{
  "cells": [
    {
      "cell_type": "markdown",
      "id": "71c0b2d7",
      "metadata": {
        "id": "71c0b2d7"
      },
      "source": [
        "# Early Prediction of Gestational Diabetes Mellitus (GDM)\n",
        "### Comparative Evaluation of Logistic Regression, Random Forest and XGBoost\n",
        "\n",
        "**Student:** Md Mahadi Hasan\n",
        "**Dataset:** PIMA Indians Diabetes Database (Kaggle mirror of the UCI-donated dataset)\n",
        "**Dataset link:** https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "3fce3bcd",
      "metadata": {
        "id": "3fce3bcd"
      },
      "source": [
        "## 0. Setup\n",
        "\n",
        "Installing and importing the libraries used across the whole notebook, and fixing a random seed\n",
        "so results come out the same on every rerun (Chapter 3, Section 3.5).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "id": "0a2cae01",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0a2cae01",
        "outputId": "e27425ad-6849-4819-c260-84360d5f783b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: xgboost in /usr/local/lib/python3.13/dist-packages (3.4.1)\n",
            "Requirement already satisfied: shap in /usr/local/lib/python3.13/dist-packages (0.52.0)\n",
            "Requirement already satisfied: imbalanced-learn in /usr/local/lib/python3.13/dist-packages (0.14.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.13/dist-packages (from xgboost) (2.1.3)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.13/dist-packages (from xgboost) (1.16.3)\n",
            "Requirement already satisfied: nvidia-nccl-cu13 in /usr/local/lib/python3.13/dist-packages (from xgboost) (2.31.2)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.13/dist-packages (from shap) (1.6.1)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.13/dist-packages (from shap) (2.2.3)\n",
            "Requirement already satisfied: tqdm>=4.27.0 in /usr/local/lib/python3.13/dist-packages (from shap) (4.67.3)\n",
            "Requirement already satisfied: packaging>20.9 in /usr/local/lib/python3.13/dist-packages (from shap) (26.3)\n",
            "Requirement already satisfied: slicer==0.0.8 in /usr/local/lib/python3.13/dist-packages (from shap) (0.0.8)\n",
            "Requirement already satisfied: numba in /usr/local/lib/python3.13/dist-packages (from shap) (0.61.2)\n",
            "Requirement already satisfied: llvmlite in /usr/local/lib/python3.13/dist-packages (from shap) (0.44.0)\n",
            "Requirement already satisfied: cloudpickle in /usr/local/lib/python3.13/dist-packages (from shap) (3.1.2)\n",
            "Requirement already satisfied: sklearn-compat<0.2,>=0.1.6 in /usr/local/lib/python3.13/dist-packages (from imbalanced-learn) (0.1.6)\n",
            "Requirement already satisfied: joblib<2,>=1.2.0 in /usr/local/lib/python3.13/dist-packages (from imbalanced-learn) (1.5.3)\n",
            "Requirement already satisfied: threadpoolctl<4,>=2.0.0 in /usr/local/lib/python3.13/dist-packages (from imbalanced-learn) (3.6.0)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.13/dist-packages (from pandas->shap) (2.9.0.post0)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.13/dist-packages (from pandas->shap) (2025.2)\n",
            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.13/dist-packages (from pandas->shap) (2026.3)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.13/dist-packages (from python-dateutil>=2.8.2->pandas->shap) (1.17.0)\n"
          ]
        }
      ],
      "source": [
        "# xgboost, shap and imbalanced-learn usually aren't installed by default\n",
        "# scikit-learn, pandas, numpy, matplotlib, seaborn are assumed already installed in the venv\n",
        "%pip install xgboost shap imbalanced-learn\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "id": "75f7103c",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "75f7103c",
        "outputId": "320c5c9c-6666-4fbc-8d74-c38183c24657"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "done, random seed is 42\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "from sklearn.model_selection import train_test_split, StratifiedKFold, GridSearchCV, cross_val_score\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from xgboost import XGBClassifier\n",
        "import xgboost as xgb\n",
        "\n",
        "from imblearn.over_sampling import SMOTE\n",
        "from imblearn.pipeline import Pipeline as ImbPipeline\n",
        "\n",
        "from sklearn.metrics import (\n",
        "    accuracy_score, f1_score, roc_auc_score,\n",
        "    precision_score, recall_score, confusion_matrix, roc_curve\n",
        ")\n",
        "\n",
        "import shap\n",
        "import joblib\n",
        "import os\n",
        "\n",
        "# same seed everywhere, makes results reproducible across runs\n",
        "RANDOM_STATE = 42\n",
        "np.random.seed(RANDOM_STATE)\n",
        "\n",
        "sns.set_theme(style=\"whitegrid\")\n",
        "plt.rcParams[\"figure.figsize\"] = (8, 5)\n",
        "\n",
        "# folder to dump trained models + scaler into, used later by the realtime script\n",
        "os.makedirs(\"../models\", exist_ok=True)\n",
        "\n",
        "# every plot in this notebook gets saved here too, not just shown inline\n",
        "FIGURES_DIR = \"../outputs/figures\"\n",
        "os.makedirs(FIGURES_DIR, exist_ok=True)\n",
        "\n",
        "\n",
        "def save_fig(filename):\n",
        "    # call this right before plt.show(), saves whatever is the current figure\n",
        "    path = os.path.join(FIGURES_DIR, filename)\n",
        "    plt.savefig(path, dpi=150, bbox_inches=\"tight\")\n",
        "    print(\"saved figure to\", path)\n",
        "\n",
        "\n",
        "print(\"done, random seed is\", RANDOM_STATE)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "6ff118cd",
      "metadata": {
        "id": "6ff118cd"
      },
      "source": [
        "## 1. Data Acquisition\n",
        "\n",
        "Loading the PIMA Indians Diabetes dataset. Originally from NIDDK, donated to the UCI repo, but\n",
        "that listing was pulled by the donor at some point so this study uses the Kaggle mirror instead\n",
        "(kaggle.com/datasets/uciml/pima-indians-diabetes-database).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "id": "02ee8a72",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 223
        },
        "id": "02ee8a72",
        "outputId": "9630a73e-8d14-444d-b835-262c797f1480"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset loaded. Shape: (768, 9)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  \\\n",
              "0            6      148             72             35        0  33.6   \n",
              "1            1       85             66             29        0  26.6   \n",
              "2            8      183             64              0        0  23.3   \n",
              "3            1       89             66             23       94  28.1   \n",
              "4            0      137             40             35      168  43.1   \n",
              "\n",
              "   DiabetesPedigreeFunction  Age  Outcome  \n",
              "0                     0.627   50        1  \n",
              "1                     0.351   31        0  \n",
              "2                     0.672   32        1  \n",
              "3                     0.167   21        0  \n",
              "4                     2.288   33        1  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-247b8850-f809-4e6d-90f1-b6f2f728df24\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pregnancies</th>\n",
              "      <th>Glucose</th>\n",
              "      <th>BloodPressure</th>\n",
              "      <th>SkinThickness</th>\n",
              "      <th>Insulin</th>\n",
              "      <th>BMI</th>\n",
              "      <th>DiabetesPedigreeFunction</th>\n",
              "      <th>Age</th>\n",
              "      <th>Outcome</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>6</td>\n",
              "      <td>148</td>\n",
              "      <td>72</td>\n",
              "      <td>35</td>\n",
              "      <td>0</td>\n",
              "      <td>33.6</td>\n",
              "      <td>0.627</td>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>85</td>\n",
              "      <td>66</td>\n",
              "      <td>29</td>\n",
              "      <td>0</td>\n",
              "      <td>26.6</td>\n",
              "      <td>0.351</td>\n",
              "      <td>31</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8</td>\n",
              "      <td>183</td>\n",
              "      <td>64</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>23.3</td>\n",
              "      <td>0.672</td>\n",
              "      <td>32</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>89</td>\n",
              "      <td>66</td>\n",
              "      <td>23</td>\n",
              "      <td>94</td>\n",
              "      <td>28.1</td>\n",
              "      <td>0.167</td>\n",
              "      <td>21</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>137</td>\n",
              "      <td>40</td>\n",
              "      <td>35</td>\n",
              "      <td>168</td>\n",
              "      <td>43.1</td>\n",
              "      <td>2.288</td>\n",
              "      <td>33</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-247b8850-f809-4e6d-90f1-b6f2f728df24')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-247b8850-f809-4e6d-90f1-b6f2f728df24 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-247b8850-f809-4e6d-90f1-b6f2f728df24');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 768,\n  \"fields\": [\n    {\n      \"column\": \"Pregnancies\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 0,\n        \"max\": 17,\n        \"num_unique_values\": 17,\n        \"samples\": [\n          6,\n          1,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Glucose\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 31,\n        \"min\": 0,\n        \"max\": 199,\n        \"num_unique_values\": 136,\n        \"samples\": [\n          151,\n          101,\n          112\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BloodPressure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19,\n        \"min\": 0,\n        \"max\": 122,\n        \"num_unique_values\": 47,\n        \"samples\": [\n          86,\n          46,\n          85\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SkinThickness\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15,\n        \"min\": 0,\n        \"max\": 99,\n        \"num_unique_values\": 51,\n        \"samples\": [\n          7,\n          12,\n          48\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Insulin\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 115,\n        \"min\": 0,\n        \"max\": 846,\n        \"num_unique_values\": 186,\n        \"samples\": [\n          52,\n          41,\n          183\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BMI\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7.8841603203754405,\n        \"min\": 0.0,\n        \"max\": 67.1,\n        \"num_unique_values\": 248,\n        \"samples\": [\n          19.9,\n          31.0,\n          38.1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DiabetesPedigreeFunction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.33132859501277484,\n        \"min\": 0.078,\n        \"max\": 2.42,\n        \"num_unique_values\": 517,\n        \"samples\": [\n          1.731,\n          0.426,\n          0.138\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 11,\n        \"min\": 21,\n        \"max\": 81,\n        \"num_unique_values\": 52,\n        \"samples\": [\n          60,\n          47,\n          72\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Outcome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "# Load the dataset into a DataFrame\n",
        "df = pd.read_csv(\"diabetes.csv\")\n",
        "\n",
        "print(\"Dataset loaded. Shape:\", df.shape)\n",
        "df.head()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "9b63fec8",
      "metadata": {
        "id": "9b63fec8"
      },
      "source": [
        "## 2. Exploratory Data Analysis (EDA)\n",
        "\n",
        "Looking at the raw data before touching anything. Distributions, class balance, and how many\n",
        "zero values show up in columns where zero doesn't actually make sense medically (Chapter 3,\n",
        "Section 3.5, Step 2).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "id": "0b71798b",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0b71798b",
        "outputId": "5529adaa-3554-43db-e3fa-90ca0742d4c7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(768, 9)\n",
            "\n",
            "Pregnancies                   int64\n",
            "Glucose                       int64\n",
            "BloodPressure                 int64\n",
            "SkinThickness                 int64\n",
            "Insulin                       int64\n",
            "BMI                         float64\n",
            "DiabetesPedigreeFunction    float64\n",
            "Age                           int64\n",
            "Outcome                       int64\n",
            "dtype: object\n"
          ]
        }
      ],
      "source": [
        "print(df.shape)\n",
        "print()\n",
        "print(df.dtypes)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "id": "55491270",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "55491270",
        "outputId": "496d997a-ca2d-4314-accf-437fe76a15e2"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
              "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
              "mean      3.845052  120.894531      69.105469      20.536458   79.799479   \n",
              "std       3.369578   31.972618      19.355807      15.952218  115.244002   \n",
              "min       0.000000    0.000000       0.000000       0.000000    0.000000   \n",
              "25%       1.000000   99.000000      62.000000       0.000000    0.000000   \n",
              "50%       3.000000  117.000000      72.000000      23.000000   30.500000   \n",
              "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
              "max      17.000000  199.000000     122.000000      99.000000  846.000000   \n",
              "\n",
              "              BMI  DiabetesPedigreeFunction         Age     Outcome  \n",
              "count  768.000000                768.000000  768.000000  768.000000  \n",
              "mean    31.992578                  0.471876   33.240885    0.348958  \n",
              "std      7.884160                  0.331329   11.760232    0.476951  \n",
              "min      0.000000                  0.078000   21.000000    0.000000  \n",
              "25%     27.300000                  0.243750   24.000000    0.000000  \n",
              "50%     32.000000                  0.372500   29.000000    0.000000  \n",
              "75%     36.600000                  0.626250   41.000000    1.000000  \n",
              "max     67.100000                  2.420000   81.000000    1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a855191e-ea3f-4889-9a78-0c25baed4317\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pregnancies</th>\n",
              "      <th>Glucose</th>\n",
              "      <th>BloodPressure</th>\n",
              "      <th>SkinThickness</th>\n",
              "      <th>Insulin</th>\n",
              "      <th>BMI</th>\n",
              "      <th>DiabetesPedigreeFunction</th>\n",
              "      <th>Age</th>\n",
              "      <th>Outcome</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>3.845052</td>\n",
              "      <td>120.894531</td>\n",
              "      <td>69.105469</td>\n",
              "      <td>20.536458</td>\n",
              "      <td>79.799479</td>\n",
              "      <td>31.992578</td>\n",
              "      <td>0.471876</td>\n",
              "      <td>33.240885</td>\n",
              "      <td>0.348958</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>3.369578</td>\n",
              "      <td>31.972618</td>\n",
              "      <td>19.355807</td>\n",
              "      <td>15.952218</td>\n",
              "      <td>115.244002</td>\n",
              "      <td>7.884160</td>\n",
              "      <td>0.331329</td>\n",
              "      <td>11.760232</td>\n",
              "      <td>0.476951</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.078000</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>99.000000</td>\n",
              "      <td>62.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>27.300000</td>\n",
              "      <td>0.243750</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>117.000000</td>\n",
              "      <td>72.000000</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>30.500000</td>\n",
              "      <td>32.000000</td>\n",
              "      <td>0.372500</td>\n",
              "      <td>29.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>6.000000</td>\n",
              "      <td>140.250000</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>32.000000</td>\n",
              "      <td>127.250000</td>\n",
              "      <td>36.600000</td>\n",
              "      <td>0.626250</td>\n",
              "      <td>41.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>17.000000</td>\n",
              "      <td>199.000000</td>\n",
              "      <td>122.000000</td>\n",
              "      <td>99.000000</td>\n",
              "      <td>846.000000</td>\n",
              "      <td>67.100000</td>\n",
              "      <td>2.420000</td>\n",
              "      <td>81.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a855191e-ea3f-4889-9a78-0c25baed4317')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-a855191e-ea3f-4889-9a78-0c25baed4317 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-a855191e-ea3f-4889-9a78-0c25baed4317');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"Pregnancies\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 269.85223453356366,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          3.8450520833333335,\n          3.0,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Glucose\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 243.73802348295857,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          120.89453125,\n          117.0,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BloodPressure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 252.85250535810619,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          69.10546875,\n          72.0,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SkinThickness\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 263.7684730531098,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          768.0,\n          20.536458333333332,\n          32.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Insulin\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 350.26059167945886,\n        \"min\": 0.0,\n        \"max\": 846.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          768.0,\n          79.79947916666667,\n          127.25\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BMI\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 262.05117817552093,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          31.992578124999998,\n          32.0,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DiabetesPedigreeFunction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.3005221658502,\n        \"min\": 0.078,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.47187630208333325,\n          0.3725,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 260.1941178528413,\n        \"min\": 11.76023154067868,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          33.240885416666664,\n          29.0,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Outcome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.3865920388932,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.3489583333333333,\n          1.0,\n          0.4769513772427971\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "# quick stats overview\n",
        "df.describe()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "id": "1f93af33",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 662
        },
        "id": "1f93af33",
        "outputId": "55dcf992-ab28-408e-cddf-ca05c72d57b8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Outcome\n",
            "0    500\n",
            "1    268\n",
            "Name: count, dtype: int64\n",
            "Outcome\n",
            "0    65.1\n",
            "1    34.9\n",
            "Name: proportion, dtype: float64\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/tmp/ipykernel_3047/3305880999.py:8: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  sns.countplot(x=\"Outcome\", data=df, palette=[\"#6c8ebf\", \"#b85450\"])\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/class_balance.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Outcome: 0 = no diabetes, 1 = diabetes\n",
        "counts = df[\"Outcome\"].value_counts()\n",
        "pct = df[\"Outcome\"].value_counts(normalize=True) * 100\n",
        "print(counts)\n",
        "print(pct.round(1))\n",
        "\n",
        "plt.figure(figsize=(5, 4))\n",
        "sns.countplot(x=\"Outcome\", data=df, palette=[\"#6c8ebf\", \"#b85450\"])\n",
        "plt.title(\"Class balance\")\n",
        "plt.xlabel(\"Outcome (0 = no diabetes, 1 = diabetes)\")\n",
        "save_fig(\"class_balance.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "id": "8b5aca6c",
      "metadata": {
        "id": "8b5aca6c",
        "outputId": "10c02589-1baf-4e0d-d8ab-16e179b26840",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "               zeros   pct\n",
            "Glucose            5   0.7\n",
            "BloodPressure     35   4.6\n",
            "SkinThickness    227  29.6\n",
            "Insulin          374  48.7\n",
            "BMI               11   1.4\n",
            "saved figure to ../outputs/figures/zero_value_counts.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# these columns physically can't be zero in a real patient, so zero here just means missing\n",
        "zero_cols = [\"Glucose\", \"BloodPressure\", \"SkinThickness\", \"Insulin\", \"BMI\"]\n",
        "\n",
        "zero_counts = (df[zero_cols] == 0).sum()\n",
        "zero_pct = ((df[zero_cols] == 0).sum() / len(df) * 100).round(1)\n",
        "\n",
        "print(pd.DataFrame({\"zeros\": zero_counts, \"pct\": zero_pct}))\n",
        "\n",
        "plt.figure(figsize=(7, 4))\n",
        "sns.barplot(x=zero_counts.index, y=zero_counts.values, color=\"#d79b00\")\n",
        "plt.title(\"Zero-value counts before cleaning\")\n",
        "plt.xticks(rotation=30)\n",
        "save_fig(\"zero_value_counts.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "id": "2fb13856",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 718
        },
        "id": "2fb13856",
        "outputId": "ef8f6b54-0e08-4d02-d043-dee47c61f850"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/correlation_heatmap.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x700 with 2 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvIAAAKsCAYAAACOH1nLAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3XdUVMfbwPEvS5PeBOkCIoiCoKiIvcYaNSaxxN5i7FETo0k0GpPYkmjsPdh77y32FrtgoYhdkN47u+8fC6vrLm3VqL93Pud4EubO3PvscHeZnfvcuVoymUyGIAiCIAiCIAgfFMm7DkAQBEEQBEEQhLITA3lBEARBEARB+ACJgbwgCIIgCIIgfIDEQF4QBEEQBEEQPkBiIC8IgiAIgiAIHyAxkBcEQRAEQRCED5AYyAuCIAiCIAjCB0gM5AVBEARBEAThAyQG8oIgCIIgCILwARIDeUEQhPfE9u3b8fT05MmTJ29sn0+ePMHT05Pt27e/sX2WVq9evWjfvv1/flzh3fP09GTevHnvOgxB+J+n864DEARBeJsePXrE8uXLOXv2LDExMejq6uLh4UGbNm3o2rUr5cqVe9chvhF79uwhPj6evn37vutQ3gvr1q3DwMCAzp07v+tQhDKIiIjgwIEDfPLJJzg6Or7rcAThvScG8oIg/M86ceIEo0aNQk9Pj44dO+Lh4UFubi5Xrlxh1qxZREREMHXq1Hcd5huxd+9ewsPDVQbyDg4O3Lx5Ex2d/18f9xs2bMDCwkIM5D8wERERzJ8/nzp16oiBvCCUwv+vT3ZBEP7fePz4MaNHj8be3p5Vq1ZhY2Oj2NajRw8ePnzIiRMnXvs4MpmM7OxstTP72dnZ6OrqIpG8uyxGLS0t9PX139nxhberuPNPEIT/fSJHXhCE/0nLly8nIyODX3/9VWkQX6hixYr06dNH8XNeXh4LFiygRYsWeHt706xZM/78809ycnKU2jVr1ozBgwdz+vRpOnfuTPXq1dm4cSMXL17E09OTffv2MXv2bBo2bIivry9paWkA3LhxgwEDBuDv74+vry89e/bkypUrJb6Oo0eP8uWXX9KgQQO8vb1p0aIFCxYsID8/X1GnV69enDhxgqdPn+Lp6YmnpyfNmjUDis6RP3/+PF988QV+fn7UqlWLIUOGcO/ePaU68+bNw9PTk4cPHzJ+/Hhq1aqFv78/EyZMIDMzs8TYC0VERNCrVy98fX1p2LAhy5YtU6mTk5PD3LlzadmyJd7e3jRu3JiZM2eq9P+2bdvo3bs3gYGBeHt707ZtW9avX69Up1mzZoSHh/Pvv/8q+qNXr17Ai/sQLl++zC+//ELdunWpVasWkyZNIicnh5SUFMaNG0ft2rWpXbs2M2fORCaTKe1/xYoVdOvWjYCAAKpXr07nzp05ePCgymvy9PTk559/Zvfu3bRq1QofHx86d+7MpUuXSt13ryrq/Ctt30ybNo2AgACl1zR16lQ8PT1ZvXq1oiwuLg5PT0+V9q/Kycnht99+o27dutSoUYOvvvqK6OholXpPnz5l8uTJtGrViurVqxMQEMDIkSOV7gfZvn07o0aNAqB3796K393FixeB0r0XBOH/GzEjLwjC/6Tjx4/j5OREzZo1S1X/xx9/ZMeOHbRq1Yp+/fpx8+ZNlixZwr1791iwYIFS3fv37zN27Fi6du1Kly5dcHV1VWxbuHAhurq6DBgwgJycHHR1dTl//jyDBg3C29ub4cOHo6Wlxfbt2+nTpw/r16+nevXqRca1Y8cODA0N6devH4aGhly4cIG5c+eSlpbGd999B8BXX31Famoq0dHRTJgwAQAjI6Mi93nu3DkGDRqEo6Mjw4cPJysri7Vr19K9e3e2b9+uktLw9ddf4+joyJgxY7h9+zZbtmzB0tKSb7/9tsR+TU5OZuDAgbRs2ZI2bdpw6NAhfv/9dzw8PGjcuDEAUqmUIUOGcOXKFbp06UKlSpUICwtj1apVPHjwgIULFyr2t2HDBipXrkyzZs3Q0dHh+PHjTJkyBZlMRo8ePQD4/vvvmTp1KoaGhnz11VcAlC9fXimuX375hfLlyzNixAhu3LjBpk2bMDEx4dq1a9jZ2TF69GhOnTrFihUr8PDwoFOnToq2q1evplmzZnz88cfk5uayb98+Ro0axZIlS2jSpInScS5dusT+/fvp1asXenp6bNiwgYEDB7JlyxY8PDxK7D91ijr/StM3tWrVIigoiPDwcMXxL1++jEQi4fLly/Tu3VtRBlC7du1iY/nhhx/YvXs37du3p2bNmly4cIEvv/xSpV5wcDDXrl2jXbt22Nra8vTpUzZs2EDv3r3Zt28fBgYG1K5dm169erFmzRq++uor3NzcAKhUqRJQuveCIPy/IxMEQfgfk5qaKvPw8JANGTKkVPXv3Lkj8/DwkP3www9K5dOnT5d5eHjIzp8/ryhr2rSpzMPDQ3bq1CmluhcuXJB5eHjImjdvLsvMzFSUS6VS2UcffSTr37+/TCqVKsozMzNlzZo1k/Xr109Rtm3bNpmHh4fs8ePHSvVeNXHiRJmvr68sOztbUfbll1/KmjZtqlL38ePHMg8PD9m2bdsUZR07dpQFBgbKEhMTlfqgSpUqsnHjxinK5s6dK/Pw8JBNmDBBaZ/Dhg2T1alTR+VYr+rZs6fMw8NDtmPHDkVZdna2rH79+rIRI0Yoynbu3CmrUqWK7NKlS0rtN2zYIPPw8JBduXJFUaauP/r37y9r3ry5Ulm7du1kPXv2VKlb2Mev/j66du0q8/T0lE2aNElRlpeXJ2vUqJHKfl6NIScnR9a+fXtZ7969lco9PDxkHh4esuDgYEXZ06dPZT4+PrJhw4apxFYaRZ1/6uKSyVT7Jj4+Xubh4SFbt26dTCaTyVJSUmRVqlSRjRw5UlavXj1FvalTp8rq1Kmj1EevKnzfTJ48Wal8zJgxMg8PD9ncuXOLje3atWsq58eBAwdkHh4esgsXLpTq9al7LwjC/ycitUYQhP85heksxc1Kv+zkyZMA9OvXT6m8f//+StsLOTo60rBhQ7X76tSpk1K+8p07d3jw4AEff/wxiYmJJCQkkJCQQEZGBoGBgVy6dAmpVFpkbC/vKy0tjYSEBGrVqkVmZiaRkZGlen0vi4mJ4c6dO3zyySeYm5sryqtUqUK9evVUXitAt27dlH6uVasWSUlJin4ujqGhIR07dlT8rKenh4+PD48fP1aUHTx4kEqVKuHm5qbon4SEBOrWrQugSK0A5f5ITU0lISGBOnXq8PjxY1JTU0vugAKfffYZWlpaip+rV6+OTCbjs88+U5Rpa2vj7e2tFOurMSQnJ5Oamoq/vz+3b99WOU6NGjXw9vZW/Gxvb0/z5s05c+aMxikhRZ1/pekbS0tL3NzcFDPuV69eRVtbmwEDBhAXF8eDBw8AuHLlCjVr1lTqo1cVniuFaUuFXk5ZUxdbbm4uiYmJODs7Y2pqqrbf1HnT7wVB+F8gUmsEQfifY2xsDEB6enqp6j99+hSJRIKzs7NSubW1Naampjx9+lSpvLjVNF7dVjgwKu7Sf2pqKmZmZmq3hYeHM2fOHC5cuKAycC7LwLXQs2fPAJTSgQpVqlSJM2fOkJGRgaGhoaLc3t5eqZ6pqSkgH8QW9nVRbG1tVQaDZmZmhIaGKn5++PAh9+7dIzAwUO0+4uPjFf9/5coV5s2bx/Xr11Xy9FNTUzExMSk2nkKvvqbCdnZ2dirlycnJSmXHjx9n0aJF3LlzRymHX92gt2LFiiplLi4uZGZmkpCQgLW1danifVlR519p+6ZWrVqKQfjly5fx9vbGx8cHc3NzLl++TPny5bl7926JzwAo6n1TmBLzsqysLJYsWcL27dt5/vy5Uo5+ac/jN/1eEIT/BWIgLwjC/xxjY2NsbGwIDw8vU7viZh9fVtwKIa9uKxywjBs3Di8vL7VtXh40vywlJYWePXtibGzMyJEjcXZ2Rl9fn1u3bvH7778XO5P/JhW16o7slZtA1dHW1i6xjlQqxcPDQ5Hf/ypbW1tA/kyAvn374ubmxvjx47Gzs0NXV5eTJ08SFBRUpv4o6jWVtMLQ5cuXGTJkCLVr1+ann37C2toaXV1dtm3bxt69e0t9/Neh7vwrS9/4+/uzefNmHj9+zOXLl/H390dLS4uaNWty5coVbGxskEql1KpV643FPHXqVMV9IX5+fpiYmKClpcXo0aNLdR69L+8FQXjfiIG8IAj/k5o2bcqmTZu4du0aNWrUKLaug4MDUqmUhw8fKm6sA/nKHSkpKTg4OGgch5OTEyD/clGvXr0ytf33339JSkpi/vz5Sjcdqnvya2m/hBTORN+/f19lW2RkJBYWFkV+sXhbnJ2duXv3LoGBgcW+jn/++YecnBwWLVqkNKP+cupNodL2R1kdOnQIfX19VqxYgZ6enqJ827Ztaus/fPhQpezBgwcYGBhgaWn5xuIqS9/4+/sDcPbsWYKDgxU3p9auXZsNGzZgY2ODoaEh1apVK/aYhe+bR48eKc3Cq0tzOXToEJ06dWL8+PGKsuzsbJWZ9KJ+b2V5LwjC/yciR14QhP9JAwcOxNDQkB9//JG4uDiV7Y8ePWLVqlUAitVTCn8u9Pfffytt14S3tzfOzs6sXLlSbapPQkJCkW0LZ4dfnrHMyclRuySggYFBqdILbGxs8PLyYufOnaSkpCjKw8LCOHv27Gu9Vk21adOG58+fs3nzZpVtWVlZZGRkAC9m919Ny1A3iDYwMFB6fW+KtrY2WlpaSvntT5484dixY2rrX7t2jVu3bil+joqK4tixY9SvX79UVyvKEheUrm+cnJyoUKECQUFB5OXlKVZ2qlWrFo8ePeLgwYP4+vqW+BCxRo0aAbBmzRql8lffRy/H97I1a9ao3CdgYGCgiP1lZXkvCML/J2JGXhCE/0nOzs78/vvvjB49mrZt2yqe7JqTk8O1a9c4ePCg4qmfVapU4ZNPPmHTpk2kpKRQu3ZtgoOD2bFjBy1atFDcdKkJiUTCL7/8wqBBg2jfvj2dO3emQoUKPH/+nIsXL2JsbMzixYvVtq1RowZmZmaMHz+eXr16oaWlxa5du9SmIlSrVo39+/czbdo0fHx8MDQ0VKwl/6px48YxaNAgunbtymeffaZYftLExIThw4dr/Fo11bFjRw4cOMBPP/3ExYsXqVmzJvn5+URGRnLw4EGWL1+Oj48P9evXR1dXl6+++opu3bqRnp7Oli1bsLKyIjY2Vmmf1apVY8OGDSxcuJCKFStiaWlZZA5+WTRu3Ji///6bgQMH0r59e+Lj41m/fj3Ozs5Kef+FPDw8GDBggNLykwAjRoxQqufp6UmdOnVUBsWlVZa+Afmgfd++fXh4eCjuz6hatSqGhoaKm7NL4uXlRfv27Vm/fj2pqanUqFGDCxcuqL0K0aRJE3bt2oWxsTHu7u5cv36dc+fOKd1wXbhPbW1tli1bRmpqKnp6eoo16kv7XhCE/0/EQF4QhP9ZzZs3Z/fu3axYsYJjx46xYcMG9PT08PT0ZPz48XTp0kVR95dffsHR0ZEdO3Zw9OhRypcvz+DBg9/IwDYgIIBNmzaxcOFC1q5dS0ZGBtbW1lSvXp2uXbsW2c7CwoLFixczY8YM5syZg6mpKR06dCAwMJABAwYo1f3iiy+4c+cO27dvJygoCAcHhyIH8vXq1WP58uXMnTuXuXPnoqOjQ+3atfn2228VqUD/JYlEwoIFCwgKCmLXrl0cOXIEAwMDHB0d6dWrl+LGXDc3N+bOncucOXOYMWMG5cuXp3v37lhaWvL9998r7XPYsGE8e/aM5cuXk56eTp06dd7IQD4wMJBff/2VZcuW8dtvv+Ho6Mg333zD06dP1Q7ka9eujZ+fHwsWLODZs2e4u7szbdo0qlSpoqhTeKVGkxtfC5Wlb0CeXrNv3z5Fmg2Ajo4Ofn5+nDt3Tqm8OL/99hsWFhbs2bOHY8eOERAQwNKlS1Wu7Pzwww9IJBL27NlDdnY2NWvWVHwhepm1tTVTpkxhyZIl/PDDD+Tn57N69WoCAgJK/V4QhP9PtGTi66wgCIIgvHGenp706NGDSZMmFVvv5MmTDB48mF27duHp6fkfRScIwv8CkSMvCIIgCO/QhQsXaNeunRjEC4JQZiK1RhAEQRDeoeKeMSAIwvvr4cOHrFixghs3bhAeHo6bm1uplqGVyWQsW7aM9evXk5CQgJeXFxMmTMDPz6/MMYgZeUEQBEEQBEEoo/DwcE6ePEnFihWVli4uybJly5g7dy59+/ZlyZIlWFtb079/f5WnSJeGyJEXBEEQBEEQhDKSSqWKpVHHjx9PSEhIiTPy2dnZ1KtXjx49ejBmzBhAvpRq69atadSoEZMnTy5TDGJGXhAEQRAEQRDKqKQnQatz9epV0tLSaNOmjaJMT0+Pli1bcurUqbLHUOYWgiAIgiAIgiCUWeGTj19+GjJApUqVePbsGVlZWWXan7jZVRAEQRAEQfh/q3nz5sVuL+rJzZpISUlBT08PfX19pXJTU1NkMhnJycmUK1eu1PsTA3lBEARBEAThvbdP9y0t0drI8e3s9z8gBvKC8A69tQ+l/0C73FDiQ8696zA0YuVdj4TgM+86DI1Z+jQgOOL5uw5DYz7uFQiJiH7XYWjE292WBxFh7zoMjbm4exB6r+wrY7wPPCs5kfrX2HcdhsZMRv1B2sU97zoMjRkHfPyuQ3hr3uSMe0lMTU3JyckhOztbaVY+JSUFLS0tzMzMyrQ/kSMvCIIgCIIgCP+Bwtz4+/fvK5VHRkZib29fprQaEAN5QRAEQRAEQfhP1KxZE2NjYw4cOKAoy83N5fDhwzRq1KjM+xOpNYIgCIIgCMJ7T0tX612HoCQzM5OTJ08C8PTpU9LS0jh48CAAderUwdLSkj59+vDs2TOOHDkCgL6+PoMHD2bevHlYWlri4eHBhg0bSEpKYsCAAWWOQQzkBUEQBEEQBKGM4uPjGTVqlFJZ4c+rV68mICAAqVRKfn6+Up1BgwYhk8lYuXIlCQkJeHl5sWLFCpycnMocgxjIC4IgCIIgCEIZOTo6EhoaWmydNWvWqJRpaWkxePBgBg8e/NoxiIG8IAiCIAiC8N6T6LxfqTXvA3GzqyAIgiAIgiB8gMRAXhAEQRAEQRA+QCK1RhAEQRAEQXjvaemK+edXiR4RBEEQBEEQhA+QGMgLgiAIgiAIwgdIDOQFQRAEQRAE4QMkcuQFQRAEQRCE955YflKVGMgLgiAIgiAI7z0tXTGQf5UYyAvCe0jbyBC3sQMwr+OLeW0f9CzNuTFgPE9W7yhVex0zE7ymf0uFji3RNixH8qVgbo+bTsq12yp1bdo3w2PScIy93MmJiefxqu1E/LoQ2SuPlC6LnNxclm3cwaGT50lJT8e9ohNfdu9MHd9qxbZ7+DSKnYdPcCv8HmGRD8nJzWPbolnY2ZRXqfvX3xu4dusuUbHx5OTkYmttRfP6dfiiQ2sMDcppHPuL+Hdy8NR5UtIzcHd2ZHD3T0oRfzQ7Dp/gVngkYffl8W9fOENt/C97Eh1Dj9ETycnNY+X0iXi5u7xW/IXS01JZs3Ix/54/RXZ2Nu4eXvQZOBQ3d89StX/y6AFBy+Zz93YwOjo61KwdSJ9BwzEzM1eql5gQx6a1f3Pz+iWSEhOwsCxP7boN+LRrL0xMzV4r/tUrF/Pv+dMF8Veh78BhuLl7lDr+v5cteCn+uvR9Jf5N6/5m8/qgIvfx66z5VKnqU+qYc3JzWb1mHceOHyctLQ1XFxf69O6Jf40aJbaNi4tn8bJlXL12HZlUSvXq1flq0EDs7GwVdWJiYzl85CgXL13i2dNnSLQluFSsSPeuXalZw6/UcZYkLS2NoJVLuXDuLNnZ2Xh4etJ/4FdUcq9cqvaPHz1k+bJF3LkVgo6OLrVqBzDgy6+U+j4+Po6glcuICAslISEeiUSCvYMjbdt3pFnzlmhplXHQpq2NXt3W6FbxR6ucIdK4Z2SfP0j+o7Bim+kFfIR+3VYq5bK8XNIWjC/6cPauGH4+HIC0JZOQZaWXLd6X5OTmsXj7QfadvUpqegbuTnYM/awNdb2LP9f/uRTM4YvXuX3/MXHJqdhamtPAz4tBHVtiYmSgqJeUms7uU/9y6vpt7j+LIS8/Hxc7G3q0asRHdf00jlt498RA/n/UvHnzmD9/vuJnCwsLPDw8GDlyJLVq1XqHkb1bFy9epHfv3mzduhUfn9L/cf6v6ZW3wGPicDIePiX1ZihWTQJK31hLi9q7l2Ja3ZPIP1aQE59IxcFfUPfoGs4EdCYj4qGiqnWrRtTatoD4k/9y6+upmHh7UPn7IejbWBEyfLLG8f8ybwXHL1yma7uWONpVYP+JM4z9dTbzp4zD16voP0whoffYsv8ILo72VHS0J/z+oyLr3om4j6+XB+2aVUBPV5ew+w9Zu2Mfl2/eZuHU8Ugkmt8C9Mv8lfxz4Qpd27XAya4C+46fZcxvf7Fg8rf4ehU9kAkJi2DLgaPy+B3sCH/wuFTH+ytoI9ra2pCbp3HMr5JKpfw2+Tse3r9Hh0+7YWJqxqF9O/lp/Chm/rUMOwenYtvHx8Uw6bsRGBoZ073PILIyM9mzfSOPHkQybfYSdHV1AcjMzOD7sUPJzsqkVbtPsLK24WFkBAf3bifk5jVm/rVMo9+FVCrl18njeXj/Hh0L4j+4byeTCuK3d3AsMf6J343E0MiYL/oMJCszk93bN/HowX2mz16siD+gXiNs7RxU2q9fvYyszEwqVa5Sprj/+HMOp8+e5ZOOHXCwt+fw0WNM/GkKM6f9ine1or8IZmZmMm7C96RnZNCty+foaGuzfdcuvhk/gUXz/sLU1BSA8xcusnnrVgLr1qVl8+bk5+dz9Ng/TPhxImO+HkWrli3KFK86UqmUn3/6gQf37/HJp10wNTVj/77dfP/dWGbPXVhi38fFxTJh3BgMjYzo1WcAmVmZ7Ny2hYcP7/P77PmKvk9JSSE+LpZ6DRphbW1DXn4e169d4a8/Z/L0yWN69x1QprjLteyOjnt1cq+fQpoUh65XbQw6DCRz+yLyn90vsX3WP1uR5WS/KJDJiqmthX7jT5DlZKOlp1+mONWZvGwjRy/d5IuPGuJsa82e05cY+cdylowfQg1P1yLb/fL3FqwtzGhTrya2VhZEPIli89GznL1xl3VTR1NOT97XNyMesmDrQer7VmFAhxboaEs4dukmExauJfLZc77qrPpFRvgwiIH8/7By5cqxatUqAKKjo1m4cCF9+/Zl+/bteHiUbkbrf021atXYtGkTlSpVetehFCs7KoajjvXJfh6Hmb83DS5sK3Vbu09bY1mvJle6jiR6+yEAorYcoMntQ3hMGsH13t8o6nrNGEdKcCj/tumvmIHPS0nHffxg7s9bTXpoZJljvx0eydGzFxneuwtfdGwDQJsm9ek5+kcWrNnM0t9+LLJtw9p+NAlcgJGBAet3HSh2IL/41+9VyhxsbZi/ahO3I+7j7aHZ7/hWeCRHzv7L8F6f06Nja3n8jevRY8wk5q/ZwrLfVI9bqEEtPw6vmoeRgQHrdh0s1UD+wvUQLl6/RY+OrQnatlejmNXu9+wJQu+EMHbCzwQ2aAJAvYbNGDnoCzat+5uvx00qtv32TWvJys5ixl/LsbapAEBlDy9+/nEMJ44eoGWbDgBcvniW2JhoJvw0A/86gYr2xiambNkQxIP7EbhVKvvnzfmC+L+ZMOWl+JsyYlAPNq1byegS4t9WEP/Mv5Yp4nf38OLnH8dy/OgBPiqI38W1Ei6uyudKXGwM8XGxNP+onWLQWRp3Q8M4ceoUA/v34/NPOwPQonkzvhw6nOUrg5jzx6wi2+7Zt5+nz54xd/YfeBZ8Pteq5c/gocPZumMn/fv0BsC3ug9r/l6JmdmLKx3t2rZh6PCRrF677o0M5M+dOcXdO7f47vtJ1G/QCIAGjRrz1aC+rF+7im+++6HY9ls2rScrO4vZcxcq+t7Dw5NJP3zHsaOHaN2mPQCurm78NuNPpbbtP+7E1Mk/snf3Dnr06iv/glsKkgpO6HrWIOv0HnKvngAg985ljHp+i3799mRsmVfiPvLCb5Z6Vl3Xpy5aJubk3rqIXo1GpWpTlJB7jzh04TqjurWnd9smALSr70+X739n7qa9/D1pRJFtZ47oTS0vd6UyLxdHflq6kQPnrvJJwSRQJccK7Jz1HXblLRX1Pm9ejyEzlrBq33H6tGuCgf7rfyER/nti1Zr/YRKJBD8/P/z8/GjdujWLFy8mLy+PjRs3qtSVyWTk5OS8gyj/W8bGxvj5+WFoaPiuQymWNCeX7OdxGrW17dyKrOhYonccVpTlxCXybOsBKnRojqRghsbYqxIm1SrzePlmpTSah4vXoyWRYKfhDM3x85fRlkjo2LKJokxfT5ePmzckJPQez+Pii2xramKMkYFBkdtLYmctT2FJS8/QeB/HL1xBWyKhU8vGijJ9PV0+btaAkLB7PI9LKLKtWRnjz8vLY/bKDXRp1wJHW2uNY1bn/JmTmJtbElDvxSDDzMyceg2bcunCGXJzi3+/Xzh3Ev/a9RQDMYDqNWph7+DEudPHFWUZGfK+NrOwUGpvbmkFgL6Gs5XFx3+2FPGfwr92oFL8vor4TxTb9szJo8hkMho1bVmmmM+cPYtEIqFtm9aKMj09PVp/1JI7d+8SExtbZNvTZ8/i4VFZMYgHcHZyooafL6dOn1GUuVSsqDSIB9DT1aV27VrExcUpfh+v4+yZU5hbWBBYr4GizMzMnAYNG3PxwvkS+/7c2dPUrh2g1Pd+NfxxcHDk7OmTJR7fpkIFsrOzycsr/RUqXXdfZNJ8ckPOvyjMzyP31kW07V3QMjYveSdaQGnOV30D9ALbkHPhILLszFLHWJRjl26iLZHQuWndF4fQ06Vj4zrcjHhIdHxSkW1fHcQDNPX3BuD+s+eKMgdrK6VBPICWlhZNanqTk5vHk5iiP9feJxIdrbfy70MmBvL/j9jb22NpacmTJ08YP3487du35+TJk3To0AEfHx/++ecfAK5du0bv3r3x8/PD39+fsWPHEh+vPPiKjo5m8ODB+Pr60rhxY4KCgvj1119p1qyZos727dvx9PTk9u3bDBw4ED8/Pz766CN27typtK8TJ07Qr18/AgMDqVmzJp9//jmnTp1SqlPafRXur1u3bvj6+lK7dm169erF7dvy3PCLFy/i6elJcHCwor5MJmPFihW0atUKb29vmjdvTlBQkMrrHTVqFPXq1cPHx4dmzZrx22+/lfVX8J8w8/OS58K/clk4+VIwOkaGGHnIL9Oa+lUFIOlKsFK97KgYMh9HYernpdHxw+4/xMneFiND5QFtVXc3AMLvly7dpDTy8vNJSkklNiGRi9dDWLphO4YG5ajqXvSl6JKE3X+Ek30FNfHL9xn2oOirBGW1cd9RUtMz6Pdp+ze2z0L3I8Nwda+sktbi7uFFdnYWz54W/XuIj4slOSmRSpVVc+ndPby4Hxmu+Lmqty8SiYS/l8wl7O4t4uNiuHrpPNs3raZOYEMcnCpqGH/4a8fvrjb+Kkrxq3PqxFHKW9tQ1du3TDFH3IvE0cEBo1cmCgoH55GR6tM7pFIp9+8/wMNddVDm6eFBVFRUiQP0xMRE9PX10X8Ds6qRkfeoVEm17yt7VCE7O4unT54U2TY+Lo7kpCS1fV/ZowqR9yJUyrOzs0lJTub582iOHT3MsSOH8KxStUyvRWLjgDQxFl5OjQHyn8vPE4m1fYn7MOr7PSZDfsN4yG+Ua/UFWobGauvpB7ZBlp5CbvB5tdvLKvThU5xty2P8yr093m7OAIQ9elqm/cUnpwJgbmL0RusK7yeRWvP/SFpaGklJSdjY2JCXl0dMTAy//PILQ4YMwc7ODnt7e65du0avXr1o3Lgxs2fPJjMzkzlz5jB06FA2bdoEyAe+Q4cOJS4ujilTpmBiYsKKFSt49uyZ2lzYb775hi5dutCvXz82b97M+PHj8fHxUaS3PHnyhKZNm9K/f38kEgmnTp3iyy+/ZNWqVQQEBJRpX/v372fMmDE0b96cP/74A11dXa5evcrz58+pWrWq2n759ddf2bJlC1999RW+vr5cvXqV33//HX19fbp37w7AuHHjiImJ4ccff8TKyoqoqChCQkLe2O/mTdK3sybhzGWV8qyomILtNqSGhFGuYAY4O0p1ljA7OpZy9jYaHT8uMRkrC9UbHAvL4hITNdqvOnfvPeDLCb8ofna2t2Xm+FGYmqj/A1wa8YlJWJmrxl/ewhyAuIQkjfetfJxk/t66hxG9u6h8aXgTkhISqFpNdSBqUTBTnhgfT0UX9elHiYnxSnVfbZ+WmkJubg66uno4ObswePg3rF6xkO/HDlHUa9K8NUNGjXtr8SeUIn7zUsT/qkcP7/Pw/j06fdq9zDdbJiQmYGlpoVJeWBafoP5qVGpqKrm5uVhaWqpss7QobJtQ5JXEp8+ecfbceRo2qF/qVJTiJCbEU81b9R6iwvgSEuJxcXVT2zah4DWqey0WlpYFr1W57/fs2s7qoBWKn339ajBy9LdlilnL0ARZRqpKuSw9BQCJkSlF3b4vy84k5/oZ8qMfQH4e2vZu6Favj3YFZ9I3zlb6ciApb4euT10ydy0vIYe+9OKSUihvbqpSXt7cBIDYxJQy7S9o33G0JRJa1K5ebL3ktAx2nrxIDU9XrNUcX/gwiIH8/7jCS5PR0dHMmDGD/Px8WrVqxb59+0hOTmbZsmX4+r74Y/nDDz/g7e3N/PnzFX/EPDw8FLP3jRs35tSpU9y6dYt169YpbpytW7cujRs3VtyQ9bIePXrQo0cPAGrUqMHJkyc5dOgQQ4cOBaBnz56KulKplICAACIiIti8ebPKQL64fclkMmbMmEH9+vVZsGCBok3jxo0pyqNHj1i7di1Tpkyha9euANSrV4+srCwWLFhA165dkUgkBAcHM2bMGNq2bato26lTpxJ6/93QNiiHNFv10rc0K6dgu3yWS1Iw+6Oubn5WNjqmmg2Gs3Ny0NNR/WjRK8g1zs7J1Wi/6rg62vPXpG/IzM4mODSCyzdvk5mV9Vr7zM7JVcT6Mj29Nxv/grVbcahgTYfmDd/I/l6Vk5OtdqCqq6en2F5k22z5NnX54YX7zMl+sX9LK2vcPb2oWasu1ja23Ll1g/27t2FiakafgcNeI351v4c3H//LTp84AkDDMqbVyPeZoz7mguNkq3mvgfw9U1S8itdbRNusrCx+nTYDPT09BvTtU+aY1cnJUf86XvRd0ak1OaV4LdnZygP5Ro2b4V7Zg+TkZC7/e4GkpMRij6GOlo4usnzVVBxZXsH7Vafoex1yr59W+jkvIpj8548waN0Tver1ybn8j2KbfuNO5D+4W+JKOGWRlZv3xj4zD5y7yq6T/9KnXROci0nXk0ql/Lh4HakZmYzr9UnZg35HxPKTqsRA/n9YRkYG1V5aJcHMzIxJkybRsGFD9u3bh7m5udIgPjMzk6tXrzJu3DjyX8qZdnFxwc7OjuDgYBo3bkxwcDCmpqZKq98YGRkRGBjIrVu3VOJo0OBFnqWhoSH29vZER0cryqKjo5k9ezbnzp0jNjYWWcEsRzU1KzwUt6/IyEiio6P57rvvSt1H586dA+Cjjz5SysesV68ey5YtIyoqCgcHB6pWrcrKlSvR1tamfv36VKyoWbrAfyE/MwuJvuoARVJOr2C7fJAjzZQPeNXV1S6nr9heVvp6euSoyW3Nyc0t2F76mwdLYmRoQO2CJSEb1anJ4dPn+W7GXP6eNZnKLs4a7VNfT1cR68tyct5c/CFh9zh46jzzfvrmtVbXAcjNzSUtVXnGztTMHD09fbW5zLkFAy29YnKB9QpSGnLV9EPhPgvr3L0dzLQp4/ntz0W4F6zwUiewIQaGRmxZH0Szj9rh5OyiYfzqfg9vNv6XyWQyTp84hnNFV5UbYEtDT19PfcwFx9RX814D+XumqHgVr1dN2/z8fKbNmMWjR4/45efJWFmpXoEojrzvlWexTc3M0NNT/zpe9J361wEvBuvFvZZX+8GmQgVsKsjz6Rs3acb8uX8y8YdvWbQ0qNTpNbK8XNBWHdJoFQ7g88r2BTwv9BrShh3QdqoMBQN5ncp+aNu5kL626JuWNVFOV+eNfGZeC41k6orNBPp4MvSzNsXWnblmJ+duhvLz4O54OJecdiS8v8RA/n9YuXLlWLt2LVpaWlhYWGBnZ6c0aChfXnlt65SUFPkfhmnTmDZtmsr+oqKiAIiJiVF/CVhNGYCJiYnSz7q6uooPdKlUypAhQ0hNTWXkyJFUrFgRAwMD5s6dqzheafeVlJQEgI1N6VNCEhMTkclk1K1bV+32woH87NmzmT17NnPmzGHKlCm4uroyZswYPvroo1If67+SHRWLvpqZmHJ2NgXb5Sk2WdHylBp9O2uynkQr1dW3tSbp0k2Njl/ewoxYNekn8YnJBdtVUw/elMYBtYBlHD1zUeOBvJWFObEJquk/cYlJAJS3NNc8wAIL1mzB16sy9jbliYqR39SclJImP05SEtGx8dhal25QFnonhMkTRimVLVy5CXNLS0WKycsSC1IfLIoZ9FlYWCnVfbW9sYmpYkb18IHdmFtYKAbxhWoF1Gfzur8JvRNS7EA+9E4IP034Wqls0cqNJcZvWYr4k0oR/8vu3g4mNiaaHn2+LHLfxbG0sFS5nwggoeB8slKT6gPyzzVdXV0SElRvOExILGyr+vk6Z958Ll66xHffjMXPt2z5/AB379zih/HfKJUt+3stFpZWJKqLpaDMsojX8fI2da8lMSGh4LUW/UUAoH6DRhw+uJ9bITep6V+7xNcBIMtIRctI9YpwYZk0vWzpKQCy1CS0yr1IZ9Jv2J688JuQn4+WifxzTEtfnhanZWIO2tqKVJ6yKG9uSkzB5+PL4pLkX7KsLUpOewl79IzRs/+mkqMtM0f0RqeYFKulOw6z5dg5RnRpS7v6/mWOV3i/iIH8/zCJRFLsWumv5n+amJigpaXF4MGDadFCdQkzi4IBmI2Njfo/OGrKSvLw4UNu377NggULlI6ZpUF6hLm5OSD/olFaZmZmaGlpsX79erWXgl1d5Tc42tjYMG3aNKRSKSEhISxatIjRo0dz8OBBnJyKX4/7v5Zy4y4WDfxBS0sph9O8TnXy0jNID7tfUO+OvNzfh+RLL2541bezwcDJjkfLN2t0/MouzlwNuUt6RqZS7vetcPlSlpVd315/5ebmIpXKSMvQfCWJyi5ORcQv7zcPDb8gvCw6LoHo2Hg6D1W9ejRu+jyMDQ04snq+mpaqXFzdmfSL8hJ+5haWuLhW5u6tm0ilUqUv8OGhd9DXL4d9MevIW5W3xtTMnHvhoSrbIsLu4OL24qbM5KQEpPlSlXr5BTOM+SU8WEwe/x8q8bu6unPnVrCa+G+XOv4ItfHfxdVN9aZSgFMnjqClpUXDJpot4VjJzZUbN2+SnpGhdMPr3VB5HG5u6m/ClkgkuLpUJCxC9UbQu6Gh2NnaquTHL1uxksNHjvLVl4No2qTo9MHiuLpW4udfZyiVWVhY4upWidtq+j6s4NxxcCx6HXmr8uUxK6Lvw4vp+5dlF6RGZaSX/gFL0tin6DpWkq8681Lalbatc8H2Z6XeVyEtUwuldhITCyRVLNCtUlOlrtEXY8iPfUrG+j9VtpXEw9mey3fukZaZpXTDa8i9RwXbVZ9z8LLHz+MYPmsZlqbGzB07EMNyRV/F2Hz0LEt2HOaLVg3p275ZkfXeVx/6CjNvg1i1RlAwNDTEz8+PyMhIfHx8VP45Fnx4+/j4kJKSwqVLlxRt09PTOX++7HfwZ6vJZX369CnXrl0r877c3NywtbVl+/btpW4TGChf9zopKUntazY2Vs4Tl0gkVK9ena+//pq8vDwePnyobrf/GX1ba4w83dB6Kb8yavtBytlaY/vJi6sFulYW2H3ampi9x5EWpIik3Y4g7c49nAZ2gZf+WFcc3B2ZVEr09oMaxdQ0sBb5Uim7jpxQlOXk5rLvn9NUq+xGhfLyGbvo2HgePFG96lIaqekZapem231MvtqRVyUXjfYL0KyuPP6dR14sk5eTm8u+42cK4pfPjEbHxvPgqWbxjx/cm+njhin9+7xNcwBG9O7C5FGDSr0vYxMTqteopfRPT0+fwAaNSUpK4OK5FytApSQncf7McfwD6inNikZHPSU6SnlljLr1G3Pl0jniYl8sYXfz+hWePX1MYIOmijJ7eyeSkhIIuan8nj1z8hgArm7FPwnU2MQE3xq1lP7J429SRPwnqFWq+Btx5dJ54mJffLF/EX8TlTjy8vI4f+YkVar6KC2bWBYN69dHKpWy/8CL905Obi6Hjx6liqcnNtbyK2UxMTE8eqy86k6D+vUJCwsnLPzFijqPnzzh+o2bNGxQX6nulm3b2bp9B926fM4nHTtoFCvI+96vhr/SPz09PerXb0hSYiLnz71Y9jIlOZmzZ05RJ6CuUt9HRT0jKkp5kBxYvwGXLl0k9qW+v3H9Kk+fPlGsSw+QnJykNq6jhw+ipaWFWymfIguQG34TLYk2ut4vnmWAtja6VWuTH/UQWZr8WFom5kgslK/aahmortiiW70eEkMT8h7eVZRl7vlb5V9uqPy8zzy0nuxTu0od78ua16lOvlTK9uMXFGU5uXnsPn0J70rO2FqZAxAVl8j9Z8oTVXFJKQybtQyJRIv53w7Coph7mw5fuM6sNTtpU68mY77Q/LwR3i9iRl5QMm7cOPr06cPXX39Nu3btMDU1JTo6mnPnztG5c2cCAgJo1KgR1apVY+zYsYwZMwZTU1OWL1+OkZFRmVd5KBx8//HHH0ilUjIyMpg7d26Z0mMKaWlp8d133zFmzBhGjBhBx44d0dPT4/r16/j4+NC0aVOVNq6urvTo0YNx48YxYMAAfH19yc3N5cGDB1y8eJGFCxeSmprKgAED6NixI66uruTm5rJmzRpMTU2LXAnnTag4tAe6ZqaK1WNs2jWlnIP8Ue0PFqwhLyUNz1/H4NS7M/+4NyPzoXwgE7XtEIkXruG7fBrGXu7kxidScXB30NYm7Gflh6LcGT+TWjsWEXBgJc8278OkmgcuQ3vweOUW0u6W/WFQANU8KtEssDaL1m0jMTkVB1sbDpw4S1RsPBOG9lfUmzpvGdduhXJu29+KsrT0DLYcOApA8F357OTWA0cxNjLExNCQz9rKZ0qvhtxlzsp1NKlbCye7CuTm5XHjTjgnL16hSiUXWjWqp1Hs8vjdaBZYi0Xrt5OYkoqjrQ37T5wjKjae74f2VdT7ed4Krt0O5fzWF6ttyOOXD2BvFsS/5cAxTIwMMTYyVAzWA/y8VY5buPZ9jaqeeLm7aBx/obr1m+BRZSsL5kzjyaMH8ie77t+JVCqla4/+SnWnfD8agEV/v7gK07lLT86fOcHkCV/TtsNnZGVlsnvbBpxd3GjW8kX+beuPO3P86AGm/zyeNh9/irVNBW4H3+DMyaNUr1ELjyqavUfq1m+MR5WqzJ8zncePHmBqasbB/bsK4u+nVHfy92MAWPz3JkXZp116cf7MSX6a8DXtOnxKVlYmu7ZtVIm/0PWr/5KaklzmteNfVqWKJw0b1OfvVatJTk7G3s6OI8f+4fnzGMaMGqmoN+vP2dwMDuHQvj2Kso/bteXAocNMnPwzn3X+BG1tbbbv3ImFhTmfdn5xM+LZc+dZvvJvHOztcXZy4tg/x5ViqFnDT3H1VFP1GjTCc9d25s6exeNHDzE1NWX/vj1I86V076l8Q+3ECfLVZZYHrVOUfd71C86eOcUP47+hQ8dPyMzMZMe2LVR0caXFRy+eT7F543ru3A6hpn9trG1sSEtN5dzZ04SHhdK+Qyfs7YufiX6Z9PkjcsOuo1+vLRIDY6TJceh61ULLxJKsIy/O63IfdUfH0Z3Uv8Yqyoz6/Uhe+HXy46IKVq1xRcfDj/yYp0pLTOZFqq5UVrisZf6Du6V+mNSrfCpVpEWd6szfsp/ElDScKpRn75nLPItLYNKAzxX1flq6gSt3I7my+ndF2Yjfl/M0Jp4+7ZpwPew+18NeLHFqaWZCXW/50qch9x4xaekGzIwNqVPVnQPnrirFUL2yC442ZbvHQng/iIG8oKRmzZqsX7+eefPmMWHCBHJzc7G1taVu3bqKGzy1tLRYuHAhkyZNYtKkSZiamtK7d2/u37/PnTt3ynQ8PT095s2bx88//8yoUaOws7NjyJAhXLhwQaPlHdu2bUu5cuVYvHgxY8aMQV9fn6pVq9KyZdF/nH/88UdcXV3ZtGkTCxYswMjICFdXV1q3lj/URV9fHw8PD9asWUNUVBTlypXD29ubFStWFHlfwJvgNro/hi4vLmHbdW6leEjT0/W7ySvIqVYhlfLvx1/iNWMcrsN7ITHQJ/lyMDcGTlCk1RSK2X+CK58Pp/LE4VSbM5Gc2AQipi8h/JcF6vddShNHDsJ2w3YOnjxHano6lSo6MWvCKGpUU11b+mWp6Rks27BDqWzDbvnTaW2trRQD+UoVHanpXYXTl64Rn5iMDBkOFWzo93kHenRsg67u6320TRoxkKUbd3Dw5HlF/L9PGEmNqiXHv3TjTuX49xxWxF84kP8vaGtr8/3kmaxZuZD9e7aRk51NJY8qDBs9AQfHktODyltX4OfpcwlaPp91QUvQ0dGhZu1A+gwcpjQj6+DozIy/lrFh9XJOHz9MUmICFpbl6dC5m8oXhrLG/8PkmaxeuYj9e7aTk52Nu0cVho8eX8r4bfh5+l8ELV/A2qCl6Ojo4F87kD4Dh6rN0T51/Ag6OjpqZ+vLYtzYMaxas5Zj/xwnNS0NV1cXfv5pEj7eql/eXmZoaMis6b+xZOly1m/chEwmo7qPN4MHDcT8pQdARd6Xv4efPnvGzD9U0zhmTvvttQfy2tra/DTlN/5esZQ9u3eQk51DZQ8PRo3+FkfHklPjrK1tmDbjT1YsW8Sqv1ego6tDrdoB9B/4lVLf16odQHTUM44eOUhKcjK6unq4uLoyavS3NGtR9vuPsg5vQD8wER0vf7T0DZDGRZG5ewX5z4qflMgNvYq2nQs6laqDjg6y1ERyrpwg59+jZb5JVlM/f9mdRdsOsu/sFVIzMqnsZMec0QOoWaX4m67DHsmvhqzad0Jlm38VN8VAPvLZc3Lz8klMTWeKmrTJnwZ1FQP5D5SWTPaGFkIV/l/LycmhXbt21KpVS+2NsoJ6+3SLHxi+z9rlhhIfcu5dh6ERK+96JASfKbnie8rSpwHBEc9Lrvie8nGvQEhEdMkV30Pe7rY8iHhzSw/+11zcPQi99+YeyvZf8qzkpDST/qExGfUHaRf3lFzxPWUc8PG7DoFT3jXeyn4bhZQ9nfd9IWbkBY1s2rQJqVSKq6srKSkpbNiwgadPn/Lnn2W/0UcQBEEQBKEkEm1xs+urxEBe0Ii+vj5Lly7l6VN5XnaVKlVYsmRJsavkCIIgCIIgCG+OGMgLGunUqdN7+2RTQRAEQRCE/w/E8pOCIAiCIAiC8AESM/KCIAiCIAjCe09LInLkXyVm5AVBEARBEAThAyQG8oIgCIIgCILwARKpNYIgCIIgCMJ7T0tbzD+/SvSIIAiCIAiCIHyAxEBeEARBEARBED5AYiAvCIIgCIIgCB8gkSMvCIIgCIIgvPck2mL5yVeJGXlBEARBEARB+ACJgbwgCIIgCIIgfIBEao0gCIIgCILw3hNPdlUlZuQFQRAEQRAE4QMkZuQFQRAEQRCE95642VWVmJEXBEEQBEEQhA+Qlkwmk73rIARBEARBEAShOJca1H0r+6195sJb2e9/QaTWCMI7FB9y7l2HoDEr73rs0/V812FopF1uKIk3Tr7rMDRm4duYp2HB7zoMjTl4+JB1aMW7DkMj5VoNIPXffe86DI2Z1GlHQvCZdx2GRix9GpBxesu7DkNjhg0/J2PVz+86DI0Z9pn0rkNAS6TWqBCpNYIgCIIgCILwARIDeUEQBEEQBEH4AInUGkEQBEEQBOG9pyUR88+vEj0iCIIgCIIgCB8gMZAXBEEQBEEQhA+QGMgLgiAIgiAIwgdI5MgLgiAIgiAI7z0tiVh+8lViIC8IgiAIgiC89yRiHXkVIrVGEARBEARBED5AYiAvCIIgCIIgCB8gMZAXBEEQBEEQhA+QyJEXBEEQBEEQ3nviZldVYkZeEARBEARBED5AYiAvCIIgCIIgCB8gkVojvHUnT55k7dq1BAcHk5qaipmZGd7e3nTo0IG2bdsikUjo1asXhoaGLFmy5F2H+97Iyc1l2cYdHDp5npT0dNwrOvFl987U8a1WbLuHT6PYefgEt8LvERb5kJzcPLYtmoWdTXmVun/9vYFrt+4SFRtPTk4uttZWNK9fhy86tMbQoJzGsWsbGeI2dgDmdXwxr+2DnqU5NwaM58nqHaVqr2Nmgtf0b6nQsSXahuVIvhTM7XHTSbl2W6WuTftmeEwajrGXOzkx8TxetZ2IXxciy8/XOP6c3FyWbtrNwdMXSE3LoFJFBwZ360RA9arFtnv4LJodh09yK+I+ofcfkZObx/b5v2Gvpu87DZtAdGy8SvknLRrx3Zc9NY69MP6gdRs5cvwUqWnpuLk4079nd2rV8C2xbWx8PAuXBXH5+g1kUhl+1asxdGA/7G0rqNRNSEwiaN0mzl+6QkpqKpYW5tT09eHbkUNfI/Y8Fuw/w75Lt0jJzKayvTXD2zUksIpLse2O3Qhjy9nrRDyLJSk9CwtjA6q72PNVm/pUtrdWqjtr+zEuRzzmWUIKObl52Fma0qpGFfo0r4Ohvp7GsRfGv3jbAfafvUJqegbuTvYM+awNdX08i233z6WbHLl4nduRj4hLTqWCpTkNa1RlYMePMDEyUNRLSk1n96mLnL52m/vPnpOXn4+LnQ1ftG7MR3VrvGbsuSzbuJODp86Tkp6Bu7Mjg7t/UorPnGh2HD7BrfBIwu7LP3O2L5yh9jPnZU+iY+gxeiI5uXmsnD4RL3eX14w/j0W7jrH3/HVSMzKp7GjLsE4tqFvNvdh2x67c4vClYG49eEp8ShoVLMxoWN2TLz9ugomhgUr99Kxslu05zpErIcQmpWJubEj1Ss5M7f8pBq9x/uTk5bPo1E32htwnNSuHyjbmDGvsS11XuzLt56v1x7j4IJqu/h6Mb1VbUb775j1+2nuhyHa/dqhHW29XjeP/L2hJxPzzq8RAXnir/vzzT5YsWULLli2ZNGkS1tbWxMXFcfToUb799lvMzMxo2LDhuw7zvfTLvBUcv3CZru1a4mhXgf0nzjD219nMnzIOXy+PItuFhN5jy/4juDjaU9HRnvD7j4qseyfiPr5eHrRrVgE9XV3C7j9k7Y59XL55m4VTxyPR8ENTr7wFHhOHk/HwKak3Q7FqElD6xlpa1N69FNPqnkT+sYKc+EQqDv6CukfXcCagMxkRDxVVrVs1ota2BcSf/JdbX0/FxNuDyt8PQd/GipDhkzWKHWDqgiD+uXiFbm1b4GRnw74T5xgzbS4LfhqLX5XKRbYLDotk84F/cHW0w8XBjrAHj4s9joeLE93bt1Qqc7ZXHTCX1Yw58zl19gKfdmiHo70dB48dZ8KU3/jz18n4VPMqsl1mZiZjv59MekYGPT7vjLa2Ntt27WP0hEks/et3zExNFHVjYuMYOe5HADq0aUl5K0viEhK5GxbxWrFPXLefo9fD6NHEH2drC3ZfDGH44q0sG9GNmpUci2wX/iwWU8NyfNG4FubGBsSnpLPzQjA9/1jD6jE98XSwUdQNeRRNzUpOdAwwR19Xh7tPnrPy6EUuhD3k75FfIHmNPNzJSzdw7NINvmjVCKcK1uw9fYlRfyxjyYSh+Hm6Fdnu15VbsLYwpU19f2ytLIh4HMXmI2c4e+MOa6eOoZyefIAYHPGAhVsOUN/XiwEdW6ItkfDPpZt8v2AN958+Z/CnrTWO/Zf5K/nnwhW6tmuBk10F9h0/y5jf/mLB5G/x9Sr6vA8Ji2DLgaPyzxwHO8JLOO8L/RW0EW1tbcjN0zjml036exvHrtziixb1cLaxYve5q4yYu5ql3/SnRmWXItv9smYX1mYmtK3ri62lORFPn7Pp+AXOBoexftJQyunpKuqmZmQxcNZyYhJT6NyoFk42ViSmpnMt/CG5efkY6L9G/HvPc+zuI76oXQVnSxN234xkxKbjLO3RghpONiXvADh29xE3n8ap3VbTyYZfOtRTKV/3713CnidSx8VW8+CFd0YM5IW35sSJEyxZsoThw4czYsQIpW1t2rShT58+6OiIU1Cd2+GRHD17keG9u/BFxzYAtGlSn56jf2TBms0s/e3HIts2rO1Hk8AFGBkYsH7XgWIH8ot//V6lzMHWhvmrNnE74j7eHpU0ij87KoajjvXJfh6Hmb83DS5sK3Vbu09bY1mvJle6jiR6+yEAorYcoMntQ3hMGsH13t8o6nrNGEdKcCj/tumvmIHPS0nHffxg7s9bTXpoZJljvxVxnyPnLjGi52f06PARAG0aBdJj7GQWrN3Gsl/GF9m2YS1fjgT9hZFBOdbtPlziQN7a0pw2jeqWOcbi3AkL5/ipswzu14uunTsC8FGzxvQfPoYlQWuYP+u3Itvu2n+IJ8+iWPjHdKp4yGcxA/xr0n/4aLbs3M3A3j0Udf9csARtbQkL/5yhNMB/HcEPozh49S5jOjahT/M6AHxcx5tPp61kzq4TrB5T9JWKr9rUVynrHFidjyYtYvOZa0zs2kpRvurrHip1Hcub8+fOE4Q8jKK6q71G8Yfce8jhC9cY1e1jerVrCkC7BrXoOmEmczfuZeVPI4tsO2NkH2p5Kc8cV3F1ZPKSDRw8d5VOTeTniZuDLTt+n4BdeUtFvc9b1Gfo9MWs2vcPvds1xaBc2UeTt8IjOXL2X4b3+pweHeVfBto0rkePMZOYv2YLy35T/awo1KCWH4dXzcPIwIB1uw6WaiB/4XoIF6/fokfH1gRt21vmeF8VEvmEQ/8GM/rz1vRu1QCA9vX8+HzSPOZsPcSqCYOLbDvrq27UqqL8Jcuroj2TVm5j/4UbdG5US1E+b/thouKT2DBxKA7WL34H/dq8ZvzP4jh0+yGjm9Wgd135lb/2Pm58vmwvc/65xqo+rUrYA2Tn5fPnsav0DazKolM3VbY7WpjgaKH8Xs3KzWPawX+p7VKB8saqVx+E95+4RiG8NX///TfW1tYMGTJE7fbq1atTtar6VIXx48fTvn17pbKUlBQ8PT3Zvn27UvnOnTvp1KkTPj4+BAQEMGjQIJ4+farYHhoayoABA/Dz88Pf35+RI0fy7NkzpX1s3bqVdu3aUb16dQICAujevTs3b774IJTJZKxYsYJWrVrh7e1N8+bNCQoKKkt3lMnx85fRlkjo2LKJokxfT5ePmzckJPQez+NUUzIKmZoYY2Sg+QeynbX8cnhaeobG+5Dm5JL9XP2sUElsO7ciKzqW6B2HFWU5cYk823qACh2aIymYHTP2qoRJtco8Xr5ZKY3m4eL1aEkk2HUu+Q+fOv9cuIK2REKnFi+uFOnr6fJxswYEh0XyPC6hyLZmxkYYlTElKTcvj8ysbI1iVefU2QtIJBLat34x06+np0fbls24fTeMmNiify8nz17As7K7YhAP4OzkQE1fH06cOa8oe/T4Kf9euUaXzh0xMzUhJyeHvLzXn1U9ej0UbYkWn9Z7kQKkr6vDJ3Wrc+PBM6ITU8q0P0sTQ8rp6ZCaWXL/OliaAZCamVW2oF9y7N+baEskfNIsUFGmr6dLx8YB3Ix4QHR8YpFtXx3EAzT19wHg/rPnL+K0sVIaxANoaWnR2N+bnNw8nqpJ1yqN44XnfcvGSrF/3KwBIWH3ij/vy/iZk5eXx+yVG+jSrgWOttYlNyiFo1dC0JZIlAbd+rq6dGzoz817j4lOSCqy7auDeIBmNeV/m+5HxSrKUjMy2X32Kp82qo2DtSW5eXnkvKGrCUfvPkJbS4vONV5c+dDX0aajbyVuPo0jOiW9xH0Enb+NVCajd0DRV91edSr8Kek5ebSp9n6n1BTSkmi9lX8fMjEdKrwVeXl5XL16lVatWr3VWffly5cza9YsPvvsM0aPHk1ubi4XLlwgISEBBwcHoqKi6NmzJ05OTsyaNYvs7Gxmz55Nz5492b17N8bGxly6dIkffviB/v3707hxY7Kysrh58yapqamK4/z6669s2bKFr776Cl9fX65evcrvv/+Ovr4+3bt3f+OvK+z+Q5zsbTF6JT+zqrv8D074/cdUKG/1Ro6Vl59PWnoGuXl5RD56ytIN2zE0KEdV93fzwW7m5yXPhZfJlMqTLwVTcVA3jDxcSQ0Jw9RP/oc26UqwUr3sqBgyH0dh6lf6P2YvC7v/GCe7Cmr63kW+/cFjKrwykNLU5ZC7NOk5nHypFFtrK7q3a0HXts1fa58RkfdxcrDHyNBQqbxwcB5x/wE21qq5y1KplMgHD2nTopnKtioe7ly+doOMjEwMDQ24ckP+JdfC3IyxP0zm2s0QJBIJtfyq8/XQL7GtULo0gFfdffKcitaWGL+Sn+Bd0a5gewy2FqbF7iMlI4u8fCnxqemsPXGZtKwcAjwqqtTLy5eSmplFbn4+Ec/imL/vNEb6eopjaSL04VOcba0xfuXLXLVKzgCEPXyGrZVFqfcXnyz/DDI3Nip9XRPjUu//ZWH3H+Fkr+68l38OhD149MbO+437jpKankG/T9tz4uKVN7LPu4+icK5gpdL33q7ydKzQR9HYWpqXen9xiv588T66Fv6Q7Nw8nGws+WbRBk5cu4NUJqO6mxMTenyMp7Pm587d6EScLU0w1tdVKve2k79XQ58nYmta9HkQlZxO0Plb/NSuLuV0S/83d/+tB5TT0aa5p5NmgQvvnBjIC29FUlISOTk52Nkpf7DJZDLyX5o9lUgkGudhp6amMn/+fLp27crPP/+sKG/RooXi/4OCgsjLy2PlypWYm5sD4OXlRbt27dixYwe9evXi5s2bmJub89133ynaNWnSRPH/jx49Yu3atUyZMoWuXbsCUK9ePbKysliwYAFdu3bV+DUUJS4xGSsLM5XywrK4xKJn9srq7r0HfDnhF8XPzva2zBw/ClMNBwSvS9/OmoQzl1XKs6JiCrbbkBoSRrmCmbzsl2bMCmVHx1LOXrPBZHxSMuXV9H15Rd8nabTfV7k7O+BbpTEV7W1JTk1j38nzzA7aRGxCEsN7fqrxfuMTErG0MFcpt7SQDyDj49XPrKamppGbm4uVmsGOVUHbuIQEnA0dePosCoA/5y+hSuVKTBo3huexsazeuIVvJv7M8rl/UE6D9I7YlHTKm6kOVsoXDGBiU9JK3EevP9fyIEb+Gg31dRnUKpBP6lZXqXf7UTS9Zq9V/OxiY8lfX3bGzEjzq1lxSSmUN1f9olFYFpuUXKb9rdr7D9oSCc3rFH+TcnJaOrtOXKCGp5va45dGfGISVubqzntzAOKKmdEu23GS+XvrHkb07qLypeF1xCWnYm2mmuJVvqAsNrlsV3OCDpxGWyKhhf+LG30fPZdf7Zi3/QiO1pZMHfApqRlZLN1znC9/X8nWn0diba5ZmllcWibWalJbCtNdYlMzi23/57GreNpa0LqaS6mPmZyZzbnIZzT1cMTolS8QwodDDOSFt0pLS/mS1aFDhxg1apTi5x49ejBp0iSN9n3t2jUyMzP57LPPiqxz+fJlAgICFIN4gEqVKlGlShWuXLlCr169qFq1KklJSYwfP56PP/6YmjVrYvDSZeJz584B8NFHHymlD9SrV49ly5YRFRWFg4ODRq+hKNk5OeipuZKhp6tbsD33jR3L1dGevyZ9Q2Z2NsGhEVy+eZvMLM3TC16XtkE5pNk5KuXSrJyC7fIBoqRg5k1d3fysbHRMNfsikp2Tg66aGa033fe/fzdc6ef2Tesz+re5bNh3hC5tmmFThpnbl8njV/2jrFdws2R2jmp/vVyuvq28LKegTuH5YWlhzm8/fa/4Imtd3opfZs3h2MnTtGvVQmU/Jceep/a81y/4fWTnlJzG8HOPNqRl5fA0LomdF4PJzs0jXyZFgrZSPTdbK5YM60Jmdi7X7z/lYuhDMtScS2WKPzcXXR1tlXJNzp2D566w6+RFerdrinMx6SdSqZSJi9aRmpHJt70+KXvQBbJzchVxvqzwd/+mzvsFa7fiUMGaDs3f7CIH8r5/vXOn0IGLN9h55gp9WzekYoUXV69ePj+WjO2HYcGX1SrO9vSZtoTNxy8w7JOWKvsrVfx5+WrPHX0diWJ7US49iObY3Ues6Vu2G52P3n1Ebr70g0mrEdQTOfLCW2Fubo6enh7R0dFK5YGBgWzdupWtW7dibf16uZFJSUkA2NgUPfOakpJC+fKqaQRWVlYkJycrYpo5cybh4eEMGDCAunXrMm7cOMX+ExMTkclk1K1bl2rVqin+9evXD4CoqKjXeh3q6OvpkaMm5zgnN7dg+5ubPTEyNKC2bzUa1anJsF5d6N6hFd/NmEv4g6Jvkn2b8jOzkKhZwk1STq9guzzfWVqQy6yurnY5fcX2stLX0yNXTd7r2+j7l2lpadGtXQvy86VcuRWq8X7k8asOugoH4fp66pfHKyxX31ZeVvhloPC/TRrUU7oa1bh+INra2ty6q1n8+no6as/77ILfh75eyXNPvq4O1PdypUvDGiwe2oV9l24zd88plXrGBvrU9XShafXKjO7YhN7NavP1sh2EPo3RKHaQ52TnqhlwlfXcuRYaydTlmwj08WTo522LrTtr9Q7O3bzLjwO64lFR8wkFfT1dRZwvK/zdv4nzPiTsHgdPnWdU325v/CqmvO9f79wBuBr2gClBO6hXrTLDPlH+Mlq4ek1j3yqKQTxA9UpOOJS34MY9zT8z9XW01Z472XlSxXZ18qRSZh65TDsfV6rZly3dcn/IA8wM9KhfSbObu98FibbWW/n3Ou7du0e/fv3w8/Ojfv36zJw5U/F5W5zExEQmTZpEkyZN8PPzo3379mzYsKHMxxcz8sJboaOjQ82aNTl//jz5+fnyJcYAMzMzfHzkN3DpFTGgKNz26oCicOBdqHCWPSYmBltb9ctmmZmZER+vevNXfHw8Li4uip87duxIx44dSUhI4NixY0ybNg0dHR1+++03zMzM0NLSYv369WpnK11d3/xsRnkLM2LVXMqOT0wu2K7ZbG1pNA6oBSzj6JmLVHZxfmvHKUp2VCz6amYgy9nZFGyXD7SyouUpNfp21mQ9Uf7CqG9rTdIl1VUbSsPKXH3fxyn63lyj/ZZGhfLy32tKWsk3thXFytKCODXpMwkF6VhWVurznE1MjNHV1SVe7Xknb1ve0rLgv/I4LV5JxdDW1sbUxIRUDeO3NjUiJkk1fSau4EY/6zJeZTE1LEcdD2f2X77N2E5Ni63b3NeDH9bs4+CVO0pLVZZFeXNTYhNV02fikuRpHdZqUldeFfbwKWP+XEElRztmjOyLjrb6ARzA0u2H2HLsLMO7tqNdg1pF1isNKwtzYhNUU/YKU8nKlyG/vCgL1mzB16sy9jbliYqR33SdVJAuFZeURHRsPLbWmt37U97MhJgk1fSZwlx3a7OSU45CH0fx9fy1VHKowKwh3VT6vjBtxlLNeWhpakRKuuZXMssbGxCTqrrAQFyaPKXG2kR9GtLe4Ps8iE/lhzYBPHvlvZOek8uzpDQsjMph8MpVxqjkdK49jqFzDXd0tT+cOd337cbU5ORk+vTpg4uLC/PmzeP58+dMnz6drKysErMNRo0aRWRkJGPGjMHOzo5Tp04xefJktLW16dKlS6ljEAN54a3p168fgwcPZvHixQwbNqxMbW1tbYmOjiY9PR0jI3l+7NmzZ5Xq1KhRAwMDA7Zt20b16qo5sAD+/v5s3ryZ5ORkzMzkf0QjIyMJDQ3l009V85AtLS35/PPPOXXqFJGR8qULAwPlK1AkJSXRrJnqjYBvQ2UXZ66G3CU9I1Mpj/RWuDymyq5v78ak3NxcpFIZaRnF52S+LSk37mLRwB+0tJRueDWvU5289AzSw+4X1LsjL/f3IfnSixte9e1sMHCy49HyzRod38PFiau3QtX0/X3F9rflacFKPxavsZxjJVcXrt0MIT0jQ+mG1zuh4QC4u7qobSeRSHCr6ExoxD2VbXdCw7GzrYBhQX94uMuXJX31C0Nubi7JKSmYl2LQpI6ngw2Xwh+RlpmtdMNr8EP5KlNVHMs+wM7KzSOtFKvW5OTlI5XJSHuNFYQ8K9pz5U4EaZlZSjddhhTM1HpULH7m88nzOEbMWoqFqTF/fTNIadb3VZuPnGHpjkN0b9WIvu1f7wZpgMouTkV85hSe96//pT46LoHo2Hg6D/1OZdu46fMwNjTgyOr5Gu3b09mOy6H3Vfs+8nHB9uLXSH8cE8/wOauwNDFm3qjeavveq+D3p+4LQ2xSKi62xT8Aq9j4K1hw+eFz0rJzlW54DXkWp9iuTnRyOnlSKf1WH1bZtjf4PnuD7/Pnp41o+srNrAdvP0AGtBVpNa9l48aNpKenM3/+fMXkYn5+PlOmTGHw4MFUqKD+uSCxsbFcvHiRadOm0blzZ0A+1ggODmbfvn1lGsh/OF/DhA9OkyZN+PLLL5k7dy4jRoxg//79XL58mePHjzNr1ixiY2MVg/RXffTRR2RnZ/P9999z9uxZgoKCWLt2rVIdExMThg0bxsaNG5k0aRInT57k+PHjTJ8+neBg+cCub9++6Ojo0L9/f44ePcq+ffsYPHgwdnZ2fPKJPJ907ty5/Pzzzxw8eJBLly6xbt06Tp8+Td268nWbXV1d6dGjB+PGjWPRokWcO3eOkydPsmrVKoYO1fwJlsVpGliLfKmUXUdOKMpycnPZ989pqlV2U6xYEx0bz4MnmqX2pKZnqF0ycPcxeRqCVyUXjfZbFvq21hh5uqH1Um5r1PaDlLO1xvaTjxRlulYW2H3ampi9x5EWXOpPux1B2p17OA3sAi9dpq84uDsyqZTo7Qc1iqlp3ZrkS6XsPHpaUZaTm8veE+eoVtlVsXJHdFw8D55q1vfJaenkS6VKZXl5eazeeQBdHR38vYt/CmhxGtevi1QqZe/BI0rxHzx6HC/PyooVa57HxPLo8VOlto3q1yU0PILQ8BcPdXr05CnXbobQuP6LJRV9faphYW7G0ZOnlS4hHzp2AqlUir+f+i/WJWnh50m+VMa2czdeij2PXReD8alop1ixJiohhfvPla+0xaeqXgV4Gp/Mv6EPqfrSIC4lQ75Szau2n5cfs6qT5g/FaV7bl3yplB3/vFiqMyc3jz2n/sW7krNixZrouEQevLSkJMhn7YfNXIJEosX8cYOxKObqw+EL1/h9zQ7a1KvJmB4dNY73Zc3qyj9zdh45+VLsuew7fqbgM6fgvI/V/LwfP7g308cNU/r3eRv5l5ARvbswedQgjeNv4V+NfKmU7ade3Cifk5vHrrPX8HFzVKxYExWfpLSkJMhn7YfODkJLS4uFo/tgaaL+75KLrTUeTracvH6HxJfOt/O3wolOSKZu1eKfIFts/FWcyZfJ2H4t/EX8efnsuhmJj72VYsWaqOR07se9uOrTqmpF/vy0kco/gAaV7Pnz00Z4O6h+wThw6wG2pobUcHozy3/+f3Xq1CkCAwOV7sNr06YNUqlUZfLxZYV/e01MlCdtjI2Nkb2yYltJxIy88FaNHTsWf39/1q1bx5QpU0hLS8PMzIxq1arx22+/0a5dO7Xt3N3dmT59OgsXLmTo0KH4+/vz+++/07Gj8h+tQYMGYWlpSVBQENu3b8fIyIgaNWpgZSUf6NrZ2bFmzRpmzpzJN998g0QioX79+owfPx5jY/kfSh8fH1atWsWBAwdIS0vD1taWAQMGKK1//+OPP+Lq6sqmTZtYsGABRkZGuLq60rq15k9RLE41j0o0C6zNonXbSExOxcHWhgMnzhIVG8+Eof0V9abOW8a1W6Gc2/a3oiwtPYMtB44CEHxXPiDbeuAoxkaGmBga8llbed7n1ZC7zFm5jiZ1a+FkV4HcvDxu3Ann5MUrVKnkQqtGqk8ALIuKQ3uga2aqWD3Gpl1TyjnIB0kPFqwhLyUNz1/H4NS7M/+4NyPzoXxQGbXtEIkXruG7fBrGXu7kxidScXB30NYm7Od5Sse4M34mtXYsIuDASp5t3odJNQ9chvbg8cotpN0t+8OgALwru9G8rj8LN2wnISUFJ1sb9p08T1RsHD981VtRb8r8v7l2O4wLm5cqytIyMth84DgAN0ML+v7gcXnfGxnweWv5FZ3Tl28QtG0fTev6Y29jRUpaBofPXOTe42cM6f6J2tVDSsvL04PG9QNZvno9SckpONjZcuifE0THxPLNyBdfPKfPnseNkNv8s2eroqxj29bsO3yM73+exuefdEBHW5utO/diYW5Ol08+VtTT09VlcL9eTJ89n1HjJ9GyaSNiYuPYvmc/PtW8aBhYhif5vqS6iz0f+Xkyd88pEtIycCpvzp5/b/EsPoXJ3V88cefHtfu4HPGYG3PHKco+m/43AR4V8XSwwdSwHI9iE9lx/iZ5UimjPn6xNvrliMfM2HaUFr6eVLS2IDc/n6v3nnDsZhjVnG1pX7samvJ2r0iLOr7M37KPhJQ0nCqUZ++ZSzyLS2DiwK6KepOWrOfq3XtcXvOnomzkrKU8jYmnd7umXA+L5HrYi/PX0tSEuj7yL3ch9x7y05L1mBkbUbuaBwfOKS/fWL2yK442ZU9PqebhRrPAWixav53ElFQcbW3Yf+IcUbHxfD+0r6Lez/NWcO12KOe3rlCUyT9zjgFws+AzZ8uBY5gYGWJsZKgYrAf4easct/B5FTWqeuJVsMSrJnzcnGhZy5t52w/L+97Gij3nrhEVn8hPfTsp6k1csZUrYQ+4tvzFSl3D5qziSWwifVs35Fr4Q66Fv3h6tJWpMXWrvRigf9O1LUP+DKL/jGV82qg2aZlZrD1yjooVyvN5kzqax+9QnpZVnJl34joJGVk4WZiwJziSqOQ0fmr34orLxD3nuPIohmvfyx9q5lreDNfy6j8vHMyNVWbiASJikgiPSaJfYFWVBSmEsomMjFS5um9qaoq1tbXiqr46dnZ2NGjQgMWLF+Pq6oqtrS2nTp3i7Nmz/P7772WKQQzkhbeuSZMmSss5qrNmzRqVsk6dOtGpUyelstBQ1ZvoPv30U7VpMoWqVKnCypUri9zetGlTmjYtPn9WS0uLnj170rNn0U+WfNMmjhyE7YbtHDx5jtT0dCpVdGLWhFHUqFb8bG1qegbLNuxQKtuwW/6EVFtrK8VAvlJFR2p6V+H0pWvEJyYjQ4ZDBRv6fd6BHh3bqF25pSzcRvfH0MVR8bNd51aKhzQ9Xb+bvKKWEpRK+ffjL/GaMQ7X4b2QGOiTfDmYGwMnKNJqCsXsP8GVz4dTeeJwqs2ZSE5sAhHTlxD+y4LXin3S8P7YbtrFwVMXSE3PwN3ZkT++G0GNqh7FtktJy2Dppl1KZev3ymfGba2tFAN5d2cHXBztOHj6AkkpaejqaFPZxYlfR39J88DXy3UGmDBmBCvXbuTI8ZOkpqXj5lKR3yZNwNdb/QPYChkaGjD7tyksWP436zZtQyqT4utdjWED+2JupjxY+KhZE3R0dNiwdSdL/l6DsZER7Vu3ZGCvLxT3xGjil17tWLDvNHsv3SIlI4vK9tbMHfwp/u7FpzR1qe/H6duRnL1zn4ysHCxMDAms4sLAjwKpbP9i1rGyXXlqV3bmRHAEcSlpyJA/1XVwq3r0aV5H7cohZTFl8BfYbTvA/rOXSc3IxN3JjjljBlKzSvFPSQ57JE8fWr3vuMq2mlUqKQby958+Jzcvn8TUNH5etlGl7k+Dumk0kAeYNGIgSzfu4ODJ84rPnN8njKRG1ZI/c5Zu3KlUtmGPPNXD1tpKMZB/26YO+JSFO83Zd+E6KelZVHaswF8jeuHvUXz6SNhj+T02QQdPq2zz93BRGsjXruLG/K97s3DnMebvOEI5PV2a1PDi689aFZsKVar4O9Rj4ckb7Au+T0pWDpVtLPirSxP8ndWnZ2hq/y3552ibMixV+b7QesM3SRdq3rz4c/TYsWNqy1NSUjA1VU0lNDMzU7mv71Xz5s1j9OjRiglNbW1tfvzxR1q1KtvDDLVkZZ3DFwThjYkPOfeuQ9CYlXc99ulqngLyLrXLDSXxxsmSK76nLHwb8zQsuOSK7ykHDx+yDq0oueJ7qFyrAaT+u+9dh6ExkzrtSAg+867D0IilTwMyTm9512FozLDh52Ss+rnkiu8pwz6aLRX9Jt35VLPlPUsyPEla7PaiBvLVqlVj1KhRfPnll0rl7du3p0aNGkydOlVtO5lMxtdff83du3cZMWIE1tbWnDt3jhUrVjBjxowisxXUETPygiAIgiAIwv9bRQ3US2Jqaqr0FPhCLy+woc6JEyc4ePAgu3fvxtNTPiEWEBBAfHw806dPL9NAXtzsKgiCIAiCILz3tCRab+Wfptzc3FRy4VNTU4mNjcXNza3IdhEREWhra+PhoZyu6eXlRUxMDJmZpV81TgzkBUEQBEEQBKGMGjVqxLlz50hJebEk6cGDBxULaxTFwcGB/Px8lfv+bt26hZWVldLT5UsiBvKCIAiCIAiCUEbdunXDyMiIYcOGcebMGbZt28bMmTPp1q2b0hryffr0oWXLF/n9jRo1wt7enpEjR7Jr1y7Onz/PrFmz2LFjR5kX1RA58oIgCIIgCMJ77317squZmRmrVq1i6tSpDBs2DCMjIz777DNGjx6tVE8qlZL/0vMrjI2NCQoKYvbs2fz++++kpqbi6OjI+PHjxUBeEARBEARBEP4LlSpVIigoqNg66pbYrlixInPmzHnt44vUGkEQBEEQBEH4AImBvCAIgiAIgiB8gERqjSAIgiAIgvDee99y5N8HYiAvCIIgCIIgvPe0JCKR5FWiRwRBEARBEAThAyQG8oIgCIIgCILwARIDeUEQBEEQBEH4AIkceUEQBEEQBOG9J9EWN7u+SszIC4IgCIIgCMIHSAzkBUEQBEEQBOEDJFJrBEEQBEEQhPeeWEdelZiRFwRBEARBEIQPkJZMJpO96yAEQRAEQRAEoTiRfdu/lf26Be19K/v9L4jUGkF4hxKCz7zrEDRm6dOAxBsn33UYGrHwbcw+Xc93HYbG2uWGknpp/7sOQ2Mmtdvy/M6Vdx2GRip4+ZNxcuO7DkNjho278Sj8zrsOQyPOlb1IP7/zXYehMaPATjwLvfmuw9CYvWf1dx2CeLKrGqJHBEEQBEEQBOEDJAbygiAIgiAIgvABEgN5QRAEQRAEQfgAiRx5QRAEQRAE4b0nlp9UJQbygiAIgiAIwntPDORVidQaQRAEQRAEQfgAiYG8IAiCIAiCIHyAxEBeEARBEARBED5AIkdeEARBEARBeO+JB0KpEj0iCIIgCIIgCB8gMZAXBEEQBEEQhA+QSK0RBEEQBEEQ3nti+UlVYkZeEARBEARBED5AYkZeEN5TObm5LNu4k4OnzpOSnoG7syODu39CHd9qxbZ7+DSaHYdPcCs8krD7D8nJzWP7whnY2ZQvtt2T6Bh6jJ5ITm4eK6dPxMvd5bViX7ppNwdPXyA1LYNKFR0Y3K0TAdWrFh/7s2h2HD7JrYj7hN5/JI99/m/Yq4m907AJRMfGq5R/0qIR333ZU+PYAbSNDHEbOwDzOr6Y1/ZBz9KcGwPG82T1jlK11zEzwWv6t1To2BJtw3IkXwrm9rjppFy7rVLXpn0zPCYNx9jLnZyYeB6v2k7ErwuR5edrFHtObh6Ltx1g/5nLpKZn4u5sx5DP2lLXx7PYdv9cusmRC9e4HfmIuORUKlia07BGNQZ2+ggTIwOluocvXOP01VuE3HvI4+dx1KxSiaU/DtcoXtX4c1mxfiuHT5wmNT2dShWdGdijC7X9fEpsGxufwPwVa7h0PRipTEYNn6qM6N8Te9sKSvUSkpJZsnoD569cJyMzk4qODvT8tANN69d9A/HnsWj3P+y9cJPUjEwqO1RgWKfm1K1aqdh2x67e5vDlEG49eEZ8choVLE1pWN2DL9s1xsRQuf+zc3NZe/Q8+y7cJCouCROjcvi6OfFVh6ZUsrd5jdhzWbV2PUePnyAtLR03l4r07dUD/xp+JbaNi4tn0fIVXLl2HZlUhm91H4YM6o+drW2RbUJu3Wb0d98DsHXdaszMTDWOXR5/Hot2HGbfuaukpmdS2cmOoZ0/oq63R7Htjl0O4fC/N7h9/wnxyalUsDSjoa8Xgzo0Vzn3X/Y4Jp7Pv/+TnLw81v40gqqujq8Zfy5/r9vEkROnSE1Lw82lIgN6dKNWDd8S28bGx7Ng+SouX7+BTCrDz6cawwb2VTr3Dx47zoy/Fha5j+/HjKRlk4av9RqE/56YkX+PzZs3D09PT8U/Hx8f2rRpw7Jly5BKpQA8efIET09PDh48+J/F9euvv9KsWTPFzxcvXlSKs0aNGnTq1ImtW7cik8n+s7j+1/wyfyUb9h7ho4Z1Gd2vOxKJhDG//cWNO+HFtgsJi2DLgaNkZGVR0cGu1Mf7K2gj2trarxs2AFMXBLFh3xFaNQhgdL+uaEskjJk2l+t3i489OCySzQf+ISMzC5dSxO7h4sRPw/sr/WvfrP5rx69X3gKPicMxruJG6s3QsjXW0qL27qXYd2vPw4VruTthFnrWltQ9ugZD94pKVa1bNaLWtgXkJqVy6+upRO8+SuXvh1Dtr4kaxz55yXrWHThBm3r+jO3VCW2JhFG/L+V6aGSx7X5dsZn7z57Tpn4tvu3VmXrVq7D5yGn6TZlDVk6OUt2tR89y8moIFazMMTUy1DhWdabNXczm3ftp2bg+Iwf0RiKRMG7qTG7evltsu4zMLEZN/IXrt+7Q87OO9O/+KeGRDxjxw1SSU1IV9dIzMhg2YTInz1+iw0fNGNq3B4YG5fhp1lyOnDz72vFPCtrB2iPnaRvgw7dd2yCRSBgxdy3Xwh8W2+6XNXu4HxVH24DqfNutDfWqubPp+L/0mb6crJxcpbrfL9/G4l3HqeXhwrfd2vBpo1pcDX9In+nLeRafpHHss2bPZdvO3TRv0pihXw5AIpHww+SphNxS/QL6sszMTL75fiI3Q27R/fPP6N2jOxGRkYwd/wMpKSlq20ilUuYvWUa5cuU0jvdVPy3fzLpDp2lTtwbf9OiARKLFyNl/cy3sfrHtfg3axv1nMbQNrMG3PTpQz8eTTcfO0eeXBSp9/7I/1u9BW/vNDaNmzFnAll17adG4AcMH9kNbImH8z9MIvn2n2HaZmZmM+WEKN0Nu0+OzzvT9ogsRkff5+vuflM796tWq8v3oESr/KldyRSKR4O/r/cZey9uiJZG8lX8fMjEj/54rV64cq1atAiArK4uLFy/yxx9/IJPJ+PLLL99xdMqmTZuGm5sbKSkpbN26lR9++IG8vDy6dev2rkP74NwKj+TI2X8Z3utzenRsDUCbxvXoMWYS89dsYdlv3xfZtkEtPw6vmoeRgQHrdh0k/MHjEo934XoIF6/fokfH1gRt2/t6sUfc58i5S4zo+Rk9Onwkj71RID3GTmbB2m0s+2V8kW0b1vLlSNBfGBmUY93uw4SVELu1pTltGr3+LOqrsqNiOOpYn+zncZj5e9PgwrZSt7X7tDWW9WpypetIorcfAiBqywGa3D6Ex6QRXO/9jaKu14xxpASH8m+b/ooZ+LyUdNzHD+b+vNWklzD4flXIvYccvnCNUd070KtdUwDaNahN1/EzmbtxDyt/GlVk2xkj+1KrqrtSWRVXJyYvWc/Bs1fp1PRFP/88pAc2FmZIJBK6jJ9RphiLczssgmOnzzOk7xd079QegFZNG9J35HcsWrWBRTOmFNl254EjPHkWzZJZU/GqLJ/9DqjpS9+R37Fp1z6+7CX/HNp96BhPo54z++cf8K8uv7rVqXULvvpuEguC1tGkXgC6upr9aQy5/4RDl0IY/dlH9P5I/oWyfaAvn09eyJxtR1g1fmCRbWd91YVanq5KZV4V7Zn09w72X7xJ54b+AMQkpvDPtTv0/qgeoz9rpahb070iX/4ZxD9Xb9OzZb0yx343NIwTp07zZf++fN65EwAtmzVl0LCRLPt7FX/9XvTvefe+Azx99oz5f87C06MyALX9azJo2Ei27NjFgD69VNrsO3iY2Lg42nzUgh27X+8zByAk8jGHLt7g665t6d2mMQDt69Xk8x9n89fm/QT9OKzItjOH9aSWl/IVEy8XByYt28yB89f4pHEdlTbngkM5HxJGnzaNWb7nn9eO/05YOP+cPstX/XrR9ZMOALRq1ph+w8ewJGgt82f+WmTbnfsP8+RZFIv+mEaVyvL3cIB/DfoNH8PmnXsY1PsLAOxtK6hcncrOzmbO4uXUrO6NpYXFa78O4b/3YX8N+X9AIpHg5+eHn58fdevWZdSoUTRv3pzDhw+/69BUVK5cGT8/Pxo1asTs2bNxcXFh7dq1RdbPysr6D6PTzLuK8fiFK2hLJHRq2VhRpq+ny8fNGhASdo/ncQlFtjUzMcbIoOjLwa/Ky8tj9soNdGnXAkdb69eKG+CfwthbvLhEWxh7cFhk8bEbG2FkULYZuty8PDKzsjWOVx1pTi7Zz+M0amvbuRVZ0bFE73jxHs2JS+TZ1gNU6NAciZ4uAMZelTCpVpnHyzcrpdE8XLweLYkEu86tVPZdkmP/3kBbIuGTpoGKMn09XTo2CeBm+AOi4xOLbPvqIB6gaS15Osv9Z8+VX6OVBZK3MIt18ty/aEskdPjoxRU/fT092rVowq3QcJ6rSaUqdOL8RapUdlMM4gEqOjpQs3o1jp+9qCi7cTsUczNTxSAe5J+zTevXJSExieu3ip/9LM7RK7fRlkgUg24AfV1dOjaowc3Ix0QnJBfZ9tVBPECzGl4A3I+OVZSlF5zrVqbGSnXLm8l/1i84v8rq9NlzSCQS2rb+SFGmp6dH65YtuH03lJjY2GLansezcmXFIB7A2cmRGr7VOXVG9SpHSmoqQWvX0adHd4yNjDSK91VHLwXL+75JgKJMX0+XTo1qczPiEdHFXKl4dRAP0LSmfHb6/rMYlW25efn8vm4P3Vs2wNHG6vWDB06evYBEIqF9qxaKMj09Pdq2bM6tu2HExBb9eXTq3HmqVK6kGMQDODs6UNPXhxNnzhV73HOXrpCRmUnzxh9ISo2W1tv59wETA/kPkJGREXl5eUVul0qlLFy4kGbNmuHt7U3r1q3ZuHGjSr1Lly7RrVs3qlevTkBAABMmTCApKUmpzvPnz/nqq6/w9fWlYcOGLFu2rFQxamtr4+XlxZMnTwDYvn07np6eXLt2jX79+uHn58fMmTMBiI6O5ptvviEgIIDq1avTo0cPQkJClPZ37NgxOnfuTI0aNahVqxadO3fm5MmTpd7u6enJihUrlPYZFBSEp+eLvOHCFKETJ04wcuRIatasyahR8hnMlJQUJk+eTIMGDfD29qZz586cOXOmVH2hibD7j3Cyr4DRK7mxVd3lf+zDHjx6Y8fauO8oqekZ9Pu0/RvZX9j9xzjZqYvdRb69FFcISutyyF2a9BxO094j6DRsApv2H3tj+9aUmZ+XPBf+lbSy5EvB6BgZYuQh/x2a+snvF0i6EqxULzsqhszHUZj6eZX52KEPn+Jsa42xofKXoWpuzgCEPXxapv3FJ8svy5ubvJnBVknC7z/A0d4OI0PldJ3CwXnE/Qdq20mlUiIfPKZKJTeVbV6VK/E0+jkZmZkA5Obmoq+np1KvnJ4+AKH3ik/DKM7dx1E4V7DC+JUvo94u8tzp0MfRZdpfXHIaAObGL/rD0dqSChamrDl8jpM3QnmemEzI/Sf8um4vDuUtaF1bs/SIiMj7ODrYq/R94eD8XqT6fpH3/QM8KqsOhqt4VOZZVDQZGZlK5UFr12NpbkG71mX/slqU0EdPcbYtr9L31dycCrY/K9P+ijv31x8+Q0pGJgM7NFPZpqmIyPs4Oaie+1U85IPz4s79ew8e4eGu2v9eld15Fv1cpf9fdvTEafT19GgUGFBkHeH9JlJrPgCFg/bC1JrDhw8zePDgIuvPnDmT1atXM2TIEGrUqMGJEyf46aefyMvLo2dP+U2AISEh9OvXj4CAAP766y/i4uL4448/iIiIYOPGF7nSQ4cO5fnz50yePBkTExOWLVtGVFQUOjolnzpPnjzBxkb5xquxY8fStWtXBg8ejIGBAcnJyXzxxRcYGhoyceJETExMWLNmDX369OHw4cNYWVnx6NEjRo0aRbt27Rg7dixSqZS7d++SnCyf3Sppe1lNnDiRDh06sGDBAiQSCTk5OfTr14/4+Hi+/vprKlSowO7duxk8eLDiC8qbFp+YhJW5mUp5eQtzAOISkt7QcZL5e+seRvTuojLw1nifScmUt1AXu7wsLjHpjRzH3dkB3yqNqWhvS3JqGvtOnmd20CZiE5IY3vPTN3IMTejbWZNw5rJKeVZUTMF2G1JDwihXcPUjO0p1pjM7OpZyGty0GJeUQnlz1RsGy1vIy2IT1ecrF2XVnmNoSyQ0r1PyzXZvQnxiElYF5/jLrCzlZUWdOylpaeTk5qpvW5AuEJeQiLODAc4O9ly5GUJ0TCy2Ni+uQN28I8/Bj4sv+opRSeKS07A2M1YpL5wtj00qW/8HHTqDtkRCi5ovrh7o6mjz+1dd+X75Nr5esF5R7lXRnqDvBqjcGFtaCQmJalMrrCwtAYhPUH81JzU1jdzcXLVtLS0tCtomYGjoAEDk/QfsO3CIXydPfGP35ADEJaVS3sxEpdy6oKzMfb//hLzvaynfZB2XlMry3cf4uls7lS8NryM+MUl9/ys+84vo/zR5/1sV0/9xCQk4F/T/y1JSU7l09Tr169bG8A19/gv/PTGQf89lZGRQrZryKiVt27YtMj8+ISGBtWvXMmDAAEaMGAFAgwYNSExMZMGCBXTv3h1tbW0WL16MtbU1ixcvRldXfinWzs6OAQMGcPLkSZo1a8apU6cICQkhKCiIwED5pfqAgAAaN26Mubm5yrGlUil5eXmkpqayadMmgoODVb5wdOvWTSn2uXPnkpKSwpYtW7Cykl+iDAwMpFWrVqxYsYJx48Zx+/ZtcnNzmThxIsbG8j+IDRu+uAxY0vayatasGd9++63i523btnH37l127dqFu7u7Yv8PHz5k4cKF/PXXXxofqyjZObno6apeItcruGyeXcwNWGWxYO1WHCpY06H5m7usmp2TozbHuPD1vKnYf/9OeZWU9k3rM/q3uWzYd4QubZphY/Vu8j21Dcohzc5RKZdm5RRsl8/8SgoGAerq5mdlo2OqOiAsSXZObhF9Ly/Lzi193x88d4VdJy/Su30znN9AylVpZGeXcO6o6St5ufx16Rb3nilo275lU3YdOspPs+YyfEAvLM3MOH72AqcvyL98ZeeoP0ap4s/JRVfNJIe+ov+LvpL6qgMXb7LzzFX6tqpPxQrK6RsmhgZ4ONnSwr8qPm5OPI6J5+8DZxi3ZDOLRvdGX00/lBx7drH9l5OjPn0tu6BcbVtdPaU6AAuWLKOOf01q1axR5hiLI//MLObcL8PnzoHz19h56hJ92jbG2VZ5xay5W/bjYG3JJ41qv17Ar8jJySniM1/ehzlFnvvycvX9X/i7U9/25NkL5Obl0eJDSatBrCOvjkitec+VK1eOrVu3snXrVtavX88PP/zA6dOn+fHHH9XWv3nzJrm5ubRu3VqpvE2bNiQkJPDgwQMALl++TPPmzZXe/A0aNMDU1JQrV64o9mViYqIYxAOYmJhQr576G6m6dOlCtWrVqFu3LvPmzaNbt24MG6Z8g1GTJk2Ufj579iwBAQGYmZmRl5dHXl4eEomE2rVrExwsTznw9PREW1ubb775hn/++YfU1FSlfZS0vazUxejh4YGLi4sixry8POrVq6eI8U3T19MlR82gK6fgj5GmebAvCwm7x8FT5xnVt9sbzXfW19MjV82ApfD1vInY1dHS0qJbuxbk50u5cquMK828QfmZWUj0VVM3JOX0CrbLBzXSTPn9F+rqapfTV2wvC3093SL6Xl5W2gHetbv3mLpsE4E+VRj6edsyx6Epff0Szh01fSUvl7+u3OLeMwVtK7k4M2nMcJ5FP2fY+Ml0HzKarfsOMWKA/IZMg9dYRUVfT5dcNWmP2Yr+L93c2dXwh0xZvYt61dwZ1qm50rbUjCwGzFpJdTdHRnZuSVO/KvT+qD6zvurKtYhH7Dp7TcPY9YvtP72C1CN17aCIvs/NUapz4tQZbt8NZfDAfhrFWBz5Z2Yx534pP3euht7n55VbCfT2YNinyqk/NyMesu/cNcZ+8fEbv0dET0+viM98eR/qFXnuy8vV93/h705926MnT2NqYkyA/5v9UiX8t8SM/HtOIpHg4/Pi0p6/vz/5+flMnz6dfv36YfhKPl1hOkn58sqzCIU/F+bAp6SkKGbAX2ZlZaXYR0xMDJYFl1VfraPOjBkzqFSpEsbGxjg4OKj98Hg1rsTERK5fv65y1QHA2Vme1+vq6srixYtZsmQJw4cPRyKR0KBBAyZNmoS9vX2J28vq1deXmJjI7du31cb4Ji8NK8VgYU6smkuphakF5QtSDV7HgjVb8PWqjL1NeaJi5DdSJaXIc3LjkpKIjo3H1rrsN3JZmZsRqyb1Jy6x4NxUk/7wplQoL5+FT0lLf2vHKEl2VCz6amawy9nZFGyXp9hkFdzAqG9nTdYT5dxpfVtrki7dLPOxy5ubEqvmhsq4gpQaa4uS1+kOe/iUMX+uoJKjLTNG9UXnLZ3j6lhZmBOr5obc+ILzqahzx9TYGD1dXeLVpN7EJ8r3V97yxRWaJvUCqF/bn4gHD5FKpXi4uXItRL7EopN96ZdsfVV5M2NiklQnEgpz3a3VpD29KvRxNF8vWE8lextmDe6i0v/Hrt4mPiWNxr5VlMprebpgXE6fG/ce06WJ6iorJbG0tCAuXvVm4vgEeaqRlaX6K1wmJsbo6uqSkKj6e0so+AwrTM9Z+ncQjerXQ0dHh+jn8huo09Ll79XYuDhy8/Iob6X6N6c0ypubEKMmdSy2INe9NH0f9ugZo/9aRSVHW2YN76nS939tPkANDxccylvwLFbeL0kFnzWxSSlExSdip+GVQCsLc+ISVNO64hWf+UX0v7G8/+OL6f/yav6OP4+NJfj2Xdq3alGqVFnh/SV+ex8gNzf5DV0RERFUr15daVthykt8fDwVKrxYZiouLk5pu5mZGfHqPrTj4zEzk+cy29jYkKDug0VNO4BKlSopfekoDTMzMxo2bKi4qfRlL38RaNSoEY0aNSItLY1Tp04xbdo0JkyYoFias6Ttenp6KjMWRa1vrPXKHexmZmZ4enry669FL//1plV2ceJqyF3SMzKVctdvhctvOPNwcX7tY0THJRAdG0/nod+pbBs3fR7GhgYcWT2/zPv1cHHi6q3QYmJ30jzoEjwtWGnGwlQ1V/a/knLjLhYN/OUrIbx0w6t5nerkpWeQXrCmdcoN+eoo5v4+JF96cWVH384GAyc7Hi3fXOZjezo7cOV2BGkZWUo3vIbck69h7lFRNU/2ZU+exzFi5hIsTI3569svMSynfhb2bXF3rci14NukZ2Qo3fR3OyyiYLuL2nYSiQS3ik7cvae6XOftsHvYV7DB8JWVnHR1dZRWuLlyQ36Dfa3XWEvb08mWy6EPSMvMUsqfDrn/RLG9OI9jEhj+1xosTYyYN7Kn2v6PT5V/KSh8lkghmUxGvkxGXr5UpU1pVHJz5frNYJW+vxsWptiujkQiwdWlImHh91S23QkLw862giL/OjY2jn9OnuKfk6dU6g4ZNQY3VxeWzJujUfweTvZcvhOp2vf35AsDeDoXP6nzOCae4X+sxNLUiHmj+6nt++j4JKLiE2n/repSnKP/WoWxQTlOLSp6idTiuLu5cC34lkr/3wmVP3uj+HPfmbAIdf0fjv1L/f+yf06dRSaTfVBpNYJ6IrXmAxQeLn9jW6i5ucXHxwddXV2VB0QdOHAAKysrXFxcAPnM/rFjx5RWvzl79iwpKSn4+/sr9pWamsr58+cVdVJTUzl3rvjlrMqiXr163Lt3T/El4OV/6m4iNTY2pm3btrRr145791Q/uIrabmtrq1K/tK+jXr16PH78GBsbG5UYy/rFpbSa1a1FvlTKziMvVt7Jyc1l3/EzVKvsRoXy8hmW6Nh4HjyN0ugY4wf3Zvq4YUr/Pm8jv4w/oncXJo8apNF+m9atKY/96Gml2PeeOEe1yq4vYo/TPPbktHTyXxnI5OXlsXrnAXR1dPD3fvM3IKujb2uNkacbWi/NaEVtP0g5W2tsP3mxjJ+ulQV2n7YmZu9xpAWpCmm3I0i7cw+ngV3gpcv0FQd3RyaVEr297A95a17Hl3yplB3HX7xnc3Lz2HPqX7wrVcS2YLYwOi6RB68sKRmXlMKwGYuRSCTM/+4rLDTI0X9dTeoFkC+Vsvvwi3W5c3Jz2f/PSap6uFOh4ArR89g4Hj5RXoGncb063A2P5G7Ei8H8o6fPuBZ8iyb1i1+R4/GzKHYdOka9WjVwKsND1F7VomY18qVStp++8lL8eew6dw0fV0dsLeWTJFHxSdx/5SbnuORUhs5ZjZZEi4WjemFZxEpBFQuecnzokvLKXiduhJKZnUMV5+K/LBSlYf16SKVS9h98adnU3FwOHfmHKp4e2FjLrzLFxMTy6PETlbah4eGEhkcoyh4/ecr1G8E0avDiAW2Tfxiv8q9JwwYAjBsziiGDBmgUO0CL2j7yvj/xYqnRnNw8dp+5jLebE7ZW5gBExSeqLCkZl5TKsFnL0dLSYsHYAUWe+z/268wfI3or/evWQp5qOrprO34drPkzUxrVC0QqlbL30NGX4s/l4LHjeHlUxsZa/nt/HhvLo1fP/fp1uRt+j9CXvkw9evKUqzdDaFzE04qPnjxDBevy+FStonb7+0o8EEqVmJF/z0mlUq5fvw7Ic+Bu3brFokWLcHd3p1atWjx/rvzH2NLSkp49e7JixQr09PTw8/Pj5MmT7N27l4kTX6wS8NVXX9GtWzcGDx5Mr169FKvWVK9encaN5WuXN2rUiGrVqvHtt9/yzTffYGJiwtKlSxU3lL4Jffv2Zc+ePfTs2ZPevXtjb29PQkICN27coEKFCvTt25eNGzdy/fp1GjZsiLW1NU+ePGH37t3Ury//A1HSdoBWrVqxatUqfHx8cHV1Zffu3Sp9V5ROnTqxceNGevfuTf/+/XFxcSE1NVVxk+3YsWPfWH8UqubhRrPAWixav53ElFQcbW3Yf+IcUbHxfD+0r6Lez/NWcO12KOe3vlhaMy09gy0H5Msw3rwr/8O65cAxTIwMMTYyVAzWA/xUZx7T0jMAqFHVE6+C5SLLyruyG83r+rNww3YSUlJwsrVh38nzRMXG8cNXvRX1psz/m2u3w7iweemL42dksPnAcXnsofLYtx48jrGRISZGBnzeWr7c2+nLNwjato+mdf2xt7EiJS2Dw2cucu/xM4Z0/0Ttij9lVXFoD3TNTBWrx9i0a0o5B/kg6cGCNeSlpOH56xicenfmH/dmZBYs7Ri17RCJF67hu3waxl7u5MYnUnFwd9DWJuzneUrHuDN+JrV2LCLgwEqebd6HSTUPXIb24PHKLaTdLdvDoAC83SvSoo4v8zfvJSElFacK5dl7+hLP4hKYOOjFIGPS4nVcvXuPy2tnK8pGzlzC05h4erdvxvXQSKUnwVqamVDX58WXo6t373H1rnzQkJSSRlZ2Dst3ygeANatUomYV1aXwSqOqhztN6wWwdM0mkpJScLCrwMHjp4mOieO74S9ukv91ziKu37rDqZ0vVm35pE1L9h4+zndTZ9KtUzu0tXXYvHs/FuZmdOvYTuk4vYZ/S9P6AdiUtyIqJpZdB49iamzE2CGaDyQBfNwcaelfjXnbj5KQko6TjSV7zl8nKi6Jn3p3VNSb+PcOroQ94NrSF7O3w/5ay5O4RPq2qs+1iEdci3ixxKyVqTF1q8r7tLGvB5XsbVi67yRRCUn4uDryODaBTcf/pbyZCZ3q19Qodi9PDxo1qMeKVWtISkrC3t6Ow8eO8zwmhrGjXtxYPuPPOdwMucWRvTsVZR3atuHAocP8OGUqn3/SCR0dbbbu3I2FuTmfffLiddcPVB1UFi5rWcffHzOzktNfiuJTyZmWtX2Yv/WgvO8rWLH3zBWi4hKZ1P8zRb1JSzdzJTSSq0EvZtWH/7GCJ7EJ9GnbmGvhD7gW/kCxzcrUmLreHgAEFvz3ZakFSzv6V3GjqqujxvFX9axM4/qBLFu9nsSkZBzsbDn0z0miY2L5dsQQRb1ps+dzI+Q2x3dvUZR1bNOKvYeOMuHnaXT55GN0tHXYsmsPluZmdOn0scqx7j98ROSDh3zxaSeVK9DCh0cM5N9zWVlZdO3aFQAdHR1sbW3p0KEDw4cPV3uXOsC4ceMwMTFh69atLF68GAcHB6ZMmaL0hFVvb29WrlzJn3/+yYgRIzA0NKRZs2Z89913isG+lpYWCxcu5KeffmLSpEmYmpoqBv3Hjr2Z9botLCzYtGkTc+bM4ffffycpKQkrKyt8fX1p2bIlIL+Z9fjx40ybNo2kpCSsra1p166dIh2npO0gX0YzPj6eBQsWoKWlRdeuXenduzfTp08vMUY9PT1Wr17NvHnzWLx4MbGxsZibm1O1alW++OKLN9IP6kwaMZClG3dw8OR5UtPTqVTRid8njKRG1eJnm1PTM1i6cadS2YY98kGWrbWVYiD/Nk0a3h/bTbs4eOoCqekZuDs78sd3I6hRVfUP4ctS0jJYummXUtn6vUeAgtgLBvLuzg64ONpx8PQFklLS0NXRprKLE7+O/pLmgbXeyGtwG90fQ5cXf5jtOrdSPKTp6frd5BXcT6BCKuXfj7/Ea8Y4XIf3QmKgT/LlYG4MnKBIqykUs/8EVz4fTuWJw6k2ZyI5sQlETF9C+C8LNI57ylc9sNt6gP1nLpOakYm7kz1zxg4qcXAdVrDO9uq9qk+prFmlktJA/tKtcJbtOKRUZ/HWAwAM+qSVxgN5gO+/HkKF9Vs4dPIMaWnpuLk4MePHb/CrVvy6+oYGBvz1y4/MX7mG1Vt2IpXKqOHtxfABvTB/ZYDo7urM/mMnSUxKxszUhKb1A+jf7TMs3sAXwKn9P2HhLjP2XbhBSkYWlR0r8NeIHvh7uBTbLqzgPomgQ6oPUPL3cFEM5HV1dFj5bX+W7jvJmeAwDv4bgmE5PZr4VWHEJy2weI01/78b8zVBa9dz9PhJUtPScHNxYeqkH6nurXp/0MsMDQ34fdovLFq2knWbtiCTSfH19uarQQMwN3v9Pi2tnwd1ZeH2w+w/d5WU9EwqO9ky5+u++HuqPl/gZWGP5VcGV+0/qbLN39NNMZB/274fPZyV6zZy5MQpUtPSqeTizG8Tx+PrXbXYdoaGBsz5bQoLlgexdvM2pDIZft7VGDagj9r+P3pCfrW0eeMGb+V1CP8tLZnslaeWCILwn0kIfnsPlXrbLH0akHhD9Q/fh8DCtzH7dP+b9Ju3oV1uKKmX9r/rMDRmUrstz+9cKbnie6iClz8ZJ1UfsPehMGzcjUfhmj+99l1yruxF+vmd7zoMjRkFduJZaNlvYn9f2HtWL7nSWxY19u1Mntn9sb7kSu+pDzsxSBAEQRAEQRD+nxIDeUEQBEEQBEH4AImBvCAIgiAIgiB8gMTNroIgCIIgCMJ770NfKvJtEAN5QRAEQRAE4b2nJRHLZb5KfLURBEEQBEEQhA+QGMgLgiAIgiAIwgdIDOQFQRAEQRAE4QMkcuQFQRAEQRCE957IkVclZuQFQRAEQRAE4QMkBvKCIAiCIAiC8AESqTWCIAiCIAjC+0+sI69C9IggCIIgCIIgfIDEQF4QBEEQBEEQPkAitUYQBEEQBEF472lpiVVrXiVm5AVBEARBEAThAyQG8oIgCIIgCILwARIDeUEQBEEQBEH4AGnJZDLZuw5CEARBEARBEIoTN2nAW9lv+Z9XvJX9/hfEza6C8A4FRzx/1yFozMe9Ak/Dgt91GBpx8PAh9dL+dx2Gxkxqt2Wfrue7DkNj7XJDydow412HoZFy3b8ja/tf7zoMjZXrPIqUq0fedRgaMa3Zkqth8e86DI3V9LAi6u71dx2Gxuyq+L3rENCSiJtdXyVSawRBEARBEAThAyQG8oIgCIIgCILwARIDeUEQBEEQBEH4AImBvCAIgiAIgvD+k0jezr/XcO/ePfr164efnx/169dn5syZ5OTklKrt8+fP+e6776hbty7Vq1enTZs27N69u0zHFze7CoIgCIIgCEIZJScn06dPH1xcXJg3bx7Pnz9n+vTpZGVlMWnSpGLbxsTE0LVrV1xdXZk6dSrGxsaEh4eX+ktAITGQFwRBEARBEIQy2rhxI+np6cyfPx9zc3MA8vPzmTJlCoMHD6ZChQpFtp01axa2trYsX74cbW1tAAIDA8scg0itEQRBEARBEN57WhKtt/JPU6dOnSIwMFAxiAdo06YNUqmUs2fPFtkuLS2NAwcO8MUXXygG8ZoSA3lBEARBEARBKKPIyEjc3NyUykxNTbG2tiYyMrLIdrdu3SI3NxcdHR169uxJtWrVqF+/PrNmzSI3N7dMMYjUGkEQBEEQBOH/rebNmxe7/dixY2rLU1JSMDU1VSk3MzMjOTm5yP3FxcUB8OOPP9KlSxeGDx/OzZs3mTt3LhKJhLFjx5Y6djGQFwRBEARBEN57Wlr/G4kkUqkUgHr/x959h0Vx/A8cf0sXpBcBQVCaqNiwY+8tscUWoybGEnuiiVGjRpOYWJLYe++x9957r2ChKFhBeoe7g+P3x8HBeUc7TcTvb17P45MwO7M7t+wNs7OfmW3YkAkTJgBQv359UlJSWLNmDSNGjMDIyKhI+xIdeUEQBEEQBOH/rfxG3AtjZmZGUlKSWnpCQgLm5uYFlgNF5z2vBg0asGzZMp49e4aXl1eR6iA68oIgCIIgCELJ9w4TU/8NFStWVIuFT0pKIioqSi12Pi93d/cC9yuRSIpch/+NZxSCIAiCIAiC8B9q0qQJly9fJjExUZl29OhRdHR08PPzy7dcuXLl8PT05PLlyyrply9fxsjIqNCOfl6iIy8IgiAIgiAIxdS7d29MTEwYMWIEFy9eZNeuXcyePZvevXurrCE/YMAAWrdurVL2u+++4/Tp08yYMYNLly6xbNky1qxZw5dffomxsXGR6yBCa0q4/fv3s2HDBkJDQ8nKyqJs2bLUqlWLsWPHYm1tDUCLFi1o1qxZgW8R8/LyYvz48Xz99ddFOu7ChQtZtGhRgXnKlSvH6dOn6devH8bGxixfvjzfvC9fvqRly5bMnz+fdu3aFakOu3fvZuLEiVy5cgUrK6silflflJKcxMY1y7h+5TwSiQR3T28GDBpORfeixc+9fB7GupWLePzQHz09PWrVacCAwSMxN7dQyRcXG822TWu5f/cG8XGxWFrZUKd+I7r36oepWf6xfppIZTLWbf6HE2fOk5ScQkXX8gz8og+1a1YvtGxUTAxLVq7j5t17ZMmzqFGtCsMHfYWjvfqLNWLj4lm3eRtXbtwiMSkJK0sLalX34YfRw4tVX/X6Z7Bs1xEOX7xJUkoa7uUdGPZZB+r7FHzOT9+4z4mrd3j49DnRCUmUtbKgcc0qDOrSBlOT0ip5j1+9w4XbDwh48owXb6KpVcmNFZNHvlO9AXRNjKk47mss6lbHoo4PBlYW3Pt6Ai837ClSeT1zU7xn/kDZzq3RNTYi4YY/D8fPJPHOQ7W8dp1a4Dl1JGW83ZFGxvBi/W5CZiwhKzNT6/pLMzJZfOY2h+6FkJguxaOsJSNb+NLArVyx9jN0w1GuPn1NrzreTOqY/0tWbj+L4Ku1hwE4+8PnWJoUbYJZgfU/cZ1DdwJJTJPgYW/NyDb1aODhXGC5Uw+esuPaA0IiYohPTcfSpDTVypflm5Z18LC3VsmbKpGx6Pg1TgQ8IS4lDScrMz5vWI2e9au+W91lMpbvOMThC9ezr3tHhvXsRL1q3gWWC3v9ht0nLxIQEkZg2Auksgz2LZiOo621Wl6JVMaWw6c5cvEGr6NiMDMxpppnRQZ374Cbs8M71T+vlOQktqxbzI0r55FK0nHzrMwXA0dRoQjtZkjQQ86dPMSToIc8DwshMzOTrQcua8x74vBuHty/RUjgQ2Ki39CkRQeGfTdZqzpLZTLWbtnO8TMXSEpJxs3Fha+/6EXtGtUKLRsVE8vi1eu5cfc+WfIsavpUYcTX/VXazSOnzjJrwdJ89/HTdyNp3ayxVnX/r5TSKVnjz+bm5qxfv55ff/2VESNGYGJiwmeffcZ3332nkk8ul5P5VrvYokUL/v77b5YsWcLWrVuxs7Nj1KhRDBkypFh1EB35EmzlypX89ddffPnll4wePZqsrCyCg4M5cOAAkZGRyo58UWzbtg1HR8ci5+/RoweNG+d+oXfs2MHBgwdZv369Ms3AwKDI+7Ozs2Pbtm24uroWuYyg+PL/Pu1HnoU+4dPuvTE1M+fYob38PGEMs+evxKFcwZ2DmOhIpv44CmOTMvQZMJj0tDQO7P6H52FP+WPucvT19QFIS0tl0rjhSNLTaNuxK9a2djx7GsLRg7sJuH+H2fNXolOMBnTWvEWcv3SV7p92xMnRgaOnzjBx+u/8PWMaPlXy7xSkpaUxbtI0UlJT6dujG7q6uuzad4jvJk5lxfw/MTczVeaNjIpm9HjFH8xP27fGxtqK6Ng4HgeFFLme+Zm2fAunbtzj87ZNcba34eCFG4z5cwXLJ42ghlf+cY8zVm/H1tKM9n61sbe2JOTFa7afuMClew/Z9Ns4jPJ8Z3aevMTjsJdUruhMQnLqO9c5h4GNJZ5TRpL67BVJ9wOxblav6IVLlaLO/hWYVfPi6V+rkcbE4TL0c+qf3MjFet1IDXmmzGrbtgm1dy0m5tx1Hnz7K6ZVPfGYNAxDO2sCRk7Tuv5T9p7n5MMw+tavQnkrM/bfDWHk5uOsHNCeWi72RdrHyYdh3HsRWWg+uTyLmUeuUlpfjzRZhtZ1zmvKjlOcDHhKX79qlLcxZ/+tx4xcd4iVgztTyzX/jmpwRAxmpQ353K8aFsZGxCSnsvfmY75YsosNw7rh5WADQKZczrC1B3jwMpJe9X1wsTHncvALZuw7T2KahEHNfbWu+/Slmzh1/Q592jfH2d6Wg+euMWb2UpZNHkONSm75lvMPDmXb0bNUcLLH1dGeoGcv8z8/i9dx/pY/XZr78XmHFkTFJbDz+Hm+/vkvts6ahIPtuw/ayOVyZv/yPc9CQ+jU7XPMzCw4fmg3v04awYx5a3FwLLjdvHvzMmdOHKC8qzt29uUIf/U837z7d20iPS0VN4/KxMdFv1O9Z85fwrnL1/jskw44Odpz9NQ5fvxlJnN/m0q1ypXyLZeals53k38hJSWVLz7rgp6uHjv2H2LMpOmsmjdL2W5Wr+LNpO/UBwt27j9ESOgzalX3eaf6/3/l5ubGunXrCsyzceNGjekdOnSgQ4cO73R80ZEvwTZu3EjXrl2VSxMBNG3alEGDBimXLiqqGjVqFCu/vb099va5fzQvXLiAjo5OsfeTw8DAQOuy/59dvXSWwEcBjJv4Cw0aNQOgYeMWjB78Ods2r+Xb8fk/hQHYvW0T6ZJ0Zs1fha2dYmTGw9ObXyaP5ezJI7Ru/ykAN69dIioygok/z8K3bu7oZRlTM3ZsXUdYaAgV3TyLVOdHQcGcOX+JoV/1o1e3zgC0adGUgSPHsnzdRhbN+T3fsvsOH+Pl63CW/DWTSp6KGMF6vrUYOPI7duzdz6D+fZV5/168HF1dHZb8PUulg/+uAp484/jVO4zp8yn9OjYHoGOjOvSaMJsF/xxgzc9j8i07a/SX1K6sGttYqYIz05Zv4eil23RpnrtCwS/D+mJnaY6Ojg49J8x6b/WXhEdy0skPyZtozH2r0ujqriKXdejeDquGtbjVazQRu48BEL7jCM0eHsNz6iju9v9emdd71ngS/QO53n6gcgQ+IzEF9wlDCV24gZTA/F+Gkh//l1EcDQhlbOs6DPBTdCo+qe5O9yV7mHfiJhsGdSp0HxJZBn8dv85Xjaqx5MztAvPuvBXIm4QUutXyZPM19ScOxa7/izccvR/C2PYNGNCkpqL+Nb3oPu8f5h25zIZh3fMt+03LOmpp3WpXps3MDWy/GsCUrs0Axcj93WcRTOvenK61FTfFPetXZdzmo6w4fZOudbyxLlP0x/I5HoSEcfzKLUb37UK/Tq0A6Ni4Hr3Hz2DBlr2s+SX/da2b+PpwevUcTEobsfHgyXw78pGx8Zy5fo8vOrVkTN+uyvSaldwY9tsCzty4y+cdWhS77m+7dukMQY/8+XbCb9TzU+yvfqMWjB3am52bVzHqh+kFlm/Vvhufdu+HgaEha5f9VWBHfuofi7GxtadUqVJ82aPgtcgL8igohNMXLvPNl1/Qu+snALRp3oSvRn3P8nWbWTz713zL7juiaDeX/TmDSh6K9qeubw2+GvU92/cdZHC/PgA42pdVe7IpkUiZt2w1tapVxdrSQuv6Cx9OyXpGIahITEzEzs5O47aCRkfj4uLo3r073bp1IzY2FlCE1qxevVqZp1+/fgwdOpSjR4/Stm1batasSf/+/Xn+PP8GqzAF7evly5d4eXlx9OhRlTJ79+6lS5cu+Pj4UK9ePQYPHsyrV6/yPcauXbuoWrUqO3bsABQhQDVr1iQwMJA+ffpQvXp1OnXqxIULF9TK7t69m08++QQfHx8aN27M3LlzVR51JSYmMnnyZBo3boyPjw9NmzZVeTxW2PZ/w5WL57CwsKJewybKNHNzCxo2bs6NqxeRyaQFlr96+Ry+dRoqO/EA1WrWxrGcM5cvnFGmpaYqRoTNLS1VyltYKZ76GBoYFrnO5y9dRUdHh07tcuMBDQwM6NC6BQ8fBxEZlf+o1blLV/HycFd24gHKO5ejVnUfzl68okx7/uIV12/doWe3zpibmSKVSsnIeD8jqqeu30NXR4euzXNvaAwN9OncrB73g8OIiInLt+zbnXiA5rUVHdLQ129U0u2tLYv1lKOo5FIZkjfajQzad2tLekQUEXuOK9Ok0XG83nmEsp+2RMdA8QSnjLcbplU8eLFqu0oYzbNlWyilo4NDt7ZaHf/kwzB0S5Wiu29u+IOhvh5da3ly72UkEQnJhe5j7SV/srKyGNCw4DCThFQJi0/fYnjzWpgaFf3pYkFOBjxBV6cU3etWUaYZ6uvRtY43956/ISJefZm6gliVKY2Rvh5J6bnf89uh4QC0q6Z6rbWr5oEkI5OzD8O0qvupa3cV132L3Al6hgb6fNqsAf7BoQVe9+ZlTDApXXhIUmpaOgBW5qo33jYWiqX4DLOfEL6ra5fOYG5hRZ0GzZRpZuaW1G/UglvXLhTablpYWmFgWLQ2z9bOgVKl3n0llXOXFe3mJ21zbwYMDQzo2Lo5DwILaTcvX6OSh5uyEw/g4lQO32pVOZOn3dTk8o1bpKal0appo3f+DMKHITryJViVKlX4559/2LFjB1FRUUUqExUVRf/+/TEwMGD9+vUFxpY/evSI1atX8/333/PHH3/w/PlzfvjhB63qqs2+Vq1axY8//kiVKlVYtGgRM2bMwMXFRXnz8baNGzfy888/M2vWLHr06KFMl8lkfP/993Tr1o1FixZhZWXF6NGjiYvL/cOzdu1aJk+eTKNGjVi2bBmDBw9mw4YNzJ07V5nnjz/+4OzZs4wdO5bVq1czfvx4lfChwrb/G0KfBlHB3UOtw+fu6Y1Eks7rVy/yLRsTHUVCfBxuHuoxoe6e3oQ+DVb+XLlqdXR0dFi7fAFBjx8QEx3J7RtX2L1tA3UbNKacs0uR6xzyNBTnco6YvDVZJ6dzHhIaprGcXC7nadgzvNzVH+FX8nTndXgEqalpANy6dx8ASwtzxv00jXbdP6dd98+Z8PNvRLwpPKSiIIHPXlHe3pYyxqodkyoVywMQ9Cz/G01NYhIUnTcLU5N3qtd/wbyGtyIWPitLJT3hhj96JsaYeFYAwKxGZQDib/mr5JOER5L2IhyzGgXHVOfncUQMLtbmlHmrY121nG32ds1tQ47w+GTWXrzPmFZ1MNIv+IHz4jO3sC5Tms9qF22uSVE8fh2Ni42Fev2dFDfSj8NjCt1HYpqE2OQ0giNimLb7DMkSKfXcnJTbpZmZ6OqUQl9XV6Vczud9+Eq76z8w7AXlHewoY6w6l6OKuysAQWH5h8sUlVNZW+ysLNh86DTnb/nzJiaOByFh/LH6HxztrGnTUPuwoLyePQ2igpuXWrvp5lkZiSSd8ALazQ8l+GkYzo4O6u2mR067+UxTMeRyOU/CnuPlrh7yV8nTndcRb5TtpiYnz13E0MCAJvXrvkPt/zuldEr9K/8+ZiK0pgT7+eefGTlyJJMnK+KAnZycaN68OV9++SVOTk5q+V+/fs2XX35JuXLlWLx4caGznpOSkti7d6+ys5+amsrEiROJiIhQCaspiuLuKykpiUWLFtGrVy9++eUXZXqrVq007n/58uUsWrSI+fPnq71KOacj37RpUwAqVKhAy5YtOX/+PJ07dyY5OZkFCxYwaNAgxo4dC4Cfnx/6+vrMnDmTr7/+GktLS/z9/enUqRNdu+Y+8u3YsaPy/wvb/m+Ij42lchX1CaKW2SPlcTExuLhqjl2Ni4tRyft2+eSkRGQyKfr6BjiXd2XoyO/ZsHoJk8YNU+Zr1rIdw8aML1adY2LjsNLwiNYqe7Q/JkZzZywpKRmZTIa1lXpZ6+yy0bGxlDcux6vXilHJvxctp5KHG1PHj+VNVBQb/tnB91N+YdWCvzAyKvpThLyi4xOVI4R52Vgq0qLiEtW2FWT9gVPo6ujQsm7hE30/NEMHW2Iv3lRLTw+PzN5uR1JAEEb2io61JFx9gEESEYWRo+YniYWJSkrFxrS0WrpNmdLK7QX56/h1KjlY094n/3kMAEERsey8Gciivm3QfY9PRRT1V293c9KiElMK3Ue/pbsIi4oHwNhAn8HNfZUhNACuNhZkyrO4/+KNSsz97bDXAEQW4RiaRMcnYq3pus9Oi47L/3XzRaWnp8vs7wYxedE6xv2ZuziCdwVnVk8fh6lJ8UOCNImLi6FS1Rpq6TlPGONioyifT7v5ocTExWFtZamWnrft0yQxObvdtNRU1iK7bBzljdW/V4lJyVy/fZdG9epgrGG78HEQHfkSzNPTk4MHD3LlyhUuXrzIjRs32LhxI7t372bz5s14e+c27s+fP6dv375UqlSJ+fPnF2mkuFKlSioj9jnrlmrTkS/uvu7cuUNaWhqfffZZofueN28eBw4cYPny5TRs2FBtu46ODg0a5IZBODk5YWRkxJs3b5THSk1NpV27dirhFw0bNiQ9PZ3g4GDq1q1L5cqV2bNnD7a2tjRu3BhPT9WY8MK2/xukUgn6+uq/S/3s369Umv9LI6TZL5TQ1/C4OmefUknu/q2sbXH38qZW7frY2tnz6ME9Du/fhamZOQMGjShynSVSqcZj5lyTEqnmx9o56ZrLKtKk2XnS0rMf0Vta8PvPk5Qjb7Y21vw2Zx6nzl2gY1vNN4WF11+GvobRXIPsNIlMVuR9Hb18i33nrtG/UwvKZ3d+SzLd0kbIJeq/H3l2aIduacXNkU52GIWmvJnpEvTMymh1fElGJgZvjTQDGOop0iSy/FfDuR4azsmHYWwa/Emhx5l15Cp+Hk40dC/eSjiFkcgyNNdfX1e5vTC/dG9BskTKq9hE9t56jCQjg8wsOToo9tGhhicrTt/k552nmdS5CeVtzLkS/ILtVx9kH0O7FYMkUpnyGs/LIPv7mC4t+nVfEFMTYzxdnGhZryY+HhV4ERHFun3HmThvNYsmjcTQ4N3Da6RSCXp6Bbd7JY00v3Yn+3zk125KJTntpqayBbe55y5fRZaRIcJqPnKiI1/CGRgY0LRpU+Vo84ULFxg6dCiLFy9WWR7S39+f+Ph4fvrppyKHe+S8IjhHTgeqOG8U03Zf8fHxAPnOAcjr2LFjeHp64uur+bGrkZGR2mfW19dXHjsnxCbvSHpe4eGK0d0pU6Zgbm7O2rVrmT17Ng4ODgwZMoTPP/+8SNvfhUwmIzlJdaTXzNwCAwNDjfGcsuyG2aCA2PWcGE+Zho5nzj5z8jx+6M8f0yfw+99LcfdQrI5Qt0FjShubsGPLOlq06YhzedcifRZDAwONx8zphBvmc33mpGsuq0jL+T3n/LdZo4Yqj8+b+jXgj78X8uBxoNYdeUMDfWQaOlzS7LSixvHeefyEX1duo4FPJYb3eLdVCf4rmWnp6Biq/350skNFMtMU3yl5dqyzpry6RobK7cVlqKeLVMPSlZIMRVpOh/htGZlyZh25Sqfq7sownPwcDXjK3ReR7BquuT14F4b6eprrL8tUbi9M9Twr87Sr7k6Xv7cCMK6DInbdxtSY+f078NP2k3yz5gAAZQwNmPBpIybvOI2xoXYdYUMDfeU1npc0+/to9B462MmpaQyePpd+nVrxRafcJ6veFcvzza/zOXDuKp+1LvryhxkyGcnJb7WbZop2MyOj8HavJDHIr93JbvvyazcNDHPaTU1lC25zT567iJlpGer51tCmyh9GKRER/jbRkf/ING7cmEqVKvHkyROV9I4dO6Krq8vYsWNZvny5ygh1SWRhYQFAZGRkoaP/S5YsYdSoUYwaNYrFixdrHLEtiLm5Yg30RYsWaTxWTpiSqakpP/30Ez/99BOBgYFs2LCB6dOn4+npSe3atQvd/i4CHwUwbaLqaihL1mzDwspKGSKTV1xsdthMAUuQWlpaq+R9u3wZUzPlCNXxI/uxsLRUduJz1K7nx/bNawl8FFDkjry1lSXRGsJnYrNvqKytNc/bMDUtg76+PjGx8WrbYrLL2mQ/9bHJfgRtaaG6vr2uri5mpqYkJWsXXgCKUIKoWPUwgujskBpbS/Xwg7cFPXvF2L9X4+Zkz6wxX6KnYZS2JJKER2Go4cmBkYNd9nZFiE16hCKkxtDBlvSXESp5De1tib9xX6vj25oaE5moHj4TnZym3K7JgXshhEUnMKVTQ17FqU4oTZXKeBWXhJVJaUob6DH3+A3aVHFFX1dHmTdnMmlEYgqyTDl2ZtqFeCjqr37tRWeHBNmaFW+ehFlpI+q6OXH4brCyIw/gW8GRQz98QXBELGlSGV4ONsrjutgU750POWwszIjSED4THa+47m0stdtvXqev3SU2IYkmvqrLHPpW9sCktBH3Ap8WqyMf9NifXyepLqe4YNUuLC2tidfQ7uWkWVqVvKdj1paa28232763mZXJbjfj1Ccjx8TFZ5dVD7t5ExXN/YeP6dSmJXp6oiv4MRO/vRIsOjoaGxsblbT09HTCw8M1vr73p59+QiKRMHz4cFatWpXvCHZJULNmTUqXLs2uXbuoVq3gl11UqFCBtWvX0r9/f8aNG8fcuXPRLUbHKOdYERERam9Wy4+XlxcTJ05k586dPHnyRK2jXtj24nKt4M7U3/5WSbOwtMK1ggePH9xHLperjDwHBz7C0NAIxwLWkbe2scXM3IInwYFq20KCHuFaMfcaSoiPRZ6pvqRpZnYo0tsvsiiIWwVX7twPICU1VWXi1qNAxeRa9wquGsvp6OhQ0aU8gSFP1LY9CgzGwb6sMo7TM3tC7Nt/+GQyGQmJiViYF97Zzo9X+XLcehhCcmq6yoTXgCeKyWaeLgWHY7x8E82o2cuxNCvD/B+GYKxlrP6HkHjvMZaNfKFUKZUJrxZ1q5GRkkpKUGh2vkeKdF8fEm7kTng1dLCjtLMDz1dt1+r4XvZW3AgNJzldqjJh1P+l4sahkr3mzkxEQjIZcjkD1hxS23bgXggH7oUwt1dLWni7EJGYwmH/pxz2V18es/fyfXiVtWL7sC7a1d/BhhtPX6nX/4UizK+SQ9Hf/ZEjXZZBcrr6UzldHR0qOeb+fbgWopiMmndibHF4ujpx62EwyalpKhNeH4SEKbe/q5gExU3B28snZ2VlKV6YIy9eWFD5Cu5M+nW+Spq5pRUuFT14/OCeWrsZEvQAQ0OjQt+/8SG4V3Dljv8D9XYz+70Y7hU0LzigaDedCQxRv54fBYXgmKfdzOvU+UtkZWXRWoTVfPTEM4oS7JNPPmHSpEkcPnyYmzdvcujQIb766ivi4uIYMGCAxjLTp0+nTZs2DBkyhPv3tRsV+y+YmpoyYsQI/vnnH6ZOncq5c+c4c+YMM2fOxN/fXy2/l5cXa9as4fLly/z444/FWkffzMyM0aNHM2fOHObMmcO5c+e4ePEiW7duZdCgQaSlKUb7evfuzerVqzl//jyXLl1i+vTp6OvrKzvphW1/F2VMTalWs7bKPwMDQxo0akp8fCzXLp9X5k1MiOfKxTP41muoEj8fEf6KiHDVFVXq+zXl1o3LREflLn14/+4tXr96QYNGzZVpjo7OxMfHEnD/jkr5i+dOAVChokeRP0tTv/rI5XIOHj2hTJPKZBw9eQZvLw/sbBWdjzeRUTx/oVrfJn71CQwOITA496VOz1++4s79AJr65T5lqu5TBUsLc06eu6B8fAxw7NRZ5HI5vkV4E2J+WtatTqZczp4zucu2SWUZHDh/napuLthbK0a3IqLjCHtrScno+ERGzFqGjo4Oi378BkstY8X/C4b2tph4VaRUntG48N1HMbK3xb5rG2WavrUlDt3bEXnwDPLsx/zJD0NIfvQE50E9IU9HyWVoH7LkciJ2qy4zW1StKruSmZXFrlu5N5/SjEz23Q3Gp5wt9uaK8xken0xo9oRQgHZVKzK3V0u1fwCNPZyY26slPk6KUVhN+dpWUazG81vXJnzfrhgv0Hq7/lXdyJRnsev6A9X633qMj3NZ7C1Ms+ufRGik6ghqjIaXgr2KS+T6k5dULiRcKDY5jbXnb+Npb019d+06qS3r1VRc96cv5dZdJuPAuatUdXfNc93HEvYqIr/dFMgl+8nO8Su3VNLP3/InTSLFy7V4dS9TxgyfGnVU/hkYGFLPrzkJ8bHcuHJWmTcxIZ5rF89Qq66fSrv5Jvwlb8LffUWed9W0YT3kcjkHjp1SpkllMo6cOou3p3tuuxkVzbOXr94qW5/HwU94HJw7CPL85Wtu3w+gacP6aHLq/EXK2trgU8CLpkoisWqNOjEiX4KNHDlS2bmNjY3F0tISLy8v1q1bR/36mr+cpUqV4vfff0cqlTJo0CA2bNhApUol84s6ePBgrKysWLduHbt378bExISaNWvm+8baKlWqsGrVKr766iumTp3Kr7/m/4KMtw0cOJCyZcuydu1aNm3ahJ6eHuXLl6dZs2bKUJ1atWqxd+9eXr58iY6ODp6enixbtgw3N7cibf831PdrhmelnSye9wcvn4cp3ux6eC9yuZxefQeq5J0+SbGm/dK1uaOh3Xp+wZWLZ5k28Vs6fPoZ6elp7N+1lfKuFWnRur0yX7tPunHm5BFm/jKB9p90x9auLA/973Hx3Emq1ayNZ6XKRa6zt5cnTf0asGrDFuITEinnYM+x02eJiIzi+9HDlflmzl3IvYCHnD6wU5nWuUM7Dh0/xaRf/qBH10/R09Vl596DWFpY0LNr7iRGA319hn7Vj5lzFzFmwlRaN29CZFQ0uw8cxqeKN40baN8Zq+ruQqu61Vm0/SCxiUk4l1W82fV1dCxTBvdW5pu6bDO3Hz/h5qbcJUxHz17Oq8gY+ndqwd3Ap9zN81IkK3NT6vvkLnV4+/ETbj9W/OGNT0wmXSJl1V7F+u21KrlRq4A3aRbGZXhf9M3NlKvH2HVsjlE5RVhZ2OKNZCQm4zVjLM79u3HavQVp2Utqhu86RtzVO1Rf9QdlvN2RxcThMrQP6OoS9MtClWM8mjCb2nuWUu/IGl5vP4RpFU9ch/flxZodJD8u/sugAKo52dGmsisLTt0kNiUdZytTDtwL4XV8EtM+zR05nLznPDefRXBvmuI7UMHWggq2Fhr36WhhSgvv3NHMvP+fIzBCEXLRyN0JS5PC10PPt/7ly9LGx40Fx64Rm5KGs7U5B24H8jouiWndc2+cJ28/xc3Q19z7I/f78Nn8bdRzc8LLwQaz0oY8j4lnz41HZGTKGdNOtb0fuGIv1cqXpby1OdFJqey6/pBUqYyFAzqio2WnpKq7K63q1WTxP/uJS0jGyd6GQ+ev8zoqhslDcl/E9vOSDdx+FMKNrblztJJT09h29BwA94IUv/vtx85hamyMqUlperZVzPFq7OtDRScHVu0+Snh0LD7uFXjxJoodx85jY2FG52bvJyS0XsPmeHhVYdn835Xt5onDu5HLM/ns80EqeX+bPBqAhat3K9OiIsO5cEZxM/o05DEAu7etBcDW1p7GLXLbzlvXL/IsVPG0MTMjg+dhIcq8vnUb41JB/em5JpW9PGjmV5+VG7cSn5CQ3W6eIyIyivGjhirz/T5vMfcCHnJ23zZlWpf2bTh4/BQTf51Fry6d0NXTZce+Q1hZmNOri/pL1J4+e86TsOd83r3ze1kDX/iwSmVlvbVgsCAI/xn/kDeF5klOSmLjmiVcv3oRqUSCm2cl+n89XC2efdhXPQHVjjzAi2ehrFu1iMcP/NHT06NWnQYMGDQCC0vVMIVXL5+zdcMqQoIeEh8Xi6WVDQ0aNaNX34EYGql3bnzcy/IqSP3pCSgmWa3Z9A8nz54nKTmFiq4uDPyiN3Vq1VDm+W7iVLWOPEBUdAyLV63l1p37yLPkVK9ahRGDvqSco/rr7U+fv8jWnXt5/vIVZUxMaNqoAYP6fV7oUmrlPH1IunE43+0SqYxlO49w+NJNklLTcHd2ZNhn7WlQLfecD/ltkVpHvvYX+b8grFYlN1ZMzo3nXb7rKCv3HNOYd3DXtgzt3i7ffZnW6cAh/fzXP28efArjfEIhcjru1Vb/odaRB9CzMMN71njsP22FTmlDEm768+jH2STcClDbV9lPW+IxZSRlKrkhjYrl5YY9BP+2mKxCXs7VURZI+lbNb7OVyDJYfOY2h+4/ITFNikdZS0a0qIWfe+7n+XrtYZWOfH6qT1tDrzreTOpYcAdx6ZnbLDt3l7M/fF5oR96oz4+k756f73aJLIPFJ65z6G4QiWkSPOytGdG6Ln6e5XPrv2KvWkd+6cnrXHj8jBexiaRKZFiWKY2vqwODmvviYa86uDHn4CXOPgolMjEFE0MDGrg7MaJNXZysCo9jN+o2hsTbJzRuk0hlLNtxkCMXb5CUkop7+XJ806MjDarn3sgP/WWeWkf+dVQMnUf/rHGfDjZW7F+Yu8RwYnIqq/cc4eKdB0REx2JsZETdql4M7/0J5exsNO4jh1mt1twOKnwtfoDk5ES2rFnMjavnkUklVPTwpu/Akbh5qL7jYNTX3QDVjvxD/9tqsfc5vKvWZOofi5U/L537G+dPa25LvhnzE01b5S5RXMvTmvDHd/Ots0QqZc3m7Zw4d4Gk5BTcXMsz8POe1M3Tbo75abpaRx4gMjqGxavXc/PufeTyLGr4VGbE1wNwclCfF7Ziwxa27NrHmvlzqOhaXm17fhwq1Sg0z78tcd7Yf2W/Zt/+XXimEkp05AXhAypKR76kKqgjX9IV1pEv6QrryJd0BXXkS7rCOvIlXUEd+ZKuOB35kqiwjnxJJzryJZOIkRcEQRAEQRCEj5CIkRcEQRAEQRBKPBHTr06MyAuCIAiCIAjCR0h05AVBEARBEAThIyQ68oIgCIIgCILwERIx8oIgCIIgCELJpyPGn98mzoggCIIgCIIgfIRER14QBEEQBEEQPkIitEYQBEEQBEEo8UrpiOUn3yZG5AVBEARBEAThIyQ68oIgCIIgCILwERKhNYIgCIIgCELJV0qMP79NnBFBEARBEARB+AiJEXlBEARBEASh5BOTXdWIEXlBEARBEARB+AiJjrwgCIIgCIIgfIREaI0gCIIgCIJQ4pUSk13ViDMiCIIgCIIgCB+hUllZWVkfuhKCIAiCIAiCUJCU5T/9K/s1GTrjX9nvf0GE1gjCBxQQEvGhq6C1qu72pB9b/aGroRWjtl/z5tGtD10NrZX19iV966wPXQ2tGfX5kUP6Xh+6GlrpKAsk6ebRD10NrZnWbkfi7RMfuhpaMavVmsdPXn7oamitkpsTMQGXP3Q1tGZdteGHroKggejIC4IgCIIgCCWfWH5SjYiRFwRBEARBEISPkOjIC4IgCIIgCMJHSITWCIIgCIIgCCVeKR0x/vw2cUYEQRAEQRAE4SMkOvKCIAiCIAiC8BESHXlBEARBEARB+AiJGHlBEARBEASh5Csllp98m+jIC4IgCIIgCCWfmOyqRpwRQRAEQRAEQfgIiY68IAiCIAiCIHyEREdeEARBEARBED5CIkZeEARBEARBKPnEZFc1YkReEARBEARBED5CYkReKBEWLlzImjVruHPnzn9+7BYtWtCsWTOmTp0KwIQJEwgICODgwYP/eV00SUlOYsOaZVy/cgGJRIK7ZyW+HDSCiu6eRSr/8nkYa1cu5vFDf/T09KhVpz5fDh6JubmFMs+2zWvZvmVdvvuYMWcRlSr7FLnOUlkGiw9f5NCNBySmSfBwtGVkx8Y0qORaYLlT94LYcekuIa+jiE9Jx7JMaaq5OvJNez88HG1V8s7ZfYqbIS94HZuIVJaBg5UZbWtWYkDLuhgbGhS5rprrL2P1lp0cP3uBpJQU3FzKM6hvT+rUKPwcRMXEsmj1Rm7c9UeelUVNn8qMGvgFjvZlVfLFxiewfMNWrty6S2paGi5O5fii+6c096v/TnUHkGZksvjMbQ7dCyExXYpHWUtGtvClgVu5Yu1n6IajXH36ml51vJnUsUG++W4/i+CrtYcBOPvD51iaGGldd10TYyqO+xqLutWxqOODgZUF976ewMsNe4pUXs/cFO+ZP1C2c2t0jY1IuOHPw/EzSbzzUC2vXacWeE4dSRlvd6SRMbxYv5uQGUvIyszUuv5SWQbLdh7m8MUbJKWk4V7ekWE9OlDfp1KB5U7fuMeJK3d4+PQ50QmJlLW2pHGNygzq2hZTE2O1/Odu+bNi91FCX0VgaVaGT5vU4+uubdHT1X2HustYvuMQhy9cz617z07Uq+ZdYLmw12/YffIiASFhBIa9QCrLYN+C6TjaWqvlTU2XsHTbAU5fv0tcYjLl7Kzp1a4Zn7VurHW9NUlOTmb9mhVcvXwRiUSCh5cXAwd9g1sR280Xz5+xeuVSHj3wR09Pn9p16jFwyDCVdvNtZ8+cZO6cPzAyMmLb7kPFqq9UJmPlP3s4du4KiSkpuLs4M6RPN+pWr1JguWevwtl7/CwPgp8Q9PQZUlkGu5bOwcHORi3v/LVbufPgMeFRMUilMuxtrWnpV5fPP22HcWntv7PChyU68oLwluHDh5OamvqhqwGAXC5nxrQJPAt9QufuvTE1M+foob1MnTCG2fNX4ljOqcDyMdGRTPlxNMYmZfh8wCDS09LYv3sbz8NCmTl3Gfr6+gDUa9gEewf1Tt6WDStJT0vDzaPgTsjbpmw+zMm7QfRt5kt5W0v2Xwtg5LKdrBzVm1pu+dc5+HUUZsZGfN60NhZlShOTmMLeq/588ddGNoz9Aq9ydsq8Ac8jqOXmTOd6Fhjq6/H45RvWnLzG1aBnrB39OTo62j+C/WPBMs5evk6PT9rh5GDPkdPnGf/rbOb/+hPVKud/LlLT0hkz5TdSUlL54rPO6Onpsn3/EUb99Ctr5v6BuZkpACmpqYyYOI24+EQ+69QWK0sLzly6ys9zFpCRkUnrpn5a1x1gyt7znHwYRt/6VShvZcb+uyGM3HyclQPaU8vFvkj7OPkwjHsvIgvNJ5dnMfPIVUrr65Emy3inegMY2FjiOWUkqc9ekXQ/EOtm9YpeuFQp6uxfgVk1L57+tRppTBwuQz+n/smNXKzXjdSQZ8qstm2bUHvXYmLOXefBt79iWtUTj0nDMLSzJmDkNK3rP235Zk5dv8vn7ZrhbG/LwfPXGDNnOct/GkkNL7d8y81YtQ1bSzPaN6qNvbUlIS9es/3EBS7de8SmGd9jZJB7c3rp7kO+n7saX293fujfnZAX4azee5zYxGQmDuypdd2nL93Eqet36NO+uaLu564xZvZSlk0eQ41K+dfdPziUbUfPUsHJHldHe4KevdSYL1MuZ9Qfi3n09Dk92jTG2d6Oq/cfMWvNNpJSUvmqS1ut656XXC7n158nERb6hK7de2FqZsaRQ/v56cdx/L1gaaHtZnR0FJPGf4exiQlfDPia9PQ09u7awbNnocyZu1jZbuaVlpbG+jUrMDLSrkP828LVnLl6k14dW+PkUJbDZy8ybsZcFk0fT3Xv/G8+AgKfsOPwCVydHHFxciQ49Hm+eR+FhFLd25OOLcpioK9PUOgzNu05xM37D1ny6wR0PoKlHUt9BHX8r4mOvCC8pXz58h+6CkpXLp0l8FEA30+cToNGzQBo2Lg5owb3ZdvmNXw3fmqB5Xdt20S6JJ3Z81dia6cYEXb39OaXyeM4c/IIbdp/CoBrBTdcK6j+oY6OiiQmOoqWbTpq/MOVH/9n4Ry9/ZixnZsxoGVdAD6pW5Xuf6xh3r6zbBj7Rb5lv2mv3oHt1qAabaYuZfvFO0zplfuHfv23fdXyOtlY8PfeswQ8C6daBcci1zmvh0EhnLpwhWFffk6fLp0AaNu8MV+O/pGl67eydNb0fMvuPXKCl68jWD7nV7w9FOezXq3qfDn6R7btO8SQfr0B2H/sFK/C3zD3l5/wraYYcevSrhXf/DiVxes206xhPfT1tWue/V9GcTQglLGt6zDAT/EE4ZPq7nRfsod5J26yYVCnQvchkWXw1/HrfNWoGkvO3C4w785bgbxJSKFbLU82X1Mf9S4uSXgkJ538kLyJxty3Ko2u7ipyWYfu7bBqWItbvUYTsfsYAOE7jtDs4TE8p47ibv/vlXm9Z40n0T+Q6+0HKkfgMxJTcJ8wlNCFG0gJfFrsugc8ecbxK7cZ83ln+nVsAUDHRnXoNWEmC7buZ8207/ItO2vMV9Su7KGSVqmCM9OWbebopVt0aZ77RGT+ln14ODuyaMIw5Qi8SWkj1u4/QZ92TXF1VH36UxQPQsI4fuUWo/t2oV+nVoq6N65H7/EzWLBlL2t+GZdv2Sa+PpxePQeT0kZsPHgy3478met3uR/0lClD+vJp9uf5rHVjfpy7itW7j9K5eUOszE2LXfe3Xb54nsePHjB+0lT8GjUFoFGTZgwbPICtm9Yz7sefCiy/c9sW0iXp/L1gqbLd9PCsxM8/jef0yWO0ba/+Hdr+zyZKlzbGp1oNrl25VKz6Pgx+yslL1xjZvyefd24PQPtmfnzx3WQWb9zOit8n51u2cZ0aNGuwGJPSpdmy70iBHfllMyappZWzt2PR+m08DAmlqmf+N2tCySVubYQS5+XLl3h5ebFv3z5++eUX6tSpQ6NGjZg1axYZGbkjfhEREYwZM4aGDRvi4+NDixYt+P3335XbJ0yYQKdOqg1uYmIiXl5e7N69O9/jv11u9+7deHl58fDhQwYNGkSNGjVo06YNe/fufX8fOh9XLp7DwsKKeg2bKNPMzS1o2Lg5N65eQiaTFlj+6uXz+NZpoPxjBFC9Zm0cyzlz+cLZAstePHeSrKwsmjRvXaw6n7wbiK5OKbo3rK5MM9TXo2v9atwLe01EXGKx9mdlaoyRgR5JaZJC85azMgcgKS29WMfI69zl6+jq6PBpmxbKNEMDAzq2asaDwGDeRMXkW/bslWtU8qio7MQDuDiVo1a1Kpy5dE2Zdu9hIBbmZspOPICOjg7N/eoTGxfP3QePtK7/yYdh6JYqRXdfr9z66+vRtZYn915GEpGQXOg+1l7yJysriwENqxaYLyFVwuLTtxjevBamRu8WzpRDLpUheROtVVn7bm1Jj4giYs9xZZo0Oo7XO49Q9tOW6BgobkjLeLthWsWDF6u2q4TRPFu2hVI6Ojh0025k+NS1u+jq6NC1eUNlmqGBPp2b1ud+cBgRMXH5ln27Ew/QvHY1AEJfRSjTnr6M4OmrCLq2aKASRtOjdSOysrI4ee3uu9W9Re7NtKGBPp82a4B/cGiBdTcvY4JJEUIz7j5+AkCbhr4q6W0a+iKRyTh3875WdX/b5YvnsbC0pEHD3HAdc3MLGjVuyrWrlwttNy9fOk+dOvVV2s0aNX1xLOfExQvn1PK/fvWS/Xt2MXDwMHS1CG06c+Umujo6dG7dTJlmaKDPJy0bExD4hDfR+bc5ZqZlMCldutjHzOFgqwjBSU4pGU+hheITHXmhxJo3bx46OjrMmzeP3r17s2bNGnbs2KHcPn78eAIDA5k8eTKrVq1i9OjRyOXyf60+33//PY0aNWLx4sV4e3szYcIEnjx58q8dDyD0aTAV3D3UHnm6e3ojkaTz+tWLfMvGREeREB+Hu4eX2jZ3z0qEPg0u8Njnz57ExtaOylWrF5jvbY9fvsHF1ooypQ1V0qu6OGRvLzxcIzE1ndikVIJfRzFt61GS06XU83RRy5eRKScuOZXIhCQuPwpl0aELmBgaKI+ljeDQMJwcHTAxVo1Lzumch4SGaSwnl8t5GvaCSm4V1bZ5e7jxKuINqWlpAMhkMgwN1Du+RgaKcxb4JFTr+j+OiMHF2pwyb3Wsq5azzd4eW2D58Phk1l68z5hWdTAq5KnA4jO3sC5Tms9qq19jH4J5DW9FLHxWlkp6wg1/9EyMMfGsAIBZjcoAxN/yV8knCY8k7UU4ZjUKjgnPT+Czl5S3t6WMsWqntoqb4ilf0LNXxdpfTILiptfCtIzKMQC8K6o+ObS1NKeslYVye3EFhr2gvIMdZYxVO4VV3F0BCArTbr95STMy0NXRQU9PtbObEzb0uIDR5OJ4+jQENzf1dtPDsxISSTqvXub/WRTtZjzuHurhLJ6elQh9ot5urlqxBJ/qNahdpxhhYHkEhT7D2dEek7fOfWV3RVsSHJp/O19cGZmZxCcmERUbx7W7AazYuhvj0kZUdq/w3o7xryql8+/8+4iJ0BqhxKpWrRqTJyseKfr5+XHt2jWOHTtGnz59APD392fs2LF06NBBWaZLly7/Wn369u1L376KcI6aNWty7tw5jh07xvDhw/+1Y8bHxlK5inpH2tJKMYksNiYGF1fNj0Pj4hSjOBZW6hPOLK2sSU5KRCaToq+v3qF8/iyUZ6FP6NK9D6WKudxXVGIKNuYmauk2ZibZ2wsfEe739ybCIhUdTmNDfQa3bUDX+tXU8j18HkG/uZuUP7vaWTF/SDfMTbQfoYqJi8fa0kIt3dpKkRYdF6+xXGJyMlKZTHNZS0tF2dg4ypcrTflyjty6H0BEZBT2drmTeO8/eqzIF1NwZ7sgUUmp2Jiqf36bMqWV2wvy1/HrVHKwpr2P+g1JXkERsey8Gciivm3QLSFxq4YOtsRevKmWnh4emb3djqSAIIzsFedcEh6lllcSEYWRo51aelFExydiY2mmlm5joXhSFBWXUKz9rT9wCl0dHVrWy20DouMTs/epfhxrCzOii/nEK+9+rTXsM+c40cWsuyYuDnZkyuUEBIepxNzfeRwCQOR7OAZAXGwMVaqqT0xXtpuxMbhW0Hx9x8bGquRVLW9FUlKSSrt58/pV7t6+ybzFK7Sub3RcAtaW5mrpOWnRcfk/DSmux0/CGDLxN+XP5R3tmT1hDGZ5bhaFj4voyAslVqNGjVR+dnNz4+rVq8qfK1euzJo1a9DV1cXPzw8XF/UR23+rPsbGxjg6OhIREVFAiXcnlUo0xqcbZI9gSaX5h5tIJYptmsrn/BGSSiQaO/IXzp4AoHExw2oAJNIMDPTUmxbD7NFdibTwCZG/9G1PcrqUV9Hx7L3mj0SWQWaWHB1UR/Iq2luzfERP0iQy7oa+4lrgM1IlBT82L7T+EqnG+HSD7PMoyWf/EokM0Hy+DQxUy3Zq3Zx9x07y85wFjPy6H1bm5py5dJULVxWdUIlU+88gycjEQMPjfcPsUVCJLP8VWa6HhnPyYRibBn9S6HFmHbmKn4cTDd2LtxLOv0m3tBFyDb8febo0e7viiYdOdhiIpryZ6RL0zLTr1EikMvQ1XPsGBnrK7UV19NJN9p29Sv9OLSlvn3tjkbMPzd8xfVK0DCuTSGUYFHDdpxej7vlp61eHVbuP8uvyTYz/qifODorJrjtPXFDW4X2QSjUPUBjkaffyL1tAu5nd7iraCANkMhmrVyyhXYdPKF/eVev6SqRSjb9PZZvzns4LQAUnR+ZP/Z40iQT/wBBu3n9IWrr2oYj/uXdYxOB/VckYRhEEDUxNVSc96evrI83TwZk7dy7169dn3rx5tGnThnbt2nH8+PG3d/Of1eddyGQy4mJjVP5lZmZiYGCITKbeiOcc18DAUG1bDgNDQ+W+1Y8nVcmTV1ZWFhfOnqK8SwW1CbBFYWighzRDvbMuyV7RxNCg8PGD6hXK4eddgZ6Na7JseE8O3XjIggPn1fKVKW1IfS9Xmlfz4LvOzejfog7frtxD4KvCw3fyrb+hATINq69Is8+jYT5LWxoaKv7oav59qZZ1cy3P1LEjeR3xhhETptFn2HfsPHSMUV/3A6C0litfgKLDLtWwfKIkQ5FmqK85hjcjU86sI1fpVN1dGYaTn6MBT7n7IpJxbepqXc9/Q2ZaOjoafj862WFGmdnzLOTZnV1NeXWNDJXbi8vQQB+ZhmtfKs1Qbi+KO4+f8OvKf2hQrRLDe3ZUOwaQz3dMVuRjvM3QQB9pAde9kZb7zcvGwoy/vh+KNCODkX8spvPon1mweS8/fNkDAGOj/NszTRTtZqzKP0W7aaAxDl5aQLuXI6dN1dhuZre7Od/j/Xt3kpiYSJ8vBhSr3m8zNDDQ+PtUtjnv4dznMDEuTZ3qVWhStxYj+vWkz6dt+XHWAoLD3k9Yk/DfEyPywkfLzs6OP/74A7lcTkBAAEuXLuW7777j6NGjODs7Zzfmqo1xQsL7eXT7vgU+CuDnid+qpC1d8w8WVlbKEJm84mIVaVbW6o9/c1haKrbFx2ouX8bUTOOo1eOH/kRFRtB3wJDifAQlWzMTIuPVw2eiE1OytxdvtNPM2Ii6nuU5fPMh47o0LzBvy+qe/LTxEEdvPVJZqrI4rC0tiNIwsS8mNh4AGw2hMwBmZcpgoK9PjIbQm5jsR+M2VpbKtGYN6+FXx5eQsGfI5XI8K1bgToBi1RdnR+1j/G1NjYlMVA+fiU5OU27X5MC9EMKiE5jSqSGv4pJUtqVKZbyKS8LKpDSlDfSYe/wGbaq4oq+ro8yblD3qHZGYgixTjp2Z5uP8myThURjaq9+EGDnYZW9X3OClRyhCagwdbEl/qfpUzdDelvgb2k26tLEwIypWvY2Jjlek2WoIn3hb0LNXjP1rJW7O9swaM1BtXXhlqEt8IvbWlirbYuITqeym3apbNhZmGkN/lKE8Rah7UdTydmfv/OmEPH9NukSCh4sTUdnfmbxPHori8aMHTJ6guprOirWbsbSyJi5WPTxN2W5qCJvJYWVlpZJXtXwspqam6OsbkJKSzPZ/NtOh46ekpqYqlyxOS0sjKwvevInA0NAQCwtLtf28zcbSnKjs9iWvmOzfh41l4fvQVtN6tYGVnLx4DQ/XkrNim1B0oiMvfPR0dHSoVq0a3377LadPn+bZs2c4Oztjb29PREQEKSkpmJgo4rMvXSresmD/FdcK7kz97S+VNAtLKypUcOfRA3/kcrnKxK3gwIcYGhrhWM45331a29hiZm5BSHCg2raQoMdUqOiusdz5sycoVaoUjZu10uqzeJWz40bwc5LTJCoTXv2fvQagklPxO9jpsgySi7BqjTQjE3lWFsnphefNj3sFF+74PyQlNVVlwuvDoJDs7a4ay+no6FDRxZnHT9SXLXwY9ATHsnYYv7W6hL6+nsoKN7fuBQBQu3rBq8UUxMveihuh4SSnS1UmvPq/VHReK9lbaSwXkZBMhlzOgDXqL7I5cC+EA/dCmNurJS28XYhITOGw/1MO+6t/1t7L9+FV1ortw7po/Rm0lXjvMZaNfBWvcc8z4dWibjUyUlJJCQrNzqdYFcjC14eEG7kTXg0d7Cjt7MDzVdu1Or6XixO3HoaQnJquMuE14Ili/XpPl4LDkF6+iWbU7GVYmpsy/4dvNI5Q5+zj0dPnVHXLDSeMikvgTWw8XVs0VCtTFJ6uTtx6GExyaprKhNcHIWHK7e+Lro4OXnn2d91f0UbV9SnepOkKFdyYPmO2SpqlpRUVKrrxUEO7GRT4GENDI8o55f9ZrG1sMTe3ICQ4SG1bUJ52Mzk5mfS0NHbv3MbundvU8g75qi/16jdk0tRfC/0cHq7luR3wmJTUNJUJrw+CFd8vjwr5t/PvSiaTIZdnkZya9q8d430q9ZFPTP03iDMifJSSkpLo2bMnmzdv5vLly5w7d445c+ZgZmZG5cqKFSnatGmDRCJh0qRJXLp0iXXr1rFp06ZC9vxhlDE1pXrN2ir/DAwMadCoGfHxsVy7nBtWkpgQz5WLZ6ldr6HKiHpE+CsiwlVXxajv14RbN64QHZUbanL/7i1ev3qhXJc+r4yMDK5cPEelyj4qS68VR6saXmTKs9h1+Z4yTSrLYN81f3xcHLDPngwYHptI6BvVUa+YpBS1/b2KSeB64DMql899kVFiajoyDeEju68ojlnZuWgvPdKkWcN6ZMrl7D9+Ok/9ZRw+fY7Knu6UzX5b5ZuoaJ69VD3fTRvW5XHwUx6H5HZwn796zR3/BzTzK3hFixevw9l37BQNa9fEuZz2I/KtKruSmZXFrlu5N3DSjEz23Q3Gp5wt9uaKJyLh8cmERsUr87SrWpG5vVqq/QNo7OHE3F4t8XFSjHZryte2imLVi9+6NuH7dtqt3lEchva2mHhVpFSe2OLw3UcxsrfFvmsbZZq+tSUO3dsRefAM8uwQp+SHISQ/eoLzoJ6Qp6PnMrQPWXI5EbuPalWnlnWrkymXs+fMZWWaVJbBgXPXqOrmohxBj4iOJez1G5Wy0fGJjJi5BJ1SpVj04zdY5vPkys3JAVfHsuw5fYXMPKt07Tx5kVKlStGybvFWmVLWvV5NRd1P5w52SGUyDpy7SlV3V9W6v3p/c4PiEpPYcOAEHuXLUbdq8TryZUxNqVHTV+WfgYEBDf2aEB8Xx5XLF5R5ExMSuHTxHHXq1VdpN8PDXxMe/lplvw38GnPjxlWi8rSb9+7e5vWrlzTMXpfewtyCiZOnq/3zqVYDAwMDJk6eTveenxfpczRvUJtMuZx9J84q06QyGYdOX6CKR0XK2ijanIioGMJehhfrHOVISklVWb45x/5Tir8t3m6uWu1X+PDEiLzwUTI0NMTT05ONGzcSHh6OkZERVatWZfXq1cpHo+7u7sycOZMlS5YwfPhwfH19+fPPP+ncufMHrn3R1fdrimelyiyaN5MXz8MwMzPn6OF9yOVyevX9SiXvtEljAVi2Nnd0qHvPfly5eI6fJ35Lx0+7k56exr5d/1DetSItWrdXO97d29dJSkwo9trxeVVzdaRNDS8WHDhPbHIqzjYWHLj+gNcxiUzrk3vMyZsOcTPkBfcWjFemfTZzLfU8XfAqZ4eZsRHPo+LYc+U+GXI5Yz5pqsx3M+QFs3adpFV1L1xsLZFlZnL7yUtO3Q+iSnl7OtUp+LXmBans6U7zhvVYsXEb8fGJlHMoy9EzF4iIjObHkbnhRjPmLeXug0ec37tFmda1fWsOHj/Dj7/OpneXjujq6rF9/2EsLczp3Vk11rnfyB9o7lcPOxtrwiOj2Hf0JGZlTBg37Gut6w5QzcmONpVdWXDqJrEp6ThbmXLgXgiv45OY9mnuhO3Je85z81kE96YNBKCCrQUVbC007tPRwpQW3rmjv3n/P0dghOKmrJG7E5Ym7/a6d5fhfdE3N1OuHmPXsTlG5RQ3Z2GLN5KRmIzXjLE49+/GafcWpGUv6xi+6xhxV+9QfdUflPF2RxYTh8vQPqCrS9AvC1WO8WjCbGrvWUq9I2t4vf0QplU8cR3elxdrdpD8uPgvgwKo6u5Kq3o1WLTtALEJSdlvdr3O6+hYpgzuo8w3ddlmbj8K4ebm+cq00bOW8Soyhv6dWnI38Cl387yQysrclPo+uW8UHtPnU8b+vYqRM5fQpn4tnrwMZ/vxC3RpVp8K5bS7iVXUvSaL/9lPXEIyTvY2HDp/nddRMUwekvvytZ+XbOD2oxBubF2kTEtOTWPbUcX66veCFPXefuwcpsbGmJqUpmfb3O/ukOnz8PGsgHNZW2LiE9lz+hJp6RLm/vDNe3uzaMNGTfDa582CuXN48fwZZmbmHDm0H3mmnD5ffKmSd+pExUvCVq7L/R5/1utzLl08x+QJ4/ikczfS09LYs2s7Lq4VaNVG8Y4BQyMj6jdUXZAB4NrVSwQHPda4LT9VPN1o0aAOSzfvIi4hiXL2dhw5e4nwqBgmDh+ozPfrwpXceRDI5V1rlWnJKansOHISAP/s1X92HjlJGRNjTI2N+ayD4snq7YDHzFuzmWb1a+PsUBZZRgb3HgVz7totKrm50raJdk9yhA9PdOSFEmHUqFGMGjUKACcnJwID1cNBfvrpJ376SfFGPgMDA3777Te1PG/r0qWL2pKUb+/79OnTKj/PnDlT5edu3brRrVs3tX3v27ev0OO/K11dXX6aNpsNa5Zy+MBupBIJ7p6VGPndBMo5FR7PaGNrxy8z57Nu1WI2rVuBnp4evnUaMGDQcI3x8efPnEBPT0/jaH1x/NavI4sPXeDgjQckpqbj4WjLgqHd8XUv+BFxT78aXHj4lEuPQklNl2JpakyDSq4MatMAD8fc2GcPBxvqeJTnrH8I0YnJZKF4q+vQtg0Z0LIu+nqaJ3QW1aRvh1F2yw6OnbtIcnIKFV2dmTX5e2pUKXh9cePSpZn/22QWrdnIhh17kcuzqFnVm5Ff98PCXHVpP/cK5Tl86hxx8QmYm5nS3K8eA3t/hqXFu8ci/9a1CYvP3Obg/RAS06R4lLVkweet8XXV/knFf6nidwMxzhN64dCtrfIlTa+27CcjvyVM5XKufzIE71njqTCyHzqlDUm46c+9QROVYTU5Ig+f5VaPkXhMGUmVeVOQRsUSMnM5wb8tfqe6T//mCxx2HubwpZskpaTi7uzIvO+HUMtbcyhbjqDnipuRDQdPqW2r5e2u0pFvXKsqc74dyIrdR5mzYReWpmX4qnNrBndt9051nza8P/Y7DnL44nVF3cuXY+4P3xRa98SUVJbtOKiStvmQol11sLFS6ch7V3Tm1NU7RMXFY1LaiLo+lfimRyecytq8U93z0tXVZer0P1i7ejkH9+9BKpHi4enF6O/G4+RUeJiKra0dv8+ay+qVS9mwdhV6+nrUrlOPgYO+0dhuvg9TRg/Gfutujp67TFJKCm4uzsyZOIaaVQp+SpGUksrKrXtU0rbuV7zV2N7WWtmRd3NxolbVSly4cYeYuASyyKJcWTu+6vEpfTu31/pN0sKHVyor6603ZwiC8J8JCPl3l6/8N1V1tyf92OoPXQ2tGLX9mjePbn3oamitrLcv6VtnfehqaM2oz48c0i8ZL5Eqro6yQJJuahd6UxKY1m5H4u0TH7oaWjGr1ZrHT979xVQfSiU3J2ICLheesYSyrvrhR+3Tt80uPJMWjHqNLzxTCSVi5AVBEARBEAThIyQ68oIgCIIgCILwERJBUYIgCIIgCELJJ5afVCPOiCAIgiAIgiB8hERHXhAEQRAEQRC08OTJE7766itq1KiBn58fs2fPRiqVFmsf69atw8vLi6FDhxb7+CK0RhAEQRAEQSj5SpX60DVQkZCQwIABA3B1dWXhwoW8efOGmTNnkp6eztSpU4u0j6ioKBYvXoy1tbVWdRAdeUEQBEEQBEEopn/++YeUlBQWLVqEhYUFAJmZmUyfPp2hQ4dStmzhb0ifM2cOLVq04PXr14Xm1USE1giCIAiCIAgln47Ov/NPS+fPn6dBgwbKTjxA+/btkcvlXLp0qdDyN2/e5OTJk4wbN07rOoiOvCAIgiAIgiAU09OnT6lYsaJKmpmZGba2tjx9+rTAspmZmfz6669888032NnZaV0HEVojCIIgCIIg/L/VsmXLArefOnVKY3piYiJmZmZq6ebm5iQkJBS4zy1btpCWlsaXX35Z5HpqIjrygiAIgiAIQsn3P7KOfExMDAsWLGDWrFkYGBi8075ER14QBEEQBEH4fyu/EffCmJmZkZSUpJaekJCAubl5vuXmz5+Pl5cXtWvXJjExEYCMjAwyMjJITEzE2NgYPb2iddFFR14QBEEQBEEQiqlixYpqsfBJSUlERUWpxc7nFRoayo0bN6hTp47atjp16rBy5UqaNGlSpDqIjrwgCIIgCIIgFFOTJk1YtmyZSqz80aNH0dHRwc/PL99ykyZNUo7E5/j9998xMjJi7NixeHl5FbkOoiMvCIIgCIIglHw6JeuFUL1792bjxo2MGDGCoUOH8ubNG2bPnk3v3r1V1pAfMGAAr1+/5sSJEwB4e3ur7cvMzAxjY2Pq1atXrDr8b8waEARBEARBEIT/kLm5OevXr0dXV5cRI0bw119/8dlnnzFhwgSVfHK5nMzMzH+lDmJEXhAEQRAEQRC04Obmxrp16wrMs3HjxkL3U5Q8mpTKysrK0qqkIAiCIAiCIPxH0vct+lf2a9R55L+y3/+CGJEXhA8oLCToQ1dBa67uniRdP/Shq6EV07odST33z4euhtaMm/Ymfff8D10NrRl1G0PSzaMfuhpaMa3djkP6RZ+IVtJ0lAUS63/xQ1dDK1Y+jXge/OhDV0Nr5T28STuz+UNXQ2ulm/f90FUQNBAx8oIgCIIgCILwERIj8oIgCIIgCELJV6pkrVpTEogReUEQBEEQBEH4CIkReUEQBEEQBKHk0xHjz28TZ0QQBEEQBEEQPkKiIy8IgiAIgiAIHyERWiMIgiAIgiCUfGKyqxoxIi8IgiAIgiAIHyHRkRcEQRAEQRCEj5DoyAuCIAiCIAjCR0jEyAuCIAiCIAglXykx/vw2cUYEQRAEQRAE4SMkOvKCIAiCIAiC8BESoTWCIAiCIAhCySfe7KpGdOQFoYSSymRs2LiZU2fOkJycTAVXVwb0/wLfmjULLRsdHcOylSu5fecuWXI51apV45vBg3BwsFfmiYyK4viJk1y7cYPXr16jo6uDq4sLfXr1olbNGu9Y9wyW7TrC4Uu3SEpJxd3ZkWGftae+j1eB5U7fuM+Ja3d5+PQ50QlJlLWyoHHNygzq3AZTk9LKfPFJKew/f40Ldx4S+voNGZmZuDrY8Xm7prSpX/j5KUr9l+4/zcGr90lKTcOjXFlGdGlJ/cpuBZY7dfshx28G8CDsNTEJyZS1MqNxNU+GdGyKqXFplbwSmYxNJ69w6Op9wqPjMTUxonpFZ775tDlujnbvVv+MTBafuM6hO4EkpknwsLdmZJt6NPBwLrj+D56y49oDQiJiiE9Nx9KkNNXKl+WblnXwsLdWyZsqkbHo+DVOBDwhLiUNJyszPm9YjZ71q75b3WUZLNt5mMMXb5CUkoZ7eUeG9ehAfZ9KBZY7feMeJ67cyb52EilrbUnjGpUZ1LUtpibGavnP3fJnxe6jhL6KwNKsDJ82qcfXXduip6urdd11TYypOO5rLOpWx6KODwZWFtz7egIvN+wpUnk9c1O8Z/5A2c6t0TU2IuGGPw/HzyTxzkO1vHadWuA5dSRlvN2RRsbwYv1uQmYsISszU+v6S2UyVv6zl6Pnr5CYkop7eSeG9ulK3epVCiz37FUEe46f5UHwU4JCnyGVZbB7ySwc7GwKLPcyIpK+301BKstgzcwpeLu7al33nPqv37SFk2fOkpycQkVXF77s1xffIrRn0dExLF21mlt37pIlz6J6NR+GDR6Ig719vmUCHjzkux8nAbBz8wbMzc3esf4ZLDlwlkPX7pOYmo5HOTtGfNqcBoW1O3cecezmAx48y2l3zGni48HgDk0wMzZSyZuaLmXR/jOcvP2QuORUnGws6dO8Lj2b1n6nugsfjri1Ef5nLVy4EC8vL+U/Hx8f2rdvz8qVK5HL5cp8Odu3bt2qto9Lly4pt798+VKZ3qJFC3755Zd/tf5//T2P3Xv30qJZU4YNGYyOjg5Tfp5OwIMHBZZLS0tj/MRJ+Ac8oHfPHvTr+zlPnj7h+wkTSUxMVOa7cvUa23fuxNHBgQH9+/F5796kpqYxcfIUjp04+U51n7ZiK5uPnqN9w1qM+6Irujo6jPlrJXcDnxZYbsaaHYS+fkN7P19+6NeVhtUqsf3ERb76ZT7pUqkyn39IGEt2HMHMxJivO7dm+GcdMDIwYNLijSzfdfSd6g4wdd0eNp24Qod6PvzQqz06OjqMWrCJO8HPCiz328YDhIZH06FeNX7o3Z6GVdzZduY6A2auIl0qU8k7adUulu07Q21PV37o3Z7uTWpzO/gZA2au4nVM/DvVf8qOU2y6eI8ONTwZ/0kjdHVKMXLdIW6HhRdYLjgiBrPShnzuV41JnZvQs34VHr+O5osluwgMj1bmy5TLGbb2ANuvBdDGx53xnRrhamvJjH3nWXXm1jvVfdryzWw+cob2frUZ178bujqlGDNnOXcDnxRYbsaqbYS+jqB9o9r80L979rVzga+mzVO5dgAu3X3I93NXY2pcmh/6d6eZbzVW7z3OnPW73qnuBjaWeE4ZSZlKFUm6H1i8wqVKUWf/Chx7d+LZkk08njgHA1sr6p/ciLG7i0pW27ZNqL1rMbL4JB58+ysR+0/iMWkYVeZPeaf6/7ZoDVsPnqBN4/p891UfdHR0GPv7fO49Ci6wXEBQCDuOnCQ1PR2Xcg5FPt78df+g+w43Tm+bM3cBu/bup2Wzpgwf8jU6Ojr8NO1XAh6o3wjllZaWxveTpnA/4AF9enxG/759CHn6lHETflJpM/OSy+UsWr4SIyMjjdu1MXX9PjadvEr7uj780LOtot1ZtJU7Ic8LLPfrpoOERkTTsa4P43u1o2FlN/45e4MBs9eotDuZcjnDFmxix/mbtPGtzA892uJS1prftx5m1ZEL7+1zCP8tMSIv/E8zMjJi/fr1AKSnp3Pt2jX++usvsrKyGDJkiDKfsbExhw8fpk+fPirlDx48iLGxMampqf9pvR8HBnH2/HkGDfyKHt27AdCqZQuGDB/JqjXrmPfXnHzLHjh0mFevX7Ng7l94eXoCULu2L0OHj2Tnnr0MHNAfgOrVfNi4dg3m5ubKsh07tGf4yNFs2LSZtq1baVX3gCfPOH71DmN6f0K/js0V+21Um14TZ7Pgn4Os+Xl0vmVnjR5AbW93lbRKFZyYtnwrRy/fpkuz+gBULGfPnj8n4mBjpczXo5Ufw2cuY/2h0/Tv2JzSRoba1T/0JcduBPDdZ23o38YPgE4NqtNj2hLm7TrB+gmD8i0755ue1PaqoJLm7eLI1LV7OHztPt0a+wIQGZfI6TuP6N+mId991laZt5a7C0P+Xsfp2w/5onVDrerv/+INR++HMLZ9AwY0UTyd+KSmF93n/cO8I5fZMKx7vmW/aVlHLa1b7cq0mbmB7VcDmNK1GaAYub/7LIJp3ZvTtbY3AD3rV2Xc5qOsOH2TrnW8sS6jPgpemIAnzzh+5TZjPu9Mv44tAOjYqA69Jsxkwdb9rJn2Xb5lZ435itqVPVTSKlVwZtqyzRy9dIsuzRso0+dv2YeHsyOLJgxTjsCblDZi7f4T9GnXFFfHssWuO4AkPJKTTn5I3kRj7luVRleLfmPg0L0dVg1rcavXaCJ2HwMgfMcRmj08hufUUdzt/70yr/es8ST6B3K9/UDlCHxGYgruE4YSunADKYXcMGvyIPgpJy5dZ2S/HvTt3A6A9k0b0nfsVBZt3MHK3yflW7ZR7RocX78Qk9Kl2bzvKMFhLwo93tW7AVy7+4C+nduxbtfBYtf3bYo28wJDBn5Jj25dAGjdojmDR4xm5dr1zP9zVr5l9x86wqvXr1n09xy8PBXXUB3fWgweMZode/bx9YB+amUOHT1OVHQ07du0Ys/+d6+/f+grjt58wHfdWjGgjeK7/0n96nz2y1Lm7j7JhvED8y07Z0gP6ni5qqRVdnFgyrp9HL7uT7dGtQA4decx956+ZFq/T+jip2gbejatzffLd7Dy8AW6+dXCyszknT/Lv0q82VWNGJEX/qfp6OhQo0YNatSoQf369RkzZgwtW7bk+PHjKvlatmzJzZs3efPmjTJNKpVy4sQJWrXSrkP7Li5euoSOjg4d2rdTphkYGNCuTWsePX5MZFRUvmUvXLqEp6eHshMPUN7ZmZo1qnP+wkVlmquLi0onHsBAX586dWoTHR2t9c3Lqev30dXRoWuL3I6ToYE+nZvW435IGBExcfmWfbsTD9Dc1weA0Ne5v5tydtYqnXiAUqVK0dS3KlJZBq+iYrSqO8DJWw/R1dFRdroBDPX16dyoJvefviAiNiH/+r/ViQdoUVPR0Q2NyP2dpaRLALA2K6OS18Zc8bOhgb729Q94gq5OKbrXzQ2HMNTXo2sdb+49f0NEfFKx9mdVpjRG+nokpeeOat8OVYzst6um+vtqV80DSUYmZx+GaVX3U9fuKq6d5rk3MYprpz73gwu5dt7qxAM0r10NgNBXEcq0py8jePoqgq4tGqiE0fRo3YisrCxOXrurVd0B5FIZkjfRhWfUwL5bW9IjoojYk9s2SaPjeL3zCGU/bYlO9jVRxtsN0yoevFi1XSWM5tmyLZTS0cGhW1u1fRfFmau30NXRoUvrpso0QwN9PmnRiICgJ7yJjs23rLlpGUxKl853+9syMjKYu2YrPTu2wsneVqv6vu3CpcuKNrNdG2WagYEB7Vq34uHjwELazCt4eXgoO/EA5Z2dqFm9GucvXlLLn5iUxLpNmxnQtw9lTN5Px/fk7YeK761Ku6NHF7+a3H/6ssB25+1OPECLGopQtNCI3OsxZ2S/bR3V8Le2tasgkWVw5l4xnyIJJYLoyAv/75iYmJCRkaGS5u3tjaurK4cPH1amnTt3jqysLJo1a/Yf1xBCnjzFqVw5TIxVRzVzOudPn4ZqLCeXywkNDcPTXb1D7OXpSXh4eKEd9Li4OAwNDTE01G5EO/DZK8rb21KmtOoj5ypu5QEIeva6WPuLSVB0PC3KFP4HU5nXtEwhOfP3+EU45ctaq9W/qqsTAIEvIjQVy1d0QrKiTnlGqJ1srShracbG45c5dy+QN3EJBIS+ZMbmg5SzsaRdHe3jzB+/jsbFxoIyRgaq9XdSjDI/Di/8JicxTUJschrBETFM232GZImUem5Oyu3SzEx0dUqh/1ZYhJG+4iHvw1eRWtU98NlLxbVjnN+186pY+4tJUIRF5L0eAp8pQuS8K5ZXyWtraU5ZKwvl9v+aeQ1vRSx8VpZKesINf/RMjDHxVNwkmtWoDED8LX+VfJLwSNJehGNWw1ur4weFPsfZsSwmb83lqOyuOG5QWMHhHcXxz6GTJKWk8lX3Tu9tnyFPQ3Eq56ihzVR0zp8U0GY+DQvD00M9Dr2SpwevwyNITU1TSV+3aQtWFpZ0bKfdTZMmj19E4GJnTZnSqu1uVVdHAAJfvnu7I83I0Py9zb5JfPS84NC7EqGUzr/z7yP2cddeEIogIyODjIwMkpOTOXXqFMePH6dtW/UGuGPHjhw8mPuI9ODBg7Ru3VrrDu27iI2LxcrKUi09Jy0mVnNnLCkpCZlMhpWVldo2K8ucsvmPrL16/ZpLl6/QyK+h1rGr0fGJ2FioT/rKSYuKz39kSZP1B0+jq6NDy7rVC8yXkJzCvrNXqelVUePxiyo6IRlbc/UbgZzR8qh4zTGz+Vl37CK6Ojq0qpU7Qq6vp8uf3/SitKEB3y7eQrsf/6bfHytJlUhZ9+PXahNjiyMqKRUbU/Wwlpy0qMSUQvfRb+kums9Yy2fzt3H8/hMGN/dVhtAAuNpYkCnP4v6LNyrlbocpbtIii3AMTaLjE7Gx1HTtKJ4cRcUV89o5cEpx7dTLvXais39/mq4RawszouOK9/t9XwwdbJFEqI8ap4dHZm9XTIA2yh7BloSr55VERGGk5UTpmLh4rC3M1dJtLC0AiI6N12q/6sdJYO3OAwzp3UXtpuFdxMbGKdu4vKyz28KYWM1Pc5KSkhVtpoayue1tbpv5NDSMQ0eOMXTQV+81vj86MVnZxuRlY2YKQFR8crH2t+74ZXR1StGqZp7vbVlrMuVZ+Ieq3qzmjNRHFrNtE0oG0ZEX/qelpqZSpUoVqlSpgq+vL8OHD6d58+Yq8fE5OnXqREBAAM+fPyclJYWzZ8/SqdP7GzEqDqlEir6+eniFgb5ilFUikaptA5BkT+rTWNbAQLlvTdLT05nxxywMDAz4+ssBWtUbFKux6Oup/4EzyK6T5K1JnwU5evkW+85do2/7ppQv4BG8XC5nytLNJKWm8UO/rsWvdB4SqQx9PfXpQ4bZo80SWYbatvwcuXafvRdv0691A1zKqq76YmpcGk9ne75q14i/h/fhu8/aEB4dz/jl25HIin6O1Oovy8BAQwfDUF+3yPX/pXsLlnzViZ86N6GCnSWSjAwys3IniHeo4YmpkQE/7zzNleAXvIpLZOf1B2y/+iD7GNqtnJLfuTcw0FNuL6qjl26y7+xV+nZoTnn73M5tzj4MNP6O9Yt1jPdJt7QRcg3fTXl2SJNu9kitTvaTIk15M9Mlyu3FJZHKlN/RvAwMiv+9LcjiTTspV9aWT1s2fi/7yyGRSvJp9xRpUqkk33KQT5uZ097mKbt4+Urq+taidq13Xx1LtR4ZBbY76cVoEw5f92fPpTv0a6Xa7rSv40OZ0ob8vGE/Vx4+4VV0PDsv3GL7uZuKOhSjbRNKDjHZVfifZmRkxKZNmwBFzPuDBw9YsGABkydP5o8//lDJ6+rqSpUqVTh48CDlypXDxMSEBg0acObMmf+83gaGBsg0NNxSmeKPt6Ghgdo2AMPszrrGstmdfAMNZTMzM/lj1hyeP3/Ob79Mw9raWi1PURnq6yPLUO/ISbPrVNT47zuBT/l11TYa+HgxvEeHAvPO2bCHy/cfM33o53i6lCt+pfMwNNBHlqH+By3nj1zOH9bC3A5+xvQN+2hYxZ0RXVqqbEtKTefrOWvo36ahckItQGWXcgz+ay37Lt2hZ7O62tVfXw+phiUIczrXRal/dZfcJffaVXeny9+KFZ3GdVDU1cbUmPn9O/DT9pN8s+YAAGUMDZjwaSMm7ziNsaF2Mf75nXupNEO5vSjuPH7Cryv/oUG1Sgzv2VHtGKAIM3ibRCZ7p/kJ7yIzLR0dDd9NnewQqcw0RWdSnpauSNeQV9fIULm9uAwN9JXf0byk0uJ9bwsSEPSEo+evsPDn79F5z+uBGxoY5tPuZd+4GWh+smqYnV5ge5ud5+z5izx8HMjKxfPfS51V66FXYLtjpOFGQ5Pbwc+YvvEADSu7MbJzC5VtNuZlmD+8N5PX7mXYgs0AlDEy5Mfe7Ziybh+l8/m7UqKIya5qREde+J+mo6ODj4+P8mdfX18yMzOZOXMmX331FZ55JoSCYlR+165dODo60r59+/f66LQ4rCytiIlRD5+JzX48bG2luaNtamqKvr4+sRrCZ2Ljcsqqh93MW7iIazdu8OP346hRveAQlsLYWJhpDIHICWmw1fD4/m1Bz14x9u/VuDk5MGv0lwWu7b1i9zF2nLrEyF4d6djo3ddCtjEvQ6SGCaE5Mae2RQjbCXwRwbeLt+DmaMecoT3V6n/q9kNiEpNpWl11bfTaXq6UMTLk3pMXWnfkbU2NNYa2RCcp5kbYFnNVCrPSRtR1c+Lw3WBlRx7At4Ijh374guCIWNKkMrwcbJTHdbEp/HesiY2FGVEaJvVFZ4dj2VoW8dr5ayVuzvbMGjNQ7dznhNRExydib60aThETn0hlN9XY+f+KJDwKQw1PnYyyQ2ok2SE26dnhN4YOtqS/FTdtaG9L/I37Wh3f2tKCKA3hJ9Fx8QDYWFlotd+8Fm/cQXVvDxztbAiPVEzCjE9UfK+i4+OJiIrB3la7QQQrK0uiNbSZOWEx1hpCFQFMTcso2sw49c+e294q2swVa9fRxK8henp6RGQvjJCcorjmo6KjkWVkYGOt3r4WhY1ZGaI0tTuJijRbi8Ln/QS+jGDM0m24Odrx55Ae6Omq3yz5erhw8LdRBL+KJE0ixcvJnqjsuUUudtrVXfiwREde+H+nYsWKAISEhKh15Dt06MDs2bN5+vQpmzdv/hDVA8CtYgXu3b9PSmqqyuStx4GKVQUqVlRfHQUUNy4VXF0ICglR2/Y4MBAHe3uM35oMtnL1Go6fOMk3QwbTvFlTtXLF5eXiyK1HISSnpatMGA14oojD9HRxLLD8yzfRjJqzAkuzMsz/fjDGBSwjuf3ERVbsOUaftk34slPLfPMVq/7O9twMDFOvf3ZcqZdz/i+IAXgRGcvI+RuxMjVh4egvNNY/JknRecn7PgOArKwsMrOyyMiUq5Upcv0dbLjx9BXJ6VKVCa/+2fHslRyK31FKl2WQnK4eyqGro0Mlx9yX/lwLUZyjvBNji8PLxYlbD0NITk1XmfAa8ESxfn9hT1tevolm1OxlWJqbMv+HbzSe+5x9PHr6nKpuueuzR8Ul8CY2nq4ttFv2810l3nuMZSNfxYhjngmvFnWrkZGSSkpQaHa+R4p0Xx8SbuROeDV0sKO0swPPV23X6vgers7cDnhMSmqaSuz6g2DFcT1d3/0GJyI6loioGLoN/1Ft2/iZCyljXJoTGxZptW+3ihW4e99fvc0MClJu10TZZgarv6fgUVAQDvZlMc4+H1FR0Zw+d57T586r5R02ZiwVK7iyfOE8rerv5WzPzaAwktMkKhNe/UMVE7y9nAppd6JiGbFgC1amJiwa2Qdjo/xH13V1dKiUpx27elWxXGk974pa1V34sESMvPD/TnCw4uUmlhomN9nb2zNgwAA6depErVq1/uuqKTX280Mul3P4SO7LjaQyGcdPnqSSlxd2toqRu8jISJ6/UF2zuZGfH0FBwQQF577E5cXLl9y9d5/GjfxU8u7YtZudu/fQu2cPunb+9L3UvWWd6mTK5ew5fSVP3TM4cP46Vd3KK0dBI6LjCHutOlkyOj6REbOXo6NTikXjh2Jplv8o1PGrd/hz4x7aN6zF2L6d30vdAVrVqkKmXM7uC7kvNpLKMth3+Q4+FZywt1KMCofHxBP61oTD6IQkhs/bQCmdUiwZ0w8rU82j3y7Zb7w8diNAJf3svUDSJFIqlS/4j3aB9a/qRqY8i13Xc18cJs3IZN+tx/g4l8XeQjF5Ljw+idBI1VHImGT1FY1exSVy/clLKpcreJnA2OQ01p6/jae9NfXdC36DbH5a1s2+ds5czq27LIMD565R1c0lz7UTq/nambkEnVKlWPTjN/leO25ODrg6lmXP6Stk5rmR2nnyIqVKlSp0UvX7YGhvi4lXRUrliYkO330UI3tb7LvmLp+ob22JQ/d2RB48gzw7RCT5YQjJj57gPKinyuvqXYb2IUsuJ2K3di9Ea1G/NplyOXtPnFOmSWUyDp25SBWPipTNXu41IiqGsFfarW4yYWh/Zo4fofKvR3vFDfio/j2ZNmawVvsFaOzXUNFmHs2zfKdMxrETp6nk5ZmnzYzi+YuXamUDg4MJDM4dAHnx8hV37/nTJE+bOe2nCWr/mjVuBMD4sWMYNvhrrevfupa34nur1u7cw6dCudx2JzZBZUlJUDwtHDZ/M6VKlWLJqL75tjuaxCalsO74ZTzLlaV+JdGR/xiJEXnhf5pcLufu3buAIgbywYMHLF26FHd3d2rX1hyGMXHixP+whppVquRF40Z+rF2/gYSEBBwdHDhx6jRv3kQydkzuC5Xm/D2X+/4BHDt0QJn2SccOHDl2nCnTfuGzbl3R1dVl9969WFpa0L1b7kTQS5evsGrNWso5OlLe2ZlTp1XnAtSqWUPjzU5hqrq70KpudRbtOERsYjLOZW04ePEGr6NjmTKolzLf1OVbuP34CTc3/q1MGz1nBa8iY+jfsTl3g55yNyj3xTZWZqbU9/ECFCO0Py/fgnkZE+pU8eTIZdW3iVbzqICTnXaP6H0qOtHatwoLd58kNjEFZzsrDly5S3h0PD/3z71hmLJ2D7eCwrizYroybcT8TbyMjuPLtn7cCXmu8kZGa7My1M9+1XrT6p64Odqx4tA5wmPj8angxIuoWLaduY6NuSld/LS/iaxWvixtfNxYcOwasSlpOFubc+B2IK/jkpjWvbky3+Ttp7gZ+pp7fwxXpn02fxv13JzwcrDBrLQhz2Pi2XPjERmZcsa0q69ynIEr9lKtfFnKW5sTnZTKrusPSZXKWDigIzo62sWxVnV3pVW9GizadoDYhCSc7W05eP664toZnPuytqnLNnP7UQg3N+fGKo+etUxx7XRqyd3ApypvEbYyN6W+T24Y05g+nzL271WMnLmENvVr8eRlONuPX6BLs/pUKKf9TRSAy/C+6JubKVePsevYHKPsfYYt3khGYjJeM8bi3L8bp91bkJa9pGb4rmPEXb1D9VV/UMbbHVlMHC5D+4CuLkG/LFQ5xqMJs6m9Zyn1jqzh9fZDmFbxxHV4X16s2UHy4+K/DAqgimdFWjSozdItu4lLTMLJ3o7DZy8THhXDpOFfKvP9snA1dx4GcmXnamVackoqO46cAuD+Y0VneMeRU5iaGFPGxFjZWa9XQ31Z1eQUxc1jzcpeeLu7alV3AG8vT5o0asjq9RuJj4/H0dGB46fO8CYyknFjRirzzfp7HvcDHnDi4F5l2qcd2nPk2HEmT/+VHl27oKeny869+7G0sOCzrrnfeb8Gqt8ByF3Wsq6vL+bm2q+W5VPBida1KrNw72lik3LanXuEx8Qzrf8nynyT1+7lVvAz7i6bqkwbvnCzot1p05C7T55z90luu2NlakKDyrlLa3791zqqVXTC2daKmMRkdl24TapEyoIRvbX+3v6n3vPciv8FoiMv/E9LT0+nVy9F51FPTw97e3s+/fRTRo4cqXGVgpJk/LixrN+4iVOnz5CUnEyFCq788vNUfKoWvMa4sbExc2b+zvIVq9jyzzaysrKo5lOVoYMHYZHnBVBPQxV/gF69fs3sv/5W28/sP37XqiMPMH3o5zjsOsLhSzdJSk3D3dmBeWMHUauS+lrNeQU9VyxfuOGQ+gTjWpXclB350FdvkGVkEpeUzC8r/1HL+/Pg3lp35AF+HdiVJfvMOXT1Homp6Xg4lWX+qL74eroWXP/smOV1x9RfIuPr6arsyOvr6bHmh4GsOHSOi/5BHL0egLGRAc1qVGJU11ZYFmNETZPferRkscV1Dt4JIjFNgoe9NQsGdMC3QsFhTT3rVeHC42dcCnpOqkSGZZnSNPBwZlBzXzzsVc+nt6MtJ/yfEJmYgomhAQ3cnRjRpi5OVtrFx+eY/s0XOOw8rLh2UlJxd3Zk3vdDqKXhZWF5BT1XdIg3HDyltq2Wt7tKR75xrarM+XYgK3YfZc6GXVialuGrzq0Z3LWdWtniqvjdQIxdc0OLHLq1Vb6k6dWW/WQk5rOMoFzO9U+G4D1rPBVG9kOntCEJN/25N2iiMqwmR+Ths9zqMRKPKSOpMm8K0qhYQmYuJ/i3xe9U96mjBrHinz0cPXeFpJQU3Fyc+XPiaGpW9iqwXFJKKiv+2auStvWAYmTc3tZa2ZH/t/049lvWbdrCyTPnSEpOpqKrK79OnUy1qlUKLGdsXJo///iNpSvXsHnbDrKy5FSvWpVvBn+t0mb+2377qguL95/h0DV/ElPT8ChXlgUjeuPr4VJguaCXiqdT645fVtvm6+Gi0pH3Lu/AiVuPiIxPxKS0IfUrVWTEp81xstWurRc+vFJZWW+9fUIQhP9MWEjQh66C1lzdPUm6fuhDV0MrpnU7knpO/QbgY2HctDfpu9//yhn/FaNuY0i6qV0IyIdmWrsdh/QL7tiWZB1lgcT6Xyw8Ywlk5dOI58GPPnQ1tFbew5u0Mx9u7tW7Kt2874euAumnNvwr+zVq2f9f2e9/QYzIC4IgCIIgCCVellh+Uo0INhIEQRAEQRCEj5AYkRcEQRAEQRBKvlJi/Plt4owIgiAIgiAIwkdIdOQFQRAEQRAE4SMkQmsEQRAEQRCEkk+E1qgRZ0QQBEEQBEEQPkKiIy8IgiAIgiAIHyERWiMIgiAIgiCUeGIdeXViRF4QBEEQBEEQPkKiIy8IgiAIgiAIHyHRkRcEQRAEQRCEj5CIkRcEQRAEQRBKPrH8pBpxRgRBEARBEAThIyQ68oIgCIIgCILwERKhNYIgCIIgCELJJ5afVCNG5AVBEARBEAThIyRG5AVBEARBEISST0eMP7+tVFZWVtaHroQgCIIgCIIgFCT10q5/Zb/Gft3/lf3+F8SIvCB8QIFPXnzoKmjNy82ZWP+LH7oaWrHyacTz4EcfuhpaK+/hTeLtEx+6Glozq9X6o62/Wa3WH+11D4pr/5C+14euhlY6ygJ5FhL4oauhNRd3LxJun/zQ1dCaea1WH7oKggaiIy8IgiAIgiCUeFlisqsaEWwkCIIgCIIgCB8h0ZEXBEEQBEEQhI+Q6MgLgiAIgiAIwkdIxMgLgiAIgiAIJV8pMf78NnFGBEEQBEEQBOEjJDrygiAIgiAIgvAREqE1giAIgiAIQomXJUJr1IgzIgiCIAiCIAgfIdGRFwRBEARBEISPkAitEQRBEARBEEo+8WZXNWJEXhAEQRAEQRA+QmJEXhAEQRAEQSjxxGRXdeKMCIIgCIIgCMJHqNgj8gsXLmTRokUAlCpVChMTExwdHalTpw59+/bFzc1NmbdFixY0a9aMqVOnFnn/165do3///uzcuRMfH5/iVk9jff38/KhVq9Y77+ttu3fvZuLEicqfTU1NcXNzY/DgwbRq1eqd9z98+HCSkpLYuHEjoPgsa9as4c6dO++87/ft7XORw9jY+IPUd926dVSoUIGmTZuqpGtzTX5oycnJrFuzgquXLyGRSPD08mLgoG9wc/coUvkXz5+xauVSHj0IQE9Pn9p16vH1kG8wN7dQ5omJiWbdmpWEBAUSGxuDjo4OjuWc6NCpMy1atqZUMeMSpTIZK//Zy9HzV0hMScW9vBND+3SlbvUqBZZ79iqCPcfP8iD4KUGhz5DKMti9ZBYOdjYFlnsZEUnf76YglWWwZuYUvN1di1VfTfVfv2kLJ8+cJTk5hYquLnzZry++NWsUWjY6Ooalq1Zz685dsuRZVK/mw7DBA3Gwt8+3TMCDh3z34yQAdm7egLm52TvXf/mOQxy+cJ2klDTcyzsyrGcn6lXzLrBc2Os37D55kYCQMALDXiCVZbBvwXQcba3V8kqkMrYcPs2Rizd4HRWDmYkx1TwrMrh7B9ycHUp03VPTJSzddoDT1+8Sl5hMOTtrerVrxmetG2td77z1/1ivfV0TYyqO+xqLutWxqOODgZUF976ewMsNe4pUXs/cFO+ZP1C2c2t0jY1IuOHPw/EzSbzzUC2vXacWeE4dSRlvd6SRMbxYv5uQGUvIyszUuv5SmYwNGzdnf2+TqeDqypf9++Jbs2ahZaOjY1i2clX291ZO9Wo+fDN4EA4Oud9biUTCoqXLeRwURFRUNHK5HEcHe9q2bsUnHTugp/duQQ451/6RC9dJSknFvbwj3/T8pNBr/9nrN+w6eYEHea79vQt+Ubv2bz0MYtiv8/Pdzzc9P2Fg13bv9Bn+P3ry5Am//fYbd+7cwcTEhM6dO/Ptt99iYGCQb5nIyEjWrVvHpUuXeP78OaamptSpU4exY8dSrly5Yh1fq6vOyMiI9evXA5CSkkJQUBDbtm1j+/btzJgxg86dOwOwaNEizMze7Q/Su1q0aBHGxsb/Skc+x6pVqzA1NSU2Npa1a9cyYsQIVq1aRePG7/5HIa8ePXqodUxLmpxzkUNH58M89NmwYQPNmjVTO18l4ZosDrlczi8//0RY6BO6du+JmZk5hw/tZ9KP45i7YAmO5ZwKLB8dHcXE8WMxNjGh34CvSUtPY++uHTx7Fsqfcxehr68PQGJiIjHRUTRs1ARbWzsyMjO4e+cW8/+ezauXL+j/5dfFqvdvi9Zw+uotenVshbNDWQ6ducTY3+ezeNoPVPfO/wYkICiEHUdO4urkiEs5B4LDXhTpePPX/YOuri7IMopVz/zMmbuAC5cu063zJ5RzdOD4ydP8NO1X/vz9V6pWqZxvubS0NL6fNIWU1BT69PgMPT09du3bz7gJP7FswVyN155cLmfR8pUYGRmRnp7+Xuo/fekmTl2/Q5/2zXG2t+XguWuMmb2UZZPHUKOSW77l/IND2Xb0LBWc7HF1tCfo2ct8805ZvI7zt/zp0tyPzzu0ICougZ3Hz/P1z3+xddYkHGytSmTdM+VyRv2xmEdPn9OjTWOc7e24ev8Rs9ZsIyklla+6tNWq3jk+5mvfwMYSzykjSX32iqT7gVg3q1f0wqVKUWf/CsyqefH0r9VIY+JwGfo59U9u5GK9bqSGPFNmtW3bhNq7FhNz7joPvv0V06qeeEwahqGdNQEjp2ld/z//nseFS5fp2vlTyjk6cOLkaSb//Atz/phR6Pf2h4k/Kb63PT9DV1eP3fv2MW7CJJYtnKf83kqkUp49f07d2r6UtSuLjk4pHj56zLKVq3kcGMTE8d9rXXeAX5ZuzHPt23Hw3FW+nb2EpZPHUKOSe77l/IOfsv3oWSo4ORR47bs62jN9+AC19MMXr3Pt/iPqF3LDUCKUsMmuCQkJDBgwAFdXVxYuXMibN2+YOXMm6enpBQ4YPnjwgBMnTtC9e3eqV69OXFwcS5cupUePHhw8eBArq6K3n1p15HV0dKhRo4byZz8/Pz7//HOGDBnCTz/9RK1atXB2dqZy5fy/OP9LqlSpojzpdevWpVmzZmzatOm9d+Tt7e2xL2BUrzjS09MxMjJ6L/vKK++5KIk+tmvy8sXzPH70gB8nTcWvURMAGjVpyjeDv2TLpvV8/+NPBZbfsW0L6ZJ05i5Ygq1dWQA8Pb2Y+tOPnDp5jHbtOwFQoUJFfp/1t0rZTp904ddpkzm4fw99+32p6CwUwYPgp5y4dJ2R/XrQt7NidKd904b0HTuVRRt3sPL3SfmWbVS7BsfXL8SkdGk27ztapM7M1bsBXLv7gL6d27Fu18Ei1bEgjwODOHv+AkMGfkmPbl0AaN2iOYNHjGbl2vXM/3NWvmX3HzrCq9evWfT3HLw8FZ22Or61GDxiNDv27OPrAf3Uyhw6epyo6Gjat2nFnv3vXv8HIWEcv3KL0X270K+T4slgx8b16D1+Bgu27GXNL+PyLdvE14fTq+dgUtqIjQdP5tshiIyN58z1e3zRqSVj+nZVptes5Maw3xZw5sZdPu/QokTW/cz1u9wPesqUIX35tHkDAD5r3Zgf565i9e6jdG7eECtzU41lC63/R37tS8IjOenkh+RNNOa+VWl0dVeRyzp0b4dVw1rc6jWaiN3HAAjfcYRmD4/hOXUUd/vndnK9Z40n0T+Q6+0HKkfgMxJTcJ8wlNCFG0gJfFrsuud8bwcP/Ioe3RXXZOuWLRgyfCSr1qxj3l+z8y174NBhXr1+zcK5f+V+b2v7MmT4SPXJMYkAAKZnSURBVHbu2cvAAf0BMDM1ZcHff6qU7dShPSbGxuw7eIihg77Gysqy2HWHvNd+V77IvvY7NK5Hn/G/sXDLXlb/kv9NQmPfapxaXROT0kZsKuDat7Ywo33jumrpq3YfxtnejspuLlrV/f+zf/75h5SUFBYtWoSFhQUAmZmZTJ8+naFDh1K2bFmN5Xx9fTly5IjKU5xatWrRrFkz9u7dy8CBA4tch/c2XGpoaMiUKVOQyWTs2LEDUIQx/PLLL8o8d+7c4ZtvvqFRo0bUqFGDzp07s3fvXo37i42NZeTIkdSoUYNGjRqxbNkytTxPnjxh2LBh+Pr6UqNGDYYMGcLz58+V2728vACYPXs2Xl5eeHl5ce3aNQCysrJYvXo1bdu2pWrVqrRs2ZJ169ap7D8iIoIxY8bQsGFDfHx8aNGiBb///nuB56FMmTJUqFCBly9zv0hnz56lR48eVKtWjfr16/Pzzz+Tmpqq9lm++OILfHx8aNWqFXv2qD/KXLhwITXfekQYHBxM37598fHxoU2bNuzfv5/hw4fTr18/tXL379+nV69e+Pj4sHnz5iKdw6Keq8L069ePoUOHqqQ9evRI5XcCit/ZypUrWbhwIQ0bNqRevXpMnDhR7Xy9efOG8ePH07BhQ6pVq0a7du2UT4latGjBq1ev2Lx5s/L3vnv3buW2vNckwPHjx+ncuTM+Pj40atSIP/74A4lEotx+7do1vLy8uHTpEuPGjaNmzZo0b96clStXFuscaOPSxfNYWFrSoGEjZZq5uQWNGjfl2tUryGTSAstfvnSBOnXqKTvxADVq+lKunBOXLpwr9Ph2ZcsikUjIyCj6aN+Zq7fQ1dGhS+vcpyGGBvp80qIRAUFPeBMdm29Zc9MymJQuXeRjZWRkMHfNVnp2bIWTvW2RyxXkwqXL6Ojo0KFdG2WagYEB7Vq34uHjQCKjogooewUvDw9lZwCgvLMTNatX4/zFS2r5E5OSWLdpMwP69qGMicl7qf+pa3fR1dGhaws/ZZqhgT6fNmuAf3AoETFx+ZY1L2OCSenCb/BT0xRPDt7u8NpYKEYuDbOf9BTXf1H3u4+fANCmoa9KepuGvkhkMs7dvK9V3eHjv/blUhmSN9FalbXv1pb0iCgi9hxXpkmj43i98whlP22JjoHimijj7YZpFQ9erNquEkbzbNkWSuno4NBNuyciFy5dUnxv2+eWNzAwoG2b1jx8/LiQ7+1lvDw1fG9rVOf8hYuFHrtsWTsAklNStKo7wKlrdxTXjtq13xD/4FDevIdrX5MHIWG8iIiinV9trcr/f3f+/HkaNGig7MQDtG/fHrlczqVL6m1+DjMzM7VQLHt7e6ysrIiMjCxWHd5r3IO7uztly5bNNyb69evX1KpVixkzZrB06VLatGnD5MmTNXZap0yZgrOzMwsXLuSTTz5h7ty5bN26Vbn9xYsX9O7dm4SEBGbOnMmff/5JbGwsX375JVKponOzbds2QNGJ3LZtG9u2baNKFUWc4owZM1iwYAFdunRhxYoVdO3alT///FPlGOPHjycwMJDJkyezatUqRo8ejVwuL/AcZGZmEh4ejp2d4ot99OhRhg0bhqenJ4sWLeKHH37gxIkT/PRT7kiqRCJh4MCBREdHM3v2bMaNG8eKFSvw9/cv8Fjp6ekMHDiQ+Ph45syZw9ixY1m5ciUPHjxQyyuTyRg3bhyffvopK1euxM/Pr0jnsKjnKodcLicjI0P5Lysrq8DPoMnmzZsJCwtj5syZjBgxggMHDrBkyRLl9ri4OHr16sX169f57rvvWL58OV9++SVv3rwBFOEztra2tG3bVvl7b9asmcZjnTp1itGjR+Pu7s7ixYsZNGgQ//zzDz/88INa3p9//hlXV1cWL15M8+bN+fPPPzl//nyxP19xPH36BDc3D7UQJQ/PSkgk6bx6mX/oQ0x0NAnx8bh7eKlt8/CsxNMnIWrpEomExIQE3ryJ4NTJ45w6cQyvSpUxNDQscp2DQp/j7FgWE2PVTkll9wqK7WHPNRXTyj+HTirCIbp3em/7DHkailM5R0yMjVXSc/7IP3kaqrGcXC7naVgYnh7q4R+VPD14HR5BamqaSvq6TVuwsrCkY7t3C+fIKzDsBeUd7Cjz1vmvkh07HRSW/zVTVE5lbbGzsmDzodOcv+XPm5g4HoSE8cfqf3C0s1brJBfVf1F3aUYGujo66OmpPmEyyo5nfRyq/fX5sV/778K8hrciFv6tNj/hhj96JsaYeCrOgVkNxVPR+Fuqf98k4ZGkvQjHrIZ24R0hT57iVK6c2ve2kqcnUMj3NjQMD3f10BUv5fdWdSBJJpORkJBIZFQUFy9fYefuvZS1s6Oco/ZzQ4LCXmq89iu7uyi3/xuOXroBQLtGdf6V/f+ve/r0KRUrVlRJMzMzw9bWlqdPi/dkKTQ0lJiYGJW5pkXx3pefdHBwIDpa8x19x44dlf+flZVFnTp1ePPmDdu2baNr164qeevXr8+PP/4IQOPGjYmJiWHp0qX06tULHR0dFi1ahLm5OWvXrlV2MmrVqkXLli3ZsWMHffv2VYb/ODg4qIQCPX/+nE2bNjF9+nR69eoFQMOGDUlPT2fx4sXKY/j7+zN27Fg6dOigLNulSxe1z5XTeY2NjWXp0qVERUUxatQosrKymD17Nh06dGDGjBnK/La2tgwZMoThw4fj4eHB7t27iYyM5MiRI7i6ugKKEJB27dopf9Zk165dxMTEsHXrVpycFLHSVatWpU2bNpQvX14lr0wm47vvvlP5LD/++GOh57Co5yqHn5+fynHHjBnD8OHD8/0Mmtja2vLXX38B0KRJEx4+fMixY8f4/nvFo8V169YRExPDkSNHlJ+7QYMGyvKVK1fGwMAAGxsbld+7JosWLaJGjRoqxytdujRTp04lMDBQ+VQHoE2bNowaNUp5vLNnz3Ls2DGaNGlSrM9XHHGxMVSpqj7pOyd8KTY2BtcKFdW252zLmzcvSysrkpKSkMmk6OvnTsg5sG83G9atVv5cvUZNRn+nflNTkJi4eKwtzNXSbSwtAIiOjS/W/vI/TgJrdx5gVP+eah2ndxEbG4eVpfrjcevs8xgTq3lkLCkpGZlMprFszuP2mNhYjI0VE5mehoZx6MgxZkybUuSwpaKIjk/E2kI9Fj9ntDw6LuGdj6Gnp8vs7wYxedE6xv25XJnuXcGZ1dPHYWpiXEDp/P0XdXdxsCNTLicgOEwl5v7OY8WNbeQ7HONjv/bfhaGDLbEXb6qlp4dHZm+3IykgCKPspweScPURcklEFEaOdlodPzYuTmNYS97vnibK762mspY53/lYjPPcIFy8fIU/ZueG2Hh6uDPu29Hv9D2Ojk/I59pXXE9RcfFa7zs/mXI5J67cooqbC8722p33/9y/tPxky5YtC9x+6tQpjemJiYka5z6Zm5uTkFD0tiQrK4vffvsNOzs7lb5yUbz3jnxWVla+K1wkJCSwcOFCTp06xZs3b8jMfqyW95FEjtatW6v83LZtW/bt20dERASOjo5cunSJDh06oKurq3zsb2ZmRuXKlQkICCiwjpcvXwYUHbO8IQMNGzZk5cqVhIeHU65cOSpXrsyaNWvQ1dXFz88PFxfN8WN5O69GRkYMGzaMnj17EhoayqtXr5g0aZLKcerWrYuOjg4BAQF4eHhw//59PDw8VDrtLi4uVKpUqcDPERAQgKenp7IzC+Dk5JRvubcnfhblHBb1XOVYt24dZcqUUf6cX3xYQRo2bKjys5ubG4cOHVL+fOXKFerXr6/yubWRkpLCo0ePlDeMOTp06MDUqVO5deuWSke+UaPc8JZSpUrh5uZGRETEO9WhMFKpVDkhNa+czrdUkn9oTc5TFU3lc2bTSySqHfkmTVvg7uFJQkICN69fJT4+rsBjaCKRyjDQeEx95fb3YfGmnZQra8unLd/vXBSJVJLPOVOkSaUStW055SCf8519jiV5yi5evpK6vrWoXavwFTWKQ3H+1Zv2nN9J+ns6/6Ymxni6ONGyXk18PCrwIiKKdfuOM3HeahZNGomhQfHDa/6Lurf1q8Oq3Uf5dfkmxn/VE2cHxWTXnScuKOugrY/92n8XuqWNkGtoK+Tp0uztisEinewQEE15M9Ml6JmVUUsvCqlEc1tpoGwrC/7eFvR7e7sNrFHNh5m//UJySgp3793j6dOwd56ont+1nxOm9r6unbxuBAQSm5D0zhO8hXe3cOFCrl69yqpVq1RuGovivXfkIyIi8h1FnjBhAnfu3GHEiBG4u7tTpkwZtm7dypEjR9Tyvj2KaGOjWIIrKioKR0dH4uLiWL9+vTIuOi9NX+a84uLiyMrKon79+hq353RO586dy9y5c5k3bx7Tp0+nQoUKjB07ljZt2qjkz+m8mpub4+joqIx7iotTjNyNGDEi3+OAYhkia2v1JdKsra1VYrXfFhkZqXG01crKSq1c6dKlMXkrBrco57Co5yqHl5fXO092ffvuVl9fXyXUJz4+Hg+Poi29WJCkpCSysrLUzr2pqSkGBgZqd9N5V+PJqVdSUtI71wMUT0yS39qXmbk5BgYGyGTqDXhObLyBYf7LW+V01jWVzzmfhm+VtytbFrvsm6+mzVqwaMHfTPnpB5auWFfk8BpDA32kGo8pU25/VwFBTzh6/goLf/7+va+MZGhgmM85U6QZGGg+D4bZ6RrLZv++cvKcPX+Rh48DWbk4/6XgtKU4/+pzGnJ+J0bv4fwnp6YxePpc+nVqxRedckeyvCuW55tf53Pg3FWtlnL8L+puY2HGX98P5ecl6xn5x2IATEob8cOXPZi2dCPGRkUPI3vbx37tv4vMtHR0NLRHOkYG2dsVf5Pk2fMrNOXVNTJUbi8uA0PNbaVU2VYW/L0t6Pf2djtraWmJZfaTtyaN/Ni6bTsTJv/M2hXLtJ7smt+1L5G9v2vnbUcv3kBXR4dW9bULhftfkt+Ie2HMzMw09gMSEhIwN1d/OqfJ9u3bWbx4MTNmzFCJLiiq99qRDw4O5s2bN2phMqCIvT179iwTJkxQmYi5ZcsWjfuKfesxWE64jq2t4rGcubk5TZs25fPPP1cr+3aH9W3m5uaUKlWKLVu2aOz0V6igiOWzs7Pjjz/+QC6XExAQwNKlS/nuu+84evQozs7Oyvz5dV5znjRMnTqVatWqqW3PiaO3s7PTGNceExOjMrqtqfyjR4/U0mNjY9XOgaanJEU5h0U9V4XR1CEtzmOnvCwsLIo9GUQTU1NTSpUqpXatJSUlIZVKi/wlfB8eP3rATxNUVyVYuXYTllbWxGl4JJxTZysr9RvAHDnb3v58AHGxsZiamqqMxmvi16gJx48e5kHAfWr5Fi2G0trSgigN4SfR2Y+GbawsirSfgizeuIPq3h442tkQHqloG+ITkxXHiY8nIioGew3rhxeFlZUl0TExauk5j+at8/lDbWpaBn19fWLj1D97bPb5yAnPWbF2HU38GqKnp0dE9tyOnIlyUdHRyDIysLHW7obYxsKMKA3hIdHxiYrtlu9+XZ++dpfYhCSa+KqGfflW9sCktBH3Ap9q1ZH/L+oOUMvbnb3zpxPy/DXpEgkeLk7K0IXy7xBi8LFf++9CEh6FoYZJt0YOdtnbFW12eoQipMbQwZb0l6pPNA3tbYm/od1kYytLS2JiNLWVqt+9tym/txp+b7FxOd/5gr+LjRv5sXbDJi5fu0an9tqtw25jYa4xfCY6XvF9sM0Oz3pf0qVSzt28R52qXhpDekqqrBK2/GTFihXVYuGTkpKIiopSi53X5MSJE0ybNo3Ro0fz2WefaVWH99aRl0gk/PrrrxgYGNCjRw+17VKpFLlcrtIZTE5O5vTp0xr3d+LECZXwmmPHjmFnZ6dcfrFBgwYEBwdTuXLlAuPS9PX11Uanc+544uPjadGi8CXSdHR0qFatGt9++y2nT5/m2bNnKh35/FSsWBF7e3tevHhB3759883n4+PD3r17efbsmTJ859mzZzx+/JjatfOfSV61alX27t3LixcvlPV5+fIljx8/xte38DvsopzD4p6r/Njb23P58mWV0KuCZnQXpEGDBqxZs4bXr1/j6OioMY+m3/vbTExM8Pb25ujRo3z55ZfK9JwnREU5h+9LhQpu/DJDdVnD/2PvrqOiTNswgF9DdzeChJSACoqUomthr92KsRYYn51rr61rY6Firl0YoKioYGJhEYIK0t093x8Do+PM0DID3r9z9pz1jZmLAYZ7nvd+n0dZWQWGRsZ4/y4EpaWlHKNvYaEfICkpBd0K2otU1dSgqKiEiPBQrn3hYR9haMR/XuJy5a9hbjVmYzAx0MOLtx+Rk5vH0b/7Lpx1s5mpgT6/U6ssPjkV8UkpGOC+gGvf/PU7IScjjVtHd9XosY2NDPHqTQhycnM5bpz7GBbG3s+LiIgIDA2aIiz8E9e+D2Fh0NbShEzZ65GUlIw7AfdxJ4D7ZumpM2fDyNAA+3Zuq1F+U4MmCH4fjuzcPI4b595FfGbvr62UDFZh/fPN/0wmE6WlpSgprdmiPvWRvZyoiAjMfni8pyGs35O21tw3h1dVQ//Zr43M1x+h3K41a57vH254VWrbAsU5ucgJiyo7jjX4pNTaGhnPvt/wKqmtAWk9bXw9eKZGz29sZITXvH5vQ0PL9lf8exsewX3z/8fQMGhraVXa6lBQ1npTnffJn5ka6CL4fVi9/OwDwIPgEOTk5dNNrrXk4uKCvXv3cvTK37x5EyIiIlz3DP7syZMnmD17NgYPHsy3c6MqalTIl5aW4tWrVwCA3Nxc9oJQ0dHRWL9+Pc/eZXl5eVhbW+PAgQNQUVGBmJgY9u/fDzk5OZ4jho8fP8aGDRvg7OyMwMBAXL58GcuWLWMXM+WfXiZMmIAhQ4ZATU0NycnJePr0Kdq0aYPevVl38hsZGcHf3x9t2rSBtLQ0DA0NYWhoiJEjR2L+/PmYMGECWrZsiaKiInz+/BlPnjzBnj17kJWVhQkTJuDPP/+EoaEhioqKcOzYMXYPeVUwGAwsXLgQc+fORW5uLjp27AhpaWnExsYiICAAs2bNgqGhIQYMGABPT09MnjwZM2fOBADs2LGD3U7Ez8CBA7F3715MmTKFfRPmrl27oKamVqWVOKvyGlbltaoKV1dXnDt3DqtXr0aXLl3w4sUL+Pr6Vuncn40dOxaXL1/GqFGjMHXqVOjp6SE6OhqfP39mzzZjZGSEx48fIzAwEAoKCmjSpAn7UuiPpk2bBg8PD8ydOxd9+/ZFVFQU/v33X7i6unL0x/9qcvLyaGXD/cHB2bk9gh7ex6Ogh+x55DMzMhD48D7a2jtwjKjHxcUCALS1v3+4cXRuhzv+t5CUlAh1ddbI2OtXL/DtWwz69hvIPi4jI51jpddyt/1ugsFgwKiKq8gCQCeHNjh5xReXbgWw59IuLCrCtbsPYWliBE011uhWfFIK8gsLYaBb/ZkeFk4eg/xCzr7V4JCPOHvDH9PHDEFT3Zqvt9De2QlnL1zC9Zt+7HnkC4uK4HvrDszNTKFRdlUwMTEJ+QUF0NdrwnGu15GjCA2PgJkJ64NSdMw3vHodwn4sAFixZCHX8967/xD3HjzE/NkzoV7J735FOtvb4LiPPy7eCWTPxV5YVISrAY9h1cwAWqqs34P45FTkFxTCoAavVdOyUVa/R8GYNOj7jVn3g0OQV1AIM4PKBzoElZ2XtMwsHL16Cyb6umhrVfPf+4b+s19VklrqEFOUR+6nr2CW3TsVd+EmtAd1h1b/bux55MVVlaE9sDsSfe6itKxNJft9BLI/fILeX0PwZf9/QNmHwaaTh4NZWor4CzdrlKm9sxPOXbiI6zd82fPIFxYVwfe2fxV+b53hdcQbYeHhMC1r24yOicGr128weMD3DoOMjEwoKMhz/X296cuactPEpPLBEX46lf3sX7oTyJ5HvrCoCD5lP/uadfyz7xv4DFKSEuho17JWj1PvftHNrjU1bNgwHDt2DB4eHpg8eTISEhKwceNGDBs2jOMeQTc3N8TGxuLWrVsAWFN/e3h4wMDAAH/++Se7pgZY7dE/T1hSkRoV8vn5+ewZTGRkZNCkSRM4Ojpi165dFU6bs2XLFixbtgwLFy6EkpISRo8ejdzcXBw6dIjr2FWrVuH06dM4deoUZGVlMXPmTI5R7aZNm+Ls2bPs/vXc3Fyoq6vDzs6OowBbtmwZ1q5di4kTJyI/Px9Hjx6Fvb09li5dCkNDQ5w+fRq7d++GrKwsDA0N0b07681XUlISpqamOHbsGOLi4iAlJQUrKyt4eXlVqwe8R48eUFBQwN69e3H16lUAgK6uLtq3b88u1KWkpHDo0CGsWLEC8+bNg6amJtzd3eHv719hD3b5ecuXL8fcuXPZ5126dImrn5uXqr6Glb1WVeHi4oJ58+bh+PHjuHjxIlxcXLBy5UqOkfCqUlZWxqlTp7BlyxZs3rwZeXl50NXV5WgRmj17NlasWIHp06cjJycH69atw4ABA7geq3Pnzti+fTt2794Nd3d3KCkpYciQIZgzh//CM/XJqZ0LzC5fwI5/NyH66xcoKCjg+rWrKC0pxfBRnCv0/b2I9SHm4JET7G2Dh45A4MP7WLJwLvr+2R95eXm4eP4smhoYoku37zc4nfnvJD68fwvb1nZQ19BAdlYWggIfIDwsFL379oOOTtWXjLY0NUInxzbwPHkBaZlZaKKlgev3ghCXlILF7mPZx63a6YWX70Px6Nz3WXKyc3Jx9garV/FN2SwiZ2/4Q15WBnKyMhjcg9WPbd/Kiut5s3NYU8TZNDer1TL1FmamcGnnBC/vY0hPT4eOjjb8/O8iITERc2ZOYx+3Yes2vHn7Drd8LrG39e3ZAzd8/bB05WoM7t8PYmKiOHfpCpSVlDCo/5/s45wdue85KZ8er23r1lBUrPmlbqtmBuhib4Pd/11BWkY2mmip4dr9p4hNSsHSSd/fQ5fvOYoXHyLw7NT30dvs3DycvslaX+B1GOty8RnfAMjLyEBeVhpDXFk3zLdvbQ2jJto4eOEm4pJTYd3MENEJSTjrex9qSgr4s2P1+zzrKzsATFq5DdamhtDTVEdKeiYu3glEXn4B/p03pVZ95w39Zx8AmrqPhLiiAnv2GI1ef0CqrGj8vPsYijOzYfbPbOiNGYA7zToh78s3AEDceV+kPX6JlgfXQc6iGYpS0tB08nBAVBRhq3ZyPMeHhRvR5qIn7G8cQuyZa5C3NIWB+0hEHzqL7I/VXwwKACzMzeDSzhmHvI8iPSMdOtrauOV/BwkJiZg9czr7uI1b/8WbkLfwu3aFva1Prx644euLpStWYdCA/hATFcX5S5ehrKyEgT98APe/exc+N27C2cEBWlqayMvLw/MXL/Hi5Ss4tG0Lm5Y1L4qtmhmis70Ndv93GakZWdDTUse1+08Qm5SCJT/87K/YcxQvPoTj6and7G2sn/17AIA3ZT/7Z30DICcjXfaz35HjuTKycxD06j06tW0FmV+wMOTvRFFREd7e3li9ejU8PDwgKyuLQYMGYdasWRzHlZaWsid4AYDXr18jKysLWVlZGD58OMex/fv3x/r166ucgcGsyUTfRGilp6ejS5cuGDt2LKZNm1b5CUSgQj9VvnpjdlYWDnvtx+PHgSgsKISJqSnGTZgME1POkcO/xrLe7H8s5AHg65fP8Drgiffv3kFMXAxt7Owx/q8pHFcoXr4Ihs+Vi/j0KRyZGRkQF5eAgaEhurn2RKcu3Xhe4TEz1kNqCO/FUgoKi7D/v4vwvf8YWTk5MG6qh0nD+sHhhyLEfdlGrmImLjGZZ8sAAGipq+KiJ//VGa/dfYg1uw/j0Pq/Ky1mVKzb4Ws49/0l5QoLC3Hk+En43w1AVnY2jAwM4DZqBOxaf59hZs7CJVyFPMDqcfc8cAjBL1+BySxFSysrTJk4odI5po+eOIVjp07j3ImjlRby+iYWyHxxi+/+gsIi7D3rgxsPnyErJxfN9HUxZXAvOLb8fjVx8qptXMVwbFIK/pyxnOdjaqup4MrO74upZWbnwuviDTx8+Q7xyamQkZJCWyszuA/rA12Niq8oKNh25Zu/PrL/e+w8Ap6HICktHbLSUmhrbY4pg3ujiWblV0IUbLvy/bkvzy/sP/vXxPlfdfgj3B8yfNo4ygv3Fl7ruAp5ABBTUoDFhvnQ6tsFItKSyHgegg8LNiIjmHsmOc2+nWHy9zTImRujMCkVMUcvInzNbvYIPy+9ikLxJYK7VbBcYWEhjhw7gTt377F+bw0N4DZqJNq0tmUfM3fhYq5CHmD93u7df7Ds95aJFtblv7ffr3CGhYfjzLkL+BgahrT0dIiKiqKJri46/9ER/fr2rnT6yabNzJDx4jbf/QWFRdh39irHz/7kwb05fvanrNrGVcjHJqWg34xlPB9TW00Fl3eu5th24fYDrPf6D1vmTkH71tzTG/OjaNulysf+KhW979WGgm3Xyg8SUlTIN3D79++HmpoadHV1kZSUhEOHDiEqKgrXr1+HtnbNF6cg9aMqhbywqqiQF3aVFfLCrrJCXthVVMgLu8oKeWFXWSEvzCor5IVdZYW8sBOGQv5XvX7C8LXVVJ1PP0nql4iICDw9PZGQkABRUVG0bNkS3t7eVMQTQgghhDRyVMg3cH/99Rf++usvQccghBBCCCH1jAp5QgghhBAi9JhCNmuNMKBXhBBCCCGEkAaICnlCCCGEEEIaICrkCSGEEEIIaYCoR54QQgghhAg/6pHnQq8IIYQQQgghDRAV8oQQQgghhDRA1FpDCCGEEEKEHpPBEHQEoUMj8oQQQgghhDRANCJPCCGEEEKEHi0IxY1eEUIIIYQQQhogKuQJIYQQQghpgKi1hhBCCCGECD+62ZULjcgTQgghhBDSAFEhTwghhBBCSANErTWEEEIIIUTo0aw13BhMJpMp6BCEEEIIIYRUJOVt0C95XFUrp1/yuPWBRuQJEaCs7XMEHaHG5GduQe6Ds4KOUSMy7Qcj59ElQceoMVnHfngRliLoGDVma6qKj59iBB2jRsyNm+Br+AdBx6gxfRMLfIkIFXSMGmnazAzXxM0EHaPGehWFNvj3HSJ86BoFIYQQQgghDRCNyBNCCCGEEKHHBE0/+TMakSeEEEIIIaQBokKeEEIIIYSQBohaawghhBBCiNCj6Se50StCCCGEEEJIA0Qj8oQQQgghRPgx6GbXn9GIPCGEEEIIIQ0QFfKEEEIIIYQ0QNRaQwghhBBChB6Txp+50CtCCCGEEEJIA0SFPCGEEEIIIQ0QtdYQQgghhBChx6RZa7hQIU+IsBIVhYRDd4ibtwZDSgalybEoeHQTJV/DKjxNwr4bJB1cubYzi4uQvXsh/6fTMYTM4GkAgOx9y8DMz6lx9MKiYnhe9ofPo1fIys2DSRMtePTrAgfLZhWe5x/8Dn7PQvDu8zekZGZDU1kR7VuYYVKfjpCXkeY6Pie/AAeu3sWt4LdISs+CkpwMWhjrY/X4gZCWlKhd/ot+uBb0Alk5eTDR04b7gG5wsDKtOP/zt/B7+hrvo2KQkpEFTRVFtG9pgYl9O0Neljt/uejEFAxevBWFxcU4vnw6mhs2qXH2H+VkZ+Hkkd149ug+CgvyYWzaHKPGT4dhM7NKz40Ie4+A29fwKew9vn6OQElJCU5dDeJ57K3rF/DuTTAiQt8jJTkBLp16YuqspbXOn52dDe9D+/E46CEKCgpgYmaG8X9NgXGzir8P5aK/foHXAU98eBcCMTFxtLGzx/hJU6GoqMT3nHt3b+PfTesgJSWF0xeuVTtzYVERvI+fxO2795CdnQMjg6YYO3okWtu0qvTc5OQUeB70QvDLV2CWMtGyhTWmThwPbS0tvue8ffcesxYsBgCcO3EUiooK1c78Y/ajx06UZc+GoYEBxo4ZidY2NlXKvvfAwbLspWjZwhpTJv4Fbe3v2QsKCrDLcx8+hoUhKSkZpaWl0NHWgmvXLujTqyfExGpXkojKysBozgQotW0JJTtrSKgo4fWEhYg5erFK54spysNi/Txo/tkVojJSyHgWgvfz1yPz5XuuYzV6d4LpsmmQs2iGwsQURHtfQMQ/e8AsKalx/sbyvkPqF7XWkEatb9++MDMzw/PnzwUdpdqkug6HhE0HFIe+QEHAJaCUCem+f0FUx7BK5+ffOYe8myfY/+XfOl3B0QxIdugPZmFBnWRfdvg8jt8KRE+Hlpg3rBdERBiYvuMoXoZ/rvC8NccuIyouiX2ek5UJTt99DLe1+5FfWMRxbFZuPsZvOIDLgS/QvW0LLB7VF8M7O6KwqBhFxTX/YwoAyw+ewQnfB+jhYIO5I/tCRISBGf8exsuwqArP++fIeUTFJqKnow3mjewLJ2sznPYPgtua3Vz5f7Tl5FWIitbt23FpaSk2rpqLwIBb6NZ7IEaM80BGehpWL/ZAXGx0pee/eh6Eu7euAgwGNLR0Kzz2yvnjePcmGE30DSEqKlpn+VcvX4z79/zRq08/uI2fiIz0dCxZMAex32IqPT85OQmL589CXOw3jHKbgH4DB+P5sydYvmQ+iop4fy/y8vLgfWg/pKSkapx70787cP7SFXTu2AHukyZAREQES1asxtt33MXgz889d/HfePP2HYYPHoQxI4cjIjIScxYuQWZmJs9zSktLsWvfgVrl/dHmrdtw/tJldOrYAVMn/QVREREsXb6qStnnLVqCN2/fYviQQRg9ckRZ9sUc2QsKC/Hl61e0bdMa493GYNKEcTAyNMTeA17YtHVbrfNLqCnD9O9pkDM3Qtab0OqdzGDA7sp+6AzrjS97juPjok2QUFeBw+1jkGnWlONQdVcXtDm/G0XpWXj3v9WIv3IbJounwnL737XK3xjed0j9oxF50miFh4cjNJT1Zn716lW0adNGwImqTkRTD+JmNsh/cBVFL+4BAIo+PIfsqHmQdO6N3LM7K32M4vA3VR5VF7d2AENeCUXvnkDCxqU20fE2Mga+T0Mwa3B3jHFtBwDo7dQKg5ftxLZzvvBeNJnvuZumDEMbcyOObRZNdbDs0Hlcf/waA1y+fw93XvBDXEo6Tv3tDl11Ffb2cT1qFR9vI6Ph++Q1/je0J8b06FCW3xaDl/6L7Weu48hSD77nbvQYhTYWxpz5DXSx7MAZ3Hj0Ev07tOU6JygkFI/ehsGtRwccvHqnduF/8CTwLsI+hOB/C9fA3rkTAMChXSfMnjwM504cxPR5Kys8v0uPAeg7cDQkJCVxeO8WxH37yvfYZet2Q01dCwwGA2MHd66T/EEP7+Pjh3eYv3gZnNuxvg/tXDpi6kQ3nDrujTkLllR4/rnTJ5FfkI+tOzyhrqEJADAxNcfyJfNx57YvXHv05jrnzH/HIS0tA+sWrfDkUWC1M38MDcO9+w8wafxYDB7QDwDQtdMfmOgxAwcOe2P75g18z71y7Qa+xcZi19ZNMDM1AQDYtbbFRI8ZOHvxMia4jeY659pNPyQlJ6NHty64eMWn2nl5ZZ84fhwGD+zPyt65Eya5T8PBQ0ewbctGvudevXYd32JjsfPfLd+zt2mNSe7TcO7iJYx3GwMAUJCXx46tmznO7d2zB2RlZHDZ5xom/zUBKirKNf4aCuIScbuJMwoSkqHY2grtHp+v8rnaA7tDxckWwUNnIP6CLwAg7uwNdHzvC9Nl0/FqzFz2sRYb5iMzJBRPe4xnj8AXZ+ag2cLJiNp5FDmhkdXO3ljed0j9o49ipNG6evUqREREYG9vj5s3b/IdhRNG4s1agllagqK3j75vLClG0bsnENUxAENOqfIHYQCQkKz8OElpSDj2QOHjm2AW5NU0Mtvt4LcQFRHhKLolxcXxZ/vWePMpGvGp6XzP/bmIB4BOts0BAFFxSextWbl5uBL4AgNd7KCrroKi4mIUFhXXOjsA3H4Wwsrf0f57fglx9HOxw5uIr4hPqSD/T39MAeAPWytW/thErn1FxSXYfOIqhndthyYaqrUP/4MngXehqKQCO8eO7G0KispwaNcJwU8eoKiosMLzlZRVICFZhZ8fAOoa2mDUce9q0MP7UFJWhqNTe/Y2RUUltGvfAU8eB1WaPyjwPuzsHNhFPAC0smkNHd0mePgggOv42G8xuHLxPMZPnFrjqwoPAoMgIiKCnt27sbdJSEige9cueP8xFIlJSRWc+whmJibsQhgA9PWawKZlC9x/yP2hIjMrC0eOn4DbyOGQk5WtUV7O5w9kZe/xvS1PQkICrt264v3Hj5VkD4KZKY/srVri/oOHlT63pqYGACA7p+btfABQWliEgoTkGp2rNcAV+fFJiL/ox95WmJyG2HM3oNm3M0QkxAEAchbGkLc0QfTBMxxtNF/2ngRDRATaA7jbGquisbzv/GpMhsgv+a8ha9jpCeGDyWTCx8cHDg4OGDduHNLT0/HgwQOOY8LDwzFy5EhYW1ujW7duuHLlCtzd3TF6NOfI16dPnzB16lS0bt0arVq1wqRJk/D1K//RybogoqGL0rQk4KdWl5IEVkuEiLpOpY8hO3Yx5KeuhdzUtZByHQGGjBzP4yQde4CZk4mikEc891fXx69x0NdUhZw05+V+q7L+y9Cv8dV6vOSMLACAkrwMe9vL8C8oKCqGnoYK5nqegqP7Kji4r8TYdfsR+jWuVvlDv36DvpYaV35LI72y/bHVerwUdn7uYuuk30Nk5ubhr76dapiWvy+RYTA0NoOICOfbvLFpcxQU5CPuW+XtNYIUGRkBY2MTrvwmpuYoKMjHtxj+7TUpyUnISE9HMxPu3mJTU3NEfQrn2n5w/x5Yt2yFNnb2XPuqKiIyCk10dSArI8OxvbzA/RTJu0WitLQUkZ8/w9SEuyAzNzVBbFw8cnM5P2QfOX4SKkrK6NW9ZoUjV/ZPkWiiq8uV3dzUtPLsUZ9h0oz7/hczdvZcju1FRUXIyMhEYlISHgY9wrkLl6CpoQFdHe06+VpqQrGVBasXnsnk2J7xLARisjKQNWW1NCq0Yg0spAeHcBxXEJeIvOg4KLSyqNHzN5b3HVL/qJAnjdKLFy/w7ds39O7dG+3atYOSkhJ8fL5fes7Pz8f48eORnp6OTZs2Yfbs2Thw4ADevXvH8TjR0dEYNmwYMjIysH79emzevBmpqakYO3YsCgsrHhGsDYaMPJi5WVzbmTmsflMRWf43tDEL8lD46iGrR/7aERS9ewIxk1aQGTSNa4ReRE0b4tYOKHhwhesPWE0lZ2RBXVGea7ta2bakDN79vvwcufEAoiIi6NLakr3ta0IKAGDnhVtISM3A6gkDsXBEb8QkpWLS5kNISud+7aqcPz2LnfVH5V9TUno181+/x8rfxprreQ5e8cfUAd24/njXhbS0FCipcI+2lW9LS+U/wioM0lJToKyiwrVduSx/amoK33NTU1M5juU8XwVZWVkcI/rPnz7GqxfPMX7ilFplTk1Ng4oyd2uIatnXkZKaxvO8rKxsFBUV8Ty3vNUkpexrAoDIqM+4dsMXk/8aV2f3JKSmpfFsa+H1/D9iZ+d1rnL518157sOgRxg8YhRGjZ2AVf+sg5qaKlYtX1pnX0tNSGqroyCe+3ciPy6xbD/rqoGUljoAoCCO+9iC+CRI6WjU6Pkby/sOqX/UI08aJR8fH0hKSqJbt24QFxeHq6srrly5gpycHMjKyuL8+fNISUnBqVOn0KQJa6TYysoK3bp1g76+Pvtxdu3aBUVFRRw+fBiSZW0Gtra26Ny5M86ePYuRI0f+kvwMMXEwS7hbRZjFZe1BYuJ8zy16xXnloTgiBCUJXyHdfRQkWjij8Pn3fkjJDv1Q8vljpTPhVEdBURHEecw+ISnO2lZQWPUWmBtPXuPSw2CM7d4eTTXV2NtzC74XYfvmjIOMFOt7Y66vA7d1+3Dm7mN49O9as/yFRZAQ584vwc5f9RatG49e4tL9Z3Dr2QH6Wmoc+3acvQ5ddRX0d7GrUc7KFBYWQIzHz4m4OGs2n8KCurmx+VcpLCxkZ/2RRBXyF5ZdyRIX5/H1S7DOLyhgPX5RURG89u9B9559oK9vUKvMBYUFPJ9Toqwto5DPzeQFFeQt/3oLfjh3974DaNvaFm1sK59NpqoKCworfH5+r3d5LomKvu4CzkGPVi2ssX7NKmTn5ODV69eIjPyM/Pz8WuWvLVFpKZQWcA/OlOYXlu1nvceIlBW/vI4tyS+AmALvK5+VaSzvO78aEzT95M9oRJ40OsXFxbh58yY6dOgAeXnWaEafPn2Ql5eHW7duAQDevn0LU1NTdhEPAE2aNIG5uTnHYwUGBqJTp04QFRVFcXExiouLoaCggObNm+Pt27e/7GtgFhcBotxv6ozywqy4ev3+xaEvUZqTCVG97z2sYiatIKptgPwHV2qV9WeS4uIoKuYu1gvKetglJao2fvAi7DNWHrkIJ0sTePTvwrFPqqxA6NDSnF3EA0ALYz3oqinj9aeatz5JSojz7LcvZOfn/yHqRy9Co7Dq0Dk4WpnCYyBn+8ObiC+4FvQSc0b04Wodqa7ioiKkp6Vw/FdaUgIJCUkU8/g5KR+Jrmr/+69WVFSEtNRUjv9KSkogISHBsw++sAr5JcquPPG6L6ao7EqaZNn0pFcunUNmZiaGj3Kr9dciKSHJ8zkLy4owCT73rEhWkLf86y0/5t79h3j/MRST/xpX67w/kpCUqPD5+b3e5bkKK/q6f5oKVllZGbY2reDSzhkzPNxh37YNFi5djlQ+VyzqQ0lePkR4TFkrIiVRtp/1gaU0j/WBg9exolKS7P3V1dDed4jwoBF50ugEBgYiNTUVf/zxB3vqM1NTU6irq8PHxwf9+vVDYmIiVHhctldRUUHBDyNPaWlp8Pb2hre3N9exvEav6gozNwsMHu0z5dtKc6p3mRUAmFnpYEh973+VbN8bxeFvgJISMORZl8UZkqw5hxnySoCoKLuVpzrUFOWRyOMycHmvu3oV5rkOjY7D/3Ydh7GuJjZNHQaxny65qyuxPqCp8Bj9UlGQRWZOzUf31JTkkZjGnT+pPL9S5fnDvsZi1nZvGDfRwqZpo7jybz9zAzamBtBVU0ZsEqvtID2bdaNfUnom4lLSoK1atdk7wj6GYPXiaRzbdhw8D2VlVaTzaD8p36asol6lx//VPn54h6UL53Bs23/4BJRVVJHGo50jrSy/Co+2mXLlv9tpPL7+tNRUyMvLQ1xcAjk52Tjz3wn07NUXubm57F7uvLw8MJlAQkI8JCUloaRUte+FiooyklO4n7O8tUSVz4ws8vJyEBcXR2oadyFbXtyWt+fsP3wELs5OEBMTQ3xCAoDvN4kmJSejqLgYaqrc722VZldWRkoK9+v98/Pzzc6jCE9NK/+6K87Tvp0zDh89jqAnT9C7R/fqRq8TBXFJkNTi/p2QKmupKShrsckva7+R1FZHfgzn/T6SWupIf/amRs/f0N53BKWh35j6K1AhTxqdq1evAgAWLVqERYsWcexLS0tDSkoKNDQ08OHDB65zU1NTIfvDDBCKioro0KEDRowYwXWsbB3MFMFPadI3iDcxZvW0/3BJXVRLv2x/9W58AgCGgjLHeSLyyhAxV4a4uS3XsbIjZqMk6RtyT26t9vOY6WvjeWgUsvPyOXow30ZGl+3nv7gNwFqkZNo2b6jIy2HnzDEcI+7lLJqybvbl9YEhKT0LBj9dTq4OUz0dPP8QyZ2/bJTfTL/iG42jE1MwbcshqCjIYuescTzzx6ekIy4lDb3ncU9HOGu7N+SkpXDfs+LpIcvpGzbD4tXbObYpKqugqZEJPr57jdLSUo7Rt4iwd5CUlIK2rl6VHv9XMzQ0xsp/OKc2VFZWgaGRMd6/C+HKHxb6EZKSUtBtwn/xGlU1dSgqKiEinLtlLCzsIwyNWDdmZmdnIz8vDxfOncaFc9zrLEwaNxL2Dk5YvGx1lb4WYyNDvHoTgpzcXI6bRj+GhbH38yIiIgJDg6YIC//Ete9DWBi0tTQhU7YgWlJSMu4E3MedgPtcx06dORtGhgbYt3NblfJyZjfCa17Zy6bwrSx7eEQE176PoWHQ1tKCzE830P6soKxNJbeWs9bURubrj1Bu1xpgMDjuF1Jq2wLFObnIKZvLPfM16++GUmtrZDz7fsOrpLYGpPW08fXgmRo9f0N73yHCgwp50qjk5eXB398fXbp0wZgxYzj2JScnY/bs2bh+/TqsrKxw6dIlREdHQ0+PVdDExMTg48ePaN26NfscR0dHhIeHo3nz5vV6I1ZR+BtItP4D4laO7HnkISoK8eZ2KIn7AmZ2OgDWyDlDTAKlad+nGGNIy4KZx/kHUbyFE0Rk5FH45SN7W97Vw1zPK2baCuJmNsjzPcl+jurq0toSR30f4sL95+x55AuLinE58CWsjZpAS0UJABCXko78wiIYan8fBUvOyIL7v0fAYDCwZ5YbVHjMuAAABlrqMNXTQsCrD0jLyoFy2XGP3oUjPjUDwzo51Cg7AHSxs8axm/dx4d4T9nzOhUXFuPLwOayM9KClWp4/DfkFRTD84ea25PQseGw6CAaDgd1zJkCZT7/s0nEDkF/A2Yrw7EME/rsdhFlDe8FAu+qj5XJyCrBuxd3vau/8B54E3sWzR/fY88hnZqTjycO7sG3rzNF/nhDHmgFGU7v+V3aUk5dHK5vWXNudnF0Q9PA+HgU9YM8jn5mRgcCHAbCzd+DIHxfH+oCqrf292HF0bo87/n5ISkqEujrre/T61QvEfotB336DAABKikpYtJS7cPG5chGhH99jzvwlPG+Y5ae9sxPOXriE6zf92PPIFxYVwffWHZibmUJDnfV9TUxMQn5BAfT1mnCc63XkKELDI2BmwvqgER3zDa9eh7AfCwBWLOFenfne/Ye49+Ah5s+eCXW1mn2Ibe/shHMXLuL6DV/2PPKFRUXwve1fhezO8DrijbDwcJiamJRlj8Gr128weEB/9nEZGZlQUJDnmqr0pi9rykcTk4pXfq4rklrqEFOUR+6nr2CWtQHGXbgJ7UHdodW/G3seeXFVZWgP7I5En7soLWsTyn4fgewPn6D31xB82f8fUFoKAGg6eTiYpaWIv3CzRpka2vsOER5UyJNGxd/fH7m5uRg9ejTs7bmnkTt48CB8fHzg7e2NvXv3YsqUKZg+fToA1o2tampqHH9kZsyYgUGDBmHChAkYMmQI1NTUkJycjKdPn6JNmzbo3Zt7UZm6UJrwFUVhryDp1BMi0nIozUiGuEUbMORVkH/r+4iPVLfhEGvSDFnbv7cmyI5biuLwVyhJjgNKiiGqYwgx01YoSfzGMcVkcSR3j3/5tJYlnz9WeTGpn1kb6aFrGyvsvOCH1Mxs6Gmo4mrQS8SlpGH52H7s4/72OofgsM94eXANe5vHNm/EJKVhbPf2eBn+BS/Dv7D3qSrIwcHy+x/6uUN7YurWIxi/4QAGutghOy8fx28FoammGgZ35F4Apcr5jfXR1c4au87dRGpmDvQ0VeHzMBhxyWlYNn4Q+7hl+88gODQSL458H92atsULMUmpcOvZAS/DP3OsZKuqIMdeat2Rx5LrWWXTC7Y2N6qTpdLtnf6AiZkl9m5fi5ivnyGvoIhb1y+gtLQEg0b8xXHsmqUzAAA7vS6wtyUlxuHBXVZREhnB+gB44TTrw5+6uhbad/q+8lbw04f4EsWa0rGkuBhfP0ewj23dtj2aGla/QHNq5wKzyxbY8e8mRH/9AgUFRdy4dgWlJaUYPmosx7HLFrEW6zlw5CR726ChIxD4MABLF85Bnz8HID8vDxfPn0FTA0N06cbqHZaUkoKDUzuu537yOBDhYR957quIhZkpXNo5wcv7GNLT06Gjow0//7tISEzEnJnf2582bN2GN2/f4ZbPJfa2vj174IavH5auXI3B/ftBTEwU5y5dgbKSEgb1/5N9nLMj94fU8qkh27ZuDcUqtK7xzG5uBpd2zjjkfRTpGenQ0dbGLf87SEhIxOyZ09nHbdz6L96EvIXfte/31vTp1QM3fH2xdMUqDBrQH2Kiojh/6TKUlZUw8IcPIf5378Lnxk04OzhAS0sTeXl5eP7iJV68fAWHtm1h07JljbL/qKn7SIgrKrBnj9Ho9QekdFlXAT/vPobizGyY/TMbemMG4E6zTsj78g0AEHfeF2mPX6LlwXWQs2iGopQ0NJ08HBAVRdgqzgX4PizciDYXPWF/4xBiz1yDvKUpDNxHIvrQWWR/rP5iUEDjed/51Zh1vF5FY0CFPGlUfHx8oKOjw7OIB4B+/fph7dq1SExMxKFDh7B8+XLMnTsXmpqacHd3x6VLl9g3yAJA06ZNcfbsWWzbtg0rV65Ebm4u1NXVYWdnBzMzs1/6teT7nYKkYxrELFqDISmN0uQ45F3xQklsxX8oikJfQFTbAGLGLQAxMTCz0lAYfA+FT29X+ybZmlo9YSD2XFLCtcevkJmTD5Mmmtg+fTRam/K+PF8uLJrVc3rk5gOufa1NDTgKeTtzI+z63xjsueSPXRdvQUpCHB1tLPC/Qa48LytXx6qJQ7Hngh+uB71AZk4eTPS0sO1/Y9HajHvBKs78rDnsva9zLzjU2syI/Qe1PoiIimL+ii04eWg3bl49i6LCAhiZWGDK/5ZCp0nTSs9PSojD2eMHOLaV/9vCyoajkH8aeA/371xn//tzZBg+R7LaSVRVNWpUyIuKimLZynU47LUPPlcuorCgECamZpgxaz6aNKm8LUhdXQNrN/wLrwOeOHr4IMTExdDGzh7j/5rCczacurJg9v9w5PhJ3L4bgKzsbBgZGGD1sqVoYWVZ4XkyMtLYvG4NPA8cwonTZ8FklqKllRWmTJwAJUXFX5b3R/PnzMKRYyfgf+ceK7uhAVYv/xstrKwqyS6DTevXYu/+gzj53xkwmUy0sObObmXZHO8/fMTdgPtIS0+HqKgomujqYvJfE9Cvb90MihjNGg8Zg+8FqfYAV/YiTd9OXkFxZjbvE0tL8bTPJFhsmA/DaaMhIi2JjOcheP3XInZbTbnE6/cQPHgaTP6eBsttf6MwKRUR6/chfM3uWmVvDO87pP4xmMw6mjyakAYuPT0dXbp0wdixYzFt2rTKT6gDP46kNzTyM7cg98FZQceoEZn2g5Hz6JKgY9SYrGM/vAjjP4+6sLM1VcXHT/wXdBJm5sZN8DWc+/6ahkLfxAJfIkIFHaNGmjYzwzXxXzuA8iv1Kgpt8O87gvYtLKTyg2pA19S68oOEFI3Ik9/W/v37oaamBl1dXSQlJeHQoUMoKSnBwIEDBR2NEEIIIaRSVMiT35aIiAg8PT2RkJAAUVFRtGzZEt7e3tDWFtwy4YQQQgjhjRaE4kaFPPlt/fXXX/jrr78qP5AQQgghRAjRzPqEEEIIIYQ0QDQiTwghhBBChB6t7MqNXhFCCCGEEEIaIBqRJ4QQQgghQo9uduVGI/KEEEIIIYQ0QFTIE0IIIYQQ0gBRaw0hhBBCCBF6dLMrN3pFCCGEEEIIaYCokCeEEEIIIaQBotYaQgghhBAi9GjWGm40Ik8IIYQQQkgDRIU8IYQQQgghDRAV8oQQQgghhDRAVMgTQgghhBChx2SI/JL/auPTp08YN24cWrVqBWdnZ2zcuBGFhYWVfy1MJvbv34+OHTuiRYsWGDp0KF69elXt56dCnhBCCCGEkGrKyMiAm5sbioqKsHPnTsyaNQtnzpzB+vXrKz33wIED2LFjB8aOHYt9+/ZBXV0d48ePR3R0dLUyMJhMJrOmXwAhhBBCCCH1IepTxC95XEPjZjU6b9++fdi7dy/u3r0LJSUlAMDp06excuVK3L17F5qamjzPKygogJOTE0aOHInZs2cDAAoLC9G9e3e4uLhgxYoVVc5A008SIkDZT64KOkKNydn3Qa73KkHHqBEZt2WIDX0j6Bg1pmPWAnEfXwk6Ro1pm7dCytsgQceoEVUrJ+TdPSHoGDUm/cdIZLy4LegYNaJo2wU5jy4JOkaNyTr2wzVxM0HHqLFeRaGCjiB000/ev38fjo6O7CIeAHr06IHly5cjMDAQAwYM4HneixcvkJ2djR49erC3SUhIoGvXrrh161a1MlBrDSGEEEIIIdUUGRkJIyMjjm0KCgpQV1dHZGRkhecB4DrX2NgYsbGxyM/Pr3IGGpEnhBBCCCFCj8n4NSPynTt3rnC/v78/z+2ZmZlQUFDg2q6oqIiMjAy+j5eZmQkJCQlISkpybFdQUACTyURGRgakpKSqkJxG5AkhhBBCCGmQaESeEEIIIYT8tviNuFdGQUEBWVlZXNszMjKgqKhY4XmFhYUoKCjgGJXPzMwEg8Go8Nyf0Yg8IYQQQggRekwm45f8V1NGRkZcvfBZWVlISkri6n//+TwAiIqK4tgeGRkJHR2dKrfVAFTIE0IIIYQQUm0uLi4ICgpCZmYme9vNmzchIiICZ2dnvufZ2tpCTk4ON27cYG8rKiqCn58fXFxcqpWBWmsIIYQQQgippmHDhuHYsWPw8PDA5MmTkZCQgI0bN2LYsGEcc8i7ubkhNjaWPbWkpKQkJk+ejJ07d0JFRQWmpqY4deoU0tPTMWHChGploEKeEEIIIYQIPaaQNZIoKirC29sbq1evhoeHB2RlZTFo0CDMmjWL47jS0lKUlJRwbJs4cSKYTCYOHTqE1NRUWFhYwMvLC3p6etXKQIU8IYQQQgghNWBsbIwjR45UeMyxY8e4tjEYDEyePBmTJ0+u1fML10cbQgghhBBCSJVQIU8IIYQQQkgDRK01hBBCCCFE6DHxa1Z2bchoRJ4QQgghhJAGiAp5QgghhBBCGiBqrSFESBUWFWPvhZu4FvgCWTm5aKanDfdBPeBgZVrheXeehcDvySu8j4pGckYWtFSU0K6VBSb+2RXystLs49KzcnDl/lPcf/UeUbGJKC4pgYG2Bka6uqCbQ6vaZS8ugef9N/B5G4Ws/EKYaCjBo0NLOBhqV+txppz0x5PP8Rja2hQLXe3Y26+8+YTlPo/5nvdPXyf0tDKsef6iIhw+cRq37t1HVnY2jAyaYsLIYWhj07LSc5NSUrD7oDeev3oNZikTrawt4fHXWOhofZ9T+Kb/XWzYvofvYyyePQNdO7avXf6TZ+B39wGycrJh3LQpJowaijatWlQhfyp2e3nj2as3YJYyYWNtCY8JYzjy3/C/hw07PPk+xpJZ02qcv7CoCAf+uwjfgEfIzMlBs6Z6mDR8ANq2tKzwvC/f4nDJ7x7ehX9CWOQXFBYV47znJmhrqHEdu/3wKbx89xFxSSkoLCyClroqOju3xYi+3SEjXfUVFXnnL8aeq/dw7ckbZObmw0RXAx59/4Bjc+MKz/N/+QG+z9/h3ZdYpGRkQ1NFES7WJpjY0wUKMpyZcvMLsevKXdx+8R5p2blooqaM4X+0xZAObWqZvQj7zl7DjQdPWe85+jqYMqQP7FtYVHjel9gEnL/9AO8iPiP0czQKi4pxaccq6KirchwX/D4MU1dv5/s4U4b0wfj+3WuRvxieF/1wLegFsnLyYKKnDfcB3Sp9z/R//hZ+T1/jfVQMUjKyoKmiiPYtLTCxb2eO98yfRSemYPDirSgsLsbx5dPR3LBJjbOLysrAaM4EKLVtCSU7a0ioKOH1hIWIOXqxSueLKcrDYv08aP7ZFaIyUsh4FoL389cj8+V7rmM1eneC6bJpkLNohsLEFER7X0DEP3vA/Gl6RGFErTXcqJAntXLlyhWcPHkSoaGhAABTU1MMHz4c/fr1q/Zj7dy5E87OzrC1ta3jlA3TigP/4fazNxjRrT30tdRx9cEzzNhyEPsWToWNGf8idc3hs1BXVkQPJ1toqSojIiYOZ24HIvD1R5xYPQtSEuIAgDcRX7D73E04tzTHhL5dICYqAv9nb7Boz3FExiZgygDXGmdf5vMI/h+/YoSdOfRV5HHlTSSmn76L/SO7wEZPo0qP4f/xK958S+a5z1ZPA2v6OnFtP/H0I8IS0tDWQKvG2QFgw7bdCAh6jEF9e0JXWxu+d+5h4ap1+Pef5bBuzr+oycvLw+wlK5GTk4uRgwZATEwU5y774H+Ll+PAtk1QVJAHALSwbI7Fs6ZznX/2ig8+RX1B65ZWtcq/fvseBAQ9waA+PdFERws3/QOwYNV6/LtmGVo0N+d7Xm5ePmYtXYWcnFyMGtQPYqJiOHvlGmYuXomD2zaw87e0tMDiWdO4zj935Roior7AtqV1jbOv2emFu4+fY2ivrmiirYnr9x5izj//YtfK+Whpwb8gexv6CWev34JBEx00baKD8KivfI/9EBGFlham6NVJExLi4giL+oLjF6/h+Zv32LN6IUREan6xepn3Zdx+8QEjOttDX0MFVx69xvRdp3Bg9hjYNNPne97q4z5QV5JHr7bW0FJRRPi3RPx37xkevo3AqcUT2b+3JaWlmLrjON5/jcPQDm2gr6GKoPefsPbUdWTm5uGvHjX/ALjK8xj8n77E8B5/QE9LAz4Bj/G/jXvguXQmWpk343teSHgkzty8B8Mm2jDQ0ULYlxiexxnoaGGluxvX9usPn+LJmw9wqOQDQ2WWHzwD/+chGN61HfS11HD14XPM+Pcw9i2YBBtT/u+Z/xw5DzUlBfR0tIGWqhIiYuJx2j8ID998xMmVM9mv/c+2nLwKUVERoLhWsQEAEmrKMP17GnK/fEPWm1CodrSv+skMBuyu7IdCCzNEbvFCYUoamk4eAYfbx/DQfgByI76wD1V3dUGb87uREvAU7/63GvJWpjBZPBWSGqp4O21F7b8QUu+okCc1tnr1apw4cQIDBw6Eu7s7GAwGfH19sXDhQoSEhODvv/+u1uPt2rULMjIyVMgDePvpK3wfv8LMYb0xpmdHAEAv59YYsngzdpz2weFl3EVguY3Tx6CNBecfXQuDJli+/z/cCHqB/mV/IIybaOLSpgXQVlNhHze4sxOmbtgH72t34darI6QlJaufPTYZvu+/YFYnG4xxaA4A6G1thMEHfLDtzkt4u1X+AaGguARb/V9grGNzeN5/w7W/ibI8mijLc2zLLyrGuptPYWegCTU5/qNolfkQFo47DwIxZdxoDO3fFwDg2qkDxk2bjX1HjmPXxn/4nnvpuh9iYuPguWUdzE1Y3wP71jYYN202zly6ioljRgAAdLQ0OUa4AaCgoADb9h6EbQsrqCgr1yJ/BO48CMKUsaMwrH8fAEC3P1wwbvpc7DtyArs3ruZ77uUbvoiJjcPezf+w87dt3Qrjps/Fmcs+mDh6eAX5C7FtrxdsW1hBVVmpRtnfh0fiduATTBszBCP+7AEA6NHRGaNmLcXuY2ewf+1Svue2t2uFjo67ISstjZOXb1RYyO/9ZzHXNl0tDezyPo33EVGwMq149JyfkKhvuPn8HWYN6AK3bqwPmn0cWmLQKk/8e+E2js4fz/fcTZMGw87MgGNb86ba+PvIZVx/GoIB7Vjvi/4vP+J1ZAxWjO6Dfs42AIAhHdpg7r6zOHD9AQY420JFQbba2d9FfIbfo2DMGNkfo3p3AQD0bG+P4fPXYOfJS/BaNZfvue1bt4C/lw1kpaVw3Oc230JeVUkBPdq35dp+8MJ16GlpoLlx02rnLvc2Mhq+T17jf0N7YkyPDgCA3k62GLz0X2w/cx1HlnrwPXejxyi0seD8nlsY6GLZgTO48egl+nfgzhwUEopHb8Pg1qMDDl69U+Pc5QriEnG7iTMKEpKh2NoK7R6fr/K52gO7Q8XJFsFDZyD+gi8AIO7sDXR87wvTZdPxasz3753FhvnIDAnF0x7j2SPwxZk5aLZwMqJ2HkVOaGStv5ZfiUbkuVGPPKkRf39/HD9+HB4eHvjnn3/g4uKC9u3bY82aNXB3d8fx48dx507t39x+V/7P3kBURAQD/nBgb5OUEMefHdriTcQXxKek8z335yIeAP5ozRrhjYpNYG/TVVflKOIB1gIVHW2tUFhUjJjE1Bplv/3xK0QZDAywMfmeXUwUf7Y0xptvyYjPzKn0MY48eo9SJhNj7Ks+Qnc//BtyCovRw7LmLTUAEBD4GCIiIujt2oW9TUJCAj27dsa7j2FITOJ9lQAA7gc9grmJMbsIBgD9JrqwbWmNew+DKnzeoGfByM3LQ+cONR9RBYCAIFb+Pq6d2dskJSTQq+sfeBdacf6AoCdc+Zs20UXrFla4+/BRlfJ36dCuxtnvPnoOURER/Nm14w/ZxdGnc3u8Df2EhOQUvucqyMtBVrrmH+C01VktONk5uTV+jNsv3kNUhIGB7Vuzt0mKi6Gfsw3eRMYgPjWD77k/F/EA0KkV6+pJVPz379nLCNYHFFc7zqs2rm0sUVBUjLuvQ2uU3f/JS4iKiKBfJ+fv2SXE0bejE0LCo5CQksb3XEU5WcjWsCXpXcRnRMcnobtz7dqCbj8LYb1n/jCSLSkhjn4udngT8bWS90zuD25/2Ja/ZyZy7SsqLsHmE1cxvGs7NNFQ5dpfE6WFRShI4P+7WRGtAa7Ij09C/EU/9rbC5DTEnrsBzb6dIVJ2RUHOwhjyliaIPniGo43my96TYIiIQLsWV2GJ4FAhT2rE29sbioqKGD+ee4RpwoQJ7GWLAWD06NFcK5d9+PABZmZmePLkCQDAzMwMALBx40aYmZlx7CstLcXhw4fRo0cPWFlZwdnZGTNmzEBWVhb78Z49e4Zhw4ahRYsWsLe3x6JFi5Cens7eHxMTAzMzM1y6dAnLli1DmzZt4OjoiMOHDwMArl27BldXV9ja2mLatGnIzMzkyJuZmYkVK1agXbt2sLKywoABA/Dw4cNavor8hX75Bn0tNcj99MfRyoh1aT7s67dqPV5KBuu1UpKvfKSuOsfy8jE+Dfoq8pCT5LwcbaXNKpRCE/gXBAAQl5GDI4/eYeYfNpASr/pFw+vvPkNKTBSdzaq3vPXPIiKjoKerDVkZGY7t5qas4jYi6jPP80pLS/Hp81eYNuMuCixMmiE2PgG5uXl8n/f2vQeQlJCAi2M1LqnzEB75GXo6PPKblOf/wus0dn6zZkZc+8xNq5A/4CErvwP36GVVhUV9gZ6OFmRlOAvy5mWZwqOia/zYPysuKUF6ZhaSUtPw5NVb7D91ATLSUmjerOYfBD9Gx6OphirkpDmvZFkZ6AAAQmPiq/V4yRnZAAAlue/fy8LiYoiKMCAuKspxbHn7x4evcdXODQBhn2Ogr60BOa7Xvil7/69wM/AZAKB7O7tKjqxY6Ffe75mWRnpl+2Or9XgVvQ+e9HvIamPq26mGaeuWYisLVi88k8mxPeNZCMRkZSBb1lak0Ip1hTQ9OITjuIK4RORFx0GhVe1am4hgUGsNqbbi4mK8fPkSHTt2hKws95ucrKws7O3tERAQgOLiqjUPnj59GkOHDsXo0aPRu3dvAECzZqzCY/Xq1Th9+jTc3Nzg7OyMnJwc3Lt3D7m5uZCXl8fbt28xbtw42NvbY/v27UhOTsaWLVsQERGB//77D6I//MHbtm0bunXrhu3bt+P27dtYv349UlNT8fTpU8ybNw/Z2dlYs2YNNm3ahNWrWS0IhYWFGDduHFJSUvC///0PmpqauHLlCiZPnowLFy6wP4TUpeT0TKgpKXBtV1NitZMkpWVy7avIkWt3ISoigi52Fd/smJGdi0sBT2BjZgh1Hs9fFcnZeVDn0dpS3u6SlMW/GASArf4vYKaljO6WBlV+zoy8AgRFxuIP0yaQleTdz1pVKWnpPFtbyttFklN5fxDJys5GUVERVHmcq6KiXHZuKvRldLn2Z2Zl4dmLV3B2sIOMTM1HlQEgJS0Nqiq88n/PwEtmBfl//Nr1eeTLzMrG0xev0M6+dvmT0zKgqqzI4/kVy/ZX/CGwOj5++oxJi9aw/62vo4WNC2dCQV6uxo+ZnJkNNUXu89XK7i1ISs+u1uMd8QuCqAgDXWy+F1gGmqooKWUiJCqGo+e+fKQ+Mb167w3lktMzoMrzPYf12ielpdfocStSUlqKW4+CYWncFHpaVbt3hp/k9CyoKcpzbVdXLH/tq/meef0e6z2zDef9HsnpWTh4xR//G9aL60ODoEhqqyP14XOu7flxiWX7NZD1NgxSWuoAgIK4JK5jC+KTIKVTu+9BfaDWGm5UyJNqS0tLQ2FhIbS1+c9Aoq2tjYKCAo5R8Yq0atWKfV75/wNAVFQUTp06hVmzZnGM6ru6fr8EuHfvXqirq2Pv3r0QFxdnP86ECRMQEBCATp2+j5q0atUKixez+mMdHBzg5+fHbgNSLitgQkNDce7cOXYhf/XqVXz8+BGXL19mf7ho3749vnz5gj179mD7dv6zMNRUflExJMS4fz0lyr6+gsKiKj/WjaAXuBzwFG69OkK/7I2cl9LSUizdewJZuXmYP7p/9UOXKSgugbiYKNd2STER9n5+nn2Oh//Hrzg2tnozV9z++BVFJaW1bqsBWB/cyl/nH0lISLD2FxTyPK+gbLs4r3PLthUW8j43IPAxioqL0aWWbTWs5yiCOI8rGRIS5T87vDMUsvPzOleiwnMDgsrz17ytpvzx6+rnvjKGTXSwfdlc5BUUICQ0As/fvEdefn6tHrOgsBjiPPJLlr2m+UVVz3/9aQguBr7E2G5OaKr5vX2jh5019l27j+VHr2DRsB7Q11DFow+fcCaAVcgVFNXszsuCwiJI8PjeS/6C177cs7ehSM3Iwrh+tW/p4Je/fFu13jMfvcSl+8/g1rMD9LU4Zz3acfY6dNVV0N+ldlcQ6pKotBRKebwvleYXlu1nXSESKfvgwevYkvwCiCnU/EMsERxqrSFC7fHjx2AymRg0aBDfY54/f47OnTtzFFDt2rWDgoICgoODOY51dv7e/ykqKgo9PT2Ym5uzi3gAMDAwQGZmJnJyWL3cgYGBMDU1hYGBAYqLi9n/OTk5ISSE8xJlXZESF0Mhj6sZhWWFgCSfWRR+9jI0Equ9zsDR2gzug3pUeOzGY5cQ9CYUf08YAlN9neqHLiMpJooiHsV6QXEpez8vxaWl2HjrOXpZG8JSp3p9p9fffoaitAScjWueu5yEhAT7df5ReREuISnB8zzJsu1FvM4t21ZeEP/sdsADKMjLwb61TY0y/0hCQhxFPIq5wsLynx3eGSTY+XmdW1jhubcDHpblb1WTyGySEhJ18nNfFbIy0rBraQmXtrbwGD0Ew/u6YsGGHQj/zP8m2cpISoihiEf+8uJaiseHPF5ehH/BymNX4dTcGNP+5GzfUFOUw3b3YSgqLsHUHSfQa+kObDt/GwuGsT78SvP5+aw8uzgKeXzvC37Ba1/u5sNnrFFvh9aVH1wJfvnLt1U1/4vQKKw6dA6OVqbwGMj5AeNNxBdcC3qJOSP61Gpmo7pWkpcPER7fdxEpibL9BQCA0jzWB1Vex4pKSbL3k4aFRuRJtSkrK0NCQgJxcfx7MePi4iApKQklJaVaPVd6ejrExMSgqsq/sMvMzOS5X1VVFRkZnDeXyctzXnoVFxeHzE+9xOUfCAoKCiArK4u0tDS8f/8elpbc81iLivIuSmtLTUkBiWncN8Ylp7P6NtWVK297Cfsai1n/HoZxEy1snD4GYhVk3X/RD2f9gzB9SE/0cq7dH1U1OWkkZnHfMJiczWqpUZfn3XrhExKFzylZWNLDHrE/tSDkFBYhNj0byrJSkP5p1C0uIwcvoxMxwKYZxEVr/8dVVVmJZ/tJSllrgRqPthUAkJeTg7i4OFJ4tH+klrXjqKmocO1LSEpCyPuP6O3aBWI8RnOrS1VZGckpvPLzzwAAChXkr+hrT0hKxpv3H9G7W+da51dTVkRSajqP588o21/z2Xwq08G+DYADuP3wCUwM+E8TWRE1BTkkpWdxbU/OLPu9Vap8xDM0Jh4zPU/DWEcDmycNhhiPn+nWJk3hs2Y6wr8lIq+gEGZNtJBU1tPdVIP397fS7EqKPNtnktNZr716DWci4ie/sBABz1/DzsqMZ0tPdakpySORR8th+etSlVbBsK+xmLXdG8ZNtLBp2iiu98ztZ27AxtQAumrKiE1i/Y6lZ7MGfJLSMxGXkgZt1V/3M8pPQVwSJHlcbZXS1ijbz2qxyY9ntdRIaqsj/6f7NSS11JH+jHuGMGHDZFJrzc+okCfVJiYmBhsbGzx9+hS5ublchXBubi6ePn0KGxsbiImJQUJCgmuU8ucCmx8lJSUUFxcjJSWFbzGvqKiIlBTu2SxSUlKgqMjdb1tdioqKMDMzwz//8J92sK6Z6uvg+YdPyM7L5+jDfPvpa9l+7j7rH0UnJGPapgNQUZDDjjl/QUaK/zSSZ24HYt9FP4xwbY+xvWt/85aZpjKef0lAdkERxw2vb2OT2ft5ic/IQXFpKcYd9ePa5xMSBZ+QKGwd6II/frqZ9eb7z2AC6FkHbTUA0MzIAC9D3iEnN5fjhtEPoeGs/YYGPM8TERGBUVN9hEV84tr3ISwcOlqaPPvH79wPBJPJrJO2mvJ8PPOHRZTt5z3FHyu/HkIjuKef+xAWwTe/f1n+rrVsqwEAEwN9vHj7ETm5eRw3vL4LZ2UyMazdjcwVKSoqQmkpE9kV3NBbGTM9LTwP+4zsvAKOG15Dolg3p5s1qXh9g+ikVHjsOAkVeVnsmjYcMlL8R9dFRURgrvf98R4/Zr1G9hbcNytXhamBLoLfhyE7N4/jhtd3EZ/L9td8sSNeHgSHICcvv9Y3uZYz1dPB8w+RfN8zzSq5yhidmIJpWw5BRUEWO2eN4/meGZ+SjriUNPSet4Fr36zt3pCTlsJ9z5W1/EqqL/P1Ryi3aw0wGBw3vCq1bYHinFzkhEWVHfeBtb21NTKefb+aLKmtAWk9bXw9eKZ+g5M6ITzXhkiD4ubmhvT0dBw6dIhr36FDh5Ceng43N9bCH1paWoiKigLzhzeYwMBArvPExcVRUFDAsc3BwQEMBgPnz/OfU7d169bw9/fnuLE2MDAQmZmZaN269pdsnZycEB0dDQ0NDVhbW3P99yt0btsCJaWluHD3++qlhUXFuPLgGayM9aGlqgQAiEtO45oeLTk9Ex6bDkBEhIFd8yZCuYK+R7/Hr7Dp2CX0cLLF7BF96yR7F3N9lDCZuPAy/Hv24hJcfhMJax1VaJXNcR2XkYOo5O8f6FybN8XWgS5c/wFAO2MdbB3oAitd7lU6b7z7DC0FGdjo8e//rw4XJ0eUlpbCx/f29/xFRbjpfxcWpibQKJumMCEpCV9jOGcP6uDsgI/hnxAa/r2Y/xrzDS/evEUHZwfwcjvgITTV1WBdwUJN1dHByR6lpaW46uvPkf+G/z1YmDb7IX8yvvyc34mV/yNH/lhWfife+f3v113+PxzboKS0FJdv3ePIfu3OA1iaGEFTjfVhPj4pBZ9jajY7S1ZOLs+b8K/43wcAWBgb1OhxAaCrrQVKSpk4/+B7S19hUTEuB72GtaEutFRYAwtxqRkcU0oCrBlqpm4/AQaDgT3TR0KlGrNGpWbl4IhfEEx1NeFgXrNCvpO9DUpKS3Hpzvf35sKiIvgEPIZVMwNolo00xyen4vO36s2+w4tv4DNISUqgo13lqyVXRRc7a9Z75r0n7G2FRcW48vA5rIz0vr9npvB6z8yCx6aDYDAY2D1nAt/3zKXjBmDL9DEc/w3rwlovYNbQXvhn8rA6+VoqIqmlDlkzIzB+uPoVd+EmpLTUodW/G3ubuKoytAd2R6LPXZSWtdVlv49A9odP0PtrCPBDa1DTycPBLC1F/IWbvzw/qXs0Ik9qpHPnzhg1ahR27dqF+Ph4dO/O6s/08/PDmTNnMGrUKPZNpq6uruybR7t06YIXL17A19eX6zGNjIzg7++PNm3aQFpaGoaGhjA0NMSwYcOwfft2ZGRkwNHREfn5+bh37x6mT58OTU1NTJkyBcOGDcPkyZMxevRo9qw1LVq0QIcOHWr9tfbr1w///fcfxowZg/Hjx8PAwABZWVl4//49ioqKMGfOnFo/x8+sjZuiS9sW2HX2OtIys6GnqQafh88Rm5yKZRMGs49bvv8Ugj9GIvjoZva26ZsP4ltiCtx6dcSrsCi8KhuNAQAVRXn2cuVvP33Fsv2noCgng7bNm+FG0AuODC1MDGo0R7K1rhq6mutj571XSM3Nh56yPK6GRCIuIxvLe32f2/zvq0EI/pqIl4tHAgAM1RRhqMb7CoqukhzXSDwARCSmIzwxHeMcm4PBqJtLrs3NTNDB2REHjp5EWnoGdLW14HsnAPGJSZg3fSr7uHX/7sLrt+9x98pZ9rY/e7jCx/c2Fq1ahyH9+7BWRr18FSpKihjSrw/Xc0V9+YrIz18wYmC/Os3f0dkBB46dQnoGZ/7507/fML522268fvse9y6fZm/r16MbfPz8sWj1Bgzt1xuiYqI4e/kaVJQUMbRfb67nivzyFZ8+f8WIgX/WSX5LU2N0crSD54nzSMvIgq6WBm7cC0RcUgoWuX+f6nb1zgN4+S4UQecPs7dl5+Ti7A3Wh6+Qj6yrD+du3IacrAzkZWQwqCdrXYAXbz9i26ET6OjQBnramigqLsbrD+EIeBIMc2MDuLpwrxhcVdaGTdDVtjl2XrqD1Kwc6Gmo4Oqj14hLSceKMd+//0sPX0Jw+Be82ruMvc195wnEJKdhbDcnvPr0Fa8+fe/VV5GXhWPz79OaTthyBC2MmkBPXQUpmdk4/+AFcgsKscNjGEREavZ9sGpmiM72Ntj932WkZmRBT0sd1+4/QWxSCpZMGsk+bsWeo3jxIRxPT+1mb8vOzcPpm/cAAG/CWFcGzvoGQE5GGvKy0hji2pHjuTKycxD06j06tW0FGam6mfnF2lgfXe2ssevcTaRm5kBPUxU+D4MRl5yGZeO/32O1bP8ZBIdG4sWR76Pq07Z4ISYpFW49O+Bl+Ge8DP/M3qeqIMd+z3S04l5ZOKvsCk5rcyM0N6zdVYum7iMhrqjAnj1Go9cfkNJlXXX5vPsYijOzYfbPbOiNGYA7zToh7wvrg3jceV+kPX6JlgfXQc6iGYpS0tB08nBAVBRhq3ZyPMeHhRvR5qIn7G8cQuyZa5C3NIWB+0hEHzqL7I/CvRgU4Y0KeVJjf//9N1q2bImTJ09i+nTWSqOmpqZYv349+vXrxz7OxcUF8+bNw/Hjx3Hx4kW4uLhg5cqVGDt2LMfjLVu2DGvXrsXEiRORn5+Po0ePwt7eHsuWLUOTJk1w9uxZeHt7Q0lJCXZ2duypL62srHDo0CFs3boV06dPh4yMDDp16oQFCxbUSQ+7hIQEjh49ip07d2Lv3r1ISkqCkpISmjdvjhEjRtT68flZNWk4PM/fxLXAYGTl5sFETxvbZk2ArXnFq06Glc2X7H3tHte+1uZG7D9KkbEJKCouQVpWDlbyuKS6fOLQGi92srqvE/YEvMa1kChk5hfCREMZ24d0RGt9zcpProbr71gfUnpUY6rKqlg8axoOnfgPt+7dR1Z2DowN9LH274VoadW8wvNkZKSxbe1K7D54BMfPnEcpk4lWVpbwmOAGJR5tXrfvPQAAdK6DtpQfLfqfBzRPnIHfvQfs/OuWzkdLyyrk/2c5dnt549jZCygtZaKVdfOy/Nw9xrcDWGspdHGpu/x/z5gIrVMXcDMgCFk5OTBuqodNi2bCxrLiaV6zcnJx4NRFjm2nrrAGDLTUVdmFvHHTJrC1MseDZy+RkpYBJpjQ1dTAuMF9MfLPHjxn7amONeP6YfeVu7j2JASZuXkw0dXEDo9haG1S8aqlYTGsxdqO+HEvHNbapClHIW+hr41bwR+QmJ4JWWlJOJgbwaPvH2iiXrv+7BXubth39ipuPHyKrJxcNNPXxdZ5U2FrYVLheZk5udh31odj24lrrCtC2moqXIW8/+MXKC4pgatz3c78smriUOy54IfrQS+QmZMHEz0tbPvfWLQ2q/gqRVg06+qO9/UArn2tzb6/Z/5qRrPGQ+aHFibtAa7sRZq+nbyC4kw+05eWluJpn0mw2DAfhtNGQ0RaEhnPQ/D6r0XstppyidfvIXjwNJj8PQ2W2/5GYVIqItbvQ/ia3bwfW8jQ9JPcGEzmTysIEELqTfaTq4KOUGNy9n2Q671K0DFqRMZtGWJDhf/GLn50zFog7uMrQceoMW3zVkh5W/FKt8JK1coJeXdPCDpGjUn/MRIZL25XfqAQUrTtgpxHlwQdo8ZkHfvhmnjdrztSX3oV1WzV4Lr0LqJmLXWVsWzGfzptYUc98oQQQgghhDRA1FpDCCGEEEKEHrXWcKMReUIIIYQQQhogGpEnhBBCCCFCj0bkudGIPCGEEEIIIQ0QFfKEEEIIIYQ0QNRaQwghhBBChB6TSa01P6MReUIIIYQQQhogKuQJIYQQQghpgKi1hhBCCCGECL1SmrWGC43IE0IIIYQQ0gBRIU8IIYQQQkgDRIU8IYQQQgghDRD1yBNCCCGEEKFHK7tyo0KeEEIIIYQIPZpHnhu11hBCCCGEENIAUSFPCCGEEEJIA0SFPCGEEEIIIQ0Qg8lkMgUdghBCCCGEEFI9NCJPCCGEEEJIA0SFPCGEEEIIIQ0QFfKEEEIIIYQ0QFTIE0IIIYQQ0gBRIU8IIYQQQkgDRIU8IYQQQgghDRAV8oQQQgghhDRAVMgTQgghhBDSAFEhTwghhBBCSANEhTwhhBBCCCENEBXyhBBCCCGENEBUyBNCCCGEENIAUSFPCCGEEEJIA0SFPCGEEEIIIQ0QFfKEEKESFxeHFy9eIDc3V9BRflvBwcE4e/YsIiMjBR2FEEJIBaiQJ6QRi4mJQVBQENLT0wUdpVKnT59G+/bt0alTJ4wcORJRUVEAAA8PD3h7ews4XeM1Z84cLFq0iP3vU6dOYeTIkfj777/Rr18/PHr0SIDpCPl1ioqKcOrUKSxevBjjx4/H58+fAQDXr1/Hp0+fBBuuCsLDwzFr1ix06dIFVlZWePfuHQDg33//RUBAgIDTkfoiJugAhJC6sX79epSUlGDJkiUAgFu3bmHWrFkoLi6GoqIivLy8YGVlJeCUvB05cgSbN2/GuHHj4OjoiPHjx7P3tW3bFjdv3oSbm5sAE1YuPDwce/bsQUhICOLj43H69GlYWlri33//ha2tLTp06CDoiDwFBwdj/vz57H/v378fgwcPxsKFC7FixQrs2rULjo6OAkxYucjISPj5+SE+Ph4FBQUc+xgMBtauXSugZLytWbOmWscvXbr0FyWpGw8fPoSvry/f118YP4hHR0dj7NixSEtLQ/PmzREcHIycnBwAwLNnz/DgwQOsW7dOwCn5CwwMxOTJk2FpaYk+ffrA09OTvU9MTAynTp0S2vccUreokCekkbh16xZmzJjB/vfWrVvRoUMHzJw5Exs3bsS2bdtw8OBBASbk7/jx43B3d4e7uztKSko49hkaGrJH54VVQ/6jmpqaCg0NDQCsDyNxcXEYM2YMZGVl0b9/f8ycOVPACSt26dIlLF68GJKSktDR0YG4uDjHfgaDIaBk/N25c6fKxzIYDKEu5A8ePIjNmzdDV1cXxsbGkJeXF3SkKlmzZg1UVFRw9uxZKCgocAxy2NnZYevWrQJMV7ktW7agZ8+e2LhxI4qLiznecywsLHD27FkBpiP1iQp5QhqJpKQk6OjoAAC+fv2KqKgobNq0Caamphg9ejQWLFgg4IT8JSQkwMbGhuc+cXFxoe+Xb8h/VJWUlPDt2ze0adMGDx48gLq6OkxMTAAAJSUlKC0tFXDCinl6esLV1RVr166FtLS0oONUSXUKeWF38uRJjBo1Sqg/bPDy9OlTbNmyBSoqKlyDB+rq6khKShJQsqoJDw/HnDlzAHB/WFVQUEBaWpogYhEBoB55QhoJeXl5pKSkAGCNECsqKrJHmSQkJLgueQsTHR0dhISE8Nz3+vVrGBgY1G+gagoPD8eff/4JoOH9UXVxccHmzZuxYcMG7N+/Hz179mTvCw8PR5MmTQSYrnKJiYkYMmRIgyniG5v09HR07txZ0DGqTVRUFEwmk+e+5ORkyMjI1HOi6lFUVERiYiLPfZ8/f4a6uno9JyKCQiPyhDQSbdq0wY4dO5CSkgIvLy906dKFvS8yMhLa2toCTFexIUOGYNeuXVBWVka3bt0AAMXFxbh37x68vLzwv//9T7ABK9GQ/6guWLAAJSUlePjwITp06IDp06ez9926dQvt27cXYLrKtWnTBmFhYULfx/+j2NjYah1ffqVNGP3xxx8IDg5uUK8/wGqfOXz4MFxcXCAiwhrTZDAYYDKZOHPmjNB/PV26dMHOnTvRsmVLNG3aFAArf1JSEry8vODq6irghKS+MJj8PpISQhqUhIQEzJs3DyEhIbC0tMS2bdugpqYGABg6dCjMzMywatUqAafkb82aNThx4gQYDAZKS0vZf1xHjBgh9JftV6xYgfv37+PgwYNo2rQpLC0tceHCBairq2PUqFHo1KmTULc2NWQfPnzAvHnzMGrUKDg7O/Ps0VZSUqr/YBWwsLCo0nFMJhMMBgMfPnz4xYlqLigoCCtWrICrqyucnJygoKDAdYylpaUAklXs06dPGD58OJSUlNCpUyd4e3tjwIABCA8Px5cvX3D27Fno6+sLOiZfWVlZGDt2LEJDQ2Fqaor379/D3Nwc0dHRMDQ0hLe3N2RlZQUdk9QDKuQJ+Q1kZ2dDQkICEhISgo5SoejoaAQFBSEtLQ2KiopwdHQU+rYaoPH9UQ0ODkZkZCTatGkDQ0NDQcepkLm5Ofv/+d3YKmyFsLm5OWRlZdGlSxd06NCh0t/LH6+uCZsfX3+A83sg7B9EoqOjsWvXLgQGBiI9PZ39njNjxgyhLuLLFRUV4cqVKxzvmU5OTvjzzz+F/r2e1B0q5AlphOLi4hAXFwdzc3Oh7/VsLBrqH9U5c+ZAQkKCPdXeqVOnsHLlSgCseyv27dsn1G0GFy5cqHRmmv79+9dTmqoJCgqCj48Pbt26BYBVqPfp0weOjo5COctORZ4+fVrpMW3btq2HJIT8nqiQJ6QROX36NHbt2oWkpCQwGAycO3cOlpaW8PDwQNu2bYV2Lva3b98iKyuLXTBmZmZi48aN+PTpE5ycnODh4cFutRE2BQUFmDlzJiZMmAA7OztBx6m2jh07Yv78+eybXP/44w+0a9eOPY98bGwsTpw4IeCUjVNhYSECAgJw7do13Lt3D3JycujevTt69+6NVq1aCToeaSDy8vJ4TmYgbC1l5Negm10JaSQa8qJK69atg6OjI7uQ/+eff3D79m04Ozvj0KFDEBERgYeHh4BT8iYpKYlnz55h7Nixgo5SIw19HvmGTEJCAl27dkXXrl2Rm5uL27dvw8fHByNHjkSfPn2wfv16QUessvDwcAQHByMjIwOKiopo3bo1expTYTRmzBi++0RERCAvLw8LCwsMHDgQmpqa9ZisarKzs7Fx40b4+voiMzOT5zHC2tJE6hYV8oQ0Eg15UaWIiAhMmjQJAJCfnw9fX1/8/fffGDhwIE6cOIGjR48KbSEPAM7OzggMDISDg4Ogo1RbQ5xHvk+fPtiyZQtMTU3Rp0+fCo9lMBi4cuVKPSWruZSUFMTGxiI2NhalpaVQVlYWdKQqKSwsxLx58+Dn5wcmkwkJCQkUFhaCwWDA1dUVGzduFMrWMnl5ebx79w5JSUkwMzODqqoqUlJSEBoaCnV1dejr6+Pw4cPw8vLC0aNHhe6G3UWLFuHx48cYNGgQDA0NuRZCI78PKuQJaSQa8qJK+fn57HnAX7x4gcLCQvbc1GZmZoiPjxdkvEoNHDgQy5YtQ05ODjp06ABVVVWuXmdhKwTKlc8j//HjR1y8eJE9Hz4gvPPIW1lZsX9eLC0tG1xfebnExERcv34dPj4+ePv2LSwtLTFw4ED07NlTKEeBedm6dSsCAgKwcuVK9OzZE3JycsjOzsb169exbt06/Pvvv0I5Y1P37t3x9etXnDhxArq6uuztMTExmDp1Kvr374+dO3di3Lhx2Lp1K7y8vASYlltQUBCWL1+Ovn37CjoKETAq5AlpJMoXVeJ1Y6KwL6qkp6eH+/fvo23btrh69SosLS3Z/Z0pKSmQk5MTbMBKTJ48GQBrlcuTJ082qJk7GuI88uU35gJoUO0n5U6fPo1r164hODgYBgYG6NmzJ7Zs2cKeD7whuXbtGmbPno0hQ4awt8nJyWHIkCHIy8vDwYMHhbKQ37VrF+bMmcNRxANAkyZN4OHhgS1btqB///4YP348li9fLqCU/Kmrq/OcapX8fqiQJ6SRaMiLKo0dOxZLly7FuXPnkJGRgY0bN7L3PX36FGZmZgJMV7mjR48KOkKNycvLcxTGPzp16lQ9p/k9LF++HLKysujVqxd7Tvk7d+7wPJbBYAj1/RcZGRkwMjLiuc/IyAgZGRn1nKhq4uLi+F7JYTAYSEhIAABoaGhwtSoKg+nTp2Pfvn1o3bo1z7n7ye+DCnlCGokJEyYgLi4Oy5YtY48gDR8+HABrUaWRI0cKMl6FBg0ahKZNmyIkJATNmzfn6DVXUlKq8MY0YdAYptfLyMhg3+zq4uICRUVFFBQUQFxcXOhmDFqzZk21jhfGBcVycnJw5cqVSvv3hb2QNzIywuXLl9GuXTuufVeuXOFb5AuatbU1duzYASsrK45Vr799+4adO3eiRYsW7H8LY5tTr169EBoaio4dO8LCwoJrdJ7BYMDT01NA6Uh9ouknCWlkoqOjuRY4Eea2GiJYTCYT//77L44dO4a8vDyOaUsnTpyIli1bYtq0aYKOyaFTp05VPpbBYMDf3/8Xpvm9+fn5YebMmbCxsUG3bt2gpqaGlJQU+Pr64tWrV9i+fTu6du0q6JhcIiIiMG7cOKSlpcHU1BTKyspIS0tDaGgoVFVVcfjwYRgbG+PAgQMQERHBhAkTBB2Zw5EjR7B+/XqoqamhSZMmPG92PXbsmACSkfpGhTwhRCjk5ubi4sWLXFPY9e/fX+gXtTI3N6/0hkth7ZEvL+Lnz58PR0dHuLq64vz587C0tMSpU6dw9uxZXLhwQdAxfxsREREIDw+HiooK2rRpA1FRUUFHqpS/vz92796NDx8+sO8JsbCwwLRp06r1oau+FRQU4Ny5c3j79i2SkpKgrq4Oa2trDBo0CAkJCdDT0xN0RL6cnJzQo0cPLFmyROiumJH6Ra01hDRg7969g7GxMaSkpPDu3btKjxfWmVPi4uIwevRofPv2Debm5lBVVUVUVBRu3ryJI0eO4OjRoxyXv4XNwoULuQr5zMxMBAYGIjExUahbgy5evIjZs2dj2LBhXL3A+vr6iI6OFlCyxovJZOLgwYO4desWiouL0b17d0ycOBFLlizBxYsX2cVws2bN4O3tDRUVFUFHrlDnzp3RuXNn5ObmIisrC/Ly8kL/4RtgrQHxY8thamoqbty4gTFjxuD169dC++EbYK0k3aVLFyriCRXyhDRkAwcOxJkzZ9CiRQsMHDiQ76iwsM+cUn6z5bVr1zh6aiMjIzFlyhSsX78e27dvF1S8SvHrYZ4+fTrmz58vtDf8AUB6ejqMjY157ispKUFxcXE9J6qeS5cuVXpMv379fnmO6vDy8sLWrVvRuXNnyMrKwtPTE6Ghobh//z4WLFgAIyMjhIWFYe/evdizZ49Q9vjzIiMj0yAK+B/l5eXh1q1b8PHxQVBQEEpKSmBhYYFFixYJOlqFevbsiYCAAJ6zlJHfCxXyhDRgR48eZRdhDXnmlKCgIKxatYrrxjgjIyPMnDlTKKd/q6q+ffti/vz5QrtCqoGBAQIDA3kWBE+fPhXq1TkB1tUQXn78UCtshfyFCxfg7u7OnuqzW7dumDZtGpYsWYJRo0YBYM3vLyYmhhMnTghdIb9mzRqMHz8eOjo6VbrxWNjyl5SU4MGDB7h69Sru3LmD/Px8qKmpoaSkBFu2bEHPnj0FHbFStra22L59O5KSkuDo6Mhz5pry2ctI40aFPCEN2I+zpTTkmVNKSkogKSnJc5+kpKRQTv9WVVFRUUK5Omq5sWPH4u+//4aYmBi6d+8OAIiPj8erV69w7NgxvlNTCotnz55xbcvIyMDDhw9x4sQJbN68WQCpKhYTEwN7e3v2vx0cHMBkMrla36ysrBAXF1ff8Sp1584dDBo0CDo6OnynzSzHYDCEppAPDg6Gj48Pbt68ibS0NCgpKaFv377o06cPTExMYG9vD3V1dUHHrJLyufljY2Nx7do1rv3CfAWW1C0q5AlpJD5+/IiEhAR06NCBa19AQAA0NTVhbm4ugGSVs7W1haenJ9q2bcsxjVpWVhb27t0LW1tbAaar3OHDh7m2FRUV4dOnT7h58yZ69+4tgFRVM2DAAGRkZGDnzp3Yt28fAMDDwwPS0tL43//+J/Sjk7wWxZGXl8ewYcNQUFCATZs24eDBgwJIxl9hYSGkpKTY/y7/fwkJCY7jxMXFhfJD7I/Fe2WFvDAZOXIkGAwG7O3tMW7cODg7O0NMjFUGZWVlCThd9dBMTKQcFfKENBJr166Fra0tz0L+zZs3ePHiBc+CUxgsWLAAo0aNQocOHeDg4MCewu7Ro0cQFxfH2rVrBR2xQhs2bODaJiEhAS0tLYwZMwbu7u4CSFV148aNw5AhQ/DixQv2tKU2NjYNfuVIExMTbNu2TdAxqqyymY+E0aVLl9ChQwcoKytz7UtPT8e9e/eEprXJ1NQUYWFhePbsGURFRZGWloYuXboI/crRvPy8Ii35fdH0k4Q0Em3btsXmzZvh4uLCte/BgweYO3cunjx5IoBkVRMfH4/Dhw8jODgYmZmZ7Oknx44dCy0tLUHHIw1MXl4eFi1ahA8fPsDX11fQcTiYm5tDWlqao3DPzc3l2sZkMpGfny/ULRIWFhY4ffo0ewGlH719+xaDBw8WqvwRERG4cuUKrl27hm/fvkFKSgodOnTAH3/8gUWLFuHo0aOws7MTdMwqYTKZCAgI4Jiyt02bNnBxcWmQHwpJzdCIPCGNRGFhIYqKivjuKygoqOdE1aOlpSX0M0U0VhkZGbh//z7i4+O5fk4YDAY8PDwElKxyffr04dpWVFSEhIQE5Ofn87xaImjCtsBWbVQ0FpiZmQlZWdl6TFO5Zs2aYfbs2Zg9eza7Z97X1xe+vr5gMBjsSQOEvZjPyMjApEmT8Pr1aygoKEBVVRUpKSk4cOAAWrVqhf379/O8AZY0PjQiT0gjMXz4cKirq2PHjh1c+2bMmIHExET8999/AkhWubi4OKSmpvKc5/7du3dQVVUV6lH5+/fvIzMzk90LHxcXh8WLF+PTp09wcnLCsmXLhHZavocPH2LGjBnIzc2FlJQU1wqRDAYDT58+FVC6yvGaw7+8ralbt258p9YkNRcQEIAHDx4AAI4fP47u3btDTU2N45iCggI8fvwYWlpaQr/CaElJCR4+fAgfHx/4+/sjLy8POjo6Qt2HvnjxYty9exebN2+Gs7Mze3tgYCDmzZuHP/74A//8848AE5L6QoU8IY3EvXv3MHXqVLRv3x4DBgyAhoYGEhMTceHCBTx8+BB79uxBx44dBR2Tp8mTJ6Np06ZYvHgx174NGzbg8+fP8PT0FECyqhk0aBB69OjBXsZ96tSpePfuHXr16oUrV66gT58+fKdJFLQ+ffpARUUFa9eupb5bUiXe3t7w9vYGwPrQqqqqyvNGXWNjY8yePRvNmjUTRMwayc/Px+3bt+Hj44O9e/cKOg5fDg4OmDdvHgYOHMi179y5c9i8eTMeP34sgGSkvlFrDSGNRMeOHbFlyxZs3LgR//vf/8BgMMBkMqGlpYXNmzcLbREPAK9fv8bQoUN57rO3t6/Soj+C9OXLF/aMQNnZ2Xjw4AE2b96M7t27w8TEBLt27RLaQj46OhoLFy5sVEV8TEwMvn79iubNm0NJSUnQcRodNzc3uLm5AQA6deqE3bt3w8LCQsCp6oaUlBR69+4t1DNNAax7QH6+ClJOXV0deXl59ZyICAoV8oQ0Ij179kTPnj0RGRmJ9PR0KCkpcS2yJIxyc3PZ08D9jMFgICcnp54TVU9xcTF7qfTyec3bt28PANDT00NycrLAslWmefPmQjlXeVWtX78eJSUlWLJkCQDg1q1bmDVrFoqLi6GoqAgvLy9YWVkJOGXj1ZCmn2xMLCwscPz4cbRr1w6ioqLs7aWlpTh27BiaN28uwHSkPokIOgAhpO4ZGRnB1ta2QRTxAGBsbIzbt2/z3Ofv7w9DQ8N6TlQ9RkZGuHLlCnJzc3H69GnY2Niwb/JLSkoS6lHhFStW4NixY3jw4AGKi4sFHafabt26xVGob926FR06dMCVK1dgbW3doKafbIiOHTvGd9GtzZs348SJE/Wc6PcwZ84cPH78GF27dsU///yDffv2Ye3atejSpQuePn2KOXPmCDoiqSc0Ik9IIxIZGQk/Pz++s48I63zsbm5uWLhwIURERDBw4ECO/v6zZ88Kbe5y7u7umDlzJi5dugRRUVGO3toHDx4I9ejY0KFDUVxcjEmTJkFERIRrhV0Gg4Hg4GABpatcUlISdHR0AABfv35FVFQUNm3aBFNTU4wePZq9Aib5NU6ePIlx48bx3GdgYIDDhw9j5MiR9Zyq8bOzs8OpU6ewd+9e+Pj4cEzZO2XKFJ4TB5DGiQp5QhqJS5cuYfHixZCUlISOjg7P2UeEVb9+/ZCcnIzdu3fj9OnT7O1SUlKYM2cO+vfvL8B0levcuTNu3LiB9+/fw8zMDAYGBux9rVq1gpmZmeDCVWL8+PFC/bNRGXl5eaSkpABgzdihqKjIHqGXkJAQ+mlXG7rY2Fg0bdqU5z49PT18+/atnhP9PqysrLBr1y5BxyACRoU8IY2Ep6cnXF1dsXbtWkhLSws6TrX99ddfGDZsGF6+fMnu77exsWkwqy7q6elBT0+Pazu/m3iFxfTp0wUdoVbatGmDHTt2ICUlBV5eXujSpQt7X2RkJLS1tQWYrvGTk5NDTEwM7O3tufZFR0dDSkpKAKkav+zsbOTm5kJDQ4NrX2JiImRlZYVuDn/ya1CPPCGNRGJiIoYMGdIgi/hycnJyaN++Pfr06YP27ds3mCL+/v378PHxYf87Li4O48aNg4uLCxYuXIjc3FwBpqvY+fPn+e5jMplYtmxZPaapvsWLF0NNTQ2bN2+Gjo4OZs2axd535coVtGnTRoDpGj9nZ2fs3r2b64bp+Ph47Nmzh+dK06T2li5diu3bt/Pct3PnTqH/vSV1h+aRJ6SRmDhxItq1a8eeFq4hqcr0kv369fvlOWqqIc8jb2VlhU2bNqFHjx4c25lMJubPn487d+4IdY98RbKzsyEhIcE1xzmpOwkJCRg6dCjS0tLg4ODAvr/l8ePHUFFRwX///QdNTU1Bx2x02rVrh+XLl6Nr165c+27fvo2VK1eyF+0ijRu11hDSSMyePRvz5s2DpKQknJ2dIS8vz3WMsM6ewq/I/bF3W5gL+YY8j/zKlSuxYMECSEtLs9caKCkpwaxZs/Do0SMcOnRIsAFroaFc0WnINDU1cenSJRw+fBiPHz/G58+foaSkhHHjxmHs2LFC+57T0GVkZPBtnZGWlkZ6enr9BiICQ4U8IY1E+Q2hK1as4Hvz4ocPH+ozUpWVz73+o4yMDDx8+BAnTpzgO72dsGjI88gPHDgQubm5mDlzJvbt2wdbW1tMnz4dr1+/hre3t1DPuAOw5s0+e/YsfH19ec7WBLCmMCW/jpKSEkdLE/n19PT0EBQUBCcnJ659jx49alQLvJGKUSFPSCOxdu3aBjv7CK+rB/Ly8hg2bBgKCgqwadMmHDx4UADJqqZ8HvmWLVs2uHnkAWD06NHIzc2Fu7s7TE1NER0djaNHj8LU1FTQ0Sq1adMmHD58GHZ2drC3t+earYmQxmjw4MHYsmULFBUVMXDgQKioqCA1NRUXLlzAkSNHMHv2bEFHJPWEeuQJIUItKCgIHh4eePnypaCj8OXv74+ZM2eipKSEPY98u3btAACLFi1CWloax9zygsbvsvvWrVvh5+cHT09PjkW4hPmDSLt27TB8+HB4eHgIOspvKT8/H3v27GFfESksLOQ6RlivBDZkTCYTq1atwn///QcAEBUVRUlJCQBg2LBhWL58uSDjkXpEI/KEEKGVl5eHM2fO8JxiTZg0tHnkHRwc+F69YTKZGDFiBMc2YS7ECgsLYWtrK+gYv62VK1fCx8cHvXv3hrGxMV0RqScMBgPLly+Hm5sbHj9+zJ6y18HBgeP9hzR+NCJPSCPy7NkznD59Gp8/f+bZK3z16lUBpKpcnz59uLYVFRUhISEB+fn52LBhA/r27SuAZI3ThQsXqtWGJcwLcq1evRoiIiJYsmSJoKP8lhwcHDBt2jSMGjVK0FF+K8+ePUPz5s153vCam5uLd+/ewc7OTgDJSH2jEXlCGokHDx5g8uTJcHR0xNu3b+Hi4oL8/Hy8ePECWlpaQv2mbmlpyVVYSkhIQEtLC926dYOxsbGAklVdamoqDh06hJCQEMTHx2PXrl0wMTGBt7c3WrZsiVatWgk6ItuAAQMEHaHOtGzZEtu2bUNKSgqcnJygoKDAdUy3bt0EkOz3ICoqSiPAAjBmzBicPn0aLVq04NoXGRmJMWPGCPWVNFJ3qJAnpJHYuXMn3NzcMHfuXFhaWmLmzJmwtLTEt2/fMGHCBDg4OAg6Il/r168XdIRaeffuHcaOHQt5eXnY2dnh6dOn7F7hhIQEHDlyBNu2bRNsSD7i4uKQmpoKS0tLrn3v3r2DqqoqtLS0BJCsaubPnw8AiI2NxfXr17n2MxgMKmh+oeHDh+Py5cvse0JI/aiomSIvL49W1P2NUCFPSCPx6dMnzJo1CyIiImAwGMjLywMA6OrqYvr06di5cyf+/PNPAadsnNatW4dWrVphz549YDAYuHz5Mntfy5YtcePGDQGmq9iKFSvQtGlTnoW8j48PPn/+DE9PTwEkqxqaWlKwpKSkEBwcjGHDhsHR0ZHrigiDwcDYsWMFE66RefXqFcdN/1evXuVarK2goAD+/v4wMjKq73hEQKiQJ6SRkJSURGlpKRgMBtTV1fH161f28vSysrKIj48XcEJOU6ZMqfKxDAZDqIvJkJAQ7Ny5E+Li4uyZI8qpqKggJSVFQMkq9/r1awwdOpTnPnt7+yqtuitINF+2YJWv8RAbG4tXr15x7adCvu48fPgQu3btAsB6XY8dO8Z1jJiYGIyNjWnWmt8IFfKENBLm5uaIioqCs7MzHB0dsXfvXigrK0NMTAzbtm0TujnBc3JyBB2hzkhLSyM7O5vnvtjYWKGevjE3NxdiYrz/FDAYDKH8PtnY2FT5Zl0Gg8E1aknqzsePHwUd4bcxbdo0TJs2DQDr/f7MmTM8e+TJ74UKeUIaCTc3N8TExAAAZs+ejSlTpmDq1KkAAC0tLfZIjrDgNZrUULVr1w6enp4crQUMBgP5+fk4evQoOnToIOCE/BkbG+P27dtwcXHh2ufv788xn7ywGD9+fINd/IyQukAfoEg5mn6SkEaKyWTiy5cvyM/Ph5GRESQkJAQdiUtgYCBUVVVhbm4OgJX5n3/+4ThGVlZW6Jd/T0hIwPDhw5GdnQ17e3vcvn0b7du3R0REBBgMBs6cOQNVVVVBx+Tp0qVLWLhwIYYNG4aBAwdCQ0MDiYmJuHDhAv777z+sXbtWqKefJIL17NmzSo8R5hmzGip63Uk5KuQJIQJx7do1zJ8/H//99x+sra0BACUlJbC0tIS6ujp7YZmUlBSsW7cOPXv2FGTcSmVmZuLIkSMICgpCWloaFBUV4ejoiHHjxgl1aw0AHDx4ELt370Z+fj57m5SUFDw8PPDXX38JMBkRdubm5mAwGByzqPx8tYRmDap79LqTclTIE9KIREZGws/PD/Hx8VwLQjEYDKxdu1ZAybhNnjwZCgoK2LRpE3tbeSF//vx59iwqmzZtQkREBPbt2yeoqBUqKCjApk2b0Ldv3wbdr5qdnY2XL1+yV4i0sbGBnJycoGMRIcerxSMjIwMPHz6En58fVq5cKdRT3zZU9LqTctQjT0gjcenSJSxevBiSkpLQ0dHhWipd2HqK3759i2XLllV6nJ2dHcd0jsJGUlIS58+fb/CLDsnJyaF9+/aCjkEamPK2uJ/Z29tDSkoKp0+fpoLyF6DXnZSjQp6QRsLT0xOurq5Yu3YtpKWlBR2nUhkZGVx946Kioti+fTv09fXZ2+Tk5JCenl7P6arHxsYGr169Qtu2bQUdpUr8/Pzg4OAABQUF+Pn5VXp8Q/+QQgTD1tYWXl5ego7x26HX/fdChTwhjURiYiJWrFjRIIp4AJCXl0dSUhLXdldXV45/JyUlQV5evr5i1ciMGTMwd+5ciIqKokOHDlBVVeW6AiJMffIzZsxgT103Y8aMCo+llVFJTd2+fVuofu5/F/S6/16okCekkWjTpg3CwsLg6Ogo6ChVYm1tjRs3bqBHjx4VHnfjxg2h7z0fNmwYAFY/f/kCOT8TpmLY398f6urq7P8npKZ4LexWVFSEqKgoxMXFYd68eQJI1fjR607KUSFPSCMxe/ZszJs3D5KSknB2duY5ii1MozQjR47E5MmTsXv3bkydOhUiIiIc+5lMJjw9PXHr1i3s3btXQCmrZu3atUJ3D0JFflwNlVZGJbXBa8EwSUlJODk5wdXVle67+EXodSflaNYaQhqJH29+4ldUCtOoMABs3boV+/fvh4aGBhwcHKCtrQ2ANS/7o0ePkJiYiIkTJ2L27NkCTtr4JSQkICEhgWu2I4DmoyZEGJWWlrLvH1JSUuIaDCG/ByrkCWkkLly4UOmosDAu7HPv3j0cPnwYL1++RGFhIQBAQkICtra2GDdunFCvinrmzBkcO3YMMTEx0NDQQI8ePeDu7i6Ui2/xEx0djXnz5uH169cAgJ//JFCPPPmZra0tjh49CisrK/a2vXv3YtCgQVBTUxNgst/DvXv34O3tjZcvX7I/eEtKSsLW1hZubm5C/Z5J6h4V8oQQoVBSUsIxuiQqKirYQJU4f/48lixZgqZNm6J58+aIiYlBSEgIRowYUaVpNYWFm5sbvn79ihkzZsDY2JjnhxB+U92R35O5uTn7ZmmA9btrZWWFc+fOsdd/IL/GmjVrcPz4cSgqKsLe3p59FTMuLg5PnjxBZmYmRo0ahSVLlgg4Kakv1CNPCBEKoqKiXNNRCrPjx4+je/fu2Lp1K/uS9t69e7Fr1y4sXrwYYmIN4+31zZs32LBhA00xSWqFxgR/vcuXL+PEiRPw8PDAhAkTICMjw7E/Ly8PXl5e2LNnD1q0aIE+ffoIKCmpTw3jLw0hpFKdOnXi21ojIiICeXl5mJubY+TIkTRqVge+fPmCOXPmcPSlDhs2DNu2bcO3b9/QtGlTAaarOk1NTeqtJaQBOHXqFAYPHozp06fz3C8tLY1p06YhMTERJ06coEL+N0Hv3oQ0Ep07d0ZpaSkyMzNhaWmJ9u3bw9LSEpmZmSguLoaZmRmeP3+OoUOHIigoSNBxG7zc3FwoKChwbCufKSg7O1sQkWpk1qxZOHDggNAvukWES3Z2NtLT09n/8dr24z5Se6GhoVzrbPDi6uqKsLCwekhEhAGNyBPSSOjq6kJHRwcHDhzguOSak5ODSZMmwcjICKtWrcKkSZOwY8cOODk5CTBt4xAZGcnRy19SUsLe/jNhugry8xzU8fHx6NSpEywsLLimLWUwGPD09KzPeKQBmDBhAte2sWPH8jyWbpauGwwGg1qYCBcq5AlpJLy9vbFs2TKuvklZWVlMmDABK1aswMSJEzF8+HAsWLBAQCkbl0WLFvHcPm/ePHabE5PJFLqZX36eg1pfX5/vPkJ+tm7dOkFH+C2ZmprCz88P7dq1q/C4mzdvwszMrJ5SEUGjQp6QRiItLY1vS0dWVhYyMzMBAIqKivUZq9E6evSooCPU2LFjxwQdgTRgwjiN7e9gxIgRWLBgATQ1NTF+/HhIS0tz7M/Pz8ehQ4dw/vx5bNy4UUApSX2jQp6QRsLe3h5btmyBrq4ubG1t2dufP3+OrVu3wsHBAQAQFRVFq3nWgbZt2wo6Qo117twZu3fvpmklSZ2Ki4tDXFwczM3Nua4Mktrr27cvXr9+jZ07d+Lo0aOwt7eHjo4OACA2NhZPnz5FRkYGRo4cid69ews4LakvNI88IY1EQkICpk6dig8fPkBBQQHKyspIS0tDZmYmLCws4OnpCU1NTZw5cwYSEhLo16+foCMTAfl5HnBCauP06dPYtWsXkpKSwGAw2PPJe3h4oG3btnBzcxN0xEbF398f3t7eePXqFcciejY2NnBzc0OnTp0EnJDUJxqRJ6SR0NTUxIULFxAQEICQkBAkJSVBXV0d1tbWHCv9DRkyRIApG4+Kpvvkxd/f/xemIUQwjhw5gs2bN2PcuHFwdHTE+PHj2fvatm2LmzdvUiFfxzp37ozOnTujpKQEaWlpAABlZWWhX0SP/BpUyBPSyHTo0IGW6K4HnTt35ijkfX19kZ2dDScnJ6iqqiIlJQVBQUGQl5ev0pRxhDREx48fh7u7O9zd3dmzNpUzNDREVFSUgJI1fqKiolBTUxN0DCJgVMgT0sjcv38fISEhiI+Px9SpU6Gjo4Nnz55BX18fmpqago7XaPy4BPrBgwehra2NgwcPQk5Ojr09KysLEydOFMoVa93c3Kp0RYHBYCA4OLgeEpGGKCEhATY2Njz3iYuLIzc3t54TEfJ7oUKekEYiNTUV7u7ueP36NbS1tREXF4dhw4ZBR0cH58+fh7S0NJYvXy7omI3SsWPHsHz5co4iHmAtEDVx4kSsXLkSkyZNElA63nr16gUtLS1BxyANnI6ODkJCQuDo6Mi17/Xr1zAwMKj/UIT8RqiQJ6SR+Oeff5CWlgYfHx80bdoUVlZW7H2Ojo60qM8vlJGRgaysLJ77fpz6U5gMGTKEbnYltTZkyBDs2rULysrK6NatGwCguLgY9+7dg5eXF/73v/8JNiAhjRwV8oQ0EgEBAVi9ejWMjY25elW1tbWRkJAgoGSNn4ODAzZv3gxtbW2OaSmfPHmCLVu2sKf+JKSxmTBhAuLi4rBs2TL2Fb/hw4cDYM17PnLkSEHGI6TRo0KekEaipKSE79zNmZmZEBcXr+dEv49Vq1Zh6tSpcHNzg7y8PHvqz6ysLFhYWGDlypWCjkjIL7N06VKMGTMGQUFBSE9Ph6KiIhwdHamthpB6QIU8IY1EixYtcP78eZ4z1ly7do1jkShStzQ0NHD+/Hncv38fb968YU/92aJFC7i4uAg6Hpdp06bRjc+kTunr60NfX1/QMQj57dCCUIQ0Ei9fvsSYMWPQokULuLq6Yt26dZgyZQo+ffqEgIAAnDx5EpaWloKOSYRUQkICEhISUFBQwLXPzs5OAIlIQ1FUVIRz586xZ8tatmwZDAwMcP36dZiZmcHY2FjQEQlptKiQJ6QRefnyJbZs2YKXL1+ipKQEDAYDrVq1wvz58/lOEUfqBpPJREBAAIKDg5GRkQFFRUW0adMGLi4u1Vo4qr5FR0dj3rx5eP36NQDW1/EjBoOBDx8+CCIaaQCio6MxduxYpKWloXnz5ggODmav7Lpy5Urk5+dj3bp1go5JSKNFrTWENAKFhYW4d+8eLCwscPz4ceTn5yMjIwMKCgqQlpYWdLxGLyMjA5MmTcLr16+hoKDAXhDqwIEDaNWqFfbv3w8FBQVBx+Rp6dKlSEhIwNq1a2FsbAwJCQlBRyINyJo1a6CiooKzZ89CQUGBY7YsOzs7bN26VYDpCGn8qJAnpBGQkJDAnDlzcPDgQejp6UFKSgpSUlKCjvXb2LBhA75+/QovLy84OzuztwcGBmLevHnYsGED/vnnHwEm5O/NmzfYsGEDe+pAQqrj6dOn2LJlC1RUVLhmy1JXV0dSUpKAkhHyexARdABCSN0wMjJCXFycoGP8lu7cuYO5c+dyFPEA4OzsjNmzZ8Pf319AySqnqakJERH6U0BqRlRUlKsdq1xycjLfmbQIIXWD3r0JaSRmz54NT09PhISECDrKbycvLw9qamo896mrqyMvL6+eE1XdrFmzcODAAaSnpws6CmmA7OzscPjwYRQVFbG3MRgMMJlMnDlzhueKr4SQukM3uxLSSPTp0weJiYnIzMyEkpISV2HJYDBw5coVAaVr3IYNGwZ5eXns3bsXoqKi7O2lpaWYNGkScnJycOrUKQEm5G/KlCn48OEDe857eXl5jv0MBoNWBSZ8ffr0CcOHD4eSkhI6deoEb29vDBgwAOHh4fjy5QvOnj1L01IS8gtRjzwhjcSPN5mR+jVnzhyMHz8eXbt2RefOnaGmpoaUlBTcvn0bycnJOHTokKAj8pWTk8NRaOXk5AgwDWlojI2Ncf78eezatQs+Pj4QFRXFvXv34OjoiM2bN1MRT8gvRiPyhDRwERER+O+//xATEwMNDQ24urpy9WqTX+/t27fYu3cvgoODkZmZCUVFRbRu3RpTpkyh+ftJo1RQUICTJ0/C2dkZpqamgo5DyG+JCnlCGrDnz59j3LhxKC4uhoqKCtLT01FaWoply5Zh+PDhgo5HCGnkWrZsiQMHDqBt27aCjkLIb4laawhpwHbu3AkjIyPs3bsX2trayM7OxqJFi7Bt2zYq5AWAyWQiKioKGRkZUFJSgoGBgVAuBnX48GH06dMHampqOHz4cIXHMhgMjB07tn6CkQbHwsICERERVMgTIiA0Ik9IA+bo6IiVK1dyzAEeExODLl264O7du9DW1hZgut/LiRMnsGfPHqSmpoLJZILBYEBVVRXu7u4YMWKEoONxMDc3x5kzZ9CiRQuYm5tXeCyt7Eoq8ubNG8ybNw+zZs1Chw4daAE6QuoZjcgT0oClpaVBS0uLY1t58Z6WlkaFfD05ffo0Vq9ejV69eqFnz55QU1NDcnIyrl+/jtWrV0NcXByDBw8WdEy2jx8/8vx/QqrLzc0NRUVFmDVrFgBASkqK4yoUg8FAcHCwoOIR0uhRIU8IIbV05MgRjB49GkuWLOHY3rlzZ6ioqMDLy0uoCvkfpaenQ0lJie/+sLAwupGR8DV+/HihbB8j5HdBrTWENGDm5uaQlpbm+kOam5vLtZ1Gxn4da2tr7Nu3D05OTlz7AgMDMWXKFKFdqGvgwIE4evQoZGVlufaFhITgr7/+wpMnTwSQjBBCSGVoRJ6QBmzatGmCjkDAWr315cuXPAv5V69eQV1dXQCpqm7y5Mk4ePAgpKSk2NtevnyJiRMnwsXFRYDJCCGEVIRG5AkhpJb27NmDPXv2YMKECejevTtUVVWRmpqKGzduwMvLCx4eHpg6daqgY/KUlpaGMWPGQENDA3v37oW4uDgeP36MqVOnwtXVFWvXroWIiIigYxIhNWbMGL77REREIC8vDwsLCwwcOBCampr1mIyQ3wMV8oQQUktMJhMbNmzA8ePHUVJSwt4uKiqK0aNHY8GCBQJMV7mkpCSMGjUKJiYmGDBgAGbNmoV+/fph5cqVgo5GhJyHhwfevXuHpKQkmJmZQVVVFSkpKQgNDYW6ujr09fXx4cMHlJaW4ujRo7Q4GiF1jAp5QgipI2lpaXjz5g0yMjKgqKiIFi1aQFlZWdCxqiQuLg4jR45EXFwcxowZg0WLFgk6EmkArl69iv3792Pv3r3Q1dVlb4+JicHUqVMxfvx4dOrUCePGjYOysjK8vLwEmJaQxocKeUII+c2sWbOG5/YvX74gJCQEvXv35ti+dOnS+ohFGiBXV1fMmTOHYy2Lcjdv3sSWLVtw69Yt+Pj4YPny5XTDPSF1jG52JYSQGvDz86vW8bwKHUG5c+cO330yMjIc+xkMBhXyhK+4uDi+008yGAwkJCQAADQ0NDjazgghdYMKeUIIqYEZM2ZU+VhhWx21okKekOqwtrbGjh07YGVlxbEA3bdv37Bz5060aNGC/W+62ZWQuketNYQQUgPfvn2r1vE/9g8T0lhERERg3LhxSEtLg6mpKZSVlZGWlobQ0FCoqqri8OHDMDY2xoEDByAiIoIJEyYIOjIhjQoV8oQQUsciIiIQHh4OZWVl2NnZQVRUVNCROKSmpiIxMRHm5uYc2z9+/Ig9e/bg06dPUFNTg5ubGzp16iSglKShKCgowLlz5/D27VskJSVBXV0d1tbWGDhwICQlJQUdj5BGjQp5QgipASaTiYMHD+LWrVsoLi5G9+7dMXHiRCxZsgQXL15kH9esWTN4e3tDRUVFgGk5LV26FO/evePI+e3bN/Tt2xf5+fkwMzNDfHw80tPT4e3tDTs7OwGmJYQQwg+t8kEIITXg5eWFrVu3QkNDAyYmJvD09MTcuXNx69YtLFiwAPv27cOcOXMQFxeHPXv2CDouhxcvXqBPnz4c244cOYLc3Fzs27cPFy5cwJ07d9CyZUscOHBAQCkJIYRUhm52JYSQGrhw4QLc3d0xffp0AKxZaaZNm4YlS5Zg1KhRAAAXFxeIiYnhxIkTQjXzS0JCAkxMTDi23b17FxYWFmjXrh0AQEpKCqNGjcLGjRsFEZEIMVtbWxw9ehRWVlawsbHhO2sNwLrRm6acJOTXoUKeEEJqICYmBvb29ux/Ozg4gMlkcq1caWVlhbi4uPqOVyEGg8FRfCUnJyMmJgZubm4cx2lqaiItLa2+4xEhN378eKirq7P/v6JCnhDya1EhTwghNVBYWAgpKSn2v8v/X0JCguM4cXFxoZs/29DQEEFBQezR97t374LBYMDZ2ZnjuKSkJKHq7SfCYdq0aez/L78iRQgRDCrkCSGkDjWE0cnRo0djwYIFyMzMhJqaGk6dOgV9fX04OTlxHPfw4UOYmpoKKCUhhJDKUCFPCCE15ObmxlW4jxw5kmObME4M1rdvXyQkJOD48ePIzMyEpaUlli9fDjGx738SUlJScPfuXRpxJVzGjBlTreOPHj36i5IQQqiQJ4SQGvixvaAhmjhxIiZOnMh3v6qqKoKCguoxEWko5OTkOD6shoSEIDk5Gebm5lBVVUVKSgo+fvzInk+eEPLr0DzyhBBCCKmRS5cuYf/+/di7dy/09fXZ2798+YKpU6di4sSJ6N+/vwATEtK40TzyhBBCCKmRPXv2YObMmRxFPAA0bdoU06dPF7o1FAhpbKiQJ4QQQkiNxMfH873Bm8FgICEhoZ4TEfJ7oUKeEEIIITXSokULbNu2DdHR0Rzbo6OjsX37drRs2VJAyQj5PVCPPCGEEEJq5NOnTxg/fjySk5NhYmLCvtk1PDwcqqqqOHz4MIyNjQUdk5BGiwp5QgghhNRYYWEhzp8/jzdv3iApKQnq6upo0aIFBgwYAElJSUHHI6RRo0KeEEIIIYSQBojmkSeEEEJIrXz69AkhISGIj4/HwIEDoa6uji9fvkBVVRVycnKCjkdIo0WFPCGEEEJqJC8vD0uXLsX169chIiKC0tJStG/fHurq6tiyZQuaNGmC+fPnCzomIY0WzVpDCCGEkBrZsGEDHj9+jAMHDiA4OBg/dut26NABDx48EGA6Qho/KuQJIYQQUiO+vr6YO3cu2rVrB3FxcY59urq6+Pbtm4CSEfJ7oEKeEEIIITWSm5sLdXV1nvvy8vLqOQ0hvx8q5AkhhBBSI2ZmZvDz8+O57969e7CysqrnRIT8XuhmV0IIIYTUiLu7O9zd3ZGXl4fu3buDwWDgzZs38PHxwfnz53HgwAFBRySkUaN55AkhhBBSYzdv3sTGjRsRGxvL3qalpYWFCxeie/fuAkxGSONHhTwhhBBCai0qKgppaWlQVFSEsbGxoOMQ8lugQp4QQggh1RIYGIhjx47h27dv0NDQQPfu3TF48GBBxyLkt0M98oQQQgipMn9/f3h4ePy/vTsLqeL/wzj+jNopPIahligVmVSHqGgzMIzIgpabJMo2KhIitAW6iKAFCQWLoiJaKLJ9Qb2xhAhKKEgLozIqosU2K7U0W9TQ0vO/+IX8RKvT/OrM/8y8X1fOfOfiuREevucz31HPnj0VFxenR48eqbS0VNXV1Vq1apXV8QBHYUceAAD4bN68eerevbv27dsnt9uttrY2ZWVlqbCwUDdv3lRQEAfiAf7CfxsAAPBZRUWFli5dKrfbLUkKCgpSenq6vnz5wgegAD+jyAMAAJ99/vxZERERHe5FRkZKkj59+mRFJMCxmJEHAAC/paGhQR8+fGi/bm1t7fK+JPXq1ct/wQCHYUYeAAD4zOPxyDCMTve9Xm+X9x88eOCPWIAjsSMPAAB8lpOTY3UEAN+xIw8AAAAEIF52BQAAf8yrV69UWlraaVYewJ/HaA0AADBly5Ytam1t1YYNGyRJFy9e1Jo1a/Tt2zeFh4crNzdXw4YNszglYF/syAMAAFMuXrzYoajv2LFDEydO1Llz5zR8+HDt2rXLunCAA1DkAQCAKe/evVNsbKwk6eXLl3r27JnS09M1ePBgLVq0SPfu3bM4IWBvFHkAAGBKz549VVdXJ0kqKSlReHh4+w69y+VSc3OzlfEA22NGHgAAmDJ27Fjt3r1bdXV1ys3N1ZQpU9rXnj59qpiYGAvTAfbHjjwAADBl/fr1ioqK0vbt2xUbG6s1a9a0r507d05jx461MB1gf5wjDwAA/riGhga5XC65XC6rowC2RZEHAAD/WVVVlaqqquTxeBQaGmp1HMARGK0BAACm5eXlacKECZo0aZIWLlyoZ8+eSZJWrFihY8eOWZwOsDeKPAAAMOXo0aPKyspSSkqKDh8+rH//yD9u3DhduHDBwnSA/XFqDQAAMOXkyZPKyMhQRkaGWltbO6zFxcW1784D+DvYkQcAAKbU1NRo1KhRXa5169ZNTU1Nfk4EOAtFHgAAmBIbG6u7d+92uXbnzh0NGDDAv4EAh6HIAwAAU1JTU7V//34VFBSooaFBkvTt2zddvnxZubm5mjt3rsUJAXvj+EkAAGBadna2Tp06JcMw1NbWpqCgf/YIFyxYoI0bN1qcDrA3ijwAAPhPKisrVVpaqvr6eoWHhysxMZGxGsAPKPIAAMCUGzduaOjQoXK73Z3WmpqadP/+fSUkJFiQDHAGZuQBAIApixcvVkVFRZdrT58+1eLFi/2cCHAWijwAADDlZz/qf/nyRT169PBjGsB5+CAUAADwWXl5uW7fvt1+XVRUpJs3b3Z4prm5WcXFxRo4cKC/4wGOQpEHAAA+u3r1qvbs2SNJMgxDJ06c6PRMSEiI4uPjlZmZ6e94gKPwsisAADDF4/EoPz9fI0aMsDoK4EgUeQAAACAA8bIrAAAw7evXrzpz5ozWr1+vtLQ0PX/+XJJ0/vz5H55oA+DPoMgDAABTKisrNW3aNG3btk0vX77UtWvX1NjYKOmfM+YPHTpkcULA3ijyAADAlOzsbEVEROjSpUs6evRoh+MoExISdOPGDQvTAfZHkQcAAKaUlZUpPT1dERERMgyjw1rv3r317t07i5IBzkCRBwAApgQHB//wo1C1tbUKDQ31cyLAWSjyAADAlISEBB05ckRfv35tv2cYhrxer/Lz85WYmGhhOsD+OH4SAACYUlFRofnz56tXr15KTk7WsWPHNGvWLD1+/FgvXrxQQUGB+vfvb3VMwLYo8gAAwLTKykrt2bNHJSUl+vDhg8LDw5WYmKjVq1dT4oG/jCIPAAAABKAQqwMAAIDAV11drbdv3yo6OlrR0dFWxwEcgSIPAABMy8vL0/79+1VTUyOv1yvDMNSnTx+lp6dr3rx5VscDbI0iDwAATDlw4IB27typmTNnaurUqYqKilJtba0uXLigzZs36+PHj1q+fLnVMQHbYkYeAACYkpSUpJkzZ2rt2rWd1rZu3aqioiJdvXrVgmSAM3COPAAAMKWxsVHjx4/vci0pKUmNjY1+TgQ4C0UeAACYkpSUpNLS0i7XSkpK+CAU8JcxIw8AAHx2//799r9nz56tzMxMvX//XpMnT1ZkZKTq6up06dIlXb9+XZs3b7YwKWB/zMgDAACfeTweGYbRfv3vGmEYRqfrBw8e+DUf4CTsyAMAAJ8dP37c6ggAvmNHHgAAAAhAvOwKAAAABCBGawAAgGmFhYXKy8vT8+fP1dzc3Gn91q1bFqQCnIEdeQAAYMrZs2e1adMmDRo0SPX19Zo+fbqmTp2qbt26KTIyUmlpaVZHBGyNIg8AAEw5cuSIMjIylJmZKUlasGCBcnJyVFxcrIiICLndbosTAvZGkQcAAKa8ePFCo0ePVnBwsIKDg9XQ0CBJCgsL07Jly3TixAmLEwL2RpEHAACmhIWFqaWlRZIUHR2tJ0+etK+1traqvr7eqmiAI/CyKwAAMGXYsGF6+PChJkyYoOTkZO3du1der1chISE6ePCgRo4caXVEwNY4Rx4AAJhSXl6uN2/eaMaMGfr06ZPWrVunK1euqK2tTcOHD9eOHTvUr18/q2MCtkWRBwAAf0xLS4taWloUFhZmdRTA9ijyAAAAQABiRh4AAPgsOztbaWlpio2NVXZ29i+f37hxox9SAc7EjjwAAPBZcnKy9u3bJ4/Ho+Tk5J8+axiGiouL/ZQMcB6KPAAAABCAGK0BAAC/7dWrVyooKFB5eblqa2tlGIaioqI0evRozZkzRzExMVZHBGyPHXkAAPBbioqKtGHDBrW0tCg6OloxMTHyer2qrq5WTU2NunfvrpycHM2YMcPqqICtUeQBAIDPKioqlJKSojFjxmjTpk2Kj4/vsP748WNlZWWpvLxcZ8+eVVxcnEVJAfsLsjoAAAAIHKdPn1a/fv108ODBTiVekgYNGqRDhw6pb9++OnXqlAUJAeegyAMAAJ+VlZUpNTVVLpfrh8+4XC6lpqaqrKzMj8kA56HIAwAAn1VVVWnIkCG/fG7IkCF6/fq1HxIBzkWRBwAAPmtsbJTb7f7lc6GhoWpqavJDIsC5KPIAAMBnnJEB/P/gHHkAAPBblixZIsMwfvoMhR/4+yjyAADAZytXrrQ6AoDvOEceAAAACEDMyAMAAAABiCIPAAAABCCKPAAAABCAKPIAAABAAKLIAwAAAAGIIg8AAAAEIIo8AAAAEIAo8gAAAEAA+h+SnBkNQMQudQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(9, 7))\n",
        "corr = df.corr()\n",
        "sns.heatmap(corr, annot=True, fmt=\".2f\", cmap=\"coolwarm\", center=0, square=True, linewidths=0.5)\n",
        "plt.title(\"Correlation heatmap, raw data\")\n",
        "plt.tight_layout()\n",
        "save_fig(\"correlation_heatmap.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "d031452d",
      "metadata": {
        "id": "d031452d"
      },
      "source": [
        "## 3. Missing Value Treatment\n",
        "\n",
        "Recoding the implausible zeros as NaN, then filling with the per-feature median. Median chosen\n",
        "over KNN imputation, simpler and less likely to overfit on a dataset this small (Chapter 3,\n",
        "Section 3.5, Step 3).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "id": "7450d6ca",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7450d6ca",
        "outputId": "d41a40e3-0ba0-461c-eb38-d0ec5bca84e8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Glucose            5\n",
            "BloodPressure     35\n",
            "SkinThickness    227\n",
            "Insulin          374\n",
            "BMI               11\n",
            "dtype: int64\n"
          ]
        }
      ],
      "source": [
        "df_clean = df.copy()\n",
        "df_clean[zero_cols] = df_clean[zero_cols].replace(0, np.nan)\n",
        "\n",
        "print(df_clean[zero_cols].isna().sum())\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "id": "ef35871d",
      "metadata": {
        "id": "ef35871d",
        "outputId": "b829ad87-4f62-4faf-8062-ba8edd4521c5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Glucose filled with median 117.0\n",
            "BloodPressure filled with median 72.0\n",
            "SkinThickness filled with median 29.0\n",
            "Insulin filled with median 125.0\n",
            "BMI filled with median 32.3\n",
            "remaining NaNs: 0\n"
          ]
        }
      ],
      "source": [
        "df_imputed = df_clean.copy()\n",
        "\n",
        "for col in zero_cols:\n",
        "    med = df_imputed[col].median()\n",
        "    df_imputed[col] = df_imputed[col].fillna(med)\n",
        "    print(col, \"filled with median\", med)\n",
        "\n",
        "print(\"remaining NaNs:\", df_imputed[zero_cols].isna().sum().sum())\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "id": "09efa299",
      "metadata": {
        "id": "09efa299",
        "outputId": "1cb8705c-86f1-460c-8b88-addfc6e6e2ff",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/missing_value_before_after.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1100x2000 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "fig, axes = plt.subplots(len(zero_cols), 2, figsize=(11, 4 * len(zero_cols)))\n",
        "\n",
        "for i, col in enumerate(zero_cols):\n",
        "    sns.histplot(df[col], bins=30, ax=axes[i, 0], color=\"#b85450\")\n",
        "    axes[i, 0].set_title(col + \" before\")\n",
        "\n",
        "    sns.histplot(df_imputed[col], bins=30, ax=axes[i, 1], color=\"#6c8ebf\")\n",
        "    axes[i, 1].set_title(col + \" after\")\n",
        "\n",
        "plt.tight_layout()\n",
        "save_fig(\"missing_value_before_after.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "id": "fac784b9",
      "metadata": {
        "id": "fac784b9",
        "outputId": "10871c73-4cbb-4598-ce81-a543044e50c9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               mean_before  mean_after  median_before  median_after\n",
              "Glucose             121.69      121.66          117.0         117.0\n",
              "BloodPressure        72.41       72.39           72.0          72.0\n",
              "SkinThickness        29.15       29.11           29.0          29.0\n",
              "Insulin             155.55      140.67          125.0         125.0\n",
              "BMI                  32.46       32.46           32.3          32.3"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1318b3c5-1eac-4552-a21d-6594afbee201\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>mean_before</th>\n",
              "      <th>mean_after</th>\n",
              "      <th>median_before</th>\n",
              "      <th>median_after</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Glucose</th>\n",
              "      <td>121.69</td>\n",
              "      <td>121.66</td>\n",
              "      <td>117.0</td>\n",
              "      <td>117.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BloodPressure</th>\n",
              "      <td>72.41</td>\n",
              "      <td>72.39</td>\n",
              "      <td>72.0</td>\n",
              "      <td>72.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SkinThickness</th>\n",
              "      <td>29.15</td>\n",
              "      <td>29.11</td>\n",
              "      <td>29.0</td>\n",
              "      <td>29.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Insulin</th>\n",
              "      <td>155.55</td>\n",
              "      <td>140.67</td>\n",
              "      <td>125.0</td>\n",
              "      <td>125.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BMI</th>\n",
              "      <td>32.46</td>\n",
              "      <td>32.46</td>\n",
              "      <td>32.3</td>\n",
              "      <td>32.3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1318b3c5-1eac-4552-a21d-6594afbee201')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-1318b3c5-1eac-4552-a21d-6594afbee201 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-1318b3c5-1eac-4552-a21d-6594afbee201');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "  <div id=\"id_db162031-291f-487f-b5cf-70ad2f9472b9\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('comparison')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_db162031-291f-487f-b5cf-70ad2f9472b9 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('comparison');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "comparison",
              "summary": "{\n  \"name\": \"comparison\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"mean_before\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 55.50649349400482,\n        \"min\": 29.15,\n        \"max\": 155.55,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          72.41,\n          32.46,\n          29.15\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"mean_after\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 50.79716399564054,\n        \"min\": 29.11,\n        \"max\": 140.67,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          72.39,\n          32.46,\n          29.11\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"median_before\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 45.310793416138715,\n        \"min\": 29.0,\n        \"max\": 125.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          72.0,\n          32.3,\n          29.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"median_after\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 45.310793416138715,\n        \"min\": 29.0,\n        \"max\": 125.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          72.0,\n          32.3,\n          29.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "comparison = pd.DataFrame({\n",
        "    \"mean_before\": df[zero_cols].replace(0, np.nan).mean(),\n",
        "    \"mean_after\": df_imputed[zero_cols].mean(),\n",
        "    \"median_before\": df[zero_cols].replace(0, np.nan).median(),\n",
        "    \"median_after\": df_imputed[zero_cols].median(),\n",
        "}).round(2)\n",
        "\n",
        "comparison\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "41a88fd4",
      "metadata": {
        "id": "41a88fd4"
      },
      "source": [
        "## 4. Feature Scaling\n",
        "\n",
        "Scaling every feature to a 0 to 1 range with Min-Max normalisation, so a feature like Insulin\n",
        "(large raw values) doesn't dominate a feature like DiabetesPedigreeFunction just because of its\n",
        "scale (Chapter 3, Section 3.5, Step 4).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "id": "24917044",
      "metadata": {
        "id": "24917044",
        "outputId": "43959dff-c7dd-4d91-8492-7368f638196c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
              "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
              "mean      0.226180    0.501008       0.493742       0.240305    0.152250   \n",
              "std       0.198210    0.196376       0.123435       0.095557    0.103826   \n",
              "min       0.000000    0.000000       0.000000       0.000000    0.000000   \n",
              "25%       0.058824    0.359677       0.408163       0.195652    0.129207   \n",
              "50%       0.176471    0.470968       0.489796       0.239130    0.133413   \n",
              "75%       0.352941    0.620968       0.571429       0.271739    0.136118   \n",
              "max       1.000000    1.000000       1.000000       1.000000    1.000000   \n",
              "\n",
              "              BMI  DiabetesPedigreeFunction         Age     Outcome  \n",
              "count  768.000000                768.000000  768.000000  768.000000  \n",
              "mean     0.291518                  0.168179    0.204015    0.348958  \n",
              "std      0.140597                  0.141473    0.196004    0.476951  \n",
              "min      0.000000                  0.000000    0.000000    0.000000  \n",
              "25%      0.190184                  0.070773    0.050000    0.000000  \n",
              "50%      0.288344                  0.125747    0.133333    0.000000  \n",
              "75%      0.376278                  0.234095    0.333333    1.000000  \n",
              "max      1.000000                  1.000000    1.000000    1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5bc61a23-7be6-40b6-9934-e875634269bd\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pregnancies</th>\n",
              "      <th>Glucose</th>\n",
              "      <th>BloodPressure</th>\n",
              "      <th>SkinThickness</th>\n",
              "      <th>Insulin</th>\n",
              "      <th>BMI</th>\n",
              "      <th>DiabetesPedigreeFunction</th>\n",
              "      <th>Age</th>\n",
              "      <th>Outcome</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "      <td>768.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.226180</td>\n",
              "      <td>0.501008</td>\n",
              "      <td>0.493742</td>\n",
              "      <td>0.240305</td>\n",
              "      <td>0.152250</td>\n",
              "      <td>0.291518</td>\n",
              "      <td>0.168179</td>\n",
              "      <td>0.204015</td>\n",
              "      <td>0.348958</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.198210</td>\n",
              "      <td>0.196376</td>\n",
              "      <td>0.123435</td>\n",
              "      <td>0.095557</td>\n",
              "      <td>0.103826</td>\n",
              "      <td>0.140597</td>\n",
              "      <td>0.141473</td>\n",
              "      <td>0.196004</td>\n",
              "      <td>0.476951</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.058824</td>\n",
              "      <td>0.359677</td>\n",
              "      <td>0.408163</td>\n",
              "      <td>0.195652</td>\n",
              "      <td>0.129207</td>\n",
              "      <td>0.190184</td>\n",
              "      <td>0.070773</td>\n",
              "      <td>0.050000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.176471</td>\n",
              "      <td>0.470968</td>\n",
              "      <td>0.489796</td>\n",
              "      <td>0.239130</td>\n",
              "      <td>0.133413</td>\n",
              "      <td>0.288344</td>\n",
              "      <td>0.125747</td>\n",
              "      <td>0.133333</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>0.352941</td>\n",
              "      <td>0.620968</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>0.271739</td>\n",
              "      <td>0.136118</td>\n",
              "      <td>0.376278</td>\n",
              "      <td>0.234095</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5bc61a23-7be6-40b6-9934-e875634269bd')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5bc61a23-7be6-40b6-9934-e875634269bd button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-5bc61a23-7be6-40b6-9934-e875634269bd');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df_scaled\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"Pregnancies\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.42752761318076,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.22617953431372548,\n          0.1764705882352941,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Glucose\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.37011610509234,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.501008064516129,\n          0.4709677419354839,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BloodPressure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.373275008956,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.4937420280612244,\n          0.48979591836734687,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SkinThickness\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.4260165205947,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.24030514039855075,\n          0.2391304347826087,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Insulin\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.4456063546436,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.15224984975961542,\n          0.13341346153846156,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BMI\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.41365984887875,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.2915175528289026,\n          0.28834355828220865,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DiabetesPedigreeFunction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.44128913329956,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.16817946288784513,\n          0.1257472245943638,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.43237743598314,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          0.20401475694444446,\n          0.13333333333333336,\n          768.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Outcome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 271.3865920388932,\n        \"min\": 0.0,\n        \"max\": 768.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.3489583333333333,\n          1.0,\n          0.4769513772427971\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "feature_cols = [c for c in df_imputed.columns if c != \"Outcome\"]\n",
        "\n",
        "scaler = MinMaxScaler()\n",
        "scaled_values = scaler.fit_transform(df_imputed[feature_cols])\n",
        "\n",
        "df_scaled = pd.DataFrame(scaled_values, columns=feature_cols)\n",
        "df_scaled[\"Outcome\"] = df_imputed[\"Outcome\"].values\n",
        "\n",
        "# saving the scaler, the realtime script needs the exact same scaling later\n",
        "joblib.dump(scaler, \"../models/scaler.pkl\")\n",
        "joblib.dump(feature_cols, \"../models/feature_columns.pkl\")\n",
        "\n",
        "df_scaled.describe()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "cf7d9af1",
      "metadata": {
        "id": "cf7d9af1"
      },
      "source": [
        "## 5. Train-Test Split\n",
        "\n",
        "Splitting into train and test sets now, before any resampling happens. The test set stays\n",
        "untouched by SMOTE all the way through, so evaluation later reflects real-world class balance\n",
        "(Chapter 3, Section 3.5, Step 5).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "id": "2ac284b9",
      "metadata": {
        "id": "2ac284b9",
        "outputId": "12135515-0aaa-42b8-a014-cf18f2267412",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "train: (614, 8) test: (154, 8)\n",
            "train class balance:\n",
            "Outcome\n",
            "0    0.651\n",
            "1    0.349\n",
            "Name: proportion, dtype: float64\n",
            "test class balance:\n",
            "Outcome\n",
            "0    0.649\n",
            "1    0.351\n",
            "Name: proportion, dtype: float64\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['../models/background_sample.pkl']"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ],
      "source": [
        "X = df_scaled[feature_cols]\n",
        "y = df_scaled[\"Outcome\"]\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(\n",
        "    X, y, test_size=0.2, stratify=y, random_state=RANDOM_STATE\n",
        ")\n",
        "\n",
        "print(\"train:\", X_train.shape, \"test:\", X_test.shape)\n",
        "print(\"train class balance:\")\n",
        "print(y_train.value_counts(normalize=True).round(3))\n",
        "print(\"test class balance:\")\n",
        "print(y_test.value_counts(normalize=True).round(3))\n",
        "\n",
        "# saving a small background sample too, the realtime script needs this later for\n",
        "# explaining single predictions with the logistic regression model, a single row\n",
        "background_sample = X_train.sample(n=min(100, len(X_train)), random_state=RANDOM_STATE)\n",
        "joblib.dump(background_sample, \"../models/background_sample.pkl\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "d7a6d791",
      "metadata": {
        "id": "d7a6d791"
      },
      "source": [
        "## 6. Cross-Validation + SMOTE Pipeline\n",
        "\n",
        "This is the leakage-safety step flagged repeatedly in Chapter 2 (Abousaber et al. and others\n",
        "warn that fitting SMOTE before the train-test split inflates results). Building the pipeline\n",
        "so SMOTE only ever sees training folds, never the test data.\n",
        "\n",
        "Quick demo below to show why this actually matters, comparing the wrong way against the\n",
        "pipeline-safe way on the same data.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "id": "dd6cbab6",
      "metadata": {
        "id": "dd6cbab6",
        "outputId": "af22ec4f-0504-4144-e85a-ed0db6f7618e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "leaky approach, mean AUC: 0.8431\n"
          ]
        }
      ],
      "source": [
        "# the wrong way: SMOTE fit once on the whole training set, outside the CV loop\n",
        "# this leaks a bit of information across folds since the synthetic points influence\n",
        "# more than one fold at once\n",
        "smote_leaky = SMOTE(random_state=RANDOM_STATE)\n",
        "X_train_leaky, y_train_leaky = smote_leaky.fit_resample(X_train, y_train)\n",
        "\n",
        "leaky_scores = cross_val_score(\n",
        "    LogisticRegression(max_iter=1000, random_state=RANDOM_STATE),\n",
        "    X_train_leaky, y_train_leaky,\n",
        "    cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=RANDOM_STATE),\n",
        "    scoring=\"roc_auc\"\n",
        ")\n",
        "print(\"leaky approach, mean AUC:\", round(leaky_scores.mean(), 4))\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "id": "477c09df",
      "metadata": {
        "id": "477c09df",
        "outputId": "e935bcbc-1041-4036-8769-ddfefe5f6804",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "pipeline-safe approach, mean AUC: 0.8408\n",
            "\n",
            "difference: 0.0022\n",
            "if the leaky score is noticeably higher, that gap is basically the leakage Chapter 2 warns about\n"
          ]
        }
      ],
      "source": [
        "# the correct way: SMOTE lives inside the pipeline, so it only gets refit on\n",
        "# each fold's training portion, never touches the fold being validated\n",
        "safe_pipeline = ImbPipeline(steps=[\n",
        "    (\"smote\", SMOTE(random_state=RANDOM_STATE)),\n",
        "    (\"clf\", LogisticRegression(max_iter=1000, random_state=RANDOM_STATE))\n",
        "])\n",
        "\n",
        "safe_scores = cross_val_score(\n",
        "    safe_pipeline, X_train, y_train,\n",
        "    cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=RANDOM_STATE),\n",
        "    scoring=\"roc_auc\"\n",
        ")\n",
        "print(\"pipeline-safe approach, mean AUC:\", round(safe_scores.mean(), 4))\n",
        "print()\n",
        "print(\"difference:\", round(leaky_scores.mean() - safe_scores.mean(), 4))\n",
        "print(\"if the leaky score is noticeably higher, that gap is basically the leakage Chapter 2 warns about\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "e4f10932",
      "metadata": {
        "id": "e4f10932"
      },
      "source": [
        "## 7. Feature Consideration\n",
        "\n",
        "Checking correlation with the target and running a quick baseline model just to sanity check\n",
        "which features look important before the real hyperparameter search starts (Chapter 3, Section\n",
        "3.5, Step 7).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "id": "5f309063",
      "metadata": {
        "id": "5f309063",
        "outputId": "799a974f-3572-4a11-ef09-6095fc01b278",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 593
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Glucose                     0.492782\n",
            "BMI                         0.312038\n",
            "Age                         0.238356\n",
            "Pregnancies                 0.221898\n",
            "SkinThickness               0.214873\n",
            "Insulin                     0.203790\n",
            "DiabetesPedigreeFunction    0.173844\n",
            "BloodPressure               0.165723\n",
            "Name: Outcome, dtype: float64\n",
            "saved figure to ../outputs/figures/target_correlation.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "target_corr = df_scaled.corr()[\"Outcome\"].drop(\"Outcome\").sort_values(key=abs, ascending=False)\n",
        "print(target_corr)\n",
        "\n",
        "plt.figure(figsize=(7, 4))\n",
        "sns.barplot(x=target_corr.values, y=target_corr.index, color=\"#82b366\")\n",
        "plt.title(\"Correlation with Outcome\")\n",
        "plt.xlabel(\"correlation\")\n",
        "save_fig(\"target_correlation.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "id": "a8239b46",
      "metadata": {
        "id": "a8239b46",
        "outputId": "22242953-2e34-4952-fce0-194dd64fa87e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/tmp/ipykernel_3047/1667556792.py:17: FutureWarning: The NumPy global RNG was seeded by calling `np.random.seed`. In a future version this function will no longer use the global RNG. Pass `rng` explicitly to opt-in to the new behaviour and silence this warning.\n",
            "  shap.summary_plot(shap_values_baseline[:, :, 1], X_test, show=False)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/shap_baseline_summary.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x470 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# quick and dirty baseline, not tuned, just to see roughly which features matter\n",
        "baseline_pipeline = ImbPipeline(steps=[\n",
        "    (\"smote\", SMOTE(random_state=RANDOM_STATE)),\n",
        "    (\"clf\", RandomForestClassifier(random_state=RANDOM_STATE))\n",
        "])\n",
        "baseline_pipeline.fit(X_train, y_train)\n",
        "\n",
        "baseline_rf = baseline_pipeline.named_steps[\"clf\"]\n",
        "\n",
        "# TreeExplainer without background data uses tree_path_dependent perturbation,\n",
        "# skips the additivity issues that come up with the interventional/background approach\n",
        "explainer_baseline = shap.TreeExplainer(baseline_rf)\n",
        "shap_values_baseline = explainer_baseline(X_test, check_additivity=False)\n",
        "\n",
        "# binary classifiers sometimes give shap values per class, index 1 = positive class\n",
        "if len(shap_values_baseline.shape) == 3:\n",
        "    shap.summary_plot(shap_values_baseline[:, :, 1], X_test, show=False)\n",
        "else:\n",
        "    shap.summary_plot(shap_values_baseline, X_test, show=False)\n",
        "\n",
        "save_fig(\"shap_baseline_summary.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "c5ab2788",
      "metadata": {
        "id": "c5ab2788"
      },
      "source": [
        "## 8. Model Training\n",
        "\n",
        "Training the three classifiers, each wrapped in the same SMOTE-safe pipeline, with a grid\n",
        "search over hyperparameters done inside 10-fold stratified cross-validation. `GridSearchCV`\n",
        "refits the winning combination on the full training set automatically at the end.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "60551d14",
      "metadata": {
        "id": "60551d14"
      },
      "source": [
        "### 8a. Logistic Regression"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "id": "0b466159",
      "metadata": {
        "id": "0b466159",
        "outputId": "01093f0f-ba0a-4a64-a5bf-f22dcfba1830",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "best params: {'clf__C': 10, 'clf__penalty': 'l2', 'clf__solver': 'lbfgs'}\n",
            "best cv AUC: 0.8418\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['../models/logistic_regression.pkl']"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ],
      "source": [
        "lr_pipeline = ImbPipeline(steps=[\n",
        "    (\"smote\", SMOTE(random_state=RANDOM_STATE)),\n",
        "    (\"clf\", LogisticRegression(max_iter=2000, random_state=RANDOM_STATE))\n",
        "])\n",
        "\n",
        "lr_param_grid = {\n",
        "    \"clf__C\": [0.01, 0.1, 1, 10],\n",
        "    \"clf__penalty\": [\"l2\"],\n",
        "    \"clf__solver\": [\"lbfgs\"]\n",
        "}\n",
        "\n",
        "lr_search = GridSearchCV(\n",
        "    lr_pipeline, lr_param_grid,\n",
        "    cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=RANDOM_STATE),\n",
        "    scoring=\"roc_auc\", n_jobs=-1\n",
        ")\n",
        "lr_search.fit(X_train, y_train)\n",
        "\n",
        "print(\"best params:\", lr_search.best_params_)\n",
        "print(\"best cv AUC:\", round(lr_search.best_score_, 4))\n",
        "\n",
        "lr_model = lr_search.best_estimator_\n",
        "\n",
        "# saving just the fitted classifier\n",
        "joblib.dump(lr_model.named_steps[\"clf\"], \"../models/logistic_regression.pkl\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "2221e0d2",
      "metadata": {
        "id": "2221e0d2"
      },
      "source": [
        "### 8b. Random Forest"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "id": "001dc9b8",
      "metadata": {
        "id": "001dc9b8",
        "outputId": "251b47a7-1adb-4740-874e-b194ccdc31f5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "best params: {'clf__max_depth': 6, 'clf__min_samples_split': 5, 'clf__n_estimators': 400}\n",
            "best cv AUC: 0.8321\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['../models/random_forest.pkl']"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ],
      "source": [
        "rf_pipeline = ImbPipeline(steps=[\n",
        "    (\"smote\", SMOTE(random_state=RANDOM_STATE)),\n",
        "    (\"clf\", RandomForestClassifier(random_state=RANDOM_STATE))\n",
        "])\n",
        "\n",
        "rf_param_grid = {\n",
        "    \"clf__n_estimators\": [200, 400],\n",
        "    \"clf__max_depth\": [None, 6, 10],\n",
        "    \"clf__min_samples_split\": [2, 5]\n",
        "}\n",
        "\n",
        "rf_search = GridSearchCV(\n",
        "    rf_pipeline, rf_param_grid,\n",
        "    cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=RANDOM_STATE),\n",
        "    scoring=\"roc_auc\", n_jobs=-1\n",
        ")\n",
        "rf_search.fit(X_train, y_train)\n",
        "\n",
        "print(\"best params:\", rf_search.best_params_)\n",
        "print(\"best cv AUC:\", round(rf_search.best_score_, 4))\n",
        "\n",
        "rf_model = rf_search.best_estimator_\n",
        "\n",
        "# same as logistic regression above, just the classifier gets saved\n",
        "joblib.dump(rf_model.named_steps[\"clf\"], \"../models/random_forest.pkl\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "cdb00a21",
      "metadata": {
        "id": "cdb00a21"
      },
      "source": [
        "### 8c. XGBoost"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "id": "deb032d8",
      "metadata": {
        "id": "deb032d8",
        "outputId": "ed57e5c7-26b1-49cd-b47a-9cb1934e6611",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.13/dist-packages/xgboost/training.py:200: UserWarning: [11:32:41] WARNING: /__w/xgboost/xgboost/src/learner.cc:794: \n",
            "Parameters: { \"use_label_encoder\" } are not used.\n",
            "\n",
            "  bst.update(dtrain, iteration=i, fobj=obj)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "best params: {'clf__learning_rate': 0.01, 'clf__max_depth': 3, 'clf__n_estimators': 400}\n",
            "best cv AUC: 0.8305\n"
          ]
        }
      ],
      "source": [
        "xgb_pipeline = ImbPipeline(steps=[\n",
        "    (\"smote\", SMOTE(random_state=RANDOM_STATE)),\n",
        "    (\"clf\", XGBClassifier(\n",
        "        random_state=RANDOM_STATE,\n",
        "        eval_metric=\"logloss\",\n",
        "        use_label_encoder=False\n",
        "    ))\n",
        "])\n",
        "\n",
        "xgb_param_grid = {\n",
        "    \"clf__n_estimators\": [200, 400],\n",
        "    \"clf__max_depth\": [3, 5, 7],\n",
        "    \"clf__learning_rate\": [0.01, 0.1]\n",
        "}\n",
        "\n",
        "xgb_search = GridSearchCV(\n",
        "    xgb_pipeline, xgb_param_grid,\n",
        "    cv=StratifiedKFold(n_splits=10, shuffle=True, random_state=RANDOM_STATE),\n",
        "    scoring=\"roc_auc\", n_jobs=-1\n",
        ")\n",
        "xgb_search.fit(X_train, y_train)\n",
        "\n",
        "print(\"best params:\", xgb_search.best_params_)\n",
        "print(\"best cv AUC:\", round(xgb_search.best_score_, 4))\n",
        "\n",
        "xgb_model = xgb_search.best_estimator_\n",
        "\n",
        "# xgboost has its own save format.\n",
        "xgb_model.named_steps[\"clf\"].save_model(\"../models/xgboost_model.json\")\n",
        "\n",
        "# saving which library versions actually built these files.\n",
        "import sklearn\n",
        "with open(\"../models/model_versions.txt\", \"w\") as f:\n",
        "    f.write(f\"scikit-learn=={sklearn.__version__}\\n\")\n",
        "    f.write(f\"xgboost=={xgb.__version__}\\n\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "adb6ab8f",
      "metadata": {
        "id": "adb6ab8f"
      },
      "source": [
        "## 9. Evaluation\n",
        "\n",
        "Testing all three tuned models on the held-out test set they've never seen, using the five\n",
        "metrics set out in Chapter 3, Section 3.6.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "id": "c14903cb",
      "metadata": {
        "id": "c14903cb",
        "outputId": "d25adb86-51d0-4cf5-d646-ca6b415d84be",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     Accuracy      F1  AUC-ROC  Precision  Recall\n",
              "Model                                                            \n",
              "Logistic Regression    0.7143  0.6207   0.8098     0.5806  0.6667\n",
              "Random Forest          0.7078  0.6512   0.8196     0.5600  0.7778\n",
              "XGBoost                0.7338  0.6822   0.8172     0.5867  0.8148"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1b91f1d2-8046-4f1a-9a54-33d680caea19\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Accuracy</th>\n",
              "      <th>F1</th>\n",
              "      <th>AUC-ROC</th>\n",
              "      <th>Precision</th>\n",
              "      <th>Recall</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Model</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Logistic Regression</th>\n",
              "      <td>0.7143</td>\n",
              "      <td>0.6207</td>\n",
              "      <td>0.8098</td>\n",
              "      <td>0.5806</td>\n",
              "      <td>0.6667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Random Forest</th>\n",
              "      <td>0.7078</td>\n",
              "      <td>0.6512</td>\n",
              "      <td>0.8196</td>\n",
              "      <td>0.5600</td>\n",
              "      <td>0.7778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XGBoost</th>\n",
              "      <td>0.7338</td>\n",
              "      <td>0.6822</td>\n",
              "      <td>0.8172</td>\n",
              "      <td>0.5867</td>\n",
              "      <td>0.8148</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1b91f1d2-8046-4f1a-9a54-33d680caea19')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-1b91f1d2-8046-4f1a-9a54-33d680caea19 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-1b91f1d2-8046-4f1a-9a54-33d680caea19');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "  <div id=\"id_86e655a6-cc0a-468e-9167-0a3d94c4b5a9\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('results_df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_86e655a6-cc0a-468e-9167-0a3d94c4b5a9 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('results_df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "results_df",
              "summary": "{\n  \"name\": \"results_df\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"Model\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Logistic Regression\",\n          \"Random Forest\",\n          \"XGBoost\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Accuracy\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.013530828996529866,\n        \"min\": 0.7078,\n        \"max\": 0.7338,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.7143,\n          0.7078,\n          0.7338\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"F1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.030750338751521635,\n        \"min\": 0.6207,\n        \"max\": 0.6822,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.6207,\n          0.6512,\n          0.6822\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AUC-ROC\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.005108163401197497,\n        \"min\": 0.8098,\n        \"max\": 0.8196,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.8098,\n          0.8196,\n          0.8172\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precision\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.013990830330374696,\n        \"min\": 0.56,\n        \"max\": 0.5867,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.5806,\n          0.56,\n          0.5867\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Recall\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.07707768808157132,\n        \"min\": 0.6667,\n        \"max\": 0.8148,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.6667,\n          0.7778,\n          0.8148\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 23
        }
      ],
      "source": [
        "models = {\n",
        "    \"Logistic Regression\": lr_model,\n",
        "    \"Random Forest\": rf_model,\n",
        "    \"XGBoost\": xgb_model\n",
        "}\n",
        "\n",
        "results = []\n",
        "\n",
        "for name, model in models.items():\n",
        "    y_pred = model.predict(X_test)\n",
        "    y_prob = model.predict_proba(X_test)[:, 1]\n",
        "\n",
        "    results.append({\n",
        "        \"Model\": name,\n",
        "        \"Accuracy\": accuracy_score(y_test, y_pred),\n",
        "        \"F1\": f1_score(y_test, y_pred),\n",
        "        \"AUC-ROC\": roc_auc_score(y_test, y_prob),\n",
        "        \"Precision\": precision_score(y_test, y_pred),\n",
        "        \"Recall\": recall_score(y_test, y_pred)\n",
        "    })\n",
        "\n",
        "results_df = pd.DataFrame(results).set_index(\"Model\").round(4)\n",
        "results_df\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "id": "584020fe",
      "metadata": {
        "id": "584020fe",
        "outputId": "e2c8fd42-9f92-4acb-a503-5ad8055d8dd1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 381
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/confusion_matrices.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x400 with 3 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
        "\n",
        "for ax, (name, model) in zip(axes, models.items()):\n",
        "    y_pred = model.predict(X_test)\n",
        "    cm = confusion_matrix(y_test, y_pred)\n",
        "    sns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\", ax=ax, cbar=False)\n",
        "    ax.set_title(name)\n",
        "    ax.set_xlabel(\"predicted\")\n",
        "    ax.set_ylabel(\"actual\")\n",
        "\n",
        "plt.tight_layout()\n",
        "save_fig(\"confusion_matrices.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "id": "b5aa138c",
      "metadata": {
        "id": "b5aa138c",
        "outputId": "d4231382-c78d-4fc0-9a73-36a603c0f510",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 590
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/roc_curves.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(7, 6))\n",
        "\n",
        "for name, model in models.items():\n",
        "    y_prob = model.predict_proba(X_test)[:, 1]\n",
        "    fpr, tpr, _ = roc_curve(y_test, y_prob)\n",
        "    auc_val = roc_auc_score(y_test, y_prob)\n",
        "    plt.plot(fpr, tpr, label=f\"{name} (AUC = {auc_val:.3f})\")\n",
        "\n",
        "plt.plot([0, 1], [0, 1], linestyle=\"--\", color=\"grey\", label=\"chance\")\n",
        "plt.xlabel(\"False Positive Rate\")\n",
        "plt.ylabel(\"True Positive Rate\")\n",
        "plt.title(\"ROC curves, all three models\")\n",
        "plt.legend()\n",
        "save_fig(\"roc_curves.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "16dd1921",
      "metadata": {
        "id": "16dd1921"
      },
      "source": [
        "## 10. SHAP Explainability\n",
        "\n",
        "Global feature importance for each model, plus a look at one individual prediction to see how\n",
        "the model actually reasoned about a specific patient (Chapter 3, Section 3.6).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "id": "59017728",
      "metadata": {
        "id": "59017728",
        "outputId": "372a309b-a675-46b7-a920-18c38130d678",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:shap:Background dataset has 614 samples but max_samples=100. Subsampling to 100 samples for SHAP value computation. To use all samples, set max_samples=614 when initializing the masker.\n",
            "/tmp/ipykernel_3047/857984987.py:26: FutureWarning: The NumPy global RNG was seeded by calling `np.random.seed`. In a future version this function will no longer use the global RNG. Pass `rng` explicitly to opt-in to the new behaviour and silence this warning.\n",
            "  shap.summary_plot(sv, X_test, show=False)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SHAP summary, Logistic Regression\n",
            "saved figure to ../outputs/figures/shap_summary_logistic_regression.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x470 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SHAP summary, Random Forest\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/tmp/ipykernel_3047/857984987.py:24: FutureWarning: The NumPy global RNG was seeded by calling `np.random.seed`. In a future version this function will no longer use the global RNG. Pass `rng` explicitly to opt-in to the new behaviour and silence this warning.\n",
            "  shap.summary_plot(sv[:, :, 1], X_test, show=False)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/shap_summary_random_forest.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x470 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SHAP summary, XGBoost\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/tmp/ipykernel_3047/857984987.py:26: FutureWarning: The NumPy global RNG was seeded by calling `np.random.seed`. In a future version this function will no longer use the global RNG. Pass `rng` explicitly to opt-in to the new behaviour and silence this warning.\n",
            "  shap.summary_plot(sv, X_test, show=False)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/shap_summary_xgboost.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x470 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "shap_explainers = {}\n",
        "shap_values_dict = {}\n",
        "\n",
        "tree_model_names = [\"Random Forest\", \"XGBoost\"]\n",
        "\n",
        "for name, model in models.items():\n",
        "    clf = model.named_steps[\"clf\"]\n",
        "\n",
        "    if name in tree_model_names:\n",
        "        # path-dependent perturbation, no background data needed, avoids additivity errors\n",
        "        explainer = shap.TreeExplainer(clf)\n",
        "        sv = explainer(X_test, check_additivity=False)\n",
        "    else:\n",
        "        # logistic regression, linear explainer needs a background sample\n",
        "        explainer = shap.Explainer(clf, X_train)\n",
        "        sv = explainer(X_test)\n",
        "\n",
        "    shap_explainers[name] = explainer\n",
        "    shap_values_dict[name] = sv\n",
        "\n",
        "    print(\"SHAP summary,\", name)\n",
        "    safe_name = name.lower().replace(\" \", \"_\")\n",
        "    if len(sv.shape) == 3:\n",
        "        shap.summary_plot(sv[:, :, 1], X_test, show=False)\n",
        "    else:\n",
        "        shap.summary_plot(sv, X_test, show=False)\n",
        "    save_fig(f\"shap_summary_{safe_name}.png\")\n",
        "    plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "id": "28379de9",
      "metadata": {
        "id": "28379de9",
        "outputId": "00297a1f-53d7-4d2b-8abd-7b521235aa72",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/shap_waterfall_single_patient.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x550 with 3 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# looking at one single patient from the test set, first row for XGBoost as an example\n",
        "sample_idx = 0\n",
        "\n",
        "sv_xgb = shap_values_dict[\"XGBoost\"]\n",
        "if len(sv_xgb.shape) == 3:\n",
        "    shap.plots.waterfall(sv_xgb[sample_idx, :, 1], show=False)\n",
        "else:\n",
        "    shap.plots.waterfall(sv_xgb[sample_idx], show=False)\n",
        "\n",
        "save_fig(\"shap_waterfall_single_patient.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "944c5dd9",
      "metadata": {
        "id": "944c5dd9"
      },
      "source": [
        "## 11. Decision Curve Analysis\n",
        "\n",
        "Checking whether these models would actually be useful in a clinical decision sense, not just\n",
        "statistically accurate. Net benefit across a range of threshold probabilities, following\n",
        "Piovani et al.'s explanation of the method (Chapter 2, Section 2.4 / Chapter 3, Section 3.6).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "id": "5849efe7",
      "metadata": {
        "id": "5849efe7",
        "outputId": "a32dce45-5795-48de-e5e0-a4174edc1a90",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 590
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/decision_curve_analysis.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "def net_benefit(y_true, y_prob, thresholds):\n",
        "    n = len(y_true)\n",
        "    benefits = []\n",
        "    for pt in thresholds:\n",
        "        pred_positive = (y_prob >= pt).astype(int)\n",
        "        tp = np.sum((pred_positive == 1) & (y_true == 1))\n",
        "        fp = np.sum((pred_positive == 1) & (y_true == 0))\n",
        "        nb = (tp / n) - (fp / n) * (pt / (1 - pt))\n",
        "        benefits.append(nb)\n",
        "    return np.array(benefits)\n",
        "\n",
        "\n",
        "thresholds = np.arange(0.01, 0.99, 0.01)\n",
        "y_test_arr = y_test.values\n",
        "\n",
        "plt.figure(figsize=(8, 6))\n",
        "\n",
        "for name, model in models.items():\n",
        "    y_prob = model.predict_proba(X_test)[:, 1]\n",
        "    nb = net_benefit(y_test_arr, y_prob, thresholds)\n",
        "    plt.plot(thresholds, nb, label=name)\n",
        "\n",
        "# treat all: everyone gets flagged as high risk\n",
        "treat_all_nb = []\n",
        "n = len(y_test_arr)\n",
        "event_rate = y_test_arr.mean()\n",
        "for pt in thresholds:\n",
        "    treat_all_nb.append(event_rate - (1 - event_rate) * (pt / (1 - pt)))\n",
        "plt.plot(thresholds, treat_all_nb, linestyle=\"--\", color=\"grey\", label=\"treat all\")\n",
        "\n",
        "# treat none: nobody gets flagged, net benefit is just flat zero\n",
        "plt.axhline(0, linestyle=\"--\", color=\"black\", label=\"treat none\")\n",
        "\n",
        "plt.xlabel(\"Threshold probability\")\n",
        "plt.ylabel(\"Net benefit\")\n",
        "plt.title(\"Decision Curve Analysis\")\n",
        "plt.legend()\n",
        "plt.ylim(-0.05, max(event_rate, 0.3))\n",
        "save_fig(\"decision_curve_analysis.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "69ed0a8a",
      "metadata": {
        "id": "69ed0a8a"
      },
      "source": [
        "## 12. Comparative Summary\n",
        "\n",
        "Pulling everything from Section 9 into one table and one chart, this is basically the\n",
        "centrepiece for Chapter 6.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "id": "d6948acb",
      "metadata": {
        "id": "d6948acb",
        "outputId": "1bf3cb0f-b7e8-469f-99f9-e0ec7551ef61",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     Accuracy      F1  AUC-ROC  Precision  Recall\n",
              "Model                                                            \n",
              "Logistic Regression    0.7143  0.6207   0.8098     0.5806  0.6667\n",
              "Random Forest          0.7078  0.6512   0.8196     0.5600  0.7778\n",
              "XGBoost                0.7338  0.6822   0.8172     0.5867  0.8148"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-07fd8b93-08f4-47f0-947b-a4440858247c\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Accuracy</th>\n",
              "      <th>F1</th>\n",
              "      <th>AUC-ROC</th>\n",
              "      <th>Precision</th>\n",
              "      <th>Recall</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Model</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Logistic Regression</th>\n",
              "      <td>0.7143</td>\n",
              "      <td>0.6207</td>\n",
              "      <td>0.8098</td>\n",
              "      <td>0.5806</td>\n",
              "      <td>0.6667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Random Forest</th>\n",
              "      <td>0.7078</td>\n",
              "      <td>0.6512</td>\n",
              "      <td>0.8196</td>\n",
              "      <td>0.5600</td>\n",
              "      <td>0.7778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XGBoost</th>\n",
              "      <td>0.7338</td>\n",
              "      <td>0.6822</td>\n",
              "      <td>0.8172</td>\n",
              "      <td>0.5867</td>\n",
              "      <td>0.8148</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-07fd8b93-08f4-47f0-947b-a4440858247c')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-07fd8b93-08f4-47f0-947b-a4440858247c button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-07fd8b93-08f4-47f0-947b-a4440858247c');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "  <div id=\"id_882670c8-1d06-4247-84af-71b0d450afdb\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('results_df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_882670c8-1d06-4247-84af-71b0d450afdb button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('results_df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "results_df",
              "summary": "{\n  \"name\": \"results_df\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"Model\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Logistic Regression\",\n          \"Random Forest\",\n          \"XGBoost\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Accuracy\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.013530828996529866,\n        \"min\": 0.7078,\n        \"max\": 0.7338,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.7143,\n          0.7078,\n          0.7338\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"F1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.030750338751521635,\n        \"min\": 0.6207,\n        \"max\": 0.6822,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.6207,\n          0.6512,\n          0.6822\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AUC-ROC\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.005108163401197497,\n        \"min\": 0.8098,\n        \"max\": 0.8196,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.8098,\n          0.8196,\n          0.8172\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precision\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.013990830330374696,\n        \"min\": 0.56,\n        \"max\": 0.5867,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.5806,\n          0.56,\n          0.5867\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Recall\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.07707768808157132,\n        \"min\": 0.6667,\n        \"max\": 0.8148,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.6667,\n          0.7778,\n          0.8148\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "results_df\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "id": "63378944",
      "metadata": {
        "id": "63378944",
        "outputId": "775563de-a070-475b-9454-f0f5b1fdf513",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 618
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/model_comparison_bar_chart.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "results_df.plot(kind=\"bar\", figsize=(10, 6), colormap=\"viridis\")\n",
        "plt.title(\"Model comparison across all metrics\")\n",
        "plt.ylabel(\"score\")\n",
        "plt.xticks(rotation=0)\n",
        "plt.ylim(0, 1)\n",
        "plt.legend(loc=\"lower right\")\n",
        "plt.tight_layout()\n",
        "save_fig(\"model_comparison_bar_chart.png\")\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "47520d64",
      "metadata": {
        "id": "47520d64"
      },
      "source": [
        "## 13. Model Comparison Plot\n",
        "\n",
        "A radar chart gives a different view of the same numbers from Section 12, sometimes easier to\n",
        "see the overall shape of a model's strengths and weaknesses at a glance.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "id": "a2829e13",
      "metadata": {
        "id": "a2829e13",
        "outputId": "d40a5c6b-8c12-472a-f9bb-980dbd1f29d1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 625
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved figure to ../outputs/figures/model_comparison_radar.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x700 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "from math import pi\n",
        "\n",
        "metrics = list(results_df.columns)\n",
        "num_metrics = len(metrics)\n",
        "\n",
        "angles = [n / float(num_metrics) * 2 * pi for n in range(num_metrics)]\n",
        "angles += angles[:1]\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(7, 7), subplot_kw=dict(polar=True))\n",
        "\n",
        "for model_name in results_df.index:\n",
        "    values = results_df.loc[model_name].tolist()\n",
        "    values += values[:1]\n",
        "    ax.plot(angles, values, label=model_name, linewidth=2)\n",
        "    ax.fill(angles, values, alpha=0.1)\n",
        "\n",
        "ax.set_xticks(angles[:-1])\n",
        "ax.set_xticklabels(metrics)\n",
        "ax.set_ylim(0, 1)\n",
        "ax.set_title(\"Model comparison, radar view\")\n",
        "ax.legend(loc=\"upper right\", bbox_to_anchor=(1.3, 1.1))\n",
        "plt.tight_layout()\n",
        "save_fig(\"model_comparison_radar.png\")\n",
        "plt.show()\n"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}