{
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    "colab": {
      "name": "Классификация, регрессия,метрики, sklearn.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fhuM1qQMF06-"
      },
      "source": [
        "# **План**\n",
        "\n",
        "- Работа с признаками. Предобработка данных на примере задачи классификации\n",
        "- Задача классификации\n",
        "    - Классификация данных методом k-ближайших соседей (KNeighborsClassifier)\n",
        "    - Метрики для задачи классификации: Accuracy, Confusion matrix, Precision, Recall, F1 score, AUC-ROC\n",
        "\n",
        "- Задача регресии\n",
        "    - Линейная регрессия (LinearRegression)\n",
        "    - Метрики для задачи регрессии: Mean Square Error, Mean Absolute Error, R2 score\n",
        "\n",
        "- Рекомендованная литература"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YgRtbc3yQktV"
      },
      "source": [
        "Ноутбук в колаб: https://drive.google.com/file/d/14niD6w38EU_6oc-4rSaePRkHNkKlBur7/view?usp=sharing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_yVN4GBVKeU0"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "from matplotlib import pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7jH_oYdPQRhD"
      },
      "source": [
        "-------\n",
        "<h1 align=\"center\"> Работа с признаками </h1> \n",
        "\n",
        "# Задача классификации. Предобработка данных\n",
        "скачайте данные с помощью pd.read_csv по ссылке https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data и уберите заголовок\n",
        "\n",
        "### **Постановка задачи:** \n",
        "Бинарная классификация зарплат (<= 50K, > 50K) по набору признаков, описывающих человека (семейный статус, наличие образования и тд)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "__piJEXrQNtC"
      },
      "source": [
        "# Считываем данные\n",
        "df = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data')\n",
        "\n",
        "# Назначаем имена колонок\n",
        "columns = ('age workclass fnlwgt education educ-num marital-status occupation relationship '\n",
        "           'race sex capital-gain capital-loss  hours-per-week native-country salary')\n",
        "\n",
        "df.columns = columns.split() #этот метод разделит датасет по колонкам как в массиве columns"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "haQlA6kW5VZs"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "id": "VahZn8PfQWNp",
        "outputId": "ab767944-4d10-445a-dc00-4b67459425f1"
      },
      "source": [
        "df.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>workclass</th>\n",
              "      <th>fnlwgt</th>\n",
              "      <th>education</th>\n",
              "      <th>educ-num</th>\n",
              "      <th>marital-status</th>\n",
              "      <th>occupation</th>\n",
              "      <th>relationship</th>\n",
              "      <th>race</th>\n",
              "      <th>sex</th>\n",
              "      <th>capital-gain</th>\n",
              "      <th>capital-loss</th>\n",
              "      <th>hours-per-week</th>\n",
              "      <th>native-country</th>\n",
              "      <th>salary</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>50</td>\n",
              "      <td>Self-emp-not-inc</td>\n",
              "      <td>83311</td>\n",
              "      <td>Bachelors</td>\n",
              "      <td>13</td>\n",
              "      <td>Married-civ-spouse</td>\n",
              "      <td>Exec-managerial</td>\n",
              "      <td>Husband</td>\n",
              "      <td>White</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>United-States</td>\n",
              "      <td>&lt;=50K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>38</td>\n",
              "      <td>Private</td>\n",
              "      <td>215646</td>\n",
              "      <td>HS-grad</td>\n",
              "      <td>9</td>\n",
              "      <td>Divorced</td>\n",
              "      <td>Handlers-cleaners</td>\n",
              "      <td>Not-in-family</td>\n",
              "      <td>White</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>United-States</td>\n",
              "      <td>&lt;=50K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>53</td>\n",
              "      <td>Private</td>\n",
              "      <td>234721</td>\n",
              "      <td>11th</td>\n",
              "      <td>7</td>\n",
              "      <td>Married-civ-spouse</td>\n",
              "      <td>Handlers-cleaners</td>\n",
              "      <td>Husband</td>\n",
              "      <td>Black</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>United-States</td>\n",
              "      <td>&lt;=50K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>28</td>\n",
              "      <td>Private</td>\n",
              "      <td>338409</td>\n",
              "      <td>Bachelors</td>\n",
              "      <td>13</td>\n",
              "      <td>Married-civ-spouse</td>\n",
              "      <td>Prof-specialty</td>\n",
              "      <td>Wife</td>\n",
              "      <td>Black</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>Cuba</td>\n",
              "      <td>&lt;=50K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>37</td>\n",
              "      <td>Private</td>\n",
              "      <td>284582</td>\n",
              "      <td>Masters</td>\n",
              "      <td>14</td>\n",
              "      <td>Married-civ-spouse</td>\n",
              "      <td>Exec-managerial</td>\n",
              "      <td>Wife</td>\n",
              "      <td>White</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>United-States</td>\n",
              "      <td>&lt;=50K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>49</td>\n",
              "      <td>Private</td>\n",
              "      <td>160187</td>\n",
              "      <td>9th</td>\n",
              "      <td>5</td>\n",
              "      <td>Married-spouse-absent</td>\n",
              "      <td>Other-service</td>\n",
              "      <td>Not-in-family</td>\n",
              "      <td>Black</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "      <td>Jamaica</td>\n",
              "      <td>&lt;=50K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>52</td>\n",
              "      <td>Self-emp-not-inc</td>\n",
              "      <td>209642</td>\n",
              "      <td>HS-grad</td>\n",
              "      <td>9</td>\n",
              "      <td>Married-civ-spouse</td>\n",
              "      <td>Exec-managerial</td>\n",
              "      <td>Husband</td>\n",
              "      <td>White</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>45</td>\n",
              "      <td>United-States</td>\n",
              "      <td>&gt;50K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>31</td>\n",
              "      <td>Private</td>\n",
              "      <td>45781</td>\n",
              "      <td>Masters</td>\n",
              "      <td>14</td>\n",
              "      <td>Never-married</td>\n",
              "      <td>Prof-specialty</td>\n",
              "      <td>Not-in-family</td>\n",
              "      <td>White</td>\n",
              "      <td>Female</td>\n",
              "      <td>14084</td>\n",
              "      <td>0</td>\n",
              "      <td>50</td>\n",
              "      <td>United-States</td>\n",
              "      <td>&gt;50K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>42</td>\n",
              "      <td>Private</td>\n",
              "      <td>159449</td>\n",
              "      <td>Bachelors</td>\n",
              "      <td>13</td>\n",
              "      <td>Married-civ-spouse</td>\n",
              "      <td>Exec-managerial</td>\n",
              "      <td>Husband</td>\n",
              "      <td>White</td>\n",
              "      <td>Male</td>\n",
              "      <td>5178</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>United-States</td>\n",
              "      <td>&gt;50K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>37</td>\n",
              "      <td>Private</td>\n",
              "      <td>280464</td>\n",
              "      <td>Some-college</td>\n",
              "      <td>10</td>\n",
              "      <td>Married-civ-spouse</td>\n",
              "      <td>Exec-managerial</td>\n",
              "      <td>Husband</td>\n",
              "      <td>Black</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>80</td>\n",
              "      <td>United-States</td>\n",
              "      <td>&gt;50K</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age          workclass  fnlwgt  ... hours-per-week  native-country  salary\n",
              "0   50   Self-emp-not-inc   83311  ...             13   United-States   <=50K\n",
              "1   38            Private  215646  ...             40   United-States   <=50K\n",
              "2   53            Private  234721  ...             40   United-States   <=50K\n",
              "3   28            Private  338409  ...             40            Cuba   <=50K\n",
              "4   37            Private  284582  ...             40   United-States   <=50K\n",
              "5   49            Private  160187  ...             16         Jamaica   <=50K\n",
              "6   52   Self-emp-not-inc  209642  ...             45   United-States    >50K\n",
              "7   31            Private   45781  ...             50   United-States    >50K\n",
              "8   42            Private  159449  ...             40   United-States    >50K\n",
              "9   37            Private  280464  ...             80   United-States    >50K\n",
              "\n",
              "[10 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_238K7-NQajf"
      },
      "source": [
        "### Перекодировка категориальных признаков"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AjrfOmclQcWM"
      },
      "source": [
        "Алгоритмы не могут работать с текстовыми данными без предварительной конвертации в числовой формат.\n",
        "\n",
        "Работа с категориальными признаками может быть устроена по разному.\n",
        "\n",
        "В этой задаче предлагается заменить все уникальные значения таких признаков некоторым числовым значением."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        },
        "id": "mutg-ibsQXch",
        "outputId": "5fa4f844-1af5-4c31-b85c-d640c4a47963"
      },
      "source": [
        "# Подключаем класс для предобработки данных\n",
        "from sklearn import preprocessing\n",
        "\n",
        "# Напишем функцию, которая принимает на вход DataFrame, кодирует числовыми значениями категориальные признаки\n",
        "# и возвращает обновленный DataFrame и сами кодировщики.\n",
        "def number_encode_features(init_df):\n",
        "    result = init_df.copy() # копируем нашу исходную таблицу\n",
        "    encoders = {}\n",
        "    for column in result.columns:\n",
        "        if result.dtypes[column] == np.object: # np.object -- строковый тип / если тип столбца - строка, то нужно его закодировать\n",
        "            encoders[column] = preprocessing.LabelEncoder() # для колонки column создаем кодировщик\n",
        "            result[column] = encoders[column].fit_transform(result[column]) # применяем кодировщик к столбцу и перезаписываем столбец\n",
        "    return result, encoders\n",
        "\n",
        "encoded_data, encoders = number_encode_features(df) # Теперь encoded data содержит закодированные кат. признаки \n",
        "encoded_data.head() "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    .dataframe thead th {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>workclass</th>\n",
              "      <th>fnlwgt</th>\n",
              "      <th>education</th>\n",
              "      <th>educ-num</th>\n",
              "      <th>marital-status</th>\n",
              "      <th>occupation</th>\n",
              "      <th>relationship</th>\n",
              "      <th>race</th>\n",
              "      <th>sex</th>\n",
              "      <th>capital-gain</th>\n",
              "      <th>capital-loss</th>\n",
              "      <th>hours-per-week</th>\n",
              "      <th>native-country</th>\n",
              "      <th>salary</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>50</td>\n",
              "      <td>6</td>\n",
              "      <td>83311</td>\n",
              "      <td>9</td>\n",
              "      <td>13</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>39</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>38</td>\n",
              "      <td>4</td>\n",
              "      <td>215646</td>\n",
              "      <td>11</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>39</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>53</td>\n",
              "      <td>4</td>\n",
              "      <td>234721</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>39</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>28</td>\n",
              "      <td>4</td>\n",
              "      <td>338409</td>\n",
              "      <td>9</td>\n",
              "      <td>13</td>\n",
              "      <td>2</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>37</td>\n",
              "      <td>4</td>\n",
              "      <td>284582</td>\n",
              "      <td>12</td>\n",
              "      <td>14</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>39</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  workclass  fnlwgt  ...  hours-per-week  native-country  salary\n",
              "0   50          6   83311  ...              13              39       0\n",
              "1   38          4  215646  ...              40              39       0\n",
              "2   53          4  234721  ...              40              39       0\n",
              "3   28          4  338409  ...              40               5       0\n",
              "4   37          4  284582  ...              40              39       0\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JAdDXdw5QdKg",
        "outputId": "8ed1694b-4198-4083-875b-a9b19ff421a4"
      },
      "source": [
        "# отображаем его\n",
        "encoders"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'education': LabelEncoder(),\n",
              " 'marital-status': LabelEncoder(),\n",
              " 'native-country': LabelEncoder(),\n",
              " 'occupation': LabelEncoder(),\n",
              " 'race': LabelEncoder(),\n",
              " 'relationship': LabelEncoder(),\n",
              " 'salary': LabelEncoder(),\n",
              " 'sex': LabelEncoder(),\n",
              " 'workclass': LabelEncoder()}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lNFAnx3TQgpa"
      },
      "source": [
        "Посмотрим, во что переведены категориальные признаки"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "Apo1SEtFQnpC",
        "outputId": "c6acb393-b0f5-4b99-c367-0fb789e2be1e"
      },
      "source": [
        "df.groupby('race').count()[['age']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>age</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>race</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Amer-Indian-Eskimo</th>\n",
              "      <td>311</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Asian-Pac-Islander</th>\n",
              "      <td>1039</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Black</th>\n",
              "      <td>3124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other</th>\n",
              "      <td>271</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>White</th>\n",
              "      <td>27815</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                       age\n",
              "race                      \n",
              " Amer-Indian-Eskimo    311\n",
              " Asian-Pac-Islander   1039\n",
              " Black                3124\n",
              " Other                 271\n",
              " White               27815"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "nSqo5f-EQfCH",
        "outputId": "4a04e356-52ed-4dd8-b3f5-44b210040f6e"
      },
      "source": [
        "encoded_data.groupby('race').count()[['age']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>age</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>race</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>311</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1039</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>271</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>27815</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        age\n",
              "race       \n",
              "0       311\n",
              "1      1039\n",
              "2      3124\n",
              "3       271\n",
              "4     27815"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JT6c_vE7Z2U4",
        "outputId": "2cf0155c-9d46-4878-ef9f-319dabc7cafd"
      },
      "source": [
        "encoders['race'].transform([' Black'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "id": "VgL-Y05QQkSH",
        "outputId": "51d62016-9feb-4e7b-b8a8-666a53ecffa1"
      },
      "source": [
        "df.groupby('workclass').count()[['age']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>age</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>workclass</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>?</th>\n",
              "      <td>1836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Federal-gov</th>\n",
              "      <td>960</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Local-gov</th>\n",
              "      <td>2093</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Never-worked</th>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Private</th>\n",
              "      <td>22696</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Self-emp-inc</th>\n",
              "      <td>1116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Self-emp-not-inc</th>\n",
              "      <td>2541</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>State-gov</th>\n",
              "      <td>1297</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Without-pay</th>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     age\n",
              "workclass               \n",
              " ?                  1836\n",
              " Federal-gov         960\n",
              " Local-gov          2093\n",
              " Never-worked          7\n",
              " Private           22696\n",
              " Self-emp-inc       1116\n",
              " Self-emp-not-inc   2541\n",
              " State-gov          1297\n",
              " Without-pay          14"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "id": "u0jtHOlxQsf-",
        "outputId": "c2f0224d-9ccd-4ed9-fa36-605c201d56a8"
      },
      "source": [
        "encoded_data.groupby('workclass').count()[['age']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>age</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>workclass</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>960</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2093</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>22696</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2541</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1297</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             age\n",
              "workclass       \n",
              "0           1836\n",
              "1            960\n",
              "2           2093\n",
              "3              7\n",
              "4          22696\n",
              "5           1116\n",
              "6           2541\n",
              "7           1297\n",
              "8             14"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "87Np8RrmQvdw"
      },
      "source": [
        "### Гистограммы значений\n",
        "постройте графики гистограмм зависимости различных признаков для того, чтоб оценить корректность данных"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 606
        },
        "id": "jD5cJdM-SC3f",
        "outputId": "9a610b6a-db06-411f-a95e-93aa7924f769"
      },
      "source": [
        "encoded_data.hist(figsize = (16,10), xlabelsize = 8, ylabelsize = 8)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x720 with 16 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "yfpcG71ZQteO",
        "outputId": "80faec19-e5e4-4e53-cab8-d7d96ca823eb"
      },
      "source": [
        "fig = plt.figure(figsize=(16,8))\n",
        "cols = 5\n",
        "\n",
        "rows = np.ceil(float(encoded_data.shape[1]) / cols)\n",
        "for i, column in enumerate(encoded_data.columns):\n",
        "    ax = fig.add_subplot(rows, cols, i + 1)\n",
        "    ax.set_title(column)\n",
        "    encoded_data[column].hist(axes=ax, xlabelsize = 8, ylabelsize = 8)\n",
        "    plt.xticks(rotation=\"vertical\")\n",
        "plt.subplots_adjust(hspace=0.7, wspace=0.2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x576 with 15 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Io6-e916Qy__"
      },
      "source": [
        "### Матрица корреляций\n",
        "\n",
        "По тепловой карте можно посмотреть на зависимости между признаками, а также на зависимости между целевой переменной и признаками. \n",
        "\n",
        "Значение близкое к нулю не обязательно означает отсутствие зависимости! \n",
        "\n",
        "**Вопрос:** Почему так?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 614
        },
        "id": "NoN4SYkJRdB0",
        "outputId": "7e58df7d-5a5f-465c-a53e-33db60c548a5"
      },
      "source": [
        "# тоже крутой модуль, для различной визуализации данных\n",
        "import seaborn as sns\n",
        "\n",
        "plt.subplots(figsize=(10,10))\n",
        "encoded_data, encoders = number_encode_features(df)\n",
        "sns.heatmap(encoded_data.corr(), square=True)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "idIpWuPzRh48"
      },
      "source": [
        "В данном датасете пропущенные значения обозначены как \" ?\".  Удалим из выборки все объекты с пропусками."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VzRj4TIeTRiX",
        "outputId": "802624c7-98fb-40f8-eda9-cdddc057e10b"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 32560 entries, 0 to 32559\n",
            "Data columns (total 15 columns):\n",
            " #   Column          Non-Null Count  Dtype \n",
            "---  ------          --------------  ----- \n",
            " 0   age             32560 non-null  int64 \n",
            " 1   workclass       32560 non-null  object\n",
            " 2   fnlwgt          32560 non-null  int64 \n",
            " 3   education       32560 non-null  object\n",
            " 4   educ-num        32560 non-null  int64 \n",
            " 5   marital-status  32560 non-null  object\n",
            " 6   occupation      32560 non-null  object\n",
            " 7   relationship    32560 non-null  object\n",
            " 8   race            32560 non-null  object\n",
            " 9   sex             32560 non-null  object\n",
            " 10  capital-gain    32560 non-null  int64 \n",
            " 11  capital-loss    32560 non-null  int64 \n",
            " 12  hours-per-week  32560 non-null  int64 \n",
            " 13  native-country  32560 non-null  object\n",
            " 14  salary          32560 non-null  object\n",
            "dtypes: int64(6), object(9)\n",
            "memory usage: 3.7+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UQ9MQNRcRg6b",
        "outputId": "d7dbbc8f-8b55-451d-dac9-9a5375c50077"
      },
      "source": [
        "# удалим все объекты, в которых содержатся пропуски\n",
        "df = df.dropna()\n",
        "df.count()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age               32560\n",
              "workclass         32560\n",
              "fnlwgt            32560\n",
              "education         32560\n",
              "educ-num          32560\n",
              "marital-status    32560\n",
              "occupation        32560\n",
              "relationship      32560\n",
              "race              32560\n",
              "sex               32560\n",
              "capital-gain      32560\n",
              "capital-loss      32560\n",
              "hours-per-week    32560\n",
              "native-country    32560\n",
              "salary            32560\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "id": "aGU4eZGFRwLQ",
        "outputId": "be725523-2e2a-4d17-d050-8920c34ffb8e"
      },
      "source": [
        "df.groupby('salary').count()[['age']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>age</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>salary</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>&lt;=50K</th>\n",
              "      <td>24719</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>&gt;50K</th>\n",
              "      <td>7841</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          age\n",
              "salary       \n",
              " <=50K  24719\n",
              " >50K    7841"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_E2UyHKZPDC4"
      },
      "source": [
        "Будем предсказывать salary (> или < 50к в год - бинарная классификация)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IK-wtiHDR4Gt"
      },
      "source": [
        "X = encoded_data.drop('salary', axis =1) #np.array(df_prc[df._get_numeric_data().columns])\n",
        "# y = np.array(df_prc['salary'], dtype='int')\n",
        "y = encoders['salary'].transform(df['salary']) # применяем наши кодировщики к категориальным фичам"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "bmNPexN0SAsU",
        "outputId": "3573030b-8a75-467a-cd17-91f54f6d25f2"
      },
      "source": [
        "X"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>workclass</th>\n",
              "      <th>fnlwgt</th>\n",
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              "      <td>39</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    </tr>\n",
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              "      <th>...</th>\n",
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              "      <td>...</td>\n",
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              "      <td>27</td>\n",
              "      <td>4</td>\n",
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              "      <td>7</td>\n",
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              "      <td>2</td>\n",
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              "      <td>40</td>\n",
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              "      <td>11</td>\n",
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              "      <td>4</td>\n",
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              "      <td>52</td>\n",
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              "      <td>0</td>\n",
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              "</table>\n",
              "<p>32560 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       age  workclass  fnlwgt  ...  capital-loss  hours-per-week  native-country\n",
              "0       50          6   83311  ...             0              13              39\n",
              "1       38          4  215646  ...             0              40              39\n",
              "2       53          4  234721  ...             0              40              39\n",
              "3       28          4  338409  ...             0              40               5\n",
              "4       37          4  284582  ...             0              40              39\n",
              "...    ...        ...     ...  ...           ...             ...             ...\n",
              "32555   27          4  257302  ...             0              38              39\n",
              "32556   40          4  154374  ...             0              40              39\n",
              "32557   58          4  151910  ...             0              40              39\n",
              "32558   22          4  201490  ...             0              20              39\n",
              "32559   52          5  287927  ...             0              40              39\n",
              "\n",
              "[32560 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2jsC7fytSCID",
        "outputId": "4cb4b81f-f5e6-4929-a1d9-0bafba03ab56"
      },
      "source": [
        "y"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 0, 0, ..., 0, 0, 1])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Hk5mil8rQ2Ej"
      },
      "source": [
        "------------------------------\n",
        "## Масштабирование признаков\n",
        "\n",
        "В качестве классификатора используем kNN, признаки: число соседей (*n_neighbors*) и метрика (*metrics*).\n",
        "\n",
        "Подберём оптимальные значения указанных гиперпараметров"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OgCz9pjaRBgO"
      },
      "source": [
        "# Будем использовать модель k ближайших соседей, которую проходили на 5 занятии\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "\n",
        "knn = KNeighborsClassifier()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Sn52WuITPi7Z"
      },
      "source": [
        "Для получения более точной оценки нашего алгоритма будем использовать [кросс-валидацию](https://neerc.ifmo.ru/wiki/index.php?title=%D0%9A%D1%80%D0%BE%D1%81%D1%81-%D0%B2%D0%B0%D0%BB%D0%B8%D0%B4%D0%B0%D1%86%D0%B8%D1%8F)\n",
        "\n",
        "Результаты тестов на каждом проходе (fold) усредним"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eKEFZ1-nf6q1"
      },
      "source": [
        "![alt text](http://scott.fortmann-roe.com/docs/docs/MeasuringError/crossvalidation.png)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rNA7Z6YeRG4X"
      },
      "source": [
        "### Подбор параметра n_neighbors для KNeighborsClassifier\n",
        "\n",
        "У алгоритма knn есть один гиперпараметр (то значение, которое мы выставляем руками) -- число соседей на основе которых алгоритм принимает решение.\n",
        "\n",
        "Как обсуждалось на лекции, подбор подобных параметров можно осуществлять на основе специальной отложенной (тестовой) выборки, а можно с помощью кросс-валидации. (Вспомните, какие плюсы и минусы имеет каждый из подходов)\n",
        "\n",
        "В данной задаче мы будем использовать кросс-валидацию на 5 фолдах."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xvLDxyjYtI_Z",
        "outputId": "98437f86-480c-4899-f97e-62578beb950f"
      },
      "source": [
        "np.array(np.linspace(1, 100, 10), dtype='int')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([  1,  12,  23,  34,  45,  56,  67,  78,  89, 100])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V0cD7zlBRDIe",
        "outputId": "7b1b1460-ddac-4390-f48b-ff7cb1b71e5c"
      },
      "source": [
        "# В sklearn есть специальный модуль для работы с кросс-валидацией\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "\n",
        "# Зададим сетку - среди каких значений выбирать наилучший параметр.\n",
        "knn_grid = {'n_neighbors': np.array(np.linspace(25, 35, 10), dtype='int')} #,\n",
        "            # 'metric': ['EuclideanDistance', 'ManhattanDistance']} # перебираем по параметру <<n_neighbors>>, по сетке заданной np.linspace(2, 100, 10)\n",
        "\n",
        "# Создаем объект кросс-валидации\n",
        "gs = GridSearchCV(knn, knn_grid, cv=3)\n",
        "\n",
        "# Обучаем его\n",
        "gs.fit(X, y)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "GridSearchCV(cv=3, error_score=nan,\n",
              "             estimator=KNeighborsClassifier(algorithm='auto', leaf_size=30,\n",
              "                                            metric='minkowski',\n",
              "                                            metric_params=None, n_jobs=None,\n",
              "                                            n_neighbors=5, p=2,\n",
              "                                            weights='uniform'),\n",
              "             iid='deprecated', n_jobs=None,\n",
              "             param_grid={'n_neighbors': array([25, 26, 27, 28, 29, 30, 31, 32, 33, 35])},\n",
              "             pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n",
              "             scoring=None, verbose=0)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zhuBGll9Srmd"
      },
      "source": [
        "# Функция отрисовки графиков\n",
        "\n",
        "def grid_plot(x, y, x_label, title, y_label='cross_val'):\n",
        "    plt.figure(figsize=(12, 6))\n",
        "    plt.grid(True)\n",
        "    plt.plot(x, y, 'go-')\n",
        "    plt.xlabel(x_label)\n",
        "    plt.ylabel(y_label)\n",
        "    plt.title(title)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 405
        },
        "id": "ZdIeyOPHRMrk",
        "outputId": "9ef3dc74-5f35-4640-aa3b-146acb5c3742"
      },
      "source": [
        "# Строим график зависимости качества от числа соседей\n",
        "# замечание: результаты обучения хранятся в атрибуте cv_results_ объекта gs\n",
        "\n",
        "grid_plot(knn_grid['n_neighbors'], gs.cv_results_['mean_test_score'], 'n_neighbors', 'KNeighborsClassifier')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HZSY1owASYUB",
        "outputId": "453b4367-b1b3-4412-88bf-13d040ae2d49"
      },
      "source": [
        "# по аналогии поменяем количество точек для проверки разных значений параметра k - 11 точек в диапазоне от 15 до 35 (равные промежутки, int)\n",
        "knn_grid = {'n_neighbors': np.array(np.linspace(15, 35, 11), dtype='int')}\n",
        "gs = GridSearchCV(knn, knn_grid, cv=5)\n",
        "gs.fit(X, y)\n",
        "\n",
        "# best_params_ содержит в себе лучшие подобранные параметры, best_score_ лучшее качество\n",
        "gs.best_params_, gs.best_score_"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "({'n_neighbors': 29}, 0.7987407862407864)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 405
        },
        "id": "g-OjCUIfSZso",
        "outputId": "efe08ed3-7591-4f77-b8fb-a1705c1ebcd7"
      },
      "source": [
        "# отобразим результат по аналогии\n",
        "grid_plot(knn_grid['n_neighbors'], gs.cv_results_['mean_test_score'], 'n_neighbors', 'KNeighborsClassifier')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VT8jdo4OdM5z"
      },
      "source": [
        "Масштабирование признаков можно выполнить, например, одним из следующих способов способами:\n",
        " - $x_{new} = \\dfrac{x - \\mu}{\\sigma}$, где $\\mu, \\sigma$ — среднее и стандартное отклонение значения признака по всей выборке (см. функцию [scale](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html))\n",
        " - $x_{new} = \\dfrac{x - x_{min}}{x_{max} - x_{min}}$, где $[x_{min}, x_{max}]$ — минимальный интервал значений признака"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "x1hv-UR70Ql8",
        "outputId": "7274d9b3-3e16-47d9-c4cf-e7d147c4b35b"
      },
      "source": [
        "(X - X.mean(axis=0))/X.std(axis=0)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>age</th>\n",
              "      <th>workclass</th>\n",
              "      <th>fnlwgt</th>\n",
              "      <th>education</th>\n",
              "      <th>educ-num</th>\n",
              "      <th>marital-status</th>\n",
              "      <th>occupation</th>\n",
              "      <th>relationship</th>\n",
              "      <th>race</th>\n",
              "      <th>sex</th>\n",
              "      <th>capital-gain</th>\n",
              "      <th>capital-loss</th>\n",
              "      <th>hours-per-week</th>\n",
              "      <th>native-country</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.837084</td>\n",
              "      <td>1.463861</td>\n",
              "      <td>-1.008726</td>\n",
              "      <td>-0.335438</td>\n",
              "      <td>1.134761</td>\n",
              "      <td>-0.406177</td>\n",
              "      <td>-0.608425</td>\n",
              "      <td>-0.900163</td>\n",
              "      <td>0.393668</td>\n",
              "      <td>0.703077</td>\n",
              "      <td>-0.145911</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-2.222086</td>\n",
              "      <td>0.291569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-0.042640</td>\n",
              "      <td>0.090120</td>\n",
              "      <td>0.245043</td>\n",
              "      <td>0.181316</td>\n",
              "      <td>-0.420020</td>\n",
              "      <td>-1.733999</td>\n",
              "      <td>-0.135478</td>\n",
              "      <td>-0.277805</td>\n",
              "      <td>0.393668</td>\n",
              "      <td>0.703077</td>\n",
              "      <td>-0.145911</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-0.035429</td>\n",
              "      <td>0.291569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.057015</td>\n",
              "      <td>0.090120</td>\n",
              "      <td>0.425763</td>\n",
              "      <td>-2.402452</td>\n",
              "      <td>-1.197411</td>\n",
              "      <td>-0.406177</td>\n",
              "      <td>-0.135478</td>\n",
              "      <td>-0.900163</td>\n",
              "      <td>-1.962553</td>\n",
              "      <td>0.703077</td>\n",
              "      <td>-0.145911</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-0.035429</td>\n",
              "      <td>0.291569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.775743</td>\n",
              "      <td>0.090120</td>\n",
              "      <td>1.408124</td>\n",
              "      <td>-0.335438</td>\n",
              "      <td>1.134761</td>\n",
              "      <td>-0.406177</td>\n",
              "      <td>0.810415</td>\n",
              "      <td>2.211624</td>\n",
              "      <td>-1.962553</td>\n",
              "      <td>-1.422276</td>\n",
              "      <td>-0.145911</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-0.035429</td>\n",
              "      <td>-4.054094</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.115950</td>\n",
              "      <td>0.090120</td>\n",
              "      <td>0.898156</td>\n",
              "      <td>0.439693</td>\n",
              "      <td>1.523457</td>\n",
              "      <td>-0.406177</td>\n",
              "      <td>-0.608425</td>\n",
              "      <td>2.211624</td>\n",
              "      <td>0.393668</td>\n",
              "      <td>-1.422276</td>\n",
              "      <td>-0.145911</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-0.035429</td>\n",
              "      <td>0.291569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32555</th>\n",
              "      <td>-0.849053</td>\n",
              "      <td>0.090120</td>\n",
              "      <td>0.639700</td>\n",
              "      <td>-0.852191</td>\n",
              "      <td>0.746066</td>\n",
              "      <td>-0.406177</td>\n",
              "      <td>1.519834</td>\n",
              "      <td>2.211624</td>\n",
              "      <td>0.393668</td>\n",
              "      <td>-1.422276</td>\n",
              "      <td>-0.145911</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-0.197404</td>\n",
              "      <td>0.291569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32556</th>\n",
              "      <td>0.103981</td>\n",
              "      <td>0.090120</td>\n",
              "      <td>-0.335461</td>\n",
              "      <td>0.181316</td>\n",
              "      <td>-0.420020</td>\n",
              "      <td>-0.406177</td>\n",
              "      <td>0.100995</td>\n",
              "      <td>-0.900163</td>\n",
              "      <td>0.393668</td>\n",
              "      <td>0.703077</td>\n",
              "      <td>-0.145911</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-0.035429</td>\n",
              "      <td>0.291569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32557</th>\n",
              "      <td>1.423567</td>\n",
              "      <td>0.090120</td>\n",
              "      <td>-0.358805</td>\n",
              "      <td>0.181316</td>\n",
              "      <td>-0.420020</td>\n",
              "      <td>2.249469</td>\n",
              "      <td>-1.317844</td>\n",
              "      <td>1.589267</td>\n",
              "      <td>0.393668</td>\n",
              "      <td>-1.422276</td>\n",
              "      <td>-0.145911</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-0.035429</td>\n",
              "      <td>0.291569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32558</th>\n",
              "      <td>-1.215605</td>\n",
              "      <td>0.090120</td>\n",
              "      <td>0.110926</td>\n",
              "      <td>0.181316</td>\n",
              "      <td>-0.420020</td>\n",
              "      <td>0.921646</td>\n",
              "      <td>-1.317844</td>\n",
              "      <td>0.966909</td>\n",
              "      <td>0.393668</td>\n",
              "      <td>0.703077</td>\n",
              "      <td>-0.145911</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-1.655175</td>\n",
              "      <td>0.291569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32559</th>\n",
              "      <td>0.983705</td>\n",
              "      <td>0.776991</td>\n",
              "      <td>0.929848</td>\n",
              "      <td>0.181316</td>\n",
              "      <td>-0.420020</td>\n",
              "      <td>-0.406177</td>\n",
              "      <td>-0.608425</td>\n",
              "      <td>2.211624</td>\n",
              "      <td>0.393668</td>\n",
              "      <td>-1.422276</td>\n",
              "      <td>1.888372</td>\n",
              "      <td>-0.21666</td>\n",
              "      <td>-0.035429</td>\n",
              "      <td>0.291569</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>32560 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            age  workclass  ...  hours-per-week  native-country\n",
              "0      0.837084   1.463861  ...       -2.222086        0.291569\n",
              "1     -0.042640   0.090120  ...       -0.035429        0.291569\n",
              "2      1.057015   0.090120  ...       -0.035429        0.291569\n",
              "3     -0.775743   0.090120  ...       -0.035429       -4.054094\n",
              "4     -0.115950   0.090120  ...       -0.035429        0.291569\n",
              "...         ...        ...  ...             ...             ...\n",
              "32555 -0.849053   0.090120  ...       -0.197404        0.291569\n",
              "32556  0.103981   0.090120  ...       -0.035429        0.291569\n",
              "32557  1.423567   0.090120  ...       -0.035429        0.291569\n",
              "32558 -1.215605   0.090120  ...       -1.655175        0.291569\n",
              "32559  0.983705   0.776991  ...       -0.035429        0.291569\n",
              "\n",
              "[32560 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U79vg1IFSjw_"
      },
      "source": [
        "from sklearn.preprocessing import scale\n",
        "X_scaled = scale(np.array(X, dtype='float'), with_std=True, with_mean=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z_rgz-2odO_k",
        "outputId": "0a9c3333-3024-40ff-fc86-f56d731a21f5"
      },
      "source": [
        "X_scaled"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0.83709708, -1.0087417 ,  1.13477863, -0.14591373, -0.21666301,\n",
              "        -2.22212013],\n",
              "       [-0.04264043,  0.24504633, -0.42002663, -0.14591373, -0.21666301,\n",
              "        -0.03542999],\n",
              "       [ 1.05703146,  0.42576955, -1.19742926, -0.14591373, -0.21666301,\n",
              "        -0.03542999],\n",
              "       ...,\n",
              "       [ 1.42358875, -0.3588108 , -0.42002663, -0.14591373, -0.21666301,\n",
              "        -0.03542999],\n",
              "       [-1.21562378,  0.11092744, -0.42002663, -0.14591373, -0.21666301,\n",
              "        -1.65520046],\n",
              "       [ 0.98372   ,  0.92986178, -0.42002663,  1.88840054, -0.21666301,\n",
              "        -0.03542999]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_g6Z8fqEdSth"
      },
      "source": [
        "### Подборка параметра n_neighbors для KNeighborsClassifier при нормированных признаках\n",
        "\n",
        "зачем нормализовывать?\n",
        "см. [пункт нормализация](https://ru.wikipedia.org/wiki/%D0%9C%D0%B5%D1%82%D0%BE%D0%B4_k-%D0%B1%D0%BB%D0%B8%D0%B6%D0%B0%D0%B9%D1%88%D0%B8%D1%85_%D1%81%D0%BE%D1%81%D0%B5%D0%B4%D0%B5%D0%B9)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 422
        },
        "id": "6cxfY36CdR3f",
        "outputId": "c6fd7518-0c00-46f5-b774-a7ca4766f6f7"
      },
      "source": [
        "# обучение идентично предыдущим, но в этот раз нормированные значения\n",
        "grid = {'n_neighbors': np.array(np.linspace(1, 100, 10), dtype='int')}\n",
        "gs = GridSearchCV(knn, grid, cv=3)\n",
        "gs.fit(X_scaled, y)\n",
        "\n",
        "print(gs.best_params_, gs.best_score_)\n",
        "\n",
        "grid_plot(grid['n_neighbors'],\n",
        "          gs.cv_results_['mean_test_score'],\n",
        "          'n_neighbors', 'KNeighborsClassifier')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "{'n_neighbors': 23} 0.8367323279087747\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zGS60ArSMt9X"
      },
      "source": [
        "<h1 align=\"center\"> Метрики </h1> \n",
        "\n",
        "# Метрики для задачи классификации\n",
        "\n",
        "[ВАЖНО](https://habr.com/ru/company/ods/blog/328372/) прочесть\n",
        "\n",
        "### Accuracy\n",
        "\n",
        "Не подходит для несбалансированных классов. \n",
        "\n",
        "Пускай имеем задачу кредитного скоринга: 100 людей, 10 из них ненадежные заемщики и выдача кредита им принесет убытки. Accuracy будет 90/100 = 90%"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ANl-xyzHduFe"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "X_train, X_test, y_tain, y_test = train_test_split(X, y, test_size=0.33, random_state=42)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1wUDjANEM4Hr"
      },
      "source": [
        "### Используем 2 классификаторва \n",
        "- умный kNN\n",
        "- глупый -- DummyClassifier (самый популярный класс)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fHhcaUY3M2u0"
      },
      "source": [
        "from sklearn import dummy\n",
        "\n",
        "# импортируем и создаем knn классификатор по аналогии\n",
        "knn = KNeighborsClassifier(n_neighbors=59) \n",
        "# тренируем для knn и для dummy\n",
        "clf_knn = knn.fit(X_train, y_tain)\n",
        "clf_mp = dummy.DummyClassifier(\"most_frequent\").fit(X_train, y_tain)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qvFlph2oM5lv"
      },
      "source": [
        "# получаем от них предикты\n",
        "y_knn = clf_knn.predict(X_test)\n",
        "y_mp = clf_mp.predict(X_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mkCJI1bGM6WD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6d2e02a2-9f33-4ded-8ab9-46000d2c029c"
      },
      "source": [
        "# ответы knn\n",
        "y_knn"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 0, 0, ..., 0, 1, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9t24QE0IM7h7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a5025438-f83e-45b9-b8ae-9202ef3d231c"
      },
      "source": [
        "# реальные ответы\n",
        "y_test"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 0, 1, ..., 0, 1, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t_N79MarNUms"
      },
      "source": [
        "### Accuracy\n",
        "\n",
        "$$Accuracy = \\frac{\\sum_{x_i, y_i \\in (X, Y)} I(y(x_i) = y_i)}{|(X, Y)|} = \\frac{num~right~classified~obj}{num~all~obj}$$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Uhh9mVV-RDUF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "df75a389-9099-4cb2-a977-8e5e4e2f29c2"
      },
      "source": [
        "from sklearn import metrics\n",
        "\n",
        "print ('knn =', metrics.accuracy_score(y_test, y_knn), 'mp =', metrics.accuracy_score(y_test, y_mp))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "knn = 0.7891112145183806 mp = 0.7553280595625872\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vsWJYqnVREVd"
      },
      "source": [
        "### Conf-matrix"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aZg8f5lVNTbz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 559
        },
        "outputId": "57dbbffe-fe93-426a-fe92-0e33b13d59d9"
      },
      "source": [
        "import matplotlib\n",
        "import seaborn as sns\n",
        "# нужно получить кол-во правильных и неправильых предсказаний по каждому классу от knn\n",
        "# см. https://habr.com/ru/company/ods/blog/328372/\n",
        "\n",
        "fig = plt.figure(figsize=(8,8))\n",
        "nn_mtx = metrics.confusion_matrix(y_test, y_knn)\n",
        "print(nn_mtx)\n",
        "\n",
        "# font = {'weight' : 'bold', 'size'   :22}\n",
        "# matplotlib.rc('font', **font)\n",
        "\n",
        "matplotlib.rc('xtick', labelsize=20) \n",
        "matplotlib.rc('ytick', labelsize=20) \n",
        "sns.heatmap(nn_mtx, annot=True, fmt=\"d\", \n",
        "            xticklabels=encoders[\"salary\"].classes_, \n",
        "            yticklabels=encoders[\"salary\"].classes_)\n",
        "plt.ylabel(\"Real value\")\n",
        "plt.xlabel(\"Predicted value\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[8099   17]\n",
            " [2249  380]]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 42.0, 'Predicted value')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3lIHHrUjNalR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 602
        },
        "outputId": "2068a6c6-0692-4e25-c171-bd592f15d3fa"
      },
      "source": [
        "# по аналогии от dummy\n",
        "\n",
        "mp_mtx = metrics.confusion_matrix(y_test, y_mp)\n",
        "print(mp_mtx)\n",
        "font = {'family' : 'Calibri', 'weight' : 'bold', 'size'   :22}\n",
        "matplotlib.rc('font', **font)\n",
        "fig = plt.figure(figsize=(10,8))\n",
        "sns.heatmap(mp_mtx, annot=True, fmt=\"d\", \n",
        "            xticklabels=encoders[\"salary\"].classes_, \n",
        "            yticklabels=encoders[\"salary\"].classes_)\n",
        "plt.ylabel(\"Real value\")\n",
        "plt.xlabel(\"Predicted value\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "findfont: Font family ['Calibri'] not found. Falling back to DejaVu Sans.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "[[8116    0]\n",
            " [2629    0]]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 42.0, 'Predicted value')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        },
        {
          "output_type": "stream",
          "text": [
            "findfont: Font family ['Calibri'] not found. Falling back to DejaVu Sans.\n",
            "findfont: Font family ['Calibri'] not found. Falling back to DejaVu Sans.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6hdYpHU1wzAj"
      },
      "source": [
        "визуализация precision и recall"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "esVeBRdqwmhq"
      },
      "source": [
        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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pgzw7cC9NiPC"
      },
      "source": [
        "## Precision\n",
        "\n",
        "$$Precision = \\frac{TP}{TP + FP}$$\n",
        "\n",
        "precision демонстрирует способность отличать этот класс от других классов"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6KT0UAHaNeSa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "213c2e9a-56c1-419e-f879-a78a147a7ffc"
      },
      "source": [
        "print ('knn =', metrics.precision_score(y_test, y_knn),\n",
        "       'mp =', metrics.precision_score(y_test, y_mp))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "knn = 0.9571788413098237 mp = 0.0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "  _warn_prf(average, modifier, msg_start, len(result))\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KYiZyVpONpwI"
      },
      "source": [
        "## Recall\n",
        "\n",
        "$$Recall = \\frac{TP}{TP + FN}$$\n",
        "\n",
        "Recall демонстрирует способность алгоритма обнаруживать данный класс вообще"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VMDmHhuTNvQe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "79ce8969-aa55-4423-d4a8-dca92b0ea5d8"
      },
      "source": [
        "print ('knn =', metrics.recall_score(y_test, y_knn),\n",
        "       'mp =', metrics.recall_score(y_test, y_mp))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "knn = 0.14454165081780146 mp = 0.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GtGyp_QYxZru",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0c35fbd3-ef36-4e58-b3ad-7f431331fce9"
      },
      "source": [
        "print(metrics.classification_report(y_test, y_knn))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.78      1.00      0.88      8116\n",
            "           1       0.96      0.14      0.25      2629\n",
            "\n",
            "    accuracy                           0.79     10745\n",
            "   macro avg       0.87      0.57      0.56     10745\n",
            "weighted avg       0.83      0.79      0.72     10745\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FTaGB36_NtCX"
      },
      "source": [
        "## F1\n",
        "\n",
        "$$F1 = 2 \\cdot \\frac{Precision \\cdot Recall}{Precision + Recall}$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yDanuPXEN5ZB"
      },
      "source": [
        "* Как взвесить Precision и Recall?\n",
        "    - Среднее арифметичиское плохо: (p=0.5, r=0.5) должно быть лучше чем (p=1, r=0), \n",
        "    - Лучше минимум, но при равной точности должен побеждать классфикатор с большей полнотой\n",
        "    - Гармоничиское среднее, сглаженный минимум"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "apOgrH7RNnH4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ef80fb8b-b6ba-4b75-e896-2dc26aabf39f"
      },
      "source": [
        "print ('knn =', metrics.f1_score(y_test, y_knn),\n",
        "       'mp =', metrics.f1_score(y_test, y_mp))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "knn = 0.25115664243225383 mp = 0.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yCADUWPtOJeg"
      },
      "source": [
        "## <span style=\"color:orange\"> Multiclass Precision-Recall </span>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5Zbbiqk8ONmv"
      },
      "source": [
        "#### Загрузим датасет с тремя классами"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6rQ8WKDCOHO1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "outputId": "829f8c98-dfe2-4b7d-ca59-3aa45949e7ca"
      },
      "source": [
        "print(sns.get_dataset_names())\n",
        "df_iris = sns.load_dataset(\"iris\")\n",
        "df_iris = df_iris.sample(n=150)\n",
        "df_iris.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['anagrams', 'anscombe', 'attention', 'brain_networks', 'car_crashes', 'diamonds', 'dots', 'exercise', 'flights', 'fmri', 'gammas', 'geyser', 'iris', 'mpg', 'penguins', 'planets', 'tips', 'titanic']\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>sepal_length</th>\n",
              "      <th>sepal_width</th>\n",
              "      <th>petal_length</th>\n",
              "      <th>petal_width</th>\n",
              "      <th>species</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>5.7</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.2</td>\n",
              "      <td>1.2</td>\n",
              "      <td>versicolor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82</th>\n",
              "      <td>5.8</td>\n",
              "      <td>2.7</td>\n",
              "      <td>3.9</td>\n",
              "      <td>1.2</td>\n",
              "      <td>versicolor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>5.8</td>\n",
              "      <td>2.8</td>\n",
              "      <td>5.1</td>\n",
              "      <td>2.4</td>\n",
              "      <td>virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92</th>\n",
              "      <td>5.8</td>\n",
              "      <td>2.6</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.2</td>\n",
              "      <td>versicolor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>4.3</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.1</td>\n",
              "      <td>0.1</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     sepal_length  sepal_width  petal_length  petal_width     species\n",
              "95            5.7          3.0           4.2          1.2  versicolor\n",
              "82            5.8          2.7           3.9          1.2  versicolor\n",
              "114           5.8          2.8           5.1          2.4   virginica\n",
              "92            5.8          2.6           4.0          1.2  versicolor\n",
              "13            4.3          3.0           1.1          0.1      setosa"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Zl_K5vLEOOxk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 748
        },
        "outputId": "cbb9adc1-c83e-40bf-a940-39d5f60a9509"
      },
      "source": [
        "matplotlib.rc('xtick', labelsize=10) \n",
        "matplotlib.rc('ytick', labelsize=10)\n",
        "sns.pairplot(df_iris, hue=\"species\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "findfont: Font family ['Calibri'] not found. Falling back to DejaVu Sans.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fe534424790>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 922.2x720 with 20 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bedla5yXxDji"
      },
      "source": [
        "[Датасет ириса](https://ru.wikipedia.org/wiki/%D0%98%D1%80%D0%B8%D1%81%D1%8B_%D0%A4%D0%B8%D1%88%D0%B5%D1%80%D0%B0)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zOkcauEnOP3E"
      },
      "source": [
        "# закодируем значения\n",
        "df_iris, encoders = number_encode_features(df_iris)\n",
        "# выбросим колонку, которую будем предсказывать\n",
        "iris_X, iris_y = df_iris[df_iris.columns[:-1]].values, df_iris[df_iris.columns[-1]].values\n",
        "\n",
        "# разделим на train test слайсингом\n",
        "iris_X_train, iris_y_tain = iris_X[:30], iris_y[:30]\n",
        "iris_X_test, iris_y_test = iris_X[40:], iris_y[40:]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o59Z65JmORod",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "2b8472d9-0c6c-492a-d108-0bcf8e8a16e8"
      },
      "source": [
        "df_iris.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>sepal_length</th>\n",
              "      <th>sepal_width</th>\n",
              "      <th>petal_length</th>\n",
              "      <th>petal_width</th>\n",
              "      <th>species</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>132</th>\n",
              "      <td>6.4</td>\n",
              "      <td>2.8</td>\n",
              "      <td>5.6</td>\n",
              "      <td>2.2</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>4.8</td>\n",
              "      <td>3.4</td>\n",
              "      <td>1.9</td>\n",
              "      <td>0.2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>130</th>\n",
              "      <td>7.4</td>\n",
              "      <td>2.8</td>\n",
              "      <td>6.1</td>\n",
              "      <td>1.9</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82</th>\n",
              "      <td>5.8</td>\n",
              "      <td>2.7</td>\n",
              "      <td>3.9</td>\n",
              "      <td>1.2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.4</td>\n",
              "      <td>1.6</td>\n",
              "      <td>0.4</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     sepal_length  sepal_width  petal_length  petal_width  species\n",
              "132           6.4          2.8           5.6          2.2        2\n",
              "24            4.8          3.4           1.9          0.2        0\n",
              "130           7.4          2.8           6.1          1.9        2\n",
              "82            5.8          2.7           3.9          1.2        1\n",
              "26            5.0          3.4           1.6          0.4        0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 109
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tVvqmE4vOSgN"
      },
      "source": [
        "# KNN и dummpy классификаторы на датасете\n",
        "iris_clf_knn = KNeighborsClassifier().fit(iris_X_train, iris_y_tain)\n",
        "iris_clf_mp = dummy.DummyClassifier(\"most_frequent\").fit(iris_X_train, iris_y_tain)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OMzeN-sOOTYd"
      },
      "source": [
        "# предсказываем\n",
        "iris_y_knn = iris_clf_knn.predict(iris_X_test)\n",
        "iris_y_mp = iris_clf_mp.predict(iris_X_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uO76F0y5OVuB"
      },
      "source": [
        "Пусть выборка состоит из K классов. Рассмотрим K двухклассовых задач, каждая из которых заключается в отделении своего класса от остальных, то есть целевые значения для k-й задаче вычисляются как $y_{ik} = [yi = k]$. Для каждой из них можно вычислить различные характеристики (TP, FP, и т.д.) алгоритма $a_k(x) = [a(x) = k]$."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g5bl4AChOUcE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 529
        },
        "outputId": "1102bf53-1fb5-44b2-9b1f-14acf9388237"
      },
      "source": [
        "mp_mtx = metrics.confusion_matrix(iris_y_test, iris_y_knn)\n",
        "\n",
        "fig = plt.figure(figsize=(10,8))\n",
        "matplotlib.rc('xtick', labelsize=15) \n",
        "matplotlib.rc('ytick', labelsize=15)\n",
        "sns.heatmap(mp_mtx, annot=True, fmt=\"d\", \n",
        "            xticklabels=encoders[\"species\"].classes_, \n",
        "            yticklabels=encoders[\"species\"].classes_)\n",
        "plt.ylabel(\"Real value\")\n",
        "plt.xlabel(\"Predicted value\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 46.0, 'Predicted value')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 112
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GUf0tJ-lOcdp"
      },
      "source": [
        "**Macro-averaging** -- подсчет TP, FN, TN, FP для каждого класса, а после подсчет точности и полноты.\n",
        "\n",
        "**Micro-averaging** -- подсчет  точности и полноты для каждого класса, а после подсчет их среденего."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tdPzHB30Oa89",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b584cca8-c139-405c-bfab-5206bc3e2524"
      },
      "source": [
        "print('для kNN:')\n",
        "print ('macro = ', metrics.f1_score(iris_y_test, iris_y_knn, average='macro'), ', micro = ', metrics.f1_score(iris_y_test, iris_y_knn, average='micro'))\n",
        "\n",
        "# \n",
        "print('\\nдля dummy-classifier:')\n",
        "iris_y_knn[iris_y_knn==1] = 0\n",
        "print ('macro = ', metrics.f1_score(iris_y_test, iris_y_knn, average='macro'), ', micro = ', metrics.f1_score(iris_y_test, iris_y_knn, average='micro'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "для kNN:\n",
            "macro =  0.9185470555861309 , micro =  0.9181818181818182\n",
            "\n",
            "для dummy-classifier:\n",
            "macro =  0.5283683585268936 , micro =  0.6454545454545455\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PLq5AeEHOhzo"
      },
      "source": [
        "## AUC-ROC\n",
        "\n",
        "[ВАЖНО](https://dyakonov.org/2017/07/28/auc-roc-%D0%BF%D0%BB%D0%BE%D1%89%D0%B0%D0%B4%D1%8C-%D0%BF%D0%BE%D0%B4-%D0%BA%D1%80%D0%B8%D0%B2%D0%BE%D0%B9-%D0%BE%D1%88%D0%B8%D0%B1%D0%BE%D0%BA/) прочесть\n",
        "\n",
        "И посмотреть:\n",
        "\n",
        "https://www.youtube.com/watch?v=V31tK9CgI6c"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2fuwKD5V6hXl"
      },
      "source": [
        "ROC-кривая - график, позволяющий оценить качество бинарной классификации, отображает соотношение между долей объектов от общего количества носителей признака, верно классифицированных как несущие признак (англ. true positive rate, TPR, называемой чувствительностью алгоритма классификации), и долей объектов от общего количества объектов, не несущих признака, ошибочно классифицированных как несущие признак (англ. false positive rate, FPR, величина 1-FPR называется специфичностью алгоритма классификации) при варьировании порога решающего правила. (ред.)\n",
        " \n",
        "Количественную интерпретацию ROC даёт показатель AUC (Area Under Curve)\n",
        "\n",
        "Пример хорошего классификатора:\n",
        "\n",
        "![image.png](https://miro.medium.com/max/1056/1*Uu-t4pOotRQFoyrfqEvIEg.png)\n",
        "\n",
        "![image.png](https://miro.medium.com/max/730/1*-tPXUvvNIZDbqXP0qqYNuQ.png)\n",
        "\n",
        "Пример рандомного классификатора:\n",
        "\n",
        "![image.png](https://miro.medium.com/max/1014/1*yF8hvKR9eNfqqej2JnVKzg.png)\n",
        "\n",
        "![image.png](https://miro.medium.com/max/730/1*k_MPO2Q9bLNH9k4Wlk6v_g.png)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S4bSHuk6OfCM"
      },
      "source": [
        "# по аналогии возьмем knn и dummpy\n",
        "clf_knn = KNeighborsClassifier(n_neighbors=29).fit(X_train, y_tain)\n",
        "clf_mp = dummy.DummyClassifier(\"most_frequent\").fit(X_train, y_tain)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g5WjaeldOkrk"
      },
      "source": [
        "# получаем ответы от классификаторов\n",
        "y_knn = clf_knn.predict(X_test)\n",
        "y_mp = clf_mp.predict(X_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S-LW_Zo6Ok2E",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "outputId": "10cb29c3-4fae-4a55-933b-bb397dda2598"
      },
      "source": [
        "# строим рок кривую, чтоб посмотреть как справляемся с данными \n",
        "# (результат плохой у монетки roc auc = 0.5, см classification report f1, классы разбалансированны)\n",
        "fpr, tpr, _ = metrics.roc_curve(y_test, y_knn)\n",
        "plt.figure(figsize=(10, 7))\n",
        "plt.plot([0, 1], [0, 1], 'k--')\n",
        "plt.plot(fpr, tpr)\n",
        "print ('ROC AUC = {0:.4f}'.format(metrics.auc(fpr, tpr)))\n",
        "plt.ylabel(\"True Positive Rate\", fontsize=20)\n",
        "plt.xlabel(\"False Positive Rate\", fontsize=20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ROC AUC = 0.5892\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'False Positive Rate')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 116
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XOHSvRj5Olp8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "outputId": "cab0221d-94f5-42a9-caa7-d04629305d22"
      },
      "source": [
        "from matplotlib import pylab\n",
        "fpr, tpr, _ = metrics.roc_curve(y_test, y_mp)\n",
        "pylab.figure(figsize=(10, 7))\n",
        "pylab.plot([0, 1], [0, 1], 'k--')\n",
        "pylab.plot(fpr, tpr)\n",
        "print ('ROC AUC = {0:.4f}'.format(metrics.auc(fpr, tpr)))\n",
        "plt.ylabel(\"True Positive Rate\", fontsize=20)\n",
        "plt.xlabel(\"False Positive Rate\", fontsize=20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ROC AUC = 0.5000\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'False Positive Rate')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 117
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JwUclSHb-5k2"
      },
      "source": [
        "# Задача регрессии\n",
        "\n",
        "### **Постановка задачи:** \n",
        "Определение оценки Вина (оценки от 1 до 10) по набору признаков: кислотность, наличие сахара и тд. Оценки были выставлены экспертами (сомелье), наша задача - предсказать эту оценку, зная характеристики вина."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2AjAVPxSOtxY"
      },
      "source": [
        "Data: https://archive.ics.uci.edu/ml/datasets/Wine+Quality"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VoFtce6zOouc"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "df = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv', header=0, sep=';')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6VE4sLMdOwY7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "d443f8ba-09df-480b-da1c-a848fa6ec618"
      },
      "source": [
        "# будем предсказывать столбец quality (качество) вина по всем параметрам с помощью линейных методов и dummy\n",
        "df.head(5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>fixed acidity</th>\n",
              "      <th>volatile acidity</th>\n",
              "      <th>citric acid</th>\n",
              "      <th>residual sugar</th>\n",
              "      <th>chlorides</th>\n",
              "      <th>free sulfur dioxide</th>\n",
              "      <th>total sulfur dioxide</th>\n",
              "      <th>density</th>\n",
              "      <th>pH</th>\n",
              "      <th>sulphates</th>\n",
              "      <th>alcohol</th>\n",
              "      <th>quality</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7.0</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.36</td>\n",
              "      <td>20.7</td>\n",
              "      <td>0.045</td>\n",
              "      <td>45.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>1.0010</td>\n",
              "      <td>3.00</td>\n",
              "      <td>0.45</td>\n",
              "      <td>8.8</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>6.3</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.34</td>\n",
              "      <td>1.6</td>\n",
              "      <td>0.049</td>\n",
              "      <td>14.0</td>\n",
              "      <td>132.0</td>\n",
              "      <td>0.9940</td>\n",
              "      <td>3.30</td>\n",
              "      <td>0.49</td>\n",
              "      <td>9.5</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8.1</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.40</td>\n",
              "      <td>6.9</td>\n",
              "      <td>0.050</td>\n",
              "      <td>30.0</td>\n",
              "      <td>97.0</td>\n",
              "      <td>0.9951</td>\n",
              "      <td>3.26</td>\n",
              "      <td>0.44</td>\n",
              "      <td>10.1</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>7.2</td>\n",
              "      <td>0.23</td>\n",
              "      <td>0.32</td>\n",
              "      <td>8.5</td>\n",
              "      <td>0.058</td>\n",
              "      <td>47.0</td>\n",
              "      <td>186.0</td>\n",
              "      <td>0.9956</td>\n",
              "      <td>3.19</td>\n",
              "      <td>0.40</td>\n",
              "      <td>9.9</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>7.2</td>\n",
              "      <td>0.23</td>\n",
              "      <td>0.32</td>\n",
              "      <td>8.5</td>\n",
              "      <td>0.058</td>\n",
              "      <td>47.0</td>\n",
              "      <td>186.0</td>\n",
              "      <td>0.9956</td>\n",
              "      <td>3.19</td>\n",
              "      <td>0.40</td>\n",
              "      <td>9.9</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   fixed acidity  volatile acidity  citric acid  ...  sulphates  alcohol  quality\n",
              "0            7.0              0.27         0.36  ...       0.45      8.8        6\n",
              "1            6.3              0.30         0.34  ...       0.49      9.5        6\n",
              "2            8.1              0.28         0.40  ...       0.44     10.1        6\n",
              "3            7.2              0.23         0.32  ...       0.40      9.9        6\n",
              "4            7.2              0.23         0.32  ...       0.40      9.9        6\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 119
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6SeCiKDQYlaF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "2e559052-3681-4e27-9f8f-4b0ae9bae578"
      },
      "source": [
        "# df['alcohol'].plot(marker='*',style=' ', color='green')\n",
        "# df['alcohol'] = df[df['alcohol'] < 15]\n",
        "df.plot(subplots=True, figsize=(10, 30))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceee621d0>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceee14c50>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceedcafd0>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceed8b410>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceedc37d0>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceed79b90>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceed30fd0>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceecef390>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceecef3d0>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceeca5890>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceec16f10>,\n",
              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceebd9310>],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 120
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9gGXZFIZhvgQwA4Cnfv2CEm2ojXh3w1loC1l8P7SZrZtiN3y75yoA4J2o0s/ebIyVeuFsZLsQ1ftYy8+zPPmLEgRB2AOjRo3ikwXbG/YUxdlc8PsKALAsWwDghr6sIcMwpTtTaSnx55l7+Dv2vsX752kL6eNtxxRa6dbYwx3WFhSiUHBCLMsiT1towxYRBEGUT+xJQPMX/M6Q+e0AwLf0mlM2SH6Si7qzdmD5kQRbN4VQoKCYEpo9JaitPXMHJv52ml9eH30HdWftwL00sXto0pOcYp+3HA8p0IIgiGcEexLQlBBmgTLo8RmGGccwTAzDMDHJycml2CzjXEt6gpz8Atl1qZm5uJ9mnXgHrp4tZ4o3N9qzyt3H2XiclWdQfvF+ukhTVBwKFbSbD9JzkPxEefoRU2TlanEjOdPi/S3l34sP+N+c5jchpWjC5+QnuWj12R589d9lqx7316MJaD1vD3acT7RqvVLi7mdY7d4TBEFYij0JaCmC316C3576/wsAPJbuxLLszyzLRrAsGxEQEFCS7VNNdp4WUV8fxDvrz8qub/HpbrRbsNcqx+Jy6tmTlqUs0eHzfWgzf4+oLPZOGvp8dxiL918DoBOEjl1PNVnX1YdPcCs1y6BcSUBrM38PWn6222S9Stbr11ZGo+vCAyb3L20e6QXe3XEPTWypnsdZeZi9VTeNzKlbBt2A1Th7Jw29vzuEHw9cL7FjWANbuTTkFxQiO09rk2MTRFnAmu+mPQlopwW/6wJ8XrRa+rI4lmUtVzeUIjn5Op+c4zdNf9SLC00DVHxyJT5UnFbywj2ddf3dDWcxdOlx0UwA2XlabD51V/QyPve/g+j85X4D7YvVlDGSek7e1KUGtEaH8HfsfaRlG2oSLUHDDxqsR5ZAKChJ5dbdx7oJoy/eTy+5gwiISXiE+MQM0xsKcHBwQEGBvHa+pLny8AmuJZW+1pYgygqFhYXQaKwjWpWKgMYwjBPDMP4Mw/gDcBKU++v/XACsFewyTb/t+wAq6MuE68sEpTFDD69BIwGtxLj88AkAIDuv6KM4Z+tFTN4YixgZbc6mU3dFy8X2QTOxe3EFljuPsvHWujN4a90Zi+sQtpF7Jq8lZSqa8rfG3rdYCFLSSFoD7lpqSml+rYFLjqHXt4fM2sfd3R2ZmbYRkkrCr5AgyhPZ2dlwc3OzSl2lpUFrDyBZ/9dOX+YgKBvKsuwxAMv06/rpy+frl88D+LaU2lpsOI0GQ5Mo2pzCQhbz/ok3cGJXA2c25u7ion3X+HUPMnTK3KxcQ3NPcqZY0Wu1NBsK5drC4kVRchrEe4911+jv2Pv46K8LWHP8lsl95R/xosLXVkTLbYC3151Bn+8Oi8ruPMrGgh2XTF4vNdfzWlImvv7vMr9tYSGLqK8P4Ht9+hYp607exqGryfz2pSWgWYKXlxcePXpkMy1aSZCZk4/UzDJhICEIRViWRVpaGjw8PKxSnz2ZOAHgDeimhLoCIA9AIoAfAUSWpVkEuEFmqWrQSuFYZZHYu2n4+eANvLPeuHbowy0XcPS6zg1S+m3mBO2NAs2YMSEhv0AsMFlL66B0zG2x5jnNp2fnY+Tyk0h6ojPZSp+ht9adwapjtzBrywX1bRM8gcLr99gMs+mE305hyYHrvMZSiHCwo+Zyjlh2At/tvYaUTN3xz99Lx7WkTCzcJZ/8ePof5zFi2UleO6exX/kMnp6e8PDwwK1bt5CWlgatVlvm0+zcSMmyaBBFEPYAy7LIzc1FYmIitFotKlasaJV6SytR7X6okFf0ec++0P+VeUpjEF7kg2adDjo7T4uGH+1EUEU3HP6gq1XqVMveSw/x6fZ47Hynk9Xq5D64WslX/fKDJxi+7AS/vPr4Law+fkt20u6bKYaO/8bg8oLtiX+Iz/6Jx29jWxtsoxThK+R6ciYG/3QcXw5sbHS7yRtjMaBFkOr2bYi5jQNXktHqsz1Y+HITNA32Ub2vFEbwWl9LykTU15YHLeRrdffItEmXRWL6U7z4wxFseKMtQv2LRqtZuVp0/99BJKbrhE9OcFT7dvxz/oHpjYrJO+vPIKiiO6b0qGfR/gzDoFKlSnjy5AkyMjKQlJRUatq0h3ota/wT65hwSrpegigtHB0d4e3tjUqVKlnNB6205uJ8piiJiMrRK6ORnafF+nFtReXWFgIvPdBpL+4+tv5otrCQRc0Z/+Cj5xtidIdQg/Uz/7yAxPQcJBUj9YQS0su09NAN2RQX2gLzzIVyZmxOFpzx53k8zMiVPc51FekxVh+7hZTMXGyXpJWYvyMePx24obCXTlhXa16fvDEWeyZ3VrWtKb7fK28+VItck7su3I9WIb54q1sdvqyQ1WkNk57k4rfjtzDr+Yb8uksPMsSaGDO12bv0kadPVQjQUtS6Nmw5q0tNYqmAxh3Dy8sLXl5epje2Ir2mbQcA2YGMPdZLEGUZezNxlg94+cx60tPeS0k4fuOR8iGtJBOa0+Jzd9MQMm07TtxQF61aoG/kvH/iZdc7OuiObq6QZAyl66J0no+z8yX7q7uwc/QpIACdgB4ybTse6v3UpCbOjl/sNfC/koPzg+KiQjNytEjLzjMqnIVM247Q6f8YlCdl5CBk2nb8HnPHYB13LYqrhZW7ptIao74+gBD9x1gJYTNuJGdhffQdyfqiDfIKCvFUELwhFY5Yvlz+WBk5+bImaMbMd/fNtacROv0ffPiXvFk4/Wl+mTdDWsqoFSdN3nNzSM/ONyviOCtXa+B2QNiemylZCJm23arPRnmDBLQSwNRHwZpYOw+aOYENR67pBLO9l5Nk1xcWsmaZB530auH8gqJzkXPCV8u9tKd8ypOn+YVITC/SrCidpvR4ShOjsxLNzErBdtLvsDTq8M4jddpJzg/qod5X7FFWHpp+vEtx+z3xhnnHcvILcPdxNm7o78OmmLsG23D3XO4JEqYWMSZgKK2SlqtJ0SD3LAtvl/B6rjp2Cw0++pdfljr3c5vKOf3nagvQeM5/IuGar0ehZ0xIyZIV6Lad02k51xy/bbDudmo2msz9Dyue0dk+9l+2TgLx68mZuJb0BE0+/s/oeyAlbPZOjPk1xiptIKzHubtptm6C3UMCWglSKkECVs6DZk3n6B/2XUOXr/bjit7p21QbOSFC+AF8eckxi4/ffsFejPlVF0UYn5iBtvNNJweWClN7LskLn3yEp8z1kuZBs3TwrtHfDE4QNsVxGU3mhDWn0OHzfbyAYkz4YVngSY5Yg9hqXlESXznB8oI+VcbSQzeKPUTgBMXUTOPakUJWeUBizvPLRa/KzcIhN1C5lZqFyK/24+td5s2QcPuRLrfa7viHVtUO2zPRCY+seq57Lz1Et4UHEPX1QYv2P3hFnZD4NK8AZ+/YRnC4nZr9TAVKUJYD05CAZgH7LiXJqthvp2bj1K3HpZqTzNwozpTMXBy6qtxZmWvakTv4P+cTkZNfgOgEnUmWy4WlVssnTBsRJ0jiefhqiuLUSAkpWZj790VoCwpxP+0p/jqr++hKk9ByKJ2nsIUsa1knUsBKBTTLHghzUj3kagtkn7t9eu0Fn25CZhuhFtaYpqHTl/sMytL0JuHTVszu/+ryk0bXG8uDZqBBA4tTtx7zCWjVInflOZP1yZuPcCs1Cz/uv447j0zXK8xV+KUF019dS3qC83ctyxln7J0pKc7cfoyXlxzD/3bLR8xaAucbW9JM2RiLlxYdQUopp/yIu5+BTl/uQ3srzTBTVmFZFn/H3n9mBjKmIAHNTB5n5eG1ldEYv+YU1p28LXqRO325DwN+PMovC78V6dn5WH0sQZUfSmEhi+WHb4p8a5QwV3wY/NMxjFh2UrEd5sgjctseu56Kib+dxoIdlwzWFVdwHb7sBAb9pNOorT1xW5Q3KfKr/VhxJAG/HL6JqZvO4f8Uptkyhe66FJ2YJRpFw5kEjKdu2BCtM4v9cz5RZBI259gL/7tiVPzlmiQ3gBAKq9zsBObCQun+qrvpdx5li57lzafuikzSBoKz5Ml/a90ZpEv8BwHgSY4WA348ivFrThusM6+FYjp/uR+f/3sJHb8wFFqlcO9JIcsiPtF8QSPq64Po+4Npn0Upm07dxfBlJ/DykqOK26Rl52HN8VuK/cHTvAIsP3wThYUsZv55XtVxN+h9Bi8/sF4y3dIa9MbqzW5Kfe/DjBxslPHjtITHWXn47YQu1yDXrz1LyHVvOy48wFvrzmDxfvueaq20IAHNTHK0uhf3+I1HmP7HeYxbZahxKEpwWvQIzthyHh/+dRGnb5tWn++48AAfb4vDlzvVj7bVOiBfT87Sby+/vrha5x0XdL44alX1x66nYszKaJFWT/rxvZ2azScYvZmShWtJTzDjz/OyQtiD9Bxec6fEr0cTcOmB/PQ6Ug2T0uXgzI4jlp00CJKQfoQ5DZqSNu6Dzedx51E2Jv52WpSmwhwN2v20p0Y/YsLnQ7oZZ4IrzkeQZeUFnZTMPHy96wpi76QZdQZ+ml8g2n/yxli8srQoDYqw/XIayb9j76PJx//hapL42n9oRi43IdaUB3jzMlt6+dVytQWYsjEWAJCQKq/lW7TvGpp+vAuztlzAxfu69+FRVh56f3uIn5B+4X+X8fG2OHy8LQ6/nSjyrzPW30iDOsoTI5efxPubzlk8Ldq+y0n8tX1nw1nM/PMCLj94gkyB7+uBK8n457x5uQ1Lg6QnOfj6v8sGA1Brkqqfx/ehwPf1WYYENDORfhxuy/jl8IlqhQk79Q+eMa1Y+tN8vLfhLB7oH860p4adwLm7adh76SF+PnhdfwxlB29jKG1vkYlTwKpjhtnnGcEHChDnJBu69Dj2XErCiGVFZi2pKfTd38+KEoxyjv93H2fjvd/PijrLlUcTFM2agM6PaPbWi4hVMBkJ7y8LdSbOwT8fFy2flAiInMnWWE2cJkZ4fHM6aVbil3XkWopovfCxlZoIuXxwxgQ0Ux+kp/kFOK/g9Pvdnqt4cdERo/sDhgl+hUJ+mkA7ZszE+e6GWNEyN3G7kJTMXEz+PRafbosz2h6WZTFn60VcepCBPG0hPth8zuj2SvA+fmBFQndJmnHUCNvCASD3zszach5xiRmY8JtO45j+VHfdUyXXUc03erdM0EpZh0sBZMxt4dKDDIRM244L9wz7mNdWRPPXlrO+SJ/7kctPYuJvyhpfWzFl4zl8t/caTt22njsDR8i07dgnE2z2z/lErDqWgAK9BveGivRE5QnKg2Ym0hdTLnxbOrrMyS/A0es6LYswOaqUDdG38ceZezjIaZNk+oB+i4/ybRjXqVaREKjfNiMnH0N+Og5vNydE1gvAG51rGVbCt9FQZBBGr/17IREbY+5i2aiWim1WYlfcQ7St6Sc4lnofNGkKCumHjLu8CanZSEjNRkV3Z9Xt6vzlfqPrfztxi4/E2xX3EFENKqmuW4k8rXJAgTFumBEBK82VNuyXE2gV6ssvC4UaczVlXRfuR8fa/qKySWtPY9ErzUVlSpoatUgHL8L7/vz3Rc+EOe2X+5DO/+cSNp8uimbNlIkU3n4uEe1r+WPl0QTsuJCIj18M583P0uMb09JduJfOC/A602wRUkGe43pyJt5edwZrx7aBt7uT7DamMF8bqtshW3IPlLS4Sv2HlD/PFF3n9Oz8YpyP4QkdvJKMRfuuYe3rbeBgJdWkNUypL+kHI89/f5jP67b/cpJBepyylnXlaZ7uPbFaSifJLXttRTQ+eSlcVMYJqhE1fPHbids4desx/rViInN7hzRoZiL9wMt1HNIUDGpSCwCAm7NOXs7K1XWScu+B9HjcIld66EoK4hIzcOxGKubL+IFxKA0AhRq08WtOK0YxSolJeGRgwhL6EAnbCoBX86tC8iaX5GTZ0jQJ1og0ytMLGvkFbKnm/BH6kwmvmZLpXMlsdSM5yyB58PZziVY3dUiTwypVX8iyZgScyLyfKvedofe50jCMUSFstZE5Sz/bXpTzT9fuIrJz5bXpP+y9hov3M7DnkuUaKFPn2Oqz3eLtWfH/HEUBDlK/SnXtEGo0hRqSFxcdwXyFfIhyyB3vzbWnceLmI2TmqEvFw+XcCpm2He0X7MWKIzdVH59DlQ+xzCYTfzuNYxJXCFvKZx2/2Kuo5e3lXjoAACAASURBVFOCOy81svDF++kImbbdaHCOMWuN9NoIA22eJUhAKyZyzwv3MeQ+7mq/8Y76J5+LApTrDIQvf/jsnXhzrWWqcGkHnv40H9qCQtmJt9V8iJcdNt3ZCWv5/F9l4VFKrCTsvTTfUWskuMw3YnKVIye/AB//bdz8Zi5qOrb76cp+HzsuGE6BZG3H5uw8dR/aHRceYN4/6p4fOQ3aH6cN02oYQzq7RYwZEavOjkVd7L20p9grGPAI35mQadv5e85pg64nZ4oE+qd5BZi2+ZyskD/9j/MImbad1zrmmXjmpAI3d5UeSJ4Bpb7LkkGSsK7YO2n46eANhEzbjm93F28GiimbYlFzetE1mbP1In+NlKZUu5f2FHNl3jFrZH6Q9hkDfzxqoJkEhDNPGK9v58UHCJm23WDAK0edmf/gvQ2mA6S4lDnvbDiLkGnbVeUkK1TZXgBYf1Lnh7gnXt0An4OrWltQKHrOpfk+d5xP1CcDl++z1EylVxYgAa24yPRTwr4rK1eLjKfyHx5pJ+ogyRxvqgvMzNXy4edKL/vjrDzZZK8sq3Msf5yVh/k74tFk7n+oPXOHbIZ7YdoIuRFRvMTJlaNoPkTumEX1ZORoTTrzKyG9biU5qrJGkk1pbjFT1P/wXyy3YHRvjJLQOpojqJjiXtpT+FdwsVp9HNaaqN5SnByKulguTQeHVKOy/MhN5BcU8n42i/aJI9kafPSvyAH/QXoO31esO6nT/LbUa8aMJXKVG3BxZYYT1cv7uAofpyc5+fwAzxLnblPpOHLyC0QR2xyc0LMr7qFo4MoljT5wJRn1P/zXYD9jqH1NhJr1C/fSRe0T1hGfmGHyPTHl97tef2/j7ssHNgnJL2Dxh0xePyU4644aQYq3DKmQ0ExtkpSRI6sM4HiaL14nzfe5Vn9N4hMNr0nsnTTU//Bf7C2GBtpeIB80M5DXaCmXMQzw3NcHFDUT2XlaODsW+U9xI2fOLMOyum3uqZgXMyE1WzYnU7NPdqGqtyuOTu8mKj98NQVjZSJQ5SgoZOHkAPx74QHGrzmF1WNaoWOdAH69UhJIqbO+8Eo9ysqzOAmt1AH+4n3LckSVFnOsrA2zBLkpnuyJ11ZEo4q3q9XrNfYRKGluJGci6Yl5AsvMP8+rivROTH+KtvP3YlKXWni/R32+XDpVGUd8YgbyCwrh7uwIXw91PpsZOflI4PwgJd3cH2fuYljrGgCAZh/vgraQxah2IaIZNeS48ygbbs4Oqo7P8crS47LXRM58LWR3nOkP9NO8Arg5OyAtOw/Xk7NMRp9z1/f2o2z4ejjj+I1UDNH7GMrNI6rGhGhKmLF2Qle5wbQauZRXAphxLG6f+MQM1AzwgIujA7LztGg1bw88XZXFD6kZVcNr0HQYC447rQ9iOHglBV3rVzajtfYHadDMQG50JesnJvhtzGwkFWC4uSg5ClkWb6w+hef+py57dscv9sm+PHJtOGeG7wHXEXIZtr+x0CRhLSXOt3vExz9hYe6uZ4mdF+1/NJlo5F2xFFMf8ZLg8FXdAKLrwgM4Z2aC2X/OG5qS5eBmW/jl0E1VPq69vj2EF344gqivD/BO7ELkrtKgJccMtHwcM/+8gM+2x2H18Vv8NTYlnF1PzkLHL/Yh4tPdRrfTFhRiztaLyM7TIjH9qSqBFdBNdfaHIPjDmG8gB+ciEvX1AVEOSyG52gLsv5yErbH3+TLuGl4SaHCycrX8vedQCl54lJUn0EjJt22NpP3cTB/zd8QjV1tkwkvLzjOYReSoYBBbUMhid9xDXlhKkAk+YlkWD9JzDKaLO3Q1mQ/e4Z4RDcPgysMnRqfxE55SUkYOen17CLP+1PlxclH4T4z4DkoviTCXoNz68gpp0MxA3mnfsCxF799x14TmK/1pPip7FWkNPpc49bMw1BaZ4pDK7QvM0CwU6OfG5DqBU7ceq54gXcQz5uBJ2J40BY1SSTJ82QkcmtrFon3ltBtycLNz5GoLRbnz1HBbRtMuZwkQZu+XS5mx9JB5Zvjv9pge2K09cRsnb6Ziy9n7+PPMPbPcAyyZb/OQXqBKMTK92Gfb42XTB0nn6Z2yMdbAV1NJ+Hpl6XHZfJlCZm25gOFtagjStADtFuzFkxwtfj54Azfn6zR2b68/i4NXknFuTvei+n85gX/e7oiGVb2w4shNfLo9HouHNUfvRlVEEdEcu+Ie4vu91wAA3w5pihebVsON5EyMWHYSLzWtim+GNBMk3GbQXa80kNMaSuGeac7Ue+y6+d+OB+m5RRdBiBEXI3MVj1tj76N9LT/4lYCrhaWQgGYGcp3Y0/wCrD95W9SxSvNiKfHJtjisHtOaXzbQdLF6Va4Zqqe1JwwnawaAEzdS0Vqf9gIAfpeZNFuJgUuO4r93O4nmqPvwrwu4qjI6dc2xW6jp7wFvN8tC7AmirKFW0LKUWRYm4FXERBdjLLegNZkhmK2Ay8FWkuQVFGL7OeMR5TeS5TVFs7deRIBn0cdcLpBGaV7ZSw+eoE6lCgBMR9wKI2k5rRPLArVn/AOgSEv85tozov16f3cIUQ0q8YLRxN9Oo3/zaort4fi/9WfxYtNqvI/flrP38b/BTcGN6d9eX3ScPG0hHwiz6dRdLN53DXsmdxbVzaVq4fxBJxkJbFO6EnyuRv2yNGiguDzMyMHb686gRY2KiKwbgNEdQuHhYnvxiEycZqAkJ0374zw+3a4+ZJzDlEnHWg8fYCg0mjM/39WkTHy355qo7MrDTNVy455LSej85f5nLkSaeHb5yoxZQCxBGoUpxJLgGxvHUtgUOYHhw78uICe/AL/H3MFhI1YJU/2ose8Cd8kvG5ln9GleAXbrHfilt0hbyIpM+HK+wLvjk0RaZLURzCzLijRQp2+n4b4+ilRo2mynnzs0JTMXUzbG4kZKFj8rBaDzjf5ip84yZE7AjtKW0qTfp28ZN39/ufMSrkoCXzgTujBimTPjnrr1GAt3XcEXZmQZKElsLyKWIawdCWfKd0StP4pa3t8Ya3ojBawx8fEMlXP5EURZR23+wJLAkuCbBf/Go9IR6wdplFX2X07GplN3ra+pFMD1/8bmDRYmVJa6wJQk2XkFGLOyyGT8ybY4WXcBbjaETwSzcjzNL+Cd+IV+ieZ8P5U25bR4XP0/7LuG/MJC1A/0RGVPV6yLvgMnvd9f8pNcbDuXiN9j7iJ6ZhRfx4mbj7DyaAJupGRh1ehWAMSZCgAgUyFHYWlDApoZlIQGaKhKc6g12HhKvVmzJJAzARDEs4KZ3gqlyoV7GQBMp3F4lihJ4UwtwpRC5swsUlzCZu8ULZ+9o6ypkublUxogJKbnYNG+a7LrpCgJc5wGTZhPkJuhwUHDiLR0nGm6sJDF1/9dRvyDJ1j6akTRlIOCfHVJkhQ4JZkM3RzIxGkGF0ognYNSlBRBEOULNyfz0ksQxMcm5ostayjNYsLBzdih5MNpzEyqNA0jwwDf7b2GXfq0K5zp9uj1VIxZGQ1ANye0EBLQyiBWmu6NIIhnEBLQCEIdOo2uISmZeaqny5NLsRMybbsoZnbPpSTZRO5PcrR2MRsBCWhmoDRxMEEQhCnSSiEqkSDKAykyM0eYC5f4WppC5YlEIJOacwGdCbX3d4eK3YbiQgKaGZCARtQP9LR1E4gyiq2nnSJKD+EcrIRtaFGjomz5G6tPqdr/RnKW7OxBpQk9RWaglBWaKD7b3upg6yaooh4JaCLoQ0QQhjQJ8rZ1E555rCFbrTiSUPxKigH1rmZAGrSSw93ZAdN61Te94TNAzQAP/vf1eb1xc35vXPqkpw1bpIyzg+27kAZVvGzdBIIQUcEOkpw+61gjj+heG6bLAUhAMwtNGbxa7/eoZ+smqMLJgg99ZL0A0xtZmTEdQku0/kbVvPFik6Js3w4aBgzDwNUMB/M+jauURNNk+axfuKrtKnm6INjXvUTa0KamLxIW9EHHOv4lUn9Fd5oBgzAPS/ozwrqYOw+uHLYOFKCnyAxqBVSwdRPMZmS7EFs3QRWODozZoc0OJajRrOnvIVveOMinxI7ZLNgHv7/R1uyR34DmQaLlhS83kZ0jb3ibYLQK8cV3Q5vJ1iPU0iUs6AN35yKhcPGw5vzvxnrzzcstgvBi0yJh8uMXw/BGp5r88tFpXQEAXwxojJMzo9AzPNCc0zIgqKKbaPl5vSBqyrdrQf9GBmUj2tQwKDuib6+U/e93Qae6pT8YUOK19iG2bkK5Y8f/dUSrUF+r1Wcrawtpk4s4dNW8eazlsLXXKAloZuDkoMGGcW3Qr5n8fGbWYOP4tlarq31tP4VpeO2PQC9Xs30GNCZ8AlvUqCiarmRSl1qq6143rg3+ftO4X9y8fo0wsm0NbBrfFsNaBxdrrtHIegH4c2J7uDk7mNTSfT6gEX4c1hxTe9bDhnFtMLhldX6dt5sTXCR+YXNfCIOGAWb3DcPv49uimo+btEoAMNDSCe+H0P8yqkFlAIbTA73aNgTTezfgl/0qOCNhQR8M0rePc7id0bu+VbRdbfRzy+YX6Or1dC0yK02ILLrXQ1oFG+z7yUuGmj8/D2eDsn/f6QhvNyc+47ilVPU2zNIvfDZHt1enmW0W7IP/61anWG2xBp3tSGC1Bn4VnPH7G9bre0tLPvOUmFK72MCqUJ55rmFlmx6fBDQzaV3TD/8b3FSkoXjvubqibYoz2m4ZYr1RHMuiVCZ8lWpwzGV0+1AwDAMvV/PaakyDdvaj57B5Qjv8904nvmxSl9qq6/Z2c0IjE46+/ZtXw9wXwxER4ovP+jUyGkTSpqbyfe1Yxx9fvdyEX/Z0NS7oDW4ZjF6NqmBiZG20ruknijSKnd2dnwaFY2S7ENyY30dgdtFtX9PfA0Nb6YSn6Xr/v7VjW2PJ8Bb6rYrqjWpQGQOaB+GtrrVR3Vcn4BUUGp9AW6pF4AQ6xsJhQ6CXWMip6K4TqLzcdM/Npy81AsMALzSpiqk96uHX0a2wbGSEYn3/vtPRoGz9uDb4cVhz/DWpPb4e1AT1A5U1EnIm9lfbGmrmAOC/9zobmJ49nIue9/Gda0p3MWBoq2D8ObE9fNzFgmQrK/YZSkyW9HHWipcyZ7BbUiZsoOR9KQdFFK+PlGPNmNaY1lvst2uOK0RJw/UTZZkFpTi9lhwkoFmB8Z1r4bmGlbGgfyNsGt8Wy0dGoKq3q104UAM6YcUayGkdAOANmY+Ls6MG4zoZljeqJhZ6agZ48H5yQ1sF45MXw/h1pkw5NfzFPk3CDzj3EatT2ROO+q+JMcGgf3Pxh0JNRyeVD42ZaCdEKguHq8e0hn8FF5PH+3V0K+wUCJxFxzW5q+z2FT2cMb9/YyQs6IM3Ous0Tu1q+/OmSO50tkxqDwcNg4WDmmBy93q84MUlgtw8oR02TzDUPkivNlcfw8BAiFTDkhEt8PWgJtj2VgesHdsavcID8elL4Xg3Sic8+Ho44+b8PvhuaDMwDIPOdQPQTa/tqxVgaLKuH+iFta+3xvJREfh2SFO4OjmgTU0/9GpUBU2q+6C/wsAjqkFlfNYvHF8Pamqwzs9D/j5qGENfNuElcHE0/bxN7y0fRPN+T8v9TP0rGGoN5XhLorWrYGIQoZaqPurn/3wnqqgN7Wr5mdxeKLgGVXTj+wE5HK3cV0sfbz/B+z0xshZay5hTfYz4OkpNl54ujuggI7AKtecNS9nc+cXAxqLlQ1PlXQYI9diHBFHGcXbUYOmrERjSKhgRIb5wdNDg6PRuRgWMrW+2x5LhzbFlUntVx1gzpjXv0yOHUEPDvejhemFIOOKWCxpYMry5aNlRw2BUuxDEzu4u2KYFhsmYin5/o63IN4iLXprSvS5m9G5gMEL2dnMS+XdtfbMD3PS+To4OGoxoG8Kve6ebeNQuZfJz4nN5r7v89lxnaUwm6BVu2rF+x/+JNS4GGiIFSaljHX84ORRf5dC5boBsmg+lXD1KGj1fvSlPKiwb1Kv/X5r7jbvf9SrrylvUqIgWNQw/OIYaNF2NDMOYzC/EmWrGdy4yVfpXcEH/5kEIr+aNdrX9odEwGN6mhiphuml1+ZxI7Wr5o2v9yiJfOlNU83HFsNY1DEzani6O6FhXXsvD6P8JcXVywOcDGmHhy03g5Gj6+RBq3IRINYvmwVi0v5KPprnIZXtXQvg8cdpLoS+h0HQf+1F3/D6+LdaPawNA1y99KhhgyvV5QJEmrbiBIdJ73adRUf8ytWd9bHijLRa90ly6myKv6DXdwb7uWPlaS+ye3BmAYSoJ4bvwfBPrBwstGd6c12RO6V4X3wwuGqSEV1XuT5Q0y8VBqMGeotD3l3VIQCsG0TOjcOD9SMX1xrqexkE+6BleBU2rq3M671DHnzfpyOEsGIEPb10Df01qLxLGdr7TCefndJe1qfeUCCceLo6Y80IYb3LsEVYZPcMDZX2+WoX6wl3/4ahbuQKGtdYJcdw8tPP7N8K2tzrgY71mjGGAPycWCaXGRrWM4OmUG11Kc3CpGVVLeaFJVQCGDuhySEexUgFEer+5U2tT0w9VvMX1H5/ezbyGGoH7xoX4iTWKJ2Z0w/4pkQbb1wqogK1vtsfMPg0M1olQeIBb1PDFnxPbYaKCybi7/hlTEogZAM1knvv2tf3goRfW29XSfQSs5QNijZB7Dk77JxSAt77ZHqc+fE4k7AwVDGh0WkPd71f070jfxlUxuGUwBrQIUoz6i/2oaJAkJ3Afn94N1YsZHav22vzzdkc++afcvZVqodWgNKiRw1EQRt88uCL+mNgOc18I458Zof+ug35AxGkI8wsKESx4P3qGV8GhqV34ZU6wOTq9K/ZPiUSdSsXMdyi5PnL5AhtUER+D8+2Ug7tKner6I7JeJVTWP2fSqyccwHnptZwDWwTh7zc7IGZWFHa920mVtl6JnuFV0CxY9wy82LQaXmpWDf31g3AXJ2VxonvDogChgS2KNNMvtwjClwMb46cRLcz22wvxKxokWKKRV4OtU5/alYDGMMwohmFYhb8ttm6flABPF9TwUx5JclqCN7vUFnUGUt7uqvvQ7dN/TLkOXPpSC9N8SJ10XSXbNqnuI+r06wV6wtPViR9x1a1cAYemdpFtF/chYBgGx6d3U4z6ExIzKwp/TGyP9rV1H9bmwboPsKuTA8KrefMpFhiGgbdA2DIWji70MRujwonaVOSU3OpvhzTFoaldRMKXWpOw9OWVfmwuzO2BQ1O7YELnWgj19+AdxSt7uSBQxmlcCqehMkUN/YdHGlzgX8EFIUaiUU2lAuCCD+SE6GbBFRU1dN+/0gzHp3cz6DS5Z6NZsA9eFGhWo2dGYf+USCwb2ZL/4AxtHYxDU7soZgM3ly71KlmlHsDQF6pfs2poHOQDZ0cNqvq44d93OiJmVhQf7crBXY06lXTvnlBAdnLQ4Pj0bpjTt6FoH293J6PpZNQ8R39MbIe1r7dWXK+kzDw5QzeIGKt/rhpW9eIHQXLvGvfhlqNNTV/snxKJD58vOj9nRw3aqhxUtQr1RRWBOTTQ2xXNgytCo2EwQP/BFwrH3DPLPeP5BSza1hQfixuUDREE2XDvjJz1o2eY+ihk6dWRe1Wksum8fobRxhy8e4AJ/02h6dTH3QlHp3XF/P6N0CjIG/4VXFCnsifCq+n6Ou47w2HKpYS75W93rY3DH3ThBwYLBjTGseldRXPNCgcWQNEgoH6gJ3oJorkbVvXCyxHV0SMsEPEfm5frUWielxvwWQNbJ6enbHolSPewQCw9dBO9GgWiuq874j7ugYYfGc779U5UXYyPrMVroj55MRwf9mmIJh//J9pO2CkuGxmB2jN3ANCpvYXvujE5hevQR7YLEY28nRwYPhpO6Dum9AE4/eFzoqg5blTWqW4ALs7tYRCcwLVP2jRjL4DwfN/sWhupWXlYeTRBcXulunSdmvxXiGEYAw2E1AlbCakAIu1w3Z0d4e5bdB0OTu2C7PwCuKrwN7r0SU/VnUN1X3dcnNtDlBbDGsx9IQwzejcw2z/HxdEBgd6GbXmuYWX+2XiSUzQvZYCnCwI8dc9P0YcI/H1pUt0HKU+KNzdf3yZV0bV+Jdl598ylm0DTEf9xT4OBlFxgAcuKnxc5rVegtytGtgvBnL/jROW/vBphYAr0cXcSmagdNIxiupHmwRVxLSlTdt24TqFYeuim7LpKXq6I+7iH6HnlzNSyAocRbVirUD+E+HtAaOlnWRZd6+ueCQAY9ssJnL2TZrDvpU96wlHDwNFBg7iPe6CgkBUF0szpG4bpvRpAo2HAMLpr7SAR0LQFhQbvK8MwsvePWydk4/i2aB5cEbVm/MOXNQnyRqwk19bUnvXwxb+X0a9ZNWw7l6hYnxxy7fhpRAt0rhuA9Sdv6+sRr28j8WUTHqdJkA+qykRsc7fpuYaVMbN3A/6dkJvG7v0e9fiBH1e1o4MGQRWLnl9nRw2qeLvhXtpTADpB2Vti8eDea/8KLqJzEPZxalwVTs2KQotPd+v3LbpeTYN9+GtvDtfn9RbdUylvdrFtxLRdadAE3GJZlpH8vWTrRplLyxBdAs0wvW3eXcGHRKNhROscNAzcnB2QpxVHyQk1So4OGrwTVQfNg31wUKIFM9YVeLs5IWFBHwxrLfYJ4IShC3N7iPx+lPD1cFbUwMhGjkr67g+fb2jUKRYQawwZhuFNRt0bVpZ1+i4JLbcxE6wUU6YiRwcNvFydVE2P5OrkYFaySw8XR6ur+TX659CacM+Gp6vuOZTma+OuoVA4/2tSe8UcZZYc25q4OTsoCtJCzZTwnhtzv5O7h44OGoOP19mPumP1mCKt2PV5vY22U+rz5+qkQcKCPhjXqZZBe5oF+/Dvmruzo8i1gY/EZRisGNUSgE6bn7CgDy9EjmoXYnBfuRqEh+Lq8nBxhIeLo6KfpquTAz9IcHd2NIhyFj6nn7wYDndnBwMNWl6BfMSx0v2Tam6dHTQG24X6e2DzhHaisvqBnkhY0EckxAO653lUuxCJVtW0eTeiRkW4Ojmga31dfYMiqovW16msO96YDqEG7jJKpm/uWWAgfifk+puCQhauTg5wdXIwGcii1V9jY/6UDCPWAkqvaasQXwyWnKMQ3l9ZL4xzaBgGXeubryU3NQj+vyjbCmikQbNjpveqj/k7LvHROFIfsHei6uIdfQSbaI0FH2pu9G0q8vT1jqEm84/JUfTh1S2P6RBqMt+X1IxST9/5qd2e4/tXmuGnA9dVnZv0A+mgYQy0F+9G1UXSkxyD/c2NpuzTqApahljHhFde+H5ocyw5cN0gl1tZhNM2DW0VrJ8RQlxuCi46VS0zezfAZ//EK7TF2J7ilUIfUYMtBZG4XJ/BfeS4tCtygxru3ezTuAq+23MVj7PzDYRGqfluRu/6uPTgibGGGzC8TQ0MFwQO+Ho4o2l1H7M/tJxGF9D5nsoF57i7OKJFjYpIWNAHr604iX2XkxWFbwbAnBfC5FfK4KBhREJ3sJ+70b5PaDo2xQc96+NB+llEyKRneatrbXy/9xq/bE4QB6dQkOtnRbUINWiS/vZ3vR/hhpg7ssfgniOdoCfGWEqcsoq9CmhVGYZJBeAJIAHAegCfsSxbPDuHHfB+j3qqPz5jOoTiysNMVQlWiztp9cbxbfHX2fsmow1n9lHfEQhhBSNvtZg7U4CSgNYjLBA99P4j3wxuipTMXAT7uht0/nLnJjfCUursN4xrg36LjyruJ2XRMPVRXM8KzzWsbPPkkEqsH9cGu+Meqt6eE1S4911t/rclw5vjWlIm3uxqnlDxeqeaIgFtVp8GvOtB7UoVEOjligcZhgMLcxJEC6Mdi8ydurKhrYIRezedDx5Z+HIT3HmcjasPMzFKP6NJJU9XHJjaBY3n/GcgNEqdzMd1Up9YWgkHDaM6Ul4JafQ2h/AV5/o1pWsp1zcZ1aSqbp35hFfzxq73OvPLJ2Z0w2fb49ErvApy8gt4Aa1P4yoYbcasFTUDKmBwRHWM6Wg48BYK48JgLrXfrYgaFfFm16KgJENztXj78Z1rYcmB66rqtmfsVUBzAsCJ93UAfAigFQD7nDHaDMxJlurooMHCQU0Myt1kbPVzXwjDgSvJeJKjhZMFGq5mwRWNOvkWF049bk62fe6lMxbyvnxUBC7cy4CG0Y2WPx/QyGjgxksC5/TuKpx+K3u54mZKlqr2NguuiPiPe2Lhf5cVU34QZZc2Nf342QvU0K95NVxLysTbeoGee55NCUTSqGpzWDYyAmN+jQEAjO1Y5EvqoGFwfEY33ErNQucv94vMhH4VnJGalaeq/gmRtZCTX4DhbWrg+I1UAEXvp6erkyh1xIAW8nnklAZSX73cBL8eTUAlTxc0KSGnb2siFLh99P2aUMjcPKEdBvyoG7DJnbIx5VRxvBU0jHna/MpernwgWK5WN/eko4YxKw0IoHvGPpfkQuPgfZAZBi6ODoj9qDt+2HcVffVR9Kb4oFd9tAzx5efGrOQpjkSVPlMf9KzHC2hbJrVH/8VHRNekSZA3Xpfk6fRwdkBWnm3n3pRibwLaVQBjAOwBkASgNXTas8oAejAME8my7H7hDgzDjAMwDgCCgw3zdJU3vhncVLbz8qvggjMfPodlh2/iVUEuMXuhfW0/fPh8Q7xsRkZthmGw8OUmRmdX6Fq/Mu+fAeiy7FuT38a2xqpjtwxC4pVwc3bALDPMDUT5xcVR/CyURjyY1PdJCmeyaiEYjP06uhUOXE5G02Af3Eg2PhjxcHHkz6lz3QDM6tNAdiotYyhpxit7uWJqT/lkvLZg21sdkJhuqHHkEI6D574YhoZVvdChdlGEb4saFVHV2xX303PMFrhq+ls+7/Pu9zrj/D3LJgrnNYEWH10BQfAPoItOVmONOTmzG7bFJiJC7xPo6uSALwY2Rvva/jh2PZXfTnp5GYbB2tdbw4Fh0LS6D/57tzOivj7Ar/9LZho/bSGLf97uiN7fHTLr1EoSuxLQWJY9hYyV8gAAIABJREFUAuCIoGg/wzDfApinX24JYL9kn58B/AwAERERtp7btMR5ycjUKI4OGj4jvL3BMIxJnzM5lEbhpUVVHzdM62U/Hw2i7GPNnGzmUiugAr4f2gzdGhQ5VFfxduOFLHP8eBiGEWnp1KIpI+6F4dW8+WTfcgg19Z6uTrLXIqyaN+6n58gGiFWQmdpuzZjWSEjN4l0yLKFmQAXUDLBMwCvpOUTNqT/U3wOVPF0xWvLd4AIl+jerhikbYwEUadCCKrrh7mNdNCmXSxHQmfhfaFIVW2PvGxynZoAHbiRnwcPFEQ2reiHu4x74fu81UXJhW2FXAhrDMBqWZaXhNqzCb6KcsmJUS6tHDxKEreGCa8zx+SoJ1JqVSgpT+QpLkt3vdS52OpoATxf8b1BTVYmxvxncFJceZPCzdwip5uOGTePbYviyE8jJ1332OtTxl53CqbRgJP9bCy6HXXOVbjTb3uogmhlCDo2GQZd6Adh3OZkX/La+2QH39ek+pCg9dvP7NcLgn4/zefHcnR3xgZ1ocu1KQAOwlWGY/wBsgc7E2QbAO4L1R2T3IsoVXSwIlyYItdgq+SR3VHOjfcsb5gb/WJPalSw3HQLAseld4e7sqNqX1sPFUXYaNI6IEF+cmBGF7DxtsdplLTQlZOKsH+iFXe92Qi2Vmj1jmkshPw5vgYcZObxp1tfDWVYYBoreP2nEK6cMUBtdXZrYm4AWBOBb/Z+UtSzLHivl9hAEUY6I+7iHzY4dWa8Sfjp4QzRv7rOIJWl67AXplG3WwNvNyazgqZKkJGXnOipnRjEHVycHo0FhckiDzjQmInBtib0JaB8BGAqdr1lV6AT5eAArAPxow3YRBFEOUEoWXRq0reWHm/N7l9i8gQRRXKxtfh4UEYQj11JNb1gKKKVC4eZoHdfJfH/KksauBDSWZbcC2GrrdhAEQZQEJJwRzxJfDDRME2Ur5GazAHSTyhtLAmxL7EpAIwiCIIrHpy+F44GR9BD2QP9m1fB8E9tHyRFiisx9dmjvKy58HsKyc24koBEEQZQjhFMd2StfD25q6yYQMpRnBa/amTzsiTKSkYYgCIIgiJKk7Ikw6vGvoIvurOBSdvRSZaelBEEQBEGUGJyJs0GV8jfx+LvP1UWIvwd6hlueBLi0IQGNIAiCIAhoNAw2jGuDuiWQEsPWuDo5YKiZ05LZGhLQCIIgCIIAALSuaXqGBKJ0IB80giAIgiAIO4MENIIgCIIgCDuDKUs5QUzBMEwygFulcCh/ACmlcBzCfOje2Dd0f+wXujf2Dd0f+8bS+1ODZdkAuRXlSkArLRiGiWFZNsLW7SAMoXtj39D9sV/o3tg3dH/sm5K4P2TiJAiCIAiCsDNIQCMIgiAIgrAzSECzjJ9t3QBCEbo39g3dH/uF7o19Q/fHvrH6/SEfNIIgCIIgCDuDNGgEQRAEQRB2BgloBEEQBEEQdgYJaARBEARBEHYGCWgEQRAEQRB2BgloBEEQBEEQdgYJaARBEARBEHYGCWgEQRAEQRB2BgloBEEQBEEQdgYJaARBEARBEHYGCWgEQRAEQRB2BgloBEEQBEEQdgYJaARBEARBEHYGCWgEQRAEQRB2BgloBEEQBEEQdgYJaARBEARBEHaGo60bYE38/f3ZkJAQWzeDIAiCIAjCJKdOnUphWTZAbl25EtBCQkIQExNj62YQBEEQBEGYhGGYW0rryMRJEARBEARhZ5CARhAEQRAEYWeQgEYQBEEQZYkVvYGNo2zdCqKEIQGNIAiCIMoSt44AF/+0dSuIEoYENIIgCIIgCDuDBDSCIAiCIAg7w6oCGsMwtRmGWcowzEWGYQoZhmEZhtGasX8wwzBrGIZJZhgmh2GYWIZhxlizjQRBEARBEPaOtfOghQMYa8mODMMEAjgKoJqguDGAXxiGCWRZ9jMrtI8gCIIgCMLusbaJ8x6AeQD6Ajhp5r5zUSScjQBQBcAJ/fJshmGCrdJCgiAIgiAIO8eqGjSWZaMBRAMAwzBT1O7HMIwGwGD9YjzLsmv05V8D2ADACcBAAF9bs72FhYV4/PgxMjMzkZOTg8LCQmtWTxBEGUGj0cDV1RUVKlRAxYoVodGQey5BELbFXqZ6qgXAW//7iqBc+LuZNQ+o1Wpx584dODo6wtfXF+7u7tBoNGAYxpqHIYhnk4J8QOMIlIH3iWVZFBYWIjs7G2lpacjIyED16tXh6Ggv3SNBEM8i9jJM9Bf8zlD4XcmaB3z06BFcXFwQFBQET09PODg4kHBGENagIB94eAF4kmjrlqiCYRg4ODjA09MTQUFBcHFxwaNHj2zdLIIgnnHsRUBTQigxsbIbMMw4hmFiGIaJSU5OVl1xeno6/Pz8SCgjCGtTqA/czkm3bTssgGEY+Pn5IT297LWdIIjyhb0IaCmC316C356C37LSF8uyP7MsG8GybERAQIDqA2q1Wjg7O5vXSoIgyj3Ozs7QalVnByIIgigR7EVAuw6AG7LWFZQLf5+x9kFJe0YQhBS77hfOrgWeptm6FQRBlALWTlTrxDCMP8Mw/tBFXnLl/vo/F4ZhQvQJbFmGYeYAAMuyhdBFawJAA4Zhhunzor2nL8sHsNGabSUIgihTPLgAbJkAbJlo65YQBFEKWFuD1h46U2QygHb6MgdB2VAj+86GLo8aAKwBkAigtX55Lsuyd6zcVoIgiLKDNkf3fxkJviAIonjYi4kTLMs+gE6oWwsgFUAugHMAxtIsAgRBID8HYJ/lXIV2bHolCMLqWFVAY1l2P8uyjJG/lSzLJgiW50j2v82y7DCWZf1ZlnVlWbYJy7LLrNlGwr6ZM2cOGIbh/1auXGl3bQgJCRGtL6+MGjVKdJ779+83a/+QiCjF67R//37RulGjRhmvrEALJMcDaaRIJwji2cBuNGgEUdJERkaKhIKEhARbN6nskZsJaPNK/DArV64U3as5c+foj/+kxI9t/8hmHCIIopxBqbLLC49vAXlZQOWGtm5Jmadhw4YYMGAAvxwSEmK7xtiQli1bIjMzk18OCAgAUq8C0ABVmxSr7oCAANE1btmypYk9yq+mUjV0CQjimYIEtPLCU8p8bi0GDRqEQYMG2boZNmfSpEmYNGmSuPD+GQCm/MBMSxJhYWHYtGmTxW17pmFJg0YQzwJk4iQMmD9/vsi8tGrVKoNt0tPT4ebmxm/TpImhRmXnzp0YOnQoQkND4e7uDjc3N4SGhmLIkCH4999/LWrbtm3bMHHiRLRv3x4hISHw8vKCk5MTfH190bp1a8yaNQuJieIoN86X6sCBA6Ly0NBQWZOnNfzgUlNTMW/ePHTo0AF+fn5wcnKCv78/oqKisHz5cuTn55td57lz5zB16lR0794dtWvXhq+vLxwdHeHl5YXw8HCMGzcOZ84YTxd44sQJvP766wgLC4O3tzdcXFxQtWpVREZG4pNPPhFtq8YH7dy5c+jfvz/8/Pzg7u6OZs2aYcnPS8GaECKUfNC48tdee020/dxPPgVTrTmYKo10Js85c/DFF1+I6li9erXBcdLS0uDq6spv06ZNG6PtIgiCsBtYli03fy1atGDVEhcXp3rbMsG907o/K5CYmMg6Ojqy0Dm7sM8995zBNr/88gu/HgD7/fff8+tycnLYAQMGiNbL/Q0YMIDNyckR1Tt79mzRNitWrBCt79Onj8l6fXx82JiYGH6fkSNHmtwHAHvz5k1VbahRo4ZovZR9+/axAQEBRo/Vtm1bNiUlxaz78uWXX5o8BwcHB/bnn3822Dc/P58dN26cyf2FSK/bvn37RM/Zzp07WRcXF9l6Br/QnQ2qGqhY9759+0TrRo4cKVuu9Dd79mz28ePHbIUKFfiyNm3aGJz30qVLRfstX75c1bW2y/7hbgzLzvZi2SWdbN0SwtbM9tL9EWUeADGsgkxDJk7CgMDAQDz//PPYsmULAGDv3r1ITExElSpV+G3WrFnD/3Zzc8Pw4cP55QkTJmDz5s38spOTE1q2bAmGYRAdHY28PJ2T+ebNm+Hl5YXly5eb1T4nJyc0aNAAvr6+8Pb2xtOnT3Hx4kXcu6dLo5eWlobRo0cjNjYWQJEv1YEDB5CSUjSrWK9eveDu7s4ve3h4mNUOOa5cuYK+ffuKfLeaN2+OqlWrIj4+HtevXwcAHDt2DIMGDcKePXvMqp9hGNSuXRuVK1eGr68v8vPzcevWLcTFxQEACgoK8NZbb6FPnz6oWrUqv9+7776Ln3/+WVRXUFAQwsLCoNVqERMTY9b8k48ePcKwYcOQm5vLl/n5+aF58+a4fv0aNmz9z6zz4uB8027duoWYmBi+vEGD+mgYWg1gNICrFxo2bAgfHx+MHTsW33zzDQDg+PHjOHPmDJo1a8bv99tvv/G/vb29MXjwYIvaZR9wpmMycRLEswAJaErsmAY8OG/rVqgn7wngVxsYaJ6wo8Trr7/OC2gFBQVYt24d3ntPN7HD3bt3RebCgQMHwsfHBwAQFxcnMgm6uLjgwIEDaN1al3M4OjoanTp1Qk6OLunmypUr8f7776NBgwaq2vXVV18hODhYJFgBOk3wkCFD8PvvvwPQmd7i4+PRoEED3pcqMjJS1O7FixdbPQBg7ty5vHDGMAx27NiBHj168G2cMGECfvrpJwA6wffff/9Fz549iyrIfwokXwYqNQQcxXPFDh48GCNHjoTcnLOLFy/m/cVyc3Px119/YcKECQCAq1evYvHixaLtv/rqK7z77rvQaHReDnl5eSKh2xTLli0TCbvh4eE4cOAAfH19UZibjdEjhuDXjX+rro+D801buXKlyMw5aOBAzBnfH9A4AYHhfPk777yD77//HgUFBQCARYsW4ZdffgEA3Lt3DwcPHuS3HTFihMFzU6YoxyldCIIwhHzQCFl69uyJ6tWr88vCj/dvv/0m8jF6/fXX+d/bt28XrRsyZAgvnAE6bdawYcP4ZZZlsX37dtXtCg0NxapVq/j2cX5wGo2GF844Ll26pLpea1BYWIht27bxy+7u7li6dCkGDhyIgQMH4uWXX8aFCxdE+wi3BwBkpQBggRxDbVb16tVx4sQJDBkyBHXq1EGFChWg0WjAMIyBM7/w3Ldu3YrCwiLH/l69emHy5Mm8cAboJggfPXq06nPdvXu3aHnq1Knw9fUFAGg0Gsyb9qbquopDjRo1MHDgQH557dq1ePz4MQBg3bp1ovN+4403SqVNBEEQ1oA0aEr0WmDrFpjHfevOJa/RaDB69GjMnTsXAHDmzBleIyU0G9WvXx8dO3bkl6W5xRo1amRQt7Ts5s2bqtqUnZ2NTp064dSpU6q2z8jIULWdtUhNTRUdMysrS2TqlUPtuQPAxIkT8eOPP6raVtiOGzduiNZ16tRJ9TGVuH37tmg5LCxMtFw1MAAVfbzwOK3k78HkyZOxYYNuKt+nT59ixYoVeO+990TPabt27RAeHq5UBUEQhN1BGjRCkdGjR4u0LKtXr0ZsbCzOny8y/Y4dO1a0j1B7BsCqmfYXLVokEs40Gg1atWqFfv36YcCAAQZmUmlb7JGsrCxxgcLlio6ONhDO6tWrh759+2LAgAEGQldZOHfLMDyvli1bis5/yZIliIuLw9mzZ/mycePGmXeYvCzgsmWRxiVOub23BEEIIQGNUCQ4OJj3nwJ05iNhKgNnZ2eMHDlStE9oaKhoWSjMKZWp9QM7fPiwaHn9+vU4ceIE/vjjD2zatMmkZqikp2Xy8/ODp6cnv1ylShUUFhYajTw2TF0h7wguPfeJEyfi0qVL2Lp1KzZt2sT7m8khvSdCvyxLEZq/AfBBChyJD5OLpT0z915NnjyZ/3316lXRwMHHx8f8vHbZqcA6ewsooCABgniWIAGNMIrQv+zWrVtYtGgRv/zSSy/B399ftH3v3r1FH9d169YhOjqaXz516hTWrl3LLzMMgz59+qhqizR3mDDqMiYmRmTSksPNzU20zEV9WguNRoPevXvzy4mJiZg5c6ZBu7VaLfbv348xY8bgxIkTquo2du7JycmYN2+e4r59+/YVaUJ37NiBhQsXivyztFqtWfneoqKiRMtffPEF7/tVWFiImZ8vkttNNQb36v59o9v37dsX9erV45ePHTvG/3711VcN6iMIgrB3SEAjjNK3b18EBgbyy1z0JSAW3jjCwsIwYsQIfjk3NxcdOnRAhw4d0LFjR7Rr1w5Pnz7l148YMQING6qbnkoYbAAA/fv3R/fu3dGpUye0adPG0FwooX79+qLlfv36oW/fvhg4cCA++OADVW0wxZw5c0TC0/z58xEUFISoqCi88MILaN26NXx8/p+98w6vouj++HdJQkILvYg0BSkCCgiiggIqIP5eioqCDVFQBNRXBMQOiigo2AXBVyAKIr23INJ76ERCC4EAIQnpvd39/TF3793du/XevSXkfJ4nT+7uzs7M7s7Onjlzzplq6NGjB+bOnSu5F1rIr/3rr7/G/fffj969e6NZs2YuzgdiWrRo4WIgP27cODRp0gSPPfYYevXqhXr16rkEh9Vi2LBhDqcAgGlFmzdvjt69e6N567aYt3iN4byUkD+refMj0GPgaxg4/B0MHDgQ8fHSRdM5jsOYMWMU8yLnAAspzAH+Xe3vWhCEeyx6DljtGwcmKyABjdAkODjYEeVdzO23345HHnlE8ZzZs2djwIABju3CwkLs2bMHu3fvdsRAA5gGTgg5YYQ333xTMl1XUFCALVu2YNeuXWjUqJHuh/ill15CcLDTLyY5ORnr1q3D8uXLTccjU6Nly5ZYs2YN6tSp49iXlJSErVu3Yu3atTh48KBEkBTXR4tu3bqhf//+kn379+9HZGQkCgsLMWnSJM3zf/jhBxcBLD4+Hps3b8aWLVuQkpJiqB4CNWvWxIIFCxAaGurYd+PGDURGRuLChVj07n4/bqnrGg7EKHfddRfuvfdex3ZJSQm274vC8vV/Y/ny5Yox25RCkHTt2tXwACDgCYQwGxvGA0uGAFeP+LsmBGGeM+uBo64rjgQqJKARugwfPtzFJmjYsGGqdkJhYWFYuXIl1q9fj2eeeQaNGzdGWFgYQkND0ahRIzz99NNYt24dVq5cibCwMMP1qFGjBvbt24fhw4ejXr16CAkJQcOGDTFq1CgcOnQIdevW1Tz/7rvvxqZNm/DII4+gWrVqXrNJe/jhhxETE4OvvvoK3bt3R+3atREcHIywsDA0atQIvXr1wuTJk3Hy5El07drVcL5Lly7F5MmTcccddziWjhowYAAOHDiga38XHByMuXPnYs+ePRg2bBhatmyJypUrIyQkBPXq1UO3bt0cHrtG6dOnD/bt24f+/fujWrVqCAsLQ5s2bTDjq6lYF/E9yoeEmMoPAFCcD2QnAwDWrl2LV199FQ0bNjQkyIaFhbnY4t2U2jN/mqCl2713C7L8WAmC8JDMBGDXNwHvcMPdTN5eHTt25MXRx7UQQkbcNAhhNuq3105HBDYZV4CcZCC8PlBZW+D0C0baWXE+kHQaCCoP1G2tnk6J6ycBWzFQ725AZDeHkiIg8RRQLhio5xq6RWD06NGOoLw1a9bElStXTA0CBE7v24xWm58BJhlfXcHrJJwAZj8I1G0LjNytn94bzP8PELcLGLIGuL2bf+pgln9XA8UFwF0mHUUCmUlV7f8DqH2WBoT71uh+4PI+YORe832UxXAcd5jn+Y5KxygOGkEEFAEwjeVPbCX2H8YHjosXL0ZcXBxiYmIQERHh2P/WW2+5JZyVaYrygeXDgJ6fATWb+rs21rBkCPt/MwlohGcU2Jfic/Q3gQkJaARBBBAczM7hzZo1S7KEF8Bs2MaPH29hvQIJL856xO0CYtYxLegL2kGWCTe5egRYNRIYvhUIrezv2pRxAnsGkWzQCIKwGA+0gB6cGhwcjNtuuw1jxozBtm3bbr7QGoHgJEB4zt8TgeQY4Moh/bSEdyglrxJp0IjSSW4qUL4SEByqn7Y0EtgDO2VsNuD6caBSHf207qJgM+sa7NdDhOmPssxNZJsceJQS6eCmxv4MArydkwaNKJ2kXwKSz/i7FoQYWzH7n5Pk33q4C88z766Uc/6uiTZe/aiQ8EAEOJf3Azunu+7PSzf+bgjaaN6mnc7PkIAWKNiKgfR4poUgjMHrGHjyNqC4UDtNoOH4Pgb2yO6mJC8VyL7um7IKc4GsRJMnBZLwpNA+eR5Ivej7qpRa6B13i0WDgX8mS4WxjCvAtMbA3h8MZhJI75I6JKC5S3Ehc/13l5JC9ieQmQDk3gDyzAUMDSiK8gLLKyY9HkiKDqw6Afb7RIJ4wOHL6Y55fYAZzd082Rf1VClDyw7uwGzgh3bOUCw3I6kXmXmFJ3ClY3otYMljS8pJ7l+6fWWRmA0mMwvsZ1CmBTS3Y8DZStiHP1F9eR1dEqPZ380Cb2OGr2lx/q6JkwL7Yt1WqrF5HsjPdL9zLSlm90kI+OlC6RjZ3cz4JDZkwjHvl+EOnjS/+P3sf8oFS6oSkPzQDvj+bg8zoXfcMJcPqAvEkn7d/s4adaQpJQ43ZVZACwoKQkmJm5qVG2T75ILwUSs0aWBdUsxG3KUlMnl+OpB6gQWTdQdhWtbsfSpz+G9kW8IDQSXG1kj1mIh+wJo3fVOW1ykdHz1cP8UClqbGune+MPDzGJ4F0c33YrDZhOPAtQAdDBhhbi8goq/yMbGA5hhUmWyDga1AK7sCWsWKFZGd7eZHsrjA2sqIyUku3apvs1Uvsq9LmW3WHscAgtG6lQjT2iUmbNtsxaLnauFHLD+TLV5NWEp2IVDxxgnfFHZxB3Dkd2NpfTk15k4ZvqpfSTGw9yf3+uGcG8AvXdjv0+usrZdRhPuUepEF0V3xmvfKmv0QMKeUrPggR2hHajNVnmjQHP1wYH9ry6yAFh4ejtTUVPe1aN6iuKCUa1fcbfAWj769KUSbJf0yM2ItyrU239QLwI2z1ubpd9TagW860hIbj9TUNITH/+OT8szhCw2VJ2X4SIN29A8g8kNg97fmz132smjDzx9noT9QNXco4+gK+jyQdR2Y0wM4F2ku71JiB1hmBbQqVaqgUqVKuHTpEtLT01FcXOwb2xMj+LIeBdmskXuMD6c3jNyfQHmWgNNJwYwtHG9jHbc3tIBKZF0PLG2cDx8fz/MoLi5GelYuLl1PQ6Uzy1AlxSJD94wrbPkkdyjMBeL2WFMP0+g8AH++X0I7dWdqMFtkmuC3aygdwoHfEfeXUfOAY3+6Hl8+HLh2BNjzvX2nxndI4phVOqbjy2ygWo7jUKdOHWRlZSEzMxNJSUnGtWnpojhPGafdq4CQh3B+XprTDusGD4SYjIIuz8/wefbRW7U0c+fJ4XkgIwkAZ64ORXls+i8kC0gyMW2od70lRUCWPU3aGaBckPG889KZFrNiTfYceJ552IZVY0vg5KUBoXlABYN2c9lJ7LwUsMW+M5PY/zSFOuVnsD8uhdmrhV4BKlRXztedZ24rAXJT2LWJ74mjHTTSPl+rTFsxuzaBcsFAqskxYEYi63jTzkgXS7eVsLy5ckC6m++cBkFBQaiYE49a+yajSspR67rvb1sDzfsAz/1l/twvbmH/By0EWv3HqhppY4nxdCALHrzKbw9JuQBsfBd45g+gfEWTdSkdwoKl7P8FKM4Duo5RTyMOo7Tubfa/3XOi4zbXWQmt9qvomBPIbbUMC2gAE9LCw8MRHh5u7sRJ94l+mxjFxR8CqjcBKtd25iGcv2E8cHAO+/3cUqB5LzZS/OVBoP/PQOP7jdVJrT5Rc4F/1wBDVpk7zyiFucAX9wNBocDHJgKVnt0MrHgGaNYTeGGZdlqbjamy7+gFfKZT7w3vAgdns99jzwJV6urXZenLQL22wNZPnfsmZQAXdwFL+gKNuwAtHmfTK/eNBh77Qj9PAJg/nq1xOGQNUOsO4JuuQOV6wDgFZ5N/pgA7v2LCYH460Pl1oM805XzdeXZbPwN2zQAe/gh4SLRWpdG8tNJlXAG+7ercDm8AvGPSU/nL3kBBBjA+FqhU07k/8xrwTRcgNBx4P95cnkY5vA+wSnMm5uxG5++lLwP12pg7P/GUTEAL0I9KaZg2EtdNr57LhgF1WgEPjdPPd/OHwPm/gdjtQMvHtdOWhvvkbTZNYP81BTSdGQdPvPOVBDmbjdnrdXsXaKXimOBjyuwUp1/47VHg14cNJLS/uPtnMjujNW8AS14C/hzkftnrxgCx29w/3zBe7HQOzwMWDQKOL9JPKwhnZoheIRXOXBC/1LLrzM9knmFnNkIdA04CXOkwXvU+N8H1K32Ao1cwIdkdAsJJQKt9+qjtenQfTGjQTi1jAVFN1cmI0FBK3/FTy73rcSrHHQFNTYOWmwr82kOc0J6H6BkU5QLXT3jXacMkJKD5mgwFg1CbTRpMVWg026ey/ynngX9XAWc3eb9+ZuF5e9097GyMTK1kXGH/M696VpYVyDsHwVh/59fs/9q3mcAWs176QdEVwGT3oTSNsq2oq+P2yPIqTfdBoDTW2aOF7n01VedBOXoatCUvAVMbS/dNqmpgWTk3hC6hfKX7NvMB4H89jeflbZLPAMteAVaN8l2ZugIar/AMVdrGtSOyZErPK/CmnElACwTmPw5E/SbaYW8ogbhOGM8DOaLVDhY8BXxWw/mimP0omQlXIa6Dvznwi/bxw/PY/7+ecwbvzUsTOQzYr8FWIg3E6NJZB8C1GsWS9qrzofPXsxfafEE2s5u86fHgPvvsGXlBg/bvKmZaICdul3a2ZrR6RgTZpGjgykH9dL5CiCxgZnCcl+7ZajtGBDQ5qvdWZb+pPHyP5QIax3GNOI5bwHFcMsdx+RzHHec4bpiB87pzHMer/JXiSHsGuLxPuq0l7GRcYfZeahRkM3sdcV7yyN556cxw3R0OzwO+vh1IshtqX9gqS2Cy01z8AvtvJFyE29N/9vQZV109FfMz3FgT0SSCAf6yl5mtIcAM6lMvAn9fLisBAAAgAElEQVRPAr66jT0TAG6N3rISjU89uPvxTI1l8ae0M9fZBrv/F3eqZ6E7VeQHAe3UCtbm4w8CX94KfGvUhsyiuvpSKPXo41QKpjglGjQ3z1PCrb4pQAdfBdls6UExjqqaaB/TGgMrXnVuF+YC05qIPC5lyPtit2zQVOrn0q4V0gXCwF+GpQIax3H1AOwF8DyAWgBCAdwF4H8cx31oZVkBS2K0uaj4mo1C4di3rYE/n1E/ZW5v4JtWzu39M4EfO0jTzGgJTL/DeB3FnLcLZC4ClYeN29ASUR7a4Hx7JzBPZsD7fTsDayJaGNbjzHr2Py+VLRuz72e2rTRqN5rvjObAj/cYK1/MrhnO8rVIjwd+aK9jnwdjdf2iPosMfnqtybz82HkK2pPr9uC1uTdc09w4J9UsA17s8L14Lzyps7+mOIsLgatHlJO64CUvTugNLJTSyrYDhV8fBr5pKd0nXBdnUmSIXun8fSSCzSJs+UQ57Xd3SftipfWKJWFSTNig6cVXvHrEGTuzMJvZFAcAVmvQPgVwq/33iwBuAXDAvj2R4zgdH34Gz/Oc7K+dxfX0DjYbMOsB4M/Bxs/Z8rHCTp2OQ0vdLo+6HH/ANU2xB1M0aqNXn44+PChL7mqdZ2DhYy1bEU/hZaFd5GWIO6GsROYJrITRpafE+W/9DNj8gf45OXZtq7zdXT8lWy7HxHNRXYc2AKc4Hc9fo7v8qSMws7N3yvf3lIvNxpxfJDaUGvh6inPz+8wA3MgaoGa8OM3gllYv8DQ2AJSXMnRXQBNj0wljJR+kKglgYsGRt8H1HhrUoAnXwfNshuPXHsCGsc7jET4Ka6ODZQIax3HlAAhuhqd5nl/A8/x1AN/Y94UAGGhVeYGJvbFcMhFccu+Prvsu6tg7mMGTF0ozPz98QI14Sl3cxbQZRlATdvxBUgxwaR8Qu0M9zewHmSdwoPBLF6ZZEzAltOt86APJScDR3nTq7CIkW1xnX9wDJQHs4Gxg0WDgpE4YHF9pguTC0NXD7H+eihZagkEN2nFZ3Drde29iirM0htlwCGiePGOT16vUz4sDd3uiQRNPSQvmIf+udh5POG60ll7FyjhoTQFUtf8Wz3+Jf4t6c3U4jksEUAPAVQCrAUzked7I2+dfHC+chy/egVlAn6keV4fh5gsVu4MFMm3SVXZATUjyRWdjQEBTGvnEH1QOHumWsGO0ozbJIpUQKmJNkxXrlSp9FPQ+FEYfrZlpSbWOVNeWxwcDALUylY5nXAXOb1E5TVTXq0eAWzsop1NCaXpHKV9fIHhPZ+usOOKzEDEq5Rh59Yxq0FaOMFklkUbGMEK7MleUfzCgRdbNwqQTkVdt0IQ8ePVzAgAr1Su1RL8zVX7XMZhXHTDhsTGAtwDs4Dgu1LPqEab4vR8w//9c96t1REY6phNLtQ3E9XB35LnkReZtajVxu4HP6xkwnveA+P1eythgp3RgtvpixS6YeS4GNWgxG9iftyjI0vfKdLQ3hToveApY+1/n9s7pyu3T7Dqsp1cr7PShYKYnyCu+g37SDPlkWtGgk4ChusjNGNyqkLO8bV+ygUJ+BjD/P8CBOR5kqFaOBVOcZtuFrkDniRenfbu4gDlqBSi+CLOhEd1TQiKYMHYHgIoAOgEQJsPvAvCsYuYc9xrHcVEcx0UlJxu0w/EaCkJLsp8Ws478GLh+0nr7FYeA5oaX3YrhzEDc/cJ1yvYx8/+P2fP9u0o/rS85+CswqZqO4KHysV3zpnTtyI3vAmvfYr+v6UTZlz8XWwmw7h1lBxChWZYUyezYZNqRv55lf8J2Ua7BqSyDfNmAOYpooqFBk09r/jNZpOn04Mur5antVbT6C8OqVCsqoo6LMKQhQMvhVTc8xE/BZxNPATumAkuHslVI4nYBG8frnmYao9P8jvRKAn4AatAO/aquAQ8ArBTQxK5N4rWTqoh+q0pQPM+f5nn+R57nz/M8n8fzfBSY04FAJ5Xz5vA835Hn+Y61a9d2q+KWIW+UJ5YAP3cCzv0t3Z/4r/frsvcHYN7/wRL1bVYi03ylXdIYKfIq+y1EKPu8PLSHt9G5Jj3jVy8UqcmGcSyDE4tdjyl2VKLCjvwu9bwyg/zZ5ySx+H4rX1c/Z/OHzI4tSzZ9ptWOdk3XrkdaHAsuKn/v5OTYu6zs60BEP/VFzR3ff6XuUqGe8lh38t9mMTN1nJfOrj3yI+v6GaODPLNdzerRUrsfdzHlxCN+JiYEBqNhNszEQXPU23g1VCnMAUoK1I/P7cM8KN3FrKOU4n0wq0HT6Vd5m2s5HMcWVd84wblv3Tuu9pPCdbgTh9OHWCmgXQAgBGMSxy0Q/1YdgtudDOR4yyfaeta8Zf8wihA0DnKvmI3v+qZOgPYLFW8wEOKM5kzz9f1d6k4C4hdl/VgWSd9bJJ70Xt5K6HVO3vCysyJLd+zNWCJ3C1TerSjA2i/wot0pwuXj4YGTwBq7xm+hzrT2kQjn74s7gCsqTiNa2gNvDUgkbcrE4Cd6Bfu/90dgls76vVrlxu2ShjRwJpDWSQmj9+ToAmDJEDO1c8Vmc4Y/0Xtptk8FMry0jque85QiFrQdyYyGxvVf3mvAyQPArm9UDpgU0MTXtvtb+y6rNWgq0+yrRkoDiUf95gwcbgZfLmulgmUCGs/zNgDCkL0Vx3HP2+OivWPfVwRgKQCIAtDOF2XxP47jPuI47g6O40I5jrsHwCTRcROukT7k8n42Yj0SIe3wAfV5e72o1JYie6HEsZoiZSE+spPZtUyqClUErYz85XF4rvLAof9pvxBCOaY1Yf425lQzNFVy9w4A1r3N1mBVRHQtavaEB381V55ah2rE20poi1Z4uInz/n2Aejr5mpgnl7imObEUOP6na74OtDQFJq/hwGzgU/uqHFraN0+8Y81geurHg2m+6JWsTyjI1k43qapoIMwDNlGkej37qO1fSretsF0T+n+1fvHLRizeoASZqcb1k2yGYtsXwNca8SkP/gp8Wl3qQFLO7ufHl1gzUBTHOhQEK3Fdjdqgie+tYOOldb+VzDF0nZfMeHGqpdNIL3gH+xGrbdAmgnleAsACAAkAhOBAn/I8rzV8qQFgMpjXZz6AKAAt7Md2AlDoPQOAqLnK+202awwrPUGp7V0XuQ8Xy6Z05OuVaSF/eQ6aMEwVylFbLqkwh3V6+2XH/R0Pircp2watHAEk+WDa2gjFsmmOqLlAtIKNnKRDlD3L1aNY+930nsEy7dMEqh2qhkG5wPktwFdNRTZdJoQQW4lzYFGYIz0eu82ZpqQIiN1uzlFFsli20ekd+3tvVsjc+C770LrY8tmFEPmzFZhUlU0XAq7viHBOUb7zOWmhZSNqOJq+nZQLxqaaAWD7NPbfjIZLLshyHNOSTaqq7QXrOF+UJna79sBUjUO/Sbfl96ggw3UgoNSPRfQFdkxzxhxUYvMHrM4SoTSI/S8ukH5n9s9ybS/iui1+AZhchzk4KWpKITWeNy2gKdx/rfaTJVq5QFh5RS8wtq1EGnYDgOkBir+/KTpYKjnY4549AOBPACkACgCcADCc5/kpOqd/A2AemICWbT83GsDHAHrxvN6EdICx4En/C2hKZYvVtvKgrWYat1l1depF42kF26B9P5krw9vE7QK2f6F8TPzRd3cZLTFa38KCLNclqwAW/+1zBUfppS+J6mXPWGzHpdRx2oqNP+PPa7NOXk2A4G3smYq9XZXsYcQR+s3YXYnX+/uiPnBpr/R4ViJ7HyfXAn7vb85RJf2S87dSZ250GtnQh0DFCWb3tyy+3/8eVj/16AJ2j+Xnfl4HOLMJmFKXPSdTQqNcy2DwXKEMIUj2yaXGixSbXeRnMLtXAV2hiwN2fMV+5qaot0cl9Kb/DA8+RNu5OkGwzdwXNYT3KP2StK/f/IFCXyCq2+m1zGZtbi9gejNgr05fq+XJLEZYqknJUUGzPxHlK8Qg07NPXPyCq4e5YYHLxPvoR6yMgwYA4Hn+MthST1ppXK6c5/mdYJqym4PYbUD1Juz3taOuoyhfIW+wS4dalLGsY8pV+OAW5QMhYey30lqbcg+4rESgSl0NT1GFF+b6KaBSbXaeN7AZnL4UhLKrUe4vo2WULxsA5au47r+uYZuXdonZEJrRApkRwqc3A0IUYs0BTKD8uilw72vOfXt/AB5y09tMrxOWG0vrLuVltFyDTgKO+2ZSg8Zx7EOoZLMnESpV8v26KRCqoAU6vkh0Km9ea+DuR8+hoTdh97j2LWa4XbmO0z5t8CKg5eMK2hIFA/FyQUBJCWuPtz0EvKS1pJgFZglywS3jqnP/V7dpn2toeTuNsgBZLEex2YLBd1eYxov8EHjgDf2ys5OYI0qFaq5prhxmg4gBvwCH50uPpV0CihQGlZ6QYjAguRYBHizYj6qdMoAwujm2UMEOQYcrUdrHDYXvsKAjvrTPdR/g2rCVDPeXDxPlrdDU5GEbhA+pWqw1pcv5pQs77/IBz+KRqXWWRhW3PrUrBFCosN6rllFrpmB5YNS7yo2OSy3WlxAWQ77+5pxu6nkF5JI5Sho0hWS5KUDSaTc6f60wMgbzKlBoA+IwMJ5ORGgJa8Kxq1FscCbYPxq5D+I0G8ZJnQeu2LVq8rrzPKT3hYPkGelNZUvqpVdHgxo0QcMuf4ZW2jOp3U+9mRqPPInt15N4Evj+buU0wjfg8l7XY9/fpbxqjiIeaK5M26BpoLY+sg8hAc2beDLV9b9HtI//bI86kp3MAqYqwck6LF0U0s57TDmpkRHauUhZXQxQkA1c2KpShkYec3upTz8aQa3TsRUH/CjLwZaJ6se0Om/FKU4LLQoEzYdgLyMgiX8mx4RhvDvPR2+xdiXkbfjGeWWB6H+PADPvk+4zU0e+RLt+qbHO/OJM+k4J71RqrP5yNmY0bbmpzmXKji6QOqd4GrewuIBN0yq1SfHC2xxn0pzECxo0Abm271fR9LTefT2hZm4tPHOVwaDu8/LkekXnqgku7pj0GI0kYBiT2t7cFPUkls02uY/lU5xlDiUDbAFhes+bzHsMSDmvftxrRpAGXvaSQiDhBFsqJli0EMSfz6ifs2okcHqNvQhZx653Ld6IL+cyrRLAKAkLAmbtIC0NBmxvKw4tnsHy5bHRxFw5zPLlbeZsjQQWv2D+HDFR85iXrCbuTHGCfaDPbtROe2o50HYgMP9xc2UIQo6whuokD0MJ5NxgHriCp6uA2L7V07a0fyb7a/2kdP/lfVLTCbmhvB48z6bfjQjrZhxgYnewusk5Z/eK1bPHXfGq8n6hL1qotqS1Tv+oN0hQE9jT4oAzBlbzENqWmWfwW0/WBq36TpnNx8UOO7AgAc1TtIID+iLivZZwJlf562GmbRu9ttkPsv9P/aadTkAQzlghsoM6FfQkEKMa/hLQrJartTrNKwqjWCt9chxTrwofiOQY5XN4HpjRQrxDelzLYN5biDt/XeHMAzKv6afJuaGfRgn5c00+y4SJe14ycK449If9/+IXlIURcQO+epgZfN/Zn+Wx72egvnz1BgPCrBDjTUBuhL/tC2aDJkY1rpe9zLVvA6cMxAdTzUKh3r/3U06rKlgZQGuwYpajC5T3z35Ief/M+40tVeaIF+nPiTlZx5mk0r/IIxgEKCSgeZNAWJLIcFxBk6N9s+mF4KGmyjB5/8wYoV41GFJk1wzg9h7Kx265W3+ayF0sn1XVaAhKXo0zH9DO7uxmz6qjiwexvirV0Q5X4C7e1EIWF8BxXUYGBZsmAPdprNBgtE6CqUTiKdcpaAf2euWlARf+kR4SFlJ3Lcj5M/0SsymblMHsTiM/NFtrY+QkAQWZ0n1aoRp43oTgYyaEjIUc+R1o/phssKKCI2CvGva6CiFZjGJ0HVl3oxZs+QRoIVr3OTtRf1k5NeQatNWjlNMpDioCDxLQvIm3Pt6mMCihTWtsLnKyWQHNHQ+e3BQWn+j27mxbT32dZ6L+v6oIXXL2/gjc1t14vt7AHc87OWZPz9LR4mhNU2tWwmSoBiVUhQI73hDOAJi+iWKnlatRbJ1TNY787nzGRrW2cmHJCGq2hYpxDGXhNfb+4Hk5qqFY3BB05IKAWx91DwUsb9unrnkTaGUwLIyeo5KVdb2wjdmPdRctqeQQ0NQEfRX2fA/EiKZQ17+jntZIvRz14QMi2KwnkJOAN/H3UhEcZ/zDbrauG8f7pvH/3l+0oXMtGZe9Uwe1D6Y3BXCxPZkVmthf/TAlKEc+/aSJhpOAJ1NSnpCnE9dKjvi5/T0JSNOwPSrMhlODZnB6+Y8nzNUHYPfRSMBaMeJYZAILn2IhJdQCy8qXt3NWwOR+DYJCzJ8jKdKM4wYvjbfnWPHABw5E7thYKsIzYcgK/hjAnLKKC5kG/kqU+xo0QHklAXcQOzAkRluTpx8hDVppJkbPcJNjI3Nvseg57+UtZ+ME9ZUHzGK2MxBH7vYHpcWLVI9ywca1Q7N0plj9geqyWSrorQUqRrxChTftHvkS8/Gj1AZ5B2drnQQX4WXJS9KQHwLH/zJXHwEzTieK8ObeLbFx/5e3Aq2f8NG7aZFBauRH1uQj5of2QOYV5rnc0x7r0x1tvzfi0Luz/maAQRq00sxfz/q3/GwLDVe14HnrhDNAWSOghacefx5zEwlo7vJjB+vq4SvMaFiLcs1PcbpDbopx4Xfla2z5o+iVysc14w4qtFkl4QxgS6X5A7Ox9uQaYLX7UpbIFJkbeKJB80abL00e+CqQBs0s7hi7+wt/a36sokAhKKsnlLJVwwLC2cQKboIO02uIlzXzZvtU85p1Byv7F01vdC9xYJbxtIW5yu/h2U3W1UeNc952yLEIjwQ0b2jQ5nueR9xuoElXz/NxE9KgmeVIhL9rYBx/28BZxdSG1uYXiNNnWhTmAJkJ+ukCnVLi2u53vPGxErAy+GZZErh3TAV+6ui6/2a/B7HbjacVbBv3fGe+nEAdNOuaEXkX0qCZITtZPw1BWM0vD0qnEoibG28KaFait5g1Ufq5aGIJO6PhOJSwBegsgSfXZAGkQTNDAKzNRZRBSDgrW1wzGKPP32gtk0PcHFze7520cpTWFg4E/OxoQAKaGW4WWyCCIAIX8fJFBOFPLqms86yE0ookhEeQgGYGP6s7CYIgCIIoG5CAZoZb5OvHEQRBEAThVcaU/qCz7kACmhk8XW6HIAiCIAhzmF0+6iaBBDSCIAiCIAIXU8vEWUiFGv4p1w4JaGap1tjfNSAIwp+8sMLfNSCIsoU7wW+tIKSCf8q1QwKaWUZ54Eosp8/X1uVFBD4t/s9/ZXuyzNLNSI3b3T9XzZs7OMz9PAnv0vUd/5Tb7nn9NN3eo7ajh1UCWuV60u0HxwFP/g8YtAB4fY9rej/3mySgmaV8Revy8pfa1gghFl7nzcCLFqy7V6+t53m4yx29/Vd2ICJEPdfj/jdc95WvpJz20U/drw/hXR6d6J9y7xzgum+cbLH6bu/6aNF1D7itm7n0r0QC/WeyPyuw4lvZbQJQubZ03yMfA3c9DbTqC9Rr49xfoTr77692Y4cEtNJGy/+4f+7gRcbTjtoHvLZDuu/O/u6XXRp596Lzd5VbPM/v4k73z/V0hF0uwF71F1UWzvYm9duz/72mACUGBbSHPwY6DJHua3S/ctpG97lfN6MElfd+GaWdJ+YADTo5t6vUN3HubOn2wLme1UVJ81O5DtPY9Pka+OCaXfjwsYDWYQjT3IkJCnX+HiBap7TnZODp+ebaXqPOQPvn2Z8VCE4CSjZhcq2YGq366WviRh8E2r/A+v5JGUCbp8zV02ICrNcu5TR/TP1Yq77O388vB17eBASHqqcXuGuQ1Oalcl31tI3sa0yKO6fwW52/Wz6uX55AcAXglrvZ7yYPMg3Sk78CL60zpgmq3dJ4Wb7g7ZNAw87G0996D1BR1BmEVfW8Dp4s+i4IF+5SsaZn57tLw/uUhcsat7mf5wNvKe9v+oj2eS+uZO/dA28AJQXGygoJA/r+ADy31LnPn97cHyeXLk1dzWbW5fX2SWPp7h4kFarfOMT+17nTfJmeCsRqTaVVX6Dza05trFkNWrsX3K9TnTuBfj8Cd/Zz7nsvHqgvCiPVyn6s5X+ALm+xvlCY7us6BqjWiP2Wf/Na9QVG7tWvw7OLgRCZJrp2KyCsmvo5r0QCrygsTm90sFWvjb6AVrsF0P/ngInYQAKalQxeBPznO+Cuwa7HxELTHY8Cje9XfynfPgnc8zL7Xf02acdSuwX7Hxruet5DY9n/e4aKduo0tLeOKu+vUpc10lH7gWf/Apo+zATK2x4EyldWzy8oFBh9CBgW6dw39oxrurufZS/cuPPOfeG3MgFwhEjTdHsP9sLcNUj7OvSo1sh574wgtzMKrw+MMLEunRKPfaG8v1U/5f1i5B2LWUP16k2cv183ER1czJP/c2oSu01w7q/aSP2cJl2BciGu+8X3t8G9xuvw5hGg12TWRh4cC7z6D9vfUEF7JR79ht/Kpi0a27Vfd/Ri/19aq18mxwHNe0n3vRMDjPlXui8vVTsfI9M9Yw2sIhCoC0sr8YjKFFH5KubzqtbIuC2S8NG+ZygQau+v5AubCwNayXlF0m2ltusNhPeh2aPa6Wo2Y8KU+H02S9OH2f9K9um+ziOBsHA21SoQWpkJWk/+6nr+Q+OdU7dirXHlusDA+UDd1tL0b58EOg6T7qvdHLh/tCxjnn2P3jjsWmZQCNPK1W7Bjj/zh/OYkQDywYKxf2AIXkYhAc1dhDlqgUp12DRSx5eB/j+5phc0GF3HiHbKBLT67ZmKtVoj58vDcVJp3jHFyblqRW7rxhq42DA1VKMjrNVc31i6TitnBycg7ugcWgsOGB8LjD/HXj5B4xRWFaiioILu9xN74SrXdnYCgxYwAVDQ3AFM/d/+Bam20WEPYfJlExahbvuMflqhw3z3IjAhjv2+5S5z5cmp1dz5u+dk9r9qIyZoqCEI23JvomaPsOCNgnZKTzsgFoLUNKBy2xiBZ/4A3rvMbDWEey9uN1qPoctbytMc4sHJkFVMiH8nRiMjOzWbsv+33A088gnTdI49o28jOPqAdLv/z0zAuu0h9XPkdjfiKf7wW4Cqt0qP602Dt38eePuU+vH7RrGBkfAxeeOw8uDm1o7a5fiC0HDW/gThfHws8Oo213RqXnBaNkV3P+f8/d/j0mPiabhXIqFKPXsfIggjgKvw9aLCIMcmSxOkYCT++HTXge07p13TjTsHx8txe3f1ugJwfAvEAs/wf6QzLwBw92AmTFVXiCYgHjjL75uYxl3Y/8p1mPDU63P7AdmLXLe11Ob6brvioVwIG3gB0rZYv73y/arWSHl2qe1A6TbPM01dLQWtq7j/r9VMej/bDJSndkUQ7MXf0vfi9c/zMySgucMH16Qd5wcJUvV7kMKoK6wq+8g9/Ilzn9C4BY1bxVrKWh5B2On+vtSrJFz2gQgKYR9OcSN8fgn7iMk1Be9fVdak9PgQ+PC6634xYpWyowPmgUo1pVOBH15X1wiIX+S7nmFC0K0dXNMpaRkFw+3XZRqtD64BLRSmcQXtmyDcPjiWPQsxL60Fxl8QlWsX0CrWcBXGAeDeEc683oiS2qsJDN0g3RYLqmF2Dejt3djUwuhDCuevBx6byspQMlav2sApzLZXmPJo3NX5u0kX1+MC/X9m1165Dttu3od1Xr2/ZNsN73U+V6Gjs5UAnV9Xz1Nop1w5oLeC5lD8XMtXYvcm3C7gNHuUvV8fJrJ3q8dH6uUA7NzyFVk7kmB/D/r96DpQCQ51FbAAYOA8pjkYewZ4Ybn02FNzgfdVFq7vP5MNZvSo1lD9WK8p7P+Ei+zdqdVM2maEPuZ2kwbbzXpqHy8XzK7rte3G8wwOY+3vraPs3Eo12fsrvz9qXnBqbad8ZeCJWcAnqewdFTRFgsbzAdF70Kgze14Cles638OGnVifIhaq5QJaSAXg3tec21UbuqZRMtVo2Jn1s2LhL9xu53brPaL61HH253qDQuF9EKZU2z4DNLjHOVAXEAZkbZ9m2uQ3j7B3ZEKcNASUkobtzSPs/ohNXao1cvbFetOsj09nzyS4PNC8Nyvztgedx7W0myEyMweeh+vITqH8D6+zfkBOWDh7R9+/CvT93vW4/NvWaZhrHcMUZqECDBLQ3KF8JalEX76iawNUIqyq1Fi77p3AxHRmMwGo28WEVGDpuk1wjjw5AM+L7GImpkvP4YKYEFGtEZsGEjQFQeWBTq8yrZiSDVxIBf3YL/eJVNNCfZQ+oiEVlO+LUqcnF4Ket38clUIaNO/FrleuCSpfCRj8p1Pg7TgM+CTNafjb8nF2Xp2W7FmIDYArVJfaP9wnV7/badwVqN8BaGcf5d/ZH6h1h7T+E9PZB0ZLKGpi79gE4bGCgu1Fk67sHj7yiVRb2nmka9oaTV33DV2nXr7AJ6lMuKtUy76dBjy7iHVe941k1yIWEoQOjrcx4XFiunLHLnxIeF6qLfkkzTVPSX3SgOeXseMhYezdavOk/nUAbIQ/Md05rSYIrU0eVD9HXnabJ5nmoEo914FWULC6RlpJiNeyF1VC6BvU3kFxfhPTpe3g1W3SPuCTVKCu3StN0FQI08FyHvmEXZfcJkhclvAn0PVt9l9+T+T3R01T1v099sEXU/025pwknCcMCiamA88tYb97fMg0la2fYNttngRG2s8Jqya1G5U/kwftsxcdX3Fei7gP7DXZVUCr2oC1i0/SgI9vsPMETfpzS5mQIuQ1MR0YvtX1/Inp+sbyj3zM/gve1ve+yv7LI+gLA1COY9rkmk3ZO1KhOvDAm+yYmr1qzabS+yNH7MWohPiZAK73V0tAa/Igc4oQBMfCbGPT1WrfEIC9o6GVWRv8KMlex2DXb8OghezZ6tUxAKHgSN6mbhsgMVrZRgZgL1r99kx1L4nVI3z0OGc6QNTAONmHUzYamahiD/Nxsuu+xznawGsAACAASURBVKYBmybI8tfg7kFsFLV0KNuelKF/Ts/PgC127eGQNfrpHddjvw8dXwGO/K5w3I4wEuY44MnZ7E8zXxnFBexF17uWl9c7f4vTcpxsW+XDNHQD0xTVuF2aXm/0Kja2zhaPKO3XExbuzG+SoO3i2HR3boprft3fB06vc/2AigcQSvfq3uHAsQVMeyAc7/kZsOxlZ5qqjYB8e13kAraQf2hlNqWXcEK9fIGaCsKnGhwHPPgO+wOMtU2tsg2XKzt3xC72If/lQeD6CeVzarUAbihMYaohNljnOGeZvT531T6XC2KCZuIppgFVuw/i/WLt3iMTga2fOssS6D8T2PyBtvZUTKXabDq0Sj3Wx3UYAuz+luUpb/NtBzqNz8WIy+c4YKxsKtzoR7fTcPanRM/PmNCXehGI/FB6zNEuZOUEBUuFFKGe4Q2k9lVGDM4fHOs0dZD0I6Iy9dpyu2fZn0CV+uw9uH4CyE7Sr4PaoEmPhp2B+APKWn4BjmNOETVuBxa/wIRx+QBI3GdWa2S8jUkzcd5vxftVumzQSEDzhPtGq3tidngJOBIBPPO7/gemQnXgY9kLVMuuGpfPxwudmtAIm/cBWnkQegMA7nsdSLsIHPjFeyOMLv8Ftn0BFOdr28UJNLyXefUI2hA9L0ZPQ4AUZHp2vhpvHQMWv+i0kVLTqqkFPxUoX5FNL0T0BR4a59zfewqw5i2p3V6fr4BL9qCLA0SG6d0mALl2wb37e+zPLPXbu3Z8bZ5kI/vfegJ9pgGNHwDORgI7pjmfdbvnmaZRzGNfmiu7Yi3z9fU2bZ4CTi1n1wy43pvXdzkFZoHxscDc3sDghcCWicCZ9dBkwC/A2Y2uH3q9D/9/vmNaRLG9YPM+LC8lQipI65+b4irAmw2dUKMp8L7M1qezfTDVegCw+X1m01q+Musz3cKDEBWdhgMx651TkDVuY/dA/szM8I7Kwt7NHjVm/yrGE2/CsQp2cd5gmIYtoJw7HgU+EpnQTMoA/hwEnN0k/fYY9dgVCCrPBEU1D2+BAPHONAoJaJ6g5pUHAP1+YH/u0nYgUPN2Np2mhDCafu4v98sQ4zCiNBgQUOj01WJCKTFgFnBhq7Fgv6FVgNGyVRseHAvc0k45vTuL6YqnBeVTG1ZR4zZgpAGvycp1mWfrcY1YdWFVpR6uANCgIzBK5tbeeQT7k9PjA/16uEtImNQmsHkvqefjAA8DVr51zJpQJ1YzcK5+rKxuE6QOIpVqAm9Gsd/P/qkvDMg1IwJd3gZSLgDtX3Tu6/eTU3tZvqKrE4TQX5yNBGIVjPrF9J6ifVyNO3oB5yKZp3GwRpiKynWATxS0u2YRpv/1PCCVqN5E3ZPdauQ2jUbo+g4bOIu9Fr1JUKjT09lXdH+fCWgeabA5Y4Li7T2Ay/vcL8fHcHygRzA2QceOHfmoqCh/V8O78Dzwz2Q2EqtjYayxvHRg62esUza6/lhaHDNM9eeoRPi4DdvCtG5miT8EnFjMtDlKzh2+ZvZDQILdA8vM9BzhPmc2Ajk3gA4v6qf1Bju+Bu7oKY1DVZrJTAD2fMecHpS8+rxBejyzTbOqPKFfoXfQ+yScAGY/yOx7X9bRJnuKzQYkHGPafCMzOT6A47jDPM8rumaTBq20wXHMqNdqKlQD/vONuXM8icVjNe4uatuwE/sLFMwalhOe06KPf8vvNt6/5VtN+C1sqtuXaHnHugstj+Yb6rVl3zQj65Z6SrlyytECAhQS0IjSTf+fgcR//bvOpZU8MRtY86Z3pyMJgtCGNGe+g+O0Y0GWYUhAI0o3SvG/SjMVazDjcYIgCKJMU7qCghAEQRAEQZQBSEAjCIIgCIIIMEhAIwiCIAiCCDBuqjAbHMclA7jkg6JqAbjhg3II89CzCWzo+QQu9GwCG3o+gY27z6cxz/O1lQ7cVAKar+A4LkotbgnhX+jZBDb0fAIXejaBDT2fwMYbz4emOAmCIAiCIAIMEtAIgiAIgiACDBLQ3GOOvytAqELPJrCh5xO40LMJbOj5BDaWPx+yQSMIgiAIgggwSINGEARBEAQRYJCARhAEQRAEEWCQgEYQBEEQBBFgkIBGEARBEAQRYJCARhAEQRAEEWCQgEYQBEEQBBFgkIBGEARBEAQRYJCARhAEQRAEEWCQgEYQBEEQBBFgkIBGEARBEAQRYJCARhAEQRAEEWCQgEYQBEEQBBFgkIBGEARBEAQRYJCARhAEQRAEEWAE+7sCVlKrVi2+SZMm/q4GQRAEQRCELocPH77B83xtpWM3lYDWpEkTREVF+bsaBEEQBEEQunAcd0ntGE1xEgRBEARBBBgkoBEEQRAEQQQYJKARXoXneQzbPAw74nf4uyoEQRAEUWogAY3wKkW2Ihy8fhBjto/xd1UIgiAIotRAAhpBEARBEESAQQIaQRAEQRBEgEECGkEQBEEQRIBBAhpBEARBEESAQQIaQRAEQRBEgHFTrSRAEARBeB+e55GVlYXMzEzk5uaipKTE31UiCL8SHByMqlWrokaNGggOtka0IgGNIAiCMAzP80hKSkJOTg5q1KiBevXqISgoCBzH+btqBOEXeJ5HYWEhUlJSEB8fj8aNG6NcOc8nKGmKkyAIgjBMVlYWcnJy0LhxY1SrVg3BwcEknBFlGo7jEBoailtuuQXBwcFIS0uzJF8S0AiCIAjDZGZmokaNGggKCvJ3VQgioOA4DtWqVUNOTo4l+ZGARhAEQRgmNzcXlStX9nc1CCIgqVixIvLy8izJiwQ0wqvw4P1dBYIgLKSkpIS0ZwShQrly5WCz2azJy5JcCIIgiDID2ZwRhDJWvhskoBEEQRAEQQQYJKARXoXnaYqTIAiCIMxCAhpBEARB+BmO4xx/TZo0uWnL9CVDhw6VXOP27dtNnd+kSRPJ+b6GBDSCIAiCCGDi4uIkgkL37t39XSXCB9BKAoRXIS9OgiAIfZ566inH7zp16ty0ZfqSTp06ITs727Fdu3ZtP9bGPCSgEQRBEISfWbZsWZko05eMHj0ao0eP9nc13IamOAmCIAjCYgoKCjBv3jz85z//QYMGDRAWFoYqVaqgadOmGDx4MCIjIyXp1ezBOI7DbbfdJkm7Y8cO1SlPud2UzWbDrFmz0LFjR1SuXBkcxyE9PV2zTDHJycn44osv8NBDD6F27dooX748atSogbZt22LkyJE4c+aM4Xty4sQJvPvuu+jVqxeaNWvmWFg8PDwcbdq0wWuvvYajR49q5nHgwAG8+uqraN26NapWrYrQ0FDUr18f3bt3x+TJkyVpjdignThxAk8++SRq1qyJihUron379vjll18CwsGNNGiEVwmERk4QBOFLzpw5gyeeeAKnT5+W7C8oKEB2djZiY2MRFhaGXr16eb0uQ4YMwcKFC906d82aNRg6dKjL2pJpaWlIS0vDqVOn0LlzZ7Ro0cJQfpGRkfj6669d9mdlZSE6OhrR0dGYO3cuZs2ahVdffVWSpri4GKNHj8acOXNczk9ISEBCQgJ27NiBjz/+2PD1RUZGol+/figoKHDsO3bsGEaOHInt27ejpKTEcF7egAQ0giAIgrCI9PR09OzZE/Hx8Y59QUFBaNOmDRo1aoRr167h2LFjhvN76qmnkJubi40bNzr21apVC926dXNst27dWvX8hQsXIjQ0FO3bt0fVqlVx+PBhQ+Xu27cPAwcORFFRkWNfpUqVcNddd6FmzZqIiYnB+fPnDV+HAMdxaNasGerWrYsaNWqgqKgIly5dwr///guArVTx5ptv4v/+7/9Qv359x3ljxoxxEc4aNGiA1q1bo7i4GFFRUcjIyDBcj9TUVDz//PMS4axmzZro0KEDLly4gMWLF5u+NqshAY3wCeQsQBBlg2kHpyEmNcbf1TBFyxotMeHeCZbkNWPGDIlw1qBBA6xevRodOnRw7Lt69SqOHDliKL9ly5YhLi5OMs3ZunVrw/ZjjRs3xqZNm9CyZUsAQFFRkaGlut59912JcNajRw8sWrQIdevWdeyLiooyNUsyaNAgvPTSS4rG+jNnznTYixUUFGD16tUYOXIkAODcuXOYOXOmJP306dMxZswYlCvHLLUKCwuxYMECw3X57bffcOPGDcd2mzZtsGPHDtSoUQM2mw2vvPIKIiIiDOfnDUhAIwiCIDwivzgfNt6GiiEV/V0Vv7Nq1SrJ9owZMyTCGQDceuutuPXWW31Sn88//9whnAFASEiI7jnJycnYs2ePYzs4OBh//PGHRDgDgI4dO5qqS8OGDbFu3TosWLAAhw8fRkJCAnJzcxWFvJgYp5C/Zs0ayfqWffr0wdixYyXpy5cvj1deecVwXf7++2/J9rvvvosaNWoAYOtpfvHFFySgEWUDDrR2H0HcrFxIvwAAaF2rtWWaqNJKbGysZPuhhx7yU00Y7sRMi4uLkwhNTZs2tUSgHDVqFGbNmmUobWZmpuO3N+7p5cuXJdvyaeL69eujevXqLvZ3voQENMIn0BQnQRCE7xHbcfmTQ4cOuQhnLVq0QPPmzVG+fHkkJydj586djmPkYEZhNggvQ4IZQRBlCXlIDLHQ4S6eLDMk2GiZQQjVIXDhwgVcvXrV7ToAwO7duyXbo0aNQkxMDNasWYNly5Y57M2U8MY9bdiwoWRbcFIQSEhI8Kv2DCABjfARNMVJEERZYMCAAZLtsWPHusT2SkxMxLp16wznWaFCBcn2tWvX3K+gAWrXro0HHnjAsV1cXIwhQ4YgMTFRku748eM4dOiQoTzFDgcA8wgVEGKtqdG3b1+JoLlx40bMmDFDYpdWXFyM+fPnG6oLADz66KOS7a+++sohkNlsNnz44YeG8/IWJKARPoE0aQRBlAXGjh0rmVa8cuUKOnXqhPbt26Nfv37o3LkzGjRoYCqKf506dRwG7ADzamzXrh2eeuopDBw4EJs2bbL0GgBg2rRpCA52WkH9888/aNq0Kbp06YJ+/frhzjvvRLt27RAdHW0ov86dO0u2v/76a9x///3o3bs3mjVrhlOnTqme26JFC4wYMUKyb9y4cWjSpAkee+wx9OrVC/Xq1cPLL79s+PqGDRsmuacnT55E8+bN0bt3bzRv3hzz5s0znJe3IAGN8CpkR0AQRFmievXq2LJliyR4a0lJCY4dO4a1a9fi4MGDKC4uNp3vsGHDJNvHjx/HihUrsHz5crfikenRpUsXLF68GFWrVnXsy8nJwd69e7F27VqXILx6dOvWDf3795fs279/PyIjI1FYWIhJkyZpnv/DDz+4CGDx8fHYvHkztmzZgpSUFFP1qVmzJhYsWIDQ0FDHvhs3biAyMhIXLlxA7969ccstt5jK02pIQCN8Ak1xEgRRVrjzzjtx7Ngx/Prrr3j88cdRv359hIaGolKlSrj99tsxaNAgPPfcc6bynDJlCj7//HPceeedCAsL81LNpTz55JM4c+YMJk+ejC5duqBmzZoIDg5GtWrV0KZNG7z++uu4//77Dee3dOlSTJ48GXfccQdCQkJQq1YtDBgwAAcOHND1zAwODsbcuXOxZ88eDBs2DC1btkTlypUREhKCevXqoVu3bvj0009NXV+fPn2wb98+9O/fH9WqVUNYWBjatGmDGTNmYN26dShfvryp/KyGu5k0HB07duSjoqL8XQ1CRFZhFh5Y9ABCyoXgyIvGAjMSBBG4nD59Gq1atZLsi77Bprla11KPaE8QZQWld0QNjuMO8zyvGFAu4DRoHMc14zjuV47jojmOs3Ecx3McZ14fTBAEQRAEUUoJxDhobQAM93clCIIgCIIg/EXAadAAXAXwBYC+AA76uS6Eh5D3JkEQBEGYJ+A0aDzPHwJwCAA4jhvn5+oQBEEQBEH4nEDUoBGEJjzPY1PcJhTZivQTE4pEp0QjNkO6vl1RSRE2x22m0CgEAOBAwgEk5yb7uxpukVOUg6IS6h+I0k2pF9A4jnuN47gojuOikpNLZ2dyM+ONj/22+G0Yv2M8Zh+fbXnegc7q86vxzNpnPM5n8LrB6L9KGpNo5vGZGLdjHHZd3eVx/kTpZ3jkcAxeN9jf1XCLuIw4nE+3PjYYQfiSgJviNAvP83MAzAFYmA0/V4fwAekF6QCAxNxEnZQ3Hx/t+chreV/PuQ7AeX8JIikvyd9VcBsbb9NPRBABTKnXoBFlDyHoLU3FWQvdV8Io1EYIQhkr3w0S0AiCAABwHK32QOgTFBSEkpISf1eDIAISm80mWdjdEwJOQOM4LoTjuFocx9UCECLaX8v+F6pxOkGUCUiDQfiLihUrIjs729/VIMoYeUV5yCrM8nc1dMnNzUWFChUsySvgBDQAXQAk2/8esO8LEu171k/1IgIEQdNTlmOsedO+pizfV0Kf8PBwpKamkhaN8CmxGbG4nHkZecV5/q6KKjzPIz09HZUqVbIkv0AU0Moc2y5vw9bLW/1dDa/gDU0PLbwO2GC9gEY2aIQRqlSpgkqVKuHSpUtIT09HcXExtRnCZ5TYAm9gwPM8CgoKkJCQgOLiYlSvXt2SfAPOi5Pn+e1A2foCv7XtLQDAyZdO+rkmRGmBPoiEv+A4DnXq1EFWVhYyMzORlJSExAzmUV0uOTDG/NezmUdyoNQnUMgvzkdwuWAElwu4T78uwjMtCitCaHDgWToFBwejatWqqFOnjmU2aKXvKRGlEm9Mm5VlIcUbU5zkJEAYheM4hIeHIzw8HADwVMRTAAJnkPlMBIsVGCj1CRTaRrQFUDrvi/BMZz06C+1ubefn2vgGGl4QXsUbghnZoHlJQAPd19LGlawrtKJGKedq9lVa9cAEZWlgTgIa4ROstBszk1d6fjq+OPDFTdcBlnUhanPcZmy6uMnf1fAr6fnp6LOiD6YemOrVcgpLCpFfnO/VMsoqWYVZeGz5Y/hs/2f+rgoRgJCARvgEr0xxGshzxuEZWBSzCJvibq6PuVe9OEvBCHXcjnEYv3O8T8s8nHgYh64f8mmZWgghB/Zc22N53uI2cM+Ce9BpYSfLyyhLxKbHYsulLS77c4tyAQB7r+71dZVKFeL2WJYGp2SDRngVf79MgsePv+thNTR17HuGbhoKIIDsd7xoMkhtwFr6r2br3gZM2ykFTN43GVsvb8X2QdvLbHskAY3wCd4IjVEaND3egsKXEN58XmX53SICgyVnlzh+i9tjWVpjlQQ0widYOQLS0/SU2Erw5cEvMbT1UMvKlJNVmIUq5avgStYVzI+ej/fvfR9B5YIMn59fnI/Of3bGoBaDsChmEWqG1URKfgrqVKyDDU9uwMe7P0bnWzpj0r5JeKLZE1h5fqXk/K5/dZVs/7fDfzG87XAAwJIzSxAeGo791/ZjdLvRqF2xtqlrK2uj1SJbEYpKilAxpKJPykvMSUStCrVMtRctvCFMlbU24C/oPlvD8eTj2H11N0a3Gy3ZX2QrQrGtGBWCrYns72vIBo1wi/zifMw5MUfXg8wfmp6TN05i8ZnFeH/X+5bXo8hWhMHrBuOBRQ/gWNIxvL/rfSw+sxgnbzinLrZd3oZjScc081kfux423oZFMYsAACn5KQCApNwk7L+2HxvjNmLSvkkA4CKcKfH9ke8dvyfvn4zxO8Zj+bnl+OLAF2Yvscwx+u/R6PxnZ5+UteTMEjy67FG8tuU1j/JJzk3GwtMLLapV2cWToKcL/l2ApNwkaypCymtNxIKsUl/+woYX8MvxX1z2v7jhRdy78F6v1s2bkIBWSkjOTca+a/s8zudG3g1dg9RJeyc54uWoMe/UPPx49EcsPbNUsj82IxYnk13tLLw5HfPG1jfwyJJHXPbbYLM8tteq86sQnRINAIhOiXZ0HOkF6Wgb0RZrL6zFW9vewosbX9TMR2vkXMJbFynbnRG6t6e3lp1dhrYRbZFdGBjrOe5L8Py9MoqwYsjB6wc9ymfcjnFYcHoBAP854JR2/jz9J+5fdL9bSwddyryEaYem4Z3t71hTmZv/dnuEREAzcbOEvrq0QlOcpYQXNryAaznXPDYyfWXzK7iYcREnhpxQFV6Wn1uuuP96znUk5ibi7tp3Ozq1/BLmfj/r2CxEp0Rjx5UdAFyNYS2d4hSEPXuWQpmO45z0uJj3dr2H6qHVkZibiEZVGuHte942VXZBcYHjd1xGnKMulzIvAQCmR003lZ8SVgpoZvBVoNrf//0dAJCYm4jK5Sv7pEwjRKdEo0X1Fl6Nsm7VPc4oyHD89oowVQYEhl+O/4K84jxkF2abngIrKGH9QE5Rjkd1KI12n8m5yXh46cN4ufXLeKejRQKqCcrC4EGANGhe4mLGRRSWFDq2+67si2Gbh7md37Wca1ZUCxczLgIw1shT8lKQkpfiMMoctXUUXtjwAoptxY40grZl5vGZLoKS0XLMomeDphVwdX3seiw4vQBbLm3Bb6d+c7tsAPjrzF8ox0lfodT8VGP5aHTM/lprzp2PxfrY9ei2uBs2x232Qo18y+B1g/HDkR/8XQ1DeFuYLgsfQWEg5ImW2ZvPYcW5FVgcs9hr+bvLtvhtAIB50fO8kv/5tPOujgC8ym8ZRrT/RSVFmLBzAuIz492roA8hAc0L7L26F/1W9cM9C+4BwBpNXGacx9MagHUeLEpaGhtvw9eHvnZsd1/SHd2XdMecE3MAAOfSzjnr4FBSGevczHz8eZ7H3FNzcS3bPaHUm4t+y6/DGx5FxXyxfqIA4b1d7yE1PxXjdowDACw9uxRnUs8YOjcQtQf/pvzr0fk8z+PVyFcdtoWuCTzKXrVMy/MsAwKacI3u3D/hvQ/irHH0UGLi3on4/MDnXss/EJl7ai6eWPMERm+VGvsbbY9G+uNDiYew4eKGUhEcmAQ0iykqKcKIv0dI9lnZ2Vk1/aXUKe2/tt8x/SRmR7xUM2bjbaY/rjx4HE48jPNp53XTJuYm4tvD37q8pEp5KiGMam2w6aZV4/fo39E2oq0jkKQ8bwFhqkPpfrhrM+hvDZonH/zP9n2GgWsHGkpr9JmM3T4WbSPa4r4/73O7Xi5l8zxWn1/tEiHf03f1032fYn/CflXnDCP574jfgbYRbR3T5v6gTITZ4IV/bgho9r4lEAcZpZn1sesBALuv7lZNo/W8xH2+RgalBhLQ3OD9Xe9j7Paxisd+PPajyz4rtSyefLyFyOMAq1PbiLZoG9HW0RmraW7kjd7d6xm6aSieWPOEbjph2lBsZwMAU/ZPwYgtI3QFCccUqAcfmT9j/gTg9K501M3EKyMYhJvFX3F+zASqTc1PxWf7fDMCjbwUCUDb3ierMEvXIDglLwXt/2iPY0nHsOfaHny05yN8d+Q7S+uqZr8pYKRNbozbCAA4kXzCUJm+0naVRqFt2sFpqqYlYg3ajbwb2HttL+Iy4gzla7Oxd1Ru4iDw0e6P8PY2c/atvsSTPsYf/ZNRJwFxG9WLMFAahGsS0NxgXew6x0cDAPKK85CSxz7kV7OuuqQ307EVlBTgRt4N1eNbL2/FpL2TjFdWxIX0C47f4pdMb0pNXn93NGji9Ik5iZppBSNtsa0bwGy+9l7bq+qS/lfMX/jl+C9effHkGjRBo2mlLUppmOLstrgblp5dqp/QR4zeOhqD1w3W/HgcSz6GYlsxfjv1m8ODNDk3WZLG2522EWFKrQ5FJUV4Y+sbrlPIXvERcM3UjCCYkJ0QEALdgtMLdE1LePD4vxX/hxFbRqDvqr4oshXhza1v4nTKadVzhEGrmoC2+sJqxQFaINwTgHnhext3TFTU2phkqSeNe1jClyCzMBOvRb6G2PRYU2UEIiSgWcCQjUPQfUl3AJ53bP/957/osaSH81yex8/HfnZsv7frPd1RuhpiTyXxh0w+jaeHZOrQYIcjvgfzo+cjoyADPZf1xLbL2yTp1sWuc0wNqo2Axu8Y75InAEw5MAU/H/tZ00nAU+SCmHAflT6qWvdGS6Dz5RRnTGoMIqIjJPvU7tsf//6haaMlXu9UfO2nbpzCn6f/dGx7IgTxPI/Xt7zusl+IO6dlAlAppBIAaXv3VLA2q00w0yblaWNSY7Djyg7VAVpafho+3fcpph2chqISbe2BbtkKbdfotZ5LO4dey3tJzCV4ng+4CPDC/bXxNuQWO9vEhfQL2H5lOz7a8xGyC7Mx/dB0l/spXIuagKZXptq2GjbehhJbCXieB8/zjt/uIjiLAXDkZxQjdV57YS16L+9t2dq1Ru8Tz/NYe2Et9iXsU3UCE/ISz7QEWtsUIAHNAmJSYxy/lRr6/oT9jt8J2QmIjGPatw2xG1y0ScLCx98d/g5p+Wm4lHlJMQCfEjbehr9i/nLYRckJDQp1phUJWSvP6QdClZRjMx5fTK0T+fbwt7iecx1vbXtLsv/9Xe/jvV3vAXDf3s5hg8abFyR185YJF+fT9W3qAODvS39jwb8LDE2hyDWHnhCbEYudV3aqHn967dMuoUHU7tVXh77CoHWDVPMSBGcAeHb9s5LfXx78EgCw5dIWt50/APbx1FocXHjmPM9j6dmlkmlRwaBbq12YEaD2Xt2Lu3+/W3VqdUPsBhcNnZHs1abwlWwrWZYs3dSDU7Hs7DIsOL0A62LXGbkEUxh9h65kXQEAycf5v9v+i7t/v9vyOilheNBoT+ciNNn3l+PK4adjPyHi3wisurBKksZdJwFVQUCnO73vz/vQ7o92WHxmMUZsGYF2f7TDG/+8oZh279W9uo4613OuO37Pj56Pdn+0Q2ZhpnYl7Bi5v8L0/Nm0swDYN1L8HfQETRs0E7M7QrpRW0f5rG2ahQQ0i5ELFfFZ8RJj9+c3PI+xO8YitygXE3ZNwIgtI+RZAAB+O/Ubxu0YJ5mW1GPTxU2YcmCKqkAnFqrEL5meICR/Idwxvhe/NOW4coaEkLziPLcEK7EGTfhAC67hppEVb2bELL43Y7aPwbRD09B3VV9JHZVwV0BTulcXMy7qOlsIWDm9F50SjbYRbV0Ceb6z/R1H7DwrEZ5Lia0EO6/sxNNrn8ZnQ+MweAAAIABJREFU+z5zGOvHZ8Xjlc2vAACiEqMw9eBUxXwOXj+I48nHDZW56+ouACw8h+DhLGbCrgkuKwYYmuJUsQVUE9yEdGKN8yd7P/FIe6FUz0OJhyR2rGoIz0IsjLj9/rmBYW2L00tAgtC/JeUm4dSNU2yfTdkO16wGlud5HEg44OKcoocQd3LFuRWOwMpqA68Rf4/QddQ5cP2A4/eKcysAwGFacyXriuZ3x0wbFnh67dN4NfJVxbSHrh/CXzF/aeZnZopT75nIz9dySPA3JKBZjNx+6PEVj0u2k/PYiFroTLWWCknMTcTb240bmgpq+rT8NN20YqGsYZWGmmmtsEETv9TluHKGg4EuObNE9Zie8MbzvEO7YcUH4s1/3lTNx6jhqpH07tqgeeLhK+kALZwa3nJpi6EyBRKyE/DM2mdU7TDVBGShPZ5NO4vRW0fjTBrTIJxIPoESW4lLJyx3/hAjfLD0ENdFbJMqJjGXacjzi/NxJvWMw1ZVCz0N2unU04qaW/k7qRbqI6MgQ7ceSs9mxJYRGLxuMDIKMnA587LieXEZcS4CptY7HAioadBS81NVhXW1Kc6MggxNG+LrOdcxPHK4ZBk6PQQhEXC/b1Cq1+B1gzFl/xTEZcaxHfbb0GdFHwxYPUA1LyPCpVFtHMCCp085MAVtI9oaylt4XlP2T8EHuz6QXBfP88a90QPfR4BWErAao9oPIZ3Wgslaef0V8xcGtxws2ScIfcvPLUerGq0wqOUg5BXnoRxXDqFBoZIRbfQN57RMtdBqAIBdV3YpllVQUqA6guF5XtHepdhWzOwl7C+T+Fo4jjM8NXA129XpwgxiVb6nwVS3x29XPaY0dSHsM9up6nkfmamDUYyMPH3BwtMLcTr1NNZeWIuX27zsclyvjukF6ZLtuMw4fH/0e9SvVN/SegLSj7PegGXM9jG6I/XCkkIEcUGq16hWhnhKToxae+j6V1cArqt92HgbimxFElMIOZezLjvO3/vsXlQpX0Xybvdd1Rej2o2S1Gvy/smq+QHOviIkKEQznVHMTnHK75MRDaqagPbQ4oc030NBOydM0wt1SMpNYsKF/dmLpyjf3fmu47cZW7H84nyEBYcBYE498gFcdEq0ZHreaP9hxPNZCJdhdgYkPst48Ni/zjCt29rYtY59xXyx4z2RX2+RrQhFJUUotLEA8nlFeZK2+9vJ39CpXifcVfsuU3X2JqRBsxijL5DwEdaaMtMS0KYcmCLZLiwplMReEgIc3rvwXnRc0BGAdKQ4ausoZ53tDVlo8HLiMuPw0Z6PXNILeXZY0MHlnL4r+yruB9iHRnzdWtdppTu4EExVTomtBE+teQrn087jTOoZbL201eVjqNfRKNVTcOZQEmD3XlNfD3XmsZmaZakxae8kfL7fvcCW7mhFzWKksxYGLGraQNX3xV51pecQdT3KWAXt6Nlk7ryyE/NPzTelsTQyjXLPgnsw+h/ndLTLFKeOcOppEOWpB6ei44KOzADdgBZVmO7ss6KPZL9gY6iUx84rOyUaIQB4bv1zin0Fz/NYeHohMgoyMPv4bMw6PstxTZFxkaoxFc1OccrTK01/y++9QyiGtlD8e/TvWHNhjWNbaDNK63+KhROxnaY4z9gMZc9EJTot7OTQlBppq75Y09XG2xARHWHaMU1vsXSBkX+PdDwrufb+sWWPofOfnR3hT44kHZGYGH135Ds8v+F5U/XyNqRB84C2EW2xZsAayT6jnXbPZT0BaBuZ6uV1MeMirmVfQ4e6HXDvwnv1C1Vp1zbepuqSLCDuZMQjPTWuZDND4UeWui5iPvfUXDzfyvkirLmwBk/e8aSifYvm1KHKMcH+QphO1mP9xfU4m3ZWEqOtQeUGAICMwgw0REPdZ6H1Mcwuki4KrrcQvbuIR5JmkQjdXgoFYERgEN6Hvdf24unmT6NqaFXJcbU4dFqeu1rXo+Z1nVOU4/D6lKNk02eVcLvn6h480Yy1Q5cpTjUNmswrzbFfdH5afhrOpZ3Dvbeo9xPCVKQNNkMx2IT3VaylFtdT6XkL906svTudqhzO4ljyMUw9OBU/HPnBYb7RsnpL/H35b0d/dPKlk5iyfwo2XNyAPc+qO4+cST2D0KBQNKnaxLFPuD/9VvXTvE4llMJsKLWzr6O+lmzLbdnE7W/r5a144c4XEFIuBN8e+dZ0nZS4kXcDNSvUNJR2zok5Ek9sdygoKcDC0wsd2/J7su3yNkyPmo6r2VfxQecPDOcrt5neekk5xmRMaoyqxjYpz9WcyIrVfbwJCWgeIo4WHxEdgaNJR02dryVE6Gnjhm4aitT8VEx7cJqhstQEmhK+BP1X9zeUB+BZhH4BsWAqjCbVpgltvE3RCFtPkDBi0ByTGoODCa4vqSBgCt6IPRv31MxHS/iYvE97ikfg116/qhrSyhF/4ASBr0l4EzSt1pTFyrt/Eibtm2QoL4C1NS2hWxw02N0pWPlU77Wca6hdsTY+3/85OtTtgGdbPuv44B26fghvbH0Dfzz+h+ScIl65bEEoULKNKuFLVIUbNRu5mNQY3FP3Hu0LkmHUuUAPVScBleeTmp+K82nnXY5vv7LdZTAwu+ds3fJzi3Lx+t+uoUzkrL2wFi1qtHDZv/I800Dy4CXrEZtFsEcSh8CQe30DUs3/1stb0aGOqzZOGLSJ3xuzfVdhSSEGrRuEF+980RGySHzPjQwI5QM9cR2+OfwN8ovzMbLdSJcwGO5ixqnJCuFMmK0RkN/jEzeY4C/EIXSHuafmuthgcuA0n2dCdoLb5fkTEtA8RKyqlocr8BQ92yVhYW4j01of7/kYg1sMVjxmNu5WQXGBxxoDo7YGu6/uRq0KtVTtHswYoyrx9NqnDaXTMnYHtAW0CxnGPHGtXNfPrD3PkrNOQ26ho7uRdwOVQiqhQnAFyRSdu4GS5VO9Yk3UprhNeLbls5J7oORJpibsCh/Kbw5/43LMnUHE7OOzMb37dISXDzd8jnzlC0Bbs7bw9ELUr1QfPRr1kOwXnBTE9c4qzMLEPRNV83pizRPoVK+Tbh0/2fOJbhohNIIeEf9GYFwnZbMBADiQcMCxHrG3GPn3SMfv3Vd3m4reb6ZdRERHYOW5lTiffh4T9zqfg7i9Ks0WyHER0GTCl+BUYhXeXCtUzKkbpyShddSYe2ouADe8X0XPKiHHVdjiOE5TkO21vJep8gIFskEzyYGEA5Jtq5eKEWNUcMoqUtYUHU487Pi96vwqrDq/SjGd2ZF//9X9HYFB3TVbEHtDTj04FUeTjipOI8ZlxqkGRz2SdARdFnVxrwIWoyYoCobXRvBU6BULifKOWTh2NOmoYoTzbw9/K/F+4nkePZb0wL0L7wXP8/jfyf850oqnu81gxIFGMuJXuB1RiVJ7snmn5kk8t5QoKCnAnBNzDNcTAPYl7EOXRV00PfLqVKgjqavaB0JNuJ96cKqiRkgg+kY0+q7si8KSQsyPno9TKadU0wKuDhJKyNvi5czLLl6WZrQuWraUWgj3Kj7TuFG4EuKBg+m1S030XZezLivef7OBauUDObmQqJSfUUHyn8v/4EjiEY/q5y5GhDNP0LNBM7MEnx4R0RGa770vIQ2aST7e87HX8pZPR4hV++4wdNNQybaaHZVaxGUtxHF0rGDIxiFYO0DZhkptFGjkg+QrlBaZB4Cui7qqCtBytDx6jaAloJXwJSjHlcOQjUN085lzco7EduaHoz8YDsirhRFvVjOekQDTmN13y32aI3LxdJFZknOTUatCLcVjcpsWJS1qZmGmSyw4OTOiZmBsR9e1fQUnkwWnFxiaKlQyA5AjaN0BaX/z5B1P6p6rhFocRz2yirIQXj4cj698XD+xQdRi2ymx7fI2S5ZUMysAufTBMllDqa9T0hgp8d9t/3XZ5ysNmhruOFfp5aP0XbRyebzpUdMxPWo6ol6I0vRo9gWkQTMBz/OGX5ZAxBvLWQguy1bwwW5lo1Fh8ejSiFHhDPB8tCseZbqsGWpiGls+VSfWnnnCT0d/0jz+2PLHJNo9juMwYecE3XyvZl9V9IqzAqPPJDUv1e06zI+er6lJyivOU10dxCrEIXF8sYj0h7s+dNkXmx5rKIajpyTmJGpqLs0gtA9h9QQ95DaS59KlQvVfZ/7Cj0d/NFWHIluRi2eslSyOWYxn1j7j1rn/z959xzdR/38Af133LnRA2QUEWvaSJXvJXmWjgAMcuP0qLrCKguDPgeJAZChDliCIgLJlI4hYpC0UuvfebZrk8/sjzfUuuctokyal7+fj0UeTm5/cJXfv+0zdUS+0tLnwpjaqM7fVpyX03tZb1B2VLVAOmhl0W+PVNTXpyFSOpW7eABCRFWF8oftYTbPphV1l6N5kH9z+IOaEGC6GsHY/aMbGkE0uShb1e5dfno/DsYeNbvfl0y/XOG1yrqZfxYG7B/B0N8OV5ndG75TtpsYUhnKSMkoyTO48t7ryyvP4B7gFRxdYdV8AcCv7lt4wd9qGSmdnnUUDtwZW2e/+O/vRu3Fv4wuaSBugafv9Mkb4ENpnex/JoN6c4viY3BhsvLlRdmiv6jbo0SpUFPJdNlWHKZ2JG6NQKWxWh2zjzY34dKh+vdbaQgGaGYRjbtZFlhq4llhHTfshUjO1bJcLgHzP8lq1kXNS12iLzaRa+tYWawdnADB8z3Cr70MoozQDI/eOlJw3aNcgvU50LWX5heU4PNV40G8qDhzu5d/DjqgdZq9riVxfYddAUuYfnY8ejXpUa9tf/fOVaNjAy6mX9XLXd0TuwNzQuRjSfAjOJJ3R24axa5opmQbWbmhiiLHGYdZGAZoZgjyCbJ2EGqlpr/zEumoaoJk6Xh0xn3boKFI74vLjrFbcacl6b0fjjta4ewpryi/PNzgCiiG6Yzo/+ceTesusurIKI1qOMDhkoZys0ix8cvWTaqWtvqAAzQwtfAyPWUlITdQ0qJKr72EqykEj9mLiLxNtnQRiIrmcUEDTInJuyFzJecN2D5OcTqpQIwFC7hPC7iaqU5/sh1s/WDpJpB6xZV0dYp/yyvPQd0dfWyejzqIAjdgFbxdvWyfBqMVdF1t1+zUu4rTCWHqEPNv9WewcvxOv9X5NcgB7Ld3RNj4ZQsVXhNQEBWjELpgyLJOtPdf9Oatuv8ZFnIJGAowxTG5r+vBdhAAQjZEr1CmgE+Z3ms+PUWtMS++WGB1cN3tvJ0Sro39Hm+6fAjRSK/oEGR/M3dDTuTXpdtLp5ewluRzHcRjdSnzT+WHMD1gzeI3V0mYO3X7uPhj4AT4fZr2RLrQMdd/h5+Zn9f0DqHZLtdqyb5JlW2I+EvqIwfnBPsHYNWGXaNq3I7/F1rFbJZf/esTXWD9qPfo36a83T/i9mtFeMzTaox0fFS2j+/nM7dPvr3l/YfPDm3FjvmXGM7WVQc0G2ToJxIJs3dEvBWgW0Nijsd60oc2H1n5C7FRYuzAs6mp8EPBRLQ0PSK4r1C+0ukkS0Q0eL869iI+HfCy5rO6Np2fjnvzAyVq/h/1udhrGBo9FS5+WkvO0F31tICk1GDSgyTUb32Y8ACDUX3NsTBleqabe6vsWDkw+IDnvzKwzRrtMsETx9o9jpUdysLZJbSeZtJy/u79F9jexzUQ82vFRLO2zFGNbj9Wb/0CDBwAAPq4+ek//DzV7CN0bdZfc7qDmgzCg6QBR3cUtY7Zo1mtaNZwax3GIWBCB1x98nZ82tPlQtGvYDgCwf5JmoHSpAM3ZQX58WDcnN/QO6m0wsLv2yDXR+5UDV8ouCwBODsbbwJmyjDnkciBryt+tZt+f0a1G49zsc8YXNNETnZ+w2Laqq6W39PVS1xt93kCwT7DkvC+HG+4U2Np9QxpDAZoFSNVN+nLEl5jf0fiwOsv7L8e1R65hVodZZu1zUZdFdeJprY1vG4QPCDf6JOLs4IwugV3M6v+oubdpxS3GSLVeHBM8BmOCx+hN79tEv8JrK59Wetu7PPcynuj8BM7POW9w3//O/xcRCyKwZsgaBLgHIGJBhN7f1yO/RsSCCLw34D1ELIjAD2NlKvNzmnpAEQsi0MJb0+JYbgSBES2rBnZ+o88b/OtG7o2q1QeVMJeljW8bs9bdMc70PqQ8nDz0ppm7P13C82/OTayBawOseGiFbOtXYa6SKU/iL/Z8Ef/rrRl8fEKbCXrzx7cZj5WDVvLB0ZrBa/RyvNo2aIvnuj+HT4fIV9g3Najs1bgXIhZEyAZ1WsKgStvB7LAWw/htAMDQFkPx96N/48We+sMRmUo3eOvg18Hg8n/NM97v46qBq0zat25wKMfS9UDf7a8ZmN3RwdFoZ8lyvhj2BT4Z+gl8XX0tlq6Xepk+KH11TW8/3eD8oS2GmrSdeaHz8GafNyXnGftdWnKMz+qgAM0CTMnO/yPsD8np/Zr0g4uji9Ef33ejxL1Lv9DzBaNjN45sKd/82RR+bn7Vyg0CNE/Vk9pOks2J0jW4+WC9acv7Lze4zmu9X6te2kz8Ya8cpP+EHtYuDCdnnBRNa+3bGidnnOSL8xw4B3g4e+ClXi/B3dFdbxtC1n5CE45R996A9/jXwvMifOrXpqd7oOGbsi5th5O+rr5Y0Em/J3ph4LOw00LRPHPGIJW6MdR0DFMXRxf+tTn1AI9MOwIHzgF7Ju6RnO/m6Ma/duQcRcHlqZmncHz6cbzaq2oMTsYY5necj5MzTuLDgR+iQ0PDAQgArBuxDqdmnsJbfat6qH+q21No7Kmfq68VPiAch6cdxuW5+uPp9mvSD0NbDNUrHpVydtZZDGg6AK/3qcpNC3APwKmZp/B8j+cBaH4vgCaHGDDtWnl21llsfngzZnWYhR/GaB5GRrQcoXczbd+wPXZP2C21CQCm5Y6Zei1w5BxxYY7xgeEZY1jSfQmaeTUTTX8k9BFcnHPRpH0JaR+wnDgns4Zr07o89zKGtazqzuLCnAs4Nv0YRrYcyed6WoowCLoy74rZIzacmnlKdJ14qafhINBQcKX7vZC7Rgi/j8E+wXrfh9oabF4OBWg1dHjqYdFJHNx8MI5M0x87MshTupNb7dN3gHsABjQdILsfU4qBdHPU5AZ5NpW7kzuaejWt1rofDf4IHw78EO0btgdgfBxQYZGJlvairsvT2RO9GvdCE68m/DTdm76uvRP3YliLYXis02N62dpyQZKzg7NefTSO4xDoEai3bKBHIP8ZhRcDW2eRa9PfN6gvpj4wFX2D+mJJ9yV6xU3aIgBtDsDWcVvxxbAvRMv835D/w7Pdn0Ub3zbYNm6baF5Ln5YIcA/AR4M+ksxREn5/dSuam5K79HvY7zg+/bjkE+0rvTSDkRurlyVHmwPXq3EvyRwQJ076Ru/lIl1XUUsY+DlwDrg8ryogCnAPQGPPxljYeSE/jYHx3y8HzgHv9HsHPi4+/Hyp4+ri6IIA9wA0cDV9aCRnB2e08G4BD2cPnJhxAkfDqjpadXF0wZfDvzSpcnQDtwZYP2q9XjAS4B7A/wYmtJmArWO38sWxpuRINHBrgN5BvfFOv3fQs3FPRCyIwOfDPpf8LWmL8rW8nb3R2re15MOd7vXkhR4vwM3JjT/GhorMHB0cRd9hqWs8oDmHT3d7GkfDjooC4Lkhc+Hu5A5PZ08AQHj/cL11pXJvOwV04vdvLHfusc6P4asRX+HA5AM4Pv04fg/7HR7O4hxnbxdvBHkG4bNhn2Hr2K0G64jqBlg7x+9Evyb9+MyE0zNPY3HXxfB28cbhqYcxN7SqvzN3J3e9oMjYNTrAPUCUy2csODI0v6FbQ0x5YAr/gCB3jRF+p5wdnfHxYHGGwnM9rNswzBgK0GqohU8L0Rcl0D1QsuhN7kZt6g3clCf7r0d+LXov9QT5zchvDG7Dy9kLrX1bm5QmOcv6LeMvRFrGLi5SFwq5Y/Nklyf5+jFaz/d4Hh8N+oh/39SzqegC08GvA74Y/gVe6f2K/n7A4eCUg5L7MufGxwdogouB9rXcTd7ahrUYhlWDVuGbkd+A4zh8//D3krm1G0Zv0LwQnKaHmj0kWubh4IfxTLdncGDKAXQL7Caa5+7kjlMzT2Fgs4GS6RD+RnQ71OXAYf2o9QY/R1Ovpmjs2Vj0nXit92v4ZfIv/D6FQf6eiXtwbvY5jGo1Cn8/+jee7/E8vh1Z1TO6tigRAL4d9S3WDV+HLWO2oKFbQ719e7p46k0TkhuuxtXR1eB6unSPXfdG3XF+znm+o09Tis/M7Wy4kUcjvQDLkjiOQ/dG3fnzphswmOuFHppBzqVyvtr6tsWFuRdwcMpBvjGD0Joh4sY82jT9POlnPBL6CLaOk25AcXrmab1pzb2bY/3I9egbJN/Hl4ezB3ZP2I09E/eghU8LODo44tLcS4hYEIGw9mGiZX8c+6MoOPl06KeIWBDBX4sXdFxg9CHX380fg5sPRpsGbdDYs7HRh2tPZ09RLq2w2gNQVbyq1SmgEzaM3oAl3Zdo9ufuj+d7PI8Lcy5IduLu61L1eVYOXIlXer2Cn8b/xNdTFBL+HrWMBWiGckgdOUeseGgFwgeEa97L5KAJr9UcONH15ci0I3gw6EGDabA2GknATD9P+hlhB8U/rhC/kGpvT/iEbGlSX3BjF/CTM08iqyQL4/aPq3bP8r2D9LO2DV1chjQfAjcnN73p5uzfxdEF49uMxxtnNfWpfp+uKZrt8kMXyeVberdEQmECAM2NVC4o/f7h77Hl5ha9HIWPh3yslxOkDaKFx53jOCzrtwx9m/TFhP369YqsjeM4yfpMestVHmthEGCt3D/dxh0cxxnMPRYSHtv5ncR1PIXp1f4mtZ2n6tYTXdBpAR5q+hAisiLg5+aHIS2GyO5zWIth+CXmF9E0Yb05qe/2233f1ntIkWOszt+0dtOwI2qHScfI3vvCm9puKm5k3sDBu9IPRMYs6rpItsGR1Ega7k7uRse8DPIMwtI+S0XTbsy/gW4/ah5C5Bp4DGg2ANll2bicVpVTpvsgrZvDJ2Vw88F8K2RterV9ynk6e/LfD+GwSOuGr4OHswce//1xAJqHVrke+w0R/p4+H/a56HoZ6BGIfx79B923ml7dYVGXRSiuKAagqaLyR7ymas/EtpqRIToHdBYt/8FDH2DyA/rdAfm6+hq9/hvKedf97cltS/ceKVzO3Acsa6AcNDNpi+wATU4RIA7Q2jZoK7uuVM6FVNHl233fxsz2M2W3o9tUfnDzwXzWrLCYR/epIaxdGPo0MdzdBQeOv9AZukHr5gitHLgSi7suxoz2M9DKu5X+CgbuG3JPStYsHjwwparVobZCvZRmXs3wdr+3MbWdeFDiMcFj9C422pwU3QvHzA4z0cqnVY1bYtW26gboxhpvdG/UHedmn0Mj90ai6cLc3SPTjkgW+RhrubVq0Cq8P+B9k9L5QMMH9M6rrrB2YVjebznOzT6HQPeqou0ugVU3Mt0Abef4nZgdMlv0/a1Ja8EOfh1wbvY5kyv3C20cvRFdA7pKViGwBWcHZyzqIg6wdLu5qa6QhvoPyrqNdJp4NtFbRoqpdY8mtp2Ic7PPoWtgVwDVC5CFQd2fs/6UbdwgzKkd0mKIKHfnmW7PwNlRvpWsHG0OkxQXBxezr8Ev9HwBb/bV1EUzpVGCVO7tlXlXcGLGCcl9C+sBzgrRb1jXo1EPXJhzQS+nVraIExxfGqObg2bqA5Y1UQ5aDczsoB9ESbX801rSfYneALRSWni3wOyQ2dh9u6qio/CHr9uqKqxdGIa3HA5AU9dhW6SmftCM9jOw+eZmfjntj/HMrDNQqBRQqpVIKkrC+xffR2JhIgBNUCSVE6Tr+IzjWHRsEe7k3gFQ9YQkx9CFS24/1qyg6eTghLOzzuLvjL/xQMMHLLJN7WeUS/eBKQcQmx+L5t7N7W4cOu2FSXiehJ9D2NLTmAeDHsTXI742mHvg6+rL70sbCAqL+Bq6NZS8QPZp0gdfjfhKto6UKbmF5tD+ZnwdffW6U9Fq17Ad2vi2wbv930XPxlVdoAhvCsL6aNVR3RZ4fZr0wfbx22u0b0tr6tUUDzR4ADF5MQDEjVeqo0tAF0RkRWBeR/0uLpwdnHFq5ik+iP5s2GeYfWg2AOMPIONaj+O7LTHE19UXb/V9C6+eflV0/k0l/G5IlSRoze4wG1tvbZWsm1vdh1m5utGA5bsgkSJV2qL9nZWrykXTZ7SfIcrQ8HL2Qkf/jriVfYufxoGTzPQwdI8R/q6F34maFsdbgt3loHEc15LjuG0cx2VyHFfGcdwNjuNs3+mKiSyZ62PsAqLNZevk34mfJqwLIJcz5OfmhyDPIDT3bo5+Tfrh8LTDon028tDkbBjq68bf3R/7Ju3DjPYzTKqnZaiIUzYHTebzS7X4lNPCu4Ve57JaDdwa8IGtJWg/o9zn8XX1RfdG3WvceMMatGkWnifh8Te3f6dBzQcZ/Zx8gCbxmzH03R/cfLBVj6FcP3NPdnlScrq7kzsOTDmgd3PWfq6adC1hqro00L2Lowv2T9avh1RTcscgwD2Av6Z18u+ExzppOsQ2dq1ePXi1Sf03ard7NOxotaqsmFo02dKnJd8lj66anP8Dkw/wXcIIgz+O42p8P5vUdpIo59kcup9Jt+GHA+egt4zc8TcUoGkD5AZuDezud2RXOWgcxwUBuABAmO/ZFcD3HMcFMcY+tE3KasfIViNxIeUC369WQ7eGyCnLkV1+UPNBRuuvXJp7Cf129DM5DRzHwcPZw+S+sJb3X260OwxAOgetb5O+uJx62awizj0T94iKmY0RBp/WFtYuDDuidtTKk6elaS9MwqJraxQxCzs91ebUSl0Ubdn69YexP+Bc8jm9FrxT201FI49GZhV9VKdPuerQHi9b99t0v1s7bK3JxaTGWPK7UZPShjYNqvoRfP+h93EkTrqFanV8OLD6t2xj1wDdz/xGnzcwvvV4k5YV7qNtg7Z4u+/bGNVqlM1b3euytzvW4Qq5AAAgAElEQVTJe6gKzh4FcBzALwD6AniX47itjLEEWyXOkj4e/LFe0DK93XRMaDOBz3L9fvT3mHZwGg5OOYgCRYHJ294+bjuupF0BYH45utTN0tPZk6/42S2wG25kmj8ci27l2a9GfIUCRYHhAE0iLaa0ZtWt21RblvZZipd7vVwnAzQ/Nz8s6rLI4kWEQtceuSYq9pPKQXPkHKFiKpv3PyTXGlW3Zau9GN5yOOaEzMFTXZ+ydVLsXk0aUlgyx92SLJXzY+vfnZDcw8agZoNwNvmsps6Yibn8uue8k38n/Jf9H7+P2SGaYu+ajodsaXZzJ+E4zgGAttZfJGNsW+X0TwHsAuAMYDoA+S6ya0mwTzDiCuJE0/zc/Azmduka01q/rhrHcaLy8HYN2/FPWeYERV0Du/KVVs0l9UP/Y/ofyCjOgJ+7H9wc3ZBfnm/2drU9jGt5OHmge6PuCPULle2kV3ixmNZuGvbd2WewEQYAnJhxQraukLU5cA4G65DYM47j8ELPF6y6D916WCF+IbiQckHUJ5sD5yCqDC01SgfR5+zgLOqslsgzlHNbV1kq58eeAjS5z/Tp0E+RXZbN537dzL5pdFsKlUL0nq+O4qDTipNy0GS1BaCtCXtbMF342i5GRP5x7I98pXqtl3q+hOUXlov6ftES9slzeOphVLAKq6dR6PDUw6hQG95nU8+mSClOkZzn4+IjKtuvTuXJboHdsH7kenx5/UvczL4JB84BPi4+2D1Rvidw4QX0vQHvmVSZWFvXhBh3cMpBmw4G/MmQTxCVEyWqAP/6g69j5eWVfFGrtkd6QiztfgrQLEUboFmqGLcmhOfn1ym/8q/dnNz41p/v9HsHXQK6oH/T/nrrC+kGaHyDLjuvEmBPAZqw1m+BzGu7uPs2dGuo16Hl1HZT9Zrsa3MGhGMFSnXoZ4qafJFM2ecPY3/APxn/1HjYHEMGNBuAjTc3AjBteB7t04yhIsNgn2CkFadZJoG16JfJvyC5KNmi2zR3PNeadkj8/ejvazTQuZeLl14rrtkhs/niBnJ/+3zY5ya1kjRGmzNrasClvZ5Y81pXW2Z1mIVd0caH5TKVA+eANYPX8P2yWUszr2ZGq+1or/+OnCOCfYMll3FzcpPsbkOXbiO1SW0nISonymArVrvAGLOLPwD9oektiwH4UTC9rWD6UYn1FgO4CuBqy5YtmT0pUhSx1VdWszJlWY23pVKr2MCfBrIjsUcskDLbSStKY59f+5yp1CrZZV48+SJbcXEFY4yxTRGbWHROtOyyKrXK4LbMse/2PnYp5ZJFtlWbVGoVq1BVMLVabfFtb7m5hd3KumXx7drKsbhj7HjccZvtf/+d/XXyO2bPUotS2dpra02+Dhi6Ll9Oucz23d5n6SRajVqtttj1T84PN3+w+DXA1Ov25ojNLCo7qsb7U6qU7JOrn7Btt7axM4lnmFqtZkqVUnLZjREbWWR2ZI33aSoAV5lMXMQxO6kUx3FcO1QVZx5gjE2pnN4dwPXK6dsYY4/KbaN3797s6tWr1k0oIYQQQogFcBx3jTEmObK8PRXA3gWgrX0u7EdB+Po6CCGEEELuc3YToDHG1NC01gSAUI7j5lX2i6Yd3boCwB6bJI4QQgghpBbZUyMBAHgXwHho+kLbpjPvPcZYov4qhBBCCCH3F7upg6bFcVxLAKsAPAzAC0A0gC8YYxtNWDcTQLx1UwhA0+I0qxb2Q8xH58a+0fmxX3Ru7BudH/tW3fPTijEmOR6W3QVodQHHcVflKvUR26JzY9/o/NgvOjf2jc6PfbPG+bGbOmiEEEIIIUSDAjRCCCGEEDtDAVr1fGfrBBBZdG7sG50f+0Xnxr7R+bFvFj8/VAeNEEIIIcTOUA4aIYQQQoidoQCNEEIIIcTOUIBGCCGEEGJnKEAjhBBCCLEzFKARQgghhNgZCtAIIYQQQuwMBWiEEEIIIXaGAjRCCCGEEDtDARohhBBCiJ2hAI0QQgghxM5QgEYIIYQQYmcoQCOEEEIIsTMUoBFCCCGE2BkK0AghhBBC7IyTrRNgSQEBASw4ONjWySCEEEIIMeratWtZjLFAqXn3VYAWHByMq1ev2joZhBBCCCFGcRwXLzePijgJIYQQQuwMBWiEEEIIIXaGAjRCCKkDmEqFtA8+hCIpydZJIYTUAgrQCCGkDij77z/kbtuG5FdftXVSCCG1gAI0QgipCxir/G/bZBBCagcFaIQQQgghdoYCNEIIIYQQO0MBGiGEEEKInaEAjRBCCCHEztxXIwmYizGGwsJCFBQUoKSkBCqVytZJIoRYkaOjIzw8PODj4wNvb29wHGfrJBFCiKR6G6AxxpCRkYHi4mL4+fkhKCgIjo6OdMEm5D7FGINKpUJRURGysrJQWlqKRo0a0W+eEGKX6m2AVlhYiOLiYrRq1QqOjo62Tg4hxMo4joOTkxMaNGgAb29vxMfHo7CwED4+PrZOGiGE6Km3ddAKCgrg5+dHwRkh9ZCjoyP8/PxQUFBg66SYj1FHaITUB/U2QCspKYGXl5etk0EIsREvLy+UlJTYOhmEECKp3gZoKpWKcs8IqcccHR3rZsMgqjNHSL1QbwM0AFQ5mJB6jH7/hBB7Vq8DNEIIIYQQe0QBGiGEEEKInaEAjdQ5p0+fBsdx/N/ChQvNWj88PFy0/pYtW6ySTnPV9HMRQgi5f1CARgghdQl1s0FIvWD1jmo5jlsIYLPM7AOMsSmCZZ8A8AKADgAKAfwO4E3GWKK100nqjsDAQISFhfHvH3zwQRumhhBCCLE8uxlJgOO4dwCsEExyBTAPwBCO4x5kjKXZJmXE3nTq1Al79+61dTIIsQ1qfUpIvVCbRZzxjDFO528KAHAc1wrA8srlLgNoAuDRyvfNAYTXYjoJgLi4OFF9qKFDh6KgoABLly5Fu3bt4Orqiu7du4vWyc7OxsqVKzFw4ED4+/vD2dkZAQEBGDlyJDZt2oSKigrJfZ0/fx5z585F27Zt4eHhARcXFwQFBaF79+547LHH8PXXX0OhUPDLm1JXq6ioCG+//Tbatm0LV1dXNG/eHE8//TQyMjKMfnbhtoODg/XmDx06VLRMXFycaP6XX36J+fPno0ePHmjWrBnc3d3h6uqKJk2aYOTIkVi3bh3Ky8uNpsNccXFxePHFF9G1a1f4+PjAyckJ/v7+CAkJQVhYGFavXo3k5GTR8rrnWFdwcLBoGSn79+/HwIED4eXlBV9fXwwdOhS//vqr0e3HxcVh2bJlmDBhAjp06IDAwEA4OzvDy8sL7du3xyOPPILTp09L7nPhwoWibZ8+fRrHjh3D6NGj4efnB47j8Msvv1T3UNo3KuIkpH5gjFn1D8BCAAxAnIFlXq1chgGYKZh+q3JaHgAHY/vq1asXM9WtW7dMXrY+io2NZYJzwrp168Y6d+6sN03r1KlTLDAwUDRf969///4sKytLtJ/t27czjuMMrgeAZWZmivYlnLdgwQLRNvPy8liPHj0kt9OkSRM2d+5c0bTNmzeL1hfOa9Wqld6xGTJkiGiZ2NhY0XxPT0+jn6dr164sNzdXtJ6xz2VIZGQk8/X1NbrfPXv28OvonuMhQ4bobbdVq1aiZXS99957svtatGiRwe3v2bPHaHoBsGXLluntd8GCBaJldM8pALZ//36jx60uXQdK/vmH3eoQwu5Nn2HrpBBCLATAVSYT09RmEWdTjuOyAXgDiAOwE8CHjLFyAD0Fy93WeR0KwBdAawB3ayepRNeNGzcAAA0bNkTPnj2hVCpRVlYGALh9+zYmTpyIoqIifvmePXuiadOmiIyMxN27mtN28eJFzJw5EydOnOCXCw8P1wbjcHR0RJ8+fRAYGIiMjAwkJCQgJSXF7LS+/PLLuH79Ov9eu10A+Ouvv7Bjxw6zt2kuHx8ftG/fHg0bNoSHhwfy8/Nx/fp15OfnAwD+/fdfLF++HF988YVF9vfpp5/y2waAjh07om3btigoKEBycjLu3bsHtVptkX1pnTlzBuHh4aJpwcHBaNeuHa5du4YNGzaYtJ1WrVqhWbNm8PPzA2MMKSkpuHHjBp/eFStWYMqUKejZs6fsNnbs2AGO49C5c2e0aNEC0dHR1f5cdo+KOAmpF2ozQHMG4Ff5uh2AZQD6ABgDIECwXIHM60aoxQAtbeVKlEdG1dbuLMI1NARBb71lte2PHj0au3fvhq+vLwDwxXTvvfceH5xxHIcjR47g4YcfBqDJoX3mmWewfv16AMDJkydx9OhRjBkzBgBExYPh4eF45513RPu8d+8ejhw5And3d5PSmJqaiq1bt/LvOY7Db7/9xqfn+PHjGD16NB8UWsP58+fRuXNnvaHEioqK0LVrV8TGxgIAdu/ebbEATXgcR4wYgePHj4vmZ2dn448//kBISIhF9gcAa9asER3HmTNnYvv27XByckJWVhaGDBmCW7duya4/ePBgJCYmonnz5nrzDh8+jPHjx/Pvd+3aZTBAc3Jywr59+zBx4kR+mrBY/L5CRZyE1Au1UQftDoAnAAQD8AAwDEB65byHOY4bamBd4aOi5FWJ47jFHMdd5TjuamZmZs1TSyQ5Ojpi/fr1fHAGAK6urlCr1Th06BA/zcPDAxs2bMD06dMxffp0zJgxAzdv3hRtS7h8q1at+Nfbtm3DF198gWPHjiE+Ph6MMbRp0wZLliyBp6enSek8ffo0lEol/37YsGF8cAYAI0eOxMiRI03/4NUQFBSE999/HwMGDEBgYCBcXFzAcRy8vb354AwA0tPTkZuba5F9Co/jX3/9hRUrVuDgwYOIjIyEQqGAv78/5syZg86dO1tkfyqVSq9+2OrVq+HkpHnmCwgIwBtvvGFwG40aNUJsbCwWLlyIjh07wtvbG46OjuA4ThScAUBUlOGHpQULFoiCMwBwcXEx8dMQQoj9sXoOGmPsPIDzgkmnOY5bC2Bl5fsHAWQJ5vsIXnsLXktGX4yx7wB8BwC9e/e22KOlNXOi6qLg4GDJCvPZ2dkoKKjK6CwuLsbPP/9scFvCICU8PByPPvooGGOIjo7Giy++yM/TVjh/7rnnTA6qEhISRO87deqkt0znzp1x7Ngxk7Znrlu3bmHIkCHIysoyvjCAgoICNGzYsMb7ffnll7Fnzx7k5+ejoKAAy5cv5+e5uLigT58+mD9/Ph5//HG9nL3qyMrKQklJCf/e29tb7/vRpUsXg9tYs2YNli5datL+hN8xKVINHO5bVMRJSL1g9Rw0juOk9sF0Xv8teN9e4nU+gFgQm2natKnFtlVcXMy/njdvHi5duoTHH38cbdq0EbUUzM/Px4EDBzBq1Cjs2bPHYvs3hzA3TstQS9DXXntNFJx5eHhg2LBhCAsLQ1hYGAICAkTLW6qotWPHjoiIiMDSpUvRvXt3Ue6RQqHAuXPnsHjxYlEArEvqs5qaKy3VwtPBQf7ykpqairfffls0rVWrVhg/fjzCwsIwduxY0Txjx8mS309CCLEHtVHEeZDjuBc4jmvJcZxbZZHmS4L55wHsAaDtg+EVjuOCOI6bB00DAQDYyRizbA1nYha5m62/vz+8vasyOps0aQK1Wm2wta1u0VifPn2wceNG3L17FyUlJbh9+zZ++OEH0XbXrVtnUjpbtGghei9VB+q///4zuA1nZ2f+dU5Ojig4SEtL4xs9SDl37hz/2tXVFdHR0Th58iT27t2LvXv3wt/f3+hnqK4WLVrgo48+wvXr11FSUoLExET89ttvomLNDRs28I07dIsAs7OzRe///vtvUS6ZUEBAADw8PPj3BQUFeg06/v33X9m0Xrp0SRQQjh8/HrGxsTh06BD27t0rygE0haFg8L5DddAIqRdq46rWHMBaAPEASgGcAtC4ct4OxthFxlgCgPcrp/UFkApgW+X7ZFA/aHbLwcEB48aN499rc0Z0+zxTKpU4ffo0nnjiCVy+fJmf/uWXX+LPP/+ESqUCALi5uaFdu3aYNWsWAgMD+eXS0kzrp3jo0KGiIryTJ0+KijN130sR5saUlpbyrT5LSkrw9NNPG6x8LvzcDg4OcHNz49+vX7/eaq0L9+/fj3379vG5k46OjmjevDnGjRuHrl278sspFAq+3ltAQIAoGL19+zbOnj0LQFOEuWTJEtn9OTo6YtiwYaJpy5Yt41teZmVlYdWqVbLr634/PDw8+Fy4oqIiLFu2zOhnJoSQ+1lttOJcDmAONHXNmkJTpBkJzfBP32gXYox9wHFcKqqGeipC1VBPNIqAHQsPD8ehQ4f44GDVqlXYuHEjunTpAg8PD6Snp+O///7j5z/66KP8uhs3bsSNGzfQoEEDhIaGIjAwEEqlEtevX0dqaiq/XGhoKEzRtGlTzJs3Dz/++CMATdHYuHHj+G42rly5YrS4bMSIEdi0aRP//pFHHsEbb7yBzMxMox3M9u3bl88hLC0tRWhoKPr27YuEhARERESA4zirtCA9c+YM1q5dC1dXV4SGhqJp06ZwcnJCTEyMKBfR398fjRo1AqDJQRs0aBBOnjwJAFCr1RgyZAhatGiBlJQUySJPoddeew2HDx/mP8+mTZtw5swZtG3bFlevXkVOTo7sug8++KDoWOzZswfdunVDs2bNcPXqVZPr8NVLVAeNkPrBUFFUXfujjmotx5ROTIVOnDjBGjVqZFLHo2fPnuXX69atm9HlGzZsyG7cuMGvY6xD15ycHNa1a1fZbU2ePNlgR7UxMTHMx8dHcv0BAwbodYIr7Kj24sWLzNXVVXLdiRMnsoEDB8quW5OOal988UWjx9HBwYFt2bJFtN6FCxeYs7Oz5PJTp05lTZs2rXZHtc8//7zo/ahRo0xKs4ODA1u1apXB759uR7WnTp0y+VgJ1aXrAHVUS8j9BwY6qq1HFTeINQ0fPhxRUVFYs2YNhg4disDAQDg5OcHNzQ0tW7bE6NGjsWLFCkRERGDgwIH8ep999hneeustDBs2DK1bt+a7WvD19UXPnj3x+uuvIyIiQlRMZ0zDhg1x7tw5vPHGG2jdujWcnZ0RFBSEhQsX4p9//tEbokpX27ZtceHCBUyZMgUNGjSAq6srOnbsiNWrV+PUqVPw8fGRXbdfv344f/48xo8fDx8fH7i5ufHr7t+/3yItKKU8/fTTWL16NSZNmoT27dvDz88Pjo6O8PT0RIcOHfDYY4/h8uXLWLBggWi9/v3749SpUxg5ciS8vLzg7u6OXr164bvvvsPPP/8sKgKVsnz5cuzbtw8PPfQQPD094e3tjaFDh+Lo0aOYPHmyaFndivyfffYZvv76a3Tp0gUuLi5o0KABRo0ahVOnTmH27NmWOTCEEFJHcew+qnDau3dvdvXqVZOWjYyMNLnYjBAiLTExEc2aNdOrpF9eXo4JEyaIOszdtm0b5s2bV9tJNKguXQdKb9xA3KzZcOvaFa1377J1cgghFsBx3DXGWG+pebU5kgAh5D7z5ptv4tixYxg6dCiaNWsGT09PpKSk4PDhw6KGHV26dMGsWbNsmNL7yH30UE0IkUcBGiGkRjIyMrB7927Z+b169cKBAwf4UQZINVHjAELqFbpiEkKq7cknn4SXlxcuXbqE1NRU5OTkwNXVFUFBQejZsydmzJiBadOmWa3uXb1COWeE1CsUoBFCqm3o0KH1a5glQgipJdSKkxBC6gIq4iSkXqEAjRBC6gIq4iSkXqEAjRBC6hLKSSOkXqAAjRBC6hLKSSOkXqjXAdr91EkvIcQ89PsnhNizehugOTk5QaFQ2DoZhBAbUSgUdbNvNiriJKReqLcBmq+vL7Kzs+kpmpB6iDGG7Oxs+Pr62jop5qNrFiH1Qr0N0Pz8/FBeXo6kpCQUFhZCpVJRsEbIfYwxBpVKhcLCQiQlJaG8vBx+fn62TpbpKOeMkHqlDubvW4aTkxNatWqF3Nxc5ObmIiUlBWq12tbJIoRYkYODA9zd3eHp6YmGDRvqDfJu1+gBkpB6pd4GaIDmYu3v7w9/f39bJ4UQQgghhFeHHh8JIaQeoyJOQuoVCtAIIaQuoCJOQuqVel3EScj9rDQiAqr8AriFdIBTQICtk0MshXLSCKkXKEAj5D4VN2MmAMDB1xcdLl+ycWqIxVBOGiH1AhVxEnKfU+fn2zoJxBIo54yQeoUCNEIIqQso54yQeoUCNEIIIYQQO2P1AI3juPkcx+3nOC6W47gSjuPSOY47wXHcMJ3lmIG/BtZOJyGE2DUq4iSkXqmNRgJvAeggeO8OYDiA4RzHzWGM7ayFNBBCSN1GRZyE1Cu1UcSZB+AdAMEAfACsFMxbJrH8MMYYp/OXVwvpJIQQQgixC7URoI1kjH3IGItnjBVCE6wVVM57oBb2TwghdR8VcVoNU6mQvWkzKjIybJ0UQnhWD9AYY0U6k1wAOFa+TpZYZQ/HcRUcx2VyHLeH47hQ66aQEELqACritJrsTZuQsWYNYgYPsXVSCOHZohXn/wB4Vr7eKDE/AJq6cQEApgO4xHFcB4nlCCGEkBpTxMfbOgmE6KnVAI3juPkA3q98ewrAGsHsDwH0AuAFTX21A5XTfQC8aWCbizmOu8px3NXMzEyLp5kQQuwCFXESUq/UWoDGcdwCAJsr93kOwGTGWIV2PmPsHcbY34yxYsZYPIBnBKs/KLddxth3jLHejLHegYGB1ko+IXat+MIF5Py41dbJIKRuouJjYodqJUDjOG4hgE2V+zsJYExlgwHtfKl0MJnXhBAdCY8/gfSVK40vSOouCiJIHVd0/jzUZWW2TkadURsd1T4GTV0zBwBHAYxnjBXrLPYMx3HrOY7rw3GcG8dxrQB8I5h/3trprG3q4mJkrvsKubt22zophBBSv1Hsa3Xld+8i8YknkRb+nq2TUmfURke176IqEBwDoJQT16VoDcAZwOLKP11pAD6wZgJtIf3jj5G3cxcAwKNXT7g+QD2OEEIMoDpo1kO5k1anLtQUmpXfu2fjlNQd9jIW568APgbwD4AcABUAEgCsB9CLMZZow7TxFElJuDtuPBKfehqshj9odUEB/5pVVBhYsuZU+fmImz0HikS7OIyE1EuqvDyoCguNLyiHggjrMfPYZnzyKbI3b7FOWmqIMVbj+5NVaB8w7DFtdqo2+kELlhgZQPgXxxi7yxh7nTHWgzHmzxhzYYy1Yow9zRhLsXYaTaUuLITi3j0UnTkDVV4NBzdwcKx6bcKTcVlkJJS5udXaVeGxYyj95x9kfftttdYn1qfMyUFZVJStk0FMoMrPR8zIUahIMe/SdLtff9x+sE+N918WEQGmVtd4O1JKb/6Hoj//hKpItxaKfUl4/HHkbN0mOz//4EGU37kjmlZy/TpKb9ywyP6zN2xAxurVFtmWpcUMHmKf/blRgGY2e8lBqxsEgVTJxYs125Sj4UOvKihAZEgo4mbNBgDETp2G2GlhJm+fKRTVDuisQV1SgvTVa6AuKam1faoKCxEzajRKIyJqbZ/VFTt5CmKnTAUAqEtLkfD4Eyi/F2u1/cU/9hhS3nlHNK3wxAlEhoSi/O5dq+23LlCXliLr22+RvWmz5Pzkl19BRVISYoaPMLodplRaLmGC64+1ct3jpk9H4uKnkPzSS1bZvqUUX7iI9A8/lJ2f8vpS3Js4STQtfs5c/nqq5z4KGpSZmVDaUZdThSdPIvOLL6wWoKkVCtybNNngA64yJwfxCxZCmZVl0X1bGwVo5hBcIJNfedXgomkrVyIyJBSpy5bLbEtw6CVy0EquXgMA0ROfMjXV5KRGde2GO/0HoPTmfyavY0mJTz+D3Mo6dgCQt/dn5GzejKwNG2otDSXXrqEiMRGZ69bV2j6rS3hBLb50CcUXLlj0Cb08JkaU61Jy8RLy9/4sWqbwj2MAgNJ/TQ9oKzIywFQq2fnK3FyL3SyYSoXovv2Qt2+/RbYnJ+WNN5H5+VpkrFkjOd/UYsroHj2RuGSJJZNWxcoBRZkVH2oU8fGaHEgLDKuUGh6OO4MGgykUFkiZvor0dESGhCJl6VLcGTbcKvu43yU9uwRZX38DWCnXN2fLDyi/fZt/wNViKhWKzp4DU6mQu3MnSi5fRs727VZJg7VQgGYWcSDFlEqkrfhA8kKTW9knVd6ePZJbEufqaLZbcOQIsr//vsapjAypGh2r7D9xgJb2/grc7tff7G0yxlB48hSYSoXU5e8ia/13BpcvOn0aaeHhVRMqcwzV+flm71tX+d27iAwJRdGff9Z4W9VhyWbiysxM5O4Wt+TlHDTHSluZtvjyFUSGhOLe5Cn8MglPPIn8336T3a5uHZR7EyYiqmMnw4nR7jfmDjI++VRvG6URN0UBf9HZs4gZPARZX30lu8k7/QfgzqDBsvPj5y9AZEgoSv6+bjhtAFh5OdT5+Uh7/32jyxqiKihAwZEjkvNKrl1D8blzBtfnHKuqJxh7ACo+Y6XvqBVudnk/7zN7HVVBAdSlpWatk7NtOyqSklAocw7MkbdzF5SZmWYXN2tV5URWfdeZQoHcnbtQ8vd1FJ/TdCCQf+AglKmpSFi8WHR9rdY+GUPS8y8g47PPJeenhocj7f0VetO1172c7duR9PLLUJeVGTz2Sc8/X6N0lsfGImv9d5avemHpHLQi3dEkNXK3b0fiokUoPl93O4GgAM0cOhldxefPI3f7dqS9G27WZkr/+QcKYTESByS/8gqSX34FGf/3ieYJ3VINtnR+DLk7dlSr/lzh8eNIevZZZG/ahLzdu5H52Wd6yxRfvIjIkFCU3b5tYEs1/2Cl1zU384LDRxAZEspfMGOnhSHphRcNrlseE4OMzz6XrcOjysszWL+n9MYNRHfvgaIzZ0TT1WVliJ0+g8/xLLl+3aSKuolLnkPa8nfFEysDpYrKRh15P+/VpD06ml+k+Px5pLz6P6Pb11WRnAxFXJz0TAfNucnZuAnZGzZApVMcEDdjBuKmT69K+yJNo+uic+ILIFMqcW/aNBQc/b1qWkUFkl/9n16xbeaivdUAACAASURBVMmVKwCAgkO/itOZmoqEp56CqrAQyuxszUQTikhYRQWSX3kVZdHRSHrpZcmGMSmvL0Xyy69IHof4eY9AXVxV/yoyJBTZGzeJFxIEaDmbNcWgJdevIzIkFFnffFMrFbStUQctdXlVbr8qPx93J0xAhUyufd7evUh44knc7tMX0b16IzIkVJRjbhB/Gi13nKqzrezNWxDVvYdetYvEJc8hLTwc8XPn6q1T/OdZ2e1VpKby16PC48dllyu+cAGFx44he/16VKSl6c3P27kLuTt26E1PfVtTJSF9xQcoPHIU0d17ILpHTxRfuCC5n8Jjx6FISJBNhzH3xo5D5mef6eVMySk6ew7qsjKU/vef5vug04VURVo6AIBZuk8TmXOvvQ9JHeO6ggI0M+h0DwKmqrxImnmx1M1x4zgOBYerniaZUglVbg0bIfAbE6RN53tcfOkSbg94SLZCcPm9WKgqW5tqi6kyP/lUdleFxzRFZCV//SWRDs2/3B07UCyov5e7c5deZV5jtBdjYf0eplaj7NYtFP7xh3BB0XqqoiLcmzAR2evXI2+3fs5m1vrvcLtff4M5TSWVwWGRzlNZeXQ0ym7eRNqHK1F05gzi58xF7nb9i6wuZZZU8V/NgtjIkFD+Yq4r86uvcXfMWMl52py7qgny6RDWgeKcnUXzCo4cQfmtSFE9pphRo1Hw22+4N24cIkNCRcGblLh581B85k/cfrAP7jw0UBT0s/Jy2VyM0n//RcHhw4idPAWFR48i7QP9Hnq0QYcwJ7To7FmURUZKbjNnq3iEBtF1oPL3lbBgIQAgc+0XyP3xR4OfTU7xxYvIXPcVKlJSUHz5ChRJyfILC645ytxcywQ7OttQxNxF0vMvSC6a+s6yqpyJyrSIcswN4I+fjap9xU6fAQDIXr8eUKmgKiwSHb/is/JBmCGFJ07yr9NXruJfFxw5AkVSMl8nuOBQVc43Ky/nX+f8+CNiw6oegHQxJn2fKb58RXYdueDN0soiI5G4aBHSV69GzpYfAABp776L5Fde4ZfJ/Lwyx5CJ7y01JnNcUHl/FuZ41zUUoJlD74bF9KYn/+81pLz9tmipiowMxIZN529qujdC3cqshX8cQ+pbb/Hviy9dlkwOYwylEREGL86G5mV+vhaqnByU346WnH9v3DjEzZip3ZDsdnhOld3qSVWMFtxQMj9fy79OCw/X+/wmcxCcDwNBMlcZ8CQ88QQ/rSJNP2cgW6Z+nPAp1JSbiyIpSfP/nnxle6ZSoSI5WXo7DvKBkcGbtkD+PuniqpJrV+VXkhzQQ19FegaiunStWs1FHKAJbzpaSp2nWGPFlMoU8fkpuXRZsi5b2a1booBf93uqzMhE7s6d4hwniZy4xEWLETt1mnRiHDg+Z6Ts1i2oK6rqO/EPaYKbgG6OYuy0MFFuQmRIKPIP6RdPJzz2OLLWrUPM8BFIWLAAd0eOlE4PwNf7UyQk4E7/Acj54QfZZU0m8Rti5TUrzk94/HEkLnlOZ6p0TihTKpF/6LcaB5vG1i+7eVO8f6a2TLAo2K/24bH033+R/PIruDtyJO70HwAAyN9fVYdS+L1MX7lKr0qKVum//6Lsxr/S+zXwPKeIizdaFCpFt4GM8JgqMzP1vuPaeqsV8Qko+LUqN1yY8aBVHhkpvrfUEFPLnDztsXWgAK1+0AnQ+Ox/wfSCQ4eQr1OXI2bwEJT99x9S3nxLcju60t4VF3klLFwoel/055+IDAlF+spViJsxE1lffw1VZd2uivR08cYY4/dXfjdG/HEqAyrtxSTzq6+Q/PrromUU8fGV2zGY5MrtaW7UUi018wQBQ+mNG5KVetNXrTJav6P40mWkVTa8KDhYdSEoj4mRW0WTptJS0QVOshWc7g2DMRQcOYK7ox9G4clTmonGukTR2UbcvEf4m7swxy/j008RM2KkXuCi2YX8PnRv2ubWh6mIFxd5aOvvlEVH6wWGdwYOQvGVKyj97z/EjBrNTy/9+5o4vYIcNMYYUt9ZZjwhMjdRdVkZsr75Rm96+sqVuDv6Yb3psdPCkPDY48j45FMkv/IKSnVuYuWRkUgLfw/Z32+smlj5ObU3R21ALYcTXOBjp4WJb5RqNZRZWaLvMystFbWELbt1S+83nfI/84unRSqPX0WyJmAvOnUairg4s7rHqEhORtH584YDGmdnZHz2ud51QU7h6dOi98UXLqLoxAnxQjJF1Tk/bkXK//6HzLVrkbB4MVLeflvydyrZIECwqdyffjIprfwqNSguFqVPGMRkZCBv717Z+lG66xSePGlwsbiZs+RnGrhe5GzZwheFqoqKUHL1qqhaiJa6uBjJr78OZWYm1MXFeg1khHWp4x55BIlPPimazxfJ6ubCCyhixdUb+HtLTcl8f7U5jpyBB157RwGaOXR+COkrKotPDHwphZTp6SiNiEDm2i9qlIzExU8BAHIri16yvlyH2337AQBihgwVLyz47uo9genkeGV9uU4U9GilfbhSMjco/9dfkf/rIRRfvoKsb9fzAZ/w892dMAFlUVEo16lomvHJJ3rby/lBUzRUFn0bGWvXSl6cdYNVrcSnntafKPjs0T16iucJgqWiM2egiI/Xr1g/dhySX9Zk0ZdFaYu/qm4u2gtdwZEjshfJ0mtVwYwwS7/4wkV+O4ZkfvGFxfpuknJn0GDEDB+B2MlTUJGoH6gkzF+AuLDpfH04QL/+E1NUQBEfj9w9e5C3d69pO5a5KWZ/t6Fav4/sDRtQcPgIMj7+WHJ+0ZkzmqLf8HDwQ/9WPnnfHTnK4LYrDARwZdHRuDNwECBoyVpy9SrujZ9gNM0l164ZXUaLKRTihjna/fGfRY27Y8bK/j7UpaWIX7BQlNsYM2IkEp94Evk//yy5DgCU34pE9vr1outCWbR0jjsAJD39jOR0RWIiUsPDwVQq5GzZov1UomW0OaTZ365H8Z9nkf/zPsljpC2ilCOsH1p+7x7K78XqBSRpKz7gGyypy8pFuT7miOrSFVG615ZKqe8sM35vUKnAlEokPSvd2leZm2vSQxhTKpG6/F2DXfOkvPEGCn6vqgKiSEzkf693ho9AwcFfcWfQYET36q2fTG09UOg/5AGA92jNb8itk5GGSDoU8fEojbgJdUlJZT3GnZr0DBuOpJdeNm0jctdQbc6a4BwwhQKpy5ZZpAVxbaiNoZ7uIzKRuKkBOmMWy9Y1Vfnt23Bwd5Ocp5uDphUZEoq2gkquuTp1cLRSXhM/Vfs/9ZTeMoqYu5KVTEv/lS+ajZ08GQDg3KgRGs6ZI7mMHkNPwRLBE180hargjnN3Fy0jqkSuTavE03/yy68geLemgrQiPl42t1FdUgL4+cmnE0D0g33g2LAh/z7ra/3cJF2WehJV5uaYtJxu44SSS5c09doYg/9iqdHa9MmFpeYWxZhKGyjn7dwFty5dKhNR84r2FTWohB0/7xGERknXe9OVs3WbKCcqZsRIeA0ZjIaPPgqgKreg7OZNKJKSkDB/AVrt2A7noCAAQNZXX6Hk8mUkXL6M0KhIpCxdym/LcKMefUXVaJmasvQNlP79N3wnTeansQqdqhBSOR0S14hyyfRKf6PujRuPoHf1uzrKFXS3kPGp/sOise2KligtRc7WbUhfuVJiruGbA1Mzg93U6DZGkqLOL0DJlSvI270bebvlx3YuOi7OyYybMxeqrCz4Tp1qcut6YX1hxhif2885au4lhUePmrQdrbsPjwEAtD2uqb+c/d0GNJw9G8rUVBSmpiJ3zwB49u8Pl+bN5Tci9ztW6zzEACg6eQqK2FioCgrRfG1VK1qmViNn8xY0mDUTjl5eZn0Ga6IcNHPIxWcmjpGnlqibY215u3fzOVNCkSGhMhc6DUP1X+Rkr19v8rKqvDzEjKjq6FPqxqw9XmkfrsTdCRNQ+s8/stszu1Ub01wYM9auFU3T3XfVPE0l7hJt8Z7ujaPyO6AuKABUMp2TMgZFQoLm2MtUSFcXFhq96esGttqLHABE9exlcF2rqUyTMifbyIKVlErp30MtjDfJKs9P/LxHRHXpbCH/0G+IDAk1WmFa9/fBFAoUHjteVQFa8MCRt2sXKlJSkH/wV+T8+COKL1yAqlhc9Jl/4KBgY2YmuhqnSKXtNFvUaEn8m5W6jlqkY1EjdSt1A5fqkO80V7+hkni2keuWXP0qgdwdO6AuM//ewrfSNqHOn/aaI+xyI1N07aysLlDNh8WcymGzdK9tacuW4+7IUXx1IqZUQq1TxC182AY0xc6sokI0PWudpisgvphVLQ6Ki8+dQ8bHH4sad9gDCtDMIBeIqQqLNE2rjdQjMFT52xLumlCsIqSszObN+ubbGvftYy5FbKyoIrhUvTVlegZKb/6H3K1boYi5i7jZBnLTBAGaSX2kMTXy9uxF9jeC4a8E24ju1l0vvQmPPY7CI8afEJlS8+PP3aFTF4Yx2RaUZjHUKKQWR2qQ3L+JNwp1cbHeMQZg1s0/88vqdUBcfksTHGsv5LakrYumSJAeJzfhiScN5rDwxTeiBxSOn5a+chUSHn9CbzURMyvl67X2NYH2xij8LKIb6PrvxPUEK6W89rpJjQZYRQXU5eVgKhXfKEhLrs+72lB0WpwDdm+SuEFU/i8HZI9/9saNUKab1kVE0rPPVi+BAPJ/PWR8ocpAUVj/L/vbqgdy7TWvurQ5mqykRPJ835s4CRUZGYjq3AXRXbuJ5gmLwSNDQhHVpSui+/bjfxOKuDi9EpaSvzR18bTd8Gg/V/Gli8g00K9jbaMAzRwyAVrJpUsAIFuPgGflZuWKag7Ro+1XzJakhsTJ2bxZ1O+WQTo/wNyfdsLQAWeM6XcLYOBGUKDXKayBkyn3VCxosFEjVuqR2xLfT3VZ9YootQGKqbnRAAx2kFvnyHz3is+fR1SnzsiSGQ1DGyyJgjg+gKraZt5PO2V3rdRtWGSU4XMUGRIq3/+WMJ3Clt0S/SryixUVgSkUUBcXG6gWMQXR3bojdoZ+/TSphjimkuuuxlRV9e0q06LTOjlnyxbZ33PGx/9X4/rKpkh9802jyxSfO4eK5GS+myGtivQMVCQn87nSNaXKz0fOpk1609VFRYjVae3PKipQFh3NZzSI5pWUVJWqSBxfbV+gxRcvahq2VF53lCmpmjrd/QeY3NjEmqgOmjlqeHO1xNO6ufVF6gpFXM3qUekWcRadOlWVKydVB02qdZgZ+1MV6A73IxgnUSV9wWVqtWUCNCt1hCpX7GoOVlK9AK343DkUnT8vmYtSH8RJBBam0H7XRA84lV8xYXc2QrpFy4XHjpmcGxnZqbM4yJJRfOEiXFq21JuevaFqpBSmNi3XJW/XLmT8n6aemN+CBQaXLb8VCeehjUXTDOZA2gHZbiLsSOk//yBmhH61l5ghmkHZ/Rc9qTevujI+/j/J6SpBPbniixeR9e16lFyW7oIKAB+YZX37rewiBb8eQslff8FziHi0E1VuLtLee9/0OtBWQjlo5qjhzdUSN8Cy/27VeBv2KMHIhdcoiack7Y9XLTF2ou44lADMCnwKDomLBSqSBEVUcjceBosEaHpdqdiRmnSMmfRczYamqY+0vd0zpaDjYCNFkNES9RRNyY1UZmWZFJwBAOck3feU8PshLCIzRBucATCpv7cina4+7D1Ak71e1CFyD6XWkvDY44aDM2ge0gEYLHHQdqqurOZQYdZGAVpdUwvDyNRFhuqplFw10DmreCPV3r+2PypA3KO4ePuWuYgZ6xairqrLPX7bmkLY9YGxDoerGbDcGTjI9IUd7adwRikzXJW9sPsA0hQWKuK0ldoYnq06KEAzRy20MDPKTr9ItmaRyvE1qNslfMrneyrXUfDbb3T+iHUIi+ztoGNOdUmxSQ2PIkNCRWOf1kv3QYBW00YCtqaIqV79bWuzn8ecOsH2F77UZSb00k6qx8rBkyl9mtVr9vAAdD+wg+Nocq41INkxan1iaGD1ukLYr9z9RNjXmy1QDpoZ7OC6Z70WfISQ+4ItbyhapnRHQzTSwt+zdRKIjLyd8q2fawMFaOawgwsfIfcrqcYcpBpMHPSeEGJYuc74obWNfsnmoACNEGLnTB7NgRBimI27QKEAzRwUoBFC7Fzuj9Jj5xJCzGTjLlAoQDMHBWiEEEJIvWD2GM8WRgGaWShAI4QQQuoFKuIU4ziuJcdx2ziOy+Q4rozjuBscxxkZ7beW1PHO+AghhBBiIgt1Ll5ddhWgcRwXBOACgHkAAgC4AugK4HuO4962ZdoA6/T47D16tMW3SQghhJCaqe0hrHTZVYAG4D0AzSpfPwqgCQDtgFvvchynP/puLRINSGwhAc8tsfg2CSGEkNrWauuPtk6CZVEdNA2O4xwAzKp8G8kY28YYSwPwaeU0ZwDTbZK4Sg4eHhbfpqOXl8W3Scj95oGTJ2ydBELqlUZLl5q9jseDD6LN4cPwe/xxfpp79+6WTFbtsvHQfHYToAFoC8C38vVtwXTh6x61lxx9zo0bo9VPO4wu13jZOwAAt44djS7rGBAAp0aNqt4HBqDh3Ll6yzWYOdOMlFpGy00b8cDpU/x7B4lg0mfcWACA1/Dh8B41UnI7zT79BI1ee41/79igAfyffgoeffoAqDpOjgEBRtPkGzYNDWZM5/fl4OmJxm++IV7I0RGu7R7QW9dz8CA4t9RkwnIuLgb349a1KwCgwaxZBpcTEn7G2hAU/i7/usGc2fAc0F922dYHD8DBwwP+Tz0Fz8GD4DV0qOyyDt7eAMTF764dNeMqeg0ZgmZr18JnwgT99Xx94RIcbDTdzi1aiN679+7Fv/YcNAitf9mPJh+t4h+IgsLD4dy0KZp9/hkCnnsOrXZI/wbbHP4N7c6fg9eIEZr9tKzKcOfc3MRp9fHRO17az9hk1Sp+WtCK99Fk1SoEvvyyaFn/p56C17Bh/HtHPz/JY2IuBx8f/nWDGTP0Pmvw7l1of+ki3Lp1rfG+qnYqvg149Otn8KYa8OyzaPrJ/1V7dw/8eUby92mI56BBCI2KRKPX/sdPcw0JMbiOKddfKUHvLjf5ett09UcAqr4zLb5bj4bz5gHQfEeEOFdX+EyaCM8hg+E5ZDC8x44xuO3gPXvQeLnhof1c27c3OL/1wQMIWvG+wWWkBCxZAv/HFiJ49y50uP43Gr32Ghx9Nbdnn0kT+eWarlmNB86chkf/fvAZP16Tpjat0fj119BiwwYAQKP/vYqg92RGS3B2hu/kySZ9HrdOneDRr5/Zn6UmHDw9a3V/ehhjdvEHoD8AVvn3o2B6G8H03w1to1evXqy2KAuLWEVWFmOMMUVaGiu5eZOpSkqYMjdXb1m1Wq35r1Lx6+bu21+1rbw8VhoZyfIO/sqUeXmaZRUKVnz1quZ1RQVjjLGSiJtMWViov32ViuUdOsQKTp0ykuZCpiwsZGq1mqkrKlh5YiKryMlhjDFWkZPDVKWlkutV5OSwovPnq9JW+TmkKNLTWUVODlMWFrLSqGhWfOWKwTRpj41smgsKmDI/n5X88w9L+t9ronnF1/5mqpISg9tWpKUxtVJpcB+MMaZIS2dqhYKV3b3Hkl9/XZyG3FxWfO0aU5WVMcYYU5WXs/L4eOl9qlSs6NJlpiwoYDk//cRK/v2XlScmsbI7d1jR5cus6PJlxhhjZXfvsawNG1jBiZP8+a3IyWF5hw4xtVrNii5dZuryctG2i86fZ1mbNjNVURFT5udL7r8iO5upKtdTpKczZW4uU6Sny35uVUmJwfOZ//vvrDwxianKyvjvCn9c8vOZqqhI9jgoUlIMnt/YufPYrU6dDZ5DQ1RlZawiM7Na6xqjSElh5QkJ4mlJSazgxAmmSE3lpxUcP84Uycn8e7VazVTFxZr/5eUs/f/+jynz8ljOTz+xipwcVhoVxdRKJSs4doyVRkezspgYVh4Xx0qjomTTkrN7Nyu5fl1vekVWFiv88yxjjLHiv/9mpVFRLHvLFlYScZMxxljW99+zzG++ZVmbNrOymBimKipitzqEsNKoKFby77+s9NYtVnztGmOMsaKLl1ju/v1mHc+8gwdZRXY2yz/6Oyu7c4e/jpVGRbOSiJtMkZbOVGVlrOjiRc3xKCtjFRkZ/PqlUVGsIjubKdLSNb9ThYKplUqmSEsT7Uf4/VSr1Szz2/Wic6NWKjW/l8rvmu53tfDMGVaekMDUajXL/+MPVhoVzRjTfH8Vqama62JBASs6f56VRkeL9q0qLRVtqzQq2uj3Vfid115zjSm7fZuV3b6tOR7JyUytUIjmKwuLWNnde0ytUjFVSQkru3dP73qtLi9narWald29J/mbV5WX1/j3Ivzum71uUhJTlZez4r//ZozJX/vVanXVvTIvjxVduMBKbtyo2k5aOn9MVaWlLG3VR3qftyI7W3R81Go1y923n6mKilhFTg4rPHOGldy4wVQlJUxVXCw6x/m//cZKIm6yxJdeMnpPtQQAV5lMTMMxG2fhaXEc1x+aBgIAsJUxNr9yelsAMZXTf2eMjdFZbzGAxQDQsmXLXvHx8bWUYkIIIYSQ6uM47hpjrLfUPHsq4swSvPYRvPYWvM7UXYkx9h1jrDdjrHdgYKDVEkcIIYQQUlvsKUC7CyC/8rWwIFr4+nrtJYcQQgghxDbsJkBjjKkB7Kp8G8px3LzKftFeqZxWAWCPTRJHCCGEEFKL7KYOGsB3VHsVVX2hCb3DGPvQyPqZAGqjEloAxEWyxH7QubFvdH7sF50b+0bnx75V9/y0YoxJ1s+yqwAN0Az1BGAVgIcBeAGIBvAFY2yjTRMmwHHcVblKfcS26NzYNzo/9ovOjX2j82PfrHF+nCy5MUtgjCVAM9QTIYQQQki9ZDd10AghhBBCiAYFaNXzna0TQGTRubFvdH7sF50b+0bnx75Z/PzYXR00QgghhJD6jnLQCCGEEELsDAVohBBCCCF2hgI0QgghhBA7QwEaIYQQQoidoQCNEEIIIcTOUIBGCCGEEGJnKEAjhBBCCLEzFKARQgghhNgZCtAIIYQQQuwMBWiEEEIIIXaGAjRCCCGEEDtDARohhBBCiJ2hAI0QQgghxM5QgEYIIYQQYmecbJ0ASwoICGDBwcG2TgYhhBBCiFHXrl3LYowFSs27rwK04OBgXL161dbJIIQQQggxiuO4eLl5VMRJCCGEEGJnKEAjhBBCCLEzFKDVUxGnk1CYU2brZBBCCCFEAgVo9VBxfjn+3Hkbh9bdsHVSCCGEECKBArR6iKk1/8uKK2ybEEIIIYRIogCtHuI4W6eAEEIIIYZQgEYIIYQQYmcoQCOEEEIIsTMUoNVnzNYJIIQQQoiU+2okAWIiqoNGCLEipVKJnJwc5OfnQ6lU2jo5hFidk5MTfH194efnBycny4RWFKARQgixGLVajcTERLi6uqJly5ZwcXEBRy2TyH2MMQaFQoHs7GwkJiaiVav/Z++846Oo1j7+m2waaZCEAAmk0DvSi7RQFAS8ykWxoAjKRRDfq1y4eC1c+xVU4FooVrg2VJogKor03kIgkBBKCimE9F52s3veP3Z3MrM7uzu7O8lukuf7+QR2Zs4588zMmTPPec5znhMNDw/nByhpiLMZQyOcBEEoTVFRETw9PREeHg4fHx9SzogmD8dx8PHxQXh4ODw9PVFUVKRIuaSgEQRBEIpRXl6OVq1akWJGNDs4jkOrVq1QUVGhSHmkoBEEQRCKUV1dDT8/P1eLQRAuwc/PD1VVVYqURQpac4bRICdBEMqi0+kU8b8hiMaIh4cHdDqdMmUpUgrRqKChB/uoLFVj7YL9uHo6x9WiEESjgNoYormiZN0nBY0gbFCUo/cnuHwk28WSEARBEM0FUtAIgiAIgiDcDFLQCEXQ6RjWLtiPS4cyXS0KQRBEk4LjOP4vJibGrrwHDx4U5Z8zZ069yGiL1157TSTHpk2b7MofGxsryp+WllYvcroTpKARiqDV6J0ij2277mJJCIIgCKLxQysJEMpCE0MJgiAIE3r16oUZM2bw2/ZaApsjpKA1YxSNskGTtgiCIAgLzJw5EzNnznS1GI0KGuIkFIUMaARBENapqanBxo0bMW3aNHTo0AG+vr4IDAxE586d8fDDD+OPP/6wmp8xhi+//BLDhg2Dv78/goKCMHHiRBw7dsxhmU6ePIknn3wS3bt3R0BAAHx9fdGhQwfcd999+PHHHyVje23atEnkF/baa6/h+vXrePzxxxEREQGVSoXnn38egDwftNTUVMyePRtt27aFr68vevbsiXfeeQcajUbWNVRUVOCjjz7ChAkT0KZNG3h7eyM4OBijRo3CmjVrUFlZKZkvISEB8+bNQ48ePeDv7w8vLy+0adMGvXv3xqOPPoo1a9aguLhY/s1UCLKgEQRBEEQDkZycjOnTpyMpKUm0v6amBuXl5UhJSYGvry/uvvtuyfwajQYPPvggtm3bJtq/b98+HDlyBAcPHsSIESNky8MYw3PPPYePPvrI7FhWVhaysrKwa9cujBkzBjt27EBISIjFsuLi4rB69WqUlZWZy63WWpUjPj4e48ePF61jeeXKFbz00kvYs2ePzej8CQkJuP/++5GSkiLaX1xcjGPHjuHYsWP49NNP8csvv6BTp0788UOHDmHSpEmoqakR5cvLy0NeXh4SExOxefNmjB49GoMHD7Yqg9KQgtYMoRiSBEEQDU9xcTHuuusuZGRk8PtUKhX69OmDqKgoZGdnIz4+3moZ2dnZ2LZtG9q3b49evXrh9OnTKCkpAQCo1WosX74cf/75p2yZ3nzzTZFyxnEcBg0ahMDAQJw+fZpfV/Lw4cN48MEHsW/fPotl/fzzzwCAqKgo9O7dG7m5ufyqEurKWov5NBoNHnroIZFyFhgYiKFDhyInJweHDx+2eg0FBQWYNGkSbt26xe/r1asXOnXqhLS0NFy6dAmAXuGbOnUq4uPj4ePjAwB4++23RcrZwIEDd+/1jAAAIABJREFU0aFDBxQUFCAzMxPp6elWz12fkIJGKAKv89EYJ0EQhCSrVq0SKWcdOnTAzp07MXDgQH5fVlYW4uLirJYzbdo0bN26FT4+Prh27Rr69OkDtVoNADhy5Ag0Gg28vLxsylNYWIgVK1aI9m3fvh33338/AOD69esYNWoUbt++DQDYv38/9uzZg8mTJ1ss88UXX8Rbb73FK2amlikpfvrpJ1y9epXfDg8Px4kTJxAdHQ0AWL58Od566y2L+VevXi1Szj755BPMnz+f337nnXfw0ksvAdAraRs3bsSCBQsAQBSu46mnnsLnn38uKjs7Oxt79uxBu3btbF6H0pCC1pwhZYogiAbmyI9XkZ9R7mox7KJ1ZABGz+zmdDk//fSTaHvVqlUi5QwA2rdvj/bt21st5/333+ctQF27dkX37t2RkJAAQG9Fy8/PR3h4uE159u3bJxo6HDt2LK+cAUCXLl3w7LPPYvny5fy+3bt3W1TQunXrhjfffFO0FqtRTmuYWvwWLlzIK2cA8PLLL+PDDz9EaWmpZP6dO3fyvzmOw++//y7y4zMdct29ezevoEVHR+PatWsAgN9++w3vvfceevfujW7duqFjx46IiIjAk08+afMa6gNS0AiCsIvqcg28WqigUtEcI4KwB1P/qDFjxthdRmBgILp37y7a17JlS9G2HKsVALNgr3379jVLY7ovNTXVYnmjR4+GSqWSdW4hN2/eFG337t1btO3r64vOnTvj/PnzkvmFMjHGsH37dqvnE6Z/6aWXcPjwYajVamRnZ2PZsmX8MT8/P4wcORJ/+9vf8OCDD8q+HqUgBa0ZwxQ0oZExrvnwxdIj6DKoDSb9rY+rRSEaIUpYopozUk76jihFgF6ZEeLsQt8RERFO5W8ojH51ADBu3DjEx8dj3bp12LdvH65evQqtVj+hobKyEnv37sXevXvx3nvvYenSpQ0qJ3WBmyGKxj8zLbsJq2qmjVlz5vq5XFeLQBCNjo4dO4q2bTm/1zem8hiHSa3tsxZgVji0aQ+RkZGi7cTERNF2dXU1bty4YTG/UCZvb2+UlpaCMWbxz9Ry2LNnT3z00UdITExEVVUVUlJSsHXrVtFQs9Qs1/qGFDRCWdxIh6nVaEmpIgjCbRD6dwHAkiVLzIbtbt++jd27dzeIPBMmTICvry+/ffDgQezatYvfTklJwdq1a0V5pk2bprgcEydOFG2vX79eNOy5YsUKi/5nAHDvvffyv9VqNZ599lmzmGeMMZw+fRrPP/88duzYwe/ftGkT9uzZw0+y8PLyQseOHTF9+nRROI6cnBzHLs4JaIizOaOk7uJmelB1hQZfLDmCofd2xJCpHW1nkIGz5n+CIJo3S5YswcaNG5GdnQ0AyMzMxJAhQ9C3b19ERkbi9u3biIuLw6xZs+pFETIlJCQEy5YtwxtvvMHvmz59OgYNGoSAgABRmA1AP4ngnnvuUVyO6dOno0uXLrh+Xb+Wc3Z2Nvr27cuH2TCGybDE0qVLsWnTJn626VdffYWdO3diwIABCAoKQkFBAS5dusSHI+nfvz+f96effsLOnTvh7++PXr16oW3btgD0Vjyhz2DPnj0VvWY5kIJGKMLlI1kAAJ3WPTS1qjJ9b+jq6duKKWiNhduppUi5kIcR93dWvGyySBKE4wQHB2Pv3r3461//iuTkZACAVqtFfHy8zfhn9cWrr76KvLw8rF+/HgCg0+lw5swZs3QjR440C46rFF5eXvjhhx8wYcIEPmJ/aWkpP7tzwIAB0Ol0uHDhgmT+1q1b448//sD06dN5paqkpAQHDx6UTO/paa76VFRUSF43oJ+k8N5779l7WU5DQ5yEIsT97rpgfoSYrSvPIm4PPQ+CcEd69eqF+Ph4fPbZZ5gyZQoiIiLg4+MDf39/dOrUCQ899BAeffTRBpPHw8MD69atw9GjR/HEE0+gS5cu8PPzg7e3N8LDwzFt2jR89913OHToEEJDQ+tNjoEDB+LcuXN47LHHEBYWBm9vb3Tt2hXLly/H0aNH0apVK6v5+/Xrh4SEBKxfvx6TJk1Cu3bt4O3tDW9vb0RERCA2NhYvvfQSTp48iccee4zP98orr+D111/HpEmT0LlzZ7Rq1QoqlQqBgYHo06cPFi1ahPj4eNx11131du2WIAsaQRAEQTQgvr6+mDdvHubNmycrvS3LtSVLEQDExsbKsnyPHDkSI0eOlCWPkTlz5mDOnDmy0v5z8Yv45+IX0SY6yGKaTp064euvv5Y8Zu0ajfj5+WHBggV8jDM5DB48uMGXcJILWdCaITRMRTgMVR2CIIgGgRQ0giAIgiAIN4MUNIIgZEMGNIIgiIZBcQWN47gojuO+4Tguj+O4ao7jLnAc95SMfPdyHLeZ47hrHMeVcxxXwHHcMY7jZigtI0EQjZuMpELcTCxwtRgEQRD1hqIKGsdx7QAcBzALQGsAPgD6Afic47iXbWRfBOBhAF0A+AMIAXAngK0cx72gpJwE0RyoF19DN/Ff3PVBPH7+UHrKPUEQ7gtjDNpanavFaBQobUF7HYBxbYTHAYQDOGXYfpXjuCgreasAvAegB4AAAM8Ijr3EcRzNOFUYN/nWEm6OuroWn/z9INIvkcWKIJobWo0OWo1yClVVmQYFWeWoVWsVK7OpopiCxnGcB4CHDJtJjLFvGGM5AFYb9nkBeMBKEY8zxpYxxpIZYxWMsfUAjOGDgwCEKSUrQTQLFFLAi3IqUavW4dSuFKtFbnnnDNYu3K/MSQmCcAsKsstRkF2uWHnq6loAICuaDJS0oHUG0NLw+6pgv/D3AEuZGWNSNcC4SFg1AOq+KwVZziyirqqlhsMEuStc5aaXUd0iCIJQCCUVtNaC36UWfreRWxjHcbOg90cDgG8YY2onZHNLtLU6bHv3LLKvFblGABrjFHHrejE+W3wYG5496GpRFKFeni5VGUIGFGuRaK4oWfcbIsyGsP8tS3KO4+4C8Llh8zKApVbSzuc47izHcWfz8vIcl9IFVBTXICelFDtWnXe1KASAWzdKXC0CQTR6VCoVNBqNq8VwKxhj0OlIaW0OaDQaqFQqRcpSUkHLF/wWruUQKPhtU4PiOO5uALugH968AuAuxpjFLydj7FPG2GDG2OCwsMblpqbyck0YOurcNhPoQRMuIDAwEKWlpbYTNiOKb1ciP6PM1WIQDUBpaSkCAwNtJ5SBkhrCDQBGRaqbYL/wt1VTkUE52wm9cpYAYCxj7JaCMroX9P1sVDT3YRvGGNVZwiYhISEoKipCfn4+1Gp1s39vAEBTQzMWmzKMMajVauTn56OoqAghISGKlKtY6ArGmI7juB8AzAfQ0+BDtg/APwxJNAC2AADHccY39n+MsTmGfZMA/AS9chYHveWsUCn5CHOEzWZ5UQ3+9+IxzFg2CO06tbSYxx5uJhagqlSN7sPDFSmPsA+lPouc3FkCBAHAx8cHUVFRKCwsRFpaGrRay8qJpkYLDxUHlWfTXtSmrKAaAFBQ6WsxjU7HoKmuhXcLL9kTcxoCObLbU46ntwdq1Tq0KPaCp7cyQ4HugEqlQmBgIKKiouDj46NImUrHFnsVwFToY6F9Y3LsdcZYhpW8L6Ju1uZAAAUmH4ZxjLGDCsnpFriuY2l+4qxkvS6ccDBTUkEryatEQCtfy8OyEi2KMZBoU1HQSFEBGJnQCBn4+PggPDwc4eGW3/2inAp895o+TOaiDeMbSjSXsHaBPvyMtev8Zd1FpF3Mx1/+3h+RPZWxwCiBHNntKSembyjSEoow5Zl+6NiztY1czRtFuy2GuGd3AvgO+rAYNQAuApjHGHtbyXM1DdzoY2dQPqSURk2NFt8sP4l9/0tsYKHci0Y3VKOwuEpdfmZyEdYu2I/S/CplCiQaJTVVta4Wwa0whvdpDO1MRXENTXpoABSPzs8Yuwn9Uk/W0piZIhhjsUrL0hAU365Ei0Av+Ph5uVoU+5H5fhmjSN9MpBHnZonxbWVQROlLPJoNAMhJKUFQ6xbOF0gQTZAjP16FVqND7KweipV59XQOgsP9ERbpuBN7bnoptrxzFp4+Kjz9wVjFZHMGdVUtKkpqENzO32q6C/sykJ9RhglzejWQZM7RtAf+G4BvXz2Jbe+ecyivqzpKUuflR+8kD9arOCIYY7hy8ha0WvcLFms6xKnTMVSWuj48355PEvDp84fqrXylR3Z1Wn0d4zxoyNiUIz9edTguYmWpmqwaTYiL+zNx+Ui2omXu/TIRP759xqkyctP1s1Fr3Wjiw84P4vnhcmsc3XINV07mNIBEykAKmgIU5VS6WgTnMXwrXd28Xz+Xi32bknDu17QGP7e9Qwsnd9zAxmVHUVVuXUnLSCrE+mcPoKayfmJD3TifB021RGNZH2ulK1DGjbhcAK736dv+/jkc33bdpTKYcnF/pkNxEasrNNi47CiOb3Wv62mqMMZw9tdUlBVWu1oUAkBuWtMM60IKWjNG+LHlZJjJGsLiV1OhV2Iqy9w/0GXqRX3ov+py67Ke/TUNulqG/Azl1rNzDcpWAFfPubh1vQTn9950rRAKoTb4c6XEN65g3Y2VktwqnNqVit82JLhaFKIJQwqaC3FLZ1B7hz+VPr0Lb0l9W3Qa+tKUm3EpuC8KXkRDrHnKGOMXZ24O0CzbhqHa0JE0/k8Q9QEpaK7EndpS4xCnlEyuNnU0EPWlMDeV26f07QkMrZ8JAmkJ+Vi7YD9y00tx7extfPb8YRTeqrCY/mw9DacnHs22awjMqfonnMjRWGhMsppwZncqgLrYXgRRH5CCRgAQWo8st5rW2lOldBBHlJminArcThX7ILijcbLBhVLodEormKHt/eulXCO/rL0IAPj988tIidMP+RVmW1bQTu1KUVyGmqpaHPjmCnauscOfzIHnlXoxHzWVmnqx/q5dsB8ndtxQvNymQLOejOGWjasetxyVcgJS0JozUpXZWv22ckyp18KR9+u7105h68qzTp+73oY4m4gFDWh8DaBxxllDy80MH3B7hsDslbGiuAa/rruI3z+7JCjDriJsEvd7urIFCmlC74UzxP95k2ICKkXjap5sQgqaQhijJNuD68Js2Gkla2QfZUepv4+4IQhwPZVuCfd9aob7Uc9WiNK8Kqdn2cX/eRNrF+x32I/Nnipl792oNcQnLM6talA/UcVoQFHP7UnDpcNZDXdCmeRllOHY1uv4+aMLrhYFOq0Ol49kQWcjxJE7VzE3Fs0hSEEjAAgnAlhO0xCVX2kjljv4f8m5t80KNwnpIoeEg5kAgKoyfSiVtIR8XD1jO46SQ/XOzjkT4nO4phMghysnbiEjybVBrk/+lIJD3yW7VAYpjDHJNC6ayHL9XC4/8/fS4Swc/DYZCQfdT5GVjTtrjw5ACppLcXFlEsfZ0O+SqOANWeeVPhdjsOogLkTuEGetRosL+zLs90NxkQkt6fgtFOc6EavP2gQSZ2jQeqXMyX5ZexF7v6ifJc8cnoHJ3KMjYol9/0vCrg/izQ+4sczNhd8/u8SHCqmu0CuJ1fUUr7EhaGL6GSlozuBso++yyiS5WICM1tKKwHLaWo1aiwPfXJHll6NU2118uxKbXz+FWzdKbKaV+zzP/ZaOo1uuoTTPvfxGLMm//6skfPfqScljOq3O5vAdJ9TQFKiznJXOgPviYI2szzFOPhujWZxEg+HWr60DsmVfK8baBfud68TWE6SgOYErKurlI1nY/r5jS0tZRY6VxMnrTTyajcSj2TjzS6rNtErf2tI85V4+Rxd5ru8YVabPTqgAWXquf25MxGfPH65HqazQkO+P0+eyswAHTFp2tycSSlnjUnoJt8RmFXLfOuZI/U8+eQsAkJXs2BJr9Ynii6U3J5xuDB3IfvBb5fwoZJ9esSma9iWvKKmBf0sfhU7uPMbnbe+nt8F80BiDvdJdO5trO1H9xKl142beNdjbnjTUUlmMsfo5VyMe4myKerA7D5PLRe5jKb5diaunc9BtWDv+wt3xmZIFzRnc8IHWB0bLT0NebmZSITa9cMw9l65xUENT4v4xxix+yCWjpkjsrCipQeGtCrt7jMW3lbFCcnyD2HA1qsEbX0dO6OgQZz1f2/6vkuqn4EbcfjqqzFis841IO3JHRcaI3Jnh3756Emd+ScO3/z7p1h0FUtCcoCkNJ3AeMsY4G/BySwz+XbdTbfuONRRGxUKWv54wn4IyHP7+KtYtPCB9UOr5SOzb9MIxbH79FH6yJ4gqDFVDyTrfqF4fy09x7YL92PjCUdklMcaQk1Ji5otp9winMLQGq/upNFdO2J616ixNqS21iqXh6MZ0/U6KWlPpXkuv8W+2Gz4DUtCcwdkRTjeqEFZH4ZSeWal1n+u2B/55OapxKXDZlw5ZngJvVp/s8U+31vOsr8fVOKuBJJUlatlpk47fwrZ3z+GLJUdE++2PC1dnmeUffWO6p8L3yA3kvnW9GOufPeB07DxrMIsbzQc5E7askRKfx/uNmeHIPaUhzqaJOz5QuxDIf2hzstk+8+TKXHCCFSWjMWD3aEQDzVqUaUCTzuuCytyg52zolQSsnC43rdTyQcfPaPhX3nXqdAwFWeWWS2uI++VmkxsuHcmCrpYh80o9OosLJ+5YSlJ/Z28S/LYhAX9ukh52d6QeufEIJylozuAOjYotGGN8kM26febpyotqLB5ztnfOdAyHNiejKEdePDLJc7sBvKO0oxpaPWNqgWGA7BtofWTb9mxQR2hUkziVPK+l+mO3kEz0nz1lnPklFd+/eRr5mRaUtAa+YW70moOrx69ifV6nRq3F2gX7kZaQX49nce/vnkOi1VecRwUgBc0ZnB7iVEYMayQezcaX/zxqtbcsRnmhCnMqcOlQFi4fyVa87IbE6Vmc9Y2Uci03awMu/uySlRXcyAHfon5m58mYQD+zV06jFa+iuMa+jEriZkOcDYJwtQjhQxNUCkebi+STel/BX9ZedLCEJoAD9ajufrtfJSQFzQlcEWbD3nNnJOnN9VLR9CWHQ6wV63711zL1KasLfdDsLl7mOesz/p3lczaeCmW3km3l0iwV5fDtqIcZo0o9mdICK8Gc3WyI00h99qdE1miLaQhHqe9Ykw0NKWhO4NI2xalzW84s6cfEmMVjPO48kA8oYsbiZ3G6wQin5JJcplYwOyL/u+QD6UYuaBcPZNbTiSX2WahASjwDh4PdOl2QNAVZMt0amtB3NT+zHKkX8lBZKjFxpB6vs7xI/uQGba2dC78KcCNd2gzmyGXRJIEmitMGNMcLkNuY2z2cZKPcguxy/PifM1AbounXVNXa1TDYjRu9NHX33LEwG0peitzGRG4dk904ubkPmmWLjfWzHfnhal1KxnB4czLWLtiPsgLH6rbV+66Qws53nJjwtzJ3tUFeOzsCIFeU1OD7N0/X6wxLe7B2m3946zR+XZ+A7988ZZ4PQGl+FTRqrcWLdrR6nPstXbR96XCWmf+xkQ3PHkT2tWIHz1RH6oU8/PyhxDqrDsB0zOK6yQXZ5fXWiUw4aOicudG3xggpaE5gWmFyJGJ2VZTU4OC3V6DVSqj2Tg1xykxodIC0cLJatRa1Gq3sk57elYq8m2XISCoEAHz/5in878XjMoWxH6XemT83KrjAtZUWtKKkBmsX7EfqRYGjLlcPXqiSi9ozW0ksF2fFB03xdtHYY60Hv7evXz7hcF7jmnxXT992fqaxI0Oc9vb+hZN3lL6VDfGxEg5x2qgLySdzUJBVXvcxdTFyrOhVZRJrDjPg61dO4Lf1Fy3eY3tvfY3E4uZFORU49F0yfv/8ssV8WVedn6366/oE3EwsVER5Or/3Jja/fgp5N8tE+9Mu5uP7N07j6unbljM3yvV9bUMKmhOY1oVtK83XyDz8/VVcPpKN9IQChU9e97P4diW+XHZUsncp1Y4I5f7k74ew6YVjksekzmWc4WRMV17oQidjCzDGcH5vuu2EdlIXqNYyxllxlyQ+JPU+A9LGs7NantzZngp8uZ0Zbb6dWupQIywnyxVDbKWMxEK7y7d4Xol9lpdNcuzeip6JUnVMoXIUH913wfdXp9UhN70UBVnlOPtrqlMTK4x1NyOpSJF36drZ2/j8H0eQmy4O3aIzxJq0ZEFzCinXZQU6WzkpegOHqdXaaFWTNdGtAfy6GxJai9MJ5DxQXT0FZRWe+/LRbFSVqnHt7G0MvDtanJC33kgVov/PVmRn4WyxNIOi6Y6V2UhuWln9Rj83+epoauoskMbbravvWZFSjaTUPrnFWbXe2HctWo0OKi+9Jv/pc4cQFhWI6UsGOlssUuLz8NuGBIx7vId9GWWSdEyvoHEq59UKq6+HxVmctsutqdSgqlyDVm38ZC/t1SiwJXZDWEgkitbUaPHpc4dE+9IvFcDTWyWryLybZfjxP2fqTiFDfA7yrVvGkQxTq5Oc89nbUVq7YL/Fd4/pAMi7JXYj55lzgEOzmd0dsqA5gaQJW8Av6y4izTDUJfUyOFOZhHk9jFYtGcNUcX+kW11T0dZsPq1GZ/NciuLATXLGAVYOphaQLe+cNTtW7w2F3I+z0pMEZCTb9GKdRVZTo7Xo62Lvx7YkV+9fZslPpSGxJrvw3ZD8Bgp2Ct0LLJW5e+0FHPjmCgDg838cwbf/PmlwmajrOdlb32wlb+jZcLbqgnF5tYbxjat7QNfPmQ+r2bNU0c1E8ciJqN20MsT502p5y7BZ1LGEy4ApSMLBTHHdqIcOqaW6Z1WhVGB9X3dU7khBcwJhz0iKNIEfkuVhDccQVkROpk+PRq3Fie03bMTJkTdO5o6V2RbXz+VaPFaSV2XTB0hWT65uYTfzfYoOcdpWxopzK+UPXVq5dnufdXW5vuNinEjiaLmaGq3IksAHEHVA/7anQ3HluIVlZARYWg+1qkyNdc8cwMZl+rU5JYc4Bb8TDgp83SyImJ5QgMSj4hiCtTVak/vHRP9Z48K+DH4Y12Kr1MDvt806JiGotlZnPYxHPWHP+2Da7gtHVBS5xRY6hPauFyzEaufD9Dz16E9q69z2oK3VoTTfRl1xw28aKWgOknT8ln2VUvJ9kc6v1ehweHMy/6GTzCnyC9MXrpP4cAkXVJYlr9yhM4U0NK1GB53UBAqnkJbt0mFpx+/yohp8s/wETu1KEe1POZ+HL5cdNX+xrbR9dQ2WlFT164Rm+ky2rTyH+D8z5BVnkjf1Yn6dQuug2N+9bj6LDZA/tPLpc4fw0+rzSL9sYoVwk5b0Rpy5wl+ab3uWofCjLaz7tl4p4ftbq9HV6WRWjDJMx5B6IU/0fI9uuWZTRve4w3VIdXL2f5WEr18+oZ8R6aaYKmhy2mB7VCtL75Kpr7D+t+m5xZllvZcmoXuMWZS0oDmiXBpz5NwoQdwf5v7HB79LxtevWJ9A5C7tihBS0Bxk/1fSa4FZQsqCJnxfNGot4n5Ph06rw7Vz+llkx3dct1ie8UU/8dMNnP01TbRPXV2L4lzDMKbhtAXZFbh2xsRcL1MZkz6/eNvR/tqG/zuI9YsOmjm58udxoMyfP7wgud/oMFuYXcEP1QJAVbm0I+1vnySgqlSN/V/ph5fkTBKoaxjNLZxGqss1Zj3/WrXWrqE7STunxM6cG/Km0hvlzbtZBsYYfl13Eb9/dknWOSxh2ZnavuGIwmz9fTHeR6FrgSXfG6WREnXPpxL3R06NFVQHcd2wnle4LFOtUClhrE4+kyIuH8nCr+sT7PfJbHALmv1D7OmX9Iq78F1uCGoqNSJHdmuhP0yXjdLJHOKUjQULljEGG7OmvTuA2WMyae90OoaMxEJUlCgzeawgu5y3Olof4tT/98cXl3Fi+w2zw+lylr9yP/2MFLQGw1CBUuLzcGzrNWQmi51Az+xOxYkdN3D19G2+Qgpfugv7MpB6Ia8ug9GnbE9db8H48u9ccx7f/vukqPzzf9zEwW+TRfuk6qPRXyjvZhnyMy1//BhjOPtrqsXj9nJih/lLpT+R/WXVWmiwdVqGylI1Nr9xqm5xeEgrz1J+bPxSTx7m6StL1di3KRFajZWhJsO+r14+bhYOYt9XSdj8+imoq2X6t0iUX6vWmuW3R+FOv1yAH/9zBp8vPszvd/Tjl31NhpOzTNn4x2P4X9jR+PE/Z3DzcgGunbmNLe9YdzkwotMxHPj2iryT8zjmo1dbo8WZX+reE61Wx/vSAfr3ms9qcqtT4vOwdsF+fltY7zQ1Asub4LymCmK5QUmuKLYvfphizvhWPqpylBVruMrNoqpMg5K8ume46wPLccCsWdBqLVj+dn8k3cGULN/Cft6HTeYtzr5WJMv6a6oIGq1dxm/Wj2+fxq4P40WRAaxhDEt047y5NbqssBrfv3Eap3+W8Z2xYSGQU1e0tTpcO3PbrSba0CxOhVm7YD96j2mP2Ee7i/Zz0Fu2ftuQAACI/zMDM18awh83+utkJhchomsrfR7By206LGEtknxuep1i5agvgtG/btGG8RbPdWqXcwqacHhHCcf+22mliN970+r5qiv01pdbN+pi1kn1zA58bd8H/Pj260g+mQMPw+xF0T0zCYMmnPUJ6C1N18/qG6iaylp4+9p+LavK1Ti+7Sb6xnbg9333mvSQohwYY7zioK6uk2/D/x0U1VMpNGotikysfztWSTs5/7kpkZ9OL3dIocow1G/Jj7Mop9LmsJ3wceRnlCHRznVh8zPK0TLMT6Jc29dw+udUDJnaEcknb+HYtusiC6BktHkDxrbCiMqz7vpr1Vp+W1OtxcX9BkXPgo+QlPuDq/lDEKPL1m3kXQes1Jn8zDLsXBMPxhhGTO+M3qPb2yUPP1vdzg+0MVB3eVG1+TCaSZXVmQ5TC/ZbC+9SVliNnJQStO0YBF0tQ6u2+rpofCUs1SPGGI78cBVV5RpE9w6xKJul99W8PPH9MbbbTKcPwCt75QgDRqvw5SPZ8DS2nYZnbM3FR0hRTgV0tdafmdz3FAB8/b0Q2SsBdBaTAAAgAElEQVTERuqGgRQ0O6mu0Ngcq798OMsseCDHcWY9lIsHBL1nw//JJ3PqlBUrM2Qk/cJM0jHGHBp7NK3MZkOjALJMLIAVJZY/NJaUxNQLdWbnW9dLcGpXCvyCvGXJV1ZQjaDWLUT7t644ayGHHnW1FpcMAUg9bIRSSD5lPiQkZ6knY5qS/GpcPZODyJ4hqFVb/zpu+lddb9O0V220oCzaMF6032iBs+RXZyTzSt1zunQo0/JwDAOunpYeBhPWB6E/Xq1GC08vFQ58fUWyjkhhXNAZkPbTkyJuTzo8vTzg6+8leTwlPk9yv5DrZ2/j0Hd6q+nURf3knVjAnk8vmT0DQO+/KJc/N0m7RZz5JdXMSlCQbR7zqVwwZKxRa+HjV9d884F1TRU0DxvDyYK6nHgsGwe+voK5746Cp7ftwRV1dS0+e/4wonqF4N6/97eZPielBCnn89D/riic+jlFNATOmN667eWjQvqlAhRklePKiVtoHRmInneGm3Vyjm27bjYJ5dKhLL4DdvDbZLsVNF4Wnf6963hHa3S8o7XN9EblICU+3yyskjULmsjNwoqifn7vTRzfZu7uMnl+H74xMrq5mFKaX80vYyb3Ha00tOWFtypw7aw4j6V6VJpfhRaB4vdz/9dJ6DqorUVl59d1F9EmOhCAvM9U3O83MWJ6F9E+nY5JdkyZjolHOuzQuaslAv+6ClLQ7OSLJUf4GE/WMFpEjHh4cvjhrdOifZb8Qvi8DNj8xineB0fIxmVHMf+DsaJ9ph88nZZJOjLbQmjhObHjBuJ+N3e6vHZWfrlSvd6aSo2Z1ezsr2kY83A3s7S56aXISCpEwsEsVBTXoMeIdrhyIgfTlwxEy7AWZuktUV2u4SORe6g4aGt1UHl6iJQGq9dhaJwyky37dRmbhKpSNfZ+kYiIrq34YWOtxlz5mji3l2jfoc3JyDKU/8z6cbLkksuhzVctHtv8ximLMfuE9WHbu3XBmHd/fAFRvUJlNfzCoTopfll3EbdTSzDrjRG4uD/DTGGxNswhZ8marKt1aX6X8B2Tg1SP/quXxKtoODI6IjWR4+A3yWb7TgrcAMxncRrOL/it0zF+JrlOy6DT6uChErddJ3bcQEi4PwKCffmZoqX5VQhuZ24tFFKr0fIK783EQpzYcQMjpnfmj99OK0VgiK8oj7HuZCYXSfoOblx2FEGtfUUd2fKiGqRdzMeomV0BAFq1FjqtTmQp/2LJEXQb1hZXT4nroUathUrFmV2zKcknb+HETykIi9IrC8b3PPVCPjreEWY1L1DXgZZSXkyXwRPWVbkruEgpZ4C+09BvXAfJY3KwNGEh6fgtjJ/dE5slJvmU5Fbh5E8pZvt3rIozL+fYLSQdu2VxFAaoG+25mVjIK8O3U0rRvluwTfm3rDiL3DRp32WdjkFlUNCqKzR2hUahIc5GjiN+OSpP642E1JBLko3p/t+bKHwX9mfgjomR/La2VmfTeiOFsPGTUs7kkHS87nqkFMzP/3FEMp/Zu8HEccaAOsW2IKtc0h9MDvkZ5djw7EF0HdJWds8S0JvTTa2H1hA6E/+5KQltO7YUHTddgipLoPxdtnMYzhmsBVS2FJMpK7lYJK+9MMZwYV8Gug9vxysSQv+3+sKSj6ItvlgqXWeNqKtqsf0989VEAPFan3KQmtksdF34dX0CJj/dx2oZny8+zCvXcXvSEbcn3cwKmJ9Rjn3/S8J9zw8QvXub3xC3LUJK86vMhvLifk/nFbSSvEpsXXEWAcE+CAn3N8svZcU1di4t+UFpDL6VicduIfGYebtoqpwBwKd/P4QWgV7oOritZJnV5RpsfOEoX/eNFj2hX6CUJd0iEq/Q+T/ELhdCP2BH2mZTjNYxR7DW6eEnmSlAeVG1XcsBnt97ExlXCtFrZITVdJaUM0C/1uiiDeNRkF2O763UZUkYkJaQD/+WPrzS7ipIQbMDyfU0ZVIfkeVL88zjugh79J89b/1jZ6kHdeaXNKfk+u61kyjKqXvB/7CyHpwtrPmcHP7evo+eFPYoZ5oarZn/mBGjFc50yNH0Y2QMOCoHo4UC0E/asEfWxsA+w5CfnLAPjQFrCpy1D6lUvDihMmaJPZ9IzCLVMWg1OnAe5r6Olsi8UoSinLpOlNBKKsWt65aV8tz0Ur5DVV5UIz0ELPFKS60nKcRRf9eqMo3o3htXo+g6pC1aBHhJdkyEHUp7OmP2Wl5s3WdXItWpdhS5ypnQ5SU/o1yyfT++3XJkA1NsWe0tkXjsFv/cpdwaGhLOncx5zjJ48GB29qx1PyRnKC2ocmoxZsI2nfqHyfIpchWhHQJQkCljTTiCcEOkhgIBYPRDXZF8MsemYhjdN9TiusKLNox3+KPY2Fm0YbxFXzGi8TL1mX6I6WfbD9EZOI47xxgbLHWMwmzYgbrKfQMiNhXcWTkDQMoZ0aiRUs70cLL85ywpZwBwbGvTsIQ6wpEfr5Jy1gTJuGJ5Zm1DQAqaHbTuEIAZywaJ9vm38hFtG6c/EwThGAHBPrYTEYpy5IerTgf9lbtqRVPk4n7HfcGUwvTbRCiAiwcYSUGzE9Np0+27tcJjbw7nt2e9Ptw0iyJ0HdIW4x7vUS9lO4q7xIpprnh4OjZBwt35y3P9MXBytNU0E57o2UDSEISy3D2vt9XjtiaUSeHtqzLLF9ohwO5yZJ2rhW3XdXsMFVOfsT/sTUOh9Bra9kIKmp34+IsrZ/tuwWgZ5ofJT/fBlIV9AQBDpsYAAO57vj+CWounmrfvXjd9uOed4WjfvZXouGksmQdeGAyVpwfuGB+JrkOkZyMpyfD7O8lOa1p3TWW3hPH+2MOwv9iWa8ITPbFow3i+oYpyEwVy8JQYyf09hrdzqtxJ86Rn8Q2cFI2Jc3pi5stDENrediPdrlMQnlk3Dl0GtRHtlxMDSi4qTw/c97ztWFmAfibviPs7i/aZdgZ6jAjHE+/cqZh8hOOEd25pO5EFhKE5hPQZ61gMs8aApVmlABAY4isZOmPOypFYuDbWcr5Q83BDOkMYI6Oi1mt0BPrfFYX5H4zFnBUj7ZRaT9+x7dFB8A0b+UAX9BvfAd6+Kty/eAAWrhuHBWtjcfdT1pVQIeFdHK8/9Y2r1+ckBc1OWrWp6xm0iQ5Ez5HhAIDOA9rwMXOG3tsJizaMR4ceIeg3PlKU//7FA7Bow3gs2jAe42f3xP2LB2Luu6P44z1GhIvSt+0YhAUfx6JtxyB4eavQf6K4vM4DwkRKn7NE9Qrlf9+3eADu/b87EGWIQO2h4jDr9eEIidBPnffy0Sur3Ya1xez/3In7nh/A5+01UnwdQobe2wkP/Gswpj17hywlICDEBwMmRaH7MOsKjVGuiG56pbffhEhryfVyjrI+lVtSnmAfPPX+aPOyRlsu64F/Dcakv+kVqt6jIzBn5UhMmNMLPn6eCAz1xYxlg6xajTx9VGb7vLxVkoF9uw1ti+7DwxEWGYiJc+ssTc+sH4e5747CxLm98OR7+jrHeXCYsrAfOA8O3U0URkv3e+CkaHToYbnOmebr0CMYCz6ORYce8hRmb1/9tf7tv2Nw32J9nZJScgOCffHgi3W+tXc/1Rt3z+st6gA88K/BGHSPdWucFCP+2hmh7QP491tIz5HhmPx0H/S28ryVYqzJiiRS2NOpqg/++k/rQ2uTn+6DRRvGS1qOBk6KFnUM5q0Zg0UbxmPsI3XXba3jZxorsFP/MAycFIX+d0XJFV9xVF4emPnSECxYG4sn3rmTD8YKAH4tzd/Xth2DMGGO/j0dcHeU5MxSL28VPFQeFq1vbTsFITC0zhgw+ek+fJzJyfP7YPzsHhgzsxtGzugCLx8V/Fv5mL3vRsbP7omh93bktwdNjua/WWMe6Q7vFnVtUb/xkRg9sxv+9t+xaN89GB4eHFQqDzPDxJBpHTH56T54+N9DAQB3/rULX6acuKIA0GNEO4x8oIvNdP3Gmyu4ox7sCi9DG/rw8qGyzgcAPn7yjA71BYXZcICnPxyL5FM56HFnuE0TaGuBmdk0KKkRvyBvfjpvWWE1zv9xEz2Gt8Poh8yDto58oCvunNFFdN6qMjUOfZeMG+frHOznfzAWXj4qqKtq8ZmM2FIRXVvh/n8MEC1DY+wpRfUOhU7HwEH/QR/1YFcc+OYKYmd1R3A7PwycHA0vbxU/Vb9VWz+ovMwViinP9OOtbm1jggDop+ynXsjHsL90RE1lraQfy+y37gTnwWHi3F58XKKZLw/Bj2+L1170b6n3XTJa0LQaHZ54507kZ5bjl7UXAeg/CMLYbgPuikKHHsF8KJBxj/dAr5ERVmej+QV5wzfAC6Me7MqHiAiJ8Me4WT34eHYT5/YC5wEc23IdPUa0Q8swP7SNCUJQ68EIjQjgG6WnVukVPY7j0K5TSwyaHI34vTcxaEoMPDw4cBwHxhiqyjTYuOwoL0NAsA/adgzC9KUDcfNyAToPbMOvfxckCN4b2j4AXYe0RUi4PziOg1+QN69AmU4hj+nbmp+JFxYViM4D22DmS0MQHO4HD5UHbl0rhpevCm2i9c8uP7MMLcP8oKnRrwGaeUW/TFlIuD//nGL6tZY1hHHv3+9AWGQgygqrERCsb9y9fT3RoXswL+eiDeNx8UAGovvUdSLaRAdh5ktD8PPHF9ChRzBaBOo/gK0jA3F823W0jgxAcFs/XD19G2Me7oaWYS34yOPGGY1dBrdBQLCvKP7fwLujMfDuaNRU1cLTS4XM5CIEBvvgZmIhVCoPdB7QBp0HtOFj1fUZ2x63rpfg7nm9cWzrddy8bNmZXshTq0ajrKCaX1oNAAbdE41zv6XjqVWjUavW4pBJnoGTo3E7tZQPBTBocgw6D2xjtv7ulIV94ePniayrxfLWM7SD7sPa4daNYox/3PZQs3EWnHD1jnue7otOA/Qd2vFP9MT1c/rA1z6C4bPgdn4oyqnEk++Nhk7HsP6ZA/wx3wAvVJdrwHEc5qwYic1vnMKomV3RY3idQt2pfxjaxgRi/aKDFmXrMqgNf+7H3xrBx3ebPL8POg9sI2oH2sQEmcXeahMdaDbzdcxD3fj4WQHBvpiysB+/Wsi4x/RuKg8vH4rv39TH52I6hh7Dw3nZU87n4cL+DHToEcyvBKIyrOzQZVAbvq2aOKcnTv2cithZ3dG+WzBUnh6id9oYpsLTS4Wed5p3JowrsfQaHYEBd0Xx9ce/pTfad2uFi/sz8cC/BpktcSaMPelhIQ6lj5+XaFbv0Gl1Cp9pu2NpSPeup3rhyvFbCA73x+iZdd/C/hOjcPV0DvZ+WRdDMnZWd/QaFcF/F40+gcHt/BAU1gJ3TIjEHRId9pAIf0x9ph9UXh5IPJpt9p6YBhdvaEhBcwBPb5XsZUSEEZFtWYAAvYn7qVWj4ePnaVH5M93fItAbk5/WD69++vwhaKq1vCLk3cITz6wfh5rKWnyxpC5O05CpMTjzSxo63tEavUe3R9uOQfwHfM6KkWZ+BsIXMbJnCGa/rR9eEg49Gi1qHXoES8ZYi+kbaia7b4C+h6LyVOHOv8Zg8JQYsyC2UsFowyIDMX52D+z/Sh9X7Mn3R6FFgLehLH16ba0OAcG+CAj2xfQlA5B1tRhDpnbEkGkxuLAvAxVFNWgZ1gKt2vqh88A2uBGXiy4D9b35WW8Mxy9rL6L4tj6e21//OYgPQjpwkt4ic8eESET2DEF+Vhm6DtIPW/ztv2OgUnnwCli3IeJnblRu+GszuR/evp4Yem8nszRGJf52ail8/Dx5Hw/vFp68VVcqZg/HcXYNNwivAYAoUKOppbZ1B/0xLx+9JU9oXV7wcSwOb07GkGnia5n6TD/8su4iv/3Xfw5CcDs/fhkno4JliX7jzBvZsKhAPCmwQgP6j3On/noFQNXCg6+vADDjhUFIu5iPgZOi4aHywKgHusDTS4W2MUFQV9fCy7uuc+HTwpNf3eLm5QLcTCxEWLR58MroPqG81cdLYO1sHRmA/AzrM3/DogLx8L+H4vs3TmPI1BgMvbcTht9nGPrz98Kkv/VBVO8QaDU6ZF4pQpfBbcBxHJJP5fDKaqs2fvr6kVbKL3lmtOhHdA22qaA9vHwoNDVaUWyuYfd1wqmd+qjxizaMx9aVZ3E7Va+gdB7URtThNCpMRu6e15tXJDwMdVzYhnTsX2c5N95vU5/Kh14eyseP9PDgMPfdUci+VoyqMjV6jgznZ536t/LBvNVjzK7JOPQ69N6O8PJR4djWulmWD70yBD+8dQaD7onmFbSg1i0QGOqLsoJqXpmcvmQgAkN9+VURjArHPQv6IqJrK1w9fdtMQTOupWxEOJHM+P4LXQ9MZ892GhCGp1aNhpePColHs9GyTQv+fRS2F21igkT12hRjQHWVl/R3pPOAMJzZnYreoyJE725ohwD4t/ThO4+mjJjeGUkSwYKlmLqoH9+GWkLqOzf03o7oNqSdWftppNvQdug2tB20Wh1Szuehy6A2onLmfzAW6qpas0l8RozP37+lN6+oDpna0ew9USKYsDMorqBxHBcF4D8AJgEIBJAM4EPG2Bcy8oYAeAvA/QBCAaQC+ALAasZYo41xMfTejpLBKC1hac1BOTzy72HIvFIIT8FHhuM4+Pp74fG3RsA3wItfjLvLoLZo1baF2VIoliq1LQKCffDIq8PQsk0LlBdWI/t6MWL6hgLgMGRqjOSL2De2A5hOb5bmPDj4+HmJepfWzNE974zgFTSjcgbAoGzlITSirhGM6BqMiK56BcPTS4VBk2NEZXl4cCLfkFZt/DDr9eHYvfYCeo4IR3jnlpIKUEiEPz+0CkDWQufO0LZjkO1ETqLENag8PTBOwroS009vpdv/dRKSjt2CdwuVU/XdEdp1bIl2hhUdJsyuk9HUB8+UqN6heHj5UNHzNmLsaABA7KPdoa6uRUZiIfxb+qD/xCizFSOMS4AZrQehEQEWg2LycvlC5Icq1eEzrs9pyfdwysK++HV9gtn+Vm39oPL0QECwD8qLarBwbSw8VB68ggbo/WEZYyjMrjAr/56n+/ALbt8xMRJdB7dFTL/WqCiq4TtY7bsHo3VkACY80dOsLXjinZH8YtlGVF4eENrh/YK8bT4jKYZM1Vtv+o7tgNKCKgS30z8/yfvNL5iu/99U2eo+vB3axgTxyr/UND+pITupc41+qBuO/HBVMsCt8Z3oG2s+XDf33VFIOZ/LX4cl7p7XG+d+S7c4TBfaXlznwqICkXezjB+JsISwrbVFTN/WQF/b6Z5aNRondtzAkKkx8PRSid4na6hUHpI+fV4+KlFHyZTQ9gEY/VA3i/Vp0Ybx2LLiLLz9XGvDUjRQLcdx7QCcBSBlXnqFMfa2lbx+AE5C+nF+zhj7m63z13egWqLhUFfXIu9mmdmabInHshEQ7MP7yqXE50FdXSsa2gDqFvIm3JNatRa3bpQgsqd7TORwlOLblUi9kI8Bd4t9nrKvFWPHqjj0GN4OE+b0Qk1VLbx9VFhnGKabt3o0CrIqzBQAJci4Uoh2nVqKLIGb/nUMFcU1eGrVaHyx5Aj8grwREOKLHsPb4di263j6w7GSHaijW64hI6kQj/x7mM3z1qq10GkZvHxUDi/B5gouH8lCUOsWiOwZgiM/XMXFA5mYuqifXrmwQWZyEXauqVsKrfPAMEyeL0Mjgd5F4Ie3ziC0vT8eXm77/tY3Oh0DY4y31lljyztnkJte5vJI+0pjXAWnIa/LWqBapRW0TwDMN2w+DuBPAD8BGAZAA6ALY+ymhbwvQm95A4AXAXwO4FMA0w37RjDGTkrlNUIKGkEQ7gBjDEnHb6HLoDYii+RPa84jK7mowT9s5UXVyEkpdcgC1ZzQ1GiRfCoHvUdFyFYyb6eWYtcH56Gu1mLKM/3QUWbkea1Whz2fXMKQqTFmrg/ujkat1Q8h2rC2NTbU1bWoVeskJ1/VFw2ioHEc5wGgEEBLAEmMsV6G/TMB/GBItoQxttpC/gQAfQCUAQhmjGk5jhsK4JQhyUeMsb9bk4EUNIIgCKKhuXWjBLs+jMcTb98pe3iOIADrCpqSA6ydoVfOAEC4yqnw9wBIwHGcLwCjx2mKwN/MZl6CIAiCcCXhnVvi6Q/GuloMoomhZBw0oV231MJvS/b1YIEs9uYlCIIgCIJoUjREoFrhQL6946k283IcN5/juLMcx53Ny3PvhbYJgiAIgiDkoKSCli/4LfR4FAYNsqRBFQIwBhyxKy9j7FPG2GDG2OCwsDCpJARBEARBEI0KJX3QbgAogd4PTRgCX/j7PCRgjNVwHJcI/SSBThzHqQx+aDbzCjl37lw+x3HpttIpQGuIFVLCfaBn497Q83Ff6Nm4N/R83BtHn4/FtegUU9AYYzqO436APsxGT47jZgHYB+AfhiQaAFsAgOM443Dl/xhjcwy/v4M+zEYggH9yHPc5gH8JTvGdDBkaxITGcdxZS7MuCNdCz8a9oefjvtCzcW/o+bg39fF8lPZBexVAluH3NwBuQR8DDQBeZ4yZL7RYx38BGENcvwP9kKYxBtrntmKgEQRBEARBNBUUVdAYYzkA7oTe2lUAoAbARQDzrK0iYMhbBWAcgPUAcgCooQ+zsQzAAiXlJAiCIAiCcGcUX2jKsFLALBtpJEM0M8YKADxj+HNnPnW1AIRF6Nm4N/R83Bd6Nu4NPR/3RvHno+hSTwRBEARBEITzNEQcNIIgCIIgCMIOSEEjCIIgCIJwM0hBIwiCIAiCcDNIQSMIgiAIgnAzSEEjCIIgCIJwM0hBIwiCIAiCcDNIQSMIgiAIgnAzSEEjCIIgCIJwM0hBIwiCIAiCcDNIQSMIgiAIgnAzSEEjCIIgCIJwM0hBIwiCIAiCcDNIQSMIgiAIgnAzSEEjCIIgCIJwM0hBIwiCIAiCcDM8XS2AkrRu3ZrFxMS4WgyCIAiCIAibnDt3Lp8xFiZ1rEkpaDExMTh79qyrxSAIgiAIgrAJx3Hplo7RECdBEARBEISbQQoaQRAEQRBNisLsTGRfTXK1GE7RpIY4CYIgCIIgNi5eAABY8sNuF0viOGRBIwiCIAiCcDNIQSMIgiAIgnAzSEEjCIIgCIJwM0hBIwiCIAiCcDNIQSMIgiAIgnAzSEEjCIIgCIJwM5p1mA2dToeioiKUl5ejuroaOp3O1SIRBEHIRqVSITAwECEhIfDx8XG1OARBKEizVdBqa2uRkZEBT09PhISEwM/PDx4eHuA4ztWiEQRB2IQxBo1Gg9LSUty8eRNRUVGkpBFEE6LZKmiFhYXw8fFBeHg4KWUEQTQ6OI6Dt7c3WrduDUDfpoWHh7tYKoIglKLZ+qCVlJQgNDSUlDOCIBo9QUFBKCsrc7UYBEEoSLNV0Gpra+Ht7e1qMQiCIJzGy8sLWq3W1WIQBKEgzVZBA0DWM4IgmgTUlhFE06NZK2gEQRAEQRDuCCloBEEQBEEQbgYpaARBEARBEG4GKWiEVQ4cOIBp06ahXbt28PT0BMdx4DgOsbGxrhat0XLw4EH+PnIchzlz5pilKSsrwyuvvIK+ffvC399flP7gwYMNLrMzzJkzx6r8wmMxMTEukdGUmJgYkVz2kJaWJspL7wpBEI7QbOOgEbbZt28f7r77blphwQXce++9OHTokKvFIAiCIFwEKWiERT7//HORctaxY0fccccdUKlU6N27twsla9okJyeLlDNPT0/ExsaiZcuWAICwsDBXiVYvzJgxg//dpk0bF0pSx5QpU5Cbm+tqMQiCaMaQgkZYJCcnR7T922+/oXv37i6Spvlget8feOABbN682UXS1D9bt251tQhmrFu3ztUiEATRzCEfNMIMo8+Qqa9Qjx49eL+aTZs2AQBee+01kb/Npk2bcO7cOUyfPh1hYWHw8PDAf//7X1E5Z8+exbx589CjRw8EBATA19cXHTt2xOzZs3H27FmrsjmT1xJpaWl47rnn0K9fPwQFBcHT0xOhoaHo0aMHZsyYgZUrVyIrK0uU3paPkSM+TMZyTcv7/vvvzXy0nJVByg8uJycHCxcuRHR0NLy8vHD//ffLkhsA8vLy8OyzzyIyMhI+Pj7o1KkTXnjhBVnR7eX4oKWnp+OFF17AoEGD0KpVK3h5eSEsLAyxsbFYvXq12Xlu3LiBoKAgvtz27dujsLCQP67T6TB69Gj+uIeHB/744w9Z987I9u3bMWrUKAQEBKBVq1aYOHEi9u3bJ+Nu6UlOThbVO29vb3To0AEPPvgg/vzzT9nlEATRRGGMNZm/QYMGMbkkJibKTtvceOKJJxgAq38bN25kjDH26quvivbPnDmTeXl5ifatWbOGL3vp0qWM4ziL5XIcx9566y1JuZzJa4mkpCTWsmVLm9e7ZcsWPk9qaqro2NixY83KjY6OFqURcuDAAdGxJ554QrJcqb/o6Oh6kSE2NpZFRESI9t13332y7mF6errZuYx/PXv2ZFOmTBHtO3DggCi/1PUJ+eqrr1iLFi2s3peoqCh27tw5Ub7NmzeL0jz00EP8sbffflt07MUXX5R97xhj7PXXX7dYB//xj3/YfDZr1qxhnp6eVq/p6aefZjqdTtYzYIzaNIIQ8v7Mqez9mVNdLYZNAJxlFnQaGuIkzBgyZAjKy8tx6NAh5Ofn8/vvuece+Pn5AYBFS8ePP/4IAOjatSu6du2K9PR03gLxzjvv4P333+fT+vv7Y/jw4VCpVDh+/DjKy8vBGMMrr7yCyMhIzJ49m0/rTF5rrF69GiUlJfx2r1690LlzZ5SWliIrKwspKSkNNknC398fM2bMQF5eHg4fPszvj46OxuDBgwHUn4+W0Vratm1b9O/fH6WlpfD0lNc8zJkzB+np6fy2r68vhg0bhvLycpw7dw5JSUkOy3XgwAHMnTtXtIxRly5d0KlTJ1y4cAG3b98GANy8eRP33HMPLl26xPvoPfzww9i3bx8+//xzAMAPP/yA+++/H926dcNrr73Glzdy5Ei88Q57OBIAACAASURBVMYbsmU6dOiQKD8AdOrUCV26dEFcXBxWr15tNf/mzZuxePFiftvb2xsjRoyAn58fzpw5w79zn3zyCSIiIvDvf/9btmwEQTQdSEGzwIFNnyI3PcXVYthFm+hOGDdnvtPlLFq0CIsWLUJsbKzIWX3dunWywiCsW7cOCxcu5LdrampQXFyMt99+m9/Xp08fHDp0CCEhIQCA3NxcDB48GBkZGQCAF198EY899hg8PDycymuLtLQ0/veECRPMhpYKCgrwxx9/oEePHjbLcpawsDBs3boVBw8exLhx4/j9sbGx/JByffL444/js88+g4+PDwD9c7PFmTNncODAAX67RYsWOH78OPr37w8A+OKLLzBv3jyHZXrxxRdFytnixYuxatUqcByH8vJyTJs2ja+jubm5WLVqFVasWMGn//DDD3HixAlcvnwZgL5ut27dGhqNBgAQGhqK77//XrYyCgDvvvsu9B1fPY899hg2bdoElUqFwsJCjBs3DhcvXpTMq9PpsGzZMn47PDwcx48f59+riooKjBkzBnFxcQCAlStX4tlnn+XrOkEQzQeHFTSO42YDmA6gP4C2AMoAXALwFmPsgCCdCsA/AMwDEAOgAMBPAF5hjBWalNkHwH8AjAbgA+ACgBWMsZ2Oykk0LBMmTBApZwDg4+ODn3/+GRUVFfw+nU6H+fPFyqTwo5ednY24uDgMHjwYf/75p8N5bREdHc3/PnPmDN58803ccccd6Nq1Kzp37ozQ0FA88sgjNstp7AQHB2Pt2rW8cgZA9NsSpgrtI488witnAPDUU0/h3XffxdWrV+2WKTc3F6dOneK3/f398eabb/IW2YCAALz11lsYPXo0n2b37t0iBa1Fixb48ccfMWTIEFRWVqKwsJD3RTP6THbo0EG2TFqt1sw38z//+Q9UKhUAICQkBC+88AJmzZolmT8uLg6ZmZn8to+PD5YuXSpKU15ezv+urKzE/v378cADD8iWkSCIpoEzFrSXAAin9LUAMB7AeI7jHmGMfW/Y/wmApwTpwgEsBDCK47hhjLEqAOA4rjeAYwCCBGmHA/iJ47jHGWPfOCGr3ShhiWqOWArKmZqaKtpOTExEYmKi1bJSU1MxePBgp/LaYvHixdiyZQtKSkpQWloqGk7y9vbG0KFDMXv2bDz55JP8R7gpMnDgQAQGBtqd7+bNm6JtqfArvXv3dkhBEw6bAvowL/7+/qJ9ffv2FW2b1hVAP2y9Zs0aPP3006L9//d//4dp06bZJVN+fj4qKyv57cDAQERGRorS9OnTx2J+U/nS0tJEVlw5eQiCaB44M4uzGMAr0FvFgqC3fBlZDgAcx41AnXK2A0AYgBcN230BPCfIs9pQjhrARAAdARhbpg85jvNzQlaigYiIiFCsLKHVrL7y9urVCwkJCXjhhRfQv39/eHt788fUajWOHj2K+fPn47nnnrNYRm1trdm+vLw8+4V2AmdlUPK5KYXQKgrA7oj+QhISEsz2xcXFiYZP3RVn3gOCIBovzihoExljbzPG0hljZdAra6WGY10M/z8qSL+CMZYP4D3oh0P54xzHhUGvlAHAPsbYPsZYGoANhn3BACY7ISvRQFjy+zL1XfvXv/5lc1aucQkkZ/LKITIyEitWrMD58+dRWVmJjIwM/PLLLyJLyGeffYbq6moAEClxgN5PTUhcXJzIylIfKC2DHH89KUytR1KWTVvWTkuYPveUlBQzZcVU8ZLykdy+fTs+/vhjs/1Hjx7F8uXL7ZIpNDQULVq04LfLyspEQ5YAeH83KUzle/jhh23WZdMJCQRBNA8cVtAYY+Umu7wBGMeAjEGjBgqOXzXk0wIwet/34jjOB3o/Ng9hOonfAxyVlXA9EydOFH3Y1q9fj2PHjpmlKygowP/+9z88+uijiuS1xY4dO7B9+3b+w69SqdChQwdMmTIF/fr149Op1WoUFRUBAFq3bg0vLy/+2NWrV3HkyBEA+iGwRYsWyT6/o7iDDID+2QjZvHmzyEF+06ZNSE5OdqjsNm3aYOjQofx2RUUFXn31Vd6yVlFRYTbD0XTIMi0tDU89Vedh0atXL0yeXNfXW7FiBfbu3StbJuOqDkJefvllfqZvcXEx3n33XYv5Bw0aJLJWbtu2Ddu3bzdLV1ZWhi1btuCee+6RLRtBEE0LJWdxLgVgdBD5wvB/a8HxUonfKgAhMtIBgGR8AY7j5gOYDwBRUVH2SUw0GMHBwXjppZd4i0VJSQlGjRqFPn36ICYmBhqNBmlpabh27Rp0Op3Ied+ZvLY4dOgQPvjgA/j4+KBnz56IiIiAp6cnrl+/LrL8hIaG8iEuvL29MXr0aOzfvx+AftLC2LFjERkZiezsbMnhRqVxBxkAYOjQoRgzZgwfFqSyshLDhg3D8OHDUV5e7nDwYCNvv/02Jk2axCtAq1atwq5du9CpUyfEx8fzYTYA/SzYJUuW8NsajQYPPfQQiouLAejv2bfffouIiAj07dsXubm5YIzh8ccfR3x8PNq1aydLpqVLl+K3337jt7/66iscPXqUD7MhDE1jioeHB1auXInHH3+cl3HGjBno0qULunbtCgDIzMxEUlJSgz1DgiDcFFvmdTl/AGYD0EIfYHE/AC/D/mTUBV70EKQ/ItjfDsAjgu03BOkmCPZvsCUHBapVlrFjx4oCZ6amppqlMQ1UawxgK4VOp2NLliyxGmzW+Ne5c2fF8lrjueees1meh4cH27Rpkyjf8ePHzQLyGv+mT59uFvRViKVAtXKPN4QM9pCWlsYiIyMl5YiOjmbjxo1zKlDtl19+yXx9fa0+ow4dOrAzZ86I8i1evFiUZuXKlfyx3bt3i45NmDCBabVa/ritQLXLly+3KMvcuXNtBqpdvXq1xWcn/FOpVLKfA7VpBFFHUwhU6/RSTxzHPQFgI/RDlEcB3McY0xgOC7uSwtmZxuliWgBFMtIBQMN6XROKw3Ec3n//fZw7dw4LFy5Enz59EBgYCJVKhaCgIPTu3RuzZs3Cl19+iTNnziiW1xoLFizAypUr8Ze//AXdunVDSEgIVCoV/P390b17d8ydOxenTp3CE088Ico3YsQIHDhwABMnTkRAQABatGiBQYMG4dNPP8W2bdtEw4/1hTvIAOhDlZw5cwYLFy5EREQEvLy8EBUVhb///e+Ii4tz2rI9d+5cJCYmYunSpRgwYIBoOa7Ro0fjvffew6VLl0Szdn/++WesWbOG346NjRWFs5g6dSqeffZZfnvfvn2iWHu2eOONN7Blyxbceeed8PPzQ2BgIMaMGYOdO3fKCiy7ePFiXL58GUuWLMHAgQPRsmVLUb174IEH8PHHH5v5txEE0XzgmMlMKbsyc9wc6IczPaC3nP2FMVYhOP4RAGMrOIwxdtoQF60YQACABMZYP8MkgRxDOb8xxqYY8i8DsNKQfwZjzNxZQ8DgwYOZ3CGVpKQk9OzZU96FEgRBuDnUphFEHase0vujLvlht4slsQ7HcecYY5IxoRy2oHEcNxd1ytkeAFOFypmB7wS//8VxXGsA/4ReOeOPM8byABgjXk7gOG4Cx3ExABYY9hUazkEQBEEQBNHkcWaI81VB/skAqjiOY4K/GMbYCdRNGJgO/TDlO4btBAAfCMr7B/STAryhV9ZSoY+FBgDPMcbqN24BQRAEQRCEm+C0D5oMngbwAvQhM9QAbgFYDyCWGVYRAADG2GUAIwH8DKAEQBWAUwDuZw28igBBEARBEIQrcTjMBmMsRmY6LYB3DX+20l4C8BdHZSIIgiAIgmgKNIQFjSAIgiAIgrADUtAIgiAIgiDcDFLQCIIgCIIg3IxmraA5EwOOIAjCXaC2jCCaHs1WQfP09IRarXa1GARBEE6j0WigUqlcLQZBEArSbBW0li1boqCggHqeBEE0ekpLSxEYGGg7IUEQjYZmq6CFhISgpqYGmZmZKCsrg1arJWWNIIhGA2MMarUa+fn5KCoqQkhIiKtFIghCQRyOg/b/7J13fBTF+8c/e6mEhJIChBJCEelIE+kgCIggKGhAQCmWL2Ch/EQQFBAFRJogvUrvHek1tEACIRBCC6T3Xi/X5vfH3W527/ZqLrkLzPv1yiu3u7Ozz+7OzjzzzDPPlHccHR1Rt25dZGZmIjMzEwkJCVCpVLYWi0KhUEzGwcEBHh4e8PPzg4uLi63FoVAoVuS1VdAAQCKRwMvLC15eXrYWhUKhUCgUCoXjtR3ipFAo1kUuK8KRv+YhKznJ1qJQKBRKuYcqaBQKxSpEhYYgMjgIV7ZvtLUoFAqFUu6hChqFQqFQRCkqyLe1CBTKawtV0CgUinWgk6BfKWIe3sc/YwIQFRpia1EolNcSqqBRKBQrw9haAIoViH/ySPCfQqGULVRBK4ckv3iOW4f22loMCoVCoVAopQRV0MohO2ZMwvW9220tBoUigJSTMc7MpARc2roehMY9pFAodgxV0CgUymvF8SXzcffUMaTFxdhalHJBWSywkpuehuSXkaV/IQqlHEEVNEqJ2PbT97h99ICtxaBQTIauGGJ/rJ8wGjum/2BrMSgUu4IqaOUYe1g7NDXqBQJ3bbW1GBQjFBXk49bBPWUyrMcw9j1JwN7lszfo46JQbANV0MozdqCgUcoHl7dtwvV9O/A8+JatRbE59tCxoVAoFGNQBa0cQxsaiqnIpIUAAKVcXnoXKWflkRqGKGVNXmYGXty7Y2sxKOUEqqCVYwihvjQUO8TONR9pfh4AIDs12caSUOwJtlyUJjtnTsHhhXOhVChK/VqU8g9V0Mox5cxgQbEhZaEzlZfymJ+ZAQC4ffSgjSWhWAuFTIaC7CzIpVKLzk+KfIZVY4fh8Y2rVpasmLjH4chLTwMASPNyS+06lFcHR1sLQLEcakGjmEs50aEoFLPYPPkb5KalAgCm7j1h9vkpUeoQH9FhoWjcqZtVZWNJi47ifqtUylK5BuXVglrQyjMq2txSTKQMpuKVu9l+5cXkRzEKq5xpc33fTiwJGIDsFGPD2WzhLb0y4ezmxv0mtO6mmABV0Mox1IJGKSuISoWctBTDacpZm1MeVj5QyGRIePrYpjKUt/fK59bB3QCAh5fPGUxXFqFXXHgKWmr0y1K/HsU04h8/QvSDUFuLIQpV0Mox5bnipNgICwvNrcN7sWHiWGQmJRhNy9j7LIFyxN+jPsbuX/4Pic+emHxOUUE+CnKyS3xt/nv89/8mIvTsfyXO02aYWO5Lc2a8g0OxR1HIySOldh2KeeyZPQ0Hfp9lazFEoQpaeUTT26MWNIqplNRCEPPwPgBwTs7ilLMeQznq4WQkxJmcdu03n2PNVyOsev202Ghc2LTaqnmWJUZfdemPcAqgdTfFFKiCVg5he7ZivT1CCNJiopAWE0XjpJUi98+dQnpcrK3FMJ8SlgmTTi8vzmhl/HmkxURhScAAZCbGl+p1FLKiUs3fFqTFRCE1JqrU8i8Lqy+/uJXFih6U8g9V0MojmrpE7COPCLyEf3/8Fv/++C0eX7tctnK9RpzfuArbpn1razHKDMYcEwPtGCA7JQl3jgnDeDwKvAQAeHb7ptHzr+7aiiUBA0okQ3p8LO6dPl6iPOyBpMhn+PfHb7Htx2+R+Nz0oV4+xORZk2VTdul6sBRToAqalSCEIOn501KzWuWkpuDmwd0ghOgdrlIq5Di1aim3nRobLTh+bv0/2Dz5f6UinyESnz3BkoABiH4QahXfGHtBpSwfU+WfBd1AVGgIAP3NT3pcLGSFBfoz0ZS5/fNmllhxsBdKc5LA4T9/w9WdW5ArMiRsSh1x5+iBEsuwc8ZkXNyyjrteQXYWclINT/TgYy+TKPgzMHNSxWdrGkNp7Ftl9I9KWA1e3qZa0HLSUpCflWlFEQhe3LtjVjmg2A6qoFmJJzcDsXPmFDy+fqVU8j+2dD5u7NupGR7RVCZaH3lajFAh07ZkhF04jcyEOBBCcPPgbpMcvkuCXCpFStQLbgbVgd9nldg35vSa5djw7ThriPfacGzpfKNR0rdOHY/91nKULTdDnKXXGMuL1AFTVUpexPgSPBdLFAdWBvY+13w9Ehu+HWt2PgqZZcFfrUfxvVv6CIkRBc2Qj+aSgAFYEjAA23763mqKjakK2oaJY7H2m1FWuSagds04vHCuReWgNIh+EIrwKxdK9Rrl2dWHKmhWIjNB7VeSEW+eX9LNg7uRFPnMaDqFTAYAUCkUXCVFCEHco4dmF8D8zAzc2LcTB+f/KtivUipxevVynPh7EXLSUriKKcJCpfPE339i+0/fo6jAgGXGTMIvn0eOyBI9clkRkp4/tdp1TKW0/YmsjoGyYuj5abdfOSJxp8TKYVzEQ9w7Y37gUFOIuH4FSwIGQJpX+kv0mItE4gBAv5VVVliAi1vWmRz5viRO5ZYOp7GyhZw8avG1rYGgXJmhofGt9SYHhjXwfaRGvSjR7Eu+RdJWQ5xppejHZy5xEQ9x4PdZOL16ma1FsVuogmYtOKXJeNL4x48glxWBEIIb+3Zi58+TjZ4jkahfFf/Djrh2GXvnTtfbAyGEICrsHpYEDMD1fTuK92sqCqVG6WOJDruH8Cvn8eTGVQTu+pfbf/c/yyro+CePABQrl6XJ2bUrsHPmFORplvExlcRnT3BbM5yUm5GGJQEDcHDBbIPn8BuMrKREk69VmJeL85vWlMnzsJTIkCAsCRgAuY6jubBhZIdD750+joPzfxWGgeA1onvnTMfFzWvNkiE9Lhax4WGiSiCfkBOHAQBZFlqCxb5VpUKOuEcPLcqPD+OgX0HLz8zA3f+O4d7p4wgx8dsqSWBTYx24S1vXY0nAAGye9DX2z/uZ26+Uyy2+pjXhy2+OM//WKeO53yqFaQqasadckmFf/jt0regOaX6eSZ1zABZ3ku2VyJAg7J0zvWwuRi1oFL4TdVTYPb0956ykROyZPQ0XN681q1fMaHrkRKUCw0g0eSVweerj7LoVAIBbB/foHMvLzMDWqRO4bX5FqOIt5quvUkw30VpouoOuYQz5YiRFqq0/cmmhWXnumjUVgRqH7PXjRwMA56+lFyMfPCEEUffv6gxjXN+zHffPnsSjwItmyWhNjDXWRxbNAwA8uHBWeEDLcsGWwYtb1iHq/l3smjXVajJunToe+377GRsmjrFanmKw31/IySOIDlMHqry6Ywv2zp2OlKgXOLN2BbZP/8GivB0c1TGvxBbFvnf6OKfAFRXkmyqs7i6VSl3OjJVHPd+fSqXEkoABuHvqGAAgMzEBMQ/DkB4Xg5y0FLvxQRPcuxlDnIW5OdxvpVKBiOtX9E4yMDkMTYkeSfHJ9du0x6H5s7Hz58m4smMz0uNiDJ7534q/9B6Lf/wI6yeOMexDagClQq2IZybGm9Xh5JOflYlzG/7h8jLEhc1ruHqmJChkMjy4dBZxEYY7VAQEz4JuoCA7q8TXLGuogmYlGI2FK+bhfRz84xfcPLgHp/5ZgiUBA3CBZ0EoyFEXkvTYGMQ8DBPkkZ2SLJhKnvj8CVeoGM6CphRxaBWvNfRV3Hf/O8b9To+LEVUmiZFKcc/snwQ9VHEBoJHZOub8f/9volXyKSnGGq4Xd+/g4Pxfcef4IeF5GoWAr7iplEqc2/CPwBFaLivCkoABnGWvNIh+EIolAQOw6fuv9KQQ3qN2A8aWR+Epxedol+VSxUDj+uDiWSwJGIAHl87qfA/s9uVtG3HgD7X/XVpsFADg8Y2reHjpLFJeRurNu6iggHMDYBWt8CsXsCRgAPdN8a2lfCkdHNgOl1Inv3UTRutcS6wzF3bhDA7O/1UwW1tsmDojIV5gEX15LxiAuPIIAFunTsCGidbxUcpNT8O59f/ovZY2ohH2LRziFGShVOK/FX9h10zxjkRuRjoA3SFAfWWG/X1520ZOZlM7P4C6DmCVxeDjh3BwvmGrvSGu7dmG3LRUJBsoqyz3zwmDDZ9esxzLR3yEs+tWYPOkb7DpB2F9wJZvY5a+y9s2Iuz8aZNmKIeeOWk0jSk8uHgGZ9euwN450w369GUmxOPY0vm4sGkNty/u0UMdv9xL/24AAKyfOAZLAgbg2e0bVpGzJFAFrYREhYYIhhhZherWwd3ctPrQMye4AsQOG8iLpDj4xy+CvDZ+Nw7bfvwW6yaMxqOrF7Fr5lRs++l7AMVDnESl0lGYzPVBC9ZSHJRyOeSyIpzi+QIYU6riH4cLth9cOosHF89CIZNBpVKCECKqkPC5tme7ujHTNFKEENG06XExSI+LEfSI+T4lRKUS9Pxe3L0DhdbwjFoeYlAePneOHcSSgAGivVLB+VoNRtzjcM4PUbtXzCo5/KGOhKcRCDt/WjD7tihf3dhbI9q49r2yMrAVaVayvh6z4YaQkRg+zpZllud3blnsrJuflYn//llS7PQuQuLzJ7i8baPONVgL8tm1K/Dg4hnhSQbk4c+i1GcV4CtDwZrhVtafhi0DbC//4SXhUkMSjYLG9++S5qnLt1gwYDFRWYtyBs8PcufMKTrpji+dj4jAy9z2oYVz1HmWgh9UavRLweSjc+tXIuzCaUQ/uAdAPXx9fuMqXN21FXFadQgAbJv2HQgheHT1Iq7s2KyWU2uI88XdO1Aq5Hh84yqnQBiDrYu1ub5vB5YEDMC13f9y8gvQefDqbWl+HpYOG4iQk0ewf95MPL11DUuHDURmUgKe3blptKxrd4pLMsqg71r8+jQrOQkpUS8ExyNDghB++TwAdUeGz51jB/H8zi1u+2VosOC4SqWESqVEbHgYpHl5Je6EWzIjnt+pNfS82XaDvX+5VIq9c6dj1dhhAjcK1pWHXdf18fWrZstkbRyNJ6EYgvVXerNTNwB6LAsA7p05iTbvD+QKcppWCAz+7KC89DScXb8SgNpfRW01K07LaDu86SuchJhkkl/xxVB0GzEGUp4ClM1vuHlKiFKh4JRFPmfXahrCdSvQoN07IColZIXq4Ubtjy8nNQWu7u4IOrwXAFCQnQ33qp44vXoZHl29iA9+mIaG7TvC0ckJAATDsCwXNq3Be1+pFYCwC8UN7+ZJ3wAA2vQfhJ5fFPcG134zCg5OTuj7vx9w4PdZGPbbX6jZqLHeZ8I6tmcmJiDo8D70+eZ7uLq7I/nFc+yYMUknvVKhwJk1yxHBs2ZkJMTheXAQ6rZ8C07OLoBmWJBvDWGHCvkKJ6P9vB0ckPjsMR5dvYhe4yaAYRgQQnBu/Uq07NUPNRo2AlGpEHLyCFzdPdC853sA1EqLtsWArcj4eqVY5cYwagWxRoNGqNW4qc5xsTLA8vRmoM6+o4t/R5//fY8WPfvoPU8MpUKBa3u2ISLwEmo3aY6WvfqKpts16/8AQtD1s9Hc8KI2mYlCXzVCCOIfPzIqw765P8PHvz56j1NbjO+dOQEnZxecWft3cV4qgoSnETrnKuRF3Lfh5OLK7RerJyQO+qtjtgEnKhVOrV6GpMhnKNJYAGQFBQbD76iteLrv2FijqCjSDXh7ftMaNO7cDbUbN+PyYBiGu59t074DAEzdq/5+2KvmpqUh/kkETq9eynWm7hw9gAkbd+kor0uHDeR+dx85VlA+4588QvDxQ/CsWVvv6grst2EKwccP6+yT5ufBtaI7kl9GYofWEHfomZNo2ft9bhIIoH4nJzVDkJt/+BoA8MEP09BY0yaIoVIpwTCS4rpA691FhYYg5NQxkTN1YTvL2q4oJ/5ehKc3AzF17wls+v5LnfMMDTNe3blFsH1j3050+OhT7r5XjR0On7r1EP84HL6NGsPDywcAIM3NVd+fUonnwbfwxtudTBo+XvbZIIz6cwVuHz2ALgGj4OrhgaRnT+D/VltBOqJS8TrbxeVCIZchOvgeGr7dUed6F7euV//Q7ObXtYbcKBw07Y8toQqahahUSqiUxQ0tO8TB8D5cPpe2rkNV35qcGVUb7WnPfCvLv1MnwqViRfV+At4QpyatHgUt+kEoCrJNi6GjHa+Jr0DyP/zlIwajWfdeBvOKDL4l2NaObL7h27Hwb9WG235w8Qw6DhmOR1fVvlkn/16EzgGjUM2/Puq3aS96jbDzpzkFLS9D1+Kg7WvCWjbZNdf2/PojKlapqvce2F5UyH9H8ez2DVTzr493hgzjJj5okxT5TKCcAWoLy9G/5qFZ917oN2EyV3FEhtxGky494eruzjVsfGsGOzNUmpeL5SMGo9uIMbi2ZxtUSiV6jv4GDo6OkObl4sHFs3gWdAPfrNuOQwtmIzZcPWTOKmgmO7uLlJ+Ep4+5kDFsY8tHrMdsbPLD2bUrcPvIfoz7W/0NKBVyMBIJgo8fBiEEPn7+Ou97+YjB8GveEoBhpZBVWpUKORiGwalVS9F1+BeCNEUF+Tjx9yJuOy0mCntmT+O2C7KzdNwOALWVM+FpBBq2fRuOzi6ikx7U1jnd56iUFVvf+BZAuZbyo1TIDQ4DXtyyDjcP7MaI+UsRoWUNunvqGBydndH1s9Gi5+ZnZeLc+n909htT0LStKgBw/+xJ3D97EhM374FrRXcs+2wQfN94E5/9vkQ0D9aX9fzGVQDA1WMs6yeOEVUE+fAVsULNzExDS18V5uaIyi6KSNk/vmwhhvw8V0c5Y9n247do1qM3ty2TSnWeJauo6OPGvp3qb19PB1psohIhBLLCAji7ViiuN3jyX9iyFl/8Vfye2Y6Spb5p2iwbPgif/jofdZq1hKywgFMM02OjUcGjklqGzWvwVt8PcOfYQVzbsw0DJ09Ho3e6mJR/yMkjeHLjqvodMwxiHoRi/PodcKtchUuzd+4M7rp1mrbg9l/fuwN3/zuKj2fMxYu7d1CPp9ilRUcBKO74mupv+PzOLahUSoEyXtbQIU4LObxwLv4e+RG3zb70QgOBWA8tmI1Mk9fUK/7wMhLiBJUY6wj/8JK6Erpz7CCykpN0ckiLiTLZ98O5gpv+g1oF2ty4NWILPbNO2QDgXbuuzvHre7fj8J9zDTp2slZHE/XFTgAAIABJREFUuYhikPj0MeRFUhz44xe9kxlMCQDJKpdsRaj9sR5aMBspUS9wevVSnXNZwq9cwPKRH3FlJDrsHlaNG4abB3cLhq7jn0QgIyGOm93EVvr8WbTFFjD1edL8PPw98iNOOeMjVhGFaiyDfEUk9tEDnXTa8fy0G6CgQ/t0zuFblPTBH4pePuIj7Jn9EwJ3bcW13f/i8J9zkafxBeLDLanFMDi+/E/uXtlnISss5J6HUi7HxS1r8fj6FZ1OT05qCp7c0D9ssebrkQZlP7hgNvbOFZ95VpCdhaDDus8kJUrcLyhw11bB9vIRH2HHDMMTEgpzc+DgKN6rv3P8kFkBhEPPnCzREOeJ5X9yCqfY982GPmHXcGVhh+9ZjClnUWH3cPvIfm7b2sOyCrlu3RHzIBTHlsw3eB47NAhoxbrT4OBs3Ppi7r3cO30c/4wJwIH5v0KmaQP41vi0mCiolEo8CrwkyHvl6E/Nuo4h9v32s8heRvCelQo5ctLUdfOjwMuQF0lBVCooFQqd0E58WMs3IYTz/VRqPVu+aw2/3spOUbd/0twchJ45gcN/zuWOsc8oMzEBSwIGiAaPZuFb1+TSQoScsO2i9lRBs5Co+3cF22xjL80z3HMyFW0LBetwnfjssWh6MRO2OTg6OxtNY814ZnxrvKu7u95kCSKVP8vNg7sBFIdb0Gbnz1MQHXbP+GQGAzwLUjuKKuQyyGVFokNT23/63ujsJ6VcrmM1ubFvJ+cfoVKpsOfXH7FFZKWHvMwMTkHifFUMdAIDd/+LnLQUHT88QG3pk+bnCeL17Z8306DsAHQUwNz0VJNmbIlBVCqEXTgNQK1I89n96zSd9Oy3dWPfTjy9GYhDmsq3MEf97PbP+5lrJC9uWYf7506JXlf7+ZcFiSbE5nsadB2ArvJiDuY29hc2r8EOE8L76CMjIQ4rPh/Kba8c/alguPjJTev472j76erzJbME7Uk8fCKDg0qUt6OjE1KjX2Lf3BkiIWtEYBjkZqTh4tZ1emO2sRb6mAehWPnFJ3h2+4bOew86sg+n/lmChzwFsrRhGEagaKfFRHNyRQbfworPh+LClnW4vm+HTrvJJzLktvoHIVw7yh+9MWQJZN+XmKFCm1uH9uo9dnzpQsG2WIexLKFDnGYil0pFp/Uamu1lEXqGLa9s36T3FFNm8ejj+t7teo8lPHmE7JRkzuHaGghmMhpoXE4sW6A/D57jvxjGpq6bw+0j+3H7yH500Ro2Mw9dWY9p7i9Vy4FXbw6aZ2VoRQZWVn2sGjvMpGsZIiY8DGu+Mmxx0seNA7tEw74AEA1CzJKbrh52VhQVITIkCPlZujHvDK3kkaBneLo0iQ67ZzTN8aX6y7g21gxwKjYZwWS0irKssEAwXHx+4+oyVRL4GFNWd8yYhJELluOqZhJCaeDg7IyLW9YhLuIhVowagsrVqhtMn5eexoX5qfWmrs8noHtfYla+7GT192NpbEBTKNQ2Qmh1FkP+O6rjB3r/rPGZm+xoiWCWPMOgICcbMQ9COT8/Q9zYv9NoGkOK3vM7wlmotg41QxU0M8jNKP6I7BFTHWMtYeN3pbe8kiHLBuPgAOgbpiXiwwulCTvbyxK0naEB40M82qS8fIG7p46V6TqgokoPIabH8NJCn3JmDkcWzeNmQr5OlMbMS0tglWVDGF3Zg2FKJYiosVUDkl88t/o1tXFwdBJ05PkzDo1xYvmfovtNCRycl6m2+JQkRI+xJQBXjxsu2Na2/EYEXkLTbu9afH2+TpSfmSE6KaskvLh7x3RRShAg2hrQIU4zYIdUKNbl6F/6ZxMZUmDkRVJs0syael3YO3d6mcfnMaXnagvK8xp7lnL7qH7LaLmjlN6fKSt1lPZqHvlmrmhiCtoz/8UwxWJrjM1WqFNL0oHkK7bWVs7MxdZ1DLWgmYG+EBoU2/D01jVbi0CxIfZiTSpLws6ftrUIdo8pCsbRxb+XqgznNujOmn2dsNVao1anBGvgWgOqcZiBqdNzq/rWLGVJXj3umhjzh0KhUEqKIWd1SskRi4VYHqFDnOUIUy1oDk7GZ0RShFxigwlSKBQKhWIHaIf5KGuogmYGhgJl8rFWqA0KhUKhUCi2Qa5ZDcdWUAXNDNhgmMawdewUCoVCoVAoJYMNCGwrqIJmBqU9SaBlr36lmj+FQqGURwb936xSy1tsrVmK+Xw4RWyVgfKNjFrQyg+mThIwh+//LY5X03bAYIz6UzwYbM/R31j92qbQqGPXMr+mj3/9Mr8mhUIpGxydXcxK7+3nDw8v7xJft3r9N0T3f/CD7uoVtkSfnPbOGx062VoEq5PwNMKm16cKmhnoi+3yzscBgu06zVqanKeTqyv328HREdX0KCeVvH1MztOavD1oqPFEVqbn5yVbtopifXwbNTY5rau7h2D7879e75ADtqbj0OHGE5UhnQNGYthvpsfWc67gZjT4rCm07ie+VqlbpSqi+8sK7XWQK/tUs5EkxnFwMr7GKAAMnVm6YUws5fvtB81K3+q9/qUkiWnYnYLGMIwfwzA7GIZJZRhGyjDMfYZhSi+MvRnom9HROWAUXCpW5LZ7fznRwivot9C5VdZfibR5/0PR/Q6Ojnp7NTUbNTFJIlMnRrCUbCkkNdoNvLnoex4A8O5Y3bUuzaFBuw6YuHkP3hlS8uWSSpuhswxXkt51dBep14ezawW89/V3JqXVXubFxc1NT8piPp4x12gaSxkwSXyBc0OMXGh84XdL4FvM9dHnf98b/N7NpdMn+pcFsxRD8r3xdnGd027gx4JjLXv3Q9sPBqPWm00wde8J1NSzrBEfhmGgUhqPR9WsR2/BtpNrBQDFClC1eg1Ez9Mur9p4ePngg+9/RNfPRhuVQR+fzl6Axp27AwDqt2mPH7YXrwOqfX1tJcj3jTf15jt511GL66IG7d4xmobfrgFAl2GfG0z/3tff4Z0hw1CxinXKb6v33jc5bfdRumpChUqVBe2Bk5nW214lbC9Kil0paAzD1ABwA8AIAN4AXAC0BLCRYRjjKzqXMhUrV9V7bMKGXdxvB0dLl6DRxFwRGUp1q1RZ9IwG7d5Bz9Ffi/aSq/k3QP/vfsTAydMx6MfiRYfNUaL0Dev6NW8lur+mgcqEj77KoWH7jlzFaik9R+sPVPlWnw9Qt2Vrnf2mWIgGTp6OwT/+AteK7mjz/oeo3/Zto+cwjATNe76nR07Th61Nscr6NS9O0/r9gajb4i1uu2nXnoK0FatU1elIeNaszf121AoVU6V6DbTQcx8A8N5X33K/B//4CwZM+ol3VF2GKnhUEj33jQ6dDK39bjaeteoItt/s2AVDZupfrUKM6vUa4NstxYsq12/T3iqyObm6olbjZgAARxdhY9Fl+Beo3aQ5mvd4D/3GlyyC+hcaq6X2e9RHBY9KAqUBAN7s1E1v+o+nz9F7jK8oaSsXTTr3ENQpjk7GY6VLJBIQLQvapJ2HMXXvCdRu2pzb1/eb79H7ywncNlsnvvfVRPyw/RB8/PyNXkuMN97uiMaduxsdTTCkbNZp2gIffP8jJu08jME//gJHZ2fOncXB0RHD5i7CwCkz8PH0OQJFY9SfK1CxiqfefCUODnBw0H2G41ZsNHZbeLNjF73Hxm9Qr2nJSIrbss//+gdtPxgsqDc+mj5bcF7LXn3R+dOROt+g9jCyRERmMWo3bWFSus4Bo9BuwEc6+/+3dpve9qBGw0b4fpvhDpOtg9PblYIGYC6AWprfowD4AgjSbM9mGMbPJlJpcHV3x7i/NwAA+n87VXCMvy6gRE+P7Nste9HoHd2P4vNFK9GiV19U8labtoeLmP/dqlRB634D8e4YYaPOavht+g8CAHT+dCRGLvwbQ2f9jo9mzIGjkxMavdMFDdt1AKCuPDsM/sTkpU70FVC+n1gFj0oYOHk6ugz7HHWatUSXYZ9j5ILlgo9S27TcfuDHGL1ktWBfky498O7Yb+BWSbwhB6CjFOmzSOjz5WMYBn20LEFVfWuh/8SpaNK1JyZu0r9OZL3W7bjfFTwq4aNpvwqOdxn2OSpWUSvx/b/7P3w45WdM3n0Uff/3g2h+7DtxN8G/ptfY8Tr7mnXvJehhVq1Zh7OYai+4XEFLwff280fVmupPzaViRTTr3hsDJ0/HmGXrMOrPFRj6yx+C9D0+/wqMRIIR85dhzLJ1mLLnOL7/9wCm7D6GSTuPoGXv4gkuNRo2wpsa30V3L28wEnWD7ODoqKMEAED3kWPhKqK81WrcDJN3H8Xgab/Aq7bup9/7ywkY9ttf6DL8C+67BIC2HwzWSctXVlkm7zqKH7Yf0lHOv/pHvYi2i1ux9aBzwCj1/Xh6oS9PefLw8sGXKzfp5M0yYv4ynX1sg1G1ui9nYer62Wh0GPwJAuYsBMMw8H+rLT6catzp+vttBzBywXKMXrIGk3YeQb8Jk/Hu2P/BQ1OXQPPsxyxbC28DCoqjiwscnYuVuVZ9PsAAC32z+BZwndUeJEJVvHJ1X+73J7/Mh0/deoLjbpWroM8336MKLx2gXusSAD79ZT6+XLkJw+ctBiORoGXv4u+h7QeD8OGUn/Fmp26Ce+MzZtlaAEBVXufEUgZM0n1e9d5qK7DaOzg6cXUqa9mTODqiVuOmaNShM+q1boeKVapi7N/rMXLBclTzr290uSFWSQ2Y+yeGz1uMr/7ZjCrVa4gq0R/9NBtT9hzHpJ1H0KRLD53j/q3a6OwLmL0Q/1u3HT5+/mAYBq3eex9Tdh/D5F1HUb+1eMdF4uCAKbuPcXVE407d8PbgT7jjX6/egiFaVvOG7Ys77V2GfY7GnbujgaaOZKnRoNg/b8jMeVw7VO+ttjoyNOnSw+B6vdXrNYSTS7GLUet+A/WmtRV2s9QTo45hwTpzRRBCdmj2LwWwF4ATgKEAltpGQjVVavhiyu5jYCQS/PfPEkHD8dFPs5EeFwOJRLxQuLhVxMDJ07EkQO0LwS4o61O3nkBpqMlrMDoO/QyywgI4ubhyylnlajXg1+ItOPJM4a4V3TF17wmDsk/Zc5z73axHb6RsjdRJ0+eb71HVtyb2zlEPC/EVtMrVayA7OUkjQ3UAakVE+0Pv8NGnAIDq9Rvi5N+LAOj25F3d3QUWGzYvbYbO+h1FBfk4vnQBPl+0Et5+/ogMuY2jf81Dk6494eTqioFTZuD40gWC86r518eUPcexdFjxR/fOEHWPupKWj8eYZWvBMAyndH+xeBUIIdj247ecXB5e3oKPmeXzv/6BxMEBKVEv0LBtB9w/fwqAWrnQ5zc46P9mITMpgbMotek3kGuo+fICQN2WrfHumG8ElfRbfQfA0dkZXYZ9DkIIFDIZajVphiade+DUKvXnwVopGrTrgMjgIDTr0RshJ49weQycPJ1T0iUOjug3QWixUamU3Pse8cdSroHjV5Cs/6SDHiV+yp7jYBiGCztDCIGjszOadO2JiMBL6DdhMpp27QlGIkHlajXQ84uvULGqF04sX6jO19EBEokDGrTtgAZtO3DfzZTdxwCG4e6x1pvq4foBk6Yj+sE9tHi3D1q82weZifGcgsAwDKbsOY4Dv89CzMP7qFavASQODqIWCH75eGfIMPg1b4Vq/vUxaecRbjiqWfdegucMAI06dEbk3duoXq8h+nzzHcAw8KpVBw3bv4Pnd25x6Xzq+qPVe++jTf9BCD1zUnOvwmEthmHwxtud0HHocNw8sFv0+Tbt2hNOLq6oXr8ht4+VS1ZYoM5HY5v0rFkb3UeOxcH5xZ2K4fMWIzX6Bc5vXM09g2Y9eiP88nlU1zMcyBOQ+/nu2P/BrVIV7r3VerMJqtVrgJSXkTpWU0bLVtpz9Neo3+ZtSCQS+DVvic8XrcT2n35ASpS6bur/3f+hSg21cjZlz3HEhochLiK8OD+JBJWrVefqI/77kEgcjDqus3XQmKVruH2x4WHYP483YCMyisCWwdz0VNw7fQJ+zVvBw9Nbp84xNHSv0rjMiA2xVq1RvBoNEVluyNWjEip5qeuX2k2ac20Sn3qt26HVe+/j/jl1neRV24+zBItd87M/lqBGg0YAgMLcHPbiAislCyORcG9y4JQZyMvQXXuUkUgEPtZdh3+B20fUa8lWrFIVFd9qi24jxiAnLQWhZ06iYhVPjFm2DiqlQuB+4VmzNjIS4lhx8NkfS/D01nX4t2wN/5atQVQq7t6/XLkRx5ctRPKL53qtbwGzF+Ly9k3oofF1/uz3JfDw8oZzhQq4d/q46Dm2wm4UNAANALDd/Ke8/fzfumNTNoAtDMPnLeYqD0A9DFK/TXuucvRv1QZDfv4NWUmJov5rYiZZbXwbNhJYbtjrWCQ3r6Jp8/5AtO43AJmJ8ZBLpdyitC3e7QMACJizEHGPHqJqjZpo3Lk7/Fu1QbPuvbhG8q33+qNKtRrwF+m58Gn7wSCEnDwKhmEwdvk6yIuKUJibwym2X/2zGfFPHun4xHnXqQtCCGf54CufDdt14Bp/QN0wjt+wEyeW/4nuI8cK7tfHvz5So17gnY8D0PnTYl+cLsM+x7U921CjwRs6w7jedepyTskdhw4X7WmysMMmXhqT/sc/zcbDy+d0Zp0179kHDy+dRSWfaoKeorZSPWDSdBQV5KNJ5+64uHUduo0ciwruHiAqFZr16I3MhHh0GTZKYN3pN2Ey97vnF1/Bxc0N9duqe56DeUPbQ2f+jqTIp6hWrwFc3CpySh9f6WKRSBzwpQnDJHy6jxwLL17Fyj5XF3d3AMVW3saduyEi8BJ832gsaFTa9B8kiDvUvGcfQf7DfvsL0WF39Vp13+zYRTBso90BYBgGH8+Yg2t7tnMWMQBo0asv4iIeYujM3wXfM6C2SLPwGzXtMmOoc+RZqw7AU9AkEgdumKhh+3dw7/Rx1G0h7jLQ6ZMROgpa189GGx1uY1czaT9oCLePLdMN2nXgyoWHtzewcTWqaZQ8VqF10gy/dh85FqnRL8E4OODdMd9g5RdqKwh7/9XqNUDrvuo6oSD7G065HfHHUsQ8CIVf81aYuvcEslOScOfYIfg2Eg55Ojm7cJZklgGTpuHKjs2oWLkq6vAaWYZh4Ne8lV73CpYxy9bqLSPtPxyCO8cOgpFIBNY9/vus07QF3uo7AESlxP1zp3T0s4btO3L5V/KuplPnjF+/A+c2rEIHnsVIDLbTY2zWJivb+99OxZk1y9Fr3HidkEz67rf3lxPROWAUru7cojP6Aqg72tkpyeg7fhJ8Gxa/G9a6Z0ob1ahDZ6NpWEYvWS1Yaaf9h0MgL5JCIZOhc8BIUTeIMcvWQqVS4tLWDWjz/kBU9a0lkFVgRKhWA2+83QnJL54LOsiDp/2CnNQUAGqL48gFxZZtdhheO+aZrScIAFD3au3hD0BHqJ2wCIBtvP31efvPGMqjbdu2xF6If/KISPPzRY8p5DIS/eC+wfNz0lPJ+U2riVKhKA3xdHgadJ2EXTxjNF3k3dvk3pmTZSARpSyIe/yIFBWIl1OKdVDI5eTO8UMkPyvT4jyiH9wnz4ODyMvQEKJSKi2W49yGVSQ3I12wPzbiIZFJCwkhhOSmp5FzG1YRuUwmmkdMeBi5ffQAUSmV5OLW9SQzMcEiWcoDKVEvyOJPPyCxEQ9L7Rqx4Q+4Z6+P3PQ0cm7jaqKQy0tNjlcJpVJBou7fM/s8lUpFAnf/S1KiXpSCVPoBEEz06DQMMTK+XVYwDNMR6gkCALCdEPK5Zn8DAM81+88QQvppnfc1gK8BwM/Pr210dHQZSUyhUCgUCoViOQzDhBBC2okds6dJAmm833w7Jz/mQqr2SYSQ9YSQdoSQdj4+tokVRqFQKBQKhWJN7ElBiwSQrfndiLef//te2YlDoVAoFAqFYhvsRkEj6qkqbOChJgzDjNDERZui2ScHsN8mwlEoFAqFQqGUIXbjgwZwgWqDURwLjc8sQsgfIvv556cCKAsnNG8Ih2Qp9gN9N/YNfT/2C3039g19P/aNpe+nLiFE1D/LrhQ0QL3UE4AFAPoCcAfwBMAKQoj+aJBlDMMwwfqc+ii2hb4b+4a+H/uFvhv7hr4f+6Y03o89xUEDABBCYqBe6olCoVAoFArltcRufNAoFAqFQqFQKGqogmYZ620tAEUv9N3YN/T92C/03dg39P3YN1Z/P3bng0ahUCgUCoXyukMtaBQKhUKhUCh2BlXQKBQKhUKhUOwMqqBRKBQKhUKh2BlUQaNQKBQKhUKxM6iCRqFQKBQKhWJnUAWNQqFQKBQKxc6gChqFQqFQKBSKnUEVNAqFQqFQKBQ7gypoFAqFQqFQKHYGVdAoFAqFQqFQ7AyqoFEoFAqFQqHYGVRBo1AoFAqFQrEzqIJGoVAoFAqFYmdQBY1CoVAoFArFzqAKGoVCoVAoFIqd4WhrAayJt7c38ff3t7UYFAqFQqFQKEYJCQlJI4T4iB17pRQ0f39/BAcH21oMCoVCoVAoFKMwDBOt7xgd4qRQKBQKhUKxM6iCRqFQKBQK5ZVCmSuDIq3Q1mKUCKqgUSgUCoVCeaVI/CMISYvLt8sTVdAoFAqFQqFQ7AyqoFEoFAqFQqHYGVZR0BiG6c0wDOH9ddE6Po5hmPsMw0gZhkllGGYHwzB1RPLx0xxL1aS9zzDMOGvISKFQKBQKhVJeKHGYDYZhnACsNHB8FoB5vF0uAEYA6M4wTHtCSJImXQ0ANwDU4qVtCWAjwzA1CCF/lFRWCoVCoVAolPKANSxokwE0BlCgfYBhmLoAftVsBgHwBTBKs10bwBxe8rkoVs5GadIGabZnMwzjZwVZKRQKhUKhUOyeEiloDMPUAvALgBQAG0SSDAXgpPm9lBCSRAjZASBCs28YwzAShmEkAAI0+yIIITs0lrWlmn1OmrwoFAqFQqFQXnlKOsS5GIA7gO8A+Iscb8P7/VTrdxMAlQHUg1pRrKwnHUvrEspKoVBshEqlQmZmJvLy8iCVSqFSqWwtEoVCeYVRfOgOAMiNiDCS0jo4ODjAw8MDnp6ecHFxsUqeFitoDMP0ADAMar+xfwHMFknmzfudo+d3Na1zTE1HoVDKAQqFArGxsXB0dISnpyfc3NwgkUjAMIytRaNQKK8osrhcAIBzbY9SvxYhBHK5HDk5OYiJiYGfn59VlDSLFDSGYRyhnhigBDCREELMrGz5iYnWtqF0YrJ8DeBrAPDzo25qFIq9kZGRARcXF/j6+lKljEKhvHIwDANnZ2d4e6ttUhkZGfD19S1xvpb6oA0G0BzAKY1wbwGowTvekGGYhgDSePsq8X7zVdpUM9LpQAhZTwhpRwhp5+MjuiA8hUKxIdnZ2fDy8qLKGYVCeeWpVKkScnNzrZKXpUOc7pr/AzR/2mwBcAXAcQCfafY1AhDK+w0A2QBe8n5X5h2D1u97FspKoVBsiEKhgLOzs63FoFAolFLHyckJSqXSKnmV9koC+wHINb+nMAxTg2GYEVBPEACAPYQQFSFEBWCvZl8ThmFGaOKiTdHsk2vyolAo5RBqPaNQKK8D1qzrLFLQCCFbCSEM/w/qOGYsXQkhPQghMQB+0+zrACARwA7NdjyEcdBma/ZBkyZRcw4AzCWExFoiK4VCoVAoFEp5o9TX4iSE/A7gSwBhAIoApAPYBaATu4qAJl0SgE6aY+matGEAvqSrCFAoFAqFQnmdKPFSTyyEkDkQWsT4xzYB2GRCHjFQLwNFobzSEIUKirRCONWoaGtRKBQKhWKHlLoFjUKh6JJ14gWSl9+FIlNqa1EoFKvCMAz35+/vb2txjGJMXkIINmzYgM6dO6NKlSpcDD+GYTBnzpwyl7ckbN26VXC/2vL36NFDcDwqKsomcvIZPXq0QKbLly+bdb6/v7/g/PIEVdAoFBsgi1bHYFYVKGwsCcUeKItGJCoqSnCNHj16lMp1XjXmzp2Lr7/+Gjdu3EB2djYIEQ3JSaFYHasNcVIoFDMoXx05CuW1Zd26dYLtdu3awc/PDwzDoGnTpjaSqnTo3r07F2wVACpWtL0LRvv27ZGXl8dtv07xTqmCRqHYEtobp1DsmqQkbi4batSogTt37thQmtJl7ty5xhOVMRMnTsTEiRNtLYZNoEOcFIotKGe+ELZCJVOCKF7dhdVZn5/o6GjBfv5QpNiQ561btzB27Fi8+eabcHd3h6urK2rXro1BgwZh3759OovRMwyDevXqCfZduXJF75DniRMnMGHCBHTu3Bn+/v6oVKkSnJyc4OnpiQ4dOmDWrFlITEy03oPQkJeXh4ULF6JTp07w8vKCk5MTKlWqhPr166NPnz6YOXMmgoODBecYGx621IeJzZdPUlKSqI9WSWXQ9oMrKirCggUL0Lx5c7i5uaFKlSomyQwAcrkcf/31F5o2bQpXV1dUr14dI0aMQGRkpNFzTfFBy83NxbJly9CzZ0/4+PjA2dkZVapUQZs2bTBt2jSdc4qKitCmTRsuTwcHB9y4cUOQ5ueffxZcd9asWSY/OwAICwvDxx9/DC8vL7i5uaF169ZYv32TycPR6enpmD9/Prp06cKVO29vb/Tu3RubN2+GXC43nklpQAh5Zf7atm1LKJTyQNKKuyT2p6ukKDbH1qKUOo8ePbL43KLYnFf6GXXv3p1Avc6wwT8WlUpFvvvuO6Ppu3XrRtLT07nzTLlG9+7dufQffPCB0fRVqlQhwcHBOvfET1O3bl2Tn0VhYSFp1aqV0etOnDhRcF7dunVFnxXLF198ITh+6dIlk+TVzlfs7+XLl1aXwdfXl/Ts2VOwr3LlyiY9Q5lMRvr06SMqq4eHB/nmm28E+2bPni04X7s8svfHEhISQvz8/Aw+kwoVKpBt27YJznv69Clxd3fn0jRo0IDk5eURQggJDAwkEomEO9a1a1eiUChMfnZnzpwhLi4uorJ8MvBjUrt2bYPv5tKlS8THx8fgPXXs2JGkpaWZ9A4IMa/OAxBM9Og0dIiTQqFQbATr83Pq1CkUFBRw+4e5EzpRAAAgAElEQVQMGSKaft68eVi5ciW3zTAM2rZtCw8PD9y+fRv5+fkAgKtXr+KTTz7BhQsXuPwKCgpw6tQp7lxvb290796d227WrJngWk5OTmjSpAk8PT1RuXJlFBYWIjw8HPHx6njiWVlZGDt2LO7fv1/Cp6Dm0KFDgrx8fX3RunVrKBQKxMXF4cWLF5BKy27Wc//+/ZGSkoKDBw9y+9zc3PD+++9z26Xho5WYmIjExES4u7ujTZs2cHJywtOnT006d8GCBTh79qxgX9u2beHu7o6goCAdfzpzSE1Nxfvvv4+UlBRun4+PD1q3bo2oqChOxsLCQowZMwa1a9dGz549AQBvvPEG1q5di5EjRwIAIiMjMXXqVCxatAijRo3iLL5eXl7YvXs3HBwcTJIpIyMDI0aMQFFREbfPy8sLbdq0wfMnz7D/+CGD5z99+hQDBw4U+Li1adMGNWvWREREBGd1vHnzJj799FPueyorqIJGoVBsStbxSMgS8kWPkSL1LFfGxb6qKueaFVFlYIMS58P6/Pj7+wuGOQ8cOKCTNiMjAwsXLhTsO3ToEAYPHgwAeP78Obp06YLk5GQAwMWLF3H69Gn069cPBw4cQFRUlGCYs1mzZqLXAYDFixfDz88Pbm5ugv2EEAwbNgz79u0DoB5aioiIQJMmTcSyMQv+0JiHhwciIyNRoUIFbp9UKsWVK1d0hm9Li9WrVwMQLt3j4+Oj95lZk9atW+PEiROoWbMmAAgUEH3IZDIsX75csG/dunX4+uuvAajfVadOnTgl3lyWLFkiUM66du2KkydPwsPDA4QQTJs2DYsXLwYAKJVKzJgxA7du3eLSjxgxAhcuXMCWLVs42UJDQ7n3zjAMtm3bhlq1apks06ZNm5CWlsZtN2/eHFeuXIGnpyekMdn4euoEbD+wS+/5c+fO5ZQzhmFw6tQp9O3bF4C6rI8fP55TavnfU1lBfdAoFAqlHHDhwgUUFhZy2927d+eUMwBo2LAhvv32W8E5J06csOha9erVw7Zt29CvXz/UqVMHFSpUAMMwkEgknHLG8vjxY4uuoU3dunW537m5uZg6dSr27NmDkJAQ5ObmwtXVFX379hVYsF5VVqxYwSlnAODi4mL0nJCQEGRmZnLbDRo0wFdffcVtt2zZEp999pnFMh0/flyw/dtvv8HDwwOAWrmZO3cutw0At2/fRmpqquCcf/75R6DMBwUFcb+nTp2K/v37myXT+fPnBdvTpk2Dp6cnAEAikeC3n2brPVelUgm+Dzc3N2zYsAFDhw7F0KFD8cknn+Dhw4eCcyz9nizFvrqlFMrrBp3EadASJYvLBQA41/bQm+Z1Qdv5ukWLFjpptPe9fPnS7OsUFBSgW7duCAkJMSl9Tk6O2dcQY8iQIVi0aBHCwsIAAGvWrMGaNWsAgAtpMWTIEEyZMgWVK1e2yjXtEWdnZ3Tq1Mns82JiYgTbTZs21Zmw0Lx5c4vlMlb+3Nzc0KBBA4SGhgJQW6CioqIEYTHc3Nywb98+tG3bFjKZjNvftm1bzJ8/32yZtO9Ze5i+Zg1fVK1aVaC4sqSnpwvKbn5+vmA4WwxLvqeSQBU0CsUW0EmcFDMhWjPSSiug7apVqwTKmUQiQbt27VCrVi1IJBI8evQIEREReuWyFFdXV9y8eRPr1q3D0aNHcffuXeTm5nLXCA8PR3h4OI4dO4Y7d+7A0VG8+VIoFIJj/GG5sqIkMlSvXh0Sif0Nblmr/D158kSgnAFAdHQ0UlJSzBretAWWDg9biv2VAopR5Mn5yLuRYGsxKBSKlTClsdMOk/HgwQOdNNr7+EsXmdqgXrt2TbC9Z88eBAUF4dChQzhw4AC6detmUj6W4ObmhsmTJ+Py5cvIyclBSkoKrl27ho8//phLExoaisDAQG7b2dlZkEd6ejr3WyqVmmwJLAnWlMFS5axOnTqCbb4SzRIeHm5R3oDx8ldYWKgTyoM/bA2oLVDjxo3TyTstLQ3Dhw+HUqk0Sybte3706JFgOzE5SdR6BqgnE/CHZH19faFSqQxGijB3mamSQhW0ckjy33eRdcx4TBsKpawpDE97peOWlRZ8Z3gA3ExJPr169YKrqyu3ffnyZRw7dozbfvHiBVatWiU4Z8CAAXqvkZAg3snTjvnEn6kYHByMnTt36ruNEhEaGor169cLAsP6+Pigc+fOOo7Z/DR8Xy0A2LhxIwC1FWvy5MllYkGzBxnatm0riJf2/PlzbNq0idt++PBhid4dvywBwK+//iqY/ThnzhzO4gkAb7/9NqpVq8Zty2QyBAQEIDs7G4C6PI4fP547HhgYaPbapr179xZsL1q0iFPIVCoVZi/6Te+5EolE4POWmJiImTNn6pR/hUKBy5cvY9y4cQKfuTLBkLZY3v5elzhosT9dJbE/XbW1GJQSkLRSHQdNGp1ta1GshjQyk8T+dJVkHo8U7Kdx0HRRqVREkS8jKpWKEELIRx99JIi7VKdOHfLhhx+SIUOGkMWLF3Pn/frrr4J0EomEtG/fnvTs2ZNUrFhRb1wzFk9PT0GaVq1akY8//pgMGTKEnDp1ihBCyJw5cwRpXFxcyHvvvUe6du1KHBwcCMMwguNbtmwRXIN/zJw4aIcPHyYACMMwpFGjRqRPnz5k8ODBpGPHjsTBwUGQ771797jzfvvtN524Vb6+vsTNzU00ppWpcdDMuZ/SlsFUtMsHANKuXTvSo0cPUqFCBZ1j5sRBS05OJt7e3oLj1apVI3379iWNGjXSKZfnzp0T5D1p0iRBmlWrVhGlUimI+SaRSMj58+cF5xmKg5aWlqZTpr29vUmfPn1I/br1RJ89n4iICJ3vplq1aqRXr15k4MCB5O233xYc135v+rBWHDSbK1XW/KMKGqW8kPTPvVdOQcsPSyWxP10ladvCBfupgqaLIreIFMXmEEWejBBCyMmTJ/UGyRwyZAh3nlKpJOPHjzcYVBMA6dy5s2hgzR9//FHvOStXriSEEJKenk7q1RNv3OrVq0f+97//laqCZuxv3LhxgvMyMjJInTp1RNO++eabpHfv3qWuoJW2DKZSVFREevXqJSqHi4sLGT58uMUKGiGE3LlzRyfwq/afq6urTpk4cuSIIE3//v25Y7GxsaRq1arcsRo1apCkpCTuuLFAtf/995/eQLXvde9FfH199SpohBBy4cIFUq1aNZPKXmBgoEnvwVoKGh3ipFAoVoKo/9EJEEYhSs2zUqqHg/v374+9e/eiU6dOcHd313ueRCLB6tWrce3aNXzxxRdo2LAh3Nzc4OzsDF9fXwwYMAC7du3ClStX4OXlpXP+H3/8gd9//51bBkgMT09P3Lx5E19++SVq1KgBJycn1KlTBxMmTMCdO3dQvXp1nXNUciVUmph1ltKlSxesWbMGo0aNQosWLVC9enU4OTnBxcUFfn5+GDRoEPbv388NH7JUrVoV169fx8iRI+Hj4wMnJyc0aNAAM2bMQHBwcJk4ntuDDIDaF+6///7DwoUL0bhxYzg7O8Pb2xtDhw5FSEgI+vTpU6L827Vrh4cPH2Lx4sXo1q0bvLy84OjoiEqVKuGtt97C1KlTER4ejtGjR3PnxMTEYMyYMdy2j48PNm/ezG3Xrl0bGzZs4LaTkpIEwWuN8f777+PmzZsYNGgQqlSpAldXVzRv3hx//jIfR7bu1/EP1Obdd9/F48ePsWjRIvTo0QM+Pj5wdHSEq6sr/Pz80KdPH8ybNw8PHjxAly5dTHxS1oFRK3CvBu3atSPa67S9isRNVzvI1lrQpdRmclFKl5RVoZDF5sJnQiu4+FWytThWoSAsFRm7HqNCcy94jWzK7S9JINNXNcyGIrsIqlwZHCo5w6GS8RhX9s6r+p4o5Rdblklz6jyGYUIIIe3EjlELWnnm1dGtX19exXdIOw0UCoVSYqiCVp55FRv314VXUYch5XeIU5FeCGWO8eV0rIbmGdFPmEKh6IMqaOUaWr1T7Ai2OJZDC5qqUAFljsx4QgqFQikjqIJmRxQ+zkD+nSTjCVmofkahlEs4FdaOv2GiIlBkSkFUdiwkhfIKQ5d6siPSt6qjPFdsX8O0E2i9SbEnOAuaTaWgWAlVnhyqfDngwMDxFZjIQKGUN6gFrRzzKs3ApZR/2PJI9bNXBSL4R6FQyhaqoL1CKPPliJseiLxbdJ3OcsOrpGRrbkWeUlAc54uiB6rGUl5vlHkyyNMKbS2GXUMVtFIkfVcEklfcLb0LaDXuykwpACDvRgJkCXliZ9iEwvA0ZB55DpXMvIVwyzNERUCUmj8xJawcOtKbijwhHwnzbgr2lRdrr0qmFMiqzJeDKEthbdFX9/VTKCahzCoCkeoPbsxG0y9vWFNmqqCVIoVhaZAn5Jt9Xs6lGOTfNmGygJ5yoEgpRMqKe1DmCxd9lT7PMm8SgpVI3x6B/FuJyNjzpMyvbSvStz9C/MxriJ95DTlnomwtTomRJ+cj8/AzzmFckVaIopgcYSJeeSTSYmXc0dERMln5mCGpSCmAKk/93RClCspMKRTpUhtL9epBFKpy2fjqgxACZY6sxKspUIpRpBVCHm8/hgZTkcvlcHBwsEpeVEGzkIL7Kcg8+ly4714K5Mn5UKQXQpFheaWecyYamYeemZRW+jQTGXseqze0rDJEY7FSZEmRuj4MaRsfIPOgafmWBtJH6SiMSOe2cy7HIm56oMFZYoQQKHNlgjR5txONPt+C+6nIPPIcRS+zS8UCknslDrmB8XqPSyMyuN95t/QrxUSm0lV0LESZJ4M8yfwOgSkkL7uL/KAkFNxLAQAkLQ5G6ur7WqnE32PlypWRnp5ebhpkIteUF9YFiw7XWhWiVEGelA9ltjDunEquLB1rZRmgKpBDmVMERSodsrMWpKh8jrjk5OTAw8M6qxdQBc1CMnY/Qf7NROG+vU+QvOwukv4KRtKiO9z+vFuJSPgjyPpCqAjSNj9EQWiq+HFNu5J7MRZFL7Ktf30jyJPzkX06SrCPL0fO2Wj1DwMKWu7lWCT+EYTMfWrrG5ErkXXoOVLXhRm8dsbux8i/lYjUdWHIPhNt2Q1oocyTcVbJ7FMvkX3yRYnzzNj3BKmr70OZV3ILU/Lyu0hebt6QOlGqjPqB5AUVl/PM/U8NZCbclEZmQVWogKenJ4qKihAXF4fc3Fwolcpyo6wBMHs4UiVTQpFdZNo9mpBEVSjXsYazyBLzrVJ2yhK2s8W3sgKAIrkA8qQCW4hUcqgSX2YY+h5sBSEEMpkMaWlpyMzMhKenp1XypWE2yoCsI8/1HlNkFSF960N4j20helyenA/GUQJHrwoGryFqhSqD+EWFjzPg5F0Bjt668qWuC4OqQGjyzwuMR5UP6gsT6hEzLygRORrlqiA0FZ7DGnNud8p80xslRbJ1rEqJv6uVbN9f3tGbRpkngzJTKyK9WAOv2ccNp8lKZjkoisnh8jKHrGORyA9Kgu+sDnBwF19UOOuw/vIrQOs9pm14AACovbAr6tati8zMTGRmZiIhIcHgQsgqqQKqQgUcKrtwVhbHXPGFvfWdzzg7gJGYrlkpMostshJnB0iSndRDnDkyMA4MHDJNDzOhyCoCCIFjFRe9vobsPUpcHCBxczJJNsequs/A0DGiIiAyJRgXB4vW7OVkdHWEpILhpoKTw4T3RJQEypwiMBLhc+XyyDH9XZuDoWdVUthnBZhXVl9njJUZfcdNfY/mlElr4ODgAA8PD/j5+cHFxTphaaiCVoYQQgQVZUFoCqRPMiFPKkD+3WSd9NnnopF7IQaAupHTzY+3IaKMlZaVgqgI1/ixsdtE5TOmIGoehTJPJvqxiSkGaVvU14PC9Huz9mNInHdLz3WI2vfPgoj0RZFZyA8pQuX36lokE3+4kQt3YUKjXPQ8CwCgkirh4K57XJFt+vJHxIA5SCKRwMvLC15eXkbziZ9zE0SqgIOXAkqN/1ftha0BqJ32C8NS4damOlS5MuRejUOVwQ258lgUk4PUf+/DpVFV+IxtbrLscdMDud9ubarB89M3kXXyBfICM+BYzQ01ppi+2HvczGuAkqDW763AOIoPUuQGxiP75Au4d66JKgMbmCRbrQVv6bxT9hj7fMSOubWuBs+AN02WnyXnUixyzkTBo0dtVO5XzyQZxeTQRpFWiKQdwXDwcoXvj29ZlIcllGb+ORdikHMuutTyfxVh30eNaU3g6Klb/+t7X6a+x9IuT2UBHeIsS3jtlzw5Hxl7nnA+PWJtKauc6c+PFK/pJ2Zi1xM4NGVVKHddc1FkFSH+52vIDxYqlIrsIhAlQeHDtGLF0ETFKOnPO8YTaZC9tHyoVvo8E0mLg4t9jAygkiogfZJhNB2LMk+G+BnXLF4uKPPgM8H7VubILPZ9ip9xDRm7H3PbqiIlVAWGrWuqPBmIQve5GLL+6mCBuIQQJK+8h4L7vGF6jWKv5Dnns/Jn7n+KrKORSPrzNtL3PEb+7SSBIzGrqJrqv0LkSiQtDha9jzyNjyFjoJZUW4O03rmm/Cf+eUf/c2e/STOeWfyMayiyoPzLU+102NAKHSdFdpHaYmkhylwZss9EvZKrJeTdSkDqxge2FsMo5rplvE5YrKAxDPM5wzCHGYZ5yTBMAcMwyQzDXGAYpqdWOgeGYX5kGOYJwzBFDMMkMAyzmmEYnUFahmGaMwxzjGGYTE2eNxmGGWSpjHYHf/q+TqViwbx7AoAdxhGpYArDUhE3PRDyZGEFLYvNRcZey2ZUpq5X+34V3BcqeEkLbiN+5jWk74iANDwd+cHJBhtJlVRhdb8NZb4ceTcT9FoOs45FQpFWCEWGrs9V1vFIxE0PRM55dS84fddjpG0J5xpffY78ylz1cVMnhRAVQfquCIOzk1RFCiTOD0LWMdOUIzFFsjAsDSqZErLYXCT9eRsJv+mx+mn+p64NQ/r2R7oJzBkas+R1EkAenydQKMVg5ZfFqt8Df+hcPIyJaZfPuRALhZYPnkqqQEFYscKozJHpbcCzjj5H4vwgqPhlXZNUlSvjfC7VIVdU6tmLKmJxmA2pxuJpDvqseNooMqTis7wNvFdljgypmx+aKZB5yQkhagvVhRjBu1ZJFUhacBtJC2+rw6HIzZ8ZmrH/KXIvxUIWZZ2JOtZGkSFF3PRAJC68bfa5WUciOQu5PUMsDL9U+DgDsrhck9ImzA9Cxr7yF0WgJBa0nwEMBuAPoAKAagDeBXCRYZhhvHTrACwC0AiAMwBfAOMBXGYYhnNcYhimGYDrAAYCqKLJ8x0ARxiGGVkCOe0Hft2hXWlaGhdJ04CKzX7KOa+2yFiz8lFqFBFD/j3pOyKQecCAMzkgtJiYiCxW/8eoSCtE4rxbyDoaqRvahBAU3EsBYYdFNc9MmSdD4WO1cpN3XR3cl31mihS1UlsYngZ5SoHIjEWNTCbEm+PrOMrsIhSGpRm04rH+aIXh6XrT8MkLEp8lmnMuGimrQjllpiA0RbcB421Kn2SadD39mNY4qgrkkMXnmWTJ1LkCvy63Qiy53MuxOvukERnI2MWzQBYokHtRXS5UMiXS/g3nHPPZcDhEREEDivtkiX/eRvyvNxA/6zoy9j7hhirNVSgsuWVTFbT0nRHIPPjMLAfstG3hKHpqZrlhb8LEe5c+yUTOuWjknIuG9HFxZ4TfsCuzixD/y3XOZ9VULFUOyoqiKLWCr9uhp6RvDUfKP6EmpVXlyFBwV3zUqCAs1W5jdJZEQcsCMAtqBa0SgPm8Y78AAMMwHQGM0+w7DMAHwAzNdgsAP/DOWarJRwagN4B6AF5qjq1gGMatBLKWKrL4PKSsE2/ABRiqkCypeQlv+MVCH3NVoaJ4VpVCBWmkiT2uEjSOKatCdfzLjA3BsefpI21beHFeWg1M0bMsZOx9wimXKZpZk2mbHiJ9aziIvPjjlLg5IvPQM65CzDoaCZWBWXJcQ2vqlHBT2iQLhr/E0LbqZex5gvgZ16AqkEMlUyLnQoyO5dXcAMdx0wOReegZ5Mn5euXNOPAUCb/fQlG0uqOQ8NstpKy8h/hfrkNmbogRnrymLDhO5CqdIT5ljtp3Les/02fhsop8wq83II3IQOLvQZDyFBO9q3dovnlVjoyzGBfeTzX6jvPvJiNueqBOPERZbC7yghJFh79VUoW4pc9AZ0qRJUXKqlAo8+XFE1bY78GET1yVa/lsOmVmkdpfzwj875PIVcgPTlJbuy8VK9dswNP8EDPjPLKPy16dfUo5oDVREsjTCu1mVrWqUFGmsshic5Gx67F5rhxlSEmKZW9CyB+EkGhCSC7Uyhpb2zbU/P+Ml34hISQNwF8AcvnHGYbxgVopA4ALhJALhJAoAGs1+6oC6FcCWUsNIlchZeU9yF4ab2gIX4nSLoSWfIeEcJUvMTArTh/KfDkS5t7krAPZZ6OQtuGBaXG5SlBviFnCMk2dKagPXoOVZmTIhUgVKAhJ4Ya2+K+CcXbQaRRNqS+0w4mUCBELQ15QIuJ/vS5ogFVSBeKmB0L6SNzSJtVjgcs6+ZJzatbumevEUTPhPeffTkLyMv1+JAXByVDlyZG6RrcTk7pWJFyKgWsKFBBDsmmOJf51B8lLQpC6qdgXJ3F+ELL/e4m8q/rj2Gkjj9NVXPnlTJUnhzy1QDDZAFB3FrT3CWTXKlzJf99F9umXyNyntkBrx0OUPslE1uHnyLko9E9VSRVImHMTOWejTLwjNXlX4yGLzUVBaAqKx2aFaXKvxEGelI+sEy8EjacirVCgPFmE5ruVmmGFY7817TBHYijSCpH2b7j++Grs/ZTByh4qmRJZ/73UuVeiUEGeIu4naA2pFFn63S/StjxE8uJg5N2w/fKAivRCJMy9WaaysK4J9mqhtFhBI4Ro11jOANjwuWzN14Z3/KnmPCUAtuvalGEYFwBv8WR5qn2OBrucipFtRpR4olBBnpyvblQfa1VIRr5EMQduguKhxtzLcYZjVImg0vhPFTxIAwAuyKJJ4RrMCGFgkiwWBCUs/H/2zjw+iiL9/5+ayeSe3HcghFPuM5FDRQQFWUFEUUHcnyh4rMh6rK73Gtb1+K7Kuip4rCi4iIrnKqgICIhy44FAuO+QOyEJuSdTvz9mutPd0z3TPZlhJvC8X6+80kd1VU0fVU899TxP7dVvxK/E0ChNTzgr3Ro0/eXa6xwCWP2ecpz+4qBj6lNyudJ2Si91O9zYByo0M2pPuV5DIDwri2qrDURU7mnTkWpUfLzfobmCQ4vaVkNwtW+w9SRQv6vM5fDp/x3SuEAQwuVHmwtrUbPupMe62BQdujiNrWE6YDvdqG4iIDxgu6QuKvez+OWfcebHAjSfqgW3c1StOoaiF7e7hNHRg1rcNk+DKtU666Doxe1oyK/AmY3qwpz4U9vanEnumSBs2U43oOil7WKoGMeg4KTLb6384iCK5+1Qj2fng2a26HltJyzBRq1WYSZhb7SJbXLtz8WqdoaNR6pEZzN7XbPM2aL8/Xz1gYkGTQVnRI2/NMi3EZpO1LgEP27v+FKx+yCAKOf2Quf/JMn5apVtM4AEHekAh41b0GEkSGT9b6WipkjpBenJTuTUP1QC3Uo0aLWbCw1HkRc+OjFgpAHbkIbd5aKBfKCo/921Q9SNgc66zJ0nlIYmRIt6Lxqf+t/LJB25f6Wgyk8PoPi1X9ymKX9PxZkA+oRed0JO7c/FnhtY6eUetB51O+TfWFuXOStfqu3IwDk3FHdNreM1MkhRLpXkLgJ/c1Etip7fipL5vzqcFWRayNZvXvqKcc5Vv5GSV39B/a4yTQ9zrXtc/NovKH8/3+FUoLDndCv4Ousjx4uYblomFAZC0gicfOIntwPz4nk7ADg0y7bSevGeaHl4i44kkuffXOQYyPt6eTzebEfFsn0ujkW2kjqZY8yppzbhVN5GAEDlsv2qdoalb+4Unc1OrziCGmdYlsajVYbbZk/fPbdzlL27C4XPaTtLlMz/FYX/1B8RoD3gEwGNMfb/APzdubsWDqcAt5dItt216h7TMcbuYIxtZ4xtLy01bnjeZgz0l/Z6m2iwr1wk1hTmfu0u3mBzUf02F9e1STUvaBfEj8OZla28AdzOcXrFYVR8vF90Y7eVyzU2ZYt2I1gwLLZoCWhe3k635UvyPONmeajWzJSG/FKrc2m+/pmWkU3nGShCafunRtU3RzTPVS7b7wgLoFfLaNBW78xP+qc01dCaShbroCagaQltglwkeQ8NGazbuex3F7+0QzupRDAoePxHuQe3STIoE6LjcI7azYWtK30ocBdKpvLTA6phL5pPnkH972WqU6IFT/ykmZ8adpWBoddmS8L91/me1+4oBmx21Kw94fAuXX3MYeOoXGbPzsU2Xc0A3ZP2vy2zA/Z6m8v1p788BHuDDdXfH0fdzyWt8SQluIRwMTLJ4HyuNetPyswW1AbxTSdqUPOj4lv0MLgpenE7GvZVeh7AGY0M4P+Z7TbRZgGNMXYLgHedef0IYBLnXGippWJ0jGRbWKiqBUCljnQAoCp9cc7f4pzncM5zkpOTvfgFbcTItImbVoRZPD+K01/Kp0tqNxUaG7V7QJjirPr6CGq+P44zGwpQt6NYXOtTGTstGBaybTxahTNbCmUxs/RQvfq4qhehyyoAHihbuAunvzrktnx7rWOqkrfYdU2zKQ3A1QzCm4tqUfKqe02XO2o3u7ffOfnIBpx8ZIOhNWVrvnf1iFTS5OGdaalu0uwYtDRMeqcubSX1oqOCz5Fos2VofJ5VX8kdFHiz3dA6lA37KsXI9Uapl0yDigo0mX2su6lZHbh7Hjraq8bj1Shd+LtoqyX9nRVutJiAw2nh5CMb9JueCGZ3dTY07K8UHUqE91/5TKRmJPY6G6pXHxdXzJBXhIs3t/FQleNbKmudli73MLg1hXq/2Hb5+/ku+Z/ZeAo16064f2c8fEZl7+5C4f85NFguWk+NwWLJAlfHrpL5v6Jqufz99zTWbDG4trVRc7AMnnQAACAASURBVIYg8ZFwoU0CGmNsBoB3nPl8D+BKp8OAgNRyuIfzGjMAIXT2Hs55I4Bf0Tp50UN5jRPveyMfUvbfPbJ4KkaCiZpj3Sz/oDMbF1W92QcCmjOPFslyNzIPKedvZG1oNPxBc0kdSt/YqX8pIj8hhOjwhL222aNAz212FCnU+DapF6Lz8rMV3NElZElb8WRr6Waa79RTG2X7gv1TjfNd1SNMlr+f7zGNV3D3oWdckisWZC948ieUvGKsidNa0cIQzjo37Kto1Ux56K08hkdxd72Odq588W40Hjgt2mp5833XrPU8WLBVNaK50PF+l72zC2Xv7HLRRPJmO+rzy3HykQ0uGqbmQsdgo6W6SVxFoPVCSTrnoMRW4t5m1FbR0OpAoPIqcTtHw/5K2JtaUL+7TDadbG9sQeVnB2BvsLnYJwoobRtdtFsqz026kkjDvkpxAFv0r9b7dOrZLTKhX1ZGZSPqfi1xxL10h4nBJgxyDUpL9XsrXFY8kWq79Zn+BKeE5vVST4yxWwG8DYdw9i2AyZxzZQu5FMA9zu1HGGN3AJgFIFpyHpzzUsbYagBjAYxhjI0BcAjAXc50Fc4yAo7SM67ZQFgC5mYaU6/ReovCKNcXGjQhD1nDKxE89YQz8CUnH9kA66gOHtPpmVLTw6m/bfScyAfUbi3yWGe1uFzSBaQ55ygwYHwbbOjxdtaL3bkea+PB07DXNaNIh/2Jv+Je2ettXq380FxwRjQq98bg3ltKXv8NKX8aIH7c0liJ3IP8VW3AMcoFHe2cvdYLxwMVzbfUSF1NYNNaKUQZB658scPmsvRNucdx2dvajg162vOW6ka0SMKUlC105Nfh+UtUBbTqlUdRs/4kzLGhaKlyvPtRuWkAgDObTjls3srq3TbT0qDlhc8o7JolU9wCysEiAFdPZQ+rp1R8uA8RfRMRP6WH5jdqr7N5HeqifNFumKyt6wjXbitqFfagPpjlNrvjOTu/2aYj1Y4ZjsYWNJfWI6xTjMs1gaAta3E+hVYN3JUA6hWGlp0555sYYwvhiIU22fkn8DuAf0v2HwCwEY4pztWKsu7lnAfleiVG3HM9eYHpwUUV7AsNGnNvoMxVtnxN4/5KnHp2C9IeGALAdbSnhlG1d6ARguC6w5PjhbDSwbmM7gC2ksGJ3iVtRIcYH9Owt0IWRFXEg9DWXFQrGpWfTZqEqV61uSUfLXvUdLIGJa/9irSHcnySnzs8BcZWQ8sxwBeegKfyNnqMTVn00g7wxhaYVdahrNvhGlRVcCYQhDMZzmfWeLgKJqtFs0x3S+Uptbq+pH5XOUyRRzQHIbKBk6L8grmbPOYvtUus/PSAm5QOSl7/zcVEp+DxVlvIlHsGIrSDVXnZWedshOe7E8DDcITMaAJQCOB1AKM456LOl3O+G8BFAL4CUAWgHsAWANdwzpechXp6xIjHpipuPlhPNkEikkalYW+FTzRovMnuXrNwlibo7dVNaAzSJVfOFkp3dyVGYned60jffZ9PxZ7P+Oh7r3V60UoN1mt+8DzwOmtoCGgyId5r5wPPScTpfBWBWC0kilutHNfYNoCgQFA6sPkKt9OckmfReLhKlpZ7aWvpDk/20yWv/eqMDRhYvNagcc6zdaZrgcOr05NnJzjnuwBc7W2d/I23C2ELuBvlCaMjTyhVxIINRVtxsaGQluH06jsbcpon41mCEDkLwUXPR3y1cLgoQEu0iMog0AFFY/ZB6hhQrRFOxJd4DDMiJlQ/XL+rTGZnpSuOpVr2Tg1a4f/5J1SFuNSe+lnZnpH4ov6i4sN9MCeEIywrcNOdwbrARVDiS4/JYMNTw2mraECdInYbQQSU4LTrDThNhbUodrMsmhTVeGY+EtAEAbrqa0loFYNZ6xZeDFD5v4NoOHha03hcakt4RhkOwh8o7rfmot4az6V8SX7bYkI64XaO+j3l+oNuG8XNe1X5iXxa0pt1evVQ+dkBQ97SWs4PZ4u22KCdf5zDApon9BhgE8RZJVh94wNMyb/1efhqCj++6ht9MPz3hwardlOh22WibMVn19xZ6Vyitai3rzSbWtjrmjWDUPsCVRtNDdo6W6VF7dYiY1rcADcxpEEzwvkrnxFE0OGvRrw9YzSOnxoNh0636fqiF7ajfleZoej8WgRi6R53wZT9gt44fiqCo5HllDwX4B+tlTeorVwQCAK9iDxp0AwQyClOFmb2n+qZIIjzjmqNWGFayzgZoXxJPkKSI9qcz/mAkSk3f+IpvMp5iZ+1lp4gDZoRAiigWdKjPCciCILQiS8EMXcIK5MQHggSwUgrwO15DU1xtiMCqUHzsJg6QRAEQRC+w992f56gXt8AvrCp8Jrz2EGBIIjzEy2DeYI4K5AGrR2h8275Y83KcznEB0EQBEEEHQF2EiABzQB6hSRzvJtF0b0t2xdLOhEEQRAEoQ/SoLUjdApoftF2BaGAFjEgOdBVIAiCIAi/QDZo7Qm9gpcfBDRmDr5HFeIHTSHhPyIHpwS6CgRBEO0HEtDaD3qdBNqkQdO4llmC8FG1w7UQE2/p7dP8QrMDt06bUeKv7R7oKrQ7UuYMQkgSxfMiiPMRe4BjjwZhrx/E6HUSCG+Dk4CGzGOODTJtlYm1S8/S8J4JPs0vrEusT/PzJyzEhJQ/Dwp0NdoVoZnRSJkzCNEjMgJdlfMa66iOga4CcR4S6ODwJKAZQafGyMhCr2l/zZXth3VW7/CDTYPGzMyQAi00y+q/yhjA56FS2pkW0WwNDXQV2h2mMDNMMfruW8bfR/i5NucnkYOC0941rFtcoKtA+BES0NoReqcuNRchViEkIVzcTpjWE5FDUtXL9pOAFjU83avrzPFhhjRo8dedf9Nr5rgg03oCPllPNnZiF0Ppo4amtam8kMRwz4n8jF7B3uSHEDtnC7NOIZRoxZIZTWs0+wkWqqPP8/O9tzfY/FuAB0hA8wOiQb/B6P8hieHgzeoSu78ENEtKpFfXJc/qj5B4Ax2nAU1Tyj0DvaiRfsIviPeYxhTlg2VqA+R5G5ISgdQHhiBykHGngLhruiH1gSFu00T2S9KdnzkuDPGTu6PD85d4nibUuF2eprcsafJ3OGVO26dx4yZ3Q9w13VoPKOrmbum19jTtLcV6eVagq6BNgMMdaLW/jDGYIvyzpHVIcoTbgS0L899gIG5SV13l6llvNfPZi73SNJp0aPujL+lgOF8jBHrQQgKaQRKm9/ScyHlXDc9+MQaTRf2jC7alnswxoYgY2DrtEHtVFyTd3k/7AgP3wt8fRdKtfT0n8sK+LmpoGuImd3M5njC9Z5uEzpTZA5F0m446O4mb1A2WlEgk3HiB23RKu8aQ5AhED0tXFdrDusUhMicV1jFZMMfo1wxKPUe5RtDHhGk9kTF3BNIfuRAxV2Z7zFNpR5hyzyBkzB0u7odmRrtc0+H5S3TW2EH00HRED5NolxUfc8rsgbIy4yZ2Qer9gwFo/053WDpEBzSUDgs1I6Jnos/zjVAR5kNSWjt1vd86bwmshJbxt+GIHKgyzSp5ZKn3D0bG34a1HlBpssO6xekOTxSVm4aoXG3tc+Zc/02nR2rUMem2vsh4Yqi4H31Jprgd0Vf9/WEmhtjxnQ3XQVef5+dPxlMb6m+Cq9dvFxh4Iwx28szMND9ef6xOYBRl3aTTPtZLMhHetXWUZOkg7yQNebae5bY4rIerRs0bW7Ww7FhED5V06s7fEZoRjdAO7m3wEqZdgOS7+queC+1ohSnaorseuqcEjfxEBiRM6YHYKzrJDiff0R8mq3bdYi7zrJVhFhNMYWaYY8MQo6Itixwo1wQqNYMsxARTWAjCeyUg7lpXAVmNxP9n0JtXca+EMgXMCeGwpDq1apL3N2pomi5P34g+iR7fe6NCpiEYYIr0vSZITUCL6J2IzGcvRuoDQ9xqIqXwFofZSEhiOGL/IO/szbEOIU953KhDUIYbgYdZTGBqmjITaw02bzbBFGmRnTMrvsWkGX08RqcXzFzU3ptAx54MSY4AkygRoi90be+kCM/fGy1jMCglQhID68Ed+DvQztDVbztHe5b0KMRe5Wqvw8I1XlamLci4U2crhSHhWNzELki8pTcsGa6NoFrDKZD2SK76CZWYMCmzB8o6uyin1iEkIRzhvSQNZBAY02c+3doAS+3DwlQcGNSMwlP/MsSlEZf+LJdpEOF+ORO50zCaItSFHCPTlKEdrciYOwIhca4Cmij8SR+hTqE5tFMM4iaqT3mEdYmFVTHNIJtClmiF1IQvNVIfGIL4KT3EfWYxwTpacq1GtZNu6SPvMDRInNEHEb0TjXXgBl5faccSP7m7S+ek7uXNENB5PMZcvlGtAQMARI90PHN3HuvMYnKJ3xgzLhsxV3QCMzFYUiJhTtA5mHB+S6Zo1+8yZfYgJN3eD9aRHWR1lmrq9GDyNGWo8nhYiEk8rmzimIkh/aFccco9YXovsBCTujZQcpsSru+BjLnDEZblKqCZoxzthDcDdmYxGTa7Ecj42zAk3+XerEX6q8SpWec90WVPpkBr9RxZPEehjfXyd4V2Cu4wSSSg+QBlQ2ZJj0L0JZlIvKknrBIVsEDMZRrz5s4vXO1lNmkJdQBiRrtqKZJv74/oizIR0StR1tm5oNboSEZICdN7Iqy7UzOmMvIL7WhFRO9W1XaYMOpjTCEMaFdBLLct4UkkxIzrpHpc+rukzhlqwqNaWBMWalZvxJ2XC7ZHaQ/lIPlPA1yShXeNQ+LNvWTH4q/vgYSbJPdYmbWBe8LCXOsnaCiY2tS5TqEjeVZfl2lPU1RIq1ZP8VpIp5ClAw69oWIsKZEuQXWl2qqwrt55ziX/aQDiJnVFhBehVqQaVU+arITrtb+36JEdkHyHiuBjUD5T064oPcLdodTIMhNcvtGwbG1buojejnsojREXP6U74q/v0SqUKzpNc2wYokdkyIQ2vZp1QTMV2tEqfhMRA5PR4flLYI4JFbX3YdmxSPnzIKTeN9jlfsZN6tqmKTE1G0qHEOEsSClQOH9baGY0Ojx/SavtpmKgy8JD0OFZ+Tslfd+lcM6RfEc/pP7FvZ2oGin3DESqXlMLyftujgmFKdLi9n0AAHOkBUm39UX89T1aBynOfLR+j/sM1TsN6fcvCKrWkZleaZiT79QehAQDJKAZReUDD8uOReY/Lmo9YGKIu6qLi61O6oM5iJ3QBdEXyYU2sRN2ftCp9w6GdUwWIgYmiw2p0PFaRzmEO1O0Ra6hgkGvQefv8GQvE9EnSZy243qcU4X7o8xXIQTFX9cdkYNTkP74UCTN6of0x4ciarBDte9OW+jOJkNAz7RawnSJoOS87xZJ469ajsq9snS0IvOZi5H57MViJxKSGIGwTjGtHYTkp0f0lWsuo4akIrJ/suaUqnhc5TwLD/H4zEOcgpUouEl+g+6+SqXs9MeHIf0xpy1KW22n1K5XHIq+qLVzNEdZNAVad4R1ikH0cEknq1JsypxBqoKOML2lx8HEnSAa94fOqkIJY4AlQ64Jd9fhpNwlHwCYrBaEJIQj9b7BuqZvM54YhpR7B7faTDJmbFpfJW1UThqihqSKAZHDsmNk9zj90QtdBhB6Az1bUiKRcs9AxI7vjKicNMRO7IIEjYFnaEY0LGlRLgJa9PAM2bGQxHBkPDUcWiTd1hcwMUT0TxLrIJbR0aF1D++VINGgye+JpvCpnInwcNtT5gySaXvDusQhRPGOCRqryJxUpD16octUaNy13Vqn4D2g1GqqDTalzy3p9n6IHJSC2AldEN4jHlFDUsUlkoR7wCwmZD5zkSGzH2aWx9oU+kJLquM5xE/p4XFiJvaqLo5ynSRMk9uUSZ+R8Du90fb5C/+4n5wHhPdKQEN+hbjPQkxIvKU3yhfvkWmUpFiSImC52FWjFtE3CXXbi2FyCgchiRGirc+pZ7c4EoUwdHj+ErScaULNupMAdzQSDfkVMMeGOdTPSREo/McWsT668DRqZ2htjHUZP0u+GKkwoPiSQlIjRSFIiM0Ve1UXWEd3dKst9FrLpviQhakCwKk9cNY34/FhjjApglxkMbXGtXP+nIy/DQOzmGFvsHmIK6Y+95ExdwROPbXRu98hITNvOOp+K0HFB/s008Rf1x1RQ1JbNR2SBikyJw3VK4+6LSP5jn6q75K0YYselo763eVoOlLlsc7JfxqA0td/E/fD+yQivLu2DaDg/aWsQ/LMfmg4UNm2OEXKKb07+qk6GAAOu6nmSzvonqZ1R0hqJGKu6ISI/kk482MBarcUAWBIuq0vbMV1qFl/Ag37KlWvjZvcDQ37Hefib+iBymX7AQBpDzmESktalEM4kZAyeyBK5v/qkldoelSr3ZmHji6iXxLqfy9rPSAOxFTS9klEzfoIxFzRCS2nGwHAZTApENkvGWGPxwKco/DZrW7rILXjtF7k2o664KG9ir4oU5x+Vgr86U8OgznKgg7PXqx6bcpsiSZKKEYpfGgMXIyu7xiaGY2w7nFo2Fvhci5hek/UbilCVG4awnsnwhQeAmZmSJzWE6cOnYb9TDOSZvVFeDfHN6a0MzTFhMJe3QTAoYG1N9gQmhENe70jvAQLN6tOaybP6gfe5Pj2wrvGyeyPgdYBodQTk5lNCO8RL/6O8N6JaNhTLv+tWVZE9ElC1TdHwMwMHZ69GCcf2SDWD3YOU3gI0h8fCrM1FNWrj8mv7xwra4csKREyjW3kgBSxvVSanCi/m2CABDSDCC+cJSVSJqABQESvRN1qVlNMKKxOrUD8Nd1gHdkBZhX7CqEDElTEpogQMIsJsX/ojMhBKYjonSh7sRJv7oWW2mbZ/L0lLQrRIzIQPSIDtooGWDKjYSurR/3OMvXAuErBStIYh6REwlZS5/kHKtsgHQMnZmYu9yD9saGo/HS/2GFFDUlFSHIETn920Hn+Qo8NuyfMCRFinZnFBGYxwd6k0vE7f5OgKTNb3HugcRUNGuBsvEIYYFPcJLXpZmdDpzVS9BR41hRqRrjECcIcHYqEaT0R1jUW4NAU0FIfGIKWqkaEdfGsqWIhJiTf0Q8Fj/7YWk5MKFqcDb+UsE4xiByUgrpfShB/Qw9Ra6pG2oM5bgPEqgl2SmLHd4YlU73hjb+mG6qjLWguqkXT8Rq3/bkpzIw4d55o7obySs0KY4gZ49DyirZEzDFoMHeJdRumI3pouqjRjhqcKgpo7uKvCdoegfQnWz0NmcuGAxdvZKV9lZvfawoPQdoDOQCAeqeA5m4gaLaGipr8yCGpsJXWoel4DQAg5opOXgeDDfFk3+YsU9pmJ/9pABoPVMoGcB4RXhyT63NWwzqyAxoPnG5NZ2otW8vuSivPyH7JiOzn0JYp65z+cC5spxthSW7V/JljwhA/pQcqP9mPiH5JSJzeSxSAZPfLg3DLQkxulQDhfRIRf213FxvaxOk9UfCkY3Aa0SvBRUALSYxoDd2huJ/Sd1xo95SaupQ7+6PxeDVKFzgGgeEXuA4MYsd3xpmNBS5CpUiAQ7pIIQHNIGFZMUi6vR/CsmNQs/6k1/lkPNbqqsxCTJrxyKyjOqJ65dHWjtpsQubTrSpbpdSvnEIDHC9v3NUOI29Bk2KOsjg0copONKxHvNwTCRA/FG7nSP3zIPcjQHUFmuvoUudHYI4JRdKtfcVGBMzhOSQIaFohH8xxYTDHhyOiZwKqvjni8J7SQGyYPKjfjcYdSpzWE9VrT6gKUekPXwh7bbO8HsqYQmYG62XuNTZhXeJgvbSDoXdRcKFXE6AELCmRhmLkCR2HMAWY8udBaKlSz18Q0NSMoKUo18BMvLkX6qRaHDdEDUtHaGa02ylxc0wo4q/tjtK3f9eVp1/wU2eQ9tdcFP1zmzhdk/7YUBQ6tfHSjlwsXnh+zpkB5UDJRdjxsc8PYwwZc4eDWcwokWhYQztEO8wFvCBqeAZCUiJRtnCX6nm1Wx/WKcbr8lzkMY32JLx7PFJmD0T198cdg3xBW6yjXCMhXJjFLBPOBKJyUmGOD2u1F3afi+7yZFcxhqgLXb89mS2smgDLeasThZ7pUCGtRFgMy4pB3KSuaC6sFY/FXJ4lajStl3aA9VJXO3BB4LSO7ojqlcdczgcCEtC8QFPy1iDx5l6GVheQEnNZR8R46KTbgnLKMFkl3pbQUUf0TXSMnNxm6PyvaEiU32JIvJdR9p3ZxozLbtUMSQ2snd9p+iMXipeofYxSLOlRiB7ZQRb3ShjJRg1Nh/WSTLTUNhsbVcOxbFeyxtJdZmuoi+Cm7BRjRmdpakYi+rROo4f3TEDN+pOGwySIxtb9k1C/swwmg79PSdojF4r3yBwdqqoRBoDwHvFeGfRG9E1SHYCoEX+NvnAbgMOov2ZDgeYya94QOThFXwcjfCdeCjxa5SgHE+aYUKTeP9h1kOEs30Xb49wNzbKi6XgNYsZlw5IejYoP9hqqnxDnTE84DdGQXNp2tMH7m5mYey2rj4Tj1jAbCo2Pm9ASoR2tiL0y2ymgeS7D1z7wRvswvyD5UQlTL0DFh/vAucPZioWZPbbbQGt8PKW9n8zWFEDM5eqOY7LqmJnYLtX/VoooHR7h/oYEtLOA3k4lEJhCHfGnWqoaNdOEJIQ7QlQYcWXmjuvEXCUfUObTF7V5ZQSp0Jr2YA64naP4pR3wpiljJoY4RQwlZjY5HD9MDMzEArJYvTxMSeumdXRHxI7NFvdDs2MQO7GL2+lCNUyhZsdvNDPUdi3StJ3US0gwLm2lA3NsGOImGFu+yhMJNxgNcOldF6xVjppco2okLowbNWzKku8aANg5GGOIHJBsWEAL7WBF8t0DEJppYC1eaR18LZn4A1HIllfWU+xD0WtfhxAqxGpUxgT0BWHd4lxsObXMM3xFSGK4fGAhGdiboyy6g/AKg1xft8+p9xn3kvUHJKC1gdAsK6KGe1i+ph3AQjx/haphGtTSORsbDiDuqi6o3VzoOGFiMCeEgze2tEk4U9PwhyRGGFqgXi+BCJSYdGsf2BtbENlff0BKxpg+o2m1a52/URZglzh7+Ksj1Ostp9DgRQ5MRsPeCtF0gpmY+7x0TLl5msp2QWpC4YP7kjF3uLq2zMfTy4IWJ/2xoaj58SRir8j2cIHw3/OPtCRH+i1QcfIs1/iMpogQWNKiEHOFZ82TUTL+NgwIMaFhd6v9WXj3eJjjwlSXdcvI0/a0jb44E+aEcM1VDNo7JKC1gZS7/btm5Nkiol+SwzPUBwh2VOHd42WCGDMxpP8116tlcGRoXc8U/9spakatxLkLF6cY1c+nPZiDohe3G8/Y6HfgrEDkwBREDNAO+6JM7w/CeyeK9kOG1vvVQDsGl28ktNDMaIdTg/OWmGNCEfcHzxrZ1hA6PqmGT2Em5ogl5wcEG2eph6cp0iIzS5Gld+fVb2aG1gZWI/H/9da1pmggIAGNQMzYbBcBLWpomtP93xiW1CikPznM1R7KgDqfUIHuW1DTZhd9jeerdJQwkKGuVKIXnHS2KcDvWsyYLDEorFG7z0CQNKMPmkvrXVZN8Ihwm71Y9/dcILxbHOImdkGYDm9sf9JW0w5/QgIaoRpQMX5yd8RP7u5VfqqNqsG2S3NN0vO0MSOCkzZPO/nN1kendkgrhpeBYuKv695mBxMpzMT8Jpil3DMQZYv3wF7TBLPKkmjeYIq0IKxT8AuSwYgyaDshhwQ0AoBjGRRl2AdfYnRUnjitp2w/6ba+qF57HCGpGqEfzI6I31Hnqi0VyaXtlqgL09CwpxzhaiN1PVP+IcywA4jwwniyoxQWGleup2oEPat7BAuhHaxIf+xCNB6uchtv7myg4VtAECJBJ6AxxrIAPAtgHAArgH0AXuGcLwxoxc5xlG7JwUZ4j3hZwFUljDEk3tRL87waKXMG6XKQCAakC6BHDTHaWROBJKJngqamLXpEBup3lcnCpijp8A/1aPbuMIWZETO2k0cPclNYiFdaQOG7Ua7p2R5gjAVHmAmS0AgPBJWAxhhLA7ARgFTv2R/A24yxNM75M4GpGeEtMWM7oXrN8UBXQxWtZX2CEWYx+c2LiwgcltQoZDyp7aXWFmJGe16T1iih2TFoOloNS2oU4q/tjnA3giXhAbvcg5YglASVgAZgLlqFsz8CWA3gCwBDATzFGPsv5zw4e3tClZjRWX7pKAiCOPtI12BUixRPGEC0PyQJjVAnaJZtZ4yZANzo3M3nnC/hnBcBmOc8ZgEwJSCVIwiCIMBCTK5LwZ1nWHykeTcnhAMmIHas72ONEecGwaRB6wpAsNrcLzku3R509qpDEARBEK1k/H2EzzzJTaFmdHiWzBYIbYJGgwZAas1arbHtss4FY+wOxth2xtj20tJSv1WOIAiCOL8xhZoDssIIcX7SHt406XDFxSedc/4W5zyHc56TnKx/eRyCIAiCIIhgJZgEtDLJtnTxNumKs6QiIwiCIAjinCeYbNAOAaiCww6th+S4dPsXdxns2LGjjDF2zA91U5IEuUBJBA/0bIIbej7BCz2b4IaeT3Dj7fPR9BJhbV682ocwxt4EcIdz92YAa9AaZqMZQFfO+YkAVU+EMbadc54T6HoQrtCzCW7o+QQv9GyCG3o+wY0/nk8wadAA4CkAV8ERC22J4tzcYBDOCIIgCIIg/E0w2aDBGfdsBIClAMoBNALYCWAWrSJAEARBEMT5QrBp0OBcKWB6oOvhgbcCXQFCE3o2wQ09n+CFnk1wQ88nuPH58wkqGzSCIAiCIAgiyKY4CYIgCIIgCBLQCIIgCIIggg4S0AiCIAiCIIIMEtAIgiAIgiCCDBLQCIIgCIIgggwS0AiCIAiCIIIMEtAIgiAIgiCCDBLQCIIgCIIgggwS0AiCIAiCIIIMEtAIgiAIgiCCDBLQCIIgCIIgggwS0AiCIAiCIIIMXQIaY6wbY+w/jLHdjDE7Y4wzxmx6C2GMZTHGljDGShljDYyx3xhjMz1cs8FZDmeMrdZbFkEQNkL50QAAIABJREFUBEEQRHsnRGe6vgBmeVMAYywNwEYAmZLD/QG8zRhL45w/o3LNHwFc7E15BEEQBEEQ7R29U5wFAJ4FMBHAVoNlzEWrcPZHAOkAtjj3n2KMZUkTM8ZiAPwTQJ3BcgiCIAiCIM4JdGnQOOfbAGwDAMbYg3ozZ4yZANzo3M3nnC9xHp8H4CMAFgBTAMyTXJYHIA3AY3AIhbpJSkri2dnZRi4hCIIgCIIICDt27CjjnCerndM7xektXQHEOrf3S45LtwcJG4yxPgDmOM+/BIMCWnZ2NrZv3+5dTQmCIAiCIM4ijLFjWuf87cWZJNmu1thOkWy/BofQOIdz3uTPihEEQRAEQQQrgQqzwSTbHAAYY1MBjALwGef8O90ZMXYHY2w7Y2x7aWmpb2tJEAQRRFRXV8Nutwe6GgRBnAX8LaCVSbZjJNtWybYgVT0BwA5gMWNsIGNsoCRNtPNYtLIAzvlbnPMcznlOcrLqNC5BEES7p6qqCvPmzcO6desCXRWCIM4C/hbQDgGocm73kByXbv/i/B/trM//nMd+kaQZ6tzP8U81CYIggpuamhoAwMGDBwNcE4IgzgZ6A9VaGGNJjLEkODwvheNJzr8wxli2JLBsHgBwzu1weGsCQC/G2HRnXLQHnMeaAXzss19DEARBEARxDqDXi/MiAGsVx8xonZ68FcA6jWufAnAVHLHQlijOzeWcnwAAznm28kLGGHduruGcX66zrgRBEARBEO0avzsJcM6LAIwAsBRAOYBGADsBzFJbRYAgCIIgCOJ8R2+g2nWQe15qoZqGc34cwHT91RKv01MmQRDEOQ9j1BwSxPlEoMJsEARBEF7AOfeciCCIdo+/VxIgCIIgCJ/Q2NiIiooK1NTUoKWlJdDVIQgRs9kMq9WKhIQEhIWF+SRPEtAIgiCIoKexsRHHjx9HfHw8srOzYbFYaNqXCAo452hubkZ1dTWOHz+OrKwsnwhpNMVJEARBBD0VFRWIj49HUlISQkNDSTgjggbGGEJDQ5GUlIT4+HhUVFT4JF8S0AiCINoB57tAUlNTg5iYGM8JCSKAxMTEiEGl2woJaARBEETQ09LSAovF4jkhQQQQi8XiM/tIEtAIgiDaEeezF+f5rkUkgh9fvqMkoBEEQRAEQQQZJKARBEEQBEEEGSSgEQRBEARBBBkkoBEEQbQDyP6KaAuMMfEvOzs70NVpEzNmzJD9nnXr1gW6Sn6BBDSCIAiCIM4ZRo0aJRPgjh49GugqeQWtJEAQBNGOOJ+9OAkCAHJzc3HmzBlxPzk5OYC18R8koBEEQRAE0W6YPXs2Zs+eHehq+B2a4iQIgiCIc4D169dj7NixiI2NRXR0NEaMGIFly5bpvv7kyZN47LHHkJubi/j4eISGhiI1NRUTJkzAp59+qqq9XbRokWw6MS8vD4WFhZg9ezY6deqEsLAwZGZm4u6770ZlZaXL9U1NTZg/fz4uu+wypKamIjQ0FNHR0cjOzsaoUaPw0EMP4fvvv5ddo2WDJhxfv369LH3nzp1l6Y8cOYI+ffqI+7GxsaitrXWp2+uvvy677o033tB9L30BadAIgiAIop2zaNEi3HbbbTIhatOmTdi0aRO2bt3q8fqPPvoIM2fOdBFUSkpKsGLFCqxYsQJXX301PvroI4SHh2vms3XrVrz66quy9ShPnTqF119/HVu2bMHmzZvFFSE455g0aRK+/fZbWR7Nzc2ora3FsWPHsH79euTn52P06NG67oMeGGN44IEHMGvWLABAdXU1lixZgjvvvFOW7v333xe3o6OjMX36dJ/VQQ+kQSMIgmgHCF6cZINGKNm/fz/uuusu2buRkZGBsWPHIiMjAy+99JLb6zds2ICbb75ZFM5MJhOGDx+Oq666CpmZmWK6L7/8EnfffbfbvL755htUVlZiyJAhGDFihOzczz//jI8++kjc37Rpk0w4S0hIwLhx4zB+/Hj069cP0dHRnn+8hNzcXFx33XVISkqSHR8/fjyuu+468S8qKgo333wzUlNTxTQLFiyQXXP06FFs3LhR3J82bRqsVquh+rQV0qARBEEQ7Z5vvvkGRUVFga6GIdLS0jB+/Pg25/Pvf/8bjY2N4v7o0aOxfPlyREREoKGhAVdffTVWrVqlef0jjzwCm80GAIiMjMSPP/6IQYMGAQBsNhuuueYarFixAoBDU/fQQw+hV69emvn997//FbVNc+fORV5ennhuzZo1uPnmmwHAxbvyt99+Q4cOHcR9m82GjRs36n6ugm3aqFGjZNOcCxYsUA0tcs899+DJJ58EAOzcuRM//vgjLr74YgDABx98IBN4ldq1swFp0AiCIAiiHbN69WrZfl5eHiIiIgAA4eHhMgFJSWlpKTZt2iTuR0VF4ZlnnsGUKVMwZcoUTJ06FadOnRLPc85FYU2NYcOGyaYCJ06cKDsvzatTp06ycw8++CCWLFmCzZs3o7KyEiEhIRg5ciRuuOEGzfLawt13343IyEhxf/78+eK2dHpzyJAhGDJkiF/q4A7SoBEEQRDtHl9ootorx48fl+336dNHtt+3b1/Na48ePSrTFJWWluLTTz91W96RI0c0z+Xk5Mj2Y2NjZftSTd+IESMwduxYfPfddwAcdnDSKdAuXbrg6quvxl//+lekp6e7rZM3JCQkYMaMGeL05qeffori4mIUFRVh9+7dYrpAaM8A0qARBEEQBGEANY9HgcTERNm+2WzWTMsYw4oVK/D2229j3LhxiI+Pl50/fPgwXn75ZVx44YU4ffp02yqtwf333w+TySEKNTc34z//+Q+WLl0qnrdarZg2bZpfyvYECWgEQRAE0Y7p2LGjbH/Pnj2yfak2SIlymnHYsGHgnLv9W7Rokc/qHhISgpkzZ+Lbb79FRUUFKioqsHXrVtx1111impMnT+Lzzz/XnaeRZdG6deuGSZMmiftvvvkmPvjgA3H/pptuMuys4CtIQCMIgmgHkBcnocXll18u2587dy4aGhoAAA0NDZg7d67mtSkpKRg6dKi4v3nzZsyfPx92u12WrqGhAV9//TVuuOEGnDx50if1Pn78OF5++WWZs0B8fDxyc3Nx7bXXytIacQAR7O8ECgoK3KZ/8MEHxe2TJ0/ixIkT4n6gpjcBnQIaY6wbY+w/jLHdjDE7Y4wzxmx6C2GMZTHGljDGShljDYyx3xhjMxVpshljLzHGtjvT1TPG8hljzzPGYrXyJgiCIIjzmT//+c8IDQ0V91evXo1u3brhyiuvRLdu3bBy5Uq31z///POyqch77rkH2dnZuPLKKzFhwgQMHjwYcXFxuOqqq/Dxxx+LHp9tpaKiAvfffz86d+6MLl264IorrsDkyZNx6aWXujgXuPMaVdKzZ0/Z/uTJkzFx4kRMmTIFDz/8sEv6ESNGYNiwYS7Hc3NzRW/WQKDXSaAvgFneFMAYSwOwEUCm5HB/AG8zxtI45884jw0D8IDi8p7Ov/GMsVzOeZM3dSAIgiCIc5WePXtiwYIFuP3220UNa0FBgag5uvXWW/Huu+9qXj9q1CgsWbIEt99+u7jG5YkTJ2SaJCnu7Mq85ciRI5rOB2PHjnUR2Nxxyy234NVXXxUFydLSUixfvhwANL0xH3zwQUyZMkV2LJDaM0D/FGcBgGcBTATgOSSxnLloFc7+CCAdwBbn/lOMsSxJ2u8BjAMQBWAQgGPO4/0BTAJBEARBEC7MnDkTa9asweWXXw6r1YrIyEjk5ubinXfewTvvvOPx+qlTp2Lfvn146qmnMHz4cCQkJMBsNiMiIgJdunTBxIkT8cILL+Dw4cMuNm/e0r17d7z77ruYNWsWBg0ahIyMDISFhSE0NBQZGRkYN24cFi5ciBUrVhgSCgcMGIBvv/0WY8aMQVxcnC6btMmTJ6Nz587ifkxMDKZOnerV7/IVzKg9A2NsHYBLAbRwzt1q4BhjJgAVAGIB5HPOezuP3wBA8KX9C+d8HmMsmnN+RnH9XwC86Nx9jHP+nLvycnJy+Pbt2w39HoIgiPZASUkJFixYgKSkJNxzzz2Brs5ZJz8/39A0F0EYoa6uDp06dUJZWRkAR9Db1157zau8jLyrjLEdnPMctXP+joPWFQ7hDAD2S45LtwcBgFI4cyJd8Mu9lR9BEARBEIROqqur8dZbb6G+vh5ffvmlKJxZLBbcf//9Aa6d/wU06YJY1RrbKWoXMsaSAMx27lYA+MK3VSMIgiAI4nyloqICDz30kMvxvLw8dO3aNQA1khOolQSkE8Iuc6yMsTgA38Bhr2YDMJ1zXq1M50x7B4A7ACArK0stCUEQBEEQhCZWqxUXXHAB7r33XnGt0EDjbwGtTLIdI9mWLglfKr2AMRYPYBWAIXAIZzdxzr+FBpzztwC8BThs0NpaYYIgCIIgzn2ys7ODOq6gvwPVHgJQ5dzuITku3f5F2FAIZ00ApnDOP/ZzHQmCIAiCIIIKvYFqLYyxJKddmEVyPMn5F+YMNMudf3kAwDm3o9VbsxdjbLozLpoQ76wZwMfOvOIBrIZDOGsAcA3n/H8++I0EQRDtHlpJgCDOL/Rq0C6CYyqyFMAI5zGz5Ji7lUSfQqsH5hIAhQCEdSXmcs6FSHiTAAx2bocD+Foi8HHG2CKddSUIgiAIgmjX+H0tTs55ERxC3VIA5QAaAewEMEuyigBBEARBuIW0h0Sw48t3VJeTAOd8HeSel1qopuGcHwcw3UMZiwAs0lMfgiAI4vzCbDajublZtuYkQQQbzc3NPlsKy+8aNIIgCIJoK1arFdXVqtGWCCJoqK6uhtVq9ZxQBySgEQRBEEFPQkICKisrUVZWhqamJpruJIIGzjmamppQVlaGyspKJCQk+CTfQAWqJQiCILzgfBVMwsLCkJWVhYqKChw9ehQtLS2BrhJBiJjNZlitVmRlZSEsLMwneZKARhAEQbQLwsLCkJ6ejvT09EBXhSD8Dk1xEgRBtAPOV80ZQZyvkIBGEARBEAQRZJCARhAEQRAEEWSQgEYQBEEQBBFkkIBGEATRjiBbNII4PyAvToI4Rzlz5gxaWloQGRkJi8US6OoQBEEQBiABjSDOUV588UUAQEZGBu64444A14ZoK6Q5I4jzC5riJIhznFOnTgW6CgRBEIRBSEAjCIIgCIIIMkhAIwiCaEfQVCdBnB+QgEYQBEEQBBFkkIBGEARBEAQRZJCARhAEQRAEEWSQgEYQBNEOINszgji/IAGNIAiiHUGCGkGcH5CARhAEQRAEEWSQgEYQBEEQBBFkkIBGEARBEAQRZJCARhAEQRAEEWToEtAYY90YY/9hjO1mjNkZY5wxZtNbCGMsizG2hDFWyhhrYIz9xhibqZF2pvN8gzP9EsZYR71lEQRBnIuQc4D/KCoqQl5eHlasWBHoqhCEiF4NWl8AswD0BsCMFMAYSwOwEcB0AEkAwgD0B/A2Y+xxRdonALztPB/mTD8dwEZnPgRBqLB+/Xq8++674j515trs27cPzzzzDJqamgJdFa+gZwvY7XbY7Xaf5bdlyxYAwLZt23yWJ0G0Fb0CWgGAZwFMBLDVYBlzAWQ6t/8IIB3AFuf+U4yxLABgjHUC8Dfn8S3OdH907ncAkGewXII4b1i7di2OHTsm7ge6E6+trcUrr7yCI0eOnNVym5qasGDBApw4cUIzzZo1a9Dc3IyKioqzWDPCl/z973/HRx99FOhqEIRf0SWgcc63cc4f55wvB1CvN3PGmAnAjc7dfM75Es55EYB5zmMWAFOc21Oc+wAwj3NexDlfAiDfeWyqM7+AUVdXh82bN2P37t1tzqulpQUHDx7E8ePHfVAzQoujR4+ipaUl0NXwyJEjR/DDDz8Euho+46uvvkJFRQUWL16Mw4cPn7VyCwsLUVJSgu+++04zjcnkaEakQmxFRQXOnDkj7h85ckTUqhDByb59+3yWV6AHNAShhr8Fnq4AYp3b+yXHpduDnP8Ha5wXtmMBdPZp7QxSVVWFb7/9Fh9//DEaGhralNeGDRuwZMkSvPPOO+fFSL6lpQWbNm1CcXExnn/+eZw+fdrvZRYUFGDRokVYs2YNAId2pbi4GKtXr4bNptuEUpOWlha0tLSoNu4lJSW6Gv36+nrs27cPixcvxvfffy+73tMUTlNTk+53Jy8vDwcOHNCVFnB0WHl5ecjLyxOPrV27FuvXr9d1vXT68L333sPGjRuxZ88elJaW6rp+//79qK2t1V1fJYwxHDx4UPU5M+aw0pDe31deeQUvvfQSAMdAbPHixfjmm2+8Lp8IPsrKymRCuF6OHTuGuro6FBUV+aFW+rHb7Th+/Diam5sDWg/i7OFvAS1Jsl2tsZ3iRdqAIDTsAET1+pEjR1Q1NBUVFfjmm29w8OBB1bzKysrE7cbGRgCOjqG6ulo1/e7du2XXuKOmpgZr1qzB9u3bdaU3SmlpKaqqqtymefPNN7FhwwZxf8uWLVi5ciVef/11NDQ04MMPPwQA/P7776KQYbfb0dLSgrq6OmzdurXNo1qhMS4rK8O8efPw7LPP4vXXX8ePP/6oamvCOZc1gM3NzS73nHOOw4cPw2634+mnn8bTTz+NlStXgnOObdu2oa6uDocOHcKCBQvwyy+/4Pjx4/j111/x66+/yvIpLy/H8uXLsWzZMnzwwQeyc0VFRViwYIFHYeiDDz7AK6+84nL8hx9+wI4dO1yOv//+++Cce+ykdu3ahf/7v/9zOb5+/XqsXbtW3C8uLsaSJUtkglRjYyPy8vJcpja/++47LFu2DPPnz5cJlVu2bEFeXp4sj127dmHp0qV44YUXUFpaiurqapw+fVqsd35+vuYUpvDOFBQUYMmSJVi9erVLGuE7Vr5fnHO89957+Oc//ykeW7p0qaqWu6SkBPPmzXPbWdpsNpkQuGzZMixevBh5eXma7QLnHE1NTW6F8/beQVdVVeGdd95BXV3dWS33tddew4svvmjomkOHDuHdd9/FP//5T7zxxhvi8UWLFuGzzz7zdRXdsm7dOrzzzjtYsGDBWS2XCBwhASpX6mjgqRd2m5YxdgeAOwAgKyur7TVzVxGJgHbkyBEUFBRg8eLFGDFiBMaOHStLu3DhQtTW1oodkBKz2eySr9AxPP7447Db7XjuuedwwQUXYNq0afj4448BQJZXc3Mz1q5di1GjRiE0NFQ8vmDBAtTXO2aiY2Ji0KNHD/Gc3W4H51xWvl6Ki4thsVgwf/58l7oAjpHmu+++i3vuuQeFhYUoLCzEJZdcAgA4deqULK2ggfz0008REhKCJ554An//+99laZKTk9G5s6vStLq6Gi+//DJmzZqF4uJiMMYwcOBAvPbaa4iPj8eAAQNwwQUXyDpgpeCrpllZtWoVNm7cKP62Z555BgBwzTXXICMjA0lJSdi7dy+WLVuG8ePHi9dt3rwZAwYMwIoVK7B//3507doVgEPQ+vLLL8V0vXr1QlhYGADg448/1hyRC3Vdv349LrvsMhw+fBjvvfceAKBPnz64/vrr8eGHH4pCkFLQkGritH7jnDlzkJiYqJrmm2++8aghlj775cuXY9KkSTh8+DBKSkpU6ySlrq4OCQkJYlmAo/O56qqrAACffPKJmFZ41wRuvPFGcXCk9l0J5QqDpvLycpc0wvd28uRJMMaQmZkpnlNOx+7fvx9FRUUYOHAgevTogQ4dOoBzLnaS3333nVhvzjm2b9+Ofv36ITw8HP/4xz/Qs2dPDBs2DImJidizZ4+Y75IlS1zqzznHRx99hL179yI5ORmzZ88WzzU0NODzzz8H4NC6trS0ePUNu6OmpgYFBQXo2bOnoeuqq6sxb948XHvttejfv7/H9Bs3bsTx48exc+dODBs2zHA9hXcMcLwD6enpuP3228Wpa2+Qvq8//fQTLrroIgCu7YbA0aNHAQDXXnut12UaRXg3Kysr0djYiOeeew4AMGvWLHTo0MEvZdpsNtTV1SEmJsYv+fuChoYGPP/885g+fTq6d+8uHrfZbNi8eTOGDRuGkJBAiTptw9+1lqofpE/YKtku9SKtCOf8LQBvAUBOTo5fDQmUDYAw6pc2GMpzathsNvz222+yY8XFxeJ2U1OTqCHYt2+faicDANu3b8fGjRsREhKC0aNHi8cF4QyAy1TiRx99hH379iEvLw/l5eXYuHEj/vCHP8BsNosj9/DwcACOjjQ0NBQhISE4dOgQ/vvf/8ryEkb5wn35/fffAbh2coBDK6J2rXA/1NC6hwcOHIDdbsfmzZuxc+dOAMCAAQNQVlaGsrIyHDhwALm5uejSpQsAuWAtIGgtAYfdktVq1dQ4rl+/HpWVlbj44osRFRUFAC5Ti4JAUFdXJzb2ynKlmlZ3Aoz0un/9618ybeXu3btx/fXXY+/eveIx6b2U/i41hGnOiooK2Gw2REREiI1vY2Mjvv76a1XNhtQBQUl+fj4YY9izZw/69OnjtnwA2LFjBz788EOZAKIXo4bhBw4cQF5eHu666y6kpTkcwYX7++233wJQF/SkmEwm/PDDD/jhhx+Ql5eHrVtb/aT27t2LPXv2YMSIEcjMzMSKFSuwceNGdOrUSTy/d+9eXR3cvHnzUFNTAwCyqeDy8nKsXr1a1s74Q0BbvHgxysrK8OSTT6Kmpgbbtm3DxRdfjIiICJe0BQUFKC4ulg1APvvsM10CmvDue6shV2qQCgsLUVlZKRtw2O121NTUIDIyEhaLRZmFW1atWoVVq1YBACZNmiQ7N3/+fNn0fWlpKZKTkw3l39LSgqeffhpJSUmYPXu2+D7u3LkT1dXVotZXTYAXkGoC9+/f7yKgffvtt6ivr8fkyZMN1U1als1mEwepM2bMQHZ2tmb6mpoarF27Fn/4wx9QUFCAd999F1arFQ888ADWrFmDAwcO4K677gJjDLW1taiurkZ6erpXdVMiDKrff/992T3bsmULVq9eDcaYKHC3N/wtoB0CUAWH/VgPyXHp9i/O/z8DuEly/ldF2ioAZ9clTIGyw1Xr+FeuXInIyEjZsZ9++gndu3dHSopjhnb//v2y8z/++KNMgHn99ddx+eWXi/uvvvqq2/pItR1KOyNB+KmpqUFpaanMsPaLL77AiRMnMGDAAGRlZWH+/PmoqqrCrFmzEBUVhX//+9/Izs7G0KFDZQKkwOLFiwEAt956K1paWkQB5+uvv5alUwpngGNkKoxCAfeN9bFjx/Dpp59i4sSJ6N69uyh0Su+j8vqamhrk5+dDC7vdjv379yM9PR1vvvkmAMgacumHXllZCcDxnKTXu8sbgIuRuTCiEwQDLaTvlaepZEA+XS6MqrUQOv59+/aJz+umm25C9+7d8csvv7gMHACHgCAN4aE2PSxoh6SDAy1++cXxyatNo7p7ZkoEIcVut+PTTz/FkSNHNDuRN954A0OGDMGYMWNw8uRJ2Tnh+WohHZjt3r1bZpsmCFSrVq0SNaeVlZUueWppYqQIeQnk5eXhL3/5i+r3r2ZWsW3bNnTs2FEURH/99Vd88cUXuPPOO5GUlITPPvsMw4YNkwmPu3btwqRJk2CxWMQ62+12vPzyywAc78tNN93kUtZ//vMfj79HC6mAK2X//v2Ij493EXhaWlrE+GSCtlLJsWPHcPLkSWRkZCA5ORlr164VTSyUgo7SthLQLywqbSj12iIL5T388MPie19WVobKykokJCTgxIkTqlOmZWVleO211wAAGRkZ4nHpNLeaoL5582YAwJgxYxATE4P6+nrs378fhYWF4jnlPRBsWtPS0vDll1+K3ynguL/Ct9XU1ISDBw/CYrGIGqtVq1Zh586d6Ny5M3766ScAjvd57ty5Yh61tbWIjo7GW2+9haqqKgwdOhTjx4/HmjVrsG/fPlx++eXIyspCeHg4Dh48CMaY+E25Q6stFp6NL+yNA4UuAY0xZkGrsb9FclywG6uBIyyGIEDN5Zzncc7tjLGP4JiC7MUYmw5gDYAHnOmaAXzs3P4YwHPO/B9gjP0AYAyAXs7zH3LOfRf4xgu0BDTpx71p0yaX64QR2axZs/D222+7nFcKMGfOnMEXX3yhWQ+bzYbvv/9eHJVv3boVWVlZ6Nu3L95//31Z2kOHDiEtLU2cIhMQbF2E+s2cOVMUBqR1PHr0qEyQkiJoVcrLyzWFSHfaiUWLFsnqo6SkpAT19fWicKD8bdLGUXl9VVUVCgsLAah7exUXF4sjLwEjtj3u4iVpNfYbN24UG0df8vrrrxu+RqotXLp0qYumQIqyE3IXzLOtjaEnYUnK008/jZtvvhlLliwRj0mnEZXs2LFD1Tbv3//+t9typNpSwdRAjUOHDrnNR8nXX3+NxsZGDB06FAUFBapptGztdu7ciW+++QaPPvqoOG0uPBfhmxPakPfeew85OTnIz89Hfn6+qD0X7EATExNx2WWXie2ZdFBQWVmJbdu2oaqqSjZo9AVVVVWor68XNXRLly4F4NDWrFy5EmPGjEG3bt1w4MAB/PzzzwCAbt26qeYl1eTl5eXp8rQvKirCTz/9hIqKCs3774mFCxdi2LBhuPDCC0V70OjoaNx9992IjIwE51w2UFNqp4W2Qs15Ji8vT/ZdKs1EBNxN7e7evRuDBw/GwoULXexp33//fUyZMkV8fz7//HPk5+fjkUcekQlnUqQCo1BHoLUvtNlsmqYbL774IvLy8sT3a8uWLRg/frwoSC9duhTdu3fH9OnTxW/ak3Yb0G5vlTM8nrDZbEE3Faq3NhcBWKs4ZkbrlOOtANZpXPsUgKvgiIW2RHFuLuf8BABwzo8zxv4O4GkAQwEUStIVIAjioCkFNOElstls+PLLLzFixAi316sJZ97wr3/9y2X675NPPlH9qA4dOqTacfzyyy+iVsxdzCg9+MJYVq1jF6aV9KDU3Khp/KQY7Uw9ITSwTU1NmmE99AhnnHOPo3l/hAT4+eefNW2PjGhL2ho2xuhvkwpn7Q1Bk6SmtRRYtmyZ6nHBM/n06dMEQ1DOAAAgAElEQVRITU11W059fb2LkC3VcgvT4kJHJu2AS0tLRcHP1wLa5s2bsXnzZpdO+MMPP0RDQ4Nop6fXNECgrq7OxQRBzTHmf//7nziIawvC75CWtWTJEkyfPh1lZWUyjblycCME3JUKmMrznmCMoaqqCrGxDh2K1AFlzZo1WLlypep1Bw4cwJYtW1BWVobc3FxRe63Wfgn3XctRTdDiGXX8UJosnDx5UmamsW7dOqxbtw5PPvmki6awvLwcn3/+uYtGXEAqoJWXl2Pt2rXYtWsXJkyYgJycHJe8Xn31Vd12lGcLv4uLnPMixtgIOLRj4wBEA9gH4BXO+UJF2n8wxgoB/BnABQDOAFgJ4FFn/LSAojalCTg0SceOHRNHef6kpKRE0zbLiNChbBDaEivM29GnFKHD8RalhtCXUcb1INislJaWyjwdlZhMJo/To8KIVgu9oS6McOLEiTYL6m1h27ZtmtNXhCvC97p69WqMGDFCnLYEHJpgYZpJQNl2SQUd4ZxW+6bEXfyxr776ChMnTgTg6GzffvttjB49GiNHjtSVN+CqsZVqLfW8o1IvXOGahQtlXQ127NihSzjTsv/1xKlTp/DCCy/g6quvlh1X2ucKtl5a6GnHfvjhB1VvZcCzRltwKBJseQGoxhBct24dSktLYbVaZcdXrVqFgQMHiponoR3Ui9Kkob6+XjYjIMxy2Gw2FwHtww8/dNE8cs5dZraqq6tlMzzLly9Hp06dYLFYsGzZMkydOlUc0O/Zs6f9CWic83XQt8STahrO+XE4lmzSU9ZCAAs9JgwAehswf6Kl5m4rgZ6nb2tQUDVHjbOJr0IGNDQ0aDa2AuvWrfNJWcHGokWLNKfTCTmCgHbgwAEcOHAAV1xxhXhu48aNLu+I1O6rsLBQJigYCSTc2Njo9lvbsWMHxo8fj5CQEDG0zPfff4+RI0eCc25Yc62cqvTGROCdd95xOfbVV1/pulZqd+oNWpoxAU8acz0DZ18vWaal0VWbNv7pp5/w008/Yfjw4bry1jNlKXVsU96bxsZG2Gw2REVFqU4LFxYWirZ6WrbAgEOQPHz4MGw2G+bNmyd6E+/duxcvv/wy7rvvPl2/x98E14RrkBMMAlpbgne6o73HVmoveBoRv/DCC2epJsEHCWfeI9VceOrUBacYgeLiYl1Lcr399tua00lS/vGPf+COO+6QHcvLy0NaWppqO5OXl4cLL7xQNS93Nn96CeZVAmpqatx643pyKAoW/N0vFRYWwmQy4ZNPPkF1dbWmoPfWW2/hvvvuQ3h4uFuPdqWjnnT/9OnTqKioQGRkpBjRIFCQgGaAYBDQjKqQ9aJmPE0QRPvDm/Ab69ev9xiiRY9wJlBQUOAiGBUVFSEpKUk1vZZn57nOkiVLxJiA7RnpFKk/kDqUeULwQDaC0mZRcPh46qmnAtrvB3RtSyJ4cGc3RRBE+8GbgK3+0F6qaa6CWZsVKPSEYCHk6F1Vp61oebOeLUhAM0Cg7bQIgiA80ZaI+r5CKxRLW9cwPhehfsU4Uk9jfxJo2+bAf8ntiLi4uEBXgSAIDdSWBTsfCQZTDACqXu3+slUiiHMREtAMYDKZcP311we6GgRBqNCrVy9dS02d65yt6R+CONdpS/gpX0ACmkECNTrt3bt3QMr1Nx07dgx0Fdot56JG9957723T9aGhoT6qSfvlbMRjJIjzgUDbB5KAZpBACWjBMm3ha+Lj4wNdhaBnzJgxqsfHjh1r6LivkHqdqS1Efc011+DGG2/Efffdh7/85S+YOnWq7rzb8j5wzl1++8yZM73OT4rWKgsEQZy7BNqphQQ0PxIVFaUr3Z/+9CePaaTrmwmRuv1B3759/Za3GkY/AOlCyn/+859l5wYPHixum81m3HjjjYby/tOf/oRZs2YZuuZsMHToUIwaNQrXXXedx7Q9evRQDRo5dOhQXWVpCYM9evQQt2+99VY8/PDDePjhh13S5eXlYeDAgejVqxfi4uJgtVrFwYWwsLKUCRMm6KqXlOuuu04zlERERASefPJJXHnllZg5c2abtYzjxo3DjBkzMHXqVJd1IIXglgK33XZbm8oiiGBEuXrA+QRNcbYz1DQGWsyYMUPcdqfVSE5OFhc+1+qwUlJSMGjQINxyyy0yQQTwrVA1btw4j2kuu+wyAI56S9cfzcrKckmbkpIi23/wwQdxxRVXoEuXLgCMx2ySahKV2pauXbsCcCz+/Oijj6JXr17iuYsvvthtvpMmTUJqaio6dOiAa6+9VhRIbrnlFkP18xV33nmnuG02mzFq1Cj069dPloYx5nJs9OjRLtpWk8mE8ePH4+abb8bkyZMxefJkl/KmTJmCxx9/XHOZE+n9s1gsiIiIEBe59kSnTp0QFxeHUaNGiRHv77zzTjzxxBPIycnBnDlz3F4/YcIEmWciYwy33367uD9kyBDxdwKO+zVs2DB07NgRVqsVubm5bvMX3mcp48aNQ15eHoYPH47s7GwAcBH4R40aJdtXe/+NkpeXJ5ZHEEZQtgW+oEuXLi59XmZmpmpaT0vUtUeEVQkCBQWqNYggWEiZNm0aPvjgA5fjycnJYsTj0tJSlzXOwsPDkZGRAZPJhAceeAAAXNaHu+SSS7BhwwaYTCZMmjRJtU5XXnkl7HY79uzZ481PkuFJAJ0zZw4SExMxZMgQhIaGwmw2Izw8HD179kRMTAyef/55AA7bshMnTuDSSy9Fnz59sHz5cvTu3RvR0dG46KKLMGjQIBw6dMhlrbupU6fiww8/dCm3V69eyM/PB2MMnTp1wrFjx1wEkbS0NJcI048++ihWr16NkSNHul22RSrk9u/fXyao9OjRwyXy9H333QeTyYTQ0FDxNysZNmyY5tI0c+bMka0Pl5eXJy4MPHr0aNnITUuItVgsmDRpEn7//XfxmFJold4PqQZowIAB+OCDD7Bv3z5069ZN/P2xsbG47rrrkJ2djebmZjFgY1ZWFubMmYOQkBBZdG3hGURHR2PQoEGq9QwPDxeXTsnIyEDv3r1l9UxMTJSlHz16NDZt2oT6+noAQE5ODkpLS2VLtqSlpYnbwr0S1gNUcsEFF2Dbtm0ux8ePH4+srCykp6fj0ksvVb1WisViQb9+/dDY2Ijc3FzZfZg2bZpY1+3bt3vMyx033HCDy3qShIOePXti7969ga6GWzIzM8UBhJ6ljbSIjo5WXeRdi6FDh8raAl+QkZGBqqoq2bHhw4fjk08+kR3Lzc3FVVdd1abf6w0TJ07UvWyXN0RHR/stbz2QgGYQ6UjebDbjkUcegcViwWOPPYY33njDJSKxQHJyMh599FE899xz4rG//vWvLjGL0tPTATg6gxkzZiAiIgIbNmzAwIEDZemUH4K7qcL+/ftrRnqeNGkS+vfvj6effhpAayeXlJQkeoPdeeedaGpqQkxMjNixSl9ctYWQb731Vhw4cEDURCk1g5GRkejXrx82bNgAwPGBX3HFFZpG3ldffTXy8/Nx4YUXom/fvi6NBqAuXIaFhYmLcN97772wWCz46quvXBZ81urcAeCmm25CfX091qxZI3a+drtdnD677rrrYDKZ8PHHH6N///4YNGgQysrKkJubiyuvvBKAY6WGn3/+WVxYPjExEZdffrls3c2RI0fCarVi4MCBYrwo4XqBGTNm4ODBg/jxxx+RmpqKkJAQTJ8+He+//z4SEhLEUezgwYM9GosLQoUSrZG4UpACHJq177//Hvfff78ubShjTNXOrG/fvuJodeTIkRg5ciR++OEH8f0ZN26cKKAJI/h+/frh999/R2xsLADtqZjOnTsjJycHl1xyCWJjY/HJJ59g165duqd9pSinma1WK2pqasQ6TZgwAXFxcZrrqU6YMAHLly93W0ZkZCTy8vJQVVWFf/3rXx7r5OtOasyYMeCcIyIi4v+zd97xbVXn//8cyZJseTveSTzi7D2cAZkk0BZKKZtCSwul0ELgW1oo/ZUORgv9lu5B+4WWtpRCv3xbWqAtpSMhYWTv4ZDETmwn8YhjO96WNc7vD+leXUl3SbqSrp3n/Xr5ZUn33HOfu855znOe5zmK+cziIT09HcPDw8jJyZF1wrZYLIpLol111VVxKWgPPfQQfvWrX+Gaa66JWEBdjcsvvxz/+Mc/dJXV4y/86KOP4ujRo7IDe8D/vM+bNw/vvfcerFYr3n77bdk6fD4fNmzYgJKSEowfPx6XXnopent7da/McM0118DpdOLFF19UPJebb745JO+YXMBaqny1Er1EYXNzc0zthFGQghYDmZmZGBgYQElJiagU2O12rF+/Hg0NDaiurpZdNsXhcKC8vBwtLS248cYbFRNKPvroo+Cciy+6nlFJWVkZjhw5AsCvUOzfvx8LFixAdnY28vPzMW/ePLzwwguw2+0YGRmB3W7H9ddfL3aAa9euRXt7O6xWq3g8r9eL/v5+sQPUw7Rp03D06FFYLBZMmzZNs/zSpUvR39+PtWvXRihnn/rUp9DX14fe3l5kZGSEXAdh6rS4uFhMJqg15SYoBtOnT49Q0LQa1YyMDFx55ZXo7OxER0dHiG+ToNBIUzyE5+RatGgRFi1ahK6uLrFRWbFiRUhHbrFYxOm6zMxM2fteVVWFqqoqXHrppYrnB/g7squuukr1nIxAUKbi5frrr5etW8BisWD9+vU4c+aMeJ7XXXcdrrvuOni9XowfPz7CR0zAarWGDBCuueaamHzf5HjggQcifrv44ovR0dGB/fv3o6amJmSB8IULF4JzjlOnTkUMmsKnYnNzc/Hoo4+is7MTGzZsQF1dHcrKyiKs7MJzv2jRIhw5cgSDg4Pitvnz5+PDH/4wnnjiCQDAggULQrKjl5eXY926dXjhhRfE31auXCl+FhQ0od0SEJQswO97N378eHGQp8WECRNQX1+Pa665Bs8//3zE9ssuuwwzZ86MUE6F92HSpEkhC7wLbY4eMjIyRN/V9evX47nnntOVPHf8+PEoKSlBe3s7AIjK5ezZs3Ho0CGx3Lhx40Ke5RUrVsDn82HLli1iPYKfp1L7aLfbMWfOHDidTlx22WXo6emJUNCEvsNisYhuA8LxAH8b9/LLL8Ptdkcou6tXr8bmzZsB+C3pgF8hfP/999HU1BQhT2FhIR555BE89thjqKqqgsViwZo1a7Bp0yaxTPialdJjaGGz2XQpWoKlW5hhcTqdEf1seno6Pvaxj4Fzjrq6OlnLuZSSkhKcO3dO0dfs8OHDKU2tRQpaDKxfvx6vvfZahC+P1WoVFR6lqcLbbrsNjDHNqcRoozZXrFiByZMng3OO8ePHhzh1A37/rFtuuQXFxcXw+XxIT0+H0+kUt8t1slarNSrlDPD76UTjWGm323H55ZfLbtOTePSzn/2s2ADp9Q9csGABpk+fjp6eHrS3t2P//v265Y3XJy183T1hajseEhnhW1xcHNPajomgqKgoJEhEQPre6cFqtSb0nCwWC66++moUFhZi0aJFSE9Px7Fjx8TObfHixVi4cCEuu+wyfP/73wegPggbN24cbrzxRtTV1aGiogLf+973APgVzXfeeQfTp0/HAw88gMzMTCxbtgxPP/00AH8nffXVVwMAvvCFLyAzMxPt7e3Yu3cvysrKcPHFF6O6ulp1GicjIwNDQ0O46667RBmXLl2KcePG4Y033gAQ6Xt35513oqWlBZMmTUJjYyPmzp2L7du3o66uDi0tLfjoRz+KlpYWVFdX4+6778YvfvGLkP2XLVuGvr4+RZk+8YlP4Ic//KFY5iMf+QgyMjKwb98+lJSU4MYbb4TH48HAwAB+97vfAfBPy+3ZsyfkXSkqKsKDDz6IxsZGdHV1oaGhAXPnzoXD4YDP58NLL70klrVYLLj77rvFazBjxgxs374d48ePx/XXX48XX3wRx48fxwc+8IGQwZswkFqzZg3effddrFq1StVaDwAPP/xwyPfc3FzceuuteOGFF3D11VcjMzNT1potZdKkSfjKV74CAHjmmWfQ2toqKpiXXHIJ6urq0NHRIZa/6KKLsHTpUmzfvh3//Oc/Q+oB/G3M+vXrRV/pNWvWYM2aNfD5fNi1a5fo3iBcH845ysrKRGXq7rvvxgsvvCBO2X74wx/G3//+dzgcDtx55504ceIEKisrQ8oIPPjgg3A6nbBYLCHKdG1trfh90aJFuPjii0OuS3V1taigfelLX8Lx48fx6quvwuFwYP369dixYwdqa2vhdDrR3NyM5uZmURG+44478Nxzz4kzWqmCFLQYcDqditNDWiQqT5PFYtF0aIymE4tHjniXmrn77rt1L7ERa2crOLmXlpaKo8hUIDR48SAo2lqNdizcc889htd5IcAYC7FEhafpsFqtyM7OjspnR5haku4jPLvC9K7g9+pyuUIUAWGgJQxmLBaL7FS2NPgC8EdKC1aKRx55BO3t7SgtLRV9R6WBULfddhucTieKi4vFKV/hmVyxYgUWL16M9vZ2ZGdni9ajkpIS8Xz27t0Lu90OxhhycnJw1VVX4fXXX4+Q0WKx4IEHHsDrr7+OPXv2ICsrC1dffTWuuOIK2fbA4XDggx/8oGwAVFpammh5XbJkifi71+sNsX6GT+HNnz8f27dv1zVLAPjb/bVr12qWU2qja2pqcO+992LcuHExD8iuuuoq0Xfzuuuui3DHsVgsWLZsGXJzc1FTUwOr1RryDMkNjiwWS8h1E2CMYfr06eJ0dUlJCe688060tbWJ18xisaC6uhoFBQUoLCwE4FfGBIVS7t2Qnvvq1avR09OD+vp6rFmzRtbF4aGHHkJraysyMzNRUlICwJ8/MicnJ2QWYvLkyeK7sWLFCkycOBGf+tSnxH1SBSlohOkoKSlJ+YsxmigvL8ett96KysrKVItCmASliDpB0Qjv5D/96U+ju7s7IkJPGq3LGBM7+HHjxkV0oFrRpw6HQzXSNTzIZOHChSgrK8MzzzyDu+66K6J8+DS+3OD3vvvui5h+04PVasWtt96qqECXlZWFbDPCin377bcrRkgCEJWYWGGMicpraWlpSKCNtIyRSdHvv/9+MdgnNzc3ZEZGcOcI57bbbpN1EQKCvsJLliyB1WpFQUEB1q9fr3h8p9MpRvcLMyxyiibgV47vuece0X3GDEvHkYJGEGMAoREiCDWE6czwaPSKigpD0oQYTbgiFC3xWpUvvfRSbNq0KWSqS+5du+KKK2C326N+D2+88UacPn0axcXFCRtgVVRUoLW1NcSlJVnk5OREPUvgcDgUBxhWqxUPP/yw5jSxHIWFhbjllltUBxLhaaFSDUt1plwjqa2t5fGGuBMEQYxlurq6kJeXF7crAjE68Hq96OrqUrQcEamFMbabc14rt40saARBEBcQ4YEqxNjGarWScjZKoSEUQRAEQRCEySAFjSAIgiAIwmSMKR80xlgHgMhMe8ZTCOBcEo5DRA/dG3ND98e80L0xN3R/zE2s96eScy47Bz2mFLRkwRjbpeTUR6QWujfmhu6PeaF7Y27o/pibRNwfmuIkCIIgCIIwGaSgEQRBEARBmAxS0GLj2VQLQChC98bc0P0xL3RvzA3dH3Nj+P0hHzSCIAiCIAiTQRY0giAIgiAIk0EKGkEQBEEQhMkgBY0gCIIgCMJkkIJGEARBEARhMkhBIwiCIAiCMBmkoBEEQRAEQZgMUtAIgiAIgiBMBiloBEEQBEEQJoMUNIIgCIIgCJNBChpBEARBEITJIAWNIAiCIAjCZJCCRhAEQRAEYTJIQSMIgiAIgjAZpKARBEEQBEGYDFLQCIIgCIIgTEZaqgUwksLCQl5VVZVqMQiCIAiCIDTZvXv3Oc55kdy2MaWgVVVVYdeuXakWgyAIgiAIQhPGWJPSNpriJAiCIAiCMBmkoBFElHDOwbkv1WIQBEEQYxhS0AgiSrZt/xA2vjUFnPNUi0IQBEGMUUhBI4goGRysBwCcaflDiiUZvXDuQ2fnO6TkRkFX1xb4fCOpFoMgiCRBChpBxEhPz+5UizBqOXX6eezbfxs6Ov6Z1OOeP78LPT17knpMI+jp3Y+9+25FQ8P3Ui0KQRBJYkxFcRIEMToYGjoFABh2tSb1uLv33AQAWLe2IanHjRf3SBcAYCBgvSUIYuxDFjSCiJUoZ+cam54hCwhhCjyeAezcdT36+4+lWhSCIBQgBY0gYoQjukjOhoan0Nj0iwRJQxD66T6/Db29e1Hf8FTEth07rkJd3UMpkIowAs598PncMe/v87kN9w0dGTmHDRtr0Nn5jqH1jnVIQSOIC4ChoVPkYD4K4NyHwcFGtQKGHIeBCRVGbOvrP4zWtlcMOQ6RfOrqvoS3Nk2PaV/OOd7aNB3Hjj9uqEy9vQcBAKdO/8bQesc65INGEDEzOiIQ3e5ebNm6BmVlN2DmjP9OtTiECo2NP8eJkz/E0qVvIitzSgKPpKygEanH5XKhq6sLfX198Hq9Ue07MnI5CvIvx5EjR2I4MkdB/jMYHECM+8vj9eahIP8ZMDgMrddMWK1WZGdno6CgAA6Hw5A6SUEzIV6vC2daXsLECZ8EY9ZUi5NwOPfiwMF7UDHx08jPX5pqccYcXm8/AKCri6YXzM75Hv9Sda7hlgQraAEozYnpcLlcaG5uRn5+PqqqqmCz2cAY094xQG+vBwCQkzMj6mNzztHX5415fyXcnj4MDaYhLS0LTme1YfWaBc453G43ent70dzcjIqKCkOUNJriNCGNjT/D8ePfQlvbq6kWJSm0tb2Gc+f+gz17b0m1KNExajo3/Y17smAmlMlM8HDLVhQdtC4C9UUch0g5XV1dyM/PR2FhIex2e1TKGZEaGGOw2+0oLCxEfn4+urq6DKmXFDQT4vb0AAA83sEUS5IcPAELz2iDOjciFnw+F3buug7nY8ijZ9QzRwqyeenr60NOTk6qxTCUC+lpy8nJQV9fnyF1kYJmIPv2fxq7dt9kWH3UiJqdUaagmdzi5/O5wHl0/jbGHNcNn8+TtOMNDDSgt3cfjh79RsQ28Z0Pu1fGtwXx1zfsavNH5nW9a4A8hIDX64XNZku1GESM2Gy2qP0GlSAFzUA6OzejJ+BDEh/m7kiJUYaZp0gkishbm2biwMF7ki7Cps2zsGXr6qQfV1ZJStq9klcEo6G3Zx8A4MyZF40QiJBA05rxk+yBl4CR944UNFNDL2ksnDv3Fnw+V6rFMB2jYUr23Ln/JP2YnHvhcrUBAIaGmtHX/37SZUg6zIgoztHXPvX1HcHQUHOqxSAU4JxjeLjFEEt6f//76O8f3RGjpKCZEZNPRZmZ8z27sf/AZ1BfH5mA03BU7tPZjn+iv/8oTp36Ldzu3sTLEobb3YNTp54H55ymyqNgy9ZLsGPHhxN8FLX3W+le6b+HPT370Nm5WackBrQ1o6i92rHzSmzZekmqxTAxqb2Xw8OnMTLSif4LYZCkA0qzYULERjMJZu6mpmfQ2PQsVq3cNSbM6m73eQBI+Sj5oGSq7nzPbsyZ/dOkHv/9o1/D2bNvIDt7FjIyJgZ+HT0d6YWB3PsWv2Vr1+7rAKivN6qWqFY3wiwpPVeEQXh9wwD8CZsJsqAllKGhZmzZuhYu19lUi6JIfcNT8HjOw+3uTrUohpKMTkPvMTwJsKBx7sXOXdfi3Lm3ZLcLi2v7p3pHl+J96PD92LCxBkNDpzXLejx92LrtMvT11SVBssQjKE5JU3risH6RZdb8DA2dgsvVkWoxRFKtzG/atAmMMfGvqqpKsay0HGMMjY2NSZNTgBS0BHL69O8xNNSEtvbXo9xT/SH2egcNH2GMBesZkOxOIzGjvIMH78WWrWtVy3g8fejt3Y/DdQ9o1GbS+6ryvLW3/xUAcObMS5rVdHdvw+DgCZw4+WPZ7V7vcEochdUQOqmYnlWjphOZJUQWYmzidp8X/StTi75n3aStVcogBc3EyDXgXu8QNm2eg/qG76RAIiIZnO34B4aGmjRKCa9uNEpi7J1xf/9RcO5Df/9RzbIeTx+Ghs5oiBKUxesdxuDgyZhlC1bpRV/fYQwMBKf2Nm2ehX37b4u7bkMRzl2tN4pQxIztuowZyFB3SkQJjQeighQ0M6IySvZ4/EldjV9lIIWNbUKcjJXr7O8/iv6B4wYcQp/cXd3vGm7FESyeXEGGUMtIfPe2s+tdbN9xBbZsvQTbd1whLnysxPbtV2DL1lW66z906D5s3XapzJbonouTjU9jx86rsG37B0Kmdbq7tyruYzbrmrbfqdHvyoXdY7rd3ejqei/VYhAipPRLIQVtlMG5v0NhzOj4DnO+GJ2db6P7/E7x++kzL2FY1WSvfR7bd1yB7ds/ZIB0+mlufjYh9Xq9/fB6h5QLSDp8JWVOi8HBEwD8EVYAMOxqUS2vtT1cLqMSnfb27BU/ezz6/P4am35uyLGjQ08UZ/xLPXm9Q2hqekYhZUH8edDGwoLr+/bfgb37PgmvdzjVohA6aWxsDPENW7NmDYaGhvD4449j+vTpSE9PR0lJCe6662E0Nmr7sZoZUtBGGUJjyy6QW7dv/+3Ys+djAACX6yyOHv069u//jI49zRMkAADDrnaDjx7ssE+elIsQlfg5pdC/sLf3IOobvqdaxjDxQirSd2+GhzWmYhOK6hxn1LWdO/cW3to0S/x+4uSPUN/wFNraXlM8dlw+aMwIJS+1DAQs6alYwYIwhp6eHqxcuRKPPPIIjh49CpfLhbNnz+Lll/+G1as/hn37/AmVfT6PqQIm9GCoGYYxtg7AlwDMBlAIfytzEsCrAJ7knCsuusgYqwqUlaOHc55npKyjg8gGXFTQDLagne/ZhePHn8TSJX+F1eo0tG6jEM59NEac6gnCOHTo88jMmqq3RvGT+lqmTHcH6nKdxc5d12Dhgt/D6azWKYc6O3ddC8CHmklfBGNKgwr5axO98iCxFsapoPf11WHHzo9g1qwfobTkI3HVJeXgofviUgbUzmv/gdCBiwQDqOwAACAASURBVNcz4P/vk7EOGZKoVlum0cNYOAdj6es7gszMGlgs9lSLooqggM2YMQPl5eXYsWOHuBbm+fO9uOmmG7Bz5xuw2TLg8YSukdnR0YHrr78+6TLrxeh5ssUAPhj224zA3wIAlxt8vJTg9Q6BMWtKHlyxcVfs7GLj+PEnMTTUiP7+95Gbu9DQuo3ivS0rAAA+3wi83kENRZLJ3qd9+z8tft60eR5WLH8XaWnZMUoU2aj7fCNiLrZQtO9X+9m/AZKMLAcO3oOOjn+iqmo9aiZ9UeXYMp2LjFLmdndiaOgMMjLGKxz/73C52nDq9AuYNjVyncjY4GH/lbYbgXQ6V6cSpKC8vh9YJ/Pw4ftDFDSPpy+O5wU4e/YNfWIZeV1kztGIPGhGR0zHe21jI3nTtBs21qCy4i5MnvzluOo5duyb6FPJkO8N+Clb07JCPuuDi4o9ADCL3ZB+LjNzMsrLboi7HiUefvhhPPHEEwCA5uZmXHTRYrS0+BvTY8fq8eqrr+OGG26M2G9wcBCvvPJKwuSKF6PnyfYBuAHAeABOAB8FIKy58yHGWIHOeqo550zyZyrr2abNs7E9gdnGhcbZ64v0LRoc9EeoMWaNqs6BgRPwSF68SEZPYkC3uwubNs/RKMWxafNs7NoVOjqSZlj3evux+e35aGn5U2yCyHR8b22agXffuyjid9ewDr+sMDo6/gkAaGx8OmJbS8vLOmthkHY+Pb17dOxjZGflr0s9LYwxHb1UYXj//a/h/Pno1sV1jZwTPw8MHAvZ1t9/FN3d27D57fno6Ph3fIKKRJ63oUqPOIiLY73NvkMx+y4CwNDQaYUBSyg9vfux+e35aD/7j5iPFRvJnf5vSpAv6oVMTk4Ovva1r4nfKyoqcMcdN4WU2bRpe7LFMgRDLWic8zfDfnqdMXYYgGCScRt5vFQiOE4nkuPHv4WKibcD8CsWOTnzcODg5wBAZbpInm3bL0Nubi1qFyl07KPQws8515w67Os/rFlPZ9dmlJf7FTnXyDkM9B9FQcFyQ2QUGBo21ln1ZKPEuV2mA1W0wKh0toZkl5cQqshwcM5RX/9tlJd/LOLI8oTKMTjYBLe7G7m58yNKulxtcNiLxe+9vXuxe89Nku1n4XAUR+wnPYY0X5TXGxzMDLvasH3HFeL37u5tKCq6TEFm/cgqY6Jfl46yOo7gr0rlfqo8D+1n/4FDh+7FrJk/RGnpVSrHUa5jy9bVSEvLw+pVu1Ul7QtEBnd3b0FJcfInWuJRQpPN1KlfV90uRFnn5MwJ+awHzn3o6wu2mXZ7EdLTS2OUNIjH0x9IpWP8da6pqUFGRkbIbzNnTg75fvp0q+y+lZWVqK8/DIvFFmEpNENu0IR5mjPGMhhjHwUgeK2+yDnvU9tHwg7GmJsx1sIY+w1jTH5OZswS+hC73T3Yt//TOHDgc4p7uN29aGj4Pk6e/Jli6oCeHmWLQrART/1DqZeOjn+Cc47mU7+JWK1BailrbPw53n//a+G7y7Jnzy3Yu++TEb93d++IyNof3TSU0dNB2lYJ/2FDLWgahWMVR5aBgXrxM+ccnZ2b0HzqOWzbHqrc6G0It25bKy5jFE5f3yHVaIOdu67RdQw5PO6ekO+GTT/KyqulJMdybJl9dFzzwcD9G1BMSaNPodf9rIbUmRyYgb54ZkOv0unx9Ef4ZhmPefuVwcET6A+zmJsFwxU0xlgWY4wDGIQ/OMAB4M8APq26YyhF8Fv3ygDcBmA7Y6zIYFFNx+HDD2DrtsiRuY/7DY8DIVa70Af+2PHH0dj0c5w4+UO0t8tFbWlh7BRnb+8BHK//b0PrDMft7sbg4AkcP/4tvPveRYoNUsOJ7+NMyx9UavJfy5bWP4lTyOF17dl7c4QTttCoDw+3oO7Il+HzjagcIXENlLzCwFW3n2x8Wjn/UwL6qlOnfhPFtKwgR+xBAuHoyaZ+ouH7UR4v9TSc+AHOn98Fd5gSCag/c8ElpdTQ98x2dm7GCdlI4ug5c+bFJOemU1bQTpz4Mbq7dyRRltQwOHgSg4ONqRYjZhoaGjA8HBoIc+RI6Dq0EyaUqVdiUgtqsnI1XAvgNxplBgB8Bf4IUCeAmQC2BLaNB7BebifG2F2MsV2MsV0dHaMrhDactvZX/VOnOh4WaeN7svFptLX9Rfzu1pkDSorgI7Rn78exYWMNvF6XYtmurvfw3pbVirmDPJ5+7Nx1DZqbf6lzFBcs09j0DPbtuz0KuYONudvdpWoZaG2VdwYVruWRI1LnXT0Kq1/u949+Ha2tf0KXWj4viVx6svEbRWQn7Zf5xIkfRFoKAzKePvNC2C6xNl7B/RpOfBcd56RTnkzhc3J4/+gjOH78SbRKEj53dr0tWzbSf848KVwaG5/G7j03yedzE3UPubp0WI60rEuSZ/rkyR9pSKqO9Hx7etSnQ/XS3b0D7763XMP3VvkcTzb+BHv23myILIQ+VHM6KtDb24snn3xS/N7QsA/PPRc6GFy9eqnC3qHvttc7jL6+Ovh85vDGMlxB45z3c84ZgEwAawCcCmy6hTG2SGW/Ds75f3POD3POhzjnRwA8KCmyWGG/ZznntZzz2qKi5BrZRka6EjLaa21TiiqRNCKSxvHEiR+ElPKFKVdSJamj4z8A/BFToRYffxn/4trA8PApcV+3+zzc7vPYsLEGra2v4Hj9kxgePq24PE9vXzDTfLQpBRoanlLsKLVR79Tqjjykv6ZAp9zU9Cw2bKxRKhT4oEfBCJY5dfp53XLoQ92CpqZgGbKiggL6pwKTr6CdOfN7NJ96DnoU8R07rwz7Rb+C1tj4P9iwsQYbNtagR5JI14/aFKcCivcylulS9W36rGz62L3nFry3ZbWusqfPvBjy3ePpF9ulaGg48V24XG3oV4l4FNA7HehvD6NP8zNafNyGhk5pF4qCwaHmEJ82IDGrd3zzm9/E7Nmzcdlll2HhwpU4cyaYd7KmphJXXnmJ7H7h/dPIyDlw7tWd6DrRJMyCxjkf5JxvBiDVNqYolWfyXu8auQRSyzvvLsbhui+k6OjKDXln5yYMDkrXcgxeupbW/wMAbH57PvYfuEvzKM2nfoW331mErm6/MfPU6Rc09gAQYnGI7ADd7l4MDBgRZBF6DYxsBHt6/bl11DLN+yPcgi+4x6s8Uk/uIu7K8ICzvkB39zYA/obJ8KStCeqU3G75xjNp11jHaQ272jDsakPDie+Kv+mJ/lQO1Ij93Dj8g6zQaazok8wODp4MufbukU7d+54/v11ciUKLs2f/HvJ989vzsGv3TQql4yPY7ehz8Th9+nd4+51axcFpX9/hkIGv1zscsJiPjih5oxUTj7snxALt9Q6iv/+IqjuIgJ4yALBw4WysWrUKhw8fxn/+8x/09gbzQubmZuPXv/4ObDZblJKbo702VEFjjP2MMXYZY6yYMZbOGFsOQOrVeyJQrpExxhljmyTbvskYe4oxNocxZmeMTQcgdQox5YJpevIanT71PM4GUibEQ+hUC0Nb2+uyI8vzPTuxddta2f2ko5murneklcseU3CMbznzsmbZ4Gav5HNkw7R7z40RjuLG4DOsk96z52OyIf99fcHRuNvdhRMnfyIe8/Dh+5UrlE69xqm4nD0bFiwtVx+XH9t4vYNob/9rUKyA7O+8uxTNzb/SdXy911iPBS0Wh3uPJ9LfCoCm47t0EfVE8957y/HeezFEAgfO4ezZf8hOzcUamLJ12wewddu6iOP4lbdunDu3Ef39x9Dbe0CmHh6o41Ls3PVR8ddoLNJynDu3UWKNUj+vvj719V9jR31N23A6OzcBgKzP1uBgE3bsvArH64PTbUeOfBnbd1yBkZGuuCUdS+iZQtTrCuJ0puNf//oXnnjiCUyfPh0Ohx2Fhfm48cYPY9Om/8X8+TPjFTdlGJ2o9hNQ8BUD8DrnXM3jMhPA5+FfiSCc9wFEJoMaJQy7WnDw4D1Yt1a+g+Cco6npfzTrkUZD9ffX4XDdF9Dbe5sOCeRTCYSWkB/hWZh/5NHVrX+9RGldw8NncK7zLVRMvEOMmFKOCosSxiDthLq6tsBu15tqL0hv3wG0tb0e8fvQYFNEwx0+3dXfV6fzKMaMhfr7j+HgIaVXTIYwpeXoUfUQfWPR1+kpRXFKlZHQ+6OkiKkraNu2f0CXPFrEGsXJET7dryzv2bNvgDErZs+S9+3y+dzYtSs49pVTmpnESuZ2d8pvA8f+A3ehp0cuP15knUNDzYoyR4Pb3Yv9B+5Ebs4C1NbGmIdQi6gGQvFbe4VrLKS2APwrtAChaVuUGBo6jXPn/gNAyV8qsSgpqSMjXbBanbBa0wH4nz23+zzs9sKUpKKQ849OS+N4+OGH8fDDD4dc/3BWrlyMnp4DyMmZg+HhFoyoWIHNMC1t9BTn0wB2AugE4AXQA2Ar/IqX1noKvw3sfziw3wiAegDfA3AR59wck8IJoKd3DxpOqK9XqMTAoLZVQE/OtpER+QALZgnV4X1yy8aEI3mw9x+4C/X13zasYY9A0kDUHXlQpaAyQ0PN8lPVehsfHeVCV4mM/cVXmlqJnegb2LojD+mzRqkmp9Xm9OkXsGv3jThz5g9h90de5uGhZC2MHNv9C0/TooXalHNr25/Dcvyp5FTTkFczgi8BHRXn/umrwaEmjZIGoOP9VBqgatHU9Cza2//mryPwvMtbmLWv4d69t+LY8W9qJHWOhujum5Jlenj4TMigemjoFFyutpj8Ao1Ari/RN+hPvcIVLUYnqv0qgK/qKFcl89s+APcaKU+q0dsRc18ca/PpMBUfOvz5GGr2NzKCSV9gYOA4sjKnRZTeu+82FBSsQFHhupB0FMJLv2//7QCYOAoDgC1bLoHP54pi/clwCSMbQulSTvHS0PAULBaHhhChVjzlcsGxUGvrHzFzRmwpSOobnor4Lfw583oH0dMbdEjXGgk2Nj2juM3t7sWx44+H/Obx9OFw3RexZLF6Ohe1Ti/03ilY0LgbPT27I6L6lEbtepISG0NsDX14h6ZXrT946D4MhinE+jpHPco3V0x6HeugUQ/btoclo02CtUJ+Wk3eF+94/bflKwl79uobvgMAKCm5EvsPfDZQJvJ66lG6Yom+9/ncGBg4BqezJqRtjQX9FiNf2P/kYsTC9gMD9TFFjCabZKXZuODwegf1W43iMRNHua/Vmhn7sSLwwet1wePpQ1fXO6iv/za2brs0pITQMA0NNYlrfQoMDTfDNdIe6gsXwOVqV46eFEm8eV27I9Qrg1GyKjeix+u/jQ0ba0KWwdq9+0Zs2bpKtcYGGaVPoDcQLBEOg0U7ilmlwfdHUAZri5YRybJMZmBwsBEbNtZoWMlCr8eIuxPvH/264nMuKKZnz76B/gG/P4543uHXVqYdEJRgj3dQQ3qtbiDyPspdf7e7R7djt9st+GTF/154PH3YsLEGp0//XrHM8HAL3to0PeJ3pUS1Un/M1ta/QA+CCwqTuZ7nVZKER8qiH4+nF5z7VKfqdKPj8FIlNzqdOrJyPX5o6ilSQuHcp5oeSoqccmZGP0FS0BLAyIh/rUi/P4E2iYo+k3sBSktjz6guIFhGOPdh9+4bsPntyKV3xLIxjnb0pH8YGKyHN+EZsI3BuHusnFJDr5O/lJbWP8r+3j9wXFXZ8HE33nl3MY4eU15UXY8FeXCgQdnpX4FTp36Ld95dmrrkmjI9k5BCQxqAEU74lOXQUDPOnHkpUKW+lC2Dgw2B3G36e0fVHGVc+9kMv4+Dg014591IP6m331mIA4IVSSfRKiU9PXvQ1fUeWltfETtvl8vvntF8SiHVJueag2U165FcgmXO3SEBFeelVl6Zc+ro+Jfq8cPx+dy6lY2ARFHVHwtudw/6+9+XKDexH9Pt7g7UFRw8yClN0hUOvN4heDz9qKwcj56eA+Lf3//+awBAX39dxBq60cnUCbNNgxodJEAA2Lb9g7K/nz37JpzOamRlRU4RJoKGhu9iypSHY3bKV2q0guZ6rjmtFKuCpkehaW7+VUxKidHoWpdVZe1Uj6cPZ8+qR/n6fG6cOPkjw335lKLjtm//EACgrPRa2e1CbqmzZ9/AjOlPypbR09gJaV+i4VxgGS+j1zfVS7jC4vO5gv6PMVvDfQCsEc+93P3u6PgX8vJC00JG+54J58DBdcgcer5q6TL05DAMb1c6Ozdj2CW/VqKUpqZnQqb4s079BkuX/A2WgJ+sNGn1+fO7Qqf5FZ9F4dyjm647cPDukO+7d98YUafgqwUAPMrcX8JMg/YamomeRVALMItdmfF6+wP/XbBanYGp2nqZksFjyG+XFo1XuUpt8mw5yIKWAILm+1AOHlpvqI+UH+UHqa+/LiJsvr39NZ2+BkzRGhBNZ+DzxTrPb44XRA+6FDQV6o58GUfe/7JqmebmXypH+nKOlpboFR09tLb9WXW72hp+eiKT4yFVueVaWv435B2SdtZy01t6aDjxQ7jd5yOUpS1bIxNsyk27nwlL7gpAUekZGDiBffs+FfjGkex3LbT9YNi3/9Nobv6l5n7h/pfCIIEFIs2lCtruPcG8ac2nfoOhkLyQUoQ0G8oKWqhyp8NzMDAY27J1jfibsFyfmdF6n/ROXytUHkJ4D2RcYIQyeno9r6Y7QHIhBc0ADh2+Hzt2XKWrrMvVhqamZwH4M2TvP/BZuEbOauylTHf3FtXt4Q+cx9OHAweVF12XoqRoDg01AgAaE9gBd4RND+tKkGtiwh2xz559E3WBpaWGh1s093cpRNkKHHn/K7ELN+pI/TSEYHlsPvUbdAYsegBULaVqNDX9AkePPaarrFxHKdexyOVo5Jxj2/bLQhTraBVdve2HMqEKmhx6Hdb7+4+CMSsAZQWio+NNvH9UPnZNOTGwlGiVB5lzSoICknzU79GIZMWFcFcUIbhNyIM34lb3KTV6hQMlhGdIV7aCJEAKmgG0t/81qgiy+obvYMPGKWhs+gXOnfsPTp78iWLZ6PwQ9KHXN07Lh6jDgOS7SpwOWw7p2LFHE3aseNDbuXV3bw35fvDQerS2/imKOpTvhfLSYGMV/7XYu++TCR0kqErAvWhtexXHj38r5PdYLWiA/k7B5xuJeTpHSG8h+UVbqQw7VrxWBn3WEn0KzY6dV0F4HqK1whw58hW4RvxLAkUkf44DuWdg3Dj1QJ1QuKaCOjjYhKEhqU9j6gct4UjT3rhc8kYIIT+cW8NB3+0+r7rdGILtcDxBSEbmTyMFLWX4cDaQqV7p4QWATZtnKiaX1eL8+d3Ys/fjMe0LGBPOPNbxePu1C2mhw+pyepRYEJPzzAQbQKUo00Tjcp3F0aMyARKMobt7exw168jZxd04Xv9ETLWH3x+/UpPsKc6gIqU0OOnu3iauYapel0cykPT/l0+6G4nU/1G6JJfMQSRf9KTUiSzTcOL7MgUjdgQAWCwW+DR0TY+nNzDDoSyPlsI6MtKlmtTVHKRO8eztPYjhGPpen88Hi8UY1YoUtJQSCIPXiGI7pnPqI5zI0bJ++voOKSz7QkgJt4xFi2vkHEaTv50Wx48rBQwYRzL8VbQ4eOge2ezwfX2HI6bn9cN0WVPlp/J0Lr8lo0DrOWa0VoGhoTNobPyFwlbJ/VMIUFDMQyZHmGznwnI3ytHdrbaoTSgDg/U4f36X7kW+lfLKydHTuz9ilsTrPYWRkfgVk/BF4jn3weMd9P/3DCi6sCQbtfQWelZg0IvPq26h9spYsEdc0VvSBgcHkZGREfV+clAUZwrRG2Kud0RoJKlbBP7CYsuWNcjOnpFqMQyj45z2guBxY4IlWJTo6zskm8hZP9ptQnjHCwCMWUOc5JWILKMnilM9fYgcSrn3WltfQWFhcE1QpdkBuXOUIy9vKYJWFh8OHvovXddhz96bddUP+P12d++5CVWVd2sXBqBXWR4ebsGuXdeirPRazJwZtOB1dr0Mm+0zSE/PivpQaor00PBpeNw9YBab3wcszmWaPJ4BMGYDY1Z4vYOw2XJjqkdtxQyvd1g1ECkaNHNayg78omtrOOc4f/48MjONyTdKCloUcM4jsqrHx9ixnBCx4fMNpUQBN5Lh4Vakp5f5vyRBeYpnqaxkEOsSOB0d/0RRUWzrhTJm0XXp336nVnZfNTg4hob1O2mfPPlTxW11Rx5CRkal7rqiwZ+u5u8JqRsA2tpew7BLO6BHrx+ioHj09h0K+d3tfhc9PRchLW0eHI5hAD2w2/NhsdhljiXMwvTC7e5VHfT7AnnGxNVndDwwar5YIyMdGBnpgNWaDq93GGlpM8WADSMZGenWLpRiOOcYGRlBZ2cnPB4P8vPzDamXFLQoGBpqxOnTv0u1GARhKt7bsgKXrDmCQ4f+S1cHFj/mVtBiXdcRiD6hqUBcKRA0B4o8KsX7hFpiXPhXFTEKzr04fPiLhtXX1vaaYpJs3c+2hsLb2PQMrNYM5OcpLYruRV/fT+AaWQO3+7MYHGwFY3Y4HMVBWYb9wQ0224gYCQm0wmYrkJ26TE9Pg8vVpuojGlpXNFgA+OBwsBAFTZAxfoyqJzbS0/WpSWlpacjNzUVxcbFhPmikoEUBY8ZernjzZxGEWejtPZCc6U3A9CkLUrWIdCzoSmLNOU6c/GHihYkBn8+lmGw5Fg7XGaPsqU01CkurLVkSau2TKlYcg3C53sCECV/Atu2fQ0ZGFebP3yDWvfGtKwEAs2b9CIcP3y/uV1V1L9obfxZxzHVrG/Dels+qTifOnPFd1B35ko6zC8VuL8LISAdKiq/E7Nk/Fn/fsPHKqOsyI+vWNmgXShAUJBAFciZmgiCSSzwWqmTgS0BqHEIBA5X1hgY9kZba+KebtaOZvR5/BLhakIZLTDbsV/jaz76BjW9NDh4rrAtvlFHOBLRkikU589frCcj2N9GSezqwhBkRH6SgRQX5jBGEHMn0C4s17UyyGE0WtNFONPkntThlmPuKRVeggrDaQf/AUcWpxb37PgnAPy3MORdTM4nodPT3+UbinAZXRiq7kDC75cz/JuRYFxqkoEWFuX1fCCJVeNzRLXg+lhlrCprZgzKMwmtETkP4LWjRrpm7c6f8mrdSTp36NayW0PQNegMSjh3/FpLRf7W1vQoA4BgbOTQzM6em9PjkgxYFZsi/RBBm5HDdA6kWwTSMNQWNiJ4dOz8aVfmhYW2Frq+/Tlx3VODgofW66u/tPZC0xONayYVHE5nO1J4LKWhRcWGMJAkiWoyyPowF5BJejm6o3YsGuTVQjUCwTsWCzzcMj6fXQGkuEOLMFRcvNMVJEARhIEamkTAFJk4MTOiDlu2LFVLQRg1GLoJKEAQxGjh9ZnSsA0soQymdYiW1fT4paFFBChpBEARBXBCk2ChDClpUkIJGEARBEBcCqY5gJgUtKkhBIwiCIIgLg9RmbiAFLQrIB40gCIIgLhBoinM0QQoaQSSKjIyKVItAEAQhQlOcowpS0AgiUaSlZadaBIIgCAmkoBEEcYFjtxeCmiOCIEwFTXGOHuLxQauZ9KCBklw4TJv2Tc0yy5b+OwmSEPFSVnqd4rbZs36cREkIIvkwZk+1CBcs6Y7ymPajKc5RRew3y+EoNlAOP4tr/2J4nWYjzZqpWSYzc1ISJCHiRW2NSmaxQe/7lZMz3yCJ4mP5xe+kWgRiFFFWenWqRbhgYZZYV7UkBW0UEXmz1q1t0LmvvkvtsJcgJ2eB4vZ5856TfAtdhmLd2oak+fGsXLEjKcdJ9VIbhBH4n33GrIbUxkzzTJhFDmDF8m2pFoHQgIJggOqq/0rRkeXf1cJxa9V345RmY9QQl7lT56Kr06Y9hoqJtyluLxy3RrXOaKxqU6d8Q3fZcOz2ceLn8rIbY65HkxQvVjvWmDjhtqQfc+0l76Oq6l5MmfI15ULRuA8wczRbTCLHpOovIDt7tmLZ9PTxiRYmsfUThjBv7q9SLcKYIiOjMr4KNN6bMTXFyRhbxxh7kzF2mjE2zBgbYozVMcaeZIxl6djfGSjbyBhzBf4/yRjLMFLOmEmCwyCHD1yn1i5nSXA6q7Fq5S5d+0+c+KmoZAsnL28pAMBmy4+rHjVYkscQY33auKrqbixb+m/Mn/fbpB2TMStqJn0BdnuBahn90wksoc+cfoLPZk7OHCxZ/JpiydpFf0RNzUNIS8tNiCTRWBWF9zbVMGZLtQhJhiMra1qqhdCF1ZqFiRM/nWoxNFm44MU4a4h8byor746zTuMwuvdbDOCDAMYDcABIBzADwFcA/FFtR8YYA/BaoGwlAHvg/1cAvBbYnmJCO5C0tBwA+nxiolE0uO7sxfKXRNp5Taq+HytWbNd97GgYV7Aq8IkjN3cRACA7e1bc9S6WdHTOzJq464sGp7M6qcdLFgsW/B5zZv8cdnshMjMnIT9fvZOumfQAcnLmJUm66KY//ZYr/c3B5JovY9rUx2OQSksOuQHSZNmyDkcJqio/i9zchcHf7CVRH1O5rUl+81hSfCXmzP55TPtmZk7Bgvm/i/g9lmuSCrKz58S2o0HW30T7YebnLUF11T3GV2xwN56eXmZofYC/7RMZY1Oc+wDcAL+C5gTwUQCCZ/CHGGPKQ2jgYwAuDXx+GkBh4D8AXAbgJoNljZsVy98DACxc8JJxlXIY+lBkZFTAYS80rD4pBeNWAAAKC9fBbi8CAGRlzYiprrS0PPFzpjPo9J+dNT2ibHr6RMV6Vq/ap+t4WZmpGclOqv5C0o61ZPHr4ufMzCkoLv6gZKtyQ7ls6T9RVXUP8vIWy25Xi8aMGWaJMKAxZkdZ2Q0A/MqAZIt6VQHLjDD1Xll5l6Zv5ooV22Pw4wrKoX8qJFgulsHMwgUvYdXKPZGSSDq+qVO+rlqHUT58VqsTxcUfjMn/zWJxwGbLi/g9J1fZ/zZZ6LHOlhRfEXW9HNywGYGiwssUt0mn02MdMHN4AUTnM1osc02itZI6HKVRlVdCrY/QQvoujakpTs75m5zzK7w4AwAAIABJREFUP3HOWzjnQ5zz1wEclhRxq+x+i+Tz45zzTgCPK2xPCeE3y2p1Bv47ZH+P6Rjco9+CpmM0Jsg8ZfLDUcsyZfJXVbfnZM/GurUNyMurRWXlXbBaM5Gft0S2bHXVfap1ORxF4ud4rp/eIIni4stlAzziObYeqqvvFT9nZc1M6LFstuB4KLJjiOyk09MnYN3aBmRmBqxAClP6M2c+haqq9RILavwwmc7AYrGLyrrDEbSsMI3nXrDGTZnyVfEeq71TFRPvgMNeGPIM6pJZKkcs7g8a5zFu3OqI36xWB2y2XEya9MWQ3zn3AvA///YEDcjCKS/3K8DRXLcVy7fAZstHTc2XwJhcZF38g9PCwktRXX1/HDVoK7ByFqzsLG1lSOvZDUcpsEBtQmnZ0n+J/pDR+D7a7UWYP+/XAADOfVHLKlW4J4y/FQAwZUpov1NacpVqHcXFl8NicShudzi0LWbVVfdh+cWbwn6Vv145OXNhtWahrPTakN9F6+4Ys6CJMMYyGGMfBSA8tS9yzvtUdhFs/z2c87MAEPjfE/g99UMrlUZ42tTHJN8iL6veh93nc6Gk+ApYLNpudwwMGRlV6oUCD1hFxR26ji9F7UUJJzdnHtasPhCiFAgIL6vAzBlPYfr0J8OuGcOC+b9DxcRIORcueBFWSbqNqVOCiuPyi9/VLaMUOUWurOwGwyIN9RDNsfRGP0lHoNL6w48l38Drt6zUTPoi5s//je7yWsiFwS9Y8DuIFieJvL29B6Euqy+wi+ScVRra8E5EQPv5t6Bm0pcAAAUFF2uUFQVR3Tpv7q9Ea2FpiXJahnDlzWYrQHnZjfp8cmTu/Yzp/629XxjSAYZev520tGysWrkL4wpWyD7/WtY/Pcyb+wwmVasPCNXR8R7IXMN5838d0dZFEl2Xe/FFbykcX60eJraXEyfcDgCy7bLcfgjcE869UbeF1dWfV91eWno1nM4q8fvEibdHlHE4SnDJmjrFOmw2dR/OdWsbMGmSnHIefO8mTPik+DktLQdrVu8X/TKDihoL7DWGLGgAwBjLYoxxAIMAXoXfF+3PALQ8DoVhX2/Y78J34xOJRY3yzZow4RPi5/CRYXXVfbqdgy3WDFitTsyZ/VPFMpmZU8TPWnnCtKxx8+b+UvxcOG5tiG9FefkNWuLKHjGcqVO/Dpsk6rOs7DqML78JEyZ8QjTVO+xFKChYLttZ5ucvw+TJ/0/8Lh0V+vNnRUdV1b0YPz7SIKs99WOs/0Q0YfexRAGGKmjhr7r2qy+N1E00mc7JIY3hlClfQ27OPMkvTHzuvd5+1QFPcBwVLKPfr1MKw/RpTyhvZRZUVX0O69Y2iMqcU+aeSu+zNABI7hwKCy/R56cTpnAyZsGMGd9WnNIK9feKrL+8/IaQQZAewmcOdO4VlELGgpaeXq5rcJpq5NoKBmDatEeVd+LcwFQzys8/Y8DsWT9CzaQvIS9vMdatbUBZ2bUKpUPrEer1W2SD22bP+ommTFJXGjnFJty/UHCLCZNesf6yshswb+4vQ/qCaLFas+CQHDd4H4WBYOCczeDyjuSl2bgWQKzD7bArGLaRsbsYY7sYY7s6OjpiPIQ+7PYi0RlejfCGd9Kk+1FQsEJzv5kzvofiog9FJZM4HaWExtRLYeFaXLTsP1i08GXMm/dLzJgRHElbLPFnvrZas8CYFRNkFCIAEkVJw69IYbs1ysY8M3MKaiZ9QfbcMrOmAlBevUB+SiZ2pM6owghXySJqs+VEXb9U3nDZ9cTcTJx4B6ZM+Zp6egyDUJLHGbgemc4aFBVeKlsm0veFB+qU/hTbSLi8/EaUFF+p24I5a9YPxM+La/+CvLylWFyrFN0pf86CH6dDxQFa3U8qtN7c3EUoKFiuUl4g8dYCadvILPLKyqKFL6Gy4i7DjllcfEVUvlC64tFULdDBc8wNy2kZ7bSh8vHVLWgORzGqqj4nnouSQhfeDgYVSB4ia0nJh2MVFLW1f0Zl5d0Rlq2KiXdg5ozvhlnelJ/BjPQJSE8vR2XFnTHKAkyYEG7hFCxlvpDvghKXo5I6JxkYrqBxzvs55wxAJoA1AE4FNt3CGFPTbs4F/of3RMJclKz2xTl/lnNeyzmvLSqKzockWhyOItQu+j/NcnKjJMaYOL8fztw5v8Dyi99FWdk1ksZB+UENLjml3ZDosRw4ndXIy6sN7BDfnHv4yEkw0SuPHCOnsOSRbxDT0qIb9Ss1VHPnPCPmCLMrTAfINa4zZnwHM6Z/OyoZBCwWG9asPowli/+Ki5b9B8uW/gtLFr8u5vaZM/tpLF3yBmbO+B4yYwhqCOkMdXQM4UqwxZKGiom3o2Li7ZLI2kSO6SKf+eLiD6J20SsoK7seLKQzkZ+y8CM8w/FZ0EpLrgJjFsye/WM40uWclyOvhXTqPCdnLhYtfElRuQ734RNWJqisuBO1tX9Gft5iLF/+nuyKBRkZE8VpmZCoMyDiXQpvd5QGO4J1b9q0b2qukhBrtGWIVVfBCT0nZy4mT/5yTPUrUZqULP7+67pq5W7xl8JCaSJUDukzIxfFqkZerj9oJzt7dvSBHgrvvyVsBoKpTHGq5flTIzdnHibXPBihDFosaSgruxaTqv9LZ+qX2AcQWZn+wbfiVQv0qcJ1zcycjMW1r6Km5ksxH9MIEtbacs4HOeebAbwi+XmKUnkAQmhSLmOsGAAC/4W5wb3GSxkba1YfwprVBxW3KykBTqd8ygiHozTKcGGpUqP+oubl1sr+ruSTENtUkDJqua/8x9P30skpGLHkFGIKVsGioktF5VgphJ4xW0Swhd02TnSWjgWrNR3Z2TNhs+UiM7MGaWmZuGjZBqxcsRPFxR9CVtY0lJVdo6uupUvfDJNX2sDGN7WSkz0ba1YfxJrVB+KqR0AzwaTE4pWbOx+MsbD3Kvjc54dFm1ZV+QMx9PqgSREsuhUVnwmxpArHLir6ECZN+iKs1qyofDSDcgTPq7z8Jsya+UMAQEH+cqSnlwfktiA3kOIk3VEq/h6OMJ0ZLkdO9tyQ72lp/hSUM2d8TzwbefzXqKz0WsVjikQMqKJ/j+Od7gvfv6pqPVav2i9+nznjKaEkpk/7VlxLc61etT9k9iRdxlldaD+UFHJmsYecvz6rZpDKyrtw0bKNqF30J00Lmr7fEGZZDAYG+BU07cCiWKmo+EzI96ClSvkYsfqDrVyxA1VV6wH4A0hCYGEWNMlznZMzJ0KBTTZGJ6r9GWPsMsZYMWMsnTG2HIA0Jv9EoFwjY4wzxjZJtklzVXyDMTYOwDcUtqcUa8BPTBEFa5CyFUP7wc/MnIKpUx8B4HeSdzhKkZE+UXHXdWsbAhF5kUqhxZKBVSt3yu8Yb9SKpAPSigIFgNychbDZClCt6dQbPFGnsxoORykm1+j3RRAU0qk6pusyMsZj3doGjC+/OVQCZtVoGEPR8pXgCtNujDEZxVY+glhKmjVLsj00L7SuzlDjMbRanbBajfEPKi29WmOZtMhrI5yzvO9KkEnV/4V1axtC3je9jXvFxE8jLS0XE8bfCotFOkVsCciQjuqq9Vi9ak/Idr1MqvFHX06b+hgYY7BpDGBiISNjguzvgqIW3j6VBCLrgo9jYvxvwq0k2i4D/mu+csVOMRhDSvg7YEvLC54jgsoHA4PFkqYrwnvmjO9Cev7FxR9GRcWdSEvLQqVEqbBas8JSvyBkv4kTbxdTxAiUln4U8XW5DE5nZUBpCB4rM3NqmGuE/vsntWr5fC5kZk6Dw14SaZVFdNOzEyZ8AmlpOSgqikwHsm5tA6ZM/krIb+XlH0NaWo6YvkR2ABdj32S3j0NOzhysW9uA3Fyt/HHm8D0TMNapBvgEgPUK217nnKst4Pi/8AcSXBqoQ1rPvwG8bIiECWRS9f04cfJHSEvLhsvVFrFdsZOUUejCO5TFta/Cak0H4I/gEnKwRUNR4WXoOPdvLFr4B8Uy8Uet+PcvLFyHigrtTNQ2W46ysihTL+BXkMPPf+7cZzE4UA/AP3IeGGhAU/MzAICLL3obGRnRO9lPn/4tONLLcOLEDwKyRpcFvqjwUtTXRx8dJ0/w/Kuq7kVuznzsP/CZgFz5yMycCoejFGlpOXC52nDRsn+FKICpyvNcohBWb9WwPslapwLnUFx8Bc6e/YfsfkqJYqXMnPFd+HwuDA+fQUFYNKTTWY3VqyLzjAWj22QiRMOYP/959PTIG/xzc+aFKqYGrE6i9s7On/+8+HncuFUoK70WVVX3Yuu24NTb7Fl+K57NlouRkQ7xWams/Bw6Ov6FwcETMjXre57WrW3Aho3+QeKihaFjbK1Bw7q1x8XPEyZ8HA0nvit+n1zzZRQULEdL6ys4ffp5oUJdMqlRVnYt6hueEr/PmR10jpc+W4wxTJ78/9B+9m+SvaW56PwDwcZGfyLfysq7ke4ohc8XmmmqtOSjaGtXXoFCCc49EpmvQ2XFZ8TrHM27bg0Z1GUiLS0TK1ZsUSitv96szClYvUr/pFdm5qSw8pHPdCIiKsWp4rApTrNgtIL2NPxJZScByAPQD6AOfuXrF2o7cs55IC3H1wHcDKAcQAuAPwD4JlcyN5iIqqp7YbGmo6BgJXbskHOqlB+ByEVi2iKiPuN/cObO/R/NMtE63SsTKe/MGU/F7MeQFlCOIketfooK1wGF6wD4G6zBwZNoan4GGRkVMSlnAhUTPyMqaDNnfBe9fWFT24HGMD19PIaHz6C6+n60tv4Jw8OnFS1k8cLAQjqjlSt2io3y/HnPoaPjX3A4SuDxDACAYlRczaQH0HDi+wmRMURWCYtrX8Whw5/HRJX1ZouKPoDy8ljzUstfc+n7pBzRpow4vapjFD+uYAXG6QgK8lec2HB+qRwWiwMzZ34XPt+IbNlFC19GV9e7olVlcs2X4B7pklXQjOjIogm6Cbd+VVb6gwimZc8KKmhhCAMqYbpW7/uoN5lsLFOA4ftMmfK1KBS0oPzSexhLm71g/u9wvP7bKCxci8bGetjthTpStCif39w5qt179MjdKoNykoW+awpRnCbBUAWNc/5VAJrzWpzzKoXfB+Ff2ukrctvNDmMMlRV3wjVyTmF76M2fMf3bsNnyZJcXysurRXXVfTjZ+FOxboWjxiVzOFlZU1Ez6cGQJWmiQ7kRLCuLPQN9UeEHMGvWj6KOctW6PrWL/qiaI8hqdcDprMbg4EnYbPliVKHdXoSRkQ7RWbp20Z8wMHAcBQXL0S42uMZ1ukqdS0HBypBnIz29XFR+hA6wIP8i2X3Lym4IU9Die5YWLngRe/Z+XLVMTs4cXHzRRvF7be2fkWYVOl//OVZX3afq+8HAkJ+/FO3tfxUV/qysmejvr0O+wrkWF1+BCed3qiqGaoi+OQb7aGYEMp5nyayYIeWiZf+B292jWkZK7aI/yWbq9xO8z5MlU01OZyWcztCppVjOd9nSf2NwsEGcgrxo2Ua43Z2RUkTpg7Z0yT+wfcflEb/n51+E7u6tEYpVQcEqzJ71E3GaTa8/kc2WB9dIu0xW++A76H8fQ98XfZarUBnt9gLMm/sr0RquF593OFhjRLoTbTkKCpZj6ZK/oa39rwD8iqI0R5kcwvktWvgydu8JDqBstnwUFX1An+A6kRuwJGQQE+6DNsYtaASUR5fhCpqWc/mkSffjZOPT8Dvvymv2iTDJVlWZZ7FYAcYYSks+Yni90SmiDIWFl2Bx7avIypqBgYGjyM4OpERwFMPhKBbLCSy/+B1s3bZO1moRTeoMqU+aX2btxspqdWDp0jeRka7kk+S33I4bdwk6O99CvI2TM5D1X1Be9ZAru96nghwSJXXG9O+gqOgDKBy3BgCwuPbPaGt7TdE6xhhTz1GlhSS6zUiczkosWfJ3ZGqsASs3iMvPW4pTp34dERQAALmqSyYFr29lhYZiELjm2dmz0dd3SPy5ROVdzMychMzM4HJtfqUv0qcoWgUtK5AGJxynswbd3VsjpjgZYyHpIZT8J6uq7kVj489gt/vfX0d6OfoHjmLqlG+EleShn2OwtghKjjQJcWHhJbJlI5X24Pn5fC7xs9WSrlhO7peysuvFzyXFV8KZUaVzZkPe2isdPK5csR1erwvxI9O+GWRBk6Y+yRaWJhSmOE2S/0zAXPa8MYPSTY79cifLghYvqc68HInx18cf3ZOmY507jvT08oDjcZDs7FnIyKjUvSwV4B/Vr1q515+FfZz+JZayMqcodkxWqxOrV+3DlDgSPwpYLA5ReWGI3jk/KhiD1epASfEVopXGYrGhvPx64/JMRRxSmsDTWLKzpscUEVpUdClWrdyD/Hz55dWUiKYT8ju2R2b4r6l5MKpjKsmxetU+rFq5CyUlV8W8zFpJid/toSBfezUHaZJvIZfc+PKbsPzid7D84rcB+JP2Wizp4uBLgIcpaJFXUe3ZC+67etU+zJjxHU1ZaxcJCRD8R8qSyCNdJzd8kCl3fzMzg8qt1DDAGENOzhxdz0Rwmj/8nQ4qTnZ7YVwuJUEi2w2jrHQFBRdj1co9WLVyD3Jy/IObvLxaWK1O1TVOUwFZ0BKAP2XCVIyMdISMVtLSssBYWoiDpxazZ/0QjU3/A6WXv6LiDrS2vaI5RZIs8vOWweEoRXXVvdqFVRg//hNxdbZG+n9FX1d4lNyVOHQ4mIxRuoh5NIRa3IxRPNPSsjGiMCWvB8H6Nnv2T2G3F8LpnIwpk/8fjh57DMPDp3T78wDQ4TCfOuXf/1yXobpKKQYqNUQbuBItBQXLxaAGqcO/UYqwMEgRAhViIT+QLT92WEiao+KiD6Jo9UGNc+RIS8tDZuYUDAz4gxn0Lp+md2AmTMmuW1sfsa2w8BKsveSYbitkaelVgXUuY08bUVPzIA7XfRHZ2aFrCPNErFcZ1hbEd38jCX9vsrNnYfWq/Qkb4MUKKWgJgDErli2NjDJjzIq1lxwVGzk9lJRcKY4Q5cjKmmb4wyvHpOovIC+vVtPHyGbLjSnCNJzp0x6La38hBYKyH070RGv+jrQeGffy5+dfhPLyj5lKYbBYbLho2T8BAG53F+qOPBRbZF1MSYsTi/+5jm3dV/Nh/PWL1fplCmSeN9mOOkxpsFjSsGzpm9j41nRw7oYR17Ws9Dr4+Ah6ew9Aq72Idoo43pxeeXm1opUx0URjeZ8968c4dPjzWFz7l7iOaTblDCAFLSUsWvR/8ETh8GsGqqvjs4glm4yMCkyd8g0UF0c6FSee0NBtwB8BmiPrbxUbFosNM6YrrxMZDfFZG+XD07kYtq6/0TPf9PhYxXgFrWLiZ3C+ezsm6kitEw+1i/4It/t8zPtnZk7FwMDxEIVS7zMq3Uf+nYn/us6c+ZR2IQWczkkKKVFiZ/asn8j6P0qRy7UZL5nOGrhcrYrbly55A/39RwEoGzFstny43d2Gy5ZMSEFLAXk61vM0C3PnPgv3SFfIb+FJUM3KxImfSslx8/MWY3CwPsSMHktqh+RhhINs+L6Rmbm1yMtbjIGBYzIpZggjiec+CxHN4VitDixYEN3SRbEQe3S5n1kzvw+rNQNTp3wDx449hta2V3T7/yklAA6SWn/gRQv/gP7+Y4bWqbUG5/z5zyNH0xc3embP/il6e/di3355hT8ra5rmSjJLl/wdg4NNhsuWTEhBI1QpCuQWE1h+8TujezojJqKz7Eyd+g1MmPgpOByxrVeYOmLpYOSvTdAapr/OqVO+hgkTblVc9owsbKlnce1f4rJgpRqLxYaZAQf9qVMfwYQJn4jKjy9olQmL6IQheXLjwm4vREFBYVKPqTvfX5TYbDkYF5ZEOlocjpJR2AaHYr5JV8LUpKeXG+rXNRaxWOzIylRbdnYMoTQ9GkNmbr3XzWzZvi8k0tKykZExMdViGEJaWqYYxaeX6qr7AvvKzSJEPpfCYunFRR9UrXd8+c2jZmaCSB5kQSMIImZEq1aY+SC4+LCRY0CyoBGpZeLET6m4TkQqaHqDuKZP/xamT/9WnNIlj+nTvoWOcxtSLcaYhxQ0gtBkbCsGwooDQl6omOoI75xMurYdEYQsNkSsjB9/M8aPvznVYox5SEEjCN2MTWXD6azEtKmPG7pci83uV/bSFVYxiAnzL8c7apg543saqw0QesnKmoa+vsMYq+1DKlm65B9inrkLEVLQCILAhAnq+e0U4fLBAEWFl2HmzO+j2OA1+vyHoo4wXsrKrkm1CGOGBfOfR3//UTH3ImEcWVlTFZf4uhCgJ4ogiDiQV9AsFhvKSq+OLB4HuXn+9DR6lvQhiGRhs+UjP39ZqsUgxiCkoBGEFjSzpk0SrFp5uYuwZvXBCzDNC0EQFyKUZoMgNGAWYUkVmlpLNaScEQRxoUAWNILQYN7cX6Kl5f+QkVGRalFMB1dY6okgCIKID7KgEYQGTmc1Jk/+cpxLIY1NhHX60qLIxk4QBEFoQxY0giBiZsrkr6Ko8FLkZM9OtSgEQRBjCrKgEQQRM1arA+PGrUq1GARBEGMOUtAIgiAIgiBMBiloBEEQBEEQJoPxMbR8CmOsA0BTEg5VCOBcEo5DRA/dG3ND98e80L0xN3R/zE2s96eSc14kt2FMKWjJgjG2i3Nem2o5iEjo3pgbuj/mhe6NuaH7Y24ScX9oipMgCIIgCMJkkIJGEARBEARhMkhBi41nUy0AoQjdG3ND98e80L0xN3R/zI3h94d80AiCIAiCIEwGWdAIgiAIgiBMBiloBEEQBEEQJoMUNIIgCIIgCJNBChpBEARBEITJIAWNIAiCIAjCZJCCRhAEQRAEYTJIQSMIgiAIgjAZpKARBEEQBEGYDFLQCIIgCIIgTAYpaARBEARBECaDFDSCIAiCIAiTQQoaQRAEQRCEySAFjSAIgiAIwmSQgkYQBEEQBGEySEEjCIIgCIIwGWmpFsBICgsLeVVVVarFIAiCIAiC0GT37t3nOOdFctvGlIJWVVWFXbt2pVoMgiAIgiAITRhjTUrbaIqTIAiCIAjCZJCCRhAEQRAEYTJIQSMIgiAIggAw7PWh9K19+ENrZ6pFIQWNIAiCIAgCADrdHgDAUyfbUiwJKWgEQRCKNA25cMv+Bgx4vakWhSCIJMAC/zlPqRgASEEjCIJQ5IkTrdjY1Yd/n+tNtSgEQSQBFtDQOFKvoRmqoDHGJjPGfskYO8wY8zHGOGPME8X+FYyx3zPGOhhjw4yx/YyxO4yUkSAIgiAIQg4WsKGlXj0zPg/abACfiWVHxlgpgC0Axkt+ngvgV4yxUs75EwbIRxAEQRAEIQvTLpI0jJ7iPAPgSQAfAbAjyn0fQ1A5uxVAGYDtge+PMMYqDJGQIAiCIAhChTFnQeOc7wSwEwAYYw/q3Y8xZgFwU+DrEc757wO//wDAywBsAK4H8AMj5SUIgiBiw+VyoaurC319ffBSEAVhID7O4eWAzZJ8e5aXc/wuj8EKL44cOaJ7P6vViuzsbBQUFMDhcBgii1mWeqoBkBv4fEzyu/TzguSJQxAEkXjOuz1IYwxZadZUixIVLpcLzc3NyM/PR1VVFWw2Gxgz0+QQMZo5OjAEj5djRo4z6cd2+3zw9g/DyhhmZGfo2odzDrfbjd7eXjQ3N6OiosIQJc0sUZyFks+9Cp+LkyQLQRBEUpj+7iHM23LY0Dp9nGPI6zO0znC6urqQn5+PwsJC2O12Us4IQxn2mmGCUb8MjDHY7XYUFhYiPz8fXV1dhkhgFgVNCelbL3u1GGN3McZ2McZ2dXR0JEksgiAIYxgwWJl6tL4F1W8fwIgvcUpaX18fcnJyElY/EQrnHNwMibkuCOIbbOTk5KCvr88QScyioJ2TfJa+9dmSz7LaF+f8Wc55Lee8tqioKCHCEQRxYbC7ZwClb+3Dgb7BVIsSM79r8TenngT2516vFzabLXEHIEJ4f2AYB/qGsL83Mc+ll3Ps7x3EuRF3QuofTcRrC7bZbIb5ZJpFQWsA0BP4PFXyu/Tz3uSJQxjNjxrbsHK7fodLgkgFb57zN0NvdRozAk4FnoClJdGNO01rJo8RX2KtZ+5A/edGdKctJRQw8r0wOlGtjTFWyBgrhD/yUvi9MPDnYIxVBRLYcsbYowDAOffBH60JADMYYx8P5EX7YuA3N4A/GikrkVz++2Qbjg+6Ui0GQagyFlQOwXJGE2JEMnF5fTjSPwR3AqfWlWgdHsGZ4ZGkHzfRGD3IWg7/VGQHgIsDv1klv92ssu8j8OdRA4DfA2gFsDTw/THO+SmDZSVMyLz3DmHue4fw5aOnyOeCSBlmWOYlXsLP4NX2bvy8+WxKZCHGPh1uD0Z8HD2e5KdcOTviicr6xzlH85ALwwkOpokXs0xxgnPeBr9S9xKATgAuAAcAfIZWEbhwaB/x4OyIB8+3dGIowWZ9gghnLE3bhSuZn6trwuMNLSmShiDMQ6/Hi263F80yVjce9j+VGKqgcc43cc6Zyt9vOeeNku+Phu3fzDn/OOe8kHOezjmfxzl/zkgZidHDWLBiEETKoNfnguC3v/0tGGPi36OPPmpo/dK6q6qqDK07VTQGFLOhFEzHRoNpLGgEQZifEZ8Pf2rrGvPTz2P77AjC/JxpagpRDtesWRN3nYNerz9HoOoLbp633ywrCRBEJOZ5T4gAP2hsx4+a2pFhteDDRXmpFsdwxs4EJ70+BBHO8YHRFahGFjTCtOgxPnPOcaR/KOGyGEGP24M9PQOjOpS9PZAnqcc9ttdeNItyM+Dx4s2OHu2CMpjlHIgLA3rejIcUNGJU80JLJy7ZeRRvd5k/b9WqHe/jij3HMfu9Q6kWhVDAbBa0mncO4rZDJ7H9fH/U+1KHmTr+P3vnHR9Fmf/xz2xJJYUQQgoQWhICoTeVIiiI9fTs/TzFs5/+vNNDsRcE6ynq2bEXxC6IIBI6SDEBUkjv2SSkbpLtO78/dmczOzszO7M7m93A8369eJHdnXnmmZlnnvk+33r06FEsW7YM48ePR3R0NLRaLZJctO2sAAAgAElEQVSSkjBx4kRce+21eOWVV9DR0QEAyM3NdTPl3XTTTR7tTY2Ldv2T6we2cOFCt/arqqqwYcMGnHXWWYiLi8OgQYOwaP58/PbD95Lao2kaH3zwAebMmYPo6GjExsZi8eLFOLBnj8e2JpMJq1evxtVXX41JkyYhJSUFERERiIyMxPDhw3HBBRfgo48+gp3jCzY1LhoXTJ7g9t327dtFTZ40TeO7777DpZdeihEjRiAiIgKDBg1CTk4OHnjgAdTX14MLBaClpQUrVqzAjBkzEB8fj8iwMMwfmYYLp07GRRddhKeeegrHjx+XdG2Uhpg4CSGLlBfMMaf2rMJgwgJn4QkbTUMFhwaOAqAKkci8pgGsOWM4yV3PFIemadgBqFlj0GS3I8z5kpFKtdHsyjkk59gE+TDXzdeI3u3bt2Pp0qUwmdzNaS0tLWhpaUFhYSG++OILzJ8/HzNnzvS7v3J5+umn8cEHH7h9t2/vHuzbuwdVKx7BmmeeFtzXYrHgiiuuwDfffOP2/datW7Fz5068u2ET0hbMc32v1+uxfPly3rbq6+tRX1+PjRs34tNPP8WGDRsQFhbm0znpOzvx7xuuxf7tuW7fm0wmFBQUoKCgAO+88w5WfvAh5i1Z6vq97UQLLlgwD3V1dZz2OqDv7EBNRTl+/vlnREVFISsry6e++QPRoBFCFruPL5i03HzcWViNtNx8XJ5XrnCvCKcCSsk2T5c3Ii0335WpfZ2uDenbj+CWY1VB6Q/BO0f0BlQbfE96+uyzz7oJZ9OnT8df/vIXzJ07F+np6Up00S8++OADDBkyBEuWLMGYMWPcfntj5bPYsWOH4L4NDQ345ptvkJaWhiVLliAuLs71m9lsxpvPPMW7X2JiImbNmoWlS5e6rkVkZKTr999++w2vv/666/Piv1yCuUvO8Wjjsssuc/0788wzXb/95+83uglnqampOO+88zBv3jyoVA4xp6urC/++8XpUlvRpw7798EM34Wz06NE4/4ILMHvBmUgflxH0cmZEg0Y4Kfmu2WE+2OODaUguRd0GLDpwHL/MyMS02KiAH48wcFhb76iLaabt0EKNb3TtAICNJ+T5lfmSciaYMt2jpXU41m1Aj9UOrYpCmCo0tNhi5AyKxNMZwwHAr2SrVVVVrr9vueUWvPfee26/NzQ0YNOmTUhOTvb5GP4wadIkbNu2DUOGDIHdbsfNN9+Mjz76CIBDe/j8889jwYIFgvtfeOGFWL9+PcLDw1FaWoqcnByYzQ6B9vDePbBYLECYQ7CJjY3F0aNHMXHiRA+NZFNTE8aNG4fubscc/dVXX+H++x3Fg1785DPUV1e7mTknTpyI9evXe/Rny5Yt2LP1N9fnG264AWvXroVarQYA7NmzB/PmzQNN0zD29uKt51Zi9VrH+TbUVLv2y8rKQkFBAewUhcJuIygKGA0btm7dimDV+SYCGiFkGShKg91OIXCdro0IaCcJgRp7/SmmfNbYhvfrWnD4jIn9eFRPLHZ6QAhoSpGeno7S0lIAwC+//IIXXngBEydORGZmJkaPHo3U1FTcfPPNQevf8uXLMWTIEACASqXCypUrXQIaAGzbtg02m80l4HB58cUXER4eDgDIyMhAVlYWjh49CgCwmM1oPXECKdEjAQBhYWGIiorCAw88gNzcXFRUVECv18Nq9XT3KC4u9ul8fvjhB7fPNTU1uOqqq9y+CwsLc2k1d235FXa7HSqVCikjRrq2qaiowIoVKzBtxgyo0kYifdw4xCQNwSWXXOJTv5SACGgDFIudxlX55fjP6GTMiR8U7O4EhIEioEU4VejmEE96SPBOoN0VfW3fl2fh6SBWDWA0UfldvQCAKQFYuJjtdlQZzBgdGQatKnS8dR5++GHs2LEDZrMZDQ0NePDBB12/RUVFYe7cubj11ltxxRVXBKV/OTk5bp9TU1MxePBgtLc7tLu9vb1obW1FUlKSx74xMTEevlhsMycAWFjm3dzcXJx//vkwGLxH2nd1dUk+BzaVlZVun7dv3y66fY9ej462ViQkDsWlf/sbvl/7Purq6mCxWLB69WrXdmq1GlOnTsXVV1+Nu+++GxERET71zx9CZ1SfAnRbbbi3qAadFv+dxWuNZuzp6Ma9xTUK9Cw0keN3M1CEOcLAINSqWPjbG1/9OQ939mBVRaOfRw8MrRYrDDY72kIs5cuiRYuQl5eHu+++G9nZ2W6aqN7eXmzZsgVXXnklXnzxRd79udql5ubQqZ+akJDg8Z2Qpg0A7rrrLjfhLD4+Huecc47LjywqKjgWB0OPY+EwJGkY8vPz8dRTT2HOnDlufnE2mw2HDh3CAw88gMsvvzwo/SQCWj+ytv4EvtK1YY0CBYuZhfhAcx6WE1kmZctTx3BC6A9OxvFE0zSO9xh92vf8w6X4b3WTwj06+cnOzsaaNWtQWFgIg8GAiooKrF+/Hmlpaa5t1qxZg06LFV2cUdfa2ur2edeuXYr2raCgwO1zY2OjS3sGOLR8jAnUH9rb21FYWOj6nJqaiqqqKvz6669Yv349vvrqK9H9pUbRctOObNq0CTRN8/7L6+xBXmcP0ljBGgkJCXj00Uexb98+9PT0oLquDm//8DNmzO2LRt2wYYOHpq4/IALaACVEMkfIprjHiCvzytBr824OfL+uBV1+OOv2N8GQlRuMZnyja+uXY+3v6MbBrh6f9q3oNWHB/mK8V9fi8dsnDSfQroBWeSDg82M7wBZiXMx2+ylzjz/88ENs2rTJ5Tiv1WoxevRo/PWvf3WLmtTpdKgymKEZ4m5K3L17t8sfq7KyUjBNBYPNLm9wrFq1Cm1tjjnDbrdjxYoVbr8vXLhQVCsmFYvF4vZZo9G4fNdomsajjz6K3t5ewf0jIt1Nig0N/Cb7iy66yO3zgw8+yJvzrLy8HGtfeQlvr37O9d0fO7bj008/dQmoFEUhJSUFcxYuwtTTT3fbX6fTCfY1UBAftCCg5Fw70ObtRQccIc7Pljfg2czhotu+Ut2ECoMJb08c1Q898x0lZOU2ixV5Xb04a0gsynuN6LLaJQUcXJpXhiqDGRcMjUeEOrDrrYv/LPN53zP2FwEAHimtx+y4aEyOcZxbQbcBDxyvw68nuvDp5DFiTfQrgQsS8G20+NMfJc7FTtP4sbkDFyXFu+V0Ez0uS1te1muCxU4jXqP2Ob/YQOH777/HDz/8gOjoaEyYMAHDhg0DABQWFqKiosK1XXZ2NgAgLT0dI0aPQW2l4ze9Xo+cnBykpaWhtrbWq9WhncfhXowjR44gMzMTM2bMQHl5OcrL+1IRURSFBx54QFZ7njjub1JSEkaNGuWKaq2pqUFmZiYmT56M48ePo6ysDBRFCZ5fwtAkJCQkuITJ0tJSTJ06FWPHjgVFUVi2bBnOPfdcnHvuuZhz5kJXmo0jR45g1KhRmDlzJpKSktDd3Y3jx4+7hLaLrr3OdYySo0fxwkP/gUajQVZWFkaMGAFtWBjKqmtQlJ/n2k6j0SAjI8PP6yIfokEboLhMnEHthe+0SlxNt/Zzctd8fS92tulhlKDh4+LPvbjhSAWuPVKBbqsNc/cX47xDJZL205kcq9R+D0/w4x1rZq34Tc7AihazRWjzfsVXAUpy+xKat9E09nHSwwRbQPuysQ23F1a70obIxSJTy3My0NPTgwMHDuDnn3/Gzz//7CacRURE4IUXXnB9vufxJ90EV5vNhpqaGtA0jav/cbvocWwyL+3999+P1tZWbN682U04A4A7/rNckaLkDC+99JLbedXW1mLDhg0oKyvDnXfeiZEjR4rs7UhTwiY/Px/ffvstvvnmG5SV9S0YX/j4M8xZuMj12Wq1Yt++ffjxxx/x+++/u2nUNGpPvZTVakVBQQE2bdqEn3780U04A4DHH38ciYmJ0k5aQYgGLQRpMVugpSjEa73fHiFnZr3VhiP6XpwRP0jSipWmaZQbTBgX1T+RKlIFikBM63aaRqXBhLGcczXa7Fh60CEYXZWcgFezxScPBl9e6Y0mM2LVakRrHKaEsl5H5JNFplNhIMWJvK5epIRrMSzc92SNuW1dOC1OOMqYEYgsdhrVBhPSI8N9PtYJsxUqCkiQ8Nx4I5i+nWuqm7CqUof1U8f29SfIS7FmpwDdbAoNQToUMNrsCFd5VoR45JFHMH36dOzZswdlZWVobW2FXq9HVFQU0tPTceaZZ+Kee+5BVlaWK8r1nL9eivEJcXjuueeQl5cHtVqNrEmTcc0dd2HxxZfgy3fecrVPwzFf+6qJvOeee3Deeedh1apVOHDgAKxWKyZNnoLLbr8TF112mc/Xg49LL70UW7ZswTPPPIMDBw6ApmmMHz8ed9xxB5YtW4YNGzaI7v/ss88iLi4On3/+OSoqKmA08vtSxsbH463vf0Ltjt/x2Wef4Y8//oBOp4PFYkFcXBzGjBmDWbNmIWvBIpyxeIlrv7P/cjHSIsOxe/duHDt2DCdOnEB7ezs0Wi0ShyVj3mlzcMstt2Dx4sWKXhepEAEtCHib/CftLoAKQMOiqYLbsIMEOixWD2EuY6cjL80LWcNxQ6p3yf8rXRvuK67FuiljsSAhxuv2QljsNEx2OwZpxH0YgvkCfKOmGc9WNOK3mZnIiekzI1pZnTqiF/aNYGO229HofGnJOadpewoxPjoCubPHS99JBKVf4HaaxrlOLZ5OZByK8VtrF64/UuHxPcXzd2GPEXP2FaF0/iTEeBk7XNotVsRr1K4ap772l9u3QCMUzV3qFNYbWcKQPwooJZ41vzWLFADaIVwocY3tNA0DS8vNlHcTElqsdhoaH3OxWex20ABUoFxt9FhtKOs1ITVCi6Fh7guYmTNn+lTC6aKLLnLzpyruNsDkvPF5ne6+n40mC1IjHGWRLrn+Bpx7zXUYExUu+dlZvHixm9BhtNkFA0m8mVhzc3MBALUGE9osNgyPcC/XdPbZZ+Pss8/m3Zed1JcPrVaLFStWePjJ8UFRlMc15MIIxAwpI0Zg6b334t5773V9Z7bbUdTtuBaBSA8jB2Li7Ef6zJLeZ0xvGiZmIqo3WTB+1zH85MyczyWvS5qgka93hEKX9PoW7cVw/ZEKjHMKh2LYJQoUgZDjGEf3OqP/2oDFB0rwQpVvzqPFPBOi/FdIYEQKJa57Ubf33Efc96lBpmm5rNeI7F3H8HFDq/eNQ4ysXcd4v+dzX/DHhB2stVAgj3tUb4De2ndVjukNqDHyl2dqs1hR0G1Ar823gKPCbiOKuo0o6Da4hGqTU2iREuwUCPTOc7HY7T65YxAchLo3JBHQFCZ5Wx5uPsofjssIVdyJ68HjtUjelue5gwjcgbVb4ZJGydvycE2+/DqW29v1krbb0NIp6ZyDbdrxhr8CrTcOdPYgeVseDnT6Fj2pFLsk3ld/kfuqKXdqm35rdU9ymbwtD8nb8lAr8NJmtnnweK3cLvqGD8OYrbgIduHzUH8OAaBDIB9atzMS3CjXWYuvLY4w1GW1Ib+rF/ldvT4LgP4g1yUiUHRYrAHJR8eM+/yuXlQbTF629iRf34tSH1PMhAJEQAsAQnX2hKR1X1b/vkr+PzZ3IHlbnod5hd0eo3Xb1tY/L2UxAjn/iL10QkXrsK3NIXjktrkLIBY7jeRteTAw1QsU7jD3um9p9czy/Xp1k+yFBRfuOJ66pwATBTRLYvsLnX6xFy0e99mT4tZT2G1A8rY8FErQEPoC0wf2+PQvSIBWLC1PaIgD7vRnn7iXkW167gkRTZbOZJbsouENRvgU02wXdvtXXF4qQgK4KLS4ltNOO/y1QxUioJ3kcH1HXncmnazkPFDsSe6nFn5zKZfNJzoxa29hSJU48jXKTAm+1LVhV7sePTYbpu4uwE4ZAq7Q+1Poez1ntR7oO8DXj2e8ZJgXenHy+aCxkRrhCwAqp+Tha6Z8IZjWfuRxHfjZ+XxsbJFS8Fxev35u7sDXzoLq7D2DHcXZH7RbrCjqNnjVFuoCEKhgsdtxTN+LehGNKxu+cRsiyiw0maxufcnNzXVL1spN7CoFseLxAz1CV858098QAS0IKDGcuROEVBMI8yJn+8t2WKxugk20xHxay0vqUGs0ozmAqTDkXquHSuqCclyGy/PKMW9/MXRmC56pUK4Worf+KDlFPlFWj3Wc5LdiCphWsxXJ2/Jw67Eq13ePldZjva5deCcJ7TJ0WW24/M8y1PG8PJmRyj7/z/3wRwuUT8qXEpMJ/5tlcnUT0ELkHehrN6SkBao1mmG2014XG00BENC6rHbYaEck8KmExW5HWa/RFSBlGuDCFuDwOWyQKGiHOkRA60eC4ZDINW0wZhP2jf+a8yLVSrSHDPRcbGL480Jkou98iXzjHlZqG0r6KL1V24L7Ob5ZYv341CkQsTWv79S1SPLPk5Iq4MfmDuzq6MbLPMEYzN7s9wq37/3Jd03tDtMzx6yyotQzszkfQkIZ1xxvsNkxevsRfN7oXRgNlnAXcvNCP03A3U6/NLZlgaZpNBjN/e7Qf8JsEa3G0mqxosdqx4kQ0CJ1WW044SUfohRNea3BjBYZgjYFxz0LxRQyREALBgrMXL40kdvWhQJn+LBKAaeUeueAfrlKh54A2fGlnqeYgNJitmBNdZNXIcbdpETj26Z2XP5nGaw+rirz9b14taoJbTImP6EuMulU/lulg52mPTWoXto93mPEZ140S9vb9LjkcCnvb2LDRWpEbl9j0jc92NmDDU7Bj+8oKlfgjbLiQI/NhrE7jsje747CagCOtDVclh2r9Ahm4MI+D/Z15Q7BL3VtMNjtuL/YuzCqxJVh2ni9pjkkX2Ry6LXZZD2TcmECV9gaXwtNo8VsRYUPju7+UG+0oLK3f48pBb3V5iE4VvaaUG+0iAph7QEIRAAc96wxBMc1EdB8hKZpfNJwwm2l/KeXlBZKaJy+0bWhzWL1aINrkuLj6vy+nFT+iGc0TePZ8j7z3ReNbXiu0t0f6b6iGuxVILLU24JJigbmjoJqPFvR6Lo/Us/9zsJq7Oroxrom32pd0gCeq2zEv4trJUcgcYUddl+Xl9RhVaUO23l827yNqTP/KMa/vGiWrsovxz6BaFGxa+aPVcTbvbjwcKlosAqfBk0J3q07Iej0LUUjxae1+FmCzxq7bfZ95h7SH587f7WttxVWKdKOEHLnJrkmz9IeE2r7wamdfXUGurWh22aTnQJHjIpek6DgKO4yE/pXUMnngghoPrLpRCceOF6HVSzBxFt5HrlKK+6NrjWacVdRDZaxfH0YDHYah2UUsvZHgdZitmJNTbPbd9yX2Ze6NvzVj9qNDN40I1LOmXEC1TnV51Kc19krXbOfb/9umw1n/lHM+5veauMVuAAmWzi7Hcc15gutZ74x2+3YLBBF7A9iw0Xu1TnU2et6qcoZhnzzHuNLqcSU2Gq2Yn+HMulMfJ2j2bux/YGUDBLwpa1y1su022qHBUCbyRxSAUKBQM7L1mi3exVilHp3KycCSHsCe6x2lCiUrqLbi7VF6YCf/sZut0OlUka0IgKaj+idD6IvtSKlmmO4K25mMmw0mXlb4AsnZuzr3KShataDKZpugvWw5OsdfhVWPgHBz2fqh+Z23ugsb80e0XtPdVDknFhu5hFshZCSMmm/RA0hDcAoIOT9s6gGV+WXo8M5abGv4xeNbW4rb7FrzDS/qkKHG49WYrfCecv4pnHmu3qTPG3Eo2X1WHSAX2D1FdlmVh4uzStDroTrJmdxY5Ap3LOfYHZqE+alxTyDcqBBu/kQ+nKl1jf1+anSALZ3m1HbqXdlXFeSgfp6brfYBIUYKkR0aFY7jWaTxVUD1xfsNO1XzrdymSZXf/rqC/7eod7eXkRGRirSFyKg9SPseb3bavMaMdTk1PjUOLU5zEPueFlLH0Y3HK3AogPH3b7rtdt5j68zWWBjtf2tc2Le096NpQdL8EhpPW+UlT+DemtrF24rqMbUPQUevx3q6nXrTyCRehTmflwsUUMo1v2dHIGAvamO5TDLZy5x38+xRbXR0Tcpvhr1RrPLv+6ol7xJXFMyhT7t1ReN8k3ATFJLOcIOrw8a80wIXONOqw072vSgadp134QQKnXj0Q/WsYTalOsT5815nAZQbTBh6cESPFYmHB3cKEFYVsIcvM9kQ09Xh+R5iNlMyuZ8C0BfMNntoi93mqZlv/zliFk0z99KzWS+GkAKug1oNFlQzBGspVoJzHY76o0WlPaYFNGeWnja4F43974qH+mhZIs0TaOjowPR0dGKtEcENB8w2+1+5X6h4fAJYmoHirFe14bZ+4qwq12PDqtDoKJp/gddaF7by2O2WXqwhPf4r9c0Y1VlX7RchcGE0h4jLs1zCCMHO3sEVdC+lj0Ry/YOAJcqYCqVgpjp02qnYbTZsbNNj9n7ivBdk/cUEt7aBTwzk4v5oLH9mqRMKmKBGy1mC2bsLcTTTl9Cb7mlxDRo/uBvjUejc4IXGnl3F9XgyvxynHXgOGbvK8Ke9m5Y7LTsoBaD3e6xUPi+uR2z9xXJyncnBBNcIBgkAri0rIcF/ASNNjum7Snk39nto/9iwnYLhaMd3TC2tsBkMvEKalLkLL7FF1d48AWT3Y7ibiOKu41upmL28dosNhR3G30KcJLvw6bsIlNua94WuVL9y4q6jehxas8UKMygSBuhAE3TMJlMaGxshNVqxeDBgxVplxRL94FJuwtEE/cJwX4Z1UtwbKVp4LDTsX17m97l9yV3TFM+7NO3L+URjcTXlpWmMcaHqDfA+yphv8JljnwRCa7ML8eejm48OS4VgDTfNwY5Kn338j5wdXbziU6XqZYvMII7/+a26bGsoArfTxuH0+IHeWzPaE8Zk5638cEvoPkzsoTbFYI78o7pe3Gtsxi7N2GAuXbMQkMu/1dciz0d3ViTne76rsx5X4t7jJifEMPpqzx+dfkN8u9J04DGed+FNExmqdosmX3z3J+GFRRe6Kax2NyOITYLrFZPbbydpj0c+DXhWlfkrdluR5PZikStBpFqFZqNZpegXcQpuM2mSWRBx+xnsttdzuYaioKVptHq/J+hW61Cj80Os9bh8MEtVVQUEQaaczyDRo0OjVq0DwzhKgoWZyF1m/NaqABoWOfGbod7zjqTRbCUk5aiQIdrXdcQAOxhGkSoVK42iyLCXH83ARii1bglZS2KCEOX1ebxLisS6B8Dcz2pMC20KspjG4tWjWa1cNF29vZMG+zve9Qq18JVG651G0NCbfOdM/dvofNhxgGznZU1bsXGIReNRoO4uDgkJSUp5oNGBDQfYA9oXyY7qRp89guJLSQJ7d5mdSQMXTIk1u17DUUJPujJ2/LwlFPoEIItD1hpmtdEImQqeKqsAY95aV+JlB9KIGau2eP0N1OxzMxS0XnJ7ePWB85nRqgvYpnf+E2c7uzqcAheBzp7eAU0sbakwrdv8rY8nJ0Q6/H9jNgoHOKJchY6fvK2PCwfnez23TpdO35o7kD1mVMAAEdZfpX++KDdX1yDl8eP9Lrd17p2rMlOl2SWlatgj3ImhxbSY9SbzDjb6aZgFdCgC3WL5vymVMRrDyj8YAbezsgAALxb24JHy+pRPn8SojVqtFusOJtTtqtwXiYStI7Xznt1LXiktB43p8VhZeZwnL893+Wzp1uULXjcRSLlxZj9DnT24EZnypgREVqnlt79xK9LicNnjW14MSsFGgq4j5OypHBeBmLVapy1Pd/13X3pQ5AUpsHDOu957U6Li8L32Y5r02SyYPGeAkSpVaiY1ndu7HPhnvPtfxQLmt0zo8KxY+p4/NnVixudwWlfTB6BRUNiXW3qFmW7tb94SCR+6+jza9QtysZLlTq8wMkvyO4H37UeFalFlcGMrbNGI3tQpMc2L2el4NrUIbz95ra5Y/YYZEZHuH1/Y2q8qwRbzZnjcdb2voX/S1kpuI6nbf5z7lsYM+fEdz5XJsdiXavDItK4cDxqjGYs2Vfktl+wICbOfqSvxp40aNa237FKztQazZjjHEBsmHpo3LqJaj/ewirOvpUGM28OIaFzerO2WeAX1jEk9IMv+acvCEVTSoW5h4FKuO1rs0KmUaH2ZGthecYQd2wwbG3zzPUVLrCiFBN2Xq/xHDtCkY3+3I7PZfrQSVlgyRUYGe2YUNtHWcEwQuYqMQFN7LNcuIdnilG/U9cCAK6kp3zPiIeGGMAHEsuz1RnNPtV+9WbSFfqdz/WCAvB+nbT+KjU++duW32K5hMTRcvhG1857P9hayspeE5K35eGovhcz9hR4bM83Ztnjuz8soGzLVqiZXImA5ifM/ZRTcFXMPLqDnftIYKUsxEqB2ohCEYQM34j4U1Hw9BNizEps/PHrlapAa/KiiZLi8MtekW460YWlB4+7fOrknIKUvHO+wPbvM9O0R345QFodQEbTJ+QvyHwrVXZ/uarJ4ztv44qN3FqjcvG34PEbPMKgVB4t89SmyBXgvV0HG2t0Wmna435b7DQWHzwOKfBpit+ubcaI3Hyce7BEVkJnoK82qZTkyUItG2x2rxGvO3z09RM6HVfQlcDvKvgnIFQZTJi1txCNJjM2OU3YwUyz4a+/J0OVUxEgtPhmP4mbWx3nvU7XJsmtB3AXkmo4vn7/Ol7rk5AuBvuqXHekwqW9CwWIgKYQcvykdrEi9/7gpGp4QKAWXyDJ95KqgvtY8wmYG/3IvaWSOHGsqfYUEhhoAFfmlcs67le6NuTrDTB4Eez4intznfuVgn3PqwQiBJcVVHnknfMwjQpoa5lADuYl7OuU7S0psxTyunpxX5Fw8lw547/Uz2zpT5crVzfVF5j7JeRHxtYqWGnaQ4PSYDK7XpxcuCZOviM8XtYAC00jT9+LF6t0+EbGAoRbv5F2/c8TOMD6jv13UY/3dDlykBJdyl4Y8gkvfK4XFCVnQWlFrdGMb5s6sNxZI5iZa5Ydq8SI3Hyx3b0mh365SueWe5N7xnc5A08Y+C/SW+EAACAASURBVDTegfAuYY9VZm6XUwGArX3+VEBY2tfRjf8rrlEkKSz7Gmxv1/u1WFMaIqD5iS8DhL3HwyI1+kJB29of3mFCpjIun4mYolaU1vscTMBOX+J92/7jB5ZZm02vzY7vOb95+q7xf89NYuvrBC13lbmbJ2fcdUcqcEAk2EIok38wESuXxX4xKd1ztgxkoz01dKKJhDmBPd7G+UtVTbirqEa4Pc5nJkWDlKH0RFkDjDY7Hi+td3tpBzKTjjfNDQ3+58ARAuPpOlAmczHAJ/z/3NIp6BcshQqDCc9XuvuOcVvjWka4pxio9EXsdpnrul5G1Lvb2BYYVJf8WYYvGtvwSnWTh5JDLltOiJdfCyYkSKAf4RtrzSJmOxqOHGH+4G99MSXU4leKRM6Z7XZeX6P+5ovGVmQ5nVXFkFJayh+kTpncHESCvmacH96ta8EZ8YNYJs7gBWgoXT+zP/jX8VpoBcYA2wSndDZ0ttnHxnPl5IzLr3RtWDZ8qM994Zax4kaViuU8+6apHWrKEfDBRmmBVs5i6/WaZtw+wvN6HOs2YGxUOGefwD0vdUYzfm/two1piQE7Bptd7f6X4uODLWB5u1rMsGXnAXTXwInzfKUOz8vrngehUCheCKJB8xOxiWBnmx4VPKst9gBmT27c0j40TXvNEeYNbsCAXOpNZr+npB0iE8FH9a2SE4QyHOjs8aiM4A80aPxfcS3OP8RfKJxNoMUZqb5L3MSSXE2ukFbwUFcvJu8pgJVmtvOOHHOXHPwOtAiSfMen+fiysdXte7kChwqUaE1JttnHxtGI1RvFn1Fubx8prcdXjW34vKHVp9yFDZx+Mr1hm9WP6HuRJ5D8mC+HJFegfay0Hse8JE/mY3VFIw7K1KTXGs1YwWPJ+CePFjGQz//MvYV4sKQO7zmDLeQey9vjwBUubTSN9Trpmi2puGnQJO6zpqbPfYUt/gdzARkKEAEtgFyRX475f/RFWzJDjS2xiw1AoQmuPxkdGR4QPwWGP304x4sOl3pURvAHOYKCXGFSLlK1Sly/H67QUOKM2BKK3BLTanIRM3f5Q4efjv2hxH3FtW6+jHvau2UlQD1hsWIKTyUNBrazdJvF5rawW3LwuOhrbG9Ht0fevnuLa3D/8Vo8zhPgIBe+gJNzDpbgxqOVvNvzafu4YuI7dS1YfLAEhzt70CIjTc0r1U248HCppKdIyrPMlcX7IyPQIyJuL2I0yFzMb27tcqs5rBQjI/u0jt5SKDHCNNtsbGXNbXtlmi/rRK6BlCoboQYR0PyEhqMEC1ftz2g02KYJ7soTcJ/Udnd0u33m1uIMBolhGhQqqK3i8q0M34RA4c0XhP3rWokpAXxFqqx4tNtdsH2JJ8oScKRn4SvpxdSSlVO6hiDOQ05HcMCx8LhbQcGWGzzwMit3VZvFhu0iEY5/P1blkeOLQayChNQXPneB4y2Jt5QoZIbzD5f2pcZRWDjyxWe1P/U5cktePVhSh2KRYAuurORv5LMQv7V2otlkwZ9dvV5dbO4rroXZbnd7x7ADzuQu4Gfu5amkAUflFN4qGyEO8UHzExrgzUnGFsxqjWbYaZrX16qHVXS2xWz1y3E0EBzs7MFHIRR2zMbX0lJcreX7TpOCEP15R6Te/p0cszGjKeMr1ixaUowC2i1WV8kkgu9wM9EHcmHDTXFy/3HhaFhvCAlp0wVedly4/ozsyEI++IQcMWGEe12loJQDfB1H69KfApovZ7DwD2HLAlcbE6hzWadr9/AxFMNG+x+F7Y1Ju4W106EMEdBkwvWVsArYx9h5i2aJTHQGTuLNEJPPBEP3Q4GzDviXdJbhiJc0I0o7fIvh65GY/bzliuNCAcje5b0mLEE+ShX9DiRbWrswVcS0KgUlzvIxL6ZWG03LErqEckLKZd5+9zlGCZ8ooXeGx3YDYPwogT9VQE52iIAmk0qOzV4o/1egMs33N9vb/S8ErSRsx2GlhEdvE2F/6pZ8nqxcTv/yXiCnuhNuIJGamHOgo8QCptiLP9jFh0txUEbuPb6yYkqghA/a2RITCiu9OObeJaHUF3s7unG6SHk4pTlZ3pWBQHEfNIqiRlIU9SlFUS0URRkpisqnKOoWCfstpCiKFvinbOpgP+AzIfHhy6R1Z2H1KTOp+4qcSVoIriO+t5V5fy5kfT0WI0TKfX8MRPHszZpmJG/LCzl3gFOdQI4lJZ57JVDiHKUEJ7wjoUSeXKQKQnId8/0lUPnYTgYU1aBRFJUMYA+ANNbXkwG8R1FUMk3Tzyp5vGCglriEOnni00ILKeWc5CKWBgQYGPm6BkIfleIpZ+LP/7Cc8gnBgxl55RIjAuUkLQ01nlXIdOqNx8qUr2whdY54vlKH4z1GwXx/ShNq9S/ZGG12RKiDF0up9JGfRJ9wdgOAFAD7nZ8fpyhqpJRGaJqmOP+mKtxPn9FIFdDIqiAgKHFZuSkqvNGfKviLDnvPxcYHc13kpq7opzmYcBJDprqBgZx57Ifmjn4TpEP5Xelvond/UUxAoyhKBeAq58cimqY/pWlaB+Bl53daAJcrdbxgMTRMmtKR2NUDgxL6s3yZodub/Uz2Kwdfa3wW9hh9SllC5DOCvxAn74GBLUTvU6DqGitBsK+Zkhq0sQDinH+z46zZf0+T0hBFUU0URVkoiqqiKOpViqLileqkv0i9XWTSCgzveUmJIQW5Yft7+tknw1fu5BRHlkKgnKkJpw6fN7Z51HglhB6hakr8Z5H8eau/CLaiRUkBjV1ArEvg7ySJbSXB4R+XDuCfALZTFBUuvkv/IPWGXSChbBBBPnzJfgkEQnARqhpACB38LRsYKEIlAISPYJtf+8P7jW1FETvbJjiEsQwAUQBmAWDikScDuIa3cYr6B0VRBymKOtjS4r92xRtSzUg1IfowEAgEAoFA8E6wlY5KCmjsGjixrL9jWH8LSlA0TRfRNL2GpukymqYNNE0fhCPogGGWwH7v0DQ9k6bpmUOHDvWp41KpNpjwjgImNgKBQCAQCKHNyaRBKwfAOCJksr5n//2n0M7OIAMutMDfQcHX0kIEAoFAIBAGFsHOtaiYgEbTtB3AV86P2RRFXefMi3a/8zsLgK8BgJWA9kNWE+9RFPUIRVEZFEWFUxQ1A8ATrN93K9VXAoFAIBAIBDGkluUKFEqXenocwAVw5EL7lPPbkzRNi1X0TQDwdwBP8/y2A8A6RXroB0FX4REIBAKBQOgXzCeLBg0AnHnPzgDwOYBWACYARwAsk1BF4GUAa+FIy9Ht3LcAwKMAzqFpOujJ+fuzaDaBQCAQCITgEeyC9YoXS6dpugbAdV628ciPSdP0Djg0ZSFLSnhYsLtAIBCCQPG8HIzfdSzY3SAQTmkStGrZeSz9wRxkE2fwikwNQIZIrCJAIBBCnxtSh0jeNl5Lnn0CIdjMiouWtf3c+EF+HS/YGjQioJ3iRKrIECD0DyMi+k8DnRau9brNg6OTJbU1MzbK7XMSa6F2cVLIFDk5Zfj3qGQMI4vlU5InxqZ534jFf0Se8emc55oPokEjBBW1D8UYr0geLPjbygx5DxAA7J2TLb8ThAFHf04216R4145RIpVIP5k0Gs9kpOHukUn4YXqG4HZvTxzl9vnDnNE4w89VO8GTBK3a9fe/Rycjf25OEHtD8IaWUr7K7wtZwzFII28WUYv048spY73uTzRohKBy+wj36ltjI71X1HohcwSWC6xMUiRoLrgkhmlw5uAY7xsSBjRjo0KiWhsA4KyEGA/xLFGrwZXJg/HRpNFYkhiHZcOH4pGxqa5J/rnM4QCA9Ajh8zh3aBy+nTYuUN0OGgsGB1foPHD6hKAe/2TioqGB1/qOj45QvM0bUhM9FlWnx4ubPMUENCnCz0kVxXkqcL2ElflAISMqHJcOc9eG/VuC2YeigFESBDku2QIPrZqiZK+M5OKLppCgLGKTpdJcm5LgdRtud47MnYjXstOxNDGOd/srkwcjOzoCT45LxTMZabh8mLAmOZBMCMDLT4zrUhKgEtE29gdi2s6TCcY0/2GOQ4MbCCL9nAxfzx7pdZtA3S2Vs+EYtQq6RVNxgRdhUyPSEY2E+SjYedCIgCaTF8ePCHYXFGPnnGzEs0wHgLSVDwXPl9sFQ+NwwdC+F9vkQZEe+73FMQcxaCjgyXHKTEZTYtyPu/80h/l004xMfJgzWpFjEOQxWOMYY/051aVGhGGDiGkS8Jz8VF4m7Gi1Gttmj8f0uGgsGz4Ur09I97OXvvH77PG832soYE8A3AVeGj/S43nnI1IVOCHKlxfVHJkO5Ury71HS/Bu5fDZlDHSLpuLcoXHgKm+GR2j9dnpXAikLrWtkBOBIgRFcmXEgdS4R66sUAY1o0Ahu/DIj0/tGXtgxezy280zizIsS6NNmcYcou5jVP4bz1zblG/Tv54zG+ywBKDVC62G2TI8Iw2us1dc5QxwlWzUUheERYdAtmgrdoqm8x/TG7LhoZEZF4LVs95dmemQ4dIumYlJMFLL6QfPw0aSTWwi8TWBMiPGqhBW3koQ7BYUZcdHQLZrqcur/G+elEQo6mUUJnqb9eI2aZ0t3ErSe28Rq1LznFBtg7TRD3hkTJW87RCQqduKgCFQumOz2nS/K1/7U2HK5c2SS9414YGsq53HMygdPn4hvpo3DjNgojIsKx4VD+TW93pCjFLqRR9BSUcD/pQ8T3W/pkFjR33NnZ0nvBIBbnfMO9456k5/EfMikKBItRIN28hGt9v2yJvJEJzGCi27RVLyUNcLte75tM6Mj3JLqvuF8QS4aEovfZzkeDOZX7hhlvxyeElCxqykKE6Idmqo12SPd+sEezty2KQq4MrnP9HRf+jDoFk31qrngsmWmpxD74/QM7JgzXnRAjw4hH6j+IoyiXAKLv+gWTcWTImYXb/6LvvTirz5ESVafOcXt89XOMffYuFSXFpUGEMl6Tv1x7BdbVNw2YijOEzCZAkAEJ4p6kFqF4vmTvC5UCudN8hCWYzVqlyCTyBKASuZP9nsMSNlbznN8x4ihKJrn6eh/Q+oQbJ01HpFqleve6xZNlaTt4HKRjxG27wlo+uXg6xuAfZuyB0XiE+eCL4M1d22YkYldc7LxXs5onxa0UkWOUZFheD7L02KkBoX/jEnxWPCwGaRRiwZ/jY+OxFsiGugCThDIDKc2lBljzDnQXs4mTmSxQ0kxcRIN2sDDm8Psq+M9NQbbZvGvGCq4K0WIh/9e54PqmNGKqdA3cZ+VEOs6HpthYVqUzp+EmjMnQ4yM6AhULJiMK5L5fX34fEbEtHVySAoTDkQIoJVFEqGglWFzVUqCrJdb/cIpXrfhG8v/GjUMn08ZI6tvUniDZxIfFqbBY2NTATj8o9i+OlwTNwAsH5OCygWTEa1Wo6zXCADY1qZHmFM4CldRWCchoksuQ8M0eHxsqkv4Y6e0CXPek7mcueQqgedJChcOjXeNPy3nQfD3PSMkfDGCQ4xaJUsIVFOeM0RWdARWOwMxAOD1Cemocs6PaopCiYR5iQ2f9ofLOJ5F24UyBbu6M6fgf5xx6us8xPX1W5IYh+J5ObwWEbkw0fejIqWluzlniGNhwU1pwpzbX0V8MLUUJbggnhbjeL+NEVkwR7EWTxULJrvyn8m9rIlhWlQsmIzaM6eIptwA+Bf+JM3GAGStFzNWaoSnACEU3RjF0bapAKyfOg7JIkJIyfxJOM6z+mTDHlbsMZYUrsWfZ0zAirEpAABuTmaKAmI0atfLi8vRuX1mDG7fvcGdkqWUziqbP8ljpT0sXIs/TsvG4dMnYNusLBSzfg+2MzMAFHq5N/3JcxnDPUwlYkgxC3G1Psx3UsZD5YLJ2DQj06X94fNVZMMnGMRq1C7n3yi1CrekJeLg6RPw8/QMbORxEVBRlEtb1miyuP1WNC8HBXNzoFFYsi+cl4N9p2VDRVFYNjwRv87MROG8HNezG+Y83pUcgexpHx3Dl49OxsNjUlyfPRdDfc/a3PhBbs+MFISujoaiUDQvB3+eMVFwzuBDq/IU0MJVlNv9VlMUIlhjKlZkXuKDbyyfxTEpz3e6YaxiCYZy0agoxHI0NVLnIa75mW8Yxms1otrJHbPHuxz3U8K12CkgzN2cNhQHT5+AyTHe83+NiAhzLYK4MNeVT3Y5KyEG22ePd9NOc5kR5zj+5JgoQcVFpFqF3NlZKJqXwzuv0Jz/hXynKTjmCK2Kwj0jh2HXHGFBV01RKJ0/ye07okEbgESr1cidnYVzEz3t7BunZyCNVRKKWaGJqVrZUJRjQM2ME36IYjVqxHnJbO4moDk/MQ9/SniY6yGzcQYgd1LjOh0PFREcgT7fknSeVRp3ipFSsGOQRo3BWo2H0+3IyHCkRoQhe1CkW5Z3f96zM2KjPCbMeV5MXzk8AsZgL/f65fEjsH6q8hobPjQqCv+bMMptInx7oqdW6r2JozzMCnJIDte6tEIMfC+LSLUKU2Oj8MjYVGyZmYmJPBqvtyak49eZmW6LAbc2VCp3U7rTh3FmXLRXAZM7PgZrNRgk8dmUQ4JWg2i12tW/KTFRiFSrXM8uM264fjByzITDnYl/bxs+FPemD4OKRyvFwH6ZxmhUsisjCD1XFNyv4VCntsWbr2K4ivIwMYVT8l5HvkSzjnSa4S9JisevMzOxMiMNv8zIxE1pibLbAuAmFDOo4Hm9hCLYUznlA32ZvjKjI1zzblZUBDJEhJXhEWGC2tQjZ0x0aTDPiB8kuGhh7lIcjx/kuxNH8fr67j8tGwVzc7BlZiYeZyWbzRZZoI2PjsRgzjhlesQ9hwUCaZrYZ6BRURgX5d63/adlu1wzotQqxGjU2D1nPNZNGYtwFRX0IAGSjtlHxkdHIty5mntqnCNX0sy4aEyJiUKzc5WeqNXgu2njUG0wi9q7v582Dpf8WQagT8v0dEYafm7pdKmD5cI2N8Q4XxR8pkH2C43PyVdMDc3HnPhB+HTyGCwYPAj/Pl7r9hv3eZdTfD4jWlo/fJXP0iPC8OP0DCw+cBxdViPOHByD7e16DBPJ63Zj6hBQAI51G1zf1ZssoCgKM2KjcKirl3e/a5ITQFEUnslIwyOl9T72WDpRapXbRMjnoM026/w0PQMXHS4VbI87lD+eNBpLhsSCoih8mDMaNGgM0WowNioCQ8I0qDSYPNrQqihMYo3tm9IS8WH9CQDAJV7SV4yKCndN0HI1poFK17BtVhavZlGIjyaNRkG30SXEAZ4a6fwzJmJt/Qn8t7qJt41bhiciPTLMde2BvoWZigJ+n5XlapPtTuDtqbsmJQF3jEhChIqC3ubYcxhr7jhzcAzuGDkUV+dXCDrv8/nSsknQajzuRIzMYIacmEgU9hhl7RPrvB7pkeGY4hx/0yRklGfYPDMTCVoNbjlWiXy9gdcysm7qWI9zmxwThSKevnIXyP6OTikzKjul0ceTRuPGo5UAHNaVv6U5xtTsOOGFKbOImMgjXEVzFjsHT5+ANosV6U4hyFu5xPcmjnKr1CEVb75oQqRHhmPzrEwc6ux1pY4aGxWBsVER0FJU0NNsEAHND5h7lxwehr+wXnDMpEXDoXES0joxL8rTWFoaRlWeEh6Gtyem++y8PC4qAlclJ+BvqUMwLTYKL2WNwOU8FQAStBrXcbxpx6Sy2BnB81zGcJwRPwj3Fdfybidn6F80NB63odqrn4s3DcSXU8bg6vwKj+//Omww1BTlSjvyxLhUHO024PzEOHzT1M7bVvagSBznTLq72vX4e1oiPpk8BhOcxbU/mTQaw8K1aDFbMTYq3PUyvWBonM8C2g2pQ1BnNGNbm172vt5eAnLr3Z3DcoI/V2ZkGfN+mjwoEjtnj0cDxwTJx8tZI7DeeU/km9kDg5gmgI84rQZncEzPuRxzz7BwLZaPSXEJaD9Nz0C7xer6XUVRbtce6JuT1KAwgdUnOUWmX+HxoX1iXBqmxkSBhsOXqURAMGoxO/pnYQkeyWFa6Mzu9/X8xDj02ty9UOVqMp/LGI51Ov5nk49Lhw3G8jEpSI8MF62GIgZjHvxpega+1rXjMudigq09TtBqQFEU1uaMwl1FNei12XH7iKH4StcGADg7IRZb27oAeJoJLT5qbOTEUMyNH4ThEVrcPyrZY/wAwMIE8QhMOWnUhkeEuTS9UkjQajBb5J3HzJ2DnfM0419rEbhsfNdl4/QMt4kgWq3GAp5oai1FNGgDGpfpkPM9s0rnSvUbpmeg0WTBsoIqAO4Dfc+cbOxs17u9cC5O8i8RJju9gVhwgb/HESJao8bVKUPQZbXhiN7gITzZZIx9FUXhxawRXjNHe3tdL0yIxbsTRyEtXItWixU3OFeP9zjD4t+eMArfNrVjfHSE15cunwaQcSpN0GowWKNGu9WGGXHRSODRWok9+zNiHS/DwwJauBeyRkBnsuD7pnY8Ud4AALh1eCLerTsh2KaWomChaUlBA7/MyERJjxG7O/RYp2t3891g7/2DhKz5zPaiEzvlCDwRMs+wGaRR47qUIWizWHHHCN/SGYQiIwWiYN+ckI6MqHA3jaMQNuecwzX1/jw9E2fsL3L7bmVGGh6WuECIUqtwLWsOYV6UQiblOqPZ9ffChBh86RROAIfbAEVRbgPpwdHJss2M0Ro1dswej4NdPbifswi8gGeh8KbTkV9OoNUb2SORFR2BxQdL3L4PU6nc2mH7eTKndd7QeAwrb0ClweyytgDi2h6jQhobFYSDsCiKwsHTpadE4Qac8CdzUQZvU1OUWoVVmcNd6WlcGmKByZSvuekSF6CXJw92aVmDBfFB8wPXapUzCoTs5DPiot1MSWzzzJiocPzNRz+IUOcfI5J4k3rKMXECwPWpQzA2SvwFLsWH56KkeEyPi8YS1uqRcWpNCtfi9pFJoibpvzvvEw3PCYAd9cM0ITTnpoRrcW/6MHzME3RCA9g4IxPDOQEnG6dnuPxekp19ZXg6Yzh2zxmPfwrkYPplRgYeHJ2MmXHRuG2EuI/QtNgoXJWSgNey06FbNNXNd2NkRBj+OTIJe+ZkY44EDe+ihFjcOjwRz2d6huxLGQEf5IzC69kj8ULWcHwx2REpqlVRuH9Usqgz8kDhuczhoj6Jlw4bLEk4A/oWPdw5aUxUOBZy/HRuZvmJectrxSU7OgJ3jkjCu5yUFEyKiktYiz6bwF1mFrIaCrh/VDLvIsYbmdERuJanuotSVR4uS05ATkwUHhubKpr4mKIoXt8r5tlXUcDGGRl4ZEyK62qkR4ThnvS+Z1VLUYK+alJhhL/NPBGJvqaF+3LKWLfoaL52fpmRiRU8/nhyuG3EUMyWIDzdlJboMpleOmww/p6WiP+M9u/YfDydMRyX+xFVrQREg+YHjP8AVygYrFW7Bo4YSuRRzIgKR6vFKtl8EUoI9fiDnFG4+ViVT22yX9fPy4jMkuOcfW/6MFQZTLhi2GCsrtS5/XY3SzhSCWhSGSiKwkNjUlDKYy5ifB+YF+4b2SOR267HtNgojxXgvenDkBnV5z/x8NhUvFbT7NFmTkwUcpwv+ifHpaHbakOsRo0uq7yxQ1EUHhaI8OJDo6LwdIb4vRC7+ucrWTsw+EG+HnibJ+RgF5iTAOCDSaNxW0EVnmA5aX88aTT2dnTjP2NSMHFQJA509Ug6joqi8Ng4zzFwYVI8dElTYbb36W8mRkfia/SZIpmuKXkr7hqZhDdYY5554l7LHol/FtX43b6UxLN8601GOHWkT4rG9Nho7GzvBgCszhruZuatlZDiRojT4gZhaWIsHnU+lzkxURikVqHbZseoyDBUGcxeWhBmXFQEfp2ZhdIeI56paHBzgXg+czg6rTZMi42S5cvH5uspY/FDc4dP1WTCVSpXjdznM4fjkdJ6vJo9EncXVcNGD/wSYURA8wN2fjE2KopyqdP5uCJ5ML6W4Tshxk5nlOUFh0p8ypEWDObFD8Kujm7MEnig/XkhJ2g1yIgKxyNjUwVrKvpLcrgWXwjkzUpiOQ0zlgFvply+nxlfFCbMe/7gGFwmsJp7yMeV60s8vkb9ja/Ovb5yc1oi3q5tweMyBMyBBLNo5PPmilKr8Mlk91x15yTGufyQLkyKl50DTIgwlcqVRPW9uha33yjO/0qMgEfHpuK8xDhc6AxuYdq8MjlBEQFNCs9kpOHBklqMZpmqaZdGs09Q6HONUU54iFCr8NEk93v7WvZIrKrQ4dmMNNx/vBYZAtaH0+Oj8VcJbi4Z0REex7hRgcXF/IQYzOfxAZPLjWmJrv7cXVTtd3uhwMC3DwSRZcMdg2GqzJUDo45V8uJvmJHJq+pXgqXOdCJKmQ3WTxsH3aKpoqlCFg6O4S2D4w2NisLOOdkBEc7CVRQe4QhDYlMsIzh5K91j53lF3es0OT3kHCvcmqne+OfIJN5yQKc6TOmvO3wsxRPqMKafe0fJM1kGEq4rA6PVULoSk1Dux/5iQUIM9p02wS132wPO5Kjsyg5MCT2+KEglOX9oPHbMGY/5CTE4cPoEwYCa76ZlKCJohSIDW39GNGh+sTAh1qdSG0wEys0+1DUMBtxVU3/wZT/lCZMDt4QQm9GRYag0mJHMChG/JmUIrpEgNHOTEu+Zk+1Kb3Jt6hA352ypPDw2VZYZMtgM9Ik0VIjRqH2uZxsouJHoHho0hYQpmtUQ28QqlaQwjUuQujJ5sKwIUSGuThmCqzlzwJLEONc94sujSFCO4MZg+g8R0IJAtDr0JlGCf9ycNhS3enG8FyJeqzllx8PChFis07UHXJtACB45MVHQLZqK31u7cO2RvhQ3SvsHsdM5eAsm4uMIK1Hza9npeC1b2E1FKUY6NboEZbkmeQg+bWwNeuk/fyECGuGUZk5cNPZ3eneMFjJTTo2NAurBG8FF8M6lwwbj7IQYr5UxCAMfRpvBmDaZl6dSWo7UiDCUzJ8EO03LrpRAOLlYnTUcTzgTyA9kyCgmnNJ8MWUsOq1W0W2Ozp3opHwwBgAAIABJREFUlseIzeXDBmNGbLTsiguEPohwdmrAFcSUDBJg4NbEBBz1VoOcEJ7Qz6gpKiAl3PobMjMSTmmi1CpEqcUzXYtVWKAoighnBIIMuD5oQoWulYJbz5FAGCiQkUsgEAiEgBPptGky9RgpisLXU8bKLpNFIJwqEAGNQCAQCAHnjPhBWJ053FW/EoAi+a8IhJMVIqARCAQCIeBQFHXSlrMjEAIBSVRLIBAIBAKBEGIQAY1AIBAIBAIhxKBopdI4hwAURbUA6I8iXIkATvTDcQjyIfcmtCH3J3Qh9ya0IfcntPH1/qTTNM2b5fykEtD6C4qiDtI0PTPY/SB4Qu5NaEPuT+hC7k1oQ+5PaBOI+0NMnAQCgUAgEAghBhHQCAQCgUAgEEIMIqD5xjvB7gBBEHJvQhtyf0IXcm9CG3J/QhvF7w/xQSMQCAQCgUAIMYgGjUAgEAgEAiHEIAIagUAgEAgEQohBBDQCgUAgEAiEEIMIaAQCgUAgEAghBhHQCAQCgUAgEEIMIqARCAQCgUAghBhEQCMQCAQCgUAIMYiARiAQCAQCgRBiEAGNQCAQCAQCIcQgAhqBQCAQCARCiEEENAKBQCAQCIQQgwhoBAKBQCAQCCEGEdAIBAKBQCAQQgwioBEIBAKBQCCEGERAIxAIBAKBQAgxNMHugJIkJibSo0aNCnY3CAQCgUAgELxy6NChEzRND+X77aQS0EaNGoWDBw8GuxsEAoFAIBAIXqEoqlroN2LiJBAIBAKBQAgxiIBGIBAIBAKBEGIQAY1AIBAIhCBR0qTH4pe3o7PXEuyuEEIMIqARCAQCgRAkXt1airLmbmwvbQl2VwghBhHQCAQCgUAIEpTzf5qmg9qP/mR/RSt2lZ4IdjdCHiKgEU45ypr1uPx/e9Bjsga7KwRCv2K02HDV23tR0NCpaLsrvjuKrw/WKtrmqcDLW0rw85HGYHej37nqnX24/v39we5GyEMENIKi6I0W1LT2Brsboqz65TgOVrdjdxlZwRFOLY7UdWJ/ZRse/6FA0XY/21+DB9YfUbRNOVSd6BmQC67Xtpa6/g6UAs1is6OkSR+YxgkBhQhoBEW55I3dWPDCtmB3g0Ag8EBR3rcZiCx8MRc3rf0j2N3wCxqBkdCe3VCEc17Zgdq20F44EzwhAhpBUcpbeoLdBQKB4IWT0dvpQFV7sLvgF4HSoB2sbgMAdAyAKNHXtpZiXQBN5f/LLcdn+wXzwoYcJ1UlAbnQNA29Xo+uri709vbCZrMFu0sDnnf/kgIAKCoqCnJPhLlpggZXZaRgiO0Eior6b1K30zRsdhpqioJK5anKUKvViIqKQmxsLGJiYkCdrOoOQtDwZ0TVtvVCb7RiQmqsYv0JNM1dRkSEqREboQ12V1DW3I1xSYMEfz+FYgQEeXlLCQDgypkjAtL+6k3FAICrZo5AXbsBoxKjA3IcpThlBTSaptHc3Iyenh4kJCQgOTkZarWavBT9xFLXAQDIHh4f5J4IU3WiB11GC9KHRCMusv8m7mJdF2xWO2wAJnKuD03TsNls6O7uxokTJ2AwGJCUlETGIyEg+BIxOP95h+tC1aoLlO5OwJi9ciuSYsLxx4rFQe3HD3n1uPfLPLz/t5k4O3sY7zZEPus/Vm4sxge7K7H3obOQEhcZ7O4IcsqaOPV6PXp6epCeno74+HhoNBryMiQEFLPVLvgbRVHQaDSIj49Heno6enp6oNcTx16CsjBT3KkgDBgtDotIs97kcxuvbCnBqOUbYLU5nt03c8vwW2GT7HYKG7oAACVN3YLbnEppNvqLfRWtuO/LP2Gzu1/bPeWOALH2nj6zb7fJinu//BPtPeZ+7aMYp6yA1tXVhYSEBKjV6mB3hTCAsFjtMFkCawpXq9VISEhAV1eX5H3qOwyw28kEH2qYrXY0dRkVbbOx0yA7Urqpy+hcIDgktFCTBXSdRlhswgsYX/h0n/++Rq86oyyPOQWs5zcdx7KPD7KupwOaplHX7v2eiOkAQuyWnBQs/+YIvs9rQHuvGZ0GTx889v34bF81fshrwP+2l/djD8U5ZQW03t5eDBok7A9AIPBRpOvC8Sa9a0UdKAYNGoTeXmkv4YqWbsxd9XtITSwEBw+uz8eclVtFtadyOf2532VFSputdsxZuRUPrM8PyShOo8WG057biuXfHFW03Wc2BM4Pds7Krfi/dXmuz+/trMS81dtwXMev9eYTvpr1Ru8bEfyizakNo2mHawuD2AIllDSZp6yAZrPZiPaM4DNclbnSqNVqyUErde0GAMDe8tZAdongA78WOMxhSmuHvHGouh1rnNof5tibC/pMc1JH787SFnywq1KRPllsdjzy/VHoOt0FE5OV6Z/O72Oc88p2jFq+QZI2Sw58L+0NRxpR196Luz4/jGc3OoRBb6ks2PJxW4BNacW6LqzeVMwrjOQeb8aHu5W5r1L4728lyKvt8Pj+WL1wwmS7ncaTPxWgurUHb28vx76KvvltS2GTrGhMKSlMQnHxcsoGCQAgPmeEkEXO2GSmHjKclcNis6PbaMXg6DC/2gnWPbnsf3sAAPecneHWF6HuGC02mKx2j6CZG9535Ba7ed5ov/rTojfhSF0HPt1Xg8YOI96/aZbrN7UzotmmgOaC8fGat7p/cjFKPQ6fgEdx7kZbrxlmqx1hGmX0Jle9vQ+dBgtGJHg6wd+09oDj/7n+3Vep/Pe3Uvz3t1KPAJOL39iN8pXn8+5TpOvC2t1V+KOyDQVOEzOz/60fHwQAXDcnXfS4zDzKvfx8z2U/r6Ekccpq0AiEk4VQUsmfLPzfV3mY9vSWYHfDbwTHBuf7C9fswpQnNwekD/UdBsx69jes+b1MoCuOvlh91Er3x/hX6ghiAvuqX4rxzy/+VOhIjrQ+gKcgGEqIWSKY26rE7aVp92vP1yaTgqPLEDoVKYiARiD4gsCcZ7HZ0dBh6FehqU+DFroT8UBD6fqIwRKhbXZ34w4zRvLrOt1qZ5Y1C0cX+ktjh8MEz5i4uMOUeUfzvaxr23oxavkGrO1HcxwAWG12XPn2XtdnqY/z6k3FaHCeLwDk13bgnR3leHentP5vUsDMyyUQFQoOVbeJ3hOz1Y4nfypAR29wIyKZsWYXuIF8U6beFDoJfYmARlCcA3t3gaIo17+bbropqP3Jzc1168+/774tYMdq6DDgRLcJeqPV49hTRgzGo/93p/IHdc49RDxTHn8FbSXvSZfRItv30WKjXedAcfrja+1Mv68J960oIqCd/dJ2AMCTPxW6fW+02FxpNKR0p9csTyuys/QE/qhs8+ykF0qbu920YBe/sRsrNxa7Phstdpisjn4Hej3Fbd5qt6NboXqll/1vr8c9YajvMOCn/Aas3V2FJ38q9Lj2Qn1gros3uozuAhRfdCYX7t1jBLbGDiM6DZaQtUIQAY1AUJBgPOfMCpko0E5ejBYbJj+xGU//zP9S5MKMBbPNjlDLvsIdpmIaHrOAY9AZq37H+Ec3ST7mhMd+lbwtAGjUvj9MFpEL/vKWEix6IdfntuXACMJ25yW898s85Dwu7zrIZePRRsxd9Tv+9XU+AOC7P+s9rr1QH/6yZrfr73yegAIA+PZwHSY/0WeK/+VoI6Y8uRmHqvkrwjB3kZuCqNSpMf77hwcw5cnNWLu7SvCcggkR0AinLKEuz/SYrPizRnopqkCcz+YCHbYWyU/M+cGuSsGUAwMJpQRuf1foBrNDu/Ddn/Wu7749XIezXsrlzX+nVTmm9kPVbS71QY/Z5iHEc+/RF3/UeO2L3FPhHvNEtwkvbz7uuia+CJDsCMi3d1RI2uedHdLT0HCvi5ILrwZnFKvY87rpmA6bjjXiuV+KfNZ6ca97jYxi6UaLDc9tLHKNO6lsLWoW/V0oPVGz3ojjTX3X/OI3dvNut+14i9vnPc7I9Ve3lmLTMWHz8Bd/1Ij64m1hJR+uaOnBx3urRCNM+wsioJ0C0DQNu93xL1RVucGCuTb+YKcDc13bey3465t7vG7HHNqX0zBb7aI53f7xySHc8tFB2e0+9XMhzn11h/wOhRj+3lUhv0C7nYbRYoPBbEOPyQq9F/OlWk259mO4f10+Klp6cJhHiNc6t7/5w4OC/jcAsPS/7vfooW+l5yLTGy0e6UO4Y8loscFqcz/+4ZoOvPZ7GQ7XOLQkBlbiZ7nPUY/J6nLu9sbKjcUwW+3oNFi8PvPcHGq+jAOjHwmtb//0EG7/9DDe3l6BN7bxB1ewj+Pr/CM05j7cU4W3d1TgHYnCL4M3Lb6Qj90DX0sztx/XuSfvZo63o6QFt396iKc/jg3ezJUunBfr9HjshwJcuGaX5H0CBRHQTgFOdJtwrKETxxo6Za2i1qxZgxtvvBHTpk1DWloaIiMjER4ejpSUFCxevBivv/46TCbfy6gUFhbi3nvvxbRp0zB48GCEhYUhOTkZp512Gh5++GF0d3s6LhcUFODuu+9GTk4OYmNjXfssXboU7733nuT+9Pb24NmnnsDYcZmIiIxAUlISrr/+etTW1gruU1BQgJWPPIBLzz4dQxP6+jtv4WI898obfl0Lf2Dm5u0lLeIb8pD5yC8Bm4hOhrWAv4K30P4rNxZh/KObkP3YJkx8/FdMemKzaASfihJORcH3jtWoVazflb8Rx+o7MemJzchY8Yvb92zNR3uPGeMf3YSr3tnH2wZN09hW3Iy5q353ffevdflej802Z02UabJ7a3s5pjy5GXd+dljWfr4gxwTrKy16E8Y/ugnv7pQnSDHctPYP3u8tztx0ZmcuxrJmPUYt34BRyzf41lGmXYHFoIFHmGXMjoWNfUIZV6D0ZjUIdSuJNyQJaBRFjaMo6l2KogooirJTFEVTFGXlbDOZoqg3KYo6QlFUG0VR3c6//0NRVLjE49Ai/0Km+rbZakdhQyf0RkvAkw36Ak3TaO4yulazHb19TpRSHCoZHnroIXzyySfIy8tDQ0MDjEYjzGYzdDodtm7dinvuuQezZ89GRwe/v4AYTzzxBCZPnozXXnsNeXl56OjogMViQVNTE/bv34/nnnsOJ06ccNtn9erVmDJlCt544w0UFBRAr9e79tm8eTNuvfVWzJo1C1VVVaLH1ukacN2FZ+P5VStRWVEGi9mMlpYWfPbZZ5g7dy6qG5pxotuE8uZuGJwOrsyxv/roPZSXFLsde++O37HiX/dg+oyZKC13TJQOzYFd8fHxy9FGvJlbhgXPb3Nlp+d7/RotNry8pURSBvtiAVOkXPNGqGK301iztdSnGntKiTZMO2arHS9vKcFHe6s8ttlw1DNydOPRRhyoanMJenwaDz6thZYloCktntGAW9LRn480uP5m8lW9t7PCzRzLh95kxd8/POD23bci+7z+eylau004LOBvJIXvne1vKtDh5S0lblqurUVN2F12gne/QCw2pPqMfnWgFmu2lmLTsUaPZL5M0t8f8hpA0zTe2l6O5i4jaJp2zfv1rKhSwH3RsLOU/3y5fRNKgv3qb6VuY3L9oTrRc/mfDE3WN4c92+LeBjmR676YitnVB4KBVA1aDoBlACZAWCg9H8AdACYBGAwg2vn3KgDf+9fN0KJY1wWrnUbliR6PjNVSVty00yRGB8g01mO2QddlRF27eLoHKceOjY3FzJkzsWTJElx88cVYuHAh4uLiXL8fOXIEjz32mKz+vfTSS3jyySfdMuUnJA7FnHlnYunSpRg6dKhH/z7++GMsX77cbZ9JkyZh8eLFiI/vk92PHj2K8847T1SbtXv7NlSUHkf2hAmYedpcaDR9+Zpra2vxwiuvoaHDgB6zFaXN3bzHzsnxPHZhwTHcdv3lMJtM0HUZoes0ol0kzJx7/6WMhzs+O4znNx1HTVsvvjpQ43GdGP6XW47XtpbiEz/qEb6Z22daafGj4HSgkBrRuK+iFS9tKcHD3x2VZOZnr/L9fTy5iTI/3VeN17aWwmKT1vCdnx3GFW/tdb2YpGjDuGZGb/v4UhWDvcfdn7tr/pr1RjyzoQhPeQloWP2LNNMkw4ubS/Cvr/P9ShvBvhavbS11Exhu+eggrntvv89tM1DwT/PKvR9tPWa8tKUEt396GP/4xN2Mx5ZPjjfpseqXYtz9+Z8uJ3g++G43+7mw22lXTjpv7hOv/FYiy0dVqFi8e8SsMN4uq4eGjXV9nv9VeLwJjanL39rL+31/IbWSQD2AlQD2AngUwGyebWgA3wB4GcCfAGYB+BFAHIBzKYqaRdP0AZ79+FhE03SuxG0DwpM/FaCwgb9YdQ9HEo8Od1xGm9OvJDJM7TJJ8GGyOvwyVBQFO2hEhylT0GFCaiwev2ii60HrMlpwtL4TkVrPkladvWZUt/Uic1gMInh+B4C13/6CcVkTMGn4YDeTSXd3NyZPnozKSkcenHXr1uG1116T1MfOzk488cQTbt/dd999uP6eh6ANC8Pk4fGw2Wz46IuvUdtNY6SdBgUaDz30kNs+r7zyCu677z4AQHNzMxYtWoTCQscLobi4GGvXrsXtt98u2I+7H1iBZ598HFWtPfjx6y/w6P196S/2796Of9z7bwCA3W73OPYDj6/EM488iDCNGhU19ViyZDEqShwPf2VZCb5f9xmuvOFmtHnJAdTUZUSz3oSctDioKAr17Qa09Zoxebg0ZbFJTIPmDFn3pwYktxh0KLHhSCPu+vwwtv7rTIwdKl5Tl3nZ6I1WjHl4I66aOQKrL5/Mu+3e8lZc826fSU6xHFLOZkw+3g+pfoZFjV0479WdvPsKMfbhjTL7Qos2KnWoCGluf8pvwEVTUnl/6+i14HWBhLdS4F4/PtMaH3LHv7TN+d8Rcu8HczzG16/bZBUVyvkE8jEPb8TZ45Pw/k2zMIbn+GLn72/Zu6Yuo/eNJPQDcFy7P1acjaSYCI/fek3yLQJdMixOgUCSBo2m6QM0Ta+gafpnAAaBzd6gafpymqb30DRtoGl6B4BPWL+P87ezoQyNPqdQK2sFwgfzINlpmvftaqdpt0Evt46flFU2Y+pk+mww2zySCiYOHYa3//s85s37f/bOPDxqqvvj39vpRjdKaaGUUlqg7Dtlk30XUVFBBFcEcUFF3HBX3FHcX8XdF/25vbi8LyoqCorgggoq+w5lX0opLYXuze+PTGaSTJJJMplJpj2f5+nTSXJz701yc3PuOeeeOwBpaWmIjo4GYwyJiYke4QwAjh49iqIidbOD+EO/bNkyiW9Z586d8cwzzyAq2rukjsvlQv8R5yC5UQpqajmsXbsWhw55zSg5OTm45ZZb3PWuRnRCso8Q9dVXXwEAKqpqfF6yZhnNcfXM2cgv5NXXQ0aeLTlecNRrRti8/h9J2c2zWuKy6V7BLzYpBdNvnC05f+VyfX4xhaXCQr788/In0KkRLNnpULH/jvNA0RldM/+s5uuNvDlwk8ogSswcd7yvn93mq/+s2S8J0ipm5Q7jfnxKcByHN1fu9phVAg2FIpjKtT6GldW1uEZhQoe4fVg2K9WabBS567P1eHXFLrz+k685rKqmFiXl5mN5yfvG2loOn609IAnUe7zUV1v82JIt+EbBBK2G3cMZrRmLK7Ypz7RcvtV3P6dxTEBNK6aXvYX6/aJ9TZy+afZJ8vMm0BpsqS64YfOTtGwtTo7jlJ6SWIzVdkiQ8onb5+wkgBUAHuQ4bov2Kdby0HmdVI+tPyD1ueqamYz9J874mLPUNCFK5ysd75qZ7NF0NY6PRvNGcbrqfvik/hGJwI5j/Gg2OY4XlDZv3owJIwej6IS+BbhLSkrQqFEjxWNijePu3VJn1gEDBoBFaI8T5D5lnTp18piOBFV+ly5dJGkEAXLHsVIUyDrcDp27SsyaCUlJkuNVld70hw5IhY/Wbdv7+D3ktu8o2T64P3CBRTxSrKqplfgUhYov1x3ym2bKm6ux/0QZzu+W4dEkhwK9cs6+wjM4ojBCv/PT9bg4r4XffM0KNKt3n/AsoB1IPgK3LfpH9ZhQ5w9+3+vjbwRYM0lAok1FcCeAnKmsUZ2ZGeii8/J613LwxOwSuOVj38kaGw4W44YQTCwwi/xxRGi8IHIzqRZC21HzVQN4M+ctI3NVj1vJiPZN8Y5oBQMlQVRtEGOmzdptOAhar88YywVwqXtzOwAjU8VSwQuPqQAmAljNGGtnbQ2tJVA1rxpCrkK/tP7ASRw8WYb1B07icLG3My4+U4n1B05i/YGTqsEdBdYfOInyKj6N2qzOO++8UyKcxcXFYdiwYZgwYQImTJiA1NRUSfrNh8zHjDks+6jsO3FG5gck9yvwfSm3H1XWpCh9nBo1SpFsu1zKJl7FsmUdgtJo22r8ty3v8eIzoVXJn3BrATs9tBQXLeBn8GmZIb5cdwjZdy9RFCTMwHEcvt98FNl3L8EeBYfeqlr1d2H9gZPIvnuJbv8XI8ijogt3xOysMj2mFrnrhYD4HTDbS7W9XzpbU+sZi03EVnMywPYtr7dS//DLTn2DUiPlyMm+ewlGPvdTwOUoaZA2Hy4xNKtz+kJtz6PXFDSZctS0cnowYj5ukiSdb6i46DnHYdGf+5F99xIUng6sf7ZbExoUAY0xlgVgKYA4AKcAXMJxnJ6hz+MAegFIAJANYLF7fxKAe5ROYIxdyxhbwxhbU1BgjXkimBixt4sRq1oL3ULBcZHjdpFGx6XkZ1HuZ1mNn3/2ytMxMTHYtm0bPv/qW3z48X/w6aefonHjxrrrLiYnJ0ey/csvv6DglPSeSE2tnM85mzZt8nmpd2yVOiRnZ2ebqp+c5i1aSrZ3bd/qt+zmmb6aGaOIncj9CWji6hwusUbwMYMQ10oLYWbfVvfU+cLSCnwsM5HuOX4aXyuYk05XVGPhL3vAcZxESP/CremTa6b9IWgFftT4uNgZqFZvX7HGPatRrZmIizYiIKoF6lTxzPCwuyB4M9+OBThZRR7lPxghSBgL7of9nZ/34KftBZpBrBet0Z5NKUbLfAmOX8TdH1pBYv2xv0h/n3VGNghRWkOW43g3BuG3gJlnbbfvreUCmls4WwEgB0ApgHEcx6nr50VwHHc/x3F/cRx3muO4veBnhQr0VjnnDY7j8jiOyxNm/zkZowKaVocazKZTVeUV+CIiIhAbG4t9J85gZ8FpvP7669i2bZupfEeOHIn4+HjP9saNG/Hsow+gqtIrlHEchxXffe3R4PXs2RPNmjXzHN+9ezdefvllz/aJwuN455UXJOWce+65puonp0OXbkhrku7ZPrAvHx8tfFOz7MEjxujKm5P9F7NfNDtYy59Rfr6W70mo0OrTPEuvuNPc9OHfuPvzDRLt18jnflKMU/X411sw98vN+HHbMU8+HKf9jhi9G77LRJp7y+RaXo8GzUCFrnrHG6NKK5yA8AFV+wCZ/cZoxcez2/RjFvls5GAIaMHmka8246p3/tAVxNooWkGrtQhkmbk7PvEf+07gJdkEEaXYj2oDWq2BrtoRu1uHpQIaY6wlvMJZMYBRHMet0jzJe65SXTiV3/UH2TR9JU6eqfRZQDYQTldUo1P3Xp7tsrIydOjQATdNvQQXDO+P66+/3lD8GTHJyck+YTnef2sBRvftjOsuvRBjx47FqLyOuGX6ZThz+jQABpfLhccff1xyzqxZs9Chcxdcd+lFGD+kN3Zt947y2rZti2nTppmqnxyXy4Wb5twv2ffUg3chr2dP9B883Kfslq3a4IJLLveb7/oDJ70fB9mzPV1RLYl0rtWxvPLjTokwEyyn1v1FZZ5AleLYUXpKO1zMn/vtxiOisBP8mYKJWGzSVrteIY5ZWWWt5IMg/Db6rZ2/lB9kaA6CNPL81/IdyL57Cc6TCTKL/zkoEa6M1m3bET4oqNosRzXUmokVJk4xu4+X1pnO+P3VwZngEmq5zypNTxtZ4GEjue4uCGyygFVsP6r83uQbmIwgYLf8rjdQbRRjLJUxlgogSrQ/1f0XIxPOTgAYwXGcojMCY2yFO/hsvmj3DYyx1xljfRhjse78XhUdV16ci0ChhcFQOY5DcVkVbrn7QUTHeO39x48fx6rl32HH1s0477zzMGDAAGN1LK3wOBrPmTMH9957LyJEkwNOHC/A6lUr8O2336LgmFddfrSkHKXlVTj/4kvx6KOPSs7ZumkjVq/6ESXFXtNWx44d8c033yAmRldsZF1ccMlluOnO+yRlb9iw3qfsVm3bY8F7n0jumx6OnarAfpEvoDyYsNao9qXlOyTbHAcsWrMfpQoz3YrPVOEzjUCSy7cclc2A8iIOTKoV2w3w7dQ3HeTNmYvW7Mcyd8wkPS6bR0vKccXbv6OssgbHSsrxjduMIhbOSiuqsfgf/5MZ/PHxH/tQVlnjo4HUquaL7nu/QWYKfF8h9pwRwXmVyZmkah9pTkcaMf6WKJr98T+eAM6EMqGa/RdsjbneZfA+XXsgKL6cZnhsyRbVxdPVcErd5eiddjUAwI+yfS4AQk9yNXifsWz3dgqANTIty8Mcx83VKCMKwLXuPzlHADyms651llDaw7v27I13P/8WC557En//sRrVVZXIyMrG+RMn45lH7seIESMM5XfwZBkiIyrQMYOfMfn4449j8uTJePGVV7Fq5UocOrAP5WVlSElJQXpmS/TuPxCNUlJQdKbSIxBce8sdGD9+PJ549kX88dsvOHLwACorypGU3AhtO3TCFZMnYdq0qxEb6xsDJ1BmzLoDQ0eNxaL/ewdrfv/Vp+yR55yP8ydOQYyJsuUTDeRdrtLyPmr8s/+k6nqKd3y6Dt9vPopOzZPQPj3J5/j0d9fAFcGw64lzfI6ptT2lz4PvpA7+/37JhBT/19T3ieUAgAcXb8Q6kX8ZE5V7//82inI09378svM4FhwoxvqDxWgcH+3/BKEeKt9GxY8mp3HMJ1/fNHo+w2rmOqMatPlLt+GBczuqHt965JRh7R5Rt6mq4RTXhCUCI3Tz4v3zJYAMAKMAZAFIBHAYwDcAHuHPrXtvAAAgAElEQVQ4LvBhclii3qVaNXYSO1dz8AoMHbt2x8sL/4P46EjkpMV7nIZdLhdWrFiBvYWnFZeO6t1/INbt931Zq2trselQMZLjotE8uQG6dOmCx59+TuKX1zUzWdXZu6aWQ5cuXXDPY88oHm+fnoToSF+lsLw+SbFRPibhdfuLPAFj1crP7dAJ9z3xrOIxNXr3H4iCU+U4ZHDWolTroS8doD6TD/A+V600NbUcsu9e4lls20rEs4vlA/PRz6/EhJ6ZeHZSN5/zjp6qwAEDjsRi9JjiheCxh0+W+QhopgZF6vKZabQiw3vKUJ0kwCn+VsOJy9eFG6EaSwfi+6UHI5dxpo4sDeckdAlo7qj+eprCXJ35DVXYtwvAHD3n20kgWiy1D2PRmUo0jI1ChFLwGmHkrTAzKCh9gFKmFnYCNbUcCksr0Dy5geJxvSp1JcqqajwC2skzlUiMjfJzhgwOQVld13A0alkdft5xHGe1aYxMnXHw1Ihym2iF0W5FlbrpVL4U0WNL9Mf00vMElfL47K8DigIavwSWd7usqsa0D6QSMe6VNDYcLIZ8BSYzrVGpZte/vxZD2qbhR60Zc27MRi/XM4tzh46gor/uOo7PFdZBJJwLaTTrJk7SoIUFWtoHOfJwALtUnCj3nziDM/ExaN5IWWgJJapmohCNCOVBZY2wt/A0umYmo6yyBvtOnEFyA2MCWrAu0cwiveKP6pzP1iMmMgLbHhvr9zytWWmRbq1YdQ2HyW+YnwHm7z7Jq6AkSwn11KMZknPffzdibOd0n/1Kl65HjItyD4yOl1ZipWxWmPaMVAa9rebvfSfxt44wJIDXt80oaoNHsYn8bhXzt5ijJRW4bZH+mXWEfYjfLX++g2aw20m+vkMCmkF0rnFsGLUI2ZzqBo/R2E/+MPuRCwUFpyp0LdotfPwrDT+sIKnQLEBpDce/9hX5rLWp9PzKq2rQ/oFvPdtawVuDifjOGnky8ijmZVU1ymbEYLybCnn+5899uOszqaBTcKoCaYn85JBgm53UeH2lcnDSs1/QNZGesAh+sfTQlxuMWOlGwpCQLGc9oV8/pp5RUlaF6tpaU7OeTlkYOkMv8kCORrBiBBej4EMWKpwyWqzSuaD21xt8g0PKL6GwtMJnyabqAEcZuwtKseGA+soRalpYsTbZ7gCQelG6FqXAnRsOiicxOFPIJ0KHHbM47RoYEMGDNGhBpKqmFvmFp5EYG2VK2Npz/LTEVysUr7xSZGa9ZecrLLVjJ2r9ldOdWU+WVSlOdtCDXO556+c9PmnMBqMUuOJtPsZX/rxxiu3Cx8Sp8CQClc8U8zSZl9XvFX0oibqCoSUMw2PMFVaQgGYY31a4+VCxYrR3YZd8XT7zpQX/DdCj2aiuqUWkwuLd/tYAVcLs0leBoBpxPcT1CAZ6Ru6BaEmNkn33EuSkxvvsD5cI7qYmcdogoG0jJ3FHEarmPeaFlUHNP1ze02Ax52x7lwAnE6dRFNqr2lI8VjRt4f2wf1DuvZpgOKMSMkw2Hj39aaAaNDF62qWwjJN4OaeANWg6X4hAhSV5kNdlm48qahXEYUDsMHF+4l57kHAGdog1wZCljCnQ6p4wFxVhr4hUrwW0oPvBWJK9kAmzzUcqPiZ0itZQXKL9wq5/zI5c9WlArbvLdpkV9QTItQJxnl+tP4xr3luDEoVVGh5cvMnyso1gJJgxQeglXHxFg4Xd7gr1VkBzuVyoqQm2Jijwxu2E1yMygmHzIa8JxSsyWo802rw5/N4zlYo7STNYVV2N8mrjT1/P2oIf/Rmc9QcF9PTpC3/19Y0LlDs/XY+P/uCv7Yq3f8eLy3bo0mZpLQuz/mAxusxdisLSChzTMYMYCKxTHzr/R1Pn7Spwlv9nfccOwWbS679Znmc9l89sp94KaHFxcSgtNR6DyUh7tcLVhxNJQ3a9K2cqayTq63KNAKdOwGzneLzUORHUucpybD5m3D/viA6fPqV4XAeKAheMAT70hx5Tx0b3+pxmUROChGWuVu04jueXbQ+oDAB4bcUunCqvxq+7CqEUR9pqzCzoDMAnfhthH0dLKrBdR0DgcEBJM7tuv7WhnQh16q2AlpSUhBMnTgRVi3akmP9YGunX5VocJ45gDhebW3YnVOx3+wOpxftyehgErrYWRUUnsGqvNUKTHgY+ZU5zI+eiBb+izOGzZI3g8QFl+t9jK1c5IMKPgyfLMOFV84GgnYSSq8VeFSuHla4TBE+9ncWZmJiIsrIy7N27FykpKUhISIDL5bK0cy03MXvT1wGZ37Yr+KEWDqsOAGngXqPxWO30t+A4DuBqwVWWo6joBL7cfAIbC5yj0VND6W0xNDXfdLmhF4IUl2IjiDqMUpe4enehYtrvNh8Ncm1Cj92DrXoroDHG0KRJE5w6dQolJSU4duyYLm1aWWUNCnUuJhzBeDNnZARTnekpcJwBZQUNUFFdK4mWfyY2EqfKq1ES7UJBlEt32VZyKtrlEztsy6kGKCytQJlJc+eWU3x8t6MmF8HWg4sZW/mhODICFcdjglonLcqrOWw+Vo5Ve88oCmc7jjovlIJdIm2oZnGu3ef1T/PXWRedrsSmQyVkbiTqDErfmw9/D64PK+Gl3gpoAN/hJiUlISkpSfc5X647hJu/+FtX2ji3YJOTGi8JMaDGJ9f3B8cBMz7wOntOH5iDt3+2dwr9Bd0z8L9/Dkv25c8bh+kL/8RyHYs/K/HD7UPQKi0BY+9eYkUVFUmKjVSccadGv1Yp+Pja7kGtUyCMej64MY+sIiQzcUM0sBVrA/0VOf6VX7DPgkkuBOEU6vtgY+3eE5g+MMe28uu1gGYGIx8foxazi1/7DcPbN5HsC4W5yA6WbTmKpZ+uD2oZRu+cTUtUhjVKQsuM99aEvB7BhoH5FQpJOCOIusXh4tAHUhdDAloQEWbA6NGeCfwg00g5VUDbW3gaxWXm1wp94mvf9Qyt5pQB7RlAUbPNoHTH1mus0ynmx23mtK8AsOGgvjKsYuOhYrRoFBfSMgmCqN+QgGYQI47ktRYIV/5810KBUhWGzF8R8noEmxqOwy87j9tdjXrD1f/+0/S5gYbpMMqrK3ahdZrvklUEQRDBot6G2QgFVmhkahxgd/ti3SG7qxASams57DUZh4pwJlYqRSkYLEEQoYQEtCBihfLLCRq0+sKWI6fq5HpywaKy2v7BA0EQRF2FBDSDhNpNyak+aHWRyupafLep7sXyCRb3/XeD3VXwCwncBEGEKySgORzSoIWWncfqxhItoeA3lYCVgfD894Evz0QQBGEFds8bIwHNIKEekRefMT9TkjBO0RnnR++vy7y4fEfAeazde8Lz2+zalgRBEHZDAppBQi1R/0yzCkOKfMUEIvyY8Ko30PNV7/xhY00Igghn7LZfkYBGEIQp7Fb/EwRB1GVIQDMIfZQIgqe0wlggYIIgCEI/JKARBGGK4rIqMgnXEd6f3hc5qRSIlyCchC4BjTHWhjH2JmNsE2OsljHGMcZ8hs+MMRdj7E7G2DbGWAVj7BBjbAFjLEVvhRhj0xlj6xhj5YyxAsbY+4yxFkYuKpiQAo0giLrGwNxUQ6ukEER9wO53Qu9ST50BXKMj3esApou2mwG4AcBAxlhfjuPKtE5mjN0P4FHRrhgAlwEYwhjrzXHcEZ31DRq0XiNBEHUR6tkIQord33u9Js6DAJ4AcB4AxWlRjLH+8Apn/wWQBuAe93YXALdoFcAYawngQffm7+CFuyvc25kA5uqsa1CxW6ImCIIgCCL42L3Soi4BjeO4PzmOu4/juK8AqGnBLhX9nsdx3HEA8wGcUjiuxEQAUe7fz3Ecd4TjuPcBbHHvm8wYs91n7q7PnB89nSCI+su957Q3dR6NPQlCSrho0PTQU/R7OwBwHFcDYLd7X0fGWIyR82W/GwLICbSSBEEQdZnE2Cj/iRSgZbEIQordgxYrBbRU0e8Shd8uAFqTBfydDwBNzFXNGsi8SRCE04lg5s6rb91btMt2gwzhcOqSBk0NcXdh5mo1z2eMXcsYW8MYW1NQUGAie/3Utw6MIIjwg8GchFbf+jdmUpAl7OObWwaFtLy6JKCJ1yRKEv1OdP+vAVAUwPkA4COBcRz3BsdxeRzH5aWlpemtqylq6lsPRhBE+FGHBI9WacGLzUYCWvjRoVmS/0QWYvcn30oB7S/R77YAHxcNQGv3vs0cx1UYOV/2uxjAnkArGQg1tSSgEQThbMzKHU504fjh9qFByzuCJDTCD2GhQWOMRTHGUhljqfDOtISwz+38/6HolLvdae8EkODe96HovIXuYLfiq/8EQJX7922MsXTG2GUAOrj3fcxxnK2TXh3YfxEO5op+Le2uAlEPcYrg0TWzoc++1y7vqZDSHpxynwjnYvcnX68GbQB482IBgLPc+1yifVM4jvsNwNvuYxe69z/p3t4A4EWtAjiO2wfgEfdmXwCHAbzv3j4IB8RBIxMnYYRuLZLtrkK9YEofxyw04gjMyh1W927dMn3b/9mdm1lcinlIPCP80TQp1tbyrZ4kcB2Au8CHxqgEL2S9CmCov1UEAIDjuMfAr1iwHkAFgELwmreznLCKAJk4CTUaNvANbeBEk1FdpH/rVP+J6hFGNUNX9uc1vUJzvW5IK6ur5EhIgeYskmL1LmwUOqJc9jYSvYFqV3AcxzT+FrrT1XAc9zTHce04jovhOC6D47iZHMedkOU3VThXoay3OY7rxnFcLMdxqRzHXebWrtlOrYMEtNZBdJ4ljDNzaGuffc5pLUR9wqjgISSvb3HQYqNcdleBEHHHmHZ4f3rfgPL4+Np+AZ3fJ1saCSwsVhIgeOx2GBQzpK2tIeEIGS6F4FOkQQsNdJ+tQRh/aoXpaNggCk9P7Kp6vHd2I+SkxuPJi7qYrsf53TIAALFR/OepeXIDQ+fr1cQ8eF5HYxUjgkpkRAQG5gamDU8P0CSZEh8t2bZ70EICmgHIB40wgoMUrrp5dHwnv2nma3yg7cBJAycnwAyq0IT0gqCrFb915Z3DMClP3efvk+vPwo93DMWUPlmmP24vTemB/HnjsPXRsQCA+8d18HOGlPVzx6BVqn8Lw7ldM3Bp3yxTddTLn/eNDGr+hJQG0ca1okmxkXj50h6Kx1qm2GupIgHNAHarO+syalG9R3YID02h0kcxHAUHPTU2KgAEA7HGsobeSwmBriSgGeg2gEf//CXdfPZNH2jv6n0PnmuNFu2O0W3xf9P7+OxX0qwbYfGNA/ymkWt9lEiOM7f8FwCkJkTj+1sH45mLfZ+flQjdip5rVqNRXDRemtIDb1+VZ6BcptrmH9YxYA0mJKAZQPzBbdMkQSNl8Lk4LzOk5aUlai2jGjgxkcpNsW3TRMX9TkOpPYShfKZrIoyd4tmANo0BAPHRLkzsxb8D/nxDO4Y4uKXd9MnRWlFPHaF/05IpApHNL+zh22c9YJGAZBar/NBuGp6L/q0aS/bdPqqtaWFZQM9McD0m/rGd0yXb2Y3jdNdhzf2jkNs00fPuaTG6Y1Pd+coRbpX4mpUG7hN7ZWJIW+Wg9FEuhvO7ZWBEB/31ED8jefu220+RBDQDiD9eH14TmDNjoIQ6onKwP8o5YT7pISEmEvnzxkn2mfmYbXx4DBJtnM1UXeO/s4+wsdcQ6ldSXg2X+wb701TaPRNLiwWXaccFWzp7sOE8myTG+rTFy/v5N+UJ3ZtVgzGzS07JUZoh7UTEmuX8eeNw84hcRBiU0C7uFZyBt3hm7/SBOaZCAOnRBmZrmJbvOru957e8fQLK/aXSu/vMxd3w7jRfbSWfh/E21zrNXmWLFiSgGUD8IXCCmSeUaF3uRFmnYma9tIfOC1yV/MVNA3DnmHYAeIHJSjIbeR2Vv7xpoK5zjHygGsVF4d9X90ZCTKSnM/3q5oFYdF1/XKLh82M1lTrshVrXNa5LYHGutJzLL++XhaMl5Z5tQVD06xvq4Hc1ggHLbx+CqWdl+xx77fJeaJeeiJEGtAFqaN0i4fYImsjzuzVXT+v+/92txgVHgbeulJqffrxjKP478yyV1MBZbVIVzaNibh7eRrrDwCNfOnsw+uSkYNltQ/SfpBOXrO3Jfd6m9MnC61f0wr3ntIcaS2YNxBtX9FI9rkdR7y/0ylc3D8Tgtml45dKe+NcUZX+sJomxisGHBS7oniERwuT4W5s+UIE+14RV66r+LfH21N6Kx368Y2hA9bECEtAMILakBOpbYJZZI3KRaFD4mNy7BW4c5hsGQkzbptqNe/bItqrHzmotVX3LtXuDVdTRYuJMOHfK6ZqZ7DE1drc4SOzojl4TQReNTkqMHrlgkHvWUqO4aAxrx/vbCZ1cu/RE9MlJQZYBcwQAXaYINar0CGga1zWgjflZWEPapuGC7urCQZfmDTGlj/cDJzirDwygTCto4tY4TT0rG+3TjZnkIxhD67QEzD3fd4ByttssJTdPAUA7t+lfSbBTQhhEab3nHhNnBJDXshEAb4w0AWFg2rZpot/2PUFFGzSknbQ/yEmNR4+sRmjWMBbTBij7pF3YI1NzssCEnnxZgvbvlhG5kuPfzh6E20Yp92Ht0hOx6Lr+im4KjQz4bindDrlgdMMQaT983eBWGNMpHckN1P3IOmU0xOhO6RITqt7n7q2HdPvSPlJBsXPzhnhvWh+M69oM57ln0SoxVhRoWO4f/MLkHprfRcHsqJamf2vffuvuc/RPEDlSXC7Z1vpWpsRHY+bQ1nh4fGc0bBDlacvigUyOjokmwYYENAOITZx2jclvG9UWGx4eY+iceRO64s4x6iMbAFh0XX/J9jBZJ3pRT+UPZ4+sZDROUDeJ5M8bh/em9fEd4crQ4+iqB+G5xEZF4J2p0pH6tYOVA3A+caGv1kY+C8zMjDR5G1n30GjJ9suX9vB8mMW5X9o3C/nzxiHKPeQ0Gng0ISZS0WFZD1U1tYrmBwHGtOtzqrxK9Zg/3p3WBw2iXT4jYeGjmxgbhetEH7geWY2QP28cWjYOvCMVDxDkjuv+tLGCn2RKfLSqpkrNSdvos501Ihf588Z5PiiX9G6B/HnjPM9MTaAQ7tV3t/pqiVLd76/QvYnrJP9YR4o+rnueVG8ngHSQpOZjKua3e0Zohr64ZlArn7YpXLt8gDe+e3PPsfx549A+PcmU68B94wLzkRO7A+x+4hyf48KtTnKbcVN1mpfFz0hLOzooNxX588b5mFr7tmqs+Z6rES16jm9d1Vsxj3O7eoW4xy7o7BGSchrHI3/eOOxSuA/jujRDixTfgegV/Vqq1lMuQMmvUfhWit8Pgb8eGIU5Im1fUix//5skBdfX2igkoBlA7utit4OrMMoV+OrmgYgXdVRx0S6svmeErryS46LRM8vboerREKYmxOCjGf0wODcV8yd2xcA2qbrLE3PjsNaqS2poiUU3Dmvt4y/jDRngm36WbFQNAE9P6IrJvaUmxG9uGeQxmwn3JEqmn/9ohv+AiPJvr9I9jdDhR6X0KL6eNUjT1KqkVRI7jz89sSuGtvPVbFYp+KCNaN8Ef9w7Ai9f2gOfXn+WpubksGwUawb5x3bVnGGYP7GrR5O0dPZgfHJ9f6VTVfnq5oG4Z6zyIOXFyd3xwiXdPds1tRw+u6E/bhrGDyr65KT4CPti3p3WB09P7Iobhrb2EeSbJMbghUu6Y8ksZbO/Hn8+pfsttBfxsX9f3Rtficr58Y6hyEmNx/9ks+I+u6E/zu6Ujo9m9MO1g1t5Bi7eSQJMchUvTvbeG6MC5Xe3DsbNw9tg+e1ewdCuwe3EXpmY5J5cJR8sBYKW+VVs4mTM9z0XzHpjOjXF/IldMXukbx8lIG5b4scg71dWzRnm+S34V1m17qgeQVsMB+CDGX3x/CXdVP3xnpvUDfMvNh66R34v2wUwoWxAm8Z49uJuuNeAxi4UkIBmAHmD6JzBm/LEo8rh7UMXFkI8k2VQbio6N28ocf5cNWcY0hsqCz7Cx0fMrSITgPyFjlT4kqy5fyRio1xgjOHivBZ4/5q+nvKm9MnS5QfWKi1eU7t3didf847A6I7p+ONeqUAo+EgoxTdSmhE0qXcLREQwXOZO/8C5HdGhWZLHFNHXbVaQn6ukjldCLCjFRkZIpvX3yGrkaTtV1eqmRaW+tWNGkupMYgbm4yOZlRIn0ZJOymvh4x8DKM+IfHtqbzRJisW5XTPQq2Uj9Mxq5JNGQM8zF8xRao6+4hqkJ8UiNsqFi/NaeK6pXXoiessift82qq1qkEoG3oTTKUPZND2+e3MkiLQrtRyHXi1TcLl7sfsr+rXE8PbKfmCD26bBFcEwKa+FjxAPACvnDMMFPZqrBltV82X1Nxvu2sF8+xTnO6xdE8l2Tmo8frxjqI+5v1fLFLx2RS/0b90Y957TwVNvT5gN8aw28PdHwKhrR9umibh9dDtkNvJqR+zy302MjcLTE7shf9443RMP1GZICvf0sxvO8sxOVboseT8qf71SE6Pd5/J9aEykuquH2hhOeCbCuyfWRAlWH/Fz03P3Zwzitch9ZTOCow0KaADveqI0g1fgop6ZiIvW7jcG5ab6uA/IzcX+6ia44iit3csYw4RembbP2pTjvMWvHIzYxBkRwTxalrzsRli9m1/NKtJPByaoWrPvXuK3vHZNE7H01sGqaQW1+H3ndMAM9yhYbG7Ucp6+Y0w7vPzjTsk+NR+7zs2TDHfMT17UReLwLT+7T06Kj1lVCbHA2TotHstvH4rz/vUzNhwsBmO+nX3TJO8Mtt92Fequ7+MXdsFjF3T25De5TxYm98nC2z/vAQA0TtBngo2MYKh238iEmCi8L5vtO21gDqaJTGiCSTA5Tj1/tdGvmvZFKflK0ahaQElrp2dx4AyZsNG9RbJHS/Pc99v9nv/4hZ3x7CR1rYO4Wk1VBhhyZo3Ixc3D2yDnnq9V0wjXO6VPFkZ1bIJpC9eICvX+FN7z9Ia+syHlNJFpcJsmxWL70VKP9sofas/2jSuVNXZClPyJvTJ9JucESrPkWOwtPANXBEOaux+Rf7CscL0NhngW6RYyA40kD/BaogqNAROg7YfZTNRmxVojxpinbbVKi8cPtw81VC+13jzKXcZNw9vgepnQoqRp1cN94zri7rEdfPr9BjoEmMZidxWLYg39n8ISUEIfvXp3ISa/sVpVGSHwoQ6rh0Cqzv4+2JCAZoDG8TG4qEdzZCQ3QMMGUZ7AteJGLP79xIVdEBnBkJHcAJe//btm3ivvHIbB83+U7BNU2h9c0xeXveV7/mV9sxDB+IYq8PiFnfHlukMA9AfWFdYvq5UJoJ7fsrf7wxl9PTZ7o1zaNwtHi8sxXyHo4fOXdMOt/1nns3/lncMw/7ttHidhvf5g/Vql4MmLuuCezzfoOk9pZH9l/5aIdjFM6ZOFh7/c7LfM5bcPwYaDxTh5pkrRuVtOYmwU/jWlh49GyF+9AN8ZYnKevKgLPv5zP55XEYbEd2PGoBw0SYzF1AHZkjRas8cEJAMXhSq9N60PIl0MLyzbgSv7t1QcpYonmpyurAbAfwzevVp5hpUSjDG8cUUvrD9QjPKqGrzlFq6F2zQoNxWPXdAZE3pmepYREhDfC3+h4L6eNQg7C0qx8Jc9Pv6LL03ugR+2HtPtYCy+Xy9f2gMvLNuBuRozmo06hxvhP9f2x5q9JxDlisDTF3fF8PZN0Lm5VOsob4vvT+8LxoDL3vpd0wxsJUtnD8aYF1ZK9qXER+PFyd1xVuvAJoy8cUUvtE9PwsJf89E7uxFOVVRLjq+4Yyh2HCvFghU7fc5ljOGVS3uiZ0v1CUqCwKT17t4/rgP2nziDQbkyFwSVdhmpoLmd3LsFPv5zv8RsrcR70/qoCjZKg/LBbdMwrkszSXzKJbMGorjM63t647A2ePe3vVpVBsD3lfsKzyge++wGbVcKMX1zUvDEhV0wvrv65AYjvHpZT3S1eJKZWUhAM0B6w1g8J/JVqXZLQC6RKmN89+b4ZuMRDG2XpnsZkXUPjkZDBefeq9ydsdrMuEhXBK7ony3ZlxQbhQfO7YhHv9qsW43fy+3L1r6Z96W7ol9LLFl/2PMb4IWr1bsLTXWCIzo0xUs/7MTk3i3QNVO58V/YI1NRQMtqHCeZ+n1l/2zM+XQ9shScSsUwxgtWBacq8Nz32xXNtP6IEt3jnNR4VUdjIfBjy8bxhp3WtWZNAVIz6XVDWuH1n3YDUDc3CSbEKX2yJLMe5UzKa4EV2woAAJf3a6lY79EqJuZRHZvi+81HAXjbB6A8VV6YxavUbto1TcS2o6dwk2gSydSzsvHg4k1Y+8BIv6YPpfqO7pSOl5bv8Oy7rC9fP8aYx2wplLPw13wAQK5odqNaqJDe2Y2QEh+NjhlJ6JiR5FkzUkyj+GjV2YtikmIjUVJeLfGbObdrBs7t6punYFL+99W9FT/GVpHeMNZTflJsFCb19h/eRVg70YjDeaAWznYqM2XHa8wA1ovQ3oXJCnuOnwYAtE9PxNYjp5CdGo/s1HhFAQ0AxnXVDjPjT2AC+MkQSogHmP1bNfZo97tkNsS+E1JB55pBrfDxn/sxrgv/PMWzd8XvtJ4Z9mIaNojCK7LYfXLXgSZJsfhoRj9MeXM1+rVSdwVpnZagGoOsV0t1Nwo5jDFLl+waG2CoICshAS0ABJu3oNKNi3bh7M7p2PbY2T4+S0qzj+SYmVWjxPSBOZpLqMjLETqLZg0bSI7J0z1+QWddkeaV6NYi2bLrm5TXwmc9QK0ZWrNG5CpOEDCKWlycjIaxmjNZA6VdeqLk3t0zltckMsYUTeYjdUbzPqdLM/Rq2Qhr9xb5fDD8Pas3VUxwRmfKLVWIp3Vl/2xcKRt4GEWwrNw8vI2qKXDu+Z08s2iVgrvK+fja/gGZ52aNyPUIjuvn6p+JnZ0ab9m7YxZXBDP97ssJpxiSOSr3PsXtkqC2RJ0awiBR8D0zgthaOLJjU+x4fCyiXBF44mZIIh4AACAASURBVOstAKSm4zZNEiT1vrBHJsZ2bhYyH6v+rc3NEiWkkIAWAP1bNcZD53XExF6ZGNouzeM4quXo6STmXdQFWw6X6PYvY4whMshR2Rde3RszP/gLZyprFMNfKPHi5O7o0ULfiOv96X3RINqF0opqJAcYofymYW2wbMtRvGVg3bdg8c0tgzD2xVV+0715ZZ7Ekfy1y3th2ZajilPczXBl/5ZYtGY/Xr28F05XVEsCy4YSQdtgZWsNOPah+wtr9zJxZvj+1sHYfLjE7mo4hmcndcOX6w6hc3NjK7q0aZKAxy/srDn5SQ25eKw0KUULpznAE/4hAS0AGGO42h1Y0Qr1uhatUuNRKvOHMMqg3FSs2nHcsz1Zw/xlF0PbNcHD53fCnZ+uxwidC6UbufeCScYK7hjTDne4Vy6wmw7NeJPbF27/QzVGybRraYkxmmZQo0S6IvCtaHkiuQ9TqBjcNg0vLNvhExTVToQPrJJp1Om0SktAK4ctiXOuH3NiMEmOi/ZxL9GLYHI3yqS8TKzdW+Szf3j7Jnhj5W7dM8uJ8IEEtDDhBwuWnVCaCeNELs5rgYtDuLxRXeGlKT3wksoyLfWNnu7ArE7CE8bC3mrUCZz2bEPBJb2zcNdnG3z29zMZdJZwPiSgEQRBhAAzq1EQ4c/skbkoKQvM+iHwf9P7+J29TdQdSEAjCIIIIfR9rV9orWNsFJ/QG0SdhlYSIAiCCAHeSP0koREE4R8S0AiCIEIAGTgJgjACCWgEQRAhwKJVbwiCqCeQgEYQBBECot0xBI0GNyUIon5CkwQIgiBCwPVDW6O8uhZX9DcXB6su8eC5HTWXASIIAmBcHdK75+XlcWvWrLG7GgRBEARBEH5hjK3lOE5xORrStRMEQRAEQTgMEtAIgiAIgiAcBgloBEEQBEEQDqNO+aAxxgoA7A1BUakAjvtNRdgBPRtnQ8/HudCzcTb0fJyN2efTkuM4xSUi6pSAFioYY2vUnPoIe6Fn42zo+TgXejbOhp6PswnG8yETJ0EQBEEQhMMgAY0gCIIgCMJhkIBmjjfsrgChCj0bZ0PPx7nQs3E29HycjeXPh3zQCIIgCIIgHAZp0AiCIAiCIBwGCWgEQRAEQRAOgwQ0giAIgiAIh0ECGkEQBEEQhMMgAY0gCIIgCMJhkIBGEARBEAThMEhAIwiCIAiCcBgkoBEEQRAEQTgMEtAIgiAIgiAcBgloBEEQBEEQDoMENIIgCIIgCIdBAhpBEARBEITDIAGNIAiCIAjCYZCARhAEQRAE4TAi7a6AlaSmpnLZ2dl2V4MgCIIgCMIva9euPc5xXJrSsToloGVnZ2PNmjV2V4MgCIIgCMIvjLG9asfIxEkQBEEQBOEwSEAjCIIgCIJwGCSgEaGD44BlDwOH13n3VZwCFpwFfHuPNO2xrcDS+/hzCP+sehbI/9nuWhAEQRAWQQIaETpqa4CfnwPeHO7dt/o14NgmYPUCadoPJgK/vQwUHwhtHcOV5Y8AC8fZXQuCIAjCIkhAI0IPVyveUElDmjOCIAii/kICGmEzzO4KEARBEITjIAGNCD1q2jHSmhEEQRAEABLQiJCiIICJFWgkoBEEQRAEABLQCFtQ06DVKu8nCIIgiHpGnVpJgHA4/jRkigIaadUIgtCmuroaJ06cQHFxMaqrq+2uDlEPiYyMRMOGDZGSkoLISGtEKxLQCAchEsaY2/ZJZk+CIDSora3F/v37ERMTg6ysLERHR4MxmnxEhA6O41BZWYnCwkLs378fLVu2RERE4AZKMnESNiPqSCUaNOpgCYLwT1FRESIjI9GsWTPExMSQcEaEHMYYYmJi0KxZM0RGRqKoqMiSfElAI0KI0iQBNQGNIAjCP6WlpUhOTibBjLAdxhiSk5Nx+vRpS/IjAY1wDmTOJAjCIOXl5YiLi7O7GgQBAIiLi0NZWZkleZGARoQORQGMNGgEQZintrbWEn8fgrCCiIgI1NZa8y2jVk04BxLQCIIwAZk3CadgZVskAY0IIf5MmErHyexJEARB1D9IQAsHaqrsrkFoqCr3/qYBcd2huhKorbG7FuFPbQ1QEwYxvupLf1Vfqa0JX3/hMLPSUBw0M/zwOLDyaf733GL+f/FB4PmO0n1KvD4EOH0cuG0T8MYwoPQocNtm33QvdgOiE4EpH/K/L3gN6HYJMLch0PcG4PdXgcF3AsPv167roX+AN4bwv+fsAeJSjF0rABxcC7w5nP/tigFqKoB7DwPRbsfcxTcCf78vve7dK4D3xgMzVwNNOvjm+XIf4Pg2YOBt3n3PtfdNt+ETYMcyYP9qoM0oYOf3wP0FQGS0en23LwU+nATc/BfQuLX02H+vB9Z95N1ukAKMeAD46lbgrnygQSN+/+F1wOuDgau/AaITgNcHAclZwOwN/PGqcuDxpt46Xf8L8NoAoPNE4Jz5wNM50nLF92ZuQ/5/98uACxZ49397D7B6AZ/299eBb+bw++/cBcSnql+vpBx33he9CXSdpNzGhHIS0oE7tvme33E8sHkxMOIhYNBtCJjnOwKnC4BeVwPnvRB4fkYR3s2J7wCdJwDfPQD8+hJ/THgun18HrP9Yuk8vwj03et7Wr4GPpwCz/gFScpTT/CsPKNzB17vkEFB5GohPA3Ytl7ZHADj0N/DGUKBxG6BwJ9+2m3QArv4aWHI78Odb3rQDbgF+eREY9Qj/+4nmQGZvvh5r3uHT3LSWf38eTua3J38EtD9H+5pWvwosvZf/EOZNA859Xnr8yEb+PRGIiAJq3QLd9O+BFn1889y3GnhnDP+74wXApHf5/qjkEHDuC8BJBhwq9z0vo4d2XbU4XQgU75PuS8oAEppK95UXAyd287/T2gNRDcyXeehvILYhkNJK/zk11cDRDUBiOnDqCJDcku/jT+wByk9K70HxAf49zOgBFO4GKoqN36OKUr49RjYAmij01xYydOhQ/PTTT57tPXv2IDs7GwCQn5+PnBzvOzNkyBCsWLFCOaOSw0Cp+96c3AuAAZExyt8lh0EaNDMIwpmYYwpClhKH/wFKDvC/D/0FlBxUTleUz794hbv4zu6f973Hfn+V/7/qWf/l7f7R+/vkXn11lLNzufd3TQX/v/ykd9/f78OHzYv5//k/e/eJR13H3YJB6VHtsv/6P144A3hBCACq/cyQWb+I/39wre8xsXAGAGUngD/cH67iA979u1fw/7cuAfa4O4mTog67okRapz0r+f8bPwWK9mjXT+CfD6Tbq0XC2u+veX+f0JmfmL/e4/8rtTGhnNIjyucKz+7XfxkvV4nTBfz/tf+2Jj+jCO/m3+77LQhnYgThLJQIZR7+Rz1N4Q7+/8bPgH2/AUfW88IZIG2PALDrB/c5O/n/ZSeAvb/wv8XCGcALZwDw68v8/8pSvq8QhDMAOPCHrL7/0b4eAPj5ea+WQpyXgPCeCNSKtG3blyrnuXWJ9/fm//H/D64FTh3mB3DBQKlfKj3mu69MFO+q4lTg5ZYbFPJrKvn/p9zv8plCdz4nfdMK7yHAC2dmEMrz1wfbzIoVK8AY4/8aZmDq7Ie89wYcUK0g0DsQ0qCFDWZtfuJZkmbV0mbKtshGqaSS9nsdwnGjdWAqv/UQRJW/bWr5MDVjyPGsSuFQ84Zl5iIz75xW2UxWNyvqaXGbCtrkAL31JF8MO4iPj8eECRM82506ddJxVvj1Z5YKaIwxf3dgGMdxKzTOHwrgR5XD6ziO626yavUXR81uMvGCmPFdEj4quq/dghfX7zqjXADPwqaOJVz9TOQwt6HAcQKaxe+mmfZl5Blb0R4sb1NO6t+IUJGWloZPP/3U2Elh2J2F2sRZGuLy6gAOaFWmFGgWraXJhcC5XEmgM/qx8/fxD0Q4MHOuUz6mjhDyhGfphLoEEzMCmkbbYgzSe2ZFe7BYSA7WANQR7dY6VqxYgVGTb0DD9oORkJCAPuOuwLuLvgQArymQMY+Pl8DcuXMlxxf+34c++YqPT506VXJ8/fr1mDNnDkaPHo02bdp4FhJPSkpC586dce211+Lvv/82fD35+fmScocOHSrZP2zYMEn6dz/5EqxJO7DmPcGa98TU2Q9h0aJFkjweffRRn3Jqa2uRkZHhSZOZmYmamtBNeLJUg8ZxnORtYYxFAtgHoBmA7QAUnIL05eV4gv1CM7m5QW+ZVtzGQEycojqauUemOnSzGjSV9EbrrRgtpBaAy1g+knPtwIEfZDNYNVhwOqaEFT8mTknSYN8/M/nbbeJ0Pm+//TZmzJgBTvT8/vxnE6b+8xB+2XxA48zA+e677zB//nyf/adOncKmTZuwadMmvPPOO3j11VcxY8aMoNZFzoQJE5CdnY38/HwAwBtvvIF7770XLpe3n/7hhx9w+PBhz/b06dMlx4NNsH3QLgAvnAHA6xxX13vIIMAFKOA4ysRpAkUTpw5zIoDAOm+jH3W9dTKBXa9NXdGgMafPhbLRB02Pad5SzOSncY6j+jcHtHVZHbZu3YqZM2dKhLOMjAx0zs3Cxm278Oabbwa9RowxtGnTBk2bNkVKSgqqqqqwd+9ebN7MT96pqanBzTffjHHjxiEjIyOgsgTftIKCAqxc6Z2Q0jKzGfK6d/F8T3p37wiXy4XZs2dj9uzZAIADBw5g8eLFuOiiizznffCBdyKXy+XCNddcE1D9jBJsAe069/9yAAuNnMgYOwogBcBBAIsBPMRxnMLUFIcQ9I6C+WojdJUZrHqFqGMMRIMWCEykAdRzn8X1VEoekCbJ4o9aKPNwggbNI2w7oS4irO4zLNegyY5bIrBb/Qz8XPM3dwNHNminUaKyFL73hvEhd8RUl3tnorpiAJdG+B+/ZbpngWadBYydp+8cP5f/0ksvobKy0rM9fEBvfPX9T2hQtBXl5RU4//oH8f3335ussH8uueQSXHXVVUhLS/M5tmDBAtx4440AgIqKCixevBg33HBDQOUJvmkrVqyQmDmH9s/Dwpef8pm9OX36dMydOxcnT5701EkQ0MrLy/H555970o4dOxYtWrQIqH5GCdrQkjHWBsAI9+YijuNOGMyiCXgBsiWAWQB+YozFWFjFMEHcQdr0gTHT8SualfysxalEIAFO9dZba1KB3o+SX01EID5o4axBc4BQ5Jkk4AQNhwJ2zuLUtHDK8wuyRtWUhcDp2tEQI7uFy5Ytk2zPvf06NGjAx2qLjY3B3Llzg1qdFi1a4Pfff8fkyZORm5uLhIQEREREgDHmEc4Etm7dGtS6KJGQkIDrrrvOs718+XJPPb766iuUlJR4jonThYpgatCuhbfHeE0roYij4IWxb8BrzjoBeB9AOwBdAUyBTBPHGLvWXRaysrICrbNzYQoaNL3nBV54AOcEYZKAbrOMg8JshOMkgbqiQXNsmA2na9Bkfq9OaVNi/F2yXk2UnMPrFCwWLqBZV+m+or18vDlAOZCtEQ65neUNBY/VvgH79++XbHdqKw3c3blzZwNlGWfmzJl49dVXdaUVC0NBQaX93nzzzXjuuedQVcVrQhcsWICXXnpJYt5s0aIFxo4dG9z6KRCU4QdjLBrAVPfmeo7jftNzHsdxWziO+xfHcTs5jivjOG4NgIdFSXornPMGx3F5HMflKalR6xaBOtGa7BwD0aCJMdPBmwqzUateB+UTTB4TJzNgKjKMTSZOJ36QzeDYMBsOwNAztqlNaZ5DszhDSXW1dKmxY8cUgve6+fPPP32Es3bt2uG8887DhAkTMHjwYMkxu1zUmzdvjilTpni233vvPRw4cADffPONZ1+oJwcIBEs/PBGAIC3pE58BMKaor7Y6UmLwsbKhSa4+DD8wgQoupgLVGsRMmA2jM2pDrUGzAivKdUSbpTAbqhgJs+HESSN2TxKwYPxrLdJKyH2mNu/YLdnetGmTZm7R0VKfusITUk+ln3/+GWrIj82cORNbt27FF198gU8//TRgfzMtmGK7UH9At99+u+d3cXExJk2ahIoKftUcl8uF6dOnW11FXQRLQBOMtaUAPlBKwBjj3H8LRbvfYozdzxjLZYzFMMZ6AZgrOv5LUGprBUGX/hVMnHrKdJSJ04QPmmIcNJ332rB/ipEwG0ZDbwQioJk5xyHaLycIaBRmQ4MQa9Asz5/CbGgxcuRIyfbDz72B8jJ+maby8go8/PDDSqd5kM+qXPT5YpwqPQ0A+P777/HWW28pnQYAHpOhQHx8vOd3QUEBnnjiCf8XYBLBz07g4BF1TR8AdO3aFaNGjfJs//ab1+g3btw4ZGZmWltBnVjug8YY6wBA0F1+wHGckQXKUgBcDcA3YhywEsCiAKsXGgKKGu+TmTRfwzhpGroJzGjQQhFmw2d/MMNs2KVBc6DGxAweQd0BdQkqQQ6z4RShX4zdGjSH96+zZs3C22+/7ZnJuWzV72iTm8uH2di6y6/gMmzYMERERKC2lu+D/vpnPdK7j0LDpAQcPnpc89y+fftKtufPn49Vq1YhKSkJq1evxqlTFqxdqkJubq6k3stW/Y7+4y5F86a8Ye+em69GL5mv3+233644o9WOyQECwdCgia9G7+QAgecA/Bt8UNtSABUANgF4AMBojgtFWHmHYuskAYfh9z4Y/QgopGd+zGI+2kx/KwmE2gfNCuqaBi0IdQnkuVqt2QsHDZrWMwj7AajzBgDt27fHggULJCa/gwcPYumK33DwyDHcdtttmue3bNkSM2fOlOw7U1aOw0ePIzIyUlN4GTJkCMaPHy/Zt3r1anz33XeorKwM6gzSRo0aSdbqBIDVa9fjs6+X47OvlysKl2PGjEGXLl0k+7KysnD22WcHrZ7+sFyDxnHcbACzdaTzebM4jlsJXlMWPpw+Duz60TuTBwBKjwB/vg0MuQuIjAZ2fA8U7gRik71p1n3s/V1TDfz6IpDaFsjqD/z8vPeY0GntXAb89Z6scA5YcjvQoi8QGQscWQ+cOgIMmM3XIbEZ8MuL3uSfTAWu/hbY8gXQfhxwYjeQkA6scdc1PhWoPAP89BRwphBIbgmc2AVs/Mz3ulcv4GcbHRQtDrH8ESB3DBDVAFjvvr5fXwbans2XVawQtXrHd1p3V5l/3ufvZVIGcOgf4NBfQO5ooFE2f4+2fc2ny18FlBUB7c4B9qzg66dE4U73Dw4o2A5EuIAt/DIo+OMNoJM3cCF+eAz48y2g3ThpHlu/8v4+vM63jC9nAWUngXTZrKlfXgISmgDZA737Th2VpvntZSCrH3B8B5DeBdj0PyAuBWg9nL/GVkN9y9u/GvjyFu/2zy8ARzcC4571TZv/C1CwBYhJku6vrQG+u59vB4W7gLS2wLZvgU4XAE078zPaykuAfav5+1xbxd/r49uBA2uAThcCi66U5rlnJf/MRzwEuKL4e1W0F0huwbfFpGbetOXF/L0+6xb+OlsOADZ9DuxZBTTrxrdhVzTw9//x11ZTCZw9j38fO54P7P4JSEwHdi7n8zv0N/D2aGl9VjwFdJ8CH8qK+DbbvBe/vXsFH+dqwyd8uW1G8PXbIRpxF2wHouP4NtNmFN+u/noXyOjJv9vF+/l886YDZ45736svZwEJaUDjXP79bdKeb2cVOjQMq18DomKB2mpg82LlNCufUT+/uhxYpmLmKj4AHPjDu71zGfDmcP53jyuAmiogtQ2QlMm/M2veAUplbffjy4Dh9wOb/sv3ZSufVq/LLy/w712rIUDXS/hYZL+/7ttH7P3V+3v7UiBVZXZdwXZeaI2MAWIb8s8P4IXE8mLg9DEgKo6/jsat+Xsfk+iOgaaAoB+oKOX7+wYpfD8pUFMJnC4EGjQCIiKAytP8PubitbgVJd53zBUFREQB5UVA+SmpK8eZQr5dV1fw35cGyfzzjWoARMW7n3cN34Yqy6R1rDoDlBV7t8uKMH3KhWiVnownnpqP3//eiFqOQ6e2rXDL9Cm49Bp+BqPoIoGqcr7uriggJhEvvvgisjKa4p1/L8TuvfuQGB+Pwf164MFHn8LJU6fx+uuve0+vrQZO7AEaZgKuKHzyySd4at48vPfeu8jfuw8NGzbEwIED8fAD9+FEkULkrfISoLqMvy65wF5aAJSn8M/npHR2Kmoq+X6E44CGGQCLwDuv/QtZzdPxv//9F/sPHUVlpdTkilNH3Np1jn8WMUm4deYMTLthlifJjGumIyLCvlAurC4F98/Ly+PWrFkT/ILmNtSXrtdU4LwX/acfMJvvnJS49BPgw4sNVc8UscnA3XuBhefyH8P6yMzfgQV9/aezA1c03wld8Brwv+v5fV0vAdb/Bxg5F1g2V18+jXOBwh3e7bnF+tuznLnF5ttL1lnAtG98y54r+rg80pjv8NM68AJkRJQ3KKg/mnQEjm02Xi8AmPUP8OnVvEA3t5gX8N6/SJpmbjHw9hheELYc+RqYhBZbxixCh5ZNQlNY4zaiAZ0KcY2B5Cxv2Aw1GqRIB/Z6yejBC27F+/2n1QFr3tPzu2VmM+T/vsR7sGELXuA8sl7pTCCju3SXcM3RCUBqLv/75D5e6EzrwAuX4nTykCL+7pleouKBqtOGT5v/6ruY8xiv1IiKikT+Xz8go/Mgw/ls2bIFHTp00JWWMbaW47g8pWPBXkmgfnNko750x7YEtx56KHcv0nDgT3vrYSsO/ijWuKOBnxb5jOx3azeOas/EkiAWzqzAbIe671f/aWrdU/oL3O+HXuEMMC+cAbx2RbgujuNH2kocDNZg0MHtsL5To6MNVilof5SoLvOfRo1QuQ7UVEG9PWpcY6VIOKpyX2coPZSqzuhO+u2Pv2DD1p3I338Ib3/s1UJfftE5yEhJDEbtdEMCWjCx5CUKcWftBJ8huwgHbbIkLlwY1DcssdoxniDCGSf5+VnPx4u/w7uffCnZ1zy9CebdO0vljNBB62QEE90jBgd9BAJZWinscdBzUKNWFCjSI0zX7Q405EhmLtbWzYk2BEFIiIiIQGazppg2eTx++2IhmqSm2F0l0qAFFb3aKKvXpwuEejxRNiy0JRIBTSHALmEBMgHNUHw8gtCJQ5oPd/AvfylCUg+7WPjCw1j4gnY8OLsgDVowqdUroNVjs6KjCIOOSOwDQxq04MDJNkgAJjyEQR9B1BlIQAsmugUvC9aCJAInHATlWgUBjQSIICCOnaZyf+m+E6roWeUl+LWwhLD8BIXLzdWGBLSgoneh7TAQDOoD4WCyEvsIkgYtSHDS4LZqglg4tBfCuYRD82FAyCpq5ftUR7pEEtCCiV6He+roHUIYPAclHzS7sLv8YGH58kYEYTXULusDJKAFE92TBKxe/oQwRTjcayUfNLtMbXVW88uBTJzhheMCruupTiDNx2GXaw1146KsbIskoAUTKwQ0IoSEQQch8UETNLQkoFmOPxMnx4WHQF8PcFWVoipUTdHKRx5QXqFse6EycYammGBTVVUFl8tlSV4koAUTrlZfJ675oasjrTYcCIdbXaMUZsOeqtTZmHmcXIOmlKYOC6dhRuKR31BSHqqXV2854dCZOA0r75l92u2SkhIkJlqzAgEJaMFE7yibRuIOIQyeg9gHzVNf0qBZiyy0hpIGra4Kp2FIyp4vUHR4D46frkVlDec8c2dYw8KiW7QbjuNQWVmJ48ePo6ioCCkp1gS5pUC1wYSr0fkRc1Cg2vpMONxrYU1OwP5AtVwN6sx0KTE+GjQlE6fb9BkGTaauE1N2FFm/3YsTOecjP70/aqISgldYXDVwxs8C564YoKAaKD7mJ1209H3WS/EWfr3Y8mLj5xoltgKILgBKVK6lWLaO9EkhHfMeO3UUqKkAChkQGSNNJz6fq/V/z/TCIqwZQDLme40quFwuJCYmIisrCzExMYGXDRLQggtXq6+R1FlNRJgRDs9BSUCzC64WdVNC0RFmg6ux//4THmLKjqLZ5jfRbPObwS3ovBeBpbdop2neC7jyC+DJs7TTpXcFjqw3Xoe5xcAPjwMrnzZ+rlGG3Q90nQR8MlC9LpLtfvz/iEjgwUL+95s3AgfXAtcsBzK7S9OJzz9zAnjazz3TS2xDawTYyFjg/qOB52MSVpfUwXl5edyaNWuCV8CJ3cCS24FdPwSvDIIgCIKoq0Q2AKrL7K6FPpgLeMiPxjTQIhhby3FcntIx8kEzQm0tsHuF3bUgCIIgiPAkXIQzwPa1qUlAM0JqG2DqErtrQRAEYR1XLuZNTe3PtbsmUiJjfU1oeklta77cqHjz5xL20qKftfm1GWVtfgYhAc0oEeS2RxBEHULo05zmg2mX+w318eGL1W3Y5mDUJKAZhVkTgI4gCMIRCH2a0wQ0u4igPj5ssVxAs1dEIgHNKBF0ywiCqEMIAonjJozZpUEjAY1wQwJamEHqb4Ig6hIRDtWg2SUwkpUkfLG8DZOJM7ygl5cgiLqEU02cdtXHZq0JEQBOa8MBQi3RKKT+JgiiLuHp05xm4rQJspKEMXWrDZOAZhR6eQmCqEs4dRYn+aARRnFcGw4MEtCMQupvgiDqEo41cZKARhjEcRNdAsNSaYMxNpUxxqn8/U/H+SmMsQWMsUOMsQrG2FbG2J2MOcjxizRoBEHUJYRBZx37uJmG+vjwpY7FQXNMS2SMxQFYAaCLaHc7AE8DaAtghg3V8oVGVwRB1CU8C8M7TUCjWZyEQZymBQ6QYNnr9nIcx2R/F/g55xZ4hbN7AKQB+K97+xrGmMVrOJiEXl6CIOoidezjZhpyYwlfrG7DNg9anNQSL3X/PwVgPsdxxwHMUzhuL6T+JgiiTuI0DZpNkJUkfHGcFjgwgiWgZTDGChljlYyx7YyxRxhjMWqJGWOxADq6N3dznGcJ+e2iZD2CVFdj0EoCBEHURUiDxkOD8PCljrXhYEkbUQBS3P9zATwAYLFG+kaiupSI9ot/N7GygqZxRdtdA4IgCOuIjOX/N8qxtx5yUtuZP7dxrvlzUxx2Hwj9NOngu69pZ/P52dwWrBbQdgCYDiAbQByAYQCOuo+NWKQrhQAAIABJREFUYYwNNZifeAqFou6SMXYtY2wNY2xNQUGBwexNEB0PDLsfyOgBXP65d/+Qu7TPEzrBQBn7NJDWgRcU09oDw+4DrvoKGDAbmPIfYOTDQFQ8nzarv+/5DRoB8U2ANqO8+wbdoV7eeS8B3S8HmnQEmuepp+s80XdfSivv7y6TgLZjvdsNs4B25wAtRK6F6V2A5r2AyAbefdf/7JtndKJ3+6K3gKyzvNuNcvh7okSDFGDwHODCN6T7W/RTvraUVsDUJQAYkNTc93ivq/lzc0d79zXPAzL7AGOe9E1/45++1yMw+jFg9OPSfXGpwLjngFGPSu+lnAGz+Q9SvxuBvjcAOUPU06ox7H7fNpzc0vt7+P183gIj5/LtaMBs/t60PVs5397XAD2v9G7njgbSuwIdZS6pcane350nAAnp3u209kD2IO92Vn/+epOz+O3M3trXNvBWYNpS7TT+aN4LaDWMb2tNOkmP9ZqqfI64HZ/9FND9Mr7faNxG2obPfR5ofy5w0ZtAi758mtYjgLzpfBub/BF//MLX+WsB+Hsv0CCFv76eVwLXrQQuXcSXIdAo27duwrMdfj/Q0N22z31OX9uJipNu970emPYdMPRe4IZfpcd6Xe39PeIh4Ox5fFsXIxbEBt3O1+mqL93vHoCb/+Kv+5xnfOvS8QKg6yX8e9/rauD6X4Dp3wMXvuYu7ylv2qu/9T1/0v8BN60FmnUDBt4GXPIB30eI6XcjX+9+M5Xvh/hexzYEXDJjUVoHoFl3vp30uda7X2hHSZnS9t1bNh/ukveBrpP565HTbYp0e/wr/Lsz8mFg6D38ezX+FaDPdfy96HA+n39COt+vixE/l+6XeX/nDAEm/pt/L3tcDlz2KX+flYhswD/PKR/z/7MH8dee0kp6/zJ6en+PepSvT9/r+e/bBa8C4xfwbeDWzd50fW/g0457lq+L/L2b8Db/PC9+l/8TuGa5cl3bjuXfNfH20HtF1z0YGPWI8rkhgnFBttkyxu4B8IR7cw7HcfMV0sQAOANeYFzHcVx39/5kAEXuZD9zHDdIfq6YvLw8bs2aNZbVXRdvDgcOruUbQab7I19WBDyV7U0z+jH+JX+kEb+d1R/Y95tvXq2HA7t+4D/yB1WuY26xsfp9fBmw9Sv+d1oH4MbVorwa8v9v3w4829a7P28a/9FQ4n83Av+877v/7v3AvBbe7dkb+A+op4xtQGI68O75wJ6fgCv+y18vAOxZCbx7Hv8yT/1KWre5xcBLPYETu7zl1FQC81t7j4uv85L3gQ7nec8Xc+8hXsAGgE+mApv+K81DOOeeg0BMgu/54jwH3soLKQCwfSnw4SRe+LjsE2+al3oAJ3aLzpeVI5DUHLhts++xmaulI0KlaxLnK2Z+G+C0aMASnybdBoB244BtS4CEpsAd26VlyOuqti2ph/tYXGPgTCEvvE5fCpQcAp7rwHfCd2xTPmdusfR3aQHwTBvvtpAHANxfAERGK+cjcNde4Okc3uRxVz4/MDm6GXhVNmjJHQ2UlwD7V8OHLhcDGz5Rvl5xefK6C1RXAI81UT7/+A7g5Tz+wzXrb9+y9fDdA8CvL/HtUBDcPPnvBF7uxQ+Ebt0grW+7c4ApHynn+dsrwNJ7+Y9pVANg1bPeY42ygaJ8fkC36hl+kHf5p755CGV1OI9/H+X3puIU8GSmKL3K/VOiKB94sRv/u/9NwJjHNZNL6iMuR1y2nMJdwL96KqcRzh+/AFg8E2gzErj8M9/6z88FTh/jBZl0kQZHnPfox4Hv7uMHvzN/U6+nUvniY+sXAZ/P4NvrhLfU74MSau34xj+BV3rzwvh9h/3n82QWUFHMC7upbdTTee7fK8DiG3lB8IIF+uqo9KyE76/ScaX72bQLcHQD/1v4Hhjp44IAY2wtx3GK2g+r46Ap5cep/Pbu5LgKAIKo3EoU90wkNcBkLxZkPDZvrXgpzFg8FStjr+jJS/7YNGcxqQj0PuWobXMKxw1M82cR2vXTPeDQuC96ZnHpKSfgwU8A7UDPNQQtxo/8WZvJQqP+uq4twvtuCukVr9euOEdBLpdpPQONsjnx+6nyDuttN6rt397YUtbgvjbVtqhyXHxPPPfRovthpbLFJfjh6X3WbrdxvRMsrKqr0Xwknx3n+5NbXcMvGGOzGGNZjLFYt0lztuj4LwAgCl67UHTsQ/f/RAB3MsZSAdytcNxZCA1E0o7ljZqTdWr+Gn2IOzC/wpUIvS+EPE+tbc2PiUJazQ+EVv2UyvRTnqlyjKTRICAByoRgbhWewKcBOOxqtUldgw6d75vf9hQIOtqYJR8qhXIitFYH0CjTI9Qq5GnVfQp2uw4pKvXh1AQ4pXtv40BOjYgoY+mFdqN7BqzSQD0ESJ6H09qSL1b30JkAXgSwF0AZgB8BNHUf+5DjOAW7nocXALh1j3gSQAGAC93bb3Ecp2CDcAJBaGihluyt0KCpasxk21ofJF0jbqZcP0u1jhbdf1s1aDqEbiePIDUFfIPCp+e3EzvkILmYmF4dQM8AxwINqZPRvGd+Bp7eTJSPh0sYCKMzWT2CvUENWqCvpOF+XzzQc3D/58bqGj4I4GMAu8ALaGcArAVwE4ArtE7kOK4M/KSCVwEcAVAJPszGHADXW1xP61AdKQVAqJeX8PkYapkQVbQi/vLQPG5Qg2b2rdatVbHIxOl4DVqQ2pmPdshEOT7PwKgGTUFAC7WJM2AtrT802pfn+k22QSXNorAdsPbPiYKyGB331V+/b0iDZhUW5i0IaHrbaa1g4tQr2DlAgxYGApqlAV84jvsCwBc60ik+FY7jCgHMdP+FCSojJS38pg11B6Z3VAjzJk4fDZqBD65EKFTRoBnxY/NbplM+IFZq0CzOXzNbC0ycWm3S6LVp+foEIvBbgRUaFUVzpMlnoMcHLdD7ZfP6hgHBmLvLN+mDFqw6WZ6nQa2zWR+0kCsjxAKa89uh80VIp+PpX5nSTnNY2nBM+CIFw8Tpz88MUP9Y1VZL89E0cRowT6gm0/Na6JkkoK849XoEuQMJ2sfDAhOYlnO10fM1r5MheFoNPYOAYJk4tXzQNNDjg6brXQtjtNqaXtOx2n0MFxOn0b4nHH3QwkCD5vwaOh2tDs0sQXPeVqmjP3OkGL0dvpFJAv5eUl0aNKME2/xkAVaaOIPp9K2WbyAfIx8BzaCgodfEadez9tyjYOdv1gdNwcTpydusf5snA5PnhQittqa3r1QcuMvzdvh9AIy/H0bXqrbTnccp/bwGtKaFZTj/YatiyActwDAbmn5JKnn7TE03aYLV+3LqeXFD4YNmZZtSqm/QRvNqGhYD5QXaeRqdVBAMgm1G1+XMHoAPGpk4fdHyjZSgx8TpYG2a2RAghsNs2KhBCwNIQAsYBVu63w+fn0Zpp12e36GRONAwGwr3y99oX3BABTReMKMmzhDc40AFoEDagT8NZjAJhgbN6MfMkCkjWPcmVPdcywfN4H3T+nAaNns5WADRxIDg66RJApbeb5Nt1+gkgZAL6+E1OAgvcdKJ6ApUaxSbBbSgBILV+mj7Ea70mDgdOSp3UpgNk2kCwk4fNCOTBOwkWD5owvtmcpKA1oxXz6G6auI0MovTnwZNywfNyffBrOY1xIFqjRJmGrTwqq0TCcZslJA3IgPaFrUOX/7C+dWgKcymUXtpuRpZWpMmTq36GSUUKwkEO8xGsDpJuX+Vqeuw8n2SO7cHqRy1co0es7TsAISogLWwet0hDGC3QO1p2+4+ybAGTZLIsmoFJz8Yfz10TxIwW0CA2N1+DEImzoAJRqBaB2vQAh01K5pQ/FxvrVxA08jfaH0cTbh+yAIVDhA605DdHXaw/QCtDFQrFzrC1oTpDx1+rLX+LCchNHEGow2bfbZ66+KEMBthQHjV1okEI1BtqIU9HwFNYxSk+uLKNWhqs520Xnw9Jk4E8FJb2TmGYJKA3cKDWSzxQZObhgKJqaZZUPDus65JAsESPAP0QWMR8O2H5IOrumri1JrF6e4bhdA//jRo4T6LM2h1pEkCegiv2jqR7pfy/xPSvPui4vj/GT34/1n9vce6Tga6TFTOq9NF/P+09t59/W8KrH4dzvefhjGgcRvvds5g9bQdxyvvd8VIt6MayMpwN7Uuk/j/jVp6jwm/hWNyBt6qvL/X1aJ6ua8zvYtyWkDqwNr+HPV0emgzwvs7rZ27DhdI0/S8yvu79wzv78w+0nQ9RIts9LnO+1vemXR2t5vUdv7r1+da7+8mHYGU1r5pOl3oW8/Utr7ldr9Muu2vTSU15/93m8z/j0nyLUeNpu7nJxduGjTSPk/p+npeKd2Od7+jfUULk3Q4T12IyR3D/1drl4D0Puf+f3vnHWdXUT3w79nGhoQEQhIioSRUgQSEBKmK0gSi9KIISLEAAlKCoBRJqIIiCipNhB8SBZH+U34ISqSJBBAlgDTp0hOKkGR33/n9cWa4sy9vN1vfvfv2fD+f+bz3Zu69b2bOnblnZs6cu23lY1LZR2J5yvPYHeI9uPKmi6bF9jcltJFlJmRpHbVhgAmfss9Vtsj6gY99wj5j+xm1un1O3K3z/KX/E/tCaC/b8jbTHVbdsmvHDR8HTcPs++T9F3/8Ustn38dNbp825UD7jHX+8an2ufwGZRfpYOA+fIXs+/jN7XO9L9ln07AsfaUKMgVoHgHDxtq7MkeuYnFj1w15+Xzlc7rD+CD/+AyL5V0c5X1ER0g9LLs6rBj6wI7aTMqSo2DIyMpp6+5ln4t7d+jQMfY5cbfsnJTyupuwxeLzVQVEa2iaesqUKTp79uzq/qmqjabqy26Qthbr0NK0tlZrsCLQ8gHUNwFi9gx1DbZ+39YCD/wCbj3OzvnePGidD6ePtd+nvNP9PL7yMFz8GRizDhx6b5LHVhvRNTSFKXu13+VlKaetxcpRas06oPpGaF2Y/A6d+Skj7POE16CxefH1FTvveF4s78L/mhIYr9vWavWVdvZtLdl1X3sMfr6JdXhHPGz5qi9b0W+Zb8dHu4m0PioR83TSm5XzXx4Xy4q0z2upBBdvAa/+Aw64FVbauP2s01krwYJ34egnYPjHsuuVSpY/qQMU2hZanVWSl6rdN3WNdvzvDoI518EuF8M6O4f6aFy03uN9kNZJmvd4D9dVGNvNuR5+u791dntc3v665f9TXqenvBOWsiW7dryfotxaPrQOvpJ8Sm1B0VK7Rn1DqP+29nJP2yVYHVy2PbxwL3xxpillWrL2OWTpjstbarN7smmYpXV0XKX7tDwvvZnBq3TfVfrvaCbQ1fb9UZ8V66sNLt0S/vMIfP1OWG5ix3lva7U+rSEM2srlWmqDGeGBe/Jciy9v7x0x7wU4bxIMWw6mPdn5sZFS4uU+3hOxHZX3CWkdxA1JqUzT/iutp/J2c+poa5/HPgtDl61wbRZtf+X5bPmgfZ+XliXyUTvt5D7ojFKb5bO+ya4V+5j6hu7dn+l5i/u/eC90Nc+lTt5SoEk/WJ7erm8p2XGNzYvmtbztdtbH9QMi8qCqTqmU5jZovUWk8k0W49K09OZtGpocnMTXN7ZvECKLzkZ1l45GF2l+ProZu2DkGctU3iA6UmygvaF2Z/XVEe3qi8odQXqNONpvbO44X43Ni79mJbqa/47KWleX1V1D06LyjmnlHWNdHe0mves6uS86um/q6rMHZ6V8l3dK5XXSWR2lS+Pl1+1KR7y4+6mzdlCp8xapkP8K7TLWc/OI7Pj43x2Vt64emocn1+3guM7qqycP1O5co137jvXTjfadfu+oHjv830r/HUnu654+BBc3Y9Lu2OT/K90TleiofGmbbtffdLDruJJyU6l+K+WzvM8rP6Yr+V0cdfXt+5G0j+nONcv7ps7+L9LV63e28UCkfX/W4TXqoK45+57mtTt9XJXxJc5CMhBsE7qL79bpPgOsDDVR506/Myjuk7z8fDm1hCtoRaQWG3Utlqk3dMW0wOvMKRI1ZA7T7/TL5jFnsOF3TxGpyQdzLZapL+jKTj+nKrgCshj6aOddTfZvZXz0jmZ/xDo9x++eQlKDHdhg6JS7hc+gFQev527h92UXyMmNhFNTuIJWRGqyA6zFMvUB/f1CbcfpK3yCsfv4DJrTC/zuKSJ93qgL0LNWW+msheWqPq2zKtRHLdS50wUG+FsqqokraE4v8LunkOTh2byfqclZQcdxnE7wfs/pBa6gFRFv1L3H67D6eJ3XOANk1qpI+Aya0wv87nGcPPDlQGeg4op413EFzekFfvc4Tq74w644uNLcKT6o6AHevp2e4wpaIfFGXfv4w64w+IxQN/H66jJ+bzm9wBU0x8kT78CdAYMPKrqNt2+nF7iC5jiDCX9gOL3Fd4M7TlUozmvbnYx1doabDoOdfprF7fADaJ3fs+uNXgvW3gk+fWzf5K877HMdPH5z98/73Jm9M7AduQqsswtsdmTPr1HO5kfB2El9c61dLoI7z4Ixay+atvc18LdLoHnpvvkvgK2nw8IPYI3t+u6a5ay6lV1/21O7fs5nT4Dh4/ovT11h6rlw+ymw4kb55qPo7Hox/OUcGLVm7681+QBYe8fs9+6Xwav/XPx5Sy0PE3eHjQ/tfR76k/1ugkevzTsXg5udL4R5z+edi14hWkOGn1OmTNHZs2fnnQ3HcRzHcZzFIiIPquqUSmm+xOk4juM4jlMwXEFzHMdxHMcpGK6gOY7jOI7jFIyaskETkTeAalgFjgLerML/ON3HZVNsXD7FxWVTbFw+xaan8llZVUdXSqgpBa1aiMjsjoz6nHxx2RQbl09xcdkUG5dPsekP+fgSp+M4juM4TsFwBc1xHMdxHKdguILWMy7OOwNOh7hsio3Lp7i4bIqNy6fY9Ll83AbNcRzHcRynYPgMmuM4juM4TsFwBc1xHMdxHKdguILWASIieefBaY8E8s6HsyguG8fpPiLSmHz39uO0oyHvDBQBEVkV2B14D3gSuEtVF+SbKwdARFYCVgReVNUX8s6Pk9GRbERE1I1bc0VEVgE+AbwCPKKqH4Z4l00BEJE1gWnAMBFpAc4HHgP+6zLKHxGZAKwOvKSqjyXxVZXNoN4kICJNwIkhRBT4NTBdVZ/KJWMOIjIEmA58A1gAjMB2yfxGVe8RkTpVLeWZx8GKy6a4BNmcAhwNLASGALMw2VyUY9YcQETqgWOBM0JUCVvJegG4RVUPyytvTru+7XBgPta3XQNcrarXV7tvG+wK2lHAD8PPG4EpwLjw+1pghqo+mkfeBjMisgLwC2CbEPUKsDzQhs1w7qSqT/tIs/p0QTY7q+pTrqRVHxFZEvgp8JUQ9RCwAZkSsBNwq6q25JNDR0Q2AX6LtZkLgXnAkcASgGCDnku9X6s+IjIKuAjYJUQ9CayB9W0LgM+q6gPVzNOgtUETkZFYYwA4XVV3Ab6EKWoAWwPfyiNvDhsCWwCvAZsB2wO3AfXAWsDPAbwTy4Vy2WxHZdm4clZ91gb2Aj7E5LIR8ANMiQaYAWycT9YGN4l92XaYcvYsME1Vv4vNqL0c0k/GJgqc6jMJ2AF4B/gM8CngKkw5WxI4L5h1VI1Bq6BhZR8SvkdbvL9iU8/vAUsDW4vITjnkbbDzeaAJeAn4t6r+E/gaZqPRBmwlIgeAG9bmQLlsHiWTTQnYMpHNYO5fqkJZHU8CmrGlzZKqtgHfB24GWoD1gD1FZEzVMzrISQaTa4bP14Cx4fsvgD9gz51xwFdExO3Dq0DZ8+PT2EzmXGCeqr6BKc93Aq3AJsA+1ZTNYO5Al8MUNAU+LSJjVLU1TGGekxyzU1iXdvoYEakTkdHBLiPl1fC5CkF5VtUXseWbuSHtpBDvs2j9QA9l83ZIi7IpuQLd94hIvYhMFJGhtO/D49JlAzBWRBpV9S3gauC+kLYbZvzs9BMi0iAiB4vIMSKyi4iMT5L/Hj43wWacUdX5wJXAEyHtqwRTG28/fU9oPxOCDXrKO+FzJDAcQFVfBS4Hoj36wZheUBXZDFoFTVXnYKN+wXai7ZYk/xJbf27GHkSjq57BGkdE9gbuB24BbhGRQ5LkucC7wDK0X2a+DOvgWoHxIrJfuJZ3Yn1IX8rG6VuCbP6BzYo9APw82AUC/AszNh+K2dHEmbJ7gT9i9k5jgW3DtQZt/99fiMiuwL+Bn2ED/d8Bt4rIZuGQF8kGOUeISDOAqt6NbeZ4H5uh3i/E+wC0Dwnt5yGsb7sTmJEoai8Br2PK2f5J+7gJuAf4AFgB8/gApjv0L6o6aAOwJ7YsUwL+D/h4iF8COD5JG593XmslAMsCv0nqNg1nYQ/+DbAlgEXqH9gjxC0Azgbq8i5TrYQuymb9MtlMSM7fPZHNOS6bPpOLYErXz5J6fy/5/nvMLnA49jCJ8fsCzeEaGwIPhvgHgKa8y1VrAZiM2ZKVsAf6Q9iApgT8DdgR2xV4D2aqUQL2j+0EW4J+H5sJnRFln3e5BnoI7WcENvES28aC5PsvsdnMlZM2UgK2SK6xNaa8lTClu7EaeR/sI6g/Av8bvm+ATV+i5gOtFRPGu9iUp9M3bIyN4OdindNxWEcGtmnjGFWNI5zIecn3a4HngEagTX0ZrS8pl823yWRzMCabh7HZm8hHslHVa7HZA5dNH6L2hFgFmIptADgUm/G/KhzyWeB0rM+6jmxTwDcxuzTUTDfeDfH/UdWFVcn84OIg4GPAX4DNgV3JvARMxvq6Rmyn4Fsh/kTs2QO2avMytuFGwWfQ+oJQhxOxDRrvYXL6Gra5CWxgeQJW9zdiSjLAySIyNlzjduA/IX6eVmsndN7abd4BG3l+gClj7wdBrQRcQjazVhVtudYCFUZ/wBWhXu8Lv+sww/NnQ/y/gM9hy87PkY00j8CWmlcFng5xh+RdxoEaXDYDK4R+qQQ8A4wMcUthy8pxxH8Stjx2JdkA80pMWVgSW9IpAefkXZ5aCkB9+Lwq1O+DSdoobANAHOxPD+3qMmzJuYQtQR8DnBba1DPAGnmXa6CGDvq2H4W6fhSbURNs8PJ4iH8TOBBbJZiVtJ+zsNm1Zclm106oWlnyrswihPCASac83wqfLcA+HQndQ7fquB5bOr4p1OscYM2QNgLbLVMKHdRMzND5QLLdgXOxpZkXw+/ZwIp5l6sWgsumWAEYknyPy1/TgmxKwKZJ+haJbF7EBpeTgBvIlnLewGbVSpiN2gZ5l3EgB8y9zEaxjYS4JmwwX8JmWrZL0jZNni0PABOwwcxPkvg0TA/X82dOz+RTn34P4Seh/cwDPpGk7520n3swBW074C6ySZtnMPu0EraRY82qlSXvyixKAPYJAnotPHDuBDbOO18DMYQHxEWYI8ZzsRmXppAW7WheAQ5PzlkNWxooYaOajYIiMDVRBGKYBayXdzkHYnDZFDcE2czElpBvwvz/LRXSDkseJL8pO+/qkPYOcGyIWxYzE3iPTLGbhStnvZHPROBWskF8C2YHu05IPyZ5qF9CZv9XH9pbVN6mJtc8AluWnoUtr22YdzkHagjt53JsJvMKzF52yZB2WtJGzk7OacZsOEuYErZnIuu/BhnHlYJZwPpVLVPelVqkgBnijgEm552XgRiwWZjTWXREOBuzXwKzl4lLyjcA64b4IZidUzznS8l1J2BLbUeknZsHl00tBEzZPSGp34Xhcx5wZThmBNnGgBext2nE89dJzj0HaAjxw0La54Ct8i7nQA7YoOS5UMdvk82olMKDvBGbvYzmAI8DXwznCub09G06WP4HRuVdxoEasNnG6Yk84vLks8C54ZjVgP+G+PtpvwFg++TcI5P4Mdjs55dJZkSrWra8K7dIAZ9S7m397YrZWZQwj/JXJjd+G+adeQTZiP8tzHP2EuH8LchsmGbkXZ5aCi6b4gZspB8f/j/AZmJeJRu5fzc85I8Lv+cDdwDDwvkjsA1PJeCGvMtTi4FsBuZebHZyQ+CfZKYxZ2DOzaeRmcfcBowL508OMi0BRyTX9WdO72WzJdkOy/OwQcqCpP3sg82UnRd+v4c5Bx4Szl8TG6iWgEvyLk8aBvsuznZokJbTPYJT0wbMBcYw4M+qeoiq7osto7VgD5ifYNP9M7Gp/mWw3WhfDJd6luAEEDPmdHpJcMrYiMumcCROgLfCZl9eBaar6g+xHbSxng/GlpMvxXb6NWEK9ckhfT6Zz7M54dret/cCEVkttBtEZAQ2uwxmz7dAbVfsd7GNM2BL0OsDv8bMAeoxz/Q/FZG1sNdwLRXOnxX/x585PSM4aSY8d6ZimzHmYKsBx2IbZqK/uZMxJewK4HlspWwHTGZgyl18q8Mj4bqF2H3ujdjpESIyOnzWq2pJVVsxPzIAbyfO/07HRp0t2Lr+vqp6I+GdjVjH9WMROQOz2xiK7Za5tzolqT1EZISINIWXybepbQkfH5JdNjkiIsuLyAYiMlrtVUxgdQ/2oIivAroWuB6b9VwBe8fm+9hSclSqp4nIzZgNzSRs2e0W8Heh9hQRWVtE7sAe1OsDqOo7ZG9pWAob6KCqN2P1/XaIO1BVX8YcOL+FPV93BG7HlIMhmFyfqVZ5ag0RWUNErgEuAAjPnY+H5Dew95yC2fzdhplsrIZtBngEWwoFG9CcJSKXYKsGy2PK9p/DdYuhOOc9hedhYAVsu/752HTw6iGuEbNxupTMhmbV5Jw9yHaRvUE2tXw5mdPTaDfwKrB73uUciAF7AJyM2Vjcg3VSnwppV7hscpfNmdhS5guYz6UjQto3yZbFDiBbVl4f89MYDc/XD/GHY0pyXJ6Osts773IO5IANYlL7zPMx57+NmJuGWNd7JedMItvxVyK4x8D8CV4Y5PYK5h/wq3mXcaCG0H7OSep5NrBSSIv2Zy3Alsk5W2F+HOPmgOVC/PfJ3GvEvu31VK5FCblnwMPACcAXsOWv2EiuLUs/k8yQ+YqytBvJtv3vF+KGYs5Rz8e8OZ9M2HXjoduy2ZXMzUVbIqMTacoHAAAG4ElEQVSXMPuLEzEnpy6b6stmD9obladh+fAgicblt9P+7QzTyBTls0JcA+Y8+6jwcDrGZdMncto8tIG4UeYDYPuQdiDZWwIeApZJzjsNG/i0AoeWXXM05oi2Oe/yDdSAOWaOrq+i4jy0LD0+l64n8Vsajn0/pMUdzs2Ym5NTgR8D3ylq+8k9Ax4GRggPkWjk+ibZTrNtkmPWS44p0d5f0zaJEvDlEJf6q2nIu4wDMWCj+6+TvVLmDswA9uVEDsdh7jRed9lUVTb12BsZYp3fhtm9zE6UgIMwo/Nrk+OOAkaEa6yH2c20YG5QJJWNhz6Rk4TPtTB7vmex5a4S5vJkBGaTeTvZpoATopKAbRiIsvtCek0PvZJLE+1fb/Z7gkuTkB5n+8eTGfmXsAFRlOmmQaYLgONCXNq3FVpOboPmdJVoL3MhZlA+N/w+Nx6gqo9gRrKtIeo8EVk6fI8vom0MAc1scFCzJXC6Tyu2nDIU+I6qbqWqB2E2S5FNVfVFzD+Qy6ZKhDpsxpa4pqnqtqp6AbZE2YC1oftV9S3gGuCpcOoh2K5ZsJ2CH2DK3ttqtOH0GRqe1NhGjSbMVun3IW4q5htrLtb3PR/ijwb2EZElsM0z72CrB6+XXdPpIWqvI7uf7LVYZ6vqnLCB42zgbBE5HVPAfk32KqaTgHXD939hM9CNhL6vrG8rtpzy1hA9DIyA2Z7thRlcDsFeXzIfG7Eclhw3BrN/ijMEv8N2Aka7tYcIr6rx0Gey2QS4m2xLf3Q8e3eo85nh93Ium6rLZjS2G3ZEErcZZlj+PLb54nBsyfJ0spnQx4EZmCPUEma7NjHv8tRywDZrlLAl4x0wRa0EPBz6vTWDjJ4gc9dwP9nMzVX4bHNfy2Q4mW3zQ5jylZpwlID7MF9lvyJ7fdZdoV39MGlPK+Vdnm6XP+8MeBg4gWQ6GNgZM3YuhUYxPEnbFrMFiA1oYfL9SGx3U6GnlgdaoMzRJbYkE98dNz2J38ZlU3XZpEsqB1HZHm065gz1pAppJeB7+DuB+1tOU0NdnxF+n0k2mJmFvTXjAmBrMhOC+JaG89M+0EOfyuUzZEvOMdwVFOQ4SXAFsB9mUxaPaU2+fwebhR5QfVsDjtNFVFVFpE7NrcYNIrIjsCc2yjmD4FdGVW8TkYex7eSfxLamvwB8T1X/nlP2axpVfTO41YhT9iOxJRsw+4x43B+DbJ7DjJeH47LpVzQsqQTXNJeE6L9hA5v1sVm2Q4A/qeqpIvI09j7AkZiCcIaa+YDTv0S/WW+Hz7sxNxlrYW8CAFuSvl1EtsTa1zjgAVWdU9WcDi7uxQaV38ZmNQ9V1ftEZHvgq8Au2Aa2q1T1WyLyEjZLPRLb3XzqQO3bJOvPHadrBN9nbSIyGfNIH/3QrIqNWvYFrlHVp4PDv3Gq+lJO2R1URAVaRL6MyeZlVV0xpI3FtqHPTI5bwWXT/yT1fRjwrqr+j4gMwZydfgvzo3WMqv4oOWeYqr6fU5YHHSLyBWxH85nY5oATsaXOyO3ADuo2mVVHRNbGdtJereYkOMZHp7TDMLc1FyRpo1T1zapntg/xTQJOt4kzAqr6ILb7bF5I+gNmV3MasJOINKvhCkCV0MxBaRzxXwkgIidgxuq/EpEp8TiXTXVI6vuCoJyJqn6IDWiGhc/nIfNi7spZ1XkDk8Oe2NsAonIWZy+3BqYG7/VOdXkcOD8qZ4mn/2Ww9tNCcAAc36Ix0JUzcAXN6SHJa2ouwnYutQJrhLjrMV9b8/PI22BHRIYDUzDbi0+KyJOYzx8wz+fuyTxngrnAnsA3QtR1mBsOkmVqp7r8G2sfq2K7bGdirwA6Fevj7gDu8Rm06hMG+nEAMzRpP/uHQ64nvEJLa+gtGr7E6fQYEdkU8+68SYj6OzbNfHd+uXJEZANst2Yj2SDsAeAoVfXXNOWIiOyDDWS2Ims3twJHq+oTuWXMASCYBhyEbayZFeKWwzYAPNXpyU6/IyLHY7azq2M+AgH+hD13HsstY/2EK2hOjwjTyDMwG5o3geNV9bJ8c+UAiMjK2GwAmNuGY102xUBEJpEtmT0FnKaqV+aYJSdBRBriDFlYRqtT9ztXGERkInAnNsP5JHCeqs7MNVP9iCtoTo8RkQnA54GLVXVB3vlxMkTkV5hNzfEum2IhIgdgNjNXq73I3ikYcSNU3vlwFkVEPon54qz55WZX0BynBom7BvPOh7MoZe5QHMdxKuIKmuM4juM4TsHwXZyO4ziO4zgFwxU0x3Ecx3GcguEKmuM4juM4TsFwBc1xHMdxHKdguILmOI7jOI5TMFxBcxzHcRzHKRiuoDmO4ziO4xQMV9Acx3Ecx3EKxv8DW7akolHRaxMAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 720x2160 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Un4lSBFJOxIr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 706
        },
        "outputId": "8a4d7aa1-8999-46e7-ee6e-61591e0762bd"
      },
      "source": [
        "# строим гистограммы быстрее, чем в начале занятия\n",
        "df.hist(figsize=(18, 8), layout=(3,4), bins=20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f4ceea6c6d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee993c10>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee95b750>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee913e90>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee8d02d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee903850>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee8b7e50>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee879350>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee879390>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee82ca10>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee7a6450>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f4cee75c9d0>]],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 121
        },
        {
          "output_type": "stream",
          "text": [
            "findfont: Font family ['Calibri'] not found. Falling back to DejaVu Sans.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x576 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XMTzH3aLO0hT"
      },
      "source": [
        "# разделяем данные, убираем из обучающей ответы\n",
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, y_train, y_test = train_test_split(df.drop('quality', axis=1), df.quality, test_size=0.33, random_state=42)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d7xC20MGO2M7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        },
        "outputId": "5d4afa06-6eb3-4b51-9435-610ff63f9376"
      },
      "source": [
        "X_train.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>fixed acidity</th>\n",
              "      <th>volatile acidity</th>\n",
              "      <th>citric acid</th>\n",
              "      <th>residual sugar</th>\n",
              "      <th>chlorides</th>\n",
              "      <th>free sulfur dioxide</th>\n",
              "      <th>total sulfur dioxide</th>\n",
              "      <th>density</th>\n",
              "      <th>pH</th>\n",
              "      <th>sulphates</th>\n",
              "      <th>alcohol</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3167</th>\n",
              "      <td>5.6</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.40</td>\n",
              "      <td>6.1</td>\n",
              "      <td>0.034</td>\n",
              "      <td>36.0</td>\n",
              "      <td>118.0</td>\n",
              "      <td>0.99144</td>\n",
              "      <td>3.21</td>\n",
              "      <td>0.43</td>\n",
              "      <td>12.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>324</th>\n",
              "      <td>8.3</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0.51</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.046</td>\n",
              "      <td>11.0</td>\n",
              "      <td>207.0</td>\n",
              "      <td>0.99300</td>\n",
              "      <td>3.02</td>\n",
              "      <td>0.55</td>\n",
              "      <td>11.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4731</th>\n",
              "      <td>5.3</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.38</td>\n",
              "      <td>10.5</td>\n",
              "      <td>0.031</td>\n",
              "      <td>53.0</td>\n",
              "      <td>140.0</td>\n",
              "      <td>0.99321</td>\n",
              "      <td>3.34</td>\n",
              "      <td>0.46</td>\n",
              "      <td>11.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2305</th>\n",
              "      <td>7.0</td>\n",
              "      <td>0.36</td>\n",
              "      <td>0.30</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.040</td>\n",
              "      <td>40.0</td>\n",
              "      <td>143.0</td>\n",
              "      <td>0.99173</td>\n",
              "      <td>3.33</td>\n",
              "      <td>0.42</td>\n",
              "      <td>12.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1777</th>\n",
              "      <td>6.5</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.26</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.041</td>\n",
              "      <td>40.0</td>\n",
              "      <td>141.0</td>\n",
              "      <td>0.99410</td>\n",
              "      <td>3.34</td>\n",
              "      <td>0.72</td>\n",
              "      <td>9.5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      fixed acidity  volatile acidity  citric acid  ...    pH  sulphates  alcohol\n",
              "3167            5.6              0.28         0.40  ...  3.21       0.43     12.1\n",
              "324             8.3              0.41         0.51  ...  3.02       0.55     11.4\n",
              "4731            5.3              0.31         0.38  ...  3.34       0.46     11.7\n",
              "2305            7.0              0.36         0.30  ...  3.33       0.42     12.2\n",
              "1777            6.5              0.18         0.26  ...  3.34       0.72      9.5\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 123
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KZ3rnveEO25r",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5e6acf82-44d9-4554-a900-2cb356b3b25d"
      },
      "source": [
        "# качество вынесли в отдельную y\n",
        "y_train.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3167    7\n",
              "324     5\n",
              "4731    6\n",
              "2305    7\n",
              "1777    6\n",
              "Name: quality, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DqTPQrjoO4Bj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "71dc8017-8e72-4431-88d4-c009db8436dd"
      },
      "source": [
        "# размеры обучающей и тестовой\n",
        "print (X_train.shape, X_test.shape)\n",
        "print (y_train.shape, y_test.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(3281, 11) (1617, 11)\n",
            "(3281,) (1617,)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q0w8o49uO5I7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8bf2b227-0a1d-43d2-f194-3c1fb595a7a7"
      },
      "source": [
        "from sklearn import linear_model\n",
        "\n",
        "# линейный классификатор\n",
        "regr = linear_model.LinearRegression()\n",
        "\n",
        "# обучаем\n",
        "regr.fit(X_train, y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 126
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0EXpqEQ9PjgA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "43deafdd-c54f-4bf1-b43c-80b3b194f627"
      },
      "source": [
        "# dummy классификатор\n",
        "from sklearn import dummy\n",
        "\n",
        "d_regr = dummy.DummyRegressor(strategy='mean')\n",
        "\n",
        "# обучаем\n",
        "d_regr.fit(X_train, y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DummyRegressor(constant=None, quantile=None, strategy='mean')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 127
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G85WK6BvPkjA"
      },
      "source": [
        "# получаем предсказания от двух\n",
        "predictions = regr.predict(X_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "obMPcp_VPlXP"
      },
      "source": [
        "d_predictions = d_regr.predict(X_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_Aeszeo9Pnx_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eb64dd93-69eb-4ae3-b547-1230da1e84b4"
      },
      "source": [
        "# для всех вин имеем предсказания от линейного и dummy, отобразим первые 5\n",
        "print (predictions.shape, '\\t', predictions[0:5])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(1617,) \t [6.37886848 6.3994996  6.40362171 5.82459689 6.45383134]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WHqBhbChPrNX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d5647d49-c963-42ab-86b3-87c1f47ce7b7"
      },
      "source": [
        "print (d_predictions.shape, '\\t', d_predictions[0:5])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(1617,) \t [5.86863761 5.86863761 5.86863761 5.86863761 5.86863761]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6uesOGk8jW4L",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        },
        "outputId": "66307788-948d-4fd8-81e1-e7dd99e79b82"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.figure(figsize=(15, 8))\n",
        "plt.hist(predictions, bins=50)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([ 1.,  0.,  0.,  0.,  3.,  1.,  3.,  5.,  6.,  3.,  9.,  5., 10.,\n",
              "         9., 10., 24., 40., 49., 40., 51., 60., 88., 70., 82., 86., 66.,\n",
              "        84., 67., 70., 65., 87., 71., 66., 67., 62., 49., 49., 40., 30.,\n",
              "        18., 24., 10., 20.,  4.,  3.,  6.,  3.,  0.,  0.,  1.]),\n",
              " array([4.1477337 , 4.21105059, 4.27436748, 4.33768437, 4.40100125,\n",
              "        4.46431814, 4.52763503, 4.59095192, 4.6542688 , 4.71758569,\n",
              "        4.78090258, 4.84421947, 4.90753636, 4.97085324, 5.03417013,\n",
              "        5.09748702, 5.16080391, 5.22412079, 5.28743768, 5.35075457,\n",
              "        5.41407146, 5.47738834, 5.54070523, 5.60402212, 5.66733901,\n",
              "        5.73065589, 5.79397278, 5.85728967, 5.92060656, 5.98392345,\n",
              "        6.04724033, 6.11055722, 6.17387411, 6.237191  , 6.30050788,\n",
              "        6.36382477, 6.42714166, 6.49045855, 6.55377543, 6.61709232,\n",
              "        6.68040921, 6.7437261 , 6.80704299, 6.87035987, 6.93367676,\n",
              "        6.99699365, 7.06031054, 7.12362742, 7.18694431, 7.2502612 ,\n",
              "        7.31357809]),\n",
              " <a list of 50 Patch objects>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 132
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q7_hTdpujw3x",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c74021f4-299f-4ba1-e77e-0cdff7df30c1"
      },
      "source": [
        "type(X_test)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas.core.frame.DataFrame"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 133
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_xYO5bv8joBY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "34f65dfe-cc3e-47e2-8ffe-18f85998df71"
      },
      "source": [
        "X_odno = X_test.values[12]\n",
        "X_odno"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([6.300e+00, 1.200e-01, 3.600e-01, 2.100e+00, 4.400e-02, 4.700e+01,\n",
              "       1.460e+02, 9.914e-01, 3.270e+00, 7.400e-01, 1.140e+01])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 134
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ONqV7Tgqj27j",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f633ba3e-1fd8-4e3c-c521-fb1f544889f1"
      },
      "source": [
        "import numpy as np\n",
        "\n",
        "regr.predict(np.array([ X_odno ]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([6.65034987])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 135
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "es3QwqrMkDQN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4fbd4f47-7a57-4520-8889-1e548e720ed6"
      },
      "source": [
        "y_test.values[12]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "7"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 136
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M__mogSXPsgv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 505
        },
        "outputId": "dbf18b7e-8cb5-45f6-97c9-b4d6353f31e7"
      },
      "source": [
        "# отобразим разность предсказаний на гистограмме\n",
        "rem = predictions - y_test\n",
        "plt.figure(figsize=(15, 8))\n",
        "plt.hist(rem, bins=50)\n",
        "rem.std()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.7465388196766426"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 137
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uNdXrml8_A5a"
      },
      "source": [
        "## Метрики для задачи рeгрессии"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "thKAFo6xQJpo"
      },
      "source": [
        "### Mean Square Error \n",
        "\n",
        "## $$ MSE(y, \\hat y) = \\frac{1}{n_{samples}} \\sum_{i=1}^{n_{samples}} ( y_i - \\hat y_i )^2 $$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KV7UGsp6PuUn",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "321d9c2f-944d-4826-b429-2ceb61d98b70"
      },
      "source": [
        "# см. ссылки выше\n",
        "from sklearn import metrics\n",
        "mse = metrics.mean_squared_error(y_test, predictions)\n",
        "d_mse = metrics.mean_squared_error(y_test, d_predictions)\n",
        "\n",
        "print (\"MSE,  LR = {0:.4}, Dummy = {1:0.4}\".format(mse, d_mse))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "MSE,  LR = 0.5576, Dummy = 0.7638\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X5MgkDBYQRO2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0a3228aa-6cf1-4d10-f6ec-6f18ff84f49f"
      },
      "source": [
        "rmse = np.sqrt(mse)\n",
        "d_rmse = np.sqrt(d_mse)\n",
        "\n",
        "print( \"RMSE / LR = {0:.4}, Dummy = {1:0.4}\".format(rmse, d_rmse))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "RMSE / LR = 0.7467, Dummy = 0.8739\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fgmeQLfZQUNB"
      },
      "source": [
        "### Mean Absolute Error \n",
        "\n",
        "## $$ MAE(y, \\hat y) = \\frac{1}{n_{samples}} \\sum_{i=1}^{n_{samples}} | y_i - \\hat y_i | $$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GXR0PRMgQSHt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "523c718b-a376-4ba1-e76a-1a3facf1a002"
      },
      "source": [
        "mae = metrics.mean_absolute_error(y_test, predictions)\n",
        "d_mae = metrics.mean_absolute_error(y_test, d_predictions)\n",
        "\n",
        "print( \"MAE / LR = {0:.4}, Dummy = {1:0.4}\".format(mae, d_mae))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "MAE / LR = 0.5806, Dummy = 0.6663\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HYPe7yfoQYGC"
      },
      "source": [
        "### Median Absolute Error "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uAmtTcCIQWw9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "893862fb-6c8c-4604-d2a5-adcfbb92a5e2"
      },
      "source": [
        "medae = metrics.median_absolute_error(y_test, predictions)\n",
        "d_medae = metrics.median_absolute_error(y_test, d_predictions)\n",
        "\n",
        "print (\"MedAE / LR = {0:.4}, Dummy = {1:0.4}\".format(medae, d_medae))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "MedAE / LR = 0.481, Dummy = 0.8686\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GPemtE3eQai-"
      },
      "source": [
        "### R² score, the coefficient of determination\n",
        "\n",
        "## $$ R^2(y, \\hat y) = 1 -  \\frac{\\sum_{i=1}^{n_{samples}} ( y_i - \\hat y_i )^2}{\\sum_{i=1}^{n_{samples}} {( y_i - \\bar y_i )^2}} $$\n",
        "\n",
        "## $ \\bar y = \\frac{1}{n_{samples}} \\sum_{i=1}^{n_{samples}} y_i $"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JrmOH1PvQZfs",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "523c6c54-9d65-48fd-8196-0996c2057b46"
      },
      "source": [
        "from sklearn import metrics\n",
        "\n",
        "r2 = metrics.r2_score(y_test, predictions)\n",
        "d_r2 = metrics.r2_score(y_test, d_predictions)\n",
        "\n",
        "print (f\"R2 score / LR = {round(r2, 4)}, Dummy = {round(d_r2, 6)}\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "R2 score / LR = 0.2692, Dummy = -0.001034\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3mCj8GeK4HiQ"
      },
      "source": [
        "# Выводы\n",
        "\n",
        "- Разобрана задача классификации на примере модели KNN\n",
        "- Часто используемые метрики для задач классификации: Accuracy, Confusion matrix, precision, recall, f1-score, ROC-AUC\n",
        "- Разобрана задача регрессии на примере линейной регрессии\n",
        "- Часто используемые метрики для задач регрессии: Mean Square Error, Mean Absolute Error, Median Absolute Error, R2 score"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S9X6gGIAN_Ss"
      },
      "source": [
        "# Рекомендованная литература\n",
        "\n",
        "- [Линейные модели классификации и регрессии](https://habr.com/ru/company/ods/blog/323890/)\n",
        "\n",
        "- [О метриках качества в машинном обучении](https://habr.com/ru/company/ods/blog/328372/)\n",
        "\n",
        "- [Кривые в машинном обучении (ROC-кривая, precision-recall кривая и тд);\n",
        "](https://dyakonov.org/2019/08/29/кривые-в-машинном-обучении/)\n",
        "    - [Подробнее про ROC-AUC кривую](https://dyakonov.org/2017/07/28/auc-roc-площадь-под-кривой-ошибок/)\n",
        "\n",
        "- [Применение решения задачи: \"Определение вероятности невозврата кредита\"](https://dyakonov.org/2017/12/25/определение-вероятности-невозврата/)"
      ]
    }
  ]
}