vV6MGDGi5LauXbuiTZs2KvANxe12q5NX+kJERERE8S8uA99NmzbhmWeewQ033BBym3379sHhcCAzM7PM7U2bNlX3hfLoo4+qdwzFl9atW1frsRMRERFRAga+U6ZMgaZpYS9SnlDa7t27MXr0aFx00UWYNGlStR/TPffco7LJxZedO3dW+3MQERERUe2zoQ7deeedmDhxYtht2rdvX/L/sjht2LBhGDRoEF566aWwj2vWrJnq+nD06NEyWV/p6iD3heJ0OtWFiIiIiOqXOg18ZfGZXMyQTK8EvX369MHrr78OiyV8slq2s9vtmDNnjmpjJjZs2IAdO3Zg4MCB1XL8RERERBQ/6jTwNUuC3qFDh6Jt27Z48skncfDgwZL7irO3ss3w4cPx5ptvon///qo+V3r/3nHHHWoRnKzwu+WWW1TQa7ajAxEREcU3aV616OddePmlX7Bk0W5IL6vefZtj0g29cfrgNqqskhJHXAS+3377rVrQJpdWrVqVua+4G5t0cJCMbn5+fsl90u9XMsOS8ZVuDaNGjcJ///vfWj9+IiIiqn0+n47JN36F995ZDZvNoq6LvXtz8OmMDRh7fhe8Ov08OBzWuj5UqiVx28e3trCPLxERUXy6567v8N9nl6ksbzBSNXnFlSfhmefPqu1Do2pW7/v4EhEREYVy8EAeXvjv8pBBr9B14M03fsPOHVm1eWhUhxj4EhERUb3zwftrwga9xSwWDe++s7o2DoliAANfIiIiqnd27siG1Rp54ZosbtuxnRnfRMHAl4iIiOqdpCSbqYxv8baUGBj4EhERUb0zclT7ki4O4cg2Z47uUCvHRHWPgS8RERHVO4NObY2uXRuFLXeQ+1q3SceIkcemxFL9xsCXiIiI6h2p3X3jnXFISXEEDX7lNqfLhrffG68WuFFiYOBLRERE9dIJJzbB3AVXYczZHcsEtzKsbcSZ7fHDj1eiV+/ABFhKDKzmJiIionqrY8eGePeDC7Bndw5WrtyvbuvevQlat8mo60OjOsDAl4iIiOq9Fi3T1IUSG0sdiIiIiCghMPAlIiIiooTAwJeIiIiIEgIDXyIiIiJKCAx8iYiIiCghMPAlIiIiooTAwJeIiIiIEgIDXyIiIiJKCAx8iYiIiCghMPAlIiIiooTAwJeIiIiIEgIDXyIiIiJKCAx8iYiIiCgh2Or6AGKdYRjqa3Z2dl0fChEREREFURynFcdtoTDwjSAnJ0d9bd26dV0fChERERFFiNsyMjJC3q8ZkULjBKfrOvbs2YO0tDRomlYr71gkyN65cyfS09Nr/PniGc+VeTxX5vFcRYfnyzyeK/N4rqLD8wWV6ZWgt0WLFrBYQlfyMuMbgZy8Vq1a1frzygs3UV+80eK5Mo/nyjyeq+jwfJnHc2Uez1V0Ev18ZYTJ9Bbj4jYiIiIiSggMfImIiIgoITDwjTFOpxP333+/+krh8VyZx3NlHs9VdHi+zOO5Mo/nKjo8X+ZxcRsRERERJQRmfImIiIgoITDwJSIiIqKEwMCXiIiIiBICA18iIiIiSggMfOvQtm3bcO2116Jdu3ZISkpChw4d1KpMj8cT9nGFhYWYPHkyGjVqhNTUVFxwwQXYv38/6ruHH34YgwYNQnJyMjIzM009ZuLEiWriXunL6NGjkQgqc75kret9992H5s2bq9fkiBEjsHHjRtR3hw8fxuWXX64av8u5kt/L3NzcsI8ZOnRohdfWjTfeiProueeew/HHHw+Xy4UBAwZgyZIlYbf/6KOP0LVrV7V9jx498NVXXyFRRHOupk+fXuE1JI9LBD/++CPOPfdcNWVLvu+ZM2dGfMzcuXPRu3dv1bmgY8eO6vwlgmjPlZyn8q8ruezbt6/WjjmWMfCtQ+vXr1cjkV988UWsWbMGTz31FF544QVMnTo17ONuv/12fP755+ofl3nz5qmRyuPHj0d9J28ILrroItx0001RPU4C3b1795Zc3nvvPSSCypyvJ554Ak8//bR6HS5evBgpKSkYNWqUerNVn0nQK7+D3377Lb744gv1D831118f8XGTJk0q89qS81fffPDBB7jjjjvUm/JffvkFJ598snpNHDhwIOj2P//8My699FL15uHXX3/FuHHj1GX16tWo76I9V0LebJV+DW3fvh2JIC8vT50feaNgxtatW3H22Wdj2LBhWLFiBW677TZcd911mD17Nuq7aM9VsQ0bNpR5bR133HE1doxxRdqZUex44oknjHbt2oW8/+jRo4bdbjc++uijktvWrVsnLemMhQsXGong9ddfNzIyMkxte9VVVxljx441EpnZ86XrutGsWTPjn//8Z5nXm9PpNN577z2jvlq7dq36/Vm6dGnJbV9//bWhaZqxe/fukI8bMmSIceuttxr1Xf/+/Y3JkyeXXPf7/UaLFi2MRx99NOj2F198sXH22WeXuW3AgAHGDTfcYNR30Z6raP6W1Wfy+zdjxoyw29x1111Gt27dytx2ySWXGKNGjTISiZlz9cMPP6jtjhw5UmvHFU+Y8Y0xWVlZaNiwYcj7ly9fDq/Xqz6CLiYfKbZp0wYLFy6spaOML/Kxj7zT7dKli8p+Hjp0qK4PKSZJRkU+Civ92pK55/JxbX1+bcn3JuUNffv2LblNzoHFYlFZ73DeeecdNG7cGN27d8c999yD/Px81LdPDeRvTunXhJwXuR7qNSG3l95eSNazPr+GKnuuhJTUtG3bFq1bt8bYsWPVJw9UUaK+rqqiZ8+eqmxt5MiRWLBgQV0fTsyw1fUB0DGbNm3CM888gyeffDLkNhKYOByOCjWbTZs2Zf1OiDIHKQOROurNmzerMpIxY8aoP5ZWq7WuDy+mFL9+5LWUSK8t+d7KfwRos9nUG9Bw3/dll12mAhapu/vtt99w9913q48WP/nkE9QXf/zxB/x+f9DXhJRqBSPnLNFeQ5U9V/Jm/LXXXsNJJ52kkh7yt1/q8iX4bdWqVS0deXwI9brKzs5GQUGBWpNAARLsSrmavJl3u9145ZVX1JoEeSPfu3dvJDpmfGvAlClTghaWl76U/0O4e/duFaRJTabUDSaKypyraEyYMAHnnXeeWmAjdYZSv7l06VKVBY5HNX2+6pOaPldSAywZJ3ltSY3wm2++iRkzZqg3WERmDBw4EFdeeaXKzA0ZMkS9aWrSpIla90FUWfKG6oYbbkCfPn3UGyl5cyVfZR0RMeNbI+68807VTSCc9u3bl/y/LE6Tgn15Yb700kthH9esWTP1kdrRo0fLZH2lq4PcV9/PVVXJvuSjacmuDx8+HPGmJs9X8etHXkuSMSgm1+Uf5vp6ruT7Lr/4yOfzqU4P0fxOSUmIkNeWdGipD+R3RT4ZKd81JtzfG7k9mu3ri8qcq/Lsdjt69eqlXkNk7nUliwOZ7Y2sf//++Omnn+r6MGICA98aIO/Y5WKGZHol6JV3Zq+//rqqCQtHtpM/jnPmzFFtzIR8vLpjxw6VPajP56o67Nq1S9X4lg7s4klNni8pB5F/XOS1VRzoyseI8vFYtJ004ulcye+NvJGU+kz5/RLff/+96rhSHMyaISvNRby+toKRsio5J/KakE9MhJwXuf6nP/0p5PmU+2XVfTHplhGPf59q+lyVJ6USq1atwllnnVXDRxt/5PVTvi1eIryuqov8fapPf5uqpK5X1yWyXbt2GR07djSGDx+u/n/v3r0ll9LbdOnSxVi8eHHJbTfeeKPRpk0b4/vvvzeWLVtmDBw4UF3qu+3btxu//vqrMW3aNCM1NVX9v1xycnJKtpFz9cknn6j/l9v/8pe/qG4XW7duNb777jujd+/eRqdOnYzCwkKjvov2fInHHnvMyMzMND799FPjt99+Ux0xpMtIQUGBUZ+NHj3a6NWrl/o9++mnn9Rr5NJLLw35e7hp0ybjwQcfVL9/8tqS89W+fXtj8ODBRn3z/vvvq84e06dPVx0wrr/+evUa2bdvn7r/iiuuMKZMmVKy/YIFCwybzWY8+eSTquPM/fffrzrRrFq1yqjvoj1X8rs5e/ZsY/Pmzcby5cuNCRMmGC6Xy1izZo1R38nfoeK/SRKK/Pvf/1b/L3+3hJwnOV/FtmzZYiQnJxt//etf1evqueeeM6xWqzFr1iyjvov2XD311FPGzJkzjY0bN6rfO+k+Y7FY1L+BZBgMfOuQtLKRF3GwSzH5R1WuS3uSYhKE3HzzzUaDBg3UH4Lzzz+/TLBcX0lrsmDnqvS5ketyXkV+fr5x5plnGk2aNFH/8LZt29aYNGlSyT9C9V2056u4pdnf//53o2nTpuofcHlTtmHDBqO+O3TokAp05Q1Cenq6cfXVV5d5g1D+93DHjh0qyG3YsKE6T/IGVv5BzsrKMuqjZ555Rr3ZdjgcqmXXokWLyrR1k9daaR9++KHRuXNntb20oPryyy+NRBHNubrttttKtpXfubPOOsv45ZdfjERQ3HKr/KX4/MhXOV/lH9OzZ091vuSNZum/XfVZtOfq8ccfNzp06KDeRMnfqKFDh6pEGQVo8p+q5YyJiIiIiGIfuzoQERERUUJg4EtERERECYGBLxERERElBAa+RERERJQQGPgSERERUUJg4EtERERECYGBLxERERElBAa+RERERJQQGPgSERERUUJg4EtEVMMmTpwITdNCXo4ePYpEUFhYqM5Fjx49YLPZMG7cuLo+JCJKMAx8iYhqwejRo7F3794yl48//hiJxO/3IykpCX/+858xYsSIuj4cIkpADHyJiGqB0+lEs2bNylwaNmxYZpvp06cjMzMTM2fORKdOneByuTBq1Cjs3LmzZJsHHngAPXv2LLnu8XjQsWPHMpnjDz/8EB06dFCPb9SoES688EIcPHiw5DGyrTxHaUOHDsVtt91Wcv2tt95C3759kZaWpo71sssuw4EDB0runzt3bpnnPHLkCE466SRceeWVMAwj6DlISUnB888/j0mTJql9EhHVNga+REQxJD8/Hw8//DDefPNNLFiwQAWWEyZMCLn9s88+i/3795e5rWvXriqI3rBhA2bPno1t27bh7rvvjuo4vF4v/vGPf2DlypUqSJZ9SJlCMLm5uTjrrLPQvn17vPbaayogJiKKRba6PgAiIiobcEowO2DAAHX9jTfewAknnIAlS5agf//+ZbY9fPgwHnroIRXU/v3vfy+5XTKvxRo0aKCyvlJmEI1rrrmm5P8loH366afRr18/FeSmpqaW3Od2u1VGOTk5GR988IGq3SUiilXM+BIRxRAJHCXALJ29lfKHdevWVdj2wQcfxLBhw3DaaadVuG/+/PkqQJXHFhQU4F//+leZ+y+99FJ1f/FFti9t+fLlOPfcc9GmTRtV7jBkyBB1+44dO8psd/nll2POnDnqfinnICKKZQx8iYji0MaNG/HKK6/g8ccfD3q/1Of++uuv+Oabb3Do0CG8/PLLZe5/6qmnsGLFipKLbF8sLy9P1Ranp6fjnXfewdKlSzFjxoySmuLS9u3bpxbpPfLII1i1alWNfK9ERNWFgS8RUQzx+XxYtmxZyXWp05U6Xyl3KE3KG6677jq1sC0Y6Z4gC+Ske8L111+vAtjSZHGZPLb4ItsXW79+vQqWH3vsMZx++ukq61x6YVtpn332GcaPH68WrF199dXq+ImIYhWLsYiIYojdbsctt9yiamql7OFPf/oTTjnllDL1vZs2bVIlB/I1mPfff191dWjatKnKDL/wwgtlMrqRSHmDw+HAM888gxtvvBGrV69WC92CKe5MIUGy1BbL13vvvTfkvteuXauyxlKfnJOTo7LNonSnCiKimsLAl4gohsgiMcnmSvuw3bt3q4zrq6++WmYbKUWYNm1ahXZoxaQe+K677lLdHho3bowxY8bgySefNH0MTZo0UV0hpk6dqgLw3r17q8efd955IR8jrcqko4P0K5bBFN27dw+6nXR/2L59e8n1Xr16qa+hWqAREVUnzeBfGyKimCDBpvTSTZRJbkREtY01vkRERESUEBj4EhEREVFCYKkDERERESUEZnyJiIiIKCEw8CUiIiKihMDAl4iIiIgSAgNfIiIiIkoIDHyJiIiIKCEw8CUiIiKihMDAl4iIiIgSAgNfIiIiIkIi+P8yn0LtsHK/qAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8, 6))\n", + "plt.scatter(X[:, 0], X[:, 1], c=labels, cmap='plasma', s=50)\n", + "plt.title(\"Результаты кластеризации DBSCAN\")\n", + "plt.xlabel(\"Признак 1\")\n", + "plt.ylabel(\"Признак 2\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "a322bd81-2c0a-45e8-ba97-450dca238577", + "metadata": {}, + "source": [ + "**Интерпретация результатов:\n", + "Алгоритм DBSCAN успешно выявил три кластера, соответствующие исходным данным.\n", + "Точки, помеченные как шум (label = -1), находятся вне плотных областей данных.**" + ] + }, + { + "cell_type": "markdown", + "id": "2cefd150-9186-40ef-8a16-ec8af853d752", + "metadata": {}, + "source": [ + "# **Часть 2: DBSCAN на реальном датасете из OpenML**" + ] + }, + { + "cell_type": "markdown", + "id": "78648178-0cbc-4e79-b1ee-98dd8c2ebaa8", + "metadata": {}, + "source": [ + "**Цель-применить алгоритм DBSCAN к реальному датасету для выявления кластеров в реальных данных.**" + ] + }, + { + "cell_type": "markdown", + "id": "bdbb1d75-f88c-4823-8492-0ba87e090b9a", + "metadata": {}, + "source": [ + "**Загрузка датасета**" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "d7890642-1e16-48f8-a921-d437118dd4da", + "metadata": {}, + "outputs": [], + "source": [ + "import openml\n", + "import pandas as pd\n", + "\n", + "# Загрузка датасета \"Banknote Authentication\" с OpenML\n", + "dataset = openml.datasets.get_dataset(1461)\n", + "X, y, _, _ = dataset.get_data(target=dataset.default_target_attribute)\n", + "X = X.select_dtypes(include=[np.number]) # Используем только числовые признаки\n" + ] + }, + { + "cell_type": "markdown", + "id": "136f2221-2db5-4bd0-a748-feb6116ec563", + "metadata": {}, + "source": [ + "**Предобработка данных**" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "d135c708-3bdb-419d-9651-a7f5ad4c0ee4", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "# Масштабирование признаков\n", + "scaler = StandardScaler()\n", + "X_scaled = scaler.fit_transform(X)\n" + ] + }, + { + "cell_type": "markdown", + "id": "89840396-9b8f-488b-9669-a210a5715a06", + "metadata": {}, + "source": [ + "**Применение DBSCAN**" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b80856dc-f661-42fc-9e24-10880dd79176", + "metadata": {}, + "outputs": [], + "source": [ + "dbscan = DBSCAN(eps=0.5, min_samples=5)\n", + "labels = dbscan.fit_predict(X_scaled)\n" + ] + }, + { + "cell_type": "markdown", + "id": "0566b5fc-63f2-4b53-812e-60555fb69902", + "metadata": {}, + "source": [ + "**Снижение размерности для визуализации**" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "2d17ec0c-5d49-4ca9-8b60-d2a573c4f485", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.decomposition import PCA\n", + "\n", + "pca = PCA(n_components=2)\n", + "X_pca = pca.fit_transform(X_scaled)\n" + ] + }, + { + "cell_type": "markdown", + "id": "d2b9bf69-111b-421c-b33f-3d4d4d6c7fec", + "metadata": {}, + "source": [ + "**Визуализация результатов кластеризации**" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "8c1ff471-66f4-428b-b2c4-19ed5afcad9e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8, 6))\n", + "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=labels, cmap='plasma', s=50)\n", + "plt.title(\"Кластеризация DBSCAN на реальном датасете (PCA)\")\n", + "plt.xlabel(\"Главная компонента 1\")\n", + "plt.ylabel(\"Главная компонента 2\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "ca380da1-6d1c-4ebb-b918-8e36b17ba4f4", + "metadata": {}, + "source": [ + "**Интерпретация результатов.\n", + "DBSCAN выявил несколько кластеров в данных о банкнотах.\n", + "Некоторые точки были помечены как шум, что может указывать на аномалии или выбросы.\n", + "Использование PCA позволило визуализировать многомерные данные в 2D-пространстве.**" + ] + }, + { + "cell_type": "markdown", + "id": "10b7f90c-6fea-44a1-9178-ef4ef779b528", + "metadata": {}, + "source": [ + "**Вывод: Заключение\n", + "Алгоритм DBSCAN эффективно выявляет кластеры в данных без необходимости заранее указывать количество кластеров.\n", + "На синтетических данных алгоритм точно определил исходные кластеры.\n", + "На реальном датасете DBSCAN выявил структуры в данных, что может быть полезно для обнаружения аномалий или сегментации данных.**" + ] + }, + { + "cell_type": "markdown", + "id": "d48992b5-516d-4bb2-93e0-e2a8159553fd", + "metadata": {}, + "source": [ + "**Интерпретация результатов (реальный датасет)\n", + "Наблюдаемые эффекты:\n", + "Алгоритм DBSCAN позволяет эффективно выделить плотные области данных и отделить разреженные точки как шум (аномалии).\n", + "В реальном датасете, содержащем многомерные числовые признаки, DBSCAN идентифицировал несколько кластеров, а также точки, не попавшие ни в один кластер (label = -1), что может указывать на потенциальные аномалии.\n", + "Несмотря на использование снижения размерности (PCA) для визуализации, полная интерпретация структуры кластеров в исходном многомерном пространстве остаётся ограниченной.\n", + "Практическая значимость:\n", + "Точки, классифицированные как шум, могут представлять особый интерес — например, в задачах обнаружения мошенничества, сбоев или отклонений от нормы.\n", + "Алгоритм не требует предварительного задания количества кластеров, что делает его особенно полезным при анализе плохо структурированных или неизвестных данных.\n", + "В целом, DBSCAN может быть полезен как инструмент предварительной сегментации и выявления аномальных наблюдений, подлежащих дальнейшему анализу.**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ed74e390-d3e7-40ec-98ff-120d1faca6b5", + "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": "3.13.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/Untitled.ipynb b/Untitled.ipynb new file mode 100644 index 0000000..b1935a3 --- /dev/null +++ b/Untitled.ipynb @@ -0,0 +1,198 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "b90a9f64-8f6c-4766-949c-2d2b5b2f5cfb", + "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 0.50 0.67 12\n", + " 2 0.54 1.00 0.70 7\n", + "\n", + " accuracy 0.80 30\n", + " macro avg 0.85 0.83 0.79 30\n", + "weighted avg 0.89 0.80 0.80 30\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "D:\\Practice4\\.venv\\Lib\\site-packages\\sklearn\\neural_network\\_multilayer_perceptron.py:691: 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": "code", + "execution_count": 2, + "id": "31c17449-d620-449b-ad0d-12375f567a70", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 0.89 1.00 0.94 8\n", + " 1 0.38 0.89 0.53 9\n", + " 2 0.00 0.00 0.00 13\n", + "\n", + " accuracy 0.53 30\n", + " macro avg 0.42 0.63 0.49 30\n", + "weighted avg 0.35 0.53 0.41 30\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "D:\\Practice4\\.venv\\Lib\\site-packages\\sklearn\\neural_network\\_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n", + " warnings.warn(\n", + "D:\\Practice4\\.venv\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n", + "D:\\Practice4\\.venv\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n", + "D:\\Practice4\\.venv\\Lib\\site-packages\\sklearn\\metrics\\_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\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=100)\n", + "clf.fit(X_train, y_train)\n", + "\n", + "# Отчёт о точности\n", + "print(classification_report(y_test, clf.predict(X_test)))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "5642dd14-042f-4895-ad2c-e04c919db0ed", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 1.00 1.00 1.00 10\n", + " 1 1.00 1.00 1.00 7\n", + " 2 1.00 1.00 1.00 13\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" + ] + } + ], + "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=2500)\n", + "clf.fit(X_train, y_train)\n", + "\n", + "# Отчёт о точности\n", + "print(classification_report(y_test, clf.predict(X_test)))" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "60f55406-d189-4b57-90d0-f0393235e99b", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import openml\n", + "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, accuracy_score\n", + "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.pipeline import make_pipeline\n", + "from sklearn.inspection import PartialDependenceDisplay" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "662ac0f8-7b50-42f3-b372-7c41aea3619e", + "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": "3.13.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/week4_scikit_learn.ipynb b/week4_scikit_learn.ipynb new file mode 100644 index 0000000..794fc25 --- /dev/null +++ b/week4_scikit_learn.ipynb @@ -0,0 +1,502 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "c7951e95-0bd8-4b23-863d-528051c0dc85", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 1.00 1.00 1.00 8\n", + " 1 1.00 0.14 0.25 14\n", + " 2 0.40 1.00 0.57 8\n", + "\n", + " accuracy 0.60 30\n", + " macro avg 0.80 0.71 0.61 30\n", + "weighted avg 0.84 0.60 0.54 30\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "D:\\Practice4\\.venv\\Lib\\site-packages\\sklearn\\neural_network\\_multilayer_perceptron.py:691: 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)))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0aab83de-75f3-4e00-ad79-f011f2195366", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 1.00 1.00 1.00 8\n", + " 1 0.82 0.75 0.78 12\n", + " 2 0.73 0.80 0.76 10\n", + "\n", + " accuracy 0.83 30\n", + " macro avg 0.85 0.85 0.85 30\n", + "weighted avg 0.84 0.83 0.83 30\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "D:\\Practice4\\.venv\\Lib\\site-packages\\sklearn\\neural_network\\_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) 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=100)\n", + "clf.fit(X_train, y_train)\n", + "\n", + "# Отчёт о точности\n", + "print(classification_report(y_test, clf.predict(X_test)))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "c5b95df2-6d00-440c-b7a5-9bd3360c9f70", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0 1.00 1.00 1.00 9\n", + " 1 1.00 1.00 1.00 12\n", + " 2 1.00 1.00 1.00 9\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" + ] + } + ], + "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=2500)\n", + "clf.fit(X_train, y_train)\n", + "\n", + "# Отчёт о точности\n", + "print(classification_report(y_test, clf.predict(X_test)))\n" + ] + }, + { + "cell_type": "markdown", + "id": "c4687a52-9dc6-4fca-9bb5-f433acddca90", + "metadata": {}, + "source": [ + "# 1. **Часть 1: DBSCAN на синтетическом датасете make_blobs**" + ] + }, + { + "cell_type": "markdown", + "id": "5027127f-d121-4544-9432-dc6c6d6ef670", + "metadata": {}, + "source": [ + "#**Цель-Продемонстрировать работу алгоритма кластеризации DBSCAN на синтетических данных с тремя кластерами.**" + ] + }, + { + "cell_type": "markdown", + "id": "518c3a5c-5f80-4ae7-9637-f810b1e577aa", + "metadata": {}, + "source": [ + "**Импорт библиотек**" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "43634fe1-67dd-4b63-a730-00e7ccbc07c7", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.datasets import make_blobs\n", + "from sklearn.cluster import DBSCAN\n", + "from sklearn.preprocessing import StandardScaler" + ] + }, + { + "cell_type": "markdown", + "id": "1b51a387-bfea-418e-8a0f-79b02b6024a0", + "metadata": {}, + "source": [ + " **Генерация данных**" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0b08cf7d-0761-45b0-8a2e-2817ce2d5e4a", + "metadata": {}, + "outputs": [], + "source": [ + "X, y_true = make_blobs(n_samples=300, centers=3, cluster_std=0.5, random_state=0)\n", + "X = StandardScaler().fit_transform(X)\n" + ] + }, + { + "cell_type": "markdown", + "id": "3d43f16d-aae5-4e39-81cc-f876cbe76068", + "metadata": {}, + "source": [ + "**Визуализация исходных данных**" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "bc586730-b430-44a2-a5b7-852f25ce19c5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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s6RE8RcMpHYAeW9KPLUU5SQyRWKBUDRrIQzl2lPJBIpVy9egHnnL7KC/277//tiq8TXnGtDxZNjmyHyTqaLk+ffpI8U2+o/TjSxFcKlJCP4qUMmDr+NPjVFqGbojMH8HSjztFxGkQEV0blBJCOaT0SJUG0dANEkUJM7pOEO0bRRdNqQ5kQ1WiRAmZs508cprW40PRUhKhJEJIkJCooUFKFI2kVBka+OYMSKDS54CuG7r+6QaKopj0mSDo+iJBSkKYorLUjnLfKT2BIqG0nxQptQSlx9B5tma9RlDONF3PtC41ud62sHRNkxcw5fHTeaPjZuvmmgQtXff0WaLIJwl9SpmhG2XzG2TaZ0p9oBt88u6lG0S6Puk7g/KCKVXA2Z9zE5RORtZ41JYixCTo6WkG7bcpTYyevFG0lwZG0qA/WhftO91Q2MqfJp9mupFRk15B39vJfZyZHE5m20owTGZy8eJFaddUsmRJ4eHhIe1umjRpIr7//vsk1lP0UVEURRw9etSmbVh62JkRV65cEX379hUFCxYU7u7u0tqJbJj++OMPh9dHfaA+jh49WrWllDnJbYJM/Pnnn6Jp06ZyP+lVsWJFaat14cKFJO327t0rraXoWFO76tWry+NtzabMxIABA0SuXLnE7du3U7UfdG7I7oksury8vESZMmVE//79pb2ULWhd9l7mx3rfvn2iYcOGwtvbWxQuXFha3/39998pLJTS087M9KJrlq6Zrl27inPnzqXL8SGePHki3nrrLXld0ueoaNGi8vw8fvzY7rK2+mTqF81btmyZmDBhgrTDomNLx4Psx5Jz/Phxub958uQRnp6e8tj16NFDbNu2LcU1bG5XZk7y+ZcuXZLXKm3fUr8dsTOzdk1/8cUXol69emLJkiWqjs+6devkZ4fOFX1/0fJkPWjpOFJbsj+k40bbq1+/vjyejtiZOfI5N13bdO2QDRz1kfZ/1qxZKSzVPvvsMzmPzlWtWrXE+vXrUxwvU7/M7cos9duSnVly20rT9cR2ZjkXLlnMMAxjA4q8UZTPvEJf8mghvbgSVPpAx7VFixbyKQzl4DJZH/qsUN5tRuR+M4yjcI4vwzAMwzAMkyNg4cswDGNn1H/y8rnJcx8pv5dhGIbJ+vDgNoZhGDteo7Ygv+bkns0MwzBM1oRzfBmGYRiGYZgcAac6MAzDMAzDMDkCFr4MwzAMwzBMjoBzfFVUPKLSi2TUnVHVuhiGYRiGYRj1UOYuVXek4ilU0MYaLHztQKK3WLFimd0NhmEYhmEYxg63bt2SJcGtwcLXDhTpNR1IKv/IMAzDMAzDZC3CwsJkoNKk26zBwtcOpvQGEr0sfBmGYRiGYbIu9tJSeXAbwzAMwzAMkyNg4cswDMMwDMPkCFj4MgzDMAzDMDkCFr4MwzAMwzBMjoCFL8MwDMMwDJMjYOHLMAzDMAzD5AhY+DIMwzAMwzA5Aha+DMMwDMMwTI6AhS/DMAzDMAyTI2DhyzAMwzAMw+QIWPgyDMMwDMMwOQIWvgzDMAzDMEyOwC2zO8AwDMM4jhAC/+2/gHU//I2z+y/I9xXqlUWn4S+iZouqUBTFads59+9F7PnzICJCIpG7YCBa9n4OJSoVRUYSFxOH8OBI+OTyhrevV4Zum2GY7IMi6FuNsUpYWBgCAgIQGhqKXLlyZXZ3GIZhoEvQYebQOfhn/k5o3TTQJejldNPfTV6ujw+WjoGHp3uatvPgxiNM7jYdl45dg9ZNa5wq5DYadqyD8YtGwjfA1+Y6gh+E4Pj2M4iLjkOBkvlQo3kVaDTqHzZeOHwZK2f+hb1//mvYTwWo17YWXnm7I2q3qp6m/WMYJufpNRa+dmDhyzBMVmPuuwvw59frYe3bW9EoaN23Gd77dUSqt0GC9c264+S/JmFtjkarQbk6pTFz52R4eHmkmB/yKBQ/jJmPXSv3Q2+2fL5iedB/Sk+82K+53T5sXbwbX/afBY1GSdIH2rZep8egz3qh5/iXU72PjG0uH7+GdT9sljcuungdSlUrjo5vvIj67WtBqzXdCDFM1oCFr5Ng4cswTFYi9HEYXi08VEZ9baIAi67MRsGS+VO1nTlj52P195ukwLTF2HlvoN2gF1L0cVSjD3D/+iOryw/54nX0eO8lq+u9cvI6htd5H0Jv+yfq0/UT0KB9bZttGMcgWfDrB0ux/Is1SZ4omG44qj1XCZ/8NR6+uXwyu6sM47Be48FtDMMwLsT2pXuh19sWowSlE1AqRGrzaTf+ss2u6KXI8prvN6WY/vP4JTZFLzFv/GLcunDH6vzV321UlRIx9bWvsWvFfrvtGPXQ0wQSvYR5pN10Pim3fEr3r6RAZhhXg4UvwzCMC/Hg+kNotfa/umls24Obj1K1DRKt0eExdttRNPbamZtJhHh4cIRMUbAnmknU0sA8i+sVAjuW77Mf1QZkPz/t+TXmjVtsty2j7qZnyad/2mxD5/bYllM4f+hyhvWLYZwFuzowDMO4EJ4+niojbQo8LeTeqiEthhBnD1xEQlyC3XYkno78fcLivPi4BDkYzhFWTF+LCvXK4PlXGjm0XEJ8AvatOYwNP23B7Qt34eHtjvrtakt3jGIViiCn8e/6o9K9wx402HHzL9tQqUG5DOkXwzgLjvgyDMO4EPXa1bI42Cw5FC2tn8rc1wIl88M3wH7+JqU6lK1ZMklKQnxsvOrtxMVYbuvu4QYPb8dEO+Wf/vH1eoeWCX4Yirfqj8enr87EyZ3/4dHtJ7hz6T7W/rAZAyuPkY/8cxoPrj+Sx1LN9XX/+sMM6RPDOBMWvgzDMC5ElcYVULJqMZvihOaRe0K9djVTtQ2yQeswpJVdAUSpDi+91S7JtCJlC6raBq27WEXLEVXyIG75WlM5sEotFEE+d+CiFLNqCA+JxDvNJuHamVuJyyeui24sBDDnnQXYtmQPctwTBTsDCk3niNoyjKvBwpdhGMaFIMExcfnb8Pb3sihMaZq7pzs+/uPdNFlO9Xj/JeQrmgcaK+KTtlO1aUW07NU0yfRS1UqgfJ3SMhpsCxKaHYe1tjr/5VHtrdq12SLSzmP6J/eC8e3wn9CjwCDcunDXbi7y/EnLVQ0mzC7UbVNDVSqNgGA3DcYlYeHLMAzjYpSoXAyzD32ORp3qJhWYikG4fH9gqqzilhYC8ubCN3s/QaUG5eV7ir66uWsNYlsBnuvaAJ9t/ADuHimLZAz8rJeMmFI7S9A6SBxT/61RunoJjFvwll0BnfymICCfdRsjejRP3sTkWJEQb3/gnFzm2kP8t+8CcgqFyxRE3TY1bUbb6Zx4+3mnuOlhGFeAfXztwD6+DMNkZR7ffYorx6/J6CgVGChQIp/Tt3H5xDXsNZYsDqKSxb2aolCpAjaXIVcGKj5BuaCmR+cmH9iK9ctK/10S1/a4ePQKPuv1Le5cumezHUWm67ethU/WjbfaZmTDCbh47GqSghpqeH/BW2jdpxlyCo/vPMHIhh/g6YOQFMeKiokoGo308a3XJnWpNAyTHnABCyfBwpdhGCZ1UL7t379ux78bjiImIgaFyxZCu8EvoE7r6g6VLSa/36E13pUODDKSbCXaO2PH/1D9+coW5184ckUOZEsNk1a+g+e6NUROglJCfpmwBDuW7U0SHaeS0wOnvobKjSpkav8YJjksfJ0EC1+GYZjM5+CGo/hftxky39Y8CkmP5PU6ISvItR3Y0ury8z9ajuVfrFbliGEOpXf8fncecuXxR04k7Em49OulyD0NRixarlBmd4lh0qTX2MeXYRiGyRR0Op2M4JInrD0adKiDeadnYt3szfhnwU5EhkZJV4HmrzZGl5HtULZmKZvLR4ZFyaiwI1BqRstez+VY0UvQvtdvVyuzu8EwToOFL8MwDJNhULoCWYStnb0Zl49dlbnJRSsUxktvtkWbgS3g7etldVmKNr75zQD5ItHsiGtF3iJ57Do4JBe9ZM027Ku+qpdhGCbrw6kOduBUB4ZhGOcQExWLjzp9jhM7zkhngES/WGMgtmSVYpi+7WME5gtw+rapOEXvksNVedS6e7rhxX4tMGhaL/gH+Tm9LwzDOB9OdWAYhmGyFN+P+Bmndv0n/04iQI1/3jx3B1Ne+Qozd01x+rbJk7h132bYsnCXVfFLYrxyw/KYumECfAN8nd4HVyY8OAKn95xDfEw8CpbKj/J1yzicOkJcPn5Nloe+ce62LJRSs0VVtB3UMl1udhjGEhzxtQNHfBmGYZxju9ar+BuqIq6zDk5Lsw+xJeJi4uQAucObjidaqxGmv6s3q4xP/xovPWqJBzceYf3cLTJCnRCXgFLVi6Pj0Nao1LB8qkSfqwreeeMWY+uiXYiPTUicXrxSEQz49DU0fbmB6mP/Rb9Z2L3ygByQaBpkSDcbWq0Go38canNwIsPYg10dnAQLX4ZhmLTz59frMfe9hXaFLw106/xmG5nHmx5QbvD+tUewdtYmXDh8WU4rW6sUXhrRVlqWmQbarZyxDvPGL5YC1ySQTYKtSZf6mLBkFDy9PbO96B3dZKL0UE6eH026n9QDCVZbFfhMfNLjK+xZddDm+f9oxVg8/0ojp/SdyXmEcaoDwzAMk1UIeRgqI3sJetsV04Rej+AHIenWDxoQR1Xn6GWNjT9vw0/vLzL0x8w42BSlPLDuML7sPxsf/T4W2RmK9FoSvYQpZPb9iHmo82J1mwVNyEN59x//2t0eHfOmXRs45PHMMI7CVxfDMAyT7vgG+ECvIs2BqoL5BfpmquvErx8utdmG9oMe2V89dQPZFarSR+kNdp0wFAUbf9pqs8mmeVtVWdY9uP4IJ3YYcsAZJr1g4cswDMOkOxTJU2MnRoUSnsvEx92HNh5H6KMwu+0o7WHjvK0IexqOu1fuy7SA7MSZveeT5PRag87pgfVHbbahgWx0Xu1B6RO3zt9JMu3KyetY/sUaLPzfCmz+bQeiwqNV9J5hrMOpDgzDMEy6U7R8YdRrVwtHt5xMUnktuZgsUq4QarWsisyCHu2bD3yzBqU9bF9q8COWKEDdNjXR493OqNWyGlyd2Og49W2jYm3Od/NQJzUofcLd2JZuJr7o+z3OHrgozwcNgiPxPGvkL+g5rgt6fdiVUyKYVOFSV83u3bvRqVMnFC5cWA44WLNmjc32O3fulO2Sv+7fv59hfWYYhmEMjFvwFoqULSSFTHI0bhpZJWzK2nGZ6pjg7umuynmCCA+JfPZGAMe2nML7raZgzaxNcHUKlc6vvtCHnTLGNZtXlcJVDdWeryTdNEY1+kCWSiboJkQXb6jyRyJ7wce/44cxv6laH8O4tPCNjIxEjRo1MHv2bIeWu3DhAu7du5f4yp9f3QeaYRiGcR4BeXPh+wNT8dqElxGQ91kZYG9/L3QZ0Q4/HpsuhXFmUuuFqlBtdpSsmSlKPHvUrziz7zxcmXK1S6NE5aJ2b0JonzsMaWWzTbvBLaGxI3xJQJOnb7EKRTBv3CKZY2wr6r521mY5aI5hsnWqQ7t27eTLUUjoBgYGpkufGIZhGPVQYYj+U3ri9Y9ewcObj+VAsfzF8sDDy8Oh9Ty8+UhGBEkclapWHCUqF3NK/2g91Z6rhP/2X3CoxHHylI1V32xA1SYV4aqQ4CWf3v91nW5TrJaqWgyNOte1ua7cBYPw1veD8e3wn6yuxyeXN0b/OARP7wdjz58H7R57OsZ//fg3Kvzypso9YhgXFL6ppWbNmoiNjUXVqlXxv//9D02aNLHaltrRy9wXjmEYhnEubu5uKFymoMPL3bl8D3PGLsDBDceSRGYrNyqPYTP6onKjCmnu29ifh2NUww8QGRaVKvFL+b/71hySDhG0n1mF4Ieh2LpwF26euw2tu5ss2EGDDqmCmiXIr/jtucMMgtXMz9iUA02id9rmiar2kbx+SdySRdrj208MJavp/AnIG40xc4bKPPB/1x9VOQhSj5M72QGCcZys84lMBwoVKoQ5c+agbt26Usz+/PPPaN68OQ4ePIjatWtbXGbatGmYPHlyhveVYRiGsc3N83cwusmHiAqLTpGOcP7gJbzT/GNM3fABareqnqbtFC1XCLMOTcP3b/2CI/+cSJHSoAYSb9ERMfAP8kNmo9frsfDjFVj+xWoZYTekHSiydLB/bj+MWzgSDdpb/k1sP6QV6rxYQ7YlURobFYfCZQvK6Y0711VlU2ai5WtN0axHIxzfdka6N9CgtxrNq6B4xSJJ+qp6v1IZkWdyNi5buY0ew6xevRpdunRxaLlmzZqhePHiWLTIYE6uJuJbrFgxrtzGMAyTybxZbxyunLhuVfBQFJE8gJff+clqFNNR7l17IK29aHBVgZL5MO7FT1QNfnNz12J95BKHhGF6QVHWFdPXWpwnB31rFEzb9GGabxicAbk59Cs30m47ijo37FQHk1e9nyH9YrI+XLnNCvXr18fevXutzvf09JQvhmEYJnXERMVi76qDuH3xrnRJoEFLlIqQFrcGKi986ehVm21IkIY/jcCeP/7FC72fgzOgimTmVckadaqLgxuOJlZxs5Z/2rxnkywheklIrphhWfQSpnSD70f+gl/PfpOpjhoEpb/UbFkVp3adtRnRpXmdh7fJ0L4x2QOXcnVwBidOnJApEAzDMIxzIRG16tsNeLXwEOnBaio8MKbpRAyt8Y4sRpBajm45ZdEGLTnURqYnpBPd3+0MnZ1H7KQlu43piKwAFdmw53dLNwy3L9yVke2swODPX5c3D9acIOgc121bE7VecH2/ZCbjcSnhGxERIYUrvYhr167Jv2/evCnfT5gwAX379k1s/80332Dt2rW4fPkyzpw5gzFjxmD79u0YMWJEpu0DwzBMdoCKCVw+fg1n9p6TDgvEkk//xI9vz5c5uLJNvC4xanfz3B0pgK+dTl2Z37iYOFVesCS+42LikV6QU8Pbc9+QkVESZ+ZQhJdEGeXMlq1VClmBS8euqsqFpWNL5zMrUKFuGTlozs+YHy0LWJgd78Zd6uHjP97lAhZMqnCpVIcjR46gRYsWie/Hjh0r/+3Xrx/mz58vPXpNIpiIi4vDO++8gzt37sDHxwfVq1fH1q1bk6yDYRiGUU98XDxWzvgLa77fiOAHoYnTKzUsj3P/XrS6HIkvEqQ0YGzmrikOb7dgqQIqy94qKFQqfb3a2w9+AWVqlMDq7zZi14r9SIjXyZSOlr2a4uVR7VGmRklkFVSnLggH2mYANZpVwbLbc2XKzKFNx+SguoIl86PtwBZOs65jciYuO7gtqyVLMwzDZHfiYuMxseM0nNh+JoWrAokmtT8nP//3NUpUKurQtqMjotG94BC75XGJ385/K62xMgJyIaA+efp4ZskI5PyPlmPZ56tVRX2/O/AZKjUolyH9YpjM0mtZ71PKMAzDZPrgtHtXH+DxnSdJxOzSqX/ixI6UopdwJIZy7oD1yLA1vP280fvDbnYf17d6/fl0E71USvefBTtl3ix5yJLoJbFLfcuKopdoP+QFuy4UdNxKVi2GivXLZli/GCazcKlUB4ZhGCb9uH3pnrS92rp4N+KNebJFyhWSj+9b92uGtbM3q7Lysgd5yaaGnuO7ICI4AitmrJP5niZnBdPfsuDCvDfgbCiH+dsRP+PQxmNJPH3J3mzIF33QrHsjZFXyF8+Hvv/rgQUf/25V9Gq1GoyZMyxLpTqkBrpRe3DjMTy83GU1v6xUPITJOnCqgx041YFhmJzA2QMXpEdtfGx8Uqsuhf5TUL5eaVw4dMUp20rrI/VrZ27irx//wandZyF0epSpVQqdh7+IKk0qOl28keh9q8EEhD4Ot5ouQNXNqKCDI0SFR8vqc6GPw5Arjz8atK8lyzmnB/Qz/8dXf2HB/1YgNjoWbm5aqd9p8GH+4nnlYLzqz1eGq0LlpRdPWYkjW04m3pgE5MuFl0a0xavvv+RwOWwme+s1Fr52YOHLMEx2h0RY75LDERUaleporBpIlJaoUhQ/nfzKZaKLEzt/jsObj0Nvx7d3yY05yFMoSNXgwN8+XIZ1P/yN2Oi4xNxoilJ2HPYiBn3e22nFNyyd553L98kKeORAQVXT6rapke5pGuQlvGHuFhz++4S8sSpeqai8UaBta7Vp8zreu/ogPnl1phS8yW9MKJpNLhzTNn8IT2/258/uhLHwdQ4sfBmGye78NecffDdiXqpK86qFdK6i0Uibqtou4r9KOb2vl37T7nEhv9nXJ3VHn0ndbbYjV4qPu06XKROWUkZIqNGx+XT9hGzzmH7VNxsw590FUuCbhCnZk9HfVZpUwKd/TZDV9lLD0/vBeL3Um0iI01nNMadz0+3tjhg6/ZnVKZM94cFtDMMwjCp2LN9LGQ1ORXqvapTEohM+uXzwv1XvuYzoJah6mJqbAYqSH9t6ym67LYt24+D6o1bzpGn60a2nsOmX7cgOUK74j2Pny/0yj8aa/j737yVM6vKFQwMjzdn083aZrmFreTo363/aIgdsMgyRPW4pGYZhmFQT9iRCVhtLKyRygwoEyKguPVKnwXLunm6o2byqLOHr5ZMxj5spshoTGQMvX680lQ2mx/JqUVM0g7yP6WbA1gBByqdeMX2NLDxx9sBFKeoq1iuLTsNfRMX6rmM1Ro4Xv3641HYbnR6nd5+TTiG1Wjp+Q7T7jwOqUnOiw2NwevdZ1Gtby+FtMNkPFr4MwzA5nNwFA3Hz3O00OTbQo+zA/AH4Yssk6dFb6tPiyGguHr0iH62bikpo3bV4rlsDWT44NaKRHC3UQDm+xSsVsetDfOWE/ZLNJHTvX3uEv3/bkRgZvXPxrrRRI2eNd+YNT5OYzyhO7PgPj249UXXsNv68NVXC11QhUFXb8BiH189kTzjVgWEYJofTuk+zNIneoIKBGDajL35JRWEKZ0HCkNwXdv6+T4pegh6D7/njX4xq9KH03nWUas9XQqHS9qvAkQtGh6GtbbaJj0twaNvmqQEml42tCw2pA67A/WsPVbWjfbtz8X6qtpGveB5VZayJvEVyp2obTPaDhS/DMEwOp1mPRshTOEhal6WGwdN6ywFEqR2klFYuHL6MGYN+kOI9iRWbUVhRFPXrN+bizL7zDq2X3A4Gf/667TZaDeq2qYkqjSvYbEfHxj+3H9IC7Qe5QTy++xRZHXKpUIunT+rsxtoOaKnqhq1gqfyo1NB10kSY9IWFL8MwTA6HfE5H/zg01a4OFTO5zO2fX6+Xo/dtQUUa/pz5l8Prfv6VRnj7pzfkI3nzbdB7onar6vhoxdsyT/Xn8Ysxe/SvWPXtBunPm1xEdxzWOnGwX1pSSv6ZvxNZnZotqqiKxlKb+u1qp/qGrUCJfHaPae+Jr2TZynpMxsM5vgzDMAyObTlliPg6IH5JcJDwoFLGFI0sW7MUXuzfHAF5Hbd+pOWpDPDFI4YiGeXrlpE+s/b8fskXd/ef/6aI9CaH5u9fexjRkTHw9vVyqG/tB7+ABh1qY9PP26R7Q1xMHIpVLIIOQ1rB08cTI+qNx+2L92TuLXVXp9Nj3vuLZBR8wNTXEr1qu4xsJx0bwp5YL4ZhDzoeVE46q5O3SB40fbkB9q09ZNsDWatB20EtU7UN8ub9YstHeO+FyXh82xAFNzk8mKr59f24B9oOaJHKvWCyI+zjawf28WWYnAsZ79Mgowc3H8HTywP129dGw451XGJwkaN0yz8QYY/DVbcngWf69ZARNyGkZiYh0/+T19Djvc6qi1SQmPx2+E+4e+VBYvSOhGHhMgUw6ochqNO6htVlKbL6Sv5Bqvu97NYcKcqcwfX/bmFUow9kIQqLQlYBOg5tbYimG7lx7jY+aDcVD28+llFIcj+gSLLawiE0YI8E98hZgy3Op590coPYsmCnTInwyeWNxp3rocnL9eHukT6FMWz57I5s+IHsR3LxKwt3QGDcgpFo9frzadpOZFiUjIKvn7sFD64/hLuXu/ycdn6zbZoqBDKuBRewcBIsfBkm50ERva+HzpU+pCYhRj/UZJNFubAf//letvtBbef1GhIcHIBli6Ff9kH3dzvbbUdV0SZ2+lwKtuT5mnTM6VH4J+vGo347y1ZUcbHx6OTbW51wVIB1oQvh7eetej9O7voPa2dtxtF/TsrocqHSBdHpjRdlZHvKKzNwfPsZu9Hb2Yc/R/k6ZRLf03r2rzmM7cv2IvhBKALy+aNUtRJY9tkqVX2avOZ9KWYt3QT8r+t0nNl7PjHiaSoWQc4dU9aOQ4V6ZZHR4nfuuwuxa8UB+fkxUapacQya1hsN2qcuzYFhksPC10mw8GWYnAV9JX788pf410qhARIS7h5u+O7AZyhdvQSyCz2LDMWTe8Gq2rq5axOdE6xB/r2/350H/yDrA7oS4hPQs+gwGWm29lNEwjdXHn8svz3XajWzyd2m48BfR2ymO5AQrPNiDUxd/wHUQP2Z+84C/PnNhkQRKftjjGLnKRKU+HjdFrRs677N8c7Pw+1ub0DF0TKNwZqQpshw7kJBWHz9hxSlfulmbVTjD3Ht9E2Ly9N16+ntgVmHPkfxirat19KD4Ieh+G/fecTHJqBIuYIoV7u0y5StZlwDrtzGMAyTCo5vO40D645YHS1OooKsqX6esATZidb9mqsaeEUFKuyJXoLKyG5dtNtmm31rDiP0UZjNylt0HqgN5edag3Jp1eT4vjK2E9Sy+ruNUvSalk3sD0WmhcCTu+puEmjZswcu2G1HIvDDZWOkG4Kl80DTtB5umPj72BSil9i+bJ/0CbYmmmk6ieMln/6BzCAof4DM+W3Rs4mMfrPoZTILFr4MwzBmrPvx78QR+9YgEUGP6B/ceITsAlUGc/d0tytIyMGBIr72IKF29dSNFNMjQyPx9/wdWPrZKqz7YbOqfGnKaz2955zV+VWbVsKI7wYa2iY7dyYROXR6X9VFEigSvWzaapttHPE9VtuWoqD0JIEG9SWn2nOV8O3eT63aptGxtOeiQCKcUg5ocB3D5FTY1YFhGMaMi0eu2o0eSgTkY2VyNcgO5C+WV+aATur8OeLjE5IMRjI96qeczPAn4Ti06biqdZrbf1F+568fLpNleykvl6KW5jmf9rB3Trq81Q4lqxTDypl/4dDGYwZ3CsVgN9b9nU7yX7VQ3m7Iw1A4Azp2jti9lapaHF9umSQHVpocLsrULIliFWynJ9w8q67yHh3zO5fvy/QRhsmJsPBlGIYxw54frDlqq0a5CrVfqIZ5p2dizfebZFQ2MjRKRlubvFQPL49qLyOre1YdhG7GOlUCq1IjQ3SSUgM+7/Mddq7Yn2iX5ojoJRFeorL9inA1W1SVLxrlHxEcCb9AH/gGOF5UQ20ag1rB3ml4G4eXK1ymoHypxRF/YHtPNBgmO8PCl2EYxoyqTSvi8Z0ndiOMJDTK1S6FrMT5Q5fwz4Jdsv/efl5o1KmuwzZWhUoXwPCv++ONmf0QHxufIv2hcee6Ms835KGN3FwF8PH3RvNXG8u3NFBw5+/7U71fbp5uaPX6c6rb++byka/U4uOv3ufX5DxhKbeW5r3Q+zlUrJ/+TgpVn6sknSfsOUzQeVFzE8Ew2RUWvgzDMGZQdG7bkj12RW+TLvWRu2AQsgLhwRGY0v0rnNh+RubMUjSV+rh96V4pUsfMGYrzhy5LARobFSvFbfshrdD4pXpWnRJItFFFt+TQ+t/55U181PlzKFAsi18B6V3r5eMp366dtSnRVis1UBGC1ERu7UF9P7X7LK6duinFK5W1pYFXlBZBXrDxMfE2l6dj1GVUe+z58188vv1ERsdp300D4Chv+s2vB2TIQK6XRrTFYTspKHQO2g1+QRZ+YJicCtuZ2YHtzBgmZ0FfiTOHzsHmX7dbrGJG4oGiieTNSgIysyFP2Lefm4RLx65ajjpqFJn7afqXMInQklWL4fO/P0KeQo4L+IMbj+GbYXPx+M5TwwA1qlgWr0Ng/gC89f0gNOveKLFtR9/essiDI1Af6VyQ6O09sZtTxGNESCT+WbATe1cfxKNbT6SHLt0IyJQVo2ClAWaj5wyVhUvWz/3Hat4sLUP2YMtuzYW3vxcObzqBI3+fkPtJ18WL/ZqpKpRB+c57Vx3EoU3HEBsVJ3PG2wxoIXN9HcGUTrJj2d7EwiLmaNw0KFgyP77/9zPkys35vUz2g318nQQLX4bJeeh0Ovz24TJpZ0VijnIi6auS0h/K1iqFD5aOtjvYKKPYvnQPpr3+XaqWpf2i0rs/HPkiVVW96Dgd2XxCRpNlyeJapWTFrKjwaPz96w5s+mWbzJel9448svcL8JEli9sNaum0KmtH/jkp/X5JXNr62ZO2YW4aKTwvHr1qtQ29Pv1rvM2qcvagaPOUV76ShSek0KcqblrDQEJ6ojBu0UiHyitTpH/+R8ux6tsNiQMIqTIc7W/DDnXwzi/DEZgvINX9ZZisDAtfJ8HCl2FyLmFPw7Fz+X5ZBtXTxxP129dCxfpZq2LbmKYTce7fi6pL3lqC/GObv9rEKf25fOIaxr/4CcKeRjhk+UWQTdqK+z/bLHqRGi4evYLRTSZKYehonyxBEW66+Xn+lWdRbWvQT6ylaDVF6Ec3+VDeWFk6d1TOuNYLVfHZpg/l345Ag/soikzReMrpbdipDgqVyvynEwyTFfQa5/gyDMNYgR4Jd37T8RH5Gcm1MzfTJHopwrhh3lanCF+KXI5r/YlMKXBUYFKUtXnPJk4XvcSiKStlaoczRC9BAvqrQT+iXJ3SFgUliX9yxtj9xwHERMQgV95caNO/hbyWTPZ3P49fLCO71s4dRWqPbjmFI3+fTFGumdZPZYlJNJeoUgy1W1VLIo4pFYe2Zy6+qYjGrQt3ZU53tecqIn/x7GHDxzCOwsKXYRjGhXHExsoSJAjvXLrvlL5s+mW7HGjnqMCU5XR9PNF74itwNk/vB+Pg+mM20xtSQ1RENBZNXon357+VZPqGn7bg2+HzoNEqic4gVHnuj5l/Ye3szfhk3TgULJUfx7aeVnVcqKCKSfhSQZCZQ+bgwuHLBjcJhQSyQP7ieTFsRl+LEeiDG45i7nuLcOv8ncRptGyDDrVlLnZ28aFmGLWwmR/DMIwLQxW90urL6uljcG8IfhiKP79ejx/G/IZfJiyR1dIcEYybft7qkOg1iXYaEDd928coWq4QnM39aw+dLnolAnIgGaXDmDi27TS+Gf5TYj64pZLBH3X6HCd3/KdqE7TMlRPX5N9XTl6XqRGUIiE3L0RitPjhzcf4pMdMbFm4K0X+98TOn+P2hbtJuy6ELEIyov543L/+MJUHgGFcE474MgzDuDBkY3Vg3ZFUL0/is0H7Wvjh7d+wbvZmKaa00lEBWP7FGun5OvH3sbIqmj0op1QtlRuVR4GS+dCkSwM06WLdVi2tuHmk389cQrwON8/dQdUmFeX75Z+vlikH1mzb6KYgPi7BUFlOJaYUhq8G/YC4mHiblnBfD5sr83kpXYTKEs8Y9KPBrcKCPQmtJ/xphHTmIGcPhskpcMSXYRjGhSHP2db9mkk7sdRAuaT3rj7Emu82ySgliTMSdKbKapQXSgPobl+6Z3ddXg44EIz6YQg+WDJG2p6ll+glSlYtDv8g53sAmzANXKOUiuPbTtv1Kqb5x3eQ37L9n19qU6N5FTk479Kxa3bXnRCXgH/m75R/kx1bQnyC3b5QHvGdy/bPLcNkF1j4MgzDuDAkvN75eTh6jnsZHl7uUgCT64CpnLKXr6fF0somo4Guozpg/9rDVtMBSBxFR8Tgl/GL7fal6cv1VQm6vEXzSA/hjMDD0x0d33gxzbnQlnD3dEusgkaewGqhcsqUj0veumrKHZ/adVZlKW2B03vOyr+ObjmpOu2ECp8wTE6BhS/DMIyLQ36tgz7rJa3A3vn5TfSZ1B3DpvfF/IvfyQIL7Qe3kpXIzClaoTA+WjEWTx8E2xWrJH73rT2Mx3dtpzK89FY76OxEJUlwdx3dQfbZGVCO7bof/sa8cYvlYDMa+JWc1z7oijI1SjpV/NK6Xuj9PPwCDdFk3wD1JZJpIN/gL16XriG2jj25QFRqUE5G4BPvVGxA9y7xcYZIPaVFqIFuiuJjbUeGGSY7wTm+DMMw2QSysWo74JmNlQkqWTz4895ysBpVKiNXgQr1yspo8dx3F6YYiGUJih5eOX4NeQvnttqmdPUSGPHtQMwe9auMUCa36iLt1rBjXXQd3R7pUWRELwQWTl4hbcY+WDomcbAcFYGYseN/cl+3LNyZROhRlFytSDQXvbny+KPv/3okTiN3hFLViuP6f7dsRlqpn5Tekb9YXnx3YCq+7DdLWpNJUU4uDQl62YZSNPxy++HcwYsoVrGwqnLPtFzxiobCKkXLF5YWZvbOLfW1cNmCDu0/w7gyXMDCDlzAgmGY7EyvEsPx6NZjVW2pUlmDDnXstjvw1xEs+fTPJNHXPIWD8PKoDnhlbEdDieO0lpUe8iM2/7bDcllpNw38AnxlWWkq02sO2a0d23JKVpPLWyQ3arasiqE13sWdi3ctlvq1BFWom7TynRQlq6kc8vQBs20vrACzD32O8nXKJE66dvoGln+xFvvWHJI3JskJyOeP+JgEVRXwfjv/rRS95w9dwsiGH9htT+dlyY0fnRaBZ5jMggtYMAzDMHapUK8Mnt57ajcySNHhUtVLqFpno0515YsGxD258xTe/l4oU7Ok08TVf/svYPOvO6zOp6hpZGgkfp6wBBOXvZ1kHjkeNOvROMk0Sr34bsQ8u9t9vnsjvDK2EyrWN0TLk9O6bzMZoV0/Z4tMITCP/FJEl6K2o2YNTiJ6iRtnb0vrMWuEPnpmmWaLpl0bSNFLUESfykcf2nhcDmC0xsCpvVj0MjkKFr4MwzA5GMojpfK2tiDRRkUU8hXNg5O7/sPf83dIf1wqh0sR4Bd6Pyf/NkG5wJt/2Y7/9p+XYq909ZJyvkmUWYvi0ktNeV6yXaPH+rbEOs3b88cBBH8zAEEFAm2ur/2QF3DknxM4sPaI1UF+L73VVqZxWBK8JmjeqNlDUKlBeaz8ah2un7mVOK/685XRc3wX1GldI8kysdGx+OaNn2z2L/k2LPWRpu9fdxg7f98nq/DR+w+WjcGnr86U4tf8eNH5pHW8MaMfXuzXXPW2GSY7wKkOduBUB4ZhsjP0EzCl+1fyMbul3FQSSZQHO+3vifhl/BKZj2oSUVKEQcDbz1s++q/7Yg1ZoYwGmlHegCnH1xTtJPE4/Ov+iRFG2jalRaydtQknd52FPkGHgqULoPPwNmg3qCV8A3xTpCmQSJ/z7gJEhdp/7E/Q9iiiaw+yb1s2bTVWf7dReuCaoHSIV8d1kX7JtkRvcmjfqDhEZEgUggoGIk+hIIvttizaJfN8VUGbt/OLTceaUjzK1iyV2I//9p3H+rlbcP3MTbh5uqP2C9XQcVhrLlvM5Ei9xsLXDix8GYbJ7sTFxuP7ET9L71d6RG8SeCQGqcjEh8vGyAFr1rxkaRkqetH17Y5Y8eVa6xsyOjoMn9lfDk6bMeAHbF28O1EYm9ooUJC/RF58tWOyHDQWHxcvxfT6Of/IAhD2xF9yBwXKe6VotRpoW6f3nEdEcISMFFduXD5dUwG+G/EzNv68VQ7QcwZ0U9Ky13MpSikzTHYnjIWvc2DhyzBMTuHhzUf4Z8EuPLj+UArG+u1ro26bGtjzx7/4tOfXNpc1WYXZcx8gUb34+g8yFWLRJyutilgScIXLFsLck9Px6atf20xDsNevHu92xqBpvZEV+Xb4T9j0y/bEgiHOwM1di78iFqdrYRCGyWrw4DaGYRjGIejR9+sfvZJi+l9z/k4albWAGrstU3SYIrdrZm2yGbmlVIpb5+9g/sTl2L/msLodsNKvDfO2ZlnhW6ZmKRn9dibk+0sOEOQTzDBMUriABcMwDGOTG2fvqBa2dhFCDpCLDo+x25TENrk3pLXwRPjTCMTFxCEr0rJXU3h6eTh1neSh7O2nvnw0w+QkWPgyDMMwNtG6OzHHVVGQEKdTNVCMxDYNNEur6CYh6OaRNR9wktvFkC/72G9Iuc+KYvcmgFJEGnWuB3ePpJX6GIYxwMKXYRiGsQm5ANgra6wWErFU4UxVvq56EwWrUL/rtqulyiYtsyDHiDe/GWA1J5fuESgqPODTnnZvAihFpOsY+y4WDJNTyZq3wAzDMEyW8vrdsnCXzTYUiaRCFdFh0SlKFZugiKWXryf6TOqOrYt22S+VLCCtwEIehKZqYBtB23h5pPoSybQdco5w93BzyL7Mdh90OLjhGI5vP42EuAQUKVcIrfo8j8B8AYltXh7VXhbAWDt7M/as+hf3rjyQTg+0/+S1235IK2mJlpCgw8KPV1jd1tDpfaRnsDkJ8Qk4f/ASIkOjkLtQkKw856x9YxhXg10d7MCuDgzDuBrREdGICo+BX6APPL09nbLOn95biJVf/WU1qkoD40b9MBgfd/lSDq5KHpk06CwFE39/G5UalseACqMQG20975aEmX9uP7w24WX89N4ix4Wv0fO2+zudMHR6X7vNLx69Ij18d604gPjYeOlq0er15/Hy6PYoUakoUsup3WfxWa9v8ORucGLKCB0b2r+WvZ/D6B+HwEvlOaJBcAMqjMa9qw+stqlQvyy+2z9VRrhJcC//Yo3cr9BHYYltipYvhF4fdkPrPs3sbpMGyR3fdhoRIZHIXTAQtV6oxm4RjEvrtaz77McCu3fvRqdOnVC4cGH5pbFmzRq7y+zcuRO1a9eGp6cnypYti/nz52dIXxmGYTKao1tOYkK7qegc0Bc9iwzFSwF98elrX+PC4ctpXjfloQ6b0Rd+Qb6J7gzyX0VBw4518e3+qaj7Yk3M3P0JShtLG9M8U7uCpQpgytpxeP6VRtITWPrx2oCE7ju/DkeHoa1QtEJhq6kWFGl293SHfx6/JNMLlSqAt396Q1X+7Maft+Gt+hOwY9leKXqJ2KhYbP51G4bVeBd7V9uubGeNs/9exLgXP0Hw/RD5niK49KJCISR+ty7cha65B2D+R8tlBTd7fDPsJ5uil7hw6DKWf75Git7J3WZgwaTfk4he4s6le7JoxqLJK62uhwYDzhk7Hz0KDcH/uk7HjIE/4IP2n6Fn0WHyBohjZoyr4lIR302bNmHfvn2oU6cOunbtitWrV6NLly5W21+7dg1Vq1bFG2+8gcGDB2Pbtm0YM2YMNmzYgDZt2qjaJkd8GYZxBajq2K8fLk1hO0aCkVIPxi0YKUsLO6PYBT22f3TzsUxbqNu2JvIXy5ui3YUjV3DuwEXo9Yac3potqkoh/Oj2E/QuMdyucCLB3PvDbug3+VU8vR+MiZ0+x6WjV6F100pRp9Eq0OuSroNSCBp2qIPmPRujQr2yqh7nn95zDmObT7JuraZAFrCYc3w6SlYpBkcYUX88Lh+7ajX1w3wblRtVwJdbPrIaoafj1cG3N+JjDMLcFgF5/dF74iv48e35do/z17unoGrTSinO8YS2n8pjY6maH9HxjRcxavZgTplgsgzZvoAFfdjsCd9x48ZJkXvmzJnEaT179kRISAg2b96sajssfBmGyeoc3HBUCkNbkCD+8eiXidHYzGLbkj34vM93qtpSSgQ9tifop4rSBrYt3oOrp27I1ASSXOaiksQyCTXKn33vtxGqBrR91PlzHNp8HHob+cZ089B2QEuMmTsMarl84hqG135fdXs6P93GdLCalnHp2FW8WXec6vXlL54XD289tumVTPvVtFtDTFz2dpLpK6avxc8TllgVvSambvgA9dvVUt0nhklPsmWqg6McOHAArVq1SjKNIr003RqxsbHy4Jm/GIZhsjK/T19r1+aKAnNrvt+IzMZeioM55t67FOyo0awK+n/yKq6evmFIF0gmzExCbeui3Vj9rf19pbzVgxuP2RS9pgFyWxbvdujxPkWnHYGi9Ot/2oKYKMspD6GPwx1a38ObtkWvab/+XXck6TSdThYXsSd66XqTRUgYxsXI1sL3/v37KFCgQJJp9J7EbHR0tMVlpk2bJu8YTK9ixRx7tMUwDJORBD8Iwend51TZXG1fujfTczOLliuoqh1FI4tXLJJi+prvN6t63P/HzL/sVkQjj2B7As9EXHQcYiLtF91IC1TU47995y3OK1I26W+Zs6C0BvNr4t7Vh3h064nd5eh6O771VKZfTwzjKNla+KaGCRMmyDC56XXr1q3M7hLjJETCVejDPoP+SS/on/SGPnw6RAKfX8a1CXsaobotuSiQtVVmUqVJRRQuU8CuRy8J9eY9mySZRiJr1bfrVW3n8Z2ncqCXLXwDfKAWcmQgpwe1lK9bBqkhOsKyuC5UuiDyFA5StY7SNUqqzr2ldZq3jXegwh3lWrPwZVyNbC18CxYsiAcPko6ApfeU++Ht7W1xGXJ/oPnmL8a1EUIPfdinEI/bAlGLgPgjQPxhIPJXiMetoA//lr+8GZclVx5/1W09vT0y3YqKRNbgL/rYfQxPTH5lhhy0Z/p8UjQ0Nkq9MAsPjrQ5PyBvLlR7rpKqamj129fCxSNXcO30DbuRZKJMjZJygJ2j5ZbzFc1jdd7Aqa+pWsfIWYPQoGNtu9uminYdhrROuv1ieeUAQlV9LZY3SxcGYRhLZOsrtlGjRtLJwZwtW7bI6UzOQUR8BUQtNL4z/8GivwUQORuInJdJvWOYtBGUPwDVm1VWJd7I1SErjMJ/rmsDvPJOJ7vtKPeWnCpI/BKbftnu0HYC89kPXFA/1KSJHFh7BCMbfoChNd6VrhTLP1+N+DjbKRdvfT9QHnc1x5yakG2brUjxi/1aoPu7nW2uZ+TswajapCJ6fdAtscyxJeh68QvyQ4dhSYWvX6AvmvVoZLdSHw0k7DRcnTsSw2QlXEr4RkRE4MSJE/Jlsiujv2/evJmYptC377MRsWRjdvXqVbz//vs4f/48fvjhB6xYsQJvv510BCuTfRG6RzKya7ddxCwIvfpHxgyTlejx3kt2xRvRZWQ7m/MpskqDq8iCzJzI0Eis+X4ThtV6F93yDcTrpd+UBS3uXrmf6j6f2nVWdVvyue1ecBC2L93jUCS8XJ3Sdts17lwPvSd2k38nv3lI9Co2/muCilH8OnEZJnacZlP8VqxfDl9umYQ8ReynKFBQu+/HPeyK5KFf9sHMnZNRsUE5GbE1pWHUebE6fj4zE52NYrRSg3L46PexUsAm2S+jGPYP8sMXWz6SN07J6Tn+ZRn1Tb7fJmh9VMyi/ZAX7O4Xw2Q1XMrOjIpRtGjRIsX0fv36ycIU/fv3x/Xr12U782VI6J49exZFixbFRx99JNuphe3MXBsR8RNExEyKHdlpqUDJNRmKT88M6hnDOJffv1yLn8cvhoZ8e81cCkj40Lf8+EWj0CJZzqyJO5fvYc13m/D3gh1ygBUt06hzPXQd3UEWrBjXegpCHoZB0BMS4y+GSUy9++ubqiqAmUPpAhQ5TU/I0oy8i9Wyb80hrPxqHf7bdyFxGglEWz+RJAx7TeiK/p/Y/t6g1Ih/5u/EnLELZCU0c+hYU0R5yBevyxsYZ0OWZhvnbcXO3/cjKsxQspis2Vr3fR6+AYZiJJY4ufM/fPTSF4iJiEk87yS0yUmjQIl8+Pyfj1C0XCGn95dhUku29/HNKFj4ujb60AlANFX4s5eT5wb49IEm14QM6hnDOJ/j209j1TcbpEUXuRVQJLD5q43RbUxHlKtd2mq1NxI4NFApuWAmQebl6yVtxaxFlEkcUuSwVstqqvu5589/MaX7V0hPFl2djYIl86fKJYNygzf/sg1/frPBbiSdUgN+v/sTPLw8VJWS3rp4Dzb8tAX3rz+UyzTuVBed3mwjc4KzGhTp37JwN3at3C+PSd7CQXixX3Pp/evh6Z7Z3WOYVOk1LrjNZHPoy1llTqPCHwfGtSHxSS8qfxsVHgO/QB+4e1gXKA9uPMKkLl8iIS4hha0XiV7CnoUXRT2XTl3lkPAlQZ5eUFSyfofaqRK9RFCBQPk6uPG4qvQR8gI+s+8Car9gf/+9/bzR6Y0X5csVoIgwpcfYS5FhGFfCpXJ8GcZRFI/6ANTYNyVA8eBBj0z2gMreUu6mLdFL/PXj3xZFryOQODyx4wwe3nykepnKjcqrdg5wBErzoEf5o38YkuZ1UVqAWqKTpS8wDJN14RAXk73xehEICwJEiMHBwSIaQFsI8GicwZ1jmMzln4W7VEU11fDw1hPkL54v8T1l0Z07eEnml948dwfunm6o3ao62g9+QUZUyTlgx/J9aRLd5lBqxnOvNMSwGf2Qt3DuNK8vb5HcchCbmmxAtf66DMNkPix8mWyNongAgTMggocaB7gJCw893KAEfAVF4QcgTM4i/IljZXBt4eX7rLhDdGQMpr72DQ6uP5qYK0yc3nMOi6aslBHZodP74tTuc3hy92mqxS9FeOu2roF2g19AlcYVpKB2Fm0HtsT5w7YLYFAWVeEyBaVfL8MwrgH/0jPZHsXzOShB8wE3Cz9ObpWg5F4CxaN2ZnSNYTIVn1yWC/k4CkU8S1UrLv+mCCmJ3sObjsv3JtEr5+kFdPE6zBwyB2f3X8D3/36G+u1T/9mjwXjkw9v05QZOFb1Ey15NkadQkG1/ZAG8PvGVDPFGJmcISie5d+2BXf9ghmGswxFfJkegeDYAPNYD8SeBhHOGUI17NSjuVTK7awyTabTo2RTr5/6TRJw6Cg1u6zKyPbRaQ87u2QMXZaTX9kLAvHGLseDS9/h03XjpcHDkn5O4dPQqIoIjUaBkXmxfuhdP74dYjQaTIKXSxzVbVFXdVxLl/+2/gK2Ldkv3BipZ3LRrAzToUDux/+YD0b7YMgnvvTAZIQ9Dk/TDFMXu+78eaN3XMSs3RyH7s9XfbsTaHzYj+H6I8YbFR6aMdH+3E3IX5DQLhnEEtjOzA9uZMQyTXbl5/g6GVBurKs/Xkqctid46rWvgk3XjEkshTx8wG9uW7FYlpj9YOlqKb0vcOHsLo5tOlL7CyftHotfbzwtf756CUtVKQA3BD0PxcZcvce7fi4nC1eR5XKBkPnz61wSUrFIsxXLhwRHY/Mt2rJ+7RXrieni5o1Gnuug8oi0qNyyfpC1FZKkd5S5HhkQisECgtP9qN6ilLI/sKLTtd5p9LI8F+ecmPwaB+QPwzZ5PUKh0AYfXzTDZDfbxdRIsfBmGyc5QNbTP+34vbcDMxaqpWMFLb7VF9ecrY8mnf+LqqRuJ8wPy5UKXt9qh5/guiaKXeKvhBFw4ZCc31oxX338JAz/rBY1GY7GwBpUs3rvqUKL4JcHXpEt9uYzaAgqUczyywQTcvnjXoiCndVL098ejX8riDKmBCmB82vNr2U9zoU43B5RS8tnGD1MIZXuQ1dzBDUet3piQgC9avjDmnZ6ZJUpRM0xmwsLXSbDwZTIKIfRA3D4g/pRhIJ5bJcCzORT2F2bSmbP/XsSKL9di/7rDiY/0acBWt7c7ygIYpmjv9f9u4fGdp/Dx90aFemWSCF4TY5tNkoPYHOH1j15Bv8mvWp1PaQlXThpEd+nqxWUVuW2Ld8sorm8uHzTt1kCKc2vib+3szZg16hfrxi7GgXLtB72A0T/SQFjHuHDkCkY3/lDm4VraBt1EePl54eczXyNf0Tyq1nnv6gP0LfeWzT6boJQMNT7CDJOdYeHrJFj4MhmBiN0HEfohoL9LcRxj0Y0EQJMXSq5JULzaZnYXmRwAFWMIeRQG31zeqR4sRq4Ni6esTPFo3hbk6UvVz+ylA9Cj/6mvfY2j/5yS0U4pChWKVOvk4LrJq9+3+Nh/UJUxuHX+jizdbAtKY/jj0a/w9vWCI1AVun1rDyWpfGcpqtzj3c4YNK23qnWunLFOlqC2dxxpve0GvYAxcxwX7AyTE/UauzowTCYjYvdCBA8C9PeMU3TPim7oH0OEjIKIXp+ZXWRyCFR+l9IH0uKQ0H5IKylGHUGv1+OfBbtstqFqdO+3noLj287I95SyoNPppeglbp67jTFNJ+LJveAU67514a5d0UvExcTjwXX1hThMNwuU5mBL9Mp+6PTY+PM21eslkU9pEvag9SbfZ4ZhrMPCl2EyESF0EKHjjf7C1n6ZFYiwjyAEV4disj5kATZy1mCHl7t8/JrN+eTEQG2s5buSEKZoNaVsmEPpD47kv9q0L7MAOU+oLQIS9iQcCfFqKklCDlxT67YRfJ+FL8OohYUvw2QmsbsA/UMbopcQgIgEOOrLuAgdh7XGh8vGqPYJprziHcv34p8FO622WTNrExSZAmQdEqCbftkmo8MmSPRSiWQ1gjZXHn9pkaaW0Mdh2LLIdqTaHErPUFuquV67WqrXe+8qfYcwDKMGFr4Mk4mI+GMq7bS1EPGGggAM4wo0f7UJxi0cpbo9iV+yQtu7+mCKeZSucOPsbVXlg6MjYvDgxuMk014a0dZuVJaEMQl2SwP2LLFl4S70LDIUv3+xRrXobdixrvroswPDbyiSzEUtGEYdLHwZJlNxYGypMOQyMoyr0KBDLeQtmke6GqhCAX56f1FKv2AHc4aTN3/ulYZo2KmO1ZxZEr3FKhRGj/dfUrV+Eudf9p+FhHid6nLLlLbQZWQ7qMXDy0N1Wzq+aiPJDJPTYeHLMJmI4ka+nmpy/vRQ3CtkQI8YxnlQNbTxC0eqz5sVwL0rD3Bq99kUwrdsrVKqBnvRAL0CJfOn6Mekle+g85tt4OaulesjoSjXp0CK4pm7p0hrNLtdFAI/vbfIYLzigAjvPbGbQ1Xm8hfPa3CosLMdOrY1W1a16IPMMExK+JPCMJmJVxtA8VPRUAt4v5wBHWIY51KjeRVM3/axtApTy+0LZOuXlJdHtrcbXSUR2GFoK3h4ptyWu4c73vpuEH6/Ow+jfxwihegbX/XDoiuzMXnV+8iV219V30iUk8eu2oc1xSoWwbiFI9F/Sk84AolzihDb09eUwvHyqA4OrZthcjLsjM8wmYiieAH+4yHCJtpu5zcSiiYow/rFMM6katNKKF+vLM6oLGyhtZBn2+K1Jvh7/g6c3n1O5vymWMZNg/zF89lNV6ABbB2GtkZquXU+pSi3BnkLzz0xI9VV1ShCfWjTcRzbesqq6Ceh36BD7VStn2FyIhzxZZjMxqsj4E1Vq0w5eorxo0kvLRS/0YDvG5ncSYZJG7VbVlP3OF4Bqj9fKcVkGnT2yV/jpQAmIUl5rZS2YEqjqPpcJXyz9xPVkdvUQttUi1+Qb5pKCct9XjcOr773Erz9vVLYnQ39so+sNMflihlGPVy5zQ5cuY1JL4SIg4j4FohaAogosznugFspwLMDFJ/uULR5kV0QVI45drf0JFa0RQGv9lA0AZndLSYDeHz3KXqXGG7TXYFELJXenbbZ9hOQh7ceY8eyfdK/1jfQF891a4iSVYohI7hz+R76l7fvVkH78vrEV9Dn4+5O2W5MVCxObD8jC2YEFQiQKSRqHSgYJicQxiWLnQMLXyY9ECIeIngoELffurODVzcoAZ9li2iOSLgGETIWSPjPrCQzuVS4A74DoPiNgaLwqPTszl8//o3vRvxsVSjSwLRZB6dZLDuclRj34hSc2PGfTRFPA+eW3PgR+YrkQWYQFxuP/WsO4fqZW7IvlRtXQJ3W1XkQHJNtYeHrJFj4MumBiFwIET7Vrp2ZEjgLiteLcGVEwi2IJ90AEW4UuxbwfhWagE8yumtMJrB96R7MG78Ej28/kTd1pp+g2q2qycf2hcsURFaHor4jG36AyNAom+KX8om7vd0BnYa3gX+QmkGszoE8hn8cOx/hTyOgpdQMQXZqOuQvkQ/v/fqmQ+4SDOMqsPB1Eix8GWdDHznxuDWgu2VH+GoBj7rQ5F4EV0YfPAqI3WJd9BpRcv8OxUN9tSrGddHpdDi+7QxuX7wrHRiqN6+CouUKwZUg8fvNsJ9wYscZu23zFcuDr3d/ggIl8qV7vzbO24qvh821OI8iv5Qb/fnfH7H4ZbIdLHydBAtfxtkI3T2IR81UtlagFDgHRXHNx5NC9wji0XPSh9g2WjnITxM4PYN6xjCGdID/9p2XkdvchYJQsX5Zh1MBVn71F356b6HddsUrF8W8U1+la6oB5f/2KDwE8THWq7iR+CUBvuDS95z2wORIvcaZ8QyT0YhYRxobC1yor+KUpYg/o0L0Ejog/mgGdIhxJSguc2rXWZkbfOHwFSnaqjatKFMHKjUol+r1JsQnYOnUVVjz/UaEB0cmTi9YKj96fdAVbQe2VJVbT7Zqq7/boGqbN8/extF/TqJe2/R7qvHPgp1IiLVdEIds0e5feygHytVuVT3d+sIwWRUWvgyT0WjyG4VsnIq2eaEoLip6HS7JrEYgMzkpGjut97fYu+qg9Oilkr/Ew5uPZA4r+deOnD1YVmVzBMp1/bjLlzi8+USK0sj3rz/EzCFzZIGKgVN72V0XeQo/uvVE3YYVYNvSPekqfM8dvCQrxdl7jkvH8+yBiyx8mRwJP+dgGHv5uORIEH8aQnffKetUND6AVycz315raKD4vAaXRpZkVuNKoQXcq2RAhxhX4ds3fsK+NYfk3ybRa/73hnlbMf+j3x1e79pZm3F48/EUoldinLRs2mqc3EkOJLa5c9mB7wQBBN8PQXoi9HqVt5qK3Sp4DJNdYeHLMNYEb9RyiMdtDK8n3SAePQ/9k9chYvelef2K3xBj1NfaR1ALUKU2b/tRp6yM4lYU8GiiQuTroPi49r4yzoMirv8s3GlbnAngj5l/ITw4QvV6KTVh1XcbVEVE18zaZHd9jpRhJnLlTd9xIqWqllB1m0lR71LVi6drXxgmq8LCl2GSIYQeIpTKCE8CdDeSzow/AhE8UIritKC4lYaS+zdA8TVGRJWkH0lKcci9CIo2czxAnYni/54xq8ra140G8GwBeDTK4J4xWRUqTaxm4JUuXicLWajl7pUHeHD9kf31JuhxcOMxu+1qtqii7oGGkWbd0/cabzuopeq2hVzANo5h0gMWvgyTnOgVQMxq45vkoSF6zCogwj6GiD+fps0oHrWh5NsFJdckwL0O4FYO8GgIJeBLKPm2QnEri+yA4l4JSu6FgMYk4rWJ5ZglXh2gBH7rss4VjPN5cMO+ODVFZu9fe6B6vbFR6geWJsTGW06HMCNvkTxo0qW+KvGbt0huNOpUF+lJnkJBKF/X/vcGDRJc893GdO0Lw2RVeHAbwyRPcYj81RiBtfWjp4GIWgIljUUXFI0f4NMbik9vZFbZZMQdJrNdQBMIeNRPl8F00p83304gdjtE7C6Ds4W2MBTvblDcSjp9e4xr4+nlocpVgT6vnj6eqtebr2geKfrU5LfmKZJbVR/e+n4Qzh+8jCd3n1pt4+3nJcswa93StzohpXJcP3vTbjva/21LduOt7wfC01v98UsL107fwPq5W3Dp2DVotAqqNK6Ijm+0RqFSWbtKH5P9YOHLMOborhte9hsCMZsAF602JoQOiJwHEfkbIIKfzVACAN+BgO9Qp5cQVhR3wKsNFK82Tl0vk/2o27amHLymJiUhPjZelhAOfxqJPIWD0KpPMzTpUg9u7m4WK6k17lwPB/46YrfccMeh6iom5i2cG7MPf45ZI3/GvtWHk0SJSTg36FAbo34YIkV3ehMVFo2YCHVR7fjYBIQ+Dkf+YukrfCmf+LsR87Bx3rYk7hzn/r2EFTPWou+kHnh90ivZojQ74xpwAQs7cAGLnIWIPwXx5BWVrd2gKXgWroY+/joQ8gagu2q9EaUfBHzF6QeMXZ7eD0Z0RAwC8wfAN5eP08RS75LDEfwg1KpApQpkhF4vEksfU14wRT0LlS6Az/+eaLH88YUjVzC68YfQ63QWB7lptBr4B/li3pmvEZQ/wOFjcWrnWTx9GIr8xfOiXtuaMnqdkRZwHRwYEPvno1/lzUB6MmvUL1g3e7PNAYXDZvTFK2PJ6YZh0l+v8a8aw6Tw2FXb1vUGnomYHcCTdrZFLxGzAYhZl1HdYlwMEpnbluzB8Drv49XCQ9G//Ch0zTMAn7z6lRSWaYVSAiatfEdGbUmIJoemkeA1xW1M/5LoNXn9vtPifwh7Gp5i2Qp1y+B/q96Du6d7ongmZMBRAQLy+mP6to8dFr1E7oJBaN6zCbqOao+mXepnqOglqPwzlSK2dMzMof0uX6d0uoteOg/rZv9t10Vj4f9WIDoyJl37wjAmWPgyGYqIvwQRsw0idi+EPsL569c9kYPORMJtuwNTLKFoCwLu9VR8NDSAt9rIcNZAJFyGCHnLkKZhFw1E5AKDw0XCDYj4cxB66zmMTM6BPlffvDEXn/f5DldOPksLosjsvtWHMKrxB9jz579p3k7lRhXw7f5PUatl1RRpCJTSQHmi1j7i9Didcm7p8bolGnasg0VXZ6PPxz1QskoxOfCsfN0yGDV7COZf/B6lqpWAq/LyqPY20zgIuml4eXSHdO/L5l93yPNlD3pisHvlAdVWd/PeX4S+Zd9C94KD8Wbd92Vlv6jwaCf0mMkJcKqDHTjVwTmI2D0Q4V8DCVTC1oQX4NMVit87UDRpizyIuEMQEXOBuL3PBqW5lYfiMwDw7upQ/pjsa/AgGy00gOINJe9mKFrXGZihD51kcKxQVULYiKYIoL9jfKMAni9A8R0GxaNGenWTyeLQAKVvh/9kvYECuLlp8eu5b2XKgTMgsXP11A0pooqUK4Q3ar6LhHj7N3D5S+TFkms/IidBP+mzR/2KtbM3W23Tum8zvPfbiHTPq/2s9zfYteKAXSHu5q7FK+90xqDPbKdpbFm0CzMG/iD/Nq1TVqozOlp8ufVjFK9YxIl7wLgSnOrAZBlE9FqI4MFAQvJ82Bgg6neIpz0h9GGpX3/UKoinfYC4/UmdGBIuQYRNgAib6FD0V/F8DkquyUZnB61l0Rv0s0uJXjmYLZos2hwsC6y/a74WIHaH4XzF2B94xGQ/6HO0csZa2/ZdwhBRpCicsyABTbZhNDCNwrxqRC/x8MZj6HTq2mYXSMyO+G4gRs0eLPOMzaFI+Rtf9cO7v76ZIYPJ3DzcDCkkKq4rdw/bY+2PbTuN6f1nS8FrLqTlVztVxXsQivdbTUZkaKQzus5kY9jVgUlXhO4BROgEoyC1JD51QMJViPAvoQR8mrrUibAPjOtO/gNn3F70SsC9GuDTU/V6Zalg95oQUYuBmM2krg05vd7dofi8akiJcCWo/4hNzYLJ3tMxViBCRgP5trnecWDSxPUzN2URCHuQMNm2dA+GTu+bLmJKLZTrqqYQRnrw8NZjbJi7BduX7UVkSKQc/Pdiv+ayyERgPsfzhx2BRG2n4W3QYVhrnD90GWGPw+Gf2w8VG5SFVpu+lmrm1GpRDVsW7LLbjlJTaiZLaUnO4ikrQWNt6R7e2jX39F4I/p6/E10zII2DcV044sukKyLqdxVRRopGroHQh6Zi/UvMqp5ZQ5HevI5m9VDhBU3AVGgKHIWm4Dlo8u+Fxn+0a4o9xcuJH3fDTYbh3DI5ifBg9dG04PuhuHXBlCbjPAqWyo+8KqzBSPTWaF4lU2yyyC6tf/mRWP7FGty/9lAet1sX7uLXicvQr9xI/Lf/Qob0g0R/5YblZU5zlcYVMlT0Es16NIJfkK/Nc0DnqVjFwqj2XCWrbe5ff4jTe85Br7P9HS4gsFGFDR6Ts2Hhy6QvsdtVPl6nQgoHHV9/DFUfsvcoUxj9ee04GWRjpIculQVOkbqRWvTGY8/kJChqqRa60RzT9CPVVdjUQuKty1vt7A6aoghgl5HtkNFcPn4Nk7vNQHxcQorcViocQQO5JrT7FPeuPcDhzcexaPJKLPj4d+xbc0jauGUnPLw8MH7RKHmuLJ0vEr2U4iDb2BDHD28+VrdB4UBbJsfCqQ5M+iIcGGlL1bwcXr8D+VxOdJGQDge6h4DiC2iLuoT5uuLTHyLW8ij3VCFSn5fNuCbFKhRG6eolcO3MTVXVzyjfctHkFXj31xFO7cfLo9rh3/VHcHb/BZlPbIkX+zdP9xLBllj+5RqDArNyeOi4xUTGYliNd6UINsfd0w2vTeiKPpO6I7vQoH1t6an8w5jfcP3MrSTzKjYoh5GzBqFszVI21+FIdT5H2jI5E3Z1sAO7OqQN/dMhQNweVVFfJfcyKB51HFv/w+cAvf2cQ7n+vNuhuBVFWhBxxyEi5wCxO5/lv2pLQfEl94geWb7gg4iYAxEx0/iwx8I5casOJJxSsSYaul8Rmrxr06ObTBZmx/J9+KzXNw7l5K64Nw/+QX5O7UdMVKy0tdr063bEx8QnTvcL9MUr73TCaxNezvD8XrLU6pqnf2J1stTSqFMdTF4zziVuqNVCUoPyja8Z3TlI9JaqWlzVsgnxCXit2BsIeWg7HY4qw7Ud0BJj5g5zUq+Z7KjXOOLLpCuKT3eIOHuDGxRAWwxwr+34Bry7ASREbQprDeBeI+2iN3ojROhYY06x2f2i7jpE2CRDqkYWr3am+L0BuJWFiPwJiD/xbIZbZSi+gyE82wNP2gC6m1YGI5qti449k+No0bMJbl+4i4WTyRrPPglxCbh57o7MMXUmXj6eGDlrMAZOfQ2HN59AZGgUggoEom6bGvIRe2YQ/CAkzaKXOPDXUayZtQkvj2yP7AKJ+EoNysmXo1Ahk5dGtJXXnK0nDXTsO73JJdEZ22TdX2gme+DZEnCrYCe3VEDxG5Oq6IZCTg2Kp51LWQ/F9w2H152khwk3IULfNQpsK+4RlPMatSBN27HbDxEv0yyEIykkyVC8WkGTZwWUfDuh5FkFJe82aPKugeLdUUbIFL837YheLaAEAt4vp7oPjGvT5+Pu8PJN3SNlZz9k9A3wRfNXm6DD0NZo/FK9TBO9hJcvDSJ1Dov+tyLHWbHZ4tVxLxkGK1rIFTb9dpBVW5kaJTOhd4wrwcKXSVcUxQ1K0K+AWxkLlxyJYQWK/wQpulK1fm1BKEHzjOI3ubg2vFf8P4DiRQO7Uo+IWmY3AirHFEfON3jmpkPVNX3oRxAPakM8bAjxoAb0T/sbShDbWk7EQcRsl/0X0X9B6IMT5ynawlDcq0JxK5ZkGYUEra8pJ9OSj7E/lNy/pbnoCOPaVG5U3m5pXFPeqqevB+a+uxDd8g9EG7ceeCmwL74ZNhfXTt9AdiJ3wUCZA62mWpk9yAniv30Z4/7gCrh7uGPqhg/Q64Ou8A/yTTKvRJWi+GjFWHR7O3W/I0zOwuVyfGfPno3p06fj/v37qFGjBr7//nvUr1/fYtv58+djwIABSaZ5enoiJkZ9TXDO8XUOJMAQs8UgIHU3DELVs4X0y1XcSqd9/bq7BmuzqD8AQeLOC/B6EYpPH6dUGdM/bAbo76lqK6Oo7rY9KR3BUEluuDHSbC6qSZTqAN/BUPzeSxIxlx/rqF9lTi+EeV6cG+D1EpRcH0LR2M65FHGHISIXyaIV0nVDk196GMO7JxRtUmP89EDoowD9EwrrQ9Hat69iMpb9aw/j45e/tJtzWbNFVZzacw66eF0SlwOaRwPT3v3lTelvm134e/6OxOpiaeWDpWNkagmTlLjYeJw/eEkODsxXNA9KVSuerfKhmdSRLXN8f//9d4wdOxZz5sxBgwYN8M0336BNmza4cOEC8ufPb3EZ2nmab4I/HJmDongA3h2geKePsbiMXvq/B/i/ByH0zs+zFQ44QujDnbdZ3T2IYEo9iLdSTIKGzv8MuJVLTD0g0SvCPgWiF1lYYwIQsxqCqujlXgpFkzRyYo7iUU++TOvMqM+OiL8IETkPiNlg6C9Nc6sExbcf4NUlS+dQ5yQadKyN+u1r4cjmExadFTRuGvjk8sHJ3Wehi9OlSHEw5cKSSCxcpgCqNrXu4+pKkIg/seMMti7aneZ1+fg7L3UiO+Hh6Y7qz1fO7G4wLopL/YLMnDkTQ4YMkVHcypUrSwHs4+ODX3/91eoy9GNdsGDBxFeBAq5TZpZJHekijKhqm1q0+Zy2WRG13IroNUeBiJj3TFjEHbIiek3ogYQLBncKlWSY6I3dC/GkKxCzPlH0Sqi/oeMhQsfJGxsm8yE/3Y//eBet+jST1welPbi5a6F1M6THlKxSDPXb1YLQ6W3m9VJawO/Ts487CB2L934bgeFf90e+Ykm/N4qUK5R4fOxBOdQ1WjjvyRHDMC4W8Y2Li8PRo0cxYQKVvzVAA3FatWqFAwcOWF0uIiICJUqUgF6vR+3atfHZZ5+hSpUqVtvHxsbKl3nonGHIwUBEfG3HPYIsvsoDWlM+sxOIJk9QvYoCHZcB3RWDY0PUomdpEFbRA1HLIfxGGqLxWQChe2Qjum08BjFrAffKANnHMZkODSQjkddvcg9sW7IXj24/gbefF5p0qSftqroE9rPrckDpDwfXH0N4cITTLc8yC/ptorK5VEDj0rFrCH8agaACATL/d9W3GzBnrJ1BsArQ6Y0XpXMFwzA5VPg+fvxYjnBNHrGl9+fPn7e4TIUKFWQ0uHr16jLnY8aMGWjcuDH+++8/FC1q2dpq2rRpmDx5crrsA+PC+HQHyAJMFsyw9kMuoPgOd250VISob2sauBa3X0U1O1p3KJBwCXC3fiOYoUSTPVac3UGEVH4aPn2hKBlbfpWxTv7i+aRvrjlxMXEpCjRYgyLCoY/Cso3wNRfAFeomvRHuNqYj7ly6j79+/NvyQgpQrWkl9P+kZ8Z0kmFyGC6V6uAojRo1Qt++fVGzZk00a9YMq1atQr58+TB37lyry1BEmUSy6XXrVtJKM+mJSLgOEb0GInoVRPyZDNsuYx9Fk9vgTqH4WPjYGN0j/N6G4u1k301FfYlYaTFGCLMUAXvQoMMsArlOqCpvTQVL4tUU2WAyEypcoXVXf3Pik8sbOYVRswfjiy0fyXQQcwILBGDAJ6/h838+ylRbNobJzrhMxDdv3rwyp+zBg6RVuug95e6qwd3dHbVq1cLly5ettiHXB3plJGRVJcI+AeKSpmzIAT1kxeXZIEP7w1hGukPk3WjIu43+3eA4AHKneAGKbx+Hq86pwrszEPmLnQguFQApKdMcJG4lgISLKuzXNIbCIVmFJO4TdtA7EAlnMi3a2fTl+ti76qDNdAeNRkH5umWQu2AQchK1X6iOeadnyqIXD28+hoe3B4pXLKI6B5hhmGwe8fXw8ECdOnWwbdu2xGmUt0vvKbKrBkqVOH36NAoVKoSsghzB/qSHYUBScmhAT3A/CFkeN+sh3QP0URD6iFSb0pPnLXnR6oPfgv7xS9A/6QUR+UsSv9msBPkGa/zHQJP/AJQC56EpeBqaoG/SR/TKAh29Ev2OrUMpFkMTUywMy9g7H1pZXCQjbMlUo8mtvi3bm7kEL4/qYD/HVy/wythOyKlQtbkK9crK8r0sehkm/XEZ4UuQldm8efOwYMECnDt3DsOHD0dkZGSiVy+lNZgPfpsyZQr++ecfXL16FceOHcPrr7+OGzduYPDgwcgqiND36RmvlYge/WAIiJB3IIR67+H0hvoiIhdCPG4D8bAmxMPaEI9bGgWrfdsvoQ+VUVN92DSIR80hQoYBsduAhHNA/BGI8C8hHj4PEbMVWZmMsNWSNm2B3xsfzlgoJkH49AW8uz6b7PWSIQJstVoeLaeF4vcWshKycIZNgS9bAdqigBuPds/qPLz1GIc3H0exioUNE5KdWlORh65jOuD57uqCFwzDMDkm1YF49dVX8ejRI0yaNEkWsKDc3c2bNycOeLt586Z8vGYiODhY2p9R26CgIBkx3r9/v7RCywoIylMkP1XbrQARDkRvBHzMxE0mIfThEE/7AwnJcpB1d6RgRfSfQO7FMic2xbIiASJ8BiBdB2jkfpIVmLeUg5xEyFtA7kWJXrKugCy6EPMXRPRKQHcXUHwNhTSo6EOyCmlqkVXn8qw2DOqK+evZsXOvY/C29WydZECdovEBci+ECB5kGLyW6PBgbKN4QwmcDYXcEbIS3t2AiB9VDCCk6LZL3bPnKOjpz+Ipf2DRlJVS3CYWrUj2EKJ0teLo/u5LaNmrKfurMwyTYbhc5baMJj0rt4mIHyEivlMxAl8LeLWHJvArZDb64BFA7HYbfdYC7rWhybMkZVpE6FggZqOKx/AmNIB7XWjyLIYrIAcn0k2B/q5RZJr2k4SngBIwzRjVTMM2RKwhv1XxtV95jUonx+6SgyWlCNf4Q/FqA3h1trtsZiHijkMEDwTkEw4LVep8+htKXLNQyrIs/3w1fvlgqc023d/phKHT+2ZYnxiGyf6EqdRrHDbJRISgyJ2aH3A9hYeR2YiEm0DsVjtCXQfEH4aI/y/pZMpTlpW4HLnP0gPxhwzbzeLIPOen/QyOA4YpZnPpeOkNBRhi96VpO4riCUVbQJVwJbsvxaslNEGzoMm7CprcC2T+b1YVvYTiUQtK3vWATz+yyTBNBTwaQgmcy6I3ixMREomFU1babbdm1ibZlmEYJqNh4ZuJKDT63rw6lVU0gFtxZDpSuKoRHVqIaKq89QwRRRHgVA7c0N1AlocKTejv23VfEBGUr8vYhFIxKFWGHCc0hQH3mlC82gGeDVn0ZnG2L92LhFj732kJcTpsXZz2kr4MwzCOwsI3M/F60ZADahcdFO/uyGwMTgsqLxn906Tv44+qK6pgEXdkdYQsvqAmgn3MJSLYmYWI3Q3xsDlExFeGwY6UNhJ/AiJsIsSjVtL6j8m63Dh7C1o3+98R1Obm2dsZ0ieGYRhzWPhmIgpFtvxG2msFeHU1RoczF0UToDJVQQFkW3NUFCawiDfgXg1ZHt0d9Wkcsq1lZC503GGIqD8hotdB6CiKnDMQ8WchgodTXkyyY2n8W/8U4mkfiOQ3VUyWgey41HwKqA1bdzEMkxmw8M1sfAYAviOMb8x/CIx/e7WHEjAFWQKvtiqjtglQvDokneRWPhWXmxbw6QZFoyYqnskoXg60tVyhSsT8DfG4NcTT3hBhEyBC35V2bzSgML0EsBTaukcQursQmVzFjQZ7miz8LKMzlGWO+j2De8aopdrzlaGLt/8dQW2qPV8pQ/rEMAxjDgvfTIZyFjX+o6Hk/cfgx0r+pG6VAK+XoeT5A5rAr6EoWaN0peJWBvB4zk6uLrk6VDe8zJf16e1g1FcLaEtA8RsDl8CzlbocZiorbMFGTEStgAgZCeiSl8jWSxcN8eQVp4pfErkGL+bWEI+aGPyUH9aHPuxTKYLTt+hJhKHwiZmhjCCnitgtKm6s9IbKeUyWpHHnuggqEJDo0WvtOy8wfwAav+Q6NoUMw2Qf2M4sE+3MXBF6zCyevg4kXLUgZKkEbiEouZfJCmcphNaT14y+xfbEjRvg1QFKronG9Iqsj4i/APGks510Bw3gO1ze6CRZVvdACk/bx4UqrbWAJugH5xQgCR5iVi3QvM9a6aagkH+ye8U0bytxm1TYJPp3iMhFRrs32lRJKD59AJ8eQMI14/FTgyKr5vFAt6zJ0S0n8WGHz2RFNqFP+nkgQUzn7dO/xqNe21qJ0yPDorBl4S78/dsOPL7zFD7+Xnj+lUboMKw1CpbMnwl7wTBMdtVrLHztwMLXioiJWgQRtRjQPzJMVIIAssry7QdFE2hluVCIkFFA3AFjdFRvfOige7Y8RZU9G1ssgJGVMfgUjwNi1tjwJK4DJfdvKSL4ImKWfNmPiGug5NuZ4qbCUfShk4HoZTa2p5Xlg5V8O5zytEHonsj0DeiuJRPZRuHqVg3INRl4qtbj2AOagskKqDBZihM7zuDbN+fh9oW70BijvySEi5YvhFE/DEGtls/y9q//dwvvt56C4AchhgnGS0Sj1UiRPG7hSLTo2SRT9oNhGNeBha+TYOFrp0CC/rHhl0qTF4qirhCgiD8NQfZfugeGQgxerWQ0U+3yWVL0hn0ESGcH88IVZshc7S+kD29y9E96SOcCNSgBM6B4d059X+nm4yGJCPv5vErATMCjPkTUMiD6D8NNDuUne74IxbcPFHd1ZYP1T3oB8cdtRLQ1gOcLAHk/m6LBGRD5ZtL/c3F6zzlcOkpPh4CytUuh+vOVk0Tqw56GY1DltxH2JPxZhbdkUJR4xvb/yWUZhmHSqtdcU2kwWQIqkABtAceXc68mX66E0IcZBlZR9bPk0ejopUbRK1taXkHMNsA/xPLxcmRQWVoHoFEhERWil8SoiFoKhE2iBORn0WEqJxyzDiJmNeD/oaFksq3uxp8G4o/Y2RblMW8FfIcBkXPtpIvooPi8rqL/TGZDApfEqi3Buunn7Qh9HJYiJSL5epZ8+geq/zMpnXrKMExOgge3MaoQQg+heygHWBkqzuUMyFpMHzwM4mE9w0Cwhw2hf9ITIuafZ8clYp6KNcWbieNkuJVWXdxDaAtJqzP9k1egf1Af+odNoQ/9UFqBqUIfqr5aYPyxpKI3EUPkVoRPhYjZbru/spCJmn1TDM4YHk1s989nEBTPxirWx7gCG+dttSl6CYoEH9t6Go/vPMmwfjEMk31h4ZvFMfi6noA+/Fvow7+UFdDocXXGbT8aIvJniEctIB41hXj0PMTDRtCHT5e5m9kZEfWHYSBfLFWYMvtxpoIKIW9BH05FFtQ8nif0ENFrLc5RvF9VMeCPvJELA2FTpNUZKJIqQgD9QyB6FcSTLhARKh7/y2i1Si9mKXht5R1rICLJgswGsuiJGjSAPgRK0BxD5DexXLFpdiEouSZD8X9f5foYV+CRA2L24a3s/X3DMEzGwKkOWRiqUiVCxgIJ541RMwWCBFLYZxC+A6D4vW1IN0iv7ZPt1NM+RicGM7EkwoDIXw1CLvdSKFmhnHJ6FFMI+9C438lFqVEMRs6FcKQMs7UbFo/6gEdDIO6wDQFM/dADOlPVN5EyAhvxDaDJD8XnFet98CT3CPIcjrHTWaEyKnxSVqKzeg3IgY7qIsyKJkgOplP8x0L4jTC4TujDAW0+wL12ul7rTObg6eWB+Bh1T5C8fVPmxzMMwzgKR3yzKCLhBsSTnkDCJTNxk2AUJPFA5E8QYR+nbx9CPzSUjbUogmhg2xMISgMQqa3KlnUhj1v7Hw8NEEPesyrRBFmcLAf75JpqtbCFxOMFQH/fbmRYRHxv83woGj/A93U7YtRwk6Uaijpb255XO+N1a3clxgIpxuUUTyiez0Hxbg/Fox6L3mxKo851VZU4zlskN4pXLpohfWIYJnvDwjeLIsK/NAwksiV0olfINIh02b7uHhC72c6jbh2gu2K0J3PitkUCROxeiKiVENEbIFQ/LnciMRtVFVOA7pIhBcGuUNRA8bZs1yUrpoWMMObTWkIB4rar+7jq7xkjx9ahJwXkjGDqV/J+ynQIxQH/5ORpCea41zTYldkreuLxPBS3Uuq3yWQLXhrRFroE2zfOdGPYZWR7aLV888MwTNph4ZsFoYIGiN2mQnhpZc5vuiAHb6mJ+mkhpEh0Uj5z1FJDHnHwQJlqIELflvZb+pAJEPTYO6Ns2uymApjh3c1+4QoauOXd3fLsmA3GdBZrAkA8S3VQA4lfGyiKOxAwC8j1BeBmNuKeBK/vm1Dy/gV4d1QxKE0BtEWM5aitbUuBEjQbkN7Dlr5uNHJwnxI43d5eMdmQCvXKYtC03s+efCSDptV5sQa6vZ2sBDrDMEwq4RzfrIgcoa9G5OiA+KPp0gVZQlYKFXv90MtBSU7ZJuWoWhwslSALQ4iE00Du5YbH9WrXGX9KlgOWlebk4/MmgHdXmwUy6LG6oCimiFC3Ee+eFKIHouYbxaL5DQu994AS9BMUbV7LfZQ3L2qOtUpspEyI2H8hohYCsbsMKTOa/LKaHLy6yjzdRPHh09tgZ2YTAcVnABTF9v2zLLiRZ5UhfYTWKYwRfJmP3Bvw6ePQOWWyFz3HdUHBkvmw+JM/cOPs7cTpufL4o8vIdnhtwstwc+efKoZhnAN/m2RBhFrBZWicLn2ggUZyIJ1djI/G0wgJVMui14QOoMF+EbOg5Bpvf336KIjQsUDs9iRiVMTtB8K/BgKmQvHuYn0FNI8KN9grI+xRDxq3fBD+E+QANSkqaRsmAerdDYpPPyhuJayvxmL559TiYRgoZymaHvGVzA1PIs4pP5e8c2lfcy8A3CsZuk4V9HJ9ZnCQMFXXS8RYpMOrI6DSU1cOXPMfbRi0JouekEtFPruimckZNH+1CZr1aIwrJ6/jyd1g+Ph7o2KDsnD3cM/srjEMk81g4ZsV0xzIJksVWsC9Svp0hAYahX+mYnS/Lk2VxEyIyMUWoqXJ0cuIofAfA4VSB5KXUaYIpkLVWjQQIWOAuN2JfTRrKdvJ8sKKPxSvFyxuiYokiKjl1iuxmdbr8zr0Eb8B0csByoumEr8kCEnwejRUOSjLWbmLWsD7ZSgaC/m5VHlNil5jv5Ogl04dIngAkHdrYvRV8ekKaAtDRM55JublZopD8R0gI92OCldZnS+NJZeZ7Ak9bShbs5R8MQzDpBcsfLMQMioX/Cagf6ByCapiZciPczaKNj+E10tAzFob0Ugt4FYBcK+b9g3G7VGR00zEQET+BsVvuCEXl6qIRS4wWq5Rx/0BKqWrYsAduWKIuFP0i2sov+vZPLFsskJFJQK/hwgZacHSzCjQ3RsBIaOTzhMxQMwmIGY94DcaoAinPShCS5XLVO2/NShXtiwU/3Ep95OKbMhoui0RTykrwYbzbXZNKZ4N5YuKl8josOILaEtazMdkGIZhmKwOP2fMSsQfByiPVZUAUgDPVhYfazsLJeB/0j81cXtJ0MhoIBUccIoIcqQaXOQv0FMqQ8hIQ+RWDgwzrSdcpcuEMAi5qJ8M1nAhbxoG1cWQADVA0WAl7zpAFpgw5c26AR7PAcgDxB+wcq5MvrrfQkSvttsTQwnetIheD4DSKXIvs5wrS2kkOsqdtJ8WQ1XhLPZRm1/eHJDzAotehmEYxlVh4ZuFEBQlVBuEd6sMJfBrQHddPpIXkYsMFmDSkcA5KIo3lNzzoeSaAmjLPptBg5L8xkDJs9owcMkZaG3kwCaHCmiQ4JXOF0hjfqzJH5lW8wQiZAREzN+JcxW3stAE/A9KgRNQ8p8A6KW7DuCpinUrEBGzZSTfJlTAwvu1NKQ3vApNrgnWB4jJnFqovxlgGIZhmGwKpzpkJaRfrV51bq8IHgLE/WucZnyMrSkI+L8PRdpRpR2qpAWfnlB8esryxSBhrfg6Peqn+PQyDqRSg5tR9Dp7YB+tT4EI/Uj63Mp9N/WP9lfxAWL+hpDCV+X6qNIaRVw9ahj8eqn8se6uwd7MsykUiprLAhYfG/yKpXeyYyhU2cxmA38HVkY50gzDMAyTPWHhm5WQ5V1VWohFrzMM5krEKAL19w1uBiIcik9qo4jWI8COFPRyCO8OQPhUlRZidHzSq1qcAESIwcfYws2DiJjr+Bp194HIk9KRQq478RwrEJ4tDRF1isrGkneyo+gAWR3NxvZlxTgq9xqrosiGuhsmcs2Qgh5xgLYYF59gGIZhXAJOdchCKF7tVZZ3JZEbZzMvVIRNgdA9gqsgXRp8Bqlsnd4lkt0g4lNWxBOR84GEM46vLvZviPBPjaLXvP8CiN0J8aQHRMQ8x8oES7QACWcrVmmUYqEPnwE86ahC9NK23a0X2TCtUx8BfdhUiEeNIIL7QgQPhnjcBvonr0qPYIZhGIbJyrDwzSLIMr26YEAJtCOAFJXiT8iSxq6E4tvHMFDLdivHHt2nmqTHVyRchQif5vhqZHoE5W5bQ2eotBarpkRykhUDbuWgBHxhvQk5OSRamNmCXCq0UAK/s5k2QZXzxNOeQNRigNJezIk/CRHcH4IcLRiGYRgmi8LCNwsg4v+DeNQSCH3LMHDLau4qmf6rHUymh1DlbpB1UDS5LNpxmbUw/JPrfzark6WdBChk02aGkMUsHP24kPNFcRU+vQ6mbij5oFAet6xiF2BFpIZBRPygbn3aMlDyrIDi1cJmMxH+hSwiYlmgU/8FRMi7EDq1g+kYhmEYJmNh4ZvJyEji09fNRtNbEUCawlLswHegAyundAi4XNRXSSJs3Z6loiu5ZFRS493JWDHMkdQABXBvoCKibKy4RkUozInd4bjlGPkb6+hGxnlOG5K866D4DoKi8bHeRkaZVZ5/iji72S6EIvShQPQaOwLd6HccvRKZ5oMdfxYiZruhNLOwl97BMAzD5DR4cFsmI8K/MxQ9sBfx83sPik8HgH7QVa2ZikuUg6shnSM8XwQ820GJ3QIhPXo1UNxrAl4vJjotkJ2aoOijFKS2CjMQGplyoAR+DpAoCv/EZh9kNFXjm6xjdI7UogF8hxuKbDx6wQHzCRUDG90bQKPNY3dNIkGt84TR+zjhP0PhD2tI9xA1QlovvZBp3zMSEbMZIuJ7IOHSs4mKP4TPa1D8RkJRPDOmHyIBSLhoSAUhxw5toQzZLsMwDKMOFr6ZiNA/lQOf7EcENUD0UoCEL3m+aosCujt2xB5VdaPCC66BiN0vK7IZygzTfrlBeLWVpXEV92op2iuKOxA4G4heBRG10CA2UrYy/uMHJegXKNoigMwj1kOEf2kcSKgYXyQ43WSqhcVqeJSyIP1wVaQk5P4dGo8ahv1yKwvEPVKZyqCiDVVOUwMdHwcQcUcN1eusNoh2YGVRyEho0KGQ5bWVlII+8meIuGNA7t/SVfxKq7rIXyCiFiXxTRYejaH4jYDiUS/dts0wDMOoh4VvZpJwReVjcH1idTJF0QD+44yldK2hATxfgOJeHa4AORqIiOnGXFiTmE+QpX9FzEYgYDoUSm8wtdeHA9GrIaL/AMgqjAaQefeWDgdIuADEbDB4ImvyQPF+CfB+GYrm2YA4xbcfQNOj10DEG1wapOiT7VLmzNLjc3U2c1Q2uEqi6JXr9XkNIm4fnEbcdoiEm1DcKHfYOopHA4hIcopQiXSx6Gd9vrawA3nNRZFRiPiLZoMOLd0I6oH4YxARc6D4j06fPog46W6BuIMp+xB3EOLpv0DAV1DIso9hGIbJVFj4Zir2Bj1ZTsdWvNoAuaZBhE0yRi2F2fp0spSxEjgDroCI3WUUvbBwE2As/Rv6nsHBwL2iQegE95dV1oxrMNiERS8HopdBCZgGJa+KMsHkmezb326WsIj4ESLia5XnSqQUVyTG3WtI1wPnoIWI/h2K/3u2m3k0NdiTJfF6tkHMFoi4k1DMRHuKfGVNYUB/186K9FB8bFuiORMRtcT42bB1A6kHopZA+A1PUpTEaX2ImA3EHbIivHXGoijvAR61OfWBYRgmk+HBbZmJW3ljYQF7aAGPOkmmKD7doOTfA8VvLODR2CBMvF+BkudPaIJmGXxxXQAR8bOqy1CEfQJ9wjWI4H7GCncimdAggaGHCB0v0yacgT7qT6PoNa3fGiSftdJaTPF8PukcxQ3I9alT+pPYj3hD9N8W8smAZ1sH1ktRy35ysKW19Sn+o1TklZc3iP2MInaruqcmdHMkI/fORQ6gI3s3u4P+9BBRvzt9+wzDMIxjsPDNRBSNn3y8bj+aqLOYd6pockPxGwZN7vnQ5FkKTcAnFvNhsypC9wSIP6iuUl38YeBxW2Ok17YIVWPjJR0ARIz8N+U8PfQkyMM+VLEXdO/SCkq+HVC8u1jpkZqiJM5/UqD420qHsYCIlRFuq+vz7grF7x0LfTB+jWhLGnKpSexnFI4MOnQkT1ktlD9MucR20QMxjpejZhiGYZwLpzpkMjTiXMTuBPSPrAg6BfDqYHx0nc1IrGSmegEVbUgkH4LQ3TEMZku+BkqVoMFwsuQziSYPCK92UCjtwb2KFL0i+E2ZS6sOjaE8tLagnVLUzkIDxaO2qpaKW0kIzxeMzhdqBtfpZH600E9MzHWW7hAk7ki8UzTXdygUz+YQUUtl1TlDyeISUHx6ytLJGeWekAidY8rrVnNtWLge0oyITJ+2DMMwTOYL340bN2LVqlXInTs3Bg4ciIoVKybOCw4ORrdu3bB9u1rBwBCyUlaeFdL4nwSbIXpmyll0A3z6QPF/F4riaDlbF0BWqUsnaNBbMqEjojdChJoilqabjDjpeSti1kFQNJO8anVUpEEtekBnO++VBLhwqwoknHVCuWXFblnhJK0DvoB42s9gV6aKBOkYIvSPIcImG23MzNCWhZLrA2gCJiMrQM4lVJ7bNhrAvabdAYGpwtYNTxIUB9oyDMMwmZ7qsHTpUnTu3Bn379/HgQMHUKtWLSxZQgNLDMTFxWHXrl3p1c9sDUULNXkWQ8mzAYrf24DvEFnEQcm/D5pc4zP20XEGopAfrXv99Mm4SVbZTcSfM4penZVBdAKImOGg6DVty09Fk6F2RK8hT9gwIM368VD8PzAcN0eq4eVZ5tBASmkP9rg7EHc45UzdFelgIGLIhi8L4PWSsZqhrf0T8slKukCFP7SlVBRTEVC8X0mfPjAMwzCqUa04pk+fjpkzZ2L9+vXYs2cPFixYgGHDhuGXX35RvzXGJop7OUPOrv/b0gZLOg9kcxS/wU6IgiZDkx9IXnI4coFzt/FsY1C8XrTbSvFqC/iOML5LLtLovQZK4NdQci+VubLPppuq1gVAyfWZrGznKHKgo0cj9R/3GKrQFmEl9cYwqFCEjoPQU5vMz5NXci8ENAVMU8zmGp6eKAGfQ/Fskj7bVxSjqLaVaqE1iHOvZ5Z8DMMwTOagOpR46dIldOr07Iu7R48eyJcvn4wCx8fH4+WXaZAWwzgG5YvC710Iiraa7NjStkYolB6iaJNW04r5y/mlg01RWpWpBxr/0RAeNWREFXEm5wk3mcNtKNRR2TAp7yYg/ggQd8SYW1vW4MucBisuOiYibi+cA1nIRQEx6wCfXshsFLcSQL5NQPR6iOgVhtQT8namSn/er0FxS19fYcW7oyE9JOKrZNewUYSTn3Tu+bZLTDMMwzBZS/jmypULDx48QKlS9FjPQIsWLWQEuGPHjrh9+3Z69ZHJ7lA0NPYgEJ9WYaYYBgH6DrRQSUyln62D2yO/ZJmnrXYJz+aGwWH6SMNgJ01AigFhMp+bKn3ZqfYlXTGi/4Qw5u8qlEdMNnea3Ckb0w2GV2eDWHUKCkTsv1CygPAlFEpt8emeoR7CSbbvNwzwbAwRuQSI3SYdMmTJYhr0R24YmlyZ0i+GYRgmlcK3fv362LRpExo2bJhkerNmzfDXX39J8cswjiLi/4N42sdoNaXGtYHQGEr3mttIkbWbTx+D60Dycr0y39cZ0WTzLhQyiN5UlqJVNFR6WGX54WRIC7aoXyDCZyZJExHYDJDvMA2GTCb+pZimgW5UVS3yRweOtdVeGAYGMomQlaAS+Hlmd4NhGIZxhvB9++23sX+/5cIAzZs3l+J34cKFalfHMMZSr0ONEVm1eb70+NgDSm4asKUA+gcGEexeNaXgNS2huBttvbY5Sfz6yAFjiuoyvk4m6jeI8C+tzEyACCfx5QbFt2+SOZT+ofiPgZ4GpumoXHZa0EobM4ZhGIZxJRRhycGfSSQsLAwBAQEIDQ2V6R6M8xDRGyBC33Z8QffaUIJ+sPxI39q24o5APHXGY3kfQ76mR01kBkIfDvGwMZUss9PSG0r+/cbIclL0TwcAcQfSPKhQybsJiluZNK2DYRiGYTJSr3HlNibTELH/pO4SjD8J8eRVCH2IqpKyInqNoSJZ4sj/VF722jIAVWjLJNErkYP01KQYREt/YksoslpgWkSvBvDqwqKXYRiGcTlcTvjOnj0bJUuWhJeXFxo0aIBDh6jog3VWrlwpC21Q+2rVqskiHEwWQR+aSgGmA3S3rZYmFrq7EPGnoY/ZCfGwBUTo+0DcPkNahGHDjn9EPFtCybsKGm0QMhOqPKfOk9cNQlY0szKYUFNE5Xq0Kf+mCm0Bn6rqL8MwDMNkJVxK+P7+++8YO3YsPv74Yxw7dgw1atRAmzZt8PDhQ4vtKSf5tddew6BBg3D8+HF06dJFvs6cOYPsitDdg4jdAxG7H0IKyywM+e06UFghKTogeiWEHBRnQMRsg/5JD4hHzSGedANCKH/4sXFuKiOc2mJQ8vwBTdAcg3NAZqM48pG1fGzJFk3J/au02UpZeMG4jHcvIM82wHeQrHoGcozwehlKnj+hIb/hNFirMQzDMExm4VI5vhThrVevHmbNmiXf6/V6FCtWDCNHjsT48eNTtH/11VcRGRkpLddMkCtFzZo1MWfOnGyV4yviz0KEfw3E7TYbse8uTfMV/7FQtCQysxYidh9E8IA0rYOEGI2mFxHzICKmG+/lnFkQww1K/oNQNP7ICgjyqg0dq6qtEvgtFK921tdFqSJRKyGilgJ6KrvsBng0NhTJ8Hgue5bJZhiGYbIlavWaU2vhnj17FpUrG034nQyVRD569CgmTJiQOE2j0aBVq1ayhLIlaDpFiM2hCPGaNVSZyjKxsbHyZX4gszqGgVskIBOS2VTFAzFrDYUL8qyEoi3k/G3TfRMVW4g/Z4geulc3vMijNma9FOSEQtO8OySNmno0BtwqAQkXU++2IHQQcYeNohfOrwJHx5QKImiSVoLLNKhKXFgAIOi6tHbPqpDqBTxb2VyVrAzoNwSK3xB5HlnoMgzDMNkdh1Md+vfvLyOt5tD7qVOnymhsevH48WPodDoUKGAaoGSA3t+/f9/iMjTdkfbEtGnT5B2D6UUR5axvCTbCWKDBknjUAfonECHj0idi+7gNxNPeEOFTIcI/hXjaHeLR8xAPG0GETQKi/5AvEfaBYVr0qqTlXoN+kukEhkfujgovLeBW3FiOOLUpE/YR+qxz8yPTFAI+M72z1MLw/4BpVu3dLK+XRS/DMAyT/XFY+FKubPfu3WWZYuK///6TKQjz58+XBS5cHYooU5jc9Lp16xayNOTJKoLtRDp1QPy/EAlp9W59hojdCRE8CNDdME15FoGUg8hMUfME48tQQU2EjpcuCyYUbQEoeVZD8Z8IaKkqoKLystQaBmlRZNNp/rxWCPsoSS5xZqN4tYYSSC4VpvQV7TPhrykIJWguFK+WTt+uiDsGfcg70D9sBP2DetA/6QkRvVbefDEMwzBMthS+O3fuxL1799C+fXt8+umnqFu3Lho1aoSTJ0/i+eefT59eAsibNy+0Wq0sm2wOvS9YsKDFZWi6I+0JT09PmRti/srKkABVexopMuqMlG4ZZQ55P6nYdWT5sE+lzZgJ8pqlvFJNvs1QCpwH8p80pEBYjeJS5TYPKH4U6Y5NX9FL6K4C0c4q9escSNgq+XZCCZwLxe8twyvoJyj5tsuSyM6Erhl92GcQT3sCMRvlEwSIUCD+BEToexBPukPonzp1mwzDMAyTJYRvUFAQtmzZIn8MyV1h2bJl+O677+Dj44P0xMPDA3Xq1MG2bRTde5ZiQe9JeFuCppu3J6jv1tq7JI5UPYteDhHyNoQwROvTFmUmD91UimjKT43ZbPWRu0bjKYtESDcBiTbp5aoJghK0EIpbWUp6BZT0vfZkl6OWIKshK7F5tZA3APLl2VxOczpRvwJR841vzG8yjNddwkWI4GFOualiGIZhmCwlfGmwF+XaLl26FC1btpTi98aNG3J6eg8Eo4Fq8+bNw4IFC3Du3DkMHz5cujYMGGBwBujbt2+SwW+jR4/G5s2b8dVXX+H8+fP43//+hyNHjuCtt95CtkGWzXVA7MRugggz5YimDhF3MI3jIt0g4v+z2UIhcZt7qaE0sXc3wKOZTG1QAmZCybcLikeNZ7mp3l1TkeOrAG611DdPuGAohCGcPXguayMLgFDxD5tQKs1JQF4XDMMwDJN1cVi9BAYGJg6EMUV4SpcunTgqnERxekH2ZI8ePcKkSZPkADWyJSNhaxrAdvPmTen0YKJx48ZSoE+cOBEffPABypUrJx0dqlatiuyC4t0VImqRA0sIQ+TX700o2nyp3Cqd47RG9+wPppLXmUcdKB51bLfz6QsRtcIYgVTRL4oQ+/QGPFsDT3uo7K8wFMKI2Q4EzoSiONUQJetCqTTSQcIeWojoP6F4NsyATjEMwzBMBvn47tq1y+b8Zs2aITvhCj6++qeDAbIsU23lpYHi/x4UKk6QCgyeuV+lyTpMRm69O9reDg2aEgmk7u26DsiiHcFvGgfSmd98USRYAD59DKkRZOFFHrUaH0Ou8sPGKoVdYs8B3xHQ+I9CTkDmhYdPU3eu3etCk2dpRnSLYRiGYTLGxze7CdvsgBL4jcyxRPxhlUtoIHT3HTYPS8T7ZSBiZmqXNjgxkB+tBWQqQcxGiKiFcvCURJMX8HlNRmkVTW7Lq/R8Dsi7CSJ6GRC1ypCDrPgC3h2h+LxuzAdOtoziAeHzKhD5iwMiXgCRP0GvLQHFu132r2AmfZfVHBvyDvbNgA4xDMMwTCZUbouKipKpBVRYwpzq1asjO+EKEV9CiASI4OFAnO2IvAEt4DsYGv93Ur09ffhMIFJd9btnkNQWUAK+geLd3vI+hLwNxP5toQKbRpbYVXIvhuJGtmfOQegjIJ6+BiRcdtwdQgmE4j8eig/lGGdP6AaJSkCrEb9KrilQfHpmSL8YhmEYJkMivpRjS4PJrHn2pmeOL2MdmXPq2xdClfDVQfFskbbt+Y0xuENEUbRULf5QAqZYFL2EiPgWiP3H+C650NJTTofBOzjv3w4VZ7CFovEDci+FCJsiq9w5hAiBCKNS2XHZVvAp2oIQlAsdu9XGjYEx2uvVKYN7xzAMwzDp7OowZswYhISE4ODBg/D29paDy8hlgQaOrVuXtbxOcxweTYxV0LR2qp2VB9xrWY5+Rq2APmwa9OHTDUUqhGWxoygaaHKNMxadUAkNCrMmevVRAKU32BycpgN0t40FK5yHovGHJnA64F47FdXjKEX4Ewh9iOPLxZ+HPvxb6MnXOOJHiISbyIooAZNtXFfG4hm+QyBCx0H/uLOhsEXEXPb2ZRiGYbIcDkd8t2/fjrVr18rCFeSgUKJECbRu3VqGlancb4cOHdKnp4xdSIwicJYsIQxZaSy5aNUCij+UwO+SDBaT2S5Rv0KEf0dmv4mXhYicB2gKAYEzoHhYKUftQEUzRa7bChSpVrUujawWplDVNiejeL8MEX8sFUsmAFSK2XegqtZC98iQ0hF/yCgcFQiKaEd8A+HZRpYklpHoLILMq86zAiLie0MJ6sTzpADu9QH9QyDia+O+GK45EX8ciPjOcO14tcvU/jMMwzBMqiO+5JubP3/+xGIWlPpAVKtWDceOpUY0MM5Eca8EJc8fgGerZKfXUOJXyfMnFLfSSReKnAMR/oVR9CYrM6x/APG0H0TcUcsb1BZQHyVNLLFrAd0TleuhlIfHSBfoUb0SlJqPBQT52Kpppw815BTHm46nznisjVZssf/IdI6sVgZY0QRCk+sjKPn2G/yVgxYAebcZBhHqrhtbmd9oUeTekLMtYg9kUq8ZhmEYJo0R3woVKuDChQsoWbIkatSogblz58q/58yZg0KFCjm6OiYdIGGrBH0vI4tUVUtCgtiCI4IcvES5tVYx5NqKsElAnvUpbMUU724qRJ8CaIsA7oaiExYhmzFV3sAaozh1HEGRyvjTgIiR/VHcyiTtpcYHyP0LxNO+jlXEkytXl9suyEGC0jWsrlsPULQ0eg3g00MO+CMvXUGRVlpO8YVCNzU+3aw6XKQnVF4aHnUNb6I3QiScs9GazqcCEfE1FM9sVC2RYRiGyTnCl6qh3bt3T/5NVdvatm2LJUuWyJLC8+ebypoyWQFZoMJOkQoR9buKNemBhEsGezGPWimjpPQIXOZzWhN/AorvcEMqhjU8n6ckZTlQzF5frOUJW4Pyhw2P6ZeT8nw23a06FP/RBis0I4p7VSDvXxBP+gB6Eqhqq8CVt98PORhwmQpBrRiKkng2hwgeaLx5MU8jOGFMI/gKihVbuIxARC234L5hScifgEi4bNFSjmEYhmGytPB9/fXXE/+uU6eOLFdM5YCLFy+OvHnzOrt/THoTf0plZFNjaJtM+MoIYNB8iOC+gD442bqMYs13OOD9is21K5pcEN49gOilNvpDlma5AQdyRoU+EuJpHyDhbMr1JpyBCB4MBHwu83uT9Ft/R/U2ZP99VFSA090DRKiaXhtKJD/tZyONIA4iZBSQe5H1/Ov0RndNfVScBu6x8GUYhmEyGceTGZPh4+OD2rVrs+h1WRypvmY5FUFxLwcl7wYofm8DmiLGy8pblgRWci+Bxv9tu5XX5HpyvQ+4k4ijtoqFgXm+UILmQVE81fc44hvLoldiyKsVoR9A6O4+m5xwxbGSzL5DpO2Xit7AIXRXbEbR5f/DbaWppDOOFO/I7oU+GIZhmOwZ8R07dqzN+TNnpqGiF5PxuFcB4v5VUbxBD7hXtjpX5pv6DYPiNyzVXVEUL5ljS+kAsnKb7pZxjjfg0xWKz0AobmSrpT7ai6gVKsS9kCkfiv/bpp440Gkfg+BXg7aQdNWACLe3UmPaR7yKNIJD0gZNcSuODIfSU2S6g71rx9N2fjfDMAzDZFXhe/z48cS/9+7dK9MdyM+XUBPVY7IWincPg22Z7VaAtrgxGpvO/aHIoG8/wIdSJx5QQiugzZ8iyisSbgPiKYWJASofbOnak84JaizSqEzyFsAkfKXAdzcKT1toAc8WtnOXLZZI/s2OWBR0J0HKXdV65Q1CJghfxbsXRNQSO620gHdX6ZXMMAzDMC4nfHfs2JH4t7+/P5YuXYrSpZPZYzEuA0UKhe9gwKr4NaQdKLk+ztAbG7ktC+kDImaLLI6ABMpNNkIDy3wHAV5dkvbRAY9hg4uDcduaQAiv9ioquekA79fUb0MGiAdBRG8weN9aFL9UYKSCwbJNbf+dVMXOUSjFBX7vQER8ZaWFVha+eBZJZxiGYRgXz/FlXB/F7x3A903jfZDGOCjNeE+k5IIS+CMUz6aZ3U1DNbCQEXJQWhISLsmqYSJ8qqEYhwltYZVrVqTw1T8dCn34DEMFNbXLmucGq9mSNg+UPMsAt0rGKW7Pqp8RHo2h5F4AeDazU4HPtEIfwK0qMgtKbVFyTTMUOkmCG+DVEUqe3+WNBMMwDMNkBRSRRCk4BkV8T548ma0jvmFhYQgICEBoaKisTpedEVREImYNhBzcpYXiUR/wamNIP8jsvsUdNlSks4MS8E2i3Rld2uJxO6P7gNrLnMQmpRhQ+k6Uva1J0anJ+yccRX7s4k9CxGwik2RAkweKV2co7gZbNBF/FuJJF/t99ekDTa4PkNnI0tZxhwDdHYBytT0aSZHPMAzDMFlJrzmc6rBu3brEv/V6PbZt24YzZ55F4Dp37pya/jJZAClUfAc5MrQrwxCR85N42VpGAxH1W6LwlWkP/qMhQkY7sCXT+qPU9ApIOC39eRWV6QZS8MbtN+TGymp4esCtIhTfZoBZRT2F8oz9RkGQX69FKCWiDBS/UcgKKArlO3ORCoZhGCabRXw1GuvZESQ0dDp1FaxchZwU8c2qUDRRPKDH+equLSXfgSTRRhG5ACL8M2Mah/OvT6XAKYMjhR2oCpsIHQ/ErEsm4o1FINzrQQmaC0Xj92yZqBWG4hs00C8Rd8DrJSi5JvCgMYZhGIZBOkZ8KcrLMBmKiHVMsIoIAM+Er0IuEZ5NIKhqWsw2QB8GgNo4AU0BVaJXdit8BhDzl/Gd+f4YP1PxRyFC35HiN0lhDO9uxjSCe4DG25BGwHmzDMMwDOMwPLiNyfoo3oZBXKowVndLvgq3stDk+gia/Duh+A1MzT2fxW0pPvbzjgmhDwWoDLHNXGM9ELsDIv5CijQCxbMRFPIy9mrHopdhGIZhMkr4Pn78GIMHD8aAAQPw9OlTfPHFF6hevTr69+8vw8wM42xkrq53VxUuB5Rn2krF439aj9oMH2sZz1pAUxDwUWlnFrOR7CdUNNRCRK9S2TeGYRiGYdJV+L755pvSyeHevXvo2rUrFi9eLIXwoUOH8N577zm6OoZRhUIFLaRgtTX0TkAhT2J7eNRVnzpBldaSfFSM4ltbEkruxVA0AapWIyhNQY09GQly/X11fWMYhmEYxiEcft67fft2/PPPPyhbtiyCgoKwZcsWtGzZElWqVJFRX4ZJDxS3kkDQHIjg4cbIqblwNQhKJWA6FI+a9lfmXhfQlgZ01+2UBPYC8m6BQmWBKWKrDwE0+aB4dwI8nlNdsU32TfGBsFs6WbZ0IK2DYRiGYZh0Fb6RkZHInz+/HDHn4+ODEiVKyOnly5eXaRAMk17IIhr5NkNELQUoHYCEKEVkvTvKXFvFrYz6lfkMBMI/NkaQLac9KAGfQNEGAdo2ULzapK3zni2BiJkqGuqgUFuGYRiGYTJf+BYpUgQ3btxA0aJFsWnTJvkv8eDBAymIGSY9UbRFoPi/B9ArFYjodQZvXN1NC3ONtmKaglByfQDFqy2cBRWmEBRpjj9uI82CBublAzxbOG27DMMwDMOkQfhOmzZN+qQRTZs+K2N75coVOeCNYbIqImIeRMR0K3nCCqDJD+SaCMXzBUNBBiejBM6AeNID0D+xIH61FNKGEvQjFMUZjhMMwzAMwzi1ZHFOgAtYZA9E/HmIJ/aqCmpk5TpNKqPJqvqhe2iIOEevARD3bLueL0LxH+1YugbDMAzDMOlbwMKeZRmLQyYrIvOC7ZY81gNRyyH8RkFRPNOlH4o2P5SATyH8xwEJ5w35xdrSULR502V7DMMwDMOkQfgGBgYafFWTQYHj7FiymMkmxG5XZ2EmwoH400bLs/RDeg171EvXbTAMwzAMk0bhW7p0aTx8+BDjx49HkyZNHF2ccQFEwlWIqOVA7B6qowu4lYXi09No4eX83NcMQcQ5WCKZYRiGYRjkdOF77tw5fP/995g6dSqOHz+OL7/8EqVKlUqf3jEZjoiYCxHxVdK0AN0dCIqYkitB0FwVldGyINqiQEKouopt1JZhGIZhmGyHw5Xb3N3dMXbsWFy6dElam1G54nfeeQchISHp00MmwxBRK42iF8nSAox/xx+HCH5TprW4GorPqypErwZwrwPFzeBNzTAMwzBMDhe+JnLnzo1vvvlGRn2vX78uK7nRe8Y1ESIBIuJrO610QPxBIP4IXA7vzoC2uJ2ywQKK36gM7BTDMAzDMFnazqxWrVopBrfRKi5fvoyoqKhsN7gtp9iZidhdEMFDVLTUAl6doAn8Eq6GoJSNp/0B3Y1nxSok9LcGSsCXULw7ZnIvGYZhGIbJMnZmXbp0cbgzjAugu22zfK9ZQ0B3Ha5a9Q15NwAx/0BErQD0dygHAorXi4B3dyjagpndRYZhGIZh0hGHhe/HH3+cPj1hMhnyrVUZ/Fe84aooigfg3ZEjuwzDMAyTA0l1bdQjR45IhweicuXKqFOnjjP7xWQ0no1VRnwVKJ7NMqhT2RdBlmkiHlB8LfpiMwzDMAyTBYTv7du38dprr2Hfvn2ymAVBjg6NGzfG8uXLUbQoW0G5Ioq2MIRnCyB2l41CDyTQKGLaNYN7lz0QQg/EbISIWgDEnzRMVAIhfF6D4vM6FG2+zO4iwzBMhnEjJAQLTx3H6vNnER4bC38PT7xUsRL6VK+J0kG5M7t7TDbFYVeHwYMHIz4+XkZ7nz59Kl/0t16vl/MY10XJNQXQ5LfifECXigIlcDoUjeGGh3HQNSPkbYjQsYbKcIkzQoDIuRBPOkEkXLayrA4i7ihEzDaIuCNyXQzDMK7M1quX8eLi37Dw5HGExMRAJwRCYmOw+NQJtF2yABsvXczsLjLZFIddHby9vbF//37p7mDO0aNH8dxzz0lnh+xETnF1MCF0jyDCv5CRScBMYLlVheL/DhRPrtaXGvTh3wKRP9hIJdECmrxQ8m0z5CEb3VIQtQgich6gf/CsqSYfFN9BgE9/KEqqHQkZhmEyhQtPHqPTskXQ6fUWvxHp2aJGUbD61d6omr9AJvSQcUXSzdWhWLFiMuKbHLIxK1y4sOM9ZbIU9LhdCZwBof8AiDtmKFmsLQXFvWJmd81lESIaiJpvJ39aZxC3MX8D3p2k6BVhk4Do31M21dPNyedA/AUg4HPOEWYYxqX47fhRw3eclfmm6T8fP4Jv2nTIwJ4xOQGHw0XTp0/HyJEj5eA2E/T36NGjMWPGDGf3j8kkFE1uKF6toHi1Y9GbVmL3ACJSRUMNRPRa4zL/WBa95sSsBmLWO6WLDMMwGUGCXo81F87J1AZb0HxKd4hJSBloY5i04HDEt3///jKdoUGDBnBzMyyekJAg/x44cKB8maD8X4bJ8eiD1TaU0VxCRC5IVmTDEhqIqIVQvDs5pZsMwzDpDQ1ii1NZ6IpEMuX/FvRzT/d+MTkHh4UvlyVmbCHzUhMuAPpQQJMbcCvLj+I1ASobKvKYydQIVWWh9dIdQujDoGiyf/45wzCuj4+7uyrjTBO+7oYxDwyTacK3X79+Tts4k80Eb/QKiMifjSWBjWjLAH5DAa8uOVcAezQF4EW5CXYaCiheHQFhr13yxaIBsPBlGGdy8sF9LDhxDFuuXkZ0QgLy+/ri1SrV0KtqDeTz9c3s7rksnm5ueL5ESey9ecNmugMNbmtQpCj8Pam4EsNkgvCl0XJqyAnOB0xSDAOxpgDRS4zjcc3QXYUIHQckXIbi/x5yIorGD8Knl3GAm7XUBQ2gBADe7QG4G6rjSUFrD09AE+TkHjNMzmbescOYtnc3tIqSKM7uR0Tg+0P/4rcTx7CwyyuoXoBLnKeWgbXqYNeN6zbb6IXAwJpcGIvJxMFtVKwiKCjI6ss0P72gfOHevXtLYU3bGjRoECIiImwu07x5cxllNH+98cYb6dbHHEvsZqPoJZLfwRvfR86DkMUxciaK/1jAo7HpXbK5WkDxgZL7FyiKNxTFDfB+xYqfcrLlvF9OtD9jGCbtbL58SYpeInlEksRYRFwc+q35E0+js5d1Z0byXPGSGNOgcWJk1xzT++F16+OF0mUypX9M9sahVIc//vgDuXNnTjUVEr337t3Dli1bpJ3agAEDMHToUCxdutTmckOGDMGUKVMS3/v4+GRAb3MWIvI3FQOxtHLAVk4tdyzFadBcIHqlYeCa7ppxjjfg0w2KzwAobsWetffpBxH9B0CljS0eVzre7lB8+2fYPjBMTmDW4QNUqgfWzLZI/IbFxmLl2TMYVqd+hvcvuzCqQSOUz5MXc44ewqkH9xOnV86bD0Pr1EPH8uwmxGRyAQuNRoP79+8jf36q7JWxUGW4ypUr4/Dhw6hbt66ctnnzZrRv316WULbmH0wR35o1a6ZpQF5OK2DhKEIfCvGwnsrWCpQCp3N8hFJ+5PRPAMQZilZYOR6yWlvwEKMVmvnHVJGpEErgXCieDTKs3wyT3bny9AlaL6aUJPuUCgzCtr7PXIyY1HMnLAxPoqMQ5OWNYgFqBwMzTOr0mkuUfTpw4IBMbzCJXqJVq1ZSjB88eNDmskuWLEHevHlRtWpVTJgwwW5ludjYWHnwzF+MDYQjj/uEyrzV7I1Mu9HmhaItbPMmQPGoY6jk5v8+4FZRVmyDW3kofu9CybedRS/DOJmHkWr8tg08ilLflrFNkVy5ZM40i14mS7o6ZAaWIs3kG0xpFzTPGr169UKJEiVkRPjUqVMYN24cLly4gFWrVlldZtq0aZg8ebJT+5+tkQOr3JKWN7aKF6D4ZUCnsg8KHV/fQYYSxQzDpCt+DjgI+LHNFsO4JKojvqbBYc5k/PjxKQafJX+dP38+1eunHOA2bdqgWrVqMkd44cKFWL16Na5cuWJ1GYoKU5jc9Lp161aqt58TUBQvwKuDuoFYPl2hKPbaMQzDZA6UX1rQz/7NObk9dChfIUP6xDBMJkV8KS+RqrZ52rkjthVNTc4777wj12mL0qVLo2DBgnj48GGS6VQtjpweaJ5aqNoccfnyZZQpY3m0KO2fvX1kkkLRSBGzwehWYCllnKa7yQFbmY0QCUDsNkNpYN0DQBMIxast4N1ROiowDJNz0Wo00kLrs732HWh6V6uRIX1iGCaThG96FK7Ily+ffNmjUaNGCAkJwdGjR1GnjsHXb/v27dDr9YliVg0nTpyQ/xYqVCgNvWaSo7hXBAJnQ4SMNKY86JM9VPCAEjQHilupTOwlIBJuQQQPAnTXzVwoFIi4PUD4dOm6oHjUytQ+MgyTuQyoWRvH79+VtmZIditPkV5ydZjeui1KBrJ/NsNka1eHzKZdu3Z48OAB5syZk2hnRoPdTHZmd+7cwQsvvCDTGerXry/TGWgeOT/kyZNH5vi+/fbbKFq0KHbtUu8ny64O6hG6uxBRywGKpopQQAkCvLtA8XkVijZzzd6prK943BnQPyB3TisFJDyh5FkNxa10JvSQYZisgk6vx5LTJ/HL8aO4FRaa+NyqafESGFGvIeoXKZrZXWQYJpV6zSUGt5ncGd566y0pbsnNoVu3bvjuu+8S55MYpoFrJtcGDw8PbN26VVqZRUZGolixYnKZiRMnZuJeZG+kSwEVaqBXViN6BaC/Z6NCvJ78wyAifoIS+HkGd45hmKyW8tC3Ri30qV4T10KCERUfL0sW5/flwbkM4+q4TMQ3s+CIb/ZA/6gloLutoqU7lPwHZZlhhmEYhmFcg2zl48swaUEIvUrRS8QDOooMMwzDMAyT3XCZVAeGST2Unae1kttrqbl7eneIYRjGIcJiY3AnPBweGg1KBAbBTZP+cSt6IHzx6ROExsQgj7c3SgfldrqtKcNkNCx8mWwPfVELjwZA3EH74ldTANAWy6iuMQzD2OTSkyeYfeRfbLx0EQl6g2NOPh8f9KleC4Nr14GXm3u6CN7f/zuNuUcP40ZoSOL0Cnny4s16DdCpfEWnb5NhMgoWvkyOQPHpAxG3314rKD6vc5ENhmGyBIfv3ka/NX8iXqeDzmw4zqOoKHxzcD+2X7uCxV17wMfd3ami96MdW7H0zCn5rMyci08eY/TmDbjy9CnGNGzstG0yTEbCOb5MzsCzJeD1so0GGsC9JuBru6AKwzBMRkBOEkP+WoO4ZKLXBPkJn3r4AFP37HTqdv+6eF6KXiL5Vk3vvzt0APtu3XDqdhkmo2Dhy+QIZAnsgGlQ/EYDSnLHBg/AuweU3POhKFy1j2GYzGfthXMIi42VAtcaNO/Pc//JHFxn8evxo9DYyeOlQh7zTxxz2jYZJiPhVAcmx6AoGsBvBOA7CIjdDegfA0ouwPM5KJqAzO4ewzBMIpsuXbRaBN4cigjvunENnStUSvM2H0dFySiyPSgCveP6NVnogzyPGcaVYOHL5DgUxQvwejGzu8EwDGPTxUGtyX54XJxTthnpwHoo2hyTkABfDw+nbJthMgoWvgzDpEDoQ4Ho1RCxewARA7iVgOLdXeZBs50Rw6Q/Bfz8oXn00GaqgwlyeXAGeXx8VEWZCRpQ58xBdQyTUbDwZRgmCSLmb4iQd+kh6rOfwPhjENF/AB5NgcDvuLIdw6QzXStVxparl+22y+XpiWYlSjllm24aRebvJqgQ2+3LluebYMYl4eQchmESEbH7IEJGJxW9EqP/cdx+iJA3DdXwGIZJN14oVQalAoOkELXFkNp14enmnBjW5suXVIlegqO9jKvCwpdhcmAag4g7DhF3AkIfnnRe+HSj4LX246cH4v6VAphhmPSDKrMt6NINBf38ZfqBufw1ieEelatieN0GTtvm1eBgVRXhaOtPo6Odtl2GyUg41YFhcggi4TZExCwg5i/KXTBO9YDw7gLF7y1AHwwknFWxJi1E1DIonk3TuccMk7MpmisAG3r1xcqzZ7D41AncDA2Bu1aLhkWKoV/NWmheopRT0w3ctRpZwMIeZHeWESWTGSY9YOHLMDkAkXAF4slrFNJNVrY5Doj+EyJ2O+D7hsq16YCES+nUU4ZhkufwDqpVR75IlKZnXm2DIsWgE/tV2Zk1KMql3RnXhG/ZGCabQz+WIvgtC6LXhA7QPwUif1a/UoXz+xgmo0nvwWT1ChdB2aDcNgtY0Bw/Dw90Ll8ROYWQmGicfHAf/z18gNiEhMzuDpNGOOLLMNmduIOA7oqdRnpAf1/lCrWARxMndIxhmKwmrP/f3n2AR1VmfQD/T3pPIISETggdQu8d6SBFehFEUdR1Xesquoqfrq51ddeua0FsFKUpIh3pHUKHJJQQIAklvUIy33NemDgJU+6kzmT+v+cZk5m5M3NzM4Zzz5z3nHcGD8PknxeqwRjFW6npDNsMGgpvJ1jcFnvtKt7fvRO/RZ8sHBvt7+GJKZFt8JdOXVU2nhwPM75EVZw+d30Zn+PmQ+czpQyfj4jsRZvQMCwePxmRNUMLbzPkf6XLxJcj78LgiCao6g4mXMLoBd8XCXpFel4uvty/F+MX/aAyweR4mPElqur0mRpb0muj83sCOrey6RtKRPanVc1QLJ00DccvJ2F/wiWV+W0WXEOVQjhD714pZ3jgl6XIyb9hcoCIBMJnUpLxwoZ1+HD4yErZRyo5Br5EVZ1LaGmf4GYphEswdH6PQeczuYx2jIjKw/Erl1UXiPVnYpF7Ix/1AgMxtXUbjG7WwqYShRYhNdXF2ayKicZVK+3aJPj9PTYal9LTUcvfv8L2jUqPgS9RFafzHgN95kcle7D3BOjcmgGu9QDPXtBxURuRXfts3268uW2L6vVr+Ig+LSkHz29Yi0/37sb3YyeiTkBAZe+mXVsTG60W+FkbFy0LhzecPY1pkW0rbN+o9FjjS1TF6dwaAJ7DSvS/u849EjrfGdB59WfQS2Tnlp04roJeYVyXavjuQnoa7l662C47E8SnpSIq4ZIqIdDSS7g8SR2vtaBXSHCcmZenuj3IsV956iQupqdVyD5SyTHjS+QEdIGvQ5+SAuTtsO2BLjXKa5eIqAxJsPjfXdvVQjRzIZsEw+dSU9RH9FL2YA/Wxsbg4727VLswgybVgzG7Y2eMbd6yUmqKZVqeccbcHLn/20MH8ca2zYW36W6Nm57bt78aQEL2hxlfIiegc/GBrtqX0AW9D7g21vigAMCzd3nvGhGVURcCCWr1GrKUC48ehj34ZO8uPLhyOQ4nJRa5PebaVfx97e94ZfPGSsn+SsBtLeg1uFQswyuP2nj2NMYs+F5N2rNEWsZJFj4xI0NThpnKBjO+RE5Cp3MDvIYCngOgvzIMyL9gZqDFre19Z0GnY59KIkdwKUMG1FgnAdaFtMr/OH73hXi8vX1r4T4ZM1z7JuoAOtaqjTsreFhGt7r1VFs3KWGwFgAXmLhNHpOam4M569bgh3ETb7s/KTMDXx7YhwVHDiE9L0/dVsc/ADPatsP0Nu3g5caysvLEjC+Rk5FaXV21rwCXmib+BLje/OI1HvB9sDJ2j4hKwJZuDT52MHzi64P7LE6IE3KvBIgVTcor/jdyDCKqVS/cDwMpgdBCgt+dF86r7LWx08nXMOKHb/HVgX2FQa+QzO8bW7dg8s+LkGF0O5U9Br5EhrG+evtb8FFedG71oauxAjr/vwMudW/9aXcDPLpBF/QZdIGvQafjnwciR9Gldl14u1n/EFeCzSGVPIBCMrxrT8da75oAqNrfy1nSi7xihfj4YtnkaXj9jkFoXiMEnq6u8HZzR+/6DdE+rFaRYNgc2Wbb+XOF1/MLCnDfiiVq8IWpTLIeehxJSsSLG9eV8U9DxljqQE5L1Y7lboI+az6Qt1N97K93Cb05lcxnMnQuN8/2qyqdSyAg5Qy+s6DXywd2OqdoTk9UFfl6eGBS6zaYH3XAYkApge/k1pGoTNJVwpaa1vScXBWIVjQpOZBjKhdj9yz7WdNIIDnW0kfZYNO5M4hLTbX4GDkuv5w6ged69UFNX78S7zuZx5QOOW+GN20u9CkPFga9SkEi9BnvQ3/lTuhvxMJZSHaXQS+RY3u6ey+0DqlpsoRAbpPLvwcPU10LtJBMq3xUfzUrq0z308vNTVPG1OCnY0dgTxoGBWkqeZCsbv3AoMLrv0Wf0vQ4+fdpdWxMqfeTTGPGl5xT1ldA9sJbV4ov8CoACpKhv3YvELKWC7yIyCFI7e6P4ybh/d078MNhWTiVW3ifLBJ7rGsP9KhXX1OLsc/378G+SxcLb+tRtx5md+yCPg0alno/5STb1cUFNwpMLQ273aLjR/BUj17qMfZgUqtI1cbMmmpeXrgjvFHhdXMlDsW56lyQlptT6v0k0xj4ktPR669Dn/k/K1vlAwUJQM4qwHtMBe0ZEVHpF7k927MPHu/aQ7UJy7lxA/UCAtEg6M/MoyXSC/i/u3bcljXedSEe2+PP4x+9+2FW+46l3s9qXt6aa3evZWdjz8ULqtuCPWgZUhODIxpjnZU65ce79YSH660FwwCqe/to7A9coLal8mEfp09EFSlvF1BwTcOGLtBnL62AHSIiKluebm7oVLsOetVvoDno3XDmtAp6RfGAzhCsvbZlk2pFVhqnrl5BTV/banYTMzNgT94bPBx9b2W/jcsXDN8/2a0n7i42ynhUs+baMr4uLhgSobHfOtmMGV9yPgWXtW4I5CeV884QEdmHLw/stZqRlPvnHdyPLnWkG4ztPty9E+/u3Ka5LZiBn7sH7C2z/sXIu9RJwA9HDuHElctwc3FB97r1Ma1NW4QHVbvtMT3rNUDT4BqIvXbV7DGWTPuElq3NZnylM8Qf587ih8NROHXtCtx0LuhZvwHubtMOzYI5aVMLBr7kfGQimbYNAel8QERUxUlN6Y7481a3k4Bt7ekYXM/Ph7vRx/haSLAmQa/hebSSNmL2UuZQvFa5a9166qKFBLVfjroLU35aiIsZ6UWy6oZR093r1sPcPv1NPj49NxcP/LIMuy/GFzlBOX8kFd8fjsKjXbqpEhcuVLaMgS85H4/ugM4H0FtfqazzGl4hu0REVFLSdUG6L0jA0zQ4GEFe3jY/R3qu9qEJEnBl37huU+ArC9n+s2u7zfslweKU1m1Uu7aqQCa0/TJlOr47HIXvDh0sLOGQXsEz2rZX45JNHVfp9PCX31Zg36ULt504GL7/YPdOBHv7qOch8xj4ktPRufhA7zMVyPzKzMBJ4XIzOPa+q4L3johIm3MpKSqD+lv0ycLgRz5uH9W0OZ7s3hO1/bV+ugUEeXmpIFNLf11ZsOVrY+nBlrizuGJjWzTZHxkW8XSPnqhKAr288EjnrvhLpy7Iun5d/c6kJtuSAwmXsO18nNXnlhrtya3bFFlUR0VxcRs5JZ3f42pK2c0PmIp/LCR/MGSs76fQuWjrd0lEVJFOXr2C0Qu+KxL0GjKry08ex6gF3+FsSrLm55OM6qBGEVZrb+X+0c2a29xaLD4tzabevZK5/FuX7vjurglqkERVJBl6Oe7Wgl6x6OhhTXXRyTnZ2HT2dBntYdXEwJeckk7nAV21/0HnPwdwrW10jxvgdSd0NZZC59GlEveQiMg0yco+vHI5Mq/nmayVldtSc3Lw6Kpfb06o1OiBDp0tZnxVmkCnw8x2HUs0tELrnrQLDcP2+2bjb127awoKy5ssKEvMyMDlzEybJs6VJZn4pqUuWrLk59PSKmSfHFXlv6OIKolO5w743gv43APkS91UHiAji104JpKI7Nf283E4m5JicRsJko5eTkJUYgLahdXS9LwdatXGW4OG4tl1q1WQaxxoSbZRgt7/Dh2BFjVCbN7nXvUaaCqlkNe9s2lzmxfOaXU+NRUbz55WNcq1/PwxqFFj1aHBlOTsbMyL2o/vDkWpTKoI8/PDjDbtMb1NuwqtO/Z2vzntzlroKyc63nZwsmDPeHTI6cm4XrjZ34phIiJTNpyJVXWh1iafSaur9WdiNQe+YlyLViqw/SZqP1acPInc/BtqItyY5i1xT5v2aBIcXKJ9ruUvQWaEGvpgLnMpgZ2nq5vah7Im2do561dj09kz6roE4bIfvu7ueKhTFzzcqWuRoR2X0tMx8acFuFSs+0JCRgbe2bEVK06dwI9jJ6p63YrQt0F44b5b07t+6afrVWUMfImIiCqQZOVkoposQCrJGN6M63nyJFa3kzgu8/r1Ek0me3PgULwxYAiuFxRYXSgVn5aqJrvl5eer/rXS47f45DfxSv+BOJKUhISM9NuCX8P2/xk6vMyDSel6MW7RDyqINbyq4fXl+Px7xzYkZWbi5X4DCn8/D/66TO2nqQy13BZ99QqeXvs7/jeyYiZ73tW8Jd7ctlm9b8z95iUrL0FvvUC24bSEgS8REdktybz9eOQQfo0+oVpuhfj4YHzL1hjfshUCPCsm21aWH7PLR+eLjx1BRl6eCvb6NwzHzHYd1HADreQjei2VphLc1fIreemWlDZYCnovpKXhxY3r8Me5M0X2p25AAOb07IvhTZoW2T7ExxdLJ01TAdyKk8dVUG3QNjQMf+/RW1O/XksnDpLZlZ62C48eViOR5WP/mr5+t/XNLe7bQwcxsmlzNe1u36WLOHI5yeqxlWy6dNbQOhmvNPw9PfH+0Dvx4MrlKjNe/GeRoFeO778GDCr3fXF0Or0tle9OKC0tDYGBgUhNTUVAgPbWMEREVDprYqPVAi0JMgz/0OuM2m99M2Y8WtcMhSPYFX8e961YorKixWtn5bp0MHi8Ww9NzyXBVv/5X1rdTgJrWSQmgV9Zk6B3zMLvkZKTbbZ04fU7BmFS6zYm75PHSYsuGYQRHlRdUwmFZJa/iTqgOhyk3zpxkLHBcuIgmU6pZ75n6U8qI27rIjT5PYxo0gz/GToCL/+xAd8fisINveVSEnn9p7r3VGUSFUUmxb21bQv2J1wsvE3KXmTf5/Tsg9BSnOg4S7zGjC8REdmdqIRLeOS3X1QAYxzCGL5Pzc3F9KU/Yc3dMxHi6wt7lpSZgVm/LEVufv5tAZkhaHx/9w40qlYNo5q1sPp8kmGU7OTK6JNmAzw5QZjcKrJcgl4xd9M6i0GveGHjOtwRHmHy9yNDNvo3bKT59fZcjMe9y5cg98aNwteUn33zubPYePYMZrZtj5+PH1WlCyXpvCDPuSP+Zp/clJwcFGjIqUuwLNtWJCkj+WniFDWwJDb5mgp624XWQrCP6RHHdDu2MyMiIrvzyd7d6qu58EOCm/S8XPWxtr2TUg35aN5aq7CP9+7W3H7sjQGD0bNeffW9cX9Xw/fSrWBu3ztQHiTzKgutrLXXknsXHD1U6teTwRf3LV+qjmHx1zRcnxd1QJWPlKbdmGGxYDVvb7ho6Dosr13d2/YpeWWhcfVgDIloggHhEQx6q2rg+9prr6FHjx7w8fFBkMZ6GvkDMnfuXNSqVQve3t4YOHAgoqOjy31fiYio5KSN1Loz5lf/G0iQI0GlvZNMpLWATO49dfWKyuJpIS24vho1Fp/fORrd69VHoKeXKv+Qj/zl9o9HjCq36V07489rqjGWn3lr3LlSv978qP3I0lC+UJq6TSlbaBpcQ30vk++slTmo19PrcWeT5qV4VaoMDlPqkJeXhwkTJqB79+748kvrtU3irbfewvvvv49vvvkG4eHhePHFFzFkyBAcO3YMXhXUgoSIiGyTmJmhOXMnC5hkW1NdBCqDBEMyVU2y0TV8fFWXg2vZN3vAau1AINk8LWRh18BGjdWlIhkvSrNGappLY9v5c/hoz65SBbVayHvo7sh2hQvtOoTVRlTiJbMnX/J+GxrRBHW49sfhOEzg+/LLL6uv8+bN0/zH5z//+Q9eeOEFjB49Wt02f/58hIaGYtmyZZg8eXK57i8REZWMtw0jaiWraQ9BrwROPxyOwhcH9qopWwaRNUPh4eKKLGhrKxbgAEkZCea1kk4DJXXschJmrVha7kGvlIfIIsnBEY0Lu1l8MmIUJv28EHEpKUXqfQ3vNNn+9QGDy3nPyKlLHWx15swZJCQkqPIGA1nt17VrV+zYscPs43Jzc9XKQOMLERFVnPqBgWgQGGS1ylIClgHh2hdIlRdJtMi0s7mb1quWZcZkelpKbo7Vn0V36+dufuvjdnslP6tkcWUEsRaS/S5p86gPd+9U44LLmq5YPbS0MJs3elyRaXGyIG/5pGl4ukcvNa3NeGHh3L79sXDcJNVirKoq0OutDkhxVA6T8bWVBL1CMrzG5LrhPlNef/31wuwyERFVPMm43duug2orZYl8DC3jYyvbT8ePqjpeUTzEM5RsWB01C+CBDp3Vz26v1LqZTevVgkKte3k+LVW13upYq45Nr5WYkYHVsdFlnu0d2bQZ8vILkHk9D3X9A1RP6PZhtUwedwlsZarbgx07F7ZPk0lv9vw7Ko0CvR6/x5xSLeOkl7Fcl2N0d5t2mNw60uH6Zttl4Dtnzhy8+eabFrc5fvw4mjevuOLx5557Dk8++WThdcn41qvHcbZERBVpWmRbbI+Pw9rYmNuCHwk75LZHu3RDVw0DD8o7GPxi/97CfbKVBFMSYExqFYmpZnre2ovP9u0p7KJhy886Z90afD5yjOYSCelV+/DK5TYfz7uat8CyE8cLxxEbGH43I5o0xbuDh5udlncxPQ2/njqJK1mZKsgb2riJqreWQDfA01O1Ult+8rh6jSvZmaju5YM7mzZTreVksaHh/SClLlLjLWUejtJX90ZBAR5fvRK/RZ8qfE+K+PQ0NXDku0MH8eO4SVWiprlSA9+nnnoKM2fOtLhNo0Yl+xgrLCxMfU1MTFRdHQzkert2NwvYTfH09FQXIiKqPBKcfDhsJD7ftwdfH9yPq9lZhfc1DKqGRzp3xdgWrVDZLqanI/raVc3bFw+QW9YIwX3tO2J0sxZ2nUmUoO/TfTdbzNnqdPI1jFnwHRaOn4zmNUIsbnsw4RKmL12MGwW2hb3jWrTCmwOHYGLLSHy8d5fqJmF4Bhnhe1+7jipzaaoePOv6dTy/fg1+OXVC/Q5cbwV+7+7cplrGvTdkBK5lZ2Hmsp+RkJlRGBjqoMPW8+fw9vYt+HLUWDWQ47N9u5GQkVH43N3r1lMDLnrV1z6ZrzK8u2MbVkWfUt8XX1gq12Tc873Lf8aqafeUaMy2PanUwDckJERdyoN0cZDgd/369YWBrmRvd+3ahYcffrhcXpOIiMqONOf/S+eueKBDJzWVKy03FzV9fdEqpKbdBImS2bOFIaR4a+AQ9G0QbvfDNwxkLLEc/5LQ3wouZSDJuun3Wvzd/XPzRpWtLTq2xLLWITXV8ZTnlU8A5CKji6U7iI+7u8o0m3tNqVe+b/kS7L10Qb2iZGyNAz9p3TZ20feqR3D6rZ//z/KVm1+la8ddC783ucfyeLm8escgTLHTjH5GXh6+idpv8YjL7yQm+Rr+OHcWd9hBXX1pOEzYHhcXh4MHD6qv+fn56nu5ZBidWUlJxNKlS9X38iZ//PHH8eqrr2LFihU4fPgwZsyYgdq1a2PMmDGV+JMQEZEtZNGRLECSf3BlNb29BL2GqWy2kozilrizDhP0isTMTM11veYCpzMpySoItLQQTrKmtg6hmNOr723vCTm28l5pVK26xfeLlC7svhhv9jVlv+PT0pCak2O2tZkKmM08v+G+FzasVV0q7NH6M7HIvnFD0/t22cljcHQOE/jKIIr27dvjpZdeUsGufC+XvXv3Fm5z8uRJNaPZ4JlnnsGjjz6K2bNno3Pnzupxv//+O3v4EhFRmZCxwbYyBFOOxM/do9QLzSSDv+HsabP3H0uyPTCU+tobBfk4mpRYou4R86MOaJrSVtqfXYJveS17dCUrS1NLQHnfJmVkwtE5TFcH6d9rrYdv8Te9vNFeeeUVdSEiIipr0Ve1TVozJiGGr4cHHEnfhg1V4FraFldS8mCOLYl82VQWnEldrlxEw6AgPNixCya2bK3pUwFplSZZ2PLuEywko/xbzCm8MXAI7E2Ap6emLLsExzId0NE5TOBLRERUmc6mJGPh0cM4k5wMd1cXdKtbH64uJSsAGFTB09ZKq7q3D8Y0a4GlJ45ZHSVtjgRXtf3NdwVoE3pzUbrWBYLFa47PpaTgufVrEHP1Kv7Rp5/V57FUolAesi0E/ZXpjoaNNJ3UyO9vWJOmcHQMfImIiCy4np+Plzatx4Kjh1WdowR+Uie4MvqUChhsaWUm28qCKwkiHc2Lffrj2JUknLhyxeY6XIOxzVuavU/qcbvWqYs9Fy9YfH7DPcW3MFz/8uA+dKtXDwPCIyzui/zuGlerjtjkaxUSAFf39q6AVwFyblzHL6dOYsXJ46obSg1vX4xq1ly1XvMyMRUx2McHY5q3wJLjx8wed8n2yv7LmGZH5zA1vkRERJXh+Q1rVaZXGLKdhtyYZMm0Bk0SNEsrqI+Gj3LIqV+yzwvHTcbDnboU+chbgqJ6AYFWHx/s7W21W8PcPv3hXsp2WXKcvzm4X9O209taH4BSVkspJ7SMRHmT0o3eX3+hJgluP39enaRsOx+HZ9atRp95X+C4mQV2L/W5Qy0GNFXr63prcMdXo8bCU+PEPnum05d0lqCTkBZoMupYFs0FVIHGzUREpN3xK5cx4of5ZfJcfeo3xBPdeqBt2J+95R2VtAGLuXZVZcPrBgSqoPjx33/F77ExZh8jIVU1L2/8NnUGapoZ7HA4KRHjFv1QJuNyj//lMauBmpQfjF/8I05euVx4MlM86JOAPTI0DBvOnC5xZtjdxRUb77nPYqlHackAjuE/zEdmXp7JchT5Wfw8PNXxr+XvbzJT/NWB/Zh/6ACSMm8uYvN0dVX9smV6Xf3AIFSFeM3xQ3ciIqJysuDIocLyBmuCvX3UR8vGpQ+RNWvi3nYd0blOXdQpFvRI0CU9YH093BHkVTEfg5cVD1dXtAypWeS2Sa3aWAx85Zhcy8nGoO/m4a1BQzDExMfmb23bXKLuDKbk5t+wGPjK8V907LAaX2wc9MrvzzD9rUlwMD4bMUYFih/s3qGGqUjfWwNPVzfk5d+wGBDL83125+hyDXqFBK3mgl4ht2fk5WJe1H4816vvbfdLGYT0zZYg90J6mjr5CPPzV6U5VQkDXyIiIjOOX76sKejV3RqhHF6tmlr8JoGhDFIwNaZXssj/27cHv0afLMxstgurhfvadcCIJs3sqk+xLd7avkXz0I+HV67A63cMwiSjoQ5xqSnqY/my4OPmDl93850zkrOzMW3pYpXpLU5/azGfDMXo06Bh4e/jiW49VZnH5nNn1QmLnKz0rt9A9QF+ZOUvyMm/vRduoKcnvhh1FzrWqoPyJO8jCeKtvVfz9Xp1MvdMj95mJ7DJ7fae3S0NBr5ERERmaO3aoL81aKN3/YbqYmlYgAR9ktU0DlIOJSbgb7+vxK4L8Xil3wCHC34laJWA3hYvbFyHPg3CCz92j76qffSzJZKhH9+ylcXRun/7/VdEX71iNlMrmfvFx46gb8Pw27Kig4tlqvs3bIRt983GT8ePYFVMtJrwVtvfX41PHhTRWJ0ElbfknOwimWhL0vPykJKToxa1OSMGvkRERGZ00dBlwKBDrdoW75ePj2Vsr/SPLf5shuf//nAUWtQIwdTItnAkPxyOsvkx8hMvOHpIZVJFWQT7UqIggaaUl5gjC7ysZZbl97Eq5hTWno7B7zHR2HAmFrn5+ajl569GD09s1RoBnn8u8Kvm7Y0HOnRWl8ogtbi28KiAYNxesasDERGRGZNb/flRvKUMY8datdEsuIbV4NBaFwgJ/T7fv6fM6lwrimQ6bSXB5aazZwqvR4aGqmOpJbiVJnLFOxDIdS83N3w5aiwaBAVZHFOs5XXEg78uV23BUnNzkXPjhurl/PrWPzD423k4nWz78JLyIkG4nDBZm0LnotOhZUhIuXQVkfesnFRIKcj+SxfLZIFieWDGl4iIyAz5GP7Znr3x+tbNJu+XAEoWUP2z/0CrzyUBl7XMsdwbl5qKE1cuo0WxxWOVSYZFLDl+FIuOHkZiZoaaPDe8cVOVmZZ6UFkgVhISTBqE+PhiaOOm+D3mlMVaVTmGX4wcg0OJieqYysf80mN2XItWmNgqUj2PJVezszXtm2EPjPdFb1QKcffSxVg3/T67Wfw1s10H1cbMkgK93mI2vKTk9/DR7p2IMToZCPHxUa/1QIdOFstOKhoDXyIiIgvk42tZKPX29q1Izc1Rgw8kgJBL0+AaeGfQUDSvEWL1eVJzik4as0RqMO2FBOHTl/6Ea9lZhcFfck4OvjywT13eHjRMdSyQBV+2kJOGRtWKLv6b06sPdsTHITUnx2zwO71NO9wRHqEuj3frcdv9Ukoi9cYyHjnU1++27K+M6NXZNHbkdrJvCRkZ+OXk8SIL9CqTDAdZdzoG607HmvzJ5CceHNG4zIenfLh7J97due22XPPlrCy8vX0LohIT8OGwO+0m+GXgS0REZIVkNiWjKIvTTicnq+C3e916NvXklayk1sxodTtZeCTdDySzKYFo8WDKEJg+teY3ldk7kpRo03PL441LSeSj8vjUVETWDL1Zg3vr+eXjeTnJ8HZzw4Mdu+CvXbqZfD75aP2rA/vw9cF9SLzVh9bQMUM6bsgiNDGscVPVlqy0JNBbeOyI3QS+Elh+OGwk/rtrB76J2o9MoxHJfh4euKdtezzWtUeZBqB7L15QQa8wFWzLbWtio1Xt+gwNw0IqAgNfIiIiDaSkYXiTZiV+/NgWLfHB7p0Wyx0kmIqoVh1NqwfDHkiLrORsCXot7LNOh6OXE1V29UpWpqb2b5LtlZOG3g0aFmZpZUKedFIw7pssx0OOV3hQEL4fOwlhZgZfSNAr3TJkEVrxV5eOGbNWLFXlKNMi2yKiWjX4uXsgo4TlGQbyOpfS02FPpLPI0z164ZHOXbEl7qzKzFeXtmsNGpgcV1xa30Qd0NTn+quD+1Sm3h66ldhH3pmIiKiKk24Asvr+5sfspkn48FCnLnYRIIgFRw5bHTMsgam0YXtv8DDU8PFRP525vTcsKmsTGqbqdA0L1P6za7sKes3V1J5LTcU/Nqwxuw+S5TUV9Br2T8zduA6HExMwfdnPyCpl0GucSbVH3u43265NanWzpVp5BL1CPgHJ11i3fjY1BfaAGV8iIqIKUNPXD1+MvAuzflmqRv0aBwyGrNlDHbvgruYtYS8SMtJtyoivvvteLD1xFD8eOYSL6elwd3FR9b+5sohNBzQKqq5OACTTawh6ZeHcF/v3WnxuCV43nj2DY5eTbpsYJ9limVpmLc8sr/fPzZtU5wG9hnZfMpbZ2vMNb9IUzkqv19/8vWqUY1R6UZkY+BIREVWQ7vXq47epMzDv4H6V4cy+cUNlR3vUq4/72nW8bWBCZZP2YNK/VtO27u5q4dg9bTuoi1bSL9dakGk4Ofjp+FHMLRb4yuI76TRhjZxY7E+4qGmf5MRES+Cnpd1dVaXT6RDi64sko3pqs9veOvGzBwx8iYiIKlDDoGr4v34D8GKf/moBkgSX9jpQYGCjxlh24pjVj7OlvrekdclSJysLrqz1fZWs78X0tNtuN17EZY2WQSRCr3GbT/buQlxaqso6S2cPyWY3qlYdzmJyqzb4cI/lunU5YenbINxuJsUx8CUiIqoEEuxJhtSeyUr8n48ftbrdtNZt1HaHkhJVJrRVSE2MatZCUw2s9MHVEpBKaYGPiVpVcwveKsJ3RhPrdsafV+3dprZuo05spPNHVTctsq1a4Jael2vyd2hoGveXzl1hLxj4EhEROSgJNqTv7amrV+Gik7HJdVQ7sLKidcLZh3t2Ia8gvzDY+7GgAK9u2YTne/XF3W3amX2c9AaWfrhaAl/JOg8Ijyi8npKTreqIZcFgu9AwFXRb7pihQ6CXp8nWbGXBkBWX+mY5qXm53wBUdSG+vvj2rvGYsewndVyF3uhERd4/7w0ZYXWcd0Vi4EtEROSA1p+OxcubNyA+LU0FGZJplaBDsq3/GjC4SAAs98mq+pTsbAR6eSE8qJqmzhHSD1ZLuyoJeoVxuYJMZZu7ab363lTwK0Mmpi9ZjJRc7cM6gn281eM+3rNTjUk2BLpBnl5WP26X7Pp97Tvh3R1bUZ5kL747dBD3t++EeoGBqOpa1wzFxhmzVP314qOHkZSViQAPT4xo2gxTW7dFnYAA2BOd3tEGglewtLQ0BAYGIjU1FQF29ssjIiLn9Fv0STy66lf1ffF/xCUIdndxxYLxk9A2NAy/nDqBT/buVovADJoF11DDIEY3a24xAG798fvIulG61fhSw7xr1kPwNyrrkE4OA+Z/qSbUaen7K2Qvg7y8kZmXqx5T/HGGj9Ul52xcLexyK9P77V0TVMA/fvGPOHX1iubXLQkJtGd37Iy/9+hdbq9BJYvXqn4BChERURWSmZeHZ9atVt+b61t7vSAff1+zCu9s34rHfl+Jk1euFNlGAr8n1/yGt7ZvMfs6smCrtEGvkJZXy04eL3LbkuNH1YhjW4LPm6OSs3G9oMDk4/S3yhma1qih+glL7bAsJHymZ2+sm36faoMm/W2/HzsBveo3QHmS30Fs8rVyfQ0qGZY6EBEROZAVp04gy0onAwm8YpKvIWbvLnW9+BAKw7XP9u1Bp1p1MKDRn7WzBj/dGihRWlLvKv13DTafO4vXt/5R4jpbS4+Tn/NcSgp23f+w2YV1kjX+evQ4fHvoAF7atAHlQbLP0sOY7A9/K0RERA5EugcYhj+Uhf8d2HPbbT8cjsJzG9aWzQsYRarrTsfgvhVLVNa2vEhv5G3nz1ndTupPpSOELcdSFtJp/ZE7165b5DYJyKUue+PZ07ialaX5NalsMeNLRERUQtKDVoIsWchVNyBQfYRe3m2spAShLMtTd1+4gIy8vMIMaXpuLl7ZvLHMnv+GvkCNKM65cR1PrVmlFtqVN/kZtGSi3xk0DPcs+6mwPtgcub9taC1MbhWJf+/cissWAlfdrSl2hgl8hxIT8Na2zdgef/7P19bpMKJJMzzbsw9q+fvb+NNRaTDwJSIistHlrEzM3bgea0/HFOkmEOLjgye69cTk1rZP9DqTkqwyrTKaV+piG1Wrhimt22Jgo4giwXRE9eqQJGVZxo8nriSh060M5fKTxzVNUtNKeu+OatocK6NPIT0vDxVB65QwmZj33V0T8PyGter4q+yvXl9kcZyQQ30o8RIOJl6y+HyG3PEbAwarxXySnZfAunhNslxfGX0S2+PjsHTiNLvrfFCVsdSBiIjIBleysjB24Q/qY/viLbQkEyhB1Ed7dtr0nF8d2IeB879So4xPJ1/DhfQ0bDsfh7/8tgJjF35f5KPx0c1aaJ5AptW607GF3x9OSizT557btz98PTyw68J5zX2BSyPY2wfd69bTvH3XuvWwbvq9+HHsRDzRrYcavSydIIrTUpwR5uuHT0eMVsM75ORFfn8S5Jr6fcntydnZeHrtKs37SqXHwJeIiMgGb27bjISMdIsdCf69Yxuir17V9HySYZVhD/Jsxs9pCJakb+2sFUtUiYNkYuduXKfpeUN9faFVQmYGSurhjl0Q6OmlvpfMtCE77e/hgTcHDsHEVpHq+o38ktX1GoLlCS1aoY6fv9Xg+aFOXeBu4whoaekmAXB1bx+1cLCgBEvvJFs8qnkLDIporK5LRlfatVk6SZHf964L8ZrfK1R6LHUgIiLSSDJ0K04et9qGS4Kz7w8fVKNrLZGg6N9WBirIa8lUss1xZxF77Rp2GNWKmiO1qBL8fXvooNVtXYuNApYBGIuhnfTI3TnrQaw5HYOohATVWUGeY3iTpvAyel4p0dAaTjYIDFKtx6TIQGpr745si1Y1Q3E2JRlTlyxCYkZGkecyDNmY3qYd7mvXQdNryInEpnNnVHlJ9LWr8HBxVaUY1up9Lf0uFxw5jGd69FaBtDy3BMPWsvOyzR/nzqBJcHAJXpVsxcCXiIhIowMJlzR1JJAgTAJVa/ZevKAmr1kjgd2Phw+p7K+1oEzyrZcy0lWtsZbAV/a1f8NGhdcl82mLqMREtZhrZNPm6mLO+Bat8d7O7Vafz8fNDb9NnXEr8C1K+vKumnoPFh07jO8ORamSEMkw96rXAPe0ba8WF2qZSJeWm4P7VyzD3ksXNE2m0yo1NweZ16+rhYJS6qClJEUC3+wy6JdM2jDwJSIi0kgGQ2jeVsMCsfi0VE3PJYFZzLWrKtCzRsJyqQ/+atRYNbZYeuiaC+wk6Krp44v+4X8Gvmtio2ELaz2FDUL9/HB/+4743/69FoP3p3r0Nhn0GsjI5Qc6dFYX6RChJdA1Jo956NcVOJBwUV0v6wluHrfKLOr4B2gKqmXMc13/qj/a2F6wxpeIiEgjGXmrhQQ8jasHaxrna2tApYUEU5Jt/O/QEar+1lRdrNwmfWk/GTGqSNeIuNRUzb1tZat6NnQkkBG+kpk1vL6BvJ5c/talO2a0aaf5+WwNesWeixew88L5Mg94Zf+71K5b+Hsa37K1pteQCXNDGjcp030h85jxJSIi0qhpcA20DQ1TnQ+sLVqaFtnW6vN1rVNPBZ0SqFoLqgY2aozTKclWtxW1ZBGYi4sqDVg++W41mvi36JOFgZiEi/0ahuPpHr3RLLjGbcG4dDXQssBLfyvA00r2aW7fOzC9bXssOHIIR5ISkZGXi8y866qd2Pu7d+Dz/XtUD9x723XQdPJgq0VHD5dpeYOBvB9mGtUXy4jkAeERamCFpffKw526qODXXJ/ohUcPF3baaBMaikmtIhHmx96/JaXTV0QnaQeWlpaGwMBApKamIoB99oiInN6O83GYvuwn9ZG5qX9AJaiSgQ2Lxk9WgZ41MtTB2oI5CY633Tsbr23dhJWn/gxgTZGg9snuvfBI5663tWE7fjlJBWGykKq2v+l/06TU4aGVK6BF25phWDp5Gkrq0727VVBePBCV6xLsfzJiNO4wKsMoCxMW/4h9l26WOZTp87Zsrfr3GmehM/Py8NDK5ar0xPhnNHwvgfKLvfvdlrmW95acBHyw+2ZbPEPgbMjEP961h/r9liTj7ezxGjO+RERENuherz4+HDYST6z+DXn5NwqDX0Mw06FWbXx+5xhNQa94oXc/VW96PjX1toBWd6vHwFsDhyDE1xcPd+qK1THR0N8qZTBFbt1wJhZtaoaid4OGhbfX8PEpct2cO8IjVCs06UlsKVMpmeFvxozT9DNKIJeWm6uy1UFeXurYSB9kCXqFqQEPcrn/l6XwdXdXgyamt2mPnvXqlzrYs1Q/XJxxsBoRVA31g4JU0Cw/i3Hf4NkdO2FW+0637Zv0L/5mzHhsPncW3x06qBYnSvAqfYbvbtNOnSCZ8sne3fjvrh233W74fby7c5sqqZjdsbPmn4VuYsbXCmZ8iYjIlNScHPx0/Cg2njmtFng1CApSH0N3rVPX5uAsJScbb27bgqUnjhWZmiZtwZ7q3kuVJRhnnGf/uhyZ181PQZPgSv55f/WOQZhSgily+y9dxLQli3GjIN9kdtnL1Q0/TZiCljVrWnwe+Vnko/pvZDBHSrK6TQLfqa3bYsu5szh65WYGWmsAKsf3tTsGaa5BNjcs5LVbfZMtkVdYffdMuLu4qiC/pq+v+r1KtwaZyCYdHKTvr/y+be0bbO191fXLT61Oz/N0dcPu+x9SE+IImuM1Br5WMPAlIqKKIkHP/oSLyL2RjwaBgWgRUtNsO67n1q/Bqphoq8Hbyqkz0LxGiE37cTkzE1vjzmJ+1AFEGU1yk+fr06ChylJHWKm/zblxHfctX6omtgnjYENLf1tzHuvaHY917YHSHOPuX36GXKNsvalAW1q8fT5yDCqaHPOX/9igKTB/ud8AlTkmsNSBiIjI0UirLuOeuub4eXjiSFKS1WELEmBKL1/JkmoRlZiAD3btUAuyDM9bzctblRoMahShyjjqBmhrvfXPzZuw+2K8yf0rzchlaYcmrczMLQjTcozfGzocj/z2izp+xfdFgt6avn549Y6BqAynrl1VpSDWFjHKNtLijmzDdmZEREQORia4nU9LtZoVlPKAVdGnND3nhjOn1cIvmSJm/LzJOdlYFXNKDYyQOmEtrmVnYfGxI6UKcM2RshKpDy6NIRFNMH/MeNXnuPgiQhnCsWzSNBX8VgZ3jbXhQmsdOf2JGV8iIiIHIy3AtMrSMBXsalaWyoDKGF9zGVopwXhn+za80Kef1edbezpWU9u1kpCMbEJGhtn741JTVI2y7LO0n2tdLLg1kCz20knTcPLqFZxOvqZGFrevVUvV7VamTrXq4JuoA1a3k+PbuXbdCtmnqoSBLxERkYOp6ac9G6klSyvZWVlMZSk/K4Hkj0cO4YluPVS3AmuL9cqjV65hP0y9vgSvUhu7Je5ckdtbhoTgH736qW4cpkgf4+K9jCvToIjGqO7lrTLt5o6elGgE+/hgYKOICt47x8ccORERkYORcbiSGbTW3UDul04I1kgpg+muxEVl37iupp5ZE+TlrSnoNey9LV0apLPCHcXqoKXW9a6F32P7+bjbtj9x+bLqu7z+TCwcgbQpe2fwMPVz3mxnV5S6VafDvwcNKzJxj7ThESMiInJAMsDAUg2tBJPSA3dyK+vtzDLyzLdGK8m2shBOS1Ame/9wxy7oEFZb02tLFnlQo8ao5e9/2xAQqf01FWxLwYU0sJK+y9nXrZd92ANpX/f16LGoFxhQZKSzqB8YqPona+nJTLdjqQMREZED6tswHK/0G4CXNq1XQZFx0GcIemV4ggy+sKaWnx/OpaZoWowWqmHRl9TJyiQz6eFr7jkliJUOEU9276kWaSVnZ2NHfByeXvM7rpvoHyzb1w8Mwr+KdaiQsceGkb7m6G8F7CtOndCUAbcHves3xMYZs1TP4KOXk9RtUq9ckj7R5IAZ39deew09evSAj48PgoKCND1m5syZNz8qMLoMHTq03PeViIjsk0xH+3D3TrywcR3e2LZZLYJy5Hb20sP11ynTVZAZ6OmpOgLU8vPHo126Ye30e9EurJam5xnfsrWmoDfMzw+da9fR9Jwv9umHLrcWXxUP0ySIlYlnX40eW9iZoJq3N4Y3aaZGIA+OaFyk/MHPw0ON910ycaraztjWuHOaSiVkm23ni9b/2juJW6Q2+f4OndSlW916DHqdJeObl5eHCRMmoHv37vjyyy81P04C3a+//rrwuicnnBAROR35iFsGPvxy6oQKgCR4kDjv83170LJGCD4eMUplEx2RDLn414DB6lJSwxo3xbs7tuFSRrrF2txHOnfT3ELLy80d88aMwyKZ3BZ1ALHJ1wont02LbIsZbdsjxOf2bLQsNPto+ChcycrCudRkuOlcVHcGc6OGZVGellBQAvuc6zc07TuVTmJGBi6mp8HL3R1NqgfbVS2ywwS+L7/8svo6b948mx4ngW5YmOlZ2EREVPVJ26fZvy7Djvjz6iNvFdgZBXfSzmr84h+xYvLdCPMrWjvqLDzd3DD/rvGYumSRClqE4QgZujM81LELpto4/lgWaklWWgLd9LxcXM8vUIGvluBZulFo6Ugho6K1do8orxZrdNPeixfwwe4dKgtv+I3U9PFVJzmSsZb3Q2WznxC8nGzatAk1a9ZEs2bN8PDDD+PqVctTTnJzc9XYO+MLERE5rtUx0dh2Ps7sR/kSNEl96Yd7dsGZNQyqht+nzcQ/evdT30uQ4ufugaGNm2LBuEl4pmdv1T/32OUkXEi37d9GybAHeHqpFlxlPXShe13TbcpMuZiRXqavTX/6LfoUJv+8UHXWMP4/LSkrE//esRX3rViC3BuVn3F3mIxvSUiZw9ixYxEeHo7Y2Fg8//zzGDZsGHbs2AFXM2cdr7/+emF2mYiIHN/8QwdUeYOlGlYJfn8+dgRzevZR9aTOKsDTE/e176guxtbGxmDcoh9wIOFS4W1taoZidsfOqi7XmrTcXCw7cQwbz55RZSf1AgNVXbLUC5e2ZjXBhmD2XEpyqV6LzP8Onli9UtXLm8qpy/95skjvwz078VT3XnDajO+cOXNuW3xW/HLixIkSP//kyZMxatQoREZGYsyYMfj111+xZ88elQU257nnnkNqamrh5fx56/0KiYjIfsmqfy0Lt3Lz89UQBCrq4z278ODK5YhKTChy+5HLSfjrql9VbbAl0j+3+5efquESm8+dwe6L8SoIluzgtCWLkZabU6r9k1IMrWzpF0zayWATOXm0NgDl20MHKz3rW6kZ36eeekp1XrCkUaOiTapLQ56rRo0aiImJwYABA8zWBHMBHBEREdTH1u/s2Kq+L37yYLguWby2YWEYEH77FLHdF+Lx4K/LVSbQ+NGGmtw9F+Mxa8VSVUpR0hKIRtWqq9ZtmVZ69EqA3F5jlwtTLmdmYl7UflU2k56bi9p+/ugf3gjjW7ZSZRzObFX0KU0nl5L533fpohoX7ZSBb0hIiLpUlPj4eFXjW6tWyd/4RETkWKT3qfxja+0fZk9XV4QHVauw/bJn+QUF2Bx3Fi9tXK86JuitBJRfHdhnMvB9e/sW9dXc4yUAlt/NxrOnMbBR4xLtq3R7mNgqEvOjDlhc5Cb3TW/b3ubnlwzl3E3r8dOxI0V+jjMpydgWH4e3tm3GGwOHYEzzlnBW6TYMQMm0YVunXtwWFxeHgwcPqq/5+fnqe7lk3Fp9Kpo3b46lS5eq7+X2v//979i5cyfOnj2L9evXY/To0WjcuDGGDBlSiT8JERFVpBlt2lsNeiV4G9uiFfz5iZ8aBtHvmy9VJjY+Pc3qIGMJKKVjhmTzjMVeu6rphEOO/XeHoko9xU76F5sre9DdmiYnU99sPQF4aOVyLC4W9BrLKyjAk2tWYU1sNJxVLX9/TS3lRE0/6wNQypPDBL5z585F+/bt8dJLL6mgVr6Xy969ewu3OXnypKrLFbJ47dChQ6rGt2nTppg1axY6duyILVu2sJSBiMiJDGncBD3q1jNb3ynBUpCXN/7auRucnbR2m/LTQtXP11YZeUUD39PJ2haSSeAcc81yxyUtk+J+mjgFXercHJghv2vpHSu/cfkq7dQ+GDbS5hrfVTGn8Me5s5q2fXXLJk0f91dFE1q2tnqCJEe+YVCQWhRZmRymq4P077XWw9d4+o63tzdWr15dAXtGRET2TAKf/428C3PWr8GvRgMsDH1dZTjCx8NHqayVs3tj6x/Izb9hcwAnJw/VvIpOVHNz1Z5bs2Vbc2r6+uH7sRNVEL32dIwaUSzjlUc0aabaqJXE/KiDVks9DOLT0lTngsqsX60so5u1wAe7duByVqbZchO59W9dulf65DmHCXyJiIhKSupA/zt0BJ7q3hPLThxHYmaGalsmo3E7hNWu9H+M7cGFtDRsPndWU5BXPOiVyW/FJ6u1C62lTjqsDY2Qx/es1wBlpXH1YHUpLUmmHUy8ZNPxkKDbGQNfH3d3fHvXeNWlQ4Jf42NmGIDyZLeedlEHzcCXiIichowl/lvX7nAEsqhqZfRJLD95HNeys9UUs1FNW2B4k6Zq0lpZO3Hlss1Br5DHyFSu4qp5e2NU0+Zq/60tOpPpbvbI+JNkLcp6OIcjiagejNV3z1T10D8cOYRL6WnqfSqLHqe3aYd2peioUZYY+BIREdmZ45eTMHP5EpU9MwzfkK9Sb/rmts34esw4tKhRcV2RTDEsJHtvyHC0CQ0zuc2zvfqohW9JmRlmg99Hu3Sr9J/FFPkUQMpgjl+5rPkxMpDDmQV6eamTIFMnQvbCeU9NiIiI7NDF9DRMXbIY17Kz1HVDva3h69XsLExbssimiWVaNKqmvZWbm84FU1q3wapp9+DOps3Nbhfi44ulk6aiX8PwwlX/hgVmUhP8f33vwONde8BezdCYiZafqGOt2ipQJvvGjC8REZEd+frgftUhwVyGVG6XAQrzDu7HnF59y6ys4pm12heE/zBuIjppzG7KojNZXCg1xFviziL7xg3U9Q9QwbC7qyvsmdSkfnc4CscuJ1ksA5GP9F+9Y1AF7hmVFDO+REREdkIWgi08ethiTayQ+9WYWCsLx0T29etq3PD+SxeRnJ192/3xqakYteA77Eu4qGkfx7VopbKbtqoTEIDJrdvg3nYdMCiisd0HvYaAVhZtdbewYE2yvEsnTUMzZnsdAjO+REREdiI5J1u14dI6LSs1N0f1sDX5XNnZ+GDPTiw6ehhZt8b5Sl2utPeSBX4yZveFDWux5nSM5v2r5uWF1wcMdqouGNLj+bu7JuBIUiJ+Pn5UZX/z8vPRMqQmJreKRKSZ+mayTwx8iYiI7ISMTbaFu4vp7WVR3IRFP+JCelqR7LF8L50i1p6ORYCnBy5nZtr0esk5Obien6/alDnj6Gu5kGNzvncuERGRnfL38FQfmVvLp8pMMumEYG7E8rNrV98W9BrIbTk3riMxMxPWCyVud11DeQWRvWLGl4iIyE5ICcHMdh3w3Po1FrcrgF5tZ8q5lBRsOnfG4uNLOli3urc3/D08UNWdTr6myhoSMjLg6+6OgY0ao1f9BjaPPCb7w8CXiIjIjsjisbWxMdh49rTJAFVCLxkKMNbMFKz1Z2ILe/+WJXnduyPbVen63sy8PPx97e/4PTa6sE+x/LzS2aFBYBA+vXM0F7E5OAa+REREdkTqZz8ZMQrv7tyG+VEHkX3j5sI0w2jYGW3a44luPcxOCZPFceUR+Nbw8VUTuLRMO9t1IR7fRO3Htrg4XC/IVxPzpkW2VUG9r51mjKWjxuxfl6l9F4VlIre+xqelYtLiBVg++W40CAqqzF2lUtDpbZ3H52TS0tIQGBiI1NRUBAQEVPbuEBGRE5FuDH+cO4OUnBwEeXmhb4NwFfxaIu3QrJVK2MrHzR0rp86wGvBJSPHK5o34JuoAXHUuyNffrAc25IjrBQTi+3ETUcdf+7+n0kFh3elYxCZfVc/ZtW5ddAirXeaZ59+iT+Gvq36xuI1kgUc2bY53hwwv09emiovXGPhawcCXiIgcSVpuDrp88akKGMuCh6srlk2ahuYaxgp/sX8v/rX1D4vbhPn6YeM9s1SPXGukFdsb2zarwF8y4RKySCa2SfVgvD1oqNlRySUx5eeF2HPxgtVMuezHrlkPoZq3d5m9NlVcvMauDkRERFWI9OeVhW+W8qFaF2nJYrYfx07UFPRKoP3J3t1Wt0vIzMCgb7+22kpNSiXmrF+jgl5DKYKh/CA2+Rom/bQQh5MSUVakP6+W8hDZD3l9ckwMfImIiKqYp7v3Uh/JC8MiLeOAt2VICP47dLgqmzAOgXVGgype7T8Q2+6djfYap7RtjTunBnBoIa3Wpi/7SY1KNteH+NXNm8w+XgJUqR1+vgxLOnRWm8gZbVt11/dVeVzcRkREVMXIx/HvDRmOMc1bYn7UgcKP8JsEB2NGm3ZqepuUGvRt0AjLThzDhjOnkXk9T9XgTmwVia516tpcQ5uUmaF5W8mrnrp6BatiTql9LG7R0SNWW67Jz3P0chIOJSaUSclD+1q1VPBubVy0lH40qc7ODo6KgS8REVEVJIFrv4bh6mJOgKcnZrRtry6lZWu3Bsk+f384ymTgu1dDra2Q0HzfpYtlEvhOb9Mef5w7a3EbyZ5LGzk5buSYWOpAREREpda7fgO42zDKWALbMynJZu4r0Bzc55fRJDk5QRgS0dhswYMEvdW9ffBY1x5l8npUORj4EhERUakFeXljbItWNlTKAu4uriZvlyERxrXJloLnZjXKpuxAMtD/HXonpka2Va8t1yWQN+xHZGgYfp44BaF+fmXyelQ5WOpAREREZeKF3v1wODEBx65ctrqtBJR9GzQ0ed/k1m3wxYF9Fh8v4Wht/wD0rNcAZUXqd//ZfyD+1rU7Vpw8gcSMdPi4e2Bgowi0rhlaZq9DlYeBLxEREZUJqfNdNGEKpi1ZhKjEBIvbyiIyc5PgGlWrjrsj26oaYEuVvi/06ae5NZstQnx8Mat9xzJ/Xqp8LHUgIiKiMiMt0r4ZMw4R1apbDEof69odrSxkUef2vUMFxrpb2WH56nLrq5ebm5qeNiSiSTn9FFRVcXKbFZzcRkREZLvUnBy8umUTlp88roY+GNT09cXjXXuocgYt4tNS1RjmmGvX4OaiQ5c69TCmWQv4s7MCGeHI4jLCwJeIiKjkrmVnYdv5OGRfv45a/v7oUbc+XG3o/kBUlvEaa3yJiIio3EgLMMMUOaLKxlMuIiIiInIKzPgSERERORgZ+bwz/jzy8vMRXq0a+jYIV6OqyTIGvkREREQO4nTyNTy3fg32XLygOlzI9DoZ5BHi44Nne/ZRQ0TIPAa+RERERA4S9I5d9AMy8/LUdelOYOhRcDkrC0+v/R1pubmY2a5DJe+p/WJOnIiIiMgBzN24TgW9MvzDnNe2bEJCRnqF7pcjYeBLREREZOfOpCRje/x5i0GvkHsXHDlcYfvlaBj4EhEREdm5PRfiNW0n9b474uPKfX8cFQNfIiIiIjtnPP2uLLd1Ngx8iYiIiOxc4+rBmrZz1enQNLhGue+Po2LgS0RERGTnOteug/qBgaqFmSVSAzw1sm0F7ZXjYeBLREREZOekX+8/evWzuI2LTodhjZsgsmZohe2Xo2HgS0REROQABkU0xr8HD4OHq2uRzK+UN4jhjZvi3cHDK23/HAEHWBARERE5iDHNW6Jfw3D8dOwotp+PUyOLI6pXx+RWkWgRUrOyd8/u6fSGkR9kUlpaGgIDA5GamoqAgIDK3h0iIiIiKmG8xlIHIiIiInIKDHyJiIiIyCkw8CUiIiIip8DAl4iIiIicAgNfIiIiInIKDhH4nj17FrNmzUJ4eDi8vb0RERGBl156CXl5eRYfl5OTg0ceeQTBwcHw8/PDuHHjkJiYWGH7TURERET2wyEC3xMnTqCgoACfffYZjh49ivfeew+ffvopnn/+eYuPe+KJJ/DLL79g8eLF+OOPP3Dx4kWMHTu2wvabiIiIiOyHw/bxffvtt/HJJ5/g9OnTJu+XPm4hISH44YcfMH78+MIAukWLFtixYwe6deum6XXYx5eIiIjIvlX5Pr7yg1WvXt3s/fv27cP169cxcODAwtuaN2+O+vXrq8DXnNzcXHXwjC9ERERE5PgcMvCNiYnBBx98gAcffNDsNgkJCfDw8EBQUFCR20NDQ9V95rz++uvqjMFwqVevXpnuOxERERE5YeA7Z84c6HQ6ixcpTzB24cIFDB06FBMmTMADDzxQ5vv03HPPqWyy4XL+/Pkyfw0iIiIiqnhuqERPPfUUZs6caXGbRo0aFX4vi9P69++PHj164PPPP7f4uLCwMNX1ISUlpUjWV7o6yH3meHp6qgsRERERVS2VGvjK4jO5aCGZXgl6O3bsiK+//houLpaT1bKdu7s71q9fr9qYiZMnTyIuLg7du3cvk/0nIiIiIsdRqYGvVhL09uvXDw0aNMA777yDy5cvF95nyN7KNgMGDMD8+fPRpUsXVZ8rvX+ffPJJtQhOVvg9+uijKujV2tGBiIiIHJs0r9p76QK+OxSF/ZcuQg892oaG4e7IduhWt54qqyTn4RCB79q1a9WCNrnUrVu3yH2GbmzSwUEyullZWYX3Sb9fyQxLxle6NQwZMgQff/xxhe8/ERERVbwbBQV4dt1qLD1xDK46HfJvxQyJGRlYFRONoRFN8J+hI+Dh6lrZu0oVxGH7+FYU9vElIiJyTK9u3oivD+6HuUBHcr0TW7bG6wOHVPCeUVmr8n18iYiIiMy5kpWFb6IOmA16hdy36NgRXEhnz35nwcCXiIiIqpzlJ49Dy2faUuO75PjRitglsgMMfImIiKjKkSyui4v1hWsu0CGeU1qdBgNfIiIiqnK8XDWu39cB3m4OsdafygADXyIiIqpy+jUMV10drJFt+jX8c1gWVW0MfImIiKjK6Vy7DhpXD1ZtzMxx0elQxz8AfRo0rNB9o8rDwJeIiIiqHFm09uGwO+Hj7m4y+JXbpBzi4xGjVABMzoGBLxEREVVJTYNrYNnkuzEgPKJIcCvf9WkQjiWTpiKyZmil7iNVLFZzExERUZUVHlQNn945GgkZ6Th6OUnd1rxGiCpxIOfDwJeIiIiqvDA/f3Uh58ZSByIiIiJyCgx8iYiIiMgpMPAlIiIiIqfAwJeIiIiInAIDXyIiIiJyCgx8iYiIiMgpMPAlIiIiIqfAwJeIiIiInAIDXyIiIiJyCgx8iYiIiMgpMPAlIiIiIqfAwJeIiIiInAIDXyIiIiJyCm6VvQP2Tq/Xq69paWmVvStEREREZIIhTjPEbeYw8LUiPT1dfa1Xr15l7woRERERWYnbAgMDzd6v01sLjZ1cQUEBLl68CH9/f+h0ugo5Y5Eg+/z58wgICCj313NkPFba8Vhpx2NlGx4v7XistOOxsg2PF1SmV4Le2rVrw8XFfCUvM75WyMGrW7duhb+uvHGd9c1rKx4r7XistOOxsg2Pl3Y8VtrxWNnG2Y9XoIVMrwEXtxERERGRU2DgS0REREROgYGvnfH09MRLL72kvpJlPFba8Vhpx2NlGx4v7XistOOxsg2Pl3Zc3EZEREREToEZXyIiIiJyCgx8iYiIiMgpMPAlIiIiIqfAwJeIiIiInAID30p09uxZzJo1C+Hh4fD29kZERIRalZmXl2fxcTk5OXjkkUcQHBwMPz8/jBs3DomJiajqXnvtNfTo0QM+Pj4ICgrS9JiZM2eqiXvGl6FDh8IZlOR4yVrXuXPnolatWuo9OXDgQERHR6Oqu3btGqZNm6Yav8uxkv8vMzIyLD6mX79+t723HnroIVRFH330ERo2bAgvLy907doVu3fvtrj94sWL0bx5c7V9ZGQkfvvtNzgLW47VvHnzbnsPyeOcwebNmzFy5Eg1ZUt+7mXLlll9zKZNm9ChQwfVuaBx48bq+DkDW4+VHKfi7yu5JCQkVNg+2zMGvpXoxIkTaiTyZ599hqNHj+K9997Dp59+iueff97i45544gn88ssv6h+XP/74Q41UHjt2LKo6OSGYMGECHn74YZseJ4HupUuXCi8//vgjnEFJjtdbb72F999/X70Pd+3aBV9fXwwZMkSdbFVlEvTK/4Nr167Fr7/+qv6hmT17ttXHPfDAA0XeW3L8qpqFCxfiySefVCfl+/fvR9u2bdV7IikpyeT227dvx5QpU9TJw4EDBzBmzBh1OXLkCKo6W4+VkJMt4/fQuXPn4AwyMzPV8ZETBS3OnDmDESNGoH///jh48CAef/xx3H///Vi9ejWqOluPlcHJkyeLvLdq1qxZbvvoUKSdGdmPt956Sx8eHm72/pSUFL27u7t+8eLFhbcdP35cWtLpd+zYoXcGX3/9tT4wMFDTtvfcc49+9OjRemem9XgVFBTow8LC9G+//XaR95unp6f+xx9/1FdVx44dU///7Nmzp/C2VatW6XU6nf7ChQtmH9e3b1/9Y489pq/qunTpon/kkUcKr+fn5+tr166tf/31101uP3HiRP2IESOK3Na1a1f9gw8+qK/qbD1Wtvwtq8rk/7+lS5da3OaZZ57Rt2rVqshtkyZN0g8ZMkTvTLQcq40bN6rtkpOTK2y/HAkzvnYmNTUV1atXN3v/vn37cP36dfURtIF8pFi/fn3s2LGjgvbSscjHPnKm26xZM5X9vHr1amXvkl2SjIp8FGb83pK55/JxbVV+b8nPJuUNnTp1KrxNjoGLi4vKelvy/fffo0aNGmjdujWee+45ZGVloap9aiB/c4zfE3Jc5Lq594Tcbry9kKxnVX4PlfRYCSmpadCgAerVq4fRo0erTx7ods76viqNdu3aqbK1QYMGYdu2bZW9O3bDrbJ3gP4UExODDz74AO+8847ZbSQw8fDwuK1mMzQ0lPU7ZsocpAxE6qhjY2NVGcmwYcPUH0tXV9fK3j27Ynj/yHvJmd5b8rMV/wjQzc1NnYBa+rmnTp2qAhapuzt06BCeffZZ9dHikiVLUFVcuXIF+fn5Jt8TUqplihwzZ3sPlfRYycn4V199hTZt2qikh/ztl7p8CX7r1q1bQXvuGMy9r9LS0pCdna3WJNBNEuxKuZqczOfm5uKLL75QaxLkRL5Dhw5wdsz4loM5c+aYLCw3vhT/Q3jhwgUVpElNptQNOouSHCtbTJ48GaNGjVILbKTOUOo39+zZo7LAjqi8j1dVUt7HSmqAJeMk7y2pEZ4/fz6WLl2qTrCItOjevTtmzJihMnN9+/ZVJ00hISFq3QdRSckJ1YMPPoiOHTuqEyk5uZKvso6ImPEtF0899ZTqJmBJo0aNCr+XxWlSsC9vzM8//9zi48LCwtRHaikpKUWyvtLVQe6r6seqtOS55KNpya4PGDAAjqY8j5fh/SPvJckYGMh1+Ye5qh4r+bmLLz66ceOG6vRgy/9TUhIi5L0lHVqqAvl/RT4ZKd41xtLfG7ndlu2ripIcq+Lc3d3Rvn179R4ibe8rWRzIbK91Xbp0wdatWyt7N+wCA99yIGfsctFCMr0S9MqZ2ddff61qwiyR7eSP4/r161UbMyEfr8bFxansQVU+VmUhPj5e1fgaB3aOpDyPl5SDyD8u8t4yBLryMaJ8PGZrJw1HOlby/42cSEp9pvz/JTZs2KA6rhiCWS1kpblw1PeWKVJWJcdE3hPyiYmQ4yLX//rXv5o9nnK/rLo3kG4Zjvj3qbyPVXFSKnH48GEMHz68nPfW8cj7p3hbPGd4X5UV+ftUlf42lUplr65zZvHx8frGjRvrBwwYoL6/dOlS4cV4m2bNmul37dpVeNtDDz2kr1+/vn7Dhg36vXv36rt3764uVd25c+f0Bw4c0L/88st6Pz8/9b1c0tPTC7eRY7VkyRL1vdz+9NNPq24XZ86c0a9bt07foUMHfZMmTfQ5OTn6qs7W4yXeeOMNfVBQkH758uX6Q4cOqY4Y0mUkOztbX5UNHTpU3759e/X/2datW9V7ZMqUKWb/P4yJidG/8sor6v8/eW/J8WrUqJG+T58++qpmwYIFqrPHvHnzVAeM2bNnq/dIQkKCun/69On6OXPmFG6/bds2vZubm/6dd95RHWdeeukl1Ynm8OHD+qrO1mMl/2+uXr1aHxsbq9+3b59+8uTJei8vL/3Ro0f1VZ38HTL8TZJQ5N1331Xfy98tIcdJjpfB6dOn9T4+Pvq///3v6n310Ucf6V1dXfW///67vqqz9Vi99957+mXLlumjo6PV/3fSfcbFxUX9G0h6PQPfSiStbORNbOpiIP+oynVpT2IgQchf/vIXfbVq1dQfgrvuuqtIsFxVSWsyU8fK+NjIdTmuIisrSz948GB9SEiI+oe3QYMG+gceeKDwH6GqztbjZWhp9uKLL+pDQ0PVP+ByUnby5El9VXf16lUV6MoJQkBAgP7ee+8tcoJQ/P/DuLg4FeRWr15dHSc5gZV/kFNTU/VV0QcffKBOtj08PFTLrp07dxZp6ybvNWOLFi3SN23aVG0vLahWrlypdxa2HKvHH3+8cFv5f2748OH6/fv3652BoeVW8Yvh+MhXOV7FH9OuXTt1vORE0/hvV1Vm67F688039REREeokSv5G9evXTyXK6Cad/Kd0OWMiIiIiIvvHrg5ERERE5BQY+BIRERGRU2DgS0REREROgYEvERERETkFBr5ERERE5BQY+BIRERGRU2DgS0REREROgYEvERERETkFBr5ERERE5BQY+BIRlbOZM2dCp9OZvaSkpMAZ5OTkqGMRGRkJNzc3jBkzprJ3iYicDANfIqIKMHToUFy6dKnI5eeff4Yzyc/Ph7e3N/72t79h4MCBlb07ROSEGPgSEVUAT09PhIWFFblUr169yDbz5s1DUFAQli1bhiZNmsDLywtDhgzB+fPnC7f5v//7P7Rr167wel5eHho3blwkc7xo0SJERESoxwcHB2P8+PG4fPly4WNkW3kNY/369cPjjz9eeP3bb79Fp06d4O/vr/Z16tSpSEpKKrx/06ZNRV4zOTkZbdq0wYwZM6DX600eA19fX3zyySd44IEH1HMSEVU0Br5ERHYkKysLr732GubPn49t27apwHLy5Mlmt//www+RmJhY5LbmzZurIPrkyZNYvXo1zp49i2effdam/bh+/Tr++c9/IioqSgXJ8hxSpmBKRkYGhg8fjkaNGuGrr75SATERkT1yq+wdICKiogGnBLNdu3ZV17/55hu0aNECu3fvRpcuXYpse+3aNbz66qsqqH3xxRcLb5fMq0G1atVU1lfKDGxx3333FX4vAe3777+Pzp07qyDXz8+v8L7c3FyVUfbx8cHChQtV7S4Rkb1ixpeIyI5I4CgBpnH2Vsofjh8/ftu2r7zyCvr3749evXrddt+WLVtUgCqPzc7Oxr///e8i90+ZMkXdb7jI9sb27duHkSNHon79+qrcoW/fvur2uLi4IttNmzYN69evV/dLOQcRkT1j4EtE5ICio6PxxRdf4M033zR5v9TnHjhwAGvWrMHVq1fxv//9r8j97733Hg4ePFh4ke0NMjMzVW1xQEAAvv/+e+zZswdLly4trCk2lpCQoBbp/etf/8Lhw4fL5WclIiorDHyJiOzIjRs3sHfv3sLrUqcrdb5S7mBMyhvuv/9+tbDNFOmeIAvkpHvC7NmzVQBrTBaXyWMNF9ne4MSJEypYfuONN9C7d2+VdTZe2GZsxYoVGDt2rFqwdu+996r9JyKyVyzGIiKyI+7u7nj00UdVTa2UPfz1r39Ft27ditT3xsTEqJID+WrKggULVFeH0NBQlRn+9NNPi2R0rZHyBg8PD3zwwQd46KGHcOTIEbXQzRRDZwoJkqW2WL6+8MILZp/72LFjKmss9cnp6ekq2yyMO1UQEZUXBr5ERHZEFolJNlfah124cEFlXL/88ssi20gpwssvv3xbOzQDqQd+5plnVLeHGjVqYNiwYXjnnXc070NISIjqCvH888+rALxDhw7q8aNGjTL7GGlVJh0dpF+xDKZo3bq1ye2k+8O5c+cKr7dv3159NdcCjYioLOn0/GtDRGQXJNiUXrrOMsmNiKiiscaXiIiIiJwCA18iIiIicgosdSAiIiIip8CMLxERERE5BQa+REREROQUGPgSERERkVNg4EtEREREToGBLxERERE5BQa+REREROQUGPgSERERkVNg4EtEREREcAb/DyRDnp10SxhaAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8, 6))\n", + "plt.scatter(X[:, 0], X[:, 1], c=y_true, cmap='viridis', s=50)\n", + "plt.title(\"Синтетические данные с тремя кластерами\")\n", + "plt.xlabel(\"Признак 1\")\n", + "plt.ylabel(\"Признак 2\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "6dbcd759-c02f-41ca-b7df-c36a78f8ac49", + "metadata": {}, + "source": [ + "**Применение DBSCAN**" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "a765ae38-a2f1-4b5d-b81a-ebd63485c5a5", + "metadata": {}, + "outputs": [], + "source": [ + "dbscan = DBSCAN(eps=0.3, min_samples=5)\n", + "labels = dbscan.fit_predict(X)\n" + ] + }, + { + "cell_type": "markdown", + "id": "c4a3b09b-2600-4974-b584-449f5d8c3592", + "metadata": {}, + "source": [ + "**Визуализация результатов кластеризации**" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "fa83a1e9-6ab3-4406-bae4-30dd881cccde", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8, 6))\n", + "plt.scatter(X[:, 0], X[:, 1], c=labels, cmap='plasma', s=50)\n", + "plt.title(\"Результаты кластеризации DBSCAN\")\n", + "plt.xlabel(\"Признак 1\")\n", + "plt.ylabel(\"Признак 2\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "a322bd81-2c0a-45e8-ba97-450dca238577", + "metadata": {}, + "source": [ + "**Интерпретация результатов:\n", + "Алгоритм DBSCAN успешно выявил три кластера, соответствующие исходным данным.\n", + "Точки, помеченные как шум (label = -1), находятся вне плотных областей данных.**" + ] + }, + { + "cell_type": "markdown", + "id": "2cefd150-9186-40ef-8a16-ec8af853d752", + "metadata": {}, + "source": [ + "# **Часть 2: DBSCAN на реальном датасете из OpenML**" + ] + }, + { + "cell_type": "markdown", + "id": "78648178-0cbc-4e79-b1ee-98dd8c2ebaa8", + "metadata": {}, + "source": [ + "**Цель-применить алгоритм DBSCAN к реальному датасету для выявления кластеров в реальных данных.**" + ] + }, + { + "cell_type": "markdown", + "id": "bdbb1d75-f88c-4823-8492-0ba87e090b9a", + "metadata": {}, + "source": [ + "**Загрузка датасета**" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "d7890642-1e16-48f8-a921-d437118dd4da", + "metadata": {}, + "outputs": [], + "source": [ + "import openml\n", + "import pandas as pd\n", + "\n", + "# Загрузка датасета \"Banknote Authentication\" с OpenML\n", + "dataset = openml.datasets.get_dataset(1461)\n", + "X, y, _, _ = dataset.get_data(target=dataset.default_target_attribute)\n", + "X = X.select_dtypes(include=[np.number]) # Используем только числовые признаки\n" + ] + }, + { + "cell_type": "markdown", + "id": "136f2221-2db5-4bd0-a748-feb6116ec563", + "metadata": {}, + "source": [ + "**Предобработка данных**" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "d135c708-3bdb-419d-9651-a7f5ad4c0ee4", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "# Масштабирование признаков\n", + "scaler = StandardScaler()\n", + "X_scaled = scaler.fit_transform(X)\n" + ] + }, + { + "cell_type": "markdown", + "id": "89840396-9b8f-488b-9669-a210a5715a06", + "metadata": {}, + "source": [ + "**Применение DBSCAN**" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b80856dc-f661-42fc-9e24-10880dd79176", + "metadata": {}, + "outputs": [], + "source": [ + "dbscan = DBSCAN(eps=0.5, min_samples=5)\n", + "labels = dbscan.fit_predict(X_scaled)\n" + ] + }, + { + "cell_type": "markdown", + "id": "0566b5fc-63f2-4b53-812e-60555fb69902", + "metadata": {}, + "source": [ + "**Снижение размерности для визуализации**" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "2d17ec0c-5d49-4ca9-8b60-d2a573c4f485", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.decomposition import PCA\n", + "\n", + "pca = PCA(n_components=2)\n", + "X_pca = pca.fit_transform(X_scaled)\n" + ] + }, + { + "cell_type": "markdown", + "id": "d2b9bf69-111b-421c-b33f-3d4d4d6c7fec", + "metadata": {}, + "source": [ + "**Визуализация результатов кластеризации**" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "8c1ff471-66f4-428b-b2c4-19ed5afcad9e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8, 6))\n", + "plt.scatter(X_pca[:, 0], X_pca[:, 1], c=labels, cmap='plasma', s=50)\n", + "plt.title(\"Кластеризация DBSCAN на реальном датасете (PCA)\")\n", + "plt.xlabel(\"Главная компонента 1\")\n", + "plt.ylabel(\"Главная компонента 2\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "ca380da1-6d1c-4ebb-b918-8e36b17ba4f4", + "metadata": {}, + "source": [ + "**Интерпретация результатов.\n", + "DBSCAN выявил несколько кластеров в данных о банкнотах.\n", + "Некоторые точки были помечены как шум, что может указывать на аномалии или выбросы.\n", + "Использование PCA позволило визуализировать многомерные данные в 2D-пространстве.**" + ] + }, + { + "cell_type": "markdown", + "id": "10b7f90c-6fea-44a1-9178-ef4ef779b528", + "metadata": {}, + "source": [ + "**Вывод: Заключение\n", + "Алгоритм DBSCAN эффективно выявляет кластеры в данных без необходимости заранее указывать количество кластеров.\n", + "На синтетических данных алгоритм точно определил исходные кластеры.\n", + "На реальном датасете DBSCAN выявил структуры в данных, что может быть полезно для обнаружения аномалий или сегментации данных.**" + ] + }, + { + "cell_type": "markdown", + "id": "d48992b5-516d-4bb2-93e0-e2a8159553fd", + "metadata": {}, + "source": [ + "**Интерпретация результатов (реальный датасет)\n", + "Наблюдаемые эффекты:\n", + "Алгоритм DBSCAN позволяет эффективно выделить плотные области данных и отделить разреженные точки как шум (аномалии).\n", + "В реальном датасете, содержащем многомерные числовые признаки, DBSCAN идентифицировал несколько кластеров, а также точки, не попавшие ни в один кластер (label = -1), что может указывать на потенциальные аномалии.\n", + "Несмотря на использование снижения размерности (PCA) для визуализации, полная интерпретация структуры кластеров в исходном многомерном пространстве остаётся ограниченной.\n", + "Практическая значимость:\n", + "Точки, классифицированные как шум, могут представлять особый интерес — например, в задачах обнаружения мошенничества, сбоев или отклонений от нормы.\n", + "Алгоритм не требует предварительного задания количества кластеров, что делает его особенно полезным при анализе плохо структурированных или неизвестных данных.\n", + "В целом, DBSCAN может быть полезен как инструмент предварительной сегментации и выявления аномальных наблюдений, подлежащих дальнейшему анализу.**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ed74e390-d3e7-40ec-98ff-120d1faca6b5", + "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", + 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