{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"text-align:center\">\n",
    "    <a href=\"https://skills.network\" target=\"_blank\">\n",
    "    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/assets/logos/SN_web_lightmode.png\" width=\"200\" alt=\"Skills Network Logo\"  />\n",
    "    </a>\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Lab: Exploratory Data Analysis**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estimated time needed: **30** minutes\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this lab, you will work with a cleaned dataset to perform Exploratory Data Analysis or EDA. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Objectives\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this lab, you will perform the following:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Examine the structure of a dataset.\n",
    "\n",
    "- Handle missing values effectively.\n",
    "\n",
    "- Conduct summary statistics on key columns.\n",
    "\n",
    "- Analyze employment status, job satisfaction, programming language usage, and trends in remote work.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hands on Lab\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 1: Install and Import Libraries\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Install the necessary libraries for data manipulation and visualization.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in /opt/conda/lib/python3.12/site-packages (3.0.0)\n",
      "Requirement already satisfied: numpy>=1.26.0 in /opt/conda/lib/python3.12/site-packages (from pandas) (2.4.1)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in /opt/conda/lib/python3.12/site-packages (from pandas) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n",
      "Requirement already satisfied: matplotlib in /opt/conda/lib/python3.12/site-packages (3.10.8)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (1.3.3)\n",
      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (4.61.1)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (1.4.9)\n",
      "Requirement already satisfied: numpy>=1.23 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (2.4.1)\n",
      "Requirement already satisfied: packaging>=20.0 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (24.2)\n",
      "Requirement already satisfied: pillow>=8 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (12.1.0)\n",
      "Requirement already satisfied: pyparsing>=3 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (3.3.2)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib) (1.17.0)\n",
      "Requirement already satisfied: seaborn in /opt/conda/lib/python3.12/site-packages (0.13.2)\n",
      "Requirement already satisfied: numpy!=1.24.0,>=1.20 in /opt/conda/lib/python3.12/site-packages (from seaborn) (2.4.1)\n",
      "Requirement already satisfied: pandas>=1.2 in /opt/conda/lib/python3.12/site-packages (from seaborn) (3.0.0)\n",
      "Requirement already satisfied: matplotlib!=3.6.1,>=3.4 in /opt/conda/lib/python3.12/site-packages (from seaborn) (3.10.8)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.3.3)\n",
      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (4.61.1)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.4.9)\n",
      "Requirement already satisfied: packaging>=20.0 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (24.2)\n",
      "Requirement already satisfied: pillow>=8 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (12.1.0)\n",
      "Requirement already satisfied: pyparsing>=3 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (3.3.2)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib!=3.6.1,>=3.4->seaborn) (1.17.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install pandas\n",
    "!pip install matplotlib\n",
    "!pip install seaborn\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import textwrap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 2: Load and Preview the Dataset\n",
    "Load the dataset from the provided URL. Use df.head() to display the first few rows to get an overview of the structure.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   ResponseId                      MainBranch                 Age  \\\n",
      "0           1  I am a developer by profession  Under 18 years old   \n",
      "1           2  I am a developer by profession     35-44 years old   \n",
      "2           3  I am a developer by profession     45-54 years old   \n",
      "3           4           I am learning to code     18-24 years old   \n",
      "4           5  I am a developer by profession     18-24 years old   \n",
      "\n",
      "            Employment RemoteWork   Check  \\\n",
      "0  Employed, full-time     Remote  Apples   \n",
      "1  Employed, full-time     Remote  Apples   \n",
      "2  Employed, full-time     Remote  Apples   \n",
      "3   Student, full-time        NaN  Apples   \n",
      "4   Student, full-time        NaN  Apples   \n",
      "\n",
      "                                    CodingActivities  \\\n",
      "0                                              Hobby   \n",
      "1  Hobby;Contribute to open-source projects;Other...   \n",
      "2  Hobby;Contribute to open-source projects;Other...   \n",
      "3                                                NaN   \n",
      "4                                                NaN   \n",
      "\n",
      "                                             EdLevel  \\\n",
      "0                          Primary/elementary school   \n",
      "1       Bachelor’s degree (B.A., B.S., B.Eng., etc.)   \n",
      "2    Master’s degree (M.A., M.S., M.Eng., MBA, etc.)   \n",
      "3  Some college/university study without earning ...   \n",
      "4  Secondary school (e.g. American high school, G...   \n",
      "\n",
      "                                           LearnCode  \\\n",
      "0                             Books / Physical media   \n",
      "1  Books / Physical media;Colleague;On the job tr...   \n",
      "2  Books / Physical media;Colleague;On the job tr...   \n",
      "3  Other online resources (e.g., videos, blogs, f...   \n",
      "4  Other online resources (e.g., videos, blogs, f...   \n",
      "\n",
      "                                     LearnCodeOnline  \\\n",
      "0                                                NaN   \n",
      "1  Technical documentation;Blogs;Books;Written Tu...   \n",
      "2  Technical documentation;Blogs;Books;Written Tu...   \n",
      "3  Stack Overflow;How-to videos;Interactive tutorial   \n",
      "4  Technical documentation;Blogs;Written Tutorial...   \n",
      "\n",
      "                                             TechDoc YearsCode YearsCodePro  \\\n",
      "0                                                NaN       NaN          NaN   \n",
      "1  API document(s) and/or SDK document(s);User gu...        20           17   \n",
      "2  API document(s) and/or SDK document(s);User gu...        37           27   \n",
      "3                                                NaN         4          NaN   \n",
      "4  API document(s) and/or SDK document(s);User gu...         9          NaN   \n",
      "\n",
      "                 DevType OrgSize PurchaseInfluence BuyNewTool BuildvsBuy  \\\n",
      "0                    NaN     NaN               NaN        NaN        NaN   \n",
      "1  Developer, full-stack     NaN               NaN        NaN        NaN   \n",
      "2   Developer Experience     NaN               NaN        NaN        NaN   \n",
      "3  Developer, full-stack     NaN               NaN        NaN        NaN   \n",
      "4  Developer, full-stack     NaN               NaN        NaN        NaN   \n",
      "\n",
      "  TechEndorse                                            Country Currency  \\\n",
      "0         NaN                           United States of America      NaN   \n",
      "1         NaN  United Kingdom of Great Britain and Northern I...      NaN   \n",
      "2         NaN  United Kingdom of Great Britain and Northern I...      NaN   \n",
      "3         NaN                                             Canada      NaN   \n",
      "4         NaN                                             Norway      NaN   \n",
      "\n",
      "   CompTotal                             LanguageHaveWorkedWith  \\\n",
      "0        NaN                                                NaN   \n",
      "1        NaN  Bash/Shell (all shells);Go;HTML/CSS;Java;JavaS...   \n",
      "2        NaN                                                 C#   \n",
      "3        NaN  C;C++;HTML/CSS;Java;JavaScript;PHP;PowerShell;...   \n",
      "4        NaN            C++;HTML/CSS;JavaScript;Lua;Python;Rust   \n",
      "\n",
      "                              LanguageWantToWorkWith  \\\n",
      "0                                                NaN   \n",
      "1  Bash/Shell (all shells);Go;HTML/CSS;Java;JavaS...   \n",
      "2                                                 C#   \n",
      "3  HTML/CSS;Java;JavaScript;PowerShell;Python;SQL...   \n",
      "4                 C++;HTML/CSS;JavaScript;Lua;Python   \n",
      "\n",
      "                                     LanguageAdmired  \\\n",
      "0                                                NaN   \n",
      "1  Bash/Shell (all shells);Go;HTML/CSS;Java;JavaS...   \n",
      "2                                                 C#   \n",
      "3  HTML/CSS;Java;JavaScript;PowerShell;Python;SQL...   \n",
      "4                 C++;HTML/CSS;JavaScript;Lua;Python   \n",
      "\n",
      "            DatabaseHaveWorkedWith      DatabaseWantToWorkWith  \\\n",
      "0                              NaN                         NaN   \n",
      "1      Dynamodb;MongoDB;PostgreSQL                  PostgreSQL   \n",
      "2       Firebase Realtime Database  Firebase Realtime Database   \n",
      "3  MongoDB;MySQL;PostgreSQL;SQLite    MongoDB;MySQL;PostgreSQL   \n",
      "4                PostgreSQL;SQLite           PostgreSQL;SQLite   \n",
      "\n",
      "              DatabaseAdmired                    PlatformHaveWorkedWith  \\\n",
      "0                         NaN                                       NaN   \n",
      "1                  PostgreSQL  Amazon Web Services (AWS);Heroku;Netlify   \n",
      "2  Firebase Realtime Database                              Google Cloud   \n",
      "3    MongoDB;MySQL;PostgreSQL   Amazon Web Services (AWS);Fly.io;Heroku   \n",
      "4           PostgreSQL;SQLite                                       NaN   \n",
      "\n",
      "                     PlatformWantToWorkWith  \\\n",
      "0                                       NaN   \n",
      "1  Amazon Web Services (AWS);Heroku;Netlify   \n",
      "2                              Google Cloud   \n",
      "3          Amazon Web Services (AWS);Vercel   \n",
      "4                                       NaN   \n",
      "\n",
      "                            PlatformAdmired  \\\n",
      "0                                       NaN   \n",
      "1  Amazon Web Services (AWS);Heroku;Netlify   \n",
      "2                              Google Cloud   \n",
      "3                 Amazon Web Services (AWS)   \n",
      "4                                       NaN   \n",
      "\n",
      "                   WebframeHaveWorkedWith            WebframeWantToWorkWith  \\\n",
      "0                                     NaN                               NaN   \n",
      "1           Express;Next.js;Node.js;React  Express;Htmx;Node.js;React;Remix   \n",
      "2                            ASP.NET CORE                      ASP.NET CORE   \n",
      "3  jQuery;Next.js;Node.js;React;WordPress      jQuery;Next.js;Node.js;React   \n",
      "4                                     NaN                               NaN   \n",
      "\n",
      "                WebframeAdmired   EmbeddedHaveWorkedWith  \\\n",
      "0                           NaN                      NaN   \n",
      "1         Express;Node.js;React                      NaN   \n",
      "2                  ASP.NET CORE              Rasberry Pi   \n",
      "3  jQuery;Next.js;Node.js;React              Rasberry Pi   \n",
      "4                           NaN  CMake;Cargo;Rasberry Pi   \n",
      "\n",
      "  EmbeddedWantToWorkWith    EmbeddedAdmired  \\\n",
      "0                    NaN                NaN   \n",
      "1                    NaN                NaN   \n",
      "2            Rasberry Pi        Rasberry Pi   \n",
      "3                    NaN                NaN   \n",
      "4      CMake;Rasberry Pi  CMake;Rasberry Pi   \n",
      "\n",
      "                            MiscTechHaveWorkedWith  \\\n",
      "0                                              NaN   \n",
      "1                                              NaN   \n",
      "2  .NET (5+) ;.NET Framework (1.0 - 4.8);.NET MAUI   \n",
      "3                     NumPy;Pandas;Ruff;TensorFlow   \n",
      "4                                              NaN   \n",
      "\n",
      "                            MiscTechWantToWorkWith  \\\n",
      "0                                              NaN   \n",
      "1                                              NaN   \n",
      "2  .NET (5+) ;.NET Framework (1.0 - 4.8);.NET MAUI   \n",
      "3                                              NaN   \n",
      "4                                              NaN   \n",
      "\n",
      "                                   MiscTechAdmired  \\\n",
      "0                                              NaN   \n",
      "1                                              NaN   \n",
      "2  .NET (5+) ;.NET Framework (1.0 - 4.8);.NET MAUI   \n",
      "3                                              NaN   \n",
      "4                                              NaN   \n",
      "\n",
      "                       ToolsTechHaveWorkedWith  \\\n",
      "0                                          NaN   \n",
      "1  Docker;Homebrew;Kubernetes;npm;Vite;Webpack   \n",
      "2                                      MSBuild   \n",
      "3                               Docker;npm;Pip   \n",
      "4                                 APT;Make;npm   \n",
      "\n",
      "                       ToolsTechWantToWorkWith  \\\n",
      "0                                          NaN   \n",
      "1  Docker;Homebrew;Kubernetes;npm;Vite;Webpack   \n",
      "2                                      MSBuild   \n",
      "3                        Docker;Kubernetes;npm   \n",
      "4                                     APT;Make   \n",
      "\n",
      "                              ToolsTechAdmired  \\\n",
      "0                                          NaN   \n",
      "1  Docker;Homebrew;Kubernetes;npm;Vite;Webpack   \n",
      "2                                      MSBuild   \n",
      "3                                   Docker;npm   \n",
      "4                                     APT;Make   \n",
      "\n",
      "          NEWCollabToolsHaveWorkedWith         NEWCollabToolsWantToWorkWith  \\\n",
      "0                                  NaN                                  NaN   \n",
      "1  PyCharm;Visual Studio Code;WebStorm  PyCharm;Visual Studio Code;WebStorm   \n",
      "2                        Visual Studio                        Visual Studio   \n",
      "3                                  NaN                                  NaN   \n",
      "4                                  Vim                                  Vim   \n",
      "\n",
      "                 NEWCollabToolsAdmired        OpSysPersonal use  \\\n",
      "0                                  NaN                      NaN   \n",
      "1  PyCharm;Visual Studio Code;WebStorm            MacOS;Windows   \n",
      "2                        Visual Studio                  Windows   \n",
      "3                                  NaN                      NaN   \n",
      "4                                  Vim  Other (please specify):   \n",
      "\n",
      "  OpSysProfessional use                     OfficeStackAsyncHaveWorkedWith  \\\n",
      "0                   NaN                                                NaN   \n",
      "1                 MacOS                                                NaN   \n",
      "2               Windows                                                NaN   \n",
      "3                   NaN                                                NaN   \n",
      "4                   NaN  GitHub Discussions;Markdown File;Obsidian;Stac...   \n",
      "\n",
      "              OfficeStackAsyncWantToWorkWith  \\\n",
      "0                                        NaN   \n",
      "1                                        NaN   \n",
      "2                                        NaN   \n",
      "3                                        NaN   \n",
      "4  GitHub Discussions;Markdown File;Obsidian   \n",
      "\n",
      "                     OfficeStackAsyncAdmired  \\\n",
      "0                                        NaN   \n",
      "1                                        NaN   \n",
      "2                                        NaN   \n",
      "3                                        NaN   \n",
      "4  GitHub Discussions;Markdown File;Obsidian   \n",
      "\n",
      "                  OfficeStackSyncHaveWorkedWith OfficeStackSyncWantToWorkWith  \\\n",
      "0                                           NaN                           NaN   \n",
      "1                         Microsoft Teams;Slack                         Slack   \n",
      "2  Google Chat;Google Meet;Microsoft Teams;Zoom  Google Chat;Google Meet;Zoom   \n",
      "3                                           NaN                           NaN   \n",
      "4                              Discord;Whatsapp              Discord;Whatsapp   \n",
      "\n",
      "         OfficeStackSyncAdmired AISearchDevHaveWorkedWith  \\\n",
      "0                           NaN                       NaN   \n",
      "1                         Slack                       NaN   \n",
      "2  Google Chat;Google Meet;Zoom                       NaN   \n",
      "3                           NaN                       NaN   \n",
      "4              Discord;Whatsapp                       NaN   \n",
      "\n",
      "  AISearchDevWantToWorkWith AISearchDevAdmired  \\\n",
      "0                       NaN                NaN   \n",
      "1                       NaN                NaN   \n",
      "2                       NaN                NaN   \n",
      "3                       NaN                NaN   \n",
      "4                       NaN                NaN   \n",
      "\n",
      "                                          NEWSOSites             SOVisitFreq  \\\n",
      "0  I have never visited Stack Overflow or the Sta...                     NaN   \n",
      "1  Stack Overflow for Teams (private knowledge sh...  Multiple times per day   \n",
      "2  Stack Overflow;Stack Exchange;Stack Overflow B...  Multiple times per day   \n",
      "3                                     Stack Overflow   Daily or almost daily   \n",
      "4  Stack Overflow for Teams (private knowledge sh...  Multiple times per day   \n",
      "\n",
      "  SOAccount              SOPartFreq  \\\n",
      "0       NaN                     NaN   \n",
      "1       Yes  Multiple times per day   \n",
      "2       Yes  Multiple times per day   \n",
      "3        No                     NaN   \n",
      "4       Yes  Multiple times per day   \n",
      "\n",
      "                                               SOHow           SOComm  \\\n",
      "0                                                NaN              NaN   \n",
      "1  Quickly finding code solutions;Finding reliabl...  Yes, definitely   \n",
      "2  Quickly finding code solutions;Finding reliabl...  Yes, definitely   \n",
      "3                     Quickly finding code solutions   No, not really   \n",
      "4  Quickly finding code solutions;Engage with com...  Yes, definitely   \n",
      "\n",
      "                  AISelect          AISent  \\\n",
      "0                      Yes  Very favorable   \n",
      "1  No, and I don't plan to             NaN   \n",
      "2  No, and I don't plan to             NaN   \n",
      "3                      Yes  Very favorable   \n",
      "4  No, and I don't plan to             NaN   \n",
      "\n",
      "                                               AIBen           AIAcc  \\\n",
      "0                              Increase productivity             NaN   \n",
      "1                                                NaN             NaN   \n",
      "2                                                NaN             NaN   \n",
      "3  Increase productivity;Greater efficiency;Impro...  Somewhat trust   \n",
      "4                                                NaN             NaN   \n",
      "\n",
      "                       AIComplex  \\\n",
      "0                            NaN   \n",
      "1                            NaN   \n",
      "2                            NaN   \n",
      "3  Bad at handling complex tasks   \n",
      "4                            NaN   \n",
      "\n",
      "                               AIToolCurrently Using  \\\n",
      "0                                                NaN   \n",
      "1                                                NaN   \n",
      "2                                                NaN   \n",
      "3  Learning about a codebase;Project planning;Wri...   \n",
      "4                                                NaN   \n",
      "\n",
      "                           AIToolInterested in Using  \\\n",
      "0                                                NaN   \n",
      "1                                                NaN   \n",
      "2                                                NaN   \n",
      "3  Testing code;Committing and reviewing code;Pre...   \n",
      "4                                                NaN   \n",
      "\n",
      "  AIToolNot interested in Using  \\\n",
      "0                           NaN   \n",
      "1                           NaN   \n",
      "2                           NaN   \n",
      "3                           NaN   \n",
      "4                           NaN   \n",
      "\n",
      "                          AINextMuch more integrated AINextNo change  \\\n",
      "0                                                NaN             NaN   \n",
      "1                                                NaN             NaN   \n",
      "2                                                NaN             NaN   \n",
      "3  Learning about a codebase;Project planning;Wri...             NaN   \n",
      "4                                                NaN             NaN   \n",
      "\n",
      "  AINextMore integrated AINextLess integrated AINextMuch less integrated  \\\n",
      "0                   NaN                   NaN                        NaN   \n",
      "1                   NaN                   NaN                        NaN   \n",
      "2                   NaN                   NaN                        NaN   \n",
      "3                   NaN                   NaN                        NaN   \n",
      "4                   NaN                   NaN                        NaN   \n",
      "\n",
      "  AIThreat                                           AIEthics  \\\n",
      "0      NaN                                                NaN   \n",
      "1      NaN                                                NaN   \n",
      "2      NaN                                                NaN   \n",
      "3       No  Circulating misinformation or disinformation;M...   \n",
      "4      NaN                                                NaN   \n",
      "\n",
      "                        AIChallenges TBranch                  ICorPM  WorkExp  \\\n",
      "0                                NaN      No                     NaN      NaN   \n",
      "1                                NaN     Yes  Individual contributor     17.0   \n",
      "2                                NaN      No                     NaN      NaN   \n",
      "3  Don’t trust the output or answers     NaN                     NaN      NaN   \n",
      "4                                NaN     NaN                     NaN      NaN   \n",
      "\n",
      "  Knowledge_1 Knowledge_2 Knowledge_3 Knowledge_4 Knowledge_5  \\\n",
      "0         NaN         NaN         NaN         NaN         NaN   \n",
      "1       Agree    Disagree       Agree       Agree       Agree   \n",
      "2         NaN         NaN         NaN         NaN         NaN   \n",
      "3         NaN         NaN         NaN         NaN         NaN   \n",
      "4         NaN         NaN         NaN         NaN         NaN   \n",
      "\n",
      "                  Knowledge_6 Knowledge_7 Knowledge_8 Knowledge_9 Frequency_1  \\\n",
      "0                         NaN         NaN         NaN         NaN         NaN   \n",
      "1  Neither agree nor disagree    Disagree       Agree       Agree         NaN   \n",
      "2                         NaN         NaN         NaN         NaN         NaN   \n",
      "3                         NaN         NaN         NaN         NaN         NaN   \n",
      "4                         NaN         NaN         NaN         NaN         NaN   \n",
      "\n",
      "  Frequency_2 Frequency_3 TimeSearching TimeAnswering Frustration  \\\n",
      "0         NaN         NaN           NaN           NaN         NaN   \n",
      "1         NaN         NaN           NaN           NaN         NaN   \n",
      "2         NaN         NaN           NaN           NaN         NaN   \n",
      "3         NaN         NaN           NaN           NaN         NaN   \n",
      "4         NaN         NaN           NaN           NaN         NaN   \n",
      "\n",
      "  ProfessionalTech ProfessionalCloud ProfessionalQuestion Industry  \\\n",
      "0              NaN               NaN                  NaN      NaN   \n",
      "1              NaN               NaN                  NaN      NaN   \n",
      "2              NaN               NaN                  NaN      NaN   \n",
      "3              NaN               NaN                  NaN      NaN   \n",
      "4              NaN               NaN                  NaN      NaN   \n",
      "\n",
      "   JobSatPoints_1  JobSatPoints_4  JobSatPoints_5  JobSatPoints_6  \\\n",
      "0             NaN             NaN             NaN             NaN   \n",
      "1             0.0             0.0             0.0             0.0   \n",
      "2             NaN             NaN             NaN             NaN   \n",
      "3             NaN             NaN             NaN             NaN   \n",
      "4             NaN             NaN             NaN             NaN   \n",
      "\n",
      "   JobSatPoints_7  JobSatPoints_8  JobSatPoints_9  JobSatPoints_10  \\\n",
      "0             NaN             NaN             NaN              NaN   \n",
      "1             0.0             0.0             0.0              0.0   \n",
      "2             NaN             NaN             NaN              NaN   \n",
      "3             NaN             NaN             NaN              NaN   \n",
      "4             NaN             NaN             NaN              NaN   \n",
      "\n",
      "   JobSatPoints_11           SurveyLength SurveyEase  ConvertedCompYearly  \\\n",
      "0              NaN                    NaN        NaN                  NaN   \n",
      "1              0.0                    NaN        NaN                  NaN   \n",
      "2              NaN  Appropriate in length       Easy                  NaN   \n",
      "3              NaN               Too long       Easy                  NaN   \n",
      "4              NaN              Too short       Easy                  NaN   \n",
      "\n",
      "   JobSat  \n",
      "0     NaN  \n",
      "1     NaN  \n",
      "2     NaN  \n",
      "3     NaN  \n",
      "4     NaN  \n",
      "Initial dataframe: (65437, 114)\n"
     ]
    }
   ],
   "source": [
    "# Load the Stack Overflow survey dataset\n",
    "data_url = 'https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/n01PQ9pSmiRX6520flujwQ/survey-data.csv'\n",
    "df = pd.read_csv(data_url)\n",
    "\n",
    "# Set pandas option to display all columns\n",
    "pd.set_option('display.max_columns', None)\n",
    "\n",
    "# Display the first few rows of the dataset\n",
    "print(df.head())\n",
    "print('Initial dataframe:', df.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 3: Handling Missing Data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Identify and manage missing values in critical columns such as `Employment`, `JobSat`, and `RemoteWork`. Implement a strategy to fill or drop these values, depending on the significance of the missing data.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fraction of missing values in each column\n",
      "EdLevel                   0.0711\n",
      "Employment                0.0000\n",
      "JobSat                    0.5549\n",
      "JobSatPoints_1            0.5519\n",
      "LanguageHaveWorkedWith    0.0870\n",
      "RemoteWork                0.1625\n",
      "YearsCodePro              0.2113\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "## Write your code here\n",
    "frnan = df.isna().mean().sort_values(ascending=False).round(decimals=4)\n",
    "print('Fraction of missing values in each column')\n",
    "columns = ['Employment', 'JobSat', 'RemoteWork', 'YearsCodePro', 'LanguageHaveWorkedWith', 'JobSatPoints_1', 'EdLevel']\n",
    "print(frnan[columns].sort_index())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.DataFrame'>\n",
      "RangeIndex: 65437 entries, 0 to 65436\n",
      "Data columns (total 1 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   JobSat  29126 non-null  float64\n",
      "dtypes: float64(1)\n",
      "memory usage: 511.4 KB\n",
      "None\n",
      "Number of unique values: 12\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Employment column has no missing values\n",
    "print(df[['JobSat']].info())\n",
    "print('Number of unique values:', len(df.JobSat.unique()))\n",
    "df.JobSat.hist()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_m = df.copy()\n",
    "# The data in the JobSat column has 55% missing values and it is skewed.\n",
    "# Hence, it is better to omit missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                  RemoteWork\n",
      "count                                  54806\n",
      "unique                                     3\n",
      "top     Hybrid (some remote, some in-person)\n",
      "freq                                   23015\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_300/3573580997.py:4: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
      "  ax.set(xticklabels=labels)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(df[['RemoteWork']].describe())\n",
    "ax = sns.countplot(data=df, x='RemoteWork')\n",
    "labels = [textwrap.fill(label.get_text(), width=20) for label in ax.get_xticklabels()]\n",
    "ax.set(xticklabels=labels)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count                                    65437\n",
      "unique                                       4\n",
      "top       Hybrid (some remote, some in-person)\n",
      "freq                                     23015\n",
      "Name: RemoteWork, dtype: object\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_300/3001049836.py:6: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
      "  ax.set(xticklabels=labels)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#The RemoteWork column has 16% missing values. Hence, it is better to add a new category.\n",
    "df_m['RemoteWork'] = df_m['RemoteWork'].fillna('Unknown')\n",
    "print(df_m['RemoteWork'].describe())\n",
    "ax = sns.countplot(data=df_m, x='RemoteWork')\n",
    "labels = [textwrap.fill(label.get_text(), width=20) for label in ax.get_xticklabels()]\n",
    "ax.set(xticklabels=labels)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 4: Analysis of Experience and Job Satisfaction\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analyze the relationship between years of professional coding experience (`YearsCodePro`) and job satisfaction (`JobSat`). Summarize `YearsCodePro` and calculate median satisfaction scores based on experience ranges.\n",
    "\n",
    "- Create experience ranges for `YearsCodePro` (e.g., `0-5`, `5-10`, `10-20`, `>20` years).\n",
    "\n",
    "- Calculate the median `JobSat` for each range.\n",
    "\n",
    "- Visualize the relationship using a bar plot or similar visualization.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['1', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '2', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '3', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '4', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '5', '50', '6', '7', '8', '9', 'Less than 1 year', 'More than 50 years', 'Unknown']\n"
     ]
    }
   ],
   "source": [
    "## Write your code here\n",
    "print(sorted(df_m.YearsCodePro.fillna('Unknown').unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     JobSat\n",
      "YearsCodePro-binned        \n",
      "0-5                     7.0\n",
      "5-10                    7.0\n",
      "10-20                   8.0\n",
      ">20                     8.0\n"
     ]
    }
   ],
   "source": [
    "df_fe = df_m[['YearsCodePro', 'JobSat']]\n",
    "df_fe = df_fe.dropna()\n",
    "df_fe = df_fe.replace({'Less than 1 year': 0, 'More than 50 years': 51}).astype(int)\n",
    "\n",
    "import numpy as np\n",
    "bins = [0, 5, 10, 20, 52]\n",
    "group_names = ['0-5', '5-10', '10-20', '>20']\n",
    "df_fe['YearsCodePro-binned'] = pd.cut(df_fe['YearsCodePro'], bins, labels=group_names, include_lowest=True)\n",
    "df_feg = df_fe.groupby(by=['YearsCodePro-binned'])[['JobSat']].median()\n",
    "print(df_feg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Median JobSat')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_feg.plot(kind='bar', rot=0)\n",
    "plt.xlabel('YearsCodePro')\n",
    "plt.ylabel('Median JobSat')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 5: Visualize Job Satisfaction\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use a count plot to show the distribution of `JobSat` values. This provides insights into the overall satisfaction levels of respondents.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='JobSat', ylabel='count'>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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y8vL05JNPyul0qk+fPpKkAQMGKDY2VkOGDNGnn36qzMxMTZw4USkpKeZbXiNHjtThw4c1btw4ffHFF3rjjTe0YsUKjR071pu7DgAAfIhXryH6xz/+occee0z//ve/1aZNG91+++3auXOn2rRpI0maPXu2GjVqpKSkJJWWliohIUFvvPGGub6/v7/Wrl2rUaNGyel0qlmzZkpOTtbUqVPNmujoaK1bt05jx47VnDlz1LZtW7399ts13nIPAACsx88wDMPbTfg6t9utoKAglZSUyOFweLsdAKh3cenveLsFD3kzh35nTUPsGXXrh7x++9Q1RAAAAN5AIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZHIAIAAJZXq0DUv39/FRcXXzbudrvVv3//H9sTAABAvapVINqyZYvKysouGz9//rz+/ve//+imAAAA6lPjH1L82WefmT8fOHBALpfLfFxRUaH169fr+uuvr7vuAAAA6sEPCkQ9evSQn5+f/Pz8qn1rLDAwUK+99lqdNQcAAFAfflAgOnLkiAzDUIcOHbR79261adPGnLPZbAoJCZG/v3+dNwkAAHA1/aBAFBUVJUmqrKy8Ks0AAAB4ww8KRBc7dOiQNm/erKKiossC0qRJk350YwAAAPWlVoHorbfe0qhRo9S6dWuFhYXJz8/PnPPz8yMQAQCABqVWgejFF1/USy+9pPHjx9d1PwAAAPWuVp9DdPLkST388MN13QsAAIBX1CoQPfzww9qwYUNd9wIAAOAVtQpEHTt21PPPP68nnnhCs2bN0ty5cz2W2pg+fbr8/PyUmppqjp0/f14pKSlq1aqVmjdvrqSkJBUWFnqsV1BQoMTERDVt2lQhISFKT0/XhQsXPGq2bNminj17ym63q2PHjsrIyKhVjwAA4NpUq2uI3nzzTTVv3lw5OTnKycnxmPPz89Mzzzzzg7a3Z88e/eEPf1C3bt08xseOHat169Zp5cqVCgoK0ujRo/XQQw9p+/btkv7z6diJiYkKCwvTjh07dPz4cQ0dOlRNmjTRyy+/LOk/n52UmJiokSNHaunSpcrOztZTTz2l8PBwJSQk1Gb3AQDANaZWgejIkSN11sDp06c1ePBgvfXWW3rxxRfN8ZKSEi1cuFDLli0zPxV78eLFiomJ0c6dO9WnTx9t2LBBBw4c0MaNGxUaGqoePXrohRde0Pjx4zVlyhTZbDYtWLBA0dHRmjVrliQpJiZG27Zt0+zZs2sMRKWlpSotLTUfu93uOttfAADge2r1llldSklJUWJiouLj4z3G8/LyVF5e7jHeuXNntWvXTrm5uZKk3Nxcde3aVaGhoWZNQkKC3G639u/fb9Zcuu2EhARzG9WZNm2agoKCzCUyMvJH7ycAAPBdtTpDNGzYsCvOL1q06HttZ/ny5fr444+1Z8+ey+ZcLpdsNpuCg4M9xkNDQ80vlXW5XB5hqGq+au5KNW63W+fOnVNgYOBlzz1hwgSlpaWZj91uN6EIAIBrWK0C0cmTJz0el5eXa9++fSouLq72S1+rc/ToUY0ZM0ZZWVkKCAioTRtXjd1ul91u93YbAACgntQqEK1ateqyscrKSo0aNUo33HDD99pGXl6eioqK1LNnT3OsoqJCW7du1euvv67MzEyVlZWpuLjY4yxRYWGhwsLCJElhYWHavXu3x3ar7kK7uObSO9MKCwvlcDiqPTsEAACsp86uIWrUqJHS0tI0e/bs71V/zz33aO/evcrPzzeXXr16afDgwebPTZo0UXZ2trnOwYMHVVBQIKfTKUlyOp3au3evioqKzJqsrCw5HA7FxsaaNRdvo6qmahsAAAC1/nLX6nz99deXfQZQTVq0aKGbb77ZY6xZs2Zq1aqVOT58+HClpaWpZcuWcjgc+tWvfiWn06k+ffpIkgYMGKDY2FgNGTJEM2bMkMvl0sSJE5WSkmK+5TVy5Ei9/vrrGjdunIYNG6ZNmzZpxYoVWrduXR3uOQAAaMhqFYguvuBYkgzD0PHjx7Vu3TolJyfXSWOSNHv2bDVq1EhJSUkqLS1VQkKC3njjDXPe399fa9eu1ahRo+R0OtWsWTMlJydr6tSpZk10dLTWrVunsWPHas6cOWrbtq3efvttPoMIAACY/AzDMH7oSv369fN43KhRI7Vp00b9+/fXsGHD1LhxnZ548jq3262goCCVlJTI4XB4ux0AqHdx6e94uwUPeTOHfmdNQ+wZdeuHvH7XKrls3ry5Vo0BAAD4oh91Kufbb7/VwYMHJUmdOnVSmzZt6qQpAACA+lSru8zOnDmjYcOGKTw8XHfeeafuvPNORUREaPjw4Tp79mxd9wgAAHBV1SoQpaWlKScnR2vWrFFxcbGKi4v1t7/9TTk5Ofr1r39d1z0CAABcVbV6y+yvf/2r/vKXv+juu+82x+677z4FBgbqkUce0fz58+uqPwC4pvjahb4SF/sCUi3PEJ09e/ay7weTpJCQEN4yAwAADU6tApHT6dTkyZN1/vx5c+zcuXP67W9/yydAAwCABqdWb5m9+uqruvfee9W2bVt1795dkvTpp5/Kbrdrw4YNddogAADA1VarQNS1a1cdOnRIS5cu1RdffCFJeuyxxzR48GC+MBUAADQ4tQpE06ZNU2hoqEaMGOExvmjRIn377bcaP358nTQHAABQH2oViP7whz9o2bJll4136dJFgwYNIhABAFALvnYXopXuQKzVRdUul0vh4eGXjbdp00bHjx//0U0BAADUp1oFosjISG3fvv2y8e3btysiIuJHNwUAAFCfavWW2YgRI5Samqry8nL1799fkpSdna1x48bxSdUAAKDBqVUgSk9P17///W/98pe/VFlZmSQpICBA48eP14QJE+q0QQAAgKutVoHIz89Pv/vd7/T888/r888/V2BgoG688UbZ7fa67g8AAOCqq1UgqtK8eXPdeuutddULAACAV9TqomoAAIBrCYEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYnlcD0fz589WtWzc5HA45HA45nU59+OGH5vz58+eVkpKiVq1aqXnz5kpKSlJhYaHHNgoKCpSYmKimTZsqJCRE6enpunDhgkfNli1b1LNnT9ntdnXs2FEZGRn1sXsAAKCB8Gogatu2raZPn668vDx99NFH6t+/vx544AHt379fkjR27FitWbNGK1euVE5Ojo4dO6aHHnrIXL+iokKJiYkqKyvTjh07tGTJEmVkZGjSpElmzZEjR5SYmKh+/fopPz9fqampeuqpp5SZmVnv+wsAAHxTY28++f333+/x+KWXXtL8+fO1c+dOtW3bVgsXLtSyZcvUv39/SdLixYsVExOjnTt3qk+fPtqwYYMOHDigjRs3KjQ0VD169NALL7yg8ePHa8qUKbLZbFqwYIGio6M1a9YsSVJMTIy2bdum2bNnKyEhod73GQAA+B6fuYaooqJCy5cv15kzZ+R0OpWXl6fy8nLFx8ebNZ07d1a7du2Um5srScrNzVXXrl0VGhpq1iQkJMjtdptnmXJzcz22UVVTtY3qlJaWyu12eywAAODa5fVAtHfvXjVv3lx2u10jR47UqlWrFBsbK5fLJZvNpuDgYI/60NBQuVwuSZLL5fIIQ1XzVXNXqnG73Tp37ly1PU2bNk1BQUHmEhkZWRe7CgAAfJTXA1GnTp2Un5+vXbt2adSoUUpOTtaBAwe82tOECRNUUlJiLkePHvVqPwAA4Ory6jVEkmSz2dSxY0dJUlxcnPbs2aM5c+bo0UcfVVlZmYqLiz3OEhUWFiosLEySFBYWpt27d3tsr+outItrLr0zrbCwUA6HQ4GBgdX2ZLfbZbfb62T/AACA7/P6GaJLVVZWqrS0VHFxcWrSpImys7PNuYMHD6qgoEBOp1OS5HQ6tXfvXhUVFZk1WVlZcjgcio2NNWsu3kZVTdU2AAAAvHqGaMKECRo4cKDatWunU6dOadmyZdqyZYsyMzMVFBSk4cOHKy0tTS1btpTD4dCvfvUrOZ1O9enTR5I0YMAAxcbGasiQIZoxY4ZcLpcmTpyolJQU8wzPyJEj9frrr2vcuHEaNmyYNm3apBUrVmjdunXe3HUAAOBDvBqIioqKNHToUB0/flxBQUHq1q2bMjMz9dOf/lSSNHv2bDVq1EhJSUkqLS1VQkKC3njjDXN9f39/rV27VqNGjZLT6VSzZs2UnJysqVOnmjXR0dFat26dxo4dqzlz5qht27Z6++23ueUeAACYvBqIFi5ceMX5gIAAzZs3T/PmzauxJioqSh988MEVt3P33Xfrk08+qVWPAADg2udz1xABAADUNwIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwvMbebgAAADRccenveLsFD3kzh9ZqPc4QAQAAyyMQAQAAyyMQAQAAyyMQAQAAyyMQAQAAyyMQAQAAyyMQAQAAy/NqIJo2bZpuvfVWtWjRQiEhIXrwwQd18OBBj5rz588rJSVFrVq1UvPmzZWUlKTCwkKPmoKCAiUmJqpp06YKCQlRenq6Lly44FGzZcsW9ezZU3a7XR07dlRGRsbV3j0AANBAeDUQ5eTkKCUlRTt37lRWVpbKy8s1YMAAnTlzxqwZO3as1qxZo5UrVyonJ0fHjh3TQw89ZM5XVFQoMTFRZWVl2rFjh5YsWaKMjAxNmjTJrDly5IgSExPVr18/5efnKzU1VU899ZQyMzPrdX8BAIBv8uonVa9fv97jcUZGhkJCQpSXl6c777xTJSUlWrhwoZYtW6b+/ftLkhYvXqyYmBjt3LlTffr00YYNG3TgwAFt3LhRoaGh6tGjh1544QWNHz9eU6ZMkc1m04IFCxQdHa1Zs2ZJkmJiYrRt2zbNnj1bCQkJ9b7fAADAt/jUNUQlJSWSpJYtW0qS8vLyVF5ervj4eLOmc+fOateunXJzcyVJubm56tq1q0JDQ82ahIQEud1u7d+/36y5eBtVNVXbuFRpaancbrfHAgAArl0+E4gqKyuVmpqqvn376uabb5YkuVwu2Ww2BQcHe9SGhobK5XKZNReHoar5qrkr1bjdbp07d+6yXqZNm6agoCBziYyMrJN9BAAAvslnAlFKSor27dun5cuXe7sVTZgwQSUlJeZy9OhRb7cEAACuIp/4tvvRo0dr7dq12rp1q9q2bWuOh4WFqaysTMXFxR5niQoLCxUWFmbW7N6922N7VXehXVxz6Z1phYWFcjgcCgwMvKwfu90uu91eJ/sG4Oq5Vr5lG4D3efUMkWEYGj16tFatWqVNmzYpOjraYz4uLk5NmjRRdna2OXbw4EEVFBTI6XRKkpxOp/bu3auioiKzJisrSw6HQ7GxsWbNxduoqqnaBgAAsDavniFKSUnRsmXL9Le//U0tWrQwr/kJCgpSYGCggoKCNHz4cKWlpally5ZyOBz61a9+JafTqT59+kiSBgwYoNjYWA0ZMkQzZsyQy+XSxIkTlZKSYp7lGTlypF5//XWNGzdOw4YN06ZNm7RixQqtW7fOa/sOAAB8h1fPEM2fP18lJSW6++67FR4ebi7vvvuuWTN79mz97Gc/U1JSku68806FhYXpvffeM+f9/f21du1a+fv7y+l06vHHH9fQoUM1depUsyY6Olrr1q1TVlaWunfvrlmzZuntt9/mlnsAACDJy2eIDMP4zpqAgADNmzdP8+bNq7EmKipKH3zwwRW3c/fdd+uTTz75wT0CAIBrn8/cZQYAAOAtBCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5BCIAAGB5jb3dAHAtikt/x9steMibOdTbLQCAT+MMEQAAsDzOEAGQxFktANbGGSIAAGB5Xg1EW7du1f3336+IiAj5+flp9erVHvOGYWjSpEkKDw9XYGCg4uPjdejQIY+aEydOaPDgwXI4HAoODtbw4cN1+vRpj5rPPvtMd9xxhwICAhQZGakZM2Zc7V0DAAANiFcD0ZkzZ9S9e3fNmzev2vkZM2Zo7ty5WrBggXbt2qVmzZopISFB58+fN2sGDx6s/fv3KysrS2vXrtXWrVv19NNPm/Nut1sDBgxQVFSU8vLyNHPmTE2ZMkVvvvnmVd8/AADQMHj1GqKBAwdq4MCB1c4ZhqFXX31VEydO1AMPPCBJeueddxQaGqrVq1dr0KBB+vzzz7V+/Xrt2bNHvXr1kiS99tpruu+++/T73/9eERERWrp0qcrKyrRo0SLZbDZ16dJF+fn5euWVVzyCEwAAsC6fvYboyJEjcrlcio+PN8eCgoLUu3dv5ebmSpJyc3MVHBxshiFJio+PV6NGjbRr1y6z5s4775TNZjNrEhISdPDgQZ08ebLa5y4tLZXb7fZYAADAtctnA5HL5ZIkhYaGeoyHhoaacy6XSyEhIR7zjRs3VsuWLT1qqtvGxc9xqWnTpikoKMhcIiMjf/wOAQAAn+WzgcibJkyYoJKSEnM5evSot1sCAABXkc8GorCwMElSYWGhx3hhYaE5FxYWpqKiIo/5Cxcu6MSJEx411W3j4ue4lN1ul8Ph8FgAAMC1y2cDUXR0tMLCwpSdnW2Oud1u7dq1S06nU5LkdDpVXFysvLw8s2bTpk2qrKxU7969zZqtW7eqvLzcrMnKylKnTp103XXX1dPeAAAAX+bVQHT69Gnl5+crPz9f0n8upM7Pz1dBQYH8/PyUmpqqF198Ue+//7727t2roUOHKiIiQg8++KAkKSYmRvfee69GjBih3bt3a/v27Ro9erQGDRqkiIgISdIvfvEL2Ww2DR8+XPv379e7776rOXPmKC0tzUt7DQAAfI1Xb7v/6KOP1K9fP/NxVUhJTk5WRkaGxo0bpzNnzujpp59WcXGxbr/9dq1fv14BAQHmOkuXLtXo0aN1zz33qFGjRkpKStLcuXPN+aCgIG3YsEEpKSmKi4tT69atNWnSJG65BwAAJq8GorvvvluGYdQ47+fnp6lTp2rq1Kk11rRs2VLLli274vN069ZNf//732vdJwAAuLb57DVEAAAA9YVABAAALI9ABAAALI9ABAAALM+rF1UD30dc+jvebsFD3syh3m4BAFDHOEMEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsr7G3G2jI4tLf8XYLHvJmDvV2CwAANEicIQIAAJbHGSKL4awWAACX4wwRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPEsFonnz5ql9+/YKCAhQ7969tXv3bm+3BAAAfIBlAtG7776rtLQ0TZ48WR9//LG6d++uhIQEFRUVebs1AADgZZYJRK+88opGjBihJ598UrGxsVqwYIGaNm2qRYsWebs1AADgZZb4LrOysjLl5eVpwoQJ5lijRo0UHx+v3Nzcy+pLS0tVWlpqPi4pKZEkud1uj7qK0nNXqePaubS/6tDzj0fP9YOe609D7Jue60dD77nqZ8MwvntFwwL++c9/GpKMHTt2eIynp6cbt91222X1kydPNiSxsLCwsLCwXAPL0aNHvzMrWOIM0Q81YcIEpaWlmY8rKyt14sQJtWrVSn5+fnX6XG63W5GRkTp69KgcDkedbvtqoef6Qc/1g57rT0Psm57rx9Xq2TAMnTp1ShEREd9Za4lA1Lp1a/n7+6uwsNBjvLCwUGFhYZfV2+122e12j7Hg4OCr2aIcDkeD+Y9bhZ7rBz3XD3quPw2xb3quH1ej56CgoO9VZ4mLqm02m+Li4pSdnW2OVVZWKjs7W06n04udAQAAX2CJM0SSlJaWpuTkZPXq1Uu33XabXn31VZ05c0ZPPvmkt1sDAABeZplA9Oijj+rbb7/VpEmT5HK51KNHD61fv16hoaFe7ctut2vy5MmXvUXny+i5ftBz/aDn+tMQ+6bn+uELPfsZxve5Fw0AAODaZYlriAAAAK6EQAQAACyPQAQAACyPQAQAACyPQFQP5s2bp/bt2ysgIEC9e/fW7t27r1i/cuVKde7cWQEBAeratas++OCDeur0P7Zu3ar7779fERER8vPz0+rVq79znS1btqhnz56y2+3q2LGjMjIyrnqfVaZNm6Zbb71VLVq0UEhIiB588EEdPHjwO9fz5nGeP3++unXrZn4ImdPp1IcffnjFdbz9/+JS06dPl5+fn1JTU69Y5+2+p0yZIj8/P4+lc+fOV1zH2z3/85//1OOPP65WrVopMDBQXbt21UcffXTFdbz5OyhJ7du3v+w4+/n5KSUlpcZ1vH2cKyoq9Pzzzys6OlqBgYG64YYb9MILL3zn9155+1ifOnVKqampioqKUmBgoH7yk59oz549V1ynPnv+rtcQwzA0adIkhYeHKzAwUPHx8Tp06NB3bveHvpb+YHXxXWGo2fLlyw2bzWYsWrTI2L9/vzFixAgjODjYKCwsrLZ++/bthr+/vzFjxgzjwIEDxsSJE40mTZoYe/furbeeP/jgA+O5554z3nvvPUOSsWrVqivWHz582GjatKmRlpZmHDhwwHjttdcMf39/Y/369fXSb0JCgrF48WJj3759Rn5+vnHfffcZ7dq1M06fPl3jOt4+zu+//76xbt0648svvzQOHjxo/OY3vzGaNGli7Nu3zyf7vdTu3buN9u3bG926dTPGjBlTY50v9D158mSjS5cuxvHjx83l22+/9dmeT5w4YURFRRlPPPGEsWvXLuPw4cNGZmam8dVXX9W4jrd/Bw3DMIqKijyOcVZWliHJ2Lx5c7X13j7OhmEYL730ktGqVStj7dq1xpEjR4yVK1cazZs3N+bMmVPjOr5wrB955BEjNjbWyMnJMQ4dOmRMnjzZcDgcxj/+8Q+f6Pm7XkOmT59uBAUFGatXrzY+/fRT47/+67+M6Oho49y5czVu84e+ltYGgegqu+2224yUlBTzcUVFhREREWFMmzat2vpHHnnESExM9Bjr3bu38T//8z9Xtc+afJ9ANG7cOKNLly4eY48++qiRkJBwFTurWVFRkSHJyMnJqbHG146zYRjGddddZ7z99tvVzvlSv6dOnTJuvPFGIysry7jrrruuGIh8oe/Jkycb3bt3/9713u55/Pjxxu233/6D1vG130HDMIwxY8YYN9xwg1FZWVntvLePs2EYRmJiojFs2DCPsYceesgYPHhwjet4+1ifPXvW8Pf3N9auXesx3rNnT+O5556rdh1v9nzpa0hlZaURFhZmzJw50xwrLi427Ha78ec//7nG7fzQ19La4C2zq6isrEx5eXmKj483xxo1aqT4+Hjl5uZWu05ubq5HvSQlJCTUWO8LfK3nkpISSVLLli1rrPGlnisqKrR8+XKdOXOmxq+S8aV+U1JSlJiYeFk/1fGVvg8dOqSIiAh16NBBgwcPVkFBQY213u75/fffV69evfTwww8rJCREt9xyi956660rruPtni9VVlamP/3pTxo2bFiNX4jtCz3/5Cc/UXZ2tr788ktJ0qeffqpt27Zp4MCBNa7j7b4vXLigiooKBQQEeIwHBgZq27Zt1a7j7Z4vduTIEblcLo9+goKC1Lt37xr7qc1raW1Y5pOqveFf//qXKioqLvs07NDQUH3xxRfVruNyuaqtd7lcV63PH6umnt1ut86dO6fAwMB666WyslKpqanq27evbr755hrrfOE47927V06nU+fPn1fz5s21atUqxcbGVlvrC/1K0vLly/Xxxx9/5/UKVXyh7969eysjI0OdOnXS8ePH9dvf/lZ33HGH9u3bpxYtWlxW7+2eDx8+rPnz5ystLU2/+c1vtGfPHj3zzDOy2WxKTk6udh1f+h2UpNWrV6u4uFhPPPFEjTXePs6S9Oyzz8rtdqtz587y9/dXRUWFXnrpJQ0ePLjGdbx9rFu0aCGn06kXXnhBMTExCg0N1Z///Gfl5uaqY8eOPtnzpb1UPf+l/dT0b1+b19LaIBDhmpKSkqJ9+/bV+JeSL+nUqZPy8/NVUlKiv/zlL0pOTlZOTk6Nocjbjh49qjFjxigrK+uyv0592cV/7Xfr1k29e/dWVFSUVqxYoeHDh3uxs+pVVlaqV69eevnllyVJt9xyi/bt26cFCxbUGIh8zcKFCzVw4EBFRER4u5UrWrFihZYuXaply5apS5cuys/PV2pqqiIiInz6WP/xj3/UsGHDdP3118vf3189e/bUY489pry8PG+31qDxltlV1Lp1a/n7+6uwsNBjvLCwUGFhYdWuExYW9oPqfUFNPTscjnr9y2P06NFau3atNm/erLZt216x1heOs81mU8eOHRUXF6dp06ape/fumjNnTrW1vtBvXl6eioqK1LNnTzVu3FiNGzdWTk6O5s6dq8aNG6uiouKydXyh70sFBwfrpptu0ldffVXtvLd7Dg8PvywUx8TEXPFtPl/5HZSkb775Rhs3btRTTz11xTpvH2dJSk9P17PPPqtBgwapa9euGjJkiMaOHatp06bVuI4vHOsbbrhBOTk5On36tI4ePardu3ervLxcHTp0qLbeF3q+uJeq57+0n5r+7WvzWlobBKKryGazKS4uTtnZ2eZYZWWlsrOza7xWxOl0etRLUlZWVo31vsDbPRuGodGjR2vVqlXatGmToqOjv3Mdb/dcncrKSpWWllY75wv93nPPPdq7d6/y8/PNpVevXho8eLDy8/Pl7+9/2Tq+0PelTp8+ra+//lrh4eHVznu75759+172sRFffvmloqKialzH2z1fbPHixQoJCVFiYuIV63yh57Nnz6pRI8+XQX9/f1VWVta4ji/0XaVZs2YKDw/XyZMnlZmZqQceeKDaOl/qOTo6WmFhYR79uN1u7dq1q8Z+avNaWit1dnk2qrV8+XLDbrcbGRkZxoEDB4ynn37aCA4ONlwul2EYhjFkyBDj2WefNeu3b99uNG7c2Pj9739vfP7558bkyZPr/VbUU6dOGZ988onxySefGJKMV155xfjkk0+Mb775xjAMw3j22WeNIUOGmPVVt3Smp6cbn3/+uTFv3rx6vQ111KhRRlBQkLFlyxaP237Pnj1r1vjacX722WeNnJwc48iRI8Znn31mPPvss4afn5+xYcMGn+y3JpfeZeaLff/61782tmzZYhw5csTYvn27ER8fb7Ru3dooKiryyZ53795tNG7c2HjppZeMQ4cOGUuXLjWaNm1q/OlPfzJrfO13sEpFRYXRrl07Y/z48ZfN+dpxNgzDSE5ONq6//nrztvv33nvPaN26tTFu3DizxheP9fr1640PP/zQOHz4sLFhwwaje/fuRu/evY2ysjKf6Pm7XkOmT59uBAcHG3/729+Mzz77zHjggQcuu+2+f//+xmuvvWY+/q7X0rpAIKoHr732mtGuXTvDZrMZt912m7Fz505z7q677jKSk5M96lesWGHcdNNNhs1mM7p06WKsW7euXvvdvHmzIemyparP5ORk46677rpsnR49ehg2m83o0KGDsXjx4nrrt7peJXn04GvHediwYUZUVJRhs9mMNm3aGPfcc48Zhnyx35pcGoh8se9HH33UCA8PN2w2m3H99dcbjz76qMdn+vhiz2vWrDFuvvlmw263G507dzbefPNNj3lf+x2skpmZaUgyDh48eNmcLx5nt9ttjBkzxmjXrp0REBBgdOjQwXjuueeM0tJSs8YXj/W7775rdOjQwbDZbEZYWJiRkpJiFBcX+0zP3/UaUllZaTz//PNGaGioYbfbjXvuueey/zNRUVHG5MmTPcau9FpaF/wM4zs+khMAAOAaxzVEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAK5pW7ZskZ+fn4qLi73dCgAfRiAC0OA88cQTevDBB+t0m2+99Za6d++u5s2bKzg4WLfccssVv/W8On5+flq9enWd9gWgfjT2dgMA4G2LFi1Samqq5s6dq7vuukulpaX67LPPtG/fPm+3BqCecIYIQINWWlqqZ555RiEhIQoICNDtt9+uPXv2XFa3fft2devWTQEBAerTp49H2Hn//ff1yCOPaPjw4erYsaO6dOmixx57TC+99JJZs2fPHv30pz9V69atFRQUpLvuuksff/yxOd++fXtJ0s9//nP5+fmZjwE0DAQiAA3auHHj9Ne//lVLlizRxx9/rI4dOyohIUEnTpzwqEtPT9esWbO0Z88etWnTRvfff7/Ky8slSWFhYdq5c6e++eabGp/n1KlTSk5O1rZt27Rz507deOONuu+++3Tq1ClJMkPY4sWLdfz48WpDGQDfRSAC0GCdOXNG8+fP18yZMzVw4EDFxsbqrbfeUmBgoBYuXOhRO3nyZP30pz9V165dtWTJEhUWFmrVqlXmXHBwsNq3b69OnTrpiSee0IoVK1RZWWmu379/fz3++OPq3LmzYmJi9Oabb+rs2bPKycmRJLVp00aSFBwcrLCwMPMxgIaBQASgwfr6669VXl6uvn37mmNNmjTRbbfdps8//9yj1ul0mj+3bNlSnTp1MmvCw8OVm5urvXv3asyYMbpw4YKSk5N17733mqGosLBQI0aM0I033qigoCA5HA6dPn1aBQUF9bCnAK42LqoGgP/PzTffrJtvvlm//OUvNXLkSN1xxx3KyclRv379lJycrH//+9+aM2eOoqKiZLfb5XQ6VVZW5u22AdQBzhABaLBuuOEG2Ww2bd++3RwrLy/Xnj17FBsb61G7c+dO8+eTJ0/qyy+/VExMTI3brlr/zJkzkv5zUfYzzzyj++67T126dJHdbte//vUvj3WaNGmiioqKH71fAOofZ4gANFjNmjXTqFGjlJ6erpYtW6pdu3aaMWOGzp49q+HDh3vUTp06Va1atVJoaKiee+45tW7d2vwso1GjRikiIkL9+/dX27Ztdfz4cb344otq06aN+VbbjTfeqD/+8Y/q1auX3G630tPTFRgY6PEc7du3V3Z2tvr27Su73a7rrruuXo4DgB+PM0QAGpzKyko1bvyfv+emT5+upKQkDRkyRD179tRXX32lzMzMy8LI9OnTNWbMGMXFxcnlcmnNmjWy2WySpPj4eO3cuVMPP/ywbrrpJiUlJSkgIEDZ2dlq1aqVJGnhwoU6efKkevbsqSFDhpi3+l9s1qxZysrKUmRkpG655ZZ6OBIA6oqfYRiGt5sAgB/i3nvvVceOHfX66697uxUA1wjOEAFoME6ePKm1a9dqy5Ytio+P93Y7AK4hXEMEoMEYNmyY9uzZo1//+td64IEHvN0OgGsIb5kBAADL4y0zAABgeQQiAABgeQQiAABgeQQiAABgeQQiAABgeQQiAABgeQQiAABgeQQiAABgef8PGhTdICzRvfsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Write your code here\n",
    "sns.countplot(data=df_m, x='JobSat')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 6: Analyzing Remote Work Preferences by Job Role\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analyze trends in remote work based on job roles. Use the `RemoteWork` and `Employment` columns to explore preferences and examine if specific job roles prefer remote work more than others.\n",
    "\n",
    "- Use a count plot to show remote work distribution.\n",
    "\n",
    "- Cross-tabulate remote work preferences by employment type (e.g., full-time, part-time) and job roles.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_300/3415317324.py:4: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
      "  ax.set(xticklabels=labels)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Write your code here\n",
    "ax = sns.countplot(data=df_m, x='RemoteWork')\n",
    "labels = [textwrap.fill(label.get_text(), width=20) for label in ax.get_xticklabels()]\n",
    "ax.set(xticklabels=labels)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Employed, full-time', 'Employed, part-time', 'I prefer not to say', 'Independent contractor, freelancer, or self-employed', 'Not employed, and not looking for work', 'Not employed, but looking for work', 'Retired', 'Student, full-time', 'Student, part-time'] 9\n"
     ]
    }
   ],
   "source": [
    "#Encode the Employment column using one-hot encoding\n",
    "cat = set()\n",
    "empl = df_m.Employment.unique()\n",
    "for el in empl:\n",
    "    if ';' in el:\n",
    "        cat = cat | set(el.split(';'))\n",
    "    else:\n",
    "        cat.add(el)\n",
    "cat = sorted(cat)\n",
    "print(cat, len(cat))  # Columns that should be added to the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            Employment  Employed, full-time  Employed, part-time  \\\n",
      "0  Employed, full-time                 True                False   \n",
      "1  Employed, full-time                 True                False   \n",
      "2  Employed, full-time                 True                False   \n",
      "3   Student, full-time                False                False   \n",
      "4   Student, full-time                False                False   \n",
      "\n",
      "   I prefer not to say  Independent contractor, freelancer, or self-employed  \\\n",
      "0                False                                              False      \n",
      "1                False                                              False      \n",
      "2                False                                              False      \n",
      "3                False                                              False      \n",
      "4                False                                              False      \n",
      "\n",
      "   Not employed, and not looking for work  Not employed, but looking for work  \\\n",
      "0                                   False                               False   \n",
      "1                                   False                               False   \n",
      "2                                   False                               False   \n",
      "3                                   False                               False   \n",
      "4                                   False                               False   \n",
      "\n",
      "   Retired  Student, full-time  Student, part-time  \n",
      "0    False               False               False  \n",
      "1    False               False               False  \n",
      "2    False               False               False  \n",
      "3    False                True               False  \n",
      "4    False                True               False  \n",
      "(65437, 123)\n"
     ]
    }
   ],
   "source": [
    "df_me = df_m.copy()\n",
    "dummies = df_me['Employment'].str.get_dummies(sep=';').astype(bool)\n",
    "df_me = pd.concat([df_me, dummies], axis=1)\n",
    "print(df_me[['Employment', *cat]].head())\n",
    "print(df_me.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RemoteWork                                     Hybrid (some remote, some in-person)  \\\n",
      "DevType                                                                               \n",
      "Blockchain                                                                       34   \n",
      "Developer Advocate                                                               29   \n",
      "Developer, game or graphics                                                     168   \n",
      "Developer, QA or test                                                           201   \n",
      "Cloud infrastructure engineer                                                   273   \n",
      "Developer Experience                                                             79   \n",
      "Developer, back-end                                                            3763   \n",
      "Developer, front-end                                                           1140   \n",
      "Developer, mobile                                                               675   \n",
      "Engineer, site reliability                                                      122   \n",
      "Designer                                                                         56   \n",
      "Security professional                                                           136   \n",
      "Developer, full-stack                                                          6934   \n",
      "Senior Executive (C-Suite, VP, etc.)                                            359   \n",
      "Engineering manager                                                             603   \n",
      "Data engineer                                                                   522   \n",
      "DevOps specialist                                                               500   \n",
      "Developer, AI                                                                   195   \n",
      "Product manager                                                                 130   \n",
      "Other (please specify):                                                         751   \n",
      "Database administrator                                                           64   \n",
      "Developer, desktop or enterprise applications                                   993   \n",
      "Data scientist or machine learning specialist                                   489   \n",
      "Marketing or sales professional                                                  33   \n",
      "Research & Development role                                                     432   \n",
      "Project manager                                                                 195   \n",
      "Student                                                                         265   \n",
      "Data or business analyst                                                        228   \n",
      "System administrator                                                            217   \n",
      "Educator                                                                        122   \n",
      "Developer, embedded applications or devices                                     745   \n",
      "Scientist                                                                       149   \n",
      "Academic researcher                                                             532   \n",
      "Hardware Engineer                                                                78   \n",
      "\n",
      "RemoteWork                                     In-person  Remote  Remote_frac  \n",
      "DevType                                                                        \n",
      "Blockchain                                            24     144     0.712871  \n",
      "Developer Advocate                                     9      61     0.616162  \n",
      "Developer, game or graphics                           95     256     0.493256  \n",
      "Developer, QA or test                                 61     229     0.466395  \n",
      "Cloud infrastructure engineer                         52     282     0.464580  \n",
      "Developer Experience                                  29      91     0.457286  \n",
      "Developer, back-end                                 1318    4179     0.451296  \n",
      "Developer, front-end                                 501    1342     0.449883  \n",
      "Developer, mobile                                    348     806     0.440678  \n",
      "Engineer, site reliability                            45     126     0.430034  \n",
      "Designer                                              24      57     0.416058  \n",
      "Security professional                                 46     127     0.411003  \n",
      "Developer, full-stack                               3143    6945     0.408001  \n",
      "Senior Executive (C-Suite, VP, etc.)                 124     326     0.402967  \n",
      "Engineering manager                                  160     483     0.387640  \n",
      "Data engineer                                        138     416     0.386617  \n",
      "DevOps specialist                                    102     368     0.379381  \n",
      "Developer, AI                                        107     169     0.358811  \n",
      "Product manager                                       55      89     0.324818  \n",
      "Other (please specify):                              495     599     0.324661  \n",
      "Database administrator                                43      50     0.318471  \n",
      "Developer, desktop or enterprise applications        589     727     0.314855  \n",
      "Data scientist or machine learning specialist        153     285     0.307443  \n",
      "Marketing or sales professional                       28      25     0.290698  \n",
      "Research & Development role                          200     248     0.281818  \n",
      "Project manager                                       93     107     0.270886  \n",
      "Student                                              268     195     0.267857  \n",
      "Data or business analyst                             123     123     0.259494  \n",
      "System administrator                                 164     107     0.219262  \n",
      "Educator                                             146      61     0.185410  \n",
      "Developer, embedded applications or devices          535     250     0.163399  \n",
      "Scientist                                             94      42     0.147368  \n",
      "Academic researcher                                  310     115     0.120167  \n",
      "Hardware Engineer                                     84      13     0.074286  \n"
     ]
    }
   ],
   "source": [
    "df_tab1 = pd.crosstab(df_me.DevType, df_me.RemoteWork).drop('Unknown', axis=1)\n",
    "df_tab1['Remote_frac'] = df_tab1['Remote'] / df_tab1.sum(axis=1)\n",
    "print(df_tab1.sort_values(by=['Remote_frac'], ascending=False))\n",
    "#print(df_tab1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RemoteWork                                          Hybrid (some remote, some in-person)  \\\n",
      "Not employed, and not looking for work                                                27   \n",
      "Not employed, but looking for work                                                   204   \n",
      "Independent contractor, freelancer, or self-emp...                                  3469   \n",
      "Retired                                                                               39   \n",
      "Employed, full-time                                                                19689   \n",
      "Student, full-time                                                                  1219   \n",
      "Student, part-time                                                                   822   \n",
      "Employed, part-time                                                                 1917   \n",
      "I prefer not to say                                                                    0   \n",
      "\n",
      "RemoteWork                                          Remote  In-person  \\\n",
      "Not employed, and not looking for work                  85         17   \n",
      "Not employed, but looking for work                     432         73   \n",
      "Independent contractor, freelancer, or self-emp...    6333        901   \n",
      "Retired                                                 61         21   \n",
      "Employed, full-time                                  15852       9604   \n",
      "Student, full-time                                     856        755   \n",
      "Student, part-time                                     569        496   \n",
      "Employed, part-time                                   1210       1013   \n",
      "I prefer not to say                                      0          0   \n",
      "\n",
      "RemoteWork                                          Remote_frac  \n",
      "Not employed, and not looking for work                 0.658915  \n",
      "Not employed, but looking for work                     0.609309  \n",
      "Independent contractor, freelancer, or self-emp...     0.591703  \n",
      "Retired                                                0.504132  \n",
      "Employed, full-time                                    0.351135  \n",
      "Student, full-time                                     0.302473  \n",
      "Student, part-time                                     0.301537  \n",
      "Employed, part-time                                    0.292271  \n",
      "I prefer not to say                                         NaN  \n"
     ]
    }
   ],
   "source": [
    "df_tab2 = pd.DataFrame()\n",
    "for col in dummies.columns:\n",
    "    df_tab2[col] = df_me[df_me[col]].RemoteWork.value_counts()\n",
    "df_tab2 = df_tab2.T.fillna(0).astype(int).drop('Unknown', axis=1)\n",
    "df_tab2['Remote_frac'] = df_tab2['Remote'] / df_tab2.sum(axis=1)\n",
    "print(df_tab2.sort_values(by=['Remote_frac'], ascending=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 7: Analyzing Programming Language Trends by Region\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analyze the popularity of programming languages by region. Use the `LanguageHaveWorkedWith` column to investigate which languages are most used in different regions.\n",
    "\n",
    "- Filter data by country or region.\n",
    "\n",
    "- Visualize the top programming languages by region with a bar plot or heatmap.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Ada', 'Apex', 'Assembly', 'Bash/Shell (all shells)', 'C', 'C#', 'C++', 'Clojure', 'Cobol', 'Crystal', 'Dart', 'Delphi', 'Elixir', 'Erlang', 'F#', 'Fortran', 'GDScript', 'Go', 'Groovy', 'HTML/CSS', 'Haskell', 'Java', 'JavaScript', 'Julia', 'Kotlin', 'Lisp', 'Lua', 'MATLAB', 'MicroPython', 'Nim', 'OCaml', 'Objective-C', 'PHP', 'Perl', 'PowerShell', 'Prolog', 'Python', 'R', 'Ruby', 'Rust', 'SQL', 'Scala', 'Solidity', 'Swift', 'TypeScript', 'VBA', 'Visual Basic (.Net)', 'Zephyr', 'Zig'] 49\n"
     ]
    }
   ],
   "source": [
    "#Encode the LanguageHaveWorkedWith column using one-hot encoding\n",
    "plr = df_me[['Country', 'LanguageHaveWorkedWith']].dropna()\n",
    "cat = set()\n",
    "lang = plr.LanguageHaveWorkedWith.unique()\n",
    "for el in lang:\n",
    "    if ';' in el:\n",
    "        cat = cat | set(el.split(';'))\n",
    "    else:\n",
    "        cat.add(el)\n",
    "cat = sorted(cat)\n",
    "print(cat, len(cat))  # Columns that should be added to the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(57679, 51)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Write your code here\n",
    "plr = df_me[['Country', 'LanguageHaveWorkedWith']].dropna()\n",
    "dummies = plr['LanguageHaveWorkedWith'].str.get_dummies(sep=';').astype(bool)\n",
    "plr = pd.concat([plr, dummies], axis=1)\n",
    "plr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_tab3 = pd.DataFrame()\n",
    "for col in dummies.columns:\n",
    "    df_tab3[col] = plr[plr[col]].Country.value_counts()\n",
    "df_tab3 = df_tab3.fillna(0).astype(int).T\n",
    "\n",
    "country = 'Ukraine'\n",
    "plt.figure(figsize=(8, 5))\n",
    "barpl = df_tab3[country].sort_values(ascending=False)\n",
    "barpl = barpl.iloc[0:10]\n",
    "ax = barpl.plot(kind='bar')\n",
    "plt.title(f\"Top programming languages in {country}\")\n",
    "plt.xlabel(\"Languages\")\n",
    "plt.ylabel(\"Count of answers\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#df_tab3fr = df_tab3.div(df_tab3.sum(axis=0), axis=1) # column‑wise normalization\n",
    "plt.figure(figsize=(30, 20))\n",
    "sns.heatmap(np.log10(df_tab3 + 1), cbar=False)\n",
    "#sns.heatmap(df_tab3fr, cbar=False)\n",
    "plt.title(\"Programming Language Trends by Region\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 8: Correlation Between Experience and Satisfaction\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Examine how years of experience (`YearsCodePro`) correlate with job satisfaction (`JobSatPoints_1`). Use a scatter plot to visualize this relationship.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Write your code here\n",
    "df_cbes = df_me[['YearsCodePro', 'JobSatPoints_1']].dropna()\n",
    "df_cbes = df_cbes.replace({'Less than 1 year': 0, 'More than 50 years': 51}).astype(int)\n",
    "df_cbes.plot(kind='scatter', x='YearsCodePro', y='JobSatPoints_1')\n",
    "plt.title('Correlation Between Experience and Satisfaction')\n",
    "plt.ylabel('JobSatPoints_1')\n",
    "plt.xlabel('YearsCodePro')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 9: Educational Background and Employment Type\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Explore how educational background (`EdLevel`) relates to employment type (`Employment`). Use cross-tabulation and visualizations to understand if higher education correlates with specific employment types.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<StringArray>\n",
      "[                                                         'Primary/elementary school',\n",
      "                                       'Bachelor’s degree (B.A., B.S., B.Eng., etc.)',\n",
      "                                    'Master’s degree (M.A., M.S., M.Eng., MBA, etc.)',\n",
      "                             'Some college/university study without earning a degree',\n",
      " 'Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)',\n",
      "                                     'Professional degree (JD, MD, Ph.D, Ed.D, etc.)',\n",
      "                                                'Associate degree (A.A., A.S., etc.)',\n",
      "                                                                     'Something else',\n",
      "                                                                                  nan]\n",
      "Length: 9, dtype: str\n"
     ]
    }
   ],
   "source": [
    "print(df_me['EdLevel'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.DataFrame'>\n",
      "Index: 9 entries, Employed, full-time to Student, part-time\n",
      "Data columns (total 8 columns):\n",
      " #   Column                                                                              Non-Null Count  Dtype\n",
      "---  ------                                                                              --------------  -----\n",
      " 0   Bachelor’s degree (B.A., B.S., B.Eng., etc.)                                        9 non-null      int64\n",
      " 1   Master’s degree (M.A., M.S., M.Eng., MBA, etc.)                                     9 non-null      int64\n",
      " 2   Some college/university study without earning a degree                              9 non-null      int64\n",
      " 3   Professional degree (JD, MD, Ph.D, Ed.D, etc.)                                      9 non-null      int64\n",
      " 4   Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)  9 non-null      int64\n",
      " 5   Associate degree (A.A., A.S., etc.)                                                 9 non-null      int64\n",
      " 6   Something else                                                                      9 non-null      int64\n",
      " 7   Primary/elementary school                                                           9 non-null      int64\n",
      "dtypes: int64(8)\n",
      "memory usage: 648.0+ bytes\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "## Write your code here\n",
    "df_ebet = pd.DataFrame()\n",
    "dummies = df_me['Employment'].str.get_dummies(sep=';').astype(bool)\n",
    "for col in dummies.columns:\n",
    "    df_ebet[col] = df_me[df_me[col]].EdLevel.value_counts()\n",
    "df_ebet = df_ebet.T.fillna(0).astype(int)\n",
    "print(df_ebet.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ebetfr = df_ebet.div(df_ebet.sum(axis=0), axis=1) # column‑wise normalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Zno984O9/rChZsmSq70HBggX1008/WT4/eG7z7/Uy+zP2qJ/lB/5+jR78HAUGBqZZ/vfvVVqxVqhQQdL95xb9/f1T9ZmZe968eXMFBARoyZIlatq0qcxmsz799FO1bt3aMvXzgbSur4+PzyPP5dKlS7p27Zo+/PBDffjhh6likqSLFy9afX7Udyun+fr66oUXXtAnn3yicePGSbqfHJcoUUJNmjRJVf/v3+myZcvKyclJiYmJku5P+zUMI83vviTL9GoAeRdJIQC7YDKZrEaxHvj7AhwZkZCQoKZNm6pSpUqaPn26AgMD5eLiojVr1ujdd9+V2WzOiZAfytnZ+ZF1tm3bphdffFGNGjXS7NmzFRAQoPz582vhwoX65JNPcjSepk2bSpK+//57vfDCC0pJSVHz5s115coVDRs2TJUqVZKnp6fOnj2ryMjILF+jdu3aadGiRVqyZIleffXVbMf915G1zMrsdyq9e5ZWG1lx7do1NW7cWN7e3ho7dqzKli0rNzc37d+/X8OGDUt1zXM7nqxIL6a8Equzs7O6dOmiefPmafbs2YqLi9P//ve/NEfHsnouD+7Tyy+/nO7z0X9dHTQjbeaGiIgILVu2TDt27FDVqlX11VdfqW/fvhlavffvybLZbJbJZNLatWvTPJesPv8I4PEhKQRgM6VLl9amTZuUlJRk9UvDsWPHUtUtWLBgmlOpHowSPFC2bFmtX79eV65cSXe08Ouvv1ZycrK++uorq7/QpzXFKaMjcqVLl7bE/ve/tB87dsyyPzOWL18uNzc3rV+/Xq6urpbyhQsXZrqtR7l3756k++80k6RDhw7p+PHjWrRokeWdhpK0YcMGq+PKlCkj6f600IyYOnWq8uXLp759+6pAgQLq0qWLZd+Da3TixAk988wzVrElJiam+kU6LZm5Dxn9TmXUg7Z/+eWXVPvS+k7/3ZYtW/T7779rxYoVatSokaX8t99+y1I8D2I6fPiwDMOw+i5nJB5bOHHiRKpYjx8/LknpjhZn9mcvIiJC06ZN09dff621a9fKz89P4eHhOXYOfn5+KlCggFJSUqxG5LMrO7MD0tKiRQv5+flpyZIlql+/vm7duqVu3bqlWfeXX36xGpU/ceKEzGaz5Z6ULVtWhmHoiSeesIzsArAvPFMIwGaee+453bt3z+pVECkpKZo5c2aqumXLltXPP/+sS5cuWcoOHjyouLg4q3rt2rWTYRgaM2ZMqjYe/NX9wV+y//pX+OvXr6eZbHl6eqb5ioy/q1OnjooWLaq5c+daTfNcu3at4uPjs7RSqLOzs0wmk9XIVWJiolauXJnpth7l66+/liRVr17d0rdkfY0Mw9CMGTOsjvPz81OjRo20YMECnTp1ympfWqMcJpNJH374oV566SV1795dX331lWVfnTp1VLhwYc2bN8+SpEr3p7VldBpdZu5DRr9TGRUQEKAaNWpo0aJFVlM9N2zYoKNHjz7y+LSu+Z07dzR79uwsxSPd/xn73//+Z/Uak1u3bqU7rdHW/ve//1m9wuPGjRtavHixatSokebUUSnzP3sP3uP30Ucfafny5erUqZPV847Z5ezsrHbt2mn58uVp/rHkr9+3zPD09MzS887pyZcvnzp37qylS5cqNjZWVatWTfcPL++//77V5wf/jX6wym3btm3l7OysMWPGpPq5NwxDv//+e47FDSB3MFIIINesXbs21eIYktSgQQOVKVNGL7zwgho2bKg333xTiYmJlneSpfWLT8+ePTV9+nSFh4crKipKFy9e1Ny5c1W5cmWrZ6+eeeYZdevWTe+9955++eUXtWjRQmazWdu2bdMzzzyjfv366dlnn5WLi4teeOEFvfrqq0pKStK8efNUtGhRnTt3zqrf2rVra86cORo/frzKlSunokWLpvnMTf78+TV58mT16NFDjRs3VufOnS3L4gcFBaVa+j0jWrVqpenTp6tFixbq0qWLLl68qPfff1/lypWzem4ss44fP66PP/5Y0v0EYefOnVq0aJHKlStnGSmoVKmSypYtqyFDhujs2bPy9vbW8uXL00zO3nvvPT311FOqVauWXnnlFT3xxBNKTEzU6tWrdeDAgVT1nZyc9PHHH6tNmzbq0KGD1qxZoyZNmsjFxUWjR49W//791aRJE3Xo0EGJiYmKjY1V2bJlMzRSkpn7kNHvVGZER0erVatWeuqpp9SzZ09duXJFM2fOVOXKlS2jsOlp0KCBChYsqO7du2vAgAEymUz673//m60phL1799asWbMUERGhffv2KSAgQP/973/l4eGRqXYe9bOcUypUqKCoqCjt2bNHxYoV04IFC3ThwoWHjo5n5WcvIiJCQ4YMkaRceaH7pEmTtHnzZtWvX1+9e/dWSEiIrly5ov3792vjxo2p3tGYEbVr19bnn3+uwYMHq27duvLy8rI8/5tVEREReu+997R582ZNnjw53Xq//fabXnzxRbVo0UI//PCDPv74Y3Xp0sXyR6SyZctq/PjxGj58uOU1MgUKFNBvv/2mL7/8Uq+88orlegPIox7bOqcAHMbDlrHX35Zu//33341u3boZ3t7eho+Pj9GtWzfjxx9/TFXPMAzj448/NsqUKWO4uLgYNWrUMNavX5/q9QGGcf+1FlOnTjUqVapkuLi4GH5+fkbLli2Nffv2Wep89dVXRrVq1Qw3NzcjKCjImDx5srFgwQJDkvHbb79Z6p0/f95o1aqVUaBAAavXIvx9WfwHPv/8c6NmzZqGq6urUahQIaNr167GmTNnrOp0797d8PT0THXdHiz//lfz5883ypcvb7i6uhqVKlUyFi5cmGa9rL6SwtnZ2ShZsqTxyiuvGBcuXLCqe/ToUaNZs2aGl5eXUaRIEaN3797GwYMH07w3hw8fNv71r38Zvr6+hpubm1GxYkVjxIgRqc7t0qVLlrJbt24ZjRs3Nry8vKyW+H/vvfeM0qVLG66urka9evWMuLg4o3bt2kaLFi0sdR5c/2XLlqV5nhm5D4aRse/Ug9ctTJ06Nc3r+del/g3DMJYvX24EBwcbrq6uRkhIiLFixYo0v6dpiYuLM5588knD3d3dKF68uDF06FDLKw/++l1r3LixUbly5VTHp9XPyZMnjRdffNHw8PAwihQpYgwcONBYt25dtl9J8dfvQXrXKL379KDdPXv2WMpKly5ttGrVyli/fr1RrVo1y3f+78dm52fvgXPnzhnOzs5GhQoV0tyf3vV9EOPfSTJef/11q7ILFy4Yr7/+uhEYGGjkz5/f8Pf3N5o2bWp8+OGHj7w+D67nX3/OkpKSjC5duhi+vr4ZfsWJYaT9Soq/qly5suHk5JTmtXrwc3v06FHjpZdeMgoUKGAULFjQ6Nevn9XrPx5Yvny58dRTTxmenp6Gp6enUalSJeP11183jh07lqFYAdiOyTBs+EQ6AACPYDab5efnp7Zt22revHm2Dge5JCgoSFWqVNE333yT631dvnxZAQEBGjlypEaMGJHr/eVlNWvWVKFChbRp06ZU+0aPHq0xY8bo0qVLKlKkiA2iA/C48EwhACDPuH37dqrpkosXL9aVK1cUFhZmm6DwjxMbG6uUlJR0F1ZxFHv37tWBAwesFpMC4Jh4phAAkGfs3LlTb7zxhtq3b6/ChQtr//79mj9/vqpUqaL27dvbOjzYue+++05Hjx7VhAkT1KZNm3RXNP2nO3z4sPbt26dp06YpICBAHTt2tHVIAGyMpBAAkGcEBQUpMDBQ7733nuW1IhEREZo0aZJcXFxsHR7s3NixY7Vjxw41bNgwzVWOHcUXX3yhsWPHqmLFivr000/l5uZm65AA2BjPFAIAAACAA+OZQgAAAABwYCSFAAAAAODASAoBAAAAwIGx0AzyjOTDG2wdgt1x8i9r6xDs0s3+UbYOwe54Tp9t6xDs0oz6E2wdgt15fWJpW4dgly68s9vWIdidvlfy2zoEu7Tm1Bpbh5Cmu5d/tXUI6cpfpIytQ3gkRgoBAAAAII94//33FRQUJDc3N9WvX1+7d6f/R5+wsDCZTKZUW6tWrTLVJ0khAAAAAOQBn3/+uQYPHqxRo0Zp//79ql69usLDw3Xx4sU0669YsULnzp2zbIcPH5azs3Om3+1LUggAAADAvplT8u6WCdOnT1fv3r3Vo0cPhYSEaO7cufLw8NCCBQvSrF+oUCH5+/tbtg0bNsjDw4OkEAAAAADyiuTkZN24ccNqS05OTlXvzp072rdvn5o1a2Ypc3JyUrNmzfTDDz9kqK/58+erU6dO8vT0zFSMJIUAAAAAkEuio6Pl4+NjtUVHR6eqd/nyZaWkpKhYsWJW5cWKFdP58+cf2c/u3bt1+PBh9erVK9MxsvooAAAAAPtmmG0dQbqGDx+uwYMHW5W5urrmeD/z589X1apVVa9evUwfS1IIAAAAALnE1dU1Q0lgkSJF5OzsrAsXLliVX7hwQf7+/g899ubNm/rss880duzYLMXI9FEAAAAAsDEXFxfVrl1bmzZtspSZzWZt2rRJoaGhDz122bJlSk5O1ssvv5ylvhkpBAAAAGDfzHl3+mhmDB48WN27d1edOnVUr149xcTE6ObNm+rRo4ckKSIiQiVKlEj1TOL8+fPVpk0bFS5cOEv9khQCAAAAQB7QsWNHXbp0SSNHjtT58+dVo0YNrVu3zrL4zKlTp+TkZD3Z89ixY9q+fbu+/fbbLPdLUggAAAAAeUS/fv3Ur1+/NPdt2bIlVVnFihVlGEa2+iQpBAAAAGDXjDy8+qg9YKEZAAAAAHBgJIUAAAAA4MCYPgoAAADAvv1DVh+1FUYKAQAAAMCBkRQCAAAAgANj+igAAAAA+8bqo9nCSCEAAAAAODCSQgAAAABwYEwfBQAAAGDfzCm2jsCuMVIIAAAAAA6MpBAAAAAAHBjTRwEAAADYN1YfzRZGCgEAAADAgZEUAgAAAIADY/ooAAAAAPtmZvpodjBSCAAAAAAOjKQQAAAAABwY00cBAAAA2DWD1UezhZFCAAAAAHBgJIUAAAAA4MCYPgoAAADAvrH6aLYwUggAAAAADoykEAAAAAAc2D8iKYyMjFSbNm1sHYZGjx6tGjVqZOqYW7duqV27dvL29pbJZNK1a9ceeUxiYqJMJpMOHDggSdqyZUuGj/07k8mklStXZvo4AAAAIM8wzHl3swM5lhRGRkbKZDKl2lq0aJFTXfwjLVq0SNu2bdOOHTt07tw5+fj45Eo/6SWs586dU8uWLXOlTwAAAAB5X44uNNOiRQstXLjQqszV1TUnu/jHSUhIUHBwsKpUqWKT/v39/W3SLwAAAIC8IUenj7q6usrf399qK1iwoGW/yWTSBx98oOeff14eHh4KDg7WDz/8oBMnTigsLEyenp5q0KCBEhISLMc8GOH64IMPFBgYKA8PD3Xo0EHXr19PN47k5GQNGDBARYsWlZubm5566int2bNHkmQYhsqVK6d33nnH6pgDBw7IZDLpxIkTkqRr166pV69e8vPzk7e3t5o0aaKDBw9aHTNp0iQVK1ZMBQoUUFRUlG7fvp2p6xUWFqZp06bp+++/l8lkUlhYmOU6/X1Kp6+vr2JjYzPV/gOxsbEaM2aMDh48aBnBfdDWX/t6MC116dKlevrpp+Xu7q66devq+PHj2rNnj+rUqSMvLy+1bNlSly5dsurjo48+UnBwsNzc3FSpUiXNnj07S7ECAAAAmWZOybubHXjszxSOGzdOEREROnDggCpVqqQuXbro1Vdf1fDhw7V3714ZhqF+/fpZHXPixAktXbpUX3/9tdatW6cff/xRffv2TbePoUOHavny5Vq0aJH279+vcuXKKTw8XFeuXJHJZFLPnj1TjWguXLhQjRo1Urly5SRJ7du318WLF7V27Vrt27dPtWrVUtOmTXXlyhVJ0tKlSzV69GhNnDhRe/fuVUBAQKYToRUrVqh3794KDQ3VuXPntGLFikwdn1EdO3bUv//9b1WuXFnnzp3TuXPn1LFjx3Trjxo1Sm+//bb279+vfPnyqUuXLho6dKhmzJihbdu26cSJExo5cqSl/pIlSzRy5EhNmDBB8fHxmjhxokaMGKFFixblyvkAAAAAyDk5mhR+88038vLystomTpxoVadHjx7q0KGDKlSooGHDhikxMVFdu3ZVeHi4goODNXDgQG3ZssXqmNu3b2vx4sWqUaOGGjVqpJkzZ+qzzz7T+fPnU8Vw8+ZNzZkzR1OnTlXLli0VEhKiefPmyd3dXfPnz5d0//nHY8eOaffu3ZKku3fv6pNPPlHPnj0lSdu3b9fu3bu1bNky1alTR+XLl9c777wjX19fffHFF5KkmJgYRUVFKSoqShUrVtT48eMVEhKSqetVqFAheXh4yMXFRf7+/ipUqFCmjs8od3d3eXl5KV++fJYRXHd393TrDxkyxOp+7Nu3TyNGjFDDhg1Vs2ZNRUVFafPmzZb6o0aN0rRp09S2bVs98cQTatu2rd544w198MEHuXI+AAAAAHJOjj5T+Mwzz2jOnDlWZX9PdKpVq2b5d7FixSRJVatWtSq7ffu2bty4IW9vb0lSqVKlVKJECUud0NBQmc1mHTt2LNUzcQkJCbp7964aNmxoKcufP7/q1aun+Ph4SVLx4sXVqlUrLViwQPXq1dPXX3+t5ORktW/fXpJ08OBBJSUlqXDhwlZt//nnn5aprfHx8erTp4/V/tDQUKtkyVa8vLws/3755Zc1d+7cTB2fkXt08eJFSfeT8ISEBEVFRal3796WOvfu3XvoojnJyclKTk62LrxzR64uLpmKFQAAALCXVT7zqhxNCj09PS3TL9OTP39+y79NJlO6ZWZz7t7YXr16qVu3bnr33Xe1cOFCdezYUR4eHpKkpKQkBQQEpBqxlO4/25fbTCaTDMOwKrt7926Gj3/wqgpJlsQ6MzJyjx7cn6SkJEnSvHnzVL9+fat2nJ2d0+0jOjpaY8aMsSp767WXNaJvRKbjBQAAAJB1OZoU5pZTp07pf//7n4oXLy5J2rlzp5ycnFSxYsVUdcuWLSsXFxfFxcWpdOnSku4nVHv27NGgQYMs9Z577jl5enpqzpw5Wrdunb7//nvLvlq1aun8+fPKly+fgoKC0owpODhYu3btUkTE/yUxO3fuzIGzlfz8/HTu3DnL519++UW3bt3K8PFpJeYuLi5KScn5B12LFSum4sWL69dff1XXrl0zfNzw4cM1ePBg68IT23I4OgAAAACPkqNJYXJycqrn/PLly6ciRYpkq103Nzd1795d77zzjm7cuKEBAwaoQ4cOab5OwdPTU6+99pr+85//qFChQipVqpSmTJmiW7duKSoqylLP2dlZkZGRGj58uMqXL6/Q0FDLvmbNmik0NFRt2rTRlClTVKFCBf3vf//T6tWr9a9//Ut16tTRwIEDFRkZqTp16qhhw4ZasmSJjhw5ojJlymTrXCWpSZMmmjVrlkJDQ5WSkqJhw4ZZjdRlRVBQkH777TcdOHBAJUuWVIECBXLsdSFjxozRgAED5OPjoxYtWig5OVl79+7V1atXUyd+/z9XV9dU/SczdRQAAABZkcuzDP/pcnShmXXr1ikgIMBqe+qpp7Ldbrly5dS2bVs999xzevbZZ1WtWrWHrvQ5adIktWvXTt26dVOtWrV04sQJrV+/3ur1GJIUFRWlO3fuqEePHlblJpNJa9asUaNGjdSjRw9VqFBBnTp10smTJy3P2HXs2FEjRozQ0KFDVbt2bZ08eVKvvfaaVTtbtmyRyWRSYmJips532rRpCgwM1NNPP60uXbpoyJAhlqmtWdWuXTu1aNFCzzzzjPz8/PTpp59mq72/6tWrlz766CMtXLhQVatWVePGjRUbG6snnngix/oAAAAAkDtMxt8fXstjRo8erZUrV1o9J5dTtm3bpqZNm+r06dOWZC8nLVy4UBMnTtTRo0ezPdLnCJIPb7B1CHbHyb+srUOwSzf7Rz26Eqx4Tufdo1kxo/4EW4dgd16fWNrWIdilC+/stnUIdqfvFX43y4o1p9bYOoQ0JR/ZZOsQ0uVauamtQ3gku3imMKclJyfr0qVLGj16tNq3b58rCaEkrVmzRhMnTiQhBAAAAHITq49mi0MmhZ9++qmioqJUo0YNLV68ONf6WbZsWa61DQAAAAA5IUefKcwNo0ePzvGpo5GRkUpJSdG+ffus3n8IAAAAAI7GIUcKAQAAAPyDsPpotuT5kUIAAAAAQO4hKQQAAAAAB8b0UQAAAAB2zTBSbB2CXWOkEAAAAAAcGEkhAAAAADgwpo8CAAAAsG+8vD5bGCkEAAAAAAdGUggAAAAADozpowAAAADsGy+vzxZGCgEAAADAgZEUAgAAAIADY/ooAAAAAPvG6qPZwkghAAAAADgwkkIAAAAAcGBMHwUAAABg38wpto7ArjFSCAAAAAAOjKQQAAAAABwY00cBAAAA2DdWH80WRgoBAAAAwIGRFAIAAACAA2P6KAAAAAD7Zmb6aHYwUggAAAAADoykEAAAAAAcGNNHAQAAANg3Vh/NFkYKAQAAAMCBkRQCAAAAgANj+igAAAAA+8bqo9nCSCEAAAAAODCSQgAAAABwYEwfBQAAAGDfmD6aLYwUAgAAAIADIykEAAAAAAfG9FEAAAAAds0wUmwdgl0zGYZh2DoIQJL8fYNtHYLd4cc3a7zye9g6BLtz896ftg7BLhVx9bF1CHaH7xoel7skEVly5sphW4eQpj+/j7V1COlybxRp6xAeiemjAAAAAODAmD4KAAAAwL6x+mi2MFIIAAAAAA6MpBAAAAAAHBjTRwEAAADYN4Ppo9nBSCEAAAAAODCSQgAAAABwYEwfBQAAAGDfWH00WxgpBAAAAAAHRlIIAAAAAA6M6aMAAAAA7Burj2YLI4UAAAAA4MBICgEAAADAgTF9FAAAAIB9Y/XRbGGkEAAAAAAcGEkhAAAAADgwpo8CAAAAsG+sPpotjBQCAAAAgAMjKQQAAAAAB8b0UQAAAAD2jdVHs4WRQgAAAABwYCSFAAAAAODAmD4KAAAAwL4xfTRbGCkEAAAAAAdGUggAAAAADoykEAAAAIB9M8x5d8uk999/X0FBQXJzc1P9+vW1e/fuh9a/du2aXn/9dQUEBMjV1VUVKlTQmjVrMtUnzxQCAAAAQB7w+eefa/DgwZo7d67q16+vmJgYhYeH69ixYypatGiq+nfu3FHz5s1VtGhRffHFFypRooROnjwpX1/fTPVLUggAAAAAecD06dPVu3dv9ejRQ5I0d+5crV69WgsWLNCbb76Zqv6CBQt05coV7dixQ/nz55ckBQUFZbpfpo8CAAAAsG9mc57dkpOTdePGDastOTk51SncuXNH+/btU7NmzSxlTk5OatasmX744Yc0T/urr75SaGioXn/9dRUrVkxVqlTRxIkTlZKSkqnLR1IIAAAAALkkOjpaPj4+Vlt0dHSqepcvX1ZKSoqKFStmVV6sWDGdP38+zbZ//fVXffHFF0pJSdGaNWs0YsQITZs2TePHj89UjEwfBQAAAIBcMnz4cA0ePNiqzNXVNUfaNpvNKlq0qD788EM5Ozurdu3aOnv2rKZOnapRo0ZluB2SQgAAAAD2LQurfD4urq6uGUoCixQpImdnZ124cMGq/MKFC/L390/zmICAAOXPn1/Ozs6WsuDgYJ0/f1537tyRi4tLhmJk+igAAAAA2JiLi4tq166tTZs2WcrMZrM2bdqk0NDQNI9p2LChTpw4IbP5/5Li48ePKyAgIMMJoURSCAAAAAB5wuDBgzVv3jwtWrRI8fHxeu2113Tz5k3LaqQREREaPny4pf5rr72mK1euaODAgTp+/LhWr16tiRMn6vXXX89Uv0wfBQAAAGDfzHl3+mhmdOzYUZcuXdLIkSN1/vx51ahRQ+vWrbMsPnPq1Ck5Of3fuF5gYKDWr1+vN954Q9WqVVOJEiU0cOBADRs2LFP9mgzDMHL0TIAs8vcNtnUIdocf36zxyu9h6xDszs17f9o6BLtUxNXH1iHYHb5reFzuGplbsh/3nbly2NYhpOnPLyfZOoR0uf8r9fsF8xq7mT4aGRmpNm3a2DoMjR49WjVq1LB1GDkmLCxMgwYNsnUYAAAAAGwkU0lhZGSkTCZTqq1Fixa5FR8eIaPJ8pYtW2QymXTt2jWr8hUrVmjcuHG5ExwAAADwOBjmvLvZgUw/U9iiRQstXLjQqiyn3rOBjEtJSZHJZMp2O4UKFcqBaAAAAADYq0xPH3V1dZW/v7/VVrBgQct+k8mkDz74QM8//7w8PDwUHBysH374QSdOnFBYWJg8PT3VoEEDJSQkWI55MCXzgw8+UGBgoDw8PNShQwddv3493TiSk5M1YMAAFS1aVG5ubnrqqae0Z88eSfefsypXrpzeeecdq2MOHDggk8mkEydOSJKuXbumXr16yc/PT97e3mrSpIkOHjxodcykSZNUrFgxFShQQFFRUbp9+3ZmL5mCgoI0btw4de7cWZ6enipRooTef/99qzrTp09X1apV5enpqcDAQPXt21dJSUmW/bGxsfL19dVXX32lkJAQubq6qmfPnlq0aJFWrVplGbXdsmVLqv4TExP1zDPPSJIKFiwok8mkyMhISamnjwYFBWn8+PGKiIiQl5eXSpcura+++kqXLl1S69at5eXlpWrVqmnv3r1WfWzfvl1PP/203N3dFRgYqAEDBujmzZuZvlYAAAAAHq9ceaZw3LhxioiI0IEDB1SpUiV16dJFr776qoYPH669e/fKMAz169fP6pgTJ05o6dKl+vrrr7Vu3Tr9+OOP6tu3b7p9DB06VMuXL9eiRYu0f/9+lStXTuHh4bpy5YpMJpN69uyZakRz4cKFatSokcqVKydJat++vS5evKi1a9dq3759qlWrlpo2baorV65IkpYuXarRo0dr4sSJ2rt3rwICAjR79uwsXZOpU6eqevXq+vHHH/Xmm29q4MCB2rBhg2W/k5OT3nvvPR05ckSLFi3Sd999p6FDh1q1cevWLU2ePFkfffSRjhw5ovfee08dOnRQixYtdO7cOZ07d04NGjRI1XdgYKCWL18uSTp27JjOnTunGTNmpBvru+++q4YNG+rHH39Uq1at1K1bN0VEROjll1/W/v37VbZsWUVERFgWOUlISFCLFi3Url07/fTTT/r888+1ffv2VPcYAAAAyBVmc97d7ECmk8JvvvlGXl5eVtvEiROt6vTo0UMdOnRQhQoVNGzYMCUmJqpr164KDw9XcHCwBg4cmGpE6/bt21q8eLFq1KihRo0aaebMmfrss890/vz5VDHcvHlTc+bM0dSpU9WyZUuFhIRo3rx5cnd31/z58yXdf9bu2LFj2r17tyTp7t27+uSTT9SzZ09J90e2du/erWXLlqlOnToqX7683nnnHfn6+uqLL76QJMXExCgqKkpRUVGqWLGixo8fr5CQkMxeMkn3Xyz55ptvqkKFCurfv79eeuklvfvuu5b9gwYN0jPPPKOgoCA1adJE48eP19KlS63auHv3rmbPnq0GDRqoYsWK8vb2lru7u9XobVovqXR2drZMEy1atKj8/f3l45P+injPPfecXn31VZUvX14jR47UjRs3VLduXbVv395yT+Pj43XhwgVJUnR0tLp27apBgwapfPnyatCggd577z0tXrw43ZHV5ORk3bhxw2oz7GTONQAAAPBPkumk8JlnntGBAwestj59+ljVqVatmuXfD96pUbVqVauy27dv68aNG5ayUqVKqUSJEpbPoaGhMpvNOnbsWKoYEhISdPfuXTVs2NBSlj9/ftWrV0/x8fGSpOLFi6tVq1ZasGCBJOnrr79WcnKy2rdvL0k6ePCgkpKSVLhwYasE97fffrNMbY2Pj1f9+vWt+g4NDc3E1Ur/uNDQUEuskrRx40Y1bdpUJUqUUIECBdStWzf9/vvvunXrlqWOi4uL1bVNT8uWLS3nU7ly5UzHmpH7J0kXL16UdP9axsbGWl3H8PBwmc1m/fbbb2n2ER0dLR8fH6vtZvLvmY4VAAAAQPZkeqEZT09Py/TL9OTPn9/y7weLoaRVZs7l4dRevXqpW7duevfdd7Vw4UJ17NhRHh7330+WlJSkgICANJ/B8/X1zdW4/i4xMVHPP/+8XnvtNU2YMEGFChXS9u3bFRUVpTt37lhidnd3z9DiMh999JH+/PP+e57+et0zKrP3LykpSa+++qoGDBiQqq1SpUql2cfw4cM1ePBgq7LygXUzHSsAAABgL9M086pMJ4W55dSpU/rf//6n4sWLS5J27twpJycnVaxYMVXdsmXLysXFRXFxcSpdurSk+1Mr9+zZY7VoynPPPSdPT0/NmTNH69at0/fff2/ZV6tWLZ0/f1758uVTUFBQmjEFBwdr165dioiIsJTt3LkzS+f39+N27typ4OD7L2vft2+fzGazpk2bJien+4O3f586mh4XFxelpFi/fPWvI65/rScpVd2cUKtWLR09evSRfyz4K1dX11Sr1ppMdvPaTAAAAOAfI9O/hScnJ+v8+fNW2+XLl7MdiJubm7p3766DBw9q27ZtGjBggDp06CB/f/9UdT09PfXaa6/pP//5j9atW6ejR4+qd+/eunXrlqKioiz1nJ2dFRkZqeHDh6t8+fJWUzibNWum0NBQtWnTRt9++60SExO1Y8cOvfXWW5aVNQcOHKgFCxZo4cKFOn78uEaNGqUjR45k6fzi4uI0ZcoUHT9+XO+//76WLVumgQMHSpLKlSunu3fvaubMmfr111/13//+V3Pnzs1Qu0FBQfrpp5907NgxXb58WXfv3k2zXunSpWUymfTNN9/o0qVLViubZtewYcO0Y8cO9evXTwcOHNAvv/yiVatWsdAMAAAAYAcynRSuW7dOAQEBVttTTz2V7UDKlSuntm3b6rnnntOzzz6ratWqPXSlz0mTJqldu3bq1q2batWqpRMnTmj9+vVWr8eQZJmC2aNHD6tyk8mkNWvWqFGjRurRo4cqVKigTp066eTJk5Zn5jp27KgRI0Zo6NChql27tk6ePKnXXnvNqp0HL4VPTEx86Pn9+9//1t69e1WzZk2NHz9e06dPV3h4uCSpevXqmj59uiZPnqwqVapoyZIlio6OztB16927typWrKg6derIz89PcXFxadYrUaKExowZozfffFPFihXL0YStWrVq2rp1q44fP66nn35aNWvW1MiRIy2jvgAAAECuMoy8u9kBk2HYPtLRo0dr5cqVOnDgQI63vW3bNjVt2lSnT5+2JHs5aeHChZo4caKOHj2a7vN7QUFBGjRokNXUVqTm7xts6xDsTh748bVLXvk9bB2C3bl5709bh2CXirimv9Iz0sZ3DY/LXSPnH6lxBGeuHLZ1CGn68/Mxtg4hXe4dR9k6hEfKM88U5rTk5GRdunRJo0ePVvv27XMlIZSkNWvWaOLEiVla0AUAAAAAbO0fmxR++umnioqKUo0aNbR48eJc62fZsmW51jYAAACADGD10WzJE9NHAYnpo1nBj2/WMH0085jSlzVMH808vmt4XJg+mjV5dvrop3l3iqZ757w7tfUB3gEAAAAAAA7sHzt9FAAAAICDYPpotjBSCAAAAAAOjKQQAAAAABwY00cBAAAA2DeD6aPZwUghAAAAADgwkkIAAAAAcGBMHwUAAABg31h9NFsYKQQAAAAAB0ZSCAAAAAAOjOmjAAAAAOybYdg6ArvGSCEAAAAAODCSQgAAAABwYEwfBQAAAGDfWH00WxgpBAAAAAAHRlIIAAAAAA6M6aMAAAAA7BvTR7OFkUIAAAAAcGAkhQAAAADgwJg+CgAAAMC+GUwfzQ5GCgEAAADAgZEUAgAAAIADY/ooAAAAALtmmA1bh2DXGCkEAAAAAAdGUggAAAAADozpowAAAADsGy+vzxZGCgEAAADAgZEUAgAAAIADY/ooAAAAAPvGy+uzhZFCAAAAAHBgJIUAAAAA4MCYPgoAAADAvvHy+mxhpBAAAAAAHBhJIQAAAAA4MKaPIs+4fOuGrUOAg/j9zz9sHYLdcTKZbB2CXbp6O8nWIdidFF5AnSVlfAJsHYLduX77lq1DQE7ivx3ZwkghAAAAADgwkkIAAAAAcGBMHwUAAABg35g+mi2MFAIAAACAAyMpBAAAAAAHxvRRAAAAAPbN4OX12cFIIQAAAAA4MJJCAAAAAHBgTB8FAAAAYN9YfTRbGCkEAAAAAAdGUggAAAAADozpowAAAADsm5nVR7ODkUIAAAAAcGAkhQAAAADgwJg+CgAAAMC+Gaw+mh2MFAIAAACAAyMpBAAAAAAHxvRRAAAAAPaN1UezhZFCAAAAAHBgJIUAAAAA4MCYPgoAAADArhlmVh/NDkYKAQAAAMCBkRQCAAAAgANj+igAAAAA+8bqo9nCSCEAAAAAODCSQgAAAABwYEwfBQAAAGDfDFYfzQ5GCgEAAADAgZEUAgAAAIADY/ooAAAAAPvG6qPZwkghAAAAADgwkkIAAAAAcGBMHwUAAABg38ysPpodjBQCAAAAgAMjKQQAAAAAB+aQSeGHH36owMBAOTk5KSYmxtbhAAAAAMgOs5F3Nztgk6QwMjJSbdq0sUXXunHjhvr166dhw4bp7NmzeuWVV2wSx8Nk9PqEhYVp0KBBuR4PAAAAgH+uf8xI4Z07dzJU79SpU7p7965atWqlgIAAeXh4ZKm/u3fvZuk4AAAAAMhL8mRSGBsbK19fX61cuVLly5eXm5ubwsPDdfr0aUud0aNHq0aNGvroo4/0xBNPyM3NTZJ07do19erVS35+fvL29laTJk108OBBS7tVq1aVJJUpU0Ymk0mJiYmSpFWrVqlWrVpyc3NTmTJlNGbMGN27d8/Sn8lk0pw5c/Tiiy/K09NTEyZMSDP2oKAgTZw4UT179lSBAgVUqlQpffjhh1Z1Dh06pCZNmsjd3V2FCxfWK6+8oqSkJMt5LVq0SKtWrZLJZJLJZNKWLVtS9RMZGamtW7dqxowZlnoPzmXr1q2qV6+eXF1dFRAQoDfffNPqXP7u5MmTeuGFF1SwYEF5enqqcuXKWrNmjSQpJSVFUVFReuKJJ+Tu7q6KFStqxowZlmO///575c+fX+fPn7dqc9CgQXr66afT7RMAAADIMYY57252IE8mhZJ069YtTZgwQYsXL1ZcXJyuXbumTp06WdU5ceKEli9frhUrVujAgQOSpPbt2+vixYtau3at9u3bp1q1aqlp06a6cuWKOnbsqI0bN0qSdu/erXPnzikwMFDbtm1TRESEBg4cqKNHj+qDDz5QbGxsqsRv9OjR+te//qVDhw6pZ8+e6cY+bdo01alTRz/++KP69u2r1157TceOHZMk3bx5U+Hh4SpYsKD27NmjZcuWaePGjerXr58kaciQIerQoYNatGihc+fO6dy5c2rQoEGqPmbMmKHQ0FD17t3bUi8wMFBnz57Vc889p7p16+rgwYOaM2eO5s+fr/Hjx6cb7+uvv67k5GR9//33OnTokCZPniwvLy9JktlsVsmSJbVs2TIdPXpUI0eO1P/7f/9PS5culSQ1atRIZcqU0X//+19Le3fv3tWSJUseeo0AAAAA5A159j2Fd+/e1axZs1S/fn1J0qJFixQcHKzdu3erXr16ku5PGV28eLH8/PwkSdu3b9fu3bt18eJFubq6SpLeeecdrVy5Ul988YVeeeUVFS5cWJLk5+cnf39/SdKYMWP05ptvqnv37pLujyKOGzdOQ4cO1ahRoywxdenSRT169Hhk7M8995z69u0rSRo2bJjeffddbd68WRUrVtQnn3yi27dva/HixfL09JQkzZo1Sy+88IImT56sYsWKyd3dXcnJyZb40uLj4yMXFxd5eHhY1Zs9e7YCAwM1a9YsmUwmVapUSf/73/80bNgwjRw5Uk5Oqf8OcOrUKbVr185qFPWB/Pnza8yYMZbPTzzxhH744QctXbpUHTp0kCRFRUVp4cKF+s9//iNJ+vrrr3X79m3LfgAAAAB5V54dKcyXL5/q1q1r+VypUiX5+voqPj7eUla6dGlLQihJBw8eVFJSkgoXLiwvLy/L9ttvvykhISHdvg4ePKixY8daHfNgBO7WrVuWenXq1MlQ7NWqVbP822Qyyd/fXxcvXpQkxcfHq3r16paEUJIaNmwos9lsGU3Mjvj4eIWGhspkMlm1n5SUpDNnzqR5zIABAzR+/Hg1bNhQo0aN0k8//WS1//3331ft2rXl5+cnLy8vffjhhzp16pRlf2RkpE6cOKGdO3dKuj9Nt0OHDlbn+HfJycm6ceOG1WYY9rE6EwAAAPIYW68wauerj+bZkcKM+HvSkZSUpICAgDSfwfP19U23naSkJI0ZM0Zt27ZNte/Bs4pp9Zee/PnzW302mUwym/PufOJevXopPDxcq1ev1rfffqvo6GhNmzZN/fv312effaYhQ4Zo2rRpCg0NVYECBTR16lTt2rXLcnzRokX1wgsvaOHChXriiSe0du3aNO/BX0VHR1uNQEqSyclLJmfv3DhFAAAAAOnIs0nhvXv3tHfvXstU0WPHjunatWsKDg5O95hatWrp/Pnzypcvn4KCgjLcV61atXTs2DGVK1cuu2E/UnBwsGJjY3Xz5k1LkhkXFycnJydVrFhRkuTi4qKUlJRHtpVWveDgYC1fvlyGYVhGC+Pi4lSgQAGVLFky3bYCAwPVp08f9enTR8OHD9e8efPUv39/xcXFqUGDBpbpsJLSHHXt1auXOnfurJIlS6ps2bJq2LDhQ2MfPny4Bg8ebFVWsHClR54zAAAAgJyVZ6eP5s+fX/3799euXbu0b98+RUZG6sknn7QkiWlp1qyZQkND1aZNG3377bdKTEzUjh079NZbb2nv3r3pHjdy5EgtXrxYY8aM0ZEjRxQfH6/PPvtMb7/9do6fV9euXeXm5qbu3bvr8OHD2rx5s/r3769u3bqpWLFiku6vYPrTTz/p2LFjunz5crqvvwgKCtKuXbuUmJioy5cvy2w2q2/fvjp9+rT69++vn3/+WatWrdKoUaM0ePDgNJ8nlO6vFLp+/Xr99ttv2r9/vzZv3mxJvsuXL6+9e/dq/fr1On78uEaMGKE9e/akaiM8PFze3t4aP358hp67dHV1lbe3t9X21ymvAAAAQEYZZnOe3exBnk0KPTw8NGzYMHXp0kUNGzaUl5eXPv/884ceYzKZtGbNGjVq1Eg9evRQhQoV1KlTJ508edKScKUlPDxc33zzjb799lvVrVtXTz75pN59912VLl06p09LHh4eWr9+va5cuaK6devqpZdeUtOmTTVr1ixLnd69e6tixYqqU6eO/Pz8FBcXl2ZbQ4YMkbOzs0JCQuTn56dTp06pRIkSWrNmjXbv3q3q1aurT58+ioqKemiCm5KSotdff13BwcFq0aKFKlSooNmzZ0uSXn31VbVt21YdO3ZU/fr19fvvv1uNGj7g5OSkyMhIpaSkKCIiIptXCQAAAMDjYjLy4OoesbGxGjRokK5du2brUJAJUVFRunTpkr766qssHZ/PpUQORwQgpzgxkp8lzIDIvBQ7+at6XlPGJ8DWIdidy7ev2zoEu3Tlj19sHUKakoa3s3UI6fKKXm7rEB4pzz5TCPtx/fp1HTp0SJ988kmWE0IAAAAgy+xklc+8iqQQ2da6dWvt3r1bffr0UfPmzW0dDgAAAIBMyJPPFEZGRjJ11I5s2bJFt27d0rvvvmvrUAAAAAC79v777ysoKEhubm6qX7++du/enW7d2NhYmUwmq+2vr9TLKEYKAQAAANi3f8j00c8//1yDBw/W3LlzVb9+fcXExCg8PFzHjh1T0aJF0zzG29tbx44ds3zOyvPseXKkEAAAAAAczfTp09W7d2/16NFDISEhmjt3rjw8PLRgwYJ0jzGZTPL397dsD3vrQnpICgEAAAAglyQnJ+vGjRtWW3Jycqp6d+7c0b59+9SsWTNLmZOTk5o1a6Yffvgh3faTkpJUunRpBQYGqnXr1jpy5EimYyQpBAAAAGDfDHOe3aKjo+Xj42O1RUdHpzqFy5cvKyUlJdVIX7FixXT+/Pk0T7tixYpasGCBVq1apY8//lhms1kNGjTQmTNnMnX5eKYQAAAAAHLJ8OHDNXjwYKsyV1fXHGk7NDRUoaGhls8NGjRQcHCwPvjgA40bNy7D7ZAUAgAAAEAucXV1zVASWKRIETk7O+vChQtW5RcuXJC/v3+G+sqfP79q1qypEydOZCpGpo8CAAAAsG9mI+9uGeTi4qLatWtr06ZN/3daZrM2bdpkNRr4MCkpKTp06JACAgIydfkYKQQAAACAPGDw4MHq3r276tSpo3r16ikmJkY3b95Ujx49JEkREREqUaKE5ZnEsWPH6sknn1S5cuV07do1TZ06VSdPnlSvXr0y1S9JIQAAAADkAR07dtSlS5c0cuRInT9/XjVq1NC6dessi8+cOnVKTk7/N9nz6tWr6t27t86fP6+CBQuqdu3a2rFjh0JCQjLVr8kwjH/Gmx5h9/K5lLB1CADS4ZSFF+Eiay8QdnQpZrOtQ7BLZXwyN1UM0uXb120dgl268scvtg4hTX8MesHWIaSrQMzXtg7hkXimEAAAAAAcGEkhAAAAADgwnikEAAAAYN8ysconUmOkEAAAAAAcGEkhAAAAADgwpo8CAAAAsG+sXJwtjBQCAAAAgAMjKQQAAAAAB8b0UQAAAAD2jdVHs4WRQgAAAABwYCSFAAAAAODAmD4KAAAAwL4xfTRbGCkEAAAAAAdGUggAAAAADozpowAAAADsmmEwfTQ7GCkEAAAAAAdGUggAAAAADozpowAAAADsG6uPZgsjhQAAAADgwEgKAQAAAMCBkRQCAAAAgAPjmUIAAAAA9o1nCrOFkUIAAAAAcGAkhQAAAADgwJg+CgAAAMCuGUwfzRaSQuQZYcWq2DoEu+Pt5GrrEOySB//py7Q/jDu2DsEuXTfftnUIdsfHyc3WIdilm8ZdW4dgd/xcvG0dApBnMH0UAAAAABwYfy4HAAAAYN+YPpotjBQCAAAAgAMjKQQAAAAAB8b0UQAAAAD2zWzrAOwbI4UAAAAA4MBICgEAAADAgTF9FAAAAIBd4+X12cNIIQAAAAA4MJJCAAAAAHBgJIU5yGQyaeXKlbYOI0NGjx6tGjVq2DoMAAAAIPvMRt7d7ABJ4f8vMjJSbdq0sXUYdi02Nla+vr62DgMAAABAJpAUAgAAAIADIylMQ1hYmAYMGKChQ4eqUKFC8vf31+jRo63q/PLLL2rUqJHc3NwUEhKiDRs2pGrn9OnT6tChg3x9fVWoUCG1bt1aiYmJlv0PRifHjBkjPz8/eXt7q0+fPrpz546ljtlsVnR0tJ544gm5u7urevXq+uKLLyz7t2zZIpPJpE2bNqlOnTry8PBQgwYNdOzYMatYJk2apGLFiqlAgQKKiorS7du3U8X70UcfKTg4WG5ubqpUqZJmz55t2ZeYmCiTyaQVK1bomWeekYeHh6pXr64ffvjBEkePHj10/fp1mUwmmUymVNcMAAAAyBXmPLzZAZLCdCxatEienp7atWuXpkyZorFjx1oSP7PZrLZt28rFxUW7du3S3LlzNWzYMKvj7969q/DwcBUoUEDbtm1TXFycvLy81KJFC6ukb9OmTYqPj9eWLVv06aefasWKFRozZoxlf3R0tBYvXqy5c+fqyJEjeuONN/Tyyy9r69atVv299dZbmjZtmvbu3at8+fKpZ8+eln1Lly7V6NGjNXHiRO3du1cBAQFWCZ8kLVmyRCNHjtSECRMUHx+viRMnasSIEVq0aFGqfoYMGaIDBw6oQoUK6ty5s+7du6cGDRooJiZG3t7eOnfunM6dO6chQ4Zk7yYAAAAAyHW8pzAd1apV06hRoyRJ5cuX16xZs7Rp0yY1b95cGzdu1M8//6z169erePHikqSJEyeqZcuWluM///xzmc1mffTRRzKZTJKkhQsXytfXV1u2bNGzzz4rSXJxcdGCBQvk4eGhypUra+zYsfrPf/6jcePG6e7du5o4caI2btyo0NBQSVKZMmW0fft2ffDBB2rcuLGlvwkTJlg+v/nmm2rVqpVu374tNzc3xcTEKCoqSlFRUZKk8ePHa+PGjVajhaNGjdK0adPUtm1bSdITTzyho0eP6oMPPlD37t0t9YYMGaJWrVpJksaMGaPKlSvrxIkTqlSpknx8fGQymeTv75+DdwIAAABAbiIpTEe1atWsPgcEBOjixYuSpPj4eAUGBloSQkmWpO2BgwcP6sSJEypQoIBV+e3bt5WQkGD5XL16dXl4eFi1k5SUpNOnTyspKUm3bt1S8+bNrdq4c+eOatasmW68AQEBkqSLFy+qVKlSio+PV58+fazqh4aGavPmzZKkmzdvKiEhQVFRUerdu7elzr179+Tj45OhfipVqiQAAADAFnh5ffaQFKYjf/78Vp9NJpPM5oxPCk5KSlLt2rW1ZMmSVPv8/Pwy3IYkrV69WiVKlLDa5+rqmm68D0YmMxrvg37mzZun+vXrW+1zdnbOsX4AAAAA5D0khVkQHBys06dP69y5c5bRsp07d1rVqVWrlj7//HMVLVpU3t7e6bZ18OBB/fnnn3J3d7e04+XlpcDAQBUqVEiurq46deqU1VTRrMS7a9cuRUREWMr+Gm+xYsVUvHhx/frrr+ratWuW+3FxcVFKSkqWjwcAAADw+JEUZkGzZs1UoUIFde/eXVOnTtWNGzf01ltvWdXp2rWrpk6dqtatW2vs2LEqWbKkTp48qRUrVmjo0KEqWbKkpPtTQaOiovT2228rMTFRo0aNUr9+/eTk5KQCBQpoyJAheuONN2Q2m/XUU0/p+vXriouLk7e3t9Wzfg8zcOBARUZGqk6dOmrYsKGWLFmiI0eOqEyZMpY6Y8aM0YABA+Tj46MWLVooOTlZe/fu1dWrVzV48OAM9RMUFKSkpCRt2rTJMi32r1NjAQAAgFzBxLVsYfXRLHByctKXX36pP//8U/Xq1VOvXr00YcIEqzoeHh76/vvvVapUKbVt21bBwcGWV0H8deSwadOmKl++vBo1aqSOHTvqxRdftHqVw7hx4zRixAhFR0crODhYLVq00OrVq/XEE09kON6OHTtqxIgRGjp0qGrXrq2TJ0/qtddes6rTq1cvffTRR1q4cKGqVq2qxo0bKzY2NlP9NGjQQH369FHHjh3l5+enKVOmZPhYAAAAALZhMgyDpzJtJDIyUteuXdPKlSttHUqe0Cww3NYh2B1vJ9dHV0IqHkySyLQ/jDuProRUrptTvxMWD+fj5GbrEOzSTeOurUOwO3+auWZZEXf2O1uHkKar7cJsHUK6Ci7fYusQHonfjAAAAADYNVYfzR6mjwIAAACAA2Ok0IZiY2NtHQIAAAAAB0dSCAAAAMC+sfpotjB9FAAAAAAcGEkhAAAAADgwksI8KigoSDExMY+lr9jYWPn6+j6WvgAAAICcZpjz7mYPSArtWEpKiszmvPNNy2vxAAAAAHg0ksIsMpvNmjJlisqVKydXV1eVKlVKEyZMkCQdOnRITZo0kbu7uwoXLqxXXnlFSUlJlmMjIyPVpk0bvfPOOwoICFDhwoX1+uuv6+7d+y9RDQsL08mTJ/XGG2/IZDLJZDJJ+r8Rva+++kohISFydXXVqVOntGfPHjVv3lxFihSRj4+PGjdurP3791vFe+3aNb366qsqVqyY3NzcVKVKFX3zzTfasmWLevTooevXr1v6Gj16tCTp6tWrioiIUMGCBeXh4aGWLVvql19+sbSZXjwAAAAA7AdJYRYNHz5ckyZN0ogRI3T06FF98sknKlasmG7evKnw8HAVLFhQe/bs0bJly7Rx40b169fP6vjNmzcrISFBmzdv1qJFixQbG2t5RcWKFStUsmRJjR07VufOndO5c+csx926dUuTJ0/WRx99pCNHjqho0aL6448/1L17d23fvl07d+5U+fLl9dxzz+mPP/6QdD+BbdmypeLi4vTxxx/r6NGjmjRpkpydndWgQQPFxMTI29vb0teQIUMk3U9e9+7dq6+++ko//PCDDMPQc889Z0le04sHAAAAeKzMeXizA7ySIgv++OMPzZgxQ7NmzVL37t0lSWXLltVTTz2lefPm6fbt21q8eLE8PT0lSbNmzdILL7ygyZMnq1ixYpKkggULatasWXJ2dlalSpXUqlUrbdq0Sb1791ahQoXk7OysAgUKyN/f36rvu3fvavbs2apevbqlrEmTJlZ1PvzwQ/n6+mrr1q16/vnntXHjRu3evVvx8fGqUKGCJKlMmTKW+j4+PjKZTFZ9/fLLL/rqq68UFxenBg0aSJKWLFmiwMBArVy5Uu3bt083HgAAAAD2g5HCLIiPj1dycrKaNm2a5r7q1atbEkJJatiwocxms44dO2Ypq1y5spydnS2fAwICdPHixUf27eLiomrVqlmVXbhwQb1791b58uXl4+Mjb29vJSUlWaZyHjhwQCVLlrQkhBk9x3z58ql+/fqWssKFC6tixYqKj49/aDwAAAAA7AcjhVng7u6e7Tby589v9dlkMmVokRZ3d3fLM4YPdO/eXb///rtmzJih0qVLy9XVVaGhobpz506OxZuZeAAAAIDHyV5W+cyrGCnMgvLly8vd3V2bNm1KtS84OFgHDx7UzZs3LWVxcXFycnJSxYoVM9yHi4uLUlJSMlQ3Li5OAwYM0HPPPafKlSvL1dVVly9ftuyvVq2azpw5o+PHj2e4r+DgYN27d0+7du2ylP3+++86duyYQkJCMnweAAAAAPI2ksIscHNz07BhwzR06FAtXrxYCQkJ2rlzp+bPn6+uXbvKzc1N3bt31+HDh7V582b1799f3bp1szxPmBFBQUH6/vvvdfbsWasELy3ly5fXf//7X8XHx2vXrl3q2rWr1ehg48aN1ahRI7Vr104bNmzQb7/9prVr12rdunWWvpKSkrRp0yZdvnxZt27dUvny5dW6dWv17t1b27dv18GDB/Xyyy+rRIkSat26ddYuHAAAAIA8h6Qwi0aMGKF///vfGjlypIKDg9WxY0ddvHhRHh4eWr9+va5cuaK6devqpZdeUtOmTTVr1qxMtT927FglJiaqbNmy8vPze2jd+fPn6+rVq6pVq5a6deumAQMGpFoFdPny5apbt646d+6skJAQDR061DI62KBBA/Xp00cdO3aUn5+fpkyZIklauHChateureeff16hoaEyDENr1qxJNfX177Zs2SKTyaTExMRMnTMAAACQJbZeYdTOVx81GYZh2DoI/LMsXLhQEydO1NGjRx+ZQP5Vs8DwXIzqn8nbydXWIdglDx6nzrQ/jDu2DsEuXTfftnUIdsfHyc3WIdilm8bdR1eClT/NXLOsiDv7na1DSNPl8Ma2DiFdRdZvtXUIj8RIIXLcmjVrNHHixEwlhAAAAABsgz+XI8ctW7bskXWSk5OVnJxsVWY2zHIy8XcKAAAAZA6rj2YPv4HDJqKjo+Xj42O1Jd741dZhAQAAAA6HpBA2MXz4cF2/ft1qC/IuY+uwAAAAAIfzWJNCwzD0yiuvqFChQjKZTDpw4ECu9fVgBcxr167lWh+OKDExMdW9i4uLU9WqVZU/f361adMmQ+24urrK29vbamPqKAAAALLCMOfdzR481mcK161bp9jYWG3ZskVlypRRkSJFHmf3yCWDBw9WjRo1tHbtWnl5edk6HAAAAACZ8FiHZhISEhQQEKAGDRrI399f+fKlzknv3HGsZc9z83wf17VMSEhQkyZNVLJkSfn6+j6WPgEAAADkjMeWFEZGRqp///46deqUTCaTgoKCJElhYWHq16+fBg0apCJFiig8/P676g4fPqyWLVvKy8tLxYoVU7du3XT58mVLe2azWdHR0XriiSfk7u6u6tWr64svvki3/99//12dO3dWiRIl5OHhoapVq+rTTz+1qhMWFqYBAwZo6NChKlSokPz9/TV69GirOteuXdOrr76qYsWKyc3NTVWqVNE333xj2b99+3Y9/fTTcnd3V2BgoAYMGKCbN29a9gcFBWncuHGKiIiQt7e3XnnllQxfw+XLl6ty5cpydXVVUFCQpk2bZrU/o21/8cUXqlq1qtzd3VW4cGE1a9bMKsaPPvpIwcHBcnNzU6VKlTR79uw023kwlfT3339Xz549ZTKZFBsbm+HzAQAAAHKCraeI2vv00ceWFM6YMUNjx45VyZIlde7cOe3Zs8eyb9GiRXJxcVFcXJzmzp2ra9euqUmTJqpZs6b27t2rdevW6cKFC+rQoYPlmOjoaC1evFhz587VkSNH9MYbb+jll1/W1q1pvxzy9u3bql27tlavXq3Dhw/rlVdeUbdu3bR7926reosWLZKnp6d27dqlKVOmaOzYsdqwYYOk+4loy5YtFRcXp48//lhHjx7VpEmT5OzsLOn+iFmLFi3Url07/fTTT/r888+1fft29evXz6qPd955R9WrV9ePP/6oESNGZOj67du3Tx06dFCnTp106NAhjR49WiNGjEiVhD2q7XPnzqlz587q2bOn4uPjtWXLFrVt21aGYUiSlixZopEjR2rChAmKj4/XxIkTNWLECC1atChVW4GBgTp37py8vb0VExOjc+fOqWPHjhk6HwAAAAB5g8l4kA08BjExMYqJiVFiYqKlLCwsTDdu3ND+/fstZePHj9e2bdu0fv16S9mZM2cUGBioY8eOqXTp0ipUqJA2btyo0NBQS51evXrp1q1b+uSTT7RlyxY988wzunr1arpTGp9//nlVqlRJ77zzjiWWlJQUbdu2zVKnXr16atKkiSZNmqRvv/1WLVu2VHx8vCpUqJCqvV69esnZ2VkffPCBpWz79u1q3Lixbt68KTc3NwUFBalmzZr68ssvM3XtunbtqkuXLunbb7+1lA0dOlSrV6/WkSNHJClDbe/fv1+1a9dWYmKiSpcunWp/uXLlNG7cOHXu3NlSNn78eK1Zs0Y7duxQYmKinnjiCf3444+qUaOGJMnX11cxMTGKjIzM1Dn9XbPA8Gwd74i8nVxtHYJd8uAVrZn2h+FYU/tzynXzbVuHYHd8nNxsHYJdumnctXUIdudPM9csK+LOfmfrENJ04ZnGtg4hXcU2pz1olZfkid+MateubfX54MGD2rx5c5qLliQkJOju3bu6deuWmjdvbrXvzp07qlmzZpp9pKSkaOLEiVq6dKnOnj2rO3fuKDk5WR4eHlb1qlWrZvU5ICBAFy9elCQdOHBAJUuWTDMhfBD3Tz/9pCVLlljKDMOQ2WzWb7/9puDgYElSnTp10jz+YeLj49W6dWursoYNGyomJkYpKSmW0cpHtV29enU1bdpUVatWVXh4uJ599lm99NJLKliwoG7evKmEhARFRUWpd+/elmPu3bsnHx+fDMXZp08fffzxx5bPSUlJGT1FAAAAIGsMk60jsGt5Iin09PS0+pyUlKQXXnhBkydPTlU3ICBAhw8fliStXr1aJUqUsNrv6pr2yMnUqVM1Y8YMxcTEqGrVqvL09NSgQYNSLcaSP39+q88mk0lm8/3JwO7u7g89j6SkJL366qsaMGBAqn2lSpWy/Pvv55uTHtW2s7OzNmzYoB07dujbb7/VzJkz9dZbb2nXrl2WBHnevHmqX79+quMyYuzYsRoyZEjWggcAAADw2OWJpPDvatWqpeXLlysoKCjNFUpDQkLk6uqqU6dOqXHjjA0Vx8XFqXXr1nr55Zcl3X8+8Pjx4woJCclwXNWqVdOZM2d0/PjxNEcLa9WqpaNHj6pcuXIZbjOjgoODFRcXZ1UWFxenChUqZDhhe8BkMqlhw4Zq2LChRo4cqdKlS+vLL7/U4MGDVbx4cf3666/q2rVrluIsWrSoihYtmqVjAQAAADx+eTIpfP311zVv3jx17tzZshLoiRMn9Nlnn+mjjz5SgQIFNGTIEL3xxhsym8166qmndP36dcXFxcnb21vdu3dP1Wb58uX1xRdfaMeOHSpYsKCmT5+uCxcuZCopbNy4sRo1aqR27dpp+vTpKleunH7++WeZTCa1aNFCw4YN05NPPql+/fqpV69e8vT01NGjR7VhwwbNmjUrW9fk3//+t+rWratx48apY8eO+uGHHzRr1qx0VwZNz65du7Rp0yY9++yzKlq0qHbt2qVLly5ZpraOGTNGAwYMkI+Pj1q0aKHk5GTt3btXV69e1eDBg7N1DgAAAEBusJdVPvOqPJkUFi9eXHFxcRo2bJieffZZJScnq3Tp0mrRooWcnO4vmDpu3Dj5+fkpOjpav/76q3x9fVWrVi39v//3/9Js8+2339avv/6q8PBweXh46JVXXlGbNm10/fr1TMW2fPlyDRkyRJ07d9bNmzdVrlw5TZo0SdL9kcStW7fqrbfe0tNPPy3DMFS2bNkMrcgZFhamoKCgdF/pUKtWLS1dulQjR47UuHHjFBAQoLFjx2Z6cRdvb299//33iomJ0Y0bN1S6dGlNmzZNLVu2lHR/sRwPDw9NnTpV//nPf+Tp6amqVatq0KBBmeoHAAAAgH14rKuPIn2lS5fWmDFjsr2Cpz1j9dHMY/XRrGH10cxj9dGsYfXRzGP10axh9dHMY/XRrMmrq4+ebxRm6xDS5f/9FluH8Ej8ZpQHHDlyRD4+PoqIiLB1KAAAAIDdMcysPpodJIV5QOXKlfXTTz/ZOgwAAAAADsjJ1gEAAAAAAGyHkUIAAAAAdo3VR7OHkcJ/mKCgIMXExNg6DIWFhbFiKQAAAGAHSAoBAAAAwIExfRQAAACAXTMMVh/NDkYKc4nZbFZ0dLSeeOIJubu7q3r16vriiy8kSVu2bJHJZNL69etVs2ZNubu7q0mTJrp48aLWrl2r4OBgeXt7q0uXLrp165alzbCwMPXr10/9+vWTj4+PihQpohEjRuhhr5o8deqUWrduLS8vL3l7e6tDhw66cOGCJCkxMVFOTk7au3ev1TExMTEqXbq0zOb7k7MPHz6sli1bysvLS8WKFVO3bt10+fJlS/2bN28qIiJCXl5eCggI0LRp03LsOgIAAADIXSSFuSQ6OlqLFy/W3LlzdeTIEb3xxht6+eWXtXXrVkud0aNHa9asWdqxY4dOnz6tDh06KCYmRp988olWr16tb7/9VjNnzrRqd9GiRcqXL592796tGTNmaPr06froo4/SjMFsNqt169a6cuWKtm7dqg0bNujXX39Vx44dJd1//rBZs2ZauHCh1XELFy5UZGSknJycdO3aNTVp0kQ1a9bU3r17tW7dOl24cEEdOnSw1P/Pf/6jrVu3atWqVfr222+1ZcsW7d+/P6cuJQAAAIBcxPTRXJCcnKyJEydq48aNCg0NlSSVKVNG27dv1wcffKBXXnlFkjR+/Hg1bNhQkhQVFaXhw4crISFBZcqUkSS99NJL2rx5s4YNG2ZpOzAwUO+++65MJpMqVqyoQ4cO6d1331Xv3r1TxbFp0yYdOnRIv/32mwIDAyVJixcvVuXKlbVnzx7VrVtXvXr1Up8+fTR9+nS5urpq//79OnTokFatWiVJmjVrlmrWrKmJEyda2l2wYIECAwN1/PhxFS9eXPPnz9fHH3+spk2bSrqfuJYsWTKnLysAAACQJlYfzR5GCnPBiRMndOvWLTVv3lxeXl6WbfHixUpISLDUq1atmuXfxYoVk4eHhyUhfFB28eJFq7affPJJmUz/N2c6NDRUv/zyi1JSUlLFER8fr8DAQEtCKEkhISHy9fVVfHy8JKlNmzZydnbWl19+KUmKjY3VM888o6CgIEnSwYMHtXnzZqvzqFSpkiQpISFBCQkJunPnjurXr2/po1ChQqpYsWKmrxsAAACAx4+RwlyQlJQkSVq9erVKlChhtc/V1dWSGObPn99SbjKZrD4/KHvwXF9ucXFxUUREhBYuXKi2bdvqk08+0YwZMyz7k5KS9MILL2jy5Mmpjg0ICNCJEydyNT4AAAAAuYukMBeEhITI1dVVp06dUuPGjVPt/+toYWbt2rXL6vPOnTtVvnx5OTs7p6obHBys06dP6/Tp05bRwqNHj+ratWsKCQmx1OvVq5eqVKmi2bNn6969e2rbtq1lX61atbR8+XIFBQUpX77UX5eyZcsqf/782rVrl0qVKiVJunr1qo4fP57muQMAAAA5zTCz+mh2MH00FxQoUEBDhgzRG2+8oUWLFikhIUH79+/XzJkztWjRomy1ferUKQ0ePFjHjh3Tp59+qpkzZ2rgwIFp1m3WrJmqVq2qrl27av/+/dq9e7ciIiLUuHFj1alTx1IvODhYTz75pIYNG6bOnTvL3d3dsu/111/XlStX1LlzZ+3Zs0cJCQlav369evTooZSUFHl5eSkqKkr/+c9/9N133+nw4cOWRWoAAAAA5H2MFOaScePGyc/PT9HR0fr111/l6+urWrVq6f/9v/+XrSmhERER+vPPP1WvXj05Oztr4MCBloVr/s5kMmnVqlXq37+/GjVqJCcnJ7Vo0SLViqbS/YVuduzYoZ49e1qVFy9eXHFxcRo2bJieffZZJScnq3Tp0mrRooUl8Zs6daplmmmBAgX073//W9evX8/yOQIAAAB4fEzGw15yhzwlLCxMNWrUUExMTI63PW7cOC1btkw//fRTjredUc0Cw23Wt73ydnK1dQh2yYO/h2XaH8YdW4dgl66bb9s6BLvj4+Rm6xDs0k3jrq1DsDt/mrlmWRF39jtbh5CmU3Wa2jqEdJXau8nWITwSc/wcXFJSkg4fPqxZs2apf//+tg4HAAAAwGNGUujg+vXrp9q1ayssLCzV1FEAAAAAj9f777+voKAgubm5qX79+tq9e3eGjvvss89kMpnUpk2bTPfJHCo7smXLlhxvMzY2VrGxsTneLgAAAPC4/FNWH/388881ePBgzZ07V/Xr11dMTIzCw8N17NgxFS1aNN3jEhMTNWTIED399NNZ6peRQgAAAADIA6ZPn67evXurR48eCgkJ0dy5c+Xh4aEFCxake0xKSoq6du2qMWPGqEyZMlnql6QQAAAAAHJJcnKybty4YbUlJyenqnfnzh3t27dPzZo1s5Q5OTmpWbNm+uGHH9Jtf+zYsSpatKiioqKyHCNJIQAAAAC7ZphNeXaLjo6Wj4+P1RYdHZ3qHC5fvqyUlBQVK1bMqrxYsWI6f/58mue9fft2zZ8/X/PmzcvW9eOZQgAAAADIJcOHD9fgwYOtylxds/9asT/++EPdunXTvHnzVKRIkWy1RVIIAAAAALnE1dU1Q0lgkSJF5OzsrAsXLliVX7hwQf7+/qnqJyQkKDExUS+88IKlzGw2S5Ly5cunY8eOqWzZshmKkemjAAAAAOyaYeTdLaNcXFxUu3Ztbdr0fy+7N5vN2rRpk0JDQ1PVr1Spkg4dOqQDBw5YthdffFHPPPOMDhw4oMDAwAz3zUghAAAAAOQBgwcPVvfu3VWnTh3Vq1dPMTExunnzpnr06CFJioiIUIkSJRQdHS03NzdVqVLF6nhfX19JSlX+KCSFAAAAAJAHdOzYUZcuXdLIkSN1/vx51ahRQ+vWrbMsPnPq1Ck5OeX8ZE+TYWRmUBPIPc0Cw20dgt3xdsr+Q8qOyIO/h2XaH8YdW4dgl66bb9s6BLvj4+Rm6xDs0k3jrq1DsDt/mrlmWRF39jtbh5CmX6s+a+sQ0lXm0Le2DuGReKYQAAAAABwYfy5HnrH1wmFbhwAHkc+Z//Rl1r2Ue7YOwS4V9vC2dQh258qff9g6BLvk4+Zp6xDsTjmv4rYOAcgz+M0IAAAAgF0zDJOtQ7BrTB8FAAAAAAdGUggAAAAADozpowAAAADsmmG2dQT2jZFCAAAAAHBgJIUAAAAA4MCYPgoAAADArplZfTRbGCkEAAAAAAdGUggAAAAADozpowAAAADsGi+vzx5GCgEAAADAgZEUAgAAAIADY/ooAAAAALtmmJk+mh2MFAIAAACAAyMpBAAAAAAHxvRRAAAAAHbNMGwdgX1jpBAAAAAAHBhJIQAAAAA4MKaPAgAAALBrrD6aPYwUAgAAAIADIykEAAAAAAfG9FEAAAAAds1sMH00OxgpBAAAAAAHRlIIAAAAAA6M6aMAAAAA7JrB9NFsYaQQAAAAABwYSSEAAAAAODCSwmxKTEyUyWTSgQMHbB2KTCaTVq5caeswJOWtWAAAAPDPZhh5d7MHuZIURkZGymQyadKkSVblK1eulMmUufm+QUFBiomJycHoAAAAAAAP5NpIoZubmyZPnqyrV6/mVhcAAAAAgGzKtaSwWbNm8vf3V3R09EPrLV++XJUrV5arq6uCgoI0bdo0y76wsDCdPHlSb7zxhkwm00NHGa9du6ZevXrJz89P3t7eatKkiQ4ePGjZP3r0aNWoUUMLFixQqVKl5OXlpb59+yolJUVTpkyRv7+/ihYtqgkTJli1azKZNGfOHLVs2VLu7u4qU6aMvvjii4ee09atW1WvXj25uroqICBAb775pu7duydJWrx4sQoXLqzk5GSrY9q0aaNu3bpZPq9atUq1atWSm5ubypQpozFjxljakKRffvlFjRo1kpubm0JCQrRhw4aHxpSW33//XZ07d1aJEiXk4eGhqlWr6tNPP7WqExYWpgEDBmjo0KEqVKiQ/P39NXr0aKs6ORELAAAAkFVmw5RnN3uQa0mhs7OzJk6cqJkzZ+rMmTNp1tm3b586dOigTp066dChQxo9erRGjBih2NhYSdKKFStUsmRJjR07VufOndO5c+fS7a99+/a6ePGi1q5dq3379qlWrVpq2rSprly5YqmTkJCgtWvXat26dfr00081f/58tWrVSmfOnNHWrVs1efJkvf3229q1a5dV2yNGjFC7du108OBBde3aVZ06dVJ8fHyacZw9e1bPPfec6tatq4MHD2rOnDmaP3++xo8fb4kzJSVFX331leWYixcvavXq1erZs6ckadu2bYqIiNDAgQN19OhRffDBB4qNjbUkrGazWW3btpWLi4t27dqluXPnatiwYY+4I6ndvn1btWvX1urVq3X48GG98sor6tatm3bv3m1Vb9GiRfL09NSuXbs0ZcoUjR071pL45VQsAAAAAGwjVxea+de//qUaNWpo1KhRae6fPn26mjZtqhEjRqhChQqKjIxUv379NHXqVElSoUKF5OzsrAIFCsjf31/+/v5ptrN9+3bt3r1by5YtU506dVS+fHm988478vX1tRrVM5vNWrBggUJCQvTCCy/omWee0bFjxxQTE6OKFSuqR48eqlixojZv3mzVfvv27dWrVy9VqFBB48aNU506dTRz5sw0Y5k9e7YCAwM1a9YsVapUSW3atNGYMWM0bdo0mc1mubu7q0uXLlq4cKHlmI8//lilSpVSWFiYJGnMmDF688031b17d5UpU0bNmzfXuHHj9MEHH0iSNm7cqJ9//lmLFy9W9erV1ahRI02cODFjN+UvSpQooSFDhqhGjRoqU6aM+vfvrxYtWmjp0qVW9apVq6ZRo0apfPnyioiIUJ06dbRp06YcjQUAAACAbeT6y+snT56sJk2aaMiQIan2xcfHq3Xr1lZlDRs2VExMjFJSUuTs7JyhPg4ePKikpCQVLlzYqvzPP/9UQkKC5XNQUJAKFChg+VysWDE5OzvLycnJquzixYtW7YSGhqb6nN5qo/Hx8QoNDbWa6tqwYUMlJSXpzJkzKlWqlHr37q26devq7NmzKlGihGJjYy2L8zw4n7i4OKuprCkpKbp9+7Zu3bql+Ph4BQYGqnjx4unGmBEpKSmaOHGili5dqrNnz+rOnTtKTk6Wh4eHVb1q1apZfQ4ICLBco5yKBQAAAMgqXl6fPbmeFDZq1Ejh4eEaPny4IiMjc6WPpKQkBQQEaMuWLan2+fr6Wv6dP39+q30mkynNMrPZnBthWtSsWVPVq1fX4sWL9eyzz+rIkSNavXq1ZX9SUpLGjBmjtm3bpjrWzc0tx+KYOnWqZsyYoZiYGFWtWlWenp4aNGiQ7ty5Y1XPFtcIAAAAwOOR60mhJE2aNEk1atRQxYoVrcqDg4MVFxdnVRYXF6cKFSpYRgldXFyUkpLy0PZr1aql8+fPK1++fAoKCsrR2CVp586dioiIsPpcs2bNNOsGBwdr+fLlMgzDMvIXFxenAgUKqGTJkpZ6vXr1UkxMjM6ePatmzZopMDDQ6nyOHTumcuXKpdvH6dOnde7cOQUEBFhiyqy4uDi1bt1aL7/8sqT702uPHz+ukJCQDLeRU7EAAAAAsI3H8vL6qlWrqmvXrnrvvfesyv/9739r06ZNGjdunI4fP65FixZp1qxZVlNNg4KC9P333+vs2bO6fPlymu03a9ZMoaGhatOmjb799lslJiZqx44deuutt7R3795sx79s2TItWLBAx48f16hRo7R7927169cvzbp9+/bV6dOn1b9/f/38889atWqVRo0apcGDB1tNU+3SpYvOnDmjefPmWRaYeWDkyJFavHixxowZoyNHjig+Pl6fffaZ3n77bcv5VqhQQd27d9fBgwe1bds2vfXWW5k+r/Lly2vDhg3asWOH4uPj9eqrr+rChQuZaiOnYgEAAACyytYvqOfl9Rk0duzYVFMOa9WqpaVLl+qzzz5TlSpVNHLkSI0dO9ZqmunYsWOVmJiosmXLys/PL822TSaT1qxZo0aNGqlHjx6qUKGCOnXqpJMnT6pYsWLZjn3MmDH67LPPVK1aNS1evFiffvppuqNpJUqU0Jo1a7R7925Vr15dffr0UVRUlCWhe8DHx0ft2rWTl5eX2rRpY7UvPDxc33zzjb799lvVrVtXTz75pN59912VLl1akuTk5KQvv/xSf/75p+rVq6devXqlepWGdP91Eg+bsvv222+rVq1aCg8PV1hYmPz9/VPF8igZjQUAAABA3mQyDHvJX23DZDLpyy+/zHSylBFNmzZV5cqVU42g5pTSpUtrzJgxufYsZ07L71LC1iHAQeRzfiwz5/9R7qXce3QlpFLYw9vWIdidK3/+YesQ7JKPm6etQ7A75byKP7oSUvnh7OZHV7KB/YGtH13JRmqdXmXrEB6J34xs4OrVq9qyZYu2bNmi2bNn50ofR44ckY+Pj9WzkAAAAMA/kb28JD6vIim0gZo1a+rq1auaPHlyqsV3ckrlypX1008/5UrbAAAAAP45SAofITdm1yYmJuZ4m/YmOTlZycnJVmV/XbEVAAAAwOPx2BaaAf4qOjpaPj4+VpvZzHMkAAAAyDzDMOXZzR7YTVIYGRmZ44u9hIWFadCgQY+1z7QYhqFXXnlFhQoVkslk0oEDB3K9z5w2evRo1ahRI8P1hw8fruvXr1ttTk4Fci9AAAAAAGmy+fTR0aNHa+XKlXkyEZoxY0auTB/9u3Xr1ik2NlZbtmxRmTJlVKRIkVzv09ZcXV3l6upqVcbUUQAAAODxs3lSmJf5+Pg8ln4SEhIUEBCgBg0aZLkNwzCUkpKifPke7y190C8AAABgK6w+mj3Zmj4aFhamAQMGaOjQoSpUqJD8/f01evRoqzqnTp1S69at5eXlJW9vb3Xo0EEXLlyQJMXGxmrMmDE6ePCgTCaTTCaTYmNjM9R3cnKyBgwYoKJFi8rNzU1PPfWU9uzZY1Vn69atqlevnlxdXRUQEKA333xT9+6l/66t1atXy8fHR0uWLJGUevpoRs73559/1lNPPSU3NzeFhIRo48aNMplMWrlyZZp9RkZGqn///jp16pRMJpOCgoIydH5btmyRyWTS2rVrVbt2bbm6umr79u2p2n/ppZfUr18/y+dBgwbJZDLp559/liTduXNHnp6e2rhxY472m5CQoDJlyqhfv36PZbQVAAAAQNZk+5nCRYsWydPTU7t27dKUKVM0duxYbdiwQZJkNpvVunVrXblyRVu3btWGDRv066+/qmPHjpKkjh076t///rcqV66sc+fO6dy5c5Z9jzJ06FAtX75cixYt0v79+1WuXDmFh4frypUrkqSzZ8/queeeU926dXXw4EHNmTNH8+fP1/jx49Ns75NPPlHnzp21ZMkSde3aNUvnm5KSojZt2sjDw0O7du3Shx9+qLfeeuuh5zFjxgyNHTtWJUuW1Llz5ywJ2KPO74E333xTkyZNUnx8vKpVq5aq/caNG2vLli2Wz1u3blWRIkUsZXv27NHdu3cto5Q50e9PP/2kp556Sl26dNGsWbOYFgoAAADkYdlOCqtVq6ZRo0apfPnyioiIUJ06dbRp0yZJ0qZNm3To0CF98sknql27turXr6/Fixdr69at2rNnj9zd3eXl5aV8+fLJ399f/v7+cnd3f2SfN2/e1Jw5czR16lS1bNlSISEhmjdvntzd3TV//nxJ0uzZsxUYGKhZs2apUqVKatOmjcaMGaNp06bJbDZbtff++++rb9+++vrrr/X8889n+Xw3bNighIQELV68WNWrV9dTTz2lCRMmPLQ9Hx8fFShQQM7OzvL395efn1+Gzu+BsWPHqnnz5ipbtqwKFSqUqv2wsDAdPXpUly5d0tWrV3X06FENHDjQkhRu2bJFdevWlYeHR470u2PHDoWFhWnIkCHpJuAAAABATjLy8GYPsv0A2t9HiQICAnTx4kVJUnx8vAIDAxUYGGjZHxISIl9fX8XHx6tu3bpZ6jMhIUF3795Vw4YNLWX58+dXvXr1FB8fb+k7NDTUapSqYcOGSkpK0pkzZ1SqVClJ0hdffKGLFy8qLi4uQ/E87HyPHTumwMBA+fv7W/bXq1cvV87vgTp16jy0rSpVqqhQoULaunWrXFxcVLNmTT3//PN6//33Jd0fOQwLC8uRfk+dOqXmzZtrwoQJD13VFQAAAEDeke2Rwvz581t9NplMqUbi8rKaNWvKz89PCxYsyNCzb3ntfD09PR+632QyqVGjRtqyZYslAaxWrZqSk5N1+PBh7dixQ40bN86Rfv38/FSvXj19+umnunHjRqbbBAAAAPD45ep7CoODg3X69GmdPn3aUnb06FFdu3ZNISEhkiQXF5dMr15ZtmxZubi4KC4uzlJ29+5d7dmzx9JucHCwfvjhB6tELy4uTgUKFFDJkiWt2tq8ebNWrVql/v37Z+k8H6hYsaJOnz5tWUhHUqrFbzIiI+eXGQ+eK9yyZYvCwsLk5OSkRo0aaerUqUpOTraMDGa3X3d3d33zzTdyc3NTeHi4/viDl9EDAAAg95kNU57d7EGuJoXNmjVT1apV1bVrV+3fv1+7d+9WRESEGjdubJl+GBQUpN9++00HDhzQ5cuXlZyc/Mh2PT099dprr+k///mP1q1bp6NHj6p37966deuWoqKiJEl9+/bV6dOn1b9/f/38889atWqVRo0apcGDB8vJyfq0K1SooM2bN2v58uXZmvb44Bm77t2766efflJcXJzefvttSZl7B19Gzi8zHjxXeOTIET311FOWsiVLlqhOnTqWUb+c6NfT01OrV69Wvnz51LJlSyUlJWU6XgAAAACPT64mhSaTSatWrVLBggXVqFEjNWvWTGXKlNHnn39uqdOuXTu1aNFCzzzzjPz8/PTpp59mqO1JkyapXbt26tatm2rVqqUTJ05o/fr1KliwoCSpRIkSWrNmjXbv3q3q1aurT58+ioqKsiRpf1exYkV99913+vTTT/Xvf/87S+fr7OyslStXKikpSXXr1lWvXr0sq4+6ubllqq1HnV9mVK1aVb6+vqpRo4a8vLwk3U8KU1JSLM8T5mS/Xl5eWrt2rQzDUKtWrXTz5s1MxwwAAADg8TAZvEQuV8XFxempp57SiRMnVLZsWVuHk6fldylh6xDgIPI5Z3uNLYdzLyX9d7wifYU9vG0dgt258iePHmSFj9vD1xhAauW8its6BLv0w9nNtg4hTXH+L9k6hHQ1PP+FrUN4JH4zymFffvmlvLy8VL58eZ04cUIDBw5Uw4YNSQgBAAAA5EkkhTnsjz/+0LBhw3Tq1CkVKVJEzZo107Rp02wdFgAAAACkiaQwh0VERCgiIsLWYQAAAAAOw35eiJc35epCMwAAAACAvI2kEAAAAAAcGNNHAQAAANg1Q/bxkvi8ipFCAAAAAHBgJIUAAAAA4MCYPgoAAADArpkNW0dg3xgpBAAAAAAHRlIIAAAAAA6M6aMAAAAA7JqZ1UezhZFCAAAAAHBgJIUAAAAA4MCYPgoAAADArvHy+uxhpBAAAAAAHBhJIQAAAAA4MKaPAgAAALBrZlsHYOcYKQQAAAAAB0ZSCAAAAAAOjOmjAAAAAOwaq49mDyOFAAAAAODASAoBAAAAwIExfRQAAACAXWP10exhpBAAAAAAHBhJIQAAAAA4MKaPAgAAALBrTB/NHkYKAQAAAMCBkRQCAAAAgANj+igAAAAAu8bL67OHpBB5RlFPX1uHYHdu3U22dQh2qaBbAVuHYHcu/3nd1iHYpQL5PWwdgt1xdc5v6xDskruzq61DsDvX7t60dQhAnsH0UQAAAABwYIwUAgAAALBrZmaPZgsjhQAAAADgwEgKAQAAAMCBMX0UAAAAgF0zs/potjBSCAAAAAAOjKQQAAAAABwY00cBAAAA2DXD1gHYOUYKAQAAAMCBkRQCAAAAgANj+igAAAAAu2a2dQB2jpFCAAAAAMgj3n//fQUFBcnNzU3169fX7t270627YsUK1alTR76+vvL09FSNGjX03//+N9N9khQCAAAAQB7w+eefa/DgwRo1apT279+v6tWrKzw8XBcvXkyzfqFChfTWW2/phx9+0E8//aQePXqoR48eWr9+fab6NRmGwWI9yBNKFKxs6xDszq27ybYOwS4VdCtg6xDszuU/r9s6BLtUzKOgrUOwO3fMd20dgl1yd3a1dQh2x8TLzrMk/mL6o1a29EVAV1uHkK6Xzi3JcN369eurbt26mjVrliTJbDYrMDBQ/fv315tvvpmhNmrVqqVWrVpp3LhxGe6XkUIAAAAAyCXJycm6ceOG1ZacnPoP+3fu3NG+ffvUrFkzS5mTk5OaNWumH3744ZH9GIahTZs26dixY2rUqFGmYiQpBAAAAIBcEh0dLR8fH6stOjo6Vb3Lly8rJSVFxYoVsyovVqyYzp8/n277169fl5eXl1xcXNSqVSvNnDlTzZs3z1SMrD4KAAAAwK7l5efhhg8frsGDB1uVubrm3JTvAgUK6MCBA0pKStKmTZs0ePBglSlTRmFhYRlug6QQAAAAAHKJq6trhpLAIkWKyNnZWRcuXLAqv3Dhgvz9/dM9zsnJSeXKlZMk1ahRQ/Hx8YqOjs5UUsj0UQAAAACwMRcXF9WuXVubNm2ylJnNZm3atEmhoaEZbsdsNqf5zOLDMFIIAAAAwK79U15eP3jwYHXv3l116tRRvXr1FBMTo5s3b6pHjx6SpIiICJUoUcLyTGJ0dLTq1KmjsmXLKjk5WWvWrNF///tfzZkzJ1P9khQCAAAAQB7QsWNHXbp0SSNHjtT58+dVo0YNrVu3zrL4zKlTp+Tk9H+TPW/evKm+ffvqzJkzcnd3V6VKlfTxxx+rY8eOmeqX9xQiz+A9hZnHewqzhvcUZh7vKcwa3lOYebynMGt4T2Hm8Z7CrMmr7yn8PA+/p7BjJt5TaCuMFAIAAACwa2Zy/GxhoRkAAAAAcGAkhQAAAADgwJg+CgAAAMCumXlGNFsYKQQAAAAAB0ZSmIMSExNlMpl04MABW4cik8mklStXZrh+bGysfH19cy0eAAAAAHlTrieFkZGRMplMmjRpklX5ypUrZTJlbpg3KChIMTExORgdclpYWJgGDRpk6zAAAADgQIw8vNmDxzJS6ObmpsmTJ+vq1auPozsAAAAAQAY9lqSwWbNm8vf3V3R09EPrLV++XJUrV5arq6uCgoI0bdo0y76wsDCdPHlSb7zxhkwm00NHGa9du6ZevXrJz89P3t7eatKkiQ4ePGjZP3r0aNWoUUMLFixQqVKl5OXlpb59+yolJUVTpkyRv7+/ihYtqgkTJli1azKZNGfOHLVs2VLu7u4qU6aMvvjii4ee09atW1WvXj25uroqICBAb775pu7duydJWrx4sQoXLqzkZOsXkLdp00bdunWzfF61apVq1aolNzc3lSlTRmPGjLG0IUm//PKLGjVqJDc3N4WEhGjDhg0PjelhVq5cqfLly8vNzU3h4eE6ffq0ZV9kZKTatGljVX/QoEEKCwuz7N+6datmzJhhuUeJiYlZjgUAAABA7nssSaGzs7MmTpyomTNn6syZM2nW2bdvnzp06KBOnTrp0KFDGj16tEaMGKHY2FhJ0ooVK1SyZEmNHTtW586d07lz59Ltr3379rp48aLWrl2rffv2qVatWmratKmuXLliqZOQkKC1a9dq3bp1+vTTTzV//ny1atVKZ86c0datWzV58mS9/fbb2rVrl1XbI0aMULt27XTw4EF17dpVnTp1Unx8fJpxnD17Vs8995zq1q2rgwcPas6cOZo/f77Gjx9viTMlJUVfffWV5ZiLFy9q9erV6tmzpyRp27ZtioiI0MCBA3X06FF98MEHio2NtSSsZrNZbdu2lYuLi3bt2qW5c+dq2LBhj7gjabt165YmTJigxYsXKy4uTteuXVOnTp0yfPyMGTMUGhqq3r17W+5RYGBglmIBAAAAMspsyrubPXhsC83861//Uo0aNTRq1Kg090+fPl1NmzbViBEjVKFCBUVGRqpfv36aOnWqJKlQoUJydnZWgQIF5O/vL39//zTb2b59u3bv3q1ly5apTp06Kl++vN555x35+vpajeqZzWYtWLBAISEheuGFF/TMM8/o2LFjiomJUcWKFdWjRw9VrFhRmzdvtmq/ffv26tWrlypUqKBx48apTp06mjlzZpqxzJ49W4GBgZo1a5YqVaqkNm3aaMyYMZo2bZrMZrPc3d3VpUsXLVy40HLMxx9/rFKlSllG38aMGaM333xT3bt3V5kyZdS8eXONGzdOH3zwgSRp48aN+vnnn7V48WJVr15djRo10sSJEzN2U/7m7t27mjVrlkJDQ1W7dm0tWrRIO3bs0O7duzN0vI+Pj1xc/j/27jssirNrA/i9oCBIV0QxSLEgWBB7iQVFRY29BhURJSbGLsYWezf2GEuk29DYkxgbCgoaGwoWFKQaFbGigFLn+8PPfbOhLXVY9v69F9eVnZ2ZPTMvsnv2Oc951KCpqSn9/0hVVbVIsRARERERUdko0+6ja9asgY+PT64ja+Hh4ejQoYPMtg4dOiAyMhJZWVlyv0ZoaCiSk5NRrVo1aGlpSX9iYmIQFRUl3c/MzAza2trSx0ZGRrC2toaKiorMtsTERJnzt2vXLsfjvEYKw8PD0a5dO5lS1w4dOiA5OVk6Yurq6oozZ87gyZMnAD51Af3cnOfz9SxdulTmWj6PxKWmpiI8PBwmJiYwNjbOM0Z5VapUCa1atZI+btiwIfT09PK8PiIiIiIiUnxlunh9p06d0LNnT8ydOxfOzs6l8hrJycmoVasWAgICcjz37yUXKleuLPOcRCLJdVt2dnZphClla2sLGxsb+Pr6okePHrh37x7+/PNP6fPJyclYsmQJBg0alOPYKlWqlGps/6WiogJBkO2hlJGRUaYxEBERERH9V+l+Yq/4yjQpBIDVq1ejWbNmsLS0lNluZWWF4OBgmW3BwcFo0KCBtARRTU2twFHD5s2bIyEhAZUqVYKZmVmJxg4Af//9N5ycnGQe29ra5rqvlZUVDh8+DEEQpCN/wcHB0NbWxhdffCHdb/z48di0aROePHkCe3t7mXl4zZs3x8OHD1GvXr08X+Px48d49uwZatWqJY2pKDIzM3Hjxg20bt0aAPDw4UO8ffsWVlZWAABDQ0PcvXtX5pjbt2/LJNPy/H9ERERERETlR5kvXt+kSROMHDkSW7Zskdk+c+ZM+Pv7Y9myZYiIiICPjw+2bt0KNzc36T5mZma4ePEinjx5gpcvX+Z6fnt7e7Rr1w4DBgzAmTNnEBsbi8uXL2P+/Pm4ceNGseP/7bff4OnpiYiICCxatAjXrl3DpEmTct134sSJePz4MSZPnowHDx7g+PHjWLRoEWbMmCFTpuro6Ih//vkHu3btkjaY+WzhwoXw9fXFkiVLcO/ePYSHh8PPzw8//vij9HobNGiAMWPGIDQ0FJcuXcL8+fOLdG2VK1fG5MmTcfXqVdy8eRPOzs5o27atNEns2rUrbty4AV9fX0RGRmLRokU5kkQzMzNcvXoVsbGxePnyZamPtBIRERERUfGUeVIIAEuXLs2RLDRv3hwHDx6En58fGjdujIULF2Lp0qUyZaZLly5FbGws6tatC0NDw1zPLZFIcPLkSXTq1Aljx45FgwYNMGLECMTFxcHIyKjYsS9ZsgR+fn5o2rQpfH19sX//flhbW+e6b+3atXHy5Elcu3YNNjY2+PbbbzFu3DhpQveZrq4uBg8eDC0trRxLPvTs2RN//PEHzpw5g1atWqFt27bYuHEjTE1NAXwq6Tx69Cg+fPiA1q1bY/z48TmW0gA+LelRUMmupqYmZs+eDUdHR3To0AFaWlo4cOCATCwLFizADz/8gFatWuH9+/cyo6YA4ObmBlVVVVhbW8PQ0BDx8fH5viYRERERUXGJvUC9oi9eLxH+O0mM8iSRSHD06NEciVtJ6NatGxo1apRjBLWkmJqaYsmSJaU2l7Mk1NZvJHYICic1I63gnSgH/SraBe9EMl5+SBI7BIVkpKkvdggKJz2bc9WLQkNVXewQFI4ECrJWQDkTnihfV/qy5lV7lNgh5Gnskz1ih1CgMp9TSLLevHmDgIAABAQEYNu2baXyGvfu3YOurm6OUT0iIiIiIiImhSKztbXFmzdvsGbNmhzNd0pKo0aNEBYWVirnLqq0tDSkpcmOcglCNiQSUSqaiYiIiEiBKcoi8eUVk8JCKI1K29jY2BI/pyJYtWoVlixZIrNNS706dDRqiBQREREREZFy4rAMiWLu3LlISkqS+dGuUl3ssIiIiIiIlI7CJIVdunTBtGnTSvScZmZm2LRpU5m+Zm5SU1MxePBg6OjoQCKR4O3bt6X+miXN2dm5UA141NXVoaOjI/PD0lEiIiIiKorscvyjCFg+mo8jR47ILMxeWnx8fHDp0iVcvnwZ1atXh66ubqm/JhEREREREcCkMF8GBgZl8jpRUVGwsrJC48aNi3yOrKwsSCQSqKiU7Wjb59clIiIiIiLFpLD1em/evIGTkxP09fWhqamJXr16ITIyUmafw4cPo1GjRlBXV4eZmRnWr1+f7znd3d2hp6cHf39/ADnLR83MzLBy5Uq4uLhAW1sbderUwa+//ipzjsuXL6NZs2aoUqUKWrZsiWPHjkEikeD27du5vmaXLl2wfv16XLx4ERKJBF26dJHr+ry9vaGnp4cTJ07A2toa6urquS4U37JlS6xbt076eMCAAahcuTKSk5MBAP/88w8kEgkePXpUoq97/fp1GBoaYs2aNfnccSIiIiKi4hO7RFTRy0cVNil0dnbGjRs3cOLECVy5cgWCIKB3797IyPi06O3NmzcxbNgwjBgxAnfu3MHixYuxYMECeHt753q+tWvXYs6cOThz5gy6deuW5+uuX78eLVu2xK1btzBx4kR89913ePjwIQDg3bt36Nu3L5o0aYKQkBAsW7YMs2fPzvc6jhw5AldXV7Rr1w7Pnj3DkSNH5Lo+4NNcxDVr1sDd3R337t1DjRo5O3d27twZAQEBAD51T7106RL09PQQFBQEAAgMDETt2rVRr169Envd8+fPo3v37lixYkWB109EREREROJSyPLRyMhInDhxAsHBwWjfvj0AYO/evTAxMcGxY8cwdOhQbNiwAd26dcOCBQsAAA0aNMD9+/fx008/wdnZWeZ8s2fPxu7duxEYGIhGjRrl+9q9e/fGxIkTpcdt3LgRFy5cgKWlJfbt2weJRIJdu3ahSpUqsLa2xpMnT+Dq6prn+QwMDKCpqQk1NTXUrFlT7usDgIyMDGzbtg02NjZ5nr9Lly7w8PBAVlYW7t69CzU1NQwfPhwBAQFwcHBAQEAAOnfuXGKve/ToUTg5OcHd3R3Dhw/P914SEREREZH4FHKkMDw8HJUqVUKbNm2k26pVqwZLS0uEh4dL9+nQoYPMcR06dEBkZCSysrKk29avX49du3YhKCiowIQQAJo2bSr9b4lEgpo1ayIxMREA8PDhQzRt2hRVqlSR7tO6detSuT4AUFNTk4knNx07dsT79+9x69YtBAYGonPnzujSpYt09DAwMFBaslrc17169SqGDh2K3bt3MyEkIiIiojIjSMrvjyJQyKSwJHXs2BFZWVk4ePCgXPv/txupRCJBdrY41cIaGhoFNnnR09ODjY0NAgICpAlgp06dcOvWLURERCAyMlI6Uljc161bty4aNmwIT09PmXJTIiIiIiIqvxQyKbSyskJmZiauXr0q3fbq1Ss8fPgQ1tbW0n2Cg4NljgsODkaDBg2gqqoq3da6dWv89ddfWLlypUxDlqKwtLTEnTt3kJaWJt12/fr1Qp9HnusrjM6dO+PChQu4ePEiunTpAgMDA1hZWWHFihWoVasWGjRoUCKvW716dZw/fx6PHj3CsGHDmBgSERERESkAhUwK69evj/79+8PV1RVBQUEIDQ3FqFGjULt2bfTv3x8AMHPmTPj7+2PZsmWIiIiAj48Ptm7dCjc3txzna9++PU6ePIklS5bku5h9QRwdHZGdnY1vvvkG4eHhOH36tDTRLMyyDfJcX2F06dIFp0+fRqVKldCwYUPptr1798qMEpbE69aoUQPnz5/HgwcP8PXXXyMzM7PQ8RIRERERFYbYHUbZfVQkXl5eaNGiBb766iu0a9cOgiDg5MmT0vLO5s2b4+DBg/Dz80Pjxo2xcOFCLF26NEeTmc++/PJL/Pnnn/jxxx/x888/FykmHR0d/P7777h9+zaaNWuG+fPnY+HChQAgM8+wJK6vMDp27Ijs7GyZBLBLly7IysqSzicsydetWbMmzp8/jzt37mDkyJEycziJiIiIiKh8kQiCIIgdREW2d+9ejB07FklJSdDQ0BA7nHKttn7BjX5IVmpGWsE7UQ76VbTFDkHhvPyQJHYICslIU1/sEBROejanHhSFhqq62CEoHAkUpANIOROeeE3sEHK1zWSU2CHkaeLjPWKHUCCFXJKiPPP19YWFhQVq166N0NBQzJ49G8OGDWNCSERERERUShSlTLO8YlJYwhISErBw4UIkJCSgVq1aGDp0KFasWCF2WERERERERLliUljCfvjhB/zwww9ih0FERERERCQXJoVERERERKTQ2CSleBS2+ygREREREREVH5NCIiIiIiIiJcbyUSIiIiIiUmjZXGGkWDhSSEREREREpMSYFBIRERERESkxlo8SEREREZFC4+L1xcORQiIiIiIiIiXGpJCIiIiIiEiJsXyUiIiIiIgUGstHi4cjhUREREREREqMSSEREREREZESY/koEREREREpNEHsABQcRwqJiIiIiIiUGJNCIiIiIiIiJcbyUSIiIiIiUmjZErEjUGwcKSQiIiIiIlJiTAqJiIiIiIiUGMtHiYiIiIhIoXHx+uLhSCEREREREZESY1JIRERERESkxFg+SkRERERECo2L1xcPRwqJiIiIiIiUGJNCIiIiIiIiJcbyUSIiIiIiUmjZLCAtFo4UEhERERERKTGOFFK5kZjyVuwQSEmkZHwUOwSFo6WmIXYICikmKUHsEBSOikQidggKSVVFVewQFE5mVqbYIRCVG0wKiYiIiIhIoXHx+uJh+SgREREREZESY1JIRERERESkxFg+SkRERERECo29R4uHI4VERERERERKjEkhERERERGREmP5KBERERERKTR2Hy0ejhQSEREREREpMSaFRERERERESozlo0REREREpNCyJWJHoNg4UkhERERERKTEmBQSEREREREpMZaPEhERERGRQsvm8vXFwpFCIiIiIiIiJcakkIiIiIiISImxfJSIiIiIiBQai0eLhyOFRERERERESoxJIRERERERkRJj+SgRERERESm0bLEDUHAcKSQiIiIiIlJiTAqJiIiIiIiUGMtHiYiIiIhIoXHx+uLhSCEREREREZESY1JIRERERESkxFg+SkRERERECo3Fo8XDkUIiIiIiIiIlxqSQiIiIiIhIibF8lIiIiIiIFBoXry8ejhQSEREREREpMSaFRERERERESozlo0REREREpNC4eH3xcKSQiIiIiIhIiTEpJCIiIiIiUmIsHyUiIiIiIoXG4tHi4UghERERERGREmNSqKS6dOmCadOmlcq5zczMsGnTplI5NxERERERlSwmheWcs7MzJBIJJBIJKleuDHNzc/zwww/4+PGjXMcHBARAIpHg7du3MtuPHDmCZcuWlULERERERERlK7sc/xTWL7/8AjMzM1SpUgVt2rTBtWvX8tx3165d6NixI/T19aGvrw97e/t8988Lk0IF4ODggGfPniE6OhobN27Ezp07sWjRomKd08DAANra2nk+n56eXqzzExERERFR4Rw4cAAzZszAokWLEBISAhsbG/Ts2ROJiYm57h8QEICvv/4aFy5cwJUrV2BiYoIePXrgyZMnhXpdJoUKQF1dHTVr1oSJiQkGDBgAe3t7nD17FgCQnZ2NVatWwdzcHBoaGrCxscGhQ4cAALGxsbCzswMA6OvrQyKRwNnZGUDO8lEzMzMsW7YMTk5O0NHRwTfffAMACAoKQseOHaGhoQETExNMmTIFKSkp0uMSExPRt29faGhowNzcHHv37i2DO0JEREREVPFs2LABrq6uGDt2LKytrbFjxw5oamrC09Mz1/337t2LiRMnolmzZmjYsCHc3d2RnZ0Nf3//Qr0uk0IFc/fuXVy+fBlqamoAgFWrVsHX1xc7duzAvXv3MH36dIwaNQqBgYEwMTHB4cOHAQAPHz7Es2fPsHnz5jzPvW7dOtjY2ODWrVtYsGABoqKi4ODggMGDByMsLAwHDhxAUFAQJk2aJD3G2dkZjx8/xoULF3Do0CFs27Ytz28yiIiIiIhKg1CO/5eWloZ3797J/KSlpeW4hvT0dNy8eRP29vbSbSoqKrC3t8eVK1fkug+pqanIyMiAgYFBoe4fl6RQAH/88Qe0tLSQmZmJtLQ0qKioYOvWrUhLS8PKlStx7tw5tGvXDgBgYWGBoKAg7Ny5E507d5b+QtSoUQN6enr5vk7Xrl0xc+ZM6ePx48dj5MiR0hHF+vXrY8uWLejcuTO2b9+O+Ph4/PXXX7h27RpatWoFAPDw8ICVlVXJ3wQiIiIiIgW0atUqLFmyRGbbokWLsHjxYpltL1++RFZWFoyMjGS2GxkZ4cGDB3K91uzZs2FsbCyTWMqDSaECsLOzw/bt25GSkoKNGzeiUqVKGDx4MO7du4fU1FR0795dZv/09HTY2toW+nVatmwp8zg0NBRhYWEyJaGCICA7OxsxMTGIiIhApUqV0KJFC+nzDRs2LDD5BIC0tLQc35AIggCJRFLouImIiIiIyqu5c+dixowZMtvU1dVL/HVWr14NPz8/BAQEoEqVKoU6lkmhAqhatSrq1asHAPD09ISNjQ08PDzQuHFjAMCff/6J2rVryxxTlF+0qlWryjxOTk7GhAkTMGXKlBz71qlTBxEREYV+jc9y+8ZEoqIFVVWdIp+TiIiIiJRTUbp8lhV1dXW5PptXr14dqqqqeP78ucz258+fo2bNmvkeu27dOqxevRrnzp1D06ZNCx0jk0IFo6Kignnz5mHGjBmIiIiAuro64uPj0blz51z3/zz3MCsrq9Cv1bx5c9y/f1+akP5Xw4YNkZmZiZs3b0rLRx8+fJhj+Yvc5PaNiUG1hoWOkYiIiIioIlBTU0OLFi3g7++PAQMGAIC0acy/e3r819q1a7FixQqcPn06R+WfvNhoRgENHToUqqqq2LlzJ9zc3DB9+nT4+PggKioKISEh+Pnnn+Hj4wMAMDU1hUQiwR9//IEXL14gOTlZ7teZPXs2Ll++jEmTJuH27duIjIzE8ePHpb+UlpaWcHBwwIQJE3D16lXcvHkT48ePh4aGRoHnVldXh46OjswPS0eJiIiISJnNmDEDu3btgo+PD8LDw/Hdd98hJSUFY8eOBQA4OTlh7ty50v3XrFmDBQsWwNPTE2ZmZkhISEBCQkKhPvMDHClUSJUqVcKkSZOwdu1axMTEwNDQEKtWrUJ0dDT09PTQvHlzzJs3DwBQu3ZtLFmyBHPmzMHYsWPh5OQEb29vuV6nadOmCAwMxPz589GxY0cIgoC6deti+PDh0n28vLwwfvx4dO7cGUZGRli+fDkWLFhQGpdNRERERJSrbAhih1Aihg8fjhcvXmDhwoVISEhAs2bNcOrUKWnzmfj4eKio/G9cb/v27UhPT8eQIUNkzpNbI5v8SARBqBh3kBReZbXaBe9EVAI4Kl14WmoFVwBQTu/SUsUOQeGo8N9nkaiqqIodgsLJzMoUOwSFlJFeuEXRy8pEs2Fih5CnbbEHxQ6hQCwfJSIiIiIiUmIsHyUiIiIiIoXG0sfi4UghERERERGREmNSSEREREREpMRYPkpERERERAqtonQfFQtHComIiIiIiJQYk0IiIiIiIiIlxvJRIiIiIiJSaNliB6DgOFJIRERERESkxJgUEhERERERKTGWjxIRERERkUIT2H20WDhSSEREREREpMSYFBIRERERESkxlo8SEREREZFCY/fR4uFIIRERERERkRJjUkhERERERKTEWD5KREREREQKjd1Hi4cjhUREREREREqMSSEREREREZESY/koEREREREpNHYfLR6OFBIRERERESkxJoVERERERERKjOWjRERERESk0LIFdh8tDo4UEhERERERKTEmhUREREREREqM5aNERERERKTQWDxaPBwpJCIiIiIiUmJMComIiIiIiJQYy0eJiIiIiEihZbOAtFg4UkhERERERKTEmBQSEREREREpMZaPEhERERGRQhNYPlosHCkkIiIiIiJSYkwKiYiIiIiIlBjLR4mIiIiISKFlix2AguNIIRERERERkRJjUkhERERERKTEWD5KREREREQKjYvXFw+TQio3zHRrih2Cwnn5IUnsEBSSXTVrsUNQOOde3hU7BIV0vWZLsUNQOGPSE8UOQSGZq1UTOwSF83OND2KHQFRusHyUiIiIiIhIiXGkkIiIiIiIFBoXry8ejhQSEREREREpMSaFRERERERESozlo0REREREpNC4eH3xcKSQiIiIiIhIiTEpJCIiIiIiUmIsHyUiIiIiIoUmCOw+WhwcKSQiIiIiIlJiTAqJiIiIiIiUGMtHiYiIiIhIoWVz8fpi4UghERERERGREmNSSEREREREpMRYPkpERERERAqNi9cXD0cKiYiIiIiIlBiTQiIiIiIiIiXG8lEiIiIiIlJoAruPFgtHComIiIiIiJQYk0IiIiIiIiIlxvJRIiIiIiJSaFy8vng4UkhERERERKTEmBQSEREREREpMZaPEhERERGRQhMElo8WB0cKiYiIiIiIlBiTQiIiIiIiIiXG8lEiIiIiIlJo2WIHoOA4UkhERERERKTEmBQSEREREREpMZaPEhERERGRQhO4eH2xcKSQiIiIiIhIiTEpJCIiIiIiUmIsHyUiIiIiIoWWzfLRYuFIIRERERERkRJjUkhERERERKTEWD5KREREREQKTRBYPlocSjlS2KVLF0ybNk3sMKSOHTuGevXqQVVVVe64nJ2dMWDAAOnjol7T4sWL0axZs0IfR0REREREFUO5SApfvHiB7777DnXq1IG6ujpq1qyJnj17Ijg4WLqPRCLBsWPHxAuyAP9N0gpjwoQJGDJkCB4/foxly5aVbGD/kts9dHNzg7+/f6m9JhERERERlW/lonx08ODBSE9Ph4+PDywsLPD8+XP4+/vj1atXYodW6pKTk5GYmIiePXvC2Ni4zF9fS0sLWlpaZf66RERERERUPog+Uvj27VtcunQJa9asgZ2dHUxNTdG6dWvMnTsX/fr1AwCYmZkBAAYOHAiJRCJ9nNvo3LRp09ClSxfp45SUFDg5OUFLSwu1atXC+vXrc8SQlpYGNzc31K5dG1WrVkWbNm0QEBAgfd7b2xt6eno4ffo0rKysoKWlBQcHBzx79gzApxJMHx8fHD9+HBKJBBKJROb4vAQEBEBbWxsA0LVrV+lxuZV0btq0SXrdRZHXPfzva32+pytXroSRkRH09PSwdOlSZGZmYtasWTAwMMAXX3wBLy8vmfM/fvwYw4YNg56eHgwMDNC/f3/ExsYWOV4iIiIiInllQyi3P4pA9KTw80jVsWPHkJaWlus+169fBwB4eXnh2bNn0sfymDVrFgIDA3H8+HGcOXMGAQEBCAkJkdln0qRJuHLlCvz8/BAWFoahQ4fCwcEBkZGR0n1SU1Oxbt067N69GxcvXkR8fDzc3NwAfCrBHDZsmDRRfPbsGdq3b19gbO3bt8fDhw8BAIcPH5b7uKIozD08f/48nj59iosXL2LDhg1YtGgRvvrqK+jr6+Pq1av49ttvMWHCBPzzzz8AgIyMDPTs2RPa2tq4dOkSgoODpYlzenp6qVwPERERERGVDNGTwkqVKsHb2xs+Pj7Q09NDhw4dMG/ePISFhUn3MTQ0BADo6emhZs2a0scFSU5OhoeHB9atW4du3bqhSZMm8PHxQWZmpnSf+Ph4eHl54bfffkPHjh1Rt25duLm54csvv5QZDcvIyMCOHTvQsmVLNG/eHJMmTZLOxdPS0oKGhoZ0PmTNmjWhpqZWYHxqamqoUaMGAMDAwEDu44qiMPfQwMAAW7ZsgaWlJVxcXGBpaYnU1FTMmzcP9evXx9y5c6GmpoagoCAAwIEDB5CdnQ13d3c0adIEVlZW8PLyQnx8vFwjpkREREREJB7Rk0Lg05zCp0+f4sSJE3BwcEBAQACaN28Ob2/vYp03KioK6enpaNOmjXSbgYEBLC0tpY/v3LmDrKwsNGjQQDpqqaWlhcDAQERFRUn309TURN26daWPa9WqhcTExGLFV1pWrlwpcy3x8fGFOr5Ro0ZQUfnfr4aRkRGaNGkifayqqopq1apJrz80NBSPHj2Ctra29DUNDAzw8eNHmXv4b2lpaXj37p3MjyBkF+FqiYiIiEjZCeX4f4qgXDSaAYAqVaqge/fu6N69OxYsWIDx48dj0aJFcHZ2zvMYFRWVHGuSZGRkFOp1k5OToaqqips3b0JVVVXmuX83YKlcubLMcxKJpNTWQynudX377bcYNmyY9HFhG9jkdq25bcvO/pTEJScno0WLFti7d2+Oc+U1Irlq1SosWbJEZpu+Rk1Uq1r2zXaIiIiIiJRZuUkK/8va2lpm+YTKlSsjKytLZh9DQ0PcvXtXZtvt27elCUzdunVRuXJlXL16FXXq1AEAvHnzBhEREejcuTMAwNbWFllZWUhMTETHjh2LHK+amlqO+IrK0NAQCQkJEAQBEokEwKfrkpeBgQEMDAxybM/tHpaE5s2b48CBA6hRowZ0dHTkOmbu3LmYMWOG7HksOpd4bERERERElD/Ry0dfvXqFrl27Ys+ePQgLC0NMTAx+++03rF27Fv3795fuZ2ZmBn9/fyQkJODNmzcAPnXsvHHjBnx9fREZGYlFixbJJIlaWloYN24cZs2ahfPnz+Pu3btwdnaWKY1s0KABRo4cCScnJxw5cgQxMTG4du0aVq1ahT///FPu6zAzM0NYWBgePnyIly9fFnrE8t+6dOmCFy9eYO3atYiKisIvv/yCv/76q8jn+3eM/72HJWHkyJGoXr06+vfvj0uXLiEmJgYBAQGYMmWKtBnNf6mrq0NHR0fmRyIR/deRiIiIiBRQtiCU2x9FIPqncC0tLbRp0wYbN25Ep06d0LhxYyxYsACurq7YunWrdL/169fj7NmzMDExga2tLQCgZ8+eWLBgAX744Qe0atUK79+/h5OTk8z5f/rpJ3Ts2BF9+/aFvb09vvzyS7Ro0UJmHy8vLzg5OWHmzJmwtLTEgAEDcP36denoojxcXV1haWmJli1bwtDQEMHBwQA+JXj5lcDmxsrKCtu2bcMvv/wCGxsbXLt2TdrptDhyu4clQVNTExcvXkSdOnUwaNAgWFlZYdy4cfj48aPcI4dERERERCQOiVBaE+MIAGBqaoolS5YUOjFURvUNWxS8E8l4+SFJ7BAUkl01a7FDUDjnXt4teCfKIbBak4J3Ihlj0stnE7fyzlytmtghKJyfa3wQOwSFVOeGv9gh5KpT7W5ih5Cni0/K5z37t3I7p7AiuHfvHnR1dXOMXhIRERERUcnhKFfxMCksRY0aNZJZb5GIiIiIiKi8EX1OIREREREREYmHI4VERERERKTQsllAWiwcKSQiIiIiIlJiTAqJiIiIiIiUGMtHiYiIiIhIobF8tHg4UkhERERERKTEmBQSEREREREpMZaPEhERERGRQhMElo8WB0cKiYiIiIiIlBiTQiIiIiIiIiXGpJCIiIiIiBRaNoRy+1NYv/zyC8zMzFClShW0adMG165dy3Pfe/fuYfDgwTAzM4NEIsGmTZuKdP+YFBIREREREZUDBw4cwIwZM7Bo0SKEhITAxsYGPXv2RGJiYq77p6amwsLCAqtXr0bNmjWL/LpMComIiIiIiMqBDRs2wNXVFWPHjoW1tTV27NgBTU1NeHp65rp/q1at8NNPP2HEiBFQV1cv8uuy+ygRERERESk0oRwvXp+Wloa0tDSZberq6jmSuPT0dNy8eRNz586VblNRUYG9vT2uXLlSqjFypJCIiIiIiKiUrFq1Crq6ujI/q1atyrHfy5cvkZWVBSMjI5ntRkZGSEhIKNUYOVJIRERERERUSubOnYsZM2bIbCtOqWdpYFJIREREREQKrTwvXp9bqWhuqlevDlVVVTx//lxm+/Pnz4vVREYeLB8lIiIiIiISmZqaGlq0aAF/f3/ptuzsbPj7+6Ndu3al+tocKSQiIiIiIioHZsyYgTFjxqBly5Zo3bo1Nm3ahJSUFIwdOxYA4OTkhNq1a0vnJKanp+P+/fvS/37y5Alu374NLS0t1KtXT+7XZVJIREREREQKrSiLxJdHw4cPx4sXL7Bw4UIkJCSgWbNmOHXqlLT5THx8PFRU/lfs+fTpU9ja2kofr1u3DuvWrUPnzp0REBAg9+syKSQiIiIiIionJk2ahEmTJuX63H8TPTMzsxKZT8k5hUREREREREqMI4VERERERKTQynP3UUXAkUIiIiIiIiIlxqSQiIiIiIhIibF8lIiIiIiIFFpF6T4qFo4UEhERERERKTEmhUREREREREqM5aNERERERKTQBJaPFgtHComIiIiIiJQYk0IiIiIiIiIlxvJRIiIiIiJSaNlcvL5YOFJIRERERESkxJgUEhERERERKTGWjxIRERERkUJj99HiYVJI5Ubih7dih6BwMrOzxA5BIV17Hy12CAonLStD7BAUUv9k/q4VVnp2ptghKKSkjBSxQ1A4nWMkYoegkGLEDoBKBctHiYiIiIiIlBhHComIiIiISKGx+2jxcKSQiIiIiIhIiTEpJCIiIiIiUmIsHyUiIiIiIoXG7qPFw5FCIiIiIiIiJcakkIiIiIiISImxfJSIiIiIiBQau48WD0cKiYiIiIiIlBiTQiIiIiIiIiXG8lEiIiIiIlJo7D5aPBwpJCIiIiIiUmJMComIiIiIiJQYy0eJiIiIiEihsfto8XCkkIiIiIiISIkxKSQiIiIiIlJiLB8lIiIiIiKFxu6jxcORQiIiIiIiIiXGpJCIiIiIiEiJsXyUiIiIiIgUmiBkix2CQuNIIRERERERkRJjUkhERERERKTEWD5KREREREQKLZvdR4uFI4VERERERERKjEkhERERERGREmP5KBERERERKTRBYPlocXCkkIiIiIiISIkxKSQiIiIiIlJiLB8lIiIiIiKFxu6jxcORQiIiIiIiIiXGpJCIiIiIiEiJsXyUiIiIiIgUGruPFg9HComIiIiIiJQYk0IiIiIiIiIlxvJRIiIiIiJSaNksHy0WjhQSEREREREpsQqZFHbp0gXTpk0TO4xyLyAgABKJBG/fvhU7FCIiIiIiEkmZJIUvXrzAd999hzp16kBdXR01a9ZEz549ERwcLN1HIpHg2LFjZRFOkTg7O2PAgAFihyEjNjYWEokEt2/fLnDf3BLl9u3b49mzZ9DV1S2dAImIiIiIyoBQjv+nCMpkTuHgwYORnp4OHx8fWFhY4Pnz5/D398erV6/K4uUrpPT09GKfQ01NDTVr1iyBaIiIiIiISFGV+kjh27dvcenSJaxZswZ2dnYwNTVF69atMXfuXPTr1w8AYGZmBgAYOHAgJBKJ9HFuo3PTpk1Dly5dpI9TUlLg5OQELS0t1KpVC+vXr88RQ1paGtzc3FC7dm1UrVoVbdq0QUBAgPR5b29v6Onp4fTp07CysoKWlhYcHBzw7NkzAMDixYvh4+OD48ePQyKRQCKRyByfn8/nPnbsGOrXr48qVaqgZ8+eePz4sXSfqKgo9O/fH0ZGRtDS0kKrVq1w7tw5mfOYmZlh2bJlcHJygo6ODr755huYm5sDAGxtbSGRSGTuy785OzsjMDAQmzdvlsYfGxubo3z0c6x//PEHLC0toampiSFDhiA1NRU+Pj4wMzODvr4+pkyZgqysLLnvLxERERERlV+lnhRqaWlBS0sLx44dQ1paWq77XL9+HQDg5eWFZ8+eSR/LY9asWQgMDMTx48dx5swZBAQEICQkRGafSZMm4cqVK/Dz80NYWBiGDh0KBwcHREZGSvdJTU3FunXrsHv3bly8eBHx8fFwc3MDALi5uWHYsGHSRPHZs2do37693DGmpqZixYoV8PX1RXBwMN6+fYsRI0ZIn09OTkbv3r3h7++PW7duwcHBAX379kV8fLzMedatWwcbGxvcunULCxYswLVr1wAA586dw7Nnz3DkyJFcX3/z5s1o164dXF1dpfGbmJjkGeuWLVvg5+eHU6dOISAgAAMHDsTJkydx8uRJ7N69Gzt37sShQ4cKdX+JiIiIiEqLIAjl9kcRlHr5aKVKleDt7Q1XV1fs2LEDzZs3R+fOnTFixAg0bdoUAGBoaAgA0NPTK1Q5Y3JyMjw8PLBnzx5069YNAODj44MvvvhCuk98fDy8vLwQHx8PY2NjAJ+SvFOnTsHLywsrV64EAGRkZGDHjh2oW7cugE+JztKlSwF8Smw1NDSQlpZWpHLLjIwMbN26FW3atJHGaGVlhWvXrqF169awsbGBjY2NdP9ly5bh6NGjOHHiBCZNmiTd3rVrV8ycOVP6WFVVFQBQrVq1fOPS1dWFmpoaNDU1C4w/IyMD27dvl96HIUOGYPfu3Xj+/Dm0tLRgbW0NOzs7XLhwAcOHD5f7/v5XWlpaji8JBEGARCLJNz4iIiIiIipZZdJoZvDgwXj69ClOnDgBBwcHBAQEoHnz5vD29i7WeaOiopCeni5NtgDAwMAAlpaW0sd37txBVlYWGjRoIB211NLSQmBgIKKioqT7aWpqShMhAKhVqxYSExOLFd9nlSpVQqtWraSPGzZsCD09PYSHhwP4lNy6ubnBysoKenp60NLSQnh4eI6RwpYtWxb4WpcuXZK5zr179xYq1v/eByMjI5iZmUFLS0tm2+d7I+/9/a9Vq1ZBV1dX5ict402hYiUiIiIiouIrs8Xrq1Spgu7du6N79+5YsGABxo8fj0WLFsHZ2TnPY1RUVHIMuWZkZBTqdZOTk6GqqoqbN29KR9Y++3eiU7lyZZnnJBJJmQ33urm54ezZs1i3bh3q1asHDQ0NDBkyJEczmapVqxZ4rpYtW8p0IzUyMipULLndh9y2ZWdnA5D//v7X3LlzMWPGDJltX9RqVqhYiYiIiIgAIFtBunyWV2WWFP6XtbW1zBIUlStXlmleAnwqK717967Mttu3b0uTlLp166Jy5cq4evUq6tSpAwB48+YNIiIi0LlzZwCfmrBkZWUhMTERHTt2LHK8ampqOeKTV2ZmJm7cuIHWrVsDAB4+fIi3b9/CysoKABAcHAxnZ2cMHDgQwKdEKzY2Vq6YAMjEpaGhgXr16pVo/Pkp6v1VV1eHurq6zDaWjhIRERERlb1SLx999eoVunbtij179iAsLAwxMTH47bffsHbtWvTv31+6n5mZGfz9/ZGQkIA3bz6VEXbt2hU3btyAr68vIiMjsWjRIpkkUUtLC+PGjcOsWbNw/vx53L17F87OzlBR+d9lNWjQACNHjoSTkxOOHDmCmJgYXLt2DatWrcKff/4p93WYmZkhLCwMDx8+xMuXLws1Ylm5cmVMnjwZV69exc2bN+Hs7Iy2bdtKk8T69evjyJEjuH37NkJDQ+Ho6CgdictPjRo1oKGhgVOnTuH58+dISkrKN/6rV68iNjYWL1++lOv88iip+0tEREREROIok+6jbdq0wcaNG9GpUyc0btwYCxYsgKurK7Zu3Srdb/369Th79ixMTExga2sLAOjZsycWLFiAH374Aa1atcL79+/h5OQkc/6ffvoJHTt2RN++fWFvb48vv/wSLVq0kNnHy8sLTk5OmDlzJiwtLTFgwABcv35dOrooD1dXV1haWqJly5YwNDREcHAwgE+LwudXAgt8mqc3e/ZsODo6okOHDtDS0sKBAwekz2/YsAH6+vpo3749+vbti549e6J58+YFxlSpUiVs2bIFO3fuhLGxsUyS/V9ubm5QVVWFtbU1DA0Nc8xXLI6SuL9EREREREUldodRRe8+KhEUJdJyytTUFEuWLMkzMfT29sa0adOkawFS3nS16ha8E8nIzC75kmBloF8l7/mulLsXqXlXIlDejDT1xA5B4aRnZ4odgkJSV61c8E4kQwWctlIUMa9CxQ4hV9V1GogdQp5evosQO4QClUn30Yrq3r170NXVzTF6SUREREREpChEazRTETRq1AhhYWFih0FEREREpNSyWfxYLBwpLGXOzs4sHSUiIiIionKLSSEREREREZESY/koEREREREpNPbOLB6OFBIRERERESkxJoVERERERERKjOWjRERERESk0LLB8tHi4EghERERERGREmNSSEREREREpMRYPkpERERERAqN3UeLhyOFRERERERESoxJIRERERERkRJj+SgRERERESm0bJaPFgtHComIiIiIiJQYk0IiIiIiIiIlxvJRIiIiIiJSaAIXry8WjhQSEREREREpMSaFRERERERESozlo0REREREpNDYfbR4OFJIRERERESkxJgUEhERERERKTGWjxIRERERkUITWD5aLBwpJCIiIiIiUmJMComIiIiIiJQYy0eJiIiIiEihcfH64uFIIRERERERkRJjUkhERERERKTEWD5KREREREQKjd1Hi4cjhUREREREREqMSSEREREREZESY/koEREREREpNJaPFg9HComIiIiIiJQYk0IiIiIiIiIlxvJRIiIiIiJSaCweLR6OFBIRERERESkxJoVERERERERKTCKwVQ9RntLS0rBq1SrMnTsX6urqYoejMHjfCo/3rGh43wqP96xoeN8Kj/esaHjfSAxMCony8e7dO+jq6iIpKQk6Ojpih6MweN8Kj/esaHjfCo/3rGh43wqP96xoeN9IDCwfJSIiIiIiUmJMComIiIiIiJQYk0IiIiIiIiIlxqSQKB/q6upYtGgRJ3oXEu9b4fGeFQ3vW+HxnhUN71vh8Z4VDe8biYGNZoiIiIiIiJQYRwqJiIiIiIiUGJNCIiIiIiIiJcakkIiIiIiISIkxKSQiIiIiIlJiTAqJiIiIqERERUXhxx9/xNdff43ExEQAwF9//YV79+6JHBkR5YfdR4n+38WLF2FjYwNdXV2xQ1EovG+5MzMzg4uLC5ydnVGnTh2xw6kQunbtCjs7O8ycOROamppih6M0srOzERgYiEuXLiEuLg6pqakwNDSEra0t7O3tYWJiInaIJS4+Ph61a9eGqqqq2KEolMDAQPTq1QsdOnTAxYsXER4eDgsLC6xevRo3btzAoUOHxA6x3Bg0aJDc+x45cqQUIyH6hCOFRP+vS5cusLCwwPr168UORaHwvuVu2rRpOHLkCCwsLNC9e3f4+fkhLS1N7LAUWp06deDv74+GDRuKHYpS+PDhA5YvXw4TExP07t0bf/31F96+fQtVVVU8evQIixYtgrm5OXr37o2///5b7HBLlJmZGaytrflhvJDmzJmD5cuX4+zZs1BTU5Nu79q1a4X7HSkuXV1duX+IygJHCon+X1xcHKKjo/HXX39h7dq1YoejMHjf8hcSEgJvb2/s378fWVlZcHR0hIuLC5o3by52aArr3bt30NHRETuMCs/ExATt2rWDs7MzunfvjsqVK+fYJy4uDvv27cPOnTsxf/58uLq6ihBpyQsMDER0dDROnTqFAwcOiB2OwtDS0sKdO3dgbm4ObW1thIaGwsLCArGxsWjYsCE+fvwodohElAcmhUREZSAjIwPbtm3D7NmzkZGRgSZNmmDKlCkYO3YsJBKJ2OFRBZaVlQVvb2/4+/sjMTER2dnZMs+fP38+1+PCw8NhZWUl12tkZGQgPj4edevWLXa8pLi++OILHDx4EO3bt5dJCo8ePQo3NzdERUWJHWK59uLFCzx8+BAAYGlpCUNDQ5EjImVSSewAiIgqsoyMDBw9ehReXl44e/Ys2rZti3HjxuGff/7BvHnzcO7cOezbt0/sMMuF7OxseHt748iRI4iNjYVEIoG5uTmGDBmC0aNHM3kuoqlTp8Lb2xt9+vRB48aN5b6P8iaEAFC5cmUmhIQRI0Zg9uzZ+O233yCRSJCdnY3g4GC4ubnByclJ7PDKrZSUFEyePBm+vr7SL21UVVXh5OSEn3/+mXOoqUxwpJAIwJgxY/D48eM8vzGn3PG+5S0kJAReXl7Yv38/VFRU4OTkhPHjx8vMh7t79y5atWqFDx8+iBhp+SAIAvr27YuTJ0/CxsYGDRs2hCAICA8Px507d9CvXz8cO3ZM7DAVUvXq1eHr64vevXuLHYpCmDdvHhISEuDp6Sl2KAonPT0d33//Pby9vZGVlYVKlSpJy+a9vb3ZuCcPEyZMwLlz57B161Z06NABABAUFIQpU6age/fu2L59u8gRkjLgSCERgNq1a0NFhX2XCov3LW+tWrWSvpkPGDAg1/lY5ubmGDFihAjRlT/e3t64ePEi/P39YWdnJ/Pc+fPnMWDAAPj6+nK0oQjU1NRQr169Ujm3lZUVIiIikJWVVSrnF8OTJ0/w+PFjscNQSGpqati1axcWLlyIO3fuIDk5Gba2tqhfv77YoZVrhw8fxqFDh9ClSxfptt69e0NDQwPDhg1jUkhlgiOFRESlIC4uDqampmKHoTB69OiBrl27Ys6cObk+v3LlSgQGBuL06dNlHJniW79+PaKjo7F169YSL8E9duwYkpKSMGbMmBI9L1UMWVlZuHPnDkxNTaGvry92OOWWpqYmbt68maNk+969e2jdujVSUlJEioyUCZNCUmqZmZn4+PEjtLS0xA5FofC+UUmrWbMmTp06hWbNmuX6/K1bt9CrVy8kJCSUbWAVwMCBA3HhwgUYGBigUaNGOUatuewClZRp06ahSZMmGDduHLKystC5c2dcvnwZmpqa+OOPP2RGwuh/unXrhmrVqsHX1xdVqlQB8GlJmDFjxuD169c4d+6cyBGSMmDdFymF33//Hd7e3jLbVqxYAS0tLejp6aFHjx548+aNOMGVY7xvhaOvrw8DAwO5fkjW69evYWRklOfzRkZG/F0rIj09PQwcOBCdO3dG9erVi7QGWkxMDCIjI3Nsj4yMRGxsbAlHXLquXLmCP/74Q2abr68vzM3NUaNGDXzzzTdcU7SIDh06BBsbGwCf3j+io6Px4MEDTJ8+HfPnzxc5uvJr8+bNCA4OxhdffIFu3bqhW7duMDExweXLl7F582axwyMlwZFCUgp2dnYYMmQIvv/+ewDA5cuX0bFjRyxduhRWVlaYP38+evXqhQ0bNogcafnC+1Y4Pj4+0v9+9eoVli9fjp49e6Jdu3YAPn0YPX36NBYsWIDp06eLFWa5pKqqioSEhDxbsD9//hzGxsYVau6aIuncuTNcXFxylInu2bMH7u7uCAgIECewIujVqxe6dOmC2bNnAwDu3LmD5s2bw9nZGVZWVvjpp58wYcIELF68WNxAFVCVKlXw6NEjfPHFF/jmm2+gqamJTZs2ISYmBjY2Nnj37p3YIZZbqamp2Lt3Lx48eADg03zdkSNHQkNDQ+TISFkwKSSlUKNGDZw+fRq2trYAgBkzZuD+/fs4deoUAODkyZOYOnVqrt+EKzPet6IbPHgw7OzsMGnSJJntW7duxblz59hJ8z9UVFTQq1cvqKur5/p8WloaTp06xaRQJDo6OggJCcnRsObRo0do2bIl3r59K05gRVCrVi38/vvvaNmyJQBg/vz5CAwMRFBQEADgt99+w6JFi3D//n0xw1RIpqam2LVrF7p16wZzc3Ns374dffr0wb179/Dll19ytJ+oHGP3UVIK79+/R7Vq1aSPg4KCMHToUOnjRo0a4enTp2KEVq7xvhXd6dOnsWbNmhzbHRwc8mymoszkaVTCzqNFd+jQIRw8eBDx8fFIT0+XeS4kJKTA4yUSCd6/f59je1JSksIl6m/evJEpVQ4MDESvXr2kj1u1asXuo0U0duxYDBs2DLVq1YJEIoG9vT0A4OrVqzLL8VBOUVFR2LRpE8LDwwF8en+dMmUK1/+kMsOkkJRC7dq1ER4ejjp16iA5ORmhoaHYuHGj9PlXr15xcdhc8L4VXbVq1XD8+HHMnDlTZvvx48dlEm36xMvLS+wQKqwtW7Zg/vz5cHZ2xvHjxzF27FhERUXh+vXr0tLwgnTq1AmrVq3C/v37pWvNZWVlYdWqVfjyyy9LM/wSZ2RkhJiYGJiYmCA9PR0hISFYsmSJ9Pn379/nuoQMFWzx4sVo3LgxHj9+jKFDh0pH/lVVVfllWD5Onz6Nfv36oVmzZtJ1CoODg7Fz5078/vvv6N69u8gRkjJgUkhKYejQoZg2bRrmzZuHkydPombNmmjbtq30+Rs3bsDS0lLECMsn3reiW7JkCcaPH4+AgAC0adMGwKdvy0+dOoVdu3aJHB0pk23btuHXX3/F119/DW9vb/zwww+wsLDAwoUL8fr1a7nOsXr1anTu3BmWlpbo2LEjAODSpUt49+4dzp8/X5rhl7jevXtjzpw5WLNmDY4dOwZNTU3pNQFAWFgYR2eKYciQITm2ccmS/M2ZMwfTp0/H6tWrc2yfPXs2k0IqE5xTSErhw4cPmDBhAn7//XfUrFkTv/76q8yHADs7Ozg4OEgbD9AnvG/Fc/XqVWzZskVaDmRlZYUpU6ZIk0T6HxcXF7n28/T0LOVIKh5NTU2Eh4fD1NQUNWrUwNmzZ2FjY4PIyEi0bdsWr169kus8T58+xdatWxEaGgoNDQ00bdoUkyZNUrhuui9fvsSgQYMQFBQELS0t+Pj4YODAgdLnu3XrhrZt22LFihUiRqk4tmzZIve+U6ZMKcVIFFeVKlVw584d1K9fX2Z7REQEmjZtio8fP4oUGSkTJoVERCQ6FRUVmJqawtbWFvm9LR09erQMo6oYLCwscPjwYdja2qJly5ZwdXXFhAkTcObMGYwYMUKu0cL4+HiYmJhAIpHk+lydOnVKI/RSlZSUBC0tLWk57GevX7+GlpYW1NTURIpMsZibm8u1n0QiQXR0dClHo5hMTEywYcMGmTn7AHDw4EG4ubkhPj5epMhImbB8lIioFBT0Ji7Ph+jdu3djx44diImJwZUrV2BqaopNmzbB3Nwc/fv3L6lQy4XvvvsO+/fvR0xMDMaOHYtRo0Yp3AhUedW1a1ecOHECtra2GDt2LKZPn45Dhw7hxo0bGDRokFznMDc3x7Nnz1CjRg2Z7a9evYK5ubnCNZsBkOcajfy9K5yYmBixQ1B4rq6u+OabbxAdHY327dsD+DSncM2aNZgxY4bI0ZGy4EghEYB58+YhISGBpWmFxPuWNxUVlVxHVT4r6EP09u3bsXDhQkybNg0rVqzA3bt3YWFhAW9vb/j4+ODChQslHbLo0tLScOTIEXh6euLy5cvo06cPxo0bhx49euR7Lyl/2dnZyM7ORqVKn74H9vPzw+XLl1G/fn1MmDBBrhExFRUVPH/+PMc6knFxcbC2tkZKSkqpxC6Gbdu24eXLl1i4cKHYoSis9PR0xMTEoG7dutLfO8qbIAjYtGkT1q9fL+3obWxsjFmzZmHKlCn8+0dlgkkhET5Ngn/8+LHCNUwQG+9b3kJDQ2UeZ2Rk4NatW9iwYQNWrFhR4AiNtbU1Vq5ciQEDBkBbWxuhoaGwsLDA3bt30aVLF7x8+bI0wxddXFwcvL294evri8zMTNy7dw9aWlpih6V0Po9SbN68Ga6urjLdhrOysnD16lWoqqoiODhYrBBLXLdu3RATE8NSxyJITU3F5MmT4ePjA+DTnDgLCwtMnjwZtWvXZgdSOXxe+kVbW1vkSEjZ8OsbIkD6BkaFw/uWNxsbmxzbWrZsCWNjY/z0008FJoUxMTGwtbXNsV1dXb1Cjcrk5fNIqyAIClmaWN58/PgRYWFhSExMRHZ2tsxz/fr1y/O4W7duAfg0knHnzh2ZUUU1NTXY2NjAzc2tdIIWib+/v9ghKKy5c+ciNDQUAQEBcHBwkG63t7fH4sWLmRTKgckgiYVJIRFRGbK0tMT169cL3M/c3By3b9+GqampzPZTp07BysqqtMIT1b/LR4OCgvDVV19h69atcHBwgIqKitjhKaxTp07Byckp19FliUSSb9L9uUx57Nix2Lx5M3R0dEotzvIiPDwcHh4eWLdundihKJxjx47hwIEDaNu2rUzJY6NGjRAVFSViZOXb8+fP4ebmBn9/fyQmJuZotsUvxqgsMCkkpfH+/XtERETA0tISWlpaCAkJwaZNm/DhwwcMGDAAI0eOFDvEcsfX11eu/ZycnEo5EsXz7t07mceCIODZs2dYvHhxjrbjuZkxYwa+//57fPz4EYIg4Nq1a9i/fz9WrVoFd3f30gpbNBMnToSfnx9MTEzg4uKC/fv3o3r16mKHVSFMnjwZQ4cOxcKFC2FkZFSkc3h5eQEAHj16hKioKHTq1AkaGhoQBKFCzHdKSUmBn58fPDw88Pfff8Pa2ppJYRG8ePEiRzMi4NP9rQi/J6XF2dkZ8fHxWLBgAWrVqsV7RaLgnEJSChcvXsRXX32F5ORk6OvrY//+/RgyZAhq164NVVVVhIeHY8eOHXB1dRU71HJFRUUFWlpaqFSpUp7LBEgkErkXwFYmuTWaEQQBJiYm8PPzQ7t27Qo8x969e7F48WLpN+zGxsZYsmQJxo0bVyoxi0lFRQV16tSBra1tvh+Ijhw5UoZRVQw6Ojq4detWsRZkf/36NYYOHYoLFy5AIpEgMjISFhYWcHFxgb6+PtavX1+CEZed4OBgeHh44ODBg/jw4QOmT5+O8ePHo2HDhmKHppA6deqEoUOHYvLkydDW1kZYWBjMzc0xefJkREZG4tSpU2KHWC5pa2vj0qVLaNasmdihkBLjSCEphR9//BFDhw7F0qVL4enpieHDh2PSpElYuXIlAGD58uX45ZdfmBT+h5WVFZ4/f45Ro0bBxcUFTZs2FTskhfHf7qAqKiowNDREvXr15O7GN3LkSIwcORKpqalITk7O9Rv4isLJyYnfjpeSIUOGICAgoFhJ4bRp01C5cmXEx8fLlC8PHz4cM2bMUKikMDExEd7e3vD09ERSUhK+/vprBAQEoF27dnBxcWFCWAwrV65Er169cP/+fWRmZmLz5s24f/8+Ll++jMDAQLHDK7dMTEzyXZ+VqCxwpJCUgp6eHv7++280bNgQ6enp0NDQQEhIiLQZyKNHj2Brayvt+kX/c/XqVXh6euLAgQOoV68exo0bh5EjRyrF3KLiuHjxItq3b58jAczMzMTly5fRqVOnAs+RmZmJgIAAREVFwdHREdra2nj69Cl0dHTYiZPklpqaiqFDh8LQ0BBNmjRB5cqVZZ6fMmVKgeeoWbMmTp8+DRsbG5luuNHR0WjatCmSk5NLK/wSp6GhgSFDhmDUqFHo3r27dL5q5cqVERoaCmtra5EjVGxRUVFYvXo1QkNDkZycjObNm2P27Nlo0qSJ2KGVW2fOnMH69euxc+dOmJmZiR0OKSkmhaQUVFRUkJCQIB1p+feHGuDTJG9jY2NO5s7Hhw8f8Ntvv8HLywvXrl3DgAED4OnpCXV1dbFDK5dUVVXzXOy7Ro0aBf6uxcXFwcHBAfHx8UhLS5O2dp86dSrS0tKwY8eO0gyfKhAPDw98++23qFKlCqpVqyYzIiuRSORaekFbWxshISGoX7++zN/PGzduoGfPnnj16lVpXkKJatiwIdLS0uDo6IjRo0dLRwaZFFJZ0tfXl/m3mJKSgszMTGhqaub44oZTNKgssHyUlIJEIsnxQYilaoWjoaEBJycnmJmZYdGiRfDz88PWrVuZFOYhrwYcr169QtWqVQs8furUqWjZsiVCQ0NRrVo16faBAweyzJkKZf78+ViyZAnmzJlT5C6uHTt2hK+vL5YtWwbg09/Q7OxsrF27FnZ2diUZbql78OCBdC5hq1at0KBBA4waNQoA+L5AZWbTpk1ih0AkgyOFpBRUVFTQuHFjaSlfWFgYGjZsKF1z6/Pi2BwpzN2TJ0/g4+MDLy8vpKSkSOcYcu5NTp/XHzx+/DgcHBxkkuasrCyEhYXB0tKywIYL1apVw+XLl2FpaSkzMhMbGwtra2ukpqaW6nVQxWFgYIDr168Xa07h3bt30a1bNzRv3hznz59Hv379cO/ePbx+/RrBwcHFOreYkpOTsX//fnh5eeHvv/9G586d4ejoiAEDBsDQ0FDs8IiIygxHCkkpLFq0SOZx//79c+wzePDgsgpHYRw8eBBeXl4IDAxEz549sX79evTp0weqqqpih1Zu6erqAvg0UqitrQ0NDQ3pc2pqamjbtq1cI33Z2dm5fknxzz//cHFjKpQxY8bgwIEDmDdvXpHP0bhxY0RERGDr1q3Q1tZGcnIyBg0ahO+//x61atUqwWjLlpaWFlxdXeHq6ipdn/DHH3/ExIkTkZGRIXZ4pCROnjwJVVVV9OzZU2b7mTNnkJWVhV69eokUGSkTjhQSUZ4+LxMwcuTIfNc3k6dRhbJZsmQJ3Nzc5CoVzc3w4cOhq6uLX3/9Vdra3dDQEP3790edOnWk68YRFWTKlCnw9fWFjY0NmjZtmmO+0oYNG0SKrHzKzMzEiRMnpKP+RKWtadOmWL16NXr37i2z/dSpU5g9ezZCQ0NFioyUCZNCIsqTmZlZgXNs5G1UoWw+fPgAQRCgqakJ4FPjmKNHj8La2ho9evQo8PjHjx/DwcEBgiAgMjISLVu2RGRkJKpXr46LFy9W6OUp8nLx4kXY2NhIR2NJPvnN+ZNIJDh//nwZRkNE/6WhoYHw8PAcnUdjY2PRqFEjpKSkiBMYKRUmhUREpaBHjx4YNGgQvv32W7x9+xaWlpZQU1PDy5cvsWHDBnz33XcFniMzMxMHDhyQae0+cuRImZJUZaKiogJ9fX3MmzcPM2fOFDsc0dnb2yM6OjrfL2WysrIQHByMJk2aQF9fvwyjI2U0cODAXL9IlEgkqFKlCurVqwdHR0dYWlqKEF35VbNmTezbtw9du3aV2X7u3Dk4OjoiMTFRpMhImRStDRkREeUrJCQEHTt2BAAcOnQINWvWRFxcHHx9fbFly5Z8j83IyEDdunURGRmJkSNHYu3atdi2bRvGjx+vtAkhAMTExODQoUN4/vy52KGUCwMHDsSYMWPy3UdVVRU9evTA27dvyyYoUmq6uro4f/48QkJCpF2+b926hfPnz0u/5LKxsUFwcLDYoZYr/fv3x7Rp0xAVFSXd9ujRI8ycORP9+vUTMTJSJmw0Q0SlKjw8HH5+frh06RLi4uKQmpoKQ0ND2NraomfPnhg8eHCFXNYiNTVV2hDmzJkzGDRoEFRUVNC2bVvExcXle2zlypXx8ePHsghToZiamsLU1FThlkAoLd9//71c+zVu3BjR0dEwNzcv5YhI2dWsWROOjo7YunWrdPmT7OxsTJ06Fdra2vDz88O3336L2bNnIygoSORoy4+1a9fCwcEBDRs2xBdffAHgU1Oxjh07Yt26dSJHR8qC5aNEVCpCQkLwww8/ICgoCB06dEDr1q1hbGwMDQ0NvH79Gnfv3sWlS5fw7t07/PDDD5g2bVqFSg6bNm2K8ePHY+DAgWjcuDFOnTqFdu3a4ebNm+jTpw8SEhLyPX7lypWIiIiAu7u7dCkVZSAIAm7evInY2FhIJBKYm5vD1taW68cVw6lTpzB37lwsW7YMLVq0yNH8SEdHR6TIqKIxNDREcHAwGjRoILM9IiIC7du3x8uXL3Hnzh107NiRo9f/IQgCzp49i9DQUGhoaKBp06bo1KmT2GGREmFSSPT/fH190aFDB4Vdb6u8MTc3x6xZs+Do6Ag9Pb0897ty5Qo2b96Mpk2bFqtlfnlz6NAhODo6IisrC926dcOZM2cAAKtWrcLFixfx119/5Xv8wIED4e/vDy0tLTRp0iTHB/kjR46UWuxiuXDhAsaNG4e4uDh8fmv6nBh6enoq7Qek4s7T+veC9f8+jyAIkEgkxV6ftWvXrrCzs8PMmTOljZUUnYuLC+zs7DB69GixQ1Eo+vr68PHxyVHyeOLECYwZMwZv3rxBZGQkWrdujTdv3ogUpWJ4+/Ztvu+dRCWNSSHR/1NRUUHlypXxzTff4OeffxY7HIWXkZGRo/V9Se6vCBISEvDs2TPY2NhIP5hfu3YNOjo6aNiwYb7Hjh07Nt/nK9qSFI8ePYKNjQ3atGmDqVOnomHDhhAEAffv38eWLVtw48YNhIWFwcLCQuxQy5yzszOOHTsGPT09tGjRAsCnkfi3b9+iR48eCA0NRWxsLPz9/dGhQ4ccxwcGBuZ7/s6dOxc7vtjYWERHRyM+Pr5Y5yovunTpgtjYWOjp6eH27dtih6MwpkyZgv3792PevHlo1aoVAOD69etYuXIlHB0dsXnzZri7u8Pb25vlo/+yZs0amJmZYfjw4QCAYcOG4fDhw6hZsyZOnjwJGxsbkSMkZcCkkOhfYmJi8Ndff2HixIlih0KkVCZNmoTw8HD4+/vneE4QBNjb28Pa2lopv7CZM2cO3r17l+c8rRUrVuDbb7/FvXv3RP2g/e7duwpXinr//n1YW1uLHYbCyMrKwurVq7F161ZpQygjIyNMnjwZs2fPhqqqKuLj46GioiKdO0efKmv27t2L9u3b4+zZsxg2bBgOHDiAgwcPIj4+XlppQlSamBQSUbGoqKigS5cu+Omnn6SjGPK6ceMGUlNTlbYskP6ncePGWLVqFfr27Zvr87///jvmzp2Lu3fvlnFk4iuJeVqXLl3Czp07ER0djd9++w21a9fG7t27YW5uji+//LIMroKUzbt37wBwzqo8NDQ0EBERARMTE0ydOhUfP37Ezp07ERERgTZt2rDUlsqE8nQvIKJS4enpidjYWHz//ff4+++/C3Xs6NGjERERUew5TRVRXs1V/j2PzNnZucJ04oyPj0eTJk3yfL5x48YFdm2tqDIzM/HgwYMcSeGDBw+k/3aqVKmSZzOew4cPY/To0Rg5ciRCQkKQlpYGAEhKSsLKlStx8uRJueK4fv06Lly4gMTERGRnZ8s8t2HDhsJeVrn17NkzZGRkoE6dOmKHotCYDMpPX18fjx8/homJCU6dOoXly5cD+FQlwfdHKitcp5AInxaBVsa5SiXB2dkZixcvLnRCCAD+/v75LrytzBwcHBAdHY2qVavCzs4OdnZ20NLSQlRUFFq1aoVnz57B3t4ex48fFzvUEpGcnJxvkxJNTU2kpqaWYUTlx+jRozFu3Dhs3LgRQUFBCAoKwsaNGzFu3Dg4OTkB+DRvsFGjRrkev3z5cuzYsQO7du2SmbfboUMHhISEyBXDypUr0aZNG3h5eeHGjRu4deuW9Keizbnr2rUrl+8ooufPn2P06NEwNjZGpUqVoKqqKvNDuRs0aBAcHR3RvXt3vHr1Cr169QIA3Lp1C/Xq1RM5OlIWHCkkAjBgwAC8evVK7DCUjrGxsdghlJqUlJQcHUML4+XLl5g5cyYWLFggs3358uWIi4vDmTNnsGjRIixbtgz9+/cvbrjlwv379/NcquPly5cFHp+dnY3AwMBc18S0t7eHiYlJSYdcJjZu3AgjIyOsXbtWZp7W9OnTMXv2bABAjx494ODgkOvxDx8+zLVEW1dXV+5lATZv3gxPT084OzsX6RoUia+vr9J+AVFczs7OiI+Px4IFC1CrVi0uJSOnjRs3wszMDI8fP8batWuhpaUF4NOoNXscUFnhnEKi/5eVlcVvMgtp27ZtePnyJRYuXJjvfidPnoSqqip69uwps/306dPIzs6WfitakWhpaWHYsGFwcXEp0pwtXV1d3Lx5M8e3xI8ePUKLFi2QlJSEBw8eoFWrVnj//n1JhS0aFRUVSCQS5PaW9Hl7XssnfPjwAevXr8f27dvx+vVrNGvWLMeamE+fPkWPHj2wcOFCtG3btiwuqVQUZZ6WhYUFfv31V9jb20NbWxuhoaGwsLCAr68vVq9ejfv37xd4jlq1auHixYuoX79+kWNXJHfv3kXjxo3FDkPhaGtr49KlS2jWrJnYoRBRIbF8lJReREQEZs+ezU5oRXD48GF4e3sXuN+cOXNy/TAvCALmzJlTCpGJb8+ePXj9+jW6du2KBg0aYPXq1Xj69Kncx1epUgWXL1/Osf3y5cuoUqUKgE8jY5//W9HFxMQgOjoaMTExOX4+b8+r1LhBgwYICwvDrl278O7dO1y5cgWHDx/Gnj17cPLkScTHxyMqKgodO3bEiBEjsGvXrjK+upKjo6NT6Llarq6umDp1Kq5evQqJRIKnT59i7969cHNzw3fffSfXOaZPn45ffvmlKCErjPfv3+PXX39F69atuQRAEZmYmOT6xQ4RlX8cKSSllJqaigMHDsDT0xNXrlxBy5YtMXjwYMyaNUvs0CokDQ0NhIeHw8zMTGZ7bGwsGjVqhJSUFHECKwMvXrzA7t274e3tjfDwcPTs2RMuLi7o168fKlXKu4J/+fLlWLlyJVxdXWXW+3J3d8e8efMwf/58bNy4ESdPnsTZs2fL6nLKpfDwcFhZWcm1b0ZGBuLj41G3bt1Sjqr0zZs3DwkJCfD09Mx3P0EQsHLlSqxatUpaFqmurg43NzcsW7ZMrtfKzs5Gnz59EBERAWtr6xxrih45cqRoF1EOXLx4ER4eHjh8+DCMjY0xaNAgDB48WPrvjuR35swZrF+/Hjt37szx956IyjcmhaRU/v77b7i7u+O3335DnTp1EB4ejgsXLqBjx45ih6aQwsPD4eHhgXXr1uW7X82aNbFv3z507dpVZvu5c+fg6OiIxMTE0gyz3Pj5558xa9YspKeno3r16vj2228xZ86cPBus7N27F1u3bsXDhw8BAJaWlpg8eTIcHR0BfCqb/NyNVNGFhYUVuE+lSpVQs2ZNGBgYlEFE5d+YMWPw+PFjnD9/Xq7909PT8ejRIyQnJ8Pa2lo6b0kekyZNgru7O+zs7GBkZJRjrpiXl1ehYhdbQkICvL294eHhgXfv3mHYsGHYsWMHQkNDuS5hMejr6yM1NRWZmZnQ1NTM8eXB69evRYqMiArCpJCUwvr16+Hp6YmkpCR8/fXXGDVqFGxsbFC5cmV+CCiklJQU+Pn5wcPDA3///Tesra0LXDtuwoQJuHLlCo4ePSodoXn06JH023h3d/eyCF0Uz58/h4+PD7y9vREXF4eBAwdi3Lhx+Oeff7BmzRoYGxtzYWLkP6fw3yQSCWxsbODr68s5X2VIW1sbfn5+6NOnj9ihFFvfvn1x8eJF9OnTByNHjoSDgwNUVVX5flACfHx88n1+zJgxZRQJERUWk0JSCpUqVcLs2bOxdOlSmWYy/BAgv+DgYHh4eODgwYP48OEDpk+fjvHjx6Nhw4YFHpuUlAQHBwfcuHFDOnfzn3/+QceOHXHkyBHo6emVcvRl78iRI/Dy8sLp06dhbW2N8ePHY9SoUTLXGhUVBSsrK6Snp+d6jrdv3+LQoUOIjo6Gm5sbDAwMEBISAiMjI9SuXbuMrqRsyLMGYXZ2Np4/f46ffvoJiYmJuHTpktznt7KyqhBrYn78+FHukeFnz55h69atWLFiBQDgyy+/lOmqqaqqimPHjsn1u2RqaorTp0/L9e+9vKtUqRKmTJmC7777TqZxDt8PSCxjxozBuHHjcu0STFRWuCQFKYVly5bBy8sLu3fvxtdff43Ro0dzlEEOiYmJ8Pb2lhllDQgIQLt27eDi4iL3B0RdXV1cvnwZZ8+eRWhoKDQ0NNC0adMK/QY4duxYjBgxAsHBwXnOTTI2Nsb8+fNzfS4sLAz29vbQ1dVFbGwsxo8fDwMDAxw5cgTx8fHw9fUtzfDLnKmpqVz7mZubY82aNYVuBLJq1SokJSUVJTTRZWdnY8WKFdixYweeP3+OiIgIWFhYYMGCBTAzM8O4ceNyPW7btm148+aN9HFoaChcXFyk5bd//fUXNm7cWGD5NwAsXrwYixYtgpeXV77rSSqCoKAgeHh4oEWLFrCyssLo0aMxYsQIscNSWO/evZM2P/rcHTcvXNA+d0lJSbC3t4epqSnGjh2LMWPGVLgv/kgBCERKJCAgQHBychI0NTWFpk2bCqqqqkJQUJDYYZVbVapUEUaNGiWcOnVKyMrKkm6vVKmScO/ePbnP4+PjI3z8+DHH9rS0NMHHx6dEYi1vUlJSinV8t27dhFmzZgmCIAhaWlpCVFSUIAiCEBwcLJiamhY3vHIlLi6uUPv/888/wu3bt0spmvJnyZIlgoWFhbBnzx5BQ0ND+rvg5+cntG3bNs/jmjVrJly8eFH6+N+/R4IgCKdOnRKsra3liqFZs2aCtra2oKWlJTRu3FiwtbWV+VFEycnJgoeHh9ChQwehcuXKgoqKirBp0ybh3bt3YoemUFRUVITnz58LgiAIEolEUFFRyfHzeTvlLTExUVi/fr3QtGlToVKlSoKDg4Pw22+/Cenp6WKHRkqC5aOklN6/f499+/bB09MTN2/eROvWrTFkyBDMmDFD7NDKlYYNGyItLQ2Ojo4YPXq0dGSwsGVWqqqqePbsGWrUqCGz/dWrV6hRo4bCl/TlprjXrKuri5CQENStW1dmbbm4uDhYWlri48ePpRl+mTIyMsKAAQMwfvz4PEdVk5KScPDgQWzevBnffPMNpkyZkut+MTExyMzMzLGeXmRkJCpXrqyQHRHr1auHnTt3olu3bjK/Cw8ePEC7du1kRgP/TV9fH3fu3JGWbA8aNAjbt2+HkZERgE/df62treVaqH3JkiX5Pr9o0aJCXlX58vDhQ3h4eGD37t14+/YtunfvjhMnTogdlkIIDAxEhw4dUKlSJQQGBua7b+fOncsoKsUWEhICLy8vuLu7Q0tLC6NGjcLEiROVZp1QEgfLR0kpaWtrY8KECZgwYQLu3LkDDw8PrF69mknhfzx48EA6l7BVq1Zo0KABRo0aBQA5ug/mR/j/hcf/659//oGurm6JxVue5PV9W1paGtTU1Ao8Xl1dPddSrIiICBgaGhY7vvLk/v37WLFiBbp3744qVaqgRYsWMDY2RpUqVfDmzRvcv38f9+7dQ/PmzbF27Vr07t07z3M5OzvDxcUlx4enq1evwt3dHQEBAaV8NSXvyZMnqFevXo7t2dnZyMjIyPO4jIwMvHjxQpoU/nfZiDdv3kBFRb7lihU96SuIpaUl1q5di1WrVuH3338vcJkP+p9/J3pM+orv2bNnOHv2LM6ePQtVVVX07t0bd+7cgbW1NdauXYvp06eLHSJVUBwpJPp/GRkZOdpn0/8kJydj//798PLywt9//43OnTvD0dERAwYMyDNJsbW1hUQiQWhoKBo1aiSzLl9WVhZiYmLg4OCAgwcPltVllLotW7YA+LTY97Jly2Ta/mdlZeHixYuIjY3FrVu38j3P+PHj8erVKxw8eBAGBgYICwuDqqoqBgwYgE6dOmHTpk2leRmi+PDhA/78808EBQUhLi4OHz58QPXq1WFra4uePXvKNQ9YR0cHISEhOZKoR48eoWXLlnj79m0pRV96WrRogenTp2PUqFEyI4VLly7F2bNn82y406JFC7i4uOD777/P9fktW7bA29sbISEhpRk+KZm3b9/i2rVrSExMRHZ2tsxzTk5OIkVVvmVkZODEiRPw8vLCmTNn0LRpU4wfPx6Ojo7SeZhHjx6Fi4tLnpUBRMXFkUIiADdu3MCHDx+4XmE+tLS04OrqCldXV+n6hD/++CMmTpyY52jFgAEDAAC3b99Gz549ZRIkNTU1mJmZYfDgwWURfpnZuHEjgE8jhTt27JDpdvv5mnfs2FHgedavX48hQ4agRo0a+PDhAzp37oyEhAS0a9dO2k2yotHQ0MCQIUMwZMiQIp9DIpHg/fv3ObYnJSUpbJnywoULMWbMGDx58gTZ2dk4cuQIHj58CF9fX/zxxx95HjdixAgsXLgQHTt2RNOmTWWeCw0NxdKlSzF79my5Yvi8ZEheFPXe5mbbtm149eoVFixYIHYoCuf333/HyJEjkZycDB0dHZnfGYlEwqQwD7Vq1UJ2dja+/vprXLt2Dc2aNcuxj52dXYXs1E3lB0cKiVBx2tWXtYyMDPz+++8YNGhQvvv5+Phg+PDhFWKRdXnZ2dnhyJEj0NfXL9Z5goKCEBYWhuTkZDRv3hz29vYlFGHF1LdvX2hoaGD//v3ShDwrKwvDhw9HSkoK/vrrL5EjLJpLly5h6dKlCA0Nlf4uLFy4ED169MjzmIyMDNjb2+Py5cvo3r07LC0tAXyaP3f27Fm0a9cO/v7+clVIHD9+PMe5b926BR8fHyxZsiTPDqiKqFu3boiJiUF0dLTYoSicBg0aoHfv3li5cqXCd6ktS7t378bQoUOV6j2Syh8mhUQAnj59ioyMDLnb4lPhfV5zLyoqCrNmzarQa+6ReO7du4fOnTtDT09POvJ/6dIlvHv3DufPn1e6pWjS09OxYcMG+Pn5ISIiAgBQv359fP3115g+fTrU1dWLdf59+/bhwIEDOZJGUk5Vq1bFnTt3YGFhIXYoCiMjIwMaGhq4ffu20v19ovKFSSERFZm9vT2io6ML/Eb9v2vuPXz4EBYWFvjxxx8r1Jp7M2bMwLJly1C1atUCmxZt2LAhx7bP8xHlkVf3Tfr0Jc/WrVtl1sScNGmSdH0+RZBXc6byJjo6Gk2bNkVycrLYoZSYz+Xx8qzfSLIGDRqEESNGYNiwYWKHolAsLCxw9OjRQq+/SlSSOKeQlJYgCLhw4QI+fPiA9u3bF7vMTxkNHDgQL1++LHC/6dOnw9nZGWvXroW2trZ0e+/eveHo6FiaIZapW7duSedX5tdIJq8P+5/nI3724sULpKamSueRvH37FpqamqhRowaTwjzEx8fDxMQEK1euzPW5OnXqiBBV4TVq1AgLFy7EoEGD8u1WGxkZiQ0bNsDU1BRz5swpwwg/NQbasmVLhRjpT0lJgZ+fHzw8PPD333/D2tqaSaGc/r10R58+fTBr1izcv38fTZo0yVGa3K9fv7IOTyHMnz8f8+bNw+7duxXqyyuqWDhSSErh7du3mDp1KkJCQtC2bVusX78evXv3xuXLlwEANWrUkHb8ykt2djYCAwNx6dIlxMXFITU1FYaGhrC1tYW9vT1MTEzK6nIUjjKtuVdS9u3bh23btsHDw0NmLpirqysmTJiAkSNHihxh+VRR1sT09/fH7NmzER0dje7du6Nly5Y5lukICgrCvXv3MGnSJMybN69Ul3fR19eX+TJDEAS8f/8empqa2LNnj8J+2P+85M7Bgwfx4cMHTJ8+HePHj5euyUoFk3dZE4lEojD//sqara0tHj16JJ3GUrVqVZnn2SGYygKTQlIK48ePx8WLFzFmzBj8/vvvUFFRgSAI2LRpE1RUVPDDDz9AS0sLv//+e45jP3z4gPXr12P79u14/fo1mjVrBmNjY2hoaOD169e4e/cunj59ih49emDhwoVo27atCFdYvtWoUQOnT5+Gra2tTFJ49uxZuLi44PHjx2KHWOo+z2lr2LChXB8469ati0OHDsHW1lZm+82bNzFkyBDExMSUVqii2717N3bs2IGYmBhcuXIFpqam2LRpE8zNzdG/f/98j1VRUcHz589zLJMSFxcHa2trpKSklGboJS4oKAgHDhyQfhn132U6Ro4cWSZVDt7e3jJJoYqKCgwNDdGmTRuFq7JITEyEt7c3PD09kZSUhK+//hqOjo5o164dQkNDYW1tLXaIpGSWLFmS7/MVfZ1QKh+YFJJSqF27Nvbt24fOnTvjyZMnMDExwfnz59GlSxcAwLVr19CvXz8kJCTkONbExATt2rWDs7Mzunfvnmunvri4OOzbtw87d+7E/Pnz4erqWtqXVCZcXFzk2q+ghZ6Vcc29YcOGoVOnTpg0aRI+fPgAGxsbxMbGQhAE+Pn5FbgUh6amJgIDA9GqVSuZ7deuXUOXLl2QmppamuGLZvv27Vi4cCGmTZuGFStW4O7du7CwsIC3tzd8fHxw4cKFXI/7PIdz8+bNcHV1lel8mJWVhatXr0JVVRXBwcFlch1Ufn1e+mTUqFHo3r27dKSrcuXKTAqLydfXF8OHD8/RwCg9PR1+fn5ckoKoHGNSSEqhUqVKePz4MWrVqgXg0wfuO3fuoG7dugCAhIQE1K5dO9fSlvDwcFhZWcn1OhkZGYiPj5eeV9GpqKjA1NQUtra2yO9PxdGjR/M9T1JSEoYMGYIbN27g/fv3MDY2lq65d/LkyRylMhVBzZo1cfr0adjY2GDfvn1YtGgRQkND4ePjg19//bXAxev79u2LJ0+ewN3dHc2bNwfwaZTwm2++Qe3atWXm8VQk1tbWWLlyJQYMGCAzqnz37l106dIlzzmsdnZ2AIDAwEC0a9dOZh7e5/Uh3dzcUL9+/TK5joogLCwMjRs3hoqKCsLCwvLdN7/S+/KmYcOGSEtLg6OjI0aPHi0duWdSWHwVpXybSBmx0QwphezsbJlFxFVVVXMsqpsXeRNC4NOHioqSEALAd999h/379yMmJgZjx47FqFGjijQJXldXF2fPnkVwcLDMOmsVec29pKQk6b06deoUBg8eDE1NTWkjhoJ4enpizJgxaNmypXR0OjMzEz179oS7u3upxi6mmJiYHCWzAKCurp5v6efnEcSxY8di8+bN0NHRKbUYK5KlS5fCzs5OunzHvzVr1gwJCQmoUaMGmjVrBolEkuuXQ4o2V+zBgwfSuYStWrVCgwYNMGrUKAD5vxdQwfLqmvvPP/+U6pxXRZeVlYWNGzfi4MGDiI+PR3p6uszzr1+/FikyUiZMCklpuLu7Q0tLC8CnD9fe3t6oXr06AOD9+/dihlZu/fLLL9iwYQOOHDkCT09PzJ07F3369MG4cePQo0ePQn+A6tChAzp06FBK0ZYvJiYmuHLlCgwMDHDq1Cn4+fkBAN68eSPXAsWGhoY4efIkIiMjER4eDuDTCEeDBg1KNW6xmZub4/bt2znWDD116pRcX9B4eXkBAB49eoSoqCh06tQJGhoaCrPEQ1nz8vLC6tWr0a1btxxzqmNiYqRzMyvaHNbPf4u2bNmC/fv3w8vLC1lZWZg4cSIcHR0xYMCAHPNSKW+2traQSCSQSCTo1q0bKlX638fLrKwsxMTEwMHBQcQIy7clS5bA3d0dM2fOxI8//oj58+cjNjYWx44dw8KFC8UOj5QEy0dJKZiZmcn1gbCoH3ysrKwQERGhUN+WF0VcXBy8vb3h6+uLzMxM3Lt3T5pok6xt27Zh6tSp0NLSgqmpKUJCQqCiooKff/4ZR44cyXNunLJzd3fH4sWLsX79eowbNw7u7u6IiorCqlWr4O7ujhEjRuR7/OvXrzF06FBcuHABEokEkZGRsLCwgIuLC/T19bF+/foyuhLF8eHDB1y4cAG9e/cWOxRRfV6fcPfu3Xj9+rV0eRkq2OdGKUuWLMHMmTNl3hc+l28PHjw43+VVlFndunWxZcsW9OnTB9ra2rh9+7Z0299//419+/aJHSIpASaFRCXg2LFjSEpKwpgxY8QOpVQ9fvwYXl5e8Pb2Rnp6Oh48eMCkMB83b95EfHw8unfvLr1Pf/75J/T09JRmxLQo9u7di8WLFyMqKgoAYGxsjCVLlmDcuHEFHuvk5ITExES4u7vDyspKOifx9OnTmDFjBu7du1fa4VdIPj4+qF69Ovr06QMA+OGHH/Drr7/C2toa+/fvzzGyq8gyMzNx4sQJDBo0SOxQFI6Pjw+GDx8uVzUE/U/VqlURHh6OOnXqoFatWvjzzz/RvHlzREdHw9bWFklJSWKHSEqASSER5SstLU1aPhoUFISvvvoKY8eOhYODg9zrUymbjIwMNGzYEH/88Ueh5qSSrNTUVCQnJ+doWpGffzf4+XejmujoaDRt2hTJycmlGHHJeffundz75jZ/sqDGMP8mT5MYS0tLbN++HV27dsWVK1fQrVs3bNq0CX/88QcqVaqEI0eOyP16YkpJSSlUY6vC7k+f1gU+dOgQoqKiMGvWLBgYGCAkJARGRkaoXbu22OGVS5aWlvD19UWbNm3w5Zdf4quvvsKcOXNw4MABTJ48GYmJiWKHSEqAcwqpwvPz8yuw5Oyzx48fIz4+Ps9RnJiYGGRmZuboYBgZGYnKlSvDzMysuOGWKxMnToSfnx9MTEzg4uKC/fv3S+dhUt4qV66Mjx8/ih2GwsrMzERAQACioqLg6OgIAHj69Cl0dHQKHJlOSUmRWY7is9evX+dok1+e6enpFVjy/nmeZG5l6/k1hgEgfU7eJjGPHz9GvXr1AHyqjBgyZAi++eYbdOjQQbq0jyKoV68epk6dijFjxki7Uf+XIAg4d+4cNmzYgE6dOmHu3LllHKXiCgsLg729PXR1dREbGwtXV1cYGBjgyJEjiI+Ph6+vr9ghlksDBw6Ev78/2rRpg8mTJ2PUqFHw8PBAfHw8pk+fLnZ4pCQ4UkgVXufOnZGYmIixY8eib9++OUZukpKSEBwcjD179uDs2bPw8PBAv3798jyXi4tLjjLRPXv2wN3dHQEBAaV1GaJQUVFBnTp1pE0E8qIoowRlaeXKlYiIiIC7u7tM0wXKX1xcHBwcHBAfH4+0tDRERETAwsICU6dORVpaGnbs2JHv8b1790aLFi2wbNkyaGtrIywsDKamphgxYgSys7Nx6NChMrqS4gkMDJR7386dO+fYFhcXJ/fx8pR+1qhRA6dPn4atrS1sbW0xY8YMjB49GlFRUbCxsVGYEdiHDx9i3rx5+PPPP2FjY4OWLVvC2NgYVapUwZs3b3D//n1cuXIFlSpVwty5czFhwgSZztWUv27duqFFixZYu3atzEj95cuX4ejoiNjYWLFDVAh///03Ll++jPr166Nv375ih0NKgkkhKYUTJ07g559/xvnz51G1alUYGRlJPwQkJCSgevXqcHZ2xvTp02FkZJTneXR0dBASEiL9xvyzR48eoWXLlnj79m0pX0nZcnZ2lqtBz+eOj0WhoqKCLl264KeffkKLFi2KfJ7y5vM3v1paWmjSpEmOEjR5E+nU1NRcW5Qr0rpwhfF5fUIPDw9Uq1ZN+qEyICAArq6uiIyMzPf4u3fvolu3bmjevDnOnz+Pfv364d69e3j9+jWCg4Mr1JIxZWnkyJF48OABbG1tsX//fsTHx6NatWo4ceIE5s2bh7t374odYqHEx8fjt99+w6VLlxAXF4cPHz6gevXqsLW1Rc+ePdGrVy8mg0Wgq6uLkJAQ1K1bVyYpjIuLg6WlJSso8nDx4kW0b98+xxeImZmZuHz5Mjp16iRSZKRM+PU1KYV+/fqhX79+ePnyJYKCgnJ8CLC1tZVrfpxEIsl1+YqkpKQK2XnU29u71F/D09MTsbGx+P777/H333+X+uuVFT09PQwePLjIx7948QJjx47FX3/9levzFfH3DQAuXbqEy5cv5+hSaGZmhidPnhR4fOPGjREREYGtW7dCW1sbycnJGDRoEL7//vs8ywUVwdu3b+Hh4SFdnqRRo0ZwcXGRe+23qKgobNq0SXq8tbU1pk6dKneS/Msvv+DHH3/E48ePcfjwYVSrVg3Ap2ZKX3/9dRGuSFx16tTBzJkzMXPmTLFDqVDU1dVznQ8bERHBJT7yYWdnh2fPnuWYP52UlAQ7O7sK+/eeyheOFBIVQt++faGhoYH9+/dLv0XOysrC8OHDkZKSkucHeKLCGjlyJOLi4rBp0yZ06dIFR48exfPnz7F8+XKsX79e2gWyotHX10dwcDCsra1lRhqCgoIwePBgPH/+XOwQy9yNGzfQs2dPaGhooHXr1gCA69ev48OHDzhz5gyaN2+e7/GnT59Gv3790KxZM+l86eDgYISGhuL3339H9+7dS/0aSDmMHz8er169wsGDB2FgYICwsDCoqqpiwIAB6NSpEzZt2iR2iOWSiooKnj9/niNxjoiIQMuWLQvVeIqoqJgUEhXCvXv30LlzZ+jp6aFjx44APo1svHv3DufPn0fjxo1FjrDkfPvtt/jxxx/xxRdfFLjvgQMHkJmZiZEjR8p9fkEQcOrUKXh4eCjMPK/C+m/DFG1tbbkbptSqVQvHjx9H69atoaOjgxs3bqBBgwY4ceIE1q5di6CgoDK6irI1fPhw6Orq4tdff5XOCTQ0NET//v1Rp06dYpUqK6qOHTuiXr162LVrl7S8LDMzE+PHj0d0dDQuXryY7/GfSyJXr14ts33OnDk4c+YMQkJC5I5F2cqZqXCSkpIwZMgQ3LhxA+/fv4exsTESEhLQrl07nDx5kp1c/+PzsifHjx+Hg4ODTDOsrKwshIWFwdLSEqdOnRIrRFIiLB8lKoRGjRohLCwMW7duRWhoKDQ0NODk5IRJkybBwMBA7PBKlKGhIRo1aoQOHTqgb9++uTZkCAoKgp+fH4yNjfHrr7/Kdd6YmBh4enrC29sbL168gL29fSlfiTj+2zCle/fu0NbWxpo1a+RqmJKSkiItJdLX18eLFy/QoEEDNGnSpFAf4hXNunXr4ODgAGtra3z8+BGOjo6IjIxE9erVsX//frHDE8WNGzdkEkIAqFSpEn744Qe0bNmywOPDw8Nx8ODBHNtdXFzkHrl58eIFnJ2d8/xwyvI2Aj7NKTx79iyCgoIQFhaG5ORkNG/evML+nS+uz+XfgiBAW1sbGhoa0ufU1NTQtm1buLq6ihUeKRkmhUSFEB8fDxMTE6xcuTLX5+rUqSNCVKVj2bJlmDRpEtzd3bFt2zbcv39f5nltbW3Y29vj119/hYODQ77nSktLw6FDh+Dh4YGgoCBkZWVh3bp1GDduXK5rrFUEU6dORcuWLREaGiqdfwV8akAjz5u8paUlHj58CDMzM9jY2GDnzp0wMzPDjh07FHpuXEFMTEwQGhqKAwcOIDQ0FMnJyRg3bhxGjhwp84FJmejo6CA+Ph4NGzaU2f748WNoa2sXeLyhoSFu376dYymd27dvy70G5LRp05CUlISrV6/mWs5M9G9ffvklvvzyS7HDKPc+Vz6YmZnBzc2NI6kkKpaPEhWCqqpqrpPBX716hRo1alTob8vfvHmD+Ph4aYOeunXrFtiZ9ObNm/Dw8MD+/ftRr149jB49GsOHD8cXX3yB0NBQWFtbl1H0Za9atWq4fPkyLC0tZebGxcbGwtraGqmpqfkev2fPHmRmZsLZ2Rk3b96Eg4MDXr9+DTU1NXh7e2P48OFldCVlJyMjAw0bNsQff/yRY+kYZTZlyhQcPXoU69atQ/v27QF8mhM4a9YsDB48uMDRvqVLl2Ljxo2YM2eOzPFr1qzBjBkzsGDBggJjUNZyZiq869ev48KFC0hMTER2drbMcxs2bBApKiIqCEcKSSmlp6cjJiYGdevWLdQacp8Xe/6v5ORkVKlSpSRDLHf09fWhr69fqGM+L8T7999/w9LSspQiK5+ys7Nz/ZLgn3/+kWt0Z9SoUdL/btGiBeLi4vDgwQPUqVMH1atXL9FYy4vKlSuzZX0u1q1bB4lEAicnJ2RmZgL4dK++++67HPMEc7NgwQJoa2tj/fr10oXYjY2NsXjxYkyZMkWuGCpqOfOlS5ewc+dOREVF4dChQ6hduzZ2794Nc3NzjnQVwcqVK/Hjjz/C0tISRkZGMu+X8ixvpKyeP38ONzc3+Pv7IzExEf8dr6nIXzhT+cGkkJRKamoqJk+eDB8fHwCQLow9efJk1K5dG3PmzMn1uBkzZgD49Ka2YMECaGpqSp/LysrC1atX0axZs1KPX9F069YNHh4eSExMxOjRo9GzZ0+l+WDQo0cPbNq0STrXUiKRIDk5GYsWLULv3r0LfT5NTc0Cu0xWBN9//z3WrFkDd3f3Qn1hI4+uXbvCzs4OM2fOlPk3XN6pqalh8+bNWLVqFaKiogAAdevWlfsaJBIJpk+fjunTp0uX1JHni4l/q4jlzIcPH8bo0aMxcuRI3Lp1C2lpaQA+NUtZuXIlTp48KXKEimfz5s3w9PSEs7Oz2KEoFGdnZ8THx2PBggWoVauW0rxPUvnCpJCUyty5cxEaGoqAgACZeXD29vZYvHhxnknhrVu3AHwaKbxz547MGmpqamqwsbGBm5tb6QavgE6fPo3Hjx/Dy8sL3333HT58+CAte6zob3rr169Hz5492TClkK5fvw5/f3+cOXMGTZo0yTHH5siRI0U+d506deDv749du3YhPj6+uKGWOU1NTelofVGS2hcvXuDhw4cAgIYNGxZqxHnq1Kl49uwZAGDRokVwcHDA3r17peXMimj58uXYsWMHnJyc4OfnJ93eoUMHLF++XMTIFJeKiop02ROSX1BQEC5dusQvl0lUnFNISsXU1BQHDhxA27ZtZeZ5PXr0CM2bNy9wLaCxY8di8+bNFbY5Smk7e/YsvLy8cPToUZiYmGDIkCEYMmRIhR0By8zMhJ+fn0wXPmVumCKPsWPH5vt8SSxJ8e7dO4X6N5ydnS1t6JKcnAzg00jfzJkzMX/+fKioqOR7fEpKCiZPngxfX1/pHC9VVVU4OTnh559/LlKCmZqaqvDlzJqamrh//z7MzMxk3g+io6OlX+ZQ4axduxZPnz7leoSFZG1tjb1798LW1lbsUEiJMSkkpaKpqYm7d+/CwsJC5kNAaGgoOnXqhKSkJLnO8+jRI0RFRaFTp07Q0NDIc64h5e7NmzfYs2cPPD09ERYWViHnS3z8+LHCzzOlsjF37lx4eHhgyZIl0lGYoKAgLF68GK6urlixYkW+x0+YMAHnzp3D1q1bZY6fMmUKunfvju3bt5f6NZRHFhYW+PXXX2Fvby/zfuDr64vVq1fn6LhMBcvOzkafPn0QEREBa2trVK5cWeb54oz0V2RnzpzB+vXrpWXZRGJgUkhKpVOnThg6dCgmT54sXRjb3NwckydPRmRkZIELxL5+/RpDhw7FhQsXIJFIEBkZCQsLC7i4uEBfX79Ct2YvzkLs+QkJCamQI4U6OjoYOHAgRo0ahW7duhU4mkPFl52dDW9vbxw5cgSxsbGQSCQwNzfHkCFDMHr0aIX94sbY2Bg7duxAv379ZLYfP34cEydOxJMnT/I9vnr16jh06BC6dOkis/3ChQsYNmwYXrx4UWAMWVlZ8Pb2ljbC+G9XyfPnz8t3MeXIqlWrpF9Ode/eHSdPnkRcXBymT5+OBQsWYPLkyWKHqHA+L2NkZ2eXo9EMUDIj/RWRvr4+UlNTkZmZCU1NzRzJ9OvXr0WKjJQJ5xSSUlm5ciV69eqF+/fvIzMzE5s3b8b9+/dx+fJlBAYGFnj8tGnTULlyZcTHx8u0zB8+fDhmzJhRYZPC4i7E/m8pKSk4cOAAPnz4gJ49e1bIhBAAfHx8sG/fPvTv3x+6uroYPnw4Ro0aJddi4wAQFhaW63aJRIIqVaqgTp06UFdXL8mQywVbW9tck7fP112vXj04OzvDzs5O5nlBENCvXz+cPHkSNjY2aNKkCQRBQHh4OJydnXHkyBEcO3asjK6iZL1+/TrHGoXAp3mB8nxYTE1NhZGRUY7tNWrUKHBplM+mTp0Kb29v9OnTB40bN1bYBPvf5syZg+zsbHTr1g2pqano1KkT1NXV4ebmVqiEMCMjAwkJCUhNTYWhoSEMDAxKMeryzcfHB4cPH0afPn3EDkWhsNyWygWBSMk8evRIGD9+vNCqVSvByspKGDlypBAWFibXsUZGRsLt27cFQRAELS0tISoqShAEQYiKihKqVq1aajGLrX///sKoUaOEtLQ0meu+cOGCUK9evTyPi4uLEzp16iRoaWkJ9vb2QlxcnNCgQQNBIpEIEolE0NTUFAIDA8vqMkTx7t07wdPTU+jevbugqqoq1K9fX1iyZEmBx0kkEkFFRSXPH3V1dcHJyUn48OFDGVxF2ZkzZ46gq6srfPnll8KMGTOEGTNmCB07dhR0dXWFqVOnCt27dxdUVFSEY8eOyRzn6ekpaGtrC+fPn89xTn9/f0FbW1vw8fEpq8soUa1btxYmT56cY/ukSZOENm3aFHh8165dhaFDh8r8rqSmpgpDhw4VunXrJlcM1apVE/7880/5g1YgaWlpwr1794SrV68K79+/l+uYd+/eCdu2bRM6deokVKlSRVBRUZH+m61Tp44wfvx44dq1a6UceflTp04dITw8XOwwiKgImBQSFYKWlpYQEREh/e/PydH169cFAwMDMUMrVQYGBsKDBw8EQZC97piYGEFDQyPP44YOHSq0bdtW2LNnj9CvXz+hYcOGQp8+fYSEhAQhMTFRGDx4sGBnZ1cm11Ae3Lt3T2jWrJmgoqJS4L7Hjh0TLC0tBXd3dyEsLEwICwsT3N3dBSsrK8HPz0/Ys2eP8MUXXwgzZ84sg8jLzvjx44WlS5fm2L5s2TJh/PjxgiAIwsKFC4UWLVrIPN+9e3dh1apVeZ53xYoVQo8ePUo22DISEBAgVK1aVbCyshJcXFwEFxcXwcrKStDS0hIuXrxY4PF37twRjI2NhWrVqgldu3YVunbtKlSrVk2oXbu2cPfuXbliqFWrlvDw4cPiXkq5FBkZKZw6dUpITU0VBEEQsrOz891//fr1goGBgdCqVSth6dKlwqlTp4SwsDAhMjJSuHr1quDh4SE4OzsLenp6Qs+ePaXvGcrA09NTGDZsmJCSkiJ2KArn0aNHwvz584URI0YIz58/FwRBEE6ePCn3v1Gi4mJSSErn8x/er7/+utB/eHv16iX8+OOPgiB8So6io6OFrKwsYejQocLgwYNLNW4x6enpCffu3RMEQTYpvHTpklCjRo08jzMyMhKuXr0qCIIgvHr1SpBIJMLly5elz9++fVuoVq1aKUYuvg8fPggHDhwQ+vfvL6irqwt16tQRZs+eXeBxrVq1Ek6dOpVj+6lTp4RWrVoJgiAIR48eFSwsLEo8ZjHp6OgIkZGRObZHRkYKOjo6giAIQnh4uKClpSXzvJGRkXDr1q08zxsSEiIYGRmVaKxl6cmTJ8K8efOEQYMGCYMGDRLmz58vPHnyRO7jU1JShF9//VU6+rpr1y5pEiSPdevWCRMnTiwwYVIkL1++FLp27Sod4fv8d23s2LHCjBkz8jxuxIgRcr1ffPz4Udi+fbvg4eFRYjGXd82aNRO0tbUFLS0toXHjxoKtra3MD+UuICBA0NDQEOzt7QU1NTXp7+KqVasq9GcLKl84p5CUSmBgIHr16oUOHTrg4sWLWL58OWrUqIHQ0FB4eHjg0KFD+R6/du1adOvWDTdu3EB6ejp++OEH3Lt3D69fv0ZwcHAZXUXZK+pC7ImJiTA1NQUAGBgYQFNTU2ZuU82aNfHmzZvSDV4kp0+fxr59+3Ds2DFUqlQJQ4YMwZkzZ9CpUye5jr9z54703v2bqakp7ty5AwBo1qyZdO24iqJKlSq4fPky6tWrJ7P98uXL0m6u2dnZOTq7vn79Otd5c58ZGRkp9O+asbFxgV1G86OpqQlXV9ciHx8UFIQLFy7gr7/+QqNGjSpEV8np06cXaY64vOuMqqur49tvvy2RWBXFgAEDxA5BIc2ZMwfLly/HjBkzoK2tLd3etWtXbN26VcTISJkwKSSlUtw/vI0bN0ZERAS2bt0KbW1tJCcnY9CgQfj+++9Rq1at0gxdVMVZiP3fDSkqQnMKeQ0cOBBfffUVfH190bt37xwfogvSsGFDrF69Gr/++ivU1NQAfGposXr1amnTkSdPnuSbCCmiyZMn49tvv8XNmzfRqlUrAJ8WtHd3d8e8efMAfEq4/7vIc1ZWFipVyvstTVVVFZmZmaUWd2l7+/Ytrl27lmvnTycnpwKPj4yMxIULF3I9fuHChQUer6enh4EDBxYu6HLuzJkzOH36NL744guZ7fXr10dcXJxIUSm2RYsWiR2CQrpz5w727duXY3uNGjXw8uVLESIiZcSkkJRKSfzh1dXVxfz580s6tHLtiy++QGhoqMxC7OPGjZNrIfaFCxdKF8dOT0/HihUroKurCwBydz5URM+fP5f54qGwfvnlF/Tr1w9ffPEFmjZtCuDT729WVhb++OMPAEB0dDQmTpxYIvGWFz/++CPMzc2xdetW7N69GwBgaWmJXbt2wdHREQDw7bff4rvvvpM5ThAEODZeHU0AAGlpSURBVDs759mRNS0trXQDL0W///47Ro4cieTkZOjo6OT4oqWgpHDXrl347rvvUL16ddSsWTPH8fIkhRVxKYGUlBTp36Z/e/36dbE7+27btg0vX76U695WRDdv3kR4eDgAoFGjRlyUvQB6enp49uwZzM3NZbbfunULtWvXFikqUjZcp5CUyhdffIGDBw+iffv2MosVHz16FG5uboiKihI7xAqlS5cuco0OXrhwoQyiKX3v3r2Djo6O9L/z83m//Lx//x579+5FREQEgE/J0ec1IknW2LFj5dpPEZObBg0aoHfv3li5cmWuSUxBTE1NMXHiRMyePbsUolNcvXv3RosWLbBs2TLpurWmpqYYMWIEsrOzC5xOkJ9u3bohJiYG0dHRJRhx+ZeYmIgRI0YgICAAenp6AD6NctvZ2cHPzw+GhobiBlhOubm54erVq/jtt9/QoEEDhISE4Pnz53BycoKTkxNHYKlMMCkkpcI/vEW3e/du7Ny5E9HR0bhy5QpMTU2xceNGWFhYoH///mKHVy6oqqri2bNnqFGjBlRUVHJNiAVBgEQiQVZWlggRKoa3b9/i0KFDiI6OhpubGwwMDBASEgIjIyOl/Na8atWquHPnDiwsLIp0vI6ODm7fvl3k4wHg1atXWLhwYZ4lqIq4uPbdu3fRrVs3NG/eHOfPn0e/fv1k5ojXrVtX7BAVzvDhwxEdHQ1fX1/pPM379+9jzJgxqFevntzzMZVNeno6vv/+e3h7e0tL4bOysuDo6Ahvb2+oqqqKHSIpASaFpFT4h7dotm/fjoULF2LatGlYvnw57t27BwsLC3h7e8PHx6fCjPQVV2BgIDp06IBKlSohMDAw3307d+5c4PmKOw9MEYWFhcHe3h66urqIjY3Fw4cPYWFhgR9//BHx8fHw9fUVO8QyN2jQIIwYMQLDhg0r0vHjxo1Dq1atitX0pHfv3nj06BHGjRsHIyOjHF94jBkzpsjnFlNSUhK2bt2K0NBQJCcno3nz5hV+jnhp0tXVxblz56TzgT+7du0aevTogbdv34oTmIKIj4/H3bt3kZycDFtbW9SvX1/skEiJMCkkpSEIAh4/fgxDQ0O8fPkSd+7c4R9eOVlbW2PlypUYMGCATNnt3bt30aVLlzznYy5dulSu81fUBKc4CpoHFhISImJ0pcfe3h7NmzfH2rVrZX7XLl++DEdHR8TGxhbpvIo2x+vEiRPS/37x4gWWLl2KsWPHokmTJjmaFvXr1y/H8Vu2bJH+d0pKCjZs2IA+ffrkevyUKVMKjEdbWxtBQUGwsbEp7KWUSxkZGXBwcMCOHTuK9fd/1apVMDIygouLi8x2T09PvHjxQulKdrW1tXHp0qUcjaBu3bqFzp07F1hWT0TiYVJISuNzG/t79+4xCSwkDQ0NPHjwAKampjIf1CMjI9G0aVN8+PAh1+NUVFRgbGyMGjVqIK8/NRU5wSlOx0hlnQemq6uLkJAQ1K1bV+Z3LS4uDpaWlvj48WORzqtoc7xUVFTk2i+vUuT/NqzI73h57kmrVq3w888/o23btnKdVxEYGhri8uXLxXo/MDMzw759+9C+fXuZ7VevXsWIESMQExNT3DAVSv/+/fH27Vvs378fxsbGAD51SR45ciT09fVx9OhRkSMsnwRBwKFDh/KsDFHEJV9I8bD7KCkNFRUV1K9fH69evSqVpLBr166ws7PDzJkzi9QMojwzNzfH7du3c6ybd+rUKZn1vf6rV69eOH/+PFq2bAkXFxd89dVXcn/YVXTF7Rj55s0bDB06tLTDLHfU1dVzHU2IiIgoVpMKf3//4oRV5v77obCwSjoZ2bZtG+bMmYOFCxeicePGOUYb5WmcVN6MGjUKHh4eWL16dZHPkZCQkGupqaGhYYVbQ1QeW7duRb9+/WBmZgYTExMAwOPHj9G4cWPs2bNH5OjKr2nTpmHnzp2ws7PLtTybqCwwKSSlsnr1asyaNQvbt29H48aNS/TcderUgb+/P3bt2oX4+PgSPbfYZsyYge+//x4fP36EIAi4du0a9u/fj1WrVsHd3T3P4/788088ffoUPj4+mDVrFiZMmAAnJye4uLjA0tKyDK+g7M2cORMuLi5F7hg5dOhQnDlzRukWv+7Xrx+WLl2KgwcPAviUQMfHx2P27NkYPHiwyNEpLz09Pbx79w5du3aV2a7IjZMyMzPh6emJc+fOoUWLFqhatarM8xs2bCjwHCYmJggODs4xMhscHCwdKVMmJiYmCAkJwblz5/DgwQMAgJWVFezt7UWOrHzbvXs3jhw5gt69e4sdCikxlo+SUtHX10dqaioyMzOhpqaWY429kuig9+9lCSqSvXv3YvHixdJlO4yNjbFkyRKMGzdO7nNcvHgRXl5eOHz4MJo0aYJz584VuM6hoipux8hVq1YVex6YIkpKSsKQIUNw48YNvH//HsbGxkhISEC7du1w8uTJHB/cAdn5dwXJbf5deTdlyhTUq1cvx//nW7duxaNHj7Bp06Z8jx88eDBat26doxR57dq1uH79On777bcCY2jdujUq/V97dx5PZfr+AfxzkH1J2VqskQgNbd82FVqkiCY1tFjap8kobdO+qbRpmZmaIss0aW+opoUWKTMpQotkCSkppUIRnt8fXs6v07EchYdzrvfr1Wu4n/M8rmM4zvXc931dEhLw8vKqcSZDkMJJLc3QoUNrPcbhcHD58uV6r+Hn5wc/Pz9s2bKFmzBHRUVh0aJFWLBgAZYuXdpo8RLhpauri3/++QfdunVjOxQiwigpJCIlODi4zuOttYJeUyovL8dff/2FESNGQF1dHSUlJSgqKoKamlqDr/XhwwccO3YMv/76K5KTk5GXlyeUCTTw7RUj69oTJug+sNYsJiYGSUlJ3IqQdc00fLkkmcPh8Oxh/TyBaY0zWp06dUJ4eDh69uzJMx4fHw97e3s8ffq0zvNVVVVx+fJlmJqa8ownJyfDxsYGL168qDcGWVlZJCQkCP0Mf0MxDIMlS5Zg165dKCsrAwBIS0tj8eLFWLFihcgsA4yNjUVBQQFGjx7NHQsJCcGqVatQXFyMsWPHYvfu3ZCSkmIxypYrODgY58+fR2BgoNDeKCUtHyWFhDSC27dvo6SkBJaWlmyH0iRkZWXx8OFDvj2FgoqNjUVgYCCOHj2Krl27wt3dHS4uLtzmxsIoICCgwRUjybeLjIzE4sWL4evri379+gGo+vlbvnw5fH19MWzYMJYjbDhpaWncu3cP+vr6PONpaWkwMTGpt/iOjIwM7t69y5fQpaSkwNzcvNZCUZ+ztLTEypUraRlgLYqKivDw4UPIyMjAwMBA5JIfW1tbDBkyhDsbnZycDAsLC7i5ucHIyAhbtmzBzJkzsXr1anYDbaE+fPgAR0dH3LhxAzo6Onx/L4S1GBtpWWhPIREptZXD5nA4kJKSgqSk5Fddd/LkyUhNTW2VsxCC6NOnDxISEhqcFPr5+SEoKAivXr2Cq6srrl+/DjMzsyaKsmWZPn06gJrbcrTWPVhN5fP2CfWpb9nszz//jL1792LgwIHcsREjRkBWVhYzZszAw4cPvzpOtujr6+P8+fOYO3cuz/g///wj0PJkU1NTHDlyhK8dR1hYGIyNjQWK4aeffoKXlxcWLlxY402O1vh77ejoWONMHofDgbS0NPT19eHi4lLn7KiHhwd27twJBQUFnt58xcXF+OmnnxAYGNgksbc0d+/exbp167ifh4WFoW/fvti/fz+Aqr2Gq1atoqSwFlOnTsWdO3cwadIkKjRDWEMzhUSkiImJ1fli27lzZ7i5uWHVqlUNqpL57NkzfPr06atn0lq6o0ePYunSpfD29q6xIENtbwjFxMSgpaWF0aNH15lwC1LQQRTMnz8f69atg5ycHObPn1/nY4Xpe/blUtmXL1+ipKSEO5NcWFgIWVlZqKmp1btsVkZGBnFxcXyFpJKSktC3b1+BZsVamsDAQMydOxcLFy7k2be2bds2+Pv7c29A1CYiIgJOTk5wcXHhOf/w4cM4duwYxo4dW28MNb0eVi/Tba03Odzc3HD69Gm0bduWuzQ3Pj4ehYWFGD58OBITE/HkyRNERUVhwIABNV5DXFwcz58/51tO/+rVK2hoaKC8vLzJn0dLIC0tjcePH3Mrjg4cOBC2trZYtmwZAODJkycwNTXF+/fv2QyzxZKTk8OFCxd4bmYR0txoppCIlKCgICxbtgxubm7o06cPAODWrVsIDg7G8uXL8fLlS2zduhVSUlL45ZdfBL6usFeZmzhxIgDeWRpB3hBaWlqCw+Hg/v37tV6b7oj+v4SEBHz69In7cW2E7Xv2efuEv/76C7/99hsCAgK4MzSPHj3C9OnTMXPmzHqv1bt3b8yfPx+hoaFQV1cHALx48QILFy7k/s63Nh4eHigtLcWGDRu4szE6Ojr4/fff621tAgBjxozB6dOn4evri+PHj0NGRgZmZmaIjIwUuECMMPbb09DQgIuLC/bs2cNNeisrK+Hl5QUFBQWEhYVh1qxZWLx4MWJiYnjOfffuHRiGAcMweP/+PaSlpbnHKioqcO7cua/ad91aqaurIzMzE5qamigrK0N8fDzWrFnDPf7+/Xu+2WXy/zQ1NYV2fz1pPWimkIgUa2trzJw5k6/4x9GjR7Fv3z5ERUUhNDQUGzZs4JbT/lxTLT9t6bKysuo8LqwzpN+ipmWjn/tyKR+p0qVLFxw/fhzm5uY843fu3MH3339fb3KSlpYGR0dHpKam8vRJMzAwwOnTp/n25bU2L1++hIyMDOTl5Zv16xYXF9dY+bU1U1VVxY0bN9C1a1ee8dTUVPTv3x+vXr1CcnIyBg0ahMLCQp7H1LfqhMPhYM2aNdyZMmE3e/ZsJCYmYvPmzTh9+jSCg4Px7Nkz7t/EQ4cOwd/fH3FxcSxH2jKdPXsWu3fvxt69e6Gjo8N2OERE0UwhESk3b97E3r17+cbNzc0RGxsLoGrZS219Btu2bdsky09bOkr6Gu7UqVM8n3/69AmZmZmQkJBAly5dKCmsxfPnz2tccldRUSFQlUx9fX0kJSXh0qVLfH3SWusM64cPH8AwDGRlZaGqqoqsrCwcOHAAxsbGGD58eL3n5+TkgMPhoHPnzgCqVkf89ddfMDY2xowZMwSKQV1dHc7OzvDw8BCaJW7l5eVISUnhSwpTUlK4qx+kpaVr/Lm5cuUKGIaBlZUVTpw4gXbt2nGPSUpKQltbW+hXkHxu3bp1cHJywuDBgyEvL4/g4GCem6SBgYEC/ayKqkmTJqGkpARdunSBrKws36xqY7TLIqQ+lBQSkaKpqYmAgABs2rSJZzwgIIA7q1BQUABlZeUaz2+q5actXW194D4vyFBXCwVRVNPyz3fv3sHNzQ2Ojo71nl9cXIxNmzYhKioK+fn5qKys5DkurC0pqmfzDxw4AAsLCwBVs4SzZ88WuPIlh8PB8OHDheZNqIODA5ycnDBr1iwUFhaiT58+kJSUxKtXr7B9+3bMnj27zvNdXFwwY8YMTJ48GXl5ebCxsYGJiQkOHTqEvLw8gW5Q/PnnnwgKCoKVlRV0dHTg4eGBKVOmtOrEZ/LkyfD09MQvv/zCLRITFxcHX19f7rLca9euoXv37nznVi+7zczMRHZ2Nvbt24f09HQcP34cnTp1QmhoKHR1dYUmga6PiooKoqOj8fbtW8jLy0NcXJzn+LFjx5p9drs1qa/XKCHNgiFEhPz999+MpKQkY2Zmxnh6ejKenp5Mjx49GCkpKSYiIoJhGIb57bffGG9v7xrPt7KyYo4cOcI3fuTIEcbKyophGIYJCQlhDA0Nm+5JsIDD4TBiYmIMh8Ph+Vc9JiYmxlhaWjKvX79mO9QWLykpidHW1q73cRMnTmQ6dOjALFq0iNmxYwfj7+/P809Y5efnM7a2tgyHw2EkJSUZSUlJRkxMjLG1tWVevHhR63m2trZMYWEh9/ONGzcyb9684X7+6tUrxsjIqClDbzLt27dn7t27xzAMw+zfv58xMzNjKioqmKNHjzLdunWr9/y2bdsyKSkpDMMwzM6dO5n+/fszDMMwFy5cYHR1dRsUS35+PrNt2zbG1NSUkZCQYOzs7JgTJ04wnz59auCzYl95eTmzfv16RkNDg/uapqGhwWzYsIEpLy9nGIZhsrKymJycnFqvcfz4cUZGRoaZNm0aIyUlxaSnpzMMwzC7d+9mbG1tm+V5EEJIY6CkkIicjIwMZvHixYyjoyPj6OjILFmyhMnMzBToXGlpaSY1NZVvPDU1lZGRkeFev/pjYREZGcn07duXiYyMZN69e8e8e/eOiYyMZPr168ecPXuWiYmJYbp37854eHiwHWqLd/36daZt27b1Pk5JSYmJiYlphohaptTUVObvv/9m/v77b+bRo0f1Pl5MTIwnaVRQUOC+QWcYhsnLy2PExMSaJNamJiMjw2RlZTEMwzDjx49nVq9ezTAMw2RnZwv0WiMnJ8d9jRszZgyzadMmhmGqEh5paemvjmvXrl2MlJQUw+FwGFVVVWbFihVMcXHxV1+PTW/fvmXevn3b4PO+++47Jjg4mGEYhpGXl+f+zMXHxzPq6uqNGiMRbmlpacyyZcuYiRMncl/Lzp07x70hREhTo+WjROTo6uryLR8V1LcuP22tvLy88Mcff6B///7cMWtra0hLS2PGjBm4f/8+/P394eHhwWKULcuXvfcYhsHz588RGhoKW1vbes9XVlbm2ackagwMDGBgYCDw45kvaqZ9+Xlrpq+vj9OnT8PR0REXLlyAt7c3ACA/P1+gioXdu3fH3r17YWdnh0uXLnErmD579gzt27dvUCwvXrxAcHAwgoKCkJWVhe+//x6enp54+vQpNm/ejH///RcXL15s+JNkSXl5Oa5evYr09HS4uLgAqPq+KCoqCrTc8dGjR7C0tOQbV1JS4itOQ0htrl27BltbWwwYMADR0dHYsGED1NTUkJiYiICAABw/fpztEIkIoKSQiJzr169j3759yMjIwLFjxxq0/2Pr1q0YP348/vnnH+4elNu3byMlJYX7oh0XF4cJEyY0+fNoTunp6TW++VRUVOTubTMwMMCrV68afO3s7Gx06tSJbw9Ka7djxw6ez8XExKCqqoqpU6di6dKl9Z6/bt06rFy5EsHBwZCVlW2qMEkrsHLlSri4uMDb2xvW1tbo168fAODixYt8VVprsnnzZjg6OmLLli2YOnUqevToAaBqr7CgbTpOnjyJgwcP4sKFCzA2NsacOXMwadIkbi9JAOjfvz+MjIwa/gRZkpWVhZEjRyI7OxulpaUYNmwYFBQUsHnzZpSWltZYlOxLGhoaSEtL46sYGRMTAz09vSaKnAibJUuWYP369Zg/fz4UFBS441ZWVtizZw+LkRFRQkkhESknTpzA5MmT4erqivj4eJSWlgIA3r59C19fX5w7d67O8+3t7ZGSkoJ9+/YhNTUVAGBra4vTp09z3xTUV/ShNerZsycWLlyIkJAQqKqqAqgqjb9o0SJucvx54+KG0NHRgYGBATZu3AgnJ6dGjZtN39rXbdu2bUhPT4e6ujp0dHT4qtHFx8d/0/WFDYfD4asS2VqrjX7p+++/x8CBA/H8+XNuQgdUzdYLUrRoyJAhePXqFd69e8ezimHGjBkC33Bwd3fHxIkTcePGDe7v/Jc6duzYqloweHl5oVevXkhMTOSZMXV0dMT06dMFusb06dPh5eWFwMBAcDgcPHv2DLGxsfDx8cGKFSuaKnQiZJKTk/HXX3/xjaupqX3VzVZCvgYlhUSkrF+/Hnv37sWUKVMQFhbGHR8wYADWr18v0DW+ZflpaxUQEAAHBwd07tyZp/ebnp4e/v77bwBAUVERli9f3uBrX7lyBRkZGThy5IhQJIVaWlqwt7eHg4MDhg4dCgmJr3uZHTt2bOMGJuQYhoGbmxukpKQAAB8/fsSsWbO4vfWqbwC1VhoaGtDQ0OAZE3SWDwDExcX5lrU3pB/a8+fP600gZWRksGrVKoGvybbr16/j5s2bfP1ldXR0kJubK9A1lixZgsrKSlhbW6OkpASWlpaQkpKCj48Pfvrpp6YImwihtm3b4vnz53xVvBMSEtCpUyeWoiKihprXE5EiKyuLBw8eQEdHBwoKCkhMTISenh4yMjJgbGyMjx8/1nuNwsJC3Lp1q8Y2AdVlzIVRZWUlLl68yJ0hNTQ0xLBhw4SqH2NjuHbtGsLDwxEeHo6XL19ixIgRsLe3h52dHc9Su7qUl5fD19cXHh4e3N5ypG7u7u4CPe7gwYNNHIlwu3//PreHH1CVbNbUsqE1UFZWxo0bN2BsbMzz9yAmJgbjxo0TqC9mtbKyMqSlpaGoqAjGxsbUfoE0iI+PD/777z8cO3YMXbt2RXx8PF68eIEpU6ZgypQprepmC2m9KCkkIkVPTw9//PEHbGxseN4EhISEYNOmTXjw4EGd50dERMDV1RVFRUVQVFTkWZ7G4XBEosHsx48fISUlJTRL85rS/fv3ER4ejr///ht3795F//79YW9vD3t7+3r3GykoKCA5OblBszmtVVJSksCPNTMza8JIyJeuX7+O+fPnIy4uDkDVz2VJSQm3kA+Hw8GFCxcE7iHZkkyYMAFKSkr4448/oKCggKSkJKiqqsLBwQFaWlp0A4E0m7KyMvz4448ICgpCRUUFJCQkUFFRARcXFwQFBQndnnvSMlFSSETKxo0b8eeffyIwMBDDhg3DuXPnkJWVBW9vb6xYsaLe5T5du3bFqFGj4OvrK1LFPyorK7Fhwwbs3bsXL168QGpqKvT09LBixQro6OjA09Pzq677yy+/IC8vD4GBgY0cccuTl5eHiIgIhIeHIyoqCnp6eti8eTPs7OxqfHx1w/KpU6c2c6TNT0xMDBwOp9aKodXHOBwOzywVaXo//PAD+vXrh3nz5gGoSgrPnj0LbW1tMAyDXbt2ISsrCydOnGA50oZ7+vQpRowYAYZh8PjxY/Tq1QuPHz/mNmJXU1NjO0QiYrKzs3Hv3j0UFRXB3Ny8QRWYCflWlBQSkcIwDHx9fbFx40aUlJQAAHf/R3WZ9rrIyckhOTlZ5KrKrV27FsHBwVi7di2mT5+Oe/fuQU9PD0eOHIG/vz9iY2O/6rpTp05FTk4OLl++3MgRt2wlJSW4cOECFBQUap1h2bt3L9asWQNXV1f07NmTuzeumr29fXOE2iyysrIEfqy2tnYTRtIyFRcX8/3/by4GBgY4deoUTExMAIBnhQVQtefJzs4Oz549YyW+b1VeXo6wsDAkJSWhqKgIFhYWcHV1hYyMDNuhEUJIs6KkkIikr93/4eTkhIkTJ8LZ2bmJI2xZ9PX1sW/fPlhbW/O8KUxJSUG/fv3w5s0btkNskdLT03Hw4EGkp6dj586dUFNTwz///AMtLa1692HVtVeTZsxEi7y8PJydneHh4VFv25zaREVFISoqqsa90HXN1MvIyCA1NZVbYOrkyZMYOXIkd6VEVlYWunbt2uoL+RDS3ObPny/wY7dv396EkRBShaqPEpEkKSkJY2PjBp9nZ2eHhQsX4sGDBzA1NeVrEyBMszefy83Nhb6+Pt94ZWUlPn36xEJELd+3NiP+8o27qHnw4AGys7NRVlbGMy6sv2N1+fPPPxEUFAQrKyvo6OjAw8MDU6ZMQceOHQU6f82aNVi7di169eqFDh06NGg/sIKCAtLT07lJ4ZcVgjMzM2vsYdpShYeHC/xYUfxZI80nISFBoMfR/n3SXGimkAi9hrQ5OHnyZJ3HRXX2pmfPnvD29sakSZN4ZgrXrl2LS5cu4fr163Wev2vXrhrHORwOpKWloa+vD0tLS6HaTN+vXz+MHz+e24y4+nt269YtODk54enTp2yH2CJlZGTA0dERycnJPPsMq98YCevvmCBevnyJ0NBQBAUF4eHDhxgxYgQ8PDxgb29fZ+uTDh06wM/PD5MnT27w1xwzZgxUVVVrnU10c3PDq1evcObMmQZfmw1fvobXtJeVftYIIaKIZgqJ0FNSUuJ+zDAMTp06BSUlJfTq1QsAcOfOHRQWFgqUPIrq7M3KlSsxdepU5ObmorKyEidPnsSjR48QEhIi0JvBHTt24OXLlygpKeH2Snvz5g1kZWUhLy+P/Px86Onp4cqVK9wZidauMZoRFxcX49q1azXOmFUX/hA2Xl5e0NXVRVRUFHR1dXHr1i0UFBRgwYIF2Lp16zddOzo6Gj169OB5TWhNVFVVMX/+fMyfPx+7d+/GwoULce7cOaioqGDWrFlYsmRJjQWwysrK0L9//6/6mvPnz4eNjQ3at2+PhQsXcouv5OfnY/Pmzfjzzz9x8eLFb3pezenz1/DIyEgsXrwYvr6+6NevHwAgNjYWy5cvh6+vL1shEhGWlpaG9PR0WFpaQkZGhltgi5BmwRAiQhYtWsRMmzaNKS8v546Vl5czM2bMYHx8fFiMrOWLjo5mbGxsGFVVVUZGRoYZMGAAc+HCBYHO/euvv5ghQ4YwaWlp3LHHjx8zVlZWTFhYGJOTk8MMGDCAGTduXFOF3+w6derE3Lhxg2EYhpGXl2fS09MZhmGYkydPMnp6evWeHx8fz2hoaDCKioqMuLg4o6qqynA4HEZOTo7R1dVt0tjZ1L59eyYxMZFhGIZRVFRkUlJSGIZhmKioKOa77777pmtzOBymXbt2zNatW785Tjbk5eUxmzdvZoyMjBhZWVnG1dWVuXz5MhMSEsJ0796dGTZsWI3nLVq0iFm7du1Xf91ff/2VkZSUZMTExJi2bdsyysrKjJiYGCMpKcns3r37q6/Ltu7duzPXr1/nG4+Ojma6devGQkREVL169YqxsrJiOBwOIyYmxv174e7uzsyfP5/l6IiooOWjRKSoqqoiJiYGhoaGPOOPHj1C//79UVBQUON5o0aNwuHDh7kzDJs2bcKsWbO4zcgLCgowaNCgevsciqouXbrgxIkT+O6773jGExISMG7cOGRkZODmzZsYN24cnj9/zk6QjexbmxEPGTIEXbt2xd69e6GkpITExES0adMGkyZNgpeXV4OWRbcmysrKiI+Ph66uLrp06YIDBw5g6NChSE9Ph6mpKbdq8NfIyspCRkYG/vnnH/j5+TVi1E3r5MmTOHjwIC5cuABjY2NMmzYNkyZN4r7+AFVFjYyMjLgzyp8XsaisrERwcDDMzMxgZmbGtxdakCIWOTk5OH78OB4/fgygqirp999/36pn9mVkZBAXF8etrFotKSkJffv2xYcPH1iKjIiaKVOmID8/HwcOHICRkRF3u8GFCxcwf/583L9/n+0QiQig5aNEpJSXlyMlJYUvKUxJSalzaeiFCxd4quv5+vrC2dmZ+6asvLwcjx49apKYhcHz589RXl7ON15eXo68vDwAQMeOHfH+/fvmDq3J+Pr64scff4SmpiYqKipgbGzMbUa8fPnyes+/e/cu9u3bBzExMYiLi6O0tBR6enrw8/PD1KlThTYpNDExQWJiInR1ddG3b1/4+flBUlISf/zxxze3gtHW1oa2tjaGDh3aSNE2D3d3d/zwww+4ceMGevfuXeNjOnbsiGXLlnE//7KIRfUNmXv37vGMC7o0TVNTE97e3g2IuuXr3bs35s+fj9DQUKirqwMAXrx4gYULF6JPnz4sR0dEycWLF3HhwgV07tyZZ9zAwKBBLXsI+RaUFBKR4u7uDk9PT6Snp3P/6P/333/YtGkT3N3daz3vywl1UZhgV1ZWFvgN4+vXr+s8PnToUMycORMHDhyAubk5gKo3rbNnz4aVlRWAqj14urq63xZ0CyIpKYn9+/djxYoVX9WMuE2bNtyiGGpqasjOzoaRkRGUlJSQk5PTlKGzavny5SguLgZQ1R9z9OjRGDRoENq3b48jR47Uez7DMLhz5w6ePHkCDocDXV1dmJubt9p9OeXl5di4cSPGjRvHTVxqIiMjwzP7fOXKleYIr1ULDAyEo6MjtLS0uDOeOTk5MDAwwOnTp9kNjoiU4uLiGvcDv379GlJSUixEREQRJYVEpGzduhUaGhrYtm0bd5lihw4dsHDhQixYsIDl6FoWf39/7scFBQVYv349RowYwVOQ4cKFC1ixYkW91woICMDkyZPRs2dP7tK18vJyWFtbIyAgAEBVL7Zt27Y1/hNhmZaWFrS0tBp8nrm5OeLi4mBgYIDBgwdj5cqVePXqFUJDQ/mWuwmTESNGcD/W19dHSkoKXr9+LdBNiitXrsDT0xNZWVk8VUt1dXURGBgIS0vLJo29KUhISMDHxwd2dnZshyJ09PX1kZSUhEuXLiElJQUAYGRkBBsbm1Z7E4G0ToMGDUJISAjWrVsHoOp1q7KyEn5+fq1uZQNpvWhPIRFZ7969AwCBemyJi4sjLy8PqqqqAKp6dyUlJXFntl68eIGOHTsKbQnzcePGYejQoZg7dy7P+J49exAZGSnwXfWUlBSkpqYCAAwNDfmW8QqT2hoTf96Gw8HBAe3atavxcbdv38b79+8xdOhQ5OfnY8qUKbh58yYMDAwQGBiIHj16NGX4rU5aWhp69OiBvn37wsvLC926dQPDMHjw4AF27dqF27dvIykp6ZuXoLJhyJAh+PnnnzF27NivOt/R0bHGJOfzn0UXFxeh/n0kpCW7d+8erK2tYWFhgcuXL8Pe3h7379/H69evcePGDXTp0oXtEIkIoKSQEAGIiYnB1taWu4wjIiICVlZWkJOTAwCUlpbi/PnzQpsUysvL4+7du3wN7NPS0vDdd9+hqKiIpcharqFDhyI+Ph4VFRXcN9upqakQFxdHt27d8OjRI3A4HMTExMDY2JjlaFuO4uJibNq0CVFRUcjPz+fb65uRkVHjeXPnzsXDhw8RFRXFd4xhGNjY2MDY2Bi7d+9ukrib0tGjR7F06VJ4e3ujZ8+e3NedamZmZnWe7+bmhtOnT6Nt27bo2bMnACA+Ph6FhYUYPnw4EhMT8eTJE0RFRWHAgAF851dUVODGjRswMzPjKW5DCGk8b9++xZ49e5CYmIiioiJYWFjgxx9/RIcOHdgOjYgISgoJEUBd+w0/d/DgwSaOhB3a2tqYN28e3xLbbdu2YdeuXfVuhK+oqEBQUFCtb/QvX77c6DGzzd/fH9evX8fBgwe5s9Fv377FtGnTMHDgQEyfPh0uLi748OEDLly4UOM1ysvLcfXqVaSnp8PFxQUKCgp49uwZFBUVIS8v35xPp9n88MMPuHbtGiZPnowOHTrwzXB5eXnVeJ6JiQk2btyIMWPG1Hg8IiICS5cu5Su00hp82XAd+P+m6xwOp96bUUuWLMG7d++wZ88e7rUqKyvh5eUFBQUFbNiwAbNmzcL9+/cRExNT4zWkpaXx8OFDodr3SwjbAgMDYW9vDxUVFbZDIYSSQkJI/YKCgjBt2jTY2tqib9++AKoK9Jw/fx779++Hm5tbnefPnTsXQUFBsLOzq/GN/o4dO5oqdNZ06tQJly5d4psFvH//PoYPH47c3FzEx8dj+PDhNTazz8rKwsiRI5GdnY3S0lKkpqZCT08PXl5eKC0txd69e5vrqTSrtm3b4uzZszXOWNVFUVERSUlJ0NHRqfF4ZmYmzMzMWmWF2/puumhra9d5XFVVFTdu3EDXrl15xlNTU9G/f3+8evUKycnJGDRoEAoLC2u8Rq9evbB582ZYW1s3KHZCSO2srKxw8+ZNWFhYwMHBAQ4ODujWrRvbYRERRYVmCCH1cnNzg5GREXbt2oWTJ08CqCrIEBMTw00S6xIWFoajR49i1KhRTR1qi/H27Vvk5+fzJYUvX77k7mdt27Ytt6/cl7y8vNCrVy8kJiaiffv23HFHR0dMnz696QJnmbKycq37LOtSVFRUY/W+arKyst/U45BN9SV99aluxfNlUpiSksKdZZSWlq6zuMr69evh4+ODdevW1biEVZC92YQQXpcvX8abN29w9uxZhIeHY8OGDVBXV4e9vT0cHBwwcODAGlcKENIUKCkkIq+wsPCb98n89ttvePXqFVauXNk4QbVAffv2xaFDh77qXElJSb79iMLOwcEBHh4e2LZtG7e3XFxcHHx8fLgFQ27dusX3Rr3a9evXcfPmTUhKSvKM6+joIDc3t0ljZ9O6deuwcuVKBAcH15nk1eTBgwfcvpdfqmk2trV58OABsrOz+W4k2Nvb13ne5MmT4enpiV9++YXnZ9HX1xdTpkwBAFy7dg3du3ev9RrVN3Ts7e15kkdBl7C2VOnp6Th48CDS09Oxc+dOqKmp4Z9//oGWllad3w9CGouysjImTZqESZMmoaysDJcvX0Z4eDhcXV3x4cMHjBo1Cvb29rC1teW7GUNIY6Llo0SkbN68GTo6OpgwYQIAwNnZGSdOnICGhgbOnTv31RUdra2tkZmZWWsRDFG3bds2ZGRkYM+ePSJT6r2oqAje3t4ICQlBeXk5gKr2AlOnTsWOHTsgJyeHu3fvAvj/xuKfU1ZWxo0bN2BsbAwFBQUkJiZCT08PMTExGDduHF68eNGMz6b5mJubIz09HQzDQEdHh9vCpFp8fHyN54mJiXH32X2pIfvvWqKMjAw4OjoiOTmZ5zlW/y7V95wqKiqwadMm7Nmzh/tzo66ujp9++gmLFy+GuLg4srOzISYmxtc8u9q1a9fq/BqDBw9u6NNi3bVr12Bra4sBAwYgOjoaDx8+hJ6eHjZt2oTbt2/j+PHjbIdIRNzt27cRHh6Ov//+G99//71ALaAI+VqUFBKRoquri0OHDqF///64dOkSnJ2dceTIERw9ehTZ2dm4ePEi2yEKJUdHR1y5cgXt2rVD9+7d+d7oVy9JFUZFRUXcmwV6enoCF4iZMGEClJSU8Mcff3BboKiqqsLBwQFaWlpCW9RozZo1dR7/vEH75+rbd1ftW5dismHMmDEQFxfHgQMHoKuri1u3bqGgoAALFizA1q1bMWjQIIGv1ZBWPMKuX79+GD9+PObPn89z4+XWrVtwcnLC06dP2Q6RiIgrV67U24/w06dPfH87CWlMlBQSkSIjI4PU1FRoamrCy8sLHz9+xL59+5Camoq+ffvizZs3bIcolOqr3iqsCQ5Q1bYjPT0dlpaWkJGR4c5Y1efp06cYMWIEGIbB48eP0atXLzx+/BgqKiqIjo6GmppaM0RPWgIVFRVcvnwZZmZmUFJSwq1bt2BoaIjLly9jwYIFSEhIaJY4CgsLERAQgIcPHwIAunfvDg8PDygpKTXL129s8vLySE5Ohq6uLk9S+OTJE3Tr1g0fP35kO0QiIqSkpNC5c2e4u7tj6tSp0NTUZDskIoJoTyERKcrKysjJyYGmpibOnz+P9evXA6jaFyPIsrKCggJu0Y+cnBzs378fHz58wJgxY2Bpadmksbdmwpz01aagoADOzs64cuUKOBwOHj9+DD09PXh6ekJZWRnbtm2r8/zOnTsjMTERR44c4fat8vT0hKurK2RkZJrpWbDnzp07PMmHubk5yxGxp6KiAgoKCgCqEsRnz57B0NAQ2traePToUY3nWFhYICoqCsrKyjA3N6/zRkRtS3I/d/v2bYwYMQIyMjLo06cPAGD79u3YsGEDLl68CAsLi694Zuxq27Ytnj9/ztdmIyEhAZ06dWIpKiKKcnNzERoaiuDgYKxZswZWVlbw9PTE2LFj+faVE9JUKCkkIsXJyQkuLi4wMDBAQUEBbG1tAVS9CairEEpycjLGjBmDnJwcGBgYICwsDCNHjkRxcTHExMSwY8cOHD9+nFtARNi9e/cOly9fhqGhIYyMjGp9XH5+fp0zWuXl5YiPj+e+yRQm3t7eaNOmDbKzs3m+RxMmTMD8+fPrTQqBqj2Irq6ucHV1bcpQW5T8/HxMnDgRV69e5RaAKiwsxNChQxEWFgZVVdWvuq6RkRFSU1Nb5Z5CExMTJCYmQldXF3379oWfnx8kJSXxxx9/QE9Pr8ZzHBwcICUlBQCN8rrk7e0Ne3t77N+/HxISVW8dysvLMW3aNPz888+Ijo7+5q/R3CZOnIjFixfj2LFj4HA4qKysxI0bN+Dj48MtwENIc1BRUYG3tze8vb0RHx+PgwcPYs6cOZgzZw5cXFzg6en51TUPCBEYQ4gIKSsrY7Zs2cLMmzePiY+P545v376d2b9/f63njRw5khk9ejQTExPDzJw5k+nUqRPj4eHBVFRUMBUVFcycOXOYvn37NsdTYMX48eOZ3bt3MwzDMCUlJYyBgQHTpk0bRkJCgjl+/Hit54mJiTEvXrzgfm5iYsJkZ2dzP8/Ly2PExMSaLnAWqaurM3fv3mUYhmHk5eWZ9PR0hmEYJj09nZGTk2MztBbN2dmZ6dWrF/PgwQPu2P3795levXoxEydO/Orrnjp1igkKCmqMEJvd+fPnmRMnTjAMwzCPHz9mDA0NGQ6Hw6ioqDBRUVHNEoO0tDTz8OFDvvH79+8zMjIyzRJDYystLWWmTZvGSEhIMBwOh2nTpg0jJibGTJo0iSkvL2c7PCLCcnNzmVWrVjFSUlKMnJwcIy4uzgwcOJC5d+8e26ERIUZJISECaN++PZOYmMgwDMO8f/+e4XA4zO3bt7nHHz58yCgpKbEUXdP7PME5dOgQo6+vzxQXFzO//fYb891339V6HofD4UkKP0+OGKYqKeRwOE0XOIvk5eWZ1NRU7sfVzzsuLo5p164dm6G1aIqKisytW7f4xv/77z+h/h1rqIKCAqaysrJB55SWljI5OTlMVlYWzz9BqKmpMRcuXOAbP3/+PKOmptagOFqa7Oxs5uzZs8yRI0e4v7OENLeysjLm2LFjjK2tLSMhIcH873//Y/bv388UFRUxmZmZjKurK2NkZMR2mESIUUdMIhJCQ0O/qZLc69evoaGhAaCqOIGcnByUlZW5x5WVlfH+/ftvjrOlevv2Lbeh+Pnz5zFu3DjIysrCzs4Ojx8//qZrC2uLikGDBiEkJIT7efXyND8/v3qrzImyysrKGivstWnTBpWVlSxE1DK1a9dO4N+d1NRUDBo0CDIyMtDW1oauri50dXWho6PDt5+uNhMmTICnpyeOHDmCnJwc5OTkICwsDNOmTcMPP/zwLU+FNWvXrkVJSQk0NTUxatQoODs7w8DAAB8+fMDatWvZDo+IkJ9++gkdOnTAzJkz0bVrVyQkJCA2NhbTpk2DnJwcdHR0sHXrVqSkpLAdKhFitKeQiISpU6dCSkoKM2fOhL+//1dd48s3YMKazNREU1MTsbGxaNeuHc6fP4+wsDAAwJs3byAtLc1ydC2Tn58frK2tcfv2bZSVlWHRokW4f/8+Xr9+jRs3brAdXotlZWUFLy8vHD58GB07dgRQVYTB29sb1tbW9Z7/4sUL+Pj4ICoqCvn5+Xx9C1vLnkInJyeBH1tfSxd3d3dISEjgzJkz6NChw1e9dm3duhUcDgdTpkzh9t1s06YNZs+ejU2bNjX4ei3BmjVrMGvWLMjKyvKMl5SUYM2aNVi5ciVLkRFR8+DBA+zevRtOTk7cvcBfUlFRwZUrV5o5MiJKKCkkIqGyshKpqanf1IfQzc2N+2L98eNHzJo1C3JycgCA0tLSRomzpfr555/h6uoKeXl5aGtrY8iQIQCA6OhomJqa1noeh8PB+/fvIS0tzW3FUFRUxO2VVv1fYWRiYoLU1FTs2bMHCgoKKCoqgpOTE3788Ud06NCh3vP19PQQFxfHrXZbrbCwEBYWFtzeh8Jmz549sLe3h46ODrcse05ODkxMTPDnn3/We76bmxuys7OxYsWKr06AWoLP2zwwDINTp05BSUkJvXr1AlBVnbWwsFCg5PHu3bu4c+cOunXr9tXxSEpKYufOndi4cSPS09MBAF26dOFLqFoTppb2MImJidyVEYQ0tU+fPkFbWxv/+9//ak0IgarCY4MHD27GyIiooT6FRGRUVFTgxo0bMDMz41Y1FFR9ffaqCXPrhTt37iA7OxvDhg3jNmA/e/Ys2rZtiwEDBtR4jpiYGM+bri/fhFV/3lpmb5qTmJgY8vLy+Kq3vnjxAlpaWkJ9I4JhGERGRnKXShkZGcHGxkagcxUUFHD9+nV89913TRhh81q8eDFev36NvXv3QlxcHEDV69mcOXOgqKiILVu21Hl+7969sWPHDgwcOLA5wm3xlJWVweFw8PbtWygqKvK8JlVUVKCoqAizZs3Cr7/+ymKURJQoKSnh7t27Ai/nJqQpUFJIRIq0tDQePnxIL7zN5Nq1awI9TljufiYlJQn8WDMzsxrHw8PDAVS1EQgODuaZMaqoqEBUVBQuXbpUa386UWdsbIxDhw4JVV9DVVVVxMTEwNDQkGf80aNH6N+/PwoKCvjO+XwW/vbt21i+fDl8fX1hamrKt2dTUVGxaQJvoYKDg8EwDDw8PODv78/zOyYpKQkdHR3069ePxQiJqJk6dSq+++47eHt7sx0KEWG0fJSIFBMTE2RkZFBSKCBPT0+MHDkS48eP/6rzhSXZE9R3330HDofDt4/tS3XNjlb3lONwOJg6dSrPsTZt2kBHR0egHoetya5duzBjxgxIS0tj165ddT523rx5dR739/fHkiVLsG/fPujo6DRilOwpLy9HSkoKX1KYkpJSa/Gdtm3b8s3Kf7knU1Rn6qt/r3R1ddG/f/8aCxsR0pwMDAywdu1a3LhxAz179uRuTalW3+seIY2BZgqJSDl//jyWLl2KdevW1fjCK2p3zOszZMgQpKWlQU1NDfHx8WyH0+JlZWUJ/Fhtbe06j+vq6iIuLg4qKirfGlaLp6uri9u3b6N9+/Z13rDhcDg17qWsXg5Yrbi4GOXl5ZCVleV7w//69evGC7yZzJ8/HyEhIfjll1/Qp08fAMB///2HTZs2YfLkydi+fTvfOYLO0gOid/OmJh8/fkRZWRnPGP09IM3la173CGlslBQSkSIm9v9dWGhvm+Du3bsHExOTRr+ujY0NMjIy6A8e+SbBwcECP/bL2dfWoLKyElu3bsXOnTvx/PlzAECHDh3g5eWFBQsWcPcZkoYpKSnBokWLcPTo0RqX4NLfA0KIKKHlo0SkUDnnhisvL8fJkyfRtm1bdO7cuVGv7ejoiFevXjXqNdlUvR9QEPb29nUer69PmqiUy6+oqEBycjK0tbV5eoN+rjUmeg0hJiaGRYsWYdGiRdy9gmzMYoWGhmLv3r3IzMxEbGwstLW14e/vD11dXTg4ODR7PN9q4cKFuHLlCn7//XdMnjwZv/76K3Jzc7Fv375W22aDEEK+Fs0UEkLqpaCggOTkZKHZo9VUPp+Jrosgs9JfFkr59OkTMjMzISEhgS5dugjtct6ff/4Zpqam8PT0REVFBSwtLREbGwtZWVmcOXOG2w7lS5WVldiyZQvCw8NRVlYGa2trrFq1CjIyMs37BITU77//jpUrV+Lnn3/Ghg0bcO/ePejp6SEoKAjBwcGt8oablpYWQkJCMGTIECgqKiI+Ph76+voIDQ3F4cOHce7cObZDJCLk6dOnCA8PR3Z2Nt9S5pqWiBPS2GimkIicwsJCBAQE4OHDhwCA7t27w8PDg6cCHeFlZWWFa9euUVJYj9qKfnyNhIQEvrF3797Bzc0Njo6OjfZ1Wprjx49j0qRJAICIiAg8efIEKSkpCA0NxbJly3Djxo0az9uwYQNWr14NGxsbyMjIYOfOncjPz0dgYGBzht8kXrx4AR8fH0RFRSE/P5+vkFFzLHPcvXs39u/fj7Fjx/LMovXq1Qs+Pj5N/vWbwuvXr6Gnpwegaua1er/pwIEDMXv2bDZDIyImKioK9vb20NPTQ0pKCkxMTPDkyRMwDAMLCwu2wyMigpJCIlJu376NESNGQEZGhluwYfv27diwYQMuXrxIL761sLW1xZIlS5CcnFxjgZ7alkJ6eHgIdH1heOPeHBQVFbFmzRqMGTMGkydPZjucJvHq1StoaGgAAM6dO4fx48eja9eu8PDwwM6dO2s9LyQkBL/99htmzpwJAIiMjISdnR0OHDgg8AxuS+Xm5obs7GysWLECHTp0qLHhelPLzMyssc2HlJQUiouLmz2exqCnp4fMzExoaWmhW7duOHr0KPr06YOIiIgG97Il5FssXboUPj4+WLNmDRQUFHDixAmoqanB1dUVI0eOZDs8IiIoKSQixdvbG/b29ti/fz8kJKp+/MvLyzFt2jT8/PPPiI6OZjnClmnOnDkAal7CUtdSyKCgIGhra8Pc3LzeNg3C6Nq1a9i6dSt3VtrY2BgLFy7EoEGDvvqab9++xdu3bxsrxBZHXV0dDx48QIcOHXD+/Hn8/vvvAKqKgtRVUCU7OxujRo3ifm5jYwMOh4Nnz541+l7Y5hYTE4Pr16/ju+++Yy0GXV1d3L17l69q7vnz52FkZMRSVN/G3d0diYmJGDx4MJYsWYIxY8Zgz549+PTpEy3XI83q4cOHOHz4MABAQkICHz58gLy8PNauXQsHBweauSbNgpJCIlJu377NkxACVS/AixYtQq9evViMrGX72mWRs2fPxuHDh5GZmQl3d3dMmjQJ7dq1a+ToWqY///wT7u7ucHJy4vaYunHjBqytrREUFAQXF5c6z/+yXx/DMHj+/DlCQ0Nha2vbZHGzzd3dHc7OztwZMRsbGwBVLRi6detW63nl5eWQlpbmGWvTpg0+ffrUpPE2B01NzW+6qdIYy0/nz5+PH3/8ER8/fgTDMLh16xYOHz6MjRs34sCBA18dG5s+bxRuY2ODlJQU3LlzB/r6+jAzM2MxMiJq5OTkuPsIO3TogPT0dHTv3h0AhKoYG2nZqNAMESnq6uoIDQ3F8OHDecYvXLiAKVOm4MWLFyxF1np8/PiR7813XUpLS3Hy5EkEBgbi5s2bsLOzg6enJ4YPH87KMrjmYmRkhBkzZvC88QSqZlv379/PnT2szZd9q8TExKCqqgorKyssXboUCgoKjR5zS3H8+HHk5ORg/Pjx3Fm+4OBgtG3bttYql2JiYrC1tYWUlBR3LCIiAlZWVjzLnU+ePNm0wTeBixcvYtu2bdi3b99X7eu1tbVFdnY25s6dW+PyU0Erhx46dAirV69Geno6AKBjx45Ys2YNPD09GxwTIeT/jR07FnZ2dpg+fTp8fHzw999/w83NDSdPnoSysjIiIyPZDpGIAEoKiUiZN28eTp06ha1bt6J///4AqmZvFi5ciHHjxsHf35/dAFuoiooK+Pr6Yu/evXjx4gVSU1Ohp6eHFStWQEdHR+A3hVlZWQgKCkJISAjKy8tx//59yMvLN3H07JCSksL9+/ehr6/PM56WlgYTExN8/PiRpchan8LCwnr3eLm7uwt0rYMHDzZCRM1LWVkZJSUlKC8vh6ysLNq0acNzvLpASm0UFBQadflpSUkJioqKoKam1ijXa067du3CjBkzIC0tzTcb/6XqGX5CmlpGRgaKiopgZmaG4uJiLFiwADdv3oSBgQG2b9/Ot2ybkKZAy0eJSNm6dSs4HA6mTJmC8vJyAFVLzGbPnk19qeqwYcMGBAcHw8/PD9OnT+eOm5iYwN/fX+CkUExMDBwOBwzDCH1jaE1NTURFRfElhZGRkdDU1GzQtZ4+fQoArX5vnCA2b94MHR0dTJgwAQDg7OyMEydOoEOHDjh37lyty/paY7InqG+9WfWty0+/JCsrC1lZ2Ua7XnPasWMHXF1dIS0tjR07dtT6OA6HQ0khaTbVVXCBqqWke/fuZTEaIqpoppCIpJKSEu4SqC5durTaNzjNRV9fH/v27YO1tTUUFBSQmJjILZ3dr18/vHnzptZzP18+GhMTg9GjR8Pd3R0jR45s9VUh6/L777/j559/hoeHB8+sdFBQEHbu3MmtklmbyspKrF+/Htu2bUNRURGAqhmfBQsWYNmyZUL7vdPV1cWhQ4fQv39/XLp0Cc7Ozjhy5AiOHj2K7OxsXLx4ke0QW52vXX5qbm4u8BJvYe2bSUhzKyoq4tvHr6ioyFI0RJTQTCERSbKysjA1NWU7jFYjNzeXb8YLqEpc6irkMWfOHISFhUFTUxMeHh44fPgwVFRUmjLUFmP27NnQ0NDAtm3bcPToUQBV+wyPHDki0B6uZcuWISAgAJs2bcKAAQMAVFWhXL16NT5+/IgNGzY0afxsycvL486knjlzBs7Ozhg+fDh0dHTQt29flqNjT0VFBU6fPs3TX9Xe3r7OiqzVJkyYgJKSEu4NMEGXn44dO/ab4yaE1C8zMxNz587F1atXebYWMAxTZ4VvQhoTzRQSoefk5CTwY1tjEYrm0LNnT3h7e2PSpEk8M4Vr167FpUuXcP369RrPExMTg5aWVr0zDvR959exY0fs3buXrwfk33//jTlz5iA3N5elyJpWx44dcfz4cfTv3x+GhoZYv349xo8fj0ePHqF379549+4d2yE2u7S0NIwaNQq5ubkwNDQEADx69Aiampo4e/YsunTpUuf5wcHBdR6fOnVqo8XamowbNw59+vTB4sWLecb9/PwQFxeHY8eOsRQZETUDBgwAwzDw8vKCuro639/LwYMHsxQZESU0U0iEnpKSEtshtHorV67E1KlTkZubi8rKSpw8eRKPHj1CSEgIzpw5U+t5U6ZMEeoKo3WJi4tDZWUl3+zWf//9B3Fx8XpboLx+/brGFgzdunWrt7BIa+bk5AQXFxcYGBigoKCA234jISGhxtlqUTBv3jx06dIF//77L7elS0FBASZNmoR58+bh7NmzdZ4vqklffaKjo7F69Wq+cVtbW2zbtq35AyIiKzExEXfu3OHe9CGEDZQUEqEnzAUomouDgwMiIiKwdu1ayMnJYeXKlbCwsEBERASGDRtW63lBQUHNF2QL8+OPP2LRokV8SWFubi42b96M//77r87ze/TogT179vBVSNyzZw969OjR6PG2FDt27ICOjg5ycnLg5+fHrU77/PlzzJkzh+Xo2HHt2jWehBAA2rdvz7O0WFAfP37k9kOrJsh+peoiUbVpjcvbioqKICkpyTfepk0bkZyRJuzp3bs3cnJyKCkkrKKkkIic8vJyXL16Fenp6XBxcYGCggKePXsGRUVFoW2P0BgGDRqES5cusR1Gq/HgwQNYWFjwjZubm+PBgwf1nu/n5wc7OztERkaiX79+AIDY2Fjk5OTg3LlzjR5vS9GmTRv4+PjwjX/Z71GUSElJ4f3793zjtSU1XyouLsbixYtx9OhRFBQU8B0XJKE7deoUz+efPn1CQkICgoODsWbNmnrPb4lMTU1x5MgRrFy5kmc8LCwMxsbGLEVFRNGBAwcwa9Ys5ObmwsTEhG/fb21VlwlpTJQUEpGSlZWFkSNHIjs7G6WlpRg2bBgUFBSwefNmlJaWUhnoWujp6SEuLg7t27fnGS8sLISFhQUyMjJYiqzlkpKSwosXL3hKjQNVM14SEvW/9A4ePBipqan49ddfkZKSAqBqaeWcOXPQsWPHJom5pQgNDcW+ffuQkZGB2NhYaGtrw9/fH7q6ugI3Whcmo0ePxowZMxAQEIA+ffoAqFqGPGvWLL49pzVZtGgRrly5gt9//x2TJ0/Gr7/+itzcXOzbt0/gVjw1fd+///57dO/eHUeOHGmVDexXrFgBJycnpKenw8rKCgAQFRWFw4cP035C0qxevnyJ9PR0nn6r1e2bqNAMaTYMISLEwcGBmTRpElNaWsrIy8sz6enpDMMwzJUrVxh9fX2Wo2u5OBwO8+LFC77xvLw8RlJSkoWIWr6JEycygwcPZgoLC7ljb968YQYPHsyMHz+exchatt9++41RUVFh1q9fz8jIyHB/Rw8ePMgMGTKE5ejY8ebNG8be3p7hcDiMpKQkIykpyYiJiTFjx47l+fmqjaamJnPlyhWGYRhGQUGBefz4McMwDBMSEsLY2tp+U2zp6emMnJzcN12DTWfOnGH69+/PyMrKMu3bt2eGDh3KXL16le2wiIgxMjJinJycmH///ZfJzMxknjx5wvOPkOZA1UeJSGnfvj1u3rwJQ0NDniqaT548gbGxMUpKStgOsUUJDw8HUFWaPjg4mKdoT0VFBaKionDp0iU8evSIrRBbrNzcXFhaWqKgoADm5uYAgLt370JdXR2XLl0SqIF9YWEhbt26hfz8fL6+VVOmTGmSuNlmbGwMX19fjB07lud39N69exgyZAhevXrFdoisSUtL47akMDIyErjwjry8PB48eAAtLS107twZJ0+eRJ8+fZCZmQlTU1NuH8yG+vDhA5YuXYp//vmHXgMI+QZycnJITEwU2WJapGWg5aNEpFRWVta4DOPp06dQUFBgIaKWrbpPGYfD4atg2KZNG+jo6FCVvlp06tQJSUlJOHToEBITEyEjIwN3d3f88MMPfPtFahIREQFXV1cUFRVBUVGRp8gHh8MR2qQwMzOTm0R/TkpKCsXFxSxE1HLo6+t/1ZtGPT09ZGZmQktLC926dcPRo0fRp08fREREoG3btgJdQ1lZmednkGEYvH//HrKysvjzzz8bHFNLcufOHZ7+jzX9/BHSlKysrCgpJKyjpJCIlOHDh8Pf3x9//PEHgKo310VFRVi1ahVGjRrFcnQtT/XslK6uLuLi4kSm8XxjkZOTw4wZM77q3AULFsDDwwO+vr6QlZVt5MhaLl1dXdy9exfa2to84+fPn4eRkRFLUbHrW/vpubu7IzExEYMHD8aSJUswZswY7NmzB58+fcL27dsFisHf35/nczExMaiqqqJv375QVlZu0PNpKfLz8zFx4kRcvXqVmxwXFhZi6NChCAsLg6qqKrsBEpExZswYeHt7Izk5Gaampnw3DgXZO0zIt6Llo0SkPH36FCNGjADDMHj8+DF69eqFx48fQ0VFBdHR0VBTU2M7xFajsLBQ4FkG0nBycnJITk7mK1Qj7A4cOIDVq1dj27Zt8PT0xIEDB5Ceno6NGzfiwIEDmDhxItshNjtVVVVcvnwZpqamPOPJycmwsbHBixcvGnS9rKws3LlzB/r6+iJd1XDChAnIyMhASEgI94bDgwcPMHXqVOjr6+Pw4cMsR0hEhZiYWK3HqNAMaS6UFBKRU15ejrCwMCQlJaGoqAgWFhZwdXWFjIwM26G1WJs3b4aOjg4mTJgAABg/fjxOnDiBDh064Ny5c0LdN48tTk5OmDhxIpydndkOpdkdOnQIq1evRnp6OgCgY8eOWLNmTauscNkYZGRkcPfuXb4eZikpKTA3N8eHDx+aJQ5h2+OqpKSEyMhI9O7dm2f81q1bGD58OAoLC9kJjBBCWEBJISGkXrq6ujh06BD69++PS5cuwdnZGUeOHMHRo0eRnZ2Nixcvsh2iUKgu7ANUlShfu3Yt3N3dhX45UXh4OGxtbfmeY0lJCYqKikR+Br9Pnz4YPXo0Xz+91atXIyIiAnfu3Knz/Hnz5kFfXx/z5s3jGd+zZw/S0tL4lobWpL49rq9fvxb8CbUQCgoKuH79Or777jue8YSEBAwePJga2BNCRAolhUTkPH78GFeuXKnxbveXb7pIFRkZGaSmpkJTUxNeXl74+PEj9u3bh9TUVPTt2xdv3rxhO0ShUNcSos8J23IicXFx5OXlQVVVFeLi4nj+/LnIJ4Kfi4iIgJOTE1xcXGrsp1ddEKo2nTp1Qnh4OHr27MkzHh8fD3t7ezx9+rTeGLp27YpRo0YJ1R5XBwcHFBYW4vDhw9zen7m5uXB1dYWysjJOnTrFcoREmO3atQszZsyAtLQ0du3aVedjv7yhQ0hToKSQiJT9+/dj9uzZUFFRgYaGBt/d7vj4eBaja7k6duyI48ePo3///jA0NMT69esxfvx4PHr0CL1796Y76rUoLCzE8ePHkZ6ejoULF6Jdu3aIj4+Huro6OnXqxHZ4LYaGhgb279+PMWPGQExMDC9evKAiH184e/YsfH19cffuXcjIyMDMzAyrVq3C4MGD6z1XWloa9+7d46tsmJaWBhMTE3z8+LHeawjjHtecnBzY29vj/v373BYxOTk5MDExQXh4ODp37sxyhESY6erq4vbt22jfvj10dXVrfRyHw0FGRkYzRkZEFVUfJSJl/fr12LBhA18VP1K36lkKAwMDFBQUwNbWFkDVMisqoV2zpKQk2NjYQElJCU+ePMH06dPRrl07nDx5EtnZ2QgJCanz/JCQEEyYMAFSUlI842VlZQgLC2uVe7hqM2vWLDg4OIDD4YDD4UBDQ6PWxwrTDGlD2NnZwc7O7qvO1dfXx/nz5zF37lye8X/++UfgJG/EiBG4ffu2UCWFmpqaiI+PR2RkJFJSUgBU9X+0sbFhOTIiCjIzM2v8mBC20EwhESmKioq4e/euUL2xaQ6fPn3Czp07kZOTAzc3N24frx07dkBBQQHTpk1jOcKWx8bGBhYWFvDz8+Npwn7z5k24uLjgyZMndZ5f2zLKgoICqKmpCV1ylJKSgrS0NNjb2+PgwYO1VrZ1cHBo3sBaiOpZ54yMDPj4+DRo1jkwMBBz587FwoULeZafbtu2Df7+/pg+fXqN54niHleqqkya26dPn9CtWzecOXNGZNvukJaBkkIiUjw9PdG7d2/MmjWL7VCIkFNSUkJ8fDy6dOnCkxRmZWXB0NCw3iV7tS2jTExMxNChQ1tlYQ9BrFmzBgsXLhSafWuN4ctZ50ePHkFPTw/Lly8XaNYZAH7//Xds2LABz549AwDo6Ohg9erVdc44C/se1y+rKjs7O+PEiRPQ0NCgqsqkWXXq1AmRkZGUFBJWUVJIhN7nG7iLi4uxfft22NnZ1Xi3mzZz1+3BgwfIzs5GWVkZz7iwzBI0JjU1NVy4cAHm5uY8SeGlS5fg4eGBnJycGs8zNzcHh8NBYmIiunfvDgmJ/1/lX1FRgczMTIwcORJHjx5trqfCipcvX+LRo0cAAENDQ5HeY/its86fe/nyJWRkZCAvL990AbcSVFWZtBS+vr5ITU3FgQMHeF7zCWlOlBQSoVfXBu7P0Wbu2mVkZMDR0RHJycngcDioftmoLtTTGmcJmtq0adNQUFCAo0ePol27dkhKSoK4uDjGjh0LS0vLWtsArFmzhvvfBQsW8Lx5l5SUhI6ODsaNGwdJScnmeBrNrqSkBHPnzkVoaCj350pcXBxTpkzB7t27RXIG8VtnnUnNqKoyaSkcHR0RFRUFeXl5mJqaQk5Ojuf4yZMnWYqMiBK6HUGEHm3g/nZeXl7Q1dVFVFQUdHV1cevWLRQUFGDBggXYunUr2+G1SNu2bcP3338PNTU1fPjwAYMHD0ZeXh769euHDRs21HreqlWrAIC7rE1aWrq5Qm4RvL29ce3aNYSHh2PAgAEAgJiYGMybNw8LFizA77//znKEzU9KSqrGCr+pqam1zqBaWFggKioKysrK3Nnn2ghSdbkxeh22NMrKysjJyYGmpibOnz+P9evXAwAYhqEbXaRZtW3bFuPGjWM7DCLiaKaQEFIvFRUVXL58GWZmZlBSUsKtW7dgaGiIy5cvY8GCBUhISGA7xBYrJiYGSUlJKCoqgoWFBVU2rIeKigqOHz+OIUOG8IxfuXIFzs7OePnyJTuBsehrZp0/35tZPftcm+obEXVpjF6HLc3cuXNx5swZGBgYICEhAU+ePIG8vDzCwsLg5+dHLYoIISKFZgqJSBk3bhz69OnD15LCz88PcXFxOHbsGEuRtWwVFRVQUFAAUPWm/dmzZzA0NIS2tjZ33xep2cCBAzFw4ECBHtuuXTukpqZCRUUFysrKdc7uCGuhmZKSEqirq/ONq6mpoaSkhIWI2Pc1s87ViV5FRQWGDh0KMzOzb6qqWVBQACUlJb5xRUVFvHr16quvy6YdO3ZAR0cHOTk58PPz4y7Vfv78OebMmcNydEQUVFZWYsuWLQgPD0dZWRmsra2xatUqyMjIsB0aEUGUFBKREh0djdWrV/ON29raYtu2bc0fUCthYmKCxMRE6Orqom/fvvDz84OkpCT++OMPau9Rh7i4OFy5cgX5+fmorKzkObZ9+3a+x1e3+Kj+uK6kUFj169cPq1atQkhICHfp7IcPH7BmzRr069eP5ejYoaSkhEuXLuHGjRtITExs0KyzuLg4hg8fjocPH35TUtgYvQ5bmjZt2sDHx4dv3Nvbm4VoiCjasGEDVq9eDRsbG8jIyGDnzp3Iz89HYGAg26EREURJIREpRUVFNRboaNOmTY17dkiV5cuXo7i4GACwdu1ajB49GoMGDUL79u1x5MgRlqNrmXx9fbF8+XIYGhpCXV2dJ8GrLdmbOnUq92M3N7emDrFF8vf3x8iRI9G5c2duS4DExERIS0vjwoULLEfHrgEDBnD3WTaEiYkJMjIyBC66VZP58+dj7ty5ePnyZY29Dluj4OBgqKiowM7ODgCwaNEi/PHHHzA2Nsbhw4ehra3NcoRE2IWEhOC3337DzJkzAQCRkZGws7PDgQMHBG4JQ0hjoT2FRKT06dMHo0ePxsqVK3nGV69ejYiICNy5c4elyFqf169f17vEUZSpq6tj8+bNX53cTZkyBUOHDoWlpSW6dOnSuMG1cCUlJTh06BBSUlIAAEZGRnB1dRW5JVWxsbEoKCjA6NGjuWMhISFYtWoViouLMXbsWOzevRtSUlJ1Xuf8+fNYunQp1q1bh549e/JVNlRUVBQonq/pddiSGRoa4vfff4eVlRViY2NhY2ODHTt24MyZM5CQkKCKj6TJSUlJIS0tDZqamtwxaWlppKWloXPnzixGRkQRJYVEpERERMDJyQkuLi48d7sPHz6MY8eOYezYsewGSIRGhw4dEB0dDQMDg686f9q0aYiOjkZaWho6deqEwYMHY8iQIRg8ePBXX7Ol+/TpE7p164YzZ85QE2dULWsfMmQIdw90cnIyLCws4ObmBiMjI2zZsgUzZ86scUn85z6fcfj8Jg7DMF/VeF5Yeh3KysoiJSUFWlpaWLx4MZ4/f46QkBDcv38fQ4YMEcmiRqR5iYuLIy8vj6eKsIKCApKSkr5pZp+Qr0FJIRE5Z8+eha+vL+7evQsZGRmYmZlh1apVGDx4MNuhtTgeHh4CPY72P/Dz8/PDs2fPvnlpXW5uLqKjo3Ht2jVcu3YNqamp6NChQ6us9iiITp06ITIykpJCVN1YiIiIQK9evQAAy5Ytw7Vr1xATEwMAOHbsGFatWoUHDx7UeZ1r167VeVyQ174PHz6AYRhun8isrCycOnUKxsbGGD58uCBPp8VRU1PDhQsXYG5uDnNzc8yfPx+TJ09Geno6evTogaKiIrZDJEJOTEwMtra2PLP9ERERsLKy4pnRp1lr0hxoTyEROXZ2dtw9JKRuQUFB0NbWhrm5Oej+UcP4+PjAzs4OXbp0gbGxMdq0acNzXNA/8srKymjfvj2UlZXRtm1bSEhI1NqbThj8+OOP2Lx5Mw4cOAAJCdH+E/XmzRueSqzXrl2Dra0t9/PevXsjJyen3us0xg0vBwcHODk5YdasWSgsLESfPn0gKSmJV69eYfv27Zg9e/Y3f43mNmzYMEybNg3m5uZITU3FqFGjAAD379+n/YSkWXy+j7zapEmTWIiEEEoKCSF1mD17Ng4fPozMzEy4u7tj0qRJaNeuHdthtQrz5s3DlStXMHToULRv377Bey9/+eUXXL16FQkJCTAyMsLgwYOxZMkSWFpaQllZuYmiZl9cXByioqJw8eJFmJqa8u1/E6U75urq6sjMzISmpibKysoQHx/P03Pw/fv3fDcbanP9+nXs27cPGRkZOHbsGDp16oTQ0FDo6uoK1DIlPj4eO3bsAAAcP34cGhoaSEhIwIkTJ7By5cpWmRT++uuvWL58OXJycnDixAm0b98eAHDnzh24uLiwHB0RBQcPHmQ7BEK4aPkoESkVFRXYsWMHjh49iuzsbJSVlfEcF9beb9+itLQUJ0+eRGBgIG7evAk7Ozt4enpi+PDhVGSmDgoKCggLC/vqWWkxMTGoqqrC29sbTk5O6Nq1ayNH2DK5u7vXeVyU3kTNnj0biYmJ2Lx5M06fPo3g4GA8e/aMW0H50KFD8Pf3R1xcXJ3XOXHiBCZPngxXV1eEhobiwYMH0NPTw549e3Du3DmcO3eu3lg+33/n7OyM7t27Y9WqVcjJyYGhoaHQ9ZC8d+8eTExM2A6DEEKaDSWFRKSsXLkSBw4cwIIFC7B8+XIsW7YMT548wenTp7Fy5UrMmzeP7RBbtKysLAQFBSEkJATl5eW4f/9+qy820VS0tbVx4cIFdOvW7avOT0xMxLVr13D16lVcv34dkpKS3GIzQ4YMEZkkUZS9evUKTk5OiImJgby8PIKDg+Ho6Mg9bm1tjf/973+1NrCvZm5uDm9vb0yZMgUKCgpITEyEnp4eEhISYGtri7y8vHpjMTMzw7Rp0+Do6AgTExOcP38e/fr1w507d2BnZyfQNVq69+/f4/DhwwgICMDt27cbXICHEEJaM0oKiUjp0qULdu3aBTs7OygoKODu3bvcsX///Rd//fUX2yG2aDk5OTh48CCCgoJQVlaGlJQUSgprcfDgQZw/fx4HDx7kFuf4FomJidixYwcOHTqEyspKoXvDWllZiS1btiA8PBxlZWWwtrbGqlWrRK4NRU3evn0LeXl5iIuL84y/fv0a8vLyNfZe/ZysrCwePHgAHR0dnqQwIyMDxsbG+PjxY70xHD9+HC4uLqioqIC1tTUuXrwIANi4cSOio6Pxzz//fP0TZFl0dDQCAgJw4sQJdOzYEU5OThg3bhx69+7NdmiEENJsaE8hESl5eXkwNTUFAMjLy+Pt27cAgNGjR2PFihVshtZifb58NCYmBqNHj8aePXswcuRIaq5bh127diE9PR3q6urQ0dHh2/sVHx9f5/kMwyAhIQFXr17F1atXERMTg3fv3sHMzEwoK+Vu2LABq1evho2NDWRkZLBz507k5+dTZVsASkpKNY4Lur9XQ0MDaWlp0NHR4RmPiYmBnp6eQNf4/vvvMXDgQDx//hw9evTgjltbW/PMXrYWeXl5CAoKQkBAAN69ewdnZ2eUlpbi9OnTMDY2Zjs8QghpdpQUEpHSuXNnPH/+HFpaWujSpQsuXrwICwsLxMXF1dsAWhTNmTMHYWFh0NTUhIeHBw4fPgwVFRW2w2oVvrXnZbt27VBUVIQePXpg8ODBmD59OgYNGoS2bds2SnwtTUhICH777TfMnDkTABAZGQk7OzscOHCAbj58o+nTp8PLywuBgYHgcDh49uwZYmNj4ePj06CbYRoaGtDQ0OAZ69OnT2OH2+TGjBmD6Oho2NnZwd/fHyNHjoS4uDj27t3LdmiEEMIaWj5KRMqSJUugqKiIX375BUeOHMGkSZOgo6OD7OxseHt7Y9OmTWyH2KKIiYlBS0sL5ubmdRaVEaWKkM3l7NmzGDRoEBQVFdkOpVlISUkhLS0Nmpqa3DFpaWmkpaWhc+fOLEbW+jEMA19fX2zcuJFbEEZKSgo+Pj5Yt25drec5OTkJ/DVa02uAhIQE5s2bh9mzZ8PAwIA73qZNGyQmJtJMISFEJNFMIREpnyd9EyZMgJaWFmJjY2FgYIAxY8awGFnLNGXKFKow+o3u3LmDhw8fAgC6d+8Oc3Nzgc4TtV6a5eXlkJaW5hlr06YNPn36xFJEwoPD4WDZsmVYuHAh0tLSUFRUBGNj43r3A9e2bLW1i4mJQUBAAHr27AkjIyNMnjwZEydOZDssQghhFc0UEkJIE8jPz8fEiRNx9epV7pLPwsJCDB06FGFhYULdgP5riImJwdbWlmcZd0REBKysrHh6FbamGSnSshUXF+PIkSMIDAzErVu3UFFRge3bt8PDwwMKCgpsh0cIIc2KkkIiUgoKCrgNinNycrB//358+PAB9vb2GDRoEMvREWEyYcIEZGRkICQkBEZGRgCABw8eYOrUqdDX18fhw4dZjrBlqa8/YTVR6lPYWD5+/Ijdu3fjypUryM/PR2VlJc/x+ooeiYJHjx4hICAAoaGhKCwsxLBhwxAeHs52WIQQ0mwoKSQiITk5GWPGjEFOTg4MDAwQFhaGkSNHori4GGJiYiguLsbx48e/uTgIIdWUlJQQGRnJV9b+1q1bGD58OAoLC9kJjIgcV1dXXLx4Ed9//z3U1dX5loSvWrVKoOscP34cR48eRXZ2NsrKyniOCUtiWVFRgYiICAQGBlJSSAgRKbSnkIiERYsWwdTUFIcOHUJoaChGjx4NOzs77N+/HwDw008/YdOmTZQUkkZTWVnJ14YCqNon9+VMDSFN6cyZMzh37hwGDBjw1dfYtWsXli1bBjc3N/z9999wd3dHeno64uLi8OOPPzZitOwSFxfH2LFj6W8BIUTk0EwhEQkqKiq4fPkyzMzMUFRUBEVFRcTFxaFnz54AgJSUFPzvf/+j2RvSaBwcHFBYWIjDhw+jY8eOAIDc3Fy4urpCWVkZp06dYjlCIiqMjY0RFhYGMzOzr75Gt27dsGrVKvzwww9QUFBAYmIi9PT0sHLlSrx+/Rp79uxpxIgJIYQ0N2r+RETC69evuf215OXlIScnB2VlZe5xZWVlvH//nq3wiBDas2cP3r17Bx0dHXTp0gVdunSBrq4u3r17h927d7MdHhEh27Ztw+LFi5GVlfXV18jOzkb//v0BADIyMtzXy8mTJ9P+WEIIEQK0fJSIjC/30VCrBdKUNDU1ER8fj8jISKSkpAAAjIyMYGNjw3JkRNT06tULHz9+hJ6eHmRlZfmWNb9+/brea2hoaOD169fQ1taGlpYW/v33X/To0QOZmZmgBUeEENL6UVJIRIabmxu33P3Hjx8xa9Ysbqn70tJSNkMjQorD4WDYsGEYNmwY26EQEfbDDz8gNzcXvr6+NRaaEYSVlRXCw8Nhbm4Od3d3eHt74/jx47h9+3aDmtwTQghpmWhPIREJVO6eNJfY2FgUFBRg9OjR3LGQkBCsWrUKxcXFGDt2LHbv3s3Tj4+QpiQrK4vY2Fj06NHjq69RWVmJyspKSEhU3UsOCwvDzZs3YWBggJkzZ0JSUrKxwiWEEMICSgoJIaQR2draYsiQIVi8eDGAqnYoFhYWcHNzg5GREbZs2YKZM2di9erV7AZKRIaFhQV+++03/O9//2M7FEIIIS0UFZohhJBGdPfuXVhbW3M/DwsLQ9++fbF//37Mnz8fu3btwtGjR1mMkIiaTZs2YcGCBbh69SoKCgrw7t07nn+Cun79OiZNmoR+/fohNzcXABAaGoqYmJimCp0QQkgzoaSQEEIa0Zs3b6Curs79/Nq1a7C1teV+3rt3b+Tk5LARGhFRI0eORGxsLKytraGmpgZlZWUoKyujbdu2PFWY63LixAmMGDECMjIySEhI4O7Dfvv2LXx9fZsyfEIIIc2ACs0QQkgjUldXR2ZmJjQ1NVFWVob4+HisWbOGe/z9+/c1NrUnpKlcuXLlm6+xfv167N27F1OmTEFYWBh3fMCAAVi/fv03X58QQgi7KCkkhJBGNGrUKCxZsgSbN2/G6dOnISsri0GDBnGPJyUloUuXLixGSETN4MGDaz127949ga7x6NEjWFpa8o0rKSmhsLDwa0MjhBDSQtDyUUIIaUTr1q2DhIQEBg8ejP3792P//v08lRkDAwMxfPhwFiMkou79+/f4448/0KdPH4ErkmpoaCAtLY1vPCYmBnp6eo0dIiGEkGZGM4WEENKIVFRUEB0djbdv30JeXh7i4uI8x48dOwZ5eXmWoiOiLDo6GgEBAThx4gQ6duwIJycn/PrrrwKdO336dHh5eSEwMBAcDgfPnj1DbGwsfHx8sGLFiiaOnBBCSFOjpJAQQpqAkpJSjePt2rVr5kiIKMvLy0NQUBACAgLw7t07ODs7o7S0FKdPn4axsbHA11myZAkqKythbW2NkpISWFpaQkpKCj4+Pvjpp5+a8BkQQghpDtSnkBBCCBFCY8aMQXR0NOzs7ODq6oqRI0dCXFwcbdq0QWJiYoOSwmplZWVIS0tDUVERjI2NIS8vjw8fPkBGRqYJngEhhJDmQkkhIYQQIoQkJCQwb948zJ49GwYGBtzxb0kKP1daWopff/0Vfn5+yMvL+9ZwCSGEsIgKzRBCCCFCKCYmBu/fv0fPnj3Rt29f7NmzB69evWrQNUpLS7F06VL06tUL/fv3x+nTpwEABw8ehK6uLnbs2AFvb+8miJ4QQkhzoplCQgghRIgVFxfjyJEjCAwMxK1bt1BRUYHt27fDw8MDCgoKdZ67ePFi7Nu3DzY2Nrh58yZevnwJd3d3/Pvvv/jll18wfvx4vmJKhBBCWh9KCgkhhBAR8ejRIwQEBCA0NBSFhYUYNmwYwsPDa328np4e/P39YW9vj3v37sHMzAxubm4ICAgAh8NpxsgJIYQ0JUoKCSGEEBFTUVGBiIgIBAYG1pkUSkpKIjMzE506dQIAyMjI4NatWzA1NW2uUAkhhDQDSgoJIYQQUiNxcXHk5eVBVVUVAKCgoICkpCTo6uqyHBkhhJDGRH0KCSGEEFIjhmHg5uYGKSkpAMDHjx8xa9YsyMnJ8Tzu5MmTbIRHCCGkkVBSSAghhJAaTZ06lefzSZMmsRQJIYSQpkTLRwkhhBBCCCFEhFGfQkIIIYQQQggRYZQUEkIIIYQQQogIo6SQEEIIIYQQQkQYJYWEEEIIIYQQIsIoKSSEEEIEwOFwcPr0abbD4AoKCkLbtm3ZDoMQQogQoKSQEEKIyHFzcwOHw+H7N3LkSIGv0dKSREIIIeRrUZ9CQgghImnkyJE4ePAgz1h1k3ZCCCFElNBMISGEEJEkJSUFDQ0Nnn/KysoAgMePH8PS0hLS0tIwNjbGpUuXGnz9AwcOwMjICNLS0ujWrRt+++037rH+/ftj8eLFPI9/+fIl2rRpg+joaABAaWkpfHx80KlTJ8jJyaFv3764evXq1z9hQgghpBY0U0gIIYR8prKyEk5OTlBXV8d///2Ht2/f4ueff27QNQ4dOoSVK1diz549MDc3R0JCAqZPnw45OTlMnToVrq6u8PPzw6ZNm8DhcAAAR44cQceOHTFo0CAAwNy5c/HgwQOEhYWhY8eOOHXqFEaOHInk5GQYGBg09tMmhBAiwmimkBBCiEg6c+YM5OXlef75+voiMjISKSkpCAkJQY8ePWBpaQlfX98GXXvVqlXYtm0bnJycoKurCycnJ3h7e2Pfvn0AAGdnZzx79gwxMTHcc/766y/88MMP4HA4yM7OxsGDB3Hs2DEMGjQIXbp0gY+PDwYOHMi35JUQQgj5VjRTSAghRCQNHToUv//+O89Yu3btEBoaCk1NTXTs2JE73q9fP4GvW1xcjPT0dHh6emL69Onc8fLycigpKQEAVFVVMXz4cBw6dAiDBg1CZmYmYmNjuUljcnIyKioq0LVrV55rl5aWon379g1+roQQQkhdKCkkhBAikuTk5KCvr9/o1y0qKgIA7N+/H3379uU5Ji4uzv3Y1dUV8+bNw+7du/HXX3/B1NQUpqam3GuIi4vjzp07POcAgLy8fKPHTAghRLRRUkgIIYR8xsjICDk5OXj+/Dk6dOgAAPj3338FPl9dXR0dO3ZERkYGXF1da32cg4MDZsyYgfPnz+Ovv/7ClClTuMfMzc1RUVGB/Px87h5DQgghpKlQUkgIIUQklZaWIi8vj2dMQkICNjY26Nq1K6ZOnYotW7bg3bt3WLZsWY3XyMzMxN27d3nGDAwMsGbNGsybNw9KSkoYOXIkSktLcfv2bbx58wbz588HUDVTOXbsWKxYsQIPHz7EDz/8wL1G165d4erqiilTpmDbtm0wNzfHy5cvERUVBTMzM9jZ2TXuN4MQQohIo6SQEEKISDp//jx3JrCaoaEhUlJScOrUKXh6eqJPnz7Q0dHBrl27amxsX53gfe769euYNm0aZGVlsWXLFixcuBBycnIwNTXlq2Lq6uqKUaNGwdLSElpaWjzHDh48iPXr12PBggXIzc2FiooK/ve//2H06NHf/uQJIYSQz3AYhmHYDoIQQgghhBBCCDuoJQUhhBBCCCGEiDBKCgkhhBBCCCFEhFFSSAghhBBCCCEijJJCQgghhBBCCBFhlBQSQgghhBBCiAijpJAQQgghhBBCRBglhYQQQgghhBAiwigpJIQQQgghhBARRkkhIYQQQgghhIgwSgoJIYQQQgghRIRRUkgIIYQQQgghIoySQkIIIYQQQggRYf8H7SflEx/v8qcAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 10))\n",
    "ax = sns.heatmap(df_ebetfr)\n",
    "xlabels = [textwrap.fill(label.get_text(), width=30) for label in ax.get_xticklabels()]\n",
    "ylabels = [textwrap.fill(label.get_text(), width=20) for label in ax.get_yticklabels()]\n",
    "ax.set(xticklabels=xlabels, yticklabels=ylabels)\n",
    "plt.title(\"Educational Background and Employment Type\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 10: Save the Cleaned and Analyzed Dataset\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After your analysis, save the modified dataset for further use or sharing.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Write your code here\n",
    "df_me.to_csv(\"Lab12out.csv\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Summary</h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this revised lab, you:\n",
    "\n",
    "- Loaded and explored the structure of the dataset.\n",
    "\n",
    "- Handled missing data effectively.\n",
    "\n",
    "- Analyzed key variables, including working hours, job satisfaction, and remote work trends.\n",
    "\n",
    "- Investigated programming language usage by region and examined the relationship between experience and satisfaction.\n",
    "\n",
    "- Used cross-tabulation to understand educational background and employment type.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copyright © IBM Corporation. All rights reserved.\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.5"
  },
  "prev_pub_hash": "2a4f0935f8d3cf9549d9e18dbbd812b8dd5a034c94517c8adba13875f8268801"
 },
 "nbformat": 4,
 "nbformat_minor": 4
}