diff --git a/.gitignore b/.gitignore
index 0949605..c1cac32 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,4 @@
 .venv/
-.idea/
\ No newline at end of file
+.idea/
+.ipynb_checkpoints/
+train.csv
\ No newline at end of file
diff --git a/week2_analysis.ipynb b/week2_analysis.ipynb
new file mode 100644
index 0000000..7cb6873
--- /dev/null
+++ b/week2_analysis.ipynb
@@ -0,0 +1,1982 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "528837f1-b656-463f-a39c-9d58ede4bf96",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:30.896553800Z",
+     "start_time": "2026-04-29T17:28:30.845984Z"
+    },
+    "jp-MarkdownHeadingCollapsed": true
+   },
+   "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",
+      "4  Дмитрий       20     91\n",
+      "<class 'pandas.DataFrame'>\n",
+      "RangeIndex: 5 entries, 0 to 4\n",
+      "Data columns (total 3 columns):\n",
+      " #   Column   Non-Null Count  Dtype\n",
+      "---  ------   --------------  -----\n",
+      " 0   Имя      5 non-null      str  \n",
+      " 1   Возраст  5 non-null      int64\n",
+      " 2   Баллы    5 non-null      int64\n",
+      "dtypes: int64(2), str(1)\n",
+      "memory usage: 252.0 bytes\n",
+      "None\n",
+      "         Возраст      Баллы\n",
+      "count   5.000000   5.000000\n",
+      "mean   22.000000  86.600000\n",
+      "std     1.581139   7.569676\n",
+      "min    20.000000  76.000000\n",
+      "25%    21.000000  82.000000\n",
+      "50%    22.000000  89.000000\n",
+      "75%    23.000000  91.000000\n",
+      "max    24.000000  95.000000\n",
+      "Имя        0\n",
+      "Возраст    0\n",
+      "Баллы      0\n",
+      "dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Ячейка 1: Импорт и создание DataFrame\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from tqdm import tqdm\n",
+    "import time\n",
+    "\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\", \"Дмитрий\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24, 20],\n",
+    "    \"Баллы\": [89, 76, 95, 82, 91]\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())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "ade3384b-139c-48be-9e76-77080707ce4a",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:30.938961500Z",
+     "start_time": "2026-04-29T17:28:30.910423700Z"
+    }
+   },
+   "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>Имя</th>\n",
+       "      <th>Возраст</th>\n",
+       "      <th>Баллы</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",
+       "    </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",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Дмитрий</td>\n",
+       "      <td>20</td>\n",
+       "      <td>91</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "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\n",
+       "4  Дмитрий       20     91"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Ячейка 2: Поместить df в последнюю строчку блока\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "d7b68944-00f3-4337-8f29-be1165655b19",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:30.978835700Z",
+     "start_time": "2026-04-29T17:28:30.940467500Z"
+    }
+   },
+   "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>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",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Дмитрий</td>\n",
+       "      <td>20</td>\n",
+       "      <td>91</td>\n",
+       "      <td>100.1</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\n",
+       "4  Дмитрий       20     91          100.1"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Ячейка 3: Добавить новый столбец с вычисляемыми значениями\n",
+    "df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "31c3402f-55b8-4f6d-b532-211b3587c3cb",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.006495900Z",
+     "start_time": "2026-04-29T17:28:30.980342900Z"
+    }
+   },
+   "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 tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\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 colspan=\"4\" halign=\"left\">Баллы</th>\n",
+       "      <th colspan=\"3\" halign=\"left\">Возраст</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>mean</th>\n",
+       "      <th>min</th>\n",
+       "      <th>max</th>\n",
+       "      <th>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>min</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Возрастная группа</th>\n",
+       "      <th></th>\n",
+       "      <th></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>22 и старше</th>\n",
+       "      <td>84.333333</td>\n",
+       "      <td>76</td>\n",
+       "      <td>95</td>\n",
+       "      <td>3</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>22</td>\n",
+       "      <td>24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Моложе 22</th>\n",
+       "      <td>90.000000</td>\n",
+       "      <td>89</td>\n",
+       "      <td>91</td>\n",
+       "      <td>2</td>\n",
+       "      <td>20.5</td>\n",
+       "      <td>20</td>\n",
+       "      <td>21</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       Баллы               Возраст        \n",
+       "                        mean min max count    mean min max\n",
+       "Возрастная группа                                         \n",
+       "22 и старше        84.333333  76  95     3    23.0  22  24\n",
+       "Моложе 22          90.000000  89  91     2    20.5  20  21"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Ячейка 4: Применить .groupby() и .agg(), чтобы сгруппировать данные\n",
+    "# Создадим группу по возрастным категориям\n",
+    "df[\"Возрастная группа\"] = df[\"Возраст\"].apply(lambda x: \"Моложе 22\" if x < 22 else \"22 и старше\")\n",
+    "\n",
+    "grouped = df.groupby(\"Возрастная группа\").agg({\n",
+    "    \"Баллы\": [\"mean\", \"min\", \"max\", \"count\"],\n",
+    "    \"Возраст\": [\"mean\", \"min\", \"max\"]\n",
+    "})\n",
+    "grouped"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "0c3bd71d-b471-4028-a753-f1053e91677a",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.030281400Z",
+     "start_time": "2026-04-29T17:28:31.009498200Z"
+    }
+   },
+   "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>Имя</th>\n",
+       "      <th>Возраст</th>\n",
+       "      <th>Баллы</th>\n",
+       "      <th>Новый столбец</th>\n",
+       "      <th>Возрастная группа</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",
+       "      <td>22 и старше</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>22 и старше</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>22 и старше</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Имя  Возраст  Баллы  Новый столбец Возрастная группа\n",
+       "1   Борис       22     76           83.6       22 и старше\n",
+       "2  Виктор       23     95          104.5       22 и старше\n",
+       "3  Галина       24     82           90.2       22 и старше"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Ячейка 5: Фильтровать записи по условиям (Возраст > 21)\n",
+    "df[df[\"Возраст\"] > 21]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7e72b540-043b-42fd-94c6-c77ea3385526",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.047668800Z",
+     "start_time": "2026-04-29T17:28:31.031287500Z"
+    }
+   },
+   "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": [
+    "# Ячейка 6: NumPy - простой массив и статистика\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": 7,
+   "id": "97ea3224-c27e-49d6-8e46-8dfdf9a68296",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.071219200Z",
+     "start_time": "2026-04-29T17:28:31.050206500Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Двумерный массив:\n",
+      "[[1 2]\n",
+      " [3 4]]\n",
+      "\n",
+      "Сумма всех элементов: 10\n",
+      "Транспонированный массив:\n",
+      " [[1 3]\n",
+      " [2 4]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Ячейка 7: Создать двумерный массив\n",
+    "arr2d = np.array([[1, 2], [3, 4]])\n",
+    "print(\"Двумерный массив:\")\n",
+    "print(arr2d)\n",
+    "print(\"\\nСумма всех элементов:\", np.sum(arr2d))\n",
+    "print(\"Транспонированный массив:\\n\", arr2d.T)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "1a1fa6f1-1555-4ce2-89f1-a09c0db43349",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.091197600Z",
+     "start_time": "2026-04-29T17:28:31.072217700Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "np.linspace(0, 10, 6): [ 0.  2.  4.  6.  8. 10.]\n",
+      "\n",
+      "np.random.randn(5): [ 0.09741999 -0.05418549  0.15909255  0.52113092 -0.68057794]\n",
+      "\n",
+      "Скалярное произведение [1,2,3] и [4,5,6]: 32\n",
+      "\n",
+      "Матричное умножение:\n",
+      " [[ 7 10]\n",
+      " [15 22]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Ячейка 8: Использовать np.linspace(), np.random.randn(), np.dot()\n",
+    "# np.linspace() - линейно расположенные числа\n",
+    "lin = np.linspace(0, 10, 6)  # 6 точек от 0 до 10\n",
+    "print(\"np.linspace(0, 10, 6):\", lin)\n",
+    "\n",
+    "# np.random.randn() - случайные числа из нормального распределения\n",
+    "rand = np.random.randn(5)\n",
+    "print(\"\\nnp.random.randn(5):\", rand)\n",
+    "\n",
+    "# np.dot() - скалярное произведение векторов\n",
+    "a = np.array([1, 2, 3])\n",
+    "b = np.array([4, 5, 6])\n",
+    "print(\"\\nСкалярное произведение [1,2,3] и [4,5,6]:\", np.dot(a, b))\n",
+    "\n",
+    "# Дополнительно: dot для двумерных матриц\n",
+    "print(\"\\nМатричное умножение:\\n\", np.dot(arr2d, arr2d))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "fb402089-89b9-4cf6-901e-e4ad700237fe",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.199092200Z",
+     "start_time": "2026-04-29T17:28:31.093198100Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Ячейка 9: matplotlib - график синуса\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# Ячейка 9\n",
+    "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": 10,
+   "id": "d1e46af4-27ae-44c5-a03f-075ce8badce0",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.312190800Z",
+     "start_time": "2026-04-29T17:28:31.202607600Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Ячейка 10\n",
+    "plt.plot(x, y, label='sin(x)', color='red')\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": 11,
+   "id": "c34f00c4-fb94-4cf6-b4f8-634303552e25",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.411507200Z",
+     "start_time": "2026-04-29T17:28:31.315251500Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Ячейка 11\n",
+    "plt.plot(x, np.sin(x), label='sin(x)')\n",
+    "plt.plot(x, np.cos(x), label='cos(x)')\n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Графики синуса и косинуса\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b6153a84-c250-4980-9565-e90423c388bb",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.654361700Z",
+     "start_time": "2026-04-29T17:28:31.417334200Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Ячейка 12\n",
+    "plt.bar([\"A\", \"B\", \"C\", \"D\"], [10, 20, 15, 25])\n",
+    "plt.title(\"Столбчатая диаграмма\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.scatter([1, 2, 3, 4, 5], [2, 4, 6, 8, 10])\n",
+    "plt.title(\"Диаграмма рассеяния\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.hist([1, 2, 2, 3, 3, 3, 4, 4, 5], bins=5)\n",
+    "plt.title(\"Гистограмма\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "6a4afde3-e348-4c26-98ef-7335076fa498",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.744720500Z",
+     "start_time": "2026-04-29T17:28:31.656870Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Ячейка 13\n",
+    "df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\", \"A\"]\n",
+    "sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "77c0e316-3750-4260-9e6a-bc1ff1b6414d",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:31.918812800Z",
+     "start_time": "2026-04-29T17:28:31.745720900Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Ячейка 14\n",
+    "sns.histplot(df[\"Баллы\"], bins=5)\n",
+    "plt.show()\n",
+    "\n",
+    "sns.scatterplot(x=\"Возраст\", y=\"Баллы\", data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "1afddb1b-7cd3-4f0d-8efe-3c951300b95f",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:32.324019300Z",
+     "start_time": "2026-04-29T17:28:31.922333400Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 500x500 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Ячейка 15\n",
+    "sns.pairplot(df[[\"Возраст\", \"Баллы\"]])\n",
+    "plt.show()\n",
+    "\n",
+    "sns.heatmap(df[[\"Возраст\", \"Баллы\"]].corr(), annot=True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "a5310486-5e60-44d5-afd3-edde67b91be7",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-04-29T17:28:32.333615100Z",
+     "start_time": "2026-04-29T17:28:32.325029700Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 94.36it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Ячейка 2: Базовый пример tqdm\n",
+    "for i in tqdm(range(100)):\n",
+    "    time.sleep(0.01)  # Симуляция долгого процесса"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "425c6b1b-773a-453b-ad8d-7615a0743746",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка строк: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:02<00:00,  1.99it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Ячейка 3: tqdm для обработки данных (df.iterrows())\n",
+    "# Симуляция обработки каждой строки DataFrame\n",
+    "for index, row in tqdm(df.iterrows(), total=df.shape[0], desc='Обработка строк'):\n",
+    "    time.sleep(0.5)  # Симуляция обработки\n",
+    "    # Пример: что-то делаем с данными\n",
+    "    result = row[\"Баллы\"] * 1.1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "91ddc825-1b3a-4763-b6ff-1623ffacd87d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Загрузка: 100%|\u001b[32m██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████\u001b[0m| 100/100 [00:01<00:00, 95.02it/s]\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Ячейка 4: Кастомная стилизация с desc\n",
+    "for i in tqdm(range(100), desc='Загрузка', colour='green'):\n",
+    "    time.sleep(0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "99576d76-9f22-4ef7-8bab-9a43e9006881",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Прогресс: 100%|\u001b[34m█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████\u001b[0m| 50/50\u001b[0m\n",
+      "Обработка: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50.0/50.0 [00:01<00:00, 48.2шаг/s]\n",
+      "                                                                                                                                                                                                                                   "
+     ]
+    }
+   ],
+   "source": [
+    "# Ячейка 5: Дополнительные стилизации tqdm\n",
+    "# Разные варианты оформления\n",
+    "\n",
+    "# С цветом\n",
+    "for i in tqdm(range(50), desc='Прогресс', colour='blue', bar_format='{l_bar}{bar}| {n_fmt}/{total_fmt}'):\n",
+    "    time.sleep(0.02)\n",
+    "\n",
+    "# С единицами измерения\n",
+    "for i in tqdm(range(50), desc='Обработка', unit='шаг', unit_scale=True):\n",
+    "    time.sleep(0.02)\n",
+    "\n",
+    "# С leave=False (убирает полосу после завершения)\n",
+    "for i in tqdm(range(30), desc='Быстрая операция', leave=False):\n",
+    "    time.sleep(0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "20d8ba45-8479-4ec5-bef8-8e24e991ac62",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка студентов:  20%|\u001b[31m██████████████████████████████████▏                                                                                                                                        \u001b[0m| 1/5 [00:00<00:01,  3.32it/s]\u001b[0m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Обработан студент: Анна\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка студентов:  40%|\u001b[31m████████████████████████████████████████████████████████████████████▍                                                                                                      \u001b[0m| 2/5 [00:00<00:00,  3.32it/s]\u001b[0m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Обработан студент: Борис\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка студентов:  60%|\u001b[31m██████████████████████████████████████████████████████████████████████████████████████████████████████▌                                                                    \u001b[0m| 3/5 [00:00<00:00,  3.32it/s]\u001b[0m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Обработан студент: Виктор\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка студентов:  80%|\u001b[31m████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                  \u001b[0m| 4/5 [00:01<00:00,  3.32it/s]\u001b[0m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Обработан студент: Галина\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка студентов: 100%|\u001b[31m███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████\u001b[0m| 5/5 [00:01<00:00,  3.32it/s]\u001b[0m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Обработан студент: Дмитрий\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Ячейка 6: Практический пример - обработка списка с tqdm\n",
+    "items = [\"Анна\", \"Борис\", \"Виктор\", \"Галина\", \"Дмитрий\"]\n",
+    "\n",
+    "for name in tqdm(items, desc='Обработка студентов', colour='red'):\n",
+    "    time.sleep(0.3)\n",
+    "    print(f\"Обработан студент: {name}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "f8b58f25-6888-4d19-9c31-136a52452e6f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Применение функции: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:01<00:00,  4.96it/s]\n"
+     ]
+    },
+    {
+     "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>Имя</th>\n",
+       "      <th>Возраст</th>\n",
+       "      <th>Баллы</th>\n",
+       "      <th>Новый столбец</th>\n",
+       "      <th>Возрастная группа</th>\n",
+       "      <th>Категория</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",
+       "      <td>Моложе 22</td>\n",
+       "      <td>A</td>\n",
+       "      <td>178</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>22 и старше</td>\n",
+       "      <td>B</td>\n",
+       "      <td>152</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>22 и старше</td>\n",
+       "      <td>A</td>\n",
+       "      <td>190</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>22 и старше</td>\n",
+       "      <td>B</td>\n",
+       "      <td>164</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Дмитрий</td>\n",
+       "      <td>20</td>\n",
+       "      <td>91</td>\n",
+       "      <td>100.1</td>\n",
+       "      <td>Моложе 22</td>\n",
+       "      <td>A</td>\n",
+       "      <td>182</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Имя  Возраст  Баллы  Новый столбец Возрастная группа Категория  \\\n",
+       "0     Анна       21     89           97.9         Моложе 22         A   \n",
+       "1    Борис       22     76           83.6       22 и старше         B   \n",
+       "2   Виктор       23     95          104.5       22 и старше         A   \n",
+       "3   Галина       24     82           90.2       22 и старше         B   \n",
+       "4  Дмитрий       20     91          100.1         Моложе 22         A   \n",
+       "\n",
+       "   Новый_столбец  \n",
+       "0            178  \n",
+       "1            152  \n",
+       "2            190  \n",
+       "3            164  \n",
+       "4            182  "
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Ячейка 7: tqdm с pandas apply (продвинутый пример)\n",
+    "# Симуляция медленной функции\n",
+    "def slow_calculation(x):\n",
+    "    time.sleep(0.2)\n",
+    "    return x * 2\n",
+    "\n",
+    "# Применяем с визуализацией прогресса\n",
+    "tqdm.pandas(desc='Применение функции')\n",
+    "df[\"Новый_столбец\"] = df[\"Баллы\"].progress_apply(slow_calculation)\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "001e8775-7d53-43ee-aa60-5f306841bc27",
+   "metadata": {},
+   "source": [
+    "6 задание"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "bbb10c7e-87e4-451c-b894-16ac6af3e485",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Строк: 1460, столбцов: 81\n"
+     ]
+    },
+    {
+     "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>Id</th>\n",
+       "      <th>MSSubClass</th>\n",
+       "      <th>MSZoning</th>\n",
+       "      <th>LotFrontage</th>\n",
+       "      <th>LotArea</th>\n",
+       "      <th>Street</th>\n",
+       "      <th>Alley</th>\n",
+       "      <th>LotShape</th>\n",
+       "      <th>LandContour</th>\n",
+       "      <th>Utilities</th>\n",
+       "      <th>...</th>\n",
+       "      <th>PoolArea</th>\n",
+       "      <th>PoolQC</th>\n",
+       "      <th>Fence</th>\n",
+       "      <th>MiscFeature</th>\n",
+       "      <th>MiscVal</th>\n",
+       "      <th>MoSold</th>\n",
+       "      <th>YrSold</th>\n",
+       "      <th>SaleType</th>\n",
+       "      <th>SaleCondition</th>\n",
+       "      <th>SalePrice</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>60</td>\n",
+       "      <td>RL</td>\n",
+       "      <td>65.0</td>\n",
+       "      <td>8450</td>\n",
+       "      <td>Pave</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Reg</td>\n",
+       "      <td>Lvl</td>\n",
+       "      <td>AllPub</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>WD</td>\n",
+       "      <td>Normal</td>\n",
+       "      <td>208500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>20</td>\n",
+       "      <td>RL</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>9600</td>\n",
+       "      <td>Pave</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Reg</td>\n",
+       "      <td>Lvl</td>\n",
+       "      <td>AllPub</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2007</td>\n",
+       "      <td>WD</td>\n",
+       "      <td>Normal</td>\n",
+       "      <td>181500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>60</td>\n",
+       "      <td>RL</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>11250</td>\n",
+       "      <td>Pave</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IR1</td>\n",
+       "      <td>Lvl</td>\n",
+       "      <td>AllPub</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>WD</td>\n",
+       "      <td>Normal</td>\n",
+       "      <td>223500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>70</td>\n",
+       "      <td>RL</td>\n",
+       "      <td>60.0</td>\n",
+       "      <td>9550</td>\n",
+       "      <td>Pave</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IR1</td>\n",
+       "      <td>Lvl</td>\n",
+       "      <td>AllPub</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2006</td>\n",
+       "      <td>WD</td>\n",
+       "      <td>Abnorml</td>\n",
+       "      <td>140000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>60</td>\n",
+       "      <td>RL</td>\n",
+       "      <td>84.0</td>\n",
+       "      <td>14260</td>\n",
+       "      <td>Pave</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>IR1</td>\n",
+       "      <td>Lvl</td>\n",
+       "      <td>AllPub</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>WD</td>\n",
+       "      <td>Normal</td>\n",
+       "      <td>250000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 81 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
+       "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
+       "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
+       "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
+       "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
+       "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
+       "\n",
+       "  LandContour Utilities  ... PoolArea PoolQC Fence MiscFeature MiscVal MoSold  \\\n",
+       "0         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
+       "1         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      5   \n",
+       "2         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      9   \n",
+       "3         Lvl    AllPub  ...        0    NaN   NaN         NaN       0      2   \n",
+       "4         Lvl    AllPub  ...        0    NaN   NaN         NaN       0     12   \n",
+       "\n",
+       "  YrSold  SaleType  SaleCondition  SalePrice  \n",
+       "0   2008        WD         Normal     208500  \n",
+       "1   2007        WD         Normal     181500  \n",
+       "2   2008        WD         Normal     223500  \n",
+       "3   2006        WD        Abnorml     140000  \n",
+       "4   2008        WD         Normal     250000  \n",
+       "\n",
+       "[5 rows x 81 columns]"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_houses = pd.read_csv(\"train.csv\")\n",
+    "print(f\"Строк: {df_houses.shape[0]}, столбцов: {df_houses.shape[1]}\")\n",
+    "df_houses.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "531511cb-60b8-4e26-8aee-a3a4a82c6447",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.DataFrame'>\n",
+      "RangeIndex: 1460 entries, 0 to 1459\n",
+      "Data columns (total 81 columns):\n",
+      " #   Column         Non-Null Count  Dtype  \n",
+      "---  ------         --------------  -----  \n",
+      " 0   Id             1460 non-null   int64  \n",
+      " 1   MSSubClass     1460 non-null   int64  \n",
+      " 2   MSZoning       1460 non-null   str    \n",
+      " 3   LotFrontage    1201 non-null   float64\n",
+      " 4   LotArea        1460 non-null   int64  \n",
+      " 5   Street         1460 non-null   str    \n",
+      " 6   Alley          91 non-null     str    \n",
+      " 7   LotShape       1460 non-null   str    \n",
+      " 8   LandContour    1460 non-null   str    \n",
+      " 9   Utilities      1460 non-null   str    \n",
+      " 10  LotConfig      1460 non-null   str    \n",
+      " 11  LandSlope      1460 non-null   str    \n",
+      " 12  Neighborhood   1460 non-null   str    \n",
+      " 13  Condition1     1460 non-null   str    \n",
+      " 14  Condition2     1460 non-null   str    \n",
+      " 15  BldgType       1460 non-null   str    \n",
+      " 16  HouseStyle     1460 non-null   str    \n",
+      " 17  OverallQual    1460 non-null   int64  \n",
+      " 18  OverallCond    1460 non-null   int64  \n",
+      " 19  YearBuilt      1460 non-null   int64  \n",
+      " 20  YearRemodAdd   1460 non-null   int64  \n",
+      " 21  RoofStyle      1460 non-null   str    \n",
+      " 22  RoofMatl       1460 non-null   str    \n",
+      " 23  Exterior1st    1460 non-null   str    \n",
+      " 24  Exterior2nd    1460 non-null   str    \n",
+      " 25  MasVnrType     588 non-null    str    \n",
+      " 26  MasVnrArea     1452 non-null   float64\n",
+      " 27  ExterQual      1460 non-null   str    \n",
+      " 28  ExterCond      1460 non-null   str    \n",
+      " 29  Foundation     1460 non-null   str    \n",
+      " 30  BsmtQual       1423 non-null   str    \n",
+      " 31  BsmtCond       1423 non-null   str    \n",
+      " 32  BsmtExposure   1422 non-null   str    \n",
+      " 33  BsmtFinType1   1423 non-null   str    \n",
+      " 34  BsmtFinSF1     1460 non-null   int64  \n",
+      " 35  BsmtFinType2   1422 non-null   str    \n",
+      " 36  BsmtFinSF2     1460 non-null   int64  \n",
+      " 37  BsmtUnfSF      1460 non-null   int64  \n",
+      " 38  TotalBsmtSF    1460 non-null   int64  \n",
+      " 39  Heating        1460 non-null   str    \n",
+      " 40  HeatingQC      1460 non-null   str    \n",
+      " 41  CentralAir     1460 non-null   str    \n",
+      " 42  Electrical     1459 non-null   str    \n",
+      " 43  1stFlrSF       1460 non-null   int64  \n",
+      " 44  2ndFlrSF       1460 non-null   int64  \n",
+      " 45  LowQualFinSF   1460 non-null   int64  \n",
+      " 46  GrLivArea      1460 non-null   int64  \n",
+      " 47  BsmtFullBath   1460 non-null   int64  \n",
+      " 48  BsmtHalfBath   1460 non-null   int64  \n",
+      " 49  FullBath       1460 non-null   int64  \n",
+      " 50  HalfBath       1460 non-null   int64  \n",
+      " 51  BedroomAbvGr   1460 non-null   int64  \n",
+      " 52  KitchenAbvGr   1460 non-null   int64  \n",
+      " 53  KitchenQual    1460 non-null   str    \n",
+      " 54  TotRmsAbvGrd   1460 non-null   int64  \n",
+      " 55  Functional     1460 non-null   str    \n",
+      " 56  Fireplaces     1460 non-null   int64  \n",
+      " 57  FireplaceQu    770 non-null    str    \n",
+      " 58  GarageType     1379 non-null   str    \n",
+      " 59  GarageYrBlt    1379 non-null   float64\n",
+      " 60  GarageFinish   1379 non-null   str    \n",
+      " 61  GarageCars     1460 non-null   int64  \n",
+      " 62  GarageArea     1460 non-null   int64  \n",
+      " 63  GarageQual     1379 non-null   str    \n",
+      " 64  GarageCond     1379 non-null   str    \n",
+      " 65  PavedDrive     1460 non-null   str    \n",
+      " 66  WoodDeckSF     1460 non-null   int64  \n",
+      " 67  OpenPorchSF    1460 non-null   int64  \n",
+      " 68  EnclosedPorch  1460 non-null   int64  \n",
+      " 69  3SsnPorch      1460 non-null   int64  \n",
+      " 70  ScreenPorch    1460 non-null   int64  \n",
+      " 71  PoolArea       1460 non-null   int64  \n",
+      " 72  PoolQC         7 non-null      str    \n",
+      " 73  Fence          281 non-null    str    \n",
+      " 74  MiscFeature    54 non-null     str    \n",
+      " 75  MiscVal        1460 non-null   int64  \n",
+      " 76  MoSold         1460 non-null   int64  \n",
+      " 77  YrSold         1460 non-null   int64  \n",
+      " 78  SaleType       1460 non-null   str    \n",
+      " 79  SaleCondition  1460 non-null   str    \n",
+      " 80  SalePrice      1460 non-null   int64  \n",
+      "dtypes: float64(3), int64(35), str(43)\n",
+      "memory usage: 924.0 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_houses.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "189f7354-9c41-4afb-bae5-d81c041eb7fc",
+   "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>Id</th>\n",
+       "      <th>MSSubClass</th>\n",
+       "      <th>LotFrontage</th>\n",
+       "      <th>LotArea</th>\n",
+       "      <th>OverallQual</th>\n",
+       "      <th>OverallCond</th>\n",
+       "      <th>YearBuilt</th>\n",
+       "      <th>YearRemodAdd</th>\n",
+       "      <th>MasVnrArea</th>\n",
+       "      <th>BsmtFinSF1</th>\n",
+       "      <th>...</th>\n",
+       "      <th>WoodDeckSF</th>\n",
+       "      <th>OpenPorchSF</th>\n",
+       "      <th>EnclosedPorch</th>\n",
+       "      <th>3SsnPorch</th>\n",
+       "      <th>ScreenPorch</th>\n",
+       "      <th>PoolArea</th>\n",
+       "      <th>MiscVal</th>\n",
+       "      <th>MoSold</th>\n",
+       "      <th>YrSold</th>\n",
+       "      <th>SalePrice</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1201.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1452.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>1460.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>730.500000</td>\n",
+       "      <td>56.897260</td>\n",
+       "      <td>70.049958</td>\n",
+       "      <td>10516.828082</td>\n",
+       "      <td>6.099315</td>\n",
+       "      <td>5.575342</td>\n",
+       "      <td>1971.267808</td>\n",
+       "      <td>1984.865753</td>\n",
+       "      <td>103.685262</td>\n",
+       "      <td>443.639726</td>\n",
+       "      <td>...</td>\n",
+       "      <td>94.244521</td>\n",
+       "      <td>46.660274</td>\n",
+       "      <td>21.954110</td>\n",
+       "      <td>3.409589</td>\n",
+       "      <td>15.060959</td>\n",
+       "      <td>2.758904</td>\n",
+       "      <td>43.489041</td>\n",
+       "      <td>6.321918</td>\n",
+       "      <td>2007.815753</td>\n",
+       "      <td>180921.195890</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>421.610009</td>\n",
+       "      <td>42.300571</td>\n",
+       "      <td>24.284752</td>\n",
+       "      <td>9981.264932</td>\n",
+       "      <td>1.382997</td>\n",
+       "      <td>1.112799</td>\n",
+       "      <td>30.202904</td>\n",
+       "      <td>20.645407</td>\n",
+       "      <td>181.066207</td>\n",
+       "      <td>456.098091</td>\n",
+       "      <td>...</td>\n",
+       "      <td>125.338794</td>\n",
+       "      <td>66.256028</td>\n",
+       "      <td>61.119149</td>\n",
+       "      <td>29.317331</td>\n",
+       "      <td>55.757415</td>\n",
+       "      <td>40.177307</td>\n",
+       "      <td>496.123024</td>\n",
+       "      <td>2.703626</td>\n",
+       "      <td>1.328095</td>\n",
+       "      <td>79442.502883</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>20.000000</td>\n",
+       "      <td>21.000000</td>\n",
+       "      <td>1300.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1872.000000</td>\n",
+       "      <td>1950.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2006.000000</td>\n",
+       "      <td>34900.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>365.750000</td>\n",
+       "      <td>20.000000</td>\n",
+       "      <td>59.000000</td>\n",
+       "      <td>7553.500000</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>1954.000000</td>\n",
+       "      <td>1967.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>2007.000000</td>\n",
+       "      <td>129975.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>730.500000</td>\n",
+       "      <td>50.000000</td>\n",
+       "      <td>69.000000</td>\n",
+       "      <td>9478.500000</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>1973.000000</td>\n",
+       "      <td>1994.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>383.500000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>25.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>2008.000000</td>\n",
+       "      <td>163000.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>1095.250000</td>\n",
+       "      <td>70.000000</td>\n",
+       "      <td>80.000000</td>\n",
+       "      <td>11601.500000</td>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>2000.000000</td>\n",
+       "      <td>2004.000000</td>\n",
+       "      <td>166.000000</td>\n",
+       "      <td>712.250000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>168.000000</td>\n",
+       "      <td>68.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>8.000000</td>\n",
+       "      <td>2009.000000</td>\n",
+       "      <td>214000.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>1460.000000</td>\n",
+       "      <td>190.000000</td>\n",
+       "      <td>313.000000</td>\n",
+       "      <td>215245.000000</td>\n",
+       "      <td>10.000000</td>\n",
+       "      <td>9.000000</td>\n",
+       "      <td>2010.000000</td>\n",
+       "      <td>2010.000000</td>\n",
+       "      <td>1600.000000</td>\n",
+       "      <td>5644.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>857.000000</td>\n",
+       "      <td>547.000000</td>\n",
+       "      <td>552.000000</td>\n",
+       "      <td>508.000000</td>\n",
+       "      <td>480.000000</td>\n",
+       "      <td>738.000000</td>\n",
+       "      <td>15500.000000</td>\n",
+       "      <td>12.000000</td>\n",
+       "      <td>2010.000000</td>\n",
+       "      <td>755000.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>8 rows × 38 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Id   MSSubClass  LotFrontage        LotArea  OverallQual  \\\n",
+       "count  1460.000000  1460.000000  1201.000000    1460.000000  1460.000000   \n",
+       "mean    730.500000    56.897260    70.049958   10516.828082     6.099315   \n",
+       "std     421.610009    42.300571    24.284752    9981.264932     1.382997   \n",
+       "min       1.000000    20.000000    21.000000    1300.000000     1.000000   \n",
+       "25%     365.750000    20.000000    59.000000    7553.500000     5.000000   \n",
+       "50%     730.500000    50.000000    69.000000    9478.500000     6.000000   \n",
+       "75%    1095.250000    70.000000    80.000000   11601.500000     7.000000   \n",
+       "max    1460.000000   190.000000   313.000000  215245.000000    10.000000   \n",
+       "\n",
+       "       OverallCond    YearBuilt  YearRemodAdd   MasVnrArea   BsmtFinSF1  ...  \\\n",
+       "count  1460.000000  1460.000000   1460.000000  1452.000000  1460.000000  ...   \n",
+       "mean      5.575342  1971.267808   1984.865753   103.685262   443.639726  ...   \n",
+       "std       1.112799    30.202904     20.645407   181.066207   456.098091  ...   \n",
+       "min       1.000000  1872.000000   1950.000000     0.000000     0.000000  ...   \n",
+       "25%       5.000000  1954.000000   1967.000000     0.000000     0.000000  ...   \n",
+       "50%       5.000000  1973.000000   1994.000000     0.000000   383.500000  ...   \n",
+       "75%       6.000000  2000.000000   2004.000000   166.000000   712.250000  ...   \n",
+       "max       9.000000  2010.000000   2010.000000  1600.000000  5644.000000  ...   \n",
+       "\n",
+       "        WoodDeckSF  OpenPorchSF  EnclosedPorch    3SsnPorch  ScreenPorch  \\\n",
+       "count  1460.000000  1460.000000    1460.000000  1460.000000  1460.000000   \n",
+       "mean     94.244521    46.660274      21.954110     3.409589    15.060959   \n",
+       "std     125.338794    66.256028      61.119149    29.317331    55.757415   \n",
+       "min       0.000000     0.000000       0.000000     0.000000     0.000000   \n",
+       "25%       0.000000     0.000000       0.000000     0.000000     0.000000   \n",
+       "50%       0.000000    25.000000       0.000000     0.000000     0.000000   \n",
+       "75%     168.000000    68.000000       0.000000     0.000000     0.000000   \n",
+       "max     857.000000   547.000000     552.000000   508.000000   480.000000   \n",
+       "\n",
+       "          PoolArea       MiscVal       MoSold       YrSold      SalePrice  \n",
+       "count  1460.000000   1460.000000  1460.000000  1460.000000    1460.000000  \n",
+       "mean      2.758904     43.489041     6.321918  2007.815753  180921.195890  \n",
+       "std      40.177307    496.123024     2.703626     1.328095   79442.502883  \n",
+       "min       0.000000      0.000000     1.000000  2006.000000   34900.000000  \n",
+       "25%       0.000000      0.000000     5.000000  2007.000000  129975.000000  \n",
+       "50%       0.000000      0.000000     6.000000  2008.000000  163000.000000  \n",
+       "75%       0.000000      0.000000     8.000000  2009.000000  214000.000000  \n",
+       "max     738.000000  15500.000000    12.000000  2010.000000  755000.000000  \n",
+       "\n",
+       "[8 rows x 38 columns]"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_houses.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "75045618-55b6-4f73-9cb7-98e288cf9e02",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "PoolQC          1453\n",
+       "MiscFeature     1406\n",
+       "Alley           1369\n",
+       "Fence           1179\n",
+       "MasVnrType       872\n",
+       "FireplaceQu      690\n",
+       "LotFrontage      259\n",
+       "GarageQual        81\n",
+       "GarageFinish      81\n",
+       "GarageType        81\n",
+       "GarageYrBlt       81\n",
+       "GarageCond        81\n",
+       "BsmtFinType2      38\n",
+       "BsmtExposure      38\n",
+       "BsmtCond          37\n",
+       "BsmtQual          37\n",
+       "BsmtFinType1      37\n",
+       "MasVnrArea         8\n",
+       "Electrical         1\n",
+       "Condition2         0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_houses.isnull().sum().sort_values(ascending=False).head(20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "fa359eda-af32-4e6e-b9e4-332c1d448ec0",
+   "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(data=df_houses, x='SalePrice', bins=40, kde=True, color='steelblue')\n",
+    "plt.title(\"Распределение цен на дома\")\n",
+    "plt.xlabel(\"Цена ($)\")\n",
+    "plt.ylabel(\"Количество\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "db62cca9-9fe7-4989-8af6-83a3df7a3ae3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Xylann\\AppData\\Local\\Temp\\ipykernel_820\\778300029.py:1: FutureWarning: \n",
+      "\n",
+      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
+      "\n",
+      "  sns.boxplot(data=df_houses, x='OverallQual', y='SalePrice', palette='viridis')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.boxplot(data=df_houses, x='OverallQual', y='SalePrice', palette='viridis')\n",
+    "plt.title(\"Цена в зависимости от общего качества\")\n",
+    "plt.xlabel(\"Общее качество (1-10)\")\n",
+    "plt.ylabel(\"Цена ($)\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "bcbf0718-68a1-4102-9e2a-3db75a871f9b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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HOTr1008/sTBxd3fH+vXrceDAAZSWluL3v/89/vu//xtRUVGDHhsWFoY///nPqvsffPABgoKCOFIUGBiIt956S7WvoKCAC7i3bt3Kz0PHfP755xwNu+OOO+Di4sJdcxRh+vLLL0e8/tbWVjzyyCO44YYb8N5772HWrFmcHnz44YfxySef4JtvvsG2bdv42CNHjvAa1E1QExISeButj7ja9YwWIqoEQRCEaYm29sU/AnX19C66v7mpBdmZeUhOSEdxQSl6unswHlAUat++ffjFL36h8ldSQo7gd911F4sg+hoTE4Pc3FzV/tTUVCQlJeHOO+/k+ySQXnjhBbz00ktIT0/Hyy+/jD/84Q8sbNR59tlnOYpEx6xduxYdHR2IjIzErl27kJKSgp/97Ge45557+PlGAolBEkK/+93vBu3buHEj/P39L0sUXe16Rgvp/hMEQRCmJXYONvDwckNhfvGQ+4NC/IZ9bG52AbZ99iNKi8v5vq6uLuYtisTa61fAynpsuwcp5UepMYouDQVtr6+vh52dHUelvvjiCxZKShFF0StfX1++/+KLL+Lvf/87Nm/ezPe9vLyQlpaGd999F/fdd5/qnFTgrTxGibog+tWvfsVCj6JLc+fOveRryMrKUq11KChipjxmJFCE6mrWM1pIpEoQBEGYlpiYGGPj5jUwNDIYtG/J8vlwdXce8nGV5dX4v7c/VwkqoqenByeOnMHhn46jr29wjdZYMJKaI4pWkahSHk/RH9qmTMFRFOuhhx6Cqamp6kY1TerRLYLqt9ShQvL/+Z//4TSbtbU1P27fvn0oKioatddA6c2RMlrruVokUiUIgiBMWwJD/PDL/3oYcafPITszH2ZmJliwZC78g7xhbKKZWlOSn1uExmE6A08dj8X8xXPg5OIwZmumKBPVE1Eq7qabbhq0n7ZTNx1FqqjO6JlnnsHZs2fR3t7OHYNbtmzh41paWvjr+++/P6j2auCYFhMTE437r732Gt544w22SCAhQ/ufeOIJdHV1jeg1+Pn5qda6YMGCIV8D1Vmpp2nVBdjAYvmrXc9oIaJKEARBmNZ4ervBw8sVnZ2dnMaj28UoK7kQoRpIR3snWzOMJTQLcPXq1VxQ/uSTT2rUVdEQZkrx3XvvvSy8qLOOCsxpG4kqehzNtiMcHBzYjoE6CZXRq5Fy8uRJbNq0CXfffTffp+hcVlYWgoODR/R4qsuiiBKlHgeKqu3bt3OKU+lpReKQKC8vZ7GoLFQfzfWMFpL+EwRBEKY9JECos+1SgoqwtrUedh89fqh04mjz5ptvsggkcXLs2DGOQO3du5dFE9UXUeG5EhJMX331Fb7++utB4ulPf/oTXnnlFfzzn/9kEZKcnIyPPvqIvaIuFWnav38/+0xRVOnnP/85KisrR7x+iiRR3daPP/7IReVUPE+dfB9++CHuv/9+7gwk/yplZM7NzQ1//OMfWWxRMTqJsdFcz2ghokoQBEEQLgNff08YGA5d7zMzPBiOTv2RoLGERERcXBy8vb1x2223wcfHh8XJ8uXLER0dzVEgJbfccgt32rW1teHGG2/UOA9ZGJClAgkpSptRVOvjjz/mgvWL8fzzzyMiIoJFHTmVU9fhjQPOfSloXeRPRXVPixcv5uek9VCnIdksKNHT0+NaMPKxmjlzJv72t79x3ddor2c00FJMRXetKUpTUxMsLCzQ2NgIc3PziV6OIAiCcAXQx2bi2VR88fG3aGttV2338fPEnfffDAen/nTV1UAWAfn5+Sw0KII2Hejo6OAUHkXdjh49qkr7jefzD3fNR/r5LTVVgiAIgnCZqcKwiBA4OtmhpKgcra1tsHewhYubE8wtzORaXiEkZCgdSLVUlNK8+eabMdUQUSUIgiAIVyCsHJ0d+CaMrrB69tlnp+wllZoqQRAEQRCEUUBElSAIgiAIwiggokoQBEEQBGEUEFElCIIgCIIwCoioEgRBEARBGAVEVAmCIAiCIIwCIqoEQRAEQRBGARFVgiAIgiAIo4CIKkEQBEEQJpRjx45h48aNcHZ2ZmPVH374YUq+IyKqBEEQBEFQ0dfTg572NnS3NPNXuj/WtLa2IiwsDP/+97+n9DshY2oEQRAEQWB6OzvQUVuFvs5O1RXRNjCAoY09dAzGbrDz+vXr+TbVmdBIlaenJ4f5Bt4ef/xx1cRo+t7GxgampqY8XLGyslLjHEVFRdiwYQOMjY1hb2+Pp556Cj0DVPWRI0cQEREBAwMD+Pr64uOPPx60FlLHtB6aOxQVFYWYmBiN/SNZiyAIgiBMVSgiNVBQ8fbOzv7t4xCxmupMqKiKjY1FeXm56rZ//37efuutt/LXJ598Ejt27MDXX3+No0ePoqysDJs3b1Y9vre3lwVVV1cXTp06hU8++YQF0wsvvKA6Jj8/n49Zvnw5EhIS8MQTT+Dhhx/Gvn37VMds3boVv/3tb/Hiiy/i7NmzHIJcu3YtqqqqVMdcai2CIAiCMJXp6+4aJKhU+zo7eb9wCRSTiN/85jcKHx8fRV9fn6KhoUGhp6en+Prrr1X709PTFbTk6Ohovr97926Ftra2oqKiQnXM22+/rTA3N1d0dnby/aeffloREhKi8TxbtmxRrF27VnV/7ty5iscff1x1v7e3V+Hs7Kx45ZVX+P5I1jISGhsb+TH0VRAEQRCGo729XZGWlsZfx4uu5iZFU17WsDfaPx4AUHz//feKyXTNR/r5PWkK1Sna9Nlnn+HBBx/kFGB8fDy6u7uxatUq1TGBgYFwd3dHdHQ036evoaGhcHBwUB1DEaampiakpqaqjlE/h/IY5Tnoeem51I/R1tbm+8pjRrIWQRAEQZjKaOnoXNV+YRIVqlP7ZENDA+6//36+X1FRAX19fVhaWmocRwKK9imPURdUyv3KfRc7hoRXe3s76uvrOY041DEZGRkjXstQdHZ28k0JPacgCIIgTEa09fS5KH2oFCBtp/3CxZk0kaoPP/yQK//Jo+Ja4ZVXXoGFhYXq5ubmNtFLEgRBEIQh0dbV5S4/ElAa2893/9H+saKlpYXrnummrIem76kZbSoxKURVYWEhDhw4wAXkShwdHTk1R9ErdajjjvYpjxnYgae8f6ljzM3NYWRkBFtbW+jo6Ax5jPo5LrWWoXjuuefQ2NiouhUXF1/WdREEQRCE8YRsE4zsnWHk6AJDO0f+SvfH0k6BiIuLQ3h4ON8Iah6j79Ubz6YCk0JUffTRR2yHQF16SiIjI6Gnp4eDBw+qtmVmZrJqnT9/Pt+nr8nJyRpdetRBSIIpODhYdYz6OZTHKM9BaT16LvVj+vr6+L7ymJGsZSjIwoHWon4TBEEQhMkMRaR0jYyhZ2rGX8cyQqVk2bJl1Dg36DaUBdJkZsJrqkjAkKi67777oKv2xlG67KGHHmK1am1tzYLkV7/6FYuYefPm8TFr1qxh8XTPPffg1Vdf5fqm559/nv2kSNAQjz76KN588008/fTTXAR/6NAhbNu2Dbt27VI9Fz0HPf/s2bMxd+5cvP766+zu+sADD4x4LYIgCIIgTHMUE8y+ffu4TTEzM3PQPmpr/MUvfqGwsrJSGBsbK2666SZFeXm5xjEFBQWK9evXK4yMjBS2traK//qv/1J0d3drHHP48GHFrFmzFPr6+gpvb2/FRx99NOi5/vWvfync3d35GLJYOH369GWv5VKIpYIgCIIwWS0Vpjvto2CpoEX/TLSwmy5Q9x9Fvai+SlKBgiAIwnDQFA8q1vby8uJJH8LEXvORfn5PipoqQRAEQRCEqY6IKkEQBEEQhFFARJUgCIIgCMIoIKJKEARBEARhFBBRJQiCIAiCMAqIqBIEQRAEQRgFRFQJgiAIgiCMAiKqBEEQBEGYMN5++23MnDlTNc6NppXs2bNnSr4jEz6mRhAEQRCEyUNvVxe6W9rQ19UNbX096JkaQ0dff8yez9XVFX/961/h5+fH8/4++eQTbNq0CefOnUNISAimEiKqBEEQBEFguppb0JCew1+V6JuZwjLIl7+OBRs3btS4/9JLL3H06vTp01NOVEn6TxAEQRAEjlANFFTqQov2jzW9vb346quv0NraymnAqYZEqgRBEARB4JTfQEGlhLbTfh3rsUkDJicns4ii+Xumpqb4/vvvERwcPOXeFYlUCYIgCILANVRXs/9qCAgIQEJCAs6cOYPHHnsM9913H9LS0jDVkEiVIAiCIAhclH41+68GfX19+Pr68veRkZGIjY3FG2+8gXfffRdTCYlUCYIgCILAXX7DFaPTdto/XvT19aGzs3PKvSsSqRIEQRAEgW0TqMtvuO6/sbJVeO6557B+/Xq4u7ujubkZX3zxBY4cOYJ9+/ZNuXdFRJUgCIIgCCoBZTMreFx9qqqqqnDvvfeivLwcFhYWbARKgmr16tVT7l0RUSUIgiAIggoSUGPV5TcUH374Ia4VpKZKEARBEARhFBBRJQiCIAiCMAqIqBIEQRAEQRgFRFQJgiAIgiCMAiKqBEEQBEEQRgERVYIgCIIgCKOAWCoIgiAIQ1Jf14DK8mp0d/fA2sYSjs720NHRkaslCMMgokoQBEHQQKFQIDUpE19/sR211XW8zcBQH8tWLcTy1QthOswoE0GY7kj6TxAEQdCguLAUH7/7pUpQEZ0dXdi38zDizyTJ1RKEYRBRJQiCIGiQkpiBjo6hh9ke3Hcc9bUNcsUEYQhEVAmCIAgaFOQVD3tF6mrr0dbWLldMGDP++te/QktLC0888cSUu8oiqgRBEAQN7B1sh70ipmYm0DcYv7lwwvjT09GF1spaNBVX8Fe6P17Exsbi3Xff5aHKUxERVYIgjCvtbR2oLK1GVVkNuru65epPQsJnhw7b5bdwyVzY2duM+5qE8aGjvgklx8+i5Ng5lJ9O4a+lJ87x9rGmpaUFd911F95//31YWVlhKiKiShCEcaG3tw9Zqbn4/O1v8M5fP8F7r/4H33y8EyUF5fIOTDLcvVyx5Z4bueNPCaVjwiNDsXDZ3AldmzB2UESqIi4NnQ0tGts76ptRGZ8+5hGrxx9/HBs2bMCqVaswVRFLBUEQxoWC7CJse/9H9PT08n36mpmUg9L8ctzzy1vg4GIv78QkQU9PF1ELI+Dh5YrS4nJ0dnbBydkBzq4OMDYxnujlCWNEZ2PzIEGlLqxov67h2EQpv/rqK5w9e5bTf1MZEVWCIIw5XR1dOHkgRiWo1GlpbkV6Yo6IqkkGpf9c3Jz4JkwPei+Rjr/U/iuluLgYv/nNb7B//34YGhpiKiPpP0EQxpymxhaUFVYMuz87NXdIwSUIwviho693VfuvlPj4eFRVVSEiIgK6urp8O3r0KP75z3/y9729U+d3g0SqBEEYc3R0tKGnr4uO9qG9jwyMDLhmRxCEicPAwgyGVmac6hsIbaf9Y8HKlSuRnJysse2BBx5AYGAgnnnmmSk1GmnCI1WlpaW4++67YWNjAyMjI4SGhiIuLk5jXMILL7wAJycn3k8FbNnZ2RrnqKur444Bc3NzWFpa4qGHHuIuAnWSkpKwePFiDi26ubnh1VdfHbSWr7/+mt9EOobWsXv3bo39I1mLIAiDsbSxwIzIoGEvTfh86jab8F9HgjCt0TXUh0NkEAsodeg+baf9Y4GZmRlmzJihcTMxMWFdQN9PJSb0t1h9fT0WLlwIPT097NmzB2lpafj73/+u0UpJ4odCgO+88w7OnDnDF3rt2rXo6OhQHUOCKjU1lfOxO3fuxLFjx/Czn/1Mtb+pqQlr1qyBh4cHhxlfe+01/PGPf8R7772nOubUqVO44447WJCdO3cON954I99SUlIuay2CIAyGolARC2fC0dVu0L7Q2YHw8nOTyyYIkwBDK3O4LAqH65JwOM2bwV/pPm0XRoBiAnnmmWcUixYtGnZ/X1+fwtHRUfHaa6+ptjU0NCgMDAwUX375Jd9PS0tT0MuIjY1VHbNnzx6FlpaWorS0lO+/9dZbCisrK0VnZ6fGcwcEBKju33bbbYoNGzZoPH9UVJTi5z//+YjXcikaGxt5rfRVEKYjddX1inOnkxVfvved4puPdyjSk7IVLU0tE70sQZh0tLe38+cbfRUm/pqP9PN7QiNV27dvx+zZs3HrrbfC3t4e4eHhbPqlJD8/HxUVFRqeFRYWFoiKikJ0dDTfp6+U8qPzKKHjtbW1OZqkPGbJkiXQ178QuqQIU2ZmJkfLlMcM9MagY5TPM5K1DKSzs5OjZOo3QZjOWNlaYlbUDNz+yE24+b7rERjqCxMzk4leliAIwqgwoaIqLy8Pb7/9Nvz8/LBv3z489thj+PWvf41PPvmE95OIIRwcHDQeR/eV++grCTJ1qFvA2tpa45ihzqH+HMMdo77/UmsZyCuvvMLCS3mjWi5BEARBEK5NJlRU9fX1cQvlyy+/zFEqqoN65JFHuGbpWuC5555DY2Oj6kZeHIIgCIIgXJtMqKiiLrrg4GCNbUFBQSgqKuLvHR0d+WtlZaXGMXRfuY++kr+FOj09PdwRqH7MUOdQf47hjlHff6m1DMTAwIA7EtVvgiAIgiBcm0yoqKLOP6prUicrK4u79AgvLy8WLAcPHlTtp7okqpWaP38+36evDQ0N3NWn5NChQxwFo3on5THUEdjdfcENljoFAwICVJ2GdIz68yiPUT7PSNYiCIIgCMI0RjGBxMTEKHR1dRUvvfSSIjs7W/H5558rjI2NFZ999pnqmL/+9a8KS0tLxY8//qhISkpSbNq0SeHl5aVRnb9u3TpFeHi44syZM4oTJ04o/Pz8FHfccYdGl56Dg4PinnvuUaSkpCi++uorfp53331XdczJkyd5Lf/v//0/RXp6uuLFF19U6OnpKZKTky9rLRdDuv8EYfJSU1mriD+ZqPjq/R8U27/Yq8hJy1O0tUrnlTAxSPff1Oz+m1BRRezYsUMxY8YMtiYIDAxUvPfeexr7ycrgD3/4A4siOmblypWKzMxMjWNqa2tZRJmamirMzc0VDzzwgKK5uVnjmMTERLZvoHO4uLiwQBrItm3bFP7+/gp9fX1FSEiIYteuXZe9loshokoQJicVJVWKN/74nuLFx1/VuO377pAIK2FCEFE1NUWVFv0z0dGy6QKlC6kLkIrWpb5KECYHVIP542d7kByXMeT+ux+/Bb5BXuO+LmF6Q6bSZOVDpSdTfcjwtXDNR/r5LXMhBEGY1tTVNCAjKXfY/WlnNes+BUEQhkNElSAI05q+nj50d11oYhlIa2vbuK5HEISpi4gqQRCmNWYWprB3th12v1+w97iuRxCmI6Wlpbj77rt5iLKRkRFCQ0MRFxeHqYaIKkEQpjUmZsZYum4+tLW1Bu2zsrWAl7/7hKxLECaKrrYO1BZVoSKjmL/S/bGkvr6eLZb09PSwZ88epKWl4e9//7vK8mgqoTvRCxAEQZho/EN9cPP91+Po3mhUldVAV08XAaE+WLxmHmzsrSd6eYIwbjRVNSDtp3g0VzWotpk5WCJ4dSTM7S3H5Dn/9re/8Ri3jz76SLWNisWnIiKqBEGY9tBfyCERgfDwc0NLYyu0dbRhbWfJc0QFYbpAEamBgopormxA2v54RNy0EPrGo9+JuH37dqxduxa33norjh49ChcXF/ziF7/gsXVTDUn/CYIgnMfUzASOrvawd7IVQSVMO5prmgYJKtW+ygbePxbk5eXh7bffhp+fH/bt24fHHnsMv/71r/HJJ59gqiF/hgmCIAiCgO62zqvaf6XQWLnZs2fj5Zdf5vvh4eFISUnBO++8g/vuuw9TCYlUCYIgCIIAPWODq9p/pTg5OSE4OFhjW1BQEIqKijDVkEiVIAjCEHS0d6K6ogaNdU3QN9SHnaMNrGzGplBXECYDZrbmXJROqb5B+xwsef9YsHDhQmRmaprsZmVlwcPDA1MNEVWCIEwIZKpZlF+C5IR0dHV2ISg0AF4+7rCeBMKlvqYB+384ioykbPT19U/yMrc0ww13roVv8NTsShKES0FF6NTlR0Xp6sJK2f03FkXqxJNPPokFCxZw+u+2225DTEwM3nvvPb5NNWT23zgis/8EoZ+Wllbs+n4/jh8+rXFJPLzccN8jt8He0W7CLlVvbx/2fHMQcccTBu0zMjbE/U/cDgfniVufMD2YyNl/1AVIRelUQ0UpP4pQjZWgUrJz504899xzyM7O5tf829/+dty7/0Zj9p9EqgRBGHdys/IHCSqiML8Yp47FYtOt66GlNdiMczyoqaxDUkzqkPva2zpQlFsiokq4piEBZeM+vkLu+uuv59tURwrVBUEYVxQKBaKPxw+7Pyb6HOpq6jFRdLR3oKtz+FmANRV147oeQRCmDiKqBEEYV6h9uqW5Zdj9HR2d6O7pwURhaGgAfQO9YffbOIjDuiAIQyOiShCEcUVHRwfBoQHD7ndzd4aFxdh0GY0EW0cbhM4OGnIf1VR5+LiO+5oEQZgaiKgSBGHcmRkezO7lA6HxMKvXL2XxMlHo6Ghj0ZooBM3y06jrMrc0xeb7N8DBRYrUBUEYGilUFwRh3HF1d8bPfnUvdv1wANkZuZwSdHJxwIZNqxAQ4jfh7wj5UW26ez3mr1D6VOnB3tEWVrYTb/cgCMLkRUSVIAgTgrevBx755d2oqaplGwPypzIzN5007wbVVrl7uwB0m2CqSqpRkF6IsoIKWNiYwy/MF47u9tDVk1/hgjCZkP+RgiBMqHChqJUwPEVZxdj72QF0dXTx/ZLsUqTFZGDxxgUIjgqCrq6OXD5BmCRITZUgCMIkpbW5Dcd3nFIJKiWKPgVO7jqNOrF3EIRJhYgqQRCESUpDVQPqh5jDRvT29KKqpGrc1yQIwvCIqBIEQZik9PT2XnR/V8fwJqWCIIw/IqoEQRAmKWYWpjAwMhh2v52L7biuR5gedLR0oCKvHIUpBfyV7o8lnp6ebF8y8Pb4449jqiGF6oIgCJMUK3tLRCwLQ/SemEH7PILcYetsMyHrEq5d6ivqELvjNOrLL4xjsnKyxpyN82DlODbTBGJjY9GrFpVNSUnB6tWrceutt2KqIZEqQRCESQr9tR4SFYTlNy+Gha05oAUYmRgifFkYlm5aCCMTo4leonANQRGpgYKKoPu0fawiVnZ2dnB0dFTddu7cCR8fHyxduhRTDYlUCYIgTGIMjQ0REhUMz0APdLR1QFdfFxY2FhO9LOEapKGqfpCgUkLbab+jqdOYrqGrqwufffYZfvvb32pMNJgqiKgSBEGYAphYmPBNEMaKzrbOq9o/Gvzwww9oaGjA/fffj6mIpP8EQRAEQYCB8fBNESPZPxp8+OGHWL9+PZydp6YpsIgqQRAEQRBgaW/FRelDQdtp/1hSWFiIAwcO4OGHH56y74aIKkEQBEEQYGhq2N/lN0BYKbv/aP9Y8tFHH8He3h4bNmyYsu+G1FQJgiAIgsCQbcKSO1ZwUTrVUFHKjyJUYy2o+vr6WFTdd9990NWdutJk6q5cEARBEIRRhwTUWHf5DYTSfkVFRXjwwQcxlRFRJQiCIAjChLJmzRooFIop/y5ITZUgCKNCe1sHujq65GoKgjBtkUiVIAhXRXlxJVLiM5CdmgddPR2Ez58JvxBvWFqby5UVBGFaMaGRqj/+8Y+DBigGBgaq9nd0dPBARRsbG5iamuLmm29GZWWlxjkoB0udAsbGxtw18NRTT6Gnp0fjmCNHjiAiIgIGBgbw9fXFxx9/PGgt//73v3moo6GhIaKiohATozlrayRrEYTpRklBOT779zc4eSAGVeU1KCuqxK6t+7H98z1orG+a6OUJgiBMr/RfSEgIysvLVbcTJ06o9j355JPYsWMHvv76axw9ehRlZWXYvHmzaj8NYCRBRbb2p06dwieffMKC6YUXXlAdk5+fz8csX74cCQkJeOKJJ9gDY9++fapjtm7dypb4L774Is6ePYuwsDCsXbsWVVVVI16LIEw36I+XUwdj0NrSNmhfXmYRCnNKJmRdgiAIE4WWYgIrwyhSRZb0JHYG0tjYyEMWv/jiC9xyyy28LSMjA0FBQYiOjsa8efOwZ88eXH/99SxwHBwc+Jh33nkHzzzzDKqrq6Gvr8/f79q1i6deK7n99tvZBn/v3r18nyJTc+bMwZtvvqlq7XRzc8OvfvUrPPvssyNay0hoamqChYUFn8/cXFIjwtSmprIW7736Kbo6u4fc7xvsibt/MfWmzAvCZICyIxQU8PLy4gyKMLHXfKSf3xMeqcrOzmY7em9vb9x1112cziPi4+PR3d2NVatWqY6l1KC7uzsLGYK+hoaGqgQVQREmevGpqamqY9TPoTxGeQ6KctFzqR+jra3N95XHjGQtQ9HZ2clrUb8JwrUC/T12sT/Jenv7xnM5giAIE86EiiqKEFG6jiJGb7/9NivExYsXo7m5GRUVFRxpsrS01HgMCSjaR9BXdUGl3K/cd7FjSOC0t7ejpqaG04hDHaN+jkutZSheeeUVVrbKG0W/BOFawcLaAp5+rsPuD40MGtf1CIIgTOvuPxqaqGTmzJkssjw8PLBt2zYYGRlhqvPcc89xrZYSEnIirIRrBX19PSxaHYWi3FJ0DrBScHKzh5e/+4StTRAEAdPdUoEiQf7+/sjJycHq1as5NUe1T+oRIuq4c3R05O/p68AuPWVHnvoxA7v06D7lREm46ejo8G2oY9TPcam1DAV1G9JNEK5VPHzdcNcvbkbs8QQUZBVDV1cHM+cGI3R2MKxsNSO7giZdXd1obmiGjq4OLKzMuftZEISpzaQSVS0tLcjNzcU999yDyMhI6Onp4eDBg2xfQGRmZnLN1fz58/k+fX3ppZe4S4/sFIj9+/ezYAoODlYds3v3bo3noWOU56C0Hj0XPc+NN96oKlSn+7/85S/5/kjWIgjTFXdvV7i4O6G5qQXaOjowtzCd6CVNauj3S0F2MU4djEVpQTl09XQROicI4fNDYedgM9HLEwRhqtZU/e53v2N7goKCArZEuOmmmzhqdMcdd3AN0kMPPcTps8OHD3Ox+AMPPMAiRtltR7b2JJ5IhCUmJrJNwvPPP89+UsoI0aOPPoq8vDw8/fTT3LH31ltvcXqRLBKU0HO8//77bMmQnp6Oxx57DK2trfx8xEjWIgjTGYq2WFpbiKAaAXkZhfjine+Qk5bPLvTNjS04dSAW3360A/U1DWP/ZgnCJWhpbuWf0+S4dORlFvL9saa5uZktj6gEiLJICxYsQGxs7JR7ryY0UlVSUsICqra2li0LFi1ahNOnT/P3xD/+8Q/uxKPoEHXSUdceiSIlJMB27tzJIogEjomJCU+4/vOf/6w6hlojyVKBRNQbb7wBV1dXfPDBB3wuJVu2bGELBvK3osLzWbNmcfG8evH6pdYiCIJwKTraOnB03yn0dGsaFBMVJdXs7SVpU2GiJyRs/2Ivyosv+DQ6uTvghjvWwslNs6FrNHn44YfZ+ujTTz9lR4DPPvuMO+7T0tLg4uKCqcKE+lRNN8SnShCmN5Vl1Xj3r5+gr2/oX7v+oT648+diKixMjE8VRaQ+f+sbDUGlLqzueuxmmJqZjPrztre3w8zMDD/++CObdSuh0htqaPvLX/6CqeJTNalqqgRBEK5ltLW0OOLd19c75H49fT1MBjo6OlFeWoHmplYYGxvBydUBJibGE70sYYypKq0ZUlAR5UWVvN800GRMpjP09vYOEjKUBlSfsjIVEFElCIIwTlBqzzfECxmJOUPunxERMOHvRVVFDb7fugupyZlcVE94+bjjtrtvhJuH80QvTxhDhho5dTn7rxSKUlEJz//8z//wpBIqvfnyyy/ZXJvm9U4lJtxRXRAEYbpAnX7k7TVUCiUkIgCuXi4THqH6butOJCemqwQVkZ9bhE8/3IYGGZJ9TWNianxV+68GqqWiaiSqn6JGs3/+859cc02R3amERKoEQRDGEVdPZ9z9+C3ISMpGVkouDAz1ET5/JpulmpmPfmrlcqCUX1py1pD7ykoqUFpcBksrmVt6rWLvYsu1U5TqGwhtp/1jhY+PD7sBUOc91S85OTlxExmNsJtKiKgSBOGaoKuzC2Wllaiva4CBgT4cnR1gbTM5DUgdXe35tnDVXP5LnCwpJgNUqKweoRpIXa1YPlzLUASVuvy2f7lPQ1hx99+da8ekSH0g1MVPt/r6erZJevXVVzGVEFElCAJDH6bFBaVcS1NdWQNXd2cEhPjB1c1p0l+h+rpG7Nl+AGdOnuWCV8Laxgq333sjgkMnvk5pOCZLYbqSS40HE2PXax+yTaAuPypKpxoqSvlRhGqsBdW+ffs4/RcQEMBTVZ566ikEBgaq/CKnCiKqBEHgX2ZnY5Lw2f99w504ROzpBBibGOHBR+9EYIjfpF77sUPROHVM0yiwrrYeH737FX7zzM+mhDCcDFCXHxWlUw3VQCytLODiJoXq0wESUGPR5XcxyKqA5uWSf6W1tTV7QtLEFJpmMpWYWhVggiCMCeVllfjq0+9VgkpJW2s7tn76w6QuUK6qrMGpo5ozQJW0t7UjOz133Nc0VSHbBOryc3Z1HCSo7vvZFtjaWU/Y2oRrm9tuu43H1JG5dnl5Od588032hZpqSKRKEASUFVego71zyCtRXVWLivLKSVugTKNeWluHb/UuLS4f1/VMdcg24RdPPshF6VRDRSk/ilCJoBKESyOiShAEbqW/GN1d3ZP2KhkaGsDQyGBYUejg1D9sXRg5JKAnq4gWhMmMpP8EQYCDY/+8zeGKqS2tJmcXHWHvaIuo+ZFD7tM30EdAsM+4r0kQhOmJRKoEQeAamtCwIDZ9HMjCJXPh5HJ50R6qiygtqkB2Zh66u7rg7ecJN3dnmFmYjfrVJkuC5WsXoaGhEUnn0rhwXVlse/s95AI+dYaxCoIwtRFRJQgCt03fcudGtiE4Ex3PqTQzc1MsXTkfCxbPha7uyH9VUHH4wX3HsW/nYZXAIWbMDMStd2+Cja3VqF9xqve568FbsLykArXVdTAwNICTi8NFI3CCIAijjYgqQRAYGztr3HLXRixeOQ+dHZ0wNjGGnb3NZV+d3OwC7N1xaND2lKQMuJ90xXWbVo3JFafBv77+Xnwbiq6OLrS3d8LASJ/rsARBECZUVKWnp+Orr77C8ePHUVhYiLa2NtjZ2SE8PBxr165lXwma2SMIwtRES0sLjldR2E2RqdMn4ofdT15S8xbNHlencxKIeZlFiDl6FnXV9TC3MsPcJRHwC/aCobHhuK1DEIRrnxEVqp89exarVq1i8XTixAlERUXhiSee4InSd999N/8i/f3vfw9nZ2f87W9/43oKQRCmH729faivbxx2f3t7+7h2EtLvpnPRydj2wQ/IzypCY30zivPK8O3HO3HqUCy6uzV9uQRBEMY8UkURKLKM/+abb2BpOfxfmNHR0XjjjTfw97//Hf/93/99VQsTBGH0IXPPloYWaGlpw8zKdNQnwOvq6sAvwAuFecVD7nd0chiX+WFKqitqcWT3KaiVdqk4dSAWgTP94OyuaXQpCIIwpqIqKytrRFbx8+fP51t39+T1tBGE6Up5YQUSjyejJKeU03xeMzwROj8Eds6jO3k+fHYoThw5M8g3ip5z1folXBQ/XlC6bzj/qp6eXtRU1l6RqKqqqEF5WQU6O7pgY2vN3ZNGkkoUhCvm2LFjeO211xAfH8+O6t9//z1uvPFGjajziy++iPfffx8NDQ1YuHAh3n77bfj5+U09UXW5s3em2qweQZgOgmrn/+1BZ3uXalvamQwUZRZj44PXwcZx9MaPeHi54aHH7sIPX+9RuZnTmJPrblw1ocONKe1InYmtLe3Q0dGGqbkJD5G+HOgXe+LZVHz1n+/R0tyqEouzImfgxtuuG5PORkEYb5qbWlBaUsE/42ZmJvxHA3UDjyWtra0ICwvDgw8+iM2bNw/a/+qrr+Kf//wnPvnkE3h5eeEPf/gD13KnpaXB0NDw2un+O3DgABeuz549Gxs3bhydVQmCMGr09vQi+VSqhqBS0tLQitzkvFEVVUTQDH+4erigurKGn9/a1mpCBIeNvRVHkGh2YXlxBXcAKmltbkNPVy+PuRlplKm4sBT/+WAbujq7NOu24pJhYWmOm++4nkWWIExVigvL8MXH3/LPuhJ3T1fccd9mHmE0Vqxfv55vQ0H/x15//XU8//zz2LRpE2/7z3/+AwcHB/zwww+4/fbbMVm4rIKKX/ziF6wOlXz77bdYt24ddu3ahS1btuB///d/x2KNgiBcBa1NbSjJKRt2f15KgYbYGC3oL1xvXw/4BXpPWATH1sEGyzcsRENd46DXuHLjEpw5dg6lBSOfDZiRlqMhqNQ5czIeleXVV71mQZjICNVAQUUUFZTgy0++4/0TQX5+PioqKrhhTgkNW6amOarlnkxclqg6fPgwlixZorpPIurll19GXFwcPvvsM7z11ltjsUZBEK4CLW1yHR8+eqKtqw2ti+yfynDtWIA7brh9LUIjg+DoYo+gWf64/eeb0dPdg+ryGiTHD3aRH46qi4im9vaOS85QHCmtTa0ozilBXmoBKkuquMFAEMYaSvkNFFTqwor2TwQVFf3PS5Epdei+ct+USv/96U9/4q9FRUX48ccfWRlSOC42NpZzoH/+85/R0dHB++l74oUXXhjblQuCMCJMLUzhG+aDhGNJQ+4Pmh3A8/2uVfp6FYg7mQBnN0d4+Lmzb1XSmVQuVFemAUeKk+vwRe0mJsYwHoVi9dK8Mhz+7jgaqhr4vo6uDgIi/DBnVSTMLMe2rkWY3ijrBK90vzBCUXX//ffz13feeQerV6/GrFmzuI7K0dERzz77LAssKjKjIjI6Vn00hSAIEx+tIeGUn1aAxpomjX1OXo7wCHAb0+enYvDy0iqUl1ags7OLzUXHs1vO1NwYtvbWKM4fOgXqF+Ktcb+9tR3dnT0wNjWCrr7mr8iAIB8YGhkM2VG4YOlc2DlcXSdlXWUd9n66H+2tHaptVJOWFpMBfUM9LNwwX2q2hDHjUnYn42mHog5pDaKyshJOTk6q7XSf9MiUE1UeHh78dd68edzy+Pjjj+Nf//oXbrrpJri7u/M+ilpRRb7yviAIkwcqRL/+gfUoTC9CdmIutHT6hZabnys7jA+kr7cPjXVN/NXE3PiKncfJXDP29Dl8++UOth9QirzIuTOx6db1sLIee2d1EzMTLFk3H998tHPQH3wWVmbwDuj//dbS2IrclHyknk5DZ3snbJ1tELZoJly8nThaRLi6O+OBn9+Jr/7zHerr+k1OdXR0MHdBBJasuHrBU15QoSGo1EmLyUTwnCBYO0iHoTA2uLg6clE6pfoGQttp/0Tg5eXFwurgwYMqEdXU1IQzZ87gsccew2Tisrr//vGPf+Cee+7Bz372MyxatIg9I5S8++670v0nCJMYKztLvoUuCAG0+sXAUNRW1CHhRBJyk/LZhoDExZyVEXD3d4Ou3uU1DBfll7D9AIkzJSRs4s4kwt7BFtfduBrjgf8MH9x8/wYc3XMK1RV1LJJ8g72wdN182DnaoL2lHSd2nEJOUp5GgX9xdilW374CfmE+qu0hMwPw5HOPcvStq6uLR+44OTtA30D/qtdJ1344qNC+o21owSUIowHZJlCXHxWlqwsrElR33r95TG0VWlpakJOTo1GcnpCQAGtraw7W0BSXv/zlL+xLpbRUoCku6l5Wk4HL+g3p6enJab+h+OCDD0ZrTYIgjCHKqMtQNNY2Ye9n+1F/vp6HqC6pwZ5P92PdXavgE6qZKrsU5+KSNASVOieOxnCEx/YKhjZfLlQzNiMyCJ5+bmhqbGFBaW1rqaolqy6r1RBUSmjtp/fFwNnLESbmF1If1jZWfBttzG3Mh91Hglbf8OqFmyBcDLJNeOyJ+1U+VZTycxkHn6q4uDgsX75cdf+3v/0tf73vvvvw8ccf4+mnn+YyIwrqkPknBXb27t07qTyqRsWnShCEa4eyvDINQaVE0adAzIF4OHk5ca3RSKkorxp2H7Vnd43jHEDC1NyUbwMpzRu644mgOjQSm+qiaqxw9nKCnoEeujsHXxefUC+ONArCWEMCKjDYd1wv9LJlyy5aj02pdWqEUzbDTVZGZKnw17/+lQehjgTKcZJvlSAIU4/CzAsz+xRQcGF5U2Mz+zwV55SisXb4YclD4ek1fBE81VNNltEuNAvx4vvHx3KCRgat2rJsUA2bq58Lp2AvFmUUBGGKRKrIBp5ymrfeeivXTZF7up2dHe8j/xTaf+LECfaqKisrY6dTQRCmHsr0Egmq5sYWVJXVoLe3VzUsOT+7CAbGBrC2G1nqa8asYBzaf3JIw8yV6xaPaaF6fU0D2yXo6OnC1t7qorYRrr7OiDt4dsh91o5WsLhIWm40IfHmHeIFK3sr1JbXsgu+ha0FbJ2sYWQy8gihIAiTWFSRSEpMTMSbb76JO++8k6vuqSbBwMAAbW39Hi/h4eF4+OGH2VJhsuU4BUEYGVQzRe371P1WWVKNPsWFeii/MF+kJ2ajrrYR1926Etralw50e3i54oGf34Ftn/+I+tr+tCIVdC9btRCRc8PG5G2h7rnEmBScPBDLwpDm/PnN8Mby6xbCwcV+yMfYOtsiZF4QUk+nD6pjWrA+CsZm4zcEmoSVtb0Vp/qa6puh6FXIPFVBmCJoKS7TVIo8Z5KSklBYWMgpQVtbW25xpK/CxSExStb6jY2NMDcfn798BeFyoO6ymP1xOPzDcdRUXuhEs7S1wNKbFuPU4VgWGg8/dTfsHUf+f76utgGV5f3O4FTg7eBkB13dsSnpPH04Dnu/PTxou62DFe567BZY2Q4dHWtraUdxVglSzqSho7UDju72CJoTCCdPx3H3hqqrqENKTDpyEvPYp8rJywHhi8Pg7O0kPlXTBDLUpg446nSTQMXEX/ORfn5f9m81+uuURNRkM9wSBOHqoVqeuatnQ9/EAEknU9jk0tXHBYbmRog9mYC+PgW6Orsve1Yg2Q7Qbaypq6nHyQMxQ+6rqaxnA9DhRBUV4JNzufcMT/R098LAUB/aOpc1yWtUaKhuwO7P9qsc1YmCtCKUZJfh+gfWwdXXZdzXJAjCyBj/3xiCIEx6YaWlq40+fW0Y25oiN7cIMcfPqcw7SXwYGU/O+h7ylmpuHH6URnH+8F1+Sqj2ysjEcEIEFVGUVaIhqJTQrML4Iwnj3jEpTCwyoWRqXWuxVBCEaUp5WSWy0/OQm13AUaQZYUFw93Lh+h1PP3cc2XNqSHfvOYtnwcZ+bFy9m+ub0VDbRL/dYGFtflHfpqGg1CRF06lMYSRjNkioVBZXsct8fXUDHN3s4T3DC/audhOSZqNf6tlJucPuL8+vQEt9i7iqTwPo/yFBdctGRpPzj5hrjbbzNeLKaz+lI1Vk20C/xMg1VT2/SSNxbGxsYGpqiptvvpln/ahDQ5w3bNgAY2Nj2Nvb46mnnho00f3IkSOIiIjgwnpfX182EhvIv//9bzY3pTxqVFQUYmI0UwgjWYsgTBXycgrxr9c+4ALy+JhE7N9zFG+8+h5OHYtFd3c3HFzscOuDN2iIJz09XcxdGo7Zi0Y/9U91QyRsvntnO358byd+fH8Xvn1nO9LjMln4jBQbB2v4BPaPnRmItrYWvNX2kbFnRnwWfnxvF1Ki01CaU4b4wwn44d0dKEgvxERAvwP1BswbVEdHVxta2uMv9oTxh5rBLC0tUVVVhdraWq5hps8huXWM+jWga0vXmK41XfPhpk1MmUgVzQ2kMTczZ87U2P7kk0+y59XXX3/NBWK//OUvsXnzZpw8eZL3U6s3CSqaCXTq1CmUl5fj3nvvZZX58ssv8zFUdEbHPProo/j88895dhB1KdJQxrVr1/IxW7duZfdWGhhNgur111/nfZmZmSzURrIWQZgqtLW144dtu9l/Sh2K7nz31S54eLnB09uNZ+Ld/+stqK6s43E15pZmsHOyGZMCc5p5t/+rQxru662NrTj0zVEYmRrBM3BkM0X19fWwYuNi1FTVob6mUUNQrblpGRxdHTSGF5/YET0oqtXd1YNjP56ErZMNzIaYizjWBEb4oyhz8Ow1wjPYY8hZjcK1iXKQMH3YC2MPCSrlNR+37r+xmPdDUaS33nqL5/pQATyJGqqwJy+sL774Arfccgsfm5GRgaCgIERHR/Nw5z179uD6669nbywHh/5fliSMnnnmGVRXV0NfX5+/JzGUkpKies7bb7+dbe7J4p4gITVnzhy2jCDol6ybmxt+9atf4dlnnx3RWkaCdP8JE0FbSxtamto4ykFeR5WlVTh2KBrZ2floqB9s5nnTlg1YuXbxuK2PolT7tx7iTrehcPN3xXX3rrmoz9RA6qrrUZRXyoXplPLzCfKEk5sDR9uUUJTqwNbBXYJKbnj4Op53ON6wmPzuGA+/VsfUwgQb7l8HOxfptJ5uUACBIsjC2EHBmItFqMas+085o2fbtm2ceqOBoup89913l3UuSqlRJGnVqlUsqpTEx8fzDxFtVxIYGMgmpEohQ19DQ0NVgoqgCBNNrU5NTWXvLDpG/RzKY5RpRlo/Pddzzz2n2k81GfQYeuxI1yIIV0pPTy+nuPQN9Ebk/TSQyrJq5KTl840+eGfODoarlzN6OruRlZSD0z/FsV+Ti7cTiwQqFSo4V4jAGT7QCdHByROxGudraxm+0HssoE7CmrLaYffXV9az1cPliCoyJ6XbrKgZwx7TfYm0Iom9icDEwgTLNy9BSU4p0uIy0NPZwx2JXsGesHG0npA1CRMLfdhfTUpKGD8uW1R99dVXnGIjYfLTTz9hzZo1yMrK4vqim2666bLPdfbsWU7/DaSiooIjTRSOU4cEFO1THqMuqJT7lfsudgypTsqj1tfX818BQx1D0aiRrmUoOjs7+aaEnlOY2lC7e3lhJWrKajg1RLPaKHJwJUXNJCZKc8vYF6mloRU2ztYIJl8kD8cRjyOhSMzW937gwadKkmPTsfH2NShIKcDRHSe5+Lm3uxc5SbkwtTDFmjtXImR2IPZ/cxgBYb6YFT4DCecuRHI9vEeWahstdPV1uaOwoXroETiGJobQ0x/9QcJcL0Zv2xCxepq/N5FpNhLHgZH+8Avz4fePCvAFQZj8XPb/VKpV+sc//sERJjMzM7zxxhtslPXzn/+c65RGSnFxMX7zm99g//7916yx2SuvvII//elPE70MYZSoKKzEns/2c3pGCX3YrbxtKXxn+lyWsKLIVOLJFJzZd+EPitqKOk6BrbptGfzD/UYkyg7vPKEhqAgSZC0NLYj+KZY/kGkYMtVEES2NLUg9k46Q+UGwtLFAZmIONkasV3XMeXi6wt3TFeMJRaBmzA9BWf7Qf6CELgiBobHBqD+vtZM1v285iYO77cIWhfKomIlGZv0JwtTisnMNubm5nK4jKHrT2trKHyZUyP3ee++N+DyUUqPiO6qnosJXuh09ehT//Oc/+XuKAlFqjmqf1KGImLKQjL4O7MBT3r/UMZQTpTZVcoKnsOpQx6if41JrGQpKKVL+VXkjISlMTcha4Oj2ExqCSimODn1zjB2wLwcSULEH4gdtp0Ltk7tOo5FsBS5BTXU9CrI1624IWwdrlGSXovW82GJhpVY6SRErLWgjaKYf1xhVl9XAxtYKUQsjce/PtsDSavzc/ltb27iui1KTs5bM1Oxs0wKPjvEKHrqb72oxNDLAwg1RmLM6Eibmxvzc5tbmWHrjIhZVE+VTJQjCNIpUWVlZobm5v2vIxcWFC8CprokEh9LjYSSsXLkSycnJGtseeOABrlWi4nIqFKfCMerWI/sCgrrxqI5r/vz5fJ++vvTSSyzOlF16FPkiwRQcHKw6Zvfu3RrPQ8coz0HCMDIykp/nxhtv5G30Fzvdpw4/gvZfai1DQRYOdBOmPvVV9agurhlyX3dnN6pKqmHjZDPi89WU12p0ug00sGyobbzkEN++3l62DyFTTqr/oagGzdXT1tLi+8O13tPPt56eDkxMTeDt5wlffy9cd8ca2NhZ8R80NVW1qKyoQV9fL2xsreHobH9FtV4Xo76uEUlnU3Hy6Bm0t3fA09sdy1cvgneIJyqLq1kE0pgY6sBTDnm+Gro7uqFQ9EHfSPP/o5mlGaJWz0ZQpD93/RkYGXDqTRAEYVxE1ZIlS1iUkJC69dZbOYV36NAh3kZCaaRQ6nDGDM0iUhMTE/aBUm5/6KGH2OrA2tqahRJ145GIURaGUz0Xiad77rkHr776Ktc3Pf/885yaVIoZslKgrr6nn34aDz74IK+ViuypI1AJPcd9992H2bNnY+7cudx9SBE4EnkEVfxfai3CtQ194F6MoUwyL8ZwgkqJ4hL7CYqwkniiuioyy1TWH5EAWrh0NiytLbhAXUubvI20oThvHeAZ4A4TMxNkl+XAQF8fPiFePIuPagvjzyTiu6070djQrIrmrF6/DIuXz4OxyegYEDY3teDbL3Yg4eyFOq76umSkJKbjocfuQvgSTWuVq6GlvhllWaXIT8zla+oc4Ab3EA9YOmim9ihCJQiCMO6iigQKmWURv//97zmCQx5RFMEhQTOaUO0WfUDQuangm4rjyXpB/UNl586d3O1HAodEGYmjP//5z6pjqN6LBBSlJ6n+y9XVFR988IHKo4rYsmULWzC88MILLMzI1oHsFtSL1y+1FuHaxtjMmE0ZhxNX1g6X15VFERiKJFG901BjYixsLS76+I6OTpw4EIPZi2ehIKdYqal4EHBRXgkWrZyLoAh/JEancCSLOgs727v4NSy6fgHqyutYkEUsmwVb5/4IW0FuET798GsN81ya/bfju32wtLJA1MIIjAZFBSUagkq9G2/7d/vg4e0GM3PTKz5/W2s7D0dGnwJpR5JQnn1hNE1jdSMKEnOx+I7lsJoGnXRdnV2oLa9DXWU9W2pYO1qzQarUagnC2DDhPlXTCfGpmrqQADm1+wwST2imrAkHdztcd+9amJibXNaHHZ2PnLw10AIWb1yAmQtnqArfSeT0dPVwGkyZhiPh9NE/voKDqx2c3Rxx6lAMSvPL2Idq5pwQrLtlBWztrJEUncKDkRtqGuHs7YTZyyO4WL2+oh6hC2ZAoa1g0UWPy8zIxvZv9w054sXZ1RG/euoRmA0Y83IlfPPFdhw5cGrY/b97/nE2H71cSABmp+bh1IEY1NU0cMFoQKA3rMzNUJGhaabpNcsXszfMvabrplqb23Dmp1ikx2aqxDs1VsxbPxcz5gZx16UgCCNjzHyqLmULcLEnE4SpCv1lH7EsDDp6Okg9nY7O9k7e5hnkjqg1cy5LUBFU+zR3dSRHrJJOpaC9uZ2jU5T6IrNLElQkEgqyixF3IgFNDc1wdLVHxPyZcPN2QWtzO9cdVRRX8cy6mbNDsHBlFAuwssIKXl9leQ3qm5sRND8Ido42XKNk52jL9gp1tQ3Y//0R5GYUoK9PAS0tBfSNDbBk+XwcOzzYZbyuph5trW2jIqrGYqYeXYtzp5Kw7/sjqvu1JdXITc7jaJ63uzNqi6pVx5dlFaNtUQhMra9dd3Lqakw7028Lo95YcXJHNKztLSfE2FQQrnUuW1SRV9NQvxTplxhtp7oMQbgWIeE0f91cHiPCZpQGerCyt7zisS3GpsaYMS8YPqFe6OrohqGJAQwM+2sByQLh9OE4HNl9IaJTVVaDlLh0bNiyGqbmJpgVFcKu4XXVDchKuWAL4OLuyGIs9njCoBEutzy0EW6eztj99UEUZBX1OzV3dHEhd019EZrqmxEY7Ie0lEyNx1I6zvD82q6WoBkBOLx/6PFObh4uHGG7XGoqa3Fs32mNbcoQfPzJRAT/wh9QE1UUn7+WQ/QtTa0s1oeCflfTTEU3v37xLgjC6HHZnwaHDx9W/ce87rrruD6JugAFYTpAH0LWA4qcrxZKvdFNCaXqyksqsXvrAa67orQf1Q+SrUdjXRM+/fc2LFwVhRM/nUbkwlnsHE5u6kq8Aj1wdM9J6Oho/vfu6urm6NTazcv7BVVPLxqrG7honlJB5hZmSE3IQPiCGejt7oGOmuHk0lULYGE5OlFod09nzI4KQ9yZxEGib+PmNTxW5nJpqG1Ce1uHxvtkZGbEgpFSXzS2hl4jpVEJRx8nGJsb41qFOlLbW4ZvnmisaeKIpaQABWGCRdXSpUtV39Mveup+8/b2HuVlCcL0pCCjCMe+PwETezO2aSDMbcygraeD2so6FkAmZsZwcLGHmaUpDu06jhUbFsPazpIjVpQipBjMQEGlpLqiDnXnBw13tnXwhyrV3lANEhls2tnZoK25HY11zbCys+QU54IlsxExZ/Q68kzNTHm+oH+QL04cOYOO9g54+XpgwZI58Pa9Mk+qoWqjqBOyrbGVhZSOri66ztcV6Rvpw29uwDVdrE3vpZmVKRepD4Wdqy2nsgVBGF2kUlEQJglkCHrsx5Owc7eDQhcwtjCGjrY2Guoa0dbawZEmormpFdUVNZi/fA6iD8chL6sAt9y/Ebr6enB0sUPimdSLPo+BoT7bK/T29vF5a85/8JJDO3U5+vp7Ql93Few9HODj7wEnV8dRS/0poagXiaiIOaHc9WdkbHjFaVTCxt4aFlbmaKy/UPOpq6cHaycbdLV3wdbeGpW1bXDwcYJvpB9srvGhxBT5DF8SNuTAaBKTAeF+kvoThDHgqltfJCcvCKMDRaKsnK1w9KdotgSgOqGOzk6us+JaxfONuiQemuqauJ7KwdkOUGixiWVgqC97U9Ew5eEwszBl4WVpbY62ljY0no9aEXR6c0szlKSXIOdUFnrq+iNIoy2o1DE0MuR6rasRVAS9nrU3Lxs0I4/q3jbddx2C5wdj5YNrMWdD1DUvqJR4Bntg3ro5Guap5By/8rZlcHTXnHUqCMLocNm/ycLDw1VCigYSb9y4kV3JldCAZEEQLp/8nCJ8+/FO/j47NR9zl0bg+L7T7FtFYqmmqo7d0ldcvwgJp5M5wrPi+sWor2nkcTNKKAUYNMsP6QnZGuen/7bLrlvAqcO1m1egtrKend2V2DnZYvXGJTjxw0mee9dU18xijtL8U4HAmX6495e3Iik2DWVFFbCkbsp5oXD3cYWBwegPZJ7skHEr+ZB5BXuyCCcDWGqssBCjU0GYPKJKOcqF2LRp02ivRxCmJbVV9Yg+FKe6n5mYjQWr5+DGe9Yj5tg5dkCnmX6Ri8KQdi4T1RW1XFulra0Fn0AP3qfExNQY6zavgIuHE+JPJHIBt62jNRasnAPfoP76x/bGNlx3yypELQ7nc5mam6KrpQPHvjuBjrZO2DrrwNHTcdIKqvbWdlSX1qK8oILTWeTBZetkzQKKbtQ9SVGr6R5JJ18zGzL8nAZGp4IwJUXViy++ODYrEYRpTGNDE0eeSCBQVx5x5shZmFmbwdPXDWFRM1BZWoV93x5is07CO8CDI0krbljMvlfqUDRi0eooBIf7s49VVUUNslLz2L/Kw9eNi7jjDyewz1b6yXR2YqcieCr4pnQR7fcP88VkpLm+Gce2n0R+aqFqG4kn8hELXzaLIzR6+nqYapAhLDmfU+eeoYkRe0ldy8X0gnAtckWFDDQ8+ZtvvkFubi6eeuopnodHaT8a6yL2CoJwBf8RdXVZCFBXFnVs0QcrtbxT59q56GQ4uTmivLiKU3c0hkVHRxvX3bYa7t4usLK1HPKcZB6acDoFx/Ze8G9KiE7hTsGb7lqvEihLNi3EmX2xXMdF4oSiPhvuWwcH9/4h5ZONrIQcDUGltHghkUi1Ql4hnpiKTQond51GcXYJW0BQlC0g0g+zl4fDzOraNSgVBEx3UZWUlIRVq1axXXtBQQEeeeQRFlXfffcdioqK8J///GdsVioI1zA29lZwcrVHeUkVCwPypFL0Krjt3cLaDL7BnigtLGcPp+BZAVi0Jgpe/u4XTW9RXZG6oFJC1guJcWlcsHzo66MwMDbAiluWQQEFR6h8Z3jBYYILmSlqxq71ejoaUbiWxlaknkkf9nGpMenwCHJXjfOZCrQ2tXKXXnVpjYbzOTn303VYetOiqy7kFwRhfLjs/6m//e1vcf/99+PVV1+FmdmFv6DICPTOO+8c7fUJwrSA6qDWbF6ObR/8yDVQRrr9ZqAkmlbduBQRC0LhP8MHfQoFLC3NNTq6hiM9MWvYfQlnUjFv2Wzc/IsbUFVSg/aWdljaW8LOyQamllc+zPhqoYgT1UmR4zd9NTAywIyoILgHunMNGdVKUc3XcLQ2tXH6VFt/6ogqqg1TF1TqZJ3LQej8ENi72o37ugRBGAdRFRsbi3fffXfQdkr7VVRUXMESBEEgKPJ076+38FDgguwiWNlYICQiEK6eztA30GP7gcuB0nnDQZGQ7u5uOLk5wFqtyH2ognASMRQtonb8oSAR03DeH8rSyvyq6oCKsoqx99P96D7vfE5UFlXBP8IXi65fACNTI1g7WKKisGrIxzt5OU65eqqGmoZh99G1bWtuG9f1CIIwjqLKwMBgyKHKWVlZsLOTv6YE4WqgFCDdlqydd9UXkgrZU89qzvBTYutgxfMDh4NSb/lphTh3LBHN9S0wMjXEzAUz4BvmwxEjJZSSPHMkHjlpBXyf0pRRyyK583AkUSkayUMpLhJLFJU7vTdWQ1ApyTqbg4Bwf3gEuCF86SwWXvT4gZ5U/rMmZ3H9xVAfUTQUeiOISgqCMEVF1Q033IA///nP2LZtG9+nX4RUS/XMM8/g5ptvHos1CoJwBXj6ucHSxpzn4qlDZVhL1i1gI9ChILGScjoN0XtiVNvIbf349lNsULpow3xOP5YVV+CLt79Da8uFSEpSbDpy0wtx1+M3w9nNcdi11VfVI/FkCrITcrnrjfyTSLRdKopFosrD3w3Lb1mCmJ/iuMaKsHa0wsLr5sHBbXIW118MOxdb9iKjId0DsXezg80oz5oUBGESiaq///3vuOWWW2Bvb8/mnzQLkNJ+8+fPx0svvTQ2qxQE4YpGt2x5+EYc3xeNrJQ89PT0coRq8dr5bJQ5HNTWT510Q5Eem4mgyAA4ejjwOBx1QaWEttE+J9f+Yvfy4kpkp+WjqqwaDi528AnwxIntp1BdcqGOqK6iHnu/OICZ80NYKFGN10BotA5B8wqD5wTC1ceZo2g0dJqMPmnEzlBQNKwsvxwlOSUwNDaCd4gn7FzteFzPZIAGdK+8bSkXq3e299tlEGSnsfTGRSy4BEG4RkUVdf3t378fJ06c4E7AlpYWREREcEegIAiTC6qZ2nz/9eyeTp5WFJ0aLkKlhNy3KTI1FNTuX1dZB1NrM2Sn5A17Dtq3eE0UivPK8P1/dqvmFmYm5aC1vhV5aQU8nkZ1Xiigq6uDlDNpLJhyEgef293fXeO+ubU5enp7UVJQjvSUbJ4n6ObtDHtnO1VXZE1ZLXZ/+hOa1KJ1SSdTMHtlBMKXhk0aYUWu55sfvQEVxdVoaWyBtb0V7F1tYWFjMdFLEwThMrjiPt1FixbxTUlbWxvi4vodoU1NTVloCYIw8VA7PkWIRkJfXx96uns5FUURICr6HmhPoK2jw07uZBQ6HLSvraUDu7YeUAkqwtzKDBUFFagqq+GZhnp6OhydaW9qg76BLvwjAuDq4wI7Z1to6+qwT1dFYQX7NpHIUKekoAxff7gdjfXNqm0kksiFniJxJCLjDp3VEFRK4g6e5UiXq68LJgs2TjZ8EwRhGoiqoYrT1UlOTsby5cvh7u6OkJAQ7NzZP8NMEITLp6W5FTXVdfy9ja2VRlRnrGhuaOHCdDIebW1uR3N9ExeQW9lZqryiSNzYOFmzBcTMuSE4tOP4kOeifc2Nzfw61Ont6YOJnQmMjA25A7GnsxsNFXWwsDFH2JJZOLkrGoknk7mui1KAoQtm8LickKggjfQeGaDu3nZQQ1BRpItSnNs/38epTx0tbS62H468lPxJJaoEQZhGosrS0vKiRoP0S5D25+fnj9baBGHaQf+P0lOysOO7n1BcWMrbnF0dccPmtQieGTBiU0vq3uts7eT6I+NhrBDUITFCUR0ynCTxsmjDPPz01SG0NbdzWz/5JOnp6SFq7RzYOFiz1YKXvxuilkVwh2FL0wXx5ORmj5Bwf5QVVWo8B0WRQmb5w9TYCCd+PIWuti4YGOrByMIEYUvD8NOXBzk6pq+nh872DpjbWeDc8SQss7VAZnwmDA30OHJmbGGM6vIaNjclXD2d4O7pwiKMImgGxoaoq66HtY2lauTPUJAwEwRBmBBRdfjw4Yvuz87Oxs9//vPRWJMgTFvysgvwwb8/00iZlZVU4MO3P8cvnnwQfoH9A5GHgyI/5bnlyDiViubaJugb6cM7wg8eoV4wsRjeQoHqpDLi+s1CyReprKAcG+5bi6LMYlSX18IryBPhS2dyeiotIQunDsawMzv5Z82IDOSxOUW5pZg5Nxg+QV6wtrVk0UIip6+v3/ogcv5MHPvhBBdmz1kVgfiD59De3AZbFz001jWjp6eHa4kaqxq4dktbS5vPm5uch3mrIrHvvd0818/eyxHOwW7sLu/h5wYbawvU1zYCfQqU5ZWjMKsY625fBaeVDlzAToXqQ+Hm53qF75IgCMJViirq8rtUJEsQhCuHRMXJozEagkoJDVs+digaXj7unIIbjoKUAsTvOnPhcZ3dSD6UgLqyWsy5fh6PpBmKtvNO5Eoaa5qQVJPCAsgz0I3n0JEIOX04Dvu+O6I6joY7nz4cj5lzgnD7z27S8LBycLJD6OwgJMak8Rie8rxyNNY28c3c3AwbH7oOuUm5MLMy58J4qqOqL69jQaWM2lFRfWlWCVojA9Ha2AptLS2UpBehKK0Iy9ctQFNzC77/eBdHraiOKyDUl2cZpp5Og1eQB+asisT+rYeoEl4DcxszuHg7j/StEQRBGBFTZ5aDIFzjUEotP7eIRQWJFXIyp7ojJQX5xWhp0axRUqelrhmpR5OG3FeaUYyGyvphH0vGmcPZK5TmlkMLWuxRdWzf4FmCRHJcOmoqazW2kZfVio1LuAvQzcMJ+emF0NHRgY2dFVshUBdeR3MHeru6eRwNRdnICJSgNCCJpB7aZ6iPro5OLpBXoqunw47wn7y+VZUGpMemJ2Rh+1f7EDw/CMnRqTzeZtVtyzliRZDbu0+oF9bfs0a1TRAEYbSQKZ2CMEmgeiESHeTr1NrcxjYDenq6sLaz4oiNkZEh1zUNBUWZmuub0XGR0TS1JTVw8BrakJMiUnauthreUUpI8Ni52KCutgHtrYMNKtWjXYUpBShKKUBvbx/cg91h7+mIFRsXo7qsBjUF1TA3N4W+fn/Re5+iD821zdwNuPbeNcjU1WEhReLIzNqcz9HR2onwJTNRnl2qYX9g626PE/vPsHcVVXoq1IrVu9q7UFVRCyNdffKAQGCkP9z8XHguIIkqC1tzGVAsCMKYIKJKECYQMsqkmiWyMCBRNW/BbBw/cJoFFaW/KBVYWVbNxy5aGsVddxqPb25FflYRzkYnwc/XE9WVddwpaGg02H9JW1f7oqNSlm5ahL2f7Ve5lCsjWCtuXQIreysWKs0NzRxFI5sGIxNDjkZRg8qsOSHIPZ2J1poLXcKVuWWwdLTG/JsXwd7FDsFzgnD2SALbNpCLeldHN3QN9GBm1x8xWn7zEhz5/jgoVtXV2Q1FTw9CogJh52CNvLI6dKE/LUpCU9dEH2WFFTA0NuDrROuk9dDkGqrjomu2eOVcVdeiibkJ3wamWyvKqlBbUw99fT04ONlzcbsgCMKYi6rNmzdfdH9Dw/BDQQVBGAylrXZ+9ZOqS665qQXu3i745X89hNdfeRfd52urKLri5e0OvwDNIvW2ljbs//EoEk6n8n0TY2No6Wqzf5OLhyPbFigh4WPrdnGvKnJJv/HnG1FZVInaijqYWZnBycOBi9NpqHFpdim0+oCW+pb+//M1/d5Ktg7WMNalsTXlXEiu8Xuhog6FyfkIXRbGdVlZCdkoyCjicyijS47uDnD1d4WNoxX8IwNQU1nHBexmVqbsX7X9zR9Ux1Kkzt7ZForePphamLAoIz8ritSR0ScJNsLD2xW2jjbDemnRtT649xjXqSlr2KxtrHDbXTcgJCzwop3OgiAIVy2qyEn9UvvvvffekZ5OEKY1jXVN+O6TnahRq3OiqFP04TgWBs/9z29w5sRZjqb4+HqitryefaQcXexVH/ilhRVIT8iGsakRp+Wy0/Mxb9ksnP7uJJoaWth+gW5kqxCyJBSWI5ghR3VGA2uNOts6cWLnKS5eX7VpKa+bIkmkdOoq6hAS7oemsjqOWg1FYVIefCL82IphwXXzYG5ljtzUfH4dvqFe7IxOdgpU5+QZ6M7z7lqbWhF7PAHNdU1w8nVBWU6/vQTVUVF6lFKLc5ZGIPZEAkf5aB3KAct03qAwf/y07RBufPj6IecBxpw6hwN7j2lsq6utx0fvfYnfPP0zuHtObGdgd2cXOlrIgFUbplZj71EmCMI4i6qPPvpolJ5SEISK0ioNQUWQAKJuvaN7TsHe0RaKzj6EzQpmAaOro4OashpUV9bCL9ib66zIKTwg0Jv3U00UpbFSUrNx3WMbkXs2G7WltTAxNULAvEDY+TpdtGvwYtRV1aOiqIpFVGV+JW5/5CYWcBUlleyQvnBlFPJOpaOnbejRNmT4SXVSZNUQeyAe3V09CJjly/soIlaSU8bfp8dlwtrGAnmJeTxXdNeX+7grcOn1C+EW4oGyjGI+j7O/K1xneMLezR7FBWUozSvjui9l1+DS9QvQ2dKB7vZuFKQXDRJVJJ4O7z8x5FoptZmSmDFhoqqvtxeVBZXIOJmG+vJaFsTuod7wDveBuY35hKxJEISRIzVVgjAB1Nc0cBSKLAKoq62nt4fTfJ0dnSwOKKXWUt2MA1uPcNTCzccFTTXNMLYyxsEdx+Dv54UfP9rNXXGmFqZoqm+BnasN5q+PwsvPvgE7R1uERgahRbsHO747BHMrU9z16M2wc9Ic9XIpuK6rsxvBswNYHBkY6aO6rBZmBkawmxnIIpCKyZ393NBU3Z+GHIiduz2MzAzR3NDKZqJkTNrS0MKv18XLiaNTvd297NQe/f0J1JXVwTnUnUUkyaRdX/wEV38XePl7QFdLCykZuWjq6cSW2YG48a718PBwQWFuMdekefm5o6GyEWW55fzcVSVVg9bT1taBhvqhvauIwvwSTBTkMXZq2zFVGpOub+apVFQVVGDhrUsu6jUmCMLEI6JKEMYR6mgryi1BS3Mbm2WSuaWlTX83Wn11A+yd7LiWqq+nDyf39NsXUAF2X3cfdvzfbtzw0HVwc3dG3JEELLphAarKa9BQ1wjfCF8u6E44ncKPqaqo4eJ1imhRsXZDbROK8srQ2tKOjKRsdkD39HODp587C7ihoKhQTnIuC7v89ALo6etz3ZXvDC8WaZnncvi4uasiYeltjvzEXHQO6A6kSIvf3ADo6OpyUTn5Q1WXdMLSzhI+ge7IictC9sk0jjTNXBIKGxdbFKYVcVcgrZu6IGn+X1lOGbu+0xoIO8f+NVMkrrqgCubGJpymPL07hqNb9FgjU0MusFdC17c0twwtra3o6ehBT18vdxSSfYM6jk4jm5M42tC1I0sMpaBSp76sFjXFVTCx8JqQtQmCMDLEp0oQxpGs5Bx8/tY3aGlsgZmFCUemKkqruTibiqqpK27O4lkoziyGlY0lnFwdYGFpzkKLaqfOHUviDjXvEE+O5Ojr66I4vwxfvvc9SooqkJ9dBAcXe1jbWrFwou5CwtHVHjlpefjw/32K6EOxSInPwM6v9uPTN7epfJ4GUllShYPbjnK0asGG+Zi5LBSNbS04G5cMGOggaG4ADzm2c7WDlaM1Ft++DC5B7tDR67dGcPRxxqIty1QF8obGhghfEsadet4Bbji+9ShKs0o5GtPd0YXkI0lIOZoMt2B3lGWUYPaScNVa2ls6WDRRDpJsE/xDfHi7hY0FAiL9WSylx2WhvqqBrRNIQFWX1sDh/HNXlVTjx/d34sh3x5Edn4NZs0J4UHNTXbMqbUiQpUVYRAgmAkqPkvnpcJRl9adJBUGYvEikShDGiebGFk7dUcQlMzkX19++Bru27kdtVR0a65tg52gDCytzRESF4vP//Zo73OgxFDGirkAbR2uuoyrMKMK37+/oTx9qayNqzWyYmhnzsdTVZmJmgt6eHo54kLAyMzOBo7MdvvvPLliYmXDx88z5M2DrYs0iLj05i53Q6bnVySO/qZ5eBMz2w/FDMVxcTmakJLLSzmVjwZq52HzfBu7CIyjKNP+mBWipb+X6K2NLY07JqUOpvuWbF+PU18dVRp8kkiztLDhSU5FXDvdQT36dgf4uCJs/g8fORCwKg62TDdspeAV7wsH1Qp2UzwwvZMZncVpS2SZIUbFlNy1G0slU7lA8vS8GLQ39VhFUcO8d5oV5iyJx5uQ5Ppac5qlz8dY7b4C71wQVqWtpcdRMXeSpQ+lSQRAmNyKqBGGcqK9tUBWnt7d1ICkmjY0xKQVI3XoOzrZskklF4T3d3VxnRB+vZpamnAKkgcHUAUiiqLe3f6QMCZNTe87gunvWIvbUOZ67V5xPacX+D2ASXVp9CpQWlLHwoojXkusXIDY2EanbMvkYcktfunY+7nn4Nrh5uKjWS0XkJJiqKmtRlF3Sb06qq6Manl5aVM6F4s4eFwxFKc1ncd53aiioQ5BSdzpaWv1RJC0tFkp6+rq8jr6+OlTklnPt0Nl9cQhbGY7Fa+bj+I6TKEotgom5MacHGxY1YNbiUI5+ka+Wha0FbnjwOu4apJQjpVOLsorZuZ2iVCXZmlGevMR8BPv4YU5UOHq1+9hHy9nFEY7O9iMeWj3akIWEg5cTKnKHjki5BrmN+5oEQbg8RFQJwjhBokEdpbDi71vbgYhAxB49h0Wr5rJw0tGldJQ27J1subCbirwd3ezRUNvIooYtBLQALQWQdS6bBwz7BHpy1Kv+/BBhqjkiN00tHW3oaOvAd6Yn4s8mIyG+v/aKnofMMnOzCvHph1/z0GbL8xErO2cbjpycOBKrWrNScFCKj4RbwulkhEWFwNDwgj9VU30zR7go+jWUzQI9J0WF+tRG49DQZYq8kX0AnZu+p4iesYUJvv/3DzC1NuNaKSs7S/R09iDu4FkWfDPmBXP0jNJ/dKO0I10X9WgP1WQNVadUllcB5AEzFgRjdtQsTDS6+noIWRrKXX/9qc4LeIb5wMbZZsLWJgjCyBBRJQjjhJWtBWwdrVFTMbhuhoSNT4AnrCzNOfqz7o5ViN59hh3Ue7t6WJDRh+7c1bORdDqVC7tJZFDajEQV1eO4z3DHoZ0ncM/jt6C8pArZKbkwMjREQLA3DE0MkXAsEa6+zti5Zz862/vtD7R1tLiou5eESVE5SovLVKLKK8QT9TVN3H04ELJSIIsGskdQDmJuqG5AWmwGMs9m83ZbFxtELp0FV18XjdSVqZUZHLydUH7ee4qgNGRteR2sHKwQuDAE7QfiuRaruaUNBqZGaKxvhp2TjSoCRyQcS4JnsAcsbC0RMi+Ii/t1dLXZs6s4u5SvD4ks8t0ytTRlYToU6pG2icbW1Q5L717JsxrLc8qgZ6QP71k+sPd0gIHJBTNXQRAmJyKqBGGcMDU3xcqNS/DtR1QP1S9E+lGwWaWJiREUVhZor2+DhYUZ7nziVmSfy+Z5fN4zPDlak3gsiW0YZi+ZBRdPRzRQYbNCAdcgd5SUVSIozI+jWBHzZ2LNpqVIO5aM4tQiGPs5wcndEd29vejt7R/rQpCPqI29FRd2k2Cpr7tgNUD+TsFzAniQc8zRs/0btSgdacY2DoRvsBeMTYx47uBPWw+hqqh/pA5BtgYVBZVYd/cqeIdc6FpTmpFSRKbjfLcgiTyKLTn4OEFbTwdG9hbcmUfu6xSZc3C1gxFF3dSgiFhrYyvyUvMRvecMaiv6U6v2rnaYt3YOcpPy4BHkDgd3e8xZGY7oPTHwDPKAqakxR7fqaxu5kJ86Gmn9FcVVKC+o4Ciam58r7Jxtea3jDRX90y1o0QwW2xTZEwRhajCh/1vffvttzJw5E+bm5nybP38+9uzZo9rf0dGBxx9/HDY2NjA1NcXNN9+Mysr+kR5KioqKsGHDBhgbG8Pe3h5PPfUUpw7UOXLkCCIiImBgYABfX198/PHHg9by73//G56enjA0NERUVBRiYmI09o9kLYJwKQJCfXD347cgJCIAVraWcHZ3wIYtqzEjPBDfv7sT6fFZMNTVRfbpdOz81w+oyCyFgZY2qnMroEvmoD29CAz3h4WREU5/cwLJhxORdCQRZ3fFQL9DgY1bViNyYRjbJZDwsXa2RU9XNyoySrDlkRtha2fN97vaOzkZaWNvDQMDfU7rkUihFKISEmdUWL7uthVw93flgctOno6wdrDkyBOJqZlzgvm48sIKDUGlhGq+YvbH96c31bBxteWITOjyMC5wdwlwxaLblkDH1AAnd5/hETsu3k78vBRposjcwFonYzNjNNQ0Iv5QAoxNjWFhY87pUqqhOvT1EUStncNF/FQL5uzlhNkrItBQVY+y/HJ0tnVAp0eBBavncnpw1yf7sO+zA0g6kcLr/e6d7UiKTuF9EwVdYxFUgjC1mNBIlaurK/7617/Cz8+P6yA++eQTbNq0CefOnUNISAiefPJJ7Nq1C19//TWPwfnlL3/JMwhPnjzJj6diXRJUjo6OOHXqFMrLy3lUDs0He/nll/mY/Px8PubRRx/F559/joMHD+Lhhx+Gk5MT1q5dy8ds3boVv/3tb/HOO++woHr99dd5X2ZmJgs14lJrEYSRQMKAvKFcvZx5vAql9Hq7epF4IoltFjLPZcOXxrUY6cMj1JMf09nSibqSajbKXHfPatQUVCExPo4jKuTFZGlryaac7XUt6G7q1Oi4c/J15lQbzeCj9FpzRRMWr5yPnMw8TtuRH1RDTwNHpSiC4+A42KPJO9ATD/3XXTjx0xnkZxeziPIJ8sDCVXPh7N6fOivIKB72NdNMPiqwp6HN6tDYHLoFLghGTXkdvn37Ry7OJ4qySvgWuiAE3R3dXGc1kKA5AUg8nszfUyrSyt6Si/qpfoquc0d7vzFqTXktdv7fHmTFZ7HI4wHMerpYcesyFKcXoLG1ndeoDtVkRe+O4evi4u0sP9yCIIwILYVyYNYkwdraGq+99hpuueUW2NnZ4YsvvuDviYyMDAQFBSE6Ohrz5s3jqNb111+PsrIyODg48DEkjJ555hlUV1dDX1+fvycxlJLSX5hL3H777TwAeu/evXyfhNScOXPw5ptv8n36pezm5oZf/epXePbZZ9HY2HjJtYyEpqYmFmR0PorMCdMXSrfRkOL66nqefUdCaM+nP/GYFEq5pZ3JYJFFRdkkFlbctgwzF/T7Jx346CdU5vd7S1F6igSCEgsHKyy/dxVHdpRQiqyuvBY7Pt6L4pxSzF4fid07DyI/u1B1jG+INx549A7MWRzOnXNDQYOHqQheW0GGpEacjlPOITz87VGknskY8nFU7L7l15th6zy8mzvVP53cfRqpp9M1tpPLOqU+E44ls5+V8nyBEf4ImReMb978fthz0uPW3LESez/bj3OHE3g488BI0O2/uw07PtwNE0vTIYcohy2agcU3LMS1Ao3BaaxqRFtTKw+iNrc1h8n5VK4gCFf/+T1paqoo6kRRoNbWVk4DxsfH8/DUVatWqY4JDAyEu7u7SsjQ19DQUJWgIijC9NhjjyE1NRXh4eF8jPo5lMc88cQT/H1XVxc/13PPPafaT3/l0mPoscRI1jIUnZ2dfFN/UwSBZtXt+/wgiyYaAUPpOBJBK29bhtbGNnz+v1s5iqStpQ09A130lPfi6A8nWJQ4uNqir6eXLRaGoru9sz/aoxYUInsCEms0DocK22N2xWHJ/Cis27AcTU3NMDU1gamxMTx93IYVVHzutk7UF9Yg/1wOr4/MPT1nesHa2YZrpoYTVVSobj5gSPNAqEswavVsjgwlnUzhWitrRyuELQyFk5cjfGZ4s8UD1UJZ21uxZxe5rVOETll0PxAyBm2sbUJ+WiGnOwdCr6GjrZOtKozMjTWK4JWQkei1Ar3OzOg05MRmqZoLqLsycv1cOPk5DykqBUG4PCZcVCUnJ7OIopolqlX6/vvvERwcjISEBI40WVpaahxPAqqiov+vdPqqLqiU+5X7LnYMCRwa2lpfX8+CbqhjKBqlPMel1jIUr7zyCv70pz9dwVURrlXIR+nwt8fQ3NDM9UDNdc1cNE63fV8cxHX3roFHoDsK0go5kkKdebbONrw/6WQy1t25GjYudmipax7y/FbONjAw1h9StFANEnXZmVv1IOVkKtsYUNqsr68XizYuvOhcwLbGVsRsP80z6JQ0kxFpcj47qVMxODmsp8dkok/R1y/stMBdd3NXR0J/gAnoUND6gucEwifEi6NiVFelLBQnEaWrp8NRN+rw09bt7+oLjPRH4okLUWgl1PVHrvMkJhWKvkGjaNSFhrWj9bCCguq6rhUKkvKRGZ0+6H2N/u44lt+7msWxIAhTXFQFBASwgKKQ2jfffIP77rsPR48exbUARb+oVksJCTlKKwrTl8a6JjakpAgItfibWZuhraWdx6vUVdZxSnDNlhU4uSuaj6G0IAkfgrrb2tva2QQy83Qap8P0jQzYOJNEBN385vTP2RsIeTrNXDgDJ3acgrmNOafuyAiUlA912UUum6V6nqGoLqrSEFRKKAKUcSoN825eiPnrojjSlHI6jW0NbBysuNCdhOHlQO7mdFNCxeXkqn58RzQbepqam2D2ykhOzc1cGMritFCtpotex+JNC3h8TktDMzvMt1m0o6mqYfCT9fVhwYZ5OPNT3KBdZDTq4nvBDHUq09rQguxhIolUjE/2FiKqBOEaEFUUAaKOPCIyMhKxsbF44403sGXLFk7NUe2TeoSIOu6oMJ2grwO79JQdeerHDOzSo/uUEzUyMuKQP92GOkb9HJday1BQtyHdhOkNFUxTR1pBagGLKu9QL/Z0yjzbzQXa/eKGnRW41ur49pNYd88aNrhUN7H08HdF3tkclKQVIWTpTKQdT0ZtcTWnrshSYdbqCNi5XxjfMhC/MB801jYi9Uw6tAz6/akogrXw+nlsK3AxCpMLht1XQYOa61vR1taBxupGmFuacRqR0o5VpTVIjk7F+nvWwHqYwc0Xg6wOqCNy2z+/47ororWhFbs+3ouSnBJc/9B6rNqynK9jbXltv2O7iy1sHKzPe1RZImxxKE7sjEZnmyE6Wy4MfLZysORh1u4hXizi4g+dYyFLUS1nbyfMXzeXU41sv1DdgMLMYq5FcvRwhKO7PdfCTRW6OrrR3jx8KrOubPiZg4IgTCFRNRAqEqc6JBJY1MVH3XpkX0BQNx5ZKFC6kKCvL730EqqqqlRdevv372fBRClE5TG7d+/WeA46RnkOEnX0XPQ8N954o2oNdJ86/IiRrEUQhoI6/CgKcvZoAtf3UJqJPvwd3B0QvnQWdn/S3yxB7SLUM0K1Vc3kvZSSx35LFLkiKBXo4eeK0swSmDtaoa60Bl5h3gheNIP3k5hyDbx4FJQiLwuvm4eACD+ef0dpNCt7K1g7WLFYqGtoZSFiZm2uESni/xMX62dR9NdEZifkYOfHe1X1OgSde8mmhShIL1KJKhIo5H5eklvKrutkMkqvdaiIFn3YH99+SiWoLjynAsmnUhGxbBaPmHHzdeHbUITMDeJre/ZoIqcsqY6KrBqW3rgI9m72HLWbuWAGPALcOT1LnYZkd0FiKjclHynRqRxJpNqw7u4e7P/yECztLbD2zlU8j3AqQGlUek8HOrUruVTNmyAIU0BUUXps/fr1XPDd3NzM3XXkKbVv3z6usn/ooYc4fUYdgSSUqBuPRIyyMHzNmjUsnu655x68+uqrXN/0/PPPs5+UMkJEVgrU1ff000/jwQcfxKFDh7Bt2zbuCFRCz0Fpx9mzZ2Pu3LlsqUAF8w888ADvH8lahOkHiQeKQNEHLwkF+nD3DHbnr8oaHfJESjiexEKqvbWTh/eaWprxdmcvR66Xqjzv7+QT6sUz9qgWiUwvl2xaxKKKitIXXD8PZ48lIedcNkdSfEK9Yelsg4KkPK5fqiqsZOsEck6/GFSLRDVElKajNZJwKEjMQ8rRJK6vIaycrBG2KgIOXheisB4hHqgcZiadvacjix7qslMXVERdZT2Ln6BIf04z1VXXY89/fuIUqJLEkyls1kmpPH2N0TV96OjsYsFFESs6lzpUE1aUWQz/WX4wtzYb9jWTaCKPKt9QH7S1tPXbL9hZDhqhQz5XdCNIXB378SRSY9LZwJQkZfLpNE5nBs0JREZcJmIPxGP1HSsuWtw/WaA0s3e4L9JPpg7aR0KafMIEQbh6JvS3AUWYyFeK/KVIuJARKAmq1atX8/5//OMf3IlH0SGKXlHX3ltvvaV6PKXtdu7cyd1+JHBMTExYHP35z39WHePl5cUCinymKK1I3lgffPCByqOKoFQjWTC88MILLMxmzZrFdgvqxeuXWoswvaDIR1ZCDhedk/cRkZ9agNgDcRzBcPJwREdrO84dTUIXuYWfHz1HgogsEKjIOutcDoJmB/DYGrIIcPFyxqHvjvHMvaamFo6CLLx+Plsq/PT5AZRklaDnvK3A2cMJnI4i36r6inp23m6saeRohFLQUdqxrqKO65uMzYy4o45SaVQcT2KOirzRq0DsjtP9cwTPU19eh5PbjmLZPatUdTY0JoUK5KuLq7iWi14zfRjTeQMXBqMwp3SAS/wFqPsuckU4i6SYn+I0BFX/xQRO74uFs6cTp92I6tIapMdnIvV0GipLquEX7ssGn8d/PMlCkK/l+QjMcEXo6tA1oetIt5FAYi03OZ8L2dVjdCR2KSJGqU2KvtVXNfL7NRXwme2PloZWFKdeSOVSA0T4ujmwdr781KwgCFPAp+paRnyqrh0o8vTt29s5QqOAAl1tnSxWSPRQhCdsbjDaG1qRl1uCvJR8nuGma6DHfwhUFFdyzY+FrTmW37wUvT09aG9u54JrKjxPiU3nsSxeYV5YtCoKh787xjP1Giob0H4+mkTnonEu1C2Xn5yH9rZOOPk4IWrNXATPDUBLfQuObj/JaTaqCzKzMsOZn2I4BadMs2lpAxGLw1CVWYqOln7H814yx+xTcGqQxqSErQxXveaa4ipkns5Adkwm20BQZMwr3AduQR5IOZOG/dsODxZM53nohXu51unrf32vEqEDiVgWhgXXzUNlcRV2frSXBQ05sVcUVaKjtZOtFcirK+7gOZ5HSGm8+5+/m1N3o2kHQJ2H29/fiYrCKtSU16C5of+aKyFBSuvITy3ELb+8EY7uF69Hm0zQz2tjVQOaappYkFraW8Kc5keKnYIgXFs+VYIwlaitrFfV+VAkqq6slsUI+f4UpRYidE4gGirrYe9mh5zEXP4QM7cxg7axIUdmaivr4B/uyzYBNLuOTD7z0wtRWVLFNUjOvs4oLixDfU0DpxcpdUbRERp8TKaNFGGoKatBTnIenNwd+HzdnT3c3Ue1U+VFFTxr0D/MF6ZWpvjxg118DnIXp9QfiTsqXj658zTW3L4c1flVKM0s5jVTBMpjhid0DPV4Fp6OtjZ62ztxdm8cakqq4eznymlGbQNdtNY2oyAxl8fAWFibc1Rs4GgXG0dLtkSg1OBwgkpZf0b7qYaJBBXBlhJONijJKePoEdkt0PBoGkV13b1ruVicIoZ0DNVvjYY4oMHMdG0IAyPDQaKKfLHI84veD+MB8wgnO1zI725/0YYGQRCuHBFVgnAFKDv2KNBLtUgkqCgNpaWjDRMbM+iZGELPyoQ7/TLOZqEiv4JTLw6WphwFsrC2QPjiMJzYFc2iSet8d17k8lmIORAHYwtj+Ad6IyU6DRWFFWhrbmfPp66eHrTVN7H4MDQ2hJWDFVskNDe3qtYTsz+OLRRiDsTzMQs3zOO6rJbuFhYEJAZJFJHIoW5AKsIuTiuAW7AHHH2cYOthzwKH6m/odVm72HD0TcdAD83VTehsyeFOw5aqBpQXVPJavKMCsGLTQpw6GI+6inquSSKBQ2tevnkx10W1NLbCzMp02GgWjYNpbmzRsEegKCA9jqJctKaywnIs3Dif5w62t3QgIy4Lucl5bAK6bPMS+M70vmphRedy9XHmGi6qgSPh23N+fA6v08uJ7TAil4VNqQ5AQRDGHhFVgnAFUKs+KSGOapx36zY87/1Erev1VfU8uoUEzg0/vx7pMRnISchl4UXu4yQAjvx4HNkJueik4cZaWkg4noyS3DIeAlxTXAOtXi0knkyGm58bCtILOWpEIoc+9HluX0Mzt/aT03p5Yb8lSHtbB7ISsuE/y5/TY1TnVFdVz/VWJABIoFCKj7rA6stquT6KRFZ5dhnfFt+xDPVldTi69Qj0DfV4fAtFi2jOoO/cAGj1KWDpaIWypHx0trTzOqgzsTy1EIYWxlh63Twc2RENcyszFnKzlszk7jt6fTSXb86qCBz6+tig60m1To6eg+1JaH30OuhGflw0Hod8tSgl2t3Vg40PrufjSCwe3HaEC81JwF0NtNaASH+u6erq6IS1nSWnZuk59I30ERIVyEal/uF+V/U8giBce4ioEoQrgGbS+c70Qda5LBZKhmZG0NLVRmtdK+asjOAapvBlYTh7JBHf/PM73Pm7LZixIIRtFUzMjbioPTcpnzv3qONNi1JsPb1cP9RQ08SF2lTs7jfTh6M0NNqG5rZBS4tFER3v6uXE31OkiSNRza1oqG6Etb0l1yIRlIqjFBWNw6HH8/w8hYLraij6QhErXW1tHmzc3dXFqcX0kymcXiSLBjd/N6SdSEXK4QSY2pgjcF4QbFxtkbYvHh3NbRyZoyJ5dibX0kJfYzu2/GYzOju6YXx+2LM6dM1ItMQdOse2DtSJ5xXigcjl4Zw+pKiXR7A7O7MT6t2EJKJcfVw4Akff92877/FFr7W7ByU5pVctqgjyr1q6YT5O7TqN4qwSGBsZcCp1zuoIOHk6wWaKWCkIgjC+iKgShCuAIjcLr4viyEjcwXiU5pbDxMIYi66fj8bqBmx9/Vv4hvlg3vq5iN0fj5iD8VzrVFpUgTW3rsC5Y4mkj1gUUFcpRb3YGV1bm13DacRKSkw6tLW0YOtigxnzguEV7MEdZzo62ty5R1GomP3x3I1GqTMyFqWoGYm303svmOLmpuRxMXfm2SweYUNdeDTuhWYIzl8/F7kxmezf5OTrjJpC6u7rgYW9JQuqU9+e4HPQWmk0TkVuGcoziuA9LxAZhxI4SsWRr/ZOdl03sjCGz8JgGBkZ8v2kn86xx5XHDA/Yutmhr1cBVy9nuD3qhramNn68ha0FdHV1VEXivqHeyIjP4uJ0EnlKnDwcOEqnnj4kx3l1SLQq+vpYnOlcxCH+UtQVVqH0TCZmhPogfGEoJyJ7WztRFZcDM30DEVWCIAyJiCpBuEIoGkWu2xRJaqprRmVxJXfbUSTj9v+6lU0ryczTwcOBU0c0WsU71JuFEaXcTC1MVQN7SQRQNIk8jyh64+bnitN7Y/k4qona8X972CiTDCgpMlZRXIWa0lp+HNX8kFCiAnNKHVJqj1JtZKFAYifzbDaPoVl9+wouhu9sbYeDmx0PKybx0FDVwBEhEnidbeQ4roDXDE+OUJGY6jcm7RdWWtBCfWUDTR2Hvokh15NxLZmWFrp6u1gI0eDjgoQ8lJ6vjTKxMmUTz/g9sbwmbW0deIR6sHGpleOFVn6Kzh3fcZLd0UPnBXO9Vl1VHXT1nOAV5MkCNjk6hUUlCTk3PxdOZypx9XaCk4sdTmw7xilYWzd7uM/wgI2L7WXVWVH0sCQ5n69tY0nNoP2lyflwDHKDATUdCIIgqCGiShCuAqq1ObEjGimnU9lksrW1HTFHzsHW0Zr9qkjUeAZ7sElo9J4zXIdDKb6QecHISczhmijqJOzrVFoZ6GDOinBkxGeitaWN64copec/yxfpsZkcwSFxQTYJ1E1oZGqIqDVz2C+Kxs2U5VdwtyEJNipapzQZ+WXlJOUjdNFM9oHq6+hBRU4ZEvbEkacKizgyBW2sbIBHqBd7W1EtFc3cIzHCekSh4NfHQ5KtzTkaR+nAjub2fsOo89j7OiP6p3g4OljxfRJ6zn4uOPPDKRZmeob6bIdQlV+O4tQirHlkPXthNdU3Y98XB/i1EkknU9lyglzOKWWYHpeJtJgM7rqjYncqgI9YOovnDBIkEo309dlzS2kgSn5b+Qk5WHDLEo7CjZS+nh50D+M8TrBP1zCeXIIgTG9EVAnCVUAF4ulxGfwhX1FaxSKKIkrhi0JhbW2O7p4eOLjaw7awEjs+2sMiwdXXGQ5uDuxfRREu8qQi5dLV2YXAcH80NjSzsaezh8P5Lj8DBIT7oaqkijsITS1N+Lm1tbRZbJFQo7omEmtlNIevqRXuAW5cI3Xku+MczZkRFYy4A/EsniwNjeDo5chpMnpexfk0GqUTzUiwOdtytIZSb31stKnFaTeKzNUUV3NHoZGZMdDZzbVkSo8rSydrWHs5YM8Px+By+0re5hLohuL0Yo7IdXKUShsmliYwMjdBRW45ClMKWFRRET5FqkiEkd0DQTVXdKPU6qZHNvBIGop0UZqUxCyN/1FaNHgFuiP1cCIMDQ3YaZ1Fz/nXlrA/HlaOVtxIMKJfigb6sHSxQWtd85D7zewtoW8kUSpBEAYjokoQrgLqtCMR1drSznPh5q6MxKI1Ucg+nYH97+xhQeQd6Qff2X4wNTfhlNU3//4Brc1t7EdFacHi7BIuDF+2YjGMzIyw+5M9aG1oQS95U5kZo7uVOt/0cNuvbuZxOEUZxdDR10Hw7MD+dCC0kJuci5zkfBYgJM6oYNvAxBAbH7iOH0NmpbGHzrKflFWoLzJjM7Hw1iWoyqvgyBTViHmGeXN328zlYXy832x/5MZnczE7RcQo4kWRq9bmVjgGuKLOUI+FCg04tvKwhwG5jGeXcgE8Fcj39vWxH9LJbcdUM+f60Me1VK2NbbB0sGQjUXtvR673otE9ZEhJkThyT+daM+7s6+SuRg//C7MNSQBS1I1qw8h7qb64BgaG/bPtyPiUasu4gcDUiNdCxqwjFVU8UDnYExUZxSwuB+7ziPDl+YCCIAgDEVElCFcIpde4u87MGJUVNXDzccH8ZZHY/8FeNNc09tcZtXUgdkc0jwa5/+k7kRqfwXVSFHE59sNJHldj72aL3p4+VJfVQEtHC41VTWzySfVYS29ajPLMYtSX1GLOxnmw97TH7OXhfG5KQ9WWVHFUi0QUWSYsv2kRspJykXkuB9UlNXxOGlycGZ/N4qs8vwLzVs3mCBRFiahIPGhBCEetaktruEA96VAC1zpFrJ3NEZ+W2mbUltWwaSk5w8/eEMViqCClAN5h3nCc5Y2KvHLYWZkg9sg5FmFU4+U+05vFDD2mu6O7v+5LW5ujS/Q9dyJSsX5HNzvJU4SJTDerS2th7dDH8/xozfRaDQYMW6bCdpqxCLpRGraklgUVmbCir39IBKVT2xpaebvS9mIoqJ6srb6Z16VPUThzY1g4W2Pm9fOQcyIVzdUNfJyxtRl8F4bAahS6CwVBuDYRUSUIatAHK/k6UXSEIiDknzTcwFz6sPeZ4cWRJvJyWrguCkWpBSyoCO3zBdVEVUElyjJL2CHd0NSQhUdbSzv7WTXWNbK4ouebt3o2mhc2wsTcBOaWpsg8lQZFdy+nvNJOpiKwtw+2Lnb8eDLs3PXxPpTnl6OX7BbOp/E2PLIBjTXNvK6zxxIxe1k4C6ymuiYs2riAU3bdDpborW2ChYs1hY+4fmrG0jA0Vtdz/VRtSTUaKuoQtCCYTTZL0ou4MNvZz5mFC4lCGtJblluGgIXBKC2pwt6vDrG1wu2/uRm1ZbXoam9GZkwFnPxcOOKlq0vWEf0iiqB0oOdMb35uS/K1MiVDz/5UIvlqkRUEvR6KSJFb+sWwcrbm7kSloFKHzjtw0LMSEkx50emoya/oT7WaG8M7KhAO/i6w9XKEuaMV2hpaWFBSZ6OBydRyUBcEYXwRUSUI56Fi6bNHErhbjqIoVDTuE+qFuasjB/ktKfEIcOMP/Ia6JlhZmSPnWCpHXyjCQgXg3R1dnDKiqElJeiGcA1yQeTaH91ExOVX9UMSLUlZNJo0wMjZEZ00z6vIq2dGbiq4pWqRnoA9rBQ0Q1uN0G503ek8Mp+no8XR+gqJgez/Zh02PbULCiSR0t3dxd+DC6+bBPcCVa5EqC6tQnF3M+qO8uArOXo6YtSQM56JT0FrfAr9Qb3Q0tKK2uBolGcUcRaKID6X/KC1JhevUgUcROkrL1dc0oSCjkC0j1t6xAtXltYg/dBYBs/y4689rjRcq88vRUtcC7d4LVe0+kf7sHJ8WnQYrdzusunUZDnx9hIUViVFKp9KYn0Ub57PgvBgknGi0T0FS/iDhG7I0FMXpRXAP8dTYR2IpccdpntGopKOpDWn7z/I1dZ1J6VADvgmCIIwEEVWCcN5E8vS+GGSdzVFdDxJVBgZ6SD+VBl1tHZhZm8LO0xHWjlZsvklY2VvxDLq4Q2e5zobEEhVaU2SJDSq5dU4LCgUZdvZ7ThkY6rGAow986ojjYmv6EPdzZTsCsivobGvneiyeo6eg6E4XtHR1OD1I9VRUB0UGopS24/OoRWjI5oAiYI4e9nDzd+WhuU1VjVxkToObrWws4OzjjDN7zvDoF3JypzSgp58bP5aiUNbudrz0mqJq+M1xRsrRRFg72ULvvLahp6PomG+EH4/iMbU2Q2lOKb+ekzujOeVWkFkEv0h/xOw6g8g1s3nYdF0pWRRowdnfhUfflGSXsEg0tDZjN/kVNy/h94LG8tBsRHd/VxaaNHOwo6WDa88s7Cw52qcOeVK5BLnBysmah1vTa6YUoYWDJXtXKa0r1GkorYWhmTEs3Oz4OrMIbu1AfVEV8mMyYePl2F+QLwiCMEJEVAkCDUiuqENOYt6F/xh6ugiNCkL8rhiOIpFAoQ93ElqzN86DR4iHSljRMN81t69EVXE1wlaFI+NUGlrqm3ncC6UAKepBnXSU6rJ1soWlnSUa65p5OxVCkzghA88Zc4PY6ZxEimeIJz828dA5fn6C5vLR85tamqGutJbFB0V0TKzN+qNVCgULLEqrUQE3mWWGRgWjrrwOZWlFKMsu5eOprskrzAurbl+BT/7yOaycrJB9Ngdd3s68dnImN7Uyw+r7V7PgoSHLS+5YgezYTFWROAkVfWMD6JkbYtcn+2DnbMMzDskZnQQKdShSQbuxtSkLnJjdZ2BoYsT2EorePu4YJOF1bv9ZRF43F4W5pTyMmWwT6DWSWHX3d4OWAjiz/TRKM4pUwtHCwQqzN8yFrVptEz0fGYvautiiKqMYBafTVCOEbDwcEHHTwkE/51TQX5pfwdE45bntPR0QsngGKlIL0dXSIaJKEITLQkSVMO0hEVFX2cBWBCRkeESLrzMyTqSqBA1HjIz7i5rjd53haAm16SshF3JtLXA0huqAHL2dELokDKknkrkGiQSVW4gHWts62RrAM8gDabEZHKXym+WLoFl+OPDRPmhDiwu0ybySPJnmbIjCmR2nuX7J2sMOTt7O3CFobmvBhekdnV0sxOg8/cIKMLUyhYuvC8KcZ6I0uxSpR5I4SqWEisRzz5GXlQnmrpvNvlY1ZTXw8HHmyBoJSnr+2B1nsOrBNTC3sYCxuTHcQzzYBoGOdTPQQ3dvL5Ki0/ia0NgeGpdD6UoamUMilboAt3+0G0tvWAjvCD9U5pZxGo8ifRTFy4hOQ8DcAJjbW8K8od++gIQVCUOaEUhjbmJ3nkFJWqHGz2hjZT2ivz2B5feuYvFH0LUKiApEzNYj3LWnTkt1I/JPp8PaxZY7Ivvfry5kxmSiOK1I41iqfaPU74xFIWw/IQiCcDmIqBKmNVRjRGk/8l6qKKriD3SazUejSVIK+ocUKz+0lZDAIqFEoopMPQszitDb3o3YnadZqFDCj4QOmVvOu2kBF5UbW5ni1P44Hj9TW16H7KRcWNpY9LuRK4BT3x6Hnq4uWhpa0NLYL+So+D0/IQ8bHr8BOcl5bAlg7+XA+6xdbLBg0wJ8+8/v+/2mCC0tFnYUtTHU0+Pz9Xb2r5UiMeqF80RWXBZWP7iOTUVdvJ24MJ1UmbmNOUysTOAfGYCaoho0VjZyV6C1kzXcgt2h0NHiuinqOqTH2TlYo7erF8s3L2G/LkpRUjSLLgSJvFN7Y1hsBc4OQOiKMGSdSud03cJblrAQzEvIhW5XH/yCPWHjZscjYBzc7dm8szhVU1ApoTQlvS6lqGJ6e9Hb3sWCk+qy6NqaWJhwTVRrTRNaahpVoqqxupFTikNBz6tvbszvmSAIwuUgokqYtlD66egPJ3hgrk+oN2ydbVBTVouWRjKq7FSl1HS0tXkGH0VXqFaKoLRSRWEFdn60l2fVJe6L53olqt2hETHkBm5sYYK8czmYf/NiLghvb2njMTYegW6IO3yOa6KImx7agOrOEja/1DfU4+fR0dVGR3snCjMKEb4uEi2tbfAL6x9GTJDdgo2dFVbctoxnCzbXNbHHk+8sX8yYE4Sk/Wex5tEN6OnqZpFH0Sk2+NTuVaW6yDy0p7OH5wHS4Obmqga4B3pw+tDJxwkFiXlc28RjYXp6WXgGzPVH7LajMLEyQ+TyMDTWt+DoF4f5fP5zA/h6zV8Xhf1bD3MHJaXyyJiU5v+RpxbVOK16aC0X1KceS0HO+ZQirag0rQgNZXVwvm1pvx1Fe5fK3HMoyK5BHaqloigj3Wg0DqE+noZelxIel6Ony6nTgSafVBtHqV2dYbo+NZ6zvRP1FfU8E5EsIahOzNrZmlOdgiBMP0RUCdOWmopath0g6Ct1yB365iiaG1rQ0dEvCOiD2MrZBo1VZDUATlVRp5mZrTnO7I9HR1sndLW1WVApoceTaSd1y1FExHNWGVqa2xAY5stu5TQ7b+0dKxF7MB55aQUc3eq3cNBjUUKjaZReTlpa2myWuf7O1Rx1qiquQltrO1pa2lCSko+WigYsu2kRr5UiaGTbcPzzQ5y6aq5uYud0irLpG1JRvIJNPkm0UXSLIk9UT7X0xsX9BfZaWkg7noqFty1GXnI+qmoauLbJM9CtvyaL0mo0HHmmD+qKKpG2Lx6OIR6wcbZhC4Xm2mZUVdWxdcP6u1dz3VV1aTU7sbv6uEBPTwedDW0oLqphQVOQkNNfIK6vy8KPBFB7YytST6Rg/k0LoGdIFgyaRfjqUBSK6G7vRGNFPXfzNVKUiWq9jPS5U1Id9S4+MgoloWxoYczPQwKbfaoM9XmUDo3guRT0/iYfTkLe2WzVtqzT6XAOcEXEujmq9QmCMH0QUSVMW3gY7/nPa4qcZJ3L7nc57+hi8825G+ZyXRVFrajomaAUmcO8IPYrIsNNgsSPOiRwqKuOCsSpK46egiI39BwUQZm9OhJOno5w9HTE8puXwNLSjIvOSWCwkGvrryuiaElvXy96evuNOem527X6sP+Ho+jq7sbc2aHISclFQ3UDdHV02B+LIjB0DhMLU1QXVsI91BMOng4oySxR1V3RfidfF5g7WKK8qPL8MOUeFnVL712JXR/tQWlWKdsdVJVWs2v88luWcE0VRa/sfJ1QkVnM9WP5ZzLgu3gGiyqKxHlF+rF3VUFqAXTYHd2Cr4+5qRHqs0txaHcsp/50DPXg4O+GpoYWrmcjJ3cl5VklbL9gYWcBRx9nlGf3X2d1DIwNYOVkw5GinBMpyDudAStXWxZUdcVV0DMy4LE5PE5GC5zKM1ETSub2Fjxwuaa4CtrnhZQSqh+zvIQvFlGZV6EhqJSQsLX3cEDAvKCR/SAKgnDNIKJKmJbwGBMFpYTaOZJDAoCiTv1De7W5ZmfDPWs4OkTRh46WXk4Luc/whD99WFK90PkICosEXR2VwaS5lRl3uFk72XDEiOp46PvOzk4WS2kx6SxAqM6IUl6NFqbwDvdB1plMFlfkcUW1SDTs2DXQjc0xu5ra4DrLC28/9S+2Y6DHLlgSSS5XKM4rxbz1UWzUSaKJICsAem3kN7Vg8yLEbo/mCBmPbqGxM+bGCJgfjKToVCSdSuEapPBlYWyvQCLO3M4C2goFpwSJ3R/sxtrbV8DK1oJruxz9XZF7pv9a6evqcnF95KpIFoR9rZ0sbtx9XdHY1MrGnsUxmagvqOTrRFGpjqZ2ZBxKQNDKcC5wJ8FH5yL6o3QKjjRRNyWJUfLMUkLPH3XjAhZdldmlbH/QVNWA1romBK4M5/ehsbyW03padtowt7dCyNrZ/JqVUPo0Yv1sxGw/3V9Ldh5K2dK5qdj/YpDozo2/YL8xEDI79ZjhNcj6ob21nf3H6GeNzE1tHK0v6cElCMLUQUSVMO1oqqxH+sFz0DczhlavAg2VtSwCKJJBaTBKxbGreGkNt/5Tyz9Fjag8h+pnCpPzsCBwCezcbFFdXIOywkqELp2J4pQCFg1koEndcyRgfOcEsMt65NIw7P/mCHe3kfChmX93/24Lsk6lIflYEtY/sgEuAW6oyClDQXIBizqvWd6w83LkaBq1/WubGXBhPXtgdXZj99cHcMOWNTA2MEDB2VykHEpgQWZibQr3YE/Mvm4On2f/e7vhO9sfXmE+LCbtPBxQXlKFuCPnkBKd1m+lpQDsXe0Rd/Acu8ibmRqjnka+sLqj+XtdaG/rRFlMNhz9XGDlbg+D5Dy2hKDIzryN85B4MIHtFyj1RvYNeedyMWtVBMxdDVHd1KYSTSR6KNLU3tSGgrgsuM72R0lmMbR1+sWFpaM1dzgS1GW56NalLCzJ3oHEENVlUTckUZZSgPbGNl4nrYWEmluYN7zmBrLwsfV2hJ23M4zPD6FWh0bxLLljOa+5ramVxSZFqEwsL12gToX4ne0XarQGQu9PTw8No74ARf1owDVZbxAksMlHbPHGBXzNBUGY+oioEqYVHc3tSNkbi9baZug2tGDZjYtwYNsRtlPQ029HyKoI2DnZwNLGHJkn03j0CY8/UYPsAYxMjBC1ajb2fLqfPxBdvZ24Nop8nsgjiqIoAfODeJhx0sEE7qiLINfyE0k8x66tvgWFZBWgBax5aD1SYtNRkF7IRdZh6yI5gnFmTwz6iqthZ2fJdVotTa0s1Ej4eYe4wyfAA1YOllC09cAj1JPrp1h8aWujMLWAC8R9Iv243iv5cCKvnbbNXD8bHV3dSI5O5W0sGKmYnEbdKBRc+9TR3C9UeH+/7zu7p1vYW6AkIRfGjlZwC/XmWjN9E0NknsngdCMJGxIU1MFHYo1Skn3udmzEqSwa505EbW3oGuhxDRWZnCqjfnRM8OIZLHCUULTH0dRp0HtJaUWqeevt6h97Q9AQ6oLYLP6exJ2prTmbpQ4HiTelgLscKLpE6cOm6v6RREMJNirsV081H9h6GHUV9aptJK6LMotxHKew7q5VErEShGsAEVXCtKK5poEFFdHT0Y2mvAqsvnUptI30uE4qJykPp/fE8MiVoDmBcApwQ/qxJNXjSQx4zvTiiI+tozU2P3YDkk+lspeUf4Qf+1F5hvugmUa3JOfzhyZ13VHqbSY5gRvoo6m2ib2xCAtHa3z8l09hYmnCkRztNh0c/fEk3PxcsHDjApSkFSD/bA5H0qhyy8beEpvvXI+azBLYmJsDrT1IpIL5lk5O2flG+qOpphFFh0pY5HnM9IK+iQEXkRM0soa0DaUlqfOPapmU3lwUQaK0IQkbsl5QT2mSsLJ3sUV5RQPvt3KzQ5+LDTyNAll7VZ0XVCTO6BpR0Tj5VHHEJtQLWmSC2qfg/URXawcLz86OTn5+Sr9SQ0DwohnceTgS6HnsfJxQNERdE19bB2tOJdLrGG3oGniFeaMoJb/fw2zAuvyjArkAXwl1laoLKnWoSYJ8vajOThCEqY2IKmFaQbU86tD4l5bSWlgFueHzv32FLpr5RwIACiSdSMbiTYvgFxWI7DMZLDzm3DCPRdHZvXEcJfGI8IG+ng7Kc8owa/ks7Ptwr6ognCJYJBgoomJoYsBCjD5oaTSKjaMV7FxscfibY7yG5to+ruNprGqEua05F3vXltWgpqCq33hzljen/+565CYk7TzDKbyGinrkxueyrxIJh66OTpTnlGLhrUtYmNBrodQWCZWYHac5xUdCp7awGoHLQmHtaI2Wpv5hwSR6Ms9lY+6qSCSfTOFoVV93D3SogFwBeIZ4oLelHTXldTBysMTR7SdRklWKGfODEb4kjIUjrZPOQ2k3GilDtNa1wNjGDAry0NLV5mvTP55HwXP2aL6ea7AH/BeGcM0TpfcuB3uyaXC2Rm1BlcZ2ir65hfvAwslmUBfgaGHjaosFtyxB8uEEfg8IM1sLhC4Pg72nvcaxSu+xoSCxSbVWgiBMfURUCdMKquUZiEOQO/Z9fYStC6i9nuCByPp6OLXrNB78431YeNtSmNmYIzsmE7nx/eklgiwT6AORxqOQ1QF9QCqLxSnl4+jhwP5TJHBIcFSWVLOpZ0hUUL/oqW3kdB49hIQRFarXldfC0duZO/Nolh0VPBuYGfFQYiq+Dlo0k7vLdrz+PSwdrViEUS0QRZUoYpR0OJELvOkriQt6/sh1c1CUXoiAuUEcRarOLsfitXMAXR2cORiPhupGNiUlv6oF10WhKLMIRckFLBiD5wbC088FCTvPsN8UzcqriE5lV/Kkk8kwsTCGnYc9F5fTwGV6HbSeloZm9prqaO+C36IQZBw8x12UZIFA18nS2QZ+i2fAxsP+iocWm9lZYM6W5UjdF4fS5HwWbXRezzn+HP2ic48VJA6dfJ3ZmoKc9+l9p4jjUPMCjS+RYrxcMSkIwuRERJUwrTCzt+RIEdcMnadXWwsFaYXsBK5MT5F4oLROX08vchNzYaCjA+MhPiwplUbRHxs3W2TEZ8E9xB35yQWqD8q2hlauL9LW0YKVgxWWblrEKbjoHdGYu24u2y2QGCKRQdvJgqCxtpG76MgLy9mlv+0/PTqNz9nV3M6pQDqehhIHzQtCe30L6ktqoGdswPfJY4qK2XUNdLlAOycuG05+zph3wwLEbI9m4UbGlnoGumisa8LSDfORGJOG5roWpJ1Oxy2/vBFODtZYtnEhGstqUZFSiPzoDBiZm8B/+Uyci05ls1FevJYWEo4l4/Ynb4Gtix2n86gAPTsuC8ZmJnD2c2VTThJ7ngtnwEBfj13fSQyZkyC0v7R1waWwdrND1B3L0LhiFjpb2nlZ5LRuYmcxLnVK1N2pdGofDltHG5hZmaL5/NgjdWiuJNXQCYIw9RFRJUwrjCxMMGP9HC5Wp/QTwYOItbVYaFAtEdcUkaA67+bd3d0D3T4FUo8l9ztmu9qirqSGxVRbfStqK2vhGeCB5DNpiFwewUaSZbnlbBLa09nFQiN0xSwknUpFblIu7yfK88p5GHN3exfXHnW2dLCNAhU403O7eDtDp0eBzJgMtn+gmq+eti6uhaJIWvDCGcg8eI6FBNdoUZdgUh78l8yEpb0V/OcHI+bgWSy6fSm7wh/98jCLNRpwrEfRsT4FLKzMkRuThYWr56C7pw/N1Q3IO5MJa3sr5J5IhUuwB3zmBULb2ABFOaWIPnQOpVn9hqkECUFKldKMwdzTGWig+X+G+ghfHQmFFuDo7cgdjZnR6cg7m4vl961C0OLQUX9f9U2MYOc9eV3MqVFh9e0rsP+rQxrCysbZGktvWqxR1C4IwtRFRJUw7SCTyMhbl/AsOIqiaBnqwd7DnoUQQXVPJFK4Kw6Au78rsk+kcade3tkcNsi0c7bh/zx0nG+YF2qqGxG6KJRNPmctDsWSOQHcQUhFy2RfcOSH4+jt6YOBsSG6O7pZNNEg47X3ruEUosK0Dy21/dEfExsz+Ef6w9LaHDmnM1BXUsvPbWbdyx5N7U2tnG7LOZbMgooeQzVNyrE6ReeyEbBoBmKPnWNPLHqemx+7gdOPVOfVXN3IIouEHDmrkzGmjpY2Mk8kwSPcF+nHUtDs0gz3MG8WSLpGBmhq70Ti6TTUq3k60ZqoDopqu3o6+kfKUHqVXnPykQTMvWEBGsrr2XWc1kjpQgtbC0xXnL2ccNOjN6C2vBZtLe3cSECi2sRcnNcF4VpBRJUwLSGTR7pVFFXi4NdHuSD9m39+19/tRnVR1OKvpUDIghA2AKVic6qF0nO0gqmhHrKOJXKhOhmCknu3W4QfotbMgaWtJRtplhZVQKENLqBubmvnGXrkQE7pOKqTIv8oEh+NNQ3Y8pvNnDoszillU8/wZbNgYWOO2O2noavb7+1EoqS5tgn6LrZc69Xd1oHOpjaOqpEfUl9Xf4SNIm5GpsZszBm1IpJrmDJiM9lp3dBInwUd1fxQXRNbKHAxeTMUPb1ob27lqFLEutnsuN7XRxYLQFFqIbQNdLn2i2baUd0UwV5Tze3wDfNBXXENizT2jNLq92nKiE5jV3GaY0imBzOWhV1x7dS1AhnD0k0QhGsTEVXCtCYvJR/1lfWoMjfBHU/dhpif4lBZWMX1U7OWzYRXsCe7dpOQoULskKgAFBxLgqK3l0UZ1SSR51NnrwKphxNQWVjNI2qsXWzg4OYAG1tLdHZ2sycVpfC6WjrQ097N3ktWjlYIXTADrTVNaC2thaO1BYug1AMJLFhcAly50JvDZVTIrqfDQ4RtXW3Q10tmlz3cgUZeSWRGSXVUVNvTct58lFJuyzctwoKVkez6nheTqfJ2orl0FLkinyiKyJED/MIty7n1nww3M0+n87gVSn26BbjBOcAF6+9ZjYPfHOWOxpaGFujq6nKBflC4HzJPpbOfF52HomW0FloXFdGT9YCNmz06WtoGOYwLgiBcS4ioEqY1VSU1Kq8gilrNv24ep/+o3in+4Fkc3noEDv+/vf8Aj/Suzv7xe9RmRtM0M+q9d2l7b+4NsE0gGMJLHFr+EMgPAqEmtFxJyEUSSt4QUngDed/QCbbB2Ia1197eu6RV79KoT68aaf7XfUYjS7va9a5Ze4u/H65hLc1o5pln5H1un3Of+5TkYOsDG+EdcyHqC4jgoZGdy41J7f0bcfSXh0UQxVJSZIqQLTbmYW1+dCsm+sdxzzvvwvHnT2HaMQWdSY+SumLUNFdgsncMh//ngLTZWGmi4LHkWTHRPybipai2GPaCTHimPCKi2EJj5pXfG4C9OAeeCae0IPlY+sGmF94Pp94oyE79bL8ILJrCc4qyxbTOvYBs43EvYVq6DiVNZZjuH0MwywJNcjKOPnVYvFLRuTmJlxhuH5QqWfX6KqzbWIckvRbJ2lRZTcP3yPYe18TEq3uMCICY/OndQjSK3NIcjPQ4JNGdE5QKhUJxu6JEleINxVw0Km04Vp5YvbFlZywuRubYe29bP44/fxL2HCuKqgqx9o7VYgrv7xhC8/ZGzA6OS8WIuUP8kzlIjh6HPCdbXlqzEfOxeTEeD7cNotVmElM4R+0ffPfdSKZ4StJg+Hw/Ove2oKC+WFbhsD3HnCproX0xcXywpR855XlYc9869JzqwmDboGRHcUWLzpwux+593iU/S1ElFaf5mKxmoWDa+91nkVWULdUttuloOG/Y1YSBlgGpGLHVue5NG5Gq0aD9pbPY9J57EPYGUVCSJUGeNOTPc1fhvvOYHhxHqK4I7r5xeS6uz6lbVw2XkdlSqTDZTfBNe8W8n5KaJF6r+u0NOP2LQzDYTFjz1m3ILs9dTFVXKBSK2xElqhRvCFjNcTtmMNU3JiP/XG1S1FyOmrVVaDl6QR7TsKEOL/z8JRSW5qJpU4N4gvpPdMmIfkFlAVJTUmAoysJUryPuK0rSwJiVga6z/SJCJIF8bk6iFEL+oIiW0c4RFDeWSL5V5MWzWP3AerQdbBXxw7F/hmRS3DEYk4uD+f25UETaj1x3o9WnSeWIbb6Nb9ksx5ldlotDP98n/qSdb9+BjpfOytobVthyaoqQbNDC0TGMJE08bJMtP75/tv8MViNq1lUiqzJfjs1sM+PMU4fQ9OBGeEamcfpXh+NRCQBGWvpFWK170yac2X0SE4OTKKzIh2t0GrOyHiYq03112xpkYbOY0JM0Ipy4IHrWE4A52wJLjhW5lflIVYuDFQrFbY4SVYrbHnp8RtuH0HnkAqaGpqRKU9pYisEzPbJu5b533YXJoUkJxRzrdeDh9z2EAz/bFw+ppJcpOQmj3SPY/Z/P4ZE/fRQx9rdoCmf0QnROxAyn6HQWE2YmXDBnWmRNDaHQonAK+EOSD8WQBrYHOQXo4mqSqgJ5DI+Rrb2IP4ywNyDRD0wop1hjpYm3vjM9qNpYC+f4jDwnX5sp7Wz18X0wmd3RNYyChlJoDVoY7SZEuRdvITKCe/+Ym9W57zy0ZgNaXzqLbe/YKeKSE4dnnjiEpORkad0xw4oCb7p/HCau1zHoxXBuL8sRUSXndT4+zdh052qZKhzrGpX3QR9VYNIN9/CUmPsLGkuVoFIoFG8IlKhS3PaMtA/hue/8CpFAZPF7bM0137MGJlaWoIE2OQW6bCMeevwBiU1gZhT9QcYMI9KNevGKp6amovdsL6rv34jAkwfgmXRhZnAMJY2lMt0XjtDbFF8cnFhPU9RYgv4zvZiNROF3+SVWgUKNvqxoiIt5uXNQC++kR/Ke+D9WrFhhWv/wZlmY3LirCZHQLLKKs0X0tR5okYW9W96yBeefPS5iSda++ELiowrO+LDl3Xeha3+LVM1Y0eLx8z4WoXQmXXzpc0GmtPEMdjP6j1yQDCsuMg7OB8VwHs/sAkZb+1G6tR7pZgMGT/dI2CZN6QwDJVzfk1Wcg7HWAZlIdCyILsLn5ioZhUKheCOgRJXitoZ+o9O/PblMULFqw+XDWqMep357WszhzgmnrKjZ9PAWCeyk2LHlxKMPZigSYnHPFXf8VaytRMPD2zAzPClCw2C3wDnlQfvhdvFssTXIPClWmijEqGhoFmdFijEGGbkZshOP5vRze85gw5s34+zuU7KnL4UrXvJtqNpQK1lYAyc6seHBDWg91Ib9P9sb9zrlWbH197bDNTwlrUxWjJi+ztUwrFaFgmF0H21HXn0JBk52SZL71NBkXLLNx1CythqdJztRu6Ve1tNwio/fZ4WK7UGmyNM3xeOmQORz8rmDMx4Mne7B+sd2IruqQPKtEhgzzWh6aCMmex0IcjJQmwqj3YKMAjvSM15+3KuBAtM/7RHvGVulrMDRYL8SbElGAiH5jLULy6FvBliFDLv88vnz2LWcvnyNjk3CYCOzSNGmvWLSu0KhuL4shODcGL761a9iw4YNMJlMyM7OxqOPPoqOjo5ljwmFQvjIRz4Cu90Oo9GIt73tbRgfH1/2mMHBQbzpTW9Cenq6PM+nPvUpye5ZyksvvYS1a9dCq9WisrIS3//+9y85nm9/+9soLS2FTqfDpk2bcOzYsWs+FsXNBSsqztFEYGVMLvbJulQUNZXh6FOHJE6BeUxMP6fIobBJTk6BNdsqkQDMnCL0NlF0UKTNjM5guGsUhhwb9u4+jh986+eo2d6Ane++Q2IQmLq+9W1cxFyDjqMXpFLERG36olxTbqy+f70kZ9LnxKm68y+cQXF9MX7v0++Qn1t/33rMOj3wTThRe8cqaOZjmPeFcM/j92LzI1tw9x/eLx4qZmDRIE9TeMgbxOTgBDxTbszPzkkLsXpHIyo31krbka+dkWdD04MboLMZ0birGQMt/Rg414fJoXEUr6mQc8MgUkt2htx4TpjiXrqmUuIgBk92Iyk1WSpUefXFl5xrrv+hkHSPOaWi1XOoDWMdQxJW+rsIhM5953Dsxy/hzJOHcPJn+3Di5/tlLc9SKArdI1Po2XMS7b88iPZfHcLQkTYEnV7caLxjM+h67hjanz6EzmeP4sLThzB2tkfE6vWElUa2tE/8dB+O/uBFnPz5Pgyf75M2tkKheANUqvbu3SsihcKKIujzn/887rvvPrS1tcFgiLcW/uzP/gy//vWv8bOf/QwWiwUf/ehH8Xu/93s4ePCg3E9jMAVVbm4uDh06BIfDgT/8wz+UCsHf/u3fymP6+vrkMR/60Ifwgx/8AC+88AI+8IEPIC8vD/fff7885ic/+Qk+8YlP4F//9V9FUH3zm9+U+yjyKNSu5lgUNx9si3FKT3b6aeKxAwy2ZKzBLHfuJc0iKZKENH0apnlRPtmF8jWVGG4fElHFpHKpMMkamBhKm8rQsu88Nr91K37zg+cxOTiJ9Xetwe7v/UZacs33rJUqAdt9WSU5aL57DTA/L5lUbK1F52LS+tv5rl1wjjnFLF5UXyzJ2tPdI+jcew7FaypRvLZK4hHOv3ROliZXb2uQClTn0Q50Hr6A2m31yOSUXjgiwnE2zOObR6o2TdbepFsN0pYrY9suJ0M8YAwedU97Mdg2AEdnfOKRfjEuBNaZDSioLcL00KR8PxoMIyU5SVbNZJbl4uzTR0QYcsKRlRZOT16M48KgLE1OwP2KPQfb4Blzov6+ddcc/MnPbuhMj1THlsJcr3NPH5FUfONCRINndBLdz5+UtqUwC0y09cMzMoXK+9bL+7sRBJ0edP7mmFTvuJ5IKmjpOgwduyACNaeh7Lq8DgV6/7EODJ7qXvwe4y4u7D6FkNuP8i310pJWKBSvLZoY/+a6SZicnBQBQ7G1c+dOuN1uZGVl4Yc//CHe/va3y2Pa29tRV1eHw4cPY/PmzXj22Wfx5je/GaOjo8jJyZHHUBh95jOfkedLS0uTf6YYamlpWXytd77znXC5XHjuuefkawopirt//ud/lq/FD1NUhD/90z/FZz/72as6llfC4/GIGONzmc0qr+f1gO27F/5rNyZ6HdBb0lGztR4TYzPiO2rdf16iCxhUWb2xFvZ8O6KhWWmljfeNSUsuEbrJllj1ploRIf1ne/G2zz0GR++oCB1TthXPfPtpaRvyosnk8azCTCQnJ2PVXavhGpjAeNcw3FNulKyqRMnaCszFINUj97hLWoUBpxdnnzqE3KoCFKyqwJ7/+i38Tl88JV2jQZpBi22P3SHLlofbh0XoVa+rRN+hC5genoxnRMXiK3Yo/hruXwePy4eme9ZJztTMyLTs5WO0Q2ZRluRVOR0zqN1ah9zibIRcPuRWF0plg+LIO+ESg3rJhmr0neySrzmtyCrfXR96i0wFLjvPLh9O/GSvtFJXYu3bdoih/lrwz3ikQsXPZCXq7lmDwuZyEbHdu0/At3SFzhJKtjUiq7YEN4LRM90499QBWYe0FLZZ7UVZqHt4u7Qpf1fcYzM4/uOX4r8HF5GUkowN77wDZuaGKRSKV8XVXr9vKk8VD5bYbPGN7SdPnsTs7CzuueeexcfU1taiuLh4Ucjwz6ampkVBRVhh+vCHP4zW1lasWbNGHrP0ORKP+fjHPy7/HIlE5LU+97nPLd7Piy1/hj97tcdyMeFwWG5LPxTF6wtTz6s31kjrj1N5gWAYR39zDOt3rpaVLbZ8G9bcvVbSx9v3t4hnKbciD7vefZdUcBxdoyKqsoqyMHyBFZ5xGCzpcA6MY+ZMtxi/DdE5/MHnHkPn6R5ZNqxL14rXKqc4SxYesx1nyrGidtcqzAxOoO/wBeTVFWE+2yqCqONoO1btahYRlc+25C8Py5RewnPD/+7hEuUTTx/F3R94EI5uhxxnmikd69+2HR7HtFTS5uZjGGobjCe9T3vQdbQdNdsa0br3HCYGJuRn+FysMu145y7JwWLW1eknD8FG/9bpHmSW5mDTu+6UytfA6W6ce+6EHAcFFVPbm+/dDNfIpEwCWnLj/54SLqe+nKAi7tHpaxZV/HxWElRsU5oyLdKOlcf5g/BPOC/7PM7+sRsmqqZ6Ry8RVISfNYcIuDPxeogqtoNXElREPHIunxJVCsXrwE0jqlgZosjZtm0bGhsb5XtjY2NSacrIWP5fWBRQvC/xmKWCKnF/4r4rPYYiJxgMwul0ShtxpcewGnW1x7KSZ+wrX/nKqzofiuvkpxp3ikmYlaigL4S9vzoIp8MpeUrpZr0IqkM/3y8XaE7RMS/K5/Ri349eRM3mWkwOTYjXqv9Ut7RYGNCZmW9DYHRSWoMzjmm4x50wdY8ge3UVbHnNGO0cFhGkT9fJTj0KFVageg+3iemadB9oxdDZPhSuqcSsPyztOQnwTEmWqtqiiZnXSQ0k7NPvCWCkfRBDFwZlCe+cN4C+E+1ITtKI94hp6Kxe+UKzOPzz/bAWZskkYeWGGtRua8Bgaz96T/VKZefUb07g7sfvReeLZ+I+qAnX4oLlmaFJbP5fdyO/qRRZ5XlwOaaRxABTm0mqYGzpsc3EQM+EsGLw6JVgq+taied3xauE8ReBVNOYZj/eMQzfjEdS7G1FmbAU5yAaCiMw5ZFzQSHMScz4a9+Yv+YCHr9UJC8Hq5x8f9eDV2rtcSWRQqF4A4kqeqvYnjtw4ABuF1j5ok8rAUUcW4qK1xaKBpqwTz13QjKhWEGh4ZwrY7ILMtF7vheHnzuGh9//Jgye7RUxIWiSpMLEFS1sl3E1DJPRafROTddCn5oOnTYV5c3lmGrthWvCLaKFYiziCUCXmgK3O4DajbUyVedoG0RKuhYN96zBkf+7GxFvUCpFFFZak17EQu/hVtTtaJAqEE3hFAkUUpzUE2ElVrAkuSjyIh0ORZBfmY9Vd67CwIFz8ro00TOziqZ1z/MnUbK1QabzKIKOPHFQ/GFsC3IdzY533YGWvWflfXH58XxkTqpifB0el2vMJW1J+nF4DGkmPXQRswiv4KQbk22Dcqro2xo53w9ztlVanpwEZNYVf+5i+D4y8u3X/DmyRZZTXSDnkeRUFWKsawST3aPynJZ8Ozr3npWqWcXGGkyc7oS1JBfGXBscZ7rlHHMCzl6RjxtBNDIHnd0s52elKpKtPB+p12kXYrrNJJ9xonq3lFR9GgxqibNC8cYRVTR8P/3009i3bx8KCwsXv0/zOVtz9D4trRBx4o73JR5z8ZReYiJv6WMuntLj1+yL6vV68b7wttJjlj7HKx3LxXDSkDfF6wen6Ua7RvCb/3gGc+GoFHq41oUXm3MvnMHGR7dKlSfgDWBidApep1dagHQWsiLFVg0N6mSsdwx3PX4vHN0jEr5ZWF2IqNOD4WPtIjjoa6IfiqKmoKEMhgyuqAEC0x6kaoCS9ZVizmYIJgVVopogyesi5IKIxmLQ6tLQ8uIZNOxooq6D1qhb1krTmfUScaA36VFQVYgYJxB7HMiuLoqbno+3y+vIz8SA8dZ+lDSUIkWXJouR48GiUcnLovBiq4+7+rxTbpnM40VfRvBTU+LnKhCSibXTvz4m5vY1D2+BJcOAOQo4k15afYT7AsP+oEz9cXS/emczzj19VHYULqVscy2MWZZr/ixZxSnbVCuxEd5xl2RmiaBK0kj7j2LWP+XGbCAkLc/ktFQMH2+H3mpCwbpqmf4r2tIAY7YVNwKGzLqcfpTuWIWBg+dfrrgB8YywulKkMHLjOmC0mVG1swntL5yRzzsBz1X1ruZ4lVFx0xIMhOT6YjCmS8SJ4tblhn56/JefRvAnnnhCIg/KypZPwqxbt06m+Ditx/gCwmk8Rihs2bJFvuaff/M3f4OJiYnFKb3du3eLYKqvr198zDPPPLPsufmYxHOwrcfX4usw1iHRjuTXFHxXeyyKGwtFxYWDbeJToqAiYvROTpJFvk13rcKFAy2YGJ6UoMyGHQ1iPt/z3y/IBa+wqlCqHowooEgxWAxoP9SK9uMdIoTMVgP8vSNSXUhN16FmfQ3H58QbM3imGwO/OSHVH17IcirzocsoRcQXRMDFnXhRmUijsOJz0bPHVTlpxnSpYngm3Og714eMQjvWPLQJx588uBgiKgZ0bQryKwowfLZbJuIMBp20uSjqGh5Yh+n2QRFMrFilpaYgryIfB588FD8xMb5uPCB0oHUAd77nbpxzTMs0onfGJwGjnkAYRls6Ilw/MxtFql6LwoYSlDSXYvJsF8bCEREt9vJ8JBdnY7ilP97yW5K1ZC/Nwbq378B45zCcI/HF0fmNpbDm20WwvRpYYVn15k3wO/1o/e0JMc/zXNAXFmJ7jSn1c/MYuzCI+rtWyfocRgjwVnXfRhjz7PJZ3Qgo0ovrS3B+z2mU3rkGc4GwHK8uwwh/ICzBqNcL/s4xl4yZYKNtA/DPeGHMtCC/vlj2UypuTtwuD1rOtuPAS0cRCARRWlaE7XdsQkV1qfwdobj1SLnRLT9O0z311FOSVZXwJtFhzwoS/3z/+98vLTSa1ymUKMIoYhLGcEYwUDy95z3vwde+9jV5jr/8y7+U505UiRilwKm+T3/603jf+96HPXv24Kc//alMBCbgazz++ONYv349Nm7cKJEKfr8f733vexeP6ZWORXFj4XSbz+mBa9wFe0EmsouzkKrTYrR3FGWrynHgx3ul1ZdZnCUVrRPPHkfVmipsevNmqeLwgkcPFMUGIxaqNlTJxWqwY0j23iXrdZhLTUVWVa4876mnDsvF22S3ILumUKo4TGL3Tnsx3zmCGceMCDn9EiMyBUAiBJRen7T0NETCs8guz0NxYylcI9PIrczDzvfcjfN7zshzpfBYNtYiXZ+Kc78+Jl6hhEeJgZj0ZmUV2hGc8SIlSSMhpvR1BWa8MFiMiEZcSJaAz3mkJMV3DGaVxJcb83sijDTxeAW29UrXVyE2N4fy1WXoev6kVNVEmGZZpCpmK8tDdkUe0u1mEXUJpCWXZ5MbPYq8KFyPgEuJcNCmiUihUJPzOD8vAkpKjGypRufiNwpCXZpkVmmN6RJYai1Z7pV8PeFuxGikES0vnZVIBX72Rm8YjXc2S8XwesLnthVny43nn9V3xc2Lz+fHkz99BsePnFn83vTkDM6easX7PvwHaF4TLwoobi1uqKj6zne+I3/ecccdy77/ve99D3/0R38k//yNb3xD/nJmdYiTdJza+5d/+ZfFx/IvDrYOOe1HgcN8K4qjv/qrv1p8DCtgFFDMmfrWt74lLcbvfve7ixlV5LHHHpMIhi9+8YsizFavXi1xC0vN6690LIrrCwUDlyB7xmZEgLCFlJFru2xKNIUSqz5r7lmN6c4huIcmEElOwpqdjeg43SPVIv4sW4HmDJP4hFjtsTFxPMMggoLZTrw45ZTlIewPY7zHgQ2Sc5SOI7uP49533AnvhFsiF/KbK5BuSUffoTacf/ooau9eIz+Tlq5d8GS5oTVuxnj7IAqayiSqgCKG1STZ9zc3j+qdTZhPSkLY6UPnntNI0mgw1TmM8s11uPt9DyAcCsvvHNO4j/zoRczPMRU9iuTU1LgoisXgGppAyapypBkmJfST2Ucn956XyhWrSRSYFGez4TnE5mKSsM4+5ZRjGjV3rIJndApJM8lSiara0SjiiTETo6e7pMU2z7yqRP4TxevgOJo21CI5LQV9R9qkWhdLToIl2wprni1ejbvOF3Q+Z05Nofw+LCcu2pilxX2DskB6bh4pNN3HYkhbIvpuBDTb08vGzDLGe0jr0ma65syua35dJahueoYHRpcJqgTMbPzV//wGpeVFMFtU2/ZW46bKqbrdUTlVVw99NAzCTE7XSkAm18PwgsRgzrpdTSIULobmdD/38bX1iqFZs5BaXnHnahx+6ghSTelS2KCoYQAnFiobFRtrkVeeJ/lTyWnJsOdnikeHOVYzY06phKx/8yZ5za7jnTi3++WQSVaF1j+0CZ6RSUT8EdTfs0YWDidrUzB0rk++DoxPI6uyWKYKR873SjVKb9ShYlujmKone0bhaO2XFiBH7Cn0KP7KuEZmygVrcS4QmYWjbUD8XvQ/UWhZ7GaEvX4RT6sf3oLBQ+dRtK4GlvJ8dJ/thdFikOoNn8vRP46RzhHYC+wSYDrWM4qxHgdyK/ORW5ojYjQjOwO9Ry4Ac/MoXVuJnudPyHukEKRQYeuNWVx8PpqsRy8MyCg/sVXkw1SSJ+Zx7kJ8LVawsKV15qlDi68Zcvsk2JLCsemB9Rg+fH7REJ63qlImKct2NIvHSqG42Xjyp8/i+ef2Xvb+T37+wyirvDFRIIrbJKdKoUhAocHJuSNPHRaBleDMb09ifGAc937wQcmdWoo9z4rQ0JhEDXDNjHfGA00SKzpJIi6SNRqEwrMyReeb9ojBnDvteLHuH5kUf1NgOoDTRztkJL/5zZsxfOElES1sh3EJc+/JLqnyUJxRN3DC69ivjuCO/3U3zvx8v4QwXnj+NP9zBQ0PbJBWGKtKp3aflCm73Kp8NK+vgd6ix1DHCJwzXv6XDYrWVknb6uxTB8UInmbQoXPfeVTubJRE9jSjLt46shoX9/FRMNIvlFGQCUOmBUVbmzgzKBEP6Wkp6Hj+tKwuoWE9uyIfmx/eLPsOmXfFBc0V66tRsaZSBJY5KwOWXKuco3kJHH35vFK00DdGr9n8nBa+cae8NnOvEsz0jEqbrtcxDWuODZbsazemvxI0W696eIsElE50Dkv8hb0kBzlV+XCc7lgUVMx9shRlwZSXqQSV4pZFVTtuTZSoUtx0UDAwK2lseHKZoEow2TcmIZcNO5sWv8eqhaffgbGzXdIqo+cow24G60nzNICuqsBwxxDm5ig7NJifjyEpJQUBdwBNO5rQ/twxGLPnMdE/LlNnFFKsHuVXFUoLUG9Mx9ndp6VaFk85jyeYi59nbh7DnUOwFmbGlzXnZqBsYy08406c/Nl+McVzV95kLIbTzx5H677z2PmuO2FI1+L0U4fjlRcNYMmxSsVlqseBsc5haWxR+AX9IZjsJhgzDPCMz8rCZrYZKXxo2C7dWIuTvzgA35QHZZvrpHXXdbAVeotB0uHJXDCCiQtDyG8ukz2DPpdPwj9nRqaw8913IbMwS0RJ3b1rZbUJz4sxxyoCiq03roPheYkEQ3LutGaDVNSWfS4dgyjc1gzXhPM1EVWEx1GzqxklayoXRFQMM90jMGXbkG41w1KQJVUzfYYJOsuNWU2jUFwNtQ2Vl61U5eXnIDPr5XBdxa2DElWKmw7xxOjS4OgcXX6HBsguzUFWcbZUYGi4pnnZ7/HDM+FEkk6LlHS9CCearrkXL0Wvg2d4EuVrqjEzOg0XV79IyGd8H2BRQ7EYunWWeAUoUe3gn94pDyzFWZjRpkplimKGy4QXyziJak4sJtNpOXk2EYTc3Xf2l4elFTbeOybenomeUVRurUdhQykGW/pkUrH/yIWXE8NjkJU1F144g8b71kkFhhUrI03wFUYEJ2ZQSDFUkImeI+2Yi0SlCla6oQZj7YOyUJlmcltBJtpfPCvVNLYm8+tLpOoW9gYx3jGE/JoCeLuGYM6zo/T+deht6UffmV5Z0cOKVG5tEQw2sywszizJlpYiv5+Y3mM6fMH6akx0DV/yufGY6MFaKSvpesLPiYIxQfqGWmQ3lMo/c2rxtWg9KhTXm8KSfGzYvPoSXxUjFd7ytvuVn+oWRYkqxU0Hwwrlornk2sjWE/foTfU64DjbC1ffOHTJyTDkW9F5rhdpkSim+8ZRWJaNmYFxMQjTS+N1+xHwBuH3nMWu99yNscFJdJ/olOpL1foazIfC6D3YJrvrciryJCOKrbe86kIJrAyGIuLVYiCoNc8O17gTxkwzvJPu+OTcAhQlBfXFUnXqOdouok0SymPz0n6kEOs92oHVj24RT9TgqS75ObawFoPTYzExqtPQHnT74XY4kaZPlfdRtb0RDN+OOaaw5pHNUpXiNNloaz8cF4ZEQFH4sE3ISIS6BzdgenQGZ146K/4v7upj9YzHRLHGfKeZfgcaHtmGSYcTfrdfVtGIVyvXKrdEnpKzzyF79RiAWrS5AVNdQ3AtLF5eCoUwF1Zz8XIC+te4VJgVLwoyQ5YF6XaLiJ+LoSD1TrrgHp0RwUtRStP8SsubL4atR4XiVsJoNODRdzyEyppyHHjpCAKBEEpKC7Hjzs0SqaC4NVGiSnHTwQs7V7sU1Rej/WCbVB4oqNp+c0IqPCm6VFkMfP75U4ilJGH9o9uw+38/Ib6pkuYyaDNM8aDIgXEZxWe7L4VZUq0DmJlwo3pDjWRCHX3yIHa+Y5esseGIvmvMiab71knLceh0D2b6xmTNyI537ILZbpJ2497/u1uqYBQdDArlazJNvHJTLS7sPomChlKJNqBYYsUtPqG3kJKugYiljDwrJtuGYDDpEQlGRMhx5Q09U3z89MA47KW5khmF5CSMD4xhsH1AdvKBEQm+AAaPd8A36Ya5KAs6k07W4hizzVJJK91ci7aDrZgenpI9eTwXQ+f7MXJhEA/9f4+KWKG3ypCfiY7D7fB6AzKZVrOpDlmlOVL9S2DMypAbIyBYsQq5vBg91SFGflbulpJTXyqTjJaceDguxd3EhQGMnnzZ70TMBVmy5Hjpzju2Erv2nxeBuAgDVNdVo2xjjfjNFIrbDUuGGdt2bcSaDU2yuUGFf976qHQxxU0JvTMNd6ySEf3sshxJ0qYAoaDiODorQR6nV5LKudzYkBGf8Dr166MovWMNLGV5MGVbJWCxbEcTTBUFOPHcSalSRWfn4ByelMoMxRErOIwT4GoXjuz3HbkglSymrrN1FwuE0PnMYZgtemz5/Z3yOjLar4mP8t/xh/fg2I9ewGjboGRdEYlNYLRAaoq0DoV4pJKIMVZgqHYsrNwY9ZiPRCUPKhIMI6eqQCpzFDrcD8f3a7ZbEJjyYnLag7BGg/KNNaja2Yg0XSqyKwtQsaVOYhi4p0+TliqCyl6YhYKaQvFqJVqe3Se7YK8qlFap5CalJos4opfswE/3ovNYezyo9CKYjSVtN6sZFXevE9HHQFVpoyYnIa+5HPbqItRsql0UZf4JF0aOt1+yooWTkpPt8dUzCca7RpYLqoXzNXCiEzODl1bFFIrbifR0vQgslaZ+66MqVYqbDsYijLf1wT/pxo6370A4GsWZJw5Cb0mXbCmdQS/5TVQorGpxuS7bW1ywS8HCJcidx7uRVZQpk2x9XaPwTvvkYs/Jv6mhCQnazC7OFv8Rk6jX/N52WDItOP/0EZgXREhyIBk1O5sweOCc+IUcx9thrcjHg3/yZpmeo+Ci2d3v9KJ0fQ26D7ZK1hUN0hFO3WlTJRyTokJWtyRBEq87jnfgznffhbO/OiIVGv4MZQfX1QRdPnl9ikfmQMU0Grj5vpihZdLDWlMAc3YGkpjOHQojs8CGok0N0vLsO94h7bpIUhJ2/a+74RqelHZkRlku6rc3YrBtEF2H25BbmIW2F8/KMeVUF6JuK5ctD8i5v7C/BXmV+RIrcTnM+Zmof3grgk6fiEAK0lRjOoy2uC8twXTPyGWfY6prGJk1RdDR8B4IYfhs72UfO3yuF5nluVLJUygUipsZJaoUNxW+SRe6f3tc8prIxJlO2KqLJHMJGcZFf004HL+fVRWKl9m5OeTXFaOorhgZORnQ6bVwjjsxcGFo4UKvQXKSBtZcK2w0lLv8YibnAmMKHaam12yoESFDvxI9SjpjOpK53kW8UzHx/HS+cEqeizlXWnM6slZVwusOYqStH5veeadUpiwFdrTvOSPVKgkTtZvESF6yrgqhUBi7/vAeiQfgrjzmLrHSQ8+WPsMgYaBMdOcx192zBi/+9/MS2Mn3zVT4qN+Hlp/vQUFFHnRGAww5VngnnBhv60d2eS5KtzZirGMIx36yD/PRaDz6YWACI60DqLt7DTyTLhFwjEPga0z1jSOvrliyp9haXVyqfAVRRdIMerldCQaRXg4OETC9Pv44rvLxYTYQlsoXJzeXijM5roXAVMIBBb/bJ5Us7ltc2q5UKBRvTDxuLxwj41LdZ7hzXkEOdLrXf/euElWKmwZWdKY6BhcFVYLglBv2oiyMdY4siip6kNh+Y+WpcFW5ZDMhGMLg/nMYT9didiHDafvbdyDoDWCeO+Ki8wiHZ6UtePjZ4xINwAszzd451UUSW9Dv9sOcZZGIhoQRnUKDAonHl8p1Kfr4RZyLfK25NgRj01j10CaM9Y+jZ2G5cf2OJllKLHlY6TrkNZTAlG2Bf8AB7/kOpG9sxFw0iqaHNsaDNTPNcozj53pkUTF3EJZsrpdg0ZPPHkPjzmapxo1f8CKZE49OH4ITLuim3bA1V8OUaxOByWMcPNEtx85KGt9zYmFy+/OnsPbRbXD2jcmUHtuPDDvl3rzMmkIJB41/DvH3zefi8XM6ks+ltxqlLXu1FSNTnk0M7iuhNRmQrE3DTJ9DKloUr/4plxwrvVZppvTF3Wds0SY+d7YpW/eew+TghBwTW5wNu5qQW56npv4Uijcofd0D+OF//UJEFeHfHc1r6/Ho2x9EZvbru/tSiSrF6wbN4Aza9E955J+5LNeQaZYKkG/CJUIhOhdDRnk+vMMTMk3GVhMzo6yVBbJqJWGO5qSbNSsDGm0aQvNzsFjSMdQ5IIIoJS1FPFFJei2iTg+c7YOYHJgQscAsKXuWBRUbazBBI/rsvDxXSWMJwp6AHAvFGvUWhdp8jEZzLjROk6lE7WxUKieEgZvp9GUFIrID0GBOR1lDqeQ79bcOSMZU+fpqGLLMSNPrxB+kjUVlci6jPigThGzD0Rw/1dIt54WChcdPMcRATV1mBu7/k0dkAvHF//e8VLTKV1fAYjUg6piQ42IOV05DCZKSU+Q4qBT1Jr0IIpKo+nDyj+b44SmXVPdAn1VSknyfnqnEYxmISsE32jKArgMt0vokPKfFayvFPM5VPK+ErSwf010jslT6YvJWVYgRv29vfJy8qLkc031jIuSYks7j4YoZGv7zG0pFbE2PTOHAT16S403A5dkHf7oXO//gLmTfwB1/CoXixjA5Po3/850fwuV0L36P15czJ1qQlpqGP/ij33vVC91fDUpUKV4X6N+hkbtr3/m4v0iSujXIqy2CJiUJI+f6ZcKMo/ecTJMKTiiMnhdPS+XCWlUEe3E27CXZmBqckH9JqnY0wZhlFrHUt+cUkjRJCDq98twGqxEla6rQtfs4Ug1xvw+rW3OMSDhwFvUPb4c9N0NG8lhRGe0YwnjXKOruXYehMz0SO8ALvKN9CEUbauAbnRJzOo+dFRIuKGbI5IknD0rgJE3eTDtf+8AGtL94BiVrqyS9ncLFM+qEzmpEmskgsQg6mxm+kSlkVeQhad95GM16jDOiYaGdSaHD42eEQcTjR8DlRdeRVqng8T6myhfVlaC2uQTe3mGpXPlCc7LCpnh1hbx/nT4NqXl2BH002zNENJ7fxCiFuXAUtsIsuBaqSNbCLAkDJUxZt2RnwDU8jY4Xz8p7TcCKWv/xThGSBY0rj3yzIhaYcksMAwVqZnWRtCE5BchIBQplrpDJKMnByKnOxXU/oWk3Gh/YgO5DbeIrC3kDMOfZUHPnKom24HH0netdJqhe/t2aQ/fxTlnBw89FoVC8cRjsH14mqJZy6vg53HnfNhSVFLxux6P+BlK8LrgcM+jYc2bZRZoCpfW3p1C9q0lyi1hlYUYUL5ydB1tRva0B+ZvqJQDz9BMH4uP9uTY0PrAeKcnJ8Ds9cA+MSTXLPTIlhm/WZGKIIc1iFJ8RL9oaxGDMMMI9Og0dx/jn5zF87AI0qclwnO+DJdcGY2EW0q0GZFflS5VntHVALuy24ixkFGaKATx6pE2qKBQVmbUlGLowiOHz/WLUZhvKOTqNw/9zAJse2YK2357EPf/fozj+gxckQ8lUlIX2QxdQf0cTyu5YD010FskmA/IbS6SNKGdl4dRQbPJ88MuZsWkYKwvkPqkmcRpxPobxnlFUrCpHJBRGiicIW2kRWl88K2KJXqVogBUrwCDLpzVI1qZKZYzVJoocijZNvl1M4rn1xRjqGMaGt2xGfnWBTASOtPQv+6yWwowtCsKLlwIz9HOipU8WMS9+7v1jEmdRceda8Y7x82XQKp+bC5AThJxepIYjqOVanqQkiW/IriuWfYOEVTe9Ng3V66rkeSaGJuFcslx5amgSIX8YBov6K02heCMxMT512fu4nNrvu7y387VA/Q2keM3hBdTROiAXVGtR1kJy+bxUcWZDs+g/0YnSdVUIugPQmdNl6XCgawTV2xslZsA1MIbKzXXIri0SQ/PwoRZ4J1woWl8jJnO2l9IzDJg36qXCNBsKi/HaPTQhgoLVHd+UG6bsDMlsYmuNgi67rhS2yiLM9I5i6Gg7qh/YyFgoycOiWZztPj5usncM453DIkQslVbMz8Vw4pdHFqtWDCTNrciFZ8Il79fvCcBWlAXvuBOpOi3MORlSfVv3wDppLXaf7oZzwiWrczg1qE9LhuMsfVAxaatRULF+k8ypwUgU0ei8fI/Gb74e19BQXHEHotVihCE/CwNH21BQV4zhtgHk1Bahd9otgpKtU0Ih1XD/emm5UWBRtDDgtHRTjYSLMmeL1SzCn+FE4+UI+0KSBH+xqApMu5cJqgTRYFgqVeV3rVmsJPF3QJdhhG/Cufg4GtVdfQ75Z7b+0tZWyT9P9Y+hbfcpDLcOSPWLoq9kbTWMdcUibAlbpvShKRSKNxa2zHhQ8UokJydDn37lgZrrjRJVitcc9rdZxaCfiRWcoNsnVRdO2NGfw8ymrJIs8RRx+qugoVhym4aPtYnIMOVmynLl6Z5RDJ/skEm6ip3N6N93FkmpKWJIN+XYMHa+V9K6WclgtYv76Wb98fUtrNBQtLC9Ru9WVXM5kpI18IxMidDLa2Ropwez/rAINAZ/itF7PobVb90mC55HzvWJGNHbTFLhYSBlLBKVcFH+j0uXWdyh54otNO+4CzqTHgW1Reg/2gbnQgo521q1m+rRcqAVhY1l0JVky/GHPH55PQqOKCMj5ueRVVkoyeg0det4H1XfwntJNRtgK7LDO+XFTK8DZXetQ/+zx5FbmY+mt2xG977zEjZK4cm2IDOtYmlJ2Pb+B0UQMc6An8HFcILRaDdJuOhKaE16iXwgkkElnncNXINxk+hKMJsq7A4gfUnauq2yANNdwytWxLLrSkSIUqie//UxEXoMHHWHItLu6z16AdW7mmX6jz67sjWVErWhUCjeWJSUFcJoMsDn9V9yX31TNfIKsl/X41GiSvGaw/9asOTbsP8/npWpM32GUdaxzDL76cIgrPmr0f7sUfjHZqTlVbCmCqXbmyR5nBdQxgGkpyTBcaoD/mkPchpKJfAzp6FMvEq84HL6LVmvlbZeus2M6e4RVN+7DrFoVO5n5Yqj+qxYVexaJcngXUxkj3HBMrOX7BJHwD5bYWOpGOeL1lahoK4IE2faUcxWmz8kIoKxC1qDXjxGLH0xNHSgfVAEIZ/PYEnHrNOHrNUVyK8tRNtTB5GU9vLEnHfMid6XTqN2a5OYrDe8dTtqH9goe/YoGFmdongzZmfAUJKHs9/7rbQYKT6ZWUX/E1+nVq/FkSPtqKktlvcm1T+NRlp32997P0xWI4Iuv0wV+sam4QuEUbihVibpOPXnn3CKEKR3S2sxLqaWs/2Y31CG8Y6RFQUPoyFiTEvvH8NMz4gIKgaKyqoYlgJX+BmeN4rrpbCdW7S1QT4z+q3iL65BZlWBCC4yMzixWG1j9TDMauSC8X3wVDfKdzTA5zJKlIZCoXjjkZuXjcc/+E7893/+DG5XfDiHVFSV4ZHffxBpaa9v5IoSVYrXBS7o5ToX5g0xl4gXa1Zx2Mqh+bm4sVjM55yoM+TaJZSTHivmPGVX5ksm0nyUIZpzsJXmYy4UklaTKd8OvdkoYZIUU82/fyei4QhCvhDmk5JRsKEOY+d65GtWqPh4XvQnO0fie/cWrv+MDRg+3o76R7bFPVBZFqmijJ7qlMpMdnEWpvusMqHGyTi9UQuf0wdLboaEfc6MTMtz6SzpErPgiUYRnHTCOe1C+Y4myd+iYGKKOUULhVNgYgYVm+qQW5YD36QTRduaJazTN+2WY2D7cTY6jzSdFpqUZDinPfBO0xeVjIq1VRjuHETn6S6Jidj59jukfdp0/zoRiUxk53Sl7N2bdCFJm4ZodA79p3rhGT8BU5YZeVUFGDl2QT6L/DVVyKwphinHKq3GjAK75GR17j+/uPSZorGERvYcK7pfOCnreBK4hyehyzDAUpSN6a4hqSAmIhGIxCRcNDHI58uqLoYx2yoDBmxX8lwytZ3ClbDNm4CTkawAMgA2uCCsCmqKkJFnl+8pFIo3JnWNVfj4Z/9/GB12wO8Lwp5pRX5hLkxm4+t+LEpUKV5zuNOKFSZ6ZoIe/6KQYTABPVC2osx4GGVKElItRpz6xX6pbLCVF5hyYeh0N9a/6y6k203wjM+Iobz/QA8K1lRjor0fM90jSNFpkVSdFPfpTLnF6F7QWIb85nKY60pg12hk6o0RDu1PH5YWHV+DlRoao1npochiBcztmMbIiQ5pg7EaxQXKnuEJ1D6wGaM5VvFXUeSVb6mX3YCtB1rjC5xNemx6ZCvmAiFkl2TDcaYb88zL0mmRXVMklafxtgERfSQpOofqNeXoe/4E8rc2YahzWMz2fae7Mdk/LkWf9Y9sxb1//CBGukfRcbJTgk1ZlfE43Wg/1YVUnQ49p7pQt7oS7b86KkJq/WO7RNRQhLB613uiO+6RisX9UpzOY37UXGhWjolm8sFDLfJ43/gM8ldXSlRDfmOpBJlS6FHwsI3ItT+Os13LBBWnEgMzHsn2YsVLRPP8vHi1eF5I3urKFcNCKTAphnlbCQrxpch7MuolqZ6xELLmRwkqheINT1a2XW43GiWqFK859DOx8sJpOhqV4wHnmngoZTje6qJBXZdRinNPH4UmiVNu8yJ6OClGH1H34Quo2d4g3iyuR2EGUveeExBHt3iQZsWDFfEFULK9Ccl6HTRzUfSe6kb3mV7YizJh1GuRHc6R44i32BZSu+fji48p7EIun+ysS7TyKCZYLeGEIKMYcmqLYTSWy3oZa2kOxocm0bi9XgRHBitU/Q6EZyOI+GJyHKEpD8ZaejHR1g9bRYF4tyL+IIJOP4wUBFYTineuRusLZ2SRMoVHQW0hqjfXof3wBXQfaUNusR15lbmY8XgwF53H+WNtUnXiY/lemOwOiZhohMfhRP/RDljz7RJSyupYus0o3ioKRJk0nGeYabz1uubhLSKqyHhrH7Lr4wuhTXl2OSdGm1luXLvDoYGw1w/P8MvTNjTr06DO547MzUtLsXBjLQYOtsikpK08T6pgGSW5r+p3J7M0F/3HOuKt1ovIry+W86dQKBQ3C0pUKV5TOLHGnCWmYrNqwUgDabtRVGk0cuHNqSlCEgM701LlxqlAPpZeH7aFZj1++TOyvkq8R4Fpj/iPuL6FyDThgjdqqmMIRZsbMHSkBdbSPAy2DcjrTfSNo+RNGxc8RDrMRehLYpGKHiCIqPOMO1G4oQ7Dp7pE6Mkd8YwGMaZz1x7jATwDo/CMu5Bmy0D7M8cWL/gb/+BOaWEG2S5LToZ3aFLM26xW8cYKEfca5jRXIOCfQTTJD63dj7YXzmBmdFpek+nvIooKM1G6ulx28Xk9IUljv7D/PPIr8rFuR5P41GbGnbhwsgszjmlEPAEgEkXh6jJotWnofv4EZr0BzIYjMBdkoe7OVRKU2b3/vJjF+b45STm3xOfEz0KiF8ZmRFQRtmCd/Q6Mt/SJp4x+LK7Gsehz4B4clwXSi4InFpMAVfq/yu9YLWLYXlEg7b1XC/cg1t+/Hn3H2qUlm5yaKq/DtnHxmkqVoq5QKG4qlKhSXHfEN+ULYm52Vqo+qQadhFCu+/0dsusuPB0SoZKsTUHtnaulncdJNPquOIFH0jMt8XF7mXhj5QpSXWICd/7a6rgAYHtO9sfFBRUv4vTixKfQNDDlZ8LocMlqEwqovpZ+rLtvHZIZayA7/OK+nngsQygu+qxGhH0BaDTMSopX02RNTSSKNKMuHsCZmoK8dbUY6XWIB4gtTe4J1Bt0aPnFPmlRle1che7nT0KTRJ+VUcQYj495Wr6XzqB4WzN8M160/PaktPyYdM6qT1KqHj6XH+NdI8ipKRQRIwbyQAgPvOc+uHpH4TjahsjClOL2e9dgxDEDTWQWw+f7ULKqHO3PHEaaNlXacHzjnHBki7R4axM2/8FdmG7vl4qVtqkY1uIsTLVopTXLGAO+P4rU/v3n5GtW1RiHkPBHsWLlPtkBW3kBDFkZ0vJbCj1V3tFphD1+eT98DJdCs433aoI5ef6ZFRZwetF7+AKCnoB4s/IbSmR1kEKhUNxMqGAXxXWFU3OjZ7rR9tQBtP5iHya5yy8YQWZJDroPtKJ65yo0v3kzmt+8CU0PboSTWVIxDabaB5BCT1W6FobsDGkZ0ouktXDsn9MbMRawxBCd2APHiyoN3EkpKUheGPFn9ACFVl5zBZzD07I8matxePEfbR+EZ8qDFFM66t+8BbaSbDF0B11eeZ3ibU2IJHKduDsvXnwR4UWxZsy1Q2fPQGpeDua1eok7yCjNRZrZgLIt9Rg+0S7HSIUX31/I3YIxhN0+mXgMuPzxChgrLcka8TPNDExIe1GqVGw9TrqQbtRBZ9TBNTKF5BQN7Lk2hJw+zI5OSXRCwjhOr9PAgRasWlsN9+CkLJQePNwKvSldRCcT6glFEp87GgxhumMQfhroe4Yxc6EfjgNnZMcg319WbTHGW/vl3E91DmE2GELvi6elCpaY3ONzUWxNXOgX4ctzk4A5ZHxPNMezCsY1PzNDUzj6wxfR8sxxCR+9VliBHD7bJ4KK8POiaB3vGEbrcyekvalQKBQ3C6pSpbhu+Gc8GDrWhj7mRyUnSXaTa2BcvDgxvV7yqdr3nBbRwcoHK0C8QOotRhTWF0prZ9UjW3HuV4elepNYYcLJsbr71ksIKL/nHJlEZk2RVFBkL51mwfDMqTFdGjKKc+Acc8JxpAOFaythy8+UXKXaTbUSnHnqFwdgLciUqo6GWVRzc3BPuDB4rg+V2xulZcVMLIoiaW3NQYzU2c0VOP3MMXiHpyW1XWc1IbeuGEkp+bLnz+n0QW+3wDvphCY53t6UBHTeFhYwU6Tx9Xgfs7h43HxP9DhJLEJ0XrK1OEHIqTaKNb5HTkG6+x3IyrUhMhuVHC6eO/5X0cD+c8ipKkaKNgUjR9pgtBvjzx+dx3xsXtpxPBSvY1qqPMVbm+Ebn0ZwfAre4Uk4OwdQfudazMdiKNxUD01aKow5Npm2pEBlfhbPa9JC5AJN7PEWIhPS9SKazcXZsJXlya4/Ch0KWa6o4Xnl+5voHpXpyzVv3Qq92SDPw/fAUFJOGy6dFFz+O+XF4AqBooTtWu+EU6ZIFQqF4mZAiSrFdYOeoYFDLfELOqfeGDCZwWmwANxD03IxTUkNS4q6RCoYdbCX5kpkwkTfhEwIsvLR/Mg2qWD1H7kgRmTmIplsBgSGx0WQONnK2tYk7S2+jsQiaSAtsdw1JfC5A+g+2IaQP4Sul85i7cNbJOTyxM8OICPfhsqtDejadw6TXSMy2cd9gBQ1a9++E7P+EHRZGahgNEDvqDx/Vk0RsmqKceJ/9ovYY6o3g0MDky5MaVNRe/daEWujsRhmZ6Ow5NrlvdOfxDwnVtNIPNcK8XMSnsV0rwPZFfnS6pM0dR0T3Odkfx6nIhkyuu8He7DuoY3Qz0elFRr1M44CmPMFEV0opVGMabknkHlcJp0UyBJtUXnBhRNEAUe/lN5mxsT5XhRurJNqIB+XbNCjd38L3KNTUgnjGhoKzMT6IKaiJ3KsFoVVdgYaanfFW4St/XJjuGrA7Ye1NBeWohwMnOlZ/Bl+vm6HU1qrU30OaVdyIpO7/fKbSuXPxPLnBPRxJSpzK0FvW1ZFvvq3WKFQ3BQoUaW4bnAtjIgcpmyzVZNhgm9iRq7tnP7zu/zxC7OkcGtkOo0X0jNPHJRJOIovenEm2gdRfdcarHv7DniGJjDd2gtnchKyG8vhcUzBXlmIYCAMe30ZvCOTYlxPt5lQcXeVCAyKntL1VTJqPz9HL5QBJ3++H1ptirTF6NVi+3HswqCIl4KmMlgyzUhJisE7OQ0z23ysQjWXI4XVo7k5zEfmUHPnanS8dFZalHPheCWNC6FnvX4kG7TQ6riweVamCWf6HBJgyik4PpZiUdbezM2hcF0NBs8PwD00jroHN0nFhS3NcCiyGHRZtKYCk4MTcl/LS2ex5cF18hxseaaZ0sVbFPebJYkXjJU4F432a6sx2dYvZn+ZjFxo2dHfZC7IlNBTtkLZnhw4cB6V92+QENaWZ49L61YCRLlPq2sEAXcAFRtrMLj/3CXBnWwXUvCyrckbfWPc30d/mW+KeVpeDJx9WVAloCeL55DPn4CtwvGuYax6yxbYS3OWPX5pe3EleE4VCoXiZkGJKsV1gyIj0bKjaGLriS0o79g0Su9cBy8vtuMzkp5N43bBljr0He+Qyg1/jmtJWDVibELnnjNY8+gWTLT2iSjg8mNeyBn8qbVbcPJne9nzEx8PTdCB4CzOP3cCNTsaYco0YVaXgtDEDLSWdKSkaGQvXIT+JqcPziSNZFFZcjKQkWdDTmUeZl0+zIejYlpPS9VI5tSsy4OBo60IzbilsmYuysGmt2/Hmd+cxOSFQeQ1lSAWCqPvZAcyK/KQ21guHiQa3bluhuKSU3AUipzCY+q4JjUVg6d7pBqVkq5Dz4HzWP3oVhF7jDiQQMzKPMl4OvYfz8l5jAQjmEumid6MkNMjVSMGcDImgfKVFSGGm+ZU5EObnioRC3xNnntZtTM3h7w1leJHy64vg+Nku4gkNtxY7XN0O+It1GTuZHz586RYDYfnxDslQngBVrzYJuTnloCfHW8Yc6Llt6elPWrO4s5DnQhF95gzns4eWwiCZbWOE5Vs30o0wxy6D7fBnGtdVhEz2EySxu8efXl5cgK2mC0Mc1UoFIqbBCWqFNcFmpKNvMAtxBvQ70N/UAK/YwL1963DyZ/uhS7bAFuBXbKfGA0wPzuLoD8kbbJUgx66jBSpyMzFNCjd0QzHuV65uJqyrTIlyL1v9F9RLMSic7K4mEKD9wU8AYydakeQ2UkLe+msFQUo31CNnuMd0r5j7AF/jpUYjYdBlYCtLBeOY61SycmsK0UsEkHPs4ekjZZoSbn6HdLyW/3wTrw0MImChlK0P31QWmjMduIEXdW96zHZOSTRAmwRUrzkrqqU9PfAhBP6bJu023i8ttIc2AoyMRcIIjLthCXLJL6jsdZ+6PKypLpE8cQ9fe2H2rBmVyOGDrcuVm9S09OQqteh7I41mOkbxURLDzIqCpGztga5zZWY7h6W6AT6o5glZcjPhLNvVKpF8X/7U8RHxQoiz6ecv+mX1zzw/E50D6Px3nXS2qXwo9izV+TLMMHFrTpisBmRW18Mo0knn3loalqOv3xtOWbngWAkgtn0NMzwPOfZYTOlw9k7JsLL45gRM78l92VRRYFVvbMZZ391RFqBS4UdK4cmCj6FQqG4SVCiSvE7QwE02eOAwaxD3qpKOM52ixhh5pStqgDWklwZrac/586PPoJZrw/uvhEks5IVCsnE3lxKskzA8eaX9tSsLNNlq6poa6PkNHkdM2KCnu4dE58PW1UUcPT3iGsoJRmOtn7Ys0xiguaFmlUvz+gMMo0GZJfmIjklFf4pl7SrxCivTRVxQt+RuSQPxoJsWKuKMLL/9KIolAyshak9+oe8wxMo21InQaHMytJbDFIZYlvRMzoFW3k+bBX5YtSmOZzRCtJ2m/EgqXNIRF5uea5EM9jL83HhmSOSw5Vq1CM9x4bM/CycffGsCC55PYdXzlPQG0Tuqgo5Jr5/JsFzf97I8QvS8rQ3luPYU4cRCoRgMBtQvr5GFlXr0rVyP1uSYZdPPE0xhqtyYi9dL4MAkUBY8ru47IUtUbZxKZoYFcHVPjn1pfHzsIKQIkyJ545Bfub5lbno/NWBxVYm5/P849PI29SAAy+dQdeJzsWfM2YYce877sB0+/CCD+xS2CJmK5gVLgovZoqxTWhemBJVKBSKmwUlqhSvChq7/eMuTHUPSyQBk6IM5gLYqwulijHZPoiC9TWSjzR2rlcmyLJrS5BZmoWJMx0Sg4DkFKSkpUg2lTbDJIGZbi5VFrGTgnRLOgaOtkl0AKtcFE8poYiIM7bP4jlSSXGfkUEn1R/6qHgsbge9XHExxMpM6FQQTW/fBffkcfECUdCwUlVQkSf+osHWPvhGJjEXDMNcnAOvY0p8SRoxg8cN4TKpN8+q2yTMJYUITblhys6Q6cYEFAbcfccSGYUk9/S5BhyyckeXYRIhyIoPb+yGcRF0xd3rEY1EZErv8BOH4D3dg4gsVp6N548mJ6FyfTWmWnpljUz1g5uRnJaGkdZ+lDI+weWDraYYJ3efju8WhEYqdi17TovXiq22hvVV8I075X1zlUyiomjMsUrmE/cvSlyCQY8UXVq8javRoHxbI9L52Sx4s5bC12KV0DUc99LpF6IgZtp6YM62iLDlUAJbrwx37dp7CnVr65eJKi6HPrL7BNZvacBcMAK9ZeUdfka7WW5YVa7+jVUoFDct6j/zFNcMhcPkhQF0PndURJNvzInRU1248KtDYpqe6ByWth0Tt9lOigRDUsmwFNoxcvh8vOKRnARP7zAqtzXIP7MFKG2pBRN76YZamRTTGuP+oKn+ccyGw4h4aSwvFQ8OKzWshlA4ac0Gqcbk1hTC0dq/MPHGbTfz8Wm4yCyCLj/KNtUhxUD/TzqaHtoAe0mOpIUzn4mGbYoOERfpuoVj4Y8zFmEhYF0DpBrTYS/OlqkzRgJEfEHxiInwkhcF9FajtANZEUrRauUxjCXgU7IqxTwq7+gUApNuTPSM4sTPD8A75UbZmgqJmIgLubjPqWpjDXKLs8Q4X3nPBhFoNMuXba5HZmUh0kx6zCcnyc9fDI+bew5TM+Lrfih+GMzKc8Udfzw/3PHH5PLFvxSS6V9LRdGqCtiKslb8HeCEX+tzx3H0//4W5395CK3PHsOpJw4iOjsnbU6mz9NjxfYcRdns7Jx4vFLmojDalq+WcfSNISldh4qtDdIqVCgUilsVValSXBMURFxyzNH+nLoiaJJTJLySlSj6Yfr2n0PJtiapsriGJsWgTNO3nhlSyWw7xcTXxAk2CqTgsEOM2pP9E5gcmBBBwZ1urET1HzwfVzEcnR+bAQJ+8f1kludLa5ABkGxdSWK724/KrfUStJkwPycKKxQOWhOTzwNSPeKOvrA/iPPPHMPGd+yCb2xaTOVsgemyM+JRB6urpc2Xok9D2BOEe2BUxCRFY2ZtmYhKS0GWCJOhI/FgSgorVq0oXgo31mPkVAcK1lQhzRw34HMvHgUL9RKPMZ5fFUMsGEK6xYBT/3MAuz70ZmQVZUlQZsgXQDqFidWI0ZMdktPF98EKWmZVofi32Ma0FGYjRJGZQKORzCqKTYqvkDsgbdDKe9dLphS/zzUvPKc5Rr0sYW5+y2YJG53sdYgfLru6QDxvK4kcHvfQmW6Z4KNYTMDzw9womvEZTcEl1/znxH3ys6w60QeVpIm3GedjEndhysm4ZPJPoVAobjWUqFJcNRQnnsExDB88K20owpaYtbJYxEX/oVa4hqeQxeTw+bjBm+09VkU4+i7rXnjxl0XFMaRzzQl3+p1qQ/6GBjFUU4gNHu9AqkELvc0ir0nxxedhW4v+IQZXNty3Tio1NMgHudw4JwMpKckYO9stRm5exJd6gPJWV2HgfD8Km8tkpD8BpwAplGQpM9t4SUlyTNZCOzz9o/D0TUm7rHj7KvjHZ2AqzMEkV8Wc7oJ/3IncpnJpd46f6xOhwFBMGuo9jmkRPhRajGiQEFSGfeqT5BxQTHAnHqtINLaXbG2U88OYB3OWBdlFWXCc60ZkKoTR7mG4hsZFUGlZlZqbl5Zf/4HzqLpvg6THO9qH4v6ihYgFCkieg5RgBFqDDoYMIybP9ywozfgUHlu1iYXETCrXm4uRV1f8ir8HTGd3tA5K1ERcJr1M2B+J77hmVWxuDkkLoipNmyavnaTTSruWmWWcDGQ7lRlbDDu9nF9LoVAobhVU+09x1dD7NHbiAqKhcLw1xtiAuXnMdA4gNUWDzPI8Cdfk8mRmF1FwUUBJ5MG0J75WhtUqxGSyjS1BVpooZmY6+pGqTcHYhQExj8eX9MbEfK7PykBhU5m0y6SVNzuP8bNdVHkw5lkx6ZjBdP8Yzj11UNqO5vzM+IJm+odM6SjduQp+fxgzgxMLi5LjC5St+TYRIBQ59EZx0syca5MIhs6n9km1jW1FerWcHQOwVRXDNeZE777z4gnj8fTsOSliL6MsB6YcWzw2IS1FfF0M2mTEAg3gWfUl0v5LbGi2leeJ6XzoWLtUdXgefdMeaXPSvO4dnYS9Mh+F6+swGwrLUmSKRd+kS6pDrAzSFM9WIqtveXUlqNnVLO/ZO+mK78Wj32x2DrZ8uxjbrRX5slyarc+ijXUoWFcjbb5rZY6p77KG51Lo87LXlsU/+3gzVGAmWf7qKvQyvmGh2sX7KQQbN9fD9jssXVYoFIqbBVWpUlw13mGunOHFdKGqQ+mQlCQX+5nOQVgqi0UAsODAag8v5IZMs8QLsOI0fmEQWU2VmLnQJ1UULjHmrjgmfGc1VkCj06NwbRWcA+MITjHXKP66xRtqYC3MxOBCiFLBumpoOPkXDECTmoKiyjwRLlxb03u4DZayfJmw4zWd4mzGMYOh8/0o2VCFkDeA6l1NIvK4eNk9Ni0ZTpPne6E365FRnI3BF49LO5Cihetp4pOMKejbcwL2pirxJLEKQ7/QrC8gwolBn6k0wGuAnt8ckyBTCjZJL2/rR/GWBpRua5JWJScbJ3tG0LH7xGKAZ0KA0MsVm5+TJcgYmUJWQ6nsHGRlkJOAbM0RCjG2FGl4p4jkeW6+e42svuk81o5IICKrbUpXlyO/PA+DJ7ux9ve2ibDhcdHYfy3w/fDz5GfNSApOPPqj0cVJwqVVLEYn5G9ZheCkU36GxveMiiIkmdIxuvuknLug0ydLn1ftbEZNY2m86qUm+RQKxS2OElWKqyY45YJ/yi1+HHp1uMtOWnoLrTaSyTiCkx3wDE+iaH1tPLNp3ie73dg+4yRa2f1bMHGmEzGNRqb+ssoKJDncc74Plmwb8u9fJ6nqxFaUiajbi9FDZ6Syw+s3c53GT16AMS9Tptzck27krqtF7Zs2S1suGg4j5A9jomtU/Dqsmm3+X3fBmmVCcHJaJvzSN1awJ4WO/a3we0Io3rEK/rFpMVizGsZ2YyLckqGj9ErNRyJScbHk2UQ8sGpktJtEQFI4eAcdErBJAdX70mlp9zFKITVdL6KSnqhoIAAWkZwj04vnlZWpyf4x+eeCxlJoDXqYi7OgTddDp0+FPj0Vhqp8OVcT7UNSASM894mlyfJ1eBZpGmDLw1vk3BL/hAtjrQOLK124Fuha4GTkdE98gpOfNwWgvbIAhavK0bXvvCyTDru98RT9WEx+L5gsT8+cva5MKpIixNj+A2TKr4h7BbmTkM/v9GLghVOYXVstrdRXSlBXKBSKmxklqhRX/8ui18lFnDdWOljxYBuK/iit2QhzUTaCMz5JG+djaNSuemATfGPxKgurPqxcdD1/UrxGWrMZMa0OA4fb5OItS39Pd8Dq8sKebUFgygl3a5eIB/qJctbWITDJRcnn5fUp5NgKy8i1SuBn7uZmOANR6KGBpTgbFdsbwWbjfDDEnEuM7juO5LRkeS7HoAOalBTkVhSh7cVzGD3bg/xVFcixm2FmuywQlvc86417k5ghJYuPwxEpqHBnoGfMKanurGJRRNA3xSpW2OtH49vvjFfzYjGJn8hgVpfdhL4XTyMlJUnEJdezmPPsMBdmo23PaZmE5O4+TuKlaaswtP80vN0Byb+KTzlqkLuuTo6LwopJ54xe4H0p2lTxLPmnvXJbiXhL7tqY6hrG8LG4EZ/wHEx1DMFWWYjyzbUSxUBRzSXQBpsZNXc0i3lem2mV1uLS9iIzxxheynbqxTDbzFKYJa1MhUKhuFW5oZ6qffv24S1veQvy8/PFpPrkk08uu58XzS9+8YvIy8uDXq/HPffcg66u5RvrZ2Zm8O53vxtmsxkZGRl4//vfD5/Pt+wx586dw44dO6DT6VBUVISvfe1rlxzLz372M9TW1spjmpqa8Mwzz1zzsdzupJrjY/mLi24jsyImuHePwZPzMQ2C7oVzvxAdMHy8XSocjEXgxBxTyQn/ZFJ6SlqaTO6xGiTTcAv5SBGfX1LROSnI15mbn5dUcHe/Q6pCDAxNVMrYyjPbzNBqYsgtzxOxxIm9mYFxDO09gdS0JEyf74Q+wxBfzULh4/Ej7PJg3ueBrShb2nhcBh1LTpH2nBzPghE7sV+PwirsDUmAJltgFAwUM8b8LGmPcZlw0fbV8IxM4+yPnkfH04fQu+ck/GMz8VV8Hicq71qF0i11qL5/PdY/fj9Kdq6Sxck73ns/civzYGfC+mwUMxf6gWg8nJQp5iKaYjGMnbyA7NpiMcQXbqiFf9q9KJboXaNYWwn++3WtK10ogsbOXbq/j8x0D4snrXRjDcq3NqDp4W2o2NGEqcFJnHn2BHoOXRAxuez5PIEVBZX8uvBzdK4sBhUKheJW4YaKKr/fj1WrVuHb3/72ivdT/PzTP/0T/vVf/xVHjx6FwWDA/fffj1Do5XUVFFStra3YvXs3nn76aRFqf/zHf7x4v8fjwX333YeSkhKcPHkSf//3f48vf/nL+Pd///fFxxw6dAjvete7RJCdPn0ajz76qNxaWlqu6Vhud3hRzN/YKDvrCCskYV8I6fnZcI8xViEgC42Z0URozM6qLkBGYSb8jmkEJmYQnHLLihhWMzgdF52dFe9PfMw/VQQM17f4J2bEKM62WXIK19bMy4g+p/VSjQYJBGV1S2dKFzO2b8otVSzfyAR6955Fx57T0Jn0SLdbEfH4JICSe/NofA8xBkA89DF4B0aRXZYtU2p8reHz/bA3lMt6GU4dCvMxqVwVbF2F8da+hViIMNIz4vEG9FMladNQtGM1Rs90SmK7gWGfFoMIL3rEJjuGkZymRXhyCjG/G1pNGKnJ8zDZjfD0jqB/3xmMne5E9+7jmOkahmdkQl6aEQyE4pVVHAowGvrz19ZgqnMI9oqC+PQizfdGPap2NIoZ/WKK11XClHVtK11E0F7GkE5YmRttHcBoSz/6j3eg71hHvK0ZA8Y6huCbukgkLR8UvJQl+wUVCoXiVkQTS5hhbjD8L+knnnhCxAzhYbGC9clPfhJ//ud/Lt9zu93IycnB97//fbzzne/EhQsXUF9fj+PHj2P9+vXymOeeew4PPfQQhoeH5ee/853v4C/+4i8wNjaGtLS4r+Ozn/2sVMXa29vl68cee0wEHkVZgs2bN2P16tUioq7mWK4GCjyLxSI/y8rarYZzYAyDh1qQUZQtIoUTYFEGgXaNSn5UBEnIrcpD1BtA9+4TKNpQg8DIuEwL5q6vF5O4s39M/FWFmxqkMtH70ilwBp/tPJ3VCFNWBnQGLaZausWnw6oUwzrDwTDyt66B49h5pKYki1Bi9hLjDJiPxcXAfI3WvS3y/bq7WTGaQv29axGdmYK7ZwgRfwBpRgP8Ll98Om6BjIZatD5/BhFPAFm1JShuKJQW3OS5zrhPyWKAqTBXhBtFEj1GNGjTEE9P0cDpbgTdAZRvqMLEuR4JMp2lOX9BRfD9pmdbUXn3GoRGRxdfN81uw+DxLvFkpVnM4ieiJymvuRxjR8+L+Z6iihUf7t5jBYs1KWtNCUL+WTG9l+1cJROOCXjOXKNTGGkZEJ8a4wrof7IVZy9bVHw10DPW/qtDi0GqF2OvKcLA+cH4ypwVWPXIFmRX5C9+TR8an0+S4lf497/mzVskZkKhUChuNq72+n3TRir09fWJEGKbLQHf0KZNm3D48GH5mn+y5ZcQVISP50WM1aTEY3bu3LkoqAgrTB0dHXA6nYuPWfo6icckXudqjuWNAHOkrOV5mOwYEvOzo6Uf3S+elYuqqTBbVpY4R2aQUZSFpt+/A+Y8m3ht2J6aae+DJjqLjDwbTFlmOI61wFKYiZJtzcgozoEhx4rS7c3I31iP+bko0ixG6OwWxJKTEQ5FUXLHBoSDIRSIpygGU36mvA4n4Li+hEt+zcXZWP/2Hdjx/vuRmpYsfi96rvQ5meLxYvQBn5trbhLobRlwj7tE0OisJpgyzZhsG5BJwhRDOtJz7Ai7Axh48QR8gw44jrchTZeKkh3NmEtJQdehC4gEGb2QLpU6CoZZX3BRUEmwQHI8+yrGf92WZDHNz2skpoJetbgBPB+ZJZmYY/t6LoqI24O5cFhiBwyZFmkDUtQZcuzIW1OFsl3LBdViblhhluR4bXhsF1a/dRtyqguvWVDJubEYYMzlAuhL4etwxc7lBBVJuSiugZW7/LVVKz42u75UqnAKhUJxK3PTGtUpYgirQUvh14n7+Gd2dvay+1NSUmCz2ZY9pqys7JLnSNxntVrlz1d6nVc6lpUIh8NyW6p0b0W424/G6OC0B6kGPSruXgePY0q8R2W7VsuOt0GGX/L8a+P5TTO9oyjcUIf87atFWrCVFhibgGdoQi62bK8FJl0Ya+mTtSv0RnmmPGj/6T5seOwOpGRkSDq6QZsm1YveA+fhGpqAvSwX+Y2V8I9OYD4SXwdjzMuCtbYMU70O9O07J0KFJu7yjbWYCwahyTRBZzUjMBnfK6gzGSQ9nRVIQ3EBBl48B01ysgjAjNwM9Ld0ieeq7s1bMLDnuEwEsljDFHlO/0WZFq7XwTfhRum6SmlnUpTRiO7qHpJqkQRxauK7CVmF4Y2Gd2tdFbz9Q7LehhW1NJNBlhDTpJ00G4Sr14FUQ7pUo6bOd2HW65dKHV+P+VKceMysKZF24JWg6Hk1QmopsqpmQy26XzgpEQ4vP7kGhRvrJC6Cr7FSZhUjHgwXiSSeAy6Z5n5BtlHDbr8MLGQ3lC5UP2/av44UCoXiqlB/i72GfPWrX8VXvvIV3Mowq6nrt8fFmJ6UpJFwSXp4ijazojQv5nMayXNKs2VhcHqWGaNH2mAuyUPP8U4Mn6SZPyZVq7KNteAqvtCUK16xidEM7Y+voIEG5sIsMYgHZryYHpqQybKs8jzo+8Yw3T0ilZHs6kIxlUu7sChHTOKIzWGqawjjZ3uQbtYjTZsi/qiBvaeRWV0sx5y5tlHM6t6hUcy7vbCVFyDVbkfX4QsywcddfiVrK8WTVbC+Fnq7Ga5BBwq2NEkrkitm2DLMaaqAtaYMY10jSJqNoOf5E/E4AcY/lGSjYF0tho+3IbawKicBJyMZBaG1FUFny1hc6ZKsjUdHmHMsmD7TKv886w8g1R9A7voGCR2dDYaQrNPBVJgFe335Kwqq6wl9XDUPbhJRzYXMbElairLEM0Yh2XD/OrQ8e1wEYgImpdffvUaS3BPQUM92LHcecmCgYEOtCDIa8VMX4hYUCoXiVuemFVW5ufE8nfHxcZm4S8Cv6XVKPGZiIm7oTRCNRmUiMPHz/JM/s5TE16/0mKX3v9KxrMTnPvc5fOITn1hWqeL04a0CfTwdzxyBe2jhHGt4wdRLterCLw9K+4lhlZLRNDSB0JQb9vINMBfl4MyTByVVXJPEvW/zcI9M4fwzR9H4wAbMBUJS5ZjpH5Nk80gwAlNuBlyOaWQzqPJom2Qh5VQWwFqUiaFDLTBkWVC8thITp9qAufmFRckxpOfYULxjjSx2ZmxD3IekkXBJiqnpriHkrq7EaOcIUtPSYa6qjLfjPAEERydRsbkehmwrxs72YKqlF5Y8Kya6BzHT1iN7/xipYCjMhb2hQipbxsJcTHQPIzzjlRgGhnEmJiL9Ux7MBXtElA0fennIget4chvL4q28lOT4wmItkJ4ZQ5pRL8nyvG8pYacbWoMW2aurJBldb7cimcGhgTACE1GkmdPFuP96wKEC3rJqLl1hw6XS6x/bBdfojExxMmqCOV7cJ5jAMzKJnj2nF71ULlZ/z/WieGujDCsoFArF7cJN66liy45i5oUXXlgmSuiV2rJli3zNP10ul0z1JdizZ4+0luh3SjyGE4Gzsy+bYzkpWFNTI62/xGOWvk7iMYnXuZpjWQmtViuGtqW3W4WwL4Dp3lE4e0flYsh2FdtcNBuzlUfBMj87B+fgGLzjM8goyRGjuWd4HKFgBCFfSIzV+swMafHIhNp8DENne5HZVAFTaYEsZk5O0iC/oRRlO1Yj3WxA8ZpKJGticPeNwl5kk0oVp+zKtjRgqqVLjmGRpCREAyGMn26HpSg7ntLu8UsmVPnd61G0uQHW8nxE52Lo3t8K57QP8ylp8Lv8iIQiSDEaMXx+ADNc5JxhFN9Vsk4rQorihx4m78gkplp7MXzoPNx9DvQdOC/H4B4cj+dWMfh0oVLFliInEfleK+5dj8JNdai4ey3ym0rh7R+FtbxgcZqPcHKR7VMKQRrfl7bd6C+i4T00OYWgYwzRUAhDL5zAyP4zGNp7EkP7TsmE5M0AhwuKVpWjemcT8utLlgmqSCCEgcOtl5jTec6GjrSJ+FUoFIrbhRtaqWKeVHd39+LXNISfOXNGPFHFxcX4+Mc/jr/+679GVVWVCJsvfOELMoWXmBCsq6vDAw88gA9+8IMypUfh9NGPflSm8fg48gd/8AfSgmNcwmc+8xmJSfjWt76Fb3zjG4uv+7GPfQy7du3CP/7jP+JNb3oTfvzjH+PEiROLsQv0grzSsdx2i5OHJxF2eReT0rn+hObrxO48+pYCMx4xaHOBMDOd2JILc8fe8FR8Z14oAu+YU5YA0xPEqk4kHIWhIBvBcSeKNtUhzZiO2GwUaUYdvL1BBMamRGix5TXnD8ly3ry1NVLRYip3NBbDPKMWuCwZGslvosizFubBkGNDdpx9M8cAACmiSURBVF0pHOd6MHKqS46JAouP0VvNYqJnyjqnEfm2ePzEkm+Du3MA5XetQ1JqEgq3NssuQh4/L/5zkYhU48xlBeg50CJtSAoetrkS3iwei+RsaSB+rGg0JNUsf2RWfpbBpBSYF8Pnqr5/I2Z9foQnJ+R3jYJVPFmLHwgQmHSLaEwQcfvhOHweRbvWStL6zQoXP9M7tRJ8P8weY+aWQqFQ3A7cUFFF4XLnnXcufp1olT3++OMSVfDpT39aog6YO8WK1Pbt2yUygQGdCX7wgx+IkLr77rtl6u9tb3ub5EktndL77W9/i4985CNYt24dMjMzJcRzaZbV1q1b8cMf/hB/+Zd/ic9//vMinBi50NjYuPiYqzmW2wVWe7zcPSd7/VJEVNDHk7TQ6mL1gVUaa0kuJk63y/g/xQfDMSvu2yQ79LjKJuyNikBjNYI7/riyhUZ2T98opk63w1ycA31tCfTZZsxGoija0iQtRlN+Fsba+hEKRXH8hy+KKKneXC3RCTSDzyUnSfAn85goQmjUojGbK3I6n+PUp2ZhlZ4G7uEJ9O87i8KmUnQfviB5U/xZCiBWhPg+GORJI/bIiXbxbHFNTMG2VfAOjolooiBMyzBh4FSXrMSxOn0I+UNIt5pklQ2rMKxApaVrZSch87HMObmYC83KcVAgzXpcmAvlIMl46b9ynOCThPimWri744b/l4khPT8Pzp6XoxgS8HVZrbqZRdXSNTorwVU+CoVCcbtw0+RUvRG4VXKqPENjEuw43ecQzw/XkrDNxnYeBQ6DMm0V+WIKHz/VES+lyKSbRipPBXdswMmf7xOxw18uVrc4KUgDNttExjQGg6aK/yZZr5NKE6cCKeaoQjKqi5GSmYlTP98n4idFq0XdHU0Y3n9KRBTDRGPRqAi3qC8AbYYZ+TvXiaGe3ioeCw3vfKzWYpDntFYWYrBtEL4xpxjs+bO8n3EMRQ3F0uLjeyvb3gTf8LiEhNIbxurUwJE2OM73YmZ0WipcphwrCupLMHS6C0FPADnleWK6po6LBvyovHsdIpPLvX4ko7YCxoKXPXkXI+1Ltwd+xzjmgiGkmU3Q2qxwHGsTIbgSpqIc5G9uws0Kq4HtTx+SVvFKVD+4SRZCKxQKxe1w/b5pjeqKG4hUcVJEJGQUZokxnCPwiMREiFiLs5HXXIGB5+NZYEhEBsxGkdNciTm3E8XNpejaezZe3WJaulYLY0kOskqyMXO+E4VbmxCcnJJ2oW9kUsI8E/Ke1Yv+feekejM/H5Moh/FeBzLK88XXxIlBvTk+AccsKUN+FvxjU/JznECcm2XLTSvRDZKTlZoi7cqsigL4xl2SBM8KFaf1qnc0YuRIi4govd0iBvo0faqIwfTcTIl74KRjjHvsjMNSHTPm2oF0rfzJhc4ME9WmpcCYYxWPVNRDK/alUABeCcnKslvlxgofz1vY41sxLDMBq4M3M/oME3IayuA483KbPwFjJOhbUygUitsFJaoUl8A1MKHJbpnO6nrqJWl/FW+sFeFBE3Y0EMTU2U7xKoUX2lus/tDThLlZuDr6YCktxNrf2y5rS+jjNmebkVGQhcHfHIGpMEcyq9JzszHR0oOIL7AstFuTmgr/pBNJnG6bj0m1auhkF2ruWo3M+jKJPWA2Ehc0G3LtsuQ4POPBfDiM+UgEyZyuS9ZgNkBBlYxwIIxkXwiWbCs2vvsuGe2n4NIgBlfvqLQ2mUVFkTVzrk0CQtlS02UYxKCPpGR0nusX0cZoiYn9rTLRWL6uCtUPbEKyBjAzkykWQ2pqEkLhlVe7JKdfvQBKeNeYY8V4ClfP8AoP0sCQe3NXeVi9ZLAnW63jLX1ScaNgt1cWIqehdFkQq0KhUNzqKFGluASazCl8YhHu1jNIpcTVNSD+Kg6paS1mmeiLuealPSghk7F5ZNaVIDA8IhWXiNON4PQg9CYD9FlWBCccCMxFYCzMksdHfZ74wmIqrosa0POhsFQ4Qv4FE/jCwuD2509L3lXdXauh1aWI4HC29cDnmBQTu62iAI5TnYgxTyslBWlpqfCMuxD2h5C/rgZtvzkBe2kuMouy0He0DTqjDhlsPc3HYC3NQXqGHuFZvfjGKGo8PQNISdcjOd0g+wmD3iBmI7PSMuT9U0MTGOsaRm5VAarriuAbn0HZjpd9eEthuCjblNeKVAari0V4BsZfnvbjMeasqZHK2s0OhVNuUzmspblSJWTrlb9j4odTKBSK2wglqhSXQFFkqy2Fb3RS/FLRYNzPM89puNi8ZCUV7liD0LQrPtHn80urUAzZvgBSjemyWJkXfiaC8yKanJIqE3OMLJifn0OayShCI24oj1dmJHuKeU8j4yhaXY7uw+3UauKJkseCi5M9EjTZv/8sGh7dDt/4tEzLSdXGbpb1Nb4Jp3wvHAhJRSunvhTuCRfmInOY6BqRBHimwqekJMuS4ZRUDea8Xsy6XPHnWoJ/yAH7qnqUr63CuedPSTWK738pZU1lCE7MiEjg0mSdzYrQjPPl85maCmtdpbznVwN9ankbGyRhnjcKRibE0y+WqGjdCtCQr1XdPoVCcRujRNUbGC7qDTu9UunhDr30LKtUlXgRZ+WH1ShOtWktRqkq0WxMoUTR5eobQe6GeowePCPTc/QxcXxel8l4hai005K1aeJd4hoW5jeZSgrgm/HB2zeC/PW1iPr90NssmPUGpc0mAoGxBPPzSJ6LoGJbA3qPtEulKjkpRRYbV+1sQmjKCUueXULWctbUSvwBxcas34/yO9ci7A9KJATbluUZRvSf7MLwqc7FvXsexww6957D+nfdiayqAkyePLcoHC+G3+exFdeXYHJwHINnl0/nVW2uRaomhkg0fm7YStQVZkpEwlwwHvZJ3xdXz/wuiEdMp5W9fwqFQqG4OVGi6g0sqFxdQ5hq6Vn8nmdgTIzPnCZjJURiCpoqMXrorEymsVrETCkKn+xV1UjVp6Fo5xoEnV4RH0zdTjXkYPzoGdEvKXq9rKXxTriB5GSkukPQZ9skJT0aDCPVYoDdxEiCKLwjE/K8rMJQjBmzbdBlW5FXXwLX8DRmKdKSNfA5phENR8U87uwagM8xJVN6+Vua4O4ZweCeo/J89HfF5qNIMmvj61IWBBUn/HRmg/inOEUoPjG97rKiKpnTjikpMGRoseHNm1G+qhL9JztE+GUxcNQfgJ/xEwDsFQUSIkohlWzNAOLZsgqFQqF4g6BE1RsUVqiWCqoEs74gpi/0IW9jI1LT9Qi5fSjctQ6BsWmEXPGFyqaCbBE2UX8A4ekZJGnTkKpNhn90DGlGA2yN1fD2DUqrzzPhRgoXARcXYmbCA4s9Hd5eRzz2QJsGfaYNBduaEQ1GEJx2L6xkscixeHpHpUKms1lgstngHJiAOd8uJme2AJk5xVacezC+pJnHTcO8ZiGAk7vqXANjqHzTdpnMm+x2iODJrshDbn0xDAv5TsbCPIRnVp7YMxYVyM8QvVGPwroiZOZbMXqmW7Kj6PmSdmllAfJWVSw+VqFQKBRvPJSoeoPCCs/l8DumxBjNeAJbZRHGTlwQQ7ohJ1MqVq6eEdgby2U3HUXVPKfdYkwej8I/MQ3d3ByM5WXQaHWYM7kR9IQx0j6ChvvWwtfdHZ+i87HlNyeVJ0YnpKRrkb1hFWIxDZzdQ7JIOLHShenh9DqxgsZpP1bG+vaeQWZVMQKTTjGoewYd8cRxTiOmpMY9WhwpjMXg7BxAbl05zFYjdDaTLAPm5GACrdUCa301PP2DspeQ8OdNZUXQ2S9NQWdFrmRro0y1MUaCU5A8V8tS0BUKhULxhkOJqtscJlrPBQIIO50SmJlqNCLFZIpHBVwGpqMnTOMMl6SXx9U7LL4l+qzYakvPtkl8gVd2AEal8sRly/5Jl1S19DlZiCUnw5xlgdHkR2FNJtLSNNBaMzDTOSDeoCStFtFgEP7RSWgjeoSnnRJf4Op8WVAtvo/ZKKZauqG1mhD2BKRK5RyZQsGWZolGcHb0S7tSvEfpOok+EDQahL0BWWrM9tzF79M/5YJrcELS3nUWA0zVRVJ1ox+LPqjLGcEZLWHMulRwKRQKheKNixJVtzFsnYUmJxEcfXnFSUQm3FJhLsyTdTGJZcBL4YJfeo8IxQ2rQ/qsDBE29BclWlzMHrI31cHV2SNTf8naVBjy7NBardCkajHnnsFc0B9fwRKch29mGslmC7Kba+Ds6BEfE1uM9rpyhNh+S04WQTYXDiFZq4MmabmwCjm98jqsWpny7WKCn+odQ97qCljKCsSXxWm/qNsvpvEEbB9qLlocwCrWTL9DVtjweRJMXBhA+a7VSM9+dZN6CoVCoXjjokTVbQyrQEsFVQJGG0Smp6QKRXP6xdjqykTsLIXi6uLqUaJ1lrm6UV6L4oQ+KY02DeGpaYRjISRl2mS9DX9WZ7EiNDkDz+iAJJ3HovMIM7jT6UZGTSXA2AUROKyUzV0iqggN6/RWuQYmJEQyq7ZIqkkZlUWY6hgQkciYhwQUesa8TKlgLYWp7IOHWpYJqvi5mcPAoRbouNfPzBU3CoVCoVBcHUpU3cbMejyXvW8uGICtqlx8SH7HtLT7aEK315XCWJhzVc/PSlNiJ12KQQ/NQjGIeU1MOfeOu+EdYNZU/I6cDfXwj0/H9/Zp0xCNBheeSYPA+CQMRXnQZ2YAHfEqG1Jkc+Di63FSz9k3jsmOIVnyzJadf3wGGSXZyG2qEM/VdCsT2oPQxDRIz7HBVlMivij6npbCn50Lr7z+ha1FGvSVqFIoFArFtaBE1W3up7oSbKNxyo+mdGYfMD7g4grVSlCAMRh0sqUHs96ArHVhara1qghRnxfaTBsC4y54+zkdt+TnIrNSlZK4hvkY5lNnJaYhOS0tfgxzc0jRJsGQmyUG9KWCKoYYTEW5mOgcWWxR8jhCMx5MtvVLWjfN9FmrasQIzypWLInPlQlTru2S98DcrCu+x+jyCpZCoVAoFK+EElW3MTSlhyeZin4p9FXJjUt8F6IFrpbAhBOjR1pkso6CKuL2IuL0IDjpRP7WZpmgm27tltBPCqlFNBqpWrHFx0XJSE6NB5AGaBI3QpMUQ2w2hMz6EgRnsuAZHBcfF0M/LeWFGDnbK/lWhIKK/0zDOPGPO6HVxd9PmsUohnZLcd4lFaoEWi5kZvbCRV4rOUyGeN7ki4oVCoVCcfOhRNVtTEp6OpL1eswFE222l9Hn5iJZe+3LbNkudHYNLoiRmCSxy/6+hQk9VrBMxblSLaJo4UReov0nfqfUVNn1R+9SNDIrrULGG7DylJTCxcwMDdXC3pCHjIqieLq6Nk08UMEp95IDicVbhIkvJZ9Kg7DLKzcufbZXFV/2faRbTbCV52Gm51LPWWZVoXiqFAqFQqG4FpSouo2haDKWliI4Pi5Tf2zxMcZAn5ODtIxXFwfA9TOcwiNSdYpElt0fmnbLJB6nBCnAGG8QY44VwzyHx5FRV4mAYxzpJkM8tiFJI02+jJpyiTFItlqRlBZfj5NkeLlaxMqR3mZCcCb+2nHBlrRoNDfnZyLoeLkqx9U6Vzw3aakoWF8rzzvVMYRoKCItzKz6EmRWFy0zuysUCoVCcTUoUXWbw1UxxuJizOXkSHVJwzUwafG4hFcDzeL0YtGIvsTytAirSnOhEMwlufAMOJCUlobk1PjrzUdjCHnDyNm4CsHJaakmpRoMMORnI83CtTiXD8+k4ClYW4OePadEjLHNR/9XxOuHuSBTsqoS2VoUXJxsfCWYq1W4vlYqU3PROWklKnO6QqFQKF4tSlTdBjDIMxFBwArRxVCsUFxdDxhNkFFRgMmzXdBokmQVTdT/cnvRXJKH0MQUTIVZ8eBNd2CZ4LLXliA9Jwv67EypMtG/xLbd1WAuzELlfesxfr4XgSk3UtKtyFtdCW16GryD8WgIWUOzuloWNV8t9HMlsqsYcCqmeY1GFktzQfLVHp9CoVAo3tgoUXWLiylO20W8LvEXsQqVZrYixWBcMVPqemEqzBFTum90SipRmnAEsegcMqqK2CCMm8i9PuRtbpbYAgnsTEuF1mwUkUIoVFj1uhw0oUcDAXmPbGOmGg0imCwFWTBmWzEbDMtaGLbxKIQM2VYRaPIaZsM1CyFmabl7RzDd1htfd7PQIuRCaVbdXsvzqVAoFIrbAyWqblFYmQq7phH1vpxFFZudRXh6ArG5KNIybJcVFsx4Ei8UlxrrdNcsGGgqz1lXB0u5F4GJGcRi81LtmfX5EfX7YakshS7TLrlXQpb1mp6f6erOC13i3xI0gD4rU55XfFepKYtTfySd2Va8/Q4wyX3yXNey781FZjF+ql3eL1PlFQqFQqG4EkpU3aJQGC0VVEuJuJ1SrUpOWz7dx2oWDeuBsTHMh+OCJcVoRHp+vsQvXGsb0JinlaqQb2QCrp5RpBi0SDOYkKxPlwm+VwOrWjMt7fF9gosHDgQnpsTLlVFdfkXv1athbnY2PtG4ErEYXH0jSGcl7Dq/rkKhUChuL9RV4hYlNhu5wp0xWUVzMRGPB76BgUVBRaI+H7y9vdJqu1aYpu441iL+qpDTA9/wJGY6BjC8/zT8Y9N4NYTdnuWCagmBsYll/q3rxXwkisgVnjfi9ksEhEKhUCgUV0KJqluVV/AMXdz6YzUmOHbpnj/CtTER95IMqKskOONGaGl2VOL55mOYau1BdCFK4VqI+i8v7mhsp8fqesMK2JUqa6lGPTQp6l8VhUKhULzC9USdoFsTZjldTlhx9QvT0i8WTow6eDV7Ai+H3zF12fvCLh+iC3sBrwXuELwcbL9plniprhc0pHPFzuXIKC9QRnWFQqFQvCJKVN2iJKWmQWvLvPQOjQZaW5bcv/zbGhFbl3++1Gs/hit5jCj4XkUUgZZ5VSvEQhB9TuZV7SZ8NRhzs2CrLZEE+AScJsxqroT+Go32CoVCoXhjoozqtygUSalGs4inWZ8X87MRMaanGk1I0uoueTyT1NOs1svuAtTar326zZCfBVdvfMHxxegzM16VAGJ0gr2xBjMXujC/pH2oy7TCXFr0mpnFk7WpsNeVw1iQjYg3IHowzWSE1mJQBnWFQqFQXBVKVN3CxEM9OWmXLsGVV8pm4n26rCyJPJi7yJSuy85GisFwza+vs5lhLs2Fp3/sEo9SZkM5ktNe3a+Xzm5F1romRH3MqZqTScMUo2FZjMJrAXOwGBp6LcGhCoVCoVAkUKLqNuFqwi5TdDqYystFWM16vdIOTDObZenySknsr/h82jRkNVXBkGOHu3dUcp3Sc2yyUFlvNeN3IVWvl5tCoVAoFLcKSlS9weDeP9601uvjE2IVyVycJ20zTv291tUkhUKhUChuVtQVUHFdkFR2tclFoVAoFG9g1PSfQqFQKBQKxXVAiSqFQqFQKBSK64ASVQqFQqFQKBTXASWqFAqFQqFQKK4DSlQpFAqFQqFQXAeUqFIoFAqFQqG4DihRdY18+9vfRmlpKXQ6HTZt2oRjx45dj89BoVAoFArFLY4SVdfAT37yE3ziE5/Al770JZw6dQqrVq3C/fffj4mJidfuE1IoFAqFQnFLoETVNfD1r38dH/zgB/He974X9fX1+Nd//Vekp6fjP//zP1+7T0ihUCgUCsUtgRJVV0kkEsHJkydxzz33vHzykpLk68OHD6/4M+FwGB6PZ9lNoVAoFArF7YlaU3OVTE1NYW5uDjk5Ocu+z6/b29tX/JmvfvWr+MpXvnLJ95W4UigUCoXi1iFx3Y7FYld8nBJVryGf+9znxIOVYGRkRNqGRUVFr+XLKhQKhUKheA3wer2wWCyXvV+JqqskMzMTycnJGB8fX/Z9fp2bm7viz2i1WrklMBqNGBoagslkgkajudqXViz8VwLFKM+f2WxW5+Q6oM7p9UedU3VObwXU7+m1wwoVBVV+fv4VH6dE1VWSlpaGdevW4YUXXsCjjz4q35ufn5evP/rRj17Vc9CDVVhYeLUvqVgBCiolqq4v6pxef9Q5Vef0VkD9nl4bV6pQJVCi6hpgK+/xxx/H+vXrsXHjRnzzm9+E3++XaUCFQqFQKBRvbJSougYee+wxTE5O4otf/CLGxsawevVqPPfcc5eY1xUKhUKhULzxUKLqGmGr72rbfYrrB71pDF1d6lFTqHN6s6F+T9U5vRVQv6evHZrYK80HKhQKhUKhUCheERX+qVAoFAqFQnEdUKJKoVAoFAqF4jqgRJVCoVAoFArFdUCJKoVCoVAoFIrrgBJViteNffv24S1veYsk0jJR/sknn1x2P2cmGFeRl5cHvV4vy6q7urqWPWZmZgbvfve7JbQuIyMD73//++Hz+ZY95ty5c9ixYwd0Op2ksH/ta1/D7Qh3S27YsEES+rOzsyWUtqOjY9ljQqEQPvKRj8But0ui/9ve9rZLtgIMDg7iTW96E9LT0+V5PvWpTyEajS57zEsvvYS1a9fK1FBlZSW+//3v43bkO9/5DpqbmxdDEbds2YJnn3128X51Pn93/u7v/k7+/f/4xz+uzuur5Mtf/rKcw6W32tpadT5vBjj9p1C8HjzzzDOxv/iLv4j94he/4MRp7Iknnlh2/9/93d/FLBZL7Mknn4ydPXs29vDDD8fKyspiwWBw8TEPPPBAbNWqVbEjR47E9u/fH6usrIy9613vWrzf7XbHcnJyYu9+97tjLS0tsR/96EcxvV4f+7d/+7fb7kO+//77Y9/73vfkfZ45cyb20EMPxYqLi2M+n2/xMR/60IdiRUVFsRdeeCF24sSJ2ObNm2Nbt25dvD8ajcYaGxtj99xzT+z06dPyGWVmZsY+97nPLT6mt7c3lp6eHvvEJz4Ra2tri/3v//2/Y8nJybHnnnsudrvxy1/+MvbrX/861tnZGevo6Ih9/vOfj6Wmpso5Jup8/m4cO3YsVlpaGmtubo597GMfW/y+Oq/Xxpe+9KVYQ0NDzOFwLN4mJyfV+bwJUKJKcWN+8S4SVfPz87Hc3NzY3//93y9+z+VyxbRarQgjwgs6f+748eOLj3n22WdjGo0mNjIyIl//y7/8S8xqtcbC4fDiYz7zmc/EampqYrc7ExMTcn727t27eP4oCH72s58tPubChQvymMOHD8vXFFFJSUmxsbGxxcd85zvfiZnN5sVz+OlPf1r+Al/KY489JqLujQB/n7773e+q8/k74vV6Y1VVVbHdu3fHdu3atSiq1O/pqxNV/I/LlVDn88ai2n+Km4K+vj5JqWfLb+mepU2bNuHw4cPyNf9ky49rghLw8dypePTo0cXH7Ny5U3Y1Jrj//vulLeZ0OnE743a75U+bzSZ/njx5ErOzs8vOKVsExcXFy85pU1PTsq0APF9cuNra2rr4mKXPkXhM4jluV+bm5vDjH/9YVlGxDajO5+8G29BsM1/8u6TO66uD1ghaKcrLy8USwTa+Op83HpWorrgpoKAiF6/84deJ+/gnPT9LSUlJERGx9DFlZWWXPEfiPqvVitsRLvemR2Xbtm1obGxcfL8UlxSiVzqnK53zxH1XegyFVzAYFP/b7cT58+dFRNE/RR/aE088gfr6epw5c0adz1cJxempU6dw/PjxS+5Tv6fXDv9jk77GmpoaOBwOfOUrXxEfaUtLizqfNxglqhSK26QKwL9QDxw4cKMP5ZaHFyoKKFb+fv7zn8sS9b17997ow7plGRoawsc+9jHs3r1bhkcUvzsPPvjg4j9zsIIiq6SkBD/96U9vu//IudVQ7T/FTUFubq78efFkGr9O3Mc/JyYmlt3PKTVOBC59zErPsfQ1bje4i/Lpp5/Giy++iMLCwsXv8/1GIhG4XK4rntNXOl+Xewyn427Hv8BZ3eOE47p162TCctWqVfjWt76lzuerhO09/nvL6VFWlnmjSP2nf/on+WdWPdXv6e8Gq9HV1dXo7u5Wv6c3GCWqFDcFbNnx4v3CCy8sfo/tJXql2Ioh/JMCgX9JJ9izZ4+0vvhfaonHMLqBXqIE/C9kVh9ut9Yf/f4UVGxP8Txc3PakKEhNTV12Tukto/di6Tllu2upWOX5omBiyyvxmKXPkXhM4jlud/j7FQ6H1fl8ldx9993yO8bqX+JGXyR9QIl/Vr+nvxuMlenp6ZE4GvXv/Q3mBhvlFW8gOP3DsX3e+Kv39a9/Xf55YGBgMVIhIyMj9tRTT8XOnTsXe+SRR1aMVFizZk3s6NGjsQMHDsg00dJIBU6+MFLhPe95j4zB//jHP5Y4gNsxUuHDH/6wRFC89NJLy0arA4HAslF1xizs2bNHIhW2bNkit4sjFe677z6JZWBMQlZW1oqRCp/61KdkevDb3/72bRup8NnPflamJ/v6+uR3kF9zuvS3v/2t3K/O5/Vh6fSfOq/Xzic/+Un5956/pwcPHpRIFEahcAJYnc8bixJViteNF198UcTUxbfHH398MVbhC1/4gogiRincfffdkhW0lOnpaRFRRqNRxv7f+973ilhbCjOutm/fLs9RUFAgYu12ZKVzyRuzqxJQkP7Jn/yJxAJQGL31rW8V4bWU/v7+2IMPPih5XvyLmX9hz87OXvLZrV69OpaWlhYrLy9f9hq3E+973/tiJSUl8j4pLvk7mBBURJ3P10ZUqfN6bTDSJC8vT35P+Xccv+7u7lbn8yZAw/+70dUyhUKhUCgUilsd5alSKBQKhUKhuA4oUaVQKBQKhUJxHVCiSqFQKBQKheI6oESVQqFQKBQKxXVAiSqFQqFQKBSK64ASVQqFQqFQKBTXASWqFAqFQqFQKK4DSlQpFArFLQhXB9XV1WFubu5GH8pNAfcHlpaW4sSJEzf6UBRvYJSoUihuYTo7O2Uh7Yc//OFl33/ppZeg0WiWLVMOhUK48847sWbNmkuWLCtuPT796U/jL//yL5GcnHzDjqG/v19+z7jD72ZYhP3nf/7n+MxnPnOjD0XxBkaJKoXiFoab6Z977jn86Ec/wuc+97nLPi4ajeL3f//3MTo6it/85jey1V5x63LgwAFZoPu2t73tRh/KTQWXNPPctLa23uhDUbxBUaJKobjFYeXp17/+Nf7pn/4JX/va1y65f35+Ho8//jjOnj2L3bt3Izs7e/E+tku++c1vLmspsfLw6KOPLnuO73//+/L9pbfVq1cv3k9ht337dhFrdrsdb37zm+Wiv5TDhw9jy5YtMBqNKz7Hxaz0monbxZURvo+LH/Pkk08u3r93715s3LgRWq0WeXl5+OxnPytCM8Edd9yBj3/844tf82f5HBe/xtJzdTXvmfzRH/3RJce29LW+/OUvX/E8rMSPf/xj3HvvvdDpdJd9nlOnTsmxffe731383tJjMJvN8hwrHfOV+OUvf4mioiL5PfrFL34h3+PvVUFBgXzvP//zP+V73IBWWVmJf/iHf1j28/zs+Prd3d0rfm6JGz//xDEv/SyXwvfL953AarVi27Ztcn4UihuBElUKxW0ALyS8wH3hC1/Av/3bvy277yMf+Yhc9J5//nkUFxdf9jkovj75yU+K6LkYXiB5EXY4HHLj45bi9/vxiU98QvwsFGZJSUl461vfKs+Z4O1vf7tcjE+fPr3ic6zE0tfk7dixYys+jsf3V3/1V4uPW8rIyAgeeughbNiwQYTld77zHfyf//N/8Nd//df4Xbia95zggQceWDw2Csvflf3792P9+vWXvb+9vR3333+/tAc/8IEPLLvve9/7nhzHvn37MDExgc9//vNX/bpTU1N417veJUKRP882M3nmmWfkd4y/fx/84Afl9SmG3ve+98nrXfz6O3fuFMF1/PjxxfNSWFgoojXx9WOPPYZXA8Uzz49CcSNIuSGvqlAorjsWi0Uu6H/6p38qFzPCliArFRQnr9Ty+6//+i+Ew2E88sgj8Pl8y+6bnZ0Vz0pubq58fbHwurgNxWpFVlYW2tra0NjYKBdvth5ZoamqqlrxOVaCF+bEayZ8YSvB47PZbMsem+Bf/uVfRMz98z//szxfbW2tHAu9N1/84hdFDL0aXuk9J+A55XtNHBvP4+/KwMAA8vPzL3sfK1B//Md/LB6ji+HvAY9Fr9fDZDLJ783VwjYzq3IUsDyXX//61/GrX/0Kf//3f4/6+nq58TEUrfwexRfPMcUwxQ4/px/+8IeL1SuerwT0hvFYVvoMrwWeF54DheJGoCpVCsVtMvnEisSHPvQhERGJahWFEqsoDQ0N+OhHP3rZnw8EAlLVYPswJeXS/9byeDwwGAyX/fmuri6pYJSXl4uAY1uHDA4Oyp8UPLxg/vSnP5UL6/XmSsd34cIFqQ4tbeexskfhODw8/Kpf85Xec4Lp6Wm5/0qcP39ehBfPESf6/u7v/u6Kjw8Gg8tafwk4gHDPPffI+2KlaiV4zHwttsq8Xi+++tWv4mphy66mpmbxXCZ+V5b+zlBY8XEJgfOmN71psSVIAUaRSX/ftZA4ZrZu+XwUrpeDYpG/zwrFjUCJKoXiNuBv/uZvRCTwAklxxUoC+clPfiKtFlareEF76qmnVvx5VhV4sXzLW96y4v2s7FyuMkL4czMzM/iP//gPHD16VG4JsZe46P6///f/8POf/1wuerxA/u3f/u11E1RsxV3p+F4LXuk9J+jt7UVZWdkVn4vnnl4jVnTo92J1h+fqcmRmZsLpdF7yfVZoNm3aJD4jVitXEhff+MY3Fl+LVSFWk643bMcm4O8jPU4Ugmz9sa2Xnp5+Tc+XOGb+DlOUv+Md77jsY/mZLK2AKRSvJ0pUKRS3OC0tLVLZYHUq0VLbsWPHsj85JfilL30Jf/InfwK3273s5+lf+cd//Ee5XQ56X2iIXwlWYjo6OqTSdffdd0ulZaULPkXI1q1b5U9eIFlVux7w2K5keufx0CS/9EJ/8OBBaX3Rx/NquNr3zIoRRVXic7gcbAnSY0RxxaGCVatWXTGmgJ/FStUaVs1o8P6Lv/gLqY6tNBFKIcXXoieLrWIOOVxt9ZDPz/edOJcJs/9S0z+Pq6KiYvFr+tlYRaSXjeb+RGv6Wlh6zB/72MfkNS53zPz34XK/qwrFa40SVQrFLQw9VKwEvPOd77xsuycB/TXMtLrYZ/Ptb39bDNYrXYhoTOYFmiKEF/uVYBuJPpt///d/l7bPnj17xMB9MfTfUCjwos8LJFuCvysvvviiGPF54V461bgUCsmhoSEREDRQs1pHgcljXOqnYogmPVu8JS7Yia95o5CgeODjruY9U2TRt1VSUiKidmxsTG6sZLGCtNS3xufma7Dixue62Jd1MfysGR1wMRSKrAryxvNMoX2xaZstQh4HxRG9TxRKqampch9F2B/+4R9esQ03OTkp548/n3jPzMziMdO3duTIEbz3ve9d5pViNYzPTT/dqzHq8/Pg+eFx//d//7ecz8QxXwzf73333XfNr6FQXBdiCoXiluXrX/96LCcnJzY9Pb3s+y+++CJLCTGn07ns+6dPn46lpqbG9uzZI1+XlJTE9Hp9bGhoaPExjz/+eOyRRx6Rf/7mN78ZW7duXezJJ59c9jxf+tKXYqtWrVr8evfu3bG6urqYVquNNTc3x1566SV5/SeeeELu37dvX8xsNsfOnTt32ee4mO9973sxi8Wy7Ht9fX3yvHwfpLS0NPaBD3zgkve59LUJj2fDhg2xtLS0WG5ubuwzn/lMbHZ2dvH+Xbt2yc9czY3HdTXvmefxSs/D9584D4nvJSUlxYqKimJf+MIXYleCn7dOp4u1t7df8Xz+1V/9VayysjLm9/sXz0viZjKZ5H0nzmXimPm9K/E///M/sfz8/FhmZmbsG9/4hjzXP/zDP8Ty8vJidrs99m//9m+X/ExPT4887mtf+9pln5e/i4lzu5SVjvnMmTNyH99v4jySQ4cOxTIyMmKBQOCK70GheK3Q8P+ujzxTKBSK2xtOL7LNeDU+JD6G+VcrPZbRAawYLc1YulY+9alPiZ/s4giN1ztRnX4xxmRcKWuL1SO2SVkxZLX0tYJ+LbZOryUmQqG4nqj2n0KhUFwlbDld7VoYTvLRlL8S9BhdTaTElWBblq3FlXKxbhY46UdfGcUjJ/5eS0HFtmpTUxP+7M/+7DV7DYXilVCVKoVCoVC8JpUq+rre//73y31MYmfqukJxO6NElUKhUCgUCsV1QLX/FAqFQqFQKK4DSlQpFAqFQqFQXAeUqFIoFAqFQqG4DihRpVAoFAqFQnEdUKJKoVAoFAqF4jqgRJVCoVAoFArFdUCJKoVCoVAoFIrrgBJVCoVCoVAoFNcBJaoUCoVCoVAo8Lvz/wefdKgkowygxgAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.scatterplot(data=df_houses, x='GrLivArea', y='SalePrice', hue='OverallQual', alpha=0.7)\n",
+    "plt.title(\"Цена от жилой площади\")\n",
+    "plt.xlabel(\"Жилая площадь (кв. футы)\")\n",
+    "plt.ylabel(\"Цена ($)\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "da580b45-8f0b-4bbf-8be6-8ddb3340670a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка домов: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1460/1460 [00:08<00:00, 175.61it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "for index, row in tqdm(df_houses.iterrows(), total=df_houses.shape[0], desc=\"Обработка домов\"):\n",
+    "    time.sleep(0.005)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "60e57244-d2d7-4675-ab57-3aa988454308",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.14.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}