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AmirOfir/imdb-5000-movies.ipynb

Created August 18, 2020 17:35
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imdb-5000-movies.ipynb
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"metadata": {
"colab": {
"name": "IMDB 5000 movies",
"provenance": [],
"collapsed_sections": [],
"authorship_tag": "ABX9TyPiQ+ZPzPb90K6XKzmPOU96",
"include_colab_link": true
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"name": "python3",
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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
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"source": [
"<a href=\"https://colab.research.google.com/gist/AmirOfir/bd2957ca12d9f4f72bdc947ae20e19a7/imdb-5000-movies.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "jvcVZH7EIAKO",
"colab_type": "text"
},
"source": [
"# IMDB 5000 movies dataset\n",
"## A machine learning project by Amir Ofir\n",
"Project goals are learning of the IMDB 5000 Movie dataset and understanding how the director, actors, budget and genre will affect the expected profit and rating of the movie.\n",
"\n",
"The dataset holds the following columns: color, director name and number of facebook likes, duration, actors 1-3 (names and number of facebook likes), gross, genres, movie title, movie imdb link, number of voted users, plot_keywords, number of critics for reviews, number of users for reviews, language, country, content rating, budget, title year, imdb score, aspect ratio and movie facebook likes. <br/>\n",
"\n",
"From those I used the following:\n",
"1. Director name\n",
"2. Duration\n",
"3. Actors 1-3 (names and number of facebook likes)\n",
"4. Genres\n",
"5. Language\n",
"6. Country\n",
"7. Content rating\n",
"8. Budget\n",
"9. Year\n",
"10. Imdb score (rating)\n",
"11. Gross\n",
"\n",
"As I wanted to predict profit, and there is no such column I create two columns from the dataset: profit, as substraction of gross and budget, and norm_profit which is normalized field where 1 stands for good profit per budget and -1 states it is very bad.\n",
"\n",
"As the dataset contains single genre column, I flattened it (see below).\n",
"\n",
"For other textual fields such as director name, language and such I applied label encoding technique which creates num_classes binary columns.\n",
"\n",
"The tools used are:\n",
"1. EDA and visualization, correlation between the columns\n",
"2. Profit prediction\n",
"3. Rating clustering\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ehLfFbJ8IQ7N",
"colab_type": "text"
},
"source": [
"#Loading of the dataset\n",
"and picking the requested columns"
]
},
{
"cell_type": "code",
"metadata": {
"id": "QjiUXK-tpJKT",
"colab_type": "code",
"colab": {}
},
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import itertools\n",
"\n",
"%matplotlib inline\n",
"sns.set(style='white', color_codes=True, font_scale=1.25)"
],
"execution_count": 58,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "ZZ7p9Bhg6ES_",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 170
},
"outputId": "63090873-dab9-48a2-d6d9-67eb03b6b0e9"
},
"source": [
"df = pd.read_csv('/content/movie_metadata.csv')\n",
"df.columns"
],
"execution_count": 59,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['color', 'director_name', 'num_critic_for_reviews', 'duration',\n",
" 'director_facebook_likes', 'actor_3_facebook_likes', 'actor_2_name',\n",
" 'actor_1_facebook_likes', 'gross', 'genres', 'actor_1_name',\n",
" 'movie_title', 'num_voted_users', 'cast_total_facebook_likes',\n",
" 'actor_3_name', 'facenumber_in_poster', 'plot_keywords',\n",
" 'movie_imdb_link', 'num_user_for_reviews', 'language', 'country',\n",
" 'content_rating', 'budget', 'title_year', 'actor_2_facebook_likes',\n",
" 'imdb_score', 'aspect_ratio', 'movie_facebook_likes'],\n",
" dtype='object')"
]
},
"metadata": {
"tags": []
},
"execution_count": 59
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "d2CSz7q0H73H",
"colab_type": "text"
},
"source": [
"#Data Preperation"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "X-083FDtpuIA",
"colab_type": "text"
},
"source": [
"##Picking the requested columns"
]
},
{
"cell_type": "code",
"metadata": {
"id": "wx8XGJk36ReT",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 292
},
"outputId": "02fa2491-0626-4340-9252-8c9b31007ffc"
},
"source": [
"# Pick the requested columns\n",
"requested_columns = [\n",
" 'director_name', \n",
" 'duration', \n",
" 'actor_1_name', 'actor_1_facebook_likes', \n",
" 'actor_2_name', 'actor_2_facebook_likes', \n",
" 'actor_3_name', 'actor_3_facebook_likes',\n",
" 'genres',\n",
" 'language',\n",
" 'country',\n",
" 'content_rating',\n",
" 'budget',\n",
" 'title_year',\n",
" 'imdb_score',\n",
" 'gross'\n",
" ]\n",
"df=df[requested_columns]\n",
"df.head()"
],
"execution_count": 60,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>director_name</th>\n",
" <th>duration</th>\n",
" <th>actor_1_name</th>\n",
" <th>actor_1_facebook_likes</th>\n",
" <th>actor_2_name</th>\n",
" <th>actor_2_facebook_likes</th>\n",
" <th>actor_3_name</th>\n",
" <th>actor_3_facebook_likes</th>\n",
" <th>genres</th>\n",
" <th>language</th>\n",
" <th>country</th>\n",
" <th>content_rating</th>\n",
" <th>budget</th>\n",
" <th>title_year</th>\n",
" <th>imdb_score</th>\n",
" <th>gross</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>James Cameron</td>\n",
" <td>178.0</td>\n",
" <td>CCH Pounder</td>\n",
" <td>1000.0</td>\n",
" <td>Joel David Moore</td>\n",
" <td>936.0</td>\n",
" <td>Wes Studi</td>\n",
" <td>855.0</td>\n",
" <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>237000000.0</td>\n",
" <td>2009.0</td>\n",
" <td>7.9</td>\n",
" <td>760505847.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Gore Verbinski</td>\n",
" <td>169.0</td>\n",
" <td>Johnny Depp</td>\n",
" <td>40000.0</td>\n",
" <td>Orlando Bloom</td>\n",
" <td>5000.0</td>\n",
" <td>Jack Davenport</td>\n",
" <td>1000.0</td>\n",
" <td>Action|Adventure|Fantasy</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>300000000.0</td>\n",
" <td>2007.0</td>\n",
" <td>7.1</td>\n",
" <td>309404152.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Sam Mendes</td>\n",
" <td>148.0</td>\n",
" <td>Christoph Waltz</td>\n",
" <td>11000.0</td>\n",
" <td>Rory Kinnear</td>\n",
" <td>393.0</td>\n",
" <td>Stephanie Sigman</td>\n",
" <td>161.0</td>\n",
" <td>Action|Adventure|Thriller</td>\n",
" <td>English</td>\n",
" <td>UK</td>\n",
" <td>PG-13</td>\n",
" <td>245000000.0</td>\n",
" <td>2015.0</td>\n",
" <td>6.8</td>\n",
" <td>200074175.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Christopher Nolan</td>\n",
" <td>164.0</td>\n",
" <td>Tom Hardy</td>\n",
" <td>27000.0</td>\n",
" <td>Christian Bale</td>\n",
" <td>23000.0</td>\n",
" <td>Joseph Gordon-Levitt</td>\n",
" <td>23000.0</td>\n",
" <td>Action|Thriller</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>250000000.0</td>\n",
" <td>2012.0</td>\n",
" <td>8.5</td>\n",
" <td>448130642.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Doug Walker</td>\n",
" <td>NaN</td>\n",
" <td>Doug Walker</td>\n",
" <td>131.0</td>\n",
" <td>Rob Walker</td>\n",
" <td>12.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Documentary</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>7.1</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" director_name duration ... imdb_score gross\n",
"0 James Cameron 178.0 ... 7.9 760505847.0\n",
"1 Gore Verbinski 169.0 ... 7.1 309404152.0\n",
"2 Sam Mendes 148.0 ... 6.8 200074175.0\n",
"3 Christopher Nolan 164.0 ... 8.5 448130642.0\n",
"4 Doug Walker NaN ... 7.1 NaN\n",
"\n",
"[5 rows x 16 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 60
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "fud2db2rSO63",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 306
},
"outputId": "337aa9d9-de11-40e7-c10e-0f0ef89a1307"
},
"source": [
"# Data type investigation\n",
"df.dtypes"
],
"execution_count": 61,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"director_name object\n",
"duration float64\n",
"actor_1_name object\n",
"actor_1_facebook_likes float64\n",
"actor_2_name object\n",
"actor_2_facebook_likes float64\n",
"actor_3_name object\n",
"actor_3_facebook_likes float64\n",
"genres object\n",
"language object\n",
"country object\n",
"content_rating object\n",
"budget float64\n",
"title_year float64\n",
"imdb_score float64\n",
"gross float64\n",
"dtype: object"
]
},
"metadata": {
"tags": []
},
"execution_count": 61
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "O6z576h9pxUn",
"colab_type": "text"
},
"source": [
"## Data cleansing\n",
"The goal is learning based on imdb score and profit (gross - budget), therefore elimination of missing data is done"
]
},
{
"cell_type": "code",
"metadata": {
"id": "f0HcSaojIFgk",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 51
},
"outputId": "03b67798-34cc-4559-c436-0b26a9a787fe"
},
"source": [
"# Remove duplicates\n",
"print('Before removal of duplicates', df.shape)\n",
"df = df.drop_duplicates(keep='first')\n",
"print('After removal of duplicates', df.shape)"
],
"execution_count": 62,
"outputs": [
{
"output_type": "stream",
"text": [
"Before removal of duplicates (5043, 16)\n",
"After removal of duplicates (4937, 16)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "sXqCoLl_IlUK",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 68
},
"outputId": "e8d5a67f-0a40-4aef-eeec-a84dad0ad81e"
},
"source": [
"# Remove missing data\n",
"# we are most concern with rating and profit. \n",
"# profit is gross minus budget, so if any of them is missing remove\n",
"print('imdb_score min:', df['imdb_score'].min(), 'max:', df['imdb_score'].max(),'has nulls:', df['imdb_score'].isnull().values.any())\n",
"print('gross min:', df['gross'].min(), 'max:', df['gross'].max(), 'has nulls:', df['gross'].isnull().values.any())\n",
"print('budget min:', df['budget'].min(), 'max:', df['budget'].max() ,'has nulls:', df['budget'].isnull().values.any())"
],
"execution_count": 63,
"outputs": [
{
"output_type": "stream",
"text": [
"imdb_score min: 1.6 max: 9.5 has nulls: False\n",
"gross min: 162.0 max: 760505847.0 has nulls: True\n",
"budget min: 218.0 max: 12215500000.0 has nulls: True\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "2VSDTI-XPvOs",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "46978da6-aa6d-4834-bf43-c57655e3e08d"
},
"source": [
"df.dropna(subset=['gross'], inplace=True)\n",
"df.dropna(subset=['budget'], inplace=True)\n",
"print(df.shape)"
],
"execution_count": 64,
"outputs": [
{
"output_type": "stream",
"text": [
"(3803, 16)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "FLAFbHJPp6n1",
"colab_type": "text"
},
"source": [
"##Creation of computed columns"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "W9DT6KTdp_BZ",
"colab_type": "text"
},
"source": [
"###Create profit column"
]
},
{
"cell_type": "code",
"metadata": {
"id": "7K1I7E5NGPAZ",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 51
},
"outputId": "bcc285e8-d97b-4d72-e1fc-e71a64d55a97"
},
"source": [
"# Create profit column\n",
"df['profit'] = df.gross - df.budget\n",
"df.head()\n",
"print('Profit range: [', df['profit'].min(), ',', df['profit'].max(), ']')\n",
"print('has nulls:', df['profit'].isnull().values.any())"
],
"execution_count": 65,
"outputs": [
{
"output_type": "stream",
"text": [
"Profit range: [ -12213298588.0 , 523505847.0 ]\n",
"has nulls: False\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "4voOJnT46QOs",
"colab_type": "code",
"colab": {}
},
"source": [
"# Create normalized profit column between -1 to 1\n",
"a,b = -1., 1.\n",
"x,y = df['profit'].min(), df['profit'].max()\n",
"df['norm_profit'] = (df['profit'] - x) / (y-x) * (b - a) + (a)"
],
"execution_count": 66,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "Ye_P9MRYqBYj",
"colab_type": "text"
},
"source": [
"###Flatten genres\n",
"The dataset has genres as vertical-bar separated string per movie.<br/>\n",
"Instead, I seperated to a list of boolean columns, each tells a movie in single genre."
]
},
{
"cell_type": "code",
"metadata": {
"id": "RY_QigX4UKXX",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 54
},
"outputId": "f4c43275-a75c-404d-baf3-95ae493bb146"
},
"source": [
"# Flatten genres\n",
"genres = []\n",
"for i in df['genres']:\n",
" curr_genres = i.split('|')\n",
" for c in curr_genres:\n",
" if c not in genres: \n",
" genres.append(c)\n",
"genres = sorted(genres)\n",
"print(genres)"
],
"execution_count": 67,
"outputs": [
{
"output_type": "stream",
"text": [
"['Action', 'Adventure', 'Animation', 'Biography', 'Comedy', 'Crime', 'Documentary', 'Drama', 'Family', 'Fantasy', 'Film-Noir', 'History', 'Horror', 'Music', 'Musical', 'Mystery', 'Romance', 'Sci-Fi', 'Short', 'Sport', 'Thriller', 'War', 'Western']\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "jrVfcYlFacw_",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 717
},
"outputId": "668ee6e8-ea3e-47af-8731-b6f0c7f66040"
},
"source": [
"for g in genres:\n",
" new_col_name = 'genre_'+g\n",
" if new_col_name not in df.columns:\n",
" df[new_col_name] = 0\n",
" print(new_col_name)\n",
"df.head()"
],
"execution_count": 68,
"outputs": [
{
"output_type": "stream",
"text": [
"genre_Action\n",
"genre_Adventure\n",
"genre_Animation\n",
"genre_Biography\n",
"genre_Comedy\n",
"genre_Crime\n",
"genre_Documentary\n",
"genre_Drama\n",
"genre_Family\n",
"genre_Fantasy\n",
"genre_Film-Noir\n",
"genre_History\n",
"genre_Horror\n",
"genre_Music\n",
"genre_Musical\n",
"genre_Mystery\n",
"genre_Romance\n",
"genre_Sci-Fi\n",
"genre_Short\n",
"genre_Sport\n",
"genre_Thriller\n",
"genre_War\n",
"genre_Western\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
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" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>director_name</th>\n",
" <th>duration</th>\n",
" <th>actor_1_name</th>\n",
" <th>actor_1_facebook_likes</th>\n",
" <th>actor_2_name</th>\n",
" <th>actor_2_facebook_likes</th>\n",
" <th>actor_3_name</th>\n",
" <th>actor_3_facebook_likes</th>\n",
" <th>genres</th>\n",
" <th>language</th>\n",
" <th>country</th>\n",
" <th>content_rating</th>\n",
" <th>budget</th>\n",
" <th>title_year</th>\n",
" <th>imdb_score</th>\n",
" <th>gross</th>\n",
" <th>profit</th>\n",
" <th>norm_profit</th>\n",
" <th>genre_Action</th>\n",
" <th>genre_Adventure</th>\n",
" <th>genre_Animation</th>\n",
" <th>genre_Biography</th>\n",
" <th>genre_Comedy</th>\n",
" <th>genre_Crime</th>\n",
" <th>genre_Documentary</th>\n",
" <th>genre_Drama</th>\n",
" <th>genre_Family</th>\n",
" <th>genre_Fantasy</th>\n",
" <th>genre_Film-Noir</th>\n",
" <th>genre_History</th>\n",
" <th>genre_Horror</th>\n",
" <th>genre_Music</th>\n",
" <th>genre_Musical</th>\n",
" <th>genre_Mystery</th>\n",
" <th>genre_Romance</th>\n",
" <th>genre_Sci-Fi</th>\n",
" <th>genre_Short</th>\n",
" <th>genre_Sport</th>\n",
" <th>genre_Thriller</th>\n",
" <th>genre_War</th>\n",
" <th>genre_Western</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>James Cameron</td>\n",
" <td>178.0</td>\n",
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],
"text/plain": [
" director_name duration ... genre_War genre_Western\n",
"0 James Cameron 178.0 ... 0 0\n",
"1 Gore Verbinski 169.0 ... 0 0\n",
"2 Sam Mendes 148.0 ... 0 0\n",
"3 Christopher Nolan 164.0 ... 0 0\n",
"5 Andrew Stanton 132.0 ... 0 0\n",
"\n",
"[5 rows x 41 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 68
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "GIidvtM0akqp",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 326
},
"outputId": "d33d28ea-18f5-4a86-ab19-c2d0f1179793"
},
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"for index,i in zip(df.index,df['genres']):\n",
" curr_genres = i.split('|')\n",
" for c in curr_genres:\n",
" col_name = \"genre_\"+c\n",
" df.at[index,col_name] = 1\n",
"df.head()"
],
"execution_count": 69,
"outputs": [
{
"output_type": "execute_result",
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"text/plain": [
" director_name duration ... genre_War genre_Western\n",
"0 James Cameron 178.0 ... 0 0\n",
"1 Gore Verbinski 169.0 ... 0 0\n",
"2 Sam Mendes 148.0 ... 0 0\n",
"3 Christopher Nolan 164.0 ... 0 0\n",
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"\n",
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]
},
"metadata": {
"tags": []
},
"execution_count": 69
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "bTjhe4OLrGmQ",
"colab_type": "text"
},
"source": [
"###Flatten textual fields\n",
"For the explatory task, as the textual fields doesn't show in Pandas correlation matrices, replace them with id columns, where each entity has its own ids.\n",
"For the learning parts below, a label translation mechanism will be used which will create a boolean column per value."
]
},
{
"cell_type": "code",
"metadata": {
"id": "B2l-6waHUFDD",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 445
},
"outputId": "74134590-8d05-4655-e847-5faa2cede861"
},
"source": [
"# Add id columns for string columns director_name, language, country, actor_X_name\n",
"string_cols =['director_name', 'actor_1_name', 'actor_2_name', 'actor_3_name', 'language', 'country', 'content_rating']\n",
"for col in string_cols:\n",
" if 'name' in col:\n",
" new_col_name = col.replace('name', 'id')\n",
" else:\n",
" new_col_name = col + '_id'\n",
" if new_col_name not in df.columns:\n",
" df[new_col_name] = df.groupby([col]).ngroup()\n",
" print('Created column', new_col_name)\n",
"df.head()"
],
"execution_count": 70,
"outputs": [
{
"output_type": "stream",
"text": [
"Created column director_id\n",
"Created column actor_1_id\n",
"Created column actor_2_id\n",
"Created column actor_3_id\n",
"Created column language_id\n",
"Created column country_id\n",
"Created column content_rating_id\n"
],
"name": "stdout"
},
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" <th>profit</th>\n",
" <th>norm_profit</th>\n",
" <th>genre_Action</th>\n",
" <th>genre_Adventure</th>\n",
" <th>genre_Animation</th>\n",
" <th>genre_Biography</th>\n",
" <th>genre_Comedy</th>\n",
" <th>genre_Crime</th>\n",
" <th>genre_Documentary</th>\n",
" <th>genre_Drama</th>\n",
" <th>genre_Family</th>\n",
" <th>genre_Fantasy</th>\n",
" <th>genre_Film-Noir</th>\n",
" <th>genre_History</th>\n",
" <th>genre_Horror</th>\n",
" <th>genre_Music</th>\n",
" <th>genre_Musical</th>\n",
" <th>genre_Mystery</th>\n",
" <th>genre_Romance</th>\n",
" <th>genre_Sci-Fi</th>\n",
" <th>genre_Short</th>\n",
" <th>genre_Sport</th>\n",
" <th>genre_Thriller</th>\n",
" <th>genre_War</th>\n",
" <th>genre_Western</th>\n",
" <th>director_id</th>\n",
" <th>actor_1_id</th>\n",
" <th>actor_2_id</th>\n",
" <th>actor_3_id</th>\n",
" <th>language_id</th>\n",
" <th>country_id</th>\n",
" <th>content_rating_id</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>James Cameron</td>\n",
" <td>178.0</td>\n",
" <td>CCH Pounder</td>\n",
" <td>1000.0</td>\n",
" <td>Joel David Moore</td>\n",
" <td>936.0</td>\n",
" <td>Wes Studi</td>\n",
" <td>855.0</td>\n",
" <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>237000000.0</td>\n",
" <td>2009.0</td>\n",
" <td>7.9</td>\n",
" <td>760505847.0</td>\n",
" <td>523505847.0</td>\n",
" <td>1.000000</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>655</td>\n",
" <td>197</td>\n",
" <td>1055</td>\n",
" <td>2627</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Gore Verbinski</td>\n",
" <td>169.0</td>\n",
" <td>Johnny Depp</td>\n",
" <td>40000.0</td>\n",
" <td>Orlando Bloom</td>\n",
" <td>5000.0</td>\n",
" <td>Jack Davenport</td>\n",
" <td>1000.0</td>\n",
" <td>Action|Adventure|Fantasy</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>300000000.0</td>\n",
" <td>2007.0</td>\n",
" <td>7.1</td>\n",
" <td>309404152.0</td>\n",
" <td>9404152.0</td>\n",
" <td>0.919273</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>567</td>\n",
" <td>718</td>\n",
" <td>1670</td>\n",
" <td>1035</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Sam Mendes</td>\n",
" <td>148.0</td>\n",
" <td>Christoph Waltz</td>\n",
" <td>11000.0</td>\n",
" <td>Rory Kinnear</td>\n",
" <td>393.0</td>\n",
" <td>Stephanie Sigman</td>\n",
" <td>161.0</td>\n",
" <td>Action|Adventure|Thriller</td>\n",
" <td>English</td>\n",
" <td>UK</td>\n",
" <td>PG-13</td>\n",
" <td>245000000.0</td>\n",
" <td>2015.0</td>\n",
" <td>6.8</td>\n",
" <td>200074175.0</td>\n",
" <td>-44925825.0</td>\n",
" <td>0.910742</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1473</td>\n",
" <td>266</td>\n",
" <td>1881</td>\n",
" <td>2384</td>\n",
" <td>10</td>\n",
" <td>44</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Christopher Nolan</td>\n",
" <td>164.0</td>\n",
" <td>Tom Hardy</td>\n",
" <td>27000.0</td>\n",
" <td>Christian Bale</td>\n",
" <td>23000.0</td>\n",
" <td>Joseph Gordon-Levitt</td>\n",
" <td>23000.0</td>\n",
" <td>Action|Thriller</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>250000000.0</td>\n",
" <td>2012.0</td>\n",
" <td>8.5</td>\n",
" <td>448130642.0</td>\n",
" <td>198130642.0</td>\n",
" <td>0.948908</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>260</td>\n",
" <td>1411</td>\n",
" <td>405</td>\n",
" <td>1308</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Andrew Stanton</td>\n",
" <td>132.0</td>\n",
" <td>Daryl Sabara</td>\n",
" <td>640.0</td>\n",
" <td>Samantha Morton</td>\n",
" <td>632.0</td>\n",
" <td>Polly Walker</td>\n",
" <td>530.0</td>\n",
" <td>Action|Adventure|Sci-Fi</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>263700000.0</td>\n",
" <td>2012.0</td>\n",
" <td>6.6</td>\n",
" <td>73058679.0</td>\n",
" <td>-190641321.0</td>\n",
" <td>0.887861</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>65</td>\n",
" <td>332</td>\n",
" <td>1925</td>\n",
" <td>2046</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" director_name duration ... country_id content_rating_id\n",
"0 James Cameron 178.0 ... 45 7\n",
"1 Gore Verbinski 169.0 ... 45 7\n",
"2 Sam Mendes 148.0 ... 44 7\n",
"3 Christopher Nolan 164.0 ... 45 7\n",
"5 Andrew Stanton 132.0 ... 45 7\n",
"\n",
"[5 rows x 48 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 70
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "D-CZwhlstm20",
"colab_type": "text"
},
"source": [
"# Understanding the data"
]
},
{
"cell_type": "code",
"metadata": {
"id": "KaJgwv4btsPb",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 298
},
"outputId": "c992be4f-146f-463e-cbc4-43e7790724ea"
},
"source": [
"# Movies by genres\n",
"genre_cols = ['genre_'+x for x in genres]\n",
"count_by_genre = [df[df[col] == 1].shape[0] for col in genre_cols]\n",
"genre_perc = [(i, round(i / float(len(df)),4), g) for i,g in zip(count_by_genre, genres)]\n",
"genre_perc = sorted(genre_perc, key=lambda tup:tup[0])\n",
"print(genre_perc)\n",
"count_by_genre, genre_labels = [a for a,b,c in genre_perc], [c for a,b,c in genre_perc]\n",
"\n",
"# Plot\n",
"plt.pie(count_by_genre, labels=genre_labels, autopct='%1.1f%%', shadow=True, startangle=90)\n",
"plt.axis('equal')\n",
"plt.show()"
],
"execution_count": 71,
"outputs": [
{
"output_type": "stream",
"text": [
"[(1, 0.0003, 'Film-Noir'), (2, 0.0005, 'Short'), (60, 0.0158, 'Western'), (67, 0.0176, 'Documentary'), (102, 0.0268, 'Musical'), (147, 0.0387, 'Sport'), (153, 0.0402, 'History'), (159, 0.0418, 'Music'), (159, 0.0418, 'War'), (197, 0.0518, 'Animation'), (242, 0.0636, 'Biography'), (379, 0.0997, 'Horror'), (380, 0.0999, 'Mystery'), (443, 0.1165, 'Family'), (485, 0.1275, 'Sci-Fi'), (498, 0.1309, 'Fantasy'), (706, 0.1856, 'Crime'), (770, 0.2025, 'Adventure'), (870, 0.2288, 'Romance'), (941, 0.2474, 'Action'), (1094, 0.2877, 'Thriller'), (1493, 0.3926, 'Comedy'), (1923, 0.5057, 'Drama')]\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "vEBLdHEJ75sn",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 272
},
"outputId": "2fee297e-0752-463a-bbf4-4354bbb4ca9e"
},
"source": [
"# Production year\n",
"plot_by_year = df['title_year'].value_counts().sort_index().plot()"
],
"execution_count": 72,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "rG6N7cdjDSig",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 566
},
"outputId": "36fe5a9c-ea4d-4093-c82c-3b6305f0066f"
},
"source": [
"# Top 10 by rating\n",
"df.sort_values(by='imdb_score', ascending=False).reindex(sorted(df.columns), axis=1).head(10)"
],
"execution_count": 73,
"outputs": [
{
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" <td>461.0</td>\n",
" <td>268</td>\n",
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" <th>3466</th>\n",
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" <td>1437</td>\n",
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" <td>0.938025</td>\n",
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" <th>2837</th>\n",
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" <td>Luigi Pistilli</td>\n",
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" <td>Enzo Petito</td>\n",
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" <th>339</th>\n",
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" <td>1104</td>\n",
" <td>Orlando Bloom</td>\n",
" <td>857.0</td>\n",
" <td>233</td>\n",
" <td>Billy Boyd</td>\n",
" <td>416.0</td>\n",
" <td>235</td>\n",
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" <td>45</td>\n",
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" <td>192.0</td>\n",
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" <th>1874</th>\n",
" <td>14000.0</td>\n",
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" <td>Liam Neeson</td>\n",
" <td>795.0</td>\n",
" <td>677</td>\n",
" <td>Embeth Davidtz</td>\n",
" <td>212.0</td>\n",
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" <th>3355</th>\n",
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" <td>Bruce Willis</td>\n",
" <td>902.0</td>\n",
" <td>698</td>\n",
" <td>Eric Stoltz</td>\n",
" <td>857.0</td>\n",
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" <td>10</td>\n",
" <td>0.933488</td>\n",
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" <th>97</th>\n",
" <td>29000.0</td>\n",
" <td>864</td>\n",
" <td>Leonardo DiCaprio</td>\n",
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" <td>2145</td>\n",
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" <td>1308</td>\n",
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" <td>160000000.0</td>\n",
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" <td>292568851.0</td>\n",
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" <td>10</td>\n",
" <td>0.938613</td>\n",
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" <td>2010.0</td>\n",
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" <tr>\n",
" <th>270</th>\n",
" <td>16000.0</td>\n",
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" <td>Christopher Lee</td>\n",
" <td>5000.0</td>\n",
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" <td>Orlando Bloom</td>\n",
" <td>857.0</td>\n",
" <td>257</td>\n",
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" <td>93000000.0</td>\n",
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" <td>New Zealand</td>\n",
" <td>30</td>\n",
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],
"text/plain": [
" actor_1_facebook_likes actor_1_id ... profit title_year\n",
"1937 11000.0 1041 ... 3341469.0 1994.0\n",
"3466 14000.0 21 ... 128821952.0 1972.0\n",
"2837 22000.0 1196 ... 44300000.0 1974.0\n",
"66 23000.0 259 ... 348316061.0 2008.0\n",
"4498 16000.0 279 ... 4900000.0 1966.0\n",
"339 5000.0 1104 ... 283019252.0 2003.0\n",
"1874 14000.0 874 ... 74067179.0 1993.0\n",
"3355 13000.0 188 ... 99930000.0 1994.0\n",
"97 29000.0 864 ... 132568851.0 2010.0\n",
"270 16000.0 268 ... 220837577.0 2001.0\n",
"\n",
"[10 rows x 48 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 73
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "3cEJFrwyGqYO",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 549
},
"outputId": "54ca7090-9730-4f11-b175-a32edc539dfa"
},
"source": [
"# Top 10 by profit\n",
"df.sort_values(by='profit', ascending=False).head(10)"
],
"execution_count": 74,
"outputs": [
{
"output_type": "execute_result",
"data": {
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>director_name</th>\n",
" <th>duration</th>\n",
" <th>actor_1_name</th>\n",
" <th>actor_1_facebook_likes</th>\n",
" <th>actor_2_name</th>\n",
" <th>actor_2_facebook_likes</th>\n",
" <th>actor_3_name</th>\n",
" <th>actor_3_facebook_likes</th>\n",
" <th>genres</th>\n",
" <th>language</th>\n",
" <th>country</th>\n",
" <th>content_rating</th>\n",
" <th>budget</th>\n",
" <th>title_year</th>\n",
" <th>imdb_score</th>\n",
" <th>gross</th>\n",
" <th>profit</th>\n",
" <th>norm_profit</th>\n",
" <th>genre_Action</th>\n",
" <th>genre_Adventure</th>\n",
" <th>genre_Animation</th>\n",
" <th>genre_Biography</th>\n",
" <th>genre_Comedy</th>\n",
" <th>genre_Crime</th>\n",
" <th>genre_Documentary</th>\n",
" <th>genre_Drama</th>\n",
" <th>genre_Family</th>\n",
" <th>genre_Fantasy</th>\n",
" <th>genre_Film-Noir</th>\n",
" <th>genre_History</th>\n",
" <th>genre_Horror</th>\n",
" <th>genre_Music</th>\n",
" <th>genre_Musical</th>\n",
" <th>genre_Mystery</th>\n",
" <th>genre_Romance</th>\n",
" <th>genre_Sci-Fi</th>\n",
" <th>genre_Short</th>\n",
" <th>genre_Sport</th>\n",
" <th>genre_Thriller</th>\n",
" <th>genre_War</th>\n",
" <th>genre_Western</th>\n",
" <th>director_id</th>\n",
" <th>actor_1_id</th>\n",
" <th>actor_2_id</th>\n",
" <th>actor_3_id</th>\n",
" <th>language_id</th>\n",
" <th>country_id</th>\n",
" <th>content_rating_id</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>James Cameron</td>\n",
" <td>178.0</td>\n",
" <td>CCH Pounder</td>\n",
" <td>1000.0</td>\n",
" <td>Joel David Moore</td>\n",
" <td>936.0</td>\n",
" <td>Wes Studi</td>\n",
" <td>855.0</td>\n",
" <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>237000000.0</td>\n",
" <td>2009.0</td>\n",
" <td>7.9</td>\n",
" <td>760505847.0</td>\n",
" <td>523505847.0</td>\n",
" <td>1.000000</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>655</td>\n",
" <td>197</td>\n",
" <td>1055</td>\n",
" <td>2627</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>Colin Trevorrow</td>\n",
" <td>124.0</td>\n",
" <td>Bryce Dallas Howard</td>\n",
" <td>3000.0</td>\n",
" <td>Judy Greer</td>\n",
" <td>2000.0</td>\n",
" <td>Omar Sy</td>\n",
" <td>1000.0</td>\n",
" <td>Action|Adventure|Sci-Fi|Thriller</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>150000000.0</td>\n",
" <td>2015.0</td>\n",
" <td>7.0</td>\n",
" <td>652177271.0</td>\n",
" <td>502177271.0</td>\n",
" <td>0.996651</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>281</td>\n",
" <td>190</td>\n",
" <td>1123</td>\n",
" <td>1946</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>James Cameron</td>\n",
" <td>194.0</td>\n",
" <td>Leonardo DiCaprio</td>\n",
" <td>29000.0</td>\n",
" <td>Kate Winslet</td>\n",
" <td>14000.0</td>\n",
" <td>Gloria Stuart</td>\n",
" <td>794.0</td>\n",
" <td>Drama|Romance</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>200000000.0</td>\n",
" <td>1997.0</td>\n",
" <td>7.7</td>\n",
" <td>658672302.0</td>\n",
" <td>458672302.0</td>\n",
" <td>0.989819</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>655</td>\n",
" <td>864</td>\n",
" <td>1161</td>\n",
" <td>916</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3024</th>\n",
" <td>George Lucas</td>\n",
" <td>125.0</td>\n",
" <td>Harrison Ford</td>\n",
" <td>11000.0</td>\n",
" <td>Peter Cushing</td>\n",
" <td>1000.0</td>\n",
" <td>Kenny Baker</td>\n",
" <td>504.0</td>\n",
" <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG</td>\n",
" <td>11000000.0</td>\n",
" <td>1977.0</td>\n",
" <td>8.7</td>\n",
" <td>460935665.0</td>\n",
" <td>449935665.0</td>\n",
" <td>0.988448</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>547</td>\n",
" <td>528</td>\n",
" <td>1727</td>\n",
" <td>1423</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3080</th>\n",
" <td>Steven Spielberg</td>\n",
" <td>120.0</td>\n",
" <td>Henry Thomas</td>\n",
" <td>861.0</td>\n",
" <td>Dee Wallace</td>\n",
" <td>725.0</td>\n",
" <td>Peter Coyote</td>\n",
" <td>548.0</td>\n",
" <td>Family|Sci-Fi</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG</td>\n",
" <td>10500000.0</td>\n",
" <td>1982.0</td>\n",
" <td>7.9</td>\n",
" <td>434949459.0</td>\n",
" <td>424449459.0</td>\n",
" <td>0.984446</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1576</td>\n",
" <td>545</td>\n",
" <td>564</td>\n",
" <td>2012</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Joss Whedon</td>\n",
" <td>173.0</td>\n",
" <td>Chris Hemsworth</td>\n",
" <td>26000.0</td>\n",
" <td>Robert Downey Jr.</td>\n",
" <td>21000.0</td>\n",
" <td>Scarlett Johansson</td>\n",
" <td>19000.0</td>\n",
" <td>Action|Adventure|Sci-Fi</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>220000000.0</td>\n",
" <td>2012.0</td>\n",
" <td>8.1</td>\n",
" <td>623279547.0</td>\n",
" <td>403279547.0</td>\n",
" <td>0.981121</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>881</td>\n",
" <td>252</td>\n",
" <td>1843</td>\n",
" <td>2296</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>509</th>\n",
" <td>Roger Allers</td>\n",
" <td>73.0</td>\n",
" <td>Matthew Broderick</td>\n",
" <td>2000.0</td>\n",
" <td>Nathan Lane</td>\n",
" <td>886.0</td>\n",
" <td>Niketa Calame</td>\n",
" <td>847.0</td>\n",
" <td>Adventure|Animation|Drama|Family|Musical</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>G</td>\n",
" <td>45000000.0</td>\n",
" <td>1994.0</td>\n",
" <td>8.5</td>\n",
" <td>422783777.0</td>\n",
" <td>377783777.0</td>\n",
" <td>0.977118</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1427</td>\n",
" <td>962</td>\n",
" <td>1610</td>\n",
" <td>1908</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>240</th>\n",
" <td>George Lucas</td>\n",
" <td>136.0</td>\n",
" <td>Natalie Portman</td>\n",
" <td>20000.0</td>\n",
" <td>Liam Neeson</td>\n",
" <td>14000.0</td>\n",
" <td>Ian McDiarmid</td>\n",
" <td>1000.0</td>\n",
" <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG</td>\n",
" <td>115000000.0</td>\n",
" <td>1999.0</td>\n",
" <td>6.5</td>\n",
" <td>474544677.0</td>\n",
" <td>359544677.0</td>\n",
" <td>0.974254</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>547</td>\n",
" <td>1055</td>\n",
" <td>1323</td>\n",
" <td>1003</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>66</th>\n",
" <td>Christopher Nolan</td>\n",
" <td>152.0</td>\n",
" <td>Christian Bale</td>\n",
" <td>23000.0</td>\n",
" <td>Heath Ledger</td>\n",
" <td>13000.0</td>\n",
" <td>Morgan Freeman</td>\n",
" <td>11000.0</td>\n",
" <td>Action|Crime|Drama|Thriller</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>185000000.0</td>\n",
" <td>2008.0</td>\n",
" <td>9.0</td>\n",
" <td>533316061.0</td>\n",
" <td>348316061.0</td>\n",
" <td>0.972491</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>260</td>\n",
" <td>259</td>\n",
" <td>845</td>\n",
" <td>1850</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>439</th>\n",
" <td>Gary Ross</td>\n",
" <td>142.0</td>\n",
" <td>Jennifer Lawrence</td>\n",
" <td>34000.0</td>\n",
" <td>Josh Hutcherson</td>\n",
" <td>14000.0</td>\n",
" <td>Anthony Reynolds</td>\n",
" <td>575.0</td>\n",
" <td>Adventure|Drama|Sci-Fi|Thriller</td>\n",
" <td>English</td>\n",
" <td>USA</td>\n",
" <td>PG-13</td>\n",
" <td>78000000.0</td>\n",
" <td>2012.0</td>\n",
" <td>7.3</td>\n",
" <td>407999255.0</td>\n",
" <td>329999255.0</td>\n",
" <td>0.969615</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>527</td>\n",
" <td>649</td>\n",
" <td>1112</td>\n",
" <td>175</td>\n",
" <td>10</td>\n",
" <td>45</td>\n",
" <td>7</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" director_name duration ... country_id content_rating_id\n",
"0 James Cameron 178.0 ... 45 7\n",
"29 Colin Trevorrow 124.0 ... 45 7\n",
"26 James Cameron 194.0 ... 45 7\n",
"3024 George Lucas 125.0 ... 45 6\n",
"3080 Steven Spielberg 120.0 ... 45 6\n",
"17 Joss Whedon 173.0 ... 45 7\n",
"509 Roger Allers 73.0 ... 45 1\n",
"240 George Lucas 136.0 ... 45 6\n",
"66 Christopher Nolan 152.0 ... 45 7\n",
"439 Gary Ross 142.0 ... 45 7\n",
"\n",
"[10 rows x 48 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 74
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "tr_dgjaYHupx",
"colab_type": "text"
},
"source": [
"# Relationship between features"
]
},
{
"cell_type": "code",
"metadata": {
"id": "MgucoCgd0e8d",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "48f96c10-e8bf-4a24-be98-82edc11c1882"
},
"source": [
"correlations = df.corr()\n",
"f,ax = plt.subplots(figsize=(15,15))\n",
"sns.heatmap(correlations, annot=False, cmap=\"YlGnBu\", linewidths=.5)"
],
"execution_count": 75,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f99a8c988d0>"
]
},
"metadata": {
"tags": []
},
"execution_count": 75
},
{
"output_type": "display_data",
"data": {
"image/png": 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Atm7dytixYylfvjz+/v5cv36dvn374uTkRFxcHFeuXGH06NEMHz6c6OjoPPu6adMmBg0aRGRkJMHBwTbrw+vXrxMZGcm2bduIi4vDxcWF7du3Ex4ezsiRI6lXrx4HDhxg1KhRODg4EBoaytq1a4mNjWXatGk899xznDhxgvT0dJvlJCIiIiIi8iDka6DdsmVLs+UxY8bg5+fH77//TkJCAqVLl2bq1Kk89thjALi5uRnr2tvb4+joiLOzs1EWFxdHpUqViIiIwM7ODjc3NzIyMpg3b57ZQNvLy8ts+V4pXrw4JUuWBDDL08vLy2y98ePHU7duXVJSUvD09GTVqlWcPn2ahIQEo33lypWN9WfMmMHw4cONQXWlSpXYtWsX8fHxZgPt7t27G8vjxo3D19eXFStW0KlTJ2JjY/H29iYsLAyAqlWrsnv3bubOnYu/vz8//PADaWlpfPvtt1SoUMGI0aFDB9LT06lSpYqxncTERCIiIpg8ebLZ9q2VnZ3N4MGDOXDgAJ999hnlypUDICoqirCwMNq0aWPsf58+fVi4cCGhoaEcP36ccuXK4eXlhb29PS4uLtSpU8dmeYmIiIiIiDwI+Rpop6en89FHH7Fz504yMzON8mPHjpGamkq9evWMQXZ+pKWlUadOHbOr1HXr1mXq1KlcuHCBEiVKAODu7p7vmPfCqVOnmD59Otu2bePUqVPk5OSQlZVl3DafmppKjRo1jEH2jS5dusThw4cJDw9nxIgRRnlWVhaurq5m69aqVcv49xNPPMHzzz9PWloakNtXAQEBZuvXrVuX1atXG/Wurq7GIBvAw8MDe3t70tLSjIF2cnIy69atIyYmBh8fHyt6Ja+xY8dSvHhxFi9ebDaJ3J49e0hOTmbmzJlG2bVr14wr/gEBASxYsIAWLVrg4+ODr68vzZo1o0iRR+eWEhERERERW3mUZvUu6PI10A4LC6NSpUqMHz8eZ2dnLl68SIcOHcjKyrqnyRUrVuyexr+TYcOGce7cOUaOHImLiwv29vYEBwfna78vXboEwIQJE6hZs6ZZ3eOP3/856KpUqULJkiVJSEigcePGd/WHkTvx9vZm5cqVbNmyhZdeeskov3TpEm+//TZ+fn63bOfi4sLatWvZvHkzmzdvJiIigpo1azJ37tx7+qiAiIiIiIjIvXTHP3lkZmZy8OBB+vbtS8OGDXFzc+PMmTNGvclkMp7JvhV7e/s8dW5ubuzYsYOcnByjLDk5mQoVKhhXswuC5ORkQkND8fHx4dlnnyU7O5vLly8b9SaTiV27dnH+/Pk8bcuVK4ezszNHjhyhcuXKZj83X9G+cfKzP//8k927dxu337u5uZGcnJwnrxvrjx49yokTJ4z6X375haysLLNb+MuUKUNsbCypqakMHTrUbOI5a7Vo0YKJEycyZMgQ1q9fb5TXqFGD9PT0PPt/4+31jo6O+Pv7M3r0aGbNmkVSUpLZRHsiIiIiIiKFzR0H2k5OTpQuXZr4+HgOHz7M5s2b+fDDD436V199lTNnzvDuu+/y22+/cfDgQRISEjh27BgArq6u7Ny5k6NHj3L69GmuX79O165dOXLkCOPGjePAgQOsWbOGWbNm0bNnT6t25tChQ+zevZuTJ08aA9bdu3dbHK9KlSp89dVXpKWlkZycTEREhNkrxoKCgihTpgz9+/dnx44dHD58mNWrVxvb7NevHzExMSxatIiDBw+yZ88e4uPj88z2vXDhQtavX09aWhqjRo0CoFWrVgCEhoaSlJTErFmzSE9PJz4+noSEBHr16gXkPkfu5ubGkCFD2LVrl5Gnn5+f2fPZAOXLl+fTTz8lJSWF4cOH23SwHRgYyAcffMDgwYPZuHEjAH369GHJkiXMnDmT/fv3s3//fpYvX84nn3wCwNKlS0lISGDfvn0cPnyYVatWUapUKeMZbxERERERkcLojgPtIkWKMH36dFJSUggKCmLq1KkMHTrUqH/yySeJjY0lMzOTrl270r59e1auXGncHv3X4DkwMJBGjRpx7NgxY5bu5ORkXnnlFcaNG0doaCjdu3e3amdGjhxJmzZtiI+PZ//+/bRp08aYiMsS48aNIzMzkzZt2jBixAjeeOMNihcvbtQ7ODgwf/58SpYsSa9evQgODubTTz81bsvu0qULo0eP5osvvqB169aEhoayevXqPK8fGzx4MJ988gnBwcHs2bOHmJgYYzu1atVi2rRpfP3117Rq1YrZs2ebTbBWpEgRoqOjKV68OF27duWf//wnJpOJCRMm3HKfKlSoQGxsLNu2bWPUqFFmdxVY65VXXuG9995jwIABJCUl4evrS3R0NJs2bSIkJITOnTsTFxdnXNEvVaoU8fHxdOrUieDgYH799VdmzZqFg4ODzXISEREREXlU2NkVKfA/j4p8PSzs5eVlTL71lxvfFV29enUWLFhwy7ZVq1YlPj4+T3nDhg1ZunTpbbf57bff5ic1MwsXLrzrNn8JCQkhJCTErKxGjRp53nu9ZcsWs2VXV1eioqJuG/fvBvsVK1Y0+jEoKOi2MVq2bJln5veb48TExNy2fuLEiWbLLi4u+e7fm/v05nY3ngcAbdu2pW3btsayr68vvr6+t4zt7+9v09nPRURERERECoJH508KIiIiIiIiIvfB/Z/+2kIxMTHMmjXrlnWtW7dmzJgxf9s+KCjIeG78ZnPmzMHT09PqHAujv3tv9apVq3BxcbmP2YiIiIiIiKUepVuzCzq7HFs+pHsPnTlzhrNnz96yrkSJEpQtW/Zv2x89epTs7Oxb1lWoUIGiRYtanWNhdOjQodvWubq6PpBXkYmIiIiIyN0rZ3r7QadwR6dS//WgU7gvCs0oqnTp0pQuXdri9je/Ukty3fiqLREREREREbFeoRloi9xKvc+/t6r9T12aUGX4Kovbp0/IncTO8ekuFse4fPhzANy6xN1hzdtL+7wrTVdttrg9wIagxngutrw/t3duAkD9L5MsjrG1gzcAz0RvtDjGgb6++K60vC82tmoMYJMYTZZb3hffv+JNwyWWtwf4sZ03LdZYvh/fvJy7H36JlsdY3zI3RvtvN1kcI6G5j1U5/JVHu/WWn99L/HLPb1v0Z8v/WH5cE1/ytsln3docwPr9AOvPi7brrPsdsMy/Ca2/sTzGiha550WQFX2x6n99YW0MW5wXttgPW/SntZ+zgLXWfXeuDfC2yfeetd85ttiPgnJ+d/zO8s/6F8188P7aur5ICvbGZ4Xlx3RT68ZWbf9+ssPuQacg/6Ob+EVERERERERsSANtERERERERERvSreMiIiIiIiIPAc06XnDoSNxg8uTJNGzYEJPJxLp16+759jIyMjCZTOzdu/eebic8PJwBAwZY1LZbt25MmjTJWG7evDmLFi0ylk0mE999953VOYqIiIiIiDws7vkV7W7duuHu7s6wYcPu6Xb27NnD7Nmz+emnnzhz5gyurq506dKFbt265av9zz//zPz581mwYAHPPvssTk5O9zTfwiohIQFHR8cHnYaIiIiIiEiBVWhuHc/KysLe3v629b/++itlypRhypQp/OMf/yA5OZnIyEgef/xxunS584zQhw4dwsnJiUaNGtky7YdOmTJlHnQKIiIiIiJyC7p1vODI15HYsGEDnTt3xtPTkwYNGtCvXz+OHz9u1KemptK7d2/q1KlD3bp16datGydOnCA8PJytW7cyf/58TCYTJpOJjIwMAH788UdCQkJwd3enSZMmREVFcf36dSNm8+bNiYmJYciQIdSpU4fx48f/bY7t27dn5MiR1K9fn0qVKhEcHExISAjffPPNHfdvxowZDB06lDNnzhh5AuzcuZMePXrQoEEDPD096dGjB/v27TNre+zYMQYOHMiLL75I7dq16dChA6mpqUb9F198QUBAAB4eHgQGBrJkyZI829+/fz8dO3bEw8OD4OBgUlJSzOoTExMJDAzE3d0dPz8/4uLMXwOVkZFBWFgYtWvXxtPTkyFDhnD27Nnb7u/27dupX79+njj5cfOt4zebNGkSTZs25eDBgwCsW7eO4OBgPDw8aNGiBXPmzDGOc05ODh9//DG+vr64u7vj4+PDtGnT7jonERERERGRgiRfV7QvX75Mr169qFatGhcuXODDDz9k0KBBLF68mMzMTLp3746XlxeLFi2iaNGi/PTTT1y7do2IiAjS09OpXr06/fr1A3KviP7++++88cYbdOzYkSlTprB3715GjRpFiRIl6NGjh7HduXPn0r9/fwYMGICd3d2/E+78+fP5ugW8Z8+elCpViujoaFauXGmUX7x40fhjQHZ2NrNnzyYsLIzExEQcHBy4evUqr7/+Ok899RSzZ8+mTJkypKSkGAPJ5cuXExUVRWRkJCaTiV9++YWRI0fi5OSEv7+/sZ2pU6cyYsQIqlSpQkxMDG+++Sbr16+nWLFipKSkMHjwYAYOHEhAQABbt25l7NixlC9fHn9/f65fv07fvn1xcnIiLi6OK1euMHr0aIYPH050dHSefd20aRODBg0iMjKS4ODgu+7T27l+/TqRkZFs27aNuLg4XFxc2L59O+Hh4YwcOZJ69epx4MABRo0ahYODA6Ghoaxdu5bY2FimTZvGc889x4kTJ0hPT7dZTiIiIiIiIg9CvgbaLVu2NFseM2YMfn5+/P777yQkJFC6dGmmTp3KY489BoCbm5uxrr29PY6Ojjg7OxtlcXFxVKpUiYiICOzs7HBzcyMjI4N58+aZDbS9vLzMlu/Gjh07WLNmDXPmzLnjusWLF6dkyZIAZnl6eXmZrTd+/Hjq1q1LSkoKnp6erFq1itOnT5OQkGC0r1y5srH+jBkzGD58uDGorlSpErt27SI+Pt5soN29e3djedy4cfj6+rJixQo6depEbGws3t7ehIWFAVC1alV2797N3Llz8ff354cffiAtLY1vv/2WChUqGDE6dOhAeno6VapUMbaTmJhIREQEkydPNtu+tbKzsxk8eDAHDhzgs88+o1y5cgBERUURFhZGmzZtjP3v06cPCxcuJDQ0lOPHj1OuXDm8vLywt7fHxcWFOnXq2CwvEREREZFHiW4dLzjyNdBOT0/no48+YufOnWRmZhrlx44dIzU1lXr16hmD7PxIS0ujTp06Zlep69aty9SpU7lw4QIlSpQAwN3dPd8xb7Rv3z769u3LW2+9ZdUz16dOnWL69Ols27aNU6dOkZOTQ1ZWlnHbfGpqKjVq1DAG2Te6dOkShw8fJjw8nBEjRhjlWVlZuLq6mq1bq1Yt499PPPEEzz//PGlpaUBuXwUEBJitX7duXVavXm3Uu7q6GoNsAA8PD+zt7UlLSzMG2snJyaxbt46YmBh8fHws7pNbGTt2LMWLF2fx4sVmdxDs2bOH5ORkZs6caZRdu3bNuOIfEBDAggULaNGiBT4+Pvj6+tKsWTOKFNEXhIiIiIiIFF75GmiHhYVRqVIlxo8fj7OzMxcvXqRDhw5kZWXd0+SKFSt21232799PaGgoHTt25M0337Rq+8OGDePcuXOMHDkSFxcX7O3tCQ4Oztd+X7p0CYAJEyZQs2ZNs7rHH7//c9BVqVKFkiVLkpCQQOPGje/qDyN34u3tzcqVK9myZQsvvfSSUX7p0iXefvtt/Pz8btnOxcWFtWvXsnnzZjZv3kxERAQ1a9Zk7ty5Fj0qICIiIiIiUhDc8dJhZmYmBw8epG/fvjRs2BA3NzfOnDlj1JtMJuOZ7Fuxt7fPU+fm5saOHTvIyckxypKTk6lQoYJxNdsS+/bto3v37rRp04ZBgwZZHOfGnEJDQ/Hx8eHZZ58lOzuby5cvG/Umk4ldu3Zx/vz5PG3LlSuHs7MzR44coXLlymY/N1/RvnHysz///JPdu3cbt9+7ubmRnJycJ68b648ePcqJEyeM+l9++YWsrCyzW/jLlClDbGwsqampDB061GziOWu1aNGCiRMnMmTIENavX2+U16hRg/T09Dz7f+Pt9Y6Ojvj7+zN69GhmzZpFUlKS2UR7IiIiIiIihc0dB9pOTk6ULl2a+Ph4Dh8+zObNm/nwww+N+ldffZUzZ87w7rvv8ttvv3Hw4EESEhI4duwYAK6uruzcuZOjR49y+vRprl+/TteuXTly5AjjxmuDQmUAACAASURBVI3jwIEDrFmzhlmzZtGzZ0+Ld2Tv3r10796dxo0b8/rrr3Py5ElOnjzJ6dOnLY5ZpUoVvvrqK9LS0khOTiYiIsLsFWNBQUGUKVOG/v37s2PHDg4fPszq1avZvXs3AP369SMmJoZFixZx8OBB9uzZQ3x8fJ7ZvhcuXMj69etJS0tj1KhRALRq1QqA0NBQkpKSmDVrFunp6cTHx5OQkECvXr2A3OfI3dzcGDJkCLt27TLy9PPzM3s+G6B8+fJ8+umnpKSkMHz4cJsOtgMDA/nggw8YPHgwGzduBKBPnz4sWbKEmTNnsn//fvbv38/y5cv55JNPAFi6dCkJCQns27ePw4cPs2rVKkqVKmU84y0iIiIiInejSCH4eTTccU+LFCnC9OnTSUlJISgoiKlTpzJ06FCj/sknnyQ2NpbMzEy6du1K+/btWblypXF79F+D58DAQBo1asSxY8eMWbqTk5N55ZVXGDduHKGhoXTv3t3iHVm7di2nT59m+fLleHt7Gz/t27e3OOa4cePIzMykTZs2jBgxgjfeeIPixYsb9Q4ODsyfP5+SJUvSq1cvgoOD+fTTT43bsrt06cLo0aP54osvaN26NaGhoaxevZpKlSqZbWfw4MF88sknBAcHs2fPHmJiYozt1KpVi2nTpvH111/TqlUrZs+ebTbBWpEiRYiOjqZ48eJ07dqVf/7zn5hMJiZMmHDLfapQoQKxsbFs27aNUaNGmd1VYK1XXnmF9957jwEDBpCUlISvry/R0dFs2rSJkJAQOnfuTFxcnHFFv1SpUsTHx9OpUyeCg4P59ddfmTVrFg4ODjbLSURERERE5H7L18PCXl5exuRbf7nxXdHVq1dnwYIFt2xbtWpV4uPj85Q3bNiQpUuX3nab3377bX5SM7z11lu89dZbd9XmRiEhIYSEhJiV1ahRI897r7ds2WK27OrqSlRU1G3jtmnTxph1+2YVK1Y0+jEoKOi2MVq2bJln5veb48TExNy2fuLEiWbLLi4u+e7fhQsXmi3f3O7G8wCgbdu2tG3b1lj29fXF19f3lrH9/f1tOvu5iIiIiIhIQXD/Z+USERERERERm9PrvQqOQjPQjomJYdasWbesa926NWPGjPnb9kFBQcZz4zebM2cOnp6eVudYGP3de6tXrVqFi4vLfcxGRERERESk8LPLseVDuvfQmTNnOHv27C3rSpQoQdmyZf+2/dGjR8nOzr5lXYUKFShatKjVORZGhw4dum2dq6vrA3kVmYiIiIiI3L1/1Ix40Cnc0fHfxj3oFO6LQjOKKl26NKVLl7a4/c2v1JJcN75qS0RERERECi/dOl5wFJqBtsit1Pv8e6va/9SlCVVnbrS4/cF+uRO9uXWJu8Oat5f2eVcAHJ/uYnGMy4c/p+mqzRa3B9gQ1JgXv0iyuP22jt4AeH9teYyk4NwYT0/fYHGMw4Oa4rPC8r7Y1LoxQIGIYc3xgNxj0mKN5Tl883LufrT8j+V5JL6Ue0xbf2P5Z3VFiyYEr7Pus/61fxParbc8xhK/JgC0tSKPZf65MZqttvyYfBfYmIZLrDsvfmznbZNjGrDW8hhrA3JjWHtMrGn/V4wgK/pi1f/6whYxrD0mviut+x2wsVVjm5wXBaEvrGn/Vwxrv7PA+vPbmr6E3P70S7T8vFjfMvd3gDXfv1//73uv/bebLI6R0NzHqv+3gNz/v7DFd5bI3dCfPERERERERERsSFe0RUREREREHgJ2uo5aYOhIiIiIiIiIiNiQBtoiIiIiIiIiNqSB9g0mT55Mw4YNMZlMrFu37p5vLyMjA5PJxN69e+/pdsLDwxkwYIBFbbt168akSZOM5ebNm7No0SJj2WQy8d1331mdo4iIiIiIWMfOrkiB/3lU3PNntLt164a7uzvDhg27p9s5d+4cgwcPJjU1lczMTMqWLYufnx+DBw+mRIkSd2z/888/M3/+fBYsWMCzzz6Lk5PTPc23sEpISMDR0fFBpyEiIiIiIlJgFZo/KWRlZf1tvZ2dHc2aNSM6Opq1a9cyceJE/vvf//Lee+/lK/6hQ4dwcnKiUaNGODs74+DgYIOsHz5lypTRQFtERERERORv5GugvWHDBjp37oynpycNGjSgX79+HD9+3KhPTU2ld+/e1KlTh7p169KtWzdOnDhBeHg4W7duZf78+ZhMJkwmExkZGQD8+OOPhISE4O7uTpMmTYiKiuL69etGzObNmxMTE8OQIUOoU6cO48eP/9scS5YsyauvvoqHhweurq40atSILl26kJycfMf9mzFjBkOHDuXMmTNGngA7d+6kR48eNGjQAE9PT3r06MG+ffvM2h47doyBAwfy4osvUrt2bTp06EBqaqpR/8UXXxAQEICHhweBgYEsWbIkz/b3799Px44d8fDwIDg4mJSUFLP6xMREAgMDcXd3x8/Pj7g483c2Z2RkEBYWRu3atfH09GTIkCGcPXv2tvu7fft26tevnydOftx86/jNJk2aRNOmTTl48CAA69atIzg4GA8PD1q0aMGcOXOM45yTk8PHH3+Mr68v7u7u+Pj4MG3atLvOSUREREREpCDJ163jly9fplevXlSrVo0LFy7w4YcfMmjQIBYvXkxmZibdu3fHy8uLRYsWUbRoUX766SeuXbtGREQE6enpVK9enX79+gG5V0R///133njjDTp27MiUKVPYu3cvo0aNokSJEvTo0cPY7ty5c+nfvz8DBgzAzs7urnbsxIkTfPPNN9SvX/+O6/bs2ZNSpUoRHR3NypUrjfKLFy8afwzIzs5m9uzZhIWFkZiYiIODA1evXuX111/nqaeeYvbs2ZQpU4aUlBRjILl8+XKioqKIjIzEZDLxyy+/MHLkSJycnPD39ze2M3XqVEaMGEGVKlWIiYnhzTffZP369RQrVoyUlBQGDx7MwIEDCQgIYOvWrYwdO5by5cvj7+/P9evX6du3L05OTsTFxXHlyhVGjx7N8OHDiY6OzrOvmzZtYtCgQURGRhIcHHxXffp3rl+/TmRkJNu2bSMuLg4XFxe2b99OeHg4I0eOpF69ehw4cIBRo0bh4OBAaGgoa9euJTY2lmnTpvHcc89x4sQJ0tPTbZaTiIiIiMij5G7HTHLv5Gug3bJlS7PlMWPG4Ofnx++//05CQgKlS5dm6tSpPPbYYwC4ubkZ69rb2+Po6Iizs7NRFhcXR6VKlYiIiMDOzg43NzcyMjKYN2+e2UDby8vLbDk/Bg8ezPr167ly5QrNmzdnzJgxd2xTvHhxSpYsCWCWp5eXl9l648ePp27duqSkpODp6cmqVas4ffo0CQkJRvvKlSsb68+YMYPhw4cbg+pKlSqxa9cu4uPjzQba3bt3N5bHjRuHr68vK1asoFOnTsTGxuLt7U1YWBgAVatWZffu3cydOxd/f39++OEH0tLS+Pbbb6lQoYIRo0OHDqSnp1OlShVjO4mJiURERDB58mSz7VsrOzubwYMHc+DAAT777DPKlSsHQFRUFGFhYbRp08bY/z59+rBw4UJCQ0M5fvw45cqVw8vLC3t7e1xcXKhTp47N8hIREREREXkQ8jXQTk9P56OPPmLnzp1kZmYa5ceOHSM1NZV69eoZg+z8SEtLo06dOmZ/calbty5Tp07lwoULxuRl7u7u+Y75l+HDh9OvXz/S09OZNm0akydPZuTIkXcdB+DUqVNMnz6dbdu2cerUKXJycsjKyjJum09NTaVGjRrGIPtGly5d4vDhw4SHhzNixAijPCsrC1dXV7N1a9WqZfz7iSee4PnnnyctLQ3I7auAgACz9evWrcvq1auNeldXV2OQDeDh4YG9vT1paWnGQDs5OZl169YRExODj4+PRf1xO2PHjqV48eIsXrzYbBK5PXv2kJyczMyZM42ya9euGVf8AwICWLBgAS1atMDHxwdfX1+aNWtGkSKFZuoAERERERGRPPI10A4LC6NSpUqMHz8eZ2dnLl68SIcOHe44QZm1ihUrdtdtnJ2dcXZ2xs3NDScnJ1599VX69OlD2bJl7zrWsGHDOHfuHCNHjsTFxQV7e3uCg4Pztd+XLl0CYMKECdSsWdOs7vHH7/lk73lUqVKFkiVLkpCQQOPGje/qDyN34u3tzcqVK9myZQsvvfSSUX7p0iXefvtt/Pz8btnOxcWFtWvXsnnzZjZv3kxERAQ1a9Zk7ty5uu1FREREROQuPUqvzyro7ngkMjMzOXjwIH379qVhw4a4ublx5swZo95kMhnPZN+Kvb19njo3Nzd27NhBTk6OUZacnEyFChXy9Squu2XpHwSSk5MJDQ3Fx8eHZ599luzsbC5fvmzUm0wmdu3axfnz5/O0LVeuHM7Ozhw5coTKlSub/dx8RfvGyc/+/PNPdu/ebdx+7+bmlmdCt+TkZLP6o0ePcuLECaP+l19+ISsry+wW/jJlyhAbG0tqaipDhw41m3jOWi1atGDixIkMGTKE9evXG+U1atQgPT09z/7feHu9o6Mj/v7+jB49mlmzZpGUlGQ20Z6IiIiIiEhhc8eBtpOTE6VLlyY+Pp7Dhw+zefNmPvzwQ6P+1Vdf5cyZM7z77rv89ttvHDx4kISEBI4dOwaAq6srO3fu5OjRo5w+fZrr16/TtWtXjhw5wrhx4zhw4ABr1qxh1qxZ9OzZ0+Id+f7770lISCA1NZWMjAw2btzIe++9x4svvshTTz1lUcwqVarw1VdfkZaWRnJyMhEREdjb2xv1QUFBlClThv79+7Njxw4OHz7M6tWr2b17NwD9+vUjJiaGRYsWcfDgQfbs2UN8fHye2b4XLlzI+vXrSUtLY9SoUQC0atUKgNDQUJKSkpg1axbp6enEx8eTkJBAr169gNznyN3c3BgyZAi7du0y8vTz8zN7PhugfPnyfPrpp6SkpDB8+HCbDrYDAwP54IMPGDx4MBs3bgSgT58+LFmyhJkzZ7J//37279/P8uXL+eSTTwBYunQpCQkJ7Nu3j8OHD7Nq1SpKlSplPOMtIiIiIiJSGN1xoF2kSBGmT59OSkoKQUFBTJ06laFDhxr1Tz75JLGxsWRmZtK1a1fat2/PypUrjduj/xo8BwYG0qhRI44dO2bM0p2cnMwrr7zCuHHjCA0NpXv37hbvyBNPPEFCQgKvvvoqgYGBjB8/nqZNm95y5u38GjduHJmZmbRp04YRI0bwxhtvULx4caPewcGB+fPnU7JkSXr16kVwcDCffvqpcVt2ly5dGD16NF988QWtW7cmNDSU1atXU6lSJbPtDB48mE8++YTg4GD27NlDTEyMsZ1atWoxbdo0vv76a1q1asXs2bPNJlgrUqQI0dHRFC9enK5du/LPf/4Tk8nEhAkTbrlPFSpUIDY2lm3btjFq1Cizuwqs9corr/Dee+8xYMAAkpKS8PX1JTo6mk2bNhESEkLnzp2Ji4szruiXKlWK+Ph4OnXqRHBwML/++iuzZs3SO8xFRERERCxgR5EC//OoyNfDwl5eXsbkW3+58V3R1atXZ8GCBbdsW7VqVeLj4/OUN2zYkKVLl952m99++21+UjPUr1+fxYsX31WbG4WEhBASEmJWVqNGjTzvvd6yZYvZsqurK1FRUbeN26ZNG2PW7ZtVrFjR6MegoKDbxmjZsmWemd9vjhMTE3Pb+okTJ5otu7i45Lt/Fy5caLZ8c7sbzwOAtm3b0rZtW2PZ19cXX1/fW8b29/e36eznIiIiIiIiBcGj8ycFERERERERkfvg/k9/baGYmBhmzZp1y7rWrVvf8X3ZQUFBxnPjN5szZw6enp5W51gY/d17q1etWoWLi8t9zEZERERERCylWccLDrscWz6kew+dOXOGs2fP3rKuRIkSd3x919GjR8nOzr5lXYUKFShatKjVORZGhw4dum2dq6vrA3kVmYiIiIiI3L0qtSfeeaUHLP3n8Aedwn1RaEZRpUuXpnTp0ha3v/mVWpLrxldtFUbeXydZ1T4p2Bu/xM0Wt1/fsjEATVdZHmNDkG1iOD7dxeL2AJcPf47vSstz2Ngqdz+arbY8xneBuTEaJFh+XLe09wb2Wtweqv3vv9bHsOb8TAr2puES687vH9t5W50DQOtvvrc4xooWTQAI+o/leax6yduq9n/FsMV+2CKGtZ8za9r/FaOlFf2Z+FLueRGw1vIYawNyY7RYY/m+fPNyY6uOB+QeE1v0hbXnN0DwOsv35Wv/Jjb5vigofWFtHtb8Xofc3+0FoS+s+YxB7ufMFv+PY4vvPc/FlsfY3rmJTX4H2OLcFLkbhWagLSIiIiIiIrenW8cLDh0JERERERERERvSQFtERERERETEhjTQFhEREREREbEhDbQfUt26dWPSpEk2jblo0SKaN29u05giIiIiImIbdhQp8D+PikdnT6VAWrp0KQ0aNHjQaYiIiIiIiNiMBtoiIiIiIiIiNqSB9kMsKyuL9957j3r16tGoUSNmzZoFQEZGBiaTib17/+89wXv37sVkMpGRkWGUffnll/j6+lK7dm3efvttzp8/nyf+mDFjqFevHg0aNGDGjBkMGDCA8PD/ewn9n3/+ycSJE/H29qZOnTp07tyZn3/+GYAtW7YwfPhwzpw5g8lkwmQyMWPGjHvZJSIiIiIiDy+7IgX/5xHx6OzpI2jJkiUUK1aML7/8kiFDhhAVFUViYmK+2iYnJxMZGUloaCjLli3Dw8ODuXPnmq0zd+5cVq9ezZQpU4iLi+PYsWNs3rzZbJ2xY8eSkpLCRx99xNdff42Pjw+vv/46J06coE6dOowYMYLSpUuTlJREUlISPXv2tNn+i4iIiIiIPAgaaD/EKlWqxNChQ3nmmWdo164dHTp0IDY2Nl9tFy1aRNOmTenZsydVq1alV69eeHp65lknLCyM5s2b4+bmxvvvv88TTzxh1B87doxly5bx8ccfU69ePZ5++mn69u3Lc889x/Lly3FwcKBkyZIAODs74+zsTPHixW3XASIiIiIiIg/A4w86Abl3XnjhBbPl2rVrs2LFiny1PXDgAC+//HKe9vv27QPg/PnznDp1ilq1ahn1Dg4OVK9e3Vjeu3cv2dnZtGjRwizOn3/+abaeiIiIiIhYz+4RujW7oNNA+xFUpEjuBzAnJ8coy87Otvl2Ll26hL29PcuWLcPOzs6srkSJEjbfnoiIiIiISEGgP3k8xFJSUsyWd+7ciZubG2XKlAHg1KlTRt2ePXvM1n3mmWfYuXNnnvZ/KVmyJOXKleOXX34xyq5evWoWp3r16mRlZZGZmUnlypXNfsqWLQuAvb09169ft3JPRURERERECg5d0X6IHT58mKlTp9KuXTt+/vlnvvzySyZOnEjRokWpVasWc+bM4amnnuL48ePMmzfPrO2rr77Ka6+9xr///W98fX3ZsGED27Ztw8nJyVjntddeIyYmhqeffpqnn36aefPm8eeffxpXr5955hkCAwN59913CQ8Px2Qycfr0ab7//nvq169P/fr1cXV15fz582zZsoXnnnsOR0dHHB0d72s/iYiIiIg8DG6+i1QeHF3Rfoi1a9eOs2fP0q5dOyZNmkSfPn0IDAwEYNy4cVy4cIG2bdsSFRXFgAEDzNrWq1eP999/n3nz5tGmTRt27NhB7969zdbp3bs3LVu25J133qFr16784x//oF69ejg4OBjrTJo0iaCgIMaPH0/Lli1566232LdvH+XLlwegbt26dOrUiQEDBtCoUaM8M5uLiIiIiIgUNrqi/ZBauHCh8e+xY8fmqa9WrRoJCQlmZampqWbLHTt2pGPHjmZlffr0Mf5tb29PZGQkkZGRQO5z3v7+/jRs2NBYx8HBgUGDBjFo0KDb5vr+++/z/vvv52OvRERERERECj4NtMViR44c4ccff8TT05M///yTBQsWkJmZmWe2chERERERuffsdMNygaGBtlisSJEiLFmyhIkTJwK5k58tXLgQFxeXB5yZiIiIiIjIg2OXc+M7nkRERERERKRQes5zxoNO4Y72bX/rrtb/7LPPmDdvHidPnuT5559n5MiR1KpV65brduvWja1bt+Yp9/X1Zfbs2QCEh4ezbNkys3pvb+88k0NbS1e0RUREREREHgJ2dg/XreOrV69mwoQJvP/++7zwwgvExsbSu3dv1qxZY7yy+EYzZswgKyvLWD5z5gzBwcF5Hm1t1qyZ2TxWN07mbCsaaEuh1veH76xqH+3VjIZLkixu/2M7bwA8F39vcYztnZsA8OIXluexraM3vis3W9weYGOrxjg+3cXi9pcPfw5A2GbLj0lM42YAVu3LxlaNCV5n+fH42j/3eNgiRsBay4/p2gBvq3L4K48myy3P4ftXcs/vZqstPx7fBTa2SYzW31jXFytaNMFnheU5bGqdux8t1lge45uXbdMX1pxXkHtudd+40eL2n/r6AhD0H8vzWPVS7rll7efMFudF//9a/p0V1Sj3O6vpKsuP6Yag3POirRV9scy/CS2tOB4AiS952+SY2uIzYm0Ma/oScvvzNSs+I4v+9xlp/+0mi2MkNPexyfltTYwVLXJ/l1lzbiX+77yw9jPSbr11fbHErwn1v7R8P7Z28LZq+2Lu3LlznDt3Lk95qVKlKFWqlFnZggUL6NSpE+3atQNyJ1HesGEDy5Yto1evXnlilC5d2mx51apVFC1aNM9A28HBAWdnZ2t35W9poC0iIiIiIiL3RWxsLFFRUXnK+/fvz1tv/d9t5VevXuW3334ze+tRkSJF8PLy4ueff87XtpYsWUJQUBDFihUzK//vf/9Lo0aNKFWqFF5eXgwcODDPIN1aGmiLiIiIiIjIfREaGkrbtm3zlN98NTszM5Nr165Rrlw5s/KyZcty6NChO24nJSWFvXv3Mm7cOLPyJk2a0KJFCypWrMiRI0eYNm0ab775Jp9//jlFitju1nsNtEVERERERB4GdnYPOoM7utUt4vdCQkIC1apVyzNxWlBQkPFvk8mEyWTC39+f7du3U79+fZtt/+F6Wv4htmXLFkwmExcvXvzb9Zo3b86iRYvuU1YiIiIiIiK29+STT/LYY49x6tQps/I//vjjjs9XX7p0iVWrVtG+ffs7bqdSpUo8+eST+bpKfjc00C6gunXrxqRJk4zlOnXqkJSUZDxfsHTpUho0aPCg0hMREREREblnHBwcqFmzJj/88INRdv36df773/9Su3btv227Zs0arl69yiuvvHLH7fz++++cOXOG8uXLW53zjXTreCFxP2bGKwiuXr16T6bXFxERERF56D1kl1Fff/11hg0bRs2aNalVqxaxsbFcuXLFeMZ76NChVKhQgXfeecesXUJCAv7+/jz55JNm5RcvXiQqKoqAgADKlSvHkSNHmDJlClWrVqVRo0Y2zf0hOxQPh/DwcLZu3cr8+fON5waWLl1q3Dq+ZcsWhg8fzpkzZ4z6GTNu/XL6s2fPMmLECBo0aEC9evXo1asXaWlpd8zhp59+wt3dndOnT5uVR0REEBYWZiyvW7eO4OBgPDw8aNGiBXPmzOH69etG/dy5c2nVqhUvvPACTZs2ZcKECfz5559G/YwZMwgJCWHx4sU0b95cV+lFRERERASAwMBAhg0bxscff0xwcDC7d+9m7ty5xju0jx8/zsmTJ83aHDhwgJ9++umWt40/9thj7N27lz59+vDyyy8TERGBu7s7ixYtsvnFPl3RLoAiIiJIT0+nevXq9OvXD4D9+/cb9XXq1GHEiBFER0ezcuVKgDxT1v/l7bffplixYsybN4/ixYvz6aef0rNnTxITE2/bBqBevXpUrFiR5cuX06NHDwAuX77MmjVrmDBhAgDbt28nPDyckSNHUq9ePQ4cOMCoUaNwcHAgNDQUgMcff5xRo0bh6upKeno6o0eP5oknnmDw4MHGtg4ePMh3331HdHQ0doVgAgcREREREbk/XnvtNV577bVb1i1cuDBP2TPPPENqauot1y9atCjz5s2zaX63oyvaBVDJkiWxt7fH0dERZ2dnnJ2dzaaad3BwoGTJkgBGffHixfPE2b59O7/99hvTp0/H3d2dqlWrMmrUKK5du8aGDRvumEf79u1ZtmyZsfyf//wHe3t7mjVrBkBUVBRhYWG0adOGSpUq4evrS58+fYiPjzfa9OjRgwYNGlCxYkW8vb3p168fiYmJZtvJzs5m0qRJVK9eHZPJdFd9JSIiIiIi/2NnV/B/HhG6ov0QS01N5fz583lux75y5QpHjhy5Y/s2bdowffp0du3aRY0aNVi2bBmtW7fG3t4egD179pCcnMzMmTONNteuXTO7dfyHH34gJiaGAwcOcPHixTz1ABUrVrT5C+JFREREREQeFA20H2IXL17kqaee4t///neeOicnpzu2L1euHL6+vixdupQnn3ySLVu2EB4ebtRfunSJt99+Gz8/v1u2z8jI4M033+S1117jnXfeoVSpUmzevJmxY8earefo6Hh3OyYiIiIiIlKAaaBdQNnb23Pt2rW/rb/5yvDNatSowf/7f/8PBwcH/vGPf1iUR/v27Rk+fDglS5akevXqVK9e3Sx+eno6lStXvmXb3377DYBhw4YZZUuWLLEoDxERERERuYNH6Nbsgk7PaBdQrq6u7Ny5k6NHj3L69Ok8g2pXV1fOnz/Pli1bOH36NJcvX84Tw8vLCw8PD/r27cvmzZs5cuQI27dvZ9KkSfmaeRzA19cXe3t75syZQ0hIiFldnz59WLJkCTNnzmT//v3s37+f5cuX88knnwBQuXJlrl69yqJFizhy5AgJCQlmz3yLiIiIiIg8jDTQLqB69uwJ5E5p36hRI44fP25WX7duXTp16sSAAQNo1KgRc+fOzROjSJEizJ07l9q1azNs2DBatmzJ0KFDyczMzPcz0Y899hjBwcEAtGrVyqzO19eX6OhoNm3aREhICJ07dyYuLg5XV1cAqlevzvDhw4mJiaFVq1Z88803vP3223fdFyIiIiIiIoWJbh0voKpW3rwPkwAAIABJREFUrWo2ezeQ54ry+++/z/vvv29W9u2335otlyhRgtGjRzN69GiLczl58iR+fn55XvgOuYNtX1/f27bt0aOH8Xqwv3To0MH491tvvcVbb71lcW4iIiIiIvI/uoxaYGigLbd1/vx59uzZQ2JiIgsWLHjQ6YiIiIiIiBQKGmg/woKCgjh27Ngt6+bMmcNHH33EL7/8QmhoKJ6envc5OxERERERkcJJA+1H2OzZs8nOzr5lXYUKFVi4cOF9zkhERERERKTws8vJycl50EmIiIiIiIiIdZ5rMutBp3BH+75/80GncF/oirYUalUiE61qnz6mJQ0Skixuv6W9NwD1v7Q8xtYOuTG8v7Y8RlKwN81Wb7a4PcB3gY0J2/ydxe1jGjcDwPHpLhbHuHz4cwCqzdlkcYy9//Sh6SrL+2JDUGMAm8TosWmjxTH+7eNLy/9Yfk4AJL7kjc8Ky/djU+vc/fD49HuLY/zSvQkAo35aZ3GMsfX8rToekHtMGi+zvD83t839nFaetN7iGIeG+QH8f/buPK6qOv/j+AsUCmXUVNwRtwEXLoJQ5IIiaKSmEtpoLk0uTKXpmCvumSjgWtCkTOhYUmaCYqhFLqih/SizUdMRkzBwGWNcc0sSfn8w3ukGKt57FcT38/G4jwfne873cz7f7z3nXr+e7z2HF3aYf1y836kT/VPNPz8APurckcBPze/Prd0KjwvvVeYfF988X3hcTPxq2x22vLV5TwTQc7P5OQAkd/Wj62fm98Xmpwv7IijF/GMrJajw2LKkLcld/ei7zbLjIiGgo1XaYcl3UWr3wv78kwXH+MedO+LzkWXHxZ7+flb5DrD02LLG93oPC75HNj5V+J5aI4Yl78me/n4WHRNQeFxY4/tQ5G7ovnQiIiIiIiIiVqQr2iIiIiIiIuWBTWknIDfpiraIiIiIiIiIFWmgLSIiIiIiImJFGmjfB4MHDyYqKsqqMaOiohg8ePA93YeIiIiIiDxAbG3K/ushod9o3wcxMTFUrKiuFhEREREReRho9HcfVKtWrbRTKFPy8vKws7Mr7TRERERERETuCU0dvw9+O607ICCA2NhYxo0bh6enJ4GBgezatYuTJ08yZMgQPD09ee655zh27JhJjCVLltC2bVu8vb15/fXXycvLK7KfvLw8Xn/9dby9vWnbti2xsSV7YP3169eZNWsW7du3x2AwEBgYyMqVK43rz58/z9SpU2nbti0eHh706tWLL7/80rg+Pj6ewMBA3N3d6d69OykpKcZ1x48fx83NjU2bNjFgwADc3d3ZsqXweboff/wxQUFBGAwGunfvTmJiYon7VEREREREfsfGpuy/HhIaaJeC5cuX8+STT5KUlMTjjz/OhAkTmD59On/+859JTEykYsWKzJo1y7j9hg0bWLJkCRMmTGDNmjU4ODiwdu3aInETExOpVKkSa9asYfz48bz99tt8+umnd8xn5cqVpKam8tZbb/HZZ58xd+5catWqZVw/atQoDh48yKJFi9iwYQOjR4/G5r8nSUpKCpGRkfzlL38hOTmZXr16MWbMGA4ePGiyj0WLFjF06FA+/fRTHn/8cT755BPefvttJkyYwKZNm3j11VeZM2eOcRAuIiIiIiLyoNLU8VIQEBDAc889B8Arr7zCunXr8PPzw9/fH4A///nPjB8/nvz8fGxtbVm5ciV/+tOfCAkJAWDSpEmkpaUVievs7MzEiRMBaNKkCQcPHuS9996jW7dut83n1KlTuLi44O3tjY2NDfXr1zeu++qrr/jmm29ISUnB2dkZgIYNGxrX/+Mf/6Bv377069cPgJdffplvvvmG5cuXs3DhQuN2Q4YMoUuXLsblmJgYJk+ebCxzdnbm0KFDrF692mQ7ERERERGRB42uaJcCNzc34981atQA4I9//KOxrGbNmuTl5XHx4kUAfvjhB1q3bm0S4/fLxZV5enqSmZl5x3x69+7NoUOHePrpp5kzZ47JtPCMjAzq1atnHGT/XmZmJm3atDEpa9OmDT/88INJmbu7u/HvK1eukJ2dTVhYGF5eXsbXihUryM7OvmO+IiIiIiJSDJsH4PWQ0BXtUvDbO5DfnIJd3F3J8/Pz70s+BoOBrVu3snPnTnbt2sWIESPo0aMH4eHhVtuHg4OD8e8rV64AEBERQatWrUy2093ZRURERETkQacr2g+AJk2asG/fPpOy3y8D7N+/v8g2TZs2LdE+qlSpwjPPPENERARz5sxh3bp15Ofn4+bmxsmTJ8nJySm2XtOmTdm7d69J2d69e2+735o1a+Lk5EROTg4uLi4mr99OWxcREREREXkQ6fLhA2DgwIFMnz4dd3d3WrduzZo1azhx4kSRx4ZlZ2ezYMEC+vTpwz//+U/WrFlDZGTkHeOvWLGCWrVq0bx5cwoKCtiyZQsuLi7Y2tryxBNP4O3tzahRo5g0aRINGjTg+++/p3Llyvj6+jJkyBDGjRtHixYt8PX1JSUlhbS0NBISEm67z5EjRzJv3jwqV65M+/bt+eWXX9i3bx83btxgwIABFvWXiIiIiMhDyfYhmptdxmmg/QDo1asXOTk5REREkJeXR48ePQgJCSEjI8Nkuz59+nDhwgX69OmDvb09r7zyCt27d79jfAcHB2JjY8nOzqZChQq0bt2amJgY4/ro6GiioqIYM2YM165do3HjxkyePBmAoKAgcnNziY2NZfbs2TRs2JA333yzyJTw33v++edxcHBg+fLlREZGUrlyZZo3b87w4cPN6CEREREREZGyQwPt++C3z6Tetm2bybrKlSsXGTD7+PgUKRs5ciQjR44s0T5mz559V/n169fPeNfw4jz22GO3vTI+aNAgBg0aVOy6Bg0aFGnLTcHBwQQHB99VriIiIiIiImWdfqMtIiIiIiIiYkW6ov0Q+OSTT5g5c2ax67y9vYmLi7vPGYmIiIiIiNXZ6DfaZYVNQUFBQWknIffWpUuXOHPmTLHrHn30UWrXrn2fMxIREREREWv7Y9dlpZ3CHX2/eVhpp3Bf6Ir2Q8DR0RFHR8fSTuOeaPy3HRbVzxrZCc8PvjC7/j8H+gHQ5B3z8/hhRCcAGi7ebnaM7Nf88U1IM7s+QHrfDnTasMvs+jueaQ+A67s7zY5xJLQjAA4Nnzc7xtXsVbjFmZ9DxvDCHKwRw9K+aDQrxez6AMdmBtFimfk5/GtYYTv+lGp+jI87F8bo9rn5x+enT3Vg0A7LzvX4Tp0YsN38GB/6F56nU/dsNTvGHJ9AwPLjwpL3FArf1x4WvB8bn+oAQJ+t5n92JgYWfnZa8r7Gd+pkUQ438+j6mfmfe5ufLvzc67nZ/DySuxb2haXnWat/WHZcHBzS0SrtKAsxnt1i2XGxroufVc4RS2MEpVj2vZ4SZFmMlKDCdljjHHlxp/nn+oqOnWgdb9l7um+QH6O/TDW7fnTbzhbtXx5OGmiLiIiIiIiUB5o5XmboZmgiIiIiIiIiVqSBtoiIiIiIiIgVaeq4iIiIiIhIeWCrueNlha5oi4iIiIiIiFiRBtoiIiIiIiIiVqSp42K2vLw87OzsSjsNEREREREB3XW8DNEVbTG6dOkS48aNw9PTEz8/P1atWkVISAgxMTEAuLm5sXr1al566SVat27Ne++9B0B8fDyBgYG4u7vTvXt3UlL+9+zf69evM2vWLNq3b4/BYCAwMJCVK1cCUFBQQHR0NJ06dcLd3Z2OHTuyaNGi+99wERERERERK9IVbTGKjIxk3759xMbGUq1aNRYuXEhWVhadO3c2bhMdHc2ECROYNm0aFStWJCUlhcjISKZPn84TTzxBSkoKY8aMISEhgVatWrFy5UpSU1N56623qFu3LsePH+f8+fMApKSk8N5777Fo0SL++Mc/cvr0aY4dO1ZKrRcREREREbEODbQFKLyanZSUxJtvvomvry8AERERdOrUyWS7Xr16ERwcbFx+7bXX6Nu3L/369QPg5Zdf5ptvvmH58uUsXLiQU6dO4eLigre3NzY2NtSvX99Y99SpU9SsWZN27dphZ2dHvXr18PLyug+tFREREREpfwpsNHe8rNDUcQHg+PHj5OXlYTAYjGU1atQwGRgDJusBMjMzadOmjUlZmzZt+OGHHwDo3bs3hw4d4umnn2bOnDl8+eWXxu2CgoK4evUqXbt2ZcaMGWzdupX8/HxrN01EREREROS+0kBb7oqDg8NdbW8wGNi6dSujRo3i0qVLjBgxgmnTpgFQr149UlJSmDZtGhUqVGDq1KmEhoZSUFBwL1IXERERERG5LzTQFgAaNGiAnZ0dBw4cMJadPXuWEydO3LZe06ZN2bt3r0nZ3r17adq0qXG5SpUqPPPMM0RERDBnzhzWrVtnvHLt4OBAly5dmDlzJrGxsaSlpXHq1CkrtkxEREREROT+0m+0BQBHR0eCg4OJioqiSpUqVK1alUWLFmFnZ4fNbX7rMWTIEMaNG0eLFi3w9fUlJSWFtLQ0EhISAFixYgW1atWiefPmFBQUsGXLFlxcXLC1tWXt2rXk5+fTunVrHnnkETZu3EiVKlWoWbPm/Wq2iIiIiEj5YavfaJcVGmiLUVhYGDNmzCA0NJQqVaowYsQIjh8/jr29/S3rBAUFkZubS2xsLLNnz6Zhw4a8+eabtGrVCii8Yh0bG0t2djYVKlSgdevWxseFValShdjYWObOnUtBQQEtWrQgNjb2tvsTEREREREp6zTQFiNHR0eT51hfvHiRyMhIXFxcAMjIyCi23qBBgxg0aFCx6/r162e8I/nvdenShS5duliYtYiIiIiISNmigbYYfffdd/z4448YDAbOnz9PdHQ0jo6O+Pn5lXZqIiIiIiJyJ5o5XmZooC1GBQUFxMXFcezYMezt7TEYDMTHx1OpUqXSTk1EREREROSBYVOgZymJiIiIiIg88Jr1XFHaKdzR0eQXSzuF+0JXtEVERERERMqD2zwtSO4vDbTlgdb1s10W1d/8dHs6bzI/Rmr39gB02mB+jB3PFMbomGx+jJ092wNHzK5fyJXeW74wu/b6LoW/5fffaH47tvco7Au3uJ1mx8gY3hGHhs+bXf9q9ioAq8To9nma2TE+faoDgZ9adnxv7dbe4hwAglLMj5ESVBjDknN189Pt6WFBOwA2PtXBKu3os9X8cyQxsPAcsfQzp6wcF5a8Jxv/G+NZCz5z1nXxs8p3gDWOi7JwjljSl1DYn2Xl88LSPCz5LoPC77Oy0BeW1L8Zo+dm8/siuat1PrMAXv0y1ewYb7ftjN8nlvXFF706WPx5I3K3bEs7AREREREREZHyRFe0RUREREREygNbTR0vK3RFW0RERERERMSKNNCWe+rw4cOEhITg7u5O7969OX78OG5ubhw5YunviUVERERERMomDbTlnpo/fz5169bl888/Z8WKFdStW5e0tDSaNGkCQHp6Om5ubly+fLmUMxURERERecDZPACvh4QG2mKWvLy8Em2XnZ3Nk08+Sb169XjssceoUKECTk5OVKyo2wOIiIiIiEj5pIG2ADB48GDCw8N5/fXX8fb2pm3btsTGxhrXu7m5sXr1al566SVat27Ne++9B0B8fDyBgYG4u7vTvXt3UlJSTOpkZ2cTHh6Om5sbMTExJlPHjx8/zgsvvABAmzZtcHNzIyws7P42XERERERExMo00BajxMREKlWqxJo1axg/fjxvv/02n376qXF9dHQ03bp1Y8OGDfTo0YOUlBQiIyP5y1/+QnJyMr169WLMmDEcPHgQgLS0NOrUqcPYsWNJS0tj6NChJvurW7cuMTExAGzZsoW0tDSmTp16/xosIiIiIiJyD2j+rhg5OzszceJEAJo0acLBgwd577336NatGwC9evUiODjYuP1rr71G37596devHwAvv/wy33zzDcuXL2fhwoU4OTlRoUIFKleujJOTEwDnzp0z1q9QoQJVq1YFoHr16lSuXPm+tFNEREREpFyyeYh+BF3G6Yq2GLVu3dpk2dPTk8zMTOOywWAwWZ+ZmUmbNm1Mytq0acMPP/xw75IUEREREREp4zTQlhJzcHAo7RRERERERETKPA20xWj//v0my/v27aNp06a33L5p06bs3bvXpGzv3r23rfN7dnZ2AOTn599FpiIiIiIiUoSNTdl/PSQ00Baj7OxsFixYQFZWFuvWrWPNmjXGu4IXZ8iQISQkJLB69WqOHTtGbGwsaWlpDBkypMT7rF+/PjY2NqSmpnL27Fk9T1tERERERB54uhmaGPXp04cLFy7Qp08f7O3teeWVV+jevfsttw8KCiI3N5fY2Fhmz55Nw4YNefPNN2nVqlWJ91m7dm1GjRrFvHnzmDhxIsHBwURGRlqjOSIiIiIiIqVCA20xsrOzY9q0acyePbvIuoyMjGLrDBo0iEGDBt0y5rZt20yWGzRoUCTWyJEjGTlypBkZi4iIiIiIkeYrlxl6K0RERERERESsSANtERERERERESvS1HEBYOXKlaWdgoiIiIiIWOIhuqt3WWdTUFBQUNpJiIiIiIiIiGWa/emD0k7hjo5+PLC0U7gvdEVbHmhdP9tlUf3NT7en8ybzY6R2bw9Apw3mx9jxTGGMjsnmx9jZsz1wxOz6hVzpveULs2uv7+IHgP9G89uxvUdhX7jF7TQ7Rsbwjjg0fN7s+lezVwFYJUa3z9PMjvHpUx0I/NSy43trt/YW5wAQlGJ+jJSgwhiWnKubn25PDwvaAbDxqQ5WaUefreafI4mBheeIpZ85ZeW4sOQ92fjfGM9a8JmzroufVb4DrHFclIVzxJK+hML+LCufF5bmYcl3GRR+n5WFvrCk/s0YPTeb3xfJXa3zmQXw6pepZsd4u21n/D6xrC++6NXB4s8bkbulgbaIiIiIiEh5oJnjZYZuhiYiIiIiIiJiRRpoi4iIiIiIiFiRpo6LiIiIiIiUAwW2mjteVuiKttxzGzduJDAwkBYtWjBnzhzWrl2Lr69vaaclIiIiIiJyT+iKttxTv/76K9OmTePll18mODiYypUrU7FiRTp16mTcJiYmhtTUVNauXVuKmYqIiIiIiFiHBtoPmOvXr2Nvb1/aaVBQUMCNGzeoWPH2h9B//vMfrly5gr+/P7Vr1zaWP/roo/c6RRERERERkVKhqeP32ODBg5k7dy5z587Fx8eHjh078sEH/3uQ/OHDhxk8eDAGg4Enn3yS2bNnc/36dZP64eHhhIeH4+vry6uvvkp6ejpubm588cUX9OzZEw8PD4YPH87FixfZtGkTXbp0wcfHh9dff50bN26UKE83Nzc++ugjhg4dioeHB0899RQ7duwwrr+5z507dxIcHIy7uzuHDh3i2rVrvPHGGzz55JMYDAYGDx5MRkaGsc7NK9e9evXCzc2N9PR0k6nja9eu5e233+bgwYO4ubnh5uamK9siIiIiIuawsSn7r4eEBtr3QWJiIjVr1iQhIYEXX3yR2bNnk5mZyZUrVxg2bBg1atQgMTGRBQsWsGXLFubPn1+kfqVKlfjoo4+YPHmysfxvf/sbb7zxBvHx8Rw9epRRo0axYcMG3nnnHRYuXMjatWvZuHFjifN86623eOaZZ0hKSiIwMJBXX32VU6dOmWyzaNEiJk2axKZNm2jUqBHz589n69atLFiwgMTERGrUqMHw4cO5evUqXl5erFmzBoCVK1eSlpaGl5eXSbzu3bszdOhQmjdvTlpaGmlpaXTv3v1uu1hERERERKTM0ED7PmjVqhV/+ctfaNSoEUOHDqVmzZp89dVXJCcn8+uvvxIZGYmrqysdOnRg0qRJrFq1iitXrhjrN2nShLFjx9K4cWMaN25sLB87dixeXl54eHjQu3dvvvrqK+bMmYOrqyudOnWibdu2pKenlzjPHj16EBISQpMmTZg0aRKNGjVi1apVJtuMGTOGtm3b4uLiQoUKFVi9ejWTJk2iQ4cOuLq6EhERwfXr10lOTsbe3p7q1asDUK1aNZycnIpMe3/00UepVKkSFSpUwMnJCScnJ00rFxERERGRB5oG2veBq6uryXKtWrU4c+YMmZmZtGzZ0mRg6e3tTV5eHtnZ2cYyd3f3YuO6ubkZ/65ZsyY1a9bkscceM5bVqFGDM2fOlDjP1q1bF1nOzMw0KfttLjk5OeTl5eHt7W0sc3BwoGXLlkXqiYiIiIjIPWbzALweEhpo3wd2dnZFygoKCkpcv1KlSsWW//ZGZDY2NkX2Y2Njc1f7KQkHBwerxhMRERERESlvNNAuRU2bNjXeUOymb775Bjs7Oxo2bHjf89m3b1+R5aZNm95ye2dnZ+zs7Pjmm2+MZdeuXePQoUM0a9asxPu1s7MjPz//7hMWEREREREpgzTQLkU9e/akYsWKhIWF8f3335OWlkZUVBTPP//8La9i30ubNm0iKSmJrKws5s2bR1ZWFv3797/l9pUrV6Zfv35ERUWRlpbG999/T1hYGPb29jzzzDMl3m/9+vXJzs7m8OHDnD171uSu6yIiIiIiUkK2NmX/9ZDQc7RLUaVKlVi2bBlz5swhJCSEypUr06NHDyZMmFAq+YwaNYqkpCSmT59OnTp1iI6Opl69eretM2HCBAoKChg/fjyXL1/G09OTd999966mmAcFBbF582YGDx7MxYsXiYiIICQkxNLmiIiIiIiIlAoNtO+xlStXFin77XOimzdvXuw2t6vv6+trfFb1TYMGDWLQoEEmZXPmzLmrXOvUqcOKFSuKXVfcPqHwruEzZsxgxowZxdZr0KBBkXohISEmA2l7e3uio6PvKlcREREREZGySgNtERERERGR8sDm4ZmaXdZpoP0Q2LNnD6GhocWuq1evHhs3brzPGYmIiIiIiJRfNgXWfv6TlDnXrl3j9OnTxa6rWLEi9evXv88ZiYiIiIiItTV9YXVpp3BHme/3K+0U7gtd0X4IPProo7i4uJR2GiIiIiIici9p5niZoYG2PNCeTEyzqP7/9elAx+RdZtff2bM9AH6fmJ/HF706AFicR4f1lvVFWu8OBKWYHyMlqLAdL+7cYXaMFR07AeD67k6zYxwJ7Ui3z81vx6dPFbbDGjEcGj5vdoyr2atwmbvZ7PoAP07pyrNbvjC7/roufgAMT9tudoy4Dv4ATPp6q9kxoh4PpHW8+e0A2DfIj/6p5h9XH3XuCMC8/ea/JxM9ugJYnIclnzdQ+JnTw4Lje+N/j++em81/T5K7Fh5bf7KgLz7u3NGizxso/Mx5YYf5Md7vVPiZ1Wer+X2RGFjYF5P3mH+ORPgE4rJgm9n1AX4cH2CV48LS9xTAZb75bflxQgD+G83/PgXY3qM9nTaYH2PHM4X/Nui8yfwYqd3b0/Uzy9qx+en2BH5qfoyt3QrbYY0Yln6nWvJ5A4WfOZa+H1J6PvjgA5YtW0Zubi4tWrRg2rRpeHh4FLvt2rVrmTx5skmZvb09Bw4cMC4XFBQQHR3NmjVruHjxIm3atGHWrFlWvzCp52iLiIiIiIhImbNp0yYiIiIYOXIk69atw83NjeHDh3P27Nlb1qlWrRppaWnGV2pqqsn6d999l5UrV/L666/z8ccf4+DgwPDhw7l+/bpVc9dAW0RERERERMqcf/zjH/Tr148+ffrQrFkzZs2axSOPPMK6detuW8/Jycn4qlmzprG8oKCA999/nxEjRtClSxeaN2/OvHnz+Pe//822bZbNDPo9TR0XEREREREpD2zL/o+0L168yMWLF4uUV6lShSpVqhiXr1+/zsGDB3nllVeMZba2trRr145//vOft4x/6dIl/P39KSgooFWrVowdO5ZmzZoBcPz4cXJzc2nf/n8/B/jDH/5A69at+ec//8nTTz9tjSYW5mq1SPJQCwgIID4+vrTTEBERERGRMuy9994jMDCwyOu9994z2e7cuXPcuHHD5Io0QI0aNcjNzS02duPGjZkzZw5Llixh/vz55Ofn8/zzzxufwHSz3t3ENJeuaD+koqOjWbJkCdOnT2fAgAElrrd27VqioqJIT083KU9ISMDBwcHaaYqIiIiISDny5z//mWeffbZI+W+vZpvLy8sLLy8vk+Xu3buzZs0aXn31VYvj3w0NtB8geXl52NnZWRwnPz+fpKQkhg0bRmJi4l0NtG+levXqFscQERERERELPABTx38/RfxWHnvsMSpUqMB//vMfk/IzZ87g5ORUon3Z2dnRokULfvzxRwBjvf/85z/UqFHDJKa7u3tJm1AimjpupkuXLjFu3Dg8PT3x8/Nj1apVhISEEBMTA8CFCxeYMmUKvr6+eHt7M2zYMDIzM431Y2JiCAkJISEhAX9/fx5//HFmzJhhcre7gIAAli5dyvjx4/Hy8mLu3LkA7Nmzh/79++Ph4UHnzp2ZN2/eXd0l78svv6RChQqMHj2anJwcjhw5YrL+l19+ISoqio4dO2IwGAgKCmLjxo2kp6czefJkzp8/j5ubG25ubsb2/n7q+PHjx3n55Zfx9PTEx8eH8ePHc+HCBeP6sLAwRo8ezdKlS2nbti1t27Zl8eLFd/EOiIiIiIhIeWVvb0+rVq3YvXu3sSw/P58vv/wST0/PEsW4ceMGR44cMQ6wGzRogJOTk0nMS5cusW/fvhLHLCkNtM0UGRnJvn37iI2NJS4ujtTUVLKysozrx4wZw4ULF1i2bBkJCQk0bNiQoUOHcuXKFeM2WVlZ7N69m7i4OBYuXEhycjJr16412U9cXBzu7u6sX7+eoUOHkp2dTWhoKD169CA5OZn58+ezc+dOFixYUOLcExMT6dmzJ/b29gQFBZGQkGCyfubMmaSkpPD666+zadMmpk2bxiOPPIKXlxdTpkwxuWX+0KFDi8TPz89nxIgRXL58mQ8//JC///3vZGRkFHmm3a5duzhz5gwffPABU6ZMITY2li++sOw5iSIiIiIiUj4MGTKE1atXs27dOjIzM3n99de5du2acer5xIkTWbhwoXH7t99+m7S0NHJycjiQYpfqAAAgAElEQVR48CATJkzg1KlT9O3bFwAbGxteeOEF3nnnHbZu3UpGRgYTJ06kTp06BAQEWDV3TR03w6VLl0hKSuLNN9/E19cXgIiICDp16gQUXnE+ePAgaWlp2NvbAzB9+nQ2b97M9u3b6d69uzFWeHg4lSpVolmzZgQEBJCenk7//v2N69u1a8eLL75oXJ46dSrBwcEMHjwYABcXFyZOnMjo0aOZPHkyNja3ny5y4cIFtmzZwieffAJAr169GDVqFBMmTMDOzo6cnBySkpJYuXIljz/+OADOzs7G+n/4wx8AbjtdY/fu3WRmZrJt2zZq164NwJw5c3juuec4duwYjRo1Agqnm0+ZMgUbGxuaNGnCBx98QHp6On5+frdtg4iIiIiIFFVQ9meO35Xu3btz9uxZoqOjyc3NpUWLFsTFxRl/tnrq1Clsbf937fjixYtMnz6d3Nxcqlatiru7O6tXr6ZJkybGbUJDQ7l69SozZszg4sWLeHt78+677xrHbdaigbYZjh8/Tl5eHgaDwVhWo0YN6tevD0BGRgY///yzcRB+07Vr18jJyTEuOzs7U6lSJeOyk5MThw4dMqnz+98KHD58mIyMDJKSkoxl+fn5XLt2jdzcXGrVqnXb3Dds2ICrq6txsOvj44ODgwPbtm0jKCiI77//nooVK+Lt7V2CniheZmYm9evXNw6yAQwGA3Z2dmRmZhr33axZM5P/GHBycuLMmTNm71dERERERMqXQYMGMWjQoGLXrVy50mR5ypQpTJky5bbxbGxs+Otf/8pf//pXq+VYHA2074HLly9Tp04dVqxYUWRd1apVjX9XrGja/TY2NhQUFJiU/XYgDnDlyhUGDhxY7A3MSnJDssTERA4dOkTLli2NZfn5+SQmJhIUFHTH+tb0+xu7Fdd+ERERERGRB40G2mZo0KABdnZ2HDhwwHjV9uzZs5w4cQKAli1b8tNPP2Fvb0/dunWtuu+WLVty9OhRXFxc7rru4cOHOXToEPHx8SZ3+jt58iQjRozg9OnTuLq68uuvv/LNN98Yp47/lp2dHfn5+bfdT9OmTTlx4gSnT5829s+BAwfIy8ujadOmd523iIiIiIiUwANw1/GHhW6GZgZHR0eCg4OJioriq6++Mt7oy87ODhsbG9q1a4fBYGDEiBHs2rWLnJwc9uzZQ1RUlMmdx80xfPhwvv76a8LDwzl8+DBZWVl8/vnnREVF3bFuQkICXl5e+Pj44Orqanz5+/vj7OxMUlISDRo04NlnnyUsLIxt27aRk5PDl19+yZYtWwCoX78+P//8M+np6Zw9e5arV68W2U+7du1o2rQp48eP59ChQ+zdu5epU6cSGBhonDYuIiIiIiJSXmmgbaawsDAMBgOhoaEMHz4cf39/6tWrh729Pba2tsTFxeHp6cmkSZPo1q0bEydO5Ny5c1SrVs2i/bZo0YL333+fo0eP0r9/f/r06cOSJUuoU6fObetdv36d5OTkW04PDwoKMt7xfObMmQQGBjJ9+nS6d+/OG2+8YXx8WJs2bejXrx+jR4+mbdu2xMXFFYlla2vLO++8Q+XKlRkwYAChoaG4ubkRERFhUdtFREREREQeBJo6biZHR0cWLVpkXL548SKRkZHGKd2Ojo7MnDmTmTNnFlt/1KhRjBo1yqRs0qRJJsvbtm0rtq6np2exv/++HXt7e9LT02+5fuzYsYwdOxaARx999LY3Epg1axazZs26ba4NGjRg6dKlt9xfZGRkkbLo6Ohbbi8iIiIiIndwhycQyf2jgbaZvvvuO3788UcMBgPnz58nOjoaR0dHPZpKRERERETkIaeBtpkKCgqIi4vj2LFj2NvbYzAYiI+PL3KX8Ptpz549hIaGFruuXr16bNy48T5nJCIiIiIi8vDRQNtMBoOBdevWlXYaJtzd3U2er/1bv3+UmIiIiIiIlDO663iZYVOgBxeLiIiIiIg88Jq8sra0U7ijH5aElHYK94Uuc8oDrd3aNIvq7w7pgP/GXWbX396jPQBPJpqfx//16QDA4x+bH+PrP3WwKIebefTe8oXZ9dd3Kbw/QbfPzc/j06cK+6LRrBSzYxybGUTgp+a/p1u7Fb6n1ojhMnez2TF+nNIVh4bPm10f4Gr2KlzmF39TxRLlMCEAgEE7dpgdI75TJwCeteDYWtfFj/Hp5rcDYIFvAH237TS7fkJARwAWf2f+e/qae1cAXMItOC6mdaVhtPnvB0D26E70sOA83fjf89Qa5/rQL7abHWO5nz/9U81/TwE+6tyRzpvMP9dTuxee65bk8VHnwmPr1S9TzY7xdtvONP6bZcdF1shOVvncG7Dd/Dw+9LfO50VQimXfhylBHei0wfy+2PFMYV90/cz8GJufbm+Vdljj3ziW5JESVHiuW/qZY8l5CoXn6lsHPze7/l9bPWXR/uXhpMd7iYiIiIiIiFiRrmiLiIiIiIiUB7qMWmborRARERERERGxIg20RURERERERKxIA+0HlK+vL2vXlv27CoqIiIiIyH1iY1P2Xw8JDbTLiOjoaFq0aMGHH35Y2qncUkBAAPHx8aWdhoiIiIiISJmmgbYF8vLyrBInPz+fpKQkhg0bRmJiolVilmXXr18v7RRERERERETumXIz0L506RLjxo3D09MTPz8/Vq1aRUhICDExMQBcuHCBKVOm4Ovri7e3N8OGDSMzM9NYPyYmhpCQEBISEvD39+fxxx9nxowZJoPCgIAAli5dyvjx4/Hy8mLu3LkA7Nmzh/79++Ph4UHnzp2ZN2/eXQ0mv/zySypUqMDo0aPJycnhyJEjJutzc3N56aWX8PDwoGvXrqSkmD5juE+fPixevNikLCcnBzc3Nw4fPmyV9g8ePJgTJ04we/Zs3NzccHNzM6n3W1FRUQwePNi4PHjwYMLDwwkPD8fX15dXX30VgCNHjjBs2DA8PT3p0KEDU6dO5eeffy5xv4mIiIiIyG/Y2pT910Oi3Ay0IyMj2bdvH7GxscTFxZGamkpWVpZx/ZgxY7hw4QLLli0jISGBhg0bMnToUK5cuWLcJisri927dxMXF8fChQtJTk4u8jvouLg43N3dWb9+PUOHDiU7O5vQ0FB69OhBcnIy8+fPZ+fOnSxYsKDEuScmJtKzZ0/s7e0JCgoiISHBZH1YWBg//fQT8fHxLFy4kLi4OC5fvmxc37NnTzZt2mRSZ8OGDfzxj3+kefPmVml/TEwMderUYezYsaSlpZGWllbi9t1sY6VKlfjoo4+YPHkyFy9e5M9//jMeHh6sXbuWpUuXcuzYMcLCwu4qroiIiIiISFlTLgbaly5dIikpibCwMHx9fXFzcyMiIsI4tXvPnj0cPHiQxYsX4+7uTuPGjZk+fTo3btxg+/btJrHCw8Np1qwZHTt2JCAggPT0dJP17dq148UXX6Rhw4Y4OzsTGxtLcHAwgwcPxsXFBR8fHyZOnMjHH39MQUHBHXO/cOECW7ZsoVevXgD06tWLTz75xJj7Dz/8QFpaGnPmzMHDwwMPDw9mzJhhMm29R48eHD9+nP379xvLNm7cSM+ePa3W/mrVqlGhQgUqV66Mk5MTTk5OJXhn/qdJkyaMHTuWxo0b07hxY+Lj4zEYDPz1r3+lSZMmuLu788Ybb7BlyxbOnDlzV7FFRERERETKkoqlnYA1HD9+nLy8PAwGg7GsRo0a1K9fH4CMjAx+/vlnfH19Tepdu3aNnJwc47KzszOVKlUyLjs5OXHo0CGTOu7u7ibLhw8fJiMjg6SkJGNZfn4+165dIzc3l1q1at029w0bNuDq6kqjRo0A8PHxwcHBgW3bthEUFMQPP/yAvb09LVq0MMnBzs7OJM8nn3yS5ORkPDw8OHz4MEePHqVHjx5Wb7+5iuu33bt34+XlVWTb7OxsatSoYZX9ioiIiIg8LAoeort6l3XlYqB9J5cvX6ZOnTqsWLGiyLqqVasa/65Y0bQ7bGxsilyV/u1AFODKlSsMHDiQAQMGFIldvXr1O+aWmJjIoUOHaNmypbEsPz+fxMREgoKC7lj/pmeeeYbFixczefJkkpOT8fLyokGDBoB12/97NsWczMXdJK64fgsMDGTs2LFFtq1du/Zt9ykiIiIiIlKWlYuBdoMGDbCzs+PAgQPGQdrZs2c5ceIEAC1btuSnn37C3t6eunXrWnXfLVu25OjRo7i4uNx13cOHD3Po0CHi4+OpUqWKsfzkyZOMGDGC06dP06RJE65fv86//vUv42D84MGDRQazQUFBzJo1i/T0dDZt2sTw4cNNcrRG++3s7Lhx44ZJWfXq1cnNzTUpy8jIuGOsli1bsnXrVho0aECFChXMzklERERERKSsKRe/0XZ0dCQ4OJioqCi++uorMjIymDx5MnZ2dtjY2NCuXTsMBgMjRoxg165d5OTksGfPHqKiokzuvG2O4cOH8/XXXxMeHs7hw4fJysri888/Jyoq6o51ExIS8PLywsfHB1dXV+PL398fZ2dnkpKSaNKkCe3atWPatGns37+f/fv3M3v2bJOp4zf7wN/fn4iICH766Se6detmXGet9tevX5+vv/6a06dPc/bsWQCeeOIJcnNzWbFiBT/++CNLly4t0XTzgQMH8p///Ifx48dz4MABsrOz2bFjB9OnTy9xPiIiIiIi8hu2D8DrIVFumhoWFobBYCA0NJThw4fj7+9PvXr1sLe3x9bWlri4ODw9PZk0aRLdunVj4sSJnDt3jmrVqlm03xYtWvD+++9z9OhR+vfvT58+fViyZAl16tS5bb3r16+TnJx8y+nhQUFBxjt+R0VFUaNGDQYOHMiYMWMYMmQIlStXLlKnZ8+eZGRk0L59e5Np69Zq/+jRo8nOzqZLly60bdsWgGbNmjFt2jSWLVvGs88+S25ubpHHfRWndu3afPjhh/zyyy8MGTKEnj17Mm/evBJNtxcRERERESnLysXUcSi8orto0SLj8sWLF4mMjDRO6XZ0dGTmzJnMnDmz2PqjRo1i1KhRJmWTJk0yWd62bVuxdT09PYv9/fPt2NvbF7mj+W+NHTvW+PvlWrVq8e6775qsf/rpp4vU6dq16y2nbVuj/Z6ennzyySdF6g4aNIhBgwbdsi0rV64strxp06a88847t6wnIiIiIiLyICo3A+3vvvuOH3/8EYPBwPnz54mOjsbR0RE/P7/STk1EREREREQeIuVmoF1QUEBcXBzHjh3D3t4eg8FAfHx8kbtd30979uwhNDS02HX16tVj48aN9zkjEREREREpt2z1eK+ywqbgTs9vErNdu3aN06dPF7uuYsWKxud8i4iIiIiIWKrxuKI/8yxrshb2Ku0U7otyc0W7LHr00UfNeuyXlNzkPVstqh/hE0i3z9PMrv/pUx0A6PrZLrNjbH66vVVidFhvfjsA0np3wO8T82N80auwLzomm9+OnT0L+6LFsp1mx/jXsI5WeU+tEePZLV+YHWNdFz9c5hd/X4iS+nFCAA4Nnze7/tXsVQD03Wb++5EQ0BEA9xXm98V3L/rx4s4dZtcHWNGxEz03m59DctfCnyGNTzf/PVngGwBAs+fizY5xdM0gGv/Nsr7IGtmpTBzfAAO2m9+WD/0tawcUtsXwvvntOPBCYTuscY4M2mF+X8R36mTR5zcUfoZb47iwxnk2Yneq2THeadeZ3hYcmwDru/hZpS96WBBj41OWvR8387CkL9b/9zy1xrluaX8GpVjWFylBHfjHkRSz6w9xLf7mxSK3o4G2iIiIiIhIeWCjqeNlRbl5vJeIiIiIiIhIWaCBtoiIiIiIiIgVaeq4iIiIiIhIeaC7jpcZuqJdjri5uZGaav4NRCwxePBgoqKiSmXfIiIiIiIiZYkG2mVIdHQ0LVq04MMPPzSrflpaGu3bt7dyVqbS09Nxc3Pj8uXLJuUxMTGMHDnynu5bRERERETkQaCBtoXy8vKsEic/P5+kpCSGDRtGYmKiWTGcnJywt7e3Sj53q1q1ajg6OpbKvkVEREREBLB5AF4PiXI10L506RLjxo3D09MTPz8/Vq1aRUhICDExMQBcuHCBKVOm4Ovri7e3N8OGDSMzM9NYPyYmhpCQEBISEvD39+fxxx9nxowZXL9+3bhNQEAAS5cuZfz48Xh5eTF37lwA9uzZQ//+/fHw8KBz587MmzfPpN6dfPnll1SoUIHRo0eTk5PDkSNHTNaHhYUxevRoli5dStu2bWnbti2LFy822ea3U8ePHz+Om5sbn332mTGvfv36cfLkSf7v//6Pnj174uXlxZgxY7hy5Yoxxvbt2+nfvz8+Pj74+voycuRITp06ZYz5wgsvANCmTRvc3NwICwsDik4dP3/+POPGjcPHxwdPT09efvllTp48eVd9LSIiIiIi8iAqVwPtyMhI9u3bR2xsLHFxcaSmppKVlWVcP2bMGC5cuMCyZctISEigYcOGDB061GSgmZWVxe7du4mLi2PhwoUkJyezdu1ak/3ExcXh7u7O+vXrGTp0KNnZ2YSGhtKjRw+Sk5OZP38+O3fuZMGCBSXOPTExkZ49e2Jvb09QUBAJCQlFttm1axdnzpzhgw8+YMqUKcTGxvLFF1/cNm50dDSjRo0iISGBX375hbFjx7J06VLmzp3LsmXLSE9P57333jNuf/XqVeNV9eXLl3P16lVee+01AOrWrWv8T4stW7aQlpbG1KlTi91vWFgYR44c4e9//zsffvghly9fZuTIkRQUFBi3KUlfi4iIiIiIPGjKzUD70qVLJCUlERYWhq+vL25ubkRERBindu/Zs4eDBw+yePFi3N3dady4MdOnT+fGjRts377dJFZ4eDjNmjWjY8eOBAQEkJ6ebrK+Xbt2vPjiizRs2BBnZ2diY2MJDg5m8ODBuLi44OPjw8SJE/n4449NBpa3cuHCBbZs2UKvXr0A6NWrF5988kmRaenVq1dnypQpNGnShJ49e+Lp6Vkkt98LDQ2lffv2uLq6MnDgQL799lsmTZqEwWCgTZs2dOvWzSRGt27d6Nq1Ky4uLrRq1Yo33niDb7/9ln//+99UqFCBqlWrGnNxcnLiD3/4Q5F9ZmVlkZqaypw5c2jTpg0tW7ZkwYIFHDlyhN27d99VX4uIiIiISMkU2NqU+dfDotw83uv48ePk5eVhMBiMZTVq1KB+/foAZGRk8PPPP+Pr62tS79q1a+Tk5BiXnZ2dqVSpknHZycmJQ4cOmdRxd3c3WT58+DAZGRkkJSUZy/Lz87l27Rq5ubnUqlXrtrlv2LABV1dXGjVqBICPjw8ODg5s27aNoKAg43bNmjXDxuZ/B6eTkxNnzpy5bWw3Nzfj3zVq1DDG+W3Z119/bVw+duwYb731Fvv27ePcuXPG8pMnT1KnTp3b7uumzMxM7OzsTN6L2rVrU79+fTIzM403bCtJX4uIiIiIiDxoys1A+04uX75MnTp1WLFiRZF1N6/SAlSsaNolNjY2Ra5K/3ZwCHDlyhUGDhzIgAEDisSuXr36HXNLTEzk0KFDtGzZ0liWn59PYmKiyUDbzs7ujrn93m/bc3OQ/ts4v4/x8ssv4+zszNy5c3FycuLy5cs899xzVrvp261yKy4XERERERGRB1G5GWg3aNAAOzs7Dhw4QO3atQE4e/YsJ06cAKBly5b89NNP2NvbU7duXavuu2XLlhw9ehQXF5e7rnv48GEOHTpEfHw8VapUMZafPHmSESNGcPr0aWN77rVz586RlZVFREQEXl5eAOzcudNkm5uD9Pz8/FvGadq0KXl5eRw4cAAPDw8ATp8+zYkTJ0yupouIiIiIiJRH5eY32o6OjgQHBxMVFcVXX31FRkYGkydPxs7ODhsbG9q1a4fBYGDEiBHs2rWLnJwc9uzZQ1RUlMmdx80xfPhwvv76a8LDwzl8+DBZWVl8/vnnJnfhvpWEhAS8vLzw8fHB1dXV+PL398fZ2dlkOvq9VrVqVapVq8bq1avJzs5m165dLFy40GSb+vXrY2NjQ2pqKmfPni3yPG2Axo0b07lzZ6ZOncrevXs5dOgQ48ePx9XVlbZt296v5oiIiIiIPFxsbcr+6yFRbgbaUHina4PBQGhoKMOHD8ff35969ephb2+Pra0tcXFxeHp6MmnSJLp168bEiRM5d+4c1apVs2i/LVq04P333+fo0aP079+fPn36sGTJkjv+pvn69eskJyebTA//raCgoPt6F25bW1sWL17M/v376dGjBwsWLGDixIkm29SuXZtRo0Yxb9482rVrx+zZs4uNFRERgaurK6GhoQwYMIDKlSvzt7/9zeQ35iIiIiIiIuVRuZk6DoVXtRctWmRcvnjxIpGRkcYp3Y6OjsycOZOZM2cWW3/UqFGMGjXKpGzSpEkmy9u2bSu2rqenZ7G//74de3v7295le+zYsYwdOxYofHTZ70VHR5ssZ2RkGP9u0KCByTJA586di5SNGDGCESNGGJfbtWvHpk2bbhkXYOTIkYwcOdKkbOXKlSbLjz32WJGr4b9Vkr4WERERERF5EJWrgfZ3333Hjz/+iMFg4Pz580RHR+Po6Iifn19ppyYiIiIiInJvafZomVGuBtoFBQXExcVx7Ngx7O3tMRgMxMfHF7lL+P20Z88eQkNDi11Xr149Nm7ceJ8zEhERERERkXvJpkDPU7qnrl27xunTp4tdV7FiReNzvkVERERERCzRaNqnpZ3CHR0L71baKdwX5eqKdln06KOPmvXYLxERERERkbtSrm51/WDTQFseaK3+sfPOG93GwSEd6bxpl9n1U7u3ByDwU/NjbO1WGKPb52lmx/j0qQ703PyF2fUBkrv6WaUvDO+bn8eBFwrvp/CnVPPf1487dyQoxfy+TAnqAGCVGMPTtpsdI66DP4N27DC7PkB8p0703WZ+XyYEdATAoeHzZse4mr0KgDH/V/yNJEvizScDLDo/oPAc6bTB/ON7xzOFx3fTJeb3Z+Yrhf05YLv57+uH/p14cadlx8WKjp0s/rwBcJm72ewYP07pCmDRMR7fqRN+n1h2XHzRq4NVPvcsbQdA7y3mf3au7+LH0C+2m10fYLmfv1WOC4+V5rdj/+DC7wBLjvEVHTvhm2DZcZHetwNdPzP/uNj8tHW+1y05JqDwuLDGd5kl/75I7lr4nvawoC82WqkvrPFvNZG7of/zEBEREREREbEiXdEWEREREREpD3TX8TJDV7RFRERERERErEgDbREREREREREr0kD7ARETE0NISEhpp1FiD1q+IiIiIiIPPFubsv96SOg32mVAQEAAJ06cAMDW1hYnJycCAwOZOHEiDg4OAAwdOpRBgwaVZpoiIiIiIiJSAhpoWygvLw87OzuL44wdO5aQkBDy8/PJzMxkypQp2NnZMWXKFAAqV65M5cqVLd7P7Vy/fh17e/t7ug8REREREZHyrlxNHb906RLjxo3D09MTPz8/Vq1aRUhICDExMQBcuHCBKVOm4Ovri7e3N8OGDSMzM9NY/+Z054SEBPz9/Xn88ceZMWMG169fN24TEBDA0qVLGT9+PF5eXsydOxeAPXv20L9/fzw8POjcuTPz5s0zqXcnlStXxsnJidq1a9OuXTu6devGoUOHiuR2U35+PtHR0fj5+eHu7k5ISAhfffWVScwtW7bQtWtXPDw8GDZsGKtXr8bNza1IzI8++oiAgAB8fX0B2L59O/3798fHxwdfX19GjhzJqVOnjPXS09Nxc3Njx44d9OzZE4PBwIABAzh27FiRdt2qL5csWULv3r2LbP/UU0+xfPnyEvebiIiIiIj8V2lPC9fUcaNyNdCOjIxk3759xMbGEhcXR2pqKllZWcb1Y8aM4cKFCyxbtoyEhAQaNmzI0KFDuXLlinGbrKwsdu/eTVxcHAsXLiQ5OZm1a9ea7CcuLg53d3fWr1/P0KFDyc7OJjQ0lB49epCcnMz8+fPZuXMnCxYsMKsdJ0+eJC0tDQ8Pj1tus2LFCt5//32mTJnC+vXradOmDX/5y184ffo0ADk5OYwZM4ann36a9evX07NnT6Kjo4vEycrKIjU1lXfeeYePPvoIgKtXrzJs2DASExNZvnw5V69e5bXXXitSd8GCBUyZMoU1a9bwyCOPMGrUKPLz80vUlyEhIXz//ff861//Mm6/Z88eTpw4Qa9evczqNxERERERkbKg3Ay0L126RFJSEmFhYfj6+uLm5kZERAR5eXlA4SDu4MGDLF68GHd3dxo3bsz06dO5ceMG27dvN4kVHh5Os2bN6NixIwEBAaSnp5usb9euHS+++CINGzbE2dmZ2NhYgoODGTx4MC4uLvj4+DBx4kQ+/vhjCgoKSpR/ZGQkXl5exivi1atX569//estt1++fDkvvfQS3bp1o2nTpkydOpX69evz4YcfArB69WqaNWvGuHHjaNy4McHBwXTv3r1InF9//ZWoqCiaN29uvNrdrVs3unbtiouLC61ateKNN97g22+/5d///rdJ3dGjR9O2bVuaN29OVFSUcWBdkr6sXbs2HTp0IDEx0bjtunXr6NixIzVr1ixRn4mIiIiIiJRF5eY32sePHycvLw+DwWAsq1GjBvXr1wcgIyODn3/+2Tg9+qZr166Rk5NjXHZ2dqZSpUrGZScnJ5Mp3ADu7u4my4cPHyYjI4OkpCRjWX5+PteuXSM3N5datWrdMf+XXnqJXr16UVBQwKlTp1i8eDETJkwo9ir0zz//TG5uLm3atDGW2djY4OXlZZwKn5WVZdIXQLFXyBs0aEC1atVMyo4dO8Zbb73Fvn37OHfunLH85MmT1KlTp9h4tWrVol69emRmZtKhQwfgzn3Zp08fZs6cyaRJk/j111/57LPPiIqKun1HiYiIiIiIlHHlZqB9J5cvX6ZOnTqsWLGiyLqqVasa/65Y0bRLbGxsilyV/u3gEeDKlSsMHDiQAQMGFIldvXr1EuX32GOP4eLiAkCjRo1wcHCgX79+HDt2jEaNGpUohjlu3tX8t15++WWcnQ+dEaQAACAASURBVJ2ZO3cuTk5OXL58meeee844O6Ck7tSXAQEBvP7666SmpnL16lXs7e3p1KmTeQ0REREREXnIFdg8PL+BLuvKzUC7QYMG2NnZceDAAWrXrg3A2bNnjY/NatmyJT/99BP29vbUrVvXqvtu2bIlR48eNQ6UrcHWtnBW/y+//FJk3R/+8AecnJzYu3cv3t7eABQUFPDtt9/SpUsXABo3bkxaWppJvQMHDtxxv+fOnSMrK4uIiAi8vLwA2LlzZ7Hb7t+/n65duwKQm5vLyZMnadq0aQlbCHZ2dvTu3Zu1a9dy7do1evXqZZU7uIuIiIiIiJSmcjPQdnR0JDg4mKioKKpUqULVqlVZtGgRdnZ22NjY0K5dOwwGAyNGjGD8+PE0bNiQ06dPs3XrVvr27XtXA8TfGz58OP369SM8PJy+ffvyyCOP8P333/Ptt98yadKkEsW4fPkyubm5FBQU8O9//5v58+fj4uJyy7yGDh3KO++8g7OzM66urnz44YecOHHCeFW9X79+rFixgsWLFxMcHMz+/fvZtGnTHfOoWrUq1apVY/Xq1dSoUYOcnBwWLlxY7LYxMTHGvr6Zb7t27UrU3pv69u1L7969yc/PZ/LkyXdVV0REREREpCwqNwNtgLCwMGbMmEFoaChVqlRhxIgRHD9+HHt7e2xtbY13v540aRLnz5+nVq1aPPHEE0V+o3y3WrRowfvvv8+bb75J//79sbW1xcXFheDg4BLHWLRoEYsWLcLGxoYaNWrg7e1NeHh4kenXN7344otcunSJ8PBwzp8/j6urK3//+9+NV/OdnZ158803iYqKYvny5TzxxBOEhobectB8k62tLYsXL+b/2bvzqCiu9G/gX4i0Cx1AERdWDTgEQiMoiiI7uCAuiBgYl1G2iWIwRA2gURmVCLiggqOi7RI1MTEoGMRdIQZNiIzGdSTqgOISQsImW0Tl/YOf9dqCit0dQfl+zulzqOU+dau6upqn761b0dHR8PT0hImJCcLDwxEQENBg3ZkzZ2LRokW4ceMGJBIJEhMThZb4pjIxMYG5uTkePnwo8+gxIiIiIiJ6SW/MUNevvzcq0RaLxYiPjxemy8vLERsbK3TpFovFiIqKQlRUVKPlQ0NDERoaKjPv6Rbp48ePN1rWysqq0fu/m+JZMZ9XN1VVVcyYMQMzZsx4Zhl3d3ehKzkArFixQqZ7e2P7C9SPqv5063dubm6D9fr164f09PQm1RdoeCyB+kHj/vjjDwQGBj5zP4iIiIiIiF4nb1SiffHiRaF1tbS0FAkJCRCLxXBwcGjuqjWLHTt2oHfv3tDU1ER2djZ27NiBDz/8sLmrJSguLsa3336L8vJyjB49urmrQ0REREREpBRvVKJdV1cHqVSK/Px8iEQiSCQS7Nixo8Eo4a9STk4OgoODG12mq6v7zBZhZcjPz8f69etRVlYGPT09fPjhh/D39//LtveyBg4cCG1tbURHR0MsFjd3dYiIiIiIXm8cdbzFUKl7+tlVpFQ1NTUoLCxsdFmbNm2E53wTEREREREpwijmaHNX4YVuzHF/8UpvgDeqRbslateunVIf+0WyNuUeUqh8oOlQ+Bxv/PFlTZHs6ggASokx8sj3csdIG+wAz8NZL17xOdKH2MNl/0m5y2cMHwQAmP8f+S/wi/vWX3g9FNiXA0PsMfig/PtxZFj9figjRsTpY3LHiOvnhjFH5T8nACDF3QEWW+WPcXFK/W03YT++eByJZ1k1wBUA0N7w73LHqL65ExO/+07u8gCww8kJfhnyf06/cqn/nK64cETuGLMk9Y9DNF4nfz2uT3OEc7r85yYAZHoOUuh6kT7EHgAw44cMuWMkDHQBAMzOlv/cWm7rqtA1C6i/bjmmyR/jxEjlXffe2yL/eXHJ3xEB32fKXR4ANjs4Y+gh+c+LQ0PrzwtlxNh744DcMUYbeWDqSfnPTQBYP8gF7ytwvdj1f9cLRa7hKe4OCn0XAvXfh8p4P5RxvVD0eA5KUexYnBxjj6CsTLnLS+2dFdo+tU5MtImIiIiIiN4Equw63lJwAHgiIiIiIiIiJWKiTURERERERKRE7DpORERERET0JmDX8RaDLdr0SmRkZMDU1LS5q0FERERERPSXY4v2a+z8+fNYv349zpw5g6qqKujp6cHe3h6BgYHo1q1bc1ePiIiIiIioVWKLdjOora1VOMaRI0cwfvx4aGpqYvXq1di/fz8WLVqEqqoqbNmyRQm1JCIiIiIiInm0+kS7oqICs2bNgpWVFRwcHLBz5054e3sjMTERAFBWVoa5c+fC1tYWffv2RWBgIK5fvy6UT0xMhLe3N5KTk+Hs7Ix+/fphwYIFuH//vrCOq6sr1q9fj9mzZ8Pa2hpLliwBAOTk5MDPzw+WlpZwcXHB0qVLZco9S2VlJebNmwc/Pz/ExMTA1tYW+vr66NevHz777DNMnz5dWHfHjh1wc3ODhYUFhg8fjkOH/v9zp2/dugVTU1McPHhQqIevry/u3LmDH3/8ESNHjoS1tTXCwsJQVVUllHv06BHWr18PV1dX9O7dG2PGjEFmZqZMHTMyMjBkyBBYWloiICAAhYWFwrK7d+/CzMwM//3vf2XKrF27FiNHjnzh/hMRERERUSNUXoNXK9HqE+3Y2FicO3cOSUlJkEqlyMjIQF5enrA8LCwMZWVl2LRpE5KTk2FoaIiAgACZxDMvLw+nTp2CVCrFihUrkJaWhj179shsRyqVwsLCAnv37kVAQABu3ryJ4OBgeHp6Ii0tDcuWLcOJEyewfPnyF9b55MmTKC0tRXBwcKPLNTQ0AACHDh1CbGws/vnPfyItLQ2jRo1CWFgYLl26JLN+QkICQkNDkZycjD///BMzZ87E+vXrsWTJEmzatAnZ2dn4/PPPhfWTkpKQlpaGxYsXY9++ffDz88OHH36Iy5cvAwBu376N0NBQuLu7IzU1FZ6enli1apVQvnv37rCzs2twjFJTU+Ht7f3C/SciIiIiImrJWnWiXVFRgdTUVERGRsLW1hampqaIiYkRunbn5OTg0qVLWLlyJSwsLNCzZ0/Mnz8fDx8+bNCCGx0dDRMTEzg6OsLV1RXZ2dkyy+3s7DBlyhQYGhrCwMAASUlJ8PLywqRJk2BkZAQbGxuEh4dj165dqKure2698/PzIRaL0bVr1+eut2XLFvj4+MDX1xc9e/bE1KlTYW9vj82bN8usFxwcjEGDBuFvf/sbJkyYgLNnzyIiIgISiQR9+vSBh4eHsD/3799HUlISYmJiMGjQIBgYGMDX1xeDBw/Grl27AABfffUV3nnnHYSHh+Odd97B2LFjMXz4cJlt+vj4IC0tTeZY3759G6NGjXruPhEREREREbV0rXowtFu3bqG2thYSiUSYp62tDT09PQBAbm4u7t27B1tbW5lyNTU1KCgoEKYNDAzQoUMHYVpHR0do3X3MwsJCZvrKlSvIzc1FamqqMO/Ro0eoqalBUVERunTpovD+Xb9+HePHj5eZ16dPHxw+fFhm3pOjgWtrawMATExMZOadPn0aAHDjxg1UV1dj8uTJMjFqa2uF4/S///0PvXv3llluZWWFL774Qph2c3PDv/71L2RmZmLw4MFISUmBk5OTsH0iIiIiIno5dXy8V4vRqhPtF6msrES3bt2wdevWBss0NTWFv9u0kT2MKioqDVqln0zEAaCqqgoTJkxokAgDQKdOnZ5brx49eqCiogKFhYUvbNVuiifrr6JS/+FUU1OTmfd4fx53md+4cSN0dHRk4rRr167J2xSJRBg1ahR2794Ne3t7HDx4EHFxcXLvAxERERERUUvRqhNtfX19qKmp4cKFC0LCWlxcjNu3bwMAzM3N8dtvv0EkEqF79+5K3ba5uTmuXbsGIyOjly47aNAgaGpqYuPGjZg3b16D5eXl5dDQ0ICxsTHOnDkj0x37zJkzMDY2lrvexsbGUFNTw6+//gobG5tG13nnnXdw4sQJmXnnzp1rsJ6Pjw+8vb2xc+dOtG3bFs7OznLXi4iIiIiIqKVo1Ym2WCyGl5cX4uLioKGhAU1NTcTHx0NNTQ0qKiqws7ODRCJBSEgIZs+eDUNDQxQWFuLYsWPw8fFRKGENCgqCr68voqOj4ePjg7Zt2+Lq1avC/dHPo66ujkWLFmHWrFmorKzEmDFjoKenh19//RV79+5Fhw4dEBkZCX9/f8yaNQtmZmawtbXFoUOHkJWVheTkZLnrLRaLMWXKFHz22Wd48OAB+vTpg/LycuTk5KBr167w8PCAr68vtmzZguXLl2Ps2LH4+eefsX///gaxTE1NYWZmhvj4eEycOLFBzwAiIiIiInoJKuw63lK0+swmMjISCxYsQHBwMDQ0NBASEoJbt25BJBJBVVVVGEk8IiICpaWl6NKlC/r37w8tLS2FtmtmZoZt27Zh1apV8PPzg6qqKoyMjODl5dWk8sOGDUPXrl2xYcMGhIaGorq6Grq6unBycoK/vz8AYOjQoSgqKkJSUhIWL14MQ0NDrFq1Cu+9955CdZ81axa0tbWxbt063L59GxoaGpBIJMJjxfT19bFq1SrExcXh888/R9++fTFjxgz861//ahDL29sbCxcu5GjjRERERET0xmj1ibZYLEZ8fLwwXV5ejtjYWKFLt1gsRlRUFKKiohotHxoaitDQUJl5T7dIHz9+vNGyVlZWjd7/3VTW1tZYt27dc9eZOHEiJk6c2OgyfX195ObmysxzcXFpMC8kJAQhISHCtIqKCvz9/YWEvjHu7u5wd3eXmff3v/+9wXpFRUWQSCT429/+9tz9ICIiIiIiel20+kT74sWLuHHjBiQSCUpLS5GQkACxWAwHB4fmrtobrbKyEgUFBdi5cyciIyObuzpERERERK8/jjreYrT6RLuurg5SqRT5+fkQiUSQSCTYsWNHg1HCX6WcnBwEBwc3ukxXVxfp6emvuEbKt3jxYqSnp2PYsGF8djYREREREb1RVOqefg4VNbuamhoUFhY2uqxNmzbCc76JiIiIiIgeM1z9XXNX4YVufuTU3FV4JVp9i3ZL1K5dO7ke+0VERERERK0Ye463GEy06bXmsv+kQuUzhg+Cc7r8MTI9BwEA3A7IH+OYR32M0Ue/lzvGXncHeB7Okrs8AKQPscfII/LXIW1w/bgGyjieE7+T/9fYHU5OCh2L9CH2AKCUGL13yH88z010wOzsxgdSbKrltq6YckL+Y7nVsf4XZw8FjsWB/zsWir6n7Q0bDqb4Mqpv7sTYY/K/H7vd6s9vxzT5z+8TI+vP7w9/yJA7xpqBLgj7UbHzYtUAV6V8Tt/POCF3jF0ujgCAf2Zlyh1jg72zQnV4XA+f4/LHSHat34/+38j/GflpXP1nZOpJ+c+L9YNcFDqvgPpzSxnXPUU/6wDQI+qg3DHyFw5TqA6P6zH0kPzH4tDQ+mPREr7XlfGeDj4o//XiyLD664Wi/18o41iYb5b/s345wFGh7VPrpNrcFSAiIiIiIiJ6k7BFm4iIiIiI6A2g+gY2o37xxRfYtGkTioqKYGZmhnnz5sHS0rLRdXft2oXU1FRcvXoVKioqsLCwwMcffwyJRCKsExkZiZSUFJly9vb22LRpk1LrzUSbiIiIiIiIWpz9+/cjJiYGCxcuRO/evfH5558jKCgIBw8eRKdOnRqsn52dDU9PT/Tp0wcikQhSqRQBAQFIT09Hly5dhPVcXFywePFiYVokEim97m/gbx70V5s0aRLi4uKauxpERERERPQG27JlC3x9fTF27FiYmJhg4cKFaNu2bYMW6cdWrFiBCRMmwMzMDMbGxoiOjsbDhw+RnZ0ts55IJIKOjo7w0tTUVHrd2aLdip0/fx7r16/HmTNnUFVVBT09Pdjb2yMwMBDdunV7ZrnExES0acNTh4iIiIiIXk55eTnKy8sbzNfQ0ICGhoYwff/+fVy6dAnTpk0T5qmqqsLOzg4///xzk7ZVXV2NBw8eNEikf/jhBwwcOBAaGhqws7PDRx99BC0tLTn3qHHMll5DtbW1UFNTUyjGkSNH8PHHH2PkyJFYvXo19PT0cPfuXaSmpmLLli2YM2dOgzL379+HSCRS+klIRERERESKU3kNHu/1+eefY82aNQ3mf/jhhwgNDRWmS0pK8PDhQ3Tu3FlmPW1tbdy4caNJ21qxYgW6d++OAQMGCPMcHBwwePBg6Ovro6CgAPHx8fjggw+wc+dOqCrxJncm2gqqqKhAVFQUjh07hrfffhshISH45ptv4OLigtDQUJSVlSEuLg7Hjh3DgwcPYGVlhblz58LY2BhAfetwRkYGxo8fjzVr1qCyshIeHh6YN2+ecK+Aq6sr3n//fVy7dg3Hjh2Dl5cXoqKikJOTg+XLl+Py5cvQ1taGh4cHwsLCXniPQWVlJebNmwc/Pz/MmzdPmK+vr49+/foJvzA9rtv777+PDRs2oKSkBGfPnsWkSZNgYWGBiIgIoX6+vr745ZdfcOzYMWhra2PRokXo2bMnPv30U5w9exa9evXCsmXL0KNHD2F7R48eRWJiIv73v/+hW7dueP/99xEYGKjUE5yIiIiIiFqOyZMnY8yYMQ3mP9marQwbN27E/v37sX37dpn8yNPTU/jb1NQUpqamcHd3R05ODvr376+07TOjUVBsbCzOnTuHpKQkSKVSZGRkIC8vT1geFhaGsrIybNq0CcnJyTA0NERAQACqqqqEdfLy8nDq1ClIpVKsWLECaWlp2LNnj8x2pFIpLCwssHfvXgQEBODmzZsIDg6Gp6cn0tLSsGzZMpw4cQLLly9/YZ1PnjyJ0tJSBAcHN7r8yZM8Ly8PGRkZWLt2Lb766qtnxty8eTMGDBiA1NRU9OvXD5988gnmz5+PyZMnY/fu3WjTpg0WLlworJ+Tk4PIyEj4+/tj//79mDdvHrZv347t27e/sP5ERERERPR60tDQgL6+foPX04l2x44d8dZbb+H333+Xmf/HH39AR0fnudvYtGmTkJ/97W9/e+66BgYG6NixY5NbyZuKibYCKioqkJqaisjISNja2sLU1BQxMTGora0FUJ9MXrp0CStXroSFhQV69uyJ+fPn4+HDh8jMzJSJFR0dDRMTEzg6OsLV1bXBDft2dnaYMmUKDA0NYWBggKSkJHh5eWHSpEkwMjKCjY0NwsPDsWvXLtTV1T233vn5+RCLxejatesL9/HBgweIi4vDu+++C1NT02eu5+rqinHjxqFHjx6YNm0a/vjjDzg4OMDZ2RnGxsaYPHkyTp8+jUePHgEA1qxZg6lTp8LLywsGBgZwcnLCtGnT8PXXX7+wTkRERERE1JCKSst/NZVIJMJ7772HU6dOCfMePXqEH374AVZWVs8st3HjRqxduxZSqVTmsV7P8uuvv6K0tFRmVHJlYNdxBdy6dQu1tbUyb6C2tjb09PQAALm5ubh37x5sbW1lytXU1KCgoECYNjAwQIcOHYRpHR0dXL58WaaMhYWFzPSVK1eQm5uL1NRUYd6jR49QU1ODoqIipZ0o+vr6Tbon+8kkXFtbGwDQq1cvYV7nzp1RW1uL8vJyaGlp4cqVKzhz5gz+/e9/C+s8fPhQSMSJiIiIiKh18/f3R0REBN577z1YWlri888/R01NjdD1PDw8HF27dsWsWbMAABs2bEBCQgJWrFgBPT09FBUVAQA6dOgAdXV1VFZWYs2aNRg6dCg6d+6MgoICLFu2DD179sTAgQOVWncm2n+hyspKdOvWDVu3bm2w7MmR754ewVtFRaVBq/STiTgAVFVVYcKECRg/fnyD2I09U+5JPXr0QEVFBQoLC1/Yqt2+ffvnLn/syX1Q+b+fqhobmfxxIl1VVYWwsDC4ubk1KT4REREREbUuw4cPR3FxMRISElBUVAQzMzNIpVIh37l7967M+E5fffUVamtrMWPGDJk4jwdae+utt/DLL78gNTUV9+7dQ5cuXWBvb4+PPvpI6c/SZqKtAH19faipqeHChQtCwlpcXIzbt28DAMzNzfHbb79BJBKhe/fuSt22ubk5rl27BiMjo5cuO2jQIGhqamLjxo0yg6E9Vl5ervTBCJ5mbm6O/Px8uepPREREREQNqbxM3+zXxMSJEzFx4sRGlz09vtPx48efG6tdu3bYtGmT0ur2PEy0FSAWi+Hl5YW4uDhoaGhAU1MT8fHxUFNTg4qKCuzs7CCRSBASEoLZs2fD0NAQhYWFOHbsGHx8fISRx+URFBQEX19fREdHw8fHB23btsXVq1dx9uxZYTTwZ1FXV8eiRYswa9YsVFZWYsyYMdDT08Ovv/6KvXv3okOHDoiMjJS7bk0xbdo0hISEoGvXrhg6dCgA4PLly7h9+7bMs/KIiIiIiIheN0y0FRQZGYkFCxYgODgYGhoaCAkJwa1btyASiaCqqiqMJB4RESHcZN+/f3+Fn0VtZmaGbdu2YdWqVfDz84OqqiqMjIzg5eXVpPLDhg1D165dsWHDBoSGhqK6uhq6urpwcnKCv7+/QnVrCicnJ6xduxZr165FUlISRCIRTExMGu0KT0RERERE9Dphoq0gsViM+Ph4Ybq8vByxsbFCl2ixWIyoqChERUU1Wj40NFTmwewAGrRIP6sLhJWVVaP3fzeVtbU11q1b98zljdUNeHEXDXV1deTm5srMs7GxaTDPyckJTk5OL1ttIiIiIiJqxBvYc/y1xURbQRcvXsSNGzcgkUhQWlqKhIQEiMViODg4NHfViIiIiIiIqBkw0VZQXV0dpFIp8vPzIRKJIJFIsGPHjgajhL9KOTk5CA4ObnSZrq4u0tPTX3GNiIiIiIiIWg+VuqefI0WvvZqaGhQWFja6rE2bNsJzvomIiIiI6M3RK+lEc1fhha5+4NjcVXgl2KL9BmrXrh0fm0VERERERNRMmGjTa+0f332nUPltTk7wOS7/L3/JrvW/yI099r3cMXa7OSglxsgj8pcHgLTBDnBMOyl3+RMjBwEABqVkyR3j5Bh7AMD4TPnf1y+dnTD0kPx1ODS0vg7KiOGXIf+59ZWLo0LnJlB/fipyXqQNrj83nfbJf158N6L+vFD0WCjy+QDqPyPtDf8ud/nqmzsBAAHfZ8odY7ODMwAofM1RxnnhcVj+8/vAkPrz2+Fb+WN8P6o+hqLXPUWuN0D9NUcZnxFlfAcoet1TxnkxYLf8x/PHsfXvqXO6/NeLTM/668VEBb7bdzg5we2A/HUAgGMeg5RyXij6ORt9VLHr3l53B6V81scoUI8U9/pjoeh3qiL7AdTvS8ipDLnLr7VzUWj71DqpNncFiIiIiIiIiN4kbNEmIiIiIiJ6A6iwGbXF4FtBREREREREpERMtImIiIiIiIiUiF3HiYiIiIiI3gAqKs1dA3qMLdpN5OrqClNTU5iamqJ3795wc3PDJ598gvPnzzd31V6ZPXv2wNbWtrmrQURERERE1KK1ikS7trZWKXFmzpyJrKwsHDhwADExMRCJRPDz88OePXuUEr+1ePDgAerq6pq7GkRERERERH+JV55oV1RUYNasWbCysoKDgwN27twJb29vJCYmAgDKysowd+5c2Nraom/fvggMDMT169eF8omJifD29kZycjKcnZ3Rr18/LFiwAPfv3xfWcXV1xfr16zF79mxYW1tjyZIlAICcnBz4+fnB0tISLi4uWLp0qUy5F1FXV4eOjg50dXXRv39/fPbZZwgODsbixYtRWloqrHfgwAEMHz4cFhYWcHNzw5dffikTp7S0FJ9++ikGDhwIS0tLjBo1Cj/88AMAIDIyEjNmzJBZf8aMGYiMjJTZv6SkJOE4urm54eTJk7hz5w78/f1hZWWFcePGIT8/XybO0aNHMXr0aEgkEgwePBgbN27Eo0ePhOWmpqb45ptv8MEHH6B3794YMWIEcnJyAADZ2dmYM2cOSktLhZb9x+9ZSkoKvL29YW1tDXt7e0RGRqKsrEyI+7gl/OjRoxg2bBgkEglOnz4NCwsLFBcXy9Tx008/xdSpU5v8nhARERERUT1VlZb/ai1eeaIdGxuLc+fOISkpCVKpFBkZGcjLyxOWh4WFoaysDJs2bUJycjIMDQ0REBCAqqoqYZ28vDycOnUKUqkUK1asQFpaWoNWZalUCgsLC+zduxcBAQG4efMmgoOD4enpibS0NCxbtgwnTpzA8uXLFdqfKVOmoLq6GqdOnQIAnD9/HjNnzsSoUaOQlpaGf/7zn1iyZAmOHj0qlAkNDcWlS5cQHx+Pffv2YcaMGVB5yRsqNm/ejAEDBiA1NRX9+vXDJ598gvnz52Py5MnYvXs32rRpg4ULFwrr5+TkIDIyEv7+/ti/fz/mzZuH7du3Y/v27TJx165dizFjxmDv3r0wNTXF7NmzUVtbC2tra8ydOxdaWlrIyspCVlYWAgICANS3UIeFheHbb7/F6tWr8csvv2DRokUycSsrK7F582bExcVh3759sLKygr6+Pr799lthnerqahw8eBDe3t4vdSyIiIiIiIhakleaaFdUVCA1NRWRkZGwtbWFqakpYmJihK7dOTk5uHTpElauXAkLCwv07NkT8+fPx8OHD5GZmSkTKzo6GiYmJnB0dISrqyuys7NlltvZ2WHKlCkwNDSEgYEBkpKS4OXlhUmTJsHIyAg2NjYIDw/Hrl27FOrG3LFjR2hra+P27dsAgM8//xz29vaYOnUqevbsCV9fX/j4+EAqlQIAfvrpJ/znP/9BYmIiBg4cCENDQ7i7u2PAgAEvtV1XV1eMGzcOPXr0wLRp0/DHH3/AwcEBzs7OMDY2xuTJk3H69GmhxXrNmjWYOnUqvLy8YGBgACcnJ0ybNg1ff/21TNyxY8di2LBh6NGjBz788EPcvXsXN2/ehEgkwttvvw0A0NHRgY6ODtTV1QEA48aNg6OjIwwMDNC3b19ERETg0KFDMq3ltbW1WLhwIXr37g1jY2OIRCL4+PggJSVFWOfw4cNQU1ODi4vLS74LXkiE1wAAIABJREFURERERERELccrHXX81q1bqK2thUQiEeZpa2tDT08PAJCbm4t79+41GHCrpqYGBQUFwrSBgQE6dOggTOvo6ODy5csyZSwsLGSmr1y5gtzcXKSmpgrzHj16hJqaGhQVFaFLly5y79eTifr169cxdOhQmeV9+vTB/v37AdTvo66uLgwMDOTeHlDfzfsxbW1tAECvXr2EeZ07d0ZtbS3Ky8uhpaWFK1eu4MyZM/j3v/8trPPw4UOZZPjpuDo6OgCA4uJiGBsbP7MuFy5cwJo1a5Cbm4uysjI8evQItbW1KCoqQteuXQEA7dq1k6kfAHh5eWHlypW4fPkyzM3NkZKSgpEjR0JNTe1lDwcRERERUavHUcdbjhb1eK/Kykp069YNW7dubbBMU1NT+LtNG9lqq6ioNGiVfjIRB4CqqipMmDAB48ePbxC7U6dOcte5pKQExcXF0NfXlzvGkxrbl8YGc3vyGDzudv70cQEgJNJVVVUICwuDm5vbc7ffWNynk/EnVVVVISgoCE5OTli+fDk6deqE69ev48MPP5Spd7t27RqU7dy5M5ycnLBnzx507NgR2dnZMveiExERERERvY5eaaKtr68PNTU1XLhwQWjpLC4uFrpdm5ub47fffoNIJEL37t2Vum1zc3Ncu3YNRkZGSo27detWtG/fHnZ2dgAAY2NjnDlzRmadM2fOCC3CpqamuHPnDgoKChpt1e7UqZPMPeuPHj3C1atXYWNjo1A9zc3NkZ+fr9D+q6mpNUi6//e//6G0tBSzZ88WegU83Y3/eXx8fDBnzhy8/fbbePfdd/Huu+/KXT8iIiIiIqKW4JXeoy0Wi+Hl5YW4uDj89NNPyM3NxZw5c6CmpgYVFRXY2dlBIpEgJCQEJ0+eREFBAXJychAXFycz8rg8goKCcPr0aURHR+PKlSvIy8vD4cOHERcX1+QYlZWVKCoqwp07d/DTTz/h008/xcaNGzF//nyhxX3y5MnIyspCUlIS8vPz8fXXXyM5ORmBgYEAgP79+6Nv374IDQ3FDz/8gIKCAhw/flxITvv3749z584hPT0deXl5WLJkCUpKShTadwCYNm0adu/ejX//+9+4du0arl27hm+//Rbr1q1rcgw9PT3cu3cP2dnZKC4uRnV1NXR1daGmpoYdO3agoKAAhw4dwqZNm5oc08nJCWpqati4cSMHQSMiIiIiUoCKSst/tRavfNTxyMhISCQSBAcHIygoCM7OztDV1YVIJIKqqiqkUimsrKwQEREBDw8PhIeHo6SkBFpaWgpt18zMDNu2bcO1a9fg5+eHsWPHYt26dejWrVuTY8THx8Pe3h5Dhw5FZGQk/vzzT3z11VcyCaKlpSXi4+Oxd+9ejBgxAhs2bMCcOXPg7u4urJOQkIB3330XYWFhGDFiBBISEoRlTk5OCA4ORnR0NPz8/NCxY0cMGjRIoX1/HHft2rU4ceIEvL294efnhy+//FK4P74p+vTpA19fX8yYMQMDBw6EVCpFp06dEBsbi3379mH48OHYtm0bPvnkkybHfOuttzB69GgAwIgRI156v4iIiIiIiFqaV36PtlgsRnx8vDBdXl6O2NhYoUuzWCxGVFQUoqKiGi0fGhqK0NBQmXkREREy08ePH2+0rJWVVaP3fzfFs2I2xsPDAx4eHs9c3rFjR8TGxj5z+cyZMzFz5swm10VdXR25ubky82xsbBrMc3JygpOT0zPjPr1+Y3EXLlwo89gwoD5BfjpJfrKct7f3c1uri4qK4Obmho4dOz5zHSIiIiIiotfFK0+0L168iBs3bkAikaC0tBQJCQkQi8VwcHB41VWhZnbv3j1cuXIFBw4cwJYtW5q7OkRERERERErxyhPturo6SKVS5OfnQyQSQSKRYMeOHQ1GCX+VcnJyEBwc3OgyXV1dpKenv+IatQ4hISG4cOECJk+erPBgb0RERERErZ1Ka7oJuoVTqXv6WVKtUE1NDQoLCxtd1qZNm5e6j5mIiIiIiKg5WGz9vrmr8EIXp7SOnswt6jnazaVdu3ZKf+wXvRqGKzMVKn/zY2cMPnhS7vJHhtUPVKeMGGOOyn9hTHF3wMgjil1Y0wY7KGU/jOKOyR3jRkT9c94/zZE/xmc2bhh7TP5jsdut/uKvjBhLzx+RO0a45WCsvCh/eQD42GIwZmc3fXyJpy23dQUAGK87IXeM69McAQArLsi/L7Mkg+GYJv+5CQAnRg5CwPeZcpff7OAMAGhv+He5Y1Tf3AlA8fN7/n+Oyl0eABb3dYfbAfmP5zGP+s+6Iv/MPf4na+FZ+fclytodDt9myV0eAL4fZQ/Pw/LHSB9iDwBKiWG5Xf7jeX6Sg0LHEqg/nqMV+B7a617/ng5Kkf9YnBxTfywUrYdkm2Lfhxf+4QCX/fJ/RjKG139Ghh6S/1gcGmqv0HcyUP+9rIzPujLO7wG75Y/x41h7+GXI/z0EAF+5OCr8GSN6WUy0iYiIiIiI3gAqr/yZUvQsfCuIiIiIiIiIlIiJNhEREREREZESses4ERERERHRG4CDjrccbNEmIiIiIiIiUiK2aL/hXF1dcfv2bQD1o6t37twZffr0waRJk2BpadnMtSMiIiIiInrzsEW7BautrVVKnJkzZyIrKwsHDhxATEwMRCIR/Pz8sGfPnmeWefDgAfiIdSIiIiKi14eKSst/tRZMtJuooqICs2bNgpWVFRwcHLBz5054e3sjMTERAFBWVoa5c+fC1tYWffv2RWBgIK5fvy6UT0xMhLe3N5KTk+Hs7Ix+/fphwYIFuH//vrCOq6sr1q9fj9mzZ8Pa2hpLliwBAOTk5MDPzw+WlpZwcXHB0qVLZcq9iLq6OnR0dKCrq4v+/fvjs88+Q3BwMBYvXozS0lIAwJ49e2Bra4ujR49i2LBhkEgkKCkpwblz5zBlyhTY2trCxsYGU6ZMwdWrV4XYt27dgqmpKQ4ePCjU0dfXF3fu3MGPP/6IkSNHwtraGmFhYaiqqhLKZWZmws/PDzY2NrC1tcX06dNx9+5d+d4cIiIiIiKiFoSJdhPFxsbi3LlzSEpKglQqRUZGBvLy8oTlYWFhKCsrw6ZNm5CcnAxDQ0MEBATIJJd5eXk4deoUpFIpVqxYgbS0tAatylKpFBYWFti7dy8CAgJw8+ZNBAcHw9PTE2lpaVi2bBlOnDiB5cuXK7Q/U6ZMQXV1NU6dOiXMq6ysxObNmxEXF4d9+/ZBLBajsrIS3t7e2LlzJ7788kt07twZU6dObZDoJyQkIDQ0FMnJyfjzzz8xc+ZMrF+/HkuWLMGmTZuQnZ2Nzz//XFi/uroagYGB2L17NzZv3ozq6mp8/PHHCu0TERERERFRS8B7tJugoqICqampWLVqFWxtbQEAMTExcHJyAlDf4nzp0iVkZWVBJBIBAObPn48jR44gMzMTw4cPF2JFR0ejQ4cOMDExgaurK7Kzs+Hn5ycst7Ozw5QpU4TpTz/9FF5eXpg0aRIAwMjICOHh4ZgxYwbmzJkDFTn7X3Ts2BHa2trC/dtAfVf1hQsXolevXjL1edKSJUvQp08fnD9/HjY2NsL84OBgDBo0CAAwYcIEzJs3D6mpqTAzMwMAeHh4IDs7G9OmTROmn7Ro0SK4ubnh119/Rbdu3eTaJyIiIiKi1qw1dc1u6ZhoN8GtW7dQW1sLiUQizNPW1oaenh4AIDc3F/fu3ROS8MdqampQUFAgTBsYGKBDhw7CtI6ODi5fvixTxsLCQmb6ypUryM3NRWpqqjDv0aNHqKmpQVFREbp06SL3fj19D3a7du1kkmwA+P3337Fy5UqcPn0av//+O+rq6lBbW9ugm7epqanwt7a2NgDAxMREZt7p06eF6fz8fKxevRrnzp1DSUmJMP/OnTtMtImIiIiI6LXGRFsJKisr0a1bN2zdurXBMk1NTeHvNm1kD7eKikqDZPfJRBwAqqqqMGHCBIwfP75B7E6dOsld55KSEhQXF0NfX1+Y165duwbrRUREoLy8HPPmzYOuri7U1NQwevToBgO1Pblvj1vZ1dTUZOY9ua9Tp06FgYEBlixZAh0dHVRWVmLcuHFKGwCOiIiIiIiouTDRbgJ9fX2oqanhwoUL6Nq1KwCguLhY6HZtbm6O3377DSKRCN27d1fqts3NzXHt2jUYGRkpNe7WrVvRvn37Bl3Dn3bmzBksXrwYjo6OAIDr16+jurpaoW2XlJQgLy8PMTExsLa2BgCcOHFCoZhERERERK2dKruOtxhMtJtALBbDy8sLcXFx0NDQgKamJuLj46GmpgYVFRXY2dlBIpEgJCQEs2fPhqGhIQoLC3Hs2DH4+PjA2NhY7m0HBQXB19cX0dHR8PHxQdu2bXH16lWcPXsWERERTYpRWVmJoqIi1NbW4tatW9i7dy9SUlIQHR0t0+LemB49egj3WpeVlWHp0qUyLdXy0NTUhJaWFr7++mtoa2ujoKAAK1asUCgmERERERFRS8FRx5soMjISEokEwcHBCAoKgrOzM3R1dSESiaCqqgqpVAorKytERETAw8MD4eHhKCkpgZaWlkLbNTMzw7Zt23Dt2jX4+flh7NixWLdu3UvdxxwfHw97e3sMHToUkZGR+PPPP/HVV1/B29v7hWU/++wzlJSUwMvLC3PnzsU///lPqKurK7JLUFVVxcqVK3H+/Hl4enpi+fLlCA8PVygmERERERFRS8EW7SYSi8WIj48XpsvLyxEbGyt06RaLxYiKikJUVFSj5UNDQxEaGioz7+kW6ePHjzda1srKqtH7v5viWTGf5u3t3WjibW5ujt27d8vMy87OFv7W19dHbm6uzHIXF5cG80JCQhASEiJM29nZYf/+/TLrPF2GiIiIiIjodcREu4kuXryIGzduQCKRoLS0FAkJCRCLxXBwcGjuqhEREREREfHxXi0IE+0mqqurg1QqRX5+PkQiESQSCXbs2NFglPBXKScnB8HBwY0u09XVRXp6+iuuEREREREREanUPf18KXpt1NTUoLCwsNFlbdq0EZ7zTUREREREb76+O79v7iq80H/+3jp6BLNF+zXWrl07pT/2i4iIiIiIXk/sOt5yMNGm11rE6WMKlY/r5wbPw1lyl08fYg8A8FAgxoH/i+Gy/6TcMTKGD4LTPvnLA8B3IwYpXAcA+Md338kdY5uTEwDgbxvlf676L8GOStkPZcTwy5B/P75ycYRR9BG5ywPAjXmDYTJuh9zlr30zEQAwPlP+9/RL5/r31Hid/Mfi+jRHfPhDhtzlAWDNQBf4HJe/DsmujgCAT3Pkv+Z8ZuMGAGhv+He5Y1Tf3Ikeiw/LXR4A8ucPUco1S9HzGwCCsjLljiG1d4bbAcWue8c8BsF8s/z7cTmgfj+UcSzeVyDGLhdHOKcrdiwyPZXzHaCMGPP/c1TuGIv7uiv0fgD178nII/K3CqYNrm+tUzTG4IOKvadHhg1Syv84yjgWY47KHyPF3UGh8wqoP7e+/1X+WyodunkqtH1qnfh4LyIiIiIiIiIlYos2ERERERHRG0BFlX3HWwq2aBMREREREREpERNt+sskJibC29tbmI6MjMSMGTOasUZERERERER/PXYdb0VcXV1x+/ZtmXm9evXCvn37/pLtBQQEYOLEiX9JbCIiIiIiksVRx1sOJtqvidraWqipqSkcZ+bMmTKtzG3a/HWngLq6OtTV1f+y+ERERERERC0Ru47LoaKiArNmzYKVlRUcHBywc+dOeHt7IzExEQBQVlaGuXPnwtbWFn379kVgYCCuX78ulH/cpTo5ORnOzs7o168fFixYgPv37wvruLq6Yv369Zg9ezasra2xZMkSAEBOTg78/PxgaWkJFxcXLF26VKbci6irq0NHR0d4dezYEcXFxfj444/h4OCA3r17Y/To0Th6VPbRGq6urkhKShL2283NDSdPnsSdO3fg7+8PKysrjBs3Dvn5+Q32szHffvstBg4ciNraWpn5U6ZMweLFi5u8P0RERERERC0NE205xMbG4ty5c0hKSoJUKkVGRgby8vKE5WFhYSgrK8OmTZuQnJwMQ0NDBAQEoKqqSlgnLy8Pp06dglQqxYoVK5CWloY9e/bIbEcqlcLCwgJ79+5FQEAAbt68ieDgYHh6eiItLQ3Lli3DiRMnsHz5coX2p6amBpaWltiwYQPS0tIwatQofPTRRzI/DgDA5s2bMWDAAKSmpqJfv3745JNPMH/+fEyePBm7d+9GmzZtsHDhwiZtc+jQoXjw4AG+e+KZy3fv3kV2dvYzk3MiIiIiIno2FZWW/2otmGi/pIqKCqSmpiIyMhK2trYwNTVFTEyM0DKbk5ODS5cuYeXKlbCwsEDPnj0xf/58PHz4EJmZmTKxoqOjYWJiAkdHR7i6uiI7O1tmuZ2dHaZMmQJDQ0MYGBggKSkJXl5emDRpEoyMjGBjY4Pw8HDs2rULdXV1Tap/bGwsrK2thdc333wDXV1d+Pv7w8zMDIaGhggMDESfPn1w6NAhmbKurq4YN24cevTogWnTpuGPP/6Ag4MDnJ2dYWxsjMmTJ+P06dN49OjRC+vRtm1bjBgxArt37xbmpaSkoFevXnjvvfeatC9EREREREQtEe/Rfkm3bt1CbW0tJBKJME9bWxt6enoAgNzcXNy7dw+2trYy5WpqalBQUCBMGxgYoEOHDsK0jo4OLl++LFPGwsJCZvrKlSvIzc1FamqqMO/Ro0eoqalBUVERunTp8sL6f/DBBxg1apRM3R8+fIh169bh0KFDKCwsRG1tLf7880/06NFDpqypqalMOaB+MLXHOnfujNraWpSXl0NLS+uFdRk7dix8fX3xxx9/QFtbG6mpqRg/fvwLyxEREREREbVkTLSVrLKyEt26dcPWrVsbLNPU1BT+fnoQMhUVlQat0k8m4gBQVVWFCRMmNJqMdurUqUn169ixI4yMjGTmbdiwAV988QXmzp2LXr16oX379pg3b16D+6efrLPK//X7aGwwtaa0aAP1PySYmJjg22+/hUQiwZ07d2R+BCAiIiIiInodMdF+Sfr6+lBTU8OFCxfQtWtXAEBxcbHw2Cxzc3P89ttvEIlE6N69u1K3bW5ujmvXrjVIlBV15swZDB48GCNHjgRQP8L5zZs3hVb6v5KPjw927dqFa9euwdnZuck/GBARERERkazWdA90S8d7tF+SWCyGl5cX4uLi8NNPPyE3Nxdz5syBmpoaVFRUYGdnB4lEgpCQEJw8eRIFBQXIyclBXFxcg8HFXlZQUBBOnz6N6OhoXLlyBXl5eTh8+DDi4uIUimtkZISsrCz8/PPPuHr1KubOnYt79+4pFLOpRo4cifz8fOzdu5eDoBERERER0RuBLdpyiIyMxIIFCxAcHAwNDQ2EhITg1q1bEIlEUFVVFUYSj4iIQGlpKbp06YL+/fs36b7l5zEzM8O2bduwatUq+Pn5QVVVFUZGRvDy8lIo7rRp01BQUAB/f3+oq6tj/PjxsLe3VyhmU2lpacHNzQ2nT5+Go6PjK9kmERERERHRX4mJthzEYjHi4+OF6fLycsTGxgpdusViMaKiohAVFdVo+dDQUISGhsrMi4iIkJk+fvx4o2WtrKwavf+7KZ4VU0tLC2vXrn2psurq6sjNzZWZZ2NjIzPv6f2MjY1tNHZRURFGjx7d6P3eRERERETUNKrsOt5iMLORw8WLF3Hjxg1IJBKUlpYiISEBYrEYDg4OzV2110pZWRl++OEHnD179plJOBERERER0euGibYc6urqIJVKkZ+fD5FIBIlEgh07djQYJfxVysnJQXBwcKPLdHV1kZ6e/opr9GJjxoxBeXk55syZAwMDg+auDhERERERkVIw0ZaDRCJBSkpKc1dDhoWFhczztZ/UUrtkP6srOxERERERvTyOOt5yqNQ9/fBmIiIiIiIieu0MSslq7iq80Mkxr2bQ5ebWMps6iZpofOZ3CpX/0tkJbgdOyl3+mMcgAIBzuvwxMj3rYwzYLf+F8cex9nDaJ38dAOC7EYMw9JD8dTg0tP6i6ZdxQu4YX7nUjzxvtkn+GP8NdFTKe6qMGA7fyn88vx9lD8MExc7vmzOc0PPf8sfIm+4EAJhyQv4YWx3rYyj6GQn7UbEeMKsGuMLnuPznVbJr/bk5/z9H5Y6xuK87AKDH4sNyx8ifPwTtDf8ud3kAqL65Ex6H5T83Dwyp/6xP/E7+82KHU/15YZssfz2yfewx+uj3cpcHgL3uDgr9U/r4n8UxCtQjxb1+fBdFz09FrllA/XXLU4HzIn2I8r4DAr7PlDvGZgdnvK9AHQBgl4ujUt5TRb9HlHF+K2M/lHFejDwifz3SBjvAZb9i53fG8EGIOH1M7vJx/dwU2j61Tky0iYiIiIiI3gAqqs1dA3qMbwURERERERGREjHRJiIiIiIiIlIidh0nIiIiIiJ6A3DU8ZaDLdpERERERERESsRE+w3h6uoKU1NTmdeIESOUEjs7OxumpqaorKxUSjwiIiIiIqI3GbuOtwC1tbVQU1NTOM7MmTPh7e0tTLdpw7eXiIiIiKi1UGHf8RaDLdpPqaiowKxZs2BlZQUHBwfs3LkT3t7eSExMBACUlZVh7ty5sLW1Rd++fREYGIjr168L5RMTE+Ht7Y3k5GQ4OzujX79+WLBgAe7fvy+s4+rqivXr12P27NmwtrbGkiVLAAA5OTnw8/ODpaUlXFxcsHTpUplyL6Kurg4dHR3h1bFjRxQXF+Pjjz+Gg4MDevfujdGjR+PoUdnnwLq6umLDhg0IDw+HtbU13N3dcfhw/XNeb926hX/84x8AgD59+sDU1BSRkZEAgMzMTPj5+cHGxga2traYPn067t69K8QtKyvDrFmzYGtrC0tLSwwbNgwHDhwAAPj7++Ozzz6Tqcfdu3dhZmaGixcvNnmfiYiIiIiIWhom2k+JjY3FuXPnkJSUBKlUioyMDOTl5QnLw8LCUFZWhk2bNiE5ORmGhoYICAhAVVWVsE5eXh5OnToFqVSKFStWIC0tDXv27JHZjlQqhYWFBfbu3YuAgADcvHkTwcHB8PT0RFpaGpYtW4YTJ05g+fLlCu1PTU0NLC0tsWHDBqSlpWHUqFH46KOPZH4cAIDNmzejX79+SE1Nhbu7OyIiIlBSUoLu3bsLPzIcPXoUWVlZ+PTTTwEA1dXVCAwMxO7du7F582ZUV1fj448/FmKuXr0a169fh1QqRXp6OubOnYu3334bAODj44N9+/ahtrZWWD8lJQUmJiawsLBQaJ+JiIiIiIiaExPtJ1RUVCA1NRWRkZGwtbWFqakpYmJihGQwJycHly5dwsqVK2FhYYGePXti/vz5ePjwITIzM2ViRUdHw8TEBI6OjnB1dUV2drbMcjs7O0yZMgWGhoYwMDBAUlISvLy8MGnSJBgZGcHGxgbh4eHYtWsX6urqmlT/2NhYWFtbC69vvvkGurq68Pf3h5mZGQwNDREYGIg+ffrg0KFDMmVdXFwwbtw4GBkZISwsDDU1Nbhw4QLeeustaGpqAgA6deoEHR0dIVn28PDA4MGDYWRkhPfeew+LFi3C2bNn8euvvwIA7ty5AzMzM0gkEhgYGMDR0RH29vYAgMGDB+PRo0cyxy01NRVjx45t2ptFRERERETUQvEm3ifcunULtbW1kEgkwjxtbW3o6ekBAHJzc3Hv3j3Y2trKlKupqUFBQYEwbWBggA4dOgjTOjo6uHz5skyZp1ttr1y5gtzcXKSmpgrzHj16hJqaGhQVFaFLly4vrP8HH3yAUaNGydT94cOHWLduHQ4dOoTCwkLU1tbizz//RI8ePWTKmpqaCn+3a9cOGhoaKC4ufu728vPzsXr1apw7dw4lJSXC/Dt37qBbt27w9fXFRx99hP/+97+wt7fHkCFDYGlpCQAQiUQYMWIE9uzZg8GDByMnJwd37tyRqT8RERERETUdb9FuOZhov4TKykp069YNW7dubbDscasv0HAQMhUVlQat0k8m4gBQVVWFCRMmYPz48Q1id+rUqUn169ixI4yMjGTmbdiwAV988QXmzp2LXr16oX379pg3b55Ml+3G6gzUJ/rPM3XqVBgYGGDJkiXQ0dFBZWUlxo0bJ8R2cXHB8ePHkZmZiZMnT2L8+PGYPn06pk2bBqC++7iPjw9+//13pKSkwMnJqcn7SkRERERE1FIx0X6Cvr4+1NTUcOHCBXTt2hUAUFxcjNu3bwMAzM3N8dtvv0EkEqF79+5K3ba5uTmuXbvWIFFW1JkzZzB48GCMHDkSQP0I5zdv3hRa6Zvi8YjoTybeJSUlyMvLQ0xMDKytrQEAJ06caFC2c+fOQkK9YcMGfP3110KibWZmBlNTU3z99dc4ePAgli5dKvd+EhERERERtRRMtJ8gFovh5eWFuLg4aGhoQFNTE/Hx8VBTU4OKigrs7OwgkUgQEhKC2bNnw9DQEIWFhTh27Bh8fHxgbGws97aDgoLg6+uL6Oho+Pj4oG3btrh69SrOnj2LiIgIueMaGRnhyJEj+Pnnn6Guro4NGzbg3r17LxVDT08PKioqyMjIgL29Pdq2bQtNTU1oaWnh66+/hra2NgoKCrBixQqZcgkJCXjvvffQq1cvVFVVISsrC++8847MOmPHjkVMTAw0NTXh5OQk934SEREREbV27DrecnAwtKdERkZCIpEgODgYQUFBcHZ2hq6uLkQiEVRVVSGVSmFlZYWIiAh4eHggPDwcJSUl0NLSUmi7ZmZm2LZtG65duwY/Pz+MHTsW69atQ7du3RSKO23aNLz77rvw9/eHv78/evbsKQxI1lRdu3ZFaGgoli5dCjs7OyxevBiqqqpYuXIlzp8/D09PTyxfvhzh4eEy5dq0aYPly5djxIgRmDx5MrS0tBAdHS2zzuOW9lGjRvG530RERERE9EZgZvMUsViM+Ph4Ybq8vByxsbFCl26xWIyoqChERUU1Wj40NBShoaEy855ukT5+/HijZa2srBr5dP5/AAAgAElEQVS9/7spnhVTS0sLa9eufemyT4+SPn36dEyfPl1mnp2dHfbv3y8zLzc3V/g7JCQEISEhz912aWkpHjx4AG9v7+euR0RERERE9Lpgov2Uixcv4saNG5BIJCgtLUVCQgLEYjEcHByau2pvlNraWpSUlGDVqlWwtbVFr169mrtKRERERESvNXYdbzmYaD+lrq4OUqkU+fn5EIlEkEgk2LFjR4NRwl+lnJwcBAcHN7pMV1cX6enpr7hGijtz5gwmT56Md955B4mJic1dHSIiIiIiIqVRqXv6uVPU4tTU1KCwsLDRZW3atHmpEcSJiIiIiOjN5LL/ZHNX4YUyhg9q7iq8EmzRfg20a9dO6Y/9elN4Hs5SqHz6EHt4KBDjwJD6geVaQgxFyj+O8Y/vvpO7/Lb/GzXe7YD8F/hjHvUXXkXe15b0niq6H2/S+a3osXBOV+wfh0zPQUrZD2Wc3y3hs97e8O9yl6++uRPAm3PdU8Z+OKbJf16cGNn81z1AecdCGTEUSRQyhiv2WX9cD2Xsx+CD8u/HkWGDFLreAPXXHEXPK0Dx9wNQ/LwYekix9/TQUHuMPPK93OXTBr8+t5Cqsut4i8FRx4mIiIiIiIiUiIk2ERERERERkRKx6zgREREREdEbgF3HWw62aBMREREREREpERPt19ytW7dgamqKX375BQCQnZ0NU1NTVFZWNnPNni0xMRHe3t7NXQ0iIiIiImrhvvjiC7i6ukIikeD999/H+fPnn7v+gQMHMGzYMEgkEowcORInTpyQWV5XV4fVq1fD3t4elpaWmDJlCm7cuKH0ejPRfk24urrC1NRU5jVixAh0794dWVlZeOedd/7yOpiamsLS0rLBo8YmTZqEuLi4JscJCAjApk2blF09IiIiIiJ6g+zfvx8xMTGYPn06UlJSYGpqiqCgIBQXFze6/pkzZzBr1iz4+PggNTUVbm5uCAkJwfXr14V1Nm7ciO3bt+Nf//oXdu3ahfbt2yMoKAj3799Xat2ZaL8CtbW1Sokzc+ZMZGVlCa/t27fjrbfego6ODtq0eXW32ycmJipUXl1dHR07dnzmcmWf5ERERERErYGqSl2Lf72MLVu2wNfXF2PHjoWJiQkWLlyItm3bIiUlpdH1t23bBkdHRwQFBcHY2BhhYWEwNzfHF198AaC+NXvbtm0ICQmBu7s73n33XSxduhS//vorjh8/rvDxf1KrS7QrKiowa9YsWFlZwcHBATt37oS3t7eQPJaVlWHu3LmwtbVF3759ERgYKPMLyONuz8nJyXB2dka/fv2wYMECmeTQ1dUV69evx+zZs2FtbY0lS5YAAHJycuDn5wdLS0u4uLhg6dKlL5VUqqurQ0dHR3h17NixQdfxp+3Zswe2trY4evQohgwZAisrK8yePRv379/H9u3b4eDggAEDBmDNmjVNqsOECROQkpKCvLy8Z65TWlqK/8fevcdFWeb/H39BMpoSHkFFhRQ3khjDI4mc1TylEdBGGmootT/ztGmCuqm7UYIKGdgm7tiauVkuoubiIQ+oeYhiK78eVjaNPO56yDwSX0n4/UHO1xEMnJkU9f18PHjkfd339bmv6557ZvrMdd33PX78eDp37oyfnx+/+93vOH78uHn99VPHExMTGTNmDHPnziUwMFDTykVERERE7lLnz5/n6NGjFf7Onz9vsd3ly5fZu3cv3bt3N5c5OjoSEBDA119/XWnsr7/+2mJ7gMDAQPP2R48e5dSpUxbbPPDAAzz66KM3jGmtey7RTk5OZteuXWRmZmIymcjNzbVIGseNG8e5c+dYsGABWVlZeHh4EBcXR1FRkXmbwsJCduzYgclkIjU1lVWrVpGdnW2xH5PJhK+vLytXriQuLo7Dhw8THx9P//79WbVqFbNmzWLr1q3Mnj37V+/zpUuXWLJkCenp6bzzzjvk5uby//7f/6OgoICFCxeSmJhIRkYG//znP6uM1bVrVx577DHefPPNG26TmJjIv//9b+bPn88HH3zApUuXeOmllygru/EvWJ9++inHjh1j4cKFzJkzx6p+ioiIiIhIzfbee+/Ro0ePCn/vvfeexXY//PADV65coUmTJhbljRs35tSpU5XGPn36NI0bN77h9lf/ezMxrXVPPd7r4sWLrFixgjlz5uDv7w/AjBkzCAkJAcpHnPfu3cu2bdswGAwAvPrqq6xfv57NmzfTr18/c6ykpCTq1q1L27ZtCQ8PJy8vj5iYGPP6gIAAhg0bZl6eMmUKERERxMbGAuDp6cnEiRMZM2YMkyZNwsGh6nvxJycnk5qaal6ePHky3bp1q7JeSUkJf/rTn2jRogUAYWFhbN++nXnz5uHk5ISXlxcmk4m8vDw6depUZbzx48cTFRXF7t27MRqNFusKCwvJzc3l73//O+3btwdg9uzZhIeHs2PHjgq/MF3l7OzMn/70J5ycnKrcv4iIiIiIVHQnPN5r6NChPPXUUxXKXVxcbkNrfj33VKJ99OhRSkpKLJLDxo0bmxPQgoICLly4YE7CryouLubIkSPm5VatWlG3bl3zsqurK/v27bOo4+vra7G8f/9+CgoKWLFihbmstLSU4uJiTp06hZubW5Xtf/HFFxk4cKBF28+ePVtlPWdnZ3MfofwXHE9PT4uktnHjxuabCkydOpVVq1aZ13311VcW8Xx8fOjTpw9paWn89a9/tVh38OBBnJycLI5x06ZNadGiBQcPHrxhou3t7a0kW0RERETkLufi4lKtpLphw4bcd999nD592qL8+++/x9XVtdI6TZo04fvvv7/h9lf/e/3I9/fff18hf7PVPZVoV+XSpUs0a9aMhQsXVlhXv35987+vv/GYg4NDhWnR1ybiAEVFRQwePJhBgwZViN2oUaNqta9hw4Z4enpalFUn0a6svdcntQ4ODpSWlgIwduxYhg8f/osxx40bR79+/di5c2d1ml6l64+XiIiIiIjcuwwGA4888gg7duwgPDwcKB+o3LlzJ0OHDq20jp+fH9u3bzfPIgbYsWMHfn5+ALRs2RJXV1d27NiBt7c3UD7redeuXTz33HN2bf89lWi3bNkSJycndu/eTdOmTQE4c+YMx44dA8pHak+ePInBYKB58+Z23bePjw8HDhyokCjXRI0bN65wbcP1PD09iYqKIjU1lfvvv99c7uXlRUlJCbt37zZPHT9x4gTHjh2jbdu2v2q7RURERETuZXfbDbief/55EhISeOSRR2jfvj3vvfcexcXF5qnnEydOpGnTpowfPx6AIUOGEBsby7vvvktISAirV69mz549vP7660D54OKQIUP485//jIeHBy1btuStt96iWbNm5mTeXu6pRNvZ2ZmIiAhSUlJwcXGhfv36pKWl4eTkhIODAwEBARiNRkaOHMmECRPw8PDgxIkTbNy4kejoaLy8vKze94gRI3jmmWdISkoiOjqa2rVr88033/DVV1+RkJBgx17eOi+99BKPP/44ZWVl5qkWrVu3JiwsjClTpvDHP/6ROnXqMGPGDB566KFqXU8uIiIiIiIC0K9fP86cOUN6ejqnTp2iXbt2mEwm84zg//znPzg6/t/PCx07dmT27NnMmTOHtLQ0HnzwQd5++22LPC4+Pp4ff/yRqVOncv78eTp16sRf/vIX8z267OWeSrSh/I7YU6dOJT4+HhcXF0aOHMnRo0cxGAw4Ojqa7ySekJDA2bNncXNzo2vXrjRo0MCm/bZr145FixYxZ84cYmJicHR0xNPTk4iICDv17NZr2rQpsbGx/OUvf7EonzFjBklJScTHx3PlyhUee+wxUlJSqnXDNxERERERkauee+65G07rfv/99yuU9e3bl759+94wnoODA2PHjmXs2LF2a2Nl7rlE29nZmbS0NPPy+fPnSU5ONk/pdnZ2Ztq0aUybNq3S+qNHj2b06NEWZdePSN/oYed+fn6VXv9dHTeK2bJlSwoKCszL/v7+FsuRkZEVnktd2Qh6ddp1bdyrJkyYwIQJEyzKGjZsaHF39OtdfwyTk5Or3LeIiIiIiPwyR4cbP05Xbq17LtHes2cPhw4dwmg0cvbsWdLT03F2diYoKOh2N01ERERERETuAvdcol1WVobJZOK7777DYDBgNBpZvHjxbb3rdX5+PvHx8ZWuc3d3Jycn5xa3SERERERERKzlUHb9c6nklisuLubEiROVrqtVq5bFM7BFREREREQq8+SGT293E6q0sue9MZP4nhvRronq1KlzRzz2S0RERERERKqmRFvuaA/O3WJT/e9GhTBgvfW//K3qVf6LXN9PtlkdY83jgQD0Xmd9jHW9A22qfzVGfxv6kfNzPzotsf54/vPZ8uMZtdH6GMt6BNmlH/aIYeu5Zct5BeXn1lM2/LK9/OdfnD3fWG91jEOTewEwZmeu1THSu4Xx29ytVtcHWBoWTNDH1h/PTweWv6a+C60/nnuGlR/PGBv68mFYMM9tse1zb3FIiF0+s+73eNbqGD8eXgLYfixqyueerf0A2z8vasp5Yet3Gdh+PD2TrP/MAjj0h16E/GO71fW3PNEdgLDV1sfI7dfdLt8BtrYBoNda62Os71Meo/ty6/uy/alAm84JKD8v7HF+i9yMu+2Z5iIiIiIiIiK3lUa0RURERERE7gIaRa059FqIiIiIiIiI2JESbRERERERERE70tTxe1xiYiJFRUWkp6ff7qaIiIiIiIgNHB1udwvkKo1o36XCw8NZvHhxhfKUlBRiY2PNy1OmTCEpKalaMRMTExkzZozd2igiIiIiInI30oh2DVRSUoKTk9Mt2dcDDzxwS/ZzrcuXL2MwGG75fkVERERERG4FjWhX4eLFi4wfPx4/Pz+CgoJYsmQJkZGRZGRkAHDu3DkmT56Mv78/nTp1Yvjw4Rw8eNBcPyMjg8jISLKysggNDaVLly5MnTqVy5cvm7cJDw9n3rx5TJgwgQ4dOvDGG28AkJ+fT0xMDO3btycsLIyZM2da1LOH60ep165dyxNPPIHRaMTf35/hw4dTWlpKRkYGy5cvZ926dXh7e+Pt7U1eXh4A+/fvJzY2FqPRyGOPPcZrr71m0c7Y2FiSkpJISkrC39+fUaNG8Yc//IGRI0datOXHH3+kU6dOrFu3zq59FBERERG5Fzg4lNX4v3uFRrSrkJyczK5du8jMzKRBgwakpqZSWFhIWFgYAOPGjaNu3bosWLCAevXqsWjRIuLi4lizZg1169YFoLCwkB07dmAymTh+/Dhjx47Fx8eHmJgY835MJhOjRo1izJgxODg4cPjwYeLj43n55ZdJSUnh1KlTTJ8+nZ9++onJkyf/Kn09efIk48eP55VXXqFnz55cvHiRzz77DIC4uDgOHjxIcXExr732GgD169enqKiI4cOH06VLF5YtW8bJkyeZMmUKjo6OTJkyxRx72bJlxMbG8uGHHwLlP1A899xznDlzhkaNGgHwySefUKtWLfOxFRERERERuRMp0f4FFy9eZMWKFcyZMwd/f38AZsyYQUhICFA+4rx37162bdtmngr96quvsn79ejZv3ky/fv3MsZKSkqhbty5t27YlPDycvLw8i0Q7ICCAYcOGmZenTJlCRESE+XpqT09PJk6cyJgxY5g0aRIODlXf6SA5OZnU1FSLspKSEjp06FDp9qdOneKnn36iV69etGjRAoCHH34YgHr16lGnTh1KS0txdXU111m+fDk//fQTycnJ1KlTh4ceeoiEhAQmTpzI73//e/OPDW3atOHll1+22J+npycff/yxud/Lly9nwIABmlYuIiIiIiJ3NCXav+Do0aOUlJRgNBrNZY0bNzYnoQUFBVy4cMGchF9VXFzMkSNHzMutWrUyJ5wArq6u7Nu3z6KOr6+vxfL+/fspKChgxYoV5rLS0lKKi4s5deoUbm5uVbb/xRdfZODAgRZl8+fP5/Dhw5Vu//DDD9O1a1cGDBhAcHAwgYGB9OnTB2dn5xvu4+DBg/j4+FCnTh1zWadOnSgpKeHw4cPmRP36/gFERUWRnZ3NsGHD+M9//kNeXh4JCQlV9ktERERERCrSXcdrDiXaNrh06RLNmjVj4cKFFdbVr1/f/O9atSwPs4ODA2VlltcnXJuIAxQVFTF48GAGDRpUIfbVqdZVadiwIZ6enhZlLi4uN9z+vvvu47333uPLL7/k008/ZcGCBaSnp5OdnU2TJk2qtc8bub5/AE8++SRpaWns3buXLVu24O3tTbt27Wzaj4iIiIiIyO2mRPsXtGzZEicnJ3bv3k3Tpk0BOHPmDMeOHQPAx8eHkydPYjAYaN68uV337ePjw4EDByokyr82R0dHOnfuTOfOnXnppZcICAhg27ZtRERE4OTkxJUrVyy29/LyYuXKlRQXF5tHtf/5z3/i5OSEh4fHL+6rcePGhIWFkZ2dzaeffspzzz33q/VLRERERETkVtFdx3+Bs7MzERERpKSk8Pnnn1NQUMCkSZNwcnLCwcGBgIAAjEYjI0eOZPv27Rw5coT8/HxSUlIs7jxujREjRvDFF1+QlJTE/v37KSws5JNPPiElJcVOvato165dzJs3j927d3Ps2DFWr15NUVERrVu3BqBFixbmtpw5c4aSkhIGDBhArVq1SExM5JtvvmHbtm2kpKTw7LPPVjqKfb3o6Gg++ugjjh8/zoABA361vomIiIiI3O0c74C/e4VGtKuQmJjI1KlTiY+Px8XFhZEjR3L06FEMBgOOjo6YTCZSU1NJSEjg7NmzuLm50bVrVxo0aGDTftu1a8eiRYuYM2cOMTExODo64unpSUREhJ16VpGzszNffPEFCxcupKioiJYtW/Laa6/x6KOPAvDb3/6Wzz//nMjISIqKili0aBH+/v4sWLCA119/ncjISOrVq0f//v155ZVXqrXPwMBAGjRoQMeOHWnYsOGv1jcREREREZFbRYl2FZydnUlLSzMvnz9/nuTkZPOUbmdnZ6ZNm8a0adMqrT969GhGjx5tUXb9Db82bdpUaV0/P79Kr/+ujhvFvH7fycnJ5n97eXmxYMGCG8Zs1KgR7777boXyhx9+mPfff/+G9X5p3Y8//silS5eIioq64TYiIiIiIiJ3EiXaVdizZw+HDh3CaDRy9uxZ0tPTcXZ2Jigo6HY37Y5WWlrKDz/8gMlkwtXVVcdTRERERMRGjg5lVW8kt4QS7SqUlZVhMpn47rvvMBgMGI1GFi9eXK3rj38t+fn5xMfHV7rO3d2dnJycW9yim3f8+HF69OiBu7s7s2bNwtHxXrpiQ0RERERE7mYOZdc/Z0pqvOLiYk6cOFHpulq1apmf8y0iIiIiIveOQZu33O4mVOmD0JDb3YRbQiPad6A6derc8sd+1VSjdubaVH9utzCiN221un5WeDCAXWJEbfzU6hjLegTRa+12q+sDrO/TnSc3WN+GlT3Lp/9P/Lzy+wNUx8yu4QA8t8X6L4nFISE8ZUM/lv/cD3vE+G2u9efF0rBg4j7dbHV9gHeDQm36wr36RWjr6wEwIc/682K2fzgvbNtsdX2A+YGhNr/HAP741QarY0zr0BOAETb0xRQYin/WNqvrA+RFB9L3E+tjrHk8EIAYG87vD8PKP/fu93jW6hg/Hl5iUxuutsMen3uP/NX6dux9vvxYjPvM+vfInMfC76rzwudd62Psiwu2y3lhj8+LHmus/17e2Lc7vdfZ9pqu6x1ol/O7vw3nRc7P54WtMWypfzVGxw+sPxZfDtIljnLzlGiLiIiIiIjcBRwdbncL5CpdGCsiIiIiIiJiR0q0RUREREREROxIU8dFRERERETuAhpFrTn0WoiIiIiIiIjYkRLte0h4eDiLFy+uUJ6SkkJsbOxtaJGIiIiIiMjdR1PH7xAlJSU4OTnd7mZUqqysjCtXrlCrluXpdPnyZQwGw03Hq8l9FRERERGpqXTX8ZpDI9pWuHjxIuPHj8fPz4+goCCWLFlCZGQkGRkZAJw7d47Jkyfj7+9Pp06dGD58OAcPHjTXz8jIIDIykqysLEJDQ+nSpQtTp07l8uXL5m3Cw8OZN28eEyZMoEOHDrzxxhsA5OfnExMTQ/v27QkLC2PmzJkW9eyhtLSU9PR0goKC8PX1JTIyks8//9y8Pi8vD29vb7Zu3UpERAS+vr7s27eP2NhYkpKSSEpKwt/fn1GjRgHw2WefERkZia+vL0FBQcydO5fS0tIq+yoiIiIiInInUqJtheTkZHbt2kVmZiYmk4nc3FwKCwvN68eNG8e5c+dYsGABWVlZeHh4EBcXR1FRkXmbwsJCduzYgclkIjU1lVWrVpGdnW2xH5PJhK+vLytXriQuLo7Dhw8THx9P//79WbVqFbNmzWLr1q3Mnj3brv1buHAhixYtYvLkyaxcuZKOHTvywgsvcOLECYvt0tLSSEhIYPXq1Tz44IMALFu2jLp16/Lhhx8yadIk/vvf//LCCy/QsWNHVq5cyeTJk83xf6mvIiIiIiIidypNHb9JFy9eZMWKFcyZMwd/f38AZsyYQUhICFA+4rx37162bdtmnjb96quvsn79ejZv3ky/fv3MsZKSkqhbty5t27YlPDycvLw8YmJizOsDAgIYNmyYeXnKlClERESYr6f29PRk4sSJjBkzhkmTJuHgUPVckeTkZFJTUy3KSkpK6NChg3n53Xff5cUXX6Rv377m/e7cuZMPPviA3//+9+btxo0bR7du3SxitWnThpdfftm8nJaWRqtWrZgyZQoODg54eXlx9OhRFixYYNG36/sqIiIiIiI3x9Gh7HY3QX6mRPsmHT16lJKSEoxGo7mscePGtGjRAoCCggIuXLhgTsKvKi4u5siRI+blVq1aUbduXfOyq6sr+/bts6jj6+trsbx//34KCgpYsWKFuay0tJTi4mJOnTqFm5tble1/8cUXGThwoEXZ/PnzOXz4MAAXLlzg1KlTdOzY0bzewcGBDh06WEx/r6x9lZUdPHiQDh06WPwI0LFjR2bPns3Fixdxdna+YSwREREREZE7kRJtO7t06RLNmjVj4cKFFdbVr1/f/O/rbxzm4OBAWZnlL1DXJuIARUVFDB48mEGDBlWI3ahRo2q1r2HDhnh6elqUubi4VKvu9e6///4KZde3ubqsrSciIiIiIlLTKNG+SS1btsTJyYndu3fTtGlTAM6cOcOxY8cA8PHx4eTJkxgMBpo3b27Xffv4+HDgwIEKibI9PfDAA7i6uvLll1/SqVMnoPyu4l999RU9e/a86XheXl5s3LiRsrIy86j2l19+SdOmTc2j2SIiIiIiYjvddbzm0M3QbpKzszMRERGkpKTw+eefU1BQwKRJk3BycsLBwYGAgACMRiMjR45k+/btHDlyhPz8fFJSUipMvb5ZI0aM4IsvviApKYn9+/dTWFjIJ598QkpKip16Vy4uLo7MzEzWrl3Lt99+y+uvv86xY8cqHUmvyqBBgzhy5Aivv/463377LWvXriUzM1M3PBMRERERkbuWRrStkJiYyNSpU4mPj8fFxYWRI0dy9OhRDAYDjo6O5juJJyQkcPbsWdzc3OjatSsNGjSwab/t2rVj0aJFzJkzh5iYGBwdHfH09CQiIsJOPSs3bNgwLl68SFJSEmfPnuWhhx5i/vz55hH8m9GsWTPmz5/PzJkz+fDDD2nYsCFDhw5lyJAhdm2ziIiIiIhITaFE2wrOzs6kpaWZl8+fP09ycrJ5SrezszPTpk1j2rRpldYfPXo0o0ePtihLSEiwWN60aVOldf38/Cq9/rs6bhTz+n07OjoyZswYxowZU+n2/v7+FBQUVCh///33K93+scceq/Dosuq0S0RERERE5E6kRNsKe/bs4dChQxiNRs6ePUt6ejrOzs4EBQXd7qaJiIiIiMg9StcF1xxKtK1QVlaGyWTiu+++w2AwYDQaWbx48W29c3Z+fj7x8fGVrnN3dycnJ+cWt0hEREREROTe5FB2/TOl5I5UXFzMiRMnKl1Xq1Yt83O+RURERETk7vTCts23uwlVmh8YerubcEtoRPsuUadOnV/1sV8iIiIiIlKzOTpoDLWmUKItd7S+n2yzqf6axwOJ2vip1fWX9Si/Lv+pDdbHWN6zPIat7Riw3vr6AKt62RZjVa/yftgjhq3Hotfa7VbXX9+nO4BdYgzbusXqGAuDQ4jJ3Wp1fYAPw4Jteo+seTwQgKCPrY/x6cDyGGGrrT+euf2681sbj8XSsGC6L7e+H9ufst+x6LHG+mOxsW93nrTh8wZgZc8gu5wXvddZH2Nd7/IYtpzjH4YFc7/Hs1bXB/jx8BICsq3vx47I8n7Ycn4uDQsGIOQf1p8XW57oXmM+L+zxnWrLiNz8wFC7vEfs8V1m63vElv+3gPL/v7DHa9rfhhg5dophy3cIlH+P2OP/1URuhq6XFxEREREREbEjjWiLiIiIiIjcBRwdbncL5CqNaIuIiIiIiIjYkRJtuWWys7Px9/e/3c0QERERERH5VSnRvseFh4fj7e3N2rVrLcpLS0sJDQ3F29ub3Nxcu+yrX79+rF692i6xRERERETEkqNDzf+7VyjRvoOVlJTYJU7z5s1Zvny5RdnOnTvtEvtaderUoXHjxnaPKyIiIiIiUpMo0baTixcvMn78ePz8/AgKCmLJkiVERkaSkZEBwLlz55g8eTL+/v506tSJ4cOHc/DgQXP9jIwMIiMjycrKIjQ0lC5dujB16lQuX75s3iY8PJx58+YxYcIEOnTowBtvvAFAfn4+MTExtG/fnrCwMGbOnGlRryoDBw5k+/btnDx50lyWnZ1NRESExXZ5eXl4e3tz6dIlc1lubi7e3t7m5f379xMbG0uHDh3o2LEj0dHR5n5WNnV8w4YNREZGYjQa6datGxMnTqx2u0VERERERGoiJdp2kpyczK5du8jMzMRkMpGbm0thYaF5/bhx4zh37hwLFiwgKysLDw8P4uLiKCoqMm9TWFjIjh07MJlMpKamsmrVKhZdEr0AACAASURBVLKzsy32YzKZ8PX1ZeXKlcTFxXH48GHi4+Pp378/q1atYtasWWzdupXZs2dXu+1ubm5069aNlStXAnD+/HlzAnyzJkyYQLNmzVi2bBnLli1j6NChODhUPkckLy+PsWPH0rNnT1asWMGCBQssknYREREREak+xzvg715xL/X1V3Px4kVWrFhBYmIi/v7+eHt7M2PGDPPU7vz8fPbu3cubb76Jr68vrVu35tVXX+XKlSts3rzZIlZSUhJt27YlODiY8PBw8vLyLNYHBAQwbNgwPDw8aNWqFZmZmURERBAbG4unpyedO3dm4sSJLF26lLKysmr3ITIy0pzU5+TkYDQa8fDwuOljcfz4cQICAmjTpg2tW7dmwIABtGnTptJt586dy8CBAxk5ciReXl74+PgwfPjwm96niIiIiIhITaLnaNvB0aNHKSkpwWg0mssaN25MixYtACgoKODChQsVpk0XFxdz5MgR83KrVq2oW7euednV1ZV9+/ZZ1PH19bVY3r9/PwUFBaxYscJcVlpaSnFxMadOncLNza1afejRowfTp0/n66+/Jjs7m5iYmGrVu96QIUOYMmUKH3/8Md27d6dv377m43C9f//730RFRVm1HxERERERkZpKifYtcOnSJZo1a8bChQsrrKtfv77537VqWb4cDg4OFUalr03EAYqKihg8eDCDBg2qELtRo0bVbqPBYGDAgAGkpqZy4MAB+vTpU2EbR8fyCRDXtumnn36y2GbcuHEMGDCALVu2kJubS3p6OpmZmXTr1q3abRERERERkZvn6FD9Ga3y61KibQctW7bEycmJ3bt307RpUwDOnDnDsWPHAPDx8eHkyZMYDAaaN29u1337+Phw4MABPD09bY4VFRVFREQEkZGR1KtXr8L6q4n76dOncXZ2BspH1K/n5eWFl5cXcXFxjBgxgo8//rjSRPuhhx4iLy+vwk3XRERERERE7mRKtO3A2dmZiIgIUlJScHFxoX79+qSlpeHk5ISDgwMBAQEYjUZGjhzJhAkT8PDw4MSJE2zcuJHo6Gi8vLys3veIESN45plnSEpKIjo6mtq1a/PNN9/w1VdfkZCQcFOx2rVrx2effVZh1PwqDw8PmjVrxty5cxk1ahT79+9n2bJl5vXFxcXMmjWLPn364O7uzrFjxygoKKgwZf6qUaNGERcXh4eHB7179+by5ct89tlnDBs27KbaLSIiIiIiUpMo0baTxMREpk6dSnx8PC4uLowcOZKjR49iMBhwdHQ030k8ISGBs2fP4ubmRteuXWnQoIFN+23Xrh2LFi1izpw5xMTE4OjoiKenp9WjxA0bNrzhOicnJ2bPns306dMZOHAgXbp04aWXXuIPf/gDUD61/IcffuCVV17h9OnTNG7cmCeeeILnn3++0nj+/v6kpaXx9ttv8/bbb+Pi4kJISIhV7RYREREREakplGjbibOzM2lpaebl8+fPk5ycbJ7S7ezszLRp05g2bVql9UePHs3o0aMtyq4fkd60aVOldf38/Cq9/rs6bhTzqoKCAovlLl26kJOTY1H29NNPA+XXeV97DK4XGRlZ4ZFhvXv3pnfv3jfTZBERERERqYRj5U/VldtAibad7Nmzh0OHDmE0Gjl79izp6ek4OzsTFBR0u5smIiIiIiIit5ASbTspKyvDZDLx3XffYTAYMBqNLF68+IbXO98K+fn5xMfHV7rO3d29wsi0iIiIiIiI2E6Jtp0YjUaWL19+u5thwdfX1+L52te6/lFiIiIiIiJyZ3O83Q0QM4ey6x/ULCIiIiIiInecCXm/fP+lmmC2f/jtbsItoWFNuaP1/2SbTfVzHg/kqQ2fWl1/ec/ya/AHrLc+xqpe5TFs6UvO44H0tfFYrHk8kFE7c62uP7dbGAC91m63Osb6Pt3tEqP3OuuPxbregQB2iTFkyxarYywKCSFstfXHASC3X3eMi6w/N3cPKT83bWlHbr/y1zR4lfUxtg7oTvSmrVbXB8gKD64R71MAn3et78u+uGC6L7ftvb79Kds+L9b83A97HIsnbfj8XdkziIBs247FjshA7vd41ur6Px5eAkDURuv7saxH+bkVuNL6vmx7MtAu7xFb2wDY5Tt12FbrPzsXBofY9F6H8ve7Pc5vW7/L7PG9bo/vMnt8dtr6mdNjjW3fhxv7difpqw1W1/9Dh5427V/uTUq0RURERERE7gK663jNoWn8IiIiIiIiInakRFtERERERETEjjR1XERERERE5C7g4KD7XNcUGtEWq2VnZ+Pv72+3eBkZGURGRtotnoiIiIiIyO2gRPsuEx4ejre3N2vXrrUoLy0tJTQ0FG9vb3Jzrb+z9LX69evH6tWr7RJLRERERETkbqFEuwYpKSmxS5zmzZuzfPlyi7KdO3faJfa16tSpQ+PGje0eV0REREREbp6jQ83/u1co0b6BixcvMn78ePz8/AgKCmLJkiVERkaSkZEBwLlz55g8eTL+/v506tSJ4cOHc/DgQXP9q9Ogs7KyCA0NpUuXLkydOpXLly+btwkPD2fevHlMmDCBDh068MYbbwCQn59PTEwM7du3JywsjJkzZ1rUq8rAgQPZvn07J0+eNJdlZ2cTERFhsV1eXh7e3t5cunTJXJabm4u3t7d5ef/+/cTGxtKhQwc6duxIdHS0uZ+VTR3fsGEDkZGRGI1GunXrxsSJE83rTCYTTzzxBI8++iihoaHMmDGD//3f/612v0RERERERO4ESrRvIDk5mV27dpGZmYnJZCI3N5fCwkLz+nHjxnHu3DkWLFhAVlYWHh4exMXFUVRUZN6msLCQHTt2YDKZSE1NZdWqVWRnZ1vsx2Qy4evry8qVK4mLi+Pw4cPEx8fTv39/Vq1axaxZs9i6dSuzZ8+udtvd3Nzo1q0bK1euBOD8+fPmBPhmTZgwgWbNmrFs2TKWLVvG0KFDcXCo/KeovLw8xo4dS8+ePVmxYgULFiywSNpr1arFq6++Sk5ODklJSWzYsIG33377ptskIiIiIiJSkynRrsTFixdZsWIFiYmJ+Pv74+3tzYwZM8xTu/Pz89m7dy9vvvkmvr6+tG7dmldffZUrV66wefNmi1hJSUm0bduW4OBgwsPDycvLs1gfEBDAsGHD8PDwoFWrVmRmZhIREUFsbCyenp507tyZiRMnsnTpUsrKqn8XwcjISHNSn5OTg9FoxMPD46aPxfHjxwkICKBNmza0bt2aAQMG0KZNm0q3nTt3LgMHDmTkyJF4eXnh4+PD8OHDzeuHDRuGv78/LVu2JDAwkJdeeok1a9bcdJtERERERERqMj3eqxJHjx6lpKQEo9FoLmvcuDEtWrQAoKCggAsXLlSYNl1cXMyRI0fMy61ataJu3brmZVdXV/bt22dRx9fX12J5//79FBQUsGLFCnNZaWkpxcXFnDp1Cjc3t2r1oUePHkyfPp2vv/6a7OxsYmJiqlXvekOGDGHKlCl8/PHHdO/enb59+5qPw/X+/e9/ExUVdcNYO3bsYN68eXz77bdcunSJK1euUFpaalW7RERERETEkkZRaw4l2la4dOkSzZo1Y+HChRXW1a9f3/zvWrUsD6+Dg0OFUelrE3GAoqIiBg8ezKBBgyrEbtSoUbXbaDAYGDBgAKmpqRw4cIA+ffpU2MbRsfyteG2bfvrpJ4ttxo0bx4ABA9iyZQu5ubmkp6eTmZlJt27dqt0WKP/x4sUXX+S5555j/PjxuLi4sH37dl577bWbiiMiIiIiIlLTKdGuRMuWLXFycmL37t00bdoUgDNnznDs2DEAfHx8OHnyJAaDgebNm9t13z4+Phw4cABPT0+bY0VFRREREUFkZCT16tWrsP5q4n769GmcnZ2B8hH163l5eeHl5UVcXBwjRozg448/rjTRfuihh8jLy6tw0zWAvXv3ApCQkGAuW7ZsmXUdExERERERqcGUaFfC2dmZiIgIUlJScHFxoX79+qSlpeHk5ISDgwMBAQEYjUZGjhzJhAkT8PDw4MSJE2zcuJHo6Gi8vLys3veIESN45plnSEpKIjo6mtq1a/PNN9/w1VdfWSSp1dGuXTs+++yzCqPmV3l4eNCsWTPmzp3LqFGj2L9/v0XyW1xczKxZs+jTpw/u7u4cO3aMgoKCClPmrxo1ahRxcXF4eHjQu3dvLl++zGeffcawYcPw9PTk8uXLLF68mJCQEPLy8io8gkxERERERKzn6FD9ezrJr0vT+G8gMTERo9FIfHw8I0aMIDQ0FHd3dwwGA46OjphMJvz8/EhISKBv375MnDiRH374gQYNGti033bt2rFo0SIOHDhATEwMUVFRvPPOOzRr1syqeA0bNqR27dqVrnNycmL27Nn861//YuDAgfz973/npZdeMq93dHTkhx9+4JVXXqF379688sorPPHEEzz//POVxvP39yctLY01a9YwcOBA4uLiKCgoAODhhx9m0qRJzJs3jyeeeIL169czbtw4q/okIiIiIiJSk2lE+wacnZ1JS0szL58/f57k5GTzlG5nZ2emTZvGtGnTKq0/evRoRo8ebVF2/Yj0pk2bKq3r5+dX6fXf1XGjmFddTXyv6tKlCzk5ORZlTz/9NFB+nfe1x+B6kZGRFR4Z1rt3b3r37l3p9sOGDWPYsGGV7gsqP2YiIiIiIiJ3GiXaN7Bnzx4OHTqE0Wjk7NmzpKen4+zsTFBQ0O1umoiIiIiISAWODre7BXKVEu0bKCsrw2Qy8d1332EwGDAajSxevPiG1zvfCvn5+cTHx1e6zt3dvcLItIiIiIiIiNx6DmXXP29Kaqzi4mJOnDhR6bpatWrd8PnWIiIiIiJy95v25Ybb3YQq/bFjz9vdhFtCI9p3kDp16tjlsV93kx5rtttUf2Pf7vRet83q+ut6BwLQ/xPrY+Q8bp8YttS/GiM0x/rjubl/dwC7HM8B6z+1OsaqXkF2aYM9YkRttL4fy3oEEZO71er6AB+GBRO9yfoYWeHBADy3ZYvVMRaHhADw6j+t/+J/rVNPuv7dtvP786cDbX49wD7vdVte1w/Dgnlqg/X9AFjeM4jgVda/17cOKH+v29oPgEf+an2Mvc8H81sb3yNLw4Ltcl7c7/Gs1TF+PLwEgLhPN1sd492gUEL+Ydv34ZYnuteI8xvAM2Wj1TEOJfSw6TWF8tf1SRveZyt7lp8XtrxXl/cMotda217T9X262/QeWfrz61ET/j/Jlv8vgPL/N/DPsr4NedGBNu3/VtLU8ZpDdx0XERERERERsSMl2iIiIiIiIiJ2pKnjIiIiIiIid4H7bncDxEwj2iIiIiIiIiJ2pERbRERERERExI6UaN/hwsPD8fb2Zu3atRblpaWlhIaG4u3tTW5urt32tXjxYrvEEhERERERuVsp0b6NSkpK7BKnefPmLF++3KJs586ddon9a7BXv0VERERE5P84OpTV+L97hRLtn128eJHx48fj5+dHUFAQS5YsITIykoyMDADOnTvH5MmT8ff3p1OnTgwfPpyDBw+a62dkZBAZGUlWVhahoaF06dKFqVOncvnyZfM24eHhzJs3jwkTJtChQwfeeOMNAPLz84mJiaF9+/aEhYUxc+ZMi3pVGThwINu3b+fkyZPmsuzsbCIiIiy2e/7553n99dctyv7zn//Qrl079uzZQ1lZGenp6YSEhODr60twcDBpaWkAxMbGcuzYMV577TW8vb3x9vY2x6iq/ZX1u6q2iIiIiIiIVNfx48d54YUXePTRR+nWrRszZ87kypUrN9z+6NGjTJ48mfDwcNq3b0/Pnj2ZO3euxaDg0aNHzbnPtX9ff/11le1Rov2z5ORkdu3aRWZmJiaTidzcXAoLC83rx40bx7lz51iwYAFZWVl4eHgQFxdHUVGReZvCwkJ27NiByWQiNTWVVatWkZ2dbbEfk8mEr68vK1euJC4ujsOHDxMfH0///v1ZtWoVs2bNYuvWrcyePbvabXdzc6Nbt26sXLkSgPPnz7NhwwYiIyMttouOjuYf//iHxcmzfPly2rZti6+vL+vWreO9997jT3/6E5988glvvfUWrVu3Bsp/SGjWrBkvv/wy27ZtY9u2bQDVbv/1/a6qLSIiIiIiItVx5coVXnzxRUpKSvjwww9JTk4mOzubuXPn3rDOt99+S1lZGX/605/Iyclh0qRJfPDBB7z11lsVtn3//ffNOdC2bdt45JFHqmyTEm3KR7NXrFhBYmIi/v7+eHt7M2PGDHMSmJ+fz969e3nzzTfx9fWldevWvPrqq1y5coXNmzdbxEpKSqJt27YEBwcTHh5OXl6exfqAgACGDRuGh4cHrVq1IjMzk4iICGJjY/H09KRz585MnDiRpUuXUlZW/akVkZGR5qQ+JycHo9GIh4eHxTa9evWitLTUos0rVqwgKioKKB9RbtKkCQEBAbi7u9OhQweeeuopABo0aMB9991HvXr1cHV1xdXVFaDa7b++31W1RUREREREbo6jQ83/+zVs27aNgwcPMmvWLNq1a0dISAhjx45l8eLFN7xsNTg4mBkzZhAYGEirVq3o0aMHcXFxrF+/vsK2DRo0MOdArq6uODk5VdkmPUeb8ikBJSUlGI1Gc1njxo1p0aIFAAUFBVy4cAF/f3+LesXFxRw5csS83KpVK+rWrWtednV1Zd++fRZ1rh+t3b9/PwUFBaxYscJcVlpaSnFxMadOncLNza1afejRowfTp0/n66+/Jjs7m5iYmArbGAwGnnjiCbKzs+nVqxf5+fkcP36cgQMHAtC7d2/++te/0qtXL4KDgwkJCSEsLAxHxxv/HlPd9l/f76raIiIiIiIid5/z589z/vz5CuUuLi64uLhYFfPrr7/m4YcfpkmTJuaywMBApk+fzrfffmtx2esvuXDhAvXr169Q/sILL3D58mUefPBBXnjhBUJDQ6uMpUS7Gi5dukSzZs1YuHBhhXXXvhC1alkeTgcHhwqj0tcm4gBFRUUMHjyYQYMGVYjdqFGjarfRYDAwYMAAUlNTOXDgAH369Kl0u+joaKKjozl9+jTLly8nJCTEvB93d3fWrVvH9u3b2b59O1OmTOGRRx7BZDLh4FD5z0/Vbf/1/a6qLSIiIiIicvd57733Kp3SPWrUKEaPHm1VzNOnT9O4cWOLsqtJ9+nTp6uVaB8+fJjFixczefJkc1ndunVJTEykY8eOODg4sG7dOn73u9+RmZlJSEjIL8ZTog20bNkSJycndu/eTdOmTQE4c+YMx44dA8DHx4eTJ09iMBho3ry5Xfft4+PDgQMH8PT0tDlWVFQUERERREZGUq9evUq3adeuHd7e3nz00UesXbuWmTNnWqy///776dmzJz179iQiIoLf/va3/Oc//8Hd3R0nJ6cKNxSwpf1VtUVERERERKrv15qabU9Dhw41X556rcpGszMyMn7xOmuALVu22NymEydOMGLECPr3729xKWujRo14/vnnzcvt27fn1KlTmEwmJdrV4ezsTEREBCkpKbi4uFC/fn3S0tJwcnLCwcGBgIAAjEYjI0eOZMKECXh4eHDixAk2btxIdHQ0Xl5eVu97xIgRPPPMMyQlJREdHU3t2rX55ptv+Oqrr0hISLipWO3ateOzzz6rdPT4WlFRUcyYMYP69etbnCDZ2dmUlpby6KOPUrt2bXJycnBxcTH/GtSiRQu++OIL+vTpg5OTE40aNbK5/Tdqi4iIiIiI3H1uZor44MGD6dev3y9u06RJE5o0acLevXstyk+fPm1e/0tOnDjBkCFD8PPzY/r06VW26dFHH61wH67K6GZoP0tMTMRoNBIfH8+IESMIDQ3F3d0dg8GAo6MjJpMJPz8/EhIS6Nu3LxMnTuSHH36gQYMGNu23Xbt2LFq0iAMHDhATE0NUVBTvvPMOzZo1sypew4YNqV279i9uM2DAAKD8sWDXTnd3cXHho48+4plnnuHJJ59kz549ZGZmYjAYABgzZgyHDx+mZ8+edOvWzS7tv1FbRERERETk3taoUSO8vLx+8a9WrVr4+fmxf/9+zpw5Y667Y8cOXFxcaNOmzQ3jX02yH3nkEWbMmPGL96a66l//+pf5xtC/RJnNz5ydnc3PjIbyi/STk5PNU6KdnZ2ZNm0a06ZNq7T+6NGjK1xTcP2I7qZNmyqt6+fnV+n139Vxo5hXFRQUVCg7e/YsP/30U4XHf12dMn4jfn5+fPzxx5WW/1L7f6mNN2qLiIiIiIjcnPvugKnjv4bAwEC8vLx45ZVXeOWVVzh16hRz5sxh8ODB5juE/8///A8TJ07kvffeo2nTppw4cYLY2Fjc3d1JSEiwSNKvJtLLly/HycmJdu3aAbB+/XqWLVvGjBkzqmyTEu2f7dmzh0OHDmE0Gjl79izp6ek4OzsTFBR0u5tmNyUlJfzwww/MmTMHf39/fvOb36gtIiIiIiJyR7vvvvuYN28e06dP55lnnuH+++/nqaeeshgI/fHHHyksLDQ/7mv79u0cOnSIQ4cOERwcbBHv2sHKP//5zxw/fpz77rsPLy8v3nrrLR5//PEq26RE+2dlZWWYTCa+++47DAYDRqORxYsXV3m9868pPz+f+Pj4Ste5u7uTk5NzU/G+/PJLhg4dSps2bcjIyLBHE61Wk9oiIiIiIiJ3thYtWvCXv/zlhuv9/f0tEujIyMgqZ9U+9dRTld64rTocyq5//pTUGMXFxZw4caLSdbVq1TI/51tEREREROTNPetvdxOq9HvfXre7CbeERrRrsDp16tjlsV8iIiIiIiJy6yjRljtajzXbbaq/sW93ntzwqdX1V/Ysv4a//yfbrI6R83ggAH1tiLHm8UCb+gHlfXnKhhjLfz4WA9ZbH2NVr/IYv83danWMpWHB9Fpr/Xmxvk93ALvEmJS/0eoYMzr3YNTOXKvrA8ztFsZzNjxbcvHPj9yzx3vkkb9a/5rufT6Y32237VjM6x7GoM3WH4sPQsuPRfv3rT8W/xNrn/M7epP19QGywoPt8pllj/f6uM9++Yaev2TOY+GE/MO274AtT3QncKX1x2Lbk+XHIu7TzVbHeDcoFID7PZ61OsaPh5fY5fPCHp979jgvpn25weoYf+zY06bvUyj/TrX1Oxls/x6x5VhC+fHsvc76fqzrXd4Pe8Sw9byw5ViC7cfz6rkpcjOUaIuIiIiIiNwFHB10VXBNoedoi4iIiIiIiNiREm0RERERERERO1KiLSIiIiIiImJHuka7BgsPD+fYsWNA+R3IPTw8GDJkCE8//fRtbpmIiIiIiNQ0jg63uwVylRLtX0lJSQlOTk42x3n55ZeJjIzkf//3f9m5cyfTp0/Hzc2NkJ/vBiwiIiIiIiI1yz0xdfzixYuMHz8ePz8/goKCWLJkCZGRkWRkZABw7tw5Jk+ejL+/P506dWL48OEcPHjQXD8jI4PIyEiysrIIDQ2lS5cuTJ06lcuXL5u3CQ8PZ968eUyYMIEOHTrwxhtvAJCfn09MTAzt27cnLCyMmTNnWtSrSr169XB1daVly5Y8/fTTeHt7s2PHDvP6o0eP8rvf/Q4/Pz86d+7MhAkTOHfunHl9YmIiY8aMYe7cuTz22GN07dqVBQsWcPnyZaZOnUrHjh0JDw8nN/f/HgtSUlLCpEmTCA8Pp3379vTt25elS5datCs2NpY33niDN954g86dOxMcHMzf/vY3i22OHz/O2LFj6dKlC35+fjz99NMUFBSY1y9dupTevXtjNBrp168fy5Ytq/ZxERERERERqanuiUQ7OTmZXbt2kZmZiclkIjc3l8LCQvP6cePGce7cORYsWEBWVhYeHh7ExcVRVFRk3qawsJAdO3ZgMplITU1l1apVZGdnW+zHZDLh6+vLypUriYuL4/Dhw8THx9O/f39WrVrFrFmz2Lp1K7Nnz77pPpSVlZGXl8fBgwepVat8IkJpaSkjR47k0qVLfPDBB8yfP5+CggImTZpkUXfbtm2cPXuWDz74gLFjxzJz5kxGjhzJQw89RHZ2NuHh4SQkJHDp0iVzXHd3d9566y1ycnIYMWIEr732Gtu2WT5HcdmyZTRp0oSsrCyGDRvGa6+9Zv6B4vLlyzz//POcPXuW+fPns3LlSoYMGUJpaSkAH3/8MXPnzuWVV15h9erVjBo1itdff50NG6x/dqaIiIiIyL3svjvg715x108dv3jxIitWrGDOnDn4+/sDMGPGDPPU6/z8fPbu3cu2bdswGAwAvPrqq6xfv57NmzfTr18/c6ykpCTq1q1L27ZtCQ8PJy8vj5iYGPP6gIAAhg0bZl6eMmUKERERxMbGAuDp6cnEiRMZM2YMkyZNwsGh6osokpOTSU1NpaSkhJKSEurXr090dDQAO3bs4ODBg2zatImmTZsC8Prrr/P000/z3Xff8eCDDwLQqFEjJk+ejKOjI23atCEzMxODwcBzzz0HwMiRI3n//ff517/+RefOnalduzajR482t6FVq1Z88cUXrFmzhsDAQHP5I488wgsvvABAXFwc7777Lp9//jleXl7k5ORw5swZsrKyeOCBB8z9vyojI4NJkybRs2dP8z727dvHRx99ZC4TERERERG5E931ifbRo0cpKSnBaDSayxo3bkyLFi0AKCgo4MKFC+Yk/Kri4mKOHDliXm7VqhV169Y1L7u6urJv3z6LOr6+vhbL+/fvp6CggBUrVpjLSktLKS4u5tSpU7i5uVXZ/hdffJGBAwdy6tQpUlJSePbZZ2ndujUABw8epEWLFuYkG8BoNOLk5MTBgwfNifZvfvMbHB3/b/JCkyZN+M1vfmNebtSoEffddx9nzpwxl/3tb39j2bJlHDt2jMuXL1NSUkLXrl0t2vbQQw9ZLLu5ufH9998D5cfVx8fHnGRfq6ioiMOHD5OYmMjkyZPN5SUlJebXRURERERE5E511yfaVbl06RLNmjVj4cKFFdbVr1/f/O+r07WvcnBwoKyszKLs2kQcyhPKwYMHM2jQoAqx3agGVAAAIABJREFUGzVqVK32NWzYEE9PTzw9PUlPT2fAgAG0b9+etm3bVqs+UOlN2a7vD2Ce1p2Tk8PMmTOZNGkS7du3p169esydO5f//ve/Vca9/phU5uqU/BkzZvDII49U2S4REREREama7jpec9z1WU3Lli1xcnJi9+7d5pHfM2fOmB+b5ePjw8mTJzEYDDRv3tyu+/bx8eHAgQMWU6Zt0bx5c/r160dqairvvPMOXl5eHDt2jBMnTpj7tnv3bkpKSvDy8rJ6P19++SWdO3e2mBZ/6NAhateuXe0Y3t7eLFu2jAsXLlQY1W7SpAmurq4cOXLEYmq+iIiIiIjI3eCuvxmas7MzERERpKSk8Pnnn5tvFubk5ISDgwMBAQEYjUZGjhzJ9u3bOXLkCPn5+aSkpFjcedwaI0aM4IsvviApKYn9+/dTWFjIJ598QkpKitUxhw4dyubNm9m9ezcBAQF4eXkxYcIE9u3bx5dffsmUKVPo0aOHedq4NTw9Pdm1axfbt2+nsLCQlJQUDhw4cFMx+vfvT6NGjRg1ahRfffUVhw8fZvXq1fzrX/8C4KWXXmLevHksXryYwsJC9u/fz0cffcQHH3xgdbtFRERERERqgrs+0YbyR1wZjUbi4+MZMWIEoaGhuLu7YzAYcHR0xGQy4efnR0JCAn379mXixIn88MMPNGjQwKb9tmvXjkWLFnHgwAFiYmKIiorinXfeoVmzZlbH9PLyIigoiPT0dBwdHfnzn/9MvXr1GDRoEPHx8Xh7ezNjxgyb2h0TE0PPnj0ZO3YsMTExlJSUEBUVdVMxDAYD7777Lg888ADDhw/nySefZNGiRdx3X/m9Bp999lmmTZvG0qVLGTBgAEOHDmX16tW0atXKpraLiIiIiNyrHB3KavzfveKunzoO5aPaaWlp5uXz58+TnJxsntLt7OzMtGnTmDZtWqX1R48ebXEXboCEhASL5U2bNlVa18/Pr9Lrv6vjRjHnz59v/nfLli2ZN2/eDWMkJydXKLv+sWSAxY3dDAZDpfWu9f7771cZt0WLFsydO/eGMSIiIoiIiPjF/YiIiIiIiNxp7olEe8+ePRw6dAij0cjZs2dJT0/H2dmZoKCg2900ERERERERucvcE4l2WVkZJpOJ7777DoPBgNFoZPHixRXuEn4r5efnEx8fX+k6d3d3cnJybnGLRERERETkTnaf7jpeY9wTibbRaGT58uW3uxkWfH19LZ6vfS094kpEREREROTO5VBWnQcfi4iIiIiISI22oGDd7W5ClYZ7977dTbglNHQqd7Rea7fbVH99n+70XrfN6vrregcCEJpjfTs29+8OQMg/rI+x5YnuPLbM+n4AfBYVSN9PrI+x5vHyYxG9aavVMbLCgwF45K/Wx9j7fDBPbfjU6vrLe5bfu8EeMTxnV35Dw+o4NCGc1m9vsbo+QOFLIQR9bP1r+unA8tc07tPNVsd4NyjULjFG7cy1uj7A3G5hdjk3//jVBqtjTOvQE7D986LHGts+9zb27W6X9/pzW6w/PxeHhADgn2V9O/KiA4nJtf41BfgwLNgu54Wtn9+ATef43G5h3O/xrNX1AX48vIT+NpwXOT+fF7+14TVZGlZ+PDstsf7z95/PBjFos22fnR+EhtjlO8DW42nLZwWUf17Y471uy2fOxr7l57etx9OWfkB5X6I2Wt+GZT10Xye5eUq0RURERERE7gKOuka7xrgnnqMtIiIiIiIicqso0RYRERERERGxI00dFxERERERuQto6njNoRFtsZvw8HAWL15sVd28vDy8vb25dOmSnVslIiIiIiJya2lEW8z27NnDW2+9xe7du/nxxx9xc3PDz8+P119/HYPBUGX9rKws7r///l/cxtvbu0JZaGgoGRkZbNu2jbp161rdfhERERERkZpAifZdoqSkBCcnJ6vrf//998TFxdGzZ08WLlxIvXr1OHToEOvWraO0tLRaMRo1alSt7WbOnElAQIB5uXbt2hj+P3t3Hldlmf9//AXKEfW4JIIrMG6hfAHBBRJFhUxTtBCdIo0ylBbLZSYV1JKZJAX3kabRxL5mlMsPtyE1M8UctBEZzVyC0nDBHLXMBZHxJPz+YDzfTuJ2zlFQ38/Hg8fj3Mv1ua/7uu9zHz9e133fBgOurq5W1V1ERERERDR0vDLR0PE7oLCwkNdffx1/f39CQkJYsmQJkZGRpKSkAHDu3DkmTJhAUFAQ7du3Z+jQoRw6dMhcPiUlhcjISNLT0+nevTsdO3Zk0qRJXL582bxOWFgY8+bNY8yYMQQEBDBlyhQAcnJyiIqKws/Pj9DQUKZNm2ZR7np2797NpUuXmDx5Mq1bt8bd3Z0uXbowefJknJ2dzevt3LmTQYMG0bZtWwIDA3nxxRf5z3/+Y67TrQwdr127Nq6urua/2rVra+i4iIiIiIjcN5Ro3wFJSUns2bOH+fPnk5qaSmZmJvn5+eblo0eP5ty5cyxcuJD09HQ8PDyIiYmhqKjIvE5+fj7bt28nNTWVmTNnkpGRwcqVKy22k5qaio+PD2vWrCEmJoajR48SGxtLeHg4GRkZTJ8+na1btzJjxoyb1tnFxYXLly+zefNmSktLy10nPz+fF154gf/5n/9h+fLlfPjhh3Tq1OmWe7xFREREREQeBBo6bmeFhYWsXr2aOXPmEBQUBMDUqVPp1q0bUNbjvH//frKyssz3Pb/55pts3LiRLVu20KdPH3OsxMREatSoQcuWLQkLC2PHjh1ERUWZlwcHBzNkyBDz9MSJE4mIiCA6OhoAT09Pxo0bx8iRIxk/fjwODtcfSxIQEMCwYcMYNWoUtWvXxt/fn+DgYCIiIqhduzYA7733Hu3atWPixInmcuXdc30zo0aNokqVKubpv/71rxbTIiIiIiJy+6o4lN9hJnefEm07KygowGQy4evra57n4uJCkyZNAMjLy+PChQvmJPyq4uJijh07Zp52d3e3eDCYq6srBw4csCjj4+NjMZ2bm0teXh6rV682zyspKaG4uJjTp0/j5uZ2w7qPHTuWmJgYvvzyS7766isWLFjAggULSE9Pp0GDBuTl5fHoo4/eUjtMmjSJjIwM8/Tu3bvNn9944w2L/Xdzc+Prr7++pbgiIiIiIiKVnRLtu+zixYs0bNiQRYsWXbOsTp065s9Vq1oeGgcHh2uGdP/2Cd1FRUUMHjyYQYMGXRP7Vh9U5uLiQt++fenbty+jRo2iZ8+eLF26lFGjRt1S+atGjRrF0KFDy13m6uqKp6fnbcUTERERERG5VyjRtrOmTZvi5OTE3r17adCgAQBnzpzh+PHjAHh7e3Pq1CkMBgONGjWy67a9vb05ePCg3ZLYWrVqUb9+fS5dugSUDRPfsWMHr7766k3Luri44OLiYpd6iIiIiIjIzekBXJWHjoWdGY1GIiIiSE5OJjs7m7y8PMaPH4+TkxMODg4EBwfj6+vL8OHD2bZtG8eOHSMnJ4fk5GSLJ49bY9iwYezcuZPExERyc3PJz8/ns88+Izk5+aZlMzMzGTduHF988QVHjhzh4MGDzJgxg4MHDxIaGgrAiy++yK5du3j77bf59ttvOXjwIB988IE5ERcRERERERH1aN8R8fHxTJo0idjYWGrXrs3w4cMpKCjAYDDg6OhofpJ4XFwcZ8+exc3NjcDAQOrWrWvTdtu0acPixYuZM2cOUVFRODo64unpSURExE3LtmzZEoPBwJQpUzhx4gTVq1enefPmpKSkmO+nbtasGQsXLmTWrFksXbqUGjVqEBAQYPGANhERERERkQedEu07wGg0MmvWLPP0+fPnSUpKMg/pNhqNJCQkkJCQUG75ESNGMGLECIt5cXFxFtObN28ut6y/v3+593/fjLu7O4mJiTddLygoiGXLlpW77Hp1+rW8vLzrxr3eMhERERERuTnH679kSO4yJdp3wL59+zhy5Ai+vr6cPXuWuXPnYjQaCQkJqeiqiYiIiIiIyB2mRPsOKC0tJTU1lcOHD2MwGPD19SUtLe2ap4TfTTk5OcTGxpa7rHHjxqxdu/Yu10hEREREROT+5FD623dGyX2puLiYkydPlrusatWq5vd8i4iIiIjIvWn5959WdBVu6qnmj1d0Fe4K9Wg/IJydnfXuahERERGR+5ju0a48lGjLPW3Qli9sKv9x926Ef5Zldfm1PbsA2CVGbxtirO/ZxabyV2PYYz96bbA+xoZeZTH6bfyH1TEyHguxuS3B9uMBtp8Xj67fZnV5gE29O1eatrD1vLClLaGsPR9ZYX2Mfw4o248nP7f+3FzTo+w5HaHrrD+umX0626UtKst5URmue13WWB8j60n7/QY89qn158XGx+1zXlT3eMbq8peOLgEqx7XTHudFZbju2VL+agxbf0+hcvwbxx5tMWSr9f9mXNS1m03blweT3qMtIiIiIiIiYkfq0RYREREREbkPVHHQ47cqC/Voi4iIiIiIiNiREm25JStXriQoKKiiqyEiIiIiIlLpaei4ALBv3z7+8pe/sHfvXi5duoSbmxv+/v68/fbbGAyGO7rt+Ph4ioqKmDt37h3djoiIiIjI/UxPHa88lGjfB0wmE05OTlaX/+mnn4iJiaFHjx4sWrSImjVrcuTIETZs2EBJSYkda2rpl19+oUqVKncsvoiIiIiISEXQ0HE7Kyws5PXXX8ff35+QkBCWLFlCZGQkKSkpAJw7d44JEyYQFBRE+/btGTp0KIcOHTKXT0lJITIykvT0dLp3707Hjh2ZNGkSly9fNq8TFhbGvHnzGDNmDAEBAUyZMgWAnJwcoqKi8PPzIzQ0lGnTplmUu57du3dz6dIlJk+eTOvWrXF3d6dLly5MnjwZZ2dni3W3bNlCr169aNeuHSNHjuTChQvmZcXFxbz11ls88sgj+Pr6Eh0dTV5ennn51eHnn3/+OY8//ji+vr689dZbrFq1ig0bNuDl5YWXlxc7duywrvFFREREREQqASXadpaUlMSePXuYP38+qampZGZmkp+fb14+evRozp07x8KFC0lPT8fDw4OYmBiKiorM6+Tn57N9+3ZSU1OZOXMmGRkZrFy50mI7qamp+Pj4sGbNGmJiYjh69CixsbGEh4eTkZHB9OnT2bp1KzNmzLhpnV1cXLh8+TKbN2+mtPT6Tyq8ePEiaWlpzJkzh9TUVHbv3s17771nXj59+nQ2bdrEjBkzWLFiBS4uLgwbNoxLly5ZxHj//fdJTk7mk08+4Y9//CO9e/cmNDSUrKwssrKyCAgIuKW2FhERERGR/+PoUPn/HhRKtO2osLCQ1atXEx8fT1BQEF5eXkydOhWTyQSU9Tjv37+f2bNn4+PjQ7NmzXjzzTe5cuUKW7ZssYiVmJhIy5Yt6dq1K2FhYdf08gYHBzNkyBA8PDxwd3dn/vz5REREEB0djaenJx06dGDcuHEsX778hskzQEBAAMOGDWPUqFF06tSJl19+mcWLF3P+/HmL9UwmE2+99RZt2rShXbt29O/f31yvixcvsmzZMuLi4ujSpQsPP/wwU6dO5fLly2RkZFjE+POf/0zbtm1p0aIFtWrVwtnZGYPBgKurK66urnf8nnAREREREZE7Sfdo21FBQQEmkwlfX1/zPBcXF5o0aQJAXl4eFy5cuObp3cXFxRw7dsw87e7uTo0aNczTrq6uHDhwwKKMj4+PxXRubi55eXmsXr3aPK+kpITi4mJOnz6Nm5vbDes+duxYYmJi+PLLL/nqq69YsGABCxYsID09nQYNGgBgNBpp3LixRb1++uknAI4dO4bJZKJ9+/bm5dWrV8fb29tiaLyzszOtWrW6YV1ERERERETuZUq076KLFy/SsGFDFi1adM2yOnXqmD9XrWp5WBwcHK7plf51Ig5QVFTE4MGDGTRo0DWx69Wrd0v1c3FxoW/fvvTt25dRo0bRs2dPli5dyqhRo265Xjfz23u+RURERETEPh6kodmVnRJtO2ratClOTk7s3bvX3At85swZjh8/DoC3tzenTp3CYDDQqFEju27b29ubgwcP4unpaZd4tWrVon79+hb3V9+Iu7s7Tk5O/Otf/6JPnz5AWU/9gQMHzNPX4+TkxJUrV2yus4iIiIiISGWgRNuOjEYjERERJCcnU7t2berUqcOsWbNwcnLCwcGB4OBgfH19GT58OGPGjMHDw4OTJ0+yadMmBg4cSIsWLaze9rBhw3j66adJTExk4MCBVKtWje+++47du3cTFxd3w7KZmZmsX7+e8PBwfve732EymVi9ejUHDx7kjTfeuKXt16xZk6efftq87w0aNOCvf/0rBoOBvn373rBskyZN2L59O/n5+dSpU4datWrZ9LoyERERERGRiqRE287i4+OZNGkSsbGx1K5dm+HDh1NQUIDBYMDR0dH8JPG4uDjOnj2Lm5sbgYGB1K1b16bttmnThsWLFzNnzhyioqJwdHTE09OTiIiIm5Zt2bIlBoOBKVOmcOLECapXr07z5s1JSUm55n7yGxk7diylpaWMGTOGixcv4u/vz4IFC6hevfoNyz311FNkZ2cTGRlJUVERixcvvq3tioiIiIiIVCZKtO3MaDQya9Ys8/T58+dJSkoyD+k2Go0kJCSQkJBQbvkRI0YwYsQIi3m/7ZHevHlzuWX9/f3Lvf/7Ztzd3UlMTLzhOpGRkURGRlrMe/bZZ3n22WfN087OzkyaNIlJkybdcgwou4f8/fffv+16i4iIiIjI/6mie7QrDSXadrZv3z6OHDmCr68vZ8+eZe7cuRiNRkJCQiq6aiIiIiIiInIXKNG2s9LSUlJTUzl8+DAGgwFfX1/S0tKueUr43ZSTk0NsbGy5yxo3bszatWvvco1ERERERETuXw6lt/t+JrnnFBcXc/LkyXKXVa1a1fyebxERERERuXd9dnxdRVfhpno2ufEbie4X6tF+ADg7O9vttV8iIiIiIiJyY0q05Z726PptNpXf1Lsz4Z9lWV1+bc8uAPTb+A+rY2Q8Vnb/vq31sKX81RiPfWp9e258vDMAoeusj5HZpyyGre3Za4P1bbGhV9kxtUeMpzK3Wh1jeWhXBm35wuryAB9372aXc9PvQ+tjfB1dFsPW9nz2C9vaIq1bN7qvtf7c3BJedm52XmX9fmzrX3Ze2PodibLhvAJYGtqV3jZcL9b3tN93xJZ9WRralQGbrD83AVY8GkL/z62PsapH2flt636A7dc9W643UHbNscd5Ud3jGatjXDq6BIAXs7ZYHeO9Lt1tOqZQdlyftCHGmv+eF7aeW7YcDyg7Jvb4TbbHd8TWGLbsB5Tty8DN1n9H0sO62rR9eTAp0RYREREREbkPOFZ0BcRMx0JERERERETEjpRoi4iIiIiIiNiRho6LiIiIiIjcBxwdKroGcpV6tEVERERERETsSIm2ALBv3z5iY2N55JFHaNu2LY899hhjx47l8uXLd3zbKSkpREZG3vHtiIiIiIiI3A0aOn4fMJlMODk5WV3+p59+IiYmhh49erBo0SJq1qzJkSNH2LBhAyUlJXasqaXS0lKuXLlyx+KLiIiIiDxIqmjoeKWhHm07Kyws5PXXX8ff35+QkBCWLFlCZGQkKSkpAJw7d44JEyYQFBRE+/btGTp0KIcOHTKXv9q7m56eTvfu3enYsSOTJk2y6FkOCwtj3rx5jBkzhoCAAKZMmQJATk4OUVFR+Pn5ERoayrRp026pR3r37t1cunSJyZMn07p1a9zd3enSpQuTJ0/G2dkZgJUrVxIUFMSGDRt47LHH8PPz46WXXuKnn34yxykpKWHu3LmEhITg4+NDZGQk2dnZ5uU7duzAy8uLrVu3EhERgY+PD4sWLeKdd95h//79eHl54eXlxcqVK207CCIiIiIiIhVIibadJSUlsWfPHubPn09qaiqZmZnk5+ebl48ePZpz586xcOFC0tPT8fDwICYmhqKiIvM6+fn5bN++ndTUVGbOnElGRsY1yWdqaio+Pj6sWbOGmJgYjh49SmxsLOHh4WRkZDB9+nS2bt3KjBkzblpnFxcXLl++zObNmyktLb3uehcvXuT9999n5syZpKWl8e9//5vx48ebly9atIjFixczYcIE1qxZQ7t27XjxxRc5efKkRZxZs2YRFxfHunXreOKJJ4iJiaF169ZkZWWRlZVFnz59blpnERERERGRykqJth0VFhayevVq4uPjCQoKwsvLi6lTp2IymYCyHuf9+/cze/ZsfHx8aNasGW+++SZXrlxhy5YtFrESExNp2bIlXbt2JSwsjB07dlgsDw4OZsiQIXh4eODu7s78+fOJiIggOjoaT09POnTowLhx41i+fPkNk2eAgIAAhg0bxqhRo+jUqRMvv/wyixcv5vz58xbrmUwmEhIS8PPzw8/Pj8TERL744gvzfyS8//77vPTSS/Tu3ZsWLVowceJEmjRpwscff2wRZ/To0XTq1AlPT0/c3NyoUaMGVapUwdXVFVdXV3MvuoiIiIiIyL1I92jbUUFBASaTCV9fX/M8FxcXmjRpAkBeXh4XLlwgKCjIolxxcTHHjh0zT7u7u1OjRg3ztKurKwcOHLAo4+PjYzGdm5tLXl4eq1evNs8rKSmhuLiY06dP4+bmdsO6jx07lpiYGL788ku++uorFixYwIIFC0hPT6dBgwYAGAwG2rRpY1EHJycnDh06RP369Tl9+jTt2rUzL3dwcCAgIMBiaHx5dRcREREREds5Oty4g03uHiXad9HFixdp2LAhixYtumZZnTp1zJ+rVrU8LA4ODtf0Sv86EQcoKipi8ODBDBo06JrY9erVu6X6ubi40LdvX/r27cuoUaPo2bMnS5cuZdSoUbdU/lZVr17drvFEREREREQqEyXadtS0aVOcnJzYu3evuRf4zJkzHD9+HABvb29OnTqFwWCgUaNGdt22t7c3Bw8exNPT0y7xatWqRf369bl06ZJ53uXLl/nmm2/w9vYGYP/+/ZhMJlq0aEGtWrVwdXVl165dtG/fHih7qvju3bvp0aPHDbfl5OR0R59uLiIiIiIicjcp0bYjo9FIREQEycnJ1K5dmzp16jBr1iycnJxwcHAgODgYX19fhg8fzpgxY/Dw8ODkyZNs2rSJgQMH0qJFC6u3PWzYMJ5++mkSExMZOHAg1apV47vvvmP37t3ExcXdsGxmZibr168nPDyc3/3ud5hMJlavXs3Bgwd54403zOs5OTnx1ltvMWHCBAASEhIICQmhWbNmAMTExPDuu+/i7u7Oww8/zMcff8zx48fL7WX/tSZNmnD06FFyc3Nxc3PDaDRiMBisbgsRERERkQeRo17vVWko0baz+Ph4Jk2aRGxsLLVr12b48OEUFBRgMBhwdHQ0P0k8Li6Os2fP4ubmRmBgIHXr1rVpu23atGHx4sXMmTOHqKgoHB0d8fT0JCIi4qZlW7ZsicFgYMqUKZw4cYLq1avTvHlzUlJSLO4nr1mzJs8//zyjR4/m9OnTdOrUibffftu8fMiQIRQWFpKYmMjZs2d5+OGHee+998y9+9fTq1cvNm7cSHR0NOfPn2fq1KlERkZa3xgiIiIiIiIVSIm2nRmNRmbNmmWePn/+PElJSeYh3UajkYSEBBISEsotP2LECEaMGGEx77c90ps3by63rL+/f7n3f9+Mu7s7iYmJt7Ru79696d27d7nLHB0dGTlyJCNHjix3eVBQEHl5edfMNxgMzJ0799YrLCIiIiIiUokp0bazffv2ceTIEXx9fTl79ixz587FaDQSEhJS0VUTEREREZH7mIaOVx5KtO2stLSU1NRUDh8+jMFgwNfXl7S0tGueEn435eTkEBsbW+6yxo0bs3bt2rtcIxERERERkfuXQ+lv3xsl953i4mJOnjxZ7rKqVaua3/MtIiIiIiL3ri9PVf4OtE5u4RVdhbtCPdoPAGdnZ7u99quyeXT9NpvKb+rdmW6fWB/ji76dAXjsU+tjbHy8LEbvz7KsjrG+Zxebyl+NYY/9eCpzq9Uxlod2BaDfxn9YHSPjsRCb2xJsPx4AntPLf57CrTgyNoz+n1vfDgCreoQwfHum1eXfDQ4FYMjWL6yOsahrNwDWHFlvdYwnPXvzu4RPrS4PcPjPj/PsF9bvR1q3sv140oZjsqZH2S1Eb/7rc6tjTG7fg5h/bLG6PMD7Id0JXWf9dz2zT9l3PcqG7/rS/37Xvd+3PsaBmK68mLXF6vIA73Xpbpfz2zN5k9UxjsQ9CkDCLuvPiz+360H7JbZdL/71TAjhNlz31v73umfLMXmvS3cAqns8Y3WMS0eXMHCz9ecVQHpYVwZssr49Vzxa9l239Xphy28ylP0u2/p7Crb9W2tT77Lrha1tYUv5qzHaLLT+vPhmaFebtn83OVZ0BcRMx0JERERERETEjpRoi4iIiIiIiNiRho6LiIiIiIjcBxz01PFKQz3aIiIiIiIiInakRPsBlZKSQmRk5G2XKygowMvLi2+//RaAHTt24OXlxcWLFwFYuXIlQUFBdq2riIiIiIjIvURDx+8zO3bs4LnnnrvhOosXL7Y6fqNGjcjKyuKhhx6yOoaIiIiIiNifRo5XHkq0KyGTyYSTk5NVZQMCAsjK+r/Xc7z55ps4OzszceJE87w6deqQnZ1tdb1cXV2tqtvtbkdERERERORepKHjN1FYWMjrr7+Ov78/ISEhLFmyhMjISFJSUgA4d+4cEyZMICgoiPbt2zN06FAOHTpkLn91iHZ6ejrdu3enY8eOTJo0icuXL5vXCQsLY968eYwZM4aAgACmTJkCQE5ODlFRUfj5+REaGsq0adMsypXHYDDg6upq/jMYDDg7O18z76rbrddvh47fis8//5wnn3wSX19fHnvsMRYsWEBJSYl5uZeXF8uWLeOll16ibdu2fPDBB7ccW0REREREpLJRon0TSUlJ7Nmzh/nz55OamkpmZib5+fnm5aNHj+bcuXMsXLiQ9PR0PDw8iImJoaioyLxOfn6Kl2geAAAgAElEQVQ+27dvJzU1lZkzZ5KRkcHKlSsttpOamoqPjw9r1qwhJiaGo0ePEhsbS3h4OBkZGUyfPp2tW7cyY8YMu+2bNfW6XTk5OcTHx/PCCy+wbt063njjDT788EM+/PBDi/Xmzp1L7969+eSTTwgPD7dpv0RERERERCqSEu0bKCwsZPXq1cTHxxMUFISXlxdTp07FZDIBZUnk/v37mT17Nj4+PjRr1ow333yTK1eusGXLFotYiYmJtGzZkq5duxIWFsaOHTsslgcHBzNkyBA8PDxwd3dn/vz5REREEB0djaenJx06dGDcuHEsX76c0tJSu+3j7dbrdr3zzju8/PLLRERE4O7uTrdu3XjllVdYtmyZxXpPPPGEeZ1GjRrZtE8iIiIiIg8iB4fK/3en/PDDD7z44ou0bduWTp06MW3aNK5cuXLDMmFhYXh5eVn8vffeexbr5ObmMmjQIHx9fenWrRupqam3VB/do30DBQUFmEwmfH19zfNcXFxo0qQJAHl5eVy4cOGap2wXFxdz7Ngx87S7uzs1atQwT7u6unLgwAGLMj4+PhbTubm55OXlsXr1avO8kpISiouLOX36NG5ubjbvnzX1ul25ubns2rWLv/71r+Z5V65csRg6Dli0sYiIiIiIyK26cuUKL730EvXr12fp0qWcOnWKuLg4qlWrxqhRo25Y9o9//KPF25hq1qxp/lxYWMjQoUPp1KkTf/7zn/n222+ZMGECdevWZeDAgTeMq0TbBhcvXqRhw4YsWrTommV16tQxf65a1bKZHRwcrumV/nXCC1BUVMTgwYMZNGjQNbHr1atnQ63/jzX1ul1FRUWMHj2aRx999IbrVa9e3abtiIiIiIjIgykrK4tDhw7xv//7v9SvX582bdowatQoZs2axfDhw2/4oOWaNWte92HPf//73/nll1+YOnUqTk5OtGrVim+++YZFixYp0bZF06ZNcXJyYu/evTRo0ACAM2fOcPz4cQC8vb05deoUBoPB7sOdvb29OXjwIJ6ennaNe7d5e3tz+PDhe34/REREREQqu3vhvuDz589z/vz5a+bXrl2b2rVrWxXzq6++onXr1tSvX988r0uXLvzpT3/i+++/x8vL67pl582bR0pKCo0aNeKJJ57gueeeM3dIfvXVVwQGBlok6l26dGHBggUUFhZiNBqvG1eJ9g0YjUYiIiJITk6mdu3a1KlTh1mzZuHk5ISDgwPBwcH4+voyfPhwxowZg4eHBydPnmTTpk0MHDiQFi1aWL3tYcOG8fTTT5OYmMjAgQOpVq0a3333Hbt37yYuLs6Oe3lnvfLKKwwfPpwGDRrQq1cvAA4cOMDx48d55ZVXKrh2IiIiIiJyN33wwQe8884718x/7bXXGDFihFUxf/zxR1xcXCzmXU26f/zxx+sm2tHR0Xh7e1OnTh127drF7Nmz+fHHHxk3bpy5rIeHx3XjKtG2QXx8PJMmTSI2NpbatWszfPhwCgoKMBgMODo6mp/YHRcXx9mzZ3FzcyMwMJC6devatN02bdqwePFi5syZQ1RUFI6Ojnh6ehIREWGnPbs7unXrxrvvvsu7777L/PnzMRgMtGzZstwh8SIiIiIicn97/vnn6d+//zXzy+vNTklJKTcp/7UvvvjC6rq88MIL5s+tW7fGYDDwpz/9iT/84Q83HG5+K5Ro34TRaGTWrFnm6fPnz5OUlGQeCm00GklISCAhIaHc8iNGjLjmf2Z+2yO9efPmcsv6+/uXe//37Zg7d65d69W0aVPy8vLM00FBQRbTkZGRFg8TgLJku1u3btet46/Li4iIiIiIdRwc7Pd2ojvldoaIDx48mD59+txwnfr161O/fn32799vMf/HH380L79Vbdu2xWQyceLECTw8PKhfvz4//fSTVXGVaN/Evn37OHLkCL6+vpw9e5a5c+diNBoJCQmp6KqJiIiIiIjct+rVq3dLD4L29/dn/vz5nDlzxrz+9u3bqV27Ns2bN7/l7X3zzTdUqVLFHMPf35+//OUvmEwmcw/39u3badWq1Q2HjYMS7ZsqLS0lNTWVw4cPYzAY8PX1JS0tzeancdsiJyeH2NjYcpc1btyYtWvX3uUaiYiIiIiIVIwuXbrQokULxo4dy9ixYzl9+jRz5sxh8ODB5gT566+/Zty4cXzwwQc0aNCA3bt3s2fPHh555BFq1qzJ7t27mTp1KhEREeYkul+/fvz1r39l4sSJxMbG8t1337F48WImTpx40zo5lP72fU5S6RUXF3Py5Mlyl1WtWtX8nm8REREREXlwfPXTJxVdhZvyd+l7R+IeP36cP/3pT2RnZ1O9enX69+/PmDFjqFKlCgA7duzgueeeY9OmTTRt2pT9+/fz5z//me+//x6TyUTTpk158sknGTJkCAaDwRw3NzeXt956i7179/LQQw8RHR193U7PX1OiLSIiIiIich94kBPtykZDx+We9vCCrTaV/za2K70/y7K6/PqeXQDotcH6GBt6lcWwtR6Prt9mdXmATb070//zf1hdflWPsucWdFhqfYycqLIYttbjSRvKr/nvftgjRve11h+TLeGdbTqvoOzcssd+BKVbX48dA8vO75e3ZVodY17nUJ614YmiAGndutn0HdnUuzMAvoutb8+9z5W1Z1Sm9detpaFdecqG8gDLQ+1z3fNM3Gh1jCNvPAbY3ha2nN9Qdo7322h9jIzHyo7pgE3Wx1jxaFkMW4/JoC22fUc+7t7NLueFPX5HBm62/rxID+tKdY9nrC4PcOnoEkLXWX+9yOxTdr2w9ZoTbsPxAFjbs4vNv0Ngn3/jPLLC+hj/HNCF52z8DVjcrZtd2kLkdijRFhERERERuQ84OFR0DeQqx4qugIiIiIiIiMj9RIm2iIiIiIiIiB0p0RYRERERERGxIyXacstGjhzJyy+/bDFv7dq1eHl58cEHH1jMnzhxIoMGDbqb1RMREREReaA53AN/Dwol2g8Qk8lkU/nAwEBycnIoKSkxz8vOzqZRo0ZkZ2dbrLtz504CAwOt2s7ly5dtqqeIiIiIiEhFUqJdQQoLC3n99dfx9/cnJCSEJUuWEBkZSUpKCgDnzp1jwoQJBAUF0b59e4YOHcqhQ4fM5VNSUoiMjCQ9PZ3u3bvTsWNHJk2aZJGkhoWFMW/ePMaMGUNAQABTpkwBICcnh6ioKPz8/AgNDWXatGm3lNwGBQVx4cIFDhw4YJ6XnZ1NbGwsOTk5XH0l+8mTJzly5AhBQUGYTCbGjx9PWFgYfn5+9O7dm+XLl1vEjY6OJjExkcTERIKCgnjttdesb1gREREREZEKpkS7giQlJbFnzx7mz59PamoqmZmZ5Ofnm5ePHj2ac+fOsXDhQtLT0/Hw8CAmJoaioiLzOvn5+Wzfvp3U1FRmzpxJRkYGK1eutNhOamoqPj4+rFmzhpiYGI4ePUpsbCzh4eFkZGQwffp0tm7dyowZM25a51atWlGvXj1z7/WPP/7IsWPH6N+/P1WrViUvLw8oS74NBgMBAQGUlJTQuHFj/vKXv7B27VqGDRvG5MmTycqyfJ/iihUrqFGjBkuXLmX8+PFWt6uIiIiIyIPK0aHy/z0olGhXgMLCQlavXk18fDxBQUF4eXkxdepU89DunJwc9u/fz+zZs/Hx8aFZs2a8+eabXLlyhS1btljESkxMpGXLlnTt2pWwsDB27NhhsTw4OJghQ4bg4eGBu7s78+fPJyIigujoaDw9PenQoQPjxo1j+fLl5h7pGwkMDDQn2tnZ2fj4+FCjRg06dOhg3nZ2djZ+fn44OztTrVo1RowYga+vL+7u7gwYMIDw8HDWr19vEbd58+b88Y9/pFmzZjRr1szaphUREREREalwVSu6Ag+igoICTCYTvr6+5nkuLi40adIEgLy8PC5cuEBQUJBFueLiYo4dO2aednd3p0aNGuZpV1dXi2HdAD4+PhbTubm55OXlsXr1avO8kpISiouLOX36NG5ubjese2BgILNnz6akpISdO3fSsWNHADp27MiXX37J888/T3Z2NuHh4eYyH330EStWrOD48eNcvnwZk8l0zf3bv62niIiIiIjIvUqJdiV08eJFGjZsyKJFi65ZVqdOHfPnqlUtD5+Dg8M1vdK/TsQBioqKGDx4cLlPBK9Xr95N6/br+7R37tzJuHHjAOjQoQMpKSmcPHmSw4cPmxPptWvXMm3aNMaPH4+fnx81a9bknXfe4d///vcN6ykiIiIiIrfnARqZXekp0a4ATZs2xcnJib1799KgQQMAzpw5w/HjxwHw9vbm1KlTGAwGGjVqZNdte3t7c/DgQTw9Pa0q37JlS+rXr8+nn35Kfn4+7dq1A8DLy4vS0lLS0tLM92cD7Nq1iw4dOhAVFWWOceTIEapVq2b7zoiIiIiIiFRCuke7AhiNRiIiIkhOTiY7O5u8vDzGjx+Pk5MTDg4OBAcH4+vry/Dhw9m2bRvHjh0jJyeH5ORkiyePW2PYsGHs3LmTxMREcnNzyc/P57PPPiM5OfmWY3Ts2JGPPvqINm3aYDQagbLe9Hbt2pGWloa/v785kfb09GTPnj1s27aN/Px8kpOTOXjwoE37ICIiIiIiUpkp0a4g8fHx+Pr6Ehsby7Bhw+jevTuNGzfGYDDg6OhIamoq/v7+xMXF0bt3b8aNG8fPP/9M3bp1bdpumzZtWLx4MQcPHiQqKooBAwbwt7/9jYYNG95yjKCgIIqKisz3Z18VGBhIUVGRxf3XUVFR9OjRg1GjRhEVFYXJZGLAgAE27YOIiIiIiFzLwaHy/z0oNHS8ghiNRmbNmmWePn/+PElJSeYh3UajkYSEBBISEsotP2LECEaMGGExLy4uzmJ68+bN5Zb19/cv9/7vW/XMM8/wzDPPXDM/JiaGmJgYi3kGg4GkpKQbxvvwww+trouIiIiIiEhlo0S7guzbt48jR47g6+vL2bNnmTt3LkajkZCQkIqumoiIiIiIiNhAiXYFKS0tJTU1lcOHD2MwGPD19SUtLa1Cn76dk5NDbGxsucsaN27M2rVr73KNRERERETkVj1AI7MrPSXaFcTX15dVq1ZVdDUs+Pj4WLxf+9d++yoxERERERERKZ9D6W9fvCwiIiIiIiL3nG/OflLRVbipNnX7VnQV7gp1U8o9LfD/ZdlUPvv3XXh0/Tary2/q3RnALjH6bfyH1TEyHguh92e2tcX6nl149osvrC6f1q0bAN3XWt8WW8LL2iLchn1Z27OLTW2xvmcXALvE6PaJ9W3xRd/ONpW/GsMe+/HYp9bXY+PjZcf0qcytVsdYHtqVXhtsO7839Opi83cMIHSd9W2R2cc+3/X+n1tfHmBVD9uuF/Y6vwEGbLJ+X1Y8GmJTW0JZe9p6vQF40oZjsqZH2bll6zGpLOeFPdrC1vPClu8plH1Xq3tc+9DXW3Xp6BLA9n8b2HLthbLrrz2+p/Y4L2xtC3v8BtgSY0OvLjZt/27S0PHKQ6/3EhEREREREbEjJdoiIiIiIiIidqREW0RERERERMSOdI+2iIiIiIjIfcBRN2lXGurRFhEREREREbEjJdr3oJEjR/Lyyy9bzFu7di1eXl588MEHFvMnTpzIoEGDbN5mSkoKkZGRNscRERERERG53ynRrgAmk8mm8oGBgeTk5FBSUmKel52dTaNGjcjOzrZYd+fOnQQGBtq0PXu6fPlyRVdBREREROS+5HAP/D0oHvhEu7CwkNdffx1/f39CQkJYsmQJkZGRpKSkAHDu3DkmTJhAUFAQ7du3Z+jQoRw6dMhc/mpPb3p6Ot27d6djx45MmjTJIqEMCwtj3rx5jBkzhoCAAKZMmQJATk4OUVFR+Pn5ERoayrRp024pEQ0KCuLChQscOHDAPC87O5vY2FhycnIoLS0F4OTJkxw5coSgoCAATpw4wciRI2nfvj1BQUGMHDmSkydPmmP885//ZMCAAbRt25aOHTsyePBgzpw5w8qVK3nnnXfYv38/Xl5eeHl5sXLlyttqn6VLlxIWFmaui5eXF//v//0/XnrpJdq2bUvfvn3Jycm5vYMnIiIiIiJSCT3wiXZSUhJ79uxh/vz5pKamkpmZSX5+vnn56NGjOXfuHAsXLiQ9PR0PDw9iYmIoKioyr5Ofn8/27dtJTU1l5syZZGRkmBPRq1JTU/Hx8WHNmjXExMRw9OhRYmNjCQ8PJyMjg+nTp7N161ZmzJhx0zq3atWKevXqmXuvf/zxR44dO0b//v2pWrUqeXl5QFnybTAYCAgIwGQyMXToUOrWrcuSJUtIS0ujtLSUV155hZKSEn755Rdee+01goKC+OSTT/j444+JiIgAoE+fPsTExNC6dWuysrLIysqiT58+t9U+mZmZvPvuuyxdutQ8/91336V///6sWbMGLy8vxowZY3Nvv4iIiIiISEV7oBPtwsJCVq9eTXx8PEFBQXh5eTF16lRzspeTk8P+/fuZPXs2Pj4+NGvWjDfffJMrV66wZcsWi1iJiYm0bNmSrl27EhYWxo4dOyyWBwcHM2TIEDw8PHB3d2f+/PlEREQQHR2Np6cnHTp0YNy4cSxfvtzcI30jgYGB5kQ7OzsbHx8fatSoQYcOHczbzs7Oxs/PD2dnZ9atW4ejoyNvvfUWDz/8MK1atSIpKYnc3Fz27dtHYWEhFy5coHv37ri7u9OqVSt+//vfU69ePZydnalRowZVqlTB1dUVV1dXnJ2db7l9fvnlF5KTk2ndujVeXl7m+QMGDODxxx/nd7/7Ha+99honTpzg6NGj1hxKEREREZEHnoNDaaX/e1A80K/3KigowGQy4evra57n4uJCkyZNAMjLy+PChQvm4c5XFRcXc+zYMfO0u7s7NWrUME+7urpaDOsG8PHxsZjOzc0lLy+P1atXm+eVlJRQXFzM6dOncXNzu2HdAwMDmT17NiUlJezcuZOOHTsC0LFjR7788kuef/55srOzCQ8PN2/v+++/JyAgwCLOlStXOHr0KH5+fjzxxBMMGzaM4OBgunTpQu/evXFxcbluHW61fZo2bUrdunWvKf/rpNvV1RWAM2fO0KJFixvuu4iIiIiISGX2QCfaN3Px4kUaNmzIokWLrllWp04d8+eqVS2b0cHB4Zpe6V8n4gBFRUUMHjy43CeC16tX76Z1+/V92jt37mTcuHEAdOjQgZSUFE6ePMnhw4fND0IrKirCz8+P5OTka2JdTaanT5/O888/z9atW1m1ahVz5sxhyZIltGrVqtw63Gr7VK9evdzyv243B4eyRyP8+gFvIiIiIiIi96IHOtFu2rQpTk5O7N27lwYNGgBlParHjx8HwNvbm1OnTmEwGGjUqJFdt+3t7c3Bgwfx9PS0qnzLli2pX78+n376Kfn5+bRr1w4o6yUuLS0lLS3NfH/21e1t2LABFxcXjEbjdeP6+Pjg4+PDK6+8Qnh4OBs2bKBVq1Y4OTldkwTfyfYREREREZHb8yA91buye6Dv0TYajURERJCcnEx2djZ5eXmMHz8eJycnHBwcCA4OxtfXl+HDh7Nt2zaOHTtGTk4OycnJFk/WtsawYcPYuXMniYmJ5Obmkp+fz2effVZuj/P1dOzYkY8++og2bdqYk2cHBwfatWtHWloa/v7+VKtWDYB+/fpRq1YtXnvtNXJycjh27BhffvklCQkJnD9/nmPHjjFz5kx2797NDz/8wJYtWzhx4gTNmzcHoEmTJhw9epTc3FzOnDnD5cuX72j7iIiIiIiI3Kse6B5tgPj4eCZNmkRsbCy1a9dm+PDhFBQUYDAYcHR0ND9JPC4ujrNnz+Lm5kZgYGC59xzfjjZt2rB48WLmzJlDVFQUjo6OeHp6mp/0fSuCgoJYv369+f7sqwIDA8nMzLR4f3aNGjVIS0tjxowZvPrqqxQVFdGoUSM6d+5MtWrVqF69OocOHWLVqlWcPXuWhg0b8sorr5ifLt6rVy82btxIdHQ058+fZ+rUqURGRt6x9hEREREREblXPfCJttFoZNasWebp8+fPk5SUZB7SbTQaSUhIICEhodzyI0aMYMSIERbz4uLiLKY3b95cbll/f/9y72++Vc888wzPPPPMNfNjYmKIiYm5Zn6DBg2YPn16ubGqVavGu+++e91tGQwG5s6de818a9oHML+C7KqaNWteM09ERERERG6dg8aOVxoPfKK9b98+jhw5gq+vL2fPnmXu3LkYjUZCQkIqumoiIiIiIiJyD3rgE+3S0lJSU1M5fPgwBoMBX19f0tLSrnlK+N2Uk5NDbGxsucsaN27M2rVr73KNRERERERE5FY5lP72PVRS4YqLizl58mS5y6pWrWp+z7eIiIiIiMhV31/IqOgq3FTzWv0qugp3xQPfo10ZOTs7W/3arwdN97XbbCq/Jbwz/T//h9XlV/Uou8VgwCbrY6x41D4xwj/Lsro8wNqeXRi4eavV5dPDugLw2KfWH5ONj3cGsGlf1vbsQq8N1pff0KsLgF1ihK6zvi0y+3S2qS2hrD1tbUuA3jbEWP/fGLZ+z560oTzAmh4hdtkPe5wX/TZavy8Zj4Xw6HrbzotNvW07t65+T209vwGb9mVT7842HQ8oOyb2aAt7/I7YWg97/AbY4/y2R1vY8n1f08M+3xFbz02A6h7XPkfnVl06usSm7xiUfc/ssR/2OC9sPab2OL/t8Xt4L3igXylVyehYiIiIiIiIiNiREm0RERERERERO9LQcRERERERkfuAXu9VeahHW0RERERERMSOlGhXMpGRkaSkpADg5eVFZmZmBdfIPgoKCvDy8uLbb7+97jqZmZl4eXndxVqJiIiIiIjYn4aOV2JZWVnUqVPnjm4jPj6eoqIi5s6de0e306hRI7KysnjooYfu6HZERERERB5UGjleeahHuxJzdXXFYDBcd7nJZLqLtbmxy5cv33B5lSpVcHV1pWpV/d+OiIiIiIjc35RoV6CLFy8yZswY/P39CQkJ4aOPPrJY/uuh41eHXq9bt45Bgwbh4+PD559/DsDy5cvp1asXvr6+9OnThxUrVljE+eGHHxg1ahQdO3bE39+f3//+9+Tl5ZGSksKqVavYsGEDXl5eeHl5sWPHDgByc3OJjo7G19eXRx55hMmTJ1sk09HR0SQmJpKYmEhQUBCvvfbaDfe1vKHjmZmZ9OzZEz8/P2JiYjh58qT1jSkiIiIiIlJJqHuxAiUnJ7Nr1y7+9re/8dBDDzFt2jTy8/MJDQ29bplZs2YRHx+Pl5cX1atX5+9//zvvvPMOkyZNwsvLi7179/LGG29Qp04devToweXLl3nhhRdo2LAh7733HvXq1ePrr7+mpKSEmJgYDh06RHFxMZMnTwagTp06FBUVMXToUDp27MiKFSs4deoUEydOxNHRkYkTJ5rrsmLFCqKjo1m6dOlt7/vx48cZMWIEzz33HAMHDmT37t1Mnz799htRREREREQAPXW8MlGiXUEKCwtZuXIls2fPplOnTgAkJSURFhZ2w3IvvPACPXr0ME+npKQwfvx48zx3d3cOHDjAsmXL6NGjB2vXruXMmTOkp6dTq1YtADw9Pc3lnZ2dKSkpwdXV1Txv1apV/PLLLyQlJeHs7MzDDz9MXFwc48aN4w9/+AM1atQAoHnz5vzxj3+0av+XLl1K8+bNGTdunDnW/v37r+nVFxERERERuddo6HgFKSgowGQy4efnZ57n5uZG48aNb1jOx8fH/LmoqIijR48SHx9PQECA+W/RokUcPXoUgLy8PLy9vc1J9q04dOgQ3t7eODs7m+e1b98ek8lkjvvbutyu77//nrZt21rM8/f3tzqeiIiIiIhIZaEe7XtM9erVzZ+LiooAmDp1Kv/zP/9jsd7deOjY1Z5tERERERGpeBo5XnmoR7uCNG3aFCcnJ77++mvzvNOnT/PDDz/ccoz69evj6urKsWPH8PT0tPhr0qQJUPZAtQMHDnDhwoVyYzg5OXHlyhWLeS1atODAgQMUFxeb5/3rX//CyckJDw+P29nN62revLnFvgPs2bPHLrFFREREREQqkhLtCmI0GomIiCA5OZkdO3aQm5tLfHw8Tk5OtxXn1VdfZd68eaSlpZGfn09ubi7Lli3j448/BiA8PJx69erx2muvsXv3bo4ePcq6dev45ptvAGjSpAm5ubnk5+dz5swZTCYT/fr1o2rVqsTHx/Pdd9+RlZVFcnIyzzzzjN16sZ9++mkOHTrEjBkzyM/PZ9WqVaxbt84usUVERERERCqSEu0KFB8fT9u2bXnxxRcZNmwYoaGhNGvW7LZiPPPMMyQkJLB8+XL69evH888/z7p163B3dwfAYDDw/vvvU6tWLYYOHcqTTz7J4sWLqVKlCgBPPfUUnp6eREZG0qlTJ3bt2kWNGjVYuHAhP/30E5GRkYwZM4YePXowduxYu+1706ZNmTNnDhs2bOCJJ55gzZo1jBw50m7xRUREREREKoru0a5ARqORmTNnWsx79tlnzZ/z8vLMn5s2bWox/WsRERFERERcdztNmjThnXfeKXdZvXr1eP/996+Z37p1az788MPrxrzRsvKUV/8ePXpYPEEdyv7jQEREREREbp+jbtKuNNSjLSIiIiIiImJH6tEWu/j73/9OQkJCucvat29PamrqXa6RiIiIiIhIxXAoLS0trehKyL2vsLCQn376qdxlzs7ONGjQ4C7XSERERETkwXKiKKOiq3BTjWr0q+gq3BXq0Ra7MBqNGI3Giq6GiIiIiIhIhVOiLfe0xz7dZlP5jY935tH11sfY1LszAL02ZFkdY0OvLgCEf2Z9jLU9u9hUh6v16LfxH1aXz3gsBIDQdda3Z2Yf+7SnPY6HPWLYcn5ufLyzXY5pbxvOq/U9y/bjyc+tPy/W9Cg7L2ythy3fDyj7jthjP2w9pvaIYct+QNm+2OO6Z49zy9bvWX8b22JVjxC77Ic9zgtbr7/d19r2e7gl3LZrztXrXmVoT3tcL+xxTG39PazuYbKF9ZwAACAASURBVNsDYi8dXWKXY2qP64Wt7WnLeQVl55Y9zk2R26FEW0RERERE5D7g4KC7gisLPXVcRERERERExI6UaIuIiIiIiIjYkYaOi4iIiIiI3AccKroCYqYebbkr4uPjGTly5A3XiYyMJCUl5S7VSERERERE5M5Qj/Y9Ljo6Gh8fH+Li4u74thITE9m1axfffvstDz/8MCtXrrzlshMnTkSvbBcRERERkQeBEm0BwGQy4eTkdNP1BgwYwJ49ezh48OBtxa9Vq5a1VRMRERERkVvgoLHjlYaGjlcCW7ZsISoqig4dOhAUFMSrr77KiRMnzMvz8vIYNmwYAQEBtGvXjujoaE6ePEl8fDzZ2dm8//77eHl54eXlRUFBAQD//Oc/iYyMxMfHh5CQEN555x1KSkrMMcPCwpg3bx5jxowhICCAKVOm3LSeb7zxBoMHD8bd3f229/G3Q8cvXrzImDFj8Pf3JyQkhI8++ui2Y4qIiIiIiFRG6tGuBC5dusTQoUN5+OGHKSwsZObMmfzhD39g6dKl/Pzzzzz33HMEBweTlpaGs7Mz//rXv7hy5QoTJ07k8OHDtG7dmldffRWAevXq8e9//5sXX3yRp556iunTp/Ptt9/y5ptvYjQaGTJkiHm7qampvPbaa4wcORKHu/zfX8nJyezatYu//e1vPPTQQ0ybNo38/HxCQ0Pvaj1ERERERETsTYl2JdC7d2+L6bfeeotHH32Uf//736Snp1O3bl1mzJhBlSpVAGjRooV5XScnJ6pXr46rq6t53scff4y7uzsTJ07EwcGBFi1aUFBQwMKFCy0S7eDgYIvpu6WwsJCVK1cye/ZsOnXqBEBSUhJhYWF3vS4iIiIiIvcLjRyvPJRoVwKHDx/mL3/5C3v27OHnn382z//hhx/Iy8ujffv25iT7Vhw6dIiAgACLXup27doxY8YMCgsLMRqNAPj4+NhvJ25DQUEBJpMJPz8/8zw3NzcaN25cIfURERERERGxJyXalcDLL7+Mu7s7U6ZMwdXVlYsXL/L73/8ek8l0R7dbo0aNOxpfRERERETkQaSHoVWwn3/+mfz8fIYPH84jjzxCixYtOHv2rHm5l5eX+Z7s8jg5OV2zrEWLFuzevdvidVq7du2iQYMG5t7sitS0aVOcnJz4+uuvzfNOnz7NDz/8UIG1EhERERERsQ8l2hWsTp061K1bl2XLlnH06FG2bdvGzJkzzcsHDx7M2bNnGTt2LPv37yc/P5/09HRzUtqkSRP27NnD8ePHOXPmDCUlJQwaNIhjx47x9ttv8/333/Ppp58yf/58YmJibKrrkSNH+Oabbzh9+jT/+c9/+Oabb/jmm29uO47RaCQiIoLk5GR27NhBbm4u8fHxt/R6MRERERERKZ/jPfD3oHiQ9rVScnR0ZPbs2Xz99deEh4czY8YMxo0bZ17+0EMP8cEHH/Dzzz8zaNAgBg4cyCeffELVqmWj/q8mz3369KFTp0788MMPNGzYkPfee49du3bxxBNP8Pbbb/P888/z3HPP2VTXN954g4iICJYtW8bBgweJiIggIiLCqljx8fG0bduWF198kWHDhhEaGkqzZs1sqp+IiIiIiEhloHu0K4Hg4GDWrVtnMS8vL8/8uXXr1vzv//5vuWWbNWvGsmXLrpn/yCOPsHLlyutuc/Pmzbddzw8//PC2y1yVlJRkMW00Gi167gGeffZZq+OLiIiIiIhUFkq0RURERERE7gMOer9XpaFEWwCYN28e8+fPL3dZv379eOutt25YPjw8/LoPM1uwYAEdOnSwuY4iIiIiIiL3AofSXz+aWh5YZ8+e5dy5c+UuMxqNuLi43LD88ePH+eWXX8pd1qBBA5ydnW2uo4iIiIiIXN+Z//y9oqtwU/WqPVHRVbgr1KMtANStW5e6detaXb5JkyZ2rM2te3T9NpvKb+rdmV4bsqwuv6FXFwD6bfyH1TEyHgsBbNuXTb0726Ut7LEf4Z9Z355re5a1p63HxB77URmOafe1th3TLeGdefJz6/djTY+y/bDHd8TWGLacV1B2bvW2Icb6/56bth5TsP070t+GYwqwqkeIXb6noeusb4vMPmVtYev5acsxhbLjao/z+6nMrVbHWB7aFbD9O2KPtrDHdc8e54Wt9bDHtbPbJ9bH+KJv2X7Yer2w5ZyAsvOiusczVpe/dHQJUDl+D+1xftvj+n1v0NjxykJPHRcRERERERGxIyXaIiIiIiIiInakoeMiIiIiIiL3AQcNHa801KMtIiIiIiIiYkdKtOWuiI+PZ+TIkTdcJzIykpSUlLtUIxERERERkTtDQ8fvcdHR0fj4+BAXF3dHt5Obm/v/2bvvsCiu9uHj31VRUAwEgw3RKEYsiIIaFEEDaowoKGAs2DWxYosNS4zBBogaY6+xYEfQYMNesCWWqPGJ2LCgYkWN2GjvH/yY15W27K6K5v54eV3szJ57zszOlnvOmXNYsGABJ06c4NGjR1hYWNC+fXs6deqkUfnRo0cjM8kJIYQQQgjx9qhU0o6aV0iiLQBITEzEwMAgy/V///03ZmZmTJkyhVKlSnHy5EnGjh1LgQIFaN8+56kjihYtqs/qCiGEEEIIIUSeJYl2HrBv3z7mzZvHpUuXyJ8/P7Vr12bMmDGUKlUKgOjoaKZMmcKJEydQqVRUq1aN4OBgpk+fzh9//MEff/zBkiVLANi9ezdlypTh6NGjBAUFceHCBT799FPatm1L3759yZcv7SqXq6srbdq04dKlS+zevZtWrVrx008/ZVnH1q1bqz22tLTkr7/+YufOnRol2n5+fjx79oxff/0VgISEBH766Sd27dpF0aJF6d27t1bHTgghhBBCCCHyGkm084Dnz5/To0cPKlWqxNOnT5k6dSqDBw9mzZo1xMfH07lzZxwdHQkJCcHQ0JATJ06QnJzM6NGjuXr1KpUrV6Zfv34AmJmZERcXR8+ePWnTpg1TpkzhwoUL/PjjjxgbG9O1a1dlu4sWLcLX15cBAwagUuV+hMJ///0XExMTrfY5MDCQkydPMnfuXD799FOCgoKIiYnBxcVFq3hCCCGEEEIIkVdIop0HNGvWTO2xv78/jRo1Ii4ujtDQUExNTQkODiZ//vwAWFlZKc81MDDAyMgIc3NzZdmqVauwtLRk9OjRqFQqrKysiI2NZfHixWqJtqOjo9rj3Dh16hTbt29n4cKFuS779OlTwsLCmD59OvXq1QMgICAAV1dXreoihBBCCCGEAGR6rzxDEu084OrVq8yYMYPTp08THx+vLL916xbR0dHUqlVLSbI1cfnyZezs7NRaqe3t7QkODubp06cYGxsDYGNjo1V9L168SN++fenfv7+SKOdGbGwsiYmJ2NraKsuKFy9O6dKltaqPEEIIIYQQQuQlkmjnAb1798bS0pJJkyZhbm5OQkIC3377LYmJiW91u4ULF851mUuXLtGlSxfatGlDr1693kKthBBCCCGEECJ3bt26xbhx4zh27BiFCxfG09OTIUOGZNlgeezYMTp37pzpuvXr12Nra0tsbCyNGjXKsH7t2rXUrFkz2/pIov2excfHExMTw+TJk7GzswPgwIEDynpra2siIiJITk7O9CQxMDAgOTlZbZmVlRW7d+8mNTVVadU+efIkJUqUUFqztXHx4kW6dOlCq1atGDx4sNZxypQpg4GBAWfOnKFJkyYA3Lt3j1u3bmkdUwghhBBCiP861X+063hycjK9evXis88+Y82aNdy9e5cRI0ZQqFAhBg4cmGkZOzs7oqKi1JbNmDGDI0eOUL16dbXlK1asoHz58spjU1PTHOskE629ZyYmJpiamrJ27VquX7/OoUOHmDp1qrK+Q4cOPHr0iGHDhnHu3DliYmIIDQ1VklILCwtOnz7NzZs3efjwISkpKfj4+HDjxg0mTpzIlStX2L59O/Pnz6d79+5a1/PChQt07tyZ+vXr061bN+7du8e9e/d4+PBhrmMZGxvTqlUrAgMDOXbsGOfPn8fPzy/b6cWEEEIIIYQQIjNRUVFcvnyZKVOmUKVKFRo2bMjAgQMJCQnJspdwwYIFMTc3V/6bmpqye/duvLy8MgwUbWpqqvZcTfIWSbTfs3z58jF9+nTOnDlD8+bNCQ4OZvjw4cr6Tz/9lGXLlhEfH4+Pjw+tW7dm8+bNFCiQ1hkhPXl2c3OjXr163Lp1i5IlS7JgwQJOnjyJh4cHEydOpEuXLll2jdBEZGQkDx8+5Pfff8fJyUn5/+a0X5ry8/OjRo0a9OzZk++++w4XFxe1q0RCCCGEEEKIj8+TJ0+IjY3N8P/Jkydax/zrr7+oXLkyn332mbLMycmJJ0+ecOXKFY1i7Nmzh0ePHuHt7Z1hXc+ePXF0dMTHx4d9+/ZpFE+6jucBjo6ObN26VW1ZdHS08nflypX57bffMi1bvnx51q5dm2F53bp1CQsLy3Kbe/bsyVUd+/fvT//+/XNV5nUBAQFqj42NjdVa7gE6duyodXwhhBBCCCFE3u86vmzZMmbNmpVhua+vr9b5xv379ylWrJjasvSk+/79+1hbW+cYIzQ0FCcnJ0qWLKksK1y4MH5+ftjb26NSqYiMjKR3797Mnz+fhg0bZhtPEm0hhBBCCCGEEO9Ely5d8PT0zLD8k08+ybBs5syZmSblr9u/f7/OdYqLiyMqKopffvlFbbmZmRndunVTHtva2nLv3j0WLVokibbQzLx585g/f36m69zd3fH398+2fPPmzbMczGzhwoXUrl1b5zoKIYQQQgghPmyffPJJpkl1Zjp06ICbm1u2z/nss8/47LPPOHfunNry+/fvK+tzsmHDBkxNTXF1dc3xuTVq1ODYsWM5Pk+VmpqamuOzxEfv0aNHPH78ONN1xsbGGbpivOnmzZskJSVluq5EiRIYGhrqXEchhBBCCCFE1p4k7nzfVcjRJwZN9B5z//799OnTh6ioKMzMzIC0KbiCg4M5fPhwtoOXpaam0rhxY77++mtGjBiR47bGjBnD+fPnCQ0NzfZ50qItgLSR9DQZpj4rFhYWeqyNEEIIIYQQQmjGyckJKysrhg0bxrBhw7h37x6//PILHTp0UJLsM2fOMHz4cJYtW0aJEiWUskePHiU2NjbTQZ7Dw8MxMDCgSpUqAOzcuZMNGzYwefLkHOskibb4oH215ZBO5fc1r0+T7drH2PlNfQCa74jK4ZlZ2/K1EwAtdx3UOsamxs6479S+PEBEE2ea6bAf2/5vP/RxLHR9TVy2al9+r1vaa6qPGI22aR9jd7P6NI3U/lgCRDZ1wlOH8yq8sTOATudWRJO0GLqeF7qcE5B2XujjWOjj/Nb1eOpSh/R66OP8zgufnfo4Fvo4v3V5r0Y2ddJLDF0+byDtM0cf57c+3md54bNTH9+HeeE11cf5bVS2vdYxnl9fDeSNY6GP96nIu/Lnz8+8efMYN24cbdu2xcjICE9PT7XB1Z4/f05MTEyG6b5CQ0Oxs7PDysoq09hz5szh1q1b5M+fHysrK2bMmMHXX3+dY50k0RZCCCGEEEKIj0LeH3X8bbGwsGDhwoVZrndwcFCb2SndmzMhvc7T0zPTgds0IfNoCyGEEEIIIYQQeiSJthBCCCGEEEIIoUeSaIt3ws/PjwEDBmT7HC8vL2bOnPmOaiSEEEIIIcTHRfUB/PuvkHu0P3CdOnXCxsZGo6HodfHkyRN++OEHoqOjiY+Pp1ixYjRq1IgffvgBY2PjHMuPHj0amUlOCCGEEEII8V8gLdoCIMPoe29SqVS4uLgwZ84cIiMjCQgI4MiRI4wbN06j+EWLFtV4YnohhBBCCCGE+JBJop0H7Nu3j3bt2lG7dm0cHBzo168ft2/fVtZHR0fz3XffYWdnh729PZ06deLOnTv4+fnxxx9/sGTJEqytrbG2tiY2NhZImw/Oy8sLGxsbnJ2dmTVrFikpKUpMV1dX5s2bx9ChQ7Gzs2PSpEnZ1rFo0aJ06NCB6tWrY2FhQb169Wjfvj0nT57UaB/f7DqekJDA0KFDqVmzJs7OzqxcuTI3h0wIIYQQQggh8izpOp4HPH/+nB49elCpUiWePn3K1KlTGTx4MGvWrCE+Pp7OnTvj6OhISEgIhoaGnDhxguTkZEaPHs3Vq1epXLky/fr1A8DMzIy4uDh69uxJmzZtmDJlChcuXODHH3/E2NiYrl27KttdtGgRvr6+DBgwAJUqd/dL3Llzh507d/Lll19qtc+BgYGcPHmSuXPn8umnnxIUFERMTAwuLi5axRNCCCGEEOK/7r90D3ReJ4l2HtCsWTO1x/7+/jRq1Ii4uDhCQ0MxNTUlODiY/PnzA6hNpm5gYICRkRHm5ubKslWrVmFpacno0aNRqVRYWVkRGxvL4sWL1RJtR0dHtcea+OGHH9i9ezcvXrzA1dUVf3//XO/v06dPCQsLY/r06dSrVw+AgIAAXF1dcx1LCCGEEEIIIfIa6TqeB1y9epXBgwfj6uqKnZ0d7u7uANy6dYvo6Ghq1aqlJNmauHz5MnZ2dmqt1Pb29ty9e5enT58qy2xsbHJd15EjRxIWFsacOXO4fv06QUFBuY4RGxtLYmIitra2yrLixYtTunTpXMcSQgghhBBCiLxGWrTzgN69e2NpacmkSZMwNzcnISGBb7/9NscBynRVuHDhXJcxNzfH3NwcKysrTExM6NChA3369KFYsWJvoYZCCCGEEEIIzUk7al4hr8R7Fh8fT0xMDH379qVu3bpYWVnx6NEjZb21tbVyT3ZmDAwMMqyzsrLi1KlTatNpnTx5khIlSmg0FVdu5faCQJkyZTAwMODMmTPKsnv37nHr1i19V00IIYQQQggh3jlJtN8zExMTTE1NWbt2LdevX+fQoUNMnTpVWd+hQwcePXrEsGHDOHfuHDExMYSGhipJqYWFBadPn+bmzZs8fPiQlJQUfHx8uHHjBhMnTuTKlSts376d+fPn0717d63refDgQUJDQ4mOjiY2Npb9+/czbtw46tSpQ8mSJXMVy9jYmFatWhEYGMixY8c4f/48fn5+GBgYaF0/IYQQQgghhMgrJNF+z/Lly8f06dM5c+YMzZs3Jzg4mOHDhyvrP/30U5YtW0Z8fDw+Pj60bt2azZs3U6BAWq//9OTZzc2NevXqcevWLUqWLMmCBQs4efIkHh4eTJw4kS5dutC5c2et61moUCFCQ0Pp0KEDbm5uTJo0ia+++oo5c+ZoFc/Pz48aNWrQs2dPvvvuO1xcXChfvrzW9RNCCCGEEOK/TqVS5fn//xVyj3Ye4OjoyNatW9WWRUdHK39XrlyZ3377LdOy5cuXZ+3atRmW161bl7CwsCy3uWfPnlzV8csvv2TNmjW5KvO6gIAAtcfGxsZqLfcAHTt21Dq+EEIIIYQQQuQV0qIthBBCCCGEEELokbRoCwDmzZvH/PnzM13n7u6e43zZzZs3z3Iws4ULF1K7dm2d6yiEEEIIIYTIzn+na3ZeJ4m2AKBdu3Y0a9Ys03WajFS+YMECkpKSMl1XokQJneomhBBCCCGEEB8SVerrc0AJIYQQQgghhPggJSQdeN9VyFGRAg3edxXeCWnRFh8059+jdCp/0MOJNnu1/0Ba55L2QaGPGK33aB8j1LUBtdcc1Lo8wPF2zny15ZDW5fc1rw+gUz2Ot3MGoOuB/VrHWNqgIb5H9mpdflY9FwC9xGi2Q/vzc9vXTjTXoTzAlq+ddK4DoFM9tvxfDF3fI+47dTu/I5o40zRS+/2IbJq2H3U3aB/jqHdaDM9d2u9LeGNnvRwLfZwX9cO1j3HIUz/n1sf0HtHldY1o4qzTeQVp55Y+joWu5zdASx1ibGrsrNP7FNLeq422af99uLtZ2vehrvvRZLv2dQDY+U19veyHPj47jcq21zrG8+urGXl8t9blASbXbqSX9+mHQCVdx/MMGQxNCCGEEEIIIYTQI0m0hRBCCCGEEEIIPZJEWwghhBBCCCGE0CO5R1sIIYQQQgghPgrSjppXyCuhZ506dSIwMPB9VyPP0eS4ODg4EBYW9o5qJIQQQgghhBBvh7Roi3di5syZFCggp5sQQgghhBDi4yeZj3gnTE1N33cVhBBCCCGE+KjJ9F55h3Qdf4vCw8Px8vLCzs4OJycn/Pz8ePz4sbI+LCwMBwcH9u3bR9OmTbG3t2fAgAH8+++/ynOePn3KkCFDqFmzJs7OzqxevRovLy9mzpwJQGxsLNbW1ly4cEEpc+HCBaytrYmNjQXg4cOHDB48GGdnZ2rUqEHLli3ZtWuXWl3v3LnD999/j62tLU2aNGHnzp0ZunLfvn2bAQMGUKtWLRwcHBgwYAB37tzR6Fi82XX83r179OrVS9leZGRkLo6sEEIIIYQQQuRdkmi/RUlJSQwaNIjff/+dGTNmcOHCBfz9/dWek5CQQEhICL/88guLFi3i1KlTLFiwQFkfEBDA6dOnmT9/PosWLWLv3r3ExMTkqh4vXrzA1taWBQsWEBERgYeHBwMHDuTy5cvKc/z8/Hjw4AEhISFMnTqVJUuWkJCQoKxPTEykR48emJqasnr1akJCQkhNTaVPnz6kpKTk+tj4+flx9+5dZXuLFi1S254QQgghhBBCfKik6/hb9O233yp/W1paMmLECHr06MGUKVPIly/tGkdiYiL+/v6ULl0aAE9PT44ePQqktWZv3LiRX375BQcHBwAmT55Mw4YNc1WP0qVL061bN+Vxjx492LdvH5GRkfTt25fLly9z+PBhNm7cSJUqVQAYO3YsrVq1Usps3bqVfPnyqV0oCAgIoE6dOvz999/Y2tpqXJ8rV64QFRVFeHg4VatWVbbXunXrXO2XEEIIIYQQ4v9TqaTreF4hifZbdPbsWWbNmkV0dDSPHz8mJSWFxMRE7t27R4kSJQAwNjZWkmwAc3NzHjx4AKR1C09MTKR69erK+mLFimFhYZGreiQnJzN37lwiIyO5c+cOiYmJvHz5ks8//xyAmJgYChYsSOXKlZUylStXxsDAQHl8/vx5rly5gp2dXYbY169fz3WiXbBgQSWpB7CxsVHbnhBCCCGEEEJ8qCTRfkuePXvGd999R8OGDQkODsbMzIzLly/j6+tLYmKi8rw3R+JWqVSkpqZqvJ30lvHXyyQlJak9Z/HixaxcuZJRo0bxxRdfYGRkxJgxY9Tqocn+2NraZjpFV7FixTSOI4QQQgghhBAfO0m035IrV67w6NEjhg4dSvHixQE4duxYrmKUKVMGAwMDzp49q7SAP3z4kJs3byrPMTMzA+D+/ftYW1sDaa3Przt58iRNmjTB3d0dSOuufv36daVlvHz58rx69Yro6GilVTs6OlotEa9atSqRkZEUK1YMY2PjXO3HmypUqMCrV6/4559/lK7j586dy1XiL4QQQgghhHiTdB3PK2QwtLekdOnSGBgYEBISwo0bN4iMjGTx4sW5imFsbEyrVq0IDAzkjz/+IDo6mpEjR2JgYKDcf2FoaIitrS0LFy7k8uXLREVFZdhOuXLliIqK4q+//uLixYuMGjVKbWRzKysrHB0dGTNmDGfPnuXs2bOMHz9ebTvu7u4ULVoUX19fjh8/zo0bNzhy5Ag//fQTT548ydV+VahQQdnemTNnOHPmjLI9IYQQQgghhPjQSaL9lpiZmREQEMDmzZtxc3Nj+fLlDBs2LNdx/Pz8qF69Ot9//z3fffcdX331FaVLl6ZgwYLKcyZOnMjTp0/x9PRk1qxZDBgwQC1Gnz59qFy5Mt26daNbt26UL18eJycntecEBARgamqKj48PgwcPpmvXrhgYGFCoUCEAChcuTEhICObm5vTr1w83Nzd++ukn8uXLpzwnNwIDAylWrBgdOnRg0KBBdOvWjSJFiuQ6jhBCCCGEEELkNdJ1XM9WrFih/N2iRQtatGihtj46Olr528vLCy8vL7X1HTt2pGPHjspjY2Njpk2bpjx+8uQJAQEBlCtXTllWqVIlQkNDs9yOqakpc+bMybbeJUqUYNGiRcrjK1eu8OzZM8qWLav2nClTpmQbJyuvHxeA4sWLs3DhQrVl33zzjVaxhRBCCCGEEKCSdtQ8QxLtPO7vv//m2rVrVK9enUePHvHrr79ibGyMs7OzXrdz+PBhXrx4wRdffMGdO3cICAigUqVKVKtWTa/bEUIIIYQQQoiPnSTaeVxqaiqLFi3i6tWrFCxYkOrVqxMSEkLhwoX1up3ExESmTp1KbGwsxsbG1KlTh1GjRmk8F9+b0369bsuWLWpTmAkhhBBCCCHEx0yVmpu5pITIwrVr17JcZ2FhkWEaMyGEEEIIIYR+vUz+431XIUeF8n/5vqvwTkj2I/Ti9XvG36VmO6J0Kr/tayecNmkfI6pl2qByeSFGcx2PxZavnfDefVDr8hsapd3O0GbvAa1jrHNpAECNEO3rcbqjM86/a38sDnqkvR76iOG+U/v9iGjijMvWQ1qXB9jrVp+mkdrvR2TTtP1ouUv7/djUOO28qB+ufT0Oeern/Nbl82Lb12nHop0O5/ea/zu/dXld97rVzzPnhT6OhS6v65avnfRyLBpt0z7G7mb1Ad3f6wBNtmtfj53f1NfL96E+zgtdz2/Q/TOn8/79WpcHWN6woV6Oha7ntz5eU3187unjPTLy+G6tY0yu3Qijsu21Lg/w/PpqvezHh0Gm98or5G55IYQQQgghhBBCjyTRFkIIIYQQQggh9Ei6jgshhBBCCCHER0DTgYzF2yct2kIIIYQQQgghhB5Joi3eibCwMBwcHLJ9TmBgIJ06dXpHNRJCCCGEEEKIt0O6jv/H+fn58ezZM3799de3uh03NzcaNmz4VrchhBBCCCHEf5t0Hc8rJNEWGklMTMTAwEDr8oaGhhgaGuqxRkIIIYQQQgiRN0nX8fcsJSWFefPm0ahRI2xsbHB1dWXZsmUAHD16FC8vL2xsbHB2dmbWrFmkpKQoZa2trdm7d6/yOCEhAWtra44dOwbAwDo6MQAAIABJREFUsWPHsLa25siRI7Rs2ZKaNWvStWtX7ty5A8DMmTMJDw8nMjISa2trpWxsbCzW1tZs3boVHx8fbGxs2LJlC7Vq1WLXrl1q9d+0aRMODg68evUq2/3MrOv43LlzqVevHrVq1WLcuHEkJiZqfyCFEEIIIYQQIo+QRPs9mz17NkuXLmXgwIFs3bqVgIAATExMiIuLo2fPntjb27Np0yZGjRrF0qVLWb58ea63MXPmTH766SfWrFnD/fv3CQwMBKB79+40a9YMFxcXoqKiiIqKws7OTik3bdo0unfvzrZt23BycqJ58+aEhYWpxQ4PD8fd3Z2CBQvmqk6bN29m7ty5DBs2jPXr12NkZJQhthBCCCGEEEJzKvLl+f//FdJ1/D16+fIlCxcuxN/fHw8PDwDKli0LpCW5lpaWjB49GpVKhZWVFbGxsSxevJiuXbvmajuDBw/G3t4egE6dOin3YxcpUgRDQ0NSUlIwNzfPUK5bt240btxYedy6dWt8fHx4+PAhZmZm3L59m2PHjjF8+PBc7/uKFSto06YNXl5eAIwYMYKoqKhcxxFCCCGEEEKIvOa/c0khD7p69SovX77MdDTuy5cvY2dnpzYXnr29PXfv3uXp06e52k6lSpWUv83NzXnw4IFG5WxsbNQe29raUr58eX7//XcgrTW7UqVKVK1aNVf1Abhy5Qo1atRQW/bmYyGEEEIIIYT4EEmi/QFTqVSkpqYqj5OSkjJ9XoEC/7/jwptlsmNkZJRhmbe3Nxs2bABg48aNSou0EEIIIYQQ4n1TfQD//xsk0X6PPv/8cwwNDZXBy15nZWXFqVOn1JLikydPUqJECYyNjQEwMzPj/v37yvrz58/nug4GBgYkJydr/HwPDw9iYmJYtmwZt27dwt3dPdfbBKhQoQKnT59WW/bmYyGEEEIIIYT4EMk92u9RoUKF+P777wkICCB//vzUrFmTu3fvEhsbi4+PD0uXLmXixIn4+Phw4cIF5s+fj6+vr1L+yy+/JCQkBFtbW549e8b06dNzXQcLCwsOHz5MTEwMJiYmFC1aNNvnm5mZ0ahRI6ZMmYKLiwtmZma53iZAhw4d+PHHH7GxsaFGjRqsX7+emzdvYmpqqlU8IYQQQgghhMgrJNF+z/r06YNKpWLatGncu3ePEiVK0LVrV0qWLMmCBQsICgpizZo1fPrpp3Tp0oXOnTsrZf38/PDz86Ndu3ZYWlri5+dH9+7dc7X9Nm3a8Mcff+Dl5cWzZ89Yvnw5FhYW2Zbx8vJi+/btOnUb9/Dw4MaNG0yePJnExESaN2+Ol5cX0dHRWscUQgghhBDiv0z1H+qanddJov2e5c+fn379+tGvX78M6+rWrZvtlFclS5Zk6dKlasteT1QdHBwyJK4uLi5qy8zMzFiyZEmG2NklvPfu3cPc3BxnZ+csn/MmLy+vDIl5VvsthBBCCCGEEB8ySbSFxp4/f87du3dZvHgx7du3VxtkTQghhBBCCCFEGsmUhMYWLVrEvHnzqFu3Lj169FBbN3bsWCIiIjIt16tXL3r37v0uqiiEEEIIIYQQ750qVdO5noTIxoMHD7Kc39vExEQGORNCCCGEEOItS049876rkKP8Ktv3XYV3QhJtIYQQQgghhPgISKKdd0jXcfFBcwyL0qn8YS8nGm4+pHX5/S3qA9AgQvsYB9zTYjSN1H5fIps60XyHbsdiy9dOfLle+xh/fOsE6OdYDDiyV+sYv9ZzwXPXQa3LhzdOG+RPHzFctmp/LPa61WfGuR1alwcYWO1rfrsQqXX5bpWaAtBom/b7sbtZ2mv6XdQ+rWMscvqKqksOaF0e4H/dG9D3sPbn1RxHFwBsV2h/XpzplHZeHIzbonUM55LNGfHnbq3LAwTWaYT7Tu33I6JJ2n400+EzZ9vXaZ8X9qu0r8dJH2ed3qeQ9l6dcGqX1uXH2DUGwCFU+2NxrHXasdD1NfHerdux2NDIma4H9mtdfmmDhgC03qP9ezXUtQEAVRZrH+OfHg34aov2n1kA+5rX1/k7GdDpe3nL1046vccg7X2mj8/vvHAsdNkPSNsXo7LttS7//PpqnbYv/psk0RZCCCGEEEKIj0K+910B8X/klRBCCCGEEEIIIfRIEm0hhBBCCCGEEEKPpOu4EEIIIYQQQnwEVKjedxXE/5EW7f+omTNn4uXl9c62FxYWhoODQ7bPCQwMpFOnTu+oRkIIIYQQQgjxdkiinY1jx45hbW1NQkKC3mP7+fkxYMAAvcfNjLW1NXv3qo+22717dxYvXvxOtg/g5ubG1q1b39n2hBBCCCGEEOJ9ka7jH6jU1FSSk5MpUEC7l7BIkSIUKVJEz7XKmqGhIYaGhu9se0IIIYQQQvz3SNfxvOKDb9FOSUlh3rx5NGrUCBsbG1xdXVm2bBkAR48excvLCxsbG5ydnZk1axYpKSlKWVdXVxYsWMDw4cOxs7OjcePG7NiRNm9tbGwsnTt3BsDe3h5ra2v8/PzUtunq6kqNGjXw9PRk3759Stz0lvAjR47QsmVLatasSdeuXblz5w6Q1m07PDycyMhIrK2tsba25tixY9nuZ3rMAwcO0KpVK2xsbPjf//7H1atX6d27N46OjtjZ2dG2bVuOHz+uto8AvXv3xtraWnn8Ztfx9Bb2efPmUa9ePerVq8f06dPV6nD58mXatWtH9erVcXd358CBAxrVHTLvOj537lzq1atHrVq1GDduHImJiTnGEUIIIYQQQoi87oNPtGfPns3SpUsZOHAgW7duJSAgABMTE+Li4ujZsyf29vZs2rSJUaNGsXTpUpYvX65WfsmSJdSpU4eNGzfSuHFjRowYQXx8PKVKlWLmzJkA7Nq1i6ioKEaPHg3A/PnziYiIYPz48WzevJl27drh6+vL//73P7XYM2fO5KeffmLNmjXcv3+fwMBAIK3bdrNmzXBxcSEqKoqoqCjs7Ow02t9p06YxYsQItm7dyueff05CQgIuLi4sXbqUsLAw7Ozs6NWrFw8fPgQgNDQUgKCgIKKiopTHmTl06BAPHjxg5cqVjBo1ivnz53Pw4EEAkpOT6devH0WLFiU0NJQxY8Ywbdo0jeqcmc2bNzN37lyGDRvG+vXrMTIyIiwsTOt4QgghhBBCCJFXfNBdx1++fMnChQvx9/fHw8MDgLJlywJpCamlpSWjR49GpVJhZWVFbGwsixcvpmvXrkoMFxcXvv32WwAGDRrEsmXLOHv2LA0aNMDExAQAMzMzpZv1q1evmD9/PsuXL8fW1haAtm3bcvToUdatW8e4ceOU2IMHD8be3h6ATp068euvvwJp3bYNDQ1JSUnB3Nw8V/s8aNAg6tWrpzyuVq0a1apVUx77+fmxY8cODh48SMuWLTEzMwPgk08+yXFbZmZmjBo1CpVKRYUKFVi5ciXHjh3D2dmZQ4cOERsby8qVKylWrBgAvr6+9OvXL1f1T7dixQratGmjtKqPGDGCqKgorWIJIYQQQgghQKWSruN5xQedaF+9epWXL19mOpr15cuXsbOzUzvZ7O3tCQ4O5unTpxgbGwNpA4WlMzQ05JNPPlFagzNz7do1nj9/TpcuXdSWJyYmZqhHpUqVlL/Nzc158OBB7nYwEzY2NmqPExISmDlzJvv27eP+/fskJyfz4sULbt++nevYFStWVDter9c5JiYGCwsLJckGqF69upZ7AVeuXKFjx45qy2rUqMG1a9e0jimEEEIIIYQQecEHnWjrQ2aDib1+H/ebnj17BsDChQsztBC/OdjX67FVKhWpqam6VBUAIyMjtceBgYEcPXqU4cOHY2lpiaGhIT179tTqfmcDAwO1x/qqsxBCCCGEEEL8l3zQ92h//vnnGBoaZjoYl5WVFadOnVJLFE+ePEmJEiWU1uycpCeeryfeVlZWGBgYEBcXR7ly5dT+lyhRQuO6GxgYkJycrPHzs3Lq1Cm8vb1p3Lgx1tbWmJqaEhcXp/dtlS9fnps3b6q19p89e1breBUqVOD06dNqy958LIQQQgghhBAfog+6RbtQoUJ8//33BAQEkD9/fmrWrMndu3eJjY3Fx8eHpUuXMnHiRHx8fLhw4QLz58/H19dX4/gWFhaoVCr27t2Lk5MThQoVwtjYmK5duzJx4kSSkpKwt7fnyZMnHD9+nBIlStCsWTONYx8+fJiYmBhMTEwoWrRohhZlTZQrV47IyEgaNmxISkoKU6dOJV8+9esnFhYWHDlyhBo1alCwYEHl3vPcqF+/PmXKlMHPz48hQ4bw+PFj5syZA2h3L0iHDh348ccfsbGxoUaNGqxfv56bN29iamqa61hCCCGEEEII+MDbUT8qH/wr0adPHzp16sS0adNo1qwZw4cP58mTJ5QsWZIFCxZw8uRJPDw8mDhxIl26dFGm7NJEiRIl6N+/P0FBQTg6OjJ+/HgAhgwZQs+ePZk7dy5ubm707NmTI0eOYGFhoXHsNm3aUK5cOby8vKhXrx4nT57M9b5D2uBnRYoUoW3btvj6+vLNN99Qvnx5teeMGDGCgwcP8tVXX+Hp6anVdvLnz8/s2bN58uQJ3t7e+Pv706dPHyDtgkdueXh40LNnTyZPnoy3tzf//vuv2nRjQgghhBBCCPGh+qBbtCEtAezXr1+mo1/XrVs32ymj9uzZk2HZm93QM4utUqno1q0b3bp1yzSug4MD0dHRastcXFzUlpmZmbFkyZIs66ZJTIAyZcqwYsUKtWXpo6inc3V1VebPTte/f3/69++vPA4ICMgQO32U9HRWVlasWbNGeXzw4EFUKhWWlpY51t/LyytDIp3V6yaEEEIIIYQQH7IPPtEW705kZCSffPIJZcqUISYmhgkTJtCwYUNlCjEhhBBCCCHE+6NCpvfKKyTRziPmzZvH/PnzM13n7u6Ov7//O65RRk+fPiU4OJi4uDjMzMxo0KABw4cPB2Ds2LFERERkWq5Xr1707t37XVZVCCGEEEIIId4bVarM35QnPHr0iMePH2e6ztjYWG3+6rzowYMHPH36NNN1JiYmMsiZEEIIIYQQ4j9DEm0hhBBCCCGEEEKPPvhRx4UQQgghhBBCiLxEEm0hhBBCCCGEEEKPJNEWQgghhBBCCCH0SBJtIYQQQgghhBBCjyTRFkIIIYQQQggh9EgSbSGEEEIIIYQQQo8k0RZCCCGEEEIIIfRIEm0hhBBCCCGEEEKPJNEWQgghhBBCCCH0SBJtIYQQQgghhBBCjyTRFkIDcXFxJCYmvrfy+orxsZBjIcT/97///U+n8omJibi7u3P58mWtY+zcuZOkpCStyyclJTF+/HhiY2O1jpFX6Pp65BV//vlnpq9pUlISf/75p0YxNm7cyKtXrzIsf/XqFRs3bsyxfFJSEkuWLOHOnTsabS8ziYmJ9O7dm2vXrmkdQwghtKFKTU1Nfd+VECIvmT59OuXLl6dVq1akpqby/fffExUVhYmJCQsWLKBGjRpvtby+YsyaNYsePXpgZGSktvzFixcsWrQIX1/fLMsmJibi4ODA2rVr+eKLL3Lc1tukj2OhDxs3bsTNzY2CBQuqLX/16hVbt26lVatWOcY4dOgQx44d48GDB6SkpKitmzx5ssZ1efjwITdu3KBKlSoZ6pOTpKQkwsLCsqzH8uXLsy2/dOlSPDw8MDMzy9V2X+fh4YG3tzfu7u46xVmxYgVr1qwhNjaWzZs3Y2lpybx58yhTpgwtWrTIsXyfPn3w9vbGxcWF/Pnza12PO3fucPv27QwXf+rUqZNj2QkTJtC6dWsqV66s9farVq3KF198oRzTTz/9NNcxnJycWLZsGVZWVlrVoXbt2hgYGODu7o63tzfW1ta5jmFvb8+mTZuwtLTUqg4Afn5+WFtb061bN7XlS5cu5cKFC0yaNEnr2JrSx+sBsGfPHuX8Xrx4MaVKlWLNmjVYWlpSv379TMs8f/5c+cx//vx5tvHf/G54U5UqVYiKiqJYsWJqy+Pj43F0dOSff/7JcR/0EcPOzo7NmzdjYWGR43Oz4uDgwLp16yhXrpzWMZKTk7l+/ToPHjzgzZ/OmrzXtTVr1iyNn5vV93peiSHEf02B910BIfTp6dOnLFy4MMskYvfu3TnG2LRpEzNmzABg7969nDt3jnXr1rF582amTJlCSEjIWy2vrxizZ8+mffv2GX5MPX/+nNmzZ2f7RWhgYICpqWmG46ctbX4wptPHsRg5ciSjR4/G2NhYbfmzZ88YP368RknuyJEjcXZ2zvCDMSEhgZEjR+aYaP/yyy/Mnz+fGjVqULx48Ry3l5mnT58ycuRIdu7ciUqlYseOHVhaWjJ27FjMzMwYNGhQjjH8/f2JiIjA1dWVKlWq5LoOq1evJjg4mIYNG+Lt7U3Dhg1znaR+8803rFq1iilTpvDVV18pcfLl07yT1aJFiwgJCaF3795qr5+FhQUrV67UKNE2MzPDz8+PggULKglipUqVNK5DXFwcP/zwAydPnkSlUpGamopKpVLWa5JEXLp0CS8vLypVqoS3tzctWrTIdWK2e/duwsPDWblypdoxbdCggcbHtH379ixZsgR/f3+tLjpERUURGRnJxo0b8fT0pHLlynh5eeHu7o6JiYlGMRo1asTevXvp3Llzrref7sCBA3Tt2jXD8rp167Jo0aIsy3l7e6u9dtkJDQ3Ndr0+Xo+wsDAmTZpE+/btOXr0qNKynC9fPhYtWpTl56a9vb2S2NrZ2WW7Tzmdn2+ez+keP36cY5KeU4w7d+5QtGhRjWI4ODhw/PhxnRJtd3d3wsLCGDx4sFblT5w4wbBhw7h9+3aGJFulUmV5LCtXrqzxeZVVjL1796o9vnr1Ki9fvlSOx82bNylUqBDly5fP8ns9r8TQpBdDusy+Uzt16qTx8czqorE+YgihKUm0xUdl1KhR/PXXX3h6emJubq7xh+nrHjx4QIkSJQDYt28fbm5u2NraYmpqiqen51svr68YWf3AuXjxokY/fHv16sX06dOZMmWKxj+IMqPtD8Z0+jgWGzduZOjQoRkS7RcvXrBp0yaNEm1dfzCuW7eOKVOmaJQAZiUgIIBHjx6xZcsWWrdurSxv1KgRwcHBGiXa27dvZ+bMmTg5OWlVh8jISI4fP87GjRsZPnw4hQoVwsPDAy8vL417P/Tt25e+ffsqcYYNG4ahoaESp2LFijnGWL9+PePHj8fZ2ZnAwEBledWqVTXuAj1x4kR+/PFHJUFs1aoVlStXVhLenN4nEyZMwMjIiF27duHu7s7y5cuJj49n2rRpjBgxQqM6LF26lNu3bxMeHk5ISAhBQUG4uLjg5eWlcWJWqlSpDMd06NChGBoa0rJlS7y8vHJsqY6OjiYqKoqoqCisra0zJFLpF7uykr6tli1bKvuzYsUKgoKCcHV1xdvbG2dn52xjVKxYkVmzZnHq1CmqVauWoQ4dOnTItjykXYwqVKhQhuWFChXiyZMnWZZzcXHJMbam9PF6LFmyhAkTJvDNN9+oXUysUaMG06dPz7LcsmXLlPNW2yRh4MCBQFoCOXr0aLVeMykpKZw/fx47O7tsY6RfuFCpVPTo0UPt4k1KSgrXr1/P8bM/naurK1OmTOHixYtUq1aNwoULq61v2LBhjjFUKhUhISEcPnwYGxubDOfW8OHDsy0/btw47OzsWLJkSa5+W8ybN0/5+86dO/zyyy+4ublRs2ZNAP766y+2bdumHPPMbNiwQfl71apV7N69m4CAAMzNzQG4d+8eI0eOzPYczisxAgIC1B4/e/aMV69eYWBgAKT1pitYsCBFihTJNNG2sbFR/k7vnVW6dGnleJ4+fZqbN2/i7e2dZR30EUMITUmiLT4qhw4dYvHixcoHpjaKFSvGpUuXMDc35+DBg4wZMwZI6yKsyZerruV1jVG3bl3lB46bm5va81NSUvj3339p27ZtjnVYt24dV65cwcnJiTJlymT4YZJTq046bX8wptPlWDx//pzU1FRSU1N58eKFWlfK5ORkDh06lGPXZX3+YHz9C14b+/btY8GCBRl+pFeoUEHje1uLFClCqVKldKpH7dq1qV27NmPGjGHHjh2Eh4fTqlUrqlSpQuvWrfHw8MjwYzinOKtXr2batGn89ttvVK9enU6dOuHu7p5l2du3b1O+fPlM12V2T2hWXk8Q4+LiWLduHYGBgQQGBtKoUSM6deqEvb19pmWPHz/Ob7/9RpkyZVCpVBgbG1O9enXy58/PlClTCAsL06gOrydmJ06cIDw8nAEDBvDJJ5/g6elJu3btNG7Nq127NhUqVKB06dLMnTuX5cuX89tvv+Hg4MCPP/5IhQoVMi1XpEgRmjZtqtE2NNkfFxcXHj58yNq1azlx4gT79++nePHiTJ48OcvjuXbtWoyNjTl9+jSnT59WW6dSqTRKtCtWrMiOHTvo1auX2vLIyMgs9x3eXldXbV+P69evU7169QzLCxUqREJCQpbb+/LLL+nduzfBwcF8+eWXABw5cgR7e/tML0BkJv29m5qaiqGhIYaGhso6AwMDWrduzbfffpttjPRk6++//6Zu3boUKVJELYaFhQVff/21RvUZO3YsQKY9ErJrTX7d+fPnqVq1KpDWi+TNGDm5ceMGs2fPpmzZsppUWfHVV18pf/fo0YPhw4erXSB2d3fHxsaGiIgIjb6X58+fz8KFC5XkFsDc3JyhQ4fSs2dPjd4j7zPG0aNHlb937NjBokWLGDt2rPLd+PfffzNhwgS6d++eafnXL2D+/PPPtGnTJsNFzaCgIJ4+fZpl3fURQwhNSaItPiqfffaZxl3asuLl5cWgQYMwNzcnJSVFafk7ffp0tj/U9FVe1xgjRowgNTWVUaNG0bdvX7XW1vQfODm1RkDaDyV9tPJo+4MxnS7HIr3rpEqlonHjxhnWq1Qq+vfvn20Mff1g7NKlC6tXr2bkyJE5PjcrCQkJattP9/jxY6VFICe+vr7MmTOHSZMmafzDOysGBgYULlyYQoUKoVKpyJcvHwsWLGDatGlMnDiRJk2aZFs+OTmZvXv3EhYWxoEDB6hSpQpeXl7cvXuXSZMmcejQoQwtIOkqVKjAqVOnKFOmjNryyMhIre53Pn/+PBs2bCAiIgITExNatmzJvXv36NatG127ds20y2lycrLSS+LTTz/l3r17lC9fnrJly2o1sNjDhw85e/YsZ86cAdLu+zx16hS//fYbI0eOzPYHcPqxDA8PZ//+/VhbWzNy5Ejc3d2Jj4/nl19+YeDAgURERGRaPjdjBGQlPj6e33//nfDwcC5fvoyLiwuzZs3C2dmZZ8+eMXv2bIYOHcqePXsyLZ/V8tzo27cvgwYN4saNG0qieezYMTZt2qTRhT190fX1KF26NNHR0RkusBw6dCjHz739+/fz8uVL5dzs169fru59Tz8XjIyM+OGHHzL0BNKEr68vycnJGBkZ0bJlSz777LNcx0h3/vx5rcumW7FihU7l69atS3R0dK4T7dcdP36cH3/8McNyOzs7xo0bp1GMJ0+e8OjRo0yX//vvvx9UjKlTpxIcHKx2AdrGxoZRo0bxww8/5Pi9unnzZtavX59heZs2bWjdujX+/v451kEfMYTIjiTa4qMyatQopk6dyvjx45Xuxrk1YMAAKlWqRFxcHE2bNlWSkXz58tGzZ8+3Xl7XGOlXy8uUKYOdnZ3GCdib9NXCo8sPRtDtWCxfvpzU1FS6dOnCzJkz1boCGxgYULp06RzPk/TjYGFhgZubm9bJ6blz5zh8+DD79u2jYsWKFCig/vGbU9dcgFq1ahEREaH22qSmprJkyRIlqcjJqlWriImJwdHREUtLywz10KSnwvnz5wkLC2Pz5s2oVCo8PDwYNmwYVlZWpKamsmzZMn7++ecsE+3z588THh5OREQEKSkpeHh4EBYWpnZ/dNOmTWnbtm2Wibavry8jR47k3r17pKamsnv3bmJiYtiwYQNz587V6FjEx8cTERFBeHg4Fy9epGHDhkyePFntfvHWrVvTs2fPTBPtihUrEh0djaWlJTVq1GDx4sUUKlRIGX9AE8nJyezbt4+wsDD279/PF198QZs2bdTubd6+fTtjx47NMtGeNGkSW7ZsISkpCXd3d0JDQ9UuNhQtWhQ/Pz+Nuthqq1+/fhw4cIBy5crh7e1Ny5Yt1XqLGBsb89133/Hbb79pFC/9IlxmF5ay07hxYxYvXszs2bPZuXMnANbW1rl6j7x69YrZs2ezfft2bt26lWHk7ZxaUPXxenTv3h1/f39lgL1z586xbds25s2bl2NS9uY9xNqMeZucnMzatWvp2LGjVok2QP78+Zk+fbrGLdd5WePGjZk8eTKXLl3iiy++yPC9qsl7q2TJkmzYsIEhQ4aoLd+wYQMlS5bUqB6NGjVi1KhRjBw5EltbWyDtonNQUBCNGjX6oGLExcVl2ptApVJx7969HMsbGBjw119/8fnnn6st/+uvvzT+3aOPGEJkR0YdFx+VunXrkpCQQFJSEsbGxhmSiCNHjrynmr0fd+/eJSIiguvXrzNw4EDMzMw4fvw4xYsX1+nKfG6sW7eOOXPmMHLkSPz8/Jg8eTLXr19XfjB6eHi89TrcvHmT0qVLa3XPvr7k1JKtSYvihQsX6Nq1K7a2tkRFRdGkSRMuXbrE/fv3WbVqVZZdqV+X08ixOV1gadWqFZcuXaJ+/fp4e3vj6uqa4X328OFDHB0ds2yJqlq1qlK+UaNGmf6g0WSguuPHjzN79mzOnz/Ps2fPqFKlCn379qVBgwbZ7kM6GxsbypYti7e3N61atcow0B2k3fPbp0+fTFvE9u/fz4sXL2jatCnXrl2jV69eXL16FVNTU6ZPn069evVyrIOjoyPJyck0b94cb29vqlWrluE5T548oVWrVlm2+Hbv3p3WrVvTuHHjLEehT0pK4uTJk2rJZuvWrVm8eDEmJiY5DgaW0wWYH3/8kdatW2c7C0Bqaiq3bt3Kthv88uXLWbx4MXcbxnSFAAAgAElEQVTv3gWgRIkS9OjRg06dOmW7fX0KCAhg9+7d9O3bl3HjxjF8+HBu377Nxo0bGTRokNr4CJnR9vV40++//86sWbO4fv06kNY1t1+/frRr1y7b7VeuXJlDhw4p57OdnR2///57rkdzb9asGYGBgUoipQ1PT0/8/PxwcHDQOkZqaiohISE6zTAAcPjwYbZt28atW7cyzBCQ0/3s2fWS0bT7+t69exkwYABWVlbKMT179iyXLl1ixowZuLq65hjj2bNnBAQEEBYWRnJyMpB2QSP9OGtyYSqvxOjVqxf37t1j0qRJyvE9f/48o0eP5rPPPmP+/PnZlp87dy7z5s2jXbt2asn++vXr6dmzJ3369MmxDvqIIUR2JNEWH5Xw8PBs12s6eFZm0wbNnz8fCwsLjb7UdS2vjxinT5+me/fuVKxYUWkNsbS0ZPbs2Vy6dCnHbpS6tuq8TtsfjAArV66kePHiSuvo2LFjCQsLo3z58syYMSPLVvFLly5RoUIF8uXLl+GevDdlNfhWvXr12LJlC2ZmZsq971l5Vxdx/v33X0JCQpTksmrVqvj4+GjdgyO35s2bh6enp07bi4uL07gF5236888/qVGjRq6nSMvOo0ePMDEx0fiiTkREBE2bNtVrHTT1+hSAulyASUxMpH///owcOVKn6ZNmzZrFsmXL6NWrl3If94kTJ1iwYAFdu3alX79+WsfODRcXFyZOnIijoyN2dnZs3LiRcuXKERoayq5du9QGuHpTUlISkydPplu3bhlua9DW8+fPefbsWaYXgjJTuXJlgoODlduGBg4cyJgxY9Tup4WcW2F37drF0qVL+fnnn7We9u3gwYNMnz6dQYMGZToImSa3er05w0D692FERASrVq1i9erVOcZYv349EyZMwM3Njc2bN9OsWTOuXbvGpUuXaN26tU639OTGzZs3Wbt2LVeuXAHSboFp27ZtrkdUT0hI4MaNGwBYWlrmuudHXohx//59RowYwaFDh5SeYq9evaJevXoEBQVpdLvB5s2bCQkJUTueHTp0yHZ8j7cRQ4isSKItxBt0/VLXx48CfcTw8fGhQYMG9O7dW61F4/Tp0wwcOJB9+/ZlW17XVh1I+9G5e/du6tSpg5mZWa5/MAI0adKESZMmUadOHY4ePUq/fv0YP348u3bt4t9//2XhwoWZlnu9VSd9ipXXP+5en44pq4sG4eHhNG/enIIFC+rtIs7169eV+3crVqyocSuTvpKZdEeOHFGrR926dXWO+b48efIkw1R0pqam2ZZJTk7G1taWiIgIjcdOyKsiIyMpWrQojo6OQNpARaGhoVhZWTF+/PgMCdbboI95ihs0aMDo0aMzDMq2fft2Jk+ezP79+zMtp+8LYjVr1mTr1q2ULl0aZ2dnZs+eja2tLTdu3MDDw4NTp05lW75WrVps3LhRp/nAL168SHJycoaW1PPnz1OgQIFsR+bXZIwCTVphX+8h9uagaKDZsXy9Lpm9LppcsG3atCljxozB2dlZ7bvs8uXLtG/fnj/++CPHGG5ubnz//fd4enqqxQgKCiIpKYlRo0ZlWTYxMREHBwfWrl2r8cwKQnNXrlwhJiYGSEtyNemZJcSHQu7RFh+dly9f8vvvvytXJytWrEiLFi00vrdW12mD9DHtkD5i/PPPP2pl0xUrVowHDx7kWD4yMlJp1fH398fJyYly5crx+eefs2vXLo0S7QIFCjBs2DC2bdsGpLVe5Hawujt37igtQ3v27OGbb77Bzc0Na2tr2rdvn2W53bt3K/eIajJ/embOnz+vtDam3/P+ZjdpTT158oRRo0axa9cupat0UlISjRs3ZtKkSTlOEWZgYJDjD3xN3L59m379+nHhwgW1+U+tra2ZPXt2ji3N6dOhZDVXfVZdMPUxn+zrrl+/zs8//8wff/yh1tsip4sn6fLnz0/ZsmV1Gln2xYsXLFu2LMtjkdVAV9lN5fMmTe7dnzFjhpIonD17ltmzZ9O/f3+ioqKYNGlSrgYB0/YCjK7zFEPaPfOZzWNubW1NfHx8luWGDx+u3Ees6bRq2bG0tOTWrVuULl2aChUqEBkZia2tLQcOHNBoKj9XV1ed5wMfM2YMnTt3zpA0X7lyhRUrVmR7sVUfg4eBfo6lPuYh1scMAzdv3lS66b8+EGebNm1o165dtom2gYEBpqamGd7fmtBHz6qBAwcyceJEjI2Nc/zsyOrzIq/EyEyFChU++IudQmRFEm3xUblw4QLfffcdr169UqbyCA8P59dff2XhwoWZ/oh7k65f6vr4UaCPGMbGxjx48CBDq8r58+cpXrx4juXj4+OVAUKMjY15/PgxkNZyNXHiRI3qAFC9evVMB0PT1CeffEJcXBylSpXiwIEDDBgwAEgbDO3N7uyv8/X1ZenSpZiYmBAeHq50kc2NkJAQvv/+ewoXLkznzp2JiorKVWv868aPH8+1a9dYt26dci/YmTNnGD16NBMmTMj0osib9JHM+Pv7U6RIEXbv3q10/75z5w7Dhg3D39+fOXPm5Fg+IiICV1dXqlSpovF29TGf7OuGDh1KgQIFCA4OplixYlrdfz9kyBCCgoK07ho7cuRIjh07RrNmzahdu7bGddBk6rPcuHnzpvJ5sWPHDpo0acL333+Ps7Mz3bp10yiGrhdgdJ2nGKBSpUqsWbMmQzfeVatWZfvZ/XpvEk17lmSnVatWnDt3jtq1a9OrVy969+5NSEgIr169ws/PL8fy+pgP/MKFC5neG53+efou6ONYajoAXXb0McNAsWLFePz4MRYWFpQuXZqzZ89SuXJlbt26pVEC3atXL6ZPn86UKVM0utiSrkWLFkrPqhYtWmToWZUuu4uDr39eaPvZkVdiBAUF4evrS+HChQkKCsr2uZl9Zuij90pevCVMfLwk0RYflQkTJlCrVi0mT56sdHN78eIFfn5+TJgwQaOr67p+qevjR4E+YjRv3pzg4GB+/fVX5YskfVRQTQYg07VVJ13Hjh0JCAjgzp07VKtWLcMXdHZdICGt6/iQIUMoV64cDx8+VAa6+ueff7Id0O3SpUu8ePECExMTZs+eTfv27XOdaJcqVYrw8HC++uorUlNTiYmJybJlLaf92LdvHwsXLlT78Wxra8vPP/+cYc7frOgjmTl69CirV69Wu8e6RIkS+Pn5aZQAbN++nZkzZyrTrGlK3/PJXrx4UblXX1tjxowhISGBFi1aaNU1dv/+/SxZskS5WKApfUyl9TojIyMliYiKilIGDitSpIja3PHZ0fUCjK7zFAMMGzaMXr16cfjwYWUKwlOnTnHjxg0WLFigUYwrV66QL18+5SLh0aNHiYiIwMrKiq5duyqjyWenR48eyt+Ojo5s27aNc+fOUbZsWY0+f/UxH7iBgQHx8fEZLpQ+ePBAo314k729fa6m+Eqnaw8xSBuUc9WqVUoMKysrfHx8NL6lQR8zDNStW5c9e/ZQtWpVvL29mThxIpGRkZw5c0ajUbLXrVvHlStXcHJyokyZMhk+e7MaLFAfPate/7zQ9LPjxIkTVK9eXRn7Ia/EOHv2rHKB/OzZs1mWy+ozQx+9V/TdA0aI7EiiLT4qf/31F2FhYWo/mA0NDenXr59GXZ1B9y91ffwo0EeMH374AX9/fxo0aEBSUhJubm4kJSXRrFkzjQYV0rVVJ1166+vPP/+sLNPk/uh0o0aNokyZMty+fZshQ4YoX5B3797Fx8cny3KVKlViwoQJ1K1bl9TUVMLCwrK8Cp/VD9/BgwczZswYpk2bhkqlomPHjmrrc7Mf6fc5vsnIyCjblvnX6SOZKVCgAC9fvsyw/OXLlxp1iy9SpAilSpXSaFtZ0cd8snZ2dly/fl2nRFvXH1kWFhbvZRCzN9WvX58xY8ZQpUoVrly5olzUuHjxosY9SXS9AKPrPMWQlgzt2LGDVatWKd3XXV1dczXYn5+fH126dOHzzz/n1q1b9O7dmzp16nDw4EEePnzI0KFDc10vCwuLXPXI0cd84PXq1WP69OnMmjVLGWDq6dOn/PLLL8q9+LmhzXA8+ugh9ueff9KzZ08sLCyUiyc7d+5k6dKlLFy4kNq1a+cYo3HjxpiamjJ79myMjIyYPn06VapUYc6cOTg7/z/2zj0sxvT/4+9JydImqbZUWunstCUSETlECim7zocQOSSSkGM6oHLqgKhsyuZQiiyFTUtRIbRLZItSOqkVOin9/uia5zfTnO6Zeexa33ld117Xmum+55mZZ57n/tyfz+f9Hkn0Xry9vanM9Zw5c6CgoIDc3FxYWloSbeyNGTMGY8aMIXotVljPG9JzyNnZGT4+PkSVZ7xYunSpSBsrn3sO1usE6TWjvLwcKioqkJKSEql6JTw8HDNnzoS8vDzHOFHnkCCBFIkYmoSvCnNzc+zbt4/DVicjIwMeHh7IzMwkmkdc2yBxx9M1BwCUlZWhoKAAHz58gKGhociBSWlpqVBZHdZx/BC1pFwQ+fn5CAwMRHFxMUpKSvDdd99xzQQxGAy+mYbW1lZUVVVh9OjROHv2LJs3MCuC3sfy5ctRX1+Pffv2UWqqVVVVWL9+Pbp27Uq8gSIu7u7uKCgogJ+fH/r37w+gPbPg5eUFfX19BAQE8B0fHx+PzMxM+Pn5iewpbm1tjQkTJnD4yQYFBSE1NRUpKSkC53j9+jW2bt0KS0tLrr7kQ4YMEenYhOHOnTsIDw+Hp6cndHR00KlTJ6JxdNpqAe39/wcOHMDr16/x008/UYF2cHAwpKWliSxqhgwZguPHj3PYc+Xm5sLZ2Rk5OTkC5wDaK4iY7gK9e/fmurnEDbrE/gYPHoyEhARoaWkhIiIC6enpiI6ORnZ2Njw9PZGWliZwjo0bN0JfX5+j7P7EiRN49uwZ/Pz8iI+nuroaioqKQmehX79+jYULF+Lvv/+mgtzHjx9DUVERkZGRQm92iWLxNX/+fPTs2ZNrhVhNTQ1RhZiDgwNMTEzg5eXF9riPjw8ePHhAdH6Lw9y5c2FmZgYzMzP88MMPX8TGmCBEtWP7WucQtRqDrvF0zSHhfxNJRlvCV8WkSZOwefNmbNy4kdo9v3//Pvbs2QMbGxuiOV6+fAlTU1NERUVxPJeZmSkwmyDueLrmYNKrVy/06tWL+O95IWxWh3WcuDx58gSRkZFsIk1OTk58A34DAwMcP36c+v/4+HiR+qs7deoEVVVVREdHw9DQUGQxtK1bt8LFxQWjR49m64Ht27cv7aXE/Ni2bRs8PT3h6OhILTo/fvwIS0tLbNmyheuYjsFgYWEhhg8fDk1NTY7Pg2ThvHHjRri6uuLmzZtc/WRJKCoqwpMnT3Dr1i2O50h9bVmpqqri8NYV9LvR0tJCfX09pk2bxvV5XscwevRo6rMXJUvWEXl5eWzbto3j8dWrVxPPMWrUKGzdupVjA2b79u1sZf+8aG5uRlBQEH755RdKR6Jz586YPXs23N3duXqls0KX2B9r7iAjI4PyJtbQ0CASgQSA33//HQsXLuR4fNiwYdQ1hR/Nzc3Yt28fTp8+jaamJqSkpFAK12pqakSe4GpqakhOTkZycjKePXsGAJg6dSomT54s8LPkxpQpU4S2b6KjQuzZs2cIDAzkeHzOnDk4c+aMUMcjClpaWkhOTkZoaChkZWUxcOBAKvAW1tqvsbERN27cQHFxMZXdLCoqQvfu3XluwEoQH3HzgXTkEyU5SQmiIgm0JXxVeHp6gsFgwN3dHa2trQDaA6WZM2fCw8ODaI5FixZxlFAC7f2Ybm5uAheD4o6naw5evqAMBgOysrLQ0tLCxIkT+YoccfPyPnLkCDQ0NIj9wAHRAmUmqampcHNzg4WFBSZMmACgffPEwcEBBw8exLhx4wTOQYcK79ChQ9HU1ITz58+z9Rra2dkRZXbV1dWRlJSEjIwMtvHDhw8nLvueN28e378lyTB1794dR44cQVFREdtxMHtaudExGCQJvPgxZswYXLlyBXFxcZSty8iRIxESEkK8MbNt2zaMGjUKLi4uIouh1dXVwdvbG6mpqRxBNiBY/Xzt2rVoamqCt7c3lJSUiI+B1ZOanz+1sFRUVOD169cc74Ukuy/KBgwre/fuxbVr17Bnzx42D+y9e/eitbWVI6PJDTrE/vr164ewsDCYm5sjKyuLalEoKysj8uUF2ku0uf2mZWVlUVdXJ3D8wYMHkZGRgUOHDrFtdvzwww84cuQIUaANtG8+0CFIBrC37pDSrVs3VFVVcehPVFZWEgftPXr0QEFBAUcl1bNnz/ha8AkSqWKFn5YCU7izoqIC2dnZyMnJQXJyMkJCQiArK4tBgwbBzMxMYDtVYWEhnJyc0NraipqaGkyaNAny8vI4e/Ysamtr/9HNUgkSJPx3kATaEr4qZGVlsXXrVri7u7OVLwqjkGltbY0FCxbg1KlT1C71b7/9hnXr1hH1j4o7nq45Pnz4gMzMTMjKylIBbX5+Ppqbm2FiYoIbN27g4MGDOHnyJJXBYqWjlzcTdXV1xMbGEgfa4gbKhw4dwpo1azgEw44ePYoDBw4QBdqAeME+wLtfMTg4mLhfkcFgwMLCQmghMSYdv6eWlhbk5+fjyZMncHBwEGquPn36ELcR0BkMMlFXV+coHReGN2/ewMXFha8gniD8/f1RVFSE48ePw9nZGYGBgaiqqkJkZCSRsNyTJ08QHx8vUAiPFFH8wIH2Hsa1a9ciNzeXTTeA9TgFIcoGDCuXLl1CUFAQW7WNjY0N5OXlsWHDBqJAmw6xPy8vL3h4eODatWtwdnamzvErV65QVU6C0NHRQWpqKsc1JyUlhciG6PLlywgICMDgwYPZvgc9PT3qvkRCYWEhcnJyuFrH8fpNxsbGwtHREbKysoiNjeU7v6DeezoqxBwdHbFlyxa8evWKbY6jR4/ytT+jW6Tqu+++g52dHezs7AC0bxbExMQgJiYGOTk5AgNtX19fjB07Fl5eXhg8eDD1uJWVlURQS4IECTyRBNoSvkq6du0qVB8xK56ennj37h2cnJxw8uRJ3LlzB+vXr4ePjw91k/6c4+maQ09PD926dYO3tzdVatjc3IydO3dCTU0NYWFh2Lx5M/bs2cNVlIQOL29A/ED5xYsXmDhxIsfjEydOREhICNEx0JEVF0XRns5FL8B78XnkyBFUV1fzHCeupQo3MjMz2TYtOuoiCCI/Px9nzpxBSUkJfH19oaKigpSUFPTq1QsDBgwQON7Kygo5OTliBdo3b95EcHAwjI2NISUlBR0dHYwbNw6KioqIjo7G+PHj+Y43NDTkmvETBnH9wIH2c7Nr1664du0a7OzsEB0djdraWuzbt0/oIECYDRhWPnz4wFWwTFVVlfIsFgQdYn8GBgZc/cs9PDyI+6RXrFgBNzc3lJSUUPZUWVlZSEpKIvIkf/PmDVchq8bGRqrSShCxsbHw8fGBkpISlJWV2d4/g8HgGWhHRETAxsYGsrKyiIiI4Dk/ifo5HRViq1evhpycHKKioqhrj7KyMlxcXLiW5zOhK5PPytOnT5GdnU1lttva2mBmZkZkQfbw4UNs27aN4xxSVVVFVVUV7ccqQYKErwNJoC3hP8+aNWvg6+sLOTk5gR68pP2fu3btwrp16zBz5kyUlpbC39+feAefjvF0zBEbG4vY2Fi2fr7OnTvDyckJc+fOxapVq7Bo0SKeZYx0eHkD4gfKqqqqyM7O5hBIysrKIlYipiMrLkq/Ip2LXn7Y2Nhg+vTpPEt8SS1VSHj58iVWr16NwsJCtl7zPn36IDg4mCgDmp6ejtWrV2PcuHG4c+cOpYL++vVrnD9/ns1zmxf6+voIDAzE/fv3oaenx9ErTvJ5fvjwgbIY6t69O2pqavD999+jX79+ePTokcDxixYtgq+vL5YuXQp9fX2OYyAJwOnwA7979y6ioqKgoaEBBoMBOTk5DBgwAJ06dUJAQAASEhJ4jhW08QK0n5+CAqtBgwYhLCwM/v7+VOl5c3MzwsLCOATWuNHa2gpPT09oaWkJZR9IijDCfePGjUNERARCQ0Nx9epVAO3nW2RkJFFQZmRkhN9//53jHIyPjyfOqoeHh2PDhg3EPuhMWBXPxVU/p6NCjMFgwMnJCU5OTnj//j0AUM4R/CC1pQPA17bx5MmTVGAtLS0NU1NTDBs2DKtWrYK+vj7xa0hLS6O+vp7j8eLiYqKqk38adXV1kfVEvrQ5RLkmSpDwpSAJtCX852G96X/zzTciXZTT09M5Hps8eTLu378PW1tbdOvWjfobS0tL2sfTNQcrHz9+RElJCUepY0lJCdXDyU8RmA4vb0D8QHnhwoXw9vZGfn4+W+nhuXPniLN1dGTFRelXpHPRy4+0tDS+PZOiWKrwYvPmzVBSUkJERAQVpFZVVWHjxo3YsmULYmJiBM5x8OBBbN26FTNmzGALPJjK1yTExcXhm2++we3btzl6NEk3Lvr06YMXL15AQ0MD+vr6OHv2LHr37o2zZ88SefwyN/ZYz0NhLN8AevzAW1tbqeClR48eqKqqQp8+fdC7d2+B1SeCNl4ePXqE5uZmgYG2l5cXlixZAktLSzaV7E6dOvHdZGLCzJRevnxZrEDbwMCA7z2AVCSPKZglCu7u7nB2dkZhYSFaW1tx6tQpFBQU4O7du0Q6CgBQX19P5O/Mj+bmZrS1tXFsMjQ1NYHBYBALgYlTIcbk5cuXbBUwgipRjI2NBd7LSX5nvr6+6NWrF1xdXTF9+nRiFfyOWFlZ4fDhw9i3bx/1WEVFBQIDAwVWvgDCqep7e3uLJNzJSnJysljjhZ2jpqYGHz9+5Lin03EcvITIWlpaiIJ4UYQAP8ccEv43kQTaEv7zsPYP7969W6Q5OmY6WTl37hylpMzrpi7ueLrmYGXKlCnYtGkTXFxcqFLcvLw8HD58mFJJvnv3Lvr27ct1PB1e3oD4gfLcuXOhrKyMqKgoqiRUW1sbgYGBVBm4IOjIiovbrxgSEoLFixdzZF8aGxtx/Phxoj7ojurfbW1tqK6uRlVVFVEPLNAukufl5cWRVaqvr8euXbsEivrk5eXh3LlzbIGosrIyPDw88OOPPxIdQ2FhIddSc3l5ebx9+5ZoDjo2LubPn4/y8nIAwMqVK7F06VIkJiZCRkaG6FrCzxaOFDr8wHV0dPD06VNoampi0KBBiIiIgKysLOLi4gTa0fDaeLlz5w6CgoLAYDCwZMkSgcdgYGCAq1ev4sKFC1SPt7W1Nezs7PhmHFnR1dVFWVmZWBY6HashWlpa8OTJEyQkJAjsw6ULU1NTJCYmIjw8HHp6ekhPT4ehoSHi4uKIA9bp06cjJSUFS5cuFfk4XF1dMWzYMI4S7dOnT+POnTsICwvjO/79+/c4duwYsrKyuPaJk5z/NTU12Lx5M27cuEFVV7W0tGDUqFHw8/PjGVCSbkgIIigoCDk5OYiJiYG/vz/69++PoUOHYsiQITAxMSHOzm/cuBFr1qzBiBEj0NTUhAULFqCyshIDBw7EunXrBI4XRlWftD2Mlfz8fNjb2wtcG5w+fRqpqalQUFDATz/9xFahUVNTgxkzZvD9Xt+/fw9vb2/cv38fQ4cOxc6dO7Fnzx7ExMSAwWBgyJAhCAsLI6paYJKXl4eSkhKMHj0aXbt2xfv379G5c2dqI4jX52ZhYYEpU6Zg+vTpfH9X/IQAedkWMjeiNDU10aNHD5HEBCVIACQ+2hK+MubPn4+QkBDIy8uzPf7+/XusWLGCtpv3f4GWlhYcO3YMsbGxVP+ukpIS5s6diyVLlkBaWhqvXr2ClJQUTxsjury8U1JSEBUVRS3AtbW14eTkJDBQbmlpQXR0NCZPnkwcEHMjJiYGe/bswY8//sg12CfJfjY1NWHv3r04ffo0135FQaWphoaGuHXrFsfCsra2FsOHDyfaPAkODubo1VRUVMTQoUN5bpiQHkdNTQ0sLCzw+PFjvuPt7OywdetWjhLa7OxseHt7E2UwrKys4OvrC3Nzczaf1aSkJBw5cgSXL18mei9009DQgMLCQqipqf1jdj10+IGnp6ejoaEBEydOxMuXL7Fs2TK8ePECCgoK2L9/v1D983/++Sf27duHrKwsODo6YsWKFVz7jTuSk5MDY2NjjuNvaWlBbm4u0fu4efMm9u/fDzc3N65iaKQBOzeuXLmC+Ph4HDt2jOvz5ubmuHTpEhQVFQUqXvNTuaYLf39/JCQkoF+/flxbI0i0FMzMzBATEwNdXV22x58/f465c+fizp07fMe7urriwYMHsLe35+gTB8jaM5YvX47y8nL4+PhQYo5//PEHtm3bBhUVFaI2Ebqorq5GTk4O9V9RURGMjIwwdOhQrF+/nmiOe/fuUfdDIyMjoVwjfHx80K1bN7FU9XmRn5+PadOm8XXYiImJQWBgIKZPn453797hypUrcHV1pTZzqqurMXLkSL73ol27duH27duYNWsWUlNTIS8vj+LiYuzYsQNtbW3YuXMnrKysiN5jZWUlXFxckJ+fj0+fPiE1NRWamprYsWMHOnXqRDkG8CIpKQmJiYnIysqCvr4+HBwcYGtrK1QpP2sFDDMcYv23lJQULC0tERAQINTmgQQJTCSBtoSvCgMDA2RkZHANIkaOHIk///zzXzqyfxdheuO+NIyNjZGcnCy2H7eowT7QXpr75MkTaGlpoVOnTiL1KxoYGCAzM5MjgMvOzoarq6vARa+4NDQ0oK2tDSYmJrh+/TrbcbS2tiItLQ179uzh6kvNyu+//46goCC4urpSHtgPHz5ESEgI1q5dyxaA8wqMjhw5gkuXLsHf3x/z589HREQEXr9+TfU78xJJolvUjY4qg48fPyIvL4+rrRYvf21WMjMz4eHhwdXjWRQ/cCZ///03unfvThwEvHz5Evv27cPVq1cxceJEuLm5CSU0R8dGEmtWittxi/pZAO3vb+rUqXjw4AHX58+fP4/Jkyejc+fOOH/+PN+5BAl10fFZ8NT6l6wAACAASURBVLMAYzAYRJvGP/zwA86ePcsRaBcUFMDR0REPHz7kO37w4MGIiIjADz/8IPC1eDFo0CDExMRwCBw+evQI8+bN43kMz58/h7a2NqSkpDiE8Toiihjhn3/+iStXriA2NhYNDQ0Cv5PExETY2NhwlNs3Nzfj119/Jfqt+/r6IiEhAdra2kKr6gvyLW9qasLz58/5vg9bW1s4OztjypQpANozxStXrsTMmTPh6upKFGiPHj0ae/bsgZmZGSoqKmBpaYnDhw9TFpDp6enw9/fHlStX+B4v0L6RA7RvKllYWFAbrrdv38aOHTuQkpIicA7g/7U9kpKSUFZWBisrK0yfPh0jR44UKIB48+ZN7Nu3DytXrqTuZ48ePUJYWBhWrFgBWVlZ+Pj4YNiwYZKstgSRkJSOS/gqYL0RFxUVoba2lvp3a2srbt68yTcjKq46NB3q0nQrVLMiSoDt4uICBwcHjBkzBp06dRJ6PJOsrCwwGAyODCizZEtQpsvMzAx3794VOdBmzYrHxcWJNAdr/6impqZQ/YrM7BiDwYCNjQ1bAPHp0ye8e/cOP/30E9Fc4izgmT2PDAaDq/gbg8Fg8/zlhbOzM4D2UuuOmYDly5ez/S2/Nom2tjbMmzcPDQ0NmDVrFmRkZLBw4UK+SsSkom6kwWVoaChmzZrFseBtaGhAaGiowED7+fPnWL58OSoqKtDS0oIuXbqgoaEBnTt3Rrdu3YgW33T4gXNrB1BQUCBqB6isrERISAgSEhJgbm6O+Ph4GBoaCn0MHS3FmLx9+5Y4E01HxVFHES1me0VoaCjfknTW4FlcxWte+Yvm5mY2cUp+iKulALR7isfHx2Pjxo1sj589e5boO1ZSUhKrigBot9Xidl4wGAy+vua2trbUprmtrS2lfcA6XhgthMePHyM7OxtZWVm4d+8e3r17h549e8LS0pKoF3/Tpk0YOXIkx7X3w4cP2LRpE9FvXRxV/adPn2Ly5MkcmilMqqqqBG5IvHr1ivK4B9rvCT///DMWLlyIjx8/YsGCBQLfw5s3b6gNuO+++w5dunRhE8DU0dGh2nEEkZ2djdjYWI7eZ01NTeI5AEBNTQ0rVqygqhYDAgKQmpoKZWVlzJ49G05OTjz1CAICArB161a2dci4ceMgLy+PXbt24eLFi/Dy8sL27duJj0eCBFYkgbaErwLmjZjBYGDevHkcC50uXbrwVGQGxFeHpkNdmo45rKysiBfqgvrrFBUVsXHjRnTu3Bl2dnaYPn26UCqtTPz9/bkGcO/fv0dwcDBfRWSg/T0FBASgoKAA/fr148ggCxKGk5aWRnBwMKytrYU+dlZE7R/19PREW1sbNm/ejBUrVrAJPcnIyEBdXZ1YiVicBXx0dDTa2tqwYMECBAcHo3v37mzH0atXL6LyfDqCIQaDARcXFyxevBjFxcWor69H3759BYrN0CnqBvAODgsKCtg+H174+vrCxMQEPj4+MDMzw4ULF9Dc3AwvLy+OTQde0OEHnpiYiPXr13NsqDU2NiIpKYlvoM2s6Jg/fz7MzMxQWVmJyspKjr/j9TtjCsIxGAx4eXmxLWg/ffrEps0gCBJFb0FwE9Fqa2uDqqoqAgMDieYoLCyElJQUFUDcuXMHFy9eRN++fbFw4UKeWTLmBimDwUBCQgLbterTp0/Iyckh8uGmCzc3Nzg5OSE/P58KJrOysnD//n0igbrNmzcjKCgIu3btErl1h2lLuWPHDmqDMj8/H/7+/nwzuKxVN+JoISxfvhz379/Hu3fv0KNHDwwdOhRubm4wMzMjbrcBeF8rKioqiMX7xLlm6erqYuDAgZg9ezbX5588eYIzZ87wnUNBQQHl5eVswbquri5+/vlnqudcED169EBNTQ3U1NQAAGPHjmVr1fvw4QOxyB6rnSErFRUVQinb19bW4sKFC0hISEBRURHGjh2L6dOno7KyEpGRkbh37x7PlpEXL16gR48eHI8rKCjg5cuXANqr32pqaoiPR4IEViSBtoSvguvXr6OtrQ3jxo3D2bNn2cpiZWRk0LNnT75ZWXHVoelQl6ZjjsWLF1P//+7dOxw/fhympqZU6d+DBw9w9+5dIoEdX19fbN26FSkpKUhMTIS9vT0MDAyoPiiSQARorzDQ09PjeFxXVxdFRUUCx2/btg0AuKpRk2YzxM2KA8C6deuwZ88eoftHmdkxDQ0NmJiYiGR1QscCnhnEXL9+HWpqasSewrzmoYPOnTuLVPb58eNHmJmZ4fTp0xxlsSTQVWXwxx9/4JdffkHnzp0hJSWF5uZm9O3bFxs2bMCWLVswevRogXOI4wfObAdoa2tDY2MjWza3tbUVGRkZAnvNGxsbAQCRkZGIjIzk+jf8fmfMc7GtrQ1dunRhU3WWkZGBo6MjZsyYQfyeKisrcerUKarFo2/fvpg9ezaRCjzAuREkJSWFHj16QEtLi/i3t3HjRixYsADff/89ysrKsHz5cgwZMgQ3b95ETU0Nz35eZvDa1taG2NhYtt+YjIwMNDQ0hCo/zczMxOXLl1FWVsbRlkCy4TVkyBBcuHAB4eHhbDZlFy5c4GnD17E//f379xg9ejTk5OQ4Pj+SXvVt27bhw4cPsLe3Z7N9k5aWxo4dO7Bjxw6u8zGv1S0tLYiMjMSiRYt4ZnP50blzZ6xZswZmZmYiXWuYApQMBgOLFy9mW0d8+vQJxcXFGDFihFBzNjY2srUfkSihm5iY8L1fduvWDaampnznGDx4MFJTUzn+TkdHBydOnMD8+fMFHoe+vj4ePXqEfv36AWgXm2MlLy+PeDNpxIgROHnyJNs5UF9fj9DQUCIdmOvXr+P8+fNIT0/H999/D0dHR0yZMoUtcB4yZAgmT57Mcw4jIyMEBgbC39+fGldbW4ugoCDqPZaUlIilESPhfxtJj7YECV8p69atQ//+/eHk5MT2eFRUFB48eEDsKc6kvLwcZ86coQLesWPHYt68eWylaNwYPnw4Dhw4wBGg3blzB25ubp+9NxkAzpw5g0OHDmHatGkiZcUB8ftHf/31V8jKynJY9ly/fh0fP37kaj/GxMrKCgBQVlYGVVVVrgt4V1dXIr9iJhUVFVz7iklEq8Qd39jYiJ9//pmnmjFTXZ4fTLsdUaoszp8/T1UZbN68WeQqAzMzM5w5cwZaWlqwtrbG1q1bYWFhgcLCQtjb2wvsgQXa/ZKjoqJgZWUltB+4ICsrZjuAi4uLwOMQl5CQEDg5OQmViepITk4OnJ2d2T7/3NxclJaW4tixYwIDCboYPHgwEhISoKWlhYiICKSnpyM6OhrZ2dnw9PREWloa3/Hz5s1DSEgI8WYkN86ePQsfHx/Y2NggOTkZkyZNwsuXL/H8+XM4Ojpi06ZNIs/ND0H96ayQlNjTMZ+JiQmSkpLEUqMnxc7ODuHh4VTGlmn/GBISgkWLFrFV3TCvFRMmTCDK4jY3NyMoKAi//PILmpubAbRvBMyePRvu7u7EbQWikp+fjz///BMODg5cn3/27BlSU1P5tsy8e/cODAaDZzvarVu3ICsrS3QfKC8vx+LFiyElJYXCwkIMGjQIL168wLfffouYmBiBm2umpqawtbWFg4MDhwYAE0F6G3/99RdWrlyJ0tJSanOnrKwM6urqCA0Nhba2NlJTU/H+/XtMnz5d4HuSIKEjkkBbwleHKOJEgoSVWOFW7ibueLrmYMXY2BiJiYkcllYvXryAvb09sdUI0H6Djo+Px8WLFyEjI4OpU6eiqqoKV65cwcKFC/kqjHp5eeHJkycICQmh1M1LS0uxatUqGBgYCLST4uVzzWAwICsrCy0tLYwcOZJvVoBfTzVpVjw7O5vv84IyvZMmTcKWLVs4sh+3b9+Gj48PLl26JPAY6FjAl5eXY+3atcjNzWXrc2Qi6LMQdzwArF27FllZWZg0aRLXvmSSwPD06dNIS0tDQECAyL7L2dnZMDY2FnmBu2jRIqrCw8vLC8+fP8eCBQuQmJiI2tpanD17VuAczE0UbjAYDL5ls9nZ2bS0A3wOampqcPPmTWhra/NcBHfEwcEBJiYmHFZ1Pj4+ePDgAWVxyI309HSi1yDZVDMxMcH58+ehpaUFJycnjBo1CgsXLkRZWRkmTpyIR48eEb0WK+Xl5ejZsyfxuWZjY4OlS5fC3t6eTZl/7969aGlpwebNm3mObWlpwadPn9iCv6qqKsTFxVH+3P/UpgUdeHh4YMCAAUQZV3Fh/axZYRXLExUfHx9cu3YNnp6e1Ab1vXv3sHfvXowfP57YopGEHTt2wNXVVSz3hH9ijpaWFly6dAlPnz6llNxJLAGZ4ywsLMT2HP/06RNu3bqFFy9eAAD69OmDESNGiFz1JUECK5LScQlfFaKKE/ETVmKFV/ZI3PF0zcFK9+7dkZaWxiEudePGDQ77M27U1tbi4sWLOH/+PAoKCmBpaQl/f39YWlpSNyBHR0c4OzvzDbQ3bNiAVatWYcKECVSgXVZWBhMTEw6RHm6kpaXhxYsXaGpqonacS0tLISsrCzU1Nbx69YraAe+4qcCEn+UJKeKWTJeWlnI9Pk1NTbx69YpoDjr6kn18fNC1a1dcu3YNdnZ2iI6ORm1tLfbt20fkay7ueKA9KIqMjBRLzfjMmTMoLCyEhYUFNDQ0OBZm/IIyJkOHDkVrayuKiorw5s0bjh54QVmZtWvX4sOHDwDaK0iYJePff/89/Pz8iN6HOH7gdLUDdESUDOKSJUswatQozJ8/H+/fv4e9vT3q6+vR0NAAHx8fIrGoZ8+ece2jnjNnjsD+02XLlnGI83WEdFOtX79+CAsLg7m5ObKysiibobKyMr4CXkz279+PPn36YNq0aWhra8OSJUuQkZGB7t27Izw8nKjypLS0lPp+ZWVlqfPsxx9/xMyZM/kG2l5eXpCVlYW3tzeA9iykg4MDWlpaoKSkhOjoaAQHB/Pc5KEjUKcz2NfR0UFISAhyc3PRr18/jt+6sOKgojB69Gi2/uO//voLKSkp6Nu3L7H+x6VLlxAUFIThw4dTj9nY2EBeXh4bNmygNdC+cOECFi9eLFaQ/E/MIS0tjalTpwo9r7S0NLZu3UqLFaSUlBRGjRoltG2pBAkkSAJtCV8VoooTiRLAlJeXQ0VFBVJSUmKPp+MYOrJy5Ups374dOTk51MLu4cOHuHHjBltPFC9GjhyJ3r17w8HBAdOmTeO6a2xoaEh5o/Kie/fuOHnyJLKzs/Hs2TMA7X1epCXKM2bMQFpaGvz9/ambdU1NDTZv3owxY8bAxsYGa9euhZ+fH44ePcpznpSUFJw4cYLN3mvBggV8S7Y7UlFRwdY/qq2tjVmzZkFVVVXg2B49euCvv/7i6DMsKCggzsi2tLQgISGBZ8k1Sd/m3bt3ERUVBQ0NDaoEcMCAAejUqRMCAgIEitOJOx5o778UJzMEAGPGjKEsZUTl3r178PDwwOvXrzmCM5KgTFNTkyqh7NmzJ5HA1OdAXV0db9++RV5eHtcNA5IglxVRCt3++OMPqtImJSUFcnJyuHbtGi5duoTjx48THUOPHj1QUFCAPn36sD3+7Nkzgd64qqqqYDAYsLe3h729vVhlxl5eXvDw8MC1a9fg7OxMHc+VK1eIWgqSkpKo1py0tDQ8fvwYZ86cQXJyMgICAhATEyNwjp49e+Lt27dQV1dHr169kJeXBwMDA5SVlXH87juSm5vLdo1PTEwEAKSmpkJOTg6BgYGIiIjgGWiLG6jTNQeT06dPQ05ODg8fPuRox+AnDkonrq6umDp1KhwdHVFTU4OZM2dCRUUF5eXlePXqFZs+Ci8+fPjAtcJEVVWV2kihCzqKVT/3HMzzkhvMajWmSjs3BgwYgKdPn4pt/ZmRkcHzniqo4k6CBEFIAm0JXxV0iBORYmNjI1bfmLjjBc0xY8YM9O3bF7GxsdSur7a2Nk6ePCmwrxpoD9oE/Z2cnBzc3NzQ3NwsMHAaOnSoSFnhw4cP4/jx42w74oqKili7di2cnZ3x008/wdXVlbKd4kZ4eDhCQkIwY8YMSrX1wYMH8PT0RHFxMd+xTNLT07F69WpoaWlRmdi0tDRERUUhODhYYEmqjY0Ndu3aBTk5OQwePBhAe9Dq5+cHW1tbga8PAN7e3rh48SKsrKxEsmAC2kWymMFhjx49UFVVhT59+qB3797466+/Pvt4oH0RHhgYCE9PT+jo6IhkH0ficS2IHTt2wNjYGJGRkVBWVhbKWqu1tRUWFha4ePGi2ErShYWFSE1N5Sp6RbLQu3r1KjZs2ICmpiZ8++23bO+DwWAIHWiLQn19PXVe3Lp1C+PHj4eMjAyGDh1KtLEHtFfIbNmyBa9evaIC2vv37+Po0aMCy4bT0tJw+/ZtxMfHY8qUKejfvz8cHBxgbW0ttEWVgYEBV50ADw8PoqqBN2/eUAHVjRs3YGNjg4EDB0JBQYHYOmzYsGH47bffYGRkBAcHB/j6+iIlJQWPHj3i0HnoSGVlJZu4XkZGBqytranvx97enm/Fh7iBOl1zMBGn6oMunj59Sp2Tly9fhpaWFs6dO0dtApME2oMGDUJYWBj8/f3ZhOHCwsKE0tf4Wti9ezfq6+vZXDM+fvyIzp07o1OnTmhoaICBgQGOHz/OtZJk7ty52L17NyoqKrhqr5CI3x04cABHjx7FoEGDoKKiQs8bkyCBBUmgLeGrQkpKirpgKykp4fXr1+jbty8UFBRQWlpK62uJu9v7T+w4m5iYEAXVvMaSsHTpUr4bBrGxsVBRUcH48eMBtKvQJiQkoE+fPjh48KDAIKWurg5v377l+nhdXR2A9oCPKS7DjRMnTmDnzp1si1w7Ozv0798fAQEBRIG2n58f5syZw1EevXfvXvj5+QkMtNeuXYva2lrMnTuXErxqbW3F1KlT+Zbes3LlyhUEBwfDwsKC6O+5oaOjg6dPn0JTUxODBg1CREQEZGVlERcXR7TpI+54ANDS0kJ9fT3PAJBfJrmiogInTpzAypUrOQR53r17h7CwMDg5ORGpVJeUlCA0NFQkxe9OnTqhd+/eeP/+vdBjWbl+/TrWrFkDY2Nj5ObmwsTEBMXFxXj//j2xmvHevXsxc+ZMuLm5QVZWVqzjAYApU6YItFrriJaWFq5du4bx48fj999/R3h4OID26hNSgbTVq1dDTk4OUVFRlGaFsrIyXFxc+PqrA+0bCsOHD8fw4cNRV1eHS5cu4dSpU/D29sakSZOwfft2sasoSD/bnj174vnz51BWVsbNmzcpa8nm5mbizRxvb28quzZnzhwoKCggNzcXlpaWAhXxv/nmG7YM6cOHDzFlyhTq3zIyMpTaPDfEDdTpmuPfgNf309zcTOmA3Lp1C+PGjQPQvilD6vns5eWFJUuWwNLSksrUPn78GJ06dfrXqmH+TXx8fBAZGYlt27axWb/5+Phg4cKF0NbWhqenJ/z9/TnUzQFQ901WJX9h/dXPnDmDgIAA4s1uCRKERRJoS/iqMDIyQl5eHrS0tGBqaorg4GDU1dUhMTGRq8XU10xZWRnf55n90uIiKNg/ceIE1a96584dJCcnY+/evbh+/Tr8/f15+lsysbKywubNm7Fx40ZKVCkvLw+7d++msiF5eXk87WqA9kUSt5JPY2NjNDU18X19JuXl5VwXuD/++CNlv8WPzp07Y/fu3Vi1ahUKCgoAAHp6ekKVvXXr1o1SwxWV5cuXU4vsNWvWYNmyZfjpp5+goKCA/fv3E41n2kiJMh5oXyA1NTXB29sbSkpKQmWSIyIi0NDQwFX19ttvv8WHDx8QGRlJ1C8+bNgwPH36VGQPa3d3d+zduxc7d+4UypOXleDgYLi7u2PRokUwNjaGr68vVFVV4eXlRZwpr66uxuzZs2kJsgEIZUHFZOXKlVi/fj38/f0xZMgQqmojIyODb/knKwwGA05OTnBycqI2MHipG/NDXl4es2bNoqx7EhISsGHDBuJAW5Cau6AF/PTp0+Hm5gZlZWV8+vSJ2hh7+PAh8XfaUX1+8uTJfG2KWBkwYABiYmLg7e2N69evo66uDsOGDaOef/HiBd92F3EDdbrmYEJHywwpvO5nOjo6iIuLg6WlJTIzM7F69WoA7Rt/pOKUBgYGuHr1Ki5cuEC1H1lbWxOJf32NBAQEICgoiE2s1MDAAJ6ennB3d0dqaio8PT3h5ubGdbw4/uqsCGp/kyBBHCSBtoSvCjrEib4WrKysxFos0kVFRQXVl/zbb79h0qRJsLGxgb6+PmbNmiVwvLe3N/z9/eHq6orW1lYA7dlEe3t7SkxNS0uL6gXkhp2dHc6dO8fhf5uQkEC8eDU1NcWDBw84AvoHDx4IVTWgoaFBfR5VVVUIDw9HQkICrly5InDsqlWrEBYWBj8/P5GDKtbMu5aWFq5cuYK///4b3bt3Jwp4xR0PtJ978fHxIvnaZmRk8A0Ep02bhi1bthAF2uPGjYO/vz+eP38OXV1dDkVoQVUKW7ZswYcPH2Bra8vhIQ2Q+Qy/ePGCyo517twZ9fX1kJGRwdKlS+Hk5MRXW4LJhAkTkJ2dLbb9UW5uLhXMdAw4mFlZXkycOBGDBw9GVVUV28LZ3Nycen/CIEqADbRvOiQlJSE+Ph61tbWYPHkyvLy8hFLqP3LkCNu/W1pa8OTJEyQkJGDlypUCx7u6ukJPTw/l5eWwtramfqtSUlJE1TNMGhoa8OTJE9TU1HAElxMmTOA5bs2aNXBycqI0SpYsWcLWenPp0iW+bTziBup0zcGEjpYZVqqrq6GoqMi1DeDYsWNc+6jXr1+P1atX4/jx47Czs6M2j3777TcMHDiQ6HVzcnJgbGzMsWHb0tKCnJwcYt2Sr4Xy8nKu9wwGg4GKigoA/PvXy8rKYGxszLEp1dLSgtzcXKJN7AULFuCXX375bHZ5EiRIAm0JXxVfijjRl0DHHkPmYjEyMhJr1qz5x45DXl4e5eXlUFNTw++//w5XV1cA7YvOlpYWgeO7desGHx8fbNq0CSUlJQDav2fW0tZ+/frxnUNaWhq//PILbt26RS2K8vLyUFxcDAcHBzZrNV7WaRMmTEBAQACePHlCzfHw4UP8+uuvWL16NZu9EL8ArbW1Fb/99hvi4+Nx69YtaGhoEKvWnjp1CkVFRRg+fDg0NTU5FhiilmIKEppi8vHjR5iZmeH06dPQ1dUVejwTQ0NDVFVViRRov3r1im81hqqqqsBqDibM4JGbpzxJ6SGpyjo/5OXlUV9fDwBQUVHBX3/9BX19fdTX1xMLJPXt2xdBQUHIzc2Frq6uUF7cTEJCQhASEgJdXV0OyzXSDRRlZWWOkn2SIGTevHlEr8Evc5mamoqEhARkZmbC3Nwcrq6uGDt2rEjWbdy0PMaNGwddXV3Ex8fD0dGR7/jHjx9zFVkk7c8G2nu7PT098fbtWw4NAwaDgT/++IPn2H79+uHy5cu4f/8+lJSUONT9J02axLcCQ9xAna45mNDRMtPc3Ix9+/bh9OnTaGpqQkpKCmWXpqamhnnz5gEATyX0YcOG4c6dO3j//j3bps2PP/5InI2eP38+bt26xSEs+u7dO8yfP1/g9aalpQX+/v5YtGgRh6hmR5YvX851c+lLmQNo123Zvn07fH19oa+vD6C9F37nzp0wMzMD0C4WyitgFvfzBIA///wTmZmZuHHjBnR0dDiundzuDRIkCIMk0Jbw1UCnOBEJwpS7fo7xguZgDYSYGBoaQkVFBaGhoVTP9Odm/PjxcHd3h5aWFmpqaigLjSdPnghVstutWze+ftj8yM/PpzIQRUVFANozZkZGRmw3Y36f5/bt2wEAP//8M8/nmHNwu8E/f/4c586dw4ULF9ClSxeUl5fj8OHDRL6+TOhQ2m5sbMTPP//MswyTmwgUExkZGSgoKAhUPRbEokWL4Ovri6VLl0JfX59jccMvAO/atStKS0t5BtulpaXEC19xbd+ECZx4YWpqitu3b0NfXx/W1tbw9fVFVlYWbt26xWYDxI+4uDh06dIFmZmZyMzMZHuOVJU5NjYWe/bsEcpqZ82aNfD19YWcnJzAzTt+C9aOpZsnT57EtGnThPJHd3V1Ra9evbBo0SKoqKjgzZs3XC3BxFGoNjQ0RE5OjsC/c3R0hK6uLhwcHGBnZ4cePXoI/Vq7du2CnZ0dVq5cKdJ4RUVFnpUEHTcS7OzsEB4eTrWliBuo0zUHEzpaZg4ePIiMjAwcOnSIKvsGgB9++AFHjhyhAm1+dOrUCcXFxSgpKcHo0aPRtWtXKCgoELckMHuHO/L27Vuia5a0tDTOnz8vUK8AaLe7+5LnANpdYjw9PTF16lSq6qO5uRnm5ubw9fUFAHTp0gUeHh5cx4v7eQLt59Y/tRaS8L+JJNCW8NVAlzgRKf8FMTRu9OrV6x8rGweAzZs3Q0NDA69fv4a7uztVcVBZWUkpgH9u6PCfFjUoi4uLw7lz51BSUgJra2scOnQIgwcPRv/+/YW2JaFDaXvTpk3IysrCpEmTYGpqKvSGz7Jly7B//34EBAQIFQixwgzKWDPCpCI2JiYmSExM5FlmmZCQILIAoLDU1dUhMzOTElrU1NSEubm5UJ/Lli1bKJ2AFStWoHPnzrh//z7Gjx8PFxcXojnoUGWWkZEhLoFlwipyRip4xo2OlQFxcXFYtmyZUKXwzI0XfhtFpJsOTA0CJm1tbaiurkZoaCjRMV2/fh3nz59HbGwsAgICMHr0aDg4OGDUqFHEXud///035s+fL1KQLSyvXr3iqC4SJ1Cncw6AnpaZy5cvIyAgAIMHD2a75unp6aG4uFjg+MrKSri4uCA/Px+fPn1CamoqunbtisDAQHTq1InyWucG83rHYDDg5eXFFph/+vQJ+fn5RLZxADB27FikpaUJVOH/L8yhoqKCqKgo/PXXX3jx4gUAoE+fPmyJEnNzc45xdH6eEvsuCZ8bSaAt4auCDnGiuLg4zJw5k+PxtrY2bNu2Dbt2EbjdZgAAIABJREFU7QLQ3s/4OcbTNcfz5885xlZXV+PYsWO0CsOpq6tzZCRZkZGR4Wp90nE33NnZGT4+Pv95i42OC0Zvb28sWbIEq1evFqmMtSONjY24ceMGiouLMXPmTMjLy6OoqAjdu3dnK83kRXp6OiIjIzkyTKScOXMGhYWFsLCwgIaGBkfmgKR8XRwRm2XLlmH27Nno1q0bli5dSpUqM/vdL168SCROB7T/JmJiYhAXF4dXr14hOTkZmpqaOHLkCDQ0NPgq0SYmJsLb2xsNDQ3o2bMn2traKIXtrVu3CrTUsrOzQ0xMDPWdxcfHY+LEiUL18NLJ0qVLERUVhe3btxPbrbEuUv/tBSudFlDGxsYcG1BtbW1QVVVFYGCgwPFqampYsWIFVqxYgbt37yIxMRHr169Hly5dMHXqVEyfPl3g/cnW1hY3b978RzyixYVboC7uHA4ODmzfQWFhoVgtM2/evOF6b2lsbKS0P/jh4+MDdXV1REdHs5WwW1tbC7SvY25CtbW1cWg5yMjIwNHRETNmzBB4DEB7tU9ISAhyc3PRr18/jusvyfnypczBpG/fvkKt1+j8PCVI+NxIAm0JXxV0iBPt378fcnJyHIvsTZs24e7du599PF1z2NraUllCVgYOHEiVZQmCJKhLTk4mmksQOTk5xArgXzIdF4zLly9HYmIiUlJSYGdnh6lTp4osWlVYWAgnJye0traipqYGkyZNgry8PM6ePYva2lqiYEddXV0smyM6yteFzeSzMnDgQOzfvx9btmzByZMnqQqJ9+/fQ15eHkFBQcSetBEREYiJicHy5cvZPjt1dXXExsbyDLQfPXoELy8vLF26FAsXLqR61P/++29ERUVhy5Yt0NHR4atmW1BQwHae+Pr6YujQoULbajER14t75syZWL58OUaNGgUtLS2OYIZOZecvAX4Z1I7vVUpKCj169OD6uQjC1NQU2tra6NWrFw4fPozo6GhERUXBzMwMW7du5dnm5OXlhZUrV+L27dtce0fpqG75kul4jeHWNy8MRkZG+P333zkCwPj4eKLsZ3Z2NmJjYzl+n5qamgLtvZi/P3V1dSxevFgshfHTp09DTk4ODx8+xMOHD9meI63Y+FLmAES7brF+nk5OTkJX0zg6OiIiIgLdu3fn2NDpyJdoQSfhv4Uk0JbwVUGHOFFoaCiWL1+Obt26YcyYMfj06RM8PDzwxx9/EJUgizuerjk6Zg2lpKSgqKhIXHpXWFiIxYsXo6WlReSgTkJ77+jq1auRmZmJhIQE2NraQl9fH21tbXj37p1Qc/n6+mLs2LHw8vKi7JOAdoV50nPfy8sLgYGB8PT0hI6ODnH2kgldC3ymMN9ff/0FoD1D4uTkRNSHP378eIwYMQK3bt3Cy5cvAQDff/89RowYIdSi6+zZs9i1axdGjhyJPXv2UI8bGRlRx8WNmJgY2Nvbc9jOKCgoYO3ataiurkZ0dDSbyJ4gxGklocOL28vLCw8fPsSYMWOgpKRE/Np0CJn9G/DLwpKKdPGjtbUVaWlpOH/+PNLT06Gvr49NmzbBzs4OtbW1OHDgANasWcOz1D02NhY3b97Ed999h7KyMg5xuq890F61ahVycnLwww8/0FIJ5O7uDmdnZxQWFqK1tRWnTp1CQUEB7t69S3Ru8jpXKioqiK851tbWePnyJcc1Lj8/H9LS0kTikHRUbnwpc4h73RL1NzB69Ghqs3n06NG06OVIkMALSaAt4auCLnGiffv2Yd26dThw4ADOnj2L/Px8REdHc7X9oHs8XXOoq6sjJSUFJ06coDw7tbW1sWDBAq6KuB3x9fWFlZWVWEGdhHYYDAZGjBiBESNGoK6uDhcvXkRLSwvmzJkDY2NjWFtbE/W6PXz4ENu2bePo81RVVUVVVRXRsWhpaaG+vp5nafM/0b+fmpoKNzc3WFhYUDZF9+/fh4ODAw4ePEhkB9W1a1e+FkdM+GUuX79+jT59+nAd19zczHPO+/fvY/fu3TyfnzZt2j9qF0OHF/fVq1dx5MgRSu2XFDqEzDqW+re2tiIpKYmjP/lzl1GzOgfwQ5CAoZ+fHy5duoSWlhbKWpA1uPr222+xceNGvvMcOXIE27Zt+0d0LL7UQIOXqrQomJqaIikpCUePHoWenh7S09NhaGiIuLg4os29ESNG4OTJk2xl4vX19QgNDaUEPgWxZcsWzJ8/n+P1CgsLcfLkSfzyyy9CvSemK4GoVTD/9hziXrcqKyuxZ88eZGVloaamhmOzkte9jDVAZxXGkyDhcyAJtCV8VQiy9eFnC8TKqFGj4OPjg2XLluH7779HbGysUFkeccfTMUd4eDhCQkIwY8YMarH24MEDbNy4EcXFxQJ7QekI6iRwIi8vjzlz5mDOnDnIz8/HuXPncPjwYaJAW1pamrKCYqW4uJjYYmvt2rVoamqCt7c3lJSUhF5kGxgY8BwjKyuL3r17Y/r06XwVaQ8dOoQ1a9ZwKNIePXoUBw4cEMl3mRf8Mpfa2trIzc3lsKhJSUnhu/iurq7ma2ujoaFB9BtJSEigsmHiBJd0eHGrqKiIJLxFh5BZRxtGJSUlJCQksD0mTDmqqCxbtow6t3lVGJDYvj1//hxeXl4YN24czzYNRUVFrg4GTKSkpIhV58VFXGHOz+WgQYdgKMBuR+Xj4yPSHJs2bcLixYthZ2eH5uZmeHp64sWLF/j222/ZqmH48ezZM66CgwMGDMDTp0+JjyU6OhoRERGorKwEAHz33XdYvHgxkXL6lzSHuNctT09PVFdXw9XVFcrKyiKdh2PHjsW5c+c4rn11dXWwt7cXS09EggRAEmhL+MqwsrLie7HltUDiZU2jqKgIRUVFSnwM4G5TI+54uuZg5cSJE9i5cydblt/Ozg79+/dHQECAwECbjqDufxFhbvYGBgbYsmULW7DCLwNrZWWFw4cPY9++fdRjFRUVCAwMJLYoefLkCeLj40XysAaAnTt3Ijg4GDY2NtSi8dGjR/j111/h7OyMqqoq6vzkFWy/ePGCa1XFxIkTERISItJxicKqVauwadMmVFVVoa2tDdevX0dRURHi4+Nx+PBhnuMaGxv5lrPKyMjwzYgD7Zt+rBkscYJLOry4PTw8sHfvXvj4+EBVVZVoDF3QKWQmDqqqqmAwGLC3t4e9vb3IWgqRkZEC/0ZaWppvifrcuXNx6tQpbN68WaRj6Eh1dTUUFRW5qp4fO3aMuFKKG5/TQYOOIF4YOypeqKqqIikpCZcuXcLTp0+pqiA7OzvinmsZGRnU1tZynFdv3rwhVqMPCQnBzz//jGXLllHuCvfu3cOhQ4dQV1eHlStX/mfmEPe69eDBA8TFxVEe3KJQWlrK1a6yubkZFRUVIs8rQQITSaAt4auiY79bS0sL1QvKz+eVV48Vq7ooP8QdT9ccrDQ3N3MVeTE2NiYSHaMjqPtfRJRFJ2vQxi8Du3HjRqxZswYjRoxAU1MTFixYgMrKSgwcOBDr1q0jei1DQ0NUVVWJHGhfvXoVHh4ebH7Ltra26NevHy5evIjjx4+jd+/eiIqK4rmwVVVVRXZ2NrS0tNgez8rKEmvBLyzjxo2DgoICQkND8c0332D//v0wNDREWFgYRo4cyXcsaza6IySLRDqDSzq8uJlCkmPGjIGcnByH+BaJkOQ/Bb/NKFK4BXBpaWm4ffs24uPjMWXKFPTv3x8ODg6wtrYmCqboKj0HgKdPnyIjIwM3btyArq4ux/dBstna3NyMffv24fTp02hqakJKSgo0NTWxd+9eqKmpUZlHU1NTgXPREaiLMoePj49AXRESvRBR7ajmzp0LMzMzDB06FMbGxkL5zHfE3Nwc+/fvR0hICFVm/f79exw4cID4d3rmzBn4+PjA2tqaeszExASamprw9/cnCnC/lDnEvW5paWmhsbFR4N9xg/W3evv2bbZWl9bWVmRmZool2ilBAhNJoC3hq0JXV5fjMUNDQ6ioqCA0NJRngCiusBcdwmB0i4sxewPXr1/P9nhCQgImT54scDwdQZ0weHt709KL928jbnaIH/Ly8oiKisLdu3eprIqRkRGGDx9OnPlZtGgRfH19sXTpUujr63Ms4AUF4Dk5OVw9YwcNGoRt27YBAIYNG8a3RHPhwoXw9vZm8zu9f/8+zp0794/3/5uamiIqKkqoMR2z0dwQJwjkBr/gkg4v7v+S7gIddlLcNsQYDAaGDx+O4cOHo66uDpcuXcKpU6fg7e2NSZMmYfv27XwV++kqPQfa+11JNAj4cfDgQWRkZODQoUNsvag//PADjhw5IrDEl45AXdw56uvrxf6uAdHtqLS0tJCcnIzQ0FDIyspi4MCBMDMzg5mZGQYNGiSUg8PGjRuxcOFCWFlZwcjICADw+PFjKCoqEt//a2trudpz6uvro7a29j81h7jXLU9PTwQEBGDt2rXQ09PjuJfx2xxjti0xGAyONZK0tDTU1dWxceNGovchQQI/JIG2hP8JevXqJbTIU3FxMZsisrBlhOKOF2UOVpVjaWlpnDp1Crdu3aJKfPPy8lBcXAwHBweBr01HUMeERJTNzs5OqDn/adra2nDp0iVkZWXhzZs3HOVmR44cAUCWHRKVZ8+eQU9PD6ampiK/DrOygzWwYtrAkQQB3333HRISErB27Vq2x8+fP0+VHL99+xby8vI855g7dy6UlZURFRVFVaFoa2sjMDBQ7OCiI6Tnal1dHcd3yqtF4t8odeYWXNLpxS2qkOSXImTGDXGysPLy8pg1axaMjIwQGBiIhIQEbNiwgW9gRVfpOUDPxuvly5cREBCAwYMHs/0O9PT0UFxcLHC8uIE6HXP4+vrSsgErqh0V0wqzoqIC2dnZyMnJQXJyMkJCQiArK4tBgwbBzMyMKIOrpqaG5ORkJCcn49mzZwCAqVOnYvLkycTK6np6eoiLi+MQWzx16hTXwPdLnoN53QLaNQmEvW4tWrQIQPv9hBv87mX5+fkA2iv3zp07x3YsEiTQiSTQlvBV8fz5c7Z/t7W1obq6GseOHSO++NfV1WHz5s24du0adfNraWnBuHHj4OfnJ1BNV9zx4syRl5fH9u9+/foBAIqKigAAcnJyMDIyom4yJIgT1AHii7J9KXh7eyMhIQHm5ubo2bPnv6LUO2XKFOjq6mLKlCmwtbUVKWsqrrjLhg0b4Obmhps3b1KK03/88QcKCgpw4MABAO1CeqwlhdywtrYW+Dd0wK+Uv7i4GDt37kR2djZbEEu66UAKHaXO3BDXi7uhoYH4tXhlh74UITMmdGRhq6urkZSUhPj4eNTW1mLy5Mnw8vJC9+7d+b62uKXn3BBnw/bNmzdQUVHheLyxsRGtra0Cx4sbqIs7B53XWHE3x7777jvY2dlRG8KVlZWIiYlBTEwMcnJyiAJtoL1NSBx3FA8PDyxbtgyZmZlUNVBubi5KSkoQHh7+n5pDXPFaOiwDvxR9CAlfL5JAW8JXha2tLZWdY2XgwIHUzrQgdu3ahZcvX+LMmTNsYk9eXl7w8fERqDAq7nhx5iD12OZFx+wUP0gXzuKKsn0pMLMYgnp3xYXf4vLq1atITk7GhQsXsH//fhgbG8POzg4TJ04kFqgTt+9s3LhxuHz5Mk6fPo0XL14AaLe+OXToEKXEzevcqKiowIkTJ7By5UrIycmxPffu3TuEhYXByckJysrKQh2TqJnL9evXQ1paGoGBgZ9184SOUmcShNUHMDY2FvieBW06fGkLVXEyqKmpqUhISEBmZibMzc3h6uqKsWPHEmcbxS09Z4WODVsjIyP8/vvvHL/H+Ph4rvodHRE3UBd3DrpUx+ni6dOnyM7OpjLbbW1tVP82Kb/99htOnz6NkpISREREQE1NDXFxcdDU1CTyjh42bBhSU1Nx6tQpagPGysoKs2fPJm5Z+lLmEFW8lgkdfvcA8Pfff+PmzZt4/fo1h4jl1+5XL+HzIwm0JXxVdMzWSUlJQVFRUaCYCis3btzAsWPH2Gw4Bg4ciJ07d3LYEX2O8XTNIQods1O8ECZDJa4o25eCgoICsT2cOPBbXGpqasLFxQUuLi7Iz8/HxYsXER4eDh8fH1hYWFDl6x1JT0/H8OHDISMjI1CwiUSoSVNTk6OvjYSIiAg0NDRwBNlAu7fwhw8fEBkZSdQvTEfmsqCgAAkJCTy9tL926MgICcvnEjJjIk4G1dXVFb169cKiRYugoqKCN2/e4MyZMxx/R6oEL2zpOSt0bNi6u7vD2dkZhYWFaG1txalTp1BQUIC7d+8SfffiBurizhEdHS2wioAVfudWS0sLEhISeLb+8Po8Tp48SQXW0tLSMDU1xbBhw7Bq1Sqh1a4TEhLg5+eHWbNm4fbt29Tmm5SUFI4fP04UaJeVlUFNTY2jdYf5HMk96kuZQ1TxWiY5OTl8nx8yZIjAOe7du4fly5fj22+/RUVFBTQ0NFBRUYFOnTqhT58+kkBbgthIAm0J/3mEsQMiuWi2tLSgS5cuHI9/8803RFkpccfTNYcofI7slLiibF8Ka9euxf79++Hn58e3/5gEOhR8DQwMYGBgAAsLC+zevZtvAL1s2TJkZGSgZ8+efDdqSMulKysrcerUKarnXkdHB7NmzRKYic7IyMDOnTt5Pj9t2jQOuzNe0NE/amxsjOLi4v9EoM0ruBTHi5uujJAwfC4hMybiZFCZwUHHAIAVkk1GUUvPWaFjs9XU1BRJSUk4evQo9PT0kJ6eDkNDQ8TFxfH1iWcibqAu7hzCnp/8zi1vb29cvHgRVlZWMDQ0JJ7T19cXvXr1gqurK6ZPn871vkxKZGQkfHx8MHHiRMTExFCPDxo0CPv37yeaY+zYsbh16xZH33ptbS3Gjh1LdP3+UuYQVbyWCbdrPOt1kuQYAgIC4OjoCE9PTxgbG+P48eOQl5eHu7s7VwtKCRKERRJoS/jPk5aWxvbvoqIiNDc3UyWypaWlkJWVJd6dNDMzg5+fH/bt2wclJSUAQFVVFXbv3o1hw4Z99vF0zSEuISEhWLx4MUdvYWNjI44fP873s6RTlO1LYeTIkThz5gzMzc2hpKTEoXAqqPeZTqudvLw8JCcn4/Lly6irq8OoUaPYgs2OsPbkC9Ofz42cnBw4OztDXV2dykilpqYiKioKx44d43v8r1694pvpUFVVFdi3x4SO/lFfX19s3boVxcXF0NHR4fhOSTIi/xTcgktxvbifP38ObW1tSElJcehbdERUOzhREXUzSpwMqrgbjeKWnrNCx4avv78/Fi1axNcBgB/iBup0zUEHV65cQXBwsNB2mUFBQcjJyUFMTAz8/f3Rv39/DB06FEOGDIGJiQlPiz9uFBcXY8CAARyPy8rKEvvd89pkamhoIK7c+1Lm4AWpeO39+/fZ/s3MiB84cACurq5Er/Xs2TOqOkRaWhqNjY3Q1NTEunXrsHr1ajg6Ogr/BiRIYEESaEv4zxMfH0/9/6lTp3D9+nXs3r2byq5VVVVh06ZNGDNmDNF8W7duhYuLC0aPHs0WrPft25dICVbc8XTNIS6hoaGYNWsWR6Dd0NCA0NBQvoH25xBl+7dxd3fHy5cvsXTpUigpKQndz0uXgu+vv/6KV69ewczMDG5ubpgwYQLXUuzPxe7du+Ho6AgvLy+2x318fLB7926cO3eO59iuXbuitLSUZ7BdWlpKLBpFR/9oUVERnjx5glu3bnE8R6cYGum5ImxwKW5gaGtrS1U6cNO3EEaNng7o2IyiIwtLSsdSZTpLz8XdbJWWlsb58+d5etkLgo5AnY456KJbt24itStMnjyZqryqrq5GTk4OcnJysGfPHhQVFcHIyAhDhw4laqXp1asXnj59yqGTkZGRAW1tbb5jmZvXDAYDoaGhbJswnz59woMHDwRuXHwpczARV7yW2yaHmZkZPDw8sGPHDly4cEHgHKwbV0pKSigpKYGuri6kpKRQU1ND9D4kSOCHJNCW8FVx9OhRHDt2jK2EVVlZGevXr4ezszPRAkddXR1JSUnIyMigSmP79u1LbGsl7ni65hAX5gK7IwUFBQJLIMUVZfsSycrKQmxsLKW0LSx0ZGBv3ryJ2bNnY/LkydTiWxQyMjJ49ioK2sh59uwZAgMDOR6fM2cO16CCFRMTEyQmJvLMFCckJMDExETA0bdDR//otm3bMGrUKLi4uHxWMTR+pc50VjoIomNgeP36dcrWRlw1ejqgYzPqn8ygdixVpqv0HOC/2ern50d0fGPHjkVaWhrmz59P9PesiBuo0zUHXaxatQphYWHw8/MTOeOqpKSESZMmYdKkSfjzzz9x5coVxMbGIi8vjyjQdnJygre3Nz5+/AgA+PPPP3H58mUcOXIEO3bs4DuWuXnd1taGx48fs1VJdO7cGXp6enBycvpPzMGEDvFabnTr1g0lJSVEfztw4EDcv38fffv2haWlJfbs2YPnz58jNTWVrW1DggRRkQTaEr4q6urq8Pfff3N9/N27d8TzMBgMWFhYCF1mRtd4uuYQhWHDhoHBYIDBYMDGxoYt+Pj06RPevXuHn3766R89pi8BLS0tjqBUGOjIwPLLFpNy4MABHD16FIMGDeJ6PILo0aMHCgoKOPqanz17JlD5fNmyZZg9eza6deuGpUuXslWdhIeH4+LFi8TK93RkLt+8eQMXFxf07t2b6O/5IWqpMx3BJSkdA0N1dXXKi5sZzDG9uEktwoTlcwmZAf9+BpVOjQs6Nlt1dHQQEhKC3Nxc9OvXj6NaRFDAL06gTuccpPD7XE6dOoWioiIMHz4cmpqaHG0igq6tjx8/RnZ2NrKysnDv3j28e/cOPXv2hKWlJczMzIiO78cff0SXLl0QFBSEhoYGuLm5QVlZGRs2bMCUKVP4jmVuXm/atAleXl4iVTF9KXMwEVe8tqMuSVtbG6r+r727j6v5/v8H/jh0YSLXc5lsUmhJIVfDZJsxNkZzNdcUGxFWKny2RheIzXzRFJNGmIuxz8h+ZjaMj4ukIWaysrkuShHl/fujT+fjXHQ6nffrdE7H43677Xaz9+n19MrO3nqe5+v9fN6+jW+++UbvD1vnzp2rPLbv7++P/Px87NmzBy1atMDcuXP1ikGkCxNtsih9+vRBSEgIgoODlZ9GpqSkYPHixejTp4/ecQ4cOIC4uDiV+aUTJ06Et7d3hawXFcMQQUFBkCQJISEh+PDDD1XGyFhbW6s8m1ua0aNH6/3DoCk6HxsiMDAQkZGRmDVrFlxcXDR+UCvryLOhFdhdu3bpvcdBgwaV+TVbt27FkiVLMGDAAL3jPmvo0KGYN28erl27ptz36dOnERMTU+YP0+3atcPy5csxb948bNy4UflD2oMHD2Bvb4/o6Gi4u7vrtQ8RlUtvb2+cOHHC4ERbRDVaxEkHOeTO4i4vYzUyA8yrgqqPsjqwa/uw9dy5c1ixYgViYmLKjL9lyxbUqFEDKSkpSElJ0YhdVqItN1EXFUNfut5bvXv31vvxsWdNmTIFp0+fRm5uLurUqQMvLy/MnDkTnTt3RsuWLfWOU1hYiAMHDuDVV1/FO++8g4cPHyI/P1+jmVhZZs2ahQcPHmgkuDdu3ICVlZVeJ53MJYbcUZPqTQEVCgXq1q0LLy8vvZLkoqIi5ObmokWLFgCKj6KHhYXJ2hOROibaZFHCwsIQGRmJGTNmKH8wq1q1KgYPHqz3p5ObN29GeHg4hg4dihEjRgAoHgExc+ZMhISEYPjw4UZdLyqGoUrmXTdr1gweHh4GNfJ59nh1yViVJk2aoH379gCKP/z4+++/K1UztEmTJgHQ3ukUKLvDqaEV2MjISJV/z8/Px+PHj5X/XZ48eQIbGxvY2dnplWgDMPj4OwBMnz4dNWrUwPr165XP6zVo0ABTp07VK8F544030L17dxw+fBh//fUXAKBFixbo3r273o2FRFUuXVxcsHTpUpw+fRrOzs4aH56UlQSIqEaLOOkgkojZxaZoZFaiIiuocpXWJfvXX3/F0aNHYWVlhaFDh8LR0RF//vknoqOj8fPPP6Nnz556xZdbYZebqIuK8SxD31uGjmmysbHBjBkz0LlzZ1kNAa2srPDxxx9j7969AIo/mNW3H8Wz5syZgwEDBsDHx0fl+pEjR/Dvf/8b69atqzQxSpsYo1AoYGtrC0dHR/To0aPUTu9ye7xUrVoVw4cPx969eyu0zwk9ZyQiC/TgwQPpwoUL0oULF6QHDx6Ua+3rr78ubdmyReN6YmKi9Prrrxt9vagYhsjPz1f5ta5/9PXJJ59IkZGRGtejoqKk+fPnC9l3RTh+/LjOf/SRkZEhhYaGSkOGDJH69esnzZo1S7pw4YLee0hKSpJ8fHyk1NRU5bXU1FRp2LBhUlJSkl4x1qxZI4WHh+v9e+qSm5sr5ebmComlzYABA6R//vlH62seHh5SRkaGrPi9e/cu9R9vb2+91p88eVKSJElq3769cj/p6elShw4d9NrD8OHDpYSEBI0YCxculMaPH2/It1WqZ+OXcHFxke7cuaPza/RRUFAgRURESO3bt5fatGmjjBEVFSXFx8frFePEiROSh4eHFBYWJrm5uUmRkZHSxIkTJXd3dyklJUWvGGvWrJE6deokzZw5U1q7dq2UkJCg8o9Ict+D2v6st27dKrm6ukqDBw+W3N3dpc6dO0s7d+6UOnbsKC1YsED6888/5W670hHx3pIkSXr48KG0d+9eKSYmRrp//74kSZJ05coV6e7du8L2quueNXLkSOnAgQOy4nt6ekpXrlzRuJ6eni517NixUsV47733JE9PT8nV1VV68803pTfffFNydXWVPD09pbfffltyd3eXXn31Venq1atlxnrw4EG5f9aTJEkaNGiQdOzYsXKvI9IXK9pkkezs7AxufHP9+nWtz1x16dJFr+qZ3PWiYhjC09NTORvTw8ND6/FvqZxdiL///nts27ZN4/r777+PoUOHVoqjWk+ePMG6desQHBwMR0fHcq8XVYHx5iuYAAAgAElEQVSNjo7G0qVLVSrSr7zyCkJCQjBr1iy8+eabZcY4d+4cjh49ip9//lnrSKsvvvhC7/0Yuwqgay6uiMql3IqfiGp0RXbJNsYs7hLm0shMdAVVF0lA9V9dfHw8/vWvf8HHxwfHjx/H2LFjsXnzZuzZsweNGjUqV6yS00SlNT6sLI/tiHhvXblyBRMmTEBRURGysrLQr18/2NvbY9u2bcjOzhY2zUPXPeuDDz5AZGQkbt68CVdXV40TPPpUzCVJQkFBgcb1/Px8vefTm0sMHx8fHDx4EBEREcqmjFlZWQgJCUHv3r3Rv39/BAQEIDw8vNRHJeLj4xEXF4dbt24BABo2bIiJEyfq3dti1qxZiIqKwsyZM/HKK69onDIw5NQB0bOYaBOpcXR0RFJSEnx9fVWuJyUl6ZVkyV0vKoYhNmzYoOwoHhERgUaNGqFq1aoqX/P06VNcv35d75jW1tY4c+aM8jmoEmfOnDHoWLopWFtbIzk52eD1op4dvXHjhtZkSaFQ4Pbt23rFsLOzwxtvvFGu33fo0KGIi4tDrVq1MGTIEJ3P34to2KaPinz2szQijjpXZJdsbYmh3FncJcylkZnIhmSA4UeVDZWZmYnu3bsDKB5VZGVlhcDAwHIn2UDxo1R79uyBt7c32rRpU+71IhJ1ETFE9DFYtGgR+vTpg9DQUHTo0EF53dvbG0FBQXrFkCsgIAAA8OmnnyqvlXeEXocOHbB27VosXbpU+WchSRLi4uL0nthgLjFWr16N2NhYZZINAHXr1kVAQAB8fX0xbNgw+Pv7a/wcVGLlypXYsGED/Pz8lL/nqVOnsGLFCuTk5OCjjz4qcw+TJ08GAPj6+mr9e60ixhqSZWOiTaRm2rRpmD17Nk6dOqW8eZ8+fRqHDx/GsmXLjL5eVAxDeHl5KX8dEhKirG4/Kzs7G+PHj1c+y12W0aNH41//+hcuXLig0qBu27Ztpf4Fao4GDhyIHTt2KH9YKi8RFdguXbpgwYIFCA8PVyZhaWlp+OSTT/SarQuUPb5Lm9deew02NjYAYFBDIWMQUbkMDg7W+XpZf1Zyq9HG6JJd0bO4S1hSI7OKGrmm7Qf7R48eqXRdtra2Nmg6AADs27cPX375pcGTK+Qm6qJiiDg5kpKSggULFmj8f9GoUSO9P6SUS8QIvTlz5mDs2LHo16+f8v138uRJ3Lt3T+8TCuYSIycnB/fv39d6PScnB0DxlIvHjx9rXb9161YsXLgQffv2VV7z9PSEg4MDIiIi9Eq0K8upDqq8mGgTqenXrx+aNm2KDRs2YN++fQCAl19+GYmJiXBzczP6elEx5JJKmaP98OHDcs0hnTp1KhwcHJCQkICdO3cCKP5ewsLCMHDgQGH7NTaFQoGEhAQcPXpU6xGzwMBAnetFVGAXLVqEoKAgDBo0SPnf4PHjx+jatausRO327dvYuXMnduzYoXy/PevZRkKGNhUSTUSCWDLWpURhYSH++OMPZGdnK6uKusitRotKLk05i7uEuTQyE1FBraiRa6UdPRdxlB8oPr1SWkdzfchN1EXFEPHesrKyQn5+vsb1jIyMMscSiiK3yzZQ3MBx7969+Oabb3Dp0iUAxfOoP/jgA72/D3OJ4e3tjZCQEMydO1f5c01qaioiIyOV01VSU1M1TsOVyM7OhrOzs9a9ZWdn67WHZ4sLunzyySfw9/dXqb4T6YOJNpEW7dq1Q3R0tMnWi4phiJJO0gqFAitXrlTp+Pn06VOcOXOm3EdaBwwYYPA4KXORlpaGtm3bAgAuX76s8po+o8xEVGDr16+PuLg4pKenK2frvvzyyxozrfVRVFSEn376Cdu3b8fhw4fRrFkzlcqAvjIyMlBQUICWLVtqraLKoe+IOEOtWLFC45okSVi0aFGZY3dEVaNFJJemnMVdQsSz5iI+jBJRQRU5cq28JwxEHeUHij8UW7VqFcLDw8v14WgJuYm6qBgi3lve3t5YvXq1yomwmzdvYunSpeV+lEYX9XvWoUOH0K1bN1hbW2vMfVbXq1cvvX6POnXqwMfHB9evX8eTJ08AFI/pA4BOnTpVmhhhYWGIiIiAv79/qVNiHB0dS+3j4uzsjMTERI2TSZs2bdKagMuxe/duTJw4kYk2lZtCMkY3D6JK7tGjR9izZ49yhnXLli0xYMAAvRtjyF0vKoYhSn4oP3HiBNq3b6/yHLWNjQ2aNm2KCRMmlPopsy45OTkaFaaKqiZYqrKq0eouX76Mb7/9Frt370a1atVw48YNrF69uswf8h49eoTPP/8c586dQ/v27TF9+nTMmTMH+/fvh0KhgKOjI9auXQsHBwdR3xo8PDywe/durTGN2ejp6tWrGDFiBH777TedX+fp6YnvvvtO1vccExODuLg4dO/e3eDk0tvbW5kYPvtndvXqVQwdOhQnT540eH/qdP03yczMRExMDNLS0pCfn482bdpg8uTJ5ZprXhqFQqHX0VsvLy8sW7ZMVgXV3d0d33//PRwcHFS+37S0NIwYMaLMfg36njAwtiFDhiA9PR0KhQIODg4ajQ/L6qewfft2HD161OBEXVQMQP57KycnBzNmzMD58+eRm5uLRo0a4datW3Bzc0NsbKywufHq/3+0bt0aR44cQb169XTuVd9ntG/cuIGAgACcOXNG6+uVKUaJvLw8ZGZmAgAcHBz0/m9x7Ngx+Pn5oXnz5sqTDcnJycjIyMDatWv1rlbrQ9d9j0gXVrSJ1Jw9exZTp07F06dPlRWR7777DsuXL8eaNWuUzxkba72oGIbauHEjgOLnV0NDQ2V3ls7IyMCnn36K//znPyqVsPJ2LzcXjx49Ula1mjdvXuqMT2MypBqdmJiIb7/9FpmZmejbty9WrFiBDh064JVXXtHrSOPixYtx8OBBvPXWW/j555/x+++/Iz8/H1u2bIFCocCSJUsQHR2Nzz//vFzfi6HNpkRULktz/vx5varzIqrRIk46mHoWtzk1MhNRQZV7VLkiTxiUdpQfKO6nIKenwqZNm5Ceno5u3boZlKiLiCHqvWVvb4/169fj1KlTymS9bdu26NatW7lPzpTnnvXsrGe5c58BYOHChahevTp+/PFHDBw4EPHx8cjOzsayZcv0bupmLjFKGDolpkuXLti/fz82bdqkLEh4e3tj5MiRwpsUEhmKiTaRmgULFqBbt25YtGiRsgFUQUEB5s+fjwULFmDXrl1GXS8qhlyixp3MmTMHVlZWWLp0KerVq2f048DG8vjxY0RHR2Pz5s3K5iw2NjYYOXIkZs+eXWYHdREVWEOr0UBxYjpp0iRMnz7doG7vBw4cQGRkJLp27YrRo0fD29sbGzZsgLu7OwDg448/xocffqhXLBHPFIt49nPGjBkq/y5JEu7cuYOUlBRMmjSpzPUijjqLSC5FPMMqhzk1MpN7XBqQf1RZ5NHzsugaJyW3n4LcRF1EDFHvrZUrV2pcS05OxpkzZ2BrawtHR0f06NGj1A9ODb1naft9tVEoFHo17zp58iTWr1+PZs2aQaFQoEaNGnBzc0PVqlWxZMkSjccMzDnGgwcPsHbt2lL/TizrBMvGjRthb2+v0aB09+7dyM3NrZDJE0RlYaJNpObKlSuIjo5WJrgAYGtrCz8/P706bctdLyqGufjjjz+wY8cOg54jNieLFy/G//t//w9RUVEqo0QWL16MoqIihIaG6lwvpwIrtxoNAFOmTMGuXbuQlJSEgQMH4t133y3XMbjbt2+jZcuWAIqfI7W1tVWpojVu3BhZWVl6xRJR8RNRuVSfY6tQKNC8eXNMmTIFPXv2LHN9Rc5s1sUcZnGbSyMzEVVYuU3uTH3CQP33/Pnnn5GRkYHhw4fD3t4e6enpqFWrVpnPm4pofCgihoj31sGDB3H16lUUFBQo75l///238j527do11KxZEwkJCVpHaBp6zzp48KDKv6enp+Px48cae3jppZf0SrSLioqUp8zq1KmD27dv46WXXkLz5s2VVd3KEiMkJARnzpzB4MGD0aBBg3J/CP/1118jKipK43qzZs0QFBTERJvMAhNtIjVt2rRBRkaGMqko8ddff8HFxcXo60XFMBceHh7IyMio9In2v//9b0RHR6Nbt27Ka/3794e9vT0CAwPLTLTlVGDlVqMBwN/fH9OnT8fRo0exY8cODBgwAC4uLpAkCbm5uWWuf/r0qcpM9SpVqqj8YFQyD1YfIip+IiqXck9tiKhGi0guTT2LGzCfRmZyK6gijiqb+oRBiStXrmDChAkoKipCVlYW+vXrB3t7e2zbtg3Z2dl6vf/lJOqiYoh4b/n4+ODgwYOIiIhQ/p5ZWVkICQlB79690b9/fwQEBCA8PBwxMTEa6w29Z23fvl35602bNilPBjVo0ABA8QeYwcHBer9nnZyccPHiRTg4OMDd3R1xcXGwtbVFYmKi3h+cmkuMI0eOIC4uDu3bt9fr69XdunVL6xHxBg0a4ObNmwbFJBKNiTYRVLtIjx07FgsXLkRmZqbK3OeEhIRSZyjLXS8qhjlatGgR5s+fj4yMDDg5OWlUmPTtcGpqeXl5Wv9Sb9SokcaYKG3kVGDlVqNLKBQKdO/eHd27d0dOTg727NmDwsJCjBo1Ch4eHujbt6/OqpGusUP6/BmUEFHxE1G5PH78OBQKhUbTnBMnTgComPem3OTSHGZxA2Kq+yIeB5BbQRVxVLkiTxjosmjRIvTp0wehoaHo0KGD8rq3t7dez9GKSNRFxBDx3lq9ejViY2NVEvu6desiICAAvr6+GDZsGPz9/eHr66t1vYh7VkxMDNauXatMsoHipHDOnDnw9fXV6/uYMmUKHj16BKD40Rc/Pz8MGzYMtWvXxvLly/Xah7nEqF+/vqzmrg0bNsTZs2c1/i5MSUlB/fr19Ypx4sQJeHh4aPz9UVhYiOTkZOXfAVOmTEGtWrUM3is9v5hoE6F4/JR6RS48PFzj62bPno3+/fsLXy8qhjlKT0/HhQsXcPjwYY3XKlMzNHd3d6xatQoRERHKI/2PHz/GqlWrlM8p6yKnAiu3Gq2Nvb09Ro0ahVGjRiEtLQ3ffvstVq9eXWqirc/YIX0/SBBR8RPx/GhERITKMdASDx48wJdfflnmc4YiqtFyk0tzmcVtLo3MAPkVVLlHlSvyhIGu47YpKSlYsGCBxgcmjRo1wu3bt8uMLTdRFxVDxHsrJycH9+/f13o9JycHQPER6JL+G+pE3LNycnJw7949rdf1vY8/24/D0dER+/btw71791CrVi29j16bS4yQkBBER0fjs88+M6h52dChQ7Fo0SIUFRWhc+fOAIo7kUdFRendcHDMmDE4fPiwxjjH3NxcjBkzRvnziZ+fX7n3RwQw0SYCUHbTDWOvFxXDHC1YsAA9e/bE1KlTK3UztNDQUEyaNAm9evVSztM+f/48qlatiri4uDLXy63Ayq1G69K6dWvMmzdP5Qdf9W7GIn7YLSGi4ifi2c/09HSt81ZbtWqF9PT0MteLOOosIrmsbLO4SyPicQARFVQ5R5WNccJAF12Pa1hZWSE/P1/jekZGhl5jFeUm6qJiiODt7Y2QkBDMnTsXbm5uAIDU1FRERkYqx8qlpqaWOrZSxD2rT58+CAkJQXBwsMpJtcWLF6NPnz4Gf28iRmSaIkZQUBDy8vLw2muvoUaNGhp/J5Y1XtHPzw9PnjzB/PnzlR+Q2NraYtKkSXonxiXTT9Tdv3/f6KNU6fnARJsI0LuhlLHWi4phju7evYupU6eiefPmpt6KLK1bt8aPP/6oMtu8b9++GDhwoF5/IYuowJYobzVaX88+/62rm7E+dI0dElXxk1u5tLOzw/Xr1zWOHl67dk2vRE/UUWe5yaWIZ1jlPjdvLo3MRFRQ5RxVNkYHdkNH4Hl7e2P16tVYtmyZ8trNmzexdOlSvPHGG2X+vnITdVExRLy3wsLCEBERAX9/f+VR76pVq2Lw4MGYO3cugOLKbFhYmNb1Iu5ZYWFhiIyMxIwZM0rdw/OkvGPA1CkUCkyfPh1+fn64evUqAKBFixYqTWRLUzJxQqFQIDQ0VGXN06dPkZaWVqH9FMhyMdEm0uKnn35CYmIirl27hri4ODRu3FjZ5KN79+5GXy8qhjnw9vbGiRMnKn2iDQDXr1+HJEmoVasWnj59ilu3bimr2WVVWEVUYLXRpxptCqUl6qIqfiIql71790ZkZCRWrlyJJk2aACjuAhwVFaXXhyIiqtEikktzmMVtDo3MADEVVLmnN0ScMBAxAm/u3LmYMWMGunfvjoKCAowdOxa3bt2Cm5sbZs2aVeYe5CbqomKIOjmycOFCBAcHIzMzEwDg4OAAOzs75de4urpqXSvqnlW9enWEhYUhKCio1D08T0RNULGxsdF6MkmXkl4jkiShWrVqKmPdrK2tMXToUPj4+AjZHz3fmGgTqdmxYwfCw8MxYsQIHDt2TJksVKlSBbGxsWUmuXLXi4phLlxcXLB06VKcPn0azs7OGolEZRnB8c0332DhwoWoX7++xigShUKhVyItooNvaURWo41JVMVPROUyMDAQ06ZNw5tvvqlMtP/55x94enrqVWESUY0WkVyawyxuc2hkBoipoMol4oSBiKP89vb2WL9+PU6dOoW0tDTk5+ejbdu26Natm16P8MhN1EXFEPHeKmFnZ1fu5+RFn1IwZA+W7vbt23jy5InKtZJ7sjGUfBDbtGlTTJgwQWPUI5EoTLSJ1Kxbtw4LFy7EW2+9hYSEBOV1d3d3vbppyl0vKoa5SExMxAsvvIDffvtN45mripw1LNdXX32FwMBAjB8/3qD1IiqwlkJExU9E5bJWrVrYuHEj/vOf/+DSpUsAij8Y0rfbuIhqtLFOOpSX3GdQzaWRmYgKqtyjyiJOGIgYgbdy5UqNa8nJyThz5gxsbW3h6OiIHj16qFTzniU3URcVQ9R7Sw4R9yxSlZOTg7CwMOzfv18jyQZQIY1SzeX+S5aLiTaRmoyMDGWzlGfZ2trqNcJI7npRMcyFyCZappSfny+rYY2ICmxFMmbTOhEVP5GVSy8vL40RX/oQ9dy93OTSHGZxm0sjMxEVVLlHlUXc80SMkzp48CCuXr2KgoICZQ+Qv//+G7a2tmjcuDGuXbuGmjVrIiEhAY6Ojhrr5SbqomKIeG/JJeKeRaoiIiKQnp6O2NhY+Pr6YunSpbh9+zbWrVuHwMDACtnDrVu3EBUVhePHjyMrK0ujuWBlmYpC5ouJNpGaJk2a4OLFixrNyY4cOYKXX37Z6OtFxTClxYsXY9q0aahevToWL15c6tcpFAp8/PHHFbgzw7333ntISkrC5MmTDVpvLt139aWrm7E+dCXqIip+IiqXQHG3/7i4OGWDOycnJ0ycOFHZiVgXEdUQEcmlOcziNpdGZiIqqCKPKhtKxDgpHx8fHDx4EBEREcoPbLKyshASEoLevXujf//+CAgIQHh4OGJiYjTWy03URcUQ8d6SS8Q9i1T9+uuv+PLLL+Hh4YEqVarAyckJr7/+OurWrYv4+Phy3ccNFRQUhDt37sDf31/jkTAiEZhoE6mZMGECwsLClEeZzp07h71792LNmjX45JNPjL5eVAxTSk1NVT4jnJqaWurXVba/1L766iscOXJE67PmZX0CX5HPjur752poN2N96ErURVT8RFQuN2/ejPDwcAwdOhQjRowAAJw6dQozZ85ESEgIhg8fXmYMudVoEcmlOcziNpdGZiIqqHKPKos4YSBinNTq1asRGxur8j6sW7cuAgIC4Ovri2HDhsHf3x++vr5a18tN1EXFEDmxwVCWcjLLnOTl5aFBgwYAih/jycrKQosWLeDq6oqzZ89WyB7OnDmDxMREuLi4VMjvR88fJtpEat5//31Uq1YN0dHRePjwIWbOnIkGDRogMDAQ77zzjtHXi4phShs3btT668rs/PnzaN26NYqKijSOk+mT2IqqwOpDV5IroptxCWMm6mURUblct24d5s+fj/fff195beDAgWjTpg1iY2PLTLRFVKNFJJfmMIvbXBqZiaigyj2qLKJLtohxUjk5Obh//77W6zk5OQCAOnXqKGcQq5ObqIuKwedoLdNLL72Eq1evolmzZnBxccG2bdvQvHlzbNu2TZmAG5ujoyMePXpUIb8XPZ+YaBNp8c477+Cdd97Bw4cPkZ+fj3r16lXoelExSBy5HxiIqMA+y9AkV243YxGJuoiKn4jK5fXr19G5c2eN6126dNHrCLWIarSI5NJcZnGbQyMzERVUuUeV5Z4wEDVOytvbGyEhIZg7d66y50dqaioiIyOVj0akpqaiRYsWWtfLTdRFxQCMO7FBHyLuWaRqzJgxuHHjBgDgo48+wuTJk7Fz505YW1sjKiqqQvYQFBSEJUuWICAgQOtJNfX7IFF5MdEmUvPHH3+gqKgIrVu3xgsvvKC80aalpcHKygpOTk5GXS8qBpkXERVYEUmu3G7GIsYOiaj4iahcOjo6IikpSaOalpSUVOqaZ4moRotILs1hFre5NDITUUGVe1RZ7gkDUeOkwsLCEBERAX9/f2UDtapVq2Lw4MHK8XWOjo4ICwvTul5uoi4qhjlMbBBxzyJVgwYNUv7azc0NBw8exJUrV9C4ceMK+fAEgHKKyAcffKD1dTZDI7mYaBOpmTdvHsaMGaNxPO/KlSvYuHEjNm/ebNT1omKQeRFRgRWR5MrtZixi7JCIZlMiKpfTpk3D7NmzcerUKXh6egIATp8+jcOHD6skvqURUY0WkVyawyxuc2lkJqKCKveosogTBiLGSdnZ2WHhwoUIDg5GZmYmAMDBwQF2dnbKr3F1dS11vdxEXVQMc5jYYA4N8iyBruao6iqi8zhPIpCxMdEmUnPp0iW0a9dO47qbmxsuXrxo9PWiYpB5EVGBFZHkyu1mLGLskIhnikVULvv164emTZtiw4YN2LdvHwDg5ZdfRmJiotbxeupEVKNFJJfm8AyruTQyE1FBBeQdVRZxwkDkOCk7Ozu9n+tWXycnURcVwxwmNpjDLG9LoKs56rMqqlGqIWMdicqDiTaRGmtra2RnZ8PBwUHl+t27d7U+Dyt6vagYZF5EVGBFJLlyuxmLGDskouIn6tnPdu3aITo62qA9iKhGi0guAdPP4jaXRmYiKqhyjyqLOGFgTuOkDE3URcWoyIkNpTGHWd6WwBybo6alpWHr1q3IyMhAeHg4XnzxRSQlJaFJkyZ6feBKpAsTbSI1Xbt2xfLly7Fy5Urlp+4PHjzA559/jm7duhl9vagYZF5EVGBFJLlyuxmLGDskouInonKZk5ODo0eP4u+//wZQXGnr2rUratasqdf3IaIaLSK5NIdZ3ObSyExEBVXuUWURJww4Tup/KnJiQ2nMYZY3iXfo0CFMnz4dr7/+Oo4fP46CggIAxY0yd+7ciTVr1ph4h1TZKSRdc2CInkPXr1/HuHHjcO/ePbRt2xZA8WinunXrYt26dWUeH5O7XlQMMi8eHh5Yu3atRqOyEydOwNfXF8nJycjMzMS7776L06dPa41x8uRJ+Pr6YvDgwdi2bRtGjRqlkuRqe9zgWc92M27WrJnB30tmZiZiYmKUyWWbNm0wefJkvStW2qq4z9InUcnLy0NERAR27dqltXJpZ2eHc+fOQZIkvPLKKxrrd+3ahc8++0zZ0V+SJGRlZaF69eqYP3++SqOe8n4fCoVC72p0YmKiXsll1apVS00uJ06ciBYtWigTw927d8PBwQEnT55EUFAQDhw4UOb34uXlhWXLlhn8DGpOTg5mzJiB8+fPIzc3F40aNVJW92NjY1US3dL06tULsbGxaNWqlcr1ixcvwtfXF4cOHcLZs2fh6+uLY8eOGbRPfXTs2BHbt2+Ho6MjPDw8lH+e165dQ//+/fWa8WvqLtmWRMR7Sy4R9ywyP++99x5GjBgBHx8flf/Xz507Bz8/Pxw+fNjUW6RKjhVtIjWNGzfG999/j++//x6XLl0CALz77rt4++23YW1tbfT1omKQeRFRgZVbjZbbzVjU2CERP5TKqVyePXsWoaGhmDx5MsaNG6c8fnrv3j2sX78e8+bNg5OTk9YE/VkiqtEiTjqYwyxuc2lkJoLco8oiThhwnNT/iHhvycVE2jJduXIFXbt21bhub2+v9V5EVF5MtIm0sLa2xuDBg022XlQMMh9ynx0VleTK6WYsauwQIK7iZ8iznwkJCRg8eDBmzpypcr127doICAjAnTt3EB8fX2aHXBFHnUUkl+Ywi9ucGpnJJfeosogu2Rwn9T+i+hjIxVMKlqdu3brIzMzUOOF1+vRpWae+iEow0SbS4smTJ0hNTcX169fx5MkTldf0OVIqd72oGGQ+5D47KirJldvNWMTYIVPPxT19+jQiIyNLfX3QoEEIDg4uM46IarSoWcWmnsVtLo3MRJDb5E7ECQOOk/ofEe8tuUx9zyLjeP/99xEeHo6IiAgoFArcuXMHqampWLx4MSZPnmzq7ZEFYKJNpOby5cuYMmUKbt68icLCQlSrVg0PHz6EjY0N7Ozsykxy5a4XFYPMk5zuuyKSXLndjEWMHTL1XNw7d+7orFY0a9ZMr4RIRDVaRHJpDrO4zaWRmQhyjyqLOGHAcVL/I+K9JZep71lkHH5+fpAkCaNHj8bDhw8xYsQIWFtbY9y4cUJObhGxGRqRmvHjx6NBgwZYuHAhOnfujN27d+Px48cIDQ3FlClT8Nprrxl1vagYZHliYmIQFxeH7t27y56ta6iSKqs2CoVCr8ZbIppNydG6dWscOXIE9erV0/r6nTt30KNHD1y4cEFnnNmzZyM1NVVrNdrNzQ3R0dH44YcfEBsbix07duiMlZeXV2pyqS9TPsNqLo3MRJDb5C4kJAQPHjzAsmXL0KlTJ+zevRs2NjaYOnUqPDw8MH/+/DL3sH37dhw9epTjpGAe7y1T37PIuB4/foyMjAzk5+ejZcuWFdJgj54PrGgTqfn99+083iYAABSCSURBVN+xefNm2NjYoEqVKnj8+DFatmyJwMBAzJs3r8wkV+56UTHI8pjDbF0RY4fMYS7ujh07UL16da2v5eXl6RVD5FFnOScdzGEWt7k0MhNB7lFlEScMOE7qf8zhvWUO9ywSLzg4GKGhoahRowacnJyU1/Pz8/HZZ5/xkQCSjYk2kZoqVaooO3vXr18f169fR8uWLVG7dm3lvF1jrhcVgyyPiCTXHLoZm3oubpMmTbB582adX6PPsV1zOepsDrO4zaWRmQhyjyqL6JIt9yi/JTGH95ap71lkHLt27cKcOXNQo0YNleuPHj3Cd999x0SbZOPRcSI148ePx5AhQzBgwACEhobi8uXLGDt2LHbt2oXs7Gxs27bNqOtFxSDSZsGCBcpuxi+++KLG62U9bygiUTeHubiWxBxmccuda25O5B5VFjFfnf7HHN5bvGdZlocPH0KSJHh6euLAgQMqJ3aKiopw8OBBREVFcY42ycZEm0jN2bNnkZeXh65du+Lu3bsIDAxEcnIyWrRogfDw8DKPd8pdLyoGWR4RSa6XlxeWLVtmcDdjuYn6s0z5THF5DBw4EF999ZXZNqcS8QyrqGdQRTxrbmoeHh5Yu3YtOnbsqHL9xIkT8PX1RXJyMjIzM/Huu+/i9OnTGuuHDBkipEs2x0mpMof3VmW5Z5FurVu31vnfTaFQYPr06Zg6dWoF7oosEY+OEwE4cOAAevbsCWtra7Rr1055vV69eoiLizP6elExyLKJmK0rt5uxiLFD5jIXV1/Xrl1DYWGhqbdRKnOZxQ3Ie9bcXMg9qiyiSzbHSWky5Xurst2zSLf4+HhIkoSxY8fiyy+/RK1atZSvWVtbo0mTJmjYsKEJd0iWgok2EYBp06bh8OHDqFevHtq0aaP8dUWtFxWDLJuIJHfatGlYtWqVwd2MRYwdMoe5uJbEXGZxWwq5Te5EzFfnOCnzwnuWZfHy8gJQXOBo3Lixxsx7IlGYaBMBqF27Ni5fvox69epBkqRyHwWTu15UDLJsIpJcud2M5SbqgHnMxbUk5jKL21LIbXIn4oRBSkoKFixYoJEANGrUSK8Z7yQW71mWqWnTprh//z5SU1Nx9+5dqD9NO2jQIBPtjCwFE20iAIMHD8a4ceNQq1YtKBQK9O/fv9RE97fffhO+XlQMsmwikly53YxFjB0SUfGj/xHR/VxEp2xLY+hRZREnDDhOyrzwnmWZfvzxRwQGBqKgoAA1a9ZUudcpFAom2iQbE20iAIGBgejbty+uXr2KoKAgfPjhh6hZs2aFrRcVgyybiCR32rRpsvYgYuyQOczFLY/KkmiawyxuEnPCgEf5zUtlu2eRfhYvXozhw4dj5syZBn94TaQLE22i/3J3d4e7uzsyMzPh4+ODF154QefXnzp1Cm5ubrCxsRGyXlQMslyiZuvK6WYsN1EHzGMubnk8D8M5+AyqOCJOGPAov3mpbPcs0s+dO3cwcuRIJtlkNBzvRWQgT09PfPfdd3BwcDDJelEx6Pmi3s143759cHBwwOLFi/XuZix37JA5zMVVd+fOHdStW1drU5yTJ0+iXbt2Fv2BlohZ3CQej/KbB3O8Z5F8QUFB8PLywpAhQ0y9FbJQTLSJDPTsrFlTrBcVgyoXuUnuxIkT0aJFC2U345L3z8mTJxEUFIQDBw7oXC8iUS9h6rm4jx8/xrJly7BlyxYUFBQgKSlJ+b00btwYo0ePrtD9mJKIWdwkjraj/EDxYww8ym86pr5nkVhfffUVvv76a3h7e6NVq1Yaj2ONGjXKRDsjS8Gj40RElYSI2bpyuxmLHDtk6pnLX3zxBY4cOYIVK1Zg+vTpyuvt27fHmjVrnqtEm8+gmhce5TdPpr5nkViJiYmoVq0ajh49iqNHj6q8plAomGiTbEy0iYgqCRFJrtxuxpY0dmjv3r1YsmQJOnTooHIc19nZGRkZGSbcWcXjM6jmheOkiIzvp59+MvUWyMJxQjsRUSWRkpKCMWPGyEpyS7oZFxYWKq+Vp5uxJY0dunv3Ll588UWN648ePVI+h/m8CAsLg5eXF/z9/dGzZ0/07NkT/v7+6Ny5s7I7dlmdskmc1atXY86cOVrHSa1atQo1a9aEv78/UlJSTLhLIsuRl5eHvLw8U2+DLAwTbSKiSkJEkjt37lzk5uaqdDPu06cPbG1t9epmLDdRNydt27bFL7/8onF9+/bt8PDwMMGOTKekU/bx48exc+dO7Ny5E8ePH8dnn32mfA7V1dWVjZ4qCI/yE1WM+Ph49OrVCx07dkTHjh3x2muvYePGjabeFlkIHh0nMlDTpk01GmdU5HpRMajyEDFb197eHuvXrze4m7EljR2aPXs2fH19ceXKFRQVFWHTpk34448/cPLkScTHx5t6eybBZ1DNA4/yExnfypUrsWHDBvj5+cHT0xNAcaf/FStWICcnBx999JGJd0iVHbuOE1UCWVlZePLkCRo2bGjqrZAJ5eTkYMaMGTh//jxyc3PRqFEjZZIbGxurVwdcUd2MLWXsUGZmJmJiYpTfS5s2bTB58mQmm2RSHCdFZHw9e/ZEaGgo+vbtq3J93759iIiIwKFDh0y0M7IUTLSJ9JSWlobBgwfjwoULpX7Nli1bsH//ftSuXRvDhg2Dl5eX8rWsrCz4+PjoHJ/04MEDhIWF4fTp0/Dy8sKnn36KqKgoJCQkQKFQoFOnTli1ahVq1Kgh9HujykVOkjtkyBBZ3YwtZexQYWEhIiIiMH78eDRr1szU2yHSiuOkiIzHzc0Nu3fvxksvvaRyPT09He+++y7Onj1rop2RpeCZU6Jy0PW5VEJCApYuXYr33nsPubm5mDhxIvz9/TF58mQAwNOnT/HPP//ojL98+XL8/vvvGDt2LPbv34+ZM2ciIyMD33zzDSRJwqeffoq1a9ciICBA6PdFlYO2JDc5ORlnzpzRO8mV283YUsYOWVlZYefOnRg3bpypt0JUKh7lJzIeZ2dnJCYmIjg4WOX6pk2b4OzsbKJdkSVhRZvov4YOHarz9YKCAly+fLnUivaAAQPg6+uLd955B0BxAvTRRx9h+PDh8Pf3x507d9CjRw+dFfHXXnsNUVFR6Ny5M27evIlevXph9erV6N27NwDg0KFDiIiIwL59+wz8Lqkyk1uNBoBevXohNjYWrVq1Url+8eJF+Pr64tChQzh79ix8fX1x7NgxjfWJiYl6JepVq1Y1+7FDH3/8Mdzc3DBmzBhTb4WIiCrYsWPH4Ofnh+bNmysbYCYnJyMjIwNr165VOZVIZAhWtIn+6+LFi3j77bdLPUZ6+/ZtXL58udT1165dUzbTAAAPDw9s2LAB48aNw5MnTzB27Ngy93D37l00b94cANCwYUNUq1ZNpdmNk5MTbty4oed3RJZGxGxdud2MV69ejdjYWK1jh3x9fTFs2DD4+/vD19dX7rdrdE5OTli5ciWSk5Ph6uqKF154QeX1UaNGmWhnRERkbF26dMH+/fuxadMm/PnnnwCKGxGOHDmSPXFICCbaRP/VqlUrtGvXDiNHjtT6+oULF7B169ZS19euXRs3btxQSdRbtWqFDRs2KDszl6VOnTrIyspC48aNAQB9+vSBvb298vW8vDzY2Njo+y2RhRGR5MrtZmxJY4e2bNmCGjVqICUlRWMesUKhYKJNRGTBNm7cCHt7e43H8Xbv3o3c3Fz+HUCyMdEm+i9PT0+kp6eX+rqdnR06duxY6usdOnTA/v37Nb7GyckJX3/9tV7HU11cXHD27Fm4uroCAKKjo1VeT01Nxcsvv1xmHLJMIpLcsLAwREREwN/fX2s3YwBwdHREWFiY1vWWNHbop59+MvUWiIjIRL7++mtERUVpXG/WrBmCgoKYaJNsfEabSJC0tDScO3cOQ4YM0fr6pUuXsH//fkybNq3UGLm5uVAoFKV2FT98+DBsbW3RqVMnIXumymX27NlITU3VmuS6ubkhOjoaP/zwA2JjY7Fjxw6dsQztZsyxQ0REZAnc3Nzwww8/wMHBQeV6ZmYm3n77bXYdJ9mYaBMZ6JNPPoG/v7/KMd6KXC8qBlUe5pTkWsLYocLCQuzYsQPHjx/H3bt38fTpU5XX4+PjTbQzIiIyttdffx0BAQF4++23Va5///33WLZsGU89kWxMtIkM5Onpie+++07jk9CKWi8qBlU+lpDkmoMFCxZgz5498Pb2xosvvqjxelBQkAl2RUREFWHNmjWIj4/H3Llz0blzZwDFncijoqIwevRoTJ061cQ7pMqOz2gTGUjuZ1QiPuPi52TPJ87WFWPfvn348ssv8eqrr5p6K0REVMH8/Pzw5MkTzJ8/X9nbxNbWFpMmTYKfn5+Jd0eWgIk2ERE9l+zs7JQd/omI6PmiUCgwffp0+Pn54erVqwCAFi1acLoLCVPF1BsgIiIyhWnTpmHVqlUoKCgw9VaIiMhEbGxs4OzsDGdnZybZJBQr2kRE9FzatGkT0tPT0a1bNzg4OMDKSvWvxG+//dZEOyMiIqLKjok2ERE9l3r37o3evXubehtERERkgZhoEz2jsLAQERERGD9+PJo1a6bza6dMmYJatWoJXS8qBhGVTddMeyIiIiI5ON6LSA3HdhE9Px49eoSff/4ZGRkZGD58OOzt7ZGeno5atWpxPj0REREZjM3QiNT06dMHBw8eNNl6UTGISLcrV67grbfewqJFi/DFF1/g/v37AIBt27ZhyZIlJt4dERERVWY8Ok6kxsnJCStXrkRycjJcXV3xwgsvqLw+atQoo64XFYOIdFu0aBH69OmD0NBQdOjQQXnd29sbQUFBJtwZERERVXY8Ok6kxtvbu9TXFAoFDhw4YNT1omIQkW4dO3bE9u3b4ejoCA8PD+zevRsODg64du0a+vfvj7Nnz5p6i0RERFRJsaJNpOann34y6XpRMYhINysrK+Tn52tcz8jIQO3atU2wIyIiIrIUfEabSIe8vDzk5eWZbL2oGESkydvbG6tXr0ZhYaHy2s2bN7F06VK88cYbJtwZERERVXY8Ok6kRXx8POLi4nDr1i0AQMOGDTFx4kSMHj26QtaLikFEpcvJycGMGTNw/vx55ObmolGjRrh16xbc3NwQGxsLOzs7U2+RiIiIKikeHSdSs3LlSmzYsAF+fn7w9PQEAJw6dQorVqxATk4OPvroI6OuFxWDiHSzt7fH+vXrcerUKaSlpSE/Px9t27ZFt27doFAoTL09IiIiqsRY0SZS07NnT4SGhqJv374q1/ft24eIiAgcOnTIqOtFxSAi3VauXKn1ukKhgK2tLRwdHdGjRw9Uq1atgndGRERElR0r2kRqsrOz4ezsrHHdxcUF2dnZRl8vKgYR6Xbw4EFcvXoVBQUFaNq0KQDg77//hq2tLRo3boxr166hZs2aSEhIgKOjo4l3S0RERJUJm6ERqXF2dkZiYqLG9U2bNmlNfkWvFxWDiHTz8fFBx44d8csvvyApKQlJSUn45Zdf0KlTJ4wePRq//vorXFxcEB4ebuqtEhERUSXDo+NEao4dOwY/Pz80b94cHh4eAIDk5GRkZmbiq6++gpeXl1HXi4pBRLr16tULsbGxaNWqlcr1ixcvwtfXF4cOHcLZs2fh6+uLY8eOmWiXREREVBmxok2kpkuXLti/fz+8vb2RlZWFrKwseHt7IykpSa8EV+56UTGISLecnBzcv39f6/WcnBwAQJ06dfD48eOK3hoRERFVcqxoE6n5559/0LhxY61dh//55x80adLEqOtFxSAi3WbPno3U1FTMnTsXbm5uAIDU1FRERkbCzc0N0dHR+OGHHxAbG4sdO3aYeLdERERUmTDRJlLTpk0bHD58GPXq1VO5np2djW7duuHChQtGXS8qBhHplpeXh4iICOzatQtFRUUAgKpVq2Lw4MGYO3cu7OzscO7cOUiShFdeecXEuyUiIqLKhF3HidSU9tnTw4cPYWtra/T1omIQkW52dnZYuHAhgoODkZmZCQBwcHCAnZ2d8mtcXV1NtT0iIiKqxJhoE/3X4sWLARTP0P2///s/ldm5T58+xZkzZ9C6dWujrRcVg4jKx87Ojv9fERERkVBMtIn+KzU1FUBxNfn8+fOwtrZWvmZjYwNnZ2dMmDDBaOtFxSAiIiIiItPiM9pEaoKDgxEaGooaNWqYZL2oGEREREREZBpMtInU3L59G0VFRWjUqJHK9Rs3bsDKygr169c36npRMYiIiIiIyDQ4R5tIzZw5c/Drr79qXD9y5AgCAwONvl5UDCIiIiIiMg0m2kRqfv/9d3Ts2FHjeocOHZTPUBtzvagYRERERERkGky0idRIkoSCggKN6/n5+SgsLDT6elExiIiIiIjINJhoE6np0KED1q5dqzLLWpIkxMXFwdPT0+jrRcUgIiIiIiLTYDM0IjUXL17E2LFjUbt2beXx7ZMnT+LevXuIj4+Hs7OzUdeLikFERERERKbBRJtIi+zsbHzzzTe4dOkSAMDZ2RkffPABateuXSHrRcUgIiIiIqKKx0SbqBQ3b97E9evX8eTJE5XrnTp1qpD1omIQEREREVHFsjL1BojMzY0bNxAQEIAzZ85off3ChQtGXS8qBhERERERmQaboRGpWbhwIapXr44ff/wR1apVw9atWxETEwMXFxesW7fO6OtFxSAiIiIiItNgRZtIzcmTJ7F+/Xo0a9YMCoUCNWrUgJubG6pWrYolS5Zgx44dRl0vKgYREREREZkGK9pEaoqKilCjRg0AQJ06dXD79m0AQPPmzfHnn38afb2oGEREREREZBqsaBOpcXJywsWLF+Hg4AB3d3fExcXB1tYWiYmJcHBwMPp6UTGIiIiIiMg02HWcSM2hQ4fw6NEj9O3bF3/99Rf8/Pxw9epV1K5dG8uXL0fXrl2Nul5UDCIiIiIiMg0m2kR6uHfvHmrVqgWFQmGS9aJiEBERERGR8THRJiIiIiIiIhKIzdCIiIiIiIiIBGKiTURERERERCQQE20iIiIiIiIigZhoExEREREREQnERJuIiIiIiIhIoP8PrdfzRfVwn+gAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 1080x1080 with 2 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "-x1G2o4sDTGY",
"colab_type": "text"
},
"source": [
"##Breakdown of correlations\n",
"As we want to understand what makes a movie have high rating or gross \n",
"\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "KqAFmu_gBRVm",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 887
},
"outputId": "76fff666-fabe-4183-8e6b-15daecbd242d"
},
"source": [
"proj_df = df[['profit', 'imdb_score', 'director_name', 'budget']+genre_cols]\n",
"\n",
"correlations = proj_df.corr()[['profit','imdb_score']].iloc[2:]\n",
"f,ax = plt.subplots(figsize=(15,15))\n",
"sns.heatmap(correlations, annot=True, cmap=\"YlGnBu\", linewidths=.5)"
],
"execution_count": 76,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f99a8c604e0>"
]
},
"metadata": {
"tags": []
},
"execution_count": 76
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x1080 with 2 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "eNbWlF0v5aOU",
"colab_type": "text"
},
"source": [
"###Plotting score vs profit\n",
"As we can see from the graph, having much profit"
]
},
{
"cell_type": "code",
"metadata": {
"id": "MC1cju99BrCA",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 672
},
"outputId": "66382af6-8f41-41bb-a5f5-1eeb7e47d66d"
},
"source": [
"# imdb_score vs. profit\n",
"m_df = df[['imdb_score','norm_profit']].copy()\n",
"m_df.head()\n",
"m_df.plot(x='imdb_score', y='norm_profit', kind='scatter', figsize=(10,10))"
],
"execution_count": 77,
"outputs": [
{
"output_type": "stream",
"text": [
"*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
],
"name": "stderr"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f99a8c687b8>"
]
},
"metadata": {
"tags": []
},
"execution_count": 77
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ZT2TXlVHHlHY",
"colab_type": "text"
},
"source": [
"#Profit Prediction"
]
},
{
"cell_type": "code",
"metadata": {
"id": "qsfoghfYJxCf",
"colab_type": "code",
"colab": {}
},
"source": [
"from sklearn.model_selection import train_test_split, cross_val_score\n",
"from sklearn.linear_model import LinearRegression\n",
"from sklearn import tree\n",
"from sklearn import preprocessing\n",
"from sklearn.preprocessing import LabelEncoder, OneHotEncoder\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"from sklearn.metrics import mean_absolute_error, mean_squared_error, median_absolute_error, explained_variance_score, r2_score"
],
"execution_count": 78,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "Zo14yo-9a8yg",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 238
},
"outputId": "ecb01b49-f2de-4983-f862-f8f84663a92f"
},
"source": [
"p_df = df.copy()\n",
"p_df.columns"
],
"execution_count": 79,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['director_name', 'duration', 'actor_1_name', 'actor_1_facebook_likes',\n",
" 'actor_2_name', 'actor_2_facebook_likes', 'actor_3_name',\n",
" 'actor_3_facebook_likes', 'genres', 'language', 'country',\n",
" 'content_rating', 'budget', 'title_year', 'imdb_score', 'gross',\n",
" 'profit', 'norm_profit', 'genre_Action', 'genre_Adventure',\n",
" 'genre_Animation', 'genre_Biography', 'genre_Comedy', 'genre_Crime',\n",
" 'genre_Documentary', 'genre_Drama', 'genre_Family', 'genre_Fantasy',\n",
" 'genre_Film-Noir', 'genre_History', 'genre_Horror', 'genre_Music',\n",
" 'genre_Musical', 'genre_Mystery', 'genre_Romance', 'genre_Sci-Fi',\n",
" 'genre_Short', 'genre_Sport', 'genre_Thriller', 'genre_War',\n",
" 'genre_Western', 'director_id', 'actor_1_id', 'actor_2_id',\n",
" 'actor_3_id', 'language_id', 'country_id', 'content_rating_id'],\n",
" dtype='object')"
]
},
"metadata": {
"tags": []
},
"execution_count": 79
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "L-Z9So8l88we",
"colab_type": "text"
},
"source": [
"## Data cleansing\n",
"###Remove NaN values and linear dependent columns\n",
"(as we dont want to predict the label using the label)"
]
},
{
"cell_type": "code",
"metadata": {
"id": "UlqEdMSxmLNc",
"colab_type": "code",
"colab": {}
},
"source": [
"p_df = p_df.dropna(axis=0, how='any')"
],
"execution_count": 80,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "gf7GQbEDJKbF",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 221
},
"outputId": "4efac2a9-13b3-4d95-86ee-3993ada9c15d"
},
"source": [
"# Remove linear dependent columns\n",
"p_df = p_df.drop(['gross'], axis=1)\n",
"p_df = p_df.drop(['norm_profit'], axis=1)\n",
"p_df = p_df.drop(['budget'], axis=1)\n",
"p_df = p_df.drop(['genres'], axis=1)\n",
"p_df.columns"
],
"execution_count": 81,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['director_name', 'duration', 'actor_1_name', 'actor_1_facebook_likes',\n",
" 'actor_2_name', 'actor_2_facebook_likes', 'actor_3_name',\n",
" 'actor_3_facebook_likes', 'language', 'country', 'content_rating',\n",
" 'title_year', 'imdb_score', 'profit', 'genre_Action', 'genre_Adventure',\n",
" 'genre_Animation', 'genre_Biography', 'genre_Comedy', 'genre_Crime',\n",
" 'genre_Documentary', 'genre_Drama', 'genre_Family', 'genre_Fantasy',\n",
" 'genre_Film-Noir', 'genre_History', 'genre_Horror', 'genre_Music',\n",
" 'genre_Musical', 'genre_Mystery', 'genre_Romance', 'genre_Sci-Fi',\n",
" 'genre_Short', 'genre_Sport', 'genre_Thriller', 'genre_War',\n",
" 'genre_Western', 'director_id', 'actor_1_id', 'actor_2_id',\n",
" 'actor_3_id', 'language_id', 'country_id', 'content_rating_id'],\n",
" dtype='object')"
]
},
"metadata": {
"tags": []
},
"execution_count": 81
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "R0LTx7DAaon9",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 51
},
"outputId": "b35a6558-4023-4c18-8a73-be86517c3d2e"
},
"source": [
"numerical_columns = [\n",
" 'duration', 'actor_1_facebook_likes', 'actor_2_facebook_likes', \n",
" 'actor_3_facebook_likes', 'profit', 'imdb_score'\n",
" ]\n",
"cat_columns = [c for c in list(p_df.columns) if c not in numerical_columns and not 'genre_' in c and not '_id' in c]\n",
"print(numerical_columns)\n",
"print(cat_columns)"
],
"execution_count": 82,
"outputs": [
{
"output_type": "stream",
"text": [
"['duration', 'actor_1_facebook_likes', 'actor_2_facebook_likes', 'actor_3_facebook_likes', 'profit', 'imdb_score']\n",
"['director_name', 'actor_1_name', 'actor_2_name', 'actor_3_name', 'language', 'country', 'content_rating', 'title_year']\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "PaVBiLSK-y8o",
"colab_type": "text"
},
"source": [
"### Split targets from data"
]
},
{
"cell_type": "code",
"metadata": {
"id": "KLbtdpipOrxe",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "1f3e9619-bd1f-4322-d665-de9feec2bda8"
},
"source": [
"# Split targets from data\n",
"target_profit = p_df['profit']\n",
"target_rating = p_df['imdb_score']\n",
"p_df.drop(['profit', 'imdb_score'], axis=1)\n",
"p_df.shape"
],
"execution_count": 83,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(3744, 44)"
]
},
"metadata": {
"tags": []
},
"execution_count": 83
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "nqnBNis2_oUs",
"colab_type": "text"
},
"source": [
"### Source data"
]
},
{
"cell_type": "code",
"metadata": {
"id": "XY2vNEwV_m32",
"colab_type": "code",
"colab": {}
},
"source": [
"X = np.array([])"
],
"execution_count": 84,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "0PuiZFo38brk",
"colab_type": "text"
},
"source": [
"###Normalization\n",
"Using Label encoder for the category columns. <br/>\n",
"Using min-max scaler for the numerical columns. <br/>\n",
"Using min-max scaler also for the targets. <br/>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "K-3KJWQQHk2M",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "d2c927c8-6263-4525-8eec-c414beca67ca"
},
"source": [
"# Remove all the textual columns\n",
"label_encoder = LabelEncoder()\n",
"label_binarizer = preprocessing.LabelBinarizer()\n",
"\n",
"for i in range(len(cat_columns)):\n",
" col = cat_columns[i]\n",
" label_encoded_data = label_encoder.fit_transform(np.array(p_df[col]))\n",
" label_binarized_data = label_binarizer.fit_transform(label_encoded_data) \n",
" if i == 0:\n",
" X = label_binarized_data\n",
" else:\n",
" X = np.append(X, label_binarized_data, 1)\n",
"print(X.shape)"
],
"execution_count": 85,
"outputs": [
{
"output_type": "stream",
"text": [
"(3744, 8225)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "czGafjy9RCDH",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "df1fbbaa-d232-4576-b2d4-8f73dd53002c"
},
"source": [
"# Normalize the numerical columns\n",
"min_max_scaler = preprocessing.MinMaxScaler()\n",
"numerical_data = np.array(p_df[numerical_columns])\n",
"scaled_data = min_max_scaler.fit_transform(numerical_data)\n",
"X = np.append(X, scaled_data, 1)\n",
"print(X.shape)"
],
"execution_count": 86,
"outputs": [
{
"output_type": "stream",
"text": [
"(3744, 8231)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "p7AIqhXIgKyG",
"colab_type": "code",
"colab": {}
},
"source": [
"# Normalize the targets\n",
"target_profit = min_max_scaler.fit_transform(np.array(target_profit).reshape(-1,1))"
],
"execution_count": 87,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "g3qWAy-fg8GM",
"colab_type": "code",
"colab": {}
},
"source": [
"target_rating = min_max_scaler.fit_transform(np.array(target_rating).reshape(-1,1))"
],
"execution_count": 88,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "AYtkgJUr_6VN",
"colab_type": "text"
},
"source": [
"##Matrices used for examination of models\n",
"\n",
"### 1. Mean absolute error (MAE)\n",
"The error is the sum of the absolute distances between target values and predicted values, divided by the size of the test set. Absolute values are used for the error to be indifferent to the direction of the error. Division by the number of test items is used for comparison against other MAEs. Also known as L1 error.\n",
"### 2. Mean squared error (MSE)\n",
"The error is the sum of squared distances between target values and predicted values, divided by the size of the test set. Compared to MAE, it penalizes large errors more and should be used when large errors are perticulary undesirable (and also avoids using absolutes which has other mathematical benefits)\n",
"### 3. Median absolute error\n",
"In comparison to mean absolute errors, it uses the median and therefore not sensetive to outliers.\n",
"### 4. Explained variance score\n",
"Explains the variance: The variance of the target values (from the mean of them) divided by the variance of the distance between target values and predicted values (from the mean of the distance). The closer to one, the better."
]
},
{
"cell_type": "code",
"metadata": {
"id": "O5zOxM2An2__",
"colab_type": "code",
"colab": {}
},
"source": [
"def show_score(prediction, y_test):\n",
" mean_abs_error = mean_absolute_error(y_test, prediction) \n",
" mean_sqr_error = mean_squared_error(y_test, prediction)\n",
" median_abs_error = median_absolute_error(y_test, prediction)\n",
" explained_var_score = explained_variance_score(y_test, prediction)\n",
" r2__score = r2_score(y_test, prediction)\n",
" print('Regression scores:')\n",
" print('mean_abs_error:', mean_abs_error)\n",
" print('mean_sqr_error:', mean_sqr_error)\n",
" print('median_abs_error:', median_abs_error)\n",
" print('explained_var_score:', explained_var_score)\n",
" print('r2__score:', r2__score)"
],
"execution_count": 89,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "J3_7Jly9m-SS",
"colab_type": "text"
},
"source": [
"## Linear regression"
]
},
{
"cell_type": "code",
"metadata": {
"id": "8zSD1fYtnQ7I",
"colab_type": "code",
"colab": {}
},
"source": [
"X_train, X_test, y_train, y_test = train_test_split(X,target_profit, test_size=0.3)\n",
"lin_reg = LinearRegression().fit(X_train, y_train)"
],
"execution_count": 90,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "i1XEOQddnqgz",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 136
},
"outputId": "5055aa70-cf52-4f61-fa2f-6b1d04a5d048"
},
"source": [
"print('score', lin_reg.score(X_test, y_test))\n",
"predicted_profit = lin_reg.predict(X_test)\n",
"show_score(predicted_profit, y_test)"
],
"execution_count": 91,
"outputs": [
{
"output_type": "stream",
"text": [
"score -0.41644072454157954\n",
"Regression scores:\n",
"mean_abs_error: 0.005037912864012351\n",
"mean_sqr_error: 6.621724165755914e-05\n",
"median_abs_error: 0.003696328331295573\n",
"explained_var_score: -0.4153702120519469\n",
"r2__score: -0.41644072454157954\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "cfbBYyIxsKDa",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 286
},
"outputId": "64dea982-6fbc-48e1-eaec-ed4df47aa268"
},
"source": [
"# Plot\n",
"predicted_profit = lin_reg.predict(X_test)\n",
"predicted_profit = min_max_scaler.inverse_transform(predicted_profit.reshape(-1,1)) / 1e6\n",
"y_test = min_max_scaler.inverse_transform(y_test.reshape(-1,1)) / 1e6\n",
"plt.plot(predicted_profit[:200], c='b', label='Prediction')\n",
"plt.plot(y_test[:200], c='g', label='Actual')\n",
"plt.legend(['Actual', 'Prediction'])\n",
"plt.ylabel('Prediction (In Millions)', fontsize = 14)\n",
"plt.grid()\n",
"plt.show()"
],
"execution_count": 92,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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ZP348/fv378Ir2IFxHKEFTUJxjOrqatatW8fgwYN7/QRtXUkzV5WYdkTQh1lfuJW1hZt7rLzrMicyJbPzS70qisK+ffv497//ze23305dXR0Wi4XnnnsuvHDT559/jkaj4bnnngsf99JLL3HllVeSl5fHyJEjWbRoEQ899BBTp04FCM+AcSa2b99Obm4uK1euZODAgQAMGtS05G5ERARarbZN19Ty5cvDlo7JZGLo0KE88cQTzJ49m9/97ndEREQAcNlll/HAAw8AcP/99/O3v/2N7du3h9dd7yraLRwPPPAA11xzDffccw9Op5Pbb78dt9uNy+XihRde4Ic//GGXVqy30jw4LiwOgaC3880333DFFVcQCASQZZnp06czc+ZMnnvuObKyssKiAao76Pjx41xxxRXNzhEMBikqKiIzM5Pq6upmLnmj0Rh2EbXGkSNHGDBgQFg0OsOxY8cYMWIEJpMpvC0nJwe/309RURHDhg0DaDFNU3JyMlartdPlnol2C0deXh6PP/44AKtWrcJisbB69WqWL1/OggUL+oxwiBiHQKAyJXP8OVkAPcXEiROZM2cOer2e5OTkZtlUoZ56CJfLxciRI3n55ZdbnCchIaHXj906VQRDdEed250/63K5iI6OBtQ0se9+97vo9XrGjx/fbM3di52gsDgEgguKiIgI0tPTGTBgwFlTcEeMGMGJEydISEggPT292T+LxUJUVBRJSUns27cvfIzX6+XQoUNnPGdWVhZlZWVnbCf1en2Ltc1P55JLLuHgwYN4PJ7wttzcXPR6fTO3V0/RbuFISUlh165duFwuNm7cyMSJEwFoaGhoZj5d7IjguEBw8XLTTTcRFRXFI488ws6dOykuLmbLli08++yz2Gw2AO666y7mz5/P6tWrOXbsGHPmzMHn853xnOPGjSMnJ4eZM2eyZcsWiouLWbNmDdu2bQMgNTWVoqIiDh8+TG1tbavnuummm9DpdDz55JPk5+ezceNGXn75ZX7605+2sJp6gnYLx3333cfs2bOZMmUK/fr148orrwRgx44dLfxqFzPNx3GI4LhAcDERERHB+++/T1JSEg8//DA33ngjzz77LBqNBqPRCMB//dd/MW3aNGbPns3PfvYzUlJSmDRpUpvnfeONNxg2bBizZs1i+vTpvPHGG+HvbrjhBiZNmsSMGTOYMGECK1asaLVeCxYswGq1ctttt/H73/+eqVOnhsMHPU2H1hzPy8ujvLyciRMnhpchXLduHVFRUb02syq05viZ1s49G6cv6/nN9pO8/uEeAN547FoyB/TOkZ3niwthGdTexoVwzQ4dOtRmALgnEUvHdpy2rllr9/Zs7WaHxj1nZ2eTnZ3dbNu1117bkVNc8IgYh0Ag6Ot0SDj27t3Lli1bsFqtLSL1zzzzTJdWrLfSfByHEA6BQND3aLdwLFiwgFdeeYX09HSSk5ObfSdJUpdXrLcixnEIBIK+TruFY+HChTzzzDPhuVf6KsLiEAgEfZ12Z1U5HI4+Mx9VWzRPxxVZVQKBoO/RbuGYNm0aGzZs6M66XBCcKhbCVSXoS/T2UdOCjtPZe9puV1VKSgrz5s1j165dLeZ3AXWcR19AFq4qQR9Er9fjdrvPy2AzQffhdrtbnabkbLRbOD7++GMiIiLYvXs3u3fvbvadJEl9RjhEjEPQF0lOTqa0tJTU1FTMZnOfSoi5GFEUBbfbTWlpaXidkY7QbuFYs2ZNh09+MXL6CoACQV8gNE9dWVlZeC2L80VXrtTXV2jtmun1evr16xe+tx2hUwufOp1OJEnqk2brqdOMiBiHoC8RHR3dqUamq8nNzWXUqFHnuxoXFF19zdodHAdYvHgx1157LWPHjiUnJ4frrruOxYsXd1llLgTEQk4CgaCv026LY/78+bz99tv84he/CM+rs3PnTubOnYvT6QyvOnWxIwYACgSCvk67hWPJkiU8//zzTJ8+PbxtwoQJpKen85e//KXPCIcIjgsEgr5Ou11VVquVyy+/vMX2kSNHUlNT06WV6s0I4RAIBH2ddgtHRkYGy5cvb7F9xYoVZGZmdmmlejPBoEwoE1EIh0Ag6Iu021U1c+ZMZs2axc6dOxkzZgwAu3btYseOHbz++uvdVsHeRlBW0Ou0+PxBZLGQk0Ag6IO02+L43ve+x0cffURiYiLr1q1j3bp1JCYm8vHHHzN16tTurGOvQpYVDDr1sgmLQyAQ9EU6vJDTq6++2unCHA4Hr732GqtXr6a+vp5Ro0bx3//931x66aWt7v/RRx/x2WefkZ+fjyRJZGdn87vf/a7VWEtPEZQVDHoNuEEWc/cIBII+SJvCUV9fT2xsbPjvtgjt1xZPP/00x48fZ+7cuSQkJLBw4ULuu+8+vvrqKywWS4v9t23bxrRp0xgzZgwGg4H33nuP+++/ny+++KLFmiA9RVCW0eu06t9i5LhAIOiDtCkcEyZMYOPGjSQkJDB+/PhW56dRFAVJkjh06FCbBXk8HlatWsXbb7/N2LFjAZgzZw4rV65kxYoV/OQnP2lxzNy5c5t9/tOf/sTKlSvZtm0bN91001l/XHcQDCrohatKIBD0YdoUjn/+85/ExMQA6kJO50IgECAYDGI0GsPbNBoNer2e3bt3tyocp+N2uwkEAuE6nQ9kRcEQsjiEcAgEgj5Im8Ixbty4Vv/uDBaLhVGjRvHmm28yd+5cYmNjWbRoERUVFe0eBzJ37lxSUlIYP358h8vPy8ujsrKyw8eBOs9LiLq6erw+NZuqpLSU3FxHp855MXPq9RK0D3HNOoa4Xh2nI9esurq6ze/PGuNoL+2Jcbzyyis88cQTTJo0Ca1Wy/jx45k8eXK7FhN59913+fLLL1m0aFGnZsbMzs4mLS2tw8fl5uaGp1gB+GzHZvT+IBV1dfTr15+cnBEdPufFzOnXS3B2xDXrGOJ6dZyOXrOSkpI2v29TOM4U1ziV9sY4ANLT01myZAkOhwOv10tCQgJ33nknI0a03fguWLCAt99+m7///e8MHTr0rOV0J0FZQaOR0GokMVeVQCDok7QpHOca1zgTFosFi8VCcXExeXl5PPLII2fc991332X+/PksWLDgvKbhhgjKMjqtBq1WEjEOgUDQJ2l3jKMr2LBhAxqNhvT0dAoKCnjhhReYMmUKkydPBmD27Nn069ePxx57DIB33nmHN954g7lz55Kamhr2u0VERBAZGdmldWsvQVnBqJfQaDRCOAQCQZ+kR2McNpuN1157jaqqKuLj47n55puZOXNm+Pvy8nI0mqbB7EuWLMHv9/Ob3/ym2XkeeeSRZsf1JEFZQavVoJGkZos6CQQCQV+hR2Mc06dPbzYt++ksWrSo2efeuFytHFTQaiThqhIIBH2W8xLjuJAJyrIIjgsEgj5Nj8Y4LgaCcqPFoREWh0Ag6Jv06FxVFwOqcGjQajTC4hAIBH2SHpur6mJBDY5LaITFIRAI+ig9NlfVxYIclNFqQsIhsqoEAkHfo8fmqrpYOHXkuJhWXSAQ9EXavQKgQCUcHNdKYiEngUDQJznrCoCh9cXPxq5du865MhcCoQGAIqtKIBD0Vc4qHC6XiwEDBnDrrbd2anbZiw1ZlhvTcTXIwlUlEAj6IGcVjnfeeYelS5fy7rvvMmbMGG6//XZuuOGGTk1tfjEQDCpoJJFV1Rp7j1bz4bdWxoxRzjrjgEAguHA5a4xj8uTJvPHGG6xfv55rr72Wd955h0mTJvHHP/6RgwcP9kQdexWyoqbjakVWVQt2H63iULEbry94vqsi6GUcLaqjus59vqsh6CLaHRyPi4vj3nvvZfny5bz33nscO3aM22+/nYaGhu6sX68jlFWlEVOOtKDUVYQ+cz9ub+B8V0XQy3jxH9v58Jsj57sagi7irK6qU3G5XHzxxRcsW7aMI0eOcMstt2A2m7urbr0OWVZQFBpHjgtX1elU+E+gSyrF5nYRF20639UR9CJsLj92l+98V0PQRbRLOHbu3MnSpUtZuXIlQ4YM4Y477uDGG2/EYrF0d/16FSGhCAXHhXA0xxvwgg5sbhcQf76rI+glBIIyPn8Qt+fCsESL6ktJiUpGr9Wf76r0Ws4qHDfccAN2u51bbrmFpUuXcskll/REvXoloZhGeByHEI5meGUvAA0e53muiaA34WoUjAvBhenyu3li1Yv8YsyPmXrJNee7Or2WswrHyZMnMRqNLFmyhA8//PCM+/WFcRwhodBqJXUhJxEcb4a/UTgcXhEEFTTh8viBC0Q4fG6CcpA6d9+K3XaUswrHiy++2BP1uCAIuabElCOtE0BtIIRwCE4lJBiuC0A4PAG18+P2e85zTXo3ZxWOW2+9tSfqcUEQEgqtRoNGTDnSjKCsIONDAziFcAhOIeyqugBiHCHhcPnFM9wWYq6qDhAIBkHnFQs5tYLL4wet2jA4feKlEzRxqqtK6eWdrSbh6D6L4/DJWv6z7WS3nb8nEMLRAfZU5mEavQ6v4lKzqoSrKozD5UfSqgP/uvOlO99s2ldGYZnwf3cEZ6OlEZQV/IHeFRcMykH8QX/4szeopgy7A93X+flq8wn+tvxAt52/JxDC0QEqHVVIGgW3bO+RAYBuvwffKQ91b8bh9oUtjovVP6woCm98uJtP1xWc76pcULg9Tc/wuQTI1XFUXfvOLdyzjD+tfyP82RNQn11XN1rNNqcPp9t/QXsshHB0AJvPAYBP8fTIlCMvrJ/HP3d/3K1ldBUNTk/Y4giZ+xcKbm+AWtvZxc7p9uPyBGhwnttAtp2HKnG6298h+ObYt+wq239OZXYFJVX2TjXcrlNiG50VDo83wM+f/YpN+8o6dfyZKLGVUWKrCH/2BtR76wp0X+fH3vj8uE4R1ALrCZw+V7eV2dUI4egAdm9IONzdHuNQFIUT9cWU2Su7rYyupM7RNHbDG7ywhONfKw/z6P+uP6sFWVmrvtg2R+d/X029mz++t5VvdhS1a39ZkXl/76d8nb+u02V2BSVVdh56eQ25h6s6fOyp2VSdFY7qejd2l5+C4vpOHX8mbB4HDp8TubET2BPBcVvjCPrQSHpf0M+cNa+ysmB9t5XZ1XRoypG9e/eyZcsWrFZri57HM88806UV643YGy0Or+zB1M2uKpvXji/ox+69MAbT1bsc4b9DAwG7gmBQ5o2P9nDzNYO5JC22y857KlV1LqwNHk5W2MgcENPGfmpjYjsHi6Oowg6AtaF9PdpKRw0uv/u8jysoq1afwxPlNsYO79ehY12nWFeuTmZWWRvUa19d54aUrpt52eZzoCgKTr+LKKOlR9JxQxaHw6VeF6urjqAcpNbdtaLYnbRbOBYsWMArr7xCeno6ycnJzb7rK1NoO8LC4SKymy2OamctoArI+aDC6qR/QmS79693NZnZvi4Ujqo6N2t2FhMdaeg24SgNHEI/uIj9BdlnEQ71N56Lq6qo0gZAvb19DdPxOjX7ps7Ts8Jh89iRJIkoozqtUE1jw11e0/GOTFdYHCGhra53AxGdOsfpKIqCrdGLYPc6iDJawq4qT8CLLMtoNF3rlAnKCs5GF1XI4rC61HfdcYF0EqEDwrFw4UKeeeYZfv7zn3dnfXo1Dr96Y72yB6225VxVX2wqxOMNcPv1Qzpdxtx/5TI8I57YNPVhsnvVHlFPinN+cR2P/u8GXnp4EpcNTmjXMTZPk3AE5K6bzC7UYOV3sYviVBo0JWjjy9lbUMXNk888pU5Vo6vK6wvi8QUwGTpksAONFockU2dvn7geq1VdWjavg0AwgE7b8TI7w+tb/4ZZZ+L3kx4EVBcbQFmNo63DWsXl8Yddu50dyxGKQXVWODbuLUWv1XBVdkp4m9vvISircTmb18kAmsfn3AEPkYamsurcDUQZIs/pHjhcPkLOGnujxVHjqlM/+y4c4Wi3nDocDqZMmdKddel17DxUSYNLfdBVc1Z9adxBFxpJapHl8c2OIj5bf6zTmR8VVifrcktY/PVhyu3VAAQVGae/Z4NmIbfEvoKadh/j8DbWUdbhV7pOOKyNDdbx0vpus/D8khtJo5BXXNZmGaEYB3TeXVVYXYnpijVUBPLbt39dUyyk3mPrVJmdocpppdppDX+uaXCjTSqmzNrxOrg8AeJj1NmSOwzexE8AACAASURBVDt6PGRx1Da4O/UcLP76MMvWNs+GO9WaD7uhTxGOU+MciqIw+z9/Zv7O989QPzcv/XMHjrPMAHzqDMGOsMWhCseFZHG0WzimTZvGhg0burMuvY55H+1m4wH14fIEvASUQOPfbrRa1QI4Nc5RU+em3uHt9II12w+q2R02p4+9J5oGCIXM6dY4fKKWLfvLW2w/UVfMyvyWwbb9BTX8/o0NeNp4gesbg7+HT9a2u+6OxvRFbdBEkI6nECuKwra8cgLB5plqoQbD7Q1SVt3+3m6tu57/3bKgXb5qWVL38cg2thXks+HEtlb3q6pzodWo970zwqEoCqXSXiRdADtnF2VZkTleW0RShDrTcE/6wO1eR7MecImjGEPmARp0hXh8HWv8XR4/CY3T7HfeVaU+X7ICdnfHFgqTZYXKWleLe3bqexVKfGlmcZzy7Dj9Lho8Nr49sZ0TdcUtyjh4vJZN+8rC7/CZOLUO9lNiHNA1FoeidH3Kcmu0WzhSUlKYN28ejz32GO+88w5///vfm/27GImPMVNrVx/0hlN6J+5gUwMSmnbE6w+GG9yjxXWdKm/7gQrSki0MTo3hWHWTGNjbEI5P1xfw9xUtBxP9p2ADf9v9YThbJMThk7UcOVnH3vzqM56zvtGNcuRkXbsTAEJ577qguVPCkV9cz5/+vp3cQ82zyEKuqtA+7WVfxSE2F+0k31rY5n7+gIyiU3+vZHSz/PAq/rp9YYvrBqqrKj0lGgCb48zCIctKCwEEOFFdjRKnWhB+yUEwKLP/WA0ub+tp3RWOatwBDzkDRgI9Z3EE5CAuv7tZQ1bnUTsRmgg7ldaOWcAuT4CEGHXdns4KR63Ng66xs2ZznVk4cg9XUlzZPC5Ya/PgD8htCkfob0+waZ9TLY5Q466gsHjfZy3KtbvV4/YcPfN7BWpgXNf/OIZh28IWR01jjKMrhOO9z/N4+v82n/N5zka7hePjjz8mIiKC3bt3s2TJEhYtWhT+9/77rZtvFzopCZHUOtQH3eZRH0bFZ2gmHKHR4yGXCsDRoo73DJ1uP3nHrFx1WX+mXZ2JFwdxRjUY3JbF4fEFWx0TYHXXqcE/X/NjQ/vubCOtMiQcTref0nb28kMDp/SKGUXquHCUVKnl1J/WIFsbPKQlWzAatBSUtP+6hl70qlPcLa1R53Ah6dR7HBHtp9JViazIzToKAA63H6cnwJCB6j1pcJ45RvH6h7v53eurmbvx3XA9AP59cA1oZAxKFBg8lFudPDN/M9uPtn6Nj1lVqzMn9XKg+y2Oo0V1lFY7cHib3Da+oB9FUbAH1eC8ZHZQ1sEAucsbwBKhx6DXnlNwfHCqmrjQ4DyzcMxdvKvFAM1yq1pfh9vXzM3VmsXhDXjRadQYxqkzIITu45Wpo9hbcZBKR3OBCLmg9uZXt9njt7t8aGKsaKLqaGhMKAmd2xvwNhvF3hm2HajgYKG120fotzvKs2bNmu6sR6+kf0IEG/cGCQTlsD9U9lhwm+zhbIvQgxhyT+m0Go4WddziWLn1BEFZYdxl/YmONCAddxOrTaOO+rBotYbXF8Tl8bcIoNc0ZmXVuxuINUWHt4fSIXcerEBRRrYadK+ze4g063G6/Rw+UcvAflFnrb+nceyGQTHh0AQ6HNAPBV1P9xHX1LtJjosgOtLQoRz+0MtYfRbhqGhouleRMX5sSh1IUOeuJ87clGFV3ZhRdWlaLCs52aarqrCsgSJ3IZWluxnZfxjfvVRd16Gw/iSKK5pBSYM46isg75gVWVbO6Ho5UH2USL2Zy5Kz0Eiabk/Jnbs4l8RYMw/+NCO8zeF1YiACWedEA2gibB1yGYL6zEWa9EQYdZ0SjqCsUGf3MnHkAI4W1dNwBovD4wtgd/lapPxWNgqHoqjPV4zFCDTFOCINEeG0d0/AS5w5hmqntZnFEbIKvnvJNewo3cuRmuP0sySFvw+l1tbavJRUOZq9M3U2T3hFTJvTj2RyIUlQ61GfvRp3HXqtHn/Qj93nJN7cuexBa4M7HIcrqbK3mSF4rogBgG0wIDESRVFFoSFkcbgt+GU/cqM7JiwcjRbH6KFJHCvpWCD349VH+fuKg4wZlkxWejwRFhlJIyN5zm5x+PxBAkEFX0DGH5DDo1Fr3OpDebp7I5QKWNPg4UR5666PeoeXYelxWMx6Dp9snwj6ZS9a9OglA0hKu6ZK8QeCLFuTj88fDKd5nr68qLXBTUKMiSED4zhWUo8/IFNW42DFxuNtntva2DuvcrYdS6iyNf0+n7EKRaM2OrWnNdKhF3JwagwajURDG4MArQ0eTDHq87Kt4Fh4e63XitYfRWpsEpLBw94C1epzeM4gHJVHGJ48FJ1GS6wpuluFQ5YVqupcHCyspcbZVI7d56CmwYNkUJ9vSe+nyNr+pInQ6n8RJh1mo67ZaOn20uDwIssKackWIs16GpzqPTpe2sA/vzgY7uHXNsbDTo/BlFtbT2qweR3otXqSIuLDlrk34CPepDa4p8Y4alx1aCUN2f2GYdabOFrT/PmzOX0YdGpzeqq7qqzawb3PrWRv47Z6pyt8LRt8dbj8btx+D+kxqcC5BcgPFjbFJM/0bncVZxWO02MZZ/rXHhwOB8899xxTpkxh1KhR3H333RQUtD3vz1dffcX3v/99Lr/8cm666aYeDdCHxjGU1zjDrgvZrW4LoDYcoWlHquvdSBJMuDwFj+ympNKOw+XjoZdXc+D4mXu9/oDM4q8Pc9Vl/Zlz/1VoNRJWt/oANNQYMGoNHCmtINiKzxzU2Aqog6z+tfIwj8/7FpfPHX7oTxcOlydAfGPvZ+cp8YRgUCb3cCWKolBv9xIXZSIrPa5dAXJ/QCag+NFLRgySutymu9F1dXqM5MBxKw+9vJp6u5cDx63844uDbM0rDwuH4xS3WyCopq0mxpoZnhGPLyBzvLSeT9YW8Pan+3F5/PgDQU5WtHxJmiyOtutf7VQFJt4Yj1tpsuxObaRXbj3JvI/2YNBpGJAYSZQFDjl2sXFPKQcLm99bfyCIzekjcYD6+/cVnaCqzoUv4MOj2InWxZMSk4gkwf6TJQA43S3vbY2zlkpnDdnJQwGIM8dQ52ngjQ93897neW3+phN1JWwq2tHmPqdTZ/cQCKqxmcMlTc+F3eukpt6NZHQTpVd70SfrS9p93lDv39woHJ2xOEKB8fhoE0mx5rDF8Z9tJ1m6Jh+vL9i4X0g4mgtxhbWpMW4mHB47Bkz4PbpmwfG4xh7/6TGOeHMsOo2WoQmZHKlp6hCAanGkJUfRPyGiWfzweFkDskLYzVrtqiFkiDvlhvBzmhGbBnQsznHcWsTPP57FMasaNzt0ohajQYtOq+FkNwvHWV1VixYtOutJJEnivvvuO+t+Tz/9NMePH2fu3LkkJCSwcOFC7rvvPr766qtW1y/ftWsXjz32GI8++ijXXXcdy5cv59e//jWff/55jyxhm5LYKBxWJ7YIBwaNEa9fbXT9NG8Yq+tcxFqMxCX7MF2xhrVHkrksOYuSKgcbdpeccTxEZa0TxVLNyBGD0WlVHQ+5VyoqFGISjWw/WswzrncZmdmfn468pdnxoZfG6fFTVuOguNJOhb2pMTu9l+ry+ElNspAcZ2b1jmLuuH4IkiSxeV85//P+Tl75zTU0OLzERRvplxBB7teHcbj9WMxnXn+53u4FbQCT1ohBo+7n8LqI0lv4zWvrMBt1/ObO0QxIsvDW0r2UVDlUX3qjSBw5WRf2m59qcdTaPCgKJMSYGJ6pZhYdLKwNv5j1di97C2qYv2wvb82+nrTkJvdAaFDV2SyOOpf6gmXGplNb2SQydR71RVcUhfmf7CNjQDQP3no5lggD+qQKjim7eWOFxOi0IYzIbLq3auOlUB9sjCEZHbz9yX7uvj0VJEiOSGJgnOrisAcagPhWLY68qiMAZCdnARBniqHKaeXo4cpwoPl0/AGZv684wD7/SmrkQkb2Gx4ewHc2Ts0EPFraJBzl9XUE6vVIRg+j+k1gY8lmSu1lZ30mQoQsjAijHrNJFY4T5TYijDqS45uPx/jHigPYXX5m3jm62faQICTEmEiMNVNSodY1NEuxxxfEZNSFEym8p1kcFVYn0ZEGbE4fNqeXj1cfZePeMuoSinEFJdwBP8mp6nPnDXiJNlnQSJoWwpEQEUedzYPOk0BRw2FcfjcRevVe2F0+LBF6BvaL4sDxpmcu1CEKPd9WTw2onjI8UkPYBZYR1ygcbXgXTueT/WvxyV4Wb/qW/775Lg4WWskaFIfd5Tv/FseaNWvO+m/16tVnLcjj8bBq1Spmz57N2LFjyczMZM6cOQSDQVasWNHqMQsXLmTy5Mn88pe/5JJLLmHWrFmMGDGCxYsXd/yXdoL4aBM6rUR5jRObx45JGwEB9WXxK+rDfKqrKinOTJErH0mCfVUHKShRH+y9+WduvI6WV2DI2slh9/bwtpCbJOA24HRokPReCpz7WX1sU4vAmy9kcXgCNLjtYHRwwtr04rdwVXk9yBHV/GBiJqXVjnAjfKxUbSj3F9QQCCrEWowMS49T63iau6reY+NEXVOvs87uQdIGMOtNYeFocLnYvL+cogo7hWU2fjN3HU+8+W0448Xp9ocD9TtOmfQv5CsGsNaHGgwz8dEmUhIiWberhIqGejQx1dTZvRyuKkCXtZ2lW3LDx3n8Hpx+N2a9iXqPDV/gzPGI0PUZmpgJgOIzY8AcvgdOt59AUGbKFWkMS1fFSxuhNgI+bX1YuMN1bvAgmZz4FR9x5hgkk5s9+ZUU1qqT8w2MSWFAjCockkH9fU5PS4sjr+oI0UYLaTEp7DxUiSZowuqqw9FvCxXRa/G0kma8N7+a5d8ep9JVgYzM0txvm32vKMoZe/wh4YiPNlJkbep4vPXpDj7ZtB9JUhjeL4MYQwxBo42vt5wA1B78nLc3n9GqDpUXaW6yOJ5bsJX3/t3SatqTX83WvJap5aHBfwkxZpLizNQ7AsiyEm4cQ66pM1kc5TUuhg6KC9d3494yqutc+CU3EbpIfG5tU1ZVwItJZ8KsN53mqqol3hzHSwt3sHmrBwWFAqt6Db44sppKw27METKDU2OoafCEXZmhMVGhJBNbQH2XIqVYAloHNc6QxTEQoN1TDAXlIHlWdeLL/eX57DteTrFxAxnpetJTorvd4uixGEcgECAYDGI0GpsK12jQ6/Xs3r271WP27NnD1Vdf3WzbpEmT2LNnT7fWNYQkScRZtFRYVVeVUTKj+A0A+FBfNH8gQEAOUl3nJik2gn2VhwCo9BZzrNE8La12hM3t09lWmoskQaWnadbPek+DmtkR1CP79BhjbUjaIDafnSpnDWXVDooa3TMhV5XT7afMuB3j8G0UNQqHSWdsMVVFXcQBjptXkpEpER1pYMVGNV21sEw9X0hIYqOMDB0Uh0ZqPp4jKAd5cf2b/HnDvKZz2jygDRBpMGPSqtfH5nHy2foCUhIjefcPU5l2dSbFlXYuSVP9x45ThCPUK9NpNc2Fw+YGTZB/FPyVP6x6mdjMMo6XNqDrX4gxK5eS2moKXPvRRtey2fUxuaVqWnIovnFpnCoG1a4zu6tsXjtKUEtmgtrji1DiIGAKW2qh6UViLIbwMYpBbQQ0Efbw9Q9Ra/OgsajHThp0JQoyfo2TXYXHURS4NDmVxMZxGZLBjcmgxR9s2aAfrMpnRPJQFBlefX8nBYUenH4X2rgqApGV/HnDm+HpMUJsP1iByQgak+rT//rQlmaz/i5eeZj7n/9Pq+IRmk7lupyB1LtsKEEtAPHxWqocqij0j0picMJATHEN/HvjUfyBIG98uJs9R6vPmIYauscRRjU4XlbtpLrO3WqAvabejc3paxE/sjZ40GgkYixGLkmNxeNXyD1c2bSyoDckHOo7dqpwON1+7C5fWDgaHD4qrE6mXJFGfLyGQYkJKAEDLr8bX9CPXw7QYAtg1pnCFoesyFjd9VhrVItXdsQiIXG4pgCX383ifZ/hjj3EAdPHaKLVa3Wi8X0KJX2UN/7vVOrRyWbiDclgdFHaUIkkScToEgE1pvT8utd5ft3r4RmRT5TbePyNDew+0pQJub/yCK6AE8VnhIh6/vujZWgTyvHHFJLRP5qaBs9ZByOeC226qj7//HNuvvnmdmXHlJaWUl5eztixY1v93mKxMGrUKN58803mzp1LbGwsixYtoqKigpqa1nvkNTU1JCQ0d/EkJCRQXd12rnRr5OXlUVnZ8Zlm46N0HC+pwRhbibXGQGJkBA6grLoUSOSVb/8Xs15HZW02qQl+jlQfQ6Po8Onr2H+0lOQYI1UNAT77zw5GD24+95OiKBys2w06dXrnrTu2odfoOFZZSITGhE+vQasYCShNjenXO1azfVsMCvCL7ybjsxShi3Oz70AsHkM5ks7PjqKdSEgk6GIpqS4jNzc3XJ4vshgJ+Dz3CzIGx7BHWcOX67wcPak2diEzu6r8JIfkShLjFL4qX0LClkkkGuLYWreXwnp1ANTm7Vswag3syXcgaQPIXj8mrR5kWLcjj6NFEdw4NpbC/AOMGQgDEo3IAZljJXDo6LEWPe1+sTqs9Y5wffcctiOZ7VS5qrB7TLg1J0AzFW2k+hJuyt9KbbAE2RmPZLbzr81fwmAPhS7VGtq1K4A+Db7esomNW03cOSmB5Njm7hWrwwqKkZoTak/XokRR4fBzpLSEbdt3Ular5t0fLoFo1BfXgypMktlBbZUtXF+AvYftaCIb0Et6ohxqJ0kyOckrrkTRmHHVVpC3txYpaEAyekhN0HGsPMjGrbnEW9TX0RFwUeOqZWTEUP69aitOT4BgjYw0CGRHDIHKdA6zj4UbPmRMzIjwvd20p4KUAR4qUIjRxlAfWcPf/72Oa4cnUWPz8/HqSmQZPvl6K8nJPnbXH+a6pCvRSBoOHK3DpJdIi3JgiQqiSGZkycOQNBmfy4cPqCosZ6g0kN3aPDyx+/jZM0E8ftUCPnK8mNzclr3lI6Vq43vyRAH1DiteQxV4EyirsfG3Nf9iU0kh0cFkfnzZFTQ0pmJ/syGXjH5NHcyCwjoiDBJ7du9C12hd/HN5U2dzz74D1JYbKTihPrtOlzd8T8pr1XMGnFXodRL7Dp/E5Qngd9dSH2ggXp+MElA7Beu3qxbaN1tLiR0oUy5VkJubiyPgIigHOZLvIs6ipc4BcVIia45uwlvjIiAH8J/IxjSwiI+PvY8magzrtx8gYI+iqFx9VmptXjZv3YFXasAcjETr1SEZ3KzJ34riiOeXz68l8kotuwv3c8RRiBYt+ysP87MBN3Oi0MThkw08//XfGLAhjskp2RzSbEWHHld5Job0w1gGFeED9lXuZopuAABfrttG/wSI1KkuwVOf07Nxtja2TYtj2bJlfP/732f+/PkcOXKkhZukvr6e1atX89vf/pY77rgDu73tCfleeeUVfD4fkyZNYtSoUWzcuJHJkyf3yDxM2dnZ5OTkdPhfvEVHncdNrddO0Gvk6XuuBSAqLgK0fsr9FRxzFRM02IhLBxmFcckTkSTw6GuZPjlL9a8GLOTk5DBmzBhGjR5FTk4OCZf0w6uzYfKmoKAQl5lITk4Omggd/aIT+dVtoxk7dBAAZo0FJaDDbvJRpS3EHVNM9siR6NKOoEvLxxvrA50qMNVUEB8Ry6CkNBr8XpLThpKTk0NsZhKS0YUWHcd8xTgSj6KJcLCjoRiHR0arkQgEQTK42MJ60rIGMWCIF6+5kl3+IyRfmsLmut3h9N7+l6aSk5NDVFw/JG2Agf1TwhZHjRs0Etx729Xk5OSQMXwwH1V+yW5lHwDxiSlExyaGB3VJEozMGoAvCDk5OVyWPYp6rxlDtCoSPx2txnY0EXaM0WrvuEpfRFDvIs14KZKswytr1euaqrqCZJvas6/wBqmxBcgr0zFmzBiSUocwZswYcnJyUHRBdLKJ66+6lqmXXMNDU28hOSoOZ8BFuTsOJU6PftBRioz55OTkkD3qcvxatXyN2Y5Wb2z2vBgtcWjjqsjuP5Trxk4GQGt24VBsKO5IvnPNWHJycjBJUUgGN5PGqLG6gelDwucwp6qxmutHXYMTtafstUWhw4jvxAiC1hQGRqdxxHcy/DsSBgzB5gqSNUxtJH5x1Z1IksJ+/QaO6Iv58uQRjCYwGbTU+6PYWV/OTtt+lMQIcnJykPRR9E+MYuqUqxg6OJpBSUnEmqOJSrDw/Sn9kZCYMm4yt19zM9OGfgddvyKGj5IbZy2OQdJbml2HkaNHskM+RCBO7f3XxVVzLP5rjMN3IJmcBC1VfF39LXZDKWXGAwwanBV+V82xKc3OZYmKJSbKTE5ODt+ZfBUJ0VpKDXlIEWpnJyPzUnJycpA1JgzDtyL3Pxw+9pgzgGFILleNyyIu2kxNY8xl1OWD8SsBhmcMDruf+2Wq81gpQS1mfSSGSPXepl6qupGCXjOjs9R9suPGUetvYG3NLmKM0QSqUrkh+WckWuIxDttOgTaPocMvw+GRw1Z2/4FDUQwOEs39GJJyCZJGwSM5MbsGExWhR4eJYq868nxi9C0oAR37vYUEddFED6xC1/8kVZF5vL/lBIcdhYyIG4VsV59xn9ZOYkQ8tf4GRo4diE4r8YV1DV82bCInJwegQ+1ednZ2m+1pm8KxcOFCnnrqKXbs2MEPf/hDrrjiCq6//np+8IMfcPXVVzNhwgSeffZZ0tPT+eKLL7juuuvaLCw9PZ0lS5aQm5vLt99+y9/+9jcaGhpIS0trdf/ExESs1ua+U6vVSlJSUqv7dwcDk4xoBhxBkYL8dMz3uSQ1jgi9Ga/sQRNtRUEVU11KIWWBI5h1Jn486vsosoQmqpZLB8YyekgS63eV8NyCLby8fj4Pr3gGq6uOjw98AbKGIdoJAByrVQd81XtsxJpjmDpuEENS1CmsM6IzkB1xbC/ZAwP344zbw5dH1yIZvEgSbLSuRFFQTVcUEs1xmDQR2Hw2PtyyhVc2zmfZga9QZInLLVdT5bRS7iyHoJ4DDbsBhTHD1FmPtfGVFNuLWX9iG8EItZe9uzyPF9bPI0Jv5tfj7gHUkc2gumckXYBIvRlzo3CU1zWQkmjBbNShKAoLcpfgDng4UH0Uc0QgHONIjDWTHGcmKVaNY7i9QRwuHw+/upZtByoYmK4QqTdzZeooALIuk/FLTlAkaoOqlTAwIgOtpMUfUBup0KRxsjMaFA0FjaPwN+4tZd5He3j4lbWszVWtEq/iQo8ZjUbDA2N/RnZqJteNHIKk91FUWc/Wqk0AHG84jtVVR7ldvR6yIwbJ4MMju5p1qI45DiMZPNxw6RSijVFE6M1Y4nwoRif6YDSRjQFlizYayeiiX38F9B7VLddIvrUQrUZLRtxAdh2uwmLWo7hiCO7/LoorBpC4MmkcRQ2lHGlMC91+QG1w9NEuDFo941JHE1M3DiWo4/ND/6HcvJUBVxxj9NAkdh6qZH+xmonzRZ46vUq5rQpDUgXl9qrwTLEWYyR2r5N6bz0JEXHoNKr76mcjbyE9JpUy8yZ+9P10EmPMVNvqOFytZhrJisxfty9kzfFN7KndAZogXxWuJFKjNqBasxONuTFOdHI4itbLvtLGLCWtn02lG/ntl8/y1KqXCMpB6vw1KFFNPeDUVA/6AcfRJ5UCTTGOKqcVbVQ9UvIJrM569uZXsaH6a7Rx1cgGG+YYF7UDl6ONLyeqMY8iOToWraImvITH/Mg6tOjDrqpQADvoMRIfbUKSICqQjlFjxhG0kRExFJBIjorlxalPEhcYSoXmACsPb0EyuLGl/QdtUjHbjx9G0vuJNyaQEq22YUpAx21XXM0lqbEoAbVMvUaHzp1IoHogedY8jtj2E+yfR2pUf9AGMGTtRFZkroi7CsVlwaBR37kHxt6FhMSB2jym/gDchgo0dYPoDs4a47j22mtZsGABmzZt4tVXX+Wee+7h1ltvZdasWXz88cds2LCBRx99lPj4+HYXarFYSEhIoLi4mLy8PK6//vpW9xs9ejSbNm1qtm3z5s2MHj261f27g7gkB9qkEm4ePpU7rr4CgGijhQZ/LdqYGoxaIyPjxqBLLKPAfpjvXTqZ1IQ4tN44tDFWBg+I5q5plzJ2YoC9ga/YVbkPu8/JnNWvsrN0L/6SIVyaNIg4cwwFIeE4ZdBedGNWTHb/Icj2ODyyG/xGUDQsyfsMxW8gaI/FIztRXNEE69XGPyEynqDXgKQNcsi1nR2le8kt34tsS+TyuCvQa3QMikkl23QNGJ1oouq4dowq4NpY1eTfWryLct9JgrX9iNRaqHXX88j4e3Fa1TodrSjB5nVw0LMJNAFMehNmvfoQuwMuYlJr+d/N7zHry//HzrJ9XJM+DkVRMCTWcNy9n33SZ9gzvuCaq2K4fuxAnJoKQGH/MStVtS5+c+doIuPcpMemEW+OJcYYhdeiXiOTW62r4tczMGYAGkmDP6gKR2FNJYrfwMDkGGSPCYfpGPHjNmO44hvW1SxHI8HqHaGpP9wYNc1diPHmGJCgxFnMCddRgrX9UFDYeHJHeGEti099IV0xh/jV8qcotVWoc1Ep+9EHohidchmSJJESpboTJW2QWH2T23VEahoas4t5+/+C+Yp1vHPkLxQ2zoFUUHuCjNg03G6ZgpJ6fjAxA41GwuUOYDKojXdmxHDMehNfHlUH5m4vPELqJU4qXRWkRaeg0WjIMI4gsuRa/jj+efxlgynz55MxWKGm3o1XUr0D+fWHWVe4hZoBX1Js2sA7Oxdj8zqINlqIMlhweB0UNZSSEtW0lIJeq+c3E+7HHfDyzo7FJMSYsEbu5tm1cym1VbDiyDdsKtpJnCmGcncJUUkOZEXmMstVAAwcpEEyqoIdrO2PosDWor3o+hdivmIt+fJmdJKWY7Un+fzwfzhhWkV9wqbw2CBNnHoPzLGNa3Q463D7vDi0qpBIGpkvjqxl/pr/oI1unLLc58IQ2Ti74wJ//QAAIABJREFUQfohtlSpbql+lkQSIlUVCc0yoAS1aBVDeOR4cYMafwx6TRj0WmIsRmz2IKma4Wo9POqzaIkwEGEwMynhBhSfkR1le9AmluKQ6zBkHuDT0oUoPiMj4kcwKLY/AHLtAK4bk0lqsgW/R3VVZsQNpMERIFCRDkjUx21DJ+l44pqHGGTJQGP0MDz+MqJ0sYCGjJgMUqP6M6r/cIYlXcLSA1+wvuorUk0ZDI/qnray3cHx+Ph4pk6dyj333MMDDzzAj370I7Kzszs0X/2GDRvYuHEjxcXFrF27lvvuu48pU6YwebJq0s+ePZu5c+eG97/77rvDlsmxY8eYN28eeXl53HXXXR34iefGPtsRTDojt4+4MbxtUvqVFDoK0CaUMzAigxGRVxFsSOCXo+7lrlG3AjDQMAxNpI3DdUd4K/dt9vlWoY2xkuK9kl9d+XNqXLWkRw8iUJHBgMRILonP4FjtCQLBAHafMzxqOS06Ba1Gy8TMkejd/VBkCV9hNsHKdBQUAjWpBKsaTemGxLDpmhgRh8uuNjJ2TSmT0sdxY+YP8BcPJTbCwuOTHuJ3E3/JzZdPQgnoMA7bwaflf0My29FY6og2WiixleP0OwnW9WNizE38buIvGdV/BMvXF6H4Dfx7+37e2PABNfoDRAT7MT7tCiJ0ao9al5ZPoWENeVVHGBSbyl0jb+XX4+4mOTKBQGI+BdIGAnIAWeMlaoCV0WO0rKxZgjaxlKPFtehSjpGSouVkQynpsWlIkkRG3MBwj7+/rE7DIdvjiY82o5E0BBqnyC62VqH4TPzy5ssJVKUjO2IYljyYfuYUdInlTL8+hX0FNZTX2JElLxG65sIRyuMv0W1HQkJbkc2QhEw2nNwWFo6XZ/wIACWhkDp3Ayvz13OoOh+v3soAKRuNpL4XwxMvRafR4C/LZIjl8nAZd+VM56ErZ/DrK+/Bd2IEoOG5tX8h31pIQe1JhsRnsuf/t3fm4VGVZ///nm32mUxmMslkkpAVkkAWAmFJ2EGQTSrgjlqtS6lbXYpWRAFb30BfQaq01oUquKDVVvuiFlqk/lxA2WRTFhEDgbBkI/tktvP748w5mUkyyQxMZg7k+VyXl2GWzJ1nznnu596PVIHngRGDrOjnrUQWg7ytdmDGgIn4+uRurNvzd1To/o1a8xc4WHUU/bzFZPEmDarqWnCmugWuygxoWA0OO7cBADhNG2gwcHGNWLPrXbgbjUhTDcSh6h9xvq1BUBxKLc611OJ4/Slkx2X4rVFKjA1zcqdiZ+U+cLpmePSC4nx113q8d+BjFCcV4saCn8FNtUGXfBoURSHLkA3excISz4NStcDTqgZcCvDNMTjStBdsymEYeBu4Y+Px7NQnMSh+AN7Z/39wMS3gKbdUdFdFCdYirxJa1L9X8SpWf70OtKEGjEsDd20CPv7hP6gxfgWFtwV7s6MFCpUQU6M4B/5b/iWm9h+PvPhsJBgEhX7krLd5oYcBxXNoamvCNye/xT8ObkR+fA7g4sDQFEwGFWob7NA15cJxLA/Vp4TrR68Rrv3MJCPcdQkob/oRjOUUss1ZYGoz4Dpvhvr4BFw5ZCCSYuPgOFqIIsNoGLQKJFl0cDkExdHflCakuDtVUFYOR9sPg3Fjv3tg1cdjTOI48B4apQljpIzOmwddjyfG3w+KonBX8U24IX8W5gychqemzMct0weiN4ho5XhDQwOeeuopTJs2DYsXL8bUqVOxatUq6fnTp0/7BWWGDBmCZ599Fu+++y5+9rOfYdOmTfjTn/4UkRoOQDC5jzafQKF1INScSnr86typiFObQTFuxHOpcNtVcBwehrHpQ6XXPDX7Wlg0cVi59RX8UFuO+cNuwRDHrWiqSMHYtBFYMHo+rrTOBUDBZtEiy5SK043npI3J6K1eHRCXgddnr0SSwYo0YwrsuybDU2+BozIdQ+OHwnUmFe5aKxT1mXCfS4aFSQY8NFIMNtSKyUQUUJoyFMMto8C36qFVcRicOBBJBivyM63gTg5DnGMQqltrocreDdAezCuYLf0tTIsFdKsJJSlD0drmwqHyWsRwsWDVrThSexRMkxWDmVlIi02BgqPhaYqBp8mImcnX4aVZy/DIqLvxs9wpYGgGI1OGwMM2Q+GKhfHMRKj5OOw98z2+rtgtfJbpDPac2Q8u5Qe8ffgttLnakOotjkqPFRSkmlPBqrHBcTwXzsoMmGJUYGgGLq/FUWuvh5bRoyjbgpjWbFjqxuHxCb/E4it/CQoUWK+L4z+7jwIUoOuoOLxr71LUId6dC6PSiAnppaior8Smo/8PZk0s4rVxUFBq8G4GAy398fnxb7Buz9/BO1QYoCuQftetRdfgwfzfwnUyG8lx7a1fjCoDJmSUYnzGSHDnU1FIXQWtQoMlW1aizdWGLHMa9v9YDY2KRVZKrNSnKTdNOBg0NLdh7sDpyE/IwUeHN8Pj4pCkToPL40I/oxAcjY/VwO5w4/DxOlA8i+kDJuJQzRFcc2USPGwrhicJFnSbywFn+SAMjiuC2+OG2+OGXiFYHPX2BvA8j+y4zvfcpIxRoCkau1v+DYp1IT0mDd+dOwIAuL3oWpgYQY7zjGBBFWYkQgUDeGUzGHUL2poFt4/7fDxcdCsohwaTE2ajoVqFxhYnfj74WihZJdR1AwGewv6zh3Cq4Qxqnedh1cXDydtBx1SjzWPHjtO7QRurEEslw3myPwrj88GfysEwpRAba3I0g1UILq2YxkJcM2g6biu6FhRFISnWBDiV+PF8OQCApTgoeQOana1Y8dXLSNDG4b7hvwBAgfZRHFU1Lrirk/GDtzedXiNY20Oy42FlMsFTbtDKVkzMKEEaXwLHD0Nx18xiaFQcYvUqXJlTgnmThWslKV4nxVqyzOlSv7i6k0Z46qxItwoHhixjf9h3XYF4lVXqkxerNkqZesmGRMwZOA035M/ya5kTbiKqOGbOnIktW7bgwIED+Pzzz/Gb3/zGLz33jTfewLJly/zeM23aNGzatAkHDhzARx99FNGZIMdqT6DJ3YJiW4Hf4wqGw13F8+Cxq2H09EN9kwMqBQOVsj1JTa9WYV7hz+B0O1HarxgTM0qRmRSLc7UtaGp1YlhSIaqrhS/eFqeTNsU9Z74HAL/+UkpWuCBTEwWfPUUBcHOYnDgLcKoAnkHz0QHgHRpkJiagdc94FCcOwdmzwkbKe2hkGTOl9EWNul1Ohqbw9E2z8OT023DtoOmAohUUGIzqV4yBlv7IjE2FWWuU2jl8d6wGbg+PfrFWUNoG2NGAtroYqRpdwdJo+74EjoMjMbF/MRivX1xkYnoptC4rYqpK0dLigZlKwZGan/B1xW5QoEDH1KCS2gtAcNkA7VW1GbGCe6ifwQaTXiVYXS3CZ7M0Axcv/L0ujxM6lQoUReGhG4tw37WCuW7RmpGXkI2dZ3dhYIYJm/cKax2r8nezmrw3HO9ioajNgUGnwMSMUgyx5aPe3gCbPgEURWGwbhwcRwdjdvZ0tDhbcazuBJwns2CJ8e/tlZNqgi1Oi/ysOHSFTsWgrVmJJRMfhkkjbBADzOk48GM1BmWYwdAUMr2KY0CqkCLd0OQAQzN4sOQODNQPhePQMPx6+F24IX8WRvcbBkBQHADw7ZEqWGI1yLcKVejm1PMAeBQn58HKZsB5Mgt8qx4FtgFQemNUYowDENLS+5vTO8ltVMdgiC0f1Y6z4F0sZqddDx3MmJwyFRatGSdPerwxNyDX0h+piQYMTU9HZeMZgLODt2uQnhgDqt4Gj10DY91IZNqE0/+JMw1Ii03Gmqv/F/S5AdAjHvvPHpJa3s8dOA0AwMYLVoKCVoKiPUjTZ4G363Bt1g2wn0qDRS3EEpqdLaA5F3iewgBVMa7Lu0qyChNMGrhbdLB7hLiLQa2BxTUQz165CHcX34RF4x+AihUK/RiaRqxeidoGu1SRLqb/6rwWh0rJ4n/vuBosrwINBiNSijCuKBlXjkzF6EJBmdI0hV/NLZT6SSVbdFJ2V39zGs43tUluSQBS7yuWoQBeGCInWhxiw9VIQnpVdcPOyn2gQGGIrXOGQZEtF/ThSXC2KlDf1AajXtnpNSUpQ/H42Hsxf5gwNVG8SMor68HzPD7bVYHcNBO0ak4qANpzWqhF6Oq0kGrVe/8vKBXfDq0u7+kjwxYDuBSoONOE6mrBNPc0mFDf0N5FV6vyT0nNSjEiMU6L6f0nol9MEobaBkHBKvDwqLvx2Nh7YDKoUOOtB9j7QxU4lsYAazJ4SlBErgYTYvWC4uBYyvt/GoldjJ61GazIp2bC3qxEs92JRGW61I12bMpoUBQPXnMeMS250Co0oCkayTFCJouoXFOMSX7rbTKowNA03B43PB4eHt4DBSsox8ED4pGX2b5hT0gvRVVzDSaO1aAZgk/bpm2fCgcABqUeRs4E58n+qKi0w6hTgqZoPDDidmTGpqLQKvi2cwz58NRbkGpIQ7+YJOEUWJ0Ec4zK7/fpNAq89PgVfhXmvmhVNOqbHIjTmPC7Sb/Bb8fcA86jx6mqZuRlCLKPyEvE0Jx4DEwzQe+tggaEDd7UOBQ6xojUhFjMGTgNRu+1k+CtzD5V1QRbnBbpsf2ELgEnhLTMeK0Zz89dgPmj56IgKw4ZibEY6G1xYlBqoVcI31+/mCSpQrojE9NLAQDuungcOdaCqu3D0HRS2BwP/FgD1i7IP9AiTMW06i1Sl1++TYN+Vj2sOgva9o1FojoZ/VOMYBkKW70zZhQMB7vDjTgmGT/WHcf/Hf4PcnQZGJwouGDomCqoKQOGGMaBd7HITxCys8SDjk6jgIZTo8nRAjBOwMV2ui4TTBp4WtqVvYLh4HTy6GdMwhWZYxCnMbVv0gwFU4wK5xvb0GJ3+W3aOk17rY9WpcCdw6/FLYNnQ8OpMbUkDfddOzhgBmmcUQ26PglZ7AgYFbFobnVK161Rr5SsGUZsrurmpdb/RHHIjF2V+5GsSgjYtsGoV+J8YxvON7ZJHTd9oSgKRYl5ULHCc+k2YcP/qbIBB47V4FRVM6aWpAIQFEWMyoCD1ULvLtFd4ktumgk0BQz1Zj+JhVK+rR/Ez9j+/RnApUAckwRXVQrO1rVI09c0qq7Ld1iGxe+vWIAHS+4AIATmjSoDzDEq6Ubcc6QKuWkmJBkEGXgXC75F72NxCBdxSrweDNP15aVVc2hsbkNrmxs2TTI0nBoMRWPuwOnw2NXgeQqZqiLcOfQGzMy+AgpG+PvitXG4ImM0xqaOgNGrqFiGFlIZaQageNQ1ClW9ouLoyBBbHiiKQj11Gjk5LHgnB2uMv8VB0zTuzX8Q7nOpaG1zw6AVblqNQo2yKb/FrJwpACCdCB1OD1JbJuP4VwOh4FjpOwgWnYqRZpAbVQYMseXjwI+CUsvPEpRNgkmDJXeVQKdRwKBV+B0ajpyoQ/9+sZ02pfjY9s3eFqeFilUi2ZAoWXLxOmFjunJkKp751ShoVJykFPVKnXTdd4xv+FKUOAiTM8bBdSYd/+9bwQVYcbYRPM9j/9FqpOqyoGKVyLFkCX+Htj0j0mPXICVBj0Sz8DnmGBVidEqMKkjCpztOSIV9docLVmUqeJ6HQaHDFEspYlQGGJQ6UBRggBWJyIV99ySkmIXvUjzo6NQctAoNmh0t4GkHeDcHq9m/1UmCSQO+pf07UzBKOFz+hZ1irzgxxiEitsJRcAyUXAfrOqMUM7InBVw7X2iagk1vhbIuRyo6HTxAWKt+Pp12xQFybo9HUmY0URzyIicuEyNiCwI+b9Qpcb6pDeeb2mDsQnF0xGRQwaBV4KfKemzadhxaNYdRhUnS8+nGZLg9blCgYFB1bmWemWzE+t9Pl04ioh801iB8Nk1TkjXyydZyABQWlN4PT10Czta0oCWAxeGLilVCwSr8HhMtjvqmNpSfbkBhfwsSvJuOEIynJAuAoSmwDIV+iYFbsWvVHFrbhBtTr1FgYnopxqaNhMUQA9fJbLgqBiDVHI9R/Ybh5sL2WAtFUbh72DzkWDIR6/08k0EJiqLAMgwAHpXVzaAoD5Rc13+jhlMjNSYJh6t/hFtZjwxTCkb7fAciccb2TberQwEAKDlBOdkdLhw51oLs5AT8ddFkv55ZwaBVMdJ3KSLGNzK6aI1t0CqlYrkWuxMnzjYixxs09/u9ak46JCRZhM050yQcVDiG83OHioxPL8FNBVcjy5QmZfTldBHfEGFoBncNuwEaPlaayX7iTCPOeadhju03HC/NWib9Lqu+XXHwXsVhjRM2cnHNZ4xKR4vdhc92nxQaaLp5JKqTUZIyFL8u+QXUjLBxp8QIlo3GFY/GVic0Kg4a77UtzkjXqjjoOK/iYJyAi0Nmsn/b8rREA8bk5Ej/VtJKqZWPiMfHLSRa14AQzwDaA+MXQ1K8DqeqmqRrIdGsxZDseOkzgHYl4eeqCnBA601Cmrq+d+9ebNu2DTU1NZ2KARctWhRWweTAHUNv6Lba0qhX4lRVExqb21sadAdFUciwxeDLvZVoc7gwfVS63yklLTYFe858D71SK+XMd0Sj4qSTrrh5xOpVqDjbBJ2agyVWjRsmZ2PvD1XQaTikJRqg4Bicq2sBx9KgaQpKRde/OxDmGDUcTrfUjiQ3zQSbQQ2O4UC3JsAB+J3Crps0AAX9A9fa+FpIOjWHWUXXSP9Wt6agqdYJ60RNV2+VEBWVOOeAY1iA4oX2JRQPVQDFAQDZcZn4rPxreHgPpmSOhYLrvB5mn7/Ht92IL+I6tjmFmSgZSTEBlUy3f4uWQbPdhVNVTdIG/92xGgxMN3e5KRi0Cmnw1esffw+eR5frTVEU4mM1KD/dAJv392aZUvHZT9sQrzVLPn5fNJwaV+deCUBwL91SOBfDk4t6/BvMRjWazzSCoSk0NDuw65CQ5NG/X6xfYolVJ2yCGlaNpEQLctNMqPW2ChGbN+akxSLDFoNPt5+QYgIalQIPld4JANhVIdyTKQYbvjt3BAqHBY1wQKdRSPeG2GpF62NxuCk3BmfaOs2pYBgav/7ZGNzy9/fh5j1QsBwcTv+uBu2ne9rPFVmUHY91nxyUXEkXQ7JFh237T0t9w4x6JZbeXeL3GrERqtvN+1lBkSZoVbVmzRpcf/31+OCDD3Do0CEcPnxY+u/IkSO9KaNsidEpUdfQhvpmR8DNpSMDM8xwON2YMToDt0zL9XtOjHMYu3BT+SIG4cVRteKmrddwoCgK86bm4A/3j8FTd4wERVFIMKlxtrYFLXYXNEo25Ep9c4c27Ok2A3QKLV6Y/jT6a4TCPNHqAYAbr8wJ2A0Y8Fccmg7Wj3gDWk2d4yO+iKc+k6Q4GFCUp11xKAIrjhxLpjRtLdXY2doAhDUWi/UCWhyi4nC40Wx3BXQB9kRBmgYKlsb7n/4AQLBgTlU1SdMGOxKjU6KhuQ2btx/Hv7aWY874rIDrLQbIbd5Oz5mmNABAgrbrQL0vLMPiqpx2V2F3iNfIyHwhXrRlRwVYhkJaor9VY1QZoGQUSNTH47mHxsOoVwoZRWh3rVEUhawUI87VtUjuKpWi89qOTy+BoTkHvF2LphYn9BpO+k7Ehoei4mhytqDJ0QK9suvrimVYJBkSoWSVUHKsVEwq4u7C4jDqlUi1GkDTlBQYvxgyk43weHhJ6XYVN5Umj/q4qqKhOIK+0tetW4dFixbh5ptv7k15LimMOqXUBryrL7krrp3UH1eNyeiyJbXYWjlW3b2PXO1VHA1eP7f42boAp574WA3O1rZAqWCgCaIVdkdM3hPW7sPnYIlVS59j0hgxbKAV5xsdXd7YgdD6yKDtII9WwwE16OSH7ohOzYFlaGnDUrA+FgfHQ92N4vBNLRUztroiLkaF5lYnYrTdKw67w41Wu7NbF2B36NQMrixJwydf/YQbp2SjocUBnm9PguhIjFaBxmYH1n1yEAPTTbh1RuBcfWucBixDSy3MU2OSvBt3wgXJGgjRWphRmo6v9lbi8Ik6ZKUYwbH+1hxFURgQl44kQ3tCQkGWBQtvG4ZCH6tJp+bQ1OqE3as41F1cXxmmfkh0DkOrw4U2hxt6tUK6NyTFoeKgU2jR7GiBy+OGThH4QJIemyLUe3A02jpZHN7TPdPulrWaNOBYGkkWLUx6VaffFyrZ3m7U278XugB05f6WXFXu6GZVBX23NzU1RTQV9lLA6GNlBBPjAARTU6fu2tCz6ixQsyqpAC0QojkuzudutzgCKA6TBoeP1yEuRg3tBZyKRdO8vsmBEYOsfs/NGpOJWWNCq6vRdnBV+aJXC7Ope1LENE3hsVuLpROtwtdVZfN0qzjiNCaYNbE431qPJIM14OvMRjWOn2mEIZCryuviOt/YBg/f2XoKhTnjs/CvrT/hk60/oZ83e078f0cMWgU8PFDX2IYHri/qduOYO6E/RgyySi4OlmGxdOIjsGiD7/QQDMMGJqDZ7kRephkaFYsWuwv9k7u+jp8Y9wAotMtM0xRK8m1+r9FpODhdHilQrFJ27V5VK1nUNQhDqOKMaii9CkZ0f0kWh0NoVKhVBD6Q3FRwNepaz+ODjdWdLQ53+ybNsUJKrjivZ+FtwyWFdTGYDCpYYtWoqmuFVsV26UJlfGMc7ugFx4P+a2fMmIHPP/88olXbcseo9/WDh+7b7ghN0Vgw+peI0wZ28wDtFkd9k9CnSrI4AlgT6YkG/GtrOY6cqJPcAqEQ6+PvD8ccY9+TecdTeopVD5c7uHnlI/PaT60Kzqs4apqAJD5gcFxkqC0fFfWnwXXjhonznqIDHQpEK6uuUXSLXPjmEWdUIzvVhL1HhXYvLENLG1NHDF55bHFav8BpV5gMKr/4EyCc1MNNaYENpQXC5p+SoMfh43UBXW1dxVY6Ilq1or9fFWBjVikY2B1u2B0u6DUKaWNvtrtAUcK9olNo4PIIlkt3FkesOgax6hgo2LpOMY724Lgg+8LbhkvrGmoyRHdk94tFVV1rwINTe4zDA7dHaEwaiSaxneQI9oWJiYl44YUXsHv3bmRnZ4PrcGMGMwHwciPmAiyOnshLyOnxNeKpqs3hhlLBSJtvID/r6MFJePWfB3C+qS2oIH6nz+MY6DUcGlucIaeadoWvxdHRdXbHVXkIflp7O6KrqrXNBTUlxDy64xdDrkdPH2Q1C66InoLjYiBWo7w4P3dephnvbT4CJccgOV4nbRIdES3dGaPSo3La7Il+XsWRFUBxBIN4CBKzo7pyVQGC8m5tcwkTCcUCPAUDp8sDjYoDTVPQcu1Whq4bi0NEwdKdsqo6pr7mpIXXYhPJTjXhy72VfodSX3wtDo+Hj4qbCghBcbz33nvQaDT49ttvOw1eCnZ07OWG76kgHBZHsDDezKg2hxtKjpGCsoFcVXqNAqWFNny266Rf1XgomAxCGwix9cXFIG4KFAVoOpwkL3QjZGkGNM0DlPcG7+FUS1M00MNHXTU6A8W5CZ389CKiq0pSHBdhcQBAfkYc3uWP4LtjNRg7uOugPQDkZcbhV3MLcMWw3ul8erEMG5iAE2cb/eoPQkVMbxUVRyBXlUrJotEbExKvf6WCRWOLU3LL+rqnglIcHAOHS7A4dh86h4ykGL8YR28iTt0MZHF0TMftbXkCEfSVvmXLlt6U45JEtDJoCtBrLz4dLxTUChZtDjcUHNPeqrubzI6pI9Pw2a6TFxzANceoUXW+VcrSuRg0Kk5SGuE6MTMUDYriAUq4wQOlM4eCSsl265oTLY66BiFJ4ULXViQ7LRYsQ8Hl5rutg2EZGtNLO7cAkQsl+bZOMYtQ0am9rirR4gjgqlIrGIiVAeKBRIwBSveFn+LoPlsPADhOsDicLg+Wrvka867MQUF/IQutt0/4GUkx4Fi6U/cBEdEKdbmFrKpQmsyGkws6IjU3N4OiKGg0F7+JXMpovZk9OjUXcZNRpWSAJuHUG2dUQ6VgAmbhAMDAdBMmD++H4twLy6aZMiIVhf0tYdnoaZqCxifdNRzQNAOKho/FcfGKoydYhgbLUO0WxwWm44qoFCz6p8TiYHkt+iVcvEvwUkbX0eII5KryUShiXKSj4vC1OLoLjouIlmRDcxs8Hh5tTrdfcLw3UXAMfj+/FNYu2vX4fr7HI9RxyN5VBQBvvfUWXnnlFWkEq9VqxZ133tlnA+YURcGoU4R1AwwW8UZSKhjoNQq8+8yMbjd1iqLwwPU9F3IFYlThxZ0gO6JVc2FdN4aiBaXhVRzhsDiCQckxfsVmF0tephkHy2ulvmR9FVEJtCuOAK4qn8dF95YYAxQtQG2oFgcrKg4ho8vt9nQKjvcmgXqaAV24quSuOP7yl7/gpZdewh133CGNIty5cydWrFiB5uZm3H333b0mpJwxx6ijojhE0108HckxSNodQjuMcCsOj+SqCiZzJxwoFSya7aLFcfF/z8zRGTAbVAEzqvoKQqEq0NTqBMfSAdtq+HWk9iob8d6QXFVcaBaHghM+S+wF53LzUowj2vcZRQmt3V1eZSZ7xfHOO+/gd7/7HWbOnCk9VlJSgtTUVDz33HN9VnE8cP3ggNkvvYl40urYWO1SYfb4LCgCBJ0vBKF9Oy/EORBBi0PRrrgDnYpDwWRQYcbowE0F+wo0TUGrEooAuysu9X1OJ1kc/q4qsbOvguGCqoIXr0uxTsqvSjtKwWhfWJoSXFUeHnQU9h4gBMVRU1OD/Pz8To8XFBSguro6rEJdSvTrJq7Qm4gnrVD7TsmFCUNTwvr7GJoBT3kg5thGzOLwKu4LaeVC6B69RoGmVifUATKqAH9XVacYh9cCpGkaGk4tzbXpiY4WR7SrtDvCMJRUABgteYK+u9LS0rBhw4ZOj3/00UdIT5dvhsflSkdXVV+Hpmjw4AHae4NHIDgOtG9SF9LKhdA9Wp/BSIEQ7wPftuaiFeLX2kahCSq+If4uwNdVFdkYR0/QtDDIyeW5BILj999/Px588EHs3LkTQ4YMAQDs3r0bO3bswB9mKkYMAAAZiklEQVT/+MdeE5DQNeKG1VVbgr4IQ9EA2tNxO04e7C0kt8hFZlQROqP3bvyBiv+AdqXi29ZcvDd0PnU1Ok4DFRdcrZXoqqqXXFXysjiElO1LJMYxZcoU/O1vf8Prr7+Ozz77DACQkZGB9957DwMH9s5AdEJg1Je4qyrciIqCokXFESlXlfA9hDPQTxCQXE9BuKp8i1+VXVgccwZNA0cHt91xnYLjHnii2BeqI4wY43DzUZnFAYSYjpuXl4dnn322t2QhhABxVfkjxjR+fWMB/rJvW8RdVRdb/EfoTHtBX8/BcV8lIbkPfb6TEUHMFBFRdnBVuX2yquQQHKdpWpJJlhbH+fPnYTQapZ+7Q3wdITKofHy7hPYsKnOs/2zm3kYpxTiIqyrciFlS3XWeFa0RP1eVsrMyCQWO9VoczV1kVckgxsHQFFxemWSpOEpKSvDll1/CbDZj5MiRXWaN8LzQyfTgwYO9JiShM74FgIR2i8PpFsbjRsri8M2qIoQXse1Id8FxJceAovxdVQneORlid+NQ6WhxuGSWVcUyFDxub5NDObqq1q5di5iYGOlnkm4oH8QUReKqEhAVhUNUHJEOjpOsqrDj2+02EBRFwRan85tdUjTAgjeXTr3guJNYOd5iF1qxu93RnbbXETGrSrYWx/Dhw6WfR4wY0evCEIKHuKr8EV0IjkhbHAoSHO8t9JqeYxwA8OdHJ8L3TEtR1EV9H2Idh4jbw8PjlkflOOB1Vbk9cLs94NjoWLpB2zm5ubmoqanp9HhdXR1yc3O7eAehN1ETV5UfYlNDp1s4JUYuq4qk4/YWoququwJAQNjMw+kN6XgYc/laHFFyDfnCigWAUbQ4gl4Fnu966o3D4eg01InQ+4ht3ANN/etriMFxh1sIaDIRqhwXg7PE4gg/uiAKAHsDBdvB4vCJccjA4ABD01LLkWgF63v8Rl577TUAgvm3fv16aLXt1Zdutxs7d+5ERgbprRNp0hINePruEhT0t0RbFFkgBscjHuPgSIyjt0gwaWCL0yIjDOOKQ4FhaNDeWgmgY6+q6FscNE3B7fEWAMp1kNMbb7wBQLA43n//fb/BIRzHITk5GUuXLu09CQkBKeph3nRfInoxDtHiIK6qcKNRcXjp8Sui8tlKjkZrmzA+1rc7rhyC44x32Jfb44lazKXHq12c/HfLLbdg9erVUpYVgSAnREXh9ETW4shJNWHEICvSEvv24KXLDY5lJMXh9vhUjssgs5SlabQ53XC5ebBydVWJrFmzpss4R1tbGyiKgkIR2dGpBIIvkqvKJVockbmh4oxqLPoFyTi83PANkIt1HDQlj6wqmqHgbvNEdeZ40HfXr3/9a7z99tudHl+/fj0efPDBsApFIIRKu6vKGxyPkMVBuDzxDZC7ozzfuyNCOq6QIiz7rKrdu3dj1KhRnR4fNWoUvv3227AKRSCEilQA6PGm40bI4iBcnnRlccihTxUgzLqXBjnJXXHY7XYwTOdTHE3TaG5uDup3NDU1YcmSJRgzZgwKCwsxc+ZMfPjhhwFf73K5sHLlSkycOBEFBQWYMmUK1qxZE6zIhD4E0zEdl1gchItALALUqFhvVlX0TvcdEbOqZFs57kt2djY+/vhjPPDAA36Pb9iwAf379w/qd5SVlWHnzp1YuXIlrFYrPv/8czz++OOw2Wx+VeoiL7/8Mt577z0sW7YMmZmZ2Lt3LxYuXAiz2Yyrr746WNEJfQBG6lUlWhxEcRAuHLHtiE6jQEurE54oTtvriOiqcsu1V5Uv9957L+655x4cP34cI0eOBAB8/fXX2LhxI1avXh3U79i7dy/mzJmDYcOGAQDmzZuHdevWYf/+/V0qjr1792Ly5MkYN24cACA5ORn/+Mc/sG/fPqI4CH6013EIFodc/NGESxOxPkev4dDY3BbVYruOMLRQOe6JohUU9EqMGzcOL774IiorK/HMM8/gmWeeQWVlJf785z9jwoQJQf2OoqIifPrppzh79ix4nscXX3yBc+fOobS0NODrt27divLycgDA/v37ceDAAYwZMyZYsQl9hHZXlZBVxRKLg3ARiK3V9WpFe1aVTCwOlqHhcXuiOnM8pKqlsWPHYuzYsRf8YYsWLcITTzyBsWPHgmVZsCyL5cuXB+x1dffdd6OhoQFXXnklWJYFz/P47W9/G7Si8uXAgQM4e/bsBcm9a9euC3pfXyUa63WuTeijVt9YDwDY8+2eS6qbM7nGQqO316vJex052prgcntwrqoKbpdTFt9TbW0d7G0OQa5zZ7Frlz2o94Uie1VVVbfPR7Tc9c0338TBgwfx8ssvIyEhAdu2bcPChQthtVoxePDgTq//17/+hY0bN2LVqlXIyMjA/v37sWzZMiQmJmLy5MkhfXZeXh6Sk5NDlnnXrl0YOnRoyO/rq0RrvSrqK4GKD8AqOVBOCsXFxRGX4UIh11hoRGK9vvhhN747UYF+SQn4/kQ5YmJMUNfXyuJ72l6+F0cqK+HhHUiy2TB0aE6P7wl1zU6ePNnt890qjiFDhmDz5s0wmUwoKirq9gS3e/fubj/Ibrfjueeew4svvii5mnJycrBv3z6sXbu2S8Xxhz/8Ab/61a8wbdo0AEKAvry8HK+88krIioNwecP4DHIigXHCxaJg/ScLOlxu2QTHWYaGy+32/ixDV9WTTz4JnU4HAHjqqacu6oNcLhecTmenlF6apuFyubp8T1cpwAzDwOPtG0MgiNA+MQ6Siku4WBTeyYJi12OH0y2bhAuapuBwRnc+SLeKY/bs2V3+fCHodDoMHz4cy5cvx6JFi2C1WrF161Zs3LgRZWVlAIBHH30UCQkJeOSRRwAAEyZMwIsvvoiEhARkZGRg3759eOutt3DHHXdclCyEyw/GpzsuKf4jXCzDByWABw/Wm+7qcMqnjkPMqhJ+lnk6bjhYuXIlVqxYgYcffhgNDQ1ISkrCwoULMWvWLADA6dOn/bT6okWLsGrVKixevBg1NTVISEjA7bffjrvuuiuSYhMuAdpHxzqgUWiiLA3hUqcgy4KCLAs++vIYAMHikEvluG/thizbqufk5ASdmXLw4MEeX2OxWLBs2bKAz4st3EV0Oh0WLVqERYsWBSUDoe8inrzcvIdYHISwIW7SbU53p5Gy0YL1sXxkmY67atUqSXFUV1fj+eefx+TJk6VA9p49e7B582bcf//9vS8pgdANvgFxEhwnhAtxY3Y43VBHeBJhIGhG5opj6tSp0s/z58/HI488guuuu0567JprrkFBQQE2b96MefPm9Z6UBEIP+Lo45VLhS7j0EbOWhOC4TFxVPtd3tAL2QX/qN998gxEjOs8dGDFiBLZv3x5WoQiEUCEWB6E3kNr1u+QTHGdlYHEErThiY2OxadOmTo9v2rQJJpMprEIRCKHiG9cg6biEcNGeVSWfOg5fy0eWwXFfHnjgATz++OP45ptv/GIc27ZtwzPPPNNrAhIIweDnqiLBcUKYYHxcVdHqRNsRxs8tK3PFcfXVVyM9PR3r1q2T5pBnZGRg/fr1KCws7DUBCYRgoCkaFEWB53licRDChmhxePjobdIdYfyyqi6BOo7CwkKsWLGit2QhEC4KhmLg4l3E4iCEDV+3kFyC434xDrnPHAeElNw1a9ZgyZIlqK2tBSA0z6qoqOgV4QiEUBAVBrE4COFCDoHojtAycFUFrTgOHDiAqVOnYsOGDXj//felcbFbt27FqlWrek1AAiFYxBuKKA5CuGBkmOYtB1dV0J+6fPly3Hrrrfjwww/BcZz0+OjRo3vsjEsgRAIxDZcmripCmJCDW6gjLHMJWRzfffddl40OLRYLqqurwyoUgXAhiJYGSywOQphgZLBJd8Qv7iL3GIdKpUJ9fX2nx48dOwaz2RxWoQiEC0GMcRCLgxAufE/3cgmOMzKIuwR9h02aNAmrV6+Gw+GQHjt58iSeffZZTJkypVeEIxBCgQTHCeGGkUFDwY7IQaagFcdjjz2G+vp6jBw5Ena7HTfddBOmTJkCg8GABx98sDdlJBCCQhzmRFqOEMKF3+leJgWArAwC9kHXcTAMgzfeeAM7duzA999/D4/Hg0GDBqG0tLQ35SMQgoZYHIRww8og9bUjtAwC9kEpDrfbjeLiYvzzn/9ESUkJSkpKelsuAiFkGMnikMfJkHDpI4d4QkcYGRQlBnWHMQwDm80Gp9PZ2/IQCBcMsTgI4UaOwXFfmdgouc+C/tR77rkHzz77rFQxTiDIDTG2QSwOQrjwT8eVx3VFyyA4HnSM469//StOnjyJsWPHwmq1Qq1W+z2/YcOGsAtHIISCVDlOguOEMMHIoIV5R+TgqgpacUyZMiXo+eMEQjQgripCuJFjryo5pOMGrTjIXHGC3JGC4zJxKRAufeQw+6IjrAzcZz1+amtrK5YuXYoxY8agpKQEjzzyCIlzEGRJe4yDWByE8EDTFER9Ea353h2RwwTAHlfi+eefxwcffIDx48djxowZ+Oqrr7BkyZIIiEYghAYjdceVxw1OuDwQA+RysTjkYAX16Kr6z3/+g2eeeQYzZswAAMyaNQs33ngj3G43GIac7AjyQexRRSwOQjhhGQpOl3yC475xF9nWcZw5cwbFxcXSvwsKCsAwDM6dO9erghEIoSK5qkhwnBBG2ue8yENx0JfCPA632+03fwMQCgJdLlevCUUgXAgkHZfQG4gnfLkoDjm0eu/RVcXzPBYsWOCnPBwOB5588kmoVCrpsb/85S+9IyGBECQsRbKqCOFHvJ7kEhwXlQVNybiOo6vhTbNmzeoVYQiEi0G8sck8DkI4kZvFIcoTTUXWo+IoKyuLhBwEwkUjuqjIBEBCOJGyqmQSHJdcslGUhxzNCJcN7RMAieIghA+5WRyiGNGUhygOwmWDeBIjFgchnMitPoiiKLAM1XcUR1NTE5YsWYIxY8agsLAQM2fOxIcfftjte+rr67F48WKUlpYiPz8f06ZNw/bt2yMkMeFSQgyOkxgHIZwwUkxBHhYHIBySoqnIgu5VFQ7Kysqwc+dOrFy5ElarFZ9//jkef/xx2Gw2DB8+vNPrHQ4Hbr/9dlgsFqxevRrx8fGoqKiA2WyOpNiESwRxdCyxOAjhhJVZHQcgyBJNRRZRxbF3717MmTMHw4YNAwDMmzcP69atw/79+7tUHH//+9/R0NCAd999V0oHTk5OjqTIhEuI9hgHsTgI4UO0OOQSHAcExdFnguNFRUX49NNPcfbsWfA8jy+++ALnzp0LOLd8y5YtGDx4MJYsWYLS0lJcddVVeP3118HzfCTFJlwiMCTGQegFWEZeMQ5AkCmaFlBELY5FixbhiSeewNixY8GyLFiWxfLly5Gbm9vl6ysqKrBt2zbMnj0br7zyCo4ePYqnn34aFEXh5z//eSRFJ1wC0FKMgygOQvgQN2g5uapoOrrB8YgqjjfffBMHDx7Eyy+/jISEBGzbtg0LFy6E1WrF4MGDO72e53lYLBYsWbIEDMNg0KBBqKiowDvvvBOy4jhw4ADOnj17QXLv2rXrgt7XV4nWep2tPQMA+PHoUbgrW6Miw4VCrrHQiOR6NTU1AgCOHDmM5hpFxD63O9wuJxyUK6R1COW1VVVV3T4fMcVht9vx3HPP4cUXX8SYMWMAADk5Odi3bx/Wrl3bpeKIi4sDx3F+XXgzMzNx+vTpkD8/Ly/vguIju3btwtChQ0N+X18lmutVcbAaqN2F3OxcDIzvHxUZLgRyjYVGpNfrX3u/ASrPYNDAXGQmGyP2ud2h3vQfqJVs0OsQ6pqdPHmy2+cj5rRzuVxwOp2dWrHTNA2Px9Ple4qKinDixAm/58vLy5GYmNirshIuTRjSq4rQC0gxDkY+1xVDRzfGEbGV0Ol0GD58OJYvX44dO3agoqIC7777LjZu3IhJkyYBAB599FGsWLFCes+NN96Iuro6LFu2DD/99BM2b96M1157DTfddFOkxCZcQjCkOy6hF2BkVjkOCDL1mTqOlStXYsWKFXj44YfR0NCApKQkLFy4UGqaePr0ab/GXUlJSXj11VdRVlaG9evXIzExEfPnz8e8efMiKTbhEkEa5ESyqghhhJXZBECgj9VxWCwWLFu2LODzb7zxRqfHhg4divfff783xSJcJrTPHJePS4Fw6SO1MZeT4mDovlPHQSD0JqKlQSwOQjhhZFjHwTG0VNEeDSJqcRAIvYmKVfr9n0AIBywtv8rxeVNzJBdaNCCKg3DZMDypEE+NfxBmTWy0RSFcRjAyjHEU9rdE9fPlY3sRCBcJy7DIS8iOthiEywy5zeOQA0RxEAgEQjeIFoecguPRhigOAoFA6Ib2GAfZLkXIShAIBEI3mI1qGLSKqAaj5QYJjhMIBEI3TBrWD2MGJ5EYhw9EhRIIBEI3MDQFtZKcsX0hioNAIBAIIUEUB4FAIBBCgigOAoFAIIQEURwEAoFACAmiOAgEAoEQEkRxEAgEAiEkLvscM7fbDQA4c+bMBb2/qqqqx/m7hHbIeoUOWbPQIOsVOqGumbhfivtnRy57xVFVVQUAZGoggUAghEhVVRVSU1M7PU7xPM9HQZ6IYbfbceDAAVgsFjAMGfBDIBAIPeF2u1FVVYW8vDyoVKpOz1/2ioNAIBAI4YUExwkEAoEQEkRxEAgEAiEkiOIgEAgEQkgQxUEgEAiEkCCKg0AgEAghQRQHgUAgEEKCKA4CgUAghARRHAQCgUAICaI4AvDWW29h4sSJyM/Px3XXXYd9+/ZFWyTZ8MILLyA7O9vvv6lTp0rPt7W1YenSpRgxYgSKiopw//33o6amJooSR5YdO3Zg/vz5GD16NLKzs/Hf//7X7/lg1qeyshJ33303CgsLUVJSgj/84Q8B+wZdDvS0Zrfcckuna+6pp57ye01fWrOXXnoJc+fORVFREUpKSnDfffehvLzc7zW9eZ0RxdEFn3zyCcrKynDvvffigw8+QHZ2Nu68807U1tZGWzTZkJOTgy+//FL67+2335ae+5//+R/897//xapVq/DGG2/g3LlzeOCBB6IobWRpaWlBdnY2Fi9e3OXzPa2P2+3GL3/5SzidTrzzzjtYtmwZ/vGPf2D16tWR+hMiTk9rBgA33nij3zX36KOPSs/1tTXbvn075s2bh7/97W947bXX4HA48Itf/AJ2u116Ta9eZzyhE9dccw3/9NNPS/92u9386NGj+VdffTWKUsmH559/np89e3aXzzU0NPCDBg3iN27cKD129OhRfsCAAfy+ffsiJaJsGDBgAL9lyxbp38Gsz2effcbn5ubyVVVV0mvefvttvri4mHc4HJETPkp0XDOe5/mbb76ZX7ZsWcD39PU1q6mp4QcMGMDv2rWL5/nev86IxdEBh8OB7777DqNGjZIeo2kapaWl2LNnTxQlkxfHjh3D6NGjMWnSJCxYsEBqw3zgwAE4nU6/9cvMzITNZiPrh+DWZ8+ePcjJyUFcXJz0mtGjR6OhoQHHjh2LuMxy4YMPPsCIESMwc+ZMPPfcc36n676+Zo2NjQCAmJgYAL1/nV32bdVDpa6uDm63228xAcBsNuP48eNRkkpeFBQUoKysDOnp6aiqqsKf/vQnzJs3Dxs2bEB1dTVUKhV0Op3fe8xmM6qrq6MksXwIZn2qq6thNpv9nhevx+rqamRnZ0dGWBkxc+ZM2Gw2xMfH49ChQ1ixYgXKy8vxxz/+EUDfXjOe51FWVobhw4cjMzMTQO9fZ0RxEEJm3Lhx0s85OTkoLCzEhAkTsGnTJrAsuaQI4ef666+Xfs7OzkZ8fDxuu+02nDp1CklJSVGULPo8/fTTOHLkCNavXx+xzySuqg7ExsaCYZhOp+OamhpYLJYoSSVvDAYD0tLScPz4ccTFxcFut6OpqcnvNTU1NZ2suL5IMOsTFxfXKftFvB7JGgoUFhYCAE6cOAGg767Z7373O2zZsgVr165FQkKC9HhvX2dEcXRAoVBg0KBB2Lp1q/SYx+PBtm3bMHjw4ChKJl+am5tRUVEBi8WCvLw8cBznt37Hjh1DZWUlWT8gqPUZPHgwDh065JfFt3XrVhgMBmRkZERcZjly8OBBAJAOc31tzXiex9NPP41///vfWLt2LVJSUvye7+3rjPgVuuD222/HY489hkGDBqGgoABr166F3W7H7Nmzoy2aLFi+fDkmTJgAm82Gc+fO4YUXXgDDMJg+fTr0ej3mzp2LsrIyGAwG6HQ6/P73v0dxcTHy8/OjLXpEaG5ulk7CAHDy5EkcPHgQcXFxsFgsPa7P6NGjkZmZiQULFmDBggWoqqrCqlWrMG/ePHAcF60/q1fpbs1aW1uxYcMGjBs3DkajEYcPH0ZZWRlGjhyJrKwsAH1vzZYuXYqPPvoIf/7zn6HVaqUR2Xq9HiqVKqj78GLWjEwADMCbb76JNWvWoKqqCrm5uXjyySdRUFAQbbFkwUMPPYQdO3bg/PnzMJlMKC4uxkMPPSSdetra2rBs2TJ8/PHHcDgcGDNmDBYvXnxZuwx8+eabb3Drrbd2evy+++7D/fffH9T6nDp1CkuWLMH27duhVqsxe/Zs/OY3v7lsxx93t2bXXHMNFixYgB9++AEtLS1ITEzElClTMH/+fL/gb19as0CB67KyMsyZMwdAcPfhha4ZURwEAoFACAkS4yAQCARCSBDFQSAQCISQIIqDQCAQCCFBFAeBQCAQQoIoDgKBQCCEBFEcBAKBQAgJojgIBAKBEBJEcRAIBAIhJIjiIBAIBEJI/H/hstBBwWOPDgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "bI9Euwe2MvuO",
"colab_type": "text"
},
"source": [
"## Random forest\n",
"\n",
"Here I used cross validation to estimate if it will be a good idea to use random forest."
]
},
{
"cell_type": "code",
"metadata": {
"id": "iGkVcO5EVkeC",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 224
},
"outputId": "fd992f19-f7fa-489d-ef9c-648c79687a77"
},
"source": [
"model = RandomForestRegressor()\n",
"y = target_profit\n",
"result =-1 * cross_val_score(model, X, y, scoring='neg_mean_absolute_error')\n",
"print(result)"
],
"execution_count": 93,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/sklearn/model_selection/_validation.py:515: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" estimator.fit(X_train, y_train, **fit_params)\n",
"/usr/local/lib/python3.6/dist-packages/sklearn/model_selection/_validation.py:515: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" estimator.fit(X_train, y_train, **fit_params)\n",
"/usr/local/lib/python3.6/dist-packages/sklearn/model_selection/_validation.py:515: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" estimator.fit(X_train, y_train, **fit_params)\n",
"/usr/local/lib/python3.6/dist-packages/sklearn/model_selection/_validation.py:515: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" estimator.fit(X_train, y_train, **fit_params)\n",
"/usr/local/lib/python3.6/dist-packages/sklearn/model_selection/_validation.py:515: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" estimator.fit(X_train, y_train, **fit_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"[0.00022563 0.00021515 0.0001621 0.00122151 0.00034862]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "k6Cld1AmeTp_",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 51
},
"outputId": "6b45d1c3-ddf8-4eae-f5eb-bf100b1f4289"
},
"source": [
"print('Cross validation score', result)\n",
"print('Cross validation mean error', result.mean())"
],
"execution_count": 94,
"outputs": [
{
"output_type": "stream",
"text": [
"Cross validation score [0.00022563 0.00021515 0.0001621 0.00122151 0.00034862]\n",
"Cross validation mean error 0.0004346015344798023\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "s9a8VRK2AU32",
"colab_type": "text"
},
"source": [
"seeing that the error is low, I ran random forest "
]
},
{
"cell_type": "code",
"metadata": {
"id": "jYnQF3TeenvL",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 170
},
"outputId": "ad1096dc-340f-4bf4-bb46-93ae38e9261b"
},
"source": [
"# Without cross validation\n",
"X_train, X_test, y_train, y_test = train_test_split(X,y, test_size=0.3)\n",
"model.fit(X_train, y_train)"
],
"execution_count": 95,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:3: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" This is separate from the ipykernel package so we can avoid doing imports until\n"
],
"name": "stderr"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\n",
" max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
" max_samples=None, min_impurity_decrease=0.0,\n",
" min_impurity_split=None, min_samples_leaf=1,\n",
" min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
" n_estimators=100, n_jobs=None, oob_score=False,\n",
" random_state=None, verbose=0, warm_start=False)"
]
},
"metadata": {
"tags": []
},
"execution_count": 95
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "PODmTvSjolZQ",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "1e8671b6-ebc6-4eab-985d-c1f4c17c75c7"
},
"source": [
"print('score', model.score(X_test, y_test))"
],
"execution_count": 96,
"outputs": [
{
"output_type": "stream",
"text": [
"score 0.9531567715528929\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "cK85dCk-joYM",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 119
},
"outputId": "bc8942ee-95b6-4418-870e-c64b1cabf63d"
},
"source": [
"predicted_profit = model.predict(X_test)\n",
"show_score(predicted_profit, y_test)"
],
"execution_count": 97,
"outputs": [
{
"output_type": "stream",
"text": [
"Regression scores:\n",
"mean_abs_error: 0.00017773827095461645\n",
"mean_sqr_error: 2.7702029557381676e-06\n",
"median_abs_error: 6.755031146749024e-05\n",
"explained_var_score: 0.9531592004066806\n",
"r2__score: 0.9531567715528929\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "2KK9T6R-iCnv",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 286
},
"outputId": "52757afa-dd05-4eaf-dd8c-1923c318931a"
},
"source": [
"# Plot\n",
"predicted_profit = min_max_scaler.inverse_transform(predicted_profit.reshape(-1,1)) / 1e6\n",
"y_test = min_max_scaler.inverse_transform(y_test.reshape(-1,1)) / 1e6\n",
"plt.plot(predicted_profit[:200], c='b', label='Prediction')\n",
"plt.plot(y_test[:200], c='g', label='Actual')\n",
"plt.legend(['Actual', 'Prediction'])\n",
"plt.ylabel('Prediction (In Millions)', fontsize = 14)\n",
"plt.grid()\n",
"plt.show()"
],
"execution_count": 98,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "0__7zuhpkhVc",
"colab_type": "text"
},
"source": [
"#IMDB Rating prediction\n",
"\n",
"## Preprocessing"
]
},
{
"cell_type": "code",
"metadata": {
"id": "5Ikdv4WYqLAg",
"colab_type": "code",
"colab": {}
},
"source": [
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.model_selection import train_test_split, GridSearchCV\n",
"from sklearn.cluster import KMeans\n",
"from sklearn.neighbors import KNeighborsRegressor\n",
"from sklearn import preprocessing\n",
"from sklearn.metrics import mean_absolute_error, mean_squared_error, median_absolute_error, explained_variance_score, r2_score"
],
"execution_count": 99,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "tHLeyCdpDQ5r",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 187
},
"outputId": "741fea2b-4eb6-4b3a-a1b6-deae80ac2cc0"
},
"source": [
"p_df = df.copy()\n",
"p_df = p_df[['duration', 'actor_1_facebook_likes', 'actor_2_facebook_likes', 'actor_3_facebook_likes', 'budget', 'title_year', 'imdb_score', 'language', 'content_rating'] + genre_cols]\n",
"p_df.columns"
],
"execution_count": 100,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['duration', 'actor_1_facebook_likes', 'actor_2_facebook_likes',\n",
" 'actor_3_facebook_likes', 'budget', 'title_year', 'imdb_score',\n",
" 'language', 'content_rating', 'genre_Action', 'genre_Adventure',\n",
" 'genre_Animation', 'genre_Biography', 'genre_Comedy', 'genre_Crime',\n",
" 'genre_Documentary', 'genre_Drama', 'genre_Family', 'genre_Fantasy',\n",
" 'genre_Film-Noir', 'genre_History', 'genre_Horror', 'genre_Music',\n",
" 'genre_Musical', 'genre_Mystery', 'genre_Romance', 'genre_Sci-Fi',\n",
" 'genre_Short', 'genre_Sport', 'genre_Thriller', 'genre_War',\n",
" 'genre_Western'],\n",
" dtype='object')"
]
},
"metadata": {
"tags": []
},
"execution_count": 100
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "EOcZkbvqEf6S",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 258
},
"outputId": "2e58470f-a7c8-4275-c214-5cc1078999eb"
},
"source": [
"def createColumns(p_df, textualColumn, limit=0):\n",
" p_df.dropna(subset=[textualColumn], inplace=True)\n",
" \n",
" # List of columns\n",
" columns = p_df[textualColumn].value_counts().sort_values(ascending=False)\n",
" if (limit != 0):\n",
" columns = columns.head(10)\n",
" columns = sorted(columns.index)\n",
"\n",
" # Append columns\n",
" for g in columns:\n",
" new_col_name = textualColumn + '_' + str(g).lower()\n",
" if new_col_name not in p_df.columns:\n",
" p_df[new_col_name] = 0\n",
"\n",
" # Set data\n",
" drop_indexes = []\n",
" for index,g in zip(df.index, p_df[textualColumn]):\n",
" col_name = textualColumn + '_' + str(g).lower()\n",
" if (col_name not in p_df.columns):\n",
" drop_indexes.append(index)\n",
" else:\n",
" p_df.at[index,col_name] = 1\n",
" \n",
" # Remove limited columns\n",
" p_df = p_df.drop(index=drop_indexes)\n",
" \n",
" # Remove the textual column\n",
" p_df = p_df.drop([textualColumn], axis=1)\n",
"\n",
" return p_df\n",
"\n",
"p_df = createColumns(p_df, 'language', 10)\n",
"p_df = createColumns(p_df, 'content_rating')\n",
"print(p_df.shape)\n",
"p_df.head()"
],
"execution_count": 101,
"outputs": [
{
"output_type": "stream",
"text": [
"(3789, 52)\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>duration</th>\n",
" <th>actor_1_facebook_likes</th>\n",
" <th>actor_2_facebook_likes</th>\n",
" <th>actor_3_facebook_likes</th>\n",
" <th>budget</th>\n",
" <th>title_year</th>\n",
" <th>imdb_score</th>\n",
" <th>genre_Action</th>\n",
" <th>genre_Adventure</th>\n",
" <th>genre_Animation</th>\n",
" <th>genre_Biography</th>\n",
" <th>genre_Comedy</th>\n",
" <th>genre_Crime</th>\n",
" <th>genre_Documentary</th>\n",
" <th>genre_Drama</th>\n",
" <th>genre_Family</th>\n",
" <th>genre_Fantasy</th>\n",
" <th>genre_Film-Noir</th>\n",
" <th>genre_History</th>\n",
" <th>genre_Horror</th>\n",
" <th>genre_Music</th>\n",
" <th>genre_Musical</th>\n",
" <th>genre_Mystery</th>\n",
" <th>genre_Romance</th>\n",
" <th>genre_Sci-Fi</th>\n",
" <th>genre_Short</th>\n",
" <th>genre_Sport</th>\n",
" <th>genre_Thriller</th>\n",
" <th>genre_War</th>\n",
" <th>genre_Western</th>\n",
" <th>language_cantonese</th>\n",
" <th>language_english</th>\n",
" <th>language_french</th>\n",
" <th>language_german</th>\n",
" <th>language_hindi</th>\n",
" <th>language_italian</th>\n",
" <th>language_japanese</th>\n",
" <th>language_korean</th>\n",
" <th>language_mandarin</th>\n",
" <th>language_spanish</th>\n",
" <th>content_rating_approved</th>\n",
" <th>content_rating_g</th>\n",
" <th>content_rating_gp</th>\n",
" <th>content_rating_m</th>\n",
" <th>content_rating_nc-17</th>\n",
" <th>content_rating_not rated</th>\n",
" <th>content_rating_pg</th>\n",
" <th>content_rating_pg-13</th>\n",
" <th>content_rating_passed</th>\n",
" <th>content_rating_r</th>\n",
" <th>content_rating_unrated</th>\n",
" <th>content_rating_x</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>178.0</td>\n",
" <td>1000.0</td>\n",
" <td>936.0</td>\n",
" <td>855.0</td>\n",
" <td>237000000.0</td>\n",
" <td>2009.0</td>\n",
" <td>7.9</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>169.0</td>\n",
" <td>40000.0</td>\n",
" <td>5000.0</td>\n",
" <td>1000.0</td>\n",
" <td>300000000.0</td>\n",
" <td>2007.0</td>\n",
" <td>7.1</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>148.0</td>\n",
" <td>11000.0</td>\n",
" <td>393.0</td>\n",
" <td>161.0</td>\n",
" <td>245000000.0</td>\n",
" <td>2015.0</td>\n",
" <td>6.8</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>164.0</td>\n",
" <td>27000.0</td>\n",
" <td>23000.0</td>\n",
" <td>23000.0</td>\n",
" <td>250000000.0</td>\n",
" <td>2012.0</td>\n",
" <td>8.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>132.0</td>\n",
" <td>640.0</td>\n",
" <td>632.0</td>\n",
" <td>530.0</td>\n",
" <td>263700000.0</td>\n",
" <td>2012.0</td>\n",
" <td>6.6</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" duration actor_1_facebook_likes ... content_rating_unrated content_rating_x\n",
"0 178.0 1000.0 ... 0.0 0.0\n",
"1 169.0 40000.0 ... 0.0 0.0\n",
"2 148.0 11000.0 ... 0.0 0.0\n",
"3 164.0 27000.0 ... 0.0 0.0\n",
"5 132.0 640.0 ... 0.0 0.0\n",
"\n",
"[5 rows x 52 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 101
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "1ET_Cii6H1j0",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 241
},
"outputId": "e8545ed1-0b72-4b76-d6c8-ac89b047546f"
},
"source": [
"# Normalization\n",
"for i in p_df:\n",
" p_df[i] = p_df[i].map(lambda x: np.log1p(x)) \n",
"p_df.head()"
],
"execution_count": 102,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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" vertical-align: top;\n",
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" text-align: right;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>duration</th>\n",
" <th>actor_1_facebook_likes</th>\n",
" <th>actor_2_facebook_likes</th>\n",
" <th>actor_3_facebook_likes</th>\n",
" <th>budget</th>\n",
" <th>title_year</th>\n",
" <th>imdb_score</th>\n",
" <th>genre_Action</th>\n",
" <th>genre_Adventure</th>\n",
" <th>genre_Animation</th>\n",
" <th>genre_Biography</th>\n",
" <th>genre_Comedy</th>\n",
" <th>genre_Crime</th>\n",
" <th>genre_Documentary</th>\n",
" <th>genre_Drama</th>\n",
" <th>genre_Family</th>\n",
" <th>genre_Fantasy</th>\n",
" <th>genre_Film-Noir</th>\n",
" <th>genre_History</th>\n",
" <th>genre_Horror</th>\n",
" <th>genre_Music</th>\n",
" <th>genre_Musical</th>\n",
" <th>genre_Mystery</th>\n",
" <th>genre_Romance</th>\n",
" <th>genre_Sci-Fi</th>\n",
" <th>genre_Short</th>\n",
" <th>genre_Sport</th>\n",
" <th>genre_Thriller</th>\n",
" <th>genre_War</th>\n",
" <th>genre_Western</th>\n",
" <th>language_cantonese</th>\n",
" <th>language_english</th>\n",
" <th>language_french</th>\n",
" <th>language_german</th>\n",
" <th>language_hindi</th>\n",
" <th>language_italian</th>\n",
" <th>language_japanese</th>\n",
" <th>language_korean</th>\n",
" <th>language_mandarin</th>\n",
" <th>language_spanish</th>\n",
" <th>content_rating_approved</th>\n",
" <th>content_rating_g</th>\n",
" <th>content_rating_gp</th>\n",
" <th>content_rating_m</th>\n",
" <th>content_rating_nc-17</th>\n",
" <th>content_rating_not rated</th>\n",
" <th>content_rating_pg</th>\n",
" <th>content_rating_pg-13</th>\n",
" <th>content_rating_passed</th>\n",
" <th>content_rating_r</th>\n",
" <th>content_rating_unrated</th>\n",
" <th>content_rating_x</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>5.187386</td>\n",
" <td>6.908755</td>\n",
" <td>6.842683</td>\n",
" <td>6.752270</td>\n",
" <td>19.283571</td>\n",
" <td>7.605890</td>\n",
" <td>2.186051</td>\n",
" <td>0.693147</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
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" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>5.135798</td>\n",
" <td>10.596660</td>\n",
" <td>8.517393</td>\n",
" <td>6.908755</td>\n",
" <td>19.519293</td>\n",
" <td>7.604894</td>\n",
" <td>2.091864</td>\n",
" <td>0.693147</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5.003946</td>\n",
" <td>9.305741</td>\n",
" <td>5.976351</td>\n",
" <td>5.087596</td>\n",
" <td>19.316769</td>\n",
" <td>7.608871</td>\n",
" <td>2.054124</td>\n",
" <td>0.693147</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>5.105945</td>\n",
" <td>10.203629</td>\n",
" <td>10.043293</td>\n",
" <td>10.043293</td>\n",
" <td>19.336971</td>\n",
" <td>7.607381</td>\n",
" <td>2.251292</td>\n",
" <td>0.693147</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>4.890349</td>\n",
" <td>6.463029</td>\n",
" <td>6.450470</td>\n",
" <td>6.274762</td>\n",
" <td>19.390323</td>\n",
" <td>7.607381</td>\n",
" <td>2.028148</td>\n",
" <td>0.693147</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.693147</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" duration actor_1_facebook_likes ... content_rating_unrated content_rating_x\n",
"0 5.187386 6.908755 ... 0.0 0.0\n",
"1 5.135798 10.596660 ... 0.0 0.0\n",
"2 5.003946 9.305741 ... 0.0 0.0\n",
"3 5.105945 10.203629 ... 0.0 0.0\n",
"5 4.890349 6.463029 ... 0.0 0.0\n",
"\n",
"[5 rows x 52 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 102
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "TLQ1FW3yW8TG",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "7ad2e17a-ec58-4a89-c391-ef6fab078a3c"
},
"source": [
"# Data filling - for all missing values set the median\n",
"for i in p_df:\n",
" median = p_df[i].median()\n",
" p_df[i] = p_df[i].fillna(median)\n",
"p_df.isnull().values.any() "
],
"execution_count": 103,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"False"
]
},
"metadata": {
"tags": []
},
"execution_count": 103
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "Ool1BvqwVUH6",
"colab_type": "code",
"colab": {}
},
"source": [
"# Scaling\n",
"X = StandardScaler().fit_transform(p_df.drop(columns=['imdb_score']))\n",
"target_profit = p_df['imdb_score']"
],
"execution_count": 104,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "_avwdlNQUglk",
"colab_type": "text"
},
"source": [
"## train-test splitting"
]
},
{
"cell_type": "code",
"metadata": {
"id": "fm4PgfOyt4r0",
"colab_type": "code",
"colab": {}
},
"source": [
"X_train, X_test, y_train, y_test = train_test_split(X, target_profit, test_size=0.3)"
],
"execution_count": 105,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "V7p9e4iwC2MV",
"colab_type": "text"
},
"source": [
"##K Nearest neighbors\n",
"\n",
"The idea behind KNN is simple:\n",
"keep the entire set in memory.\n",
"When a prediction for X is required, calculate the distance from X to any other datum, and predict using the prediction of the K nearest neighbors."
]
},
{
"cell_type": "code",
"metadata": {
"id": "gtt5wTDPC5eP",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 187
},
"outputId": "73d35f9b-b35b-446d-ba86-04c2f2a5840b"
},
"source": [
"knn = KNeighborsRegressor()\n",
"params = { 'n_neighbors':np.arange(5,15), }\n",
"knn_grid = GridSearchCV(knn, params, cv=5, scoring='neg_mean_squared_error')\n",
"knn_grid.fit(X_train, y_train)"
],
"execution_count": 49,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"GridSearchCV(cv=5, error_score=nan,\n",
" estimator=KNeighborsRegressor(algorithm='auto', leaf_size=30,\n",
" metric='minkowski',\n",
" metric_params=None, n_jobs=None,\n",
" n_neighbors=5, p=2,\n",
" weights='uniform'),\n",
" iid='deprecated', n_jobs=None,\n",
" param_grid={'n_neighbors': array([ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])},\n",
" pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n",
" scoring='neg_mean_squared_error', verbose=0)"
]
},
"metadata": {
"tags": []
},
"execution_count": 49
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ILQ4va69cUTX",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "d20931d5-e865-49ae-89ec-1da95417604f"
},
"source": [
"knn_grid.best_params_"
],
"execution_count": 50,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'n_neighbors': 12}"
]
},
"metadata": {
"tags": []
},
"execution_count": 50
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "zg8Z6kExcbMa",
"colab_type": "code",
"colab": {}
},
"source": [
"knn = KNeighborsRegressor(12)\n",
"knn_model = knn.fit(X_train, y_train)"
],
"execution_count": 51,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "6YaDRkZtc2Rw",
"colab_type": "code",
"colab": {}
},
"source": [
"prediction = knn_model.predict(X_test)"
],
"execution_count": 52,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "jklpuAJdcmbh",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 119
},
"outputId": "eb152241-f977-4085-90ee-7c19cfda3789"
},
"source": [
"show_score(prediction, y_test)"
],
"execution_count": 53,
"outputs": [
{
"output_type": "stream",
"text": [
"Regression scores:\n",
"mean_abs_error: 0.09863457289840259\n",
"mean_sqr_error: 0.018422394903156513\n",
"median_abs_error: 0.07598590697792185\n",
"explained_var_score: 0.183171342672945\n",
"r2__score: 0.1817818457697924\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "44eC-AhUqAv9",
"colab_type": "text"
},
"source": [
"#K-means\n",
"\n",
"The idea behind K-means is clustering based on partition of the space into K Voronoi-cells, each cell minimizes its within cluster variance."
]
},
{
"cell_type": "code",
"metadata": {
"id": "pMpc3tlDp_Mt",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 170
},
"outputId": "8aa5ffbf-a3ed-4bc2-8bfb-95f3b23a4887"
},
"source": [
"kmeans = KMeans()\n",
"kmeans_grid = GridSearchCV(KMeans(), {'n_clusters': np.arange(3,15)}, scoring='neg_mean_squared_error')\n",
"kmeans_grid.fit(X_train, y_train)"
],
"execution_count": 54,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"GridSearchCV(cv=None, error_score=nan,\n",
" estimator=KMeans(algorithm='auto', copy_x=True, init='k-means++',\n",
" max_iter=300, n_clusters=8, n_init=10,\n",
" n_jobs=None, precompute_distances='auto',\n",
" random_state=None, tol=0.0001, verbose=0),\n",
" iid='deprecated', n_jobs=None,\n",
" param_grid={'n_clusters': array([ 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])},\n",
" pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n",
" scoring='neg_mean_squared_error', verbose=0)"
]
},
"metadata": {
"tags": []
},
"execution_count": 54
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "QyaZ9MP7eJbb",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "f28313d9-ff7b-41e1-f1b9-525df753120d"
},
"source": [
"kmeans_grid.best_params_"
],
"execution_count": 55,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'n_clusters': 4}"
]
},
"metadata": {
"tags": []
},
"execution_count": 55
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "S3T9aiEtt3FL",
"colab_type": "code",
"colab": {}
},
"source": [
"model = KMeans(n_clusters=4).fit(X_train, y_train)"
],
"execution_count": 56,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "ymJrnfd6wHZw",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 136
},
"outputId": "2930fdf5-2d6e-4139-c223-ec6b68cf6ba2"
},
"source": [
"print('score', - model.score(X_test, y_test))\n",
"show_score(model.predict(X_test), y_test)"
],
"execution_count": 57,
"outputs": [
{
"output_type": "stream",
"text": [
"score 53083.36007936136\n",
"Regression scores:\n",
"mean_abs_error: 1.1694799333304542\n",
"mean_sqr_error: 2.146602239733493\n",
"median_abs_error: 1.174751721484161\n",
"explained_var_score: -44.965180393834856\n",
"r2__score: -94.33988016727548\n"
],
"name": "stdout"
}
]
}
]
}
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