From 7360f2e5aaa9fe89b7875d0901cab67bbefcb571 Mon Sep 17 00:00:00 2001 From: Tatiana Lisitsa Date: Sat, 10 Feb 2024 19:14:21 +0300 Subject: [PATCH 1/4] Add func compute_distances_two_loops, compute_distances_one_loop and compute_distances_no_loops --- hw1/code/KNN.ipynb | 985 ++++++++++++++++++++++++++++++++++++++++++++ hw1/code/knn.py | 156 +++++++ hw1/code/metrics.py | 87 ++++ 3 files changed, 1228 insertions(+) create mode 100644 hw1/code/KNN.ipynb create mode 100644 hw1/code/knn.py create mode 100644 hw1/code/metrics.py diff --git a/hw1/code/KNN.ipynb b/hw1/code/KNN.ipynb new file mode 100644 index 0000000..d9b1372 --- /dev/null +++ b/hw1/code/KNN.ipynb @@ -0,0 +1,985 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "39a37345-99a6-4b16-9be7-ebdca1414c7f", + "metadata": {}, + "source": [ + "# Домашнее задание №1 - Метод К-ближайших соседей (K-neariest neighbors)\n", + "\n", + "Сегодня мы с вами реализуем наш первый алгоритм машинного обучения, метод К-ближайших соседей. Мы попытаемся решить с помощью него задачи:\n", + "- бинарной классификации (то есть, только двум классам)\n", + "- многоклассовой классификации (то есть, нескольким классам)\n", + "- регрессии (когда зависимая переменная - натуральное число)\n", + "\n", + "Так как методу необходим гиперпараметр (hyperparameter) - количество соседей, то нам нужно научиться подбирать этот параметр. Мы постараемся научиться пользовать numpy для векторизованных вычислений, а также посмотрим на несколько метрик, которые используются в задачах классификации и регрессии.\n", + "\n", + "Перед выполнением задания:\n", + "- установите все необходимые библиотеки, запустив `pip install -r requirements.txt`\n", + "\n", + "Если вы раньше не работали с numpy или позабыли его, то можно вспомнить здесь: \n", + "http://cs231n.github.io/python-numpy-tutorial/" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "9638c464-806f-41b5-9dfe-1ea2048a1fa1", + "metadata": {}, + "outputs": [], + "source": [ + "import time\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import numpy as np\n", + "import random\n", + "import pandas as pd\n", + "\n", + "\n", + "from importlib import reload\n", + "from sklearn.datasets import fetch_openml\n", + "from sklearn.model_selection import train_test_split\n", + "from knn import KNNClassifier\n", + "from metrics import binary_classification_metrics, multiclass_accuracy\n", + "\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "43bd8dc9-c430-4313-a6a1-4d3e5a7e9c47", + "metadata": {}, + "outputs": [], + "source": [ + "plt.rcParams[\"figure.figsize\"] = 12, 9\n", + "sns.set_style(\"whitegrid\")\n", + "\n", + "SEED = 111\n", + "random.seed(SEED)\n", + "np.random.seed(SEED)" + ] + }, + { + "cell_type": "markdown", + "id": "2867b963-214c-49ea-9460-5b427b56544d", + "metadata": {}, + "source": [ + "## Задание 1. KNN на датасете Fashion-MNIST (10 баллов)" + ] + }, + { + "cell_type": "markdown", + "id": "60a90da7-87ac-42e6-b376-bb34dac2b10b", + "metadata": {}, + "source": [ + "В этом задании вам предстоит поработать с картинками одежды, среди которых можно выделить 10 классов. Данные уже загружены за вас: в переменной X лежат 70000 картинок размером 28 на 28 пикселей, вытянутые в вектор размерностью 784 (28 * 28). Так как данных довольно много, а наш KNN будет весьма медленный, то возьмем случайно 1000 наблюдений (в реальности в зависимости от вашей реализации можно будет взять больше, но если будет не зватать ОЗУ, то берите меньше)." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "54fa4253-ea6a-4ec4-b914-f7cb2346b195", + "metadata": {}, + "outputs": [], + "source": [ + "X, y = fetch_openml(name=\"Fashion-MNIST\", return_X_y=True, as_frame=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "3a188c83-6bf3-485d-9995-9f71d0868d30", + "metadata": {}, + "outputs": [], + "source": [ + "idx_to_stay = np.random.choice(np.arange(X.shape[0]), replace=False, size=1000)\n", + "X = X[idx_to_stay]\n", + "y = y[idx_to_stay]" + ] + }, + { + "cell_type": "markdown", + "id": "4a9e7f89-97f9-4257-94aa-989826258726", + "metadata": {}, + "source": [ + "Давайте посмотрим на какое-нибудь изображение из наших данных:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "277e132c-b89f-4dbb-8efd-cbcea015876d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# возьмем случайную картинку и сделаем reshape\n", + "# 28, 28, 1 = H, W, C (число каналов, в данном случае 1)\n", + "image = X[np.random.choice(np.arange(X.shape[0]))].reshape(28, 28, 1)\n", + "plt.imshow(image)\n", + "plt.axis(\"off\");" + ] + }, + { + "cell_type": "markdown", + "id": "236e593f-595e-45f1-a794-4069a16637d7", + "metadata": {}, + "source": [ + "### 1.1. Посмотрим на все классы (0.5 баллов)" + ] + }, + { + "cell_type": "markdown", + "id": "8cdf3ab2-47a4-492f-bf9a-25c4b00eb945", + "metadata": {}, + "source": [ + "Возьмите по одной картинке каждого класса и изобразите их (например, сделайте subplots 5 на 2)." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "362137fb-4577-4a21-8088-98cba79206f2", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(2, 5, figsize=(10, 10))\n", + "\n", + "for class_to_display in range(10):\n", + " idx_of_class = np.where(y == str(class_to_display))[0]\n", + " random_idx = np.random.choice(idx_of_class)\n", + " image = X[random_idx].reshape(28, 28, 1)\n", + "\n", + " row = class_to_display % 2\n", + " col = class_to_display // 2\n", + "\n", + " axes[row, col].imshow(image)\n", + " axes[row, col].axis('off')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "866ea214-4de8-41b8-a2aa-c86ac0a04b74", + "metadata": {}, + "source": [ + "### 1.2. Сделайте небольшой EDA (1 балл)" + ] + }, + { + "cell_type": "markdown", + "id": "1fe3abdf-2c95-4ce8-8fd3-2445d815ea3c", + "metadata": {}, + "source": [ + "Посмотрите на баланс классов. В дальнейших домашках делайте EDA, когда считаете нужным, он нужен почти всегда, но оцениваться это уже не будет, если не будет указано иное. Делайте EDA, чтобы узнать что-то новое о данных!" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "74595ef7-06ab-4700-b9d9-42db3fdd36d5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "unique_classes = sorted(list(set(y)))\n", + "sns.countplot(x='y', data=pd.DataFrame({'y': y}), order=unique_classes, stat=\"percent\", color='lightskyblue')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "68e8f61e-32d5-4ad7-9f2c-f7e0de050d32", + "metadata": {}, + "source": [ + "### 1.3. Разделите данные на train и test (0.5 баллов)" + ] + }, + { + "cell_type": "markdown", + "id": "25cf3d30-6bd6-4bbb-bba6-4e249da33475", + "metadata": {}, + "source": [ + "Разделите данные на тренировочную и тестовую выборки, размеры тестовой выборки выберите сами. Здесь вам может помочь функция `train_test_split`" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "1932bd43-16d6-4201-8950-7dbe720a9fa1", + "metadata": {}, + "outputs": [], + "source": [ + "X_train, X_test, y_train, y_test = train_test_split(X, \n", + " y, \n", + " test_size=0.2,\n", + " random_state=SEED)" + ] + }, + { + "cell_type": "markdown", + "id": "7c8e4cd4-b3d7-49b7-9b10-be02991ecfa7", + "metadata": {}, + "source": [ + "### 1.4. KNN для бинарной классификации (6 баллов)" + ] + }, + { + "cell_type": "markdown", + "id": "aac2e121-639a-4b0c-8e9c-471ad5a8fac6", + "metadata": {}, + "source": [ + "Давайте возьмем для задачи бинарной классификации только объекты с метками классов 0 и 1." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "f40beae7-54a4-4323-b467-3173737dfd84", + "metadata": {}, + "outputs": [], + "source": [ + "binary_train_X = X_train[(y_train == '0') | (y_train == '1')]\n", + "binary_train_y = y_train[(y_train == '0') | (y_train == '1')]\n", + "\n", + "binary_test_X = X_test[(y_test == '0') | (y_test == '1')]\n", + "binary_test_y = y_test[(y_test == '0') | (y_test == '1')]" + ] + }, + { + "cell_type": "markdown", + "id": "7df7db35-8832-47ec-9955-d0656695e7cd", + "metadata": {}, + "source": [ + "И вот мы подготовили данные, но модели у нас пока что нет. В нескольких занятиях нашего курса вам придется самостоятельно реализовывать какие-то алгоритмы машинного обучения, а потом сравнивать их с готовыми библиотечными решениями. В остальных заданиях реализовывать алгоритмы будет не обязательно, но может быть полезно, поэтому часто это будут задания на дополнительные баллы, но главное не это, а понимание работы алгоритма после его реализации с нуля на простом numpy. Также это все потом можно оформить в виде репозитория ml_from_scratch и хвастаться перед друзьями." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "44d468e9-2a00-4268-bfdc-fbae3857ce90", + "metadata": {}, + "outputs": [], + "source": [ + "knn_classifier = KNNClassifier(k=1)\n", + "knn_classifier.fit(binary_train_X, binary_train_y)" + ] + }, + { + "cell_type": "markdown", + "id": "c5817a1d-161e-4242-bea5-821f416b3eec", + "metadata": {}, + "source": [ + "### Настало время писать код!" + ] + }, + { + "cell_type": "markdown", + "id": "61c760bb-63c9-426d-9f4e-8fab02536da5", + "metadata": {}, + "source": [ + "В KNN нам нужно для каждого тестового примера найти расстояния до всех точек обучающей выборки. Допустим у нас 1000 примеров в train'е и 100 в test'е, тогда в итоге мы бы хотели получить матрицу попарных расстояний (например, размерностью 100 на 1000). Это можно сделать несколькими способами, и кому-то наверняка, в голову приходит идея с двумя вложенными циклами (надеюсь, что не больше:). Так можно делать, то можно и эффективнее. Вообще, в реальном KNN используется структура данных [k-d-tree](https://ru.wikipedia.org/wiki/K-d-%D0%B4%D0%B5%D1%80%D0%B5%D0%B2%D0%BE), которая позволяет производить поиск за log(N), а не за N, как будем делать мы (по сути это такое расширение бинарного поиска на многомерное пространство).\n", + "\n", + "Вам нужно будет последовательно реализовать методы `compute_distances_two_loops`, `compute_distances_one_loop` и `compute_distances_no_loops` класса `KNN` в файле `knn.py`.\n", + "\n", + "Эти функции строят массив расстояний между всеми векторами в тестовом наборе и в тренировочном наборе. \n", + "В результате они должны построить массив размера `(num_test, num_train)`, где координата `[i][j]` соотвествует расстоянию между i-м вектором в test (`test[i]`) и j-м вектором в train (`train[j]`).\n", + "\n", + "**Обратите внимание** Для простоты реализации мы будем использовать в качестве расстояния меру L1 (ее еще называют [Manhattan distance](https://ru.wikipedia.org/wiki/%D0%A0%D0%B0%D1%81%D1%81%D1%82%D0%BE%D1%8F%D0%BD%D0%B8%D0%B5_%D0%B3%D0%BE%D1%80%D0%BE%D0%B4%D1%81%D0%BA%D0%B8%D1%85_%D0%BA%D0%B2%D0%B0%D1%80%D1%82%D0%B0%D0%BB%D0%BE%D0%B2)).\n", + "\n", + "$d_{1}(\\mathbf {p} ,\\mathbf {q} )=\\|\\mathbf {p} -\\mathbf {q} \\|_{1}=\\sum _{i=1}^{n}|p_{i}-q_{i}|$" + ] + }, + { + "cell_type": "markdown", + "id": "c32db2d0-355c-4d74-961e-22d6f42aa11b", + "metadata": {}, + "source": [ + "В начале я буду иногда писать разные assert'ы, чтобы можно было проверить правильность реализации, в дальнейшем вам нужно будет их писать самим, если нужно будет проверять корректность каких-то вычислений." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "01b1ef27-4284-4d6c-978b-25f0fefd39be", + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: compute_distances_two_loops\n", + "dists = knn_classifier.compute_distances_two_loops(binary_test_X)\n", + "assert np.isclose(dists[0, 100], np.sum(np.abs(binary_test_X[0] - binary_train_X[100])))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "505e2c4b-1cfe-4e4a-8002-d9ce089d100e", + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: compute_distances_one_loop\n", + "dists = knn_classifier.compute_distances_one_loop(binary_test_X)\n", + "assert np.isclose(dists[0, 100], np.sum(np.abs(binary_test_X[0] - binary_train_X[100])))" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "dd81b766-5de2-4f62-82cf-8b6bd52002db", + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: compute_distances_no_loops\n", + "dists = knn_classifier.compute_distances_no_loops(binary_test_X)\n", + "assert np.isclose(dists[0, 100], np.sum(np.abs(binary_test_X[0] - binary_train_X[100])))" + ] + }, + { + "cell_type": "markdown", + "id": "64d108b7-b132-42b5-bdca-bc91af8ed3d7", + "metadata": {}, + "source": [ + "Проверим скорость работы реализованных методов" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "8ed08354-d0ef-497a-9d9c-b17c92b7bef9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "24.7 ms ± 209 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", + "5.65 ms ± 37.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "10.8 ms ± 23 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + ] + } + ], + "source": [ + "%timeit knn_classifier.compute_distances_two_loops(binary_test_X)\n", + "%timeit knn_classifier.compute_distances_one_loop(binary_test_X)\n", + "%timeit knn_classifier.compute_distances_no_loops(binary_test_X)" + ] + }, + { + "cell_type": "markdown", + "id": "8180ecc3-8c24-4564-8963-1a0123b06043", + "metadata": {}, + "source": [ + "Реализуем метод для предсказания меток класса" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "9ca2679e-c731-467b-94b5-91a3a0641d7e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n" + ] + } + ], + "source": [ + "# TODO: predict_labels_binary in knn.py\n", + "prediction = knn_classifier.predict(binary_test_X)\n", + "print(prediction)" + ] + }, + { + "cell_type": "markdown", + "id": "d746796d-6ca0-4828-be8a-8b9e22999f54", + "metadata": {}, + "source": [ + "### Метрика" + ] + }, + { + "cell_type": "markdown", + "id": "c29f2abf-be34-4273-a7cd-d2c62ba1eecc", + "metadata": {}, + "source": [ + "Теперь нужно реализовать несколько метрик для бинарной классификации. Не забудьте подумать о численной нестабильности (деление на 0)." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "94268969-5334-4672-a939-65733068a89a", + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: binary_classification_metrics in metrics.py" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "7842978b-a328-4035-b9c4-eb3711cb58c4", + "metadata": {}, + "outputs": [], + "source": [ + "binary_classification_metrics(prediction, binary_test_y)" + ] + }, + { + "cell_type": "markdown", + "id": "71dbca1f-9ad4-4059-9b1c-0c0c85d7d816", + "metadata": {}, + "source": [ + "Все ли хорошо с моделью? Можно проверить свою реализацию с функциями из библиотеки `sklearn`:" + ] + }, + { + "cell_type": "markdown", + "id": "5982d081-ddf9-4522-99b0-459a5cee087c", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "5caeb94f-6464-4adf-b3b6-8e12bf4a50b4", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.metrics import precision_score, recall_score, f1_score, accuracy_score" + ] + }, + { + "cell_type": "markdown", + "id": "6e9b0e1a-3c67-4cc3-bf75-6848f43e8256", + "metadata": {}, + "source": [ + "### Подбор оптимального k" + ] + }, + { + "cell_type": "markdown", + "id": "4069069e-f200-4673-a99c-745e7a5b6b36", + "metadata": {}, + "source": [ + "Чтобы подрбрать оптимальное значение параметра k можно сделать следующее: задать область допустимых значений k, например, `[1, 3, 5, 10]`. Дальше для каждого k обучить модель на тренировочных данных, сделать предсказания на тестовых и посчитать какую-нибудь метрику (метрику выберите сами исходя из задачи, но постарайтесь обосновать выбор). В конце нужно посмотреть на зависимость метрики на train'е и test'е от k и выбрать подходящее значение.\n", + "\n", + "Реализуйте функцию `choose_best_k` прямо в ноутбуке." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "374d6fcf-21f2-433c-b011-76019201ce52", + "metadata": {}, + "outputs": [], + "source": [ + "def find_best_k(X_train, y_train, X_test, y_test, params, metric):\n", + " \"\"\"\n", + " Choose the best k for KKNClassifier\n", + " Arguments:\n", + " X_train, np array (num_train_samples, num_features) - train data\n", + " y_train, np array (num_train_samples) - train labels\n", + " X_test, np array (num_test_samples, num_features) - test data\n", + " y_test, np array (num_test_samples) - test labels\n", + " params, list of hyperparameters for KNN, here it is list of k values\n", + " metric, function for metric calculation\n", + " Returns:\n", + " train_metrics the list of metric values on train data set for each k in params\n", + " test_metrics the list of metric values on test data set for each k in params\n", + " \"\"\"\n", + " \n", + " \"\"\"\n", + " YOUR CODE IS HERE\n", + " \"\"\"\n", + " pass" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "a2418dd8-93f1-4a11-8488-a8bce98e7d5f", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "ename": "TypeError", + "evalue": "cannot unpack non-iterable NoneType object", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[20], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m params \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m4\u001b[39m, \u001b[38;5;241m5\u001b[39m, \u001b[38;5;241m8\u001b[39m, \u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m30\u001b[39m]\n\u001b[0;32m----> 2\u001b[0m train_metrics, test_metrics \u001b[38;5;241m=\u001b[39m find_best_k(binary_train_X, binary_train_y, binary_test_X, binary_test_y, params, accuracy_score)\n", + "\u001b[0;31mTypeError\u001b[0m: cannot unpack non-iterable NoneType object" + ] + } + ], + "source": [ + "params = [1, 2, 4, 5, 8, 10, 30]\n", + "train_metrics, test_metrics = find_best_k(binary_train_X, binary_train_y, binary_test_X, binary_test_y, params, accuracy_score)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7053ce06-854c-412b-8559-833595b1d6c0", + "metadata": {}, + "outputs": [], + "source": [ + "plt.plot(params, train_metrics, label=\"train\")\n", + "plt.plot(params, test_metrics, label=\"test\")\n", + "plt.legend()\n", + "plt.xlabel(\"K in KNN\")\n", + "plt.ylabel(\"YOUR METRIC\");" + ] + }, + { + "cell_type": "markdown", + "id": "73fdecd7-a4b6-4ca9-8688-d1ae2195647f", + "metadata": {}, + "source": [ + "На самом деле, это не самый лучший способ подбирать гиперпараметры, но способы получше мы рассмотрим в следующий раз, а пока что выберите оптимальное значение k, сделайте предсказания и посмотрите, насколько хорошо ваша модель предсказывает каждый из классов." + ] + }, + { + "cell_type": "markdown", + "id": "0bc98c29-3217-407c-a466-58072bb7b8cc", + "metadata": {}, + "source": [ + "### 1.5. Многоклассоввая классификация (2 балла)" + ] + }, + { + "cell_type": "markdown", + "id": "aa0fa9bf-3002-4b0e-8e52-1d9e70795092", + "metadata": {}, + "source": [ + "Теперь нужно научиться предсказывать все 10 классов. Для этого в начале напишем соответствующий метод у нашего классификатора." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "88b37ef1-fa15-4cc5-8558-0254890c899d", + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: predict_labels_multiclass in knn.py\n", + "knn_classifier = KNNClassifier(k=1)\n", + "knn_classifier.fit(X_train, y_train)\n", + "predictions = knn_classifier.predict(X_test)" + ] + }, + { + "cell_type": "markdown", + "id": "fa8ed7ad-e347-4f78-b34f-88febee9e94b", + "metadata": {}, + "source": [ + "Осталось реализовать метрику качества для многоклассовой классификации, для этого реализуйте функцию `multiclass_accuracy` в `metrics.py`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "65887922-a799-4042-902e-f63f69508beb", + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: multiclass_accuracy in metrics.py\n", + "multiclass_accuracy(predictions, y_test)" + ] + }, + { + "cell_type": "markdown", + "id": "a6fe44f6-e056-4f17-beb6-0ce65fab268f", + "metadata": {}, + "source": [ + "Снова выберите оптимальное значение K как мы делали для бинарной классификации." + ] + }, + { + "cell_type": "markdown", + "id": "daa8ee4a-88c1-4967-84f1-6f7ec223db7e", + "metadata": {}, + "source": [ + "## Задание 2. KNN на датасете diabetes (10 баллов)" + ] + }, + { + "cell_type": "markdown", + "id": "d3dac1f9-42ef-406f-988c-2d663b8b2806", + "metadata": {}, + "source": [ + "Теперь попробуем применить KNN к задаче регрессии. Будем работать с [данными](https://scikit-learn.org/stable/datasets/toy_dataset.html#diabetes-dataset) о диабете. В этом задании будем использовать класс `KNeighborsRegressor` из библиотеки `sklearn`. Загрузим необходимые библиотеки:" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "8ab4c84e-6036-4fe2-b81f-8115bf0a4774", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.datasets import load_diabetes\n", + "from sklearn.metrics import r2_score, mean_absolute_error, mean_squared_error\n", + "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.neighbors import KNeighborsRegressor" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "4136b3bb-e482-4102-ad5f-af5b3b1a030a", + "metadata": {}, + "outputs": [], + "source": [ + "X, y = load_diabetes(as_frame=True, return_X_y=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "c884e687-964a-4b00-9f10-232c45705f12", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " age sex bmi bp s1 s2 s3 \\\n", + "0 0.038076 0.050680 0.061696 0.021872 -0.044223 -0.034821 -0.043401 \n", + "1 -0.001882 -0.044642 -0.051474 -0.026328 -0.008449 -0.019163 0.074412 \n", + "2 0.085299 0.050680 0.044451 -0.005670 -0.045599 -0.034194 -0.032356 \n", + "3 -0.089063 -0.044642 -0.011595 -0.036656 0.012191 0.024991 -0.036038 \n", + "4 0.005383 -0.044642 -0.036385 0.021872 0.003935 0.015596 0.008142 \n", + "\n", + " s4 s5 s6 \n", + "0 -0.002592 0.019907 -0.017646 \n", + "1 -0.039493 -0.068332 -0.092204 \n", + "2 -0.002592 0.002861 -0.025930 \n", + "3 0.034309 0.022688 -0.009362 \n", + "4 -0.002592 -0.031988 -0.046641 " + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "X.head()" + ] + }, + { + "cell_type": "markdown", + "id": "9ce6cd71-dd17-40af-b7cc-c48e61d31719", + "metadata": {}, + "source": [ + "### 2.1. EDA (2 обязательных балла + 2 доп. балла за Pipeline)" + ] + }, + { + "cell_type": "markdown", + "id": "4397b3ad-63f9-4b25-ab7e-d572216e21c5", + "metadata": {}, + "source": [ + "Сделайте EDA, предобработайте данные так, как считаете нужным, нужна ли в данном случае стандартизация и почему? Не забудте, что если вы стандартизуете данные, то нужно считать среднее и сдандартное отклонение на тренировочной части и с помощью них трансформировать и train, и test (**если не поняли это предложение, то обязательно разберитесь**).\n", + "\n", + "**Дополнительно**:\n", + "Попробуйте разобраться с [`Pipeline`](https://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html), чтобы можно было создать класс, который сразу проводит стандартизацию и обучает модель (или делает предсказание). Пайплайны очень удобны, когда нужно применять различные методы предобработки данных (в том числе и к разным столбцам), а также они позволяют правильно интегрировать предобработку данных в различные классы для поиска наилучших гиперпараметров модели (например, `GridSearchCV`)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a4aa413d-d830-4355-a063-9c5d6d5a6c9a", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.pipeline import Pipeline" + ] + }, + { + "cell_type": "markdown", + "id": "8e1fa5ec-18db-4e7b-88f1-6d010f449488", + "metadata": {}, + "source": [ + "### 2.2. Регрессионная модель (1 балл)" + ] + }, + { + "cell_type": "markdown", + "id": "3d79f583-5feb-4eeb-b748-9b4cdea9150d", + "metadata": {}, + "source": [ + "Создайте модель `KNeighborsRegressor`, обучите ее на треноровочных данных и сделайте предсказания." + ] + }, + { + "cell_type": "markdown", + "id": "5ed4a2ea-4f42-43cb-95d7-50cdeab5f284", + "metadata": {}, + "source": [ + "### 2.3. Метрики регресии (3 балла)" + ] + }, + { + "cell_type": "markdown", + "id": "cbf563ad-1b71-464c-8359-75fa4da268d3", + "metadata": {}, + "source": [ + "Реализуйте метрики $R^2$, MSE и MAE в `metrics.py`. Примените их для оценки качества полученной модели. Все ли хорошо?\n", + "\n", + "Напомню, что:\n", + "\n", + "$R^2 = 1 - \\frac{\\sum_i^n{(y_i - \\hat{y_i})^2}}{\\sum_i^n{(y_i - \\overline{y})^2}}$\n", + "\n", + "$MSE = \\frac{1}{n}\\sum_i^n{(y_i - \\hat{y_i})^2}$\n", + "\n", + "$MAE = \\frac{1}{n}\\sum_i^n{|y_i - \\hat{y_i}|}$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "580f604f-e9c5-4109-8b9f-235369836057", + "metadata": {}, + "outputs": [], + "source": [ + "# TODO: r_squared, mse, mae in metrics.py" + ] + }, + { + "cell_type": "markdown", + "id": "a6568d8d-a9ec-4639-aac1-0ea18a644f9e", + "metadata": {}, + "source": [ + "### 2.4. Подбор оптимального числа соседей (2 балла)" + ] + }, + { + "cell_type": "markdown", + "id": "d82f145d-41f5-4bbe-b553-1d05d90ec2a2", + "metadata": {}, + "source": [ + "Мы почти дошли до конца. Теперь осталось при помощи реализованных нами метрик выбрать лучшее количество соседей для нашей модели.\n", + "\n", + "!!! Обратите внимание на то, что значат наши метрики, для некоторых хорошо, когда они уменьшаются, для других наоборот." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "138a7969-8079-4a38-b92e-8eae5d246325", + "metadata": {}, + "outputs": [], + "source": [ + "from metrics import r_squared, mse, mae" + ] + }, + { + "cell_type": "markdown", + "id": "1b4bbef7-35a4-4f05-abf8-5d2b450c86f2", + "metadata": {}, + "source": [ + "Для поиска лучшего k вы можете воспользоваться функцией `find_best_k`, которую вы реализовали выше." + ] + }, + { + "cell_type": "markdown", + "id": "2cb77960-fa30-4a29-9a1b-7c195cc867cb", + "metadata": {}, + "source": [ + "### 3. Социализация (0.5 доп. балла)\n", + "\n", + "Так как у нас теперь большая группа, то было бы здорово всем познакомиться получше (так как выпускной не за горами). Соберитесь с одногруппниками в зуме, познакомьтесь, а сюда прикрепите скриншот с камерами всех участников." + ] + }, + { + "cell_type": "markdown", + "id": "e116a42f-fae8-499c-a985-dc09e66a29b0", + "metadata": {}, + "source": [ + "## Therapy time" + ] + }, + { + "cell_type": "markdown", + "id": "031c493b-26f3-4622-a1f4-affee64f81db", + "metadata": {}, + "source": [ + "Напишите здесь ваши впечатления о задании: было ли интересно, было ли слишком легко или наоборот сложно и тд. Также сюда можно написать свои идеи по улучшению заданий, а также предложить данные, на основе которых вы бы хотели построить следующие дз. " + ] + }, + { + "cell_type": "markdown", + "id": "6d1c75b8", + "metadata": {}, + "source": [ + "**Ваши мысли:** я немного подавлена" + ] + } + ], + "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": "3.12.1" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/hw1/code/knn.py b/hw1/code/knn.py new file mode 100644 index 0000000..ad3c4a9 --- /dev/null +++ b/hw1/code/knn.py @@ -0,0 +1,156 @@ +import numpy as np + + +class KNNClassifier: + """ + K-neariest-neighbor classifier using L1 loss + """ + + def __init__(self, k=1): + self.k = k + + + def fit(self, X, y): + self.train_X = X + self.train_y = y + + + def predict(self, X, n_loops=0): + """ + Uses the KNN model to predict clases for the data samples provided + + Arguments: + X, np array (num_samples, num_features) - samples to run + through the model + num_loops, int - which implementation to use + + Returns: + predictions, np array of ints (num_samples) - predicted class + for each sample + """ + + if n_loops == 0: + distances = self.compute_distances_no_loops(X) + elif n_loops == 1: + distances = self.compute_distances_one_loops(X) + else: + distances = self.compute_distances_two_loops(X) + + if len(np.unique(self.train_y)) == 2: + return self.predict_labels_binary(distances) + else: + return self.predict_labels_multiclass(distances) + + + def compute_distances_two_loops(self, X): + """ + Computes L1 distance from every sample of X to every training sample + Uses simplest implementation with 2 Python loops + + Arguments: + X, np array (num_test_samples, num_features) - samples to run + + Returns: + distances, np array (num_test_samples, num_train_samples) - array + with distances between each test and each train sample + """ + + num_test = X.shape[0] + num_train = self.train_X.shape[0] + distances = np.zeros((num_test, num_train)) + + for i in range(num_test): + for j in range(num_train): + distances[i, j] = np.sum(np.abs(X[i] - self.train_X[j])) + + return distances + + + def compute_distances_one_loop(self, X): + """ + Computes L1 distance from every sample of X to every training sample + Vectorizes some of the calculations, so only 1 loop is used + + Arguments: + X, np array (num_test_samples, num_features) - samples to run + + Returns: + distances, np array (num_test_samples, num_train_samples) - array + with distances between each test and each train sample + """ + + num_test = X.shape[0] + num_train = self.train_X.shape[0] + distances = np.zeros((num_test, num_train)) + + for i in range(num_test): + distances[i, :] = np.sum(np.abs(X[i] - self.train_X), axis=1) + + return distances + + + def compute_distances_no_loops(self, X): + """ + Computes L1 distance from every sample of X to every training sample + Fully vectorizes the calculations using numpy + + Arguments: + X, np array (num_test_samples, num_features) - samples to run + + Returns: + distances, np array (num_test_samples, num_train_samples) - array + with distances between each test and each train sample + """ + + X_test_expanded = np.expand_dims(X, axis=1) + X_train_expanded = np.expand_dims(self.train_X, axis=0) + distances = np.sum(np.abs(X_test_expanded - X_train_expanded), axis=2) + + return distances + + + + def predict_labels_binary(self, distances): + """ + Returns model predictions for binary classification case + + Arguments: + distances, np array (num_test_samples, num_train_samples) - array + with distances between each test and each train sample + Returns: + pred, np array of bool (num_test_samples) - binary predictions + for every test sample + """ + + #n_train = distances.shape[1] + n_test = distances.shape[0] + prediction = np.zeros(n_test) + + for i in range(n_test): + nearest_indices = np.argsort(distances[i])[:self.k] + count_class_1 = np.sum(self.train_y[nearest_indices] == 1) + prediction[i] = count_class_1 > (self.k / 2) + + return prediction + + + def predict_labels_multiclass(self, distances): + """ + Returns model predictions for multi-class classification case + + Arguments: + distances, np array (num_test_samples, num_train_samples) - array + with distances between each test and each train sample + Returns: + pred, np array of int (num_test_samples) - predicted class index + for every test sample + """ + + n_train = distances.shape[0] + n_test = distances.shape[0] + prediction = np.zeros(n_test, np.int) + + """ + YOUR CODE IS HERE + """ + pass diff --git a/hw1/code/metrics.py b/hw1/code/metrics.py new file mode 100644 index 0000000..b65c588 --- /dev/null +++ b/hw1/code/metrics.py @@ -0,0 +1,87 @@ +import numpy as np + + +def binary_classification_metrics(y_pred, y_true): + """ + Computes metrics for binary classification + Arguments: + y_pred, np array (num_samples) - model predictions + y_true, np array (num_samples) - true labels + Returns: + precision, recall, f1, accuracy - classification metrics + """ + + # TODO: implement metrics! + # Some helpful links: + # https://en.wikipedia.org/wiki/Precision_and_recall + # https://en.wikipedia.org/wiki/F1_score + + """ + YOUR CODE IS HERE + """ + pass + + +def multiclass_accuracy(y_pred, y_true): + """ + Computes metrics for multiclass classification + Arguments: + y_pred, np array of int (num_samples) - model predictions + y_true, np array of int (num_samples) - true labels + Returns: + accuracy - ratio of accurate predictions to total samples + """ + + """ + YOUR CODE IS HERE + """ + pass + + +def r_squared(y_pred, y_true): + """ + Computes r-squared for regression + Arguments: + y_pred, np array of int (num_samples) - model predictions + y_true, np array of int (num_samples) - true values + Returns: + r2 - r-squared value + """ + + """ + YOUR CODE IS HERE + """ + pass + + +def mse(y_pred, y_true): + """ + Computes mean squared error + Arguments: + y_pred, np array of int (num_samples) - model predictions + y_true, np array of int (num_samples) - true values + Returns: + mse - mean squared error + """ + + """ + YOUR CODE IS HERE + """ + pass + + +def mae(y_pred, y_true): + """ + Computes mean absolut error + Arguments: + y_pred, np array of int (num_samples) - model predictions + y_true, np array of int (num_samples) - true values + Returns: + mae - mean absolut error + """ + + """ + YOUR CODE IS HERE + """ + pass + \ No newline at end of file From 2d3df8bd37cdd68d43c2d1e37612ae2d3f46312e Mon Sep 17 00:00:00 2001 From: Tatiana Lisitsa Date: Sun, 11 Feb 2024 11:33:30 +0300 Subject: [PATCH 2/4] Add func binary_classification_metrics, add my_awesom_eda.py, add socialisation and therapy --- hw1/code/KNN.ipynb | 316 +++++++++--------- hw1/code/knn.py | 2 +- hw1/code/metrics.py | 25 +- hw1/code/my_awesome_eda.py | 136 ++++++++ hw1/data_folder/cat.jpeg | Bin 0 -> 104268 bytes hw1/data_folder/photo_2024-02-11_11-03-30.jpg | Bin 0 -> 140216 bytes hw1/data_folder/photo_2024-02-11_11-04-15.jpg | Bin 0 -> 145547 bytes 7 files changed, 312 insertions(+), 167 deletions(-) create mode 100644 hw1/code/my_awesome_eda.py create mode 100644 hw1/data_folder/cat.jpeg create mode 100644 hw1/data_folder/photo_2024-02-11_11-03-30.jpg create mode 100644 hw1/data_folder/photo_2024-02-11_11-04-15.jpg diff --git a/hw1/code/KNN.ipynb b/hw1/code/KNN.ipynb index d9b1372..6f65ea7 100644 --- a/hw1/code/KNN.ipynb +++ b/hw1/code/KNN.ipynb @@ -23,11 +23,22 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "id": "9638c464-806f-41b5-9dfe-1ea2048a1fa1", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The autoreload extension is already loaded. To reload it, use:\n", + " %reload_ext autoreload\n" + ] + } + ], "source": [ + "%load_ext autoreload\n", + "%autoreload 2\n", "import time\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", @@ -36,14 +47,11 @@ "import pandas as pd\n", "\n", "\n", - "from importlib import reload\n", + "from IPython.display import Image, displey\n", "from sklearn.datasets import fetch_openml\n", "from sklearn.model_selection import train_test_split\n", "from knn import KNNClassifier\n", - "from metrics import binary_classification_metrics, multiclass_accuracy\n", - "\n", - "%load_ext autoreload\n", - "%autoreload 2" + "from metrics import binary_classification_metrics, multiclass_accuracy" ] }, { @@ -96,7 +104,8 @@ "source": [ "idx_to_stay = np.random.choice(np.arange(X.shape[0]), replace=False, size=1000)\n", "X = X[idx_to_stay]\n", - "y = y[idx_to_stay]" + "y = y[idx_to_stay]\n", + "y = y.astype(int)" ] }, { @@ -156,9 +165,9 @@ "outputs": [ { "data": { - "image/png": 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", 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"text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -166,10 +175,10 @@ } ], "source": [ - "fig, axes = plt.subplots(2, 5, figsize=(10, 10))\n", + "fig, axes = plt.subplots(2, 5, figsize=(10, 5))\n", "\n", "for class_to_display in range(10):\n", - " idx_of_class = np.where(y == str(class_to_display))[0]\n", + " idx_of_class = np.where(y == class_to_display)[0]\n", " random_idx = np.random.choice(idx_of_class)\n", " image = X[random_idx].reshape(28, 28, 1)\n", "\n", @@ -273,11 +282,11 @@ "metadata": {}, "outputs": [], "source": [ - "binary_train_X = X_train[(y_train == '0') | (y_train == '1')]\n", - "binary_train_y = y_train[(y_train == '0') | (y_train == '1')]\n", + "binary_train_X = X_train[(y_train == 0) | (y_train == 1)]\n", + "binary_train_y = y_train[(y_train == 0) | (y_train == 1)]\n", "\n", - "binary_test_X = X_test[(y_test == '0') | (y_test == '1')]\n", - "binary_test_y = y_test[(y_test == '0') | (y_test == '1')]" + "binary_test_X = X_test[(y_test == 0) | (y_test == 1)]\n", + "binary_test_y = y_test[(y_test == 0) | (y_test == 1)]" ] }, { @@ -339,7 +348,6 @@ "metadata": {}, "outputs": [], "source": [ - "# TODO: compute_distances_two_loops\n", "dists = knn_classifier.compute_distances_two_loops(binary_test_X)\n", "assert np.isclose(dists[0, 100], np.sum(np.abs(binary_test_X[0] - binary_train_X[100])))" ] @@ -351,7 +359,6 @@ "metadata": {}, "outputs": [], "source": [ - "# TODO: compute_distances_one_loop\n", "dists = knn_classifier.compute_distances_one_loop(binary_test_X)\n", "assert np.isclose(dists[0, 100], np.sum(np.abs(binary_test_X[0] - binary_train_X[100])))" ] @@ -363,7 +370,6 @@ "metadata": {}, "outputs": [], "source": [ - "# TODO: compute_distances_no_loops\n", "dists = knn_classifier.compute_distances_no_loops(binary_test_X)\n", "assert np.isclose(dists[0, 100], np.sum(np.abs(binary_test_X[0] - binary_train_X[100])))" ] @@ -386,9 +392,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "24.7 ms ± 209 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", - "5.65 ms ± 37.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "10.8 ms ± 23 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + "24.7 ms ± 127 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", + "5.33 ms ± 57.2 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "10.8 ms ± 31.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" ] } ], @@ -416,13 +422,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n" + "[ True False True False False True False False False True True True\n", + " True False True False True True False True True True True True\n", + " False True False True False False True False True True True False]\n" ] } ], "source": [ - "# TODO: predict_labels_binary in knn.py\n", "prediction = knn_classifier.predict(binary_test_X)\n", "print(prediction)" ] @@ -458,7 +464,18 @@ "execution_count": 17, "id": "7842978b-a328-4035-b9c4-eb3711cb58c4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(1.0, 1.0, 1.0, 1.0)" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "binary_classification_metrics(prediction, binary_test_y)" ] @@ -481,7 +498,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 21, "id": "5caeb94f-6464-4adf-b3b6-8e12bf4a50b4", "metadata": {}, "outputs": [], @@ -489,6 +506,28 @@ "from sklearn.metrics import precision_score, recall_score, f1_score, accuracy_score" ] }, + { + "cell_type": "code", + "execution_count": 24, + "id": "9f02cbc9-3fcf-4818-ab9b-eb90c3db1703", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.0 1.0 1.0 1.0\n" + ] + } + ], + "source": [ + "print(precision_score(prediction, binary_test_y),\n", + " recall_score(prediction, binary_test_y),\n", + " f1_score(prediction, binary_test_y),\n", + " accuracy_score(prediction, binary_test_y)\n", + " )" + ] + }, { "cell_type": "markdown", "id": "6e9b0e1a-3c67-4cc3-bf75-6848f43e8256", @@ -507,6 +546,14 @@ "Реализуйте функцию `choose_best_k` прямо в ноутбуке." ] }, + { + "cell_type": "markdown", + "id": "f583c3b4-5f2f-4918-b61a-90b151415cf7", + "metadata": {}, + "source": [ + "Я выбрала метрику accuracy - она простая и интуинтивно понятная. Наша модель должна отличать футболки от брюк, нам достаточно просто знать как часто она попоадает в точку, судя по графику в начале ноутбука (про который я к этому месту уже забыла) - наши классы сбалансированы, в отличае от моего шкафе, где больше футболок. Ну и у нас на входе нет никаких специфических ограничений, например нам не важно, чтобы она определяла абсолютно точно только брюки, потому что человек в футболке и без брюк выглядит менее социально приемлемо, чем в брюках без футболки." + ] + }, { "cell_type": "code", "execution_count": 19, @@ -656,7 +703,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "id": "8ab4c84e-6036-4fe2-b81f-8115bf0a4774", "metadata": {}, "outputs": [], @@ -669,148 +716,37 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "id": "4136b3bb-e482-4102-ad5f-af5b3b1a030a", "metadata": {}, "outputs": [], "source": [ - "X, y = load_diabetes(as_frame=True, return_X_y=True)" + "X, y = load_diabetes(as_frame=True, return_X_y=True, scaled=True)" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "id": "c884e687-964a-4b00-9f10-232c45705f12", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " age sex bmi bp s1 s2 s3 \\\n", - "0 0.038076 0.050680 0.061696 0.021872 -0.044223 -0.034821 -0.043401 \n", - "1 -0.001882 -0.044642 -0.051474 -0.026328 -0.008449 -0.019163 0.074412 \n", - "2 0.085299 0.050680 0.044451 -0.005670 -0.045599 -0.034194 -0.032356 \n", - "3 -0.089063 -0.044642 -0.011595 -0.036656 0.012191 0.024991 -0.036038 \n", - "4 0.005383 -0.044642 -0.036385 0.021872 0.003935 0.015596 0.008142 \n", - "\n", - " s4 s5 s6 \n", - "0 -0.002592 0.019907 -0.017646 \n", - "1 -0.039493 -0.068332 -0.092204 \n", - "2 -0.002592 0.002861 -0.025930 \n", - "3 0.034309 0.022688 -0.009362 \n", - "4 -0.002592 -0.031988 -0.046641 " - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "X.head()" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "d199d24e-2a61-4a00-a5ed-707d314608c1", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } + }, + "outputs": [], + "source": [] + }, { "cell_type": "markdown", "id": "9ce6cd71-dd17-40af-b7cc-c48e61d31719", @@ -837,7 +773,18 @@ "metadata": {}, "outputs": [], "source": [ - "from sklearn.pipeline import Pipeline" + "from sklearn.pipeline import Pipeline\n", + "from my_awesome_eda import run_eda" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f84b891e-b397-4c58-9b0a-d8becef14411", + "metadata": {}, + "outputs": [], + "source": [ + "run_eda(X, category_values=2)" ] }, { @@ -936,6 +883,39 @@ "Так как у нас теперь большая группа, то было бы здорово всем познакомиться получше (так как выпускной не за горами). Соберитесь с одногруппниками в зуме, познакомьтесь, а сюда прикрепите скриншот с камерами всех участников." ] }, + { + "cell_type": "code", + "execution_count": 38, + "id": "cd21e2b7-8310-4ffb-893f-8c571110037d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/jpeg": 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y1LMleWtdY1kJf+Sjlcih/SYYGYbAH23zl6D6fO5fUcv0Vo95Zqd61fISONGvHKeOGtdd83A8LxnuDVOWiyRbrf8A4540Sm7WsTXenQx1uzXCR5MfFGsdairrNWeKOlk4pa0Rs6yMfJHyaJpVDL59Py74Pk67/B9NfjvBkyZMmTJlnS1yVT+M88XL1OGhO6L6mrjIcluxKUODsEb/AOqD7+nXQ+iP7eoR85/IiJbkxJnWq1UR6Ru6H1/+sX+pyU5O82O13QSaDyaoz0TS6rN+d358H/MtQkq+QqAp5aspVrFWB7V2vI9Fj3TW917p/AyTOEW1NGIq27dp85eg+nzw/ql27ugjeNs1PyPSyoS4exJM9epLsWfP9KlJrXnuNGpb8hPKfIf/AI1+1wjbuTgeNvvehys7ez57PlatuTCfnbtc8NeYlXdR6HHeheGUSUZrpez9fydd/g+mvxyZMmTJkybwvzPJea5O0dWXZJm7RSR66oolj+blnaXnwtNoI/8AQ/hD93TjofRP6dRCp2+qRvFn8BdA7kZsmWujDqSg+pzLUqNtonisiYhKp51HJq+WfW18+KmeC1I4TQyUW3hdkibujmcMbHG9i6FGOwzRj0hfN65GwtZryOc1EI4PnL0H0+fHBvcK302h4osge48FkGFmqRnHxx1nzN3vZgsFHFRiGwMtWEQtMzTf+Nbm5LE+PCQYKkkBZbMWearc7mCWLeIjYZ46RzPPG0DY89xQzMytx9xGQODxksHY47LebePXf4Ppv8d4MmTJkyK1DEnyNUQlLfLqmfR78fc41i0dtCVOESOCNpLAswt/ofwi+7pwvMPt8Ooh8p2+uSLyJtHTA6Mm2aqItCJ9zp2+nT9Az4okL6NBaOAocgMsZ2NzxSq+W6f56T6TNOcJC4zwS1ycq1Yme9aClAU52prVdxlxshQqnmhNhyVcrGQyFMqvzl6D6fPia2i00bOTbBm+oq8Tb4uaJrW5xEGcotNwzMAnbLWR9T/8UvIbMm2SgfNUzOQDH1rBb3hsPXkimE2aNiUYgKy1htcbPo4yaS02cnOFxI8TFIEUMlSWnJy1vHrv8H03+O8GTJk7sLZDNE785OYC+7xxxctJV42d8eNarHDI7UIrcleFsxWUc8cvzv4B93Tp/VF9nh1C30yBrL2uoWYdpfSCctfFvDVDqaEPK2/6vgzqOTY7SIJVO+4/nrfuGarXDgMc1AzS9Qwg1m3JcnxuNcxlka1eiLawTMybJPQVoa2QD5y9B9Pnx+mxyWbn5LQNytRq7zpVCmht46bbbxLAHCRSxYG8rlOarIf3f+LcmaONqD3D5PZdLKZE7shknUUxRuNs9Htm6mJ3eiekgfyaR6KwXIZRRsWNshHi8KYvT8euyb2L03+O8WTLK5DuJ3PVF+8vVE21pLQRiGaNdwyiuiCaWW2oXeSe/a4493KVS+EJwZ6Z5xNibXwsa8HNLyF6IfXp1/rg/a8M95iEO6Yav0ZaUef5dfCIU3kjLcXyMS5Exbm+eDyM4WlbY7O0ZoqLTtGHZqTIzzhHTuivYtk3fExQvJi55Y6OIm4fnL0H0+fH6qS3pLZFzVOuIwQhosVLtezp287eeTbbJjdSqyQhKHUFSOllf779Uiz+9Ir3qFe9Qr3qFF1YLNP1DyvR6hGBuos899TP5E6d1qq8qJ/KU9xQlo8P1Kmf6136S42NTSOy9q8Rx3R3zMUiLvhfrA5ZMThr7Vqfthl7ZZe2mTZtlcz36PN9TyIZWZNZZUSaexli/XTxRmhpREq9WvC0xu6x8jct4t783CIm6xTb7FScSj3LeiLUJ24ru3cu3d1wOyxNvtSg6oEQ96hRdVCshm2stFZYSuZfbWKBycx2l8resDqw+kHyt6MKFtG2LidbFsWxbFsVX9OQmZn+9C4ijmd0YSTvjo4oAGQXUY7hirtuc9Ebu8fzl6AOrcb6PG7PsWxbFsWxVckMAFb8nN3NrK71ttPJcJHc547LsCyc4yyYKfmoEurPzf8Af/8Auld1AImnhHh7YRlKLdVCMSkjgDjnqgSvxPWld0/hGWhcoaH90frWL/GGTQ5j3KMkztAqRdu+DuHYvUckN4yk0brCXfi8eLyRT1gjkkgEGt1WrI64yFJTi5pKQbmxQEZ0gavdxwRXIzehclB5mdtED6oWdlufQ31cPpTyvpu3Fqsd9EZXGr1cTcOzWc/NnWbB47A+uJcxaaRzNoI4ccUDRmbMw8TSDLWhCPshGeanGc0uP4YZv3PmiNG2+Lb8oIE6qfyMlIe+kI7vZw2rTY8CGHEEU8FUHnDGxmpse0UEmOBpLVMKrDiROeLEDz1q5mRVJo1TsED67hr1SnJ6kcFT5y9I/tkkMKNMWmutTG6bUAar7IDkbHgQliSFBRc5mAe0OjG8/YAB9h+kdXtbFqZ4atmQjKbzl6Vsfpk2o9VPrmv775atq+VruvaldPmQ3Plhd3yjPHFlWjD20Ok96SdWTKdcRLiJcZLhJDX1RQuyACZQzbBGdmXdx7XlDl7kNbFmKRu+CKPF5+DH14+p6TxZzL1chTp8kEbTGLd1Ltksyyp7ErO1q4Jc1nYM1mMq8Nq3K2CzbE3TeUKYun7zCfS+RdN0vk2QdPZHT3evr3byGrdO5BZHH2qANuTG673bXitCb1c5ThF+oKSDqKiyy92G1I8ZxE10hW9lDd2JsrE6fKQOnycWpZVieTJasORsCnnJ4pAcj4iXES4iXES4iXESECZAbsxg5FxEuIlxEuIk0ZMgbROhs7Bls8pQZKStEWYsE8uTkkCTIzSruX1jvSRO9yR1Yy009n2jM6jyRr2wTFQyVaIvbdHSXJU3elnKgyh1TiQabq3FFX3Lcty3Lcty3J3UMvEit7own4yLIzEZ35ZIxyEovLk5JAK6ZP7VeNR3ygL2xMbtdZkWQ1Ud8d17NVZ45bkRI5BJsPk4KTj1bi9M5chu5Lcty3Lcty3Ld/Z2rati2rYnFbVsZbFxstiYFsZbFxsuNlxrjZbFxsuNlsWxaLRbVjPyUMDSRyRsDuXnv89SW5b3XI6aR3W90xJlotjKxJFVCXPHu9vTr3hsL3isKHqA3elcguLt2XbjpwCuAU8bMtrLNY+PJ5X3Ppr3Sp6+6FN290qa90aS9z6S9zqK9zaKboygm6Ix7i/RdBl7mUV7mUV7nUV7n0k/SNJP0nTT9K1E/TFRP03VZP07WQdN1iUHRlKVe4dBP0JQT9D0VnsbHir3uJQXuFQXuHQXuDQXuBj18P8AHr4f49fD/Hr4f49fD/Hr4f49fD/Hr4f49fD/AB6+H+PR9C4uJR9DYqZfD/Hr4f49fD/Hr4f49fD/AB6+H+PXw/x6+H+PXw/x66j6UqYbHaE6YJHVPGtOo+maxN7rVVJ03VBTYiIF7OBVcDHO4dHVib3Mqr3Nqr3OqqbpmpCixFNk+LqL2XVXsqsvZVdDha5KLpqsar9FUpV8P8evh/j18P8AHr4f49fD/H/2dFp4P8+nhu8hPVeTMtFtXGuF0UeidvDRaLRY5v8Akar/AKFnXe5+bNoydO6dCnQpkys2Rqw3LkluXRzQ13T12RQ7V9qimKI8be72HXwI9EUq5VL555x8yFP5Lk1T+SY/Let63oJE5Lct3lqnJOSd07p3TunUPrT8HRLrH8wybx10TSM/+i1aipxZLrOQlJJcuHTe5Rmq9YE0kM4WI/n67/B4yo01YMaKhqNGgbRjkYVNPq7juTtoWHBiQwNpwsuBkUDaZ1+Np7hMfeEhtEhsOhndVD1VZUm/8mRtxaeTPqRt9ISbVDHyIKeqGmu2ZWYdETeei0Wx1xOqcTjdqv8AoTev/wBidO6d1qmfwFMmWVt9zMEfI8cW1P4OGqmh8tdH6btbZ3JSTaKa0nsrndF+f0TtqiBE2iI3FMbEt2iYkxISWq1Wvg6daOnjJPE6eNODKH7qnp4EusfzHomLXw0RNqwxvu+aSQYY8rkp87biqhEtqZkcbG2JyZ4iwBtIHzdd/g8D/AB1qik0Vu1ow2dS7lma1cCAfeS6CfNXJijyUmsefuVlQ60mFszaG1FP5khdA6B1SVRU28v72n+h0RLlLV/NRswgRap3VSyUJQGE0fhZHVu3dyCi7oca7oMWgxis02gKn+xKG5cTD4OndO61TOmQplkJ+CtN+nFNWaqzSEL+viaseR4ybhulLoNq7qTy7lqmdN+fTt5uibVpBTpjdlrqm1Qs6YFxMtIxZ8hXEo5Y5U6dOydkTJ2TycI1PsZOiXWX5iYtqnykdEH6pskUXVIaDm6RMEgknLRDIz/L1jfeOvFx14O9i1F2JtEzspY2Melcjyw/N13+DwhaURk0RWGU1tmVy1uUJO7zycQSylKUMRTHHhJNtbAmam6eNwOjPVOG48au1YrVd49ELIUHkqUipeaqen93RaLRaLRaLRaLROzaE/mAsS4iRRun+pxjQM27DnsfwINyCu2sUDIIGXEK2sss300f45MiZEyJOnTuhdMhTK/OxSR1ZpFOJ6tIbEP2nIuU2RyqKLcclUSVm1tjKTc7OmdM6H8+/iXkpGRMnFD9woWTeSyVqUZu+k2vZPSlkirFVtx3A2omT6OiFEyys/GFF9YGTol1j+YzOSiohatyWZIJNyklaMBssbY7MFTh94apjWz0JWG8/kzE3dZe07CopgMgkGJ5JmRxARV3MF0u7e1vm67/AAePs8UB39qPJqS7qim3vAWiyNjc6xNYYootFCoibcFKvYHqrp2LsscxhLNX0TReYxIgVR/qxqq+n91qzpqiOtoiHTx0Wi0Uilj+uniNhyNFE8dZpGlqcbjE7o4jieibvOzLamFCKjZAtE6y/wBlB/8AHJEiRIkTp3QpkKPXjaErWTzBsAyOooRNG6m3atM4oP1jaIHTC4KUXMUzpnQuhf8A55Oi806NOyJA31CzIWV+TjrFARIK6KunidlDOdeWjaG7Xyjf4PIbN3kwr2pZFT2Dsniy3VRTp11j+XlnOeSQ9Grs4s8zEmJnaMvpDlmlKGxWfBZMZqdnqKCJ6fUTSHvF468bnMce4nhBlXB98jaSvR1KuDgsCbjmfm65PXCxlopjTuhZyQQOibhjd9zi2pVG0ijQeTQvuej9l9mKlzMy28oyRbULJwd1Wiffjm0VZ/Jv7rQsmjZSRaqevoiHT5ZG+h31KvUmaKXH2JpKVTZHYrHJLwyK8JgGDrkVzYtiaNDEmDRD4aLMtpHjv47ok6JEiT+opkHhiGaTJ5aw0lt2cnsWmsUzNC3IMkLaOXGmldiil3ipR0fVMSYkH51/JP4E6JOiUTfUDJmWel1MgW3Rca4mVuLaunbLhYyf8LFaO80UbqWAETaHhS3UR8CXWH5fVE25FIcLBOIsJEb1mmsSYTG9hU6liY8VWuNMdPB2rUbw9tIFyftIoxjh7bRTs8aitA7jZCUmIXaMgZ60fBfwuQe/B8kn29ZlrimfR5X8lXDVCLMrujwaLHBustJIAx3zF4rTGME21q3UAQu0o3KhMU70oLUEsujoWZMwqFh1pPoq5oH1b+5FY1TGnJlLo7TCy0Wi0WiNn2VoXK2wjse0IynlIY1HdikmkidxyErw3cPkIbcr+ApiW5CmZaLN/tY9/wDHd07p3RIkaf1FChTKjs5shq0sRSFFzaP5Oo/J5H8pvu0dmqzOJCSkbVn8kzoUJf8AOO610ReadF4w/cCZZVt16WwTFHZcnmnIVyG5TNvr0341LP3OPxf7kqlUv7nT560BfwddYfl9dEBaLViTwRkmgdl0vbrtXUkYyhU6Kp1rPVJS15Bn/TCbVnuDrHLuVkd0TCDrYKZmUQs5tS7jKUqUVCH5D9OtA0xL+pv5a+dIdUUX02h+h1hx3WLUU7IRndsVE72Ooq51IMRJYKzTicapO8LZTKzT43n3LkXcOq8z605VXmUEmo6/3APRDYT2EUzon1Wi2rYtjqb9OLFE3fZGY4q9CdgeekZxmHalWtlI+Vf9fp1tbrJzZk9lmXdoLWrwnuQ+iz/8fEv/AIjundO6JbSNyqyriLUYT11YE1iJk1qHTFZmOe7VxrHYs76VopYTeU+N43d0ZeRm2o2m12+UZeSmHR0Crfmd2ifwd/Mn8HUXqKmPjhm+op4XJ4oHEpo2JDW1ThtihHQK7f8AG4t/15VIp/KXps9aQv5ap11f+XrVZLUuN6aq1wsdLY+yi6HHW10ldrs/LXlwnUpOXh1BVa3j4z2PFMzDYmgZ4G2hpvFonFPyAoic1jg1tYqwLZrw1TmyeZmR2mXWczHh449wnCni0eg2iL7bDt4YcttoGYmlEAbEjuu5N4Rr4+pAx2ZWr1pf1pM1Y1nCVb9W3KsXnVNQSqtN5DLq4vr/AG2ZMDriddu6aq6ak6Gg6bHpsesjhZLMAULtSyWkox1wKOaxNErDd08rBErsE9izgaEtVnLRTyOyKZ9Wd3UOutX0BaLqBv8AGxnlVd07rVCDynJLFSApk56p3XKnJRmwyF/hXr94oZZy5jOJkMTMvRWJtzl5PEHJJcxY8Eb6EKMNzO2jgq/lmXWrJ/N38NU6hQoh3hL9Ds7EJSixnNESryeU5aRVt078HDRxn8qVSKz+70yX+OJeWqd11d+WxVSOgEcqCRM/hk8LWygZTEWMOVXq7iqwdXQGrWXila5HETlGZPFW2FG/kJKzH+qIJm0UY9nQo5FwyT2hR3WZSX0V109l3XK66mPXGBLsF7Gqc9VVkZlNZZhnn3JnVE9luM1KW9Y0zisXhsWa+LtvHL1dd7bBUzZ7tt3edi0QyJi1Vf1rl5QmoJvKKfzhmTPr/aGigooKDJqTJqbJqzLhZcbLRkMO5NDouEGLaKkhA2sYmMhPD3YrLBouNFGrQeWn1RtqoY1A2ij8M/8AsU/KB3TundQO0FexLyJ/DVE61TFoU+lge+5o3fVEilZlYskmJxWix9StZZyFo8hEJvGXmpm8xUMW/OFWfQwIX18H8NVD6N6aq3j47jFDJWLaW7YWkYk0lduSwMUUTzPqGPLS5K6kVr9zpgvpF1qnddXflgmUc6jsKOZDJr4SRhKN/pOrOrtCxjzGVlu1TJw1dn8xUjb4oReR4Ke48tlCvSGX6mOuPPScndOtEzLRdS/jZPXVaoZtqOdyXr4a7XpztPFNHuervYqglNFHS47/AF1kRsSwwvWoG/gzoSVYlCXlESjkUcqhnUM3k8zN/Z0UbJmWnyb97ttBS5KMGa/ZNNYsM/fMyG1uZptydxkYx4ichZuUHVlhJpQ0KJnUAqPyUSZZ5v0YW2xu6llaIYjadXZdxGnTp07rVOmJSaEt8gojN1qiWiZtEzoLs0a78jYJPrH0lHUWZRNsz+qfzXEGtrQZNfDVQOy5IWcpItoksrBviE2NMzMnJmWHZpJXdSP5V/5hqRW/v6aL6xJbluXVn5VnQmglUUyjkQSJjRG2mdPVF5PHMt6jPV3f6gJAS3tVOeVyoTt2xno79Ombwp/BkK6nb/jCHVcSNtPHVaoNN1X9JMW5QAGuM4mHOWexpSzlI8uS53kaKUbNUq7plXLzgLyiJASA1FJ5xTaMdn+1G6Yk56IrLMnuiiscjlK0YnaOwgFo1yrkXIn0dxnKNRWWNcmrWxeARuEmsuSCDkUVTRBGwptECD0z37X2p3Ujs7Y8N5TS/wCQXq6dEn+V06JOgb5G9RUL6ijbR7Eo1s4GQgNcout+qtF+sorld5b+WgEvalhSZO2Sr5yQIva0wSnkJrUpboy5ZEzm6qZNseUN2Cyxuq76ZCR1I6t/d06WlkX8CXVP5Rx0TlogkUMi9oV4kXUEAKz1ORxPkLInJkOVSNCTxRxkWyLSSNoX8yeP0FfeEtrkXbd0xVCeaizRD/061TOgXVP4uKPcLxeU4afNjpOSPRV/N8ZAEY9eXBao3mnLU+XVQzDIrNd4DUDecPpG6F0JKMk0vlv1/sjdsHIU1qJ4bF2Zzt2lNNaYHtSqO3NGIyXLLd1Ko5bMr0pZJJNH+Qg84LWqNhlA4tlhq7Co5hBBOxLemPzB1Gs7+1mbM8Nz2jadPkLKhyduOOaa5Eu7sMitWBd7M+17Uq55iXPIq0hH4OnTr1X3l8oOqz+SlHy6oN4b0BTWEVmeJR37kbFbsOpslMSKQjWrupYZa76odxOW4X3efMZNvJQORSZAtEMjghyNgIxmcDbJk5kTE1v16fLS6DrVO66p/JvYsGcxTxOFmxIctqyBdxIuc0JSG8wzRFqtzppSZcpacpEgdRoXUZaGQPHarSK8G6GlNq4v9JP4aqJ11V+Jr/t9nLxSxijrsD8ILhBcILhBQvwOMxkPLNCb5uxCFywd6XjFcQJ30ICfdta3G0L6xRaIFG6F0LoHW9RNu/swC7HY05KO107RMJnBIYBDq/avXZ/8cO23b41TYHtratqdvDYo5Fci5Glt/Qdt91S3q8D72CB00e1o1nP2827R5pzj7ZygnsyHGFphhhZuJ4ylgmOOUQP/ABmqDLWcw4WKmtU7p3T+aN0LbW8dPAXVZ/qZE3l1eGt6oHGxesRCUUb13mBqhMDVzYZYY8jWqg8jSV+CXsnncqdlx7IyDs1Hw73YO/uyb59fByTuo5nBTmxjhH0uxktVquqPycchOd4v1KUTlEMcA2XaEIhClXsREDWIAGJn7FwLhYheuR6UypZHh3C+iiTOmdZQXazWkNR2TFQADGFgGHUTW1bVH5Lqn8TTBzCXTtA2S2JrNO6VUcfyQlDHLC9U6RDVeV5KOylNDDRjsVp3BqXbx9psHseC8NZqR/fH99aXa4V2mI6e1tu1RuhdC6Elqq39nvTXfGybJysnysrp7xumumy7013xrvjXfGoMrLAXvBYXvDYXvDYXvDYT5+d17dnXtyfX3gsKTISSJ5XdR2zieHqSzAh6yuCn60uum6xuMveifIWMgWEyU3Y4BBUwEbvXwLt2WAXY4BdhgF2GAXYdPr2d0+vZ3T6jp4CNdvgV2+BXa4BdpgE1HAM/aYBdpgF2eAXZ4BdpgF2mAXZYBRwYGN9+EW/CLq7KQT2u/NNkDZFYIn5nXM6awYtzOhtSAPM65nXM65nQ2zFu9NBkJAfld1yOuV1yOuR1yOuV1WuHVlbqi0y967a97Lav3jyE/cEu4JdwWncE6KyZpp3ZdwS7gl3JLuCXcEu4Jc5JrZsmyUjL2vMvbEymy0swDkJBTZaVkObnFe27C9rTpuprTN7z2k3VFplfz0+Rrx2CjF7RO25bluW5bluW5bluW5blvW5PCzu0TChbaor0kJHnpzYshISa/IybKSsvbEzL21Ovbs6Dqa1H/Z7eFdtCu2hV+CNmsgLFA4s8fG6aON1xRoYAXbxpq0aatGhrRIasS7WFNVhTVYV2sKeCBk0NdNBXXbQKaCFlJFFrwxLqCMBodPQhJjzqxsigBcAaTQipo2W1MDIY2TRitgomFkcyOQScfNhN9BFBsJbBWwUTCy1FOQodrpgFbBWwVhxY7fAC4AXCCeEEcQMiYFILaxRimiFcQKGINYIItGrxJqsSepFodeNBXi1CtCu2hXbQrtoUVaFVa8G7tK67OuuzrrrcBjzfGC4wXGC4wXGC4wXGK4xXGC4wXGK4wXGC4xXGC4wXGC4wXGC4wQxR7eGNcUa4o1wxrhBZoBGnXhMw7aZdtOuCwuOdk58ZbGWxlsZbWW1lOzM2ijZCzJhZMIraK2itgohFGzLRaJ/X+7e+2yGpDFo4PtUUmqHzTemqYlyICQkmNM61RHo09h2drDqOd3QH5TkifzZdQ/j+mfxsiL108phU7J2TJm8HdSyfWcmqEDdVaRm0eEckeGnAe3KJ9VqpSTkiJREgLw1WE/m6LRaJ2UjI2T+sLJm8IV3MdeOfqE3UmZnN4cg8jjctRNTuhKg018GRsoH0IfNvDrr85/TZR/b8jrNfwqs7RgD7lomZMsj52Wbw0WnhZ9FGmTOmdarVao3Rv4On/vXvSYvqHREovWNSy7Re/o4XWJBHNMx4q2bXAy2NfG9RhKhkTFqjdFFvcaTqOo7JoHZrLaJ382XUP4/phv8AjZWT+rN5TMp2Tpk3gT6KU/1IIHMqlURaINFCy2qemEw3KvbykjWxFGm+lDMhPVOsH/N8NE6kUif7oWTeEk41xkklvzDQAUdIFJVIXxt94XhiFyhDlTFq+iZF6A+hwPqHh11+c/qQ/Z8ub/h7XdRzlG0Um9k3pa+rI6eGnhorAMzb42dti3bXZ1qtVqtyIk7/AOuniJrsPu5ZXu5ZXu5ZXu5ZXu5ZXu5Z/wBuvjdbUbEb7tHZMahdArf2Sa7sSAnYYxZmt6yTsMkeUqsM+CzB6VbG9GSqjuIIG04WRxtpebRf9iuovx/Szf8AFzL/ALb0mZWWRJmW1bVKP0RgxlFC0YRKFlCo2Tis7FpXFuQXiXGpAUvkt/nAWrLB/wA3xdSOpF/8oW8HLRrU/LJR+kdfB49UVTVR2TqoTHZcEngEmJk/o/kVQvp8Ouvzn9SD7flzf8OrC0kFoXgCtaKNQzDILeh/VkfFh3PqMLTO8xjAtrMjUcyYlqtU5J38dFotq0+bp/8Agf0hPVM/hZ82li1coEcOihBRq39jt9VQJoK7O7xDDMRFVM2zsRwzU9faGOdP6UPub0R/bkF/2K6j/HdK/i5l/wBt6SLsgtQG2hCy08JH0Gto0hebRKu2rB5KLwzv8OL7E6kUzsv+66ZYP+d4kjUiH1j9FftLdqq3kLJkKjjZ1Zpbhw5l2uO04Yn4507o3VM/Hrr85/Ug+35c3/DofsHG0glTQyduIfbF9VzwJ9qGbaAclw5K8cQmnTsjbRRTeeq1WvyaeGi2/N0//A/pRoX8lP6H6uykFC7CmmZWpm209JL88wxp7xKtMxg0jadRwPcrDWOGbGp28qH3N4H6ZF1r5guo/wAd0s//ABczpvVvSVYx1kBZro+Nh9I5da4xNIQhCbrvbFMRzFoIgyFmyEDHI2RmZpSFtU6kUwO78bqEdEywX87xJGpEHqPpYm44530KN9XikYB7sWUdliTS6NDajUDDYixkrVMljGeGa5q2XRp9VWLRx82XXX5z/YRMKaUH+eu/zZv+FXvR1wbLQL2tWXtKlq2Xqqk+9/Cwep2Zt5VA2Q2n4Qdty4/KaVteRbvqiPe3zt8/T/8AA/0CLmVTFtXi/wBAIVqrB6M8zbmfVpi0azb2J8i6PIOSrW9lmzJwr2vRZV7UdmQFPscsncgKzjXRSNpjy1JlqpH+nKT6FHJq4Ouovx3S/wCLmQ+v/U77Rx0fHDIfLO3jc/YbSWK2O2RubWUzVOuV7FjGUlatWkWaheNoj5I06NSP56sgdMsF/O8HRo1I/nH6t6X9YxM9XjZ0yfboMrwlUOXIRjDHrWoQvHY5a92oO+R5mkzpDonFGCjfQ4S1BddfnP8AS/hdvvuGGaRFvF6d5xdn1b5K/r4P45v+FVFnj4xXEK4QXBGgBg8SdyMn86+TdoJGklJ98Dd6czuQRopGmic/qgPSb52TfN0//A8LmK3R/Lho6/HL+1/oZtFqtVfPQe4/VjP6bc2jXJtS18GLRV3bJ4aKhGw0seFdP5Lqa68t6l/KrC4NJYdnxM2ri/k5aKzYEQy9lt0NvQqs29uovx3TD/8AGSuh9f8AqWTfMZN2Ytoh8bgboKbbyOTahNS6yTYP6Vdg7aWrMyOq84VvpZOpFO6c9FAaF/LBfzvB0aNH6xeossz5VlXj3LhXCqkDT26dQKV18fxHBROZZDDy9zWtDXgqPw5Mb0E5FE7MbL0KoerLrr85/qvT8UdGLeT+SsC230LHz74/kh+75c1/CqftMmTfI5Mz1/1itaBJj4nOGSA903kzQO8An5b1YDa4PoXya+GqZ1r83T/8Dwi/ay9SHZ8kUpwnWyIW4f8ATqtVkfs/+6Mv070ilfUvBm1fpq60SA4RXdhpav7I7Er2LFSGV3qHyQ2B0fGntcbe0LGTYVczG5Tb7DjVIXrHxLNWuWj01+NkdC/nKe0FRDSObG1p1ewpQM7eE32cnBP/AN2LT8cbsL4qTaW3lUsJ46e9eaPG131FzTmyMtVI2qKJRjtTH5YL+d4OjRovWJCs1/EZVx/S3kikNUCaApo4r9IcwTSYrM8qJ2rDcyhWxmn+qobm+KsscU8ex5PWmfmuuvzn+q4XJMDPEEJFK9iRH60ZNkrfJF9/i/hmv4cUTvXD7WTeDlouQURjukmeI931Q134jcZ45K2jQQsVeKAInKmLjk49r+jt6fNqtfm6f/geE92OnXsWZLMnys+j/wCjVarVX3+h/wB5n0jvGnTQSPHXrjLXAnjPC6yZGWoWsVY3fqG5wxssMAvHQHmO3iWnhrNsU9vaN666hkeWWhUEgs1WFpy2K3JuDpx9MabrdtRy7lTjaWQRZh2yav5tlGBrmiPzad/qpzc9W0RxvTneYsdFI43LElSAYrc9fObY61URaGabaXO65nXKuRci5XWD/m+Do1Ii9YkKuV+6rywSwHW8odyLzQso3kFO2j17RQFJkJpieXzlbUqn0DjrGySZuSGVVi0IH1Hrr85/plLbHCPLLJXZQ1xgjlHUjUT6FEW4PGL7/F06zH8QS/xfRP5EtUb+X0sxaOd8frZYqV3rwgKsu7nERApm2qHzjyxcckke2AfT/b0//A8DMpC+UIyNhi3MYuBfPqtVuVttwnFoZnoNw/OGJ55c7TChh8XuZ7sHbS4aHiucTOijYG6mAd6xFh43x7aQwvtbNR9oVi5uVh96rDsOre4xsX2JrVjVyk3LBHpRI0cy13LGRMcYi4M07CuQXV4I2mmfz3atOGrYu08UhjveOMd1WLyjgHbOYwRT2SuWIhVqPbNsW1bVotFosH/N8CRupE/rEhTLYxK3HxzonNNyIClZtTdU67yy5OAq0m5lZoduUbqsej0pWmhsBtKJ9CrlqHXX5z528L8m2LHloRkU8shlHGT6PJ5lH61H1i8Q9fF/DMfxajayxF9di3tlF9R3MvUidnTm+jwdxXcHFY+xwzQvqroPJJDRlXY6KD6RtzNYm8nb/d0//ATNufiJpDicG+SM9iY42I33H8+q1WqnfymPzkfynDc/T9XflOpyc6+Ort292PlOjF+vXNiCd22503muLF+duB9rQv5XKw3qkwSQzxR7122jPqCI3dSstNHwz/4dg/Jy1QlosPK+ry6I5xZ7OjjkKjRRysv/AKTj1jqt+rCfkLaFTLcIEzBlMu984i3Ji2WclVOMjPRPMyeZlzLmXMsJ/N8DRKTwiQoEyysP0s6ZCyD0CqUqxlTa+Wpx2cXaoTVIxlLQDUcixlx4jujvAfJ6hrrr858uvyZI/Ooe144QNTttc2d3JB60C1jZa+DJn8k/jmP4tN/0bJ6Qszs8pbYh11sHpGDuxWpty3kyk9ZG+rG2y2E294Yz1as7rL3OFBKLONgGZrEbrXX5H/09P/wPA5RdTkBf7+5jXcxprMSmnjdpSHWUlr59PvHE2VaOzBhZx23Q4rOLdiUA7AlWdZ4siq58c1ObncT0UZat1XTYLMEm1xmFxsk2u9O2qlDRsXKwVpJ2J2MUxjrjrVYB76qhlr2Fwi9exDy1LjbE38X1CsH1wwE4Vw3qtVDblD7WlFG4tTVaNpMhhxit1Opem5sSZa/LhSYbnPEueJFPGilBSSCtzKOQU0wIZwXcRK5koBASQmyGQVX4ncZ4Iw2PZr99OCnkOQlG6B1BJtfHW9w2q/CdctF1u+ua5QXIC5AXIC5AXICeQFyCuQVdffJtdmp2tWmIXUpeHosd9jfIP2p/HL/xqr/pG/h5OvJSysKMjInfzclCHIVqPQscotGaIG0mdZl/8vximeNwNjHwdTloMUjk3zYzLw0q3vHWXvHWXvHWXvHWXvHWXvHW/wBsEHczhWmkaOvLI5ASmikiaWobVu0ncIoDjjeCXa1CV5JYJNmF+kxfynPR+o7sdmRVA5CxEiElCXl1FX7jHb9F3WjHZ3PGW5DG7q1Htir/ALTwQDWij55wx5lMFSbRq8rl09GxWqxIo9K+Xg22eyJ61entG7VaOxTH6II2Z4vpbJlzmEP04+J4Arnx2+nWZzkiCaPqjpYsWRDo/jS/dqxxm0m1l27vWOpIxHUk3FBKIHWsRFLWsRsEEs4yU52XYysMNGaQ+zsMTVZtYKcjzQVTkRxlt+oK4wd2ioTAI+oOoBI3pRuC2jYh7Yol1p+ZiFjmshFEVWAJ37aQmlrywLtZtkcEkrwwvLPNW2OVOddtLtiqzE5abXHz0UdUplGHCO76attzUczSJnUb/Tr8mX/jQfZLBANWAO5tRwTWE9exwzQSwK3Vao5/eqzujJzVF9pxtqMf2zPoOX/e+SGV4y118HUvm0Kb+zFZKu3fAu9EopMiZNfvtZjLLkpMtzOOQhkgfJuo8izHJeZ62KiZoAf6eorxV4WiKRcGkOOb68QGkwuoy0af647UbwTSOmfzqCq8TOsxCwUqm3YU7HBX/SmjtfT3jcda40D4BtZbbccs/wC1mm/yvSvFu7A4uZQQ7RCPR9doXq3A02+I5X4rjm0U2FEoZPRSwhYi6jwZ4a6/jS/dimCJP5u18hj9p/QeWYnfJhw+1NZZrwnBUuvVi9pCzvlR2R5MRka7EMY3/OvY2rmElPZ/QaXjCzpRtzyapvN68Ds0bs4BYEFSsuS18us/zEZCD2ZWmOGXhIbojThyAgY5JxAMjo7WW5wv8cclsJnfIcxheihkkHahHVBHqqg6Ix1I23o4BNCPG8HG8ZTbIhPcK1Tust/GrODNNaCStWkavZiyUNZvaCv3xuDPbCSsf3soj2j5IPpKtZFxGyDNYmbbem5p/lrya+Duj9I/ub+zqS+pfUvqWhLaS2EtDW2R1oa0NM8rLdMiaQ1sJbS0YHZMUrJ5pWXPMuadOJk/ES4CXFItkzI2l24/p/IZKD3QzK90cyvdHNL3RzK90syvdfNRs+BzS9h5pPgMs6938svd7K6e7+XXu9mF7vZle7uZdP05miXuxmHXurmHf3WzLpumM4y92s+vdnPo+ks5KvcrLr3Ky69ysum1X1L6l9S+paOtHWjqlhLuQj90csrPTuRqN7OsL2fZQ4i4S9hX17FyDL2RkF7Jvr2ReVmpagHca1Nb5FySrfImnnZdzZRkRv7DvuvYOQXsDIJ8FkGUlKxGXY2E9eYU0EpIMXbkTYW869g5BewsgvYV9ewr69iX17FvsvZF9eyby9lXl7Lur2XcZFjrgj3Dsu5dd0u6XPyLRaOtHWjrR1o60dbF7s5BN0xknXutk17r5Ne62VXuvll7rZZ17o5Re6GUXuflV7n5VXKEtCfYtq0daOtHW1aP/aYlqtVqtVqtVqtfkYXXC+wm08NdFrqmTJvBvGx+30P+E8HfRvB/NpG2u7rVarVM6ZMm8WTJkyZlp8g+vz9EwsWNcWZs79UZMeg+sGqiDVuBcCeFPCy6iDbU+cvUUyu3GrK3bt21Wx8xPHimZjx0bo8VE6moWIVHkpoZaGTCw+if5HZP8mSk46j/ACQ/ePp8+xMHmc7wvNU5VotFtWiYVtTiurPzn9/XXwZbXXn8uq1Teair+RbIkVwiXK5KYGBSOmTJvFvGx+30P+E8M4bjRwuSa3F4XMoPdd+u+XfLvl36fJMyhyHKLXHTW3XdOmsumsOu4dR2txNKSaRWL0VUatsbUOqH1+fod9MPLJqsw/0yE4qNlXZQuzNqiMWTmKIl1G+tT5y9RUhuLXyblxlFrTNW0RReTwoolICv0Qsj+rTnxeeG27ok/g6dE2qdarNyfQ6/78IfvH0+fatieJtreGiZkzJhWisSMDdTPrmP7+jt473W50xkuQ1yEuUlyOuRRFq4kzticD3jR4ipCNnF15hy+IPHi8jSeDJk3g3jY/b6H/CeHUUm2GtaOjYpXAu11kC3zvuT7l9S+pakicl062tVmTMtFBmIDMNpNtUP02GZXsq0Ku1ruzCedFmQ+vz9JT8eL52dZgtWkbVD9CLImKr5onKsYTxaMnTrqT+J85ereSsyNGo4Xyd+KAYIzfRa6rapH0RkpG1WXq70buz4DLd/A/i6f5MxLusFCbMtE7KH7x9P9DeH0g7eiZMmZSybGdnkfqodua/8opWAsOHcWY/oF5PpM1eLUbULV7SZMmTIWdykxtqGNWP2+h/wnh1Kf6pszrCZMsdY3sQTPuFxWxbGWxlsZELLpz+OybwxOIivSzZiLEzH1dYnRZbLOU3UeV2U81YrH7ztkK+D/HofX5+mG/47RZT001avQksjYxOwZq8lYsflSqTN5sSJdR/xPnL1Vub6ulaXGEluEW76CR2DVmi1Vs44GO/C7tMJqYd42q/FLjbT0b2u9k/i/htc3o4c3yuRx8RQw4uxanuYmzRZ1D94+n+hlfvR0IJJLuXKr39BVLI2odUxoptG85Sjh0XWX5//AMDX59r+Atqr08U0/S8X1S5UImizwzHPkQiaxma0pZWQDsimTJlSxc91UcXDjxcyNZCHHyLIVmhj6H/CeGel32iZSDuWFzGyvJ+0tFotPAl01+yyZMsrkpBlxeEkuNFjY4m7UE1CM1f6eZ08ctYumuodjIfX5+kw1xTgsy+1Q1ZSEQGGCXzWRZtCfQcTO8uOIkRuuoX/AMX5y9ZT2R15ms19Hir+xTmUfToiuGWjEN1xU5hPMOOqkpMcCcTB8z5I2d2xFjuKD+qJOtU6xEe+xbbiKwOseDjHm6lq8lElF9w+nz6o5Gijy+TkvWa9qRhlnN48ZeKtc3LevVdyESg1ePrL8/8A3yHVBVT1i3ds6etImhNcAqVuN+RO+rlpDZ6mq1quXxFJo6lujdZUsdNuzdQ2KaO6LWmcJWfczJlhKA3bEe0BlJgbJ5c7Ek0b75gcGwOWOrjcflRlFjYmyMnJJ/3J5OLM5TPozLRaLRaOiZdM/Zp4dTZHsaOLwktg/IR3LVCajfeNmuwlk+ngrNh5jmx4+vz9HDrhyBdQfSqNkHr5V5d08nDTsk5LQilojPVgc7TifcaZlpe2+cvXKStHTwpEFkiCmRZQzVuxb3QXZghyGQkZfWxRPPJH/nV3vSNPXybnDGzu7dNXREdU6J07+DrA+ZZZtsZAxQ49u3zuSi5ILDbZYm+ofT52ZWG1gsNqcAQlXgkPbO4nAxagLqzadnqgov2+svz/AP4DFomN1udM7+DMrLfXooo90t0NZ7U/c2qR8dezfigjhvjplsjXIBvDJBlJGK26ZMsJVevT02rOZLchbRlYbQMbviq0rmh0rm9r2K5VJCcJF5kTbAtHpOJrcty3LVE66ZdarVZ16zyx3ILjv5r08GZQm4vcnCKnD1FeAsJnAhEfX5+jiEMKUwOXUpsseI9pcLdJl2/QLTt8bUqBG9yuLFkKyLJ1VmrkNiD5y9eppHGPHSv3c7O491YZO8sq7TR8lATlWJpU1NFX2qdmWd04GVEnC4/gSdeiddPt55cN9SCXfVl/TzlqNnDMw8GQCqAdMD6fOwrKzdvSlL6sfLyRx9wmDR9m0NFZDSWsg+3rL8//AH98joTLQdTGrF3CbHmpo46yGxSdONCQamDC+m6XkgWWpcMLRkyqStZpTkcE9icLsNt2GXnLhmfdLrqhWDx3fWHdo2yOQ2BPaKWzHOJtyCrH7eAxJ5DC5DEWKVqvEcbxzOpIo7AXqT07M7N2s9qFrAW4E1qBd1XXd113dZHbrLATBJK0iyF/s6lq1JcsdOHpWlvRgo7YSo5djNkQZ4LwbspLupxv9DTu4D6/PhJ5Qp1c8svaGV5bR8mEvBkAydY05tDHwRkZ19j8S40Y6N85evVkJNFjf5p1eSNqxMQxA8bDCaysUMadoBHG7LEM2OFXImjWfLzFtXpDrdfwJf8ARJ10+2r5Af0MUzS4/Jhpdn12dWBtv/8A8QH0+dmXVDbaRv8AVFIUckF8WGhZ5si0omMZjI95tJKyj+3rL8//AH+ZBNq/L+njrIVhEV1ARHJRikkJg0r9JU3hplDuj6oqu0JMwDgrxAq7MY2JHiG4DWJclbGGPTVADu+J6ZgjhEIqwWbAbctc3OMbMhbVbEeunTNySDEu9iyjeaqzXx3PlWY5Ra5Qkd3jl1KYEzuvNaOvNEz6dMfvsurpXCDesLG/s+1FLtpxyclyN2Aoydq0MrCcblWHyEC8h9fnC1x1Y5PO4W9U8VNfPG04cdYvg5K3Vd34H3hHx19yezGpJAMfnL1yQvdUmL7Y6r61Zp49beVaNo8rLFLdvvYitPKJUsiYKrnQN8kDGGe8jEtFhQ5cnqnToK0kgELi66a+/JPoPT1nSDMNI5s4zRdat/m3IeDo4fT/AEdU7XoyeTj5uA/TGfFJUzLg1K19WRf66xqB9Q6y/P8A99hFxZhZf93dsI9PWiv080+tzp4N2Rdt0uF0DGlergs7Zxt+DIT7xwcTvINmWkZdQR6ZDNC7GbyFTpT25ML0/HQRnortloxt3iN9NztH4aqf7OiYYyw7Nos+f1+pMHlipPpyMHa3NPqBkwrRaeBenTP8spQiXUlyldorAs3s04hUYsycdwlCDvHAzOYfTL9MjfaPr89fZx6M6pY07804R9lNr2NaYbsUtYQGNqymfuCmiaMbX7kL/V85euQeSvJNm3mjxUzWcVNvaaQ445KWNbSzj+UbWOF0D7ZSpy8jfxM8TlZYXd8Li3qgndarCuFijkqG1OO0+nf35od6GHjmKDchDjHqjGTWLHVsYB02Pp85268JZOcrRTM4yVoOR2j0aSuzuDaFWf6bp6x1ZlRk3N1l+f8A77QuhFnWmjE/19AO/eXy32+mxfvB/kRZGTsjNWR5BOGTdi64hDcH6Z285IzkPF9JySKpSgpRkeiu3hgG3cktm7aJvkm+zok2HCM6zkmtr0TemOf6+ogcbO5CSYluW5bk5eVLIvjymtnMZFq/ksHY21DncnaYoWHIOykld3jsoS5As46w0slCKvTH1+eqOsbNo9SNqmPtzbGeYiGpL2dvKX+NqIaTVo9Wsx+VqPyg+/5y9fVS9M1Jcf0s/YwXaMUymxMNkHr3IR1ubJ8cW+lTYZJZRhG9caKCKMOPhiZ9Vr4OsDPx3sgGoXA2S9N+R7hdFH9Qp41JWYl1mOzDD6fPm91jNh6ZUWGzXl4pOUHUk4swl9VV/oq0I71WZu2nxlrz6t/Of3xmIlE3nPqKbzXT2RjxOPItx1bMtZVm3ysTbSJGei8nUMnGUzcoQ4d5WqY2vTb0RysKvZBo2sTHcN42EXHkb0+SX7eiphDEMspJvsG/0j5qprFLlq/dYzyTEmJblr4O6lPVzfy8MXY45RLVSymCa0yaXextY34rH3rU+ZxslGO99o+vz1m1jH+RbfRrBIy3VJtZQh1sBQ+oqAMbWIPK4LOo2+v5y9WNVjY8O0riqOSayDPotWJpJBVjaS8ohvW9ZpZSmKF9Yn8H8/B3UcrwywyBdr5XHb4cEbxs5sYxTExs+5vDrof+FH0+fJxxRTQEsuOrarVM6ElWL6MG+tPMUHtxU5XjtdWPrnP7/ELNGOjTRbmGvoow0EYw3SSMMg2N0veOu9ZHOzqObV62OnlOtSCFmbRO+ilsMLW8htUspTm/kLlqzPtUnn8kn29NZcaGN96B0PKg5PcZ2a+zJ8sLqLqAWG9G3cM2i08dHUr7FJIni/SYXfwHXWuZMJfUwg63eQROq0XaVctlprYaFdrg2r7Pnh/awsLTZDITjrc3jJRHfRpm6ORmkxWpQYg/8meFnG9Aij45PnL179QZbZT9oocnseHqXUPeHRFn9yLNqxmtWeZzMJWZhyksTQ5iGV+RnHVa+PTdv65x3C9cY42Pa7noUB6rVbl1yWuFAdW430eN2fYti2LYtiZzZQ29rXZ+aLatq0QP51z0bF2mjq+0CjazMwZLqY9+Y/v1REa5VYSjLGszDiQKePEMVjHhG5FimknDHtEzUAI2oCQeyPro1AgyQjotdEUuimt6K3eRG8xF9Iu/kD+Tv5uSdEW1NIifdHhm3RTRxkB43RirQuBUdFCQx1uyFk9EJ3OntrDjpiaWjJDGV1kdqQ05O/gx/QJOL66oH2k+23XeyUTjbZV5WkfGRNPYkykXNZL68fNpcj+754P2+l4f1b7bByE29Y5/+ON+KexJtixh7IIfOycburcYOrsewvnL1r/v2iLSuYBEUEJKvUi2hCDRvWHdXCOVpaYvAWOjAJMeEKnrRvFPAwsExxqHKGLe0wTX4nQ24jerYKtZrzhZiMGJTwaJ20VebabvqnXWz/8AER/bJIYUaYtNempxiZY8WqnhzCWDCtLPjYYZS9miNPsIYVLiNXDEgT+yta16o1VRl9dAHJ7soAUUuqljCRskIhb/AL8Nsq5R5QwUlyQ39oWEOUsCUVySA++lUN7aI5VgY8sxi+TF3o5WvFafqPHo+oqbo89WdTZWM09kDLuYkdkHbuA0acdHkZb2W9kW0kfq57o6F6KvBYy8cwlkyXtWTf7Q1aHJvAwZPYPtTa8l7kCzM5C4SOuIlxEuIlxEuIlxEuIlxEqtieo/fQzhrWUVqtGqnUdakNy93c0NuFlFcx4Sg+j8grcty3Lcty3IJtrYrN43H0rfUVaQZpQNVMjwwFfgOOfJV5KkWQiBgzUO5+osY6sZulIr9uKcNy3Lcty3LctydNd2sF8SOK8VchycoqDIMK9qxsmysLD3sWntPQwyrsT5d9z3WdWLEZw8gppGXKKeYVyiguvGsN1QFGT30w6LrDDEpOqcS695sZrF1jiRB+scQups9RyVCGXiRW90YT8ZBekiT35Cja9IJjdME0+1mvysXfGZFlJCcckYn7RLjs23sqLRpIMtSghHKQOU2VeRR5M4iuWRsz7luW5bluW5bv7J9EURRdIU2T9K1E/S9Vk/TdZF09WZewa6bp2u6j6Xqm9foWhK03QdCNm6NopuiaC9ycevcrHr3Mx69zaCfo+gvdGivdOkvdSkh6Rpum6NpL3MpIuj6bL3TqrMYKHHVKdALMLYeJ02DhdNgIV7vwL3egQdPwPN7o1NsXRlKQH6JpM9npGnAj6XrCXuvWXutVTdJ1XTdIVV7nVF7mVF7mVE/R1VP0jVZP0nWXurWXurWTdJ1XTdIVXTdG1HWIpBft+6tRe6lNe6dNe6VNe6NR03RtZ03Q9de5NJk/RuNZP0jjk/SVJe6VRe6VRH0zTBD01TJvdyk6916q916q92ay926y93ayfAV0+CgRYWFlPUGKQImIrUQwyewoF7Brr2BXXsCuvd+svd+svd+svYFZewKy9gV17Arr2BXXsGuvYVdew669iQL2LAvY8C9kwr2XChxMLqDA1ZE2KhKSHCQSNi+lql238P8euo+lKmGx2Lw0N6q/TlZkWArsnw0DOGDqkpMJWFpKEYv2YLtAXaAuyj0w/T7ZORugaGnuDj1J0LQFF0ZSZP0hTR9LVAVjCwQqeq0aM3FDI7pm1W1bVtW3+zK6kdOiTo03qKr+tP7bf2STbS7t09109109113rp7brunXcEu5dVpNyFaIxQhq/VwbcTiG1qiCEVomDVcaBv8w/IYP48rfTlPqgF94sKYUwoRTMtq2pxTinBca2JhTCmFdN/kWEkwpuNlygy53XObrV38NFotForEmwbloiKO6QhzkJUsjq+u5nTp0RNq6JZFtJm8jtFuk1Wq3Lcty3Lcty3KS6EbxWWkVi4wCV42UeRLXXVnJO7p07rVMTujmPSr5lW9MWfDnF13+D6bbXGmjUgpzcFJcTyblqtVqiByHp2JgFvCZ0bp1ZfytupW1VsNELqPzbatq2rZ/ZkdSOnRIkfgKr+tP7bf2Sjqfbo4FwKWPRRhuft/Jq/m1Xyli2vTUbJhUgpvJ+ri1xOFbWozIQTAmFEq/nal9Yf45KxHuCINoMyOQYRAmJmTeLp07LRaJmTMmXTz7chud0KZN4MyZvHTwImZZTJDuKU5iCE1IBAo1Tn3CiQNvknrPw95qmPc2TFOpfu/0WZtgnKU0tNncOzkdhx8rK1SmiWFN5nIXF3Tp06H1dVfKav6sXFll13+D6ZH/iZi0dyTq23lKWhNImlW7VD6ys0b9OR7aK1U7p06seatN5y+ttvpfyem28WiXEuNcf8AZN1I6d0SdGmQqt60/ttfZJ5HJZCAJsnvXtCVl3vIoj0XcNp3DatabSaXc9L1ibyYVKyddWfisG3+GAIBTD4EqnnLN947mgdTJ28yJgVqdpH5RiAX18NVr/p6f/nimTIU3g3ySEwDZyRIavI4VhBbUUDEuB4igHYoy1YkzO8kMAVxsQ8E8UM+mRhJq7o/X5NFotFosme1sfT3vBWERCNmW1HXY2Cm+PyORp6u7J06Lw/6r/yIP3Lv0TQlvi67/B9Ll/w1n1b1VtvKcfNappFXLcdw9SxUXFReURRzjpJJqtyIm0mfztD5zt9Vv9sljX1IW8v7ZupHWqJ0TokyFVvWn9tn9u2XGjkKzIwMzFEzo4nFQSai5ut7re6YtXoKJvJmU3o7efVv4rp8daIChHTwdGqDavL90XlEpvMFM5GU0f61ln4YPsWv+rp/8gyZMmTJk3yZufhpVx3k3gzIWTxsTRxqPyR7mUfLKdagcRWqW6Z5Ilfljaui9dFotFotFotE6uxcyrAzMLpvBlZhaUWPWplavbWHZOnTr/qD9+H9zKjpUoFup9d/g+nT0xknn4aqQNzW4NETebrRUv5EMTS3o22wWHilaxqDxzm61dhlviKmvSG8hTEjF1bb9N1RLbOzrVEWieX+yTqR1qidESJ0yFVfWn9k/wBmcLaom+l1qnZbeKXg1XbrtUUO1UGUXozKUfJ2XVzf8T043+ALJvB1Isb5ovMh+xS/bt8pAJFVIjrwuKjHQPRHoD+LGzo9FGzG3dR743Hac8YP09+QZMmTJvBvk6nf9OszcWqZMnmEVFNuTAibQppT4jsm6KYk8jumN9cru0dlJ92i0Wi0WniXoBbxCRhUNiN1G4uz7QU+SjgUWWikPa743KPy0nTp06BQfvxfu5AWLEYI9+O67/B4EtKBEiJbkLatfbRH6v4U21sP9N6MGKveIqcty9uLCVLEr5Cu8daact1e82tm4wILJylc/ZUT6SCS1Ro/7JupXWqMkRLVMhVX1p/ZL9ue87Jvsbk8/wDrkfU2coq/1Q6eYh5TiqTecTeTMiHVii8+sg0w/TX45k3g6l+3EOxS/wDzb7SHRSutFctw0wmzxyHDnWdUM2RqAmcdGNtPDewtkMzLWsv1BaT9RWnYsnIabqK0ARZSxZm6e/IMmTJkyk3aa/TJYkd6RO46rL1O9q1tRreaGRf/ABklYXp2uY4i3iQ+WzUTrNq9dlwCtjCrTvONyLjOT7vl08HUlo6srQnMnh4U2WkgXtCW6QyQjJuh0x1dmlzBto6dOnQKD9+L923H/wAT0vLuqdd/g8I/+ERJyTOo/TII/V/DHDutS+V+sWsFmAJwLGwsdaNoxyv8MG/yTxsU4yYIWcoBiWRfQf8AsPu3uuRb0/8AZIlKS3IyT+DIVU9af2SfbmR1umDEuIWd28uBneGJU43aEY3d462rWoNFTHQom+nw2rrkdMJ01+OZN4OrP7eOgGIRb60/m9hnVmw1aC9eO5JWrFK1SjEysYvc+IyDoWW1OKKLVZStGFqGtWsw06sYhmqrMxVuSQMRFDD09+Qc9jR5COQpCkZRu7s3gXoTgSokzxyStGL3gJBE51popEOqhj5QlgJiqRtAVT9Qp49G00UraO6JOiV8fol+/mBc0aExP5HTrI19LPZ8qHHMyGLdeuxDCZY+Kd+2CJsbHz1bZ8xEiT+DKv8AuRP+rI26h0ofn13+Dw5aUyJapn843+nIOi9STLDDrdtednGWeSic+jWchtek0uzLlpXmJwlo2Wmhnl0aZ9XyJfqqJvMYNR4HXC64f7JEpSW9ES18GQKp60/sl+zKhuRmtXXI63aPU/UlEGEYh84hbbfFtK33xfb49d/g+m/xzJvB1a+yp5RR/uL1eZdWW3eGjUKaVxaAYLDawTx65MBr3qUnLV8kTM6YRWXhCS9WBqdSv1Jwqx1J3Ie1m5G6oNh6e/IWz2Q48nkmZaqNtFr4NDEvIWMWkGxDG0ePkZq0oi7/APyoFtKy7cgeapeTXrLQoZNxSjqDvonU0oxJ7MLq39UEv3biW5101/Fb5HUgkVkIZWVk7EI0RigllsQMJVYt1aGsSqSD2uVghhiJOn8G9a/7gfvMOtHpstl3rv8AB4t9K3gyj9Mg/gSZYANZJm1k6cmaSpkZjiWNoOZt9CzUrFHM31V5nhfmaYZFcPfYUA+cFdijeqyOvonjZv7JEpCWqd1r4MgVT1pfZL9l0dzGmZ2fRkOrlih1m0UfrCX03iVZ/ri+3x67/B9N/jmTeDq0saHHQhb9RN62pWijpShbgaMHls1WkfH03KaxUsd/msXZtQYk9KHKJNvFeQqxts1widPjmeN6LI6jAqmOjsH0/wDz5ouUYavG7LVXZtio2OaTVarVOjAuVw4Jdy12nBPtU0xTuH0qmXl1DY2WK0u5A7ENyuwH7VOnHfvyXkz6KDSSKX7/AA6bb/CZlotE7J1eco44S8p/1TCpDrCFcR5IhWxwmMtmMyFnmTp0/h/8q/7gfvVx30cF5ZHrv8Hi/wCP4g/lfda+ZLHY2bInWxwY+uf2dPX2qZXLx7ooDt1YzstsyLiYyRfUFlimr+TZGw0MeurioBVQv0FIykb+yZKQlqtU3gyjVX1pfZL9k/3XomjkdbV9qhyx1i9v2lJlJ5XC2YoMqbtULV4H+nx67/B9N/j2TeDqWNppYI2hq12/UTrqm7x1ql9qlejPzQ2ZSI6MhxPbtSBkZLzQzYScbJV4BrCrEZEow/TpZCtGp7UUVm7O7uFubWjdrVpMB/PTeMtEJTgpBCeq1Wqd0bIoNy26Ocu12taOEkkjAJa1/pbIW2u5CkTEMJKzX/UuNtks1Gr45Y6XztBsm8Om2/wWbw0TsnUsTSiGleXJVHIKTiC5sewS1xuSCIgN6X9B06dP4f8Ayr/eH7+O0KpjS48h11+Cxn8bwZN6XV/3VqlbsVa0dWKy/wCmTfoWDcZMXfbMYusGyKaHQbZPvvc0qgrtGjdoo8hZ7iZkHrCKpF+juREpP7Jv5GS1WqbxjdVy0fHnq1uzFAFu9uKxKRP3Oi7sFYtPImdM7ofNMTihLzwsm8YPTx67/B9NfjmTeDptXsMztBXb6kb6NmneW3aDSTp+1xTy12kkqwxFLNRN7eQykly/0vYaAxbwfzYIYhYsXDq+LhT42FkVKEU1WBYD+e3gzrVarVarVarVF4XImYfVMCgZ00GivHxUIC0WN9NzMcs+0MnHvlvm9mrp5QEQFcfWXw6aHXHMK0Tp06dTBvZpN8e12KEiEo21eKq8pTm5yunT+L+tX7g/fxsW2tD9N3rQt/TuN/jIi0TTebF5XH8OnIdZpBlJ5vOG39FK0PlgsueKt1pAsRTibNbMmVrUlG2x8jO+10yH1gH6BlONocpNvht8iI/7MpIi82dD4P4A6GZo17WmZjslo84un81Y+lN5rb5MKZC3kzaofJYH92D08eu/wfTP45k3gSCeOK0X2106k+3IjuyNh9xQvskr3WljqWIxk6gzQkFSL64T2nhci1qPxOuW8q5Ioz1gh+vjFxwP85a/LqtVqtUwEbPEIoo4LY2KoVkyrnouTcsmX+FGzsVM9FLNGK7lnHtIrDSdPT1xKIxeL6WsmJy+7sarYOvEoq4Qjp4OiTp16py0MCE0DChcdakznaP7nTp/F/Wo/wBQfyKP8Sdtlzqgt3TGOf8Ax9VJ5phfUftuOtVgachVOeKdPXaKvfH9KcNQ00fprIHBAdsXGzIxNadSPo10vL/vamZVg1gJvpCNgjp2XnlOE9n9jkllOaKWFweQyaU1zmuY1zGuSUSm7mFwllMysSOzmSac9JXPRnQ+jJlHGRqKrohqM6x0AwKv6N49d/g8ZZlhq89vZ39hnK9aFPkLKa9Lylk7aDKXGXta4iyd12szyke1lxiopHFu4IE/mYm0Y1DYosWRVrLPq3hcuzRWWsWClGMtCa416rpIGOMo5+eyu8mXeTrvZ1jrEkp6rVOWif7I5hcCty6xkUh+QPbZ3Tvo8ZaJjdWH3DKG0htcSpjqDP5xF+pYs/XdwkGQe7jiqz2I+KTvLLmdi1Gmu2ifv7K76yu7tOgntzFLYtwl30zKa7O6eY1zyMqk8xqDyDH/AMicCikdOn8X9af3R/v47zp2/K11DLu6bqm4xcE/HuNzlCeu/KalfcmjYyqX5xhrBYrA96w4yzyGzkTqWBYWfYQaSx2KxMrEBMpx8rvm7AnHy00akLdtKOiqFyRyjHBFBo4f2ImdpL37uPmCst1UDHthgcoiCXtnQHHHfGOCNo5IIpx4URUhsHLXBzem8dxh42EtI65Eo4BBNoyYkxKhJueB03j13+Dx47oTf9CIWKSWWCwUDVuSDjEweMq2kXIc1eOOpbaZMccBCUB17HY8bT1DtBJUG5NDWegx6vBJxx1bTgeGy0eRh1WqzGnd1tpt3NiEuOVccqpfu1J43KNq7Vimjjjhjrw2sZ+5uVq4NYYrHtA5yeQQLQNfOs6M33SiTpxfw8046o63KhxYbj+kVF+4R6zyFvrzMGXhycckNoG/UsffUkCBxaFlFJGTlwkU7sU/0lKQwtFJwMQHHKwtU4cdqyF/Kg+2xcq17di5hXEZYpIkXiSp/eH7+L86twv8rOH/AMHUFzGUm7SmTBc2Vhkft3tFxKsNN45hhGrG7OcDQxhKMVaK7DC8Nmj+gDlDJi7bSg+jqyDOrUHlLFzSnXYEQpxd1U1GKT6jDZC+SrlcqQwNjqf9h7ROu4JdyS7ol3RLuiXdEu6JdyS7s13RLuCXOS53TWCZNlZWb2vMvbEy9szJszMy9uzqHqW1AQ9cXgTdf5BfEDIL4gZBZbqu3mKkVw4Q9oyL2jIvaMi9oyIcjIK9qSr2rKynuyTre63ut63re63LcnDUmbRMbsqeTmoze+15e+t5Weo7NqWHPTwsXUdgj97ri97riileIu9Nd6aHISgT35HUGWmrv7wWEWVlOaTqCc17ZnTZmZm9szKPqCxGn6gsO/vDYZPnbDr23Ovbk69uTr27Ovbc6fNTuva8yHMzC/tqff7y2tvvDZ1yeSlylh8nI7+0pF7SkXtKXT2rKvakq9pyL2lIvaUq7813hrvDUWSkiXtudk3UFll7yW0PVNwHfq22YSZUzXtCRe0JF3xqLKSxO2amEq/W96uEucnlltZia3WCZwbuCXcku5JDbMXed3Udw429oyKO9JGvaMi780GRkjR9V2JBlyZylBn7FdN1hcZF1ZbJH1HYNvaB6nbM1zOuZ9RyMgt3x7prJTKvmZq8U+Zlsf8A5lVrlbsZXCez4f8AVHEcpdjaRC4P/SihOc7OMmrP/qhhOxJapT0icXH/AFQwnYk927qnwNyvF/qqY6e63sC2nwNtm9P9UFA5hmxpg3z1MVaujHhzG3IHGfzCBG/by73bR/8ARFGU0nZgux3f6xqagdTQP/Bwsf8Al52PnreNeIZTsRDEfy9LfvqepDPl81+U8Io+WSzBFG3+3F5WChjpqM+WsZNnG3/pxE0le5kMg5W8/kK1wMTHKimMMb4dpFw/JgPyisfseHaRcPz9O/xMiVtpg3OE37viI7isVoow8QbcWNjFllBZqt6MYrnyg24iNqxS7btRV4mmksxBGXyQT8NOtdeN75EdxVogkKxE0Mny43+cqJjHb8Yo+WSzBFG3y2dRneZpfGvE00lmIIy/2RVAEe3iXbxLt4l28S7eJdvEu3iXbxLt4lbrjG3zU5jjkyMxRR/6qF+THze9Mqt5iezYsTnam/owTCIwZiLHY4icy/04fMVqNW11BTlrTZijLS/0gZRlP1DO9ebKXJw/1YjKRUoizdI0/UFXQi3F/po5jYrmZYmInIvmq56E6+QzgS1/nx1yOsLdmb2p+5sf6I5CikhyHFYk6lcw/wBUkkNpgpYwB/o4urXtwhgJDb2BJyDgSd/Yx7CwMgxF09MBN09NrcqvTnvfs+HazcX+uGrNYb+qVWYIv9jRGQkLiX+wAKQ9hbPmkrywt/Qlrywf6I6s0wfPDTnsCYFGf+iGrNY+YAKQpIyiLxlryQeMlCzEH9QX3NFkLMEPte6myltj9sztUDM3owfJWnD2la3NkrYlNMc8l5/0vAbMHZTFQ3TSUimGxRJSTVtBnx7TRWIDYmhC4M9DdGdaNrpRlIgKOarZtxStHYpvb5aXG09PmeaixDarckjVwszS0DOIqnLyU4oLxwlH/qeWmcJT1O5eWpxlYqSSSS1Xfmo7Xlq7o7MTNdGuxfJQsjVijlqnBJLS1isxMgkoOD2KRNJLU7X568z154rFU4p7NdvlqxNNPuiNnlqk5S1nd5aWozQjNujas51FpWCN56qpnELA9aWUZK+pSU91gq/a+DerS1tj2agTNNSaBzqlJO0bTeNa4FaqU1Em56G+AYJGGegL3TrlF4PIPYFLXd3Om8B2ahqOai0sc9JjealxlPQ5b8kUsypNHWH9CCJpqbTwzUgKkUYg0tPja1XjIJKZSB2kbNPQ3jNSGO/JWKLwksRFanKoFnmoyN3FDfz0zZ5aDJpqPFJYpbf9oTHG3dTLupl3Uy7qZd1Mu6mXdTLupl3UyIyN1xrjXGuNca41xrjXGuNFukfjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNcacXduNca41xphcX41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNaPt41xrYti2LYti2LYti2LYuNca41xrjXGuNca41xrYiFyfjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrjXGuNca41xrj+fYW1ojc3bR//AAwgIl2q7Vl2rLtV2q7Vl2q7Vl2rLtWXasu1Xasu1Xasu1Xasu1Zdqy7Vl2qKs7f+mLeXiX2/wB7a7ogISavK5Ozi/zYbFPk7E3S9HivYuegouPcF0YceNqW5Uk3NJ/e6cq15cdNTqtavVKzVVAG568B2pnw4F4RQSTlNXlr/wC+KvLMnx0rIcdISsU5K6nDUVhabyZF6mKWcoURw/hh8Q9pTYrjjylDspVEO+V+mazr3MjWawI4qv4QRwO2lIvGGIp5XIq0Y5Hne1XerOqlfuZ65Vq4yU4LoXKz07Kp1u5lr0dIrPTslgDB4zXTWRejhO0nsKK6eLu2/wCUqFPu5I6NZlFEDRdTRRxzqpWxJVirYxSwVxjTeleJhEZFehDR/t+b1+SzTjhHwCI5FsJcZ7PD2ZII2actXwkxtmKV22vHj55I5MfPFH8s/Kde3+tZOTZclkKaTE4GfLDksbNi7HyYfJY6PHtmMeupcpRloRRFMfYzbpA4z/v4BpfZ8vP3Fzm7dVvtxtgK1upWEbNpjazUfSKuwHA0EMiMIiUkcXZ/6qwRKrc7qTuoRls2ChsPbA4Jf21ijYE92BZbJVCwvh0rbhhO9lqYrqCcZPCt/ImtRQJ8pVXVhseP8BgkMArSn44kmG/Vn4WsY3gr5T6ZVji0nvkZDj8pXgqZC13ltYgmYiiO1HSAoamRkGW+uniaGC5WluTZBvOdts6wsgi2KvU5JMpc4xlmknJYKcoUNCS9Jdry1HTelC3FBH7Qh0yU4zM/2/NBk2oQ3CgkmVZoylsRRD44y3HUqteHsMs8skyA3jPHX+UL9/uHxttq4RTR03k9cTkIY8HjBHFkgB5C9nWO4ajM8/suxrXoy2RfG2GjfHT8xg8Z9Nz1qmL6uOGw/wA9SYYir3oqoBkwjk9oQtUbIwcftGJ3nNpJv7eKy0NOqearlNYy8EkSjPjJnYmUkhyl/vx8lAW7vHi3PT1CzRZT5LHxhan5jUd/jj9oKQt5+AZFo43yg6SylMajLjkv58bkj5BlfyzXKXhDa7eOa9YsD4UpQgslNQmIbFSqjN5DQk4v3gm0k7eMchRHFk43V/qLkg8MFlsfVxZZitG9XqPGtPObSTqOQoibKPpPYOw/g0xMw2pRRzGfg3oEu1dwykleR3+3/URkTf7xZnKe5VlnK7XlmK5VJVZKteOS9VmQ5KvBYsmMtitbmpSGZSn/AOd6LkJchLkNchrkJchLkNchrkNchrkJchLkNchLkNchLkNchrkJchLkNO7v/cq2GrSWJWnl8aloaryHySf6IboxV/k70e18GPyqXhqv7aiViy00rv5f+N//xAA7EQACAgEDAgQEAggFBAMAAAAAAQIRAxASISAxBBMwQSIyQFEFFDNCUFJhgZGxFTRTYOFDcaHwI2Jw/9oACAEDAQE/AfOyLL3/AJf7Qpf7Q8RCWTFKMHTPw/BkwY2p/wBLv/8AMk79ZRbKa0UJPsh8dy/V2S+xsn9jZL7G1myX2Gmu/oU2bWbZfY2y+x5c/seXP7Hb62Cr0KGunF8pk08P8pmXOqGUUM3Cdvox8zQ+DchfENVITM/t6GL307EY3rk+d/sSMb4FBIcETVPoxfKT08P2M65KKInlMjgbMuPYMoiq6MXzoaNpEycyOxmd16GH307i41yfO/pYR3M2KiSplm5Ckn6MK3KxRpiJMyO5dGL5Senh3wZtKMceTciLR4kZXTi+dE4uT4NnwkItMnP4jczL6GH30o2e5GV6ZPnf0m0xIpjXFjQ0Lia9DB89HuYnaOCSSVj6MXyk9MDM2sO5tVkoqzO6jWj6cfzo3imWSfNjyIlK/QxCiJtzpGzjkupjyEuZP6NCpojJRfBubJD0nxz6GDuR7iWwszT4pdOP5SWmHuZOTtpHvpyZpe2jRXRD5kRaZGMbM2RR+FChfcUGmZPb0PDq2SqMRS2ys3/CSduzch9/o1pZGdEp3pIkY3cemzlsxQ2RLRTZKsa3TMk5b7Xub2bk9O5D5ST0g6ZKd6xdMsXCJO3q+hdy2hZZrsLvbNxuZO/f0PDurJZNxDDbtnmPdtMuNJWP6GOFPC8rfb0pKyUZR7DySswO4XrQl7iytdyUnJiz5F2ZKUpO5MrmyiTanwLkijw2PzpqBPvS61I7x6Y4U8Lyt9tezNxuZbFIXJm9unxGFYK59r1TaNzFmkjd8W5kvEvK6RJV9DvlW2+Cjt10UbEx4IMhBQVLoopGyJ5cTy0bEbTyokYKKoXBCUo/K9KK1oopickUymUyqHn423weZE79F0b2yOaUVRKTl0J07RKTl36LN43ZH4ew5N/TUUNdT0XSkRibUSXRHtpRWlFdNaS7DQokehKzabENV1WX03oxfRrTy2MorofzFdKFEWklZKNa4/k6+OqXYhGzYjaVqhPSXU9IR3MWNE4RSsa+2lDI/Rx7mKFuyKsni5Hwy9Hp+uupEFUdGtGhqtMHONdLI4x4xrbpu1l2Eq138mxdxxXsUKJKPJJdKQ0Iw/cRkVxo7asj3+k8HW2zd9hte5mfxPoZ/wBRde63RZZasoktPD/ol0sVkkzIqPbol2JTSFNMW2SolFxYmIaIO1pPrZi7CVIjJyjZJ3yIseif0eHL5R+bX2HmiS+J3olY8fAz/qLqiQpIZOftpCddzhklR4fjGulifB2M3c9uiXYbbE6IyN6fzG2HsdtEOQ30LSyzCxcnbglx0PTd9DDDfc8qI8KJQcdY8Mc1RIr4uu2jezvrBk0Rj8JbF2N6NxvITPMJvnpl20oWOfsRwTa5PJmjypHbRrVdWJ8ikTl7j5OV016sccF4dzkudUeYyOalR5yNykZIV26Ge3qQYzwsFkyqMuxJpy46UyLdk38Wq0l2IYILA5yXIuDezczczexaI8ps8uSOUMjcux4qGPHSh9ujcxu9ezFq/V3ilZRtY1rybpaVrkyeVG6F4pP2F4hP2FNP26dvRZvY+eu2c62y2WWy2clstnJycnJvn9zzJ/cbb79VFFFFG1FFFG1etETESRtNjGq0Q6Hp4v8ARkRMx6ojEUCeMo2lG3rjBs8trof7AyZYYY7pukfn/C/vo/P+F/fR+f8AC/vr0EIjpFFGTsWWWWWeK/Rkewu5DE4xNpR7mMQ3wPvquuC4KJRRLh/ToUShr0Pxf/K/zXpLRClQpGGSY6JcmWk+DcWbizxP6IXYxrdIlxBLVrkXArJXWrF1rI0hZRysm7fp36kTdRuTHx6H4v8A5X+a0z+HyeGlU/VwOpEpIzMkMts7G4z84SJ4WHx2SjuJR26R+Jm0S4HHgl30YuqKs2olGkO0rIx3jxIfoNUi1QtXqumPLPKk2eQ2ZMTjEXX+L/5X+a0/EfFYY4vKat/29FaIoiqYpGR2yrJwOxLSavCYsTkYMVFGbtpj7li7E5fCWX6GPuWVpwPkyIYulK2M9hEuHo/Qg6ZdoSdGZ/D6H4v/AJX+a0cZ8t+jHSPfRaS7kSXI4ko6VugYcSSIcG5GWQiHcRfBOVjNxvN/UmQkbkSyWzbt7MbJcjF0wJPSiffqssvRIx8oRml8VF9f4ninm8Ptgrdn5DxX7jH4TxjX6P8A9/qfkPFfuP0F0LuNnciMRNDgYV7HiXB0sf2G+RPk7kfch3ETdDGdh6eF2LKnPsSdy9DzHHgx5XLuOQ9IuEfDvtu6LGYorbZKXNEh8dC5PEyg6WOu3QjEy1Rkdyf0Vllm43M3M3Mtlstm5m9m9kXaL1oor1YqzaUUUunzGbpCTZtY7RuZuZvZvZuZuZfpV9PQom1FDHrHtpjx7oDVOiONs8lnkyJwcFZuHNR7m8sn4iMXRGVq+miKFBkoNdaIxIooaJRK6GIv9gR6GMSs8sS2rTEqgZsd/EiHbXP8umfHLJSR4fwzhGmeUZPCQlZs28dKMdbuRpMa4o2jXHTDuIQ2WSJdGPGmSxolHb1rFGh/Ryv9U/8AkKyN8mR1EjN2IRRIYkIeWmY3vZLEmQaqiXYrjXN8umONvWRJPpRDuVwS+HST46YC7CGhIkPox9hsydMdIyTRNckuxH6HsTmyEnJ0TiLHLujHzEjpN2UJFDxxMcafAn7PS7RtVGxGxGWNREYvmLH1p86Y5uUDI2KRJqumBDk2acGTVKyqZB6PnpR7EG0XbMnYX0MnRFWRjUyXLowfhs5RW4l+GKC4HjeKW1kqSFwzuO4qyU70h2MKuZkEz21yLdElj2Iw/MWjgZx0rtpinTozSV9ceCDORJ+4zIy9IMnHerI3EbLTH0RVkMe/glh2CxoyiV/Q5LZDhFVyeFpZk59iPisCXcXisEnVn4hkwvt3HLTwfgvNe6XYy4YbdtHifCvC/wCGkOxhaTtk8kWjcjzY1pROSRkdidMTHRJi6V2GL0FFkG4sUkzeiUkS51XBGXsUSKH0Qq+SOWKZLNjku5uTXBlL+kj3Hkl7HmSLvTwmPFJ7skheJ8PHhSRk8Tia+ZGTJiyxpyRnxqE/hdoiuBa2ee12JZZy6IzRuQ6Y5KulMfoxzKHh3jXd6LoyqV8F5F7G6f2ItsjItacNnis3nVXsuhFkZUSkMX0G+X3FJlsXVZZbNzMXxdzYjbElFaJFI462WclMooURxobrol2Ittm6RukWzkUWbTYbStKbNvwiJukbmbi2WyPJRSFFDihjLN3qojotdtm16PRvTBrLt9ClSFivlmbHSISadaN0N2iPzaISEiMNzI+GH4Ynj2lFFFfCe5k+UT1oiuhjJDZfqpCWiGIihxTJRrRj0way6No+im+tEdMvYnwyORjbeke+iERMPBGiUoruZnFrgaGIfyaZPl1WkRHGrGSlyLn1UtEIZEooyoYyMbHAwqtZ9tInYjByMkGhPTY37iUu1ksbj30rRGRrYIToWT7k3J9jJ3IdxIoXzCEREY7bEsi7DhPszJiceWZIuDpjEfqsaoydtUIibTbxpQxnlijXq1ohDI9yyzLKxjIdtMffWekRRuQk0Zew1TG+CMU+UU0+5Jyn3el2LXc0jHUkTjaohH4eTLH4yXwuyOVM3le5R7kSJh+Mrng79zPFOPBOUpP4hiP1GPsT7FaREREPWWlDXqtFCEMimzsOSSHzpNGPTH31npBWQdTFZmmTjzZL4lRGLqkSjKQsUl1we0jTJz2Hd2ZCPD0i709yLIsxZNrI8m2K9zPPiixi7n6rI+5LtqiyHOi5OBjYhl+qsU5R3Jca2NilQ53rRk4Rj0g6ZNSx/MjeiTt6RmkbuRZ6N2+Q/ijQxOh5XE8PWeDl29CLoyfFyVwONsljNzj8xBe5HDmnHeuxtYkJkZkc6iRy748HiO+j0/VIj7E8OTH8yo2iQ0Y3tLsRZIoRMcq9XzqxeWl18C2m5E/iRCLT0jSfJmzec0y+pOmeYh6M7dSZZZZejMmLcY4ShL+B5lYfKSFfRaMfiIRjRlyY8nuWkXpu4IujizPl85r/ALdCE6NyLRuRaNyHyOEn+zJ5IYo7pukfnvC/6i/2f+J4p5vDOMFb4J+F8TOEYeV2/gR4X7DliwYMfycf9jf4P+H9P+Dd4T7L+n/Bv8H/AA/p/wAEPyuR1FL+n/B+J44YvEVBV+w5SUIuTI+KlXMT8zL9xj8Q1Xwn5r/6MWduLexn5p/uMj4htpbH+wf8WwyivMgf4l4T/T/8I/xHwf8Ap/2P8T8J+5/YX4r4aLtQ/seM8R+azb0iyyyyyyyyyyyyyyzcbmbmb2b2b2b2b2b2b2b2b2b2b2b2b2b2b2b2b2b2bmbjczcWWWWbmb2b2b2b2b2bmWWX1WWWWWWWWWWWWWWWWWWWWXo22yLbXP0PjZbcV2PI3OPxf3++i0orqjGzbEkkuxFWx6OqEeFcIxlKdV/ElHw08cniadfZ6Rbrbs08TulOqtKuP58/0MUsfmLyuzv/AMHiJOGKUkR8PkaWaL5IXtW48P8Ai/5DHOOOCeS1T/geKyvxOLHnnGpM/DsccviEpK/4fcqPiKhNqnfH2/8Af5aZZzn4vY5UlRgzx8RHdHoyNylulI8HNzxc9WOW5epHNN59vt9Lmwxzx2yP8Nwcd+PT3C4HKxOjc30TisuN45djBih4e/L99Fkmo7U+NJ4Yzlut3/3IYowd+4+SPhscO2k8MMnzE8ksj+IhOUJbo9zJ+JeIyxp/20y+GxZ+ZojGMFtj0ZsClP8AR3/MxxUIpJV9FXN6f//EAD8RAAICAAUCAwYCCAQFBQAAAAABAhEDEBIhMQQgEzBBFCIyQFFSBaEzQlBhgZHB0SQ0Q3EjU2BicjVEcLHw/9oACAECAQE/AfZMCXT2oKq5v93/AEhqlVWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWTTlFpGDCUFv/8AGXHymqP1Ncfqa4/U1x+pqWVru8SC9TxcP7hYkHwzVH6niQ+opKXHkOSXJ4kPqeJD6muP1PEh9TxIfU5+dk78h90Sed0N2OBJUYcHIeDIw1uJbDgVXZiusNshHUyWCNaZbF3Cxx2s6Ph+R1PpkiUqWeH8C/Yjekc2xTYt9+yJPNnAtyWFqFUNiWKkRkp7kWjUhu+zG/RSMKLGzFTTML4GhO9mdPBQuvI6n0EcEreSMP4F8q3QmIopleTLZDlY0JEfh7Ik8kUOIo0RJImmYOxqZqZF2+zG/RSMKahHceP79nUYkXHZEYXhpmlPcwHd+R1CuhIjubPZko6Xlh/AvlNRIvse8fIxNllibPKN8dsSYslmtskzDVyJIjh2aNL7MT4GaLQ8FaTFw/doSksNRR7PNmDDRe/kY3oSYlUC0SVwQoWQ2ivlXuJdkfp5GNwM+JCMOPq+2JPL1z0jzwl6jjZhpJGK12T3iy3ElL3DpcB4z1S4Ooxd9UB4ykrs6fmS8jqHSIXKRVwo9aK2oojx8rQ0JZIW5JU+1KxJRRiT1yNLfAlRHDliOkKKcdzwkyUHHOJLjKKs0j90seUuSKpZWS7JcFI04b+IniNx0YeyHBDwomEorjyOpV0YeFo3MfrNEXGIl/w9Z0fVTxJaZCXyLl71eUpUbTKoa3zTou9h4afBhxUY0OEXyjaqRe1DNClhklpdDe5KeiNltrKL0niMTvNj2l2S4HL3qze6NJoQ0qHElS5OllqvthLVm0nuUh9JCT4JQvCcIHT/AIeumqUnuQdr5GkXlZZZZZZZZro8VmLjTWIoxV2f4n7F/M1dQv1PzPE6j7F/M8TqfsX8zxOsXoj2jrvojx+ufojxeu+iFi9be8UeN1P2L+Z7V1X2L+ZPG6ibtwX8zXj/AGfmYWKsXDUmjUWamcm6NRrNY2mazxDxTXq2NBXa4piw0ifTQm7Zh4UcLjtSrscbPDQlRL3iMNPzNl9n/uof7M9C+1F0ahOx5WdJ+gjlZZZZZZZfZDkssfbrNbOfMorJ/K3k8kIok662C/7X/QvvZQnRefQu+mhnZZZTGn3Q5ybZqLze5RVkfp5EnRrYpMTLLyl8mxskJ5UULLE/9Qw//GX9O5eR+HO+kw//AN9exuiLbZqNQ91lSHlDnJlCWxbLLGxMi77bLOSZRHkQ8kS+ToxuSsobrsRiL/Hwf/a/6eXIvL8PWnpYLsZhr1ytEN83lHkW+TQuyso5OSRq7Ik+TkpJkR5I5Gvk54eo8I8Ni2WVZIxP87D/AMX3vJRykhiOhi/ZodjMOdZURlS7Y8izo3zeSJ4js1ikQ3jkkUYizh2LLT8i5/Q1M1ikmNCLyiYn+ch/s/IrNkhcnQbdNAaQ1uaGaDwjTQ0JZvjKPObxYL1H1MUzx4s9ojYnYxPLE3YolGH8IsrJ5RVsWxSlkyyxPzb96uzSaLNBRFlZxMT/ADUf9n233Mksun26aNC2Xa0S4IrYooeUeR4j1UhqzwoihE0I8NdksZR2NSZZqML4CDb57NKEqGxMkrXYvN0j2NR4gpmo1motGs1o1Go9nfU4ialTQ+gxF/qs9ixP+a/yJ4M4f6j/ACKn97/L+xU/vf5f2Fh4n/Mf5f2HCa/1H+X9h61+u/y/sap/e/y/sXP73+X9j3/vf5f2Pe+9/l/Y0v73+RhYawoKC7qKRWdFIpFIpGxSNjY2LNjRhv0PCh9Dw4fQ8KH0ElFbZ2WWWWWa5F5WavOkMYu1isWXSfGSGjGQxCWxizoliinZYpZX84835sMOWI6ij2PqPsPY+o+w9j6j7PIYyXYhoo0FCOk+MfI+DExFJ0SQhLY6jkaEnYxEeDE+cfyH4b+n/h5by02aCSoWS3NJRpNJ0v6QZJ1Fsi7xGxiE/dJJSZOhVqJ85RexP5SrNA1WazeVjzoryfw39P8AwywceGOrj5L7JcZQEVkjSdOqxRnVT0wojjJEMTWRRL3YmoxHuLkktiiFepiRv5RZNZrN8diHsa1R4iQp2x9/4b+n/hl0WBiyxPEWy/8AvyX2UOJFULNLLCf/ABTExFE6zG9x5dMtyKMTgomQj7xLg0o0opfMrNlZMWxLdHqOkYfxeR+G/p/4ZKUeF5MhdyyumQlknpmY2JbMe2jw2YOyImJwOQ92QjQyETw0eGvOfaux5LNlFFFFkuRkI7Fd/Q4kcPGuTo9s6f7xdR0y/XPbOn+/zmLLEIM1k2Ru9xU0YqWkWxFmK9iTIckcoCeU7rY9PIUbVk46ex259vp2NJlV2QT9exkkNEdl8nRRRRRRRWdFdjysvOyy/Ilsa2WWW+3QhpIckjWKmaUaUaEaEaUKCY4Irtbo1Gpmpmpmr5eyy+15TnUi7Lo1I1ITTKKNJRXdqJPJPJd05DYmJkJF9kCRXbL5t9+o5yxH75CRLOHOSRaia/3C0zQ412yHwanYmaiMt+2XBJDQkURF2TnpIzZhz1olz2Sy1O86+RR7pccrLzWTyoo3ROLTI8jWVEOcm6RFDiUNOu2RLg9c4fF24i90bfZEXZi8iMDklz2TIjjuJ0Q3Y/kkh7C3HpRLNFjZZbyspMcNM8rLI8lElsJJKxe8SVMa7ZcZS9yZB5LntxXsS2LLLIC4yboW6MX4soOn2yI8kkOBh8j+RihjODE6yEXsR6vWKercTz2uhLJmI/dOn5Jx37I8iRuNCTQ0Xt2t5YkLRhKkLuluTiLPDjnibmHLTsT3eS2I7rsmRk1IbE3RDkb2+RiN7lmPbw3pHgY30FgYi3o6aM1yVlj9Ro91EJyuzBxtayZiq1sYS0slTGt84Id2MTGy+5i7F2tolUkaWimJECnV5Pckh5WQ47JKzRLUJPKD3+VfAoR9TSissaUkqijwsR7tCwpXwKEo8Iw5Nrc9RiyZpQkkWaixUOhNCrtaYkUUymLtcLnZsS7Omlh+HUmSjgP9ZDw8H7jFhFcMaKZTI8EI6e/SR2+RjhQrdEoR+hpiNLJm5uWzctlvJvY1M1MTYhtmuRqkapGpmpmpmplvOzUzUzUyeJpQsWTE2y2WyyHJJbFI2Ni0ajWazUXlsbWTVMRRRSKQ/IrzeCWTyl2LJLKXGa5yZyRj5DH2U8WX7hRpER7onKkYT1OhbMl8JY2NjZqpWx4osYU7EyyIuSfBHnNljfchIrzZMeTyYy8lmyfGaGMTqRrOR7ZaWzSyms3nPghDYURIonh6kQwtO+T+EeTGSGhRbMKLQskLknwR5zeTy3zQhIl5rYxjyZeaEPKXGcRk1RGGo2QjEWxW4ppeh4kfoLEUuFlaYx8GHercZDfJJepWxZY2XcSspDJUke6y4mHJNiEIXI+BZvJl5MsWWsbvzbzeUs6Fk8p8ZxHwYjtHwxyWSw0nZKbVI1wa4IyjHiI+BRolsIo0amRjTFsxvcv3RGlooT9MmMaJ7C3QotEH72aFzks3k3kh5IZYn5zyeUnlTKyRLKfGcR8HqS+EQhP0I7MlKHMjDxcOEtRi9TDF9M6KziyyrJOokXZyhFU8mMZONoXFM+Ewo+oskLk9e6W2XGaGLztaWxZeemxRrOyLsllLdCVmkS2GhxK2NOXrlKKfJDAjPiR1OG+mlXPaxssw2xEyJCRpT4L9DXFOs2hwHhMlGjD4yoQuR8j5FJPgvOas4zRYyBp82vevv3HqNLIppjd5MjHT5FZrZl32uLNLPDZGLWTSZpXplCeklJSRXvX20yeFJshGUCrKELk1KyTvggtPYxqymUUymOLIqhSX7MbUVbPGw/r/ANH9RFyw6Q8PEaS0i/Ydyk+SsQrEKxB61yYLbhv+w26FiP6HiP6Gv9x4n7jW64PE/cKd+n7B8CS4Z4OJ9TwcT6ngT+p4E/qYcNEaKKKNJpNJpNJpNKNKNKNKNKNKNCPDQsKIsCJ7PA9mgezQPZ8M9nwz2fDPZ8M9nwz2fDPZ8M8CB4MDwYHgwPAgezwPZoHs8DwIHgxPCieFE8NHho8KJ4MTwIns8D2eB7NA9ngPAiPDRoRRRWdFGk0o0o0mlGlGk0mk0mkoooooooorKKSXBiJJ7eehGGrZHD2ewyTaL2NRq7HlKVCbZG/UxZuEdiDk5LJynDE0qNmLFRlSPxp4zxMOODd78X/Q6fqvxGPVYcOotKT9VX9MpJN6tYjEtuvoYbhrXh8Mwo6ppH4k3hwagtzC1PDWvk8GPWdZ4OLPTGjosaS63H6VS1Qhwzr5uGA2i3hXKP8AP65QjGPTalG2zFwXgun2YMY4eGsOGHt/A/FMKOD1HuqrV90lXmOC0X8mhEJODtC6rEyoooooooaKMTpViO9TPYIfczBwI4PA4KfJHDjDjL2jEW1jdvcUVHGWMviV/mdR/inB4n6rtZPDg5amt8nhqTshBR3EPGnLnLHwIYy946bo8Ho4acJGJFTjpZHocGDtZQxsTC+FkpOTt9nT/iGNhQ06/wAjFxJ403Obt/Kf/8QAURAAAQMBAwcGCggEBAYCAgIDAQACEQMSITEEEBMiMkFRIDAzYXGRIzVCgYKSoaPR4jRQUmKDk7HBFEByokNjc3QFJFOy4fBw8RXCRJRgZID/2gAIAQEABj8CfSyWnLadznkb02nlbLNowHRF6sVqoY6648gNtiS4tA6xml5gTHLZTc4B75sjij/D1G1Ixsn/AOB7VY3nZbN7logx9N0SLRaZ7jyDULXPAxshUWUjpTVvbYv1ePZnymnUpVJfW0gcKkBzZmMFk9GHOsua5xnCCT+6bpMnquoUr22YhzuOO5O0QrNr2X6R5q6ruFm+5NAGUUsmNQS11XW2XTvwwVE1jVM0TpLb7WtN3sWVVKTZdX0gpuP+FiR5iv8AlRWoDwfTvt3zrHa4Jv8AGCrWZp/8J1n/ABRG/h3KjbfUay6z5VnWOOsPJjiqjsk0zatquC99TVN7rIF/YqdmoWeEJOlYSALPC3OPWjpaeUPfoKUuacCNrei9xqtY19UNa115BDod+kKpRyy051R1pptFwAsNnEzitIHUyHW2h1+o2yQE6rUomgNDTp2TG6fiskbVNTR0qlpxt7Ug49h/ZUnVHObVNOmLJdIbDhjxumVX/i3WnGqSCMIu/wD8/bpdJq4WKrmfoi6kasm7WrOd+p5GTV6NE19HaDmtIBv7U/La9N2T3WWscQZ7uQf4dofU3WjcrVA6UVj4ebr/ALQ+GeK3/CmVB96rP/6qKP8AwptMfdqx/wDqvF3v/lXi73/yrxd7/wCVeLvf/KvF3v8A5V4u9/8AKof/AMNBHXX+VeLvf/KoZ/w0AdVf5V4u9/8AKvF3v/lXi73/AMq8Xe/+VeLvf/KvF3v/AJV4u9/8q8Xe/wDlXi73/wAq8Xe/+VeLvf8Ayrxd7/5V4u9/8q8Xe/8AlXi73/yrxd7/AOVeLvf/ACrxd7/5V4u9/wDKvF3v/lXi73/yrxd7/wCVeLvf/KvF3v8A5V4u9/8AKvF3v/lXi73/AMq8Xe/+VeLvf/KvF3v/AJV4u9/8q8Xe/wDlXi73/wAq8Xe/+VeLvf8Ayrxd7/5V4u9/8q8Xe/8AlXi73/yrxd7/AOVeLvf/ACrxd7/5V4u9/wDKvF3v/lXi73/yrxd7/wCVeLvf/KvF3v8A5V4u9/8AKvF3v/lXi73/AMq8Xe/+VeLvf/KvF3v/AJV4u9/8q8Xe/wDlXi73/wAq8Xe/+VeLvf8Ayrxd7/5V4u9/8q8Xe/8AlXi73/yrxd7/AOVeLvf/ACrxd7/5V4u9/wDKvF3v/lXi73/yrxd7/wCVeLvf/KvF3v8A5V4u9/8AKvF3v/lXi73/AMq8Xe/+VeLvf/KvF3v/AJV4u9/8q8Xe/wDlXi73/wAq8Xe/+VeLvf8Ayrxd7/5V4u9/8q8Xe/8AlXi73/yrxd7/AOVeLvf/ACrxd7/5V4u9/wDKvF3v/lXi73/yrxd7/wCVeLvf/KvF3v8A5V4u9/8AKvF3v/lXi73/AMq8Xe/+VeLvf/KvF3v/AJV4u9/8q8Xe/wDlXi73/wAq8Xe/+VeLvf8Ayrxd7/5V4u9/8q8Xe/8AlXi73/yrxd7/AOVeLvf/ACrxd7/5V4u9/wDKvF3v/lXi73/yrxd7/wCVeLvf/KvF3v8A5V4u9/8AKvF3v/lXi73/AMq8Xe/+VeLvf/KvF3v/AJV4u9/8q8Xe/wDlXi73/wAq8Xe/+VeLvf8Ayrxd7/5V4u9/8q8Xe/8AlXi73/yrxd7/AOVeLvf/ACrxd7/5V4u9/wDKvF3v/lXi73/yrxd7/wCVeLvf/KvF3v8A5V4u9/8AKvF3v/lXi73/AMq8Xe/+VeLvf/L/APEVX+IbasNtAKo7RgspMuqD9P8A4Yfpm5KXadnS4pmhbkodp39FiqNOiKbapNEEttSLQ3zdjwVHS1LNtrnPu2IEqpRtWrDonjnbUpHWCFJrBSZvA3//AAwaeTuAaXh+zvCFPKHAtDy/Z3lUxpj4Mgt82CeGv28SRKNWrBecTx//AO7vo7fzWr6O381q+jt/Navo7fzWr6O381q+jt/Navo7fzWr6O381q+jt/Navo7fzWr6O381q+jt/Navo7fzWr6O381q+jt/Navo7fzWr6O381q+jt/Navo7fzWr6O381q+jt/Navo7fzWr6O381q+jt/Navo7fzWr6O381qNXKqYawOs7YK0lBgLZjaXRD1wuiHrhdEPXC6IeuF0Q9cLoR64XQj1wuhHrhdCPXC6EeuF0LfzAuhb+YF0LfzAuhb+YF0DfzAugb+YF0DfzAugb+YF0DfzAugb+YF0DfzAugb+YF0DfzAugb+YF0DfzAugb+YM8MCmlRafxAvo7fzWr6O381ql1Bv5jV4Rg9ZXN9qupj1guiHrhdCPXC6EeuF0I9cLoW+uF0LfXC6FvrhdCPXC6EeuF0I9cLoR64XRD1wujHrhdGPWC1aQ9cKdC38wLXpj1grFUQeY0WTNDnxOMKyGCf6wodTA9MKRSHrhdF/ctdgHpK5rfXCuoD1wugb+YF0LfzAugb+YEbdICMdcfyPRj1wujHrBdGPWC6MesFOjHrhQW+1RZV1MesujHrBdGPWC6MesiyoIcPrpw41Gn9V6Z56SrAcahGNlWiXdyAZWAcftc4EM5R/kozR9wcxcY1ChSyZku3lTW1nKAAtkKaYUs1HA4LQ1DhcCi1us5a4jgFIVV33D/KwM1o8l/m+umO/zAvTPOkuMAJ1DJXWMnwuxcplEYrem0MqeXNdg53k82EM5R5kuqODWjeVFJrqpXg6DR2qzlTNH94K1ScHt6uX6A5i77KtOGu7HkQUK1PzqjlFHAuh3ag5qG5ayrf0H+UJRzDkv8311+M3916Z51mS0jBqXv7Fcta7N4NDVlaCrtsGqeI5oIZyjzBc8w0Yohpii3ZGe5WqRjq4q2LnDaHK/DHMMaeGbHPcU9r+CrUXXhwu7U5j7jwUbRWo2yFU/oP8pAUIHlP7B9VzUcGoik0Ada1rJUVNQqReOb/Gb+69M85JVepTPgwbLexWqg5Fl4TKB3k+fmghnKPMCgw678exS7fyGuZtBaN/+Jdyp+6OYL/s0yVqGFFSFIWK8HgtHXaJNyc1uLXwqmkueCbQ7c0vKqhn2D/JkoqTy3+b6qnyzshS5xKvC4LS5O+3xahTfs/pzf4zf3XpnnLLMaxseZDfTF+bo5HUv2zXL/h5bi1pc7mghnKOYciJWKeeFyAzyiqQp42+V6I5h7aW1oyoNmYRLnX8F4TZTalIapxQLBb43JsUog4hZVaGpbEJzxuohvtRttUFVQXQbB/k4zNpZO0F7laa60eoqzlDSR1oOYbjyH9g+qJeYC6SexeD2RcFO8q8qUKZtT2JlagYa8XheEbasro/ar2kLeoB5X4zf3XpnmiARI3ZqceSZRnFYwp0jrK1hemaQwXCQm6HKSATGyquV18S0MZ2c0EM5RzBYrFG9YrFZRv3q7PeVqlOc8XNHK9Acx+GV4Rt/FS8jqUMEIh+CljlqLzAomcU0tOqQrRItKu/7h/kYKnNaev4lw1qt8ncFiE6mZMb7OCOT1Nk4ch/YPqjRtdqs/VYpoG8oU2GzxKm2XFX8LlOjiHYEI1XAQBgiDxRac2KF6BPJ/Gb+69M802pSO20EoOGBEprXiRvUMcS19/ZmvQgQsn0mo+zAQDmAgc2EM5RzYrFYrHPlLvKIGe7HNrItWPJ9AcwT/llG9MqVujaZTg15jdcm0nODrSIJ1cz+poQa3EmE2nvACc4Xu4KtdGof5KFJTLO8qidE6o2yLMJz6jbBnVUMc2wqFTyg69NPEZ3ns+qH1arBVe52/chRyvJmCcLlSyrJeim9p3Ih6tvdI4JrhqdSpV22LJ2uKqh8YXJ8cU2oMRjnCI5P4zf3X4h5ofdYAqP9AQbpG2uEqg/cQRngXqi2p/h4FBvNhDOUUeXUbxzjMADinIcn0BzB/oKtbpvRa61PCFIBHmVpzD2wvAuJdwsoWllBny4TMryrUp3Opjisc1af+m79P5QNPkrJgINRrLJQGmaARsqwXh5TS7ih1K5dSn6nsjEoRMnBVKOUdIy8FVy/wAloKDpUSgbWCtVjfCuMBPHnRab11Z7HHk/jN/dfiHmq7sdchBgrPDBulX71kzX+SDfxzSww5C9s9aZTqNbDhiFbjHDmwghnKPKk4KBvzzKtYIu3JxWuLkDTMjkeiOYtD7N6lhkIVWarxvVlzaT92EKzLWA8Ai7EnGVxqeSFT+3avKGT5Q7G9mbUrudJvE7KrOqutmwcf5MnzJ60FS7gtSz51agSg1mxTu7Vcpqq4IhuH1PJ4plcfZwVR1LymwqlJtUmngetax1grsVcUDXqEowr+CKJGKvGZl/J/Gb+6/EPMeEqsb2lWtOyOop7uJnNKbWaNakb84hyoNiQTtbkA3DmwghnKPIvuUNzDkADio355YfMpFzt4zz1cx5lLDdvbxVqlvWyhDVaqbW4IOdtOdACyem6+JJTHNxbeFZyga/EJwNruVbRG0+yd38m1nnXahf1qLUtV5TuMotfgoYrKP1MVKanxFo4Iu4qRhvQIKxWKsNUJ460QrNhjmcXJxaGNcB/hvlNccNxVN3FvI/Gb+69M8qXGAizJTDd7uKIcZlTu5FeifKbdmvTq9VoDWiU2nN5dIHnVNztYReE3SOsWl4N7Xdh5kIIZzmwzXXnlwgoG7kTzfmzS09oU1Glq8ELZRc/Wdu6kKu+ZtHci+n0bdUIKZQqOvpHyuCq5RSqgEtvA/k3EYC5CdkJxdghBBhHV9qa6hdU4cUBskmOxbIPnXhqTmdo+py3eUYKLqpuaE57+Nwz3HNitYyhKPBHirMo2MrAMcFU04D7bgxsppbgTyAN+mb+69M8o02HwTPautMjfnkqb39QUMOjWM5mmvq5OMG8UzgCmtHDNZdjxTWAAtJi9SM9SyYNkwnHSPtTfrcgIZzncynfG/mieXPMeZSxQsVLJnjuXkk8YRZRDzaNmVZY2wOpA/xAE42gvDZS5/UxkL/AJM1A3e2oZBVSpJyd7Z1HazXfyIYE8Tc32p78b9YKPtXrCAiE89ShUo8o2SqWkvfZElFtRoc04gqtRoCywQQPN9QR/DH119Fd66+in119FPrr6KfXX0Y+uj4I+svo5PpptJjDTAv2lPIg8hj09p3IOCa62AVQoUb7OPaqGTUDdR3je5Ci53hQ29Syq6l2KWPZU6sEDlFLRv0gwNys2LWsTiuiPrLoT6y6E+suhPrIsp07Lnb5UwsFNmStlNYW4osZsNuVy8IxYu70CGS7iVwQtLFfeKlAndeuGdye3iVCuKB3IGzaQH8MT6a+in119GPrroSPSU2PanNpssvcIBlSXIjmHR/ITjcpZqrBa3hOpaxu4BRauRAx3nirirlLwrk+PsnmpUG7lE6LWI4p915zDVwWx7VrMkSg2kxxbvcpe6FTDN16pnfCHaq/Y39PqA9uZ7XCSRDTwKpiIfa1zwulNbpJtVGNbdjMLTWoN2r1d6yS6541vWP7Jmu624EwWcAjWr1nMZZDtVk4kjj1KrSJnRvLZ48nFHMU2o3HehOGY1mGScOpHKavk7PWVpa7tQazynWR2Zon/FCY1l7nOgIFgaaZpvFzrV4GP6FOLnEGbLA1uP/ALKA0geZIIuVGkzRN1Q4xtbMmdyl9eadprRZbax43p3hC2o4Pexti6BO/wAyqD+IhrCGlxAGt5zgi7TTV0Wks2LsYxWUBz7DG2nkNZMNtQITDTdpGwHNkRcQnPF+858ORjnqP8ydfuuU1cRvzucNxnNVsNvfABXULgBuVHKGttvczW+7eb1UFq8PqCLN2rKHYz/sCZT8E1zmiDN/XPtVcmoXFrA5sRx33p9JjhUhz2S4Wb7JVmpXc0aXQtil5V0z3p1U1NSyIuxdMWfYU7mCEermKZiYMqDdaElVKlVoeylTLoPHAe0pwadA0hlnhaLZ3lACsdLYa8ixdBjf506nVfYaBIc2y6b44wsqpVXACmx0PO6CqJZWbYFG0943m2R5UKrWNQPaxxaIvkqoxld1TRVdHU1LMY34/dKcX1jY/wAOwybWqDff1haEVzbZVFOr4PDsvvw6k2mKuo4CHwMT6XVuTgNytC9AOQIV1w4qtZF+jN/NM1YsAY8Vk7aus19Vod13qo6k+k1lJoLtE12F/G+Vp6lVzYgubYE2TvxVZv8AEw1lU0g54a2XD0sEA2sdJYa8jR3QY3z1pg0o0jtJqm6LIB9sose+zcINxEnz/oq7iNYRHesqYwWYylrG9Q1vgmtr1nB2iLzZZMRN2PUrZfAIaW3YzHxTaRdafvUjFFzjJXmWjJ35q3Y39PqAw/E/ZW3/AGrbPcrQqutTMoO0ri4EEFCnpXWPsosFZwYdyb4Uy3ZuwR0lRzpTnE2nuMk5sFgsFrPhXGc0FXoCfYpabkL7t6DWOho3Qm0qLjZxceKq601n3YYLwtc2v6ChRyVxfUtgxYKHg6ocPuFQG1gP9MpzYrWXbQsG9DSis6OLCrbG1rYwNgpzm6cF2OqUWeHsHFtkpzmacF+1qG9NoUmVLThYFoRcrUXyT0o34q3WphxOJNQKGUm3464XRN9cLoW/mBa9FvrhdEPXC6JvrhdE31wmnKKR1rhZ1v0XR1fyyujq/llBjKdUmZPgyh/E6aOGicrMVgP9By/xvyHK81vyHomg2qQf8pyGla5naFdGFnZzQXmLNjzcFL6hJv3ccVtnuQcKhkYGE4mq7WFk9YTyKhLnSUS2u8TE38E2kXnRgyG9aJCwWCwzYLDNDlMLBYLBYZr80Dz3Yq0/HsTqdF9gOdJKB0zmmACRvhMYHuaxrWizPBa9Zx/9lPNsy/a60DTqubDbI7E7wrtaQeuU6tpXt13OaJ2ZT5rPNsQ7rTLdd5sGW9StNrvB4p5rOIkcF0h9QoOpvM/0o6eqWs/pKgViPwyqjRXdJaQPBnmZ3qw4iMcEHMdDmmQeCDjWdaEXrRvrONP7KqFtZwNQy/rKYwPc1jWtFmeCJdVcSSSfPivA1nNR0FQskQUHVMofaDrQPXxQ1zcI8yHhXXCyOxM0tQkNN3UmtpvOP2Srim8VNVxF/BX1nfllVa2TutUzEGOr66yP/XZ+qtElQCc0DFYjmrdZ0BHQ0xZ3WlsU10dL2ro6XtXhabfRUAkO4LErErErErErFZJQrOc1uhcdXzLpq/ePgulr94+C1a1fvHwXS1+8fBdNX7x8F02Ud4+C6bKO8fBdNlHePgunyjvHwU6fKe9vwXT5R3j4Lp8o7x8F02Ud4+C6bKO8fBdNlHePgumr94+C6av3j4Lpa/eF0tbvC6St3hdJV9ivqVvYr62Ud4+C6fKe9vwXT5T3t+C6fKO8fBaCg5zm2A6XLp8p72/BdPlPe34Lp8p72/BdPlPe34L6RlXe34L6RlXe34L6RlXe34L6RlXe34L6RlXe34L6RlXe34L6RlXe34L6RlXe34L6RlXe34L6RlXe34L6RlXe34LwmV5Q3te34LwWWV39j2/BfSMq72/BfSMq72/BfSMq72/BfSMq72/BfSMq72/BfSMq72/BfSMq72/BfSMq72/BfSMq72/BfxOT1az36QNh5HwWqFgvCFw7FfVrd4XS1u8Lpa3eFqueVi5XueFfVr94XS1+8fBdLX7x8F0tfvC6Wt3hdLV7wulqd4XSVO9dJU710lRbdT2LpK3ePgtavlHePgvpGVd7fgvpGVd7fgvpGVd7fgvpGVd7fgvpGVd7fh9S3IiL1JdHOZH/AK7P1XnVyjm3VHovqHsHBXK/kNcwwQg7v5WS/wC3f+o5EPU4j+RHJ/Cbzxq5Q8MYEWZA2z97ei6q90niUKtCoQ4INy+hZB8pqFSi4OYd/MfjN/dWvvLDljkmEb+UEPqm7PKE3q7mcFkZP/XZ+q86POWGHwbEeA5N2apSJucJHKyX/bv/AFHJuXA83gsM2PL/AAm8659Q2WtEko2CW5M3ZCwzw4Sg1xJyd+I4IOYZacOX+M3916Z5dp/mCjJ36EdSmrlVU+kunq+uhocpeoy6zVHVirdEyCjyQh9WTvV+YEXoPZgeTgsFhmyR3/8As0/1Xn5wxtOuCs41HHvTKdqXBsu7VfeOVRdumCgTfycm/wBu/wDUcu+8LVWGbFYqXOUQe1TTg8sv4Icj8Jua3VvO5vFajGNbwQ01AzxBQ8LE8VLTIPLZklPaqbXYheolXZscxySodens9nL/ABm/uvTOfFY5rRUuKssElTvWu2EbAvXhGFAexOr0YFRu0Bv5IQ+qL11ZohYKIRUJzJx5nJP91T/VefnLT+jZczrX8S9tlo2Vc5XhBXLC7MX1MOCD6NxF8cUADu5OTf7d/wCo5uTcnWXywqy0wFC+03eFNM38M3BXEHOxg3lU+zkfhNUE2qpwajUec1t25QWkKy9ukYMF5TVZLS1n2yeTWe/Wa3VYE0PHYFZNKFE9igGV0lkqy42wnDfZPL/Gb+6s9axWKxztptwGOYOjWdnErwlNrkcoyNll7MVfsOuKI5AQ+qAOKAbfKjKCC8eSFZNIzxTjZgJzwbpuWMK0bxxTO3mck/3VP9V5+bdYxi5Ucjd0bDHoplFlzQMMxcRhmkLWXALiupY8nJv9u/8AUZ7uYPXcpPIDmGCEKgx8oKt2K5zu9XVXLblB1TFUT93kfhNRfVNpxzTOKDYzQnU6VMvcOCBymk6nOFpWazwHUuPBEUQapUZSywDgQi9plsYqrlFQ3W1OK2UXPQgXFWpVk4Kj1tIPLj/Ob+/KLlJQCYOrk1w7CwU9jRAdeCg4bxfyR9UFAb5QLBDt8rakJ4f2I2NluCIqNVKh6UIW24CeZyT/AHVP9V6XOZQ94h9MRHb/APSfHk3ZqeqGPYYdG9XK/NAuUgqc08jJ/wDQf+3N0qI7ShyA5Gn5L1X/AKVUkStkLZRCo9nI/CbmhRErGSVcYCFLJaZqu6kBVA07tshVXWZLNZOsk3IVHubRouEyU+lb0gaYtDeqlBrzTabitHitR5Ch5RbZIsowL2rFX3qpUJwbI6k63tMMTx5Uf5o5RGYTuXg2ArwtIhXFSVBpvKcbwHN3omm6zZNyqfxVMspuFx3cgIfVBsqi3i5cFYZ4RycHNcIRsGJU2gU18Wrt6cNHo6kd/M5L/uqf6rz85Vga5AlVi3EOKD3NBauHKLSLuVk0f9B/7c2HTdMKGNkBQWwtVa1SEZxTHNxCquIvsp/ZnKp8j8JvJ2kMnhrKw3/azOZUEtdcQnVdI97CZDNyo2SRQs3AcVKlWWnNPDkANCNBpi7WWjoC7lT/AJreU7M7sXgjCOkN6a1ypjJhA3qzUoaRicCCwEXNO5O6isj08BxGA5AQ+qDO/cqAONpPNLaVgWnZQ/G5ONWjVKNoFo+8E5vk4pvYp4N5nJv91TXpHkwwSVeAO1wXk+uFEe1a7mj0l0rO9E6RpgTAKFF1I03OEA2pVepXEtLiAFVZS1qQdsOXhAaZKGiMqSIzTKhwuUjPOeh/ov8A1Cw5ZzPcNwU9comYUk5pN6cEFV7CndmcqODuR+EE2nSbacUDlLRWq7+AUhhou4sK1crd3K1Qc3KB3FWXB1Oo1NyfL752X53gbbNYIsUFWWX1CdyARad4hEHEKW63UrxCZOAMlPa7bqgu5cf5rVPJOaOIV6mFTdF0r/mBINyDqQVWo7BrZTW73uTKTcKTY+qcFgsMw/h+kacOKpu0D5a6bgiIgxeEx7RYqNEBwUCu4KK7tJei2mIJXg6Ty0XAwqlTKG2XOwHM5N/uqa9LkBrcSnMp9JG0uOfHM0m8KjUH+G+e1HR4WB7UXO38gU6V7zcERimN4mE05Pc9rfWRacRyaH+i/wDbmDmLeITmOxagiXmGhRKhyd2IMpXlOp4myj2ch46+R+EFq3vOLuT4YQ/c8YrwutS8moFRYaJqPa3WdKitSdT60dE+UXNDrc7sMwO9DNa3Ovz1cqfvFlio5RVN9q/NdyfxAo5JzUz15oQk3SiC+0MQIQY/FVYxq6nemHGyLh1qoTeZ+p8FhyeGYmLzjmvaCnaHUcqYrkGm517goHNZL/u6f6rz8h1Z2JwU8eXjDmi4qmyrdVY2z2jkQxGMTdmpE1hRqNxBulRamArTOk/VX3ZpzZOMPAP/AGVyvGY8g552Kn2loqhlwGKOrN61mtK6lTab70TSphvYn9nJqjkfhDlltRoc07ii7JScnf7FZrCW/aHICjN1tUBF1W6ky9xQp0tSgy5ozUnTfEHlfiDmARiEHjgpBgrahAOqkr7u5UcipmRS1n9qflDAdI42R9WamHFSjYNp25YALWcIUGVisVDhKn/D/RTN3M5J/u6X6qM1pybY3mFUotwpRZ/fmrnd6vPK1ahjgtZTyMm/27/1Ga+9TZRDbuRfhKhz4CbonWpzCs3FmPXyHvPk4Zj2IRdeeRVHI/DHMG+9HNBzC/kXDawVnDSmFfirSqWhDJu5X4g5gWsFqYK9a2atlLBBFzZTqlQ2nudeVTYWimGNgBqFtt53ri04H6oxQYzftFXXAIt2WK7kSoAkK7HgoN6OjOpzOR/7yl+ue8SiYiB7Snv4uK6v5MZ8lc+4aB/6hRpI7VtDvWKcpwCLK7rDftKxkJNTi4rVq2VD60hAPEltzSnVGGCU3S1CROClqwWsUA9s03Yngpo1AerN6WcJw+7yPwxydZ89i1WlyLcnp6Nx3qdMWqK7i/rWq5y3x1qIWo6VNrOR3Kw07AVp20rGBL4TWNwHK/ECnmBxF2YAq1CyfJwdZzrRCHapQ6kWVb2lfdOB+og1tQySjarYKKTqlQ/dEq+q5B7i+wcHcVtldIRKcaelqNbjDZhbZUUi956k4PJN3Jlpgqy/aRa7eix4j9+YyL/eUv1TadB7hLRcN6urOKPhnLUruG9N02kZawtCJV73BQ57gVNswtsq5xN0raKdaM8nq5vJSDHgnfqnWamzjKA0htcOC1HvF0q1VrEb1GlJWs6cwFem+kTeLbYzQySeAUPkdubaW0gCU1q1TCsNrOhB/lICoBClpkIL0eR+GFZFQ3lG3VwQZRL3vOAaJRZWc9jhi03QtoraQaySTgArGUNdTdwcIWKxVxW0rzyAqgJwKaeCblVEazDeEOV+IF502pIhyO/rWvTsmJvWytlbK2VLLlaBNnCVDy5jhuK6d3YjVyl2keeKwWCdHFBaPeNlRF/1DbmIPegOpPDgw3YPdZT7OjsSZtbXVCpGrotHapAcd0z1QiaOh2W6PScL5nrVaNHi+P260W77apsqWCGXSN5s/FVWUhRaSWE2yLJx8yraKdHfZ7Jz8c878zanlMzjk5D/AL2l+qyZzzDQaZJ9JBos2hR89qfgnNbo2tbWdYje29WmGwyBePJMfFNL7D6sPnWtA3XKrsA6NutdjGEdqdpBTuqNg8bjj54QbXFAzVbbjCymarS66SSJme9A1A1jZqtOj+zF37rW/h7Ok8J/Rds+3rT+TZHN5J/pO/VEOum8gI3Jp0tEf8u5kGoBfJX/ADNSk9obTYRbF118f+FkwaaTdnTW+xO/hm0tTJ7jV+1pMT5k51NwYyCA4YB1nHvTqGUPYbTbdtrrVmLz7JVS22kHVLT4b5N7YA9qaGGnSpw+KjTMCLvP23qsHWaVsU7LsbNxlVnxSax7didnU+PBM/CtcMBKGl0Gksu2Ys7o6uKdoYsSYhHq5NxQITOR+GFbmAD3oAXwFXq2mN1bDbb7N5/8Si7KnUnMcymNsYWYJ7xuTNIKAaadMj7Vq79pT3WmvaRcLnxrd2Hcsqax4p2w5tN24X/C5PbayZ1UEbZltlCxG1rTjo7Zw64hU3Vf4eWFzop4Fu4d/nVpv8OJLNLb+zZEx55wvVMTTYTGtdaGv34KjoAwOs69gg7+q7ktezB7ZzGMDipbIUOlvarjyPxAgAsSdwVNlR1ila13dSFapaENqNLXY8Wx+ilxZoi1jSHkAi68/wD0siuyY5MXM0loAu+9KqOyjRW3gnVhpaeodnmVfTGgKAZNLRYnWF3bHFZRq0g59uxAnyLuy9VHVCDVZVDqdP7Rg+xVX5Q+m9zrFpzyPsX9ePBUNKabjaYSZExBte3im/w+j0uiu08Y2z5sFW6Hafw+wMN8WpwVMUTTNUOGs04iPjxTu1BSgRicfqHBqwatli2WLBq2WrBq2WrZasGoua1mEXro6Xt+K6Ol7V0dL2ro6XcV0dL2rYprYpro6XtR1WjNcAtWnSPaCuhyfuPxXQZP3H4roaHcfisjp5W2jTpNyim8ubN0FaWt/wASY0xGrUC8ae8b8FI/4n7wfBR/+TH5gXjT3jfgvGnvG/BeNPeN+C8ae8b8F409434Lxp7xvwXjX3jfgrv+KY/5jfgvGY/MHwXjP3gXjT3g+C8Z+8HwU/8A5T3jfgvGnvB8F4z9434Lxp7xvwXjT3jfgvGnvB8F409434Lxp7xvwUj/AImPzAvGTfXC8ZN9cLJn5FVp14pkGDgtlq2GKYAWAWATgLg4QetYBOawwHbXWsAsAsAsAogLZapAbn3ckVGASOK6Kj3FdFR7iuiodxWmqta10RqrALAKM2tfuWAWAWAWAWAWAWAWAWAWy1bLFsMTWvYzVwVzWrZZ7Vc1ivDSsGqNHS7iuio9xXRUe4rQVWUmtmdVQAFgOemTnBbCg0qXcVstWy1bLFsMWxTWxTV1Oj3H+Z6JnqhdEz1V0TPVRimweitkK9oWw3uWw3uWw3uWw3uWw3uWw3uXRt7l0bPVXRs9VdEz1QuiZ6q6Jnqromequip+quip+quip+quhp+quiZ6q6Nnqro2+qpa1o1xgFLmNOudy6NvcthvcthvctkdywCwWCwWAWAWyERZCtAIuhEQgYWyFshbIWyFshYBYBbIWyFshQROqVsN7lsN7lsN7lsN7lsjuWyO5YBYBbI7lsjuWw3uXRs9VdEz1V0LPVXRM9VdEz1V0TPVXQ0/VXQ0/VXQ0/VXQ0/VXQs9VX0afqLoKXqBdBS9QLoKXqBRTaGjQtwHatkdy2B3LZHctkdy2R3LZHctkdy2R3LZHctkdy2R3LZHctkdy2R3LZHctkdy2R3LZHctkdy2R3Iaje5bDe5bDe5bDe5bDe5bDe5S1oGuNylhbHWsafcv8NdGwroB3porUbFrBYBYBYBYBYBYZ8FgFgFgFshbIWAWH1Cf5f0wvxDzcKFcJWEZtW9RVbB5r0Dzluq6Go6IWWrbK6VzXdq19dn2kBVbZ61APM/gt/f+VHK9MKDx5OTt8/11qCOty1csLT2K1pS8dSDMtim/7S48jDlemF+IebkZrxyNZqddq8z6B5u09X//AErzJV2bRZQdQ7+ChpuN4QbNl7NlyLXXPGPMfgt/f+VHK9MK5NFm5A52Dgzla7oWsDC1Cod/JaWm5gExeukpd5+C6Sl3n4LpKXefgukpd5+C6Sl3n4LpKXefh/MB1e6m32ocEW02F3WiCLzuKcaYi9fwtUm7Z5Zz+mF+IeaOYcovG0FPMegealSTcMAiePIkBU5wamZQzZI1k3KKW1TvP3moEXg8v8Fv7/zfphX8U0NKdOs0KWmRmqdQjkQnHGETyL/5H0z/ADvWqYFNtnfKDizeiRW0Y3BSTLuIQNRli17U2OPLOf0wvxDyXWLqoRERyCu0q7lVOpDmPQPNaNh7cw5OCqU8dFu4tQbNpuA7FWydwjRHV/p5f4Lf3/lTyvTC86IKApmy0buKLWazpvQWUnrzyUXm7gg3BiAaL+RIUH+Q9M/ztEOwtK4SUGig4oGoIdmAb5JlUnObvx5Zz+mF+IeS4qrZ48gprm4r/mXm19kLVa4dcqekYFpn5ONHxQqOOjacAFJk+ktFDg04tKmm2yzmPQPM3bRwRHIuUq8rVvVZlTygspoHBhlqaRsuFl3IGf8ABb+/O6xhXOHLPK9MKy8E3rBy8ruU3z2LaPcqr+Ls4Z5ygNyBbtFQ/E5pKhl61gtX+Q9M8yGsEuO5OqV76tnD7P8AI4rFUnzg5Co8wHb1Ar1bX9KIpODiOGaw9waDxVLJclNoNOs5X8ko5/TC/EPJcXcJVR/E8hx4JoOKJYMQrn3J9s3J1OdcbKpFt0CCF0rgsk33Ypw4HmPQPM6ThcM0q9XKcU/RMbTZS2nKX2nKWVatN3U5MLajqkOvtLTfbY1Gl9yeX+C39+c0dDzlS4lQblYq3jlHlekFhvWyFshbIWyFqiM9Q9akrwFO8XWyrVSrepa4PTW7IK1b+tH7QQchwPP+mc7auTC+L28q0wzW8qdyf/SecOc8mna2ojzoNsi5F4Gsc2jYbqYhMHXnGc3o35/TC/EPIDdwVSz9nkuAQbvBQadYblq03H0UZuE4ZjUoiWO228FdSdKnKgIYCWtVUfe5j0DzI/qzRna2JAxVWhEUsqpS3tH/ANo2IcELLYKaBiWEoaV0BoiU7LMorNi+GhQ1/epF44jk/gt/fm4btFFz8xuzWTiOb9MLz8uE5WJkp1Nt5BUExCO9WhuV7VsoHigef9M52f0hGtIpv/7uSH0zDgntOrVsmRx5w5zyICqZJWu3hTIWqnP8kJ9Q+UZQfSvdNwQ0jbFUC8ZhmN6IB5Fn74X4hz9a1cULbVfTAPEIvoa7M8IOHFAqxTuRumVsrWbcVbYSaJ9irVfuqeueY9A8z6WZhbtLYWzCb23lN0T7OUU9ZhR0tIyDfCs0cnJPFzgn5RlLmmpZQa6GgHcoCxuQpncurkfgt/fmyhrhqN4MIgZhyRyvSCdUD4jchyL1ipTmt4qU2vk7oO9C1tIDyjgv4eRIMuWNoFSxMzDnvTOdhde4tuardU/+OVIu5w8k1A02BvVQxNTyVIxCbxKli1kMnZi7HMH/AGQpA7Si+l0g3cc2KN6vQnPC9M8gSgAriIWsn6PDMEVTOJwKNkSocA0phJbei5pDneS0b0P4wi07yRuTMkZibynh24hOHXy/QPMup7zgrNRhBTZ5Acyo4HNLCiaric0hBBSO3kfgt/fmic14TiN4RzBA8gcr0gmMHlPWCjPC3KdytgY5nN4KSgY7FsiSrVUwgWGZVM70CcXGUOe9M57TzJ5TiMGiSrUhonei12I5yc7abNpxgKjQpYNN/WUYwdcnNasmcMTerlKY4G/M5n2kN0oBaVg1H55zYo5o++VK6s3Xm1pCxTyxqO5Eq11rR+QVaQuQgoFGpUMABad28wE9p4p46+X6B5q8AoiLs12bBXthAJpiGEXFA4wg8PBpPvZmCARHDP8Agt/fmo4ouVlqsKc45A5XpBNJEtai5wuRgSpWITe3MSiN6I3hQcHLqKiSIUh6tVXWkZVQjZ3fyHpnMAE5l0txQMgg8OS6d7SE0Ova1t103omS6d55+kT5GsqbetSBherfWqT24AKVeJTm7mZqY60BwQKqUXbxd1J9KptMMcv0igO/PEK9MvmTgv0UicMxzgFTmvOCeymYosuA4pgHFQdnejWiaVTB3L9A822qN2PJkLWF6dSpw+ri1NNaA53k8EGlxMXZxOCFVmG/P+C39+aA6kBxRLlGKx5gcn0gvOihIxRQmUULUrwR7UNZWlLcFZduUqNyvK0FLfiVeVtLa570znqOGLz7EBSLrIwBbEe3n+kb3rpG966RvettvesRmwVWo9wa43CU6xUbaGF6dTrmwetOaw2mTiuwJuaoXiGvbdmY4bih2Sc7MoYID7ir+TKvIGssQtoLaCHhWA9q6al6y1Cx5H2SiQL02ccE4fZRRb1ZpCvWJTg06zrgq08FRj7Sax+8p+S5Qy20o1aE1MkO/wCzypcYFgrbb3rbb3rbb3raC2gsVtBbQW0F0rO9OptOkc667NisQtZ7e9XVGd6e8ZbSoAYNtXlQH+cKXmeQFYfe0q7YOGb8Fv7raC2gtoLaC2gtoLaC2gtoIwmwoq3IweQeSOT6S86EQVstWAN62Bitm2tnOJ2UeG7NhmiV5uR1KRyLlfy9HUY8m1Oqujq+xdHV9i6Or7F0dX2Lo6vsXR1fZzti0GfeO5EspuIBg3KGU3OMSsDhKa6owtDsOtUqwM2zFnhw74Kc/ROsNxMICyd6a7Ruh+zdiiBSNsJ1U0zYFxKJOzmvTGU7yzfmI6kziW56hGNPW5U9eZjjNrFyZTbq6R4aOqVWp2hFJpda47/amEMJt7PWg1rSXRePYntOBARouxaYRCrtQ61Se++StVsCM2GYjdTErKAfsyqZd5V6Y94uD8U907sE5lVocx2IKdlGS62SuPqck9ieau7AKGbt/FGvIudFn9/0VSw0vazF0ICm0vkCLuLZT3lhssuceCa19CoHONkCN6EUnHwdt92zefgqBpunTVNHHA3fFAim9zHOhjrO1wU2TbDoLfNMqhbY6mys9rQ+OKa3QvDnCQIVnRv0kxZs+dNp1QaZLmjDim6hMi0iI3FCozXZOs1A5N6pRJZcMc9wQtGFZK4hfgt/dNDsCb0dGDfhO5OD6ujIBOzOCtUml1OYDkdKwtiJ/wDfMmv0brLsCgKbC4kSE2lsyYPUm6Imq1wBBsp50TtR1l3arWjdZvvjhiiG0nGAHeZHPwChFxuanWj2SuBG7l+kvOqbyXWsXR+ip026mkeGjqlH+HpufGMLTaJ+iibUIaZjmThKDTUtVN4s/od6d25ijKhA5igd8cnq5B/m6oYBafvIBu/9hMrOpk1hWdUufGtDL+8IUq1K0xobFk2TIHYjLW3teDcPKn4plNlLRta8ui1hMXDuRaabTRhoa26RZwvWkdR8NZcxpDoaGmd0da6B4cbR6XeWxwVNwZrNi1hBujgi7RuswABLbt/2Y9iqUm0rJqYkOu2p/wDGKDkFqYuuRJxRen9incG53Ndg4QU+mfJMZxmn7wQtzHUrDbvRVKpE2Hh0diYyzgCCftXEDulBjacAfe+6R+6YTTlzIgz1k/uqjuACp1meXcV5lU7FQCtEQQg7cRnkptrbq3uTnRq1BYCp02GQxsJrKmy8yqRODxq9avTqdVtpjhBCsY0X30zyD2L/AMY5hSst0WjsRAnv7b08WIvLmkRdPm6lRtMdNJoYCx8XRHBVqdPJ9HpQ4XOuv8yrudSltaq55FvcQRHtWhpUixllrb3zgT8VWZZtaQapnZdhPcSrbab2VXWdI5tXhGF12CrUxk8Uqu0A6P24ptVtE6WWF+vcbJBu4YLQtou0BBtDS618b4+6FdTgRA1vuWVR1ejLfPBlHStJtRah0XhVbr3G48Fk07NoghZIaZ1cE8h10YcV2q05Ai7isVqhawX4Tf3Unam7qQLcAIwRMTLXN7xCdQFOC5tkm1jrTKrOqUdIKjmuiRuniOtMboxqFhB36s/FNdUpy5rLILYb5U8FXrWNZ9qzrbMqy2nrWA1rpwxv9qtvpG2KhcyH8TK16PgxpAGNfEBwA/ZMqU6LrQDPL+zdExnKPagg3cFhCN8cUX2pUhA8j0l4Q3dS0bbjN+r7FSrbVh4dHGE5lGi+wSHXvaSHD0ELTLXgdGb8daVTaykabWFxGtOMdQ4JlCkyoGtda8JUtR2XXJ3bmOYFBYqSUSMOVZP89iVisSseRj7Vj7Vj7V/5VznDzrbd6y1yXdpz3K5zu9RpH+sulf6y6V/rKTesFhmuJ71rkkdq02RUw6nMTbAXQj80LoR+aPiuhH5oXQj80LoR+aFNiOysFfa/OXlfnLWaT+Ktn3qixd/qhbPvVsn81YH85bJ/OC1mk/jLo/ej4qdFf/qhdH70IQ03f54Xlf8A9heV/wD2ENJTt/1VgvozPzGr6Mz8xq+jM/Marlie9YnvWJWPI0mSsDmzG2AugH5gQNekGg/fC2f7ls/3K5n94WwPXC2f71h/etn+9bH96DsomJgay2j3rErbd3rbd6y23d6uqvHprpqvrqahLj1rY/vXR/3hdH/eFsD1wrLotcLaw/uV/wD3K7/uWoB66uaPzAuj/vC2P7wuj/vC6MeuFsf3hbH962f71s/3hYf3rZ/vWz/eiXC4ffW25bbu9bbltuUWiVdy8F0LfXC6FvrhdC31wuhb+YF0I/MC6IfmhdEPzQvo7fzGr6O38xq+jt/Mavo7fzGo0MpYG1G4jFYcnD6omM881+M79s8m7OR/Ol3+YczU6/DmKf8Aqfsebxk8FZtaJiGi87yvCGSsFgpyd6s1paUGTfx5t/E3fyA0g1ScUL7McxX7G/p9R4FYcxLlLu4IWG3IaRpbO9XXt4qOa/Gd+2e4xLoWiefCM9uerTtEFhi4LpHdy6R3qrpHequkPqrpD6qvqn1UXMqkgGNldJ/atv8AtXSf2rpP7V0n9q6T+1ECrePurpPYuk/tXhal/CL02ow3HiOad/qnM1OG52PJxCxWBVO7/E/Y81DcVZBmNorSvHgvJHFYRybxrbioJLS0oUco1Ku48eaaz+QMCXKDjzFYng39PqCRnxWKxWKxzblshTAUC9aXLLmHdxWpQai0sCdVyUl1Le1TzPnX4zv2z0m8b02owwJuTarPOOGbK3TjVW0VtlbZ71tnvW2VtFVpv1+RZqjRlS2COIzP8xzGnko0lXjwWnryASh/WeaI/wAw5qfnzaxhCxcocU14vWGen/qfseatb03Jm4TNQprGCAOXpRi1Wm3ELR1emZ7cx5ZHC5SWOjs/kC5zo7eXJVYfdb+n1WAOEprd29ANwzkOwKcwbJvHKAaJJ3K2+iQ3P+M79s7RwYoKsVDNNytsMtIlE/aqO5eUD73IymrlRsNYNrgizIqprgdxUZFkwHW5F8hp6k5tSoYd1Jrqb8OK0GVUw1x8sYJhGBM81+IczEVMw1GwZKtKmC6aLsQpGen/AKn7HmnuF7RcquV1cX4K94UByluGbWKxhXFEFOamP3TerQ38uGi9U3ZbT8FMpzbAsxwT2ZOybJU5SyyO3nTVq+YcU5732KZwammnWtsHkymvZ5+Teso/pZ/2j6rByano2hoB60ajiLgopUalePsqw6jUonrUvuWLwP6UHUTLY5I0Q1ftK1t1N7ytwZ1qHkNqcWqWVA9sr8Z37Z6vVq5uHBVcmyk4N1VS855eU9o5FbJ6T4pB3knaWmyjVZuCgZocrWT3FWajSIVPJMpgMwY7mp/zDmp+dF0CwcE1sgGMxCZ1KgT9mM9P/U+PMudwCjyrSp5NR4XqXvIV1aCjLg9i6lDzcpNFzvSRNGk9qh4ITXhaQC7iqbuF3LPUEw9ebK2EQRUT/u38457sAvCXMbst4LwVHU4ymmmWsneUxrnA061xPXyIaLT/ANEC7ErKP6Wf9o+oNRaxlY6quV0KDcsShCwQWTxsl16czJDqG8gbkxwbrOCJbXgbmsCJrOd1KjZdMjgoY223+hEOFk8FJ35yaw8Ey89aDabQ1owCt1DDQrGTuhgxKDpJ4ratBCgy4aUkoB5VxlPd9pxOaUXcAqI+4OXlXmz2KZipVu8yZWykWaRvA4qBhyRUdTDx5TeIVKv/AMNlzX+QqJqGXxB5n8V2al502nBmF4JjXBNfEE3Qj4Fx+9aQYL9yp0QwWRiVgAexY+xM0p8vmakmLQgJjLjL0HOF61aD+5CKboTW1TjxVgu1T1IGZXg7iptN7ERZsvWhcJaTIcoJuTsmcetvLqKV5llNL/qttBPHUnjgebd1CUUHxfHFEGmIneVbbquokOHegcwZTunfmCyj+ln/AGj6nGZoVHcBiU+r9pypD7ql5VvKHikdzSmaKqC4FT1J6EZxa2n6xUlaGmbzn86bVb9oraUSrWTn0VFRpaVCrRuCjgI5eVebPRblbmixrAHei/JOiGq3lW8SFaa8WWjVBGCNPK9qqbYIw5kueYGlcgJvKpweKp3blZaL01o3Fde9Uq1RzdLNraXTU/WXTs9ZX12esmNo1A825u5mkNxKoX+WE1+9Rqha16BqeSEUGviVcSFN5UJvG1moFv2uXUT1T/pWS1OOqiq7Yi9aaNd1YX81UMwSIRTqVqy7yVFpo80qlRmS9wlAcMzOzMFlH9LP+0fUGCvYibMQvB0XGOtfRj6y/wCYouZ51g9B8vvuTv4TSOs4q3ZqGES+67epjBU3NOLVaqsfVa3c0If8q+4YrWtADipZgU4qc1p48CzHrzGEaivuK2l5011IgOFV0z5kxrmHHEb0CEAVZqtlNESx2y5PO9zoTwcna4jevoje9fRG96+ht719CZ3r6E3vX0Jvesp0VEU7hcthqfVsttbk6rlDrTjgqk4B2bVUqDKvCq2TuzUvu8zFN8BriU4P2mYdam+YlXOITWVemYI7UbLnQiybzxWu+CepQsFhzWTv8lUZ+0EHMMXLwiiPOtGDevCGEXU36+5AVDeriSFqqmEVRH3uXUTh1Ki7qWSH7+a1vITP9cc1PXARQLStZmtxTXvuAKmdy1CqXZmCyj+ln/aPqDZKiyrEXpoN9s92aLS0bL3nZVNka0qq8+W9FvVCoscNaL05GidkYK0jZYUNUk9aFGmACMzWtEuOATamXt0lU+TuCs0mhjeARvVimVJWC2VBCssdA0hU2H1PMvDUnNnBcFAmOKccSzWCpN3Gqqh6+TisVlQ+5moDyTOZxG96EVNZNlaqItQ7chL7Se08Ob0bd5ko33ouGELV1GYl7sFRbi44v4rFQ0J07kXPHYrwsCtTHmWUD5BlUKo2SVSP3VBKs0r1aiSp0MO61MIQg2qICtMVPNR6r+RaaLlBzVAin0ntIh9ypVGNtBj5TXcQmwFQBxNVp5qLWsDIHIkKy8yE14uVHz58o/pZ/wBo+oJkLEZqOi8pmt2og61SlcczOppKo3YuTCbgtaszvWtlFmozZMKlSawAUp1h5SqE7wpF7eCgsR0TIKl2KDMnYXlCtlHhMo/7cxJKMFTybTmgu0rv2V1ypt+y0nMFZdhgqVLg8uR5eUf0Kaj2s7SixlcGrTMiN+Znbm1eQU9vXzWs2TK2AEGTZpC95QoZNqhrbgmVDthyY7yt6LoTnPeHX3hExDBstV6mIR5luU0haA2gmsA1WmVRezexOBOtK13JtSBfhmdri4YLRMaD1pthqIcgADAUAXrTVukdgOHILPKYVIUKpmuUIhUalNtpgOsqQp4B7P35mzWrMYeBKqu4m5EFG/NOYLJ3dWYrKP6Wf9o+ocL8+VN3aNOON6qOjZpElUepNoC5g9ua7FYLV2t+a5BlNpc47greXeDb9negzJ2BgzG9fdV/Kv8A+s79s1bqaAndib2ZqVbdozzFZzNtzLI6kXVHlxRRVjgVAQ3q5sq1h1LHNUe6k4Nm4qlUqv8ADPOwNw5nzqFTu1nazlLTETem6U25fZHUo8hybRpCXv38AndqqGd8SpwbuXYj2czB3qtlLJZULoHUv4SrUt8CrVm9WXNwQpUazmsGCAqVHOhOcXOk9awXWrDcUJAPapsN7uTY3VAisMVUcseRgrO7St/fmTRpXuuaFBUjeFfgcVcRnCYahcLPBPY29oNxRb5lXn7Lf0+oCOrM4tzZXXnw7hZaFJVQ5OYtCy7sUvNkNCjHkWmedCL5WvqheCpi19o5zesdRavLsuEzVd+2aufvooZqoaNcNkc5ZODkIxWtTBV9MrZcEdG3fimjSim1Ne7KHVtya3RPaYxdzN6AAnWwUYECE8Du4IPGIIcpZfvCD37Wwqh3Coq8bnqT/wDScGYI9nNVwfJdKBbiFYqGHjPeMxKgblemdnKZUZi0ym1G3yEXNF4VW1uUhX3qc8/5zf35l2Uvrl+UONzQIzNfw5IXpK1RHhW+1NB+2FX7G/p9QXHM6/FYqMUC4XrwQs3XhG02WgzCwK2PatlNACmLDDxWEnkG9X7KuQCKnkimaOk1yZtL6MfXVqrRtT95bBx4oantTTosOtQaBPpJ7qbbLHGQOHKvKxVuRBVwzSEzSiCRmvULtTyANIyHosfTa0TMhVBVfL23t5qnbwGsidaoepaR904qrPGFYOLFlJY2zfIHmVY9crKWG6b0QVcQjzOx7VlFLRHWjfgtj2qWsIPaofRn0l0J9ddCfWXQn1lApx50SVgo0Yc1Q/wblIM8l9B2BvCuUNbChAq7P+K3980qDdyhDtXghIlERHICAQbaAM71aNN7m8QnO3aS0qzupv6fUFas+mKpYWtDXYXzf7Pam13E5O0sDixjbW8i6/qWU26pBplwZDNqyJWhFc22VRTq+Dw7L78OpNp6fUcGw+G4ndtRu3LKf4jR+DpSC+YGsBuTix2io6VzeMYEd8qk+tVIbXizZZP/ALirIrO1qmjZ4PE9d/Wrqxt2WvIscY+KptfVgvL5FnCIP7rR7cTfyCsVehmJ48qetZODgaoB71btBrLBLnU2n9D2pk1m2ztC666eMqk8VHCkKcl2j1jrkYT+6J0moJLjZwukd8pzzSZUNsDW86e7SaNs6rTHCYPfCotty4upzLLhaj4qnVa+2XbQ3NQMsv8Avpz3vpw3761QsYV5zFs3KRmBTX0z2KKlyxWNyF0xgqtDKPBPslh7U4Ept+q8Qear1T5LI704gaq3XJx4vTKg33FVzxpD4LhLoTHw20Rtb1gocZ6lhzLTEwZT5ukSq9R1NtQtAi0i5zn0BohUIDLUdWKJfXdcGWvB4WmzxT9KSCKZcLI+/CstqbJh+rh1qq1wlxEMPByotgirbOkdwESngPc+rpGBkNxDhPFWn1joYGsGSb5643HerTHQ9tFj3NsXbt/nTag8pajivCC0tkrEqAb1Tqs8kptSmZBzXZhnj/Nb++ZmrFgDHisnbV1mvqtDuu9Fk2aVOnbdVAtW5uuWn04vaXMaYEie2ZT6dsOIqPY2zDpgE/sm0jlF5a0my3CXRxWUtyjDRarvsutAT7UGPaRlWlbb+60h13slVbWUONimKjYpgyDH3utMaytM7RIF108f1hOP8U3RCyLWrieOtG7im1GVbdRwBsAD7VnjPsVMsqaRtRszdxjcSm9qtcFTNoi7o2Yla7GtHaUbtI3e1ycKZcWwNr6gtUXlhwuVU6R2kqRrzwXSuNxHfimeHf4My2/BWhlDw67BF1GoWOcIPWr6z9u3j5XFEPqOiRd2YJwZWcA7FNbpHBgAu7ES6q4kzPnxTalaoY4wulPqFXVD6hVzz6q1XexaxQgq4rFY8iJWreFftJoe4h7XTgj4UkkRgmDTO1NnqVvTvtRZ8yeDUcdJe/rRFKq5k8E5oquDXYhSx5m72YIMLjYGAQFG7ir/ANVgsFgsFgsFgsFqYcF4Vtly2ito9ymmSX9iNR+8yUNLeibw3EXczCDDUdpXXv1CnNozfxWqUaRcbJvRBdf/AEqwHeEsgbKe0uumW3Jg0xa0OnZmF0p9QqGVbv8ATKAYZMzhzMN48E41TiOCdoahZOKf4Z2uZdO9G3UMGJ82CuquwjBVdd1uoLJd1IgPN+Nytiu+1JdPWi7TvkwT5sFa075iEdc3iyexMaw3jHPisVitV8heGcdGdoQvpDvynLp3flOV1d35ZXTO/LKAdlDvy3Lp3flOWiySoXvtg7BCkYqw4iMcE1zDDmmQeCbYquFmY86NM1XWHGSEXtquDy4unrTbNRwswR5sE4Bx1rndaLtM+2Tamd6catRzrTbJngmnTv1bwnOFZ1p2KFMVnhrcIQNSq6oRhO5C1cFAqEuj7BTqlRxtnqWq8tarTahRqDf9QdNlHePgumr94+C6Wt3hdLW7wukq+xdJV9i6Sr/75l0lX2K+rW7wtavlPe34K6vlPe34Lpso7x8F0+Ud7fgvpGU97fgunyjvb8F0+Ud4+C6fKO8fBdPlHePgunr94+C6av3j4Lpq/ePgumr94+C6bKO8fBdNlHePgumr94+C6Wv3haak+o51oDWVtznTMXLaetuotuotuqtur/75k1hfUvQOmr39Y+CLjWyi7rHwQ8PlF/WPgm+Gr3mMR8ERpK3eF0tbvC6Wt3hdLW7wulr94XS1+8fBdNX7x8F01fvHwXS1+8fBdLX7wulrd4XS1u8Lpa3eF0tbvC6Wv3hdNX7x8FoqrnNbZJ1V0tfvC6Wv3j4Lpa/eF0tfvHwXS1+8fBdJlHePgr6tcecLWymt6wX0nKPZ8FdWynvb8FdVyjvHwXS1+8Lpa/ePgulr94UitW7x8F01bvC6Wt3hdLW7wukrd4XSVfYukq+xdJV9i26i26iLQSoKssJIib1t1F0lX2LpKq6Sr7F0lX2LpKvsXSVfYukq+z4LpKvsXSVfYukq+xdJV9i6SotuqukqLbqLbqLbqLbetp/sW09a1Wr7E4Nc+yECX1L1WoVatZtj7JHwX0jKu9vwX8Tk9Ws9+kDYeR8Fpar3h1qLl0lX2LpKq26i6Sr7Fq1KvsVznLErErEokucr3OaziF0+U97fgvpGU97fgunynvb8F02Ud4+C6av3j4Lpa3eFqvqFapJ+up/zQvSPKb1NTexFXYhAjtQd1fyHoHNe5Yyrmq5oCxWPLuerMzK2ig2oruRE554jMD93moxOay28q68rwwEIOYZaeXDTATkO1EfbaM34zf3X4h5McljeKAYLhzM/XP4oXpnlP/pQHVnezzhNBzWnlN6xPO3fYKx5yzj1BXCM0m9A8hw6kxgrNfVa7FbKlMPNlEq9GFcFacDC0WIKg48q7inLzrJ39Wb8Zv7qf8w80CcAE1x8vlnkH6pl58y8E2FtLX5v8UL0zyqp7MzLDbV+ZpzXprVQJMal6nnPQPNlxwCdG9Wn71hnjyVLVfmfYjDenaSo0vJnVN6sg2rV4WzciTuR5oq08LBYZoIlNLOjcrbBunlDtXmXnWSv60w8Qvxm/uj/AKruZag3rVAfdV7gFjzLm9X1KM5cdyk4Z5HN/ihemeUet6KbmOYQqaoBt+ogSInnPQPNmDBcYUu5cK5jndgTyyk5t3liE91YsBd7FSe2u2G8VtogtMPuHN+fldYVGod2qVq7LxI5Q7F51QqfehUT91fjN/dR/mHmafag1yacABm1KpQBMqTm1BctbMcw+pRna3jyQdxU8z+KF6Z5JQu8rM3szHNqGFbc42leSUBmALhfyLlw4K+5FoO+Fgoc6CvQPN0OEoEb+TgpzSwwryeQxvDm3cVeYUWxKxUlYIA3SsqaP6mrJ6nlMNk8puYOnB6pL8Zv7r0zzNLtTe1NB+ynB9M6PcQoptcrVUQ3cE5yKs1BBRVwuzt+pRnY3qUTCudm2la+ymnmfxWr8Q8kpzg4m6LPBBDszRmmqewKKWqEWmprKzVFoqWmZWuJ5Bp0QGwhe25RctZBrS0AKyxrLRxXoHlCxmOuRenSd+YtG028IN3grbWOa4SoacOpdeYjklpDR1q7mnNay1rKatSOxWmPKAeLY3QtHSa6nAl04qzUx6yhYDTenVHPdZgNs7jKoUm3QJI5TM1XC4os4L8Zv7r0zzNKOKB4FUz91Q8SpsrVT1fxU2YKtTKgBAZh9UA9XJs8VB48z+M391+IeS5agjVQzgjEJ9V4iFbeZXUr2q3krrFQICrc4Gy8cjFB1SDcppWGlFrqbMeCpOosa2++5BsAK1TMuhegVJUMBQLGyhaEHkGXgJxbhKLnYBP0ofZIusqWcShZdB3oI5rQF6BKu5bXdebbb3rpG+stVwPZymuGBvK2oajZlUaf2byqeUsGFz44LSU4fKtPaGgKtNwN7D2I1DNrA8qnmd2Ko2V+M3916R5lvYpVA/dzWW7SBq4ncipCChFR1ZwfqcP+zmnO0IAcz+M3916Z5MJ08IQ5GgpXmYKsPERioa3MA9wCa5pgVmqi/i3NtBbQV7oLmXKqQCfKxR8CXT1oA5PEdaD9EbutWdAF6BTj1LDVGa5G/PsBXCEQ59jzInTWt1zUW7w4ypUBEcURnpNJvdhyfCuDJ4q6o3vTo7c20e9YnvVT+rlOcQbOC8E4Rwctao0T9kLWdJO9C28Xq1k9oD7pQde8/eKrWrmxCpOoknScpmZ3YnNX4zf3XpczUf8AZaiU6lOtTKhaSoZV6MFGVqrrzOzs7PqQZinDMbSxXUieAz45xyPxm/uvTPJAiepAWTT+6TMIZr0+o+5rRKdlFVtt5qlaRoguasYKvMtRuApzqpj6Yl1Nt4G9UxOxcVIMhf8AhQqjRBMcE5uLSIhEtuWCGob+pWZC9AqJQ17uGeoZM7hKpajmHr5L2jYxVWMDmkXqW7SBeBnyYfZEoIhEMcb+JT6di26d6YawGpcIzWRw5B/r5QLOOa9S56hxB7VAIQdT2XYp8+U4BUWMwpsjlNzVrW5ibK/Gb+69LknPFK5u9xTmtNpxxKJQY86lbVKBTK1HwlGYe3h1rWGqd6MPRJRYwSBvRKJm/dyGdn1IORLfK3ch2hAv4rELXqFSHu70G1TaCB5P4zf3XpnktpuwOKaxuAw5BoMOs/FaI427SDpvhWWJrGBMaQWiAmNmLpKy0NOoX3IikJCwQsGFUioHGMeCivWb2wi2nVaaR3yqRySuLjeJQt1GxvvRc6oL16B5JcXEK00knkmyYlORBWyrmrVatZBPeNhtwzYoPcy2FV3dSo1n9JWdqjqzQOCcDn9PlQ5AG9qmg6wdyaMtDpBvRDKbqhm5NssNJoxUbgqVLrtHls7Ue1Vr8WJvavxm/uvS5JzMpN3m9Np0mwAE5EoFhggpjv8AFAsvHWg1E0z5k+cnngURZ0QIQAzGNkYZgim9X1IM3hHQjo1acZWssVDbhyOKvRb9nk/jN/demeTqxIG9MtY70c8njCPUnUnG5+CtG5Q4Qeoqi6tUtUm39iruo7BMN7FZfsv5GoyyYvR1F0a2Fe0LZC9A84UavDFcVgrkCq7hjZRzQgnua2IbesmcL9ELJ6lipYhONnOP6jy+tFjlDlhmaE4nlt7Ue1VOtqBH2kw/5rf3Xpck5n1eFyGjeGM38U+8G5MG8mVKDsaLrnhCpSMtIWrejcjcpKIGcLzJ1l0KyHEqH4/UUqKZsLXdKxV96PMO7OT+M391+IeTFQwX6rU0dSOYqxw1indqaRiCtbFC0EcjyM3uGu7gohOi6L1Ycdccg5jAmE41B/StcCV6B5uQLlL3QnUdaHC8oMozZF1+/kPbxziBLlEJwJIL22U8UnirTc3BFrgQRitZTTwhYLXph6s0m2Rw5goTnaPJCPby29qd2q7grk3/AF2/uvPy6bxq03Pl3YntpPBLbnRuRaDKb1Z2tmWcFiijyQiqitwrBZCtMv8A5kMDryYTtI8Xe1QyXHgFtLaKxK2lBJDuCArtqUycLTYTWsJJJgBbZWKi0U0vnWvHJwV5V6Nm8nk/jN/dBtN5aJKDtNiumJWtVeLpXTOQl5tTcuncrq7l9IcumeZuTqjy7WMSsFgrirnIuOJRVW+9ypkHegc5Yymxw3a8K1/ByeqorTqRpuOIVRtBri1hleEaQUSwwbKbe/X2bsV0hXSFdIU/SOtXZ+CLpho3q02POotoOeZhXKRfyL80AyjWqYnDMExjfJxX/TygiWH7S0dVha5QrLapxRtV1DajiepdM5dK5dK5WKbnvdwaFZrF7HcHCF0hXSG9bSucUb5WttJqc14LTPLCKHYvOrPCs391cYTaloQ7rVlhL74Eb0BXY+mTuc2FtK+9ARitGyoWsbcAqtejbsHaeBculJV7ysVKslBaqPJCJTxxQm5UnQGCbyiQQWn+ZtzEHvQAvgKpWeSHiAyzj2+z2prWCmadSs6ZxayGx+6oyKVR4cw7YE3GZ8/FCjpKNkV7RNkDcP3uVewKTJpgzIdBjAf+E4scGMghrh5N2KaJpfxFk7T7TZu83FUXNFKdPTtuG7CY86p6T+H0jWuMNiyRdHVOKDAKei0lS/8A7fMnltOiXW6Yvh12tPVwVNtoGyYdP/T0hw603odJaPQ4Wf8A3zrZKwshYTyI5P4zf3TQOJWJO5NDzZbN5TahtXWgQfZCJdGjhohxF3FZK6KJp2m2pEn70p7qtm24TdAgqpbNPRhkssb7x7e1Vi+y2S6O5M16dKxlDHG2+NVZO2q6hUaa9QuvDwGmz8FadoADTdpLte3fEexZQ6lo7b6dljfskRf5/iqgqCiKTa7tHZaGy2+PNgg+oKNgupsLTDhiLTuGCp1W1AKwZe2RrG0fPgnNUdaBlWdmqzFueoS2SGAhN1XCeDk+jWL3MN9OCpsVvXWxV9dHsWRU6zwGshwcfJNsn2j9ky0GVHy07QE33hVm+CqN0rHEWQJEXwjTrFjhShr5utX3nzKp2ZpN5OATqWUU3MpMvc7rQ8lgwajyLleM96iFLig0ZgndqZfDhgVoa0Nyluw5Fldth43K1wKCdVcSHC5tnH/34oObotCazptY2IbcO9UBVDNgzDQNaTiqjTDLwZB705zQGgmYG5ZQ5mhLrd2lws3olgpaItfFrb2nWf2TT4EsFQGnGNn73/lNdFAVtH5QAbNo+bBVeixd/wBgw3xM4JyhNKs1m6rmTPBOfkhL7OLd68IxzO0ckdqKATupysz/AIrf3QaFtE+SFkznmGiq0k+dNd4FrwHEsa+004ReZ61TpUW0nUjXdu8mbr8V/wDxv4mx6GPdMKs5uiue6+77DcN8WpwTAyyXgi8b7lRraRthgaC2b7sRHX+6yelU0Zh7C8+lf7E/RltR5A2odGP/AIVMZPYc9riCW+U26ChUZiNoKQhnNyMZ4UZvshUGUDMmUKb3y5x/mcAsAsAsAsAsAsAsAsAsAsAsAtywC3LZYtli2GLZYtli2KatNp0j2yrqOT9x+K+j5L6rvivo+S+q74r6Pkvqu+K/hsopUWMtB0sB+KstDYWy1bLVstWy1bLVssWyxC1A7OYtTnbVoxLV0GT9x+K6DJ+4/FaR9OkDEXAoBrKdyDjSoyOoroaHcV0NDuPxUtWy1bLUHMDQRgpICJY1hniujpe1NqvYwluAUaKi3sC2WI6jFsU1dTpe1To6XtV1Ol7VsU1sU+4rYpro6S6OktimtimtlimwxWrFOVGjpe1A2KUjtWnyhrQ+yG6q2WLZatlqDbLYBlbLFssWyxbLENVt2C2WrZatlq1WtWyxXNYsGe1araftTmVKOTva7GWlXUaTOyVstWDVstUhrCrVimrLKGTecH4ovNOkCTK0D2MDZmQoACwCwCwCBbAKwCgALZajAaVstWy1XNagHZNk1wjA/FWtHTb2StSnS7iuhodx+KvpUO4qDSo9xRNhl6va1YBTAUWWqbLVrADsTKbWsIZhKGkp0ru3/wCMqdFlxeYTarKukbMG7m7NJjnu4NEr6NW/LKLXggjcf5MMotL3HcERdUc0S8N8nmxTottPOAQblLLE4da1hHNNp0m2nuwC/wAP1k6o5rXNbebJ5smiBZG8lf4frKYYfS5sPe4Umu2ZvLuwJxpuFSyJc2C1w8x5i1RZqfaNy0OVObTunax7EW2muje3DlwxpceAVjRPt/ZsqDzLabL3OMBfS8n7z8FFLKKNR32QTf7Oba6pWpUrV4DinOp1qVWzeQ0/UVGvIstqWT5wVTotIDn1BE8jwtQU2AS4/BeCqCowiWn48rKP6RmpGqwOiiT23rKO0fpnay01k73G4JrsnraVhu4Ec9SFVrjLnDVH/vFfx2QuFNjtm0YN1yc15tPa1rXHiY5ptSjRdWgQQ1ZI/KMkq06FJ0m23FUm5ObbgZtRgn1WMNSkyLTQy0XdSh56V1lojADPP8Q3T2bdjdHbx5NLsP6Zqs/YOef4huns27G6O3jzFT/U/YKjoHtpsLw0fePWhpAA6LwFU/qPIAuE3Xq1QrirBsvGHd1choN0lV3xraQs7GjAI1v8SkbTCq7GbLXkDlAG6Ssno09G1puh3AcFX0xb4JzoNN2GaHvFNuJcU00agqU3CRxHbya+jfYque0XY2b1U05qPD22ZD9YKqajbDpwzONaoKdNok8T2KGPFRuIcOVR/qzU3PMAb+Q1lprJ3uNwTXZPW0rDdwI5WRYt8B9qz+qygC0bNIjWIO8cM8PeKbcS4ppo1BUpuEjiO3nRbFpy2B3LYHctgdy2B3LYHctgdy2B3LYHctgdyDmXdXLssskPuc1+yUNCaWs2y5wraRw4jHDm9JSgzcQd6+js9ZU6zfAuYIFlOq1dt2P8k6lWBNJ3DceKbRoO01a+DFwRc8ySZJ5rRVmuDpmQMVUYGveXNiC1aKox1V4ZElm/mg5hLXDAhUaeTuIeG+Eed5RZVruLTiObfTrB17pBCbbDzZMjVwVwqHzIu4nmpNQU6h27Qlr+vqKBL21S29rGA2Z4mUXOMk3nlto/8To6Sz5UTK/hsgp6KmbicOYeHl1MlwNprZkfZTn1TVZLibDGC5VKsWbRw5lr6Zhzbwm1tBRMCIsJzf4Vl4ja5vJ9JU0RaAx2pu4p1n/iB1mwf5Ks2qwGoGuLYqa2G5qoRWb4VwaRGzIlRpgGaO2XFuF8JrDlFMVHvexgv1iEHaVuxTfh9swqr3VmCwXho+1ZxUOqNAtsYDxtKnaqNFq0XfdA/wDtGkXB++QvPn0uido8bUc4TRpOqAY2R/LCq6mRTODudDg0lpdZB60Q4QRcedDWC044BB8asxPLBqsLQcJ/kRpqbmThPMF9Kk57RvA5guoUnPaLpCLKgsuGI5k6Cm6pGMcoNpguccAEWvEO5A0rCycJ35y+pRe1oxJH8qCN6NKlVLGHgmeHOoQRcEHNqxDbMBoiOzBMpUnOY+08vd9qU1jK+q0ADUCqMNYltQkuHai/Sm05zXG4YjBBwrOtBxdPWcUalU2nFAcTna1z2ToHMONuZPmVV7C2XMcABhs9nFUXUzTbTY61UbY2kDXa0zo5stjcZVmrZe91OHPoswM+ZWiGHwxgWPJgXqg2too0Tw/UjWvhN0Dho7r3Yfp+yqTooLh5H3ezj2LJKlVjRpYty3AN+KacnjR2RAjDtzUGGuKDqLiTIN/WE+rk+iY4vc5zXskngqjqhpaO00AaO6zv3KLOtoInrtfrCFs0S22bFmnFlsHG7sTnEMdBpkANxxlUw4UrH8Q614PyNyo6J0suNTeBejNizZfst6xG4LTTQa2qWNslmF1/tTKb2NcRAqcZm/d+6aGGm59s302WdXm6Rr2HWabBqza6+rBUy0UQwTJ4j1E6yaViy+W6PWLr4j2JwcabWCqywRT3QeriiaTqLKpY3WcyW753dm5azb9EySN94nzoW3UC+X2HNp6o4SmNrGi7/mBaIpDY7k3+GMztRgOTWc5zSfIZ97c5HSAtq6Kzs4m1j2plk0rQthrrF3VNyptrGi7/AJgWiKQ2O5QRZFl87ziI3KpApMe6LGpc3U+Kc1gaarqLb7ODrv8AzzDKrLywyqLSBRDajnRteTcq+h0WtSbHg/KundyWteYbi49SFSq9lRgrlzw3dOH6J7XBjbTQ20L+N+A6l4HR03WGgFzLt/twVzf+pHVwVIg0tDF7dHeO25MdV0evTdIsXkyYTBLDBImzus77uKaXlj/BRq73Byq3M1rUQzDV+KqfxFktjDf+iydtIMxFsWcdVNL3Ui8Mvhmqb+zgrmg31IP6INplpeC2DF+F+7kUGPqUpZaOoNXzyE009FZNZhd4OdWL/aohpe6lB1cL/wBVWD3UDSLfBANsxeOpPFAl1OdUnkM1bdZlYvaJwuCoiGtbLb97bv6fiiXinexuDLrUnqTAX0dJo6jTdi6+E0QzGkXEs7wqLcmA1C4ExecL87ac6+lLo8wRrvNLRuyh8lzJLmwMEWNsCo+kzWLdkyP/AChY0THC2GF1PDCJ80pxq6NzbohnlWbz2KoYpnZsAiNXhgb1cyH6CPPa7MYWoGWBWLpsYiCmuoABths9ubI9JWpsl+lcDPm/dOpVNHaY17ajbOsX7oKJqaJ+TWDYY1kOGHtQdX0VR2mdgy6yYvVa06myrdYdUbaHWhb0Zp2W6gZr2t9/etujbNsNe2ncAcJQtuo3PpFxsXOibUXKk55pO1XtkfameHDqTC+m0eFJ1cAIHUgIaXmmy0bOBBF36oNyUCW1XXxiLs+XkOltUQzr1gn062iHhXgWaewIOPnVmyym11MM2dm83/opa1g8G0NkdZ6jfgn6mjcGVA0RIPBMEseGk+Ti2z2cVNkatNsNN5LpO/uWUNaGa5qWYZ3c9DHQttba21trbW2ttba21LzObaC2gtoLaC2gtoLaC2gtoLaCl9S1uvK2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaCxC2gtoLELELELELELELaC2gtoLaC2gtoLaC2gtoLaCxCxC2gsQsQtoLaC2gtoLELELaC2gtoLELELaC2gtoLaC2ggC8XYLaC2gtoLaClrwCtoLaC2gsQtoLaC2gtoLaC2gtoLELaC2gsQsQsQsQtoLaC2gtoLaCs29XGFiFtBbQW0FtBbQW0FtBbQW0FtBbQW0FtBbQW0FtBbQW0FtBbQW0FtBFzny44kraC2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaC2gtoLaHLDrJsm6VYsOt/Zi9QfqSdlbfsW37Ft+xbfsW37Ft+xbfsW37Ft+xbfsW37Ft+xbfsW37Ft+xbfsW37Ft+xbfsW37Ft+xarg760wCwCwCn+fF2OCsuBDuBRaKT7Q3WUQ4QRu5cPJZRaJc5EBpYftAqao1JucvD2rP3VpJs1BSY2k3StcLQeDNncqopVWUspNQWhb0csiBeU62bTpvMzP8+XVqNOo7SG9zQVQAyejBDp1Aq5bk9IGwcGDhmk7kylREvcbkWZPlbKtf7Fkiew5i2iwvIE3IaZhZOE8/wCDYT1qJZa4StpgWte3iFa3jNkZrUrVA1BaneF9EyX8gLK30skoNIpEtc2kBnD9GazjeGdS/wCZyMNYbtlCx0bsOrMxvFwCjRU+8r6W71Eyq2salp9mC2M9rKXlo4NxK8A57XxcKuBztpsxcYVQ/wDDqbbFK59Z15JVjL2NqMPlRDmp1MmRuPEZgwmy3Fx4BWaFMtHGFFZoM4O3qpRdfZOPHNHki8oFujo09xdvUjRWiNVzXYpzXiHNMHNWFLpX5QY6tVq0mVV203OEt0r7yhQfUfUycgbYwVf/AFHZiHGGN2kGtotKdpGw4CfgqOjaA6IfG85qbso/iNLZ17KMaZOLLU7s4JxOYVKYjiF5+brCnUc59B9ipIuPZ3ZzYY50YwMENU33hW7JscYzg5RVo5NODar9buTTUALHbL2m013nzaN9PXsaSODVBTagDGsds26rWz3p1Qhjmt2rFVro7uV/ws6Vhe0Ft1doi+7suVDQvpU3htNtt1eTSMnyt/HqVAVKs0cnpE2jVBNWJN8de5OqVDae4yTxTnsc2nTaYtHetDlEG6QW7+TQbpadNwYA4ExevpNL1wnU8nqNqVH4WdyDKYkpoAabUw4OEXY3ottNfG9v1B4OqGC2brEqjNYYO8hVprA6h8jMe1B1W5hBY48JEKk52U0LFqQRU2lV0rbD7RlvBZX/AKP/AOwVAOsucNJZa7e65EV9HSqaGXx5Ot+sIuySlTNSyyyx24b011NrDXsaw4C0cObNTKTqDBoxcixrBRotbJIOCNOLDdzuKI6k4OdiE7NkpcYAhdMz1llNNuU0TUNKLNu/OHVnim00Yv8AMqDtM2oBUkht6AaZmoXDNS/rH6oaV0SulVEgyNKP0Oe2xpcN8bldTd1nhnpTvuVfI8pJYx5guHklaTTsqGYDW71RYdplFrXZj1tVlhuHtVNtWrrtxuT60QDhmqt3kBUTkwNSyyyWjEJjHnWknsWUPZsmoYzaWrSFanpHNsnsCFXJvDsLG3jd2rJqFvS1GU4PwVQHEOOZ4PGY4o07LMlbuafL7T+yrOomxLtRWqri52Z1qycmLPDB3BVXf8NoufRa66SE6nlDLD4mMwThVpaS1EYLVyZtrrA70XNYKc7gvPy2DIGeFd073tm19zs/VWskY6mxwksPknq6s1mubLSCJ4HcsorV5DK79JEjruHG/PWe9zw4V6Tmtpvsl0B6dVrtbpi5zaIa7Bjjr3f+7SrVRXZUyVz/AAYbVGzu1cczXsuc0yE4Co6lUaC98V9FbjEl2LnHgnMpHwRMm6LZ+0Rx7FXb/EVMlfUsxUYsmp1qzTYFOrIMggF/tMwgOAVehaaX1snLB4Rov1uJ61Xr5dToZRT0VnRadptmRwnM1rBLjcAqlFzWtfTFp9p4gefzqpQshr6e3adAb51UbDLbJltsSYvuRdSsHHVtiTvuCY8tbDrPli6cJ4KjSa0PdX6Oy6Q5Oa7aaYKY2tlVBrnOLo0guWT1cnr0qsS0hrwTzDxVmxUYWEt3IUaT3wbc1A2C0kRd3Jr21apdNMOdvcBinMaXl2IacA61K6KJ0stm42rPwXg3vyY+DvYOAiFUexthrnEhvD+c0VW1NqbgqbteBO5VGttSWkYZ5bmtVXF54n+QjLKZt8TeERSqNYD9lq+kFX1v1Rs021j/AEI2QGiZgZmts4BbCLsJzsa2ngOK1WGVafma7GyZQcKLm3RtLYPrKjk4plujMzOc6IFtWdsHdwVmrVJHDPTqVZLWmbk63TrMkzbDlayVj6tXc6puRc8y44nMC24heEEO6lqDz5w5lxCGmDm8YWgyFhpMiC44562S/wDEdJadVttsN6giKFWqWn7sIZTl1StWrjDwdwVR7cHOJGYOYYKvp39ql/mGeFqOLexa5nMM29cAvPzbWuNzRDer+QAcbLd5WVjSP0WUUmC3o9ktj4LKy5z2tyinY2NmC2P0VapTe6nXI0bXOZMMDQ3vKqFlZwyg3NeaWDY3dadbdU/5jRNqgM2A3GO5NLG6SkAGMDdXRtm9VX0xDXPJC0mS1DTfhITn1CXOcZJO/wCsNo962j3raPeto962j3raPeto962j3raPeto962j3raPeto962j3raPeto962j3raPeto962j3raPerzP85adSZWuiHpzwxtMHyW8hxdQp1p+3uTnWQ2TMDdzJpHJqTyfLcL+Tof4alMRpIv5DrVBlaft7l9Aodyc9tNtOfJbgo+p/wD/xAAtEAACAgEDAwIHAQEBAQEBAAAAAREhMRBBUWFx8IGRIDChscHR8UDhUHBggP/aAAgBAQABPyGfWJs0FzaSbsF/lSB5ePf4KM9YHnMvTSA2NJvduF+PjthyXcMx2ELp33Ef+nGtAgQIECBAgQIECBAgQIECBAhqpf8AtxO8ATOFMEgZbACJzRlZ+BWKbTON3HQYYV/vDqfvbeGEJVyKgg6XcJz1qK+H2ys7pw2d2N28bKXYlLilA4HWzwlSncnjOwmiLT6V3PqwWUYhS0s+1PZEjIZrBekbrUjImCd058Xi0WwocRUOV6KzdLkuJuBFxIbk+CwPmXQlCm6wIpKajctvvR7jTIWuabOsU2EcQCJbKdukFPxCNyj3YxbNWzd3iaUYLdhGTWta7vcMN/eTZtGpOTugqq00UwhNuF/+/tRLcg5mpHlCML9nfAiBJUMK7JbEfgVo6W3J/A8cdWDufREIk7An/F1dGVL+8SyzZf2/GqqqqshSccF6KshTccl//F1VVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVV1Hq/8Ai47HUQ6kOpDqdGiyVJLB74FHesqLikjP/wAYTrgBfCV9B1wAvhL+gx0ODLva8hQJMeD1NrUfWI94IGtqYDzpAG5d+hvwKf8A4wTHFiUfAIcWIRchjCookoebrGxJLc4J7cvPNSPRRqBRRRPwT/8AGJEyZMk8/wD8neMfk8Y/J4x+Txj8njH5PGPyeMfk8Y/J4x+Txj8njH5PGPyeMfk8Y/J4x+Txj8njH5PGPyeMfk8Y/J4x+Txj8njH5PGPyeMfk8Y/IoHxmrHobiDGi+5NqiknD4vUXhv3Fs+L1OLx+p5v+Twf8nj/AOTwn8njP5PCfyeU/k8x/J4j+Tyv8njf5PG/yeV/k8b/ACeN/k8b/J4X+TwH8nmP5OxItjfchROqfyeMfk8Y/JHnXluQZJ9EMPv06HZY3m9STHj9R+b/AHOHx+otjw+p5n+TzP8AJBnx+py+P1Obxep4r+R+TfqNWTOQ7JUZAi8dxzCL6FiiZpz8iqquCGLWi7ikb6QmigkgLoF8NE+0RSk7D7w0GTK89zwH8nh/5IM+D1FToPkRVVNlkTPHyKqrLaYNDnQipLWgiAnohAaN9xHLi6po1zBcvsTu9hP/ALVVUzbjCGSEEEE0EEEEEEEKwCGbasyiCX0OxEighHyADIWdJSdrX6AoDB8D1qY1jhoJGhKMRLGTRLSFoWb5B7kguUfB+SBk2ZKNl2N1IMyjfDQ3OdtA63RGEBwNwB7hGwB+Kf4f8ITaZsiNhIWbkdACKimofQ/Z/wC16R3oSCCQgmgkJqCQhDkUttm7+0vFEW5QFYQMYTbiDJGAZfot8IMsM5CIO98G/TFQkGAcMfwgWVKzIH7plSNj3WfZrp15wxAMjdG2GyQZMT5z8iSObc5+cbytM1uIuyIQhPahuJre2w9wXchJSW5ALcjTm8/Z/wAIQQLCEMCSbChwKiVovrPpvs/9rB50PL7aiCCaEJoIIIR6TQJbyRwnQUYnFxmOLsMyc3hKh9iCNEaGGMjcb4AU9gfQ9khBFuUOQ4kFwyw2M13OrG2w2b0AuucmwIY4nCxRgCEEQgYDxn5CJo1LAyipCbsJbGbjRspNolDlvxDEh8B4aIElOyRXJ+qQVLv5x/hBoUxhYwzgW2MArEiwUDaEPAcf+W3I3Vm1iryFHB15cm+wsNTMNfMd4/Yy+KCEEE0KxCQ2UJD0USKnAha0YpIJcZHU2AuhosQQRo0MIWRgb4mEQEUaOoQejmcYiaQ0HgZyJlSVJNuOBMlC+ocgpIhBSOwLh8iW5wdS1OgohEwBlkIwh6JJsmVgu6cxIc0YfugRIUMrm7jYJewun+EJJCUB2gmSxIU1CD6CQfQfZ/5WJXWESY3dmxXozAkB6Fsz8w7z+whPgiFqIIYBSTT4WOzqSTiyfc0MLT5KxMo6wFqXswhIIIIII0I3G0AWizrSLBQlFyPXQxIdpUhJwDjQjKQlodqC7iIgEwmhhzFV8i7Az9CXSt+JItW0WiNwGScMFhlxFuCLay7JXUrEly3myAafdJjI+ibid2dQgHT/ABAlDsB9lnUYJbciSVDdQj9Ndk9AlLQhXxK/8h/VVux/DR0IXIiDQtumJkYIw9RDF+K2YrqXukzzD742hKgX1E5x8Ts3ngT4gLUZVZkdrRmzO/sM6sTsMIQZ32ZLckhguqhbG8TpQkSnHHqb9XpBHwRrFoKsaW0FgF6ZAsJrFWDA0LQEy3JCtxQieBArUTGysTWwzYwdx7HzVjW88GFFwOGQUhIogdjYl3RQxrobkEAVNueighnYKElHgnL9whVap9v8IQbBIKRZi4MkKp6CiY2OpAR+y1u4wGcr8kiYseU4/wDIlnEq1Idv9RlQzgIICSO/ExnsdSUN+CocqwHawjgykuHQzkcEIAzNvid5fb5QAgiQL6GI1ISyGYPiBNWCKYokiiqgGgySsm5gyNOEJSPij4GCg4NEkoBcoZhoRhDlJDHslsMcAxsYGxYdwIA4DuSEnRLDjfJzob+M2EGNSkZIYjyCrFkoJQ0txRDoxLpUtESFgU4ZCIJbkhWf/l/4g7cxxAIHL8YmmEmsH2ZWEYNrmBe7jMtSQnOkISYj7P8AyGujO1CenSGVGNoeG8EUS+56ewLYVqZlr+FyGlyJ1NWJkGSy6HbGaZfcx8TvB7CF8gV5aMkKLX4SSe3ZHfpSDdjcOTcgIppnA9mO/bYhfG9G0Dh0SdIWYHSSG76u4/YIkRYVRwJ6BERz3ImFzYwICRBuBDDYPkG2JXOoShFcfYMsh8CmjTrEJcSsnpR6iAPV2OregkpP3NmuT/CCQQNO72F+5DRKjgeCrIKU+R6BKVyCBUl7kIdzKFKEg9N/+QwOzoAgsgMrskRyUCSaMkJHS2b2CenqBHOK8t6KBig33pXW2fE7xewvkBEMF1DhUJiBCWKEbxMKWv6M0Hf0Bh0hMrzGZGjNSmi+PDRvgmrtq6hei1kOaF+pj7gMUzke7ozUo6iJb0TLwIYWWZBcloFXkExTHhkPkUBpUkvToMKjeBvoJFWclKwcyoSuYgEtywqFqjqDmds7CQxCB7dCZNN9EpJLKckfoN1HrVj/ABACIOBWG2HJm2VRFdcy5SZLZD4Q+wM9QtXc3LDk0FGtP/HZIStoghzViixssjmoBwKHkyQwQg30RAMWyY5qLYVNuiUBxFGQCF8EuxYMhwUoaB/C7yewhfEBk0xWUkkFvefYgHf0IpMlACmOzMhg3RIQnIxle6W9iAIRVovjxGNGgrT2tGTaYSSMgbmZQQvNZhB0LIhhHuQB+/BQqYnQPWA2GAFkMQyI9KfkXHWMM5tyguPmGOCwO/QYEHc9AA3FMSpwBCfuByNn4cgrI4NMSmjS6vsJBbESun/CG4NoLVuJTb7IRImkHMZqwyCOzFm6bJA3WdcC0oXhyTB3/wCM8voOiciJdqIJT20gxtbaREd0ihAyGaEAsBBGJosVEFbhiHMjA2/MgmxSp+guNnRhiVbmD4XeX2EIYbRDojLbIA33ew9ZIJFHBkolG4Vn0EHApIWmbGvZdBnYuBbnJE6CkTTqpOsmIxgzI0/BmyjkZTeElfuRmTJ+DJDOWCJkPAjhJpOgyBuchAi0zXyGho5nGzD/ALmGILj2lH4ZqHN8ZOkIrJQSKiXT27eUtxHEMUpdzjAXPIbFZUzH+EIZI5KMxV/SZl4OvkaZ0kdyyYNcLYPjaFLZ0GiFfJ3GdH6H1hdD9f8Ax5YMRRtBUhcncb/9gTIY24CFDFMiSSBe3Fd1sDqbE29M2zdIxJjFZBe7G6WEp1kQk2+wPD7CEIY6xvEZDy5FUdBu+wJwqFQZiF1HuLFsi+BXDOFfUZGy7F38ghLEgkcJcgwzwCmzhzI0SZGti5gUrVLKWdai6C86LpaD7wIeJgke0+FMw0ma6FF0kMb7v4WQJkXD5DyNWMEGWSmTKiiACb8BDtcRKPcvuQTr2IL3AJXWTkJ+h6IIs39S4jUQwKIfKgRtuv8ACDcyyY5V0xJUKm5ImJKATb9ZsUBiC02NIUzUwUC8GzMM0RyVR/RlMghqYxMv/Af5cOPMHkP0eb/R5v8AR5v9DrE+3lFou87D5LL8bGQF2UjZMy2zg0NW+IwJUjTJ4wzlATbOhG7tI5TbhzJQcuJO4RftL1ihMi4JyUwluViJ63ytkmfelCPyfYSfB9jxH6PCPwMbbV4USs+onxAYJ/UDXDuxk1J+RGBtdWKc4mAU+VTGGH0HXSzJbOnAhjIfVJQOirBSZWz3BwpQpaGiIx0ZNGHe5sqFuCOEKcO2HBLHouBrIXjY83+iPC8/YdEu5EvOw23IGBbC3yiSbj4UxhkGM6l8BIygLbl7UOVmjvO87zvO8a1uo+9INQ3PkRQrf2G1WxxjZwgW3GTWMQNiuQZLMSUav5fJOknYHvAwWFs0d53ned53kurztqJ4IvluThV7MRnJdRjovX0JjpBSnUJe5VRerJzYd2EN3NDKWHi+P/gepcnRSlFRDyNyv16iDbNfkTBcYXbLJGwAmrVw+H1LDFk65Ye76IkGc3rrf0ImKXRAoY5meU1sIN6AeGtDMHwhbHHwC4eDEcTZDDqzRjjgeSRo2VcPB9wihlQmmRUBpmm299Am5wbs/wDUXFQHVlYSFo29jefqDQYegsksy6w5GKI0zo12brvHYZDO9Zw5ju4ENmF2b2QiscsgaQCyn1cqd9mOhmfenhpFv6CAtIgwrn+uCQPdssbKcriCDAMLkhSts9TkC8iHtY+hgE9jdGasRsopmflBOV6IvqlfVRBMHzHqR26HBrnqZCDYz7JEMzH0LjC40ToUgnRPPN7xC7MZCSwmBOrooyOJKJ+sxjTyYs++W2RHRsQidm9uMQdffIm0m0A5XiUjmCxa4DahU5fQdISStyzejP0+NJikxCDdEpR0MZ+Iq6JpWOcuxCxw+RrZdiQ1hLDbg6BC9EyScHCl/ccD7O703ZRR/ZMKPS0m7IrchcMhTCkwJTMVKE3TwMK0SUMb4d2KoTKKQTwnHJMCDmUOibs1d4yQ5oJ3Nv1GRSPKmcaSeG7JjVEgogh0LSThA9TFiJB3YdPkn3iBkX9x7i7oGN4NZGQYCFkcK5INwyAyISL84H357EDafQxPYcBz7Q9O4uklFNhCpSW3s9AkK9c3FTE/sGJZbcTAkT2RXKq/QJsjTLnteVtGTeKMd5kftEyZicFV4h77DHuElI4F1GSQ3gNRDEEh84/+Bc6JMh3Lae4ypRPrEsnZk8vI+kZI8rDHFYqijgkDfKJxefc6NtNpQhtHYK3srXtZKFMh5Y+H6nmZx/UeJkKh+0jKhTKr6lhwieVF2L1OAlLrtFbxlsNhAASMmxZDAnuT0KtV2F5FKQBkLdm6/WOD4+zHHc8cptixPj/xiAiiglUUUFFJLxj2Hzk4Nzn305yJ9q2hi7ol7FqM1+U3J1Asb+5YU8GzA+P1G1eD1MEH0/ePZ8fqeI/uJZ8PqQuDsI6u/J6G48noX1Pk0Mibh/USJ0D9JKp+foeEb2ObdivuiQEfSHXZk5JIcn/CBDzQje59BKM1s7Z/IIob8b9lCIMscDSowNEHjfQESFRTttQ/uxm7lRuhC9hsC246TZf0QiSUzovc8TPEzo/XReJmTX1NuA6LCep4meJniZ4mZhfUYDS6LjSTcy9h9Czl2wIaRLK3Gwqs7DDshvrcCB/hKSufyfcL6/kclaXVbkZqnQPnMe4iRvhZwyn6CoT7D6PtQ7FlSPYoX0LOOrHZUhN2LFKxj2sTxuSyBoEVUTu5QmauI0Lz2GLnbj7ECBAgQIEBbVE5LEcSpGKcK+rPckcUIblhiAmglYtY4O4ZFcmWZK9bvkQP8JSVz+RmqUby6+6jsOxKxggBqhZJAyW4h9xyzVp5ZX1ZGswyTSOUjkFYm8pYwKibkMjv0ZAG9zR2g2zKHyvQeCTmMsQ3IECBAgQIf6Y7C5kdKTeRKwLmVZZDli3GxpsJ3OsyAt5s4myG7Z1mQFuNj2GyBAa7aXwF83aRxnMUySB6jMBs8kfxSWg1caAwYxp0rmZ7tfb7Fa/rfoOOvbf7H/xP2OP2P2LJ/UvuQ3JZn9UaPyRoYPY9wy3uHWFwCN1NPloqisSz2fUXIpiRarJLQk63GiiO47R6pw0ae1pqFshSWASPk/Q2Hg9DCeR0Ece/+gy+6/QgIGie7A6jgXms4VN9oJtenfqHqd8sqVKlSpUqVKlSrvbSZKvzN+VSpUqVKlSpUu0HE8OeEOUIcX9Iw9wEnQfT9B4r+BFXgdBn9eX6Lvzo9kc1+iUeB6aemQn4D9jNeD0Gfgexs/E6HD7D9H8Z+jj9xfo/cf6GSV2BDwTV/wC8qVKlSkCEEEaRqdZH1psQvUlVJuiFokxM9hOGpehGlaEHm1PrI0mwkRTCfAm0N8BsoSwluygkDbZIWmOtsNNhxV+U0xzLMR3bjShs9cLuzreho3DQ4MkN51RKh6CQVRChlel/IoFDaJMfAeR31oEjkG0L5G74BjGP7MpDoncLJPBTT7nPvzgV4WUnyXTupcloGMUaEoyUCZkMUOCSZ9QccHSJutQAC5mNbj24w8jIyX0Bf+BBHwRphS1Qyjngoy37j0QQ2ShMFHcRydjcISthKWBCUQ6EyTYTRQ1+ufVDcGyCRvhAZE0dQxkj6r5H0pBCUtMSIyLTKe4qQ9SG5IrLHUUMeg2Ix0zJMado9g3Q72LQOWXwIY6FLRiW1jfhvYazAZy0jlPJkTVvT4HckKw1Po+Qq48oNkTNPH5BRUn1IbaFFAZjYipiMsvkuJGlAVUzLsYsgpbwbmCuismifR9jNI7sVh93P3F6c1SNVdi31m6tQqf7o0QRpGsEN6GLFmSjfVvsSSWLskuqipJwPMlOxA0PZA9SAx24TuhC1FR+5E5CYlWOvgA9Ew2mQg0gT7kYgaIGJ7iCXCRGjEWRRaF17DFfUwZAnEDsmLWPIuq0CrazIFeilAkySicdn6jN0FuFYUdyC2rkhFKXR9iY74Itxg8uMNTwO47AljJgdiRc8IWQrvSgcvpkEChgNMQkjGPhYDFvQGUOHZE8TexIrChk4b3GBPJIVzt/kXVAJyEFkSOBJcaBNawe53AnPMGpr46QbCBEXl2N5uo3QLAcGIVjSLEGCv8A4d9B6jjKGKCsOIeR5X0GxmicCwmZW0RLuE+g5pRqQhixsBXo4IkYRxIgPXtz+CRNezUuXG6a+jPdl3aDNRHYimz1IpMZDpsahupdAlrhlA1sZEak2mTAXIvQy8fxIVEt5ojMjdxIR+pkEpFEtCC4HUWS8GHsS+kLyZETZoBU9cWPmIVtw7n2APWJBQ7yULiNK1PI7nBAF/ckBPZcEZn0iRA7uHOcN1oyE3DUiFNAGSJq18GIQgfQaSRtiHUTHFBpWD4LB2bEWH0yUFHyE7MYuzaBzyGkwdwdTD3DtjTyyMYQWBegysZ1RxRUt0Zv9AFuhYYpYCCBUMQYSMf+7jMdwM2knRr4BijAZkDwrHb8Jsr3IAIKLAW4+AN4smQZeqEBHCqojlw18BNmhhooMG+s/GAsGG084m9Q9Cbpbpf1EI7QETcGL68wSYogslIjXdG4cBkJ9Q5lWaFDuLMPPwggidckVjA0Bjew1lFiTgoaBHBSaJz+UVFnAMaGd3ypzHqGNpo4CCNU9T96Q+qnB2UjUNp8TuOW5LbMCMTszIMr3LDB1JHHHCycIDEDIsUNt7hWd7qkQTMcJDVhYSGxwhbmUuRRsfQZuFsMvSeC8jdzYQNXxUbhaGDKIdFDZMITrPpQPbkYxRbb1keZoDby8BpBZjrqBpdvqCZSGCjAhgQBQMP91REqTKQ1iCCCCSDKGorCUAJSCJL9gTdFETfktJGDAD6pDKTMMJJ0spFTL4QHbWjfdfHWwf4BpF6nQ2RI+m+kmL5IojUWEkUxDylieQJcu4iSAhTBW0Y8UVLDFDUvLchoFs0YyMkozoKfAQa3wgTRbIROWT1CkUh68H1NxyICpIWxmPbLsQFICQFuB6PM7mFDqLZIDJ0JI9KovSBR9x2aYh9BycCfArVl15Ip9DrgjJIowN5EZ+CFKS3JFvRIM2OwmLHRkmGTblFBVJ7Nl1S6MqBAMpXffCNDFy8Z0CQbi8hLgdAymNNhWcSSe5IZ7ElmSRlqFwiD1fQRdNlbKIDBkB3T7YsuhtCZZAEIhFBQv9w7gU1qumV8IP8AuDMmEgroj0JqWCQU5qDMJ7ojFLsMIjLAJNR77BuNGEEGZFGmp5eLm/wVN8gCRK5m3Klj5iD6j4o3WxuBuIwNAkwQ6gZib4ZIkTpb10GEJlv2CVDVLGpGDqGmZJXqP6lmb4EMB1ijD91IEOUKGMlghuB2ahsSajJkqYkTHUK0txQuw5OQkejwO42yEpg3dl/h9DmCED4YsIUwWkboY6UDgJF7g1CSC5LYmTgpg2S4Vit5+JnIkulQn0N4pREIbYxi42WyFhxSlt5b+FZHhrfRZqLAGNHQ6iYcFknCERLtGwynkmlSDD1g27GfbSboQHTYIPbhjAuQbrBwMuQ4YjMCR/7GPkYkMGPgNLbSWTlVBiNoE0yGH1oCSCcORrCo+AXm0UCSbLNO3i6szZihrsbwUNJniOSD4Nw5YTiSIEpek/JNFN30/aUSb6IPJDqhmkFBCeWDcKRxVzVkXBPrC+JyZoxZXod1kKV7o9hZOSGwhvBZmHuACkGdCZKBgQ2niCXQulA2vXUD5Za1Q+7UGIyxMpSbJdGQXmI6kRsJaCRxxBZrQ1zbhVncLoHcRoEHo8nucADjAi3BP+HCzDVcMMXBiQd6SKGhzmx+3WNJkpbekjtS+pcffpzwJMGIxkScjZQIiQJKBCe+1MQtWiyJb6NySAPKRMwfFDgkDnI4InF6IqITJIgTVCMjiKKREIrjfb2KGNA2OYQGKBGkWoqaZA/1tGNhME3YZ2HRuA7ccyKg7oJq6Flk2bkIp2KVnu5khFAbGiBCCuyHNwog8MowFM4GIJKGctO3hg0WPMNzEfLUGLqg4zR9Y7D9TN4jhJb/AFEmYFZQO0stYZO6Ob0L9nM397DLGwwxl1G0WJTbgRVMHkYh2xHJRUR9XUsKnWmhygKR6Mjv94WczpSQYUTySm7Q2wm/RM2IiVZdFjIfBsIBBxw0daiGcCNXbFKGkPMcjQjrGHGsdlaQtA/l6lADliGSCIlH9CJik7oV6lf1GZsZ+o0oqbMVPPKWFWoQ5UyyIDhIYMAQIajAVxT+5E0j9IjhzohuzNozDsbR0T8Z0QgIDG6KQVSZzHAVCAwAyZyU5fCuBVXLcltICfq1Qshgtn4ADEQIWIgQ3BKoZE/1dETujcLXKT2EvYhIXFDATlbFCPeQJaoiirsSNlxOC9lQ7C0SUkuFobA1MOFhYwaRxaVYi5/ABU5XMuJT1WEMoRjRwhut0JZ0WXiwIwOol4tnGupLWhLZ9BciQ2U3cppkg7F1HiNI/ZwPcEkttKyY0WXCX6hNszGY6Mk3IfgZ0D5B4GA4S4EX3OIQG5LJJhJLROhfK4yUyR3Q9BvdDoKZU9H8EPVSKBaDxe51DqacuWICcmVsiJQn6CLDOurGE2DJ52ImI7kUoKMiQi7PQyFRIpqSOBepQ3LIyklJliZLcsEE8PUZ4EiQ4bgTuIFhtkm5vbuMkXSGuSdUPxUZVGabe4yGWqQqIsCtLeC686QFxYtZwJaPUEO/+rGiFiSBGkirWBVSeBCcARmOrZZOOYOiE0J7kAUNCgXyCZA23IGw4QYQ2A2hGGMNKnrTQyVUxAjhaqTyY5Y7xyhtVtbS0NWHBuEcj7T8Pkt2PLcaEpeSIRQzyOSgyJJKktT4WEKjxBtkVEAMNE8jhkcaTw4vijeCyOzKFOYcwMga32wSSmpGNfVlrMFh1Fo5FMYbp4JWSihuXzqI+kWswsefPuOITrnUHlFiSNJGm0klGPhG4h8REqSEJo0YYZSTKwaF/AD60ioOWxAsg3NvgLEXh3NiS3+EJDbtKxZRRuBdKkcUi49RiQR7ocpUNm5wn2DuJFS2BYOMaqhQLPgAbqcD/wBLEIQLQzeiMuSSeBGzwII9A5K9DcYsEp9z6uMQ7ORiSAg8jGY+p4ZJyUbMgRnp0GBoeghCYQtGB1rsqGiIheG5Cm5kehxXs+FWPA+hOo4kG6yBLTnG0Q7VmDwNjpgbQRuiDbPEMEfqIsHyoy2UQrcdCWcL0HLfB8IvR0khCVagLgCrJSqmVC7RJ7X1DHASo/RkLUn5WZI4ILuM2oIy3FS0wPJ764MORx3EpleokpTucsQXMERLveRKm0kTXYqEylZH9xKlThnABqDDU3biRQ/eyCExsYlYpjhclzWibUMJ4ep6g+QBd+VqYQsnViU9QPZFKd2gkzcRDIEQVlJDg0JPwfWERbf6VGelYvXpcHl8DIlFLX4QlKVa5ERrYYq7DcDVN8N2Jbk7o7EODgcKmFmhIFvehcaMdaI4FXIUwNCwRNPgXjKVsxzOgcJIGoQOj4xF5NilwUTXA6pBk5GwFpP0pI4irpUrYYlRszkviepuTTDrm9Cs5y2jo+Aeh2uhdFIiFWjOw1BQYQtBMkfgCdo0ktUoDbl9RBVj2duSWa2skVJIcSzuYmKt9BVOYGTXroh0bFElIOhOkU7QmSNODKMzqiQinIiH3LJjdHBZYdRGXKOZHYj8FoBxoKDn4AvF7kp9wKTAP1ZfBuAEQ/RGL5Bl6DJ94ohsSkdCEtkAF5/2ZISUqFBCi1DDgSsk1FhxJEElKWQURH6K0FQ0ZJaGDzySxxIm4SqbjkmJSrhkhDmIiSKdp+p0R0R0R0QndWTOZYKngXASCGURUYRjKFCW2ElUhZiQyikVirJJqT7iVaCZN4in++hRBqV8twirS43/AIMidcNnmUSTbmkP4fWaJhVBxSgvrMjsyey+p1ePrBgdvYnas+0VcxuPRjWa5IS6x7o7yVEQlKI6lgqC3GdoSjB0UMI8KFo0mIYyKq4OBiRvMG6EYbIYYdDAYQHIIINkhEhclIZENZqSuKZ2pW5yQPIislzrj7CwyXdj3nYrKnUpRnRudywQAFElEL5K2souY1hNYQ4ivUwLTCXP2R6ED4yqTr/4EpfNXohb+mTk6aODSZ40YAQDxpnRBA71SYRh+CHCF6Bj1GdVp3ECzA/bQyDOSUKZmhzfR3LMJP8AVXTM9SSK6hmBXVL+6CBBo3LhDosRAmZBdSLn7AzjFRNrduUbfAqOh1fQDgL6OUHTe7dT1aGcEJECnFqJTbzWGMktpxY+0xfMm5fv9v5nI3EawUO1XQo3FYRYM/ofFJKLwe5KmGxluEKnHyeegkb6aIlS8hbj1Q4g74MDvxBHNt9PQHYf8jmwiN0y4CZnOEUXnZOXqHiwL8yYeJxO4tDLzm/EMuLMOVnLf3JFhLmESFs3nL0Ca4gbJ2ZtpfrLyQEiWZRgsII9k9+Dm0MUi9W4nTwMsuA1R32C2MADgLE3PUpkdhJGLzyZAZeWOkE/VWy/BYOJI8bi7YlKkP0bbTsixGRNGZDueh9RtpKcg89xn6GxsoUWoUE32CSeSMFQ8pS5ZZZZrhIqbtuEZGF5wppk30ZfsMJxMLiKa7e4KpT1mQ0ZqJqGT5Nht0hmTypEmMi7OGO3SRR4VEvu2kq9Rn1DSZhDFRSgNxDdrINGjQRw/wBP8IWF7bMD7D/Zkvaf7Gd+0zDewz+MfxWfxWfz2N528B/s/mB/E/Y/ifsS58jqZb2v2P57/YlyXtv9nJ7H7FgSfCYylwTJ3uhBHjDcwx7MjsOKgB+xPUtiwg1jF+q04iJbE5NE/HGqDHDpDE2sEYS8D6tAS6Hx6EmwXQi+5AHQC6EEmwHQA6AXSAskCQl3/ScXj9Bs8f6Cr5d7I/msw3sP9jA07prieyCCmfwtEhkeEWz4UxMgRvofwCzvD2Y8qJZ0kR7Bu2Q2bI7B2YGyvGMX4PU8F/J4j+SjIYo4rufyT+CcJHA4Uw45GCeJJJ4VIwXsH8E/gH8U/kn8E/gn8kyDV2MF7L/ZB+t/sX/Nf7E7adySf7PuJTMF7f7GD77P9krnuSf7InKQ/X9iYz+/7DyH8mG8HqVRjNHNd2SHV1QyKHsiRIkT6EifQkSJE+hMl0JDM0jY6lNkmVYmN45RAR7fsMgn0ZhPZZgPaf7Fgey/2JWPaf7IX+N/sWWvDn/Vd/Dn8OehSIMUJ9C2Huhk/hH6Bk365ufbn8Of8vP+Fn/FDe+20k/4Gf8AGz+fMt7E/wCAn/JTh9iLq9uMU9oSfpEjbmgJwnfkYD2ZN/HNl7U2Kwnj2iM4exwnsblPY/4oav1CG/YE0K9BVgOMQWz6CdVvoTSRS6DQJSdUfxT+Yfrk/in/AA436sY/SfyT+CQlJvL4MIxsNAGQRma+0bx3pocg2UZ3ERLvQM/pjDi3tMJ7Yl17EzHsBhX7E/mT+JP4k/4GZh90+DphhexOKXzhhGMYznGM4xlo4y2vgxjGUhso/Sfw5/Ln8Ofw4v8AjyWi2BBxlsOMnHP0I/tmbx/ZB9iEM4Z/GP5x/GP5x/MKwi9NCHlHDex/wx/wQv8AlC/5J/AIH4jYp7DTj6EOCIhcEf7LBIQMoGJeqoIRkRGhs1I6NQWkKBo3w12+HSvL7FUxPgI2C/BC1JsNkiHkgucwgumMyrLAL6EB6BsjR+5QL5iAVAkQTsbNbrPIx6KKqldxEvuQqU4CEkg47jZI4HRvooIkaF6+X1+SjXv8UcaraTHquBEzsoSU5XQWgU996CNSBKkfJYbJqy0j/TIiTKWZG3CSqEYfQkWsaUys0we3xFUJ8X7ho1icBMJppHhzpKB9ehNsaCZOfgGpPLsQfCP1hiaoEskkSigKZECChTKFAihDNZ9iwSbAz2JPIpfANBG+QgW0Sae0Zci4m9NggKhVgoAgzMbIRSPCOvQUrHY7D4Y1B2LUTQENr5fX4EfC8aRpGr+BfAHo9EXdRocXIhbMCxQuhEhAw0dFnt2CtT0M76+SWA0Vq6aMzGxjXyLk/tc/b5pgwYMGDC+KInpMCDQLIOQkZiicoNiTB9DkQQ0tgxT69Ar+1BBKbBBGm7P0IFlQu4TWRJMDpDCHj9zyPQWmNFTIQCXpLQwPBEnsyLVY11oIIeRDWhMel1BcKJQI3E6DQWiQRpjqc6hTGpIY+ZUSciLiUi9ukVhttqeCQ8qRXHJcBhQYzkLRNAnhr5fX5BaLBjA+uj0aF8DTrY9U2EcxpUyCFS0hWfHoggbAJ1Ug3AlWyMT2s2BJj5GBy/ypL4ntqIKARsSKGJiQZjBSlig7zDZRA2nQoYYI+gmqPYEo4dh+5OAgWmmQy1Ph9zx+w9Mzo4D6ABjGEip6CECH3iDIYBoNhNNSIFkygaSKEmgN2h6IaSsPiIeq+S5WA2MlwlvLBIAnJES7ImSyQYYz3yMlIg5Nw76lm2BFFiZII18vqF8L+La9JJgb+KLV6p96JjlMZU8ALxJhBG44G9B6MQskIw3i2OiikmydIgiBrg56Kw/hIF/kCXxNegnQQJEGQEd0MvDM4mQoJrYgIjeHg6HlFaFpTsEHZYoNZQEGGmUQmEr0vD7nh+mhbUpYuTAJOdCa96UIob4lDPULDAklcFRW4nKIwXUO8t/IY9xiBUu5KnoI8E29x6FoqApjefCRjDmb1JzOhDWDlkCIk5HmGWWImYIKhTNwkFESihlkSfYEvdv8GkthJWQBjQvTy+vwMCH8Eaq5R3MeW/Umc/FibaPAx6hO/WpG5T6C3QWMTkdoZC+1pMjvCFimjESeFGGFtNmQsENghT3A4OXoJcsndEPRm2iEIJfPJkCokRBFMjZT76r4lsbRkhyz0BASnDJQUQGKYRCoy5Etj35nJfbRikSkmUUm22wuFPp+yL+RughEDVogKIG9ioPL7nh9hs6CC2TucQwYx34EkjWGUDcjkLC2qEewuIzBkRQ4WjYwc5MZSh0O0g9FgnowsQrFwnYbWHow1BAoaQv6hjpHY5SoOo2by0xIRCDHlPbvgn4PlsowNBNxK7AiBSMqlp+4tMh5EIiCK08vroeka7G4htFN0CeRXVmbW7iw3qCJFek6McI0wEPQpU0b5IX/AABbvsi3/bF/wymgdtHpFcEEazIaMqQerjYcIyslwncMBpFUXTfJCuj8K1Yb5JbG2171sNNOHXw+gbL7Oh5TjVfGkEGRhNRslvoBjkmSJGYEiJSZ9AtzmnAwiuicAjvrEPcSkFGCKFiJVE5FACpaIVyHH5yQeXbSuJCMoaD/AGDcV3+AyoskJmpFr9SJF7syKqacBsIjNv8AK5RiNtyiIQsGfX4AWAyaGsSu/gCP4A+goOwwMjfqEBpOiQzKQD60IRZjCXzEaJbI6FAXSCHxmiFwymIU2zyFAwoNPL6hayTfwSMvqBTakiCUhiSTHsFgT8K8FD0ejg+4MviLAuJEcFzYkAjsw8EGGEk3BXJJNOQ8epEvcdUXxD0J4pbDo8/iTqF8kXkOD9yy/fwsZ7xETKvQW2q+KdRpCfq0FIltXKRLYmtG/wB5Yij3BDmkmdZgS6QQi671oLBZBlqDwFlkljofkKg8h4vYu0iKMj3NyQaaSRfFAZB0NxifGiz1mJ+6Zui1eqyYJGPVI0lHBoIARB70hL8KhSOchITpJtil8QB9JbMDFHAY2CgRq3b6McpS9RkJ3ZhAfUDtMhSxJaGxY2xQMsHCaS4Qj6XUKLBQbZp1MzaUY/LBWpAk6eX1Csn4H8DrIyBaICaezJw6AYXIjVixYZ0EnckaJidHobGkUYA4lZdaiZA2aeMTOJHXNKVo3FmEBoZB9KN8GwIISwybIg5LDWDNJCdrka9Bn0GjHrJT5UmgxkWXQ5SXstuz4mSEu+q+RoSdgR6MmmCzGPD4caJoJoCJnC43KI2oZxEdboWhiMQnKOgmLChe0HZUOoGOEKaU2QQsowhmkN3lnifBebjNwbFCjA3g7BHQEDFdHOqPemOxIgsiLksve4gJ2WQD/QmQwldsDWtTFJ2UM3RBgyb6ZEGuSMMNGowISr6gYF70JI0oVBZkblMX9EDGMbcsqmZRnISnAhW0QQTYorjlATQIBnl9RIyZJgknXBsHQx08jtXE6bZMaR1WSEgLj4GyasbVW4TNPezjZIjE+onomguTEifYgGizeCVIiCSxwXblraE49gWNv6kfiWMogJuhyBJq5tDELNH0XyF8kpAedv4oX8oYxLTpS/nQpYZzovkKGQETBMKJAqyUwrg0E0SLFI+2NGZQlCheSTa0SHFCQYCUMoTSMnRlpJjusehhSFOgVAMR6WIrD3aoJ2onrm5CMiCVV2IWECiFsTQvQWblliEg2N0stit9hOO9SSFLLZTDhVWcIRWpK/Qa25jDL1D+AjR8ImAsn30KRS6GzTYZLsFEmtBEDGi2kCkdkkjcWrMEOBTDcQZ6NKGdS2gVR5fXQ9Xo9DKMJAswxElIdD5SgstUNpVnRlO9q+upzPYUjCFqDT3JUpO5CPSfJ2buTbpDdEl3EWnCSEYLYOGU+y+dpnMDo1UMZVFdx7pcSIsQXhJQhKbXUXwP5hPtDfUbhysqokP5qXm1t9V8KN1iOpJDBQ61tpx1IymJhhv76L5GtdjWHUkAJSMZsqZvMUWPOQyDgaEJgGAC8aQYuJUlelcYmMs6ws5FErLSMyslIkM66FVMY9BEKg76MwcACOERzwcCUSV8BJkNyMx+UQjdLkhRobsBAJaEIwSdSSS7JB0/IaLdipXS2GJdqYt+BGWoTUh8LGMjA30MZGAx2LpoE0egJIR+cCHVPcGoOcHLQRSlYS8aUEQT0lhN+ZaDRD1lI8m2jEiwTJUNghzRsT6MQxHDuXWCR0iWJXoxtFlM6MzqL3JvQIKczkLHBIuoXIvCycDPqIkXjDJKR6soWCJJl6mFb5EKBDDiNnYzrYZgoWVRkERLBJCKn9BgPcQSVfbR6pGT8ksTYcRaz/RloMJ9xL+e93QI3Aq67sHKO9RCVX2Ju7exnDRIFM2+YCiS5wREbQ5Ii5J3K4L28FoQtLtlIq3sBCVg7AQLD6qEAsBh/gckOaSyza93Nx7hmvdJu6kVz3oGe6uSDMB3YrIB1Mzkk2PLTFcZU0Ms1BAuUYVUQig9RbagyGREGEPekiCKaJFNOmhCXr/v0pZOkkGW4PWlNqTY++Mqm+p03uI5R6in7zf++LfQY6Cw0vUQnZuRgP3CIhIXLPtHeQEAUvZWJJJx36ieoMYkhdkWPn/FFTQhye+f3z+2f2z+2f2z/qT+uf1R2dRSDTQrMeozsCJojnRJS86pjIvgh6faC1ZxY6JO5Y3U7n0JZ7kohD73qJKJG3UE2bLshqZOiRVRHGHFCyfcgE5SQ0UPVB9BG51o18BAf8BjJQzeIT+K5bqFH3P4P7H8H9j+D+x/B/Y/g/sfwf2+a6Clc4e76DBuuA1ld8FGYUWzx7kFRc61spl/RmUxdrxwJKY5mVS9h2IznWtpGfYaZWDrdKX7IlKeShkePfYRgrnGwzILQxsSS4huJaCYqI5qBoSy2kIngC0kkZm1RtgSzDeQZoxszgfeZMFgmJ/QqZ0gkgQ5PBypQj7CiuTBcJJQnNC4YkYCcnmoTByQNVyKExjAuCN9AVEhNIIz3GIBIt+5MY7Zs0AXi4RTa8gqFiUkSEMiEX7oHXfB9VJVHWBwSIpWTCNvWCN+yWnqInFp0SQU80tyI+kkgn0Awqdq7TKJpDsmCygzI+5vGGQxeUbLh12JN5fBwt4JFlUqpwmSrIA2b+xOVvPY/AsG65ZxIrZNLRJbEgunNEcZ+zMdyeXuhiwG3uwyCfsmPA4CwTPpBEa7bO6JueuljQDI4up2EQw0o3uHdlbvpJe/QTLF0RNwOJbBLaZj7jcpJQZnHvDKJEhZUx9xynOca9VdBmDHBltJR6G2lkixjA0qy2q3iiVIzFNIW5Svcy1MZmZFkmMOrklNwIZVOAwKeQyLSRTqO+v2wxURlMbxwMiCb4UkEAZ7WexfEdIRMT7jWerMOTGGY3ShqU9gfWBGIuEQR5stVCAJIIYLPU2iK1oF7hQStSiaKG/0tJ2JNNhbUNPL+gbkqDKAsoow2VQmUUm0K3KU5/6KvEjNLPKcSo2jcSqgagSBJQl3DFeBJJSlWXh+7ENhKk28S2d7okStVBrhdotU7pV7n3bJJXCTf3D2EU0NdwMRM9wYJcrRENVdBlgnuL8p9CZpZwgipmEwIrg+GV94cOMlhCpIVRdQLkQSm3aVI2UyKr0umZSOTyu/LlMerA1MajqEWzEJdW41xUip1xHTyxjJtO/ujAoDWFi90I5BI6DNSRGqVrewxCMhkabUhzVERcdCJIZEIgQH6iRptVyPqjHfcTBBU6aG6Hi8noeBIev1Ue0njN5e6wNI3YgDlZribmshlZm4puiTmX4Ygqhojfk5dOfy0cfIdQaVKza7pdCDfRfBpqRx7xygYWbN0slA+mipipGPPkLdbTkZRH1CNSzKRTCcJdDNst4oIyjyRg9xBs8rB2mSwjWz2lJZrO5FzzM7n8xIU9vWZJqnGXREhxcaHg8r6L68m6HUJMxJ1JxsJni5AaBoY0PYTMuxuMlKtkFbPLN+CtGXyfAnu7lIEQqR9zuOJGT8hgOkaOAjO2S3SdhqkOWnxgTtqdESaLbi5x4iCMvFH2l7427iTDvDUtXF03wOYh10U2h1t9zicrCVNqL3uhLKtgggm08WneREOitZUOopqHsbqzcGSqB3Oi5AQDTbgyBIsHx0KhMhO9CFG5I4aH2wsSKbncSBmowjaUkIt1osmBLWtWsXLZRfHqSeWTTb1op4sNemUQJCKGg9ixVB75wj6wRmxsDLLZpk1oim7LSZCAu4h+lKWi31RE3tta7DR/q/6B3vc8jI5vc8pPKTwkjwyQVBN6jqh1mEUJDxn+6AEWFHqOo8dzg3ZmB3Yt5K7McPuyX9ssA3LZJmXqcC+4lYrszYPsVPV2ZZ6+9V3Z5f+dM3B4fU8T/J5H+SWR/I3OULt/Y9z6f7Pr4L+zqfb+zxA+pVT+39i2PY/s/lv2eZPufViX9jzpLqawI/Hub6b6/vKAtkfsJNva/Z0fa/ZtLcn8kvhfU8y/J5l+SzZ6kkSR5GdTe53ffUIs9ksepw+f1OqVB/Jyr7BbH0DDwcPldT/ir+x7j+39jdl2uz9nJTsIUmYneiuD3hbY+Ba7tN/QCY5veHVpryLCX2fs408up0Xl1MgpeW56KQjHuw9JxkZgMyvQZE+HJxp5dR7vm7j308Op4B+TiXw6mwh2T9nJ9H9nm/YeFP2c30BYUF0QgCLl0ODerP7Yl/3ZL/ALMUnuzE3xgAHyQW35vUwnl9Twv8j8B+4tjx+p5T+TdO7/tPBPycPmdTwz8nhn5EWmUDWSnbQksKDu+/+0qZBnUQQXwJJOjWCw0H2G50M3GCxt/BloRufc+ACJmHVj0VNCZT0H8EG0IIXwCmDmFD5gxWdETruWUBHvaWBm9E7E2zsHrciBw+SC6EXsRROSWYfvRTlPKSMayfcyXjZskjwRo+lLI+WRDudh6HQPeTcfQVDcCyGbjPtfKFSXC6G0KrCNwaaIbY0ILSdhQeH4/+BDC9GbxbOX2iNzexfUsknUshDgMq1g4RqUlQzcVDiy4BI4WvgCFoWn3PgA53FCxn6XWZ67BB4PEHURIZJpzG+ICdJP6cXRes/ptHL+gImZiTuNZFrVhKOiW4gjbNgp7p+nyRDD8YNge8sSJrgaGKdAQMgruzYSfSzhf6DJbqnyQvgipL4JSZyTCIyBVV8AihwYHrhJZpEckVKcjoothODoySt9iGxwNgzoFayNLuxL0b6fa+UEEGKyWNakcOCBfAUjuNEWMzT8X/AMBfZBPNE8UdXp9n9J4UeZHJHsdNvQlu30GSFrojIUlsJtMDeKYV1UiYJdEbudSwIYP3Xw5aMa62gQdQT9hmIHoKEZ9YMYhh+Mg/ecHviOTOX/RP+qLGBIgSbo9RSckG9vDJICJPb7BacO80tFmXPGnll4FHyScfGB9OJgWhAZRTBboZN3qLdF1YkK3UhtIn0Wv9P+SCLATSvZA6VygOBOdOFqiG5tC4gEDu0cCQ3ZNFn1+whubwpDyPY1ddG8kIkLoEErmxHGo+x8kgTSVK7kUMnJOV0YvgBPUNhpM1fp/+BC0Wq1gjSgSPeGZOQhUU4GMNSMzMklDoC+HGpMJFbFb666fe+CHRP3hA7EzZOD7DhZAGhbXLQhjT4KIhGNw0ZCUp9hqVAlKBnUsmT6D8kiOwkUILqIbRm6vasl5zVoVOybQXyRrp4wUPvSx6HuABgA3QRvenfcaGxMTR9J+SGxtWfcYKPifBVB6mVTFTUhyjbc+g4/UNxBNkTGPMbCB19MP1BGoSN42t8jZYgymFuv1LJhLA/wC029kQa9CWino+WGP0u43BJHNDo6gG8lBTE9j2YihaA8jApU8+P/BwPRItELRoUvHfSYiEiCmZLcQuoA+RgYOCtIk5AQLZ3Tp/A0q6+DSWN9zpFFLYH2NiJZdTkoA3Dv4IdCP9BumyctwyBG6TGfQf1CB8CRIhim51hyRm62AifcQUoEUCKBNCxkOPVBCvYZHcS+SeE9tLICZZDR2MZ1MJBxphEnsLJvwUN20k3afb5I6lDFBLdk0SsjiMMBBv1Q6Igxg21DDw2+koj9ghVHWRiRuqETIRyT0pWJKuMxsVgfXRsGH4EOtSMN1B6lRc4z9BVXg0P9PyhVCmaN+1Q8BQsVZQ+hvNzslA5Jw3IxVjN5i/QWGYU/8AgmB9KPqbhG5pF0H9TN49TIUCTlMkNOU7mTopLlSkgrwg+whvRMMhMp556ASCJ7j5DAxHuIAt9VGE08MDkZtW0Q10buBMcEEPHUljJtODKE7kQRyIiyy4hM7EgAkiOxm4AkUOwDx7uDoCTMk9EttJolT5KCQzYzNbbjIegyVCXC8D0YWI5DBcrkElc9TXYiD0nr8k8A40qg9BDEo+vXY9hsYWhBhFJtMBs4nc7sUH4nqbST7CZzV44fySy4I+M6olkkDtH2IWHdlcMigYwkjJrYKQ2iEMh1WRLJT3McD1BkCJfYkd6CKc/cHbRJRsrYp4GI+gOz2IDYkq0gFt1MsdX9DrRSXyg4zuOliu/HykZhXoBoi7nIoeguUTOyzIG47fUSE9P/BwQoTGBjIj3BnNieDAcaZIxIhh2ga65BLSlAsEeyW57gso0DKRWoDtiZRBQoktaMTQkEkgwPwkFGiKA1AqHHYS5KDkTOt3IcdNbmQTDlFLJMXskJ2riUXwyor0/Mhox8wYc1K1RGCeA5FsbIgkiwgLLtpYANlclVu+ScjAvQTGWCEMu5QUbCekgJglSOQRmatEEhqNZC2I9IrhfoEPsUEUIlnR/JEZcME2UGCJXzaMBB2EC+wTwdzUPc2ii0VwLk3UHcynqMwFioRkPohpTKiRCuLQ2mo6CJ76FKzBKHcoRUq5sbxGNi4iqkVTv8oItoQut2NQRLCMnGTe97jAAHZAbsQLsPp//BwY0BPM9SV4OogXuUnee30Yian9kPWlO0hFpTxdesNCER50HGZWIHTQTTDUiCWl4FRSWChBSlRPYXZGKYOofzhflwUakhSzxQqttM+qEJuEGmlhTuMCEZYLoSQJDGAyK5XvuhgzCIVCJcLWJN2f9KNz7o5vdH9h+z+3/ZBr3/7IItZmT+CyCl4TW42BMtwbFlbXMdhhb3ESHBfi+xBULqjIZCwSi7WPkiJkTukdCrKUIPBeCViq3Ht/TvJKgupjryrliQgkOSmRfZ0yAaDAV8kohJsWOMWaMlNDI2XoiBGTGyCuTdk+EZCqkFPfSxFerGY9BJ1D0AxNuow2MdWo7i0dBSFI6TZtpTdLYXAq2KbPlA0HMPyDrCBIzNNOQrZxHcoIfIyrc/8AwywQTpiEXCIRXuJbG1CZTEGJIShG0kFipWRTKIKQ29oXI0waUsElKKSMhrRAVtqxQenRMk5sECC2FL1MDaIWSBM5sPSHgISW7mai3N1BOEjrMcwlO5/BGxL2QIDUPkhm1C2wmQGtDaEDyTLk1l6C+51xIs0JyHs0I24ZI2SM5NhghK4RErrehACDWbEALboU5bcwyhOPkjXVXkjJJKFDX2yNlVLA+83TZcyNigl7EtDZhViAxrkYTJ2NwgUpZbr5IzuEmFykWdNTFFoyCCIrdgWJeZRAWnRaaSjgdbEL7sulgw5sxtLPPLqlpm9DXs0ISiaGzwVkRpCoLK5QIwko/wCLgP5RgvvSSZORQmmh8pDJ7YBm0HvwKoxARsJr/wDBwUZ+o7tT6s6BEbWt2CAXsHYmU9hE8iEOkkjuRWNsxaMQyRG8fEIAIHwaYVHMTuQL8rQ6vlhykvZUu5SiD0EQhI+puF8MnKtiN7FCxWhvqN9fTCk2OiKawFT3MyraEbphwgk7EmzqN0pSdxHU6o8JZqEdoih0foEjSuWJd2ccEX2jBEmUAQldDsZzg+SJgemFgeiGIjYC24E5SyXzYipIpCTOVOaaCC4k0CsUjuYjYGNuoyklm0kna+SbF7ZFngCtwZB1klmCjnctPhMkSktRGyEFVsc3wZVmwgMze5zxjEKS4FJpttBGqF9hqdQwCVRikCQY+1FJLsiYQnwhCNsDENIax9JEAiXL2+SOwR2xhbTvQLBhoZAglkSqDZgg++lciCi2RX1/8HA4uBtDl1ELGIxx3Ft0Qc6baREUkcsxuVAk92tiZcmwEUrTXYkmDBibtEtI0N9IliddoBTU+4pLGww0xWxEjloknT7xcEA4MFELwbA2Qoo7pP1UaGDSXJKckpzpEzTafqHQpyzu4ShubwXl5dCaUhIKPqiDVYKCJZlj9heRZI6eUe58ksAqRbMDBWWo8EfQmja4YTAcffKGLPAHNZwwMoGBlixtNWTz6CHJSvlAKRolZGC6g6DkZmXfYUTRcxNTTwYp3MQQlM3ulKjlII+6jIymp0S4mIhLrU0koi30Uh2QxM50PW0zfcW01sSEQXISQMFIZSE2YhiO09UUSvk4MgOWdJGTgSxMRCNcwiVlpdxyhyzcaC6uM0EM7shRQxzLbE3vPw//AAJ8x0FhjIpRQuTFcnOC9jeNsu5kUQVApbyyjU6nFKRKs7LGofK2CMC4iF9DZVI2UWdRuVkEBglkasF0Uy6OmTr98ly4IdGCAt3R9oMHoQMjpiaBPdkUsCEQIErqJSomIIG1Q+vD3FK0EW3qckwanR3hDa+QZKavckjLo0YRLZHyRTepjLaD3WPTDDJFTxm5boHdJs9BchLfHmNYKwlkhR/oiB3XsSNe0uKECKb8kHygCHyPaGAiO5TyShSCgQqw2EJCiGS1JQkDVOijaNCjfQbBEYRvITAwayRKLRhQ+hECUpBaIj8kDkFyt36FNuRCfL6JrA3cmaFo/fwmpvF0cFYTjf2PIeP/AIElczLWMTgnDYb/AMRE73YLAuCdEqWrRZDakbA5oOJHDDb1FSoeoywBwfdoFW6hsRoXUAqgddBBqoiAMtGEERYJ0v6h4BtuEfhfQkxWTa5EFiYUhwwWyYxhEecC944OdATEMci2iBQvURO7sVJnUJizSJKGhf2dZu7OKaNgikGUeqRRGLIL7fQUJ3fG9u7EpufZYjK6CJb8KN+hBLKKHU3yRWHYKMhKcao3GcfUVCvUh2G0MZKx0+SQT3CSnuYEnMRqo4LpAy3RW14uwnLz9hT8H2LMDdm2+S0T9SFUGLswWOWKgR9TLQ8jHJ3QbWpJnI8JM80Mm0MQ5IFh6FATpJ2B7wMFhbNHed53ned41etuZlC6Mhn3hdR3aMFzoAyc8dCYQ26mvoSChkTpckGb/a/+AzY+D6xEYgK496beYSs7ZnjJBXcy1G3OTMvGgnc2/WZCNMpyinaXqGTG3RALu77uygxCVVEW7pro2TQI2KlS5tYh9y7a6XFhdFU5ETocaXJOQmw9BZFRlpS+wSUpmLNdJ/IgQCdwihwQSkLKhEUFRKWSBeK9G6OFSSS0kF2Ptw1RVKsAUppVA5pwIVSgaZQviJIS3SH1o50hbAqs17AR+ieso3TTOlHBoamcEzJNK0jWNiRGHhKom5uOwXI5oSmum5ma4XcVCNJtBMeqXCSJ5G+pkIuEZAekWbbdTChjZpZ0SYtzI9BkGIwssBDCewNhijdBFr9R8/Q6ePjydyZNKiizhJlRga1tFsSGQPRRIKnDIaf5Qu1g09RJtEemEYMQiXLMV9ZT0G3QU/JHeEThpVyW7EDDVKFL6NGAVoDvFld1GciH0zKEbo3wPi84b3bLttpkhG3C7Si8CACNxxM698eoy7PmsVDaVLtlk7VciBWyuXCnZYhFJ5+WEhuz2HeQFkn6kEV2nEGUQe96OsAdhIJOaeBISJDshiDwIg1erp94gZF/ce4saBjeDVMWXIrFZSWVUtLbcb4V2ZcLxNDpJ9y7WQM28m4b2EFdgIcpOVlJ7/QSDSDHEyXpGQf3dzo2lS4ihRx6HE7L6hCBRnEYrjfhg0yWIlvPQSmGMXGG0zij7RFneJCkSKh9RlHAVGtFi/WT77Ihrhina+pS92RPsyq4CVqsf+BRb5PcuCHXum1ugtnKXlO5NdrRJkVJ+g2PRJLRjHtZIugLZM/oUimKebKn3DP0Kh7Cw5qpOxNVlzig3BLs07f5IRDUk5le0Gy83poTJj68ZzfqJg1Lsf8AIGbHoLK+gUZP6BnD+mh1xlyh6CNWhWNswiGazDVcokHdywNJCU6eeGCjUXd0x2KMzKx3WJEym7gL22GdiVCNauH4KiY2/okyfJJkDY6b3Om9zpvc6b3Om9zpvc6b3PMzcve7pn2CpLcC7MiY94QUJUm5KiW8NmG8psSrAa3piJ3SOt9CBAgQIEBGz6jyuGDJxgmAJYbV/omFIuiEr41MksjYqlQZWXk22bY6oriRSDVnBI02+fAkpxFJ5NyZECBAgQIEBpdCGMSTk+RAXUdfqPhNWCyhhBqoEz5ckE4oPZHsM5RzzYblr7kCNlKd8tR6IhQy2GLEpctbU36jJTrl5yehQNzw8TMEEnSaHhhfREuxrwKM/QR3+gt9vYZx9B5kPrOFoVlsEZ+wofE9jzM+h48/YikvJ6HhA3Q2fmdDEHa6C7k5RRxKkYpwr6s9yRVQhuWGVy9xjd7jpdhh82x9WArudN/ViJFjQHiU+xtkJRLRsmfwhW4m0ktFCfs2UzwxplHKX2HakelxDwIG0pR3jHsRQkoSUXP3siCFr3VEpe23BxdkDDbr6GjXAEiQH3kqPiveCBAgQIECH+nAG8aKS836CqvB6COPf/QwHufof2EM1736CgkPHgkIrJx2VZLc6dysOsvsfbAM9oU9vWUIxNaSpYEVx+T0MEIrKL9COJLYjLe+v0ZL3l+hnPvr9Cbn3l+jg95BC2uLX6IWgJZkErXCUiZNRkiDl1/QLxD7C8h+xkPF6DPk/QWpIFCTwawng9BHxfoeY/g8x/BkPF6GS8noZAVl+Fa67njP40JeE/jQksY1hgTP1T9Zth48GRb2Z7gl2S7m4fJ6aMs54PQZwUnIXg9Dh8noPwH7D8Y+w0fv/Qe17n6CWPc/QTx76/RgvcX6HPKXLJKtLoJUAQ/rr9H9D9D+gv0c/ufof0P0P6H6H9D9D+0H9j9D+5+h/c/Q/ufof0V+j+0v0f0V+j++v0NP7l+hox7y/Q9n3V+j+3+hkvfX6JWB2f6DRtruV+hRtLZr9GRnU9CS7QcTw54QuMyDqPsYj3/0MB7i/RYPeX6Mgr1/QnTXd/oQBld0f0z+mf0xQQpdUOXXgjJadm4UrgSSAJRXi9Ca9ea/R9Ro2NGwpCREiR6kOv8ArR7HocYYOYRfpKB7oOM5JydDKckl0lLeiwFrgTA8Z1WUoXAeEiVk0G4UoqM3cSdlUiSln4gRpCD0ebRhJDVoiWF/8xzoJ2l6m6Jbp7sX4COieg8536kfCEvFMZebZkYMwcokeoxhnqJJLL4GojQbxL1oUDQHaB8lPfMmh9g6PoJXF30BFEv3WNdlK0M0DMYNxxCN0LsSR7mNg3hWsd4rwLAg7Y30ksxG4fAYQQet5FQRoenNoioZJJjkTQQZ0PQSO0l/pk0G05DidjmP4PZSRAxS+CpICRjjIoXwQKzxv4RK49Fg9hXgBKdWjJkloHbKWhVEpjA4FVSttNSdUNB/CAbJRkspiWhBLUEiNDRKTsIWtFoJXYjK0ThNMcmXJnGic3Cx6FggJOyeSJlsokXfRzQ8+grgrgrhfAtIg6ouJnZkEVizR3Mlz1QgbroLReD3HpcIIxGIJZQbNhqOUVYRXl7hWtHS+XgQCGImQvA4HrJzEBdCoQe5awh6FzHUBIEj6G57a2JD/YIw4xkOY9VgFsT2Qd9wN/L0J1RTyJedAtACaCwraFRkeD3JgcmqY0r3RDIPZDZMaKPqQWRBLQKTSmRwAKSQhEloWpI2MgjRC1YusghCCCBjsIkhZW9JDHAbUI8GRRQFLDGkodtNGSSMyEHLIBmDC9QyEeplIc50uTjSCCNRDAYFq4EkYjoZpFKBlhH0KDmjrs/c0E1NvgSFRodBV6OQkPwgywTyNmMbwMLGyGIgK3Y5NeAjFwgq+sCFEfqKLWTMkgyNiwUGRI28hIhEIr/aQsHMjLXNmELVQZHiEaNvDAxiW3wA2WFoKGgmiJ4evwAIepI99DIFiQCZtiAvHA6R1TIoSYlaCYknRPxL5tWGOAEZmiEfANoUkMzSZJZbDcHBt1mwLnTzYakuWRvp+g4NQ2Ib5M/yACUUYKVFEaUEmLqN6nqERMvNAnZaSl1orraej2KLOGjvGOwkrGknqiSyALopLgYecokilGW/ZiY57lWIeAB1DcmAg6MGXbkzWjgKwcH/AIQWcG+AhZFJ6mRahDJJDqgJ5wJmSiBowakvPI9SY0Gh6MBdgs5LvfSHqnKkElCEDOe+s6RI6i/RjLJ1abkUXZ8iuKcsdDmoJVGUlKogT4PjJyeiSSR6m3DYOmhiO+DIsXg0CMC0RAMwPzDGOffSoogvxYiEjULVQQZIFcYxGSGkd2hEaWh1C+oZFDkx3ZiIiSnY0uOjAtk9yjJ3FIZtBLuK0dgC5NBaAjMzaEc4KUKYUBKaEk8yBkkvsdScGYiFJtod9dRQjajo9AGjTkZxCyBERpVGX+4YMuNrhZNEKENAKWUS7iyoEIOZEenCUIeAnS1NQNoeVcng9tV6Hjsm9JBwInuFAQFuIjkWRCen6jHxKP1gCRQ5HBm8JKSF1KUsaO4EQLORqz9hNj9I+qm+4uVMEgK1vhoMMNMs5Jq1MUHbGSDPQqeidgGEdciBw5MmRCpAlkR2cYDYFXUiVW6YldE6JjRsPGQmCNbLEowTWkkRpBGiDfyTQDobk+ymYbJuvUSsBoAdWaOGBC+iE6OXsIZBd18Hw1D7whxUQywNLoNAXFoxfJkMxZGJC01sCeeQZERKC+wqJIQ6s4FciCp6QRxB1ZhgQEMXBBIky/8Arx6Bp0oZmA+yZSZuJm0YDIgWwpKN4mSCw0i4H56BU1aMXKDxe2hB6GBm6gSd8g3FIiBqeTUvcZJ58F/pslEhsfJsCz7ngOdBsN5Q7BBQFVnsqkjg1rKLLBEoUIH30NwA40pTMCEZz3Q5jOhUsJji+NPIwCcLKCgrZzZaUbMCWLIUMjZSOoigJsiGOnJE3cZwy+AzIZUNJf8AFnJ7IuO9pFrhoVTsF0HCpZHDItS+WLS2nGh6tb3is9dqUkBuIagTmz0CwY3K34EsfJMPqSGsfZ7VwVA9QmQyarouzCSYMTKS4imiICWwIQPAGJbMc7HI2FT3JFBkon4UHkkDEC2HxD4iW/8ApqLdEmiRhrMGnmJKcjgLoHrCeyhGi5MaSFNZFNAJAwfC7w+2lx6LMmWI9wSBZ0lu6EB+GIs+7wr4Q1ZQTpL5ZamRw90R45gs6nAypHqbVnqYhgk2rqQbpOyQ+w27rAQx5NgoTKEBOXVmQksLGwXQKko3MZM5SyHKkzkSde2KgpOwqGvWQirL0Njh2MhAhRyCmOwUsruWXgVUFUTX7DNky1cCsnBfFkBwCUFK0EWQrA+0c2idKRue7TGj0NmsTYlrcAsv7LCSTe2ZDAXJiDOzXgJlfECCxVuQZwrvhDD6HobQT69Aeu2jvdBIzIocg8mZkStj7gtJdljH0RWXEiPScmPYKIESWklrwuC+VbipNU5ScaSIMqBwBH+oFWk9IhIxnoPsaSHstC+5JGURYM5NnhAsShQ6I33Is50D/CO8fsYGeqTSJW92SEu+T1EwMV9RDMJNimeXoVhhMIm69SYrz5LHsAthF6M+zEaYwS2bbpSdErEznAkSHfgKQbncESLTwbJGuwxk9blRDEiK40aiw7obImmxaFQdAYi2BZNylkWg9FWYbYEAy5FLI5SpGLdEiAJrhDtr0LkWXCVKmMYP3GCkyMw3UWlAY0rI7baW4WIPX3lrHoEIFMpHuplb+TAL10os6jdjKZ2ByQYrsWc/BGSNmVfuLQTeUMfaL0d91qvhQOAdhVoLhYzMkCDKc7C0ClyJCWEbTgex4MavBcNEiMCTEQeD0GzG7EvTmE3OhB/poLPgC0MMDyMw9hEoVgsnUNpLonQ8kF/wzBv0ohkw70J2IAtMkC+B3n9hDPV2BMySXHJnshmZ+gDCQyJBAyNFmGOlT7ksVz7mIEDkRbqAgGT+xksZfJDEkl70Ro2PIWfN7KF8voB9U39IO599Ahukxpy0ToxFPYRlLyxfAB2S+5CGRuXySqDRRuS6GQCgaZALPoRkUupaF7aiYPI/DoLa5Fan6jkoyT6CqFzsSS0z1jNNIy+rSgegTTkvqACXTbDJUxSlQLa7EmqFTzetkCKMEio/goYcbTtoy1oLeBBMUcXjQ+40Whw8hDAx7Q4GXF10I3cSWdETGTsQIYqihJbhlvTDLdRIRmEzoCLGdA9BAiTbQSxuWFzEEX/q1ggtBiZZoCFQ4QtwIwK5Y4ShsDk0BvDnQI0sqcBvQErbdlOisfA5fH00ZkGIquYhQwrhoGCQZnaUVVpzAV7t0bMD2ZYEumG5AFrFD5opQwlpERRgSTcygYWLcueTgvcwCmCHqdY9XoDCeoWgtQywshCHGgIFBJBAaNqcsQXA0JLOOFiv9FBRjaSspCIQtR9jBFsZkIJ07nQD1imtgdhDrEyiCoL7GAokFCb3OQatVh619EyIFImkkiGd/sh/qEkEQJ9GTslzFQnOC1YdPrpDIosrQGQB/ZEC5pPQhdGUdDcDOQRxrEmT0LASy5DwcvQY9QkPSCDJ/pgXwQLAwmQshGt9DC10GJMZ8sz0GO5Kp40HqMgKBChwQBN1mzLSFj4HeL20JpibCKIyyoi3oJPAIQzhTCchrPFQUYxCy8CWS5Kxs4F1U3kUo8FtwJlb9zJAhyBZfJAcR7lRNyGPhLlbhUz0ImIJkkk/AmZIOpm7l0Hl5lE89nNYdbimse5SEPhCIOitogVJbEhcGhjZRsIYxCUI1gsYWXYUQuCI3bcogZ4y0xoTUa2WdKHIBKkUSBKKQ0hvcaHGHknWFkITtQ4RFngTAg9XRRWgTyMg45GNWZyhArsGEG5BJwrpzcGD6lsTBQLwEtw0C1JEjZoJktke6EMTaU0iiJs0bcln/TOm4SysFg1u4Eia7EsSw2jPK4jrDvEhWRYBKOmvUUFshu2WpiGsuWSIwAJZupj8MYsEaPJB0rXIisTKIIY0zLsUDewtsyJGGHwOkh2hCt6OsbRJYZQwhZbO0bgLg7mjA3l5iWPdOjymC34HODZOuMr6ob8hdAKNSEk3Ax1atwYaqR1OSYMURN9hSDDWknPsJGJAr5TAxIXS5Ij7CdV0O7VlFgQWbP8AMMVzovBDoaheiSJ1UZP3GRTeCjDssegmuwlNBSSHKdZGsEOgiyjYDrqhETz0OhTvBIwgye84zBtPJBjfeE2I4E9LG7btc9i01Uiy5wQ2kQvqzp55J0iXGjDv80P6HecwfUkU3ubCy2Ny4sFMgTZJ3LbswmAlplTWhx9cBu8SfUiA3QtW9n6CCZjFRjAnaOSyo6D6BdbpTTx6kW4ZlCy2GGD8iEDV9RMwJEccQsuRFQuuELvCgWN2RYENQRwDJsiDshxzMJFkUMQ1JKmhjdtBypz/AKVipXy3CHUo03eeg7tZZXdu20QCkJ5LLD06RPsYubEEM3LSohuLEGYz4kukG2VvgyEblSlELLi4QQRMhTOKpwyQHThvxb6l9KEwMpClUu1YWTZEaUiS09zc4SyMG534W2Nk8EKTqPVgcXKxOT7cehVZ/gWfr9xuWuxmu4MdJyKCpoVsSDZMRj8DnZQCMcBKJNqnSW5HCSPSmIb9JyvRF1LPpHJWxzxBCGB56pcZ+h1DeFeyUfpGIDvoEuZKfqEBOqkmt6zi8RkRQWgF1nZILxkgi3mMiMsWoLhfHTWRrchDfyT2QEYQ4RBbGZbhbG4i46iiv7iBWoHcgsHSyVxEQXgRyQJQseVytDFM7NEmn8sbbr3OOpsJu04V+g+qjdrtGNhP0PqNx6V3cKld2+sFMCmtSoQ46dxoWpxWNmT4KMjJQ6EBMJG4x0rAcNcCServuQlc6UswIWLGYi/uoSa2gXBD+gNwEiEp8IVYQjBn9dNZCsijZjFnTqkN+pMMTThbO76EYFcLcjFTKo3vfaB9XJG+4peognSyBgqXaBloqAhsqJqrv1ggxVYewdzGbciUfTrwKAG+4oKcFBAnJP2T+BtAL1UlupkYxnvxWG3Sw0CokwBI2JEKVQcshBNyPsPsCXwNg+cbHkZSk0TS22Y0QMgMvLFFhuqIpb9hdRnGySiYG9QRtJP14Q00BZl9gQfZ8x5zxiiU2LoLdJGYKxUo7SkueZGwfxzEe6C4UDS33OKSIGqeXvJNV3dRkDFJYJCSrfMvqMeDlKhIXaeDZGtyDdk5QgHSJjCjGkQosR7ASxksXMS1sLJb0/8ATkvZP5J/NP4p/FP4p/FP4p/NKvxk/wCk5PZOJewlz7Bhl7BESYuz/Ykfrf7OP2X+z+O/2YN/dP8AYk49t/snLuj9tKfT1Dhw7ycgyu4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WrVq1atWrVq1atWrVq1atWrVq1atWrVq1atWrVq1atWrVq1anIxmJ+U3c/wDf/wCZI9rbbbbbbfo220gWRO/G3cud2XovhXwr40P0+EPW3foUDWe8f1vifrdAv53xJNxP63dd+w7Nl8D9b4H63wr4/wCt8X9YQaffeI/F19JYtgsHr6Orp55ck1WaA6EbkLDCW+LVnL6GK9CXZsDck0hw0/NLfyfsP5f48HYMrt2C/Yn31859BjWfjvvIIPCSXTxOou0naQIOMyzdLF++ETRjj6OeHtC5jTLVE+VMYM97PsP5v4haHbRsSy/Yn3TLLKstLV8Uo7PofpSqTZ2AN7neYoB8pdPE68gpaJdky7IOLetsLafB+j9pZGMcHEJYyXtJ4h5JyE6z7D94sO4D5l4C6jqzm/Yn3TJxP1uaQsMNyfrzZOpcIbAwI1ZLgxwZ4226R4ukdwnqSXa1xnx4mRYCQ29n6DpfE8ElYC19yHTnI5Tw2Ds3PsP5oXghNbg20k/Jhg+Pub1YjGBARFyH3fS+MtYJKctrs9yzsl3DJPo6XSOohI2u2ZmE8cTgcSCw3pb+Q8fQMFhyPTuN6J/r+FmQ4P8AEX7Pb2n3NzOfxPsMj87BLnZs2MAi94uB+5rd+DvVgRPGJ0ts874ZSxZ9vSBcOJO8Wv2vOJVg5Aa9WR3l0hsOp34o/FKW5Fjc8FkHhQZa7+jtte4dxYzxM0DZji8RqfYVIPm1aebAePWxO3eb+0dfd3LXmOD7ggCd+HizLcc8MEeGWwlzJ4ZdQj4u5TxLGofjywiNRowYRmn6WCMzK4DIggjfWzjZ+BKdMr1s8D2hhDxF2QiAJ3PFjuQ/Mg+0N3EwcQ+jshVWR/h9Kb4znI5jnqzVOTxc63+f/ZyHKIXPB+20fhSOvuHJuc3CUbFixIgWfOKKGZCHQXvOnPZ97c7/AG/lLun9/heh/b+U5Oaf17Qof350/v8A5v6P/d/6f/Y2kn45/uX/ALf8WP8AZ/i/pS/lL+j+/wALBJvp3/eoHp5Sot5Lfk7CyWLBZjtucy718vMLjP6baMf1/wCQCev6EExg6WXVmmQjNvmbeJ6SWL6Qbz1dsWTPt9tt87LHkHfGScX9tJcjp8pJdZc39AMev8fyw5a8SvnPg22XfCVi+hQObXpcnJCDT6DyxZBZ4Yg5+6W3LMeGNq5RP6M8xfXjbfBzdXe6XcsMs22+P5fC+JMWhYrUcbfAcT4XhhMe76PoWTmSOI4q+g85zY98b3L3bg2Iu32+2+ekZw2A4Y8LvyDIlwf02M+G2TLNsmk6W7bbL4/mLxb4UeAKLfrY2IIjhk+FYazyteVhxls7h7K8ThApEcfLxamDOfFwskO9QR8c2P3EsmDDlp7nTm4q2E5HDcr8Nf5Y2cSSNjA7BNsDLYw5bt8DH8svHhZW+xBIw5jhkxyLoebk4kZB2QnEmzhZtwfA8hhbdISfHhV9U4Uc6jtiTxkmPP22WQWWXFSEHc63GI5nBevieb+unh6sssuMtbbc2zxexDGW3APb+WbZ68AaPraLOLau2J6jwADjwk46tmby23CNXiyEBFptJRlqxmw5s1uR2Dmz3ZPEuLvhl7x9rpaW+C6nzwvXwGhKeE8t2jzf30j6sGxcHVl1h6zjBPs/5ZPpM5Jzj3y00YfBZe5Ii5eVmSh3dzM4cxbpQnS5Fk4wkN08BjyhyZyNuHmyifeQSIy8CB9qtI6ksNn1LGz2SiWSPDYG9LZcw/vep43jfHrl02Ovp6XBJjNZ2z+W1yWA8f3ueWzfAQCZGxJhhZ4sheLDrOmYSswP0Lh6IF6IwcJIQZfUu4k2JnL8bZV63zZPUh6f3IHxJNxJoTu2RdPtcQJk9LB6QPpJ9rHtZfS+KQeltxB9oz1aCETTOuPcv9Bn+pD+r/F6k/18eDBrEHHlCQZ/6cCWcrEfciv9X+JANCfoyQyxlgsILF8UA6F8V8Ensvgs9tntvdlj2kfZLOTHs7418KxA4ht+k+UM6gDu22+Gj7V6uRC7z4tYYJWbckuIduf5H+Ic2hZbC5WETjJnjGYLskkTzZZFv1b9DPlm22I89I5nw3LYty2G36ub5vkft/u+R+3+75H7f7+t8g5i6gu8bMOG3FyHN/jf4jMDZ+e7Au5A7ufCRiG4Sdyw8pY8RHH0M/ST5fDPM27L4GHfA3S6tGXx8S4Q22ltttnn/K/j7J8ElQ4SwZCnVoc3KI6bEM/I3eJjrLbrlEE8TlMCoEwNuPHqHmU4XePqyzy7dXp5fDMJ4WM7nXg8gsBaWHqXMEnHEJ7hkG7Al6xcWef8r+PGheuz1PsHmFkAHg7GGvgRAhvjxHw3FmQWvAuIGfTHLbFSE2InlMGQFpF1bb9gkfQzb6Ryzm2PGeGRPJ3MuR2wObPHiFmXGPARx5/yv48bkRXn8XX4fP6c/YrITY6snXE5yWCRkM8viMIjfxdha4Mus78YR7nuSzix1mdw0ENBXxRPg879LE+WSDm6hd2ebMfI8dPLkzMQ6I3tKtOpd8Fn0f5X8SgawMQ+PsN8O8deHvwmS8PGYXgsMuV+JOC48JHlP2i5T2IbhC9JbodQpz5gmyPDetz4xjz08p4HMnrZ47eB55TO1zghOHLApqwZbEmP1cWzH+L4n7/6lhBx+Ptnt7XxP3/19b1MBv5/tc5cbG+O3kOdkIVy7Ma9/wC0NDbOXsSaTcJI7uE8cxU4tuPG7O8GRzePLwcT5EoPS6g0vSAO88MwG/33jZnhOYDiH2g8LkTXffrF6TDnxKsUR8ZJ47+1yxYsWLFmxYssLFiTmwsJY2/F+Dw09i09r8HgTX6gJPWEbVqNst+g8DdRHKfdCfTBKZDZJ9LdLVy9XweDTHX3DbbbfC5PsheWee3kwcpPkaWFmzAbJxYnQ4+lBaG25acWy5+l4NnJ2SUYHuw2+GQOw9dnjPH0eiyPHccR19xyPI4juLY68Lnhva9LVPtejHXixsY+CL1DM7uPc3g42Z4/SOZpS3Ts3Qn08Zp34XuHj1gzwk/AiardpHPoenwosg08C7z7igeYXOPEvrDW6ZPjkxdLdspeyTgJ4tt4SbIyoTJsSNNYMjLpd19QUTMOlzBx9JFYxjcEvFzY4eGZbe0sZPfoem5KWHKwZLtuv3HuI4idJeyTZkMZeZvewA8GowjWVnMj97IPeV2Zqew1Z8YTCdIRuHPpA3DOYnB6xPUi9RQb9OuJkHCmc2xPWI8yNiDDu5mXXfoOy1ROSYJDJyPuKLLJaEINmHa3c8QAEizyYWYRrk58OEsbmpHYSGd2SyMSTozYAyHc8aA/Sgsu8EWnrLo3eOT6TiyhsYSbckAFscS8kRmySpcn0JDicEzzOi52WodN+4MO7aYSAC5kP+5/uC1/hdU4glwXzmHq8w5evjvJnG5ZRjELhuTYYENuSBITDnL9INYcybAZDjPT6ffRwFq48HvyB5noOPBxYuyWOO4xxLZvlBxBbzi9lZhAPYRM+4kvPgjjPaMGPb/sEHEY68b5L+E887+Fvav0mhS4XxtOUOLt1PPVytu70C4Sm5d2XrJnds5bXhT6dmk+cyr4Lm6gj9OA0ws9CWdcnN8a2eM/FkuP1C9Af1uRBteSfal/SKdbmr6scBvj8ZDeofidPSF3FWs9/cHbCG8RD0iPUyy33W+6+S33eQ1mNjfLfLK9ZbGeGdO4f1j3L5L5J92+WPe8LLL5J9y+SXbYzdjO75PBt9ZLygNB4EE4kpJYfE3GrSICgcERebPtYj2L4IgWtrK2sMcwFj7V4ZKXxZWvhbUl6smefIwc8TlxaHP1DngbcJZlDmeV6QZHjjSbYuWQT2PaUSMkkBI5nJYlwyQvDpuQjsSWXhsR3bPPghcP2zlnOzm7zTqGQkoILp4ctu90lxcg2d4jekHtbBN8TxJm72zdpYCRs3JBxBlC8SO8z3lCTw6WkwkO7oJbmUd+K4wiyDZ4Pg7OrUhbtdrgln2u0t8H4WMDebTYT08BLLdPou0uI18Rcm9PJm6TIyHwisoDsXWHA1jqPh7UmyMeJnDY3cPEKdQjqVJvgrky6XCxG0ueYLkMLEBxfC7ePTHVd48OPJuvgR63rHD7aMWWXjtBYRDF28m+ayAeR0QiRLuwnu3jqYYXTFcR8p9rkT7JGr4rOsEwOWzyLnzsSI9PHeO+Jp4kpt0E5DDqO/Dpn1LgwtvguSeBcrpj4Cy07+12XkRbd9Q3EELq73b6U8R4T0huiAx5tNi5pzhAgLOi5z2jqTZGyDqZc5sXWDKvGT8oeGbkNH38CELQmkFORLq4cQZG6Z5ZBjnlu3Jbg02HEpHLDieXIgz7Vdp5k+Cxk6bMvCyeolHwOCDo27KaEqx0WxswsTVvFg6yT4PydjB7G8Q4WzZZO7TglEw5k5bXmWOFg43NYrVek6B5lGTbW4u5Hra8YruCPD0y53F7L4tsW7cdz9Y043cjHG6T2YwE+1y6su283EvtBdXDqC8W6j6eApxL+rbHIk0y9YwduJ5lr4eYmxxOnN6ZObvhGQ7LO3JuXoNxl2FlAyDVtM5kurKMt1JPsSZIrMP1jsTPAYyDUom27PRu87GBnjTm5TrYO14g5HUtAc//ADNwYXwf/wAemHXS4mM+IYB/8Me/lc/r+v8A2/E/X/t+J+v/AGw6k/P/ALbpben0em+Tnz6fYen1+t6fYAFZBz+i+TLM/r/F+JCJ1xa3NSo58+PT6PT7DfqOY5g2HTjx62/Xuej87+1bk3+d/XssYj97CTZs2bFixYsWPrqqIFke8n3tvVvkb5Gw9W+Rvkb5H+/lfM/38p9xvkZP1ZP1b5G/EhPVhvVkPVkPefmn55L3kPKiQnvD+8e83zN8jJerB94chJLNiyyxBseSx5jFixYsWbNmzZs2bNnwbzW/h/uw1yPsiI8vBy/8HtdJziewuHcF9JnyZNYdev8Ae4TPX8JmfMHH7XID2e/vMIwkPR9l/CY/B+WnUl2xwenE9O2ftcD1PVcPuP2ZlqZnpoB8JnP58+3p4b+NAOe+vLnrgcHv6Rg9Rpzmmcg9d4+j+MDPSyZn0Z/yTIzJv45zO0g0chr+fH6+3Fsjh+pmbye/XGikkOOhvtr3cMIiYle36O/G/k3YM6wB19vT5f0Pzg7ipvHzMPjf1g53loavr2+v+rG8AR7Lvtx6fTmtom3xzLLnnfBB9z6cggz7EiPL6oIAhnPx8Z7+GGfDfgu34WNUHxvF/wCgf6guSr7u/wDIsDPqe5geOH4EyK1YJuED8Y3jr0L1rfaMcTeO+HpmHFR64b+sXIaOZw58yryV9V1/v4STkuP/AFeNYOfccZvnF1V1X3V5f7xLh0bLj74qn6f4mMTIZM+rNh4DgmcApT89tyJ6/wB6PiPofpfpyyy1zPH/xAAtEAEAAgIBAwIFBQEBAQEBAAABABEhMUEQUWFx8IGRsdHhIDChwfFAUHBggP/aAAgBAQABPxAUb9NTYVQBNeXtnBDDawHKKBuqtNH6BrzJlsJHemenDFlikXqqD9ZwWR4ZFjmjmBdMIc5Zrh4f/TQxMp2ngngngngngngngngngngngngngngngngngngngnglIGU/+3t8AZkW2hGldETTXbA1foVIxa3vQ7IMoZg3GgwHf3R5cuursJXEgh3J4MLi0deneqRoX7vsdiD8zQ8AAEu1UDkeJGAc1kAxJJOWVpL4nA0BtlBdHXgZHuiuYwdfLbUvaCzqAUAIDlDa2cmoyZdGzVnqZg5DDQLOCSeODcBKm5QOIFhHIvBmTgBtP3e0me8OLwtVjfgATRRIAMXB3YD5SEmh86m2DLAUV6FxiFLJm38c7woUxbB2i6c0kdeSY6LlbPM34r//AH6/ykCX4NzLqAWFKOAx/RTPtuKougni626VRw/Q4EVXZWr98iGWLqbkKlcGrufjOo0V0UIrdrij+tzMzM0QoxLVHPRmiFGBas4/+LszMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMzMwHKJIsf/FgVqAcp5I8keSHudNfrH6qrDQ5VtG5L1utuCE0P/i8ffDa77w+uP3y2+usfpg0vXg75a4lOW+fdYbBbw4ZFXEHjuatqb/WDSM+JlgDtHZmOp26tvxREYP8A4s6g2rOzYKt9IbVnZsVWesX0lfHpqCw5S7ZFi06zsKAvgl2BYHLVsW162/8AjAfM888888dl/wDzQ/fv379+/fv379+/fv379+/fv379+/fuHA5D0UmZaU2meFD3B/mHtH6wbXufMFii5xcMF6GfB5wkwkYgYT963b86zSsQLFiFIi34FgfiAhP3J9YbWvbPU/fuwI4kdDXc/RitTr3efn05wnMFGCQxcUOnbszOIQxLoZs3k571PziXsPzj4Lel9Xopmc+aD9GVM1qjg+k8U8U8U8U8U8U8UdFaDvM2gniqzf7nuQj3gT20dypkneJdIa2xoMxofrTCRaHTFhVIJjGNqK8EPjPFPFPFPFPFPFPFCbEJsTxTxTxTxTxTxTxT2+fnD3T9Y+6n5wQv3PrFPtl5jynd1PC0awD4QM9yf3E/YfnEvYfnBomFA7FmSeKeKeKeKeKeKeL/ANME6P8AKLn7cH69tKf0NVdVbCAlq4AiPkRViTdOVfOaRCXfDb0SSHoMr6D0Lg/VSj9x1NzH46YUpk69LcGR3MEIQO8VHy7oWuPxRuNRbeEVof3jb+xmj3v7TEWy+8gPKhwR74j0hoY4CB9yD4wbuDMtUqvGyA+YwqJwx61vlWCQi1kRN/CmPRu80v2PqT6n7BSZwmUgKBFL5Y75YSjFglZzxIr93j/7QVoQy9uD9K7lmD9ejxoGK4AbWL3Bto+zGrScZmH3hJzLBkYDW/0B6c4Z0Np8LpeHU3A/j2VMrIYEoYkrljox7NdUIeh8xqTuq1gW6dWsnVnvPn0FMmgEMwQ8jqh1+0/sS++lxulIaJv+fBCTBOxYc1CcdM+995PivJrWfhCOY366hydGO2GG0z894JH7r+x9SfU/YbzeZ+OXEvsGYgc4XC1QURw6eh732/8AtC7uEhv92JEPVcsEP6dqoj9GG7LQQODZQjI1MS91HiA2PtRrwkTM2d2i3khP6C/oUk0etFkdGaor9dmP6xk2EggjSFJiGBaboCKgwaZGbdEJ3PH1te8kJ25KU7CJ6Cz+hFZ7D+xDVNx6iVQUkfgXHFQ0UQ7GRiGqfWEvowOaRleKZUzzNg3KYmhvruVhyj1h26JysO7f2PqT6n7FMNwcITzjbU9OHxsAweZl0/de3/yzIAXGQh7ayoG0PgnGnRy4bcbRY/t6PZiPbeOsCCCCHrtvQVCg1V0BPEy16SQxVakwKCUJUqG5sE6dkYvJercGAN9VmpXMU36NXqdMNdK5u0w9ZlHxxo0rLlQRBQ5PLj4wjvpoRbcMk4QQSBjPKH+Nx6dRioJZgm8HO5cWjeKvkv7FYf8ARo1RSgT8ekWMv3iVqNTSeZO8AfmiLJNttipb6soSngYmVLDgxXgRaiGZjf8AY+pPqfsqswVEVO8qZk+Am1S43Dep1fsMf/KZ2t0fWZS1NhRTVbhmhrLHAL5Kj77qG6g3+1o9mINv3Yk9UIOucQw3o0Ptq4iTSE5eG/8ACCtHDRG7tz0rD80d0h6jHPDG+BP5cj9UpfpJljfop9aAz0OnoEYfimUygxUSnHaR9RD2EX5cckY8CGzLxtIKuWCE68BGnmp38QVcTePfrb+xYRdg5UznSN5ZD6gMtzSHIxfLqpSqjKjoU4Mg9o6Zqx4VOSOCAvsiGohd4vdQX8p40jw+ED11WiGCGs9X9j6k+p+wbm1xgXl+CJRUBRZXc8Q0HCu34J2dWor4ZW8mJUlEl4w1vbX/AMjbA5aCMtoKXCjAwoZnBfT8uxhA7W0lJclpwvJCDApxKR4+Qj6AFg2D5iHXPwIBtWfp0ezEexdulHXp1BATXSSX1SZEbj/A9JvumXxjia4TDO6SDL5GAdpWJGC/zL5R/r0LkwJCu4giQ6tRIkZOtbYaOgo+JVD5vDYK2iYCRJHFfVcFEFZj59h4l6eGughAwuvA2DHQWuzd7oflFKij6Pb+X9ij2eZFxPUQUdAIL4X4RtcEtsEPImSev5T6i3pD48yvgjOOV8iP6TpckID1KfC/2PqT6n7DDPKGyPDYwuoWhXzBkcN6dU4rbOk4ssc8hF4g1xrwIMOmaJ7j2/8AkAPZMAVHq7YAeiyi3ehJkXElsuS3kQ0ssM0AygQkmVGzm0Ndr3IWorwvLuNXZw/p0ezEbvdj9E2YOg9Aj3Fxm5WeiE/jPxSyHIr+UkRHb9vlVXHy6Fe7KGKPveAJlYtubuDBPCgQDpUSM1GXK+gX8DpQfHTx+sjAQEqDGyWtkWNSjaavj+sfNsFtDnZkPsQvKYNzcvclIgJtwWHUtZ7Xy/sF7wMoVqY/oZnpkiCL6YkEjyXnDFHKqOy4baL/AO1KXHkBC+61EMt40aiz0J7hlTJ/v/sfUn1P2HrnTKXsw4bYNvkfczHBi5HqI/lKB3F6ht6WPwAc3zD4gGEG24bnX0P/AI60LA8sSsmFWyuHxSLrs7wdVLWDzFvTOyQDarbghBQQOqLTM999F0600Ki9MHpaVNoYPBF/To9mI2+zHTf60hK9x8yWLLui+WdsX1jP7z3QykqgugMVnTioXdk5LBhhBTkA/US4nQyv1JSR/B6VXxMl0Rs8wPmK2ipvo8kvXg/hcus2oNhEJdm07uW4iXE0rfghUtmduIUV1UrtykfYX9i773ZHc+UOUjlC4b7H4zM+br7TMVHo6y9pd4SONOJM9l6TjmAcNi+xdoAI0pTYmeCuVXGobNVfL9j6k+p+wIEopl6BxC1cV6K1gbs5k2Ksj8EYhCt2fL+Fw/DOb3qc7aKc1IoRKoKifwf+OPE0520YwEnB8RBodxRIG2xXuZiKKt9R6rAHAol+NGO7jD8Po2htNZStJYv+m0ezEbfZiX+yRZbyDsWsUtx+B2xLrIb2KcLJGGQuMvvrtABOXdyNvQRYfx1NZhc7d39apWOgsr9aC0n8boKfibEvk79H0i0vif2J8BRooUCosoy2l62NCFGnF1PgPEIgt2FP50IXJvmTnUMyO+xDf2AVF33rq/VNftXujvpDyV3JiYEroO8M0AMfm5iz71azFIl5zS+CPd3DHAuTY3GALkXvntvYtMELri5GwbVFqgpim+r/AGPqT6n7FbPGabzmvVYKL5LwcRcHdOkj3oLbi0U7haaMxy1YPd2ylNTCtvQ9PdFgEp8v/GWhYtsMM1NbQLzEIyjoJmVYNKU+HgZbVbsjLwhpGSPitGZtJbd6wI5hfqQQspxeO4esYthQQNJ+jR7MRv8AdjpOLoUwj1NTv/JEwV2X8rM4ffPm4iqja4YDqEJ4SxIFQVHorCvM34Bde6CUKCaA/Y8dFz4qjwuPQLGWqWF5j4sViC4IHxaeSC/eC3Ylm4BYy83G7qLdj8ymcu6ZFsdZqyd20TcViaCVW5X+H+wTx3W2LYB9Gc70c12YmYRA6ISOXxmLniq5BaAjvKJZei0dkghfBYCAhbzB5cpbwP67ty/sfUn1P2MVECBwJeyT5rKr+RHcDwYML7zFS+uQWAwzDO0j7cu3H3gYyKzX/jeMH9J22y/5l8XqFHU21fqzMeY8MHhMAynqsTE520siImriVNkgZDq55uyO9Z/Pslmb/DGCASWu9fo0ezEb/djpOaei4rF91wEY9i6f65B8MiwVyGzuxctNSogfzWIoqBgf5cdXzLr4L5YOfnKaipp07cByMs7FUzZfZqFBj2X9C/0pX6kxa7S7eOtsnYIdXslfrJgjXyI3bQ6FkltxkqZlyyrW0dZwj4zmdnaUWyyPYxltTmpven9hWwXrAfkXZYaiTX6mLrkGkwPrG0rj06Fzd1tCxeIcXLYsyvVjtWkKH6JjhVYe1mhJiwp4V3RP2PqT6n7AwmAGVJZGkDFWeYnGvHqEHeLmHSzO2xVwVBvldIwxur0krz6eNurjkw7t/WHztTT0dGO2+D/xnF5Hg6aWFoU1yhe+V2BHeGsMrZ6hCzqFJCudXvPTbYU2issjAzc49XEKZbwrm/pDdAj2roleO42VOtZSULh6Q2e7EvpfTcKy16h7m0ej+Y4RzblWQWjmV57jHkKBfODCCIZNwXMIqPwiPk7L7mmH5tQZRteURzNf4hcV8bFkq8bLqCwEtLp9SU6E/MIZZSRzG0IL3M+pFjj+fksPjorGIivsRR+2WNFDmMW39FbC0LcoFYNRXuDVmxhmDCXLxDHprfsQ4ho7IkYHZFOYc+rzsgzp4DqoUv0F7jnrKmmjQiFqhmiPiwFNjk8oCDTdUvm0WKmGyvo1EXqnoIrxf2H6k+p+wvN+nDpktdgmYH+dFtByDNKYO4TuwMyMocXmFFqvVmtUCPhFk1jh+Es9MWogpYAxKqH0YijOAx2f+BuPI0nJX8Wf8lP+Sn/NSqWhwS6Lnihc54BAq9ZcqP2JiqjkgVxfS4mUBPCxqO65aI6qO7Hkh0WGS/z4suJruOFa/pUtFCeQm0UhB9fZOxo+PUIxO1n+aY7srVJUm3XoeaiH2kj7YIPwCAfaQfLL5+9xBkiL42CG7HThVxfbwi8qBfiLDWYaeOdlaemJaiW0t+cbhk29XFfKVc/JY/AcEMu7MhyyYYbSoEBZjMnewNZdnwzDTm3srEXLjMPuJT7S4MtRIbRqrctBDFLUv0psGG91SKnoNhn/ACUuXyBNyx7D/U2uUqTYsuXNVEFpWsEceWX1WPLh0PJCU+jDiDl6DpmYk/j2Cjw77N7A5ZaLRaLRaCU6tHW5m8+TRl9iutQjfiHQwhPBYfGUdf2LfNlITDPlG6kLjJAETZcPok4//qv2PqTI3tKBldRqWWorpqJLRaLRaLRpd9WfwRbgnPZFtssGFuoKiiAxEqZLfWceritaPFdnm7BRWX/DxkxN5PWFsqeh9ciquQP/AAX5d1YN8mVLwS93sQ7Tky829HfsSmS7Sk4EMNtuUjQ8AgQOKBnBtExhr6rQIvmkcd4uq/JontgZgTgOxNajBYCHGoBNZXcIc80hNYHvUtilJmIUg9UqjF3i4tJSV8OPfAQ+5GZzGPzxBvvplSg+HKcwadScLGw3h4ArbUdhLUcdnC18Jvmr36AEOURap+wBGLhm0IeRNbjV4It+mVxbS1bhDh2SZkQMmZZBcWhHkbZqQDemnPomdyjaKgKFFPJcugtB3naQRQYsqgy3isooBCCnAz3FiM24tWzhtWZcKfm+QtqkucPEoH8HBqPEerBHOTd1Eu3hqR6fZ9VFBm0OXEp02UbEl9mHjsYB+b0QFezsxabetnRE42XSx1BxEmpizyntyQxUPiyLbYvEgyKWvn5yW4Vpj5oCboOeGEOyrYoU44cJqTC+ce2oF1sNI6VGikjNAcsEGon53GMnuJ/kH06vS5SjAKaeihZsFwYj1LisSEWE9FHTiscKyVXQRdr1sq02GwbCL4yCzFsMFPPb5dahfa8vxTtaEmdbspgO4VIBU1tobkxXURl2KhdmOTA4pdAbYBOOQM7MCtDET/tk0QZyscgA9GDoCDsZd3rB1vYxCEb28JHe8JXyOK+AX84zUG5tACmGA3EQmYjJuc75Of7H1Ju9UGg9AmH/ACN2HG2XlbWwUL5GXUWPGRWAakoraCEilVvsDD1/Fipio3lbC6JXWtJmW0xZT0TKBU8BteEdLxqg/Fv1jeuT5c1CzWZr3QXm4X5XHrtP7IjqTh0dVeDc5Yld2Hza8hzLKYlTN/PmMB7uB0Zwg/CtUIHg3A7p/wCBdzv3uS/SfCfglBzRJr7yqzSpNnJuO/KDoYXdyofUx0A2FeOJs3I4pXyN941+HsUdAQ4IKCCjIoh6JoRZeGdI2qsS6/JPA+SJaPknhfJAd4+Xt8o9O8tfWad+SAq0jyey2i7hbi47RObRl0CpfUXwCrtD3jPjVsPa9CHpeApzZD/i9fyJeVFTQs5IPbKqS/SL/Z2FTafxCIBl7eCVVaRjZlNyXBPKBqlSmuAqcxmePSMPCPrX3mFXw0tkO2vUWI0uNnDM5wxpLYAQZNDue7205wleZOTH8kclnFLHAq0ExlCRxe3SjqapjE7C2y1S7xQdQxZbDAYIOACIwHyjDpyCu/Rl6QYpuKVIioK30uXN1xZyYDq+e8Te+YrTzMkuOnk3FmZddRRa7sw2UA06/wCKCpqaqPQo+Km2uZ1ssVqPqxLk5X1CYLDqsUsb7jA7IqK1FSAHdJXlmVmf5CeF8ke0+SeD8k8b5k8b5J9uU4WNQcScLfgnjfJPE+SeJ8kAYk8YdsE5r5nDVm/CA9mKU7+tRD+krSCvguH0aUsvTB8OIDdy0AfMY8MUW/ARQUcR43OGSM9lUepl6FyqEnXsu6g3QKpECe60Uy/w+Amy0XnfuSyXiO1yV9sRgFsAqULPKGBh8BLbQd1DVmkN2gEuN+CPHZp+zK+YJBPpKsnovvwIDPO0QDzTlUR5Z5Z5Z5Z5Z5Z5ZU1Dc3Vxw1h9SLgXauba7W1mBb3Wiqw8jETEs2LVMMpilnAUsRoV2HXaIxqgrRVfxZRAbuWgD5jHhiNH/KcV8gtFTmy/aa+SLIF4IN5EhlUuwLqsGlx74Mpb8BzQTYDNFF8CXHZDIqDhermUmjrFAeSHvyqikmnoy2QztJ0nwhBOx99m1pWI8s8s8s8s8s8s8v8A0vMYbszHtiR5jdo2phuz1jDCM+zEbPT27bGRs2TSc27bGQnI/IxHlhnJgbgBtK52usXQqxHNIORAIijZTt0R/LfvMPEQ4I7qeIITgg8SQPLHE1Ff4y8Y5m9VpWWd2xDXgxIdvqP0wD3MmCJvZrlH2ENPe4dNZXS9EU+gRm4gbUX7IxKdaqG57s2LU1KV8aU3ocHGLl1xdp1Ux5eS/RfDpy4ur5miUXV3l1XNEX+QM6coE6CC9sJuS6eyCYh1SVDzfft0qVKlSpUqVKlQohuv72G+wKv+X7SpUqVKlSpUqOc5EKv8BF1hEaB80HnpMfUYPiDsepX4ideeqRGL7D0goKlCemWaedOXO3E9dk+OD2R4Tq7OWlDMb5eCcQX/ANtKlSpUIOgNQ6QZXTUIrdWoaF5MHHclwYsnOLIbLg01OwnNJxzMOShi/wBJWtc422/dORi0swk1UQQKlrFRfRyIcHRjJdbyaCeJgdCDAeDTramuQZYcbmuJCrK2NYxWd7Ut8TzmeHwSu6zseSssvRTuCfCnXlIwywtwDpw1IG+Xkyi4/ePzj95g7ju8tHRBxKiRXmVzExosVnMKl30YTX7sztB0USguLHZ/YAkOV29juy1n4/guOE61sckxlPhECvRMw+aXf1LY/saPZiP6+jhMRpHhCAIjmLqCmwPHmJ4VKHhS8i36y/01GfJ1bce5krV4eNpvbr5MX/cB4idM+mpUroSKO6Ug9HBA+LcYQ0DK+oWk5Iqm4wQIMidSbdnSXx0+KEInaF7SGV5qKh8qFT9CTlMcHriCFyWQ7NuHvNBfdgumGiVeoM1gnyOOjgx1MQjshHd3fkjNvFt7rZmUnw7xllhFZCNmqAcEcVjLgitR1Fa+0y1U4dzyzyxbt0VZfRsMHo9tmdEFXogOUVn1hoMGPp1e7Mhh6lAuEOSDWt3AoD9TLDKUBtj6o+NXd5YRqHnJgJhDlLECqNFyeRB2LasR/Xo9mIwt7aJcJQIHuMiJ+elZs1FHrAJC+ikx6ajQ+UXR5CG1vclch7GS0t+411yS6vLBqc0MIaYUAZIWH/fHSqM1XUgWqQlogIBIVKNEUWi5jLdQ0hwg+1OeKQz4D4PZlTiY4aiaswsy6ABTAdRv8v58O5XnLMV5kLDc9LNKmYv0UtLmp7rv4BFBJy8q9EFnCZE7Q71KrmonEqbiToKTFtIvw21ZUcFwy4GFzGigmPLF13FQzFcSqOjaEW7x43i06OVYKn45nPGOyHlRya9UKuOosGwKlrRmak5QEC+h9y+gQbbneTn6sFLgwd2efgehgTKaPdmTcoofjZolC3cKVItabNKdA1FRCjuu+EZfzFYx+mwKb+zNKra4VgXY3u1Q04I2cLaz9oJ7TEu7ZBt+s0ezEFl/5k2gmv8AokMKF6uY0RGwdjgJw63JeUhZtJApJm4Ku0+HiKs5QChErpiPTOMPN6eaYf8AaQN4l+3UT1QVRyzE4jNnglLstMJWKaYzRwJUK41FkAdvYlzL6XKMaxeucZMvFaxlcx6SVRLpimbcGCTbDMejsj6ecO8wvQugtX9hKAl2/D08vlGWaW1mMNOiwFQGonVblzF3odtVcRiHeVZ3Sa3uGEbo7MtAttF9yO6R0lfTaxrDMbteyLNWWGDEWRh41mGGV7Qy3li4geoJaxne4awgt6W7F+aO+feWFyuwDD3vBGrCCpx2tCAvlkxjjoYYmfSTvibpuRMJr92Zr6I7T1i5E+mOx03xuVJF05aHW4zSwGARtXy2Q9ZgB18opIgIn6DYXnejZjljWPF+WDbdVhGwUx4/jtCAjcLB9h8ucRZ/r0ezEf7q9RgsMWkPY2iVBiyGP1FE3O2EkEMDAURKMGhCEVYRIKzdeJNxzblTf5jprRupl4OriV4/iw0f9qkk2oDZSuul0y6CCm6KYemE1ssLrLEn2sRwK4dh9JdX7OjM84GY+iKN22pHhrvr/GXRBMVzLXLY5pKAmroBFawkzqDoHTsn83rbYzwE9QxLTXPga/jyYWUJMIEs4Ar156DAbAv+Cjym+Aymh9rBD5+Lu2fMgpuGQho9R6LymWQK7JYrudIaujCpIC0qWS4aDVU7aAZuVLDs3GNtLgyhmCBTSM6y7diVMh6SHEVhBh9Ec4/O9oENfjhs6wOEe03O09F4Zr92ZfL1zmzoPFyriC5eLgPpCqhXtwQ5x1edd2peCzRQ1CioDl8IxZBvpfWYdCJv1IrHNixKgOsx+cPu2t6Iha0QLoDUl2JFNFlcrCNRb1TAynycr9RMsAeX9MOwa1Ru8x0PKIiPB80fe3thC0AEftghui5eVQzpjLFD+pA+E+SoAaCP6VTwOyOrHtZWbwl5xoqoqy/9pOCcLF+IysVZUemSSjKz0sYPWHMeW1qZIcUY1BQpyfG2XoP4ytwMHnHGmxxHaOllxNXcejCq6gHSX8QYUYtSllbLVDZlf6RdDGp6x6I4sEASOQ3RsZf1IMNA+seOxriW/wBbe2iekCSYcTCrh2gmnLcxcjp0wtSzZDU39cemqjPT84tekdbWUUNKCJe9yqsoozpKgSNQ49sE+NKYNU1qjSrtqHY7GmMnpfBDYxDnpC0MYl6tGogYXZwQKIds5TV7s9KTbICS3nhKRAS+NzLNRbZEPK4n9CK0tCMVeRXbCcNTkBmXRg18ZgzbA9yOjvkp3INJc3vWDja87EukrhwJhIArh6IClALFniC3sRoZr4i5hMjHhyimCXcOH9NsO0f2nUnEGmGaxHR7W4GG2YOARgIUPBkBGV2aQW5kVsv7kIMysUhBx0KckOkwPuMPkBhbjaG9ROFR5yTyMgkD3wiT/tKoofbJ3RLjUI4YtBy8rUYLfiVM2c19WLlo3kNRiBiO8R1V1JB4p5xRgdNrrTtLz0QZA7ILpAblcGQnYzeYmEVKzEHX+6b45o9J9GtxkGRrbyAgw4Gw/PLxojeKO4xuCbWSkZqySV1c0TMN9t6Dr9RCkLNMYspODfxDNsf2xwOSWy8IrGkSojWLlNKYToVIB8hOflmHXyLQ8zASX1yp3vuIuNIZ/n8fIZ9yLg3BPzaetojVcMnLs+7Mn0Zb/jYlwBHStEVQeJEWhwERQRYqdInEtYHMIN/U2gHZeFw/bySViLMuYbY6qJ2+qPGlHF+ZCEChXAIl2p2Kjcy9Ce+6f0MVyP7xiQ5+JeQRBEKmeqecSJqoHoDkF+zOfEf5Tl8J73rArbM54kXVFYWrFx6X8qGVfddgQ/LNqiOFjrnMrZTv4IWnKf8AYek+XG8wVzHm66lu0E0gxqOyPFlg93QpehR4lce2Br+xCwppQV9yib5nlXpbHRW1Zd9DHfm78ZW2QcibtOalMTUUYiGFJO79mDppfUQtPuryy799HcJdwxGKg7Pu43XZUBlfCsRU05CyA5aIci1gQzYO0HHy1Uhg0lWcSd3wy9uWf4mBO26xDD745EYT2Q8d3EHMYki7uGb7CsjqGUdRcQ3IKEbhUc6/uFvEFbjLQjvIYniTMTJqqRCzkKKQpolb6Yv9xWUhuHzBky9QSnmJau/XS3SkFRAw4zDnX7cyxBtB4O72IfMS1zwAS4s+zlLZ4yOC6Ew2Ma0ZxBQiksRLOlu4A8qcTSCjWG5BaYJrSh0LD4oE345fGL9eDDrVkX91MjDn+MAi0I57dDrsE35nNEspSexBU1o5SGVOmVGGfDPSJjlh6rZUpiwoJipmRl8dYeLm9r1Ghtr2CEh/v2P5oPVlW0P9BX+vPOWhhmCaf9buI1tD7pnN+i+ZRPQoLUX/AGwxUY9hwpGvJGtsDJD2SWsAwcMA2jO58yMGrZIF/CcTdvBCTZhETvuIwE5jHKmKy85VmLDZ5h0n9Wdre7CZ+vjrY+AG1iD22rYo/B572HgMXCtRDCwZynvs26hA8ozPYVDyD5I9MUA7U7gucroq90QfU8vXRMI8LRXTXJAJ/umOpHmIqaXHYxiLgrkThjuIDc477hghOLmjXd2iVl+nmWCOrqLSoySC1k7o1U1IW/hyn2QkUpZtNOwGDc2k+YSdQl8cFCpGMEJd5/uE8vxMub5W3pL+25gR48uPtzNYH1l6ExswPcDlKcSyE/GjcD9JJ2Mo3wTooDv/ABEnQz+jD0OJjysY2LFlbJi9vBM5F+OJ8XMSalJEUOLYJb2PSI0D1UhWIQSoQ2IiD3JNqR+7gb3hI+uWAVFoXaQtFLsAhCAuMivjGNdiLnR6QC3tBikGaRGEqVF3sE+qb0xuGVpMuY6jBuD1clb3FzZYLQCSDcf9WmFVABA/CE4Tj04dDikT6WeJnqpDMo5xJfKlbBRFSnu4wvNvmGGRYaAQ+10URbLfEw4xq+6GEC8YJCa5pMyjZIM8sgjN2J7QPvC2QtI9xwyuXOCOXEfvKULlviIUqCCr9I5ud0GmAZxBvKW4Z2Q75kWT5Q7bL4uNwajq2GsLahu4KsMlpa8sP3dtU0Wj566XsYXVysrLcxgc1D6SXWDZDN8ogshvTyjaW40FWZnVyQyYb5idSpSpEisIIr66nGSmeEEHqWeaoJMffkSb9HyVvlC57hm6PLDV5T2rwKwoU0e3M1pFdSVGYJIkEODL9RafBm08wzfUju856lbwQOthF9EwxhEbBhHYlqFqnfugUYGgu7Ulb5+Sd3yy34wPlG0BesQzJl7tlkJDVHB7MSD0JQ7lU5+BVeXSwTfSgHwi+6q9hsjAf0wJRPee4/EUawEvgejFYJPzGiCUA+YbemMse+b30SXDBkVJWkbOiiZlKEk7f9SN6I/jpqOjETULQLTx+EcnwtWBiq9XCktdcXTAbtNPCMMvpnImdpK/OzBTzHP1zhIs6Zhbi4pLVPMclGLFTECLZMzMXCfrLMky+oE7Viu1X72alhsIOQFL5yUa6ig9NnnI+LobgpdWTivSBqr8FlfEg+PyQ0NMOAXxUtYiqQCW1SwV2uLVk5P0xheEtjtmVQQzkxggPJL+KEiCkRVXmBLXCawz8sUl260lcbO6l1uOkLc+IwBDwRy1kX2y5SAjXAl4PVsxpLPbUwbZM13YXPbFlmtnn1pWEDGKv9+ZI3ccmZXUO1DgzKRaIqVxVkWTo8d1QZ8GwyrED6FlpOYKhcByLx5jwHaVuXPgbjsddwvvHJLTcHyXcSRGoi4Ayu92JV2Jyjo7gzCKQDDAg1wgQ0joNo5A7wzPxhFz5vyc3fktcMbhYWXaG8selVaWCFbn0T0SMr6LYMpDpoDMUZS/+kqwMzKfTl/YgcUlq1BPhHxlvJpCXwWwuzMi/M7ikj4zwQ3jxaSt/lwmZK95EaDHR7xG00fApZ5xeTVrGRkwIIjOIYvOMMQaiIxxmlkALXjBhx/KL89TtcfKEtfkfiDMOJpDMWOAjDcjjZjZXvvNsHOVQtWOoDhlshtItoPPS3vLI+q8f2IfwKLBXrVWiFh4sB3MjUUlAWQFSDbD4TF5cKYubfLhfQlOnIol7WMbLnODDu5bB8hHjbajXgA2h2iuqrikfnm7EPwiJ5kb0pM02MzSPARVS+hmPfmXOor6Iikx3jG0dkj6nPCaWKS0S6BLTZYP7mNDFvkSb6RbeUcHnnyi613x+kvkDiDB8QxdHokl9ysH1RRjn83Up81Bou4fLuO8tRK4wVw2Vl99Tq3IgCxHhKal/oFDKPk6YDEoLws2dDcLKjahIvf38JHXyhNeKVIGqmcrC94irKiMSM4zGdKktxqr/wCrMAEenLDIAU32cMbl38X0GrQMvaNEoIksKkmMcKqZbuB7eAdYZuSOHeQagHUS9EG1g2tGCAxbJ3WTwylox6CDm7BYzD9Zr+vkx8dLtpzH51pJUJwaZR8ZOWki2wZmK+KgUd2Fopbg13TeyHtA5ldCthRAEwHeg5oLh9+DHWtJZpmwydVkR8FOuVRMRewwHAWfgRZizM174u+gxPVDJ56jLKwVMSZCdBmMdgonzWVSE3jeq2zzMvQyVC41Vm05jiL6rJu2Wn0yuLQarEsfRnY/10MtI4ES6tBsy+w0h3gBZLuLhX6u6TRbglQh0USFlPCNkv2BsiBOpm74WHoQHctcQOL1lPHRUMwc2+cJCdLuSnzldApu6JcEKkGma/fmcNBeneV50FJa7hjcu1xa0i2gVjESBJW8oElXdQrJucMuReANsYhsVojpQHot+QHeCIhkxKIZRNBEAhJ8yWAoIQRTJO5KtSpbekyqwVi2IR1nsfaaxaBzMuWo2t4Jmd9DAHvmA1a/adAeA2P6TMzQj25zMTYFoIvLvGlArp1lliQyUnEQbcb6hwRnplTemeIAHoMMTyEvUWS7Qd0tD2SNVg6kzExnTUqC7xsv+m0jPT0MHaaq3RVVihjOKVDoZYfDxdks3uDrCjcWKODS/wCaUAfkhfkYZAYD8TYqLCzr+GViab4fGYt2HzoO5V0jlwVfntxUDSckd94A7jLtL6Ua+05+ai4rEOaisGofNYJcMdPopNVLfcogxeL9vuPImrw2iaRK2pYMxPMcwvVZf9V36Jl7mhCEQEWgVYUkUCeBu2wrNDdeDxinkGoqqgYFJ2Lw2RNza8DkUrioYs2NAvEagxX7NLOthyMjBLqWTprpVtIGsHiXa0ZL22lOWFBM7kvB5DXGNoezuVi10eBVIFt9YbOeYbhxEa9oQzi4NBe4ZdE8yP5Ty2pyxCzbyvBL3mJ5MbL3BFoJBLGL9SvCXcLFLIVYo8ZSW9r5ZbRECAHHx2BwEmby/wA33421sITWpWasyGHHvAsLEnoI6AdQlnpmC1q6EvcZft6+tomaA75jM7Xe7GhWuQc4zwzshhxTlBUySzGjlWjRnhsQjZD08Y7QBux/GNqhsMOSGDLO1c8Z3vck9fiTASqREdn3ZnkcnudW8/SHq826KVXwmOHMlMNjUx0J7AN5lqslkOhZCrpyW2WXXlKTDSX3BYTb7s4VqaCyXtsjepXmVtHphxmbzMA7d+8usCxiGIZJ4AHSJzIKilBa0/gRKel5CKLY73GFYV3smruHil8iMVzbQqIrqDRkDxWFRSkKqCq0Qw2CbPSVwp7YGVjwU2nCITBxV+7xIvl+IANq9iGSKwULBt8uCU6BNANs81qOzh799sV24kisjaCZ1xxSFTQTuNBgIDg6DCIbjsL8W6ixGGIL/wC6r9Ki8BZKSmHGBSNkYbrW5ftQsqA7r5owXwBPtibXzgLlC14ujAvsktUlVW98a9GqjdZl93Ns5oYvvpb1SxoKpT9+7xZ+zH3gwuwlO7LdFbEwZjJjdB1Jl/01Vf5H3ntkfPprAFQi/eweYJXsHmZL/kfeAew/me8P7nvj+5bhcKFWPA6zh5N7MeNUPDK6X8GVKh6CcdVD5sqdJBQd77wrReruvY79x9U/5mCVUVSn+VCgryRgj2uKzN4/Jne1kewkD2yeFIg2k8uTypeJ46IyXn3dhsNE8s6qBij0FOmPoYpwuQW8I4cc28Yj71rpLPbH9xe7cCvJ3Qq+vVAe8EEugBH4t0Ct7V2UNg+P0wkJWneV95/qvvND6eoV3jii5awOJJP30/6+JwVUlB5YMn8J+jTXpXX05lPUYv8AcRX7icZnver+cIBI0ZYI1A3Nmgo9AJ/ZBP8AQT/bQL7z7xf7yf7yf6Cf7CAV5cvvK/TKgIbCnlQQW/PrF/v+xnpaFivOZle9EArwG5VoE3HZtUuG663vv6mCjFW2vMz5xVp954yeMnjJ4Y8ZPDHjJ4yeMnhjHomGqjxkvcAuuZlD1DN31RwFrd956rRHfX077k9qD5/oMijtOLKWqHrn/T/en9Q9u/SNL734TTVcCbmjgwR8MYH6VBEhLIo6tbuyHomQQj25+k97fpCv2vyntG/KI97/ABGnvflLj2X4R37b6dCMIMG0W1Vpj2oyzWiXUcWsJe8MO34Ngr/AxNzOCaxG/CM+2mN35DLaQZGsI0ORg1hrBB849w1C4erHsK5ph+Kz/Lx/+jEPsYL7GKn0sD/qxv8A6MPx2ZauVccT/Iyv7WVfYz7dZYv8eVP+HGb8hjE+SZRPo477eP8AlRh/jdD2s/x0+Ce0a+vtnjpxPdw/CNXtflPcv9Qr9r8ofPtfSVx7A8TF7T5T2N/U9jf1Lcq07vsj+Lz/ABc/y8/y8fxef5eW/bz/AD8/ycfxOf5+H4vEvt4+/p5/l59k8/w8G+zh+Jw4+nls0P0THVSkIsI7R5ZjpmTwTewb+zgenxcPpWHTf3N6FFw/CI/jMR+xj+IT/CQzuopcSwz8ZSj/AEZS/oz8Yz8cx/AYb+phlhXXCPChsx0Aex/03BiwnoGLGCMZkgoLjKQC6Ul5QYrBNe0wHo1y0iG076GZa4dGXQpr9+GEzfYSwcvjNzdM7MuP0hA6JrQYrmA3L3oJrJwx25spSeVmhrynzIYTA9T9ogE9DBv3dnQxSBCRj0wsXpNEOIcEzxgyLsQUyNd8+HUohXwBWr9GGKZp1Et64Bqcwyyg5SFh6FknnytuTrr/AFAzUC4ViHQYckqpT01UqNxU2qN9NA/SHT7MMW/Oo7XywidNMeeN3l95ge0LHylErGGHpW8vbN4/QIKyr07LGYEy/frly5cuXL/WcZdelLZlwMx5rCXTcbkTBG+nnwfAnH0R48aw6fEl5sYt/WNMHZ2EhRnkf0igbQ3nNXhvQmc1+/DFX2YlLwzbONmdl70lFUlzxQ86I/VDgxfiuukQKobxKiHchCNs+SHEi3UPLRihiEGSvM9r5JUSMHDNJowdRSP0487jr/HElcbnYxtyI228JHNKC8haSPqCPM/8fyBMS2+XyeIwJlxZCo4euuBf6VdXUbpgmIy/XHPRwdauSROpik0+zDDBO/0jqLXE0qZCGEZVielp+fST1tagMoaQR8c30eXMR7pc4nABBpDlIyzviTOO8StgQD9WtHk9j0X/AB5s2bNmzBumseBc7pm7RCBPpGLXEd6mOE0PYnEXqZ4k3Ib1jM6lkZlVS53xw+lbirtxBZNQ0CcMQjpCUO+j1+7E3J99Scr+n5cC8tcaNChLuZaM5TNkktlcDKSMlJSqggSz5zznJLtYfGEOL5u8EQ3N3vyQmsekDZFhh/NKiWBGwp2s9JkME7pW4NSvD89MVeON+HZPjno3+syi4DO3corofuMCWKYTMl66/wBQL1LfHTMW0eIK6C2VdCzU3MD2ej1EyM9p4YGbCIk5xEveJUK4AkNwsNmUnIEemYGJYm15isO4fMr6LIwWmKGJEVCWbIj0TqxFzj9W/wBuD/jG5cEuyXscYlJpFwOnqRCMAc46CaLc8tYqOqrtuFD4QZ9YcOW2MkqvBzyEM1gqErgoYbTKPQiQxVSu50mj3Ynf78dOcvTusldtjifEsLOvydOvo0NlKnvMwjriYuYBYB8oFIbUju7CMGvshJSCkLcbXhlEyJn7eyBKx0qbyuTOu6bq8/H8QoE9BYcdqC4oCRDbiQWL2N6B8Kl29Uyuny9Fw3BHb9Olr6A46H6ArMhAmRm5KXN5jGDZLXpVyqh6Bj0Lc9p4ZScwYaWVgubVreWHhO7v8y3fUueHZnQpp5li9t5efMVoi3qvywyNecdNQt3OJ6bzPwXq7ulSodWy/Vv9uD/jKGYEJVwbKiWNRKE5C4RnGVEfF38eAgqkc6INFXmc+QVCkcyMYcd9FqSyQhmn0jEfD6zbVhNPuxNT9uJuWKAqbgpB8ghUBJncymESe9eY8S+5FelEwF9MluLuIcYdsMxJAXjM7qwwM43PkwVSU+ncpZQQEsw3D0Ksjik42NWGUTd78kCJjormdjiW0dGMPac7pEfMQ/mCL0j9Q+XwSWBHfI/EQPzjOpJeWo/KNugnslXiIQ1yjpMq5nnY6a4FkqPJOHRpAg211W1LdStn71R+MeiBdLEaEgtzAS8zUa+2g11mfTMezDM/1XxU9Hl/3svbzu+O/sY7tmjArodHzMb6igIdYMAyVDMt1mERwCKkTLKceWpMmpPN6l82CGvx+jnqV1DYf6t/twfsuBwtSrCcvu7I+f7I4MRwI4QntGREbLjJlfgZ9FzLgNj4LN4PeBcIabh8oEGg3iI81HHYDNZXhCGJ5sWBl3tBkp0SDWMX7xEsod/dGHMdj3Ynd7cdKy6PnNiQ+bUaVVemVpjElTlUSIBKIcipcAL9kPd6SbahKiQ8G4YCTwgQbm/vi6JmwwRtqo4vHhmFxA4dQNLkjGT3/khNIsRZx7mQS99NSWgB/kjLIYStkCUAnGz17KbHtFfYxngfJH1Gc1fpUDOFjV/DC8EMa5dwIrGxPrmNVRSmoLBOulCqcHTXALq/0ARyh0EYnRGowXFofoRmEZCV/TNJD+bKOZCz0eYJ09iOpjO50LM4xKhmn3YZl6iH45n24x39D01ESbqKSunPTcjhWlzCAjQHwR022+Y9CC3Wc0USU4LeVWYKuDKXMDgiq9yZwx1mut9Awejh/Vv9uDqNJPV1wr5+I7NQ0j+kjxqsQXgfV+0AKkq6N6NEfyrKdgMroIFOZabpE4PC+Fb0C8mBfpimgTCm3EMH1XluKqGlsZxDVmLMN3ibpALgjnk1F4uGMwSr7RNn7cS2Y4GubMnL5nA4qIwQsAVGMT+zmEVbZ3I5w8syPaJxnsD5pHtIWSVwsM8YTVjNrH8tqDc0hbJtR4bC0e9xXJWnoVOAfQlTi4Td78kJp0KPcucNxgyzuUEvDCmFPlhTCaTKdT4p4T6wvpBoUXp3UpJ1Ev7/AGcKwI/ooCM3CaXCsS+nELmQ/NgSyXT6ypbs6a+gbqXYstLwpLITMjKjvRaHgg2cG+WGrBMoOY6GHLXXqQplhBzFuV53OopHBJePZhmfVDWEuiXHvhsvkzJPNDmLSiSDiIZieSPBrMOfcPFZUcfdiMGwcBopFIZidsTtG9WX0EmECY/1b/bg6+ydk2hNVo7VfV+lXPY+k9yeN35pt+zHTJ+Co1lQG+I4Vxeufk6gJfPn3vw6al8IHeWSrK9+nPwy9DuLDy0K5vuQ/i9BgLsQ1REjp+QYINiuvCrZ/hjFT9mJzelQix1ErAtmYDG2ekVSfYMOIG+OVOsNx6OuM+hlXptwzYUz2YVPaXK4tkYhGhEKpfTmzNsFA7sv1la9bl9nmGJDJcvILCFU3qez8kGXFFN8zfT6oVThIm/SIVAWHuMwXdmKZ3tzIycW4WB7aGKJ9GHakq7J2G4jhwoKlCOdQB4WM0RXdD49uOGjBHADPKG+2UQl8VSBsGa4BpHjFxEj0JAolXcdbi0FDRFYHuZ5WrXsi4JQ1FXXGxFEBg8xVhziVGOIh3uCHuwy2/F90I2lL/Q4KuhLuEfQYXmnGjRZC4zBuLX6DABUGVxuHVuW4oziuTwfCNRMDWawgBESqlhlzV1B23hH9IMhA/V3+3B1Bxa5S0z4PMsQWD0dh+oMsdJRP2XrjJyqeUFbzOd4jIqXdhETc4eLj/pBHHnoC4azPnZb3t4eE95AElKnYi2w2mL9Y4x427lPbL8ATMGxhOyRkcUOQDlQFI8ImSRHJn6lWCh7qm5yquhvOEdc5UmAiFu0IVnqErYtWakOFw0PLK/JC5GSPJAwc+uUpYNKnnxzSypWRIRS8Sl/SYwe8aQ+AZDsoo8S5YRtE76M5Y7mLjDuJ7fyQeqxsrMeUM0wcCVrwjrEq70+RiBbBlVbjXx50+63BLCtrAqhnMwHUJib4ymfcE8VFyTlFAz3GHpdrgFZ3wqi1NYOJi5uXWLbYKA/kmP+FWx/6JFsdzashPGrD5QJaJFxLKgnlQyxwxzDFNXswx9i/wAioZe9bzLu/Q9GQwbkI0MUdkOOJZ4Q9DZmP5msIa8QAc5R8OG6aT+cgEC5Turx9msoY6IVbDEKN8CXKHpuiRIn7Tf7cHV8rAdsYD9Qs3CCY8HLGtYLC0BdD3gfikasfsGXprU7Is7kdpxL6VW0HlhLBF+X2sA47mtdHB3SkZdd7ZFNFifwGkdLbsMYl7T0h9waesE3GtdRFTbXu65FQvOyO5YjG7mXdv8AMhlTBuO32aJeVHrWbEA2aTjRNriWlzviVXb53bMcxWoFpRH5LD1i/KLfDENKTIKu9pXmMGG13nMGIs1jBZXY+iAvr7XKuH846V545LdTt9uSDLlLpLDHcHJNHT1DG9uCfPmVlnEI4K1BUyhZhcsfAGaimyMPoLO5HPnDyeGGQjM9IrUozxGTgwxQXE1wLmcumKVNSGCNSCy4yUbZUKmQ8zFzMZmCPfLEdMoz+XPT8NYuIW5l7guiNEbTAsjcdPswy/dQ0Wx0ALtxLfqgsDgDu9IVDkaYRYYWeJeev0gpEqHuxG0rb8kvVSDH/tUwqmlBPCjUS7unkQz6n2j7UfwErRC+mRLA7MaS+j0MGLBf1b/bg6H2LosB82YwQ1kA25lSGGqKFX6RpFoPkItRdzK2wLFsFYiVKHag/sDL0+fGvFWegmftj1JvUIsJzeM7A6GAqJIShGy4XoTiF30AHPKBPdbWc1GfJWFMjvwlZTo6uS0MYXbLQx3uolLO8Ph0R4vqdKgbUtxYxJcgsNnrMLgFkuatlI7OGI6j1sD4XNUS6RHIRyinVCLEqVNshkNtd3KJME56Lv496V7z2Pkly4tRt4845k6miU6AEX5DdMsaisXDUqAhfGfQVzKGoiUpK2+D5wNQzT8sA4IVjcDMg2kV+FRTtwxNsw0js+7MLKdJbm25iqpeNJreMpYkhmBr1iu4qmpI4vgdpUYolsMJHPJQIzaiKxb5iZhFeIUQuXZ92GYbaCY6mKOZulimzLwGDhwzsNRAjbQpIyxyCjn16ajvytr84TB51bBjtDOi2EWzNfnJzYcJkYVRY4EmadzMaHpmTv12I+LwpmeuQzQ/whcoHnq4gmLHTD9Xf7cHWz6Hwll82BrtUYDzZYcvWpUqVKlfrL/Qx/GZQ+gxj8MYy+EQyHB7+4OHxRKiN+gYtx4jBTIlwPuUlMCW6hl2Wxj42ZSBubuc28h1XPpkEii07ICFeNXkRLhLxcQwzA9ZMrQag/ZCWBXY3plf3M1kq/yYJwJvSvkhjHe4x7xSEPHHwx7wSbx+K4cJtmB6waI+6EdkDtG/xlHOlKym7vH8pyDKktETeVa28M0lxleWy0V7vKjZH8Vj+Kxw/wADFr/DxP8AJMz9NKKP6WGT+HhwfWyS+rlLL+WBdtROiECECHILJK124SLlyvA/HEdrGzRNdkj535l1mmY+lAOqxkAsuR/RGClP7cw/YGf4Gf5Gf5GU/Yz/ADM/CsfxmFb9LGc56Eiqe7PDKuca4EYipAMWYtoigvmdjGFghbcG4apM/Tl0ylR2VGzp9WBSNMaFeKH8kcxi6KxxP7oUeKOAd4QRGVZXrGfiy1LAaOSIYqNR8NqvuziAYg18FARlowT8UzqojvolcvqPU8k34Bi9FiJ/mYCvYl/6tpnaaNdx/wAdevXr1692ptqWj4lESiyDa4+gFVF+M+7hv7HeKG13qr+gZoLJVrilLXkuxOV1/wA5X1IpmVj9J18zfaLWB9GX65WGtBJXgA7/ADIUGDKFpoezbLfUaNjt2zj1mZIwYUu5BS4cyk0KdD8bwjS71LSXCa8YTZPRNxi4XiNoYTIcYZXnijxk07e4fid/pPNy80p8oXGc3s1/5dM+EXYqJ2hbVeMxxuyXLUHfJGP/ALlG9xLyGmFwUMKtC5jWaEH1mPxFd1Kcmp0ZWyOzlFZjUM1lnZgaYn6Ag3OVyppmfpHynYq/qY6YF8AzMBWbWig/Qw9tkmNTDNlu34VEVFg3l6cBxCrB5CaPRevy7e6qwqz5GWXXS09sx6M2Ww9FcQg3XZY/3lp/KhHYmAuWgt2Swxs2OMUWL9ksMqfsAM+RsVz3QrzVbp2oOgi9SRtJQxsbO8FfqxyNvHd2jsxeVkNfGt12lwy5jBmedYUzpfEvd9nRC56KboBzmHoQq5m6I167iVg2ga6cqkkiU4gyMZMvmQHkHMQnwsqNXtzFa7DCq2YUkApQ5fl4JT6qUEdYpqeJx9r0L2tg0id1lhrlh8XUYC/IYi13nq7U8VqMivDqTZg/GlU7bLOVl+ySpoResXJMjYc0pGULwkqpa/gyRNuDUReBssgwaWHjlKb/AE3MRo7a31i6Y+qkZis+DpgRebU7xYrno+NO5yC98Du36JzQQ1FPlC4oAQhaXgerwbZ52d8+121uH7ixNDD8TkmP9ox2A4TuRe+5jzDqOVUR7OTGmSS+WYw9INx/0PoWb2ehATkawhTD0WIYobf+omyt6maOOXfEn8Y8vs23FIrTcTC72wNXJxFXc/tm7UC0M9H3jjQGm0q3jtxKG6BNyYyv5CmtpCAwSXlkWwcKjYXGbsU4F9AWp4cv7ObVv4p1JH0F8bEWXAMnBDj6/nirdsRx1SQxu5K0HsY79FfnE1sXl6Ry5IbdAvDC/wDoCEGM2gyHwIey6vmMOTyx2a4JZqemAORsaN3WZ2soTFrfF1KuN+wPhIgPbg4hVCkPLaH32lq6LasAFpcziPjF3bAHyaYoXivxlPHSX45PyIiV/M6Pf4u8dnT5VIh/pfn4heKfcnUPJdzudsSK9ZvLKNwprrkg3AtQ+LHBUHsSGK27l35ZHX2buSu4tll8KmAWiOkbK3Fig91utVnQjV3n7wcamizjnahEkh2QXk02V5tZzRwW0DV1HmduYGCDCkuyBcNfouYipeYuqQw20alLJ0pYSldilqSNuxctIAZk6bFz0ZvIwy0rFawgStbLvDgaRkN+CLY75sBuwlf4Hdi8YdWqZVJKgpdSpTkjjopja21Nxfc3gwjWlh4FVbj/ABUsKajhYdNaY9pjB9UphDftEzKZWBAVxEs5sjs+zMKhxSqD4qX2EtqBWaxXvb1naXTRnvhnKE8WDAKN0hvrBx2Dw5KOw2y/41NT7p0HAlvR54imBAOehMH0uihCy7Vrd0qsbm7RtXADsw6t8DGac7igDB89AtnmYslGU0mQ77243FUN4OCaanqEt3YYWLyDpBwl3DuzWRlWYhQzzevuU47+HZl4uwJxIbmMuy2OzMZKIaW8F6uLKtIgpRC1ocrWWVqePY5s1dTG7P8A9gvA1LxfXDG7LdHmqlaJu0aIWgAlQVj21DVnVjZl793mLSA2rUpVNHRxrPy5Xw1glMe+o/jRLOjADydA6HXSy+lGIZVrmn/TfLXS5vjv5YujxQFrwSWILXjp9eFojCH32+8MMDr76F+Jtrx0lmn5SM/PUlvN7G4ewH8z2Q+sXK/d9Zxz4EPsFNb+BIRA7lAw4ubGRjuYoOoOtV1HT566vmv9JYAQaGfUU121e7frOAIvmPhEYtHpwuSvrQroonf/AFkYKhsieqCMK0aDT0VGJkMyP7F2XC/OXSLrG7djOrxTrSlwW/6DB3aW3fp4RB4U/BqE+khNhHND7PMPH3TzDZFmQwI5j4SNQYWr+7B8QUDUvC9p/v4B/Ywf9rAyuwIZ7/kz+H4f3Fiva/MxfoLrr1ekPD9Dt2VmNy+KtX8MCWPq+5HUqjw+8uKvk+892P8AGYvxhMb4cPT01OrhibxpEMg5ZvJkT5yN3tPnCq94OYxlDOUHxieqA1jpUX9KqTyTTJ/MaX+t/wD2N/obWTbsDcsfphgSVEC2UH6mfNj/AFEMABlJPQg2w6g1uJcbpPB/2YW/Sqp3gOsKwUpuArraCFaKo4gukS2+rNZT9KsfRzZ7cRXR8IdtBKxJzkkbZCZekQGus59ebYGoCC0ICGKK0r9s1Zi6SM+06w8g53q+mmkL6aBSaSthw0TuX7VCaIh42NsvTc0whB4Xef6bjNz5hm4TO9xkWKqb50Id+uGGWuA1Ly5SFJFwxnB2R5YKsYYEdF0Ya4hnoH8pdr5mKEOl9RPqfsV7TPvbmDYsTwF0QM3NLFYBwKgf0zADYx/8AstWIWK1BT/YxkQdvQZfOHl0BPYxlAxHOC1tmthI5WUZUrTS4vjGUlclEE1/TxlQ18GbPbjozCZ5cOEOrixZmQ1vlcM98/pKoAsA/wB1Dv8AcmT+eQrrIoZne/miEkfAqQKr+yX7pCnGD5HUQsfnhQy+qCjqLYfgEVnyrR7T76f2Rsf85dU8R073ESRJbbGpa3DG6AC41QD5QxygFxf6Ird9xdPrPPR37MXuRxskzD1r1yA9HOQhYcGgg4VG7TxRdEIhX9JGBrOT27JK65CkgxuBqEYKUMzNlBTlKqSSicPYXLGw6YyM6Ey7EvaJPqJ9T9gEJ5nPnfmmQmfU2/SzlAiDJCrBN1L/AMBS79uZGgiB8uhzvoLZ8kO9+SHafLLPs+kB/eSUhhAsu2c56DkwbdlniIYIG7kXUTgILAOIUwA7JoLgHRw6oIFOn0ENnvxAQku6tD08y4XZ8MRURDmjW4gR1Cdodh/Pi1+Zx/m5+c4Q/sx8O5cG525BOoQXQLHyb8I48KGouGC0YUanK0/zoIyoaZfn1dsbYBOm/kySCfsg9SX/AInfrFtRPsgF7wK5MTIs1ayjTcNgDCqX8of4Hm1Mu4cq4MLxmOMf2ajOQZTAhi+i0IeAxwVEyoMEkENZUBYBm/Ooc6i8ZEgIesL/ADwB7YpUOAYS8cm/WGiXyVMuhwGNu6XCOY9DFPrp9T9g6UomaTC0wD1gYyFjZK9BGARrmG/OwRjGz8//AAMKOeoIYGOskIfNMTutS1KpIRpRAIoQxnmFSgIY/jNRfW4dR0OVdeiRgwLxkepBGfQzf78RVkCJ3QY4X2kNod6/3EOobpkqf1uHSD7j+Yd6HfhXuF2lXE9OJr/dTDhtXtuIQUknvetSrPNhaYRpk7Z6IQ340ChvvKWmlSJ5GP7b3uMP7I6fYJVLT2+IrsC+cSWBzxmhnbhitLkI36nuAPCC9piPcYsL+1SAztl4LTPqjkD0HYyajcFM7ISDFixzQIM7ds4U4OMCjD6zVlraAHvBWuBX4x/H3Gp5ysw3QMNYXAcwQ218atNyswAkODMvEA6+0I/TBB8xPqfsVNGY1DR+jECNaVBDQEN5JztjdDMrQVtFs6og2Y7HJggZjx7P/BcYnQXjh0adDZEMQS1jmLlcHvKbOC0INumlCDyQ0bkYDpuKwrhbCWXcgx77dDhLSjdeaQw7ih3DsYklxvwjnjcxLoaBBv8AfiCYg9qICvqgoKHPZZaLzwntKz/ipetxIe9CKRGZgMaibjjF8uZrdLUuofLYZxa01YrXI9XJRLzIpcEGrBHi/aKKf2S2p/nLEDsvwlXBJ/ERvSuiBbizMbS9mz6xAbAT64XtO8/atRkmLUZ5Z2At1C9xg2wov68Q53DPiVinG9R1NMJG6IeF6/jgeBpYmHSKkQKI8LZ/bcJHuWQsbiCVctlL1Om4EYhhcO2ZfRivdfPKO+4jgEu+NPqfsF49im+T4PLD+VZgIMvBTTXMGwMM6F8LrR1ViV1CsNrxEU1OP7Jt15f/AAXB5mWKqu+xqL+JzeNmeIfSaHlXCL04B7+Ite86ShjClm4nfIsYWDIIEhgqN5c6xgQJXG015Zu6yZgIu7+dfNlTp22yaZa2bzeAS0PI1Av2qiAh3gXVARMdw5Ms3XZtRFlc8qiejS2WSIZd+ZXHVcG4EkuwK/oMMjOXyjflM3KGmHcS/mLcoeedqxTvl9eiZLWWO8CHtq4sOYzmUA4BBY15h75SrFUGoHOxtzJHY2DORvIKQcP7Jce7E8VQ/DP6TEnAWlW+bmM3AHEl/wC1uBYkOVeR6EWj9UzasGSCzRfoLLkiFhifOBkXhA/qwb+2DQfH+yHd6epDpU5rhqWmTHvYxGS3uaaCVbKCTOZ7foL6ES+bLz9ILPQNUD13mzf8xm+78GX8bxE7wTpbZxuWKVz/ADEJMQwJYUt5hVR4UqzUeh9ZygFgM/i8FmOg1QYL2N2w8T6n7Je7PQUHbm0eAGo6UNVFRWpHXpDsfY7qZ844lCb9SX98ENOhb2E8s5X/AMIUcMtVUy3Kajq1Oel3guRA4RlHS3Co514gKjlt1b4JTaEXy9GevsSve3TPJKiApK6+SYeJN+ZZFTBK4lCmP6nR4dEHaYLlByEPaQS8CYZbTsQQACuWiaUzb1h9GMHXje69GM+GkhyRqOxzT8ZVcPl3R+eVrcCO5nzDSriDzkkiKu7NUuybnTrQ4AzmI5XEd7naqPBaKQ7If0SCEeoFT9kNmYX6Jx4xXZZcBypbMy2VYSeWHfGuCUu4Z2l5H8SlaBHtNICF3ZQbT44Re1wsor/aKQq5LbQOBAM6CkgcyzvPGAEDQbBC0J9nfH6Q0XvNPhFkp2Ud5i0eMKmKWGRzs+wfCMg2w1Njccowyt9B0RDnA97LL9LfTqStwDFzoQl7XvZVT9T9lIwQ+OS+62rDEHWnh9TT9YuaeedNwdboD0Ji7nkH+0FEcL/wTgIYpK9aveMbwrLWxCfSjEj4SvQG6c9R2kG1GOm4Uckr9TDwAs0U13QmJJvOm7ZESz6I7kIW+N0d2FWSLxJdlTZgd8iObaTmwRFwHZecfgg1gOib/RHoaYh2/eIbqzNu0Q2RVyKhQgK4lO7mCZchEYtx9Ky0Nlhi7QZcmTsq/GewX1ntK/mBe3fOF88S9Qw7LDMEm0Q9x/MEhhnN4/nLOPAIJnApON2jKz0hp0K6VsZYI+kaRzJxOPEfT9kQc6AUUWowho2nM+xigEdvJWyHas4DrBC8ah2OhCv6rYdhB3zyyqjm/LGsxFUdjcPclPGduhEjb9k1w+BOwDmHcVhcJtn90QPawTXC+fRyqi1kmAupbJZLUFhF729Bm0hrPadLb0o769CPLbJbhCzEtQl4Q536nFHb6kx1RyVoyAxDwQNIc/pM+p+yoiN/HXcM8iMigbtyXQwmi8PAE8zPykVlLKQn8g+TEURXX2/8Fwx4btZtyQffhdQpNUer8nvEvbSBc/ae0WB10v2/n2LiF/A4RewVeSCAu4hibUY3YYvp8tslDQiN047wJVVgsNZeTG2MLsvsRWJ19ImzXVAgqUGzow5XDGGeL8kbzUU6Qfc3o2qST89W16RMTDIuobtklZwNRV4S/nE0oiznL0vR7iBGd/DEZiDG4L0MoQ+sqOT4FQ1MiRtVpQqp4l7jukisKnCV0Cv4i7RK9lkpLR+yXpteSOJ9TxYPLb5qCx7GZkIeAylwzj1wO0zLPf0RymVjSNQEFLthrahxcQONA1EP1pZP2Q2sijK+8fzENUhW++I5ggYYiIgzVZNS26jm4mPVbYXMtmyC3oCx78+zzPhKT1ZYbBaV6EVfFloxwHfeEaEtScIPLiSKrLU8l9oI6Oo4AEAt96h6aGvv1hH6n7AQjok5oqpU+SPf2hd8IfWFx26UK3CX9H4jphzeH9EQXpiGFXTn/wAFx8JRS5m5DFMLsrmof/B965MDXopZeLGGTVz+ig5mXx2Whyi0Qq/hR+kyS6xI9jHQBzxayzFBES8LqVH43yntCiR9j5/Y7mC4mV1/xQ3Lg8qDiDJstQv715YVF+jiPSOgr8OUuovhxRydiqXbw3q1UKrjJhrYgx9anY8MX/Flxvjagu8arthMeeLMSO/HZbkvyCP1Rlzj1O7od9TY91Mo4IKdpXjRFMwoudxim/60NBWef2R1rMy2lWVnNYzLjGcR5Yqda2zkLi601+QpT5TT1J7JK9L5MXeViy44ySjVHiFaH1iK9tzu3EpK31infsxnxE4x3hVjR2kN/CoO9S4rOughu5SLq3G2yGYxKL2LHWarbYMdpsXLki8QIT3gQNx4VSsbu1AsrNAw8jQwwiciL1In4Y3OJxSZp4lqEHT9vBKzLEuzt1D7QKbMNiBR9T9gzXI0aHwxqPgZagI4ZUoyeeeYK8AIuuqtQvGirzxrbafwQBkQPboP/BOG+GCdAS2Bw0sc7uXNpZJvmM+D/wAxl+adiPZi1LAn7uQZ3lLoINMpeZpihTf31Qb4MvhpSJA8nwIy/wAbRO0vky9VjJUM9L/ILNFNEVQkm59DMWr/AE4BBWUyJoP5uW8abcB3lIk1ZsXe2Ec76U9xpgOF035Qml06Ji5A6r/SK7ug7j+AjqC58zbXLO7i+8YiJ4ij47Qw0iXwkvTPGHpl9ZGooc9q/sjYeLZl3PTmNp7+RdD4CE2dgQBP4j+lnrAWgVoYJxCLorhgCDb07iYjcPk0Moio7UEa3FOjFyk6aHMZmCs75go/L6n7IVaNRciQKqoSqqo/pyAbNyMLAa1Nu6iBQZoy1UPwEz/Fc/MPNbNyeatwWRKPqwWNTryYHrDdxbD0JVAtjBiJUxOKwKFMOltJgfAxhmwvEZqalZyx9Yj2NwQsZ9CPqfsX/dC0OSV9Ao86lYIF9SGu2QbiA0FdSwPdAZGhC2CNYiXRE4X8jf8A/AnvzsdI8CsKY/jHVkKsvJGNadvqwnL+cC3uJD96npQWbwMVN0nxIecS1urJxonw8kbu1RvBbdnpLzyFDgmyEvQCUk05YCNEe4DzEdGiEjBjH4UMNwFX2QAqBMsH+hMbe6+efKBKHq9NARNjRGo5dg5LpfcX+3SJMCCrMEd7At2Eu9mJTwTRpcBeY3N7ylhkqgEgMiLwLi0MDKpvdzn9kv8A41TflIHgKlbJCxWGMS97V/E2NeEjptbww3aWsNNy70R6S43ZZ2zNWFvGtPpGDKPXdKh6NwX9tWwZYShevnJdq5fX9kFmt+D1Y7Cy2YqGQRCJt4hTVlkeBZdhqGmrxK2q53S6pdfHpoIeLi0qNs2YjRzV9JX2Nrs9oLTK4jtHGGNLuEytTT0vgjuIMKDf9MfU/YQkNZFsXRwCLzE4qo+jMic/HNqF6qeMiXL2mg3Ow7qjyol9mxEuf/geN7nEFrWWWIB6FQQKyxC42GHxEIgZxWl0X3UGvWV6yBYHqwuvtpIfSOfwt+0NURbpdrvDkZTyPoQ0Nz3pxkEXH2SCAFy/tgTcA6Atje6UHKOcJGfxUd1awb0dmLT/ABZZ0K+lr4RBhJONHwiCwQ4/aCRrt+0vfVEpD9mccHi+sh0hexBpegGRg1AI12MKTV3UbuqgzmRGP1JMJryEJSbmIJk862sErbHuZmxl7fwLEg/Z4UMPebnwxQL+u4UN+z6qYz4FxgPjoh9s4q2VG674O8yta2MdkqsaJgC9PVbg0bBZaxE1XQaIlH6yoffnr19INdyhtYc9yn1fsgiXoyzDVmNC9lSqE9/B2MdU/wCJ/Uf+nQJ9Ij7OIV8L8/6hnqTC8dd5Fd58Q+Jr2XEqePhLDMnmH8puYwluWJC0dEQC995laGFFwc+kIjcSqMUHt1GRvaUDK6jUstRXTUSWi0Wi0WjG3yhfOU6rMsRcNc5Rgm0DOYKeyJ6SRDjrpH7RRqpmFOnoDItU/wDArXwQQZk0nAC6uX8BYwfDhEWqtctD2lY9kWWH463sYBCN2G/Qb1JW7HD454fUmTBEB3e7AjVksLYJEvjSijkkKALtIPW65GTNVcgJeJeZjV8Vvp4VKqyozxsI2pQEcq3Q5yjSHyYG67xGAlOddWiSGhBc8QG3wPASuF5I7qVRi3KwhSiE8sPOjXdMTOlAXTD6AjaIFoL9qkKplmXK2XGWyPTbgzpKE5mF2ADiR7UM7xmuRUrsDJGyny0Hc1xW8DYF1E2lK0AOq5d2mqTxFTbDRafjGe9seHYGCvyWI3lmp36k9OAHduIvbgR8jGKZnKobUBfYqOfZmrLi+GPLSpeTsj/340jXRrrIVVJDssmHZPmia/Rm/wDXoeUKp19VfYj1nXvYzs8LWgbSht7ARGrES+8K5Qh8qX0jG+yYujHaTXCytZ2uMQtN2zWFmVJWAuyNlWskPqIge5+yca4fBm1dEHIprhbNCcBwQWAVuta1AyZCKbcgV7HKpuSEgCLNa9iDhhukl5Edo9p5aqjZCCTE8FYMbxSz7Ep1VxWCao2tuUs/eJMRbgMOaiKoI9UbDw/5Agqma7ap3OpD6Mqqjo0nr2mDL6YMM5Ph58Y8Ol7WB452LdmKF3EUpiBGygB9EiYafYqN3qg0HoEw/wCRuw42y+Za2Ci+Ri8L+o7JCpoqNpt+Asc0XgIOK2eJqIVbEWgOgLtYrKPSG11Ad87IT6uNkAffm9KxW6sIHMA4aKURxUqVRQbm02IUIHeWkcNILoJBsDG7YJveI0fcWEMuv5WiLTXE5Wga1ofWBmUJVZdqslfxev4yhey1VRfLZGGbW3XHJ8f+BcXVblm13JbzIy0tSsbIMRgFvVvrZczN3iq0fUIwLEd+W0GtQ1ZpHXB58FG/Io2uybayE92G5bDl2TH+BgjMOTyzhfVh1VuawA/Muoq1Clq2XvlSl827Zq0dE4M+8+kLjJiepFPiy3Ewvi7zlef4swi3XfGx7ayjKrCruZNpa0O9oZK34TGO1EqMR/KLdYCCQCuysjO61q5Qzo6Lwo+OIbc8Z4VtdZN1FC54pcVd6LFbkXhaafCXG9AtwNKX1Y+QVWI1+hSZzjZQuhrxeJ4LuYvzg6Fve8/zE/zE/wAxP8xP8xP8xP8AMQ7L5JdWK4pgmX8xh/ibsiLEFbUitly1FRZMsWFjaLiR8LKbebRL94GKDnHlnlnlnlnlnlnDRbZzlyBAWAYNtccKJWo74qWV/IS/m0wR3i2pa6+0WfMI2PSudPNqIWtctAu0MLBszlGRSbKpK3tqDT2sURHYTyzyzyzyzyzyzyw7YPrbfx0N7PEDUk2u30EMHJxU2XcK9p+iJYFWmJ0UIuv6UwQerCuZ2hpVSjouE2GI2ua9RqtKgrpsirKt7IbV7RhliJBuuGzvwZaX/wBsgHJMY6zYop4JP5UZTbHDv805N80N/YSrs+aZht80PlsG81AVEwJ6w4NcJ2ZF1kRLDWBQQLiGvcbVDyIecVccNYfUi4F2rm2u1tZgWv1oqsPIwwujIqxV9KZIkpBiKv5HLHcYfGLZ7pIiqaxdmPViYw3ltCr8WmfJNypjyhoryocgPSiUJmVcogMsbaiZsewHta8O0F6xaxrpM4x+Y8aRWaLh2CsdCK2dUu6GXN+UcKjQtTgJw3G4YF7jLhhGpungBnlnlnlnlnlnlnl/77ecVW4NV8XzpGo/0t1LSo9JLA195FVi6ejkQ/Ti8eXFFyw836j7r9U4f3Wau0jX6B7CaxGCFHqPVnoODvoNC7TFrXZ22yoyuRaSvSOyerwJy+UVyiXkdkO7q3HTqyNP2po1VcVNu3ajtK0Lr2YxZHYwXoUIQKJ1ahrql3Nfc9E6MGYUqWpjvXNCerX+m76RC0eGljT9L9c0fXrqP6wvaudpXMx87IpQ2K3b6QjYaFIHP1559+fHX/rP6JfR69KXZmT62l1nEhyXSAvH2LieBiwzWowuoZxyY0kvzXSo5zkQq/wEf4G/0A7rpA4MHq1GIm/TJ38g6fyh9iI/ZfaP4V9oN9l9oUsPsxCU2hSP8jEDpocHesnju2+R149knFrQeMbqe5mEG2eZnmZ5I8n/AEsLN0zunzwaeqRc6gw7Xx09JbMMdJG5Y8mUNot3FuWbkx6zOGSFWoMBfsSc77qJq7TjJXpHNTA0rh25fwWG53SPecoT0msqbekbOBX0xhYhQ+3SMBow+ENjwIFxD7Q+0IQrHb+6eNg1Ti2z8QmngFIUK+V0fR6S76WD48yy1ujaD7cSPVt2RZkOpMIIQQxwvWGdk5dLcWP8S0d56VLCAnMt3lurnLSsj0wSNKzagZ2cQ2doQzocGGGwNfTFXDO3ZV0w8C80VcEB1W4fL1M72GMAcU3TR7MRevsqTbLI5aQ9hLwsXJO0qZqmDk7cPxtDlixNIZctMdxqoZOhMJRLtKY8u6TxS/dLuP8ApO02S9Y8R9T8ZHc/ozl5itM30MisOXolUMVSZCochoktneQg1KMyur/jPuTg6bJcvrHT4CTwVB8Z6aiVl2kATfCNfhm5mqXsPWmkLKwkmmbTKGVgMEiIVA7Q4HokQEvr9xI5ClzDLv06bLJkyMYXG3JsdLl4CBzTFhYPOwhHMobgR6hBfvZXUCo9RRM8ANQaiPW2ONcTK98ZXYgdmVB8Jnt1NhETFEyyldIJLdKuCrWt3tLjM8w5+TeEW1zR7S/NdJ1W3xjaINgG4yE9azMb64lfpnwMdb3Jo9mId/dqURFYbqHOWZm9S/aHMlS92XAgB6xdzZwIQMe2OsNXmRmIipB6YmbZxmB7SriBcf8ATjZtljMczs2xXGvoDT9IRyiR6zL8eYy6p885eUV21mL41mWojW4S1kwdzKhMaWxxShzFzV7cS3uNEZbikMSmMLcH3huOvDHbB7qw+Mdqx+9blkgOeaIy1FfeVnktVUe20sY+o9PnGSQjpjntfJB0jAdI9E6TN68G+kvTtCa5O1bcPpTjk9i/1ocvs7iEw2rov3SWNluptvP0fNYEcVTt7JTX9yqGTY5GkanwQIfqpNI+SkraHYQxKuYTTkE6HSMIemp4ZkWcRwjHTGWDMdpXwwxlDvOCg+CDKRrgPSaPZiPZ0Etuh8joUMhm1LkdnMx92Mjw5Ye8yoTEhd9Yh8zHLznZU2gsQRSAGobmK2zxKvwgh0mah/6bLm6OcxdFvjuHhHLb6QUOYveUxofEOxMdS8hrbBMs9bQ4dg36PwTKmZKz7cTmPfRNOJShglwY3bR8ol9aUjo+eEKmQ3u0IOFZVX4R4yuruk1ixcwQ6RN9EiSs9AQUnufJDN+g4voXQdDCGrQy9jXllVYHUVMQsCBj24k89rKwjZRiinZalN9HP5jONtMWjgqDwjqsKp3r15EVTohBBBJ0SM+W+Ih0OASrQHJqQdRqpdfHF8x+84bfw3shBDphgwwtLN/KAvDwYmPmxTR7MQ73/wAJNejdKlvCbUvjpiWNPDT7V+OMCrfIEyPutxF4LQ6z18qdp6Z3gR/VDPbY3YHq2JvFTdn1wKqGFCzP/wBJUzfE2ysljLJnjydMrPpEpO8U88zMmIIh5gKQ/PkhXHCWRUzNRdcr8PSGUxx4jB9uJz/vo6XIh6FXpQ7oZvTPjUYh2EcPyo0ZDNgeZzsh4CYSkwXB0omgZbmPtWaF6L6K5Ai43DBUl4vuk2eY6xOtSTsxdi3sH9reZ7nyTfqOKumoSYxk22TTysgCG8zvOix8LpirDEEygGM6QiifM5b5+NPSm+tM+Z3zxn5GfIoGB/QgegPoGauvpDYcjeCYP4Wx0VCf5iCh9gzEivPO4Xxf81D0s5sgDUVo7hHUThA/QYrjaWNHsxCU+yEV2nklydCOMzOYS4YqyJHbdiFTOOYfCW3jeojxae6GCMDA4jCIrrWiM6U+M7XTgyHo7lG7Ohk3pgDnpG8Bv/04ZTc3mKJrpZ5nI7kMfSWuLph8MTAaJi5E54kPCV/oGLv2OO6QmdSsy/pF4MQVIxezEnP2YlR9a+dlGThdoXP43Pj0/JUu95Ese3dSk3Txpj3U38S4O5RiXE7H0uLUdpNld2zHD5wlO2Rajhk5XZ7s2qFyy9Rg+hGzTLDycMz6Y25s9uSPMeY+ujwKMcJKp1czGFqgJhywFykuS1ex2gV3tUxbCGPyghnX0U9cAL1SRtgNaLgm6Nx8t5I576rumQxKa1skD5p/mT6J06wISHtERk2HsY1h44gssD78QI4AznEbSjSwU29a8HYiOjLL9+Y5UVU0+kRJZ93r1Ej0Mm9FR0Tl1D+s3fWEVFLvUOWO24gzR7MQjezB0LnDrBXMc5er1rjeDOOEXCpkx7vogQUKKIYOSmoiPEq5Y3BxhN1C1NQhstxwfiCE5nllWUf/AE45avRtGW4sdo7PT6oYWd4mkNUFxww4hlI4/G5UD88bKg7+IYl9qZsSpJVIKJXfpACuvpx7DxOf6Kq8hH+0tfKvSy9VDgXYhCSz5naHyuuvD0tc0+BMaOz8dpQjhN+lVwYoDnDwYxRyvTRcbJ9WQd4lQTHpVnCI76mNJE/KDjMOzlSTZ7ck1X9sdEPKBM/rLPWKQNsOroP0j1LbVf4JY1n56ieILahwQgQZ82R9OKFZU4Sc6oA+WF061fPFQk35x+ftsz+6GqjODcN9AkrTPzyWGl6HS0bIQBAjSmD5TKV+gMeIp4R2qSVXPMY3sPo8enYmphHMvsO0oaUWoxWpCyCOZTnWNj60EW2+6a0nYYorejVjiYU3rEGM8Ps2INwzGj2YiwPZREd5mmBGtL4VwM2j7oyDphpmehsjncXXfRIrdIexE0YITNDaju0lGNEIUVdiIzQs2QAy9Jo7J/6VvMuPRSHpcPp8h6TGYc8h9GViQX0Ll+KFL7snZ5M18/SsBwS0xD+NB+j0ezEYr3YnSZ4YIHfYCLNbxXTzt9YAbabitqXS497YTWUTsEwfD6Svq4bV1ll05/GpfLm33l5BKW/umMIhlNTuki4fKMbZh1HccTh4tOKmeMgxNUVQVqHSEq4ew9yGvQh+bCkwUjSEpdYW7ZQdoXVIoKhW23bWHxlShDYREXL8CZCdShOzMu4ABj4JeXJo4olruxBpOSHIexxHdpCc5Fw5peaovmX0Sj0C9weLi94fGXuwofCafTL2/m8fzmNsrc7QzWJDBLVZdNUP9oWA8FQgYfH0O+blKt0cqwYBqrBE8Xei9CGg132n0luF9jAMtFpLo8v8zb030b5eqDXHqtSzdYTR7MQ9MVpGrNcURjN9DOaE6F+YcvKlzX6tc3jhbYzlYRGFPEmAtUDlinmdJc3iYxjSHjxvwh0rZdkwpFlicZ/01OZmKyzpHTOzEfGmRj+MxT2VUdsgeVXDG6wZmBp6eGshOEjsQjPIW/HLf0Wj2Yjd7sTo6L0hb6pR8BmdkC/QhjXoWmViy2/WXYyfgg4KLc3xTDoIiM1geMfpH3FG2qVI5iGuDzJ4US/hIdLX/rIub/PD4Skg3crpu3Ziau+AIbgpGhYS+Cww0zDbuN6e7K8Kmy0dP25ItQu5yEWkXdMIpTJ1GYJIoAiXeiOizGH27fiMTQ0fCS6sNdxHLAgIPVyOiiBbjO5OetQrXARmykpmX+TTR6QprIOMj9/WRhgvUZjf+/FjNwEOmb7x1Qw/RCn9Wq+ZZ+y4fHt9kqJaoHrDnDK5oMCDRwA4PeHfkxipXvovdR/ohVQrylhpxv6q8lQzNtpNHsxFJVKjUZZKX6S5jdHtiGh+UTGQktuUh71inkxtCVcU2lOOk2kM4lA7ymPx54l/ipFzUjJ0IkChZLzESstvRON9oHpcE1DRjN/6c3MufQ2i6FM5K5fKY66fs0CfE9Pa8JfcBD3FBualdIwx4mT/AJIvHm6l3gneGjKGaddHsxGb92Jx9Yy6DOYTXhIRmdcLR3WEh6k88G9nAh9tLJcRhXbwgnBGeU948tUPS5qGToTe7RDIKnxBSHNa+lwbMniEJeL8w6wPk3HDcFZb4x9rBG4Ze2BiFqnZreqRjopWbvbkjjhI4mxoJqoHQUOkkJgRtg6mu07Zjka9+8cyWiRb73IAMuVvyWYqSzNSWsZZx683mnb8WHdgy/iRjU8CbrdlulzOyzsV2/G+g0bbSuVTicerP7o4iH6NPGwyS99CmKfp4KSi+BsvdiGjNwpb1jbdEcWB6yqRDORdTXdRKl21qFadlDEACrFohXv0iVeilwyDkcoRTtO3JgOjMcnuwztFPHylPGO3TTKNgOyEHFXCRxRUX1RMu7o6icVx7k7woIu2UmylvEl2ctUFEt9SPLDNQKZXDrjF/wCmlS99G5gj6eLDiojmXlHQcymBwzazwsDf50SvhlpZyPeLBlQyuFtbZXN7x/mh4zFj+g0ezEXP3YkQ9Ixv4o43Mx1bht7TMRKTwES/9FiVStQjolJtpC3rlCm412S8qEnIr0iWI3f7AxTjBl3Ig8OKghqVisipfrrykRhz2nKfkLrBXBXsIKl78n6HD9KN6a2b3dhIqr7U7xp3gOpZHojgiVlRJxuOUqvWObawzYipug0vdRkn6i6Pfbzg2H2IENYq4y1ys7ypg2Jc+gFSCTHqAX1xjkUaY/Ao9yasYXAynIg3gRWeYewRR9Ny5z9KmihDNrPZgMCC5X0LPxQJn4FxXeHryeqwbYy7aeCGwbZuhB886ZkMV4cBp8fsx7SkLHLKhJCKjwndbsFetB09b02wwOUZdZzIfh2zUEv/AEo8vUtZmkNdXmcP9CQfWc5ve5bpekC8/LxXHyhgLDKy+eiokVsfRSIONJhNXXR7MQLfsx0iGV0Dl+mWVg8YZnOivdjMg1CD3BscNcOPViPjlV/IlrED5dTGit34BKtxE8oBz+MlRjLkocpkaQTxVjHMW8zHly0MvZ2msYe2I6fvyfo7JJJwlYmGRx8mUFPDSHmtARi4GNmLyHLDlCFqx6ChZzglYmjMf2QY7TY1yTcv/iFd3iaYe1RVFiMUVZZLgFKJ8JXugfEj4k60xUlbwi2AOIyZsgmEYNdGOTuYYq1gjYhKoutI+85WC68+j9KVeG8B3K0pV9nBaTdL0ECrnVllgVvMQB2RpN5Q/wD3n6Aesqp5ya0ZuVBd1GIQX3cIwK5jLGodk7ohFKspYS5m8RmsWlA/JKoZlSnAIo0+5GWhO3xvDDonX8n/AE4kqrQtYDUUt3bx895n12kpRbQdjp7YjTdKvo7nNgwLOsR24xQ7wAsmaA8qqgPKy1ICLLCcdgRmaVdATT4lN+YkuEbjG6Gh38QmU+WPzpxCFumXZMF9yXj9Fo9mIcAm99j+zcqId3Goc6OErMHs4AhQsyaRsiT+hLhWjw3ORqKhQHiGv8dE/Yxfjw1NrQo2zFiJYWrZ3MxD6CFRDSBbBio5dSd90SreXMquAXyz4vbLXDNTSYsDBRalfKCwxdqGMfOG7AMLXyQqK9M5iZVUztYpEir5SFx9nnXIrHMIwotNthHYDseDfWGsh3aSxtWa/h3ikFvCzGNpcFQmOlGMLldyk14ip7qpkjK0GBo2hunxYmr/AKOpR5q/SjVqQdag4kuXexQJyInbX5GXv4wS+uQ6gaXXmotVp+eZ3PHwlopSI3cGIdbroiaLcBH/ADIfbqf5iXlgUuweBMXdFfQ80CIqR2pKfvDAiIcnMDmYZ4Qa0dys+Vwb60aLpVxYsYRRMZdnSMKCP8591roBFiWVo6UbW8ETgnNla0A2rwS4ijA0sAQJO9kOVZU00aoKIweYmjxTUdZ30jydPRY+tyVc5z4COc9iBJouwx704ro0TY4HDdYGjyTLtWdu0qtLhCz2Gk/6bAs9PQ28/SVzxt0UqvhC50GoehpS7L9FRrPPkzvvIyzlB2wmAthmXm0JFcDJBE8bROcei0q7IpsJxb7xBbsyTnWXSLNo6a1cngDZE83VWRDp2hcg2KA4ySQlIh3aL4lb58zG5utcK1AyXULyzND8qeXSYmLW00Gvm8LjQZA3eVwx87MrnyPpmIhgKgavLlQYr6tHsxBc5eIIUlLbwKOfTtKOXvO5HkIdtN/Ucuyj2JOSLX1tVWm+SJ88WdWjGpwcVhM3sgtUAW1IXhisQ0OwM32FeQZRIW9cBVMknOtblf7yui6rFwb+COFUolgdbDTTcBk+W5QVdDgxeSLKasWMQzYMHONbCBeSFAhTmQEpr6ggtBK2IPD6T5Q8/FZpqRPRDdZ50ADjHtvEF7vTHXaWIK+bL1TQQ9qY4rAbzsCYH7N3JhZOK7YQyPMiWiQuStegDWDwiwtSM1uwtNXBU3QSXgsEYR4yx+KV8+g2pnPuA0IhC0e6zCs1FZo58pe7Qg+UchR2Jqdz/aZ/dD5rZD8/QRaRqcpPW30QuXoaEfLzGkf7woHIHnn+mORXaZwNp2u1DsbTt0VVahqar1kqewL5dNecafldGMyj6ZFHgTVdsd4vess164BAYlo6tQluvAjdGdUpIr48pujjt2yOeL18YaU0JRKh/By1GZfg01ZgOGjFzL3abZzRzu9EtEAf4CEVV09BTELg4ajvScpDVqX59FxYrZtLSKgwKQRVlUYIi9cz16EDyX4gAyq8BAcFdKFBt5cExsPdFKvgIYx08YFLpFoxLG4eeMSSO2jWu9d3LzYqGqVnQXByM4u6raoBENZKLFNZECPmP0c4xWU9IiHmGBBKj5gU3JNDpqULe3oUQWXRd2Az7kmtkcFWucoaBODFpoOIYlNAuOE4lURL0uY/VKvVUIWNpeWPZuoTnB5gj4+t0AvB/wBKy/NvvP8AUQL7z7z/AH33n+++8fy77z/Xfef6b7z/AE33mp/K+8fut94v/YQP+wj/AGwn96ECLDoPsFHmPn16M1jG6hqunx8LXWBEjmQgGze53hEzTbXn0Z7s/ue/P7nvz+4t7z+YIGevP3Iq3EGVEF+Cbg/lngnxR4SeEmKqnxk8ZGV1YyrMrnAJ2gcYj2aTpuWh9ySgY/E4GlKJ1OvUTnh0bMTIyrPuD+57g/uH8YVWJ8Ynv1biryqxyIAe19BFod7v3/CccLix2925u6ATAuC6mensPOSLs30egEFg4ZYqGL7qdr3YFTu81rTbTHGLjZxuwubg8zRBF6WzmWSIsHvz+4ZPafGLVADgAK3ySQhEHoIwLXywKfALIFQz3VPfk+cC/sPvP9195vzbfzOmTXx3kxeMTvlIzElUTS3jj+yz25/c98f3Pfg+cDKhuQ12t1GPkZVwnzMWfPrLVerHe3dTI8F2n+ez/afef5T94PCtnYj8+hBFtUK+8U5wr2MNHObn9xs/ees9+j5zfaefuSsyFhqHpKFL4EfyoaKqeNXQ/dbcR2nq3oIHonBfeDOU8oD/ACRAdOezcJ6AYPrBcj3j6rC+7SletCH+curp/wDmWsptrO1+BESDDfQolLZ+3gRF2aDmujYpBKYB8j/x6uZJUYFLdSUpzR0x+2t/a2WO2WegDdKSFU4sGGn9pLXeIYOQaQgawbaQ/bqXlWVs0Ty/O+0Pgi95+ZHJqVI/tPcxHRO6oDvqW8Uqb7YJ7k/YrzsoGqdu8w+yGiEzczSRv6A36Xh/WTUtJT4E9WSz7il1E1PRKET9k+QoUFvdnF6g/pN+htnUsUC/t73SV+4KApBdJtfpgsFv/hG2Bdi0+ilQWjS1BI8D9Boj83R8Q8ENAfi7PgHk/UTpjjRINaDmiTQnUN9NBOTapiS8TvqyryL95edLPApZOIuxElcW0ayQjGIMNdu8/tXUwP7kINRu580+YIv/AD290rURNYM1IeBpconFYXqajV2m6/IsGi99YZ/SJfMidF3wUV7X6/IsGi99YZ/ZKt+UpSF4Go95pVFMgz2Lu/QTYomStWrgITL/ACC5db6V/otrq9otXFu42bfFFFwpXIYVD6Q3ITIKdAKj9XhvK4tLHmzgXwOKFwYcrNzg9teGOin9aR7pvsCaQaHwm+0fpr7CC6AZE4vKG6TMOJrYWZIcG2PjFXya29NIND4RfLIJ/W0eqb7i/V77w9DV8ZhbP0PpoJybVMSXid9WVeRfqSXpX8j8Opy0ReWdOqn9aR7pvsCaQaHwm+0fu10MC8wewftOc5znOc4y7+zZ5P10NMAFlYNAU6sibRjrV1t8Sn7aU7W+6DKvpe2dttndxTiCqmAwP+JqT4fOFvaXSckPQCrFNHvHYjtHtgjav7Ty28ch7w94PFUoVuV85FFGKmz9oCTLkTkSXOWFdsESoL3KAR2aH7dGNQDYIflH84uhpKBmM58xWW/OMYsA7W3+0FzIzwKN1JSoMPXk/RwN5gkTQxskbV/W0IgKrTTqQxG8SPPTD+xm2QdrQZVkY5qMrYV48TQKmc4gv9mvfu3QjffMJ7boGu1lvmQgLK1+2F6KJok1UaOoKWh36TR7iEJ0Fp1f/DUJaudaKe9x6NG7t5SlEN1epUUU3apARwAKioqEO2a8iL6oPWKpjxKuzgngxVTrV2HA2IyS/AAuJsEI7fe7qWOR7n6MHNwbFofkX+4teqVA7rHMdioaT/lVSMII0T90zyLkLLPXE2M7IDSfu583JL7Ed+E3CC+oH9bveRVChf8AwAsBZ0TWotlFd16fsPsI5AhYx2H9jM1CkKXUfNqvA2P7JaAYVtm6+dfqf2VKI+AmClcZqy+P0Nnxg0Oe7sdPU+ojSgWs/wDKvNIj6whwFOpqK0GKqfRIVtTKDFxuGq7aMC51AUkfo4sWisiO6rDLXta1HZL73v2PUgA3EPjWqCLk8FQBNmQFhxMGCY2hRQAI/WIh6dTe2VQl1ZbgTM8NDSwDjVBydQrn5mVXrxRCmCF6OSXSyj6wBXBcwutxBw2OAng1kpdyR06wtbJdutpkJM4ZXJtF0TDg722a41f0MrMXfXNrkpw7Mp0wMfjL93fLoeplXQhVbNVTGfBkk3bGFbLi9fOmooCmz5RHQ06xZ6teXqc9kpXnk1snbaZJVoSVpFFajxS77peF2jA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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "image1 = Image('../data_folder/photo_2024-02-11_11-04-15.jpg')\n", + "image2 = Image('../data_folder/photo_2024-02-11_11-03-30.jpg')\n", + "display(image1, image2)" + ] + }, { "cell_type": "markdown", "id": "e116a42f-fae8-499c-a985-dc09e66a29b0", @@ -959,6 +939,28 @@ "source": [ "**Ваши мысли:** я немного подавлена" ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "9d9034f6-239b-4633-b47e-a0911bb421f5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/jpeg": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Image('../data_folder/cat.jpeg')" + ] } ], "metadata": { diff --git a/hw1/code/knn.py b/hw1/code/knn.py index ad3c4a9..7664cfa 100644 --- a/hw1/code/knn.py +++ b/hw1/code/knn.py @@ -124,7 +124,7 @@ def predict_labels_binary(self, distances): #n_train = distances.shape[1] n_test = distances.shape[0] - prediction = np.zeros(n_test) + prediction = np.zeros(n_test, dtype=bool) for i in range(n_test): nearest_indices = np.argsort(distances[i])[:self.k] diff --git a/hw1/code/metrics.py b/hw1/code/metrics.py index b65c588..14bc243 100644 --- a/hw1/code/metrics.py +++ b/hw1/code/metrics.py @@ -11,15 +11,22 @@ def binary_classification_metrics(y_pred, y_true): precision, recall, f1, accuracy - classification metrics """ - # TODO: implement metrics! - # Some helpful links: - # https://en.wikipedia.org/wiki/Precision_and_recall - # https://en.wikipedia.org/wiki/F1_score - - """ - YOUR CODE IS HERE - """ - pass + labels = np.array([0, 1]) + cm = np.zeros((2, 2), dtype=int) + for i in range(len(y_true)): + true_label = np.where(labels == y_true[i])[0][0] + pred_label = np.where(labels == y_pred[i])[0][0] + cm[true_label, pred_label] += 1 + tp = cm[1, 1] + tn = cm[0, 0] + fp = cm[0, 1] + fn = cm[1, 0] + accuracy = (tp + tn) / cm.sum() + precision = tp / (tp + fp) if (tp + fp) != 0 else 0 + recall = tp / (tp + fn) if (tp + fn) != 0 else 0 + f1 = 2 * precision * recall / (precision + recall) if (precision + recall) != 0 else 0 + + return precision, recall, f1, accuracy def multiclass_accuracy(y_pred, y_true): diff --git a/hw1/code/my_awesome_eda.py b/hw1/code/my_awesome_eda.py new file mode 100644 index 0000000..5fb2a86 --- /dev/null +++ b/hw1/code/my_awesome_eda.py @@ -0,0 +1,136 @@ +import numpy as np +import pandas as pd +import matplotlib.pyplot as plt +import seaborn as sns +plt.rcParams.update({'font.weight': 'normal'}) + +def run_eda(df: pd.DataFrame, category_values: int = 0) -> None: + ''' + Perform Exploratory Data Analysis (EDA) on the given DataFrame. + + Args: + - df (pd.DataFrame): The DataFrame to analyze. + - category_values (int): The threshold for unique values to consider a column as categorical. + Columns with unique values less than or equal to this threshold will be categorized. + + Returns: + None + ''' + # Greeting + print('Praise the Omnissiah! Welcome to the Sanctum of Exploratory Data Analysis.\n') + + # Number of observations and parameters + num_observations = df.shape[0] + num_parameters = df.shape[1] + print(f'Number of Observations (Rows): {num_observations}') + print(f'Number of Parameters (Columns): {num_parameters}') + + # Data types of each column + print('\nData Types of Each Column:') + for column_name in df.columns: + unique_values = df[column_name].nunique() + if unique_values <= category_values: + df[column_name] = df[column_name].astype('category') + column_types = df.dtypes + max_len = max(map(len, column_types.index)) + 2 + for column_name, data_type in column_types.items(): + print(f'{column_name.ljust(max_len)} {data_type}') + + # Categorize features into numerical, string, and categorical + print() + numerical_features = df.select_dtypes(include=['int64', 'float64']).columns + string_features = df.select_dtypes(include=['object']).columns + categorical_features = df.select_dtypes(include=['category']).columns + print(f'Numerical features: {", ".join(numerical_features) if not numerical_features.empty else 0}') + print(f'String features: {", ".join(string_features) if not string_features.empty else 0}') + print(f'Categorical features: {", ".join(categorical_features) if not categorical_features.empty else 0}') + + # Counts and frequencies for categorical features + print('\nCounts and Frequencies for Categorical Features:') + for col in categorical_features: + counts = df[col].value_counts() + frequencies = counts / num_observations + count_df = pd.DataFrame({'count': counts, 'Frequency': frequencies}) + count_df.index.name = col + count_df = count_df.sort_index() + print(count_df.to_string()) + + # Descriptive statistics for numerical features except ID + print('\nDescriptive Statistics for Numerical Features:') + numerical_features_selected = numerical_features[~numerical_features.str.contains('Id')] + numerical_statistics_selected = df.loc[:, numerical_features_selected].describe().round(2) + print(numerical_statistics_selected) + + print('\nHistograms with Boxplots for Numerical Features:') + numerical_features_selected = numerical_features[~numerical_features.str.contains('Id')] + for col in numerical_features_selected: + plt.figure(figsize=(6, 3)) + sns.set(style="whitegrid") + plt.subplot(1, 2, 1) + sns.histplot(df[col], bins=30, kde=False, color='red') + plt.title(f'Histogram of {col}', fontsize=10, fontweight='bold') + plt.xlabel(col, fontsize=8, fontweight='bold') + plt.ylabel('Count', fontsize=8, fontweight='bold') + plt.xticks(fontsize=8) + plt.yticks(fontsize=8) + plt.grid(False) + + plt.subplot(1, 2, 2) + sns.boxplot(x=df[col], color='red') + plt.title(f'Boxplot of {col}', fontsize=8, fontweight='bold') + plt.xlabel(col, fontsize=6, fontweight='bold') + plt.xticks(fontsize=6) + plt.yticks(fontsize=6) + plt.grid(False) + plt.show() + + print('\nCorrelation Heatmap:') + plt.figure(figsize=(6, 4)) + sns.set(font_scale=1) + sns.heatmap(df[numerical_features_selected].corr(), annot=True, cmap='inferno', fmt=".2f") + plt.title('Correlation Heatmap', fontsize=10, fontweight='bold') + plt.xticks(fontsize=8) + plt.yticks(fontsize=8) + plt.show() + + # Outliers for numerical features except ID + print('\nOutliers for Numerical Features:') + outliers = {} + for col in numerical_features_selected: + q1 = df[col].quantile(0.25) + q3 = df[col].quantile(0.75) + iqr = q3 - q1 + lower_bound = q1 - 1.5 * iqr + upper_bound = q3 + 1.5 * iqr + num_outliers = len(df[(df[col] < lower_bound) | (df[col] > upper_bound)]) + outliers[col] = num_outliers + for col, num_outliers in outliers.items(): + print(f'{col}: {num_outliers}') + + # Missing values + print('\nMissing Values:') + total_missing = df.isnull().sum().sum() + rows_with_missing = df[df.isnull().any(axis=1)].shape[0] + columns_with_missing = df.columns[df.isnull().any()].tolist() + print(f'Total Missing Values: {total_missing}') + print(f'Rows with Missing Values: {rows_with_missing}') + print(f'Columns with Missing Values: {", ".join(columns_with_missing)}') + + print('\nMissing Values Proportion:') + missing_proportion = df.isnull().mean() + plt.figure(figsize=(6, 3)) + sns.set(style="whitegrid") + sns.barplot(x=missing_proportion.index, y=missing_proportion, color='red') + plt.title('Proportion of Missing Values for Each Variable', fontsize=10, fontweight='bold') + plt.xlabel('Variables', fontsize=8, fontweight='bold') + plt.ylabel('Proportion of Missing Values', fontsize=8, fontweight='bold') + plt.yticks(fontsize=8) + plt.xticks(rotation=45, ha='right', fontsize=8) + plt.grid(False) + plt.show() + + # Duplicate rows + print('\nDuplicate Rows:') + num_duplicates = df.duplicated().sum() + print(f'Number of Duplicate Rows: {num_duplicates}') + print('\nMay the data guide you, and the Omnissiah bless your analysis.') \ No newline at end of file diff --git a/hw1/data_folder/cat.jpeg b/hw1/data_folder/cat.jpeg new file mode 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zLXLAzR(!!S2`hRZ+0O!jf5*o;^?-|~79mWbp{oPOz@kF>2v!s#qze+i^o!UCV8$&> zsVx`9v^R9OS;6EH;*?>-kNv01twcv4(k#xsiR|z|JaaCqHDQSa_z89^Zy^JaCzI_+ z%t3@amZgEuASQlbHpX>LaFy!AXvB9!kZ$x7!m!UG@eVqwPR-HET~W?o;GzF~_Pz9k zhKIdS7%!GzMzFSyOHmJ9KLvsHEAi5jE?>xFa+pN$s9ymr8gX3m7>s7X0?IZ;~nl@ZB$n45Rd0#6H^`8t5lN;!$%27?jPlWk*v>aK7p3ihYIX(w%i$}}^T?}x{xuwG3`?vIf6JwX| ze@a&uu%|x}6o4~h-`#(eeo_BZ`cr4RqYHC6yqJhQ5an4sEj{;*QHklbHiMzPqT$b% zeJ8c5&DeGdG#p>jU{Cyb`QS8qeli~M@(VY=48qzu<>kDK!3+Sihpmk4d(hcWgr5ul E1NamxBme*a literal 0 HcmV?d00001 From 5573d099a1ed5f7f17abb7f1b2ac92210f72cf4f Mon Sep 17 00:00:00 2001 From: Tatiana Lisitsa Date: Sun, 11 Feb 2024 16:28:44 +0300 Subject: [PATCH 3/4] Add r_squared, mse, mae --- hw1/code/KNN.ipynb | 1060 ++++++++++++++++++++++++++++++++++++++++--- hw1/code/metrics.py | 23 +- 2 files changed, 1005 insertions(+), 78 deletions(-) diff --git a/hw1/code/KNN.ipynb b/hw1/code/KNN.ipynb index 6f65ea7..1ae035a 100644 --- a/hw1/code/KNN.ipynb +++ b/hw1/code/KNN.ipynb @@ -23,19 +23,10 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 1, "id": "9638c464-806f-41b5-9dfe-1ea2048a1fa1", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The autoreload extension is already loaded. To reload it, use:\n", - " %reload_ext autoreload\n" - ] - } - ], + "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2\n", @@ -47,7 +38,7 @@ "import pandas as pd\n", "\n", "\n", - "from IPython.display import Image, displey\n", + "from IPython.display import Image, display\n", "from sklearn.datasets import fetch_openml\n", "from sklearn.model_selection import train_test_split\n", "from knn import KNNClassifier\n", @@ -392,9 +383,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "24.7 ms ± 127 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", - "5.33 ms ± 57.2 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "10.8 ms ± 31.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + "28.7 ms ± 1.02 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", + "6.02 ms ± 201 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "12.2 ms ± 605 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" ] } ], @@ -498,7 +489,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 18, "id": "5caeb94f-6464-4adf-b3b6-8e12bf4a50b4", "metadata": {}, "outputs": [], @@ -508,7 +499,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 19, "id": "9f02cbc9-3fcf-4818-ab9b-eb90c3db1703", "metadata": {}, "outputs": [ @@ -556,7 +547,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "id": "374d6fcf-21f2-433c-b011-76019201ce52", "metadata": {}, "outputs": [], @@ -575,44 +566,68 @@ " train_metrics the list of metric values on train data set for each k in params\n", " test_metrics the list of metric values on test data set for each k in params\n", " \"\"\"\n", - " \n", - " \"\"\"\n", - " YOUR CODE IS HERE\n", - " \"\"\"\n", - " pass" + " train_metrics = []\n", + " test_metrics = []\n", + " metrics_dict = {\n", + " precision_score: 0,\n", + " recall_score: 1,\n", + " f1_score: 2,\n", + " accuracy_score: 3\n", + " }\n", + " if metric not in metrics_dict:\n", + " raise ValueError(f\"Invalid metric '{metric}'. Supported metrics are: {', '.join(metrics_dict.keys())}\")\n", + "\n", + " for k in params:\n", + " knn_classifier = KNNClassifier(k)\n", + " knn_classifier.fit(X_train, y_train)\n", + " prediction_train = knn_classifier.predict(X_train)\n", + " prediction_test = knn_classifier.predict(X_test)\n", + " metric_idx = metrics_dict[metric]\n", + " train_metrics.append(binary_classification_metrics(prediction_train, y_train)[metric_idx])\n", + " test_metrics.append(binary_classification_metrics(prediction_test, y_test)[metric_idx])\n", + "\n", + " return train_metrics, test_metrics" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "id": "a2418dd8-93f1-4a11-8488-a8bce98e7d5f", "metadata": { "tags": [] }, "outputs": [ { - "ename": "TypeError", - "evalue": "cannot unpack non-iterable NoneType object", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[20], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m params \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m4\u001b[39m, \u001b[38;5;241m5\u001b[39m, \u001b[38;5;241m8\u001b[39m, \u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m30\u001b[39m]\n\u001b[0;32m----> 2\u001b[0m train_metrics, test_metrics \u001b[38;5;241m=\u001b[39m find_best_k(binary_train_X, binary_train_y, binary_test_X, binary_test_y, params, accuracy_score)\n", - "\u001b[0;31mTypeError\u001b[0m: cannot unpack non-iterable NoneType object" + "name": "stdout", + "output_type": "stream", + "text": [ + "[1.0, 1.0, 0.9937106918238994, 0.9937106918238994, 0.9811320754716981, 0.9811320754716981, 0.949685534591195] [1.0, 1.0, 1.0, 0.9722222222222222, 1.0, 1.0, 0.9722222222222222]\n" ] } ], "source": [ "params = [1, 2, 4, 5, 8, 10, 30]\n", - "train_metrics, test_metrics = find_best_k(binary_train_X, binary_train_y, binary_test_X, binary_test_y, params, accuracy_score)" + "train_metrics, test_metrics = find_best_k(binary_train_X, binary_train_y, binary_test_X, binary_test_y, params, accuracy_score)\n", + "print(train_metrics, test_metrics)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "id": "7053ce06-854c-412b-8559-833595b1d6c0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "

" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plt.plot(params, train_metrics, label=\"train\")\n", "plt.plot(params, test_metrics, label=\"test\")\n", @@ -634,7 +649,7 @@ "id": "0bc98c29-3217-407c-a466-58072bb7b8cc", "metadata": {}, "source": [ - "### 1.5. Многоклассоввая классификация (2 балла)" + "### 1.5. Многоклассовая классификация (2 балла)" ] }, { @@ -647,10 +662,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "id": "88b37ef1-fa15-4cc5-8558-0254890c899d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "AttributeError", + "evalue": "module 'numpy' has no attribute 'int'.\n`np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\nThe aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:\n https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[23], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m knn_classifier \u001b[38;5;241m=\u001b[39m KNNClassifier(k\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m 3\u001b[0m knn_classifier\u001b[38;5;241m.\u001b[39mfit(X_train, y_train)\n\u001b[0;32m----> 4\u001b[0m predictions \u001b[38;5;241m=\u001b[39m \u001b[43mknn_classifier\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_test\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/Documents/bioinformatics_institute/ml/BI-ML-HW/hw1/code/knn.py:42\u001b[0m, in \u001b[0;36mKNNClassifier.predict\u001b[0;34m(self, X, n_loops)\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpredict_labels_binary(distances)\n\u001b[1;32m 41\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 42\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict_labels_multiclass\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdistances\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/Documents/bioinformatics_institute/ml/BI-ML-HW/hw1/code/knn.py:151\u001b[0m, in \u001b[0;36mKNNClassifier.predict_labels_multiclass\u001b[0;34m(self, distances)\u001b[0m\n\u001b[1;32m 149\u001b[0m n_train \u001b[38;5;241m=\u001b[39m distances\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 150\u001b[0m n_test \u001b[38;5;241m=\u001b[39m distances\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m--> 151\u001b[0m prediction \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mzeros(n_test, \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mint\u001b[49m)\n\u001b[1;32m 153\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 154\u001b[0m \u001b[38;5;124;03mYOUR CODE IS HERE\u001b[39;00m\n\u001b[1;32m 155\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 156\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n", + "File \u001b[0;32m~/miniforge3/envs/ml/lib/python3.12/site-packages/numpy/__init__.py:324\u001b[0m, in \u001b[0;36m__getattr__\u001b[0;34m(attr)\u001b[0m\n\u001b[1;32m 319\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m 320\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIn the future `np.\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mattr\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` will be defined as the \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 321\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcorresponding NumPy scalar.\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;167;01mFutureWarning\u001b[39;00m, stacklevel\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m 323\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m attr \u001b[38;5;129;01min\u001b[39;00m __former_attrs__:\n\u001b[0;32m--> 324\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(__former_attrs__[attr])\n\u001b[1;32m 326\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m attr \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtesting\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 327\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtesting\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mtesting\u001b[39;00m\n", + "\u001b[0;31mAttributeError\u001b[0m: module 'numpy' has no attribute 'int'.\n`np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\nThe aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:\n https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations" + ] + } + ], "source": [ "# TODO: predict_labels_multiclass in knn.py\n", "knn_classifier = KNNClassifier(k=1)\n", @@ -703,49 +733,168 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "id": "8ab4c84e-6036-4fe2-b81f-8115bf0a4774", "metadata": {}, "outputs": [], "source": [ "from sklearn.datasets import load_diabetes\n", "from sklearn.metrics import r2_score, mean_absolute_error, mean_squared_error\n", - "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.preprocessing import (StandardScaler,\n", + " OneHotEncoder)\n", "from sklearn.neighbors import KNeighborsRegressor" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "id": "4136b3bb-e482-4102-ad5f-af5b3b1a030a", "metadata": {}, "outputs": [], "source": [ - "X, y = load_diabetes(as_frame=True, return_X_y=True, scaled=True)" + "X, y = load_diabetes(as_frame=True, return_X_y=True, scaled=False) # я выставила здесь False, потому что стандартизацию надо делать не сразу на всем, а на тренировочной части\n", + " # а еще меня очень сильно смущает среднее значение и стандартное отклонение по полу" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "id": "c884e687-964a-4b00-9f10-232c45705f12", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " age sex bmi bp s1 s2 s3 s4 s5 s6\n", + "0 59.0 2.0 32.1 101.0 157.0 93.2 38.0 4.0 4.8598 87.0\n", + "1 48.0 1.0 21.6 87.0 183.0 103.2 70.0 3.0 3.8918 69.0\n", + "2 72.0 2.0 30.5 93.0 156.0 93.6 41.0 4.0 4.6728 85.0\n", + "3 24.0 1.0 25.3 84.0 198.0 131.4 40.0 5.0 4.8903 89.0\n", + "4 50.0 1.0 23.0 101.0 192.0 125.4 52.0 4.0 4.2905 80.0" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "X.head()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "id": "d199d24e-2a61-4a00-a5ed-707d314608c1", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, + "metadata": {}, "outputs": [], - "source": [] + "source": [ + "diabetes_X_train, diabetes_X_test, diabetes_y_train, diabetes_y_test = train_test_split(X,\n", + " y,\n", + " test_size=0.2,\n", + " random_state=SEED)" + ] }, { "cell_type": "markdown", @@ -768,23 +917,674 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 43, "id": "a4aa413d-d830-4355-a063-9c5d6d5a6c9a", "metadata": {}, "outputs": [], "source": [ + "from sklearn.compose import ColumnTransformer\n", "from sklearn.pipeline import Pipeline\n", "from my_awesome_eda import run_eda" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "id": "f84b891e-b397-4c58-9b0a-d8becef14411", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Praise the Omnissiah! Welcome to the Sanctum of Exploratory Data Analysis.\n", + "\n", + "Number of Observations (Rows): 442\n", + "Number of Parameters (Columns): 10\n", + "\n", + "Data Types of Each Column:\n", + "age float64\n", + "sex category\n", + "bmi float64\n", + "bp float64\n", + "s1 float64\n", + "s2 float64\n", + "s3 float64\n", + "s4 float64\n", + "s5 float64\n", + "s6 float64\n", + "\n", + "Numerical features: age, bmi, bp, s1, s2, s3, s4, s5, s6\n", + "String features: 0\n", + "Categorical features: sex\n", + "\n", + "Counts and Frequencies for Categorical Features:\n", + " count Frequency\n", + "sex \n", + "1.0 235 0.531674\n", + "2.0 207 0.468326\n", + "\n", + "Descriptive Statistics for Numerical Features:\n", + " age bmi bp s1 s2 s3 s4 s5 s6\n", + "count 442.00 442.00 442.00 442.00 442.00 442.00 442.00 442.00 442.00\n", + "mean 48.52 26.38 94.65 189.14 115.44 49.79 4.07 4.64 91.26\n", + "std 13.11 4.42 13.83 34.61 30.41 12.93 1.29 0.52 11.50\n", + "min 19.00 18.00 62.00 97.00 41.60 22.00 2.00 3.26 58.00\n", + "25% 38.25 23.20 84.00 164.25 96.05 40.25 3.00 4.28 83.25\n", + "50% 50.00 25.70 93.00 186.00 113.00 48.00 4.00 4.62 91.00\n", + "75% 59.00 29.28 105.00 209.75 134.50 57.75 5.00 5.00 98.00\n", + "max 79.00 42.20 133.00 301.00 242.40 99.00 9.09 6.11 124.00\n", + "\n", + "Histograms with Boxplots for Numerical Features:\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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", 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", 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", 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Correlation Heatmap:\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Outliers for Numerical Features:\n", + "age: 0\n", + "bmi: 3\n", + "bp: 0\n", + "s1: 8\n", + "s2: 7\n", + "s3: 7\n", + "s4: 2\n", + "s5: 4\n", + "s6: 9\n", + "\n", + "Missing Values:\n", + "Total Missing Values: 0\n", + "Rows with Missing Values: 0\n", + "Columns with Missing Values: \n", + "\n", + "Missing Values Proportion:\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Duplicate Rows:\n", + "Number of Duplicate Rows: 0\n", + "\n", + "May the data guide you, and the Omnissiah bless your analysis.\n" + ] + } + ], + "source": [ + "run_eda(X, category_values=5) # в том семестре было ДЗ по python написать скрипт для EDA, не пропадать же добру" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "1ebaf244-129d-4074-8794-8bb0ed761d4b", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Praise the Omnissiah! Welcome to the Sanctum of Exploratory Data Analysis.\n", + "\n", + "Number of Observations (Rows): 353\n", + "Number of Parameters (Columns): 10\n", + "\n", + "Data Types of Each Column:\n", + "age float64\n", + "sex category\n", + "bmi float64\n", + "bp float64\n", + "s1 float64\n", + "s2 float64\n", + "s3 float64\n", + "s4 float64\n", + "s5 float64\n", + "s6 float64\n", + "\n", + "Numerical features: age, bmi, bp, s1, s2, s3, s4, s5, s6\n", + "String features: 0\n", + "Categorical features: sex\n", + "\n", + "Counts and Frequencies for Categorical Features:\n", + " count Frequency\n", + "sex \n", + "1.0 190 0.538244\n", + "2.0 163 0.461756\n", + "\n", + "Descriptive Statistics for Numerical Features:\n", + " age bmi bp s1 s2 s3 s4 s5 s6\n", + "count 353.00 353.00 353.00 353.00 353.00 353.00 353.00 353.00 353.00\n", + "mean 48.82 26.40 94.80 189.42 115.19 50.32 4.04 4.63 91.41\n", + "std 12.94 4.48 13.86 35.27 30.78 13.18 1.29 0.53 11.51\n", + "min 19.00 18.10 63.00 97.00 41.60 23.00 2.00 3.26 60.00\n", + "25% 40.00 23.10 84.00 164.00 96.00 41.00 3.00 4.26 84.00\n", + "50% 50.00 25.60 93.00 185.00 112.20 49.00 4.00 4.58 91.00\n", + "75% 59.00 29.60 105.00 212.00 134.20 58.00 5.00 4.99 98.00\n", + "max 79.00 42.20 133.00 301.00 242.40 99.00 9.09 6.11 124.00\n", + "\n", + "Histograms with Boxplots for Numerical Features:\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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", 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", 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Correlation Heatmap:\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Outliers for Numerical Features:\n", + "age: 0\n", + "bmi: 2\n", + "bp: 0\n", + "s1: 3\n", + "s2: 5\n", + "s3: 7\n", + "s4: 2\n", + "s5: 4\n", + "s6: 10\n", + "\n", + "Missing Values:\n", + "Total Missing Values: 0\n", + "Rows with Missing Values: 0\n", + "Columns with Missing Values: \n", + "\n", + "Missing Values Proportion:\n" + ] + }, + { + "data": { + "image/png": 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353 rows × 10 columns

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" + ], + "text/plain": [ + " age sex bmi bp s1 s2 s3 s4 s5 s6\n", + "382 62.0 1.0 32.0 88.0 172.0 69.0 38.0 4.0 5.7838 100.0\n", + "195 56.0 2.0 28.7 99.0 208.0 146.4 39.0 5.0 4.7274 97.0\n", + "391 42.0 1.0 19.9 76.0 146.0 83.2 55.0 3.0 3.6636 79.0\n", + "117 65.0 1.0 24.4 120.0 222.0 135.6 37.0 6.0 5.5094 124.0\n", + "337 54.0 2.0 25.2 115.0 181.0 120.0 39.0 5.0 4.7005 92.0\n", + ".. ... ... ... ... ... ... ... ... ... ...\n", + "275 47.0 2.0 25.3 98.0 173.0 105.6 44.0 4.0 4.7622 108.0\n", + "86 29.0 2.0 19.4 83.0 152.0 105.8 39.0 4.0 3.5835 83.0\n", + "212 67.0 1.0 26.7 105.0 225.0 135.4 69.0 3.0 4.6347 96.0\n", + "364 49.0 2.0 25.8 89.0 182.0 118.6 39.0 5.0 4.8040 115.0\n", + "340 44.0 1.0 25.1 133.0 182.0 113.0 55.0 3.0 4.2485 84.0\n", + "\n", + "[353 rows x 10 columns]" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cat_cols = ['sex']\n", + "num_cols = ['age', 'bmi', 'bp', 's1', 's2', 's3', 's4', 's5', 's6']\n", + "all_features = cat_cols + num_cols\n", + "\n", + "preprocessor = ColumnTransformer(transformers=[\n", + " (\"scaler\", StandardScaler(), num_cols),\n", + " (\"ohe\", OneHotEncoder(drop=\"first\"), cat_cols)\n", + "])\n", + "preprocessor" ] }, { @@ -803,6 +1603,22 @@ "Создайте модель `KNeighborsRegressor`, обучите ее на треноровочных данных и сделайте предсказания." ] }, + { + "cell_type": "code", + "execution_count": 90, + "id": "f0510c4a-83d0-4318-9d39-818f23a8e08d", + "metadata": {}, + "outputs": [], + "source": [ + "knn_pipeline = Pipeline(steps=[\n", + " (\"preprocessor\", preprocessor),\n", + " (\"knn\", KNeighborsRegressor(n_neighbors=9, n_jobs=4))\n", + "])\n", + "knn_pipeline.fit(diabetes_X_train, diabetes_y_train)\n", + "diabetes_X_test = \n", + "diabetes_predicted = knn_pipeline.predict(diabetes_X_test)" + ] + }, { "cell_type": "markdown", "id": "5ed4a2ea-4f42-43cb-95d7-50cdeab5f284", @@ -829,12 +1645,61 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 78, "id": "580f604f-e9c5-4109-8b9f-235369836057", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The autoreload extension is already loaded. To reload it, use:\n", + " %reload_ext autoreload\n" + ] + } + ], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2\n", + "from metrics import r_squared, mse, mae" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "id": "e7ce7f32-87ff-4431-b5e4-206ce18ed667", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.3982447365859344 2828.5185185185187 42.561797752808985\n" + ] + } + ], + "source": [ + "r_squared_val, mse_val, mae_val = r_squared(diabetes_predicted, diabetes_y_test), mse(diabetes_predicted, diabetes_y_test), mae(diabetes_predicted, diabetes_y_test)\n", + "print(r_squared_val, mse_val, mae_val)" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "id": "8a4fc5ff-474b-498e-be10-d50578e2b0d1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.3982447365859344 2828.5185185185187 42.561797752808985\n" + ] + } + ], "source": [ - "# TODO: r_squared, mse, mae in metrics.py" + "r_squared_val, mse_val, mae_val = r2_score(diabetes_y_test, diabetes_predicted), mean_squared_error(diabetes_y_test, diabetes_predicted), mean_absolute_error(diabetes_y_test, diabetes_predicted)\n", + "print(r_squared_val, mse_val, mae_val)" ] }, { @@ -857,12 +1722,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 81, "id": "138a7969-8079-4a38-b92e-8eae5d246325", "metadata": {}, "outputs": [], "source": [ - "from metrics import r_squared, mse, mae" + "def find_best_k_for_regression(X_train, y_train, X_test, y_test, params, metric):\n", + " \"\"\"\n", + " Choose the best k for KKNRegression\n", + " Arguments:\n", + " X_train, np array (num_train_samples, num_features) - train data\n", + " y_train, np array (num_train_samples) - train labels\n", + " X_test, np array (num_test_samples, num_features) - test data\n", + " y_test, np array (num_test_samples) - test labels\n", + " params, list of hyperparameters for KNN, here it is list of k values\n", + " metric, function for metric calculation\n", + " Returns:\n", + " train_metrics the list of metric values on train data set for each k in params\n", + " test_metrics the list of metric values on test data set for each k in params\n", + " \"\"\"\n", + " train_metrics = []\n", + " test_metrics = []\n", + " \n", + " for k in params:\n", + " knn_pipeline = Pipeline(steps=[\n", + " (\"preprocessor\", preprocessor),\n", + " (\"knn\", KNeighborsRegressor(n_neighbors=k, n_jobs=4))\n", + " ])\n", + " knn_pipeline.fit(X_train, y_train)\n", + " predicted_train = knn_pipeline.predict(X_train)\n", + " predicted_test = knn_pipeline.predict(X_test)\n", + " train_metrics.append(metric(predicted_train, y_train))\n", + " test_metrics.append(metric(predicted_test, y_test))\n", + "\n", + " return train_metrics, test_metrics" ] }, { @@ -873,6 +1766,42 @@ "Для поиска лучшего k вы можете воспользоваться функцией `find_best_k`, которую вы реализовали выше." ] }, + { + "cell_type": "code", + "execution_count": 93, + "id": "fc461477-8a45-433b-b1a5-b12815ba2899", + "metadata": {}, + "outputs": [], + "source": [ + "params = [1, 2, 4, 5, 8, 10, 30]\n", + "train_metrics, test_metrics = find_best_k_for_regression(diabetes_X_train, diabetes_y_train, diabetes_X_test, diabetes_y_test, params, mae)" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "id": "f23ef387-ec3f-4477-b441-da8591efda0e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(params, train_metrics, label=\"train\")\n", + "plt.plot(params, test_metrics, label=\"test\")\n", + "plt.legend()\n", + "plt.xlabel(\"K in KNN\")\n", + "plt.ylabel(\"YOUR METRIC\");" + ] + }, { "cell_type": "markdown", "id": "2cb77960-fa30-4a29-9a1b-7c195cc867cb", @@ -885,7 +1814,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 30, "id": "cd21e2b7-8310-4ffb-893f-8c571110037d", "metadata": {}, "outputs": [ @@ -937,12 +1866,13 @@ "id": "6d1c75b8", "metadata": {}, "source": [ - "**Ваши мысли:** я немного подавлена" + "**Ваши мысли:** я немного подавлена... в общем, я тут поору немного опоссумом... я чувствую себя очень глупой, я забыла все про numpy и matplotlib, я не понимаю статистику, мне хочется плакать... В остальном все хорошо... как улучшить? даже не знаю... это было больно, но в целом полезно.\n", + "Про следующие дз: у меня есть данные из лаборатории - там про мутации в генах BRCA1, BRCA2, ATM, PALB2, CHEK2 и фенотип рака молочной железы, рецепторный статус там, ki-67, возраст манифестации и тд, можно например привести это в нормальный вид и попробовать по фенотипу предполагать в каком гене мутация, могу еще дополнить каким-то количеством данных про пациентов без мутации))" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 31, "id": "9d9034f6-239b-4633-b47e-a0911bb421f5", "metadata": {}, "outputs": [ @@ -953,7 +1883,7 @@ "" ] }, - "execution_count": 27, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } diff --git a/hw1/code/metrics.py b/hw1/code/metrics.py index 14bc243..7b58130 100644 --- a/hw1/code/metrics.py +++ b/hw1/code/metrics.py @@ -55,10 +55,10 @@ def r_squared(y_pred, y_true): r2 - r-squared value """ - """ - YOUR CODE IS HERE - """ - pass + y_mean = np.mean(y_true) + ss_res = np.sum((y_true - y_pred) ** 2) + ss_total = np.sum((y_true - y_mean) ** 2) + return 1 - (ss_res / ss_total) def mse(y_pred, y_true): @@ -71,10 +71,9 @@ def mse(y_pred, y_true): mse - mean squared error """ - """ - YOUR CODE IS HERE - """ - pass + n = len(y_pred) + ss_res = np.sum((y_true - y_pred) ** 2) + return ss_res / n def mae(y_pred, y_true): @@ -87,8 +86,6 @@ def mae(y_pred, y_true): mae - mean absolut error """ - """ - YOUR CODE IS HERE - """ - pass - \ No newline at end of file + n = len(y_pred) + s_res = np.sum(np.abs(y_true - y_pred)) + return s_res / n From 173d3ec413be9a6c4d66fb1e29c7e64372e8606b Mon Sep 17 00:00:00 2001 From: Tatiana Lisitsa Date: Sun, 11 Feb 2024 17:51:06 +0300 Subject: [PATCH 4/4] Add func to multiclass predict and multiclass accuracy --- hw1/code/KNN.ipynb | 818 ++++++++++++++++++++++++++++++-------------- hw1/code/knn.py | 14 +- hw1/code/metrics.py | 16 +- 3 files changed, 573 insertions(+), 275 deletions(-) diff --git a/hw1/code/KNN.ipynb b/hw1/code/KNN.ipynb index 1ae035a..cb81c9c 100644 --- a/hw1/code/KNN.ipynb +++ b/hw1/code/KNN.ipynb @@ -383,9 +383,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "28.7 ms ± 1.02 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", - "6.02 ms ± 201 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "12.2 ms ± 605 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + "24.7 ms ± 232 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", + "5.19 ms ± 9.81 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", + "11.4 ms ± 648 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" ] } ], @@ -619,7 +619,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -633,7 +633,7 @@ "plt.plot(params, test_metrics, label=\"test\")\n", "plt.legend()\n", "plt.xlabel(\"K in KNN\")\n", - "plt.ylabel(\"YOUR METRIC\");" + "plt.ylabel(\"ACCURACY\");" ] }, { @@ -663,29 +663,45 @@ { "cell_type": "code", "execution_count": 23, + "id": "99040e49-065c-4dc7-bdee-72079403815c", + "metadata": {}, + "outputs": [], + "source": [ + "idx_to_stay = np.random.choice(np.arange(X.shape[0]), replace=False, size=500) # при 1000 на выборе best_k ноут не вывозит\n", + "X = X[idx_to_stay]\n", + "y = y[idx_to_stay]\n", + "X_train, X_test, y_train, y_test = train_test_split(X, \n", + " y, \n", + " test_size=0.2,\n", + " random_state=SEED)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, "id": "88b37ef1-fa15-4cc5-8558-0254890c899d", "metadata": {}, "outputs": [ { - "ename": "AttributeError", - "evalue": "module 'numpy' has no attribute 'int'.\n`np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\nThe aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:\n https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[23], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m knn_classifier \u001b[38;5;241m=\u001b[39m KNNClassifier(k\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m 3\u001b[0m knn_classifier\u001b[38;5;241m.\u001b[39mfit(X_train, y_train)\n\u001b[0;32m----> 4\u001b[0m predictions \u001b[38;5;241m=\u001b[39m \u001b[43mknn_classifier\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_test\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/Documents/bioinformatics_institute/ml/BI-ML-HW/hw1/code/knn.py:42\u001b[0m, in \u001b[0;36mKNNClassifier.predict\u001b[0;34m(self, X, n_loops)\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpredict_labels_binary(distances)\n\u001b[1;32m 41\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 42\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict_labels_multiclass\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdistances\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/Documents/bioinformatics_institute/ml/BI-ML-HW/hw1/code/knn.py:151\u001b[0m, in \u001b[0;36mKNNClassifier.predict_labels_multiclass\u001b[0;34m(self, distances)\u001b[0m\n\u001b[1;32m 149\u001b[0m n_train \u001b[38;5;241m=\u001b[39m distances\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 150\u001b[0m n_test \u001b[38;5;241m=\u001b[39m distances\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m--> 151\u001b[0m prediction \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mzeros(n_test, \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mint\u001b[49m)\n\u001b[1;32m 153\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 154\u001b[0m \u001b[38;5;124;03mYOUR CODE IS HERE\u001b[39;00m\n\u001b[1;32m 155\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 156\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n", - "File \u001b[0;32m~/miniforge3/envs/ml/lib/python3.12/site-packages/numpy/__init__.py:324\u001b[0m, in \u001b[0;36m__getattr__\u001b[0;34m(attr)\u001b[0m\n\u001b[1;32m 319\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m 320\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIn the future `np.\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mattr\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` will be defined as the \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 321\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcorresponding NumPy scalar.\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;167;01mFutureWarning\u001b[39;00m, stacklevel\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m 323\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m attr \u001b[38;5;129;01min\u001b[39;00m __former_attrs__:\n\u001b[0;32m--> 324\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(__former_attrs__[attr])\n\u001b[1;32m 326\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m attr \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtesting\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 327\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtesting\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mtesting\u001b[39;00m\n", - "\u001b[0;31mAttributeError\u001b[0m: module 'numpy' has no attribute 'int'.\n`np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\nThe aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:\n https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations" - ] + "data": { + "text/plain": [ + "array([7, 0, 0, 2, 5, 2, 9, 4, 5, 8, 3, 9, 6, 4, 0, 3, 9, 0, 7, 5, 9, 1,\n", + " 6, 0, 6, 1, 4, 1, 5, 3, 2, 8, 3, 5, 3, 6, 0, 8, 6, 7, 8, 7, 0, 6,\n", + " 3, 7, 9, 6, 2, 2, 3, 9, 3, 7, 3, 1, 3, 6, 2, 5, 7, 2, 6, 3, 2, 0,\n", + " 0, 0, 6, 3, 3, 9, 7, 5, 5, 6, 3, 6, 4, 7, 2, 7, 5, 3, 9, 0, 9, 2,\n", + " 9, 1, 1, 6, 9, 7, 0, 8, 9, 1, 7, 4])" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "# TODO: predict_labels_multiclass in knn.py\n", "knn_classifier = KNNClassifier(k=1)\n", "knn_classifier.fit(X_train, y_train)\n", - "predictions = knn_classifier.predict(X_test)" + "predictions = knn_classifier.predict(X_test)\n", + "predictions" ] }, { @@ -698,12 +714,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "id": "65887922-a799-4042-902e-f63f69508beb", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "0.75" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# TODO: multiclass_accuracy in metrics.py\n", "multiclass_accuracy(predictions, y_test)" ] }, @@ -715,6 +741,69 @@ "Снова выберите оптимальное значение K как мы делали для бинарной классификации." ] }, + { + "cell_type": "code", + "execution_count": 26, + "id": "6b06246e-c58b-4a01-b415-25e1137a85b9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1.0, 0.8575, 0.7825, 0.7875, 0.78, 0.7625, 0.67] [0.75, 0.78, 0.74, 0.79, 0.77, 0.75, 0.59]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def find_best_k_multiclass(X_train, y_train, X_test, y_test, params):\n", + " \"\"\"\n", + " Choose the best k for KKNClassifier\n", + " Arguments:\n", + " X_train, np array (num_train_samples, num_features) - train data\n", + " y_train, np array (num_train_samples) - train labels\n", + " X_test, np array (num_test_samples, num_features) - test data\n", + " y_test, np array (num_test_samples) - test labels\n", + " params, list of hyperparameters for KNN, here it is list of k values\n", + " metric, function for metric calculation\n", + " Returns:\n", + " train_metrics the list of metric values on train data set for each k in params\n", + " test_metrics the list of metric values on test data set for each k in params\n", + " \"\"\"\n", + " train_metrics = []\n", + " test_metrics = []\n", + " \n", + " for k in params:\n", + " knn_classifier = KNNClassifier(k)\n", + " knn_classifier.fit(X_train, y_train)\n", + " prediction_train = knn_classifier.predict(X_train)\n", + " prediction_test = knn_classifier.predict(X_test)\n", + " train_metrics.append(multiclass_accuracy(prediction_train, y_train))\n", + " test_metrics.append(multiclass_accuracy(prediction_test, y_test))\n", + "\n", + " return train_metrics, test_metrics\n", + "\n", + "params = [1, 2, 4, 5, 8, 10, 30]\n", + "train_metrics, test_metrics = find_best_k_multiclass(X_train, y_train, X_test, y_test, params)\n", + "print(train_metrics, test_metrics)\n", + "\n", + "plt.plot(params, train_metrics, label=\"train\")\n", + "plt.plot(params, test_metrics, label=\"test\")\n", + "plt.legend()\n", + "plt.xlabel(\"K in KNN\")\n", + "plt.ylabel(\"ACCURACY\");" + ] + }, { "cell_type": "markdown", "id": "daa8ee4a-88c1-4967-84f1-6f7ec223db7e", @@ -733,7 +822,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 27, "id": "8ab4c84e-6036-4fe2-b81f-8115bf0a4774", "metadata": {}, "outputs": [], @@ -747,18 +836,20 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 28, "id": "4136b3bb-e482-4102-ad5f-af5b3b1a030a", "metadata": {}, "outputs": [], "source": [ - "X, y = load_diabetes(as_frame=True, return_X_y=True, scaled=False) # я выставила здесь False, потому что стандартизацию надо делать не сразу на всем, а на тренировочной части\n", - " # а еще меня очень сильно смущает среднее значение и стандартное отклонение по полу" + "X, y = load_diabetes(as_frame=True, return_X_y=True, scaled=False) # я выставила здесь False, потому что стандартизацию надо делать не сразу на всем,\n", + " # а сначала посчитать среднее и стандартное отклонение на тренировочной части, и потом\n", + " # с этими покаазателями делать стандартизацию для тестовой\n", + " # еще меня очень сильно смущает среднее значение и стандартное отклонение по полу" ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 29, "id": "c884e687-964a-4b00-9f10-232c45705f12", "metadata": {}, "outputs": [ @@ -874,7 +965,7 @@ "4 50.0 1.0 23.0 101.0 192.0 125.4 52.0 4.0 4.2905 80.0" ] }, - "execution_count": 36, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -885,7 +976,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 30, "id": "d199d24e-2a61-4a00-a5ed-707d314608c1", "metadata": {}, "outputs": [], @@ -917,7 +1008,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 31, "id": "a4aa413d-d830-4355-a063-9c5d6d5a6c9a", "metadata": {}, "outputs": [], @@ -929,15 +1020,9 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 32, "id": "f84b891e-b397-4c58-9b0a-d8becef14411", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1144,15 +1229,9 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 33, "id": "1ebaf244-129d-4074-8794-8bb0ed761d4b", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1367,210 +1446,433 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 34, "id": "1d555002-83cd-4677-93dd-66fec529f2d7", "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
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" + " @media (prefers-color-scheme: dark) {\n", + " /* Redefinition of color scheme for dark theme */\n", + " --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n", + " --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n", + " --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n", + " --sklearn-color-icon: #878787;\n", + " }\n", + "}\n", + "\n", + "#sk-container-id-1 {\n", + " color: var(--sklearn-color-text);\n", + "}\n", + "\n", + "#sk-container-id-1 pre {\n", + " padding: 0;\n", + "}\n", + "\n", + "#sk-container-id-1 input.sk-hidden--visually {\n", + " border: 0;\n", + " clip: rect(1px 1px 1px 1px);\n", + " clip: rect(1px, 1px, 1px, 1px);\n", + " height: 1px;\n", + " margin: -1px;\n", + " overflow: hidden;\n", + " padding: 0;\n", + " position: absolute;\n", + " width: 1px;\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-dashed-wrapped {\n", + " border: 1px dashed var(--sklearn-color-line);\n", + " margin: 0 0.4em 0.5em 0.4em;\n", + " box-sizing: border-box;\n", + " padding-bottom: 0.4em;\n", + " background-color: var(--sklearn-color-background);\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-container {\n", + " /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n", + " but bootstrap.min.css set `[hidden] { display: none !important; }`\n", + " so we also need the `!important` here to be able to override the\n", + " default hidden behavior on the sphinx rendered scikit-learn.org.\n", + " See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n", + " display: inline-block !important;\n", + " position: relative;\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-text-repr-fallback {\n", + " display: none;\n", + "}\n", + "\n", + "div.sk-parallel-item,\n", + "div.sk-serial,\n", + "div.sk-item {\n", + " /* draw centered vertical line to link estimators */\n", + " background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n", + " background-size: 2px 100%;\n", + " background-repeat: no-repeat;\n", + " background-position: center center;\n", + "}\n", + "\n", + "/* Parallel-specific style estimator block */\n", + "\n", + "#sk-container-id-1 div.sk-parallel-item::after {\n", + " content: \"\";\n", + " width: 100%;\n", + " border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n", + " flex-grow: 1;\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-parallel {\n", + " display: flex;\n", + " align-items: stretch;\n", + " justify-content: center;\n", + " background-color: var(--sklearn-color-background);\n", + " position: relative;\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-parallel-item {\n", + " display: flex;\n", + " flex-direction: column;\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n", + " align-self: flex-end;\n", + " width: 50%;\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n", + " align-self: flex-start;\n", + " width: 50%;\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n", + " width: 0;\n", + "}\n", + "\n", + "/* Serial-specific style estimator block */\n", + "\n", + "#sk-container-id-1 div.sk-serial {\n", + " display: flex;\n", + " flex-direction: column;\n", + " align-items: center;\n", + " background-color: var(--sklearn-color-background);\n", + " padding-right: 1em;\n", + " padding-left: 1em;\n", + "}\n", + "\n", + "\n", + "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n", + "clickable and can be expanded/collapsed.\n", + "- Pipeline and ColumnTransformer use this feature and define the default style\n", + "- Estimators will overwrite some part of the style using the `sk-estimator` class\n", + "*/\n", + "\n", + "/* Pipeline and ColumnTransformer style (default) */\n", + "\n", + "#sk-container-id-1 div.sk-toggleable {\n", + " /* Default theme specific background. It is overwritten whether we have a\n", + " specific estimator or a Pipeline/ColumnTransformer */\n", + " background-color: var(--sklearn-color-background);\n", + "}\n", + "\n", + "/* Toggleable label */\n", + "#sk-container-id-1 label.sk-toggleable__label {\n", + " cursor: pointer;\n", + " display: block;\n", + " width: 100%;\n", + " margin-bottom: 0;\n", + " padding: 0.5em;\n", + " box-sizing: border-box;\n", + " text-align: center;\n", + "}\n", + "\n", + "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n", + " /* Arrow on the left of the label */\n", + " content: \"▸\";\n", + " float: left;\n", + " margin-right: 0.25em;\n", + " color: var(--sklearn-color-icon);\n", + "}\n", + "\n", + "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n", + " color: var(--sklearn-color-text);\n", + "}\n", + "\n", + "/* Toggleable content - dropdown */\n", + "\n", + "#sk-container-id-1 div.sk-toggleable__content {\n", + " max-height: 0;\n", + " max-width: 0;\n", + " overflow: hidden;\n", + " text-align: left;\n", + " /* unfitted */\n", + " background-color: var(--sklearn-color-unfitted-level-0);\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-toggleable__content.fitted {\n", + " /* fitted */\n", + " background-color: var(--sklearn-color-fitted-level-0);\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-toggleable__content pre {\n", + " margin: 0.2em;\n", + " border-radius: 0.25em;\n", + " color: var(--sklearn-color-text);\n", + " /* unfitted */\n", + " background-color: var(--sklearn-color-unfitted-level-0);\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n", + " /* unfitted */\n", + " background-color: var(--sklearn-color-fitted-level-0);\n", + "}\n", + "\n", + "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n", + " /* Expand drop-down */\n", + " max-height: 200px;\n", + " max-width: 100%;\n", + " overflow: auto;\n", + "}\n", + "\n", + "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n", + " content: \"▾\";\n", + "}\n", + "\n", + "/* Pipeline/ColumnTransformer-specific style */\n", + "\n", + "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n", + " color: var(--sklearn-color-text);\n", + " background-color: var(--sklearn-color-unfitted-level-2);\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n", + " background-color: var(--sklearn-color-fitted-level-2);\n", + "}\n", + "\n", + "/* Estimator-specific style */\n", + "\n", + "/* Colorize estimator box */\n", + "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n", + " /* unfitted */\n", + " background-color: var(--sklearn-color-unfitted-level-2);\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n", + " /* fitted */\n", + " background-color: var(--sklearn-color-fitted-level-2);\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n", + "#sk-container-id-1 div.sk-label label {\n", + " /* The background is the default theme color */\n", + " color: var(--sklearn-color-text-on-default-background);\n", + "}\n", + "\n", + "/* On hover, darken the color of the background */\n", + "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n", + " color: var(--sklearn-color-text);\n", + " background-color: var(--sklearn-color-unfitted-level-2);\n", + "}\n", + "\n", + "/* Label box, darken color on hover, fitted */\n", + "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n", + " color: var(--sklearn-color-text);\n", + " background-color: var(--sklearn-color-fitted-level-2);\n", + "}\n", + "\n", + "/* Estimator label */\n", + "\n", + "#sk-container-id-1 div.sk-label label {\n", + " font-family: monospace;\n", + " font-weight: bold;\n", + " display: inline-block;\n", + " line-height: 1.2em;\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-label-container {\n", + " text-align: center;\n", + "}\n", + "\n", + "/* Estimator-specific */\n", + "#sk-container-id-1 div.sk-estimator {\n", + " font-family: monospace;\n", + " border: 1px dotted var(--sklearn-color-border-box);\n", + " border-radius: 0.25em;\n", + " box-sizing: border-box;\n", + " margin-bottom: 0.5em;\n", + " /* unfitted */\n", + " background-color: var(--sklearn-color-unfitted-level-0);\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-estimator.fitted {\n", + " /* fitted */\n", + " background-color: var(--sklearn-color-fitted-level-0);\n", + "}\n", + "\n", + "/* on hover */\n", + "#sk-container-id-1 div.sk-estimator:hover {\n", + " /* unfitted */\n", + " background-color: var(--sklearn-color-unfitted-level-2);\n", + "}\n", + "\n", + "#sk-container-id-1 div.sk-estimator.fitted:hover {\n", + " /* fitted */\n", + " background-color: var(--sklearn-color-fitted-level-2);\n", + "}\n", + "\n", + "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n", + "\n", + "/* Common style for \"i\" and \"?\" */\n", + "\n", + ".sk-estimator-doc-link,\n", + "a:link.sk-estimator-doc-link,\n", + "a:visited.sk-estimator-doc-link {\n", + " float: right;\n", + " font-size: smaller;\n", + " line-height: 1em;\n", + " font-family: monospace;\n", + " background-color: var(--sklearn-color-background);\n", + " border-radius: 1em;\n", + " height: 1em;\n", + " width: 1em;\n", + " text-decoration: none !important;\n", + " margin-left: 1ex;\n", + " /* unfitted */\n", + " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n", + " color: var(--sklearn-color-unfitted-level-1);\n", + "}\n", + "\n", + ".sk-estimator-doc-link.fitted,\n", + "a:link.sk-estimator-doc-link.fitted,\n", + "a:visited.sk-estimator-doc-link.fitted {\n", + " /* fitted */\n", + " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n", + " color: var(--sklearn-color-fitted-level-1);\n", + "}\n", + "\n", + "/* On hover */\n", + "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n", + ".sk-estimator-doc-link:hover,\n", + "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n", + ".sk-estimator-doc-link:hover {\n", + " /* unfitted */\n", + " background-color: var(--sklearn-color-unfitted-level-3);\n", + " color: var(--sklearn-color-background);\n", + " text-decoration: none;\n", + "}\n", + "\n", + "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n", + ".sk-estimator-doc-link.fitted:hover,\n", + "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n", + ".sk-estimator-doc-link.fitted:hover {\n", + " /* fitted */\n", + " background-color: var(--sklearn-color-fitted-level-3);\n", + " color: var(--sklearn-color-background);\n", + " text-decoration: none;\n", + "}\n", + "\n", + "/* Span, style for the box shown on hovering the info icon */\n", + ".sk-estimator-doc-link span {\n", + " display: none;\n", + " z-index: 9999;\n", + " position: relative;\n", + " font-weight: normal;\n", + " right: .2ex;\n", + " padding: .5ex;\n", + " margin: .5ex;\n", + " width: min-content;\n", + " min-width: 20ex;\n", + " max-width: 50ex;\n", + " color: var(--sklearn-color-text);\n", + " box-shadow: 2pt 2pt 4pt #999;\n", + " /* unfitted */\n", + " background: var(--sklearn-color-unfitted-level-0);\n", + " border: .5pt solid var(--sklearn-color-unfitted-level-3);\n", + "}\n", + "\n", + ".sk-estimator-doc-link.fitted span {\n", + " /* fitted */\n", + " background: var(--sklearn-color-fitted-level-0);\n", + " border: var(--sklearn-color-fitted-level-3);\n", + "}\n", + "\n", + ".sk-estimator-doc-link:hover span {\n", + " display: block;\n", + "}\n", + "\n", + "/* \"?\"-specific style due to the `` HTML tag */\n", + "\n", + "#sk-container-id-1 a.estimator_doc_link {\n", + " float: right;\n", + " font-size: 1rem;\n", + " line-height: 1em;\n", + " font-family: monospace;\n", + " background-color: var(--sklearn-color-background);\n", + " border-radius: 1rem;\n", + " height: 1rem;\n", + " width: 1rem;\n", + " text-decoration: none;\n", + " /* unfitted */\n", + " color: var(--sklearn-color-unfitted-level-1);\n", + " border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n", + "}\n", + "\n", + "#sk-container-id-1 a.estimator_doc_link.fitted {\n", + " /* fitted */\n", + " border: var(--sklearn-color-fitted-level-1) 1pt solid;\n", + " color: var(--sklearn-color-fitted-level-1);\n", + "}\n", + "\n", + "/* On hover */\n", + "#sk-container-id-1 a.estimator_doc_link:hover {\n", + " /* unfitted */\n", + " background-color: var(--sklearn-color-unfitted-level-3);\n", + " color: var(--sklearn-color-background);\n", + " text-decoration: none;\n", + "}\n", + "\n", + "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n", + " /* fitted */\n", + " background-color: var(--sklearn-color-fitted-level-3);\n", + "}\n", + "
ColumnTransformer(transformers=[('scaler', StandardScaler(),\n",
+       "                                 ['age', 'bmi', 'bp', 's1', 's2', 's3', 's4',\n",
+       "                                  's5', 's6']),\n",
+       "                                ('ohe', OneHotEncoder(drop='first'), ['sex'])])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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" ], "text/plain": [ - " age sex bmi bp s1 s2 s3 s4 s5 s6\n", - "382 62.0 1.0 32.0 88.0 172.0 69.0 38.0 4.0 5.7838 100.0\n", - "195 56.0 2.0 28.7 99.0 208.0 146.4 39.0 5.0 4.7274 97.0\n", - "391 42.0 1.0 19.9 76.0 146.0 83.2 55.0 3.0 3.6636 79.0\n", - "117 65.0 1.0 24.4 120.0 222.0 135.6 37.0 6.0 5.5094 124.0\n", - "337 54.0 2.0 25.2 115.0 181.0 120.0 39.0 5.0 4.7005 92.0\n", - ".. ... ... ... ... ... ... ... ... ... ...\n", - "275 47.0 2.0 25.3 98.0 173.0 105.6 44.0 4.0 4.7622 108.0\n", - "86 29.0 2.0 19.4 83.0 152.0 105.8 39.0 4.0 3.5835 83.0\n", - "212 67.0 1.0 26.7 105.0 225.0 135.4 69.0 3.0 4.6347 96.0\n", - "364 49.0 2.0 25.8 89.0 182.0 118.6 39.0 5.0 4.8040 115.0\n", - "340 44.0 1.0 25.1 133.0 182.0 113.0 55.0 3.0 4.2485 84.0\n", - "\n", - "[353 rows x 10 columns]" + "ColumnTransformer(transformers=[('scaler', StandardScaler(),\n", + " ['age', 'bmi', 'bp', 's1', 's2', 's3', 's4',\n", + " 's5', 's6']),\n", + " ('ohe', OneHotEncoder(drop='first'), ['sex'])])" ] }, - "execution_count": 97, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } @@ -1605,7 +1907,7 @@ }, { "cell_type": "code", - "execution_count": 90, + "execution_count": 35, "id": "f0510c4a-83d0-4318-9d39-818f23a8e08d", "metadata": {}, "outputs": [], @@ -1615,7 +1917,6 @@ " (\"knn\", KNeighborsRegressor(n_neighbors=9, n_jobs=4))\n", "])\n", "knn_pipeline.fit(diabetes_X_train, diabetes_y_train)\n", - "diabetes_X_test = \n", "diabetes_predicted = knn_pipeline.predict(diabetes_X_test)" ] }, @@ -1645,28 +1946,17 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 36, "id": "580f604f-e9c5-4109-8b9f-235369836057", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The autoreload extension is already loaded. To reload it, use:\n", - " %reload_ext autoreload\n" - ] - } - ], + "outputs": [], "source": [ - "%load_ext autoreload\n", - "%autoreload 2\n", "from metrics import r_squared, mse, mae" ] }, { "cell_type": "code", - "execution_count": 91, + "execution_count": 37, "id": "e7ce7f32-87ff-4431-b5e4-206ce18ed667", "metadata": {}, "outputs": [ @@ -1685,7 +1975,7 @@ }, { "cell_type": "code", - "execution_count": 92, + "execution_count": 38, "id": "8a4fc5ff-474b-498e-be10-d50578e2b0d1", "metadata": {}, "outputs": [ @@ -1722,7 +2012,7 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 39, "id": "138a7969-8079-4a38-b92e-8eae5d246325", "metadata": {}, "outputs": [], @@ -1768,7 +2058,7 @@ }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 40, "id": "fc461477-8a45-433b-b1a5-b12815ba2899", "metadata": {}, "outputs": [], @@ -1779,13 +2069,13 @@ }, { "cell_type": "code", - "execution_count": 94, + "execution_count": 41, "id": "f23ef387-ec3f-4477-b441-da8591efda0e", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -1799,7 +2089,7 @@ "plt.plot(params, test_metrics, label=\"test\")\n", "plt.legend()\n", "plt.xlabel(\"K in KNN\")\n", - "plt.ylabel(\"YOUR METRIC\");" + "plt.ylabel(\"Mean Absolute Error\");" ] }, { @@ -1814,7 +2104,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 42, "id": "cd21e2b7-8310-4ffb-893f-8c571110037d", "metadata": {}, "outputs": [ @@ -1867,12 +2157,12 @@ "metadata": {}, "source": [ "**Ваши мысли:** я немного подавлена... в общем, я тут поору немного опоссумом... я чувствую себя очень глупой, я забыла все про numpy и matplotlib, я не понимаю статистику, мне хочется плакать... В остальном все хорошо... как улучшить? даже не знаю... это было больно, но в целом полезно.\n", - "Про следующие дз: у меня есть данные из лаборатории - там про мутации в генах BRCA1, BRCA2, ATM, PALB2, CHEK2 и фенотип рака молочной железы, рецепторный статус там, ki-67, возраст манифестации и тд, можно например привести это в нормальный вид и попробовать по фенотипу предполагать в каком гене мутация, могу еще дополнить каким-то количеством данных про пациентов без мутации))" + "Про следующие дз: у меня есть данные из лаборатории - там про мутации в генах *BRCA1*, *BRCA2*, *ATM*, *PALB2*, *CHEK2* и фенотип рака молочной железы, рецепторный статус там, ki-67, возраст манифестации и тд, можно например привести это в нормальный вид и попробовать по фенотипу предполагать в каком гене мутация, могу еще дополнить каким-то количеством данных про пациентов без мутации)))" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 43, "id": "9d9034f6-239b-4633-b47e-a0911bb421f5", "metadata": {}, "outputs": [ @@ -1883,7 +2173,7 @@ "" ] }, - "execution_count": 31, + "execution_count": 43, "metadata": {}, "output_type": "execute_result" } diff --git a/hw1/code/knn.py b/hw1/code/knn.py index 7664cfa..43e7958 100644 --- a/hw1/code/knn.py +++ b/hw1/code/knn.py @@ -122,7 +122,6 @@ def predict_labels_binary(self, distances): for every test sample """ - #n_train = distances.shape[1] n_test = distances.shape[0] prediction = np.zeros(n_test, dtype=bool) @@ -146,11 +145,12 @@ def predict_labels_multiclass(self, distances): for every test sample """ - n_train = distances.shape[0] n_test = distances.shape[0] - prediction = np.zeros(n_test, np.int) + prediction = np.zeros(n_test, dtype=int) - """ - YOUR CODE IS HERE - """ - pass + for i in range(n_test): + nearest_indices = np.argsort(distances[i])[:self.k] + counts = np.bincount(self.train_y[nearest_indices]) + prediction[i] = np.argmax(counts) + + return prediction diff --git a/hw1/code/metrics.py b/hw1/code/metrics.py index 7b58130..f5de55d 100644 --- a/hw1/code/metrics.py +++ b/hw1/code/metrics.py @@ -39,10 +39,18 @@ def multiclass_accuracy(y_pred, y_true): accuracy - ratio of accurate predictions to total samples """ - """ - YOUR CODE IS HERE - """ - pass + labels = np.unique(y_true) + cm = np.zeros((len(labels), len(labels)), dtype=int) + for i in range(len(y_true)): + true_label = np.where(labels == y_true[i])[0][0] + pred_label = np.where(labels == y_pred[i])[0][0] + cm[true_label, pred_label] += 1 + + tp = np.diag(cm).sum() + + accuracy = tp / cm.sum() + + return accuracy def r_squared(y_pred, y_true):