3task/week2_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a2a00945-75e9-4543-b03b-16c5353735d6",
   "metadata": {},
   "source": [
    "Лабораторная работа 2\n",
    "Основы работы с JupyterLab\n",
    "\n",
    "Цель работы: познакомиться с JupyterLab, научиться выполнять Python код, добавлять пояснения и смотреть результаты прямо в notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fc6dab54-147a-4a7c-b55a-9b0dedb054f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "JupyterLab работает\n"
     ]
    }
   ],
   "source": [
    "print(\"JupyterLab работает\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b99ed371-9c7b-4678-b99a-eec9f685b08a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Сумма: 15\n",
      "Разность: 5\n",
      "Произведение: 50\n"
     ]
    }
   ],
   "source": [
    "x = 10\n",
    "y = 5\n",
    "print(\"Сумма:\", x + y)\n",
    "print(\"Разность:\", x - y)\n",
    "print(\"Произведение:\", x * y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54c07945-bf4f-42bb-b023-5d02f93ea5f0",
   "metadata": {},
   "source": [
    "В этой ячейке я проверил, что ноутбук конкретно отражает результаты"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7df37e6-67da-45e7-b4d8-dce22e484f6f",
   "metadata": {},
   "source": [
    "Работа с pandas и numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "11be82a1-600d-47cb-bdc7-4ab702a0f25a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Первый взгляд на данные:\n",
      "      Имя  Возраст  Баллы\n",
      "0    Анна       21     89\n",
      "1   Борис       22     76\n",
      "2  Виктор       23     95\n",
      "3  Галина       24     82\n",
      "<class 'pandas.DataFrame'>\n",
      "RangeIndex: 4 entries, 0 to 3\n",
      "Data columns (total 3 columns):\n",
      " #   Column   Non-Null Count  Dtype\n",
      "---  ------   --------------  -----\n",
      " 0   Имя      4 non-null      str  \n",
      " 1   Возраст  4 non-null      int64\n",
      " 2   Баллы    4 non-null      int64\n",
      "dtypes: int64(2), str(1)\n",
      "memory usage: 228.0 bytes\n",
      "None\n",
      "         Возраст      Баллы\n",
      "count   4.000000   4.000000\n",
      "mean   22.500000  85.500000\n",
      "std     1.290994   8.266398\n",
      "min    21.000000  76.000000\n",
      "25%    21.750000  80.500000\n",
      "50%    22.500000  85.500000\n",
      "75%    23.250000  90.500000\n",
      "max    24.000000  95.000000\n",
      "Имя        0\n",
      "Возраст    0\n",
      "Баллы      0\n",
      "dtype: int64\n"
     ]
    },
    {
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       "      <th>0</th>\n",
       "      <td>Анна</td>\n",
       "      <td>21</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Борис</td>\n",
       "      <td>22</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Виктор</td>\n",
       "      <td>23</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Галина</td>\n",
       "      <td>24</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "      Имя  Возраст  Баллы\n",
       "0    Анна       21     89\n",
       "1   Борис       22     76\n",
       "2  Виктор       23     95\n",
       "3  Галина       24     82"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Создаем DataFrame\n",
    "data = {\n",
    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
    "    \"Возраст\": [21, 22, 23, 24],\n",
    "    \"Баллы\": [89, 76, 95, 82]\n",
    "}\n",
    "\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "print(\"Первый взгляд на данные:\")\n",
    "print(df.head())\n",
    "print(df.info())\n",
    "print(df.describe())\n",
    "print(df.isnull().sum())\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "28e4a60d-f585-450a-8835-8179b7abd18d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Имя</th>\n",
       "      <th>Возраст</th>\n",
       "      <th>Баллы</th>\n",
       "      <th>Новый столбец</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Анна</td>\n",
       "      <td>21</td>\n",
       "      <td>89</td>\n",
       "      <td>97.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Борис</td>\n",
       "      <td>22</td>\n",
       "      <td>76</td>\n",
       "      <td>83.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Виктор</td>\n",
       "      <td>23</td>\n",
       "      <td>95</td>\n",
       "      <td>104.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Галина</td>\n",
       "      <td>24</td>\n",
       "      <td>82</td>\n",
       "      <td>90.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Имя  Возраст  Баллы  Новый столбец\n",
       "0    Анна       21     89           97.9\n",
       "1   Борис       22     76           83.6\n",
       "2  Виктор       23     95          104.5\n",
       "3  Галина       24     82           90.2"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "da90f033-a30d-46ab-aa87-637a433341e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Имя</th>\n",
       "      <th>Возраст</th>\n",
       "      <th>Баллы</th>\n",
       "      <th>Новый столбец</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Борис</td>\n",
       "      <td>22</td>\n",
       "      <td>76</td>\n",
       "      <td>83.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Виктор</td>\n",
       "      <td>23</td>\n",
       "      <td>95</td>\n",
       "      <td>104.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Галина</td>\n",
       "      <td>24</td>\n",
       "      <td>82</td>\n",
       "      <td>90.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Имя  Возраст  Баллы  Новый столбец\n",
       "1   Борис       22     76           83.6\n",
       "2  Виктор       23     95          104.5\n",
       "3  Галина       24     82           90.2"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Возраст\"] > 21]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5585d60d-440e-4da8-bbf4-5459dbc5b50d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Имя</th>\n",
       "      <th>Возраст</th>\n",
       "      <th>Баллы</th>\n",
       "      <th>Новый столбец</th>\n",
       "      <th>Категория</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Анна</td>\n",
       "      <td>21</td>\n",
       "      <td>89</td>\n",
       "      <td>97.9</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Борис</td>\n",
       "      <td>22</td>\n",
       "      <td>76</td>\n",
       "      <td>83.6</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Виктор</td>\n",
       "      <td>23</td>\n",
       "      <td>95</td>\n",
       "      <td>104.5</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Галина</td>\n",
       "      <td>24</td>\n",
       "      <td>82</td>\n",
       "      <td>90.2</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Имя  Возраст  Баллы  Новый столбец Категория\n",
       "0    Анна       21     89           97.9         A\n",
       "1   Борис       22     76           83.6         B\n",
       "2  Виктор       23     95          104.5         A\n",
       "3  Галина       24     82           90.2         B"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "80d65487-ea6c-4748-a84f-be79214e7a56",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Возраст</th>\n",
       "      <th colspan=\"3\" halign=\"left\">Баллы</th>\n",
       "      <th>Новый столбец</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>mean</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Категория</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>22.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>95</td>\n",
       "      <td>89</td>\n",
       "      <td>101.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>23.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>82</td>\n",
       "      <td>76</td>\n",
       "      <td>86.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Возраст Баллы         Новый столбец\n",
       "             mean  mean max min          mean\n",
       "Категория                                    \n",
       "A            22.0  92.0  95  89         101.2\n",
       "B            23.0  79.0  82  76          86.9"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(\"Категория\").agg({\n",
    "    \"Возраст\": \"mean\",\n",
    "    \"Баллы\": [\"mean\", \"max\", \"min\"],\n",
    "    \"Новый столбец\": \"mean\"\n",
    "})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "191465db-d1c2-42b2-9e88-65146a2bef1d",
   "metadata": {},
   "source": [
    "С помощью pandas я создал таблицу, добавил новый столбец и отсортировал столбец"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0df4d7a7-a461-40af-b257-ca188fc019a7",
   "metadata": {},
   "source": [
    "Работа с numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f2d09831-5792-4682-bfdd-ffc3efc0df5c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Сумма элементов массива: 15\n",
      "Среднее значение: 3.0\n",
      "Медиана: 3.0\n",
      "Стандартное отклонение: 1.4142135623730951\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "arr = np.array([1, 2, 3, 4, 5])\n",
    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
    "print(\"Среднее значение:\", np.mean(arr))\n",
    "print(\"Медиана:\", np.median(arr))\n",
    "print(\"Стандартное отклонение:\", np.std(arr))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0a9a3266-8789-48c8-8264-c8980006a376",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2],\n",
       "       [3, 4]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matrix = np.array([[1, 2], [3, 4]])\n",
    "matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "71c3ff3e-a464-4221-b7e9-c1881d5b5056",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.,  2.,  4.,  6.,  8., 10.])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linspace(0, 10, 6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9662204e-cba0-4f75-af4a-6e147a77eaf0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.99439456,  0.02189998, -0.82691765],\n",
       "       [ 1.01269877, -1.18328238,  0.8618282 ],\n",
       "       [ 0.04894217, -1.484882  ,  0.03966165]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.randn(3, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "207af23e-4331-42ad-bf3c-b11548d2ba63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[19, 22],\n",
       "       [43, 50]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([[1, 2], [3, 4]])\n",
    "b = np.array([[5, 6], [7, 8]])\n",
    "\n",
    "np.dot(a, b)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "888add68-7af6-4c1e-aa7f-0bffc3076788",
   "metadata": {},
   "source": [
    "С помощью numpy я выполнил базовые вычисления и действия с массивами"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16cbe613-7aca-462c-a121-f17f656b5278",
   "metadata": {},
   "source": [
    "4. Визуализация данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "24118a3e-535f-4cce-b625-00b6fbeb77f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7d522671-9015-40e6-a171-5c66ff4f0e8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 10, 100)\n",
    "y = np.sin(x)\n",
    "\n",
    "plt.plot(x, y, label='sin(x)')\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"Y\")\n",
    "plt.title(\"График синуса\")\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "41b86818-f387-47dd-9959-f29ae4f7b498",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, label='sin(x)', color='red')\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"Y\")\n",
    "plt.title(\"График синуса красным цветом\")\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "024ae66a-97cf-4bcf-97f9-ddf6a2baf89f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wFlu3ImbkSMRMmkQXIwcbSEoy7osVQ0r37ki5806gatVMb1ods1AeO0HGOppkdE6fPMm0BhdmznRhxowYbN7sQlychpIlgVKlNJQuDdSureHBB1NQpAicxd69iPnqK7jWrQMOHYLr0CHg4EG4kpKg1amDlHbtoHXoAK1ZMyTGGMEZmTvCSzjn6GC3aWtj6eDBgyhWrJjHc/w/jZvz58/j+PHjSE5O9vmazZs3+93ukCFDMGjQoMuenzp1KnKGaOWhacDRoy3hcuXFgQMxOHAAmDzZ+Fvu3Jdwxx1b0LHjDsTHa7ArMZcuoeSiRSg3dSoKb9jg/4UnTyL2zTf12/HKlbG3RQvsbt0aSblyZerzpk2blvWdFmSsTYT3OX3gQE58800drFxZFCkpnlkYSUku7N4N7N7t0v//yy/AW29p6NBhJ7p23Y6CBdMXiHYk9759qPz77ygzZw5iuBDzAQ2oWBpRQ4ciKXt2HGvSBNnuvVfmjggRjjn63LlzQb3O1sZSuKAninlOChpfZcqUQfv27ZE3b96QfU779okYP34SihZtgw0b4rFmjQtz5riwfXuCPuHNmVMbQ4Yk46abNLiM+c02uBYsQOzdd8O1b5/+fy0mBlrHjkjp1QsoVw5aXByQenOtXImYn36Ca9o0FNi+Xb/Vnj4dyd9/D61p06BWFvwRtmvXDvHx8RH4ds5Fxjo648xr/0cfxeD112Nw4YIxWVSurKFNmxS0bq2heXMNdJbv2+eiYwV79rgwZowLK1fGYfz4yvjrr0q4//4UDBiQguLFYS+2bkXsK6/ANW4cXFylMup2/fXQbr8dWokSQIkS0Ligjo+Ha/ZsxEydqs81cYcO6YZVseXLoX3wAWKYymG3idgB88ap1MhQhmgWhbs+duzYgK+57rrrtCeeeMLjuZEjR2p58+bVH1+8eFGLjY29bDu9evXSbrrppqD35eTJk/r+8D6UXLp0SRs3bpx+r0hK0rThwzWtaFGOgXFr2VLT9u7V7EFKiqa9956mxcYaX650aU0bNEjT9uzJ+L2HDmnasGGaVqGC8V5u4403jEHL5DgL4UHGOvLjvHy5ptWvnz5ftGmjaZs2BfdTnDRJ05o2TX9vyZKatnKlZh/++kvT8uVL/4Kc9xcuzPh9ycn661IaNEh/b4cOmrZrVyT22nFcCuMcHez121LVcJmladOmmDFjhsdztE75PElISECjRo08XpOSkqL/X73GbDABs08fYPt24MUXgWzZKI8ANG9uPGdpTpwAunUDnn0WSE4G7rrLyHJ/9VXoSRQZUbQo0L8/sHq18V5u4+WXgXbtuGSOxDcQBFPx2WcxuPpq4ydRsCDw7becA4Hq1TN+L50krKdZsACYOROoWRPYvx+47jpgwgRYn88/Bzp3NhK4rr0WYHjtjz944cj4vcxVatoUSQsWYEOvXtA4EbPKulYt4PffI7H3QqTRLMTp06e1VatW6Tfu+tChQ/XHu1Kt+RdeeEG755570l7/zz//aDlz5tSeffZZbdOmTdpnn32me5KmTJmS9poxY8Zo2bJl00aNGqVt3LhR69u3r5Y/f37t4MGDpvQsebN9u6ZVrmwsbIoV07Q1azRrsn69plWqZHyRhARN+/xzY2l7pfC9o0ZpWq5cxjYLF9a0det8vlS8HZFDxjpy4/zAA2vTnB49ehiO16xw4oSmtWtnbC8mRtM+/lizJomJmta/f7pHqFcvTbtwIWvnM+eWa69N92j//nvId9vJXDKBZ8lSxtKsWbP0L+V9u/fee/W/875FixaXvad+/fpaQkKCVrFiRe3bb7+9bLvDhg3TypYtq7/m6quv1hYvXpyp/YqmsUQOHNC0unWN32n+/Jq2YIFmLXbu1LQSJYwvUK6cpi1dGrptb9miafXqpccQduy47CVyAY8cMtaRYejQpDRb4MUXs7bucIdTUd++6XYGbY4Motzm4tw5I1ymvsCQIVkaHI/zmQPBxTq3Gx+vaePHh3TXncwlMZbsQbSNJXL8ePrCJmdOIxRvCf79V9Nq1DB2vHZtTTt6NPSfceyYptWqZXxGlSqXLbHlAh45ZKzDD9P2lC3w3HNJITOUvNMKXXo2tKY9/3xotx82uON33JE+Sf72W+jPZxpMd96Z7iFn0pdgC2PJ1jlLToK6S1OnAh07shQSuOUWIFC1vSmgyNvNNxt5SaVKAdRQKlQo9J/DZA3mE5QtC2zbZuQpUIVPEGwGmxs89pjx+NZbt2Lw4JSQF2hxe//5D/Ddd8b/33kHGD0a5mfwYLZsMKpo//zTyI8MR1Lp998D3btTyM+YiDkxC5ZHjCUbQYkn5ie2aWMYTLfeyrJImFcRlzIA8+YBlFugiFSZMuH7PBpjnLQKFwZWrDAmMTdhUUGwOlwPsL6B/Oc/ybj77k1hrWS/5x7KqBiPH3gAWLYM5oWiUQMHGo+/+AJo2TJ8n0VjjNajmmO6djWSxwVLI8aSzUhIAH76ySge27LFmMRSpUPMBZemnMComTF2LFCnTvg/s1o1wyjLnRtgBSTLCgXBBlC0lsYL6dsXePPN0HuUfPHGG8CNNxo2AZ3ErJYzHVwc3Xuv8ZjdGx58MPyfyXltzBiK5QHnzwM9ehgrWMGyiLFkQ9ieQNkhv/4KfPghzIX7To0aBbRuHbnPbtzYMM5Y+vvf/xpueUGwMHTS0lA6cgSoWxf4+OPIaSPyZ/TDD0bFPA02OlFoG5gG7hStOO4UcxTeey+yK1cODlU8N24E3ISMBeshxpJNueaadHvkueeMaJcpOHwY6NfPeEwfPvWQIg37BVKkinBfRINJsDDMGaKjlGF4OjOyZ4/s5zOKzvA/UwMZinv0UZjHirzjDuP3XaOGMTgMkUV65UqDidbrV18Bv/0W2c8XQoYYSzbmkUeAnj0Nbcbbb9d7QUYXxgMffphN74wl8GuvRW9fKHTZsCFw/DhiH3rIpLFKQQgMBSNfecV4/Omnhk0QDSpVMrzZ9DRR+FL1sYwqX35prBIZdh8/HsiXLzr7wSTS5583HjMEyAZ8guUQY8nGqMVM7dqGoaSqZKIGk6kYAuPqjqU0dFNHC8YoGYbLnl3v9VTeFLO7IATPv/+mC9VzUdS7d3RHj9H0J55Id9ieORPFndmzJ91AGTKEjfCiuDMAXn8dupQ6uxTwYPlp1CuYFzGWbE6uXEZhBitamSo0ZUqUdoSZn6pUh16d+vURddi/4e239Ye1mDtFWQFBsAiPP244KWgHsMDLDD1caROUKwfs2pXu8Yo49BIra61ZM8PFHm24OONiMU8eYP58w4ATLIUYSw6AES9OrIT2SsQTMDl5sUTn+HGgUSPghRdgGh57DCmtWyPu0iXEsmu4rPgEC8DrLRdBNJB4z2uwGWDEi9Ev8sknwNKlUdgJ5iZRR4me66+/NmKDZqBiRcOqJW++CezYEe09EjKBSc4iIdwMGmRIDf39d5ozJXIw5KYmLz7mKsssxMQgecQIJObMiRjO7GoyEwSTwrCbCqlT/YLRHTPBojNGmphfzRSdxMQIfjjzIdXKkE20o5XE5Q/GTRmvpNYC5VMEyyDGkkPgyvOjj4zHNJYiFnGiKibL8ZSPnjXGZqNMGWykQKayKukBEwSTMmIEsHq1odpPnSMzwkpcivFTi/H99yP4wU89ZRhMTNRUOUtmgq5AajswL+L334GZM6O9R0KQiLHkIKjo3aGDocLP8t6IFICxrpkCMBSENLHOyK527aBxFXrsmOEiFwSTJnW/9FL62oOV6WaE+6WkS7j+iMjijPoJLNNn2O2bb6JbQBIIGnJKPoUZ8RL6twRiLDkILmpYXpwtGzBtmlHqG1b27gWGDk13Z5kp/OaFFhuLZBp2ZNgwI14pCCaDtRE0mNyvt2bl7ruBdu2MiJMy8MIGV37Kk8SEbrPFJr2hBUnX2/r16UlegqkRY8lhsHJG9XOixzqsCvyc2dkst3lzQ0XX5Gh0u3F2p+vNTEnoggBg7dr0lDomT0daX/FKFmcffGDcc2G2cmUYP4xij2xrwgxzzjtmhwqebOxLuL8MHQqmRowlB8IFWPnyRjV/2BY1nNlZjk+YtGCGuuZgZ3e68amzQMU/QTABdJwwqZtJ02xo36oVLAFbPiqRfiWaH3IYxlKuq2eeMW9s0htWCLNUmTmSUdNZEIJFjCUHwnYI6rfJ6FhYxONokXGGp3R4kyawDJzd77/feMwcK16dBCHKTJwIzJ0L5MgR2fZmoYo40Qv211/AnDlh+AAuyrZuBQoXNnVe5GUwyZsuQjJ8uBGSE0yLGEsOhY032aKAudeffRbijU+fbqhfMkfprbdgOegep5onpQSk0a4QZbjmYDI3YVU8RR+tBOcZSggo71JIC0soGqfaJtG7xEZ1VqJFC6BbN2NRZtbSRkFHjCWHQjtm4EDj8bvvGhX+IYE/+mefTU+05ExpNdglXOUscXaPqFCMIHjCTjzLlxuNchllsiL0ZNMrtnChIbkWMrjSY6PcsmWNvpNWRE3E//sfsHlztPdG8IMYSw7mzjuNin5W1yhvcJZhrg9FYNi00spxeLrzmfuwc6ehCCwIUfYqce1hlXQcb0qWTBfSpAMoJNHtkyfT24Yw1sf8AivCvCUWwPBgi2yJaRFjycEwj0AtapjXzB6PWYI/diUPzlI7lsZaFS7j+R0Iv5PkLglRgBIfS5YYdoDVBZ+Zxsg1FGs/QrL+YOEIV3rUR2NegZVRC8sffwS2b4/23gg+EGPJ4TD/mqLaNJSUwneWZvZVq4x8H9U018pwKc8ciI0bgfHjo703gsPg2oMOE8IIU7FisDSsllcRei7S2LblinGfsJjrw2RpK8OemZ07G4syabJrSsRYcjicY1R+JBV3uVC7YpRXiSWxVvYqKbgMptQ54QQWEclzQTCYNcvI8aGIrOoYZHUoWE2jic6TceOysKGvvjLKeKnOecstsAXKu/T990b4XzAVYiwJejEGw+ZM8r5i7xJjBZzdGdtT4Ss78OSTRgyElXHSx0mIICpXiWuPEiXsMfTUjKTDllAC4YrWHxSNZX81wtikFTTcguGaawxRXOpGRbzbuZARYiwJugajWtRQIZjVuJlGtQphj4MyZewzqkWLptc9i3tciBDUI+KN7c3s4lVSMELP78X1FT1nmeann4ADB4yscVap2Ak1EY8cCezZE+29EdwQY0nQoSebqt5U3R89OpODsmkTMHas8dhuM7tavdJjxkad9DAJQphRRVEPPACULm2v4WbulcrHZmFJpqAriondKqZn1ma5V8p11xnaS5QroaaLYBrEWBLScpdUaS9DcZlyjytJYZa/sjLFblAFkB4zIt4lIcywnoC1EvT42nHtQZTQNvOWtm3LxBspA06la8bzGJ+0I+7eJbZCEUyBGEtCGlzFcg7asMGYrINi717ghx+Mx3ZuPsu6Z+ZGcHbnAAlCmPj00/S1B729dqRmTaBLF2NRlqk8SeVV6tMHyJ8ftqR1a6PtErucf/tttPdGSEWMJcGj+Eu1RQt6AmMJHV3GdB0zQdGuVK+eXnUTMgVPQbi8Iv6779Jbm9gZpUZOe4Dh/wxZudIIhdMNzsILu8JFmXLz03LOksaCECrEWBI84ATN3ypbLDAVKSAs3R0xIt3zYneYI0HoScuygqcgXA4jL3Qo0LHA9YedadkSaNjQKChhYUmGqASnO+4w2pvYmZ49gQIFgB07gEmTor03ghhLgjds5XbTTcZjVZ3rF2aCnz4NVKkCdOhg/8Fk8iV1XXg1oxaKIIQQOhBUCE4tWuwMv59SJef3vnAhwIt3705vam11KfNgOwgwL4IMGxbtvRHEWBJ8oWSSaA8cO+ZnjJhsoJaDlBdmNqrd4eyuRGI+/1xEKoWQQgcCHQl0KNx1lzMG97bbDKWRw4czqMJlw1xak8znadAAjoBzDeccJpBKg92oY7kr3GeffYby5csje/bsaNKkCZYGKOVu2bIlXC7XZbcuzCxMpXfv3pf9vWPHjnAy118P1K9vuMeHD/fzosWLgTVrDMHG3r3hGFgVlycPsGWLiFQKIUWlwjF3mY4FJxAfn56e8+WXAUQoVaKz3RO53KlQAbjxRuOxcjkKUcNSxtLPP/+Mp59+GgMHDsTKlStRr149dOjQAYe5LPHB77//jgMHDqTd1q9fj9jYWHTv3t3jdTSO3F/3E0XPHAwXM8q7xN8o87cvQ3mVmD/A/gVOgYZSr17pq11BCJFcwPTphoNWOS+dwn33GXJJy5cbOdyXwQrUI0cMEUq3ha4jUMYhs/5Pnoz23jgaSxlLQ4cORZ8+fXDfffehZs2a+PLLL5EzZ06MZFakDwoWLIjixYun3aZNm6a/3ttYypYtm8frCtAP7nBoA1E8bv9+YOJErz+ydOV//zMeO21mJ/36Gfd//GFIJwhCCOUCKOvlJAoXNlouEZ+ebPaBI8zhoTisk2DYkToLLKYZNSrae+NoLHPmXbp0CStWrMCAAQPSnouJiUHbtm2xaNGioLbxzTffoEePHsiVK5fH87Nnz0bRokV1I6l169Z44403UChAI9iLFy/qN8UpNlUDPTCJ+i1UqG2FcpvBwhXuPffE4P33YzFiRApuuCG9fDXm668Re/EitAYNkMR4XRT2L5RkepyrVkVsixaImTMHyZ9/jhTVGl4I/Vg7Ri6AU7ELjzyShMREzXHj/MADLowZE4fRozUMGZKk673pbNuG+JkzocXEIOnee00310RinGP69UPsY49B+/RTJDklPzSC4xzsNi1jLB09ehTJyckoRneHG/z/5iCS35jbxDAcDSbvEFy3bt1QoUIF/P3333jxxRfRqVMn3QBjyM4XQ4YMwSAfF8ipU6fqnqtQQ49YNKhYkUZlW/z1lwvffTcTRYpcAFJS0Objj8G5bHWzZthNjQGbkJlxLnn11bhqzhwkfvEFpjZsCI3JF0JYxtruTJxYAefO1UXZsqdw5syskFaKW2WcWS9SsmQb7N+fGy+/vAHt2+/Sn685ahSqADjUsCGWULmbNxMSznGOLVwYHXLmRPz27Vj+1ls4TL0FhzItDON8jtXNQeDStCvq+xxx9u/fj1KlSmHhwoVo2rRp2vPPPfcc5syZgyXsyhiAhx56SDeA1q5dG/B1//zzDypVqoTp06ejTZs2QXuWypQpoxt0efPmRSgtXp4c7dq1Q3yULsZt28Zi7twYDByYjJdeSoFr6lTE3XADtHz5kLRzJ+DlpbMiVzTOiYmIq1wZrgMHkPTf/0Jj3FIIz1jbnKuuisOaNS589FEyHnkkxbHjPHRoDF54IRaNGqVg0aJkTrSIq1ABrqNHkfTbb9BUsrOJiNQ4xzz9NGI//RQp3bohecwYOI3EMI4zr9+FCxfGyZMnA16/LeNZ4pehp+fQoUMez/P/zDMKxNmzZzFmzBi8/vrrGX5OxYoV9c/avn27X2OJOU68ecODGI4fTLi2GwyszJk7l+HyWLz6aixiUkUoXb16Id5m7QYyNc58HXtTDRqEOOZUqN5xQujH2sasWmUUlTLB+Z57YhEf79ub7YRxZkrSq68CK1bEYN26GDTc+puRH1mqFOIo/mbifKWwj/ODD+qJbTETJiCGid5M9HIg8WEY52C3Z5ngZ0JCAho1aoQZlLtPJSUlRf+/u6fJF7/88ovuCbo7iAva3r17cezYMZQoUSIk+211br3VaIOyaxcw46fDwIQJnknOToaWJEO18+cbUgKCkElUbQo76TipqDSjRG99TaYSu2komNhQigj16hn6Usyv+fHHaO+NI7GMsUQoGzBixAh899132LRpE/r166d7jVgdR3r16uWRAK5gnlLXrl0vS9o+c+YMnn32WSxevBg7d+7UDa+bb74ZlStX1iUJBCBHjnSnyddDjug5S3qfgho1ZHhKlWLSmzEOqqGXIAQJFauVEKPqyeh06Kwlo/+bjDOzlxnJzErJ2umok0Sa60YFSxlLd9xxB95//328+uqrqF+/PlavXo0pU6akJX3v3r1b10lyZ8uWLZg/fz4e8PGDY1iPOUw33XQTqlatqr+G3qt58+b5DLM5FS7syNgNVXAUhWRmd4cVOuS//5WGl0KmGD8eOH7cULD2E/F3HFyHsXvS6bOxGIMeQOfOxgAJhqw747WrVxvxWyGiWM632b9/f/3mC0oAeFOtWjX4y2HPkSMH/vrrr5Dvo92gOkCjamewYktu/DfhATylfOWCobBLXS7qLc2cCbRrJ6MiZCoER3vbT+GtIwVx+96fhGcHxGE4+uLBh3wLDjsSxmm7djU07uhdckrbF5NgKc+SED0eLDxOv/86x+PQclq/Ai5ksN1Ljx7GYwnFCUGyZw+lRozHTuoWFAz3lpiKeFzCMlyNdaU7RXt3zBmKY/zWrSJbCD9iLAkZc/487lz3InLiLDaeLKW3hRPcUFe733+XlgRCUNCupsObYadKlWTQ3Cky/ht0wZ/649FjxOXmQdu2QOnSwL//GnFcIWKIsSRkzPjxyHdqD27PZUxgX38tg+bBVVcB1asbnYd/+UUGRwgIayRUjq4kdnvBJK6JE3EP/pvmQOF4CakwXqvyJP20+RLCgxhLQsakhpd632K0dfn1V6OSR3BLtFDeJQnFCRlA3bJ//jF6MlOaQ3CD+TiXLqFL7d2gjBtTAefMkRHyQM01jONKb8qIIcaSEJiDB4HUJPjrXrpeL0xhK7w/DSeToKC+Asucqbm0fbuMi+AX5RC4804gDN2RrM0PP+h32e7tgdtvTy80FdyoXBm4/nrD5fb99zI0EUKMJSEwyg/etCliqlfVJ3j1tOCluaQq4WQCE/xw9izw22/G41R5OEGxY4ex2KCn9s470/Td6MlmhFtwQ508o0YZyW9C2BFjSfAPf4QqrNSrl37Xs6fxX3qWmF4guKFyCThmkmgh+IA5uezbyaTuJk1kiHx5lXTRqVKlcO21QPnywOnTkst8GbfdZrglt20Dli+XEykCiLEk+IdNq9atM4TQUhvF1q0L1K6tpxXoxV+CG9RAYSPG3bsl0ULwyU8/Gff00NKBIrgtzFS87Z57jItTTPriTNlRQiq5cwPsl+d+UglhRYwlwT/Kq8QfJYUX3YRkiYTifPSGSTUqJdFC8IbV3lOmGI9VOFtIZelSw0tCb4mb6K0KxXHcjhyR0fJA6bv9/LN0D4gAYiwJvklKSm/YqMJLXsYSBdP37ZMB9EAthceOFdE4wQPmKrEPKr2zNWvK4HigvErsKEyvSSpU5Gjc2JiOaBMIbrAvJUsG9+8H5s2ToQkzYiwJvqEldPgwwObDXk2Fy5UDmjc3POfiAfaCA1OiBHDiRLpEsyC4RUvUYkNIhTH9MWM8XUluqKekKs4L9i9VXjiZiMOOGEuCb9Qyjj/G+Hi/DhQJxfkQjVM1z7IUFlKhB1a1rlTREyEVSpMcOwawIToVqr3gePFnxUjdli0yah6oeC5LBml0CmFDjCXhchgrUNnbKgfHi+7dgbg4owH2xo0yiB6oMfvjD6l5FtK0FumJbdbM8MwKbqhwPy/8nFS8oA3Vvr3xWBZnXrRqZQwQE+KmTZPTKoyIsSRczowZxo+vaFGgRQufI8ToHEPm7nOdkMo11xhXxDNngEmTZFgEjyo4wQ0KKE2YkOHgKE+2MjoFH55sCcWFFTGWhMtR4SNqefhY6XlPYDSWZAJzgzXhagJTuRiCY2GR17JlxnWNHlnBjcmTDaVOLi7YY9EPN95opOgwDEc1E8ENZWSOG2eIeAlhQYwlwZOLF41KrgAhOAUVBVi4QuHdxYtlID1QiSlU76SqnuBYlL1MrUVGTAQ36CpSC7MAwlOUL1OebOlV7cOTTfVOGp0TJ8rpFSbEWBI8Ydz75EmjoosSugGgJIrSRVMtHIRUGjQweji5hxkEx+FeMSohOC/421AXd+WJDYDyytFYEk+2GzQy1eJMQnFhQ4wlwXcIjjMT4wYZwAWhKsaQCczPBCZVcY5l7Vpg0yYjhEQJISHzIThfobj162UkPVCWOHMkKVsihBwxloR0LlwwKriCCMEp6BrPlQvYtQtYsUIG0wM1hrwoyATmSJSd3LkzkC9ftPfGpCE4LsyC6P3CUJySfJNQnBd16hhKp5QPUGkUQkgRY0lIhxd15teUKWPEwYPs8NGlS7p3SXCDTfRq1TKkGJh8KTgKelpVeFoSu71gIrIKwWVicNRLpSougCdbciLCghhLgu+VHrtYBsmttxr3EooL4F2SqjjHsWEDsHWr0YdaLSiEKwvBKZgjKaG4DCZi5p2eOiWnWogRY0lIX+mpROQgQ3AKhhiyZwf+/htYs0YG1AM1ltOnGyrFgmNQuq4UVGQISXBDxdGCDMEpJBQXgBo1gGrVjFAcq3CFkCLGkmDAHxdXehUqZGqlRygf0KmT8VhCcV5UrQrUq2d0BZeqOEehoiGqfZfgY2F2BfFJqYrzA41O5V2SUFzIEWNJMHBPrsjESs+7Kk7Ken2gyqCUq0GwPdu3G5VwLChV8hqCWwiOBlMmQ3DuVXEMbW7ebIQ6BTeUZa7GWAgZYiwJhhClastxhcvgG24wJjDmaMgE5oUa06lTjRYogu1RdjFbd7E1kHDlVXDesKpQVcWpTQmpNGxoGKE0lDjfCCFDjCXB6AXHKriSJa9opeedSyChOB9VcZUqGUYpV3yCYxy1Kioi+KiCC0KI0h8SivMDjU+1OJNQXEgRY0lI1+Xo2jVTVXCBBCoFPxOYaKDYnj17gKVLjcPOn5TgBiu1aDCVLQs0bnzFQ8PQpgrFbdwoI+yBstCZF8ZkbyEkiLHkdJh4rIQoszizM5cgPt4Iw1G1WPCRt8REenqYBNuH4NgtqHjxaO+NyVB6Y/w9XEEIzj0U17at5yaFVJo2NU48tq2aOVOGJUSIseR0Fi4EjhwB8ucHWrbM0qYKFEifwMQD7EWTJka/PeqfyATmCGNJQnBeJCWlV8GFwOWmNqHWekIqjA5IUUnIEWPJ6aiwEDO06RbKIioUJ8aSjwlMze4SirMthw4B8+YZj0UywIsFCwytsYIFgebNszzW9GTTObVsGbB3b5Y3Zy/UyUe3G6MHQpYRY8np/Rjc3eIhgBMY7YLVq41+cYIbMoHZHv6c+LNinQTTcgSvwVGTRFxcloeGkSbVlWn8eBlpD1q0MIxSRg3mz5fBcaKx9Nlnn6F8+fLInj07mjRpgqXMpPTDqFGj4HK5PG58nzuapuHVV19FiRIlkCNHDrRt2xbbtm2DI6AQzI4dhvy2KmXLIkWKAM2aGY9lAvMxgTFWyQmM4U/BtiE48SoFWJiFMOtdQnF+YJRACXyJm995xtLPP/+Mp59+GgMHDsTKlStRr149dOjQAYcPH/b7nrx58+LAgQNpt11e7o53330Xn3zyCb788kssWbIEuXLl0rd54cIF2B4VDqKhlCtXyDZ7883GvRhLPiYwhjvdx16wDSdOpKejibHkY2G2c6fReZv9X0JsLHHcOf6CGyppjhZ8SooMjZOMpaFDh6JPnz647777ULNmTd3AyZkzJ0aOHOn3PfQmFS9ePO1WrFgxD6/SRx99hJdffhk333wz6tati++//x779+/HOCeUWKgLdohCcN7G0uzZMoFdhrqKcgLjaluwDVOmGDnMNWsaXW4EN1QWNg2lnDlDNjQcZ7ZE47iLhJkXrLZhL6p9+4CVK+V0zCJZDxxHiEuXLmHFihUYMGBA2nMxMTF62GzRokV+33fmzBmUK1cOKSkpaNiwId566y3UqlVL/9uOHTtw8OBBfRuKfPny6eE9brNHjx4+t3nx4kX9pjiV2uE5MTFRv4UKta1QbjONf/5B/Nq10GJjkUTPUgg/o3x59nOMw5YtLkyYkIQePcxtFIR1nL1p1QpxOXLAtWsXEpmZ2qABnERExzrCjBsXq68/u3RJRmJidFfyZhvnuLFjQaGApBtugBbifbrhhhhs2hSLsWNTcNttyY4eZw9iYxHbrh1ixo5F8rhxSGGPSouSGMZxDnabljGWjh49iuTkZA/PEOH/N1OZzAfVqlXTvU70GJ08eRLvv/8+mjVrhg0bNqB06dK6oaS24b1N9TdfDBkyBIMGDbrs+alTp+qerlAzjUJuIabSuHGozXGtWRMLlywJ+fZr1aqJLVuqYMSIg8ibdwWsQDjG2RdX1auHkosX45/338fmnj3hRCI11pEiKYkLA3aTjkGhQgswadJxmAEzjHOOw4fRfvVqaDExmJaQgEuqtVKIKFKkAIDrMXFiMv74Ywri41McOc6+KFOmDBoCOP3jj5hzhd0ZzMS0MIzzuSB76FnGWLoSmjZtqt8UNJRq1KiBr776CoMHD77i7dK7xdwpd88ST8r27dvrOVKhtHh5crRr1w7xISjrdyf23Xf1+4L334/OnTuHdNv6dgu69EjTmjWl0LZtMV1t16yEc5x94Tp+HFi8GFU3b0bFMIy9mYn0WEeKWbNcOHcuDkWLanjiiaZ6A91oYqZxjvn0U/1eu/ZatL3zzpBvv2NH4MMPNRw4EI/s2TuhQwfNkePsk6uugvbpp8i/Ywc6s+2SRUs0E8M4zioyZBtjqXDhwoiNjcUhCpm4wf8zFykYOMgNGjTAdrYE10tPi6dtg9Vw7tusX7++3+1ky5ZNv/nafjh+MCHfLhPiU0OXsbfeitgw7DPVi+mwO3TIhYUL49GuHUxPuI6fP30F17p1iN+/32h86TAiNtYRQjlLunRhxa15vpcpxjlViDLmllsQE6Z9YeHXV19RID8urYbCcePsC/b7ZHny/PmI/+sv4JFHYGXiwzDOwW7PMgneCQkJaNSoEWaw6WsqzEPi/929R4FgGG/dunVphlGFChV0g8l9m7QyWRUX7DYtO7MzuZgdqsuUCctHUGuJNgERhV0v2Iae1iRRTUUFy8Kfkqr8VNXaQioUoZw717PyIwy4SwhI4ZcX6qSU8uQsYRljiTD0NWLECHz33XfYtGkT+vXrh7Nnz+rVcaRXr14eCeCvv/66nkf0zz//6FIDd999ty4d8OCDD6ZVyj355JN44403MH78eN2Q4jZKliyJrnbugKlaDoR5Ceb+G5XCLy+UJamOhWBZ2AuRcmV0NlvBgxpR2AuRCtJ16wIVK4btY1q1AvLkAQ4cMBS9BR9zzaxZwOnTMjROMJbuuOMOPUmbIpIMk61evRpTpkxJS9DevXu3rqWkOH78uC41wDwl5uXQa7Rw4UJddkDx3HPP4bHHHkPfvn1x1VVX6dVz3Ka3eKVtYBXf1KmeP6IwwSJD5ruzCzsVvQU3lKEqE5jlUQt2nu8hlCuzB8qtHEavEqGhqtL/xJPtRbVqQJUqLClPn/sFextLpH///rp3iKX7DJexzF8xe/ZsXbVb8eGHH6a9ltVtf/75p56z5A69S/RA8e8Uopw+fTqq2lkkZc4c6ikYvQIYhgsj7vpzMoF5Ub06UKmSMYFNnx7W4yCEFwnBBbEwC7Ox5P4RMtd4wQZ6EopznrEkZBGVI0PPBhOLwoxMYAEmMAnFWR4qjCjljWgkFpsa5iqphVkE9MRYFccqxI0bDbFwwQ1lLDEsSgVPIdOIseQkmDgUoXwlRZcu6Y11d++OyEdaB2UscQKTrFRLrz0oYcPCI8ENntfuk0CYYdtFVTehPlpIhRVxHCAm3AcQcRb8I8aSk1BLLgb43VTLw4l7Y13JZfbiuusoGW9IOQRoCC2YFwnBmWdh5v5RUmTqRVycYbQSmYivCDGWnIT6kbRuHdFMVDWByWrPC+p7MHbgfmwEy0DhXyUoLJIBXmzZordU0tVoI7QwI8oeYN3E2bMR+1hrIHlLWUKMJSehllthroILNIEFqSzvHCRvybIwL//CBUMUuU6daO+NSeeali2NZq4Rgk11K1Qwcsvd5PMEwh6gXKDRkN26VcYkk4ix5BSOHk2PVSvrJUKwbzEvKLyw0GAS3OjUychKXbcO2LVLhsZCKGcg7V3m6wtuKDdyhLPeeRzU9CahOC/YiovGKxGBykwjxpJTmDzZSCJm5+kI9wdyn8AkFOdFwYLpWakSirNUSo5qcRJhR635OXECmDcvKgsz77C/iOEGKCoRMoUYS04hCsmW7rgbSzKBeSGhOMuxdi3Atn7UEmvRItp7YzLYg4yq3RT/DaNqtz94PJiSyeMjYrh+JuL584GTJyN+bKyMGEtOgMKHnMCiuAxmOwKKolM+gO0hBDfUMZk9W9oRWATlVWrTxjivBT9ablGAx0PllIsDxQsar1T0ptaSiOFmCjGWnABd4qdOAUWLGoIwUYBtT2gwEZnAvKBifOXKouZtIdQ5rFpsCKnQo8SQf5RCcAqREAiAOmmVxS8EhRhLTlrpRUgczh+StxQgqUtNYOpCI5iWf/9Nr5UQY8kLyplT+DB//nSBtSigjgvlyyhjJvgxliQnImjEWHICagURxZWe+8cvXMgmx1HdFfMhE5hlYLsz1kqwyrNcuWjvjUkXZqzypBBilKCaOltf0haQ9YcPMVwmdbFXz6pV0TlAFkSMJbtDYThqanDiiqA4nC/KlzdyPumpVylUgltWKrOF9+0D1q+XYbHA2kO8SubLV3JHQnF+YAeHdu2MxxKKCxoxluyOWlaxPJ2tNaKMhOICZKVSWZ3IBGZa6FFSPykxlrxg9Qb1whjqV8r0JphruDBjjYvghuQtZRoxluyOuvDSLW4C1ATGCw49TIIbkrdkepYtM/Rdqe+n5LGEVJQV2bSpoR8WZRo3NmpaTp82KuUFN9T1YPFi44QWMkSMJTvjLpltkmUwcz7p4GIOqPSO9TOBiQaK6dce7dsbnSMEH8aSSRZmdHCpXZG8JS9Klwbq1jWSupiEJ2SIGEt2Zs4c4Px5oFQpoHZtmAFeYNiiiIiEgBdsalW9uuFyEw0UUyL5Sn5gnEs1YzOJseS+K1OmRHtPTIiE4jKFGEtOCcGZqHmV5C0FMbtL3pLpOHQIWL7cdPaAOaA39MwZoFgxoH59mAXmMdPDxJqJPXuivTcmNZZoSUpORIaIsWRnTOYWV6jcT7YiOHAg2ntj4rwl0UAxFco70agRULx4tPfGpINDt3EUtdy8YepUkybGY/EuecHcMuphSU5EUJjnrBZCy/btwLZtppAM8IZJl7zgEAmX+9FAoRW5Zk0Ujo7gD1Httt7CzH1xJsaSF7w2qJwI8WRniBhLdp+8mjc3SndMhuQSBNBAYcMxIhOYaUhMTDfsTVIrYR4Y32Kcix4lpd9jwrmGaYA8joIbkrcUNGIs2RUTr/TcV3u8AEm43Asp4TEdrLBmk/ZChaLWXtG8KJfN1VcbA2Qy6MUuXNhoj8nuAYKPiXjlSsmJyAAxluwIK+BMJhngDfMIKCHAPlvUrhF8GEvSF8Y0KMV5SgbExkZ7b0yGyRdmdHipaJOE4nzkRFCQikhOREDEWLKrZAA1lqilwQZWJg2XK4+9TGBesOEY+8JQLnratCgcHcEbdY6aQJjaXDCupWQuTGosEXHWBkCSuoJCjCU7YlLJAG/kNxoAySUwDexav2JFumdJcIPeT0pkM86lqjZMCI8bp0LWTOzfH+29MRnK7caFmeRE+EWMJTtikeZV6jdKJW9Wrwo+lsKM/4iEQFRR0QnKB4lkgJ+5xmSSAd4UKZIebZIm3l5cc016WwW1KhAuw7xnt3DlkgG8USpbVVWZFEYJ69QxbAGJNnnBxmM5cwIHDwJr10bnAAkeF1cJwVkvX8kdCcUFyIlQ1wrJifCLGEt2ndl5sc2TB2ZHQnEBJARatTIeywQWNZg2JsaSHxjPoiHP+JYF4pNqruHCLCkp2ntj0sERt5tfxFiyG+pkVzEuCxlLvDAJPgZHJrCosWoVcOSIse6g4LHghjLiGd9inMvkUNmgQAHgxAlgyZJo743JUNcLamQcPx7tvTElYizZrZmlkgywiLFEBxgFq9l3SwSrvVDHUPXdEiKOslNbtwYSEuQAWDUERyj5oBxgateFVMqWBWrUMFas0sTbJ2Is2a0yhRdVamfUqwerRJt4ISISbfKicmWgQgWjPHv27CgcHUEkA/zAOJa6qFoomUvylgIgnmx7GUufffYZypcvj+zZs6NJkyZYylIqP4wYMQLXXXcdChQooN/atm172et79+4Nl8vlcetooR+/X+U8E1emeCOtT/zAXBDlXZJQXMShYrdSfLaIozZyUEmW8Sw2YrWQpLk6jiq8KvjJiZAK3MuwzhUVwM8//4ynn34aAwcOxMqVK1GvXj106NABhymE4oPZs2fjzjvvxKxZs7Bo0SKUKVMG7du3x759+zxeR+PowIEDabeffvoJlsRi+UoKtbu8MPECJfgYHDGWIs7MmYbsTNWqhoNP8KGnwCbdrKayCJR+qFtXKnD9NvHOnh3g9XHjxkgfGtNjKWNp6NCh6NOnD+677z7UrFkTX375JXLmzImRI0f6fP3o0aPxyCOPoH79+qhevTq+/vprpKSkYMaMGR6vy5YtG4oXL552oxfKcjDph8slYoHKFHcqVjQuSPTsex0agTFKXoy2bQP++UfGI4JICM5+CzP3XZbuHl7kyAG0bGk8lpyIy7DMkuDSpUtYsWIFBgwYkPZcTEyMHlqj1ygYzp07h8TERBQsWPAyD1TRokV1I6l169Z44403UChAQ8iLFy/qN8UpdmjUlf8T9VuoUNsKZpuuyZP1g6nVr48kGnsWa6/drl0Mtm6NxZQpybjxxsiWxWVmnCNOjhyIveYaxMyfj+RJk5Dy0EOwMqYeazcYhZgyhb8oF9q2TUJiogYrEdZxPnECcUuWgL0BEilvYfJj6U2bNi68914cpk7VcOlSUpaaHFjlfA6WmHbtEDtlClImT0by44/DLCSGcZyD3aZljKWjR48iOTkZxYoV83ie/9+8eXNQ23j++edRsmRJ3cByD8F169YNFSpUwN9//40XX3wRnTp10g2wWD8dM4cMGYJBgwZd9vzUqVN1T1eomRaEYmPDUaNQBsC2SpWwSbU7sRAFCvC4XoM//riAzp2nR6VLSzDjHA2qlCuHmvPn4/B//4ulZXiUrY9Zx1qxZ09u7N7dBvHxyTh/fgomTUqGFQnHOJdYuBBXp6TgdOnSmLl+PcCbhbh0KQYJCZ1w4EAcvvhiHsqXP2378zlYcmfLBspTanPm4K/ff0cyw3ImYloYxplOFFsZS1nl7bffxpgxY3QvEpPDFT169Eh7XKdOHdStWxeVKlXSX9fGjwI2vVvMnXL3LKl8qLx584bU4uXJ0a5dO8RTkdsfKSmI69tXf1jx4YdRoUULWI3rrwfeeUfD4cO5ULVqZ1SpErnPDnqco5loMXo0im/ahM7sPmzGfbTLWKfyySdGhkKLFi7ccov1Qk3hHOfYCRP0+5y33ILOJm+p5I/WrWP0SNOFCy3QuXOK7c/noNE0aO+9h9hdu9AxRw5oJpGFSAzjOKvIkG2MpcKFC+uenkPMzXGD/2eeUSDef/993ViaPn26bgwFomLFivpnbd++3a+xxBwn3rzhQQzHDybD7TJXiUnuuXMjjlaHBX+0jBxSc4kV8rNmxaNmzcjvQ7iOX5ZhtVGRInAdOYL45csNy9LimHasU0mvio9BfLylUjvDO86MT6YOTmzHjog18THMKG+JxtKMGbF4/nnfEQQ7nc+ZHpzhwxHH43zTTTAT8WEY52C3Z5lZICEhAY0aNfJIzlbJ2k0DSOu+++67GDx4MKZMmYLGqpNiAPbu3Ytjx46hRIkSsFyyJfMHLKycJ4mXfqAMBD1KRKriws6FC8CcOcZjq6qIhI2tW4Fdu4x5xoIebO+5Zu5chmGivTcmQ530kgFvTWOJMPRF7aTvvvsOmzZtQr9+/XD27Fm9Oo706tXLIwH8nXfewSuvvKJXy1Gb6eDBg/rtTKoaMu+fffZZLF68GDt37tQNr5tvvhmVK1fWJQksg4UrU9xRRXws2bZJvmToEAmBiLFgAXD+PFCyJKLi4TQ16gLKMnNK71uU6tWNRt6s05k3L9p7YzK46Ga+7pYthmEsWM9YuuOOO/SQ2quvvqrLAaxevVr3GKmk7927d+s6SYovvvhCr6K77bbbdE+RunEbhGG9tWvX4qabbkLVqlXxwAMP6N6refPm+QyzmRIafpzdbWAs1a/PcKvxlYIscHQOypJcscIIuQphtwfozItGoYFlhG8tjOi9BoBCo02aGI9tkrgeCiyTs6To37+/fvMFk7LdobcoEDly5MBfVg9rsBcc3TAUK2J7DAujok3UBOUFywapOaGDeXlsYcMGepzAevaM9h7Z3liyuD0QeuiGsVjvyUDwK3zzjUSbfMKTnyrB/DE8+GCkD40psZRnSbBvCE6hLlASLveBOsay2gsbrB9Zvdp47KYwIhBePJngQ09+BoUyVoD1O1ygbdjAXNVo743JUDmSzBGmjL0gxpLlsdkyWH0NFn0dOxbtvTHpBEZjSXo3hbUKrkEDox+14CcEZ4P4JLWJVVs7WX94cfXVAGVw/v0XWLkyCkfHfIhnycowzMg2GEzGY1KeDWBSbe3ahi0grU+8aN7c6N20f7/0bgoTNlt7hGdwbOLFdj/OVs/GCDlssaSkc8TNryPGkpVRy6FrrgHy5YNdkAnMDzSUVLm2TGAhhwa6GEtB9J5UHk6bRbYl2uSF5ER4IMaSHYwlG01e3r9RiTZ5oY61GEshh107Dh40+olSIFWwf3ySRV8SbcpgImau2umst4SxOmIsWRUug9QEZrOYASVcqNzApMsg2/45B3WsqZro1sxZyDrK/mTjdasoh0QMm7rcJNoUAFZYV6oEJCUZrRUcjhhLVoVJd8ePG+E3laVoE9iLWMkGiAPFCyZ0UUaAqolKX0sICTa1B7IO3bs29WJ7100IXkgoLg0xlqw+s7dubSyPbIbkLfmBVUgygYUc2p5sfeF+7gmpsLaeYr82jU+6R5tSmzsICgn7pyHGklWx+TJYfS16fyXa5IUshUPO/PlGT7hSpYAaNUK/fUujXC5097LIwGYw0lShgqHtq3oCCl6tT7am9gR0MGIsWREm26l+IDZ0i5M6dQztO674ueIT3FBqiQzFHjkiQxPitYcNJIRCi41DcApZf/hBWp+kIcaSFeHyR7U44bLIhvCCJRNYBq1PiEryF0JiD9jUUXvl0K2rknttPDgy1wRAwv46YixZEQes9IhMYDI4kYByAWy5RwNdWpx4Qbcu3bs00FlcYFOY+snWJxs3SusTv8bS9OmOFqMSY8mK2DxfSaEuXCtWSOuTyxAxqrBICBUuHLrt2mqu4Y/RxvFJtj5p3Nh4LM5aL1htnS+fUX3NydihiLFkNfbsMcSHuAzicsjGsPVJrVrS+iRg65N9+4BNmyJ9aGyFQxy1V4aD4pPiyfYDq61bp15rHKyvIMaS1VAnKxsdMvnO5sgE5geWcVO90+ETWFaxuYRQ1jh6NL2JqgPik8oe5PmQkhLtvTEZ7USMSowlq7rFHTKzu/9GpfWJFyJGlWWYo0IJITrpbCghlDXYyZo/OpamligBu8MWm7lyGQWma9dGe29MOhEvdK4YlRhLVoLLHZu2OPEH+8bGxxsSH9u3R3tvTDqBSeuTK8bmEkJZw2Eut4QEo9UNEWetF5UqAeXLG1XYSr3VYYixZCXY9fvYMSBPHqMDpAPgSq9ZM+OxTGBecMXPpqbnzgGLF0fh6Fgfh9kDwePQ+KREm/zgEi0XMZashJq8qKpKd4tDcM8lENxgkr/KJZHByTSXLqUrNjvIHggOKjbv3m24W1SjRgfNNXSeUDFBcKOds/OWxFiyEg5c6bl/3ZkzjQbYgo/BcegElhUogn/2rOGco5NOcEOdT6y6ZGdrh1C9utHyhlqcbIEjuNG6teFhYq/A/fsdNzRiLFkFhlrUr9cBlSnuNGwIFCgAnDoFLFsW7b0xqbG0fLmhgyJk2h7gz4lOOsG5hSQKiTYFoFAhoFEjx4pRyRRhFWgoMW5QujRQrRqcBPs4tmljPBYHiheq8yuT/+l6E4LGoY7ajGESr2px4sDBUV9Z2YuCj8Fx4EQsxpIVZ3YbK+n6QyawIAbHgRPYlUInHJ1xDrUHArNkidGsm54Eypo7DOW4Zwucw4ejvTcmo127dM+Sw7RcxFiyCg5fBquvzaIvhuMENyTJO9PQCUdnHJ1ydM4JbqgQC925DoxPModN9amm1JTgBkuTmcPGhorr1ztqaJz3S7Aihw4Zyxyi4lEOo0IFQ+qDfRxVhEBIheIwbEnwzz/GTcgQh689AiODI85af2TLll4d6TBPthhLFsClclG43OGyx6FItMkP1N2i/LBDEy+vBLEH/HDypBGGc7glKZ0DAtDWmXIlYixZgBhlLDl48iJiLMnghALlgKMzjgrxght029J9W7kyUK6cY4eGbRfpRNm715CcEtxwaOcAMZbMjqbBpQLnDjeWKPPBFIotW4A9e6K9NyZDnRs8V3ixE/yiFsRNmxpOOcEN5Zl0+FzDPtWqV6DDHCgZU6cOUKyYodrJXnEOQYwlk5N73z64uLzhMkd1mXco+fMDV11lPJZokxccmHz5jDIv1Sle8ImE4AIgg5OGeLL94HI5MhQnxpLJKbJ6dbqSLpc7DkcmMD8wpsQ2OA6bwDILnW4qqu0wbdeMobuWblu6b9W55GDUXDNrliE9JTh7Ig7aWNrvQHlzM1BEVcE53C2uUBc4epZY+i04ewLLLHS60flGJ5zyUgrwPG+uvtpw4zocSkwVLGhITknnAD9zzYoVwL//wgkEbSzVqlULP/74I6LNZ599hvLlyyN79uxo0qQJli5dGvD1v/zyC6pXr66/vk6dOpg0aZLH3zVNw6uvvooSJUogR44caNu2LbZt2wZTkJiIwkrLQpbBaXkmuXIBR44A69ZF9eiYD3WOMI+ATc+EgL2o6YwT3FCxbZlrdOhgk84BfihZEqhZ0xCmdEjngKCNpTfffBMPPfQQunfvjn+jZEn+/PPPePrppzFw4ECsXLkS9erVQ4cOHXDYj8zqwoULceedd+KBBx7AqlWr0LVrV/223k1M691338Unn3yCL7/8EkuWLEGuXLn0bV64cAHRxrVsGeLPn4fmUCVdX7AJuqpgEgeKF1WqAGXLGm1x5s2LwtExP5KS4we6aSW5+zLEWRuAds7yZAdtLD3yyCNYu3Ytjh07hpo1a2LChAmINEOHDkWfPn1w33336ftAAydnzpwYOXKkz9d//PHH6NixI5599lnUqFEDgwcPRsOGDfHpp5+meZU++ugjvPzyy7j55ptRt25dfP/993rIcdy4cYg2rtTJS+My2IFKuv5w2G80eKQLaEDobFuwwHgsUW0v1q413LV02yrNLkE6BwSinbMm4kw5oitUqICZM2fqxka3bt10AyTOy5dNj084uHTpElasWIEBAwakPRcTE6OHzRYtWuTzPXyenih36DVShtCOHTtw8OBBfRuKfPny6eE9vrdHjx4+t3vx4kX9pjiV2n8jMTFRv4WKmFRjKbFVK8RIhmEahmcpHvPmaTh9OgnZs2dtnNUxC+WxixauVq0Q98030KZORZIJv080x3rWLBcSE+NQtqyGcuWSbJ20m9lxjpkyBbF0MLVogWQa3XYenEzAVjiVK8dh+3YXpk9Pwo03aradOzJN06b69d+1YwcSWRhQsWLYPiqc4xzsNjMdtd+1axd+//13FChQQPfGeBtL4eLo0aNITk5GMeo7uMH/b9682ed7aAj5ej2fV39Xz/l7jS+GDBmCQYMGXfb81KlTdU9XKHAlJ+P6w4fBNMs58fE475Vr5WQYJi9QoAOOH8+Ojz5airp1j4Zku9NssEJKSElBR5cLrvXrMWP0aFwsUABmJBpjPXJkLQCVUbXqbkyenFplanOCHeemP/8M9gbYULw4/pG5xoPKleti+/YKGDlyN2Jj19l27rgSrq1aFYU3bsSGjz/Grg4dwv554Rjnc+fOBfW6TFk6I0aMwDPPPKN7YjZs2IAiRYrAidC75e6xomepTJkyaN++PfLmzRuyz0ns2BGTf/kFLbp3R3x8fMi2awc6d47F6NGsVLkGnTunZHllwR9hu3bt7DHOH34IrFoF+ku1zp1hJqI51i+/bEx3vXuXQufOJWFnMjXOFy4gLtWLXv2xx1C9Fo1KQXHxogtTpkA3mDp3LnPl42xDYlatAgYNQt2DB1ErjHNNOMdZRYZCZiwx94eVZwzB9erVC5GmcOHCiI2NxSE2lXWD/y9evLjP9/D5QK9X93yO1XDur6lfv77ffcmWLZt+84YHMdQH8lL+/GHZrtXhIobG0syZsYiPZwAh69hmnJlLsGoV4ti6ondvmJFIj7V7k/QOHeJgh8McsnGeO1c3mFjhFM/+kwzDCWm0b686B7hw6FA8Spe+wnG2Ix076sZSzOzZeloMYkMzF/sjHOMc7PaCzhpmCIwJ3tEwlEhCQgIaNWqEGar1h17AkaL/vynryX3A591fT2idqtczB4sGk/traGWyKs7fNgVzoEp6mSJ37Fi098ZkSBfQy1A/cRaVFi4c8SNiblRogz8qMZQCdg5waLTNP40bO6ZzQNDGEo2M0r5M6gjC0BdDgd999x02bdqEfv364ezZs3p1HKEh554A/sQTT2DKlCn44IMP9Lym1157DcuXL0f//v31v7tcLjz55JN44403MH78eKxbt07fRsmSJXWJAcHcMh+MFjhI5iN4qPbOrHcKyW7aFO29MQUiGSCDkxUcVvgVPHHO6RxgqXr0O+64A++//74uIskw2erVq3VjSCVo7969GwcOHEh7fbNmzXQhzeHDh+uaTL/++qteCVe7du201zz33HN47LHH0LdvX1x11VU4c+aMvk2KWArmRiYwP/DcVX0EbT6BBQMNajGW/HD0qB6y1RExSr9I54AAOGQitpSxROgVYkUeS/cZLmOZv2L27NkYNWqUx+sporllyxb99RSj7OyVhEbv0uuvv65Xv1GIcvr06ahatWrEvo9w5Ui0KcjZ3eHQuUYnG21IOt0EN+iWpTXJBaRb3qbgiXQOCGIipoiZjTsHWM5YEgTF9dczOQ/YuRP4+28ZF58TGJO8nagB44ayF1V0UnBDXG5BIZ0DAlC5stE5gPOMjTsHiLEkWJbcuY0VnwM8wJmHVU2U9jhzBli8GE5G7AE/SHwyUzgk2pR5XC5HDI4YS4KlccBv9MqQLqA6XOzSuUakxYkX27dTZdhwm9BNKwREnT9KaUFw1kQsxpJgi98oUy+SkqK9NybDARNYRtCpRuca5QLobBPcUOdFs2ZGTzghIDVrGlW4NJRUj0HBS8tl3TpD1MyGiLEkWF7mgzooJ08Cy5dHe29MmuS9dKkxQA6XEJJe1H4GR1xuQUeb1E/KwesP33A1QhEzGxeViLEkWBoKxrZubTyWCcwLJl2ysjMlhV1k4UTUOUEVZsENumGVQJkYS0EjzlrnDo4YS4LlsflvNGs4eHBOnDCcakTsAS/ohmVPLDZabtgwCkfHmijPEqWpKFEluKFWJJxrWDxgM8RYEmzzG120iI11o703JsPBxhKdaXSqVasGlPHsfyq4xyfD3M/LTrCdaJ06hi3g1UlLuPZaQ5uDwtAbN9puPMRYEixPxYrGjZGFOXOivTcmo2VL42K4bZtR+eQgpk417sWrFMBYEtXuTOPg9UdgaCipqkobDo4YS4ItkAnMD2xyqVTubTiBBULylfxA9yvdsEQsyUwjnQOCGBy1UrERYiwJtkCMJWdOYP7YscNQdWefTzrXBDfofqUbVrlkhUzBtouUptq923DYCj7mGp5jFy/CToixJNgCVsSxNJx9wPbujfbemDSpi0kWyclwklfpmmuAPHmivTcmQyQDsgQlqShNRWbMkEuoB0zoYmP7c+fSvZc2QY60YAtY1EPNJRvLfFw5V18N5M0L/PsvsHIlnIDYAzI4kXCgTJ/uCuvnWI6YmPQ8OJt5ssVYEmyDhOL8wFiUg8So6DxTlUqir+TFvn2G+5UXNXVOCFmINrmQnCwGkxMmYjGWBFv+RlkyLvgYHJut9nyxYgVw/LiR2668jQI8L2BXXWW4Y4UrgtJUBQtSqsqFbdvyyyi6ozxL/CEeOwa7IMaSYBuaNjXyCY4cAdaujfbemAzlYlm40GiW5gB7gI4TOtUEN5SxLC63LEE1jnSByqJyirlTqhRQq5YhRqVU4m2AGEuCbWCFSosWtvQAZ51KlYDy5YHERNuLUUm+kh/obpXBCbmzdvVqMZac4MkWY0mwFTb8jYauC6hNcwncodOMzjMizhMvVq82enTkzm2UCQpZQv2ctm0roLfWEewtRiXGkmAr1AVy3jzg/Plo742JezfZFDrN6DyrUMFwpgluqBUE45Px8TI0WaRcOfap1pCS4sLs2ZLk7QFd/DzH2DVg+3bYATGWBFtRo4YRMqceGg0mwQ1eJOlhYt8mm4pRSZQpiMERl1vIaNfOqCQRCYEAYlQ2WZyJsSTYCtoCHToYjyUU5wXLd1gFZWMxKjGW/HD2LDB/vvFYjKWQ0batEWKaPl0upZehzjObTMRyhAXbYbPfaGixcVIXnWV0momEkA/mzgUuXTJiR5UrR/7g2JQWLTTExaXgn39censdwcdcM2uWERu3OGIsCbajTRvDw7RuHXDgQLT3xrTSw7YTo1L2HwXL6UQTfAwOVxL8cQghgbny1ar96zHEwmViVMDSpbA6YiwJtqNwYaBRI1uFy8MjRrVmDeyESAjJ4ESD+vUPe5x/gpsYlVqc/fUXrI4YS4ItkVBcADGqli1ht9mdLU4kfzlAixOJT4aN+vWP6PfUX0xKCt/nWJL29smJEGNJsH2VvM2iTVnHRhOYgv2B2SeY/YKbNIn23pgMZUWy94vEJ0NOxYonULCgZpdoU3jmmmXLjB+ohRFjSbB1tOnwYWl9chmqXJDVUaySsgHKy898NWlx4oXEJ8MebWrdWrPb+iM0lC4N1KxprFhVd2uLIsaSYNtoU6tWxmOZwLyoWtWoimJ1lE1an4g9EESLE5EMCLveksw1PrCJlosYS4JtsclvNLxiVDZIvGT4Y9Ei47H6WkIqTOKXFidhp00bw7O0ZAmk9Yk3ykjnXGPh1idiLAmOaH1y7ly098bEE5jFoYwLE2spH8Q2J0I6MUp8lG5WaXESNsqWBapXNxx5TPQW3Lj+eiBbNmDPHmDLFlgVMZYE21KlSnq0iZp8ghtM7mGyBScv9m+yMMpzKF6ly3FJCC5i2LBuIjTkzAlcd53lF2eWMZb+/fdf9OzZE3nz5kX+/PnxwAMP4AxbjAd4/WOPPYZq1aohR44cKFu2LB5//HGcPHnS43Uul+uy25gxYyLwjYRIRJtkAvND/vzpZWMWn93V/CspOZ7Enj8P14IFxn86doz4cXEaNok2hYcO1s+JsIyxRENpw4YNmDZtGiZOnIi5c+eib9++fl+/f/9+/fb+++9j/fr1GDVqFKZMmaIbWd58++23OHDgQNqta9euYf42QqQQYykANshbYosJ3lgBp+SjBIPC69bBxTYTFStKi5MIwPOPhSU7dwJbt8pZ6HMinj3b6HJuQSxhLG3atEk3dL7++ms0adIEzZs3x7Bhw3QPEA0iX9SuXRu//fYbbrzxRlSqVAmtW7fGm2++iQkTJiDJSzmMnqrixYun3bJnzx6hbyaEm9atjV5hGzYYvcMEH8YS81osqqanokxscE6NJSGdYqtWGQ8kPhkRKFVig2hTeKhTByhe3EgeVd5OixEHC7Bo0SLdoGlMUbVU2rZti5iYGCxZsgS33HJLUNthCI5hvDgvIZZHH30UDz74ICpWrIiHH34Y9913nx6O88fFixf1m+IUy3HAXoGJ+i1UqG2FcptOI08e4KqrYrFkSQwmT05C796X+8cdO8716iGuQAG4jh9H0sKF0ChOFWZCPdaTJ8fqa742bZKRmCjqo+7jXCTVWEpq2xaa087tCOF9PrdtG4MZM2IxeXIK+vVLjvLemYtYXrN/+AHJkycjRVmVQRLOOTrYbVrCWDp48CCKFi3q8RwNnoIFC+p/C4ajR49i8ODBl4XuXn/9dd3rlDNnTkydOhWPPPKIngvF/CZ/DBkyBIMGDbrseb6f2wk1DD0KV06FCtWwZEl1jBp1CEWLLpdxdqNxjRootXAhtn/+ObYcPx6x0ywU53RSkgvTp3fSjaWcOedj0qQTIdk3O5DrwAG0PXgQKbGx+OvSJSRNmhTtXbI16nzOkSMP/dmYOTMF48ZNQUKCGPCKUkWKgO6O07/9hjnNm8Ms18JzQZZKuzQteqloL7zwAt55550MQ3C///47vvvuO2zxKjukAUWjpV+/fgG3Qc9Pu3btdONq/PjxiA9QQvvqq6/qOUx7WOaYCc9SmTJldIOMnqtQWrw8ObjvgfZZCMySJS5cd10c8ufXsH9/0mUKz04eZ9e33yLuoYeQ0qQJkqmxEGZCOdYLFrjQqlUcChXSsHdvkl7cJxhon36KhKefRvJ11yHF4srJZsb7fObVtEKFOOzf79I92Up/SYDeTiGeit4cN15fixW74nEOJbx+Fy5cOC3yZErP0jPPPIPevXsHfA1DY8wjOsy+FW4w74gVb/xbIE6fPo2OHTsiT548GDt2bIYDzZwoeqBoDGWjNoQP+Lyvv3Hb4bjYhmu7ToHRpQIFgOPHXVi1Kl7Pb/GFI8e5c2f9LmbZMsSwupQDFQFCMdbKBmjb1oXs2R123DIgzUDq0MF553QUcD+fmSL27bdMBYyTIkR3SpUCGjbUGznGM9H77ruRWcIxRwe7vagmeBcpUgTVq1cPeEtISEDTpk1x4sQJrFixIu29M2fOREpKim7cBLIY27dvr2+DHqVgErdXr16NAgUK+DWUBOtBj4ONNBjD17tJCRhahClTjHupivfi0iW4eDGi0dSuXcSPi9OxQZFp+AdnSuqP10JYohquRo0auneoT58+WLp0KRYsWID+/fujR48eKFmypP6affv26cYV/+5uKJ09exbffPON/n/mN/GWnGwk3rEyjhV2lBbYvn07vvjiC7z11lu6PpNgL9QF1YK/0fBjwdmdjublqelnUuzlxYIFcJ09iwv58ulJ/EJkadvW0Hhbv14qcP1OxJxruECzEJYwlsjo0aN1Y6hNmzbo3LmzLh8wfPhwj5gmc5pUstbKlSv1Srl169ahcuXKKFGiRNpN5SPR/fbZZ5/pnqv69evjq6++wtChQzFw4MCofU8hPKgL6rJlRqsswY9gnEXU9JS2Xf36QIkS0d4bk5G6IjjSoIGhmyFElEKFgKuvtrwGY/hyIvLmNSZht0iRFbBENRxhcvaPP/7o9+/ly5eHe656y5YtPf7vC3qreBPsDy+oXGSzrygLKu68M9p7ZLLeTQxRcxGxaZMRljM5EoILQKqH8HCDBgic0SmEc/3Bpro8T++/X8Y5DeYH0fX2++/G4Fx1FayCLDsExyChOD/kyAG0aGE8njwZZofeexUx7ETlACGdAweMFQGNJQnBRX2uYRpgataH4D04Fphr3BFjSXAMFg6Xhx9ldVhgAqP3nl58evMjoKNpLVLjPikNG+IS+/8JUYEOEw4/pcsY+hd8TMR0vf37L6yCGEuCY6BkQO7cwKFDaYtvwdtYotZSgAbVZgrB0ZsvVfFepLrcNKmCiyrUclOHQIpKvChTBqhVy1ixWkhwWYwlwTGwySV7xRGZwLyoUsVouHrpEnU5YGaU80vSDb1gvCfVs6QprQwhaliwyDRydLReebIYS4KjsOBvNDKw1tkCoTh67em9J2Is+YhPHjumN0TUrrkmCkdH8GUsUc2Gh0VwQ801nIgtkhMhxpLgyAls4UI2Vo723pgMd2PJpBICTJjl3EovPr35ghuq/xvjPxKfNIXea+3alos2RYbmzYFcudj4FVi7FlZAjCXBUTDSVLUq2+WYPtoUeVq1Yi8fYNcuYPNmmBEJwQVhLKW2sBGijzoU0sfYC84zKifCxJ5sd8RYEhyHRStXw0/OnKaWEKCzS4VPRTIggKS5DI7pjCX+nCwSbYocHa2VEyHGkuDo36hJo03Rw8R5S/TW02tPm45efMENZhHzZKakeWoLKMEcFbhKsFrZsoLXRLxggSVyIsRYEhxHy5bpgtXs3yT4MJbmzjWdhICy3+i9lz7XXkgIzpQwdUwVJkoozk9OBKs4Z8yA2RFjSXCkYLUKl//5Z7T3xmRw8ipf3pAQmDULZkJCcH5gAp6qT5d8JdMheUvW9GR7I8aS4Ei6dDHuZbVnDQkBeunprSciGeAFtRQoFV2gANCkSRSOjhAIdb5SyZuCuIKfBFKT50SIsSQ4erVHCQFeZwRzSwhQa5EOlGrVDO+94IYyahnvoXS0YLom3g0bGo9FoNILFpTQ1b9vH7BuHcyMGEuCI2GkqWZNI1w+bZor2rtjLhijpNz5zp3Ali0wAypcesMN0d4TEyL5SpaqihOsmRMhxpIAp4fiJk+Wn4EHFIu7/no1OIg2LLlWu6GOmZDK/v3AqlXGY4lPmt5YomeJHlLBDfWjnjgRZkauEoJjSZ/AXLqHSfARijNBUhdLrikjxBJskQzwk/XONvdFi0bh6AjBcPXVQMGCRshftesRvIylxYtN3RdGjCXBsVx7LZAvHzVQXPj77wLR3h1zoeJdc+YAp05FdVfUgpMpOdLFwwsJwVmC2Nj0VksmWH+Yi7JlgTp1DBeyiQUqxVgSHIu7Bsry5cWivTvmkxCoUgVITIx6YyuVyiAhOC/cj41IBpgekRAIYnFm4lCcGEuCo1ET2IoVYiyZcQI7cABYudJT0UBAeiknvX5FigCNG8uwmBx6lnger15tFH8JbqiVED1LJk3qEmNJcDTqAvz33/n1C7Pgxo03prt2otTYSoUsmJJTTOxZ34PDq3CMTOVmhzYtc5eIiaNN0eGaa4ykrhMngEWLYEbkFyY4Gl6AGzVKSUv0FtxgNjWzqo8cMRT1ooByakkIzgcTJhj3EoKzDOpQmbxKPjpJXZ06mToUJ8aS4Hg6dTKEF0VCwEdSlypHj8IEdvFiekqOGEte/P03sGmTIUIpkgGWi2xTZPXChWjvjcno0sXUlqQYS4Lj6dzZMJamT3fpLdEEc+QtsZfv2bNA8eJAgwZyVHx6la67zmhzIlgCnselShnn9ezZ0d4bk9Ghg+Fh2rDBEMQ1GWIsCY6nYUMN+fJdwOnTLsyf7/jh8ISucZWVumdP1EJwkpLjxfjxnnllgiXgT0kdMnUIhVSYs9SsmWm9S2IsCY6HF+JGjQ57LNiFVAoXBpo2jfgExpZ0IhngBybBzptnPBZjyXKoQ8a5xiStF81DF/OG4sRYEgRdYfegPg5//CETmBlCcVu3Gmk5TJtq21ZOUQ9UeXWNGkDlyjI4FoOt0HLmBPbuNRy2go+5ZuZMI1ZpIsRYEgQA9esfRrZsGnbsMELmgo+l8IwZwLlzERkatbBkU/I8eeRoeCAhOEuTPXu6GK54sr1gd/Ny5YzqDhpMJkKMJUHQJ7BktGlj+MQll8CLWrWMCYzlOxGawOjhc19oCm6q3aqrsITgLIvkLQVI6lI/epNZkmIsCUIqN9xg6C2JsRRgAotAKO7oUaQl2t98s5yeHixYYOQsFSqUnksmWDI1hz+rFStEzTtgUleUxHB9IcaSIKTSpYvhWWJXcFHz9sLdWApzVqoSDK9XDyhfXk5PD5Qlz6sty6wFy4rhNmliag3G6NGqlSGGe/AgsHQpzIIYS4KQSokS6e0IZALzomVLIyuVTa1WrYpICE68Sl7QSFWhCQnBWZ6bbjJltCn6JCSkq3mrycAEWMZY+vfff9GzZ0/kzZsX+fPnxwMPPIAzZ84EfE/Lli3hcrk8bg8//LDHa3bv3o0uXbogZ86cKFq0KJ599lkkmbSRnxC5CUxCcT6yUikaR8aNC9v4nz/PtjPGYzGWvNiyBdi+3biYqGMhWBZl706fbrrCr+jTtWvY5xrbGks0lDZs2IBp06Zh4sSJmDt3Lvr27Zvh+/r06YMDBw6k3d599920vyUnJ+uG0qVLl7Bw4UJ89913GDVqFF599dUwfxvB7MaSTGA+uOWWsE9gHHcW3JUpI6rdl6FcEPTySYmgLeomKlQwCr943gtu0LNE3ZDNm41FggmwhLG0adMmTJkyBV9//TWaNGmC5s2bY9iwYRgzZgz2798f8L30GBUvXjztRs+UYurUqdi4cSN++OEH1K9fH506dcLgwYPx2Wef6QaU4Dxq1zYmMBZ+qb5kAjzzZNatM0SQwhyCYwKs4IZIBtgKUfMOQL58Ru6SiUJxcbAAixYt0kNvjRs3Tnuubdu2iImJwZIlS3CLWvH6YPTo0boxREPpxhtvxCuvvKIbUGq7derUQTFm26XSoUMH9OvXT/diNfDTkOrixYv6TXHq1Cn9PjExUb+FCrWtUG5TyHicb7ghBsOGxWLcuBR06ZIsQ6bIkwexLVogZuZMJP/2G1Keeiqk53RyMu0BTkkudOmShMREkTdO49gxxC1cCNqPiWycm8GcIHNHZMjqOHfu7MInn8Rh4kQNFy8mSVsfN2JuuAGxU6ciZdw4JPbvH7ZrYbDbtISxdPDgQT2fyJ24uDgULFhQ/5s/7rrrLpQrVw4lS5bE2rVr8fzzz2PLli34/fff07brbigR9f9A2x0yZAgGDRp02fP0VClDLJQw9CiEHzXORYoUBnAtxo1LxE03TZGiIzcqVKqEujNn4sSoUZhfrVqWx9qdTZsK4siR65AzZyLOnp2MSZPEWFKUmTEDDVNScLJ8ecymamqQyqkyd0SGKx3nxEQXcubshMOH4/HRR4tQvfrxkO+bVcmeMyeYmedavBhzf/kFyJ8/LOfzuSCFdqNqLL3wwgt45513MgzBXSnuOU30IJUoUQJt2rTB33//jUqVKl3xdgcMGICnn37aw7NUpkwZtG/f3iPMFwqLlydHu3btEM/4rRAWvMe5XTtg6FANJ05kQ6FCXdCsmVy006hTBxgxAgU3b0bnRo2MGugsjLU7c+caWQE33RSLm25KrYYRdGJHjNDvc99zDzp37pylcRZCRyjG+YYbYvG//wGHD1+Lp582j66QGUj54gvErFiBVmfPYkr+/GE5n1VkyNTG0jPPPIPevXsHfE3FihX1ENrhw0ajUwUr1lghx78FC/OdyPbt23Vjie9d6qXjcOjQIf0+0HazZcum37zhQQzHxBSu7Qq+x5lDzevRjz8CkybF6S03hFQqVgQaN4Zr+XLEs0fZgw+G5Jx2r4q/5ZYYxMdbIp0yMpw+nZYBHNu9O2IzMRfI3BEZsjLO3btDN5b++CMW778fK7l63lVxK1YgnuJrffuG5XwOdntRnZGKFCmC6tWrB7wlJCSgadOmOHHiBFZQ7jSVmTNnIiUlJc0ACobVqV0L6WEi3O66des8DDGuEugdqskeNQKcXhXHwi/pDB7+sl4WvWzbZhTAMCVHcIPtTZgjyaa5rEAQbAXPdypzsGaCtRPC5XONa8YMxFJXJIpYYvlWo0YNdOzYUZcBoCdowYIF6N+/P3r06KHnI5F9+/bpxpXyFDHUxso2Glg7d+7E+PHj0atXL1x//fWoW7eu/hqGzWgU3XPPPVizZg3++usvvPzyy3j00Ud9eo4EZ1WuUs5m61Zg48Zo743JUAUVzB+g1yMEqIKXNm0M8V7BjdQcS3TrJiWCNiR37nTZLHWoBTd9hYoV4bp4EUVTnR3RwhLGkqpqozHEnCPG7CkfMHz4cI/YMZO3VbIWPVLTp0/XDSK+jyG/W2+9FRPc5FJjY2N1zSbe08t099136wbV66+/HpXvKJgHXrBVZ/Dffov23piMGjWAKlUAymswFBcCRLXbD9SwYAhCGUuCLVGHVuYaH/oKqd6l4lFufWKJajjCyrcfmUTih/Lly0Nzi5cw4XrOnDkZbpfVcpMmTQrZfgr24dZbjbYnv/4KiE6p1wRG7xIFXseONZIusgD78LEfn3v4U0hlxgyAnQpKlQKuukqGxcZq3nFxwPr1hje7atVo75GJuPlmVtyg+PLlTFY2YvVRwDKeJUGINLxwcwJjHgHzaQQfeUv0emRRwJWhB65zmH6YGlUX3AeH0DiNkenarhQoALRubTzm+kNwo1kzaIULI+H0abgWLEC0kF+fIPihYMH0CUzc417QsmHFKMtuZ83K0jlECRWSRQeV/eAqWsUnJQRne9QhlrwlL+LikPz221j88svQMlHQFWrEWBKEDEJxhKE4wX3miEnvdJuFpTCVOubONR7fdpuMsAfz5unK3ShUCLjuOhkcm6Na/DA1Z8+eaO+NudB69cIhdvBg2WCUEGNJEDKINtEuoGrFzp0yVD6r4mgssVdJFkJwV1/N/EEZ38sGR11FGQ8WbA0dtddeazyWUJz5EGNJEALALjvXX288Fve4F4xRMlZJnTLlHsokymMnXiUvUlLSr5gSgnOcJ1vmGvMhxpIgZICE4vzAqhR1IacEcSahjTV7tvFYjCUvli2jeJzevFgXnxIc5axlBNaraYUQZcRYEoQMUPbAokXG9Utw4/bb0zPgmZCcCSgATgcKW8xVqCCj6oFyLXTpEtU8DSGyMBTN3wN/F+PHy+ibCTGWBCEDWM7erJnxWHIJvGjVykhAPnIECELXzB2pgvMDk7hUfFK5GgTHIAKV5kSMJUEIAgnF+YGJx2pwMhGKO3o0XXFAQnA+QnD//APkzGl4lgRHoX4P7J3MYkjBHIixJAhBoOwBySUITShu/HiXXkDXoAFQqZKcgh6MGZNeBZcrlwyOw6B6N38X/CmJvpt5EGNJEILMJaDMB3MJpFLFixYtgCJFjGXwzJlBnU+//WZMPeJV8oIn2M8/G4979JDfpkNRh/6nn6K9J4JCjCVByKQDRS38hSsLxZ06FY+ZM136Y1Ht9mL+fGD/fiBfvvRW9ILjuOMO455pgDwdhOgjxpIgZHK1xwlMFHb9WJJ0uyUmBhzHpUtLIDnZhXr1gCpV5PTzQFnizPLNlk0Gx6HQk82iEub6X4EqhxAGxFgShCApUyZdoFK8S15wYKjgefw4MGNGwHGcP7+Ufi8hOC9oZKoSQQnBOZ4775S5xkyIsSQImeCuu4z7H3+UYfMgNjbd+gmwFD54EFi7toj+WOwBL5jvxTJB5n+pDs6CY2GImq2WliwxiiOF6CLGkiBkAtoDTNFZvRrYuFGGzmeiBcWoLl3yOTj/+18MUlJcaNIkBZUry/h5oNyVvEpKLzjHU6xYus2scv6F6CHGkiBkAuovduxoPJZKFS/YBbRECeDECWDqVJ/j99NPRmL3nXdqct65c/FiepmluNyEVKQqzjyIsSQIWQjFMQFTcAvFKe/Sf/972bBs2QKsWBGDmJgUdO+eIsPmzuTJLBMESpVKbz0vOB7m+bMF47p1wIYNjh+OqCLGkiBkkptuMsSVmUewdKkMnwf33GPc//GH4WFyY/Ro475hw8N6Wo7gIwRHY5OJKoIAoECBdE+2hOKii/wqBSGTUFS5a1fjsSR6e0Hp4Vq1jLCS6m+W2u5MGUvXX79Xzjl3zp4FJkwwHksITvBTFcewv3iyo4cYS4KQhVAcV3tBdvhwBi4X0KuX8fj779OeXrzY8MTlzq2hSZOD0ds/M0Iv3LlzRt8XysQLghs33gjkyAFs384wtgxNtBBjSRCugPbtjWTvQ4fSG8IKbpYkjSY20tuxQ3/qhx+MP918s4Zs2ZJlqNwZNcq479nTGDdBcCN3biP077X+ECKMGEuCcAUw6VK16pBQnBelSwNt2hiPf/hB11pU+RZ33SWJ3R7s3m20lye9e8tvUfCJOjUYymaEW4g8YiwJQhZDcewMziiK4IZbKO6vKZreY7d4caBVKykf9IBVg0xEadkSqFBBTiHBJ+3aASVLAv/+C0ycKIMUDcRYEoQrhBXevL6dPm0YTIIbt9xilAxu344fPj6WlrssWotu0EhSITjxKgkZqHKo9ce338pQRQMxlgThSn88McB99xmPv/lGhvGyRItbb8Vp5Mb4OXn1p+6+W8bIgwULjKxdjpU0yhMyQM01lOQ6cECGK9KIsSQIWYAOAebkzpljXPcEN3r1whj0wPmkBFSvloKGDWV0PFAuAia/UY9CEAJQtSrQrBmQkuJT81UIM2IsCUIWKFMG6NDBeDxypAylB61aYUT8I/rDB5pskEIvb20l1XBYuQwEIQPUqUI7WzSXIosYS4KQRR54wLhn+oloLqWzel0sliU2QDwu4d7D78l55g6T3M6cMbSVmjeXsRGC4vbbDc2lzZuBJUtk0CKJGEuCkEWogVK4sJFHMGWKDKdixAjj/haMRZFpPwL798vgKNwTu0VbSQiSvHnT09sk0TuyiLEkCFkkISG9JZokehtQSkG1N+lTaxGQnCxxSgWFOqlk6q52LgiZDMWxnaBIlkQOyxhL//77L3r27Im8efMif/78eOCBB3CGbmw/7Ny5Ey6Xy+ftl19+SXudr7+PUU0tBSGToThqoFDV2+nwJ3bypCGt0Pq51BYew4cbRpPTUTLMFO4sWzbaeyNYjBYtgPLlgVOngLFjo703zsEyxhINpQ0bNmDatGmYOHEi5s6di759+/p9fZkyZXDgwAGP26BBg5A7d2506tTJ47Xffvutx+u6qi6pghAk7B3bpImRsyQtCdJDcA8+CMTcfhtQsCCwZw9cTo9T0lhU8RPRVhKuULJEnToSioscljCWNm3ahClTpuDrr79GkyZN0Lx5cwwbNkz3AO33kwcRGxuL4sWLe9zGjh2L22+/XTeY3KGnyv112bNnj9A3E+zoXWJVnJMrVTZsMCSEKKSnhwz4e0qNHcQoK8qpTJoE7NplGI/dukV7bwSLcu+9RhR3xgxg69Zo740ziIMFWLRokW7QNHbryN22bVvExMRgyZIluIVqwRmwYsUKrF69Gp999tllf3v00Ufx4IMPomLFinj44Ydx33336eE4f1y8eFG/KU7RHwogMTFRv4UKta1QblMI3zjz2vfkk3HYvNmFefOS0LSpMy2m4cO5BotFly4pKFw4We8NR2Mp/oMP4Jo8GTm6dnXsOR07bJi+Qk3u3RsplDMP0zjI3BEZojXOpUoBnTrFYtKkGAwbloyhQ+3dczExjOMc7DYtYSwdPHgQRYsW9XguLi4OBQsW1P8WDN988w1q1KiBZlT1cuP1119H69atkTNnTkydOhWPPPKIngv1+OOP+93WkCFD9JCeN3w/txNqGHoUwk8oxvmaaxpg5syyGDjwAJ58ciWcxqVLMfj2WwpPxaJu3SWYNOlw2t+a1a2LImvXoty0aZjm9Xt2Arn27UPbadOguVyYWa0aztHLFGZk7ogM0Rjnq64qgkmTmmHkyBRce+1U5MiRBLszLQzjfC7ILPmoGksvvPAC3nnnnQxDcFnl/Pnz+PHHH/HKK69c9jf35xo0aICzZ8/ivffeC2gsDRgwAE8//bSHZ4k5Uu3bt9cT0ENp8fLkaNeuHeLZ5l4IC6Ec56JFXbrK7oIFpfH99wzrwlGMGePC6dNxKFNGw0svNdZDcQoXJ6W77kK56dNRZsQIxIdhYWFmYp55Rr/XOnVCyzALUcrcERmiOc4dOwI//qhh27Z4HD3aEQ89ZF/vUmIYx1lFhkxtLD3zzDPonUGSI0NjzCM6fDh9hUqSkpL0Cjn+LSN+/fVX3XrsFUSZLnOiBg8erIfZsmXL5vM1fN7X33gQw/GDCdd2hdCPc9Omxm3RIhe++SYer73mrFH++mvj/v77Xcie3Wssb70VWrFiyH7oEJKmTEHcHXfAMbBy97vv9Icxjz+OmAj9nmXugK3HuX9/4IkngC++iMWjj8baXrIrPgzjHOz2oprgXaRIEVSvXj3gLSEhAU2bNsWJEyf0vCPFzJkzkZKSohs3wYTgbrrpJv3zMoJ5TQUKFPBrKAlCRjz5pHH/xRfMb3POePHnOXcuQ+RGFdxlJCQgJXVx5LhE7x9+MGq9q1QB2rWL9t4INoE/J9YrbdxoSHcJDq+GY65Rx44d0adPHyxduhQLFixA//790aNHD5QsWVJ/zb59+3Tjin93Z/v27brMABO4vZkwYYJeYbd+/Xr9dV988QXeeustPPbYYxH7boL9YL1B6dIAnaE//wzH8OGHxj0dRvz+vkh54AE9ZyeGZTzbtsERsDTy00+Nx48+atR+C0IIYNaHCpioU0wID5ZI8CajR4/WDaQ2bdroVXC33norPvnkE4+Y5pYtWy5L1ho5ciRKly6t5xP5cr+xOu6pp56CpmmoXLkyhg4dqhtloYZesEuXLmXqPfxOTGS/cOECkkXML0N4PCkZEW3o1eU1ccAA4KOPDHVvu7vH9+5NNwyfeirAC8uXx6GGDVGcbqhhwwC337BtobuNegq5chk134IQQjjXfP458McfhipFuXIyvI42llj5xiRtf5QvX143eLyhp4g3X9BbxVu4oZG0Y8cO3WDKDPw+zMnaQzE/u19tQ4TSzIr2eNHefv11YNUqYP584LrrYGu4qqUgJ9WFGzUK/Nq/b7rJMJaY4PTqq0ZjPTujlvx3380TNNp7I9iMmjUNMXg6a7/8ktXa0d4je2IZY8mq0OChKjg9HqyYo1csWGhcUcaAIpqZeZ9Tx5leRVUIUKJEiajuT6FCxrWRqTkff2xvY4m5y199ZTx2KxL1y9G6daE1aAAXLUnqng0cCFu73FRPCroABCFMid40ljjfcP2RI4cMc6gRYynMsGqPF3HmVmVWg0mF7qgoLsZSxuRInSFoMFGXK9ohOapPcPLitdLO7vFRo4ATJ4DKlYEbbgjiDS4Xkp95BnG0JhmKe/ZZwK4yAvx+DKFffz1Qp06090awKfzdsc3g7t3ATz+xGjXae2Q/xF0RZlSuEav6hPCjDFIzKETXrm24xxl99SEcbwt4ejMvS+UqBesA1Sh3zi67x47Zt8HVv/8aySTkP/+J9t4INoYVqPQuEUoXSopr6BFjKUJEO4fGKZhtnKmBQuhhOn0atmPCBODvv4ECBTKZu8zZPVWkER98YCQ82dGrxBhlvXpButwE4cp5+GHjd8hecb/+KiMZasRYEoQw0qULULWqEaayo3dp6ND0iZrFXpmCKtZM7t6xA/jtN9gKWsZMViMvvmj/ckgh6uTJk67x9sYbhkdbCB1iLAmZhqrrXbt2zfT7ZsyYoWtmBSuDsHHjRl32gS1orArDUqqjzvvv28u7tGQJMG+eIZWgQgCZgiFTpWn27ruGHpFdoCLp8eNAtWq6crkgRCpPktpL69cbXl8hdIixJGSajz/+GKOY1ZtJnnvuObz88stBJ17XrFkT11xzja59ZWV69DC8S0zPsZN3iVU3pGdPIFUbNvOwQoxG08qVlOWHLTh/3ggtEoptmUD7S3AGVKZQC5fBg+2z/li2zIUjR7JHdR/EWBIyTb58+XQ9o8wwf/58/P3337qYaGa47777dGV1VhVaFabn2M27RJ3FqVM9v9sVayw88IDxOIOm2paB+lGUsChfXm8cLAiRhKE4rj8oZfbXX9Yf+8RE5kPG4pFH2mLatOiFs8VYijQ09RlWisYtk8sMNiCuU6eOXpJfqFAhtG3bVg+JeYfhWrZsiccff1z3HFE8lKKQr3l1kB0zZozeMZoyCMYwaPr2OnTokCYmysbIDLu9qlwWYButdvrzc+bMgV28S1ZvS8DD9fLLxmN2EapYMYsbpDgTvS/TphlWmJWhSj9DiuT5540YpSBEELZAZQ6hXbxLI0eybZkLOXMm4ZprovdlxFiKNGzHws6HQdxi8uZF/tKl9ftg3xPw5tUKJhAU0rzzzjtx//33Y9OmTZg9eza6devmUyWdfPfdd8iVKxeWLFmCd999F6+//jqm8eKXyrx589C4cWOPqjW+Z9myZWltax5++GGUKlXKw1ii5EL9+vX191sZO3mX6FHi4WCv6ZdeCsEG6YHp2zfdwLDy7P7994YQJUVRU5sGC0KkoVIFf58LFwJWXmeePQuodXf37lv0JPZoIcaS4NdYYuiLBhJbydDD9Mgjj+hq4r6oW7cuBg4ciCpVqqBXr166YcSEbsWuXbvSmh4raBh99dVXeOGFFzBgwABMmjQJP/zwg94Pzx2+j++3Osq7RPkdq3qX3L1Kjzziv2FupqGBzNjB4sXpitdW9CqpXhMU2kz1ogpCpKGtrnrH07tkVT7+GDh4kJJsGjp02BnVfRFjKdLwgkDtlSBuKadO4cTevfp9sO8JeMuESnK9evX0psU0krp3744RI0bgOKt7/EBjyR22G1GtR8j58+fTQnDucNu33HIL3n77bbz//vu6seUNw4DeDZKtCG1A5TSzqneJzTqXLzdkAl54IYQbLl48XXeJSdFWzFFj9v4//wBFi6Z7ygQhSjz3nBEFZt2EFXOXjh1LT2McODAZ8fHR9TiLsRRpqLfCK000bpnQemHFGsNokydP1qvShg0bhmrVqukNgX0R75WbwTCbe+PgwoUL+zS2aAStWLFC/7xt27b53DZzloowEG8D3L1LSobHKlDxQYUSKbZJmyDksQPqLlFVj4kKVuLoUWDQIOMxG3dnWnRKEEIL25+oyjiq65ugqUGmoJOWfgJquvboEf3QvBhLgl9o8Fx77bUYNGgQVq1apecPjb3CEEmDBg103SRvnnnmGb3vHY0y5i7N9FE+vn79ev39doB5zCoG//bbwJ49sAz/+5+h35IvX5i6dzA3T1ljHCQr6WuxGfDJk0D9+pKrJJgGerK5/ti0CfjyS1iG3bvTUxVoNJmhj7wJdkEwI0zUfuutt7B8+XLs3r0bv//+O44cOaKLSl4JrHqjfIA7f/75J0aOHInRo0frVW/PPvss7r33Xg8P1M6dO7Fv3z69cs4u0Lt07bWGLaAiT1aQDlK5SjSU2FYhLDz0kNEz7sAB67jeaEGqK9GHH4qukmAaqPBCNW9lzzO0ZQVeew24eBFo0QLo2BGmQIwlwSd58+bF3Llz0blzZ1StWlUXk/zggw/QqVOnKxqxnj17YsOGDdiyZYv+fxpeDzzwgC4x0LBhQ/05erCKFSumV8UpfvrpJ7Rv3x7lypWzzZFiNJTpLVwt/fILMH06TM+bbxrpOMzRV/3uwgJLePhhhAkLDG+ZPeOd0gcMObM5cMuW0d4jQfCAid5MKeUalAaT2dmwgdXV6VOAaToFaUKWOXnyJAOq+r0358+f1zZu3KjfZ5bk5GTt+PHj+r0d+M9//qP17ds36NdfvHhRK1u2rDZ//vyg33Ml433p0iVt3Lhx+n0keewxXmk1rVo1flfNtKxfr2nx8ca+/vZb1rYV1FjzfG/QwPjAPn00UzNhgrGfCQmatn27ZhaidU47DauM88yZxmkaG6tp69ZppiU5WdOaNzf2tVu3yIxzoOu3O+JZEiLGSy+9pHuI3BO/A8Hw34svvqjnTdmR1183kqTpbPvoI5gSHio6+pgceuONwC23ROBD6XJTAzJiBJsKwrRSASqOStnkSpWivUeC4JNWrQzHJ4s0mOxtVimzL75gtwejPkJ1DDILYiwJEYMtUmj8MKE7GCpXroyHmMNi43wCJfZMw4lahmbj22/TJy8mXEbMJX799YaQk4ojUPrCbNCgY+UeLd6QqHMKQvh47z2K/Bphf0qAmI2dOw1NWlX8Qq1aMyHGkiBEkXvuMW+yN2WyqK2ojDmWIkcUJiwwV42zaEhFnULAmjXplXss12ElnyCYGLYlUnMMvcVuMnhRR9MMaTLOg82bp6+TzIQYS4IQzR9gTHqyN0vzf//dPIeDEyuTQlkN//jjUdgBqsWzKS3hIJmlbxxLA9kgl2G4m25it+do75EgBAXt+9q1gUOHjP7VZgnHjRpltIakbvE335hDKsAbE+6SIDgLiq4p3aL77zeqzqLNpEnADz8YYbfhww318ahAyQjVt4GDYwYld0ojUzOMquM05kxTriMIgcmRA/jxR6PodOJE4PPPoz9iBw4YBaWEuq4U7TUjYiwJggmgFkqzZoauYffuwIUL0duXv/+m1IPxmB6lq65CdGFvGDah444psadoWpFKLY8JXTZRlhecQ506Rv6S8h5TJixaaBrQrx9w4gTQqFG60WRGxFgSBBPAbjFjxgCFCgErV0Yvf4k5A6x44+TVpEl6b6aoQslwureU6ONvv0VnP5jkoUJutCLNopYnCJmEbVA6dzaEH++8M3qLszffNJLN6blmh6OoebCDQIwlQTAJZcoA//2v8Zju8Z9/jvwqj5GudeuAYsUMm4TuelNAMdTHHjMe3303sHRp5DUUmORBg6lWLaNcRxAsCiPHdIyykJOeJUaWI83//pdeI0FnrVcvdtMhxpIgmAjaBAMGGI/79AH89BYOW7SLExhXd7/+CpQqBXMxdKixHOYymInVu3ZFzoqkocYkD9ZeM+mDyR+CYGFoKCml7GHDIpu/tGQJcO+9xmPqPllBIUaMJSFqXH/99fiRF54g6dGjh95yxe6wTJ8yQ6dPG7ZBJJrtshJFVed/8olRvms6aMUxVsmMeJbzdOliJHmFExpKtF55JVHLcbMvgQUhSBhJVt6dRx81qtLCza5dwM03G2ueG25Iz58yO2IsCVFh/PjxOHTokG4ABQv707355ps4Ge4LpAlsgp9+MkTZtm83DKcdO8L3ebNmAbfdZkSaGIZza81nPvLkMTw8bFLHJlLMhqe8eLighpJK3GKzXEoGCIKNYAUaBegJI81cj4SL06eNTgBc63DNwbVybCwsgRhLQlT45JNPcN999wWt5k1q166NSpUq4QfWtNsc2gKUFapc2dBkpMFEsehQw7wori5PnTJ6wFLOyPSV8KyMmzDBkBWnS+z2241ZONQwNqGUuRmjpGqeINgM/t4Z4WYojAsmpgSOGxf6z9m712i7wpxIqm5wzcO1j1UQYynC0KvPiqNo3DIrQMYebu+++67ediRbtmwoW7as7tkh69atQ+vWrZEjRw4UKlQIffv2xRm3lhSzZ8/G1VdfjVy5cultTtjfbVdqjsmRI0cwc+ZM3MglhtvrExISMG/evLTn+NlFixbVPVAKvmdMOJc+Jkv4psFUo4Yx0bRoYcj7hAoWltGxR21FepYmTzZE4SxBw4bGEphlhJzZmzY13HChgFcMGkdKiZOt2s0mry4IITaYGGlmRwH2j7vjjtAWnS5aBDRuDKxYARQubKx1OL9ZipC38HUggboWnz9/Xtu4caN+T86cMToqR+PGz84Mzz33nFagQAFt1KhR2vbt27V58+ZpI0aM0M6cOaOVKFFC69atm7Zu3TptxowZWoUKFbR7771Xf19iYqKWL18+7T//+Y/+Pn5/bmPXrl3633///XctV65cWjJbTLvx7LPPauXKldNOnDihrVy5UktISND++OMPj9dMnjxZf/7ChQs+99l7vO3QOfzQIU2rW9c4hoULa9ovv2haSsqVb4/D/vTT6efFY49pWlKSFhFCPtYLF2paiRLGF8mfnydI1rbHc7R16/TBeeqprA12lDD7OW0X7DbOiYma1r17+unPKf348axtc+RITUtIMLbHeWzHDnONc6DrtzuWMZbeeOMNrWnTplqOHDn0C3EwpKSkaK+88opWvHhxLXv27FqbNm20rVu3erzm2LFj2l133aXlyZNH3+7999+vnT59WnO6sXTq1CktW7ZsunHkzfDhw3UjikaT4s8//9RiYmK0gwcP6mPK8Zg9e7bPbX/44YdaxYoVL3v+4sWLWv369bXbb79dq1mzptanT5/LXrNmzRp92zt37nSMsUSOHdO0xo3Tj2W7dpq2eXPmtsFrPm2Jhg3Tt/POO5G1BcIy1vv2aVrTpsYXcrk0bfBgTTt7NnPb4CB8/72m5c1rbCdnTk37/HNLGkpWOaftgB3HmV/l2WeNnxJ/CqVKadqUKZnfzuHDmvboo+lzTbdumpbJS6upjCXLhOEuXbqE7t27ox/lPoOEYRzmxnz55ZdYsmSJHhLq0KEDLrgpcPXs2RMbNmzAtGnTMHHiRMydO1cPKYWLnDmNBurB3E6dSsHevSf0+2DfE+jGzw6WTZs24eLFi2jTpo3Pv9WrV08fTwXDbAzbbdmyBQULFkTv3r31sWbY7OOPP8YBatqncv78eWT3Ee9hGG706NH47bff9GP0IeNEXjDsR86Zoe1FBClY0AjJvfqqoX3EVB0q8bJQi/lGGTF/vhHGozQBRS/Zdo2aTtRXMX2OUjAJXsxSp9YC52WW99DHz8HJqJSQcwGTJ7p2BXr1MgaTapyrVxvSwpYfHEHIHIxsv/uuMWcwZ3LfPiOvkcUfCxYYYbpAbN5s5D+x8TZzIMlrrwG//GLMO1bFxHqZngxiyr7ecC+42kZ6zT766CO9gupm1ikC+P7771GsWDGMGzdOr8LiRX/KlClYtmwZGjOgqud0DkPnzp3x/vvvoyQn4RDDudfNxsgwdYInJl8f6caCyii5Ur799ls8/vjj+vj+/PPP+nGgQXrNNdegcOHCOM4OrT5YuHChfv/vv//qN3eDTD1PijiwzQQPCX8GvKYznYadN6iNyNJbVtOzXQpvNWsCu3cbCeFbthgJlYsXG9ugocUSYcoE2GoI+cWo8s0B4CAxK14NTrduxvNUAle3I0eAsWONQVS5dixD5Kz+/PPmlhIWhAjAn8yaNcaa45NPDNUM3phzREkTppzy8bFjnJeNexpYf/6Zvg1eVvlz5Outjm1nhB07duDgwYNoy0acqeTLlw9NmjTBokWLdGOJ90w+VoYS4etZoUVP1C3s++ADelx4U5xKXdonJibqN3f4fxpu9Lrwlhn4PnWf2fdmFVad0WCigfOgamSaSrVq1XSj9fTp02nGDBOzOW5VqlRJ21d6n3h7/vnndc8TvUZM+uZzPDbHjh1DgQIF0rb7999/46mnnsJXX32F//3vf7j33nsxdepUj4q5tWvXonTp0rr3yteY8DmOF8c9NsiaVHXMvI+dWeGKjdf5iRNdGDAgFlu3unRvEW+qbZk3sbEaevfW8NJLyXoxGYnG1w37WLOpXY8ecE2ciJhPP0XMnDnGkpY3P2ilSiHl5puRwqUz65n5u7PIuWCXc9qq2H2c6WVirUPXri4MHx6DKVNcOHrUhe+/p/PB93tcLg033KDhqadScO21mu4gyOrwhHOcg92mbY0lXowJPUnu8P/qb7xntZU7cXFx+oVYvcYXQ4YMSfN0ucMLe06vWBe3V7x4cb1SjKHEK4FGSTR44okndEOHBgiNzKNHj2Lz5s249dZb8dprr+Huu+/W/06jh16kO+64QzewWClHY6pTp076d9++fTu2bt2K2267TTcsaYixgo6GWMfU/lrJycl6SJQVdtw+jSve3nrrLX3bilmzZqFly5ZpBqo3HGOG+RhOTUpKytT35f5YCdqCdJcfPZodW7YUxObNxu3AgVwoUuQcSpY8i1KlzqBkyTOoUeMYihU7j7VraXBGe88jMNac5Z96Cnm7dkWZWbOQ/fhxxJ89i7hz5xB/7hy0mBgcatQIB5o0wQnGGmiQs+SQNxthtXPaqjhhnHv0YNWsC5s2FcSyZcWxenVRJCe7kCfPpdRbIgoVOo+WLfegVKmzekSbFbZmH+dgUzqiaiy98MILeCeDTp0MlVWvXh1mYsCAAXjarT0yL9xlypRB+/btkTdvXo/XMvdmz549yJ07t888nUDQQ0JDKU+ePHBFIXdi8ODBuufo7bffxv79+1GiRAk89NBDugHE8Bq9QMxpooHYrVs3XV2b35MGKD17zFuiIcX3Pfroo7rxpbxE1FhiOPR2auSkftbevXvx559/6mPIGz1MNKCY90RvFMdy0qRJ+s17nBV8DQ02qoMHO95cWfBH2K5dO8TzImsLcqXePBcD0SYqY824ow8qpN7siD3PafPhxHG+6SbvZ7zn2YqWGmd/C29TGUvPPPOMfkENRMWKVzbwvKATavTwYq3g/+vXr5/2msNsjOkGvRHMi1Hv9wU1h3jzhgfR+0DSY0JDh0ZCZgQYiQozqfdHGn4mc41484bGC7WSfMHxpiEUCBqbtWrV0g3JcuXKYeDAgfrNHXqieFN89913ehivGYPpAfaZ4+XrWGTElbxHuDJkrCODjLOMs52ID8McHez2omosMUk3XIm6FSpU0A2eGTNmpBlHtCCZi6Qq6po2bYoTJ05gxYoVaNSokf4cDQAVdhLCB4/NN998g927d+vGUrAnNRPwBUEQBCGSWCZniRdVenx4T2/Napb2gqWNlfXQD2G4jvlETMymd+HJJ5/EG2+8oScd03h65ZVX9Aq3riwTBpWRa+g5M3369NHlBejq69+/v578HY5KOMETdRyCxTvRXBAEQRAigWWMpVdffVUPwygaNGjgkfBLqPHj3mT1ueeew9mzZ3XdJHqQmjdvrufauOeysEKLBhJzbxjCYXIxtZkEQRAEQRAsZSyxuiojjSVVaq+gd+n111/Xb/5g5duPbH0sCIIgCILgA8soeFsdb0NOkHEWBEEQrIEYS2FGCSNeqcaScGWaGVLVJgiCIDguDGdVKEpJHaIjR47oF/DMSACwKo9GFrWDoiEdYDXPHQ0lSkFQlT1Y9W5BEARByAgxlsIM86aoO0SRxl27dmXaAKAaNUUWoyFKaUVoKAXSyBIEQRCEzCLGUgRISEjQ5QsyG4qjlAHbdlCNWsJKGcMxEo+SIAiCEGrEWIoQDKNltt0JL/xUFOf7xFgSBEEQhOggiTCCIAiCIAgBEGNJEARBEAQhAGIsCYIgCIIgBEBylkIoOMlGvaGECd4sh+d2JWcpfMg4Rw4ZaxlnOyHns/XHWV23MxKOFmMpBJw+fVq/L1OmTCg2JwiCIAhChK/j+fLl8/t3lyZ9OLIMxSP379+PPHnyhFQPiRYvDbA9e/Ygb968IduuIOMcLeSclnG2E3I+W3+caQLRUCpZsmRA8WfxLIUADnDp0qURLnhyiLEUfmScI4eMtYyznZDz2drjHMijpJAEb0EQBEEQhACIsSQIgiAIghAAMZZMTLZs2TBw4ED9XpBxtgNyTss42wk5n50zzpLgLQiCIAiCEADxLAmCIAiCIARAjCVBEARBEIQAiLEkCIIgCIIQADGWBEEQBEEQAiDGkon57LPPUL58eWTPnh1NmjTB0qVLo71LtmLIkCG46qqrdOX1okWLomvXrtiyZUu0d8v2vP3227rS/ZNPPhntXbEd+/btw913341ChQohR44cqFOnDpYvXx7t3bIVycnJeOWVV1ChQgV9jCtVqoTBgwdn2FtMyJi5c+fixhtv1NW0OUeMGzfO4+8c41dffRUlSpTQx75t27bYtm0bIoEYSybl559/xtNPP62XS65cuRL16tVDhw4dcPjw4Wjvmm2YM2cOHn30USxevBjTpk3TmzW2b98eZ8+ejfau2ZZly5bhq6++Qt26daO9K7bj+PHjuPbaa/VGo5MnT8bGjRvxwQcfoECBAtHeNVvxzjvv4IsvvsCnn36KTZs26f9/9913MWzYsGjvmuU5e/asfq2jo8AXHOdPPvkEX375JZYsWYJcuXLp18ULFy6Ef+fYG04wH1dffbX26KOPpv0/OTlZK1mypDZkyJCo7pedOXz4MJeG2pw5c6K9K7bk9OnTWpUqVbRp06ZpLVq00J544olo75KteP7557XmzZtHezdsT5cuXbT777/f47lu3bppPXv2jNo+2REA2tixY9P+n5KSohUvXlx777330p47ceKEli1bNu2nn34K+/6IZ8mEXLp0CStWrNBdjO795/j/RYsWRXXf7MzJkyf1+4IFC0Z7V2wJvXhdunTxOK+F0DF+/Hg0btwY3bt318PKDRo0wIgRI2SIQ0yzZs0wY8YMbN26Vf//mjVrMH/+fHTq1EnGOozs2LEDBw8e9Jg/2NONKSqRuC5KI10TcvToUT0uXqxYMY/n+f/NmzdHbb/sTEpKip5DwzBG7dq1o707tmPMmDF6OJlhOCE8/PPPP3p4iOH7F198UR/rxx9/HAkJCbj33ntl2EPECy+8gFOnTqF69eqIjY3V5+o333wTPXv2lDEOIzSUiK/rovpbOBFjSRBSvR7r16/XV4hCaNmzZw+eeOIJPS+MxQpC+Ax+epbeeust/f/0LPGcZn6HGEuh43//+x9Gjx6NH3/8EbVq1cLq1av1hRaTkmWc7YuE4UxI4cKF9RXLoUOHPJ7n/4sXLx61/bIr/fv3x8SJEzFr1iyULl062rtjOxhSZmFCw4YNERcXp9+YXM9ETT7mylzIOqwQqlmzpsdzNWrUwO7du2V4Q8izzz6re5d69OihVxvec889eOqpp/TqWiF8qGtftK6LYiyZELrNGzVqpMfF3VeN/H/Tpk2jum92gjmENJTGjh2LmTNn6qXAQuhp06YN1q1bp6/A1Y0eEIYt+JgLAyHrMITsLX3BvJpy5crJ8IaQc+fO6Tmk7vAc5hwthA/OzzSK3K+LDIeyKi4S10UJw5kU5h3QpcuLytVXX42PPvpIL6u87777or1rtgq90ZX+xx9/6FpLKu7NpEFqeAihgWPrnQfGkl9qAUl+WOigd4PJxwzD3X777bou2/Dhw/WbEDqoA8QcpbJly+phuFWrVmHo0KG4//77ZZizyJkzZ7B9+3aPpG4uqFh0w/FmuPONN95AlSpVdOOJelcMf1IjL+yEvd5OuGKGDRumlS1bVktISNClBBYvXiyjGUJ4+vu6ffvttzLOYUakA8LDhAkTtNq1a+vl1NWrV9eGDx8epk9yLqdOndJlLzg3Z8+eXatYsaL20ksvaRcvXoz2rlmeWbNm+ZyT77333jT5gFdeeUUrVqyYfo63adNG27JlS0T2zcV/wm+SCYIgCIIgWBPJWRIEQRAEQQiAGEuCIAiCIAgBEGNJEARBEAQhAGIsCYIgCIIgBECMJUEQBEEQhACIsSQIgiAIghAAMZYEQRAEQRACIMaSIAiCIAhCAMRYEgRBcIONfdk2pFu3bh7jcvLkSZQpUwYvvfSSjJcgOAxR8BYEQfCCDWjr16+PESNG6A1/Sa9evbBmzRosW7ZMb3YtCIJzEGNJEATBB5988glee+01bNiwQW9K2717d91QqlevnoyXIDgMMZYEQRB8wLaZrVu3RmxsLNatW4fHHnsML7/8soyVIDgQMZYEQRD8sHnzZtSoUQN16tTBypUrERcXJ2MlCA5EErwFQRD8MHLkSOTMmRM7duzA3r17ZZwEwaGIZ0kQBMEHCxcuRIsWLTB16lS88cYb+nPTp0+Hy+WS8RIEhyGeJUEQBC/OnTuH3r17o1+/fmjVqhW++eYbPcn7yy+/lLESBAciniVBEAQvnnjiCUyaNEmXCmAYjnz11Vf4z3/+oyd7ly9fXsZMEByEGEuCIAhuzJkzB23atMHs2bPRvHlzj7Hp0KEDkpKSJBwnCA5DjCVBEARBEIQASM6SIAiCIAhCAMRYEgRBEARBCIAYS4IgCIIgCAEQY0kQBEEQBCEAYiwJgiAIgiAEQIwlQRAEQRCEAIixJAiCIAiCEAAxlgRBEARBEAIgxpIgCIIgCEIAxFgSBEEQBEEIgBhLgiAIgiAIARBjSRAEQRAEAf75P0c4dpKiH3bVAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x), label='sin(x)', color='red')\n",
    "plt.plot(x, np.cos(x), label='cos(x)', color='blue')\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"Y\")\n",
    "plt.title(\"Графики sin(x) и cos(x)\")\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1ceb0bcd-24ed-4f08-a0fe-cd2cc07b154b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "names = [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"]\n",
    "scores = [89, 76, 95, 82]\n",
    "\n",
    "plt.bar(names, scores, color='orange')\n",
    "plt.xlabel(\"Имя\")\n",
    "plt.ylabel(\"Баллы\")\n",
    "plt.title(\"Столбчатая диаграмма баллов\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c9904f74-6742-4543-94c8-0fea58fe3d6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ages = [21, 22, 23, 24]\n",
    "scores = [89, 76, 95, 82]\n",
    "\n",
    "plt.scatter(ages, scores, color='green')\n",
    "plt.xlabel(\"Возраст\")\n",
    "plt.ylabel(\"Баллы\")\n",
    "plt.title(\"Точечный график\")\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fa5a83ee-634d-4983-9ecd-dc1963dfa7ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores = [89, 76, 95, 82]\n",
    "\n",
    "plt.hist(scores, bins=4, color='purple', edgecolor='black')\n",
    "plt.xlabel(\"Баллы\")\n",
    "plt.ylabel(\"Частота\")\n",
    "plt.title(\"Гистограмма баллов\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "277e51ce-cb39-4483-ae83-f1910d93b182",
   "metadata": {},
   "source": [
    "seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f88eabff-22bb-47a3-ba56-a59bc689c5ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fecf9ee6-30f0-4219-b929-2546c3ae29a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "21122087-8a85-4122-bda6-db2020d5d4c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(df[\"Баллы\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e050dbd1-35f7-4458-8a57-ce936c6c5487",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x=\"Возраст\", y=\"Баллы\", data=df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5ee341f2-cb89-4fa0-aff2-f6fec4f24485",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x115332e3e00>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 750x750 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c1c5e0c8-5289-476e-ab54-c7b34bb1e76d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.corr(numeric_only=True), annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fae78eb-2089-43d2-8ade-6ac622d4bbcd",
   "metadata": {},
   "source": [
    "С помощью seaborn были построены boxplot, histplot, scatterplot, pairplot и heatmap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c483fe4-ebb3-4735-a64b-4ad87b0920a1",
   "metadata": {},
   "source": [
    "Прогресс-бар с tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ad91b12f-f03e-4016-b523-661474693ae4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5911feb0-02de-4c97-b23f-3f7416570e7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 96.19it/s]\n"
     ]
    }
   ],
   "source": [
    "for i in tqdm(range(100)):\n",
    "    time.sleep(0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "35f88db4-4fef-4b2a-aa13-fd1431aa520a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Загрузка: 100%|██████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 95.73it/s]\n"
     ]
    }
   ],
   "source": [
    "for i in tqdm(range(100), desc='Загрузка'):\n",
    "    time.sleep(0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "39c452bf-3c38-43af-8241-5a2ea041c41e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Обработка строк:  50%|█████████████████████████████████▌                                 | 2/4 [00:00<00:00,  9.88it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 Анна 89\n",
      "1 Борис 76\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Обработка строк:  75%|██████████████████████████████████████████████████▎                | 3/4 [00:00<00:00,  9.86it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2 Виктор 95\n",
      "3 Галина 82\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Обработка строк: 100%|███████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00,  9.85it/s]\n"
     ]
    }
   ],
   "source": [
    "for index, row in tqdm(df.iterrows(), total=len(df), desc='Обработка строк'):\n",
    "    print(index, row[\"Имя\"], row[\"Баллы\"])\n",
    "    time.sleep(0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a71c90b-53b0-4c81-8aaf-28e1288d2500",
   "metadata": {},
   "source": [
    "С помощью tqdm был добавлен прогресс бар для цикла и обработки строк Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0cffb139-2388-4d07-a9e1-c7b26b1d3428",
   "metadata": {},
   "source": [
    "6. Самостоятельное задание\n",
    "\n",
    "Для самостоятельного анализа я выбрал датасет CO2 PPM - Trends in Atmospheric Carbon Dioxide с сайта DataHub.\n",
    "В датасете содержатся месячные данные о концентрации углекислого газа CO2 в атмосфере\n",
    "Цель анализа:\n",
    "- загрузить данные через pandas\n",
    "- выполнить базовый анализ\n",
    "- построить несколько графиков\n",
    "- использовать tqdm для демонстрации прогресс-бара\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "03390937-9dcf-4a34-a186-1814662a3266",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd # для таблиц\n",
    "import seaborn as sns # для графиков\n",
    "import matplotlib.pyplot as plt #для графиков \n",
    "from tqdm import tqdm #прогресс бар"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "506444de-4603-407c-b2cb-9af77ae253a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "co2_df = pd.read_csv(\"data/co2-mm-mlo.csv\")\n",
    "\n",
    "co2_df = co2_df.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "776f5513-48bf-438a-afe6-cb51e4675610",
   "metadata": {},
   "outputs": [
    {
     "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>Date</th>\n",
       "      <th>Decimal Date</th>\n",
       "      <th>Average</th>\n",
       "      <th>Interpolated</th>\n",
       "      <th>Trend</th>\n",
       "      <th>Number of Days</th>\n",
       "      <th>Extra</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1958-03</td>\n",
       "      <td>1958.2027</td>\n",
       "      <td>315.71</td>\n",
       "      <td>314.44</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1958-04</td>\n",
       "      <td>1958.2877</td>\n",
       "      <td>317.45</td>\n",
       "      <td>315.16</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1958-05</td>\n",
       "      <td>1958.3699</td>\n",
       "      <td>317.51</td>\n",
       "      <td>314.69</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1958-06</td>\n",
       "      <td>1958.4548</td>\n",
       "      <td>317.27</td>\n",
       "      <td>315.15</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1958-07</td>\n",
       "      <td>1958.5370</td>\n",
       "      <td>315.87</td>\n",
       "      <td>315.20</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Date  Decimal Date  Average  Interpolated  Trend  Number of Days  Extra\n",
       "0  1958-03     1958.2027   315.71        314.44     -1           -9.99  -0.99\n",
       "1  1958-04     1958.2877   317.45        315.16     -1           -9.99  -0.99\n",
       "2  1958-05     1958.3699   317.51        314.69     -1           -9.99  -0.99\n",
       "3  1958-06     1958.4548   317.27        315.15     -1           -9.99  -0.99\n",
       "4  1958-07     1958.5370   315.87        315.20     -1           -9.99  -0.99"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_df.columns = [\n",
    "    \"Date\",\n",
    "    \"Decimal Date\",\n",
    "    \"Average\",\n",
    "    \"Interpolated\",\n",
    "    \"Trend\",\n",
    "    \"Number of Days\",\n",
    "    \"Extra\"\n",
    "]\n",
    "\n",
    "co2_df.head() # покажем первые 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c3d5c3cc-68ce-4c28-82bb-87f0fdfdf824",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Date</th>\n",
       "      <th>Decimal Date</th>\n",
       "      <th>Average</th>\n",
       "      <th>Interpolated</th>\n",
       "      <th>Trend</th>\n",
       "      <th>Number of Days</th>\n",
       "      <th>Extra</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Decade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1958-03-01</td>\n",
       "      <td>1958.2027</td>\n",
       "      <td>315.71</td>\n",
       "      <td>314.44</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>3</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1958-04-01</td>\n",
       "      <td>1958.2877</td>\n",
       "      <td>317.45</td>\n",
       "      <td>315.16</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>4</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1958-05-01</td>\n",
       "      <td>1958.3699</td>\n",
       "      <td>317.51</td>\n",
       "      <td>314.69</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>5</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1958-06-01</td>\n",
       "      <td>1958.4548</td>\n",
       "      <td>317.27</td>\n",
       "      <td>315.15</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>6</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1958-07-01</td>\n",
       "      <td>1958.5370</td>\n",
       "      <td>315.87</td>\n",
       "      <td>315.20</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>7</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1958-08-01</td>\n",
       "      <td>1958.6219</td>\n",
       "      <td>314.93</td>\n",
       "      <td>316.21</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>8</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1958-09-01</td>\n",
       "      <td>1958.7068</td>\n",
       "      <td>313.21</td>\n",
       "      <td>316.11</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>9</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1958-10-01</td>\n",
       "      <td>1958.7890</td>\n",
       "      <td>312.42</td>\n",
       "      <td>315.41</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>10</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1958-11-01</td>\n",
       "      <td>1958.8740</td>\n",
       "      <td>313.33</td>\n",
       "      <td>315.21</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>11</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1958-12-01</td>\n",
       "      <td>1958.9562</td>\n",
       "      <td>314.67</td>\n",
       "      <td>315.43</td>\n",
       "      <td>-1</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>1958</td>\n",
       "      <td>12</td>\n",
       "      <td>1950</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  Decimal Date  Average  Interpolated  Trend  Number of Days  \\\n",
       "0 1958-03-01     1958.2027   315.71        314.44     -1           -9.99   \n",
       "1 1958-04-01     1958.2877   317.45        315.16     -1           -9.99   \n",
       "2 1958-05-01     1958.3699   317.51        314.69     -1           -9.99   \n",
       "3 1958-06-01     1958.4548   317.27        315.15     -1           -9.99   \n",
       "4 1958-07-01     1958.5370   315.87        315.20     -1           -9.99   \n",
       "5 1958-08-01     1958.6219   314.93        316.21     -1           -9.99   \n",
       "6 1958-09-01     1958.7068   313.21        316.11     -1           -9.99   \n",
       "7 1958-10-01     1958.7890   312.42        315.41     -1           -9.99   \n",
       "8 1958-11-01     1958.8740   313.33        315.21     -1           -9.99   \n",
       "9 1958-12-01     1958.9562   314.67        315.43     -1           -9.99   \n",
       "\n",
       "   Extra  Year  Month  Decade  \n",
       "0  -0.99  1958      3    1950  \n",
       "1  -0.99  1958      4    1950  \n",
       "2  -0.99  1958      5    1950  \n",
       "3  -0.99  1958      6    1950  \n",
       "4  -0.99  1958      7    1950  \n",
       "5  -0.99  1958      8    1950  \n",
       "6  -0.99  1958      9    1950  \n",
       "7  -0.99  1958     10    1950  \n",
       "8  -0.99  1958     11    1950  \n",
       "9  -0.99  1958     12    1950  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_df[\"Date\"] = pd.to_datetime(co2_df[\"Date\"], format=\"%Y-%m\")\n",
    "\n",
    "co2_df[\"Year\"] = co2_df[\"Date\"].dt.year\n",
    "co2_df[\"Month\"] = co2_df[\"Date\"].dt.month\n",
    "co2_df[\"Decade\"] = (co2_df[\"Year\"] // 10) * 10\n",
    "\n",
    "co2_df.head(10) # покажем первые 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "21f9572e-fce2-4c63-bd67-5978a18d12a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.DataFrame'>\n",
      "RangeIndex: 816 entries, 0 to 815\n",
      "Data columns (total 10 columns):\n",
      " #   Column          Non-Null Count  Dtype         \n",
      "---  ------          --------------  -----         \n",
      " 0   Date            816 non-null    datetime64[us]\n",
      " 1   Decimal Date    816 non-null    float64       \n",
      " 2   Average         816 non-null    float64       \n",
      " 3   Interpolated    816 non-null    float64       \n",
      " 4   Trend           816 non-null    int64         \n",
      " 5   Number of Days  816 non-null    float64       \n",
      " 6   Extra           816 non-null    float64       \n",
      " 7   Year            816 non-null    int32         \n",
      " 8   Month           816 non-null    int32         \n",
      " 9   Decade          816 non-null    int32         \n",
      "dtypes: datetime64[us](1), float64(5), int32(3), int64(1)\n",
      "memory usage: 54.3 KB\n"
     ]
    }
   ],
   "source": [
    "co2_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "f9efe5f4-10f6-4670-b446-cebbf99f784d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Decimal Date</th>\n",
       "      <th>Average</th>\n",
       "      <th>Interpolated</th>\n",
       "      <th>Trend</th>\n",
       "      <th>Number of Days</th>\n",
       "      <th>Extra</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Decade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>816</td>\n",
       "      <td>816.000000</td>\n",
       "      <td>816.000000</td>\n",
       "      <td>816.000000</td>\n",
       "      <td>816.000000</td>\n",
       "      <td>816.000000</td>\n",
       "      <td>816.000000</td>\n",
       "      <td>816.000000</td>\n",
       "      <td>816.00000</td>\n",
       "      <td>816.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1992-02-15 08:00:00</td>\n",
       "      <td>1992.166065</td>\n",
       "      <td>360.853591</td>\n",
       "      <td>360.852083</td>\n",
       "      <td>19.153186</td>\n",
       "      <td>-2.014289</td>\n",
       "      <td>-0.087647</td>\n",
       "      <td>1991.666667</td>\n",
       "      <td>6.50000</td>\n",
       "      <td>1987.230392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1958-03-01 00:00:00</td>\n",
       "      <td>1958.202700</td>\n",
       "      <td>312.420000</td>\n",
       "      <td>314.440000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-9.990000</td>\n",
       "      <td>-0.990000</td>\n",
       "      <td>1958.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1950.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1975-02-22 00:00:00</td>\n",
       "      <td>1975.187475</td>\n",
       "      <td>331.020000</td>\n",
       "      <td>330.795000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>1975.000000</td>\n",
       "      <td>3.75000</td>\n",
       "      <td>1970.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1992-02-15 12:00:00</td>\n",
       "      <td>1992.166650</td>\n",
       "      <td>356.080000</td>\n",
       "      <td>356.370000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>1992.000000</td>\n",
       "      <td>6.50000</td>\n",
       "      <td>1990.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2009-02-08 00:00:00</td>\n",
       "      <td>2009.145825</td>\n",
       "      <td>387.065000</td>\n",
       "      <td>386.932500</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.570000</td>\n",
       "      <td>0.212500</td>\n",
       "      <td>2009.000000</td>\n",
       "      <td>9.25000</td>\n",
       "      <td>2000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2026-02-01 00:00:00</td>\n",
       "      <td>2026.125000</td>\n",
       "      <td>430.510000</td>\n",
       "      <td>428.470000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>1.310000</td>\n",
       "      <td>0.580000</td>\n",
       "      <td>2026.000000</td>\n",
       "      <td>12.00000</td>\n",
       "      <td>2020.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>19.642733</td>\n",
       "      <td>33.049906</td>\n",
       "      <td>33.001039</td>\n",
       "      <td>11.856600</td>\n",
       "      <td>4.490492</td>\n",
       "      <td>0.509139</td>\n",
       "      <td>19.643364</td>\n",
       "      <td>3.45417</td>\n",
       "      <td>19.924418</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Date  Decimal Date     Average  Interpolated  \\\n",
       "count                  816    816.000000  816.000000    816.000000   \n",
       "mean   1992-02-15 08:00:00   1992.166065  360.853591    360.852083   \n",
       "min    1958-03-01 00:00:00   1958.202700  312.420000    314.440000   \n",
       "25%    1975-02-22 00:00:00   1975.187475  331.020000    330.795000   \n",
       "50%    1992-02-15 12:00:00   1992.166650  356.080000    356.370000   \n",
       "75%    2009-02-08 00:00:00   2009.145825  387.065000    386.932500   \n",
       "max    2026-02-01 00:00:00   2026.125000  430.510000    428.470000   \n",
       "std                    NaN     19.642733   33.049906     33.001039   \n",
       "\n",
       "            Trend  Number of Days       Extra         Year      Month  \\\n",
       "count  816.000000      816.000000  816.000000   816.000000  816.00000   \n",
       "mean    19.153186       -2.014289   -0.087647  1991.666667    6.50000   \n",
       "min     -1.000000       -9.990000   -0.990000  1958.000000    1.00000   \n",
       "25%     14.000000        0.200000    0.080000  1975.000000    3.75000   \n",
       "50%     25.000000        0.400000    0.150000  1992.000000    6.50000   \n",
       "75%     28.000000        0.570000    0.212500  2009.000000    9.25000   \n",
       "max     31.000000        1.310000    0.580000  2026.000000   12.00000   \n",
       "std     11.856600        4.490492    0.509139    19.643364    3.45417   \n",
       "\n",
       "            Decade  \n",
       "count   816.000000  \n",
       "mean   1987.230392  \n",
       "min    1950.000000  \n",
       "25%    1970.000000  \n",
       "50%    1990.000000  \n",
       "75%    2000.000000  \n",
       "max    2020.000000  \n",
       "std      19.924418  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "4a6814ba-49c0-492a-a942-5c77736c4e14",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JeseOHarGR/IGagpk5PPle/v0008vek2aBmqb+qBnz54q8JPecFW3s7rvV38/kNflsQTBEmjVtyykNk56sEjziqFO2PLdyj4r35sEcJfab4T82EgZSXNUQ2h7IEl3chnOQXo76X+29DKTGkLpjaRfFpI7Iv9v6QHZmKSZQy4apDZXLgjqUiaGJvuxft6N1H7Ifj1y5EhdDWt15yQpo8vJV6rPcXS5+4PkHUoNqzQpyedVJec7/fd8/vnn1XAMDzzwwEX/x3379qn9SGpu9GsuZT+SMpOgWWqdDN3caClYs0M6EhRItbR0Dx4wYIDqqixND1VzMiTxUgKT2bNnq26icmKXE4FcvcuVjyQZNoQ0m0m3V/l86SosP7aSs6OtrpeD+bPPPlPBj4yRIutJcrX8qEtCpZy8papdtkWaNhYsWKCulPTHyNAGSXJVLScfqRqXAEquvOXKS6qpZSRSuaqSvCVJ4JYmBPnBkv+fNPPJ31at0q9KfqwkB0DyDaQJQ05GEgDI1awEYXLylBNhQ0h+jzTN1XZFLl1dv//+e3XSlLKRWhU5eUrNgTwvJ8WaaryknKV7r1yVylWvlLMkisvfyhgs+tX40rwh3c3l6lua4qQp8LffflO5DdqTbl3LQspVAs5z586pcUzkalhL+6MoV72SVFvfXBX5QZNykG2U/UmaASSRWd5XvteqSc1SxvIDpZ+rdjk5IRJoyedKN3spX9mnZFgH6WYsP2JSCybBvbwu+31dk1qrI2VcNVCU716OE0l8lu9DjhX5jmU/keBWmoXk+5JRfuX7k/2luosZQ5IfbQm69LueC9kH9M9J0tQmzVfynckxK99XTd+LvK5fs6dN5JUaYjlX6Q9NUZfj6HL3B9nPJalZPkOGsZDAX8pWnpdjSZKJJcdQm18j+UCSAC3HhNQgy2N5XTuCsny+7Cf6NepSoyO1qzKGlgw1IYuWHCeXasa3Gv/2yiILVlO3zKqkq+xjjz2muuhKl/SBAweqbp7SFVO/O6a2S+gzzzyjuig7ODhomjVrprnppps0MTExDe4y+80332jmzJmjuoDK50sXZumOWtWBAwc0EyZMUF3npVu8dJGeOHGiZsOGDZU++1KLfldcsWLFCs2gQYNUN1tZ2rdvr7p/nzhxQr0uXawHDx6sukxXVbXrudbixYtVd1b5/3h4eKjRT6Wba0JCQoO7ntvY2Gj27dtX6fnqviPpyvzGG2+o8pZy8vHxUdvy4osvqpFbL+Wvv/5S3fllu6U8unbtqlm4cOFFXZLlOx85cqQa3TUoKEiVRdUhDOpSFtoyvNSi7QZc3+7GSUlJqkzDwsJ0++zw4cPVdlXdF+UYyMvLu6js69P1XN/mzZvV96YdRkG7PXfffbfG399fddWX8qjaVbshx1Fti+xrVbdXhnKQ7tHS7bt169aau+66q1KX8Mbqei7fhXS9l+EkZP+UbtpV30uGPtCWkXTJl209fvy4+n/oH7/afaG2Rb+s6nocXe7+oP//eP7559V3LMeJlLUMiSHnu8TExGq7ocuxJ8eslE2bNm3UuVk7nEPV7ajL/9naMdgho6ttfJCG0J5o9cdkqUpOUlWDHaqfmn4EG0q+k0udnOVHrrofV7o0CQiqBjvGog12mkpd9i2ybMzZISIiIovGnB2yOJKvIG3dtSW4Sg8v7fQXZBrkO7lU7z6Z86ehY8tYO8lva+zEZ1MluX/VjXdE1oPBDlkc6catn9xaUw8sMi11+U5kbi9qGElUtdZkVRljiaybjbRlGXsjiIiIiBoLc3aIiIjIojHYISIiIovGnJ1/h7xPSEhQA3ldzqzdRERE1HQkE0dGopYOJ1Un1tXHYAdQgU5TToxIREREhiPTjYSGhtb4OoMdQDc0uxSWDKNOREREpk+mBJHKiktNscJgR7qk/dt0JYEOgx0iIiLzcqkUFCYoExERkUVjsENEREQWjcEOERERWTQGO0RERGTRGOwQERGRRWOwQ0RERBaNwQ4RERFZNAY7REREZNEY7BAREZFFY7BDREREFo3BDhEREVk0BjtERERk0RjsEBERkUVjsENEREQWzd7YG2Dp4uLikJqaClPm7++P8PBwY28GERFRo2Cw08iBTvsOHVCQnw9T5uLqiuNRUQx4iIjIIjHYaURSoyOBzqQn30JQeGuYoqS4GCx743G1razdISIiS8RgpwlIoBMa2akpPoqIiIiqYIIyERERWTQGO0RERGTRGOwQERGRRWOwQ0RERBbNqMHO1q1bcd111yEkJAQ2NjZYvXq17rWSkhI8+eST6NKlC9zc3NQ6d955JxISEiq9R3p6OiZNmgRPT094e3tj6tSpyM3NNcL/hoiIiEyRUYOdvLw8dOvWDR9++OFFr+Xn52P//v147rnn1O3KlStx4sQJjBs3rtJ6Euj8888/WLduHX799VcVQN1///1N+L8gIiIiU2bUrudjxoxRS3W8vLxUAKPvgw8+QJ8+fdRgfTImTFRUFNauXYs9e/agd+/eap2FCxfimmuuwdtvv61qg4iIiMi6mVXOTlZWlmrukuYqsWPHDnVfG+iIESNGwNbWFrt27arxfYqKipCdnV1pISIiIstkNsFOYWGhyuG57bbbVH6OuHDhAgIDAyutZ29vD19fX/VaTebNm6dqjrRLWFhYo28/ERERGYdZBDuSrDxx4kRoNBosWrTost9vzpw5qpZIu8THxxtkO4mIiMj02JtLoHP27Fls3LhRV6sjmjVrhuTk5Errl5aWqh5a8lpNnJyc1EJERESWz9YcAp3o6GisX78efn5+lV7v378/MjMzsW/fPt1zEhCVl5ejb9++RthiIiIiMjVGrdmR8XBOnTqlexwbG4uDBw+qnJvg4GDcdNNNqtu5dCkvKyvT5eHI646OjujQoQNGjx6N++67Dx9//LEKjh555BHceuut7IlFRERExg929u7di6uuukr3ePbs2ep2ypQpeOGFF/Dzzz+rx927d6/0d5s2bcLQoUPV/WXLlqkAZ/jw4aoX1o033ogFCxY06f+DiIiITJdRgx0JWCTpuCa1vaYltTzLly838JYRERGRpTDpnB0iIiKiy8Vgh4iIiCwagx0iIiKyaAx2iIiIyKIx2CEiIiKLxmCHiIiILBqDHSIiIrJoDHaIiIjIojHYISIiIovGYIeIiIgsGoMdIiIismgMdoiIiMiiMdghIiIii8Zgh4iIiCwagx0iIiKyaAx2iIiIyKIx2CEiIiKLxmCHiIiILBqDHSIiIrJoDHaIiIjIojHYISIiIovGYIeIiIgsGoMdIiIismgMdoiIiMiiMdghIiIii8Zgh4iIiCyavbE3gExDVFQUTJm/vz/Cw8ONvRlERGSGGOxYuez0FHU7efJkmDIXV1ccj4piwENERPXGYMfKFeRmq9ux055Bu669YIqS4mKw7I3HkZqaymCHiIjqjcEOKX4hEQiN7MTSICIii8Nghy4pPa8Y5zLykZJThKzCEtjABrY2gI+bI4I8nBHq4wI3J+5KRERkmvgLRdXSaDQ4lZyLQ+eycD6zoNp1zqTlq1sbAOF+rugc4oXWAW6wsZFniIiITAODHbpIRn4xNkYl49y/QY6ELqG+LqoWx9fNUT0uKdcgNbcIF7IKkZxThLNp+WoJcHfCgDZ+aOHnxpIlIiKTwGCHKjmWmI2Nx5NRVq6Bva0Neob7oHNzT3g4O9QaHB1LyMbhc1lIyS3CTwcT0CbQHVe1C4CrI3cxIiIyLv4SkaLRALti07DzdLp6HO7rimHtA+HlUnOQo+Xj6oiBbfxVYLTnTDoOnctUTWDnMwowokMgWgW4s5SJiMhoOIIyKadKPHWBTu8IH4zvHlKnQEefi6MdBrcNwC29w+Dn7oiCkjL8cjgRO2LSVA4QERGRMTDYIXj2uxkJpRW1L9L0JLU0l5NkHOjpjNuuCEe3UC/1ePeZdBX0lJSVs7SJiKjJMdixcsnwhM+QKer+kLYB6BrqbZD3tbO1wdB2gRjVMUjdj03Nw4r951BQXGaQ9yciIqorBjtWLDm7ENEIUfdD7XPRPcwwgY6+9sGeuLFnczjb2yIpuwjf74tHTmGJwT+HiIioJgx2rJQ0Ka355wI0sEF+9E60cqiYNqIxBHu54ObeYfBwtkdmfgl+3HcO2QUMeIiIqGkw2LFSW06mqMDDESVI+30+GnscQBmf5+ZeoSrpObuwFD/uZ8BDRERNg8GOFTqdmot/EipqctoiAeWFOU3yuTJWjzRpebs4IKewFKsOnEd+cWmTfDYREVkvBjtW2Hy15USKut8z3BveqJjyoalUBDyhFU1aBSVYfTABRaVMWiYiosbDYMfK7D2ToZqR3J3s0beln1G2wd3ZHjf0aA4XBzs1uegvhxJRym7pRETUSBjsWBGZ1mHf2Qx1f3BbfzjaG+/rl1GXZeBCRztbNdHomqMXUF7OgQeJiMjwGOxYkb+iU1Gm0SDCzxVtTGAKBxl88LpuwWocntOpedhwPJkjLRMRkWUFO1u3bsV1112HkJAQNWLv6tWrK70uUww8//zzCA4OhouLC0aMGIHo6OhK66Snp2PSpEnw9PSEt7c3pk6ditzc3Cb+n5g+mZ1cAgrpdDU4MuCyRkg2pFAfV4zp3Extl0xCuudMRc0TERGRRQQ7eXl56NatGz788MNqX3/zzTexYMECfPzxx9i1axfc3NwwatQoFBYW6taRQOeff/7BunXr8Ouvv6oA6v7772/C/4V52H46Vd22D/ZQ3cBNSesAdwxtF6Du7zidhpNJTdM7jIiIrINRZz0fM2aMWqojtTrvv/8+nn32WVx//fXquaVLlyIoKEjVAN16662IiorC2rVrsWfPHvTu3Vuts3DhQlxzzTV4++23VY0RAfHp+YhPL4CtDdDPSEnJlyLTVGTkl+BgfCb+PJYET2cHNPNyNvZmERGRBTDZnJ3Y2FhcuHBBNV1peXl5oW/fvtixY4d6LLfSdKUNdISsb2trq2qCalJUVITs7OxKi6WSoFFqS0SX5l7wrOdM5k3pykh/tPBzRVm5Bj8fSuAoy0REZNnBjgQ6Qmpy9Mlj7WtyGxgYWOl1e3t7+Pr66tapzrx581TgpF3CwsJgqRKyCpGYVaiSgK9o4QtTZmtjgzGdg+Hv7oiCkjIV8HAMHiIisthgpzHNmTMHWVlZuiU+Ph6WStvVvEMzD7g5GbXVsk6kO/y4biFwdbRDWl5xRZd09kgnIiJLDHaaNWumbpOSkio9L4+1r8ltcnJypddLS0tVDy3tOtVxcnJSvbf0F0uUnleM2NQ8db9nuA/MhYyyLAGPva0Nzqbl43CGnbE3iYiIzJjJBjstW7ZUAcuGDRt0z0lujeTi9O/fXz2W28zMTOzbt0+3zsaNG1FeXq5ye6ydtlandYAbfEysB9alBHk6Y1SnioA1JtcOHj2vNfYmERGRmTJqu4aMh3Pq1KlKSckHDx5UOTfh4eGYOXMmXnnlFURGRqrg57nnnlM9rMaPH6/W79ChA0aPHo377rtPdU8vKSnBI488onpqWXtPrLyiUhy/UJF43SvCfGp19LUJdMfA1n74OyYNPsPvw/7EQvQ09kYREZHZMWqws3fvXlx11VW6x7Nnz1a3U6ZMwZdffoknnnhCjcUj4+ZIDc6gQYNUV3Nn5/+6JC9btkwFOMOHD1e9sG688UY1No+1k1nNJdelmaczgr1cYK4kUDt3IRln8+zw7s5MDO6dg7ZBHsbeLCIiMiNGDXaGDh1a6/QAMsrvSy+9pJaaSC3Q8uXLG2kLzVO5RoMj57PU/a6hXjBnsg/09C3DiahjQHgX3PPlHqx+eCD83Z2MvWlERGQmTDZnhxruTGoecotK4exgi8hA48+BdblkMMSUVa+hmbsdzmUUYNrX+1BYUmbszSIiIjPBYMcCHf63VqdjsCfs7SzjKy4vzMHTg3zh6WyvEq+fWnGYk4YSEVGdWMYvIelk5her7traEZMtSainPRZN7qUGSFx9MAEfbPwvuZ2IiMhgOTuSI1MbGeOGjEdmDhfhvq7wdjWv7uZ1MbCNP16+vjOeXnUE76w7iZYBbri2q3X3vCMiIgMEOxMnTsSMGTNUbyhJKJZxbGbNmqW6g5PpkO8mKrFixvBOIZY5UKK4vW84YlJy8flfsXjs+0No7u2CHmY0aCIREZlgsCNdwa+77jo1WnFMTAxeeOEFvPPOO3jggQfUrOQyvxQZX3xGgUpMdrK3RSt/N1iyp6/poBKxNxxPxtSv9mLlgwPQwsL/z0RE1Ig5O9dcc40a70aaqKQZS8axkVGLZUDANm3aYOHChSgrY+8YY4v6twkrMsjdYhKTayJ5Owtu66HykmRajDu/2I2UnCJjbxYREZmgOv0iTps2Dd27d680A3nbtm2xatUqrFixAkuXLkXHjh2xevXqxtxWqkVxaTlOJefqemFZA5nY9Iu7rkCYrwvi0vMx9as9auRoIiKiejdjjRs3Tjcq8YQJEy56vXnz5jh+/LgavZg1PMYRnZyD0nINvF0d1KjJ1iLAwwlL7+mLGxdtx+FzWXho2X58NqU3HCy8ZouIiAwc7Fx77X+TMNaUn3PTTTfV42PJ0I5fqEhM7hDsqUYdtiYt/d3w+ZTeuP3TXdhyMgVzVh7BWzd1tbpyICIiA3U9X7JkSX3/hBqZNN2czyhQ99tZ6bxR0hvrw0k9cN/Sffhx3zm4O9lj7nUdGfAQEREHFbQEkqsjM4xJ85WXiwOs1bD2QXjjxq7q/pfbz+D1tcc5yjIREdW/Zqdnz561vr5//34WaxM7kZSj64Vl7W7qFYqi0jI8s+ooPtlyGs72dph1dVtjbxYREZlTsHPkyBG4urri3nvvhaendfT6MWU5hSVIzCpU99sGWmcTVlWT+kagqKQcL/16DPM3RMPJwRYPDW1j7M0iIiJzCXaOHj2Kxx9/HF9//TXmzp2rBha0s7NrnK2jS4pOquhuHuLtDHfnen+dFuueQS1RVFqON9Yex5trT8DOxgbThrQ29mYREZER1Lt/brt27fDzzz/ju+++wxdffIHOnTvjl19+aZyto0s6mVzRhNXWShOTa/Pg0NaYOSJS3Z+35jje+oM5PERE1qjBg5FcddVVahTlOXPm4KGHHsKwYcNw4MABw24d1Sq7sARJ2RWjBrcJYL5OdWaOaIsnR7dX9z/cFINnVh9FWbmkcxMRkbWod7vH7Nmzq51OYvny5ejTpw9KSkoMtW10CadT8nRNWDKaMNVcwyO91J5ZfQTLd8Uhu6AE707sDkd7DjxIRGQN6v0LWVPtTe/evQ2xPVQPMf9OD9GatTp1mind08Ues747iF8PJyK7sBQf3t4DHs7W21WfiMha1DvY2bRpU+NsCdVLfnEpzmdWDCTIJqy6ubZriApuHvh6H7aeTMENH23H4jt6oRWDRSIii8Z6fDMVm5qnBhIMcHeCpxUPJFhfQ9oG4Nv7+6kBGGUwxus//Bubjicbe7OIiMiUanaqmwhU38qVKy9ne6iOYv7N12kd4MYyq6duYd74efpAPPS//dh7NgP3fLUHj49qhweHtOb0EkREFqjeNTsyEah2+e2332Bra1vpOWp8xaXliEvPV/dbB7IXVkMEejhj+X39cFufcGg0UGPxTPt6HzLyig38bRERkVlPBPrjjz/izTffRKtWrQy9XVQLCXSk+7T0MPJzc2RZNZD0xpo3oQs6N/fECz//gz+PJeHQua145+buGBTpz3IlIrIQzNkx03wd0dLfjc0uBppeYtVDA9EqwE2NWzT5812Ys/KwGseIiIjMH4MdM6PRaHAm7b9ghwyjc3Mv/Db9StzRL0I9/mZ3PK5+dwt+PpTAmdOJiKytGWvBggW6+6Wlpfjyyy/h7/9flf+MGTMMt3V0kaScIuQXl8HRzhbNvV1YQgbk4miHl8d3xrVdg/HkisM4k5aPGd8cwP92nsWzYzuga6g3y5uIyBqCnffee093v1mzZmpCUC0bGxsGO03UhBXu6wo7W5vG/jir1LeVH9bOHIzFW0/jo82nsDs2HeM++BtjOjfDrKvbch4yIiJLD3ZiY2MbZ0uoTs7o5etQ43F2sMOM4ZG4sVco3vnjBFYdPI81Ry+oZUSHINw/uBWuaOHDnCkiIkvO2SkuLsaJEydUUxY1jdzCUiTnVEz8GeHnymJvAtJU+O4t3fHHzMGqZsfGBlgflYSJn+zA8He34JMtMUj59zshIiILCXby8/MxdepUuLq6olOnToiLi1PPT58+Ha+//npjbCP9S5uYLKP/cuLPptU2yAOLJvfC+tlDcOsVYXBxsFMTsc5bcxz9523A/Uv3YvWB80jnOD1EROYf7MyZMweHDh3C5s2b4ezsrHt+xIgR+O677wy9fVRNsMNaHeORSVdfv7Erdj8zXI3R0z3MG6XlGjVGz8zvDqL3K+sw4aO/8cHGaByKz1QDQBIRkZnl7KxevVoFNf369auUryC1PDExMYbePvqXDCIYn14x8WcLP+brGJtMKCqjL8tyMilH1er8ceQ8YtIKsT8uUy1v/3kSDrZASx8HRPo6oI2vIyK87BHiYQ9HO+Mkl0vPyfDwcKN8NhGR2QQ7KSkpCAwMvOj5vLw8Jms2ogvZhSguK4ezgy0CPZ0a86OoAU1ct3Z0xQs3jkOxnQtcWvVWi1NYJ8DFEyfTStQCVEzxodGUozQzCSXp51Cafh6lmRdQknlB3ZZmJQFljTeYoYurK45HRTHgISKrUu9gp3fv3mpOLMnREdranc8++wz9+/c3/BaScjbtvy7ntno1amQaUlNTUZCfj0lPvoig8NbqOZlzK6+0GOnFtkgvskFGsQ1ySmxQAls4+ASrBa2vuOi9XOw0cLXXwE23QHff2VaOuYZtY1JcDJa98bjaVtbuEJE1qXew89prr2HMmDE4duyY6ok1f/58dX/79u3YsmVL42wl4WxaRa1ABJuwTJoEOqGRnWodAVsGhczIL1bJzJkFJcguKEHWv0tJmQYFZTZqSaumk5e9rQ08XRzg6Wyv5kbTLt6ujvB2dWAgTERkiGBn0KBBOHjwoOp51aVLF/z555/o2bMnduzYoR6T4eUX63U592WXc3MmNaHSk06WUB/XiwKhwpJyXeCTVfhfICS3OYWlKhlagqTqen3JqNrSxCm99Zp5OSPE20X1GiMisnb1DnZE69at8emnnxp+a6jGWc6Fv7sju5xbeCAkU1bIIsFKdUnqOYXa4Ke0UjAkNUWS03Uuo0AtWkGeTojwdVM9+Mo1TfwfIiIy52CnOjk5OXj00UfVfS8vr0rTStDlYRMWCZkepKK5yvGiAikv1yAtrxhJ2YUqmT0xq1DV/sgs7rLsPpMOB1sH+I6ejqPJReheroEtpxshIitR72BnwoQJ1T5fVFSEtWvXYuXKlZXG36HLI00b2podNmFRTSRwCfBwUovM4K4dcftseh7i0vJxNj0fRaXl8Og2Cs9vTseiAxsxrlsIbuoVisggDxYsEVm0Bo2zM3HiRLi4VJ5xu6Cgour8+uuvN9zWETLyS1RCq1zVB1fTtEFUE3dne3QK8VJLuUaDg0ej8Pu6jQjoMVLV/Hyy9bRaugY54tpIN/QMdjKJBGeOBUREJtGMtWDBgovG2rlw4QJ++OEHQ20X/Sv+31qdEC9n2Ns1eCozsnISxDjnJyN97UKkr/sYLq17w73TMLi06YPDScVqKUlPQM6+n5F7eB00pcab74tjARGR0YMdSaLUHzlZ/3kyvPiMimAnjL2w6DIV5Gar27H3PoF2XXup+3mlZYjJAc7k2gK+IfC9+gEEj5qGdp5laOVRjqYe6JljARGRSQQ7kkMyfPhw1Yzl6emJli1bYvDgwRgwYECjbKA1k6YHbc+asCrdlIkayi8kotJYQO0AlJSVIyoxG/vOZiC7sBSHM+1xusAeV7TwUc1g0oxKRGQ1wc7cuXN1CclpaWk4ffq0miuLNTuGJ2PrSFKpGj/Fg1NEUONxsLNF11BvFdgcS8zG7th05BaVYtOJFDXP15WR/mjl78bjnIjMkm1Dgh1ZZCTlTz75BOvWrUNycjLuv/9+Vevz0ksv4d133zXIxpWVleG5555TtUdSkyTj+7z88svqc7Tk/vPPP4/g4GC1jsy+Hh0dDUvK1wn1cWE3YWoSUoPTpbkXpgyIwNC2AXBztFPj+Px6OBGrDyZUO5ghEZFVjLPj5OSkAiA3NzcVfOgHI5fjjTfewKJFi/DVV1+pWdX37t2Lu+++W43jM2PGDLXOm2++qRKmZR0JiiQ4GjVqlJrCwty7wOuasJivo0RFRcFUmfK2NYS9rS26hXmjQ7An9p5Nx/6zmWoIhGW7zqoaoH6tfOFkz9GZicg8GGxQQQl0tE1chiLzbUlX9rFjx6rHLVq0wDfffIPdu3erxxJUvf/++3j22Wd1Xd6XLl2KoKAg1UX+1ltvhbkqLS9HQqY2X6dyN39rk52eom4nT54MU5ebmwtL4mhviwGt/dEx2BPbolNxOjUPB+MzcSo5F1e1C0CrAHdjbyIRUeMEOzLrudS6SO2J5Op07NgRTz75JK655hoYkiQ9L168GCdPnkTbtm1x6NAh/PXXX7pmstjYWNXlXZqutKTWp2/fvmquLnMOdi5kFap5kFwd7eDrdvGIuVbZi2jaM7peRKYmavcWrPlqPgoLC2GJZNTm67qF4GxansrjkaatXw4nom2QO4a0DYCro8Gum4iIDK7eZ6jPPvsMDz/8MO666y7ce++96jkJQGRk5Y8++gj33HOPwTbuqaeeQnZ2Ntq3bw87OzuVw/Pqq69i0qRJ6nUJdITU5OiTx9rXqiPJ1bJoyWeYmvj0/3phMfm7+l5EpkS6TFuDCD83TO7rgp2x0rSVgZNJuWqEZgl42jXz4L5KRJYR7EiOzPz58/HAAw/onrvzzjvRo0cPVdtjyGDn+++/x7Jly7B8+XKVsyOzrc+cORMhISGYMmVKg9933rx5ePHFF2Ee4+tYdxMWmR4Z3HJQG39EBrpjfVQSUnOL8cexJMSk5GFY+0A1kSkRkVn3xjp37lylZiOtq6++GmfPnoUhPf7446p2R5qjunTpgjvuuAOzZs1SwYpo1qyZuk1KSqr0d/JY+1p15syZg6ysLN0SHx8PU1JUWqYmcxQcX4dMVZCnM269Ihz9W/lBhuE5lZKL/+06izNpecbeNCKiywt2WrVqpXJ2qvrll18QHh4OQ8rPz4etbeVNlOas8vJydV96X0lQs2HDhkpNUrt27UL//v1r7T0mAyLqL6YkIbMQ0qHNy8UBni4Oxt4colq7qvdp6YuJvcPg4+qg5nH76WACNh1PVgMVEhGZZTPW//3f/6lcnZ07d+pGTf7777+xYsUKNe6OIV133XUqR0eCKGnGOnDggEpO1jaVSS6LNGu98soriIyM1HU9l2au8ePHw9zH17H2XlhkXrU8t/cJx9+n0nDwXCYOn8/CucwCjOncDP7uHBCTiMws2JHEZBm/Rrp8S06NBBbSG+vXX39V49sY0sKFC1Xw8tBDD6mBC+Wzpk2bpgYR1HriiSeQl5enBjXMzMzEoEGDsHbtWrMeY4fzYZG55vIMaReAFv6u+PNYkhqA8Ns98Wpwwk4hnkxeJiKjaVB/UcmhkcXDwwNbtmxRTVuNQd5fgipZaiK1OzJqsyyWIL+4VCV8akdOJjLHHluT+objz3+ScDY9HxuOJ6vaymEdAjkQIRGZR7AjXcy1ZEyRBx98UA0oqLVy5UrDbZ0VOv/vqMl+7o4cu4TMloy7c333EDWv1vaYVJxMzkVSThFGd26GZp7mW+tKRFYS7MigfVrmMKKtuTn/76jJod6s1SHzJrWuvSJ8EOLtjDVHL6iBCH/YG4+BbfzRI8ybzVpEZLrBzpIlSxpnS6hSsNOcwQ5ZiGAvF5W8LGPyyFg8Mu2EzPs2smMQnB04Jg8RmWDXc2o8hSVlunyd5szXIQsiQc3YLsEY2i5AdVePTc3D8t1xSMyqCO6JiEyqZsfX17fW19PT0y9ne6yaduJPGa+Ecw2RJTZrdQv1RrCXM34/UtGs9eO+cxjY2h89wtmsRUQmFOxI927pHaWfu0OGIeOSCNbqkCUL9HDGbX3CsDEqWSUubzuVqvZ9adYiIjKprueBgYGG3xorp+2JxXwdsnRO9naqZ1bz81nYGp2qa9bq5WVj7E0jIgtk25Cq6JycHBQUsK3d0PNhpeRUzMTOYIesgZxLuoZ6Y2LvUDU1Sk5hKbYk2cPjihugkflSiIiMFezISaht27Zwd3eHg4MDQkND1bQOq1atMtQ2WaXErELI6V1O+h7OnA+LrK9Zq22gOzSwge+wqZj3dwYy8yuS9YmImrwZa9OmTSrgKSkpUZNuJiQkYM+ePZg4cSIWL16Mu++++7I3yhqxCYusmbZZy+3AcexPKcfeBGDsgr+w4LYeaqweIqImDXaGDBlS7fM9e/ZUk3Qy2GkYjq9D1k6atVp5lOO3dx9Dr+kfqWPilk924MnR7XHvlS05CCERNW2CcnXuu+8+tGjRwlBvZ1VKysqRlF2o7rMnFlm7kuRYvHW1P76NscWvhxPx6u9R2Hk6DW/f3A0+bo7G3jwisqZBBU+fPq1mOv/tt9/UfZkfa/z48YbdOitxIasQ5RrA3ckens4Giz+JzJargy0W3tYDr4zvDEd7WzWZ6NgF27DvbIaxN42ILDHYKS0txe23347c3Fz1WPJ0br75ZrRp0wY33HCDCnAiIyNVzo700qLLG19HqvKJqKJZa3K/CKx6aABa+LkiIatQNWt9siUG5XJ1QERkqGDH3t4eP/30E5KTk9XjRx99FEePHsW2bdvUrOeybNmyRT03a9asun4u6Ung+DpENeoU4oVfpg/CtV2DUVquwbw1xzH58126EceJiAzSjOXv769qeMTPP/+MTz/9FAMHDoSdnZ1aBg0ahE8++QSrV6+uy9uRntLyciT+m6/Dmc6JqifDMUiz1ms3dIGzgy22x6Rh1Ptb8dPB8ywyIjJMsCNNVvv27VP3y8vLq50fy8fHB/n5+XV5O9KTlF2EsnINXB3t4O3K8XWIamvWur1vOH6fcSW6hXmrQQgf/fYgpn9zgGPyENHlBzuTJk3C008/jaSkJFWj88ILL6jmKy0ZTfnFF19Ev3796vJ2VEOXc+brEF1aqwB3rHigP2aNaKtmUP/lUIKq5dkWncLiI6Jq1anrzz333INdu3ahW7du6Ny5M37//Xds3LhRPRaHDh1SoymvWbOmLm9HejiYIFH92dvZ4tERkRjaLgCzvjuI06l5uOPz3ZjSPwJPjG4PNyf2aiSi/9T5jCA5OZMnT1ZdzSMiIlRzlrb56pZbblE9tmQKCaq7co1GdTsXId4uLDqiepLmrN9mXIl5a6KwdMdZfLXjLNZHJWPehC4Y3DaA5UlESr0uf6688kq1kGGk5RajuKwcjna28HPnYGlEDeHiaIeXru+MER2CMGflEdU0fOcXu3Fjz1A8d20HeLvy2CKydg2u65Vk5Li4OBQXV56sr2vXrobYLqug7Tob7OUMW46vQ3RZpCbnz1mD8dYfJ/DVjjNYsf8ctpxMxnPXdsS4biHMiSOyYvUOdlJSUnDXXXdh7dq11b5eVlZmiO2yCglZFcEOm7CIDENydV4Y1wnXdQvBkysO41RyruqxtXxXHF4e3xltgzxY1ERWqN7TRcycORNZWVkqYdnFxUUFPV999ZUaRVnG4KG6S8gs1NXsEJHhyEzpv80YhMdHtVPj8uyKTcc187fh1d+OIbeoYswwIrIe9Q52pBeWzG7eu3dv2NraqmRlSVx+8803MW/evMbZSguUXViiTrq2NkAzBjtEBudkb4eHr2qDdbOGYGTHIDX68qfbYjHs7c34bk+cGt+KiKxDvYOdvLw8BAYG6npiSbOW6NKlC/bv32/4LbTwfJ0ADyc42DV4PlYiuoQwX1csvrM3ltx1BSL8XJGcU4QnVxxRE4tuOcmxeYisQb1/Zdu1a4cTJ06o+zLOjnRJP3/+PD7++GMEBwc3xjZapMR/m7BCvNjlnKgpXNU+UCUwPzu2A7xcHHD8Qg6mfLFb9dw6ej6LXwKRBat3grJMBJqYmKjuz507F6NHj8ayZcvg6OiIL7/8sjG20aKTk4O9ma9DVFVUVFSjFUpPN2DBSF/8GJWLNafysPVkilr6NnfCLZ080MLboU7zBYaHhzfaNhKRkYMdyc/R6tWrF86ePYvjx4+rA19OAHRpRaVlSM2t6LLPmh2i/2Snp1x0nmlM9t7N4D1oMlw7Dsau80VqyTu+DVl/f4OS1Lga/87F1RXHo6IY8BCZicseU93V1RU9e/Y0zNZYCe2oyVKVzmHtif5TkJutbsdOewbtuvZqsqLJLilFVJYdzuXbwa39lWoJdilHW88y+DtVTmROiovBsjceR2pqKoMdIksNdmbPnl3r69JTi+rW5TyETVhE1fILiUBoZKcmLZ2OAFJzi7DrdDpOpeQiscBWLTI0RO8IH7T0d+PAhETWEuwcOHBAd/+vv/5STVky3o7grN31HEyQyclEJsXf3QljuwYjI68Y++MyEJWYg8SsQvxyOFHVxHYN9YJ3xbSARGTJwc6mTZt09z08PLB8+XK0atXK0NtlsWRsD07+SWTafNwcMbxDEPq18sPB+EwcPp+FrIISbItOhZ2NA3xHT0dMRgnYgE9kHjjASxNLyS1Sg5s529vCx/XSvT6IyHgkp25gG3/cO6glhrUPhL+7I8o0NvDoNgqPr0vFmPnb8Nm206r5i4hMF4MdY03+6e3CZj8iMyEDf3Zp7oXb+4RjSGAJ8o5tgb0tEJWYjVd+i0Lf1zbg3q/2YM2RRNXbkojMvBlLf/6r8vJybNiwAUePHtU9N27cOMNtnUUPJsjxdYjMjeQl+jtrkPrLW3jtxu5IdgnD5jMFiE4vwfqoZLW4O9pgYJgLBoQ5o6O/I+xkThgj4FhARJcR7IwfP77S42nTplU6EXDW85ppNBq9wQQ5cjKROY8FdP9dk3TP2fuFwr3zcLh1GoZcDz/8EZOvlrK8DOSf3IH843+hMP4ooGm67GaOBUR0GcGO1OZQw0iCY35xGexsbBDk4cRiJLKwsYA0GiC5sATn8m1xvsAWcPOBR49r1OJkq0GIazmau5QjwFmjJgFuLBwLiMjAgwpS3SX8O5hgoKcT7Dn5J5FFjgUUJqPL/9vz8lxGPqKTcxGTnIvC0nLE5tqpxcneFi383dA6wA0t/Nw4GTBRI2Ow04QS/01ODmETFpHFk1ydCD83tVzVLlAFPqck8EnJQ0FJGU5cyFGLWs/XFa0C3NDK3x0ujnbG3nQii8NgxxgjJzM5mch6A5/2FWNtxaRUBD7SvH06NU8tNkhWF0NS49M6wB2eLhyegsgQGOw0EbmSS8+vmPwzmCMnE1ktWxsbFdDIMqiNP9LyilUzlwQ+Mg7X+cwCtWyNTkWgh5Oq8ZHAx8/NkcNVEDUQg50mbsKSgQRZTU1Euq7s7k5q6dvKD9kFJboaHxmTKzmnSC07T6er6Sq0NT4yXxen5yFq5GBHupevXr0aUVFR6nGnTp3U+Dp2dmxrvlRyMvN1iKgm0mzVI9xHLfnFpYhNzVOBT1x6vmru2h+XqRZXRzu0kgTnQHeE+bgabSwfIosNdk6dOoWxY8fi3LlzaNeunXpu3rx5CAsLw2+//YbWrVs3xnZaTnIym7CIqA5cHe3RKcRLLcWl5TibVhH4xKblqSEsjiZkq8XRTnp2uaoaH+nZ5ShDOxPR5QU7M2bMUBN/7tixA76+vuq5tLQ0TJ48Wb0mAQ9VVqYBknIq5s4J8ebIyURUPxLARAZ5qEXbpV0Cn9MpucgrLsPJpFy1yBheYb4u8NfYwsaB5xoirXpfAmzZsgVvvvmmLtARfn5+eP3119Vrhnb+/HkVSMlnuLi4oEuXLti7d2+lUYmff/55BAcHq9dHjBiB6OhomJLMYht1gnJxsFPt7kREl9uzSyYmnTqoJSb2DkWvCB94uzigTKPBmbR87E23R+gj/8P8XZnYejJFnX+IrFm9a3acnJyQk5Nz0fO5ublwdHSEIWVkZGDgwIG46qqrsGbNGgQEBKhAxsfHR7eOBF4LFizAV199hZYtW+K5557DqFGjcOzYMTg7m8aVTWqRja5Wh0mFRGQocj6R3p2yDGzth/S8YjWWz9H4NOTCGVvOFmDLF7tVr67xPZrjhh7N0SHYk18AWZ161+xce+21uP/++7Fr1y5VqyLLzp078cADDxh8EtA33nhD5QItWbIEffr0UcHMyJEjdXlB8tnvv/8+nn32WVx//fXo2rUrli5dioSEBJVAbSrSiiqKmcnJRNSYgY/fv726RgaXIPHrxzC6tSu8XR1Uj67FW09jzPxtGPfBX/hmdxxyi0r5ZZDVqHewI7UoEmz0799f1ZzIIrUvbdq0wfz58w26cTLDeu/evXHzzTcjMDAQPXr0wKeffqp7PTY2FhcuXFBNV1peXl7o27evyimqSVFREbKzsystjSlNW7PD5GQiagI2NkBxwgnc38sLu58egU/u6IXRnZrBwc4Gh89lYc7KI+j76np1e+RcFr8Tsnj1bsby9vbGTz/9pJqTjh8/rp7r0KGDCnYM7fTp01i0aBFmz56Np59+Gnv27FFJ0NJcNmXKFBXoiKCgoEp/J4+1r1VHeo+9+OKLaAr2vqEoLreBva0NAjj5JxEZIbl5VKdmaknLLcKK/efw7e54NWKz1PDI0inEE7f1CVfNXG5OHH6NLE+D9+rIyEi1aMfdaQwyw7rU7Lz22mvqsdTsHD16FB9//LEKdhpqzpw5KoDSkpodaS5rDM6hHdVtkKczx8IgIqOSZq77B7fGfVe2wq7YdBXorDlyAf8kZOPZ1UfxxtrjuLlXGO7sH6EmKiWy2mBHmo6klkVqeCQIkaDj999/V01bP/zwg8qbMRTpYdWxY0WwoCW1SCtWrFD3mzVrpm6TkpLUulryuHv37rUmWcvSFJxCO6hbdjknoqamHfi1OtKdZEpbYEJEADafycfamHwk5pbii79jseTvWPQIdsLYSDd0C3JUU1w0Bn9/f4SHhzfKexNdVrAzbdo0JCcnw8PDA8OGDVNNRtKs9dlnn2HmzJnYuHEjDEVygU6cOFHpuZMnTyIiIkLdl4RlCXg2bNigC26klkaSpx988EGYAqfmndQt83WIqKlkp6eoWxm2o+5s4NyyBzx6XQfX1ldgf2KRWkrSziFn/6/IPboBmuKKwVENxcXVFcejohjwkOkFOxJIbNu2TQUcMtaO5NH07NlT5exIYrAhzZo1CwMGDFA1SBMnTsTu3buxePFitWh7H0iA9corr6gmNW3X85CQEIwfPx7GlllYBgffEOk3puayISJqCgW5FZ0uxk57Bu269qr33+eUFON0rh3O5NoCfqHwvfoBBI6chgi3crT2KIOHAYYLS4qLwbI3HkdqaiqDHTK9YEfG2JEmI+n15OrqqpqzhNxWN/7O5bjiiiuwatUqlWPz0ksvqWBGuppPmjRJt84TTzyBvLw81R0+MzMTgwYNwtq1a01ijJ3jqRWznHs6aODkwHnDiKhp+YVEIDSyona5vqQBXqapiErMxqFzmcjIL0FMrp1aWvi5onuYN8J9XTl2GFlugrIEExLsSAKxNCFJ0rAEGo1BxvWRpSZSuyOBkCymJiq1RN36O3H0UiIyz55c3cK80TXUS01GejA+U43QrF18XR3RLcxLDVToYMc5ucjCgh39nlCSw6PF0YGrr9nxY7BDRGZMzu0yRYUsGfnFOByfhX8Ss5CeX4xNJ1KwPSZNdV/vFuqtZm4nMvtgR2pzqC7lpIGtDaApL4OfE8uMiCyDj6sjhrQLQL/WvjiWIE1cWcgqKMH+uEwciMtEqwA39Ajz4fQ4ZFLqXe8o0zHICMR0iYK1tcG84f6If38iXJmuQ0QWxsneDj3CfdSYPNd1DUaYjwukwV5mY/9x/zl8szteBUOlZbzYIzMMdu6++25kZXF48brSlBSpoduJiCyRjMHTKsAdE3qGYnLfcHQO8VQjxqfkFmFdVBK++PsMdsSkcS4uMq9mLJl8k4iIqLoRmod3CMKANv7453yWauKSCUd3n0nH3rPpaBPoji7NvdDc24WFR6afoPz999/D09Oz2tfuvPPOy90mIiIyYy4Odujdwhc9w30Qk5KLA/GZSMwqxMmkXLXITOyhjrawdfUy9qaSlWhQsPPmm2/Czs6u2ox9BjtERKTNXYwM8lBLUnYhjpzPwsmkHGTmlyAz3x6hD32Jt7Zn4EH3FAxq46/WJzKZYGfv3r0IDAw0/NYQEZFFksmQZRkcGaACnv2nLyCj2AE7zhVixxe7VdPWuO4huL57CNo3q77lwBji4uLUKM+mjHOMNeKs50RERA0ZqLBzcy9455/Dwhcew9TXPsdf54pxPrMAizbHqKV9Mw8V+IzrFoJQH1ejBjrtO3RAQX4+TBnnGGuEYEfmxKquCYuIiKg+SlJicV9PL7w3pRs2Hk/G6gPnsflECo5fyMHxtSfw5toTuKKFD67pEowRHYIQ5tu0gY/U6EigM+nJtxAU3hqmiHOMNVKwExsbW98/ISIiqpGzg50KaGTJyi/B2n8S8dPBBOw4nYY9ZzLU8uIvx1SNz8iOQRjRMQidQ7yaLMdHAp2GzjFGZhrszJgxQ81wLrf6PvjgA5w6dUpN1ElERNQQXq4OuOWKcLVcyCrEr4cTsO5YEvacSa+o8bmQgwUbTyHI00nV9gxuG4B+rfzgxWkqyJDBzooVK/Dzzz9f9PyAAQPw+uuvM9ghIiKDaObljHuvbKWWjDyZhysZ66OSsOVECpKyi7BsV5xapIKnS6g3Brb2U726ekb4qNoiogYHO2lpaWrG86pk3B1Tz1gnIiLz5OPmqEZplqWwpAw7T6epPJ+/TqXidEoeDsVnquWjzTFwsrdF7xY+uKKFL3pH+KJHuDfcnNgfx5rV+9uXJqy1a9fikUceqfT8mjVr0KpVK0NuGxER0UWk1mZou0C1iMSsAvx9Kg3bT6Xi75hUVesjj2URdrY26BDsoQKfXhEVQZDUGpH1qHewM3v2bBXopKSkYNiwYeq5DRs24J133mETFhERNblgLxfc1CtULTKlkYzavON0OvadSVfJzdKt/ej5bLV8uf2M+hsZ10dqf2Sk594RPmgX5MFBDS1YvYOde+65R816/uqrr+Lll19Wz7Vo0QKLFi3i6MlERGRUMpJ/m0APtdzRL0JX87P3TAb2nc1Qc3TJbOwSAJ0/WKB6fQlPZ3tV49OnZcUiYwGR5WhQI+aDDz6oFqndcXFxgbu7u+G3jIiIyEA1P9d1kyVEPZbJSQ/GZarAR4KgA3EZyC4sxYbjyWoRro52iPSxg1f/W5BWZIMQjUbN8E5WFOyUlpZi8+bNiImJwe23366eS0hIUEnKDHyIiMiUuTvZY1Ckv1pEaVk5jiVmY3dsOnbFStNXupq/61BSGbwH34HNScDOtNNqUMMIP1e08HNjwrOlBztnz57F6NGj1TDa0px19dVXw8PDA2+88YZ6/PHHHzfOlhIRETUCeztbdA31Vot0cy8v1yA6ORc/bjmI979dA+/2A1BYWq6ek0WEeDmjTaC7WjycHfi9mDjb+v7Bo48+it69eyMjI0M1YWndcMMNKlGZiIjInMnIzO2aeWBMpBtSV8/DtaEluLlXqMrlkcEMRUJWIbZGp+KLv8/guz3xOHQuE0WlZcbedDJUzc62bduwfft2ODo6VnpekpTPnz9f37cjIiIrFhUVBVPfNhm0MMTbRS39W/khp7AEMSl5iE7OQUJmIS5kVyx/RaciMshdTWUR7OWskqXJTIOd8vJylJVdHL2eO3dONWcRERFdSnZ6irqdPHmyyRdWbm5F05WWNFt1D/NWS15RKU4m5eCfhGyk5RUjKjFHLX5ujqpLe1t2aTfPYGfkyJFqPJ3FixerxxK5yo4wd+5cXHPNNY2xjUREZGEKcrPV7dhpz6Bd114wRVG7t2DNV/NRWFhY4zoyMnOPcB8V+EjtjozlI8GPBD5/HEtSk5nKQIYdgz1VbhCZSbAjgweOGjUKHTt2VDuA9MaKjo6Gv78/vvnmm8bZSiIiskh+IREmO6N4UlxMndeVC3/p4i7L4Eh/HD6fhQNxmapL+6YTKaqXV58WvujSvOlma6fLCHZCQ0Nx6NAhfPvttzh8+LCq1Zk6dSomTZpUKWGZiIjIGjk52KkBCqW2R5q3ZDBDGdtn88kUFQRJMBTh52bszbQqDRpnx97e3izaWYmIiIzFwc5WBTxSm3M0IUtNXpqeV4zVBxPQ0t8NV0b6w8e1cmcfMpFg5+eff6719XHjxl3O9hAREVkUmYi0W6i3mn9LmrMOn8tEbGoezqbloV8rP5XTw9GZTSzYGT9+/EXtlDLxmvZ+dT21iIiIrJ3M1j6kbYCq6dkanYKzafnYHpOmAp+rOwaxlqcR2Tak67n+4urqilOnTtXYJZ2IiIj+4+vmiOu7heDqDkFwtLNFYlYhlu+Kw6H4TF3lARnWZfeD46BJRERE9f/t7BjiiUn9whHq44LSco1KYP7pUAIKSlhxYFLBzpkzZ5CXl8fBBImIiBrA09kBE3o0V81bktsjTVvf7I5DUnbNY/tQE+TsTJgwQd0WFBRg586dGD58OAICAhrw0URERCS1PNJrq7m3C347koisghL8sO8cRnUMQmQQZyYwSs2Ol5eXWlq2bIlXX331kr2ziIiI6NICPJxw2xVhqlt6WbkGvx+9oMboYR6PEWp2lixZYoCPJSIiouoGJLy2azC2nkzBoXNZ+OtUqqrpGdo2gCMvN2Wwk51dMZ9JTTw9PS9ne4iIiKyajLkjOTxeLg7YGp2KI+ez1EzrYzoHw9Ge82s1SbDj7e1dbQ8sqWbjODtERESXT35PZYJRmWH9j38u4ExaPlYfPI/ru4fAyd6ORdzYwU6rVq2QnJyMp556CgMHDqzvnxMREVEdtQl0h7tTqAp0ZDyenw4mMOBpimAnKioKCxcuVMnJBw4cwJtvvqmSlYmIiMjwmnk544YezbHqQEXAs/pAAsb3YA1PfdS78c/BwQGzZ89GdHQ0mjdvjq5du+Kxxx5DZmZmfd+KiIiI6iDI01mNx+Nkb4sL2RUBT1EpBx+sqwZnOvn6+uL9999XtTsyuGCbNm3UYyIiIjK8wGoCntJylnSjNGP16NHjogRlSU4uKipSNTwzZ86s71sSERFRXQOens2xav95FfDsLLYHbJmw3OiznhMREVHTCfRwxrjuIVi5/zySCm3hN+phDjxo6GBn7ty59f0TIiIiMqBgLxeM6dwMvxxOgHvXkfjun1z06sUirgkHFSQiIjJDrQLc0cO3DAfS7fH9sVx03xWH2/uGG3uzTBIHFSQiIjJTrdzLsemX5fAeeDueXX0EzbycMKx9kLE3yzJ6Y/3444/YuHFjpWXTpk3qtjG9/vrrKjlaPwm6sLAQDz/8MPz8/ODu7o4bb7wRSUlJjbodREREpiLrr+UY3tIF5RpgxjcHcSo519ibZP41O0JGTg4MDERT2rNnDz755BM1ro++WbNm4bfffsMPP/ygZmN/5JFHMGHCBPz9999Nun1ERETGMq2XF3Lggt2x6Zj29V6sfnigmmqCLqNm59ixY2ok5bi4OBQXF6Ox5ebmYtKkSfj000/h4+Ojez4rKwuff/453n33XQwbNgy9evVSs7Jv374dO3fubPTtIiIiMgX2tjb4aFJPBHs5IyYlD7O+O4Ryqeqhhgc7w4cPR6dOndQ0EW5ubujSpQvee+89NBZppho7dixGjBhR6fl9+/ahpKSk0vPt27dHeHg4duzYUeP7yZhAMnu7/kJERGTO/N2d8MkdvdTM6OujkrBgY7SxN8l8m7FiY2NVf34JMiRISEhIwO7du/Hcc8+htLQUjz/+uEE38Ntvv8X+/ftVM1ZVFy5cgKOjo5qJXV9QUJB6rSbz5s3Diy++aNDtJCIiMrauod54dXxnPP7jYby/PhqdQrxwdUcmLNe7ZiciIgItWrRAZGSkaja67rrr8PLLL2PRokVYvHixQb+0+Ph4PProo1i2bBmcnZ0N9r5z5sxRTWDaRT6HiIjIEtzcOwxT+keo+7O+O4gzqXmwdg2eG6uqW2+9Fd999x0MSZqpkpOT0bNnT9jb26tly5YtWLBggbovNTiSM1R1ElLpjdWsWbMa39fJyQmenp6VFiIiIkvx7LUd0aeFL3KLSjH9mwMotvJJtGwvJxD53//+pxZpZpLZ0CUoMSTJDTpy5AgOHjyoW3r37q2SlbX35XM3bNig+5sTJ06oxOn+/fsbdFuIiIjMhYOdLebf1h3erg44cj4Lb649DmtW75wdqWmRWpzNmzfrcmWkZuWqq65S+TUBAQEG2zgPDw907ty50nOSEC1j6mifnzp1KmbPnq1mYZcamunTp6tAp1+/fgbbDiIiInOcUuKtm7rhvqV78dlfsRjYxh9XtW/aYWPMtmZHgomcnBz8888/SE9PV8vRo0dVsvKMGTPQ1KQX2LXXXqsGExw8eLBqvlq5cmWTbwcREZGpkeTkuwa0UPcf++EQkrILYY3qXbOzdu1arF+/Hh06dNA917FjR3z44YcYOXIkGpvUKOmTxGX5bFmIiIiosqfGtFeDDR5LzFYJy19P7Qs7WxurKqZ61+yUl5erPJmq5Dl5jYiIiEyHs4MdFt7eA66Odtgek4aPt8TA2tS7ZkdGKpbu4N988w1CQkLUc+fPn1fTNkhCMRERETUtmdXgUu7p5o4P9mThvXUn0Kw8DS19mm46CX9/fzXgr9kEOx988AHGjRunxtoJCwtTz8k4NZIwLD2ziIiIqGlkp6eo28mTJ9dp/YDxT8O13QBMX7YHiUtnAWWlaAourq44HhVltICn3sGOBDjS1Vzydo4fr+jKJvk7VadyICIiosZVkFsx3dHYac+gXddel1y/sAxYn6gBAlti5Esr0Nm7rNG/oqS4GCx743GkpqaafrAjPbCkK7iwsbHB1VdfrRZ9MqXDFVdcYfitJCIiohr5hUQgNLJT3UrINxe/HUnEyWw7dGsbobqoW7o6JyhLTyuZfbw6MifWs88+i4EDBxpy24iIiMjA2gS6o30zD8ic6H8eS0JJmeV3LrKtT82ONFVVnSFcxtiR2pwvv/wSq1evboxtJCIiIgMa0jYA7k72yMwvwfZTaRZftnUOdjZt2oS8vDzVdCUBj8x8/sYbb6gpGyRnR6Z1uOaaaxp3a4mIiMgg3dFHdKgYTfnguUycy8i36FKtc86OTAOxceNGVbsj3c9lMs3o6GjVA+umm25q3K0kIiIig4rwc0PnEE8cTcjGhqhkTOobDns7g80PblLq9b+SgEcm3ZQcHZkIdOvWrQx0iIiIzNSgNv5wc7RDZkEJdsWmw1LZNmRgIKnhkSkibr/9dmRkZDTOlhEREVGjcnKw000Oui8uAyk5RdbdjDVhwoRKj2WGcanZ6dOnD7p06aJ7npNwEhERmY/WAe6qh9ap5Fysj0rCLb3DYGthc2fVOdjx8vK66HHLli0bY5uIiIioCQ1tG4D49Hwk5xThQHwmekX4WGews2TJksbdEiIiIjIKNyd7XBnpj/VRydhxOg2tA9zg7epoMd+GZaZdExERUb10DPZEmI8Lyso12HA8WQ0xYykY7BARERFkKqhh7QNhZ2uDcxkFOJGUYzGlwmCHiIiIFGm66tPCV93fejIVRSWNP1FoU2CwQ0RERDo9I7zh4+qAgpIybI+xjKkkGOwQERGRjr2tLa5qVzH2zuHzWbiQXQhzx2CHiIiIKgnzdUW7Zh7q/qbjySg382RlBjtERER0kSvb+MPR3laNvXPkXBbMGYMdIiIiqnbsnQGt/dR9yd3JKyqFuWKwQ0RERNXq0twLgR5OKC4rx9boFJgrBjtERERULdt/x96RmbJOJuXibFoezBGDHSIiIqpRkKczuoZWzI+5+UQKSsvKYW4Y7BAREVGt+rf2g6ujHTILSrDvbAbMDYMdIiIiqpWTvR0GRwao+3vOZiCroATmhMEOERERXVLbIHeE/jtR6JaT5pWszGCHiIiI6jRRqIysbGsDxKbm4XRKLswFgx0iIiKqE183R/QI91H3pXbHXJKVGewQERFRncms6O5O9sguLMWeM+aRrMxgh4iIiOpMppAYHOmv7kvPrMz8Ypg6BjtERERUL20C3RHu64oyjQabT6ZAY+IThTLYISIiononKw9tF6CSlc+m5SMmxbRHVmawQ0RERPXm4+qIXhH/JSuXmHCyMoMdIiIiapArWvjCw9keuUWl2B2bDlPFYIeIiIgaxMHOFkPaVoysvD8uAxl5ppmszGCHiIiIGqyVvxta+LmiXANsOplsksnKDHaIiIjospKVpXbHztYG8ekFOJVseiMrM9ghIiKiy+Lt6oje/yYrb41ORXGpaSUrM9ghIiKiyybBjqeJJisz2CEiIqLLZm9ni6HtAtX9A/EZSMstgqlgsENEREQG0dLfTSUsS7Ly5hOmM7Iygx0iIiIymMH/JiufyyzAySTTSFZmsENEREQG4+XioGZGF9uiU1BiArnKDHaIiIjIoHqGe6ugJ6+4DMey7GBsJh3szJs3D1dccQU8PDwQGBiI8ePH48SJE5XWKSwsxMMPPww/Pz+4u7vjxhtvRFJSktG2mYiIyNrZq2TlipGVY3Js4eAfYdTtMelgZ8uWLSqQ2blzJ9atW4eSkhKMHDkSeXn/za46a9Ys/PLLL/jhhx/U+gkJCZgwYYJRt5uIiMjatfBzQ+sAN2hgA9+RDxk1WdkeJmzt2rWVHn/55Zeqhmffvn0YPHgwsrKy8Pnnn2P58uUYNmyYWmfJkiXo0KGDCpD69etnpC0nIiKiwW0DcCY1F85hnbDrfBF69TJOmZh0zU5VEtwIX9+KxCcJeqS2Z8SIEbp12rdvj/DwcOzYsaPG9ykqKkJ2dnalhYiIiAzL09kBnb3LkPbHh7gixAnGYjbBTnl5OWbOnImBAweic+fO6rkLFy7A0dER3t7eldYNCgpSr9WWC+Tl5aVbwsLCGn37iYiIrFEbj3LkHlyjuqMbi9kEO5K7c/ToUXz77beX/V5z5sxRtUTaJT4+3iDbSERERKbHpHN2tB555BH8+uuv2Lp1K0JDQ3XPN2vWDMXFxcjMzKxUuyO9seS1mjg5OamFiIiILJ9J1+xI5rYEOqtWrcLGjRvRsmXLSq/36tULDg4O2LBhg+456ZoeFxeH/v37G2GLiYiIyNTYm3rTlfS0+umnn9RYO9o8HMmzcXFxUbdTp07F7NmzVdKyp6cnpk+frgId9sQiIiIikw92Fi1apG6HDh1a6XnpXn7XXXep+++99x5sbW3VYILSy2rUqFH46KOPjLK9REREZHpMOtipywBEzs7O+PDDD9VCREREZFY5O0RERESXi8EOERERWTQGO0RERGTRGOwQERGRRWOwQ0RERBaNwQ4RERFZNAY7REREZNEY7BAREZFFY7BDREREFo3BDhEREVk0BjtERERk0RjsEBERkUVjsENEREQWjcEOERERWTQGO0RERGTRGOwQERGRRWOwQ0RERBaNwQ4RERFZNAY7REREZNEY7BAREZFFY7BDREREFo3BDhEREVk0BjtERERk0RjsEBERkUVjsENEREQWjcEOERERWTQGO0RERGTRGOwQERGRRWOwQ0RERBaNwQ4RERFZNAY7REREZNEY7BAREZFFY7BDREREFo3BDhEREVk0BjtERERk0RjsEBERkUVjsENEREQWjcEOERERWTQGO0RERGTRGOwQERGRRWOwQ0RERBaNwQ4RERFZNAY7REREZNEY7BAREZFFY7BDREREFs1igp0PP/wQLVq0gLOzM/r27Yvdu3cbe5OIiIjIBFhEsPPdd99h9uzZmDt3Lvbv349u3bph1KhRSE5ONvamERERkZFZRLDz7rvv4r777sPdd9+Njh074uOPP4arqyu++OILY28aERERGZnZBzvFxcXYt28fRowYoXvO1tZWPd6xY4dRt42IiIiMzx5mLjU1FWVlZQgKCqr0vDw+fvx4tX9TVFSkFq2srCx1m52dbdBty83NVbfnov9BUUE+TFFSXIy6vXDmJGLcXGGKuI0sR1PC/ZHlaErMYX9MORer+0009O+s9v00Gk3tK2rM3Pnz5+V/qNm+fXul5x9//HFNnz59qv2buXPnqr/hwjLgPsB9gPsA9wHuAzD7MoiPj681VjD7mh1/f3/Y2dkhKSmp0vPyuFmzZtX+zZw5c1RCs1Z5eTnS09Ph5+cHGxsbmDOJcsPCwhAfHw9PT09jb45ZYJmxvLh/mRYekyyvupIanZycHISEhNS6ntkHO46OjujVqxc2bNiA8ePH64IXefzII49U+zdOTk5q0eft7Q1LIoEOgx2WGfcx08FjkmXGfaxxeHl5XXIdsw92hNTSTJkyBb1790afPn3w/vvvIy8vT/XOIiIiIutmEcHOLbfcgpSUFDz//PO4cOECunfvjrVr116UtExERETWxyKCHSFNVjU1W1kTaZ6TwRWrNtMRy4z7mHHwmGSZcR8zPhvJUjb2RhARERE1FrMfVJCIiIioNgx2iIiIyKIx2CEiIiKLxmCHiIiILBqDHTOwaNEidO3aVTcoWf/+/bFmzRr1moz8PH36dLRr1w4uLi4IDw/HjBkzdPN9acXFxWHs2LFqNvjAwEA8/vjjKC0thbWVlz7JzR8zZowaNXv16tVWW151LTOZWHfYsGFwc3NT6wwePBgFBQW612VfnDRpknpNBumcOnWqbn44aysvGQLjjjvuUKO4S3n17NkTK1asqPQe1lReVb3++uvquJs5c6buucLCQjz88MNqJHt3d3fceOONF42Mb23HZW1lxnO/lXY9t2ShoaFqR4+MjFQ/0F999RWuv/56HDhwQD1OSEjA22+/jY4dO+Ls2bN44IEH1HM//vij+nuZKFVOEHLi3b59OxITE3HnnXfCwcEBr732GqypvDp16qRbTwafrG56EGsrr7qUmQQ6o0ePVlOtLFy4EPb29jh06BBsbf+7XpIfbimrdevWoaSkRA3qef/992P58uWwtvKS/SUzMxM///yzmtJGymDixInYu3cvevToYXXlpW/Pnj345JNPVLCob9asWfjtt9/www8/qBFxZSiRCRMm4O+//7ba47K2MpNzPM/99WDISTmp6fj4+Gg+++yzal/7/vvvNY6OjpqSkhL1+Pfff9fY2tpqLly4oFtn0aJFGk9PT01RUZHGGsvrwIEDmubNm2sSExPVJHKrVq3SvcbyurjM+vbtq3n22WdrLN9jx46pctyzZ4/uuTVr1mhsbGzUZL3WVl5ubm6apUuXVnrd19dX8+mnn1p1eeXk5GgiIyM169at0wwZMkTz6KOPquczMzM1Dg4Omh9++EG3blRUlCqjHTt2WPVxWVOZVYfn/pqxGcvMyNXNt99+q6bDkKrz6kgTllSNy9W3kKvyLl26VBpRetSoUWqyvX/++QfWVl75+fm4/fbb8eGHH1Y7Waw1l1d1ZZacnIxdu3apZoMBAwaochkyZAj++uuvSmUmTTEyZYvWiBEjVM2P/K217WNSTt99951qapC5+uR1aaYZOnSoVZeXNFNJ7Yz8X/Xt27dP1W7pP9++fXvVLC9lZc3HZU1lVh2e+2vGZiwzceTIEXUilROmtGevWrVKNVtVlZqaipdffllVh+vnD1SdOkP7WF6ztvKS6nL5MZJmh+pYY3nVVmY7d+5Ur7/wwguquVSmY1m6dCmGDx+Oo0ePqqYcKRcJhvRJsO3r62uV+9j333+vprGR/BMpB8kxkdfbtGmjXrfG8pKAb//+/apJpir5P8ukzlUnZJbjTlse1nhc1lZmVfHcXzsGO2ZCEpAPHjyoInfJxZGJT7ds2VIp4JErHLkCkOfkh8ma1VRep06dwsaNG1VuBdWtzKRmQkybNk03ua7knWzYsAFffPEF5s2bZ5VFWdsx+dxzz6mcnfXr16ucHUmAl5ydbdu2qdoJaxMfH49HH31U5Sc5Ozsbe3Msrsx47r80BjtmQq56tFeFvXr1UpH+/PnzVdKayMnJUQmkHh4e6gpSkva0pKlm9+7dld5P28uhumYcSy4v6bEWExNz0RWk9Py48sorsXnzZqssr9rK7KmnnlLPVa1J7NChg+odoy0Xae7SJ71kpBnHUsuspvJ64okn8MEHH6haL21CfLdu3VSgI02nH3/8sdWVlzRTyf9XeqXpN/9t3bpVldUff/yB4uJiFSDqH5ty3GnLw9qOy0uVWVFREezs7HjuryPm7JgpudqWnV0b1Y8cOVKdfKX3R9WrAKlqlyp3/ZOrXC1IXk91TWGWXF7yw3348GF1Ra5dxHvvvYclS5ao+yyvymXWokULhISE4MSJE5XK9OTJk4iIiNCVmfxQyQlaS2rQ5D369u0LayovyQkT+j3VhPwwaWvJrK28pMlTzkH6x53kK0mPNO19uUCT2kIt2d8kmNbmQVnbcXmpMpP9ief+eqgleZlMxFNPPaXZsmWLJjY2VnP48GH1WHpt/Pnnn5qsrCzVU6ZLly6aU6dOqd5F2qW0tFT9vdx27txZM3LkSM3Bgwc1a9eu1QQEBGjmzJmjsbbyqk7V3ljWVl51KbP33ntP9XqR3jLR0dGqZ5azs7Pa57RGjx6t6dGjh2bXrl2av/76S/Ugue222zTWVl7FxcWaNm3aaK688kpVFlJGb7/9tnr9t99+s8ryqk7VnkUPPPCAJjw8XLNx40bN3r17Nf3791eLNR+XtZUZz/31w2DHDNxzzz2aiIgI1Z1cDu7hw4frfoQ2bdqkfqyrW+RErHXmzBnNmDFjNC4uLhp/f3/NY489puuabk3lVZdgx9rKq65lNm/ePE1oaKjG1dVV/Qht27at0utpaWnqx9rd3V0FRnfffbfqNmuN5XXy5EnNhAkTNIGBgaq8unbtelFXdGsqr7oEOwUFBZqHHnpIdeGXMrvhhhvURZs1H5e1lRnP/fVjI//UpyaIiIiIyJwwZ4eIiIgsGoMdIiIismgMdoiIiMiiMdghIiIii8Zgh4iIiCwagx0iIiKyaAx2iIiIyKIx2CEiIiKLxmCHiBrVhQsXMH36dLRq1QpOTk4ICwvDddddV2keJLF9+3Zcc8018PHxUfO7yezg7777rpr8UOvMmTOYOnUqWrZsqSZ1bd26NebOnasmkSQiqglnPSeiRiPBycCBA9VM1m+99ZYKYEpKStQs1w8//DCOHz+u1lu1ahUmTpyIu+++G5s2bVLrr1+/Xs0gvmPHDnz//fewsbFR68tkmZ988omacVxmFr/vvvuQl5eHt99+m98kEVWL00UQUaORmhqZZV5msHZzc6v0msz6LUGNBCoye/qQIUOwYsWKSuv88ssvGDduHL799lvccsst1X6GBFGLFi3C6dOn67xdd911l/r8Hj164IMPPlCzld9+++1YsGABHB0d1TpDhw5F586d1f2vv/5azcr94IMP4qWXXlKBl5AZ4e+99141A/zKlSvh5+eHhQsXqhm65XmpvZIarS+++ELNWE1ExsFmLCJqFOnp6Vi7dq2qwaka6AgJdMSff/6JtLQ0/N///d9F60hzV9u2bfHNN9/U+DlZWVnw9fWt9/ZJIBIVFYXNmzer95dg5cUXX6y0zldffQV7e3vs3r0b8+fPV81qn332WaV13nvvPVV7deDAAYwdOxZ33HEH7rzzTkyePBn79+9XTW3ymNMQEhlRPScOJSKqk127dqkZ5VeuXFnreq+//rpaLyMjo9rXx40bp+nQoUO1r0VHR6sZwxcvXlyvb2XKlCkaX19fTV5enu65RYsWqRnIy8rKdDNMy+eWl5fr1nnyyScrbYvMfD558mTdY5mlW/4vzz33nO65HTt2qOeqzuBNRE2HNTtE1FgXUo26/vnz5zF69GjcfPPNKm+nvrp16wZXV1fdY2l6ys3NRXx8vO65fv366ZqstOtER0dXSpru2rWr7n5QUJC6ldykqs8lJyfXexuJyDAY7BBRo4iMjNQlFddGmqmENClVR57XrqOVkJCAq666CgMGDMDixYthTJLLo6UNjKp7ThKricg4GOwQUaOQPJpRo0bhww8/VEnIVUmCsBg5cqRa95133rlonZ9//lnVpNx2222VanQkebhXr15YsmQJbG0bdho7dOgQCgoKdI937twJd3d31TVea9euXZX+RtaRIM7Ozq5Bn0lExsFgh4gajQQ60uTTp08f1dNKAhepqZFeT9IkJCR5WbqS//TTT7j//vtV7y3psv7555+rXlM33XST6pauH+iEh4erruYpKSlqHB9Z6kvG5pExe44dO4bff/9djdfzyCOPVAqe4uLiMHv2bNWbTJKYpafVo48+asASIqKmwHF2iKjRSLdr6ZH06quv4rHHHkNiYiICAgJUrYx0F9eSgEbG15H1rrzyShQWFqoalGeeeQYzZ87UNQWtW7cOp06dUktoaGiNOT+yvtT6SLBUk+HDh6vPGDx4sOp6LrVHL7zwQqV1pBeV1P5IsCa1ORLoSEBGROaF4+wQkUWJjY1VOT5SYyPBTG3j7KxevbrG95EapO7du+P9999vxK0loqbAZiwisijSJCW1LzUFOkRkfdiMRUQWRQYxJCLSx2YsIiIismhsxiIiIiKLxmCHiIiILBqDHSIiIrJoDHaIiIjIojHYISIiIovGYIeIiIgsGoMdIiIismgMdoiIiMiiMdghIiIiWLL/B8RTcy85x8kRAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(data=co2_df, x=\"Average\", kde=True)\n",
    "\n",
    "plt.title(\"Распределение средней концентрации CO2\")\n",
    "plt.xlabel(\"CO2, ppm\")\n",
    "plt.ylabel(\"Количество наблюдений\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "114da346-1091-494f-91db-9aace103f23b",
   "metadata": {},
   "source": [
    "Гистограмма показывает распределение значений средней концентрации CO2 \n",
    "Значения находятся примерно в диапазоне от 312 до 430 ppm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "5a82845e-7399-44d4-a23f-47cc76585e10",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=co2_df, x=\"Decimal Date\", y=\"Average\")\n",
    "\n",
    "plt.title(\"Изменение концентрации CO2 во времени\")\n",
    "plt.xlabel(\"Год\")\n",
    "plt.ylabel(\"CO2, ppm\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f88f94e7-851b-4b10-af33-0ee3203b875f",
   "metadata": {},
   "source": [
    "На точечном графике видно, что концентрация CO2 увеличивается с течением времени.\n",
    "В начале наблюдений значения были около 315 ppm, а к последним годам превышают 420 ppm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "a40f208b-b51e-4ed5-ba2d-f6b9e0eb610a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=co2_df, x=\"Decade\", y=\"Average\")\n",
    "\n",
    "plt.title(\"Распределение CO2 по десятилетиям\")\n",
    "plt.xlabel(\"Десятилетие\")\n",
    "plt.ylabel(\"CO2, ppm\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "2b61f427-d2e7-4a12-bc1e-4607bde4104d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DMsjSOyN1kTvJTksXb9mH9HpIbvDgwWp2AumNINn2rPhs5AaSbjiC3NyS45Kx7smHKEjRPjm35/2+SgX81NOoZeZ7Ib0A5BiT32zTkfoTqW8c6si1lh4+ci7Ger7IvqWNocrucrzSE+F5ycwHcvMuM7NbEBG9Ksy0ExG9JPKHpRRkk0BRAh/5w1eCg+RkyiaZm1y2SzYt+bh16cIpXU+TV1B/XtJFWLJXEiDLH8PSJVWCxdRj2w2RLrTyR31G3ZHleOUcMps1Tp49l2ORAnAyTZQE2ZIBlCy7ZMMkGJHMtwQrZcuW1c/l/iykm7IEbHJDoWfPnqrbuWS6pWeA3ByRatfSBVwylhJ0yZRaxiquZ4YE3DJNVnK6sdqyXcYQy+cpxyNFtaSCtpy/nJ8MYZCss2QxDY3Fz0qSQZfjkV4PcgwSAEpBMwmkdd2b5fOXbsryGUnAJeOJpTiizDwgwU9qcp6pz10+Dwm2ZLtkoHVBt0z5Jd9vKUaYEakkLl3Xn6eivwTgklGWGgnyecssAs7OzioTKzcfJGCXiuRChoFITw85b7nx8/7776vrIm2l675UjJebXcmrl0tWV743derUUTcJUv+ey/dYbiBlRPdz8m+HHJfcqNBN+ycBs9zckvOXz1BmGNBN+SbZ76FDh2bqs5D9SvV3Xfd46TWQemrBzHwv5BjkBocEv9LjRCrdyzHKeHTppSDHlXy2Bh3p9SBj2XU3gwzp06eP6q0gNyzlekk2X24QSF0J2S69PuQmxvOQf6fkd81QbQAiomxDQ0REL0VAQICk9DL92L17t/q5v//+Wz2vXLmyJikpKc3+5HWdvn37anLnzp3mvVesWJFin+L8+fOa5s2ba+zt7TWFChXSfPDBBxpfX99M7zO912UfZmZmGh8fnxTbGzVqpB46cjypj0vs2bNH/fyUKVPUcznvcePGadzc3DQ2NjaaKlWqaDZs2KDeW7ZlRNpI2+RiYmI0Xl5emho1amgSEhL02//44w+13crKSuPk5KQZOHCgJiwsLM15lCtXLs37TJw4UZ2PXJvk753Zay1CQkI0n3zyicbV1VUdg7Ozs6ZZs2aaWbNmpfnc5LqmJtci9bka+/wNXUd/f39Ny5YtNXZ2dur8v/32W01iYmKKtnPmzNF4enqqayGflXxfpF3qPysy8z3XfVby/vJ8yJAhKfah+/4b+kxXr16d5hwy833QWblypTrXAgUKaCwtLTUuLi6aHj16qO9favL+8jtSvHhxdV3kd6Zjx46a/fv3G/wsM3POxug+S90jV65cmrJly2p+++23FP8GiGXLlqnfB7kWch69evXS3Lp1K8Nz132uuoe1tbXGw8ND880336jfjef5Xgj5nlarVk0dc548eTQVKlTQDB8+XHP79m19G7lG7dq1M3pshl6Pi4vT/Pzzz+r3Ts41f/786n2+++47TXh4uL6dnIv8/qQm+0v+3dD9+ynHGRQUlOb9jf0OERG9Cmbyn1d944CIyBRIlkwqnUumKL0CaJltRzmDZBezw7WW4Q6SUX6engvPQ/c9l14TunHRlP287O8FERGlxTHtRERERERERNkUg3YiopdE5mfu1auX0fnVn7Ud5QwytVlmpyvLSWQcu5z7sxSRIyIiMkXsHk9ERETsBk0GsXs8EdGrx6CdiIiIiIiIKJti93giIiIiIiKibIpBOxEREREREVE2ZfmqDyA7SEpKwu3bt5EnTx419Q4RERERERHRiySzrz969AhFihSBubnxfDqDdkAF7K6uri/0ghARERERERGlFhgYiGLFisEYBu2AyrDrPqy8efPCFMXHx2Pbtm1o2bIlrKysXvXh0AvG6216eM1NC6+36eE1Ny283qaH1zxnioiIUMljXTxqDIN2KaH/pEu8BOymHLTb2dmp82fQnvPxepseXnPTwuttenjNTQuvt+nhNc/ZMhqizUJ0RERERERERNkUg3YiIiIiIiKibIpBOxEREREREVE2xTHtmZSYmKjGkuRUcm6WlpaIiYlR50rps7CwUJ8XpwgkIiIiIqIXiUF7JkRGRuLWrVtqHr2cSs7N2dlZVdBnIJo5UrjPxcUF1tbWL/jqEBERERGRqWLQngHJOkvALgFa4cKFc2xAm5SUpG5O2Nvbw9ycoyYyusERFxeH0NBQBAQEwNPTk58ZERERERG9EAzaM9FtXII0Cdhz5cqFnEqCdglEbW1tGYBmgnwXZGq8Gzdu6D83IiIiIiKirMaUaibl1Aw7PT/2SCAiIiIioheNQTsRERERERFRNsWgnYiIiIiIiCibYtBORERERERElE0xaM/hDh8+rOYUb9eu3as+FCIiIiIiInpGDNpzuDlz5mDw4MHYt28fbt++/cLeRyrsJyQkvLD9ExERERERmSIG7c8RnEbFRb2Sh7z3s5B515ctW4aBAweqTPu8efPU9rfffhs9evRIM7VdqVKlsGDBAv0UcOPHj0eJEiXU9GaVKlXCypUr9e337NmjKupv3rwZ1apVg42NDQ4cOAB/f3906tQJTk5Oas73GjVqYMeOHSneKzg4WB2P7Ff2v3jxYri7u2Py5Mn6Ng8fPsT777+vptrLmzcvmjZtCl9f32e9XERERERElAMkaZIweNNgDN8+/Jnjotcd52l/Ro/jH8N+vD1ehcivIpHbOnem2y9fvhxeXl4oU6YMevfujc8++wxfffUVevXqhTfffFMF9RJYi61btyI6OhpdunRRzyVg/+effzBz5kx4enqqTL3sQ4LoRo0a6d9jxIgR+OWXX1CyZEnkz58fgYGBaNu2LcaOHasCebkJ0KFDB1y6dAnFixdXP/POO+/g3r17KvCXuc6HDRuGu3fvpjh2OT4J6uWmgIODA/788080a9YMly9fRoECBbLoEyUiIiIiotfBnut78MfxP9R693LdUb1IdZgKBu05vGu8BNqidevWCA8Px969e9GqVSvkzp0bq1evRp8+fdTrS5YsUW3y5MmD2NhYjBs3TmXI69Spo16XoFwy6RI8Jw/av//+e7Ro0UL/XAJqycrr/PDDD+p91q1bh0GDBuHixYtqv8ePH0f16tpftL/++kvdGNCR9zl27JgK5CXwF3JjYM2aNSrbP2DAgBf+2RERERERUfYx++Tsp+s+sxm0k3F2VnYq4/2q3juzJLMtga8EzMLS0lJ1iZdAvnHjxujevTsWLVqkgvaoqCgVVEvwLK5evYrHjx+nCMZFXFwcqlSpkmKbLvDWkez9mDFjsHHjRtUNXsa5Swb/5s2b+uOSY6latar+Zzw8PFSWXke6wct+ChYsmGLfsh/pfk9ERERERKYjPCYc/174V/98sd9iTGkzBbaWtmnanrh9Avtu7MOH1T58pl7K2Rkz7c9IxnG/DhdfgnMJmIsUKaLfJmM/JHP9xx9/qC7ykjGXbPb27dtVV/TmzZurdhIwCwm8ixYtmmK/usy3jmTsk/v888/V/iQzLsG47PeNN95QAX9myfu7uLio7vOp5cuXL9P7ISIiIiKi19/BwIOIS4xDyfwl8Sj2EUIfh+JMyBnULFozTdsxe8Zg45WNuBZ2DX+01Xanf90xaM+BJFiXseSTJk1Cy5YtU7zWuXNn1RX+o48+gqurqypUJ+PGJbCW8eWibNmyKjiX7HjyrvCZcfDgQbz77rv6sfESgF+/fl3/uoyvl+M7deqUKmCny+yHhYXp20gW/s6dOyojLwXqiIiIiIjIdO27sU8tG7k1QnBkMLZc3QKf2z5pgvaTwSdVwG5uZo7Pag1BTsGgPQfasGGDCoL79++virgl161bN5WFl6BdqshLoTkp7rZz5059GxnXLhnzoUOHqiry9evXV+PhJSCXSu59+/Y1+t4yNv3ff/9VxeekV8Lo0aPVPnSkMJ5k9GVc+owZM9SNgv/9738qIy/thbwuY+nlBsOECRNQunRpNV2dZP7lZkDqLvlERERERJRz7b+5Xy0bFG8A/zB/bdAe7PO0wYYNwO7d2G1+FJP3A90Dc8Ol0W2g0dO6Wa8zTvmWA0lQLoFv6oBdF7SfOHECZ86cUV3kz58/r7rA16tXL0U7KSAnAbdUkff29lZF6iRolina0vPrr7+q8el169ZVgbsUvUs+fl1ILwCZEq5hw4YqCP/ggw/UjQJbW+2YFAneN23apF7v16+fCtp79uyJGzduqJ8jIiIiIiLTEB0fjeNBx9V6Q7eGqOpSVZ9VV2bMADp2lEAE//vlIIYcBVxuPwK2bEFOwUx7DrR+/Xqjr9WsWTPFvIa69eTZcF3gPGTIEPUwRIrZGZofUbqz79q1K8W2Tz75JMVzGa8uQbnOrVu31Nh6GQOvI0H877//rh5ERERERGSa9t7Yi/ikeBTNU1SNabc014awfnf9kDDxZ1gOH6FvG2cObKyaG52/XgizZs1e4VFnLQbt9NJJUC9j3StUqKAqzA8fPlwF+5JZJyIiIiIi0ll3aZ1ati/dHmYPHqB4rBXGHrBFl9MxsLz3JGAfORK9qlzDytNLMKj+h+jSSltfK6dg0E4vXXx8PL7++mtcu3ZNZdSlK71MP6crhEdERERERDlfaFQoohOi4ZrXVV/fKrkkTRLWX14P6wRg9KxLQCdHmCUl4evkjb78ErFjRmPDL46IswS6le2GnIZBO710Ms5dHkREREREZJp+OvATRu4aqQLzH5v8iJENR6ZpM3rXaNwKv4UFmy1R1OfpdNAxtpZY7JWAYk06ouX48dhxZRMiYiNQJE8R1C5WGzkNC9ERERERERHRS+3y/tXOr1TALpadW5amzbXb52H54zgcnAP08UkAzGXA+kbg7l1MXf45+ncGljQqIMW4sOrCKvUzXb26qunecpqcd0ZERERERESUbc04MUMtu5frrpZn755VXeX1goJg36IdvtsD1L31ZNs33wBt2wKFC6N4icpq0+X7l9Vym/82tezs1Rk5EYN2IiIiIiIieinCY8Kx89pOtf5d4+9Q3rG8vko8ZEarhQuBatXgeP662h5nawVIJfivvtLvo3TB0vqgPTA8EEGPgmBhZpEju8YLBu1ERERERET0Umy6sklN4eZVyEs9mrg3UdtP+G4G6tUD3nkHCAnBBWdLlPwUOHh+K7BjB2Btrd+HZ0FPtbz3+B42Xtmo1is5V0Ju69w58iqyEB0RERERERG9FIv9FqtlFy/ttGwtYorijblAw5tztQ3s7XFv2EeokvgLNLbWBrPn9tb28CjggasPrmLc/nFqW51idXLsFWSmnYiIiIiIiF446coumXbRt1JftWzw2yo0vJms0Z49WNvJC7FWQK2itZDLKpfBfXUq00m7z4hAtazrWhc5FYN2yrbc3d0xefLkV/Le8+bNQ758+V7JexMRERER5UQLfBeoivGN3RujTKEywL59yLf/uHot2hKImzRRjWffc0M7vVsjt0ZG99XVu6t+3cbCBs1LNkdOxaA9h3r33XfRuXPmqydaWFhgo0yh8BpjoE1ERERE9Grsv7Efqy+shkajMd7m5n7YxQEjb7gBY8cCQ4eq7XNqWcFuFHC1T1v183uv71XbG7kbD9ql23xxh+Jq/Y+2f8AxtyNyKo5ppywVHx8PKysrfqpERERERCbixsMbaLagmSow90mNT1QQnZoE40Hnj+LoX0D50PkpXlvfzhNIOg//B/6wtbRVXd6tzK3SHadubmaOTW9vgn+YPzqU7oCcjJn2ZyV3jqKiXs0jnbtW6WncuDE+/fRTDB8+HAUKFICzszPGjBmTohu66N27t8q4656LtWvXomrVqrC1tUXJkiXx3XffISEhQf+6mZkZZsyYgY4dOyJ37twYO3Ys9uzZo7ZL5r5ixYrqZ2vXrg0/P78Ux7Vq1SqUK1cONjY26j0nTZqU7nn8+uuvqFChgnofV1dXfPzxx4iMjFSvyXv269cP4eHh6r3loTvH2NhYfP755yhatKj62Vq1aqn2qbP0xYsXh52dHbp06YL79+8/12dNRERERGRqxh8YrwJ2Me34NPjdTfl3v7j+8DqGbX6I8qGAxsHh6QsdOsDaq5xalcJyuix7jaI1MqwGX86xHDqW6aj+9s/JGLQ/q8ePVUXDV/KQ935O8+fPVwHr0aNHMWHCBHz//ffYvn27eu34ce04kmnTpiEoKEj/fP/+/XjnnXcwZMgQnD9/Hn/++acKbiUwT06CYwl0z549i/fee0+//YsvvlCBuOyvcOHC6NChg8rECx8fH3Tv3h09e/ZUPyf7GD16tNq/Mebm5vj9999x7tw5dT67du1SNyJE3bp11fj3vHnzIjg4WD0kUBeDBg3C4cOHsXTpUpw5cwZvvvkmWrdujStXrqjX5TPp37+/anf69Gk0adIEP/7443N/1kREREREpiIuMQ7zTmv/hjeDNnj2ue2Tpp3PjSPodFG7brZmDXDzJjByJDB1qqoErwvadePZG7s1fnknkc0xaDcRkvH+9ttv4enpqQLx6tWrY+fOneo1CaiFg4ODysLrnktWfcSIEejbt6/Ksrdo0QI//PCDCt6Te/vtt1WWW9pItlpH3k9+RrLjEmSHhIRg9erV+qx5s2bNVKBeunRpNQZfguaJEycaPYfPPvtMBdSSlW/atKkKrJcvX65es7a2Vscvd9nkHORhb2+Pmzdv4u+//8aKFSvQoEEDlCpVSgXz9evXV9vFlClTVBAvNwDkWKRXQqtWrbL8GhARERER5TTSpT02MVZNwza45mC17fSd0ykbhYbC8cdfUSAGeORgCzRoALi6ApIoc3ND6YKlVbMTwScyNZ7d1HBM+7OyswOedMl+Je/9H4L25FxcXHD37t10f8bX1xcHDx5MkVlPTExETEwMHj9+rLqSC7kBYEidOk/HoEi3/DJlyuDChQvquSw7ddJO06BTr149lS2X95Bu+qnt2LED48ePx8WLFxEREaG66ac+ltQkiy/7k2A8OekyX7BgQf2xSE+B1Me+ZcuWdD8fIiIiIiJTd+n+JbUsU7AMqrhUUeu+Ib5PG0ycCM2oUWgYF6eehjSrjTyp/tZv49EGFmYWOBZ0TD2X9Zw8hduzYtD+rGS8RO70x1ZkR6mLw0lGOikpKd2fkfHikm3v2vXpdAo6Mk5dR7rdv2jXr19H+/btMXDgQHUTQW4CHDhwQHVrj4uLMxq0yznIDQDpjp/6RoBk4omIiIiI6PldvKft8y5TuFV2rqzPtGtCQ2E2YQLwyy+q0/zV/EB4bnOUHZ22Z62TvRNaebTSz+Fev3h9lbknLQbtpA/qJSOdnBSgu3TpEjw8tGNMntWRI0f03eXDwsJw+fJleHt7q+eylCx+cvJcMuKGsuwSdMtNBhkjL2Pbha5rvI50kU99DlWqVFHbpFeBdI83RI5FxrWnPnYiIiIiIsp8pt27kDcszS3hFBiGxKpVYHkrSL22rkcVdPI+hfervIfZlQ330n2/yvsqaHexd8GsDrP4sSfDoJ0UGSe+d+9eNG/eHLly5UL+/PnxzTffqOy2BN5vvPGGCpaly7xUgc9MoTYpdidd0J2cnDBy5EgUKlRIP3f8//73P9SoUUONke/Ro4cqFPfHH39g+vTpBvclNw6kiN3UqVNVQTsJ8GfOnJnmHCSzLmP1K1WqpLLvchOgV69eahy/BPwSxIeGhqo2MmSgXbt2agy7dM3/5ZdfVJf9rVu3sms8EREREVEmXLqnDdq9CnnBJvA2VmyyR7tjD2GZFCR/xAM//4zBNz4DIoA3y71pdD+dvTpj49sbVba+SJ4i/OyzYyG6n376SXXZlmJj4sGDBxg8eLAaBy1BpASOElzJlF7JSaExCbwkQHN0dFQVy5NPSUaZIwXgZBo0Nzc3FdgKKca2YcMGbNu2TQXYMm3bb7/9ptpk9ppK5flq1arhzp07WL9+vcqG67L4kimXiu7ly5dXNwgkyJeCdIZIEC7F637++WfVftGiRWp8e3JSQf6jjz5SNwGkmJ5UyRdScE6CdrlRIN8nuXEgFe11vQDkvGbPnq0K0sn7yPmOGjWKXx0iIiIiMklRcVEYt38cfjrwEwLDA422k7nXdd3jy8c4ALVqofORh7BKAgJqlZautLjetCpuRgSqDHw913pG9yWxYFvPtgzYs2umXQIoqUievFja7du31UOyn2XLlsWNGzdUQCbbVq5cqdpIt2cJ2KVS+KFDh9Q0XxKcSVfvcePGwZQlnzot9ZzkYo1Ms5CMZK8bNWqkpkzTdT/XBe7pVVKXX1RjpEJ76rnZk+vWrZt6pDeOPbmhQ4eqR3J9+vRJ8VzmjJdHcvJ9kLH58jBGpqpLPl2dkCCfiIiIiMjUSMA+7oA2njpy6wjW9EwZO+jI2PWw6DDsnQeUHdNabQsp4YiOze6ibPu6+NvREXtPz1fbqxepnuG865RNM+3SnVm6L0umU7pk60g2ddWqVSqYlGm6ZIovKUAm2VpdJl0yojJ/+D///IPKlSujTZs2qru1zDcuxcmIiIiIiIgo8x7HP8ZMn6fDUE8GnzTa9rcjv6FiCNDwxpMN+fPj5LRROFYMOB96Xm3ad2OfWjZy4xRur22m/ZNPPlHZchlLndE4aekaL5lgS0vtYcs4aJkDXMZM60hWWCqMnzt3Tt/NOzWZ7kseOjJ9mJAx0/JITp5LNlmKoGVUbf11psuY6871v9D9fE7/zOTc5POS74ih4nnZme57nvr7TjkXr7lp4fU2PbzmpoXX2/S8zGu+5MwSPIh+gPy2+REWE4bAiEDcj7yPvDZ5nzbSaBD0KAhL/Jbgf1eebKpcGQnbt6No/G3gmDZol0TqwUBt8ek6Revwb89UMns9X2nQLuOZT548qbrHZ+TevXsqiz5gwAD9NhknnTxgF7rn8poxMhbaUFdpydynnjpMbhBI93vpEWAK2ftHjx79533IeHWpFp/8hkhOJN+H6Oho7Nu377Wto7B9+/ZXfQj0kvGamxZeb9PDa25aeL1Nz8u45vOva7uzt3RoiW0J2xCWEIa56+aidO7Sanv+ixdRdfJkRDgkAt0T0O+8jaRFcbZmTQQcPIgETQIszSwRGReJ6f9O11eXjzgfgU2XtVO6kdbjx4+RrYP2wMBAVaRMvnjJ5/w2RAI/ycbL2PYxY8b85/f+6quvMGzYsBT7d3V1RcuWLVUmP7mYmBh1rDKnd0bH+TqTjLEE7Hny5FFFIChj8t2QIokNGzZ87b4bcldPfvdatGihxvxTzsdrblp4vU0Pr7lp4fU2PS/jmickJWDNpTU4df6Uev5+8/dx7+A97Ly+E4WK26H9Xj+ZYxnm334Ls9hYVLwDxP8gLbU9mL2HDYN3yZLa9WBvnL17FqdtTqvnHvk90LNjzxdy3K+zzCY4X1nQLvNuy9zZkpXVkcJykrWUqb+k+7p0OZZAsnXr1iqYXL16dYovqWTAjx07lmK/ISEh+teMsbGxUY/UZN+pfwnkmCSIlUfyAm05ja4be04/z6yk+14Y+t68Ll7nY6fnw2tuWni9TQ+vuWnh9TY9z3PN/zr5F3459AtiE2PxYbUP8UXdL2BhnnZo59TDU/G/bdpCzKrSu1s9lLtSDqfO70TrPmNgcf2ewf1r7Oxg9uGHsCpTRr+ttUdrFbTPP6PN2td2rc2/OQ3I7LV8ZdFZs2bNcPbsWZw+fVr/qF69uipKJ+sSsMudB8l+yzRh69atS5PNrFOnjtqHBP86cgdKsuWSlc8KurHKptA1np6vOwuDXiIiIiLKjuIT4zF061DVRf36w+v4audX2Bmw02DbmSeeFp9ztndGLqtcqGzrjonbAJdkAXti3jwoOgyY0NACDwa+C7ObN4Fff02xr45lOqZ4XqtorSw/N1PyyjLtkjmXCvHJ5c6dGwULFlTbdQG7BEZSHV6e67oPyBzcEkzL6xKcy7RfMie3jGOX+bWluJ2hTPrzkDHtMs49NDRUBWc5NQstmXa5MSFdvnPqOWblUAL5XsrNonz58r12ReiIiIiIyDT4BPuoseWidMHSuHz/spqmrWWplina3Qy/iZhrVzBjPzCzOjC4wxhg7170a/p0SLFm926YRURgZfxp3Pb7Ftv6N8bwd/42+L51itWBtYU14hK1ic8uXl1e6HnmdK+8erwxUqDu6NGjat3DwyPFawEBAXB3d1fB0oYNG1S1eMm6S9Dft29ffP/991l2HNL92cXFRb2nzBWfkwNRKaomY7Q5pj1zJGBPbxgGEREREdGrtCtglz5orupSFaN3j8a50HNp2m3wXYnVy4BqwcCAfM1gXrU/0KSJ/vX5lYBGld3hns8d29auzTB7Lt3vJ7eajOXnl2Na22komrfoCzk/U5GtgvY9e/bo1xs3bqyfhiw9bm5u2LTpxVYhlO75np6eObqLvBS3kHoCUlSN3b0zJp8RM+xERERElJ3tvr5bLZu4N0GxvMXUut9dvzTtSvz4hwrYhfnOnYCnJ3D1qnQ7xltfl8YynMfSoGMqaD8apE2s1iqWfpf3gTUGqgflsKA9O5Mu469bhfBnIQGoTFsm58ignYiIiIgo+45Tn3hoogrE67jWMdouPCYcB24eUOtNSzRV3dXFhdALSExKhIWZORAcjKS9e9Bme4B6LSFPblg+itIG7KJfP+SvaQnNifM4HnRcFZiT+dcFx6m/PBy8TERERERE9JqY5TMLI3eNRN25dREVF2W03aoLqxCTEAPvQt4oW7gsSuYvCVtLW0QnRCPgYQDw0UdA0aIwf7uXaj+hkSXMhn+p/eGKFaXCNzBtGmoWrak2Hb51WAXuGmjg5uAGJ3unl3PCxKCdiIiIiIjodSDDh2f6PK3yPv34dKNt/znzj1qOiq8DsxkzYPE4Gj0fFoNXKPBg0Rxg1ix92z1uwM53G8Lii+HAunXAwYNA8+YyJhQN3RqqNkduHcE2/21qvXax2i/wLCk1do8nIiIiIiJ6DZwOOZ1iTPrsk7PxRb0v0rR7EP0Ae2/sRZNrwFuLFwAJc4FPPsHTWu8/aRcdOmBRgSAMdjqJIe4NAZmBq0OHFPuSDH2ZgmXUtHETDk1Q29g1/uVi93giIiIiIqLXwJ4be/RTqomrD67icfzjNO22+29H6btJWL3CHGYJCYZ3JsH5ypX4oXoUwuyg7wZvSFvPtimeZ1SEjrIWg3YiIiIiIqLXwPHbx9WyY5mOcMztqMaX6wrDJbf9/HqsXgo4RCcBtWrJPNZq+4nPuqPsx8BPH3irgD1CE6PmbhfVilQz+r4dSqfMvldxrpLFZ0bpYdBORERERET0GvAJ9lHLGkVqoLxj+bRTuD16hKTwh/CetRpe94FYx4LA+vXA5s3AuHGIH/wJLjgC070jZV5rnAo+pQL/4g7F1U0AYxq7N8aE5hPgYu+C96u8j1xWuV78yZIex7QTERERERG9IoHhgTh95zTal24PsycZcUPCE8K1Vd8BVC9SHeULl8eugF04d+cs8NdfwLFjwPLlMA8Px/+e/IzF1D+AwoWBVq3UwyMqVPueEYGIjo/Gidsn9PtLjxyXjJ03NH6eXjwG7URERERERK/IO2vewZ7rezC97XQMrDHQaLvTj06rpVchLzjYOqhMu2Ui0G7MYuDonTTt13UojY5v9kixrZBdITjYOCA8NhzXwq5h+7XtajsLy2Vv7B5PRERERET0CkTERqiAXQzePBjxifEG20mA/Wfgn2q9Y+mOQFIS6l6NxdolQGNdwF6yJNCrF0b2d0eXHkDY91/rx7Inz5h7FvTUz7u+M2CnWu/s1flFnib9RwzaiYiIiIiIXoG91/fq1xM1iVh3aZ3BdmMPjMXjpMdoVKg6xm6MAby8UK7nYLS9CiSaAQ+WzQP8/XF7xgSMc72Otd5maOPZxuC+qrtou8IP2jQICUkJqORUCaULln5BZ0hZgUE7ERERERHRK6DLdOv4hvimaRMQFoDFfouROxZYeqgoLKf8Dly5AuTJgx0V7dG5J3CkSmHVdtOVTWpZo2gNo4XlpPK8iE2MVcs3y76Z5edFWYtBOxERERER0SsM2nXzrl+8dzFNm9WH/8bfqxIROR5wXrxWu/GHH4CbNzHv207YUAaqCrzYeGWjWrbzbGf0PZuWaJri+YfVP8y6E6IXgkE7ERERERHRS3Yn8o5+uraB1bUF6C7cu5CykUaD2mNmo8+ZZNs++AAYNQrIlw9VXaqqTSfvnFTj4bf7b88waLextEHvir3V+o9NflTF6Sh7Y/V4IiIiIiKil0ymaxOVnSujfvH6av3y/ctITEqEhbmFmnNdM2wY6h6/g3hzYOVXA/DGJ2Ng5eys30cV5ypqKVO3Sdf6qPgo5LfNjyou2u3GTG0zFb0q9EKrUq1e6DlS1mDQTkRERERE9JLtuLZDLZuVaIbiDsVha2mLxJgY3J/yExyPnwOWLIGu9vvXrSxQq1oLoFChFBXhZey6lbkVbobfxALfBWpb7WK1YW6WfofqfLb50Nqj9Qs8O8pKDNqJiIiIiIheoslHJuPv03+r9RYlW8DCzBz1LEvik5Xn4XhxlL5dfC4btHozFlH1q6G+uVWa/dhb26OBWwOVtZ96bKo+aKechUE7ERERERFRFjkfeh5OuZ1Q0K6gwdcj4yIxevdotf5htQ/R0qI0UKMGdvicV9sSrCxg2b4jEByMWe2dsDthLQYVqQkkGH6/Nh5t9F3tkxe1o5yDheiIiIiIiIiywLm751BxRkVU+bMK7kbdNdhm5fmVKnD3KOCBGc0nw6xdO8DHR//67H6VgH//BQ4fxnzH22pbraK1jL5nW8+2+nULMwvULFqT1zKHYdBORERERESUBWRceaImEYERgei3tp/BNouPz8Xvm4CDvz2CWb16wIULgJMTjuxcANehwISyD1S7mIQYnL5zWq2nF4iXLVwW09tOR99KfTG301w42DrwWuYw7B5PRERERET0HyVpkrD03FL98y1Xt6jAWwrM6cQlxGLoLwfR5rI8CwECQrQvTJkC77qtcWs/gIfXcf/xfVVJPj4pHo65HeHu4I4LSDUdXDIDawxUD8qZmGknIiIiIiL6j/bf2K+quOexzqMCdQniJfDWmzEDieXLoc3lJPVU4+QEeHkBS5cCPXqoDLl0mRcng0/iyK0j+sJyZskqxpPpYdBORERERERkgMx/3n9tf9yJvJPh5zP9xHS1fKv8W6jmUk1flE45fRr4+GPkuuSvnq5u4QqzO3e0XeN79NDvo3qR6mp5NOgojgQdyXA8O5kGBu1ERERERESpJCQloMHfDTD39FwM2TIk3c9Hgvp/L/yr1j+u8bEaZ64rTIfYWODzz/VtrzsAF/p3MrifBsUbqOWe63tw9NZRtc4p3IhBOxERERERUSr/nPlHjUkXy88tR2hUqNHPaNX5VSrIl6x4JedK+qDdecUmoEIFYOdOwMoKXb4vh1JDgDIVGhvcT2N37fadATtxI/wGzGCmz76T6WLQTkRERERElMqis4tSPF94ZqHRz2j95fVq2dW7q1qWK1wOra4An8w8CVy5AhQsiIfLF2Cd5gKSzIFaxQx3efcu5K3meNcp51gOeW3y8tqYOAbtREREREREyUgRuWNBx/Rj1IWuMFxqEbER2H19t1rvULoDEBWFBh/8iC1PYv6Ed98Brl3DctcItd8aRWqgWN5iBvclBed02XbB8ewkOOUbERERERFRMlL1XYLxXJa58E6ld7DEbwl8gn3SfEbxifF4c8WbiEuMQ7Mkd3jZuwPjx8N29z71+rV8wN0v+6B23rxYeX6l2tbNu1u6n/VX9b/Co7hHap9DaqU/lp5MA4N2IiIiIiLK8cJjwlVBOel+/nOLn9Ntq8uyVytSDTWL1lTr18KuISw6DPlz5de3271kHOr8tQ19wy3wlu8NmH1vp39tWWdPDPC6gu8fnkP1pMbYd0MbyHfyMlyETkfGxG98e+N/OlfKWRi0ExERERFRjpaYlIjmC5urKdzE2xXeVsGxMbrK7TWL1ESBXAVQIl8JBDwMwKmgE2jq0QLQaICxY9Fy9Bi01L5Dyh20bo1LQ2ojYu8YnAg+oTL3sYmxsLe2R+mCpV/kqVIOxDHtRERERESUo124d0EfsIs5p+YYbavRaLDFf4tar+NaRy2rOlfB6D1AI6/WQJUqgKcnMHq0eu2UM5BkZQkULgy4ugJduwIrV6LGkwz98aDjOBtyVq2XdywPczOGYPRsmGknIiIiIqIc7eqDq2kqwU9qOQlWFlZp2h6+dVh1hc9tlRttPNoACQkYufAGquyRV5OA06dVu8RcNviiQSyWtnTBrY8uA7a5AHNzqSanXtdN1Xbp/iXsvbFXrVdwrPDiT5ZyHN7mISIiIiIikwjau5frDjsrOzyMeai6u6cmxedG79Zm0Ht4dkbuPQdVV/cqG32QaAb82dYJ+OsvYP16/LxyKH6rCzQv2Rzmue0BCwt9wC4K5y6MMgXLqPUZJ2aoJYN2eh4M2omIiIiIyCSC9tIFSsOjgIdav3L/Spp2w9YMxL3Du+DxyBpTxxwHWrUCdu5EUi5bdOkBfFonDPEyhVv79jj0UNvlXaZwM6aRW6MUzys6VcziMyNTwKCdiIiIiIhyNP8wf7WUgN2zgKdav/IgWdB+5w40O3firTEr4TsTuDIpDnbnLwOWlkDjxipw313RXk3DJkXlZNy7box8jaLpBO3uT4N2K3OrdIvfERnDMe1ERERERGQSmfbkQbt+nHtwMFC1Kszu3EGz5D9UsaLqBo/ixVWms8L5Cmq8+9m7Z5HXJi9CokJgYWaBSk6VMpVp/67xd8hnm+8FnSHlZAzaiYiIiIgox4pNiMXN8JtPg/aCyTLtcXHAG2+oTLvOCc/cqD50ItC7N5Anj367jEeXoP1MyBlYW1jrq8Hnsspl9L2L5i2KH5v8iLCYMAyvN/wFniXlZAzaiYiIiIgox5IgO0mThF6XbOG4/yQ8yiYb0/7ZZ8ChQ4CDA07WKIbYi+ew6quOqN5vYJr9VHaurJYng0+qGwGiVtFaGb7/yIYjs/ycyLQwaCciIiIiohzrr5N/weM+8M+SGGBJWzSUbLoLsMUzANg3Q1vxfdEi/O/eL9hzHZhVsYnB/ejGrstY9gfRD9R6A7cGL/VcyDSxEB0REREREb12/B/4Y8D6Afqu74Y8in2ERWcXod3llNurBQMj9z158t13CGpQGftuaDc0LdHU4L6ke7wUk7sffR/Hbx9X2xq6yS0AoheLQTsREREREb12mi9sjtknZ6vA3ZgDNw8gKj4K3a7baje4uwODByPM3hKPrIHzH3UDRo7EP2f+UV3oGxRvgFIFShncl42lTYop24o7FFcPoheNQTsREREREb1WLt67iOsPr6v1rf5bkZiUaDRo73EWaHApRrthyxbg998x4u9eKDQcWN6jPGBujuXnl6uX+1bqm+77VnOppl9vVapV1p0QUToYtBMRERER0Wtl7qm5KZ4fCzpmsF3IgS1YuurJkzp1gNKl1WqZohURZwmcCz2n5l4/G3JWbW9WMsWkb2l09uoMczNzdCrTCT83/zlLzoUoIyxER0RERERErxXd+HOd9ZfXo45rnacbNBrEr16FtxaeVk9jqlSA7ebN2qJzAMoWLquW50PPq6x9fFI8HGwc4Obglu77tvFsg8ivItOd5o0oqzHTTkRERERErw2Zbu3UnVNqfVSDUWq5/+b+lI1++w1W3d5EM/8k9dRm3AQ1rZtOucLl1PLy/cs4HqQtKlfJuRLMngT16WHATi8bg3YiIiIiInrlwmPCcf/x/QzbyTzp0qW9sF1h9K7YW22TwFu2Kbt2QTNihL59mLMDzFq0SLGPYnmLIZ9tPiQkJWCe7zy1rZJTpaw9IaIswqCdiIiIiIheqduPbqPs9LLwnOqpLzBnzOFbh9VSusOXLlgaBXMVRGxirArmcfQo0K4dzOLjsdIb6PJBHljs3gtYWKTYh2TUm5Vopi9WJxi0U3bFoJ2IiIiIiF4ZjUaD3v/2VoF7WEwY3lv7ntpmjC7Irl20tgq+67rWVc9P+m0HevQAYmJwtXYZ9OoG5GrVHnm9DGfQ23m2S/G8RtEaWXpeRFmFQTsREREREb0yN8NvYvf13frnsi5V3Q2R7uy7AnalqPTeyrw05v8LvNf5O+DGDaBUKXz/kZeqDl/VpWq6ReWST9+WfA52ouwk2wTtP/30k7pT9tlnn+m3xcTE4JNPPkHBggVhb2+Pbt26ISQkJMXP3bx5E+3atYOdnR0cHR3xxRdfICEh4RWcARERERERPStdd3eZA71OMW0F+HN3DQftJ26fQHhsOPLb5kc1s6LA5MkY0H863jkD2MYmAvnzA+vW4WC4dgq39IJ2Z3tn9CzfE+753DG7w2xeOMq2ssWUb8ePH8eff/6JihVT3t0aOnQoNm7ciBUrVsDBwQGDBg1C165dcfDgQfV6YmKiCtidnZ1x6NAhBAcH45133oGVlRXGjRv3is6GiIiIiIgy68itI2opAXt0QrQK4mUqNkMW+i5Uy5F3SsOiYiXg/n1YPXltcRVLvDVnJx6WcMG1sGsZBu1iSbclqit+ZqrGE5lspj0yMhK9evXC7NmzkV/ujD0RHh6OOXPm4Ndff0XTpk1RrVo1/P333yo4P3JE+4u9bds2nD9/Hv/88w8qV66MNm3a4IcffsC0adMQF/ekeiQREREREb1UiUmJWOa3DA+iH2TYNnlhOf386ffSBu1zj8/G8r3T8c0e4H+Tj6qAHcWKIalFczTob4ZenRIQ7OGknw6uZP6SqkJ8RhiwU3b3yjPt0v1dsuXNmzfHjz/+qN/u4+OD+Ph4tV3Hy8sLxYsXx+HDh1G7dm21rFChApycnPRtWrVqhYEDB+LcuXOoUqWKwfeMjY1VD52IiAi1lPeThynSnbepnr+p4fU2PbzmpoXX2/TwmpuW1+F6z/SZiU+3foq3yr2F+Z3mG20XkxCDU8HaILu6c3VceXBF3z1enZ8Mew0Lg/m//6LzV5/hvcinP5v45ZdIGj0asLZG8AxvIMwf50POwyfYR71e2alytv6Mcto1p2eX2ev5SoP2pUuX4uTJk6p7fGp37tyBtbU18uVLeXdMAnR5TdcmecCue133mjHjx4/Hd999l2a7ZO5lbLwp2759+6s+BHqJeL1ND6+5aeH1Nj285qYlO1/vhde03djXXVyH9ZbrYWGWcso1nctRlxGfFI+8Fnlx/uB53Iu/p91+7zLWrv0XDcZPgNPJk2pbgWQ/d6NZM5yuUwfYsUM9z5eojRn+3fsv/CL91LpduB02bdqEnCQ7X3N6do8fP87eQXtgYCCGDBmivni2trYv9b2/+uorDBs2LEWm3dXVFS1btkTevHlhqnd55Fq0aNFC1QSgnI3X2/TwmpsWXm/Tw2tuWrL79Zau8X1/66vWoxKjULhSYdQuVttg21snbwFXgNputVXvW7OZMxG31QrX7OPRbvk3yHX+sr7tN42BK10aYqHbMBRp2RJFLJ+GMrt37IbPMR9YF7HGnava5F3PRj3RsmRL5ATZ/ZrT89H1+M62Qbt0f7979y6qVn1aHEIKy+3btw9//PEHtm7dqsalP3z4MEW2XarHS+E5Ictjx46l2K+uuryujSE2NjbqkZr8Apj6LwE/A9PC6216eM1NC6+36eE1Ny3Z9XqfDT6rKrzr7Li+Aw1KNDDY1veur1q2QClYjRkDjBuHj/WvPgnYp05Fz5h/sCzqKGbWfRuW1Tul2U8FpwpquefGHn0X+5rFambLzycnXnN6Ppm9lq+sEF2zZs1w9uxZnD59Wv+oXr26KkqnW5eT2Llzp/5nLl26pKZ4qyNdYaRYRZ06ah8S/OvIHSjJlpctqy1iQUREREREL882/21qaW1hrZZb/bcabXsy+CSGHAaG9ftTBew6EdbA3r6NgKNHkfjxQGyM104BV694PYP7aVqiqVr6hmhvArjmdUXh3IWz8KyIXp1XFrTnyZMH5cuXT/HInTu3mpNd1mWKt/79+6tu7Lt371aZ+X79+qlAXYrQCenOLsF5nz594Ovrq7Lzo0aNUsXtDGXSiYiIiIjoxZHp0xadXaTWR9QboZbHgo7h/uP7adr+evhXRPqdxOStgHliknSHBerXx5RtP6DwcGB6eyegZk1cun8JkXGRyG2VG96FvA2+b4n8JeBZwFP/vKFbwxd2jkQmN+Vben777Te0b98e3bp1Q8OGDVWX93///Vf/uoWFBTZs2KCWEsz37t1bzdP+/fffv9LjJiIiIiIyRZLp9rvrBxsLG3xW+zOUdywPDTTYcU1bME6JikJ4l7ao9tb/cGaaRm3StGwJREcD+/fD070q4iyhn6v9xO0T+jnXLcwNF7QTNYvW1K+PqK+9YUCUE7zyKd+S27NnT4rnUqBO5lyXhzFubm45riokEREREdHraPrx6WrZoUwH5M+VH61KtcL5O37wXz8fuO8sqXjJzMFh3WY0SvZzZr17y4Tpal03V/ule5eQkJSA40HamaaqF6me7nsPqjkIS/yWYEDVAepmAVFOka2CdiIiIiIiyn6ke/u9x/dQplAZo22uhV3D36f/Vuuf1fpMLdtaeOGjqYBH2GYA8tBKMgOWlAd6XLWBpZ090Lmz/rXiDsVVV/io+ChcfXAV+2/uT5NJN0Qq1Id9GQZ7a/v/fL5E2Um27h5PRERERESv1uP4x6g9pzbKzyiPc3e1BeEMme0zW2XGW5ZqiXpFawMrVqD+p7/AIwwItwE0pT0BT09EtGqM1r2AAT3tEHf5AuDnJwWv9PsxNzPXV4Nfd2md6nJvBjM0L9k8w2PNa5NX/TxRTsJvNBERERERGfX93u9VxlsC8vm+842223R1E9zCgHfL9gImTQK6d4f1+Usqq16nP3DxwFrg8mWsHN8H2z20mXO7YiVkruY0+6pVtJZafrf3O7WUtoXsCvEqkUli0E5EREREREarwf/p86f++bJzy5CkSUrT7lbELdRbfwbXpwDdu4wCvvxS/9ryJo644AicC9Vm6XVj1GsUqZFuV3ddll+08WjDK0Qmi0E7EREREREZ5B/mj4cxD9W6raUtbobfxNFbR9O023NkGcbv1K5b3AzUruTKBdy7h62DtQG3rmv98dsZF5bTZdp1upXtxitEJotBOxERERERGeRz20efFW9fur1a3xnwJDoXMk3bqlWoN+B7OMQCoe6Fgfff1742ahRQsCDKPankfv7eecQmxOJMyBn9Po1xz+euX2/k1ojV4MmkMWgnIiIiIiKDfIK1QXs1l2po6t5Ure8K2PW0wUcfAW+8gRI3InA/FxA6ZyowezYQHg58/bVqopt+7fSd0zh15xTik+LV+PTkgXlqZmZm+LXlr6hfvD4WdV3Eq0MmjUE7EREREREZpA/ai1RDkxJN1PqhwEOIm/sXYG8PLFigtm0rCbzxcUF4NXlT+4N58+r3oesGf/n+Zay5uEatNyjeQAXm6RlaZyj299uPonmL8uqQSWPQTkRERERkQkIiQ9D6n9aYd3peuu3uRt3Vj1+XTHuZgmXgktsZ7x6JhdX7A4CoKPXa0Vbl0eodoESDjganW5Oseqn8pdT6L4d+UcuGbg1fwJkR5UyWr/oAiIiIiIjo5Zl8ZDK2+m9VD+mi3ti9scF2w7cPR1R8FKq6VEUl50oqMz5ney602SavagBvb6BnT3yedxUQDrQo2cLoe9YqVksVtUvUJKrnDNqJMo+ZdiIiIiIiE5rCTaZt0xm2dZjBdhdCL2CBr7br+8L878O8azfAwQFttgVAJnxb2bsa4OeHB18MwsHws6qdseA/dTX4vDZ5UcmpUhaeFVHOxkw7EREREdFrLCouSs2TXqZQmQzbHgw8iICHAfrnUhgu+FEwXPK4pGg3dv9YFIrU4O3CTVC27/+0VeKfGN8AWN0AeMPcHPtv7IcGGngV8kqzj+Sal2wOK3Mr1X1+UstJsDC3eO7zJTI1DNqJiIiIiF5TCUkJaLagGY4FHcOuvrvSzXZLln3UrlFq/b3K7+HM3TM4cfsEtvlvQ9/KffXtIi76otuoRZh/EbDQ7NZudHMDhg3DvfBgjIn/CRZ3/dR7772xV73c2M34+4qyhcvi3Mfn4GDrAMfcjllz8kQmgkE7EREREdFraurRqTgapC0W99OBn9IN2jdd2aSCbBsLG3zb+FvM9pmtgvYt/lvQ91ZBIDQUuHoVdr/+gi4xqX544UKgQQMU0CTB9qc/EBkXiSv3r+Bk8En1cu1itTM8Vs+Cnv/xbIlME4N2IiIiIqLXkGTOfzvym/65FJa7+uAqPAp4GGz/65Ff1XJQzUEo7lAcTUs0xb6FP8L79FZgzdIUAcIud+D4iD74suwHQGysCtiFdG+v4FgBh28dVgG/zL0uKjtXfsFnS2S6WIiOiIiIiOg1dOn+JQRGBKrMeV3XumrblqtbDLY9E3IGuwJ2qaD701qfqm1V9l3G3nnAN2vC9O00HTtiQJ98aNYXqNbiHW2w3rx5in3pKr//deovhMeGq7Hq3oW9X+CZEpk2Bu1ERERERK+hHQE71LKBWwM0cW+i1n3v+KZpl6RJwiebPlHr3by7qSy7zLHuMHqsvk1sSTe17ercXzC71EPYWtmiQXFtdj211h6t1XLfjX368erWFtYv4AyJSDBoJyIiIiJ6jYP2liVb6qdQ8w1JG7Qv91uG+IMH0OJ2Lsy8XAa4dg3o3RtmgYEILmCNyh8C2xf9ANjZ4citI+pnqrlUg42ljcH3lay+vbW9/rnM4U5ELw7HtBMRERERvWaiE6Ox6/outd7KoxVsLW3Vut9dPyQmJWqnVDtxApg+HU03rUDPEPVTAH4EfvwFiIkBbGww638N4Ru/HecSbqM9oA/a0yssJ1l1ybavPL9SPa/uUv1lnDKRyWLQTkRERET0mjkecRwxCTEoXbC0KgwnXeBzWeZCdEK0KkZXZvcZlU1HXBzSTLAmAbuYPx9wugjs3Y7L9y+rTUeCtEF7raK10n3/aW2noW6xungc/xjvVXnvhZwjEWmxezwRERERUTYRERuBN1e8iV8Payu9G3Pw4UG17O79JswePIBFbBwqFyyH/I+B2LHf6QN2jZUVAvMCH7UHwqMfAn5+QNOmwKxZQI8eKFOojNrP5QeXERUXpR8Tn9EUbjLX+tA6QzGy4Ujkts6dZedPRGkx005ERERElE2M2TNGdTuXh3RBlyJvqUn397OPzsI9DBjxxRrglLag3CF9iyXaRdeuWPVdD7y5qoca8+5g6wCUcwB27tS3LFe4nFrKfOsyj3uiJhFuDm4olrfYiz9ZIsoUZtqJiIiIiLIB/wf++OPYH/rnX+/82mC7s6Fnke/hYxz42wy5T51L83qQc25gxgxgyRJsD9iZYpq21Mo7lkeJfCVUN/dPt2ingmtVqhXMzMyy6KyI6L9i0E5ERERElA2M2z8O8UnxcM3rqp5vvLJRdVlP7eDNg5i3BigaoQG8vYGAACA8HGeXTMHnLYCWg/MBH32EJCtLrLu8Tv1M+9JSZi4tCc57lOuh1u9E3tEXtiOi7INBOxERERHRC6LRaAwG3qndeHgDC84sUOsr3lyhAveEpAQcDTqapu3NgxvR4hqQZG4OrFsHuLsDefOieOe+mFQPOB8fhAfRD3A86LgKxPNY50Fj98ZG3/utCm/p1y3MLNC0RNPnPl8iynoM2omIiIiIXpCx+8fC4ScHbL6yOd126y+vV0G6dGOvVawW6hevr7bvv7E/RbukqEg0/ke77V7L+oCHh/41GbPuns9drZ8JOYMNlzeo9TaebdQ0bcZUdKqobhT0qdhHVYXPZ5vvP5wxEWU1Bu1ERERERC/I6N2jVXG3tovbqqy7Mftu7FPLFiVbqGWD4g3U8sDN/cCmTcCWLcAHHwD586PjmVj1Wp7/jUyzHyk4J04Fn8KeG3vUesuSLTM8zjfKvoEFXRbgw+ofPtd5EtGLw+rxREREREQvwL3H91I8339zv8GCcBLMy2tC97pk2qU6/PBFe4ArO1Nk3K47AHPal8Q3jZqk2ZdM1bb20lpsv7Ydx4KOqW2N3Btl+bkR0cvDTDsRERER0Qtw4OaBFM9XnFthsN350PO48+gO+vhZoNbjAmpb2VO3cGYG0OJKIjQWFvq2U3t5oMRnwN3GzQ3uS9etfvPVzYhLjEORPEVQKn+pLDwrInrZmGknIiIiInoBdOPRC9kVUll3XXf11Fn2IVuGoNcZYMHqRGB1ZaBFC1hs24Y8ScD+4kD0zMloeT8f4h9H4vOQT4EkoHLeygbfs0aRGrCxsEFsorYLvRSg4/RtRK83ZtqJiIiIiDJBMtcX711EeEx4hm0lGN9wRVsI7ttG36ql312/NF3mt51fD8e1O/HP6icbEhO149eTknCgqQeavQMctA0FevfGkVblEJcUD+fcznCxdjH4vjaWNvpidEKKyxHR641BOxERERFRBiJiI1Dq91LwnuaNijMrIiQyJN32viG+uHz/MmwtbdG3Ul+UdyyvtvutmQV4eQEDBgAff4xqzd/B4n+T/WDz5sA77wA7dsBn7CDEW2r3lby7fV3XuulmzwfVHAQzmGFC8wlo7dGa15boNcfu8UREREREGThy6whuRdxS6zfDb6L36t7Y3me70Sz7bJ/Zar2tZ1vkscmjqsGfv+MHjzG/A1dCgEuX1OuFAITZAvHlveH40f+A/v31+6l0XTuWXR+0B2qD9nrF6gEpE/ZpgvZ3K78Le2t7XleiHICZdiIiIiKiDPje8dXPaW5uZo4d13YgKCIoTbuw6DC8ueJNTD8xXT3vXaG3WvZdH4jE74FiErCLNm0QPeQT9HgDcPsM0OzenSJg103fJhnz6w+v4/aj2zh482CKYnPpYcBOlHMwaCciIiIiysDpkNNq2aNcD31X96NBR9O0+256dxRcuAp2SRaY2GIiOu8NASwsUOtP7fh25Ztv1Nzrmz9siuXlAVfXsnCyd0qzr/y58qOKSxW1/vvR3xEeG66C8QqOFXi9iEwIg3YiIiIiMkk3Ht7At7u/RWhUaIZtT9/RBu2VnSujVtFaav3orZRBe7z/FXwzegckPr+5uzI+r/wxzH76SRWVEz/XA6oONEfcqK/U890Bu9WyiXva+dZ1mpfQTu3288Gf1bJOsTqwNOcIVyJTwqCdiIiIiEyOdGOvNqsavt/3PUbvHp1u2+j4aFy6dylt0K7LtD9+DEyeDE29uigQrd1UcL8PULEicOOGeq4JDMSP7exxyikJ/g8D1Lbd1zMRtJdMOR97ZrrGE1HOwqCdiIiIiEzOuP3jcD/6vlr/6+RfiE3QzmtuyKHAQ0jUJKr51l3sXVC7WG21/cTtE0iaNw8oUQIYOhTWIfdwLR/wR79y2h/099cu+/aFWbFi8CrkpZ7KtHF3o+7iXOg59byReyOj7y1Ben7b/CmeE5FpYdBORERERCbnSNAR/boE5BuvbDTadtLhSWr5hvcbaqo1r4R8+HW7ORYujIJ5v37A3buAuztmD6gO70HAw3d7Al9/DVhZAQ4OwODB6ud1QfuFexf0XeOlsJ3cDDAml1UurHtrnQrcC9sV1mf5ich0MGgnIiIiIpOSpEnSV4PXzWO+/vJ6g22lW/zmq5thm2iGCfOCgN69YVGpMoYeTEKXi08ade4MXL6MH7xCEGcJ1HOtB4wdC8TFAWFhQLVqqlk1F+1y3aV1+psELUq2yPB4Jbt+bcg1XPjkAnJb586Sz4CIXh8M2omIiIjIpMgUao/iHsHawhofVvvQYFE5naV+S9Xyp9vlkGfVemDRIuDe00nSY+1zqfHsgY/vIDAiEBZmFqhRtMbTHZiZ6VffKv+WKiInY+EXnlmotnUo3SFTx5zPNh8K2hV8vhMmotcag3YiIiIiMim6LHu5wuW0WfEnXdYfxjxM0U6j0eDf00vw9T5gyBy/py/Y2WHcnHeR/0tg/Kx3ADc3Ne5dVHKuZHSOdJnWrWOZjvrnDjYOqFdc+/5ERMYwaCciIiIik+Ib4qsPsAvnLoxS+Uup58eCjj1tFBeH4B++xPyfLmHsrifbZHz6tm2Ary/yV6iJh7mAk7itXtIF7bqbAMZ82+hbFMylzZh39e7K6duIKEOc5JGIiIiIXns7r+3EyF0jVaG4Ge1mqKnZDImIjcB83/lqvapzVbWUavD+Yf6qi3xLv2jggw+A0FAUAdQj3tIcVm/3BqToXOPG6mc8/LXTtl19cFUtDwYeVMu6rnXTPU4pPCfj0+V4U0/nRkRkCIN2IiIiInrt51zvsKQDohO0k6Q3ntcY/p/6GxwDPmbPGDWm3TtXcfS/nh9IOow6DuWR/yjQb9YE4Hakvu1jazNMqalBhS9+RvuOn6fYj2dBT7WUYP/e43s4GXxSPW9QvEGGx5vXJi+6eHf5z+dNRKbhuYP2u3fvqkdSUlKK7RUrVsyK4yIiIiIiypTd13frA/YCuQrgQfQD7LuxL01gLFl2mZNdbD3uBbsv+6j1T/QtngTsnTsjqKonWgdPxNWitrjbSlusLjnXvK5q7HpkXCR+PvAzNNDAu5A3iuYtyqtGRK92TLuPjw/Kly8PFxcXFaBXrlwZVapU0S+JiIiIiF6m7f7b1XJwzcHoUa6HWj9w80Cadn+fnIuuRx/hwmwbuK7cluK16w7AwHbA4zuBwOrVWN2qOPycgMbujZHHJk+afVmYW+iLyv1y+JdMT99GRPTCg/b33nsPpUuXxqFDh3Dt2jUEBASkWBIRERERvUzbr23XB80yp7k4EJgqaL97F1U+/h7z1gJeQbHabfXqAbGxwLlzqDuiEGbWAC4khqiXjt8+rpY1i9Q0+r49y/VM8Zxj1IkoWwTtEphPmDABtWrVgru7O9zc3FI8nsWMGTNUtj5v3rzqUadOHWzevFn/+p07d9CnTx84Ozsjd+7cqFq1KlatWpViHw8ePECvXr3Uz+fLlw/9+/dHZOTTsUhERERE9PqR6dfmn56fZhq21ALCAtS4cpn/XLLiuqBdxphHxUVpG4WHI6FxIzQ8HQb9wM4CBYBx4wBra6BsWXi5VFCbz949q5Ynbp9QyxRzrqfSslRLOOZ2VOt1itVBi1LMtBNRNgjamzVrBl9f7TQZ/1WxYsXw008/qS73J06cQNOmTdGpUyecO3dOvf7OO+/g0qVLWLduHc6ePYuuXbuie/fuOHXqlH4fErBL++3bt2PDhg3Yt28fBgwYkCXHR0REREQv383wm6g0sxLeXfsu+q/rn27bHdd26CvASzf24g7FUS3RCf8sS0BSnVrA7NlAtWqwvHARQXmAN7/2kAnYgXv3gIYN9fup4PgkaA85i0exj3Ah9IJ6XqOI8aDdxtIG+97dhx19duDAewdga2mbRZ8AEdF/KET3119/oW/fvvDz81Nj262srFK83rGjdmxPZnTo0CHF87Fjx6rs+5EjR1CuXDnVBV+e16yp7ZY0atQo/PbbbyrIl/HzFy5cwJYtW3D8+HFUr15dtZk6dSratm2LX375BUWKyCQdRERERPQ6mXp0qgrcxb8X/sWdyDtwtndOt2t88xJPpk87cQI7poQhX4Q8OQc8SeaE58uF9j2i0bxRZ207M7MU+5E524VPsI/qGi+F5aTYnJO9U7rHWqZQGfUgIso2Qfvhw4dx8ODBFN3YdWRezMTExOc6EPm5FStWICoqSnWTF3Xr1sWyZcvQrl071fV9+fLliImJQeMn82PKsch2XcAumjdvDnNzcxw9ehRduhieSiM2NlY9dCIi1L/qiI+PVw9TpDtvUz1/U8PrbXp4zU0Lr7fpyWnXfO+NvSmezz81H8NqD0vTLjEpETsDdgIa4O2Dj5C46xuYT5uGfBFxuJcLKKQtKI+kfv3QtNxBnI68jO9cGxj8nKo7a/+ePBZ0DIvPLFbrjdwaZcvPNKddb8oYr3nOlNnf4WcO2gcPHozevXtj9OjRcHJK/85jZki3dwnSJRi3t7fH6tWrUbZsWfWaBOk9evRAwYIFYWlpCTs7O/W6h4eHfsy7o6NjyhOytESBAgXUa8aMHz8e3333XZrt27ZtU+9hymSYAZkOXm/Tw2tuWni9TU9OuObRidHwue2j1rs4dsHqu6ux5NgSeD3wStP26uOranq3H/dawnPPJP32oGKF4NXnHqpalcFYm3cQVKYkTvnNU6+FnQvDpsub0uwrSZOEPBZ58CjhEeacnqO2lYoqhU2b0rbNLnLC9aZnw2ueszx+/PjFBO3379/H0KFDsyRgF2XKlMHp06cRHh6OlStXqq73e/fuVYG73Bh4+PAhduzYgUKFCmHNmjVqTPv+/ftRoYJ23NHz+OqrrzBs2LAUmXZXV1e0bNlSFbQz1bs88o9AixYt0gx5oJyH19v08JqbFl5v05OTrvmOgB1IOpsENwc3DG09FKsXrMYD8wdq+GNqPx/6GQP/AUbuSUixPfyPnxB5+n2ctb2LmkM/x5GgI9D4aVDEvgje7vS20fduENUAm65qg/TCdoXxZfcvVYG77CYnXW/KHF7znEnX4zsjz/yvkBSD2717N0qVKoWsYG1trc+cV6tWTY1PnzJlCoYPH44//vhDjZ2X8e2iUqVKKmCfNm0aZs6cqarK3717N8X+EhISVEV5ec0YGxsb9UhN/tEz9X/4+BmYFl5v08Nrblp4vU1Pdr7mhwMPI+BhAN4q/5YaUmnM/sD9atnArQHKOWv/BgyMCESsJhb21vYp2l48thHzdCM2x4wBWraU6Aal6taChe+HCIsJw92YuzgTekY1qVqkarqfj1Se1wXtw+oMQy6bXMjOsvP1pheD1zxnyezv7zMH7TJHu2SqDxw4oLLdqd/o008/xX+RlJSkxpvrugrI+PTkLCwsVBsh3eolEy+F6STgF7t27VKvy5R0RERERPTqRcZFovWi1oiIjcDOazvxV8e/DAbuGo0Gqy5op/dt69EWBXIVUBnv0MehuHz/Mqq6VJUMDfDDD4gP8Mc/C4+otlFN6iP3N9/oi8tJaqZ0wdK4cO+CqgYv07+JKs5V0j3OvpX7qvH0Xby6YEA1zkZERK9x9XgZey5d2OWRnPzj+yxBuwT/bdq0QfHixfHo0SMsXrwYe/bswdatW+Hl5aUy8B9++KGqBC/j2qV7vG5qN+Ht7Y3WrVvjgw8+UJl36TYyaNAg9OzZk5XjiYiIiLKJpX5LVcAu5p6ei/eqvId6xeulaed3108F5zYWNmhfur3a5lXIC6E3Q3Hx3kVt0C5zq3//PZKnjex++ClNNfgKThW0QfvdszgUeEhtq17kafFiQ4rkKYItvbdkwRkTEb3CoD0gICDL3ly6tstc7MHBwXBwcEDFihVVwC7jc4QU/hgxYoSaGi4yMlIF8fPnz08xpmnRokUqUJf54yUr361bN/z+++9ZdoxERERE9N/M8pmV4rkE0YaC9iV+S9SyZ6HGyPP9T0CtWijv4An/iP1o0HO4TBAMXLyo2hypVBB3Yu6jYK1GaFAv7b4qOlbE8nPLsfnqZly6fwnmZuZo6PZ0XnYiotfFf6qsIV2YRHrjktIzZ462Mqcxnp6eWLVK20XKGKkULxl6IiIiIsp+giKC1LznZjDD53U/x8RDE3H41uE07eIT4zH31FzkfwxM/u0CcHmr2j7Fxgp/xALmCJK9qW2RH/RFnaLz1T6vf7bA4PtKpl3sub5HLWsUqYF8tvle4JkSEb0YKQeMP0OwXb58edja2qqHrEu3eSIiIiKi5Lb5b1PLGkVroGOZjmpdgnZd8geyvHkTG08sRqOjITg/0xz5Lt/UvmZjA6vYeP0frJqePYGDB7Hq4ybqec2iNVHcobjBD7yCY8qZhpqVaMYLQ0SmEbR/8803GDJkiOqyvmLFCvWQdZkGTl4jIiIiItLZ4q8dI96qVCs1Jt3CzAJ3Iu/g5sMbwIkTgAyLdHND59rvYtlKwDkiSSofA76+QHQ0Et7qoX7+eBHg+rSxQN262HV9l9rWtERTox+0Wz63FM87lOnAi0JEptE9fsaMGZg9ezbeeust/baOHTuq8eiDBw/G999/n9XHSERERESvobjEOGz3367WW3u0hp2VHdrCE+YXLsKhYQvA72qK9pFWQMzggSg09lfA1lZts/x7Pn62PI6ZBa5hzM39cM9fArsDdqvXmrhrM+6GyBh2qQK/7tI6/N7md9QuVvuFnisRUbYJ2qVCe/XqaStvypRrMkc6EREREeV80r09o7pG6y+tV3OlO9s7o2aRGsDgwVj3h7aQHPAkYK9cGSs/aYK+Ab+hrFs1HB8wPeVObGzwoM8buH5oAvbf3K/mb5d5263MrQwWs0tu+ZvL8TDmIQrZFfpP50pE9Fp1j+/Tp4/Ktqc2a9Ys9OrVK6uOi4iIiIiyKZ/bPnD8xREdlnRA8KNgo+1mn5ytlu9WeheWCxcBf/wBjRkQagc8ymMD7NsHnDqF2bbn8Nga6Fn+aU/O5CRQ11WdP3JLOzd7FZcqKnOfHktzSwbsRGSa1eOlEN22bdtQu7a2m9HRo0dx8+ZNNX3bsGHD9O1+/fXXrDtSIiIiIsoWRu8ejXuP72HD5Q3ov64/NvXalKbNubvnsNVfWwH+o3zNgc6d1PrZwT1QqcAy1HOtjgMNGiAhKQEHbx5UrzUv2dzg+0nldyFzte8K0I5nr1W01gs7PyKi1zpo9/PzQ9WqVdW6v7+/WhYqVEg95DWd550GjoiIiIiyr7MhZ9Xc5zq7r+9WY9etLaxTtPv54M+ABvjCpgnc+n4KREUBjRoh8YvPgTnL1Nzp4mTwSUTFRyG/bX79NG2pOdk7wTWvq+oWP+fUHH3leCIiU/DMQfvu3drCH0RERERkeqYdn6aWb5R9Q2W9H0Q/wOk7p58G0UlJeLRkPtpM+Ac/XwNcIp/87ejoCCxciNKOBdRTydTff3wfe6/v1XeBl+JxxlQvUl0F7ToM2onIVDzXPO06gYGB6kFEREREOd+j2EdYdHaRWv+kxieo61pXrR8OPAxERGgfzZsjT+/38NYZDVwioa0C/8Ybauw6XF2R2zq3yprrurvvvaEN2hsWb5jue0vQrpPPNh88Cni8wDMlInqNg3apED969Gg4ODjA3d1dPWR91KhRqrI8EREREb1erj+8riq9S0X49Cw/txyRcZEoXbA0Grk1Qp1iddT2gGNbAXd3wMFBumUi2sYCE+oCC3/rB4SFAStWAEWK6Pcj87ULydQfuHlArTdyb5Tue9dzfVopfnjd4elm5YmITLp7vMzF/u+//2LChAmoU0f7D/Xhw4cxZswY3L9/32BleSIiIiLKnqR7e/259RH0KAjzOs1D38p9jbZd7LdYLftV7qfqF8nc5wWjgB6LdgNhMeo1jbk5OrwN7HQDLvQerp9vPbk2Hm2w9tJa/HTwJzyOf4w81nlQ2blyusfZ0K0h/unyDzwLerJrPBGZlGcO2hcvXoylS5eiTZs2+m0VK1aEq6sr3nrrLQbtRERERK+RTzd/qgJ2MWLnCDVWXbqwpyZTu+0O0I5P71m+J3D/Pup9+guCNwFWSdqAHcOG4Uy5QtgZ+LXqAu9VyMvge7bx1P4dKQG7qF+8vpqeLT1yk6BXRU4vTESm55n7FdnY2Kgu8amVKFEC1tYpq4YSERERUfYVEhmCpX5L9c/vRN7BmotrDLad5TMLGmhUdt09b3Ggd2/YbNgMqyTgpDPgP+83YNIkbC6tnUFI2hlT3KE4yjuWT5FFJyKiLAraBw0ahB9++AGxsbH6bbI+duxY9RoRERERvR4Wn12MRE2imgd9cM3BaptPsE+adqFRoZh0eBLMkoBvCr8JDB8ObNmiur4PHFUZ1T4CDlUuqNoeDTqaqXnUf2v1G1qWaqm6ykt3eyIiyqLu8adOncLOnTtRrFgxVKpUSW3z9fVFXFwcmjVrhq5du+rbyth3IiIiIsp+pOjc36f/VuvvVn4XdlZ2av3UnVNp2m5cNAYbZz5C2TBLFHz0v6cvTJ8OM8fjwInTOBd6Tu3zyK0j6qVaxdIP2puXbK4eRESUxUF7vnz50K1btxTbZDw7EREREb16vnd84WTvBGd753TbydzqZ++ehbWFtRqjfiviltp+MvgkkjRJ2urscXHAjh3oMmwWHKLk1QQZXC4RPzBwINCvH8od045Ll6Bd5lGXLvYWZhb6CvFERPSSg/a//9bekSUiIiKi7OVY0DE0XNBQBd321vboXrY75nSaY7DtfN/5atmpTCcUyFVAVXC3sbBBRGwErt++gJJT5gNTpwIxMXCQmwFOQOE/F6JIi66AubkUOlI/rxub7nPbRztfO4BKzpX0mXsiIvpvOMElERERUQ6x4sIKFbALmU9dur/HJDyp7J5MXGIcFp1dpO8aL6wsrFDBqQKqBwGF67UAJk5UAXucgz0m1QHeG1oSRTr1BuzstNO4Scb9STd4uUEQHBmMqcemZmo8OxERZR6DdiIiIqJsau6puSjzRxk0nd8UgeGB6baV8eQbrmxQ6x9JZTjZBg3OhpxN03bTlU1A6D18eyIPWk/bCnz4IeDtjYODTuH4bCDPjWCgSBFg3Tr8b1FffN4KqFPh6XS/ydla2qKdZzu1fjDwoFoyaCciyjoM2omIiIiyqR/3/YjL9y9j9/XdGL5jeLptb8Xegn+YvxqjPrHlRFWZXTdGPbXtm//AyT+BMRsewXzK78CsWcDFi7COS1SvH61cGDh3DujQAQdvHcpwWrZu3inrHWVUhI6IiF7gmHYiIiIievH8H/gj4GGA/rnMp/5F3S+MFng7Hn5cLZuVaKa6q1d1ropt/ttw6tYJYNoRwM9P5ulF4v17+D04GBYaIK54UVi36wgkJQFt2+J8fDBGL/8Ih6pocNvBAY9iI+Ab4qv2W8+1ntFjbV+6PWoWranG1BfJUwSlC5bO8s+DiMhUMWgnIiIiyoYk4BaN3BqpQHiJ3xJMOToF8ztrC8ildizimFp2KN1BLXXBffGV24FFN/TtLJ4sj3vlQY29JwFHR/1rJeKjsfbcJ0iMvYfbj26rivAyRt49nzuK5i1q9FhzWeXCofcOYce1HSjuUFxbeZ6IiLJElv6LumDBAvj7+2flLomIiIhylIcxDxEdH51hu41XNqqldHMfUmuIWl/mtwwPoh+kaSvTtV2KuqTWO5TRBu31Lj5GqyvAR/8+CdjbtQM2bMA7I8rAYzBwbP74FAG7Lvj2Luyt71a//8b+DLPsOhbmFmjl0Ur/80RElA2D9nfffRdly5bF4MGDs3K3RERERDmCBNclppRA5T8r497je0bbydRpErSbwUxNySZdzys7V0ZsYixWnFuRom1QRBDe/rUOLBM0+DCiNIq9/RHQoweKvPEutiwCCkQDjyt6A2vW4HbDKlhoewnXCpqhR/keBt+7mks1tTxy6wh2BuxU603cm2Tp50BERK+oe3xSUhICAgKwefPmrNwtERERUY4w9ehUlWmXx9ur3sa2Ptou8KmN2j1KLftV7odyjuXUemu35jA7eRrn7zypBq/RAIGBCPziLRxeHvLkJy8/eTwVbQls/bY3ulhaYuc1bRBerUg1FLIrZPC9peCczOG+7vI6XAi9oLa1KNUiaz4AIiJ6Zlk+4KhEiRL4+OOPs3q3RERERK+1qLgo/Onzp/759mvbceX+FYMF6HYF7FJZ9jHlBwFbtwKJieg37SBOzgJ6jV4OrF8PFC0KuLmh9nJtdXdDNvSrh4b9gN257qjnusx58xLNjf5MY/fGaul31w+JmkR4FvBU49SJiOjVYJUQIiIiopdApm0Ljw1XRd103c03XNbOq57c/JN/44edwMNfLOHqURVo3VrNmV56w2H1es3ToUDHjkBwMDSWljjjBHzcFjjxRjskSG/HwECgShXg88/x8LOPcKKodny6zOMuheJE85LGg/YS+UrAMffTse4tSjLLTkT0WgTt8fHxGD58ODw8PFCzZk3MnTs3xeshISGwsNDVIyUiIiKi5HYH7NYHwTJOXay/vD5FG83cuXir7wSM2g/kjYx/+sLdu2pxpQAQaf1kW+nS2HpsCSoNBLa0LIGg3h9A06wZUKwYcPIkMHGivoL8qTuncCbkDIIeBcHGwgZ1XesavThmZmZo49FGrcvUccPqDOOFJCJ6Hca0jx07VlWH/1zu2j58iGHDhuHo0aP488+n3bzkDi4RERERpbXnxh61lCy7FJb7bMtn8F61F/EnB8Fqx27g/HmYAdDVXk8q4Q7zcuWBXr2A7dvV31nNHBfBISIOB2PeRt4vRmHrjVmqbTP3ZgY/cq9CXmq6OJm+7etdX6tt9YvXV1Xi0zOu2ThUcqqEXhV7pci6ExFRNg7aFy1ahL/++gvt27fXV4pv06YN+vXrp8+6y51ZIiIiIkopLDoMp4JP6ceMO9s74+dDdhi+/TGAaSnaTqkFXHq/M6a/v/rpxp49VUBvP+0I/O5dwNHe76JFKW9s371dvdy0RFMgIO2nLvOldy7TGdNPTMemK5sy7BqvI4H+0DpDeRmJiF6n7vFBQUEoX768/rl0k9+zZw8OHTqEPn36IDEx8UUdIxEREdFrbf/N/dBAgzIFy8AljwvMJk16ErA/4e0NzJyJ/gOc8VlroGX9vgb341HAQy2vPriqsufnQs+pgnVN3IxPydbVu2uK55kJ2omI6DUM2p2dneHv759iW9GiRbF7924cP35cZd6JiIiITIV0V5cp3CrMqKDmVc/MePYmxRsBAwYAX3yhno9sCnyy4WPVNf5u7y6YW+QOJKVubF50qeQuLt2/pC8qJ9O3FbQraPS9ZQo3meNdl5Gv4lzlOc+YiIiydff4pk2bYvHixWgmBU6SKVKkCHbt2oXGjbXTgxARERGZghknZuDTLZ+q9QmHJmB1j2Td2Q1UjhcDd4YDs5fJmEKcHvwmxuVfjnohvuq140HH9ePQHWwdDO6nbOGyaikZ9vvR9zNV3d3KwgonB5xEQlKCWiciohwatI8ePRoXL140+Jpk3Pfu3Yvt27XjqoiIiIhyulUXVunXN1/ZjIjYCOS1yZum3b3H91Tl9ro3gQrzV2o3zp4Nqw61gRnL4RviiyRNEo4FHVMv1Spay+h7lnMsp59DXR6ZnZJN6g4xYCciyuHd493c3NCqVSujr0vGvW9fw+OviIiIiHJa13iZ+1wnNjEWay6uMdj2j2N/IN9jDVautoKZ1ACSavDvvYcyhcqo6dci4yJxLewajt3WBu1SWd4YXab9TuQd9bCzskt3+jYiIjKhoF1nxYoV6Nq1qypKJw9ZX7nyyV1jIiIioteYZMQP3jyY4TS2N8Jv4GHMQ1iZW2F43eFq24bLG1I2SkrC49nTcfPPCVi9DHAJi5dKvsCMGap7vKW5Jco7aov8Hr11VL1vRpl2yeQXdyieYry6jaXNfzllIiLKKUF7UlISevTooR7nz59X1ePlce7cObWtZ8+enKediIiIXluX7l1Czdk1Uf/v+nhjxRtITDI+M44uyy7d1Tt5dVLrUhguxc9MmQK7AZ9g7tJoNLoBaKysgGXLgDx59E10BeJ+O/IbHsU9gou9C6q4pF8oLo/105/vU7HP858wERHlrKB9ypQp2LFjB9atW6fGtq9Zs0Y9Ll26hNWrV6vx7NKGiIiI6HUjwfbAjQNVN3fx74V/cfy2tjCcIbo516s6V1Xd2SUDHhYTBp9gH22DwEBovvlG3/5GvXIw27ABqFo1xX50Qbvu5zqV6aTmVk9P+9Lt1bKwXWG8Vf6t5zthIiLKeUH733//jYkTJ6J9e+3/KJLr2LEjJkyYgLlz52b18RERERG9cJ9v+1xVeM9lmQuVnCqpbXuu7zHYNjQqFHNOzVHrErBLN/dmJbSz62z33w7ExADdusEsMhKHiwF5frBD/p2HgJYt0+xLF7TrdPHukuGxflH3C4xrOg5nBp5RBeaIiChny3TQfuXKFTRv3tzo6/KatCEiIiLKLqRye0bO3T2HyUcnq/V5nefhvSrvpZimLbVRu0YhODIY3gW90MeiCnD4MBoVrYfS94BK4+cCzs7A8eOIzmuHt7sBzT1bGqwqLyo6VdSvy80CmUc9IzIn+1cNvoKzvXOGbYmIyISC9ly5cuHhw4dGX4+IiICtrW1WHRcRERHRf/LVjq9QeGJhDN+uLRRnzMIzC/Vd07uX644m7k3U8wM3DyA+MT5F2+j4aCzxW6LWN16uCbuqtYC6dTGkwefwmw6033INCA8HzM3xx9B6uJ4fqOyUMpuenATzn9T4RGXqd7yzQ2XtiYiIksv0/xnq1KmDGTNmqIch06ZNU22IiIiIXrUV51bgp4M/qfWJhyaqDHZrj9Zp2sn86IvOLkpR1E2Ky+W3zY9HUWG4cnwLyuYqDkRGAqGh8Lm2F+/sf4T/HbdEiXsLUuzLKgm4lQdwcfWGxZDPsFgzA7iTtgt8an+0/SMLz5yIiEw2aB85ciQaN26M+/fv4/PPP4eXl5eqFn/hwgVMmjQJa9euxe7dhruREREREb1MS88tTfF82vFpBoN2n9s+uBVxS1Vkb1e6ndpm/iAME47kRbsdYXD5oWOK9vWfPIAE7YaSJbUV4adNQ1/NaixwD8eR9/9WFeDPjRukmlRy1o6RJyIieqHd4+vWrYtly5apwFwy6vnz50eBAgVQr149tW3JkiVqnYiIiOhVkqTCvhv71PrkVtqx6kduHTE4Ne2Wq1vg/AiYc6IIbP9ZCjx6BNSogffX3IBLJBBvbakdo+7hgZiKZfEg9UjAUaOA6tWlYi+Cm9UEzICzd8/i4r2LiE+Kh4ONA9wc3F7KeRMRUc70TAOnunTpglatWmHr1q36onOlS5dGy5YtYWdn96KOkYiIiCjTLty7oArQSSX496u+jy93fKmeX31wFZ4FPVO0PX14tRqLXjD6EvBvP2D+fCAgAI8c8+HD+g8R26UNVvVep9qO2PIZZu0/j375GmPap1uAM2e0AfsTFRwrYPu17TgTckY/Nl2y7KzwTkRE/8UzVzuR4FyCdyIiIqKXSYrCaaCBtYV1uu32Xt+rlnVc6yC3dW5UK1INhwIP4fCtwymC9gf3AvHFtFMoGJ3sh/dop3nzH/cFltwaCY+wC/qX1l5ai2hroHXHYYCNjcrIJ1fBqYJaSqY9IUnbfb5mkZpZcOZERGTKMt09fteuXShbtqyqEp9aeHg4ypUrh/3792f18REREREhPCYcNWbXgOtvrmqe9PRs8d+ilo3dGqtlnWLaQrnnfHcAzZpps+POzihQuDhq3wIicpkDe/dKZkJVfceYMXDuoZ327VrYNVUxXpbXH16HlbkVmpTQVpc3Nn3b2ZCzOBp0VD+POxER0UvJtE+ePBkffPAB8uZNO8+og4MDPvzwQ/z6669o0KDBfzogIiIiotT6re0H3xBftT775Gx83eBrgx/So9hH2Hp1q1rv7NVZLas4V4FVAlBrwU5g1+0U7UPtgCXjeuDThg0BX18ZEA94esJJo0GBXAXwIPqBGp9+/PZx1b52sdqwt7Y3+N7ehbxhbmaO+9H31UMwaCciopeWaff19UXr1mmrrurIuHYfH59nenOZPq5ixYrqRoA8pMDd5s2bU7Q5fPgwmjZtity5c6s2DRs2RHT0035sDx48QK9evdRr+fLlQ//+/REp07IQERFRjiDV3VdfXK1/PuPEDH3389Q2XN6A2MRYlC5YGuXtSwL796Nj/wmI+xHouvNJwO7oCM3YsegysADKfwyU7aDNqkuxOQnYhYxDr+Skrfp+6s4p7AzYqdZlPnVjclnlgmeBp93vnXI7obhD8Sz4BIiIyJRlOmgPCQmBlZWV0dctLS0RGpp+d7XUihUrhp9++kkF+ydOnFDBeadOnXDu3Dl9wC43CuSGwLFjx3D8+HEMGjQI5tJ17QkJ2KX99u3bsWHDBuzbtw8DBgx4puMgIiKi7Gvzlc36jHkhu0IqiD9w84DBtro516ecKQqzAgWAhg2R58QZ/euJ1aoAd+7gzHvtsMbpASLz26FBccO9BOX9xMngk9gVsEutNy/ZPN1j1Y1rF/WK12MROiIienlBe9GiReHn52f09TNnzsDFxeWZ3rxDhw5o27YtPD09VRX6sWPHwt7eHkeOHFGvDx06FJ9++ilGjBihxsyXKVMG3bt3h40Uf5HqsBcuYMuWLfjrr79Qq1Yt1K9fH1OnTsXSpUtx+3bK7m9ERESUfUi3c+nyrguG07Pxyka17OrdVR8066Z0Sy74UTD2nd+MiVuB1rN3A3Fx2hd690ajofnwfgfgwsyxkkZXU72JpiWawsZS+3dFajLXupjvO19Vn5du8Rl1dy+Zr6R+/bvG32V4bkRERFk2pl2C69GjR6vMt61tyklKpbv6t99+i/bt2+N5JSYmYsWKFYiKilLd5O/evYujR4+qTLrMEe/v7w8vLy8V2EtwrsvES5f46smmW2nevLnKxMvPGqtyHxsbqx46uuJ68fHx6mGKdOdtqudvani9TQ+vuWl5Ha73t7u+xbzT89TjwecPjI4Tj02IxY5rO9R6yxItkc86H5b6LcW+6/sQX/fJ+UVHw3zBAjxaPgOXTybBOUq7OXHECCSNGKEKzMXNb4g5DkfQ1CoMZeLj9dn7Fu4tjH5O5QuVV8vIOO2wuwauDYAkqPnXjelbsa+qMj+4xmCUyV/mpV2D1+GaU9bh9TY9vOY5U2b/zc500D5q1Cj8+++/KiMuXdQl6y0uXryIadOmqaB75MiRz3ygZ8+eVUF6TEyMyrKvXr1aVanXZdvHjBmDX375BZUrV8aCBQvQrFkzlfGX7PydO3fg6OiY8oQsLVGgQAH1mjHjx4/Hd9+lvfu9bds2k59vXoYZkOng9TY9vOam5WVdb41GgzlBc+AT4YP+xfqjet6nN9MNSdQkYuG5hfrng/4ZhO7O3Q22PRVxClHxUchvmR+3fW4jKSZJbZfu8es2roPbvoMoP3curMLDUfrJzzx0sMPFQUMRIlOyPZnCLdfjXGq56cgmmPmb6bvXWwdaY9PdTUaP09rMGnEabcbeJdoFmzYZbpvcz64/A3eQqbZZjb/jpoXX2/Twmucsjx8/ztqg3cnJCYcOHcLAgQPx1Vdfqf9B6wq1tGrVSgXu0uZZSfB/+vRpNW3cypUr0bdvX+zduxdJSdr/KUtV+n79+qn1KlWqYOfOnZg7d64KvJ+XHP+wYcNSZNpdXV3V2HlD1fFN5S6P/CPQokWLdGsXUM7A6216eM1Ny3+93nGJcZh1chbqudbTj+tOzyK/Rdjgu0Gt/3jtRxzvf1xfxM3YlGzhvuH6535JfpjXdp7Btju27QCuAZ3LdUa7du2QpEnCd5O/Q5sjD9Bq5SjYn7mo2sUWc8bPJe8gwt4SX009gWquHin243vQF7v37oZZYTPk8sqFxLOJKJW/FPp36Z/uubWJboO1l9cir01ejOg8Au753JEd8XfctPB6mx5e85zJ0HTq/yloF25ubuqucVhYGK5evaoCd8l458+f/3mPE9bW1vCQaq0AqlWrporNTZkyRY1jF5J1T87b2xs3b95U687OzqobfXIJCQmqory8ZoyMideNi09O/rAx9YCVn4Fp4fU2PbzmpuV5r/fgrYPxp8+fKqi9MvhKusXU5G+B7/al7L124NYBVC9mPNs+7cQ0tWzn2U6NV7/y4AosLC3UdGnJSYC+8ap2PHuHMh305/LdeWcMWv1A+vtpGw4dihFN4jD55DS8XaE7Cpb0Njo+fe+NvXCy1yYZmrg3yfDzWdVjFW6G34SzvbOqDp/d8XfctPB6mx5e85wls/+PznQhuuQkSK9RowZq1qz5nwJ2QyTDLuPN3d3dUaRIEVy6dCnF65cvX1Y3D4R0q3/48GGKqeZ27dql9iGF6YiIiOjZHL11VAXswj/MH0eDjqbb/sK9C7j+8DpsLGwwtPZQtU3mNTfG764ftvpvVQH6b61+g7WFNaITolVgnNoyv2UIeBgAZ7M8aLvaD3j7baBHDwyaf169friJB3D8ODBpErYF7lbb3vB+w+D7tijVAg42DgiMCMSkw5PUtoZuDTP8PCzMLVAif4nXImAnIqKc6Zky7VlNuqm3adMGxYsXx6NHj7B48WLs2bMHW7duVXf1v/jiC1XgrlKlSmpM+/z589UYeulGr8u6S2G8Dz74ADNnzlTdRmS8fc+ePVXAT0RERM9GV6ldZ9GZRahdrLbR9rqCbo3dG6OqS9UMg/Z/zvyjlp3KdIJnQU81r/m50HO4EHohRdfzpMQEXPphCBZcAjoHATb3v0mxn19rA4t75MWJ6tURGhWK86HaQL6Bm+Hp22wtbdHNuxvmnp6r35aZoJ2IiMikg3bp2v7OO+8gODgYDg4OqFixogrYZQye+Oyzz1SBOpn6Tbq8S/AuY/RKlSql38eiRYtUoC4F6qRqfLdu3fD777+/wrMiIiJ6fUn3cdHFqwtWX1yN9ZfXY2rbqUbbb76qDdrbeLSBdyFvffbdmG3+2/TTtwmvQl4qaJdAv41nG22jmBg87PMmxqwMffJTjwB3dyl0A5ibI8QxN/53fRCsQ/3U+HtdUblyhcupedyN+aDaB/qg3TWvK9zyaXvuERERZWevNGifM2dOhm1kbLtufLshUileMvRERET038QkxKju8er/v/VHqKD9RvgNhMeEw8HWIU37Gw9vYPd1bbf0dqXbqXHf4m7UXTUPe4FcBVK0D4kMwak7p9R6i5LaG/S6QP+B7xHg1HRAhrzt3YsC/v5IMAP21ymCJu98A/TtCzyZctZRo0G+CaPwMOahyrDr5mzPKHMuPQb299uP2Sdno6uX9qYBERFRdvdcY9qJiIjo9TFq1yjkGZ8Hp++cTrfdkVtHEJsYCxd7F9QoUkNlo8XZu2cNtp95YqYqFtesRDN4FPCAvbktyltoh6ddupeyJo20m7T1W7Ve2bkynOwKAytW4J3pBzF+O/DNoBXAJ58Ac+cC/v6IsLdC216A76QvtBn2JwG7kCF0uq74J4NP6nsHZKa7e/3i9TG/83x08uqUYVsiIqLsgEE7ERFRDs+ej90/FpFxkfh82+fptj0UeEg/LlwC44pOFdXzsyFnDe5XMtZiUM1BUkYe6N4dJ8cEo9WVZF3kn8xBe+DHAZjwxp+YtQ6Yd8IVkDnUu3eH56rdGHEQsErUQFO9GjBqFOJXLofXEAts9wCal2xu8FirOmuDdsn0625GcIw6ERHlRK+0ezwRERG9WLpCceJY0DFEx0cbrYQur4vaRbWF5yo4VlCF6c6EnEnTdqnfUhS+eR8dYguj4+kYYFg7YPNmyOQ1WxYBkRsGAblGAnfuAE2bouGuXernPjgp6fH1+v1orKxgFh+PYHvg3qLJqFC6Po7dPIhgvxgUtiusxqkbosu06wrbSaa/SB4WoSUiopyHmXYiIqIcbJ7vPP36o7hH2HRlk9H51tX0bhqgeaAVsHYtqtuWVK+duZsqaH/0CIU+/hwXpgF//xUK87feUgF7cvbh0dqAXTwJ2FOwsQG+/x5mkZGY8L43GvYDDj86nyLjX694PaNzxOuCdp2GxVkJnoiIciYG7URERK8RKbzWZVkXjN41OsO2Evyuu7ROzYmuK/ymKxyXmsxfHhJxBzM3mqFCj8FA587o3P5/+OQocDHYTwX1iIoCfv8dCV6l0f7wffVzSYUKaSu79+8P/PwzDhxehjfeBNZWt5dqscCAAbj3RlvMqgrUHpoHSTJmPTBQVYjH6NGAtTUe9uyMqwW1c8SLg4EH1bKeaz2j5ybTxSXXtETTZ/gUiYiIXh/sHk9ERPSakOrrdebUQURsBNZcXAPvwt54u8LbBttKkP3lri/Vev8q/VXQvv3adn0WO7Wd13ai32ngwxMa7Yb8+WERFoY/NgPf7I1A4l/usLx5C0hKUn883MwLTPy0Gqb+cCLFfko9CsaqcsDq8o/x+KtQ2FjZYvb+8fh61yZ09moG8x790ry3bh74I0FH1HHrM+3pBO1yI6KJexN1E6Kua110L9c9sx8jERHRa4WZdiIiotfEroBdKmDXGbJlCBKTEg22Pf3otOrunssyF75v8r3qai58Q3zxKPaRttHt28D//qfGnF+b9RNGaKc7B376CQgNBWbMwP3c5nB8DFhev6kCdpQqhYl9SqL0YKBMh3fTvK9M+5bXJq+qFn81zF9t2xmwUy2lyrwhtYrWUssLoRfUuPrQx6GwsbBJ0wU+tZntZ+LP9n9i5zs7YWUho+mJiIhyHgbtRERErwmZkk18XP1jONg44N7jeyoIN2RN6Bq1/Kj6RyqQliJtbg5uKpg+cXEX8M8/QPnywK+/Art344eZl+H5AEgqkB8YNAiwsAA++gjvTmuOeu8B62d/AQQHI+zMMXxZKgCxVkCnMmmnTZMx6F6FvNS6VJCXKvO67u7GgnYneyd1bBpoVKV7XSV4G0ubdD+P0gVLY0C1AbC1fDodHBERUU7DoJ2IiOgVi02IzVQ76T4uJGsu07KJPdf3pGkn2fiL4X4oGKUN2nXk577cDzSq2hXo0wcIC4OmciWcd8+tXo+ys4L57L+A3NrnopSTNw4VB/YWTwKcnbHv5n4VXEtg7uqgncc9tbKFy6rlubvnVFd3Cdxl7nddMG9IrWLabPv6y9rK8i1LtczUZ0JERJTTMWgnIiJ6hSYdmgS7cXaYe2puhoG9bj5yGQPeyK2R0aB9V8BOLFyZiHsTgdLt3gH++gt4+22Mmn0JP+0EzKWbu5UVMHIkFs4ahHJ9o9DyQzs8POcDdO2aYl9lCpZRy4v3LqYoZNfYrbHRY63oWFFfdX6b/za13qxkM6OV4JN3kddpVapVup8HERGRqWAhOiIiolfk/uP7+Hz752q9/7r+agx3ZefKBtvuu7EPcYlxKGRXCCXylUBjd23QvP/mftXlXQqzIS4OWLoU1X78HCWvPPnBo0e1DwDeTzbNapgbA/ZGqvWNK3sAZkCdHp+jqHuFNO9bppA2aL90/1KKmwRNSjQxel4VnbRBu+8dX/jc9lHrHUp3SPezkGJyOtJVvrxj+XTbExERmQoG7URERK/I70d/T/F80uFJWNhlocG24w+MV8s3y76pMtaVnCqhyGMLVLv4EA/mzUChI2eAZcuA8HBoZ1cH7jasBsd92qBZJLk44/OKIZhcKwodHgWrseS7A7SZ8xaltFPCpaYLnv0f+CMgLEA/hl530yC9oN3/SSE6e2v7DIN2ybT/3vp3NZd8z/I9083KExERmRIG7URERK/I8vPL9YXlpp+Yjg2XN6hsurWFdYp2vxyYoLqlW5lbYZRLD+D+fVidOIErk5NgFwdg6SB922ingljhdB9Rua3Rd/UWYO9+YPVq4JdfYO7oiG3Ty0MTeg4+wT4qoy2V2u2s7FCzaE2Dx+iY21Fl9gMeBmDioYn6Meuy3ZjCuQurHgFSKE908eqCXFa50v0sJEgfXGvwM3x6REREpoFj2omIiF6By/cvq3HiEoj/2PRHOOV2wsOYh2nGqF/Ythi9W3+JrQuA1dGdUKRGU6BQIaB1a9jFaXDDAQj1LKKmbcPOnej9WwP07Qps7d0GVnkcgC5dgAULAEdtkF29SHW1PHH7hJpCTjQo3iDNjQJDReJmnJihljI/ekbkhoDOsDrDnuszIiIiIgbtREREr8T6S9oq6Y3cGyF/rvz66dM2X9kMHDgAuLoCNWrAu1UvOEcBLa8B7cav1M6V/sTpZuXhORgYOamdCtjjGtXHlgBt4bdG+bWF6lJLEbRf1wbtTUs0TfdYaxetneJ5el3jdYbXG46S+Uti/VvrjY7TJyIiooyxezwREVEWWnJ2iZpfvKt3yirsyWk0Giz2W6zWO5buqJYNrT3htgOwvr0DWLsECAkBbt3S/0yEcwHkvfMAqFQJaNcO8PDA+WrWiF/dW82HLo4FHcPj+McobFcYJXKVSDdolznf45PiMxe0F0sZtOsq16ene7nu6kFERET/DYN2IiKiLCKV0t/+9221fui9Q6jjWsdgu6NBR3Ey+CRsLGzwVoW31LY241agwAEAB/y0jZyckPDjDxi6YRDWlYjDui93oZLGEShQALCxUU28g0+p5YVQbdCuKyrXsHhDo4XcpICdhZkF7kffV88dbBxQxblKuudVrUg1tPFogxvhN/B+lffVmHUiIiJ6ORi0ExERZRFdoTbx0caPcOrDU9qp2FKZ5TNLLaVKuhRsw6pVKLDvmNoWZQXY9H0Plj+MhU/CDfwRFIf8tvlRwakCkGpfMh2b7F8C8OBHwSnnUA8xfIxSEK50wdL67Lx0dbcwt0j3vCzNLbGp16Zn/TiIiIgoC7AQHRERURYIjQrFivMr9M/PhJyB390nWfNkEpMSsf7SOhR/CAy0awRMnAi8pc22T21oA/uRwPkfhwDOztjm/2R8unsjg8G/VH33LqSdfX3vjb04GHgwU2PO6xR72gPgkxqfPPc5ExER0YvHoJ2IiCgLHAo8hCRNEsoVLodWpVql6K6e3PHbxzF22X3cmAzUavUeMHw4EB8P9OyJFW9rC7ZdundJLTdd1Wa323q0Nfq+ujHqPx34SU0XJ9OzlS5QOt1j/bTWp2jn2Q7bem8zOj87ERERZQ8M2omIiIyQKdm6r+iOU0/GjmcUtIu6rnX1U6LtuZFy+jZxc+bPGHDyyZPcuYEqVYC5c4FFi1DK2Vv/vjLH+dFbR9XzNp5tMgzafUN81VKCcWPj2XUqOVfChrc3MGAnIiJ6DXBMOxERkZEK773+7aUKxm25ugXB/wtGbuvcRj+rw7cO67uely1cVq3vvb5XZd/NE5O0c6WvWYPu67VTvZ35oCMqzlqbYh+6ru5n7p5RU79poEEFxwoolrdYhkG7TrvS7Xg9iYiIchAG7URERAbIeHIJ2MWjuEeYcHACvmvyncHPSrqlS7d3IRXjPQp4IJdlLpg9CMPDTwegwPL1wN27+vZLygPNJ840Otb84M2DiI6PVuvpTR0nZA50awtrdQxSBV5N3/Z0KnciIiJ6zbF7PBERmVT2XB6ZsfTcUn2xN7EzYKfRtvtv7EdMQgwK5iqoKrNbxsRhok8BXJsCFPhjjjZgL1wYp/u2wttdgWmDa6Gwg0ua/dQoWkMF4MGRwdh4ZaPa1qNcj3SP09bSFgs6L8DEFhNxuP9h9fNERESUczBoJyIik5CQlIAGfzdAiSklVKX3jBwO1HZ3H9NojFqeunNKVX43ZOGZhWr5hnc3mM+bD3h44JPVQXCIBYJLOQFr1wJBQfi2tQ2WVATaeHUwGoAn7+4uXeO9C2u7zKenR/ke+Lzu57Cx1M7fTkRERDkHg3YiIjIJc07OUVOi3Qi/gTF7tIG4MQ+iH+DSfW0F976V+yK3VW48jn+s3ZaYKCl7fdu1e2dh4+nlsEwEfpxxCXjvPSA4GOEuBdCrK/DJD7WBjh0RZ67BroBdGRaWq1W0ln79m0bfZMGZExER0euMQTsREeV4Mj782z3f6p//6fMnbkXcMtpeV7Xds4AnHHM7qnHj4uq+tYCDAzBwIPDwIe58Pxxtm36IU79GY+f6/Ci0eS9gbQ1MmICTuxZhcUXgTKh2rvYjt44gMi4She0K6/dnyPtV34dXIS9MaT0Fb5R9Iws/BSIiInodsRAdERHleHNPzUVIVAjcHNzgYOuAMyFnVLE36VZuiGTkRe1itdWyqktVta3A30uAqCjgzz/Vw/lJ+2KPgGKnw7RPli8HOnVC+Sdd8P3D/FWwvvXqVvVc5kU3NzN+z1wqz1/45EJWnj4RERG9xphpJyKi19LDmIeqm/vZkLPptpMp1yYemqjWh9cbjvqu9dX6idsnDLaXcev/nPlHrTcv2Vwta+YuA2gAzyOXU7QNcrTF9OpAVKG8gKMj8NdfKmAXhXMXRpE8RdS6VKHfdm2bWm9ZsuV/PHMiIiIyJcy0ExHRa0emN+u0tBP23dinAuxzH58zWoTt4r2Lahy7VIHvV7kflvppq8LrpmhLbdOVTap9Adv86PGgCNClC3qvWYOuloBdQqy20cCBeFy1AtyCBkFK07X+6ChKFi4NmKe8F17XtS5Wnl+JtRfXwue2j9rWshSDdiIiIso8ZtqJiOi1s8B3gQrYdd3PpxydYrTtsaBjalnNpRpyWeXSV2f3CfZRWXi9wEBoFi3C5K1jUD0I2LXZETZNWwBr1qiX7RK0zaLfehOYPh3b6rsgEUlq3HtJJ680Abuo51pPLX898is00Khq8C550k71RkRERGQMg3YiInrtHLh5QC113c//Pv13hkXldFXZZQo1ybrLOPMrN04Bd+4Av/0GeHvDrHdv7BxyEsdnA5X2XgLMzLTV4HfuxHfdCqFbd+DYN/3VfnZe087b3qJkC6PvXb+4tiu+DrPsRERE9KwYtBMR0WtH17V9fLPxMIOZ6gJ/J/KOwbY+N49g71xgxOdrgIgIWJpboopTZfy1FihTojrg4gIMG6YKzEVbmamfibeyAPLnB+bPB+bMAZo2xck36uLfssCZcO249h0BO1KMezekklMldYNAh0E7ERERPSsG7URElC3M8pmFfmv7qQJz6YmIjcCFUG119ValWqGScyW1vvf63jRtJZCvssUXDW8CBc9eBZycAHd3HHj/EPqfetJIsulFi+LIN++h0BcatBtgj8i7t4AHD4A+ffT7Kl+4vFpK5fmgiCB1o0CqwDd2b2z0WK0srDCp5SR1nN81/i7dAJ+IiIjIEAbtRET0ysmc6R9u+BDzTs9D639aq0JzxkhBNxkfLtO3Odk7oYl7E7V99/XdTxtJwF27NuxKeeHP9Zqn22NigBs39E9/e6sEkJgI3LqFkaWu47E1UKfXl8ifTzeZ21O1imm716+8sBKrLqzSj5PPnyt/uuf2UfWPsKX3FnzT6Jt0p3ojIiIiMoR/PRAR0Ss3+chk/frRoKNYf2m90bY7rmm7pdcsWlMtG7o1VMsjt45oGzx+DLz7LnD0KPLeDVebHro5AevXAxMnAmvXImjOZLzVDRhZNhgJmkTEJsTiUOAh1babdzeD79vOsx3KFS6negKM2DFCbWtWolnWfABERERERnDKNyIieuUWnV2klpI9l+nWpDJ8t7Jpg+eYhBjMOjlLrb9Z9k21rFiwLN73AVpfO4vEkDGw+GcRcPWqei3cBjhV1ALVdh8AinsA7dur7S6aJGwMGY3ouEc4H3peBeKyb2d7Z3gV8jJ4jBbmFvihyQ/ourwrohOi1TZ2dyciIqIXjZl2IiLKclFxURiyeQi2Xt2aYdu7UXfV2HMpKPdto2/Vtv039xtsu9B3Ie49vodKFkXRbe5hlTkv0XsQZq8Hup1LgsWY71TAnljEBe16myPfV0DQ6vnIIwF7MtJNvVqRamr9xO0T2B2g7Vov49PNZIy7EZ29OuunjLOxsFHzsBMRERG9SAzaiYgoy40/MB6/H/sdrRe1RnxifLptz4acVctSBUqhlUcrte4b4ovwGG3Xdp248Ae4NOkrjN8OnB4dBPNffwOGD4fZtu2ItjbHWccnDfPlw75532GTRxK8C3mjV8VeBt+3ukv1p0H7k/Hwjd2MF5UTEtD/3PxnWJhZoGOZjmredyIiIqIXiUE7ERFlqYSkBMw9NVf/fN2ldem2P3tXG7RXcKyg5l0vmb8kkjRJOHJtn7ZBZCQwbx4SPErilyX3MeJgsh/Omxfo3h1jf26HigOBBb+9C5w6hb1WQSnGvRtSo2gNfVb/8K3Dar1JCW1Ru/Q0LdEUAUMCML/z/AzbEhEREf1XDNqJiChLSZf44Mhg/fO/Tv2VqUy7BO2iQaFqWLUUaFGhE2BhATg4AP36we5eOK7lA843rwSULw+sWAGEhwPLliFfzYaAGbCx2GM1pZtkz4WuK7shutf87vqpavVyw8CzgGemztHVwZVZdiIiInopGLQTEVGW+vfCv/qMtNhzfU+6U7jpM+1OFYDr1zH+xyPoehEwT9IASUnqkeDihC9aAGUHAXlXbQDOngXeeEO/D6nqrgvANRpNpoL2EvlKIL/t0+naZOq49MazExEREb0KDNqJiChD5+6ew9SjUxEdr62abkxiUiLWX9ZO1zai3ggUsiukqrLL3OqGBIQF4PSd02q95h1LoFYtuFwIxANbYGsFO6BmTWDDBvy6Yhh+qQfU8WiMYnmLpdlPecfyann5/mX4h/kjJCpEjTuv5FTJ6LFKgJ68+rvuJgMRERFRdsIp34iIKF0SWDf4uwHCYsJUJvvPDn8abStzpYc+DoWDjYOqxF6/eH2subgGB24eQB3XOmnaf73ra8QnxWOqfxm4ju0OxMcjsWJ5VGnqh5v5HuPeF5tQ0K4gti+cnO4c6hLI57XJi4jYCPx1UtsdX6rDZ1Qobl7neWjr2VZVr3+n0jv8JhAREVG2w0w7ERGla+DGgSpgFzJH+t7re4221RWdk0DYysIK9V3rq+cHAg+kaSsB9nrfFSgTCny87BrM4uOBDh1gsXc/LEuUVG1OBp9U1ecPBR5Sz+VGgLGsua6L/PTj09WykVujDK+snZUd3q38LkbUHwFLc97HJiIiouyHQTsRERkVGB6Ibf7b1HqdYtpM+ZarW4y2X3tprVp2KtNJLXXzmB8LOpam7W7ftTg+IxEXpwHmcfFAlSrA2rVqyrYqzlVUmzMhZ+AT7IPH8Y9RIFcBlC1c1uh764L2R3GP1LKhW0NeWSIiInrtMa1ARERGLTq7CBpoVNb67Qpvq6nRJIg25NK9S7h0/xKszK3Qxq0ZMGsWKpYrjYbXgdL37yDKdjJy7z0EmJsDRYqg3j+zUOhesh188IGkzPWV5FddWAW/UD81hZwuCDc3M36vWTeuXZjBTHXNJyIiInrdMWgnIjIx4THhePvftxGbEIuPqn+EN8o+rcKe2uKzi9WyT8U+qOxcWa1L0C4V2lNXWv/79N8wSwJ65K+LvH3eV1nz3AD0nenXD03RvtCTZZKlBcxLlgJ69UoTgMt0cLcibqn1xm6Gu8brlHPUZtpFt7LdkM82X8YfBhEREVE2x6CdiMjEfLH9C2y6skmty1hx6cr+//buBCzK6m0D+M2uIIsiIgoiCriCKG5ouCu471vuWpmWVmaa/zQrM81KozI19yz3PXfcdwQ3UFQURVE2EWWXdb7rnHFG0AGsz2Vg7l/X9L4zc2Y9zDjPe57zHDH//Fl3Eu/I5djE6HbPWj1hZmQmR9ET0hMQ8SgCTmWd1G0fH9iL7u/+hOl3gdLZ+ee8PzY2wKEqOWisbw/ritUACwvcfhyL740DcalOeez/7i6MDU3y3UYu//bkAIFqrrmvs2+hr0uMxPer0w/OZZ0xvdX0/8c7RERERKQ93uic9gULFsDd3R0WFhby5OXlhd27dz/XTozodOzYUY7qbN26Nd91d+7cQefOnWFqaooKFSrgs88+Q3a2MpWSiIjyOx9zHovPLVafT89Ox9X4qxrfpt3Xd6vnsov55CaGJnC3dZeXqVPkAwMBT0+UaucLr4hslFZ9/TZrBhw6BFy8iJl/voNOg4GZv/QFjhyBYvt29OiThQWNgY5dJzwXsAvVy1ZHKcNScl+kx4s11V2tXQvtTmMDY6zrsw4z286U+0REREQlwRsN2u3t7TF79mycPXsWQUFBaNOmDbp3747Lly/na/fzzz8/l4Yp5OTkyIA9MzMTJ0+exMqVK7FixQp8+eWXr/FVEBEVHwvOLpDbgXUHwruKt9xXrZP+rJ3Xd6orwauoUuTF0m/Ytw9o3x44dw65esAfDYAFf30MpKUBJ04ArVoB7u5wdGkobxN6P1Rubz68KR9TjKCPbjha42Mb6BvkKzonRtk1/TtAREREVNK90fT4rl275js/c+ZMOfp++vRp1KmjnJt44cIF/PTTTzKot7Ozy9d+3759CA0Nxf79+2FrawsPDw/MmDEDkydPxldffQVjY80jLRkZGfKkkpSUJLdZWVnypItUr1tXX7+uYX/rZp+nZKdg3dV18vz7Dd7H+tD1OHbnGM5GncWA2gPytX+c/RiRZ/yx4hDQ48B25HglAunpmBgcAIUl0OrQSuDI17JtRtNGqN48CPfMFbja/n1kGRrK9dZVXMsqR8gvx12Wz8P/hr8836RSE5gbmhf4veNbzVcu+Va+dHkMcxvG76d/2d95t1Tysc91C/tb97DPS6YX/Xdaa+a0i1HzDRs2IDU1VabJC2lpaXj77bcxf/58VKxY8bnbnDp1Cm5ubjJgV/Hx8cGYMWPkaH19sXyQBrNmzcLXXyt/bD57EECk2esyf3/lj2nSDexv3RKcEizT4e1N7JFwMQH6CcpkqwOhB7ArUznHXSU05hR2LH2MynL1tADgWIC8vCaApXIvQv7/ZufOmNepAu7dD0QN0xq4euoqxH95peWkye3d5LtYu30tVt9VFrezz7LHrl35HzevRopGWFFnBSwMLRBzPga7zhfcljTjZ1z3sM91C/tb97DPSxYR7xaLoD0kJEQG6Y8fP0aZMmWwZcsW1K6tTIn85JNP0KxZM5kyr0lMTEy+gF1QnRfXFWTKlCmYMGFCvpF2BwcHdOjQQc6t10Vy9MvfH+3bt4eR0fMFqahkYX+XLJk5mfC/6Y8cRQ58q/tqnM8t+vyvP/+S+x1qdUDnTp1RObYyfl36K6IzItH53DnoHzoEvchIwMgIjR/Hwy4ZeFS2NMwnfQncvg0YGuJhdjLC/1kJ0xx91Jz7Fxz69MG9Tf2B+8CgRoPQqfnTVPq8pt2dhvCH4bBxs0HYrTB52bvt3uVa6q8IP+O6h32uW9jfuod9XjKpMr61PmivUaOGTIFPTEzExo0bMWzYMBw5cgQ3btzAwYMHcf78+Zf+mCYmJvL0LBGs6nrAyvdAt7C/S0bA3vnvzjhyW1mx/RffXzCuyTiNbW+m3ZRbz0qesu/rmVeHaa4hlvyZCMNr3+RrKyYjZesBIXM/h/fwz9WXW+ZkobndX/IAQWRnb1Q2NMTxyOPyujbV2hT4HVrfrr4M2hdfWIzY1FiUMS6Dt6q+BSND3f7OfdX4Gdc97HPdwv7WPezzkuVFY883WohOEPPOnZ2d4enpKdPW69WrBz8/Pxmwh4eHw8rKCoaGhvIk9O7dG61EcSNApszHxsbmuz/VeU3p9EREJc1k/8nqgF3Iu/+sm+k3YZYBNKhQDwgNhbFzDaR+k40e14AcE2Pg++9lcbnIT0ZhaX2g1ZhS8Bw0Md99iKXhqpWtJvevxV+Tlefvp92Xld4bVlIWnNPEw1ZZwG7zlc1y26NmD1mNnoiIiIi0PGh/Vm5uriwS9/nnnyM4OFiOwqtOwrx587B8+XK5L9LqRXp9XFyc+vYixVukuKtS7ImISqoTd07AL8BP7n/c5OP8S7E9Izo5Cg53HyH6J6BJk17iCxSIj1dfv328LzBpkqwGP6ddabzTHXBq1wemRs/X+ahRvobcioBddZBALAtXWBAuRtrzEtXriYiIiEjL0+PF3HKx/nqVKlWQnJyM1atX4/Dhw9i7d68cKdc0Wi7aOjk5yX0xB10E50OGDMGcOXPkPPapU6figw8+0Jj+TkSk7bJysjDz2ExcjL2INlXbFJjqLsw4OgMKKDDCYwSmt5qOnwN+RsSjCDxIewBrU2t1O8XWrbAcPhDBiU8uiH1yoNPSEjfqO+JvRTDOeuSi55M10dddVlaYf7vu2xof172CO3aE7UBQdJCsMi+0dGxZ6OtqVKmRHI0X7e0t7NGuWrt/+9YQERER6aQ3GrSLEfKhQ4ciOjoalpaWcHd3lwG7KIb2IgwMDLBjxw5ZLV6MupuZmck58d98k39uJhFRcaBQKNB/Y39subpFnt96dSt61+6NSuaVNLY9ffe03B/XeBysSlnBuZwzbiTckMukta/aBti9G9ixA/jjD1gqFE9v/OmnQM2aQK9eiE6+jK9WtIB9rDKb6cDNAzLd3cbUpsDA+q0qb8nt8TvHkZalrHrasmrhQbuNmQ0C3w3E7Ue30cS+icZieURERESkZUH70qXKhYNelPiR+ixHR8dClwwiIiouRBAsAnYR0IoCc8LJyJPoU7vPc21FcJ6YkQgTAxPUrVBXXuZp54nw+BuI2bMR2PaDmC8kL9cDsNwDaJBaDnVHTITBlCnq+6lnVg960MPdpLuISo7C6kvK5dj61ekn569r4uXgJW8jnoMgnm+Tyk2KfH3ieaqeKxEREREV0zntREQlSWpmKpafX46UzJQi2665tEZu33Z7G2MbjlUH7ZoERQXJrUdFD2VwrVCghbErfvAHhnz4hzpgz+3oiwHDzDCyB7Bz+qfInZi/sJyFiYV6vvm+8H3YcmVLkXPOxai+m62b+nzjyo1R2qh0ka+PiIiIiP49Bu1ERK/QxH0TMXL7SIzbXfDcdDyZS74hdIM6YG7m0Ezun4g8obF9YFQgrFOBt+NsZcCOadMwtvsMfHrqSQNR+2PjRuz/9ROsc0pFBdMKqGlWU+N9tXJUrsjx1eGvkJyZjIplKsrR9MLkncPeyVnz2uxERERE9P/3xtdpJyIqqURBuIVnF8r9FRdW4JtW38DB0kFj24C7AYhPi4d1aWu0cWoj09UFMT89PSs930h2TMRlRKz/A7v3AI2itgO7WwCnVNE68HtDoP+RQFmM7vCB/8nLfJ19YaBnoPGxW1Vthbmn5+J24m15vqtrV+jrFX5Md1qLaTK4F+nunV06/+v3hoiIiIheDEfaiYhekWXnl+U7Pz9wfoFtVSPqLRxbwFDfEI6WjjKAr/wgGxEndylH01euBLp3h7WLOzYvS0WjqCc3Pn4cyMkBWrfG4A8rYVwnZbAvr7pzXG6b2zcv8LG9Hb3zBenda3Qv8rWJwnL/8/4futXoBgN9zQcDiIiIiOj/j0E7EdErsunKJvVItrDz+s4ig/bmDsrgWm/PHqzZYoDrvwK1WvUB9PWB4cOB7dthlJ379IbickNDoGdPYO1aZLf0Rq6+cs67KGYn0ugFVbp9QXPUF3VZBLcKbnKUn8uxEREREWkPBu1ERK9AbEosztw7I/f9fP1ktfVLcZcQnRytcWUMVcG55lWaAwcPAp06of3pOBjlic9FgJ7kUQtr6wCtPy6L3P3+QHY2kJkJbN4MVKggK8gLZ6PPytF2sS56edPycC3nWujzfafBOwgeE4wDQw/AxNDkpb4XRERERPTfMWgnInoFxKi6Ago0rNQQ7rbu6grt+2/uz9dOkZyMYx3r4J298Vi6wwBNmvUD2raV18W4VUO7IcD6LtWArl2BoCB8O6cLBvYFHFp0gX7bdoCenvL0hGelp0G7qAavWlddL08bIiIiIio+GLQTEb0AMRrea10vWMyyQNs/28oR7MIcuHVAblVF2tpXay+3hyMOK+efb9ki56frWVigxd4rmHUAGBmUA73ISOUd1KyJW2sX4EB1YGKbLJkWj/r1sev6Lnl1R+eOGh+3gV0DuY14FIFFZxfJ/R41erCPiYiIiIopBu1ERC8g/GE4tlzdIpdEO3jrIFZeWFlo++DYYLltVKlRvmA66fI5oG5doFcvZSAOIEc1CG5gACxdCty+DQQHo6aT8raRSZFIfJyIyMRIXL5/WRaN83H2KXB+unM5Z7kflRwli9qJYnFEREREVDwxaCcinZWQniDXUb8cd7nItiJQz2vOyTlybXVNMrIzcDX+qtz3jFLIEfUOkxdj35/Ahi8uAFevAmXLAuPH488uDvAZDOyfPRo4dAgYORKoUgUwMkLZ0mVhb2Ev70cE67tv7Jb7TSo3QbnS5Qp8rqoDBIIoKifuh4iIiIiKJwbtRKSzph+ajp9O/YQmS5ogJTPlhYL2Sc0myaXYbj68qU5Vf5YI2EVA755mDttBo+WIutXO/Wh/U3l9TkVb4NIlpPwwE6MaR8sU+OrvTQa8vZ+7L7EOuiCK2KmC9oJS41VaVGkht7Zmtvipw08v8lYQERERkZZi0E5EJcbtR7dxKvLUC7VNzUzF70G/K/ezUvHNkW8KbJuTm6MO2rvW6Iph9YbJ/aXnlxaYGv92MHD+h2ToRT1ZTN3ODhsameFbb+Diqh+ASpXkfYrg3snKCU5lnTTeV10bZdAuKsGrith1dCk8aH/X811sG7ANVz64gto2tYt+M4iIiIhIazFoJ6ISk+ouRsybL2suA9yirL+8HrmKp+upbbu2rcC2q4JX4X7afZmS3rhyY4xqMEpevjNsJ+JS4/K1VeTmYv+ZtZhxENBXAHBzA8LCgKgoLB7XDNPaAufLZcq2/1z7R267uHYp8LFVI+2iqJzIBqhgViFf+rsmxgbGch470+KJiIiIij8G7USktURKeHpW+gu1new/GbGpsXKZtRUXVhTZfvPVzXI7oekEuYZ62IMwubb6s8RI+JeHvpT7U96aIgNiMXpdq3wt5ChycD76/NPGx44hwc0ZK9/bhWqPgGyLMsDp04CLi7y6ZvmacnvtwTV5wOCfMGXQ3tW1a5FBu4pPdR9ZiI6IiIiIdAN/+RGRVjp06xDcFrjBa6kXkjKSCm0rKquvvPi0mvvaS2uRlZNVaGq8KtV8uMdwdWB8/M7x59qKdPv06Eg451rhw0o9gPBweXm3BBu8HwhEhQYAGRnAnDlAy5awDr2lvq3hkGGAqan6vCpovxh7EUFRQfIgg7mxOVpWbVngc61lUyvf+aLmsxMRERFRycKgnYi00uJzi9UB7pidYwptuzd8L7Jys1CtbDXYmNrIVPZDEYcKbO9/01+us17VqqoM2L2reGsO2nNyELB3Ga7/Alz/5hFKObkAtWoBGzfiq9mnsWAnMKL7dKBUKWDyZLGYO5Z5AM3e0UPy3NnA99/nu7uWjsrg/OjtozI9X/B19pWj9wUxNTJFW6e26uXjCkulJyIiIqKSh0E7EWkdMRKed475ptBN8rKCqNr2rtUbPWr2kPvbrynXQH+WGIH/+sjXcr9HjR7Q09ND8yrN5fkr144DH38M9OgB9OwJlCuHiaNXwCoj7x1kAX37olSacl56XsdHtceoHkBp79Yw/2QyYGaW73qRVi+WcBMHDETVeuFF1lDfM3gP4j+Lx5l3z8DcxLzI9kRERERUcjBoJyKts/P6TqRlpaF62epwtHRERk5GgSPnop0oCKcKgLvX6K4O2hUKUQkuv18CfsGFmAty2bbP3/pcXlavfF30DAWWTD8L+PkB27YBW7cCScq0/IelgKx2bYCBA4GmTdX31WUg4PqjI3DrFhAUhC/eUkb3fWr10fhcxQEC3+q+6vNibvqLpLsb6hvC2tS6yHZEREREVPIYvuknQET0LFWBNjFynpyZjAVBC7D7+m6NqeHrLq1DYkaiXDbNy94LmTmZMqU8MilSptZ7VPRQt017EIM7fl9jbArg9ek02IbHAB/0Ru3Ll7H5kWihQFa1qjAa95Gcp/7jw51YmHYMbRv3w6LB65R3kpsr111PfBiDnbfHQC/lDh7bVwTsKyJgd4Bs0raaMp1dk561emLJ+SVyv41TGwbjRERERFQoBu1EpFXEmui7ru+S+yJIf/T4EdYdXYCBE5YDc68CgwYBw4cD+spEoYVnF8rtaM/RMNA3QGn90nKOevSJvXg882ugSW8gMhIwMkLmL3PgF5ks2ysuzQUwF7hzB3qimJ2pAX7zzEH9n79Hpwb9EJMSg8/nfoGc0sDGdlOePkHxuD16wEKhgOX3n8sDBjcSbuBh+kOZEWBrZguXcspq8ZqIkfUDQw/ISvWFBfdERERERAKDdiJ6LUSqulhnvKg52afunpJrrpctVRZeDl5IyUjGsm3AW2HpQNhB4OBBYNEi4I8/EOdshzN3z6DpXeCDHbHAspFAgwbol2KF/ksBs6ytwG9b1fdtBeCxAVAqB9C7c0d5ob09sHo1PopZiJWhq/FtynV0AnDw1kG5pFv9ivXzjdbnTXUXld1P3z2N4Nhg3HqorBrfwrGFvK4g4joxwk5ERERE9CI4p52IXjkx79znLx+Um1Mu/7rmGiw9v1RuO7t2hiH0YfXZNHS/przubsfmgLk5cOYM4O2NE4GbsWE9cGopUOb7ecDy5cC4cRg5ZR3MsoAsAz0ZxIu56Bl9euDbFoDjJ0D8b3MAQ0OgQwdg/355X7Ur1ZOPERIXIrdHIo7IbeuqrQt8rqKauxB4LxDH7hxTB+1ERERERC8Lg3YieuXG7x4vl1nLzs3GH2f/KLCdSElfHbJa7n9Y7z1g8GBg/nzk6gFDegJ+H3sB164B9eoBycloOOIL9Lny5MYDBgBDh6rv62BVwHqaMbIDA+RI+povumNaG6CSswfKf/CZcm31vXuBGjVke9VoemBUoNwevn1YbltVbVVk0C6yA05EnpD7DNqJiIiI6GVi0E5Er6UavMrGKxtl8K7JqourZCG5pnaN0WT2KmDNGjkifvKbd/FXPSgDYzs7YPZs2d4hIkFuI4Z2U7ZduRJYsgSKYUMxYrAZkpGBa/HX8j2Hbq5Pllh7Midepal9U1nN/ebDmzhz7wzCHoRBD3rwdlSu4a5Jo8rKoD3gXoBM/bcqZSXXfSciIiIielkYtBPRv5aRnYFR20Zh/pn5RbaNS42TI+iCqOoenxaPAzcPaGy7I2AV5u8A/KeFAYsXiwngwObNsB3zmbz+XPQ5uc46fHwQNrgjsvWAxFJAhek/PL2TUaOgt2IlHJyUI+fnY87L4naqx/R1frrkWl4WJhZy/rrw0Z6P5LZx5cYyEC+Iq7WrvJ2KKIAnAn8iIiIiopeFvy6J6F/bcnULll1Yhg93f4gfTuQJmDUIiVXOEXcu54zh9YbL/bWX1z5tkJAA7NyJiL3r8K1fCMYGAWXiHgGWlsDChUDXrqherroMjkV19tD7ocjIyUT3prdgNxFYunoSTKu5Pve4qgBcrMl+NvosHj5+CEsTS/XouCYtHVvKrSguJwysO7DQ1yYCdJ/qPurzTI0nIiIiopeNQTuRjhOV2jeGbsTFmIv/eh11Yfrh6Xic/bjAtqKyulDPth4G1B0g9zdf2ay8zerVynT3Ll1Q1XcAvO8AKaaGwLp1QEwM8N576uC4gV0DuS8C8C8OfoGr8VcBm/IY1fF/Gh9XNUddjLTvC98n90XVdkP9ghfNaFlVGbSr9KvTr8j3YnHXxRjhMUIu89a3dt8i2xMRERER/RsM2ol03Ps73kffDX3hscgDM4/OLLK9mI+++/pu9fn07HQcvX20wPan7ylHrd1t3dG8SnPYW9gjKSMJ55fPkqnsyMyEwsYGWfrAsSrAsUVfAP36AaVK5bsfTztPud16dSvmnhJrrANLuy2FZSlLjY9b30450i6q1YuDBIWlxuddQ31c43GoYFYB73u+DztzuyLfD/H4y7ovQ9i4MDhaORbZnoiIiIjo32DQTlQCiaJo6VnpRbYTbfIWiZt6aCr23thb6G22Xd0mU82tS1tjuIcy3T1vEJ/X7OOzsf7yenXQLkbMu1ftiCXbAK/3vgEePwY6d0bwhb0w/hJo/64JmvedoPG+VEG7GOVXQCFT2bvVeFJUToM6NnXkqLp4rmK0Xez3qtWr0NdmZGCEXzr+gtiJsVjQZUGhbYmIiIiIXgcG7UQlzP3U+3D+xRkNFzcsNG1dtayZWENdjH6P9BgpL1tzaU2hQf5E/4lyf7TnaHRx6SL3d994PmiPTYnFl4e+lPs/hzqi64Dpco76J4tDMOo8kKMHuaa6qPq+NnS9em32vIXd8mpi3yTf+SHuQwp9bSaGJjJwV2lfrT3Km5Yv9DZERERERNqGQTtRCTPv9DzEpsbKgm0LgxYW2nbXjV1yK4Jv1Xzzg7cOQqFQaGw/7dA0RDyKgIOFA/7n/T85B9wkC7ALuoaUkHPKtc/PnAGWLUPw/0Zh5fosXFtSGh+tvw2Di8HAmDGovvu0DNgHDCmFnJ/nQVGmjLow3YA6yuegSbWy1TDVe6q6Cn2f2n2KfC/yzjF/z1M5P56IiIiIqDgpuCITERU7yRnJmB/4dBm2mcdmyhHx0kaln2ubrciWVeCFrjW6yvnmxgbGiEyKxI2EG3CxdsnX/mTkSfVc8t87/w4zYzOYXQ7D7V/0YZucC6xUpq+rtFfv5UnTL1MGSEnB3BZG2FjtMa49uCafszgQYGZkJkfaCzOjzQx4VvKUI+YFzWXP64sWX2BE/RFIzUx97vUQERERERUHDNqJShBRpE0UeXOyckKuIhe3E29j7aW1MnB91oWkC4hLi4ONqY1MHRfzub3svXDk9hEEHVkDl0f2wPXrQLduSKtbA6u/7oNmuQq4dhmKLq5dlCPqPj7KgD2vcuUQ5VwRN6ND4RGnhzIZT0bt58wB+vcHzp7FzoS5wN3jOHPvDK7cvyKvFvPTxQh6UXrU7PGv3pNK5pX+VXsiIiIiIm3CoJ2oBFHNRx9abyhKG5bG5wc+lyPvmoL2Qw8Pye3oyt1hFBAIeHmhZZUW6LjkCAZ+Nf1pw9mzYWJogN+yc+TZnGMngAeLgYkTgaQk3KpTGc1872HHGWd42noAixbBZ11LXIoDvm83G5NOADhyRLl8m1h7vUoVNPY/hSN3j8vR+8CoQHm/8kAAERERERHlwzntRFou8F4guqzugpUXVsrR84I8SHsA/5v+cl/MTx9ZfyT0oCfXNY+JjwDi4tRtHz1+hKCHAZizD/hm6HKgeXNgxgyM9juOySLIFry9gZ495a5Bdg5SjICM0sYwuBGuDMCTkoCmTRGw5CvEmAOfjLADNmzAdcUDXIq7BCN9I+U88kmTgJ07lQG76q6reMvthtANuBBzQe63q9bulbx/RERERETFGUfaiV6zrJwsufSZgb5BkW1FZfcBmwbg5sObcmm2B+kPMMFL85Jo+2/ul2uo161QFzXL15SX/e+yNaqEx6P8j3WBXIVyxLthQ2w9vwZ/rc9GH5mZrhxBx/TpEInk4rDA+I7A1xu3wNrUGokR19BuTl0EW2cjZNRJuA75GDh+XHmbJUtQyzpb7gbHBssCdqpK8t6O3rAqZaXxub5V5S15QEEcPBDqV6wv10YnIiIiIqL8ONJO9JrXT/dY5IFa82u90Drqfqf9ZMCusip4VYFtRdAuiPnpUkAAvt0Qj/fOAYYpqUBaGuDrCwwYgAEdJ8iAPdvIAPjrL8DdXXkbFxcMmOiI+U2AgHsB8qLtiWcQZJsNZ7vacK3qCWzaJOe5w88PqFNHHiAQa6AnZiTibtJdddDe0bljgc+1bOmycLRyVJ/v7FJ4AToiIiIiIl3FoJ3oNZp1bJZciu16wnVsurLpheeoz247W45Mi1Ty6ORojW3339oP/Vygg91bwPLlQNu26useWZsBenrAgwfAunUwT8tBVBkgfuNfwKBByvT1336Tgb7ZW63lbU5FnpJb1fPsU+vJEmsVKgDbtgHjx6vXQ1eN7J++exqHbh0qMmgXetZUpt6LtdQnNZ9U5HtBRERERKSLGLQT/T9T3f3D/eWyZUURbX469ZP6/JJzSwptH54QjpC4EBjoGeBdz3flUmfC3vC9z7Vdf3k9sm9H4N5cwLdeb2DkSCA1FbkG+nAeB/SZ2xSIiZGj44dHtEazkUCX6e6w7thbeQf29sAHHwBly6Jp5abyotP3TsvnvOfGHnm+d+0nbTVwq+Amt7+e+RUZORmoYlkFtW1qF/r6vmz5JVb1XIVTo07B3MS80LZERERERLqKQTvRf5STm4OBmwaiw18d0GRJE9xLuldo+2N3jsmAVqyFLua0i6XVRDp5QVRrqLeq2grlSpeDT3Ufef5QhHIkWyVu+1o08u6PyHlAxZQnF1asCHzyCa6t+Anh1sCV+CvKEfLx4zHWMwanqgAtrJUj6s9qaq8M2gPuBuCfsH/kc3Yu56wOzDVxt3VXv0bVKLueGNkvhJjvPth9MAN2IiIiIqJCMGgn+o8Wn1usTh0XQfFE/4mFtj9466DcDqs3DB4VPfKloD9LVIkX9y/0rqUc4X5Lvyq+2w+0+X03sH07EBICrF+P8j3fhtPDPDfetw+IjATmzkWlPsql3qKSo/Aw/SEiEyPlcxUHDRpZNNL42HUq1IGZkRmSM5Px+f7P5WX96/QvNAhXBe0qRaXGExERERHRi2H1eKL/aNu1bXLr6+wrU8hFmrwItkVAXFjQ3sapjVwO7Vz0OVnsrW+dvs+13RG2A2EPwtSj0bh+He3engpfOZ39PuDfXd1WPNoRR8CqSUvU6zQCaP+kEB0Ay1KWcCnnIufQi5H9hPQEeXmjSo1QxrCM5i8FfUM0rtxYjuhHJkWqDzQUJu8ovI2pDdpWezqfnoiIiIiI/juOtBP9B4+zH+NIxBG5/12b72BqZCqXY7scd1lj++sPrqvXI29dtbU6BV0UblPLzJRLsmVv3YLp+6bIi0Z7joZ5joGs+G4YHYu7lnpYUh/IdKgElCsn2xxwAtoPAcov/hsY9nxwrUqr33tjL/aF75P77ZwKXxO9mUMz9X5zh+ZwsXYptL29hb18rn1r98XxkcdRxljzAQEiIiIiIvp3ONJO9B+cuHMC6dnpsCtjJ1PdxbrjIiA+HHEYbrb5537feXQbo7aNhAIKmTZuW8ZWHbSfjT6LzOwMGG/YDHz+OXDnjvxQbigLhNkZocOazcCNH4GcHBmkj55SBbtSL8Cizzz0q9MPG48twgD/9+Fh74nKFpU1PlcfZx/8FvgbtodtR2pmqrysQ7UOeBicN6c+v/FNxiPxcSLuJd/D5OaTi3w/ROr8wi4L/+W7SEREREREReFIOxUb3x37Dk2XNC1wybNnBUUFwW2Bm5yXrVAoimy/KXQT+m7oi492f4RHjx8V2lakrwvtq7eXAWsrx1by/NE7R/O1S7x1FSm1nfHVjOMom2OMBQ5jgF9+gfORENgalcW8LY9hYFUOePttGbDnWlkiSx9wfgh0Cs2C4bXryoDd1hZYvRp2rsoK8iGxIcrHS7kMMRAvDhoURBSyE8XvxLx2sZZ6JfNKaFK5SaGvr4JZBfza6Vds7r8ZTewLb0tERERERK8OR9qpWIhPi8cXB7+Q+2K7rPuyQtvHpsSi25puiE6JxqW4SzAxMMHXrb8uNN196NahSMtKU695fmLkCTmn/FmZOZn4O+TvfEXiGts2gHcEYBZ3EvC8CTg5ASdOQDFqMGpHZ0Msfnb/Bz0YzOgm24uSbjHqe0wDDA2BqVMxvs4drAlchg/vO2F6/U+g7+oKuLkBdnZynXX3gGvyFsFxwfnS61Uj95qIVPW33d7Gigsr5PleNXsVOO+eiIiIiIi0C3+5U7Gw8sJK9f7aS2txP/V+oe3FGugiYFdZELSg0NF2MT9dFbDbmtki9H4o5pyYo7HtzrCduJ92H3amtuiUWknOQ2/VZiSOrgBW/B4FVK8OWFgA3t6wCruNFCMgx0AfBo8zlHdQpw5grlyXPFsPWP5uIyA6GrlfTsP6W/8gwRTwnvoH9MeNA3x8gEqVZMAu1K9YX27PRp1FelY6zsecLzJoV827VxnoNrDQtkREREREpD0YtNMbc+X+FSRnJL9Q21XBq9T7Yi65WD+8MBuvbJTb3zv9LkfZRZAtqrEXRFR/F0bVH4U/uv4h9/0C/DQeHFh2YRlc44Eja0rB0LMR0KoVDO5FIcFUD5dsnjRKUS6YfrK6CZqNAgI2zAPGjAFmzQKCg2UqfODauaj6MTCzbgJQvjwuxlyUz1OMjLdwbKHxeda3qw896Mm55iJFPzs3GxXLVISjpWOh74eduR1OjTqFNb3X5CsyR0RERERE2u2NBu0LFiyAu7s7LCws5MnLywu7d++W1yUkJGDcuHGoUaMGSpcujSpVqmD8+PFITEzMdx937txB586dYWpqigoVKuCzzz5Ddnb2G3pF9KLWhKxB7d9ro+6CuriXdK/QtmJ98YuxF+X+0HpD1SPNBQlPCJeV2g30DORyaqo52cfuHNPYXgS+O64r56iLQnFdXbuijk0dOfJ+cc9K4KuvZKo7Pv0UMbdC4LJyJ678Bricv/30Try9McyvFdw+AA7PfFdelOHshHb9MxBW2QQeXd4Bfv9dWWxOXx+wsoJL9xG4ZwmEPwyXBwdUld1FdXkxB10TEdDXLF9T7k89NFVu2zq1LXQNdRUxGj+g7oAi2xERERERkfZ4o0G7vb09Zs+ejbNnzyIoKAht2rRB9+7dcfnyZURFRcnTjz/+iEuXLmHFihXYs2cPRo0apb59Tk6ODNgzMzNx8uRJrFy5Urb78ssv3+TL0km/nfkN9nPt5drjRbmTeAfv/vOuen/ApsIDyZORJ+XW1dpVBtWqqusFUc3dFgXYypuWh3cV70KD9lnHZuFGwg1YmFioC8tNCSqNE0uAdn0+A77+GnjrLWDuXBi3bIO5exXKD07HjsDFi8qAfv9+uDh4yPvb2sBUjqavnP8u0o0Bb0dvuSTcs8R8+Vrla8l9sV77vpvKoL1D9Q6Fvh+elZTF6FSZA2KZNSIiIiIiKpneaNDetWtXdOrUCS4uLnB1dcXMmTNRpkwZnD59GnXr1sWmTZtkm+rVq8uAXlz/zz//qEfS9+3bh9DQUPz111/w8PBAx44dMWPGDMyfP18G8vTfiZFssbb4ixBzxcftHidTtgdsLHokd0HgAqRmpcrl0kSq9/E7x3EtXllgTRNxvfCWw1vwtFMGrGIkPSsn67m2It1eLG8mjGk4Rnk7UVldAWQfPADcvq2sxp6bK69LykjCd8eV873nd5ovA3ckJGDQ8iA0u/v8cykXGS+3Z4f7ALt2Ae7uQLNmgLEx3G3d5XXBscGyeNy2+OPq5dUKopqLfuDmAfXrLDJof/IeCObG5nJJNyIiIiIiKpm0pnq8GDXfsGEDUlNTZZq8JiI1XqTRG4pK2wBOnToFNzc32IrlsJ7w8fHBmDFj5Gh9/frKol3PysjIkCeVpKQkuc3KypInXaR63WJ78+FNeC31gomhCY4PO47aNqL2ecHyjq5fT7iO0NhQuJRz0dhWVF5fdl5Z+d3Px0/OD98Tvgerg1djqrcy3ftZR28rl1HzquyFKuZVZGAtgu2L0RdRz7ZevrZT9k+Ry7WJx+9cvTOy0tPhtTME/n8C7W7dA36tKtsp3N2RvW0bNjw4gP6Bj9EiqSwGZoQiZ/NXgKkpDJ7cX47IOv/oY/FHg4yE+zBdtxE/eQE9f5j/3N+Km42bOgsgKS1JrtkutKnapsC/q0Z2jbD8wnL8HPCzPC/mplc1r1ro32FP155Yd2kdgqKD8L7n+zBQGPzrv9u8/U26gX2uW9jfuod9rlvY37qHfV4yvehv8TcetIeEhMgg/fHjx3KUfcuWLahd+/kgMT4+Xo6iv/fee+rLYmJi8gXsguq8uK4gs2bNwtci5fkZYuRezI3XZf7+/tgQuwFZuVnIysxC11Vd4VfDr9Alwv6OVi5/pvLVlq8wyG6QxrYBiQGIS4tDWcOy0L+hD9csV+zBHqwIXIEGyQ2eax+XGYdTd0/JfYuj93Bl+QT4mFTABsskrNy3Eu2s26nbPgjchiErlqNWJaBeeWvEb+gA68uXYZmQgKetlPREMbg6dVDLXh+jZJb5Q+DQrHxtxvsCB2qXxkzvljJl/lDCIax2AMzKV4XziUsIwaV87XMUOTDWM5YHFP639n9yTryVoRUiAyNxV++u5oMY6fkzQlwNXdV1HQrzuc3nyC2fC/10fewSI/7/j/4m3cI+1y3sb93DPtct7G/dwz4vWdLSlKtXaX3QLgrNXbhwQY6ib9y4EcOGDcORI0fyBe5iJFzMXReXfSWKgv0/TZkyBRMmTMh3/w4ODujQoYMcydfVozziS6B9+/aYuuLpiHfk40g4NXaShdkKSo3/dOGncr+dUzu5vnm4Xric9qDJP7uUVd8H1huIbj7d0DilMZb8+AvisyPRad0aGJiWQY4o2PaksNq0w9OggALjMxug71c/QS85GesB7HABrJz2o1nWZSjatJFLrGXM+wumaUATWdfu9NPnaGiIf3ydMMPuOhZHecLd3AV6Z87A6OZNNCugoHxO7dpY1iAUqcbpaNSqEcqVLoevV3yN+2WAdzwHolNLza+v4YOGOHn3JI5nKlPdW1RrIf92C5KTm4MpP06RFfGFUS1HoVNNzff9qvrbyMjolT8evXnsc93C/tY97HPdwv7WPezzkkmV8a31QbuxsTGcnZ3lvqenJwIDA+Hn54dFixbJy5KTk+Hr6wtzc3M5Cp83wKhYsSLOnDmT7/5iY2PV1xXExMREnp4l7lvXA5iI5Ahcun8JRvpGcLN1k6nvJ++dhEclZZE1Tanrovq5mFu9sMtCOP/qjHMx55CQkQDbMrbPBfh7b+6V+11qdJHvtX1UEu7O00PZdLGG+jp5nX7XrrLI295dv+LClh9gbw3MWRYGveQUwNAQubk56HJdAVy/CuAqcOiQvJ3IkUg3BBK7tEdFx9rijwC4cQN6ffrgmnkIgvZPwsz2TtjQd42c0/7VD52hv2sPHKrUwYg/Q5RP8uOPgQsXYPD337DZ5I3URxEITwzH1rCtck10UTxufNPxBf6dNK7cWAbtqmr3Ys56YX9TRjDC2EZj8VfwXxjuMRx96/YtNKvhZePfvO5hn+sW9rfuYZ/rFva37mGflywvGnu+8aD9Wbm5uer55uLIg5ijLgLs7du3o1SpUvnairR6UZwuLi5OLvcmiNFDMVquKcVeV4lgWVRHr16uepEBoXr+uIOXHDkXQfuR20dkYKmJan56/zr95f3Xr1hfBrd7w/diaN1BwJEjQJMmgJmZDGRjHt7F2GBDtGmUDdg8gt7gwU8C9jx69JAbUV7taYm1FHFUBzh2DPeO7sDab/pBYWiATzvOgMHpAKTcvYlZliFY0sIMkVN3AM8smdbwlvIgTVBUkNzGpMXh2wx/5LQBgt5dqR7Zh5+f+jYN7Bog4lEE/MP9cTxSOXI+rcU0uS56QRpVbvRcEF+UHzv8KE9ERERERERaVT1epKkfPXoUERERcm67OH/48GEMGjRIBuwiXV0Uplu6dKk8L+api5MoWieI60VwPmTIEFy8eBF79+7F1KlT8cEHH2gcSddVn+77FK6/uaL6L9UReC+w0LZH7yiD9paOLdGyaku5fyTiiAz8nyXmbm8I3SD3R9QfoV4z3OsOYD/tB6BKFaBtW6B5c5ECgan7PseMg8D8bdkw6dwNKFtWjmpnGBvI4m57xrSXwb1GolbBunVA6dKw79AHM7taYnKbHIQM7whs3Ypf5g3Ady0ArxrtNK5xXq+ismCdCMITHydi85XNcg66CKpVS6g9q3et3nL7d8jfCLgbIPd9nX0Lff+evb5hpYaFticiIiIiItLaoF2MkA8dOlTOa2/btq1MjReBt5hne+7cOQQEBMhgXqTP29nZqU+RkZHy9gYGBtixY4fcilH3wYMHy/v75ptv3uTL0rql234+/bM6YP096PcC24rAXLWWuQjaRUBroGeA2NRYRKdEP9d+/eX1sthaDesa8EqzBqZPx4Rv/HFyGdDmn0tAVJSyoVjLvGJFbBu+F5+feOZO7O2xfsE4TPQBlrW2AoKC5Lrnk3/0Ra0PAL+5/YH584Fr14Dq1eVNRFE4MQquen3Cnht75Nanuublz8ScdHsLe7l/Ke6S+mBDv9r9Cnw/urp2RSnDUrj16Jaccy5S42uWr1lge9XjLOy8UO6L52hZyrLQ9kRERERERFqbHi9G0AvSqlUrjaO7z3J0dPx/Vc8ubr489KUcJXa0csTcDnNRo3yNQtvPOj5LFnIz1DdEdm52oSPtdzPu4m7yXTmf3cuqLkp98hnurQIiTYFb7Y6iUvOna7CLvvnj7B9y/fOxjn2hJ+ahX78OuyfXXy2vhxqlKsv0d+zcKZYJgIGqO8Vly5YBYWFAtWoof/cwsPpnhN4PBWrWlAcC5h8+hlQbwKvfBEBDirlYq/xQxCG5vFqfx31wMvKkvLywNcvFOup3k+7in7B/1NMA+tTuU2B7cxNz9KjZA2svrZXnm1Ru8kLzzd/zfA9VrarC1dq1yLZERERERERaO9JO/87tR7cx4+gMXL5/Gbuu74L3cm+Zol6QlMwU7Ly+U+5vH7BdbkVgnJyRrLH96ujVctvHri1Mm7UEfvsNtok5aBgNNPQdCXzwgUxzR3Awgncth+mJQFxaoIfx3b6VAbugcHHBwCGmqPWhAhcD/xHr6yHhuD86DTNEnbHAxevHgVWrRNUFueSaSHevU0FZmf7ag2vy9ewM24nUrFQ4WTmhUaX8c8SfTTsXc9QP3DogU91FkFytbLUC3w/3Cu5y+/2J75GryEW7au3kwY/CzG47+7nHLIrIBBAHD5zKOr1QeyIiIiIiooIwaC9GAqOejpJXMq+E+2n3cey2Mp1dkw2XN+Bx9mM4l3OWc60dLBzkqHvwlcPA+PHA8ePA338D4eE4eOsgTiWegj70sGCnnjIdvXJlbPmwLULLAyYp6YBYik1UZK9XD/W6jMLhlUCduDzZEOvWQS8sDLFtm+RLXV9zdSN2O2XD2N0D9ZybP/c8q1hWkSn2IhNApLmvu7xOXdxOBMCaqOahB8cGY8vVLXLft3rh881V89pVPmn6CYoignpxwKOzS2d82PjDItsTERERERG9TAzaixFV5fP3GryHjs4d5b6o7A4N0wi2X9uOkdtHyv2+tfvK4FdV2dxi2gzg118Bb2+Zqq5wc0PC8L747DiwO8QDllt3i4IBwObNeDRyENzGAlMm1pep7EK2pTmSjIFcAAnD+gG3bgE3bwL9+uUbkRap68KyC8oK8yM8lMXqNOlWo5vcilR0VXZA/7r9C2xfvWx1WJpYIiMnQy6XJvSs1bPQ90+k1Ks0d2heZFE5la41umLH2zsKrRpPRERERET0KjBoL4Yj7SIoFoXiBN/Plygrrot54mlp6vnmk/wnyf06NnUwwWsCkJqK4SFGGHEOcNuRf167Xno6Bp5Kxpz9QIdN55UXfv890LixLLyWqw/8XSlemQIfH48Bi9rDZhIw4s9eKLdiHVC1KuDk9FxwLA4yiJFwsWycqOg+yG1Qga+te43ucitGzUV2gMgKqGebf2Q833POU4xOqGBWAd5VvAt9/1ysXbCh7wb83etvHBx28LWuh05ERERERPRfaN067aSZmIOtSjcXI+aiSrlrPNDm3ENlA5Hm7u4OTJqEE3eOo9eWaxgaoocqf/8A09LWQO/e6LplC7qq7rBlS6BZM+S28MZvvw6B4sEDeOVWQ6NsS+h16ABMmCCbqQrdRSZFIjkrFXrmJvjn+g5kGgIT2n9ZZOr6vNPz1EG5tal1gd3b1L6pDNTF4whiFLyg1HiVofWGymJ0Qq+avWCgb1Dkn09hheeIiIiIiIi0DYP2YuJGwg0kZiTKJcjE6LmRgRE+ulEeQPzTRmJ0PCoKTptX4DsZ+yqAQcMANzfg4EF1s2UeQNe/F8Omsgv23diDjxo/gIWJBRa5zkT9rr1hJIrEPSEODlQ2r4x7yfdwIeYCHqQ/QGZOpiz4JqqxF5a6Lp7vigsr5GXjm4wv9PWJgPv9hu/ji4NfyPMvkro+3GO4nNsvCtd90UJ5OyIiIiIiopKE+cHFhAiC57WZg4vbK8Ooc1egb1+M3aMM2L8d6QK4uAAJCYCfHypHJj694f37TwP2b79Frd9qYlQP4ExqmLzIL8BPboe7D0dpg9JFVmrfEbZD7ndx6VLgSLi4PG9AL5ZKE3PIi/JOg3dgYmACc2NztHFq80LvS4fqHeDX0U+mxxMREREREZU0DNqLCdsytvj4ujVcz4QDe/cCGzfKy8Osgdm21xG5ZhHQqRPSyllgXEfAe05NKMQc9G+/BZYuBQICgC++QOMna56fuXcGYQ/CZLV2PehhbMOxBT62atm1M1Fn1EXiurh2KfT5etl7qfd/9v25yFR3QQTeF96/gIB3AmBVyuoF3xkiIiIiIqKSi+nxxUV2NjBzZv7Lli3D8OxFSI0KwDHjaLy9cyd8lnvj+J3jmOc9GnrOzjJQz+sth7fw58U/se3aNpkSrxqtFunuV3G10JF2UdldKGNcBi0cWxT6dD9q+hGycrNkCntBafSaiMJ3REREREREpMSR9uLi8GHlsmo2NsCmTcCuXcCIEWhorxw5D7wXiJTMFJy+ezpfNfZn9a7dW1Zyvxh7Eb+e+VVe1q5au0IfWhW0q/hU94GJoUmhtxFzzef6zP1XATsRERERERHlx6C9uGjXDjh3DvjjD6BXL6Bjx3yp62I5ODHCnp2bjapWVeFU9ukSbHmJwnJdXZU15G8n3pbbopZKE1Xf87YpKjWeiIiIiIiIXg4G7cVJ/fpAjx75LhLLvwliLfR94fvkfpuqhRdxG9so//z1vOudF2RTv03yAEHFMhXVQT8RERERERG9WgzaizlXa1c5Nz09O129Jnprp9aF3kZUZleNlrev1l4uH1cUGzMbnH7nNCI/iSx0vXUiIiIiIiJ6eRi0F3P6evqykJyKqZEputXoVuTt1vZeix/b/4hfO/76rx7LUJ+1C4mIiIiIiF4XBu0lwEdNPlLvi9R1VVX4wpgZm+HTZp+iRvkar/jZERERERER0X/FoL0EaO7QXBaKE6PgE5tNfNNPh4iIiIiIiF4S5jqXAHp6etj59k7cT7sv11snIiIiIiKikoFBewlhbmIuT0RERERERFRyMD2eiIiIiIiISEsxaCciIiIiIiLSUgzaiYiIiIiIiLQUg3YiIiIiIiIiLcWgnYiIiIiIiEhLMWgnIiIiIiIi0lIM2omIiIiIiIi0FIN2IiIiIiIiIi3FoJ2IiIiIiIhISzFoJyIiIiIiItJSDNqJiIiIiIiItBSDdiIiIiIiIiItxaCdiIiIiIiISEsxaCciIiIiIiLSUoZv+gloA4VCIbdJSUnQVVlZWUhLS5PvgZGR0Zt+OvSKsb91D/tct7C/dQ/7XLewv3UP+7xkUsWfqni0IAzaASQnJ8s3w8HB4XX0DREREREREZE6HrW0tERB9BRFhfU6IDc3F1FRUTA3N4eenh509SiPOGgRGRkJCwuLN/106BVjf+se9rluYX/rHva5bmF/6x72eckkQnERsFeqVAn6+gXPXOdIu5jYr68Pe3v719k/WksE7AzadQf7W/ewz3UL+1v3sM91C/tb97DPS57CRthVWIiOiIiIiIiISEsxaCciIiIiIiLSUgzaSTIxMcH06dPllko+9rfuYZ/rFva37mGf6xb2t+5hn+s2FqIjIiIiIiIi0lIcaSciIiIiIiLSUgzaiYiIiIiIiLQUg3YiIiIiIiIiLcWgnYiIiIiIiEhLMWgvQY4ePYquXbuiUqVK0NPTw9atW/NdHxsbi+HDh8vrTU1N4evri+vXrz93P6dOnUKbNm1gZmYGCwsLtGjRAunp6errExISMGjQIHmdlZUVRo0ahZSUlNfyGunl9XdERIS8nabThg0b1O3u3LmDzp07y/uoUKECPvvsM2RnZ7MriulnPCYmBkOGDEHFihXlZ7xBgwbYtGlTvjb8jJec/g4PD0fPnj1hY2Mjv7P79esnb5cX+1s7zJo1C40aNYK5ubn8ru3RoweuXbuWr83jx4/xwQcfwNraGmXKlEHv3r2f688X+c4+fPiw/OyLatTOzs5YsWLFa3mN9Gr6fPz48fD09JT96eHhofFtDg4Ohre3N0qVKgUHBwfMmTOH3VEM+/vixYsYOHCg7MPSpUujVq1a8PPze+6x+BkveRi0lyCpqamoV68e5s+f/9x1CoVCfjncvHkT27Ztw/nz5+Ho6Ih27drJ2+UN2MUPvw4dOuDMmTMIDAzEhx9+CH39p38qImC/fPky/P39sWPHDvnD8r333nttr5NeTn+LL/zo6Oh8p6+//lr+I9GxY0fZJicnR/74y8zMxMmTJ7Fy5Ur54+7LL79kNxTTz/jQoUPlj4Tt27cjJCQEvXr1koGcaK/Cz3jJ6G+xFd/lIuA/ePAgTpw4IT/L4kBAbm6u+r7Y39rhyJEj8sf66dOn5b+vWVlZsv/yfn4/+eQT/PPPP/LAqmgfFRUlP8MqL/KdfevWLdmmdevWuHDhAj7++GO888472Lt372t/zbruZfS5ysiRI9G/f3+Nj5OUlCTvV3xHnD17Fj/88AO++uor/PHHH6/09dHL72/RfyLg/+uvv+Rv8S+++AJTpkzBb7/9pm7Dz3gJpaASSXTtli1b1OevXbsmL7t06ZL6spycHIWNjY1i8eLF6suaNGmimDp1aoH3GxoaKu8nMDBQfdnu3bsVenp6inv37r2S10Kvrr+f5eHhoRg5cqT6/K5duxT6+vqKmJgY9WULFixQWFhYKDIyMtg1xbDPzczMFH/++We++ypXrpy6DT/jJae/9+7dKz+/iYmJ6jaPHj2S39f+/v7yPPtbe8XFxck+PnLkiLrvjIyMFBs2bFC3uXLlimxz6tSpF/7OnjRpkqJOnTr5Hqt///4KHx+f1/TK6GX2eV7Tp09X1KtX77nLf//9d0XZsmXz/bs9efJkRY0aNdgZxbi/VcaOHato3bq1+jw/4yUTR9p1REZGhtyKtCgVMXouUqmOHz8uz8fFxSEgIEAewWvWrBlsbW3RsmVL9fWqkXiREt+wYUP1ZWJkR9yXuC0Vn/5+ljh6K0ZdxHSHvP3t5uYm/xZUfHx85FF7cYSXil+fi8/2unXrZEq0GG1du3atTMdr1aqVvJ6f8ZLT36KNGGUXl6mI9qKdqg37W3slJibKbbly5dTf0WJkTvybq1KzZk1UqVJF9uOLfmeLNnnvQ9VGdR9UvPr8RYi2YqqjsbFxvj4XWVcPHz58qa+BXn9/i/tR3YfAz3jJxKBdR6g+9CKFRnxBi9S577//Hnfv3pVp0YJIsxREytS7776LPXv2yDlvbdu2Vc+TFPNhRVCfl6GhofyyENdR8envZy1dulTOjRJBnYro07w//gTVefZ38ezz9evXyx8FYr6cCOZGjx6NLVu2yHmtAj/jJae/mzZtKusWTJ48GWlpaTIFc+LEiTKFWtWG/a2dxAE1kbbevHlz1K1bV91XIugSB86f/U5WfR+/yHd2QW1EYJ+3fg0Vjz5/Efy3vOT2t5gGIw7E552mys94ycSgXUcYGRlh8+bNCAsLkwG2KFBz6NAhOXdZNV9dNcdR/IgfMWIE6tevj3nz5qFGjRpYtmzZG34F9LL7Oy/xQ2316tX5RtmpZPb5tGnT8OjRI+zfvx9BQUGYMGGCnNMu5rdTyepvUXxOzIsU8yNFrQpLS0vZ9+JgrKbvAdIeYt7rpUuXZCYM6Qb2uW55Gf0tbt+9e3dMnz5dzo2nks3wTT8Ben1EZVGR/izSaMSojPhB16RJE3Wqu52dndzWrl073+3E6KuoRiuIitMijT4vUZVWpNqK66j49HdeGzdulCNxokhZXqJPRUHCvFRVTNnfxa/PRSVxUaxG/ENfp04deZkodHbs2DFZ7GzhwoX8jJewz7j4ISf6PT4+XmZFiREc8dmtVq2avJ7f6dpHFH9VFXm1t7dXXy76SvSzOPCSdyROfCervo9f5DtbbJ+tPi7Oi9UFRDVqKl59/iIK6nPVdVT8+js0NFRmwooR9qlTp+a7jp/xkomH2nWQGG0RP+5EyrsYaRNH6YSqVavKpYOeXX5CjOSIiqOCl5eX/DIR825URFViMUovfixS8envZ1Pju3XrJtvlJfpbjMDmPVAjKp6KH3fPHtwh7e9zcWBGeHaU1cDAQJ1pw894yfyMly9fXv4IFN/X4vMsPu8C+1t7iHqD4se8mK4i+snJyem5gzQiw+LAgQPqy8S/1+KguujHF/3OFm3y3oeqjeo+qHj1+YsQbUWAKKZG5e1zkUlZtmzZl/Rq6HX1t6hPIVZ/GDZsGGbOnPnc4/AzXkK96Up49PIkJycrzp8/L0+ia+fOnSv3b9++La9fv3694tChQ4rw8HDF1q1bFY6OjopevXrlu4958+bJKrOicuX169dlJflSpUopbty4oW7j6+urqF+/viIgIEBx/PhxhYuLi2LgwIHsymLY34LoZ1FNWqwC8Kzs7GxF3bp1FR06dFBcuHBBsWfPHlmdesqUKa/lNdLL7fPMzEyFs7OzwtvbW35+xef6xx9/lP2/c+dOdTt+xkvOZ3zZsmWy6rDo61WrVsmVAiZMmJCvDftbO4wZM0ZhaWmpOHz4sCI6Olp9SktLU7d5//33FVWqVFEcPHhQERQUpPDy8pKnf/OdffPmTYWpqanis88+k5Wp58+frzAwMJBtqfj1uerfcfHdMHr0aIWrq6v6e0NVLV5UJbe1tVUMGTJErjixdu1a+TewaNEidnkx6++QkBD5mR48eHC++xCV6FX4GS+ZGLSXIOLHm/hh9+xp2LBh8no/Pz+Fvb29XE5CfCGIgFzTsl2zZs2S7cQXuviiOHbsWL7rHzx4IIP0MmXKyAB/xIgR8sclFc/+Fj/mHBwc5HJRmkRERCg6duyoKF26tKJ8+fKKTz/9VJGVlfXKXx+9mj4PCwuTgV2FChXkZ9zd3f25JeD4GS85/S2WdRI/1kUbcYD1p59+UuTm5uZrw/7WDpr6WpyWL1+ubpOeni6XdxLLd4nPb8+ePeUP9n/7nS3+tsQSn8bGxopq1arlewwqfn3esmVLjfdz69YtdZuLFy8q3nrrLYWJiYmicuXKitmzZ7Ori2F/i2X9NN2HOGibFz/jJY+e+N+bHu0nIiIiIiIioudxTjsRERERERGRlmLQTkRERERERKSlGLQTERERERERaSkG7URERERERERaikE7ERERERERkZZi0E5ERERERESkpRi0ExEREREREWkpBu1EREREREREWopBOxEREREREZGWYtBOREREREREpKUYtBMREem4R48eQU9P77mTlZXVm35qREREOo9BOxEREUmbNm1CdHS0PP388898V4iIiLQAg3YiIiIdl52dLbfW1taoWLGiPFlaWuZrM3fuXLi5ucHMzAwODg4YO3YsUlJS5HWHDx/WOFKvOgkPHjzAwIEDUblyZZiamsr7WrNmzRt4tURERMULg3YiIiIdl5GRIbcmJiYFttHX18cvv/yCy5cvY+XKlTh48CAmTZokr2vWrJl6hF6M1guq8+IkPH78GJ6enti5cycuXbqE9957D0OGDMGZM2dey2skIiIqrvQUCoXiTT8JIiIienNCQkLg7u4ug+k6derIy1asWIGPP/5YznfXZOPGjXj//fcRHx+f73Ix6t66dWu8yM+LLl26oGbNmvjxxx9f0ishIiIqeQzf9BMgIiKiN+vevXtya2dnV2Cb/fv3Y9asWbh69SqSkpJkSr0YPU9LS5Pp7kXJycnBd999h/Xr18vHy8zMlCP8L3JbIiIiXcb0eCIiIh0XGhoKGxsblCtXTuP1ERERclRcjMaL9PezZ89i/vz58joRfL+IH374AX5+fpg8eTIOHTqECxcuwMfH54VvT0REpKs40k5ERKTjDhw4IOelF0QE6bm5ufjpp5/k3HZBjJj/GydOnED37t0xePBgeV7cX1hYGGrXrv3/fPZEREQlG0faiYiIdFR6ejqWLl2K3bt3y1HvmJgY9SkxMVHOSxf7zs7OyMrKwq+//oqbN29i1apVWLhw4b96LBcXF/j7++PkyZO4cuUKRo8ejdjY2Ff22oiIiEoKFqIjIiLSUaLY3IgRI4psd+vWLWzZskWmuIvCdC1atMCgQYMwdOhQPHz4EFZWVkUWoktISMDIkSPlqL6Yxy6qx9+5c0ceHNi6desreX1EREQlAYN2IiIiHQ7axUkE2gUR66yLoL1q1aqv9bkRERGREtPjiYiIdFTp0qULLD6nYmtrCwMDg9f2nIiIiCg/jrQTERERERERaSmOtBMRERERERFpKQbtRERERERERFqKQTsRERERERGRlmLQTkRERERERKSlGLQTERERERERaSkG7URERERERERaikE7ERERERERkZZi0E5EREREREQE7fR/zJ1zeJPMtb4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 5))\n",
    "\n",
    "plt.plot(co2_df[\"Date\"], co2_df[\"Average\"], label=\"Average\", color=\"green\")\n",
    "plt.plot(co2_df[\"Date\"], co2_df[\"Interpolated\"], label=\"Interpolated\", color=\"red\")\n",
    "\n",
    "plt.title(\"Динамика концентрации CO2 во времени\")\n",
    "plt.xlabel(\"Дата\")\n",
    "plt.ylabel(\"CO2, ppm\")\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "5f483a8c-6fef-45f4-99c2-91290ed2c768",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Обработка CO2: 100%|██████████████████████████████████████████████████████████████| 816/816 [00:00<00:00, 29822.26it/s]\n"
     ]
    }
   ],
   "source": [
    "for index, row in tqdm(co2_df.iterrows(), total=len(co2_df), desc=\"Обработка CO2\"):\n",
    "    value = row[\"Average\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "baae89a1-06ac-48cd-819c-8822a37c10ce",
   "metadata": {},
   "source": [
    "С помощью tqdm был добавлен прогресс-бар для обработки строк датасета"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96d71efd-bb67-42f6-a03b-64160eecf0d4",
   "metadata": {},
   "source": [
    "- Выводы:\n",
    "В самостоятельном задании был использован датасет CO2 PPM - Trends in Atmospheric Carbon Dioxide с сайта DataHub\n",
    "По результатам анализа видно, что концентрация CO2 в атмосфере увеличивается с течением времени. В начале датасета значения CO2 были около 315 ppm, а в последних наблюдениях превышают 429 ppm. Максимальное значение `Average` в данных достигает 430.51 ppm"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}