{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "R2AxpObRncMd" }, "source": [ "***Copyright 2020 The TensorFlow Authors.***" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "cellView": "form", "execution": { "iopub.execute_input": "2021-10-08T22:47:32.607821Z", "iopub.status.busy": "2021-10-08T22:47:32.606983Z", "iopub.status.idle": "2021-10-08T22:47:32.609543Z", "shell.execute_reply": "2021-10-08T22:47:32.609950Z" }, "id": "gQ5Kfh1YnkFS" }, "outputs": [], "source": [ "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n", "# you may not use this file except in compliance with the License.\n", "# You may obtain a copy of the License at\n", "#\n", "# https://www.apache.org/licenses/LICENSE-2.0\n", "#\n", "# Unless required by applicable law or agreed to in writing, software\n", "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", "# See the License for the specific language governing permissions and\n", "# limitations under the License." ] }, { "cell_type": "markdown", "metadata": { "id": "uc0VwsT5nvQi" }, "source": [ "# 使用 Tensorflow Lattice 实现道德形状约束" ] }, { "cell_type": "markdown", "metadata": { "id": "gqJQZdvfn32j" }, "source": [ "\n", " \n", " \n", " \n", " \n", "
在 TensorFlow.org 上查看 在 Google Colab 中运行 在 GitHub 中查看源代码 下载笔记本
" ] }, { "cell_type": "markdown", "metadata": { "id": "YFZbuZMAoBny" }, "source": [ "## 概述\n", "\n", "本教程演示了如何使用 TensorFlow Lattice (TFL) 库训练对行为*负责*,并且不违反特定的*道德*或*公平*假设的模型。特别是,我们将侧重于使用单调性约束来避免对某些特性的*不公平惩罚*。本教程包括 Serena Wang 和 Maya Gupta 在 [AISTATS 2020](https://www.aistats.org/) 上发表的论文 [*Deontological Ethics By Monotonicity Shape Constraints*](https://arxiv.org/abs/2001.11990) 中的实验演示。\n", "\n", "我们将在公共数据集上使用 TFL Canned Estimator,但请注意,本教程中的所有内容也可以使用通过 TFL Keras 层构造的模型来完成。\n", "\n", "在继续之前,请确保您的运行时已安装所有必需的软件包(如下方代码单元中导入的软件包)。" ] }, { "cell_type": "markdown", "metadata": { "id": "o4L76T-NpgCS" }, "source": [ "## 设置" ] }, { "cell_type": "markdown", "metadata": { "id": "6FvmHcqbpkL7" }, "source": [ "安装 TF Lattice 软件包:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:32.621087Z", "iopub.status.busy": "2021-10-08T22:47:32.617921Z", "iopub.status.idle": "2021-10-08T22:47:34.898363Z", "shell.execute_reply": "2021-10-08T22:47:34.897772Z" }, "id": "f91yvUt_peYs" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting tensorflow-lattice\r\n", " Using cached tensorflow_lattice-2.0.9-py2.py3-none-any.whl (235 kB)\r\n", "Requirement already satisfied: seaborn in /home/kbuilder/.local/lib/python3.7/site-packages (0.11.2)\r\n", "Requirement already satisfied: matplotlib in /home/kbuilder/.local/lib/python3.7/site-packages (from tensorflow-lattice) (3.4.3)\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Collecting graphviz\r\n", " Using cached graphviz-0.17-py3-none-any.whl (18 kB)\r\n", "Requirement already satisfied: numpy in /tmpfs/src/tf_docs_env/lib/python3.7/site-packages (from tensorflow-lattice) (1.19.5)\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: pandas in /home/kbuilder/.local/lib/python3.7/site-packages (from tensorflow-lattice) (1.3.3)\r\n", "Requirement already satisfied: six in 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dm-sonnet->tensorflow-lattice) (1.12.1)\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/kbuilder/.local/lib/python3.7/site-packages (from scikit-learn->tensorflow-lattice) (3.0.0)\r\n", "Requirement already satisfied: joblib>=0.11 in /home/kbuilder/.local/lib/python3.7/site-packages (from scikit-learn->tensorflow-lattice) (1.1.0)\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Installing collected packages: tabulate, dm-tree, graphviz, dm-sonnet, tensorflow-lattice\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Successfully installed dm-sonnet-2.0.0 dm-tree-0.1.6 graphviz-0.17 tabulate-0.8.9 tensorflow-lattice-2.0.9\r\n" ] } ], "source": [ "#@test {\"skip\": true}\n", "!pip install tensorflow-lattice seaborn" ] }, { "cell_type": "markdown", "metadata": { "id": "6TDoQsvSpmfx" }, "source": [ "导入所需的软件包:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:34.905247Z", "iopub.status.busy": "2021-10-08T22:47:34.904510Z", "iopub.status.idle": "2021-10-08T22:47:38.060549Z", "shell.execute_reply": "2021-10-08T22:47:38.061021Z" }, "id": "KGt0pm0b1O5X" }, "outputs": [], "source": [ "import tensorflow as tf\n", "\n", "import logging\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import os\n", "import pandas as pd\n", "import seaborn as sns\n", "from sklearn.model_selection import train_test_split\n", "import sys\n", "import tensorflow_lattice as tfl\n", "logging.disable(sys.maxsize)" ] }, { "cell_type": "markdown", "metadata": { "id": "DFN6GOcBAqzv" }, "source": [ "本教程中使用的默认值:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:38.066735Z", "iopub.status.busy": "2021-10-08T22:47:38.065994Z", "iopub.status.idle": "2021-10-08T22:47:38.068987Z", "shell.execute_reply": "2021-10-08T22:47:38.068480Z" }, "id": "9uqMM2joAnoW" }, "outputs": [], "source": [ "# List of learning rate hyperparameters to try.\n", "# For a longer list of reasonable hyperparameters, try [0.001, 0.01, 0.1].\n", "LEARNING_RATES = [0.01]\n", "# Default number of training epochs and batch sizes.\n", "NUM_EPOCHS = 1000\n", "BATCH_SIZE = 1000\n", "# Directory containing dataset files.\n", "DATA_DIR = 'https://raw.githubusercontent.com/serenalwang/shape_constraints_for_ethics/master'" ] }, { "cell_type": "markdown", "metadata": { "id": "OZJQfJvY3ibC" }, "source": [ "# 案例研究 1:法学院入学\n", "\n", "在本教程的第一部分中,我们将考虑一个使用法学院招生委员会 (LSAC) 的 Law School Admissions 数据集的案例研究。我们将训练分类器利用以下两个特征来预测学生是否会通过考试:学生的 LSAT 分数和本科生的 GPA。\n", "\n", "假设分类器的分数用于指导法学院的招生或奖学金评定。根据基于成绩的社会规范,我们预期具有更高 GPA 和更高 LSAT 分数的学生应当从分类器中获得更高的分数。但是,我们会观察到,模型很容易违反这些直观的规范,有时会惩罚 GPA 或 LSAT 分数较高的人员。\n", "\n", "为了解决这种*不公平的惩罚*问题,我们可以施加单调性约束,这样在其他条件相同的情况下,模型永远不会惩罚更高的 GPA 或更高的 LSAT 分数。在本教程中,我们将展示如何使用 TFL 施加这些单调性约束。" ] }, { "cell_type": "markdown", "metadata": { "id": "vJES8lYT1fHN" }, "source": [ "## 加载法学院数据" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:38.076730Z", "iopub.status.busy": "2021-10-08T22:47:38.075896Z", "iopub.status.idle": "2021-10-08T22:47:39.449673Z", "shell.execute_reply": "2021-10-08T22:47:39.449091Z" }, "id": "Cl89ZOsQ14An" }, "outputs": [], "source": [ "# Load data file.\n", "law_file_name = 'lsac.csv'\n", "law_file_path = os.path.join(DATA_DIR, law_file_name)\n", "raw_law_df = pd.read_csv(law_file_path, delimiter=',')" ] }, { "cell_type": "markdown", "metadata": { "id": "RCpTYCNjqOsC" }, "source": [ "预处理数据集:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:39.454841Z", "iopub.status.busy": "2021-10-08T22:47:39.454118Z", "iopub.status.idle": "2021-10-08T22:47:39.456721Z", "shell.execute_reply": "2021-10-08T22:47:39.456181Z" }, "id": "jdY5rtLs4xQK" }, "outputs": [], "source": [ "# Define label column name.\n", "LAW_LABEL = 'pass_bar'" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:39.463667Z", "iopub.status.busy": "2021-10-08T22:47:39.462925Z", "iopub.status.idle": "2021-10-08T22:47:39.470736Z", "shell.execute_reply": "2021-10-08T22:47:39.470224Z" }, "id": "1t1Hd8gu6Uat" }, "outputs": [], "source": [ "def preprocess_law_data(input_df):\n", " # Drop rows with where the label or features of interest are missing.\n", " output_df = input_df[~input_df[LAW_LABEL].isna() & ~input_df['ugpa'].isna() &\n", " (input_df['ugpa'] > 0) & ~input_df['lsat'].isna()]\n", " return output_df\n", "\n", "\n", "law_df = preprocess_law_data(raw_law_df)" ] }, { "cell_type": "markdown", "metadata": { "id": "YhvSKr9SCrHP" }, "source": [ "### 将数据划分为训练/验证/测试集" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:39.477695Z", "iopub.status.busy": "2021-10-08T22:47:39.477021Z", "iopub.status.idle": "2021-10-08T22:47:39.490355Z", "shell.execute_reply": "2021-10-08T22:47:39.490766Z" }, "id": "gQKkIGD-CvGD" }, "outputs": [], "source": [ "def split_dataset(input_df, random_state=888):\n", " \"\"\"Splits an input dataset into train, val, and test sets.\"\"\"\n", " train_df, test_val_df = train_test_split(\n", " input_df, test_size=0.3, random_state=random_state)\n", " val_df, test_df = train_test_split(\n", " test_val_df, test_size=0.66, random_state=random_state)\n", " return train_df, val_df, test_df\n", "\n", "\n", "law_train_df, law_val_df, law_test_df = split_dataset(law_df)" ] }, { "cell_type": "markdown", "metadata": { "id": "zObwzY7f3aLy" }, "source": [ "### 可视化数据分布\n", "\n", "首先,我们可视化数据的分布。我们将为所有通过考试的学生以及所有未通过考试的学生绘制 GPA 和 LSAT 分数。" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:39.497490Z", "iopub.status.busy": "2021-10-08T22:47:39.496825Z", "iopub.status.idle": "2021-10-08T22:47:39.499431Z", "shell.execute_reply": "2021-10-08T22:47:39.498959Z" }, "id": "dRAZB5cLORUG" }, "outputs": [], "source": [ "def plot_dataset_contour(input_df, title):\n", " plt.rcParams['font.family'] = ['serif']\n", " g = sns.jointplot(\n", " x='ugpa',\n", " y='lsat',\n", " data=input_df,\n", " kind='kde',\n", " xlim=[1.4, 4],\n", " ylim=[0, 50])\n", " g.plot_joint(plt.scatter, c='b', s=10, linewidth=1, marker='+')\n", " g.ax_joint.collections[0].set_alpha(0)\n", " g.set_axis_labels('Undergraduate GPA', 'LSAT score', fontsize=14)\n", " g.fig.suptitle(title, fontsize=14)\n", " # Adust plot so that the title fits.\n", " plt.subplots_adjust(top=0.9)\n", " plt.show()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:39.504737Z", "iopub.status.busy": "2021-10-08T22:47:39.503994Z", "iopub.status.idle": "2021-10-08T22:47:58.796751Z", "shell.execute_reply": "2021-10-08T22:47:58.797185Z" }, "id": "feovlsWPQhVG" }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "law_df_pos = law_df[law_df[LAW_LABEL] == 1]\n", "plot_dataset_contour(\n", " law_df_pos, title='Distribution of students that passed the bar')" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:47:58.822801Z", "iopub.status.busy": "2021-10-08T22:47:58.802167Z", "iopub.status.idle": "2021-10-08T22:48:00.191834Z", "shell.execute_reply": "2021-10-08T22:48:00.192300Z" }, "id": "ct-2tEedU0aO" }, "outputs": [ { "data": { "image/png": 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pZM3hKjZkV9OkMa83xYf6M6pPOIMTQhmcEMLghFCSIwK6xTG5i9ZgZO3hKn7eW8qKgxVoDSbGpUZww+RUzhmWgK+3Mvo6gShOywGK01JQ6GKK69Qs2VfG4n1lZJY0AGYnNTMjhkn9IxmfFklS+Ml1UK6oV+v4bmcxn24poKBGTVyoH7dO68s1E1IUEceJoeeeHCcZxWkpKHQB5Q0almSWsXhfKbsL6wEYmRzG2cMSOGNQDAPjQnq0k3KEySRZe7SKd9fmsjm3hhB/b26cnMrNU/oSE+J3ss07lel9J8sJQnFaCgrHSU2zlqWZZfyyt4ztBbVICUMSQjl/ZALnD08kJSrwZJvYpewtqufttTksP1COj5eKq8f34a5Z/UkICzjZpp2KKE7LAYrTUlDwgCaNnt8OVLBobykbsqsxmiTpscFcMDKR80Yk0D8m+GSb2O3kVjXz7rpcvttZjEoIrp7Qh7tnDSA+zP9km3YqoTgtByhOS0HBBa06I2uPVLJobykrD1WiNZhICg/gwlGJXDgykUHxvXPq749SVKvmP2uy+XaH2XldM6EPdynOq6s4/U4oN1GcloKCHSobNazMqmTFwQo2ZFejNZiIDjZLwS8clcSYlPDT0lHZo6hWzVurs80jL5Xg2gkp3DWrP3GhivP6AygnlwMUp6WggHk0tauwji25Naw7UsXeYrPqLzkigLmD45g7OI5J/SLxVjbdOqSoVs2bq7L5blcxXhbndfcZ/YkNUZzXcaA4LQcoTkvhtESjtzqpWrbk1LCnqB6d0YRKwIjkcOYOjmXukLheq/o7mRTWqHlz9VG+31WCn7eKW6f15fYZ/QhVpPKeoJx0DlCclsJpgd5oYm9RPRuyq9mcU8Puonp0BrOTGpYUxuR+UUzqF8W4tAhlH1IXkVfdwku/HWbxvjIiAn2454wBXD8pFX8fr5NtWm9AcVoOUJyWwimJlJLsymbWH61mY3Y1W3JraNEZEQKGJYYxqV8kk/tHMS4tUhkBdDOZxQ08/2sW649WkxQewANz07l0THKnGIkK7VA6xwGK01I4ZTCZJHuL61l+oJxf95eTX6MGoG90EFMHRDFtQDST+0UTFqg4qZPBxuxqnl+exd7iBtJjg3nsvMHMGhh7ss3qqShOywGK01Lo9ZTUt/LdjmK+21VEUW0r3irBlAHRnDU0jpkZMSRHnFqbfHszUkqW7y/nueVZ5NeoOWNgDI+dN4QBsaf+/jYPUZyWAxSnpdArMZkka49U8cHGPDZkVyMlTBsQzSWjk5g7JI6wAGU01ZPRGUx8vCmf11cepVVv5IbJqTwwJ0MZBR9DcVoOUJyWQq9CazDy464S3t+QR3ZlM3Ghflw9PoXLxybTJ1IZUfU2qpu1vPTbEb7eXkhYgA8PnpnBNRNSlK0FitNyiOK0FHoFOoOJb3cW8eaqbMoaNAxOCOX26X05f0SikjLjFOBgaSNPLT7I5twaMuKCWXDBUKYOiD7ZZp1MFKflAMVpKfRoTCbJj7tLeHXlEYpqWxmdEs5f52YwPT1a2T91iiGl5NcDFTy99BCFtWrOGhrHP84bcrqOoJWT2wGK01LosWzLq+XJxQfYX9LIsKRQ/nbmQGYNjFGc1SmORm/kfxvyeHNVNkYpuWN6P+4+oz+Bvt4n27QTiXKSO0BxWgo9jqJaNc8uy2JJZhkJYf48fM4gLhyZqDir04zyBg3PLjvET3tKiQ/155FzT6vz4LRo5PGgOC2FHkOL1sBbq7N5f0MeXkJw58z+3DGjHwG+SgSF05mdBbUsXHSQzJIGxqVGsPDCoQxLCjvZZnU3itNygOK0FE46UkoW7yvj30sOUd6o4ZLRSfz97IFKckGFNowmyXc7i3h++WFq1TouG5PMA3PTT+U9eIrTcoDitBROKofLm1iwaD9bcmsZlhTKExcOY2xqxMk2S6GH0qjR88bKo3y8uQApJddOSOGe2QNOxUjyitNygOK0FE4KjRo9r/5+lI835xPi781DZw3k6vEpSjw6Bbcoa2jl9ZXZfLOjCB8vwc1T+nLnzH6EB/qebNO6CuWH4ADFaSmcUEwmyQ+7S3h22SFqWnRcMyGFh+YNJCLolLnYKJxA8qtbeGXFERbtLSXAx4urxvfhlql9TwWZvOK0HKA4LYUTRmZxAwt/OcDOgjpGp4Tz5IXDGJ58yi+oK5wADpc38c7aHBbtLUUC5wyL58bJaYxPi+itasNeafSJQHFaCt1OYY2aF387zKK9pUQH+zL/7EFcNiYZlTIVqNDFlDW08uHGfL7cWkiT1kD/mCCumZDCpWOSiexdo3nlx+EAxWkpdBvVzVreXJXN51sL8FapuG26ksFW4cSg1hlYsq+ML7YVsruwHi+VYNqAaC4cmci8oXG9IdGn4rQcoDgthS6nXq3jw435vL8+F43BxFXj+/DAnHRiQ085hZdCLyCrvJGfdpfyy95SSupb8fNWMXtQLOePSOSMQTE9NdKG4rQcoDgthS6jslHD+xvy+HxLAS06I2cPjeehswfSP0bJlaRw8pFSsquwnl/2lrJ4XxnVzVr8fVScMTCWc4YnMHtQLMF+PcaBKU7LAYrTUvjD7C2q5+PN+SzeV4bBaOKCkYncNas/g+JDT7ZpCgp2MZok2/JqWba/jGX7y6lq0uLrrWJmRgznDo9nzuC4kz2NrTgtByhOS+G4aNToWZZZxhdbC9lb3ECQrxeXjknmtul9SY0KOtnmKSi4jdEk2VVYx9LMMpZlllPeqMHXS8W09GjOGRbPvCHxJyM5peK0HKA4LQW30RlMrDlcyU97SlhxqBKdwcSA2GBumJTKpWOSesPitoKCU0wmye6iepZlmkdgJfWteKsEUwdEc+7weM4cEn+iVIiK03KA4rQUnKLRG9mYXc2KQxUs219OvVpPVJAvF4xM5JLRSYxIDuut+2AUFJwipWRfcQNL95tHYIW1arxUgunp0Vw+Npm5g+Pw9+m2YM7Kj8oBitNS6ERVk5ZVWRWsOFTJ+qNVaPQmgny9mD04jktHJzEtPRofJR26wmmElJIDpY0sySzjp90llDVoCPX35oKRiVw+NplRfcK7+uZNcVoOUJyWAlJKjlQ0s+JQBSsOVbCnqB4pITHMn7lD4pgzOI5J/SLx81ZShCgoGE2SzTk1fLeziOUHytHoTfSPCeLysX24ZHQS8WFdsrVDcVoOUJzWaYpGb2RLbg1rDlex4lAFxXWtAIxIDmPu4DjmDo5jcEKIMvWnoOCERo2epfvK+H5XMdvz61AJmJYew+Vjk5k35A9NHyo/PAcoTus0Ir+6hTWHK1lzpIotuTVo9Cb8vFVMHRDN3MFxzBkcS5yyAVhB4bjIq27hh13F/LCrhJL6VkL8vTl/hHn6cEyKx9OHitNygOK0TmFaddbRlNlRFdSoAegbHcTMjBhmDoxhcr+o7lxMVlA47TCZJFtya/huZzHL9pfTqjfSNzqIy8cmc8noJBLD3UpuqjgtByhO6xSiVWdkZ0EdW3Jr2JJbw97ievRGib+Pisn9opg1MJZZA2OUfVQKCieIZq2BpZllfLezmG15tQgBU/tHc9GoRFf7vxSn5QDFafVSDEYT2VXNZBY3sL+kgX0l5r96o8RLJRieFMakflFM6R/FhL6RymhKQeEkU1ij5vtdxXy/q5jiumP7v84ZFs+8oZ32fylOywGK0+rhaA1GCmrU5FY1k1PVQm5VCzlVzWSVN6LRmwAI8vViaFIYY1IimNQvknFpkT0phpqCgoINUkr2FjeYQ0jZ7P8anxbBjIwYZmbEMDQxTHFaDlCc1knEaJJUNmkoa9BQVq+hrKGVUuvfBg1l9a1UNWux/YriQv3oFx3M4IRQRiSHMSwpjH7RQUpuKgWFXoh1/9ey/WWsPFRJVnkTAPnPnqf8oB2gOK0uRmcw0dCqp7pZS3WzlqomreV/Xdv/1r81LTo6dn+grxcJYf4khgeQGBZAQrg/faOD6BcdTN+YIGUEpaBwClPZqGHd0WouH5usOC0HnLJOq7JJg9EkMUmzmsckLf9LaXlu+V9KTCab/6VEozeh0RuP/TUc+1+rN9KiM9LQqj/2UB/7v1VvtGuPn7eKmBA/ooP9jv0N9iU21J/EcH8SwsxOKjTAW9kbpaCgoFwEHHDKOq3RT/5GnVrfLQcP9PUiLMCHsAAfQgN8CLf83/YI9CEqyOqcfIkJ8SPYT3FGCgoKbqNcLBzQK52WEGI5EO3BR6KB6m4ypyeitPfU53Rr8+nWXn8p5bCTbURPpFc6LU8RQuyQUo472XacKJT2nvqcbm1W2qtgRQnVraCgoKDQa1CcloKCgoJCr+F0cVrvnmwDTjBKe099Trc2K+1VAE6TNS0FBQUFhVOD02WkpaCgoKBwCnBCwysIIbYAGstTo5RyjhAiEngWyAXSgUellBUn0i4FBQUFhd7BiY4JtFxKubDDa08DK6SU3wghLgBeBG44wXYpKCgoKPQCTuialhDie2AbEABsl1IuEUIUAVOklEWWUVe2lDLyhBmloKCgoNBrONEjreeklNuEEF7AOiFEExALNFnebwQihBDeUkqD7QeFEHcAdwAMGTJk7IEDB06k3QoKCgonEqdhnGyvhyH9Ro9tzNl1Qow6wdjtgxMqxJBSbrP8NQLrgTOASiDEUiQUqOvosCyfeVdKOU5KOS4gwK101QoKCgqnJLbXQ0Nr88k254RywpyWEGKQEOJWm5fSgRxgCTDZ8tpUy3MFBQUFBTcwSoneaDrZZpwwTuT0YCNwnhAiEfOIqgj4AlgKPCeEyAD6A/93Am1SUFBQ6PXUq/XEhPidbDNOCCfMaUkpS4FL7bxVC9x+ouxQUFBQONWoadGeNk5L2VysoKCg0Mspq9e4LnSKoDgtBQUFhV5OSX3ryTbhhKE4LQUFBYVejEBxWgoKCgoKvQQfLxWlitNSUFA4lVi4sHfX39PoSe1VnJaCgsIpxxNP9O76exo9qb0+3oKSOsVpKSgonAIsXAjCEgxHiK4fIXR3/T2NntheXy8V5Y0atAbjyTblhNArk0COGzdO7tix42SboaDQaxACuvOn3t319zROQHudxh60ZcCQkdJw4dP89tcZZMSFuP5A7+Hkxx5UUFA4OSxY0Lvr72n0pPb6+Zgv4zmVp0cMQsVpKSicBihCjK6lJ7XXz9vitKoUp6WgoHCa4ulFuSddxKHn2dOdqIQgMcyfnKqWk23KCUFxWgoKCp3wVB3Xk9R00PPs6W76xwZztLLJdcFTAMVpKSgotOGpOq6nqel6mj0niiGJoRwubzotFISKelBBQaETnqrjepp6sKfZcxy4rR4cN26cfOKDX7jni138cu80hieHdaddJxJFPaigoOAenqrjepKaDnqePd3NCIuj2ldSf3INOQEoTktBQaETihCjd5EcEUB4oA97i+pPtindjuK0FHocp9sF53hQ+kjBFiEE41Ij2ZpXe7JN6XYUp6XQ4zjdlF/Hg9JHCh2Z1C+Sghr1KR88V3FaCj2G01X55QlKHyk4YnL/KAC25NacZEu6F8VpKfQYFi48pviSUrkg20PpIwVHDI4PJTzQh43ZitNSUDihnG7Kr+NB6SOFjqhUghnpMaw5XInR1Lv1/s5QnJZCj0MZPbhG6SMFe8wdEkdNi449RXUn25RuQ3FaCqcdaWmelT8dHURPC7Db08r3VGZmxOCtEvx+sPJkm9JtKBExFE47enu0hxNBT8u/1dPKnwA8iohhez28/v2tlDa0svLBmQjhdjU9ESUihsLpTVpae+WdqxHX6ajU62mZjnta+d7AucMTyK1q4UBp48k2pVtQRloKpx2nwF14t6OMtE46xz3SalDrGf/vFdwwOZV/nj+kW4w7QSgjLQUFgNRUz8qfjkq9npbpuKeV78mEBfowa2AMi/aWYjCaTrY5XY7itBQ8prdPoeTne1Z+zZrusOLE4ul39tFH3Vt/TxNK9PZzuiOXjE6iqknL+uzqk21Kl6NMDyp4TA+cSulWToX2nm7Taz3NnuPguKcHAbQGI1OfXcXI5HD+d/P4LjfuBKFMDyr8MU7FRWtnzJrVvr2zZp1Ma44PT74zKSVp/Y14+etR+ekR3kbS0pxf+XvaOdHT7DlZ+Hl7ce2EFFYdrqSgpuVkm9OlKCMtBY/p7rvYhQu792Ljaf2nwF17WxuklBTVtrK/tIGsskZyqlsorFFT0aihpkXXKZKCj5cgNsSfpPAABsQFMyQhlHFpEWTEhqBSiU719xR6mj3HwR8aaQFUNGqY+uwqbpqS1lsFGXb7wPtEW6HQ++nuResnnuhep+Vp/TNndpsp3Y7JJDlU3sjlj9Vw28e17C6so6ZFB4BKQJ/IQFKjghiSEEpUsC8h/j74eqt46kl46BEjjRo9lY1aiuvULN5byhdbCwGICPRhRkYM84bEM3tQLAsWeJ3MZnbiVBJWHC9xof6cMzyBb3YU8cDcdEL8fU62SV2CMtJS6DEsXNg+5caCBV3rvLq7/p5CdbOWdUeqWHukig1Hq9ucVGpUIONSIxmdEs7I5HDS44Lx93Hf2VhHadvza9mYXc2aI1XUtugI9PXinGEJXD2hD+NSI3r7htaewh8eaQFkFjdwwZsb+OvcDP4yN73LjDtB2O0DxWkp9Dh62h6hE4GnU5a25aWUHChtZOWhSlZlVbCvpAEpISrIl+np0UxPj2HqgGjiw/zdrn/WLNeqSaNJsjWvhkV7SvlueykGjAyKD+FPU9O4aFSSRw7xZPNH+r+b6BKnBfDnT3ewKbuG9fPPIDzQt0uMO0EoTkuhd9CdFwSjSfLwE1puvF1Lo0aPRm/EaJL4eKkI8PUiMsiX6GA/IgJ9TuiIwVNHqvLX88u2atYcrmTtkSoqm7QIASOTw5k9KJZZA2MYlhjWbt2pW+3xNfDlxlI+3JhPVnkT0cG+3Dg5jZsmpxEW2POnpXqgWrLLnFZWeSPnvLaeu2b25+9nD+oS404QitNSOL3QGozsKaxnd1E9mcUNHKloIr+mBb3R9Tkf6OtFSmQg/WODGRQXwpDEUIYnhREb6v5oxR3cnbLU6I3sKarnmf/VsLWgGr/EeoRK4os3Z46IYVZGDLMGxhIT4veH7Jk1C9auPfZ85kznI66O9j/+uOSsG2t4d10uaw5XEeTrxXWTUrltWt8u77uuwNMp4xM4xdxlTgvg/i93s+JQBWv+b1aP/B4coDgthVOfykYNvx6sYMXBCrbm1aDRmyMC9IkMYGBcCP1jg0mOCCQuxI+wAB8CfL1QCYHeaEKtM1LboqOySUtJXSv5NS0crWyiqPZY+vK4UD9GJoczso95XWh4UliXjCRs79yllJQ3asgsbmB3UT078+vYU1SPzmhCJWB4cjhrv45mxScxjOoTjrdX1+9c6YqRx6GyRv67JofF+0rxVqm4fFwyd87oT0pUYNca2wWcyiMtgPzqFua9so5zhsfz2tWj/7BxJwhFPahwatKqM7Iks4zvdxazJa8GKSEtKpCrx6cwdUA0Y1MjiAw6/rn8Zq2BQ2WNZBY3sLe4nn3FDfx2sKLt/aTwAAYnhDAgNoR+0UH0iQwkPsyfmBA/gny97E4z6o0m6iwOsrS+lcsfa+UfPzWTXdnM4fIm6tR6wCw5H5IYxk1TUpnYN4oJ/SIJ9fdhYRWMSzvuJrnEU8WkPbXe4IRQXr9mNH+bl8Hba3P5bkcxX20r5NzhCdw5sz/DksK6xtgu4FQP+5QWHcSdM/vx+qpsrhrfhyn9o0+2SceNMtJS6LUU1qj5aFM+3+4sokljIC0qkItGJXHeiATSY4O7dU2qXq1jf0kjmSUNHCht4GhFM7nVzZ2mHr1UgiBfL3y9VYDAYDKh0RvbRoC2hPp70y8mmEHxIQxOCGVYUhhDE0N7laDBGRWNGj7YmMcXWwpp0hqY3C+KW6b1ZfagWLyOc+3tFKZLR1pgnmI+85W1+Hl7sfT+6ZZzskejTA8qnBocLm/izdXZLN5XipcQ9CGBZ29LYULfSLccVVqaZ/EH3RWG6I0myuo1FNaquf52DY88YRZ7NGsM6E0SKc0jJz9vFSH+PkQE+RIT7EtCWABfvh/AMwt93Xa04eFQX+9+G9xRA56o8o0aPTP/VEjAiHxKGzSkRAZy4+RULh+b7FDddgLUej2NLndaACsPVXDrxzt46KyB3HPGgOM27gShOC2F3k1hjZqXfz/Mz3tLCfTx4vrJqdwytS/xYf49Lq5eT4v1JwToDSbKGjQU1ampbNRS3aylWWugVW8EwEelItjfm8ggX266PIDcvUHEh/q75UiPxx6dwcRvByr4cGMeOwrq8PVWcd7wBK6ZkML4tPb7vXriNoVuplucFsDdn+9kxcFKFt03lUHxocdl3AlCcVoKvZMWrYG3Vmfz/vo8VCr409S+/HlGP1593tcjJVdaGhQUHHuemup8xHU8SrHuPkZ4ODQ0HHseFmZ/xFXdrCWzuIG/PtlAiboJn+gmfCJaEF6df+++3ioE5pFihyhOqAw+TBsSzoS0CGZmxDI0MbSdjN5TtaGj8gdLG/liWwE/7y6lSWue6r10TDIFa5N4+aljwo1TdUO4HbrNadU0aznr1XXEhPjz8z1Te/I0oeK0FHofq7MqeezHTEobNFw6Oom/nz2o0ybZnjaqOdE2aQ1GDpQ2sruwnt2FZqVhcd0xxWNKZCBZW0L42x3BpEUF0ifCLBSJCvYj2M+7bT1JSolaZ6S6WcugMa2881Uzh8qa2F1Yx+GKJqSE2BA/zhkWzwUjExlrE/2iq9qr1hlYsq+MH3aVsDm3BoDxaREsfzeR3LUJf1jS34voNqcF8PvBCm7/ZAf3njGA/ztroMfGnSAU9aBC76FJo2fhooN8v6uY9Nhgvr9rMmNTI+2W9VTJdSKSQHbnMSobNUSPrOfppXXsLKgjs7gBnSXZX2KYP6NTIrhpchojksMYkhhKiL8Ps2bB/LOd1yuEIMjPmyA/byb2DeLGyccUZjXNWtYeqeK3AxV8tb2IjzcXkBYVyBXj+nDFuGRmzvRs748jdWKgr7elzj4U16n5eU8pP+4uIWreASY+fYCJfaM4d3g884bGE9d79hv1OM4cEscVY5P5z5pszhgU4/C31RNRRloKPY59xfXc+8VuiuvU3D1rAPfNGYCf96mhoPOUVp2RA6UN7Ckyb5LeU1hPSb15FOXrpWJ4chhjUsIZmxrB6JSIE3Ihb9YaWL6/nO92FrEltxZvleDMIXFcNzGVqQOiuly1KaXkcEUTS/eVsSSzjJwqc6qNkclhzB0cx5zBcQxOCDnVYh5260gLzDeG572+AYPRxJL7pxPxB7aFdBPK9GBv5XRSTn29vZD53x4gMcKX168Zzbg013eA7irpjCaJzmDCSyXw8RLdptQ7Xpq1BrLKGjlQ2siB0gYySxo5UtHUli4kKTyAUSnhjO4TzuiUcIYmhnWbHN7fHzQa1+Vyqpr5ensR3+4ook6tp19MENdOSOGyMclOL4J/RJ14tKKJ3w5W8PvBCvYU1QPmEebMgebwVVMHRBPs59kkkqeK0hNAtzstMAfUvey/m5iWHs37N4477rBf3YTitHorp4NyymiS/GvJQT7cmE9rXjRZH4x2+86vY/+U1LeyOaeG/SXm0E2l9a1UNGrbVHJg3j8VFuBDTLAfSREBx0I2xYcwMD6EUJs0Dl3d/xq9kYIaNdmVzRypaOJweROHyhspqFG3lYkM8mVYUhgjksIY2SecUX3CT+h6jqdt1uiNLM0s47MtBewqrG9TAl49vo/drQhdtQZW2aRhdVYlKw9VsimnhmatAR8vwbjUSGYNjOGMQbFu7dnrgb+xE+K0AD7ZnM/jPx/g4XMGcefM/sddTzegOK3exumSSkOjN/KXr3bz64EKGnekUbdqCEjhUolmq6Tzjmgmakwpw88t42hlM2COH5geF0JKZCCxIX6E+Hvj661CSvOCf71a3y5kk1p3zKklhQeQvzcEdVkw+tpgDHWBBBJAeZ6/U7WVlJJWvZHqJh2VTRpKGzSU1LVSVKemqFZNXnULJfWtbRdIIaBvdJB5Q3F8KEMSQxmaGEZcqN9Jme7y9wet9thzPz/3Rly2ZJU38sXWQn7cVUKT1kBqVCCXjUnmktFJ3HBpYJeoDe2hN5rYWVDH6sOVrD1cRVZ5E2D+LmcPimXukDgm94tq9/15qvY8gZwwpyWl5N4vdrP8QDlf3DaRif2ijruuLkZxWr2VHngX2GW06ozc9sl2NmbX8Pj5Q7hlWl+32yulZFNODZc+lkNA32pUAib0jeTMIfFMHRDVKbuuq7rKGjQcLm/iYFkjh8ubOFLRRG5VS5vIwUqwnzch/t74eavwUgmkBJ3RRKvOSJPG0Kk8mJMm9okMJC0qiLToIPrHBDEgNpj+MZ7ltHJmf71aT0GtmuI6ddvosrJJS12LjoZWPS1aA1qDCaNJohJmqXuIvw/hgT7EhZqzE/ePDWZgXAiDEoOQpj8mhVbrrGtfxWzKMSsBJ6RFcsGoRG6eHY9R7f7I8Xh+A2UNraw9XMWqrErWH62mVW8kxN+bM4fEceHIRKYNiG6L29gDf2MnzGmBecP3xW9upKFVz8/3TiU5okfEh1ScVm/lVF3TatUZ+dNH29iWV8sLl4/ksrHJgHvrHZnFDTy1+CDb8msxtfjx90tSuXJcny6PYG0wmojt28qPK9SUWRxBQ6ueJo0endGEwSRRCYGPShDg60WIvw9hAT5EB/sSE+JHYngACWH+XZY11miSFNaqOVrRRHaVOVZhTlULeVXNNGoM7coG+noRG+JHZJAvYQE+BPp54+/thZcKTNK8ubdJo6dOraeiUUN5o+ZY0F69ikkZ4UzsG8mk/lGMTY34Q2KYolo1P+0u4ee9pWRXNoMUTM+I4tzhCZw5JI7oYOcOzNM1sI5o9EY2HK1m+YFyfjtQTqPGQHSwH1eMS+baCSlMHxPYU0ZYVk6o0wLz+uTFb20kOSKQ7++aTKDvSReX9wynJYQIALYCv0kp/08I4Q+8CJQA6cCzUsojzuo43ZxWT6MrnKjOYOK2T3aw4WgVr1w1iotGJblVv1pn4Pnlh/l4cz5RQX78Zc4A7juvD/W17l9QuyuM0x/B3kW5rkXHwbJGDpU1cqisicMVjRytaEZrODaSiwv1o39MMP1igkiLCiI1KojkiAASwwMI9fdum2J0p80avZH8mhYOlTXy1ycbGD67jgOlDZgkBPh4MXVAFLMHxTF3SCyxIcd3c2BVAl71UCnhI8ooqFGjEjA+LZKzh8Vz1tB4EsMDOn2uK5M0ag1GVmdV8d3OIlZlVQLQR8Tz5t0DGJ7cPUF8j+McOuFOC2D14Upu+Wg75w5L4M1rR59sRWaPcVovAdFAlcVpPQyYpJTPCyGGA/+RUk53VofitE4uf3QqxWSSPPD1HhbtLeW5y4Zz1fgUt+o/VNbIPV/sIq+6hRsnpfK3swYS6u/TIzcXe4p3iIZlWxvYbwnAe6C0kbKGY4tJsSF+DIwPYVB8COlxIdxwYQjVuUFuj+COt81NGj1bc2tZd7SKlYcq2+T2I5PDOHNIHPOGxh9XcGIhzOfBwbJGft1fzrL95W1rkcOSQpk3JJ55Q+MYGGeWsnfXd1bW0MrHmwp469cCvPwNnDU0jofPGUzf6CCP2tNV9th+xN2CXX09fHddDk8vzeJvZ2Zw35z0Lqv3OLDfB1LKE/YAbgAuBRYCL1peWw9MtynTCITa+ewdwA5gR0pKilQ48SxYIKX5p2d+LFhwfPU8u+yQTJ2/WL61+qjb9S/LLJMD/7FUjv/X73JjdpWUUsqwsPblw8KcHzc1tX351FTn5buqvR1p1ujlxqNV8s1VR+Xg27fLpLt/l6nzF5sff18s5760Rv7ly13ynbXZct2RSlndpDlumzxts7PyJpNJHixtkG+sPCIvfHNDm80zn18ln/zlgNxwtEpq9Uan9c+c2b7+mTOPvZdd2ST/szpbXvzWBpn2sLnuYQ+vkhGzD0i/PtUSYXTZXk/7x1pe+Opk2JQjcsD85TL90aXyheVZUqM3OP+wG/yBc8jVtbTbrocmk0k+8NVumTp/sVy+v6xL6/YQu20/YSMtIcQQ4Hop5aNCiIVAsDSPtA4DV0kp91jKFQOzpJTZjupSRlonlz8y8vhhVzEPfrOXayak8PQlw+zeoXes/9MtBTz+835G9Qnn3RvGdZJ+9/SRVkWjhm15tezIr2V7fh1Z5Y1tMf76RgcxIjmMD18MZ/X3YQxOCHVrLaEntLmiUcPvByv47WAFW3Jq0BlNBPt5Mz09mjMGxTIzI8bhZmdX9Vc2aVh5qJJfD5SzKacGncFEeKAPswfFcvbQeKanxxDg63hK+HjbW9mk4dmlWfywu8ScD+zqUaTHhbhfURfZw0kcaYF5qviqd7eQXdHE93dPOVmBdU96GKdLAI1lOnAa4CuEeACoBGzPilDLawo9lONNgLevuJ6Hf8hkUr9InrxoqMMpJdv6rXtI5g6O5Y1rxti9UIV5uAzR3WGcKps0bM6pYVN2DVvzasi37L8K9PViTEoE985OZ0yKee+VNRXH3rdhrJt26Qwm/vrPVrbkaqho1FDVpKW6WUe92qIS1BlRaw3ojSaMlitl6m0qrnxHRZCvF6EBPkQF+RETYt6j1icigH7Rwe0yMLvTR3Gh/lw/KZXrJ6XSojWwMbua1YcrWZVVybL95QAMjAtheno0MzJimNA3sk0p6SrJZGyIP9dMSOGaCSm0aA3c868qIgeaM1L/sKsEfx8VMzNiOGdYAnMGx3aaJj3epI6xIf68fNUozhuRwN+/28eFb27ktatHMW9ovGcVOqi/t+Dv48W7N4zlgjc2cNvHO/jx7qk9Ju7jSVEPdhhpKWtapwH1ah3nvb4BgEX3TiXKhVoM4KfdJTzw9R7mDo7jv9ePwacb0sp3BWqdga25taw/Ws2G7CqOVJjXZkL8vZnYN9KccbhvJEMTQ9sk1q6QUlLaoOFIRRPZlgSTuVUtFNWqKbNR+Vnx8RKEB5pVgsF+3gT4mBNPeqmEOYK7SaLVG2nRGWhsNVDTrKXFZl8aQHSwHwPjgxkUH8qQhFCGJ4fRPybY4wSNUprXqtYfrWbdkSp25NehM5rw81YxoW8kUwdEM21ANEMSQj2OwKA3mtiaW8tvB8v59UA5FY1afL3NDuyiUYnMGRTndATmCZWNGm7/dCf7iut54sKh3Dg5rUvqdZOTOtKysreonqve3cyg+FC+umPSiU5I2mOEGJcB9wC+wFvAT5jVg2XAAOBpqagHTykWLJAU9d3B+qNVfHvnFEb1CXdaPi0NvltTy7XvbWVMajgf3zLBqdzaUzXgHwkhBOaLclZ5E2uPVHW6KI9PM1+Un/trFDk7w9y64EspCY5r5cvf69lXVE9mSQMHyxppspGwRwX5khYdRGpkIMmRgTz7jwB++CyA+DA/YoL9CQ3wdiqGsBeWqVlroLS+lcIaNbnVzRytsEToqGhqy6wc5OvFSEvYqFF9IhxG5nD2HVid+tojVWzKqW5z6tHBvsxIj2FGRgzT0qOdyt7tqe9MJsnuojoW7ytjaWYZFY1agv28OW94Al8/04e8HeFuC0QcnRMavZH7vtzN7wcrePKiY47rBIT26hFOC+DXA+Xc+dlOzh4az1vXjjmRoZ56htPqChSn1bsInZBL5OxDLLxgCDdP7euyvHeIhlHzNxDs58VP90x1mM3WyolY36lt1rE+2zxyWHekisomc9iIjLhgZg2MZUZ6DOPSItruRJ0dQ0pJbnULm3Jq2JJTw/b82rb6/LxVDE4IZWhiKIMTQsmICyE9NrhTSKvubLPRJAmIbebLXxvYW1zPrsI6DpUdi4HYJzKA0X0iLIF6IxmUENIWacQdKho19J9Sza3/MPdlnVoPwPCkMM4YFMuZg+MYlhTqURJIo0myNa+GH3aVsDSzDLXOyJCEUG6akspFo5JcjhCc1a8zmLjni12sOFTBW9eO4dzhCSdCUdpjnBbA++tz+deSQ/x5Rj8eOXdwtx7LBsVpKZxYFi6EZ95uIP6GjbTmxHLX8LE88YTj32JaGhQUSuKu2oJvQgOqFVPJ3+d4EdzTEDyehARq0Ro448pajjbU4J9ag298A0JAWIAP09KjmWkZIXTM7eXIJo3eyOacGn4/VMHaw1Vt0nFjkz+thZFoiyPRloajagpBo3Y8hehuEkgrnoZlctRHrToj+0sb2F1YZ8nbVU95o7kik16FrjIUXWkEobpwNiwKJyk8wO4op3P/SBZtaGDdEXPkit1F9UgJ8aH+zBkcS9WueN57Ogos0TncSfRZWGYgaHAJIWMK8I1tIjbEj7tn9eeaiSmdRuzunhMavZHr3t/KjuwGyj6Zhr7afF666v8/QI9yWlJKHv/5AJ9uKeDflwzjuokeLgwfH4rTUjixqHUGzn99A0fyjOx/YbrLERPA22tzeHZZFs9fNoIrx/dx6zh/dNRhNEnyqlvYX2JOAbKrsI4DpY0YTRIfL0FTfgSP/CmaaenRjOoT7taUnxCg1ZtYd6SKRXtLWXmoghadkUBfL6YNMAsTpg2IJjUq0O19SEaTpLpZS0WjhkkztXzyjZ6GVj3NGgNqnTlEk85owmQZEalU5kgd/j5ePPe0Fy8+401YgA8Rgb5EBfsSHexHbKif3alXd+wprW9lZ4E56eRbX9UTltbQtvE5LtTPnC6lTwSjU8IZnhzW7jiO6q9p1rL6cBUrD1Ww9kgVap2R8EAfijYlsPitRCb2jXRresq6D2xDdjVvrspma14tyREB/OO8IZw9rLOowp32VjZpOPe1DUQE+rBy/jRM+m5d3+lRTgvM0WFu/2QH645W8/6N4zhjUGx3H1JxWgonln/8lMnnWwuZ5z2Rd56Kdln+SEUT57++AV1+LHmfjXF7PcLdNS2TSVJS38pltzRz+4Pm9Rvzo7ktAnygrxfDk8KY0DeSCX0jGZcayTnzvDxaAztU1sg5dxcRMbqEOrWeiEAfzhoaz1nD4pncL8ruVJXtmlODWm+Jf9hIdlUzedUtFNaqKa3XtE3RdcTPW4W/jxc+XgKVpd9M0pyKRWt5OCIqyJekiACSIwLoExlIamQQr/07kB8/CSI+1N8tJ5GWBkdzTGSVNbGrsI5dheYEldYMyr7eKkYlhzOxXyST+kVx3VkR5Oc4v+hr9EbWHakyr1ntrcCAkaTwAC4bk8RVE1JIshM5w9Ye6zkhpWT90WqeXnqIrPImzhwSx78vGdYuqoe765zrj1Zxw/+2odndj/Jfu3WarMc5LTCvg171zmZyqpr59NaJjHcjddAfQHFaCieOVVkV3PLRDm6b1pd/nD/EZXmjSXL525vIr25hxYMz3VIXukKjN7Ixu5ptebXsLKjjUFljO8VcdLAfGXHBDIwPYWhiGMOSQhkQE+y2ws8WncHEsv1lfLK5gJ0Fdfh6qThzaByXjUlienqMQ+WjlJLsyma25Nawo8A89VZYeyxFSYi/N/1igkmLCiQ5IoCEsADiQv2JDvYlMsiX8ABfgvy8XNpsNEmaNQYaNXrq1Dpqms1R6CsatZQ1tFJcZ32o0RuPXRP8vFWkRQXRNzqI/rFB9I8JZkCs+eHOfrKqJi07C+rYWVDLtrxa9ltGsL5eKsamRjAtPZpZA2MYkhDq9CZFrTPw+8EKvt9VwvqjVQhgzuA4bpvW127qE3vojSY+2JDHy78fITTAh7euHcOEvp5fdB/+fh/f7ixm2V+mk9EFe7gc0COdFkB1s5Yr395MVZOWL++YxLCk7gl9heK0FBzR1bH16lp0zHt1HVFBvvx871S3Aq1a92O9ctVIXvtrskcjm4531Vvzavl0SwGrDlXSqjfi66ViWFIow5LCGBQfyvolwTw9v7O4wRHO7sKbNHq+2FrIBxvzqGjU0jc6iOsmpvDQ5cnUVdivv1VnZO0R8xTYmiNVVFlEGLEh5im1EcnhDE0MZVB8CDEh9lOUeKpe8yRRZllDK5fdpOb+x1rIr24hr9qsLiysUWOwGen1iQwgPTaE9LhgXn48hHWLQhkQG+x0a0Kz1sD2vFr+NL+GIbOrOVjWCEBCmD9zB8dx9rB4JvaN7OSEbb+D4jo1X24r5IuthdSp9YzqE86DZ2YwPT3aLed1uLyJOz/bSVGtmpevGsWFIxM9+g3UtuiY+cJqRqdE8MktE9z7kOf0WKcF5px1V/x3E1qDiW/unEz/mODuOIzitBTs09VKqL98tZsl+8r4+d6pDE10fRdW2aRhzotrGZUSzie3TEBlSffhLlb7t+XV8u8lB9lb3EBYgA8XjEzg7KEJ7VR9tuU9rd+WerWODzbk8dGmfBo1BqYOiOK2af2YmRGDStV5jUpvNK9v/bC7pM2Zhvp7Mz0jhhnp0Vx/ZjS6OvviBXdt6u7yeqOJgpoWsivN8vjDFU1kVza3S9/i66UiIz6Y4UnhjEgOY2RyOBlxnUevthEo1hyuYsXBirb0IdHBvpw/IpHLxya33cXbs6dVZ+S7XcW8vSaHkvpWpg2I5p/nD2FgvOvRT0Ornjs+2cH2/FpevnIUl4xJ8qh/rPH5vr5jUnfln+rRTgsgt6qZK97ejJ+3iq//PJk+kV2ezkRxWgrt6Y4kk8v3m/d0/HVuBn+Z616wzQe/3sPifWXE7JzOpl+P3bG5ShBoVaIJXz2RZx4geFgJ8aH+/GVuOhePSuq0ydTT9tpTlv2yXM8HG/J5f30uTVoDZw+N5+4z+jMiORzorO4LT2zlsQ8K+XpHEVVNWiKDfDlnWDznDU9gfN9IQoJUHqn72ur3MqLy1xMWbWD1egNqnRGNwYjOki/LOiK69RZQq0EaVWAUBPp7sWyJigAfL4L8vAny8yLEzwd/HxVCCI8Ulm32NJnwiWjBJ7aRkD6NzLmigczihrZUKUG+XoxOiWBi30he+nsUBbvDQZqdmK3is1VnZM3hSn7ZV8qKg5XojCZ8m8MoXZtGy6EEMHrZtUdrMPL5lkJeX3WUZo2B+2anc/cZ/V1uRlfrDMxeuIMyfS0VX09EWxTl9m9Aozcy/fnVDIwL4bPbJrr+gOf0eKcFsL+kgWvf20Kwnzdf3D6JtK4NNKw4LQX7dNVIq6FVz9yX1xIT7MfP9051K4LFzoJaLvvvZu6e1Z+/nz3IY3t2FdZx4TO78YvQcM+s/tw1a4DLiAjHM+rQ6I18sbWQN1ZlU9ui46yhcfz1zAyHMdl8Yxv582s5LM0sQ0rJGQNjuXpCCrMG2l/f6miTRm+05Moyj2SK61opqVdTaUns2Kw1dKrjj+DjJQi1JISMCPRl3e++3HaDHzEWhWF8qD/xYeZEkWEBPp1GhB3tl1KSX6Nmb1E9Owvq2J5f25ZJOMTfm/K90bzzzzhmD4q1qyptUOv5aU8Jn24pILuyGUOTH09e05/rJnWWrVupa9Gx8JcD/LynlBgRzpJHx7pModKo0XPJWxs5UqBn57+ne5Ry5Z21OTyzLItf7p3WHSlNeoXTAjhQ2sD172/Fx0vFF7dPZEBsl63zKU5LwT5dtab1yA+ZfL29kEX3TnNrcdZkklz41gaqm3Ss/NtMgvzMC/vuKrl+3lPCQ9/tQ1fvz49/H8XolAi37PSkvVJKxl9eiv+EwxTXtTKlfxTzzx7ESAdRPQ6UNvDK70dYcaiSYD9vrpnQh5umpLnMBBsYo+aT5eagunuK6jla2dymFBTCvG8pMTyA+DB/YoL9+O+rvrz4tC+h/t7msE2+Xvj7eOHrpcLHS4XZLwpAYpIweYqJlWvMakKN3kir3ohaZ6BZa6RJo6dJY6BeraehVUddi54d+3WExmipVes6OfgQP29zFuboQLNAIyaY268MoeSQ8yzMtS06NufUsP5oFV+trYRALd4qwYyMGC4ZncS8oXGdHJJV+Xflgmz8U82y9UfOGcy5w+MdTqUu3lfK3R/tIznGh49umeBSLJFd2cxZL69n9pAY3rtxnNOytjRp9Ex6eiXzhsbzylWj3P6cm/QapwVm5e+1721FSskHN493+PvwEMVpKXQf1hHT7dP78th5rtWCAN/uKOKh7/bx2tXtk0C6g3VNYULfSN65fqzbogpP2JFfy1NLDrG3qJ7BCaE8fM4gZjhY7C+qVfPCr4dZtLeUsAAfbp3Wl5umpBEWYD/flckk2VVYx7L95aw+XEluVQtg3rw8qk84w5PCGJQQQnpsCKlRgSc65lsbBqOJqmYt5Q0ayho0lFgUhoW1avJrzH+tzlUloF9MMMOTwhjVJ5yxqREMTgi1u6/NZJJkljSwNLOMX/aWUtqgITLIl6vHm528NTq87ZSuf1oVg6/OolY2ctbQOJ66eFinkZG1vE9sA7GXbyckBJb932SX01b/XZPDc8uz+Py2iUwd4Hp7hpUFP+/ny21FbH5kdpcoXm3oVU4LzGtcN36wjZpmHf+5bkxX7ONSnFZvpSuztnYFHUdCjkZMzuxR6wyc8eIa4sMC+OnuKe0cgat9V6+uOMKrK45y3ogEXrlyFBkDVF2aibioVs2zy7JYkllGXKgfA9QD+eTJZLsXX7XOwFurs3lvXR4qFdw2rR+3z+hHaoKPXbVefnUL3+4s4oddJZQ1aPD1UjGpfxTrvoph+SdRZMSGuL0vypM2e1reXbWhzmCisLaFa+5s5po7GzlY1si+4oa2sFQh/t5M6hfFrIExzBkU1xZBxPYcsm4C/nxrAb8frMDbS8WNk1K5d/aAtqlD6/SjwWjifYtsPTzAh/dvGte2nmiLEHC0ookr39lCWIAPv9w3jWA/xxL9tH5Gku5YS2yoHz/ePdVlu63n0NGKJs58ZR2PnDOIP8/s77rD3KfXOS0wC2tu+Wg7h8qa+PfFw7h6QorrDzlGcVq9lZ6Wabdj/d/tLOb/vt3Lq1eN4uLRnUdM9ux5feVRXv79CN/fNZmxqZEuy1ux3hFfPjaZZy8djreXqsv6p1Gj563V2Xy4IR+VCv48oz9/ntmPID9vu+VXHKxgwaIDlNS3csnoJOafPajtomx7DCnNF+X31uex7kgVKgEzM2K4eHQScwbHEeznfcLVgEaTRG80YZISKc3vq4TA10tlV/3oSf3WCPU78mvZklvDuiPVbWGrxqSEc8mYZG6alYhJ03kUWlDTwlurs/luZzHBft7847whXDEuuZOiNKu8kVs/2kFNi5a3rx/LrIHt7+ptFaVXv7uZy8Yk88IVI53a/9HGfBYsOsCPd09xOdVs297L/ruJerWOFQ/O7Mr09L3SaYF5W8M9n+9i7ZEq7p+Tzl/nph9vvyhOq7fhqdqtO9SAtthTlv26wsjsF9cSFezLT3dPbTdKcGRPbYuOGc+vZuqAKN654dgagqtYgl9sLeTRHzO5YGQir101in79hEexBx3Zozea+GJrIa+tPEqdWsclo5P4+1mDePsVf7vlK5s0LFx0gKWZ5QyMC+Gpi4e1bVJtrx6URI2oZPJtR8ksaSA2xI/rJqZy9YQ+bdNfnsZPbFdeSFIztPyyQktlk4bqZnNerboWHXWW9akV6/TopAGVrwHhY8TL14jK14iDwBpmq40Ck94LqfNG6H2YOv5Y/q24UH+SIwJIjQqkX0ww55/l7VJtaN1A/euBcl77sQx9UBMmvYqW/ckMEv3YuLzz1F1WeSMLFx1gS24t6iNx1CwdiUnr067+6mYtN/5vG3nVLXxx+0RGp0TYPUfPnp/F22tz+PmeqZ3WWmz7U/gaSLnvd26Y1oenLh5mt2/snUODzi3k4R8yWXTvVLujvuOk1zotMP+mHvsxk292FHP52GSeuXT48aQWUpxWb6Unj7Q+31rAYz/u59NbJzA9PcYte55Zdoj31uXy6wMz7GaFtWf/msOV3PLRdmZmxPDujePa/QCOt3+klPx+sIJnl2WRW93C5H5RPHbe4E4iEtvyi/aWsmDRAdQ6I3+Zk84dM/rZ/TH6JdZx/j8PsbOgjtSoQO6a2Z9LxiQ5VL45aoPJJCmoVXO0oonsqmYKqtUU1LawYVcr/pGadpt9rQT6ehEe4EN4oC+hAd6E+Pvw4zfe/PlWLwItgg0fLxXeXgIvyx2wxDz60lniFz73opFb/mygoVVPg1pPdYuWqkYtTR1Ui4lh/gxJDOW7d8NZ/FEEY1LDnUbKkFKyv6SRWbcXEDW2BKNJct3EFB6Ym0Fkh3VJk0nyvw15PP9rFi1lwex9bWKntChVTVou++8mdAYTv/51Rtsaom1/Nmn0zHxhDWNTIxwKLazl7/58J9vz69j26BynowPb+hta9Yz/1wpunJzqVvQXN+nVTgvM3/VrK4/y6oqjTE+P5j/XjemUrNMFdvvgRGYuVjhOjjcLa3dhzTprMkneW5fLyOQwpjlZvLa1p6ZZyyebCrhwZKLDNOYds+YerWjivi92MzA+lDev7ZwM0tPMxQsWmJPb/XvpIbbl1dI/Joj3bxzHnMGxdi9UCxaY5dSP/ZTJ0sxyRvUJ58UrRjIgtnMUgNoWHU8vPUTCjcUU1vrx70uGceW4Pi7vMq1tbmjVsy2vlu35tey2BO5V24SeignxIzUyEO/6CO64OICE8ADiQsyjoOhg88Oe5P/9m+Dfi93vo2euhhdXdH69WWuguE5NQY2a7Epz/Mb9JQ2ET6/k+v+ZpfPj0yI5e1g8Zw+NJza0vVBCCMHw5DBql48g65uBvL7yKJ9vLWTR3lJeumIkcwbHtZVVqQS3z+jH4IRQbnh3B1e/u5kf75lKqM2FLybEjzevHc0l/9nEi78ebhsh2WZGDvH34Yqxyby/IY+qJq3dfGDW/p+ZEcPSzHKyK5sdnp/Q/pwOC/Bheno0SzPLeOy8wV05RdirEULwwNwMksIDeOSHTK54ezMf/WlCp8wIHterjLQUjpfVhyv504fbPVL/vfzbYV5flc2KB2e4tZ+jRWvggjc30NhqYNG9U0m0EyTVk5FWUa2a55ZnsXhfGdHBvvxlbgbXjO/jNHbf+qNV/O2bvdSpdfz1zAzumN6vU3nrKOyJXw7S2Krntun9uHf2AKeL/1YKa9Qszixl5aFKdhfWYZK0hZ4akRzOkIRQMuJD6B8T5OmdardPGVtpaNWzu7COzTk1rMyqJLuyGZWAMwbGcvPUNKYNMKsu7dlz7V1N/PXrPRwobXS4BrI5p4br/7eVeUPi+M91nYMpP/pjJt/tKGb9/DPapl5tySxu4II3Nzhcd7ViFVa8dMVILhub7Hb7rUrYxfe5t93DDXr9SMuWdUequPvzXYT4e/Phn8Y73N/YAft9IKXsdY+xY8dKhZPHggXmv3d9tkOOefI3qdUbnZafOdP8t1VnkKOf/E3e+tF2t4/10Ld7ZNrDi+XG7Cq7dlgn7uCYXfZobNXJZ5YekumPLpUpDy6VL/6aJZs0eqfH1uqN8umlB2Xq/MVyzktrZGZxvd1ytc1aefdnO2Xq/MXy4rc2yKyyxrY2O6JFq5dfbyuUF7+1QabOXyxT5y+W57++Xr70a5bcnFMtW3UGp58PC3Nef0fAs/JCeFa+oz1Hyhvlc8sOyXH/+l2mzl8sr3h7k9xVUOvQnladQf7tmz0ydf5i+cbKI53q9/KS8q3VR2Xq/MVyzeHKTu/nVjXL1PmL5XvrcqSUslP/G4wmOfify+SCn/c7td9gNMkBjy6Rzy475Ky5nahp1sq0hxfLV3/vbLtt/R5wyl0PD5Q0yAn//l0Oe3y53JFf485H7LZXGWkpeIwQ0KQxMOap37l2QgoLLxzqsryU8MOuYh78Zq/be2GsIaHuPWMA/3fWQJf120NaRkD/WnKIqiYtl45J4vVbB2Focj5FUVyn5p4vdrO3qJ6mPSkULxpid9ptR34t9325m+pmLX89M4M/z+iPlxP1XV2Ljg835fPxpnwaWvUMiA3m8rHJ3HtBIoZGx6k2PGlzR6SUeIdo2X6wlYoGDRWNGmpadNS26GjSGGjRGtAZTRgs0d29VILflqm47kofwgJ8iAv1JzHcn/4xwfSLCbK7ZuXIHq3ByFfbinhzdTbVzVruPWMAD8zNwNurc3xJk0nyt2/38uPuEt67cRxnDjk2VWjNTzb7pTUkhPnz7Z1TOh3rzJfXkhAewCe3TLBrzzmvrScxzJ//3Tzeqf1Tn13FhL6RHm8YvujNDfh4qfjurs62Hcc68yk10rJSWt/Kde9vpapJyye3TmCMc5Wmsqal8MewndqJHV5N7KUmzhraOaGeFVsllxAw8M4i0voFMqW/6wCjTRo9CxbtZ2hiqMMYhrb2CNF56quoVs0jP2SyIbuakclh5H40jleeC28r7yjr7MpDFTz4zV7qGyTVS8egPpxAoF/78lJKPtiYz9NLD5EUHsAPd01leHJYpzbbZv59f30u76zLpVlrYN6QOG6b3o9J/SNYKUVbeXPyQsf9YqtO7NgGk0lSWKvmUFkjWeVNHK1s4qdVLXiHqelzr5FL/3OsHpXALNTw9ybQ1xs/HxXeKsH69QKhMuIdauLb1U2oAvSo/AztPjcgNphxaZHMHRzLpVOjaaj1ctinft5e3DQljcvGJvPEogO8sSqb595pBNVYhFC1K69SCZ67bAQHS83Kwenp0QQHeGG0LOn5+agIn9KH4ulHKG/QdFobGZoYyi9b67DOHNr2P0Cov3en8Ff2+nPKEz40afSOvwQHTOofxQcb8tDojW2bwZ19X6cjieEBfHn7JK5+dzM3/W8bn9w6we1INlYUp6XgNtYNlULA/71QzXc7vRiX5viEs14shIDyBg2TnqnlktEZbi1Uv7U6h4pGLe/cMM6hiMHWHtu7WCklX28v4qnFBxFC8NRFQ7l2Yipe9x5zDvbueo0myWsrjvD6qmyGJoay6N4xpL4c1Km81mDksR/3893OYuYNiePFK0e2iQNs22z9zKqsCh7/+QDFda3MGxLH3+YNbItEbnVQ7t6JWy94QpiVczvya3lmaT17iuo5WNrYpu5TCUiJDOSc6cGkRUfzwoJAfvg0gMTwAOJC/YgI9LW/ifnOzvY0aw2U1reSW9XMobIm9hXX8/PuEr7YWkjq/T5cMjqJf9+Uhr7OcdSJYD9vXrhiJMOSwliw6ACRcw5Q89vwTuV8vVU8fO4g/vThdlYcqsBgSGxnz96iGC566wh7i+uJD2t/wxQb6o9PsLZt31nH/jRnom5/Ltn2p7X8RW+p0Bk9n4EamxLBO8ZcDpQ2MjY1wmH9pzvxYf58ecckrn53Czd9sI2f751GXw8C7SpOS8FjFiyAbfl1jEmJcKqKsx0JDZhZQdRZcO5wxyMzK2UNrXywIY9LxyQxykkMM3sjrfmPGnn0x0x+3F3ClP5RPH/5iE5x/+ypDZs0eh74ag8rsyq5fGwy/7p4WNvdsm15a0qLrXm13D8nnQfmpNu9+M+caa5z4aKDfL+rmPTYYL66YxKTOqSxcDVa7GjjppwaNhytJvn2Gsb9qxkwizYGJ4Rw0ehEhiWGMSQxlIy4kHahn564GOZ6oMa2va8I9vMmIy6EjLgQzh6WAJgd9+acGp74uIQP1xWSeFsB4TP6c98ZA3jqCcchp/J+S6NhaythE3MJ6BvP/JtiOrV3RnoMMSF+/Hqggh0/JLbrn4cfN3+XRTaJMq1IKdHraTfSsu3P2hYdgxLsi39sv2O9wYSvl+cKQGvQ3IOlDW1Oy179CpAQFsBnt07korc2cuvH2/nl3mmdIuk4QnFapyDdHcZp1VojpZObuGNGP7fsEAKueqCKrPIAuzLxjky+KQ/vIZK/zs1wu34pzRelq97dRmZJAw+emcG9Zwyw61AeeKD986JaNTd/uI38GjVPXTSUGyantXt/1Cjz38pGDTf8bxu51c0uFZObDjZy3us7Ka5Tc9/sAdw3Ox1f784O3tFo0Upti46lmWUs21/G1txaDCZJoK8XpuZIHrsumfFpkQxLCnWZaNPbw1+6q1GBn7cXswbGMuvpWCqbNAy5JovwKdnsi62mSTPBocpx4UJ4xJBB/7+UcsmjOSy8vfPePi+VYERSGEfKm/h1Yfv+adGq+HIBbfEObalu1hEf7keOnZGWOdyUmnMc3DTZnhMNrXqHzs3KrFmdN1HHh/oT7OdNdmVzp/Kn85SgI/pEBvLmtaO57v2t/GvJIZ65tPPI2x6e5xVX6PHYSoq7gy0HWjCYJIMT3JKtApLt+bVM6R/lcmpQrTNgSivi3OEJHiWVq2rScs27Wzhc3sS7N4zjfgcjIGjfP3uK6rnkPxupbtbx2a0TOzksMK9RFdepueKdzRTXqfn4TxOcOqzl+8uIv34TWoORr/88mb/NG2jXYTnCZJKsOFjBbR9vZ8K/V/CPn/ZTVq/htun9+OqOSex5fB6lX07gzpn9GZsa4VZmaNucXV3JwoUQF+pPzZJRVP04hn1FDdz52U70RscLc37eXrTsT2JbXi2tNnvQbAkL9KFF1zn9Sm2LDoAIO+lMjlQ00S/G/jTTwbJGDCbJkAT7Qx7rOWE0SSoaNXZl87bYRt2wIoSgT2QgxXWtTj+rcIwp/aO5bVpfvtxWyN6ierc+ozitUwjrHSmY/3b1aGvWLHO9PlHmO8lnHnE+arKW945soaFVz8qvI52WT0uD2NEVqPwNvPv3FNLSnNuTlmYRL3gbGXHPdg6XqPnw5vHtVGe2dOyfP/+zhuve20KArxff3zWFyR0EIlb7vUJamfjIFooqdHx220SmOFE+howu4M+f7kJfHcLOp6e1hXdyhLe3jU1eJkJHFTH35bXc9skO9hU3cOu0viy9fzor/zaTh88ZxNljovDzUbW1ITzceR/5+7dvs7+LfZ1WMUjH/x1hewOgPpJA9bJhbMyuYcm+Mqf16yrCMJgkYcktdsu1aA34eava94+AwZPMObk6Rm1v0ug5XN5EQ26Y3d/A5pwaAMZ3WIPteE48tFCNwSRJdXDDZD0nrOVnzWr/fmyIH1XN3XSHcIryl7kZRAf78tLvR9wqrzitU4iFC22Dlna901qzxlyvd7h5PeH3H52PhKzlfWMbAfj4Vecjs/x8uHZ+GYYmf9QFkS6jkufnm+uPmHsAv8QG3vnTKKcOxbZ/NmZXs0ZuIyE8gO/unGJ32nLNGqhu0hJ39VYi4/T88JeJTpVO/9uQR9RZ+5k7OJaKLydhaPZ3Oc1mMJhtCuhfwYxn1xJ59j4CfL1445rRbHx4No+cO5ghiaFtI9T6+vbfsatpJ42mfXlnWZGtZWzLu7K/Y/mG3X3oFx3EV9sLnZaXJnN7du22f4Dsymb6Rge19Y/1s4+8UoOPl2BEh6SL649WYzBJHr01xu5vYFVWBYMTQjtF6Oj4m5l3pflcHeRgFsF6TlvLd5wiDA3woUnTtQk6T3WC/by5YVIa645UUVjTea2yI4rTOgXp7jBOKQNbCQ/0cXvhNH2M+W7a1XqW3mhiU04N3hWxbqXnAHNMwpCRRdw9q79T+b0t9/yznts+3kFqVCBf3zHJ4VRQq87IrR/vwDe8lQ/+NN6pKOTLbYU8tfgg5wyL5+0bxiIN7uW/qmnW8udPdxB7+Q58vFR8ePN4Ft83jQtGJjoVuXi6sO/XpameHKNSCSb0jSS70v4Iyop3mHkKLcFOSJ+KRg05VS2dov9LKfn1QAWT+0d3yi/2854SooP9GGcRQNj+BsoaWtmeX8c5wxyfH9byuwvr8fVSMSje+ZqWbZgoW3y8hNOpUQX7XGKJUrL6cKXLsorTOgXpThEGwMQzNMS7mPO3Ze7FauJD/V0mMjxc3kSz1sDr/3S9jwtgwQLJtc8fQl8TxPzz091qd2l9K1v9dhAV7Mtnt050mLhPSslD3+1lb3E9b980mvFpjqf5VmdV8tiPmcwaGMNrV4/Gx0vllrx5Z0Et0/+1nuV7q6hbPYiVD01n7Vf24x92xNOFfVcjrI64K8+2NyXt7caF+6r7akgM87fb/9apxTmDY9vVH5BSR2GtmgtGJLQrX9moYeWhSi4ZndgWXsv2XPh+ZzEAF41KdNoOgC25NYxIDnN5rjrKrG2V2yt4RkpUIAlh/uxxY11LcVoKHlPRqHW5UG3Lxt2dN4La41CZeWrm5gvdE3hMvbIC35hm6jdmIA1eLp2WwWji7s93UVlt5IObxneaKrLl/fV5LN5Xxt/PGsRVUx3foedUNXPfl7sZnBDKW9eOaRNcuFo7Wr6/jGve3UpMlBfLHpxK47b+SKPK7RsOlYe/XE8vpO6Wtzclfbi8ibQox1PH9Wodv+2rsrv2aDJJvthWyMjkMDLiQtrVf+uz+YT4e3P+iPbO5/OthRhMkusmHou0bO1Ho0ny5bYipvSPIjXK8V6ghQvN0UoySxrcitbi6Htq1RkJsOPwOq59KXSmT2RgW941ZyhOS8FjKho9G2kVlNuPrN2R/JoWvFSCumL3VIPf7CgiNsQPdZZ704L/WZPDnqJ6qpcPdxrBe3dhHc8tz+LsofHcObOfTX6s9mj0Ru7+bBc+XoJ3bxzXbrrUmVpvaWYZd3++i2FJofx8z1SGJLqrwjxGT92oWtbQyo6COqep1j/dXIDwNnGtjZOx8tvBCrIrm7llWt92r3tHNLNsfxnXT0ptF05Lozfy2ZYC5gyKbSfOsApE1hyupKS+lesndT6WLU88AeuzqzFJmDnQfoqdjuXtUafWER7QWdloT22o0B4/bxU6g+upVcVpKXiE3miiqllLnBsjJ+vUjipAx49f+bgcRbzythZtvR+YVC6VcRq9kd8zq8lenQDSdfmCmhZeWpZNy6EE1FmJDstr9Eb+9s1e4kL9+fpvI9rW1uyVf3ZZFocrmnj16tEkWaLPu1Lrbc+v5YGv9zAmJYLPbptIdKhvu/Ku9lOpVO3rdzXi8lQN6Gn5jvYMuzIbLyG4bIz9COkR8VpeWJyLOjuWQQkh7frUYDTx0m+H6RsdxHnDzVOA1nMobOpRDDoVtZvbO7OvtxdR06LjdsuewY7TlY9/WkBsiJ9bitJb/lGBHz6MdJLI0ZVCt2PqE1dqQ4VjNGsNbmVFUJyWgkeUN2iQEpLC3XNaUoLKz8ADd7t2WmdfpGPEQPNdqitl3O7CeoS3ie/ejHar/Mu/HyEoUJD5yRCn5d9YdZTc6haeu2wEdZU+DpV6W3Jr+GhTPjdPSWNmxrE7c2dqvZpmLXd/vovk8ADeu3Ecgb7endRxBhfCM5OpfXlncQqtZf6IGtBVeVt79hTWEz62iGsmpDjcY3frG1n4BBipWzOoU59+ua2Qo5XN/P2sge3Wpg6WNhI0pJS75qbx3BPHHILWYOSdtTmMS41gomVrge10Yk5lMyWmKq6dmOI0FJiUgDCRPL6K88bE4uVEBORMoWs0SYrrW0mOOBb42JXaUMGM0STJrWpp13eOUJyWgkcUWsLn9IlwbwrPYDSh8jUS7O/6DkqtM99puaOMs65/DU8Kd1m+oKaFX/aWcsOkVKdra7lVzby7LpfLxiQzLf3YukbH+rUGc6iolMhA5p89yG5d9tR6//hpPw1qPW9eO4aIDll6vdwTG7bR0xb7ha+BB7/ZQ0ywn8OI/KuzKvluZzF3zuxHkKH99Gxlk4YXfj3M1AFRnG2j8pNS8vTSQ/gJH+6eOaDdZ77fWUJpg4b75nTOv7VgAXy6pQAfL8G1E1Nc2n/HY3XUq/XMczAi64g9hW5pfSs6g6nTHjJwrDZUMLO3uJ6GVn27350jFKel4BG5VeaNxf1iXIdjAmixRDxwZ9ivN0p8vVVuKePya1oI9fcmJsTPZfnPtxYihGDJK32dTtU8uywLP28vHjm3vSPqWP+HG/PJrWrhyYuG2k1XAp3VeqsPV7Jsfzl/mZtudw3L1QirI65GWB3xdA3MI/WgShJ9/h6yK9SMbB3ZlvLelvIGDX/7di+D4kO4b3Z6uz6VUrLg5wNoDCaevGhYOwe05nAV649W8/fzBhAWeKxeg9HEf9dmM7JPODPsXOgefszID7tKOHtYArEhrmcF+kyswNdLxbR01+tZ1nZ35EiFeeNzuoM9fwqOWXu4CpXAaQZ0K4rTUvCIrPImQvy9iQt1b+OPNRWEO07LJKXb8/6l9Zq2LMbOImcYjCZ+2FXM3MGxbPjd3+FUzb7ien47WMEdM/oR3UGGbWtPTbOWN1dlM3dwLLMGOhYb2NpkMkmeW5ZFWlQgt0+3H6/R09iA3a0edKV+tLJggeTh7zIJTK/gqUuG8M5TnS86WoORuz/fiUZv5M1rx+Dv49WuTxftLWXZ/nIemJtOf5ubIb3RxFNLDtI3Ooj/uyitXZ2/7CulqLaVe88YYHeLwJ+frKChVc9V4/q41Y73l1QysV+kW+cp2D/nssrNTivDzh6v7t6G0ttZe6SKkX3CCbcTnqsjitNS8Ij9JQ0MSQi1e6GwhzUvkSdp4t1RWtW0aNucS0GB43Jb82qpbtZxsZNYgQCvrzxKeKAPf5qa5tSet1bnoNYZePgc+9OCVmxtWpVVSVZ5k8OguUBbzih36W71oDuxCo0myWM/7efLbUXUbxrAjXbiNkopefj7THYV1vPSFSPbNphb+7S0vpV//rSf0Snh3NHBoX+6uYDcqhb+cd5gGupU7ep8Z20uGXHBzHGgUlx2oJS4UL9OobnsUdbQCmEtzHBzlAX2z7kDpQ2kRAa2pamxpbvjgfZm6lp07C2ub7c27AzFaSm4TYvWwP7SRqc5tGyZNQtGTTA7rcsv9HE5gjp4AH77zfy/qxFXvVrPhpU+7ab77N39/n6wAj9vlTki+Sz7Sq6jFU2sOFTJzVPS2jnXjuWnnanhs60FXD42mQGx9iXz1niItjZ9vDmf+FB/LrSzubVjbL2TrR50N1ahRm/kga/38MXWQho296dhfYbd7+DF3w7z4+4S/nZmBucMT2jfpyrJ7Ef2YDRJXrlyVJv4AswXsldXHEFfFM3cIbFt9oSHw6acGrLKm7hter9OkVMWLgSVrwH/vlUcXZXAU086b3BaGgyYXAvAPVdEuR3v0mqPbfnMkgaGJ7VfAO3ueKCnAuuzq5ESxWkpdD2bc2owmiRT+ruedwbz9Nv3i81RuXdt9nU5rz94CMybZ/7fldKqXq3j+qvaq/vsxSpcfbiSqQOiCfD1cqjk+mBjPn7eqk4jhY7l592fi9EkuW+2/UzKcCweovUzG/e0sv5oNVdP6GNXwdbT1IPuxCqsatJyzXtb+GVvKQ+fM4i6tYMA0ek7eHddDm+tzuGaCX24d7ZZRGHbp6/9no0mrJaFFw7tJF54beVRmrUGVr88BGnJ7GxVG36xtZCIQB8uHNn5JmDhQliZWYvKx8TP/4116STy8+GhZ+sx6bxoLQt1O96l1R5r+Xq1jqLaVobZcVrdGQ/0VGDt4SrCA30Y4WSrgS2K01JwmxWHKgjydZ6tuCPljearnjubkQ0mEz5eKpdKK4PRRH2rnkgX89/51S0U1Kg73cHZ1t/Qquen3SVcPCqJyCDH9dW16PhyWyEXjUr0KGXKskxzSCJrbDVH9Bb14OacGs57fT1ZZU3897ox3DmzPwCpHfbufrQxj6eXZnHeiAT+dfHwtulk68jDr08NL/16hH6qRC4f235PV0FNC59tKeCq8X3IsGwCtyo469U6fjtYziWjkx2GWtqaW4sK4TT0li2ZJQ3oKkKdSt070rG9+0vMatZhSfY3ind3PNDeiskkWXukiunpMW73v+K0FNxCbzTx64Fy5g6Jcyt/k5WiWjXBft6EB7pe07KGwHE1Iqtp0SElbFvn73TqZY0l+OasDhEObOv/fmcxrXojN07pHDHBdiqr75kFtOqNbRdpR3ScUnzx8yrSY4OdhhCC7lMPhoe3t8dVKhNH01k6g3nj73XvbyHYz5vv75rCOcOPxQC0HaG8ty6Xhb8cZN6QOF69alS7i9HCheaIKtEX7mZAXBC/LDjm0Ky8/PsRvL0ED9gkAbWqDZfvL0dvlE5vAg6UNjAkKcRl/EAwC0m2H25CXxXi0fRdxxHZ/lJz2JRhifb3XygjLPscKm+kulnr9tQgKE6rV9DdJ7w7ar01h6uoU+u5cGSiR/YcrWzCXxfkXhBYtZ6wQNebkK2p1v98Q4DTqZfVh6voGx3UyWFY2yul5MtthYzsE85QOxebtn5RmQgeU0CSKqbtzt8RttNfBqNEFVvnlhjAXbWeFVdrL1Y6Zmnu+NwdMosbuOitjbyxKptLRiez6L5pnWT7KpW5P1/4NYt/Lz3EeSMSeOu6MZ2mRPVGE/d+sRsvPz3/uW5sp0wBRyuaWLS3lJumpNmNb7kyq5Kk8ACHIxqA3KoW1GXubcm4/yEdKn8D+rrgPzR9d7C0kcQw/07776woTss+645UA9jdtuAIxWn1ArpbeeSOWu+LrQXEhPgxIyPGbXuklBwobSRvj+vYehq9kVq1jtgQP5f151j2ivV1Mnpp0RrYnFvDGXZk6db27iqs52hlM9eMty+Ltq5HBGaU4x2s5V83prlshy151S2odUanYYGseJpZ2Jli0hZP11Rsy9e16DCN3s9Fb22gulnLezeO46UrR9qVhUuVOfyVdQ3rdUu0+448szSLbXm11CwfzkA70vDXV2UT6OPFn2d0HtEaTZLNOTXMyIhxeBMkpTnz8O6NriMrAG0BWi8/273yjsgqb3QaQ1JRD9pna14N6bHBToNXd0RxWj2YE5WJ2Fq/oxFXblUzqw9XkdSa0ibZdseevy5ooV6tR1ca7rJ8fk0LUsJj9we5rD+zpIFgP29uujzQof3rj1ahM5jalGf22nvTwiICfLw4386CPhybWgseWYihIYBLJruewrBV342YYs4p5SgFfMfyztR6Vpyp1+zhqdowPNycCTpkXC7DH1nDxxsLuGFSKiv/NtNu/D6VCryCNcRdvZUfdpdQvz6Dpy8Zbnd94rudxXywMY/GHWm0HEzuZH9BTQtL9pVy/eRUu+uLOVXNNGsNbTmz7PHYQgMGk8Sk8XHrHK1oNN8t/OUOD4e6NuiNJnKrWuyOwhX1oGOMJsmO/DqX2b074uGWRoUTycKFx0767tiXY13bcVX/e+vz8PVW8d78VH76l/v2jD67mp8WgaYg2mX5fcXmNYG9a0JJj3Ne/7a8WkanhPPpGuHQ/mX7y4kI9GGCzWK8bXtbtAYm/LuM84YlONxQ+sAD8K9X1Pin1tCwIYMH/uJ6itOqthMCPv5Kx0Pf0WmzsqPy7vSpdS3F3fLWtS93ymv0Rt5YVsRbq3Mob9QwPT2aR88dzGAHWXwBtufVcs/nuymt0fHGNaO54Fn7NwA7C2p59IdMpvSP4uN/D8bXu7M9/9uQh7dKxa1T+9qtwxq6a6iTqcEHHzLxxb/ApPdyq39qW8xOKyrY9aZWRxTUqDGYpN0kp939G+7NWG9Cxjq5CbGH4rQUnKr1Khs1fL+zmMvGJrdFr3ZXCbXiUAV9o4O4+QHXarstOTWEB/rQL9r5WkRxnZojFc3tooh3tL9Fa+D3gxVcNCqx3d4fW5bvL6dZa+CKsfajkYP5YhM7q5Tnl0PmL0n08eCG0M8Pess1qrpZy5dbC/l4cz7VzTrGpUaQ/dlIPj3oeJ3BZJK8sy6XF387TFJ4ABWfT+GCl+yLEApqWrjjk50khPvzH8s6V0f1XaNGz3c7i7lgZKLDqaICSyr2NCfTwiYPPUNDq3kfob3QU+5iDW3W107MQSuKerAzedXmmYj+boaEs+L29KAQ4mYhxA4hxG7L838LIe7w6GgKHnGiphacqfXeW5+LwWTizzOORStwx47aFh2bc2qYNzTOZXm90cSaI1VEamLw8jo2erL3OWtW27OGHguq2tH+5fvLUeuMnaJg2PbnXc8XEyICXU5NLM0sI1qEeyRzB/MIKsoyxVXZ5DhtsLtTtFY8PScclTdZ1of+8tVupjyzipd+P8LQxDC+umMS3945mWonDquoVs01723hueVZnDU0jsX3T0Nbbt9hVTZpuPGDbZik5IObx7eF6emovvthZzFqnZGb7Kg4rZQ1aIgK8nWqCnz5Rcv0tUq61T/NGgNCQJDv8d+/u+NMlWnBzhTUmJ2Ws36zh1tOSwhxD/A4sAqwim0/As4QQjzk0REV3D6BT/bGxOpmLZ9uKeDiUUntNn+6ozb8ZW8pBpPk4lFJLu3ecLSa2hYdD1+X4LS9Ukq+3lHE2NSIdvZ0LPfV9kL6Rgd1ckjW/vQKaSWwbw23zklyqmqsbNKwv6SRvA3uRf62xd+fts2SW3JrHZbzNHXFHxFWmEySK+5o4IVfs5j+/GqueW8Lq7IquWZCH1Y8OJOPb5nApH5RCCHsrq0ZTZKPNuZx1qvrOFDayAuXj+Cta8cQ6u9jd22ttkXHjf/bRmWjlg9uHt/ujtr2HJLSkq24T7jDDabe3uY9Ws720gE8/pjFaXmZ3OqfZq2RYF9vnnQROaMjtvYX1qoJ9fd2qBxUsE9BjZrwQJ92gZDdwd2R1jXAGCnl34EGACnlUeAG4AKPjqjgsZLoZKU1eH99HlqDiXtmt08J4UptaJWSD0sKZXBCqMv2fr61kKggX5cZY9cdrSa3qoVrJ7RPNWFbf1Z5I9vz67hmQh+HDilocClS4jIeodXZNGe7L8e1otVCTIgfY1Mj+GJrIRq9h8EFuwiN3si6I1Wc/egBZr6whvNe38B/1+TQPzaYV68axbZH5/LERcM6rcd0VDPuK67n0v9sZOEvBxmXFsnyB6ZzxbhjfdxRzVjTrOXa97aQV93CuzeOZXRK+3UL23NoV2EdRyqauXaC4+C2RqMlSaCLFDf+lj2Ewse9/m7W6gn08/L4N2lrf1Gd2uORuILZaaUeR7+567RMUsr6ji9KKQ2Ae+G+FY57uu9kpOpuUOv5dHM+549IbLtDdncqa1dhvTkafEWKy/YW1LSwKquCqyf04ay5Xk7rf3tNDrEhflxgUfvZ68+PNxXg563iirGdL4BW+wMHl6ItDefmy51PS9z69zpMOi90FaFuKfugsxrw95czKKlv5d4vdqE1dL6Qejo96Ept2KI1sCm7mtdXHuW697cw8onfuPGDbeSIQvrHBPH0JcPZ/thcPrllAhePTuqUWqVj/YGRGuZ/t4+L3tpIaYOG164excd/Gk+yJZ+aPTVjUa2aK97ZTF51C/+7aTzTbQLR2mvvV9uKCPL14vwRzmMz/r7ayOb1zjcMz54tMOlVCB+jW/25dZeBolyfNntc/Sbt2V9Yq3Y7v5zCMQpqW1xuureHuxO5vkKIkVLKvbYvCiHOBjwbV5/GeKokWrjw2ChCCPNi7omaIvx4cz4tOiN3zzq2X8ZdteEnm/MJ8fPm/UeT+NKF2vCddbl4q1TcNDmNh5zUvzmnhs25Nfzz/CFtsvuO/VndrGXqs8VcOibJ7lTNmjXm0E6zXmzkH+cN5rbpzvvgrCuaadQEUyRVbiu/OqsBo/l0yzD++dN+rn1vK/PPHtRu2tLdPrXy8MPWc0LiFaTlxr828/76Rg6VNZFZUk92ZTMmaa5vUHwo105MYUZGDBP7RhLoxrqN1X6Vn4GXFufy3vpcftht4tapfbl/bnqnCOYd1Yz7iuu57L870OiNfHrrxE5TtB3b26DWM/GZUi4ZndRpozEcixQiBIyfaCI62Hkb1qyBkU940extdKs/k/rqie7jww//c6//O9pvNEkG/7PV7nYABcfoDCZK6lq5xMVshz3cdVoLgI1CiHVAhhDiU2AgMAI4z+Ojnua4qyQ6WXJZjd7Ix5vymT0otp3c2R0nWtGoYcm+Mm6cnNZ2EXLU3tL6Vr7dUcQV4/q0U4x1nA6VUvLc8iziQ/25zk4WWmv9H23MR2c0cZuDnFUAvx4oB2iXHdcR5Y0a0mOD7WYhdoT9PkolxM+bfy05yJXvbGZEchizBsYyOiWcXz4P4tVn/QAvhBAsWACPPy5p1hloUOupbdFR1aSlrFFDWX0rHx1WE3+jGp/IFlR+Bn7Tw29LzFORwxJDOXtYAmNSwhndJ8LjtQKAGWcY2dNSQNIdOby2UkdgTTy/PzPIbjZeW1JTzfuwHv0xk5hgPz67baLDfUu2/XP5Y0VoDCaun2RfgGFbfudeI+mxzkdaCxdCba1ACOnWjV5ti44+kYEeq/us52hJXSs6o4l+LvpHoT0l9a2YJKR010hLSvmrEGIs8DBQDgwGMoEbpJSH3alDCKECfgG2Ar5Af+AWIAB4FsgF0oFHpZQVHrajV+HpaKm75bKzZrUXACzaU0pNi47bprffL+OOE/1sSwFGKbl5Slrba47EBW+tzgZoN5qDzsqyJZll7Cmq5/nLRjhUjjVp9HyyOZ+zhsQ7ldCuzKpEXxnaNr3ljGaNgRB/b4/iAjrqo4tHJ3HW0Hi+3FbIz3tLeWt1NkaTuUDKgyBNAj9fwRd6+OhR+4EFvVWC1DEBpEQGsuSrJF5eGERGXAjpcSFt2xEc4e9vP2K7FbXOwBdbC1HPySWyWUtrfjTLH8rotBZlj2atgaA5+/m/b0uY0j+KN68d41AwYds/OoOJWS/kMz48wm4YrY7l0/obGD/A+SVr4UL4+UlJoSXqvCuqmrRutdER1mzF9vZodbRLURAeI7/aqhz0fFrVLaclhLgR0Esp/+TxEdqzWUr5L0udPwOXAtOBFVLKb4QQFwAvYhZ4KFjo7pO945rZp1sKyIgLZnI/+zHzHDlRrcHIF1sLmTMolhSbk9HemlxxnZpvdhRx5bg+nRyI7aK+Rm/k2WVZDIoP4TIHe6qeeAISZxfSqDFw16zO4X+stGgN7CqoQ53jeCRmi4+3QGcweZyg0REBvl7cMq0vt0zrS4Naz5HKJvKqW6hr0fHwP/XMf8Rczt9HRaCvF+EBvkQG+RId4kd8qD8xIX5tkSbEbXDz7+4f21GYqEaNnk83F/C/DXnUtugsTmc0k/tHMfor1/Vuyq5m/g/7aI5q5S9z0rl/9gCHe+M68vOeUkrqW3niwqFulJbUt+rd2k+l0ZuQBtc2aPRGalp0JIX7c98Tnv3OrOf0gdJGhICB8c5DlT3hYf2nOlZnn+4gL50z3BVivAskuCzlBCmlycZheQPJwGHM04ubLcU24mC6UQhxh2Wf2I6qqqo/YoqCBXuLygdKG8gsaeDaCSkO1XeOfnzLMsupadFxk2WU5Uxk8NbqHASiLc8S2F/U/3BjPsV1rfzz/CGdQgO1CTG8jDz5dR4JqihG9gl32N6EYfUYTBJNUZRbworsvQF8tbi1zR5XCRqt5Wzb4EhRHxbow/i0SP5+eR/unNWf+vWDeOTcQbx91yAemJvBHTP6c+X4PswdEseoPuHEh/njpRJdJtyoaNTwzNJDTHlmFS/8epgRyWF8d+dkfrhvUluAX2d9VK/W8fD3+7j2/a3kZgsqvpjM3+ZlMHeO80uKNTSW8DHwwP8OY6gMY85g+9mH4dh3LPwMqHVG9m5x/qX9c4GRVr0RoxthnKybW+ff4zp0mJWO/f/2d3VkxIY4jKrSXXste/v18HBFE/Gh/sc1hY2U0uUD+N3Je+Hu1GFT/ixgOfCE5bnWWgfmkZ8EvJ3VMXbsWKngmAULPCsPx/5/8pcDMv3RpbKuRevxca/47yY58/lV0mg0OaxfSilL6tRywKNL5D9+zHRqT3WTRg57fLm85cNtTo8bNLxQps5fLNcdqXRa7u012TJ1/mKp8nevbQsX7ZcZjy2VwtvgVnlbOra5p5Q/VNYg/++bPXLAo0tk34cXy3u/2CUzi+vdrt9oNMlvdxTJMU/+Jvs9skQ+veSgbNUZPLYnYvYBmTp/sdyWV+NWed/4Opk6f7FcllnqtFxBdYtMnb9YBg0vdFnnD7uKZOr8xTKrrPG4+lOrN8oh/1wmH/txn1vlPcTta2pvvB6e8cJq+ScXv2vpoL3ujrS2CyFGOXjvBw+d5K9SyrOBvkKIu4FKwDpGDAXqpFlKr3CcHO8+MJNJsnhfKTMHxrRFLnCX3KpmtuXXcvWElE4p0Dvy/vo8pIQ/z3Q+TffW6hxadAYeOXeQwzJSSkLH5TEoPoRpA5zvp8qpaiY62A+Txr22zR0ch9ZgIiC93K3yf4SOYY26CvOdvsS/bxVxV27j7FfXs3hfGddMSGHN/53BG9eM7pRtF7ArPtlbVM9lb2/i/77dS0pUIL/cO41Hzh2Mv4+XR3sJ1x2pImRcHtdPSnE7UeOlt5rjDg5yMQ2XW20OqXT9xa7XSvYWNRDg40X/mKDjEmJsy6ulRWdkRrr7uaAUzAKs3OoWpriRssce7jqtJGCVEGKVEOJjIcQH1gfg+IpigxBiiBDCduovD+gHLAEmW16banmucBwc71SEVSixp7ieikYt5w53razryE+7S1CJ9hl67U1lNWn0fL29kAtGJnZay7K13ztEw0cbC7hsTDIDHMx7L1wIAX3q8I1tYuOHaTzxhHNnuXGXlpJsvzZ7XPXPb59GoasOJmxKNsLb6NHUjqdqT1dp3q14Mj2o0Rv55WAhCbeuI+7KbfjENhJemMHmR2bz5EXD2q07dvqsjWijvEHDg9/s4aK3NlJUq+aFy0fw/Z1T2qXicBXJw8r9jzdy/X92oa8K4ekrB7vdpzFDa4gO9iPVxcL9gVKzc3vuEdfpcLbk1jAmNRxvL5XH03Zr1sCSzFICfb2Y4SSBoRLlvTMbss05tKa6uMl0hLuS93nAzzbPj2dvlha4VQgxGvDBrEC8H9ABzwkhMjArCv/vOOpW4Pgl8tbPrcmqRCWwm4PKGVJKFmeWMalfVLvEffb2IH22pZQWnbFt3cuR/U9+ncf7603cNzvdqd2a4cV8sdGLiu2JuBocpvY1kZjixXcfu9c/TzwhmJk1iFs+2sFTPx3mH+cPcf0hC67Ueh1RqdzLRuzOvq6yhlY+3VzAl9sKqeunZ3RiKGvfHUnNngS3s04vXAjzHzXyzroc3lmbi9EkuXNmf+45oz8h/p3XIcLDj2UXdsSB0gY2+mwjMdabHR+Ow6Rz7/Kj0Rv5eXslV06Odxp2C8yOaEBsMCMH+zi9EShraCWrvIn5Z5vvuT1V9z22wMBiyjh7aLzTWIjH+5sUgoVS4oFFvYdf9paSHBHAQBcJVR3hrtNaJqW8xd4bQojX3alASpmDWS1oj9vdtEPBDTyd6rAqm9ZnVzOyT7jHU4N51S3kVrVw0+Q0l2W/3VnMoPgQRibblzgDCG8jX24r5JzhCU5HAwajiWX7y1EfiXdr46yft6otqre7zB4UR+POVN4njz6RgXadrT08Ter4R/fhSSnZVVjHx5sKWJpZhklKzhwSx81T+jKpXySqvwgcaAXs1vXCN6X86pdFWYOG84Yn8PA5g5yGKmpocF7n8v1lPPjNXsICfPjstokMeMx9qfOy/WUIXwMXudiI2qI1sC2vlmsnprCywGlRlu83T/laNwV7qu57/edSos42cI2dfYNdxAI49ZxWWUMrG7KruW92ustlBEe4NT3oyGFZ3rv/uI6s0G14EpDXeuOq8jOwp7CBqf09H7KvPWJWL3UcoXWcGvnb42r2FtVz0Sj7gWqt5QMzymjSGDBmOV/oGTCxnoZWPa3ZcW1qQ2cs+SaAfblqQLqlHrROxdWtGoL6aBwLFh3g5d8OYzI59jCeJnX0NEljJ4VlP6M5pcebG7jsv5tZfbiSm6eksfahM3jnhnFcMyeq7eLgTh/d93gDCTdsJubCPeQf9uUc38m8dd0Yhw7Lqga01h8e3v79Zq2BR3/M5M7PdpERF0LWG1Pb9jTZK9+5fsk9r+ehrwliekaU0/K/H6xAazDxzN0JLtv7055SBieE8tl/gj2avlu40BxBPnR8LtryUBZ/6HyPl6dqT9vfzKnI19uLkBIuHe15JIw2HCk0Oj4wr119AGy3PD4ABrr7+a589Ea1TE8GpFx3pFKmzl8s1x52rsCTsrM68faPt8vpz61yWr+UUn6yKU+mzl8scyqbnNYfc8l2OenpFdJkMjkt985aixowUOPSZiml/Ga7WWXoE9tZLecMq1Ls/77ZI1PnL5bXvrdZFta0uPyMp8fwBO+wFvnvJQflqCd+lanzF8u5L62Rn27Ol80a/XHVX9OslQ9/v1emPbxYjn3qNxk0vFAajM7731n9JpNJLtlXKic/vUKmPbxY/mvxAanRGxyWd8RPu4vNasChRS7LXvH2Jjn9ObN61Vn9B0oaZOr8xfL99bke22Nr0y97S9z+zHGeD6fU9bBZo5cjn/jVpRrYBrvtdXdz8TzM0Sx2AVmWlwcBe4UQF0gpPdjmqNDTWLAA9hTWIwSMTgl3Wd52KkVKya7CemZkOB6hWacrt+TWkhQe4DRZnsFowj+1mtmDnKcNAciubCYmxI8CtXtxlmYNjMVbJQgeVgI4np60h6+3iucvH8HY1AieXHyQea+s4/YZ/fjzjH52Y+Z5EvrJXTR6I78frOCbHUUk3VnN/zYI5g2J44ZJqUzuH+W0vxypE00myVfbi3j+1yyaNQZumdqX++ekE/5PH9zcIwxAmE13bsur5fnlWewoqGNQfAhvXDuasanuqQRtqWvR8dTigwxLCmXJQed35nuK6tmWV8tj5w5GpRJO1ZgfbMwjwMeLy8Ycq9PdKXW90cQrvx8hXIRw7jD3t64eR6YGDzXAPZ8vtxVSr9Zz9xkDXBd2grun5ZPAPCnlZCnlDZbHFMwCjaf+kAUKJ52FC2FfSQN9o4PsLrLblus4lVLVpKW6WctwO7Jp288B7C2uZ1RKuMOLa1oaBMY3o/Iz8to/Il1OZW3cpaX4iH87e5zx1kt+1GcmEDyyEO/QVo8TKD7xhODqCSn8/uBMZg+K5fWVR5n23Cpe/u1wp0SP7oowXE0fmUyS7fm1/OOnTCY9s5L7vtzN6h0t1K/PoOCN2Rx6fyxTBkS7dPD2RAkHSxu59L+bePTHTAbGhbDk/ukYdwwhPND9qOdW6uthR34tN/xvK1e+s5nCWjVPXzKcJfdPb+ew3FXTSSmZ//0+apr1/PbUSJDCaflXVxwhLMCnbY3JkQijpL6Vn/eUcOW45HZrt+6288ttheTXqHnpxoEercm4q660cqqJMLQGI++tz2VSv0jGpjqfUnWFu0IMKaXsFIxHSrlOCNFbsoorOGDWLDCe28hIBwn4rNhTQm3KNu+LsRcc1fZzDz9mpLiu1W7KECs33wwvfGWOUqCrDubmu5zb3X8ARCcJFn3iftT8W2oGMu3pcm54LZPHbxqPMyGsI+VXUngAb103htsK63hrdQ5vrM7mP2tymDUwlgtGJjBrYCxxET5uOS57akC1zsCW3BpWZVXy24EKKpu0+PuomDcknivGJTO1fzReXu7F1rNiq2Zs1Rl5dcUR3t+QR3iAD69cNZKLLeuMnqrdpJRsya3lwf8dpcxUQ3SwL4+eO4gbJqV1SnsC7qvpXlt5lN8OVpij8T8b6rT8uiNVrDlcxWPnDm6LTJGWZt9xvbnqKALBn2e2D/c1a5Zrx9Kg1vPK70eY1C+SdV/FMueUGwt1Hz/sKqGiUcuLV4z8w3W567SChBCxUspK2xeFEHGAEt64l7Nuk4GUSc4dii22UylFdeZU4ylOlGVPPAE332u+YiZFBDgst3Ah9J2nZcEiKM3xJ9p5DFJC/L3bUna7S0pUIJMDBrP68AGe//UwD5/j1jZDu4xOieD9m8aRW9XM19uL+HF3CSsOVeCtEkRcEcYzSyMZkhhK/5hgkiMCCAvwaTciMpokdWodRbVqgoa18MQvDewpqiezuAGDSRLg48XMjBjOGR7PnMFxDkMFuYNVzbjhaDWP/phJYa2aq8b14ZFzB3msFgWzs9qUU8NrK46yLb8WY7Mfj185mOsmpbil5HTGp1sKeHXFUS4bk8yt0/o6LavRG/nnz/tJiwrkhsnH5gQ7JqUEyK5s4psdxdwwKZXE8PbnoTs5615ZcYSGVj3/PH8Iw5KEx5v4T1cMRhNvr81heFKYywAA7uDu2fURsFMI8TGQY3ltAObAtq/8YSsUTgqzZpl/rD6x5gv/p28Fc/8c15+znUqpbDRfDWNDOy/i2KaVGDhcT8JNEO4k4GlaGtTFGYk4A2KjvEhJcL7p9vsPg/AbXY7wMSCEN2FhrvcKAQzySmXA2CbeXpuDr7eKv85Ntzu9lpZ27OInhHldyJ49/WKCeeTcwcw/exBh/erxTqnAL6WWt1fnIbyODQ+8VYJAXy+8vVTojSaatYa20UP0efC/NSpU9WHcdUU/pvSPYkLfyE77qty1yYq/v9lhqfx1RJ97iOARxfSNDuLL24/FGLTFek5Y6585s/MIZEd+LS/8epitebUE4k/t70Np3teHO97yosRFKpDw8GPyeCHo9J19sCGPJxcfZM6gWJ69bDhnnCGc2vPssiwKatR8cftE/H28HPaPlJInFx8i0MeL+2ziXbrTXjBnxP50SwEZqtS2CCJCnNgcd72VpfvLKahR8/b1Y1xOY7uDu6lJXhZCNAOPAtaNCYXAU1LK9/6wFQonBeuPM2igebT04Ruepwlo0hrw91HZ3bRqOxW0aYvksv+Cj7fjZdT8fPhksxeP/wwV1UZiQpyfnt/+J5Ib/peNf0oN6mz3k/A9+aTAYByGzmDi9ZVHKalr5d+XDOu0SbRjgkNXqFSCpvwIIAIhQKs3kVvdTH51C8V1rdS06FBrDZgkeKkEoQE+RAb60CcykLOnBaGpCuoUFLgjntrU2ipZmlnOne/txzdEzx0z+vOXOekON8Q627ycXdnMs8uyWHGoguhgPxZeMIRrJqbg96yX2/ZYHVTH8gajied/Pcy763I5Z1g8r1w1Ch8vlVN7Vhys4KNN+dw8JY0plq0ajvpnSWYZ645UseCCIUQFH7vBcmeztpSSBT8fINTfm6/+L4Pwf5/4HHe9FSkl/12TQ/+YIOYN8TzSjj3cHsdLKd8F3hVCBFueN3eJBQonHa9QcyTzZCdTd47QGUz4OpCZ2Y60pkxUkXCzeTrHGbEhZmFFWUOryxxRE/pGEhHog25MMeDaadna4+0lePzxEfxlTgCvrTzKwbJG3rhmlMOQUZ7i52dWHA6KD3UZLw8gKQSP1HruxCosqW/l8Z/2szKrElNzGIsemeAwb5Wz+hvUel5ZcYRPtxQQ6OPF/83L4JZpfdtNA3q6od1WbVjVpOWBr3ezMbuGGyalsvDCoZ2cd0f1XU5VM3/9eg/DkkLtTvHa2l/XomPhogMMTwrjBgfJJp2p+37aU8LWvFqeuXR421Rqd+e4O1VYd7SaQ2WNPH/5iOPeTNwRt34mQogoIcQMIUSGlLJZStkshBglhLCf4EihV2AdBXmFaDDpVbzy3HGkCcAclt9R/da70eyD5rrrWnRO67JuPM0qb3J5XD9vL64an4J//3IOu1He1h4pzWrAv56ZwQc3j6O8oZXzXt/AO2tzMBjN8ZQ83RhqiychnMD92IPulNcbTby7Loe5L61lU04N/zhvMAXvT3HbYYF5ik1Kyfc7i5n90ho+2ZzPVeP7sPqhWdw7O73TupWnU2TWEdfy/eWc/eo6tufX8fzlI3jq4mF2R5u2U3bVzVpu+Wg7Pt4q3r5+rN1Ro7V/pJQ89lMmDa16nrtshMNcX45EGE0aPU8vzWJkn3CuGndszVeZEnSPt9fkEBfqx0WjErusTnfv7RZi3kw81ua1ZGClEGJ2l1mjcEKxXsS9AnX0ifFzGXDW9nNWAny9aNUZrRvQ7ZKaCgmWfFBW4YYj+kUH4YcPW3Nr3bLlzzP6YdB488+f97dlAnZFxz1UswfF8etfZzAzI4ZnlmVxwZsb2ZZXy5o17Z2cJ7JlV5Ee/mh5R2zOqeG819fz9NIspg6I4vcHZ3Db9H5ER7n3U7feyHiHtxB/zVb+ZonovujeaTx9yXCig+2Pfj1x6ADT5rVy12c7ufOznSSE+7P4vmlcOc6xEMhaf0Ornps/3EZFo4b3bxrnMAO19Rz9ansRSzPLefDMge0C/LrL6yuPUt2s5ckLh3bZSOF0YW9RPZtza7h1Wl+3Y166g7tOazIwVkr5pfUFKeVizFmHlYFyL0flryciyP1Rlq1qKjLQF4NJ0qhxnE2moAC8vVT0jwnioCUKt0NbVIKa/bGszKpAb3QdQTYiyJfaFUPZllfL22tzXJYH+3EBY0P8eeeGsfz3ujE0qHVc+c5m7v1iF4U1zp2sI1zF4vuj5TuSX93CnZ/u5Jr3tqDWGXn3hrG8d+Oxi7q79f/zccl763JJuGUdsQMb+NfFw/j+zil205fY4o76DsxhnV7+/QiFw9ay+nAl/zcvgx/vnup0y4S1fqvDOlzexH+vG8uYFMf7fZ54AvaXNLBg0QGmp0dzxwz3slXbcqSiiQ825nP1+D5Ok4sq2OeddTmE+HtzzYSujc/ortNqlVJ2Ou0tEnjl9qOXYr2rVvka2LHJ2+PNtgsXQnzYsTWojnScXivNDGdXYb3DEZG1fvWhBOrVem5b6DyPlTXuXcv+JFoOJfD88sMsyyxzWd5qT8fRjRCCc4YnsPJvs7h/TjrL9lUw/dk1RMw5gHewxq0pIVfH+KPlO1LeoOGxHzOZ+/Ja1h2t4m9nZrDiwZnMG2qOiO5J/fnVLQy5bzP/WnIITUE0h16eyfsPpzodYbg7harWGXh3XQ4jHl3N6yuP0pobS/brM/nuyXR8nCzmWetXBWoZfPcWduc38MY1YzhjkP1MBG3ndKCWs/+1E2+DL69eNcqlwKUjUkoe/3k/wX7ePHTW8W+LOF3Jr25h2f5yrp+U6jRgwXHhKL6T7QNz+KZ0O69nALvdqaMrH70l1pYjPM0s3N3E37Be3vTBVrfL28ZRyyyul6nzF8sl+xxnlLWWt8Zs21VQ67x+YZLTn1slL3xjvcv4g9b6W3UGeel/Nsr0R5fKVYcq3LbfGeUNrXL+d3tlykNLZMZjS+WCn/fL4jq1W5/t7tiDU+a1yMd+3CfTH10q+z9izgJd0dB6XPUbjSb58aY8Oegfy+TwBcvlD7uKJLgfd9BZ/TXNWvnK74fbYiRe//4WubuwzqP2Zlc2ycQ7VsmB/1gq17gRG7NFq5fxN2yQA/+x1G5WZnewnqufbs4/rs935Dh+8736evjoD+Zzs6LR8TnpBscfexB4CdglhFgEZFteGwBcANzZtW701MfTNAjdTUKSxMuD/RO2yqkBscF4qcT/t3fe8VFV2QP/3knvIQkQWhJC76CIIFJFrNjb2rtr2bWtIhbAtvaGumtffvaKqwsK0pv0Lr0nQBJSCKmTTLm/P94EJ2GSzCSTZCY5389nPvDe3Hffue9l3nnn3HPPYduRAs7v5zoXW0Uk1+juRu6/2X9kMqgG186UyYreY7ry6A+b+W1bFuf0qTlUNiYGQoMC+OSm07ju45Xc+dlaXr6iP5cOch0nFONmPELb6FBevLw/5Zu6YOq3h89XHuTzlQe5oH87bhnemQEdY7yy7sRd7HZjQe/nKw9yaEAm36xRXHFqJ+4Z3aXGsiE1cTi/lInfb2bZnhxGdW/NS5f3P2E914fdDtfajPWHKLPaGderDXeP7upxCp+lu7O578sNhEQovrxjaI0uQTCiWe/5Yj0h7fKZds2ptbo1XVFgtvDcrO307xjjNdeWr/3mG5KcojK+W3eIy07pcCIa2Ju4W5rkC+ByjArG9zo+HYDLtdZfel2qZkpjVTH1tN+iQoXdg0Unzv2HBgXQq10U6w4eq7Z9xWLPmPAgRnVvzY8bDp+I0KuOy07pQNc2kTw/a3utYfIVkXox4UF8ecdQTk1uxYPfbOLVOTtduiI9dcHN+DSCV68cwKJHRnPDsGTmbz/KJe8u54Jpy5i+fH+lvIOe3uPa2mut2ZlZyGu/7WTUqwu5/uNVzFqbS8GqLuyfNpYV0/rVqLCq619rzffrDnHuG0tYn3aM5y/ty/RbTuO9N0LrLr9Jc+tTmVz30UrOfmMJM9Yf4tJBHZj74Eg+uuk0Tk1u5fb1sds17y7cw42frCYxOhT7nOG1KiyLzc7fvlrPop3Z5M7px/haXnaccXZrvvTrDnKLynj+kn4euxWrUtffvFL+m3vw098PYLHZuaMO84juoLQfrpAbPHiwXrt2bVOLUWcaemGip/0nXv87Z4028cXtQ+t0vmdnbuPzlQfZNGV8pfBj53VRYFhoZ1yZyZ2freNf151SrWVWIf/ve3O49sNV3DI8hSkT+lR7/qrjLbfaefK/W/h27SGGd43njasHVnrj8/T6VG1faLbw3w2H+WZtOn8cLsCkYHBKHGN7tuHMrgn0ahdNoIe5AZ3PkVdczpoDefy+J4eFO7NJyyvBpOCMLglcObgj5/RJJCw4oM79ZxWYmTRjCwt2HGVIShyvXjngpGKbnlyj46UWOo1Kp//lBzh0rJR2MaHcMCyZa05LIi7CdYqomvo/WmDm4e82sXR3DhMGtOely/sRERJYozxmi437vtzAvO1Z5M3rTeG6zoD7GSuq/s3ddmZnnvKgUrW7/XvY3i2N6UvPw5JyK2e8uIAhKXF8cOPg+nbncvxuKS2lVBjQGsjSWpcppVKAS4GdWutf6iuZp/jSTaoLnpb29qTfqkqipvNUpLBpc+VqTKEWeqQN9zgbNRhFIG/6ZDX/ufm0ShPkzil7wHDL5eZpxry6iLiIYH6854xK7jVX8nPKVqb/foD/3HLaSUUmK1IUVRAS8qfVpbXm27XpTP5pKxEhgTx/SV/untCuUk662lIgOacEqq79rqxC/rfpCHO3ZZ1YW2YvD6A8M4by7CiiVQTvvxFGfEQw0WFBhDgyglhsdgrNVoaPLScg0kxgTClB8UUEtykgMNYIagkLCmBoahzjerdlfO9EWkeFuCWTM4GBYDthqGqiB6aTdPF2LDY7j5zTk1vOSKkUaOFJ/2m5JZx+436CeqRjCrZhTovDtj2FjLVtq10P5epvwjmN0y9bMnjyv39QUm7lqQt788TVSRw8+Kd8ruQpMFu469N1rNiXyzMX9+HGYSluK4mK3wCACraQevdSOnZQ/Hr/SJcJf+uKu79559+APyqt/yzfz9P/28YPdw+rUzmaKtRLab0FnA1cBRwGtgOlQADwttb6lfpK5wm+dJN8EU/f6lpftIHeI/JZ/MgYt9pX/QGaLTYGPzePC/u348XL+9cqzxerDvLEj3+4VERV25stNi791+8cyS/lv/cOd1mLq6bx7jlayIPfbGLL4eOc3y+RqRP60DYmtF6WVnVkHC9l1b48NqQd44PvjxPXuZDi8ppdmxVom6J7uwi6t42iX8cYTklqxcBOsQRXk/bK03scnFDIpc//war9eQxNjePFy/qTUkNds5r6355RwL8W7WXW5iMEmBQT+rfnnb93pjzL/fmjqv0fLTTz9M/bmLUlg/4dY3jtygF0cwqDr06e9LwSbvu/NezLLuaVK/+cx/T0xVApzb1fbODXPzL59q5htc69NdSL55/y+J/SKim3MuqVRXROiODbu4Z5o8t6Ka3lwFlaa7NS6kHgAaAHhtJaqLUe4g0J3cVXbpKv4ukPqv9N27Amp7H16XPcCixw9QC5/+sNLNqZzZonxp30oI2Nrfw2XW61c9bri4gIDmTW30ecNG9QVf603BIufncZ0WFBzLj7jEq546By2Q1XWGx23l+8l2kL9hAcYKJoZTd2/5JSY6h1beN15xi7XZNXXM6RfDN5JeUUlFootxpzeUGBJqJCAokJDyIxOpSO8aHYbe7Pn7grU4HZwjsL9vD+wv3ERgby+Pk9uWpwp1rvs6vSHtuOFPDmvF38ti2LiOAArh+azC3DO5MYE3rSPa6NivY2u+bL1Wm8PHsHZVY795/VjbtGpp5kqbmS5/e9Odz35QYji/j1Rl2xujLoL3s5lryDR8/twT2jay9S2Agu/qe1mzW1fOV5+O7CPbwyZyff/3UYg1PqbWVBdcupqgsrdP4A853+vwp4ytV3jfXxxRBPf+aDxXt18sSZOr+4vMZ2U6YYoc0VH+cw3gU7snTyxJn6lxpC353536bDOnniTP3p7/vdar/2QJ7u/sQv+vy3ltQqZ3Xsyy7SN32ySidPnKnHvLJQ/7rlSI0h9TWN15vHeIK7/ZdZbPrT3/frU575Tac8NlM/+t0mnVNortM59x4t1Pd8sU4nT5yp+06ZrV//bWed74Ezq/bl6vPeXKKTJ87Uf/lghd57tNCt42w2u3534W7d+bGZ+qzXFrl9XHXM3HREpzw2U9/z+bpal1g09P11wq+eh8eKy3TfKbP1bdNXe7Nb1/qoui8qNYIVwCjgZsACJDn2hwOr3enDmx9fuEn1wdfWad38ZIZOnjhTb07Pd6u9qzU2FqtND/3nPH39Ryvd6sNut+trP1yh+06erTOrrC8KCXF9zIIdWbrb47/oC6ct1XlFZSf2Jye7dcoT500elqnPem2RTp44U1/0zjI9f3tmjQ8rT9YU1fWh5skYapKp3GrT36xJ0yNeWqCTJ87UV773u96Ufszjv7kpU7TOKTTrp/67RadOmqV7PfWrfnXODp1f4lpZedL/3qOFeuSktTp54kw97J/z9P82Ha5VWVRcn6yCUn3Dx8aLxz1frNOFZov7J3bB/O2Zuuvjs3SHG5frkjKr28d5uq6uDvjV8/Cfs7bplMdm6u0Zx73ZrcvxuusePBv4DogCXtBaP6mUGg+8C8zSWj9QZwOwDviKOVxXfK2sQXDrQtrftoS3rhnIxQM71Nq+OvfjW/N288a8Xcx/eBRdWtdSwRFj1fy5by3h9M7xTL/ltBMuq5quz4IdWfz18/UkxYXz6a1DaB8bVqfILIvVzoz1h5m2YDeHjpXSMzGKO0akckH/diclYK2re9BTmerT/niphW/XpDP99wMczi+lb4doHh7fg9HdW6OU8qj/cqud1sP3k3TuHkosNq4dksTfz+pWY9Z9d/rPPG5m2oLdfLMmHYvZxCMXdOH2EaluBTwoBXP+yOSxGVsoLjOCNK47Pale6+R+3HCIR77bTK920cx65HTsZvczNzT0nBYeZBpq6ufh3uwizn1zCRcN6MBrVw3wZtd1dw86FFsAEOu0HQkkA+Hu9uGtjy+8WdSFRnQteCZPgFUnPTJLT3h8R736O1pg1t0e/0U/PmOz28d8+vt+nTxxpn5/8R4dElL5+lRnca3Ym6P7Tp6tk/82Vwe3zT/RvjZrJTm5cv/JyYZl8u2aNH3264blNeDpOfrpn7fqLYfydUyMvVL7mJjaxzNqVOVzjBrluUzu92/Xp1+Yox/+dqPu+eSvOnniTH3Ve7/rBTuyTlgunv7N3fZklm5/+0KdPHGmbnPFKn3/UwU1tnen/6MFZv3s/7bq7k/8olMmztKtxm3RpnCzW/IkJ2ttCi3T8Rds0MkTZ+rkO5boXZk1y1QbFqtNv/jrdp08caZuf/0KrYLLPbrHjYRfPA/tdru+7sOVuu/k2fpoQd3czzVQd0vL12jqN4v64muWllIw7rXFJMeH89FNp9Wrr0kzNvPD+sMse3QMbaJrXw2vtebuz9czd3sWX9x+OkNT4926PjsyC7ht+lpyi8tI/6E/xdtqtxArcNW/1prle3L5ak0av23NxGLTpLaO4OzebXn6rjYU7GtVbSSfu+fwRnuzxcaaA3lcfPdRuo/NJLPATERwABcN7MB1pydVmwGitv4PHSvh2ZnbmLM1i84JEaz6dy9K9rpfWNNV/9mFZXy4dB+frThImdXGpYM68sC4bnSKC3d7vLP/yOCpn7ZyNL+c+8/uwn1ju3l0H6qSnlfCw99tYvX+PP4yJImpF/UmJND9IpaNiF9YWrM2Z3Dvl+uZOqE3Nw/v7O3uXV4Dt4tACt7DVwrIOa8J2bgwmsN93CsHUhN/HdWFb9ce4l+L9jL1ouoXBFeglOLlK/tz6bvL+evn6/jxnuGEhFQfil1Bz8RofrpvOPd8vh7zRRt56r/HeOKCXtVW5HXGVQFFpRRndkvgzG4J5JeUM2tLBrP/yOTjpftJvHYfA54O4NTkVpya3Ip+HWLo3T6adjGh1bqnaioq6C5aazKOm9l2pIBNh/JZe+AY69KOUW61Ez3QRN8OrZl0fk/O7t32pPpWVanub67MauOjpft5e8FuFIpHzunB7SM680KRZ2uUnPs/WmDm/SX7+GLVQcqtdi4a0J6/n9WNVCeXcW2/gYzjpUz5aSu/bcuid7tosr8/jYdecT+kvio2u+bzlQd5afYOTErx2pUDuPzUP9N8uZvaS/iT4jIrz87cRu920VxfTXHNhkAsLQGl4MMl+3hu1nbWPDGu1orBtTHx+838uOEw8x8e5XZOvIO5xVz6r98JDw7gh7vPoK0bVtrUqfD0s3ZiR+0gZsh+Wqkovrp/oFuVgt2lwGxh5d5clu/JYfWBY+zILDjxRh4ZEkhq6wiS4sLp0CqMdtGhtI4KJS4imNjwIKJCAwkLCiAkKIBAk8KkjHRZNrum3GqnxGLj5detvP8fC6YwY5HxmPPMpPYr5UBuCXuziyh0lHwJMCl6JkYxLDWe4V0TOKtfPHZL/Ra/Ltp5lKf/t439OcWc2yeRpyb0pkOs59WrK8g8bua9xXv5anUaVrvm4oHtuW9M10rKqjasNjv/t+Igr/+2E6td89DZ3bntzM7VLlZ2h5X7cpn681Z2ZBYyolsCL17ev17jbCR83tJ64ZftvL9kHz/cfYbHOSXdpO7rtHwNUVo14+kkcUoKfLcojyvfW8GHNw7m7N7uu4VckXnczOhXFzKmRxv+ff2pbsuzKT2faz9cSdnxUJY/O9QtxQWG0p2/PYtHv99MQamV+8d1486RqdWuw6ptXVdVnOUvLrOyPaOA7RkF7DlaxL6cYtLySjiSX4rFVv/fUoBJ0S4mlKS4cFJbG4uNe7WLpk/7aMKDAz3OelKB85jTckt4dtY25m4zXIFTL+rDqO6tK7UfPdr9opdZBWbG/W0vZZ3SsNs1lw7qwH1ju5IcX73F7Grd1bqDeTz5361szyhgdI/WPHtx3zonAp46Fa69u5CXZ+9k3vYsOsSG8fj5vTi/X6JXkhx7+hurQ+CGTyut3VmFnPfWUi47pQMvX+HV4AtnPFNaSqnJjv8u0lovaSip6oIorZqpy3xKabmNflPncNuZqTx2Xv3rB1UsNPz4psGM693WbXlW78/jimmrSW0fwue3n15tZVpnKh4IuUVlTP5pK7O2ZNCjbRTPXNyH01PjT2rfEPNNdrsmr6ScnKIy8orKOfsCC//53EqpxUa51Y7Fbsdu1yilCDQpggNNhAcHEBESSGxYMGeNCCJ9VwhxEcFuWRV1GUN+iYV3F+5h+vIDBAYo7hvbtdqqsu70n1tUxr8X7eWzlQcxl2uuGdKR+8Z2dUvROPefU1TGi7/u4Pt1h2gXE8rkC3tzbt+6K5d92UUMuWUPUf0OExkcyF9Hd+HW4Z29mpapoaND8WGlpbXm2g9XsS2jgAUPjzppsb8X8Sx6ECNV043AgOraNNXHX6MHGxpPI8WqRrp1v2eZvuxfy70iS5nFpgc8tlh3uHeuNoWVeSRPcPs83fH+2Tr1wbn6j8P5Hp977tZMPeyf83TyxJn6zk/XnIg2czc6sYK6RHt6Gg1Y33tWW3RiSIjWKtCqo0/fozv+fY5OenSmfvjbjSetjfOk/yKzRb81b5fuM3m2Tn50po4/f6MOjCn2PFpS2XTy2ft03ymzddfHZ+l//rJNF9Vj3dW+7CI9dtIGnfTITN3poV907OhteuLkstoP9ABP71c9IoZ99nno7VpjNeBZ9KBSaqHW2r1kdI2MWFo1U9e3wJdn7+CDJfvYMPlsr1Qb3XakgEveXc7x3fEc+fo0t8s8KAU7Mwu56ZPVFJRaeOPqgR6VmQDDcvxk+X7+tdBYa3Run0RuPbMzg5NbYTLVPQN7Qx3TEO2Pl1j4fNVBPl62n7zickb3aM0/xvdwq8aUq/5tds0P6w7xym87yS4s49w+ifzjnO50bRPlsfxhyTmMeGAru7KKGNEtgSkT+tC1jftzX87sOVrEOwt28/OmIwQHmrhhaDKTr+qCrbjBLIAWa2nll5Qz7vXFtI8N48d7hte7dEstuOy8Jj+EW5fYURhS8CE8jU6siHQb0a01VkehQW/Qu300T1/ch7DUbJ6btY3qXpBcydO9bRQ/3jOcLm0iufOzdbw5b5fL2ljVERYcwL1jurJ04ljuHd2VZXtyuPK9FZw/bRnRQ/aSnlfidl+eXM+61k9yN9rQnfpbG9PzmTRjC0NfmM8rc3YyoGMMR78cxvRbhrhdFLGqPGsO5HHRO8t49IfNdGoVxg93n8F7N5xK1zZRrjuohvS8Eu7+fB1t/7KKUouN9284lU9vHVInhbXnaCH3f72B8W8sZs7WLO4YkcrSR8fyxAW9sZc0nMICz39jvhIxXF9e+GUHx0osvHhZ/4ZWWNVSU5xsL6XUJ270Ue+iKYJ38XSlfsWE+6nJrYgKDWSuG9WC3eUvQ5LYnVXEJ8v3ExMWxAPjurstT2JMKN/eNYzHf9zCm/N2s+7gMd64eiAJHvjQ4yKC+cc5PbhnTBdGXH+YjUfSaTVmByNe3kFQSSTXjUvglORW9GkfTUp8hMsfYmNUnK0oj1EXyq12Nh3KZ/72o/y2NZN9OcWEBJq4eGB7bj6jM73bRzP9Vs/6rLgH2YVlvPDLdmZsOEy7mFCm/WUQE/q3OzHf5BwYolT1gSGl5TbeW7yXd+bvxWKBgpXdSVudyoqSAM5x0b4mDuQU8+a8Xfy06QhhQQHcMTKVO0ekEh8Z4rY89cXTPptD1eIVe3P5Zm06fx3Vhd7tvReh6yk1uQePARvd6GOA1torKX3dRdyD3sU5sunBbzYyf3sWq58Y59aaJ3cYNVpz2r2b+X7dIe4aaQR61DTJXjVyTWvNN2vSmfLzVqJCA3np8v6c1evPCEdPI7OCWhXz75+zWLwrm7UHjlHqqIwcHGgiKS6cpLhw2kaH0joqhPiIYN5+LYiXngskIiSQ8OAAQoMCCA0MIDjQdOITFKAIMpl45hnlUXSfJ9GAVpud7KIyjuSXMurCYia9WMiWw8fZlH6cUouNQJNiaGo8Fw1oz7n9EokODapztOGUKZoe56fz4q/bKbXYuGNEKveN7VrterDq3F9aa+ZszeLZmds4nF/Khf3bMen8XnRsFeaxyzXjeCnT5u/m27WHCApQ3DQshTtHproMBGjoxcItLY2T2WLjvLeWYrNr5jzg3VpjNeBx9KBbc1pNMfclSsu7OP/Al+7O5oaPVzPtL4O4aEB7r/VvtWmm/ryVz1Ye5ML+7Xj5iv4ePwB3ZhbywDcb2Z5RwBWnduTJC3oRGx5cr/kFi83OzsxCdmQWsiurkIO5xaTnlZJVYCa3uNzjsQaYFEEBipIiEwlxJgJNiqAAE4EBjn+dtgNNigDH+q358xTjxxt9aA1Wux2LTVNabqO43Ep+iYUCs6XSOIMDTfRqF82gTrEMTY1nWJd4YsJcz0V6co12ZRUy8uEthHY8xrDUeJ69pG+t7jtX/e/LLmLKz1tZujuHHm2jmHpRH4Z1ifdYnuOlFv61yIh61BquPT2Je8Z0qVSN2h15vEkjZNDwKaX16pydvLNwD5/fdjpndqt7CRgP8Tgjhru35DzPZRF8AVeulMmTE0iJD+fjpfsquYGqHufOW+bo0X+6vQIDFCNH9WHi1DBenrOD3VlFvHvdKZUehs7tlTLmVZwtrh6JUfz33jN4a95u3l+yj5nrjnJoZi+gA0opj6yaP11HJvp2iHE51zNqtJ1layyYQiyYQq0MHGzluRdtmC3Gp9xmN8LZbYaCKbfaeWuanbwijQqwU2yyExWjufxK7VBCRjurzY7Vbiwy3rtPczDdjilYM28RdOgIyUmKAKUIDTLRKjyI8OBAYsKCaBUeRNuYUNrHhJGSEEGnVmG1hsc7VyJWquZKxGVWG1dN2cvG8j0ExQeSM6s/3S/rSNc21T8/XfW/fZeNdxbu5oMl+wgNDGDKhN7cMDSZwACTR+47i83OZysOMm3Bbo6XWrh0UAceHNe9xpD6hnYPNpb70ZfYkVnAe4v3cvkpHRtTYVVLTZbWBuB+4IDWOq3aDpRqo7U+2kDyuUQsLe9S9a3xq9VpTJqxhfdvONXl3FZ9I6cW78rmga83UGqx8fj5vbhhaHIl5ehO/9uOFDDpxy1sSs+n7Egs/53a0+WaLHfk8Xb7xjiH55V5a+5/5b5cHv9xC/uyi7l4YHveua23R9F3Ff0v2JHF5J+2cuhYKZcN6sCk83u5zLBSmzwLdxzl2Znb2JdTzIhuCUw6r5dH8yhiaXkHi83OFe+tID2vhHkPjSIuIrhBzlMNHkcPbsSonzWwlo5/qJM4gs9y5akd6domkudmbaOk3Hpiv6eRcdW1H9W9NXMeGMnpneOZ/NNW/vLhSvbnFJ84zp1Iut7to/nx7jN45Yr+BESVcvUHK7nuo5Us2ZVda5RiY0Ryucpv6Iq6Rhs6z1PVh+zCMh76diPXfLCScqud/7t1CG9dM4inHvEs+s4UYebeL9Zz6/S1hAYF8PWdQ3n96oEepwQ7mFvMrdPXcMv0NQB8cvNgPr11iMcT/w19j5tLNGBtTJu/m03p+TxzcZ/GVljVUq3S0lrforW+VWt9Uki7UipVKfWUUmoHcEaDSig0GNU9MAMDTDx/SV8OHSvlqf9uPaEEqqb1cTfNjyvaRIcy/ZbTeOGyfmw9UsA5by5h2vzdmC02t/t95hnFVad14sgHY8hb0Iv1e4q48ZPVjH9jCR8t3UdWgetcTe4qhroqFKjeBVdfvPXiYCTK3cfYVxfxv01HuHdMF+Y+OOpEOid3xzpliiZqQBodbl/MzA1ZDArszi9/H8HQaqzemuR5c94uzn5jCav25fL4+T2Z/cBIxvZsW6fMGA3tsmvuLkEwrO93Fu7hylM7cmF/78xvewO3cw8qpRKAq4HrgSGAHVgAdNNapzaYhC4Q96B3qc7V8frcXUybv5uHz+7O387qVmt7T/uv4GiBmadnbmPW5gyS48PpWtCbj55p4/bDqqL/MquNnzce4YtVaWxMzwdgUFIso7q3ZlhqPH06xBAZEkhsLOTne09+V1SNgPT2Oera3mqz8/OmI7w+dxeHjpUyqntrJk/o7VbRzqqk55UwacYWlu3JwZwWx+9v9XM7Oa6z/M6uyQv7t+OpC3uflHeyoaP1PO3f0/tbB5rUPZhfUs55by0lNCiAmX87k4iQJikI4ln0IIBSKgy4BENRjQOCgPVANDBSa52plHpQa/2G18WtAVFa3qW6H6zWmoe/3cSMDYe5d0wX/jG+B0opj3+w7j4Qlu/JYfJPf7A3u5gzuybw+PnuzWO4eoDvOVrE7D8y+G1bFlsOH0drR6BAXDjbVkfw1+uNsPa4iGCiQo1Q9uCAAEwmjGzsdo3VbgRQXHiR5pvvjEAK58ALm11jczqxSUGgyURQoIm77zDx9RcBRIYEEhUaRGx4EK3Cg4kNC8LkYi1YQystU4iV6YsO8dHS/aTlldCnfTQTz+3JyCqJct3Bbtd8sTqNF37ZjkkpHjuvJzcMS0Jr9y2iqVPh4ccsvPDrDr5clUanuDCeu6TfSYl7K/C1OarmPKeltVHjbv6OLGbcPZx+Hd1bkN4AeBzy/hlwMRAB7AW+BL7UWu9q6hRPorQaD6vNzlM/beWr1Wmc2yeR5y/ty9uvhjTYgs2nn7UTNeggMcN3ExBm4fJT/iwcWJXYWDh+/M/tmBjXFlR+STnrDh7j2vsKsEcVENSqhICYEgJCrSc3bmACTIqEyGASo0NpFxPG7/PCOLA1DOvxcKz54QztF86SBdWvgXGOsISTIyydKbPaGHF5LvssGYT3yMAUYiO4KJZ37u7CuF5tXSrPCqp70Th0rISJP2xm+Z5czuyaQGJ6P1575s9742403ZJd2Tz2w2YyC8zcdmZnHjq7h8u1P3VdZ+YunvbvyfWvJ02mtL5encZjM7Yw6bye3DWqi9f6rQMeK62dQCrwAvCM1trq9N0CrfXYhpDSHURpNS5aaz5etp+XZu8gOjSInV/3pmBL+xofevVBKcgvtvDuoj1M//0AWmuuPq0Td4/u6rIOUl3fkkvLbeSXllNQasVssVFmtWOzG0k5TSZjHVVggIkhgxVbN1csIq74GGusAkwKhUJjWF52O5TZbHToZGfrThtFZVYKSi0cL7WQW2Rkgc8uLCOzwEzGcTNH8kspKbdVkq9tdAjJcREkxYfTqVU47WNDaR8bRtvoEFqFBxMdFkRwoOnEmK02OwVmK0fyS0nPK2F7ZiEb0o6x5kAeZoudqJBAMtYmMu+9ZAZ0jHHL7Vr1mlYs8H5u1na01jx+QS+uHZJ0oi9370FxmZV//rKdL1al0bVNJK9c0Z9BSa08lsfbiKVlsOdoERPeXsYpybF8duvpDfYbdxPP1mlprXsopU4FrgPWK6WWA19orZc1kICCj6KU4vYRqWyZ25pv92wiYcJGOt62j/M6dvdo7sldpkyBmPAgHj+/F7cO78zbC3bzzZp0vl6dziWDOnDHiFR6JP6Z887dqrMnrwMLYNGiMNrVcvzjd0M3j0qMBTF8IHR34xitNXnF5Vx4TQmPPVdCWm4JB3JLSMsrZsmubI4Wlrk8LukfiqSHFYFBYMde6TuTgm5torjmtCRGdk9geNcEzhkXwMBOtcvjah3S7fcbc1dLd+cwLDWel6/of5Ll60403fq0Yzz0zUYO5pVwx4jOPDy+h9tZV3wtGtAblal9jTKrjb9/tYHQIBOvXzWwqRVWtbgViKGUMgFjMRTYYCAKOF9rvU0pNUVr7aUAXPcQS6tmGnJS2WbXxPQ7wqCbdpKeV0rXNpFcd3oSlw7qQGy465BYb0yiH84v5YPFe/l27SFKLTaGpcZz7elJnN27LS8+H+DVNUtVaYSUPS6LIoKRPifzuJnMAjNZBWbySwyrbcozNh6ZqDE5FiHHhAWRGB1Kx1bhdG0TeZKrrS6BIVabUaL+5dk70MCk83tx3ZAkjx9mVpuddxbu4e0Fe0iMDuX1qwbw66fxLSICrx40uqX13MxtfLRsPx/daNTA8wE8D8RweYBSocAEDAXWHmintXbjHc57iNKqmcaIRCu32pm5+QjTfz/IpvR8ggNNjO/dlksGdmBE94RKhQW96Uo5VlzOl6vT+Gp1GoeOlRIVGkjG6kS+fjWR4V0T3MqJ5oOuIJ8oZeJMcNvjnD/5Dzam5zOiWwL/vLRfnaoIHzpWwgNfb2TtwWNcMrA9z1zSl+jQoEa5pn5OoyqtxbuyuemT1dw4LJlnLu5br768iMeLi12itTZrrb/TWl8CnAt4p46FUG88XcMzenTl9qNHu99/cKCJTT915Kd7hzPr72dy9eBOLN+Tw+2frmXwc/P4x3ebuP2po6gAu9vyuEOriGDuHdOVJY+MYXzQEDLWtiW8Rya3f7qWPpN/4+r3V/DabzuZuy2L9LwS7E7lTOozXqVg8hQ7x0stHC0wk55Xwv6cYvZmF7Evu4i03BKyCswUmC2VzlkbKSmVz5GS4plM3r7HI8aVEX/uFtrdvIx1O0pI2D2QT28dUieF9cuWDM57ayk7Mgt58+qBvHnNIF5/MajOa9+EhiGnqIyHv91E97aRPH5+r6YWp1Y8trRO6kCp7lrrXV6Sxy1amqXl7ZQ9DdXeYrOzbE8OMzdl8Nu2TArNVsMSWtuWr15ux8gqFpi3UAF2luzIZcmubFbsy2V7RuGJ2lshgSY6xIaRGGOEt8eEBfHvtwN47FETJlURQGH4880WOyXlVorLbBSaLRSVWSkqs7IvzUpYjJVyq70WSRzyKIgNCyI+MoR2jlyBSfHhpCZE0K1tFCnx4SflDGxqS6vAbOGjpfv5eOk+yqx28lalsH9mt2oT8NZEabmNZ2Zu46vVaQzoFMu0awaSHB9RL/lbII1iaWmtuXX6GpbvzeXn+4bTM7HpSo64wLNADKVUd4z5q6KKrBjKmHGfjBEKXwR8rbX+l/dlFZx5+mnPlFZDTypX1z4owMSYHm0Y06MNZda+LN+Tw69bMvnJnMUdnx4mKiSQs/u0ZcKA9pzZNYGgapK9eqqkpzxlYkS31ozoZqzxKS23sS3jOLuzitibXcSRfDMZx0vZdqSA46UWYk618cESOzatCVAKk0kREmgiJDCAyJAAwoIDiQoJpG10KF1DA/ljXiD3PBBIZHAgYY7SJCGBRqZ2kzKqIFtsdsqsdkrLDYWXV1JOTmE5GQVmtmccJafoz4CKEEd29gEdYxiU1IpTk1sBYXjwnPLaPc44XsqnKw7y+cqDFJqtXNCvHQ+N707XNpHEnByoWSvbMwr4+1cb2H20iLtGpfKP8T1c3ueWkgbJ15n++wEW7szmmYv7+JrCqpaaQt4/AM4B3tZav+rY9xjwPPALsAu4HHi5sRVXS7G0GnqNSl3x9C3ZYrOzfE8OszZnMHurYYHFRQRzYf92XDqoAwM7xXqcMLcx8Ob1Ly6zsi+7mJ1ZhWzPKGDL4eP8cfj4iXB3a2EIZenxnNU/jmf+Fke3NpFej8qsoMxqY/HObL5fd4j5O46itebcvoncM7or338YU6cx2+2a6b8f4MXZO4gJC+L1qwaceIkQ6kSDW1rbMwq4+J3ljOiWwEc3DW6wv7d64PE6rbXABK11hmM7EDgMbNJaj3fsSwK+11oPqfXsSnUBnsPIqNERyNVaP6OUigNeBPYB3YDHtdZZNfXVUpRWBc3pIV7xwPxp0xHmbcuizGqnc0IElw3qwMElHeq0UNVTy6yh3a3unsNqs7Mzq5D1B4/x0AvH6Hx67okQ91bhQZyaHMcpybEM7BRLn/YxlVx1nqSi0lrTuW8pr/xfLot2ZbNkZzaFZVbiI4K5cnAnrjs96aQ5K0/GfCS/lLGTNmGOyWVcrza8dHl/l4UZnWmMiEw/p0GVVmm5jYveWUZ+qYXZ94+o9X41ER4rrUpZL5RSZwNzgEuck+gqpRZrrWt1MCmlTgPaa61/cmxvA24A7gAWaK2/VUpNAK7SWt9QU18tTWn52g/cW0q0wGxh9pZMZmw4xMp9eQAMTY1j5jsdyVidSFSoe/MpTT0f5I1jpk41ks+m5ZWwan8eaw/ksfbAMfY5Zb9vHxNKt7ZRdE6I4I3nQ/m/90KJCQsiLDiAoACF1aYxW+3kl5STXVjGoWOl7M0uYntGATlFRkHL1lEhjO3RhvP6GdGW1blo3ZFfa813aw/x7KxtHC/QvHB15QXHNeErL2I+TIMqrSd+3MIXq9L47LYhvmwR11tp/Qe4AkjQWpc57a9TdgxHhvhLgLnAGVrrdIfVtUdrHeei/Z3AnQBJSUmnHqyoPOeH+JoS8pSGkD89r4S/v36Y1UcPERRXgt1iIjWkLZOua8+o7q1dLkL11PJrjJQ93nbp5peUszE9n61HCtiVVcgPc4swRRdjCrHVemxkSCBFGeEUHYqmLDOGsvR42kdEcuBA9c9Dd8d8IKeYp376g6W7jWS5ub/2x5ofUes18lWXtw9So9Kqz/Pwt62Z3PnZOu4amcok344W9FhpLQAma62XOTJjLMPIiHG7U5v2wI9a69M9kkSpS4HRWuv7lVJlQFutdb7DBWkBgpzTRlXF3y0tecusHq01oR3zefTdw8zakkFecTkRwQGM6dmGs3u3ZWS31rSqUtenOVhanmIKsbD7UBnHSy2Yy21Y7JpAR0BJbHgQCZEhxIQFeZxmqYLq2peW2/j34r28t3gvwQEmHj23B9efnkxAgPK5tW9+ToNYWjlFZZzzxhISY0L58Z7hBAd6vOqpMfEsehB4BpijlCoE4oF84GkApVQEcB9wG/A/j6RQagwwBnjAsesoRoaNfIzs8cdqUlj+TEss1Q2eWWZKKSbd0Yqpl7Ri8oTerNiby69/ZDB3WxYzN2egFPTvEMPQLvEMTo5jQMcYpkwJrb1jJ9yNXNNaU1hm5YzxFv44bKG4zEqJxUa5I0chGAlwQ4OMqMPY8GASIkOIDg1kypSGndSODguiS2vPw9HdpWq0odVmZ8b6w7w+dxeZBWYmDGjPkxf0OlFCxNMIVIkebHy01jzx4xYKzVa+vGOgryusaqmtNEkPYDxQDszQWmc79kdguAoBFmutD7h1MqUuAEYAk4B2QDJwEy1sTqulvWV6Y7x2u2bToXwW78pm2e4cNh3Kx2IzOk2IDKFrmwg6J0TSsVUYbaNDiY8IJjoskLCgQIICFEop7FpjsdkxW2wUOdZiHS+1cKy4nNzicvKKjYS2RmLbcvJLyrF6sFC4gvDgAJLiwumcEEGvdtH0aR/NgE6xJDTBZHd93XHlVjv/3XiYfy/ay/6cYgZ0iuXJC3pxWspJHnzBu3jd0pqx/hAPfbvJF7K3u4t30jjV+eyGi3ExUHF1I4B3gZ+Bl4CDQBfgseYePdhS5rTq+sB0p3+zxcaWw8fZcug4X/5aQGT7Ig7mFnOsxFL7CVwQGRJIXEQwCZHBxEeGEB8RTJzjEx0WRHRoEFGhxjqt4ABjjRYY+fnKrDYKzFaOl1jILiwj47iZg7lGtoyDeSUnFHZyfDhDUuIYmhrPmd0STip06AnV5SqsDk9fHCZOKSNpdDqfrzxIxnEzvdtF8+DZ3RnXy/sJkgWXeFVpZRwvZfwbS+iZGMXXdw4jwEeT4VbBu0pLKfUVMBRjPsrzHC/1wN+Vlr/ja3NIzu2Ly6xkF5aRW1xuuPPKrVhsGrvWBJgUgSYTYcEBRAQHEBUaREyYUaDR3WzjnlJcZmXrkQI2ph9jzQGjXEi+Q7H2TIxiZPfWjOzWmsEprTySoSGS/potNhbtzGbG+kPM2XIUFaA5s2sCd4xMZWS3BFFWjYtXldY9X6xj/vaj/PbgyJOyk/gwHs9p1YjW+i8ASqkVde1D8C/qOifn7vyFp/27bh9IREggKQm+8cOMCAlkSOc4hnSO486Rhptze2YBS3fnsHR3NtOXH+CDJfsIDTIZFljXBM7okkDPxCiX2dRTUqAiUEwpSE52z+Kq7joeyS9l2Z4cFu44ypJd2RSX27AVhVC0tTNFWzrS9b4oRnWv6+gFX2Dxrmx+2ZLJP8Z39yeFVS3eyD34u9b6DC/J4xZiaTUtLbAgX4NRUm5l5b5cFu/MZumeHPZlG+uyYsKCOCUploGdWtG3QzS92kXTLia0ztGAYITP78g0MnJsSs9nfVo+aXklgFF4cmzPtlzQrx1DU+MIcioyKTQJXrG0LDY7499YggJ+fWBEg+T+bEC8a2kJzQePc/35WEE+f45ECw8OZGzPtoztadQvOpJfyoq9uaw5kMfag8dYtCv7hPKIDAmkU1w4HVuFkXxZCK//FkxkaCBhQQEnEvBa7ZrScitFZivHTsyxlZKWV1Jpvq9NVAgDO8Vy0xkpDEuNp1e7qEruP3++psKffL0mnf05xXx802B/U1jVUtM6rX9rre+utQOxtPwef7ZUmjtFZVa2ZxSwI7OQPVmFpB8r5fCxUrKLyjhWUl7tfauaab5jq3C6tI6gS5tIereLpk1UiMxR+Tb1trRKyq2MemURneMj+Oauof54vz22tM5VSk12o+OOdZNHaGpk3VjDtK8L1Z0jMiSQ01LiXIaY2+2a4nIrZosdq92OQhFgUoQHBxAWFFCvcum+do38vf+m4MtVaWQXlvHe9af4o8KqlposrVIg040+ErXWdShiUHfE0vIuLc3S8sU5M1+7B752jfy9/zpQL0vLYrMz6uWFJMWH8/Wdw7wuXCPh8hrUtCR6pda6c20fYGODiCs0Gi1l/sLTqr+etm8MmRoaX7tG/t5/U/HLlgyOHDdz58jUphbF69RkaaW4k+lCKdVZa73f24LVhFhagjOjR9eeyNYZX7MiGuscnuBr18jf+68D9bK0rnpvBdlFZcx/aFS93MRNjGeWlrupmRpbYQlCVZyzkruDL0Yn+pq162vXyN/7b0z25xSz+kAeVw7u6M8Kq1r8M2OiIGBYWM6undGj3TvOUxdQY7iMfE2m5uIma4nMWH8Ik4LLT2meMXKNlnvQm4h7UHDGB107DY6vjdnf3Xe+dj2ph3vwrNcW0TY6lC/vGNoggjUiHgdiCIJP01wn0WvC18bs74ESvnY968ueo4XszS7m3L6JTS1KgyGWluD3+OBbcoPja2P2d0vI164ndbS03lu8lxd/3cGKSWNpF9OoK5EaArG0hOZJc5pEdxdfG7O/B0r42vWsK8v35NC9bWRzUFjVIpaWIAiC7+GxpVVmtTHg6d+45rQkpl7UpyFlayzE0hKExsLX5kZ8TR7B+2xMy8dssXNGl/imFqVBEaUlCA2Ac8VmX8DX5BG8z8p9eSgFp6eK0hKEetGS3vJ9LRrN1+QRGo5Nh/Lp1iaSmLCgphalQRGlJTQ4Lektf+rUP6PQtHZfSTSUMvE1eYSGQWvNpvR8+neMbWpRGhxRWkKD0ZLf8j2NRmtoxe5r8gje5dCxUnKLyxnQKbapRWlwRGkJDUZd3/KbA55YNI2h2H1NHsG7bDqUD8BAsbSEloC7OfvqSnNZA9MQ+Jpi9zV5BPfYfOg4wQEmeiRGNbUoDY4oLcHjLOmeIg++2vE1xe5r8gg1sz2jgO6JkQQHNv9HevMfoVAtdc2SLngfX1PsviaPUDO7sgrp3qb5W1kgSqtFs2hRZVeQJ4UUheaNKC3/wWbXZBWU0b0FuAZBlJYAjBrV1BIIvoZED/oPZVYbAN3bRjaxJI2DKC1BLCzhBBI96H+YLXYAuol7UBCEloZED/ofZVY7oUEmOsQ238zuzojSEgThJCR60H8ot9rp1Cock8ntxPB+jSgtQRBOQiws/6HcZqdjq5ZhZYEoLUEQBL/GYrXTKS68qcVoNERpCYIg+DE2rZt1peKqiNISBEHwc+Iimnc5EmdEaQmCIPg5seHBTS1CoyFKSxAEwc9pJUpLEARB8BdahYt7UBAEQfATxD0oCIIg+A1hwQFNLUKjIUpLEHwAWcwr1IfggJbzKG85IxUEH0ayqgv1ISigZaRwAlFagtCkSFZ1ob4oQKmWo7SUrkjp7EcMHjxYr127tqnFEASvodSf2dUFAUMXuUVY++669MiuhpSlqXB5DcTSEgQfQLKqC3WlBRlZgCgtQfAJxC0o1JUWprNEaQmCPyJKTqjA1MJMLVFaguCHSLShUEEL01mitATBn5BoQ6EqqoU5CCV6UBD8EIk2bPa4rYlik3rq/LQdDSlLUyHRg4LQXJBoQ6ECcQ82EEqpRKXUR0qpNU77QpVS7yilJimlPlFKdW8seQTBnxG3oFCBBGI0HGcCP1HZ5HsASNNavwC8AXzciPIIgiD4PS1LZTWi0tJafw8UVtl9AbDC8f0WYIBSKrqxZBIEQfB3WlIKJ2j6Oa02VFZkBY59J6GUulMptVYptTY7O7tRhBMEQfBFnJ+H5eVlTS1Oo9LUSusoEOW0He3YdxJa6w+01oO11oNbt27dKMIJgiD4Is7Pw9DQkKYWp1FpaqU1CxgGoJTqB2zSWhc0rUiCIAj+Q0tbp9WY0YOjgBuAdkqpJ5VSYcBbQLJS6kngYeC2xpJHEAShOWBqWTqLwMY6kdZ6MbDYxVf3NpYMgiAIzQ0JxBAEQRD8hpalskRpCYIgCH6EKC1BEAR/poWZWqK0BEEQ/JgWprNEaQmCIAj+gygtQRAEwW8QpSUIguDHyOJiQRAEwX9oWTpLlJYgCILgP4jSEgRB8GNamKElSksQBEHwH0RpCYIg+DMtzNQSpSUIguDHtDCdJUpLEARB8B9EaQmCIAh+gygtQRAEP0YWFwuCIAh+Q1CAKC1BEATBT4gOC2pqERoVUVqCIAiC3yBKSxAEQfAbRGkJgiAIfoMoLUEQBMFvEKUlCIIg+A2itARBEAS/QZSWIAiC4DeI0hIEQRD8BlFagiAIgt8gSksQBEHwG0RpCYIgCH6DKC1BEATBbxClJQiCIPgNorQEQRAEv0GUliAIguA3iNISBEEQ/AZRWoIgCILfIEpLEARB8BtEaQmCIAh+gygtQRAEwW8QpSUIgiD4DaK0BEEQBL9BlJYgCILgN4jSEgRBEPwGUVqCIAiC3yBKSxAEQfAbRGkJgiAIfoMoLUEQBMFvEKUlCIIg+A2itARBEAS/QZSWIAiC4DeI0hIEQRD8hsCmFgBAKTUOuAw4Cmit9dNNLJIgCILggzS50lJKhQPvAX201mVKqR+UUmdprec3tWyCIAiCb+EL7sFhwEGtdZljezlwQRPKIwiCIPgoTW5pAW2AQqftAse+Siil7gTudGwWKaV2enCOBCCnzhL6HzLe5k9LG3NLG+8fWuu+1X1Z5Xm4Fai2bXPDF5TWUSDKaTvasa8SWusPgA/qcgKl1Fqt9eC6ied/yHibPy1tzC1xvDV9X5/nob/jC+7BFUCyUirEsT0cmNWE8giCIAg+SpNbWlrrEqXU3cA0pVQ2sFmCMARBEARXNLnSAtBazwXmNuApWpoZLeNt/rS0Mct4BQCU1rqpZRAEQRAEt/CFOS1BEARBcAtRWoIgCILf4BNzWt5AKZUIPAcM0Fqf5uL70cCbQL5j1yyt9SuNJJ7XUUp1wRjveqAjkKu1fqZKm1DgVeAw0A14UWu9q7Fl9QZujvdm4K+A2bHrY631Z40pp7dQSpmA/wGrgGCgC3Cr1rrUqU2zub/g9phvppncYwClVBjGeH/TWv+jyncm4J8Y61hTMMa6stGF9DGajdICzgR+AgbW0OYBrfWiRpGm4YkDvtZa/wSglNqmlJqltV7n1OYBIE1r/bJSqh/wMTCi8UX1Cu6MF+AarfWBRpeuYVihtX4OQCn1E0Z+zi+cvn+A5nN/K6htzNC87vFzwIZqvrsKiNZaP6aUigNWKqV6aa1tjSee79FslJbW+nuHNVUTNyilBmMsYP5Qa53e4II1EFrrNVV2mYDiKvsuAB53tN+ilBqglIrWWhc0hozexM3xAtynlMoEwoF3tNZ5DS5cA6C1tmM80FBKBWJYl1WzwDSb+wtujxmayT1WSt2AkbauPxDposkFwG8AWus8pZQZ6ANsbjQhfZCWNKe1DXhWa/0q8A0w12F++z1KqUuBOVrrHVW+citFlr9Rw3gXAy857vFa4LtGF87LKKXOAWYCM7XWVbMkNNf7W9OYm8U9Vkr1BnpprWfU0KxZ3t/60iwe2u6gtT5a4VLQWm8FYoFOTSmTN1BKjQHGAA+6+NqtFFn+RE3j1Vrv11pnOzYXAKOUUgGNKZ+30VrP0VqfC3RWSt1T5etmd3+h5jE3o3t8KWBWSj2GMbUxRCn1QJU2zfL+1pdmrbSUUhFKqdaO/1f4hXH8GwxkNaV89UUpdQFwDnA/kKiUGqaUilNKRTuazMLIoo9jzmOTv7qOoPbxKqVecLiVwAhMOOCv/n+lVG/HeCvYD6Q28/tb65ibyz3WWj+vtX5Ga/0isAxYrbV+0/mZReX7GweEYiTHbdE0m8XFSqlRwI3AucC/gdeAW4F+Wuu/KqWuBi7EcBP2Br7RWs9sKnnri1LqVAxXSYX7JAJ4F2NseVrrFx2RSa8CGUBX4J/+Gl3m5njvx8h2vR/oB7zlr9FWjmjJVzCiJYOAXsDfgYdohvcX3B5zs7nHAEqpy4F7MV6i38UIOKp4ZpmAF4ASIAljHt5vx+otmo3SEgRBEJo/zdo9KAiCIDQvRGkJgiAIfoMoLUEQBMFvEKUlCIIg+A2itARBEAS/QZSWAIBS6kyl1CKllFZK7VBKPe303TDHd2bHv53rcY6VjnOkeE34RkIpFel0HW72ct+xSqmpSqlYL/b3guN6L1JKLVdKLVNKPV5x7ZVSnZ3Gc8Dx/5WO+/+yI6Teuc9JSqlSp3VigtDoSMi7UAmllAZu0VpPd/HdAa11Sj37T8FYY9PZX5OeKqUOAFNdXaN69JmCl66LUqoNsBQjFdJjWmuLY//ZwM8Ya5sec2p/AJiutZ7q2O4GrAM+01rf69RuE0aePJd/H4LQGIilJQjNj3eBIuAfFQoLQGs9F3irtoO11rsxUiRdWbFPKTUA2ANsB67ztsCC4C6itIQ64XA9VbiUHlFKzVdK7VFK3VilXQ+Ha2qLUuoXHGlpqrRpo5T6Rim1Vim1RCn1uVIqwfHdKCeX4hVKqZ+UUjsd1gFKqUSl1C9KqV1KqblKqesdbTcqpa5WSt3vcHcdUErdqJSapZTKVkpNV0oFKKXeVkqtcXKNXVRFtkil1JdKqf1KqTlKqdurfP9ExXVwbMc4uVlHO7W7XCn1u1JqoVJqlVLqDaVUiOO7fsDXjqZfO46/2/FdoONab3Tsn6eUGljDfWkLXI6R8cWVG+V9jJpVtREElDttXwd86fiMVUq1c6MPQfA+Wmv5yOfEB9DAzdV8d6DK9lSMLNRnObYvwnjDj3JsmzDSZr3t2A4AvnKcI8Wpn6XAq07bbwJLnLZTHMdMd/QZilF3CWA2Rh01k2P7LUfb0U7H34yRCuc+x/bpwHuOfg44ydsdo0hoV6dj3wNWA2GO7YeBUudr5LgOi1xcR2cZvgYucvw/yCH3ZBdjTKnSz7MYuelCHduXAseAuGru0QWOfiZ4cM8PYLg7K7ZHAGXA045tBfzhuF6pjv4fauq/Vfm0zI9YWkJ9Oaq1nu/4/yKMnIBdHdvjMPLHvQmgjcSmHzkf7LBGzsTIoVfBh8AIpVT/KuearrW2a63NWuthSqkeGAl0p2mjFhPAtGrkDAQ+cMixSmv9V4wH8witdaFj/y4M99dZDtkigVuA9/Wf1XPfpW516P6Bw8LRhsvuR+C8mg5wBEI8jFEzyuw49kfAClxfzWGxjn9d1RqriZsdltwKjJpWDwIVlaFHYSR0NWut9wErEReh0EQ0myKQgtfQGG/WlVBKKcB+cnOOOP2/ovZPRXRZL0d/B53apFU5vp+jzdfGKQDDIjsIJFK54F3Vop09Hf/ur6H/CrK01s7uLrTWWik1Vil1E4b1Y3PInOho0gUjkel+p2PMSqm6lIeIAV5RSiVjuN0SgZBajukKhAGPKqX+6rQ/nz+VU1XyHf9WKiqojOzpjziOK9Jan1nluOnaEYjhggrXYAVfAtOUUUV3e40jEAQvI0pLqEohlWv4VBCDUYSuKifKQjiUALhQek5UF646vqpSqelcdej/pGOVUldilKgfrbVe5ti3iJrld3WOStuqSn0npVQERmDDD8D1WmubMkLmp9ZyngomaiOIwh3WYrxc9MGIFDQE1HoWMEspNRXDXeoWjnm3C4EeSqknHbtDHOe4DniyumMFoSEQ96BQlT8wrJ+q9MOYn/KE7RgKIMVpX1KVNlscbbo771RKTVNKta+l/4rKxak19F8TI4HDFQrLQbDT//cCFuf+HQ/xtlX6qaroO1T5vidGxdnv9J+1n4KrtKlkxSqlojCi9cxAjyrf3eUIXz8JrXUWhuvxGuWdytznA19qrUdqrUc7PsOAOcC1XuhfEDxClJZQlY8xHnjDK3YopVphBAR84mFf8zAU1/2OfgKAqpVoF2EEYjxR8ZBVSk0ATtNaH6EGtNY7MR6ef3N6QN/pgXzbgPZKqV6O83YGBjj1X4Qx5jvVnwtt7+NkS2wj0NNxnQD+UuX7AxjBGxVzZQHAhCptcjAUV5xSKhFY4JhHexW4VykV7zg2BWN+bEsN47oXCAferohQdBzbHhiMazdvdVwHfO5i/+cYlYWHu/hOEBqOpo4EkY/vfTAUy2aMB+NyYAlwTZU2T2A8jPOBTzHch4swXGUbgXMd7Xo4+vgD+A243dFmJTDK0aY1RlThdgw32ndAe8d3pzraVhzzUBU5EoFfgV0YEXmXONoOd3x/G4ZFZnbIN9bp2ECMwIo0x7EfAJsc43rM0SYSYw5nPzAXoyDhAUef9zv19S6wE2NB70VO1+EKx/eXOI5ZjWEJfVIhk1Mfzzuu0yrgYse+AIzAiB0YRTDnAcPcuIetMAoqrnMctw5Y49jXxdGms+OamB1jWgTEOPXxHwxluwhH9KRjf2+ne7KXaqJN5SOfhvhIRgzBr1FKtdZaZztttwcOAx211oebTjJBEBoCcQ8K/s6/lVJnOW3fi2G9iMIShGaIRA8K/s5PwItKqWKM4IaDnDynJAhCM0Hcg4IgCILfIO5BQRAEwW8QpSUIgiD4DaK0BEEQBL9BlJYgCILgN4jSEgRBEPyG/wcJ4dF1p5q9GQAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "law_df_neg = law_df[law_df[LAW_LABEL] == 0]\n", "plot_dataset_contour(\n", " law_df_neg, title='Distribution of students that failed the bar')" ] }, { "cell_type": "markdown", "metadata": { "id": "6grrFEMPfPjk" }, "source": [ "## 训练校准线性模型以预测考试的通过情况\n", "\n", "接下来,我们将通过 TFL 训练*校准线性模型*,以预测学生是否会通过考试。两个输入特征分别是 LSAT 分数和本科 GPA,而训练标签将是学生是否通过了考试。\n", "\n", "我们首先在没有任何约束的情况下训练校准线性模型。然后,我们在具有单调性约束的情况下训练校准线性模型,并观察模型输出和准确率的差异。" ] }, { "cell_type": "markdown", "metadata": { "id": "vrUZvP8V736o" }, "source": [ "### 用于训练 TFL 校准线性 Estimator 的辅助函数\n", "\n", "下面这些函数将用于此法学院案例研究以及下面的信用违约案例研究。" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:48:00.203972Z", "iopub.status.busy": "2021-10-08T22:48:00.203125Z", "iopub.status.idle": "2021-10-08T22:48:00.205081Z", "shell.execute_reply": "2021-10-08T22:48:00.205503Z" }, "id": "ollW4xAZ72kz" }, "outputs": [], "source": [ "def train_tfl_estimator(train_df, monotonicity, learning_rate, num_epochs,\n", " batch_size, get_input_fn,\n", " get_feature_columns_and_configs):\n", " \"\"\"Trains a TFL calibrated linear estimator.\n", "\n", " Args:\n", " train_df: pandas dataframe containing training data.\n", " monotonicity: if 0, then no monotonicity constraints. If 1, then all\n", " features are constrained to be monotonically increasing.\n", " learning_rate: learning rate of Adam optimizer for gradient descent.\n", " num_epochs: number of training epochs.\n", " batch_size: batch size for each epoch. None means the batch size is the full\n", " dataset size.\n", " get_input_fn: function that returns the input_fn for a TF estimator.\n", " get_feature_columns_and_configs: function that returns TFL feature columns\n", " and configs.\n", "\n", " Returns:\n", " estimator: a trained TFL calibrated linear estimator.\n", "\n", " \"\"\"\n", " feature_columns, feature_configs = get_feature_columns_and_configs(\n", " monotonicity)\n", "\n", " model_config = tfl.configs.CalibratedLinearConfig(\n", " feature_configs=feature_configs, use_bias=False)\n", "\n", " estimator = tfl.estimators.CannedClassifier(\n", " feature_columns=feature_columns,\n", " model_config=model_config,\n", " feature_analysis_input_fn=get_input_fn(input_df=train_df, num_epochs=1),\n", " optimizer=tf.keras.optimizers.Adam(learning_rate))\n", "\n", " estimator.train(\n", " input_fn=get_input_fn(\n", " input_df=train_df, num_epochs=num_epochs, batch_size=batch_size))\n", " return estimator\n", "\n", "\n", "def optimize_learning_rates(\n", " train_df,\n", " val_df,\n", " test_df,\n", " monotonicity,\n", " learning_rates,\n", " num_epochs,\n", " batch_size,\n", " get_input_fn,\n", " get_feature_columns_and_configs,\n", "):\n", " \"\"\"Optimizes learning rates for TFL estimators.\n", "\n", " Args:\n", " train_df: pandas dataframe containing training data.\n", " val_df: pandas dataframe containing validation data.\n", " test_df: pandas dataframe containing test data.\n", " monotonicity: if 0, then no monotonicity constraints. If 1, then all\n", " features are constrained to be monotonically increasing.\n", " learning_rates: list of learning rates to try.\n", " num_epochs: number of training epochs.\n", " batch_size: batch size for each epoch. None means the batch size is the full\n", " dataset size.\n", " get_input_fn: function that returns the input_fn for a TF estimator.\n", " get_feature_columns_and_configs: function that returns TFL feature columns\n", " and configs.\n", "\n", " Returns:\n", " A single TFL estimator that achieved the best validation accuracy.\n", " \"\"\"\n", " estimators = []\n", " train_accuracies = []\n", " val_accuracies = []\n", " test_accuracies = []\n", " for lr in learning_rates:\n", " estimator = train_tfl_estimator(\n", " train_df=train_df,\n", " monotonicity=monotonicity,\n", " learning_rate=lr,\n", " num_epochs=num_epochs,\n", " batch_size=batch_size,\n", " get_input_fn=get_input_fn,\n", " get_feature_columns_and_configs=get_feature_columns_and_configs)\n", " estimators.append(estimator)\n", " train_acc = estimator.evaluate(\n", " input_fn=get_input_fn(train_df, num_epochs=1))['accuracy']\n", " val_acc = estimator.evaluate(\n", " input_fn=get_input_fn(val_df, num_epochs=1))['accuracy']\n", " test_acc = estimator.evaluate(\n", " input_fn=get_input_fn(test_df, num_epochs=1))['accuracy']\n", " print('accuracies for learning rate %f: train: %f, val: %f, test: %f' %\n", " (lr, train_acc, val_acc, test_acc))\n", " train_accuracies.append(train_acc)\n", " val_accuracies.append(val_acc)\n", " test_accuracies.append(test_acc)\n", " max_index = val_accuracies.index(max(val_accuracies))\n", " return estimators[max_index]" ] }, { "cell_type": "markdown", "metadata": { "id": "jeEfKSA7_aOg" }, "source": [ "### 用于配置法学院数据集特征的辅助函数\n", "\n", "下面这些辅助函数专用于法学院案例研究。" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:48:00.212860Z", "iopub.status.busy": "2021-10-08T22:48:00.212142Z", "iopub.status.idle": "2021-10-08T22:48:00.214359Z", "shell.execute_reply": "2021-10-08T22:48:00.213902Z" }, "id": "B6NU6EEKIYMJ" }, "outputs": [], "source": [ "def get_input_fn_law(input_df, num_epochs, batch_size=None):\n", " \"\"\"Gets TF input_fn for law school models.\"\"\"\n", " return tf.compat.v1.estimator.inputs.pandas_input_fn(\n", " x=input_df[['ugpa', 'lsat']],\n", " y=input_df['pass_bar'],\n", " num_epochs=num_epochs,\n", " batch_size=batch_size or len(input_df),\n", " shuffle=False)\n", "\n", "\n", "def get_feature_columns_and_configs_law(monotonicity):\n", " \"\"\"Gets TFL feature configs for law school models.\"\"\"\n", " feature_columns = [\n", " tf.feature_column.numeric_column('ugpa'),\n", " tf.feature_column.numeric_column('lsat'),\n", " ]\n", " feature_configs = [\n", " tfl.configs.FeatureConfig(\n", " name='ugpa',\n", " lattice_size=2,\n", " pwl_calibration_num_keypoints=20,\n", " monotonicity=monotonicity,\n", " pwl_calibration_always_monotonic=False),\n", " tfl.configs.FeatureConfig(\n", " name='lsat',\n", " lattice_size=2,\n", " pwl_calibration_num_keypoints=20,\n", " monotonicity=monotonicity,\n", " pwl_calibration_always_monotonic=False),\n", " ]\n", " return feature_columns, feature_configs" ] }, { "cell_type": "markdown", "metadata": { "id": "HSfAwgiO_6YA" }, "source": [ "### 用于可视化训练的模型输出的辅助函数" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:48:00.224669Z", "iopub.status.busy": "2021-10-08T22:48:00.223920Z", "iopub.status.idle": "2021-10-08T22:48:00.225586Z", "shell.execute_reply": "2021-10-08T22:48:00.225977Z" }, "id": "HESNIC5H-1dz" }, "outputs": [], "source": [ "def get_predicted_probabilities(estimator, input_df, get_input_fn):\n", " predictions = estimator.predict(\n", " input_fn=get_input_fn(input_df=input_df, num_epochs=1))\n", " return [prediction['probabilities'][1] for prediction in predictions]\n", "\n", "\n", "def plot_model_contour(estimator, input_df, num_keypoints=20):\n", " x = np.linspace(min(input_df['ugpa']), max(input_df['ugpa']), num_keypoints)\n", " y = np.linspace(min(input_df['lsat']), max(input_df['lsat']), num_keypoints)\n", "\n", " x_grid, y_grid = np.meshgrid(x, y)\n", "\n", " positions = np.vstack([x_grid.ravel(), y_grid.ravel()])\n", " plot_df = pd.DataFrame(positions.T, columns=['ugpa', 'lsat'])\n", " plot_df[LAW_LABEL] = np.ones(len(plot_df))\n", " predictions = get_predicted_probabilities(\n", " estimator=estimator, input_df=plot_df, get_input_fn=get_input_fn_law)\n", " grid_predictions = np.reshape(predictions, x_grid.shape)\n", "\n", " plt.rcParams['font.family'] = ['serif']\n", " plt.contour(\n", " x_grid,\n", " y_grid,\n", " grid_predictions,\n", " colors=('k',),\n", " levels=np.linspace(0, 1, 11))\n", " plt.contourf(\n", " x_grid,\n", " y_grid,\n", " grid_predictions,\n", " cmap=plt.cm.bone,\n", " levels=np.linspace(0, 1, 11)) # levels=np.linspace(0,1,8));\n", " plt.xticks(fontsize=20)\n", " plt.yticks(fontsize=20)\n", "\n", " cbar = plt.colorbar()\n", " cbar.ax.set_ylabel('Model score', fontsize=20)\n", " cbar.ax.tick_params(labelsize=20)\n", "\n", " plt.xlabel('Undergraduate GPA', fontsize=20)\n", " plt.ylabel('LSAT score', fontsize=20)" ] }, { "cell_type": "markdown", "metadata": { "id": "fAMSCaRHIn1w" }, "source": [ "## 训练无约束(非单调)的校准线性模型" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:48:00.230855Z", "iopub.status.busy": "2021-10-08T22:48:00.230216Z", "iopub.status.idle": "2021-10-08T22:49:16.090015Z", "shell.execute_reply": "2021-10-08T22:49:16.089504Z" }, "id": "Iff8omH3Ij_x" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "accuracies for learning rate 0.010000: train: 0.949061, val: 0.945876, test: 0.951781\n" ] } ], "source": [ "nomon_linear_estimator = optimize_learning_rates(\n", " train_df=law_train_df,\n", " val_df=law_val_df,\n", " test_df=law_test_df,\n", " monotonicity=0,\n", " learning_rates=LEARNING_RATES,\n", " batch_size=BATCH_SIZE,\n", " num_epochs=NUM_EPOCHS,\n", " get_input_fn=get_input_fn_law,\n", " get_feature_columns_and_configs=get_feature_columns_and_configs_law)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:49:16.105940Z", "iopub.status.busy": "2021-10-08T22:49:16.105253Z", "iopub.status.idle": "2021-10-08T22:49:16.588739Z", "shell.execute_reply": "2021-10-08T22:49:16.589208Z" }, "id": "Gxfv8hXMh4_E" }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_model_contour(nomon_linear_estimator, input_df=law_df)" ] }, { "cell_type": "markdown", "metadata": { "id": "eKVkjHg_LaWb" }, "source": [ "## 训练单调的校准线性模型" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:49:16.596459Z", "iopub.status.busy": "2021-10-08T22:49:16.595401Z", "iopub.status.idle": "2021-10-08T22:50:27.638248Z", "shell.execute_reply": "2021-10-08T22:50:27.638651Z" }, "id": "C_MUEvGNp6g2" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "accuracies for learning rate 0.010000: train: 0.949249, val: 0.945447, test: 0.951781\n" ] } ], "source": [ "mon_linear_estimator = optimize_learning_rates(\n", " train_df=law_train_df,\n", " val_df=law_val_df,\n", " test_df=law_test_df,\n", " monotonicity=1,\n", " learning_rates=LEARNING_RATES,\n", " batch_size=BATCH_SIZE,\n", " num_epochs=NUM_EPOCHS,\n", " get_input_fn=get_input_fn_law,\n", " get_feature_columns_and_configs=get_feature_columns_and_configs_law)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:50:27.652880Z", "iopub.status.busy": "2021-10-08T22:50:27.652224Z", "iopub.status.idle": "2021-10-08T22:50:28.056888Z", "shell.execute_reply": "2021-10-08T22:50:28.057271Z" }, "id": "ABdhYOUVCXzD" }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_model_contour(mon_linear_estimator, input_df=law_df)" ] }, { "cell_type": "markdown", "metadata": { "id": "fsI14lrFxRha" }, "source": [ "## 训练其他无约束的模型\n", "\n", "我们演示了可以将 TFL 校准线性模型训练成在 LSAT 分数和 GPA 上均单调,而不会牺牲过多的准确率。\n", "\n", "但是,与其他类型的模型(如深度神经网络 (DNN) 或梯度提升树 (GBT))相比,校准线性模型表现如何?DNN 和 GBT 看起来会有公平合理的输出吗?为了解决这一问题,我们接下来将训练无约束的 DNN 和 GBT。实际上,我们将观察到 DNN 和 GBT 都很容易违反 LSAT 分数和本科生 GPA 中的单调性。" ] }, { "cell_type": "markdown", "metadata": { "id": "uo1ruWXcvUqb" }, "source": [ "### 训练无约束的深度神经网络 (DNN) 模型\n", "\n", "之前已对此架构进行了优化,可以实现较高的验证准确率。" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:50:28.065522Z", "iopub.status.busy": "2021-10-08T22:50:28.064915Z", "iopub.status.idle": "2021-10-08T22:51:36.038154Z", "shell.execute_reply": "2021-10-08T22:51:36.037595Z" }, "id": "3pplraob0Od-" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "accuracies for DNN: train: 0.948936, val: 0.947165, test: 0.951781\n" ] } ], "source": [ "feature_names = ['ugpa', 'lsat']\n", "\n", "dnn_estimator = tf.estimator.DNNClassifier(\n", " feature_columns=[\n", " tf.feature_column.numeric_column(feature) for feature in feature_names\n", " ],\n", " hidden_units=[100, 100],\n", " optimizer=tf.keras.optimizers.Adam(learning_rate=0.008),\n", " activation_fn=tf.nn.relu)\n", "\n", "dnn_estimator.train(\n", " input_fn=get_input_fn_law(\n", " law_train_df, batch_size=BATCH_SIZE, num_epochs=NUM_EPOCHS))\n", "dnn_train_acc = dnn_estimator.evaluate(\n", " input_fn=get_input_fn_law(law_train_df, num_epochs=1))['accuracy']\n", "dnn_val_acc = dnn_estimator.evaluate(\n", " input_fn=get_input_fn_law(law_val_df, num_epochs=1))['accuracy']\n", "dnn_test_acc = dnn_estimator.evaluate(\n", " input_fn=get_input_fn_law(law_test_df, num_epochs=1))['accuracy']\n", "print('accuracies for DNN: train: %f, val: %f, test: %f' %\n", " (dnn_train_acc, dnn_val_acc, dnn_test_acc))" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:36.053401Z", "iopub.status.busy": "2021-10-08T22:51:36.052647Z", "iopub.status.idle": "2021-10-08T22:51:36.498614Z", "shell.execute_reply": "2021-10-08T22:51:36.498996Z" }, "id": "LwPQqLt-E7R4" }, "outputs": [ { "data": { "image/png": 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KnVVK/R5AKfVzpdRzwEkgGbiooeNzhU3btvHgH/9IUVERr7vrLr78xS+aScQmJiZXAh9AexNOK5MWKxGpB7ajQ9bLgFejQ9ffCGxFz0nuEJHmMRu5wsgvLOS7Dz3Eza96FV/8j//HPf90Nz3d3TPdLRMTE5OLRRfw0+HuGdNBVCVCROQksFYptQ5djCsF7UW1V0QOTHfnLgdsdjuf++pXWbpyJV/7j//gmqu38bNf/YrlK5ZPfLOJiYnJ3OJZdHDFuLUJlVKVIhLVYn40ScGfMbZXi8jLIvIdEflPEfmuKVTjo5Tin978Zr7/0EN43G52Xnstv/n1JclfNjExMbmU3I9OCt40wXXF0TYc7ZrVfUBBtA8x0axcs4af/vGPrF67hvve8Q7u//CH8fmmfbRsYmJiMlP8CB278IJSql4p9ZJS6qnhG9rbNSqimQYMAtsnUXXSZBzSMzP56o9/wne+8hV+/MAPOfLKYX76y1+Qn58/010zMTG5iPh9fpprLvvMnh2DXudxvsrwcKIWq2hGVnWcL388JkqpbdF24kojNjaWD37iE/zXt7/NyRMn2LF5C88/++xMd8vExMTkghERy0Qb531lJ000YvVztKfTRIxnx2QyiOtuuYWf/OEPpKWn8arbbucb//M106bJxMRkLjPZpNKfRdtwNGL1S+B6pdQPlFLXK6UWKqWKhm3zmIJiXsmUlJfzwO9+z+277uBzn/40977xjaZ7u4mJyZxERG6e5HVvjbbtaNaszqDnGRW6GuSY/YimA0opC3Aduh7VVnStk1j0tONfga+JSOOwe6oZu3jXOREpj6YPM01CYiKf/Op/M2/RYr79pS9x+tQpfv7rX7Ng4cKZ7pqJiYnJlFBKrUXXHXSi86/2ichE/rJjElWeFXoqcDwU8KYo20wD/oEWw/ega2bZgVcB3wberJRaYyQlD6aS0Qt41UT5/FmBUoo3veMdLFq6lE9/6INcv30H333gB9x2xx0z3TUTExOTSaOUWojWirWjnHsZePNUAvWiTQqecOimlJrMutZo3CsiLxmv+4EfKqWWoa073oGupzWY60SkeorPmrWs27yZBx/+I5/90Id40+vv4cP3388nP/NpYmJiZrprJiYmJuOilCoAngMygFeAU8AAkAAsRo+0nlVKrRWRhmjajmbN6vWTvO6aaDoA9Bj37B3l3Flj74yyzTlNTn4+3/zlL3nV617H1776Ve7a9SraWltnulsmJiYmE/EZoA1YKiJrROQNIvJOY78aWAa0G9dFRTTegL+d5HVRxWCLiF9EnhGR0VxeNxr7J6Np83LAarXyyf/8Tz71xS/y0u7dbN+8hZd2757pbpmYmJiMx03oab5To500LPveii7mGxXRjKwAUEotV0p9Wym1Vyl1Wim1Ryn1DWPK7oJRStmMSMMvA3cDnxeRR0e59F1KqVeUUv1KqT6jH/cZARuXDbvuvpsf/9//YXc4uP2mm/nm175uhrebmJjMVrKAoxNccxjIjLbhqD7YlVIfRrurvwc99zgfbWj7fuCQcX7KKKVuAtzoec43oPO6vjDG5ZuAdwLpwCK0ceJ3gT8qpS6rBZ6FS5bw4//7P269/TY++6lP8Ya7X0d3V9dMd8vExMRkOG3oqb7xWAFEva4RjZHtzcB/Ay8DHwR2okPNdwIfQlcQ/qohOFNCRP4OxKBLkHwd+DHwd6VU+rBL3wbcKCL7RMQrIg0i8q/AI8DtwPvG+T3eqZTar5Ta39XZOdWuXnISk5P51H//D//y6U/z+GOPsX3LVg4dnHIUqImJicnF4DHgZ0qp+aOdVEotAH4K/C3ahqMZWd0PfEdEtojIt0TkcRHZbey/KSKbgO8B/xptJwYjIiERqRSRrwAfA24AvjHsmqfGqJfygLEfMyJRRB4QkbUisjY1Le1CunrJUUrx+re+lQd++1uCwSA3XXc9P3rgAXNa0MTEZLbweSAXOKmUelkp9Qul1PeN/X7gBHqqcKwZszGJRqxWM3EV4H9H1zKZLn5s7O9RSiVM4vpzxn7RNPZh1rF81SoefOQRtu3Ywb9++F94+71vpb2tbaa7ZWJicoUjInXo6O4jaC14A3q55g1oDTmILtIbVdg6RCdWVnT+03j0AXHRdmIsRMSFngNV6KnBibhirJ6cqan8v+9+l/fcfz9//MMfWFw+n9fe+Wp++9BvTLsmE5MrCKVUslLqa0qpWqWURyl1Rin1KaVU1J/FSqk1SqmHlFINSimvUqpRKfWkUmrMpZXhiMgxI0x9Izqe4VPopZn1IrJ+rEjBiYhGrE4Dr5vgmnuM6yaN8ab+YYxz8WiHC4Be49j9SqmxTBDDghZVH+YqFouFt77nPTz0t7/xhre/nVMnT/Lut7+dhSWlvO3Nb+aPf/iDOeIyMbmMUUolAy8Cr0V//qail08+BjwSTbCZUuqf0YFqB9GjIid6RLSQceIAxsKIKRhcpHd/tG0MJhoHi58B31VKlQC/AU6JSNB4Mxajk4Y/QvRrVrHA1Uopp4h0Dzt3Dzrg4sQgt4pEYKdSKklEhg8h7jP2v4yyD3Oa0vnzed9HP8p77r+fowcP8vdHH+Xpv/+Nh/9PfwdYvGQJW7ddzdXbtrF5yxbSMzJmuMcmJibTxP9DR9/dKiIvGMceVkp9Dvgq8C50lPS4KKXWoNf8Pywi3xx06mml1P1MruJG2Os1HA3YMXi6Tyl1FRAQkWOTaWtE25NdnDdE6RF0Mlf4Jj/np/0U8Chwp0Sx4q+U+iy6CvGLwCfQFh2JaG/AL6FHfztF5MVh1z8JfBw4jh59/YuxPQbcLiKj+QYOYcny5fLzR0dL4Zr7BAIBTh49yoE9ezh58CB7XnoJl8sFwJKlS7l62za2bruaLVu3MtcCTUxMZoLUhMQDIjLC726yFJWVy/1f/J9JXfvBu3dN+CylVBI6BLwLyB/8uWtEULehjb1Hjcwb1tZfgS1A5hjBa5NCKfVa9GAG4Nsi8sFB594LfAstnu+PRicgipGVMYq6Az0H+W700DDeOH0CHQn43Wg7AHwZnVf1OuDXQDa6KnEd8CvgKyJSOcb1j6AjS9xo0Xof8H0RCUbZh8uO2NhYlq9axfJVqwDw+3ycOHqUg3v2cOLgQX7+4IP84HvfQynF0mXL2Hr11Vy9XY+8nKmpM9x7ExOTSXAtYAP2Dv/cFZEOpdQZYKFSasF4xrFKqQzgRuDJCxEqg39CL8O8SUQODOvTd5RSJ4GfoDVjwhHfYKI1sg2hw8i/oZRKBJKBbiMQYkqIiBv4rbFN+/Ummrj4eFauWcPKNTpY0+/zcfzwYQ7s3cvJgwd58Cc/4fvf/S5KKVZedRU333oLN99yK8tWLEepKyZuxcRkLrHc2FePcb4aPahYjq5qMRZr0csttUqpW4B/A1YBIfRM1/+IyMNR9Ontw4UqjIg8pZR6O3qK8uKJ1bCH9jNxdKDJLCUuPp6r1q3jqnXrAPB5vRw/fJj9e/bwyp49/Nf/+0+++B//j8Kioohwbbl6K3Fx0xbsaWJicmHkGPux7Gy6jX32BO2EA9NuAF6NrnLxBNoS6VvAH5RS94vIf0+iTwVog4jxeJHJRXcPYdJipZTKQq8RAbwkIr8bdO4NaCX+kojMmfCz7u5uRMQcOQDxViur1q9n1fr18IEP0NHWxgtPPcWBF17gFw/+jAe+932SU1K4/oYbuOW2W7n+xhtJSUmZ6W6bmMwZ/N4ArTUtk708w0iiDfOAiDww7Bp7uOkx2ghP6TkmeFaysZ+HLtUUjs7uVUq9DqgH/ksp9XsRmaheoBctcnXjXJNlXBcV0YSu/zPaVuk6RuYzNaMDIvYqpfKi7cRM0VRfz7te/3qqz52b+OIrjPTMTHbdfTdf+Na3+Mf+/Xz1Bz9gx4038twzz/D2e99KedE87rztdh74/vepqxvv79LExGQKtIeddoxtuFCBXquHsXNbwzEFk12mEeB/hxwQ6QX+hB7YvHoSbbwAfGWskHnj+JfRo6uoiGYa8CbgR8C7RlnMe1IptRgdEPF59DBy1pORk0PFqVPcc+ut3Pvud/OW++7DarXOdLdmHTa7ne033MD2G24gGAxy7JVXeO7xx3npmaf52Efu52MfuZ/lK1Zwy223ctsdu1i6bKk5WjUxufg0G/uxIqKcxn6i4Vx4GrHdiAkYTng0NWFUIfBFdPHF00b+7GnOF19chBa8QuDqSbQ1hGhGVqXAf4wV7WeEin8CPe85J0h2OvnqQw9x7U038cNvfpN7brmFA3v2zHS3ZjUxMTGsXLOG93/84/z674/xuyee4AMf/zgJiQl8+Yv/xdUbN7J25VV87tOf4eCBA6ZvoYnJxSNciqNkjPPFw64bi5PGfqIF6Qn/M4vIHuBN6PW0+9G5W78y9h9BTwG+UURGK7Y7LtHkWbmBlPFCGw3HiR4RsY91zWyibPFi+eKDDwLwyp49/Oy//5vGujpuuO023nrffcxfvHhmOzjH6Ghr49nHH2fPU0/x/HPPEQgEyC8oYOvVV7Nh00Y2btrEwkWLsFguq5JjJlcIF5pnlVtQLP/8wU9O6tr/99F3TjbPqg3oZOw8q0oRKZ+gHRs6XysJSB1uzqCU+hXaoOEDIvKtyfRfKZUNvAUdaehEB3vsA34uIlMqex7NNGAjsBl4ZpxrtgJRGxTOBq7auJHFv/gFDz/4II/97nc8/uc/s/Xaa7n3vvsi4d4m45Oemcmr77mHV99zDz3d3Tz/5JM898QTPPXEE/z2oYcASHE6Wb9hgxavjRtZtWYNDsdE678mJibDEZE+pdSP0fUFbwb+Ouj0vejYgq+HDxjWTL8GOoC3hfNRRcSjlPoR8GHgjcC3B92TBNyGXh+LBNVNom8t6LWpaSOakdVX0f5TbxWRp0Y5fx062et/jdpSs57BI6vB9Pf28tjvf89jv/sdPV1drN6wgXvvu4+NV19trsVMARGhvqaGwwcOcPjAAU6+cojTp7R9Y2xsLCuvuopNmzezaesWNm3aZDpqmMxKZtvICkAplQLsBlLQRgkH0PEFPzeO3yoiAePauzgvOOsGe/UZovQceurwLWgnoDx06PpN6CjBKdvYGYEVSwG3iJydUhtRiFUquvBiCdCOTjILL5wtADLQJTrWj+LxNysZS6zCeNxunnzkEf7+m9/Q2tzMomXLuPfd72bHzp3ExFxWxYgvOd1dXRw9eJDDBw5w+shhDu4/gM+nZ5gXLV7Mpi2b2bxlC5u2bCE/P3+Ge2tiMjvFCiKC9XngNeg1oVq0WH1p8LKNEan9PHpktX14MIUhWJ9ED0oK0VU0XgT+S0R2T7Iv5eikYoCPiki7MSX4FOdLN/0NeI2IRBW+PmmxMjqSjc46fhVDw9dDwMPAe6c6HzkTTCRWYfw+H8///e/87de/pra6mszsbG68/XZu3rWLBUuWmKOtacDr9XLi8GEOvfwyZw4fZt/evZFSJ0Xz5hnCtZlNmzdTPn+++Z6bXHJmq1jNJpRSX0CnOH0N+LKIDCilHgLuRlssVaBHap8Qka9F1fZUorUM0QpbyHcD++eSSIWZrFiFCQWDvPzss7z85JPsfvZZgoEAJfPnc/Mdd7Bz1y7yCgouXmevMAKBABWnTnFw3z5eeflljh44QHt7OwCZmZmRkde1119vipfJJcEUq4lRSu1Di9TvjZ+z0EnFp4FVIhJQSt2LDtZYHVXbV3JocbRiNZi+nh72PPkk+596ilf266nflWvWcNOuXVx/662mGew0IyLUVFVxyBCvYwcPUluj0z9KSku5YeeN3HDjTrZuuxqbzTbDvTW5HDHFamKUUh1AkYgMGD+/C21yfp+I/MA4lgJUi0hUH5IXLFZKqa3oRC838BMRmTN2EBciVoNpbWzkxX/8g71PPknV2bPExMayeft2btq1i23XXYfNPici+eccjfX17H7mGQ7t3s3zzz6L2+3GbrezbccObrxpJzfs3ElhYeFMd9PkMsEUq4kxxKosHLeglHoaXXokR0Q6jWMJQIOIOKNpOxpvwFvR9aoA5otIpVLqZrQVhzK29yql1opIRRTtWtAWTnegQ9/nGf2qQ4difk1EGke5bwG68Ng1aI+sY2h34Evuxp6Vl8ed997Lq97yFmrOnuWFxx5jzxNP8PyTT+JISOCanTu5adcu1m7aRGzslL2DTYaRV1DAXW98I3e98Y14PB4O7NnD7meeYe9zz/HY3/4G6GCNG2+6iRt33sj6jRtNI14Tk4vLabQ1338rpa4HtgF/DQuVwVrG9w4clWiiAX+ODmu8N1xfSil1BFgCfBZdT+ozwCER+edJd0DXUmlDRxe+B9iLFp9XoeP9u4E1IlI/6J6VnC+//HZ0QtuH0BExnxSR/5zMs6drZDUaoWCQE4cO8cJjj7Hv6acZ6O8nOSWFDVdfzebt29m0bRvpmZkX5dlXOiJCTWUlLz79NAdffJGXdu/G7/eTnJLCtdddyw037uTmW28xQ+RNosIcWU2MUur1aMeKdnRRXIAdIvKCUsqBtln6OvC0iLwnqrajEKuTwGvFKElslEF+GfitiLzeOLYW+M1EGdPD2g2L1WYReWnYuW8AHwC+ICKfNY5ZgENoi/nSwYEdSqk/oSsZr5RJlE6+mGI1GJ/Xy6Hduznwwgsc27ePjjZtTL9o2TI2b9/O5u3bWXrVVeao6yLR39fHy7t38+LTT7P3uedobm4mLi6Oa6+/nlffdRe33HYriYmJM91Nk1mOKVaTQyn1fnRSsgDfEJFfGMdvQNsuAdwz/PN+IqL5dCxED/HC3GV05ieDjh1FJ5JFQw96Km80r6hw8phz0LFrgRVokRwegfgTdLb1B5lFZrrxVisbrrmGDddcQygUoubsWV556SVO7d/Pz77/fX7yne+QlJzMhquvZtO2bazZuJG8ggIzwm2aSExK4pqdO7lm505EhJNHj/L4X/7CU3/9K4/97W/Y7XZuuuVmbt+1i23bt5OekTHTXTYxmbMYlkwjbJlE5HHG9jGckGjEqgO9nlShlIpFe0V1AE8OuiaF8wW/JoVhgPvMGKc3GvvBz7jV2I+myi8Nu2bWYbFYKFm4kJKFC+Hee+nv7eXoyy/zyksv8cq+fTzxl78AkJ2by5qNG1m9fj1rNm4kv6jIFK9pQCnFkhUrWLJiBe//2Mc4cuAAj/3pTzzz97/z8P/pMj5Lli7l6m3buHr7NrZs3WpGdpqYzAKiEasXgO8ppb6Gjv4rQAc0hAZd8zq0i8WUMUwV56EX6e4GPi8ijw66ZMxSziLSrJTyALlKqXQR6biQvlwKEpOT2XTddWy67jpEhLrKSk4eOsSJQ4fY89xz/PVhXU06KzeXNRs26M0Ur2nBYrFEqiV/5DOf4cSRIxx46SVOHDzIzx98kB9873sopVi+YgXbtm9n6/ZtbN6yhaSkpJnuuonJFUc0YvUF9FRdOPqvEfgSgFHL6rNou49/G6uBiVBK3YS24sBo/83A8Oi+iUo59wA2dCnnWS9Wg1FKUVRWRlFZGTvvugsRoaG6mpOHDnH84EH2Pv88f/vjH4HzI681GzaweuNG8gsLTfG6AGJjY1mxejUrVus8RZ/Xy7HDhznw0kscP3iAB77/fb79zW8SGxvL2vXr2HHNNey49lpWr1ljRhiamFwCorVbykePqgS9ZtRmHF+IHlUBfN9w3J1ah3QARTFa+D6PHtG9PjxKUkqdQ9fWGhGQYZyvRa+vDTFqHHT+ncA7ATJyctZ8x/jwnwuExevEwYMcP3iQ06+8QleH1uOcvDw9bRgeeZn5RdOKx+PhyIED7HvxRY7s28crhw4hIiQlJbHl6qu55tpr2H7NNSxYuND80nCZYgZYzCyz2sHCiCr5JvArEXmjcewY2r13u4g8N8o9zehR1VIROTFe+5cqGvBiERav4wcORMSru1OnM+Tm57Nm40bWb9nC+i1bzDD5aaanu5v9u3ez78UXObhnD9VVVQDk5eWx3Rh1bd+xg+yc7Bnuqcl0YYrVzDLbxcqBdnYXIMkwRXwCnUT8KhF5ZJR73OhpwIyJ1qzmulgNJxQKUV9VpUdeBw5w6tAhent6AJi/eDHrt2xhw9atrFq3znTVmGbqa2vZ9+KLvPziixzYs4cu40vDkqVL2XHNNdywcydbrt5qThnOYUyxmllmtVgBKKVagUx07tQRI8DjQ8CHReTrw67NAZqAJhGZMIS+sKxMvvqrX1220zahYJCqM2c4sm8fFa+8wuEDB/D7fMTHx7NizRo2bN3Khq1bWbh0qVm9dxoJhUKcPn6cfS++yLGXX+al3bvxer2kOJ3cuHMnt9x2K9fdcIMZqDHHuFCxyszKlzvvnlwe7A+//SlTrIYx42KllPoUsFpEXj3KuXjABcQAJSJSbSSW/QO9Zva6YdffCfwB+LGIvH0Sz5b0rCyWr1/P8nXrWL5uHSmXsauBx+3m1CuvcGTfPk4fPEjFaZ02l5KayrrNmyPilWvWj5pWPG43e194gWcff5wXn36Kzo5O4uPj2bZjB7fefhs333KrOV04BzDFavpQSgVFJKqigLNBrD4HvBftN9g97Ny9wE+BEyKy1DhmAV5BB1mM5WCxSkSOTPTstMwsmVc2n7MnjzHQ2wvAvPnzWbF+PcvXr2fxypXEX8YO3t0dHRzdt48jL7/Mif37aW/Vb2VRSYl21tixg9UbNmC1Wme4p5cPgUCAIwcP8uzjj7P7qaeorqpCKcXadeu45bbbuOW2W1mwcOFMd9NkFEyxGolSatsUb316LorVZ4HPoStSfgItRIlob8AvARZgp4i8OOieVegSzAfQ+VhtaNeKLwCfEZF/n8yzi8rK5f4v/g+hUJC6ykpOH32FqjMnOH3kCMFAgLj4eBauWBERr+IFCy7b6TIRob6qiiP79nH20CEO7tmD1+vFarOxduNGNu/Ywebt2ymYN2+mu3rZICKcO3OGZx9/nD1PP80rhw4BMH/BfG657XZuue1W1q5bd9n+zc01TLEaiVIqhI4piJq5KFZ2tOP669BuvNlAEO3K+yTwlbBx7rD7FgH/wXnX9ePoJOWHJvvssFgNx+vxcO7kcU4fPUzlqWPUntN5zklOJ8vWro1MGWblRessNXfweTwcP3iQV156ieP79lFn1I4qKi5mkyFcqzdsMGtHTSPNjY0898QT7H/uOZ5/7jkCgQB5eXnsuvNO7rzrNaxdt+6yXV+dC5hiNRJDrD4f7W3Ap6dNrJRSTw368Ssi8rdRL5zDjCVWw+nt7uL00cOcPvIKFSeO0hWuWJuby6KrrmLxypUsXrWK3MvYVaK5ro5DL73EmQMHOBAedVmtLF+9mtXr17N6wwaWrVplThlOE329vbzw1FPseeopnvjHP/D5fKRnpFNaVk5paSklpSWUlJZRUlpCaWkpaenpl+3f3mzBFKuRKKVCIhL10H8q940nVoMV8xEReSXaDs12JitWgxERWhrqOX30FSpOHKf67Cl6u7SZRkpqKgsN4Vq0ciXF8+djiYnqy8OcwOfxcOLQIQ7v3UvFkSOcPXkSESE+Pp5lq1ZFLKFM8Zoe+nt7efaJJzi0bx8dzU1UVVbR2NDA4P+7ScnJlJSUUFpWSnFJKXn5eTidqaSmppKalorT6SQ1NZUUp5OYy/Bv8lJgitVIlFLbReTZS3HfeGIVdbTGXGMqYjUcEaG1sYFzp05QefI41RWnaWtqAsDucLBgxQoWX3UVi666ivIlS4iLj5+Ors8q+nt7OX34MMcPHqTy6FFOnzhBKBQyxesi4vV6aayro76mhrqaGhpqa6mvqaGloYGa6moCgcCY96Y4nRHxSk1NxZnqxGm8TkpKxmazYrPbsVlt2Ow2rDYbdpsdq82K3W7HajX2Nht2mz5vs9ku+5GdKVZTQymVLCK9F9zOdIuVUqpIRGovtGOXgukQq9Hoam/T4nXqBDXnzlBfqZfc4qxWFi5fztI1a1i6Zg1lS5ZcljWsBvr6OHX4MCcOHuTckSOmeF1iAoEAvd3d9Pb26n13N709PXozXvd0d9PX04PP5aKrq4uurk66u7oJBoNTfq7NZsNmtw8RMLvdjs2uxc5mt+trbLbIMbtDH3fYHdgddux2Bw6HHZvNjsNhx+5wYLfbjU1f43A4ZuT/jSlWk0cp9c/omlarAauIxCqltgNvAj4rIg1Rt3kRxGrOjMgullgNZ6Cvl8pTJzl74ihVZ05SW1EBgNVuZ/HKlSxdu5ala9ZQsmDBZTltOJZ4xcXHs+yqq1izYQPrt2xh+apVxJoODzOGiOD1ePB6vXg9HnxeLx5jH/nZ6x3686Dz4fu8Hg8eY+/zevF6vahgELfbjcfjMfZuPG79eipBXnFxcdgdDhx2LXZ2uxaxwYIXEbdBQpiQ4CA1LZ309HQyMjJIy9CvHQ7HhM80xWpijNzYR4Eb0IEUACIiMUqp+cDv0KWkNotIUzRtj/f1RCmlrh70wEn1NZqHXykkJCWzfN0Glq/bAOhps4oTRzl7/CiVp0/wyre/DYAjMZElq1Zp8Vq9msKysssibDkhKYk1W7eyZutWAFz9/RHxqjhyhJ985zv86FvfwpGQwGpDuDZs3UpJefllP7U0m1BK6dHPJbTiEhH8Ph8ejweP262FzhC1wa+Hn4v8HD5mHA8FA7S3teF2u3C53LhdLtxuNy6Xi1AoNGY/HA4HaemDRMx4nZ6ZQXp6OqsMN36TCfkIunT9fwC/AeoxahyKyFml1Grgf4GPoZ2IJs1EY+lnouunyWRITE7mqo1buGrjFgB6ujo5e/woFcePUnnmJPuffx7QofJLVq9m2Zo1rFi/nuzLpHqwIzGR1Vu2sHqL/v37e3s5fuAAR19+mVMHDvDCUzoQNTM7Wxvxbt3K+s2bycjKmslum1wElFLEW63EW60kp6RctOeERdHlctHT1UV3Zyfdxr4r/Lqri+6ODrq7u6moqKCzo4O+vj4APvgv/3LR+naZ8QbgbSISKe00+DNLREJKqc8ADxOlWE0UDRhtlIcCrjanAS+MzvY2Ko4f5cyxI1SeOk6H4SyRmZMTsYZatnYtyZdpBdvWxkaOvvwyR/ft48TBg/QY0ZZlCxacN+Ndvx5HQsIM99Tkcsfn9dLd1UVcXBw3rltnTgNOgFLKBaSKiHfQsSFLQ0ZubbuIRPUf+GKsWU0p7n4mmK1iNRgRoa2pkdNHD3Pm6GEqTh7D1d8PQPGCBSxft44V69ez6DK1hgqFQlSfOcPRffuoOHyYV15+GZ/PR2xcHMtXrWLTtm1s3rGDBYsXXxajTpPZy7rSUlOsJkAp1QFcJSJ1g44NF6sVwJMiElXdooshVj8VkbdGe99MMBfEajjBYJC6ygrOHD2sraGOHh1iDRUeeV2uwRo+j4dTR45wdN8+Th08yJkTumRZRlZWRLg2bN1KUnLyDPfU5HLDFKuJMfxZAd4QDlcfrCWGt+ujgG808/LxmPb4z7kiVACugQEG+vtISJw7pRpiYmIonr+Q4vna7NTr8VB56gSnjrxC5enjPPTd7/IQel1s2bp1rNywgZUbN5J+maz3xNtsrFi/nhXr1wPQ1d7OK3v28MpLL/H0Y4/xp9//npiYGJavWhUx412wZIk56jK5bFFKJaMNHF4DZAG1wM+BL4mIf4ptrgL2oTWiRESqJ3nrf6J9W2uVUr8DDhvtvRUoQa9pFQCbo+7TlZwUrJQSpRT5xaXMX7qc8iVLKV20BEdC4kx3bcr0dndz5th5a6jOtjYACkpLWblhA8vWrmXRVVddlus9wUCAs8eO8cpLL3Fi/35OHz8OQHpmJpu2bWPZVVcxr7SUeaWlZGRlmQJmEhWzcWRlCNWLQCraX/UAcBNarJ4HbheRqJLnlFIxwMvAKuNQNGKFUup1wI8AB9rkVg3a9wNvFZH/i6ZPMHGARfjkO0TkJ5Ps6FMicm20HZkJMrJyZOmqDTTWV1J15hTBQAClFHnziilfvIzypcsoW7SEhKS5OaUkIjTV1XLq8EHOnTrGqcOHCfj9WGJiKF24kKVr1rBkzRoWrViBbRJ5JnONrvZ2DhujrmMvv0xf7/kkeqvNRl5Bgd4KC8kvLCTP2PILCkg0pxFNhjFLxepbwPuAW0Xkr4OOfwT4KvBeEfluNP1USn0UuA9tEJ5NlGJltJENvAVYh86r6gb2Aj8XkbZo2oq0OY5YbR/042kRaZ5EB8uNa+fEiGxwmWm/30djbRU1lWdobqym+sxp/H6fvq5oHuWLl1K2eBnlS5aSlOKcwV5PHZ/XS9WZU1QcP0rNudNUHD9OMBgkJiaGsiVLWLp6NUvWrGHhihVYL7NgjVAoRGdbG401NTTV1tLa2EhLQwM9bW001tXRb4Qoh0lxOkcVshSnk4TERBKSkkhMTMR6BdgMmWhmm1gppZKAVqALyJdBH+ZKqXR06aRzIjJ/sn1USpUBR9Elmh4A5jEFsboYXHCJEGMYejfwZox5yGjESun/6beh5zI3Azno6sBHgB+KyC9Guaca/SaOxjkRKZ/MsweL1XACAT9NddVavJpqqDp9Cp/XA0BWXj6lCxdTumgJpYuWkJGdMyc/sLweD1WnT3LWEK9zJ08SCgaJiY1lwfLlLFu7lmVr1lC+dOll7yzR39tLa2PjiK2rpYWmhgb8Pt+o98XExpKYmKgFbPiWlBR57UhI0JvDgSMhAfug146EBG0r5HCYJrOzmFkoVruAPwJ/FJE7Rzl/ClgILBSRM5N5rlLqCaBJRN406HN22sVKKfVXEbklmnumFGBhRHTsRA/zbgds6PnIILpYYjR8Evh34AlgF3Aa/Qb9F/BzpdQ1IvK2Ue6rBEZbPKyJ8vmjEhsbR2HJfApL9JeSYDBAc0MttZVnaG2p48i+Pex5+gkAklKclC5aTOnCJZQuWkx+cemc+NCx2mwsWrmKRSv11LTH7dK2UMePUn32JL//0Y/43Q9/OMQWatnatZelm3xicjKJycmULlo04lwoFKK7vZ3WxkYG+vtx9ffjHhiIbK6BAe2UMDCAq7+fzvZ26qqr6e/vZ6C/H6/HM+l+2MK2QcOELcEQtLDwhV/bHQ59brAYJiZGjsXHx8/JL1Imk2K5sa8e43w1WqyWAxOKlVLqbcBK9NrXxWZntDdEJVZKqeVogboHPZcZ/l/QAPwQ+DG6aGI02IAW4E4R6TeOnVRKvRY4CbxVKfVLEXlq2H3XXcqhaUxMLPlFpeQXlQIgoRDtbc3UVVVQX11BfVUlh/e+BEC81Ubx/AV65LVwMfPmL8Bmn/1rQja7gyWr1rBk1RoABvr7qDhxjLPHjlJ5+ji/MmyhEpKTWbJqlR55rV1LfnHxZf2BaLFYSMvKIm2KEZWBQACPy6UtgVyuIa/dox0f9nNvdzctjY0MDBLHyRrOxsTGkhAWssTEIaO5ISM+Y0tNSyPXWMtLy8i4LOy+LmNyjH3XGOe7jX32RA0Za0xfBT4gIu2T7YBSaurOx1EyoVgppTLRU3RvAVaEDwMe4E/AXUBReL5UKRVt1cgG4GeDhAoAEfEppR4H3gVcDwwXqxlFWSxkZueRmZ3H6o3bAOjt6aK++hx11RU0NVTx2P/9LyIhlLKQX1xC2aIllC1ZStmipXNiAT8hMYmV6zexcv0m4Lwt1JljR6g8eYyXn9UGJ870dO0kv3o185cto6Ck5LIbeV0IsbGxkZHbdBDx0zPEzD0woPcuF95BAug2BM89MHBeGA2vvI62NlyG8A0MDBDwj5ykiI+PJyc/X6/X5edHRCzX2NIzMi7rLynTjd/np6V2wqX/MBlKqf2Dfn5ARB4Ydk3YxHGs8PTw3PVkvil/E9gnIr+cbAcNFCOdjjKBJeg1szqgD0gCCo1ztUBVlM8ZW6yMkc2b0cO1GM6HHz4L/BL4vYj0GiHukYUvEYlKrETke+OcDq96z4n/EckpqSxZuZYlK/VUs9fjpqG2krqqCpqbatj9xGM8+zedM5dTUET5kqWUL1lG2eKlJDtnv3VSSmoaa7duZ+1WHXvT0drCmaOHOXP8KMf27+fFf/wDAJvDQemiRZQvWUL50qXMX7p0yqMSk5EM8dObJsstv8+H2+Wit6uLtqYmWhsbaWtqoq25mZ7WVk4dO0Z3Z+eQe6xWa0S4CoqKKF+0iAWLF1O2YAH2yzC69BLTPon1MbexH2tBOVw8zzVeI0qp24FbgWWT7955ROSaQW2VocPmbxSRJ0Z51g3AV4D7o33OeCOr33I+Nv44WqB+JSL10T7kAlhg7J8b5dy7lFI3A+Xofh4Hfgb8QETGtle+hFhtdkoXLKV0wVLgfNBGbdVZmhur2ffs07zwj78BkJWbR5khXOWLl5KaEZUTyYyQnpXNputuZNN1N0ZsoWoqzlBTcYbGumr+8pvfEDSKAKZmZlK+ZAnzly6lbOlSyhYtwn4Z5nrNVeLi44mLjyfZ6aSgpGTUazwuF23NzVrEjK21qYnutjaOHDjAgGEDppSioKiI+YsXU75oEfMXLaJ80SLyCgrMacXpJTxMG+sbi9PYt4zVgBFR+F3g01NcVvnEsJ+/AtwvIi+NdrGIPK6Uei86eTiqdavxQtd/j47S6wP+By1UI4oqXqzkYaVUGtAInADWDAvLrEYvHn4UnSGdgXbwvR89NXnnZBLhxosGvBTooI06aivP0NxcQ9Wpk7hdA4AWgrLFSylbvJT5S5eTnjXhtPOsw+/z0VBTpQXs7BkaaipprtffdZRS5JeUMH/pUkoWLiQ9KwtnejrOjAycaWmXffTh5Yb+stJETUUFtRUV1FRU0FRZSV1NTaReVUJiImULFzJ/4cIhIpaQODeS8C80GtDpzJLt2++e1LWPPvrtaKIBHxGRV41yfsJoQKXUDuDpSXUKakSkeII+dQA54zlnKKXigDYRcU7yufq+8ULXlVKp6GCKt6ArPr6IHuL9XkR6jGsullj9CL1Wtk5Ejg07dy3wgoj4hh3/Izqi8EMi8o2JnjHTYjWcUChEa1M9tZVnqK06S31NBQNG/k96Vjbzly5n/rIVzF+6nJTUtBnu7dQY6OulpuIsNRVnaW6o5tyJE/T19Iy4LiklhZT0dJxpaaRmZGghC2+GoDnT03EkJprf1mcxHreb+spKas6epaaigtbaWs6ePBnJa7NYLCxYsoRV69axav16Vq1bhzNtdv5tz0KxSkKvC3Uydp5V5WRTeUZpv5ooQ9eVUv3AJhE5Os41K4DdIhLVt5RJ51kppZaiyxTfgx52/gX4FfB/wxx1L7isvVLqDegpvX8SkT9Ecd8tRr8OisiaMa55J/BOgGRn2pr3/9t/XUhXLyoSCtHW2kTNudPUnDtNbdUZ3AN65JWdX8CCZSuYv3QF5UuXzSl/w8GICD1dnfR2dRol2Lvo6+6ip0vv3e5+XWOoo2PUXCdlsZCYlKQDGFJSIoEMicnJJBj7pGHHk5xOHImJZnDADCEidLS0UFNRwbkTJ6g+cYJjhw7h9eqqEiXz57M6LF7r15OVkzNBi5eG2SZWAEqp7wDvYWwHi/eLyLeNY8nAr4EOdM2pcWefpihWTwPJ6M/uc6OcL0cXX+wUkesn02bk3miTgo0cq5vQo607ACvwZeD7IlJ9oSMtYwHuUbRNyKQsngbduxA4BbhkErVSEhKT5KY776GodOGc+LAPhUK0NNZRXXGKpsYqzp08EUlUzsjJpbCkjKKycgpLyigoLcPuuHzWhEQEt2uAvu5uLWw9Wthc/f0M9PXh6u/DNdCP3+ehv7eXvp6eiLCPRkJSEjmFheQUFJBbWEhOYaHeFxSQeBGLAJqMjt/n49zJk5w6fJia48c5PGgNbMmKFdy0axc33HrrjBbgnKVilQLsRlsaDfcG3I0WsYBx7V3osvKgZ6z2j2xxSNvVRC9Wm9GR2zHAIXTe7ACQACxC+w36gB0ism8ybUbavhAHC6WUE3g9WrjWAv8Adk5VrJRS16PnYD8QrVAZ9y9C52ZNSqwsFktk5JyVk8+88kXMK1vIvNK5kRcVDARorK+mtvIsTfXVtLU00NnWGjmfnpVNdn4BWXkF5OQXkJVfQHbeleN7FwwEcLu0s77LSOYd6Oulv7eX9pZmervbaa6ro72lhcH/DxKTk8+L17C9Y46sr8x1goEANRUVHH35ZQ488wynjx/HYrGwdtMmdt5xB9fu3HnJ/45no1hBRLDGcl33DbouD21u2wFsFxH3KG3tYOw1rLeKyIOT6M816Lzb0lFOnwXeLiLPT9TOiHYv1G4p0pAWinuBf52KWCmlrgMeAT4oIj8edHwpsEyMMslKqfuB5SLyllHauBX4M3BIRFZP9MzMrHzZsv12Gusrae+op666goDfj1KKnPwi5pUtpLh8EYXF5cRb54ZXnmugj6b6Wi1ezQ30dHfQ2tgQ8TkESEhKJju/gOy8fLLzC8nKzycnv5DUjAwslisvPyrg99Pe0kxbczhcu5He7g6a6uroaBkaSJWcmjpEvHKLiiIjNJvdPsYTTC6U+qoqdj/+OHuffJL6mhri4+PZcs013LRrF1uuuQar1XrR+zBbxWo2YtjobUGPpJKBHvTyzO4ptzldYhVpcAqVgo2AiUfRgRE/GnbuXuBeEdlh/Pw54N3AfBHpG3btn9H5Ah8RkQmrKg736goGA7Q212nxaq+nvraSUDCIxWIhr7AkIl4F88rmVLSahEL0dHfS3tpER2sz7a3N9PV20NxQz0DfeSfyuLh4MnPzyM7PJzM3n6zcPLLy8snMzZvTZVMuBJ/PS3uzFrJ2Q8h6utppqq+nq22oeXRaZuYIEcstLCQ7P5+4+PgxnmASDSLCuRMneOGxx9j75JN0dnSQmJTEdTffzE27drF6w4aLFnBjitXMMu1iFXUH9JDxL2jlHZ4JDbpgl3uQWH0W+BzwJPBxdH5VGvAvxvYYuobLhEXHHI5E+ac3fZj4+NFHTQG/j5bmWhrrK2ltq6OpvgYJhYiLi2de2ULKFi2jbOEyUtNnf07UWLgG+iIC1tHWTHtrE91d7XS2tjI4XS0xOYXM3DyycvOMfT5ZeflkZOdcsR/EXo+btuZwzlEDbc1NdHe20VxfT2/XeQccpRRpmZmkZ2eTmZtLRk4OGYNeZ+bkXJYlWi42wUCAo/v388Jjj3HguedwDQyQlZPDDbfdxs27dk170U1TrKJDKbUWXSLEibaE2iciB6fc3lTFyoiVD1sweYEnROSxKbTzoNHOeDw7SKzs6MCO1wHr0XO0bs4nLn9/MjlWRlvicCSx8epbKC1fNuEfts/noamhmvraCpoaz9HVob9Zp2VkUbZwGWWLllFUuoC4uLn/4R0MBOjqbKOzrYXO9lY62lro7++italhxAdxakamHoXlF5A/r4SC4lJyCgrn1OhzunEN9EemFNuaGulsa2Wgv4f25mbaW1oiydJhEpKTyczJiQhZRk4Ombm52pMwMxNnejqxsdNe2PuywevxcOD55zn4zDPsfvZZgoEAJeXl3LRrFzvvuIP8wsILfoYpVpPDCHT7OTqOYTgvA28eK+9r3HbHSQreajwQdALXhkHnUtGuEks4b4UkwG9F5J5oOzFTJCWlic1up72tkfzCMjZvuw1n6uRHST3d7dTVnKW1tYaac6cJBPzExsZRVLaA8oV61JWWOfeSeSfC6/HQ2d6it7ZWOtqa6e3tpKWhPhKdaImJISe/kIKSUvLnlZBfrLcrdTpxMKFQiL7uLjrb2+hqa6WrvZ3O9lY629vo7+mirbl5RCSjUork1FTSMjNJzciIiFjkZ+N1QnLyFR+S39fTw54nn2T/U0/xyn4d8LZizRp23n47N9x6K6np6VNq1xSriVFKFaAjEjOAV9DR2eFowMVoV/dWYK2INETV9jhi9Wl0hMlf0Uazvxt07jvoSpIDwLfRThM7gZuBN4rIQ9F0YqZwOrNk27bXUl19nNOn9xII+Fmxaiur1m4nNsrRUSDgp6mhivraszQ2VNLZrhfmU9MzKV24lLKFy5hXumDOBGpMBQmF6Opoo6WpjubGOro6W2moqRwyEkvLzCK/WI++tICVkppuGqIOxzXQT1dbG91dHfR0dtLT2UFPl94P9PfS2dZGX3f3iPvirFbSBiVRpxjJ0ylpaTjT0ob8HH8JghJmmtbGRl58/HH2PfkklWfOYLFYKF+0iJVr1kS2nPz8SbVlitXEKKUeQNclvEtETo1yfjE6z2q3iLwrqrbHEau/A40yrJaUUioBrYw24DUi8sdB534OZIrIzdF0YqaIi7PK9u13k5CQgsfj4sSJF6mvP01ikpPN225jXsnI2kaTpbenk7qaM7S21VJTcQq/34eyWMjOLaCguJzCeWUUFJfPCQPbC6W/r5eWxjpjq6W9rYm2psbzNjxJSZQsXEzZoiWULlxCQWkpsbFX7hTiZAn4/YaAdUaErKerg+7OTryeAbo7tND19/aOer8jMXGEmBWWlbF+xw6Snc5L+8tcZESE2ooK9j3zDDUnT3LslVdwu7S/a3ZurhautWtZuXYt5QsXjlqPzhSriVFK1QKvGm9tyljLelhEopqbHU+szqDV8ciw43ehlXFEuWSl1GrgzyKSF00nZgqlLGKxWJg/fy3l5auJiYmhvb2BE6depLuzlaLiRWzeditJyRcmKIGAn+bGGpobq+nsaqKxtioSSp6Smk6BIVyFxWVk5uRfEfZBPp+XtqYGmhtraayrpqmhmramRkCbqhbPXxipxFyyYCFWmxkWPlUCAT/9PT3aHSSy76bP2Hs8Lno6O+nu6MDV309MTAwrN25k686drLn66ssyJD+cx3X68GFOHzlCxbFjtBlpCgmJiSxftYoVxshr2VVX4UhIMMVqEiilPEDSJLwB+0Qkqmmm8cSqF21I6Bp2/Kfo0iFfEZGPDzuXhLa2nxPzCwkJyeJ0ZtPYWEFCQgrLl28nK6uIUChIZeVhzpx5GQFWrd3OilVbiYmZngXuUDBIR3szLc01NDfV0tZaT39vN6Cr9+YXlRriVU5eUQnx8XPi7bxg+vt6qa8+S21VBU0N1TRUVyESwmKxkF9cSumixZQtWkrposUkpThnuruXHSJCY001B158jlf2vkhHSwtWm42127axdedOVmzYcNkGeYhhxHv6yBFOHzlC1fHjnDtzBhEhJiaGN77jHfzs+983xWoClFJ1wB0icmica9agR1ZFUbU9jli50GLVO+iYBW1Lnw5sE5EXh92TjHbmnRNzW4mJTlm+fDvd3a3U1Z1kYKCH3NwyFi3aSFJSKm53HxWV+6k6d5wUZwbrNt1Iceki9NswfYgIfX1dtDTV0tJUS0d7A60tjSCCslhIcaZhtdmx2exY7XasNgexsXHExsYSExtLTPh1TOyQY4lJKeQXlcwJN47R8Ho8NNSeo7aqgpamGmrOnomMSLPy8lm0chW3/tMbzLDvi0AoFKLq9EkOvPgch/fupr+3l6SUFDZcey0bduxgyZo1l61whRno6+PssWOcPnKE0sWL+epHP2qK1QQYBuTr0UtEZ0c5vwD4PfDSdK5ZnQbeKSLPDjr2KuAP6PooeTLsZmMa8JcisiSaTswUsbFxsmjRJpKSUgmFgjQ2VtDUdI5gMEBeXjkLFqwlOTmD1tYaTpzcTW9PB2np2RTMW4DDkYjdkYjDkRTZx1tt0xYo4PW6aW2uo6Wplr6+LnxeL6KCeD1uvB43Ab+fYDBAIOAnGAgw1r8jSpGZnUvBvHIKissoLC7DmZY5JwMagoEATQ011FWdpamxhlOHD5Kelc1bPng/RWXzJ27AZEoEAn5OHznMgRee5djBl/G63SQkJ7N261bW79jBig0brohgjbs3bjTFagKUUoXAQbTZ+SFGRgNeBbSjyz5NWzTgd9EJXbeLSLNRAfJvQBmjTAEa9/wCSBGRO6LpxEyhlEVASE5OJy9vPikpmQQCPpqaKmltrSYQ8JOTUxoRrcbGs9TUHqOrs5VQaGQql8USgyMhEbsjaYSYhY85EpJwJCRN25RimFAoSDAYJBgMEAoGCQT99PXq0VpXdzMNNZV4PdoKLCExmYLiMgrmlVFYXE52fuGcDGioq67g0d/+hL7ubm5/w5vZccsdc1KE5xI+n5fTR17h8N6XOHFoPwN9fdgcDlasX8+ytWtZumYN+cXFl+W/gylWk0MptQyd9nTVKKf3o/OsRkQKTtjuOGI1D13YMBFtfJiBzqlqRnv1dRrXOdFFGu8Cbgf+RSZRS2o2YLXaJTExlf7+Lnw+Dw5HMnl55aSn5xEMBgzRqsHv95KVNY8FC9aRlpaDiOD3e/F6XXi9Ljwe16DXA3i9LoIhHy5XPx63C52CNuLZ2BMGCZgjacjebuyna71KJERXZxstTXqdrKO9IZLUHBMbS15BMQXF5RTMK6Vojhj5ArhdAzz+l99w9OW9LFm9ljfc98Erxqh3pgkGApw9fpTDe1/izPHDtDfrwrXO9HSWrF7N0jVrWLp6NTmFhZeFeJliFR1KqfXoAU8K0I12sBjX6X3c9sZzsFBKrQL+G9iArhj8HPBxEakcdM0G4DeDbrtJRE5PtUOXEqvVIfn58xEJ0d/fTX9/Nx5PP1arg9zcMiPYIkRLSxUtLdX4fB4yMgrJySnGZkvAanVgsyVgsyWMOVIKhYL4fO6IoHk8A0Neh8SPy9WHa6Bv1NFabFw8ycmppGfkkp6ZR0ZmLukZudOSr+Ua6KOlWa+TdXY20dRQQygYxJGQyL3v+zip6TNXjiEaRIT9u5/myb/8nsSkZN78gY9QvmTZTHfrikJE6Ghp5uzxo5w9fpTK0yfoam8HtGfiUmPUtXT1arLy5kSw8AhMsZpZZtwbcCYJi1UYEcHl6sXl6qW/v4vY2Hhyc0vJzi5GKQstLdW0tFTj9bpGtBUXZzUELAGb7byInT+WgN2eMKareXi0Fh6ZnRe1AfxBN+1tjbhd/ZHrk5JTycjMI90Qr4zMPBwJF1aTKxDw09JUy1P/+C2JySnc+96Pz6mQ8eaGWh7935/Q3tzMztfczc7XvPaKdJGfDYgIrU0NnD12XrzCyeGZublauNasYcmqVaRnZ8+JkdeFilU4oGsy7Nnz6JwQK6XUZ0TkC1O4780i8vOJrxx0jylWIxfmRcQQi366u1uxWGLIzp5HTk4Z8fE2AgEffr8Xn8+Dz+fB7w/vvYiE8Hi02Aw2gtUoHI4kEhJSBm1OEhJScDiSJ1zH8ngG6Olpp6enjZ6eNgZc3fT2dETO2x2JhnDlkpaRS25e8ZQErKH+HH979GeULVjKa+9975zK+/J6PDz2x19z9OAeypcs403v/xecaVOz1zGZPkSEprpaKo4f5czxI1SePsmAkayckppK6eLFlC5aFNlSM2dfEJApViOZarHdqdw3LWKllPpfzpsWioiUXXCjlwCLJUaczizs9kTi4+2j/ufw+dx0d7cxMNCDUpCRUYDTmU18vI34eBtxcbZRP8xFhEDAFxExn88TGTEFg34GBnrw+71D7rHZEocJmRazxMTUUTPqAfx+H729gwTM3U1XZysSChEbF8+GLTexeOm6qP/jnzi6lxef/RObduzk2lteE9W9s4Ej+3fz2CMPERdv5Q3v+SBLV8/6//dXFKFQkMaaGipPnaCu6hxN9TXUV1UhIf0Fz5mefl68DCFLzciY0T6bYjUSpVQI+CznPWIny2dnSqxuArLR4YnfmorSzgSDKwUrZTGm6hKx2RKJjx8ahq5FoY3+/u4Ra0txcVZDvOxDRMxqtUdejxZtFwj4jBHc+S0YDDAw0IPPd76IZ0xMHDk5xeTmlpOVVTRh5F4wGKS3t53K6oM01J0jv7CMbdfeSWKSM6r358Vn/8SJo3u5/e63smLNpqjunQ10tDbz6P/+hMbaanbcuovb73nTnIx6vFLwejw0VFdRV1VB3bkKmupraKiujqRlpGZmUrpwIaWLF1OycCEFJSVk5uZespG/KVYjMcQqLCKTESwxrpMZEatIY7q8cudcEauYmFixWR0EgwGChgAFAjrp1GKJMdacErHbE4mLs6KUIhQKEgj4CAQCBIPhvZ9AQFcY9vk8kTaGPQubLQGHIxmHQ0/7JSQkExs7umFuIODH63XhdvfT29tOd3cLPp+HmJhYsrLmkZdXTnb2vDHvBz26q6k5zomTu1FKsfnqW5m/aNWkR1mhYJAnH3+IuqoK3vjuj1Awb04MmIcQ8Pt54i+/48DuZygsLefeD95PRk7uTHfLZJJ4PW7qq6uoO1dBXdU5GmuraKqtjQhYnNVK/rx55BcXD9lyC6e/RI0pViNRSu0HVgPVwK+BCesIosXq03NOrIzyx7cBb0C79eYALuAI8EMR+cUY9y0A/h9wDWAHjgH/IyK/neyzY2JixW4bWrIiFAoRCgUIBgOgtGiAFq/Bo66YmDhiY+NG/eAPhUIRARu8V8qCy9UzpMR8fLw9IlxhEbPZEka0KxKit7eTzs5Gurtb8XpdWCwxhnCVkZ1dTFzc6GHuAwM9HD/5PM2N1RQVL+Lqa3ZNei3L43Hx54d/iM/r4a3v/zdSUufm+s+powf56x9+QSgU4nXveA+rt2yb6S6ZTBGP20VjTQ0tDXU0N9TT0lBPe3MDbUboPBglagoKhghYQUkJefPmTdnr0BSr0TFm1j6BLpT7P8ADw236Rrkn+orys0CsPgX8O/AE8FHgNDAP+C90kcWfjuL8vhJ4Hp0p/Xa0C/yH0CVNPiki/zmZZ48mVsMJhUIEQwFCwQACBINDvzhoi6M4Q7ziB72OIz7eNmo0WiDgN4Iz3Ph8HkKhIG53P+HRtMUSY4zA9JacnI7DcT53SNsznRcuj2cAi8VCZmYRubll5OaWjhAuEaGy8jCnTu0hNjaOLdtvp3T+8kmNsro6W/nTHx7AmZbJPe/48JytSdXd2c5f/vAzqs+cpqhsPltuuIlVm7bMqYhHk7Hxejy0NjYYIlZHS3097a1NtNTXEwyen7pPzcggu6CA7Px8cgoKyC4oIKeggNzCQhyJY/9tm2I1PkqpLcC/oXOrvoVeEuoe49q3iMjPomp/FojVf6AFp1xE+gcdjwdOAqXAdSLylHHcgrbxKANKRaR10D1/Am4BVorIsYmePRmxGoyIIBIiJCH9OhQyftZml4GAf0gEoFIWkpLSSE7OmLB6cCgUikQV+nxuRMDl6o2IY0KCk+zsYtLT84ZEDYoI/f1dhnC14Xb3ERMTS17efIqLl+J0Dg0L7uvr4tiJZ2lrqSfFmcGCxatZsGjVhCOtupozPPbnXyAiJKWkkpmTR2Z2Hpk5+WRm55GRnTsnDHeDwQAH9zzHkQMv0lxfR2xcHPOXLmfp6nUsW7OO1IzJF980mRsEAn7am5tpbqijtaGe9pZmero7aGlooKutbci1KWlp5M2bR25h4ZB9Vn4+b9i61RSrSWDk534CuAH4EXrGq+mC2x3HwaJSREqj7ORUxOo+oFhEPjbKue8D7wK+KCL/Zhy7HngcXZX4dcOuvxPtXfgjEXnHRM+OVqwmIvxeioQIhUIEgv6I2IRHSDZb4qTXjHREoR+Xqxe3uxe3u5+YmDgyMwvJzi7Gbk8ccf3AQDetrbV0dDQSDPpJTEylsHAhBQULsdu1IIVCIerrT9PcWkFzYw1KWSict4CFS9ZQNG8BljEiD1tb6mlqqKKzo4W+vg7aW5vOl2dXirT0TIpKFzCvdCFFZQtITpm9fsYiQn11BaeOHaLy7HHam/X/pfziEpatWcfS1espLC2bU2H7JtHj9XjoaG2mrVnXWGttaqS7o5WmurohRUN33nUXj/3+96ZYRYFR3v5jwGvR61lfFpFzU25vHLGKfk5xmgMslFJfAe4H/ktEPmEc+xp6yu9Dw22dlFI5QBPQJJOoqTXdYjUaoVCIQMCnpxJDQWJi4khKSiUxMXXMNabRCOd+9fV14HL1IiIkJ2eQnV1MamrOiA/VQMAfGW11duo6URkZBRQWLiI3tzQSmNHf30Vt7UkaG8/icvVhtydQUr6c7NxCsrILSEpOG1NcQ6EQvT2ddHW20tXZQltLAy3NNREPwrSMLIpKF1JcpsUrKdk5hXfw4iMidLQ1c/bEYaorT1F1+hQiIZJTUyMjrgXLVl4RZq0m53H199Pa1EBrYwOZObl8/TMfN8VqChjmtr8CNgE/EJH3Tamd8cSK0UztJsE0itUj6HWrW0Tkb8axJ4Dr0NUoHxnlHje6inGGiHQMPz+YSyFWYUSEYNCPJSbGWJ8Cq9VBUlIaCQkpUTktBIN++vq6IiHucXFWsrLmkZU1D6t15PqLxzNAe3s9nZ1NuFy9xMTEkZtbSmHhIjIyCowoxxCtrTW0tFdSX3NWB5igPQwzswvIzM4nM6uAzOwCHI6x37NQKERnezONDVV0dDZQV3UGr8cDQHpm9hDxSkxKieYtvGS4Bvo4d+oYZ04cpqriJF63m7i4eBYsX0nZoiUUlpVTUFI6Z9fuTKbGB+/eZYpVlBgzYf8GbEdHAR4VkZVTamsCsZoKUcfPj/H8NKAROIG2kxfj+DFgKbBdRJ4b5b5mdM7XUhE5Md4zLqVYDSY8RQjaYkkphcORQlJSatTThG53H16vi+5uvXSXmppDdnYxKSkjHQD0+lYnbW1auAIBH3Z7IgUFCykoWERSUqrRvyB9fZ10d7fS1dVC/0AnXZ0tkWnOxKSUiHBlZReQkZlH3BjrVaFQiI62JpoaqmjvrKeuqgKfV4tXRlYuRWULKJ2/hAVLVqJm4ZRbMBCgpvIMZ08eobriBO0t5yPOMnPzKCwtp6i0nMLScgpK5m7tMJOJMcVq8hjlpD6BNotQaCPbbwPfmGgQMWab44hV9HYY2oG9Y5rE6kfocPZ1g4MllFLn0EEXm0XkpVHuqwUKjftGOPwqpd4JvNN4vcZhnzmHbhHReVtBP6FQgFAoNOVpQr/fZ0wR6tB4q9VBZmYhTmc2CQkpI4QrFArS2dlMb287bW06b8XpzKawcCF5efNHjNACAT89PW10d7fQ1dVKX387fb16Tl8phTM1k5y8Ypat3IwzdWyngVAoSHtYvDq0ePl9XvKKSrjpVfeQWzAvinfw0uMa6KOpvpam+mqa6mtoba6nu0MbtiqlyMrL1+JVpkUsv7jUnD68TDDFanyM4LfXo0VqMVqkmoCvAd8fHEA3pfbHEasqESmJsrNJwJFo7xulnTcAPwP+SUT+MOzcnB9Zjcb5acJY3O4+IDxNmIrDkTLp+lciIQYGeiPrWwCxsfE4nZmkpGThdGaNEEGfz0NHRwNdXS309uoPXqczi4yMAjIyCkZEIIbxet10d7fS3d2Cy9NNY0MVoWCA0vLlrFq3g9S0iV3bQ8EgFWePsH/PPxgY6GfNxu1s37kLuyNhUr/vbKC/r5fm+hqa6mtoqq+mpamO3u6wkFvIKSgkKy+PtMxs0jIyScvKIjUji7TMzDn1e17pmGI1OkqpOOBtwL+ic60UUAl8BZ16NNIlYSrPmc7Q9elAKXUD8CjwXhH5ySjn5+SaVTQMnyYEiI+3RdzbbTbHuM4VYYJBP253Py6XnioMO2skJKREhCsxMXVIcMbAQA9dXc24XH10dTUjEsJiiSEtLYeMjEIyMwtISckaNUrO43Fx7twhamqPE/D7KSlbwqp1O0jPmNgxwut1c2DvU5w4uge7I5Frb30NK1ZvnJVTg5Ohr6c7Mvpqaqihr6eTrvb2IQnhAPaEBNIyskjLzCI1MzPyOi0zk7TMLByJSbPO0PVKZbaKlVIqGZ1j+hogC6hFFz/8kohMxlECpdQO4C3ANqAA8KFTh34JfFdEAmPc9xHgX9BmDgo4is6R/a2MdPIefN/MGNlOF8Zi3B+BD4wmVMY14WjAD4vI14edm3XRgBdCeJowGAoQExOH1+uK5HHFxsYNEq+EiB3UeG35fG7c7j4CAR2gAUJMTCzJyRk4nVmkpGRhs51fcwkGA/T2dtDb287AQE9k1BUbG09GRj4ZGQVkZhaSmJg65Nler5vKysNUVx/F7/cyr2Qxq9btIDMrf8LfuaOtib17/kZDTSUFxWXc9Kp7yM4rnOI7OLsQEQb6++jpaqenq5Oero7INjDQS2dbSyQYJYw9IYHsvAKy8vLJyssnO7+A7LwCMrJziImd3mrTJuMzG8XKEKoX0WXkXwccAG5Ci9Xz6ErvIwvlDW3jjcAv0CYLHwReQYvex4F3oFOFbhlNsAYF4tUAXwX+wsSBeQqomlEHiwtBKXUd8AjwQRH58aDjS9GViX9r/HwD8A/Gz7P6sYi8faJnznaxGo6IEJIQoWCAYCiACIRC+u/nvJehrp9ltY7uIh8m7JqhAzTcEeNcmy0Rp1OPupKT04dEKfr9XsPhvZ3+/i5cLl3iIbw+lpVVRF5eeeQen89DVdURqqqP4PN6KJy3gFXrriE7Z3zxEQlx5uQh9u99HLdrgLWbr2HbjXdc9sELIoLH7RoiYp3trfT2ddLaUE9PV2fkWktMDBlZ2WQZ4hUWsqy8fBISL6yumcnozFKx+hbwPuBWEfnroOMfQYvHe0XkuxO08XbgO0CZiNQPO/c8sBX45zFmuoaPngab2o4lLjNvZDtVlFLXoqf+PiQiPxp27l7gXhHZYfxsQSt/KWM7WKwSkSMTPXeuidVwwo4awVCQUDAASkWm+pRSkUrG4YKQExV+dLv7IqOp8PRfcnJ6ZNQ1PAnZ43HR29tGT087fX2d+Hxu7PYk5s9fQ2Hh4khZE7/fFxEtr8dFfmEZq9ZdQ25e8bi/n9fjZv/eJzhxbB8JCUlcd9tdLFu14YqdFvN63HS0tdDR1kxHazMdbc10d7XT1tx4PjkbSExOIaegkNzCInIKi8grLCansNAMtb9AZptYGTECrUAXkC+DPsyVUulAG3BOREYW7Rvazi7gNSLy5lHOfRz4IvCQiNwzyvkg59epJosy+jW3xEopdQ166NgDPDvKJSWAOyxWxj2rgOfQQ95/Rv+jfBD4AvAZEfn3yTx7rovVaOiRl546tFhihpQaiY+3kZDgHDFiGtFGKITHM4Db3YvP58HjGQDOj6ByckpGrJmJCN3drbS2VtPV1YLNlkBZ2VUUFS2JBHQEAj6qq49RVXUYt3uA3LxiVqy+msJ589HfQUanrbWBfS/9jca6avLnlbJkxVpKFiwhIyv3ihWuwYSCQbq7OiIC1t7aTE9PG011tXjd5//9nenp5BYWk19cQkFxKQUlpaRnZZsuHWMgIvi8HtwDA8TGxfPJd7xptonVLvSyyR9F5M5Rzp8CFgILReRM9D0GpdR70SHnvxGR149yPmrzCOO+6AP4ZoFYPYhe2BuPZweLlXHfIuA/OO+6fhztQfXQZJ99OYrVcIaue8UaprcxpKRkTihaYcKjrnD4uq6cXExurq6cPPx5vb3ttLbW0NHRSGxsHEVFSygtXRkx4w0E/NTWnqCq+jAD/b0kp6RTVLyQgqL55OYXj1pzSiTE6RMHOHFsDx1tLQAkO9PYduMdrFizyRStURARers7aW1uoK25kbaWBjrbW2huqCNkGLta7Xby55VQUFxCviFgOQWFl13dL5/PS3tzEx0tLbgG+nG7XLgHBnC7+vFEXg/ovVv/7HENEDKKQV6369U8+cgfZptYhU3Avy4iHx7l/N+BncBdIvJ/U+gySqlvAB8A3iMi35tKG9PFjIvVTHIliNVwgsEAymLB7e4zRCuD5OSMSTtonK+c3I1SFrKyisjNLR8SmBGmv7+bpqZzdHY2ISLk5ZVRWnoVaWk5gFEttvEcLW3naG6sIRjUgpqTN4+CovkUFJaTmp49Qoj6ertoqDtH5bkjNNRWUlhczk133kNWbsGFv0FXAAG/n7aWRpobamlpqqOzvZmGmupIsnZMbCy5BUUUlGjxKiguJW9eCVabbYKWZ5ZgMEhnWyutTQ20NWqfv7amBtqam+hqbxv1Hqvdjt2RoLeEBCwqFpvNjtVux2ZzYLM7sNrsZOcV8tNv/edsE6tvA+9FV939wijnfwPczSTWrcZoPw5dpwpgvkxQ9uNiY4rVFSZWYYaLVnJyBikpkxctv99riJbOJ0pPLyA/vzxiljsYr9dNc3MVbW21BAI+UlNzKCu7itzc0sj0X9jLsLW1ls7uJro79VKkIyGJgsJy8ovKKSgsx2Y/n5cUDsR4ec8/8HjcrN9yHVffcPus/1CdjYRCIbraW2lurKWlsY7OzhbqqyoZ6NNBNEopMnPz9PShMQIrKCklIenSJ9V7XC7qKitobQoLkhal9taWyIgRdCRlVm4eSclppGVkk56RjTM9E0dCIlabHavVNsK0ORQM0tneSmtzgzEirae1qYHlazbx/ON/uiCxslodkp8/7vJRhKqqIzVA+6BDD4jIA4OvUUr9GJ3f9G8i8sXhbSilfg68CfhXEflqtP01Rm5fAG4SkX9Ee/90Y4rVFSpWYYLBAJYYCy7X1EQrEPBFogNDoSCJiamRROLhycfBYIC2tlpaW2txuXpxOJIpLV1JUdHiEWtgbncfbW11hoN8A16vG1BkZObqUVdROVk5hXpq0+3i5Zf+wakT+0lMdnLjHf/EouVrzKnBC0RE6OvpormhlubGOloaa2lraRwySnGmZxijrzIKS8soKisn2Tm9bvsel4tzp09QcfwYFSeOUV91LjI9FxcfT0ZOLikp6aRlZJOWqUUpLTMLu2Ns6zIRob+3xxAkLUytTfVDKgkopUjLzCY5OYPS8mU8+fffXEqxmtGRlZF39RjwURlmGD5TmGJ1hYtVmGAoiMViweXqNbwKk0lIcGK3J01qAT4YDNDX14nX64q0kZKiXTBSU7NH1ODq6mqOmOvqsicFZGXNIzOziISEod/WRUJ0d7fR2lpLd28zrc11iISIj7excevNLFi8GqUULc117N39V1oa6yiZv5idr7qH9MzsaX+vrnRcA/20NNbqAoeNdbS3NtLa1BDxjkxJTaOwrJzCkjJjX06y0znp9t2uASpPnaTixFHOHj9GfVUlIiFiYmIpnr+AnPwSCovLyczOJSnZOenE8baWRg7tfZ6WxjramhtwuwYi5xKTUsjKLSAxIZXU9GzS0rNJcCTT1FRNXfVpcvKKee6ph2ebWF2UNSujuO0zaB+/z032vouNKVamWA0hGAoSCPgIhYKEQkGUsuBwJJOY6MRuTxw3ai+Mz+emv78bt7sPn89jOGDkkpFRMMJgt7+/i9bWWvr7O3G5tM1UQoKTrKwisrLmkZ6eN2Kx3+/30t7eQH3jSZoaqiidv5ytO+7AarUTCoU4eWwfB/Y9QcAfYNOOnWy+9uYJi1+aXBg+r4fmxrqI7VRbS8MQAXOmp1NYqoWrqKycwtIyEpO1675roN8Qp2NUnDhKfVWVFqfYWIrnLyQ3r5h5ZQvJLyoZ0zB5PLo723nu8T9x7OAeYmJjyc4tJCkxLSJKaek52OwOHdHa1UZt9Wnqas7Q3FSDhEJYrXZKS6/i5MmXZptYhaMBHxGRV41yPupoQKXUCuAp4NuzSajAFCtTrMZARxEGCAT8OhzeGHk5HCnGiGtid3gxanD193dFcrji4qyG+0UhDkdypI3wtd3drbjdfXR0NOgpSksM6el5EfEa7JYhEqKi4iCnTu0jITGZa2/8J7JziwBtOLt399+pOH0YZ1oGN+56HfMXr7i4b5rJELweDy2NtYZnYg1tLfW0NjVGzqdm6PWjxtpqRISY2FhKFiwiJ6+YeaULyJ9XekFfMvr7enjxyb9ycO9zKKVYsmwDV63ZNmTdM+D30dhQRV3NGWqrT9Pf1w1AWnoO6Wn5pKXlMjDQQ2Kikz17Luma1WTzrNqATsbOs6oUkfLJPNMQqifR9kqfHXS8EL1u9cNJdf4iYYqVKVYTIiIEQwGCAT/BUDCSMJyQkEJCQsqkypqEQiHc7l78fh/d3brciN2eaKxvFYyIJgyFgvT2dtDT00p/fzd9fdq9wW5PJDOziKysIjIzC4mLs9LZ2czhI0/S39fD6vXXcNWa7ZGpy8b6Svbu/hvtrU0sWHoVN95xNymp6RfnjTKZEI/bRUtjXUTAguInK7uQeaULyCsqmZYRsNs1wJ5n/8HLLzxJIBhg4eLVrFp3DYmJeiTX19sVGT011lcSDAaIjY0jv7CMlCTtgdnX105d3WlaWqoRCTFv3jJqao7NKrECUEp9B3gPYztYvF9Evm0cS0ZX7O0A3jbYhkkptRw9ovqeiHxm2DN2AA+KSPGkOn+RMMXKFKuoEBGCwYBR1iQsXLGDhMsx4VRhMBiIFI48L0JJEZunpKS0EQEeXq+bnp5Wurtb6e3tIBDwYbFYWLRoI2VlqwgEfJw5t5dzZ46Qk1fMNTfcRWKSM/K8Y4df4tDLTyMIV19/G+u2XDulKSWT2YvP5+XlF55iz7OP4XG7KJu/gjUbriXFmUEoFOTMyUMcPbw7EmmanJJORrpeK01Ly4sIVEPDGfx+L1arg9TUHGy2BBITUzl27LnZKFYpwG4ghZHegLvRIhYwrr0L+J1xa6SEklJqGfA0YAX+ykiy0G5BxZPq/EXCFCtTrKbMUOEKICKGzZP2KLTbEw2PwrHFy+/34XL1GOa6HYhIJP8r7Axvsw0toxEKhejv76Krq4mmpkoyMwtZtep6rFYH9fWnOXbsOSyWGK6+9lWUlC2N3Nff183BA09y+tghbHYHK9ZsYs2mHaSZQRhzmmAgwKF9z/PCE39hoL+X8kXLWXHVNtIzchEJUVlxnP17nqC3p4OMrHyyM0vIzi4mMdGJy9VHff1p6utP0d/fjcUSQ2pqDsnJabjdA3R0NOD3e8nIKKC9vX7WiRVEBGss13XfoOvy0Oa2HegSS27j+OeAzzI+NaZYzSCmWE0fYeHSNk8WfD6dYBoWL7s9AYcjZYTjxWBCoSAezwAuVx8+nxuvV+cghs1109JySU4+P4UnIrS21lJbe5yYmFhWrbqB7Ox59Pd3c+TY07S3NrBo6Vo2XX3rkCCN5qYaThzZQ9W544RCIUoXLGHdlusoX7z8Ir07JhcDv8/LiSMHeP7xP9HT1UFRyXxWrt5BTu48QsEgdbVnOLD3KTram0hNy6K8bC05OSWEQiEaGs5QX3+K9vYGANLT80hMTCMUCtDR0RiJaHU6sw2TaAcNDWdnpVhdKZhiZYrVRUEkRNDwKNSvA8TF2SgoWDDJ+4WBgW46O5sJBnVJHqUU69bdMmKKsK+vk+PHX8BqdXDjjW9FKUUoFOTFFx+mq6uZ6256HaXly0Y8wzXQx6kT+zlz6gB9Pd28+o3vZPEK8/NhthAI+HH19zPQ34troI+B/j5c/X0M9PfS3tpM9dmTBAJ+svMKWbXmGrJyCqmvraCm8iR1NWfw+TwkJadSXraWgoL5gKK1tZZjx55jYKCHhIQUUlNzSE8voK+vndrakwQCPhISnNhsDuz2ZPr7u+jpaSUhwUl/f5cpVjOIWRDH5KKglIWYGIVICF/AR2xsPJmZ49sh6bIlfZFikeHCkwkJzsjIarhQBQI+6utPo5SFFSt2RAI9qqqO0NXVzLySxcwrWTTq8xwJSaxedw0rV1/N3//8IH/7w68oKC4nKdl54W/AFUIwGMDv8+H36XSHYCBAMBQkGAxqQ+VgILI/f+z8Ob/fN0SE9L4P10AfHvfo7j4xsbEkp6SxcMkasnPn4XEPcOzwSzT+5VeEQkFsNgfZ2SXk5JSQmppNZ2cThw8/TWtrLR7PAAkJThYu3IDTmcXAQDcVFQcYGOgmKSmNpKQ04uPtuFy9NDefIxDwk5CQMsTV3mRmMEdW5sjqoiAiKItiYKAHhyOJjIzCIYnBYUKhIH19nQQCPvr6OnUIc0wcTmcmTmc2KSmZY04d+v1ezp49QH9/J+vW3UJ2djEAZ88e5OTJ3ZSULeXaG/9phKXOaHR3tfHw/36XeaULuftt77/i3C96uzupq66gu7MDn8+D3+fD5/Xi93nw+Xz4vR58Pq8+7vMY53wEg9PwIa4UDkcCjsQkEhKTibHEY7cnYLPrdU+b3UFMbBwWpQiJEPD56O5uo7bqFG2tehovOSWdzIxCsrOLsVhiIu4nXV0tgBAXZyUpKQ2nM5uMjAKCQT+1tSdpa6slLs6K05lFQoKTQMBHR0cjbncfcXFWYiyxkb/bAVePObKaQcyRlcm0EwoFCQT9+P1eUlNzRiQCh/H5PHR0NOLx9ONwJJObW4bTmU1SUuqYQRnnc7c6aW2tZWCgh/XrbyUrax4AZ87s59SpPZTOX8411981KaECcKZmsn7TTnY/92cO7X2e1Ru3Tf0NmOUEgwFaGutpqDlHXfU56mvO0dfTFTmvLBbi463ExVuNfTzxVhuxMVZsSYnExcUTG2clLi6O2Lh44uLiiYmNI8YSgyUmBoslvFmICf9s7GMsMaAUwYCfQMBHIKBHXF6vC49rALd7ALe7n+6uNtyN1fqYZwAJjayQnpldwKJFGyO5UG1tdbz88t8iI3KnM5v8/Pk4nVkkJjpRyoJIiJaWGurqThEKBUhJycDp1AE2XV3N9PS0o5QiPs5GbGz8FfelZTYzq8RKKZUBfBd4LfBWEXlwjOuqgXljNHNusklwJtNPIODD5/eilIWcnNIRBRvDuFy9tLfXo5SFxYs3k5KSMUZ7fgYGuunr68Lnc9PV1Rz5MIqPt7Fhw21kZhYiIpw58zKnT++jfMFKtl//6kn7G4ZZsnw9TU3neOLPv6Nk/iJS07Oi++VnKW7XAA01ldTXnKO+uoLGumr8fh0kluxMJSurgGUrNpOTOw9nWiYxMbGT/pAOBYP09XUz0N+D1+vG63XjGujD53Xj8eiffV43XuO11+OOBN+MRlxcfGREFR9rJzEjDavVTny8HavVTlycFaUUgUCA7u4WGhvPcurUHkDXWwtHkKakZBAXZ9U1qXxuurpaGBjooaurCZerj+TkDJKS0oiLszIw0ENnZxPBoJ/YmDji4m1YJuHUYnJpmTVipZR6DVqoJpsVWAn4RzleM22dMpk0IoLP7yEQ8GG1JpCVVTRGXSpdpLG7u4WEhBQWLFiH1eqInPN4+unr6zJcL/rp6+uI3JuUlEZubhmpqdmkpuaQlJSGUgoR4dSpvZw9u58Fi1Zx9bV3TqmgoFIWNm65jYfrv8Ojv/kpb7rvX+dkYcK+3m4qz5ygvrqC+ppztLc0AXrElJNXyILFa8jOLSI7pzCSizYegYCfvt4uens66O3ppLenk57uDnp7Oujv60Fk5KhHWSzYrHbirXasNjsWFUdKchJx6Vbi4qzEx9uIi7MSGxsfeY9DoRDBoF8LnM8d2ff1dUReBwLn/8srZSE9PZfCwsU4nVnY7UlGNGkPjY0VDAz0RNIiwjgcyWRlzcPhSMbv99LcXInHM6D7Exs/6lS1yexgVvzLKKXuAz6Ntrt/LRMXYwS4TkSqL2a/TCZPWKhSUjJITR29gm/YlaK7u4WMjAJKS1cSDAaorz+Dz+eiq6slMmrS6wjZ5OWVkZqaQ2pq9ggXd9ACd/LkS1RUHGThkjVcfc2uSfkXjkViYgqbtt7K04//jj3PPsbma26ecluXGhHh6ME9PPbwr/H5vNjsDvLnlVJcspTsnCIyswvGdYhwDfTR0lRLT0/HEGEa6O8Fzq9tx1ttJKekk5yUQW5OGQ5HCnZ7UkSA4uOtxMToLyper57Wc7v7cbn68Hj66e3twO3uw+3uH1LJejBKWYiPt2G1OlBKJ40nJ2cQFxcfEblwMdGBgR6qqo7gcvUSCgUj9zscyUa/7MTH24iPt2OxWAiFgnR2NtHb247FEqOn/GLMKb/ZzqwQK+AosFREupRSr53pzphERzAYIBDwkZycQVpa3qjX+P1eY+G6n3nzlpGTU4LL1UtFxUHc7j6SktIGCVPOEA/AsRARjh9/gcrKwyxetp4t22+7IKEKU7ZgBc0tVTz7j0cpXbiMnLzCC27zYuN2DfD3h3/FicP7KSyZz7r1N5KWkT2p96Ozo4Ujh17g3JkjkQ97uz2B5JR0Up05FOQvNBxKnCQkDM2VCwaDdHe30tfXQXt7nyFMfRGBGj7qiomJw+FIwmKJxenMGjbCOj9tGzIMlf1+H4GA10ge74281tOYYrQZi8ORQmJiqjFdaCMuzjbk7yecPjEw0E9XV7NhsRRPfJx1Wv5mTC4+s0KsROSFme6DydTQvoF+YmPjSE3NGfWaoetTm0hJyaC9vZ6qqiPExdnYtu21kUXuyaBD3AeorDxEVdVRlq7YyKarb522b8ZKKdauu5G6qrM8+psf87YPfHJWl3mvOXeaR3/7E/p7e1i78XpWrt424fSliNDYUMmRgy9QX3uW2Ng45s1bSmHhQhITU0fUFwvj83loaammo6ORzs4murtbh4xmtHNJEg5HkiFGdqxWB/HxOmDB7/fi8ehRltvdR39/F36/l0DAx1iRyTExsRFBA51krkXTTlycDYvFYoTG+401zh6CwQ4CAb9xLEAodD5q0Wp1EBdn08EeJnOGWSFWU+RdSqmbgXL0V6zjwM+AH8hok+gmFwW/34s/4CM7u2TEB6SI0NPTRldXMw5HMgsWrMdqtVFTc5ympnOkpeWxdu1NI0xsg8Gg8e28z/hQ68Xl6iMQ8tDX241roDfywbb8qi1s2HLTtE/h2OwOtu7Yxd//9HOefewRrrv1rmltfzoIBgI89/if2P3M30lNy+T217yTrOyJc9kqK45x9NCLtLc1YrcnsGjRRoqLlxIfbx9yrYjgdvfR2dlER0cTnZ2NES9HpSw4nZlkZxeTlJRGQoKT+HibEfzgHzTC6os46YcdSfT9WnQsFr13OJKJiYk1gjssg5z1QSScpxUAFKFQALfbQ19fl3FspMjptuIIBgJGVKIeQVmUBYslxpzym4PMZbHaBLwTOAxkAB9CB2jcrJS6c7CjsMnFIRQK4g94SUxMxeFIGnGur6+Trq5m0tPzKS1dSSgU4ty5w7S311FSspylS7fi9bo5dWovAwM9BIIe+vu6GRjoY/AHkFKKhMRkEpNSyc0vISnZSVJSKimpGWTnFF20D57CeQtYvGw9e557nPmLV1BUOjn3jUtBR1sLjzz0I5rqa1i4ZA2btt4yrjGvz+fl9IkDHDv8Iv19PaQ4M1i58hoKChZGggpEQvT2dtLZ2RgRKI+nH4DY2HjS0nJISdFGw4mJTmJiYvF6XfT2dtDUdC4iToOj/ZSyYLcnEhsbh92u1x0tlphB03xegkE/fr9bO54EA6MGbIQJC1ogEMCiFHFGeHlY4M7v9d9E3BgjRJO5x1wVq7cBLwwyaWwA/lUpNR/YBbwPGLUUs1LqnWiRM79dTQFd58r4UCEUKaw4mEDAR3t7A253H0VFS8jNLcPj6efs2QN4PP1cddW1FBUtob+/i5f2PILH7SIxKYXEJCf5hWUkJqeSlOQkMclJUnIqCQnJk86Xmm42bN5Jc1MVv/vZd8nKycdqd2C12bAaUW5Wm03vB/0cb7Njs9mJt9qw2mwXHGHm93lpb22mraWRtuYG2loaqT13hpjYWK6/6fWUlC8d/T6/j4a6c9RUnaS68gQ+r4ecvHksWbyV7Oxiw5YqRHt7A83NVRHBAbDZEkhIcJKTU0JSUlqk9piI0NfXSW3tSbq6miMBEhZLjA43j7eRkOCMRPyFc5W8Xh1A09PTNkSMwuITDARAqUjYvFIWFCoiPOF1pfMiZDrmX2nMSbESkafGOPUAWqzezBhiJSIPGNcRExN75dp3REEoFNL1rIL+iFiBnvvPyMgZ8mHs87lpba0jFAqwaNFGnM4s+vo6OHNmP0pZ2LLl1aSm5uDzedh/4O9IKMSrX/de0tJnp/N5XLyVa264m0P7nyEY9NLb3alzhowtNEqy6nBi4+KIjY3DYrHoqagYY2+xRJJnLRYLyjL0mFKK3p4uurs69HwY+sM9PTObkvJlrNlwXaRGk0iI/r4eurva6O5qo7G+koa6cwSDAeLjbWRmFlFauoLU1Bz8fh9NTedobq6ipaUav9+LxWIhI6OAvLxykpPTiY+3DymM2dfXaaxTNeI38ujs9kSSklKxWhMiU4DDCec4uVy9Oik4Jlb/fsOm40zxMZmIOSlW43DO2I9uBmcyKSLFFoMBlFKRcPJwJJfDkYTNljhixOB299PWVktMTCxLl27F4Uims7ORiopD2O2JbNx4BwkJKYRCQY4ce4r+vm5ufdVbZ61QhUnPyOH6m1434njYad4XsSLS+6GvPfh9XoJBXftL1wATQqEQEgoZx0Lnjxk/BwN6n5aWQ1n5ClLTsklNz8LhSKKvt4vurjZOH99Pd3c73V1t9HS1D7E+SkxyMm/eUrKzS0hPz8XjcdHSUsWpU3tpb29AJERcnJWUlExSU3NwOrOG/HuKCL29HaMKlNOZbUT0jT3a9fk8dHfrRFyLxUJcnJW4WOsVPZsRCPhobTHTQKfK5SZWV+7/hGkgFArqNYRBtalstgSSktKw25Mi7gFhwu4AXq8Lj8eFy9WDzZbIokUbsVrtNDdXUl19jNTUHNavvxWr1a5zgY4+T2N9JduvezU5ecUz9wsPQkQio0YJhQiFRSSkBSYUCg0ZRem3QRF+OywWi54itDtQxp/h8PdKC5Hey3CBMo7pvUREa2Cgl56uNk6d2E93V1uk7LrRC5KSndhtycybt4ykpFQSE/UWF2elt7ed5uYqjh9/gd7edgASElIMg9ecEbZW4RFUZ2cjHR3nBSo1NXtQyPn407F+v5fu7lb6+7tQykJcrHXE342JyVSYc2KllLofWC4ioyUOlxn705ewS3OesEgFgn6UUiQm6jUKmy1hSIRfIODH63Xh9bqMD9LuyJRgXJyV9PR8iouXExMTG4n4y8kpZfXqGyKh39XVR6mpOcaK1VezYPHqi/L7aCfvXgYGevS+v8coMdETKTcRDAa0AIVHO5OYzpspYuPicTozSEnOoiB/YUSQEhJSsFgsRsJtLy5XL21tdVRXH6OjowGPZwBQpKXlUFS0hNTUnCH2V4GAn/7+dvr7u+jr66S/v8sYTVtwOrOIjY2flEDptnxGvlUnSikzh8lk2plzYgUkAjuVUkki0jfs3H3G/peXuE9zkuEilZycgdOZSUxMHCIhvF6PIU4D+P2+yGK6UoqEBCdZWfMiH5y6IrCuI1Vff4qmpnMUFy9n+fKrIx9YupbQ88wrWcS6jTdcUN/9fh9VFccivnRalLRA+bwjveesVjsJiSnExlgNB/gYI3LMEllL0q/VqMeVUkOEWy8hyaCfBy9/yojrRo9YGxnBNvyY1erAYokxwvjPC1JNzXEGBnpxu/uGRc8p7PZE7PYkw8Q1O+KR5/EM0NZWa9hZdeJynf/vo6d39RcUhyN5XIGKTH8OskTS/dBRg3Gx1jlpU2Uyu5mLYiVANvCwUurj6PyqNOBfgFuBx4BvzVz3Zj+jiVRKijYw7evrxOt1MTBw3vMtPt5OYmIqSUmlg77Rj/wwCwT8VFcfob29gcWLN1Fevjoy/dPX18XBg/8gNS2bHTe8dsofZiJCdeUJXnr+rwz09wAKuyOBhMQUrPEOUpKzdFkJW6IuM2FLxGZLuGRJvaFQyHATD7uK+yLJqeFcIf1zYIxjg4/78XgGhnjbgTbw1VZCCTidmVitDmy2BCP51h5Jku3v76a1tSbitRgI6ODZmJhYEhNTcTod2GyOiCCOhogQCPjx+Yb69Q1eH4uL0/ZKpkiZXExmRT0rpVQxUDXG6RoRKR50rR24A3gdsB7IAtxo0fol8P3J5lhdafWsQqEQfr8nIlJJSemkpGQSGxuHy9VHb287bncfCQkphit1KomJaeOWotdTgwN4PC6am6vo7+/iqquuo7BwYeQan8/N7pcexu/zsuu17yYpOXVK/e/uauel5/9Cfe1Z0tJzWLRw46gFGacLkRBud7+eThzoweXqxefzDBKioYIUCPgi06KTQxEbq5NXwyHcsbFxBIPBSJmN+HgrVqsjstlsCShlwe/34vO58fs9ur7UsE1PAer/2zabznPSwpQw5hqSFibfCCPZwb9TXJwNCZ3v35WUYHuh9ayi+by50GddjsyKkZVhSDupv3gRcQO/NTaTSTBcpMIjqdjYOHw+D11dnXR3t2C1OliwYB2pqTlDwpZ9Pk9EkDyeATyeAUKhgJ5yG5QAGhsbz8aNt5OZWTjo2UEOH32K/r4ebrvzn6ckVH6/j1f2P8uRQy8QExvLsmVXU1y8fFq+xYdCQVyu3oggDd5crt4hU2w6qs1GbGwcsbHxiIQMK6CkiNgM3yyWwa+Nmk4x4Q95SyR3KZwkO1QI/fj9Htzufnp72yNCFI7OHIxSirg4G/HxNiyWmMiIy2p1jIjyG+65F07OHWp5pHRbykJsXNwVJ0wms49ZIVYmF4eRIpVOSkqW8e09QEdHI319HVgsMRQVLYmYy9bWnsDjGSAY9DMw0EswOHgaSuFwJOJwpJCbW0ZCQgoOR4phdJoyZLpNR/49R1NDFTuufw3ZuUVR9V9P+Z1kzwt/ob+vh4KChSxZshmbLWHK70d7ez0tLVX09XXjcnXjcvUzeI0pJiaOhIQUrFY7KSkZxvRaAjbb2LlEoz1n8IhHT+WdF6Kwh93gKcLxZjhiY+OJj7chIlitDhISUoiJ0blb4X1YSMJRh+H2tffeUGEajA6GsBIKBYmJOS9KlrDlkekAYTJLMMXqMkREDM8+7wiR0vkz7fT0tBMI+MjKmkdBwUJEhMrKV2hvb8BiicHhSCYhIYWMjIJBgpQ84eL7YKqqjlBTc5yr1mxj/qJVUf0OPd3t7H4uPOWXzZYt15Kenj+l96Kzs5mGhjM0Nlbg87mJiYkzwvGTSU3NxWZLiGzjVYcdun4zeNpt6HTcaCMfICIs4am+sEHrkGTZQVs4CESPvAIRO6KQkQPn93uMta1g5HzISDsYjMViITZWB1nExVp18vGgwBH9+5pJuSazG1OsLjNCoRBCKOLZl5qaExnteDwDEVPRpKR0iouX4XAk09BwlqamCkSE+fPXMn/+6jFdtydLa2sNx4+/QHJKGnmFZbS3NeqaQlYb8fHWEYInIrgG+ujpbqe+toKjr7xITMzUpvwCAT/d3S20tNTQ2FiB291nTI1lkZGxFKcze0LBFZGI7124iJ/L1TsksCBMbGycMfJhwpHPcMIjL+2P5x0UZBGY0CfvvKjF6pBzFLExcaAsWIyIQv2+aUEyffJM5jKmWF0mBIMBYmJjcXv6UEqRkVFIUtLQ9aGenjbc7j7S0nKZP38tSil8Pg/19acA2LjxdrKy5k1Lf+rrz+hRXE8nf/3jT0ecj42LJz7eaqyxWOjt7SLgPz9FFc2Un8fTT2dnM52dTXR2NtHT045ICKUsZGYWkpdXPkS0R2OwOPX2ttPb2zHE987hSMbhSCEuLj7i6B0Wo2jXznw+T2RdzO8/v+YXFp6YmFhE5LxPHsPD2xVhAYq8nzGzt4SJicl0MCuiAWeKuR4NGM53QYHX68JisZCUlE5ycvqoI6NgMEBvbzvd3a2kpeVSWnoVsbFxdHe3Ull5mGDQz4oVOygsvHC3Kl1zql9PR46ymB9e0Pf7dQRduLhfYqKTxMTUIcmr4d/V6x1gYKA3km/U399NV1dTJF8oJkYX9LNatetGUtLYdZlAjzRHEye9RmSPhL5PhwOD3+9lYKB7SFCK1epAQiFiYuKGOIWbzE7MaMCZxRSrOShW4YiukOicntjY+Eio+WSmt3p62ujubiE+3s78+WtITEzF5/NQU3Ocjo4GMjIKsNkSjKi185Fso+2HvtbXD71maOTbePj9XiMy77wg6a0Hl6tvRFh4OPlVC1MaDkfKmKOccNvhyL+LKU56zdCDx+PC63UbSdV6HWuwQJk5SXMLU6xmFnMacA4RTjgNhgKEQkGsVgdpaTk4HCmT/nBVSuF0ZmGzJdDR0cjx4y8YkYCllJevxm5PoqenNbI+Ey4HEl3+0KhPjgjXcNELF/kbHpgQF2fF4UgmPt5OUlL6kORXq9U+qjCHR3RDxa53SNtxcVbi4mwkJaVOizgNtqHSmzuy1mSxxGC1ar/AiECZBWpNTKLGHFnNgZFVMBQkYDhOADgcKZGw6gtqNxiIFEh0OrMpK1tFXNzo02bnjVjDpq7BIa+HnwsbsYaPiZw3gz3/OmiYw8qwxFe9H28KTySEz+cdIUoeT38kGk67hCdhsVh0cIexxVzA+k4oFDRGS+eF6Xxov85NCoWCxFgmP6I0mRuYI6uZxRxZzVLC61HKovB4BlDKQnJyOsnJGcTFTU+YcUxMLCkpmShloaurmaNHn6G8fA3JyekjrtVrKjEXzS0Cwr+z31jf6cXv9xhODd7Ia7158PuH5gvFx9uJiYklOTkzIkpTHTGFQ9TPr7Ppffj5YcJiGh9nM5NmTWYMpVQy8HngNWhHn1rg58CXRMQ/3r3D2okHPgG8ESgEWoDfAZ8Tkf7p7ne0mGI1yxAJ/f/2zjzKjuK6w99Pg8RIGkmAxCY2AQaxhS1AsAGzCgiO7GATsyiBMQTCHowNdmxyJDvgcwD7YELYbAsPYEA2xARsAwYDAhMSgljMvltsQiAWCdAy0mhu/qhqTU+pe17PzJt5/d7Ud06fnldVXX1v3zd9X223WNGx3O1ptHIFTU3D/XYO6/R7x9ksJPlW2ig++GAezz33MOutt6mfkda5auuMon/3hVXrwla0Z9Yh+f2QvJNubm5h9Gg3I885pWaaermTsFlnasJHd4fkYvF19TgkUcQ7O1e6+HdNTTT5VlMkUku8o/pvYG1cCLrHgENxzupzkqYWCT8naThwB7A7zln9ARfObhZwgKR9zGzxwGhRjOisSoILZrqcjpUdgNHc3ML48RNXbSc+0Ky55ig22GBzFi9exIIFb+ZGAc/727U4+ian5IKzjhzZkgpVNLzbBI6iz8A5+e5BYsO/Ozo6gqgciUMc4RfOjshZOBuJlI4LgB2AL5jZQz7tVkkzgB8C/wRcUaCeM4EDgdPM7Dc+7QFJpwO3ANOBc6speG+JY1Y1HLMyMx8KCdrblyINo6Vlbb+teH7w2EYne3ysa5ysK2/lak4or3WXOL6VHW7347QzSi+cjUTyKNuYlaQxwHvAR8BGlnqZSxoPLABeNbOtKtQjXNfh+sD49NZLktbAdQeOANY1s9X33xkkYsuqBoSz+tzGhRNpaak89bwsJMFXu5xG4kjSXYNZ3YXZeeHkjCIMGzZsVQusszO1iDZsDaYc0fA1YlihSMNwANAMPGJBq8PMPpD0EjBZ0tZm9lIP9ewIbAw8Ge4RaGYdkh4FDgE+D9xdVQ16QXRWg0Tych/W1MTSZe77MGrUWMaOHU9zc0vNf9W7qN9dwVWzHFGnd65ds/iK09OGgytWLEfCT+9eo8u5eEeDzwsjN6SfWdOa8ascGXL8hT/PzcmfC0z25XpyVkXqScpFZ9XomHWyrH0xw4Y1MW7cuowZMz53mnia5cuX+e0fBq5F0N6+lHnzXs7I6VobNWxYEys7OkByC4WHpRxK0HpxDsWdgYqOOIYKikT6xAb+/FFO/kJ/Xn+Q6hlQhrSz6uxc+eniJYteHOR7smjRAhYtWjBQt5gAvF+dqmzVmFAJqKJepaERdYLG1Wty5SL5dHau/P3iJYsmFCzeLGlO6vNPzOwnQZmR/pw3PT1Z3zGqwr2qVc+AMqSdFfBioy28kzSn0XSCxtSrEXWCxtarP9eb2aHVksWz1J/zuiaSrpslg1TPgBIXikQikUh9Mt+f87bfXsuf3x2kegaU6KwikUikPnnanzfPyZ8UlBvoegaUoe6swj7gRqARdYLG1KsRdYKo12BxH9AO7KFgFpNfZ7U1bp1VTzMBAZ4C3ga282u30vWsgYtq8SnwYLUE7wtD2lllDFjWPY2oEzSmXo2oE0S9Bgu/JmomsCHw10F2K2467o+TBEljJf1W0rWSmlL1GHApbszqH4J6vgSsA1xdywXBMMQjWEQikUg9I2kc8DAwjtVjAz6MC8PU4csegQtMC7C7mc1J1TMct4ZqV1aPDfgusHetg9k2VMtK0gRJv5Jkklr7cP0Mf23esfcAiJ0niyRNlTRL0huSlktaKOlBSeGvnyL1jZA0XdLLkpZJel3SDyUNWrypaupUMlsNkzRF0mWSnpD0oaSPJT0r6WJJE3tZX81t5eWoml5lsleGbFMTOfpwbU1tZWaLgM/h4vfdhFsTdZE/piaOyvMw8BrwKPBsUM8KnJP7sT8WAtcDNwL71NpRAaRC3tT3gQuP/y5uYZsBrX2oYwZufcgLOceug6jPeV6Pe4BdcGsctgVu8+nX9KKu4bhfSouAqbh1FfsC7wCPA6PrUKcy2WqCl/9FXDDQFmBd4ETcmMK7wMb1ZKsB0Ks09grkGgu86fW0Xl5bGlsNhaPmAlRFCTgFmAd8AWjrp7OaUWt9vCzn46aUtgTpI4BXvY4HFKzrG778qUH6V3z6RXWoU5lslbzUP5uRd6nP+1492WoA9CqNvQK5rgD+p4/OqjS2GgpHo3QDPg1sb2a/q7UgVeRt4FoLmt9mthzXMgE4qFIlfpbQWbjV6dcH2bcBHwKnSBqMMO9V0amELAL2Bx7JyEviWK1VqZKS2QqqpFdZkbQXcDyupdjba8tmq4anIZyVmT1kZnlxreoSM7vSzL6Vk51ERi4S/TaJqPysZURUxvVft+AiKg8oVdSpVJjZCjObbdnh4vf053sLVFUaW/l7Vkuv0iG3K+5PgYvN7Jk+VFEqWw0FGsJZVZmd/fTO+ZLaJb0m6T8kbVRrwVJs7c9F1j30JqJyLemNTgmltJWkZkmTJV0EHInrKru9wKWltlU/9Eook73Ow73/zu/j9aW2VSMSndXq7I2b3rkNbn3BN4GvAk9K2r6WggFIWge3t8wTwF0FLil9ROU+6JRQOltJOhQXa+0FYBpwLPD9gpeX1lb91CuhFPby9zoXONHM2vtYTWlt1ahEZ9WdG4E9zOxaM1toZovN7NfASbjB5rBvuhZchBu8Pdb8aG4F6iGicm91gpLayszuApqALXFTgGcCd8lFFKhEaW3VT72gJPaSNAzX/ddmZn/sR1WltVWjEp1VCjN7ycxey8i6DTdNdxdJNWvWS5qGW5k+rRf97KWOqNxHnUptKzPrNLPXzOxi4FvAFNzsuUqU2lb90KtM9joN2Awnf38ota0akeisCuB/7f/Zf9ymFjJImgL8DDjJ/yItSmkjKvdDp1zKYKuAmf58jKTRFcqW1lYZ9EavXAbTXpI2AX4AnG5uMW1/qCdbNQTRWRWnZrPUJB0E3AqcZmbX9PLyUkZU7qdOFauvcn19xsyWAAtwMm1ZoXgpbZVFL/WqxGDZK1nY/OswgsYqQbrSZleoq25s1ShEZ+WRtImfpbRWRp6ALfzHQd1ZWNKBwH8B/5x+qUvaXtKRBaooXUTl/upUNltJOk9SZsvQT5Fex3/8uEJVpbJVtfQqi73MrM3MlHWkyiRp+1WorlS2GgoMOWelnMjDuMHj9XH98CFfwYWZeYpB/KUk6QBcn/5ZZjYzyN4dF7kjKVsXEZWroRPls9UawD5ZL2PgGJy8z5nZXKgfW1ElvSifvQpTR7ZqfAY7ZMZAH1QItwQc4fMN2C2VvplPew/3jzgBGI37Z1qAW5G+0yDqsT9ucPYdXOTj8HgEmF1JL583HLif7BhmTxKEPyq7TiW01XQvz0PAPsAY3LYNp+BaHZ8Ce9WTraqpV9nslaNrZrilerHVUDhqLkBVlHD9w5ZzzA3KTsTFofs/YGSQtztuWu6z/qXaDrwCXA5sMsg6tfWgU3LMLqKXz18T+J4v0w68AfwIGFOPOpXMViNxi2RvxQVFXY6bLfYScCWwRdHvYFlsVW29ymSvlEytPXwP96snWw2FI+5nFYlEIpHSM+TGrCKRSCRSf0RnFYlEIpHSE51VJBKJREpPdFaRSCQSKT3RWUUikUik9ERnFYlEIpHSE51VJBKJREpPdFY1QtKkMJimP9oyyoZl5g6APEcF95hU7XvUG5KuGshnXlCGVkkzBvF+kvRlSTdLekPSMklLJL0i6VZJZ0naIrhmRs532SR1SJon6aaetgCRNMeX/6uB1zJSj0RnVSPMbK65AJr7+6QHzAXQbM0ou6qcLzNpAOSZ5e9zbbXrrlfM7GT/TF6voRituLBHA46k9YAHgGtwERv2B8YBnwHOwIVJugR4Ne1UzGxG8N35mnUFiJ0I/CvwN8CjkvbLuO8OwF/6j8dWX7NIIxCdVSQSQW5PqnuBXYDPm9nFZvaqmbWb2TwzuxPnvO71l+RtOtgNM3vPXMDi7+NCE12eUawVFx8Q4Cgf0T0S6UZ0VpFIBJwz2QG4yMyeyipgZh30fYfd+/x5O0njk0QfyXwacA7OYa2Da4VFIt2IzqqOkfTtYHxgjB9nWSBpqaQ/Sto159ptJd0u6WN//EHS7hXut52kWZLek9TuxzEulDQuKLcsJdMMSQdLeljS4nD8R9Laki6X2+9omaTn/bjI18IxtAx9WyT9u6S3Ja30aa2+3v0lXSPpBT/mslDSPXJblOTpN1XSI/7ZLZB0naT1M8q1puUI8p5J6x7kjZJ0sqS7Jb0labkfF7rKd8Gtdg9cFO9w3LI1KHuYpPu9HZdIelzSqZIK/X/7VtXJ/mOP3cBm9hjwL7iArdXgUFw0918CN/u046pUd6SRqHUk3aF+APsRRBvvqVxO3mxfxy3A4cBY4LO4zeHmA6OD8tsBH+HGYvbBdc/siBuv+F9f16Tgmn2BxbixjO39NYfitn34U8Y9Er3uBe4EtsW9lG7AR8LHRfV+EhetuhUYBWyEe2E+T85WLyl9b8O92NYC9sRFBG/1ZZ4BnsBF+27GbVNxGbASmJpR5zSg08u7ldfvMNzmefMJoven5ejBpjOC9N18+iW4sZxRwF7+GbwCjC16j1T+N32d1wAb+Gd8htfzZwW/g4f4Oub387vc1oPNzvF5zwTpNwPX+7/39mWWAxNq/b8Zj3IdNRdgqB9U11mdHaSf69P/Nki/36cfFKRP9i/sbs7Kv+zf9i/ArYJrjvflL8jR6yNS+/rgxkQu839P92XOD65twjnSSs7qvCD9AmBf//ctBPsP+fTHgaeDtLHAQtweTWsHeSeSsdVMWo4ebDojSN8OuCOj/E6+/DeK3sPn7ext8hrQFORd5+ucUuA7eIYvO6ef3+W20Ga4jRVPAD4BluG33vB5a/u0g/1neV0MOLO//1vxaKwjdgM2FrcFn5/3562SBEmb4l6m79M1WA6Amb0IPJZR7xdxLYEHzOzlIO+X/tyaI9OdZvZp6h5PmNkZ/mMy82tWIMdK4Fc59aXpVsbMvmtmD/i/jzCzORnXPAPsIGlsKu1LuFlvd5vZR0H5mwrIUQgze87MDsvISnbI3auXVZ6E68pv888sTfJMWwvUkzyLpb28fx4/T3WRzgfOB34H7G5ms1PljsaNU90Lq3bfvcHnxa7ASDeis6o91dxQbF7wOXESo1JpO/vzS/7lEJI1FrGHPz8ZZpjZYtwLZ6KkDTOufTNLUO8skvU6LxaUo1Ddvv71JF0s6VlJn6ZenskW5Guniu+SJ4d3tB+G6X1F0t5+rPB1uTVIhmsdhTIVIdcudD2b3QrU87E/j8wrEIxDmqTZPdS3auq6mTWZ2YZmdpSZhdvWtwKzAkf7C3/eVdL2BWSPDBGis6o9y/y50nTdZir88jWzMD9xRkqlJb+iF+dU80lGWjKB4uvBCytxAOv4/NUmI/QgcyLHCjNbUVCObmToC4CkdXHdfacBPwA2ta51P8kEgv4+k14jaRpuDGw94Mu4cb5ErlCmIiR2uS3DJsmMviybhLzkz5vmFTCzZuu+LrBfSNoON574i3S6b90/6j/G1lVkFdFZ1Z4P/HndCuUmpMr2h0X+PDonf0xG2kJ/viD1iznreLIPcgxX9rqaLDmKciJuosZVZnaDmVVqGfXlmUB+q3hUTvp0nEM6ycweM7P2CnJVYqE/T+nBJmsVqOchnKNeV9KW/ZSpKIkjeizD0SazUqfJTW2PRKKzKgGv4X65bx5OAQ/Yha5fy/3hCX+eLCnrl3zWr+tH/HlSVoWSNpF0SE59mZjZJ7gZcOAmdhSRoyiT/DkcX4Psrq7H/XmbMENSC10tx5Clvkzo5DbqjVyScrvf6LmbuJJddlKB8EW+K/cq//H4SuX7i3dAfw+cnuVgcc97KW6c9KCBlidSH0RnVWPMrBM3c62JnBeFpDHAMXStQ+nP/d7CDWiPBw4M7rM1XWFv0vwGeAv4oqSscZUrgG/ljIH1RNIld2QgRxPw1V7WlSYZ79oxqHc4XeM8aW7HtVKmZOh3dA/3SZxO6GwP741cuCnbeXwEIKnZn8+W9J8+72rceNdq3WXegf4eNy29CNNxk0/OlpT1jBKq0dI5GNf1el1Wpp/kkkyeieGXIkB0VmXhO7ip2hdK+q6kLSQNlzRW0hScc3kWuL5K9zsd9xKc6Qf8R0jaEffyWK014rurjsZ1Yd0laU9JoyVtLulK3Mv2632Q40e4lt45ko6TNFLSRGAmXa2uvtCGcz4nSDpB0jg/C/LnuPVW3fCtvFOBFuBmSZ+RtKakw4Az8Q4jgxtxLZ8LJW0maYKk75D/f3WJP/9U0h5+kfC+dLVqskhmNB4kaQLOMX3i5X4at85qb0ltkrbxz3A34A7gHeDSHupehW9dHYibDXqfpPMkbeW/G2O8vOfjfjCtxK3H6yvHATf4555H8kwOD2ZuRoYqtZ47Hw934Fo65+O6pD4GOnCz0B7CvTBHZFzTintZpo82nzc3I29S6tptcC2Kj3HjFQ/jfoW3pcq/ENxvMm5AfD5uIe+fffmtg3JZ927L0XstXLy4d3GTTf6EW6D7j/66Yyro202vVNmtcC3Wd7ysL+ACqt6Yum52cM1huK61Zf7Z3+rrSetzVXDNNF/3clyX7ll0rbNKjt1S5Y/CTSD4xD/7+4ApQfnWVPlkIfX7uLG13wITAxkOBu7BOejFwHPAvxGsGSv4PRTwd173t/2zW4JrFd4FfBvYPLhmRo5d2oJyk8IyOTK0Ff3+xGPoHDKr5szpSKQ6SJqOewnua2YP1licSCRSY2I3YKRmSNpI0qN+LCnkMGABXZMIIpHIECY6q0gtGY5btDrTj9Ot6cdJrvbpZ1r/p3dHIpEGIDqrSC2Zj5uYsTFusewnuEC5m+LiFs7q4dpIJDKEiGNWkUgkEik9sWUViUQikdITnVUkEolESk90VpFIJBIpPdFZRSKRSKT0RGcViUQikdITnVUkEolESs//A8uUya3GjJbTAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_model_contour(dnn_estimator, input_df=law_df)" ] }, { "cell_type": "markdown", "metadata": { "id": "OOAKK0_3vWir" }, "source": [ "### 训练无约束的梯度提升树 (GBT) 模型\n", "\n", "之前已对此树形结构进行了优化,可以实现较高的验证准确率。" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:36.508097Z", "iopub.status.busy": "2021-10-08T22:51:36.507181Z", "iopub.status.idle": "2021-10-08T22:51:41.619401Z", "shell.execute_reply": "2021-10-08T22:51:41.619823Z" }, "id": "mFaI9hB-rgoL" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "accuracies for GBT: train: 0.949312, val: 0.945876, test: 0.951117\n" ] } ], "source": [ "tree_estimator = tf.estimator.BoostedTreesClassifier(\n", " feature_columns=[\n", " tf.feature_column.numeric_column(feature) for feature in feature_names\n", " ],\n", " n_batches_per_layer=2,\n", " n_trees=20,\n", " max_depth=4)\n", "\n", "tree_estimator.train(\n", " input_fn=get_input_fn_law(\n", " law_train_df, num_epochs=NUM_EPOCHS, batch_size=BATCH_SIZE))\n", "tree_train_acc = tree_estimator.evaluate(\n", " input_fn=get_input_fn_law(law_train_df, num_epochs=1))['accuracy']\n", "tree_val_acc = tree_estimator.evaluate(\n", " input_fn=get_input_fn_law(law_val_df, num_epochs=1))['accuracy']\n", "tree_test_acc = tree_estimator.evaluate(\n", " input_fn=get_input_fn_law(law_test_df, num_epochs=1))['accuracy']\n", "print('accuracies for GBT: train: %f, val: %f, test: %f' %\n", " (tree_train_acc, tree_val_acc, tree_test_acc))" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:41.634546Z", "iopub.status.busy": "2021-10-08T22:51:41.629811Z", "iopub.status.idle": "2021-10-08T22:51:41.999016Z", "shell.execute_reply": "2021-10-08T22:51:41.999395Z" }, "id": "AZFyfQT1E_nR" }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_model_contour(tree_estimator, input_df=law_df)" ] }, { "cell_type": "markdown", "metadata": { "id": "uX2qiMlrY8aO" }, "source": [ "# 案例研究 2:信用违约\n", "\n", "我们将在本教程中考虑的第二个案例研究是预测个人的信用违约概率。我们将使用 UCI 存储库中的 Default of Credit Card Clients 数据集。这些数据收集自 30,000 名中国台湾信用卡用户,并包含一个二元标签,用于标识用户是否在时间窗口内拖欠了付款。特征包括婚姻状况、性别、教育程度以及在 2005 年 4-9 月的每个月中,用户拖欠现有账单的时间有多长。\n", "\n", "正如我们在第一个案例研究中所做的那样,我们再次阐明了使用单调性约束来避免*不公平的惩罚*:使用该模型来确定用户的信用评分时,在其他条件都相同的情况下,如果许多人因较早支付账单而受到惩罚,那么这对他们来说是不公平的。因此,我们应用了单调性约束,使模型不会惩罚提前付款。" ] }, { "cell_type": "markdown", "metadata": { "id": "tz5yduNuFinA" }, "source": [ "## 加载信用违约数据" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:42.004500Z", "iopub.status.busy": "2021-10-08T22:51:42.003897Z", "iopub.status.idle": "2021-10-08T22:51:42.885581Z", "shell.execute_reply": "2021-10-08T22:51:42.885085Z" }, "id": "KuylMNBCILwy" }, "outputs": [], "source": [ "# Load data file.\n", "credit_file_name = 'credit_default.csv'\n", "credit_file_path = os.path.join(DATA_DIR, credit_file_name)\n", "credit_df = pd.read_csv(credit_file_path, delimiter=',')" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:42.889771Z", "iopub.status.busy": "2021-10-08T22:51:42.889112Z", "iopub.status.idle": "2021-10-08T22:51:42.890936Z", "shell.execute_reply": "2021-10-08T22:51:42.891262Z" }, "id": "Hv_GQcEHIf9v" }, "outputs": [], "source": [ "# Define label column name.\n", "CREDIT_LABEL = 'default'" ] }, { "cell_type": "markdown", "metadata": { "id": "13oZWY0YIoy3" }, "source": [ "### 将数据划分为训练/验证/测试集" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:42.896231Z", "iopub.status.busy": "2021-10-08T22:51:42.895168Z", "iopub.status.idle": "2021-10-08T22:51:42.904233Z", "shell.execute_reply": "2021-10-08T22:51:42.904588Z" }, "id": "dty5tXJqIscz" }, "outputs": [], "source": [ "credit_train_df, credit_val_df, credit_test_df = split_dataset(credit_df)" ] }, { "cell_type": "markdown", "metadata": { "id": "_kAciWXHKGV7" }, "source": [ "### 可视化数据分布\n", "\n", "首先,我们可视化数据的分布。我们将为婚姻状况和还款状况不同的人绘制观察到的违约率的平均值和标准误差。还款状态表示一个人已偿还贷款的月数(截至 2005 年 4 月)。" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:42.914563Z", "iopub.status.busy": "2021-10-08T22:51:42.913870Z", "iopub.status.idle": "2021-10-08T22:51:42.916089Z", "shell.execute_reply": "2021-10-08T22:51:42.915667Z" }, "id": "8CxacQxnkHWE" }, "outputs": [], "source": [ "def get_agg_data(df, x_col, y_col, bins=11):\n", " xbins = pd.cut(df[x_col], bins=bins)\n", " data = df[[x_col, y_col]].groupby(xbins).agg(['mean', 'sem'])\n", " return data\n", "\n", "\n", "def plot_2d_means_credit(input_df, x_col, y_col, x_label, y_label):\n", " plt.rcParams['font.family'] = ['serif']\n", " _, ax = plt.subplots(nrows=1, ncols=1)\n", " plt.setp(ax.spines.values(), color='black', linewidth=1)\n", " ax.tick_params(\n", " direction='in', length=6, width=1, top=False, right=False, labelsize=18)\n", " df_single = get_agg_data(input_df[input_df['MARRIAGE'] == 1], x_col, y_col)\n", " df_married = get_agg_data(input_df[input_df['MARRIAGE'] == 2], x_col, y_col)\n", " ax.errorbar(\n", " df_single[(x_col, 'mean')],\n", " df_single[(y_col, 'mean')],\n", " xerr=df_single[(x_col, 'sem')],\n", " yerr=df_single[(y_col, 'sem')],\n", " color='orange',\n", " marker='s',\n", " capsize=3,\n", " capthick=1,\n", " label='Single',\n", " markersize=10,\n", " linestyle='')\n", " ax.errorbar(\n", " df_married[(x_col, 'mean')],\n", " df_married[(y_col, 'mean')],\n", " xerr=df_married[(x_col, 'sem')],\n", " yerr=df_married[(y_col, 'sem')],\n", " color='b',\n", " marker='^',\n", " capsize=3,\n", " capthick=1,\n", " label='Married',\n", " markersize=10,\n", " linestyle='')\n", " leg = ax.legend(loc='upper left', fontsize=18, frameon=True, numpoints=1)\n", " ax.set_xlabel(x_label, fontsize=18)\n", " ax.set_ylabel(y_label, fontsize=18)\n", " ax.set_ylim(0, 1.1)\n", " ax.set_xlim(-2, 8.5)\n", " ax.patch.set_facecolor('white')\n", " leg.get_frame().set_edgecolor('black')\n", " leg.get_frame().set_facecolor('white')\n", " leg.get_frame().set_linewidth(1)\n", " plt.show()" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:42.938468Z", "iopub.status.busy": "2021-10-08T22:51:42.937874Z", "iopub.status.idle": "2021-10-08T22:51:43.095615Z", "shell.execute_reply": "2021-10-08T22:51:43.095059Z" }, "id": "VHXyYbyekKLT" }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_2d_means_credit(credit_train_df, 'PAY_0', 'default',\n", " 'Repayment Status (April)', 'Observed default rate')" ] }, { "cell_type": "markdown", "metadata": { "id": "4hnZBigB7kzY" }, "source": [ "## 训练校准线性模型以预测信用违约率\n", "\n", "接下来,我们将通过 TFL 训练*校准线性模型*,以预测某人是否会拖欠贷款。两个输入特征将是该人的婚姻状况以及该人截至 4 月已偿还贷款的月数(还款状态)。训练标签将是该人是否拖欠过贷款。\n", "\n", "我们首先在没有任何约束的情况下训练校准线性模型。然后,我们在具有单调性约束的情况下训练校准线性模型,并观察模型输出和准确率的差异。" ] }, { "cell_type": "markdown", "metadata": { "id": "UEcHW1u3Jk_2" }, "source": [ "### 用于配置信用违约数据集特征的辅助函数\n", "\n", "下面这些辅助函数专用于信用违约案例研究。" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:43.102157Z", "iopub.status.busy": "2021-10-08T22:51:43.101605Z", "iopub.status.idle": "2021-10-08T22:51:43.103708Z", "shell.execute_reply": "2021-10-08T22:51:43.103241Z" }, "id": "QBa-hczLi7DM" }, "outputs": [], "source": [ "def get_input_fn_credit(input_df, num_epochs, batch_size=None):\n", " \"\"\"Gets TF input_fn for credit default models.\"\"\"\n", " return tf.compat.v1.estimator.inputs.pandas_input_fn(\n", " x=input_df[['MARRIAGE', 'PAY_0']],\n", " y=input_df['default'],\n", " num_epochs=num_epochs,\n", " batch_size=batch_size or len(input_df),\n", " shuffle=False)\n", "\n", "\n", "def get_feature_columns_and_configs_credit(monotonicity):\n", " \"\"\"Gets TFL feature configs for credit default models.\"\"\"\n", " feature_columns = [\n", " tf.feature_column.numeric_column('MARRIAGE'),\n", " tf.feature_column.numeric_column('PAY_0'),\n", " ]\n", " feature_configs = [\n", " tfl.configs.FeatureConfig(\n", " name='MARRIAGE',\n", " lattice_size=2,\n", " pwl_calibration_num_keypoints=3,\n", " monotonicity=monotonicity,\n", " pwl_calibration_always_monotonic=False),\n", " tfl.configs.FeatureConfig(\n", " name='PAY_0',\n", " lattice_size=2,\n", " pwl_calibration_num_keypoints=10,\n", " monotonicity=monotonicity,\n", " pwl_calibration_always_monotonic=False),\n", " ]\n", " return feature_columns, feature_configs" ] }, { "cell_type": "markdown", "metadata": { "id": "iwxnlRrQPdTg" }, "source": [ "### 用于可视化训练的模型输出的辅助函数" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:43.108387Z", "iopub.status.busy": "2021-10-08T22:51:43.107817Z", "iopub.status.idle": "2021-10-08T22:51:43.109957Z", "shell.execute_reply": "2021-10-08T22:51:43.109481Z" }, "id": "zVGxEfbhPZ5H" }, "outputs": [], "source": [ "def plot_predictions_credit(input_df,\n", " estimator,\n", " x_col,\n", " x_label='Repayment Status (April)',\n", " y_label='Predicted default probability'):\n", " predictions = get_predicted_probabilities(\n", " estimator=estimator, input_df=input_df, get_input_fn=get_input_fn_credit)\n", " new_df = input_df.copy()\n", " new_df.loc[:, 'predictions'] = predictions\n", " plot_2d_means_credit(new_df, x_col, 'predictions', x_label, y_label)" ] }, { "cell_type": "markdown", "metadata": { "id": "UMIpywE1P07H" }, "source": [ "## 训练无约束(非单调)的校准线性模型" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:51:43.115123Z", "iopub.status.busy": "2021-10-08T22:51:43.114578Z", "iopub.status.idle": "2021-10-08T22:53:07.256340Z", "shell.execute_reply": "2021-10-08T22:53:07.255835Z" }, "id": "FfXUKns5cPEw" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "accuracies for learning rate 0.010000: train: 0.818762, val: 0.830065, test: 0.817172\n" ] } ], "source": [ "nomon_linear_estimator = optimize_learning_rates(\n", " train_df=credit_train_df,\n", " val_df=credit_val_df,\n", " test_df=credit_test_df,\n", " monotonicity=0,\n", " learning_rates=LEARNING_RATES,\n", " batch_size=BATCH_SIZE,\n", " num_epochs=NUM_EPOCHS,\n", " get_input_fn=get_input_fn_credit,\n", " get_feature_columns_and_configs=get_feature_columns_and_configs_credit)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:53:07.261649Z", "iopub.status.busy": "2021-10-08T22:53:07.261054Z", "iopub.status.idle": "2021-10-08T22:53:07.747961Z", "shell.execute_reply": "2021-10-08T22:53:07.747421Z" }, "id": "5zQ_jm75kRX6" }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_predictions_credit(credit_train_df, nomon_linear_estimator, 'PAY_0')" ] }, { "cell_type": "markdown", "metadata": { "id": "0aokp7qLQBIr" }, "source": [ "## 训练单调的校准线性模型" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:53:07.754842Z", "iopub.status.busy": "2021-10-08T22:53:07.752884Z", "iopub.status.idle": "2021-10-08T22:54:36.539647Z", "shell.execute_reply": "2021-10-08T22:54:36.539149Z" }, "id": "wWCG7YrLUZDH" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "accuracies for learning rate 0.010000: train: 0.818762, val: 0.830065, test: 0.817172\n" ] } ], "source": [ "mon_linear_estimator = optimize_learning_rates(\n", " train_df=credit_train_df,\n", " val_df=credit_val_df,\n", " test_df=credit_test_df,\n", " monotonicity=1,\n", " learning_rates=LEARNING_RATES,\n", " batch_size=BATCH_SIZE,\n", " num_epochs=NUM_EPOCHS,\n", " get_input_fn=get_input_fn_credit,\n", " get_feature_columns_and_configs=get_feature_columns_and_configs_credit)" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "execution": { "iopub.execute_input": "2021-10-08T22:54:36.545521Z", "iopub.status.busy": "2021-10-08T22:54:36.544896Z", "iopub.status.idle": "2021-10-08T22:54:37.048227Z", "shell.execute_reply": "2021-10-08T22:54:37.047617Z" }, "id": "JCQ2eMdndFhR" }, "outputs": [ { "data": { "image/png": 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\n", 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