amazon-prime-shows.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.038837,
     "end_time": "2020-10-03T11:33:29.791297",
     "exception": false,
     "start_time": "2020-10-03T11:33:29.752460",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Importing libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:29.874140Z",
     "iopub.status.busy": "2020-10-03T11:33:29.873116Z",
     "iopub.status.idle": "2020-10-03T11:33:29.881174Z",
     "shell.execute_reply": "2020-10-03T11:33:29.881794Z"
    },
    "papermill": {
     "duration": 0.052328,
     "end_time": "2020-10-03T11:33:29.881990",
     "exception": false,
     "start_time": "2020-10-03T11:33:29.829662",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/input/amazon-prime-tv-shows/Prime TV Shows Data set.csv\n"
     ]
    }
   ],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 5GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:29.960792Z",
     "iopub.status.busy": "2020-10-03T11:33:29.960023Z",
     "iopub.status.idle": "2020-10-03T11:33:31.029857Z",
     "shell.execute_reply": "2020-10-03T11:33:31.029197Z"
    },
    "papermill": {
     "duration": 1.111042,
     "end_time": "2020-10-03T11:33:31.030000",
     "exception": false,
     "start_time": "2020-10-03T11:33:29.918958",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import missingno as msno\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a",
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:31.111055Z",
     "iopub.status.busy": "2020-10-03T11:33:31.110197Z",
     "iopub.status.idle": "2020-10-03T11:33:31.125128Z",
     "shell.execute_reply": "2020-10-03T11:33:31.124290Z"
    },
    "papermill": {
     "duration": 0.057225,
     "end_time": "2020-10-03T11:33:31.125263",
     "exception": false,
     "start_time": "2020-10-03T11:33:31.068038",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "prime_df = pd.read_csv('../input/amazon-prime-tv-shows/Prime TV Shows Data set.csv', encoding = 'iso-8859-1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:31.224255Z",
     "iopub.status.busy": "2020-10-03T11:33:31.208134Z",
     "iopub.status.idle": "2020-10-03T11:33:31.237312Z",
     "shell.execute_reply": "2020-10-03T11:33:31.236707Z"
    },
    "papermill": {
     "duration": 0.075205,
     "end_time": "2020-10-03T11:33:31.237429",
     "exception": false,
     "start_time": "2020-10-03T11:33:31.162224",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>S.no.</th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Pataal Lok</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.5</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Upload</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Sci-fi comedy</td>\n",
       "      <td>8.1</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>The Marvelous Mrs. Maisel</td>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama, Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Four More Shots Please</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama, Comedy</td>\n",
       "      <td>5.3</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Fleabag</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>499</td>\n",
       "      <td>The Bellflower Bunnies</td>\n",
       "      <td>2002</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>500</td>\n",
       "      <td>Truck Games</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>501</td>\n",
       "      <td>AnimaCars- Truck and Animal's Adventures</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>502</td>\n",
       "      <td>Superzoo</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>503</td>\n",
       "      <td>Dubby Dubs</td>\n",
       "      <td>2017</td>\n",
       "      <td>2</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>503 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     S.no.                          Name of the show  Year of release  \\\n",
       "0        1                                Pataal Lok             2020   \n",
       "1        2                                    Upload             2020   \n",
       "2        3                 The Marvelous Mrs. Maisel             2017   \n",
       "3        4                    Four More Shots Please             2019   \n",
       "4        5                                   Fleabag             2016   \n",
       "..     ...                                       ...              ...   \n",
       "498    499                    The Bellflower Bunnies             2002   \n",
       "499    500                               Truck Games             2020   \n",
       "500    501  AnimaCars- Truck and Animal's Adventures             2019   \n",
       "501    502                                  Superzoo             2020   \n",
       "502    503                                Dubby Dubs             2017   \n",
       "\n",
       "     No of seasons available Language          Genre  IMDb rating  \\\n",
       "0                          1    Hindi          Drama          7.5   \n",
       "1                          1  English  Sci-fi comedy          8.1   \n",
       "2                          3  English  Drama, Comedy          8.7   \n",
       "3                          2    Hindi  Drama, Comedy          5.3   \n",
       "4                          2  English         Comedy          8.7   \n",
       "..                       ...      ...            ...          ...   \n",
       "498                        1  English           Kids          NaN   \n",
       "499                        1  English           Kids          NaN   \n",
       "500                        1  English           Kids          NaN   \n",
       "501                        1  English           Kids          NaN   \n",
       "502                        2  English           Kids          NaN   \n",
       "\n",
       "    Age of viewers  \n",
       "0              18+  \n",
       "1              16+  \n",
       "2              16+  \n",
       "3              18+  \n",
       "4              18+  \n",
       "..             ...  \n",
       "498            All  \n",
       "499            All  \n",
       "500            All  \n",
       "501            All  \n",
       "502             7+  \n",
       "\n",
       "[503 rows x 8 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.037364,
     "end_time": "2020-10-03T11:33:31.312522",
     "exception": false,
     "start_time": "2020-10-03T11:33:31.275158",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Getting an overview of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:31.408963Z",
     "iopub.status.busy": "2020-10-03T11:33:31.394257Z",
     "iopub.status.idle": "2020-10-03T11:33:31.412999Z",
     "shell.execute_reply": "2020-10-03T11:33:31.412382Z"
    },
    "papermill": {
     "duration": 0.06291,
     "end_time": "2020-10-03T11:33:31.413135",
     "exception": false,
     "start_time": "2020-10-03T11:33:31.350225",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 503 entries, 0 to 502\n",
      "Data columns (total 8 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   S.no.                    503 non-null    int64  \n",
      " 1   Name of the show         503 non-null    object \n",
      " 2   Year of release          503 non-null    int64  \n",
      " 3   No of seasons available  503 non-null    int64  \n",
      " 4   Language                 503 non-null    object \n",
      " 5   Genre                    503 non-null    object \n",
      " 6   IMDb rating              220 non-null    float64\n",
      " 7   Age of viewers           503 non-null    object \n",
      "dtypes: float64(1), int64(3), object(4)\n",
      "memory usage: 31.6+ KB\n"
     ]
    }
   ],
   "source": [
    "prime_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.037761,
     "end_time": "2020-10-03T11:33:31.489214",
     "exception": false,
     "start_time": "2020-10-03T11:33:31.451453",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We can see there are 503 values for each column except for IMDb rating which shows missing values. Let's check out the percentage of missing values and get insights about why these values are missing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:31.574555Z",
     "iopub.status.busy": "2020-10-03T11:33:31.573701Z",
     "iopub.status.idle": "2020-10-03T11:33:31.577425Z",
     "shell.execute_reply": "2020-10-03T11:33:31.578042Z"
    },
    "papermill": {
     "duration": 0.050742,
     "end_time": "2020-10-03T11:33:31.578206",
     "exception": false,
     "start_time": "2020-10-03T11:33:31.527464",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "S.no.                        0\n",
       "Name of the show             0\n",
       "Year of release              0\n",
       "No of seasons available      0\n",
       "Language                     0\n",
       "Genre                        0\n",
       "IMDb rating                283\n",
       "Age of viewers               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# looking for null values\n",
    "prime_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:31.663300Z",
     "iopub.status.busy": "2020-10-03T11:33:31.662400Z",
     "iopub.status.idle": "2020-10-03T11:33:32.132318Z",
     "shell.execute_reply": "2020-10-03T11:33:32.132935Z"
    },
    "papermill": {
     "duration": 0.515902,
     "end_time": "2020-10-03T11:33:32.133091",
     "exception": false,
     "start_time": "2020-10-03T11:33:31.617189",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "msno.matrix(prime_df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:32.223677Z",
     "iopub.status.busy": "2020-10-03T11:33:32.222546Z",
     "iopub.status.idle": "2020-10-03T11:33:32.227062Z",
     "shell.execute_reply": "2020-10-03T11:33:32.226301Z"
    },
    "papermill": {
     "duration": 0.05264,
     "end_time": "2020-10-03T11:33:32.227192",
     "exception": false,
     "start_time": "2020-10-03T11:33:32.174552",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "56.2624254473161"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# percentage of missing values in IMDb rating\n",
    "(prime_df['IMDb rating'].isnull().sum()/prime_df.shape[0])*100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.041196,
     "end_time": "2020-10-03T11:33:32.309889",
     "exception": false,
     "start_time": "2020-10-03T11:33:32.268693",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Nearly 56% of the values are missing because the users might not consider it necessary to leave a rating each time they watch a show. Maybe the one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:32.403728Z",
     "iopub.status.busy": "2020-10-03T11:33:32.402873Z",
     "iopub.status.idle": "2020-10-03T11:33:32.406873Z",
     "shell.execute_reply": "2020-10-03T11:33:32.407397Z"
    },
    "papermill": {
     "duration": 0.055663,
     "end_time": "2020-10-03T11:33:32.407570",
     "exception": false,
     "start_time": "2020-10-03T11:33:32.351907",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "English       422\n",
       "Hindi          39\n",
       "Japanese       13\n",
       "Italiano        8\n",
       "Spanish         6\n",
       "Deutsch         3\n",
       "French          2\n",
       "Nederlands      2\n",
       "Serbian         2\n",
       "Marathi         2\n",
       "Telugu          1\n",
       "Russian         1\n",
       "Suomi           1\n",
       "Hebrew          1\n",
       "Name: Language, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df['Language'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.042552,
     "end_time": "2020-10-03T11:33:32.492320",
     "exception": false,
     "start_time": "2020-10-03T11:33:32.449768",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Most number of missing values for IMDb rating are for english shows maybe because the maximum number of shows are in english"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:32.583459Z",
     "iopub.status.busy": "2020-10-03T11:33:32.582675Z",
     "iopub.status.idle": "2020-10-03T11:33:32.586056Z",
     "shell.execute_reply": "2020-10-03T11:33:32.585235Z"
    },
    "papermill": {
     "duration": 0.05183,
     "end_time": "2020-10-03T11:33:32.586184",
     "exception": false,
     "start_time": "2020-10-03T11:33:32.534354",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "nadf = prime_df[prime_df['IMDb rating'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:32.682335Z",
     "iopub.status.busy": "2020-10-03T11:33:32.681471Z",
     "iopub.status.idle": "2020-10-03T11:33:32.685574Z",
     "shell.execute_reply": "2020-10-03T11:33:32.686158Z"
    },
    "papermill": {
     "duration": 0.056127,
     "end_time": "2020-10-03T11:33:32.686326",
     "exception": false,
     "start_time": "2020-10-03T11:33:32.630199",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "English       230\n",
       "Hindi          22\n",
       "Italiano        8\n",
       "Japanese        6\n",
       "Spanish         5\n",
       "French          2\n",
       "Serbian         2\n",
       "Nederlands      2\n",
       "Marathi         2\n",
       "Telugu          1\n",
       "Deutsch         1\n",
       "Russian         1\n",
       "Hebrew          1\n",
       "Name: Language, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the distribution of na's per language\n",
    "nadf['Language'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:32.785292Z",
     "iopub.status.busy": "2020-10-03T11:33:32.784481Z",
     "iopub.status.idle": "2020-10-03T11:33:32.813719Z",
     "shell.execute_reply": "2020-10-03T11:33:32.812915Z"
    },
    "papermill": {
     "duration": 0.084187,
     "end_time": "2020-10-03T11:33:32.813850",
     "exception": false,
     "start_time": "2020-10-03T11:33:32.729663",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Deutsch       0.333333\n",
       "English       0.545024\n",
       "French        1.000000\n",
       "Hebrew        1.000000\n",
       "Hindi         0.564103\n",
       "Italiano      1.000000\n",
       "Japanese      0.461538\n",
       "Marathi       1.000000\n",
       "Nederlands    1.000000\n",
       "Russian       1.000000\n",
       "Serbian       1.000000\n",
       "Spanish       0.833333\n",
       "Suomi              NaN\n",
       "Telugu        1.000000\n",
       "Name: Language, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of na's per language / number of values per language\n",
    "nadf['Language'].value_counts() / prime_df['Language'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:32.910457Z",
     "iopub.status.busy": "2020-10-03T11:33:32.909297Z",
     "iopub.status.idle": "2020-10-03T11:33:32.913927Z",
     "shell.execute_reply": "2020-10-03T11:33:32.913284Z"
    },
    "papermill": {
     "duration": 0.055765,
     "end_time": "2020-10-03T11:33:32.914056",
     "exception": false,
     "start_time": "2020-10-03T11:33:32.858291",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "S.no.                        int64\n",
       "Name of the show            object\n",
       "Year of release              int64\n",
       "No of seasons available      int64\n",
       "Language                    object\n",
       "Genre                       object\n",
       "IMDb rating                float64\n",
       "Age of viewers              object\n",
       "dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# looking at the data types\n",
    "prime_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:33.022996Z",
     "iopub.status.busy": "2020-10-03T11:33:33.021882Z",
     "iopub.status.idle": "2020-10-03T11:33:33.027165Z",
     "shell.execute_reply": "2020-10-03T11:33:33.026495Z"
    },
    "papermill": {
     "duration": 0.067533,
     "end_time": "2020-10-03T11:33:33.027300",
     "exception": false,
     "start_time": "2020-10-03T11:33:32.959767",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>S.no.</th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Pataal Lok</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.5</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Upload</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Sci-fi comedy</td>\n",
       "      <td>8.1</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>The Marvelous Mrs. Maisel</td>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama, Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Four More Shots Please</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama, Comedy</td>\n",
       "      <td>5.3</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Fleabag</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Made in Heaven</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.3</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Homecoming</td>\n",
       "      <td>2018</td>\n",
       "      <td>2</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.5</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Mirzapur</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.5</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>The Family Man</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama, Action</td>\n",
       "      <td>8.6</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>Modern Love</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama, Romance, Comedy</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   S.no.           Name of the show  Year of release  No of seasons available  \\\n",
       "0      1                 Pataal Lok             2020                        1   \n",
       "1      2                     Upload             2020                        1   \n",
       "2      3  The Marvelous Mrs. Maisel             2017                        3   \n",
       "3      4     Four More Shots Please             2019                        2   \n",
       "4      5                    Fleabag             2016                        2   \n",
       "5      6             Made in Heaven             2019                        1   \n",
       "6      7                 Homecoming             2018                        2   \n",
       "7      8                   Mirzapur             2018                        1   \n",
       "8      9             The Family Man             2019                        1   \n",
       "9     10                Modern Love             2019                        1   \n",
       "\n",
       "  Language                   Genre  IMDb rating Age of viewers  \n",
       "0    Hindi                   Drama          7.5            18+  \n",
       "1  English           Sci-fi comedy          8.1            16+  \n",
       "2  English           Drama, Comedy          8.7            16+  \n",
       "3    Hindi           Drama, Comedy          5.3            18+  \n",
       "4  English                  Comedy          8.7            18+  \n",
       "5    Hindi                   Drama          8.3            18+  \n",
       "6  English                   Drama          7.5            16+  \n",
       "7    Hindi                   Drama          8.5            18+  \n",
       "8    Hindi           Drama, Action          8.6            18+  \n",
       "9  English  Drama, Romance, Comedy          8.0            16+  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# looking at the first 10 entries of the dataset\n",
    "prime_df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.061113,
     "end_time": "2020-10-03T11:33:33.139129",
     "exception": false,
     "start_time": "2020-10-03T11:33:33.078016",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Data cleaning and simplification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.054657,
     "end_time": "2020-10-03T11:33:33.255291",
     "exception": false,
     "start_time": "2020-10-03T11:33:33.200634",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* The S.no. column is not required so let's drop it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:33.371098Z",
     "iopub.status.busy": "2020-10-03T11:33:33.369828Z",
     "iopub.status.idle": "2020-10-03T11:33:33.374780Z",
     "shell.execute_reply": "2020-10-03T11:33:33.374088Z"
    },
    "papermill": {
     "duration": 0.073333,
     "end_time": "2020-10-03T11:33:33.374913",
     "exception": false,
     "start_time": "2020-10-03T11:33:33.301580",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Pataal Lok</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.5</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Upload</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Sci-fi comedy</td>\n",
       "      <td>8.1</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Marvelous Mrs. Maisel</td>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama, Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Four More Shots Please</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama, Comedy</td>\n",
       "      <td>5.3</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fleabag</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>The Bellflower Bunnies</td>\n",
       "      <td>2002</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Truck Games</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>AnimaCars- Truck and Animal's Adventures</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>Superzoo</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>Dubby Dubs</td>\n",
       "      <td>2017</td>\n",
       "      <td>2</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>503 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Name of the show  Year of release  \\\n",
       "0                                  Pataal Lok             2020   \n",
       "1                                      Upload             2020   \n",
       "2                   The Marvelous Mrs. Maisel             2017   \n",
       "3                      Four More Shots Please             2019   \n",
       "4                                     Fleabag             2016   \n",
       "..                                        ...              ...   \n",
       "498                    The Bellflower Bunnies             2002   \n",
       "499                               Truck Games             2020   \n",
       "500  AnimaCars- Truck and Animal's Adventures             2019   \n",
       "501                                  Superzoo             2020   \n",
       "502                                Dubby Dubs             2017   \n",
       "\n",
       "     No of seasons available Language          Genre  IMDb rating  \\\n",
       "0                          1    Hindi          Drama          7.5   \n",
       "1                          1  English  Sci-fi comedy          8.1   \n",
       "2                          3  English  Drama, Comedy          8.7   \n",
       "3                          2    Hindi  Drama, Comedy          5.3   \n",
       "4                          2  English         Comedy          8.7   \n",
       "..                       ...      ...            ...          ...   \n",
       "498                        1  English           Kids          NaN   \n",
       "499                        1  English           Kids          NaN   \n",
       "500                        1  English           Kids          NaN   \n",
       "501                        1  English           Kids          NaN   \n",
       "502                        2  English           Kids          NaN   \n",
       "\n",
       "    Age of viewers  \n",
       "0              18+  \n",
       "1              16+  \n",
       "2              16+  \n",
       "3              18+  \n",
       "4              18+  \n",
       "..             ...  \n",
       "498            All  \n",
       "499            All  \n",
       "500            All  \n",
       "501            All  \n",
       "502             7+  \n",
       "\n",
       "[503 rows x 7 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# drop S.no. column\n",
    "prime_df.drop(['S.no.'],axis = 1, inplace = True)\n",
    "prime_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.046319,
     "end_time": "2020-10-03T11:33:33.467348",
     "exception": false,
     "start_time": "2020-10-03T11:33:33.421029",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:33.566629Z",
     "iopub.status.busy": "2020-10-03T11:33:33.565500Z",
     "iopub.status.idle": "2020-10-03T11:33:33.568961Z",
     "shell.execute_reply": "2020-10-03T11:33:33.568214Z"
    },
    "papermill": {
     "duration": 0.055622,
     "end_time": "2020-10-03T11:33:33.569086",
     "exception": false,
     "start_time": "2020-10-03T11:33:33.513464",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:33.716870Z",
     "iopub.status.busy": "2020-10-03T11:33:33.692465Z",
     "iopub.status.idle": "2020-10-03T11:33:34.807029Z",
     "shell.execute_reply": "2020-10-03T11:33:34.806367Z"
    },
    "papermill": {
     "duration": 1.191086,
     "end_time": "2020-10-03T11:33:34.807169",
     "exception": false,
     "start_time": "2020-10-03T11:33:33.616083",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6YAAAGpCAYAAACeSysXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nO3de5zVdYE//tdcGIR085IjSiyEl0LxgpuKeVsxBQVEIbSL/Fp1d7NCbLF109a2Ws10LdPKVreUrCy7mCaa7iNSc03MzVsoKlluYIpfxUQYZS58fn+4zko6MMOccz7DzPP5z3kwcz6f94tzPp/3zGven3NOXVEURQAAAKAk9WUHAAAAYGBTTAEAACiVYgoAAECpFFMAAABKpZgCAABQqsayA7zW/fffn8GDB5cdAwAAgApbs2ZN9tprrzf8Xp8qpoMHD86YMWPKjgEAAECFLV68uMvvuZQXAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsWUTcLa9tZ+ORYAAJA0lh0AuqO+sSm3/8fkmox1yN/dWJNxAACAV1gxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUgAFn4cKFmTt3bhYuXFh2FAAgPscUgAFo3rx5WbJkSVpaWjJ+/Piy4wDAgGfFFIABp6WlZZ1bAKBciikAlMDlxADwf1zKCwAlcDkxAPwfK6bQTR3trf1yLKAcLicGgP9jxRS6qaGxKT+54siajHX0ST+tyTgAANAXWDEFAACgVIopAAAApVJMAQAAKJViCgBQMh8fBAx0iikAMKD1hVI4b968PPDAA5k3b15pGQDKpJgCAKVRCl/h44OAgc7HxQAApZk3b16WLFmSlpaWjB8/vpQMSiFA+ayYAgClUQoBSBRTAAAASqaYAgAAUCrFFAAAgFIppgAAAJRKMQUAAKBUiikAAAClUkwBAAAoVWM1dz5v3rz84Ac/SF1dXXbZZZecd955GTx4cDWHBIBStHa0p6mhqj9WazoOANRS1X6yLV++PFdddVVuuummbLbZZjnttNNy4403Zvr06dUaEgBK09TQmCk/mtft+7+8amWS5I+rVvZou/kz/qZnwQBgE1DVS3k7Ojry8ssvp729PS+//HKam5urORwAAACboKqtmG633XY56aSTcuihh2bw4ME54IADcuCBB653mzVr1mTx4sXVisQmbMyYMTUd742Ow76QAaiM1tbWzttKnWu1nCP60/xQjedCBnpj0aJF+dnPfpZ3v/vdGTt2bNlxYMCoWjF94YUXsmDBgixYsCBbbLFFTjvttFx//fWZNm1al9sMHjy45r/8wxvpC8dhX8gA/VVTU1Pn7aZ4rm2KmbtSjeeitWNtmhq6f1HYxmbo6TjVyEDlXXzxxfntb3+burq6zJw5s+w40K+s7w9vVSumv/zlL/PWt741W2+9dZLkiCOOyH333bfeYgoA0FtNDfU59ke3d/v+q1a9lCR5atVLPdruxzMO6XE2+r6WlpZ1boHaqNprTHfYYYc88MADeemll1IURe66667suOOO1RoOAACATVTVVkz33HPPTJw4Mccee2waGxszZsyYHH/88dUaDgaEjvbWNDQ29buxAAAY2Kr6QWhz5szJnDlzqjkEDCgNjU351ryJNRlr1t/cUpNxAACgqh8XAwAA3bVw4cLMnTs3CxcuLDsKUGNVXTEFAIDumjdvXpYsWZKWlpaMHz++7DhADVkxBQCgT/COuDBwKaYAm7DWjrZ+NQ70F60daze5cVxGC5TJpbwAm7CmhkE58rrTqj7OT4+5uOpjQH/S1FCf9/zogW7f/4VVrUmSp1a19mi7H87Ys8fZuuIyWqBMVkwBAHAZbR9jBZuBxoopAAD0MVawGWismAIA0G91dBSb5FhWsF9h5XjgsGIKAAxsTYPXvaVfaWioy09+8Gy377961drO255slyRHz3xLj+7Phlk5HjismAIAFdPa0bHJjTN4n0PSsMPIDN7nkIrtE6iMvrBybNW2NqyYAgAV09TQkKN/OL/b929ZtTpJ8sdVq3u03U/eM6XH2boyaNQuGTRql4rtD/qLhQsX5vvf/36OO+64Ab1aadW2NhRTAHqltaM9TQ3V/3FSq3EAeIVC9oq+sGo7EPgJD0CvNDU05qgfn1f1cW469syqjwHA/1HIqCWvMQUAAKBU/aaYelEyAADApqnfXMrrGngAAIBNU79ZMXUNPAAAwKap3xRTAAAANk2KKVB1XgMOAMD69JvXmAJ9l9eAwxtoGrTuLdAnNA3abJ1boDasmAJV5zXg8HqD9tkz9Ttsl0H77Fl2FOA1xu9zXN66w64Zv89xZUfpd4r2ol+ORWX02RXTor0jdY0N/WYcAHithlFvTcOot5YdA/gzbxu5d942cu+yY1Tc2vYi9Y11pY5V11iXpy5Y1qN9dTzf3nnbk223P8P8WmkLFy7M97///Rx33HFVuQKuzxbTusaG/L+vfbvb9+944cXO255st+2HT+hxNgAA2JTUN9bl4a8t79E2rS90dN72ZNtdP7xdj8Zh01Dtl2a5lBfokfaO1n45Fpu21o72fjUO0L+s7ajdZaW1HIuBpdovzeqzK6ZA39TY0JSvfntij7Z54cX2/719skfbfvSEW3o0DgNXU0NjJl97abfvv2bVC0mSP656oUfb3Tj9Iz3OBlDfUJc7r/p/Pdrm5Rc7Om97su0B/9+2PRoH+gorpgAAAH3YQPjoPSumAAAlq2savM4tUB1F+9rUNdZmba6SYw2Ej97rN8V0SOOgdW6BvuPV07JSp2d7R2saG5oqs7M+NBYwcA3ZZ1Jevv/WbLbXoRXbZ1tHkUENtXkX1lqOBb1R11if5Rc92KNtOv7U2nnbk223+4c9ejTO+gyEj97rN8V05m7jMv+xRZmyy9iyowB/Zsy4+ixZVGTnsZX5paWxoSn/ek3PXue6sc4+3utcgeobNGrXDBq1a2X32VCXOT9e2u37/79V7Z23PdkuSS45dkSP7g/w5/pNMd17+xHZe3uTIvRF24+oj9MTAICuePMjAADgdTZr3GydW6gmxXQ9ivbafF5drcYBoH9r7ejoV+MA5Tpqt5nZedtdc9RuM8uOwgDQby7lrYa6xsY88+8XVX2c5lP+oepjAND/NTU0ZMoPv1/1cea/57iqj0H/0N5RpLFGb4pUy7EGirHbj8vY7ceVHYMBQjEFAKAqGhvq8u/XLu/2/V9Y1dF525PtkuSU6dv16P5A3+JSXgAAAEqlmAIAAH2SN2AaOBRTgBpZuHBh5s6dm4ULF5YdBQA2CTN2mp4xW70jM3aaXnYUqsxrTAFqZN68eVmyZElaWloyfvz4suMAQJ83btu9Mm7bvcqOQQ1YMQWokZaWlnVuAQB4hWIKAABAqRRTAADoY5oah6xzC/2dYgoAAH3MhHEzM2rYrpkwbmbZUeinivaOPjWONz8CAIA+5u1v3Ttvf+veZccgyWaNg9e57S/qGhvyzFdu7Pb9O/60uvO2J9s1z57crftZMQUAAOjCzF0mZddtdsrMXSaVHaVfs2IKAADQhXHb7ZZx2+1Wdox+z4opAAAApVJMAQAAKJViCgAAQKkUUzZobXtrvxwLAADoG7z5ERtU39iUB792dE3G2uPDP6nJOAAAUJaifW3qGqu/RlircSpBMQUAAKihusb6LL/kjm7fv+NPL3Xe9mS77eYc1ONsZdk06jMAAAD9lmIKAABAqRRTAABS37TZOrcAtaSYAgCQ5v2OzdDh70jzfseWHQUYgLz5EQAA2WLUXtli1F5lxwAGKCumAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAlKZuUNM6twxsjf/7UTWNPrIGBhzFFGAjtHW09suxoNYG7bt/6nd4awbtu3/ZUegDxu47M9sO3zVj951ZdhSgxnxcDMBGGNTQlBN/PKlH2yxf1fa/t0/2aNsrj725R+PApqRx5Og0jhxddgz6iO1Hjcv2o8aVHQN4A0P+98qWIVW6wsWKKQAAAOv1njHvyq5veWveM+ZdVdm/FdM+rmhvS13joH4zDgAAsOnZe9jo7D2sele4KKZ9XF3joCz7yoeqPs5bZ19W9TEAAADeiEt5AQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApapqMV25cmXmzJmTSZMm5cgjj8x9991XzeEAAAD6nc0aB69z2x81VnPn5557bg466KBccsklaW1tzcsvv1zN4QAAAPqdme84NDc+/stM3vFdZUepmqoV01WrVuWee+7J5z//+SRJU1NTmpqaqjUcAABAvzRu2C4ZN2yXsmNUVdWK6dKlS7P11lvnzDPPzCOPPJLddtstn/zkJzN06NAut1mzZk0WL16cJBkzZky1or3Oq2P+ORlqn6GrHDLIIEP556cMMsggQ09zyCCDDOWfn305w2tVrZi2t7fn4Ycfztlnn50999wz55xzTi6//PJ87GMf63KbwYMH1/xgSWp/gMqwfn0hhwwyyCCDDDLI0DN9IYcMMsjQtzOsr6BW7c2Phg0blmHDhmXPPfdMkkyaNCkPP/xwtYYDAABgE1W1Yrrttttm2LBh+d3vfpckueuuu7LjjjtWazgAAAA2UVV9V96zzz47H//4x9PW1pYRI0bkvPPOq+ZwAAAAbIKqWkzHjBmTa6+9tppDAAAAsImr2qW8AAAA0B2KKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUoEbqmta9BQDgFYopQI1suV9DBg+vy5b7NZQdBQCgT2nc0B2uvPLK131t8803z9ixYzNmzJiqhALoj4aMqs+QUf4eCADw5zZYTBctWpRFixbl0EMPTZLcdttt2X333fO9730vkyZNyt/93d9VPSQAAAD91waL6Z/+9Kdce+21edOb3pQkOfXUUzNnzpx85zvfyfTp0xVTAAAAemWD15T98Y9/zKBBgzr/PWjQoPzxj3/MZpttlqYm7+ABAABA72xwxXTKlCk5/vjjc9hhhyVJfv7zn2fy5MlpaWnJjjvuWPWAAAAA9G8bLKYf/ehHc/DBB+fee+9NURT5zGc+k9133z1J8oUvfKHqAQEAAOjfNlhMk2TXXXdNc3NzOjo6krxyee8OO+xQ1WAAAAAMDBsspt/61rfyla98JW95y1tSX/9/L0m94YYbqhoMAACAgWGDxfSqq67KzTffnK222qoWeQAAABhgNviuvMOGDcsWW2xRiywAAAAMQBtcMR0xYkRmzZqVv/7rv17n42FOPPHEqgYDAABgYNhgMd1hhx2yww47pK2tLW1tbbXIBAAAwACywWI6e/bsWuQAAABggOqymJ577rn55Cc/mVNOOeUNv//v//7vVQsFAADAwNFlMZ02bVqS5KSTTqpZGAAAAAaeLovp2LFjkySLFy/OBz/4wXW+981vfjP77rtvdZMBQLU0Na57CwCUaoMfF3Pddde97ms//vGPqxIGAGqhcd9dUz982zTuu2vZUQCArGfFdP78+Zk/f36WLVu2zutMV69enS233LIm4QCgGhpGbZ+GUduXHQMA+F9dFtNx48Zl2223zfPPP7/O60zf9KY35e1vf3tNwgEAAND/dVlMhw8fnuHDh+eaa66pZR4AAAAGmA2+68P999+ff/3Xf83vfve7tLW1paOjI0OGDMm9995bi3wAAAD0cxt886PPfvaz+eIXv5iRI0fmgQceyDnnnJNZs2bVIhsAAAADwAaLaZKMHDkyHR0daWhoyIwZM3L33XdXOxcAAAADxAYv5R0yZEhaW1szZsyYXHDBBWlubk5LS0stsgEAADAAbHDF9IILLkhRFPnUpz6VoUOH5qmnnsqXv/zlWmQDAABgAFjvimlHR0cuuuiiXHjhhRk8eHBmz55dq1wAAAAMEOtdMW1oaMjzzz+f1tbWWuUBAABggNnga0yHDx+e973vfZkwYUKGDh3a+fUTTzyxqsEAAAAYGDZYTJubm9Pc3JyiKLJ69epaZAIAAGAA2WAx9bpSAAAAqqlbn2MKAAAA1aKYAgAAUCrFFAAAgFJtsJguXbo0p5xySvbbb7/sv//++fCHP5ylS5fWIhsAAAADwAaL6emnn55JkyblzjvvzB133JFJkyZl7ty5tcgGAADAALDBYloURY455pg0NjamsbEx06ZNS11dXS2yAQAAMAB0+XExf/rTn5Ik++23Xy6//PIcddRRqaury0033ZRDDjmkZgEBAADo37osptOnT09dXV2KokiSfO973+v8Xl1dXT760Y9WPx0AAAD9XpfF9Oc//3ktcwAAADBAdVlMk+T555/P/Pnz87vf/S5JsuOOO2bKlCnZcsstaxIOAACA/q/LNz96/PHHM3Xq1Dz00EMZNWpURo4cmd/85jeZMmVKHn/88VpmBAAAoB/rcsX04osvzllnnZWjjjpqna/fcsst+dKXvpQvf/nLVQ8HAABA/9fliumjjz76ulKaJBMnTsxjjz1W1VAAAAAMHF0W06FDh3a50fq+BwAAAD3R5aW8zz33XK688srXfb0oiqxYsaKqoQAAABg4uiymxx13XFavXv2G35s5c2bVAgEAADCwdFlMZ8+eXcscAAAADFBdFtNzzjlnvRv+8z//c8XDAAAAMPB0WUy/973vZeedd86RRx6Z5ubmFEVRy1wAAAAMEF0W0zvuuCM333xzbrrppjQ2Nuaoo47KEUcckTe/+c09GqCjoyMzZszIdtttl8suu6zXgQEAAOhfuvy4mK222irve9/78q1vfSuf//zns3LlykyePDnXXXddjwa46qqrsuOOO/Y6KAAAAP1Tl8X0VQ899FDmzZuXn/zkJzn44IMzduzYbu/86aefzm233Zb3vOc9vQoJAABA/9XlpbyXXHJJbrvttowePTqTJ0/O6aefnsbGLu/+hj73uc/lH//xH7v82Jk/t2bNmixevDhJMmbMmB6N1RuvjvnnZKh9hq5yyCCDDOWfnzLIIIMMPc0hgwwylH9+9uUMr9Vl07z00kszYsSIPProo3n00UfzxS9+cZ3v33DDDevd8a233pqtt946Y8eOzd13392twIMHD675wZLU/gCVYf36Qg4ZZJBBBhlkkKFn+kIOGWSQoW9nWF9B7bKYLliwoFeD33vvvfn5z3+eX/ziF1mzZk1WrVqVj3/847nwwgt7tV8AAAD6ly6L6fDhw3u149NPPz2nn356kuTuu+/OFVdcoZQCAADwOl0W03HjxqWuru51Xy+KInV1dbn33nurGgwAAICBoctiet9991VskP322y/77bdfxfYHAABA/7HBj4sBAACAalJMAQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApVJMAQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApVJMAQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApVJMAQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApVJMAQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApVJMAQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApVJMAQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApVJMAQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApVJMAQAAKJViCgAAQKkUUwAAAEqlmAIAAFAqxRQAAIBSKaYAAACUSjEFAACgVIopAAAApWqs1o6feuqpnHHGGXn22WdTX1+f4447Lh/84AerNRwAAACbqKoV04aGhnziE5/IbrvtllWrVmXGjBk54IADstNOO1VrSAAAADZBVbuUt7m5ObvttluSZPPNN8/o0aOzfPnyag0HAADAJqpqK6avtWzZsixevDh77rnneu+3Zs2aLF68OEkyZsyYWkRLks4x/5wMtc/QVQ4ZZJCh/PNTBhlkkKGnOWSQQYbyz8++nOG1ql5MV69enTlz5uSss87K5ptvvt77Dh48uOYHS1L7A1SG9esLOWSQQQYZZJBBhp7pCzlkkEGGvp1hfQW1qu/K29bWljlz5mTq1Kk54ogjqjkUAAAAm6iqFdOiKPLJT34yo0ePzoknnlitYQAAANjEVa2Y/vrXv87111+fhQsXZtq0aZk2bVpuv/32ag0HAADAJqpqrzF95zvfmUcffbRauwcAAKCfqOprTAEAAGBDFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACiVYgoAAECpFFMAAABKVdVi+otf/CITJ07M4Ycfnssvv7yaQwEAALCJqlox7ejoyGc/+9l8/etfz4033pj58+fnt7/9bbWGAwAAYBNVtWL64IMPZuTIkRkxYkSampoyefLkLFiwoFrDAQAAsImqK4qiqMaOb7755txxxx0599xzkyTXXXddHnzwwXzqU5/qcpv7778/gwcPrkYcAAAASrRmzZrstddeb/i9xmoN+kZ9t66ubr3bdBUSAACA/qtql/IOGzYsTz/9dOe/ly9fnubm5moNBwAAwCaqasV09913zxNPPJGlS5emtbU1N954YyZMmFCt4QAAANhEVe1S3sbGxnzqU5/K3/7t36ajoyMzZszIzjvvXK3hAAAA2ERV7c2PAAAAoDuqdikvAAAAdIdiCgAAQKn6dDE988wzs//++2fKlCmdX3vkkUdy/PHHZ+rUqTnllFOyatWqJMmyZcuyxx57ZNq0aZk2bdo6n5c6f/78TJ06NVOnTs3JJ5+cFStWVC3Ha783efLkTJ06NWvWrMmqVas6s02bNi377bdf52e8VjpDW1tb/umf/ilTp07NkUcemcsuu6xzm1mzZmXixImdOZ577rmaZ+jN89GTDK2trTnzzDMzderUHH300bn77rs7t1m0aFGmTp2aww8/POecc84bfrxRtTPU6rnoKkMtj8n1PQ594Xi46aabMnXq1EyePDkXXHBBt8dPkqeeeiqzZs3KkUcemcmTJ+eb3/xmkuRPf/pTTjzxxBxxxBE58cQT88ILL3Ruc9lll+Xwww/PxIkTc8cdd3R+/eSTT87RRx+dyZMn51Of+lQ6OjpqnuFVp5xyyjqPay0zbOy5UckMra2tOfvsszNx4sRMmjQpt9xyS00z9Ob8rOTjsLHnZyUzbOz52dMMzz//fGbNmpVx48bls5/97Dr72tifGZXMcNFFF+WQQw7JuHHjuv0YVDLDSy+9lL//+7/PpEmTMnny5Fx44YU1z5DUbp5cX4ZX9XSerHSOWs2V68tQq7myqwy1nCvX9zjUaq5cX4ZazZV33nlnpk+fnqlTp2b69Om56667OvfVm9+vkyRFH/arX/2qWLRoUTF58uTOr02fPr24++67i6Ioih/84AfFRRddVBRFUSxdunSd+72qra2tGD9+fPHcc88VRVEU559/fnHJJZdULUdbW1sxZcqUYvHixUVRFMWKFSuK9vb21+3z2GOPLX71q19VJcNPfvKT4mMf+1hRFEXR0tJSHHroocXSpUuLoiiKE044oXjwwQe7PW6lM/T2+ehJhm9/+9vFJz7xiaIoiuLZZ58tjj322KKjo6MoiqKYMWNGce+99xZr164tTj755OK2226reYZaPRfry/Ba1Twmu8rQF46HFStWFIccckhnhjPOOKP45S9/2e0My5cvLxYtWlQURVG8+OKLxRFHHFEsWbKkOP/884vLLrusKIqiuOyyy4oLLrigKIqiWLJkSTF16tRizZo1xR/+8IfisMMO65wjXnzxxaIoimLt2rXF7Nmzi/nz59c8Q1EUxS233FLMnTv3DefUWmTY2HOjkhkuvvji4otf/GJRFEXR0dHReXzUMsNr9eT8rFSG3pyflcrQm/OzpxlWr15d3HPPPcXVV19dfOYzn1lnXxv7M6OSGe67775i+fLlxV577dWtsSudoaWlpbjrrruKoiiKNWvWFO973/tKeRxqNU+uL0NRbNw8WekctZor15ehVnPlhp6PV1VzruwqQy3nyq4y1HKufOihh4qnn366KIqiePTRR4sDDzywc1+9+f26KIqiT6+Y7rPPPnnzm9+8ztd+//vfZ5999kmSHHDAAfnP/+iRmiUAABAKSURBVPzP9e6jKIoURZGXXnopRVFk1apVPf481Z7kuPPOO/P2t78973jHO5IkW221VRoaGtbZ9oknnshzzz2Xd77znVXJUFdXl5deeint7e15+eWXM2jQoGy++eY9+B9XL0Nvn4+eZPjtb3+b8ePHJ0m22WabbLHFFlm0aFGeeeaZrFq1KuPGjUtdXV2OOeaYLFiwoKYZeqvSGap9THaVoS8cD0uXLs2oUaOy9dZbJ0n233//bv/FN0mam5uz2267JUk233zzjB49OsuXL8+CBQtyzDHHJEmOOeaY/OxnP0uSLFiwIJMnT05TU1NGjBiRkSNH5sEHH+zcPkna29vT1taWurq6mmdYvXp1rrzyynz4wx/u9mNQ6Qwbq5IZfvSjH+VDH/pQkqS+vr7z+Cjjcejp+VmpDL05PyuVoTfnZ08zDB06NO985zszePDgdfbTm58ZlcqQJHvttddGfR58pTIMGTKkcw5tamrKrrvumuXLl9c0w6vbJ9WfJ9eXYWPnyUrn2FiVzFCrubI7j0O158quMtRyruwqQy3nyl133TXbbbddkmTnnXdOa2trWltbe/37ddLHL+V9I7vsskvnf/Lmm2/OU0891fm9ZcuW5ZhjjskJJ5yQ//7v/06SDBo0KJ/+9KczderUHHTQQXn88cfznve8p2o5fv/736euri4nn3xyjj322PzHf/zH67adP39+jjrqqG5Ppj3NMHHixAwZMiQHHnhgDj300Jx00knZcsstO7c766yzMm3atHz1q1/t+RJ7LzNU4/noKsM73vGOLFiwIO3t7Vm6dGkeeuihPPXUU1m+fHmGDRvWuf2wYcO6/cO1UhleVYvnYkMZkuofk11l6AvHw8iRI/O73/0uy5YtS3t7exYsWJCnn356o8ZetmxZFi9enD333DPPPfdc5w+m5ubmzst6/vz422677dY5/k4++eS8613vypve9KZMnDix5hkuvvjinHTSSdlss816PHalMiS9Pzd6k2HlypVJXnksjj322MyZMyfPPvtsTTO8Vm/Oz95kqNT52ZsMlTo/u5OhK5X6mdGbDJVSqQwrV67Mrbfemv3337+UDLWYJ9enEvNkJXIktZkru1LLubI7qj1XdqWWc2VXyporb7nllowZMyZNTU0VmSs3uWJ67rnn5uqrr8706dOzevXqNDU1JXnlAbv11ltz3XXX5ROf+EROP/30rFq1Km1tbfnud7+b6667LnfccUfe/va3r/N6x0rn6OjoyK9//ev827/9W66++ur87Gc/W+fa6+SVa8AnT55ctQwPPvhg6uvrc8cdd2TBggW54oorsnTp0iTJhRdemBtuuCHf+c538utf/zrXX399TTNU4/noKsOMGTMybNiwzJgxI5/73Ocybty4NDQ0vOHE3dtC1tMMSe2ei/VleFW1j8muMvSF4+HNb35zPv3pT+cf/uEf8oEPfCDDhw9/3ePTHatXr86cOXNy1llnrfcKhQ0df9/4xjfyX//1X2ltbc3ChQtrmmHx4sX5wx/+kMMPP7xH41YyQ9L7c6O3Gdrb2/P0009n7733zo9//OOMGzcu559/fk0zvNbGnp+9zVCJ87O3GSpxfnY3Q0+z1TJDJVQqQ3t7e+bOnZtZs2ZlxIgRpWSoxTzZlUrMk5XIkdRuruxKLefK7qj2XNmVWs6VXSljrlyyZEkuvPDCzte6VmKubOzRvfuAHXfcMVdccUWSV1Ynb7vttiSvXFby6i+gY8eOzV/+5V/m97//feeD9Jd/+ZdJkiOPPDKXX3551XIMGzYs++67b+dS+sEHH5yHHnqo86+KjzzySDo6OjJ27NiqZZg/f34OOuigDBo0KNtss0323nvv/OY3v8mIESM6l94333zzTJkyJQ8++GDnMn0tMjz//PNJKvt8dJWhsbExZ511Vuf93vve92bUqFH5i7/4i3X+ivT0009v1OVRvcmQpGbPxfoyJLU5JrvKsHjx4iTlHg9JMmHChEyYMCFJcs0116S+vmd/s2tra8ucOXMyderUHHHEEUleuVz4mWeeSXNzc5555pnOOWHYsGHrHH/Lly9/3fE3ePDgTJgwIQsWLMgBBxxQswz33XdfFi1alAkTJqS9vT0rVqzIrFmz8q1vfaumj0Nvzo1KZNhqq60yZMiQzl88J02alB/+8IfdGr+Sj0Oy8ednJTL09vys1OPQm/OzJxm68ufZevozoxIZequSGc4+++yMGjUqf/M3f1NahqT682RXejtPVipHUru5siu1nCs3pBZzZVdqOVeuTy3nyqeffjqzZ8/O+eef3/n/7u1cmWyCK6avvuPY2rVr87WvfS3vfe97kyQrVqzofGe2pUuX5oknnugsYo8//njn8vOdd96ZHXfcsWo5DjzwwDz66KOdr6+85557stNOO3VuN3/+/IqsTK0vw/bbb5+77747RVGkpaUlDzzwQEaPHt05gSavHIC33XZbdt5555pmqMbz0VWGl156KS0tLZ3jNDQ0ZKeddkpzc3Pe9KY35f77709RFLnuuuty2GGH1TRDLZ+LrjK8qhbHZFcZ+sLx8NptXnjhhVx99dWZOXNmt8criiKf/OQnM3r06Jx44omdX58wYUKuu+66JFnnGJswYUJuvPHGtLa2ds5Ve+yxR1avXp1nnnkmySt/hb799tszevTommZ4//vfn//6r//Kz3/+81x99dUZNWpUt3/ZqlSG3pwblcpQV1eXQw89tPOdm++6665uH5eVyvCqjTk/K5WhN+dnJR+HjT0/e5qhK735mVGpDL1RyQwXXXRRVq1atc4f+WqZoZbzZFd6M09WMkct58qu1HKu3JBazJVdqeVcuT61mitXrlyZv//7v8/cuXPzV3/1V533r8Tv13VFb1/YVkVz587Nr371qzz//PPZZpttcuqpp6alpSVXX311kuTwww/P6aefnrq6utxyyy255JJL0tDQkIaGhpx66qmdfzX47ne/m6uuuiqNjY0ZPnx4zjvvvGy11VZVyZEk119/fS6//PLU1dXl4IMPzhlnnNG5r8MOOyyXX355j3/57kmG1atX58wzz8zjjz+eoigyffr0/O3f/m1aWlpywgknpK2tLWvXrs3++++fM888s9tL/ZXIkPTu+ehJhmXLluXkk09OfX19tttuu5x77rkZPnx4kuQ3v/lNzjzzzLz88ss5+OCDc/bZZ3f7coNKZKjlc7G+xyGpzTG5vgx94XiYO3duHnnkkSTJRz/60R79cPvv//7vfOADH8guu+zS+dfJuXPnZo899sjHPvaxPPXUU9l+++1z8cUXd77W+2tf+1p+9KMfpaGhIWeddVYOOeSQPPvss/nQhz6U1tbWrF27NuPHj8+ZZ56ZxsYNX9hSqQyvtWzZspxyyimZP39+TR+H3pwblXwcnnzyyZxxxhlZuXJltt5665x33nnZYYcdapoh2bjzs5IZNvb8rGSGjT0/NybDhAkTOl8GtMUWW+SKK67ITjvttNE/MyqZ4YILLsj8+fM7VzBmzpyZU089tWYZNt988xxyyCEZPXp05xVqJ5xwQrd++a1Uhi233LKm82RXz8WrejpPVjLHDjvsUNO5sqvHopZz5fqej1rNlV1lqOVc2VWGWs2Vl156aS6//PKMHDmycx9XXHFFttlmm179fp308WIKAABA/7fJXcoLAABA/6KYAgAAUCrFFAAAgFIppgAAAJRKMQUAAKBUiikAA0JRFHnf+96X22+/vfNrN910U04++eSqj/3Tn/40Rx55ZGbNmrVR2y9btixTpkypcCoA6Ds2/MFPANAP1NXV5TOf+UxOO+20jB8/Ph0dHfnSl76Ur3/96xu1v46Ojm5/9vAPf/jD/Mu//EvGjx9fkf0BQH/jc0wBGFAuuOCCDB06NC0tLRk6dGiefPLJPPbYY+no6Mjs2bPz7ne/O8uWLcsZZ5yRl156KUly9tlnZ++9987dd9+dr3zlK2lubs7ixYtz0003rbPv+fPn57LLLktRFDnkkEPyj//4j/nKV76Sb3zjG2lubs6ECRPyT//0T533//P93XDDDbnwwgvzq1/9Kq2trfnABz6Q9773vVm2bFlOOeWUzJ8/Px0dHW94n9WrV+cjH/lIVq5cmfb29px22ml597vfnZaWlnzsYx/L008/nbVr1+YjH/lIjjrqqCxatCif//zn09LSkq222irnnXdempuba/pcAMCrrJgCMKDMnj07xx57bJqamvLXf/3XGT9+fM4777ysXLkyM2fOzLve9a5ss802ufLKKzN48OA88cQTmTt3bq699tokyW9+85vccMMNGTFixDr7Xb58eS688MJce+21+Yu/+IucdNJJ+dnPfpbZs2fn7rvvzhlnnJHdd9/9dXleu79rrrkmW2yxRX70ox+ltbU1733ve3PAAQekrq6u8/4//OEP3/A+22+/fb761a9m8803z4oVK3L88cfnsMMOyx133JHm5uZcfvnlSZIXX3wxbW1tOeecc3LppZdm6623zk033ZSLLroo5513XhUfeQDommIKwIAydOjQHHXUURk6dGh++tOf5tZbb80VV1yRJFmzZk2eeuqpNDc357Of/WweeeSR1NfX54knnujcfvfdd39dKU1eKZj77rtvtt566yTJ1KlTc8899+Td7373evO8dn933nlnHn300dxyyy1JXimR//M//5NRo0Z13r+r+wwbNixf/OIXc88996S+vj7Lly/Ps88+m1122SXnn39+/u3f/i2HHnpo3vnOd+axxx7LY489lhNPPDFJsnbt2my77bYb94ACQAUopgAMOPX19amvf+X9/y655JKMHj16ne9/+ctfzlve8pZcf/31Wbt2bfbYY4/O7w0dOrSiWV67v6Io8s///M856KCD1rnPsmXLNnifa6+9NitWrMi1116bQYMGZcKECVmzZk3e9ra35dprr83tt9+eL3zhCznggANy+OGHZ+edd84111xT0f8LAGws78oLwIB14IEH5tvf/nZefbuFhx9+OMkrq5Dbbrtt6uvrc/3116ejo2OD+9pjjz1yzz33ZMWKFeno6MiNN96YffbZp8d5vvvd76atrS1J8vvf/z4tLS3dus+LL76YbbbZJoMGDcrChQvz5JNPJnnlEuMhQ4Zk2rRpOfnkk/Pwww/nbW97W1asWJH77rsvSdLW1pYlS5b0KCsAVJIVUwAGrI985CP53Oc+l6OPPjpFUWT48OG57LLL8v73vz+nnnpqbr755uy3337dWiVtbm7O3Llz88EPfjBFUeTggw/e4GW8f27mzJl58sknM3369BRFka222iqXXnppt+4zderUfPjDH8706dMzZsyYzlXgxx57LBdccEHq6+vT2NiYT3/602lqasoll1ySc845Jy+++GI6OjrywQ9+MDvvvHOP8gJApXhXXgAAAErlUl4AAABKpZgCAABQKsUUAACAUimmAAAAlEoxBQAAoFSKKQAAAKVSTAEAACjV/w8eHpenEgXtrAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting the ratings by year of release\n",
    "plt.figure(figsize = (16,7))\n",
    "sns.barplot(x = 'Year of release', y = 'IMDb rating', data = prime_df.dropna(axis = 0, subset = ['IMDb rating']));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.047693,
     "end_time": "2020-10-03T11:33:34.902982",
     "exception": false,
     "start_time": "2020-10-03T11:33:34.855289",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "The ratings for shows over the years vary slightly in their values and do not follow any particular trend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:35.026013Z",
     "iopub.status.busy": "2020-10-03T11:33:35.020800Z",
     "iopub.status.idle": "2020-10-03T11:33:35.644040Z",
     "shell.execute_reply": "2020-10-03T11:33:35.644656Z"
    },
    "papermill": {
     "duration": 0.694876,
     "end_time": "2020-10-03T11:33:35.644814",
     "exception": false,
     "start_time": "2020-10-03T11:33:34.949938",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7kAAAGpCAYAAABI7vFyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nOzdbXRU9bn//8/shNBAMDDpSaIRuUkFLSpCSSCi4RAJCEEJE+GfFvijoFhA0hCEGGKBaoOHSKnYCsiJ4dSWWGpAaBIFFrGRm0NB7VGLEk9BqMEmQUIQc4OTyczvQQ6zjNzMBDPDTHi/1uqq7Oz9va695tG19t7fj8nhcDgEAAAAAEAHYFztBgAAAAAAaC8MuQAAAACADoMhFwAAAADQYTDkAgAAAAA6DIZcAAAAAECHEXi1G/CUv/3tbwoODr7abaANvv76a3Xu3Plqt4E24DfzP/xm/offzP/wm/kffjP/w2/mfzzxm3399de68847LzjusSE3KytLZWVlCgsLU3FxsSSpvLxcS5cuVUNDg6KiorRy5UqFhIRo3759+tWvfqWmpiZ16tRJCxcuVFxcnCTJarXqmWee0cGDB2UymTR//nyNGTPGZf3vde6sW2+91a1eHbZmmQIDrvxm0S4OHz7s9m8G38Bv5n/4zfwPv5n/4TfzP/xm/offzP944jc7fPjwRY97bMi1WCyaOnWqMjMznceys7OVmZmp2NhYFRYWKi8vT+np6erRo4fWrl2riIgI/e///q9mzpypPXv2SJLWrVsns9msHTt2yG6368yZM27VNxmGvlj7B7fO/bfZU9t+gwAAAAAAn+Oxb3JjYmIUGhra6tixY8cUExMjSRo+fLh27twpSfrhD3+oiIgISdLNN98sq9Uqq9UqSdq8ebMee+yxlmYNQ2az2VMtAwAAAAD8nFc3nurXr59KS0slSdu3b1dlZeUF5+zYsUO33nqrgoKCdPbsWUnS6tWrNXHiRKWlpenUqVPebBkAAAAA4Ee8OuTm5OSooKBAFotF9fX1CgoKavX3f/zjH1q5cqWefvppSZLNZlNVVZUGDx6s119/XYMGDdKKFSu82TIAAAAAwI94dXfl6Oho5efnS2p5dbmsrMz5t6qqKj3++ONasWKFbrrpJklSjx49FBwcrMTEREnSfffdp8LCQm+2DAAAAADwI159kltTUyNJstvtWrt2rVJTUyVJZ8+e1axZs5SRkaEf/ehHzvNNJpNGjhypAwcOSJL279+v6Ohob7YMAAAAAPAjHnuSm5GRoYMHD6q2tlbx8fGaN2+eGhoaVFBQIElKTExUSkqKJOkPf/iDPvvsM61Zs0Zr1qyRJOXn5yssLExPPPGEFi1apOXLl8tsNuvZZ591q77Dbnd712QihAAAAACgY/DYkLtq1aqLHp8+ffoFx+bMmaM5c+Zc9PyoqCht3LixXXv7trYMuA6bTaZAr77lDQAAAABwk8emtaysLJWVlSksLEzFxcWSpPLyci1dulQNDQ2KiorSypUrFRISohMnTmjcuHHq06ePJGngwIHOzaesVqueeeYZHTx4UCaTSfPnz9eYMWNc1jcZhr5Y91K739e//fSxdl8TAAAAANA+PDbkWiwWTZ06VZmZmc5j2dnZyszMVGxsrAoLC5WXl6f09HRJ0k033aRt27ZdsM66detkNpu1Y8cO2e12nTlzxlMtAwAAAAD8nMc2noqJiVFoaGirY8eOHVNMTIwkafjw4dq5c6fLdTZv3qzHHmt5emoYhsxmc/s3CwAAAADoELy6u3K/fv1UWloqSdq+fbsqKyudfztx4oSSk5M1depUvfvuu5Jadl2WpNWrV2vixIlKS0vTqVOnvNkyAAAAAMCPeHXIzcnJUUFBgSwWi+rr6xUUFCRJCg8P11/+8hdt3bpVTz75pBYsWKC6ujrZbDZVVVVp8ODBev311zVo0CCtWLHCmy0DAAAAAPyIV7cJjo6OVn5+vqSWV5fLysokSUFBQc6B97bbbtNNN92kY8eO6bbbblNwcLASExMlSffdd58KCwu92TIAAAAAwI94dcitqalRWFiY7Ha71q5dq9TUVEnS6dOnFRoaqoCAAFVUVOj48ePq2bOnTCaTRo4cqQMHDiguLk779+9XdHS0W7UcdrtHdkImQggAAAAAfJfHprWMjAwdPHhQtbW1io+P17x589TQ0KCCggJJUmJiolJSUiRJ77zzjl544QUFBAQoICBAv/jFL9S9e3dJ0hNPPKFFixZp+fLlMpvNevbZZ92q/7XV6pH7YsAFAAAAAN/lsW9yO3furObmZvXp00e7d+/WpEmTNHToUHXv3l1BQUE6cuSI6uvrJUkDBgxQRUWFTCaT7Ha78zXmuro6zZkzR3V1dTIMQ+Xl5dqwYYN79f/v9Wd3OGy2Nt8fAAAAAMD3+HRObkhISKtjFotFo0ePdqu+yTBUvTbXrXMjZi9y6zwAAAAAgG/z+Zzc844fP66amhoNGTKkXfsEAAAAAHQcPp2T+03FxcUaN26cTCaT1/oFAAAAAPgXn87J/aY33nhDSUlJ3mwXAAAAAOBnfDon9/bbb5cklZeXq7m5Wbfddps32wUAAAAA+Bmfzsk9r7i4uM1PcR12u9sbSpF9CwAAAAAdg8/n5ErSm2++qfXr17epfltychlwAQAAAKBj8OmcXKnlKW6XLl2Unp6umTNn6vTp0+7Vb0NObls4bE0eWRcAAAAA8N35dE6uzWZTTk6OSkpKZDablZubq40bN2revHku65sMQ/96cUH73pSkG+b+qt3XBAAAAAC0D5/OyXU4HHI4HGpsbJTD4VBdXZ3Cw8M91TIAAAAAwM/5dE5up06dtGzZMt1///265557dPToUT344IPebBkAAAAA4Ed8Oie3qalJr776qrZu3ao9e/aof//+eumll7zZMgAAAADAj/h0Tq7D4ZDU8r2uJI0dO7bNuywDAAAAAK4dXn2SW1NTI0kXzcltbm6WpFY5uRERETp69KhzR+V9+/YpOjramy0DAAAAAPyIz+fkzp07V1OmTFFgYKCioqL07LPPulXfYbd7ZCdkh61JpsBO7b4uAAAAAOC78/mc3NDQUAUGBsput6tv377q0aOHp1p2i0OOq1ofAAAAAHBpPp2TW1tbq9zcXG3ZskVms1mZmZnav3+/4uLiXNY3GYaOv5DcvjclqXfa1nZfEwAAAADQPnw6J7eiokK9e/eW2WyWJMXFxWnHjh2eaRgAAAAA4Pd8Oie3V69e+vTTT3XixAnZbDaVlpaqqqrKmy0DAAAAAPyIVyOEcnJylJOTozVr1ighIeGCnNwePXro0KFDmjt3rkpKShQaGqply5Zp/vz5MgxDgwYNUkVFhTdbBgAAAAD4EZ/Oyb399tuVkJCghIQESdKmTZtkGF59+AwAAAAA8CM+nZP7zWu+/PJLFRQUaNKkSd5sGQAAAADgR3w+JzcnJ0fl5eWSWjJz+/Tp41Z9h93ukZ2Q7TarjMCgdl8XAAAAAPDdeWzIXbVq1UWPT58+/YJjY8aM0ZgxY9q0ztXi7oDLMAwAAAAA3uexITcrK0tlZWUKCwtTcXGxJKm8vFxLly5VQ0ODoqKitHLlSoWEhLT6W11dnQzDUGFhoTp37qxDhw4pKytL586d04gRI5SdnS2TyeSyvskw9Pc1D3jq9ly6fc6fr1ptAAAAALhWeeybXIvFory8vFbHsrOztWDBAhUVFWnUqFHOv9tsNi1cuFC/+MUvVFJSoldeeUWBgS3z97Jly/T0009r586dOn78uHbv3u2plgEAAAAAfs5jQ25MTIxCQ0NbHTt27JhiYmIkScOHD9fOnTslSfv27VP//v11yy23SJJ69OihgIAAnTx5UnV1dRo0aJBMJpOSk5OdObsAAAAAAHybV3dX7tevn3NI3b59uyorKyW1DL8mk0kzZ87UxIkT9Z//+Z+SpOrqakVGRjqvj4yMVHV1tTdbBgAAAAD4Ea8OuTk5OSooKJDFYlF9fb0zG7e5uVnvvfeennvuORUUFGjXrl3av3+/HA7HBWu48z0uAAAAAODa5LGNpy4mOjpa+fn5klqe3paVlUlqeUIbGxsrs9ksSYqPj9dHH32kBx54QFVVVc7rq6qqFB4e7s2WAQAAAAB+xKtDbk1NjcLCwmS327V27VqlpqZKku6++27l5eWpsbFRnTp10jvvvKOHHnpI4eHh6tq1q95//30NHDhQW7du1bRp09yq5bDbr+oOx0QIAQAAAID3eWzIzcjI0MGDB1VbW6v4+HjNmzdPDQ0NKigokCQlJiYqJSVFkhQaGqqHHnpIDz74oEwmk+Lj4/Xv//7vklp2Vz4fIRQfH6/4+Hi36n9ttXrkvtzFgAsAAAAA3uexb3I7d+6s5uZm9enTR7t379akSZM0dOhQde/eXUFBQTpy5Ijq6+ud5/fv318hISFyOBzas2ePvv76a9XV1empp55SQECAunbtqpKSEi1fvty9+kHuD5l229UdiAEAAAAA7cNjT3ItFoumTp2qzMxM57Hs7GxlZmYqNjZWhYWFysvLU3p6ujMn97nnntMtt9yi2tpaBQYGqnPnztq2bVurNUePHu1WfZNh6MBL4906d+hjxW27OQAAAACAT/LpnNxvOn78uGpqajRkyBBPtQwAAAAA8HM+nZP7TcXFxRo3bhwRQgAAAACAS/LpnNxveuONN5SUlOTNdgEAAAAAfsanc3Lj4uIkSeXl5WpubtZtt93mzXYBAAAAAH7Gp3NyzysuLm7zU1yH3e72hlJk2gIAAABAx+DzObmS9Oabb2r9+vVtqt+WnFwGXAAAAADoGHwiJ/fPf/6z8vPzFRgYqICAAOXn5+vw4cOSWr7F7dKli9LS0pSbm+t+/Tbk5DaTkwsAAAAAHYJP5OQ+8MADeuCBByRJn3zyiebMmaNbb71VtbW1ys3N1ZYtW2Q2m5WZman9+/c7v9W9HJNh6C957r3iPPKRkiu7SQAAAACAT/GJnNxvKikp0fjx4yVJFRUV6t27t3NDqri4OO3YscNTLQMAAAAA/JxP5OR+0zejgnr16qVPP/1UJ06ckM1mU2lpqaqqqrzZMgAAAADAj/hETu55H3zwgYKDg9WvXz9JLRtSLVu2TPPnz9eUKVMUFRWlgIAAb7YMAAAAAPAjPpGTe15JSckFUUEJCQlKSEiQJG3atEmG4dW5HAAAAADgR7w6MdbU1EjSBTm5549t3779giH3/DVffvmlCgoKNGnSJO81DAAAAADwKz6RkytJ77zzjiIjI9WzZ89W6+Tk5Ki8vFySNHfuXPXp08et+g673e1dk5ttVgWQlQsAAAAAfs9jQ+6qVasuenz69OkXPT506FD96U9/cnsdVxxXdBUAAAAAwJ95bMjNyspSWVmZwsLCVFxcLEkqLy/X0qVL1dDQoKioKK1cuVIhISFqamrSU089pY8//lg2m03Jycl67LHHJEmHDh1SVlaWzp07pxEjRig7O1smk8llfcMw9ObL49zqdezMN678RgEAAAAAPsNj3+RaLBbl5eW1Opadna0FCxaoqKhIo0aNcv59+/btslqtKioq0pYtW7Rp0yadOHFCkrRs2TI9/fTT2rlzp44fP67du3d7qmUAAAAAgJ/z2JAbExOj0NDQVseOHTummJgYSdLw4cO1c+dOSZLJZFJjY6NsNpvOnTunTp06KSQkRCdPnlRdXZ0GDRokk8mk5ORkZ84uAAAAAADf5tXdlfv16+ccUrdv367KykpJ0pgxYxQcHKy7775bI0eO1IwZM9S9e3dVV1crMjLSeX1kZKSqq6u92TIAAAAAwI94dcjNyclRQUGBLBaL6uvrFRTUsqPxhx9+KMMwtGfPHpWWlio/P18VFRVyOC7cPsqd73EBAAAAANcmj208dTHR0dHKz8+X1PLqcllZmSSpuLhY99xzjzp16qSwsDANHjxYf//73zVkyBBVVVU5r6+qqlJ4eLg3WwYAAAAA+BGvDrk1NTUKCwuT3W7X2rVrlZqaKkm6/vrrdeDAAU2YMEGNjY364IMPNH36dIWHh6tr1656//33NXDgQG3dulXTpk1zq5bdbnd712RycgEAAACgY/DYkJuRkaGDBw+qtrZW8fHxmjdvnhoaGlRQUCBJSkxMVEpKiiRpypQpysrK0vjx4+VwOGSxWHTLLbdIatld+XyEUHx8vOLj492qb7Va3e6VARcAAAAAOgaPDbmdO3dWc3Oz+vTp0yon94033lBDQ4OOHDmi+vp6hYSEKCgoSMHBwTIMQzabTc3Nzc51du3apa+++kpnz57VkiVL3K5//ntfd/AkFwAAAAA6Bo8NuRaLRVOnTlVmZqbzWHZ2tjIzMxUbG6vCwkLl5eUpPT29VU5uY2OjkpKSlJSUpBtvvFEjR47UlClTNGbMmDbVNwxDWzbc516vD29v09oAAAAAAN/k0zm5knTnnXey2RQAAAAAwC0+nZMLAAAAAEBb+HROLgAAAAAAbeHTObk9e/b0ZnsAAAAAAD/n0zm534Xdbnd7Qyl2VwYAAACAjsFjrytnZGQoNTVVx44dU3x8vF577TUVFxdrzJgxGjt2rMLDw1vl5NbX12v8+PF68MEHW+Xk5ubmKj4+Xo2NjYqPj9dvfvMbt+qTkwsAAAAA1x6fz8n95JNP1L17d3Xr1k0/+tGPNGfOHLfqtyUnty146gsAAAAAvsvnc3JXr16tkJAQORwOpaWlafv27UpKSnJZ3zAMbfyvtmXrumPKQzvafU0AAAAAQPvw+Zzc8/9vs9nU1NQkk8nkqZYBAAAAAH7OL3JyZ86cqbvuuktdu3bVmDHt/3QWAAAAANAx+EVO7ssvv6y9e/fKarXqr3/9qzdbBgAAAAD4Eb/Jye3cubMSEhJUWlqq4cOHe7NtAAAAAICf8Omc3Pr6etXX1ys8PFw2m01vv/22hgwZ4lYtu93ukU2i2F0ZAAAAAHyXx4bcjIwMHTx4ULW1tYqPj9e8efPU0NCggoICSVJiYmKrnNysrCyNHz9eDofDmZN76tQpzZ49W1arVXa7XcOGDXMOxq60JSe3LRhwAQAAAMB3+XRO7ve//31t3rxZkvTTn/5UBw4cUGCgey23JSfX1mxVYADDKwAAAAD4O5/PyZWknTt3qmvXrm2qbxiGXn5ltFvnzvz/d7ZpbQAAAACAb/L5nNz6+npt2LBBs2fP9lSrAAAAAIAOwudzclevXq0ZM2boe9/7njdbBQAAAAD4IZ/OyT18+LA+++wzJSYmerNNAAAAAICf8umc3DNnzujQoUNKSEiQzWbT6dOnNW3aNP3+97/3ZtsAAAAAAD/h1Se5NTU1knTJnFyHw6GGhgZ98MEH6tu3r37yk59o7969euutt1RQUKDevXsz4AIAAAAALsmnc3K/C7vd7vauyUQIAQAAAEDH4LEhd9WqVRc9Pn369AuOde3aVS+88MJl17vxxhudebvtrS0DLgMxAAAAAPgujw25WVlZKisrU1hYmHM4LS8v19KlS9XQ0KCoqCitXLlSISEhampq0lNPPaWPP/5YNptNycnJeuyxxyRJ06ZN08mTJ527K+fn5yssLMxlfcMw9Ns/jGn3+3p86o52XxMAAAAA0D489k2uxWJRXl5eq2PZ2dlasGCBioqKNGrUKOfft2/fLqvVqqKiIm3ZskWbNm3SiRMnnNetXLlS27Zt07Zt29wacAEAAAAA1yaPDbkxMTEKDQ1tdezYsWOKiYmRJA0fPlw7d7Z8M2symdTY2CibzaZz586pU6dOCgkJ8VRrAAAAAIAOyqu7K/fr10+lpaWSWp7eVlZWSpLGjBmj4OBg3X333Ro5cqRmzJih7t27O69bvHixJkyYoBdffFEOh8ObLQMAAAAA/IhXh9ycnBwVFBTIYrGovr5eQUEtGzh9+OGHMgxDe/bsUWlpqfLz81VRUSGp5VXloqIibdy4Ue+99562bdvmzZYBAAAAAH7Eq0NudHS08vPztWXLFiUlJalnz56SpOLiYt1zzz3q1KmTwsLCNHjwYP3973+XJEVEREiSQkJCNH78eH344YfebBkAAAAA4Ec8trvyxdTU1CgsLEx2u11r165VamqqJOn666/XgQMHNGHCBDU2NuqDDz7Q9OnTZbPZdPbsWZnNZjU1NamsrExxcXFu1bLb7R7ZCZkIIQAAAADwXR4bcjMyMnTw4EHV1tYqPj5e8+bNU0NDgwoKCiRJiYmJSklJkSRNmTJFWVlZGj9+vBwOhywWi2655RY1NDTokUceUVNTk+x2u+Li4jR58mS36lutVo/cFwMuAAAAAPguj72u3LlzZzU3N6tPnz7avXu3Jk2apKFDh6p79+4KCgrSkSNHVF9fL0kKCgpScHCwDMOQw+FQc3OzJKlLly764x//qDvvvFM2m0179+7Vrl273Kp//ntff2Br9sxADgAAAADXGo89ybVYLJo6daoyMzOdx7Kzs5WZmanY2FgVFhYqLy9P6enprXJyGxsblZSUpKSkJN14441at26dzGazduzYIbvdrjNnzrhV3zAM5b46xlO3164W/bj9X6sGAAAAgGuRz+fkbt68WY899lhLs4Yhs9nsqZYBAAAAAH7Op3Nyz549K0lavXq1Jk6cqLS0NJ06dcqbLQMAAAAA/IhP5+TabDZVVVVp8ODBev311zVo0CCtWLHCmy0DAAAAAPyIT+fk9ujRQ8HBwUpMTJQk3Xffffr444+92TIAAAAAwI/4dE6uyWTSyJEjdeDAAcXFxWn//v2Kjo52q5bdbvebDZ3I3gUAAACA9uHTObmS9MQTT2jRokVavny5zGaznn32Wbfqeyon1xMYcAEAAACgffh0Tm5dXZ3mzJmjuro6GYah8vJybdiwwa36/pST20ROLgAAAAC0C5/Pyd22bVurNUePHu1WfcMw9PM/3dfu9+UJz0zefrVbAAAAAIAOwedzcs87fvy4ampqNGTIEE+1DAAAAADwcz6dk/tNxcXFGjdunEwmkzdbBgAAAAD4EZ/Oyf2mN954Q0lJSd5sFwAAAADgZ7waIXQ+J1dqeXW5rKxM0qVzcs/n6JaXl6u5uVm33XabN9sFAAAAAPgZrz7JrampkaRL5uQ6HA41NDTogw8+UN++fZ3XFRcX8xQXAAAAAOCSz+fkStKbb76p9evXt6m+3W73m12Lm5qt6kRWLgAAAAB8Zz6dkyu1PMXt0qWL0tPTNXPmTJ0+fbrde73aObUMuAAAAADQPnw6JzcyMlI5OTkqKSmR2WxWbm6uNm7cqHnz5rmsbxiG5mxxLyd3jcU/nvgCAAAAAC7Pp3NyHQ6HHA6HGhsb5XA4VFdXp/DwcE+1DAAAAADwcz6dk9upUyctW7ZM999/v+655x4dPXpUDz74oDdbBgAAAAD4EZ/OyW1qatKrr76qrVu3as+ePerfv79eeuklb7YMAAAAAPAjPp2TW1tbK0m66aabJEljx45t8y7LAAAAAIBrh0/n5EZEROjo0aPOHZX37dun6Ohob7YMAAAAAPAjPp+TO3fuXE2ZMkWBgYGKiorSs88+61Z9u93u9q7J5NQCAAAAQMfgsSF31apVFz0+ffr0C4517dpVL7zwwkXP//GPf6wf//jH7drbt3liwLU2WxXE4AwAAAAAXuWxITcrK0tlZWUKCwtTcXGxJKm8vFxLly5VQ0ODoqKitHLlSoWEhMhqtWrp0qU6dOiQTCaTsrOzNXToUEnSoUOHlJWVpXPnzmnEiBHKzs6WyWRyWd8wDI398wOeuj2X3nzgz1etNgAAAABcqzz2Ta7FYlFeXl6rY9nZ2VqwYIGKioo0atQo599fe+01SVJRUZE2bNigFStWyG63S5KWLVump59+Wjt37tTx48e1e/duT7UMAAAAAPBzHhtyY2JiFBoa2urYsWPHFBMTI0kaPny4du7cKUk6cuSIhg0bJkkKCwtTt27ddOjQIZ08eVJ1dXUaNGiQTCaTkpOTnTm7AAAAAAB8m1d3V+7Xr59zSN2+fbsqKyslSbfccotKS0tls9lUUVGhjz76SJWVlaqurlZkZKTz+sjISFVXV3uzZQAAAACAH/HqkJuTk6OCggJZLBbV19crKKhlY6aUlBRFRkYqJSVFy5cv16BBgxQQECCHw3HBGu58jwsAAAAAuDZ5bOOpi4mOjlZ+fr6klleXy8rKWpoIDNTixYud56Wmpqp379667rrrVFVV5TxeVVWl8PBwb7YMAAAAAPAjXh1ya2pqFBYWJrvdrrVr1yo1NVWS1NjYKIfDoS5dumjfvn0KCAjQD37wA0kt8ULvv/++Bg4cqK1bt2ratGlu1bLb7Vd1h2MihAAAAADA+zw25GZkZOjgwYOqra1VfHy85s2bp4aGBhUUFEiSEhMTlZKSIqll+J05c6YMw1BERIRyc3Od6yxbtswZIRQfH6/4+Hi36lut1va/qTZgwAUAAAAA7/PYN7mdO3dWc3Oz+vTpo927d2vSpEkaOnSounfvrqCgIB05ckT19fWSpPDwcA0ePFiBgYE6ffq0Tpw44Vxn165d+uqrr1RTU6MlS5a4/U3u+e9925u1uckj6wIAAAAAvjuPPcm1WCyaOnWqMjMznceys7OVmZmp2NhYFRYWKi8vT+np6a1ycmtqavToo4+qsLBQhmFo5MiRmjJlisaMGdOm+oZhaOzWtHa9J0l6M/mFdl8TAAAAANA+fDonV5LuvPNONpsCAAAAALjFp3NyAQAAAABoC5/OyQUAAAAAoC18OicXAAAAAIC28Pmc3Ctlt9s9skmUtblJQQGd2n1dAAAAAMB35/M5ubm5uSouLlZjY6Pi4+M1adIkzZs3z2V9T+XkMuACAAAAgO/y6ZzcxsZGHTlyRF26dFF0dLQeeOABtwZciZxcAAAAALgW+XROriTNmDFDw4YNk9Vq1UMPPaS3335bI0aMcFnfMAyNe31pu9/XGxN/0e5rAgAAAADah0/n5AYHBzuPBwUF6Yc//KGqq6s91TIAAAAAwM/5TU7u2bNn9Ze//EVxcXHebBkAAAAA4Ef8IifXZrMpIyND06ZNU8+ePb3ZMgAAAADAj/hFTu7Pf/5z9e7dWw899JAXuwUAAAAA+BuXT3JPnTqlxYsX65fCdGYAACAASURBVJFHHpHU8v3s+Y2i2qqmpkaSLpqT29DQIEkX5OT++te/Vl1dXashGAAAAACAi3H5JPfJJ5+UxWLRunXrJEm9e/fW/PnzNWnSpMte1x45uVVVVVq3bp369u2riRMnSpKmTp3qsrbUMkh7Yidka3MTWbkAAAAA4KNcDrm1tbUaN26c1q9f33JBYKAMw/WnvKtWrbro8enTp19w7MYbb9SOHTsuOB4ZGalPPvnEZS1vcnfAtTbbFBTg1bfBAQAAAOCa53IK69Kli2pra2UymSRJ77//vrp16+Zy4aysLJWVlSksLEzFxcWSpPLyci1dulQNDQ2KiorSypUrFRISIqvVqqVLl+rQoUMymUzKzs7W0KFDJUkzZ87UF198oebmZv3oRz/S0qVLW21KdSktObm5Ls/zlDcmLrpqtQEAAADgWuXykeyTTz6p2bNn67PPPlNqaqoyMzP11FNPuVzYYrEoLy+v1bHs7GwtWLBARUVFGjVqlPPv57/xLSoq0oYNG7RixQrZ7XZJ0urVq/XnP/9ZxcXFqq2t1fbt29t8kwAAAACAa4PLJ7kDBgzQH/7wBx07dkwOh0N9+vRRp06uX9mNiYnRiRMnWh07duyYYmJiJEnDhw/XzJkzlZ6eriNHjmjYsGGSpLCwMHXr1k2HDh3SHXfcoZCQEEktMUJNTU3OJ8oAAAAAAHybyye5b775ps6dO6ebb75Zu3bt0vz58/XRRx9dUbF+/fqptLRUkrR9+3ZVVlZKkm655RaVlpbKZrOpoqJCH330kfNvUssry3fddZe6du2qMWPGXFFtAAAAAEDH53LIXbNmjUJCQvTuu+9q7969Sk5O1rJly66oWE5OjgoKCmSxWFRfX6+goCBJUkpKiiIjI5WSkqLly5dr0KBBrb67ffnll7V3715ZrVb99a9/vaLaAAAAAICOz+XryueHzbfffls//vGPNWrUKP32t7+9omLR0dHKz8+X1PLqcllZWUsTgYGtcnBTU1PVu3fvVtd27txZCQkJKi0t1fDhw6+oPgAAAACgY3M55EZERGjJkiX67//+bz366KOyWq3OTaHaqqamRmFhYbLb7Vq7dq1SU1MlSY2NjXI4HOrSpYv27dungIAA/eAHP1B9fb3q6+sVHh4um82mt99+W0OGDHGrVktO7tXb4ZgIIQAAAADwPpdT2PPPP689e/ZoxowZuu6663Ty5EktWuR6eMzIyNDBgwdVW1ur+Ph4zZs3Tw0NDSooKJAkJSYmKiUlRVLL8Dtz5kwZhqGIiAjl5rZE/zQ2Nmr27NnOwXrYsGHOwdgVq9Xq1nmewoALAAAAAN7n8pvc4OBgjR49Wt26ddO//vUv2Ww29e3b1+XCnTt3VnNzs/r06aPdu3dr0qRJGjp0qLp3766goCAdOXJE9fX1kqTw8HANHjxYgYGBOn36tHNX5u9///vq0qWLrFarAgMD9e677+rLL79068bOf+/b3qzNNo+sCwAAAAD47lw+biwtLdWKFSt08uRJmc1mVVZWqm/fviopKbnsdRaLRVOnTlVmZqbzWHZ2tjIzMxUbG6vCwkLl5eUpPT29VU5uTU2NHn30URUWFsowWmbwlStX6vbbb2/TjRmGoaQtL7TpGneUWNLafU0AAAAAQPtw+SR39erV2rRpk3r37q233npLGzZs0ODBg10uHBMTo9DQ0FbHvp2Tu3PnTkm6ZE4uAAAAAABt4XLIDQwMVI8ePWS3253fxR4+fPiKil1pTu7ixYs1YcIEvfjii3I4HFdUGwAAAADQ8bl8Xfm6665TfX29hgwZoieeeEJms1mBgVe2qVJOTo5ycnK0Zs0aJSQktMrJPXr0qFJSUnTDDTe0yslduXKlIiIiVFdXp7S0NG3btk3JyclXVB8AAAAA0LG5nFbXrFmj733ve1q8eLGKior01Vdfae7cuVdU7EpyciMiIiRJISEhGj9+vD788EOGXAAAAADARbkccrt06aLPP/9c//znPzVx4kQ1Njaqubn5ioq1NSfXZrPp7NmzMpvNampqUllZmeLi4tyqZbfbPbJJFPm3AAAAAOC7XE5rf/rTn7Rp0yZ9+eWX2rVrl6qrq7V06VL97ne/u+x17ZGTa7Va9cgjj6ipqUl2u11xcXGaPHmyWzfmqZxcBlwAAAAA8F0uN57auHGjXn31VYWEhEiSevfurdOnT7tcuD1ycrt06aI//vGPuvPOO2Wz2bR3717t2rXLrRsjJxcAAAAArj0uH0sGBQW1GhhtNveGvPbKyV23bp3MZrN27Nghu92uM2fOuFXfMAwlbX7JrXPboiTlsXZfEwAAAADQPlw+yY2JidG6det07tw57du3Tz/72c+UkJDgcuH2ysndvHmzHnusZbA0DENms7kNtwcAAAAAuJa4HHLPxwb169dPmzZt0ogRI5Senn5Fxdqak3v27FlJ0urVqzVx4kSlpaXp1KlTV1QbAAAAANDxuRxyDcPQ5MmT9cILL+iFF17Q5MmTZTKZrqhYTk6OCgoKZLFYVF9f3yonNzIyUikpKVq+fLkzJ9dms6mqqkqDBw/W66+/rkGDBmnFihVXVBsAAAAA0PFd8pvc+++//7IXFhUVtblYW3Nye/TooeDgYCUmJkqS7rvvPhUWFra5LgAAAADg2nDJIXfdunXtXqytObmSNHLkSB04cEBxcXHav3+/oqOj3aplt9s9skkUObkAAAAA4LsuOa1FRUU5//vzzz/XP//5T9111106d+6cWzsst0dOrtTyTfCiRYu0fPlymc1mPfvss27dGDm5AAAAAHDtcflN7p/+9CelpaVpyZIlkqSqqirNnTvX5cLtkZNbV1enOXPmqK6uToZhqLy8XBs2bHDrxjyVk+su8nQBAAAAwPtcPpbcuHGjXnvtNU2ePFmS1Lt3b50+fdrlwu2RkxsSEqJt27a1WnP06NFu3ZhhGBq/+b/cOtcTilMeumq1AQAAAOBa5fJJblBQUKunou68qiy1X07uecePH1dNTY2GDBniVn0AAAAAwLXH5ZAbExOjdevW6dy5c9q3b59+9rOfKSEh4YqKtTUn95uKi4s1bty4K44vAgAAAAB0fC6H3IULF8psNqtfv37atGmTRowYofT09Csq1tac3G964403lJSUdEV1AQAAAADXhst+k2u32/XAAw+ouLjY+U3ud9HWnNzzysvL1dzcrNtuu+079wAAAAAA6Lgu+yTXMAz1799f//rXv9qlWE1NjSRdNCe3oaFBki7IyZVaXlXmKS4AAAAAwBWXuyt/8cUXSkpK0h133KHg4GDn8XXr1l32uvbKyZWkN998U+vXr2/Tjdnt9qu6w7G12UamLgAAAAB4mcsp7PHHH7+ihVetWnXR49OnT7/g2I033qgdO3Zccq3zm1X5E08NuNbmZgV963tlAAAAAEALl5NYbGzsFS2clZWlsrIyhYWFqbi4WFLLt7VLly5VQ0ODoqKitHLlSoWEhMhqtWrp0qU6dOiQTCaTsrOzNXToUEktryq/9NJLkqTw8HA999xzMpvNLusbhqHxhRuvqHdfVvzglKvdAgAAAAD4LJe7K18pi8WivLy8Vseys7O1YMECFRUVadSoUc6/v/baa5KkoqIibdiwQStWrJDdbpfNZlNOTo5+97vfqaioSP3799fGjR1vcAUAAAAAtA+PDbkxMTEKDQ1tdezYsWOKiYmRJA0fPlw7d+6UJB05ckTDhg2TJIWFhalbt246dOiQHA6HHA6HGhsb5XA4VFdXp/DwcE+1DAAAAADwc5cccs9/O/vcc8+1W7F+/fo5v6/dvn27KisrJUm33HKLSktLZbPZVFFRoY8++kiVlZXq1KmTli1bpvvvv1/33HOPjh49qgcffLDd+gEAAAAAdCyXHHK/+OILHTx4UG+99ZY+/vhjffTRR63+dyVycnJUUFAgi8Wi+vp6BQUFSZJSUlIUGRmplJQULV++XIMGDVJAQICampr06quvauvWrdqzZ4/69+/v/D4XAAAAAIBvu+TGU2lpaVq/fr2qqqr07LPPtvqbyWTSK6+80uZi0dHRys/Pl9Ty6nJZWVlLE4GBWrx4sfO81NRU9e7dW4cPH5Yk3XTTTZKksWPHtjlKCAAAAABw7bjkkHvffffpvvvu04svvqi5c+e2S7GamhqFhYXJbrdr7dq1Sk1NlSTnN7ddunTRvn37FBAQoB/84Aeqrq7W0aNHdfr0aZnNZu3bt0/R0dFu1bLb7R1yJ2IihAAAAADg0lxGCM2dO1elpaV69913JbVECo0cOdLlwhkZGTp48KBqa2sVHx+vefPmqaGhQQUFBZKkxMREpaSkSGoZfmfOnCnDMBQREaHc3FxJUkREhObOnaspU6YoMDBQUVFRFzxVvhSr1erWef6GARcAAAAALs3l7sq/+tWv9Morryg6OlrR0dF65ZVX9Ktf/crlwp07d1Zzc7P69Omj3bt3a9KkSRo6dKi6d++uoKAgHTlyRPX19ZJa8m8HDx6swMBAnT59WidOnHCuExoaqsDAQNntdvXt21c9evRw68bOf+/b3qzNzR5ZFwAAAADw3bl8kltWVqZt27bJMFrm4YkTJyo5OVkLFiy47HUWi0VTp05VZmam81h2drYyMzMVGxurwsJC5eXlKT09vVVObk1NjR599FEVFhbqyy+/VG5urrZs2SKz2azMzEzt379fcXFxLm/MMAyNL3zN5XltVfzgpHZfEwAAAADQPtzKyT179qzzv7/66iu3Fm6PnNyKigr17t1bZrNZkhQXF6cdO3a4VR8AAAAAcO1x+ST3scce08SJEzV06FA5HA698847Lp/iXsr5nNxRo0ZdNCc3KSlJlZWVzpzcYcOG6dNPP9WJEycUGRmp0tJSNTU1XVFtAAAAAEDH53LIHT9+vGJjY/X3v/9dDodDTzzxhP7t3/7tiorl5OQoJydHa9asUUJCQquc3KNHjyolJUU33HCDMyc3NDRUy5Yt0/z582UYhgYNGqSKioorqg0AAAAA6PhcDrlSy8ZQ995773cu1tacXElKSEhQQkKCJGnTpk3Ob4MBAAAAAPg2t4bc9tLWnNxvXvPll1+qoKBAzz//vFu1WnJy23+TKHJqAQAAAMB3eWzIbY+cXKnlFefy8nJJLZm9ffr0cau+p3JyGXABAAAAwHdd9t1fu92u8ePHX9HCCxcuVJ8+fXTTTTepW7duamho0PTp07Vp0ybdcMMN2rlzp2bMmKEvv/xSN954o3bs2KHk5GR9/vnnmjFjhvbs2SNJWrVqlXJzcxUQEKDnn39ev/zlL+VwOFzW91ROrrvI0wUAAAAA77vsk1zDMNS/f3/961//0g033NCmhQMCAvTkk09qwIABqqurU0pKioYPH64tW7YoLi5Os2bN0vr167V+/XotXLhQR44cUUlJiUpKSlRdXa2HH35YO3bsUEBAgJYtW6ann35ad955px599FHt3r1bI0aMuGx9wzB0f+G2NvXcnooenHDVagMAAADAtcrl68pffPGFkpKSdMcddyg4ONh5fN26dZe9Ljw8XOHh4ZKkkJAQ9e3bV9XV1SotLdXvf/97SVJycrKmTZumhQsXOiOEgoKC1LNnT/Xq1UsffvihoqKiVFdXp0GDBjmvKS0tdTnkAgAAAACuPS6H3Mcff/w7Fzlx4oQOHz6sgQMHqqamxjn8hoeH6/Tp05Kk6upqDRw40HlNRESEqqurFRgYqMjISOfxyMhIVVdXf+eeAAAAAAAdj8shNzY29jsVqK+vV1pamhYvXqyQkJBLnnex72xNJtMljwMAAAAA8G0uh9z3339fzzzzjD799FM1NTWpublZwcHB+tvf/uZy8aamJqWlpen+++/X6NGjJUlhYWE6efKkwsPDdfLkSZnNZkktT2irqqqc11ZXVys8PPyC41VVVc4nwQAAAAAAfNNld1eWpKefflqrVq1Sr1699MEHH+iXv/ylpk6d6nJhh8Oh7Oxs9e3bVw8//LDzeEJCgrZu3SpJ2rp1q+69917n8ZKSElmtVlVUVOj48eO64447FB4erq5du+r999+Xw+FodQ0AAAAAAN/kVk5ur1691NzcrICAAKWkpCg1NdXlNe+99562bdumfv36acKElp2GMzIyNGvWLKWnp6uwsFDXX3+9Vq9eLUm6+eabNXbsWI0bN04BAQFasmSJAv4vk3bZsmXKysrSuXPnFB8fr/j4eJf17Xb7Vd3h2NrcTKYuAAAAAHiZyyE3ODhYVqtVt956q3JzcxUeHq6GhgaXC0dFRSk2NlanTp2SYRiaPHmyRowYoTNnzsgwWh4gG4bR6vvab/77/DmStGvXLn311Vc6e/aslixZ0uabdMUTAykDLgAAAAB4n8shNzc3Vw6HQ0uWLNF//dd/qbKyUr/5zW9cLtyeObkjR47UlClTNGbMGLdvzDAMTSjc7ta52x68z+11AQAAAAC+y+U3uVFRUXI4HDp58qQef/xxZWVlqVevXi4XDg8P14ABAyRdmJObnJwsqSXzdteuXZJ0yZxcSbrzzjvZbAoAAAAA4JLLIfett97ShAkT9Mgjj0iSDh8+rJ/+9KdtKuJuTu4383DP5+QCAAAAAOAul0Pub3/7WxUWFuq6666TJN166636/PPP3S7wXXNyAQAAAABwl8shNyAgQN26dbuixS+XkyvJrZxcAAAAAADcdckh99FHH1VFRYVuvvlmFRUVqbm5WcePH9czzzyjQYMGuVy4vXJyAQAAAABw1yV3V544caIeeeQRPfDAA/rHP/6hoKAgLViwQHfffbfmzp3rcuH2zMnNzc1VcXGxGhsbFR8fr0mTJmnevHmXrW+3293eNZlMWwAAAADoGEyOi30M+38aGhr04osvas+ePZowYYLzG1mTydTq6awv+uijjzVgwA/bfV0GYs85fPiwbr311qvdBtqA38z/8Jv5H34z/8Nv5n/4zfwPv5n/8cRvdqk1L5uTGxgYqODgYFmtVjU0NLRpI6jKykotWrRIp06dkmEYmjx5sqZPn64zZ85o/vz5+vzzzxUVFaXnn39eoaGhkqSXXnpJhYWFMgxDTz31lO655x41NjbqZz/7mT777DNnZu4TTzzhsr5hmJS8+S9u9+uurSkj231NAAAAAED7uOSQu3v3bv3Hf/yHEhIS9Prrrys4OLhNCwcEBOjJJ5/UgAEDVFdXp5SUFA0fPlxbtmxRXFycZs2apfXr12v9+vVauHChjhw5opKSEpWUlKi6uloPP/ywduzYIUmaMWOGhg0bJqvVqoceekhvv/22RowY8d3uHAAAAADQ4Vxy46l169Zp9erVeuKJJ9o84EotGbgDBgyQJIWEhKhv376qrq5WaWmpkpOTJUnJycnatWuXJKm0tFRJSUkKCgpSz5491atXL3344YcKDg7WsGHDJElBQUH64Q9/SH4uAAAAAOCiLjnkFhQU6Oabb26XIidOnNDhw4c1cOBA1dTUOKOBwsPDdfr0aUktkUGRkZHOayIiIi4YZs+ePau//OUviouLa5e+AAAAAAAdi8uc3O+qvr5eaWlpWrx4sUJCQi553sX2v/rmN8A2m00ZGRmaNm2aevbs6ZFeAQAAAAD+zaNDblNTk9LS0nT//fdr9OjRkqSwsDCdPHlSknTy5EmZzWZJUmRkpKqqqpzXVldXO5/4StLPf/5z9e7dWw899JAnWwYAAAAA+LHL7q78XTgcDmVnZ6tv376t4oYSEhK0detWzZo1S1u3btW9997rPL5gwQI9/PDDqq6u1vHjx3XHHXdIkn7961+rrq5OOTk5bte32x0e2QmZCCEAAAAA8F0eG3Lfe+89bdu2Tf369dOECRMkSRkZGZo1a5bS09NVWFio66+/XqtXr5Yk3XzzzRo7dqzGjRungIAALVmyRAEBAaqqqtK6devUt29fTZw4UZI0depUTZo06bL1rdavPXJfDLgAAAAA4Ls89rpyVFSUYmNjZbPZZLPZZLFYNGLECJlMJhlGS1nDMFp9d/vNf58/JzIyUnfffbc6deokm82mgQMHymKxuKwfFNTZA3d19Vmb7Ve7BQAAAADwWR57ktteObkBAQFavXq1QkJC5HA4lJaWpu3btyspKemy9Q3DJMvm/Z66vatmSwo7SwMAAADApXjsSW575eSev15q2WG5qamp1dNfAAAAAADO83iEkNQ+ObkzZ87UXXfdpa5du2rMmDHeaBsAAAAA4Gf8Jif35Zdf1t69e2W1WvXXv/7VI70CAAAAAPyb3+TkSlLnzp2VkJCg0tJST7YNAAAAAPBTPp+TW19fr/r6eoWHh8tms+ntt9/WkCFDXNa32x0dcpMma7NdQQFeecscAAAAAPyOz+fkNjY2avbs2bJarbLb7Ro2bJhSU1Nd1vdUTu7VxoALAAAAAJfm8zm53//+97V582YVFRWpZ8+eOnDggAIDXc/mVzsnlzxbAAAAAPA+v8jJlaSdO3eqa9eubtc3DJMe3PyBp27PpcKUgVetNgAAAABcq/wiJ7e+vl4bNmzQ7NmzPdUuAAAAAKAD8Iuc3NWrV2vGjBn63ve+5412AQAAAAB+yudzcg8fPqzPPvtMiYmJnmwTAAAAANAB+HxO7v/8z//o0KFDSkhI0E9+8hMdP35c06ZN82TbAAAAAAA/5bEh11VOrqQLcnJLSkpktVpVUVHhzMn9yU9+or179+qtt95SQUGBevfurd///veeahsAAAAA4Md8Pif3Stntjqu6w7G12U6mLQAAAAB4mceG3CFDhuiTTz656N9+97vfXfT47NmzL7uD8o033qji4uJ26c/TOvKAywAPAAAAwFd5bMitrKzUokWLdOrUKRmGocmTJ2v69Ok6c+aM5s+fr88//1xRUVF6/vnnFRoaKkl66aWXVFhYKMMw9NRTT+mee+6RJE2bNk0nT5507q6cn5+vsLCwy9Y3DJP+vy2feur2rmmbLH2vdgsAAAAAcFEeG3IDAgL05JNPasCAAaqrq1NKSoqGDx+uLVu2KC4uTrNmzdL69eu1fv16LVy4UEeOHFFJSYlKSkpUXV2thx9+WDt27HC+srxy5UrdfvvtnmoXAAAAANABeOyd0/DwcA0YMECSFBISor59+6q6ulqlpaVKTk6WJCUnJ2vXrl2SpNLSUiUlJSkoKEg9e/ZUr1699OGHH3qqPQAAAABAB+SVDytPnDihw4cPa+DAgaqpqVF4eLiklkH49OnTkloigyIjI53XREREqLq62vnvxYsXa8KECXrxxRcvmqkLAAAAAIDHh9z6+nqlpaVp8eLFCgkJueR5FxtcTSaTpJZXlYuKirRx40bnrs0AAAAAAHybR4fcpqYmpaWl6f7779fo0aMlSWFhYTp58qQk6eTJkzKbzZKkyMhIVVVVOa+trq52PvGNiIiQ1PLa8/jx43mNGQAAAABwUR7beMrhcCg7O1t9+/bVww8/7DyekJCgrVu3atasWdq6davuvfde5/EFCxbo4YcfVnV1tY4fP6477rhDNptNZ8+eldlsVlNTk8rKyhQXF+eyvt3uYBdgDyFCCAAAAICv8tiQe/614n79+mnChAmSpIyMDM2aNUvp6ekqLCzU9ddfr9WrV0uSbr75Zo0dO1bjxo1TQECAlixZooCAADU0NOiRRx5RU1OT7Ha74uLiNHnyZJf1rdavPXVr1zwGXAAAAAC+ymPTSlRUlGJjY2Wz2WSz2WSxWDRixAiZ/l979x8dVX3nf/w1E0gkZAtOdBKaRTQEuhhroGZdRiqpoSCKkSRKziqbTZE1FpGBREkDsZT1LFA5dkv2+22VqaWiRyynGCY1EeGbUAkisC2LZSnBEvlyNrBkIiGRTQxkJjPfP7LMgvxI/MpN7h2ej7/MzeR+3ve8Dfrm3vt52Wyy23uWtdvt4fduv/j1+c/Exsbq17/+tcaPH69AIKAPPvggvCPz1URHxxhwVQPP382mWwAAAABwJZbIyX3llVfkcDi0detWBYNBtbW19bq+3W7Tks0njLq8AbMqJ2mgSwAAAAAA07JETu7bb7+tp556qqdguz28WRUAAAAAABcyfU7umTNnJEnl5eXKycmR2+3WqVOn+qNsAAAAAIDFmD4nNxAIqKmpSd/61re0efNmTZgwQS+++KKRJQMAAAAALMr0Obk33nijhgwZoqlTp0qSpk+frkOHDhlZNgAAAADAokyfk2uz2XTfffdp7969crlc2r17t0aPHt3r+sFgKCI3afJ3hzQ4ytb7BwEAAADgOmT6nFxJeu6551RSUqKVK1fK4XBo1apVva4fqTm5DLgAAAAAcGWmz8ltb2/X008/rfb2dtntdh0+fFi/+tWvel0/UnNyI9ltySkDXQIAAAAAizN9Tm5cXJwqKyvD583NzQ2/33s1drtN5Zubev0czGNhTmLvHwIAAACAq7BETu55x44dU0tLi9LT040qGwAAAABgYabPyb1QVVWVHnzwwYsecQYAAAAA4DzT5+Re6N1339WMGTOueY0AAAAAgMhg+pzc8w4fPqzu7m7dcccdRpYMAAAAALAw0+fknldVVfWl7uIGgyE2MrKYs+f8uiFm8ECXAQAAAMDCLJGTK0lbtmyRx+Pp8/qRmpMbyf7v0QaNGzduoMsAAAAAYGGmz8mVeu7ixsbGatGiRZo7d254s6qrISf3y+nuvvSdaAAAAACwGtPn5IZCIa1YsULV1dVyOBxavXq13nzzTS1YsOCq69vtNr1R8alRlxdx8nNvHugSAAAAAOArM31ObigUUigUUmdnp0KhkNrb2y/akAoAAAAAgPNMn5M7ePBgLV++XFlZWbr33nv1ySef6NFHH+2PsgEAAAAAFmP6nFy/36+33npLXq9XO3fu1De+8Q2tXbvWyJIBAAAAABZl+pzc+vp6SdItt9wim82mBx54QPv37zeybAAAAACARRk25PaWkyvpkpzc6upqdXV1qbGxMZyTFvIzaAAAHltJREFUm5CQoE8++ST8WPOuXbs0evRoo8oGAAAAAFiY6XNyExISNH/+fM2ePVuDBg1SUlKSVq1a1ev6wWCIHYO/hO7ukKKibL1/EAAAAABMzLAhNz09XR9//PFlv7d+/frLHp83b57mzZt3yfHHHntMjz322DWtDwAAAAAQeQwbck+ePKmSkhKdOnVKdrtdeXl5KigoUFtbm4qKinTixAklJSVpzZo1GjZsmCRp7dq12rRpk+x2u55//nnde++9kqR3331XL7/8soLBoDIyMlRSUtLr+na7TZW/OWXU5UWcmbNuGugSAAAAAOArM+yd3KioKJWWlmrLli3auHGjNmzYoIaGBnk8HrlcLm3btk0ul0sej0eS1NDQoOrqalVXV+vVV1/VP/7jP6q7u1utra1avXq11q9fr+rqarW0tGj37t1GlQ0AAAAAsDDDhlyn06nU1FRJUlxcnJKTk+Xz+VRbW6vs7GxJUnZ2tmpqaiRJtbW1mjFjhqKjozVy5EiNGjVKBw4cUGNjo2699dbwLswul0tbt241qmwAAAAAgIUZnpMrScePH1d9fb3S0tLU0tIip9MpqWcQPr9rss/nU2JiYvhnEhIS5PP5NGrUKB09elTHjx9XIBBQbW3tRVFDAAAAAACcZ9g7ued1dHTI7XZr6dKliouLu+LnQqHQJcdsNpuGDRum5cuXq6ioSHa7XRMmTFBjY6ORJQMAAAAALMrQIdfv98vtdisrK0vTpk2TJMXHx6u5uVlOp1PNzc3hx5ATExMvukPr8/nCd3wzMzOVmZkpSdq4caPs9n65AQ0AAAAAsBjDhtxQKKSysjIlJydrzpw54eOZmZnyer0qLCyU1+vVlClTwsefffZZzZkzRz6fT8eOHdOdd94pSWppaVF8fLw+++wzbdiwQWvWrOl1/WAwxI7BXwI5uQAAAAAigWFD7r59+1RZWamxY8dq5syZkqTi4mIVFhZq0aJF2rRpk0aMGKHy8nJJ0pgxY/TAAw/owQcfVFRUlJYtW6aoqChJ0ooVK3T48GFJ0vz583Xbbbf1un5X1zmDriwyMeACAAAAiASGPfeblJSku+++W4FAQIFAQLm5ucrIyJDNZgs/bmy322Wz9QxXra2t+vDDD9XS0qJJkyYpIyMjfK4nnnhCUVFR8vv92r9//2Xf3/2imOgYYy4Mhhk3bpwh5+3u7v3fFwAAAACRwbA7uedzclNTU9Xe3q5HHnlEkyZNUkVFhVwulwoLC+XxeOTxeLR48WLFxMRo4cKFOnLkiI4cOXLRuZYvX64XXnhB48eP15NPPqm6urqLhuDLsdltqtnwqVGXBwv57uM3D3QJAAAAAPqJaXJyY2NjlZ6erpiYi+/ANjc3q729XRMmTJDNZlN2drZqa2uNKhsAAAAAYGGmycm9ki/m5yYmJsrn8xlaLwAAAADAmgwfcvuak3slV8rPBQAAAADgiwwdcq+WkyvpopzcK/lifm5TU1P4TjAAAAAAABcyTU7ulTidTg0dOlQfffSR0tLS5PV6lZ+f3/v6wRAbDkESGcAAAADA9cQ0OblSzwDc3t4uv9+vmpoarVu3TikpKVq+fLmWLFmis2fPavLkyZo8eXKv658jJ9dy6uvrDYkRYsAFAAAArh+myslNSkqS3+9XTk6O6urqlJKSIkmqqanRf/3Xf6mlpUXLli3r0zu55ORaj1E5uUFycgEAAIDrhiVycu+77z7Nnj1b999/f5/Xt9lt2r2enFxIrgIeWwcAAACuF6bPyZWk8ePHs9kUAAAAAKBXps/JBQAAAACgr0yfkwsAAAAAQF+ZPicXAAAAAIC+MmzI7S0nV1KfcnIBAAAAAOgrS+Tkrl69WlVVVers7NTkyZM1a9YsLViw4Krrh4IhdtWFpJ4IITtZuQAAAMB1wfQ5uZ2dnWpoaFBsbKxGjx6thx9+uNcBF7iQEQNuMED2LgAAAGBGlsjJfeKJJzRx4kR1dXXpe9/7nnbs2KGMjIyrrm+z2/THXzQbdXm4zqU9SaQVAAAAYEamz8kdMmSIJk6cKEmKjo7W7bffLp/PZ1TZAAAAAAALs1RO7pkzZ/S73/1OLpfLqFIBAAAAABZmmZzcQCCg4uJi5efna+TIkdewQgAAAABApLBMTu4Pf/hD3Xrrrfre975nVLkAAAAAAIuzRE7uT3/6U7W3t2vp0qVGlQsAAAAAiACmz8mNi4vTK6+8ouTkZOXk5EiS/u7v/k6zZs266vqhYIgdcGGYYCAk+yCydwEAAACzMWzITU9P18cff3zZ761fv/6yx7dv337Z41c6DwAAAAAAFzJsyD158qRKSkp06tQp2e125eXlqaCgQG1tbSoqKtKJEyeUlJSkNWvWaNiwYWptbZXb7dbBgweVk5OjZcuWhc81d+5cffrpp+ru7tZdd92lH/3oR4qKirrq+ja7TQ3/i6ghGCNlQcJAlwAAAADgMgx7JzcqKkqlpaXasmWLNm7cqA0bNqihoUEej0cul0vbtm2Ty+WSx+ORJMXExGjhwoUqKSm55Fzl5eX67W9/q6qqKrW2tuq9994zqmwAAAAAgIUZNuQ6nU6lpqZKkuLi4pScnCyfz6fa2lplZ2dLkrKzs1VTUyNJio2NVXp6umJiYi451/nooUAgIL/fL5uNdyEBAAAAAJcyPCdXko4fP676+nqlpaWppaVFTmfPhlBOp1OnT5/u0znmzp2re+65R0OHDtX9999vZLkAAAAAAIsyfMjt6OiQ2+3W0qVLw3dk/3/88pe/1AcffKCuri7t2bPnGlYIAAAAAIgUhg65fr9fbrdbWVlZmjZtmiQpPj5ezc3NkqTm5mY5HI4+ny8mJkaZmZmqra01pF4AAAAAgLUZtrtyKBRSWVmZkpOTNWfOnPDxzMxMeb1eFRYWyuv1asqUKVc9T0dHhzo6OuR0OhUIBLRjxw6lp6f3vn4wxA64MAw5uQAAAIA5GTbk7tu3T5WVlRo7dqxmzpwpSSouLlZhYaEWLVqkTZs2acSIESovLw//TGZmptrb2+X3+1VTU6N169Zp+PDhmjdvnrq6uhQMBjVx4kT97d/+ba/rn+s6Z9SlwSD19fUaN27cQJfRJwy4AAAAgDkZ9rhyUlKS7r77bgUCAQUCAeXm5iojI0M2m012e8+ydrs9vFNya2urkpKS5Pf7lZOTo7q6OqWkpOimm27S22+/rXfeeUcjR47U3r17NWhQ77N5TPSluzTD3Kwy4OJ/0DMpFAgNdAkAAAC4gGF3cs/n5Kampqq9vV2PPPKIJk2apIqKCrlcLhUWFsrj8cjj8Wjx4sXhnNwjR47oyJEjl5xv27ZtGjp0aJ/Xt9ltOvniyWt5SQBwiRE/GDHQJQAAAOAClsjJ7ejo0K9+9SvNmzfPqHIBAAAAABHAEjm55eXleuKJJ3TDDTcYXSoAAAAAwMJMn5NbX1+v//iP/9DUqVMNqA4AAAAAEElMn5O7f/9+HTx4UJmZmXr88cd17Ngx5efnG1k2AAAAAMCiTJ+T+/jjj+vxxx+X1PPY8/e//3298cYbva8fDLEhDADDhQIh2YiUAgAAMA3T5+SmpKT8f61PTq71WCknFz3omRhwAQAATMawIfd8Tu6pU6dkt9uVl5enjIwMtbW1XTUn9+DBg8rJydGyZcvC58rPz1dzc7NuuOEGRUVFqaWlRfHx8Vddn5xc67nehyUromfWQ8+MEwoEZRvUL/s5AgCAq7BMTu5LL72kb37zm31e32a3qeknl54HAAAjJD47ZqBLAAAAskhOLgAAAAAAfWHYndwLfdWcXElaunSp7Ha7pk2bpqeffjr8mDMAAAAAAOeZPidX6nlU+Z133tGbb74Z3tAKAAAAAIAvMn1OriQlJCRI6nns+aGHHtKBAweMKxoAAAAAYFmGDbm95eRK6lNObiAQCD/S7Pf79f7772vMGDb3AAAAAABcyvQ5uV//+tf1D//wD/L7/QoGg3K5XMrLy+t1/VAwxE6XAIB+Q4QQAADmYNh/jc/n5AYCAQUCAeXm5iojI0M2m+2qObl+v185OTmqq6tTSkqKYmNj9etf/1rjx49XIBDQBx98EN6RGQAAszBqwCXb2BxCgeBAlwAA6CNL5OS+8sorcjgc2rp1q4LBoNra2npd32a3yffTPxp1eQAA4DqSUJQ20CUAAPrIEjm5b7/9tp566qmegu32Pm1WBQAAAAC4/vTLy0NfJSf3zJkzkqTy8nLl5OTI7Xbr1KlThtcMAAAAALAe0+fkBgIBNTU16Vvf+pY2b96sCRMm6MUXXzSgUgAAAACA1Zk+J/fGG2/UkCFDNHXqVEnS9OnTdejQISPLBgAAAABYlOlzcm02m+677z7t3btXkrR7926NHj3aqLIBAAAAABZm+pzclJQUPffccyopKdHKlSvlcDi0atWqXtcPBUPshAgAAK4JcpABwDoMG3LT09P18ccfX/Z769evv+zx7du3X/Z4UlKS3nzzzS+1/rmuc1/q8xh49fX15EFaDD2zHnpmPfTMHBhwAcA6DBtyT548qZKSEp06dUp2u115eXkqKChQW1ubioqKdOLECSUlJWnNmjUaNmyYWltb5Xa7dfDgQeXk5GjZsmWSpPb2ds2ePTt83qamJj388MMqKyu76vox0ZdGEcHc+J8466Fn1kPPrIeeWQ89Mw531AH0hWFDblRUlEpLS5Wamqr29nY98sgjmjRpkioqKuRyuVRYWCiPxyOPx6PFixcrJiZGCxcu1JEjR3TkyJHweeLi4lRZWRn+Ojc3N7yJ1dXY7Db5yvcYcm0AAADofwkLJw50CQAswLC/CnM6nUpNTZXUM6gmJyfL5/OptrZW2dnZkqTs7GzV1NRIkmJjY5Wenq6YmCvfgT127JhaWlqUnp5uVNkAAAAAAAvrl+c9jh8/rvr6eqWlpamlpUVOp1NSzyB8+vTpPp+nqqpKDz74oGw2m1GlAgAAAAAszPAht6OjQ263W0uXLlVcXNxXOte7776rGTNmXKPKAAAAAACRxtAh1+/3y+12KysrK/webXx8vJqbmyVJzc3NcjgcfTrX4cOH1d3drTvuuMOwegEAAAAA1mbYxlOhUEhlZWVKTk7WnDlzwsczMzPl9XpVWFgor9erKVOm9Ol8VVVVX+oubigYYnMCAACACMLuygD6wrA/Jfbt26fKykrt2bNHM2fO1MyZM7Vjxw4VFhZq165dmjZtmnbt2qXCwsLwz2RmZurHP/6xNm/erMmTJ6uhoSH8vS1btnypIZecXOupr68f6BLwJdEz66Fn1kPPrIeeGYcBF0BfGPYnRVJSku6++24FAgEFAgHl5uYqIyNDNptNdnvPsna7PbyJVGtrq5KSkuT3+5WTk6O6ujqlpKRI6rmLGxsbq0WLFmnu3Ll92qyKnFzrIVfQeuiZ9dAz66Fn1kPPrIeeWQ89M04o0D3QJXxltlAoFDLixM3Nzfr0008vysn92c9+poqKCg0fPjyck/vZZ59p8eLF+vzzz3Xo0KFwTu6yZcskSYFAQPfee6+qq6vlcDi0evVqDRkyRAsWLLjq+vX19XL8H58RlwYAAAAAESnB/R1DzltfX3/N/3LiSuc0fU5uKBRSKBRSZ2enQqGQ2tvbwxFEAAAAAABcyLCNpy70VXJyBw8erOXLlysrK0uxsbEaNWqUfvSjH/VH2QAAAAAAizF9Tq7f79dbb70lr9ernTt36hvf+IbWrl1rQKUAAAAAAKszfU7u+R0Kb7nlFtlsNj3wwAPav3+/kWUDAAAAACzK9Dm5CQkJ+uSTT3T69Gk5HA7t2rVLo0eP7n39YMiwl6YBAAAAIBKFAt2yDYoa6DK+EtPn5CYkJGj+/PmaPXu2srKydPjwYT311FO9rk9OrvWQK2g99Mx66Jn10DProWfWQ8+sh54Zx+oDrmSRnNxhw4Zp0KBBCgaDSk5O1o033tjr+jHR0UZdGgxC3pn10DProWfWQ8+sh55ZT8ptyQNdAoBryLDHlaOiolRaWnpRTu6kSZNUUVEhl8sVzsn1eDxavHixYmJitHDhwnBO7nmtra1avXq1Kioq5HA49IMf/EC7d++Wy+W66vo2u13N/3uLUZcHAACACOF85oGBLgHANWT6nNzGxkbdeuut4Q2qXC6Xtm7dalTZAAAAAAALMzxCSPpqObmjRo3S0aNHdfz4cQUCAdXW1qqpqak/ygYAAAAAWIxhjyuf91VzcocNG6bly5erqKhIdrtdEyZMUGNjowGVAgAAAACsztAh92o5uU6ns085uVLPrsuZmZmSpI0bN4Y3rgIAAAAA4EKGTYu95eRK6lNOriS1tLRIkj777DNt2LBBs2bNMqZoAAAAAIClGXYn93xO7tixYzVz5kxJUnFxsQoLC7Vo0SJt2rRJI0aMUHl5efhnMjMz1d7eLr/fr5qaGq1bt04pKSlasWKFDh8+LEmaP3++brvttl7XDwWD7JQHAACAXvnPntPgG2J6/yAAS7CFQqHQQBdhhEN/+pNu/+/dnQEAMFoo0C3boKhrft76+npyVy2GnlkPPbMeemY9RvTsSuc07E7uyZMnVVJSolOnTslutysvL08FBQVqa2tTUVGRTpw4oaSkJK1Zs0bDhg3Trl279JOf/ER+v1+DBw/W4sWLw1m4Bw8e1JIlS3T27FllZGSorKxMNpvtquvb7HY1/2yzUZcHAMBFnPNzBroEAAAgA9/JjYqKUmlpqbZs2aKNGzdqw4YNamhokMfjkcvl0rZt2+RyueTxeCRJN954o15++WW98847+vGPf6ySkpLwuZYvX64XXnhB27Zt07Fjx1RXV2dU2QAAAAAACzNsyHU6nUr978eF4+LilJycLJ/Pp9raWmVnZ0uSsrOzVVNTI0m6/fbblZCQIEkaM2aMurq61NXVpebmZrW3t2vChAmy2WzKzs5WbW2tUWUDAAAAACysX7J4jh8/rvr6eqWlpamlpUVOp1NSzyB8+vTpSz6/detWjRs3TtHR0fL5fEpMTAx/LzExUT6frz/KBgAAAABYjKE5uZLU0dEht9utpUuXKi4urtfPHzlyRC+99JLWrVsnqSeK6It6ex8XAAAAAHB9MvROrt/vl9vtVlZWlqZNmyZJio+PV3NzsySpublZDocj/PmmpiY988wzevHFF3XLLbdI6rlz29TUdNFnzt8JBgAAAADgQobdyQ2FQiorK1NycrLmzJkTPp6ZmSmv16vCwkJ5vV5NmTJFknTmzBkVFhaquLhYd911V/jzTqdTQ4cO1UcffaS0tDR5vV7l5+f3vn4wyE6XAIB+Y1SEEAAA+HIMy8n9wx/+oNmzZ2vs2LGy23tuGBcXF+vOO+/UokWLdPLkSY0YMULl5eUaPny4fv7zn8vj8WjUqFHhc6xbt07x8fH693//93CE0OTJk/XDH/6w10eWP/roI8XEEOoNAAAAAJHo3LlzGj9+/CXHDRtyAQAAAADob/2yuzIAAAAAAP2BIRcAAAAAEDEYcgEAAAAAEYMhFwAAAAAQMRhyAQAAAAARgyEXAAAAABAxBg10AddaXV2dVqxYoWAwqFmzZqmwsHCgS8IXLFmyRO+//77i4+NVVVUlSWpra1NRUZFOnDihpKQkrVmzRsOGDRvgSnHeyZMnVVJSolOnTslutysvL08FBQX0zcTOnTun2bNnq6urS93d3br//vvldrvpmQV0d3frkUceUUJCgtauXUvPTC4zM1NDhw6V3W5XVFSUKioq6JnJnTlzRs8//7z+/Oc/y2azaeXKlbrtttvomUkdPXpURUVF4a8bGxvldruVnZ1Nz0zstdde029+8xvZbDaNHTtWq1atUmdnZ7/1LKLu5HZ3d+uFF17Qq6++qurqalVVVamhoWGgy8IX5Obm6tVXX73omMfjkcvl0rZt2+RyueTxeAaoOlxOVFSUSktLtWXLFm3cuFEbNmxQQ0MDfTOx6OhorV+/Xr/97W/l9Xq1c+dOffTRR/TMAl5//XWNHj06/DU9M7/169ersrJSFRUVkuiZ2a1YsUL33nuv3nvvPVVWVmr06NH0zMSSk5NVWVkZ/h0bMmSIpk6dSs9MzOfz6fXXX9fbb7+tqqoqdXd3q7q6ul97FlFD7oEDBzRq1CiNHDlS0dHRmjFjhmprawe6LHzBX//1X1/ytza1tbXKzs6WJGVnZ6umpmYgSsMVOJ1OpaamSpLi4uKUnJwsn89H30zMZrNp6NChkqRAIKBAICCbzUbPTK6pqUnvv/++Hn300fAxemY99My82tvb9fvf/z78OxYdHa2vfe1r9Mwidu/erZEjRyopKYmemVx3d7fOnj2rQCCgs2fPyul09mvPImrI9fl8SkxMDH+dkJAgn883gBWhr1paWuR0OiX1DFSnT58e4IpwJcePH1d9fb3S0tLom8l1d3dr5syZuueee3TPPffQMwtYuXKlFi9eLLv9f/7zTM/Mb+7cucrNzdXGjRsl0TMza2xslMPh0JIlS5Sdna2ysjJ9/vnn9Mwiqqur9dBDD0ni98zMEhIS9MQTT+i+++7Tt7/9bcXFxenb3/52v/YsoobcUCh0yTGbzTYAlQCRqaOjQ263W0uXLlVcXNxAl4NeREVFqbKyUjt27NCBAwf05z//eaBLwlX87ne/k8Ph0B133DHQpeBLeOutt7R582b94he/0Jtvvqnf//73A10SriIQCOjQoUN67LHH5PV6NWTIEB5ztYiuri5t375d06dPH+hS0IvPPvtMtbW1qq2t1c6dO9XZ2anKysp+rSGihtzExEQ1NTWFv/b5fOG/LYC5xcfHq7m5WZLU3Nwsh8MxwBXhi/x+v9xut7KysjRt2jRJ9M0qvva1r+lv/uZvtHPnTnpmYv/2b/+m7du3KzMzU8XFxdqzZ4+ee+45emZyCQkJknr+PJw6daoOHDhAz0wsMTFRiYmJSktLkyRNnz5dhw4domcWUFdXp9TUVN10002S+H8QM/vwww/1l3/5l3I4HBo8eLCmTZum/fv392vPImrI/eY3v6ljx46psbFRXV1dqq6uVmZm5kCXhT7IzMyU1+uVJHm9Xk2ZMmWAK8KFQqGQysrKlJycrDlz5oSP0zfzOn36tM6cOSNJOnv2rD788EMlJyfTMxN79tlnVVdXp+3bt+uf//mfNXHiRL300kv0zMQ+//xztbe3h/95165dGjNmDD0zsZtvvlmJiYk6evSopJ53PEePHk3PLKC6ulozZswIf03PzOvrX/+6/vjHP6qzs1OhUGhAfs9socs942thO3bs0MqVK8MRDPPmzRvokvAFxcXF+td//Ve1trYqPj5eCxYs0He/+10tWrRIJ0+e1IgRI1ReXq7hw4cPdKn4b3/4wx80e/ZsjR07NvyuYHFxse688076ZlKHDx9WaWmpuru7FQqFNH36dD3zzDNqbW2lZxawd+9erVu3TmvXrqVnJtbY2Kj58+dL6nkH/qGHHtK8efPomcnV19errKxMfr9fI0eO1KpVqxQMBumZiXV2duo73/mOampq9Bd/8ReSxO+Zyf3Lv/yL3n33XQ0aNEjjxo3TihUr1NHR0W89i7ghFwAAAABw/Yqox5UBAAAAANc3hlwAAAAAQMRgyAUAAAAARAyGXAAAAABAxGDIBQAAAABEDIZcAACuM6+99po6OzsHugwAAAzBkAsAwHXm9ddfZ8gFAEQshlwAAEzI6/UqKytLDz/8sBYvXqwTJ06ooKBAWVlZKigo0H/+539KkkpLS/Xee++Ff27ChAmSpL179yo/P19ut1vTp0/Xs88+q1AopNdff13Nzc0qKChQfn7+gFwbAABGGjTQBQAAgIsdOXJEL7/8st566y05HA61tbWptLRU2dnZysnJ0aZNm/RP//RP+vnPf37V8xw6dEjV1dVyOp167LHHtG/fPv393/+9XnvtNa1fv14Oh6OfrggAgP7DnVwAAExmz549mj59engIHT58uPbv36+HHnpIkjRz5kzt27ev1/PceeedSkxMlN1u11/91V/pxIkThtYNAIAZMOQCAGAyoVCo18/YbDZJUlRUlILBYPjn/H5/+DPR0dHhf46KilJ3d/c1rhQAAPNhyAUAwGRcLpfee+89tba2SpLa2to0YcIEVVdXS5Leeecd3XXXXZKkpKQk/elPf5Ik1dbWXjTkXsnQoUPV0dFhUPUAAAws3skFAMBkxowZo+9///vKz8+X3W7X7bffrueff15Lly7VL3/5SzkcDq1atUqSlJeXp6efflqPPvqoXC6XYmNjez1/Xl6ennzySd1888164403jL4cAAD6lS3Ul2eiAAAAAACwAB5XBgAAAABEDIZcAAAAAEDEYMgFAAAAAEQMhlwAAAAAQMRgyAUAAAAARAyGXAAAAABAxGDIBQAAAABEjP8HCkSRFYS0G7UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting number of shows per year\n",
    "plt.figure(figsize = (16,7))\n",
    "sns.countplot(y = 'Year of release', data = prime_df);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.048657,
     "end_time": "2020-10-03T11:33:35.742516",
     "exception": false,
     "start_time": "2020-10-03T11:33:35.693859",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "The ratings have not changed much over the years while the number of shows offered on Amzon Prime have increased at a fast rate. The number of shows before the year 2010 are below 10. The number of shows have increased by 7.5 times by the year 2018 indicating that more shows have been released online. Although there seems to be a decrease after 2018. The data for 2020 cannot be considered for the analysis as it does not take all the months into account ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:35.847856Z",
     "iopub.status.busy": "2020-10-03T11:33:35.846749Z",
     "iopub.status.idle": "2020-10-03T11:33:36.284068Z",
     "shell.execute_reply": "2020-10-03T11:33:36.283338Z"
    },
    "papermill": {
     "duration": 0.493191,
     "end_time": "2020-10-03T11:33:36.284246",
     "exception": false,
     "start_time": "2020-10-03T11:33:35.791055",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting the shows by number of seasons\n",
    "plt.figure(figsize = (12,6))\n",
    "sns.countplot(y = 'No of seasons available', data = prime_df, palette=\"Blues_d\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.050181,
     "end_time": "2020-10-03T11:33:36.385848",
     "exception": false,
     "start_time": "2020-10-03T11:33:36.335667",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Shows with less number of seasons, mostly 1 or 2 seasons are the highest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:36.495672Z",
     "iopub.status.busy": "2020-10-03T11:33:36.494896Z",
     "iopub.status.idle": "2020-10-03T11:33:36.863164Z",
     "shell.execute_reply": "2020-10-03T11:33:36.862529Z"
    },
    "papermill": {
     "duration": 0.426387,
     "end_time": "2020-10-03T11:33:36.863295",
     "exception": false,
     "start_time": "2020-10-03T11:33:36.436908",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting the shows by language\n",
    "plt.figure(figsize = (12,6))\n",
    "sns.countplot(y = 'Language', data = prime_df);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.050754,
     "end_time": "2020-10-03T11:33:36.965435",
     "exception": false,
     "start_time": "2020-10-03T11:33:36.914681",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* The highest number of shows are in English followed by Hindi.\n",
    "This might be because of the large taget audience as the most common language used by people is English and then Hindi to a considerable extent. Shows with language particular to a country or region are very less."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:37.077060Z",
     "iopub.status.busy": "2020-10-03T11:33:37.076146Z",
     "iopub.status.idle": "2020-10-03T11:33:37.999868Z",
     "shell.execute_reply": "2020-10-03T11:33:38.000476Z"
    },
    "papermill": {
     "duration": 0.983886,
     "end_time": "2020-10-03T11:33:38.000682",
     "exception": false,
     "start_time": "2020-10-03T11:33:37.016796",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABOwAAAIWCAYAAADknBLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nOzde1xU5fr//9fMAKKioaR+TGynW0HELEJSw06kVhoiiEZbk0rNQx4qSg1PpYbbMt2KeCrDFLdpAuKAZmnlrjzkAfMQ7TyiYGkymqOIODC/P/w6P9mCYoqAvZ9/sda6131fa83to0fX477XZbDb7XZERERERERERESkQjCWdwAiIiIiIiIiIiLy/1PCTkREREREREREpAJRwk5ERERERERERKQCUcJORERERERERESkAlHCTkREREREREREpAJRwk5ERERERERERKQCcSrvAESkbG3fvp2qVauWdxhyGzp//jxVqlQp7zDkNqS5JWVB80rKiuaWlBXNLSkLmlcVz/nz57n//vuvOK+EnchN4OPjg5eXFzabDZPJRGhoKJGRkRiN5b+I1bVKFXx8fMo7DBEREREREZFi2W0FGJxM5R1GucjIyCj2vBJ2IjeBq6srKSkpAOTk5BAVFYXVamXo0KFF2tlsNpycbu0/O4PRyO+zE27pmCIiIiIiIiKlVWdgr/IOocJRwk7kJvPw8GDChAmEh4czZMgQkpOT+eabb8jPzyc3N5fZs2czaNAgTp8+jc1mY9iwYbRv356srCz69u2Lv78/P/74I97e3nTr1o0ZM2ZgsViYMmUKLVu2ZOfOncTExJCXl4erqysxMTE0bty4vB9bRERERERERG4SJexEykDDhg0pLCwkJycHgB07drBy5Urc3d2x2WzExcXh5uaGxWLh2Wef5YknngDg8OHDTJ8+naZNmxIeHo7ZbGbJkiWsW7eOOXPmMGvWLBo3bkxCQgJOTk5s2LCBadOmERsbW56PKyIiIiIiIiI3kRJ2ImXEbrc7/g4MDMTd3d1xfurUqWzZsgWj0cixY8c4ceIEAJ6ennh7ewPQpEkT2rZti8FgwNvbm+zsbACsVisjRowgMzMTg8HAhQsXbvGTiYiIiIiIiEhZKv8v4ovcho4cOYLJZMLDwwOgSJVWs9mMxWIhKSmJlJQU7rzzTs6fPw+Ai4uLo53RaHQcGwwGCgoKAJg+fTqtW7cmNTWV2bNnk5+ff6seS0RERERERERuASXsRG4yi8XCuHHj6NmzJwaD4YrrVqsVDw8PnJ2d2bRpk2PlXGlZrVbq1asHQHJy8k2JWUREREREREQqDm2JFbkJ8vLyCAkJwWazYTKZCAkJ4cUXXyy2bXBwMAMHDiQsLAwfH5/rLhjRt29fRo4cSXx8PG3atLlme3thoSruiIiIiIiISIVltxVgcDKVdxgVisF++Ye2ROS2k56ejp+fX3mHIbehjIwMfHx8yjsMuQ1pbklZ0LySsqK5JWVFc0vKguZVxVPSb6ItsSK3uSqXfRevOHab7RZFIiIiIiIiIiKloS2xUqnNnj2b1NRUjEYjRqOR8ePHc9999xXbdteuXaSkpDB69Ogrrm3dupVx48bh5OTEvHnzePfdd5kxY0ZZh19qSUlJ7N69m7Fjx173vQajkd/nfFji9ToD+t1IaCIiIiIiIiJykylhJ5VWeno633zzDcnJybi4uGCxWLhw4UKJ7e+9917uvffeYq+tXLmSl156iW7dugFUqGSdiIiIiIiIiPy1aEusVFq///47tWrVwuX/bfmsXbu2o3rqzp07iYiIoEuXLoSHh3PmzBk2b95M//79r+jns88+4/PPPycuLo6oqCiysrJ45plnih3zww8/JDg4mC5dujBlyhTg4n7zHj16EBwczCuvvMIff/wBwPPPP09MTAw9e/bk6aefZufOnQwePJiOHTsybdo0R58pKSmEh4cTEhLC2LFjKSgoACAxMZEnn3ySXr16sX37dgDOnDlDUFCQIzH5v8ciIiIiIiIiUvkpYSeVVmBgIL/++itPPvkkb7/9Nj/88AMA+fn5vPbaa0RHR7Ny5UoWLFiAq6trif10796doKAghg8fzgcffFBiu/Xr17Nu3TqWLVvGypUr6du3LwDDhw/njTfewGw24+XlxcyZMx33ODs7s3jxYiIiIhg0aBBjx44lNTWV5ORkTp48yf79+1m9ejVLliwhJSUFo9GI2Wzm+PHjxMbGsmTJEj7++GP27dsHgJubG61bt2b9+vUApKWl0bFjR5ydnW/4fYqIiIiIiIhIxaCEnVRa1atXJykpifHjx1O7dm1ee+01kpKSOHjwIHXq1KFly5bAxSSXk9ON7/7euHEjYWFhVK1aFQB3d3esVitWq5UHH3wQgNDQULZu3eq4JygoCAAvLy+aNm1K3bp1cXFxoWHDhvz2229s3LiR3bt3O1bYbdy4kSNHjrBz504efPBBateujYuLC506dXL0GR4eTmJiInDx23ZhYWE3/GwiIiIiIiIiUnHoG3ZSqZlMJlq3bk3r1q3x8vJixYoVNG/eHIPBcNX7+vTpw4kTJ2jRogXvvvtuqcay2+3X7Pd/XdquazQaHX9fOrbZbNjtdkJDQ4mKiipy39q1a0scy9/fn3feeYcffviBgoICvLy8rismEREREREREanYtMJOKq0DBw5w6NAhx3FGRgZ33XUXjRs35vjx4+zcuRO4+J03m81W5N758+eTkpJS6mQdXNyCm5iYyLlz5wA4deoUNWrUoGbNmo5VdSkpKQQEBJS6z7Zt27JmzRpycnIcfWZnZ9OyZUt++OEHTp48yYULF/j888+L3Ne1a1def/11ra4TERERERERuQ1phZ1UWrm5uUycOJHTp09jMpn429/+xvjx43FxcWHatGlMnDiRvLw8XF1diY+Pv+HxHnnkEX7++We6deuGs7Mzjz76KK+//jqTJ09m3LhxnDt3joYNGzJp0qRS99mkSRNeffVVXnrpJQoLC3F2dmbs2LHcf//9DB48mIiICOrUqUPz5s0pLCx03BccHMy//vWvEotjXM5eWEidAf1Kvm6zYbgJW4ZFRERERERE5OYw2O12e3kHISLX5/PPP2fdunW8//7712ybnp6On5/fLYhK/moyMjLw8fEp7zDkNqS5JWVB80rKiuaWlBXNLSkLmlcVT0m/iZbVSIXg4+ODl5cXNpsNk8lEaGgokZGRGI0VY9f277//TkxMDLt27cLFxYUGDRoQHR1No0aNbsn4QUFBLF++nNq1azNhwgT+85//MG/evFLdW+Wyb+dJ5aRVkCIiIiIiIn8t+j9AqRBcXV1JSUkBICcnh6ioKKxWK0OHDi3Szmaz3ZSKr9fDbrczePBgunbtyrRp04CLGfCcnJxblrC73JgxY66rvcFo5PicD8ooGrkV6g6IunYjERERERERuW0oYScVjoeHBxMmTCA8PJwhQ4aQnJzMN998Q35+Prm5ucyePZtBgwZx+vRpbDYbw4YNo3379mRlZdG3b1/8/f358ccf8fb2plu3bsyYMQOLxcKUKVNo2bIlO3fuJCYmxvF9u5iYGBo3blxiPJs2bcLJyYnnnnvOce7SclW73c57773Ht99+i8FgYODAgXTq1InNmzcTGxuLh4cHP//8Mx06dMDLy4uFCxdy/vx54uLiuPvuu7FYLIwbN46jR48CEB0djb+/PydPniQqKgqLxULLli25tHP9X//6F7Vq1SIyMhKAadOm4eHhQe/evcvq5xARERERERGRW0wJO6mQGjZsSGFhoaN66o4dO1i5ciXu7u7YbDbi4uJwc3PDYrHw7LPP8sQTTwBw+PBhpk+fTtOmTQkPD8dsNrNkyRLWrVvHnDlzmDVrFo0bNyYhIQEnJyc2bNjAtGnTiI2NLTGWvXv34uvrW+y1L774gp9//pmUlBROnjxJeHg4rVq1AuDnn39m1apVuLu788QTT9C9e3eWL1/OJ598wqJFixg1ahTvvvsukZGRtGrViqNHj9KnTx9Wr15NXFwcDzzwAIMHD+abb75h6dKlAI4kZmRkJIWFhaSlpfHZZ5/dzFcvIiIiIiIiIuVMCTupsC6vhxIYGIi7u7vj/NSpU9myZQtGo5Fjx45x4sQJADw9PfH29gYuVmBt27YtBoMBb29vsrOzAbBarYwYMYLMzEwMBgMXLlz40zFu27aNzp07YzKZuPPOOwkICGDXrl24ublx7733UrduXQDuvvtuAgMDAfDy8mLz5s0AbNiwgX379jn6O3PmDGfOnGHLli3MnDkTgMcee4w77rjD8Xzu7u789NNPnDhxgubNm1OrVq0/Hb+IiIiIiIiIVDxK2EmFdOTIEUwmEx4eHgBUrVrVcc1sNmOxWEhKSsLZ2ZmgoCDOnz8PgMtlBRaMRqPj2GAwUFBQAMD06dNp3bo1cXFxZGVlXXM7adOmTVmzZk2x165WZLmkWIxGoyOWwsJCli5diqur61VjuFz37t1JSkrixIkTdOvWrdT3iYiIiIiIiEjlUDFKcIpc5tJ33Xr27InBYLjiutVqxcPDA2dnZzZt2uRYOVdaVquVevXqAZCcnOw4f+zYMce34S7Xpk0b8vPzWbZsmePczp07+eGHHwgICGD16tUUFBRgsVjYunUrLVu2LHUs7dq1IyEhwXGckZEBQEBAAGazGYD169fzxx9/ONq0b9+eb7/9ll27dtGuXbtSjyUiIiIiIiIilYNW2EmFkJeXR0hICDabDZPJREhICC+++GKxbYODgxk4cCBhYWH4+PhctWBEcfr27cvIkSOJj4+nTZs2jvPHjx8vtgKtwWBg5syZxMTEMG/ePKpUqUKDBg2Ijo4mICCA9PR0QkJCMBgMvPnmm9SpU4cDBw6UKpZRo0Yxfvx4goODKSgooFWrVowfP55XXnmFqKgoQkNDCQgI4K677nLc4+LiQuvWralZsyYmk+maY9gLC1VltJKz22wYbnF1ZBERERERESk/BvvV9vSJ/IUkJCRQv359RwGLiqqwsJDQ0FCmT5/OPffcc8326enp+Pn5lX1g8peTkZHhqJgscjNpbklZ0LySsqK5JWVFc0vKguZVxVPSb6IlGyL/T69evco7hGvat28f/fv3p0OHDqVK1gFUuexbeiI3k/5DL2VFc0vKguaVlBXNLSmJ3XYBg5NzeYchIpWUEnYipfT7778TExPDrl27cHFxcWyLbdSoUZmPHRQUxPLly2nSpAnr1q27rnsNRiO/zhpVRpGJiIiIiEhx6g96t7xDEJFKTAk7kVKw2+0MHjyYrl27Mm3aNODistWcnJxbkrATERERERERkb8OJexESmHTpk04OTnx3HPPOc75+Phgt9uZPHky3377LQaDgYEDB9KpUyc2b95MbGwsHh4e/Pzzz3To0AEvLy8WLlzI+fPniYuL4+6773ZUxD169CgA0dHR+Pv7c/LkSaKiorBYLLRs2ZJLn5r817/+Ra1atRzVbKdNm4aHhwe9e/e+9S9FRERERERERMqEsbwDEKkM9u7di6+v7xXnv/jiC37++WdSUlKIj4/nvffe4/jx4wD8/PPPjBo1CrPZTEpKCocOHWL58uWEh4ezaNEiAN59910iIyNJTEwkNjaW0aNHAxAXF8cDDzzAihUrCAoKciT0wsPDWbFiBXCx+ERaWhrBwcG34hWIiIiIiIiIyC2iFXYiN2Dbtm107twZk8nEnXfeSUBAALt27cLNzY17772XunXrAnD33XcTGBgIgJeXF5s3bwZgw4YN7Nu3z9HfmTNnOHPmDFu2bGHmzJkAPPbYY9xxxx0AeHp64u7uzk8//cSJEydo3rw5tWrVupWPLCIiIiIiIiJlTAk7kVJo2rQpa9asueL8pa2qxXG5rDqr0Wh0HBuNRgoKCoCLq+SWLl2Kq6trqWPp3r07SUlJnDhxgm7dupX6PhERERERERGpHLQlVqQU2rRpQ35+PsuWLXOc27lzJ3fccQerV6+moKAAi8XC1q1badmyZan7bdeuHQkJCY7jjIwMAAICAjCbzQCsX7+eP/74w9Gmffv2fPvtt+zatYt27drd6KOJiIiIiIiISAWjFXYipWAwGJg5cyYxMTHMmzePKlWq0KBBA6Kjozl79iwhISEYDAbefPNN6tSpw4EDB0rV76hRoxg/fjzBwcEUFBTQqlUrxo8fzyuvvEJUVBShoaEEBARw1113Oe5xcXGhdevW1KxZE5PJdM0x7IWFKikvIiIiInKL2W0XMDg5l3cYIlJJGexX29MnIhVOYWEhoaGhTJ8+nXvuueea7dPT0/Hz8yv7wOQvJyMjAx8fn/IOQ25DmltSFjSvpKxobklZ0dySsqB5VfGU9JtoS6xUKj4+PoSEhNC5c2e6dOlCfHw8hYWF5R1WEV9++SXe3t7s37//mm0XLFjAuXPnHMf9+vXj9OnTJbbft28fHTp0oG3btqVK1gFUuexbenJj7Lb88g5BRERERERE/gK0JVYqFVdXV1JSUgDIyckhKioKq9XK0KFDi7Sz2Ww4OZXP9E5NTcXf359Vq1YxZMiQq7ZduHAhXbp0oWrVqgB8+OGHV23fpEkT1q1bd13xGIxGjsRGXtc9UryGQz4p7xBERERERETkL0AJO6m0PDw8mDBhAuHh4QwZMoTk5GS++eYb8vPzyc3NZfbs2QwaNIjTp09js9kYNmwY7du3Jysri759++Lv78+PP/6It7c33bp1Y8aMGVgsFqZMmULLli3ZuXMnMTEx5OXl4erqSkxMDI0bN75qTGfPnmX79u0sXLiQgQMHOhJ2BQUFTJkyhe+++w6AHj16YLfbOX78OJGRkbi7u7No0SKCgoJYvnw5tWvXJj4+nsTERADCw8N54YUXyMrKol+/fvj7+5Oenk69evWYNWvWdVWZFREREREREZGKTQk7qdQaNmxIYWEhOTk5AOzYsYOVK1fi7u6OzWYjLi4ONzc3LBYLzz77LE888QQAhw8fZvr06TRt2pTw8HDMZjNLlixh3bp1zJkzh1mzZtG4cWMSEhJwcnJiw4YNTJs2jdjY2KvGs3btWh5++GEaNWqEu7s7e/bswdfXl6VLl5KVlUVycjJOTk6cOnUKd3d3FixYwCeffELt2rWL9LN7926SkpJYtmwZdrudHj168OCDD1KzZk0yMzOZOnUqEydOZNiwYaxZs4aQkJCyecEiIiIiIiIicsspYSeV3uV1UwIDA3F3d3ecnzp1Klu2bMFoNHLs2DFOnDgBgKenJ97e3sDFbaZt27bFYDDg7e1NdnY2AFarlREjRpCZmYnBYODChQvXjCUtLY3IyIvbTzt16kRqaiq+vr5s3LiRiIgIxzbdSzGWZNu2bbRv355q1aoB0KFDB7Zu3UpQUBCenp6OD1L6+vo64hURERERERGR24MSdlKpHTlyBJPJhIeHB4DjW3AAZrMZi8VCUlISzs7OBAUFcf78eQBcLivEYDQaHccGg4GCggIApk+fTuvWrYmLiyMrK4vevXtfNZaTJ0+yadMm9u7d6+jHYDAwfPhw7HY7BoOh1M91teLNl8duMpkczyQiIiIiIiIitwdViZVKy2KxMG7cOHr27FlsMsxqteLh4YGzszObNm267pVoVquVevXqAZCcnOw4f+zYMccqusutWbOGrl278vXXX/PVV1+xfv16PD092bZtG4GBgXz66afYbDYATp06BUD16tU5e/bsFX0FBASwdu1azp07R25uLmvXrqVVq1bXFb+IiIiIiIiIVE5K2EmlkpeXR0hICJ07d+aFF14gMDCQwYMHF9s2ODiY3bt3ExYWhtlsvmbBiP/Vt29fpk6dSkREhGPVHcDx48eLrUCblpZG+/bti5zr2LEjZrOZ7t27U79+fbp06UKXLl1ITU0FLhaf6NevH88//3yR+3x9fQkLC6N79+706NGD8PBwmjdvfl3xi4iIiIiIiEjlZLBfbe+diFwhISGB+vXrOwpYVHQ/7dlDc1/f8g7jtmC35WNwcrl2w7+IjIwMx/cURW4mzS0pC5pXUlY0t6SsaG5JWdC8qnhK+k30DTuR69SrV6/yDuGmKrTlY1QSqlSUrBMREREREZFbQQm7SsrHxwcvLy9sNhsmk4nQ0FAiIyMxGivGLudL8RUUFODp6cl7771HzZo1yzusGzJ//nw+++wznJycMBqNvPTSS3Tt2vWWjB0bG0u1atXo06fPdd9rMBr5b1xIide9X0m5kdBERERERERE5CZTwq6ScnV1JSXlYqIlJyeHqKgorFYrQ4cOLdLOZrMV+721WxnfiBEjWLx4MQMHDrzlcdwsS5YsYcOGDSxfvhw3NzesVitr164t77BERERERERE5DZUMZZjyQ3x8PBgwoQJLF68GLvdTlJSEkOHDmXAgAG89NJLnD17lsjISEJDQwkODnYkmrKysnjqqacYNWoUzzzzDFFRUWzYsIGIiAg6duzIzp07Adi5cycRERF07dqViIgIDhw4cF3x3X///Rw7dgy4uDe7R48eBAcH88orr/DHH38A8PzzzxMTE0PPnj15+umn2blzJ4MHD6Zjx45MmzbN0degQYMICwujc+fOLF261HHez8+PadOm0aVLF3r06MGJEycAOHHiBK+88oqj2MP27dsBSElJITw8nJCQEMaOHVukqERx5s6dy7hx43BzcwOgRo0ahIaGArBx40a6du1KcHAwb731Fvn5+QAEBQUxdepUnn32WcLCwtizZw99+vShffv2LFmyxNH3Rx99RLdu3QgODmbGjBmO87Nnz+bJJ5/khRde4ODBgwAcPnzYMS7AoUOHCAsLu56fQ0REREREREQqOCXsbhMNGzaksLCQnJwcAHbs2ME///lPFi5cSJUqVYiLiyM5OZlPPvmEyZMnc6nWyOHDh+nduzcrV67k4MGDmM1mlixZwvDhw5kzZw4AjRs3JiEhgRUrVjB06NAiCbRrKSgoYOPGjQQFBQEwfPhw3njjDcxmM15eXsycOdPR1tnZmcWLFxMREcGgQYMYO3YsqampJCcnc/LkSQBiYmJISkoiMTGRRYsWOc7n5uZy3333sXLlSlq1asWyZcsAmDhxIgEBAaxcuZLk5GSaNm3K/v37Wb16NUuWLCElJQWj0YjZbC7xGc6cOcPZs2e5++67r7h2/vx5Ro4cybRp0zCbzRQUFPDvf//bcf3//u//WLp0Ka1atWLkyJFMnz6dZcuWORJz3333HZmZmSxfvpyUlBT27NnDli1b2L17N6tWrWLFihXMnDmTXbt2AXD33Xfj5uZGRkYGAElJSUUSeCIiIiIiIiJS+WlL7G3k8oK/gYGBuLu7O85PnTqVLVu2YDQaOXbsmGMFmqenJ97e3gA0adKEtm3bYjAY8Pb2Jjs7GwCr1cqIESPIzMzEYDBw4cKFa8aSl5dHSEgI2dnZ+Pr6EhgYiNVqxWq18uCDDwIQGhrKsGHDHPdcSup5eXnRtGlT6tatC1xMRv7222/UqlWLRYsW8eWXXwLw66+/kpmZSa1atXB2dubxxx8HoEWLFnz//fcAbNq0iffeew8Ak8lEjRo1SElJYffu3YSHhzti9fDwuOrzGAyGYs8fPHgQT09PGjVq5HimxYsX88ILLwA4Ksl6eXmRm5vrWKFXpUoVTp8+zffff8/333/v+BZebm4uhw4d4uzZs7Rv356qVasWeTcA3bt3JzExkbfeeotVq1bx2WefXTV2EREREREREalclLC7TRw5cgSTyeRIPF1K9ACYzWYsFgtJSUk4OzsTFBTE+fPnAXBx+f+rXhqNRsexwWBwbBOdPn06rVu3Ji4ujqysLHr37n3NeC59w85qtdK/f38WL158zZVgl8a+PI5Lxzabjc2bN7NhwwaWLl1K1apVef755x3P4ezs7EiqGY3Gq25xtdvthIaGEhUVdc3nAHBzc6Nq1aocOXKEhg0bXtHX1Tg7O1/1mex2Oy+//DIRERFF7luwYEGJScInn3ySuLg42rRpg6+vL7Vq1SrVc4iIiIiIiIhI5aAtsbcBi8XCuHHj6NmzZ7FJHqvVioeHB87OzmzatMmxcq60rFYr9erVAyA5Odlx/tixY0RGRl713ho1ajB69Gg+/vhjXF1dqVmzJlu3bgUufkcuICDguuK44447qFq1Kvv372fHjh3XvKdt27aOLaoFBQWcOXOGtm3bsmbNGsf24VOnTjneyfDhwx3f7rvcyy+/zDvvvMOZM2eAi9tkly5dSuPGjcnOziYzM/NPPVO7du1ITEzk7NmzwMV3mpOTQ0BAAF9++SV5eXmcOXOGr7/+2nFPlSpVaNeuHW+//ba+XyciIiIiIiJyG9IKu0rq0pZTm82GyWQiJCSEF198sdi2wcHBDBw4kLCwMHx8fGjcuPF1jdW3b19GjhxJfHw8bdq0cZw/fvx4qSrQNm/enGbNmpGWlsbkyZMZN24c586do2HDhkyaNKnUcTzyyCN8+umnBAcH06hRI+6///5r3jNq1CjGjBlDYmIiRqORt99+Gz8/P1599VVeeuklCgsLcXZ2ZuzYsTRo0ID//ve/1KlT54p+/vGPf5Cbm0u3bt1wdnbGycmJF198kSpVqjBp0iSGDRtGQUEBLVq04Lnnniv1M7Vr1479+/c7VthVq1aN999/H19fXzp16kRISAgNGjTA39+/yH3BwcF88cUXtGvX7ppj2AsL8X4lpcTrhbZ8jE4uJV4XERERERERkVvLYL/Wnj6REiQkJFC/fn3Hd9oquzNnzhAdHV2kUmtFNX/+fKxWK6+++uo126anp+Pn53cLopK/moyMDHx8fMo7DLkNaW5JWdC8krKiuSVlRXNLyoLmVcVT0m+iFXbyp/Xq1au8Q7ip3NzcKkWy7pVXXuHw4cN88sknpWpfxUWr524VrVYUERERERGRm0EJuwrsyy+/ZPDgwaxatYq///3vxbY5ffo0ZrOZnj17/qkxRo4cyQ8//ECNGjWAi8UqPv300xLb38h4c+bMYcCAAdds169fPz744ANq1qx53WPcqLVr13LPPffQpEmTa7Zdv34906dP59y5c9jtdh5//HFGjBhRYvusrCwGDBhAamoqGRkZHD9+nEcfffS6Y4yLi7uu9gajkfQ5wdc9jlw/vwHm8vmmKAUAACAASURBVA5BREREREREbgMqOlGBpaam4u/vz6pVq4q9XlBQwOnTp1myZMkNjTN8+HBSUlJISUm5arIO+FPj2e12CgsLmTt3bqnaf/jhh+WSrIOLCbt9+/Zds90vv/zChAkTeP/991m9ejWpqal4enqWepyMjAzWr19/XbFdeo8iIiIiIiIicnvTCrsK6uzZs2zfvp2FCxcycOBAhgwZAsDmzZuZOXMmdevWJSMjA29vbw4fPkxISAgPPfQQL774Iq+99hpnzpyhoKCAt99+m1atWl33+LGxsRw9epSsrCyOHj1KZGQkvXv35oMPPigy3ogRI/joo49YvXo1+fn5dOjQgaFDh5KVlUW/fv1o3bo1O3bswMfHx1Eoo0mTJnzwwQcMGjSI3377jfPnz9O7d2+effZZAIKCgli+fDm5ubn069cPf39/0tPTqVevHrNmzcLV1ZXnn38eHx8f9uzZg8ViYfLkycybN49ffvmFp59+mtdeew24WLV10aJFXLhwgfvuu49x48ZhMpnw8/Ojd+/efP3117i6ujJr1iwOHz7MV199xQ8//MDs2bOJjY3l7rvvLvb9fPTRRwwYMMCx8tHJycmx6nDkyJE89thjPPXUUwD4+fmRnp7uuDc/P58ZM2aQl5fHtm3b6N+/P/v376datWr06dMHgGeeeYY5c+YAFHmPcXFxrF69+or3LSIiIiIiIiK3D62wq6DWrl3Lww8/TKNGjXB3d2fPnj2Oa7t27eLVV19l1apVREVFcffdd5OSksKIESNITU2lXbt2jhVzzZo1u+ZY7733HiEhIYSEhBAVFeU4f/DgQebPn89nn31GXFwcFy5cuGK87777jszMTJYvX05KSgp79uxhy5Ytjvu7du3KihUrmDRpEq6urqSkpPDBBx8AEBMTQ1JSEomJiSxatIiTJ09eEVtmZiY9e/YkLS2NGjVqsGbNGsc1Z2dnFi9eTEREBIMGDWLs2LGkpqaSnJzMyZMn2b9/P6tXr2bJkiWkpKRgNBoxmy9uWczNzeW+++5j5cqVtGrVimXLlvHAAw8QFBTkWHFYUrIOYO/evbRo0eKa77Y4Li4uDB06lE6dOpGSkkKnTp2u2v7y93jw4MES37eIiIiIiIiI3B60wq6CSktLIzIyEoBOnTqRmpqKr68vAPfeey8NGzYs9r57772X6OhobDYb7du3L1X1l+HDhztWg13u0UcfxcXFhdq1a1O7dm1ycnKuaPP999/z/fff07VrV+BiIuzQoUPUr1+fu+66i/vvv7/EcRctWsSXX34JwK+//kpmZia1atUq0sbT09PxDL6+vmRnZzuuBQUFAeDl5UXTpk2pW7cuAA0bNuS3335j27Zt7N69m/DwcADy8vLw8PAALib7Hn/8cQBatGjB999/f833VF4uf48lve+AgIDyDFFEREREREREbiIl7CqgkydPsmnTJvbu3YvBYKCgoACDwcDw4cMBqFatWon3BgQEkJCQwPr16xk+fDh9+vRxJHeul8tl1UVNJhM2m+2KNna7nZdffpmIiIgi57Oysq4a5+bNm9mwYQNLly6latWqPP/885w/f/6aMVze5tI1o9FYpJ3RaMRms2G32wkNDS2yavASZ2dnDAaDo31BQUGJsRanSZMm7N69u9gVjCaTyfGtObvdzoULF67Z3+X3AEWe8/L3WNL7FhEREREREZHbh7bEVkBr1qyha9eufP3113z11VesX78eT09Ptm3bdkXb6tWrc/bsWcdxdnY2Hh4e9OjRg27dujm20g4fPpydO3fecGz/O167du1ITEx0nDt27FixK/Hg4nfeLiWvrFYrd9xxB1WrVmX//v3s2LHjhmP7X23btmXNmjWOeE6dOlVkhV5x/vf5EhISSEhIuKJdnz59mDt3LgcPHgSgsLCQ+Ph4ABo0aOB47+vWrSs2Yfe/4zRo0ICffvoJgD179pCVlVVsfNfzvkVERERERESkctIKuwooLS2Nfv36FTnXsWNHzGbzFd87q1WrFg888ADPPPMMDz/8MF5eXsyfPx8nJyeqVavG5MmTAfjvf/9LnTp1ih3vvffeY/bs2Y7jzz77rMTY/ne8ESNGsH//fseKr2rVqvH+++9jNF6ZC+7RowddunShefPmTJo0iU8//ZTg4GAaNWp01a2zf1aTJk149dVXeemllygsLMTZ2ZmxY8fSoEGDEu/p1KkTY8aMYdGiRcyYMYMDBw7wwAMPXNGuWbNmREdHExUVxblz5zAYDDz66KOO5xw0aBDh4eG0bdu22JWGrVu3Zt68eYSEhNC/f3+efPJJUlJSCAkJ4d577+Wee+4pNr527doV+74vbfUtjr2wEL8B5qu9KrlJCm35GJ1crt1QRERERERE5CoMdrvdXt5BSNk6c+YM0dHRzJgxo7xDqXT69+9PbGxskS23lU16ejp+fn7lHYbchjIyMkr1nUyR66W5JWVB80rKiuaWlBXNLSkLmlcVT0m/iVbY/QW4ubndNsm62bNnk5qaitFoxGg0Mn78eO67774b7nfz5s04OztfsZpu7ty5pbrfx8cHLy8vbDYbJpOJ0NBQIiMji11peKtVuYFko1aMiYiIiIiIiNx6SthJpZGens4333xDcnIyLi4uWCyWUhV0uBabzcYPP/xAtWrVit3+Whqurq6kpKQAkJOTQ1RUFFarlaFDh14xlpPTrf1nZzAa2TDvmT9170Mvp97kaERERERERETkWpSwk0rj999/p1atWo7tqbVr13ZcCwoK4umnn2bz5s0AfPDBB/ztb38jOzub6OhoLBYLtWvXZtKkSdx1112MHDmSO+64g59++gl3d3e2b9+O0Whk5cqVjBkzht9//524uDiMRiM1atRg8eLFpY7Tw8ODCRMmEB4ezpAhQ0hOTuabb74hPz+f3NxcZs+ezaBBgzh9+jQ2m41hw4bRvn17srKy6Nu3L/7+/vz44494e3vTrVs3ZsyYgcViYcqUKbRs2ZKdO3cSExNDXl4erq6uxMTE0Lhx45v7skVERERERESk3ChhJ5VGYGAgcXFxPPnkk7Rt25ZOnTrx4IMPOq67ubmxfPlyVqxYQUxMDHPnzmXChAl07dqV0NBQli9fzsSJE5k1axYAhw4dYsGCBZhMJmJjY6lWrRp9+vQBIDg4mPnz51OvXj1Onz593bE2bNiQwsJCRwXXHTt2sHLlStzd3bHZbMTFxeHm5obFYuHZZ5/liSeeAODw4cNMnz6dpk2bEh4ejtlsZsmSJaxbt445c+Ywa9YsGjduTEJCAk5OTmzYsIFp06YRGxt7o69XRERERERERCoIJeyk0qhevTpJSUls3bqVzZs389prrxEVFUVYWBgAzzxzcdtn586dmTRpEnBxG+2lZFZISAjvv/++o7+nnnoKk8lU7Fh+fn6MHDmSp59+mg4dOvypeC+v5xIYGIi7u7vj/NSpU9myZQtGo5Fjx45x4sQJADw9PfH29gYuVrlt27YtBoMBb29vsrOzAbBarYwYMYLMzEwMBsNN2RYsIiIiIiIiIhVH+X8RX+Q6mEwmWrduzdChQxkzZgxffPHFdd1vMBgcf1etWrXEduPHj+fVV1/l119/pWvXrpw8efK6xjly5AgmkwkPD48rxjKbzVgsFpKSkkhJSeHOO+/k/PnzAEWq0RqNRsexwWCgoKAAgOnTp9O6dWtSU1OZPXs2+fn51xWbiIiIiIiIiFRsSthJpXHgwAEOHTrkOM7IyOCuu+5yHK9evRqAVatW4efnB1xcKZeWlgZcTJT5+/sX23f16tU5e/as4/jw4cPcd999DBs2jFq1avHbb79x7NgxIiMjrxmnxWJh3Lhx9OzZs0iC8BKr1YqHhwfOzs5s2rTJsXKutKxWK/Xq1QMgOTn5uu4VERERERERkYpPW2Kl0sjNzWXixImcPn0ak8nE3/72N8aPH++4np+fT/fu3SksLGTq1KkAjB49mujoaObPn+8oOlGcxx9/nKFDh7Ju3TrGjBnDggULyMzMxG6306ZNG5o1a8bu3btLrPCal5dHSEgINpsNk8lESEgIL774YrFtg4ODGThwIGFhYfj4+Fx3wYi+ffsycuRI4uPjadOmzTXb2wsL/3S110JbPkYnl2s3FBEREREREZGbxmC//ENbIpVUUFAQy5cvL1I59mZLSEigfv36jgIRlUV6erpjxaHIzZSRkYGPj095hyG3Ic0tKQuaV1JWNLekrGhuSVnQvKp4SvpNtMJOpJR69epV3iH8KVVcrr5CrsCWj0mr6EREREREREQqDCXspEL68ssvGTx4MKtWreLvf//7VdsuWLCAtLQ0R2GHfv368cEHH1CzZs2bGtP69euZPn06586dw2638/jjjzNixIibOkZJNm/ezMcff8zcuXOv+16D0ci6jzqXeP2Jvmk3EpqIiIiIiIiI3GQqOiEVUmpqKv7+/qxateqabRcuXMi5c+ccxx9++OFNT9b98ssvTJgwgffff5/Vq1eTmpqKp6fnTR1DRERERERERAS0wk4qoLNnz7J9+3YWLlzIwIEDGTJkCAAFBQVMmTKF7777DoAePXpgt9s5fvw4kZGRuLu7s2jRoiLfs4uPjycxMRGA8PBwXnjhBbKysujXrx/+/v6kp6dTr149Zs2ahaura4kxffTRRwwYMMCx2s/JyYmePXsCkJ2dTXR0NBaLxVHY4q677mLkyJFUqVKFAwcOcPToUSZNmkRycjI7duzgvvvu45///CcA3333HbGxseTn59OwYUMmTZpE9erV+c9//kNMTAy1atXC19cXgMLCQp566ik+/fRTateuTWFhIU8++SRLly4t0+/3iYiIiIiIiMitoxV2UuGsXbuWhx9+mEaNGuHu7s6ePXsAWLp0KVlZWSQnJ2M2mwkODqZ3797UrVuXTz75hEWLFhXpZ/fu3SQlJbFs2TKWLl3KZ599xk8//QRAZmYmPXv2JC0tjRo1arBmzZqrxrR3715atGhR7LUJEybQtWtXR0wTJ050XDt9+jQLFy7krbfeYsCAAbzwwgukpaXxyy+/kJGRgcViYfbs2cTHx5OcnEyLFi2Ij4/n/PnzjBkzhjlz5vDvf/+b33//HQCj0UiXLl1YuXIlABs2bKBZs2ZK1omIiIiIiIjcRpSwkwonLS2Nzp0vfnOtU6dOpKamArBx40YiIiJwcrq4MNTd3f2q/Wzbto327dtTrVo1qlevTocOHdi6dSsAnp6ejiosvr6+ZGdn/+l409PTeeaZZwAICQlh27ZtjmuPP/44BoMBb29v7rzzTry9vTEajTRp0oTs7Gx+/PFH9u3bx3PPPUdISAgrVqzg6NGjHDhwAE9PT+655x4MBgNdunRx9NmtWzdSUlIASExMJCws7E/HLiIiIiIiIiIVj7bESoVy8uRJNm3axN69ezEYDBQUFGAwGBg+fDh2ux2DwVDqvux2e4nXXC6rnGoymTh//vxV+2rSpAm7d++mWbNm1xz38hgvjWMwGIqMaTQasdlsGI1GAgMDmTp1apE+MjIySnzW+vXr4+HhwcaNG/nxxx+ZMmXKNWMSERERERERkcpDK+ykQlmzZg1du3bl66+/5quvvmL9+vV4enqybds2AgMD+fTTT7HZbACcOnUKgOrVq3P27Nkr+goICGDt2rWcO3eO3Nxc1q5dS6tWra46fkJCAgkJCVec79OnD3PnzuXgwYPAxW/JxcfHA+Dn50da2sVKq2azGX9//1I/7/3338/27dvJzMwE4Ny5cxw8eJDGjRuTlZXF4cOHARz9X9K9e3fefPNNnn76aUwmU6nHExEREREREZGKTyvspEJJS0ujX79+Rc517NgRs9nMmDFjOHToEF26dMHJyYkePXrQq1cvevToQb9+/ahTp06R79j5+voSFhZG9+7dgYtFJ5o3b05WVlaJ4x84cIAHHnjgivPNmjUjOjqaqKgozp07h8Fg4NFHHwVg9OjRREdHM3/+fEfRidK61P71118nPz8fgFdffZVGjRoxfvx4Xn75ZWrVqoW/vz979+513BcUFMRbb71Vqu2w9sJCnuibVuL1Als+JieXEq+LiIiIiIiIyK1lsF9t36DIX0z//v2JjY0tsn21Itq1axeTJk3i3//+9zXbpqen4+fndwuikr+ajIwMx7cgRW4mzS0pC5pXUlY0t6SsaG5JWdC8qnhK+k20JfY25ePjQ0hICJ07d6ZLly7Ex8dTWFhY3mEV8eWXX+Lt7c3+/fuv2XbBggWcO3fOcdyvXz9Onz59U+M5ceIEcHElXqdOna5Y6VdRzJs3j6FDh/L666+Xqn1ZJh8LbPll1reIiIiIiIjIX5W2xN6mXF1dHZVEc3JyiIqKwmq1MnTo0CLtbDabo+rqrZaamoq/vz+rVq1iyJAhV227cOFCunTpQtWqVQH48MMPb3o8M2bM4KGHHiIyMhKAn3/++aaPcTO8/PLLvPzyy6VubzQaWTW/U5nE0qnPqjLpV0REREREROSvTAm7vwAPDw8mTJhAeHg4Q4YMITk5mW+++Yb8/Hxyc3OZPXs2gwYN4vTp09hsNoYNG0b79u3Jysqib9+++Pv78+OPP+Lt7U23bt2YMWMGFouFKVOm0LJlS3bu3ElMTAx5eXm4uroSExND48aNrxrT2bNn2b59OwsXLmTgwIGOhF1BQQFTpkzhu+++A6BHjx7Y7XaOHz9OZGQk7u7uLFq0iKCgIJYvX07t2rWJj48nMTERuLg67oUXXiArK4t+/frh7+9Peno69erVY9asWbi6upYY0/HjxwkMDHQcX6oIu3nzZj7++GPmzp0LwPjx42nRogVhYWFMmTKFr776CpPJRLt27RgxYgQjR47ExcWFffv2kZOTw8iRI3n88ccdz/bDDz+Qn59Pz549iYiIYPPmzcycOZNatWrxyy+/4Ovry5QpUzAYDMX2b7FYGDduHEePHgUgOjr6ugpdiIiIiIiIiEjFpoTdX0TDhg0pLCwkJycHgB07drBy5Urc3d2x2WzExcXh5uaGxWLh2Wef5YknngDg8OHDTJ8+naZNmxIeHo7ZbGbJkiWsW7eOOXPmMGvWLBo3bkxCQgJOTk5s2LCBadOmERsbe9V41q5dy8MPP0yjRo1wd3dnz549+Pr6snTpUrKyskhOTsbJyYlTp07h7u7OggUL+OSTT6hdu3aRfnbv3k1SUhLLli3DbrfTo0cPHnzwQWrWrElmZiZTp05l4sSJDBs2jDVr1hASElJiTD179uS1114jISGBhx56iLCwMOrVq1di+1OnTvHll1/y+eefYzAYimzRzc7OJiEhgcOHD9O7d28eeughVqxYQY0aNUhMTCQ/P5+IiAhHgvCnn34iLS2NunXr8txzz7Ft2zaaNGlSbP/vvvsukZGRtGrViqNHj9KnTx9Wr1591fctIiIiIiIiIpWHEnZ/IZfXFwkMDMTd3d1xfurUqWzZsgWj0cixY8cc33Pz9PTE29sbgCZNmtC2bVsMBgPe3t5kZ2cDYLVaGTFiBJmZmRgMBi5cuHDNWNLS0hxbTzt16kRqaiq+vr5s3LiRiIgIxzbdSzGWZNu2bbRv355q1aoB0KFDB7Zu3UpQUBCenp6ODzf6+vo64i3Jww8/zNq1a/n222/5z3/+Q2hoKKmpqSW2d3Nzo0qVKowaNYrHHnuMxx57zHHt6aefxmg0cs8999CwYUMOHDjA999/z3//+1/WrFkDXHxvmZmZODs707JlS/7v//4PuLiyLzs7m/vvv7/Y/jds2MC+ffscY505c4YzZ87g5uZ21ecTERERERERkcpBCbu/iCNHjmAymfDw8ABwfAsOwGw2Y7FYSEpKwtnZmaCgIM6fPw8ULVhgNBodxwaDgYKCAgCmT59O69atiYuLIysri969e181lpMnT7Jp0yb27t3r6MdgMDB8+HDsdjsGg6HUz3W1IseXx24ymRzPdDXu7u4EBwcTHBxM//792bJlCx4eHkUKdlzqx8nJieXLl7Nx40bS0tJISEhg4cKFAFc8g8FgwG63M3r0aB5++OEi1zZv3nxFrAUFBSX2X1hYyNKlS6+6vVdEREREREREKi9Vif0LuPTNs549exabDLNarXh4eODs7MymTZuuuRKtuPsvbR1NTk52nD927JhjFd3l1qxZQ9euXfn666/56quvWL9+PZ6enmzbto3AwEA+/fRTbDYbcHHbKUD16tU5e/bsFX0FBASwdu1azp07R25uLmvXrqVVq1ZXjTchIYGEhIQrzm/cuNFRifbMmTMcPnyY+vXr06BBA/bv309+fj5Wq5WNGzcCF7/DZ7VaefTRR4mOji5SpOLzzz+nsLCQw4cPc+TIERo1akS7du1YsmSJYwXiwYMHyc3NLTHOkvpv165dkfgzMjKu+rwiIiIiIiIiUrlohd1tKi8vj5CQEGw2GyaTiZCQEF588cVi2wYHBzNw4EDCwsLw8fG5ZsGI/9W3b19GjhxJfHw8bdq0cZw/fvx4sRVo09LS6NevX5FzHTt2xGw2M2bMGA4dOkSXLl1wcnKiR48e9OrVix49etCvXz/q1KnDokWLHPf5+voSFhZG9+7dgYtFJ5o3b05WVlaJ8R44cIAHHnjgivN79uxhwoQJmEwm7HY73bt3p2XLlgA89dRTBAcHc88999C8eXPgYkJt0KBBjhV3b731lqOvRo0a0atXL3JycnjnnXeoUqUK3bt3Jzs7m7CwMOx2O7Vq1WLWrFklxllS/6NGjWL8+PEEBwdTUFBAq1atGD9+fIn9iIiIiIiIiEjlYrBfbU+hyA1ISEigfv36jgIWFUX//v2JjY0tsg31Zho5ciSPPfYYTz31VJn0f70uFfQoCwW2fExOZfMepeLLyMhwfCdS5GbS3JKyoHklZUVzS8qK5paUBc2riqek30Qr7KTM9OrVq7xDKNbcuXPLO4QK5UaSbkrWiYiIiIiIiNx8SthJufDx8cHLy8txHBcXh6en53X1kZSURGBgoOP7eWVt586dTJ48mRMnTmAwGPD392f06NFFCngA/POf/7zpY2dlZTFgwICrVq0tidFoJCm+5NV+YS9+fiOhiYiIiIiIiMhNpoSdlAtXV1dSUlJuqI/k5GSaNm16SxJ2J06cYNiwYUydOhU/Pz/sdjtr1qzh7NmzVyTsRERERERERERuhKrESoVw9uxZIiMjCQ0NJTg4mLVr1wIXV5Y9/fTTjB49ms6dO/PSSy+Rl5fH559/zu7du3njjTcICQkhLy+PmTNn0q1bN5555hnGjBnDpc8zLly4kE6dOhEcHMxrr71GYWEhHTt2xGKxAFBYWEiHDh0cx8VZvHgxXbt2xc/PDwCDwcBTTz3FnXfeyalTpxg0aBDBwcH06NHDUc01NjaWESNG8NJLLxEUFMQXX3zBe++9R3BwMH369HFUi929eze9evUiLCyMPn36cPz4ccf5Ll268Oyzz7J48WJHLP/4xz+KVIaNiIgoUqFWRERERERERCo3JeykXFyqYhsSEsIrr7xClSpViIuLIzk5mU8++YTJkyc7Em6ZmZn07NmTtLQ0atSowZo1a3jqqado0aIFU6ZMISUlBVdXV3r16kViYiKpqank5eXx9ddfAzBv3jxWrFiB2WzmnXfewWg00qVLF1auXAnAhg0baNasGbVr1y4x3r1795ZYuCE2NpbmzZtjNpt57bXXGDFihOPa4cOHmTt3LrNmzeLNN9+kdevWmM1mXF1dWb9+PRcuXGDixInMmDGDpKQkunXrxrRp04CLVWFHjx7N0qVLi4zXvXt3kpKSADh48CD5+fk0a9bsT/4SIiIiIiIiIlLRaEuslIv/3RJ74cIFpk6dypYtWzAajRw7dowTJ04A4Onp6aiY4uvrS3Z2drF9bt68mY8++oi8vDxOnTpF06ZNCQoKwtvbmzfeeIMnnniC9u3bA9CtWzcGDRrECy+8QGJiImFhYX/6WbZt20ZsbCwAbdu25dSpU1itVgAeeeQRnJ2d8fLyoqCggEceeQQALy+v/4+9e4+qqlr/P/7eewOiUHFRO3nppCmoCWqK6KGsEC9hyEUsMxVTyyw1jcxbRzuGl0olRbx9T2Jpxy4KApJpmfr1UqRGgYZfy7xhHVT26QiSwt7s3x8O10+OgNoRRfu8xmgM1lpzzfXMuVd/+Iw510NeXh6HDh3iwIEDPP3008D51X716tWjsLCQwsJCOnbsCEB4eDjbtm0DoGfPnixcuJBXXnnlv45dRERERERERGoeJeykRkhPT8dqtZKcnIyzszPBwcGcO3cOABeX/1+J1GKxGOcvdu7cOf72t7+xZs0a7rrrLhISEox2S5cuZdeuXXzxxRcsXLiQjIwM7rrrLry9vfnyyy/57rvvmD17dpXxNWvWjH379hkJv4tdWAl4MZPJVC52s9mMs7Ozcd5sNmO323E4HDRv3vySVXSnT5822v6n2rVr85e//IVNmzaxfv161qxZU2XsIiIiIiIiInJz0ZZYqREKCwvx9vbG2dmZr776qtJVdBdzc3PjzJkzAEZyztPTkzNnzrBhwwbg/Iq1X375hU6dOjFu3DgKCwspLi4Gzm8tHTduHI8++igWiwWAzz77jDlz5lzyrAEDBrB27Vq+++4741xqaionT54kICDA2F6bmZmJp6cn7u7uVzTuJk2aYLVaycrKAs6vNPzhhx+4/fbbcXd3Z/fu3cD5hObF+vbtS1xcHH5+fnh4eFzRs0RERERERETk5qAVdlIjhIWFMWLECKKiomjZsiVNmza97D2RkZFMnToVV1dXPvzwQ/r27UtYWBgNGzbEz88PALvdzrhx4ygqKsLhcDB48GBuv/12AIKDg5k4cWK5LaVHjx6tMNlWt25d5s6dyxtvvEFBQQFms5mAgAC6d+/OyJEjmThxImFhYdSuXZtZs2Zd8bhdXFyYP38+cXFxFBYWYrfbiYmJoXnz5sycOZNJkyZRu3ZtAegOFgAAIABJREFUHnjggXL3tW7dGnd39yvaDltWVkbU059Wet1uK8Hi5FLpdRERERERERG5vkyOivbzifwB5OTkMHPmTP7xj38Y515++WUmTZpUZQGKmiA/P59Bgwaxfv16zOaqF8pmZWUZ1W1FrqXc3Fzj+5Ii15LeLakOeq+kuujdkuqid0uqg96rmqey30RbYuUPaenSpYwePZqXXnqp3PnZs2fX+GTd2rVrefzxxxkzZsxlk3VQ/huAUr3stpIbHYKIiIiIiIjcArQlVq6bli1b4uPjg81mw2KxEBkZSUxMzBUlna61Z599lmeffbbcuUWLFrFu3TrMZjNms5lp06bRpk2b6x7b5URERBAREXHF7c1mM/9Y3qMaI5IL+g/ecKNDEBERERERkVuAEnZy3bi6upKamgpAQUEBsbGxFBYWMnr06HLtbDYbTk7X99XMyspiy5YtpKSk4OLigtVqpbS09LrGICIiIiIiIiICStjJDeLt7c3rr79OdHQ0o0aNIiUlhS1btlBSUkJxcTGLFi3i+eef5/Tp09hsNl588UVCQkLIy8tj2LBhtG/fnu+++w5fX1/69OnD/PnzsVqtzJ49G39/f7Kzs5kxYwZnz57F1dWVGTNmVFnI4uTJk3h6ehrbRy/eFhscHMzq1avx8vIiJyeHN998kxUrVvD1118zffp0AEwmEytXrmTfvn3Mnz8fDw8PDh06RIcOHXjttdcwm81s376dhIQESkpKaNy4MTNnzsTNzY3g4GAiIiLYvHkzNpuNt99+m3vvvbfC/t3d3fn73//O+vXrKSkpoVu3bpckPEVERERERETk5qaEndwwjRs3pqysjIKCAgC+/fZb0tLS8PDwwGazkZiYiLu7O1arlSeeeIKuXbsC5yu5zps3j+bNmxMdHU16ejqrVq1i06ZNLF68mIULF9K0aVNWrlyJk5MTO3fuJD4+noSEhEpjCQoKIjExkR49etC5c2dCQ0Pp2LFjlfEvW7aMKVOm0L59e86cOUOtWrUAyM7O5pNPPqFBgwYMGzaMjRs30rFjRxYtWkRSUhJ16tRh6dKlJCUlMXLkSAA8PT1JSUnh/fffZ9myZUyfPr3C/rdv386RI0dYvXo1DoeDESNGsGvXLgICAq7FTyIiIiIiIiIiNYASdnJDXVykOCgoCA8PD+P83Llz2bVrF2azmfz8fE6dOgVAo0aN8PX1BaBZs2Z07twZk8mEr68vx48fB6CwsJDx48dz5MgRTCbTZbe3urm5kZyczO7du8nMzGTs2LHExsYSFRVV6T33338/s2bNIiwsjO7du+Pm5gaAv78/jRs3BqBXr17s2bOHWrVq8eOPP/Lkk08CUFpaStu2bY2+unfvDkDr1q357LPPKu1/x44d7Nixw/iGXXFxMYcPH1bCTkREREREROQWooSd3DDHjh3DYrHg7e0NQO3atY1r6enpWK1WkpOTcXZ2Jjg4mHPnzgHlq56azWbj2GQyYbfbAZg3bx6BgYEkJiaSl5fHoEGDLhuPxWIhMDCQwMBAfHx8WLt2LVFRUVgsFiOxeCEGOF+44qGHHmLr1q08/vjjJCUlGXFczGQy4XA4CAoKYu7cuRU+29nZ2RjPhTFU1L/D4eDZZ5+lX79+lx2PiIiIiIiIiNycrn95ThHAarUydepUnnrqqUsSXHB+hZy3tzfOzs589dVXxsq5K1VYWMidd94JQEpKinE+Pz+fmJiYS9r/9NNPHD582DjOzc2lQYMGADRs2JC9e/cCsHHjRqPN0aNH8fX15dlnn6V169YcOnQIOL8l9tixY5SVlbF+/Xrat29P27Zt+eabbzhy5AgAv/32m9G+MhX1/8ADD7BmzRrOnDljjOfClmIRERERERERuTVohZ1cN2fPniU8PBybzYbFYiE8PJynn366wrZhYWGMGDGCqKgoWrZsWWXBiIoMGzaMCRMmkJSURKdOnYzzJ06cqLACbXFxMXFxcZw+fRqLxcKf//xnpk2bBsDIkSOZPHkyS5YsoU2bNsY97777LpmZmZjNZpo1a0aXLl3Iysqibdu2zJkzhwMHDtChQwe6deuG2Wxm5syZvPTSS5SUlAAwZswYmjRpUukYKurfxcWFgwcPGivs6tSpw1tvvWWsUqxIWVkZ/QdvuKr5k9/HbivB4uRy+YYiIiIiIiIiVTA5Lv6ImMgtbuXKldx1111GAYtrLTMzk2XLlrFkyZJq6f/3yMrKol27djc6DLkF5ebm0rJlyxsdhtyC9G5JddB7JdVF75ZUF71bUh30XtU8lf0m2hIrfygDBgyotmTdf1q0aBG9evUiLCyM8PBwvvvuu0rb5uTkEBcXV+G13bt306tXL8LDw8nPz2f06NFXFcfF3/yriM1eclX9iYiIiIiIiEj10pZYkWvoQtGKrKwstmzZQkpKCi4uLlit1ior1fr5+eHn51fhtbS0NIYMGUKfPn0AmD9//lXFZDabWfZu90qvD4nZWOk1EREREREREbn+tMJOpBqcPHkST09PY3Wbl5eXUQQjOzubfv360bt3b6KjoykqKiIzM5Phw4df0s/HH3/Mp59+SmJiIrGxseTl5fHYY49d17GIiIiIiIiIyPWlFXYi1SAoKIjExER69OhB586dCQ0NpWPHjpSUlDB27Fji4+Px9/enqKgIV1fXSvvp27cve/bs4eGHH6Znz57k5eVdx1GIiIiIiIiIyI2gFXYi1cDNzY3k5GSmTZuGl5cXY8eOJTk5mUOHDlGvXj38/f0BcHd3r7BqrYiIiIiIiIj8cSlTIFJNLBaL8U07Hx8f1q5dS6tWrTCZTFXeN3ToUE6dOkXr1q2ZPn36dYpWRERERERERGoKJexEqsFPP/2E2WzmnnvuAc6XaW7QoAFNmzblxIkTZGdnV7ol9p133rkBEYuIiIiIiIhITaGEnUg1KC4uJi4ujtOnT2OxWPjzn//MtGnTcHFxIT4+nri4OM6ePYurqytJSUnVGktZWVmVlWBt9hKcLC7VGoOIiIiIiIiIXDkl7ESqQevWrfnggw8qvObv789HH31U7tyFrbMVmTVrlvF3o0aNWLdu3VXFUlJSUuV1JetEREREREREahYVnRC5xbm41MyEnM1edSJRRERERERE5I9KK+zkptayZUt8fHyw2WxYLBYiIyOJiYnBbK75uejc3FxOnDjBQw89VK3PMZvNLFrZo1qf8XuMGLDhRocgIiIiIiIiUiMpYSc3NVdXV1JTUwEoKCggNjaWwsJCRo8efYMju7zc3Fz27t17VQk7m82Gk5P+txURERERERG5lelf/nLL8Pb25vXXXyc6OppRo0ZRUlLCa6+9xt69e7FYLEyYMIFOnTpht9uZPXs227dvB+Dxxx9n4MCBBAcHs3r1ary8vMjJyeHNN99kxYoVJCQkkJeXx8mTJzl8+DATJkzg22+/Zdu2bdSvX5/Fixfj7OzM3r17mTVrFsXFxXh6ejJz5kzq16/PwIED8ff3JzMzk8LCQqZPn46/vz/z58/n7Nmz7Nmzh+HDh9OoUSNmzJhhFKOYMWMGTZs2JTk5mS1btlBSUkJxcTF33nknPXr0ICQkBIDY2FhCQ0Pp2rXrjZx+EREREREREblGlLCTW0rjxo0pKyujoKCAtLQ0ANLT0zl48CBDhw5lw4YNrFmzhry8PFJSUnBycuLXX3+9bL9Hjx7lvffe4+DBgzzxxBPMnz+fV155hRdeeIGtW7fy0EMPERcXx8KFC/Hy8uKTTz4hPj6emTNnAmC321m9ejVbt25lwYIFLF++nNGjR7N3716mTJkCQFFREStXrsTJyYmdO3cSHx9PQkICAN9++y1paWl4eHjw9ddfs3z5ckJCQigsLCQrK4s33nijmmZURERERERERK43JezkluNwOADYs2cPAwYMAODee++lQYMGHDp0iC+//JJ+/foZW0s9PDwu22eXLl1wdnbGx8cHu91Oly5dAPDx8SEvL49Dhw5x4MABnn76aQDKysqoV6+ecX+3bt0AuO+++zh+/HiFzygsLGT8+PEcOXIEk8lEaWmpcS0oKMiIs2PHjkybNo2CggI2btxIjx49tE1WRERERERE5Baif+XLLeXYsWNYLBa8vb2NxN1/cjgcmEymS85bLBbjnnPnzpW7dqHSqtlsxtnZ2bjfbDZjt9txOBw0b96cDz/8sMJnXny/3W6vsM28efMIDAwkMTGRvLw8Bg0aZFyrXbt2uba9e/cmPT2djIwMZsyYUWF/IiIiIiIiInJzqvmlNEWukNVqZerUqTz11FOYTCYCAgJIT08H4NChQ/zyyy80bdqUoKAgPvjgA2w2G4CxJbZhw4bs3bsXgI0bN17Vs5s0aYLVaiUrKwuA0tJSfvjhhyrvcXNz48yZM8ZxYWEhd955JwApKSlV3hsVFcW7774LQPPmza8qVhERERERERGp2bTCTm5qZ8+eJTw8HJvNhsViITw83NiW2r9/f6ZOnUpYWBgWi4WZM2fi4uJC3759OXz4ML1798bJyYnHH3+cAQMGMHLkSCZPnsySJUto06bNVcXh4uLC/PnziYuLo7CwELvdTkxMTJXJtMDAQJYuXUp4eDjDhw9n2LBhTJgwgaSkJDp16lTl8+rWrUvTpk2NwhNVKSsrY8SADVc1nuvBZi/ByeJyo8MQERERERERqXFMjsr2DYpIjfXbb78RFhZGSkoKt912W5Vts7KyaNeu3XWKTP5IcnNzadmy5Y0OQ25BerekOui9kuqid0uqi94tqQ56r2qeyn4TbYmVavfZZ5/h6+vLwYMHr6j95MmT+fHHH//r5+bl5RlbYgFycnKIi4v7r/v9TwMHDqRHjx6EhYXRs2dPpk2bxunTp6/5cy7YuXMnjz76KAMGDLhssg7+//fzKmOzl1yr0ERERERERETkGtCWWKl269ato3379nzyySeMGjXqsu2nT59+TZ57/Phx1q1bR1hYGAB+fn74+fldk77/0+zZs/Hz86OkpIS5c+fy/PPPs3LlynJtHA4HDocDs/m/y5P/5S9/YcuWLVfc3mw2M/cfPSq9/lL/mrddVkREREREROSPTCvspFqdOXOGb775hunTp5ORkWGcz8zMZODAgYwePZqePXsSGxtrVGgdOHAgOTk5ALRr14633nqLqKgoBg8eTHZ2NgMHDqRr165s2rQJOL+Srn///kRGRhIZGck333wDwJw5c9i9ezfh4eEsX76czMxMhg8fDpwvNPH8888TFhbG448/zv79+wFISEhg4sSJxjPee++9qxqvi4sL48aN4+eff2b//v3k5eXx6KOP8tprrxEZGckvv/zC1KlTiYqKolevXsyfP9+4Nzg4mLlz5/LEE08QFRXFvn37GDp0KCEhIaxatcqYz5iYGCIjIwkLC+Pzzz//PT+LiIiIiIiIiNRgSthJtfr888958MEHadKkCR4eHuzbt8+49v333zNp0iQ++eQT8vLy2LNnzyX3FxcX07FjR5KTk3Fzc+Ptt99m2bJlJCYmGskub29vkpKSSElJIT4+3tj2GhsbS4cOHUhNTWXw4MHl+k1ISKBVq1akp6czduxYxo8fb1w7dOgQ77zzDh9//DGJiYmUlpZe1ZgtFgstWrTgp59+MvqLiIhg7dq1NGzYkLFjx5KcnExaWhq7du0ykoUAf/rTn/jwww/p0KEDEyZMYN68eXz00UfGWGvVqkViYiIpKSm8++67vPHGG+gzlCIiIiIiIiK3Fm2JlWqVkZFBTEwMAKGhoaxbt4777rsPAH9/f/70pz8B0KJFC44fP06HDh3K3e/s7EyXLl0A8PHxwcXFBWdnZ3x8fDh+/DgANpuNadOmsX//fsxmM4cPH75sXHv27CEhIQGAzp078+uvv1JYWAjAQw89hIuLC15eXnh5eVFQUGDEeaUuTqI1aNCAtm3bGsfr16/no48+wmazcfLkSQ4ePEiLFi0A6Nq1qzHW4uJi3N3dgfOJutOnT1O7dm3mzp3Lrl27MJvN5Ofnc+rUKerVq3dV8YmIiIiIiIhIzaWEnVSbf/3rX3z11Vf88MMPmEwm7HY7JpOJV155BShfDMFisWC32y/pw9nZGZPJBJz/FtuFe8xms9F++fLl1K1bl9TUVMrKyvD3979sbBWtSrvwnP+My2azXemQAbDb7Rw4cICmTZsCUKdOHePasWPHWLZsGatXr+aOO+5gwoQJnDt3rtx4/3OsF45tNhvp6elYrVaSk5NxdnYmODi43P0iIiIiIiIicvPTllipNhs2bCAiIoLNmzfzxRdfsHXrVho1alTh1tf/RmFhIfXq1cNsNpOammok8tzc3Dhz5kyF9wQEBJCWlgac/56ep6ensZqtMjExMeTn51fZprS0lDlz5nDXXXcZq+YudubMGWrXrs1tt93GqVOn+N///d8rGaKhsLAQb29vnJ2d+eqrr4xVhiIiIiIiIiJy69AKO6k2GRkZPPPMM+XOde/enfT0dEJDQ6/Zc/r378+oUaP49NNPCQwMNFa0+fr6YrFY6N27N1FRUbRs2dK4Z+TIkUycOJGwsDBq167NrFmzqnxGWVkZR48e5Y477qjw+ssvv4yLiwslJSX85S9/YeHChRW2a9GiBa1ataJXr140btyY+++//6rGGhYWxogRI4zxXFjFd7nYq6oEa7OX4GRxqfS6iIiIiIiIiFxfJoe+WC9yWQcOHGDNmjVMnDjxRody1bKysmjXrt2NDkNuQbm5ueUS4SLXit4tqQ56r6S66N2S6qJ3S6qD3quap7LfRFtiRa6Aj4/PTZmsg/Lf5KuIzV5ynSIRERERERERkSuhLbF/MIsWLWLdunWYzWbMZjPTpk2jTZs2FbbNyckhNTWVV1999ZJru3fvZurUqTg5ObF06VKmT5/O/Pnzq3x2y5Yt8fHxwWazYbFYiIyMJCYmBrO5ZuSNr2ZubiZms5m4D3tUev3VJyrfLisiIiIiIiIi158Sdn8gWVlZbNmyhZSUFFxcXLBarZSWllba3s/PDz8/vwqvpaWlMWTIEPr06QNw2WQdgKurK6mpqQAUFBQQGxtLYWEho0ePLtfOZrPh5HR9X82rnRsRERERERERkepSM5Y2yXVx8uRJPD09jS2SXl5e3HnnnQBkZ2fTr18/evfuTXR0NEVFRWRmZjJ8+PBL+vn444/59NNPSUxMJDY2lry8PB577LGrisXb25vXX3+d999/H4fDQXJyMqNHj+a5555jyJAhnDlzhpiYGCIjIwkLC+Pzzz8HIC8vj549ezJ58mQee+wxYmNj2blzJ/369aN79+5kZ2eXG09ERAT9+vXjp59++t1zExwcjNVqBc6vOhw4cCAAX3/9NeHh4YSHhxMREWHM2VNPPcULL7xAaGgoU6ZMoaysDIDt27fzxBNPEBkZyejRo40KtsHBwcyfP98Y68GDByvtH+Dvf/87ffr0ISws7IoSpSIiIiIiIiJyc9EKuz+QoKAgEhMT6dGjB507dyY0NJSOHTtSUlLC2LFjiY+Px9/fn6KiIlxdXSvtp2/fvuzZs4eHH36Ynj17kpeX97viady4MWVlZRQUFADw7bffkpaWhoeHBzabjcTERNzd3bFarTzxxBN07doVgKNHjzJv3jyaN29OdHQ06enprFq1ik2bNrF48WIWLlxI06ZNWblyJU5OTuzcuZP4+HgSEhKuem6qsmzZMqZMmUL79u05c+YMtWrVAs4nCz/55BMaNGjAsGHD2LhxIx07dmTRokUkJSVRp04dli5dSlJSEiNHjgTA09OTlJQU3n//fZYtW8b06dMr7H/79u0cOXKE1atX43A4GDFiBLt27SIgIOB3/QYiIiIiIiIiUvMoYfcH4ubmRnJyMrt37yYzM5OxY8cSGxvLfffdR7169fD39wfA3d39usV0cZHioKAgPDw8jPNz585l165dmM1m8vPzOXXqFACNGjXC19cXgGbNmtG5c2dMJhO+vr4cP34cgMLCQsaPH8+RI0cwmUyX3d5a2dxERUVVes/999/PrFmzCAsLo3v37ri5uQHg7+9P48aNAejVqxd79uyhVq1a/Pjjjzz55JMAlJaW0rZtW6Ov7t27A9C6dWs+++yzSvvfsWMHO3bsICIiAoDi4mIOHz6shJ2IiIiIiIjILUQJuz8Yi8VCYGAggYGB+Pj4sHbtWlq1aoXJZKryvqFDh3Lq1Clat27N9OnTr0ksx44dw2Kx4O3tDUDt2rWNa+np6VitVpKTk3F2diY4OJhz584B5auems1m49hkMmG32wGYN28egYGBJCYmkpeXx6BBgy4bT0VzExUVhcViMRKLF2IAePbZZ3nooYfYunUrjz/+OElJSUYcFzOZTDgcDoKCgpg7d26Fz3Z2djbGc2EMFfXvcDh49tln6dev32XHIyIiIiIiIiI3J33D7g/kp59+4vDhw8Zxbm4uDRo0oGnTppw4ccL4/ltRURE2m63cve+88w6pqamXTdbl5+cTExNz2VisVitTp07lqaeeqjBZWFhYiLe3N87Oznz11VfGyrkrVVhYaHyDLiUl5bLxVTY3AA0bNmTv3r0AbNy40Whz9OhRfH19efbZZ2ndujWHDh0Czm+JPXbsGGVlZaxfv5727dvTtm1bvvnmG44cOQLAb7/9ZrSvTEX9P/DAA6xZs8b4/l1+fr6xpVhEREREREREbg1aYfcHUlxcTFxcHKdPn8ZisfDnP/+ZadOm4eLiQnx8PHFxcZw9exZXV1djtdjVOnHiRKUVXs+ePUt4eDg2mw2LxUJ4eDhPP/10hW3DwsIYMWIEUVFRtGzZkqZNm15VHMOGDWPChAkkJSXRqVOny8ZX2dwAjBw5ksmTJ7NkyRLatGlj3PPuu++SmZmJ2WymWbNmdOnShaysLNq2bcucOXM4cOAAHTp0oFu3bpjNZmbOnMlLL71ESUkJAGPGjKFJkyaVjqGi/l1cXDh48KCxwq5OnTq89dZbxirFipSVlfHqExsqvW6zl+Bkcan0uoiIiIiIiIhcXybHxR8RE/kvrVy5krvuussoEFHTVHd8mZmZLFu2jCVLllRL/79HVlYW7dq1u9FhyC0oNzeXli1b3ugw5Bakd0uqg94rqS56t6S66N2S6qD3quap7DfRlli5pgYMGPBfJ8NOnjzJ2LFjCQkJITQ0lGeeeeay20evZXzBwcFYrdbf/YzCwkJ8fX3Ztm3bZdsmJyeTn59vHE+ePJkff/zxdz+7Ihd/868ipfaSa/o8EREREREREfnvaEus1CgOh4ORI0cSERFBfHw8cD7bXFBQUOX20ZoiMDDQqP6akZHBgw8+WGX7lJQUmjdvbnxv71oV9LiY2WzmldU9K73+ZvSn1/yZIiIiIiIiIvL7KWEnNcpXX32Fk5MTTz75pHHuwtJQh8PBm2++ybZt2zCZTIwYMYLQ0FAyMzNJSEjA29ub/fv3061bN3x8fHjvvfc4d+4ciYmJ3H333Uahi59//hmASZMm0b59e/71r38RGxuL1WrF39/fqAj79ttv4+npaRSpiI+Px9vbu8qKsw6Hgw0bNpCUlET//v05d+4ctWrVAuB//ud/SEtLw2Qy0aVLF1q3bs3evXt5+eWXcXV15cMPP+SZZ57hlVdewc/Pj3Xr1rFkyRIcDgcPPfQQ48aNA6Bdu3YMGjSIzZs34+rqysKFC6lbt+61/zFERERERERE5IbQllipUX744Qfuu+++Cq9t3LiR/fv3k5qaSlJSEm+++SYnTpwAYP/+/UyePJn09HRSU1M5fPgwq1evJjo6mhUrVgDnV6/FxMSwZs0aEhISePXVVwFITEzk/vvvZ+3atQQHBxsJvejoaNauXQucL9yQkZFBWFhYlfHv2bOHRo0acffddxMYGMjWrVsB2Lp1K5s2beKjjz4iLS2NYcOG0bNnT1q3bs3s2bNJTU3F1dXV6Cc/P5/Zs2fz7rvvsnbtWnJycvj888+B8wUy2rRpQ1paGh06dOCjjz76vdMtIiIiIiIiIjWQVtjJTWPPnj306tULi8VC3bp1CQgIICcnB3d3d/z8/Khfvz4Ad999N0FBQQD4+PiQmZkJwM6dO8t9H66oqIiioiJ27drFggULAHj44Ye54447AGjUqBEeHh58//33nDp1ilatWuHp6VlljBkZGfTq1QuA0NBQUlNT6d69O19++SVRUVHUrl0bAA8Pjyr7ycnJoWPHjnh5eQHnq+bu2rWLkJAQnJ2deeSRRwBo3bo1O3bsuPJJFBEREREREZEaTwk7qVGaN2/Ohg0bKrxWVUHjiwsrmM1m49hsNmO324Hzq+Q+/PDDcivZLqdv374kJydz6tQp+vTpU2Vbu93Oxo0b+eKLL1i8eDEOh4Nff/2VoqIiHA4HJpPpip9bFWdnZ6Ovi8cnIiIiIiIiIrcGbYmVGqVTp06UlJSU2+aZnZ3N119/TUBAAOvXr8dut2O1Wtm9ezf+/v5X3PcDDzzAypUrjePc3FwAAgICSE9PB85vXf33v/9ttAkJCWHbtm3k5OTwwAMPGOd79ry0iMPOnTtp0aIFW7du5YsvvmDz5s10796dzz//nKCgINasWcNvv/0GwK+//gqAm5sbZ86cuaQvf39/du3ahdVqxW63k5GRQUBAwBWPVURERERERERuXkrYSY1iMplYsGABO3bsICQkhF69erFgwQLq169vFJMIDw8nJiaGcePGUa9evSvue/Lkyezdu5ewsDBCQ0NZtWoVAC+88AK7d+8mMjKSHTt20KBBA+MeFxcXAgMDefTRR7FYLABYrdYKV/tlZGQQEhJS7lz37t1Zt24dXbp0ITg4mD59+hAeHs6yZcsAiIyMZOrUqYSHh3P27Fnjvvr16/PSSy8RExNDeHg4rVq1uqRvEREREREREbk1mRxV7TMU+YMrKysjMjKSefPmcc899wCwefNmjh07VmW12Jpk3759lRbyACi1l+Bscan0ukhlcnNzjSrOItec2FyUAAAgAElEQVSS3i2pDnqvpLro3ZLqondLqoPeq5qnst9E37ATqcSPP/7I8OHD6datm5GsA4yCDzeLkpKSKq8rWSciIiIiIiJSs9zSW2JPnjzJ2LFjCQkJITQ0lGeeeYZDhw5dt+cHBwdjtVp/9/3ff/89vr6+bNu2rcp2ixcv/t3PSEhI4MEHHyQ8PNz47/Tp09XyvOXLlxvfcKvK5MmTy1VzvZ4yMzP55ptvAGjWrBmbNm1iwoQJFbbNzs7mqaeeokePHvTs2ZPJkydfdnzt2rUDIC8vz/huXnW7uCBHRUrtVSf0REREREREROT6umVX2DkcDkaOHElERATx8fHA+WWGBQUFNGnS5AZHd2XWrVtH+/btycjI4MEHH7zkusPhwOFwsGTJEp577rnf/ZzBgwczdOjQK27/e55nt9t577336N27N7Vr166y7fTp06+q72vp66+/pk6dOtx///1Vtjt16hQvvvgic+fOpV27djgcDjZs2MCZM2cuOz6A48ePs27dOsLCwq4qPrvdbnxL70qZzWaeTrm0SMYFSZGfXlV/IiIiIiIiIlK9btmE3VdffYWTkxNPPvmkce7CnmCHw8Gbb77Jtm3bMJlMjBgxgtDQUDIzM0lISMDb25v9+/cbRQ7ee+89zp07R2JiInfffTdWq5WpU6fy888/AzBp0iTat2/Pv/71L2JjY7Farfj7+xuFCd5++208PT2JiYkBID4+Hm9v7yq/gXYhAZSUlET//v05d+4ctWrVIi8vj2eeeYbAwEC+/fZbWrZsydmzZwkPD6dZs2a8/vrrjBkzhn/+85+UlZXx/PPPExoaetXzl5yczBdffMFvv/3GsWPHCAkJ4ZVXXmH27NnlnjdnzhxSU1NZsWIFpaWltGnThqlTp2KxWGjXrh2DBw9m+/btPPTQQ5w4cYKYmBg8PDxYsWIFU6dOJScnh3PnztGjRw9Gjx4NwMCBA3nllVfw8/OjXbt2DBo0iM2bN+Pq6srChQupW7cuEyZMoFatWvz000/8/PPPzJw5k5SUFL799lvatGnDrFmzANi+fTsJCQmUlJTQuHFjZs6ciZubG8HBwURERLB582ZsNhtvv/02tWrV4oMPPsBsNpOWlsZf//pXOnToUOH8vP/++0RERBgr5kwmk1E5NiEhgTp16hhJ0Mcee4zFixfTqFEj4/45c+Zw8OBBwsPDiYyM5Pbbb2fv3r1MmTIFgOHDhzNkyBACAwPLzeP48eM5fvx4hfMtIiIiIiIiIreGW3ZL7A8//FDph/Y3btzI/v37SU1NJSkpiTfffJMTJ04AsH//fiZPnkx6ejqpqakcPnyY1atXEx0dzYoVK4DzK8BiYmJYs2YNCQkJvPrqqwAkJiZy//33s3btWoKDg42EXnR0NGvXrgXOFzHIyMi47MqqPXv20KhRI+6++24CAwPZunWrce3QoUNERESwdu1aZs6ciaurK6mpqcyZM4dt27ZRv3590tLSWLduXYUr8/7T8uXLje2wAwcONM7n5uby9ttvk56ezvr16/nll194+eWXyz3v4MGDrF+/nlWrVpGamorZbDa2ehYXF9O8eXM+/vhjRo4cSf369Xn33XeNeRw7dizJycmkpaWxa9cu9u/ff0lsxcXFtGnThrS0NDp06MBHH31kXDt9+jTvvfceEydO5LnnnmPw4MFkZGRw4MABcnNzsVqtLFq0iKSkJFJSUmjdujVJSUnG/Z6enqSkpNCvXz+WLVtGo0aN6NevH4MHDyY1NbXSZB1U/X5didjYWDp06EBqaiqDBw+usu3F8+jp6VnpfIuIiIiIiIjIreGWXWFXlT179tCrVy8sFgt169YlICCAnJwc3N3d8fPzo379+gDcfffdBAUFAeDj40NmZiYAO3fuLPeNtaKiIoqKiti1axcLFiwA4OGHH+aOO+4AoFGjRnh4ePD9999z6tQpWrVqhaenZ5UxZmRk0KtXLwBCQ0NJTU2le/fuADRo0IC2bdtWeJ+Pjw9vvPEGb731Fo888kiVSacLKtsS27lzZ2677TYA7r33Xo4fP85dd91Vrs2XX37J3r17iY6OBuDs2bN4e3sDYLFY6NGjR6XPXb9+PR999BE2m42TJ09y8OBBWrRoUa6Ns7OzUeShdevW7Nixw7j2yCOPYDKZ8PX1pW7duvj6+gLnvz13/Phx/vnPf/Ljjz8aqyxLS0vLzduF+WzdujWfffbZZefpRrl4HquabxERERERERG5NdyyCbvmzZuzYcOGCq9d2KpakYs/0G82m41js9mM3W4Hzq+S+/DDD3F1db3iePr27UtycjKnTp2iT58+Vba12+1s3LiRL774gsWLF+NwOPj1118pKioCoE6dOpXe26RJE5KTk9m6dStz5swhKCiIkSNHXnGcF7t4LiwWizH+izkcDiIjI4mNjb3kWq1atSrdqnns2DGWLVvG6tWrueOOO5gwYQLnzp27pJ2zszMmkwko/xtcHJ/JZLrkd7PZbJjNZoKCgpg7d26FMTg7O1fY75Vo1qwZ+/btIyQk5JJrFouFsrIy47iicV3NPRfPY1XzLSIiIiIiIiK3hlt2S2ynTp0oKSkpt4UyOzubr7/+moCAANavX4/dbsdqtbJ79278/f2vuO8HHniAlStXGse5ubkABAQEGNsTt27dyr///W+jTUhICNu2bSMnJ4cHHnjAOH/hu2cX27lzJy1atGDr1q188cUXbN68me7du/P5559XGI+TkxOlpaUA5OfnU7t2bcLDwxk6dCjff/89cP6baddqFdnFz+vcuTMbNmygoKAAgF9//ZXjx49XeJ+bmxtnzpwBMIoz3HbbbZw6dYr//d//vSaxXaxt27Z88803HDlyBIDffvvtslWCL44R4LPPPmPOnDmXtBswYABr167lu+++M86lpqZy8uRJGjZsaMz7vn37yMvLu+xzGjZsyP79+ykrK+OXX34hOzu7wviuZr5FRERERERE5OZ0y66wM5lMLFiwgBkzZrB06VJq1apFw4YNmTRpEgEBAWRlZREeHo7JZGLcuHHUq1ePn3766Yr6njx5MtOmTSMsLAy73U6HDh2YNm0aL7zwArGxsURGRhIQEECDBg2Me1xcXAgMDOT22283VktZrdYKV/tlZGRcsnKre/furFq1qsItro8//ji9e/emVatWRERE8Oabb2I2m3FycuK1114D4MCBAwQHB1c4nuXLl5OWlmYcJyYmVjn+i583Z84cxowZw5AhQygrK8PZ2ZkpU6bQsGHDCu975plnqFevHitWrKBVq1b06tWLxo0bX7Yq6+/h5eXFzJkzeemllygpKQFgzJgxVVYJfuSRRxg9ejSbNm3ir3/9K0ePHsXd3f2SdnXr1mXu3Lm88cYbFBQUYDabCQgIoHv37vTo0YPU1FTCw8Px8/PjnnvuueR+X19fLBYLvXv3JioqipiYGBo2bEhYWBjNmzev9Pt4zZo1u+L5vqCsrKzKSrCl9hKcLS6VXhcRERERERGR68vkqGp/qFwzZWVlREZGMm/ePCOBs3nzZo4dO1ZltdhrZejQobzzzjvV/pxbzcsvv8ykSZPw8vK60aH8bllZWUY1W5FrKTc316i+LXIt6d2S6qD3SqqL3i2pLnq3pDrovap5KvtNbtkVdjXJjz/+yPDhw+nWrVu51VYXiilcD0rW/T6zZ8++0SH81y7+vt/1VGIvwUUr90RERERERESumhJ210GzZs3YtGnTjQ5DbrBFixaxbt06zGYzZrOZadOm0aZNm0va5eTkkJqayquvvnrJtd27dzN16lScnJxYunQp06dPZ/78+VU+12w282jqk9dsHFdqffiq6/5MERERERERkVuBEnYi10FWVhZbtmwhJSUFFxcXrFarUbjjP/n5+eHn51fhtbS0NIYMGWJUGr5csk5EREREREREbj63bJVYkZrk5MmTeHp6GttTvby8uPPOO8nOzqZfv3707t2b6OhoioqKyMzMZPjw4Zf08fHHH/Ppp5+SmJhIbGwseXl5PPbYY9d7KCIiIiIiIiJSzbTCTuQ6CAoKIjExkR49etC5c2dCQ0Np27YtY8eOJT4+Hn9/f4qKinB1da20j759+7Jnzx4efvhhevbsSV5e3nUcgYiIiIiIiIhcL0rYiVwHbm5uJCcns3v3bjIzMxk7dizPPfcc9erVw9/fHwB3d/cbHKWIiIiIiIiI1ARK2IlcJxaLhcDAQAIDA/Hx8eH999/HZDJVec/QoUM5deoUrVu3Zvr06dcpUhERERERERG5kZSwE7kOfvrpJ8xmM/fccw8Aubm53HvvvWzbto3s7OxKt8S+8847NyBaEREREREREbmRlLATuQ6Ki4uJi4vj9OnTWCwW/vznPzNt2jSioqKIi4vj7NmzuLq6kpSUdM2fXVZWxvrwVde838spsZfgYnG57s8VERERERERudkpYSdyHbRu3ZoPPvjgkvNeXl589NFH5c5d2DZbkVmzZhl/N2rUiHXr1l322SUlJVcZ7bWhZJ2IiIiIiIjI76OEHdCyZUt8fHyw2WxYLBYiIyOJiYnBbDbf6NAAaNeuHVlZWcZxcnIye/fuZcqUKTcspszMTJ5//nkaN27M2bNneeSRRxg/fvwNi+daWL16Ne+++y4ADoeDMWPGEBIScoOj+u+5uFSdOCuxl+Jicb5O0YiIiIiIiIjI5ShhB7i6upKamgpAQUEBsbGxFBYWMnr06HLtbDYbTk4335T9Z9xXOo7LtevQoQNLlizh7NmzREREEBISQvv27a9JzNfbP//5TxYvXkxKSgq33XYbZ86cwWq13uiwrgmz2cyja8dWen19RPx1jEZERERERERELufmyz5VM29vb15//XWio6MZNWoUKSkpbNmyhZKSEoqLi1m0aBHPP/88p0+fxmaz8eKLLxISEkJeXh7Dhg2jffv2fPfdd/j6+tKnTx/mz5+P1Wpl9uzZ+Pv7k52dzYwZM4xvls2YMYOmTZv+7niPHz/OpEmTsFqteHl5MXPmTBo0aMCECRO44447+P7777nvvvv49ddfyx2Hh4czdepUfvvtN+6++25mzJjBHXfcwcCBA2nXrh3ffPMNwcHBDBky5LIxuLq60rJlS/Lz8wFYt24dS5YsweFw8NBDDzFu3Djg/ErB/v378+WXX3L77bfz0ksv8dZbb/Hzzz8zadIkunbtSl5eHq+88gq//fYbAH/961+5//77yczMZMGCBXh6enLgwAHuu+8+Zs+ejclkMua0uLgYFxcXli9fTu3atZk9ezZff/01JSUlPPXUU/Tr16/SMRQUFODm5kadOnUAcHNzw83NDYCBAwfyyiuv4Ofnh9VqJTo6mi+++IIffviBiRMnUlpaSllZGQkJCTg5OTFs2DDatGnD999/T5MmTXjjjTeoXbs2e/fuZdasWRQXF+Pp6cnMmTOpX78+AwcOxN/fn8zMTAoLC5k+fTodOnSosP977rmH1NRUVqxYQWlpKW3atGHq1KlYLJbf/Q6JiIiIiIiISM2ihF0FGjduTFlZGQUFBQB8++23pKWl4eHhgc1mIzExEXd3d6xWK0888QRdu3YF4OjRo8ybN4/mzZsTHR1Neno6q1atYtOmTSxevJiFCxfStGlTVq5ciZOTEzt37iQ+Pp6EhIQq4zl79izh4eHG8b///W+Cg4MBeP3114mIiCAyMpLVq1cTFxfHwoULATh8+DDLly/HYrEwYcKEcsdhYWH89a9/pWPHjsybN48FCxYwefJkAE6fPs3KlSuveL7+/e9/c+TIEQICAsjPz2f27NkkJydz++23M2TIED7//HNCQkIoLi6mY8eOjBs3jhdeeIG3336bZcuWcfDgQcaPH0/Xrl3x9vYmKSmJWrVqcfjwYV566SWSk5MB+P7778nIyKB+/fo8+eST7NmzB39/f8aOHUt8fHy5SqurV6/mtttuY82aNZSUlNCvXz+CgoJo3LhxhWNo0aIFdevWpWvXrnTu3Jlu3boZc1yZDz74gEGDBtG7d29KSkooKyvj1KlTHDp0iOnTp9O+fXsmTpzIP/7xDwYNGmT8Nl5eXnzyySfEx8czc+ZMAOx2O6tXr2br1q0sWLCA5cuXV9j/wYMHWb9+PatWrcLZ2ZnXXnuN9PR0IiIirvj3EhEREREREZGaTQm7SjgcDuPvoKAgPDw8jPNz585l165dmM1m8vPzOXXqFHC+CICvry8AzZo1o3PnzphMJnx9fTl+/DgAhYWFjB8/niNHjmAymSgtLb1sLBdv2YX//w07gKysLCPhFx4ezltvvWW069mzZ7mVVxeOCwsLKSwspGPHjgBERkby4osvGu1CQ0OvaI52795NWFgYhw4d4tlnn6VevXp8/vnndOzYES8vLwDCwsLYtWsXISEhODs706VLFwB8fHxwcXHB2dkZHx8fY35sNhvTpk1j//79mM1mDh8+bDzP39+fP/3pT8D5BNvx48e57bbbqFevHv7+/gC4u7sDsGPHDv7v//6PDRs2AOfn/ciRI5Um7CwWC3//+9/Jycnhyy+/ZObMmezbt49Ro0ZVOv62bduyePFi/vnPf9K9e3fuueceAO666y5ja3Dv3r1ZsWIFDz74IAcOHODpp58GzldurVevntFXt27dALjvvvuMuaio/y+//JK9e/cSHR0NnE/ment7X/a3EhEREREREZGbhxJ2FTh27BgWi8VIhNSuXdu4lp6ejtVqJTk5GWdnZ4KDgzl37hxQ/uP+ZrPZODaZTNjtdgDmzZtHYGAgiYmJ5OXlMWjQoGsau8lkMv6+OO6Kjitzpe0ufMPu0KFD9O/f30g6VcbZ2dmI7+L5MZvNxvwsX76cunXrkpqaSllZmZGIg/Lza7FYsNvtOByOcmO+wOFw8Oqrr/Lggw9e0Vjg/Nz5+/vj7+/PX/7yFyZNmsSoUaOwWCxGAvfiiqthYWG0adOGLVu2MHToUOLi4mjcuPEl8ZhMJhwOB82bN+fDDz+s8NkVzUVF/TscDiIjI4mNjb3icYmIiIiIiIjIzaVmlEGtQaxWK1OnTuWpp56qMBFUWFiIt7c3zs7OfPXVV8ZqqCtVWFjInXfeCUBKSopxPj8/n5iYmKuOt127dmRkZADnk4lXUvThtttu4/bbb2f37t0ApKamEhAQUGHbzz77jDlz5lTZX5MmTRg+fDj/8z//g7+/P7t27cJqtWK328nIyKi074oUFhZSr149zGYzqampRvKqMk2bNuXEiRNkZ2cDUFRUhM1m44EHHmDVqlXGCsZDhw5RXFwMnF9p+J/y8/PZt2+fcbx//34aNGgAQMOGDY0VjZ9++qnR5tixYzRu3JhBgwYRHBzM//3f/wHw888/G1V9MzIyaN++PU2aNMFqtRrnS0tL+eGHH6ocW0X9d+7cmQ0bNhjbtX/99derfgdFREREREREpGbTCjv+/zfibDYbFouF8PBwY+vifwoLC2PEiBFERUXRsmXLqy4YMWzYMCZMmEBSUhKdOnUyzp84ceJ3VaB99dVXmTRpEu+8845RdOJKvPHGG0bRicaNG1d639GjR41tplXp168f77zzDufOneOll14iJiYGh8NBly5dCAkJueLx9O/fn1GjRvHpp58SGBhoFIGojIuLC/Hx8cTFxRmFPJKSkujbty/Hjx8nKioKh8OBp6cnCxcuxGq1ltvufIHNZuONN97gxIkT1KpVCy8vL/72t78BMGTIEMaMGUNaWhqBgYHGPZ988glpaWk4OTlRt25dXnjhBYqKirj33ntJSUlhypQp3HPPPTz55JO4uLgwf/584uLiKCwsxG63ExMTQ/PmzSsdW0X9e3h4MGbMGIYMGUJZWRnOzs5MmTKFhg0bVtpPWVlZlZVgS+yluFicq5xnEREREREREbl+TI6Kshdy3a1cuZK77rrLKGBRU7z88stMmjTJ+CbdzW7z5s0cO3bsmm9FviAvL4/nnnuOdevWVUv/v0dWVhbt2rW70WHILSg3N5eWLVve6DDkFqR3S6qD3iupLnq3pLro3ZLqoPeq5qnsN9EKuxpiwIABNzqECs2ePftGh3BNPfLIIzc6hOvu4m//VUQr7ERERERERERqFiXsblEtW7bEx8fH2OYbGRlJTEwMZnPN+GzhokWLWLduHWazGbPZzLRp02jTps2NDuu/NnHixHLbi2vCijuz2UxoytRKr38S+bfrGI2IiIiIiIiIXI4SdrcoV1dXUlNTASgoKCA2NpbCwkJGjx5drp3NZvtd3877b2RlZbFlyxZSUlJwcXHBarUaxSH+6P7z97jS3+dG/I4iIiIiIiIiUj30L/w/AG9vb15//XWio6MZNWoUKSkpbNmyhZKSEoqLi1m0aBHPP/88p0+fxmaz8eKLLxISEkJeXh7Dhg2jffv2fPfdd/j6+tKnTx/mz5+P1Wpl9uzZ+Pv7k52dzYwZM4yiDzNmzKiyGMfJkyfx9PQ0tmpe/H284OBgVq9ejZeXFzk5Obz55pusWLGCr7/+munTpwNgMplYuXIl+/btY/78+Xh4eHDo0CE6dOjAa6+9htlsZvv27SQkJFBSUmIU1XBzcyM4OJiIiAg2b96MzWbj7bff5t57762wf3d3d/7+97+zfv16SkpK6Nat2yUJz6tx7tw5XnvtNfbu3YvFYmHChAl06tSJ5OTkcr9HREREueP58+czadIkjh07Ru3atZk2bRotWrQgISGBEydOcPz4cTw9PS9bzVdEREREREREbg5K2P1BNG7cmLKyMgoKCgD49ttvSUtLw8PDA5vNRmJiIu7u7litVp544gmj+MXRo0eZN28ezZs3Jzo6mvT0dFatWsWmTZtYvHgxCxcupGnTpqxcuRInJyd27txJfHw8CQkJlcYSFBREYmIiPXr0oHPnzoSGhtKxY8cq41+2bBlTpkyhffv2nDlzhlq1agGQnZ3NJ598QoMGDRg2bBgbN26kY8eOLFq0iKSkJOrUqcPSpUtJSkpi5MiRAHh6epKSksL777/PsmXLmD59eoX9b9++nSNHjrB69WocDgcjRoxg165dBAQEVBnryy+/jKurKwClpaXGNuT3338fgPT0dA4ePMjQoUPZsGHDJb9HcnJyuePXX3+dVq1asXDhQr788kvGjx9vrJ7ct28f//jHP4zniYiIiIiIiMjNTwm7P5D/x969h0VZrY0f/86MIIoliOWrQqUpRBpKqGC4tY14osYBJLVM0WJTnqBEDTW11MDSNFA8XSZauNU2B5HQnabpm5p4wgNG2zxwzFCZilEEnIHfH/54XjCOJoru+/NXzzPrWXOvZ1ZeF/e11rorFgR2d3fHyspKub9kyRKOHDmCWq0mLy+Pq1evAmBra4uDgwMAnTp1onfv3qhUKhwcHMjNzQXAYDDw3nvvkZmZiUqlqnV7q6WlJfHx8Rw9epSUlBTeffddQkJC8PX1rfaZ559/noULF6LVahk4cCCWlpYAODk5YWdnB8BLL73EsWPHaNq0KefOnePVV18FbiXNunfvrvQ1cOBAALp27cquXbuq7f/AgQMcOHAAb29vAAoLC8nIyKg1Ybd48WKee+454P/OsAM4duyYUlzk6aefpl27dly8ePFPv8ft18eOHVMSoL179+b333/HYDAAt1YkSrJOCCGEEEIIIYR4uEjC7r9EdnY2Go0GGxsbAJo1a6Z8lpSUhF6vJz4+HjMzMzw8PCguLgYqVxhVq9XKtUqlwmQyARAREYGrqytRUVHk5OQwZsyYWuPRaDS4urri6uqKvb09W7duxdfXF41GoyQWy2MACAwMpF+/fuzbt4/hw4cTHR2txFGRSqWirKwMd3d3lixZUuV3m5mZKeMpH0NV/ZeVlREYGMjIkSNrHU9dVEyY3q7i73H7dVXPlY/79ueEEEIIIYQQQgjx4GscJUNFg9Lr9cydO5dRo0b9KcEFt1bI2djYYGZmxqFDh5SVc3VlMBho06YNAAkJCcr9vLw8/P39/9T+woULZGRkKNfp6em0a9cOgPbt25OWlgbAzp07lTZZWVk4ODgQGBhI165dlZVpp06dIjs7m9LSUnbs2IGLiwvdu3fn+PHjZGZmAnDjxg2lfXWq6r9Pnz7ExcVx/fp1ZTzlW4r9/f3Jy8ur13vq2bMnSUlJAFy8eJFLly7VeNZfxee2bdsGQEpKCtbW1rRo0aJe3y2EEEIIIYQQQogHh6ywe0gVFRWh0+kwGo1oNBp0Oh3jxo2rsq1Wq2X8+PH4+vri6OhYpyRSRQEBAYSGhhIdHY2bm5ty//Lly1VWLi0sLGTBggUUFBSg0Wh48sknmTdvHgCTJk1i1qxZrF69mm7duinPbNiwgZSUFNRqNZ06daJv376kpqbSvXt3Pv30U86ePUuPHj0YMGAAarWa8PBwpkyZQklJCQDvvPMOHTp0qHYMVfVvbm7O+fPnlRV2zZs3Z9GiRVhbW5OVlUXLli3r9Z5ee+015s6di1arRaPREB4eXmkFY3UmTZrEjBkz0Gq1NGvWjIULF9bre0tLS9nu82G1n5eYbmKuMatXn0IIIYQQQgghhGg4qrKa9ukJ8RfExMTQtm1bpYDF3ZaSksK6detYvXp1g/RfnbNnzxIXF8eMGTPu6ffeqdTUVJydne93GOIhlJ6ejqOj4/0OQzyEZG6JhiDzSjQUmVuiocjcEg1B5lXjU91vIivsHmCOjo7Y29srq+h8fHzw9/dXqpLebwaDgU2bNvHZZ5+hVquZN29epVVzD6r58+dz+fJlDh06BMD48eMZPHhwvfpISUnBzMyM559/viFCrKS2VXwlJiPmGvmnQAghhBBCCCGEaCzkr/QHmIWFBYmJiQDk5+cTEhKCwWAgKCioUjuj0Vjl1tSGlJqayt69e0lISMDc3By9Xl9r9dj6Ki9acT9UrAR7Jw4fPkzz5s3vScJOrVbjlfBxtZ9v93mvwWMQQgghhBBCCCFE3UnC7iFhY2PD/Pnz8edeBMEAACAASURBVPPzY/LkySQkJLB3715KSkooLCxk5cqVTJgwgYKCAoxGI8HBwXh6epKTk0NAQAAuLi6cPHkSBwcHhg0bRmRkJHq9nsWLF+Pk5MSpU6cICwujqKgICwsLwsLCajzr7sqVK1hbWyuru1q1aqV85uHhQWxsLK1ateL06dN88sknfPnllxw+fJiPPvoIuFUFNSYmhjNnzhAZGYmVlRUXL16kR48efPDBB6jVavbv38+yZcsoKSnBzs6O8PBwLC0t8fDwwNvbm++++w6j0chnn33G008/XWX/LVq0YO3atezYsYOSkhIGDBjwp4RnXcydO5fTp09TXFzMoEGDlD6qiqVp06Zs3rwZtVrNtm3bmD17NgUFBaxcuZKbN29iZWXF4sWLad26dZUxf/jhhwwaNAhPT08AQkJC8PLyarCtx0IIIYQQQgghhLi3JGH3ELGzs6O0tFSpZHrixAm2bduGlZUVRqORqKgoWrRogV6vZ8SIEUqCJysri4iICDp37oyfnx9JSUls2rSJ3bt3s2rVKlasWEHHjh2JiYmhSZMmHDx4kKVLl7Js2bJqY3F3dycqKopBgwbRu3dvvLy86NWrV43xr1u3jjlz5uDi4sL169dp2rQpcKsS7Pbt22nXrh0BAQHs3LmTXr16sXLlSqKjo2nevDlr1qwhOjqaSZMmAWBtbU1CQgIbN25k3bp1fPTRR1X2v3//fjIzM4mNjaWsrIzx48dz5MgRevbsWWOsU6dOxcLCAoD169fz7rvvYmVlhclkYuzYsfz0008888wz1cYycuRImjdvzptvvgnAH3/8wVdffYVKpeJf//oXa9euJTQ0tMqYX3nlFdavX4+npycGg4HU1FQ+/rj6FXRCCCGEEEIIIYR4sEjC7iFTsYaIu7s7VlZWyv0lS5Zw5MgR1Go1eXl5XL16FQBbW1scHBwA6NSpE71790alUuHg4EBubi5w6zy69957j8zMTFQqVa3bWy0tLYmPj+fo0aOkpKTw7rvvEhISgq+vb7XPPP/88yxcuBCtVsvAgQOxtLQEwMnJCTs7OwBeeukljh07RtOmTTl37hyvvvoqADdv3qR79+5KXwMHDgSga9eu7Nq1q9r+Dxw4wIEDB/D29gZuVbDNyMioNWF3+5bYTZs28dVXX2E0Grly5Qrnz59XEnZVxXK7X3/9lXfffZcrV65QUlKCra1ttTH36tWLefPmkZ+fz86dOxk0aNA93/IshBBCCCGEEEKIhiN/5T9EsrOz0Wg02NjYANCsWTPls6SkJPR6PfHx8ZiZmeHh4UFxcTFQuSiBWq1WrlUqFSaTCYCIiAhcXV2JiooiJyeHMWPG1BqPRqNRzpmzt7dn69at+Pr6otFolMRieQwAgYGB9OvXj3379jF8+HCio6OVOCpSqVSUlZXh7u7OkiVLqvxuMzMzZTzlY6iq/7KyMgIDAxk5cmSt46lOdnY269atIzY2lpYtWxIaGlppXFXFcrsFCxYwduxY+vfvT0pKCsuXL6825qeffpqhQ4eSlJREcnIyYWFhdxy7EEIIIYQQQgghGp/GUU5U/GV6vZ65c+cyatSoPyW44NYKORsbG8zMzDh06JCycq6uDAYDbdq0ASAhIUG5n5eXh7+//5/aX7hwgYyMDOU6PT2ddu3aAdC+fXvS0tIA2Llzp9ImKysLBwcHAgMD6dq1KxcvXgRubYnNzs6mtLSUHTt24OLiQvfu3Tl+/DiZmZkA3LhxQ2lfnar679OnD3FxcVy/fl0ZT/mWYn9/f/Ly8mp9N9evX6dZs2Y88sgjXL16lf/93/+t9RlLS0vlO6Hy+926dWut78TX15cNGzYA0Llz51q/TwghhBBCCCGEEA8OWWH3ACsqKkKn02E0GtFoNOh0OsaNG1dlW61Wy/jx4/H19cXR0bHGghFVCQgIIDQ0lOjoaNzc3JT7ly9frnI7ZmFhIQsWLKCgoACNRsOTTz7JvHnzAJg0aRKzZs1i9erVdOvWTXlmw4YNpKSkoFar6dSpE3379iU1NZXu3bvz6aefcvbsWXr06MGAAQNQq9WEh4czZcoUSkpKAHjnnXfo0KFDtWOoqn9zc3POnz+vrLBr3rw5ixYtwtramqysLFq2bFnru3nmmWd49tlneemll7Czs6tT5de///3vBAUFsXv3bmbPns2kSZMIDg6mTZs2dOvWjZycnGpjBmjdujUdO3ZUCk8IIYQQQgghhBDi4aEqq3jomRD1FBMTQ9u2bRusQmlKSgrr1q1j9erVDdJ/dc6ePUtcXBwzZsy4p99bVzdu3ECr1ZKQkMAjjzxSY9szZ87QpUuXaj8vMRkx10juXtRfeno6jo6O9zsM8RCSuSUagswr0VBkbomGInNLNASZV41Pdb+J/JUu/pLXX3/9fofQIOzt7Rttsu7gwYPMnDmTsWPH1pqsA5QViNWRZJ0QQgghhBBCCNG4yF/qolG4cuUKYWFhnD59GnNzc9q3b8/MmTOVohUNzcPDg9jYWFq1anVHz5ZXtDWZTAwYMICJEydWKuZxN73wwgvs3bu3zu1ri0NW2AkhhBBCCCGEEI2L/JUu7ruysjImTZqEt7c3S5cuBW4tCc3Pz6/xTLrGZMOGDbRq1Yrr168zZ84cZs+ezccff1ypjclkQqPR3PPY1Go1L8VHVPt5sm/wPYxGCCGEEEIIIYQQtZGEnbjvDh06RJMmTXj11VeVe+X7t8vKyvjkk0/4/vvvUalUjB8/Hi8vL1JSUli2bBk2Njb89NNPDBgwAHt7e7744guKi4uJioriiSeeUKrn/vLLLwDMnDkTFxcXfvvtN0JCQtDr9Tg5OVF+lONnn32GtbW1Uvl26dKl2NjYMGbMmDqNxdLSkg8//JB+/frx+++/85///Ifly5fz+OOPk56ezvbt25kwYQK//vorxcXFjBkzhhEjRgDg7OzMa6+9xg8//MCjjz7KlClTWLRoEb/88gszZ86kf//+5OTkMH36dG7cuAHA7Nmz61TkQgghhBBCCCGEEA8O9f0OQIiff/652qIIO3fu5KeffiIxMZHo6Gg++eQTLl++DMBPP/3ErFmzSEpKIjExkYyMDGJjY/Hz8+PLL78E4KOPPsLf35+4uDiWLVvG+++/D0BUVBTPP/88W7duxcPDQ0no+fn5sXXrVgBKS0tJTk5Gq9XWazwtWrTA1taWzMxMAE6fPs0777zD9u3bAQgLCyM+Pp64uDi+/PJLfvvtN+BWZd1evXoRHx+PpaUln332GevWrSMqKorIyEgAbGxsiI6OJiEhgaVLl7JgwYJ6xSaEEEIIIYQQQojGT1bYiUbt2LFjvPTSS2g0Glq3bk3Pnj05ffo0LVq04LnnnuPxxx8H4IknnsDd3R24VTAiJSUFuFWg4dy5c0p/165d49q1axw5coTly5cD8OKLL9KyZUsAbG1tsbKy4scff+Tq1as8++yzWFtb1zvuisWXn3vuOezs7JTrL7/8kl27dgFw6dIlMjMzsba2xszMjL59+ypjMDc3x8zMDHt7e3JzcwEwGo3MmzePn376CbVaTUZGRr1jE0IIIYQQQgghROMmCTtx33Xu3Jlvvvmmys8qJr5uV7GYglqtVq7VajUmkwm4tUpuy5YtWFhY1DmeV155hfj4eK5evcqwYcPq/Fy5a9eukZuby1NPPcVPP/1E8+bNlc9SUlI4ePAgW7ZsoVmzZowePZri4mIAzMzMUKlUNY5n/fr1tG7dmsTEREpLS3Fycqp3fEIIIYQQQgghhGjcZEusuO/c3NwoKSnhq6++Uu6dOnWKw4cP07NnT3bs2IHJZEKv13P06NF6Jan69OlDTEyMcp2eng5Az549SUpKAmDfvn388ccfShtPT0++//57Tp8+TZ8+fZT7gwcPrvX7rl+/zocffoinp6eyaq8ig8FAy5YtadasGefPn+fEiRN1Hkv584899hhqtZrExEQlkSeEEEIIIYQQQoiHh6ywE/edSqVi+fLlhIWFsWbNGpo2bUr79u2ZOXMmPXv2JDU1FZ1Oh0qlYtq0aTz22GNcuHChTn3PmjWLefPmodVqMZlM9OjRg3nz5jFx4kRCQkLw8fGhZ8+etGvXTnnG3NwcV1dXHn30UaWqq16vr3G1n7+/P2VlZZSWljJgwAAmTJhQZbu+ffuyefNmtFotHTp0oHv37vV4U/Daa68xefJk/v3vf+Pq6lpp9V51SktLa6wEW2IyYq6RfwqEEEIIIYQQQojGQlVWUxZCiP9CpaWl+Pj4EBERwVNPPQXAd999R3Z2dp2rxTYmqampODs73+8wxEMoPT1dqegsxN0kc0s0BJlXoqHI3BINReaWaAgyrxqf6n4TWVYjRAXnzp3jrbfeYsCAAUqyDuDvf//7/QvqL6p41l99yeo7IYQQQgghhBDi3pO/xEWj4+joiL29PUajEY1Gg4+PD/7+/qjVDX/kYqdOndi9e3ed4isXFRWFra1tvb4nPj4ed3d32rRpc0dx1odarealuFV39GzysLfvcjRCCCGEEEIIIYSojSTsRKNjYWFBYmIiAPn5+YSEhGAwGAgKCqrUzmg00qTJvZ/CFeO7UwkJCXTu3PmeJOyEEEIIIYQQQgjxYJGEnWjUbGxsmD9/Pn5+fkyePJmEhAT27t1LSUkJhYWFrFy5kgkTJlBQUIDRaCQ4OBhPT09ycnIICAjAxcWFkydP4uDgwLBhw4iMjESv17N48WKcnJw4deoUYWFhFBUVYWFhQVhYGB07dqxXjNevX682hn/84x+4uLiQmppKmzZtWLFiBXv37iUtLY2pU6diYWHBli1bWLt2Ld999x3FxcU4Ozszb948VCoVX3zxBZs3b0aj0dCpUyc+/fRTBg8ezObNm2nVqhWlpaUMGjSILVu20KpVqwb6FYQQQgghhBBCCHEvScJONHp2dnaUlpaSn58PwIkTJ9i2bRtWVlYYjUaioqJo0aIFer2eESNG0L9/fwCysrKIiIigc+fO+Pn5kZSUxKZNm9i9ezerVq1ixYoVdOzYkZiYGJo0acLBgwdZunQpy5YtqzGeoqIidDodALa2tkRERFQbQ2ZmJkuWLGHBggUEBwfzzTffoNPp2LhxI9OnT+e5554D4PXXX2fSpEkATJs2je+++w4PDw/WrFnDnj17MDc3p6CgALVazdChQ9m2bRtjx47l4MGDPPPMM5KsE0IIIYQQQgghHiKSsBMPhIrFjN3d3bGyslLuL1myhCNHjqBWq8nLy+Pq1avArWSag4MDcOtsut69e6NSqXBwcCA3NxcAg8HAe++9R2ZmJiqVips3b9Yay+1bYm/evFljDOXVXrp06aJ87+1SUlJYu3YtRUVF/P7773Tu3BkPDw8cHByYOnUq/fv3x9PTE4Bhw4YxYcIExo4dS1xcHL6+vvV6l0IIIYQQQgghhGjcGv4UfyH+ouzsbDQaDTY2NgA0a9ZM+SwpKQm9Xk98fDyJiYm0bt2a4uJioHJ1VLVarVyrVCpMJhMAERERuLq68vXXX7Ny5UpKSkrqHV9dY9BoNMr3VlRcXMyHH35IZGQkSUlJDB8+XHl+zZo1vPbaa5w5cwZfX1+MRiNt27bFxsaGH374gZMnT9K3b996xyyEEEIIIYQQQojGSxJ2olHT6/XMnTuXUaNGoVKp/vS5wWDAxsYGMzMzDh06VO0KtuoYDAal8ENCQoJyPy8vD39//zr3Ud8YLC0tuX79OoCSnLO2tub69et88803AJSWlnLp0iXc3NyYNm0aBoOBwsJCAF555RWmTZvGkCFD0Gg0dR+wEEIIIYQQQgghGj3ZEisanfIz4oxGIxqNBp1Ox7hx46psq9VqGT9+PL6+vjg6Ota7YERAQAChoaFER0fj5uam3L98+XKdK9DeSQw+Pj7MnTtXKTrxyiuvoNVqad++vXKunclkYtq0aVy7do2ysjLGjh3Lo48+CoCHhwczZsyo03bY0tJSkoe9Xaex3K7EZMRcI/9MCCGEEEIIIYQQ95KqrOLhYEIIAGJiYmjbtq1SPKKxOX36NOHh4fzzn/+stW1qairOzs73ICrx3yY9PV05o1GIu0nmlmgIMq9EQ5G5JRqKzC3REGReNT7V/SaydOYh5ejoiL29vbJKzcfHB39/f9TqxrEL2tnZmdTUVOU6Pj6etLQ05syZc99iunHjBu+//z5nz56lrKyMRx55BDc3NywtLe9bTFVZs2YNmzZtYtGiRXVqX/EcvfqSFXZCCCGEEEIIIcS9V6e/xG/cuMG6deu4dOkSCxYsICMjg4sXL/L3v/+9oeMTd6hiJdP8/HxCQkIwGAwEBQVVamc0Guu89bMxuT3uuo6jpnZffPEFrVu35tNPPwXgwoULmJmZ3Z2A76LAwEACAwPr3F6tVvNy3Od39F1fD3vzjp4TQgghhBBCCCHEnatTpmbGjBl06dKFEydOAPA///M/BAcHS8LuAWFjY8P8+fPx8/Nj8uTJJCQksHfvXkpKSigsLGTlypVMmDCBgoICjEYjwcHBeHp6kpOTQ0BAAC4uLpw8eRIHBweGDRtGZGQker2exYsX4+TkxKlTpwgLC6OoqAgLCwvCwsLqfZZcRbm5ucycORO9Xk+rVq0IDw+nXbt2hIaG0rJlS3788Ue6dOnC77//Xulap9Mxd+5cbty4wRNPPEFYWBgtW7Zk9OjRODs7c/z4cTw8PHjjjTeq/N4rV67Qrl075bp8DDk5Obz99tt8/fXXAHz++ecUFhYyefJkvvjiCzZv3oxGo6FTp04sXbqUZcuWkZWVRV5eHr/++isBAQEMHz4cgLVr17Jjxw5KSkoYMGAAQUFB5OTk8I9//AMXFxdSU1Np06YNK1aswMLCosr+CwsLmT9/PmfPnsVkMjFp0iQ8PT3v+H0LIYQQQgghhBCicalTwi4rK4vPPvuM5ORk4NbqLTn67sFiZ2dHaWkp+fn5AJw4cYJt27ZhZWWF0WgkKiqKFi1aoNfrGTFihHJ2W1ZWFhEREXTu3Bk/Pz+SkpLYtGkTu3fvZtWqVaxYsYKOHTsSExNDkyZNOHjwoJK0qkl5YYlyf/zxBx4eHgDMnz8fb29vfHx8iI2NZcGCBaxYsQKAjIwM1q9fj0ajITQ0tNK1Vqtl9uzZ9OrVi4iICJYvX86sWbMAKCgoICYmpsaYhg0bxhtvvME333yDm5sbPj4+PPXUUzU+s2bNGvbs2YO5uTkFBQXK/f/85z989dVXFBYW4uPjQ79+/fj555/JzMwkNjaWsrIyxo8fz5EjR2jbti2ZmZksWbKEBQsWEBwczDfffINOp6uy/1WrVuHm5kZ4eDgFBQW88sorvPDCCzRv3rzGWIUQQgghhBBCCPFgqFPCztzcnKKiIlQqFXArifNXzsUS90fFJKu7uztWVlbK/SVLlnDkyBHUajV5eXlcvXoVAFtbWxwcHADo1KkTvXv3RqVS4eDgQG5uLgAGg4H33nuPzMxMVCoVN2/erDWWilt24f/OsINbRRLKE346na7SWW2DBw9Go9H86dpgMGAwGOjVqxdwqwprcHCw0s7Ly6vWmBwdHfn22285cOAABw8exM/Pjy1bttC0adNqn3FwcGDq1Kn079+/0iq3/v37Y2FhgYWFBa6urpw+fZpjx45x4MABvL29ASgsLCQjI4O2bdtia2urHDLZpUsX5d1W1f/+/fvZs2cP69atA6C4uJhLly7x9NNP1zpGIYQQQgghhBBCNH51SthNnjyZgIAALl26REhICKmpqYSHhzd0bOIuys7ORqPRYGNjA0CzZs2Uz5KSktDr9cTHx2NmZoaHhwfFxcVA5YIFarVauVapVJhMJgAiIiJwdXUlKiqKnJwcxowZc1djL08U3x53VdfVqWs7S0tLBg4cyMCBA1Gr1ezbtw8vLy9KS0uVNuXvBm6tsDty5Ah79uxhxYoVyirUijGXKysrIzAwkJEjR1a6n5OTU+k9azQa5Tuq6z8yMvIvbTsWQgghhBBCCCFE41VrydDS0lL++OMPli1bxsKFC3n55ZeJjY3F1dX1XsQn7gK9Xs/cuXMZNWpUlYkkg8GAjY0NZmZmHDp0SFndVVcGg4E2bdoAkJCQoNzPy8vD39+/3vE6OzsriamkpCRcXFxqfeaRRx7h0Ucf5ejRowAkJibSs2fPKtvu2rVLKSxR0bFjx/jjjz8AKCkp4dy5c7Rr1w4bGxvy8/P57bffKCkpYe/evcCt/zcuXbqEm5sb06ZNw2AwUFhYCMDu3bspLi7mt99+4/Dhwzz33HP06dOHuLg4rl+/Dtx6P+VblKtSXf99+vQhJiZGWTH5448/1vp+hBBCCCGEEEII8eCodYWdWq1m48aNeHl58eKLL96DkMTdUH5GnNFoRKPRoNPpGDduXJVttVot48ePx9fXF0dHx3qv3AoICCA0NJTo6Gjc3NyU+5cvX76jCrTvv/8+M2fO5PPPP1eKTtTFxx9/rBSdsLOzq/a5rKwsWrRo8af72dnZfPDBB8CtZFm/fv0YNGgQKpWKiRMnMnz4cGxtbZX3YzKZmDZtGteuXaOsrIyxY8fy6KOPAuDk5ERgYCCXLl1iwoQJtGnThjZt2nD+/HllhV3z5s1ZtGgRanXVefPq+p8wYQJhYWEMHTqUsrIy2rdvz+rVq6t9L6WlpXdc7bXEZMRc8+BVERZCCCGEEEIIIR5kqrI6VI+IiorCwsICLy+vSlsLy89AE6IqMTExtG3bVilg0VhMnTqVmTNn0qpVqwbpf9myZTRv3pw337yzJNndlpqairOz8/0OQzyE0tPTlbMXhbibZG6JhiDzSjQUmVuiocjcEg1B5lXjU91vUqelM3FxcQBs3LhRuadSqdi9e/ddCk88jF5//fX7HUKVFi9efL9DuKdqKxBTYjJhXqGQhxBCCCGEEEIIIe6vOiXs9uzZ09BxiPvA0dERe3t7Zdusj48P/v7+1W7RvNecnZ1JTU1Vrssryc6ZM+e+xZSSksKECROwtbUFwNramvXr11dqM3ny5Fr7WbVqFW+//XZDhPgnarWal2O/rPbzr/1G35M4hBBCCCGEEEIIUTd1Ppzq+PHj5ObmKpVBAby9vRskKHFvWFhYkJiYCEB+fj4hISEYDAaCgoIqtTMajXd0Ft39dnvcdR1Hbe169OhR45lxdbF69ep7lrATQgghhBBCCCHEg6VOWZhp06aRnZ3NM888g+b/b51TqVSSsHuI2NjYMH/+fPz8/Jg8eTIJCQns3buXkpISCgsLWblyJRMmTKCgoACj0UhwcDCenp7k5OQQEBCAi4sLJ0+exMHBgWHDhhEZGYler2fx4sU4OTlx6tQpwsLCKCoqwsLCgrCwsHoXt6goNzeXmTNnotfrlcIU7dq1IzQ0lJYtW/Ljjz/SpUsXfv/990rXOp1OKUzxxBNPEBYWRsuWLRk9ejTOzs4cP34cDw8P3njjjTrHUt3Y4uPj2bNnDzdu3CA7OxtPT0+mT5/O4sWLlaIgnTp14tNPP2XChAn8+uuvFBcXM2bMGEaMGIHJZGLWrFmkpaWhUqkYNmwYHh4eBAcHK9V4MzIymDJlCvHx8Xf8LoUQQgghhBBCCNG41Clhl5aWxvbt21GpVA0dj7iP7OzsKC0tJT8/H4ATJ06wbds2rKysMBqNREVF0aJFC/R6PSNGjFCKSWRlZREREUHnzp3x8/MjKSmJTZs2sXv3blatWsWKFSvo2LEjMTExNGnShIMHD7J06VKWLVtWYzzlSa1yf/zxBx4eHgDMnz8fb29vfHx8iI2NZcGCBaxYsQK4lcRav349Go2G0NDQStdarZbZs2fTq1cvIiIiWL58ObNmzQKgoKCAmJiYWt/T0aNHlbgGDx7M6NGjqx1beno6W7duxdzcXGk7depUNm7cqKxuBAgLC8PKyoqioiL8/PwYOHAgubm55OXl8fXXXyvxPfroo7Ro0UI5lDI+Ph4fH5/af1whhBBCCCGEEEI8MOqUsOvcuTNXrlzh8ccfb+h4xH1WsWiwu7u7Ugm4rKyMJUuWcOTIEdRqNXl5eVy9ehUAW1tbHBwcAOjUqRO9e/dGpVLh4OBAbm4uAAaDgffee4/MzExUKhU3b96sNZaKW3bh/86wg1uVT8uTYjqdjkWLFintBg8erKwErXhtMBgwGAz06tULAB8fH4KDg5V2Xl5edXpHt2+JvXTpUrVj6927N4888ggATz/9NLm5ubRt2/ZPfX755Zfs2rVL6S8zM5MOHTqQnZ3N/Pnz6devH3369AHglVdeIS4ujhkzZrB9+3b+9a9/1SluIYQQQgghhBBCPBjqlLD77bffeOmll3BycsLMzEy5v2rVqgYLTNx72dnZaDQabGxsAGjWrJnyWVJSEnq9nvj4eMzMzPDw8KC4uBioXIVUrVYr1yqVSjnzMCIiAldXV6KiosjJyWHMmDF3NfaKqz8rxl3VdXXq2u52NY2t4rvRaDSVzoAsl5KSwsGDB9myZQvNmjVj9OjRFBcX07JlSxITE9m/fz///Oc/2bFjB+Hh4QwaNIioqCjc3Nzo0qUL1tbWdxS3EEIIIYQQQgghGqc6JezqUvVSPNj0ej1z585l1KhRVW59NhgM2NjYYGZmxqFDh5SVc3VlMBho06YNgHL+GkBeXh7Tp09nw4YN9erP2dmZ5ORkvL29SUpKwsXFpdZnHnnkER599FGOHj1Kjx49SExMpGfPnlW23bVrF6dOnSIkJKTWfqsbW02aNGnCzZs3MTMzw2Aw0LJlS5o1a8b58+c5ceIEcOs3MTc3Z9CgQTzxxBOEhoYC0LRpU/r06cMHH3zARx99VKfvE0IIIYQQQgghxIOjTgm7Xr16kZubS2ZmJi+88AI3btyocqWQeLCUnxFnNBrRaDTodDrGjRtXZVutVsv48ePx9fXF0dGx3gUjAgICCA0NJTo6Gjc3N+X+5cuX76gC7fvvv8/MmTP5/PPPlaITdfHxxx8rRSfsr4mI8AAAIABJREFU7OyqfS4rK4sWLVrUqc/qxlaT4cOHM3ToUJ599lnCw8PZvHkzWq2WDh060L17d+DWu5kxYwalpaUATJkyRXleq9Wyc+dOZZtsTUpLS/nab3S1n5eYTJhX2EIshBBCCCGEEEKI+0tVVvHQsmp89dVXbNmyhT/++INvv/2WjIwM5s6dW+9VUULcLiYmhrZt2yoFLBqLqVOnMnPmTFq1anW/Q6nS559/jsFg4J133qm1bWpqKs7OzvcgKvHfprz4iRB3m8wt0RBkXomGInNLNBSZW6IhyLxqfKr7Teq0tGnjxo3861//Yvjw4QA89dRT6PX6uxuhuKscHR2xt7dXVs/5+Pjg7++PWq2+36EBsHLlSr7++mvUajVqtZrWrVvTrVu3+x2WYvHixXf8rF6v529/+xuzZ89m5MiRNbb99ttveeqpp+jUqRNw6zy8nj178sILL1T7zMSJE8nKyqpzwrziOXr1JavvhBBCCCGEEEKIe69OCTtzc/NKf/QbjcYGC0jcHRUrrObn5xMSEoLBYCAoKKhSO6PReEdbUv+K1NRU9u7dS0JCAubm5uj1+jpVjX1Q7Nixg27dupGcnFynhN2LL76oJOwqVq2tTlRUVL3iUavVvBy7uV7PlPvar+b4hRBCCCGEEEIIcffVablVz549WbVqFUVFRRw4cIDg4GA8PDwaOjZxl9jY2DB//nw2btxIWVkZ8fHxBAUF8fbbb/PGG29w/fp1/P398fHxQavV8u233wKQk5PD4MGDmTVrFi+//DIhISEcPHiQkSNHMnDgQE6dOgXAqVOnGDlyJN7e3owcOZILFy7UGM+VK1ewtrZWksCtWrVSijZ4eHgoqzdPnz7N6NG3zl47fPgwOp0OnU6Ht7c3165dIyUlhVGjRjFx4kS8vLyYM2eOct7b/v37GTFiBD4+PgQFBXH9+nWl/8jISGWs58+fr7Z/gLVr1zJs2DC0Wi2RkZF1et/JycmEhoby66+/kpeXp9zfunUrWq2WoUOHMm3aNI4fP86ePXv45JNP0Ol0ZGVlERoayr///W8AfvjhB7y9vdFqtcyYMYOSkpIaxyCEEEIIIYQQQoiHQ50SdlOnTqVVq1bY29uzZcsWXnzxRd59992Gjk3cRXZ2dpSWlpKfnw/AiRMnWLhwIV988QVNmzYlKiqKhIQENmzYwMcff0z50YZZWVmMGTOGbdu2cfHiRZKSkti0aRPTp09n1apVAHTs2JGYmBi2bt1KUFAQS5curTEWd3d3Ll26xKBBg/jggw84fPhwrfGvW7eOOXPmkJiYyMaNG7GwsABuJQtDQ0NJSkoiOzubnTt3otfrWblyJdHR0SQkJNC1a1eio6OVvqytrUlISGDkyJGsW7eu2v73799PZmYmsbGxJCYmcubMGY4cOVJjnJcuXeLq1as4OTkxZMgQtm/fDsDPP//MypUr2bBhA9u2bWPWrFk8//zzeHh4MH36dBITE3niiSeUfoqLiwkNDWXp0qUkJSVhMpn45z//WeMYhBBCCCGEEEII8XCoMWH37bffsnHjRtRqNcOHD+eXX34hLS2NVatWKauAxIOjYn0Rd3d3rKyslPtLlixBq9Uybtw48vLyuHr1KgC2trY4ODigVqvp1KkTvXv3RqVS4eDgQG5uLgAGg4Hg4GBefvllwsPD+fnnn2uMw9LSkvj4eObNm0erVq149913iY+Pr/GZ559/XkkwGgwGZRuvk5MTdnZ2aDQaXnrpJY4dO8bJkyc5d+4cr776Kjqdjq1bt/LLL78ofQ0cOBCArl27KmOoqv8DBw5w4MABvL298fHx4cKFC2RkZNQYZ3JyMkOGDAHAy8uLr7/+GoBDhw4xePBgpYhF+buvzsWLF7G1taVDhw4A+Pj4cPTo0RrHIIQQQgghhBBCiIdDjYeXrV27ttJqqZs3bxIfH09hYSEzZsxg8ODBDR6guDuys7PRaDTY2NgA0KxZM+WzpKQk9Ho98fHxmJmZ4eHhQXFxMVC5YIFarVauVSoVJpMJuFUowdXVlaioKHJychgzZkyt8Wg0GlxdXXF1dcXe3p6tW7fi6+uLRqNREovlMQAEBgbSr18/9u3bx/Dhw5UVcyqVqlK/KpWKsrIy3N3dWbJkSZXfbWZmpoynfAxV9V9WVkZgYGCt59BVlJyczNWrV0lKSgLg8uXLZGRkUIdizJXU1r6qMQghhBBCCCGEEOLhUOMKu5s3b9K2bVvl2sXFBSsrK9q1a8eNGzcaPDhxd+j1eubOncuoUaP+lOCCWyvkbGxsMDMz49ChQ/VesWUwGJQz6BISEpT7eXl5+Pv7/6n97SvV0tPTadeuHQDt27cnLS0NgJ07dyptsrKycHBwIDAwkK5du3Lx4kXg1pbY7OxsSktL2bFjBy4uLnTv3p3jx4+TmZkJwI0bN5T21amq/z59+hAXF6ecf5eXl6dsKfb39690Pl35uAoLC/n+++/Zs2cPe/bsITAwkOTkZHr37s2///1vfvvtNwB+//134NZqw/L+K+rYsSO5ubnKGBITE+nZs2eNYxBCCCGEEEIIIcTDocYVdgUFBZWu58yZo/x3eWEA0TgVFRWh0+kwGo1oNBp0Oh3jxo2rsq1Wq2X8+PH4+vri6OhIx44d6/VdAQEBhIaGEh0djZubm3L/8uXLVVagLSwsZMGCBRQUFKDRaHjyySeZN28eAJMmTWLWrFmsXr2abt26Kc9s2LCBlJQUZWtu3759SU1NpXv37nz66aecPXuWHj16MGDAANRqNeHh4UyZMkUp1PDOO+8o20urUlX/5ubmnD9/Xllh17x5cxYtWoS1tTVZWVm0bNmyUh/JyckMGDCg0r2BAwcyZcoUJk6cyNtvv83o0aNRq9U8++yzLFy4EC8vL2bPns2XX35ZqahF06ZNCQ8PJzg4GJPJRNeuXXn11Vfr+pMIIYQQQgghhBDiAaYqq2HvXUhICK6urgwfPrzS/c2bN3P48OFqtxwKARATE0Pbtm3p379/g/SfkpLCunXrWL16dYP0X52zZ88SFxfHjBkz7un33qkzZ87QpUuXO3q2xGTCXKO5yxGJh0V6ejqOjo73OwzxEJK5JRqCzCvRUGRuiYYic0s0BJlXjU91v0mNK+xmzpzJxIkTSUpKUv7gP3PmDCUlJURFRTVMpOKh8frrr9/vEBqEvb39A5OsA5RVhndCknVCCCGEEEIIIcS9V2PCzsbGhs2bN/PDDz9w7tw5APr160fv3r3vSXD/LRwdHbG3t1e2r/r4+ODv749aXeMRg/fMypUr+frrr1Gr1ajVaubNm1dpu+r9Ul604q/Q6/X87W9/Y/bs2dUWl1i2bBnNmzfnzTff/EvfVVF6ejqXL1+mX79+d63P6lQsHFIVWUUnhBBCCCGEEEI0LjUm7Mr17t1bknQNyMLCgsTERADy8/MJCQnBYDAQFBRUqZ3RaKzyTLiGlJqayt69e0lISMDc3By9Xs/NmzfvaQwNaceOHXTr1o3k5OR6VYP9q9LT00lLS6tXwq6srIyysrJ6J3LVajXa2LhqP0/yG1av/oQQQgghhBBCCNGwGscSLqGwsbFh/vz5bNy4kbKyMuLj4wkKCuLtt9/mjTfe4Pr16/j7++Pj44NWq+Xbb78FICcnh8GDBzNr1ixefvllQkJCOHjwICNHjmTgwIGcOnUKuFVVdeTIkXh7ezNy5EguXLhQYzxXrlzB2tpaWaXVqlUrpSKsh4eHUnzk9OnTjB49GoDDhw+j0+nQ6XR4e3tz7do1UlJSGDVqFBMnTsTLy4s5c+ZQWloKwP79+xkxYgQ+Pj4EBQUpVVM9PDyIjIxUxnr+/Plq+wdYu3Ytw4YNQ6vVVirgUJPk5GRCQ0P59ddfK1V9XblyJYMGDWLs2LFKhdnz58/j5+entMnJyUGr1QKQlpbG66+/jq+vL2+++SaXL18GYPTo0SxatAg/Pz8GDRrE0aNHKSkpITIyku3bt6PT6di+fTvLli3j888/V/p++eWXycnJIScnhyFDhvDBBx/g4+PDpUuX7micQgghhBBCCCGEeHBIwq4RsrOzo7S0lPz8fABOnDjBwoUL+eKLL2jatClRUVEkJCSwYcMGPv74Y8rrhmRlZTFmzBi2bdvGxYsXSUpKYtOmTUyfPp1Vq1YB0LFjR2JiYti6dStBQUEsXbq0xljc3d25dOkSgwYN4oMPPuDw4cO1xr9u3TrmzJlDYmIiGzduxMLCAriVLAwNDSUpKYns7Gx27tyJXq9n5cqVREdHk5CQQNeuXYmOjlb6sra2JiEhgZEjR7Ju3bpq+9+/fz+ZmZnExsaSmJjImTNnOHLkSI1xXrp0iatXr+Lk5MSQIUPYvn07cCv5tn37drZu3cry5cs5ffo0AE8//TQ3b94kOzsbgO3btzNkyBBu3rzJggULiIyMJD4+nmHDhlV6ryaTidjYWGbOnMny5csxNzcnKCgILy8vEhMT8fLyqjHOixcv4u3tzdatW7l48WK9xymEEEIIIYQQQogHy73dXynqrGLxXnd3d6ysrJT7S5Ys4ciRI6jVavLy8rh69SoAtra2ODg4ANCpUyd69+6NSqXCwcGB3NxcAAwGA++99x6ZmZmoVKpat7daWloSHx/P0aNHSUlJ4d133yUkJARfX99qn3n++edZuHAhWq2WgQMHYmlpCYCTkxN2dnYAvPTSSxw7doymTZty7tw5Xn31VQBu3rxJ9+7dlb4GDhwIQNeuXdm1a1e1/R84cIADBw7g7e0NQGFhIRkZGfTs2bPaOJOTkxkyZAgAXl5ezJo1i3HjxnH06FE8PT1p1qwZcGulX7khQ4awY8cOAgMD2bFjB0uXLuXixYucPXuWcePGAVBaWspjjz2mPDNgwAAAunTpovwO9dGuXTvlndzJOIUQQgghhBBCCPFgkYRdI5SdnY1Go8HGxgZASRwBJCUlodfriY+Px8zMDA8PD4qLi4HKxQXUarVyrVKpMJlMAERERODq6kpUVBQ5OTmMGTOm1ng0Go1S4MHe3p6tW7fi6+uLRqNREovlMQAEBgbSr18/9u3bx/Dhw5UVcyqVqlK/KpWKsrIy3N3dWbJkSZXfbWZmpoynfAxV9V9WVkZgYGC9zqFLTk7m6tWrJCUlAXD58mUyMjKqjLWcl5cXwcHBDBgwAJVKxVNPPcV//vMfOnfuzJYtW6p8pvx3qDiG22k0GmWLMFR+n82bN1f++07GKYQQQgghhBBCiAeLbIltZPR6PXPnzmXUqFFVJo0MBgM2NjaYmZlx6NCheq/YMhgMyhl0CQkJyv28vDz8/f3/1P7ChQtKEgtuFUto164dAO3btyctLQ2AnTt3Km2ysrJwcHAgMDCQrl27KmfAnTp1iuzsbEpLS9mxYwcuLi50796d48ePk5mZCcCNGzeU9tWpqv8+ffoQFxennH+Xl5enbCn29/evdD5d+bgKCwv5/vvv2bNnD3v27CEwMJDk5GR69uzJrl27KCoq4tq1a3z33XfKc0888QRqtZoVK1Yoq/M6dOiAXq8nNTUVuLVK8Oeff65xDJaWlkqs5e/yxx9/BODMmTPk5ORU+VxN4xRCCCGEEEIIIcTDQVbYNQJFRUXodDqMRiMajQadTqdsr7ydVqtl/Pjx+Pr64ujoSMeOHev1XQEBAYSGhhIdHY2bm5ty//Lly1VWoC0sLGTBggUUFBSg0Wh48sknmTdvHgCTJk1i1qxZrF69mm7duinPbNiwgZSUFNRqNZ06daJv376kpqbSvXt3Pv30U86ePUuPHj0YMGAAarWa8PBwpkyZQklJCQDvvPMOHTp0qHYMVfVvbm7O+fPnlZVnzZs3Z9GiRVhbW5OVlUXLli0r9ZGcnKxsVS03cOBApkyZohTG0Ol0tG/fHhcXl0rtvLy8+OSTT9i9ezdwawVdZGQkCxYswGAwYDKZ8Pf3p3PnztWOwdXVlTVr1qDT6XjrrbcYNGgQiYmJ6HQ6nnvuOZ566qkqn+vTp0+V4yxfjVmV0tLSGivBlphMmGs01X4uhBBCCCGEEEKIe0tVVvGwNPFfKyYmhrZt29K/f/8G6T8lJYV169axevXqBum/OmfPniUuLo4ZM2bc0+9tTFJTU3F2dr7fYYiHUHp6Oo6Ojvc7DPEQkrklGoLMK9FQZG6JhiJzSzQEmVeNT3W/iaywEwC8/vrr9zuEBmFvb/9fnayDymcb1pesvhNCCCGEEEIIIe49SdiJGjk6OmJvb69s1/Xx8cHf3x+1un7HH5YXrWis8d0P6enpXL58mX79+jXo96jVaobGbrujZ7f5Db3L0QghhBBCCCGEEKI2krATNbKwsCAxMRGA/Px8QkJCMBgMBAUFVWpnNBqrPAOvscTXGKWnp5OWllavhN39es9CCCGEEEIIIYS4d+Qvf1FnNjY2zJ8/Hz8/PyZPnkxCQgJ79+6lpKSEwsJCVq5cyYQJEygoKMBoNBIcHIynpyc5OTkEBATg4uLCyZMncXBwYNiwYURGRqLX61m8eDFOTk6cOnWKsLAwioqKsLCwICwsrF5FNW6Pr6SkhA8++IC0tDQ0Gg2hoaG4ublhMplYvHgx+/fvB2D48OGMHj0aDw8PYmNjadWqFadPn+aTTz7hyy+/ZNmyZeTk5HDlyhUyMjIIDQ3lxIkTfP/99zz++OOsWrUKMzMz0tLSWLhwIYWFhVhbWxMeHs7jjz/O6NGjcXJyIiUlBYPBwEcffYSTkxORkZEUFRVx7Ngx3nrrLWxtbascf3x8fKX33KZNGwYNGoSnpycAISEheHl5Ndj5g0IIIYQQQgghhLi3JGEn6sXOzo7S0lLy8/MBOHHiBNu2bcPKygqj0UhUVBQtWrRAr9czYsQIJYmUlZVFREQEnTt3xs/Pj6SkJDZt2sTu3btZtWoVK1asoGPHjsTExNCkSRMOHjzI0qVLWbZs2R3Ht23brW2gSUlJnD9/njfffJNvvvmGuLg4cnJySEhIoEmTJvz++++19puVlcUXX3zB+fPnGTFiBJGRkUyfPp2JEyeyb98++vXrx4IFC1ixYgWtWrVi+/btLF26lPDwcABMJhOxsbHs27eP5cuXs379eoKCgkhLS2POnDkAXLt2rdrxV3zPhw8fZv369Xh6emIwGEhNTeXjjz+u13sSQgghhBBCCCFE4yUJO1FvFQsLu7u7Y2VlpdxfsmQJR44cQa1Wk5eXx9WrVwGwtbXFwcEBgE6dOtG7d29UKhUODg7k5uYCYDAYeO+998jMzESlUnHz5s2/FN+xY8eUYhpPP/007dq14+LFi/zwww+MHDlS2VpaHn9N+vbti5mZGfb29phMJvr27QvcKmqRk5PDxYsXOXv2LOPGjQOgtLSUxx57THl+wIABAHTp0kUZ7+1qGn/F99yrVy/mzZtHfn4+O3fuZNCgQbJNVgghhBBCCCGEeIjIX/miXrKzs9FoNNjY2ADQrFkz5bOkpCT0ej3x8fGYmZnh4eFBcXExULlSqVqtVq5VKhUmkwmAiIgIXF1diYqKIicnhzFjxvyl+ComFisqKytDpVL96b5Go1GeKY+7XHm8arUaMzMz5Xm1Wo3JZKKsrIzOnTuzZcuWKr+z4vPl471dTeOv+J4Bhg4dSlJSEsnJyYSFhVXZnxBCCCGEEEIIIR5Mjb+Upmg09Ho9c+fOZdSoUVUmvAwGAzY2NpiZmXHo0KFqV5JVx2Aw0KZNGwASEhKU+3l5efj7+9c7vp49e5KUlATAxYsXuXTpEh07dsTd3Z3NmzdjNBoBlC2x7du3Jy0tDYCdO3fWK/YOHTqg1+tJTU0F4ObNm/z88881PmNpacn169eV6+rGXxVfX182bNgAQOfOnesVqxBCCCGEEEIIIRo3WWEnalRUVIROp8NoNKLRaNDpdMq2z9tptVrGjx+Pr68vjo6O9SoYARAQEEBoaCjR0dG4ubkp9y9fvlztls+a4nvttdeYO3cuWq0WjUZDeHg45ubmvPLKK2RkZDB06FCaNGnC8OHDef3115k0aRKzZs1i9erVdOvWrV6xm5ubExkZyYIFCzAYDJhMJvz9/WtMprm6urJmzRp0Oh1vvfVWteOvSuvWrenYsaNSeKImpaWlbPMbWq/xlCsxmTDXaO7oWSGEEEIIIYQQQtwZVVl1+waFaCRiYmJo27atVEGt4MaNG2i1WhISEnjkkUdqbJuamoqzs/M9ikz8N0lPT8fR0fF+hyEeQjK3REOQeSUaiswt0VBkbomGIPOq8anuN5EVdqLRKy8cAeDo6Ii9vb2yos7Hxwd/f3/U6saxu9vZ2VnZFgsQHx9fqRLs3XDw4EFmzpzJ2LFja03WQeXzA+tLVtgJIYQQQgghhBD3niTsxAPFwsKCxMREAPLz8wkJCcFgMBAUFFSpndFofCArp94ed1XjeOGFF9i7d2+Nz1WkVqvRxX5zR/Ek+g26o+eEEEIIIYQQQghx5x68jIYQ/5+NjQ3z58/Hz8+PyZMnk5CQwN69eykpKaGwsJCVK1cyYcIECgoKMBqNBAcH4+npSU5ODgEBAbi4uHDy5Mn/x969h0VV7Y8ff88MIF5SBMvHxM6RREIUI1QksguhGYojF9GOF9QkLykew5Qy43vUMEvxqKFmFl7wmKaMw0Wz8HYyxeMF73oyNRQqCEdyBAFnmN8fPuyfHLmIgSh9Xn+x91577c/es57H5/m41vrg4uJCcHAwixcvxmAwMH/+fNzd3Tl+/DgxMTEUFRVha2tLTExMjfflu112djbvvvsuBoMBe3t75s6dy+OPP05UVBQtWrTg9OnTuLm5kZ+fX+5Yq9USHR3NjRs3eOKJJ4iJiaFFixYMHz4cDw8Pjhw5gq+vL6NHj67FryuEEEIIIYQQQoj6Igk78VBr164dpaWlXLlyBYCjR4+SlJSEnZ0dJpOJuLg4mjVrhsFgYPDgwco+eJcuXWLRokU4OzsTEhJCcnIy69evZ8eOHSxfvpylS5fi5OREQkICVlZW7Nu3j4ULF7JkyZIq4ykrglHm999/x9fXF4DZs2czcOBAAgMD2bRpE3PmzGHp0qUA/PTTT6xatQqNRkNUVFS544CAAGbOnEmPHj1YtGgRn3zyCTNmzADg2rVrJCQk1Pp3FUIIIYQQQgghRP2RhJ146N1eN8XHxwc7OzvlfGxsLAcPHkStVpOTk0NeXh4Ajo6OuLi4ANChQwe8vb1RqVS4uLiQnZ0NgNFoZPr06WRmZqJSqbh582a1sdy+ZBf+/x52cKv4Q1nCT6vV8vHHHyvt+vbti+a2veLKjo1GI0ajkR49egAQGBjI5MmTlXb+/v41+FJCCCGEEEIIIYR4GDwYO/ULcY8uX76MRqPBwcEBgMaNGyvXkpOTMRgMJCYmotfradWqFcXFxUD5QgxqtVo5VqlUmM1mABYtWoSXlxcpKSksW7aMkpKSWo1dpVIpf98ed0XHlbnbdkIIIYQQQgghhHh4SMJOPLQMBgPR0dEMHTq0XPKrjNFoxMHBAWtra9LT05WZc3fLaDTSunVrAHQ6nXI+JyeHsLCwGsfr4eFBamoqcCuZ6OnpWe09jzzyCM2bN+fQoUMA6PV6unfvXuNnCyGEEEIIIYQQ4uEhS2LFQ6VsjziTyYRGo0Gr1TJq1KgK2wYEBDB+/HiCgoJwdXWtccGIMWPGEBUVRXx8PD179lTO5+bm3lMF2vfee493332Xzz//XCk6cTfmzZunFJ1o167dXd9XprS09J6rvZaYzdjctlRXCCGEEEIIIYQQdU9luX0DMCFEtRISEmjTpo1SwOJBl5GRgYeHR32HIRqgM2fO4OrqWt9hiAZIxpaoCzKuRF2RsSXqiowtURdkXD14KvtNZIadEDU0bNiw+g6hRmxsGtV3CLVOZv4JIYQQQgghhGjIJGEnGgxXV1c6duyoLJcNDAwkLCwMtfrB2Kpx2bJlpKSkoFarUavVzJo1i65du1bY9sSJE+j1et577707rh06dIjo6GisrKxYsWIFH3zwAYsXL670uWq1isDNu2rtPR4EuuCX6jsEIYQQQgghhBCizkjCTjQYtra26PV6AK5cuUJkZCRGo5GIiIhy7Uwm0z3tQfdHZGRksHv3bnQ6HTY2NhgMBm7evFlp+y5dutClS5cKryUlJTF69GiCg4MBqkzWCSGEEEIIIYQQ4uHzYEw9EqKWOTg4MHv2bNatW4fFYiExMZGIiAjGjRvH6NGjKSgoICwsjMDAQAICAkhLSwMgKyuLvn37MmPGDPr3709kZCT79u1jyJAh9OnTh+PHjwNw/PhxhgwZwsCBAxkyZAgXLlyoMp7ffvuNli1bYmNjA4C9vb1SgbasrwEDBhASEsL169c5cOAAY8eOvaOfr776iq+//pq4uDgiIyPJysqif//+tfnphBBCCCGEEEIIUc9khp1osNq1a0dpaSlXrlwB4OjRoyQlJWFnZ4fJZCIuLo5mzZphMBgYPHiwUkTi0qVLLFq0CGdnZ0JCQkhOTmb9+vXs2LGD5cuXs3TpUpycnEhISMDKyop9+/axcOFClixZUmksPj4+xMXF8corr+Dt7Y2/vz89evSgpKSEKVOmsHDhQtzd3bl+/Tq2traV9jNo0CAOHz7Miy++SN++fcnKyqrdjyaEEEIIIYQQQoh6Jwk70aDdXgTZx8cHOzs75XxsbCwHDx5ErVaTk5NDXl4eAI6Ojri4uADQoUMHvL29UalUuLi4kJ2dDYDRaGT69OlkZmaiUqmqXN4K0LRpUxITEzl06BAHDhxgypQpREZG4ubmxqOPPoq7uzsAzZo1q/VvIIQQQgghhBBCiIeLJOxEg3X58mU0Gg0ODg4ANG7cWLmWnJyMwWAgMTERa2trfH19KS4uBlCWrQKo1WrlWKVSYTabAVi0aBFeXl7ExcWRlZXFiBEjqo1Ho9Hg5eWFl5cXHTt2ZMuWLXTq1AmVSlXlfa+//jp5eXl07tyZDz74oGYfQQghhBDOpBIOAAAgAElEQVRCCCGEEA8dSdiJBslgMBAdHc3QoUMrTIgZjUYcHBywtrYmPT1dmTl3t4xGo7IHnU6nU87n5OQwbdo0Vq9eXa79hQsXUKvV/PWvfwXgzJkzPP744zg5OZGbm8vx48crXRL7+eef1yg2IYQQQgghhBBCPNwkYScajKKiIrRaLSaTCY1Gg1arZdSoURW2DQgIYPz48QQFBeHq6oqTk1ONnjVmzBiioqKIj4+nZ8+eyvnc3NwKK9AWFhYyZ84crl27hkaj4S9/+QuzZs3CxsaGhQsXMmfOHIqKirC1tSU+Pr5mL16N0lILuuCXarXP+lZiNmOj0dR3GEIIIYQQQgghRJ1QWW7f5EsI8YckJCTQpk0bpYDFgyAjIwMPD4/6DkM0QGfOnMHV1bW+wxANkIwtURdkXIm6ImNL1BUZW6IuyLh68FT2m8gMOyFqyNXVlY4dOyrHcXFxODo6AjBs2LC76iMxMREfHx9lWW1dsrFpVOX1EnMpNhp1ncchhBBCCCGEEEKIuyMJOyFqyNbWFr1e/4f60Ol0ODs735eEnVqtImjz/kqvJwZ713kMQgghhBBCCCGEuHsyrUaIP6igoICwsDACAwMJCAggLS0NgKysLF599VXee+89+vXrx+jRoykqKuLrr7/m5MmTTJ06Fa1WS1FREZ988gnBwcH079+fmTNnUrZSfc2aNfj7+xMQEMCUKVMoLS2lT58+GAwGAEpLS+ndu7dyLIQQQgghhBBCiIefJOyEqKGy4hZarZY333yTRo0aERcXh06nY/Xq1cybN09JuGVmZjJ06FBSU1N55JFH2L59O3379qVz587Mnz8fvV6Pra0tw4YNY/PmzaSkpFBUVMSuXbsAWLFiBVu2bCE5OZl//OMfqNVqBgwYQFJSEgD79u3jqaeewt7evt6+hxBCCCGEEEIIIWqXLIkVoob+d0nszZs3iY2N5eDBg6jVanJycsjLywPA0dFR2TzSzc2N7OzsCvs8cOAAK1eupKioiPz8fJydnfH19cXFxYWpU6fy8ssv4+fnB0BwcDATJkxg5MiRbN68maCgoDp+YyGEEEIIIYQQQtxPMsNOiD8oOTkZg8FAYmIier2eVq1aUVxcDICNjY3STqPRYDab77i/uLiYf/zjHyxevJjk5GRCQ0OV+1esWMHf/vY3Tp06RVBQECaTiTZt2uDg4MD+/fs5duwYzz///P15USGEEEIIIYQQQtwXkrAT4g8yGo04ODhgbW1Nenp6pbPobte0aVMKCgoAlORcy5YtKSgoYPv27cCt/el++eUXevbsydtvv43RaKSwsBCAQYMG8fbbb/Pqq6+i0Wjq6M2EEEIIIYQQQghRH2RJrBB/UEBAAOPHjycoKAhXV1ecnJyqvScwMJDo6GhsbW3ZsGEDgwYNIiAggLZt29KlSxcAzGYzb7/9NtevX8disTBy5EiaN28OgK+vL++8844shxVCCCGEEEIIIRoglaVsd3whxEPjxIkTzJ07l3/961/Vtj116jRubp0qvV5iLsVGI5NtRc2dOXNG2aNRiNokY0vUBRlXoq7I2BJ1RcaWqAsyrh48lf0mMsNOiIfMihUrWL9+PR9//HF9hyKEEEIIIYQQQog6IAk7UWOurq507NgRk8mERqMhMDCQsLAw1OoHZ5bWt99+y8SJE9m6dStPPvlklW1XrVrF4MGDady4MQDh4eEsWLBAWX5aG/Ly8pgxYwa//PILJpOJtm3b8tlnn1XaftGiRXTv3p1nn332jmtXr16lSZMm7Nixg3PnztG4cWMGDhxYaV9qtYqQzRmVXt8U7FGzlxFCCCGEEEIIIUSdkoSdqDFbW1v0ej0AV65cITIyEqPRSERERLl2JpMJK6v6GWIpKSl4enqydetWJk2aVGXbNWvWMGDAACVhV1Ui7V4tXryYZ599lrCwMADOnj1bZfvJkydXem3Dhg2kp6eXq0ArhBBCCCGEEEKIhkMSduIPcXBwYPbs2YSEhDBp0iR0Oh27d++mpKSEwsJCli1bxoQJE7h27Romk4nJkyfj5+dHVlYWY8aMwdPTk2PHjuHi4kJwcDCLFy/GYDAwf/583N3dOX78ODExMRQVFWFra0tMTEy1RR0KCgo4cuQIa9asYfz48UrCzmw2M3/+fPbu3QtAaGgoFouF3NxcwsLCsLOzY+3atfj6+rJp0ybs7e2Jj49n8+bNAISEhDBy5EiysrIIDw/H09OTjIwMWrduzdKlS7G1ta00ptzcXHx8fJTjp556Svn7s88+IykpCZVKxfPPP8/UqVOJiorixRdfpG/fvuX6GTduHDdu3GDQoEGMHTuW8+fP06RJE15//fWa/XBCCCGEEEIIIYR4YEnCTvxh7dq1o7S0lCtXrgBw9OhRkpKSsLOzw2QyERcXR7NmzTAYDAwePJiXX34ZgEuXLrFo0SKcnZ0JCQkhOTmZ9evXs2PHDpYvX87SpUtxcnIiISEBKysr9u3bx8KFC1myZEmV8aSlpdGrVy/at2+PnZ0dp06dws3NjQ0bNpCVlYVOp8PKyor8/Hzs7OxYtWoVq1evxt7evlw/J0+eJDExkY0bN2KxWAgNDaVHjx40b96czMxMYmNjmTNnDpMnT2b79u1otdpKYxo6dChTpkwhISGBZ599lqCgIFq3bs2ePXvYsWMHGzdupHHjxuTn51f5bsuXL8fDw0OZ4VjdtxBCCCGEEEIIIcTDRxJ2olbcXmzYx8cHOzs75XxsbCwHDx5ErVaTk5NDXl4eAI6Ojri4uADQoUMHvL29UalUuLi4kJ2dDYDRaGT69OlkZmaiUqm4efNmtbGkpqYqS0/9/f1JSUnBzc2N/fv3M2TIEGWZblmMlTl8+DB+fn40adIEgN69e3Po0CF8fX1xdHRUqri4ubkp8VamV69epKWl8d133/Hvf/+bwMBAUlJS2L9/P0FBQcpy3OpiEkIIIYQQQgghRMMnCTvxh12+fBmNRoODgwOAknwCSE5OxmAwkJiYiLW1Nb6+vhQXFwOU24NNrVYrxyqVCrPZDNwqvuDl5UVcXBxZWVmMGDGiyliuXr1Keno6586dU/pRqVRMmzYNi8WCSqW66/e6PQn5v26PXaPRKO9UFTs7OwICAggICGDs2LEcPHiw2piOHTvG+++/D0BERIQyO1EIIYQQQgghhBAN14NT1lM8lAwGA9HR0QwdOrTCxJPRaMTBwQFra2vS09OrnYlW0f2tW7cGQKfTKedzcnKUWXS32759OwMHDmTXrl3s3LmTPXv24OjoyOHDh/Hx8eHLL7/EZDIBKMtPmzZtSkFBwR19de/enbS0NG7cuEFhYSFpaWl069atyngTEhJISEi44/z+/fu5ceMGANevX+fSpUu0adMGHx8fNm/erFz73yWxXbt2Ra/Xo9frJVknhBBCCCGEEEL8ScgMO1FjRUVFaLVaTCYTGo0GrVbLqFGjKmwbEBDA+PHjCQoKwtXVtdqCEf9rzJgxREVFER8fT8+ePZXzubm5FVagTU1NJTw8vNy5Pn36kJyczMyZM/npp58YMGAAVlZWhIaGMmzYMEJDQwkPD+fRRx9l7dq1yn1ubm4EBQUxaNAg4FbRiU6dOpGVlVVpvBcuXOCZZ5654/ypU6eYPXs2Go0Gi8XCoEGDcHd3B25VjA0ODsba2poXXniBt956q0bfqDqlpRY2BXtUer3EXIqNRnL3QgghhBBCCCHEg0JlqWrdnxAPqISEBNq0afPAzTobO3YsS5YsKbdktr5lZGTg4VF5wk6Ie3XmzBllL0chapOMLVEXZFyJuiJjS9QVGVuiLsi4evBU9pvIDDvxUBo2bFh9h1ChTz/9tL5DuIONTaP6DkE0UA/jP/Qyo1QIIYQQQgjxMJCEnRC17Ntvv2XixIls3bqVJ598stJ2q1atYvDgwUqRjvDwcBYsWEDz5s1rNR61WsXgzT/Uap9CPKw2BHes7xCEEEIIIYQQoloyzUCIWpaSkoKnpydbt26tst2aNWuUYhMAn332Wa0n64QQQgghhBBCCPHwkRl2QtSigoICjhw5wpo1axg/fjyTJk3CbDYzf/589u7dC0BoaCgWi4Xc3FzCwsKws7Nj7dq1+Pr6smnTJuzt7YmPj2fz5s3ArWIXI0eOJCsri/DwcDw9PcnIyKB169YsXboUW1vb+nxlIYQQQgghhBBC1DJJ2AlRi9LS0ujVqxft27fHzs6OU6dOcezYMbKystDpdFhZWZGfn4+dnR2rVq1i9erV2Nvbl+vj5MmTJCYmsnHjRiwWC6GhofTo0YPmzZuTmZlJbGwsc+bMYfLkyWzfvh2tVltPbyuEEEIIIYQQQoi6IEtihahFqamp9OvXDwB/f39SUlLYv38/Q4YMwcrqVn7czs6uyj4OHz6Mn58fTZo0oWnTpvTu3ZtDhw4B4OjoqGz07+bmRnZ2dh2+jRBCCCGEEEIIIeqDzLATopZcvXqV9PR0zp07h0qlwmw2o1KpcHNzQ6VS3XU/Foul0ms2NjbK3xqNhuLi4j8UsxBCCCGEEEIIIR48MsNOiFqyfft2Bg4cyK5du9i5cyd79uzB0dGRTp068eWXX2IymQDIz88HoGnTphQUFNzRT/fu3UlLS+PGjRsUFhaSlpZGt27d7uu7CCGEEEIIIYQQov7IDDshaklqairh4eHlzvXp04fz58/Tpk0bBgwYgJWVFaGhoQwbNozQ0FDCw8N59NFHWbt2rXKPm5sbQUFBDBo0CLhVdKJTp05kZWXdU1ylpRY2BHe89xcTogEpMZdio5H/qxJCCCGEEEI82FSWqtbfCSEeehkZGXh4eNR3GKIBOnPmjLKnohC1ScaWqAsyrkRdkbEl6oqMLVEXZFw9eCr7TWSaQQPh6uqKVqulX79+DBgwgPj4eEpLS+s7rHK+/fZbXFxcOH/+fLVtV61axY0bN5Tj8PBwrl27VidxjR8/nsGDB1d6PSsri/79+9f6c5cvX17rfVbExqZRlddvmiVnL4QQQgghhBBCPEhkSWwDYWtri16vB+DKlStERkZiNBqJiIgo185kMinVSu+3lJQUPD092bp1K5MmTaqy7Zo1axgwYACNGzcG4LPPPquTmK5du8bp06dp0qQJly9fpl27dnXynIp8+umnjBs3rkb33Mvvp1ariNBdrvT64sD7985CCCGEEEIIIYSoniTsGiAHBwdmz55NSEgIkyZNQqfTsXv3bkpKSigsLGTZsmVMmDCBa9euYTKZmDx5Mn5+fmRlZTFmzBg8PT05duwYLi4uBAcHs3jxYgwGA/Pnz8fd3Z3jx48TExNDUVERtra2xMTE4OTkVGVMBQUFHDlyhDVr1jB+/HglYWc2m5k/fz579+4FIDQ0FIvFQm5uLmFhYdjZ2bF27Vp8fX3ZtGkT9vb2xMfHs3nzZuDW/m4jR44kKyuL8PBwPD09ycjIoHXr1ixduhRbW9sq49q+fTsvvfQSrVq1YuvWrYwdOxaAkydP8u6779K4cWOeeeYZpf2gQYOIiYnB2dkZgOHDhzN9+nScnJyYPXs2P/zwA2azmYkTJ+Ln50diYiI7d+7kxo0bXL58GT8/P6ZNm8b8+fMpKipCq9XSoUMHpkyZwrhx40hJSQHg888/p7CwkEmTJjF8+HA8PDw4cuQIvr6+9OjRgw8//JDCwkJatmzJ3Llzeeyxx+5hpAghhBBCCCGEEOJBJAm7Bqpdu3aUlpZy5coVAI4ePUpSUhJ2dnaYTCbi4uJo1qwZBoOBwYMH8/LLLwNw6dIlFi1ahLOzMyEhISQnJ7N+/Xp27NjB8uXLWbp0KU5OTiQkJGBlZcW+fftYuHAhS5YsqTKetLQ0evXqRfv27bGzs+PUqVO4ubmxYcMGsrKy0Ol0WFlZkZ+fj52dHatWrWL16tXY29uX6+fkyZMkJiayceNGLBYLoaGh9OjRg+bNm5OZmUlsbCxz5sxh8uTJbN++Ha1WW2VcqampTJw4EQcHByIiIpSE3TvvvMPMmTPp0aMH8+bNU9r369ePbdu24ezsTG5uLrm5uXTu3JnY2Fh69uzJ3LlzuXbtGoMGDeLZZ58Fbq1H37JlCzY2NvTt25fhw4czdepU1q1bp8yKrK6gxLVr10hISODmzZsMHz6cpUuXYm9vz9atW1m4cCFz586t8n4hhBBCCCGEEEI8PCRh14DdXk/Ex8cHOzs75XxsbCwHDx5ErVaTk5NDXl4eAI6Ojri4uADQoUMHvL29UalUuLi4kJ2dDYDRaGT69OlkZmaiUqm4efNmtbGkpqYSFhYGgL+/PykpKbi5ubF//36GDBmiLPMsi7Eyhw8fxs/PjyZNmgDQu3dvDh06hK+vL46OjspGjW5ubkq8lcnLy+PSpUt4enqiUqmwsrLihx9+oE2bNhiNRnr06AGAVqvlu+++A+DVV19l1KhRREREsG3bNvr27QvA3r172blzJ1988QUAxcXF/PLLLwB4e3vzyCOPAPDkk0+SnZ1NmzZtqv1mt/P39wfg4sWL/PDDD4waNQqA0tJSHn300Rr1JYQQQgghhBBCiAebJOwaqMuXL6PRaHBwcABQ9oIDSE5OxmAwkJiYiLW1Nb6+vhQXFwNgY2OjtFOr1cqxSqXCbDYDsGjRIry8vIiLiyMrK4sRI0ZUGcvVq1dJT0/n3LlzSj8qlYpp06ZhsVhQqVR3/V5VFTW+PXaNRqO8U2W2bt3K77//rswuvH79Oqmpqbz++uuVxtS6dWvs7Ow4e/Ys27Zt4x//+IdybfHixXcsDT527NgdcZV9x9tZWVmVKxLyv7GX/X4WiwVnZ2c2bNhQ5bsJIYQQQgghhBDi4SVVYhsgg8FAdHQ0Q4cOrTDxZDQacXBwwNramvT09GpnolV0f+vWrQHQ6XTK+ZycHGUW3e22b9/OwIED2bVrFzt37mTPnj04Ojpy+PBhfHx8+PLLLzGZTADk5+cD0LRpUwoKCu7oq3v37qSlpXHjxg0KCwtJS0ujW7duVcabkJBAQkLCHedTU1NZuXIlO3fuZOfOnWzevJmtW7fSvHlzmjVrxqFDh4BbCc7b9evXj5UrV2I0GpXZiM899xwJCQlKQvH06dNVxgS3knRlsxMdHBy4cuUKV69epaSkhN27d1d4T/v27TEYDGRkZABw8+ZNzp07V+2zhBBCCCGEEEII8fCQGXYNRFkBA5PJhEajQavVKssm/1dAQADjx48nKCgIV1fXagtG/K8xY8YQFRVFfHw8PXv2VM7n5uZWWME0NTWV8PDwcuf69OlDcnIyM2fO5KeffmLAgAFYWVkRGhrKsGHDCA0NJTw8nEcffZS1a9cq97m5uREUFMSgQYOAW0UnOnXqVOUecBcuXChXOAJu7Rn3888/8/TTTyvn2rVrR7NmzTh27Bhz585Vik4899xz5e595ZVX+OCDD5gwYYJybsKECcTExDBgwAAsFgtt27bl008/reozEhoayoABA+jUqRMLFizgzTffJDQ0FEdHx0p/ExsbGxYvXsycOXMwGo2YzWbCwsKUIhgVKS21VFkJ9qbZgrXm7mc5CiGEEEIIIYQQom6pLFWtMRSiBhISEmjTpo2yxPRBMXbsWJYsWVJuaeqfSUZGBh4eHvUdhmiAzpw5o+wbKURtkrEl6oKMK1FXZGyJuiJjS9QFGVcPnsp+E5lhJ2rNsGHD6juEClU3062hs7FpVC/PNZktWMnMPSGEEEIIIYQQosYkYSfuO1dXVzp27Kgs3w0MDCQsLAy1+sHYUrEsPrPZjKOjIx999BHNmzev77DumVqt4kPdL/f9uVGBNauEK4QQQgghhBBCiFsejAyJ+FOxtbVFr9eTmppKfHw8e/bs4ZNPPrmjXVkhivutLL6UlBRatGjBunXr6iUOIYQQQgghhBBC/DnJDDtRrxwcHJg9ezYhISFMmjQJnU7H7t27KSkpobCwkGXLljFhwgSuXbuGyWRi8uTJ+Pn5kZWVxZgxY/D09OTYsWO4uLgQHBzM4sWLMRgMzJ8/H3d3d44fP05MTAxFRUXY2toSExNToyIbTz/9NP/973+BW+vKo6OjuXHjBk888QQxMTG0aNGC4cOH4+rqyqlTpzAYDMybN48VK1bwww8/8OqrrzJlyhTgVmGKX3/9leLiYkaMGMHgwYMB8PDwYMSIEezatQtbW1uWLl1Kq1atyMvLIzo6msuXLwPwf//3fzzzzDPo9XrWrl3LzZs36dq1K9HR0Wg0mlr+ZYQQQgghhBBCCFFfZIadqHft2rWjtLSUK1euAHD06FE+/PBD1qxZQ6NGjYiLi0On07F69WrmzZtHWZ2US5cuMWLECJKSkrh48SLJycmsX7+eadOmsXz5cgCcnJxISEhgy5YtREREsHDhwruOy2w2s3//fnx9fQGYNm0aU6dOJTk5mY4dO5abFWhtbc26desYMmQIEyZM4P333yclJQWdTsfVq1cBiImJITExkc2bN7N27VrlfGFhIV27diUpKYlu3bqxceNGAObMmUP37t1JSkpCp9Ph7OzM+fPn2bZtG+vXr0ev16NWq0lOTv6Dv4AQQgghhBBCCCEeJDLDTjwQbi9W7OPjg52dnXI+NjaWgwcPolarycnJIS8vDwBHR0dcXFwA6NChA97e3qhUKlxcXMjOzgbAaDQyffp0MjMzUalU3Lx5s9pYioqK0Gq1ZGdn4+bmho+PD0ajEaPRSI8ePQAIDAxk8uTJyj1lSb2OHTvi7OzMY489BtxKRv7666+0bNmStWvX8u233wLwyy+/kJmZScuWLbG2tuall14CoHPnznz//fcApKen89FHHwGg0Wh45JFH0Ov1nDx5kpCQECVWBweHGn9vIYQQQgghhBBCPLgkYSfq3eXLl9FoNEriqXHjxsq15ORkDAYDiYmJWFtb4+vrS3FxMQA2NjZKO7VarRyrVCrMZjMAixYtwsvLi7i4OLKyshgxYkS18ZTtYWc0Ghk7dizr1q0jMDCwynvKnn17HGXHJpOJAwcOsG/fPjZs2EDjxo0ZPny48h7W1taoVCqlfVnsFbFYLAQGBhIZGVntewghhBBCCCGEEOLhJEtiRb0yGAxER0czdOhQJWl1O6PRiIODA9bW1qSnpysz5+6W0WikdevWAOh0OuV8Tk4OYWFhVd77yCOP8N577/HFF19ga2tL8+bNOXToEAB6vZ7u3bvXKI4WLVrQuHFjzp8/z9GjR6u9x9vbm3/961/AreW5169fx9vbm+3btyvLh/Pz82v8TYQQQgghhBBCCPFgkxl24r4rW3JqMpnQaDRotVpGjRpVYduAgADGjx9PUFAQrq6uNSoYATBmzBiioqKIj4+nZ8+eyvnc3FysrKof/p06deKpp54iNTWVefPmKUUn2rVrx9y5c+86jueff54vv/ySgIAA2rdvz9NPP13tPTNmzGDmzJls3rwZtVrN//3f/+Hh4cHf//53Ro8eTWlpKdbW1rz//vu0bdu20n5KSy1EBba561hri8lswUpzZxJWCCGEEEIIIYQQVVNZbt88TIg/iYSEBNq0acPLL79c36HUuYyMDDw8POo7DNEAnTlzBldX1/oOQzRAMrZEXZBxJeqKjC1RV2Rsibog4+rBU9lvIkti/4RcXV3RarX069ePAQMGEB8fT2lpaX2Hpfjtt9+YMmUKfn5++Pv7Ex4ezsWLF2v1GcOGDas0Wefr64vBYLjnvk+fPo2LiwvfffddtW0TExPJyclRjmfMmMGPP/54z8+uiI1Noyqvm8ySsxdCCCGEEEIIIR4ksiT2T6isqALAlStXiIyMxGg0EhERUa6dyWS6q2WjtclisTBx4kQGDhzIwoULgVvZ5itXrtC+ffv7Gsu9SklJwdPTk9TUVHr16lVlW51Oh7Ozs7LP3gcffFDr8ajVKlYk5lZ6/Y2gx2r9mUIIIYQQQgghhLh3krD7k3NwcGD27NmEhIQwadIkdDodu3fvpqSkhMLCQpYtW8aECRO4du0aJpOJyZMn4+fnR1ZWFmPGjMHT05Njx47h4uJCcHAwixcvxmAwMH/+fNzd3Tl+/DgxMTEUFRVha2tLTExMlfvQpaenY2VlxWuvvaacK5saarFY+Oijj/juu+9QqVSMHz8ef39/Dhw4wJIlS3BwcODs2bP07t2bjh07smbNGoqLi4mLi+OJJ55QClz8/PPPALz77rt4enpy9epVIiMjMRgMuLu7U7ZK/J///CctW7ZUilMsXLgQBweHKivNWiwWtm/fTnx8PH/7298oLi6mUaNbM9w+++wzkpKSUKlUPP/883Tu3JmTJ08ydepUbG1t2bBhA+Hh4UybNo0uXbqQkpLCp59+isVi4YUXXuDtt98GwMPDgxEjRrBr1y5sbW1ZunQprVq1+gOjQAghhBBCCCGEEA8SWRIraNeuHaWlpUrl0aNHj/Lhhx+yZs0aGjVqRFxcHDqdjtWrVzNv3jwloXXp0iVGjBhBUlISFy9eJDk5mfXr1zNt2jSWL18OgJOTEwkJCWzZsoWIiAhl1lxlzp07h5ubW4XXvvnmG86ePYteryc+Pp6PPvqI3NxbM8fOnj3LjBkzSE5ORq/X89NPP7Fp0yZCQkJYu3YtcGv2WlhYGJs3b2bJkiW89957AMTFxfHMM8+wZcsWfH19lYReSEgIW7ZsAaC0tJTU1FQCAgKqjP/w4cM4OjryxBNP4OXlxZ49ewDYs2cPO3bsYOPGjSQlJTFmzBj69u1L586dmT9/Pnq9HltbW6WfnJwc5s+fz+rVq9myZQsnTpwgLS0NgMLCQrp27UpSUhLdunVj48aNVcYkhBBCCCGEEEKIh4vMsBMA3F57xMfHBzs7O+V8bGwsBw8eRK1Wk5OTQ15eHgCOjo64uLgA0KFDB7y9vVGpVLi4uJCdnQ2A0Whk+vTpZGZmolKpuHnz5j3HePjwYfr164dGo6FVq1Z0796dEydO0KxZM7p06cJjj91a2vnEE0/g4+MDQL5k8ZIAACAASURBVMeOHTlw4AAA+/btK7c/3PXr17l+/ToHDx7kk08+AeDFF1+kRYsWyvvZ2dlx+vRp8vLy6NSpEy1btqwyxtTUVPr16weAv78/er2ePn36sH//foKCgmjcuDGA8n0rc+LECXr06IG9vT1wq1ruwYMH8fPzw9rampdeegmAzp078/3339/9RxRCCCGEEEIIIcQDTxJ2gsuXL6PRaHBwcABQkkoAycnJGAwGEhMTsba2xtfXl+LiYgBsbGyUdmq1WjlWqVSYzWYAFi1ahJeXF3FxcWRlZVW5nBTA2dmZ7du3V3itqoLGlcWiVquVWEpLS9mwYUO5mWzVGTRoEImJieTl5REcHFxlW7PZzDfffMPOnTtZvnw5FouF/Px8rl+/jsViQaVS3fVzq2Jtba30dfv7CSGEEEIIIYQQomGQJbF/cmX7ug0dOrTChJLRaMTBwQFra2vS09OVmXN3y2g0KgUVdDqdcj4nJ0fZG+52PXv2pKSkpNwyz+PHj/Of//yH7t27s23bNsxmMwaDgUOHDuHu7n7XsTz33HMkJCQox2fOnAGge/fuJCcnA7eWrv7+++9KGz8/P7777jtOnDjBc889p5zv27fvHf3v27ePp556ij179rBz50527dpFnz59SEtLw8fHh82bN3Pjxg0A8vPzAWjatCkFBQV39OXu7s7BgwcxGAyYzWZSU1Pp3r37Xb+rEEIIIYQQQgghHl4yw+5PqKioCK1Wi8lkQqPRoNVqGTVqVIVtAwICGD9+PEFBQbi6ulZZMKIiY8aMISoqivj4eHr27Kmcz83NrbACrUql4pNPPiEmJoYVK1bQqFEj2rZty7vvvkv37t3JyMhAq9WiUql4++23efTRR7lw4cJdxTJjxgxmzZpFQEAAZrOZbt26MWvWLN58800iIyMJDAyke/fuPP7448o9NjY2eHl50bx5czQaDXAryVnRbL/U1FT8/PzKnevTpw/r169n5cqVnD17luDgYKytrXnhhRd46623CAwMJDo6Wik6Ueaxxx7jrbfeIiwsDIvFwvPPP39H30IIIYQQQgghhGiYVJaq1hkKUUcSEhJo06YNL7/8cn2HUqXS0lICAwNZtGgRf/3rXwHYtWsXly9frnZ574Pi1KnTuLl1qvS6yWzBSlM7y3XFn8uZM2eUKs5C1CYZW6IuyLgSdUXGlqgrMrZEXZBx9eCp7DeRGXaiXgwbNqy+Q6jWjz/+yNixY+ndu7eSrAOUgg8NhaTqhBBCCCGEEEKIB4sk7OqQq6srHTt2VJaeBgYGEhYWhlr9YGwduGzZMlJSUlCr1ajVambNmkXXrl0rbHvixAn0ej3vvffeHdcOHTpEdHQ0VlZWrFixgg8++IDFixfX2rPrS4cOHdixY0eN7zMYDPTq1YuZM2cyZMiQKtumpaXx17/+lQ4dOgC3inR0796dZ5999p5iroharWLD5rxKrw8OblVrzxJCCCGEEEIIIcQfJwm7OmRra4terwfgypUrREZGYjQaiYiIKNfOZDJVuJ9bXcrIyGD37t3odDpsbGwwGAzcvHmz0vZdunShS5cuFV5LSkpi9OjRShXV6pJ1NX32w2bbtm107dqV1NTUu0rYvfjii0rCbvLkyfcjRCGEEEIIIYQQQjzAHoypXn8CDg4OzJ49m3Xr1mGxWEhMTCQiIoJx48YxevRoCgoKCAsLIzAwkICAANLS0gDIysqib9++zJgxg/79+xMZGcm+ffsYMmQIffr04fjx48CtSqpDhgxh4MCBDBkypNpCDL/99hstW7bExsYGAHt7e6Waa1lfAwYMICQkhOvXr3PgwAHGjh17Rz9fffUVX3/9NXFxcURGRpKVlUX//v3v+dm+vr4YDAbg1qy+4cOHA/Cf//wHrVaLVqtl4MCBSkxDhw7lzTffxN/fn/fff5/S0lIA9u7dy+DBgwkMDCQiIkKpxOrr68vixYuV73z+/PlK+wdYuXIlwcHBBAQEVJuILJOamkpUVBS//vorOTk5yvktW7YQEBDAgAEDePvttzly5Ag7d+7ko48+QqvVcunSJaKiovj6668B2L9/PwMHDiQgIIB33nmHkpKSKt9BCCGEEEIIIYQQDYPMsLuP2rVrR2lpKVeuXAHg6NGjJCUlYWdnh8lkIi4ujmbNmmEwGBg8eLBSkOHSpUssWrQIZ2dnQkJCSE5OZv369ezYsYPly5ezdOlSnJycSEhIwMrKin379rFw4UKWLFlSaSw+Pj7ExcXxyiuv4O3tjb+/Pz169KCkpIQpU6awcOFC3N3duX79Ora2tpX2M2jQIA4fPsyLL75I3759ycrKqvY7VPbsqnzxxRe8//77eHp6UlBQQKNGjYBbycWtW7fy+OOPM2bMGL755ht69OjBsmXLiI+Pp0mTJqxYsYL4+HgmTpwIQMuWLdHpdKxbt44vvviCDz74oML+9+7dS2ZmJps2bcJisTB+/HgOHjxI9+7dK43zl19+IS8vD3d3d1599VW2bt3KqFGjOHfuHMuWLWP9+vXY29uTn5+PnZ0dvr6+yre7XXFxMVFRUaxatYr27dszbdo0/vWvfzFy5MhK30EIIYQQQgghhBANg8ywu89uL8rr4+ODnZ2dcj42NpaAgABGjRpFTk4OeXm39h1zdHTExcUFtVpNhw4d8Pb2RqVS4eLiQnZ2NgBGo5HJkyfTv39/5s6dy7lz56qMo2nTpiQmJjJr1izs7e2ZMmUKiYmJXLx4kUcffRR3d3cAmjVrVuvLdSt7dlWeeeYZPvzwQ9asWYPRaFRicnd3p127dmg0Gvr168fhw4c5duwYP/74I6+99hparZYtW7bw888/K3316dMHgM6dOyvfr6L+v//+e77//nsGDhxIYGAgFy5c4KeffqoyztTUVF599VUA/P39SUlJASA9PZ2+fftib28PoPzulbl48SKOjo60b98egMDAQA4dOlTlOwghhBBCCCGEEKJhkBl299Hly5fRaDQ4ODgA0LhxY+VacnIyBoOBxMRErK2t8fX1pbi4GEBZOgqgVquVY5VKhdlsBm4VK/Dy8iIuLo6srCxGjBhRbTwajQYvLy+8vLzo2LEjW7ZsoVOnTqhUVdcNff3118nLy6Nz5873PLOromcHBQWh0WiUpGbZ+wO88cYbvPDCC+zZs4fQ0FDi4+OVb3A7lUqFxWLBx8eH2NjYCp9tbW0N3PqWZd+vov4tFgtvvPFGtfvQ3S41NZW8vDySk5MByM3N5aeffiqXqL0b1bWv6B2EEEIIIYQQQgjRMMgMu/vEYDAQHR3N0KFDK0yIGY1GHBwcsLa2Jj09vcazpoxGo7IPnE6nU87n5OQQFhZ2R/v/nS125swZHn/8cZycnMjNzVX2xrt+/Tomk6ncvZ9//jl6vb7aZF1Nnw3Qtm1bTp48CcA333yjtLl06RIuLi688cYbdO7cmYsXLwK3lsRevnyZ0tJStm3bhqenJ08//TRHjhwhMzMTgBs3bijtK1NR/8899xybN29W9r/LyclRljOHhYWV25+u7L0KCwv57rvv2LlzJzt37uSNN94gNTUVb29vvv76a65evQpAfn4+cGu2YVn/t3NyciI7O1t5B71eX+VSXCGEEEIIIYQQQjQcMsOuDhUVFaHVajGZTGg0GrRaLaNGjaqwbUBAAOPHjycoKAhXV1ecnJxq9KwxY8YQFRVFfHw8PXv2VM7n5uZWuKS1sLCQOXPmcO3aNTQaDX/5y1+YNWsWNjY2LFy4kDlz5lBUVIStra0ym62mavpsgIkTJzJjxgw+/fRTunbtqtyzevVqDhw4oCwLfv7558nIyODpp59mwYIF/PDDD3Tr1o3evXujVquZO3cub731llKo4e9//7uyvLQiFfVvY2PD+fPnlRl2TZo04eOPP6Zly5ZcunSJFi1alOsjNTWV3r17lzvXp08f3nrrLd58803GjRvH8OHDUavVdOrUiQ8//BB/f39mzpzJ2rVryxW1aNSoEXPnzmXy5MmYzWY6d+7Ma6+9VsNf4JbSUguDg1tVet1stqDRVD2rUgghhBBCCCGEEPePylLTtXrioZKQkECbNm2UAhYN6dkHDhzgiy++4NNPP62T/ivzww8/sHnzZt555537+tx7lZGRgYeHR32HIRqgM2fO4OrqWt9hiAZIxpaoCzKuRF2RsSXqiowtURdkXD14KvtNZIZdAzds2LA/5bPrUseOHR+aZB2AjU2jKq/LDDshhBBCCCGEEOLBUmcJO1dXVzp27KgsBw0MDCQsLAy1+sHYNs/Dw4OMjIw7zuv1elauXElpaSkajYYuXbowffp0mjdvzvDhw8nNzcXW1paSkhJGjhzJ4MGDGTRoECUlJfz+++8UFRUpe8nFxcXRokULZs+ezZEjRwDo2rUr77///h3LKSty+vRpAgMDWblyJb169aq03fLlyxk3btw9fYclS5awceNGpXopwNq1a2nevHmtP2/VqlUMHjy4XLGNisyYMYNRo0bRoUOHKtuVFa2oTQcOHMDa2ppnnnmm2rbHjx9n3rx55OXloVKp8PT05L333qvy/crGXVZWFhkZGQQEBNRm+BVSq1WkbMyr9Hr/0MqXywohhBBCCCGEEOL+q7OEna2tLXq9HoArV64QGRmJ0WgkIiKiXDuTyVThPmf14d///jerV69m5cqVtG7dGrPZjE6nIy8vT0lgzZ8/ny5dupCfn0/v3r0JDAzkq6++AiAxMZGTJ0/y/vvvK31GRETg7OzMRx99BMDixYuJiopi2bJl1caTkpKCp6cnqampFSbsLBYLFouFTz/99J4TdgAjR47k9ddfv+v29/I8s9nMmjVrGDBgQLUJu3utPFsb/vOf/9CkSZNqE3Z5eXlMnjyZ2NhYPDw8sFgsbN++nYKCgmrfDyA7O5uUlJQaJ+zMZjMajaZG9wghhBBCCCGEEOLhcl8yZQ4ODsyePZuQkBAmTZqETqdj9+7dlJSUUFhYyLJly5gwYQLXrl3DZDIxefJk/Pz8yMrKYsyYMXh6enLs2DFcXFwIDg5m8eLFGAwG5s+fj7u7O8ePHycmJkYpkhATE1Pjog1wa+bYtGnTlBlyGo2GkJCQCtsWFhbSuHHjKpMnmZmZnDx5koULFyrn3nzzTXr37s2FCxeqjLEsARQfH8/f/vY3iouLadSoEVlZWYSHh+Pl5cXRo0dxdXVVilt06NCB2bNn8/e//51ff/2V0tJSJkyYgL+/f42/RWJiIjt37uTGjRtcvnwZPz8/pk2bxvz588s9b8GCBej1etauXcvNmzfp2rUr0dHRaDQaPDw8GDlyJHv37uWFF14gNzeXsLAw7OzsWLt2LdHR0Zw4cYLi4mJeeeUVJZk7fPhwpk2bRpcuXfDw8GDEiBHs2rULW1tbli5dSqtWrYiKiqJRo0ZcuHCBn3/+mblz56LT6Th69Chdu3blww8/BGDv3r0sWbKEkpIS2rVrx9y5c2natCm+vr4MHDiQXbt2YTKZ+Oc//0mjRo348ssvUavVJCUlMXPmTLp161bh91m3bh0DBw5U9oZTqVT07dsXuDVrsUmTJkoStH///ixfvhxHR0fl/gULFnD+/Hm0Wi2BgYE0b968XLJ37NixjB49Gi8vr3Lfcfr06WRnZ1f4vYUQQgghhBBCCNEw3Lf1qe3ataO0tJQrV64AcPToUT788EPWrFlDo0aNiIuLQ6fTsXr1aubNm0dZLYxLly4xYsQIkpKSuHjxIsnJyaxfv55p06axfPlyAJycnEhISGDLli1ERESUS5DVxI8//oibm1uVbaZOnUpAQAB9+/ZlwoQJVSZKfvzxR1xdXcu10Wg0uLq6cuHChSqfc/jwYRwdHXniiSfw8vJiz549yrWLFy8ycOBAtmzZwty5c5XZjAsWLOC7777jscceIykpiZSUlCqX0pZZtWoVWq0WrVbL8OHDlfNnzpzhn//8J8nJyWzbto1ffvmFqVOnlnve+fPn2bZtG+vXr0ev16NWq0lOTgZuJTWdnZ356quvmDhxIo899hirV69m7dq1AEyZMoXExESSkpI4ePAgZ8+evSO2wsJCunbtSlJSEt26dWPjxo3KtWvXrrFmzRreeecdxo0bx8iRI0lNTeWHH37gzJkzGAwGli1bRnx8PDqdjs6dO5ereNuyZUt0Oh1Dhgzhiy++wNHRkSFDhjBy5Ej0en2lyTqAc+fOVTtWqhIZGUm3bt3Q6/WMHDmyyra3f8eWLVtW+r2FEEIIIYQQQgjRMNzXtai3F6T18fHBzs5OOR8bG8vBgwdRq9Xk5OSQl3drzy1HR0dcXFwA6NChA97e3qhUKlxcXMjOzgbAaDQyffp0MjMzUalU3Lx58w/H+t///pdp06ZRUFDAW2+9pcxSK1sSazAYGDJkCL169aJt27aVvq9Kdedm/ndTmDc1NZV+/foB4O/vj16vp0+fPgA8/vjjPP300xXe17FjR+bNm8fHH3/MSy+9VGXSqUxlS2K9vb155JFHAHjyySfJzs6mTZs25drs37+fkydPKjMRi4qKcHBwAG4lJ1955ZVKn7tt2zY2btyIyWTit99+4/z58zz11FPl2lhbW/PSSy8B0LlzZ77//nvl2ksvvaSMhVatWpUbJ9nZ2fz666/8+OOPvPbaawDcvHmz3Hcr+56dO3fm22+/rfY71Zfbv2NV31sIIYQQQgghhBANw31L2F2+fBmNRqMkF27f5ys5ORmDwUBiYiLW1tb4+vpSXFwMgI2NjdJOrVYrxyqVCrPZDMCiRYvw8vIiLi6OrKwsRowYcU8xdujQgVOnTtGzZ09cXFzQ6/XMmjWLoqKiO9ra29vTqVMnjh07VmnCztnZmdOnT1NaWqoU2ygtLeW///0vnTp1qjQOs9nMN998w86dO1m+fDkWi4X8/HyuX78OQJMmTSq9t3379iQmJrJnzx4WLFiAj48PEydOrMlnUNz+7TUajfK9b2exWAgMDCQyMvKOa40aNap0BuLly5f54osv2LRpEy1atCAqKkr5zW9nbW2tJD3VanW5GG4fC/87TkwmE2q1Gh8fH2JjYyuMwdrausJ+70bZWPHz87vjmkajobS0VDmu6L1qcs/t37Gq7y2EEEIIIYQQQoiG4b4siTUYDERHRzN06NAKZ5wZjUYcHBywtrYmPT1dmTl3t4xGo7LvnE6nU87n5OQQFhZ21/2MHTuWjz76iF9//VU5V1GyDuDGjRucOXOGJ554otL+/vKXv9CpUyeWLl2qnFu6dCne3t48/vjjAMq+Z7fbt28fTz31FHv27GHnzp3s2rWLPn36kJaWVuFzrKyslFmFOTk5NG7cGK1Wy+uvv87p06eBW3um1dYsstuf5+3tzfbt25Wlzvn5+ZX+fk2bNqWgoABAKc7wyCOPkJeXx7///e9aie12Tz/9NEeOHCEzMxO49ZtdvHixyntujxHg22+/ZcGCBXe0GzZsGFu2bOHYsWPKOb1ez2+//Ubbtm2V737q1CmysrKqfU7btm05e/YspaWl/PLLLxw/frzC+GryvYUQQgghhBBCCPFwqrMZdmWFCUwmExqNBq1Wy6hRoypsGxAQwPjx4wkKCsLV1bXGBSPGjBlDVFQU8fHx9OzZUzmfm5tbaQXaGzdu8PzzzyvHo0aNYtSoURgMBsLDwzGbzTRv3hxnZ2eee+45pV3ZHm4lJSUEBv4/9u48rKpy////c+8NCErJ4DymKYokhorD0U5FjigCTo1KaZ3KATUaFDU7qJRmmiI5nCxTOg4pigxmOdY3lUIxJyzNnDBHNEECZLN/f/hzf+IIODGpr8d1netqrXvd93qvzfsPr/e5h0AeeeSRImMLDw9n4sSJdO7cmfT0dJo3b27dey8tLa3A5bHx8fHXzdzq0qULS5YsKXCJa//+/enVqxfNmjUjICCAqVOnYjQasbGx4b333gPg119/xcfHp8AYFy5cyJo1a6zXkZGRRX7T39/30UcfMXLkSAYNGkReXh62tra8++67Bc467N+/P6+88gpVq1Zl8eLFNGvWjB49elC3bt0bnsp6O1xcXHj//fd54403yMnJAWDkyJE0aNCg0D5PPvkkwcHBbNiwgfHjx3Ps2DEcHR2ve65KlSpMnz6dKVOmcP78eYxGI97e3nTp0oWuXbsSExODv78/zZs356GHHrquf5MmTTCZTPTq1YvevXsTFBRE7dq18fPzo3HjxoXuj9eoUaOb/r2vycuz0LN/lULbzWYLJtP1hXQRERERERERKRsGy81sqHaXioqKombNmjz11FNlHQoAhw8f5l//+hfjx4/n8ccfZ9OmTRw/fvy2l/DeisGDB7NgwYISf8+95s033yQ0NBQXF5eyDuW2JScnW0+zFSlOKSkpuLu7l3UYcg9SbklJUF5JSVFuSUlRbklJUF6VP4X9TUr10InS9sILL5R1CPk0bNgw37LWa4cplAYV627PtGnTbul5Ly8vkpOTrdfR0dHs3buXd999t7hDu2kV7CoU2a4ZdiIiIiIiIiLlyz1dsBO52+Tm5uZbxv2/1zfb7+8MRgMbvzxbaF+f56veeqAiIiIiIiIiUmJUsBMpJampqYSGhpKWlmbdX69WrVqMHj2aypUrs3//fjw8PLh48WK+a39/fyZMmMBff/1FvXr1CA8Pp3LlygwYMAAvLy927tyJj48PgwYNKutPFBEREREREZFioIKdSDG6dtjKNX/++af1sI+JEycSEBBAYGAgK1asYNKkSdYThI8cOcLChQsxmUyMHj0637Wfnx/jx4+nTZs2zJw5k9mzZzN27FgALl26RFRUVOl/qIiIiIiIiIiUGGNZByByL7G3tycmJsb6v+DgYGtbcnIyPXv2BMDf358dO3ZY27p164bJZLruOj09nfT0dNq0aQNAYGAgSUlJ1ud8fX1L+pNEREREREREpJSpYCdSRgyG/zvowcHBIV/b/14X5mafExEREREREZG7hwp2IqXEy8uL+Ph4AGJjY2nVqtUN+zzwwAM8+OCD1ll1MTExeHt7l2icIiIiIiIiIlK2tIedSCkZN24coaGhLFiwwHroxM2YMmWK9dCJunXr3nS/ayx5liJPgjWbLZhMhkLbRURERERERKR0GSwWi6WsgxCRkpOcnIyXl1dZhyH3oJSUFNzd3cs6DLkHKbekJCivpKQot6SkKLekJCivyp/C/iZaEityj6tgV6HI9jyzavYiIiIiIiIi5YmWxN4n3N3dcXNzIzc3F5PJRGBgIEFBQRiN5aNme/bsWcLDw9mzZw92dnbUrl2b0NBQGjRoUCrv9/HxYcWKFbi4uBRb3++++45Zs2aRkZFBhQoVaNCgAW+//Ta1atVi9OjR/PjjjzzwwANkZ2fTs2dPhg0bxtChQzlx4gSZmZmkpaVRp04dACZMmMAjjzzChx9+yKZNmzAYDDRs2JAJEyZQq1atIuMzGA1s/+Jsoe3tggpfLisiIiIiIiIipU8Fu/uEvb09MTExAJw/f56QkBDS09MJDg7O91xubi42NqWbFhaLhWHDhhEQEMCMGTOAq1NCz58/X2oFu+L266+/MmnSJObMmcPDDz8MwIYNG0hNTbUW2N5++226detGdnY2vr6++Pv7ExkZCUBiYiKfffYZ8+bNs445ZcoULl++zLp16zCZTKxcuZIhQ4YQHR1dbgqvIiIiIiIiInLnVLC7D7m6ujJx4kT69u3L8OHDWbVqFZs3byYnJ4fMzEzmzJnDkCFDuHTpErm5uYwYMYJOnTpx4sQJXn75ZVq1asXPP/9MkyZN6NOnD7NmzSItLY1p06bh6enJ7t27CQ8PJysrC3t7e8LDw2nYsGGh8Wzfvh0bGxueffZZ671r67ctFgtTp07l+++/x2Aw8Prrr+Pr60tiYiIRERG4urpy4MABOnfujJubG4sWLSI7O5vIyEjq1atHWloaEyZM4OTJkwCEhobSqlUrLly4QEhICGlpaXh6enJtK8ePP/4YZ2dngoKCAJgxYwaurq4MHDjwln7j//znP7z66qvWYh3AU089VeCz2dnZAFSsWLHQ8f766y+io6PZsGEDJpMJgD59+rBy5Uq2bt1Kx44dbyk+ERERERERESm/NC3nPlW3bl3y8vI4f/48ALt27eKDDz5g0aJFVKhQgcjISFatWsUXX3zBlClTrAWtY8eOMXDgQNasWcPvv/9ObGwsS5Ys4e2332bu3LkANGzYkKioKFavXk1wcLB11lxhDh48iIeHR4Ft33zzDQcOHCAmJobPP/+cqVOncubMGQAOHDjA2LFjiY2NJSYmhiNHjrBixQr69u3L4sWLAZg8eTJBQUGsXLmSiIgIxo0bB0BkZCQtW7Zk9erV+Pj4WAt6ffv2ZfXq1QDk5eURHx+Pn5/fLf++hw4dKvSbrpk6dSr+/v48/vjj9OjRA1dX10KfPXr0KDVr1sTR0THf/UceeYRDhw7dcnwiIiIiIiIiUn5pht197O8HBHfo0AEnJyfr/enTp/PTTz9hNBo5ffo0586dA6BOnTo0adIEgEaNGtG+fXsMBgNNmjQhNTUVgPT0dN555x2OHj2KwWDgypUrtx3jjh076NGjByaTiSpVquDt7c2ePXtwdHSkefPmVKtWDYB69erRoUMHANzc3EhMTARg69at+QpaGRkZZGRk8NNPPzF79mwAnnjiCSpXrmz9PicnJ/bv38+5c+do1qwZzs7Otx0/wIULF3jxxRfJysqif//+DB48GPi/JbGXL1/mxRdfZOfOnbRs2bLQcQwGw3X3dMiziIiIiIiIyL1HBbv71PHjxzGZTNZZXQ4ODta22NhY0tLSiI6OxtbWFh8fH+uyTTs7O+tzRqPRem0wGDCbzQDMnDmTtm3bEhkZyYkTJ264nLRx48asW7euwLaiClKFxWI0Gq2x5OXlsWzZMuzt7YuM4e/69etHdHQ0586do0+fPjfd7+8aNWrEvn37aNq0Kc7OzsTExLBgDH0ybAAAIABJREFUwQIyMzOve7ZSpUq0adOGHTt2FFqwq1evHidPniQjIyPfLLv9+/fTtWvX24pRRERERERERMonLYm9D13b1+35558vcNZWeno6rq6u2Nrasn37duvMuZuVnp5O9erVAVi1apX1/unTp617w/1du3btyMnJYfny5dZ7u3fv5scff8Tb25u1a9diNptJS0sjKSkJT0/Pm46lY8eOREVFWa9TUlIA8Pb2JjY2FoAtW7bw559/Wp/p1KkT33//PXv27Mm3N1y3bt1u+r0vv/wyc+fO5bfffrPe++uvvwp8Njc3l927d1OvXr1Cx6tYsSIBAQF88MEH1mLk6tWrqVChAq1atbrpuERERERERESk/NMMu/tEVlYW/v7+5ObmYjKZ8Pf356WXXirwWT8/P15//XV69+6Nu7t7kQdGFOTll19m9OjRfP7557Rr1856/8yZMwWeQGswGJg9ezbh4eHMnz+fChUqULt2bUJDQ/H29iY5ORl/f38MBgNvvfUWVatW5fDhwzcVy9ixYwkLC8PPzw+z2Uzr1q0JCwtj6NChhISEEBgYiLe3t/XkVrg6c69t27Y8+OCD1gMe0tLSipzt16tXL+tJrd27d2fMmDGMHTuWt99+m8uXL+Pk5EStWrUYPny4tc/UqVOZM2cOV65coX379nTp0qXIbwkJCWHq1Kl069aNrKwsXFxcWLZsWYFF17+z5FloF1S10PY8swWjqegxRERERERERKT0GCzaBEtKSVRUFDVr1iz0tNTyIi8vj8DAQGbOnMlDDz0EwKZNmzh+/PgtnxZbUs6ePcvLL7/Mc889x9NPP13ks8nJyXh5eZVSZHI/SUlJsZ7oLFKclFtSEpRXUlKUW1JSlFtSEpRX5U9hfxPNsJNS88ILL+Du7o6bm5t1pl9gYCBBQUHW2Wll7ccff+Rf//oXNjY2DBkyxDrT78knnyyV9/v4+LBixQpcXFzy3Y+IiKBixYrWAyuqVq1KTEzMTY1Zwa5Cke15uRaMNpphJyIiIiIiIlJeqGAnpcre3t5aaDp//jwhISGkp6cTHByc77nc3NwCl8+WJIvFwkcffcQ777zDs88+C1ytdJ8/f54GDRqUaizFyWA08PN/zhTa3uKVaqUYjYiIiIiIiIjciAp2UmZcXV2ZOHEiffv2Zfjw4axatYrNmzeTk5NDZmYmc+bMYciQIVy6dInc3FxGjBhBp06dOHHiBC+//DKtWrXi559/pkmTJvTp04dZs2aRlpbGtGnT8PT0ZPfu3YSHh5OVlYW9vT3h4eFF7se3fft2bGxsrMU6wDot1WKxMHXqVL7//nsMBgOvv/46vr6+JCYmEhERgaurKwcOHKBz5864ubmxaNEisrOziYyMpF69etaDPk6ePAlAaGgorVq14sKFC4SEhJCWloanp2e+ffLmzJnD6tWrqVmzJi4uLnh4eHDs2DFGjBhhPczjyJEjvPHGG0RHR5fEn0hEREREREREyoAKdlKm6tatS15eHufPnwdg165drFmzBicnJ3Jzc4mMjMTR0ZG0tDSefvpp6/53x44dY+bMmTRu3Ji+ffsSGxvLkiVL2LBhA3PnzuWTTz6hYcOGREVFYWNjw9atW5kxYwYRERGFxnLw4EE8PDwKbPvmm284cOAAMTExXLhwgb59+9K6dWsADhw4QEJCAk5OTjz11FP069ePFStW8MUXX7B48WLGjh3L5MmTCQoKonXr1pw8eZLBgwezdu1aIiMjadmyJcOGDWPz5s0sW7YMgL1795KQkMDq1asxm80EBgbi4eFBvXr1cHR0tK5xj46OJjAwsDj/JCIiIiIiIiJSxlSwkzL391llHTp0wMnJyXp/+vTp/PTTTxiNRk6fPs25c+cAqFOnDk2aNAGgUaNGtG/fHoPBQJMmTUhNTQUgPT2dd955h6NHj2IwGLhy5cptx7hjxw569OiByWSiSpUqeHt7s2fPHhwdHWnevDnVql1dVlqvXj06dOgAgJubG4mJiQBs3bqVQ4cOWcfLyMggIyODn376idmzZwPwxBNPULlyZQCSkpLo1KkTDg4OwNW97a7p168fK1euZMyYMSQkJPDVV1/d9neJiIiIiIiISPmjgp2UqePHj2MymXB1dQWwFqgAYmNjSUtLIzo6GltbW3x8fMjOzgbAzs7O+pzRaLReGwwGzGYzADNnzqRt27ZERkZy4sSJG57w2rhxY9atW1dgW1GHKRcWi9FotMaSl5fHsmXLsLe3LzKGvzMYCj4IomvXrkRGRtKuXTs8PDxwdna+6TFFREREREREpPwrH0dzyn3p2r5uzz//fIHFqfT0dFxdXbG1tWX79u3WmXM3Kz09nerVqwNY93wDOH36NEFBQdc9365dO3Jycli+fLn13u7du/nxxx/x9vZm7dq1mM1m0tLSSEpKwtPT86Zj6dixI1FRUdbrlJQUALy9vYmNjQVgy5Yt/Pnnn9b73377LVlZWWRkZLBp0yZr3woVKtCxY0fee+89evfufdMxiIiIiIiIiMjdQQU7KVVZWVn4+/vTo0cPXnzxRTp06MCwYcMKfNbPz4+9e/fSu3dvYmNjizwwoiAvv/wy06dP55lnnrHOdAM4c+ZMgSfQGgwGZs+ezQ8//ECnTp3o0aMHs2fPplq1atbDJPz9/QkKCuKtt96iatWqNx3L2LFj2bt3L35+fvj6+rJkyRIAhg4dSlJSEoGBgfzwww/UqlULAA8PD3x9ffH39yc4OJhWrVpd99sYDAY6dux4S7+JiIiIiIiIiJR/BktRa/1E7kFRUVHUrFnTeoDF3WjBggWkp6czcuTIGz67f99+mnk0K7Q9L9eC0abg5bciRbl2+IlIcVNuSUlQXklJUW5JSVFuSUlQXpU/hf1NtIed3HdeeOGFsg7hjgwdOpRjx47xxRdflHUoIiIiIiIiIlICVLCTu4q7uztubm7k5uZiMpkIDAwkKCgIo7F8rO6eM2cOcXFxGI1GjEYjYWFhtGjR4o7HTUxMxNbWlpYtWxIZGXlLfQ1GAwdnny60vfGw6ncanoiIiIiIiIgUIxXs5K5ib29PTEwMAOfPnyckJIT09HSCg4PzPZebm1vgPnUlKTk5mc2bN7Nq1Srs7OxIS0vjypUrdzxubm4uP/74IxUrVqRly5bFEKmIiIiIiIiIlGcq2Mldy9XVlYkTJ9K3b1+GDx/OqlWr2Lx5Mzk5OWRmZjJnzhyGDBnCpUuXyM3NZcSIEXTq1IkTJ07w8ssv06pVK37++WeaNGlCnz59mDVrFmlpaUybNg1PT092795NeHg4WVlZ2NvbEx4eXuTBF2fPnsXZ2Rk7OzsAXFxcrG0+Pj50796dxMREAD766CPq169PamoqoaGhpKWl4eLiwvvvv0+tWrUYPXo0lStXZv/+/Tg5ObFz506MRiNr1qxh/PjxnD17lsjISIxGIw888ABffvllyf7YIiIiIiIiIlJqVLCTu1rdunXJy8vj/PnzAOzatYs1a9bg5OREbm4ukZGRODo6kpaWxtNPP209aOLYsWPMnDmTxo0b07dvX2JjY1myZAkbNmxg7ty5fPLJJzRs2JCoqChsbGzYunUrM2bMICIiotBYOnToQGRkJF27dqV9+/b4+vrSpk0ba7ujoyMrVqxg9erVhIeHM2/ePCZOnEhAQACBgYGsWLGCSZMm8cknnwBw5MgRFi5ciMlkIiIigooVKzJ48GDg6imxCxYsoHr16ly6dKmkfl4RERERERERKQMq2Mld7+8HHXfo0AEnJyfr/enTp/PTTz9hNBo5ffo0586dA6BOnTo0adIEgEaNGtG+fXsMBgNNmjQhNTUVgPT0dN555x2OHj2KwWC44fLWSpUqER0dTVJSEomJiYwaNYqQkBB69+4NQM+ePQHo0aMH77//PnB1Ge21IqC/vz8ffvihdbxu3bphMpkKfJeXlxejR4+me/fudO7c+dZ+MBEREREREREp18rHTv0it+n48eOYTCZcXV0BcHBwsLbFxsaSlpZGdHQ0MTExVKlShezsbADrslUAo9FovTYYDJjNZgBmzpxJ27ZtiYuLY86cOeTk5NwwHpPJRNu2bQkODmb8+PF88803t/Q9BoPB+t9//5b/FRYWxsiRI/njjz8ICAjgwoULt/QeERERERERESm/VLCTu1ZaWhoTJkzg+eefz1fouiY9PR1XV1dsbW3Zvn27debczUpPT6d69asnqK5atcp6//Tp0wQFBV33/OHDhzly5Ij1OiUlhVq1almv165dC0BCQgJeXl7A1Zly8fHxwNUCY6tWrQqMpVKlSly+fNl6fezYMVq0aMGIESNwdnbm1KlTt/RtIiIiIiIiIlJ+aUms3FWysrLw9/cnNzcXk8mEv78/L730UoHP+vn58frrr9O7d2/c3d2LPDCiIC+//DKjR4/m888/p127dtb7Z86cKfAE2szMTCZNmsSlS5cwmUzUr1+fsLAwa3tOTg79+vUjLy+P6dOnAzBu3DhCQ0NZsGCB9dCJgjz55JMEBwezYcMGxo8fz8KFCzl69CgWi4V27drRtGnTQr/Dkmeh8bDqhbbn5Vow2lxf8BQRERERERGRsmGw/H0DMBG5oaioKGrWrGk9wOJm+Pj4sGLFinwnx5aW5ORk64w+keKUkpKCu7t7WYch9yDllpQE5ZWUFOWWlBTllpQE5VX5U9jfREti7zNz5syhR48e+Pn54e/vz88//1zos3v27GHSpEkFtiUlJdGjRw/8/f05ffo0wcHBN/X+b7/9liZNmvDbb7/d8NmFCxfy119/Wa9feeWVYj8R9dy5c7z66qv06tULX19fXnnllRv2eeGFF26pWFfWKthVKLLdkquavYiIiIiIiEh5oiWx95Hk5GQ2b97MqlWrsLOzIy0trciTT5s3b07z5s0LbFuzZg2DBg2iT58+AMyaNeumYoiLi6NVq1YkJCQwfPjwIp9dtGgRvXr1sh6+8J///Oem3nErZs2axT/+8Q/rnnQHDhwo9ncAbNy4sUTGvRkGo4HUD/8otL32WzVLMRoRERERERERuRHNsLuPnD17FmdnZ+uJqC4uLtZDFXbv3s0zzzxDr1696Nu3LxkZGSQmJvLqq69eN85XX33F119/TWRkJCEhIZw4cYKePXve8P2XL19m586dTJ482XrQAoDZbGbKlCn4+fnh5+fH4sWLWbRoEWfOnCEoKIgBAwYAV5eVpqWlAfD555/Ts2dPevbsycKFCwE4ceIE3bt3Z9y4cfTo0YNBgwaRlZVVZExnzpyhRo0a1utre8H977eHhYURHR0NwLRp0/D19cXPz48pU6YAMHr0aN59912ee+45unbtyqZNm/J9W58+ffDz82Pp0qXW8QcMGEBwcDDdunUjJCSEa6vTCxo/LS2N4cOH06dPH/r06cOOHTtu+HuLiIiIiIiIyN1JM+zuIx06dCAyMpKuXbvSvn17fH19adOmDTk5OYwaNYoZM2bg6elJRkYG9vb2hY7Tr18/duzYwRNPPEG3bt04ceLETb1//fr1PPbYYzRo0AAnJyf27duHh4cHy5Yt48SJE6xatQobGxsuXryIk5MTCxcu5Isvvrhu37e9e/cSHR3N8uXLsVgs9O/fnzZt2vDggw9y9OhRpk+fzqRJkxgxYgTr1q3D39+/0Jief/55Ro0aRVRUFP/4xz/o3bu3tYhZkIsXL/Ltt9/y9ddfYzAY8i3RTU1NJSoqimPHjjFw4ED+8Y9/sHr1ah544AFWrlxJTk4OzzzzDB06dABg//79xMfHU61aNZ599ll27NhBo0aNChx/8uTJBAUF0bp1a06ePMngwYOtp86KiIiIiIiIyL1FBbv7SKVKlYiOjiYpKYnExERGjRpFSEgIHh4eVK1aFU9PTwAcHR1L5P3x8fHWpae+vr7ExcXh4eHBtm3beOaZZ6wnrzo5ORU5zo4dO+jUqRMVK1YEoHPnziQlJeHj40OdOnWsmzV6eHiQmppa5FiPPfYY69ev5/vvv+e7774jMDCQuLi4Qp93dHSkQoUKjB07lieeeIInnnjC2ta9e3eMRiMPPfQQdevW5fDhw/zwww/88ssvrFu3DoD09HSOHj2Kra0tnp6e1tl9TZs2JTU1lUcffbTA8bdu3cqhQ4es78rIyCAjI6PE/lYiIiIiIiIiUnZUsLvPmEwm2rZtS9u2bXFzc2P16tU0a9YMg8FQZL/Bgwdz7tw5HnnkESZPnnzL771w4QLbt2/n4MGDGAwGzGYzBoOBt99+G4vFcsP3/11RBxtfW+4LV781Ozv7huM5OTlZl+O++uqr/PTTT7i6upKXl2d95to4NjY2rFixgm3bthEfH09UVBSLFi0CuO4bDAYDFouFcePG8dhjj+VrS0xMvC5Ws9lc6Ph5eXksW7asyJmPIiIiIiIiInJv0B5295HDhw9z5MgR63VKSgq1atWiYcOGnDlzht27dwNXZ2/l5ubm67tgwQJiYmJuWKw7ffq0dRbd361bt46AgAA2bdrExo0b2bJlC3Xq1GHHjh106NCBpUuXWt958eJF4OqMwMuXL183lre3N+vXr+evv/4iMzOT9evX07p16yLjioqKIioq6rr727Zts55Em5GRwbFjx6hZsya1a9fmt99+Iycnh/T0dLZt2wZc3YcvPT2dxx9/nNDQ0HyHVHz99dfk5eVx7Ngxjh8/ToMGDejYsSNLliyxHu7x+++/k5mZWWichY3fsWPHfPGnpKQU+b0iIiIiIiIicvfSDLv7SGZmJpMmTeLSpUuYTCbq169PWFgYdnZ2zJgxg0mTJpGVlYW9vT2ff/75bb3jzJkz1qWtfxcfH88rr7yS716XLl2IjY1l/PjxHDlyhF69emFjY0P//v154YUX6N+/P6+88gpVq1Zl8eLF1n4eHh707t2bfv36AdC3b1+aNWtW5F56hw8fpmXLltfd37dvHxMnTsRkMmGxWOjXr591aXC3bt3w8/PjoYceolmzZsDVgtqQIUOsM+7GjBljHatBgwa88MILnD9/nn//+99UqFCBfv36kZqaSu/evbFYLDg7O/PJJ58UGmdh448dO5awsDD8/Pwwm820bt2asLCwQscRERERERERkbuXwVLU+kKRWxQVFUXNmjV56qmnyjqUfF599VUiIiLyLUMtTqNHj7YewlHe7N+3n2YezQptt+RaMNjc/JJkkWtSUlKse0aKFCfllpQE5ZWUFOWWlBTllpQE5VX5U9jfRDPspFi98MILZR1CgebNm1fWIZSZ7Jyi9/FTsU5ERERERESkfNEMO5Ey4OXlRXJyMgBbtmxh8uTJLFy4kC1btuDg4EBAQEC+50+cOMFrr71W5Am2hbnRDDsRERERERGRu5UlNw+Dzd17RINm2ImUQ9u2bWPixIl89tln1KpVi2effbbY32EwGjg17XCxjysiIiIiIiJS1mq82bCsQygRKtiJlJGkpCTGjRvH/PnzqVevHgARERFUrFiRwYMHs3fvXkJDQ3FwcMh3YMbBgwcZM2YMV65cIS8vj4iICB566KEy+goRERERERERKW4q2ImUgZycHIYMGcKiRYt4+OGHC3xmzJgxjB8/njZt2jBlyhTr/aVLlzJw4EB69epFTk4OeXl5pRW2iIiIiIiIiJSCu3eRr8hdzMbGBi8vL1asWFFge3p6Ounp6bRp0wYAf39/a9ujjz7KvHnzmD9/PidPnsTe3r5UYhYRERERERGR0qGCnUgZMBqNfPzxx+zdu5e5c+de126xWDAYCj691c/Pjzlz5mBvb8/gwYPZtm1bSYcrIiIiIiIiIqVIBTuRMuLg4MDcuXOJjY3lq6++ytf24IMP4ujoSFJSEgCxsbHWtuPHj1O3bl0GDhyIj48Pv/zyS6nGLSIiIiIiIiIlS3vYiZQhJycnPv30U55//nmcnZ3ztb3//vvWQyc6duxovZ+QkMCaNWuwsbGhSpUqDB06tMh3WPIs9+ypOSIiIiIiInJ/s+TmYbC59+ajGSwWi6WsgxCRkpOcnIyXl1dZhyH3oJSUFNzd3cs6DLkHKbekJCivpKQot6SkKLekJCivyp/C/ib3XglSRPKpYFfhtvtacnUCrYiIiIiIiEhp05JYue99++23DBs2jISEBB5++OHr2gcMGMDbb79N8+bNi+2d69ev56GHHqJRo0bFNmZhDEYDp6bvu62+Nd7wKOZoRERERERERORGNMNO7ntxcXG0atWKhISEUnvn+vXrOXTo0C31yc3NLaFoRERERERERKQ8UcFO7muXL19m586dTJ48mfj4eACysrIYNWoUfn5+jBw5kqysLAD++9//MnXqVGvf6OhoJk6cCEBMTAx9+/bF39+fd999F7PZDICXlxczZsygV69e9O/fn3PnzrFz5042btzI1KlT8ff359ixYwwYMIA9e/YAkJaWho+Pj/UdwcHBvPbaawwaNIjMzEzGjBlDnz59CAgIYP369aX2W4mIiIiIiIhI6VDBTu5r69ev57HHHqNBgwY4OTmxb98+lixZgr29PbGxsbz22mvs23d1OWm3bt349ttvrX0TEhLo3r07v/32G2vXrmXJkiXExMRgNBqJjY0FIDMzkxYtWrBmzRpat27N8uXLadmyJT4+Prz99tvExMRQr169ImPctWsXH3zwAYsWLWLu3Lm0a9eOlStXsmjRIj788EMyMzNL7gcSERERERERkVKnPezkvhYfH09QUBAAvr6+xMXFcfToUQYMGABA06ZNadKkCQAuLi7UrVuXXbt2Ub9+fX7//XdatWrFl19+yd69e+nbty9wdYaeq6srALa2tjz55JMAPPLII/zwww+3HGOHDh1wcnIC4P/9v//Hxo0b+eyzzwDIzs7mjz/+KHDvPRERERERERG5O6lgJ/etCxcusH37dg4ePIjBYMBsNmMwGHB3d8dgMBTYp3v37qxdu5aGDRvSuXNnDAYDFouFwMBAQkJCrnve1tbWOpbRaLQulf1fJpMJi8UCQE5OTr42BweHfNezZs2iYcOGt/y9IiIiIiIiInJ30JJYuW+tW7eOgIAANm3axMaNG9myZQt16tTBw8PDuqT1119/5ZdffrH26dKlC+vXrycuLg5fX18A2rdvz7p16zh//jwAFy9eJDU1tch3V6pUicuXL1uva9euzd69ewH4+uuvC+3XsWNHoqKirMW9/fv338aXi4iIiIiIiEh5phl2ct+Kj4/nlVdeyXevS5cupKSkkJWVhZ+fH+7u7nh6elrbK1euTKNGjTh06JD1fqNGjRg5ciSDBg0iLy8PW1tb3n33XWrXrl3ou319fRk/fjyLFy9m1qxZDBo0iJEjR7JmzRratm1baL8hQ4YQHh5Or169sFgs1K5dm3nz5hX5nZY8CzXe8LiZn+T6vrl5GGxU1xcREREREREpTQbLtak6InJPSk5OxsvLq6zDkHtQSkoK7u7uZR2G3IOUW1ISlFdSUpRbUlKUW1ISlFflT2F/E02dkXLn78WlLVu20KVLF06ePMmSJUtYvXr1dc+fOHGCnj173vb70tLS8PDwYOnSpTf1fGFx3I65c+fmu37mmWeKZdy/q2BX4bb7WnLzijESEREREREREbkZWhIr5da2bduYOHEin332GbVq1eLZZ58tkfesXbuWFi1aEB8ff1MFs+KMY968ebz22mvW65stGt4Kg9HA6Y933Fbf6iNbFXM0IiIiIiIiInIjKthJuZSUlMS4ceOYP38+9erVAyAiIoKKFSsyePBg9u7dS2hoKA4ODrRs2dLa7+DBg4wZM4YrV66Ql5dHREQEDz30UJHvio+PZ/To0YSEhHD69GmqV68OXJ3pN3DgQDZt2oS9vT2ffPIJVapUyRfHgAEDcHd3Z9++faSlpTFlyhTmz5/Pr7/+Svfu3Rk1ahRwde+5U6dOkZ2dzcCBA3n66aeZNm0aWVlZ+Pv706hRIz766CO8vLxITk7GYrEwdepUvv/+ewwGA6+//jq+vr4kJiYye/ZsnJ2d+fXXX/Hw8GDatGmFnmorIiIiIiIiIncfLYmVcicnJ4chQ4YQGRnJww8/XOAzY8aMYdy4cSxbtizf/aVLlzJw4EBiYmJYuXIlNWrUKPJdf/zxB+fOncPT05Pu3buTkJBgbcvMzKRFixasWbOG1q1bs3z58gLHsLW15csvv+SZZ55hyJAhvPvuu8TFxbFq1SouXLgAQHh4ONHR0axcuZLFixdz4cIF3nzzTezt7YmJieGjjz7KN+Y333zDgQMHiImJ4fPPP2fq1KmcOXMGuHoybGhoKAkJCZw4cYIdO25v9pyIiIiIiIiIlE8q2Em5Y2Njg5eXFytWrCiwPT09nfT0dNq0aQOAv7+/te3RRx9l3rx5zJ8/n5MnT2Jvb1/ku+Lj4+nevTtw9eTWuLg4a5utrS1PPvkkAI888gipqakFjuHj4wOAm5sbjRs3plq1atjZ2VG3bl1OnToFwOLFi+nVqxf9+/fnjz/+4OjRo0XGtWPHDnr06IHJZKJKlSp4e3uzZ88eADw9PalRowZGo5GmTZsWGpeIiIiIiIiI3J1UsJNyx2g08vHHH7N3797rDmUAsFgshS4B9fPzY86cOdjb2zN48GC2bdtW5Lvi4+OJjo7Gx8eHIUOG8Msvv3DkyBHgasHu2nuMRiNms7nAMezs7KzPXPvva9e5ubkkJiaydetWli1bxpo1a2jWrBnZ2dlFxlXU4c1/f4fJZCo0LhERERERERG5O6lgJ+WSg4MDc+fOJTY2lq+++ipf24MPPoijoyNJSUkAxMbGWtuOHz9O3bp1GThwID4+Pvzyyy8ABAUFcfr06XzjHD58mMzMTL7//ns2btzIxo0b+de//kV8fHyxfkt6ejqVK1fGwcGB3377jV27dlnbbGxsuHLlynV9vL29Wbt2LWazmbS0NJKSkvD09CzWuERERERERESkfNKhE1JuOTk58emnn/L888+QDMt0AAAWTElEQVTj7Oycr+3999+3HjrRsWNH6/2EhATWrFmDjY0NVapUYejQoeTl5XHs2DEqV66cb4z4+Hg6d+6c716XLl144403GDp0aLF9xz//+U+WLl2Kn58fDRo04NFHH7W29e/fn169etGsWbN8+9h17tyZ5ORk/P39MRgMvPXWW1StWpXDhw/f8vsteZbbPu3VkpuHwUZ1fREREREREZHSZLAUtfZO5B7w66+/snLlSsaMGVPWoZSJ5ORkvLy8yjoMuQelpKTg7u5e1mHIPUi5JSVBeSUlRbklJUW5JSVBeVX+FPY30dQZuee5ubndt8U6gAp2FW67ryU3rxgjEREREREREZGboSWxct/79ttvGTZsGAkJCTz88MNFPjt27FheeuklGjVqdEfvPHHiBMnJyfj5+QGwZ88eYmJiGDdu3B2NWxCD0cDpmT/cVt/qIzoUczQiIiIiIiIiciOaYSf3vbi4OFq1akVCQsINn508efIdF+sAUlNTiYuLs143b968RIp1IiIiIiIiInL3UcFO7muXL19m586dTJ482Xo6bGJiIgMGDCA4OJhu3boREhLCta0eBwwYwJ49ewDw8vLiww8/pHfv3rz44ovs3r2bAQMG8NRTT7Fhwwbg6ky65557jsDAQAIDA9m5cycAH330EUlJSfj7+7Nw4UISExN59dVXAbh48SJDhgzBz8+P/v37c+DAAQAiIiIYM2aM9R2LFi0q1d9KREREREREREqHCnZyX1u/fj2PPfYYDRo0wMnJiX379gGwf/9+QkNDSUhI4MSJE+zYseO6vpmZmbRp04bo6GgqVarExx9/zGeffUZkZCSzZs0CwNXVlc8//5xVq1YxY8YMJk2aBEBISAitW7cmJiaGF198Md+4ERERNGvWjNjYWEaNGsU777xjbfv9999ZsGABX331FZGRkVy5cqWEfhkRERERERERKSvaw07ua/Hx8QQFBQHg6+tLXFwcTzzxBJ6entSoUQOApk2bkpqaSuvWrfP1tbW15Z///Cdw9WALOzs7bG1tcXNzIzU1FYDc3FzCwsI4cOAARqORI0eO3DCmHTt2EBERAUD79u25ePEi6enpADz++OPY2dnh4uKCi4sL58+ft8YpIiIiIiIiIvcGFezkvnXhwgW2b9/OwYMHMRgMmM1mDAaDtSh2jclkwmw2X9ff1tYWg8EAgNFotPYxGo3W5xcuXEiVKlWIiYkhLy8PT0/PG8Z1bfnt3117z//GlZubewtfLCIiIiIiIiJ3Ay2JlfvWunXrCAgIYNOmTWzcuJEtW7ZQp06dApe/3q709HSqVq2K0WgkJibGWsirVKkSly9fLrCPt7c3a9asAa7up+fs7Iyjo2OxxSQiIiIiIiIi5Ztm2Ml9Kz4+nldeeSXfvS5durBkyRLq1atXLO947rnnGD58OF9//TVt27alYsWKADRp0gSTyUSvXr3o3bs37u7u1j7Dhg1jzJgx+Pn54eDgwAcffHBHMVjyLFQf0eH2+ubmYbBRXV9ERERERESkNBksBa2/E5F7RnJyMl5eXmUdhtyDUlJS8hWbRYqLcktKgvJKSopyS0qKcktKgvKq/Cnsb6IZdiLFaM6cOcTFxWE0GjEajYSFhdGiRYs7GjMxMRFbW1tatmx5W/0r2FUost2Sa8ZgY7qtsUVERERERESk+KlgJ1JMkpOT2bx5M6tWrcLOzo60tDSuXLlyR2Pm5uby448/UrFixdsu2BmMBs5EbCi0vdrwp243PBEREREREREpASrYiRSTs2fP4uzsbD3J1cXFBQAfHx+6d+9OYmIiAB999BH169cnNTWV0NBQ0tLScHFx4f3336dWrVqMHj2aypUrs3//fpycnNi5cydGo5E1a9Ywfvx4zp49S2RkJEajkQceeIAvv/yyzL5ZRERERERERIqfCnYixaRDhw5ERkbStWtX2rdvj6+vL23atAHA0dGRFStWsHr1asLDw5k3bx4TJ04kICCAwMBAVqxYwaRJk/jkk08AOHLkCAsXLsRkMhEREUHFihUZPHgwAH5+fixYsIDq1atz6dKlMvteERERERERESkZOv5RpJhUqlSJ6OhowsLCcHFxYdSoUURHRwPQs2dPAHr06MGuXbuAq0tor9339/dnx44d1rG6deuGyVTwvnJeXl6MHj2a5cuXYzabS/KTRERERERERKQMaIadSDEymUy0bduWtm3b4ubmxurVq2+6r8FgsP63g4NDoc+FhYXx888/s3nzZgICAli9ejXOzs53FLeIiIiIiIiIlB+aYSdSTA4fPsyRI0es1ykpKdSqVQuAtWvXApCQkICXlxdwdaZcfHw8ALGxsbRq1arAcStVqsTly5et18eOHaNFixaMGDECZ2dnTp06VRKfIyIiIiIiIiJlRDPsRIpJZmYmkyZN4tKlS5hMJurXr09YWBibN28mJyeHfv36kZeXx/Tp0wEYN24coaGhLFiwwHroREGefPJJgoOD2bBhA+PHj2fhwoUcPXoUi8VCu3btaNq0aWl+poiIiIiIiIiUMBXsRIrJI488wtKlSwtse+655xg2bFi+e3Xq1GHRokXXPfvBBx/ku27QoAGxsbHW69atW99SXJY8C9WGP1V4e64Zg03B++WJiIiIiIiISOnTkliRe1x2TnaR7SrWiYiIiIiIiJQvmmEn8j/c3d1xc3PDbDZTp04dpk6dyoMPPnjb423cuLEYo7t1FezsimzXDDsRERERERGR8kUFO5H/YW9vT0xMDADvvPMOX375Ja+//noZR3X7DEYjZ2YnFNpebZhvKUYjIiIiIiIiIjeigp1IER599FF++eUX4OqprxMmTOCvv/6iXr16hIeHU7lyZQYMGIC7uzv79u0jLS2NKVOmMH/+fH799Ve6d+/OqFGjABgyZAinTp0iOzubgQMH8vTTTwNXT4sdOHAgmzZtwt7enk8++YQqVapw7tw5JkyYwPHjxwF47733aNmyJTExMSxevJgrV67QokULJkyYgMmkGXIiIiIiIiIi9wrtYSdSCLPZzLZt2/Dx8QHg7bff5s033yQ2NhY3Nzdmz55tfdbW1pYvv/ySZ555hiFDhvDuu+8SFxfHqlWruHDhAgDh4eFER0ezcuVKFi9ebL2fmZlJixYtWLNmDa1bt2b58uUATJo0CW9vb9asWcOqVato3Lgxv/32G2vXrmXJkiXExMRgNBrzHUghIiIiIiIiInc/zbAT+R9ZWVn4+/uTmpqKh4cHHTp0ID09nfT0dNq0aQNAYGAgI0aMsPa5VtRzc3OjcePGVKtWDYC6dety6tQpnJ2dWbx4Md9++y0Af/zxB0ePHsXZ2RlbW1uefPJJ4OpJsz/88AMA27dvZ+rUqQCYTCYeeOABYmJi2Lt3L3379rXG6urqWgq/ioiIiIiIiIiUFhXsRP7HtT3s0tPTefXVV/nyyy8JDAwsso/d/3+wg9FotP73tevc3FwSExPZunUry5Ytw8HBgQEDBpCdffX0VltbWwwGg/V5s9lc6HssFguBgYGEhITc6WeKiIiIiIiISDmlJbEihXjggQcYN24cn332Gfb29jz44IMkJSUBEBMTg7e3902PlZ6eTuXKlXFwcOC3335j165dN+zTvn17/vvf/wJXl+dmZGTQvn171q1bx/nz5wG4ePEiqampt/F1IiIiIiIiIlJeaYadSBGaNWtG06ZNiY+PZ8qUKdZDJ+rWrcv7779/0+P885//ZOnSpfj5+dGgQQMeffTRG/YZO3Ys48ePZ+XKlRiNRt577z28vLwYOXIkgwYNIi8vD1tbW959911q165d6DiWvLwiT4K15Jox2OjQChEREREREZHywmCxWCxlHYSIlJzk5GS8vLzKOgy5B6WkpODu7l7WYcg9SLklJUF5JSVFuSUlRbklJUF5Vf4U9jfRkliRe1yFv+2pd7+w5Ba+D6CIiIiIiIhIeaclsSIl4OzZs4SHh7Nnzx7s7OyoXbs2oaGhNGjQIN9zzzzzDEuXLi3RWAxGI2cio0v0HeVNtaG9yzoEERERERERkdumgp1IMbNYLAwbNoyAgABmzJgBXJ3iev78eWvBzmw2YzKZSrxYJyIiIiIiIiJ3HxXsRIrZ9u3bsbGx4dlnn7Xec3d3JzExkQEDBlCtWjVSUlJISEjAy8uL5ORkEhMTiYiIwNXVlQMHDtC5c2fc3NxYtGgR2dnZREZGUq9ePdLS0pgwYQInT54EIDQ0lFatWpXVp4qIiIiIiIhICVDBTqSYHTx4EA8PjwLb9uzZQ2xsLHXr1r2u7cCBAyQkJODk5MRTTz1Fv379WLFiBV988QWLFy9m7NixTJ48maCgIFq3bs3JkycZPHgwa9euLelPEhEREREREZFSpIKdSClq3rx5gcW6a23VqlUDoF69enTo0AEANzc3EhMTAdi6dSuHDh2y9snIyCAjIwNHR8cSjlxERERERERESosKdiLFrHHjxqxbt67AtooVKxbaz+5vp7kajUbrtdFoxGy+euppXl4ey5Ytw97evhgjFhEREREREZHyxFjWAYjca9q1a0dOTg7Lly+33tu9ezc//fTTHY/dsWNHoqKirNcpKSl3PKaIiIiIiIiIlC+aYSdSzAwGA7NnzyY8PJz58+dToUIFateuTadOne547LFjxxIWFoafnx9ms5nWrVsTFhZWZB9LXh7Vhva+43ffTSy5Zgw2prIOQ0REREREROS2GCwWi6WsgxCRkrNr1y4qVKhQ1mGIiIiIiIiIyP/Izs7m0Ucfve6+CnYiIiIiIiIiIiLliPawExERERERERERKUdUsBMRERERERERESlHVLATEREREREREREpR1SwExERERERERERKUdUsBMRERERERERESlHVLATuYd99913dO3alc6dOzN//vyyDkfuUn/88QcDBgyge/fu9OjRgy+++AKAixcv8tJLL9GlSxdeeukl/vzzzzKOVO5WZrOZgIAAXn31VUC5JcXj0qVLBAcH061bN7p3705ycrJyS+7YwoUL6dGjBz179uSNN94gOztbeSW3ZcyYMbRv356ePXta7xWVS/PmzaNz58507dqV77//vixClrtEQbk1ZcoUunXrhp+fH0OHDuXSpUvWNuVW+aWCncg9ymw2ExYWxqeffkp8fDxxcXEcOnSorMOSu5DJZGL06NGsXbuWZcuW8d///pdDhw4xf/582rdvzzfffEP79u1VFJbbtmjRIh5++GHrtXJLisPkyZN57LHH+Prrr4mJieHhhx9WbskdOX36NIsWLWLlypXExcVhNpuJj49XXslt6d27N59++mm+e4Xl0qFDh4iPjyc+Pp5PP/2Uf//735jN5rIIW+4CBeVWhw4diIuLIzY2loceeoh58+YByq3yTgU7kXvU7t27qV+/PnXr1sXOzo4ePXqwYcOGsg5L7kLVqlXDw8MDAEdHRxo2bMjp06fZsGEDAQEBAAQEBLB+/fqyDFPuUqdOnWLz5s307dvXek+5JXcqIyODn376yZpXdnZ2PPjgg8otuWNms5msrCxyc3PJysqiWrVqyiu5Ld7e3lSuXDnfvcJyacOGDfTo0QM7Ozvq1q1L/fr12b17d6nHLHeHgnKrY8eO2NjYAPDoo49y6tQpQLlV3qlgJ3KPOn36NDVq1LBeV69endOnT5dhRHIvOHHiBCkpKbRo0YLz589TrVo14GpRLy0trYyjk7tReHg4b731Fkbj//2TRLkld+r48eO4uLgwZswYAgICGDt2LJmZmcotuSPVq1dn0KBBPPnkk3Ts2BFHR0c6duyovJJiU1gu6d/1UpxWrlzJP//5T0C5Vd6pYCdyj7JYLNfdMxgMZRCJ3CsuX75McHAwoaGhODo6lnU4cg/YtGkTLi4uPPLII2UditxjcnNz2b9/P88++yyrV6/GwcFByxTljv35559s2LCBDRs28P333/PXX38RExNT1mHJfUD/rpfiMmfOHEwmE7169QKUW+WdTVkHICIlo0aNGtapznD1/z259v/YidyqK1euEBwcjJ+fH126dAHA1dWVM2fOUK1aNc6cOYOLi0sZRyl3m507d7Jx40a+++47srOzycjI4M0331RuyR2rUaMGNWrUoEWLFgB069aN+fPnK7fkjmzdupU6depY86ZLly4kJycrr6TYFJZL+ne9FIdVq1axefNmFi5caC3KKbfKN82wE7lHNW/enCNHjnD8+HFycnKIj4/Hx8enrMOSu5DFYmHs2LE0bNiQl156yXrfx8eH1atXA7B69WqeeuqpsgpR7lIhISF89913bNy4kenTp9OuXTumTZum3JI7VrVqVWrUqMHhw4cB2LZtGw8//LByS+5IrVq1+Pnnn/nrr7+wWCzKKyl2heWSj48P8fHx5OTkcPz4cY4cOYKnp2dZhip3me+++47//Oc/zJkzBwcHB+t95Vb5ZrAUNAdSRO4JW7ZsITw8HLPZTJ8+fXj99dfLOiS5CyUlJfH888/j5uZm3WfsjTfewNPTk5EjR/LHH39Qs2ZNZs6ciZOTUxlHK3erxMREPvvsM+bNm8eFCxeUW3LHUlJSGDt2LFeuXKFu3bq8//775OXlKbfkjsyaNYuEhARsbGxwd3dn8uTJXL58WXklt+yNN97gxx9/5MKFC7i6ujJ8+HA6depUaC7NmTOHlStXYjKZCA0N5fHHHy/jL5DyqqDcmj9/Pjk5OdZ8atGiBWFhYYByqzxTwU5ERERERERERKQc0ZJYERERERERERGRckQFOxERERERERERkXJEBTsREREREREREZFyRAU7ERERkf+vnbt1iTaL4zj8dVwMWmRAEcyCGAQxzX9g8BVEMIyTBDFYRBAxCv4HmgRfgsUgiDDFrmEwaTGPwaJFDKKzTdiw6/Kgzuyz15XucJ/D79QP574BAKCFCHYAAAAA0EIEOwAA+A3t7+/n5eWl2WMAAL9AsAMAgN/Q4eGhYAcA/1GCHQAANMnp6WkmJiYyOTmZtbW11Ov1VCqVTExMpFKp5P7+Pkmyvr6earX6sW5kZCRJcnV1lXK5nJWVlYyNjWV1dTWNRiOHh4d5eHhIpVJJuVxuytkAgF/3R7MHAACA/6O7u7vs7u7m+Pg4xWIxT09PWV9fz/T0dGZmZnJycpKtra3s7Oz84z63t7c5Pz9Pb29v5ufnU6vVsrCwkP39/RwcHKRYLP7QiQCAr+KGHQAANMHl5WXGxsY+glp3d3eur68zPj6eJJmamkqtVvt0n+Hh4fT19aVQKGRwcDD1ev1b5wYAvp9gBwAATdBoND59p62tLUnS3t6e9/f3j3Wvr68f73R0dHw8t7e35+3t7YsnBQB+mmAHAABNUCqVUq1W8/j4mCR5enrKyMhIzs/PkyRnZ2cZHR1NkvT39+fm5iZJcnFx8Zdg93e6urry/Pz8TdMDAN/JP+wAAKAJBgYGsrS0lHK5nEKhkKGhoWxubmZjYyN7e3spFovZ3t5OkszNzWV5eTmzs7MplUrp7Oz8dP+5ubksLi6mp6cnR0dH330cAOALtTX+zV18AAAAAOBH+CQWAAAAAFqIYAcAAAAALUSwAwAAAIAWItgBAAAAQAsR7AAAAACghQh2AAAAANBCBDsAAAAAaCGCHQAAAAC0kD8BeKDcYDxrjDIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1296x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting the shows by genres\n",
    "plt.figure(figsize = (18,9))\n",
    "sns.countplot(y = 'Genre', data = prime_df);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.055993,
     "end_time": "2020-10-03T11:33:38.112154",
     "exception": false,
     "start_time": "2020-10-03T11:33:38.056161",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "It is pretty evident that shows of genre Kids, Drama and Comedy are very high compared to others"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:38.241511Z",
     "iopub.status.busy": "2020-10-03T11:33:38.240714Z",
     "iopub.status.idle": "2020-10-03T11:33:38.417026Z",
     "shell.execute_reply": "2020-10-03T11:33:38.417646Z"
    },
    "papermill": {
     "duration": 0.249488,
     "end_time": "2020-10-03T11:33:38.417811",
     "exception": false,
     "start_time": "2020-10-03T11:33:38.168323",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting age of viewers\n",
    "sns.countplot(x = 'Age of viewers', data = prime_df);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.054434,
     "end_time": "2020-10-03T11:33:38.527619",
     "exception": false,
     "start_time": "2020-10-03T11:33:38.473185",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Most shows offered are for people above 16 years or for all age groups"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.054343,
     "end_time": "2020-10-03T11:33:38.636829",
     "exception": false,
     "start_time": "2020-10-03T11:33:38.582486",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Highest rated shows on Amazon Prime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:38.754201Z",
     "iopub.status.busy": "2020-10-03T11:33:38.753368Z",
     "iopub.status.idle": "2020-10-03T11:33:38.771056Z",
     "shell.execute_reply": "2020-10-03T11:33:38.770251Z"
    },
    "papermill": {
     "duration": 0.079389,
     "end_time": "2020-10-03T11:33:38.771197",
     "exception": false,
     "start_time": "2020-10-03T11:33:38.691808",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>The Test: A New Era for Australia's Team</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>9.0</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>281</th>\n",
       "      <td>Seinfeld</td>\n",
       "      <td>1990</td>\n",
       "      <td>9</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.8</td>\n",
       "      <td>13+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>The Grand Tour</td>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td>English</td>\n",
       "      <td>Sports</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Marvelous Mrs. Maisel</td>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama, Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fleabag</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Hostel Daze</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama, Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Downtown Abbey</td>\n",
       "      <td>2010</td>\n",
       "      <td>6</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.7</td>\n",
       "      <td>7+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>This is Us</td>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>The Boys</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Action, Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Dexter</td>\n",
       "      <td>2006</td>\n",
       "      <td>8</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.6</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Name of the show  Year of release  \\\n",
       "20   The Test: A New Era for Australia's Team             2020   \n",
       "281                                  Seinfeld             1990   \n",
       "340                            The Grand Tour             2017   \n",
       "2                   The Marvelous Mrs. Maisel             2017   \n",
       "4                                     Fleabag             2016   \n",
       "37                                Hostel Daze             2019   \n",
       "49                             Downtown Abbey             2010   \n",
       "51                                 This is Us             2017   \n",
       "12                                   The Boys             2019   \n",
       "40                                     Dexter             2006   \n",
       "\n",
       "     No of seasons available Language           Genre  IMDb rating  \\\n",
       "20                         1  English     Documentary          9.0   \n",
       "281                        9  English          Comedy          8.8   \n",
       "340                        4  English          Sports          8.7   \n",
       "2                          3  English   Drama, Comedy          8.7   \n",
       "4                          2  English          Comedy          8.7   \n",
       "37                         1    Hindi   Drama, Comedy          8.7   \n",
       "49                         6  English           Drama          8.7   \n",
       "51                         3  English           Drama          8.7   \n",
       "12                         1  English  Action, Comedy          8.7   \n",
       "40                         8  English           Drama          8.6   \n",
       "\n",
       "    Age of viewers  \n",
       "20             16+  \n",
       "281            13+  \n",
       "340            16+  \n",
       "2              16+  \n",
       "4              18+  \n",
       "37             16+  \n",
       "49              7+  \n",
       "51             16+  \n",
       "12             18+  \n",
       "40             18+  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df.sort_values(by = 'IMDb rating', ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:38.893381Z",
     "iopub.status.busy": "2020-10-03T11:33:38.892626Z",
     "iopub.status.idle": "2020-10-03T11:33:38.910368Z",
     "shell.execute_reply": "2020-10-03T11:33:38.909613Z"
    },
    "papermill": {
     "duration": 0.082309,
     "end_time": "2020-10-03T11:33:38.910490",
     "exception": false,
     "start_time": "2020-10-03T11:33:38.828181",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Genre</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Action, Comedy</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comedy</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comedy, Drama</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Documentary</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama, Action</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama, Action, Suspense</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama, Comedy</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama, Suspense</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama, Suspense, Horror</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kids</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sci-fi</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sports</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Name of the show  Year of release  \\\n",
       "Genre                                                        \n",
       "Action, Comedy                          1                1   \n",
       "Comedy                                  3                3   \n",
       "Comedy, Drama                           1                1   \n",
       "Documentary                             1                1   \n",
       "Drama                                  11               11   \n",
       "Drama, Action                           1                1   \n",
       "Drama, Action, Suspense                 1                1   \n",
       "Drama, Comedy                           2                2   \n",
       "Drama, Suspense                         3                3   \n",
       "Drama, Suspense, Horror                 1                1   \n",
       "Kids                                    3                3   \n",
       "Sci-fi                                  1                1   \n",
       "Sports                                  1                1   \n",
       "\n",
       "                         No of seasons available  Language  IMDb rating  \\\n",
       "Genre                                                                     \n",
       "Action, Comedy                                 1         1            1   \n",
       "Comedy                                         3         3            3   \n",
       "Comedy, Drama                                  1         1            1   \n",
       "Documentary                                    1         1            1   \n",
       "Drama                                         11        11           11   \n",
       "Drama, Action                                  1         1            1   \n",
       "Drama, Action, Suspense                        1         1            1   \n",
       "Drama, Comedy                                  2         2            2   \n",
       "Drama, Suspense                                3         3            3   \n",
       "Drama, Suspense, Horror                        1         1            1   \n",
       "Kids                                           3         3            3   \n",
       "Sci-fi                                         1         1            1   \n",
       "Sports                                         1         1            1   \n",
       "\n",
       "                         Age of viewers  \n",
       "Genre                                    \n",
       "Action, Comedy                        1  \n",
       "Comedy                                3  \n",
       "Comedy, Drama                         1  \n",
       "Documentary                           1  \n",
       "Drama                                11  \n",
       "Drama, Action                         1  \n",
       "Drama, Action, Suspense               1  \n",
       "Drama, Comedy                         2  \n",
       "Drama, Suspense                       3  \n",
       "Drama, Suspense, Horror               1  \n",
       "Kids                                  3  \n",
       "Sci-fi                                1  \n",
       "Sports                                1  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(prime_df.sort_values(by = 'IMDb rating', ascending = False).head(30)).groupby(['Genre']).count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.057887,
     "end_time": "2020-10-03T11:33:39.025648",
     "exception": false,
     "start_time": "2020-10-03T11:33:38.967761",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Lowest rated shows on Amazon Prime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:39.160393Z",
     "iopub.status.busy": "2020-10-03T11:33:39.159343Z",
     "iopub.status.idle": "2020-10-03T11:33:39.163844Z",
     "shell.execute_reply": "2020-10-03T11:33:39.163258Z"
    },
    "papermill": {
     "duration": 0.079628,
     "end_time": "2020-10-03T11:33:39.163972",
     "exception": false,
     "start_time": "2020-10-03T11:33:39.084344",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>Ilana Glazer: The Planet is Burning</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>3.7</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Tokyo Alice</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>Drama</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>Skulls and Roses</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Action</td>\n",
       "      <td>4.3</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>L.O.L Surprise</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>4.3</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>Wishenpoof</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>4.4</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>Alvin and the Chipmunks</td>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>4.5</td>\n",
       "      <td>7+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>Businessmen VS Aliens</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>4.5</td>\n",
       "      <td>13+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>Alice Wettlund: My Mama is a Human and So Am I</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>4.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>466</th>\n",
       "      <td>Strawberry Shortcake</td>\n",
       "      <td>2003</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>4.8</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>G.I. Joe Sigma Six</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>4.9</td>\n",
       "      <td>7+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Name of the show  Year of release  \\\n",
       "367             Ilana Glazer: The Planet is Burning             2020   \n",
       "162                                     Tokyo Alice             2019   \n",
       "243                                Skulls and Roses             2019   \n",
       "428                                  L.O.L Surprise             2019   \n",
       "413                                      Wishenpoof             2015   \n",
       "430                         Alvin and the Chipmunks             2017   \n",
       "375                           Businessmen VS Aliens             2018   \n",
       "317  Alice Wettlund: My Mama is a Human and So Am I             2019   \n",
       "466                            Strawberry Shortcake             2003   \n",
       "473                              G.I. Joe Sigma Six             2006   \n",
       "\n",
       "     No of seasons available  Language   Genre  IMDb rating Age of viewers  \n",
       "367                        1   English  Comedy          3.7            18+  \n",
       "162                        1  Japanese   Drama          4.0            13+  \n",
       "243                        1     Hindi  Action          4.3            18+  \n",
       "428                        1   English    Kids          4.3            All  \n",
       "413                        4   English    Kids          4.4            All  \n",
       "430                        4   English    Kids          4.5             7+  \n",
       "375                        1  Japanese  Comedy          4.5            13+  \n",
       "317                        1   English  Comedy          4.7            16+  \n",
       "466                        1   English    Kids          4.8            All  \n",
       "473                        1   English    Kids          4.9             7+  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df.sort_values(by = 'IMDb rating').head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:39.298240Z",
     "iopub.status.busy": "2020-10-03T11:33:39.286968Z",
     "iopub.status.idle": "2020-10-03T11:33:39.303303Z",
     "shell.execute_reply": "2020-10-03T11:33:39.302632Z"
    },
    "papermill": {
     "duration": 0.080691,
     "end_time": "2020-10-03T11:33:39.303427",
     "exception": false,
     "start_time": "2020-10-03T11:33:39.222736",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Genre</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Action</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comedy</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comedy, Arts, Entertainment, Culture</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama, Action</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drama, Comedy</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kids</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Name of the show  Year of release  \\\n",
       "Genre                                                                     \n",
       "Action                                               1                1   \n",
       "Comedy                                              10               10   \n",
       "Comedy, Arts, Entertainment, Culture                 1                1   \n",
       "Drama                                                4                4   \n",
       "Drama, Action                                        1                1   \n",
       "Drama, Comedy                                        1                1   \n",
       "Kids                                                12               12   \n",
       "\n",
       "                                      No of seasons available  Language  \\\n",
       "Genre                                                                     \n",
       "Action                                                      1         1   \n",
       "Comedy                                                     10        10   \n",
       "Comedy, Arts, Entertainment, Culture                        1         1   \n",
       "Drama                                                       4         4   \n",
       "Drama, Action                                               1         1   \n",
       "Drama, Comedy                                               1         1   \n",
       "Kids                                                       12        12   \n",
       "\n",
       "                                      IMDb rating  Age of viewers  \n",
       "Genre                                                              \n",
       "Action                                          1               1  \n",
       "Comedy                                         10              10  \n",
       "Comedy, Arts, Entertainment, Culture            1               1  \n",
       "Drama                                           4               4  \n",
       "Drama, Action                                   1               1  \n",
       "Drama, Comedy                                   1               1  \n",
       "Kids                                           12              12  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(prime_df.sort_values(by = 'IMDb rating').head(30)).groupby(['Genre']).count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.05849,
     "end_time": "2020-10-03T11:33:39.421734",
     "exception": false,
     "start_time": "2020-10-03T11:33:39.363244",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* Among the highest rated shows, most of them belong to the genre Drama.\n",
    "* A good percentage of the lowest rated shows are of genre Kids."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.060049,
     "end_time": "2020-10-03T11:33:39.541078",
     "exception": false,
     "start_time": "2020-10-03T11:33:39.481029",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Top 10 highest rated shows of 2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:39.680471Z",
     "iopub.status.busy": "2020-10-03T11:33:39.679277Z",
     "iopub.status.idle": "2020-10-03T11:33:39.683804Z",
     "shell.execute_reply": "2020-10-03T11:33:39.683163Z"
    },
    "papermill": {
     "duration": 0.082492,
     "end_time": "2020-10-03T11:33:39.683934",
     "exception": false,
     "start_time": "2020-10-03T11:33:39.601442",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>The Test: A New Era for Australia's Team</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>9.0</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>Jessy and Nessy</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>8.3</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Upload</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Sci-fi comedy</td>\n",
       "      <td>8.1</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>The Forgotten Army- Azaadi ke Liye</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama, Action</td>\n",
       "      <td>8.0</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>Star Trek: Picard</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Sci-fi</td>\n",
       "      <td>7.6</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Pataal Lok</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama</td>\n",
       "      <td>7.5</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Tales from the Loop</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Sci-fi</td>\n",
       "      <td>7.5</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>Just Add Magic: Mystery City</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>7.3</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Hunters</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama, Action, Suspense</td>\n",
       "      <td>7.2</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286</th>\n",
       "      <td>Jimmy O. Yang: Good Deal</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Arts, Entertainment, Culture</td>\n",
       "      <td>7.1</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Name of the show  Year of release  \\\n",
       "20   The Test: A New Era for Australia's Team             2020   \n",
       "452                           Jessy and Nessy             2020   \n",
       "1                                      Upload             2020   \n",
       "17         The Forgotten Army- Azaadi ke Liye             2020   \n",
       "73                          Star Trek: Picard             2020   \n",
       "0                                  Pataal Lok             2020   \n",
       "19                        Tales from the Loop             2020   \n",
       "406              Just Add Magic: Mystery City             2020   \n",
       "14                                    Hunters             2020   \n",
       "286                  Jimmy O. Yang: Good Deal             2020   \n",
       "\n",
       "     No of seasons available Language                         Genre  \\\n",
       "20                         1  English                   Documentary   \n",
       "452                        1  English                          Kids   \n",
       "1                          1  English                 Sci-fi comedy   \n",
       "17                         1    Hindi                 Drama, Action   \n",
       "73                         1  English                        Sci-fi   \n",
       "0                          1    Hindi                         Drama   \n",
       "19                         1  English                       Sci-fi    \n",
       "406                        1  English                          Kids   \n",
       "14                         1  English       Drama, Action, Suspense   \n",
       "286                        1  English  Arts, Entertainment, Culture   \n",
       "\n",
       "     IMDb rating Age of viewers  \n",
       "20           9.0            16+  \n",
       "452          8.3            All  \n",
       "1            8.1            16+  \n",
       "17           8.0            18+  \n",
       "73           7.6            18+  \n",
       "0            7.5            18+  \n",
       "19           7.5            18+  \n",
       "406          7.3            All  \n",
       "14           7.2            18+  \n",
       "286          7.1            18+  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df[prime_df['Year of release'] == 2020].sort_values(by = 'IMDb rating', ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.059818,
     "end_time": "2020-10-03T11:33:39.804180",
     "exception": false,
     "start_time": "2020-10-03T11:33:39.744362",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Top 5 highest rated English shows and Hindi shows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:39.944045Z",
     "iopub.status.busy": "2020-10-03T11:33:39.943017Z",
     "iopub.status.idle": "2020-10-03T11:33:39.948183Z",
     "shell.execute_reply": "2020-10-03T11:33:39.947568Z"
    },
    "papermill": {
     "duration": 0.083981,
     "end_time": "2020-10-03T11:33:39.948318",
     "exception": false,
     "start_time": "2020-10-03T11:33:39.864337",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>The Test: A New Era for Australia's Team</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>9.0</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>281</th>\n",
       "      <td>Seinfeld</td>\n",
       "      <td>1990</td>\n",
       "      <td>9</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.8</td>\n",
       "      <td>13+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Downtown Abbey</td>\n",
       "      <td>2010</td>\n",
       "      <td>6</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.7</td>\n",
       "      <td>7+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fleabag</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>The Grand Tour</td>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td>English</td>\n",
       "      <td>Sports</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Name of the show  Year of release  \\\n",
       "20   The Test: A New Era for Australia's Team             2020   \n",
       "281                                  Seinfeld             1990   \n",
       "49                             Downtown Abbey             2010   \n",
       "4                                     Fleabag             2016   \n",
       "340                            The Grand Tour             2017   \n",
       "\n",
       "     No of seasons available Language        Genre  IMDb rating Age of viewers  \n",
       "20                         1  English  Documentary          9.0            16+  \n",
       "281                        9  English       Comedy          8.8            13+  \n",
       "49                         6  English        Drama          8.7             7+  \n",
       "4                          2  English       Comedy          8.7            18+  \n",
       "340                        4  English       Sports          8.7            16+  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df[prime_df['Language'] == 'English'].sort_values(by = 'IMDb rating', ascending = False).head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:40.089718Z",
     "iopub.status.busy": "2020-10-03T11:33:40.088624Z",
     "iopub.status.idle": "2020-10-03T11:33:40.093819Z",
     "shell.execute_reply": "2020-10-03T11:33:40.093190Z"
    },
    "papermill": {
     "duration": 0.084581,
     "end_time": "2020-10-03T11:33:40.093940",
     "exception": false,
     "start_time": "2020-10-03T11:33:40.009359",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Hostel Daze</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama, Comedy</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>The Family Man</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama, Action</td>\n",
       "      <td>8.6</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Mirzapur</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.5</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Breathe</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama, Suspense</td>\n",
       "      <td>8.4</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Made in Heaven</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.3</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Name of the show  Year of release  No of seasons available Language  \\\n",
       "37      Hostel Daze             2019                        1    Hindi   \n",
       "8    The Family Man             2019                        1    Hindi   \n",
       "7          Mirzapur             2018                        1    Hindi   \n",
       "16          Breathe             2018                        1    Hindi   \n",
       "5    Made in Heaven             2019                        1    Hindi   \n",
       "\n",
       "              Genre  IMDb rating Age of viewers  \n",
       "37    Drama, Comedy          8.7            16+  \n",
       "8     Drama, Action          8.6            18+  \n",
       "7             Drama          8.5            18+  \n",
       "16  Drama, Suspense          8.4            16+  \n",
       "5             Drama          8.3            18+  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df[prime_df['Language'] == 'Hindi'].sort_values(by = 'IMDb rating', ascending = False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.06046,
     "end_time": "2020-10-03T11:33:40.215908",
     "exception": false,
     "start_time": "2020-10-03T11:33:40.155448",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Show with maximum number of seasons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:40.356392Z",
     "iopub.status.busy": "2020-10-03T11:33:40.355004Z",
     "iopub.status.idle": "2020-10-03T11:33:40.360251Z",
     "shell.execute_reply": "2020-10-03T11:33:40.359425Z"
    },
    "papermill": {
     "duration": 0.082354,
     "end_time": "2020-10-03T11:33:40.360382",
     "exception": false,
     "start_time": "2020-10-03T11:33:40.278028",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>Forensic Files</td>\n",
       "      <td>1998</td>\n",
       "      <td>20</td>\n",
       "      <td>English</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Name of the show  Year of release  No of seasons available Language  \\\n",
       "229   Forensic Files             1998                       20  English   \n",
       "\n",
       "           Genre  IMDb rating Age of viewers  \n",
       "229  Documentary          NaN            13+  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df[prime_df['No of seasons available'] == prime_df['No of seasons available'].max()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.062292,
     "end_time": "2020-10-03T11:33:40.486424",
     "exception": false,
     "start_time": "2020-10-03T11:33:40.424132",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Highest rated shows with 5 seasons or more\n",
    "If you want to watch a long series with more than 5 seasons then probably you would have to choose from the following shows.."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:40.637125Z",
     "iopub.status.busy": "2020-10-03T11:33:40.635995Z",
     "iopub.status.idle": "2020-10-03T11:33:40.640962Z",
     "shell.execute_reply": "2020-10-03T11:33:40.641582Z"
    },
    "papermill": {
     "duration": 0.088398,
     "end_time": "2020-10-03T11:33:40.641769",
     "exception": false,
     "start_time": "2020-10-03T11:33:40.553371",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>281</th>\n",
       "      <td>Seinfeld</td>\n",
       "      <td>1990</td>\n",
       "      <td>9</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.8</td>\n",
       "      <td>13+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Downtown Abbey</td>\n",
       "      <td>2010</td>\n",
       "      <td>6</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.7</td>\n",
       "      <td>7+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Dexter</td>\n",
       "      <td>2006</td>\n",
       "      <td>8</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.6</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>Tumble Leaf</td>\n",
       "      <td>2014</td>\n",
       "      <td>6</td>\n",
       "      <td>English</td>\n",
       "      <td>Kids</td>\n",
       "      <td>8.6</td>\n",
       "      <td>All</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Shameless</td>\n",
       "      <td>2011</td>\n",
       "      <td>10</td>\n",
       "      <td>English</td>\n",
       "      <td>Comedy, Drama</td>\n",
       "      <td>8.6</td>\n",
       "      <td>18+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Mad Men</td>\n",
       "      <td>2007</td>\n",
       "      <td>7</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.6</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Suits</td>\n",
       "      <td>2011</td>\n",
       "      <td>8</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>8.5</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Supernatural</td>\n",
       "      <td>2006</td>\n",
       "      <td>15</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama, Suspense, Horror</td>\n",
       "      <td>8.4</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Fringe</td>\n",
       "      <td>2009</td>\n",
       "      <td>5</td>\n",
       "      <td>English</td>\n",
       "      <td>Sci-fi</td>\n",
       "      <td>8.4</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Person of Interest</td>\n",
       "      <td>2012</td>\n",
       "      <td>5</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama, Action, Suspense</td>\n",
       "      <td>8.4</td>\n",
       "      <td>16+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Name of the show  Year of release  No of seasons available Language  \\\n",
       "281            Seinfeld             1990                        9  English   \n",
       "49       Downtown Abbey             2010                        6  English   \n",
       "40               Dexter             2006                        8  English   \n",
       "436         Tumble Leaf             2014                        6  English   \n",
       "47            Shameless             2011                       10  English   \n",
       "105             Mad Men             2007                        7  English   \n",
       "28                Suits             2011                        8  English   \n",
       "39         Supernatural             2006                       15  English   \n",
       "67               Fringe             2009                        5  English   \n",
       "68   Person of Interest             2012                        5  English   \n",
       "\n",
       "                       Genre  IMDb rating Age of viewers  \n",
       "281                   Comedy          8.8            13+  \n",
       "49                     Drama          8.7             7+  \n",
       "40                     Drama          8.6            18+  \n",
       "436                     Kids          8.6            All  \n",
       "47             Comedy, Drama          8.6            18+  \n",
       "105                    Drama          8.6            16+  \n",
       "28                     Drama          8.5            16+  \n",
       "39   Drama, Suspense, Horror          8.4            16+  \n",
       "67                    Sci-fi          8.4            16+  \n",
       "68   Drama, Action, Suspense          8.4            16+  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df[prime_df['No of seasons available'] >= 5].sort_values(by = 'IMDb rating', ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.06276,
     "end_time": "2020-10-03T11:33:40.768558",
     "exception": false,
     "start_time": "2020-10-03T11:33:40.705798",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# The oldest show available on Amazon Prime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-03T11:33:40.911228Z",
     "iopub.status.busy": "2020-10-03T11:33:40.906888Z",
     "iopub.status.idle": "2020-10-03T11:33:40.916106Z",
     "shell.execute_reply": "2020-10-03T11:33:40.915497Z"
    },
    "papermill": {
     "duration": 0.084041,
     "end_time": "2020-10-03T11:33:40.916250",
     "exception": false,
     "start_time": "2020-10-03T11:33:40.832209",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name of the show</th>\n",
       "      <th>Year of release</th>\n",
       "      <th>No of seasons available</th>\n",
       "      <th>Language</th>\n",
       "      <th>Genre</th>\n",
       "      <th>IMDb rating</th>\n",
       "      <th>Age of viewers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>The Cecil B. DeMille Classics Collection</td>\n",
       "      <td>1926</td>\n",
       "      <td>1</td>\n",
       "      <td>English</td>\n",
       "      <td>Drama</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Name of the show  Year of release  \\\n",
       "201  The Cecil B. DeMille Classics Collection             1926   \n",
       "\n",
       "     No of seasons available Language  Genre  IMDb rating Age of viewers  \n",
       "201                        1  English  Drama          NaN            13+  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prime_df[prime_df['Year of release'] == prime_df['Year of release'].min()]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  },
  "papermill": {
   "duration": 16.276091,
   "end_time": "2020-10-03T11:33:41.089562",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2020-10-03T11:33:24.813471",
   "version": "2.1.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}