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Date: Sat, 23 May 2026 21:12:19 +0300
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---
 .gitignore           |   4 +
 README.md            |  30 ++
 Untitled.ipynb       | 720 ++++++++++++++++++++++++++++++++++++++++
 requirements.txt     | Bin 0 -> 3956 bytes
 week2_analysis.ipynb | 757 +++++++++++++++++++++++++++++++++++++++++++
 5 files changed, 1511 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 README.md
 create mode 100644 Untitled.ipynb
 create mode 100644 requirements.txt
 create mode 100644 week2_analysis.ipynb

diff --git a/.gitignore b/.gitignore
new file mode 100644
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--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,4 @@
+.venv/
+__pycache__/
+*.pyc
+.ipynb_checkpoints/
\ No newline at end of file
diff --git a/README.md b/README.md
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--- /dev/null
+++ b/README.md
@@ -0,0 +1,30 @@
+\# Учебная практика №2.2.
+
+
+
+\# Освоить JupyterLab для работы с Python-кодом, анализа данных и визуализации.
+
+Познакомиться с основами работы с pandas, numpy, matplotlib, seaborn и tqdm.
+
+Научиться комментировать код, изменять параметры и анализировать результат.
+
+Укрепить навыки работы с Git: вести репозиторий, фиксировать изменения, документировать процесс.
+
+
+
+\## Описание
+
+В работе используется JupyterLab для анализа данных с помощью библиотек pandas, numpy, matplotlib, seaborn и tqdm.
+
+
+
+\## Файлы проекта
+
+\- `week2\_analysis.ipynb` — основной ноутбук с анализом данных;
+
+\- `README.md` — описание проекта;
+
+\- `requirements.txt` — список зависимостей;
+
+\- `.gitignore` — исключаемые файлы и папки.
+
diff --git a/Untitled.ipynb b/Untitled.ipynb
new file mode 100644
index 0000000..4cb7a14
--- /dev/null
+++ b/Untitled.ipynb
@@ -0,0 +1,720 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "135f3d22-550b-413f-8955-93a0ebf6e562",
+   "metadata": {},
+   "source": [
+    "## Самостоятельное задание: анализ свободного датасета\n",
+    "\n",
+    "Для самостоятельного анализа выбран открытый датасет penguins.csv.\n",
+    "Он содержит сведения о пингвинах: виде, острове обитания, длине и глубине клюва, длине ласт, массе тела и поле.\n",
+    "Данные были загружены в pandas с помощью функции pd.read_csv(), после чего выполнен базовый анализ и построены графики."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "6ec4844e-a8c1-4203-b4d9-6814ef719e41",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "from tqdm import tqdm\n",
+    "import time\n",
+    "\n",
+    "pd.options.display.float_format = \"{:.2f}\".format"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "7ee1c419-82b5-47a1-9f5a-d05e4cd143b6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первые 5 строк датасета:\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>Вид</th>\n",
+       "      <th>Остров</th>\n",
+       "      <th>Длина клюва, см</th>\n",
+       "      <th>Глубина клюва, см</th>\n",
+       "      <th>Длина ласт, см</th>\n",
+       "      <th>Масса тела, кг</th>\n",
+       "      <th>Пол</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>3.91</td>\n",
+       "      <td>1.87</td>\n",
+       "      <td>18.10</td>\n",
+       "      <td>3.75</td>\n",
+       "      <td>Самец</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>3.95</td>\n",
+       "      <td>1.74</td>\n",
+       "      <td>18.60</td>\n",
+       "      <td>3.80</td>\n",
+       "      <td>Самка</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>4.03</td>\n",
+       "      <td>1.80</td>\n",
+       "      <td>19.50</td>\n",
+       "      <td>3.25</td>\n",
+       "      <td>Самка</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>3.67</td>\n",
+       "      <td>1.93</td>\n",
+       "      <td>19.30</td>\n",
+       "      <td>3.45</td>\n",
+       "      <td>Самка</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Вид     Остров  Длина клюва, см  Глубина клюва, см  Длина ласт, см  \\\n",
+       "0  Адели  Торгерсен             3.91               1.87           18.10   \n",
+       "1  Адели  Торгерсен             3.95               1.74           18.60   \n",
+       "2  Адели  Торгерсен             4.03               1.80           19.50   \n",
+       "3  Адели  Торгерсен              NaN                NaN             NaN   \n",
+       "4  Адели  Торгерсен             3.67               1.93           19.30   \n",
+       "\n",
+       "   Масса тела, кг    Пол  \n",
+       "0            3.75  Самец  \n",
+       "1            3.80  Самка  \n",
+       "2            3.25  Самка  \n",
+       "3             NaN    NaN  \n",
+       "4            3.45  Самка  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Загрузка открытого датасета\n",
+    "url = \"https://raw.githubusercontent.com/mwaskom/seaborn-data/master/penguins.csv\"\n",
+    "penguins = pd.read_csv(url)\n",
+    "\n",
+    "# Перевод категориальных значений на русский язык\n",
+    "penguins[\"species\"] = penguins[\"species\"].replace({\n",
+    "    \"Adelie\": \"Адели\",\n",
+    "    \"Chinstrap\": \"Антарктический\",\n",
+    "    \"Gentoo\": \"Папуанский\"\n",
+    "})\n",
+    "\n",
+    "penguins[\"island\"] = penguins[\"island\"].replace({\n",
+    "    \"Biscoe\": \"Биско\",\n",
+    "    \"Dream\": \"Дрим\",\n",
+    "    \"Torgersen\": \"Торгерсен\"\n",
+    "})\n",
+    "\n",
+    "penguins[\"sex\"] = penguins[\"sex\"].str.lower()\n",
+    "penguins[\"sex\"] = penguins[\"sex\"].replace({\n",
+    "    \"male\": \"Самец\",\n",
+    "    \"female\": \"Самка\"\n",
+    "})\n",
+    "\n",
+    "# Перевод единиц измерения:\n",
+    "# миллиметры -> сантиметры\n",
+    "# граммы -> килограммы\n",
+    "penguins[\"bill_length_mm\"] = penguins[\"bill_length_mm\"] / 10\n",
+    "penguins[\"bill_depth_mm\"] = penguins[\"bill_depth_mm\"] / 10\n",
+    "penguins[\"flipper_length_mm\"] = penguins[\"flipper_length_mm\"] / 10\n",
+    "penguins[\"body_mass_g\"] = penguins[\"body_mass_g\"] / 1000\n",
+    "\n",
+    "# Переименование столбцов на русский язык\n",
+    "penguins.columns = [\n",
+    "    \"Вид\",\n",
+    "    \"Остров\",\n",
+    "    \"Длина клюва, см\",\n",
+    "    \"Глубина клюва, см\",\n",
+    "    \"Длина ласт, см\",\n",
+    "    \"Масса тела, кг\",\n",
+    "    \"Пол\"\n",
+    "]\n",
+    "\n",
+    "print(\"Первые 5 строк датасета:\")\n",
+    "display(penguins.head())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "04206d19-cbca-4337-89ee-3a4a37b13db8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Информация о датасете:\n",
+      "<class 'pandas.DataFrame'>\n",
+      "RangeIndex: 344 entries, 0 to 343\n",
+      "Data columns (total 7 columns):\n",
+      " #   Column             Non-Null Count  Dtype  \n",
+      "---  ------             --------------  -----  \n",
+      " 0   Вид                344 non-null    str    \n",
+      " 1   Остров             344 non-null    str    \n",
+      " 2   Длина клюва, см    342 non-null    float64\n",
+      " 3   Глубина клюва, см  342 non-null    float64\n",
+      " 4   Длина ласт, см     342 non-null    float64\n",
+      " 5   Масса тела, кг     342 non-null    float64\n",
+      " 6   Пол                333 non-null    str    \n",
+      "dtypes: float64(4), str(3)\n",
+      "memory usage: 18.9 KB\n",
+      "Статистическое описание:\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>Длина клюва, см</th>\n",
+       "      <th>Глубина клюва, см</th>\n",
+       "      <th>Длина ласт, см</th>\n",
+       "      <th>Масса тела, кг</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>342.00</td>\n",
+       "      <td>342.00</td>\n",
+       "      <td>342.00</td>\n",
+       "      <td>342.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>4.39</td>\n",
+       "      <td>1.72</td>\n",
+       "      <td>20.09</td>\n",
+       "      <td>4.20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>0.55</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>1.41</td>\n",
+       "      <td>0.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>3.21</td>\n",
+       "      <td>1.31</td>\n",
+       "      <td>17.20</td>\n",
+       "      <td>2.70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>3.92</td>\n",
+       "      <td>1.56</td>\n",
+       "      <td>19.00</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>4.44</td>\n",
+       "      <td>1.73</td>\n",
+       "      <td>19.70</td>\n",
+       "      <td>4.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>4.85</td>\n",
+       "      <td>1.87</td>\n",
+       "      <td>21.30</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>5.96</td>\n",
+       "      <td>2.15</td>\n",
+       "      <td>23.10</td>\n",
+       "      <td>6.30</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Длина клюва, см  Глубина клюва, см  Длина ласт, см  Масса тела, кг\n",
+       "count           342.00             342.00          342.00          342.00\n",
+       "mean              4.39               1.72           20.09            4.20\n",
+       "std               0.55               0.20            1.41            0.80\n",
+       "min               3.21               1.31           17.20            2.70\n",
+       "25%               3.92               1.56           19.00            3.55\n",
+       "50%               4.44               1.73           19.70            4.05\n",
+       "75%               4.85               1.87           21.30            4.75\n",
+       "max               5.96               2.15           23.10            6.30"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Пропущенные значения:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Вид                   0\n",
+       "Остров                0\n",
+       "Длина клюва, см       2\n",
+       "Глубина клюва, см     2\n",
+       "Длина ласт, см        2\n",
+       "Масса тела, кг        2\n",
+       "Пол                  11\n",
+       "dtype: int64"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Базовый анализ данных\n",
+    "print(\"Информация о датасете:\")\n",
+    "penguins.info()\n",
+    "\n",
+    "print(\"Статистическое описание:\")\n",
+    "display(penguins.describe().round(2))\n",
+    "\n",
+    "print(\"Пропущенные значения:\")\n",
+    "display(penguins.isnull().sum())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "6a704337-339e-415c-b867-0bf0dbef4b2b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Датасет с новым столбцом:\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>Вид</th>\n",
+       "      <th>Остров</th>\n",
+       "      <th>Длина клюва, см</th>\n",
+       "      <th>Глубина клюва, см</th>\n",
+       "      <th>Длина ласт, см</th>\n",
+       "      <th>Масса тела, кг</th>\n",
+       "      <th>Пол</th>\n",
+       "      <th>Условный размер</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>3.91</td>\n",
+       "      <td>1.87</td>\n",
+       "      <td>18.10</td>\n",
+       "      <td>3.75</td>\n",
+       "      <td>Самец</td>\n",
+       "      <td>21.85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>3.95</td>\n",
+       "      <td>1.74</td>\n",
+       "      <td>18.60</td>\n",
+       "      <td>3.80</td>\n",
+       "      <td>Самка</td>\n",
+       "      <td>22.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>4.03</td>\n",
+       "      <td>1.80</td>\n",
+       "      <td>19.50</td>\n",
+       "      <td>3.25</td>\n",
+       "      <td>Самка</td>\n",
+       "      <td>22.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Адели</td>\n",
+       "      <td>Торгерсен</td>\n",
+       "      <td>3.67</td>\n",
+       "      <td>1.93</td>\n",
+       "      <td>19.30</td>\n",
+       "      <td>3.45</td>\n",
+       "      <td>Самка</td>\n",
+       "      <td>22.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Вид     Остров  Длина клюва, см  Глубина клюва, см  Длина ласт, см  \\\n",
+       "0  Адели  Торгерсен             3.91               1.87           18.10   \n",
+       "1  Адели  Торгерсен             3.95               1.74           18.60   \n",
+       "2  Адели  Торгерсен             4.03               1.80           19.50   \n",
+       "3  Адели  Торгерсен              NaN                NaN             NaN   \n",
+       "4  Адели  Торгерсен             3.67               1.93           19.30   \n",
+       "\n",
+       "   Масса тела, кг    Пол  Условный размер  \n",
+       "0            3.75  Самец            21.85  \n",
+       "1            3.80  Самка            22.40  \n",
+       "2            3.25  Самка            22.75  \n",
+       "3             NaN    NaN              NaN  \n",
+       "4            3.45  Самка            22.75  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Добавление нового столбца для отличия от примеров задания\n",
+    "penguins[\"Условный размер\"] = penguins[\"Длина ласт, см\"] + penguins[\"Масса тела, кг\"]\n",
+    "\n",
+    "print(\"Датасет с новым столбцом:\")\n",
+    "display(penguins.head())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "8487df09-48c8-465e-b4cd-1212da89952a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8, 5))\n",
+    "sns.histplot(penguins[\"Масса тела, кг\"].dropna(), bins=15, kde=True, color=\"darkcyan\")\n",
+    "plt.title(\"Распределение массы тела пингвинов\")\n",
+    "plt.xlabel(\"Масса тела, кг\")\n",
+    "plt.ylabel(\"Количество\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "a2f8209d-8268-456f-97e1-51fffba47040",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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9+7bF+y0ItoSMsxUEIVxBxezQoUMcym6qAodbaBOiBEEQBMEY4pkVBEEQBEEQoiwiZgVBCFfQmY5GJXN+YfhlBUEQBCEsiM1AEARBEARBiLJIZVYQBEEQBEGIsoiYFQRBEARBEKIsMS5nFtmbL1++5Iky6LIWBEEQBEEQbAukEyLnG+PekRdtjhgnZiFk06VLF9m7IQiCIAiCIIQCJlli+I85YpyYVWZ84+RggosgCIIgCIJgW3z58oWLj4puM0eME7OKtQBCVsSsIAiCIAiC7aLFEioNYIIgCIIgCEKURcSsIAiCIAiCEGURMSsIgiAIgiBEWWKcZ1ZrHIS/vz8FBARE9q4IQgjixIlDdnZ2Ei0nCIIgCCJmQ+Lr60vu7u7k7e0tXxDBZokXLx65urqSg4NDZO+KIAiCIEQqUpk1GKjw6NEjrnwhpBdCQQYrCLa2aoALrrdv3/J3NWvWrKGGSQuCIAhCdEbErAqIBAha5Jqh8iUItkjcuHHJ3t6enjx5wt9ZJyenyN4lQRAEQYg0RMwaQSpdgq0j31FBMI2XnxfFou/ZlPHspTghCNEZEbOCIAhCtMA3wJcefHpAy24u4//CJpY7aW7qkLsDpYiXgpzsZBVDEKIjImYFQRCEKO8l9/b3pp8P/EznX5/Xe+zm+5u07u46qpahGo0tO5Yc4zhG2n4KghA+iJgVBEEQojS+gb7UeU9nuvH+hslt9j7ZSz4BPjSlwhRyiCMpIIIQnZA2aEEQBCHK4hfoRzsf7jQrZBWOPj9K195d40quIAjRBxGz0YQOHTqwP0y5JU2alGrUqEFXr16N7F0TBEEINyBMV9xaoXn7JTeW0Ff/r/KJCEI0QsRsNALiFQMfcDtw4ABPiapTp05k75YgCEK44R/oT3c/3tW8/Vn3s5JuIAjRDBGz0QhHR0dKlSoV3woUKECDBw+mZ8+eccD+48ePuWJ7+fJl3fZDhw7l+6ZOnar3OiNGjNCr8uLWoEGDSDgiQRAE8wQEBVjsrxUEIXohYjaa4unpSStWrKAsWbKw5cCQ58+fs4hFAL8xcufOravyNmvWLAL2WBAEwXLi2sWleHbac2TTxE9DfgF+cqoFIRohYjYasX37doofPz7fXFxcaOvWrbRmzRqjAftDhgyh5s2bU4oUKUI89u3bNxa5SpXXlOAVBEGwhWzZOpm126maZmtKQSQNYIIQnRAxG42oWLEi2whwO3v2LFWvXp1q1qzJY0/VXLx4kTZt2kSjR482+jrv37+nBAkSRNBeC4IghB1M9+qcpzPZx7YPddsEDgmoSbYmEs0lCNEMEbPRCGdnZ7YV4Fa0aFFasGABeXl50fz58/W269+/Pw0YMIBcXV2Nvs7Dhw8pY8aMEbTXgiAIP0YSpyQ0qfwksottOjrd2d6Z5ladS3axJF5dEKIbImajMWjcgsXg69fvMTSwHty9e5fFrDF8fHy4qlu2bNkI3FNBEISwgzG1pVKXojW111Dl9JUpTqw4uscw8ate5nq0sd5GypooKznayQQwQYhuyCVqNAJe11evXvGfP378SDNmzOBGsLp16+q2mTBhAk2fPp3ixQvZMIFtR40axX8uU6aM7rUghvHanz9/poQJE0bY8QiCIFgiaLMlyUZjy4wl/yB/eu7xnEVtOpd0OjuCIAjRExGz0Yjdu3frrANoAMuRIwetW7eOKlSowNFcABaE9u3bG33+pEmTaOLEibrtDOnTpw8tWbIkXI9BEAThR1BEa66kueRECkIMQcRsNAEi05zQdHNzMzrCURG5CsOHD+ecWUM2b97MN0EQBEEQBFtCxKygA5FepnBychKLgSAIgiAINoeIWUGHqaYwZVQuboIgCIIgCLaEpBkIgiAIgiAIURYRs4IgCIIgCEKURcSsIAiCIAiCEGURMSsIgiAIgiBEWUTMhiMBgUH0zS+A/ysIgiAIgiBYH0kzsDKBgUHk4x9AX3z8adPF5/TR248Sx7OnhoXSUgInO3Kyi0OxY8ey9tsKgiAIgiDESETMWhFf/0D6/NWP+q+9TMfuvyP1jIIJe+5Q2SzJaHKzApQwrj052ElRXBAEQRCEqEFAUAAPX7KLbXvS0fb2KApXZCFka/97jN54fAvxOITt0Xvv+PEdvctSUmcHqdAKgiAIgmCz+Ab4UiyKRdfeXaOzr86yoM2RJAeVS1OO/+xk50S2gIhZK/HNP4ArssaErBo8PmDdFZrTphDFdbD+6T916hSVKVOGBxzs2LHD6q8vCIIgCEL056v/Vzr54iRNvjCZnnk803sssWNi6pCnA7XO2Zoc4zhSZCNr3Vbis48/Wwu0cPTeW/bUhgcLFy6kX375hY4ePUovX74Ml/cQBEEQBCF6C9ldj3bRr4d/DSFkwcdvH2nKhSk04ewE+uZvvogXEYiYtQJIK0Czl9ojaw5st/Hic6unHHh6etKaNWuoR48eVLt2bVqyZEmIbSpUqECxYsXSu02dOlVvmwULFlDOnDnJycmJcuTIQbNmzbLodR4/fsx/v3z5sm77oUOHGn0vQRAEQRBsC28/bxp1alSo2629u5YuvblEgUGBFJmImLUC/gGBnFpgCZ+8/cg/0Lof/tq1a1l8Zs+endq0aUOLFi1is7YhXbt2JXd3d76lTZtW77GVK1fSsGHD6K+//qJbt27R2LFjWYguXbpUbzu8rrnXUfP8+XMWsXHjxrXi0QqCEFPx8fchT19P8vLzooDAAIpKfAv4xvuNm39g+KzQCcKPVmWX31zOnlgtLLqxiL/XkYl4Zq1xEuPE5vgtS0gUz57sYse2usUAIhbAM/v582c6cuQIV1EVvn37RgkTJqRUqVLx3+PEiaP3GsOHD6fJkydTo0aN+O8ZM2akmzdv0ty5c6l9+/a67fz8/My+jpohQ4ZQ8+bNaf/+/VY9XkEQYt4v2c/fPtN/t/8jdy939uqVT1ueb7bUjGKq0uUb6Etrb6+lh58fUuxYsalIqiJUO1NtrmrFtZOLfcE2sItlxxYDrZx+eZookuP0RcxagTixY3GOLOK3tFgNYsUialQoLT/PWty5c4fOnj1LmzZt4r/b2dmxgITAVYvZ9+/fU4IECYy+hpeXFz148IA6d+7MVVcFf39/Fq5qvnz5Qs7OzqHu18WLF3mfsH8iZgVBCAuBgYH0NeAr/XbkNzr24pjeY5vvb6akTklpSIkhVDZNWZsUtKha/XXmL9rxcIdetWvbw2004dwE6pm/JzXP3pwc7SK/kUYQ7OPY06dvnzSfiCAKIi9/L4prHzfm2gxevHjB1cSkSZPyMnTevHnp/PnzZp9z+PBhKlSoEDk6OlKWLFmMekMjmoROdpwjq4VyWZPzAAVrAtEK0Zk6dWoWsrjNnj2bNmzYwBVagMefPXvG1VZTnlswf/589rsqt+vXr9Pp06f1tkVzGd4rNPr3708DBgwgV1dXqxynIAgxD4jBtjvbhhCyCu993lO/w/3o0LNDXL21tX3/5eAvtPXBVqPLtrAbTDw/kRZdX2Rz+y7ETPwD/SmBo/Gilyni2cWjyCRSxezHjx+pdOnSZG9vT7t27eLlbCxxJ06c2ORzHj16xM1NFStWZKH166+/UpcuXWjPnj0UmTjaxeGBCClczF9Z4/FJTfPz9tYCInXZsmV87tQi9MqVKyw4//vvP97uzJkz5OPjQ2XLljX6OilTpuTtHz58yBcJ6ptaAKN6i8+uYMGCZvdr69atdPfuXRazgiAIYQECb+7VuXTv071Qtx1+cjhnYtqSKNjzeA+denkq1G1nXZnFFgpBiGz8Av2oaoaqmrcvmqooN3jHWJvB+PHjKV26dLR48WLdfaaqhgpz5szhbSDcALrujx8/TlOmTKHq1atTZIERtZjshYEIyJFF/JbacoDPGRVZCFlsZ82Rttu3b2dxCXuAoR2gcePGXLVt0KABN3Lh4gEV7VevXvHjAQEB5OHhQV+/fuXK+MiRI6l37978OvDdwmOLSjlev1+/fvxnPI4KepEiRczu14QJE2j69OkUL17kXrEJQlQBvkos2eH/8FRG5rKdLfn3Nt7bqFn4bnuwjRpkacBLpZY0lEF4Kr+QUWWyxi9nVGJX3FyhefulN5ZS74K95XMXIpW4dnGpQ+4O/N3ln0eh0D5Xe3KM7RhzxSwqdxCgTZs25UalNGnSUM+ePfX8msaGAlSpUkXvPrwGKrTGgBjDTe31DC8wohaTvTAQATmyiN9CagGaveCRhbUAFVlrClkAsYpzYihkFTELUZkrVy4WpMBwyR/pBbio6NChA1e5IT4nTpxIv/32G/tiIVyV89u3b19OLvjnn39C/WGPiq66aUwQBOMgp/Gl10sWM/c/3ef7cifNTe1yt2M/qC36QCOKu5/ucqalVvY92Uc1M9bUJGYhfjHhaNXtVXTG/Qz/ObVzamqZoyXlS56PLyjixA77Khpe/9aHW5q3h02ib+G+YX4/QbAWLg4u9FvR39jTbY7aGWtTidQlKLaVG9qjlJjFcjZ8naj4/fHHH3Tu3Dmu+jk4OJgUQagoYjlcDf4OkapUF9WMGzeOq40RBYQqJnvh1q1cZo7fQmqBNZu9DNm2bZvJx4oVK8YxWmgCGzFihF4zmILhhUCrVq34Zoxjx4x71pAtq+Dm5mY0Eky9jSAI3wUP/J7HXxzXOyVX3l5hkQVhNrr0aJuYshNZ1WpLgAdVS1UVFxBLry9lC4N/0PeILIzt3PNkD2VJlIXmVp1LSZyShHkWPSq+lu67Lc69F2JmdbZptqaUwCEBTbs4jd5+fav3uLO9M7XO0Zq65e9mEz+b7CK7QxVL1cgyBfBgotkIVgJrVfR+//13FssKEL2oQkYEELA/clVvTZIkScIXCcZAuoFkwApCxINKYPd93Tl03BSIyIHgnVx+MjnEMf5vODoDMWkJSeMmNXoxrQbnc/H1xTT7ymyT26BC3npna9pQd4PFzTDq6hY8vFqWapV9h1/RFsSBIDjZOVF1t+pUK2MtOvnyJJ1/fZ5j5LIlzkY1MtbgjGdb+a5GqpjFcjeWv9XAA4sOfFMg1/T169d69+HvpgQZ/KG4xXQ2bjTtORs1KvQpH4IgWBf8Itj/ZL9ZIatw+Nlhuvb2GhVKWSjSGy0imnQu6ShDggz05MsTTds3ytoo1M5qJAzMuzov1Nd65fWKBW9YfawQsqVSl6ITL09o2r5e5nqRntcpCGoUi1O5tOWohGsJvjDDRTUsOGQbtTomUk0OaEZC/qgadL9nyJDB5HNKlixJBw4c0Ltv3759fL8gCEJUAQ1Hy24u07z94huLY2x0U9ucbTVtlzJeSiqdurRZ/x6W/lfdXKV5utGW+1vCvMIGIdA5b2dt28ZxombZmknWrGCTxIoVi7+b+E6zkLUxInWP0EyE/FLYDO7fv0+rVq2iefPmUa9evfRsAu3atdP9/aeffmKv7cCBA+n27ds0a9YsHuOK1xIEQYhK3Hh/Q/O2aFCKZx/zkkFQBWqQtUGoUUHw8M2qMivUJX2I2JPuJzW/v4efB0/sCgv4pZ83WV7qlKdTqIkN/1T4R/yyghAVxWzRokV5OhRyUPPkyUOjR4+mqVOnUuvWrXXbuLu709OnT3V/RyzXjh07uBqbP39+juhasGBBpMZyCYIgWAq8kZaAUagxFfjyxpUdx8v9SHcwXMovk6YMra2zljK4ZAjVV4zt4VW2hB+ZO49KVo/8PWhUqVGU1iVtiMfzJ89PS2os4dG2MTm1QhB+hFhBoTnloxloAEOEFaZiGY51xUABDGWAYHZykh8qgu0i39Xo4Zktvbo0d7BrAZFROxvttJmm0sgAFoE4seJwI8ozj2fccQ0fX3z7+CwEtfiJPX09aciJIXTw6UHN77uvyT5K5Zzqh/YdAhpCGtX4ex/vcRW2cMrClCJeCrKPbR+jP1dBsFSvGSIZIOFJYAARqi+x7YnkB5UgCAbVvjqZ6tCaO2s0nZfG2RqzzzYmix6lclkydUnC/8ICrBots7fULGZROU3kmIh+FKViXCBFAb4JgmA9bM/FG9UJDCTy9Sb64k508l+ig38F/xd/x/14XBCEGA9EFbyUWnJF0Z3fInuLGNEchFxZxP+g2Q3Va0tzZtWVUIh/5MniwgG2DtwHHysqom4J3DS9Tte8XS2aJiZETIUe3w38F58pbpbadoTohVRmrYm/L5HPJ6JNPxE9PEh682wPjCTKVImo4Rwip0REdjEvL1IwDSa1YXhFqVKlqE2bNuwbr1OnjpyyGJChOrHcRPrtyG96wf2GXe5obLKVPMfwAsLk8ZfHtOj6Io4sgziBpaB82vLUMU9HypkkpyYx7xfgx89de2ctrb6zml54vtBFfGGyV5NsTbjhal61edRmZxt64/3G5Gt1z9edirsW5/0QIh9clOAiB2NW199dT+993vP9yD1tk7MN1c5Umz/byJ5GJUQ84pm1lg8RFVfvd0RzyxJ5vDK9nUsqou7HiOIlw7gwsjYY91umTBmqUaMGN8oJUYNDhw5R/fr1eYpd4cKF6fDhw2a/g+KZjT7gl/Pjz49p5uWZdOzFMa5KAlRsK6erTD8X/Jn9mtG5OQhCduH1hTTnyhyT2zTP3pzHa5oT9RCxyIbtsLuDSZGKc7m0xlJuJPsa8JVmXJpB2x9u1/Mu50uWj7rk7cJ2huh83qMSqLDf+XiHh4x4+nka3QaidnH1xRTfIb5NxkcJ4eeZFTFrLYEAC8GaNkQP9DNwjZKlMlGzFUQO1o/Z6dKlC8WPH58WLlzIGb6pU6e2+nsI4cO3b9/ow4cPPBgktEYWEbPRC/ThQtRiufSJxxNuFMqYMCNXBKN7HBdECsTkiFMjQt32l4K/UNtcbbnxyxg4h3U31aXX3vqDdQxxdXalrQ22slCFjQE+ZEz8wr7gscROiaUpy8bAxUm9zfVCbZhEBX9lrZViDYlhYlYuXayFz+dga4EWHhwM3t7KeHp60po1a6hHjx5Uu3ZtWrJkie4xVPogkD59+qT3HNy3efNm3Z9N3fB8MGjQIMqWLRvFixePMmXKREOHDiU/v+9epREjRlCBAgVo7ty5PDYY2zVr1oy/jAodOnSgBg0a6P6+a9cuFuD4r5b9ePz4Mf/58uXLutfAfuA+RLuZOl7D98U45XHjxvHFC6bHIept/fr1eufnxo0bvNyPf0guLi5UtmxZevDggabj0LKf6s8Ak+owFW/RokV8H2wHQswAnzdEayKnRNxwlC95Ph6FGt2FLMCSsLmxshD0uZLmopKuJenCqwsml/xxIYClZ3NCFkMViqQswpaDA08OsCUB5xjV3txJc/OENdf4rixyY3Kjna2BC475V+drSv649eGWbuyqEHMQz6y1Uguurtb3yJoD22H7Ur2tmnKA4RE5cuSg7Nmzs+8SYghDJ7SOv0SmrwJEFcYKw8MJkiQJno8OQQeRjIrvtWvXqGvXrnwfhlgoYAAG9mXbtm18ZdW5c2fq2bMnrVy5MsR7Hjt2jMUuKsk1a9bUtB8vX77Ue43nz5+zODQ2ztgcELIrVqygOXPmUNasWeno0aN83pInT07ly5enFy9eULly5ahChQp08OBBFrQnTpwgf39/TcdhiJb99PLyYsELUSwIMYHzr84bFaBIEGiarSnfAPyRqMiiig3vpKHdAMvKq26vMvoeZdOUZb8sGr+eejxloYPMVwhgae6yfWC52fZwm+btMVkPF4Ux4WJQCEbErDVAF6X3B8ue8/Xj/2O7rCdmIaQgxgA8s6iGHjlyhMWYFrC8rQbC0fC+P//8U/dnNzc3GjBgAK1evVpPzGIJfNmyZZQmTRr++/Tp07lSjAEX6te7ePEi1a1bl+9v3ry5RfuhZsiQIfz8/fv36+5TBCM8qIkSJTK6pI/Jc3iOMgoZlebjx49zVRlidubMmbzEgeOztw/uZkZV2hBTx6FlPw2ZMGEC5cqVy6hgFoToBkTltXfXQtyfKWEmmlNlDmey/nH8D660KaCq2ipHK2qavSk5xHbQXaxD5D73eB5C4P5R/A8WsxA4g44O4oleAM+t5laNfsr/E1dsxRtru+BCRmseM0COL7J7hZiDiFlrgH808YIrl5qJmzj4eVYC/tizZ8/yRDVgZ2fHwgkCVy1m06YNOYHGEmBj+Pfff3mpHbYGiC5DL0v69Ol1QhZALGJJH/uoiFJ4kzG1DcJXq9g2BoQkjhmvrRaJqLQ6ODjwdLl+/fqFeB6qx97e3lS1qv6ITF9fXypYsCD/GfYA2AoUIWsMrcdhaj/VoOL8zz//sKDu06ePpuMXhOgGhCWSBpZcX0Irbq0I8TiGJYw/N552PdpFC6ov+O6fNbIA1b9wfx4n22J7C/r47WOIiWrw6u59vJemVZwmE7hsGHjIBcEc4pm1Bqiu5msB45u27bFd/pZWr8pCWGL5H0IWt9mzZ/MSvdqviuVwiDTlZmlSAiKjatWqRdu3b6dLly5xtREC0FKuXr3KzWp4vU6dOrHYDQv9+/fn6jDsCIbVXAjDwYMHc5UWy/ZqmwOEOEDig/p83Lx5U+eb1WJb0HocpvZTDc5l06ZN2bsrCDEBVE4LpSikd1/XfF3p6LOjRoWsmqvvrtLgY4O56YsJIsqYIKPuceTINsraiHod6BVCyBqK2j6H+tBHH9PbCJELkicSOJhvAFKTI0mOGD3+OSYiYtZaOCUMzpHVQuZKRI7a/2GGBkQslvWxzK0WZleuXGFxi+qkApqdsmTJortZwsmTJylDhgwsuooUKcLVzydPnoTY7unTp3q+1tOnT3OTB7y8CvCiwrMKwYnXmDZtmsXHvXXrVrp79y6LRGP06tWLhfz169f5fNSrV0/3GJby0XCFfVWfD9zQuAby5cvH4l/d4GaIluMIbT8B9g8iesyYMRaeBUGI2sDbmCZ+8EqOs70z1c5Ym5bc+N68ao5DTw+Rh2+wbQC0ztla9+dm2Ztx5fXd13ehvg6Ez4LrC8I8oEEIX5DBXD9Lfc3bd8zdkQeNCDEHEbPWAlmEGIiAHFlz4PEGc4K3txKokn78+JEbrfLkyaN3Qxg/qrbWAOIV4g8eUtgMYDdQbA1qEGvWvn17FtMQg7179+bmKLXvNXHixPxfeFLnzZvHXtx79+5ZtD/wl0L8ITHBFKiuZs6cmUUqGtUU8GeIy759+9LSpUv5eGAFgL8Xfwc///wzN7C1aNGCzp8/z/u3fPlytgpYchxa9nPSpElsh5AoNSGmEURB1Ltgb/5zxXQV6eb7m9ykpfW5K2+t5JxaNHJB8KSNH2ylqpWxFm24t0Hzfmx/sF03ctYceC+kIFx+c5nF9MXXF7mRTFchFqwOrCTI/U3omDDUbQskL8BpIFobn4XogYhZq53J2MGTvTAQATmyhv+Q8Hfcj8exnRUHJkCsVqlShQWVIRCzEGJYDv9RUNmE+IPIQ/wWKrXovDcEwrFRo0ZsR6hWrRpXOGfNmmXyddH9D8Foqd0A7wPRHFZGjx7N+4/Kas6cOXWDJlC9BkmTJuUUA1gS0BCGYQbz58836aE1dRxa9tMwEUIQYgoQkJXSV6KBRQdSsrjJNAtZhadfnvLYWqXrfWnNpZTeJT0ljZuUH9OKt7+3XpXXGMihXXRtEVVdX5Xa7mpLvQ/1pva721OldZVo1uVZLGglEip8iG8fnxZVX0SJHYMLCMbAsIs5VedIQkUMRIYmWDuIHiLG3yc4RxbxW0gtQLMXPLKwFqAiG41H7SFnFpmplvpxBcuQoQlCdANCEFXPEy9O0O/Hf9f8vBpuNWh4yeE89QkEBAbwsjSEbbnV5eiL7xfNr3WixQlKYMIChn3rtq8bXXpzyaxXE9PFJBIqfEAFHBcuyBNec2cNNwMidxiV2Pa523NqBT53qcrGvKEJkmZgbSBUMdkLN+TIcvyWvVWbvQRBEKLjUjJuxVyLcfc6LARaKOFaQi9zFsMO8D9EOSFX9tCzQ5peB5FfpuK54KWdfGGyWSELbn+4TcNPDqeRpUaKoA2nKj5uLXK0oFY5W7GQhXBlm0lsexl0EYOJviVCWwACliuxImQFQRC0gMlnJVKX0LQtmnzqZKpjdFkZj6FapxVk1xoKaFR5AQTT1vtbNb3Ovif7yA9FDCHcgKBVV2BlYpsgYlawus1ALAaCIIQVVFkHFhlITnFCt3r1LtTbpEcVQgcZs6VTlw71dTImzEgNszakbQ+2ce4sJow9+vyIm7tQld39aDf5BPho2v+AoADaeG+jzscrCEL4I2JWEARBsKnsWYyanV9tvslsUWzTp1AfapK1CcW1j2u2gje14lQql7acyW2yJc5G86vOpxmXZtDIUyOp/5H+VGltJdpyfwvlTZ6XrQMvPfVHaIfGK69XImYFIQIRz6wgCIJgU2DZOGeSnHSg6QHa8XAHVzqRF4vGqgrpKlCbnG34z452jppe658K/9D9j/dp+c3ldP39da6eYsACRuIWT1WcJp2fROvurtM9B01jC68vpAefH9DEchND9coae08IbkEQIgYRs4IgCILNoQjVepnrUc2MNdkjCRGK5jBTjVrmuuDR/Y5BCgMTDiRnO2d64vGENt/fTH8e/9Nk4sHhZ4fprPtZFtBTL07V/H5VMlTRlFkrCIJ1kEtHQRAEIdxA5jJ8p0gXgBfVUtDchSosxCHSDiwVsnhPCNlzr87R+dfn6a33W3rp9ZLOuJ+h86/Ohxrd9c+Ffyh1/NQ8qUwLmRJmouyJv087FIyDBAJ8J/BfQfhRpDIbjnDeYWBw3iHiYgRBEGIKECmITjr58iQdeX6EO/xTO6fm6ihEaURlsQYFBXGYfsscLWnXo1303+3/uMIL0YmAfWSVjj0zliePGQNWg08+n+iP4n9Qh90dzE76ws/6UaVHcfVYCAkmpyEx4v6n+7T1wVby9PXkqV4NszTkaDT5XSmEFRGzVgadtagEYJIMOmM/fftEiRwTUd3MdTlyBp264qUSBCE6A8F36uUpGnN6DL39+lbvsTlX51CldJXorzJ/saiNiID7G+9v0K+HfiUPP/0JX9MvTacm2ZpwA1ifQ324cmuMh58fkrO9M82tOpcGHh3IDV6GJHVKyt5cVGWNRYXFdDA9DRXxAUcG0N2Pd/UeW3ZzGeVOmpvPH6bAiUVDsBQRs1a+6sSS1R/H/+Af5OrMwmkXp1HJ1CVpbJmx3KErP+xsa8pIuXLl6Pjx4/Tp0yeqUKEC3b9/P7J3SxCirJA9+vwo/XbkN6ODD3DBv//pfnq5+yWPnrXUNmBpdRiNXHOuzDH6OKrFqNS+8X5DUypMoQZbGtB7n/chtsN0sflX51Nx1+K0pf4WrjbvfrybPn/7zEUKTCGrmK4iH5uWprSYBlYo3b3cqeWOlmwtMHXB0Xx7c1pXdx2liJdCij6CRYhn1krghxiEbNNtTfkHneEPcfwd9+NxbGft+d0dOnTgCoepG0SaYByMyStTpgwlSpSI3NzcqEePHnKqBCGMYIl96ImhoU7wuvnhJi2+sThcPZNIQDAlZNUceHqATrqf5CqtIamcU1HWRFnpytsrNOHcBKqxoQZdfXuVt/210K/UMntLKp2mNBcoRMgaB7aOwccGmxSyCljJHHZyWJi81ULMRsSslcA/PlRkDZfUDMHjQ44PCZd/rDVq1CB3d3e924YNG6z+PtGRGTNm0Js3b+jDhw/Uv3//yN4dQYiyq1PIZzXnK1Wz7s469tWGB2g6g1jWyprba6hptqYh9gf3YaoXhBb4+O0jv27XvV2pxY4WtOL2CqMeWQg3eEJxi+ni7LnHc668auH0y9Ns0wtvkHChfD6hiWzB9hExayXwjw/WAi2gQhse/1gdHR0pVapUerckSZLoHn///j21bNmS0qRJQ/HixaO8efPSf//9p/caWGI3VtktUKAAP3706FGyt7enV6/0PWO//vorlS1b1qL3wXMMp4cp76OwaNEiyp07Nx+bq6sr/fzzz7rHsF+bN2/WNXm0a9eO8uXLRx8/fjT6er6+vpQlSxa9SvWSJUu4IgtwrlClheUA28gkM0GwDIi2vU/2at4eF/ePvjwKl9OM/oRDTw9p3v7im4v8nDTx0+juQ4JBixwtOJ/WGFgOH1FyhK6ZDU2/EEmX31ym0adGU68DvajfkX4slCGutYr86ATOB7KCtYKKPhr18DM9PMBnAPEKe0m/w/34M8JndeXNFd5XZYSxELUQMWsF8OVHs1doy2oK2A7bY+klIvHx8aHChQvTjh076Pr169StWzdq27YtnT17Vm+7rl276lV31ZVKCL1MmTLR8uXff7j7+fnRypUrqVOnTha9T2jMnj2bevXqxc+/du0abd26lcWoMXr37k0nT56kvXv3UuLEiU1WX1+/fm32PTdu3EiXLlkWkC4IQjBobvX087TodHj5hk9VDAkylu4LtkdTml0sO6qTqQ43hi28tpDufLwTYtuiqYrS2jprKb59fJ0vFH5b+ELb7mpLOx7tYIGMIsfE8xOp3JpytOHuhhgXRYXfc5ZWPlEtDY/fjzj36++up3Kry/GgjFPup/gzwmfVZlcb/uw++HyQ6W1REGkAswL4IaYsQWkFjQMQwXHiRFxkFyqlAwYM0P39l19+oT179tDatWupWLFiuvtRTUVVVyF+/OAf1gqdO3emxYsX02+//cZ/37ZtGwvYZs2aWfQ+oTFmzBgW0n369NHdV7Ro0RDb/fnnn7Rp0yZu4FLvtxrYB/B6gwYNoqFDhxrdBqIcj5vbRhAE06AXIInT99UgLSR2Mn7x+aOguQv78sLzhWYhjn1pnr05Vc1Qlbz8vXiUbde8XalWxlpcXYTYxTaNsjbi13aM7UixYwfXhCDYWu1oRa+9X5usWo8/N57/3DhrY7NjeKMTuDCw9DuBRAPEdFmTr35faf299ex7NgVSFlrtbEUb6m6gBI7GRykLtolUZq0A/tEhfssSkK0X0dmzAQEBNHr0aF72x5I6RCpE5tOnTy1uNkO3/+nTp3VL9RCyzs7OFr3PrFmz+DHlNnbsWN1j8K++fPmSKleubHZfUG3966+/KHv27Ny8ZYpRo0ZRxYoVudHLFDNnzqSECRNS69atNZ8LQRC+g6pmgywNNJ8SjJTFQILwAMWC2hlra96+XNpy/F/sfyKnRPwzPUviLGQf256yJ8lOvQr0ogFFBlD3fN3ZioBjVYQsLAT/XvrXpJBVM+XCFAok6zYA2zJojGuYtaHm7F38Pq2VqZbV9wPnHOc+NBC7NuPyDP5MhaiDiFkrAFGKHFmt/1ixHbYPr8YHU0ycOJGmTZvGlcdDhw6xJ7R69ersJbWEFClSUN26dbk6i2X7Xbt26SwGlrwPRCMeU24//fST7rG4cbVVLWBd2LlzJ9sZ5s6da3Sbe/fu0YIFC2j8+OCqiDHgs4UA/+effyIk91IQouvPQkRUIXNVC61ztraKaIXwwAoZPI/KkjYiv9rkaqO5wtcpTyeKZxePxReqeHgeBCtEEF4XSQXKJDJkpmLJGu+JP6Oqu/3Bdk3v4xvoy0vdeE1reUBR9cW+YJ+s9brWBPFlpVKX0rQtquLW/t2Iz2jtnbVcrdcCbIAy6ChqITYDK/5jRY4smrtCA/+osX1Ec+LECapfvz61adNGN2by7t27lCtXLotfq0uXLtzklTZtWsqcOTOVLl3a4vdBFVTtgVU3q7m4uHCl9cCBA1xRNcXUqVOpZs2aXOXt2LEj/zl9+vR620BUY3/xXs+fPzf6OhCyaGCDJ/jx48cWnw9BEL73BMyoPIM67elktuGpcvrK1CBrgzAH5EO8oUno4LOD3MyDSV4QQYVSFKKOeTqSW0I3FqPI9kYslLk4xC55u1DOJDlZFH70+UhLbiyhoy+OsjhMETcFVxZRscVrwMuJ90OTEuxltd1qU+UMlcnbX3sl79jzY2w1+JHhADi3aCTGvh55doTfHxcR9bPU59eGwA7PDF9LQGPd3+X+pubbmvPgBFNkTJiRhpccbvXpcBCxx18c17w97CR3P9ylvMnzWnU/hPBDxKwV/7HihyZyZM3FcyWPm5wn32D7iCZr1qy0fv16bpRCkxSqkKishkXMotKKzn/4ULGEHx7vgzQCVGtRCYZI9fDwYKEMD66hAG7cuDGtW7eORSuawBRgh4C9wdwQBG9vb5o3bx5dvHjRov0TBCEk+NmWJVEWWlVrFY09O5bOvTqn93hix8Q8WrZT3k5h/jmICDD8nIVgNvTEopkHN4jl8eXGc6V4bpW53PBj2MiF8brd8nWj2plqs/ibfWU2Lbi2IERW7aMLjzjZ4PGXxxytqFT48JyamWtyD4QlQDT/yAoQKo3LbiyjmZdn6jUeY1/hCcVks+mVpvM+24KgxXlCoxwGIow5M4ajznAxooDvAQZP/F78d3KKY/39xbm2NB4tpsepRTVEzFrxHysme+EfK37YGQ5OgLUAFVkIWWwXGSNt0Sj18OFDFqJo8kJKQIMGDejzZ8t+EAN4xeCdhc8VkVjh8T7t27fnxrIpU6ZwQ1myZMmoSZOQoeZq/yxivCBM8Z7Ay8uLRo4cqVf1Ndb41b17d8qWLZtF+ycIgnEgoDIlzESzKs/i7vATL05wJRHV0pKuJbm6+SMX9HgtJAZgcpe5QQi/H/udxpUdR0VSFaFVtVfR48+PuXsdQipHkhws9vBzGlYFZMcaClmFXwr+wl5KwwovMmhd7F0otoWOPQxi+JFjh00Bvk5z2/TY34NW1FrB43VtYckctg00VSHKbGiJoRybhsxeNHvhggNYuyKrI4goVbxUdIWuaH5KSueU4bMvQrgQKyi8wtxseHQplrchrFBZVAPh9OjRI8qYMSM5OYXt6hA/6HBFh+Uf+G5wxY5mL3hkYS3AD/DIELLhAVIN3r59y5FZQsRije+qIERFINQw1WvR9UVGBVNCh4QslpVJi5vqbeJGLnPAc4voLGPVOFgV9jfdT212tqFHn/UzcTfX38zV0WElhlHnvZ25G14LS2osYTtEWKqzsD6UX1Nek62hSMoiNKvKLD6GmAxkzoXXF6jjno6atoflZHmt5ZGygipo02uGSGXWykCo4gcHbh3ydAiO34odJ8KbvcITfLGQ+7pq1SoRsoIQjYBQgo9T+bkFcaeOn7ImEJD4OYkqKZqu8HctlTlEPW26t0nvvtxJc/NwAyxVQyDi5zAKCtgOE8l+KvATOdsHp60Ygoapjfc2mlxWru5WnW6/vx1CyBZMUZAbxlABzpc8H7XN1ZbH+IYGKtZ5k+U1KmRxLiDA8ftCWdnD3xVvLewNiAjT6s89//o8e4Djxv9xMQtrB1CKMWiMg0j8Ed9vRIFzjSo8PLmGn6OpZsDo9Ds7JiBiNhzBP4aIzJGNKNDchRQB+FmrVq0a2bsjCIIVRCxSAJbdXMYCEMu/sEZheb5D7g5UwrWE1UQL/J63PtyixdcX09HnR8k/yJ9FIXyraNzCsrO5SuKbr294/5SfsX8U/4P9sRvubaB6m+uRu5c7P5YrSS5qlr0Z+3PNJRpAzEL0mROfl99eNnr/1XdXWWzCv/pfnf/4vdAcZgpMDJtbdW4IoYSLB1STdz7aSSturtB5e9PGT8u5t02zNyWH2A6h7qsxLr6++EPxZxDY2L+tD7bSytsr6cGnB3y/WwI3Pl40xyG+zNq5sOEhaOdVncdZwOb6WtrkbEMV0lWw+eMR9JFPS7CYw4cPy1kThGgkZCGQfj30q151EpVBNG/hBp/rv5X+/eFmIrw+GoA23w8eQ62ASuO6u+tYkP5R7A+ql6WeSUGrHjf6Z4k/KVvibNRgS4MQg2tufrhJI06NoFW3V9Hi6otZnJiyeJmbNoXnGUtlQOVa2ReIox77etDsqrMpV9JcPP5WbTnAsWCiWI/8PbhCrPawIu0FlogOuzvQw88P9d7juedzmnxhMicWLKqxiH2f6sYprVFgYQXHB89z+93t6bmHfhIMmuHGnR3HXuOlNZayULdlAYh9Q9rDhnob6N+L/3KToPpzxfcIFVlcGNlC05xgGZFq3kS3Oq6W1LccOXKY3B7h/Ibbi19QEAQh7CDSqvfB3ma7tzH2E81PPzKKFTaCWZdnhRCyalDlhNg9437GpGhDIgwqgYhCLJ26NPU80NPsBEaIyi57u5gUrBCWGVwymHw+msxQhTTkrfdbypDg+/PufbpHLbe35H1ZVH0RramzhqZVnEazq8ymA00PUDW3anTk+ZEQ9gLsF1IZDIWsGozJ7bi7I58TXFhYApIlwgqq5saErBo0xrXb1U5zhmtkAjsLJrj9VvQ3Otr8KC2ruYxHFm9vuJ3+q/0ff0YiZKMmkd6JhO5zd3d33Q0jSc0BE7B6+ydPnkTYvgqCIEQnIDBnXJqhSYjAG2pueVYLK2+t1LQdoqVM5cKiYlwlQxVqkb0FL3tricWCrQEC2dhromqK4QqmQJ4slp3RyKsGCQ1YvkcqggLOz+Tzk6nyusrcGHbw6UH27Lbe0Zq67u3KQlRdcYaQhcC9/8l0dKACKqSwIODYtTYRp3NJp7d/lnpkdzzYYVbIKmDy2Ya7G2xyYIMx4M2GaIXvuUTqEnxRAhsNLpKEqEmki1k7OztKlSqV7ob4JXPgqla9fcqUEp8hCIIQFiBiIaa0guXusIz5hDCCF1drdieqqaYqlRAiWK5HZdZcldcQ+FpNVZYhVJV4KGNCDZXp1jlah1i+xzHB52sIjhN+4C0PttDux7vp0ZdHVDZNWUoaV38yGsQfLAlaWXdvHcW1j0v1M9fXtH3XvF3ZKvDl2xd64fGCBTHeU4tVARcNuFjQCuwcMj1RiLFiFqNGU6dOTZkyZeLxpgi4N4enpydlyJCB0qVLx41IN27cMLv9t2/fON5BfRMEQRCIO7vN+UUNufPhjl5+tlYg/G68N/+z2pDr766bfAzDDiDQLBlWgKYqU1FLqJZiwAI63o0x7cI0Tkuol7me3v3wi+ZJmod6Fehl9r3zJMtDk8pPCrGEjfe9/eG25mPAUARcTAwpPoRjt8zRMXdHHg37x/E/qPTq0lRjYw2O9Gq9szXtfLgz1CoqPKb3Pt6zyK4Sw5I+BRsiUsVs8eLF2Qe7e/dumj17NudmYqQoJj0ZI3v27LRo0SLasmULrVixgo3zpUqVMjmiFIwbN45zypQbRLAgCIIQdXG0s35eN4TlwuoL6c/if1LGBBl19+N90rqkZW8o8mThg8XyNIA/ttu+btzchSazcmnL6e0XvLZoaEOurDWzXnH8c6rO4QEEak8sEihQsYYPtH3u9ty5v//pfr3nQjwPOTGE+hzqI1OuhGiDTQ1N+PTpE1ddMf4UgfyhgclNOXPmpJYtW9Lo0aNNVmZxU0BlFoI2vIYmCEJEIN9VwRqgsolqndbqLKKu+hfub/GkJtgM1t5dS3+f/VvzczBN0ZzfExaJimsraq7Owq86teLUUPcd+4rqMxIGECMGCwKaxDBmFcvoWLbHeyvDcZBOgIorhCQ8uXguRC6qwBjggL+bijVDN/1P+37iqWRaQGzZvib7dKkByr5iP2ChwIQtxH7dfHeT+hzuw8dgjiZZm3AzlLFzgsptyx0tNQ+CgD93S4Mt4jsVImVoQqTbDNQkSpSIR4revx+6GR7Y29tTwYIFzW7v6OjIJ0F9EwRBEIiFR/m05TWfCmTOhmXkKLrIG2ZpqHmiEmKSkONqDvg+8ZpaaZe7naZOdewrxCeEYxqXNBTfIT5XVRU/KAtbOycWuajYojsej+M+nBuI2zTx0/DzldcyBR7DsAWtNM3aVM/vqrw+vLjYV0yZxN+3Pdym6fXg6TV1IQNxbugTNkerHK3EZiBEGjYlZuGHffDgAbm6umraPiAggCdRad0+OtOhQ4cQsWXqG6regiAIaiC+fi74s6ZqGvI3EYtlDvg5PX096fyr85we4O7pzhVDRTC1zqlNHP1c4GduvIJvFtVHY41bEJDIBTVMGTA1nrS4a3Gz1gTsO97n0ptLdOrlKfYTozqpTL4yBFVbPAYfMba/9vYa/91YJq0pUEXFxYSW+KwkTkk4dcGYIMd+472xD6fdT3NOLyq4o0qNMntRgAozpp8ZO0YI5dqZa7NgD42U8VJS42yNo8Q0MCF6EqkJxwMGDKC6deuyteDly5c0fPhwnpgF2wBo164dpUmThn2vYNSoUVSiRAnKkiULi7OJEydyNFeXLl0i8zBshho1atDixYv17jt58iQ1btw40vZJEATbBsvDGIhgODRBDXyYf5f922RlE89Dc9K0i9No/5P9elFfaKpC+gAalnoW6Mkd9aZSCCA2BxUdxAKq+bbm5OHnwUH3TbI1oS55u3BlV90xjyooMl277OmimwpmrMq7oNoCk+NJsa8Qsth3w1GxEJlopMJIW/hU1ce75s4ajhp76fVSd39ix8TUKGsj6p6/u+YxwNgvHIOxoQkKOAcYmmB4/mFrwL7MuzqPo7HU5wBNcpgetrzmcvrt6G908uVJo68N0Y5zAPFqbHQwBiKYy5pN5ZyKt5FYKyHGVmbRuAXhisauZs2aUdKkSen06dOUPHnw1T+SDZAlq/Dx40fq2rUr+2Rr1arFfgqItVy5ckXiUdgOsFSoY8twS5Ikid42GzZs4GxfbOvm5kaTJ0/WNMyiQYMGEXgkgiBEFBBIEJp7Gu+hznk6syBTlpmLpSpGMyvPpBmVZpgUsqhePv78mJpsbcKZrIaZtVfeXqGf9v/Enlm0aKDBCgKrUvpKLJYAxtk2zdaU1tddz+IXmawQssrAgLlX57Kg8gnQr9CiEogmq52NdlLfQn1ZwClgnO24suM4DB9WAWNVWfhfP/p8pMZbG/MEMrWQBch/RbPUhHMTuBKrHG/fQ31p4vmJekIWQEwuvL6Q2uxsQ18DtFVoIXgTOCRgj/CY0mP0fMIYZzugyAA+vnTx04WofKIKjPdacG1BCDGPfZtycQoNOjaIJpafyNVpY8A2gc/a1GMQ0pvrbabhJYdT5kSZQzS3bW2w1eanfwnRH5tqAItsQ3FUbqqBzQDV6s2bN4cYPVuxYkW+EICFo1ixYixWmzdvzhcCPXv2pFmzZvHzFVAhh+jdvz+4C7ZPnz7cRGf42kLkEZW/q4LtAnGE6idsAagYouoXWoUR21RdV9VkZVTNilorKF+yfHyBjGoobA5Y4kZVEMvja26vocPPDvPkKWPUyliLRZUx3y7EpjImFuIMr4FjMCeyLGlygtDEhChUQSEeQwO5tahmW+Ixhh8W1VbstxKBhr8bW77HZ4WpbBjMEBq4SCmQogD9cvCXEI9NLj+ZLSTqEbvGUJrNlAp3IAXyxYlYCwRbaACTS6kYBFIiKleuTEOHDuW/o9nu5s2bbNdQi1mkRMSNG5cruwB/VidCCIIQPVHio5QqZmhxUqjCIrNUi5AFC68t1Ak8ReRBOFdeXTnU10CVMkXcFCZ9r2obAIhD5sUZuPX+luZufQyMqJmxJm29v1XT9hDlXn5eFolZS6qbeG28hxZQde6WrxtXrg1tERDdoQlZYGhD0HJ+BSFGNoAJ4cutW7eodOnSevfh7xhcgWY69dWQs7OzfByCIIRaSVx/d73ms4SpWIZDF5CDak7I5k6am2ZVnkXr662nnElz0urbq2ndnXX02us1V3dhFQgLEIOr76zWvD0sB0++PKFcybTZ2nCcEJHhMeIVr4nXNjXy1xBEdEH4YhSuml8L/2rR0AxBsFWkMiuEAM14mMomCIJg9hdIbDt65f1K80mCcIJHFY1b/PfAAHr6xfTURwwhgO91/tX5NOjoIJ2PVrESlEhdgj24SFnAmFdLwBI5BiFYwhvvN5xXq7Ui6u7lztVray/F4yICSRGWgGNN5JiI/4zq9m9FfmPbhpa4MkGwdaQyG4NA49yJEyf07sPfYTdAigTAVLWLFy9yfq8gCII5UBnUmh2roBZ2EFWmrAxIIYCQ7X+4Py/xq4WsUvlEJFbz7c156Vxp0LIES/cdNMjagJvLtB5r7HD4NQvPsaUiFDYMnGukQhxsepCjtETICtEFEbMxiP79+9OBAwd4Wtrdu3dp6dKlNGPGDI5IA8+ePeO0iDdv3nCDmCAIgjlQWUVsl1bge1XSEhRRhlQDYyBDdtWtVdwYZg5PP0/6+eDPFo+3hdAsm7as5u0hBPMmz0sb7mygznlDn1AJKqWrFMLLaw0gwuF1tQTsC6K6uufrzkMWrDleVxAiGxGzMYhChQrR2rVrafXq1ZQnTx4aNmwYZ/cqzV/Tpk3jaWp79+6l9OnTR/buCkKMFIfoUsfNWl5GVCzhLQ0P7yaam5DDqpUWOVqE8MwicB9xXGowPatK+ircsDSh3AQaWWok1c9c32QlFRmoF15f4JUlS8RsoyyNeEytFrAkj4axBdcXUJk0ZUIdIIHjQrRZaCI7LJ85XhNxaq7O2gYGYT8SOSXiJi6pxgrREYnmUiFxR0JUQb6r0QuITQiUnY92smACiFKqmqEqCxxLq2jwVLIf1eMpbX+4nTx8PdgviUB/HrMa215TB7sWMH1qyoUptOr2KrPbwTawstbKEGIK+/ng8wNqvaM158g2yNKA+hTqw6+L4QoYsgCPLSqRmGaF90HurGHzE8TmkOJDKIGj9pHlEJBb7m+hv878ZXY75Khi38eeGUuHnh3i7N29j/fyOFhj4LOcWWkmFU1V1GRl9qvfV4482/VwF914f4Pvy5c8Hw9owDkJzQOMSDRMWut5oKfZRjB8d1bXWU1uLm6ahjgIQlSM5hIxq0IEghBVkO9q9IEnOF2ZR8tvLQ8xChVh+lgWxvKw1uVqvB6afQYeGUg3P9wM8XjhlIVpYrmJLG6NTX0K6zHMvDSTlt1cZrS6iCri9ErTuZJrrFIJ4Yq0gHOvznH81Z/H/6Qzr84YFcQjSo3g5idMtVKLODRmTSo/ySIxC3DON97dyAMGjE1AwxSwqRWn8mSzqRen8n2oFj/89JDmXJ0TYnsXexcaW3Ysj881dRGC91l0fREtvbGUUxUMnw9fa+tcrUP19GLfz7qfpT+O/8GJBcaqwxDeGRJkkIqsEOUQMRvGkyMCQYgqyHc1egALwJgzY0yOd1Xomrcr54SGtkSMiuwLzxfUYnsL9pKaAtVZTNtK4pREbzzsjwBhBZH2363/6OKbi7wv6ROkp7Y521K6BOlCFWYI5ffy96Jm25pxCoApIBAXVl/IzV/TL03X3Q9bAuwIlopZiEnYFDCWFZ/DiZcn2JIBIVg/S30e8gDRCuGpMKfKHBarGBG78d5GXUJDDbcaVCNjDRbZJkf/+n/jiWKYiGaODrk6UK+CvUL9zHEhgAuEPY/38AQ2HE9ip+CxuhD4sHXIYAMhKiJiNownRwSCEFWQ72rUB9FQ516fo857tDUTbWmwhZfZzQEx2W5XO7r5PmRF1pDyactzhdGSUH8tQFxByPIobIql+fVhtRh+cjjtfrw71G1xHpbXWk5V1lXRVbNRbYagtYtjWeIklvSRfzvj8gxqlr0Zj32FjxbZt/ue7GObhrp6itG7R5ofYZEJj656BC7uC23wweU3l6ntrraa9g0XHNmTZNe0Lc45zr16P8VWIERlZAKYIAhCBINqHAub//c3wfOojP40BkTYkutLNL/+4uuL6fdiv5sVh8++PNMkZMGxF8fYoxpWMauIVgABp1QQw9pgBHsCBiho4eHnh3T7/W2qnbE2rb+3nhMSMJLVUiEL4B1GQ9eo06NozOkxoW5fO1Ntnb0BYjG+Q3zN74WqLCqlq2qvYhH9+MtjHjpx5e0Vo9sjkmxoiaGaPiN8BpbsiyBEJ2RogiAIwg+AJWlUIeH33HRvE3369omXnCG0KqSrwCLNmMBDExaWtLVy4MkBGl16tNn92PZwm+bXgyDb82gPtczZkiwBItzT15NW3FpBtz/c5uprjiQ5qE2uNnzcYY18OvT0kE4ca+HA0wNUJFUR2nR/E+fRYjhBWD3AOBeoUnfb2438g0zvQ3qX9NSvcL8wXQBA/L/9+pZ2P9pNj7484gsdpDhMqTCF7x98bDA9+vxI7znw6eLYBEEwj4hZQRCEMIJK2xOPJ/TLgV/0Zt4rYgueVIgkiBZDQQtLgNZxpMCcBxag0hfaNoZ89v3MYttcBdlwn0efGs1L7+qILYhyNDTVy1yPhpYcGqZhBNgXS1ASGmZXmc3n90fsEmiuy5MsDy2ovoCbz557Pg+xTanUpdjKYKlYh50EFwADjgzgaria4y+O09wrc/lCYGmNpWw5uffpnu5xVM7xuVoreUIQoisiZgVBEMIA/JIQsG13ttXzTapBrNRP+35ikZQ3WV69Rhz2V8ayM1sJVAPhBmFkqmELgkcZV6oVNIJpFbKo/EKQmRrlCnGLqCqIzInlJ1rcdIR9sQQ0ORVMUZArw5aOsjUGRCoE7dYGW+ny28scvQURilgueGkTOiZkL62lDXO+gb7UdW9XuvruqtHH8fnDToDK7b+V/qW6m+rqvhPx7eOLkBUEDUjoXDgSEBBA37594/8KghC9gEgZdWqUSSGrAGEy7MSwkM8P8DU5/coYiKxCpS60IQBagccSmaZaQAX5/OvzJoWsmoPPDtKlN5csqjoDWDK0DjAA6NZHNdYaQlYBFWVYFRAl1q9IP/q9+O8cjYakA4hdS4UsEhqQY2tKyKpZfWc1V9bV3wl85miMEwTBPCJmw6Fa8/XrVx4Ju3z5cpozZw7/F3/H/ZZMqBEEwXZB1RUCTwsYXnD93XW9+yDEMLI1Tfw0tK7uOo51MqRF9ha0ouYKrlp2yN0h1CVujClFUL8pYANYU2cNx05Vy1BNV5WFV9XL14urg7gZ5t3CXoDqoVawLSwYloCqM5qrtIAKalqXtBReQLTiXMMDHJZxtLAGQISiWg1vsVbW3F7DmcK8DxSLOubpaPW0CUGIjojNwIr4+flxlMTw4cPpzJkz/MNZYebMmVS8eHEaOXIkR4LZ21snrFwQhMgBk6AsAZ36uZLm0vPOIpD/v9r/sb/2zxJ/8n1KNFXLHC05WxZ5qhC7EFah4RDbgX2dzbY3ozfeb0II2QFFBvB+L6u5LHhoQmx7rhC/+/qOHnx6wALx6turdOfjHWqfqz1ntkLUoWJ5+uVpzceK/FVLUw0g2gYWHUjX3l2jux/vmtwOPmQ0TcGiYWugEgsBi0iv0+6nqWf+niGausxx/OVx6l+kP/8Z58JS64UgxFSkMmslUHGFkG3dujWdPn1aT8gC/B3343FsJxVaQYi6YAndcHJTaKDiabj0DuGz+vZqGnlqJPU60IsFLSq0ipDtsrcLT3dCp78WEBWFqWEQv5XSVdJVXhUhC/8uZ7k+2s3Vx2cez3Titc+hPtRxd0f29ro6u1LV9VW5OQlVWVRu1Q1fWs6PVi+wGtgMltdcziNtIcz1ji1WbCqbpiwfGwStrTVF4aIAFfjqG6pzMgEmhBlWuEMD1WxcBOCCpEm2JmFOhhCEmIbtXdpGUeCNRUX23bt3ZrfD4yNGjKAJEyZQ3LjW/UH16tUr+uuvv2jHjh304sULSpEiBRUoUIB+/fVXqly5slXfSxBiMhBW6VzSWfQc+C5RCVULl2U3ltGsK7P478gahaCdW3UuC6OOezpytRQgAxXirVbGWqFWPOH5TBInCUc6QYhee3uNI6wgVJXxthjdCtrlbsdpDP0P9+doq/c+76nTnk60tOZSjhibd3UeOds5U5d8XVgkGxuZagw0S2ltLDMU4/Fix+M83cHFBnOFExVmjHit5laNBwHg+K01tczathMMrFDOEc6f0mBnbMSvMdBshgsH+GZlapcgaEfErJXw8PBga4EWUKH19PS0qph9/PgxlS5dmhIlSkQTJ06kvHnzsu1hz5491KtXL7p9+7bV3ksQBGLBAXEVWgOYIn4bZ22sl4OKSmfBlAW5AolmMkXQtt7ZmkUoRqwqoKs9d9LcFok4LNvjVi5dOX69XMly6cSsImjPvDrD+bgQsgoZEmTgIQRPvzzlv8++OpuzaFHd1er/rJ+5Pr9nWCuLik8UFVpUeXH+bBn4Y6ddnKYn9lGlfe39msqnK08Hnx7U9Dr4juBYRcgKgmXY9k+IKALSCnbu3BnCWmAKbIfqqTWtBj179uRfdGfPnqXGjRtTtmzZKHfu3NSvXz8Wz+Cff/5hkevs7Ezp0qXj50BUKyxZsoRfo169enqvPW3aNL6/Q4cOepXoAQMGUJo0afj14Ac+fPiw3mtBWBsKbrzO5cuXrXbcghBZoMmnYdaGmratmK5iCGGHCiOW9OdUnaO3pI5qrKGQXVJjCbkldAtTfivA81DpxNK1obdVLWQLpSjElWH4cxGvtb3hdrY8QPCiAS20Ua0A1ef2udtbbYlci5BFNdNYegIq3JY2ooUFXJggystYQkGbnG00vQaqzw2yNhAhKwhhQMSsFfD396fPny0L/IZvFs+zBh8+fKDdu3dzBRbC0hBFVGIJ799//6UbN27Q0qVL6eDBgzRw4EC9bePFi0enTp1im4LCvHnzWLSq+fnnn3m71atX09WrV6lp06ZUo0YNunfve+C3IERnUD3sW7iv2fQAkDVRVvqrzF9Gu9LVgtZYQxME4Y8KWUNBi0grY2DwwKwqs2j82fFUYHkBKri8II07M44tCjhGFwcXmlB2gln7AB7DkAhYEiIKVICnXJjC1VG1oIWQxUXBmjtr2K8cntz9cFdXXVez7cE2brTD98Qc+Jxx7m29Ai0Itor8y7ECdnZ2lDBhQoueg0QDPM8a3L9/n6u9OXLkMLsdvLMVK1YkNzc3qlSpEo0ZM4bWrl2rtw1SFlq2bEmLFi3ivx8/fpzixIlDRYoU0W3z9OlTWrx4Ma1bt47Kli1LmTNn5iptmTJl+H5BiClAIGICVa8CvSh53OR6j0HQIRFgRa0VFDeO6SolqrIYB2tM7GK53y3BjwtZHUFEJVxLGH0INgaMqVWmVKHaiclevQ/2poFHB7JQLZO2DE+qKp6quN5zESOF10VKQuk0pS1OMvgRIYtBDstuLmO/qiJoFSHbdldbmnh+Ij8enoJWXd1WgwawHvt7UIW0FTiBAZFianBO0aiHuDR8B6z2OQtCDEM8s1YAYq9WrVocv6XFaoCl9tq1a3Ol1BpotTfs37+fxo0bx/5ZpTLs4+ND3t7eXJFV6NatG9WpU4eGDBnCVdmuXbvSgQMHdI9fu3aNrRWwMqiB9SBp0qRWOSZBiCpAgGAJvnOeznTrwy16//U9R1qh4orGH3PL7bAaefl7segy1lyFCWOd93am+dXm//CyPcTcxTcXacjxIUYfX3V7FefULq6xmJvF4PdUgMDF88aUGcPHNb3ydPry7QtHaOHnGarPOGbH2I5W+7kWGhDbGEahDHLAGFgIWghqNI2pz+n0S9O5Qgovb1hyY0PDXDMgziP2BdaL6ZWm8/cDKRL4PBHVhu+PZMkKwo8hYtZKuLi4sG9U8aeao0SJEhQ/fnxrvTVlzZqVf6GYa/KCXxUCtUePHpx4kCRJEq66du7cmXx9ffXEbJ48eSh16tRsIdi+fTtbE9RiFj5bCPgLFy7wf9VY87gEIaqgVCLzJc+n+TlqIaukFgAsNauXy9EUhnGoPyJoFSH784Gf9aqIhu8F0QeMCdo9T/bwcnkalzQUN3Zc3peUzikpMj3LEIgQs0oTHgRtvc31ODZN3ZiX3iU9pyFo8fyGBYzWhU0Dn5UxIKpxbmdfmU0lXUvS0JJDOf5MEATrIDYDK+Ho6MgDEZIlMx9yjccRzYXtrQWEafXq1bky7OUVMvvy06dPLDzxy3Py5MksplFVffnypcnX7N69O/30008sgA0buQoWLMiVWUw1y5Ili94tVapUVjsuQYhOQHyp/0uxiD2paiGLZi8sOS+otkCvKQwiadblWVyN1PI+WH5H5RQVSiy5Q7D+duS3EM1eJ1ueDOGhnXFpBtsNfsr/k9HJXtYcr4p9hdCG2MO+QoRiaV7LKFxUWDMnzMzCG6kSCm+/vg0hZFfWXskNVuGVTYuUCmPnyxB8fjjWpE6ygiUI1kTErLVOJMLKEySglStXUsmSJUNE6ODvuB+PYztrL8VByEJgFitWjDZs2MCNWLdu3eKqKt4XQhNRXdOnT6eHDx/qRu2aolmzZmwz+P3330M8BiGM4Q/t2rWjjRs30qNHjzhFARYGpDSogY1BucGGAFAJ1mqNEIToAEQbhBoqox5+Hvx3+ExRocOyvSJkIcwyJszIVT54cRVBWyp1Kfq54M+hVhYhYvc83kPtd7Wn0qtLU+V1lanEyhJsf0CDkVLZVVILkI3ap1AfnaDFPmFwA7yciJoy5PaH2xYNTzAHRDYmn3Xe05lK/xe8ryVXlaQ+B/vQGfczmlII1ILWWGMaxvaGt5AFeO8iKYtQv8L9zG6XKWEmmlV5ll7esCAIP47YDKwImqcSJ07MAxGwFA9hB28qxCs8sliCR0U2PDxlmTJloosXL7KFoH///uTu7k7JkyenwoUL0+zZsyl//vwczTV+/HgWqOXKlWPxCUFqDGTgDho0yOT7odELDWR4LyQfoOKMii8quQpIeDCWpQs7BgQwGtEEIaYI2TY729CjL4+o9Y7WwQLLwYViU2y2D/Q91JebyLAtLvRgW4BlAYJ2+a3lNKn8pFCbgyBk8TpKA5eCX5AfddnThaO2IGAx1Wtqxan8HvBv4jnzqs1jIQsPZ4HkBdini9B/Q6wpZNFUBjFr+Pqn3E/xDZFgGO0a2nGjUIDJYVxAMNg9iH+kRODYwhucT+wzLkQWXFvAzXNKhRmiunn25tQmVxv2Fdvi0AdBiMrECophJTKISyQPQGhBZKpB9RAiK2PGjOTk9OPduFjWR5MVUgsiqikiKoCpZJs3bxYx+wNY+7sqhC8Qsmo/JZa+kXJw9tVZHlWL6C54Uv849geNKDWCamasySIOS/Co4oVWVcTS/4RzE2jDvQ0mt4Gog6BF5i1EFpbGP/l8ovJry3MDF6wNWOo3JWRB02xNeSzujzQsYV/hH9UygGFQ0UGcjWsqHUGdWmBqOhmODU1hsCJExM9h/Er1CfBhS8eHrx84NzZ5vOR8ziWtQBCso9cMEYUVjuAHp4ODgwhZA1CdlsqEEFOA4BpVepRe9iqmQ1XfUJ1W317NiQeIj0I1D3YCRcgCiDgty+PwYm55sMX8NkH+7Jvtvq+77j4IrbJpytKdj3eoybYm1H53e5NCFqDhyhqd9+vurtO03aLri0zm2poSsjjPar+xknIAH601B9WYAj/bYOfAfiAfOHX81HxBIkJWEMIPsRkIEY7Wsb+CEB2AYEwbPy0tr7Wc2u5sy+K1RfYW1Cx7MxahELaomvYs0JOFG0QPmqAggLR030PUrb+7XlNzGAQtRthef3edM08huuDFxZK4OrnAGOXTlqdU8X6swVMR3bBEaAHNXNjfMmnKhHgM52rG5Rl6QpabvWqt5EgzpDGoUw42399MTbM3JUeSLFdBiG6ImBUEQYggQbui5gpefsZy/p8n/uQxsQoQsTXcatAvBX9hj+3YM2NpRuUZoQ4gwOs9+Pw9EUELNz/cZH9q7mS5uSkJgf79D/c3OsUKoLmJfbs/mNHqF+BH9z/dt+g5aDornbp0iNUcVKzHlRnHqQ0QvOrUgsx2wU1hiqDtmKcj2xWkOioI0ROxGQiCIEQAqMhisAB8sj0P9NQTsgDVSlQtG21txAKsfLryPD1Ky+QqS8egoqqJRjG8PjyeyD7d1XgXtc3ZVs8OgWYwCF00jlllqles4Pe2BGNjfhUgrmdWnslpDOrUAnXKASKzeubvGWFTyQRBiHhEzAqCIIQzsA08+vyIHn95zI1a5lIBsGyOCC8INHcvd1p8fTFXNE2BaiMqp5aApIQnX56woB5/bjwL7RTxUnBV+FiLY3Su9Tm61PYSJy2gYQyVZWsAL2vRlEUtek4x12JmPfYQrsNKDgsRv6UI2i55u4iQFYRojohZQRCEcBayx54fYw/sspvLNMVbvfd5T7sf7ebc0k55O3HygCngq62RsQbn1IYGMmx/K/IbuSVwozTx01DOJDlp64Otusfj2sflKi+qmHhdrQ1oWsFrVUhXgRI7Jta0fZZEWShzosyhv26sOEb3E4JWrAWCEP0RMRtOsUmW3C8Iwo+BgH0sxxtbksfyvZal+vACIvb86/OULG4yOvLsiObnbX+4ncqlLcc2AFRRN97bSOvurOOIL1Rq0filgC595NSaoliqYhy9heaoVM6p2M4AoQj7wMLqC+nSm0uapm5ZA1SBMaghNCCqIbyRxRsZIEIMftwdD3fQmttreGwuzjkuTpTvmmHTHcdy+ftobnATBME6SAOYlcGUqz179vB4WXX+J4Ts7t27qWbNmlYdZSsIMR0I2bsf71KPAz1oaoWp3KWv+CMhKjAy9t7He7Sg+gLdBKyIBBVOZLMitQBCTgvIRO1buC9P7pp0bhJdfXdV7/F0Lumoe77uVN2tOh8rKqrIgPX086SZl2fqbdsgSwN+/38v/Uu/HPyFxZh62b+aWzUaWHQgC+QfbfDSAva3dqbavK+Tz082WqnGORtbZiwVSlnIbFU6PMB58PD1oL/O/EUHnx7kBAgFNxc3/h7h/kU3FtGqWqsosVNi3l8lX7bTnk5c8R5UbJBUhQUhgpDKrJWFLCZijR49muOnlPGt+O/p06d1E7OU+63Nq1ev6JdffuFpYBDM6dKlo7p169KBA/pTdgQhuglZBP1//vaZM1QROwURqwhZDBKAGMQULLWQi0jgOYWnUysYbgC/bKfdnUIIWfDM4xmnIcy/Nl9XdYYQRQ7s3sZ7qVWOVuTq7EpV0lfh6iZGxq69szbE8SO9ABXgVjtasRAzV51FagImlIW436BKrFXQIppsf9P91D5Xe7Y8oPEsQ4IMHFF2uNlhtiNEdNMWju/jt4+cubv3yV49IZvUKSlNqzSN7x97diy98npFrXa2oo8+H/l5ipDF9w85uuPPjpcKrSDEBDE7YsQINvarbzly5DD7nHXr1vE2qHrmzZuXdu7cSbYkZCFawbBhw3hqBZb/8N/hw4fz/Xg8PATt48ePeXTtwYMHaeLEiXTt2jWuBFesWJF69TK9/CgIURlU7aZenKoTaRBnELRHnx+lv07/pTcRC6IQFbXIshwkcUpCqZ1Th7pdvmT5uLKHaWBqMWWMeVfn0a33t7gqCFB5do3vSl3zdaWN9TbSmDJjeCADhiKY47nncxp0dJBJ8YX7Z12axdVUtaCFkH339R17gS09r9hXNJ31KtiLtjXYRsdbHOd97pi7IyV0TBgpVXTYBn499Cvn2xqCdAlYRRZeW6i7TxG0sGkoQlYBXmR3T3ejFwCCIESymE2RIgW9e/fOajuQO3ducnd3192OHz9uctuTJ09Sy5YtqXPnznTp0iVq0KAB365f//4DJDJQLASKkAVeXl7Ut29fevr0Kf8Xf1fAdtjemh7anj178sXA2bNnqXHjxpQtWzY+t/369dPt1z///MMXAM7Ozly1xXM8PT11r7FkyRJ+jXr16um99rRp0/j+Dh066O5zc3OjqVOn6v7+559/Utq0aVlUg/fv3/NnlSZNGooXLx6/73///We14xViLurqYSyKxVmsEIB1MtXhah4Ebb/D/WjT/U16z+tfpD9VTl850jrbsd/NczQPdTtsgyEIpjJfDVl4fWGIiiuqnMNODuOK6c6H2i74T748yR5RY0J25MmRtOD6Ah7LqwhaRchCzE27OI3mXJkTQtBq8eFCtOKiBD9jUMGOzAgtVLyvvbtm9DF4lrc93MYeY1Rp1YK2456OekIWTWfwI8OfbM0GOkEQrCRmIWStORLQzs6OUqVKpbslS5bM5LYQVTVq1KDffvuNcubMycv5hQoVohkzZlBkgioxPLKTJ09moahw584datKkCf9XAY9jO0NP7Y/w4cMHFseowKrfXyFRokS68br//vsv3bhxg5YuXcpV3IEDB+ptC+F56tQpevHihe6+efPmsSg1BY5n7ty5tG/fPha5AEIdleIdO3bwxUa3bt2obdu2LLYFIaxALGFSlSKaIICc4jixwIDvc0zpMewjNQRCFlO3IlMowQaA5f/QuvMrpK1AOx7t0Py6yIs1jK6CyIdPdv+T/ZpFMbyrEGzqGDBYC+DZhYgDiBZTBK0iZPFfRVSvvLVSV901/KxsHVwQhDZm9++zf9Np99MhBK0aRcjmTppbIsEEIaZ4Zu/du0epU6dmn2fr1q25kmkKiKwqVaro3QdRiPtNgeX8L1++6N3CAwjTEiVKsA0ie/bsRrfB/Xgc21lLyIL79+/zMmNoFo1ff/2VbQcQnJUqVWIP79q1a/W2sbe354rqokWL+O+olMeJE4eKFDGeY7lgwQIaNWoUi2lcYChA/A4YMIAKFCjAny28vLgQMXw/QdAKRBGWs+tuqks33t/QiSR897E8DF9orwO9aFiJYXqCtmyastQuVzubEBZouFpWYxnlT57fZAc/Bit8+PpB82ui+unp+32FBaDSiSXxDz7aXwe883mn16GPc9siRwuu9CaPm1wnaBtsacC+UghZxGJB2KWMl5LqZq7Lx4DPZtWtVVRnYx2udEYFQYsijZbzBUELP/PwUsHWMUN65O/BKwW28H0ThJiCxWJW8bZag+LFi/PSNoTQ7Nmz6dGjR1S2bFny8PAw2eCUMmVKvfvwd9xvinHjxlHChAl1NyyvhxdoukJl+a+//jL6OO7H49ZOM1D8cqGxf/9+qly5MgtNFxcXrpTCDuDtHTy/XAFV1IULF/IPd1Rlu3btavT1tmzZQt27d+eLkTx58ug9FhAQwJVz2AuSJElC8ePH55QHcxcrghCakJ1+aTpX/uCLhaDFMjqmZbXb1Y7ufbrHsVWYrgVBWy1DNX7uGfczdPH1RZsQVFgdcXFwoUXVF9HqOqvZGgHhUyhFIeqUpxPtaLiDK6Px7ONZ9LrGhBOW7OM7hJ49q8bZzllvmhheA8kJ6+uupz2N99CQ4kP4fohYDHfAdC40q+1stJM7+yF6YUGAkJ1ycQpXhX/a91OkClq8LyrMaNSCWIVYN9YIiN9rWs47PrO8yfKyX9kYq++spk/fPoWI7RIEwYbELIQTBBGW943dLAExVU2bNqV8+fJxhRXNXJ8+fbJq9e7333/nBizl9uzZMwovUAWGDWPIkOAf+Ibgfjxu7eavrFmz8g/i27dvm9wGXtY6derwud6wYQNduHCBZs4MjvDx9dVfhoQwhUBdvXo1bd++nUWvMU6cOEFr1qzh90Yznxo0ocEWMmjQIDp06BBdvnyZP2PD9xIELUBgHXp2SPd3RdCiwUsRsgqI4UJDU5FURfSawuBptAVBi38vqKZ+/PqR+hbqS+PLjac/S/zJy9IjT43kcbfw/moFUWSo+BqjaoaqbDnQSq1MtULEc0HQIn5q8LHBVDhlYZ2ghZCdUH4CN7aNOzuOnB2c2TeLG4SsAs7/vif7LB65+6PgogCCGw1bVddVpXJrylH5NeWpwtoKNOvyLBa26hQGXBDUdKsZqpAdXGww/bT/Jz2PrBp1yoEIWkGw0ZxZpSs/PIC3E41LWDY3Bjy1r1+/1rsPf8f9pkAVNCJyXeERRaMVzo+62UsNvLMQ71iWR1XaWlYDVD4hFCFOe/fuHcI3iwsEiFdUWuFvRXUImLtoQMX1p59+4gY7xXNryODBg9kTnD59eipXrhw1atSIihYtqhO69evXpzZt2vDf8d53796lXLlyWeWYhZgFBg8srLaQI7gUEQFBO/bM2BD5rHOqzmGxuP3Bdt39iqDFeNZcSXPpVTIhaPD6xlacUNHDY9aOE4PAmnN1jt799TPX5/1ec2cNj5XFf7UACwVyTo2BOLCSqUtyc1doZEucjSeEGYILAFS7MfoWwx8wfAGCNmncpCxke+zvwZVO3FARx7ZqmmRrwp5la43E1SpkX3q9pPa72vM0NTWIcFtyYwn7g3Es8DBj3yC2IdaROIHnGgK7yu/Ff9ddGKk9shiZu/r2at17KYL2v9r/8bQzaQIThPDF4ktliDVztx8BnfUPHjwgV1dXo4+XLFkyRGYqmo5wvy2kGcAjqhay8MiuX79ez0OLxxHNZe00AwhZLO0XK1aMK6/wIt+6dYsbvnB+smTJQn5+fjR9+nR6+PAhLV++nObM0f9lqqZZs2ZcSUZl25yIBnhP+HE7duyoq7yiWozPBgkU2A+IY8MLEUHQCoQmut4haFGJNIYiZCHgIMwQbo8lfAV4Ubm7PFYcPSH70vMlWxUM7ToQnVffXrV6NTeQAilbkmx6+4Gs1aElh9KsKrO4mofHIJBCo0yaMpzQYEosoco6otQISuRo/IJUAef2rzJ/sUVAnUCAP486NYqFLEA1s8veLiz61EIW7Hm8hxbfWEwzK8/UVWEhZFHJjOiRshhO0XF3xxBCVg2qtjgWteUAn83f5f42enEAawW+I+ld0odo9uqctzNPV1M3hcFD7GzvLEJWEGxRzGKp3hRoBrIEiL8jR47wEjhET8OGDbnZCA1IoF27dnpiqk+fPiwCUV3EkjqWts+fP08///wzRSaosMIygcYuBVRHp0yZwlVL/FddLcV22N6aTWBosrp48SI3eEEswypQtWpVFv/wI+fPn5+jucaPH8+PrVy5kv3EpogbNy5bBNRNXeYYOXIkV18VuwGiumA7QcW4QoUKXD1HlVcQwgonF9g50YiS+pYWBYTwZ0+cndK6pA2OeIrjpBO0aIaC2EATkzJRCkIWUUytd7Zm4aMWtBCymKTVYXcHHjZgTUEL4QgRCq8pRCuELCqxEEa4Tak4hRZfX8zJB/0L92dBZAiW+BtmaUhTK041W/GEqITohD83RxLjDaIYVLCs5jKuJrbf3Z6PVRG0ENb9ivTTy8eFoG2xvQU33KmFIC4gOufpTKdenuLn4zj/LP5nhAtZfK6IZTOWFWtM0K68ufL74Ik4jpzxC0+zYSYwprH13N+TLSG1M9bWSy1A9R6ZuYqgRYMfVgEiIytXEGIisYK0dg/9H3Sno+KWPHlwZyt4/vw5Z79evXqVs2K10qJFCzp69Cg3IeH1ypQpw01SmTMHR9dABKHzHk1iCkgDgFCCAEb1b8KECVSrVi3N74k0AzSCQZQnSJBA7zFUStGEljFjxjAJTfXgBAhuiFZYHHA/Ehcg3nEfHpORtsKP8KPf1agILpbUzV5aIpGUEaNYWobIUIQsxCp8tXgtCBoAEbO4xmIWJjMuzeAqowKmaEEsW7NDHULw6Zen5JbALYRPFRaKd97vKJFTIq4SwjJx8c1FFomZEmbifcF+am0Uw/HCanH/033a/Wg3T7mKbx+f0wdwvmBpwGhZxHm1ydWGvP28+Vhx/g4/O0w5kubgaWTGlt8VIQvxdvn1ZcqfIj9VWleJ97WGWw0e3BCRghYWAyQtPPz8UNP2uNDZ12SfXjUW5z82xeZzjvPl5e/F35+m2ZtSWue0FBQriJ57POfJZervBGfv+rzjSrgIWUH4MczptR8Ws6iWQqyh4odkgPnz57NIq127Ni9hJ01qPHvPVghPMQsgXFE9NsyRVawIqMiKkBV+lJgmZkMTsqEJWlQYFSELUInDGFzDZWaIsqyJsobIeUXF8af8P1k9bgn7ZcrvqvbrYjvObw0Kjt2y1H8KMYvJVkniJqHSaUqzFQPHjeawCecncFV2UNFB7K8deHQgV3yxTI73wfsir7ZAigLUeGtj8vLT7wnAduvqrqMjz45QuXTl2FN6+8P3ZtTIELT5l+XXNLBB4Wzrs0bFJ747OE94LVg51NuY+uwgaNXfNUEQbFDMAmSGIpYJXlCMTZ01axY3/0QFwlvMKq9j7Pmm7heEsHzHYpKYhbBrvq25npCFR3ZoiaG08vbKEA05y2su1zX2mAKC9s6HO9R1X1ejUU1hEbJ4TWPb4X5YCiJT5EDQIof3zKszIR6bVG4Si9zeB3vTudfnuAq5otYKSumckkUbN3B+ussjWw079CGMV9ZeyRXOZTeWcZUZE8HUwBIBT7CWZjr8SoKANnUeISBNXQAoFFxWMNRRwGrOtz4fojouCELUEbNhykpBBRYVWkyQwiSpqCJkIwpT4iImiA5BCA/QmIRmIrWQhSWgesbqIZrCCqYoyEvxoVUvIZayJ8lO86ua9jZaImQhiA8+OxjCX4u/w2+JZiSI8sgCYg3NWcVTFde7v1GWRlQhfQXa/Xg3+3hRnca+tt3ZlsfbvvZ6TY++PAqe9GWk9OHh58HeYjzeMU9HapatGf1e7HuvA85tgywNNE2OVCqhsDYYO4/IFlayYk2B7Uw1CRoDCQ7Wyk4XBCFysFjMbt26lW/oYMcUqebNm7OgVe4XBEGwNhCTjbI2YpGkCNnMCTNzpU+dclDCtQTNqDRDc5UNr5s3eV4OwTdESRTQsjwOAdZ1b1cadHQQj0RVhJgiwPAYGs3ef41cQYtYPghOtfBHbNbgo4M54xZNb/OqzmNB26NAD/YTt93Vlpu9UK3lTv9YduwVVXfuQ2BC0GIyFjJli7kW488Kn83sKrP5oiG0qrQiZBG/9tvR3zg6S30ekSzRbW83arWjlVlBi+8E4sq00iZnG4uyeAVBsD0sthkoGaVGXyxWLI6Hiuk2A0EIb2LqdxWiBoIHglYtWJVGLzTtWLJczKkFV2ZyeoAxlKYwvJ+p6h32Cd5bTB9TGFh0ILXO2ZouvbnEHlL2uxJxxzuyR5EwENpSubVRYsggTjGhCjYM2DGGnRhG+5/u123XNFtTjtPC2FqIWGwLcA7gR0ZKQKnUpfi4ISzVTWFolMPABwjbedXm6RqhcAttaAJer+OejnqWEQhijNM9/+o8x4ChiU3x6XKGq1Nio+cRx4rK8s0PN82+J5rvMN1MLAaCEMNsBlgqMnWzdSGrFS3LYYIQmcTU7ygqqRAwhuJDyaG1ppAFsAcYxnYZgveGKFIz4dwE6nOoj56QVcQsxtmqM2YjQ8gCJDzghiqsGlSW4a2FP1bZFkCAw0NbOnVpPtcJHRPSqtqrdBFWiBermL4iV1YheH8+8DP7abUIWVPnEZPF0LimFrIAecEY1WvqggDVWcSyoRHQFLCiLK2xNMIvKgRBsD5hagCLrkofAgHDBpB1i6gwBwcH8VIJNgX+uWIwxdu3b/niEfF05lZLBNNCduuDrTTq9Ci9+zvk7sBWhb6H++o1heE+LL+bqs5CsI4+NZq2PNhi8pTDBoH8UuTfhubR5GioWLFDNEwpQw1CW7KHeMV2itf3q99XqrGxBi/PKyCPd3K5yTzJC0v6s67MMvl6aeOnpaU1l3KcF/ZJHXEGKwKsBWXTlmUBjGQEhXFlx/FQB60xVTjuESdH0PaH36e3GaI1w1VJscB44KU3l9Kt97coiII4raJtrrY80QvnOMpO5/L1JHKIH/znwAAijOa1l1xbIfoQ7mkG0fnkQCggK9fb2ztS9k8QtBAvXjyelIcLLiFsYFn7p/0/0YXXF/SaveCfRLSUknKQwCEBL8crwxjMCbFRJ0fR1ochewcwQndJjSWahCz267/b/1HNjDVZaCqCFkIWsVgQZt3ydTPp5YWQRQYqjgs5shC03Jz29CD9cfwPFrk4lmU1ltEp91NUMV1FfnzTvU004/KMEK/n6uzKQjZunLi04NoCXvbHMj9e58HnB3Ts+TGq5laNuu3rpidkAc7l2LJjLRa0w08MDxGPBuBtXlh9oUUZrthPdcoEXt8htkPUFbF+PkRvbxGd+Jfo/j4iP28iF1eiAq2JincnQvawiFohGiBi9gdPDl/R+/tHG9uEEL3AyoGdnZ2sGlhIYGAQ+cGeEUTkYBebz58iaAskL6CXWqDEdvU/0p8rsqEJWaVKefTFUep3uJ/RJqO+hfuG+hp4XwjGuVfn8rQyLOND0MILDCHbZmcbThaon7k+R10ZClpFyMJOgIopPKdonMNxYRACvLFzr8zliV9IKqi3pR7VyViHhpcazkMGmm9vHmKfUMGcVH4SvyayeZXYLizP199cny0YChkTZOQsW+UCISyCFufx0LND3ARmCE9LKxQ8LS1G4v+NaHtfossrjT+O72+zpUQZy4ugFWKUmBWzkBHwS87e3p5vgiBEbb76+lOc2LFp781XdPX5Z+5bL5whMVXMkYJiBdmzWFUvyatju3Y33s2PaRGhSC34/dj3SCo1K26toNTxU3NzlamYL1QMUZGFkAXwnaLBCoIWzVeKkAWwM2D6FxqulCV/VG5hI1CErOI5Ba1ytqKlN5ZSubTlaHP9zZw60HxHcxaapdKUotfer9nfa4xjL47RpPOT+Dyh+ooRwPDawjML8awA7y08qDhXA44MYEEKsLTv7umuKTFASS0YcnyI0cdRlcZ5bJi1YcybsOXrRXRwtGkhC5D+sKYNUae9RK4F0LEdkXsoCJGG2AwEQYi2fPMLoCUnH9PsIw/ok7d+JFay+A7Ut0o2alIkLTnahX3JWRGyhs1exkDKgSlBi8lRyHeFgIWQVZqukAjg6edJb7zf6LaFdxXVUVSM1VVKU55T+EQffX5EUypO4VgtxIRhv4eUGEIFkxfkpi11s5cxsN8/F/yZ48XSu6RnkXru1TketJApUXAzFQQ2fKjYj9+O/MaCFo1hiMoKLatXEbKGzV7GQMU5xgnarx+JJmYhMpOxqwOV2ZariRy0jTsWhBg5NEEQBMHW8fELoHG7bvPNUMiCd56+NGTzdZp75CF99Q27pQiiDoJOLWTR7HW8xXG2AximHDz58iRERio8qwFBAbyEj0osLAaIBUNleFWtVZTOJZ2ekN3SYAuH/Rsut+PvI0qNoDqZ6ujdj8lp1d2qcyMbMm/xfkVSFWGBOvDYQD0hi2av/U32U8/8PUOkHCAiC/uC1AiI06KpinJcl1rIKtmwGMAwufxknZBF5dhcEgcq4EguUAtZNHudaHEixPH8ffZveuHxQvealoBqMi4cYLP45POJPwtYMGzeJ3tuoTYhCx4dIfL5GN57JQg2g1XFLLqqMUjhwoXvfilBEITI4MbLz1yVDY1/9t0l98+mx9mGBpbPMVkLzV3q1AI0jsHXqha0g4sOZjGoXnKHkDr+4jgtvL5QJ2jX1l3LDWNTLkzhqi8GQRROWZgblyBkwcAjA0NMyVIL2moZqundjwlfmKz1b6V/2baAququR7v4tVEBVoTs8lrLuTGseY7mXFVVQG4ubAqGdox8yfPpCVkcx4kXJ/jx8unK64QsPL/wE3v5exkVtHj+jMozdAJdSS1I4JgghEAfVnIYpXFJY1ETF/YBIh5Wjnqb61Hp1aWp7JqyVHZ1WZp6cSpPOjN2Pm0C2Dmen7PsOS+/5x4LQnTHqmJ20aJFVK5cOerVq5c1X1YQBBusenr4+PHN19/2GiW9vvnTvKMPNW8/9+hDfk5YgFjLkSQHC68iKYvoxW9BmCmCdlDRQVQydUluOIOwg7hShCyW5OdcmUPzr83nCiXyWVHFhfBC5qsiaEeVHsWVYFgR9jzZw1VWowIsKNiioAZCefCxwbxvEMqY/oUBB8i+XVlrJScFwLpw/e11+vD1AwteVFUhaCFk0cCmFrKobirHrwhZNK/heHB8p1+e5mNRhGybXW04wqvdrnZGBS1eB6kP8Oai4quO31IEet1MdWl4yeFUO1NtiywG2AdUn5tsbcL+3+eez3WPwcKB81x3c122OdisoDU2S9iq2wtC1EU8s4IgaAbL8Z99/GjpiUf08J0XxYkdi4q5JaVmRdPy4/EcbKOn1D8gkLIP3U0Bgdp+oSdwsqOrI6r/0HtCBKH5CVVXw/gtD18Peuv9lnNY4YuFRQBxX8hAhZCF0FQ42fIkrb2zlquFChCgqP5mSJiBWu9ozQ1bCkgJ+KfCP7rBBEgDmH1lNldIjYGBDRvqbeChARDGeB6EKRrJsOSOfUGiizrZQRHm6mPFhDDF6oD3ROV39Z3VNLvybG5UQwIDBCREM4QsPLsKSI9ABdjceTQ2aAEWAeyfpV5ZjBCGkEVigzlwnjc32My+YpvC7yvRkQlEx//R/pzel4mSZAzPvRKEcEWiuax0cgRB0Bey/dZept03XpFhOrWTfWz6uWIW6lI2EznZR35+J6qsFSYdprj2cejpB+N+yGwp49Orzz70xSe4IvtoXK1wiTuDl/aF5wvqsa+H3uhXVD6x7A1BqVDStSRNqziNxReSA1CRVYtQiDz1MIdkcZNxVRUeW4hRiMrN9zfTX2f+0nvdVPFScfrAnY93dK81rsw4qpC+gsXCUN3whgrq1IpTWdD6+vuST6APjTszju0LiONK45yG+h7qS299ghvaFM8vcmszJMgQIRFbqAAjkeHngz9r2r5J1ib0W9Hf2DphU3i8JvonO7IjQ982bRGi9juI7GPOqGsh+hHuYvb8+fO0du1aevr0KQ8ZULNx40ayZUTMCoLlfPMPoDYLztC5x+abSnpVyEw/V87KItLcRCoFpSKo/NdSdM8P9KM4ZEc+/gHk4xtACeLa0ysPD3J2tKc28y/QjZfBUVUKZbMmo/ntCtH9d5+p9byLLPyuDq+uE58QWViatlawPl4TjV8ddnUgDz8Po9tAyE6qMIkGHx3MwhO2BFgS1IJWjaGQxflFZBbG/a67s45Gnx7Nx9Utbzfqkq8LD18YdHQQ7X2yl58PT+/eJnv5WFGRDS1twFRyQ5k0ZVjQAnWSAgSzImg77OnA7xHRQhbAyoHGMviAtQBxf6zFMdvLsvX1Jtreh+jqWvPb4YKszSaijOWIoupgCEGgcE4zWL16NZUqVYpu3bpFmzZtIj8/P7px4wYdPHiQ31QQhOiFX0Agbbr4IlQhC2YefkAfPH1DTsY6NYpW3Fyh50dUoqiabmvKsVOKB1P7fvnxxCk8Hx7P5588qeuy81Rv5gnyCfhGWx+von8u/E3LuxSm3KkT6AnZma3zUb8jfeiux0la2a0QNS2Ujry/+etEZ/NtzTmrNSzd8saAMIKAW1xjsdHH4RWFVQBCFlVECMLx58azf1SdZKCARjD4XuGLVS4CIGYhGHE+8ibPS0NLDGUh2zlvZ272gr92ZKmR3BgGIYsmM7tYdtyUtfPhTk1eUYhjRHPh4kEBHlnEaSFbVh0JBjsAtnVxcNFNMcPxR6SQBTg/mFSmFVS+1WN/bQbEbNWdTpS5sultYM2oPZUofXERskKMwmKD29ixY2nKlCnc5OXi4kLTpk2jjBkzUvfu3Xm8piAI1l8yV1a/sY7i7BixvtTAoCBaePy73zE05h17QINq5GD/LMTh6FOjOeRfoU2uNly1U2eqIvcUVUY0I2mp0CpCFl5MCA88f2HVZVQ9dwqqlDMpLbu5lGZfmaXbfnmXwdR2wQVK4uzAQnbQ8X4swnAbUXIM9alWhezsAunxlyfUfld7bgpS9gnCzxoVWiyCYTqXMSCcIaLUwhV+1M++n43GRvkH+dNLz5d8HpA1C7H40ecjtdrZis8LhOuS6kvINb4rnX99nvoc7MPPgeicXWU2i1HYHAYcHcAJB7iBWplqma3QompZNm1ZmlhuIk/ogoAGEMvGMnVLpy7NGbaKNQLH75bAjSKUoOCkBEuA39cmgW2g5X9E9/YSnZpB9PT0/++PS5S7EVHpX4kSpg0eaSsIMQiLbQbOzs5ciXVzc6OkSZPS4cOHKW/evFypRSyXu7s72TJiMxCi0tL+/TeeNP/oI7r96gsL2typE1LXshnJLZnzDwX9W8J7z29UeMx+zdunTRyXDvQvTxTLn/Y+3kt/HP9D7/HeBXtTDbca1H53e91wAIBcVVQLtdJ4a2Mer6qQMl5KmlN5Ie16vIPmXZutt+24MuMplV0RSpM4Hm1//B/9e+lf3WNo2EJKQPbE2blBC0JWAVFUaLz6UVD1PPXyFPU93Fev2UsNxOvCags5EQAjbGtmrEkdd3fUa/YybFZCzBZsBnHt41KH3R1YyCr0K9yPGmdtTFXWV9Hz2aL5alqlaTT85HCdiAUQfDsa7uAJW6GJP7zesefH9AStKSH77us73f24iEEFulTqUppsDdYASQp/Hv+TR/lqIbFjYjrQ9ECYbC8RBlYMePpaLCLYPRycg7NoHeNH9p4JQtSwGSROnJg8PII9X2nSpKHr16/znz99+kTe3jYePC0IUQRvX3/quPgc1f73OG2+/IJuv/KgW+4etP7Cc6o+9Rh1X37hh4L+LcHHP5AaFkxDDnFC/rjImMyZSmZKqncf9ssudmxeSq7mVo2D+dVASNbaVEtPyKIiC2GmXr42ByqS0ytNZ9+oAkRfw211QgjZFtlbUMlU5emPjbeo7+pr1Cxba6qYriKLLVdnV146H3piKDXb3oyFLKqPtTPWpkwJMnGT1I9aDUwJ2YwJMnJ1VAHd/hB/vQr04kxVQyELHy1yYHWvG+DDwxpwHu9/vE/vvL+LRmTVwk5gF9uOG8qUZX5w+e1lKr+mvJ6QhaAfW2Ysi2gtVUycoyoZqlAGlwxGxWCz7M04ZgxVZRynAo4ftoaTL09GWASWs70zdcjTQfP2jbI24iq2TYOVAlRjUal1SkgU206ErBCjsVjMIkd23759/OemTZtSnz59qGvXrtSyZUuqXNmMl0cQBE34+gdSmwVn6eSD9ya3OXznLXVaeo63NbQkfPT2pZ1X3Wn9hWd05tF79rwiFzasJIoXi8Y2ykmz2+bVE7RZU8SndT2K0vz2+almnlS6+1MkcOT3BBC0g4oNCiFo1Sg5pxBSatFlDlTNUJHE89SC1pDm2VpQn0L9KJ6DI/WulJWKuiWhPdff8TI5RrticpVaIEKkoRKLTFNM4oIQ+lGLAQTlhnsb9IQsmr021N/AHlI0RSnAr4vtTruf1hOyOEZMAttYfyP7a9WCFpFYhVIWYrGrCFnkxeK8oiMf0Vg4JlPnFkJ2XNlxVCl9Jc3JBrCPDDk+hCO4DPn47SPbGv4o/gdHgOGGyWMKOL6N9zbyeYkoUPVX74MpcO465ekUs8bkCkJMFLMzZsygFi1a8J+HDBlC/fr1o9evX1Pjxo1p4ULjuYaCIGgDuah7b76ii09Db7Y69eA9nXzwjgIDg9iS8OLjV47OKjJmP/VcdZEGrLtKzeeepjLjD9LSk4/pWxgELaKenno8ppobq1M8l9c6QQsh+1/3IjTn2jTqebA7/d0kh07QNiuSjmKrEq4gaIcUH8JLy8ZAIxPEmlYhqxa0jrES0ezKxn/ulE1TlvoXGUiNZp6lchMO05Xnn7mS3KBAaq68Ibx//b31POQAglYRsvCv1txYk975vDNpCbAEiLbJFSZz178iZFFVxvEq1gIIWlREx5cdz8vvsBgMLjaYt8e5geiGOIW1YHH1xTpBiwou7ASI8YIHGSyovoBSOqfULZPj9SB2MWzAGKgEo8pqiZBVpxYY48TLE5yfqyQtYOCDIiZxHnA+IlLMItIMlf9iqYqZ3AY2lWU1l4mQFYQoiAxNEAQbAhXUlvNO06VnnzRtXypzUlrYviiPY2046yR9/mp6mb5OPlea3Cy/Zq8thCyWvhGrBN8hezQrzqEAn9SUI1UCFrJr7vzH26L6N73ibBqx5S791TCv3vAEJbWg5Y6Wev5JtYe2ba62YfJQevl+pUXXF4ewFgAIqcXVV9KOS19owu77fN8vlTJT9wrpqOOeDnT7w22+r1u+bpwtigxYhPyjKx+pAIkcE3GFE1YEiKEfBSIQftguebqQo52jnv8U5xnNUWiugvjHEjxuB58dZAHGqQWx7dkS8eXbF3J2cKZlN5ZRq5ytOL7r+rtgu5dyPF3zdtU7n3jv/of705HnR0LsF8bGLqi2QNP5hw1k9uXZbCFQM6DIALYXDD05VM9D2yBLAxpRcgRXt/F9WnB9AXXJ28VomoEysMHYYzgXEPumPgfsF5IZDHOCDSPh8F2EzWLx9cV05e0Vfk80pLXI0YKniuH5ll5UCYIQBXNmr169avbxfPnykS0jDWCCLYPJVVmG7NK8fVJnBzr9R2WqNPkwPfvwvcnHFKPr56HmRdOSgwZBix8NXfZ24SlVChC0Y0qNp7OvT9Lau2v0th9ZcjRVSleNnOwcdYMTFCGrpBaYok+hPtQmZxuLBC0EzpIbS2jm5Zlmq20Lqy3XCdrzQyvQjsfreaSpmo65O1LmRJlpxKkRLHBMTdf6USC6jImlr5jwBJuDfVwWYKturaKlN5fSmjpruILZcntLrsLCgwzrA2LOkB37y8Ff9ISswk/5fuJILpxPCFkIdLVH1hBcjCAGLLTzrx5Nq0z0+qPYH9Qwa0MW2uqmMJx7WDUgxJUqrKnjxzlHKgWGLTTP3lxvPyD2ER1WJFURoxcWOL75V+fr7AGKoMV5hFUDfuV6mevpXhPfa7ymMoYXIjt27NgiYgUhJolZ/KPHDwtjT8P9AQG2N6ddjYhZwdYrszmG7ta8fc+Kmbk568T992QfOxa98/xGW6+8pAdvvYxuj2X2Pb+WIwe70MWZ8ku/456OdPP9TbPb9sjXk9rn7kBxyIGcHMwLWSybIzkAS9FhFbSmhCyWsG+9v6VbclcL2s3nP1HH0m5kb0c09cJUWnV7ldn3KJKyCNsOUFWM6AB9CKx/Lvyjt4+ouDbM0pA/D3VqAcRi7qS5OZ9WDSqiEMBK/JbaIwtRfPDpQb2Gu7AI2pbZW1KDrA10S/NKygEuFlDVRrXWXCoARC9uSrwajqtH/h4sTLEfeL0t97fwRDNjlXLFu7vn8R62XsCCgX3BcUHIttkZHN2GARRNsjWJsAQFQRBsPM0AnDlzhh49ehTi9vCh+bnXgiCYxz5ObEocL/RlzngOcWhkvdzUp1JWevPlG8dnPfvoTcldnGhTr9K0sktxvUEBCo/eefFNC7g4hTBQezRNeS475u1Ice2cdEIWYMkY2acQPgrwff5X+z+aUXkGNcvWTO910PyktQKK7Z5+eap3X7NsLWhK+X9pUbUVek1hSCjAfpTKkpTs4gSxEO5buC+1ytHKrJBFCgBEYBiGJP4wsCHAC6veR4hyNFd5+nrqNSyhMQwe3LY52+q9Bo4bnwEGUhg2e40vNz5EUxgGHEAchpbeAHGP6vCGuhtYyEJ4K9PAlBxaRHwhnxe2DVOpBXgOHvP299YJWTD7ymxaeD3YB60IWYDXgjjFf7GPEKzIMIaQBbjggtBHU5xayAIMoNj5SNtgCEEQoh5hErPp06enDBkyGL0JghB2fP0DqHnRkBOf1Lg42tHqbiUodSInqjHtGLVecIamH7xPc448pD82XaOSYw/QoTtvaFXXElQys35sFnjrof0XuiJo4amEEDIE8VaoGELIxlZ3ff2/8ShTokzcYIXXUKcWYNl5YLGBOkELb+WfJf7U7E3FdsNLDae6mery31vkaEm98v9K9WacpAPXv9LCqstZ0EJ0zaq0gGL7p6C8aRKyGGy4pSH7TdFglS9ZSFsUrBQYLHDlzRXu8I+sah4E7e/Ff6c8yfLw3yHqIODnVJ3DDWMQsktqLKcX7+wJ4RG9C/XWCdpaGWuxD1R9MaJOLUDeqzrlIL1LelpZeyW/rpb0BmyD74bnN09qvK0xjTo5Sk/QwnKw/u56qrWxFt36cCuEiMS2mHbW51AfnmYGO4eaOVfm8CQzRciqv29IbcD7Q9A2ztaYPy8FCFp8vi22t9Cb4pXaOTVnBkdk05kgCBFHmGwGS5cupWTJkvEAhdSpU1PmzJlDGO9tFbEZCLYOrAJlxx+irybSBxZ1KEpfvvpxckGgmX+9VXOlpIlN8lGd6cfp+cfvftpNPUtRwfSJNe8PhMc/5/WXvBUgJOZVm8fRR6ZEH57/4NMDXg43jN/CY/se76OqblXDtJSve36GqhSb7Onis4+0+MRjqporGRXOFIc8/L5QBpeM3PQGsY0hDhiti8owKpz9jvTT88iqPaed8kZuRBME4NlX56jPwd663FNUpJEHi0lhEHUJ7ZJRnelnWKhPa16AAmP50f4n+/XOp2IXwSSwoqmK6h0T3gOe2yyJs5CLvYvmGDJURTFCGBPHlMpvvUz1aFipYfx+ELKohhr7jihCVhliUMq1FA9xmHpxKq28tdLkeyL7d2TpkXrfE+w/xHK3vd24ImsMCFkIddgURMwKQtQh3D2zei8QKxaPtW3fvj1NmjSJ7O1tuxNUxKwQFXyzF558pE5LztE3gxxZWAeWdy5OJccdCPGYMcY2zEue3/xp7M5b/PcEce3o/JCqmjyzoQlZSwQtRAeEkrHmH7zHj3hS1c/HjzMv34DgJadYARREgeTsEJe3+ev0X9QyR0sWNTc/3NSlFphC3UQV0eB8YUQshiIYBvhD0A4tMZQjxLx9v1HDTK2p+dzzNLBGDqqVNxUFBPmFOJ84LzgHxo4F74XPxZI8XTxnx8Md3DCnpqZbTXJL6MZWATVIi0DuLPYd/mlUXWEXUICgRVwXfMLr7q4L8X4YADG27FiTSQcQtJiAZjiNDNX5dXXXiZAVhChIuHpmAwMD+fbt2zd6+/YtXb58mSZPnkxr1qyhYcOG/ch+C4IAcWgfhwplSEy7+pSlevlT6w0qaF8yA607/0yTkAXLTz+mZkXSkuP/xWvTwunIPzDwh4QsRqRCuCqgIobKGKKuTHkSIaJMRR79aHOV+vm4uI7vaEfxcHNw1AlZVAI33d/EPtL7n+6HELIY8YrKn5o5V+fQouuLItxnyVXUV+dDCFnYAmq61WbBNvLUSJpyYQrNvTaLNj9aSWu6F6HVZ5+Sf0CQ0fOJ86KLpzKYsob7IWTRsKe1toHnIMoKjVVqdj3eFULIomI7uPhgbgTD+6BCD7sJLioU7ny8wyIXcWrGSB4vOZGJXYNAhmiFdcIQVKExZc3YYwJ8Td5EPl+IvnkQmbmwEwRbJ8wGIlRgkyZNyre8efNS8uTJqVevXjRu3Djr7qEgxEDi2sehTMnj07hGeWlso7z0/IM3j2FPlzgetZh3WvPrYATuey9fypMmIX3w8qW+VbPpZcCaA8IGy9mGzV7oNIcQVKccQDTAw2mtCCtrgf2cdnGabkn7pedLHlSAarJnoOf3Zq9K03TZsitvBy91w2OK44f/MyKJTbFZvMEz6+8XLDBgD5hafgb5BwSPtV19Z5VuH1M7p6GPX33p0tNPXIVXYtGMAWH/8NPD4HOgqtIixgpiEscP8afFNobnIyEAKJYCQxTrgVpgw++cyjkVC1o0fkFoLqy+kI6/OE6zrswy+jqwH8AGYVgpV+K30OxlbBTyM49n/D1VUg6iih0uXMEFCy7QvrwkOjuP6MsLIpzTbDWJctYhQgOgw/cxy4IQ44YmfPjwgZIkSUK2jNgMhKgMpnhVmXJEU6as2iO75/or6lExC8V3jENxDKxC5kBVUvE/Qsh2yN2BxYQ6tsvd052FCaZOWWO4gDVBk5CHnwe13tGanno8ZeH0V5m/WKR239edciTJwUJ26Imh5OPnw3/+9+K/tOLWCt7OkslY1oQHVnx5xEvnaN6CkO2/9iY9fudFq7oVpnnXp/PAipElx1BWl1LUet5FHphxeEAFckvmbPw1/x9jdeDpAW78KpSiEH+WEITwvUJYIjEBI3a1CloFnN+r7/QzyHHeTrU8ZdK+APG57f42yp8iP518eZImnJug9zjSEGClMGX9UAtZdbMX9h2Pqava6tiuGC1oIVS/fSFa04bo8fGQj8dNTFT7H6LsNYjsRdAK0dgzCx48eECLFy/m/06bNo1SpEhBu3bt4pSD3Llzky0jYlaIynj7+vOI2msvPmt+zsnBlShpfAe2K4TlFzkE7b2P9yhr4qx6VTFF0CL2CpVEWxOyoQnaLImykGt8Vxaydz/c5eog0gIKpCjAVgQMUYjMBjBvPx969uUF56pCyO67+ZrvxyhhCNrnXg/JPjC1TsiC839WoWTxQ9oM1HmsAI1QELSo+L72es1CVhGEsJBoFbTqix2tlVkAsYkoLkRvYYpZnU112AKiAMvHX2X/oknnJvGFhQKSD7Y23MrnBPQ93Jfzcg2bvVCRNWwK61+4P7+XrX5PIwTYCeaVJ3r/wPx2jeYT5agjFVoh+npmjxw5wrYCZM1u3LiRPD2DfwBduXKFhg83PvtbEATrECd2LKpXILXm7XO6urCQRTd/WCtSELA5k4Zs7lJiuxC5ZcsCAZVBLFGjegy/JrJXIezOuJ/h/8KfCiG78d5G6rqvK2ecQrhHppDl/SZ78vJKSH3X3NAJWXDvjSe1mneBHr5IqCdk86VNyH5hY+DCQz1KGJaKXgd60axLs/SELPj87TOLVJynHxGyYOvDrXqxXWohi/fFuT7tfloXN6YIWUSSwa+tDNJQhOzcqnN1dhbcxpcdz15iw9QCCHI0JSqxXWj8w82Wv6fhjq8X0aGxoQtZsL0v/oFHxF4JglWwWMwOHjyYxowZQ/v27SMHh+8/GCpVqkSnT2v38gmCYDkQpa2Kpdc1dIVG5zIZKY4VfimZijTiWfZmJjxZm4DAIPaFokKN/36DiVQDaG6CYFNEFYTaxPMTeSgClrvRWZ8mfhr2oCLjFBPCILoiE0f7OJQleUI6dve7CFUL2v5rr+uELOhSNhPFjh1otGENFyLIzi2csrCeoF1wfUGIPFYIQvhyzcVYKWkGhkIWaQaY4GUoaP8+8zd/BqiSK9O+ePjB/y8sMLABecRNszVlIdtjfw9adnMZ9TnYhwUtxg1DyCJzV31RhT9jalnNjDX14rf4Auz/grZ9rvZclYUHOUaDz/Oy+al3OjCY4+oaIn9f08L4m+f//+th1d0UhAgRs9euXaOGDRuGuB9Wg3fvQv7QFQTBusSOFYumNi9ABjMKjObM1s2fmuxUaQhR2Svs6x9Iu665U48VF6jx7JPUftFZWnryMXn9X9yagr2VX19T+93t9aaRKcAq0XVvV8qeJDuNLDWSl9fRqR8Zk7+MTYSb2DRfqEUyRHJVz52cvvh+prsf74YQtDhGWEUMBW1Y81hR7cboYFTl1ZaC0WVGc4OgOuUA1dF6WeqxcMXzEjsl5qY7BVgGkCaBpjQMshh4ZCBde3eNH8uYKCNXYHsV7BVCyOpe386J/i77d4j9VgQthknEeCEL3K8Q+XyPQwuVW1uDG8XU+H0l+vCQaO+fREvrEC2uGVzFfXmZyP979V0QIhqLf8slSpSI3N3dQ9x/6dIlSpMmjbX2SxAEE8R1iEMVsienxR2LUUYjzT7ODnGoW7lMNKNlQa7kRofc3buvPajU3wfo5/8u0bF77zilAVm8Y3fepkKj99G2Ky+NDplQlrSVMagKWKpWx0Ch0QiCFg1h2xpso6yJstqEAMJnXS1XKlrQrghlSBqyIQe2gh7lM9GU5vnIw+8ztdrRijrv6awXkwYhu/3Bdq6G4n5MbDNGw6wNKaGD+YqsAmLWksRNwqN0IWjV3lgl5QCC1lgGMbb5u9zfVCV9FUobPy3bPxI4JtA9PqTEEBamrXO25rHDsAYor2sKCF5j+43nxGhrgRpUUS3dXn0Vhe/T5p5E/xYkOr+I6OWlYIF8bV2wD3d5g+AqrQ1cBAoxD4sbwAYMGMB+2XXr1lG2bNno4sWL9Pr1a2rXrh3fwuqb/fvvv+n333+nPn360NSpU41us2TJEurYsaPefY6OjuTjoz0HUhrABHMEBgaRj38Aefj408UnH8kvMIiyJHemLClceJirvcbl/YgafYtwJjSDHb7zhjNGM6eIT3XyuVJgUJDmCC5b/zwevvOiejOOk7eveUvBlOb5qUYeV441U4tZZMXOvDxTdx8E1IpaK7hKqDSFKXTJ24WXyW1NAMFOAQvE5Wef6Ni9t/xZZ0kZn+rkdaVACiAv/y8sZN29ggsNEJHzq82nvMnz0sa7G2nU6VE8tAANXxC7amuBgtIUpqQcaAEWDUxSi2cfL0STF8S0h68HuTi4GH09WD6wDUYOq4UoPjM8L75D/B/OIBZUvLlJNKuk9lOSqz5R/ZlEji7BVdd1HYju7DT/HNcCRJ33BEd9CcIPYoles/i33dixYzlPNl26dBQQEEC5cuXi/7Zq1Yr+/PPPMO3wuXPnaO7cuZQvX8g56YbggO7cuaP7e4yOWRGsXgF8/N6L/tpxi47ff6dXYEAH+S+VslC13KnM5nhGJA7/r7oWzpCY8qdNSAFBQWFOLLBVcGExctuNUIUsGLXtJtXOq98cB1EKv6W3nzctvrFYJ2ThCYU4xLK6ImhRCUT0k60JWaBU2ItlTEIF0yfiixXlsw4Kik2BFJcSOybWiVl08aPSXD5tedrzZE+oQlbdFGaJoEWFFufSWL6wUhU1lT0MoYrnGz6O58CKYGuZxVGeJFmIkmQKtglooXBHIvv/r/ygChuakAXul4muriPK34IoAr30gmDxTws0fc2fP58ePnxI27dvpxUrVtDt27dp+fLlFCeO5b/kkYbQunVrfs3EiUOfF48f3qlSpdLdUqZMKZ+iYBUhe/X5J6o/4wQvYxuuV6DhpvfqyzT78H36qkFYRSTwjMaOHYsFj29AIPlpnA4W2fsMQQbghcXNGKiQ48JCCx+9/WjvjVfcJGb4M6NngZ68ZI0lbaW5CcMQ4I+FoO1dsDc/bgvWAi0+WnU6Bf6L41hUYxHlSpJLtx0ELYRsgywNqE6mOtRlT5cQzV4Q9oZNYRC0LzxfmB31q8ac6AxNkJp6XH0/Fg/RPGYMWCgiekKbJrBPSvMURuyioSrSCSIq0UvbpondiNxKY3598L6f/Ff725yZHXzMgmDLYnbUqFHk7e3NldlatWpRs2bNKGvWrGHeAVR5a9euTVWqVNEsfjNkyMDvX79+fbpx44bZ7TF2F6Vq9U0QDIGu6rTkfKhjYqcduM+i1xaagyAAzz3+QL+uuUwFR+2jXMN2U4OZJ2jthWcszk0JxMhu5Lr+4jMN3nCVCo/eRzmH7qaa047R0lPBjVx4XM0Jgwp5aBy++1bPO4vhA8tvLmdhhsorvJkQsvg7IqjW3llLcePEpfa520fpJW1F0CIfVj1qGCCxAeL054I/czVa3eyVJ2kemlNljp6gbZK1CVewtXhnwxsly3jhtYV68V4AIvbK2yt04/0N2xG02A90+Z9dQDSnNNFfrkQTMxNt7R35TVK4UCvUhih3I/PbYXBC6w1sYWJQnX10TPv7vL5BFMlJIELMw2IxO3LkSF227I+yevVq9txqHYGbPXt2WrRoEW3ZsoUrwoGBgVSqVCl6/vy5yefgteG5UG4QwYJg6D1de/4ZRz1pYfaRB0abjSISiNVuy85T0zmnOIMUEU1Yikdj1JBN16nM+IP05L2XTQla+D5/W3+V6kw/TtuuunMlFefxwVtPtnaUGHuArr/8wseme46F55mP9//qF0L2nwv/0NSLU6nNrjbsxcSoWEXIwmOKaCl4agOjQSUJghYCtIRrCb370fgGy0HFdBVpVOlRHEGmpBbANww7gCJoW2RvQQOKDLCJCrV6ytzMKzNpxMkROkEL8XrpzSXqub8nT3KzCUGLTn80RP2Tk2jvEKJ3d4n8vIm8PxBd3xDcJLWlVyQLWieihrOJqo4mSmCQV41JbTnrEv10nChR2u82AawAWCpONVb1BSHSGsBix45Nr1694iiuH+HZs2dUpEgRzqtVvLIVKlSgAgUKmGwAM8TPz49y5sxJLVu2pNGjRxvdBpVZ3BRQmYWg1WIoFmIGsA00mXOSbrzUVrVHJNbV4dUovlPkeMIg8HquukgHbr0xu12iePa0r295Su7iaBPneNT2G/Tf2Wdmt0Pz1s4+ZXUpDacfvqcW87TnV/eqkJl+qZyVYscO4KYvCFUFTPRaXnM5i1oI2ZdeL3WPIYe0Zc6WUbo6q6QWoNnLGBhVu77uem7WMtb9z0IxCP5c2zgHuOhACgWEqgLsEpjehoEXsEOgAQ3gc1taYylPdYu0/X9/n2hO2WABa45C7Ylq/h2542L9fIItBM/PE318HLwvGcsFV28dDBJSIGRnlw4W51pwiE806LF4ZgXbbgADkyZNovjxg6e1GDJs2DBNr3HhwgV68+YNFSpUSHcfGsmOHj1KM2bMYAEamgfX3t6eChYsSPfv3ze5DdIOcBMEk9+jOLHojYf2agksmZ+++kWamH303itUIQs+efvRjEP3aFCNHJGebODh40erz5kXsgCV2ol7btPEJvnJ2dGOm9tSJXCiV19Cr7qhgNS2lBs36H0L8KdaGWuxjUAZk/rg0wNqtLUR+y/f+7zXPQ9TwSqnr6xbgo+qQnbPoz0mhSx47f2ammxtQgtrLGRhayhmbU3IQ8zWz1xfT8xuf7idc3QffX6kE7IA1gpcrESakEWM1YFRoQtZcGkZUcU/IlfM2v+/uS9DqeCbOVDvQjPYnt+1vXa+ZsECWBrAhAgkTO2iJ06coEOHDoW4HT58WPNrVK5cmQcwXL58WXdDpRbNYPizlmYyiF+8hqtr8JxuIfyAn9E/MJC+fPXjZWDcDBttoipIAYjnYFnzolMk5bfic5h3VGM3MhFtvPCCR+BGBPhO+AcEsl0DN/wZ96Equ/D4I83e1703XpP//79b+I5hipkWquRMSQmd7HTCzC2hGy2psUQ3JhUgc9ZQyKJaq3UkL6LCMKABlgn8W8Ax4jMJK7A3GGu0gkXC2AQyLKVDuKpRbBN1M9elxlkb6+6v4VaDjjQ/otcU1iVfF71BB4avHelL9Spgf0D27R/F/tC7H2JWLWQxcAExZLr0BSz345wi8xT+VTSPhfdx4T1u79C2Lf4hnJ5F5KtB+NoCuEAo3D7YSxsaELCl+4Ss7gpCOBOmcs2mTZt+2Gbg4uJCefLk0bvP2dmZkiZNqrsfubUYxKB4atF8VqJECcqSJQt9+vSJJk6cSE+ePKEuXbr80L4Ipvnq60/un33YJ4pgeh+/YG9hofSJWGRUyZUyygfzQzBVypGCFp94rGn7LCniU4K4kVOVRWrBlWfap/h4fPMn908+5GZkuIK18AsI5Ma5Zace04pTT+jl52DhkDKBI7UunoE6lHKjK8+17zOELIYkFHVLwlXWdiUz0O1XX2jDxRcmn5M7dQKa1rwAxVVVoNWCFrYC30B9cQiRCyGLHNSxZ8dyfJW56iTsHbA9zDv2kE4+eM+aBFX96rlT0U/lM1Pm5PF5yIFWIFhHnhpJ/Yr005tehfvvfbpHux/tpl8K/aLbJwjN/27/xxXIYqmK6cQbLAM4FoyFHVhsIN+HSWdjyowhh9gO3BTWcXdHFobwxf599m8+VjV4bTTK5Uqai7fRmjMbUYIW4hXjhw3JnTT3dyELLyoqo6dnE11YTOT55ntnftEuREU6EeFcxgmHVYo3tyzzib64QBRkW6koZsF3s81GomX1TI+vxTZNFhPF/zFtIAhhIfLbVc3w9OlT9ugqfPz4kbp27cqeXcR4FS5cmE6ePMlZt4L1QUVtx1V3GrjhKi+tq7n49BNdXHWJSmVOSos6FLWZ7NWwgCX4rmUzaRaznUpnjLQFabyvpQVxVJ7DU8jiYqfpnJP0+ou+VQN//2ffXaqRJ5XFVXz19o72cWhsw7xUJmsymn/0Ed10/+5thgWhTYn01KVsJnI0MtAiTqw4lDRuUhaEhmI2rl1cFpGLry+mjfc2cnVzfLnxRgUtKrH9112h7Vf1px/6BQTxfbgNqJaNOpfJpEnQQrD2PNCTzr46SxdeX9A1ZAUEBrCQ7bSnE1dg4WMdUHQAN0OtvLWSm9nsYtnRtErTWNCimowMXYzqRcUSz11YfSE52znrmsJwnBC08AijWapzns407+o8ngSGY4WQXXpjKc24PIMF9YxKM2xK0IL0CdIbvR+VdY7xQgzWu3vBI1a/ftTfCJ5QjF89O4+o0x4i5xTWF7SBAeG7vS1UZ1PkIupxiujwWKLrG79Xu9E4lq0mUYXfiZJmJrKPG9l7K8RALG4Aq1ixIldmMdY2KiITwLQREBhI5x9/pBbzT4e6PIy58JObFdCbvBQVhfusQ/dp+iHT/msAD+eqLsVZYEUGWL7vt+Yy7b35WtP2CNa/PKwqxXMMn+tWeFwrTjxs1tO6uENRTlxYdfb7pK3QvK9nfq9MKRLoiyks6UOYv/X4Ru89fdlTixGvEL7GLqaw/I5OfgxFUDd7qUGVc2G1hSzuVt1eRS1ztKSBRQfq+UlhK/hn711acPxRqPs+tXkB/vegDLQwRkBQAA06MogzYBWUqCzYIBQhq7Cn8R7u3B98bLDuPkXQYriBImTVU8y65+tOb7++ZW8sBO9Xv69Ud3NdHhWL+xC9tezmMp52tuDaAhayuteObceNYhkSZIj0eC4I7ctvL3NqgdpaoAZNYSNKjiDHVc2IHoZidUOVttfZYHFmTTxeEU3Orn37wh2Iqv1F5Gi898Sm4czcWEQfHgVXlxNlCLYXiLVAiES9ZrFnFt7YqCpkBe34BgTR5H13Nfkcd157RR+9onauIKppvSploYE1spOTfWyjAgsVxhWdI0/IAmeHONRJo4cU1MybCg3q4RZptv78s1CbszZefE6tihuvrBkD1X4XI811dv8fFpA2cTzKny4R2z0wQMCUkEWl1VDIohKpFmhoCuu8tzNXKTH9CyLQEPwbOHDb+MVDTlcXslN5kqfuvxtqIxmqr30K9+GqogL2sc6mOtR2V1s9IZstcTZdg1qRlEW+H1+QP/1y8BeqvqG6npBF01vXvF25Attiewt67vk82Hsbi2hx9cWcRdt+V3saemIotcvdjn49/KuekAXNsjWjtC5pbVbIYvytGjSFjTg1gr41XUKU5ntDsVFQpb2xMdjjak2cEhBlLK99+5I/R00hq6QVQLimykPkmp8obiIRskKkI/MCBaNAnJ59ZHzspTEWnXjEFayoDEQR/J2XhlajkfVyU+28rlQ9d0rqUT4Tnfq9Mk1B9dnCRjFrg2XjwukTs0dUS1W2d+WsXME0Zg9AJuvLT1/plvsXev7RO3gSV0CgRfuy5OSTULfbfeMV+2fLZ0se6rbQhX2rZDNqGbAECMppF6fpCVmIwv9q/0dLqus3hUHQYpkdglaZDqY+T5iktaFnMcqRykXvPZoWSUM7epehaS3z6ATt4/fedP3lZ7P7hkopqqOYvqUWtPC5qpvBIGSX1VzG22PJf3aV2XqCFs1jX3y/Wy6qZqhKw0sOpx77e9DFNxf5sbY727KgxTFh+tfPB37m4zn47CANPT6UY67yJ8+ve41WOVqxh9cWkg0w6haeYrWQLZiiIB1udjhEU9iOhzvoyodb5FumX+gvfGau9Zf54zgFJxRoGcGbuTJRQsk7FwRrImJWMAoacCzh7iuPaJFuAP8sBGvLYulpfOO8NKlpfupTJRt7MyNbyCognWBll+KUNYXpyg7E4Ny2hSl1wrhG/Z+bLr2gutOPU6m/D/IErjLjD/F/1557xo9r3Y+H70IfoAJfKQY5YAm+YLpEZl9vQpP8LNTR6PYjYBgAltRLpS6ll1pw/d11FncYEqAI2uoZqvO4W2XogBr/wG+0+cE6mn55Mq3sWlgnaCFk/6idmRurUiX7pCdorz03L2YNBS2atAzBYIOlNZey31UZ7aoIWnU6gZq+hfpyFRb2AgVF0M6/Op+67O3CQlbB3cudvbhJnZLy3+tmqmszQhZg3DCyY3GeFCE7r+q8ECkHuHAZUewPymufiBy29dHWrKVEU1kL9Ha45iOqPyvYQ2qKtEWImi+3/vsLQgzHphvAhMjj/2PfLdg+6mZ0GsPBLjbfbBEIvQRO9rTtlzK05twzWnLyMT1656WzITQsmIZ+qpCZkjo7hhDgEKq/rLpk1HOLSVx/br5Oe268ogXtioRqp7DkE8f7OdnfoNXdS9CWyy9p0fFHdPuVh05418nnSj0rZKHUieJa7aIBouzfSv/S8BPDWawitQATv7B8jYokBO2Gexuof5H+9NHnIzeKqcF2a+6soakX/9Hdt7Jrf1px+gW1K+VK3fZ3otsfblPPg11pVqX5LGj7/Hdd878dCElYIYxNH1NispziOOnErBLj5e1vPNLpwecHVNK1JK2stZJa72xNzzye6QTt7Cuz9bZFLuvcqnNp4rmJXKUF8BfbEriwwEXIqtqraMLZCZzOoDSlKYIWOMZxoJqJclLcJXWIvL/HrpkkvH5WITc2V32iNIWJjv9DdGPT9yaplLmJSvQkytvU+n5dQRAsbwCL6kgDmDbeeXyjomP3a84G/aVSFupVIQs52Uj1MqYA3ypkpZL7G9/JjpfGjQ1JgA1k+oF7NPtI6Dm1bUpkoN9r5jBqUVBHVTWec5Kuv9A2OS1zcmfa1acca4nAoCC2NaBq6+Jkx382914/AjyqEHQNtjTgpXYl5QCCtkK6CuwvffzlMa2ouYJSx0/NVVOIxlvvb1Grna30XqtJ1qbUM//P1PNgdxayCqhu7mq0h/7YeIu6lctEOV3N20CU+C3DZi81rs6uLOSQcgBBq04tMIbSFFY8VXEWvGpBa0zITj4/mbY82KL3GLy5phIdIgt8Fjh+RdSrgeDHr7C4i6oHj5LVQvqSwTFTDuE4tAD5tnYORD4ewc1R+HOsODJIQBDCSa+FWcx6e3tzdJavr37jjzKa1lYRMasNCJ+eKy7S4bvflyxNgdXV839WpSTOoYfOC5EHxGeRMfs5ezY0UC29OLSqWYGJdIFzjz/Q7huvWUg/fudFJx+800WHQbSWyJSUMidz5uatijlSUMnMSdnLG1Eoy+7ImVWELEDFD4IWyQLK/fDLQtBiid8+jj0LJXT8T780Pfh4KBb7Ug89O6Tn44QVYEbFufTxUzKaceAxre9Rymz2sikhi+V0CFYPPw89QYtkAQg5QyGLqm3yeMn1BCsELarRxV2L07q76zhT1pAJ5SZQ8rjJ+f2R5gDPMJb0bVnQmgX5svf3Ez06QhTgT/T2NtGTE6a3b76CKHst83YAQRCi9zjbt2/fUseOHWnXrl0mp3IJUR/EbA2skYPD4UNrCmpVLL3RBADBtiq4u6+/0iRkAYYgbLz4gpoXTcsy7s4rD3r6wYsjp4q6JeYUAYjS5C5OVCBtQraZdCztRvaxY9PKs08oICCQWpdw4wudy88+8eQs+I5x7YzKMZ4fUWy9v1VPyCoxWBCzqLwqj2HJ/9yrc+SaxZXzXbGU3S5XO35sxqUZNKzkMKqXuR6dfHmS+h3ux4JWLWR/WXWN5rcrSrFDWcZGdjbsC4apBWj2wr602dlGt0/wtaKqfO/jPb4p4H0XVV/Ez0Nl+fzr88EPxCKK7xCfq8pTL0w1+v5jTo/hQQMYJlEoZSHacn8Lpxsogva0+2mOCIOoj+xEg1BBvixAPFTqQsECtUwfIj+f4FzZ84uI1DaOVPmIslUXIRtZI39RXX9yksjnc/BwhXTFgpvxJJtW+EEsrsxi3Cymbk2dOpUqVKjAmbOvX7+mMWPG0OTJk6l27dpky0hl1rLs1fOPP1DX5ed1k78MaVAwNY1vnC/KTwGLznnB+BwxNez0ow80/aD5HF01mPDWrEg66r78PHfpK6DRCZPffquenS49/UgD138fqlE+WzKa2DQ/21T+3nWbjt1/p2dVQZRVn8pZqXy2FBHWUIdKKJINlt9arhOyWLpHpRVCEYL2ucdzGlR0EDXN1pQGHh3I/tqhJYcGD1sI8KUrb66wSEQc1pjSY7iRCoJ2fJl/yNE/O3VbdpkHO9TM46ptaELAN57YtefxHhakaPbC/hx8epDyJsvLVVgI2l8L/Uqtcrbiiu2xF8do2IlhLLIhZLMmzqobeoAEA8RYITMXIt2w2cuQBA4JaHmt5Zw3i+r03sd7WdDGs4/HEV6ZEmIIhY1XZjG29tZ2omOTgquxChBMWasSVfyT6NMTovUdg6O4IGQ7bCdycAlu2BIiBohVTGbbN4zo6ppgUavgnIyocEeicgOIbGhIhxADbAaurq60ZcsWKlasGL/4+fPnKVu2bLR161aaMGECHT9+nGwZEbOWAS8mlqeXnnpCa5Ep+tmHI6zKZUvGIzyzp3IRIWuj4J+2h48/1Z95gtMZ8FliIpdWfiqfidIniUd/bLpu9PEETna0sksJthaM2xUsJqa1KECJ4zlQ12XnubprCuT5diyV0aTwgwC3ixOLK7io5PoHBP2Q+IWghWUATUPq0bGKn/bo86NUw60GC1mlIap+5vosaNF49fTLU86jRfUWy/vTK01nsXjs2XHqU6g/+fnHpngOcfTG6Ya6TwHfaM6VOdQ5b2cWss22NaOnHk951CwauU68PEGNsjaiEy9O0IiTI2hetXlcnYU1IEuiLHoTuiBor7y9wvmwDTY30BOy8MjiNf84/oeeJQG2ip2NdrKwRZV4/5P9/LpRRsgenRQsZM01ZLVeH1wFRLg/KrKx7ETIRiSQFzj/8ysSfTDj1XcrQ9R6g6Q8CBEnZvGCV69eJTc3N8qQIQOtWrWKSpcuTY8ePaLcuXOzl9aWETEbNiCEICwQnwS8vvmHW8OOYEXf88qLdPjOW2pSOC01LZyWms87rfn5GFN85O5bWnrS9Jhf14ROdKB/eSo/4TAlc3Gg/7qW4JgvTCoLjY09SlGhDIlDiNjPX/1o/rGHtOuaO4vxhPHsqV7+1DwswtlCwagGFVZ4Tw2XziFoYRnA8joqr2rqZapH9bLUo/5H+rOQVciaKCutr7eeOu/pzOLyt6K/hcljiveFkEWqACaQKQwuNphqZ6xNp9xP0aCjg9gCANGJaCr8GQIV8WOGjVI4Fnh8l95cyvdhO4yyhfD98u2LXlMYJp2hEq2IYghi7IvNC9nAQKLHR4mW1Q9927iJifrdDm68Eo9sxOPrTbS2DdH9A9oGSSCrVyaJCRExASx79ux0584d/nP+/Plp7ty59OLFC5ozZw5XbYXoCaqxipAFMVnIohMfzU8RCRqstOT4qvcNghJiFGy/+pJyuCagbCm1TR1KlyQuFcuYhDZdfG52O/fPPnTg1htqXiwdtSmegdaef65JyILZRx6Qt2pbjMbFyNuSfx+ghccf0cvPPuzxff7xK806/ICKjz1A26+6s+A1BY4d58AYSCkw5gGFKISgK+Fagq0GarY+3MpL9mohm84lHc2qMov+vfgve1Xhf4UYRaU1LIMBsE/Id62UrpLufjRulV9bnivFipcVFWSM3YW9wFDIArwOhOgvBX+h9rna64Qspn7BegAxjNgu7L+hkAX4s80LWYC4q+NTtG379SPRtXX6vlkh4vj6QZuQBReXEdm6R1uwWSz+5vTp04fc3d35z8OHD6caNWrQypUrycHBgZYsWRIe+ygIkQ5Ekn9gEL349JUbqVCpxhJ8nXypWTyFh7jHe+AC4uT9d3Tp2SfOdS3slpiKZ0zKDVVKDiz2DUL34Tsv2n/rNS/LuyV15vG7yzoVowm779C1F59p9dmnNKRWTuq09LxZYYz+pSG1ctGWSy/oi0/ownTDxefUv2p2SpXQidotOqP5+A7efqMLq8Wx7rjykkZvv2lye+zzwA1XKVE8e54mhmY0pQKNpqud19w5bxf+7Sq5UlDGpM58/pCkoAWIuSbZmvCfkUdrDAhBCMK7H+7SwusLdfcjEeBHQFV3QvkJNPDId5uDYf5sxXQVeZvQKsCKoFUEvJIBDQEMQbup/ia2oKiFbJQC43mRXKCVi0uJ8jSSWKzISJk4v1j79t++EN3dQ5SrXnjulRBNsfg3cJs2bXR/Lly4MDeD3b59m9KnT0/JkiWz9v4JQqQDofXwrRf9vvEqXTGY7jRsyw1ewh9SOydXr635nhCJ/x64R6+/6Ff8Uid0ov7VslOtfK4UK4jopvsXGrrlOt14qZ/3OnTzdWpRLD1PC+u16iL7ZfHnma0KUb+1l8nbSIUTkVyYepY2cVzqv/aypn196/GNBSZuhvtqDojTL1/9OBMXonP87uAVH3Og6Dp2521uIFOGQOC4/jvzlLxUxzNp7x2eJDamQR7KkSqBZr8tBF6LHC14UtiORztCPD63ylwWhPlT5KfeBXvTv5f+5RGzmMz1o1FWeP4/Ff6hmhtrcoqBGsR2TakwxWhF1uhrmaiw4vn4X5TG+13wF0Ernq+l4hcZoOnOQ/97HCqfnobX3gjRnB9u6YwXLx4VKlRIhKwQLUHzGyZVNZx1IoSQVZbGl59+Qu0XneVtrQGW0bGsjhGwxsQhlt/7r7tCS08+oq/+AdRm4ekQQhZA3GG5vvfqSzSjVSGertVu0Vletj79e2UaXjcXFUqfmDIlc+Yxs3/WzsnZsqUyJ6VW80/riUNzQMTjPOCGSDdLQHUVVebDd97QW09tQhjV16vPP3EFuvuyC7Tg2COj+4pz0mzuKbr87CNfHGj11cJTevyl8UZWNGz5B/mz6G2bqy2NKzOOhaw1qpxowtr9eDfHYhnyxvsN7Xy00+SAhRiFXcgRzWZB7BMawISIBakSlkZuOQaPixaEcBezjRs3pvHjQy7BIcmgadOmFu+AINgyGB0bWmc+OPPoA8079lCzaDLHo3eeXJENjb933aGXn75SxezBs+tNgQawDReeU6fSGbka22PFRWo0+yQvP09qmo/WdC9B/zQvwA1isEskiGtv0SjfitlTcPQXbhWzJ9f8vOwpXSi+ox3nGJ9++D0HVgunHr6nW+5fQh3qgQlj3Vdc0DTBFEL2hecLarurrZ5H1tBDO+rkKF0ObZUMVawmZBHL9fux3/UGGCjgPkR5IXEgxgva+MmJEmfUfnKzVscJFCIaCNlcDSwTv9lrhOceCdEYi8Xs0aNHqVatWiHur1mzJj8mCAjoRxMQbqieReWM1kO33/AyuhZWnH6i1yQXFpASMUfDuFmFZaeeUNuSGULdDtXj+gVTcxoAuP/Gk0ZsvUGVJh+hon8d4D/b/1/AIgarZdH0mt4fgxOaF03Hr4/jb6NhXxQ6lnFjkQmhZukgQlRzb7/SNkb3y1d/2nHV3WzTHsTpS8+XIYQsoq7QKGVO0P4oSBGAkB1+YjgNKjaI8iTLw/cjnuvvsn9TqdSl+D4kHIw8OZIFrY+fD/lhGdfIefHx8yUvH3+ulEdL8F0p1k3btviClewVvqNrBdPnPn1xosRu2s5QlspEDtoaVAXhh8Wsp6cnN3sZYm9vzzEKQswFnekePn60+MRj+nPTdfZsoukIy+Zo0olqoIoJ36pWYAlAtfBHgLcTDWZa2X7lJY+MDW1ELJbmn7zzDhGFBRLEtWNvqdP/G6qwDz0qZqYsKUL/xfJbjez0+D2W/T/T/ltvuPkKwxZCo0iGxNSwYJr/TxKLw75WS8jpmoDuvVaFr4cCPkdTgz8AIrswVUvte0Wz16paq+j3Yr9z97+axE6JrVrtS+SQiKZUnEKFUhSiOVXmUMfcHWlapWmUL1k+9soikqtgioI0teJUHnGLxrmHnx/SV+St/t8O4+cfSJ98vPh+L/+vNP/oQ67yY7UAIjfaAD9wkU7BE79Co9wgIifLvluClS88GswK3bPslIio9j/B2cCCEBFiNm/evLRmzZoQ969evZpy5coVln0QogFoxPl7920qNHofB+hvvvyCNl16QUO33OD7/sfeWUA3kbZR+NZLqUNbrFCkuFOgLe6+uLvrwvouK/+6C2u4u7vr4u7uXlxLKdT/c7/ppJM0aRNoqX3POTnQZJJMZip33u++9+Uf1pTylL4pWGN9HJ64+pUUj5/Hj9d8RSKiYpMdH6yFXlFWv50dk+/lfPIiEi4G29Evu3xodXi7OAhLhbYRjDmwQYVyGH0tVnjpuW1UMheGzj6sa+gaPPOQmPA1ol4R8RrGijWNSuXCzL5VdcM2WM1+q3xC1Tg5cmS3R+1iXlh+NMSs7cVnD48So3WTisjyzOYpxKu3k7cutYDNXnY2dspksHhBy9grpgWkVIwVq7sVfCooPty13fHDvh8wtMJQPAh/gK/3fC0mdPE+jrllOkHJHCUx5ugYdFjVQUwFC496gVMhT3H18RNsvLYOnVZ3wKILs9G6oje6TdqP7pP34cmLqAy9SpIIHntO8/JvaHqJu/7XQPV3pUBKS3ieeNHRfTngbMIOldMf6L9FGW9rjh9IIkmJNIMvvvgCbdq0waVLl1C3rpKLuHnzZsydOxcLFy609OUkmUTIvjPvKNaaqChyuXPUpgviD+rHjYunaNd/asJalls2O4ue4+aUeNXCEigAOS6WMWDmwIYrVjdpT0gObxdHlM7jhheRscjhbI9OlX1RNp+7+PvB19BiY20NF0crTO1dWfhyp+2+KvJe6aWtXdQLrSrkFed95u6rKJvPTQjSCvk90LVqfrH/A2sVxoCahTF3/3UcuPoY0bGxKOzljN7V/OCezT5RugArhz2D/UTjW3LwtTlM4Z6Z9g9CH7Cp/FljgpaikUJWTQ+g0KSgpZAsnaN0iuax0mZw5tEZMZKW1gU2enF4wciqI/F77d+FkF11eZXYltv8W+9fVMlVBdNOTcOH2z/ErzV/RVDualh/ZQO+3/+NsG2MPT5abD9vYGe0HXMALf7ZidXDq8P9Nb8/0w38pmW4focZwPP7wN6xyoQpDkfwqwFUiE/dscug8WOZCV5Y5AsA3j2pZM4y9zfimTLKtmJPIC8r7FYyOk3yZsVsixYtsGzZMvzwww9YtGgRsmXLhrJly2LTpk2oVavW6+2NJMNBEbL74kOTQlYL7QcUUMUsXFJOKxgZ1ap8Hmw8fdes7XM624s4qNeBwr9BSR+zjidpWiYXDl97nGyDGocgFMyZHT2CCgiPLZu/2HyVFNyGFx6FvJzxSZPiumxa3kfxy3/71iys86JS6KrVVhW+Fz21hCLX1PQuJwdbjKjvLwTzimO3TO5T98D84jNQPDM+jNubQ8vyeXS5vMkKWkdPYTswjMGioC3rVVZsk9LQGqAdusBYMDZ68Rxsvp4QOh8ZGykybemj5ZAEThA7/fA0quSugr+PjtJrHrv49DzcnRzEBdmFe2H4fvUZfPVWqcw18IRCyT0/UPcLIDb+go4+ZttMItozC+pFBSvpHF3LC0s2fDlIj6wkZXil32rNmjUTN4mEIopd/OYyfvtlfNuydIb4g0rB1KBkLnhmt8cjM+wDbJpi89TrFJ55XFh5NFfMUixO23Ut2e16BPkJoePsaPfKwt4YIooriQ9McWsocLWwiYnDAVjp5Ha/tisrhOeCgzfQLSgvJm2/ge0X7qNGkZwYULMQAvw8hYimZYWilpmzyUHR3rq84s81B9oKTD6WCkKWIrl5oebiOHy39zvd/erwBC20OlDI9t3QVwjZPqX7oHOJzui6uiseRzzWbdegQAN8Gfg93p13Aj+0KIq/tl3HyuO38HXLUsiUZMUGLw4l4AAJYYiKA+yyM34F6RpeIMr4LUkqYPF3/oEDB7BvX+IpP7zv4MGDKbVfkgwCf3fuufTQ7O03nb6bIYSsCpemOWTAziZpLxeX2ofWLWJ2OH9SFM/lgj7Vku8AHlqnsJj0te5U0sHkgYU80SOwQJKiMi2Ijo3Gk4gnuPbsmq4qyeop/bCjOpVCjMM5jO9RDie/aoQf25TBtUfhWH/qjrA3kJ5BfmLkbnIXJH91Ko/07hZl89lbhd/C54Gfm9yGQrZanmpCyD548UAI2S4luqDPuj64/uy6npD9NvgHvD//JL5uUhgVog5jUtcyCCjgadHPqiSdEhkORIQB+ycCczsBM1oASwcCl7YogwqMpFxIJJkdi8Xs0KFDcePGjUT3h4SEiMckWYvklrcNYVxXRoJVwPK+7pjbP9Bodz9FLrvy5w8IMtrw9Krv+VHj4viocTGjnl1Wir9oXgJv1/WHo601JnYPgF+OxJUp7g9tHdN6VzFrif1NC9nHLx+jy5ou6Lm2J64+vaoTtJExEVhxaQXe3vI23vlvBGIRhU+XnRRDJEbMO4rK320Sub6E43ppYzB27Gmr4OPBhXNaPMwhrQQtfbl5sudJ9Fiu7LnQpXgX/Hn4TyFkue2Q8kMw4fgEPSFL3q/0AaJjrDGqTTF4X5wP2wVd4LikpxC0KfU9KkkjmF5xbB7wayFgw2fA1Z1AyGHg7Gpgdlvgn0rKFC1WbSWSLIRVnIUBj87Ozjh+/DgKFSqkd/+VK1eEd/bZs2dIzzA+zM3NDU+fPoWra8bwbqZn6Jcs+b/1Znfgs2ue06e0nfMZgch40c7oLUZnsTqY1z0b2gX4Ci9oSlab+V4fLjyG5uXyiGlca0/eFlPI2BRUMo8rGpXywfbzD7Dh1B381LassA/wsaM3nmDL2bvi+QVyZEfbivlEn0x6q4SrFdnOqzvrpl052zljWuNpKOJeBAvPL8L3+xKW21mN/KXGKPSeegSHrilL6Tzms/pVRaX8HuJ7j7/FGL917eFz4d2tX8JHNLdx+ZVTxjICFPNf7f5K1+xlSNOCTfFp1U9FE9iJBycQlCcIv9X6DR9v/xg7QxImlvEYzmgyA043D8NmhmbOvX9DxHaYCWvZFJUxiXyuNE+tHJH0dtk8gMG7AdfEF0USSUbCEr1m8V85BwcH3L17N5GYvX37Nmxt09cfTcmbqcw2Lp0ryaYdLaxiUgiaagRKr6gTscr5uqNEbhfE0KJmYwXbFPaoqYMalh+7JW5scmpTMS/8vV2EaOWwg5/XnsWd0Jdi+9YV86Ja4Zzi4oBL7uV83YQ1gtmtrzvAIbWwBrNl7eFkm1BNDosKQ691vVArXy3R/KTF1cFVfCbmFasw7eGzpSewdkRNnVjvFlgAkTExsLaySneWitcVsoQpB4Tjcylo99zagw+2fZBI0F58chE91vbAjAYTkT2gL6wPThb3x2bzkMlHGRk2TK3/LPntXjwGNnwOvPWPkvggkWQBLK7Mdu7cWQjX5cuXC8VMnjx5glatWsHb2xsLFixAekZWZlMeViub/LUj2e1YTdszsi68XGRcjikYcN9t0j4cjK9AJkdN/5wY172SyQat1ITpBrww4bCFuPh9d7K3ER34yREbG4uw6DB0X9NddPKboknBJvi08lfoPeUIjtx4kujxpUOCRSRY8vsaKy68VJHLfaX1ID2sELBS/eehPzH99HS9+5lla2NlI6wFWrqV6CYsBnUW1BEiuJFfIzEprNWyVsJ/rFLSsyTmNpsD66lNEOvuh+jmfyHW2j7DRONlaKIjgbhYJVUhNgaIfgnY2CvxU7w/6qVlnfz0wR6dA6wcbt72fJ8PL8uBEZIMTapWZn/77TfUrFkTBQoUQIUKFcR9R48ehY+PD2bOnPnqey3JsLAJidFNP6013VlOzfBHh3Jwdkj5bvDMBAW/uUKW7L708I0LWQpDpnQxsoz5sxfuPhNVYC7r969RCJUKeOgq2aawtraGs60zZjadKYYBXHl6JdE2jf0aJylkCfehVF43kxPQGB0XExeHbefuY/KuKzgn7BpA6bxu6FejoJiexmNujgBPTXqW6on119brbBefVvkU1fJWE4kFTDv4af9P4n4fJx/0KNkD887OE0KWWbhDyg1BVEwkfq32LXptGoTw6HCRuvBOuUGIvLYT9jn8EdnoV1jb2OumvElSCXpVKVaPzAYOTwOe3lSiwgrVVkbwuuYGlg0BHFyB4OFArtLKYAFzvLIXN1omfm/sA/wbvNbHkUgyChb/FcybN6/wzM6ePRvHjh0TObO9e/cWFVuOtJVkPdjBz85yX49s+GPjBVy6H6b3eOm8rhjZpAQq5ndPkW7/zIy5wxK021OwvakKIz3SjCnrOGGvGJGrZcvZe+JW2c8D0/tUSVZkU9A62jgKT6wxMdvUryUOX3+C4yFPk4zd4ifnUAYbK31RStH99EU0Ok3Yg/N39b8nt52/L25s7pvZt4ryOmkkaJkXy/G4HNbAhrg+pfqglX8rxMTGYNiWYfi55s+ws7LDhBMTML3xLLg5uCG/a36Rhzu10VTcvJ8NnjaxKBQTh2n1xmLA1hH4JfgbVIixhuOcjojpNB92tjawkUI2dWG19d5pYFYbZalfy7G5yq18V6DdVGB6c2BSXaBoY6D9dPOGO7C6a9H+mJfBLJFkSZtBRkfaDFIP0QQWB5y9E4rTt0KFP69ifg/k93QSlTtbM3M+szIUphW+3YinL6LSZUNdeGQ0Gv25HTceJf2HkoJ2Tv/AJLNdOfmKqQXf7v3W6ONsChtbbzKu3s6O9xec0g1tILwwer9hMSFGGdd1/VG4sA1wVG4uN0fdFLVmf+9MdHFlSJm8blg8ODjZavKbsBvwRliNpRWDQxLY3KcOQ/jvzEOsPH4Hv7YvIaa07b/yGIXdHOB1cT7sN32GiLaTEcdqXMghIWSFoHF0A3qvA3IUNq8KKHk1Hl8FxlYDIpP+fkPlfkqVdnQV5evizRSBm9S5YfPXhi+AeP+zWQzYBuQpb/72EklWshmonD59GtevX0dkpH6Y/FtvabpnJVkKdamXy81KJ7nEUujrbFcpHybvTFypNEanKr7iIsLRYFpVakB/7Ky915IVsoQjbPdefqhrTrNUyKpNYYM39xWC9vcOpXSCtn4Jb/zRoTx+33ge/WccRLimMezHtWeF0P2hdRnY21mLdIPkOBHyVDTd1S/pLQRiWsEKLW96lWvrhIod6w6ezo5Yc+IOnkfEoIZ/TjQp5q4I2Q2fiG0cFvdVqn/selcrcy+fAlMbS0GbmlBsbvo6eSFLDk5RLAYFawJXtiuxWg8vAT4lTT+HjVwUwOaKWc9CgHcSryeRZDIs/s19+fJllCtXDqVLlxZTwNj4xVvr1q3FTSKRvDq0YXDSlTl5oKxE9g4u+MYaepgSMGNP8tPGVCZuv4yX8QMOtLD6yI57QyHL6KkNbTegkFshPUE7YutgNCzlI0YLc6AEhezAmYcwffdVPSGrQmtCqzG78DAsEp81K2Hevu64jEhGVKRjaIOo4Osh8o5pkcjtYgvvFxd0QlYQG4PYqAhEDNwH5PRPuJ+Cdmar+GlRWQQuy9M7yuV/9f8pnb9K8Robq4zSPbvSvOfQU0tBW6lXwn27/1IGISSFhx+QP9C89whmfFf6/n6WSNJUzI4YMQIFCxbEvXv34OTkhFOnTmH79u0ICAjA1q1bU3TnJJKsiKujHcZ0TXrqGMXupJ4Bb9SDzGism4/N9+Ex99bYsAJWH5mFOrjcYN19TfyaYmTlL7Hm6AtMbjBdJ2jtre3xfbVfcODqQ6w6flsIfTad7bmc9CSrl1GxGDr7sBiokNPZ/pX3Nb3BxY9Zfasil6sjftl4Cc/cSyC62vu6x2PLdMTLJqNwIiw74vpsBHIUUR5gE1KH6UBcYvGf6eCIV1ZK901Uhgh87wN856Ms6x+YrEzQet0pWVHhij921XvA2g+BOycse82Qg0AOzcXGzYPKqNekYBpC53mKXSQpKvYAynWSlhJJlsJim8GePXuwZcsW5MzJ5UNrcatevTp+/PFHDB8+HEeOHEmdPZVIsggUqJxatWJYdfyx8bxoqlL9ovSCNijpg/cbFkU+D6c3GrPErFdL4D6baqqiJ5TjWJk0cD30Oj6t8qUuteD6o/yY1GA6hm4ZgPcqfYCi7qXQ8I/dIk+WmcZ1f9tm1vvfexYhjl2HAF+M2XopRT9bWkEbRA5ne6x/pwZGbbqAbtOOYVavd0A3mXXoTUQ2/RPHb4WjfH4PWPFbo98mYHoLoOmvQO7ygF02ZGooKJ+GAFObAM8Mxjw/ugysHwnsHa1YLlxyAzav4LSjfYOjZDf+T1n+54CCR+bZgnQwrksrXlmtTa4BkRYYnr++m4CdfwBHZuk3mvmUBgIHASVayqqsJMth8U9yTEwMXFxcxP8paG/duoVixYqJqK5z586lxj5KJFlS0JbI7Yq/OpZHREysSA7gn7pCXs4pPnHMXNjxz/G65jancV+Z52pMcLORbNy2a+hUpTuyO9ih1+TDuvit6buV8azzWszDjou3cTQ0DMuGVBN/6y/de64bGGEOK4/dRp/qfsmK2YI5nREVE5tkw1p6gfvo5mQvxh2zsfLq/XC41PxAiB0rKztULpgtYWAGI6AGbleW1zO7kFWrstOaJhayWhiXRbE77IDlYpbHkR5XClkSNBQIfwi4+1r2OrSAhGoGzbCCHhOd9F9kVpTXvK+Mqw0cDNT+BLh1VBHXLrkAt3yKwB0TCLQeDxQITr7aK5FkEiz+i0ivLCO5aDWoWrUqfvnlF9jb22PChAmJpoJJJJLXw8nBFpyT5ZE/+aXy1Oalhc1p3YMKCJ+tMaJi4jB26yXMP3BDiORL95VGLQ5dKJ7LFZfuhWPk4hNYefy2yDFeOjRYDDy4dP++Rfv8ODxS2DaSo0dQAdFglZFQo8+K5VaKCyRRP7wqZrKCkKXQPDRdXySa4ukNZQhBxe7K8r258Pv5v++V/7NZr1JvgE13FI9+1YGrCWOFk4R+2b1jEr4OHALYJUzEMwqtE8fmKVVcvg/Fa+5yioXkxRPg2q6E+K4t3wI9lgPWWeC8SySvImY///xzPH+u/OH55ptv0Lx5c9SoUQM5cuTA/Pnz5UGVSDJ4NBhTCyhcmSfLkH1vVwexDJ/N1hq9gv0wb/91PDfSeKWFzVpNS+cS/2dsFi0HjBFT/b5z910TgvZuaATuIgIFc2ZHz2A/Mbr3/rMIhL2MFsvp7zUsJt6PCQpsfHJ1tOxXFrcPi1Dirkzh5eIgrAj2ZuSwqvFzD59HiOYz92x2okrOaml6HR+cpca97p9g/vb7xyti1hJYCaVdgXAQAhvrru0GDk0Dqr+rCMrkLooK1gLc8wOnVyhfM3XAr5piIzAFq6/7xilCVlth5s0YHJgQdldpGpPoH0de4IXeViwpLj7K940c+5v1xGyjRo10/y9SpAjOnj2LR48ewcODc7/lL3OJJKPyIioGh649xpj/LorJYir5PLKJymX3QD88DIvA+O4BGDBTPxJLhb8CfmhdGo1K5cafmy5g4aGbOlsCo9voeX27bhHUKuaN0f9dwrOIaF3U1pIjIWg9erdeLixjtihyfVwVIVwqjxtyZLfHw+f6kYCmeKtcXhxJYqIaX2vegEBh3UgOivyFB29i6q6rBvvogYG1CqFWUS85KjZNiQMeW+BdvX8OirHYAkIOJfzfzVdpAiP7xgOlWgNNfgXWfqQvOrXkqQB0nAWseFuxRLCZq+dKwCqZP8UUXndPWravd09JMas7ftFK1Xr338ChqUDYPeV+Clv/RkDNDwGv4oB9MtVxSbolRYx3np6eKfEyEonkDU3xonAVF5+suNrbCr/o6C0X8e9/FxNtzwSDH9acxfKjtzCzb1VcffAcq4fXwNRdV7D0cIgQpGqFkx7fPO7Z0GjUdtwPi0hU1Vxx7BbWnryNPzuWx/gelcR7qlFbxhIKGLN1+PpRdAzwxdctS4miV6cq+THayH4a4u5kJ8Tzs5dRuPssAgsP3UDoi2idiOXr9K9RUFgb7JKJQqP3t9fU/dh7+ZGRfXws9r9zFV981aIUHDJAKkLmxMJiCr//LS7AWJmO6OLkry4LgT7rlSrqmRUJCQf0yAb0BSp0A57dAW4dBhp8qwxQ4LCEVMk3lsUlXbPdi0fA5AbKYAvDx86tAc6vBZr/CZTtkLzdQ5KxJ4D16dPHrBecMmXKK+3ITz/9hJEjR4rorz///NPkdgsXLsQXX3yBq1evwt/fHz///DOaNm1q9vvICWCSrAoFGT2sq47fwoqjt0TF1N3JHm0r5hUJCUuPhuB/y04pS+kmYPXxp7Zl8NWKU+hSJT8qF/TEvdAIscTOCCwK5Dq/bcXtp0k3aTF2jGkNtAGwK3/RIRPLpRo+a1oCPYILgMEO7cftxsmQUJPbstLKkbqVCniIaikbzmgFeBIeJfQLG9k4IcycOK7wiGh8vvwklhwOSXbbL5qXQNeqBWSFNi1gpXNsMPDggnnb+5QC+v9nWYTVrSPAhNrK/wvVUVIi/g1IeJz+1TLtFJHKwQXP7yuv7+ACHIu34TE2ix5m/uk1972ZlbvrT2Drj+bv67unFF9tVoffF+NrJVTRTcFfDH02APkqv8JFjiTDTACbNm2aSCyoUKFCijdKHDhwAOPHj0fZsmWT3G737t3o3LmziAGjV3fOnDliYMPhw4dFY5pEIjGdEXvo2iMMnXMkURrBf+fuwTO7Pf7qVB4Te1RC3+kHhdAzBsP61ef3nHoAXs4O8HFzELnx9Lu6ZrNLVsgS+mWn7LyCz5uVxLIjyYtEdbBBr2p+sLexwoKBQWIa2c/rzumNuVUFN6PL/L1ddKJSbZZi9VjF3AIqxT2r0mbt4/Yr6BEkfYppRtVBwOr3zdx2iOKXtAT6W72KKRaFK9sAW/uESV6ES9lMFODNvQDglEO5jxXBmAjggwvKeGFLsXNUJoBt/wXIWSyh8YtJCpe2JJ485lcDcJIrpuKC4fq+5IWsui2Pb/vp0kObmSuzQ4cOxdy5c4Wg7d27N7p165Yi9oKwsDBUrFgRY8aMwXfffYfy5cubrMx27NhRNJ+tWrVKd19gYKB4zrhx48x6P1mZlaQWLyKjYWttjQfPI4Q4PH7zqagEsgpY3tcd0bGxOlFFoqJjEYs4XHsYLpqkHG2tUc7XXVRPUzJ6KzI6FkduPEbXiftMilS1MYs2Ai73j9p43uR2bAKrUtATQ2Yf1rt/58d1MHzuUbHsbg58v6P/a4j6f2xDyBPzhjHM7FsFNfy9xDhcO2s7vIiKwuy9IeL5TDugoC7k5SBWWB1sLKi4mSAyOgaTdlzBL+vNjx2c3a8qqhXJaZmfj5UgVpAMUwcYzm9tr4iuNBy1m27hMj4HQTy5oTQ80ZPK6qzhcrIh9KoyH5aC0BKiI4GLG4F5XZSvq70D+NcHZrRSpoAlBZMPGv2Q2JfJK0EK3ohQZfgCvb8UzRSj/B5WEylYnWUsl7OX0mjGr1l59S4BHF8A7PpLSWng9r3XA3krye+ZiGfA0kHA2QTNkCT8OfvwonIRIklzLNFrZv92HD16NG7fvo2PPvoIK1euhK+vLzp06ID169e/VqWWIpljcevXr2/WwAbD7diQxvtNERERIQ6I9iaRpHQCAD2o607dEf/O2Xcd1X/6D+3H7UH/GQfRYfweVPlhk2iIYoWU23PJf9WJW2jxz040HLUd/aYfRLfJ+1Hp200YueQEbj99IURoSvHpkhNJClkSER2Lb1edRreq+UWzlikovvO4JxYBrHpee6gknZgD3+/+s5d61dLkuHj3mRCyZx+dRfOlzREa9Qi9qvliZJMS+LBhURTydhBjcr/a/RUiWAl7TTji9vID8z8TOX/3mWVC9uUTZToVq3vsttYK2ZNLgYl1gKjniuiRaI7PC+DcWmByQ2Wpf1ozYOcooPtSwKNg0kK291rAOvnItkSwElu4juKvpPDZN1ZpImszMemIr1JtgCY/JxayPMd3jini+I/iwOx2wOz2wKhSwKx2SioB82Upoil2OSzh9+LAvK5KJNiURsDEusrFUP8tQN4ApbKYq7QUsoTnRk2fMAc27nHohiTDYdGlvoODg1jm37hxI06fPo1SpUphyJAh8PPzExVWS5k3b56wCNA2YA537tyBj4+P3n38mvebgq9NZa/eKMIlkpTkZXSM8JDWK+6DPtMO4J8tFxM1P7FCO2H7ZbQbt1sI3mVHQ/Du/GM4fzfMaJNUk7924MbjcNGY9bqcuvVUl+OaHCdCnuLG4xeicSopvyuHDHzbshQKezmLv6P0zHK53zaJEbzGsLWxNvszUmDXLuEphGz/Df1xM+wmuqzugocvH8DONg5x1tH4ds+3WH5pOVZdXpUigpafxpykA739TKaZLJGQnVQPeHhRETSqoFWF7IqhwJ3jwJTGUtBq4fHZ/Q+woDtw+1jC/dt/BY7MBgZtB5r9oUzFoujkLVdZoNVYYPAewCnnqw8UYINQ2Y7AiONAxZ7AkoFANndg2EGlUuvsrWxHcVu8mdIQ1npsYn8sz/Pl7cCk+sDl/xJHerH6SoH+4LxSdR5XDTg2NyFLVoXfO7RWbP4G6LUKKFI/a+QKm0UsYGPhRcurTIWTpDmvvG7FMbZs9mBVllPBLOXGjRui2Wv27NlwdLRwqccC2FTGErV64/tKJCkFm4M+XXISbSrkxS/rzuJgEjFQ5NStUHyy+DjK5XNPcjuK3+6T9r32/jFOauPpuxY9Z+eFByiVx/SSTmChHMhmZ42OlX2x7p0auPxDU1z6oamoOFfxM996lMfNUaQK3HgUbtb2gYU8kd/DBV/s+gIvY5Q/6A9fPhSC9vzj8zohq0JBe+DOAURy+f4Voee2hr8FlgGuPBc2c3teBWz8ImFJnMvUFLQXNijNQhSyqsBhLNP235Ql9awOK9QhhxOGFxiy4zel4YeCl+Luy8fKjaN9y7SPTw94zcQJVlg59av+V8A7x5XMWY8CACexvX9Oeb8v7isV2/yBxu0MEWHAwh5J2xPsnZVKMpMS1DgpUxyZCZxcYnncWKbGCsgfbP7mnJjnWTg1d0iSHsQsl+zpm23QoAGKFi2KEydO4N9//8X169fh7Oxs0RsfOnQI9+7dE35ZW1tbcdu2bRv+/vtv8X9jAjlXrly4e1f/DzO/5v1JVZPptdDeJBItFGGvapWJio3D+buhKJ7bFYsO30RlPw+MqOePT5uWwPB6RUROqiFrTt6Bh5M9Agp4JPnat56+xNZz9xBj4fIyBxxo/09Lg6UC2FS8FH2unaooAwZ4U8e/8vg5O9qhf03zpwB2rppfWB9YnTWHZy+jERUTg8mNJsPHKWGFhoK246qOekKWfFT5IwT4BMDekglPBrDi3KBkLng4mVfdYeZsLjczL84pqFg9ZLOOCoXNgh7Aqnf0K3Ul3gLqjLS8ypQZYWVyxx9Jb8Ol5Q2fAz/7KX5SemspYi09fqbyYlUYti8ivuK/h5laoFaC1ceNQevA3tHK1LKkYPLB9b1KddYcmKNKz60k4fgHDzP/aJTrnLz3WZKxxSztBLlz5xYRWkwSYIWTMVmMxWKV1lLq1asnxPDRo0d1t4CAAHTt2lX838Ym8R/ToKAgbN68We8+Wh54v0RiabMWl7d3XXyAcdsuidveyw+FT5W+VnPgsvriQzdRr4QPTt58iqVDquGfzhVF8xcFZE5nB4zrVgmrh1fXW7bn89jB36SM6Yswldn7ruNFZKxRAf48IloIT+bG8v0Y5D915xXcfPQCT8IjRRyVNazg62lZbmJut2x49Nz4H9nh9fxFU1TYyyhxrLafv48xWy8JC8Wxm09QLJcLGpbUtwIZo0AOJ3SrWkA0i33YqFiy29Pa8L8WJWFnYwdPR0/MaTZHT9AaQiHbvmh7OFra4GMEni9enJhjg/hS7KMFtgQuB3ddqC9oDaGQbTvR8malNwGtEmyyYTOSIayMcsyqscde6z0jgctbzN/+wCTlOebAC0cKTU7W2jsW2PG7IoZpCeA42ZSCwvro7OS3K9FCsRaYy/2zwONrr7VrmQ42c7H5LjloD6n9sUwyyKCYbQ5hWkD+/PlRqFAhUUHlzRhLliwx6/VcXFwSxWllz55djMVV7+/Rowfy5s2r89TSllCrVi38/vvvommMntuDBw9iwgQLRhhKsjwUeWtO3BYNWRwIoCW/pxPea1AUDUv56CUPGINimF30FKoFc2QXWaSbTt/Va7RiQ1WjUrmEv7SApxPGb1eaEe6EvkSZfMlH9NwNfZmoiV0I2cho0WDm7+2MX9qVE57dlcdvYVrvKsL3+uGiYxjTtSIK5cyOtpXy4Yc1Z0QcVnIwd7V52dxoM3a33v0sPg2pXURYC1joXXrkprgA4DhaLW0r5sOfncoLP/D6U8a97Nznqb0rCwE8/+ANLB4cLI7PVytPJ4rZItntbTC+eyUUz+UaPzLWVgja8Q3Go9XyVom2f6vwW+hcvDNsrVPG+5bN3gbNy+URFzlfrzK9jxN6BKCojwtsLL24p6DttkRpAGLUkpYcRYD2015/WTw10Hp+/RsqQwAYIUVUz++6T4Beq4GcRRMee13CHyQ/MlbLs9uAOd8LFN3PbgErRyREbWkrfKzaNfwuZfyo/IFKzjZAmGgQal4snA5+Bq+ir7xrmQ6eryY/KRadwzOMb8PxwpzEZu/ypvdOkkKY/duewvJNj6ulfUFb9Q0ODhbZsp9//jk+/fRTMTRh2bJlMmNWYpGQZb7pbxuML9sxIuud+UfxadPiIvw+qYgsCqtKBdzhlyM7Wo7eZTReigJy1fHbIqZr0aAgIZ5Xn7gNRztrRJix/O9oayOGBBgTsmfvPBM38m2r0uhSNb94/RHzjghBzalUFIFlHW3RsnxeswYTtA/IJ3JkGSfGMbYUt7WLeaNbYH5RBWY1dvLOK+JmjMWHb+LW0xeY2L0S3m3gj4nbL+PI9SeIio1F4ZzOwlpQvUhO/LbhnBgLSzqM24NN79cUgnHG7qtYe/IOwiKiRYW7XcV8aB/gK/72q5mxJCYuBlNPTjW6D7tCduFe+D14ZfMSldyUgMeBx6ZF+TyYtusq1p28I84DPb/tKuVDu0qJ99FsWAk8tTSxkCX0017cpGSZpqemHq2Q5T7ujy8oUNBymVttXqPonNYU6LUm5QStrYXHgRXt5OwCrNw+uaY0YzE1wBBWZVnhZTNej5Wv/zloQ6D9JbmKMW0Ilk6kSk/fJ+kFfg80+QWo/p5ixbi6Q0mIoM+5cn+gWGPFXyttPJk/ZzazIHNmszbn7oSi0Z87kt2OwmTze7VQyCtpL3joiygMn3cEW8/dT/Y1WaFl1bfRn9sxt38gVhwLwdz9STckcvsBNQvpRBKrg5vP3MWwuUf0tmtaJpdozPpm5Wm9ynDtYl6Y2CNAiNDuk/eJ8bCmCCqcQ4jfu09fwiO7vfDD8v1oH5i55xoKezujXnFv9Jiy3yzxt+OjOqICTQ8p959C/NzdZxg48yAePU8Y3EDR/N8HtcX70S7B30i8hhXpCNZWwpurhQkFhs1ehuRwzCGsCCkpaFWUfYyDtZrgYGQfLRay2mYvQ1hV7DQnfQlaVjEPTwfWfqR/P5dzKVo3fKr/eVjVfOuflBELFID/BCji0xwChwJ1P08ci2X4mqOrmhfjREFU88OkXy85KI4ZrcVosaRo9rviEV7/mXmvS88uc1LToyUlvcBjr/qa6aXmz1R6XPmQIFVyZiWSjM6zl1G6Zf7k4N9hLoPzOUnBmC1OxTKHTWfuwsXRFq0r5BVpAclNlaJI6hGkPxqVS9706H7fWt+is+bEHfxv+Sk9IRtcOAf+7lQBg2Ydwu8bzmFO/0AxGcvH1SFRqgB9q+O7VcLIxcfh4+aIjuP3oNzXGxD442ZR4d158QG6BxbA9D3JhNFrjgsndrFSHPDdJpT+cj3q/r5VVJrfqa+/BNotsIAQuoSflZ+RAxBo8zBXyLYq0ipRUxhTDu6/uI8o/sFKQZR9tDW5j68tZDkmlSM1VdSUAxHbZV7yQ6rDymTFHkAdjciq8T7w9DqwfqT+56HAbfFXylW9+NqsppkDr0rZAJSU8OTr3Txgfh7p4WmvH9/Eamvw8OS3OzAZKN/N/IsYRobFysSLJKFlhMdTjBl2lkI2kyDFrCTL4Oxgi9XHb5u9/cpjt+DiaPoPMBuvuHRv7toGq3j06n7UqJj4NzyZRrMPGhU1mllKsdeqfF5881Ypk8+lkGXz2bsLjmLzmXuYsusqHoVFon+NQtj5cV3RlDa3f1Xx78b3asHbxUFYF56+iBZRWYa5tHnds4kK639nzfD5aY4fK8MqD8Ii0WvqfjQulUuX5FAitwt6BvuZTE8whqEXls1e/wv6X6KmMBtrG1iLCgzSJ9wvQ4HHZq8u84Geq/SbwkSYr136alSnIAh+WxG0jX8CKnQD2k0BijZKPPWKVgSK95SAIqRKPyU3NjmqvQtk80i+Und4pvnvH/5IGWbwOvB8ckJXqdZJb8cxrBTZPL7J4eYL1P1CNjBJsiRSzEqyDFxq59Qpc3keqSQFmIJVUFZuc5uIYmIzmWFn+6PnkXB3shNNY5VMRHPRT/t5sxLoFVzQZBMa+6Doka1bPD6g3eDv5NhulUSDFoWsyt1nL0VVkcv5pfK4IahwThT1dhbJBWO3XhIWAFaOH2ssACq8n17aZIaI6X/W8Mj490s4Bg+fR2LWvmvoHlRACO4FA4PgYGY0F+GI2pFVR6Ktf1u91AKOttWmHHg7eWN209nIkS2HeCxdwupcieZA6wnKSdOlFjgolc+uixRBSxHbZQGQP+j1lrZTS9ByUECReso0qvk9gDYTFEFLuwGF7P7xwJhA4NyalBO0HPPae42S72r0cXug9kilOz25qib9tC8eWfb+YeatxiQJz3Pr8crgBTXKSwu/J8q0U0bbsuLa4m/TQjV3eWUCmKnHJZJMjhx1Icky2Nlai6X75Ma6ajNVk8pA5WsxXmpQrcLoOmmfGIigwook/afbzz/AkNmHdEkCbKxiFZJL1HP6V8XVB+GYtvsKbjx6IaqwDOhnYgBJqpmIH4HDEBiNZQgrxZ8vPSGawhg3pvpkjVWZ7WxtkMstG9a9UxNHbzzB4WuP4WYkU5XNTi5JNMMZg+/HCwjDFAX6hHd/Uld4iF+lYUoVtI38GqGCdwVd/BYrtqqgjY2LTd9C1lDQuq5UrAVar6MqaO+eUCZZpRe/rBaK07A7yqQqdufzRkHbcYYyFGDfGGDzt/FRN/2VIQLFmr6+KKepmv7QzvOVGC2OlWUFk1V7XgAE9FKGB5jjHaVo5GtZAid+pQQUtKy61vsC2DsOuH1UaaDzLgUEDgGyuSU0m3HgQ9kOwLF5wPl1SnOYW17FcuFdQvns0vspyaJIMSvJMnBZv35JH9GJbg4UW8xT5TAAY1CkUQBuv/AAM/tWFQ1WFLQUsvSqDptzBL2C/TCmayUhaCmimSpgLULWAQdrG5HL+nmzkrpBBxTQyXkw2ZS159JDvD1XSS0wxsp4O8WUXpXFiN17zyJEtqsx1MEHHPhQMo8L7G1sRFOWNrYs5PELhL6MEk1ifG9zoJ1g35XE295/FiE+g2u2VxeaFLSVfColGohAQevhoFS8072Q1QrafFUSjzsVjzkqy+nGHktr6N99/gC4e0pZele5sg2Y2wXIVRrYN16/Anptt5KdmlLw+OQsAjT4Role4o+Drb1lDVB22YEyHYETi8zbnsK3gAVTpZKDwp43Tg+jv5sLGVa2iQW/+nX5rkBpZWVCVHTp+5RIsjhSzEpSDXZ9m6q8iSlTBqKNua0UdYb3G27PiVjKYAMrxCFOeEht4yPcjL2u+tr2NlYYUKOQ2WKW06xMCVm+/5azd0WSAfUk95uCdszWixhe1x9D5xzGjgsPsOPCfSEoKWhn7b0G12y2InaKf3TFvtvZiL+/6mjo5Py3fN/9Vx6Jpi6tkOWoV06f4gADraBlx/30PlWw4tgtpckqCZ3MfXB2sENUdIz4LDyWL6NicezGE7Hvc/ZdFw1p5opZWgl+W3/OxJvhtTE12Sul0wveCEmJ1dQSsqzsGXttds+zqpnUceQQgTOrgNXvKUMf2k4CFvdLmJ50bZdy00L/bOMfUufzmLu8zkqyOhKYQpDP4++OwrUBl9xKJq0h7gWAgD6KgBXb2yb2LnPYQlS8z5w/xKyiW/p9yOeYU30XYv3Vp9pJJJkRKWYlqQK72U/cfIIyed2F2NRCkbTv8iNU9vPUPUZv6uPnkULo5fNw0mt8ooA7cOUhAgp6iioim5DYePU4PFIsZbcsnwdNSucWgpWVwODCOfVENF/7YVikeN/iuV3QvWp+zNx3Pcn971PdD0VMxHKxkYuRU6yMqnpSzXD96q1SGDzrkBCyhGJwwIxD2PFxHVQt6InbT1/iz43nUSavm8hcPXbzKWbvuyaqoPSWMoOV3f3MsDXml6V8ZzXXx9VRl2urNnvxeHi7OooBCqqvlrYFvifzWpNrsuLx49/hQ9eeiH3iwAY1Z5aDDU6GcMKXK94ql0eI46R4t76/+HezkYaxXK6O4nUlaQiFLLM2KdC0Oaa8/8kNwNEVyJbDdNc+hWC+AMWbOqsd0G2R0vy1qI/xcaBCyP6UdpFRFLGRYcpUr5CDSse/VzEgaCjgmk/5PBxOMb1FQvYrhSt9qvT/nlwCbP9VmXbGiVIVugNF6iqvw6X9q7uAQ9OAsLvK8+h/ps+V1ej05nOWSDIhMmdWkipCdvfFByLSqbyvu6jyqaKVgnLI7MPYcvYefmpTBm+VyytEHBujWo/ZLbyZSwYH6wQthezSwzfh5eooGqf4XC5TG8LH/uhQHtkdbHDg6mP0q15QCFoKWXbRtx6zSzR/LR0SLDr3Gbs1accVPIuIFpY5Cms2bDnZ24jGrOT8nNyvOfuu4dvVZ/TuN/TkUpT+3ak8avh7CRE+Yv5RDK5VWFQtWV3lMAVjY1FH1PdH3/jPoK10n7z1FHsvPRR2hU4T9grrwKSeAfhy+SlxTOcOCMTuSw/xzcpT+KVdWVQq4ClSCJITjxxRy2lePafsx+UHicd28vlsSqtVzEukQrACzOxZnmstHk52YuRtw1K5RLyX4YQ1wngwpiq80oAByetDwbqoN3B2tRKZRR8mBa0QsteByQ2UpfR+m5IWtNw+NEQZNEA/J8XqjLcST89iJXPkzbTz/HI/140EDk1NGJ7AJAE2qHHfXHIB1d8FaEu5fQxYPljx4fZYoYzj3fOvYp0wpFQroPoHQNhtYE68cNVi76yI4WJNpKCVSFI5Z1aKWUmKQpG3+5IiZFVRxxgmClqu5lGMqh32FJEUtM3K5kGLf3biSryIojCloKW4nH/gBm49fYn6JbzReeJeUek0BYXk5J4BQoyFvozG0NqFdUKW1UnCqVIUtJzcxOauM7eeIre7k1jiP3v3GWysrFDUxxlu2eyFf5XL9JYKWq2Q5UhZVlsnbb+MUZsviOos76Nw57Sx5AYm9KuhJBrwvU7dfopuk/aJY8DKZ4cAXzHcgHvIQ73z4n1hCehStYAQ7l4uDuKxpKaYqdx79hJN/twh0gaS4ue2ZUSlNru9rTify46E4PTtZ+Kz8sKlUSkf0fT2v+UnhU/XEO7TlvdrJRl5JnlDQlaFgpZZpo+vKEL2xeOEEZ/9NivRVqaWzPl6FHwUv/vGAZu/Nr5dwVpKIkNKjbQ1F1omVowAjs9TfuGwolqlP5DdCwg5rFRWcxQCnHPFN4HF/7w/vwc8ugK4+yrb8pidX5/wurQdcKLU3ZOKJePEQmWylDHaT1equ68i5hkbxn1kYxgrxh4FlaYvempfN+tWIslEYlb+NEhSHFZURZNTvLHs4LXH6DB+j6ia7r2sH4Ej/K20cmpGJT8Jj0KbsbtRv4SPEEvsfGcVMykhSyiev1p5GiuGVUPQj1tw8e4zUaWlJUCFoos3NlnF0J9rZ4tPlhwXqQDaXio2On3QsBhK5nZNZJNQ4f1dAwsI0WZsGMP3rUqLZf5vV57G3APKpK/e1QqKqnByQpb8tfmCGFTgZK/8HWbFVjmuwKhNF/A4PEpUuinU2YjWtmI+FM/lIiZ2VcrvATtrK7PyW59HROO7VWeSFbKE27EqzHPG89yhsq9ILCC8IOg37SB2XzbuqWVFnFFcHJwgSSv4w2bgWV05QslN5TQqVcgSVi0p1JIyONP/6uiidOKbErKElc05Hd68oL1/XhGy/Cz09bIau+1nRcxr7RCs1Nb8SJmyRluAs7dSaT02V2la6zAdWDJAEbQUsnU+BSbWURIH8lQEqg5UKrjGxubSV1z8rOUT1p7fBzZ9CZxZqT/2Nk8FZUBFkfrpM+FCIkkDZM6sJEWhwAso4InJvQKE+FI5EfJUT8hSk43qUD5+Od8a8wcGikqsVtDSh9qgpA/uh0UkOYZVC6u7R64/QasKeUUDlFbIsirIqqyPi6MQsvsvP0Sr0bvEKFrDUAA2ObUftxvrT91BeGS08JNGRMUgLCJK/Ev7wotI/jGMM1qBJPuuPBLi8+ydZyJXdtuHtVGrWE4sOJgwwpbHiJXaPzqUEyLb0Js7bfdVITb5/6I+Lpg3IFBYIQgfY8wV95/Ha/LOK/hw0XHcfvJSVD7NHUTA5jVzm+Joy6Bf1sbGSlSt2XjHyjFv2exsMa1PFfFZSud1FeeYFMyZHV+2KImtH9ZGXo9sIiJNkkbQs9p6LFCqjf79R+foC1nPQkDfTYCjW9IVQDaCnVicWMiyAtpyjCIitYKWFc43NaGKHtndfyWMhaVAndwQOL08sa835BAwtyNwcAoQ+UL5XBSy//0AXN4KLOip5Oc2+0MRsjNaAndOAMuHArcOKz5ZUwMQwh8CZ9cY/9xsHGOEGcUqb/w/q92MGRtXDTi5WF/IkltHgPndgF1/KfspkUikmJWkrqA1HBpgKGRFEoGNtchfpdD09dSvNJTO64Yd55VmKnNh8xXHxWrxck4QshRTXLYfMPMQIpMYikCB+8HCY7gXGiGaq649DMePa86i/qhtCPppi/CsLjwUgm9alhJVWNoctCw9EoLPl50UAu/XdmXFOFv+7aKoVoXs6K4VxWenkP+zY/lEgpajcimW31twTMR+FfF2FoLWlAf2f81LonOV/CarycY4ePVxksfBENpE6N81hOKW1Vo2iC0eFIxLPzQVtw3v1kTXqvmF4FVjwCTpQdCaEF9cyjZHyBJWeUu2BHxK6Td7NfsNKN0G6DgzQdBS8NX8UImfehPYZgMu/Qfk9Ff2ZV5XReAmxYbPgJdPlLzcbb8k3K8K2vyBipBlHBlhJXbtx0r1umwn06/LgRHaUcTstORxEAK/F/BXOeCv8sC6T5Tq+cyWwMvEfno9tv4I3DigCGKJJIsj/7JIUgWKKaYK9AjyS/SYezY7NCmtCFkVClpWE2sX1Z9oRd/qy2jLKjlcejdsLqpS0FN00atCduquK2ZNA/PLmR05nO0x+r+LaPjndszed10MOGATGpMIvlh2EjV/+Q9Fc7lgVMfyqFEkp97zWV3+dtVpUVldePAmfll3FrP7BQqxTSHLKmvf6QfQa+oBMUnMUNDys/CCgBXitmN348e1Z1E6j5tINDCE4rh9QD5xzCzBsIlLhRcW9Oxy/O6Iev6oV8JbJCRwn5KC55JVYVal+VkoYJPLzpW8Ydi9z7B9Y/g3UKwD5ngyaZxmo1PvdYqgpZBtEp9awCVwTuiioKUw5oheTrN6UzYDpgzQM0tbwLH5+pXn5AQtq7i0JWiHEFDQjg1OELKEn53jh9kId9+4d17Aaqua5yWqsaGKP3lmK+DCRiD0lvIaHn5K3i3FtDns/EP5jK+CuXO4JZIMgBSzkteCS+4c6arkviYQGRWD0BdReLtuEQyoWUjvMXo9OTFL+xwu2S88eAMz917T25YpB3ncLfOF5XHLJmK+tKw+cVt04LOiyOohhaU5MImA3tXpu/X3y/Dz9J56QFSRp/etgi+aldB7/PhNxSJRyCs7pu+5hr83X8CKYdV1QpZeYEaSMUmAFVouyavkFp9FqWQxzuu9+kXxwaJjwiNrCKur9CZzOITIlDUTDkjQQosAs3HXjqgphDNh9fiTxsWx/aM6aF8pn867K8mAUFg9vgbM72r88f0TgKNz9SuJ5ghaVnNVIavClAQK2ndPv1khq35O17xKTBZtFOZyepki9Jgv23ay6ala/MzM2GUcFwUuPa6mYNOWWqGOjQKmNlXsAoaUfEuxN5jLla2WiVk2lNGPy6ixnaOA/ZMUIS0azWSFV5JxkWJW8lpC9tL956j28xZROVTFKYXs88gYjNp0XnhS+1QrKASttmLIpjBOzOJz+DrLj9zCZ8tOisfUZidCLyf9ptnjq7jJVR251E+/LMWrIX9sPI9pu66K6uLdZ8n/AWAKg2d2B0zddTXZbSlGf99wTnwepgmogpbJCPMHBOH3Deex5oTiS6VgZ2yVKmRVCnplh6+nEw5fSxCq7Srlw5oTt4WQndGnCr5dfRpLDoeY3I8zt5+h/fjdFgna4rlcdfaOWkW9MKdfoBiDG/zjZrwz/yh+WX8O36w6jQajtgvbhb+PSyI7hCSDoI3fUiuVxoYYrBwOnFhioaB1Mp4jS0HLKVVvOsmAldCKPQEnT6XqaS70tnKJf/N3QK4yQO2RxrdrPkoZwLD6fSV+i41apmAVnMeB1gL6YJmCoEKRmz2ncsvmCTy1YF8pupm8YA4UsZu/AX4trHiX6XNe8z4wqqRiwXhyTdlGIsmASDEreS0hS1EW+iIa7y44Gi9oo/EiOlYI2Rl7ruHqw3B0mrAHA2sWwuEvGmBs14o6bykF7WfLToivW1fMK5axKVYn96yM/z6oje0f1hYJBcdvPBVd8+XyueHAZ/VFyoApmpbJLfytTAtY/04N9Az2SyRoOelK25xmCg41mLv/urAImAM/P7elfYKC9vf25bBoUDDsbK2EVUELP7tWyLIaOqNPVfyw5gyWHQ3RVUw5GpcNY2wS47+GQvazpiVEQoDaFKYK2mFzDicZK2ZIv+qFhB/3n84VxDAIJi4w3swQNvHxAuXS/bD4CWExiWwKolkuOkYcCzbK8aYmHkjSiOhI5cZf+dObJwhZN1/g7cPAR5eB0u0Tti/WFCjbDgi9k9jjSsGTERqPKKwr9VIEvKVd/xTelXoq9ghWMY1xdLYidut/rSQePL5qOpaMWbaE4peDGwgr1WxM+/gq8N4Z5WbuFDBDb3BysHo7q40Sn2boG6YgvvwfMKGWcqFj2HAmSTt4MWnqgpIXXW+qmTIDIMWs5JVgZW789kuiu139fUhBu/DQTfy6/qwQsioUtEwWoPDJ7Z5NCCYKWHa5s3kqPCpG+ErZFMbmJtoA/jt3TzRKLRsaLEapvt+gGGb0rSqW/FuUy21U0LJ6ydcbt+2SaPYqkCM7PmxUDD2DCui2aVY2t0gHqFnUK9nPyAlgh66Z6bMTIi4Op2+Hiv9TR1Yt5CmEnZ2VFbpWLYChdYoYfV6J3C46IatOEmMOLochTNxxRURmfb3ylGjsYmSYttmL08Io8rUpBz6uDvixbRnx3ubA492psi++bVlKjKxl01lSsOrbZ9oBYTU4d+eZyAJmRZpjhili2fhGwVv40zUo8tla1Pl9K6bvuYrwiGhESVH75qGIfXZLaRiimOowW6nGUsj2WadUCjn1662/FEFLIcsGsXWfAs5e8fFcGiF77xRwYErGELSselLMFq5n/nNyFFYqpIXrKM1e904b305tCivTTmk0M/paRYAOMxIq1jyWd44DdT8Heq9V9m1CbeBbL+V2Y79l+0obhWue5Kefbf898XhhQ1iNZqKDJH1AEXtxM3B+Q2JBy4uTtR8pE+mkoBXInFnJK8Emn5/blhXCcFP8EAQK2v8t1zRHxPNOfX/R4d5y9E4xVnZO/0Ax3KCSn4d4Tvtxe0SkFquz0TFx6DvtgGjO4jI5G5o4ySoOcWJMK4USl90p3shvG84hp7O9EHqDaxfGqI3nhYClGNx0+i7+2XJBNFwRVho5pIHijbaHjafvJvMZrcyuyqqwCknB9tXKUyI2S6QoDA0WwxoC/DyMPscvR3YhfumtZUxZi3J5MLyuvxD0/DyEx/i9BUcxvlslDJx1CLWLeumlFqixXe/MO4rZ/asip7ODRckBbNjitLAPFh43a3tOC+P+nbj5FP9suSjOVcfKvsI7vP+qfpYwG+a+X30GE7ZdxryBgfA1GFcseQNCdlI94PkDRbA0+gHouwVwclf8mVu+U/yfvVYDb/2tCN65nZVxt8yfpeC1y65U7ChkOfJVeCwjgaqD0nfWKSusVh5A8DDg4GTzntPkV0WoT22cuNmLI2oPT0+I9qKgndtJEay0DvCYkRz+yvSv3GWV46N6zHls288AfKso0VucNKZl9z9KEsReZtaa8buncl9FzJgaakHYyHdoinmfnZFgNw8A+YMT9lmSdkJ2YU/l+6DdVKBow/hJfS8VW8jFTcq0vb4blYEfprzdWQT5F0XyyjAx4N8uFcV0LlNQyPYK9hNClqKGVb0uE/cKcYc4KyFkmcP6SZPiIm6qx5T9upSB/604JRq1nB1thUimkCUcEtB5wl70qe6Hje/VFE1J7O4/ePURPmlSQghIxkcNn3cE5+6Giclhb9f1xw+tywjRSJtB2XxuaFomfukvCcHml9OyuepMP5i5V8l/JU9fROHSvec4cysUg2cdMvqctSfvCPvD0iHVsP/T+mhfyRc/rj2T6MJAFbRTelZGkzK5hE1Rey4oaDe9X8tiIaty8d4zhDwxv9q2+NBNXYWbntp1p+7g06bFTW7PvGDaUozFeklSiegXCUKWUNCt/xTIXTpByBIuPU9rBoQ/AC6sTxBlFGhTGgNRz/WFLNn0ldJ5n94rtKxCu+RWhHdy5C4PFKiu/F8rJilke64AGv+oCFdtfi63s7EHWv4LdF8GDNgKDNymJCLwh1QrMjgy178+14iNR3ld3qKIlWrvJL+v3iWAqoOT9yLfPJhw/s3h8IzkI8wkqQer9beOKUKWFyqMfxMT6DYAMdEJQpY8OK9cdEmkmJW8HhRR47pVMpp7WsHXHe/ULyqipbLbJ/zyp6BtN24P6vy2VQhZQqFKC0LT0rn1XoOCtsbP/+mErMqgWoWV14qIRt3ftmLYnCPoPe2gWP7m61LIqkXVC/fC8PP6s2DkrV18RBQnjzFKi9VEUwWIqw/CRPOauVTM7y48vz+sOauXI+tob42uk5UxtCqG+bu0Zfy87iyiY2Px75YLItuWx48VZu0ErUfPo/DlipM4fTMU1gaTmXguuPT/qlmuTI6wBFbZXRxtdZ7fOsW8E6VRGMLxwlN3X5GC9k1BkWUo4i5uBP6ukCBkVYKGAtm9Aa8SSiasytMbwKT6wNQmCUKW+JQGSrVKPFEsPcLqaFXSatIAAHj8SURBVINvFJGoFaJamLrA6jS5f04Rr/S1iqo1Y8VKKcKY9oMO8fm5ujG92ZRYLT7mVQw4vgAYHaD4bbVLxBSqM95S0gwCegE1PtDfBwpjihVOFqv1kemKa/4goM964w13hpgb86VC4Stju9IOfo/lrQAUqpNwnypo/yqbIGTViL1anwAxxgf3ZCWkzUDyWrDK9tPas0azSo/efCLG0TYq5YOFg4J0VVjC6isrdSoX74XhwbMI4fWkRtOKV8Nq4TdvlUL7AF+xxF7UxxWfNyspxCstAcb8nmyi+q5ladgbCG4K2q9alMQHDYuK6VknQ0KFnaGYj4to4OKSf3Z7W+FT5USw5BhYq7DIoWXTGqlT3Eu8d+1ft+oJWXp75w4IxJSdV0RFltBDzCletFmM7x4gGtjoS87j7ojjN58KYVw8twtCHivHokAOJ0TFxsIuBa9HmfNrCayYh0fECCE7q29VfLf6DBYnkbSgMnvvdQypbdw/LEkGiiH+YeNyoxZWbLicrP7Lain9mRRZQcOUbShe+Qey81yl4WdBj4TmLgqyoo2USpBnYaDnSqUKS1HLfFgmFUxrATy+kiBkVfuBdokgvYuEWh8D1d8B9k8Eru9VYrLoa2U+LocrUKBSgC4bCFTqowhapgvwMbUCymNfuLZyjDjKVlsZpXBlpu2q+MrqivhjX6a9cmwpZFkpJdOaKyKZ+8BpXtqlfk4qY85tlQHA4ZnA1Z3KdhTMFLqeBZWLCHOsANncLTtODq7SYpDW8CKl02z9Kix/7rWpHBSyWvtBFscqjgPVsxChoaFwc3PD06dP4eqqPyVK8mpClmNVTZEw7ctHiLxmf+8UQk0Ll/6XDa0mlslZXWRSAsXp+lOJPa0jmxQXgxi0AxfYfLT25G0xJcuQwEKemN67SrKjXZnCoIpQ+j85nIDpAUxH+PqtUsL+wAlcpqBNon4JH7QZu0ukO5AR9YpgUK0iuPfsJdqM2S0auShk1WYtCvqJOy5j3NZLGNutkhCu47Zdxspjt3RWC/qBOwbkR98aBbHsyE18s0oJZmdUWesKeTGsrj/cnewSDYl4FZg4EPjjZrMrtD+2KSPij94qlxffrTqNuQcSxvQmx/EvG8I1m2XiOcvD5qst3wA+ZYBSLRP+gFHAcmrVkv5Am0mKAL20BTi/Fmj6myLiKG7Z6FWiObBihDJIgNYBCtr20xVRtnwI0H6aUomkyGV1kkLt0mbg+UOlkkhByx/qgdszlpA1XMZl9fHZbUW88t/j8xX/auG6wPZfEiqTFXsAJVooFwGGVVKeD8MlfvqKF/UFzqxIuI/Hq8aHynHk2FwVnpfO8xUfM5eUjZG3ItBrjXI+hHC1UmLOLIH7+VsRpVnIHDrNAYo2zvIezHRz8TqzjfHmPY5X5vdmJhayoRbotQz4m0iSHmDX+q/rzyUSsvTHsjlJRU05oN8zPQftZ7O3FZVJ3rI72OKL5iXxXoNiYtTrz+vOYW7/QHzatISoiKqwctqwpI+IxuISO3NzVSGrhZO9lgwJFsdFFbL07VKA9q9RCCvfri6EZNO/doo0A+1kMi7Lj956EU3+2o6aRb2FB5kwx3fWvuuo/8c2nLkdKi4AXhdWtplqYA6ujraiUW3VscR5vpJUQGSEfg3sGQ0sHwycWq5UAUUm6hPFBkABO7m+Ml0q5KDifVz1riLe6Nss2QpYMkAZCsCudYrRQbuUeCn6asXzGyh+Sf6sehRQBNi6kcCO34CD04BeKwG3fBn7FFNEMnuWwnNKI6WB69RSpfFp28/6S+wUvQVrGl/uN+ZVpa2j7URlUIMKX48C2VDIdpylNIQtHWB6XzlYgds6uipNPpYKWfH+MUrjmjnQ58sJcFm8mUiS8ZCVWckrwWronssPMWDGQV1Fk0KLXlZK1qFzDutSDjyc7LBkSDXRrT9i3lGjr0eBt3xoNTE0YOSSE4k8sqZsBtyPzWfu6nlkDeFSP1MAkqvOGqs8U7CKSmVcnBC6THF4Eh4ppm15ONmL/7OauvjwTeEFNuTjxsXQK7ggaGNVvawUsipMPrj19AUajtqe7Hhd5s6uf6emELBsglNxcbAVTXAeGn/tq8LjybG5asSYMVhJpxeY+z583lE9m4EaLZYU9P7u+qTuK3t7s2R15sRipXKqwu+hlmOAIvWVJWl1+V+t5vVnbmhtRQyV7wo0+wNY2AM4vz5huyINgK4LlBGt9zSjWOn55HhaNoixWUwLq7jZcwBrP8l4NgNDWK3m8ZnZ2vgULUaUtZ9qni/VEL7e4v76FVpDIctl4nld4kfdmoAjgnkujQ22sARWZSfWAR5cML0Nq9Q9lgN5A9JgwIUkEdrUAmNkAZtBqKzMSlIbCsmgQjkwoUeA8HuqQpbVRorG0fEpB6qQPRnyVEyTUmGjFFMHVBjYn9PFASMXJxayeQ3G2SopBzcQHhmNnRfuJxKyedwcheBS2XruvoizsrR6yc9CweXj6ggft2xwcrAVkVLero5CkDHPttrP/4mmJ1XIGo6GZVV32u4rYOQrRaxWyFIs33wSjtH/XUpWyJKbj1+IiWiM5NLCrN8pu64kGin8KvC80N/MqWvGZi7w803oHoBcro74ZMkJcR+9xt0m7xOV67YV8yb7Hl0D81sceZaloZgq0xYo3ly/2rdssDK9SStkWXFsORY4OBW4fTQh3P+nfPpCln8ImY/K5qC3/lV8kiq0F/xeNLGQLdsBKFQL2Pg//ZSDjDoGlX5i36rKUq0xWvz16s1tPGct/jT+GEUyq70r3k5ayBJ6ZjnJ7HWh2Om3RfFFG1sh8yykeKPzVpJCNr0KWf7MaldFtCkHUWZO6svEZNBLaokhDMg3JmYo4GLj4lIlrF4VtIzHUoWsiipoVw+vISwJFJzq6h2rsIsGBYkpX8VzuYj76P+8/eQF1py8nagKu+PjOuJxLRSSVrDCgWuP9YQsl/tZpfy7cwU9MbbjwgOcCHmKyGjzBB+X/dUIKWbp8tgeuPoINx+HiyzZO6ERomnMsAq78+O66FxFf6l+ys6rIqVAC1+bwyByu2XDimPmj6/kRLI2RgQj70+J7FZODaPN4o8O5bD/s/p4t0FRYT3gJDUOcdjwbk0EFfYU2/L7SoWClrmz3QMTBlQYgx7g3sEFzff4qkvpxgQTl4nTeyxUSkFx1G6yvqAl2ulcFLJ9NgLu+RVbgna5XLsd/yi2nQwUqAaMCVQajrov1Re0hlO/uExNccc/sCGHlfsoaE8ty7id1LRTMFrs5CLjj9OKwe+/V2kr4aCCOR2MP0abx9G5StMdz5kpPAoCpdsCVinQp03bAG0K7aYB750Fan+ijPpl0gWHNwzdp1T003NmcFaBFzghR5QmTcMq7PBjymqMVtBu+yljJIqkMlLMZgIojBhJNX2PfnVOHTlb7/dtuPvsZaoJ2vye2Y2KEwpaVjA5iUud2EUhO39AIPx9XMT/WQWkoFUTEWb0rSKqg1o7Ab22HHagClp6UJcOrSaW7jlVq7BXdp2QHdetorAC1Cvug787KYKWVgGO0S2Vxw328dFcScHjNnj2IYzffllUfzl1rNJ3G3D1wXNhOWj053bRgDW7X1Xd1C1hJ4iP8fqqRSmdoFWHJjgaed/qRXKK19MmHSQHh0t4uyReAqS3NiVHxjrZ24q82gE1CqF52dwil/fK/TDxd52PlcjtKoZRMPFBnUbWuFQuXSyZMTjRbf7AIMuE7IWNyvKoYQWQYm1OR2Df+KwjaPnrmn5MVhONwYxTdq5TuAT0Bqq/Z3y7Jr8AxZoA2XMqcVxLBwKht5TnG4PNT8xQZTpCw28TYrvqf6VUdzOaAGLV62Wo4jtmaoEpsUrRztG/lgpaCtkZLRJSCwzha61+V3m8xwrjgpZCtvsSYOeolEsW4OswlYKjdfm9wcxcnkPGfNHr+7pWBknKwPOQp5xi6eHPstZOwKQSphyogjZnUcUSJJGe2cwgZPvPOCgqj+STJhzfWlDY2BjW32H8HoRFRAshwRGvPi6OsEuD6UsUqjP3XBWVXApZVdAwOeB5ZLRYjv+8WQmxoHbi5hOcvxuGthXz6aUWUGT+uuGcaJpi/ipFK0eohkXE4Lf1yvO1vljVT8uKZQ1/L73XMgXfY8icw2LoAhlerwg6BPjiyPUnovmrW3yTF0X62hE1RDIDR952DSygl7XL1xm16bwYN2vsmNNz+zAsQozArfmLiVGYRuCoWla0S/5Ps2Qcz/nvmqTKZC0ex+9Xn8bIpiV0zWvq9x4THljx7hjgC3tbK+GfXnH0Fqbuuqrz3eb3dEKPoALoUiW/sG2Y9f2nCtmFvZTqgxoFxU57Vi7mdVYalkj9r4GqAzOeqLIEfmY2KflVU5b3DSdHkeajFKHLKq5rbmBed+CSEb8dq6yc9MXteCFwZDZQth1wdB6w7mPjS9AcBKCmHHB4wrW9QOU+Ge+YcyIaK7LX9wDzu+qLVAp8Nm6JpjmNh5bHlILBHG8wL7imNwOu7dYXJ7RynF4OnF2VcD9/jphXy2zfKQ2V+7yKK1O9eI52/Q3s/AP40vyR2pJMOAWMK1OGvlh+f67/DKj7Raae/hVqgWdWNoBlYLh8z+Xlr1bozw7nOFeKRsZJUciqBBfOIUbJphXqsr1hZY6Cln9SWEElamatsUEMtFNwKwpZFQpaRtaoz9eiVqrNFbL066peUBVWf2sWzSkuGrRpBVUKemJGnyqiIsqlecP35/28x5R46zN1P/7tWlEMeeC0MXPg1LLBtYqgxb879e4vkdtFxJsxOzc1oMdVnZ5meE7jDM4VzxEtCLbW1mDyHx+nZrBIaLNyRj+oNk6IgpZVCYoNVcgS/iIfekDJ4MyMv9T5h+vuacDZSz/r1RCem+Z/AQWClIqN2gBmDDaFNf9DEbQchHB0DrDGIMBfC5vCODZTFbQ8qxlNyKrWlLUfA/X+p9gAbuxP8LG2Hqs0wlHgc5wvjztTDBhV5VfDvM/L51Io87V5nChkuy4GfCsrj2ubwuhPZcMVK96suKnP57ngpDY2a+UPVCrmGfFYS14f1QtrrMGLIpdkxt958Ugxm4VyZinAvlxxCvOSyfj093bG4sHBcHawFb5IiXEozpgxOz2J7FxSMGd2EddF3+yR648xq19Vi7Je1YryvisPcfpWKP7clESXsYY5/auKHFqOy61Xwhu3nrzAmdvP8Gu7ssKGoRX5GRraCFgBZLB8Us0N/EXO5bgi9TJtR6+SI/sYmNRAX8hm81AEvFawqikHBWsAY6spGaZcpvSrrsxx11JlIFD/S8W/ueZ9/ccotDgqU3sxoRW0GfEPKP/4n1mpZLqWaqOIeYpOp5yKkKUfmPFcrJZSxDKDt+0U5VhaIiZVQcvnd5oL5AtIeL6acsDw+26LgTUfAqeWKOeSV3yMWVNFCuG+FG+WMY+3RPIG9ZqcAJbB4bI6Q/2JKUGbXoUshSP/9hpWE3k/l6tZ6WTFj1+z0kcvrY1mqY+NWFyup6c2JYYGEL4OByDExcZhhonRrFohy6EHhN7XPAapC0nBz8EkLVbQAwp4ikgrphUkBSPGSuZ2Rb/pB9G+Uj6RhatMPbuHRqVyibguJjewYl/Iy1l4cvm4OVVpFXqEedz/O3sPNx69gLODDeqV8BHTvnguDCuzKqpfl5m3h68/FoW78vndhU+ZX5jjVVYvzmLi4uBo6wBrjg/lhCRTgjYrCFkSG6lUZkM11gL6LFnVy1kMWNQnYfmaguj8OqDkW4onlmK01TgliWDvOGD9Jwmv8fS6Ito4XEELl7hbjQXun1UsDcytJY+vKUkHzKW1zoCVQorMg1OU/1NAki4LxRwCIWQ5ZYss6K6IyBHHlYqppVVRbk8f6runle9RBt7zWLIKTmHaZqIyzWv1+8CJhQl5tobwgkIOL5BIzELaDDIJFHsdx+/Bgav6/ioKk0Of14ero126ErJc/u85db+I7mLygCpoKVxZqew1db+4n0v5/265gLUn74rBAwzrpxCkkA19GY3WY3ahWZncGF7PP8UELQUdvZ3ch10X9cfYUssxsWD5kRD8sv6c7n7uW8X8Hma/B60VtIAwyaBlubx4FB6JXlMPiAYvY7C5bWy3iiKSjONt6V/tPXU/vm1VWuwrq/P7rzzSe45ndnuRQjCoViGz7AcUkr9tOId5+2+IuC/tZ67p74XvWpUWXmHDvF6eyx0X7gvf86X7YXqP+eVwwvsNi6J+iVzJimq+/w9rz2LXxQdYol58xUYh7twaWBmbkES/WPDbWaNxhULs6i5gXifFI0che/OQ0onfcTawfKgiaOn55GQgVv/OrQZajQEKVAeyc5BJnDL4gIKWI1z7bVISDCismHdKf57w0/6jHFNWER9eUgQtl+fZkCTGt2ZAIasew3HVlM+kwkYaVq9ZkdXCz88Rt7x5F7f8vXjseL44zpbNdVqYIlDjPeX+GS2VY2uIbxWg2xKlCp6Oh81IJKmJtBmk0MHJKKipBWqzlyFqU5glFbo3IWRV8cVRtxSujNpiHm2XSXtFh7+dDVMIKomqYO+pB5ArfpIWBe3TF4qQvfZQqdgNqV04xQQto7goKrtM3CsEsyHD6hYRcVWdJuzVVVPXDK+OkqIKaT7D5hzCd63KiIiuZy+jMaK+v2g8m7P/Oi7fDxOe0wr53dG3ekH45ciOn9adxWdNlSY57huby9iUxmOTVE4tfbajOpZPUtDye4himoMwTOGazRbLhiiDLdSBBxwDvPhwCD5fdjLJz/pp0+LoHqg/htiYkFXtHcwd5hANJ+toWGmbvbSoTWEZObjfFCJ/1AqwtU8QYlx+vrFPmdLETnh2xIuBCL8rjU2HpwOV+wGX/gO8igK3jwH5qigVWlWA8nXYSMZmJwpZdfma4mv/JKBKf/2LA1XQUvDlqZBxhSyhN5gDJhgpZi7DjygNcJbAY7Z0cEL11xis0vZcATjnUiwerLxTtLLqHfS24rFlwoBEkoUJlUMTsg7JCVny09pziWK70gpWXvdefigyW1XWn7qLYXOOiOQBVcgSdvqP/u8iAgp4oFguFyEw24zZjd0XH+oJWTJ733Xx+dlw9LrHM+TJC7EfxoQs+XfLRcw/cEOMpuUQAbdsdijireTlmgvzbn9uW04I2d82nBcxYLV+2Ypzd5+JCuiW92tjzYgauuQGplWwKsvPuPXcPTx9EYW3yuXB0NmHkx24sObEHSw7EmIymo3fF2O2XkpSyBI2v/WdflAvw52RYP9bnrw4YGQXM3pNValp01iimR7GQRl2cZGmhSzJDMH9pvzC7GKnr5IilQL00HTg0SXFt0pBqwrZBt8AG75QhBAzSY/NA3KXBS5vVcSnVsgS/r9Ua30hq4orQyGr3u9ZGMhTPmMLWYEVULiu+ZszwsrS0b1s+uK0tqSErCp4GS3H92g3HRhxVBHObSYBBYKlkJVILETaDDIwFIaXjQjZQjmzo6BXdl28VHqr0FI8rT15G+8vPJZkfGOpPK4ik/bndWcxc+91k9tRTHJZmhVDtWOeXlFaLNR/DZuvaFVQ/9UKWUZttR23Wy+1gONaewQWEDYNextrPHweiVXHb4t0iI6VfbHo4A0MqFVY5K9acgwm77wshKyWBiV9cOHuM1zVCHWOq53Zt4rwq1LU85idvROKC/fC8NGi42a9H33Tq4ZXN1qdZfpA0I+bhTA1hwUDg1DZz0OkTvyw+gxm7TN9brRwOtg3LUuL5AdDeOwvP3iODuP2oGQeV8zoUQ4Oi7omTi0o301ZWmeVzcwKreqtZuWf8WHac54uhezmr4G9Y+I/13rg0FRgw+fKknO3RcCzO4pYrfclMLOVUoEtWAvoOANYMgCg15jxTlzGprA1HMfKCq+xhiJT92cmeOz+KG5ebmztT4Fqwy0T8ayoM0Xinn7CjEloCSnVNiHNQCKR6JCV2SyEGoOkFS2MaOLyPJfCtUREx6UL+xXFdJPSufF7+3Im94dClqKJTV89gvzEEre5QpZCkVVAel9vPQnXq0jz/7Qo8ELg0fMoIXRU4uKrwWqRj5mqtD8sGVwNud2zCS/vviuPxHM53YzHN7u9LfrVKGSRkCX83IZDDrpWzY/fO5QTn1sdBEF4fuPil95po+Dx4/+Z52ouFL53nhqZP89pp9efmC1kybwD1/E8MkZ85hXHzN8HXgCYupCiD5cXYQsGBQkbiTgbWi+htQ0iWk9BbLPfEddzpX7DV2y0kkVrgDq5jVV0VoZ/XHtGjAPmcU8PqxRGhdCefxUhS7ouUmKcKGQJ81FntVOqeQy7V4UsubINWDpIaVziUANrW2XcrYia0px3/p8Ztdr71MSEF48z/wAKVqSrvZv8dow2Cx5meTWaYtlcIUuY8RudyY+5RPIGSMclCklyUNiwUsfOenaaa1MLKOyYcqAKWo4lHVizUIo1Sb0uFDUty+cVzU/GmNKrshCTdrY28MuZHV80K2l0u69alET+HPpCduXxWyK7leLpeUQM1py4JSp/fKzHlH1oNXoXnoRHYdGhG0LEqYKWx4YikmIyl6ujciztbcRrdZ+8H1N2XRV2BjY6Vf95C35df14851WOKZ8zpE4RDK9bRHzdrWp+kU7QbeI+jN12SZxT7gsnjU3vU0VM3FIrmtxfVmm5NG8Jpra/H5Y445bCkg1tvKgwzPt9ROEbFyeq3qasGMagHSIiiWlnFLQU6bWLeWPYwjOI6LhAiZSytsHLVlMQUaAuYmADKzXlgIKWIfN9NwD2DA7Xr7L/uek8Kn67EZ8tOynsHDP2XMPQOUdQ9YdNWHz4pi73ON3AvNGK3ZVxtE1/VQS6fwPAR0kr0QnaGa2UMbSqkCU8FoFDlLSBCt2UyVUPLwLTmgH34wUtbxTGY4OU2DNV0Aoh+0iZtDa7feYWtJyAVftjoNYnSpKDMfJVVr6nDCva5sDjaAnhD5ToNIlE8lrItY1MImgXDQoS1Ult/JYa21W/pI+IaUovQlabWrD+1B2jj9OHyaqorZWVaI7697+LRrf7e8tFNCjlA1trK1Fxo5D9ePFxsYpIMbPq7RrI65FNRH0xnUBNe6A1g55XCtp2lXyR01mZKMZjRhHJJfmDVx+LsbbGViT5esuOhghbArNfX2VWgSpoy/q6i/MzddcVHA95Km6EgpYNZndCX2Lr2XuoVcwbtjZWePw8UuwrG+Msgd8bxmDSBaFwblspH7oHFhCjbB+ERYiLDj5O8UcxSN+y+r60b7BynpxnV4XflkkNTqBIpxeYYp6fe9hC4N+OC2AVchCX7YvjkxnHMatvVdg4xMd20VrAnFUjQvaDhcew8vhto+/zODxKNKyFvohC72ppb7vRwaXmbDmAgTuAZ7eBCTWBEi2V5AJ2vd89leC3ZAVQK2Q5FpUVW3pkGdXFwH1COwanqL19CDg0AzgwUbl/eguAFW42HL14AkyqBzy5rtwoaLsuzAQeWRNQpFYbAQQOBg5MUiK5uArA7yXex6osm69eZRmLVhBLYDKFkVUFiURiGWl6STh27FiULVtWpArwFhQUhLVrDTIPNUybNk1UpLQ3R8dXuHrOZDjGV7SM5chSnNXwT59CtuukfbppX4awKWz43CNCNH698pRes5cWCq+7TyPQZ9pBsS2Xlik+c7s5CjE4Z991sczMqqT2NbjkTm9qUR8XnL71VNgLtMcsu70t3ltwNFlrHTNVp+y68spVPp4XVciy4qvCcbAU6mwI43EYOveIaPxSrQkUffTXmguPBxMRjBHg5yGq+iuGVRd5tfQoV/puIxqM2o7qP/+HNmN3i581pgu0KJsbLcrlEQKQx7qhBftQt7i3yMA1JWSfvIgSVXM1IWLj6buiQrvzZUF0mHxURJJxX+gPj7VxUDJWDYQsfdA7Lz4wKWS1MFrN0ur2GxG0FFJsbgt/qEyC+u9HRdAa66qn4KIdwaeEImR5XOjDpN+W8D5OkGIjGV9LhSKXgvbA5AQhq8JKLt9bTPrKxBXabO5A0DCgwwygy3ygyS+KuGcT3Kv6sSiI3fTtXUlSspVs9pJIMrqYzZcvH3766SccOnQIBw8eRN26ddGyZUucOhVfgTACRe/t27d1t2vXjAfbZzUowEzlyKbWiFMVQ++nCpMFWCXTQtF37s6zREKWy9nD6hQRf0MYOfW/5iWFmBk+7wi+b10GRX2cRSPU+O6V8G+XCsJDy21qFvUSEVn/nbsn/u0Q4CumYbHqSj8nc1O/W30Ga0/ewdwBgSInlU1co7tWFPFSPGRBhXPqVef4eZYcvolwM32Vs/ZcMzpK15zjRXH36/pzekKW9AgqgCsPwjByyQkh0rmkP2zuETwJjxT+17fnHBaDExztzPsR5jGl89bwfKieXFoq2JTH87LpzD3EakT8xXth+GrFKRHdxVzbesW9laEPDrYYWKuw2Z97QM3CRkcUM82A1XetkFVzctloNmLhGV2DI/eFglacGzvHRA1fkdFxukEW5sBt6a1OV1DMMiyfo2n5AxEToSxFG12OZrmb/mErpZLK48FGOFatC9UG+m4CXPMq1cg+G4C8AfqClraD6u8C5ToniF8+J7u36WX4zAS/hxxdlQqpg4VVVWOwiY7xaObAc1KxR8rlJPO9OSRDvWWmhA+JJD2L2RYtWqBp06bw9/dH0aJF8f3338PZ2Rl79+41+RxWiHLlyqW7+fgkXRmKiIgQHXHamyTloA+VMVuGFTcKWYpVCi9t1ZJ2ANohvF0dEjV7vV2viGjmoo+0aiFP/Ny2LCrl98C90JfCazm7f1W4Z7NDgxI+Irqqe1ABYR1QPZ8nQp4KQdu0TG4x8vV3TVLAD2vOIOTxC3zfurQQslxSp4ipVsQr0TIzY7NoVzCXW09fmhx2YAjFJEfYqg1I/HtDwaYVw/Q3f9q0BKb0rIxaRRl2n9DsxguTQl7ZxWc+euMJvm0ZX4FLgvK+7uhfo6AQxRfv658Pwglquy49SJSsYKwK/eGi46LpUIUrAr2C/ZLdhw4B+VA2n5vRCWK8COM5KOzlrCdklw4JFjYANoXxQkaFFzZ2tsYvHijY914237dIAZ+U9SFtRtc+UaaeMVqrxyolfmtma8UDawiXqLktbQWqB1YVtKzmCiFrryyj0yfL+1RByyaxtpOBXGWBRt8DVQdpxK/MOH1lcczjyBG2ycHhFGL82GtCjzPPL5sF2fQ3vxuwcgRwdbtyP6vyEkkmJ938Fo+JicG8efPw/PlzYTcwRVhYGAoUKABfX99kq7jkxx9/FEMS1BufJ0kZKMjopWQ179OlJ3SCVhWyXSbuQ7txu3Hy1lOdgKLXk93qS4dUE4H/qpBls5eNldJ41HniXnErk9dNVBQ5NvafLhVw41G4uH/onMNC3DCw/6c2ZfSqkxS0bPoxFGaM0OJ77bv8CDWL5sSCgzdQt4SPUb8kxR0rheZAry1HzJqzPYXst6vPiGayGXuuiuPH92d1+d/OFYSgHV6vCPpVLwgbKytRbZ/QvZIQtBR3FPqsSNPPysSK71efRoCfJ8Z2rQgvl8TVHepjTkebN6AqomPi0HnCXrQbu0dYPNTzoY4K/mezcU+yIayWPwqP0rNJjGxSHO828BcXCIbw3HCgBSu6SVld+Nh4zWelkKU1gtVzNeWA5zy5ARCWphTwvHE4RboSspPqA7ePAmdXK/muFLLaZi9WbllB1TaFiUavs/qCllCU8r45HYBpTYHre4DOc5SufgpZDmCY8ZbSVFZ7pJKrKoXs68FKa4+VQKk2xqvpzj7KGOYSzeOr6q8BxzzznP5eXPFGn1mpxLadXKz4rP8JAB5dTpxeIZFkMtI8Z/bEiRNCvL58+VJUZefMmSOqtcbYs2cPLly4IHy2nOD122+/Yfv27ULQ0rJgqjLLmworsxS0mWkCWFoKWe3kp7aV8uLH1mURHRsrhCwrh6qgmdWvKkrncdMJGnUcLRuIKGT5NZeOuYTMIRCEwm3xoGCRZrDh1B28PfeIbvm7fglvEY/F/NCzd56h++R9umELhlDIftSoGLpN3ie2/b5VGZT3dRMeTCYqGArasJdRGDTrsPBeJoWPqwPmDQgS/z4NjxLxXdqlc8LmKL6+KmTZVa9CEdinekE8DY/E7acvhdB3cbQVgxDGdK0kBCqrhnzug+eR8HK2h328iOPxfxweKZb6OTWNk8K2nL2HPZceChuDr2c2dK1aQAhMHhUK2WM3lcYyLvXP7ldVVEq5bM99bDl6l9nnnhPJ3m9QVBSVuPx/6/EL5PHIJhrFlh65iWM3nooosdJ5XEVzHaul5kaXUVw/NPis4jhGxeDuswhxrJOyzfD5Jf+3Ts8mkRQcevHfB7V1E83SFFbQdo4Ctv6g+C6H7AFOLgFWDtdv9qK/07ukIkLVpjDi3xDoPE8/K1YVsozuIrQOtJsG+FVTYrtmt0vI7GWFttdqRYxlhRHBqQ2PK6umB6cCj68ox5TnqEg9xRLwug12bAS8sV+JaOPrmYIWigHbAI+CmW9SniRTE2rBBLA0TzMoVqwYjh49KnZ20aJF6NmzJ7Zt24aSJRNHMVH0aqu2wcHBKFGiBMaPH49vv/3W6Os7ODiImyT1vbKLD4WIyCs2V526lWDn4OVSTEycXjMVhZtbNltRBRVLz1b0bio3FQ4u4ACDt8rlxZx91/QeY6WRX1IoUjSN6VIRfTidygA2KHHJvtOEPThz+5m477NlJ3SCdvnRkESCloK7XaW8SYpZVciuP3lHTDQb172SnpBVKtN7RVpBTX8vUSXVZtqSH9eeFTaM3RcfCGH/YaNiwsNJoRojsmWVD8wKrY+LgzhmhI8vOXJTNLRx7C09rqwQt6/kiyoFPUXaQG7XbJi266qwbvDY02Kgwn1jNb1DZV9RDS+Tzx2WwEEdFLHvLjiK3Zce6s4rm8g+aFgUHzQqJi5SeBwtFYmOBp9Vhccgj7tjslVUVplrFfUWHmpz4BQ1fi+li/5IVkSrjwBio4AK3YHDM4DizZWK6dYfE4RsRCiw7Wf9lANOjWIjU6KhB/yh0jRysalrUS+gUi/g6Bz94RNxMYo/l3FRLnmUJXPJq8O8X944eIHHnb/n6JPlOUqJ7zdWfZcPS1rIEvpnV78PdJrz+pVgiSSdkuaVWUPq16+PwoULC4FqDu3bt4etrS3mzp2b4ko/swpQNhMZW15nVYsixJiv0RgUVXP3X8c3q0yHhPP1ZvSpgnK+7skmKkTFxCDspVKdTcqDWruolxCP6uuZmqZFSuR2ETaGyKhYfLDouE7k8COysls8l4t4HS5ta/ePx6nKD5uEOE9KyP607qxun7hMzkoqK8yM/qKgp3VgTNeKOkH75YpTmHfghsnPxtG1S4dWQy5XVmUTHy9+Vo79ZTOYFi6/c4n+s6Un9YRr7WJemNQjQFRfFx66gWI+rhg486AuH7ZLlfwIKpxDVL3NhRcIrCjTn2wMVn5Ziaet402naPDXGePXePyTglaXGT3KwD+3J7JnczRe9XqVnNGUgNU8Ctm1HykVWlZLuWycPxBwygmMq6Z4IQP6AnVGAlu+Axr/ZLrSx9eb1Qa4ttv0ezLLluJ4y/fAiQXAgO2AR4G0bQJjpZpCnN5eCjb+0L6puDAOsKC41w7n0B5PpkZQ+Bvbn8jwhFSK1IJ/tq/uUBIpzIHH7t3TgGue1NsniSSFydATwGJjY/VsAcn5bGlTyJ07d6rvV2YgKjoW9569FI08ht5Cfr3q+C0hxMy9vqEg7lwlv0gVeF0hS+xsbODsaCO8oX45nMwWstN2XzHZvMRqLC0P9nbWGNO1AuoU8xb3U2gxsozL36dCnupNUSP8emKPAPEZDBlUq7Cosv66ISGBYOv5+xg485BoBlOFLOGFw/sLjgnrhZr7aziZzVwhS7g/tYp5CRGuwrgs+khZYeaxYZOduu3AmoVF7Ji9jRWal80jrAkz+laNn7IF8f1QtaCnENrmQksDK8KmYOW315T94rO/aXghRvsEfcem4Gdf2Lc8ykQcgVPMM8WrqoVL85zMlFY+Q2s7oHRbZVn46Q3FD8tBCLnLKZ7WFn8r4oRRW9t/B5r9oQxcMAUFV7fFSvXWGLQsMKeWQpajc/0bAe6+aSdkKRYpCA9NU5rb/g1Q4sNowWBkGB9LbRHNnN+Qw4kHSPBrWj+iw4FbRxXPquHjN/YBYff0J9ilNHwf+mPNhb/fzpmOvZRIMjppKmZHjhwpPK9Xr14VopRfb926FV27dhWP9+jRQ9yn8s0332DDhg24fPkyDh8+jG7duolorn79zIxCyeJC9u6zl2g9ejd6Tz2Ag9ce6QQt/52+5wo+WHgcHSfssUjQ0g/buYqv0cglfx9nVC7oaVF1joLWycFGNC4Zo2ewn054qULWMNaqgq+7nghlUxgFLautFLS9qhXAvP6BYjpY+/G7MXDWIWw5c09P4HOf2YDGyKqK+fWX4UdtPC8E26iO5fREIAVttZ+26FkseFwo6NXldlZqB9Q0khcKoLp/TuRxczQpZNXO/+z2tlg4KEgIWgrZ3zqUEz5S7nO1IjmFoKUPeVrvKiLJwM7GCk/jo6+GzTkshCgFLRvw3m9YTLwmm9DMgceV8Wdz9mtySY3wLCJabGMqVzY14XGg1eGblqVEFd1QyC4fWBFFnuyEzYJusJpcXxnjqgpaCti5nYDV7wEb/5c2gpZVPUd3oN9mRdAWbaTER4llayegVEug5Viliat8Z2UJO7mmLStboHJ/44/xNRj2f+eE0rTUelzaeWYpDikGf/MH1n4I3DqsZOByRCytFbz/yKzUm1ImhOwtRTyzmn3jQMJ78d89o4HlQ5SKqFcx4MrOBEHLxzmAYU575fmpKWiZYmHpMaDdQCLJpKSpzaBv377YvHmzyItlKZmNXR9//DEaNGggHq9duzb8/PzEsATy7rvvYsmSJbhz5w48PDxQqVIlfPfdd6hQoYLZ75kVbQaMUnrwLAJv/btLF2PFrNXJvQKE+Jmw/RJ+WpsgCEvndcXCgcHJTkbSphaozV6GsCnsh9ZlzM66ZRD/f2fviXxZY4U9NoUtGhQMX49swlfJxqaD15SpXoRVzx/alMGha4/1msIo7tj09DAsEjWK5hRd7K3H7MKNR8ofBOt42wFHqaqfm01HrGRS7N0LjcCeyw9FRFjBnE5oUDKX2Ndt5++L4QrG9lVttCoZv9zOai5fr9Xo3Qh5YvwP0adNi6N7oF+yx1715XIimOGx5f0U7jzHFJ8csNDi3526DFd+1t/alxN+UVoe2ATWukJecSFjqolOZVjdIqhbzFtYQZKDk9TWjqiZZtFXtM3w4oGeZl7QsGLdrZI3sl3bAit2fquTlxh0z0gqCsY5HYHL/yW8CEfE1v8ybSwHFNjRXNK2S/z+FFAUXrw/OW8rBTkHIbDCq/XIqvD12TjmGxj/XmkkZPl57xwDpjRKfmBDy9FA6TbGbQCv/P5RymS1ibWB5/F+eR6LLouAgtWBHX8AWzS9GXkrKtaMS1uVZIKLm4F58RcXhBPZ+m8FsnspFygpbYPY8bsi8M2lw0yg5Fspux8SSSpiiV5Ld57Z1CYrilnCqmOPKft041wJxU5gIU9sv6Df6ERByOVwLou/jpC1VNAmJ2QNBW1+z2yIi7MSopWClvvNJqrBsw6LqtzTl1HoOWW/aDKb2quyGGPKyiTH/1LUckysihp9xSYjtTJKwchGJ9oGmO1aPJerEGbcz6sPn2Pr2ftY8XZ1rDgaglGb4seHauBwh4Ylc4nnmCNkLRW0log6HhNtUxQFLauxFOM8PvT7UvgOmXVYVFWNwaxaDkloN3Y3rpqYyGYo5s982xjpAfXXnBUrZU9vApMbKEvWKvQSUnRoI7DYqEMBULhuxh3tmpyQNRS0Baql3WdlpZEVz5sHkt/WyRN471zKx4jxIoFNdUwJUKGgLVAduLRZf1vVszy1qWLLuLJdX4T7VVems6XW8aTw/qO4YiFIDkc34IMLMqVCkqGQYjaFDk5WELSGmCNkVU/p4FmHxNhZFYohiqLzd5/hhzVKY5TKVy1KomPl/EJEqa8tlvWtAEch9pRA/2Z/79ATsvTIftqshPCjapvCKD53fVxXCD6+DnNb21XKJ+K36JOl73TV8Bq4cv85bGyscD80QuTTapujkhKyFJ/cknmvFLSsRLKCqaV9QD6MbFJCiGmttUCFDVnMieXn5fFqOGq73mvQIzutTxXM3nstUVPYpJ4BwtP7utPb+L6Pn0cKm8OIeUdNdvnz3E3tXVnYEhYevClyeO+GvhQVZVarB9YshBzO9mjxzy5cSsIvq8XdyQ6Hv2ggxPJrwyokX8ZYU40q0rgMb9ZrRRgXtFoyg5AlL54Af5bWX2JmsxfjuVaN0G8Ko6AddhBwy582EU4PLwH/VDR/+3ZTgZItjSQ4pIKgNUQVsmqahCGpLWQJvcOLegPn1yW/bfDbSiqGuT8jEkk6IEM3gElSDwq/GX2qomJ+D5NTmswRsoTNPV+9leBJVJu9AgvlEFVFbVMYx58yBooCiRmyXL6nAN105i6OXHssPLpMI2CebP8ahRI1e3G5mmKzYE7lFzGXjjnJS23aoh21a2AB9Jt+UAhZisT5A4PExCwu8RfwdBLi1JiQFVm2g4ORS+NV5bZcmv99wzlExcbC2cFWvD/D+80VsoRVT4pwfl6+Jpf2VW+x2uxF36thUxh9sCkhZAmFJJvcdl18gL86ldebKKaFqQel8rjh2I0nwhPLY7Lv0/pi0horxZzaxuNurCHOFDWK5LR4iIFJIcthAmxQMvSwUsiy0//O8aQrj1pYaWMjVd+NQDbjPwuZQsgSVi6b/Ko0jKlCtvc6IGcRoNsS/aaw2p8qgf5plUV6eZuF229NHe8srQtiUlpC3J4elfoAjX4A9o4zLmTzB6W+kCX0T7edBHgVT3o7jjWu+7kUspJMTZrnzEreLKyMlvN1E4kGhlQvklNUI7m8Tp+oITGxsbCJ/0PHSp86iarj+L34tV1ZvdQCphyQ3Zce4O/OFTBn33V8t/oM8ro5YvWIGth+/j7emX9UvA6ruSXzuGHRwRt4p0FRsWrG6i6nfin7bKVLOWg3bg8+aFRURF1xYAChCI2NixHimgKZU8M8nOzEa/NGr2RFPw8hxBhRpSWXq6O40TpAscZPTSHbesxuXH8UjvvPIoQHl55bjm69/OC58JoaE7IUqs3L5cbiQzd11WU15YCfkTFhcwcECqvDnP6B4n1FY5gNhKAl3A+1oSslL2JYXX0eGS2SCCiyDQko4CnG+Jb39dCzN/CY2Mdf8/I89K7mJ0baEl5ktKmYT1wIcBn/yoNwLDrEiq7iyx5Qq7DuHL22kGUV9fFV4Pk9oNkoxSdK8XpikVJhpHe0+1Il+N+c6hMFLZeG6WtkA5jeY45AvsppG0uVksKMDWNkz79A77VKsxczSkXKwRKl0alIAyBw8JsT74zaMqyoMoarzmfAiYXAg6RHK+u2Ty2YDsFxwiGHEj9WuLbit/YqYfy5FMEpsRph7vntv1m50GNuMH9WVFxyA5X7AcHD0i5mTiJ5Q0jPbBZCTS3QNntpYdf7lJ6VUTY+DUCbQsDKIpumKHS097O5jCKH/xqmFqhVudXHb4mMVzKlV2UhfPrPOKgTfHyvsd0qIbhwDjEW96NGxZHdwQZDZh8WiQOLBgUJcc0cWmsra+EBffYiCu4G2bC8n1VeCk/tpLEnQpwmNHsZE/HMguVnIKqQVaGA+6BhMVT9YbPioQ2gN7coOk3Yp1ty103V8nXDhlN3hWBVPx8HGUzvXUUcO+4jBSyjul5Gxgghrm04E8cjFbJZeS5WHAvBJ0tOGLXY8drl704VUM/EiF8VphN8tPC4qLSXyeeGFUdvicEPHL5QNp87GpbywX9n72PPpQf4onnJ1/8srLyNCVSErEr5LkDLMUoWK4Ws+oEoxPr/B3gWSt4bqKYWaJu9tLgXUESCo0fKN++kBVw6t7ZXRKxh5ZU+4pSYSGX2vrxU9odpDNpj+zREyfflxQi9s8kJ2rpfKMvnKd2wpqYWaJu9tPD9Os9X/s/vIe6zIQ2/Byr3SdkGtaTghR3zeCm+aS3hmOLcZVmZkMMvJBkW6ZlNoYOTFYQsRYx29Z2CdmzXSqhQwF1EQKld+Kog9PVwEoLU3LgttYlK9ZwycosWgT7TDupVh/m+Pq6OouOeI0bpYz19K1SI3OpFciBb/DhUCtq/Nl8U063mDwhEYW/nhH0Mj0KrMbvglyO78JyyImtMyBp+Zq2g/WLZSSw/dkt3Pyu8HJDAdAQKbcL4rEalc2FwrcLoPHEfbj15IZIhivq4wMXBVrw2vakUtAF+niKv9uGzCDHylfvKCjeHFrQZs1uMrFWFbmphSsgaHgchaDtXQL3iyQjaqBj8uekCpu+5Ki4etNA+8U59f7QLMB7X9kq+QOapbvhc/34KVo4I1X6gEm8BbScmX4UyJWQp9NSEg8woaNMDYrxue+DJDaAfEyTclWPL+xm/Nb25Mv2s+rtJC1oKtw8uAk4eb0bIGn5vUNDSisLq/VwmGETqP54WglYiyWRIz6xED1YBWWk0zGOlT/PEV40QUCDhDwID9t9feEwkHbDjn9VKrSDk+NI+0w6ICqM5sKKqek65TL/6xG18vuwkpvQK0PPu8n3V6Cj+qxWy7Pxh1BSXwb9bfRb/brkoBPL3a86I1bzwyGidkOVzOYb240XHRXTXx4uP6wlZiuRN79USy/5cQlfhc2buvYZPmhbXE7ILBwULIcsRuIQCdvfIeni/YVEsPHgDc/tXxfQ+VRD2Mhodx+8R70khSG8qc14pZD9adBxN/9khPhPzflUhy4a2/VceoefU/RZ5S3ksjG0vmtY4Blcj8EQDWHikmAym1X1NSufCya8bCa9swrYQAx54PE2FnFDIUhSP3XYpkZAlD59H4ovlpzB155WU8cvSF8hmm4bf6d//6PKrCVnaFvaO1heyXO7uOBsYul/pkld5cg1YPjRzC1khwuKMd8RT2BkOBUgJIcuuf16ITKqvLItzH1QhywrjvnHKgISeK4EchY2/Vpl2KZ9kwGiwBxcSC1ku1X9yHfCtot9EuGyQYkep8ykw8iZQvpv+8zZ+roj25MbNSiSS10Y2gGUBOM8+v6cTfm5bVmflUlML6Gmc2beqTtByiZ4d+LsuPkTTv7Zj7r7riSqbZ26H4kFYhBBPlgpaVl1XHU8QtJzEZQzGWqlCltFf/1t+Uoith/E5uRyMwErq50tP4vjNpzh395nIglXZcfEBHj2PFJOxivo466UW5PNwEp7bsV0r6gQtxR29tm/PUca6sqrIMbiswlIM8m89hSzHuPadfkCs3vWqVhDzDlzH9UfPRUWX8V+suirH3EpkwH606BjWn7oj8lu7TNqLWfuu6YSsytk7oSI5gCI1OSgmv111CgeuJgy9IDwXD8IihX1DO/SCFhAPJ3txrLSf9c9O5UVj2PhulXSCVmQP9wwQ9xsbacwqOzNblx4JSXY/f1l/Do+emzfJz2xBy2VlY/g3NE/IEgqgoKFKF7xhagErscybVQWtdwmgzSRlqTYzQhEZdh+Y10URrVpBSyF7cApweFbKCFpGVoXdBe6eTLhPFbQHpyUIWRUOH+B5z1nUeFJA879SvqGJFy1sjOOENa2QbfS98r3VbWmCoKXvuNMcZUoYt2HKRvPfEwQtf35ajVPGEad02oJEIkmE9MxmISh+Vh6/hSPXH+OrFvqpBXxs0KxDGFqnMB49V/JYjXX/s1q5dEg1vRgrc6C4oshq/s9OIeTqFvfGnx3LixzYI0ZyapmMUKmAB06GPEWPKftF4xaD/X9sUwbjt19CzyA//G/5Kaw4dkt4bmkrYHV30MxDcHa0xdIhwcjt5iiEPBufBsw4JJ6r3W9WIHdeeICVx27hu9Zl0HcaJ6Mp1ofs9jYiQ5b7ndstG47dfAJ/bxe0G7cb1x6GiyozhTEFIsXtL23L6iUiqJ9XO9rWGCJNgZm5OZx0TV8UxLxOMBw2QCH75YpTIsaLtozJPSujsp+n+D+FLC86bj99KS4QKMR5YaKKUp7fHRfui89q2GDG13177hH0CCqASgU8TVoMXkRGo+/0g6I6bw49gwvg48bFhTh+bSh06JFd90nixyhM20ywrMmFPsdlQ5SxsYXqKMJJG9u1cjjQaa4iWtKqu/9NCNlJdZW80jwVgV6rlCVxHhsK2fWfKtsyDaFit9dfLuexZaVyCiPRHpnezqc00HsNcGAKsPmrhPspbKsOBip0Td28VIr34wuViWiNuCJgDSwfrFzUNP8DWNRHubDidrlKK99H2TyBZr/zJx9Y/YEiuLlaoH5fSSQSi5Ge2RQ6OJkRiho20BsToupUKVMC7HWFrPq6qpCleDYljChQ1WYxCig1hYCClskJ7y04JoSsdqzufx/UxtLDIWhWNrcQstrhB6wO06ZgGL/FAQaFvZyFqNZOEiP0s84bECj2gdVN+n4pZFUothlhRbSvbepzmxr+UMBAyLLRjvum/QxsvJqx+5qwVqiogpZeXVXIqrDaykqxtsLKc89qsTpaVwuPBy8GkvLK8vkl/mdGpqXm+O0dWU/PzvFKaFMLTAXEsylMTTmwpFrIm6HgoOiiWKJ4yYxClnDp+59KSnVURRW0h6YlCFmV7suUGK/XFZHJCVoK2T7rlGY0nhuee6ZN8Bw5xVtiUtpeYAwKVSYaxMUA238Hdvym3M9xv4zD4gUPB20s7AmcXa08RoHLqj/9tTy+UshKJK+FFLMpdHCyIsyP3XfloZjsZQinaw2oWcioGDKFoaCrU8xb5J0aClnqHdoAWGHUClp6TgmXz1VBS+FqOHb1yxYlRRMX7RFdA/MnuY+qkGVqAaO3OAyAXltaC2gP0E7AUgXttnP38M2qBCHJDFtWZpm/mtS4VopT2iD4Xoa8XbeIyNXl89XGMApZ2hDoU1ary6qgpZikv5Y+WxVqVdoDtJFj3Gc+18fFEXYpOEqWwxcqfLvR7O15ns5+2yR1hCwjtVhRfF1Bm1WhjeD2UWBGK/1ufIpIw+zW8l2VimRKxTtRpO76E9hi4IMmvVYrOa3pZWmex+bXIvpDJ3L6K4KcWcUPLybcz8zi98+l3ThgiSSTIRvAJK+EkggQKZqmjDHmv4s4d+eZ2c1fhCJr2dEQXWWSMVd7Lj/UE7IUkOyiZ2VV2xTG5/624ZwQqVpvrSkh23niXrH9+WT2kZJo6q4roimOlWgKWVadVw+vjg3v1RT5ryoUu1N2XhHTy5hUYKmQZbMXq8jGmLjjMk7eeir2g35ZVcgyy5Z+XwpgVltZlSWsmjL5gFFfus8SpxwnS4QsRTEvWkx9D5hq3OL7W1JkZTXbXF+1SVjl2vaTvpClreDd04mbwih6KS5Y/ctIsIrHTnhjAwCY5mBJAxFfg01uid4jVv89KFpzlwd6LNMXqaktZNkERt8sG7yMsXyYUollM1Zaw+N1cqm+kCVsEqPI1QpZwv0+t/b13jMyTHk/jvS9vg94fl+5oMusvm2JJIXIpGtoEktRq5WtkshjfR4ZIzr2GbFlrqBlxbFtxXwYUd9ffP3JkuOoWtATP7QuoxOyf3WuIGK5Zu29hln9qugELadjMbuV+1bTxOQqxkDxMQpZVnWZctBxwl5cSmIfWbV9u66/mHhGKGQXxzeGcRDE0qHBOkHbuHQufNS4OHpPOyAqtqyELhwUZLaQNWz20kJRzmQINtOduROK9uP2CCGrws8dQeGu0XEsONM+4O/tbORzWYkqsqsjG7iM75c6ea3ThD2JRCuPV6+pB7D8WIhRQctkBA5fMBcOl1Cze19LzHJSFwPgtf5YVu60KQdswOk8F/AsmLEqYxSqFDDjaykZoVoxSSF7cSMwtYny/+Tgc5kEsLivfrWVQijqOTCxHnBtT2JBy+NmjKKNgeZ/pqyQvX8GmNbM9LQ2vZSDNBa0vCi4Z2TCV1JQqLPy/CrH5tEVYMVw4JdCyjGY0hD4zR9Y0B24ddi87wGJJIsixaxEQL+koZClyGMXPEWloaBlxdDcqhsFLZMAPmhYFP92rii+Fs1crcuI+K1a/l4ifL9XcEHRLERBy3GxFI3Z7W0RZ6VMBDMGhTWX4jlGV0UVtHeS2Ec2v33bsjT6Vi+oE7IUpxS6nk4cNRuMblXziwQIWhzUpX0WCC/cfWaysqnC5jlDIUuP7OguFRJVmSlorWEl0hR02zpq/LTxjXoUm2tP3BHVYkaRGXtPivjzd8NEZdfws6tCdsS8Izhw9TG6Td6nE618bTayMaJs5JITRgUtbRiDapmISjKAPtl+NQrq8oFfGQrT7F5KJim7xrWNXmrKAUeLUpBxeTojzZ5XhSynm3EcLydxqYJWFbKLegM39gEzWiQtZlQhu+kr4MwKYHF/RdDyG5ZCdkpjRRDN7aAvaAkbnYwRGqJM2TLlU7YECrynNxILWXpkO8zQj0RTBW1qTvgyB14R0jdrCcIeYfUK1eoTwLhqymhmNuep8Nhf3KwI23OrUzYqTSLJREgxK9HRMcA3UbNXw5I+QlRqBW2Nol4isoqZquZCAduvRiGUzOMq/s8l61YV8or4LXbdf92ylK75iIKWIjK7vS2iYmPF+NQ1Jwz8kfEw5osZqr+1L4fmZeOrdwBqFs2J3O5J7yNF4ieNi+uELKEApGDffOYuRjYtoSdkVdj5v/XcvSRzVFkM61pVGemrTS1oWCqXSBrQCtpqRXIK0bru5B2TQpZWAyY7cGQwq9D34yPKtPDv3tA5h0WU2L1nEXqfnd5lWio+WHhMNyiB+bkUtIwFo5Cl31h9HUae8XVYjVVhM1nZfG7iAiA5fmhdGs4OKTQOVhW0jX9OXCWkoK3UO+MJWVUsrf0IuB+f/0x7BAXt9b3KcjWFrGoxuHkQ2Pqj8WplbLRS1dv8dcJ9qqB9dksRsmokFkUlX1eI3Pj4rY3/M75/FLnTmieO7XoVOFyA44MZgWbY7FWsKdBno76grdgDaQ6r/QVrWvYcbm9pLnFcNDCrrelqNeH3wdJBQOhty15bIskiyGguiQ6Ks8k7L2Pyzit6qQVMA2C8FZfB/XJmx18dy6fKyFVDKOAoZFm11cJMXMPkATW26/0FR8WqPPNltfFT5kAhS2sAkwGYWsB4LgpbikvGczHLVoXe0dFdKopld9NRVjGYve8a/t5yQYnf8lTEqbYpjnFeozroN8Q1KOmDcd30hzqoObKGqQW86Khb3Edk1aq+5ITYLg+9yij3h1PXek89gEhN1ZavUae4N5YcVvJj+b58f/qQjX02VnHn7r+OMVsvwT2bnaiMb7/wQDxWMGd2jGxSHDX8vVJ1qlmmQBWUrLpSrCZFkXpAxzmmm9tYtT21FFgxNGnhScHfey2Qwx84NDVxakGeCsC9M/o2BW1slyn/irnwdRf3U8S3SC3IriRGaFMOgt4GAge/ufG6SUHx/1dZIFT/d5BRPAoCw/YrIthc+Ln3TwI2GJwHU1ToplzUOSS2GUkkmQ2ZZpBCBycrQsFDEclqKYWsqD5aKSV8LmPT46qrFtKTasXUgZQXLRTQT15EoulfO3EnNOEP6/etSqNrYAFM230VX61I8LPldc8mGrhY9bV6xX3iZ+VQgH4zDupsBO7xfloK0X7TD2Lb+fu67emn/adzhSSTE9TjySV69bjRT0tByL4u7quxiLJ3GxTFwJqFdGODFYvAHQyfd1SnVdjstWJoNXhktxcNZNrM3s6VffFFi5Kwil/yVIWloaClkJ3TP1B4gOftv44f157VE7LcT7u4SNioGsYum4ghoy2FKQpWsRG8IsaWi6HwdHZAmbxu4vOx0m2TWWOt3rSgTU7ImitoKWQ5VYsVUXqRpzUFbuzXb/Zq+W+8rUGTckBR2Wc94FU8ZfzIfF1Wk22d9KPPKOxYBWb1PT0IWdUCcHaV4kNODg5RKFLfsmNEXy7tBabG9hrC48JpZJYIZokkgyLTDCSvDAWMu5O9TsgyaL/aT1tExz0zSrVCdtCswxg6+7Cu2z4lYS6sq6Mdlg2tpmvGopBtUzGfzhLBCWaqkGUHP6eMUfy9qrjmZ6f3lr5WVidVIevr4SQEKyejcUwtof2CEWPJxZSpx1MrZJla0OKfXfho8THhlzWWtTtq43mM335Z18TG16lfIpcYzkABrApZ12x26DV1v5hAxrG6nIzWrlI+IWQv3A1D0E+bxcAH1RLB1wnw88C3rUrphOzha49R97etIjaNn5cWDW7H55y+fg8xd04Cf5QAbh5CbGQ4bj95iX7TD8AqJgI26z+BzYzmqO/vinJ53TBpx2UxGCMsgokJsgM7WXgyKVAoMrXL7CqehYDO882LG6PlgmNeq71j/PE2ExUhS7HFZf8eyxMmWqmpBRS52pQD7luPFcrAgpRqrOPrGhtGwddnvFV6EbKEx714UyXyjcfGlE+25RigcB3LjxEzc+klNhde+BimK0gkEmkzkBhHFbKDZx8WVUrV80mbAaumFLL/nbsntq1fwhuju1Y0W0Tytfk3XK06auFyutbrqS6v77r4AE3L5NZbuubrrDp+SwhMZtRa4uFNbv92XryPQl7OQshqUwso4iftvCKam/h5+TUlGyuvhrCCyXGyhvv11r87RfasCm0Mk3tVFkMgZu65prctBXOjUrl0xyo8Ihobz9xFFT9PIWTpdd17WfH0tiyXBz+0KSPekw1znSbsFT5Z5vVS6JbL566rto6YewTvNCgqhOzny0+KQh4F8vwBgcjrkU14fs/cuIcSNjeRbU5Lxc9n64DYrotxyqooCnplh9PmT2F9eLqyo3krIbr7Cry/7AKWH72Fwl7ZsWRINTg72MgKbXKozV4M4DesqLIC132pOL7Jijw1tWBKI+CukS784s2BdpMNorjCgX3jlWV9w4gu5tCyASpXmfQlMNPqHLFZb+8Y4NQyJW2BwptDFIQlwunVhiQw/ovpBYz1MpeRNwGHhB4GiSSzIm0GKXRwsjIUsA1Hbcel+2G6+yhomUYwZdcVbD2XsNxOa+fc/oEon989WUFLobj6xG0RLVUsl4ueoOVjf2w8j/cbFtW7X0ynio0zKhgpzGh9SCkhq90Xfi5j3mAu6VPgUsheefhcCMLWFfLpCW3u18Ttl9E+wBc5nROENp9z8X4YOo7fK1IXKGTZYFcwp7Pw0v6w9iym774qtmWldFy3inppBvTyMu6KzzsREioavrS0KJsbLcrlwYh5R4WQVWHFdvGQYPFcVoNzZHcQHuP6f2zT8+BS0P7evhyWHrkp/rWe1Rq4vDXhDWwd8LLFONhf2QLrozP13ju65Thc9KqHxv8eEF9/1KiYaPpLKsIsy6NNLTCVJ8tqX7clSQtanZDVNHsZo0QLZYKVVriqE88M0UZ4SRLOl7Wt0uRFPy3F6Oscn4gwYPlQ4PQy87b3KQX0/y9jxc9JJK+IFLMpdHCyMubkpBIKPg48qFfcJ9mGHwrElcdviaEMFKYUwKqg5WM9puwTkVFBhXJgau/KeoJWHUlrbD+NeTNNbZ8S8LUpCilk24/dI/Jnv3mrlIgTY8MVReev68+JRjo2R7GZzpigpQd3Wu/K8MuRXc++QUF7/WF4IiF7+f5z0TRGEezl7IA5/ati16UH+GrF6ST3l8kJ8wcGwc7aCn00qQUUm6x2s4Kr9SVrhfFvrfzhMKe1EuKeBFF1v8KjUr3QasJhIY57BfvhkybFjVbfJckIWd+qSsVUG5mVlKA1JWTpkWU19sQC/YqvMUErSTsYxzZRk/KQFG/9C5TrpNhEJJJMTqgFek2WTCRGoUBk9W/JkGDRof7aQjYqBtvO3xNCln9X2c3PiKmzd54Jz60qZAknhA3QNGHx8YfPIxGlmXQlXjMyRlgQRCOagcCl4NNWJlMKtaGLWa+qkCX/W3EKCw7eFP9XhSyhsGMCgXZqGQVqES9n7Piojp6QVR/7tElxjOueIGQJjxmHWqhDCBjN9enSE2hfyRfftSqdrJB14rjcuDjh11X5feN5RMfG6vmStaw8fhsfr7iI2O7LgXyVTb6HFLKvCL02zx/qC1k2e9Gj2mcDkE8Z5Sxgw5RYijbS2MXqIKur2mgn0ey1Cmg1BnhrtH4KwYsnRl9GkkbQx1yqdfLb8UKmbAcpZCUSI0gxK0lS0Lo52mFij0pGH+9SJT8al8plVgSTg401qhfx0surDY8fwFDv9206IatGS3UP8sP9Zy9FRfKDBcfQ9K8duPvspU7QUlTefvpC3P/J4hM6QasI2RgxCpbd/SkpaPmeXSftE3FhXI6vX9JH7/EvV5wSn0UVsiq0GrB5Tu942NmISq0xGwPvM7Rr8BiX93XHtN5VhAe2iLeziN9ihbtzlfx6GbtauD0jxlil5rbz+geKxAE1fiuvu5P4LExlMAZTDuJYCey+xHgsU5H6sK42HB2nHBXCneL5q7dKyYqsOfC4lu8ENPsjcWqBaLxaqQhaNhi1m6Y8Tm+mIVzydnRXBkswHkoVst4llSVxCiVV0PrVALouMq+hTPJmYNW99XilCc8UhWorFzkyxUAiMYrMmZUkiZpaoDZ7aVGbwvIz3N+M5i8uz1PAth+/G2duG+/IpZAd07USvFzsRdWSXfqsEBIurXMyl7eLA24+fiFyb1mxJa3L58VPbcuIuKlWo3frvL5VCnqK5idjfttXEbKMtdItwbcvh0+WnMDSI0o+qzGG1/PHkNqFU0zciYSB26HCc8z0Bn7ec3cSmr0MaVk+D35pV1Z3fsTwhMgYEeHFscFqaoG2Mq4luHAOzOpVHlbrPobVoWmJd4ge2o4LcSyuCHrMOC4qx393qoB6JZKv1kvioaXg8nZFsGhFphrbxfis/FWMC1ktHKjAxqSnIYBXMf3XoqXh2k7Ar6YUsukVnuvwR8Ce0cCtQ0rFnucxaFj8mGZ5ASLJWoRaYDOQYlbySkL2VQUtXzMimoJzFy4b8eKO714JLo622HT6LgbULJxoSAAFLRvEuJSvClk1nmvFsGqieervLRd197s42GL5sGp6U74shakEVx6Eo82YXWKIggoF7U9ty+L9hcd007u0MCeWebEp7RtltZoZr8kJ2aQELc+BoVfZkBK5XbCwX0U4bf4M1oeNCFkVKWhTJs/UWLWUgpa5rOY2GVHQ0pJg7LVMvYckfUG7CK0j6lhcOSBBkkUJlZ5ZyevCjn1DIUuP7NDaheGXI6FCFPoiGm3H7cbNRy/MypvlEjqzWU0JPGbL0hs6Y881McCAzVNsolKhV5TVUEMhO29AIGbtvZZIyC4cHCQef52OembucrQsvadcslc5ffsZwiOjxfsYgzm1KTHW3hAeOwpZbfyWVoD2r6E/bpZRWR8tOi7OqTqWlq9BUWwoZFkZf6e+P8rlc8PCfpWMCtnYyv2BvBUT7oiOgOP89ihnfQkTO5cS43KHzzuCLWfvJjnyV6LBlMhUc2jNhZYDU68lhWzGgDYRRm9RxEohK5GYhfTMSowSGxeHYrmc9Zu9OlXAiPpFsXRoNb2mMFZLc7o4iIis5FArgVwqNwZzUz2d7DG7X1UxYYspAIaCVosqZJccvolRmy4kErIFDRqsXhWKP/pUVUFb2MsZc/tXxej/LmHhIaXxy5Cf153DwoM3UkXQ0fPKpi0OPlChX3XhoGB80KiYGDChpWRuV11DnZZCmvNIITulV2UMrV0EE7oH4Gl4BKJ9yuptH1f/azyp8SUiuq7QbwpzdIOVe35ceKDEOWW3txVxY6kUKCGRSCQSiQ4pZiUmxds79YtiUK1COiFLHyQrnNqUA0vC8Y0taauTtlToqe097YAQoMyXpajO4WyPDxoWM/qaHzYqigdhEXpClvQM9hOCMyWErPaYMEqMPlgK2bFbL4mxulpyZNcfM8mUg9QQtKxuc1AEkwjyuDnqpRbQTsBJaaqgHdmkOHoE+SXysPLzfN2yNDoG5NMJ2YACnrCztYansz3sHJxwv1BrRDX9QydkUWUgTtx+gY9WXER0t2WKoHX2Bvptho1bbuy8HCouJLgv/N5IyeMvkUgkEokxpGdWkiRcimbOLJuxtGJIzaHltClzhCxfZ93J23hn/rFEzV6VCnig66S9ek1hbNziNCpGbD0Oj0Lr0bv0rAXaqvDcAYEi9uvbVWd097Pha3b/qqIi+TqeVVonaBVQl+U5uev4zSeoW9wbTf7aIbynKsPqFMF7DYvi/QXH9JrCWD3d/lEduDimfDYkBf/j8EiRb0shq83WpYDmueNFR1LNWOowhvyeTnrbsZnrSXgkcjjEwurRJVjlKCKWvPm61x4+FxPS7GNfAi8eAdm9xWhOeqJvPX2BPG7ZpJCVSCQSySsjPbOSFIMijp3zhmJIzaE1d1wpX6dRqdz4uHExPSGb3cEGf22+gFl9qwq/Jymd11XERh278QSPn0eaFLKqh7bzhL2oVdQbXzQvobufPtKuExU7A8Xaq0Bh9tnSkxi77ZIQcGy26j55nxC3Hk72mNwzQMRkkaF1iqBz1fz4cc0Z/NSmDFpXyKsTsosHB6faFCzGe3FfDIUs4Tkr6pP43Bk7N6yiGm7H6q+7kz2s7LLByquEzrvJ7Wi5EJ+JIzydfZQZ8/GeaDbbyYqsRCKRSN4UxjtXJK+FGL8aE2dURFBkMXM1taZTpQamRsWaErEUjxR5bDTS4mhnLZb/Wc1lVY9ClqNVOVDA190RCwYG4asVp/BZs5LYcf4+Khf0RIt/diZq9vq4SXEhGtWUA1XQrh1RQ+TQ/rTunJ6gXTY0GAVZRbRg5K0QsstOYpHqh42LQ8fK+fFli5IILJQDb/27UyzRT+oZgCPXn6BHUAG0HL1LVDjvPo3Ar+3LiqSHnkF+yOuRzeykB2MiMKnvJ5LUKF9zx/ya2o6CVtdYZGp7g2lEuudIJBKJRPIGkH91UhgKD3bjH7z2KFFcEqt728/fx/PIaJG5mhnhZ2SsFj87I6BU1HzT3RcfCuGXy81RJ2Rr+udE18ACyhjYduVw89FzTNxxWQjiBprBBBSyCwcFoXEpH1Ht1DaFNSrlA2dHW/QI9hP+Ua1dgRYJi4RsdAw2nL6bIGQB/LX5ImbvvYaKBTzE5LIbj19g8KxDQmR2rOwrKpjMvyWV/DwQZwV83qyk2UKWn52pA4bTzPj9RDvHgauP8CIyYXqXRCKRSCQSBSlmU0HIcvpU76kHsPviA52gpZBbfeIWBs06hA7j94hGp8wmaPkZFxy8gWFzj4hKqSpoVSHbaeJe9JtxEMuOhIhl7cp+nkLIMlv23rMINPpzB4J+2oyYOGBY3SIieorTpDpV9hVCdv7AQLFsz8oul9YXDQoSgrZb1fz4vHlJsVzuaGsjKrwUtLWKemFC90oWL3lTfFJE96nmp3f/6K2X0PjPHbgbGiG+pl/2s6XHxXm88/QFTt8KxddvlUKHyr5iP1ihNFfI/r7hHD5afByDZx/WCVpVyDJrl8J/58WHUtBKJBKJRGKAbABLIURD1ItosdR8/VG4uI9RVRRqdYp5Y8mRm2IMqlqspD900aBgZDeRUZrRoCBj1/4Xy0/p7mNWKZuzOAeeQpbNUyrftSqNNhUVX+mDsEgxROFRvJ3Ayd4Gc/sHonReN8zZdw1Ny+QW2aX8/94rjzC1V2VwOix7r1hFFSJWI1gpLimkefxfx7vJz/TLurOYsks/sUDFx9VBxIZxHCxjr3iBQiuAJdPGKFz/2Hge47df1t3H5jJ6htn8RiFL6wLh55nQIwBBhTxFw5dEIpFIJJkVSxrA5F/EFIL+UQoZLiurYjY6Ng4DZx4S4mTjmbt6Afr5PbOblcuaUeBHK+rjIqwBaof/sZtPhUjl575wTxkvS7gNI65YYeXyP6utXKJXxSxFIZfyaRHYeu4+Zu+7jvK+7ph34Aa6BxYQIu9lZAy8XR3E8r4h9COnxEUCBfKnTUvg6sNwbDmbeAra/AFBYr/pH6V+fZXUBIp0inZ+K6iFer5Xx/F7RLU65ImS20poo+DwBh43iUQikUgkCtJmkIJQzLBqGFQ4h+4+Clr6L7VCtlGpXPi7U/lM1fHNamRZX3fM6FNF1+FPzt8NSyRkZ/WrijJ53cTxEsLT3lZ4YYvnUtIMVEFLIUvO3nmmE7LMeKWFodWYXYhJSMVKFsZMGbN1sDJqLO2AlXZOzHoUHokTIQkVZS2stvP8vg68AKpfwgd/daqgN2DgyI0nekKWWbz0CfvKpACJRCKRSPSQYjaVBG1gIU+jj9OLmdmErKGgndm3iojeMoRVWK2QVdEKWkZJGYNClmNWu0zci0v3w/Bli1Jm7xetCKM2nhfWA62gpYidsusKHoZF6g01UDN0R/93AbbW1iLL1hh/b74oYrteNfrLmKA1BiPQVCGbWhFfEolEIpFkVORfxlSAMi64cE6jj9FykLnavvRxtLVGmbzuRpf/WV0sncdNr3KrFbRslirn6270dRuW8oGDnTVi4uKE6KP4Sy4/VRWyI+YdxZitl0TjnSpoKUD/3HRejJxtN243Hj2PEIJWFbJtxuwWCQY/rzsrxDmHL9Aby/On5a9NF1JE0FKkViuS0+ixoXWlgKcUshKJRCKRpDsxO3bsWJQtW1YYe3kLCgrC2rVrk3zOwoULUbx4cTg6OqJMmTJYs2YN0hMURCuP38KoTeeNPv7FspPYpUk5yEyI1IKoGHScsAf3nykd/1roAe00YU+i2C7C+ygKFx5MiMPSQu/x5XvPsfrtGmYLWVoLRi45gXUn74ivT90KFe8fGROLyTuvYNw2pemKebXtxu0Rnt1n8UKWk7PI/AM3hBCe078qVgytJtIRDFMOQh6/wOvYWBNSMHbpTRRT4WS0ATMPJYrtkkgkEolEksZiNl++fPjpp59w6NAhHDx4EHXr1kXLli1x6lRCR7yW3bt3o3Pnzujbty+OHDmCVq1aidvJkyeRHlDjt7SpBYaoTWHa2K7MJGQ7TdBPLTCETWHa2C7C/0/YfllYAUxBDy0TES7ce2a2cGTCAO0J2nSBEyGhWHL4pvAts9KqQkHb/J8daDhqu07IEg4+aFVeSV3IGd/s9VHj4jpB265SPnzfqrRZEVzG0MZvqakFxmBTmDa2SyKRSCQSSTqN5vL09MSvv/4qBKshHTt2xPPnz7Fq1SrdfYGBgShfvjzGjRuX4lEPlsCla86kr/XrViGiVCiafmtfVlTW9lx6qLufAmvPyLpGl+MzIvzM/1t+UiQPqHDJnA1hPBo9p+zXqzp2CywgMllj4+LE2FpWRrVwsMI79YsKjywbwFSYHrDz47pme0e5/H/mdii6TNynd/HwebMSqF3MW6QmGKsiq0J24cBgEcHFdATtZCu+7sbTd9GwpM9r+597Td2va3YjbtnshH+Y+/3u/KO6lAPCccB9qxeS3lmJRCKRZGpCLdBr6cYzGxMTg3nz5gmxSruBMfbs2YP69evr3deoUSNxvykiIiLEAdHeUgN6PnNkd8Dv7cvpKodqaoGLo51eygGbo5g/+6rVvPSIjbUVPmtWAhXzuyekFvStKjyw5QxSDirm98BnTYuL51Aglsrrho8aF9O9Fkfefta0hIjs0qYcODvYYmrvyoksCknBRrMSuV2FTYDvp/Ld6jPYeu4e5vUPFKLVEO7r4kHB8PXMlkjIqq+r+Hhf7xzSo/tnx/IolDO7TsguGRwsppY1LJlLL+WAwrlP9YJSyEokEolEkp7E7IkTJ+Ds7AwHBwcMGjQIS5cuRcmSJY1ue+fOHfj4JIw3Jfya95vixx9/FMpevfn6+iK1oI+TAnZUh/JoUlo/fktNOeBUqsk9K4vpV+b4PjMSTva2Iq0gqFAOIWTL5FNSC7SxXRT0s/tV0Qv95+O9qxUUgpZC9tMmxcVxs7JKSDkIKOAhJoAV8XK2WEBSDHJimI2BP+FO6Eu4ONrCwcbGaPICL0L4r1bIUnzSi0sML0bU+y3NJ+Y+LBkSLC4EKGR945u9tCkHjUvnwj9dKmSqCyCJRCKRSDKFzSAyMhLXr18XZeRFixZh0qRJ2LZtm1FBa29vj+nTpwvfrMqYMWPw9ddf4+7duyYrs7ypsDJLQZvSNgND76ytjVJ1NLYcz/zSzCZkDS0XbLIyHCLAZX4HG2tRxTYGl+75iKFY5evxOfSLWipkI6NjcOvJS+FJfRwepbu/X42C6Fe9kLAZaD2yWjgqlxO+cjrbC68shSwbxF5GxSKHs73e+X0RGS3sEEw9eJVqLV+bwpbfG4YWiqS+nyQSiUQiyYxkKJsBBWqRIkVQqVIlUUUtV64c/vrrL6Pb5sqVK5Fo5de83xSs+KppCeottaFQNSU8uNSdmYUsofA0Ng2LFVhTQpbwOcaEoPqclBKyQ2oXNipkaS3gKF1tUxify3G7fC016YBTzR6GRegqsRSy9M+2Hbtb+IZfpUmLQpYY8wIn9f0kkUgkEklWJ939hYyNjdWrpGqhl3bz5s16923cuNGkxzazwMokC+jGskxZ7dQ2nKUUfC++p9GpWdHGp2alNzjw4Me1Z/WErF8OJ9FYNn331USpBcuGVsOGd2smSjlgHi0FdfdJ+3D5wXNhT2g1erdO0FLIvhPfqDX/4E2jglb9mhVYc6eQSVIAHm8uPkUlTFPTwfti5XGXSCSSjE6aitmRI0di+/btuHr1qvDO8uutW7eia9eu4vEePXqI+1RGjBiBdevW4ffff8fZs2fx1VdfiUivYcOGIbNCMfk8ktFNu0VOqlb0UMgys7bbpH16E6xeF74Hl8xZgQyLjNYTtBReXy4/JaK00rsAowD9s1N5VCmoTGNjM9eiwcFgEXREfX+0jo/copCd1z8IBXI4wceF1oJgnaCtV8JbpC48CY/CHU3qgSpof1p7VidkVe6HRertB4/ZxfthaPHPTlHd1QpaPvbD2rP4e/OFdH88Mxw8zlHPgcn1gdvH9AUt/39lOzDjLeNCVyKRSCQZhjT1zDJ+i5XW27dvC18EByh8/PHHaNCggXi8du3a8PPzw7Rp0/SGJnz++edCAPv7++OXX35B06ZNzX7P1IrmSk0h237cHiEuHe2sMbtfIErlcRVxVxSyg2YeEtm1lf08MKNP1de2MKhCVs2C9fd2xuIhwSJJICo6Fl+uOIV5B26Ibd9rUBQDahYyailIT/BzfLrkhEhbcM9mJ/yv6mf9fvUZdK6SH345nUQDG+HnvPvsJf7afAHftSwt7A28j0MfWo3ZZTLKi3BC2NiuFXWWCFXIdhy/F2ER0SK1gM1ebC5jxiyFLKvEqv1heD3/dH88M5SQndIYuHsSsMsGdF8G5C6nPE4hO68LEBsN5A9UHuM2EolEIkkXWKLX0rwB7E2TocRsXBzeX3AMS4+E6O6joKVofRweiaGzDwshq0Jh+VGjYjqx9iqwAanaT1twPyxBsFHQzu5XFX9sPK8TsiqLBwejbD63dO/p5IUBj6fhseHnZaVUm65AKF6trBWrgva+pAStoZAlFKw1f/kPt56+1N1HQTunfyDGbL2IGXuu6b3GnH5VRdKFnZk5uhITxMUCy4YAx+Ym3Eex2nUx8PIpsKC7ImRVgoYBDb4GrBPHtEkkEonkzSPFbAodnLSG1xmcfMXxsCdDks7HDS6cA1N6VX7tqp6oJN4LQ8cJSiUxKUY2KY4eQX6ZvqFNCz2yP6w5g6m7lGqqlhXDqok0A61g5vG89igc7cbtRuiLpI/nuw2KYmAGqHRnCIRPNhyY1gy4dSTpbf1qAF0XysqsRCKRpCMyVJqBxDTMWWV3/fwBQSid1zXVhSxhVbGItzPmDwgU1oL0KGTpD2ZF9WX8v9p8V7WZKjIqJsVHvzK1YO2J2zpbgCEDZhzCA03KgXo8C3g6YdGgYKPDGVSkkE1hmCls5wT0Wg3kqWB6OylkJRKJJMMjxWw6RxW0CwYGwd3JLtHj+T2dMK13lRSt5lGA+fs4Y1z3SkYf71IlvxhykFZCdsWxENT7YyuevozC9N1XxJI/l/P5WNdJ+0SCwfPIGPy95UKKCVo1fsuw2UuLYcqB9nhyohcvOIzRpmJeDK5VWFZkU03QrgGclOl7ergXALovkRVZiUQiyeBIMZsBYEj/7ksPEfoiIWJK5W7oS5wMeZrinfBcpV15NMGrq2X/1Ud4GR1jNLbrTQjZT5acwI1HL0Sua5MyuXHq1lMxpKH75H04eO2xqJzS39sruGCKCFpWf0/ffpZIyNYp5i0mdmmjvCho241LPF6Zft3lR28Zff3D1x4jPFI/5UCSQkS/AK7uAF4+SfxY2B0g5JBMM5BIJJIMjhSz6RwKuF2XlNQCY9oxIjoWXSbtxWmD2K7XQcRvrTglMlONQU9tu7G7E8V2pTYUhL+uPyeENrn5+AU6TdgLV0c79Ji8XwhZlfkHboglfwrNc3efvdKoWRUOMiidxxWtKihRXmqz17huFUXz27Ih1XSC1tbaCl+2KIXomITjwvPCavFMg2YvlasPw8UwBsPYLslrQs/slR3xqQVGfjaiI4CZrYHbR6WglUgkkgyMTDPIIEJWm1pAAcXHLtwL00s5mNMvECXzuL7WcrUqZA1TCxqXzoWdFx7oNYUV9XEWua3O9rZJTvZKKTiFi0MMKPwePtfPctVib2ONMd0qioljtAdUK+KVIpYIHpuRS0+IzFltagGF8r3QCNHk9U3L0qheJKfu/VQha+izbVjSB3svP0Toy4TjmRDbZaubCCZJCSGrabzLU1Gp1t47k3CfiO1aCuQuLy0HEolEkk6QDWCZiJuPwvWELJu96J/ltCptUxiXwm89eaGrWr4OIU9eJGr2Gt2lIuYP1G8K42StMFFNfDPVWXtbG+R2cxSCL0d2+zcqZAnF649tyiSK32IsmberA7Z9WEdPyKq2zRuPwvVeh/m8Y7tVEhcC2qawJy+i8PRFFF6jiCxJOPLA46v6QpbNXr3XAP026zeFRb8EntJSk6VSCiUSiSTTIMs/6RiKoo6V8+OLZiUSpRZoUw5YFP2zY3kxrep1hRtF2sQeAajhn1MvtcDG2gpFvJx1gpbL6mJ53dnhjWaiUtDmdc+GUR3LG318WN0iKOrtgj2XHqBWsdc/HoY42NroCVmtoKUdwfD9uD3FL20J2kETPJ7alAPP7PZi8hjFOl9H8pqw2lqxB9D458SpBdqUA15ttJ4AFG+q3C+RSCSSDIe0GWQAaCn479w9IYi0FgI1h3b/lUcILOSZKPj/deDy+OYzyntqBRqX2i/dfw63bHbwdnmzQlZ7PNRmL0PyeWTDvAGBWH38NlqUyyNEd3oY6MDjtv70XWEv0J5DNYfWwdY6XsjKjNkUhaNqz28AijbUtxCoObRXdwIFa0ghK5FIJOkMOTQhhQ5OeoLi0pgXloL2ZXSsWFZ/U+/J+62trNKkgpiUkM0IgtZYVZf3s0AohWwqClpjo2opaGkxkGNsJRKJJN0hPbOZEFNNXcyhTQ0hm9R78v60ELIU0YZClh7ZIbUL63lo1ZSD5uXyYO6+a8ogg+i0N6IaE7Lq/VLIpiKmxKrIoTXxmEQikUgyDGlfrpJIzITaw8fVMVGzV89gPywcFKQnaD2c7OHEJrCoGOHxpUdVIpFIJBJJ5kOKWUmGgc1Uf3Qsh2ZlcgshO757JSFYT958itxu2XQpB2XyumFm3yqYsP0SRtQviuxvKDpMIpFIJBLJm0c2gEkyHBHRMbh0L0yMiL388DkK53QWTWrMob0bGiGSAfh/WxtrKWQlEolEIsnkntmUa3+XSN5ghdbfx0U0dRWL/5fQd5rLzVFM4aKn18bKSlZkJRKJRCLJ5EibgSRDogpYw5QCfs2mOP4rrQUSySvAhAdjxETJsb8SiSRdIsWsRCKRSBKE7KnlQNTLxEI2/IEyBtjwMYlEIkljpJiVSCQSiSJk13wELB0ArPkgQbSqQnZiPWBaM+DuSSloJRJJukKKWYlEIsnqREcoQvbwdOXrIzMVQRsTnSBkQ0OUqWnTWwD3TknLgUQiSTfIBjCJRCLJ6sTFAjn89e+joKWApbXg2e2E+x1cgOxegJUcvSyRSNIHUsxKJBJJVoeT0Kr0U/6/8fOE+y9t0d/O2QfotwlwzgXYJgwpkUgkkrRE2gwkEolEkiBoG3xr/GiwGiuFrEQiSYdIMSuRSCSS+L8IdkCp1saPhndJwDWPrMhKJJJ0hxSzEolEIolPLbgPTGlk/Ghc2QasfEcmGUgkknSHFLMSiUSS1dHGb7HpyxRqyoHMmpVIJOkIKWYlEokkq2NjB8zroi9knb2Btw8DDb5JLGhPLjI9KUwikUjeMFLMSiQSSVaHldn2M5S0AlXI9tsMuOcHqgwAGnyXsG3ZjkCZ9oCtY5rtrkQikWiR0VwSiUSS1WFl1iWXImBZoe00W4nf4v28qbFdd08Ab/0D2Dqk9R5LJBKJDilmJRKJRJIgaAftAKIj9VML1NguDkqQ+bISiSSdIcWsRCKRSBIErfjLYGQgAgWtRCKRpEOkZ1YikUgkEolEkmGRYlYikUgkEolEkmGRYlYikUgkEolEkmGRYlYikUgkEolEkmGRYlYikUgkEolEkmGRYlYikUgkEolEkmGRYlYikUgkEolEkmGRYlYikUgkEolEkmGRYlYikUgkEolEkmHJchPA4uLixL+hoaFpvSsSiUQikUgkEiOoOk3VbUmR5cTss2fPxL++vr5pvSsSiUQikUgkkmR0m5ubW1KbwCrOHMmbiYiNjcWtW7fg4uICKyurtN6dTHklxQuFGzduwNXVNa13RxKPPC/pF3lu0ifyvKRf5LnJGuclLi5OCNk8efLA2jppV2yWq8zygOTLly+tdyPTw29kKWbTH/K8pF/kuUmfyPOSfpHnJvOfF7dkKrIqsgFMIpFIJBKJRJJhkWJWIpFIJBKJRJJhkWJWkqI4ODjgyy+/FP9K0g/yvKRf5LlJn8jzkn6R5yZ94pCGf/+zXAOYRCKRSCQSiSTzICuzEolEIpFIJJIMixSzEolEIpFIJJIMixSzEolEIpFIJJIMixSzEolEIpFIJJIMixSzErMZO3YsypYtqwtEDgoKwtq1a01uP23aNDFlTXtzdHSURzyV+emnn8Sxfuedd5LcbuHChShevLg4J2XKlMGaNWvkuUkH50b+3KQ+X331VaLfTfxZSAr585I+z438eXlzhISEoFu3bsiRIweyZcsm/m4cPHgwyeds3boVFStWFAkHRYoUEecrNchyE8Akrw4np/GPsb+/vxgzN336dLRs2RJHjhxBqVKljD6HovfcuXO6r+UI4dTlwIEDGD9+vLjoSIrdu3ejc+fO+PHHH9G8eXPMmTMHrVq1wuHDh1G6dOlU3susibnnhsifm9SHv7M2bdqk+9rW1vSfQ/nzkn7PDZE/L6nP48ePUa1aNdSpU0cUsby8vHDhwgV4eHiYfM6VK1fQrFkzDBo0CLNnz8bmzZvRr18/5M6dG40aNUrZHWQ0l0Tyqnh4eMRNmjTJ6GNTp06Nc3Nzkwf3DfHs2bM4f3//uI0bN8bVqlUrbsSIESa37dChQ1yzZs307qtatWrcwIED38CeZj0sOTfy5yb1+fLLL+PKlStn9vby5yX9nhv58/Jm+Pjjj+OqV69u0XM++uijuFKlSund17Fjx7hGjRql8N7FxUmbgeSViImJwbx58/D8+XNhNzBFWFgYChQoAF9fX1HFPXXqlDziqcTQoUPFVXD9+vWT3XbPnj2JtuOVMu+XpO25IfLnJvVhVSlPnjwoVKgQunbtiuvXr5vcVv68pN9zQ+TPS+qzYsUKBAQEoH379vD29kaFChUwceLEJJ/zJn9upJiVWMSJEyfg7Ows/C9cOli6dClKlixpdNtixYphypQpWL58OWbNmoXY2FgEBwfj5s2b8qinMLywoEWAtgFzuHPnDnx8fPTu49e8X5K250b+3KQ+VatWFd69devWiV4ALofWqFEDz549M7q9/HlJv+dG/ry8GS5fvizOB22G69evx+DBgzF8+HBhNzSFqZ+b0NBQvHjxImV3MMVrvZJMTURERNyFCxfiDh48GPfJJ5/E5cyZM+7UqVNmPTcyMjKucOHCcZ9//nmq72dW4vr163He3t5xx44d092X3FK2nZ1d3Jw5c/TuGz16tHgdSdqeG0Pkz03q8/jx4zhXV1eTlin585J+z40h8ucldeDPQFBQkN59b7/9dlxgYKDJ59Ba9cMPP+jdt3r1ak6djQsPD0/R/ZOVWYlF2Nvbi47ESpUqiUpTuXLl8Ndff5n1XDs7O7E0cfHiRXnUU5BDhw7h3r17omOUjRK8bdu2DX///bf4Py0hhuTKlQt3797Vu49f835J2p4bQ+TPTerj7u6OokWLmvzdJH9e0u+5MUT+vKQObNoyXIUtUaJEkhYQUz83bNhjGkJKIsWs5LWgdSAiIsKsbfmHmzYF/lBIUo569eqJ43r06FHdjd4mes34fxsbm0TPoc+ZnaVaNm7cmKT/WfJmzo0h8ucm9aHn8tKlSyZ/N8mfl/R7bgyRPy+pA5MMtMlE5Pz586InxhRv9OcmReu8kkwNbQXbtm2Lu3LlStzx48fF11ZWVnEbNmwQj3fv3l3cp/L111/HrV+/Pu7SpUtxhw4diuvUqVOco6Oj2bYEyatjuJRteG527doVZ2trG/fbb7/FnTlzRnQQcxnpxIkT8rCn8bmRPzepz/vvvx+3detW8buMPwv169cXlql79+4ZPSfy5yX9nhv58/Jm2L9/v/ib8f333wur4ezZs+OcnJziZs2apduG54XnR+Xy5ctimw8//FD8naGVzcbGJm7dunUpvn8yZ1ZiNlwu7dGjB27fvg03NzeRl0kjeIMGDcTjXG6wtrbWy6Xr37+/MIEzi47WBOY1mmoYk6QehueGjXjMlv3888/x6aefClP/smXLZMZsGiB/bt48bEJlzvLDhw9FXmb16tWxd+9e8X9j50T+vKTfcyP/zrwZKleuLBq+R44ciW+++QYFCxbEn3/+KVaZVKgNtLYDbrN69Wq8++67wo7IrPpJkyalfMYsM+ypaFP8VSUSiUQikUgkkjeA9MxKJBKJRCKRSDIsUsxKJBKJRCKRSDIsUsxKJBKJRCKRSDIsUsxKJBKJRCKRSDIsUsxKJBKJRCKRSDIsUsxKJBKJRCKRSDIsUsxKJBKJRCKRSDIsUsxKJBKJRCKRSDIsUsxKJBKJRCKRSDIsUsxKJJJMyZMnT2BlZZXo5u7unta7JpFIJJIURIpZiUSSqVm8eLGYGc4bZ4lLJBKJJHMhxaxEIsmUREdHi39z5MiBXLlyiZubm5vRbXv16pWogvvOO+/oHufXy5Yt0309efLkRNv4+fklEst83VatWum+XrduHapXry6qw9yv5s2b49KlS0l+jtq1a+u9z6RJk8TzDx8+rLcd39/wM6j7vHXrVvE1q9Xk7NmzaNy4MTw8PMSN+/n06VOjx8Pe3h7FixfHzJkzdY9zn1u2bAkfHx84OzujcuXK2LRpEyzl5s2b6Ny5Mzw9PZE9e3YEBARg37594rGvvvpKvP/w4cP1nvPuu++K+/m4RCKREClmJRJJpiQiIkL86+DgkOy2cXFxQtypFdygoCCT2z5//hxffPGFEHGWwue+9957OHjwIDZv3gxra2u0bt0asbGxZj1/wYIFQsytWLECFStWTPQZvvnmG91nMMXjx49Rt25dnchduXIlDhw4gD59+uhtpx6PCxcuoEWLFujduzfCwsLEY/y3adOm4jMcOXJEbMttrl+/bvax4GvUqlULISEh4vMcO3YMH330kd6xoFieO3cuXr58Kb7mv7Nnzxb3SyQSiYqt7n8SiUSSiXj06JH418XFJdlto6KihDhl9ZawGmmKX375BSVLltRVfi2hbdu2el9PmTIFXl5eOH36NEqXLp3kc9euXSsE5cKFC1GzZk2jn4EVTvUzmGLevHmiQktRyOowmThxIqpVq4aLFy+iSJEiuosAvhZFcp48eUTl1MbGRjxWrlw5cVP59ttvsXTpUiFKhw0bZtaxmDNnDu7fvy+ENPebqO+twvfPnz+/+Mzdu3fHokWLEBgYaJFolkgkmR9ZmZVIJJkSVvxI7ty5k902NDRUiLXkuHXrFv744w/8/vvvRh//+OOPhShWbxSMWljl5LJ6oUKF4OrqKqwBJDlxtn//fiGEuY9Vq1Z95c+QL18+jBgxAsWKFdMJWcLXtLW1FaJaZdWqVeIzUNSyEj19+nRky5ZNV1X94IMPUKJECWF54HZnzpyxSGQePXoUFSpU0AnZ/7dz97ywRVEcxvf9DqIVhZKoFBKFKESjkGhEKLwTpURQihA6nUqh0fgACgpE5QNovESjUUskcm+elWwZMjNnrhvFmfv8kpM7zMyZmXMT+c/aa69Uw+zsbDo4OIjb/DszM9Pwa0j6PxhmJTUlghlVz6KwlEMq1cci6+vraXR09FNVstLKykqEtHwMDw9/up+leCrGVELpDc39oW9vb3Vf9/r6OkJ0V1dX1conQZYWhqLPcHFxkebn52veTy9q1t/fH5+B5X/aFyYmJtLDw0PcR5ClEru1tRXn5HGdnZ2Fn6NSDsZFhoaG0uPjYzo5OUn39/fR3iBJlQyzkpoS/Zy9vb2FjyMEUlWkSlgPgY1l7s3NzZqPaWlpiaXyfFS2OLy8vKTb29u0sbGRBgYGoqpJ/2ojWGInhLLxjIopQbISS/UE0e7u7rrnaW9vj2V63gfvJyNU0zbBe8qo8vIZ+B19vrRe5E1eV1dXsUmMfl9CLO0AOeg2imDONc3tILXQ2jA1NRWvR5tFbnWQpMwwK6mpvL6+Ruijx3RwcDA9Pz9/HOzYpweU2+/v77Grn2V/lsqpANazt7cXoa6RCm41TA1gaZ+lcnpTz87O4nyNyNXltra2tLu7mxYWFj7C6Pn5eVpaWoqKZWtra+G5aFegYj0+Ph5V18vLy1i6HxkZ+dSzygY6rhMTB5igQOhkqgE6OjqiUport2NjYw1vYsu47oRgpj0Qju/u7mKMGlXor+bm5tLa2lrdqrKk/5dhVlJTOT4+TtPT0xFaFxcXo2c2H4y4Ykme209PTzHeiYokFcei6QRUWdlt/11MLmDz1c3NTWz2YioBwfRvEex4/vLycvzMFIK+vr50dHTU0PPpgSXos2GMKi2tDz09PbEZrRJjxLhOVHN3dnbS/v5+jBUDLQ+EcyrfPJ8vDV+nK3Btc09wNVR6T09PI4ATxKnwbm9vV628EnpXV1e//UVCUnP79Zu/+JLUJA4PD+Ng7FQtLMnTf1kvbOnfTE5OxnXm/0KSfpKjuSQ1FTYWFW36Yk6pvZc/hxoJXyZoYZCkn2ZlVpIkSaVlz6wkSZJKyzArSZKk0jLMSpIkqbQMs5IkSSotw6wkSZJKyzArSZKk0jLMSpIkqbQMs5IkSSotw6wkSZJSWf0Bi21QUrZEqiQAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8, 5))\n",
+    "sns.scatterplot(\n",
+    "    data=penguins,\n",
+    "    x=\"Длина клюва, см\",\n",
+    "    y=\"Масса тела, кг\",\n",
+    "    hue=\"Вид\",\n",
+    "    style=\"Пол\",\n",
+    "    s=90\n",
+    ")\n",
+    "plt.title(\"Связь длины клюва и массы тела\")\n",
+    "plt.xlabel(\"Длина клюва, см\")\n",
+    "plt.ylabel(\"Масса тела, кг\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "768bd539-4769-4aa5-839d-e98dcd6b68dd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8, 5))\n",
+    "sns.boxplot(data=penguins, x=\"Остров\", y=\"Длина ласт, см\", hue=\"Остров\", legend=False)\n",
+    "plt.title(\"Распределение длины ласт по островам\")\n",
+    "plt.xlabel(\"Остров\")\n",
+    "plt.ylabel(\"Длина ласт, см\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "18cf8956-f195-4435-ac1f-452fc7c6f351",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Средняя масса тела по видам:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Вид\n",
+       "Адели            3.70\n",
+       "Антарктический   3.73\n",
+       "Папуанский       5.08\n",
+       "Name: Масса тела, кг, dtype: float64"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Средняя длина клюва по полу:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Пол\n",
+       "Самец   4.59\n",
+       "Самка   4.21\n",
+       "Name: Длина клюва, см, dtype: float64"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Средняя длина ласт по островам:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Остров\n",
+       "Биско       20.97\n",
+       "Дрим        19.31\n",
+       "Торгерсен   19.12\n",
+       "Name: Длина ласт, см, dtype: float64"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(\"Средняя масса тела по видам:\")\n",
+    "display(penguins.groupby(\"Вид\")[\"Масса тела, кг\"].mean().round(2))\n",
+    "\n",
+    "print(\"Средняя длина клюва по полу:\")\n",
+    "display(penguins.groupby(\"Пол\")[\"Длина клюва, см\"].mean().round(2))\n",
+    "\n",
+    "print(\"Средняя длина ласт по островам:\")\n",
+    "display(penguins.groupby(\"Остров\")[\"Длина ласт, см\"].mean().round(2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "d47424eb-aed6-404f-9d45-86d408e2a762",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка данных о пингвинах: 100%|█████████████████████████████████████████████████| 344/344 [00:00<00:00, 670.71it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Использование tqdm\n",
+    "for i in tqdm(range(len(penguins)), desc=\"Обработка данных о пингвинах\"):\n",
+    "    time.sleep(0.001)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f962b6d8-8c44-4578-8a96-c4adf3cd7d98",
+   "metadata": {},
+   "source": [
+    "### Вывод\n",
+    "\n",
+    "В ходе работы был проанализирован открытый датасет penguins.csv.  \n",
+    "Данные были загружены в pandas с помощью функции pd.read_csv(), переведены на русский язык и приведены к сантиметрам и килограммам.  \n",
+    "С помощью методов info() и describe() были изучены основные характеристики набора данных, а графики histplot, scatterplot и boxplot позволили наглядно показать распределение и взаимосвязи между признаками.  \n",
+    "Дополнительно был создан новый столбец \"Условный размер\", что показывает изменение параметров по сравнению с примерами из задания."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "69dda023-e5b1-45da-861b-a8d67cfff90c",
+   "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": "3.14.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
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diff --git a/week2_analysis.ipynb b/week2_analysis.ipynb
new file mode 100644
index 0000000..3c57205
--- /dev/null
+++ b/week2_analysis.ipynb
@@ -0,0 +1,757 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "849d9ce8-144a-4c59-9fab-c749bd024cbc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Учебная практика №2.2. \n",
+    "## Анализ данных в Jupyter Notebook\n",
+    "\n",
+    "Освоить JupyterLab для работы с Python-кодом, анализа данных и визуализации.\n",
+    "Познакомиться с основами работы с pandas, numpy, matplotlib, seaborn и tqdm.\n",
+    "Научиться комментировать код, изменять параметры и анализировать результат.\n",
+    "Укрепить навыки работы с Git: вести репозиторий, фиксировать изменения, документировать процесс."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "6920fb8d-c454-46e4-a279-86516823aada",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\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",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Дмитрий</td>\n",
+       "      <td>20</td>\n",
+       "      <td>78</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Елена</td>\n",
+       "      <td>21</td>\n",
+       "      <td>91</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Максим</td>\n",
+       "      <td>22</td>\n",
+       "      <td>85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Ольга</td>\n",
+       "      <td>23</td>\n",
+       "      <td>88</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Светлана</td>\n",
+       "      <td>24</td>\n",
+       "      <td>95</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Имя  Возраст  Баллы\n",
+       "0   Дмитрий       20     78\n",
+       "1     Елена       21     91\n",
+       "2    Максим       22     85\n",
+       "3     Ольга       23     88\n",
+       "4  Светлана       24     95"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Информация о данных:\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",
+      "Статистика:\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>Возраст</th>\n",
+       "      <th>Баллы</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>5.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>22.000000</td>\n",
+       "      <td>87.400000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>1.581139</td>\n",
+       "      <td>6.426508</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>20.000000</td>\n",
+       "      <td>78.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>21.000000</td>\n",
+       "      <td>85.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>22.000000</td>\n",
+       "      <td>88.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>23.000000</td>\n",
+       "      <td>91.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>24.000000</td>\n",
+       "      <td>95.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Возраст      Баллы\n",
+       "count   5.000000   5.000000\n",
+       "mean   22.000000  87.400000\n",
+       "std     1.581139   6.426508\n",
+       "min    20.000000  78.000000\n",
+       "25%    21.000000  85.000000\n",
+       "50%    22.000000  88.000000\n",
+       "75%    23.000000  91.000000\n",
+       "max    24.000000  95.000000"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Пропущенные значения:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Имя        0\n",
+       "Возраст    0\n",
+       "Баллы      0\n",
+       "dtype: int64"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Создаем DataFrame с измененными данными\n",
+    "data = {\n",
+    "    \"Имя\": [\"Дмитрий\", \"Елена\", \"Максим\", \"Ольга\", \"Светлана\"],\n",
+    "    \"Возраст\": [20, 21, 22, 23, 24],\n",
+    "    \"Баллы\": [78, 91, 85, 88, 95]\n",
+    "}\n",
+    "\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "display(df.head())\n",
+    "\n",
+    "print(\"Информация о данных:\")\n",
+    "df.info()\n",
+    "\n",
+    "print(\"Статистика:\")\n",
+    "display(df.describe())\n",
+    "\n",
+    "print(\"Пропущенные значения:\")\n",
+    "display(df.isnull().sum())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "2723f4ac-22c0-46e9-8a6a-d63042c74e4f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Обновленный DataFrame:\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>Повышенные баллы</th>\n",
+       "      <th>Категория</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Дмитрий</td>\n",
+       "      <td>20</td>\n",
+       "      <td>78</td>\n",
+       "      <td>89.70</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Елена</td>\n",
+       "      <td>21</td>\n",
+       "      <td>91</td>\n",
+       "      <td>104.65</td>\n",
+       "      <td>B</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Максим</td>\n",
+       "      <td>22</td>\n",
+       "      <td>85</td>\n",
+       "      <td>97.75</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Ольга</td>\n",
+       "      <td>23</td>\n",
+       "      <td>88</td>\n",
+       "      <td>101.20</td>\n",
+       "      <td>B</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Светлана</td>\n",
+       "      <td>24</td>\n",
+       "      <td>95</td>\n",
+       "      <td>109.25</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Имя  Возраст  Баллы  Повышенные баллы Категория\n",
+       "0   Дмитрий       20     78             89.70         A\n",
+       "1     Елена       21     91            104.65         B\n",
+       "2    Максим       22     85             97.75         A\n",
+       "3     Ольга       23     88            101.20         B\n",
+       "4  Светлана       24     95            109.25         A"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Студенты старше 21 года:\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>Повышенные баллы</th>\n",
+       "      <th>Категория</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Максим</td>\n",
+       "      <td>22</td>\n",
+       "      <td>85</td>\n",
+       "      <td>97.75</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Ольга</td>\n",
+       "      <td>23</td>\n",
+       "      <td>88</td>\n",
+       "      <td>101.20</td>\n",
+       "      <td>B</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Светлана</td>\n",
+       "      <td>24</td>\n",
+       "      <td>95</td>\n",
+       "      <td>109.25</td>\n",
+       "      <td>A</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Имя  Возраст  Баллы  Повышенные баллы Категория\n",
+       "2    Максим       22     85             97.75         A\n",
+       "3     Ольга       23     88            101.20         B\n",
+       "4  Светлана       24     95            109.25         A"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Группировка по категориям:\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 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=\"3\" halign=\"left\">Баллы</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>mean</th>\n",
+       "      <th>max</th>\n",
+       "      <th>min</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Категория</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>86.0</td>\n",
+       "      <td>95</td>\n",
+       "      <td>78</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>B</th>\n",
+       "      <td>89.5</td>\n",
+       "      <td>91</td>\n",
+       "      <td>88</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          Баллы        \n",
+       "           mean max min\n",
+       "Категория              \n",
+       "A          86.0  95  78\n",
+       "B          89.5  91  88"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df[\"Повышенные баллы\"] = df[\"Баллы\"] * 1.15\n",
+    "df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\", \"A\"]\n",
+    "\n",
+    "print(\"Обновленный DataFrame:\")\n",
+    "display(df)\n",
+    "\n",
+    "print(\"Студенты старше 21 года:\")\n",
+    "display(df[df[\"Возраст\"] > 21])\n",
+    "\n",
+    "print(\"Группировка по категориям:\")\n",
+    "display(df.groupby(\"Категория\").agg({\"Баллы\": [\"mean\", \"max\", \"min\"]}))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "0c5276b5-d3ac-4737-9947-770c5033cb4a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Сумма элементов массива: 42\n",
+      "Среднее значение: 7.0\n",
+      "Медиана: 7.0\n",
+      "Стандартное отклонение: 3.415650255319866\n",
+      "Матрица:\n",
+      "[[2 4]\n",
+      " [6 8]]\n",
+      "Массив linspace:\n",
+      "[ 0.          2.22222222  4.44444444  6.66666667  8.88888889 11.11111111\n",
+      " 13.33333333 15.55555556 17.77777778 20.        ]\n",
+      "Случайные значения:\n",
+      "[-0.09227145 -0.27139135 -0.71140609 -1.33075997 -1.3392746  -0.82396103]\n",
+      "Скалярное произведение: 23\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Работа с numpy\n",
+    "arr = np.array([2, 4, 6, 8, 10, 12])\n",
+    "\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))\n",
+    "\n",
+    "matrix = np.array([[2, 4], [6, 8]])\n",
+    "print(\"Матрица:\")\n",
+    "print(matrix)\n",
+    "\n",
+    "line = np.linspace(0, 20, 10)\n",
+    "print(\"Массив linspace:\")\n",
+    "print(line)\n",
+    "\n",
+    "random_values = np.random.randn(6)\n",
+    "print(\"Случайные значения:\")\n",
+    "print(random_values)\n",
+    "\n",
+    "dot_result = np.dot([2, 3], [4, 5])\n",
+    "print(\"Скалярное произведение:\", dot_result)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "d45b162e-ed66-40b7-ab88-3aea4f3dfd95",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Графики matplotlib\n",
+    "x = np.linspace(0, 12, 120)\n",
+    "y1 = np.sin(x)\n",
+    "y2 = np.cos(x)\n",
+    "\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.plot(x, y1, label='sin(x)', color='red')\n",
+    "plt.plot(x, y2, label='cos(x)', color='blue', linestyle='--')\n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Графики синуса и косинуса\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "8a1b2f7c-036b-4820-ae63-e2dbd8dce701",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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SpZKLDgDAQtauVP02Va1QNC2ILrTiQq0ePXpUenHIWLuR7Sq9CG1OacSCPTzZpq1vu9qmlWFfbZ1KC/gYPD95raJtXAEAIIumAq2Vb/yt/5shALDwqbgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALJQ8eD6/vvvp3333Tf17t07de3aNQ0cODA988wzVa+XSqU0fPjwtMwyyxSvDx48OL355psVXWYAANpYcP3ss8/Spptumjp16pTuueee9Morr6Rf//rXafHFF6+a5uyzz07nnXdeuuSSS9KTTz6ZunXrloYMGZJmzJhRyUUHAGAh65gq6KyzzkorrLBCGjduXNW4fv361ai2nnvuuenkk09OO+64YzHu6quvTksvvXS67bbb0p577lmR5QYAoI1VXO+44460/vrrp9122y0ttdRSaZ111kmXXXZZ1etvvfVWmjRpUtE8oKxnz55po402ShMnTqxznjNnzkzTp0+vMQAAkL+KBtd//OMf6eKLL079+/dP9957b/rRj36UfvKTn6SrrrqqeD1Ca4gKa3XxvPxabaNGjSrCbXmIii4AAPmraHCdM2dOWnfdddMvfvGLotp62GGHpUMPPbRozzq/hg0blqZNm1Y1vPvuu826zAAAtMHgGj0FrLHGGjXGrb766umdd94pHvfp06f4f/LkyTWmiefl12rr3Llz6tGjR40BAID8VTS4Ro8Cr7/+eo1xb7zxRurbt2/VhVoRUB988MGq16PNavQuMGjQoIW+vAAAtNFeBY455pi0ySabFE0Fdt999/TUU0+lSy+9tBhCu3bt0tChQ9MZZ5xRtIONIHvKKaekZZddNu20006VXHQAANpScN1ggw3SrbfeWrRLPe2004pgGt1f7bPPPlXTnHDCCemLL74o2r9OnTo1bbbZZmnChAmpS5culVx0AADaUnAN22+/fTHUJ6quEWpjAACg7ar4LV8BAKApBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZKHj/PxQ+/btU7t27ep9ffbs2V9nmQAAoHmC66233jo/PwYAAAs3uO644441nt9yyy3phRdeSAMGDEi77777/C8NAAAsqDauZ511Vtprr73ShAkT0iGHHJJGjhz5dWcJAADNH1yvuuqqdPnll6ennnoq3X777WncuHFfd5YAAND8wfWDDz5IG2+8cfE4/n///fe/7iwBAKD5g2v0INCx4/81le3QoUOaM2fO150lAAA0z8VZ66yzTlV3WF9++WXaYYcd0iKLLJJKpdL8zA4AABZMcN1pp53q7WGg+msAAFDR4DpixIhmWwAAAFhgwXX69OkNvt6jR4/5mS0AADRvcO3Vq1edt3yNNq4x3i1fAQBoEcE13HTTTWmJJZZo3qUBAIDmDq6bbrppWmqppeb3xwEAYOEE11deeSV98sknqVu3bqlPnz5Fd1gAANDibkCw9dZbpzXXXDP169evCK8DBw5MY8aMad6lAwCAr1Nxfeutt4oLsb766quih4G47etTTz2VTjnllPSf//wnHX/88fMzWwAAaN7g2rdv3xrP11tvveLuWauuumo67bTTBFcAAFpOG9e67LnnnkXzAQAAaPE3IFhllVW+zvIAAECd3IAAAIAsuAEBAABZcAMCAACy4AYEAABkwQ0IAADIghsQAACQBTcgAAAgC25AAABA627jWpdOnTqlddddtzlnCQAA819xnT17dhozZky64YYb0jvvvJNmzZpV4/VPP/10fmYLAADNW3EdOXJkGj16dNpjjz3StGnT0rHHHpt22WWX1L59+3TqqafOzywBAKD5g+v48ePTZZddlo477rjUsWPHtNdee6XLL788DR8+PD3xxBPzM0sAAGj+4Dpp0qQ0cODA4nH37t2LqmvYfvvt0x/+8If5mSUAADR/cF1++eXThx9+WDxeeeWV03333Vc8fvrpp1Pnzp3nZ5YAAND8wXXnnXdODz74YPH46KOPTqecckrq379/2n///dPBBx88P7MEAIDm71Xgl7/8ZdXjuECrb9++6fHHHy/C6w477DA/swQAgAXbj2s0D7jzzjvTlClTUs+ePb/u7AAA4OtXXFdcccX0/PPPp969exfP77///rTddtsV7VqjK6xzzjknXXvttWm33Xabl9kCAEDzVlzfe++94uYDZb/61a+KrrCmTp2aPvvss3T44Yens88+e15mCQAAC76pwKuvvlpcnNWhQ4ei4hqP33zzza8zSwAAaP7gGpXWJZZYour54osvnj7//POvM0sAAPj6wbVdu3bFUHscAAC0qIuzSqVSOvDAA6tuMjBjxox0xBFHpG7duhXPZ86cuWCWEgCANm+egusBBxxQ4/m+++471zRxEwIAAKhocB03blyzLwAAACyUGxAAAMDCILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBZaTHD95S9/mdq1a5eGDh1aNS5uKXvkkUem3r17p+7du6ddd901TZ48uaLLCQBAGw6uTz/9dPrtb3+b1lprrRrjjznmmHTnnXemG2+8MT3yyCPpgw8+SLvsskvFlhMAgDYcXP/1r3+lffbZJ1122WVp8cUXrxo/bdq0NHbs2DR69Oi01VZbpfXWW6+45ezjjz+ennjiiYouMwAAbTC4RlOA7bbbLg0ePLjG+GeffTZ99dVXNcavttpqacUVV0wTJ06sd34zZ85M06dPrzEAAJC/jpV88+uuuy4999xzRVOB2iZNmpQWWWSR1KtXrxrjl1566eK1+owaNSqNHDlygSwvAABtsOL67rvvpp/+9Kdp/PjxqUuXLs0232HDhhXNDMpDvA8AAPmrWHCNpgBTpkxJ6667burYsWMxxAVY5513XvE4KquzZs1KU6dOrfFz0atAnz596p1v586dU48ePWoMAADkr2JNBbbeeuv00ksv1Rh30EEHFe1Yf/azn6UVVlghderUKT344INFN1jh9ddfT++8804aNGhQhZYaAIA2F1wXW2yxNGDAgBrjunXrVvTZWh5/yCGHpGOPPTYtscQSReX06KOPLkLrxhtvXKGlBgCgTV6c1ZgxY8ak9u3bFxXX6C1gyJAh6aKLLqr0YgEA0NaD68MPP1zjeVy0deGFFxYDAABtW8X7cQUAgKYQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWKhpcR40alTbYYIO02GKLpaWWWirttNNO6fXXX68xzYwZM9KRRx6Zevfunbp375523XXXNHny5IotMwAAbTC4PvLII0UofeKJJ9L999+fvvrqq/S9730vffHFF1XTHHPMMenOO+9MN954YzH9Bx98kHbZZZdKLjYAABXQMVXQhAkTajy/8sori8rrs88+m77zne+kadOmpbFjx6ZrrrkmbbXVVsU048aNS6uvvnoRdjfeeOMKLTkAAG26jWsE1bDEEksU/0eAjSrs4MGDq6ZZbbXV0oorrpgmTpxY5zxmzpyZpk+fXmMAACB/LSa4zpkzJw0dOjRtuummacCAAcW4SZMmpUUWWST16tWrxrRLL7108Vp97WZ79uxZNaywwgoLZfkBAGgjwTXaur788svpuuuu+1rzGTZsWFG5LQ/vvvtusy0jAABttI1r2VFHHZXuuuuu9Kc//Sktv/zyVeP79OmTZs2alaZOnVqj6hq9CsRrdencuXMxAADQulS04loqlYrQeuutt6Y//vGPqV+/fjVeX2+99VKnTp3Sgw8+WDUuust655130qBBgyqwxAAAtMmKazQPiB4Dbr/99qIv13K71Wib2rVr1+L/Qw45JB177LHFBVs9evRIRx99dBFa9SgAANC2VDS4XnzxxcX/W2yxRY3x0eXVgQceWDweM2ZMat++fXHjgegxYMiQIemiiy6qyPICANBGg2s0FWhMly5d0oUXXlgMAAC0XS2mVwEAAGiI4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRUAgCwIrgAAZEFwBQAgC4IrAABZEFwBAMiC4AoAQBYEVwAAsiC4AgCQBcEVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACALgisAAFkQXAEAyILgCgBAFrIIrhdeeGFaaaWVUpcuXdJGG22UnnrqqUovEgAAC1mLD67XX399OvbYY9OIESPSc889l771rW+lIUOGpClTplR60QAAWIhafHAdPXp0OvTQQ9NBBx2U1lhjjXTJJZekRRddNF1xxRWVXjQAABaijqkFmzVrVnr22WfTsGHDqsa1b98+DR48OE2cOLHOn5k5c2YxlE2bNq34f/r06WmhmbHw3or/b4FvY9t1obNNW6cFul3tpxVhX22dpi/E7FR+r1KplG9w/fjjj9Ps2bPT0ksvXWN8PH/ttdfq/JlRo0alkSNHzjV+hRVWWGDLScvQ85c9K70INDPbtHWyXVsf27R16lmBz9XPP/889ezZM8/gOj+iOhttYsvmzJmTPv3009S7d+/Url27ii5bSxffdiLgv/vuu6lHjx6VXhyagW3aOtmurY9t2jrZrk0XldYIrcsuu2yD07Xo4LrkkkumDh06pMmTJ9cYH8/79OlT58907ty5GKrr1avXAl3O1iZCq+DautimrZPt2vrYpq2T7do0DVVas7g4a5FFFknrrbdeevDBB2tUUOP5oEGDKrpsAAAsXC264hritP8BBxyQ1l9//bThhhumc889N33xxRdFLwMAALQdLT647rHHHumjjz5Kw4cPT5MmTUprr712mjBhwlwXbPH1RROL6C+3dlML8mWbtk62a+tjm7ZOtmvza1dqrN8BAABoAVp0G1cAACgTXAEAyILgCgBAFgRXKtIhc1xk969//Su99957aZVVVrEVAIBGCa4t1NSpU4s7fdUeWsPNFKIj5s0226z4XVZaaaX0ox/9qNKL1KIceOCBdW7773//+5VeNJq47Y444oi5XjvyyCOL12IaWo+40+DBBx9c3O0n+h7v27dv+ulPf5o++eSTSi8a/0/0SHT00Uenb37zm8VV/nGHyB122KFGH/HkQ3Bt4W6++eb04YcfFkP0YdtaXHDBBWnKlCnF7XiPO+64Si9OixMhtbzdy8O1115b6cWiCeJD8brrrktffvll1bgZM2aka665Jq244orWYSvyj3/8o+hj/M033yz2z7/97W/pkksuqbpJThzfqKx//vOfxY2M/vjHP6Zf/epX6aWXXiq61Nxyyy2LL5PkR3Btof7zn/8U//fu3bu4vW0MtW+FFtWb+IZf/Za40edtfKOM18pOPfXU4tR82axZs4rT8zFNVHYffvjhOit85SFceeWVRYX0tttuS/37909dunRJQ4YMKaoNTX2f6vMJSyyxRFF9/c53vlNM88ILLyyANZmn2Ibl7V4eFl988QarskOHDq16Pdb3f//3f6dvfOMbxTreaqut0osvvljvtgrlv4PytoqK0V577ZWWW265tOiii6aBAwcKz02w7rrrFuH1lltuqRoXjyO0rrPOOlXj4sOzfOYh9vPtt98+/f3vf6/xgVt9v5g5c2YaPHhwMcTjsiuuuCKtueaaxd/MMsssk4466qiq1+LnY58tGzt27Fx/K3HWI8Y999xzVeO++uqroq/sGB/LQd0i+MQx+L777kubb755sY232Wab9MADD6T3338/nXTSSTX2udr77E477VRjOzRUnNhiiy3m+vkf/vCHxWv21fr9+Mc/LtbVU089lXbddde06qqrFvtL3NzoiSeeqNpPykMcL7/73e/W2Bdjf/uf//mf4ljYrVu3tNFGGxXHy9CUz8/q+2Ptobx/N2Ubxt/A0Gr7bl3H8qeffrpY/iWXXLLIDPF3WX3fbg0E1xaq/MHU2M0AllpqqTRu3Liq5/E4wkpj1c7qYXeTTTapqupFhTdUr/SV/fvf/05nnnlmuvrqq9Njjz1WBJw999yzye9Tl/hAf/755xuchrlF98vVq7K1b4G82267FRXte+65Jz377LNFmNp6663nqQIUVcKoVPzhD39IL7/8cjrssMPSfvvtV3wA0LA4dVx9v4xwWftuf3EHwPjwfOaZZ4oKXfv27dPOO+9c3Na6ttmzZxf7WrQLjyBaPi5cfPHFRXiKbROVpDvuuKPeNuPxfqecckrq3r37XK/Fh+Wll15a9fzWW29NnTp1spkbEPvSvffeWwSjrl271ngtvmjus88+6frrry/21RD/R2Aq77O77777PK/fQw89tMax+fLLLy/G21fr30bxBTH2kQictVVvehf7a6zTP/3pT8Wx88QTT6x6Lb4MTpw4sTiT8pe//KU4vsbxNyrtTf38LP8dlN+n9nG0ubbh559/Xtxt9NFHHy2CeRSatt1222J8ayG4tlDlgLHYYos1+gEZB6/YKWKIxzGuofmeccYZ6Wc/+1nVuKgYlKt6UQUN1St91aswEUYjJMUOdtVVV6XHH3+8zh2rrvepLeYXrzc0TVt11113FQGj+vCLX/yixrqLceVtFNuwLA5YsU1uvPHG4jRmHLjOOeec4iB90003NXkZIsxElSG+zUfbsGgjFgfrG264odl/39Zm3333LbbD22+/XQzxRS/GVRfVn1122aUImrGOI9xG+HzllVdqTBf7dYTeOA1999131wiesY9FU5toUxmVpA022GCuikzZ2WefndZYY41i360tPiDjbyPCbYgQ29BxhFSEltg2q6++ep2rI8Z/9tlnxVmw8j4bAbe8z9YOu00Rlbjqx+Zy8LKv1i32mdhGq622WqPrNtZlrNN+/foVn7vlM5zvvPNOETbjePrtb387rbzyysVxMc6WxPh5+fwMUViK8bULTM21DbfaaqviWBO/c/wNxr4cRadHHnkktRaCawsVp5lCnPprSFTSYoeL9jsPPfRQscPFuPqcdtppRdue2OnmVceOHYsPxrLYMeK9X3311fl6nwsvvLA4OERlgppi3cUppOpD9Qt+omeGuioIIZoERGUuTj9XD75vvfVWjdNfEZKqvx6nOGtX+U4//fTilFUckGOaqDDFgZyGxYfSdtttVzSNiQ+3eByn7moHnzg1GB9ScXoyThWH2uv3+OOPT7/73e+Kfa/8wRiiKvTBBx8UlfTGxHSjR49Ov/71r+t8PZoFxGnIqCjF30iE57h4hcY19eaTDe2zZfElPvazOJMW2yO+8DSFffXrbZsQ+2Ks+2iSFdXJUaNGVR0nY/3GF8Pqx8sIgtWPp03Z/qG+v4GmbsOLLrqo3oJGiLOcUZmPgkV8vsaxJT4PWtNxu2OlF4C6xQdHfPhV/6CqT5xSuOyyy4qdNB7XJz4ooyIbISi6oVpQmvI+UYmInTROSdZuB8T/Hdwa6iYsgshaa61V52txkIovPOU2WPWdGvuv//qv4tRy2ZNPPlmjKhgXMvzmN78p2t3FwTSWKap50XaZxkXFstzeNL6k1RbBMK5Aj303rkiPJgIDBgyYa/3GF8No8hHV2T322KNoWx7mpWIXbS3j9Oa3vvWteqeJY8fw4cPTG2+8UZxq1FSgYeX2+7F9oolHbTE+QlC5shb7bGznhsSXlGi/HpXv2P/ibySuiK9+RqUu9tW6RXiLbfTaa681sjVTGjNmTNF+PJrAxf4S2+HOO+8sjqcdOnQomlzF/9XV1eymPrH9Q31/A03dhvvss0+NttPnnXde0byhLPbdaC8b84rjSzQrirOkrem4reLaQkWbt2g70xR77713cTFADPG4oW/zccHO/PabGheMRXu8stdff73YyWufKmvK+0RojdMucWEW8yY+1OJDsfqFPtVFxT0+7KJCHtug+lC96hcfhtVfi1NV1UW1Z8cddyzCbASeqAxGqKFp4jRffFjEKcJy2CyLD5bYf04++eSiYlo+rVyXqLbGvGKfiUpKuXITZ1eiSttYlz7xBTKaAUSzgobEBR1xWjuuio/9l4bFGY1YZ1EBq96DRIj9b/z48cUXjQhO8aUkLpCpb58ti/0z9sXY34YNG1b8TTSlUmZfrVsUfmLfiy+O5WYw1ZUvRA1x+j7WfTSvitP00dY09t3YZlENjTMctY+n1ZsCNCYumop9NpoafJ1t2LNnzxrLULu4FfP5yU9+UrRrLV+0+fHHH6fWRMW1hYkDYHSbExWW2NniAFg2bdq0oqoa46q3j4lvffFhEwfH+trERlufOADG//MrKjCxQ8c3vAhFUU3aeOON04YbbjhP7xPtbaLdTWu70rG5L86rvu1DrPM4AJ1wwglF5bT2qf2yqBrEN+y4YjnaNcYprvi2HwfiqAzFgbmp1YoIPNGOOSpHcao5TkNFO0kaF9WZcjOa2pWaWJ8RfGI/iOp47DM///nP65xP+YPpmGOOKS5mjAu6yhflxBXF0YQkTi3H30Oc4owPrthPy6J9c7SDbazaFwErjiPRi0B8uOrlo3HR5j8KDBGO4otBtI/861//WlRO44tgXMwaPa/EdorgE0G2seJAXKQTISvaPEdIiR4qGmNfrV98jm666abF51Q0YYszVbGe77///uLixvI+GiE2jrnxORu9b0RwjM+8OH5GlXP//fcvmtpEkI0vePGFMeYVzYAaEp/Lcc1CXOwV86h9LGjubdi/f//iy24c5+NLbvwtzk976pZMcG1h4irUcrUjrlaNobb4oIv2itWVu0WpTxwIR44c2aSmBw1dGBDV1KjqRhvcqJjGDj6v7xPfYg8//PDigEDd4krY2u2b49R+NNyPg25U1+s7TRUBJC7iidNJcVFPHGSjMhDV7WjL2FRRDYx+KuNDObZ9nEqOMBwHdpom2pfVJXoQiPakURmJ5gGxbeMLYbRrrE/8TLSXjb+BuCL9e9/7XnFaMIJOnOaMCzuiYlf7WBBfZuPLTlNEBZF5CwlxFmrEiBHFNomLUmNfi/0kxsVxMNogxhf56DKrsX58I2SUg0b8XURTqsZ6lgn21fpFAI0iSXyJiC9wcUV/FH7iIsUIrmXlXj/K14lUv5A19rvyhZDx2Rf7WRRtogu7xkTVPD7HY1+NsyYLehuOHTu2+Nlyt3zx9xfHhtakXWleWi+zwMXFHDHU1T6xejCJ4Fq+mGNhiGWK9jbVT60AACxM2ri2MPFNu7GqaFTN6jvdAADQWmkq0MJEG6jG2kHVbvsIANAWaCoAAEAWNBUAACALgisAAFkQXAEAyILgCgBAFgRXAACyILgCAJAFwRWgwg488MDi9o7Vvf3226lLly7FnfIA+D+CK0ALdMoppwitALUIrgAtzEsvvZTGjx+fjj766KpxV155ZRFkf/CDH9SY9je/+U0xPqq2ZR9++GHaZZddUu/evYvXysPUqVMX6u8B0NwEV4AW5uc//3naYYcd0iabbFJj/KKLLpomTpyY3n///apxl156aVpuueVqTHfcccelN954I02YMKEIsTfffPNCW3aABUlwBWhB/vSnP6V77703jRo1aq7XOnXqlPbaa690xRVXFM8fffTR1KFDh7T++uvXmO6FF15Ie++9d9pggw1Snz590hJLLLHQlh9gQRJcAVpYtfWAAw5Iq6++ep2vH3bYYWns2LFpzpw5RbX10EMPnWuafv36pbvvvjt9+umnC2GJARYewRWghbj11lvT888/n0aOHFnvNAMGDEjLLrtsuu6669Jdd92V9ttvv7mmGTNmTJo5c2ZacsklU/fu3dM222yzgJccYOEQXAFagNmzZ6eTTjqpuCBr+eWXb3Daww8/PB1xxBFp++23T7169Zrr9VVXXbW4WGullVZKTz75ZLr88ssX4JIDLDwdF+J7AVCPBx54oOi3ddiwYY2uo9133z1NmjRprh4Gyp544ol04oknpoceeiitueaa6aOPPrLegVZBcAVoAWbMmJFGjBiRFl988Uan7dq1a/rZz35W52sRUnfbbbc0evTotO666y6AJQWonHalUqlUwfcHAIAm0cYVAIAsCK4AAGRBcAUAIAuCKwAAWRBcAQDIguAKAEAWBFcAALIguAIAkAXBFQCALAiuAABkQXAFACDl4H8BrZQu29sczI8AAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Столбчатая диаграмма\n",
+    "plt.figure(figsize=(8, 5))\n",
+    "plt.bar(df[\"Имя\"], df[\"Баллы\"], color='green')\n",
+    "plt.xlabel(\"Имя\")\n",
+    "plt.ylabel(\"Баллы\")\n",
+    "plt.title(\"Баллы студентов\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "dc358466-fd19-4689-9ee0-f7303b79e52f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Визуализация seaborn\n",
+    "sns.set(style=\"whitegrid\")\n",
+    "\n",
+    "plt.figure(figsize=(8, 5))\n",
+    "sns.boxplot(x=\"Категория\", y=\"Баллы\", hue=\"Категория\", data=df, palette=\"Set2\", legend=False)\n",
+    "plt.title(\"Boxplot баллов по категориям\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.figure(figsize=(8, 5))\n",
+    "sns.histplot(df[\"Баллы\"], bins=5, kde=True, color=\"purple\")\n",
+    "plt.title(\"Распределение баллов\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.figure(figsize=(8, 5))\n",
+    "sns.scatterplot(x=\"Возраст\", y=\"Баллы\", hue=\"Категория\", data=df, s=100)\n",
+    "plt.title(\"Зависимость баллов от возраста\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "20d1a343-12bc-47a9-b6de-06cb140e06fe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Тепловая карта корреляции\n",
+    "plt.figure(figsize=(6, 4))\n",
+    "sns.heatmap(df[[\"Возраст\", \"Баллы\", \"Повышенные баллы\"]].corr(), annot=True, cmap=\"coolwarm\")\n",
+    "plt.title(\"Корреляция признаков\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "400ecbce-9b40-43d0-9a6e-f13d7024a4e7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка данных: 100%|████████████████████████████████████████████████████████████████| 50/50 [00:01<00:00, 48.62it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Пример tqdm\n",
+    "for i in tqdm(range(50), desc=\"Обработка данных\"):\n",
+    "    time.sleep(0.02)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
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