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| { | |
| "cells": [ | |
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| "cell_type": "markdown", | |
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| }, | |
| "source": [ | |
| "<center>\n", | |
| " <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DV0101EN-SkillsNetwork/labs/Module%202/images/IDSNlogo.png\" width=\"300\" alt=\"cognitiveclass.ai logo\" />\n", | |
| "</center>\n", | |
| "\n", | |
| "\n", | |
| "# Area Plots, Histograms, and Bar Plots\n", | |
| "\n", | |
| "\n", | |
| "Estimated time needed: **30** minutes\n", | |
| " \n", | |
| "\n", | |
| "## Objectives\n", | |
| "\n", | |
| "After completing this lab you will be able to:\n", | |
| "\n", | |
| "* Create additional labs namely area plots, histogram and bar charts" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
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| } | |
| }, | |
| "source": [ | |
| "## Table of Contents\n", | |
| "\n", | |
| "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n", | |
| "\n", | |
| "1. [Exploring Datasets with *pandas*](#0)<br>\n", | |
| "2. [Downloading and Prepping Data](#2)<br>\n", | |
| "3. [Visualizing Data using Matplotlib](#4) <br>\n", | |
| "4. [Area Plots](#6) <br>\n", | |
| "5. [Histograms](#8) <br>\n", | |
| "6. [Bar Charts](#10) <br>\n", | |
| "</div>\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "# Exploring Datasets with *pandas* and Matplotlib<a id=\"0\"></a>\n", | |
| "\n", | |
| "Toolkits: The course heavily relies on [*pandas*](http://pandas.pydata.org/) and [**Numpy**](http://www.numpy.org/) for data wrangling, analysis, and visualization. The primary plotting library that we are exploring in the course is [Matplotlib](http://matplotlib.org/).\n", | |
| "\n", | |
| "Dataset: Immigration to Canada from 1980 to 2013 - [International migration flows to and from selected countries - The 2015 revision](http://www.un.org/en/development/desa/population/migration/data/empirical2/migrationflows.shtml) from United Nation's website.\n", | |
| "\n", | |
| "The dataset contains annual data on the flows of international migrants as recorded by the countries of destination. The data presents both inflows and outflows according to the place of birth, citizenship or place of previous / next residence both for foreigners and nationals. For this lesson, we will focus on the Canadian Immigration data." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "# Downloading and Prepping Data <a id=\"2\"></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Import Primary Modules. The first thing we'll do is import two key data analysis modules: *pandas* and **Numpy**." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import numpy as np # useful for many scientific computing in Python\n", | |
| "import pandas as pd # primary data structure library" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Let's download and import our primary Canadian Immigration dataset using *pandas* `read_excel()` method. Normally, before we can do that, we would need to download a module which *pandas* requires to read in excel files. This module is **xlrd**. For your convenience, we have pre-installed this module, so you would not have to worry about that. Otherwise, you would need to run the following line of code to install the **xlrd** module:\n", | |
| "```\n", | |
| "!conda install -c anaconda xlrd --yes\n", | |
| "```" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Download the dataset and read it into a *pandas* dataframe." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Data downloaded and read into a dataframe!\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "\n", | |
| "df_can = pd.read_excel('https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DV0101EN-SkillsNetwork/Data%20Files/Canada.xlsx',\n", | |
| " sheet_name='Canada by Citizenship',\n", | |
| " skiprows=range(20),\n", | |
| " skipfooter=2\n", | |
| " )\n", | |
| "print('Data downloaded and read into a dataframe!')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Let's take a look at the first five items in our dataset." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
| " vertical-align: middle;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe tbody tr th {\n", | |
| " vertical-align: top;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe thead th {\n", | |
| " text-align: right;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>Type</th>\n", | |
| " <th>Coverage</th>\n", | |
| " <th>OdName</th>\n", | |
| " <th>AREA</th>\n", | |
| " <th>AreaName</th>\n", | |
| " <th>REG</th>\n", | |
| " <th>RegName</th>\n", | |
| " <th>DEV</th>\n", | |
| " <th>DevName</th>\n", | |
| " <th>1980</th>\n", | |
| " <th>...</th>\n", | |
| " <th>2004</th>\n", | |
| " <th>2005</th>\n", | |
| " <th>2006</th>\n", | |
| " <th>2007</th>\n", | |
| " <th>2008</th>\n", | |
| " <th>2009</th>\n", | |
| " <th>2010</th>\n", | |
| " <th>2011</th>\n", | |
| " <th>2012</th>\n", | |
| " <th>2013</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>0</th>\n", | |
| " <td>Immigrants</td>\n", | |
| " <td>Foreigners</td>\n", | |
| " <td>Afghanistan</td>\n", | |
| " <td>935</td>\n", | |
| " <td>Asia</td>\n", | |
| " <td>5501</td>\n", | |
| " <td>Southern Asia</td>\n", | |
| " <td>902</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>16</td>\n", | |
| " <td>...</td>\n", | |
| " <td>2978</td>\n", | |
| " <td>3436</td>\n", | |
| " <td>3009</td>\n", | |
| " <td>2652</td>\n", | |
| " <td>2111</td>\n", | |
| " <td>1746</td>\n", | |
| " <td>1758</td>\n", | |
| " <td>2203</td>\n", | |
| " <td>2635</td>\n", | |
| " <td>2004</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>Immigrants</td>\n", | |
| " <td>Foreigners</td>\n", | |
| " <td>Albania</td>\n", | |
| " <td>908</td>\n", | |
| " <td>Europe</td>\n", | |
| " <td>925</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>901</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>1</td>\n", | |
| " <td>...</td>\n", | |
| " <td>1450</td>\n", | |
| " <td>1223</td>\n", | |
| " <td>856</td>\n", | |
| " <td>702</td>\n", | |
| " <td>560</td>\n", | |
| " <td>716</td>\n", | |
| " <td>561</td>\n", | |
| " <td>539</td>\n", | |
| " <td>620</td>\n", | |
| " <td>603</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>Immigrants</td>\n", | |
| " <td>Foreigners</td>\n", | |
| " <td>Algeria</td>\n", | |
| " <td>903</td>\n", | |
| " <td>Africa</td>\n", | |
| " <td>912</td>\n", | |
| " <td>Northern Africa</td>\n", | |
| " <td>902</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>80</td>\n", | |
| " <td>...</td>\n", | |
| " <td>3616</td>\n", | |
| " <td>3626</td>\n", | |
| " <td>4807</td>\n", | |
| " <td>3623</td>\n", | |
| " <td>4005</td>\n", | |
| " <td>5393</td>\n", | |
| " <td>4752</td>\n", | |
| " <td>4325</td>\n", | |
| " <td>3774</td>\n", | |
| " <td>4331</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>Immigrants</td>\n", | |
| " <td>Foreigners</td>\n", | |
| " <td>American Samoa</td>\n", | |
| " <td>909</td>\n", | |
| " <td>Oceania</td>\n", | |
| " <td>957</td>\n", | |
| " <td>Polynesia</td>\n", | |
| " <td>902</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>Immigrants</td>\n", | |
| " <td>Foreigners</td>\n", | |
| " <td>Andorra</td>\n", | |
| " <td>908</td>\n", | |
| " <td>Europe</td>\n", | |
| " <td>925</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>901</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>5 rows × 43 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " Type Coverage OdName AREA AreaName REG \\\n", | |
| "0 Immigrants Foreigners Afghanistan 935 Asia 5501 \n", | |
| "1 Immigrants Foreigners Albania 908 Europe 925 \n", | |
| "2 Immigrants Foreigners Algeria 903 Africa 912 \n", | |
| "3 Immigrants Foreigners American Samoa 909 Oceania 957 \n", | |
| "4 Immigrants Foreigners Andorra 908 Europe 925 \n", | |
| "\n", | |
| " RegName DEV DevName 1980 ... 2004 2005 2006 \\\n", | |
| "0 Southern Asia 902 Developing regions 16 ... 2978 3436 3009 \n", | |
| "1 Southern Europe 901 Developed regions 1 ... 1450 1223 856 \n", | |
| "2 Northern Africa 902 Developing regions 80 ... 3616 3626 4807 \n", | |
| "3 Polynesia 902 Developing regions 0 ... 0 0 1 \n", | |
| "4 Southern Europe 901 Developed regions 0 ... 0 0 1 \n", | |
| "\n", | |
| " 2007 2008 2009 2010 2011 2012 2013 \n", | |
| "0 2652 2111 1746 1758 2203 2635 2004 \n", | |
| "1 702 560 716 561 539 620 603 \n", | |
| "2 3623 4005 5393 4752 4325 3774 4331 \n", | |
| "3 0 0 0 0 0 0 0 \n", | |
| "4 1 0 0 0 0 1 1 \n", | |
| "\n", | |
| "[5 rows x 43 columns]" | |
| ] | |
| }, | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df_can.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Let's find out how many entries there are in our dataset." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 5, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| }, | |
| "scrolled": true | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "(195, 43)\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# print the dimensions of the dataframe\n", | |
| "print(df_can.shape)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Clean up data. We will make some modifications to the original dataset to make it easier to create our visualizations. Refer to `Introduction to Matplotlib and Line Plots` lab for the rational and detailed description of the changes." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "#### 1. Clean up the dataset to remove columns that are not informative to us for visualization (eg. Type, AREA, REG)." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
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| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>OdName</th>\n", | |
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| " <th>2012</th>\n", | |
| " <th>2013</th>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>0</th>\n", | |
| " <td>Afghanistan</td>\n", | |
| " <td>Asia</td>\n", | |
| " <td>Southern Asia</td>\n", | |
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| " <td>2111</td>\n", | |
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| " <td>2004</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>Albania</td>\n", | |
| " <td>Europe</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
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| " <td>539</td>\n", | |
| " <td>620</td>\n", | |
| " <td>603</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>Algeria</td>\n", | |
| " <td>Africa</td>\n", | |
| " <td>Northern Africa</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>80</td>\n", | |
| " <td>67</td>\n", | |
| " <td>71</td>\n", | |
| " <td>69</td>\n", | |
| " <td>63</td>\n", | |
| " <td>44</td>\n", | |
| " <td>...</td>\n", | |
| " <td>3616</td>\n", | |
| " <td>3626</td>\n", | |
| " <td>4807</td>\n", | |
| " <td>3623</td>\n", | |
| " <td>4005</td>\n", | |
| " <td>5393</td>\n", | |
| " <td>4752</td>\n", | |
| " <td>4325</td>\n", | |
| " <td>3774</td>\n", | |
| " <td>4331</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>American Samoa</td>\n", | |
| " <td>Oceania</td>\n", | |
| " <td>Polynesia</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>Andorra</td>\n", | |
| " <td>Europe</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>5 rows × 38 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " OdName AreaName RegName DevName 1980 1981 \\\n", | |
| "0 Afghanistan Asia Southern Asia Developing regions 16 39 \n", | |
| "1 Albania Europe Southern Europe Developed regions 1 0 \n", | |
| "2 Algeria Africa Northern Africa Developing regions 80 67 \n", | |
| "3 American Samoa Oceania Polynesia Developing regions 0 1 \n", | |
| "4 Andorra Europe Southern Europe Developed regions 0 0 \n", | |
| "\n", | |
| " 1982 1983 1984 1985 ... 2004 2005 2006 2007 2008 2009 2010 \\\n", | |
| "0 39 47 71 340 ... 2978 3436 3009 2652 2111 1746 1758 \n", | |
| "1 0 0 0 0 ... 1450 1223 856 702 560 716 561 \n", | |
| "2 71 69 63 44 ... 3616 3626 4807 3623 4005 5393 4752 \n", | |
| "3 0 0 0 0 ... 0 0 1 0 0 0 0 \n", | |
| "4 0 0 0 0 ... 0 0 1 1 0 0 0 \n", | |
| "\n", | |
| " 2011 2012 2013 \n", | |
| "0 2203 2635 2004 \n", | |
| "1 539 620 603 \n", | |
| "2 4325 3774 4331 \n", | |
| "3 0 0 0 \n", | |
| "4 0 1 1 \n", | |
| "\n", | |
| "[5 rows x 38 columns]" | |
| ] | |
| }, | |
| "execution_count": 6, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df_can.drop(['AREA', 'REG', 'DEV', 'Type', 'Coverage'], axis=1, inplace=True)\n", | |
| "\n", | |
| "# let's view the first five elements and see how the dataframe was changed\n", | |
| "df_can.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Notice how the columns Type, Coverage, AREA, REG, and DEV got removed from the dataframe." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "#### 2. Rename some of the columns so that they make sense." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 7, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
| " vertical-align: middle;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe tbody tr th {\n", | |
| " vertical-align: top;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe thead th {\n", | |
| " text-align: right;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>Country</th>\n", | |
| " <th>Continent</th>\n", | |
| " <th>Region</th>\n", | |
| " <th>DevName</th>\n", | |
| " <th>1980</th>\n", | |
| " <th>1981</th>\n", | |
| " <th>1982</th>\n", | |
| " <th>1983</th>\n", | |
| " <th>1984</th>\n", | |
| " <th>1985</th>\n", | |
| " <th>...</th>\n", | |
| " <th>2004</th>\n", | |
| " <th>2005</th>\n", | |
| " <th>2006</th>\n", | |
| " <th>2007</th>\n", | |
| " <th>2008</th>\n", | |
| " <th>2009</th>\n", | |
| " <th>2010</th>\n", | |
| " <th>2011</th>\n", | |
| " <th>2012</th>\n", | |
| " <th>2013</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>0</th>\n", | |
| " <td>Afghanistan</td>\n", | |
| " <td>Asia</td>\n", | |
| " <td>Southern Asia</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>16</td>\n", | |
| " <td>39</td>\n", | |
| " <td>39</td>\n", | |
| " <td>47</td>\n", | |
| " <td>71</td>\n", | |
| " <td>340</td>\n", | |
| " <td>...</td>\n", | |
| " <td>2978</td>\n", | |
| " <td>3436</td>\n", | |
| " <td>3009</td>\n", | |
| " <td>2652</td>\n", | |
| " <td>2111</td>\n", | |
| " <td>1746</td>\n", | |
| " <td>1758</td>\n", | |
| " <td>2203</td>\n", | |
| " <td>2635</td>\n", | |
| " <td>2004</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>Albania</td>\n", | |
| " <td>Europe</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>1450</td>\n", | |
| " <td>1223</td>\n", | |
| " <td>856</td>\n", | |
| " <td>702</td>\n", | |
| " <td>560</td>\n", | |
| " <td>716</td>\n", | |
| " <td>561</td>\n", | |
| " <td>539</td>\n", | |
| " <td>620</td>\n", | |
| " <td>603</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>Algeria</td>\n", | |
| " <td>Africa</td>\n", | |
| " <td>Northern Africa</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>80</td>\n", | |
| " <td>67</td>\n", | |
| " <td>71</td>\n", | |
| " <td>69</td>\n", | |
| " <td>63</td>\n", | |
| " <td>44</td>\n", | |
| " <td>...</td>\n", | |
| " <td>3616</td>\n", | |
| " <td>3626</td>\n", | |
| " <td>4807</td>\n", | |
| " <td>3623</td>\n", | |
| " <td>4005</td>\n", | |
| " <td>5393</td>\n", | |
| " <td>4752</td>\n", | |
| " <td>4325</td>\n", | |
| " <td>3774</td>\n", | |
| " <td>4331</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>American Samoa</td>\n", | |
| " <td>Oceania</td>\n", | |
| " <td>Polynesia</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>Andorra</td>\n", | |
| " <td>Europe</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>5 rows × 38 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " Country Continent Region DevName 1980 1981 \\\n", | |
| "0 Afghanistan Asia Southern Asia Developing regions 16 39 \n", | |
| "1 Albania Europe Southern Europe Developed regions 1 0 \n", | |
| "2 Algeria Africa Northern Africa Developing regions 80 67 \n", | |
| "3 American Samoa Oceania Polynesia Developing regions 0 1 \n", | |
| "4 Andorra Europe Southern Europe Developed regions 0 0 \n", | |
| "\n", | |
| " 1982 1983 1984 1985 ... 2004 2005 2006 2007 2008 2009 2010 \\\n", | |
| "0 39 47 71 340 ... 2978 3436 3009 2652 2111 1746 1758 \n", | |
| "1 0 0 0 0 ... 1450 1223 856 702 560 716 561 \n", | |
| "2 71 69 63 44 ... 3616 3626 4807 3623 4005 5393 4752 \n", | |
| "3 0 0 0 0 ... 0 0 1 0 0 0 0 \n", | |
| "4 0 0 0 0 ... 0 0 1 1 0 0 0 \n", | |
| "\n", | |
| " 2011 2012 2013 \n", | |
| "0 2203 2635 2004 \n", | |
| "1 539 620 603 \n", | |
| "2 4325 3774 4331 \n", | |
| "3 0 0 0 \n", | |
| "4 0 1 1 \n", | |
| "\n", | |
| "[5 rows x 38 columns]" | |
| ] | |
| }, | |
| "execution_count": 7, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df_can.rename(columns={'OdName':'Country', 'AreaName':'Continent','RegName':'Region'}, inplace=True)\n", | |
| "\n", | |
| "# let's view the first five elements and see how the dataframe was changed\n", | |
| "df_can.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Notice how the column names now make much more sense, even to an outsider." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "#### 3. For consistency, ensure that all column labels of type string." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| }, | |
| "scrolled": true | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "False" | |
| ] | |
| }, | |
| "execution_count": 8, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# let's examine the types of the column labels\n", | |
| "all(isinstance(column, str) for column in df_can.columns)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Notice how the above line of code returned *False* when we tested if all the column labels are of type **string**. So let's change them all to **string** type." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "True" | |
| ] | |
| }, | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df_can.columns = list(map(str, df_can.columns))\n", | |
| "\n", | |
| "# let's check the column labels types now\n", | |
| "all(isinstance(column, str) for column in df_can.columns)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "#### 4. Set the country name as index - useful for quickly looking up countries using .loc method." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
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| "\n", | |
| " .dataframe tbody tr th {\n", | |
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| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>Continent</th>\n", | |
| " <th>Region</th>\n", | |
| " <th>DevName</th>\n", | |
| " <th>1980</th>\n", | |
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| " <th>1986</th>\n", | |
| " <th>...</th>\n", | |
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| " <th>2011</th>\n", | |
| " <th>2012</th>\n", | |
| " <th>2013</th>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Country</th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>Afghanistan</th>\n", | |
| " <td>Asia</td>\n", | |
| " <td>Southern Asia</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>16</td>\n", | |
| " <td>39</td>\n", | |
| " <td>39</td>\n", | |
| " <td>47</td>\n", | |
| " <td>71</td>\n", | |
| " <td>340</td>\n", | |
| " <td>496</td>\n", | |
| " <td>...</td>\n", | |
| " <td>2978</td>\n", | |
| " <td>3436</td>\n", | |
| " <td>3009</td>\n", | |
| " <td>2652</td>\n", | |
| " <td>2111</td>\n", | |
| " <td>1746</td>\n", | |
| " <td>1758</td>\n", | |
| " <td>2203</td>\n", | |
| " <td>2635</td>\n", | |
| " <td>2004</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Albania</th>\n", | |
| " <td>Europe</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>...</td>\n", | |
| " <td>1450</td>\n", | |
| " <td>1223</td>\n", | |
| " <td>856</td>\n", | |
| " <td>702</td>\n", | |
| " <td>560</td>\n", | |
| " <td>716</td>\n", | |
| " <td>561</td>\n", | |
| " <td>539</td>\n", | |
| " <td>620</td>\n", | |
| " <td>603</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Algeria</th>\n", | |
| " <td>Africa</td>\n", | |
| " <td>Northern Africa</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>80</td>\n", | |
| " <td>67</td>\n", | |
| " <td>71</td>\n", | |
| " <td>69</td>\n", | |
| " <td>63</td>\n", | |
| " <td>44</td>\n", | |
| " <td>69</td>\n", | |
| " <td>...</td>\n", | |
| " <td>3616</td>\n", | |
| " <td>3626</td>\n", | |
| " <td>4807</td>\n", | |
| " <td>3623</td>\n", | |
| " <td>4005</td>\n", | |
| " <td>5393</td>\n", | |
| " <td>4752</td>\n", | |
| " <td>4325</td>\n", | |
| " <td>3774</td>\n", | |
| " <td>4331</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>American Samoa</th>\n", | |
| " <td>Oceania</td>\n", | |
| " <td>Polynesia</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Andorra</th>\n", | |
| " <td>Europe</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>2</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>5 rows × 37 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " Continent Region DevName 1980 1981 \\\n", | |
| "Country \n", | |
| "Afghanistan Asia Southern Asia Developing regions 16 39 \n", | |
| "Albania Europe Southern Europe Developed regions 1 0 \n", | |
| "Algeria Africa Northern Africa Developing regions 80 67 \n", | |
| "American Samoa Oceania Polynesia Developing regions 0 1 \n", | |
| "Andorra Europe Southern Europe Developed regions 0 0 \n", | |
| "\n", | |
| " 1982 1983 1984 1985 1986 ... 2004 2005 2006 2007 \\\n", | |
| "Country ... \n", | |
| "Afghanistan 39 47 71 340 496 ... 2978 3436 3009 2652 \n", | |
| "Albania 0 0 0 0 1 ... 1450 1223 856 702 \n", | |
| "Algeria 71 69 63 44 69 ... 3616 3626 4807 3623 \n", | |
| "American Samoa 0 0 0 0 0 ... 0 0 1 0 \n", | |
| "Andorra 0 0 0 0 2 ... 0 0 1 1 \n", | |
| "\n", | |
| " 2008 2009 2010 2011 2012 2013 \n", | |
| "Country \n", | |
| "Afghanistan 2111 1746 1758 2203 2635 2004 \n", | |
| "Albania 560 716 561 539 620 603 \n", | |
| "Algeria 4005 5393 4752 4325 3774 4331 \n", | |
| "American Samoa 0 0 0 0 0 0 \n", | |
| "Andorra 0 0 0 0 1 1 \n", | |
| "\n", | |
| "[5 rows x 37 columns]" | |
| ] | |
| }, | |
| "execution_count": 10, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df_can.set_index('Country', inplace=True)\n", | |
| "\n", | |
| "# let's view the first five elements and see how the dataframe was changed\n", | |
| "df_can.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Notice how the country names now serve as indices." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "#### 5. Add total column." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
| " vertical-align: middle;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe tbody tr th {\n", | |
| " vertical-align: top;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe thead th {\n", | |
| " text-align: right;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>Continent</th>\n", | |
| " <th>Region</th>\n", | |
| " <th>DevName</th>\n", | |
| " <th>1980</th>\n", | |
| " <th>1981</th>\n", | |
| " <th>1982</th>\n", | |
| " <th>1983</th>\n", | |
| " <th>1984</th>\n", | |
| " <th>1985</th>\n", | |
| " <th>1986</th>\n", | |
| " <th>...</th>\n", | |
| " <th>2005</th>\n", | |
| " <th>2006</th>\n", | |
| " <th>2007</th>\n", | |
| " <th>2008</th>\n", | |
| " <th>2009</th>\n", | |
| " <th>2010</th>\n", | |
| " <th>2011</th>\n", | |
| " <th>2012</th>\n", | |
| " <th>2013</th>\n", | |
| " <th>Total</th>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Country</th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>Afghanistan</th>\n", | |
| " <td>Asia</td>\n", | |
| " <td>Southern Asia</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>16</td>\n", | |
| " <td>39</td>\n", | |
| " <td>39</td>\n", | |
| " <td>47</td>\n", | |
| " <td>71</td>\n", | |
| " <td>340</td>\n", | |
| " <td>496</td>\n", | |
| " <td>...</td>\n", | |
| " <td>3436</td>\n", | |
| " <td>3009</td>\n", | |
| " <td>2652</td>\n", | |
| " <td>2111</td>\n", | |
| " <td>1746</td>\n", | |
| " <td>1758</td>\n", | |
| " <td>2203</td>\n", | |
| " <td>2635</td>\n", | |
| " <td>2004</td>\n", | |
| " <td>58639</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Albania</th>\n", | |
| " <td>Europe</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>...</td>\n", | |
| " <td>1223</td>\n", | |
| " <td>856</td>\n", | |
| " <td>702</td>\n", | |
| " <td>560</td>\n", | |
| " <td>716</td>\n", | |
| " <td>561</td>\n", | |
| " <td>539</td>\n", | |
| " <td>620</td>\n", | |
| " <td>603</td>\n", | |
| " <td>15699</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Algeria</th>\n", | |
| " <td>Africa</td>\n", | |
| " <td>Northern Africa</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>80</td>\n", | |
| " <td>67</td>\n", | |
| " <td>71</td>\n", | |
| " <td>69</td>\n", | |
| " <td>63</td>\n", | |
| " <td>44</td>\n", | |
| " <td>69</td>\n", | |
| " <td>...</td>\n", | |
| " <td>3626</td>\n", | |
| " <td>4807</td>\n", | |
| " <td>3623</td>\n", | |
| " <td>4005</td>\n", | |
| " <td>5393</td>\n", | |
| " <td>4752</td>\n", | |
| " <td>4325</td>\n", | |
| " <td>3774</td>\n", | |
| " <td>4331</td>\n", | |
| " <td>69439</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>American Samoa</th>\n", | |
| " <td>Oceania</td>\n", | |
| " <td>Polynesia</td>\n", | |
| " <td>Developing regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>6</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Andorra</th>\n", | |
| " <td>Europe</td>\n", | |
| " <td>Southern Europe</td>\n", | |
| " <td>Developed regions</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>2</td>\n", | |
| " <td>...</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>0</td>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " <td>15</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>5 rows × 38 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " Continent Region DevName 1980 1981 \\\n", | |
| "Country \n", | |
| "Afghanistan Asia Southern Asia Developing regions 16 39 \n", | |
| "Albania Europe Southern Europe Developed regions 1 0 \n", | |
| "Algeria Africa Northern Africa Developing regions 80 67 \n", | |
| "American Samoa Oceania Polynesia Developing regions 0 1 \n", | |
| "Andorra Europe Southern Europe Developed regions 0 0 \n", | |
| "\n", | |
| " 1982 1983 1984 1985 1986 ... 2005 2006 2007 2008 \\\n", | |
| "Country ... \n", | |
| "Afghanistan 39 47 71 340 496 ... 3436 3009 2652 2111 \n", | |
| "Albania 0 0 0 0 1 ... 1223 856 702 560 \n", | |
| "Algeria 71 69 63 44 69 ... 3626 4807 3623 4005 \n", | |
| "American Samoa 0 0 0 0 0 ... 0 1 0 0 \n", | |
| "Andorra 0 0 0 0 2 ... 0 1 1 0 \n", | |
| "\n", | |
| " 2009 2010 2011 2012 2013 Total \n", | |
| "Country \n", | |
| "Afghanistan 1746 1758 2203 2635 2004 58639 \n", | |
| "Albania 716 561 539 620 603 15699 \n", | |
| "Algeria 5393 4752 4325 3774 4331 69439 \n", | |
| "American Samoa 0 0 0 0 0 6 \n", | |
| "Andorra 0 0 0 1 1 15 \n", | |
| "\n", | |
| "[5 rows x 38 columns]" | |
| ] | |
| }, | |
| "execution_count": 11, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df_can['Total'] = df_can.sum(axis=1)\n", | |
| "\n", | |
| "# let's view the first five elements and see how the dataframe was changed\n", | |
| "df_can.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Now the dataframe has an extra column that presents the total number of immigrants from each country in the dataset from 1980 - 2013. So if we print the dimension of the data, we get:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| }, | |
| "scrolled": true | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "data dimensions: (195, 38)\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "print ('data dimensions:', df_can.shape)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "So now our dataframe has 38 columns instead of 37 columns that we had before." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 12, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "['1980',\n", | |
| " '1981',\n", | |
| " '1982',\n", | |
| " '1983',\n", | |
| " '1984',\n", | |
| " '1985',\n", | |
| " '1986',\n", | |
| " '1987',\n", | |
| " '1988',\n", | |
| " '1989',\n", | |
| " '1990',\n", | |
| " '1991',\n", | |
| " '1992',\n", | |
| " '1993',\n", | |
| " '1994',\n", | |
| " '1995',\n", | |
| " '1996',\n", | |
| " '1997',\n", | |
| " '1998',\n", | |
| " '1999',\n", | |
| " '2000',\n", | |
| " '2001',\n", | |
| " '2002',\n", | |
| " '2003',\n", | |
| " '2004',\n", | |
| " '2005',\n", | |
| " '2006',\n", | |
| " '2007',\n", | |
| " '2008',\n", | |
| " '2009',\n", | |
| " '2010',\n", | |
| " '2011',\n", | |
| " '2012',\n", | |
| " '2013']" | |
| ] | |
| }, | |
| "execution_count": 12, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# finally, let's create a list of years from 1980 - 2013\n", | |
| "# this will come in handy when we start plotting the data\n", | |
| "years = list(map(str, range(1980, 2014)))\n", | |
| "\n", | |
| "years" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "# Visualizing Data using Matplotlib<a id=\"4\"></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Import `Matplotlib` and **Numpy**." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 13, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Matplotlib version: 3.3.4\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# use the inline backend to generate the plots within the browser\n", | |
| "%matplotlib inline \n", | |
| "\n", | |
| "import matplotlib as mpl\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "mpl.style.use('ggplot') # optional: for ggplot-like style\n", | |
| "\n", | |
| "# check for latest version of Matplotlib\n", | |
| "print ('Matplotlib version: ', mpl.__version__) # >= 2.0.0" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "# Area Plots<a id=\"6\"></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "In the last module, we created a line plot that visualized the top 5 countries that contribued the most immigrants to Canada from 1980 to 2013. With a little modification to the code, we can visualize this plot as a cumulative plot, also knows as a **Stacked Line Plot** or **Area plot**." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 14, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
| " vertical-align: middle;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe tbody tr th {\n", | |
| " vertical-align: top;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe thead th {\n", | |
| " text-align: right;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th>Country</th>\n", | |
| " <th>India</th>\n", | |
| " <th>China</th>\n", | |
| " <th>United Kingdom of Great Britain and Northern Ireland</th>\n", | |
| " <th>Philippines</th>\n", | |
| " <th>Pakistan</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>1980</th>\n", | |
| " <td>8880</td>\n", | |
| " <td>5123</td>\n", | |
| " <td>22045</td>\n", | |
| " <td>6051</td>\n", | |
| " <td>978</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1981</th>\n", | |
| " <td>8670</td>\n", | |
| " <td>6682</td>\n", | |
| " <td>24796</td>\n", | |
| " <td>5921</td>\n", | |
| " <td>972</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1982</th>\n", | |
| " <td>8147</td>\n", | |
| " <td>3308</td>\n", | |
| " <td>20620</td>\n", | |
| " <td>5249</td>\n", | |
| " <td>1201</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1983</th>\n", | |
| " <td>7338</td>\n", | |
| " <td>1863</td>\n", | |
| " <td>10015</td>\n", | |
| " <td>4562</td>\n", | |
| " <td>900</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1984</th>\n", | |
| " <td>5704</td>\n", | |
| " <td>1527</td>\n", | |
| " <td>10170</td>\n", | |
| " <td>3801</td>\n", | |
| " <td>668</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| "Country India China United Kingdom of Great Britain and Northern Ireland \\\n", | |
| "1980 8880 5123 22045 \n", | |
| "1981 8670 6682 24796 \n", | |
| "1982 8147 3308 20620 \n", | |
| "1983 7338 1863 10015 \n", | |
| "1984 5704 1527 10170 \n", | |
| "\n", | |
| "Country Philippines Pakistan \n", | |
| "1980 6051 978 \n", | |
| "1981 5921 972 \n", | |
| "1982 5249 1201 \n", | |
| "1983 4562 900 \n", | |
| "1984 3801 668 " | |
| ] | |
| }, | |
| "execution_count": 14, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df_can.sort_values(['Total'], ascending=False, axis=0, inplace=True)\n", | |
| "\n", | |
| "# get the top 5 entries\n", | |
| "df_top5 = df_can.head()\n", | |
| "\n", | |
| "# transpose the dataframe\n", | |
| "df_top5 = df_top5[years].transpose() \n", | |
| "\n", | |
| "df_top5.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Area plots are stacked by default. And to produce a stacked area plot, each column must be either all positive or all negative values (any NaN values will defaulted to 0). To produce an unstacked plot, pass `stacked=False`. " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 15, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 1440x720 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "df_top5.index = df_top5.index.map(int) # let's change the index values of df_top5 to type integer for plotting\n", | |
| "df_top5.plot(kind='area', \n", | |
| " stacked=False,\n", | |
| " figsize=(20, 10), # pass a tuple (x, y) size\n", | |
| " )\n", | |
| "\n", | |
| "plt.title('Immigration Trend of Top 5 Countries')\n", | |
| "plt.ylabel('Number of Immigrants')\n", | |
| "plt.xlabel('Years')\n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "The unstacked plot has a default transparency (alpha value) at 0.5. We can modify this value by passing in the `alpha` parameter." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 16, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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nn32W3XbbjZNOOokbb7yRqVOnMnPmTFKpFL/5zW8wDIOdd955yG0VQgghSoEEooQQQggxKD/+8Y9xHIfTTjsNXdc57bTTeoev3xRd13nkkUe44IIL2Hvvvdluu+24/vrr+d73vtdnuptvvpmLL76YHXbYAc/z+u3etdVWW/HUU0/x3e9+l09+8pPE43GOO+64TQY9Rsvhhx/Os88+yw9/+EMOPvhgoihi22235eijj96o2+OmnHzyydx888385Cc/4fLLL+eggw7ixz/+MV/5ylc2Od91112HrutcdNFFtLS0MGPGDB588EGOPPLILdyyj/z85z/nsssu48tf/jKZTIa99tqL//u//2PXXXftM90NN9zAf//3f/PVr36VKVOm8Ktf/YpPfvKTAy43CAKuuOIKVq5ciWVZzJgxg9tvv52zzz57k+3Zdtttee2117jhhhv4wQ9+wIoVK6iqqmK33XbjsssuY8899wQGt29uuukmvv71r3P00UdTXV3NFVdcQUtLy5D30aWXXsqbb77Jxz/+cfL5PPPnz2f77bcf1LyJRILnnnuO73//+8ydO5eWlhYmTZrEfvvtxzHHHANAVVUVt9xyCx988EFvV75HH32UXXbZZchtFUIIIUqBpobTiV8IIYQQAjjiiCOora3l0UcfLXZTRBEsW7aMHXbYgeeff36zBdaFEEIIIUAyooQQQggxSG+++SavvfYaBxxwAJ7n8cADDzB//nyefPLJYjdNCCGEEEKUCQlECSGEEGJQNE3jnnvu4YILLiCKInbddVcee+wxjj322GI3TQghhBBClAnpmieEEEIIIYQQQgghxoRe7AYIIYQQQgghhBBCiIlBAlFCCCGEEEIIIYQQYkxIIEoIIYQQQgghhBBCjIkJX6x8zZo1xW7CiGhoaKC1tbXYzRDjnBxnYrTJMSbGghxnYizIcSZGmxxjYizIcSaGa+rUqQN+JhlRQgghhBBCCCGEEGJMSCBKCCGEEEIIIYQQQowJCUQJIYQQQgghhBBCiDEx4WtEbUgpheM4RFGEpmnFbs6gNTU14bpusZshxjk5zkqPUgpd10kkEmV1zhJCCCGEEEJMTBKI2oDjOFiWhWmW164xTRPDMIrdDDHOyXFWmoIgwHEckslksZsihBBCCCGEEJskXfM2EEVR2QWhhBATm2maRFFU7GYIIYQQQgghxGZJIGoD0rVFCFGO5NwlhBBCCCGEKAcSiBJiEJqbm/nmN7/JgQceyGGHHcYZZ5zB4sWLR2z5CxYsYOHChSO2PCGEEEIIIYQQohRJHzQhNkMpxdlnn80pp5zCPffcA8CiRYtobW1lxx13HJF1vPjii6TTaT75yU9u9FkQBNJdVAghhBBCCCHEuCB3t0Jsxj/+8Q8sy+LMM8/sfW/PPfdEKcW1117L/Pnz0TSNCy64gBNPPJEFCxZw7733cv/99wNw5ZVXsvfee/OFL3yBWbNmccoppzBv3jyCIOC//uu/iMfjPPDAAxiGwaOPPsqPfvQjfvOb31BTU8OiRYvYY489ePrpp/njH/9IfX09URRx8MEH86c//Ym6urpi7RYhhBBCCCGEEGLIJBAlxGa899577LXXXhu9/+STT/LWW28xb9482tvbOe6449h///03u7y6ujr++te/8stf/pJ7772Xm266iTPOOIN0Os03vvENAH7zm9+wZMkSHn74YQzDoLq6mt///vd8/etf5/nnn2f33XeXIJQQQgghhBBCiLIjNaKEGKZXXnmFk046CcMwmDRpEvvvvz9vvPHGZuc79thjAdh7771ZuXLlgNOdcMIJGIYBwBe+8AV+97vfAfC///u/nHrqqSOwBUIIIYQQQgghxNiSQJQQm7Hzzjvz5ptvbvS+Uqrf6U3T7POZ67p9Po/H4wAYhkEYhgOuN5VK9f572rRpTJo0iRdeeIF//etfHHHEEUPaBiGEEEIIIYQQohRIIEqIzfjUpz6F53k89NBDve+9/vrr1NTU8Mc//pEwDGlra+Pll19m5syZTJs2jffffx/XdclkMrzwwgubXUc6nSaXy21ymi996UtccMEFfPrTn+7NlBJCCCGEEEIIIcqJBKKE2AxN0/j5z3/O3//+dw488EAOP/xwbr75Zk466SR222035syZw6mnnsqVV17J5MmTmTZtGp/+9KeZPXs23/72t9lzzz03u445c+bwl7/8hTlz5vDyyy/3O81RRx1FPp/nC1/4wkhvohBCCCGEEEIIMSY0NVD/oglizZo1fV4XCoU+XaLKhWmaBEFQ7GaIUfTGG2/wgx/8gMcee6xobZDjrHSV67lrQw0NDbS2tha7GWKck+NMjAU5zsRok2NMjAU5zsRwTZ06dcDPZNQ8IcrAnXfeyf3338+dd95Z7KYIIYQQQgghhBDDJl3zhCgD3/72t3nllVfYb7/9it0UIYQQQgghhBBi2CQQJYQQQgghhBBCCCHGhASihBBCCCGEEEIIIcSYkECUEEIIIYQQQgghhBgTEogSQgghhBBCCCGEEGNCAlElaKeddhrS9AsWLOD0008H4KmnnpKR1YQQQgghhBBCCFGSzGI3oNRFq5aBnR+5BSbT6NtsP3LL28BRRx3FUUcdNWrLF0IIIYQQQhSXH0as6rSJKYWuacVujhBCDIkEojbHzqNF0YgtTg0hqLVgwQJuueUWamtree+999h777356U9/iqZpzJ8/n6uvvpq6ujr22muv3nkefvhh/v3vf3Pdddfx1FNPcccdd+B5HrW1tdx5551MmjRpxLZFCCGEEEIIMfaa8wGd2QJbxwLqUlaxmyOEEEMiXfNK3KJFi/jhD3/I3/72N5YvX87ChQtxHIfLLruMX/7ylzz22GM0Nzf3O+9+++3Hn/70J5566ilOPPFE7r777jFuvRBCCCGEEGIkhZGi0wlYm7FZ0eUVuzlCCDFkkhFV4mbOnMnUqVMB2GOPPVi5ciWpVIptt92Wj33sYwB87nOf46GHHtpo3rVr1/LNb36T5uZmPM9j2223HdO2CyGEEEIIIUZWux1geyGg05TzgHSxmySEEEMiGVElLhaL9f7bMAyCIABAG0Rf8Kuuuoq5c+fyzDPP8OMf/xjXdUetnUIIIYQQQojRpZSi3Q7I+REN6Rg5N8QJwmI3SwghhkQCUWVoxowZrFixgmXLlgHw+OOP9ztdJpNhypQpADzyyCNj1DohhBBCCCHEaMh6EbYfoQMVcZMIaM75xW6WEEIMiQSiylAikeAnP/kJZ555JieddBLbbLNNv9NdeumlnHvuuZx88snU1dWNcSuFEEIIIYQQI6m94JNxAiriOjFTJ2lprJI6UUKIMqMppVSxG1FMa9as6fO6UCiQSqV6X0erlsEQRrrbrGQafZvtR25565im2dttT4jRIsdZ6drw3FWuGhoaaG1tLXYzxDgnx5kYC3KciZHmBhHvtdq0FXwa0hbV1dUsXtNKzo04ftda9EGU7hBiqORcJoarp9Z1f6RY+WaMRtBICCGEEEIIIYai3Q7IeSFpy+h9L2nptBYCMk5ITVJu7YQQ5UG65gkhhBBCCCFECQsjRYcd4AaKZOyjW7iEqaNrsCYrgxIJIcqHBKKEEEIIIYQQooR1OgG2H7JeMhQAhq5RETNYk5WC5UKI8iGBKCGEEEIIIYQoYe12QMYNqYwbG32WtHQyboAXREVomRBCDJ0EooQQQgghhBCiROXckIIXoWtavwXJU5ZOGEFrQbKihBDlQQJRQgghhBBCCFGi2uyAjBtQEev/1i1maMQNjVVdUidKCFEeJBBVopqbm/nmN7/JgQceyGGHHcYZZ5zBgw8+yJlnntnv9BdffDHvv//+GLdSCCGEEEIIMVq8MCLjBAQRxMz+b900TSMdN2gtBCilxriFQggxdDLG52Ys63TIe+GILS8dM9i+JrHJaZRSnH322Zxyyincc889ACxatIh58+YNOM+tt95KEAQj1k4hhBBCCCFEcbUXAvJeRNLadP5AytTpWDdtRT91pIQQopRIRtRm5L2QSDFi/w0mqPWPf/wDy7L6ZD/tueeezJo1i0KhwNe//nUOOeQQvv3tb/c+9Tj55JN54403ANhpp5244YYbmD17NieccAItLS0APPXUU5xwwgkcddRRfOELX+h9XwghhBBCCFFaIqXosAOcMCQ9QLe8HglLRwPW5qR7nhCi9EkgqgS999577LXXXv1+tmjRIn74wx/yt7/9jeXLl7Nw4cKNpikUCvzHf/wHTz/9NPvvvz8PPfQQAPvttx9/+tOfeOqppzjxxBO5++67R3U7hBBCCCGEEMPT5YTYQYTRT4HyDZm6RiqmszojBcuFEKVPuuaVmZkzZzJ16lQA9thjD1auXMl+++3XZ5pYLMacOXMA2GuvvXj++ecBWLt2Ld/85jdpbm7G8zy23XbbsW28EEIIIYQQYlBaCz4ZJ6Q2NbiudinLoMMJCCOFoW8+eCWEEMUiGVElaOedd+bNN9/s97NYLNb7b8Mw+q0LZZom2ronJ+tPc9VVVzF37lyeeeYZfvzjH+O6krorhBBCCCFEqcl7IQUvAhT6IDKiAJKWjh8q2m2pGyuEKG0SiCpBn/rUp/A8r7dLHcDrr7/OSy+9tEXLzWQyTJkyBYBHHnlki5YlhBBCCCGEGB1tdkDWC4dUeDxualiGxqouedgshChtEogqQZqm8fOf/5y///3vHHjggRx++OHcfPPNbLXVVlu03EsvvZRzzz2Xk08+mbq6uhFqrRBCCCGEEGKk+KEi44T4YUTcHPztmq5pVMR0mnJSJ0oIUdo01TPs2gS1Zs2aPq8LhQKpVKr39bJOZ1Aj3Q1WOmawfU1ixJbXwzTNfrvpCTGS5DgrXRueu8pVQ0MDra2txW6GGOfkOBNjQY4zMVxNOY9lHQ5hBJWJgTOiqqur6erq6vNexg1Zm/E4fpdaktbgs6mEGIicy8Rw9dS27o8UK9+M0QgaCSGEEEIIIcSGItVd46kQKOqTQw8kJc3uelKNWZ8d6iQQJYQoTdI1TwghhBBCCCFKQMYNcfwIQ6N38KGhsAydhKWxOuuNQuuEEGJkSCBKCCGEEEIIIUpAeyGg0w2pjA3/Ni0dM2gv+EQTuwKLEKKESSBKCCGEEEIIIYqs4IfkvBBNKUxj+LdpKVPHDRVdjtT1FEKUJglECSGEEEIIIUSRtRcCsm5AeguLjCcsHVOHVRnpnieEKE0SiBJCCCGEEEKIIgoiRZcT4oWKxBZ0ywPQNY10zKBR6kQJIUrUmAaioijiu9/9LjfccAMAuVyOa6+9lgsuuIBrr72WXC7XO+1jjz3G+eefz4UXXsjrr7/e+/6SJUu49NJLOf/88/nFL36BWtf32fd9br31Vs4//3yuuOIKmpubx3LTRszKlSs54ogj+rx38803c++9925yvtdff52rrroKgAULFrBw4cIhr3vWrFm0t7dv8v1///vf7L///ixatIinnnqKO++8c8jr6c+CBQs488wzR2RZg/Hhhx8yZ84cjjrqKJYtW9bns3w+z+WXX86BBx7IUUcdxTHHHMNDDz00Iuvt6uril7/85YCfT58+nTlz5jB79myOPvroTf4dP/OZzwDdx8xjjz222XU3Njby9a9/fcht3hKf//zneeONN/p9/9hjj+19/cYbb/D5z39+SMvecLsffvhhrrzyyuE3dpCGc6yOZNsGcz4QQgghRHnpsAPyfkDMHHqB8v4kLZ2sG+IF4YgsTwghRtKYBqKefPJJpk2b1vv68ccfZ6+99uKOO+5gr7324vHHHwdg1apVLFiwgFtuuYUrr7yS++67jyiKAPjZz37Gueeeyx133EFjY2NvkOrZZ58lnU7z05/+lOOPP37EAgeZzoC2Fn/E/st0jk5f7ZkzZ3LttdcC8OKLL/LPf/5zxNfx9ttvc84553DPPfew5557ctRRR/Htb397xNczFv7yl79w9NFH89RTT7H99tv3+ew73/kO1dXVvPDCCzz11FM89NBDdHZ2brSMMBz6D3smk+H+++8f8PNEIsG8efN4+umn+c///M/eoG1/6/3jH/8IDD4QNWXKFH72s58Nuc2jpbW1lWeffXZY8wZBMOjtHqzh/D3XFwRSh0EIIYQQQ6eUot0OyHuKytiWdcvrkTR1QgXNeX9ElieEECPJHKsVtbW18dprr/HZz36W//u//wNg4cKF/OAHPwDg0EMP5Qc/+AFf/vKXWbhwIQceeCCWZTF58mSmTJnChx9+yKRJk7Btm5133hmAQw45hIULF7LPPvvw6quvcsoppwCw//7792ZLDWfY0/X5vmIkB5zw/S1b2Oc//3n22WcfFixYQFdXFzfffDOzZs3iH//4B3fddRfXXXcdDzzwAIZh8Oijj/KjH/2IGTNmcPnll7N69WoAfvjDH/LJT36S9vZ2zjvvPNra2pg5c2Zvdll/PvjgAy666CLuuOMO9tlnH6A7y+Pf//431113HRdddBGVlZW88cYbtLS0cOWVV3LCCScQRRFXXnklL730EtOnT0cpxRe+8AVOOOEE5s+fz9VXX01dXR177bVX77o6Ojq49NJLWbFiBYlEgp/85Cfsvvvu3HzzzaxYsYLm5maWLFnC1VdfzWuvvcb8+fOZMmUKv/zlL7Esq0+7Fy1axOWXX47jOGy33XbcfPPN/POf/+TnP/85hmHw0ksv8bvf/a53+mXLlvH6669z1113oevdcdr6+nrOO+88gN4A6VZbbcVbb73FM888w/XXX8+LL76I53mcddZZnHHGGeTzeebOnUtXVxdBEPDd736Xo48+muuvv57ly5czZ84cDjnkkN4stv5ks1mqq6v7Xe/f/vY3dtppJz744AOuv/763gyvU045hWOPPZYLLriAQqEAwI9+9CM++clPsnLlSs466yyeffZZHn74YebNm4dt2yxbtoxjjz2W73//+xu14dZbb2XevHk4jsO+++7LzTffvMnj0LZtLrnkEj744ANmzJiB4zgDbt83v/lNbr/99o0yAB3H4T//8z/597//jWEYXH311Rx00EE8/PDDPPPMM7iuS6FQwLbtPttdXV1NU1MTp59++kbb9Nxzz3HTTTfheR7bbbcdt956K+l0mlmzZvHFL36R5557jrlz53L99ddzyimnMG/ePIIg4L/+67+YMWPGgNtw880309TUxMqVK6mrq+Oaa67p97u2vqeeeoo77rgDz/Oora3lzjvvZNKkSdx8882sXr2aFStWsHr1ar72ta9x9tlnA3D77bfzu9/9jqlTp1JfX8/ee+89YJuEEEIIUV6ybkjBizA0tvjepUfc1EmYGqu6PLapTozIMoUQYqSMWSDql7/8JV/+8pexbbv3va6uLmprawGora0lk8kA0N7ezk477dQ7XV1dHe3t7RiGQX19fe/79fX1vV3G2tvbez8zDINUKkU2m6WqqmrUt22sBUHAE088wTPPPMMtt9zCww8/3PvZ9OnTOeOMM0in03zjG98A4LzzzuPrX/86++23H6tXr+a0007jueee49Zbb2W//fbj4osv5umnn95kFtlXv/pV7rjjDvbbb78Bp2lqauLxxx/nww8/ZO7cuZxwwgk8+eSTrFq1imeeeYbW1lYOO+wwvvCFL+A4Dpdddhm//e1v2WGHHXrbCt0393vuuSe/+MUveOGFF7jwwguZN28eAMuXL+eRRx7h/fff5zOf+Qw/+9nP+P73v8/ZZ5/NM888wzHHHNOnTRdddBHXXnstBxxwADfeeCO33HIL11xzzUb7qMf777/P7rvv3huE6s/rr7/Os88+y7bbbsuDDz5IZWUlTz75JK7rctJJJ3HooYcydepU7rvvPiorK2lvb+fTn/40Rx11FFdccQXvvfde7/ZsyHEc5syZg+u6NDc389vf/rbf9a7viiuu4N577+3NtLJtm9/85jckEgmWLFnCeeedx5///OeN1vXWW2/x17/+lVgsxiGHHMLcuXP7ZCwCfOUrX+Hiiy8G4Pzzz+epp57iyCOPBPo/Du+//36SySRPP/00b7/99kZ/j/V94hOf4M9//jP/+Mc/qKio6H2/p+viM888w4cffsiXvvQlnn/+eQD++c9/8vTTT1NbW8uCBQv6bPfDDz/c7zYlk0luv/12Hn74YVKpFHfddRf//d//3btd8Xi8Nxvz+uuvp66ujr/+9a/88pe/5N577+Wmm24acBugu7vqY489RjKZHPC7tr799tuPP/3pT2iaxq9//Wvuvvturr76aqC7y+gjjzxCPp/n4IMP5swzz+Sdd97hj3/8I0899RRBEHDMMcdIIEoIIYQYR9rsgKznUxEfmWyoHumYQZsdjMjDeSGEGEljEoj65z//SXV1NR/72Md46623Njv9QJk5m8rY6e+z/k64Tz/9NE8//TQAN9xwAw0NDX0+b2pqwjQ/2i2GEY1oRpSm0Wf5G+r5bP1pdF3HMAxM00TTND796U9jmib77LMPq1at6p1W0zRM00TXdXRd733/+eef54MPPuhdXi6Xw3EcXn75ZX7xi19gmibHHHMMNTU1vevp22aNQw45hP/93/9l9uzZGEb3j6RhGL3r0XWd4447jlgsxu67705LSwumafLqq6/ymc98hlgsxtSpUznooIMwDINly5ax3Xbb9Wa3nXLKKTzwwAOYpsnChQu57777ME2Tww47jIsvvphCoYCu6xx55JEkk0n22msvoihizpw5aJrG7rvvzurVq/u0PZPJkMlkOPjggwH40pe+xNe+9rV+99H6+7pnP0J3RtCf/vQnWltbezN09tlnHz72sY/17tu3336bJ598snedK1asYPr06fzkJz/hxRdfRNd1Ghsb6ejo6N13Ax0DiUSC+fPnA90ZgxdddBHPPffcRutd/3gxDKNPm5VSXH755SxatAjDMFiyZEnvdOvPc/DBB1NXVwfALrvsQmNjI9ttt12f5b/88svceeed2LZNZ2cnu+22G0cfffSAx+Err7zSu4/33ntvdt999wGPKcMwuOSSS7jtttu46qqrerfh1Vdf5eyzz8Y0TXbddVemT5/O8uXLMQyDww47jEmTJvUef+tv90Db1NXVxQcffMBJJ50EdNeT+8QnPtH7fTr55JP7fIfW366//OUvG7V9/fXqus4xxxxDZWVl7/HQ33dt/e9Kc3Mz3/rWt2hqasL3fbbddtveZc2ZM4d0Ok06nWbSpEl0dHSwcOFCjjvuuN51HH300f0eu/F4fKPzWTkyTXNcbIcobXKcibEgx5kYDNsP0e0s6cCioTI+pHkNw+jNnu+PHg9Y0W4Tq6imOhnb0qaKCUrOZWI0jEkg6r333uPVV1/lX//6F57nYds2d9xxB9XV1XR0dFBbW0tHR0dv9lJ9fT1tbW2987e3t1NXV7fR+21tbb03nT2f1dfXE4YhhUKhT5ZFj9mzZzN79uze162trX0+d12394YduuvGjHQgalO1ZKqqqnq7c/Vob29n2rRpBEH3Ew3DMHo/D4Kg999KKYIgIIoioijqfT+KIv7whz+QTCb7rEsp1Wc66N7eDdunlOLaa6/l8ssv57LLLuMnP/lJ77Q980dRhGmam22LUqrPOtZv4/rzrD9NzzxRFGFZVu/7pmn2qevj+36ftvfsr/XXNVC7euy444689dZbeJ6Hruucf/75nH/++ey0004EQUAYhiSTyT7tvvbaaznssMP6LOfhhx+mpaWFP//5z1iWxaxZs8jn833aNpCez/bZZx/a2tpoamraaL3rT9t9jH60nffccw/19fXMmzePKIr42Mc+1jvd+vOsvy81TcN13T7LdxyH733ve7213W6++ebeaQY6Djc8pjb8e/foef+AAw7ghhtuYOHChZv9+4dhSCKR6H1/w+3e1DYdfPDB3H333RvtO6UU8Xi8z7oG+n71WH+9URSRTqc3+11b/7tyxRVXcM4553DUUUf1drnsWdb67dd1Hdd1+3w3etbR37Hruu5G57Ny1NDQMC62Q5Q2Oc7EWJDjTAzG6ozHqg4HS9foigYuadCf6upqurq6Bvw8jBT5gsOiZY3sMim1pU0VE5Scy8RwTZ06dcDPxqRY+Wmnnca9997LXXfdxUUXXcSee+7JBRdcwL777tvbbeW5557rraWy7777smDBAnzfp7m5mbVr1zJjxgxqa2tJJpO8//77KKX4+9//zr777gt0d/P529/+BsBLL73EHnvsUZYpqOl0msmTJ/d2Rero6GD+/Pmb7BLX3zLWH4Hw0EMP7TNS26JFi4DuWlq///3vge5i7/0V5O6h6zp33XUXS5Ys4cYbbxx0Wz75yU/yxBNPEEURLS0tvPjiiwDMmDGDFStW9I5Y19M1asN2LViwgLq6ut5skKGoqqqiurqal19+GYBHH32U/ffff5Pz7LDDDuy99978+Mc/7g3cOI4zYDbeoYceyv3334/vdxeCXLx4MYVCgWw2S0NDA5Zl8Y9//INVq1YBG/9tNuXDDz8kDMPe7qsDqaio6BPkymQyTJ48GV3XefTRR4ddhNt1XaC7a2w+n+eJJ57Y7DyzZs3qLSD+7rvv8s4772x2ngsuuKBPkGj9ZSxevJjVq1ez4447bjTfhts9kE984hMsXLiQpUuXAt1dFxcvXrzZ+YZjoO/a+jKZDFOmTAHgkUce2ewy999/f/7yl79g2za5XG7Abp1CCCGEKC9hpOh0ArxQkYyN/G2ZoWtUxg3WZL0RX7YQQmyJMasR1Z+TTjqJW2+9lWeffZaGhgYuueQSoLvO0QEHHMAll1yCruucffbZvTV7vva1r3H33XfjeR4zZ87sLZx9xBFHcOedd3L++edTUVHBRRddVKzN2mK33347V1xxBddccw0Al1xyyUYju23KnDlzOPfcc/nrX//Kj370I6699lquuOIKZs+eTRAEzJo1ix//+MdcfPHFnHfeeRx99NHsv//+G9UH2lA8HucXv/gFn/vc55g0adJGWR/9Of7443nhhRc44ogj+NjHPsY+++xDVVVVbxHyM888k7q6Ovbbbz/efffd3u295JJLmD17NolEgttuu23Q276h2267rbdY+bbbbsstt9yy2Xluuukmrr32Wg466CBqampIJBJceeWV/U572mmnsXLlSo455hiUUtTV1fGLX/yCz372s5x11lkce+yx7LHHHr0Fr+vq6vjkJz/JEUccweGHH75RsfKeGlHQnZ1z22239cnQ689uu+2GYRjMnj2bU089lbPOOotzzjmH//u//+Oggw4ilRreE7Dq6mpOO+00Zs+ezTbbbMPHP/7xzc5z5pln9v7tdt99d2bOnLnZeY488sg+td/OOussLr/8co488kgMw+DWW28lHt84VX3D7R4oNb2+vp5bb72V8847D8/rvhD77ne/229wa0sN9F1b36WXXsq5557LlClT+I//+A9Wrly5yWXutddevTXGttlmG2bNmjXi7RZCCCHE2OtwAmwvxNJH7+F5wtJpLwQEkcIcxfUIIcRQaGpThZcmgDVr1vR5XSgU+ty4ZzqDLR7pbn2WpVFVM/Lxv/W7xZWafD5POp2mvb2dE044gccff5zJkycXu1liGEr5OJvoNjx3lStJ/xZjQY4zMRbkOBObopTi/TaHtRmX2pSJPoyeHJvrmgfgBBHLOlwO2b6KrSqkTpQYOjmXieHaVNe8omZElYPRCBpNNGeddRZdXV34vs+FF14oQSghhBBCCDGh5bwI24/QNG1YQajBihsaMUNjZZcrgSghRMmQKIsYdb/73e+K3QQhhBBCCCFKRlvBJ+MGVMRHt2SvpmmkYwYtecloF0KUjjEpVi6EEEIIIYQQAtwgIuOGhJEiZoz+7VjK0sl7IXlveAPYCCHESJNAlBBCCCHGlOtEZDrlhkgIMTG12wEFLyJpbXpAmpGStLpv+Rpl9DwhRImQQJQQQgghxoxSinwuoqPdx/eiYjdHCCHGVBgpOuyAQhCRjo3NrZipa6RiOqszEogSQpQGCUQJIYQQYsy4jiLwFXY+opCTrCghxMTS6QTYfsgYJUP1Slk6HU5AGE3oAdOFECVCAlElaPr06cyZM4cjjjiCc845B9u2WblyJUcccUS/0994440899xzAHz+85/njTfeAOCMM87Y7JCuA7n//vt55JFHhrcBQgghxACcQoTnRMTiGpmsZEQJISaWdjsg60VUxcc2EpW0dLxQ0elI0XIhRPHJqHmb0draiuu6I7a8eDxOQ0PDJqdJJBLMmzcPgG9/+9vcf//9HHfccQNOf9lll2GaJkHQ94flgQceGHY7zzzzzGHPK4QQQvTHcyN8X4GmEYvruI5CRQpNH72hy4UQolTkvJCCF4FS6NrYnvcSpo6pa6zq8qhPWWO6biGE2JBkRG2G67oopUbsv6EGtfbbbz+WLVsGQBiGXHbZZRx++OF86UtfwrZtAC666CL+9Kc/bTTvrFmzaG9vZ+XKlRxyyCFceOGFzJ49m69//eu9886aNYvrrruO448/nuOPP56lS5cCcPPNN3PvvfcC3VlWPdN86lOf4uWXX+5tz7XXXstxxx3H7NmzewNfTU1NfPazn+3N6uqZXgghxMRmFyJcR2HFFaapEQUKx5asKCHExNBeCMi4IZXxsb8F0zWNiphOc17qRAkhik8CUSUsCALmz5/PrrvuCsDSpUs566yzmD9/PlVVVTz55JODXtbixYv58pe/zNNPP01lZSW/+tWvej+rqKjgiSee4Ctf+QpXX331gG154okn+OEPf8gtt9wCwG9+8xsqKyt58skneeKJJ/j1r3/NihUreOyxxzj00EOZN28e8+bNY4899tiCvSCEEGI8CHyF53U/lDEMHcMETYecdM8TQkwAXhiRcUOCSBEzx7hA1DpJSyfjhLiB1OcTQhSXBKJKkOM4zJkzh2OPPZZp06bxpS99CeiuHbXnnnsCsPfee7Ny5cpBL3Pq1Kl88pOfBOCzn/0sr7zySu9nJ510Uu////nPf/Y7f0/XwL333ptVq1YB8Nxzz/G73/2OOXPmcMIJJ9DR0cHSpUuZOXMmv/3tb7n55pt55513qKioGNoOEEIIMe7YhQjfi7Di3d1RNE3Diuvk8xKIEkKMf+2FgLwXkjSL1xU5aelEQFPOL1obRHkJgqC3J40QI0lqRJWg9WtErS8ej/f+2zAMHMcZ9DK1Dfqhr/96oH+vLxaL9a53/VpUP/rRjzjssMM2mv7RRx/lmWee4cILL+Qb3/gGp5xyyqDbKoQQYnwJA4XrRIQBxOIf/c6YJth5RRBEmKY8GxNCjE+RUnTYAQU/pD5VvNuvmKGTsLrrRG1bkyhaO0T56OzspKOjA8MwqKmpQdflt1qMDDmSJojVq1fz6quvAvCHP/yhNzsK4I9//GPv/z/xiU8MepmHHnoo999/P77f/VRl8eLFFAoFVq1aRUNDA6effjpf/OIXefPNN0dwS4QQQpQb247w/QjT6vuww7Q0IgWFnGRFCSHGry4nxAkiDE0b8KHvWElbBm2FAKVUUdshSl9PfeOuri6WLl3KmjVreu/7hNhSkhE1Qey000488sgjXH755eywww6cddZZvZ95nscJJ5xAFEXcddddg17maaedxsqVKznmmGNQSlFXV8cvfvELFixYwL333otpmqTTaW6//fbR2CQhhBBlIIoUrq0IAo1kqu8NmGFomKYilw2pqpFLEiHE+NRWCOhyQmqSxakNtb6Upa/XHjnvioH5vk8YhiSTSTRNo6mpiUKhwNSpU6X0ithimprg4fA1a9b0eV0oFEilUr2vW1tbhzzS3abE43EaGhpGbHk9TNPs02VufStXruSss87i2Wef3eizWbNm8ec//5m6uroRb5MYfzZ1nIni2vDcVa4aGhpobW0tdjPECCrkQzKdIVHUt1tej+7aUYoddoqPWaaAHGdiLMhxJgAKfsiHbQ7tdjDi3fKqq6vp6uoa0jxhpFjc7rDbpBS7Ty7/6wYxerLZLE1NTVRXV+O6LlEU0dHRgaZpbL311tTX10tXPbFJU6dOHfAzCYNvxmgEjYQQQoiJQEUKp6DwfUUi2X+QyTQ1nEKE5yriieJ2WRFCiJHWVgjIuCEVsdK4YTd0jYqYQWPWk0CU2CTXdfE8j3g8juu66LpOXV0d+XyeFStWUCgUmDJlSp86xkIMlgSiJoDp06f3mw0F8PLLL49xa4QQQkwUjqPw/QhNH3gwDNMENMhnQ+KJ0rhRE0KIkeCHii4nJAgj4gmr2M3plbR0Wgs+XhARk4EiRD966kNpG9Q10zSNiooK4vE4bW1t2LbN1ltvTVVVVdHrn4nyImceIYQQQow4pRSOvS7TqZ8ueT00XSMW08hlpWC5EGJ86bAD8l5A3CitG/SUpRNG0FqQwtOif57nEYbhgMEly7JoaGjA932WLl1Kc3MzYRiOcStFOZNAlBBCCCFGnOcqAk+BNnA2VA/T0vBcRRhKMEoIMT4opWi3AwqBIh0vfpHy9cUMjbihsapr5OrgivHF8zxc1yUWiw04ja7r1NbWkk6nWbVqFcuXL8dxnDFspShnEogSQgghxIizCxGuq4gNonSEYWqoqHseIYQYD7rcENsP0TVVcl2WNE0jHTNoKQRM8HGrxABc18X3fSxr811Kk8kk9fX1dHV1sXjxYjo7O+W4EpslgSghhBBCjCjf6x4JTymFYWz+UsMwwDAVuYwEooQQ40P7uiLlVbHSyobqkbR0HD8i78l5V/Q1UH2oTTFNk4aGBpRSLF26lLVr18pI22KTJBBVgqZPn86cOXM44ogjOOecc7Bte8Bpb775Zu69996N3r/xxhv5+9//PuB8f/nLX3j//fdHpL1CCCHE+uyCwvMU1iAH0tE0DTOmYxfkCaoQovzZfkTOC4lQmIMIxhdD0tJRQGNOuueJvjZXH2ogmqZRU1NDZWUla9asYdmyZRQKhVFqpSh3MmreZhhuI1o0cn1dlZ4gjE/Z5DSJRIJ58+YB8O1vf5v777+fc889d0jrueyyyzb5+V/+8hdmz57NzjvvPKTlCiGEEJsSBArXjVCRwhzCaEymCa4d4XsRVokMcy6EEMPRZvtk3YAKszSzoQBMXSMd01md8ZlRX+zWiFIymPpQm5JIJJg0aRIdHR0sXryYqVOnUltbi67Lb7v4iBwNm6FFDpqKRu6/IQa19ttvP5YtW8ZTTz3FCSecwFFHHcUXvvAFWlpaNpr2oYce4stf/jK2bXPRRRfxf//3fwBcf/31HHbYYcyePZtrrrmGhQsXMm/ePH70ox8xZ84cli1bxkMPPcRxxx3H7Nmz+frXv96bhXXRRRdx1VVX8ZnPfIYDDjigd5lCCCFEf+xChO9GmObQnqSaloZCI5eVUXeEEOUriBRddogXKhIlHlRPWQYddkAYSTaq+IjjOIOuDzUQwzCor6/HMAyWLVvG6tWr8TxvBFspyp1kRJWwIAiYP38+hx12GPvttx9/+tOf0DSNX//619x9991cffXVvdPed999zJ8/n/vuu494/KO+EB0dHfz5z3/m73//O5qm0dXVRXV1NXPmzGH27NmccMIJAFRVVXH66acD8OMf/5jf/OY3fPWrXwWgqamJxx9/nA8//JC5c+f2ziOEEEKsLwwVrqMIQ4glhhaI0nUNy1LkshG18nReCFGmOuyAgh8SM0qrQHl/kpZOc757dL9J6eEHHcT4oZTC87wh1YcaiKZpVFVVEY/HaW5uplAoMG3aNCoqKkaotaKcSSCqBDmOw5w5cwCYNWsWX/rSl1i8eDHf/OY3aW5uxvM8tt12297pf/e73zFt2jR+/vOfbxS5rqysJB6P853vfIcjjzyS2bNn97vO9957j5/85CdkMhny+TyHHnpo72fHHHMMuq6z884795uJJYQQQgA467rWGdbwLl6tmI7rKFSk0PTSv4kTQoj1KdUd1Ml5EXWp0u2W1yNualiGxqouVwJRAhh+fahNicfjTJo0ic7OTpYsWcLWW29NXV0dhlH63xExeiQQVYLWrxHV46qrruKcc87hqKOOYsGCBdxyyy29n+266668/fbbrF27tk+ACrpHMHjiiSd44YUX+MMf/sD//M//8Mgjj2y0zosvvpj77ruPPfbYg4cffpgXX3yx97P1+wfLUJxCCCH6E0UKx1YEASRTw7uANU0NO4hw7IhkWi5QhRDlJeuG2H6EroE+gjfyo0XXuutENef9YjdFlAjXdXEcZ9j1oQai6zq1tbUUCgVWrFhBoVBgypQpfXryiImltDsui16ZTIYpU7qLnG8YSNpzzz258cYbmTt3Lo2NjX0+y+fzZLNZjjzySH74wx/y9ttvA1BRUUE+n++dLpfLsdVWW+H7Po899tgob40QQojxxrEVvheh68N/YGGYoBmQzcpw4kKI8tNmB3S5PpXx8rnFSpk6OTfE9qU+n+gORIVhuEX1oQaiaRrpdJq6ujra2tpYsmQJXV1dkugwQZXPWXKCu/TSSzn33HM5+eSTqaur2+jzWbNmcdVVV3HmmWfS3t7e+34ul+Oss85i9uzZfP7zn++tK3XiiSdyzz33cNRRR7Fs2TIuu+wyTjjhBL70pS8xY8aMMdsuIYQQ5U8pta5bniIWH34WgKZpWDGdQk4CUUKI8uIGEVk3REVgGeVzi5W0dBTQJFlRE15PfSil1Ih2zduQZVk0NDQQhiFLly6lqamJIAhGbX2iNGlqgocg16xZ0+d1oVAglUr1vjbcxiGPdLcpSk8QxqeM2PJ6mKYpX2Ax6uQ4K10bnrvKVUNDA62trcVuhhgix47IdIb4XkQ8uWU3YK4bYecU28+IYVqjczMnx5kYC3KcTSxrMh7LOh1MTSM5RqPlVVdX09XVtcXLWd7pUJOw+NR2VSPQKlGuXNelsbER27b7FBQfqeOsP7Ztk8lkqK2tZeuttyaZTI7KekRxTJ06dcDPpEbUZoxG0EgIIYQYL5RS2IUIz4mIJ7f8CappaiilKOQjqmrKJ6tACDFxhZGiwwlwA0VlGda3S8cM2gsBkVJlUdtKjA7XdXFdd8TrQ21KMpnEsiw6OjqwbZupU6dSU1MzqhlZojTIFZ4QQgghhs33FIGvQGNERrozDA3DVOQyUq9ECFEeOp0A2w+JGeV585wyddwwosuRrPeJrKc+1FgGoqC7x0VDQwMAy5YtY82aNfi+dBUd7yQQJYQQQohhswsRrquwRnDgGyum4zhKCpgKIUqeUoq2QkDODakooyLl60tYOoYGqzJesZsiimT9+lDFoGka1dXVVFZW0tjYyLJlyygUCkVpixgb5Xm2HEVy0SuEKEdy7hLF4PsKz+sOGBkjWJzXNDVCX+E5clwLIUpbzouw/Qg0rWy7temaRkXcoCknWSgTled5BEGArhc3PJBIJGhoaKBQKLB48WLa29vlGneckkDUBnRdl2LMQoiyUgoXDmJictbVhrJiI3vzZZqADrmsdM8TQpQmpRRhpGgr+GTcgMoxKlA+WpKWTsYJ8AI5705Eruvied6Yd8vrj2EY1NXVYZomS5cupa2tTYJR45AUK99AIpHAcRxc1y2rImnxeBzXdYvdDDHOyXFWepRS6LpOIpEodlPEBBMECseJiCKImyP7e6npGrGYRiEXUT95RBcthBB9KKUIVXfB8VApwuijfweRIlIQRGrde93/jtb9O1oXjAojiJllHogydUIFLQWfaVXlV3BdbBnXdQmCoGRGrdM0jcrKSjRNY/ny5SilaGhoKKv7c7FpEojagKZpJfMFHAoZIliMBTnOhBA9HDsi8CPMEc6G6mFaGnZeEQYRRpnf4AkhRt9AAaVgvWBRqDYOKAVKodbNF7FunlDhR4ogilCq+xynaaBQaGhA9zy6poEG1fHyD9zETZ2EqbGyy2NalTzcmkh66kOVooqKCjRNY8WKFSilmDRpkgSjxgkJRAkhhBBiSKJQ4dqKIIBkapQCUaaGihR2IaKiSgJRQmyKUoq8F3WP3hZEbFcTJzaCddtKmVKKFV0eGTcgitZlKSkIo4gg6g44BVFEpLpDSBsGlFDdD6LRwNDA0HQMXZGO6Zi6jjGBur6nYwbthQCllNzsTyClUh9qIOl0ujcYFUURW221lRyf44AEooQQQggxJI4d4XsRhj56F4K6AYapyGYjKqpGbTVClDXb7w4+dTkhThCRcQO67BA3UOy5VarYzRsTXU5Ihx3QnPMwdQ1NBx0NQ9MwdCZkQGm4kqbePQKgF1IZl9vEicJ1XVzXxbKsYjdlQKlU9/ls9erVAEyePLlkA2dicOQMI4QQQohBU5HCthWer0YtGwq6MxTMmI5jR/J0Xoj1eGFElxN2Zz/5ETkvxA2i7pHPYhoKgw/bbHaojZGOje9L/TBSNOZ8upyASWkTc4JkgfUKR7aweNLS0YE1GY9dJo3vY0d8xHVdwjDsDfaUqlQqhaZprFq1iiiKmDJligSjypicYYQQQggxaI6jumtDGYx6cMi0NJxChO8pYnEJRImJK4wUXW5Ip92drVLwQ2xfoaFIWQaV6Y8yGWoMRacdsKjJZtb0yiK2evS1FQLyXoCuMeGCUEY+Q2ztUoxUNWF13cgsU9dIxXTW5nx2mTQiixQlrpTrQ/Wnp5bzmjVrUEqx9dZbSzCqTEkgSgghhBCDopTCKUR4riIxitlQPUyzO9iVz4XE4nKhKSaWSCmybkinE5JzQ2w/JOtFgCJu6tSnjH6DwbqmMSltsarLZUZ9gvpU6Xa32RJ+qGgp+GTdkNrUxLulMXNdhF2dxFYtx99xd4K6kRliNBUz6MgHhJEa1e7XojT0jJZXTsGcZDKJpmmsXbsWpRRTp04tq/aLbvIXE0IIIcSgeK4i8BWaPvrZUAC6rmFailw2GvV1CVEKlFLkvJBVGZd3W2yWtDss67Bpzns4QURdyqAhbVEZ7z8I1aMippOwdP69Nk+k1Bhuwdhpynvk3JCYqXePXjeRRBFGIUdgmgRmHOuDRZita0dk0SlLx1eKtoI/IssTpa0c6kP1J5FIUFtbS2NjI6tXryYc4W6qYvRNvMcHQgghhBgWuxDhuhFWfOzWacV0XFuhIoUmT+fFOOUEEZ12QKfTXe8p6wX4YfcobpVxA2uI3c60dVlRyztd1nS5bFOTGKWWF4ftR7QXAmwvor5i4t3OGHYOFfiEZhyvbivobMH68C20MMCfvE330IDDFDc0YobGyi6XyRWxEWy1KEXlUh+qP/F4nLq6OpqamlBKMW3aNAzDKHazxCBNvDO3EEIIIYbM87prNQEYY1iLxTQ1CmGEbUek0nKBKcYPP4zo7KfouKFppGIa1YktO96Tlk51wuDNZputKuNYxvgJ5K7NemTdkIrYxOzcYeSzKNtGTWkAx8WrnYwyDKzF76KFEd6U6TDMrkqappGOGTTngxFutSg1URSVVX2o/sRiMerq6mhubiaKIrbZZhtMU0Ic5UD+SkIIIYTYLKegcF2FNcYPyA0TdANyGQlEifK3YdFx2w8p+N1dT1NWd7e7kdSQMlnS4bKk3WaXSeWX8dCfjBOQdUP8SFG1hcG6sqQURiFLgIZhmoALgF9Vj9J1YsveIxb6eNM+NuxgVNLS6bQ98l5IOjYB9/EE4XkeYRiW/ai0sViM+vp6WltbUUoxffp0CUaVAfkLCSGEEGKTAl/huhFKKQxzbDMQNE3DiunYBakTJcpTpBS5dUXHs26IHYRk3QiUIm7p1KfMUbsRtAydhpTJuy0206vjpMo8qBApxdqcT5cbUDVBBzDQnTwEPqG+8W1cUFELukFsxRLiYYQ7fUcYRlelpKmjAY1Zjx3rkyPQalGKeupDJRLl33XXsizq6+tpa2tDKcW2224rwagSJ38dIYQQQmySbUd4boRlFeepqWmBnVMEfoRpTcybT1FelFLk3IDVGY8uJ8ANIrrcEKUUlq5TlzLGrMB2TcKk0w55u6XAvtMqx2Sdo6XdDih4IRrakOtmjRdmPgu2TZiu7vfzIFWF0nTiq5cRDwPc7XbuHoJ0CCxDI2nprM76Eogax3rqQ42XgI1lWTQ0NPQJRpVbEfaJZHwcdUIIIYQYFWGocB1FFEE8UaRAlKmhIkU+H1FdMzFvPkX5CCPFkg4H086xusPGD8HUoSquFyV4Yugak9ImKzpdZtQlqUmW5+V/ECmacz5dbkhtsrwzu4ZtXbe8UAHmwP2kw2QFzuRtSDSuJhGGuDvsghpiv+pUTKej4BMpNfFGJZwAxkN9qP6YptknM2q77baTYFSJkqs5IYQQQgzIKUR4XohpFu9GxDA0jJgi3yXDM4vS124HdDkBLTmHuKnRkDapSZpFzeCpjBtYps6/m/JEShWtHVuiJe+T90MsXZuwgRHdtcHzCPrplrehKJ7E2WobtNZG4kveQvPcIa0rael4kaLDlqLl49F4qQ/Vn55gVFdXF8uWLRuXAbfxQAJRQgghhOhXFCkcRxH4GlasuBerlqXjOApVpjfRYmKIlKKtEJB1IyZXxkmYpZG5o2kak1MmzTmf5lz53ZS5QURbISDvRlRO0NpQ0D1aHo5NmBhcd7kolsDZajq0tRL/YFF3IGuQEqaOqWus6iq/40Vsnuu6OI4zLupD9cc0TRoaGshmsyxduhTXHVogVoy+McnN9TyPq6++miAICMOQ/fffn1NPPZXf/va3PPPMM1RVVQHwpS99if/4j/8A4LHHHuPZZ59F13Xmzp3LzJkzAViyZAl33XUXnuexzz77MHfuXDRNw/d97rzzTpYsWUJlZSUXXXQRkydPHovNE0IIIcYlx1b4XoRhKKC4gSjT1LDzEa6jSCTH3xNcMT50Od0j4Rk6JZe1k4oZVMZ13mgs0JCOYeql1b5NWZv1yDgBSUsflxkcg2UWsoRRBLHBBw8iK44zZTsSzSuJv/cm7k57ECXTm51P1zQqYjpNeQ/Y/PSivLiuSxRF46Y+VH8Mw6C+vp729naWLl3KDjvsQDweL3azxDpj8kjBsiyuvvpqbrzxRn7yk5/w+uuv8/777wNw/PHHc+ONN3LjjTf2BqFWrVrFggULuOWWW7jyyiu57777iKLu0XJ+9rOfce6553LHHXfQ2NjI66+/DsCzzz5LOp3mpz/9KccffzwPPfTQWGyaEEIIMS4ppXDsCN9TxOLFv/EzLdB0yGele54oTUopWvLdNYyq4qWRCbWhhrRFzotY1jn4zJhiy7khGTfEjSJSsYmbDaV5DnguoT70Y0uZFs5W26LsHPH338AoZAc1X8LSyTohbiDn3fFkvNaH6o9hGNTV1WHbtmRGlZgxOZtrmtab9heG4Wb7oy5cuJADDzwQy7KYPHkyU6ZM4cMPP6SjowPbttl5553RNI1DDjmEhQsXAvDqq69y2GGHAbD//vuzaNEiSd8XQgghhsl1FIGv0HVKIgNB0zRiMY1cLip2U4ToV9aLKPjdx6dRotlGMUOnNqnzTpODG5T+d0kpxdpc98iDVbHSDO6NFTOfBcchjKWGNb8yTOyttiVyPWLvvoGe7dzsPClLJwKac/6w1ilKU099KF2fGIHdnswo27ZZvHgxjuMUu0mCMawRFUURl112GV/72tfYa6+92GmnnQD461//yne+8x3uvvtucrkcAO3t7dTX1/fOW1dXR3t7+0bv96TabTiPYRikUimy2cFF+4UQQgjxEaUUdiHCcyNiRRoprz+mpeG7irAMbqDFxNOa98m4PlUlXsOoNmnhR4p3WgrFbspmdTghOTciihQxs7T362gzChmiMEBtSU0f3cCZvA1RFBJ/7w2MrvZNTh4zdBKWxsrMxMiemSh66kNNpG5quq5TX1+P53ksWbIE2y6frNDxasw6heq6zo033kg+n+emm25ixYoVHHXUUXz+858H4OGHH+b+++/nW9/61oCZTJvKcOrvs/6e4D799NM8/fTTANxwww00NDQMZ3NKTk9BNiFGkxxnYrTJMVYaHDvEt110AlIVpVM/IkhHtEcu8XgFNbXDv4CW40yMtJwbYNg50pFFQ0X3sWkYBtXV1UVuWf+0uEdz1sNKV1OdLM2hzcNIsbYxSxTT2LamqmSzzMaE7xEzTZx0BWZFRe/buq5TUTGM+k2VFZiNq0mueB+160yihq0GnHSKniDnhtTX15dEdqzYcp7nkUqlqKmpGdT0pXwuG6rq6mqam5tpbm5m1113JZ2W+mfFMuZXl+l0mt13353XX3+dz3zmM73vH3nkkfz4xz8GujOd2traej9rb2+nrq5uo/fb2tqoq6vrM099fT1hGFIoFKhY70TdY/bs2cyePbv3dWtr64hvYzE0NDSMm20RpUuOMzHa5BgrDZ3tAblshBVT+F2lk4WglMJ1Q1YudwnC2LCXI8eZGGnLO11WdLokLY2usLvbR3V1NV1dXUVuWf80pXAKLn97eyUHbltZkgGGppzH6i4X24+IhaUTEC8Gs6sNr70NW4+jcvne9ysq0uTWez0kFbXE2hsxX1uAv+NuBA1b9ztZ6IW0dnksWa1TnZjYf4fxIIoimpubyeVyg/7el/K5bDji8TgdHR0sXLiQHXbYQYJRo2jq1KkDfjYmV5eZTIZ8vvsk6Xkeb775JtOmTaOjo6N3mldeeYXp06cDsO+++7JgwQJ836e5uZm1a9cyY8YMamtrSSaTvP/++yil+Pvf/86+++4LwCc+8Qn+9re/AfDSSy+xxx57lOSPqhBCCFHKfE/h+wqUwjBKJwgF3ZnOZkzHKURSB1KUDCeI6HICgkgRL5PuY7qmManCYm3WoyUfFLs5G/HCiNZ8QNaNqE5M7NpQAGY+Q+S5qGRy5BaqaXh1UwgSaawP38JqWgn9nFcTpo6uwWrpnjcuTLT6UP3RdZ26ujqiKGLJkiW95YHE2BqTsHZHRwd33XUXUdR94XjAAQfwiU98gp/+9KcsW7YMTdOYNGkS55xzDgDTp0/ngAMO4JJLLkHXdc4+++zeL8vXvvY17r77bjzPY+bMmeyzzz4AHHHEEdx5552cf/75VFRUcNFFF43FpgkhhBDjil2I8JwIM1aaD3NMS8MplM5ofkK05n2ybkjaKq8bu4qYQTqm80ZjjiM+VlNSXd8acz5ZLyRpafJgOQjQHJtAs4AR3heahlc7GaXrWIvfRYsU3lbbwHpBCkPXqIgZNGY9dp88vELponQ4jjPh6kP1R9M0amtraW9vZ8mSJeywww5UVlYWu1kTiqYm+CPFNWvWFLsJI0K6GYixIMeZGG1yjBVXECg62gIcOyKZKs2b6ihSdLVH1G9lUFc/vNo2cpyJkeKHEe+1OrQUPBpSfY/HcujO4gQRyzpc9ptWwXa1W1AEewQV/JAP2xzaCwH1aekKZmY7sFYvx0EnSvW9Ud6irnkbraedWFcb4bY74k3doU8wqsMOaC34fHqXOqwSy5QVQ9Pc3ExbW9uQgi7lcC4bLqUUnZ2dRFHExz72MQlGjbCid80TQgghROnrzjSKMM3SzUDQdQ0zBvmMjJwniq+1EJD3QhJlenOeMHVqkwZvNhfwwtL4Tq3N+mTckIoSH31wrBj5LMp1iJKjW8cmqKzDq5uMsXwx8RUfQhj2fpa0dMKoO/tPlK8oivA86WK5Pk3TqKmpQdd1lixZQiaTKXaTJgw5wwshhBCCKFS4jiIMwCrRbnk9LEvDdRVRNKGTukWRhZGi3Q7I+xEV8fKtY1SfsnCDiPdbnWI3hU4nIOeGBGFUNvW2RlUYYth5Al0HbfT3R5Cqxm3YGn31MuLL34Ogu35Y3NCIGxqrsu6ot0GMHtd1CYIAwyjf89Vo6AlGGYbBkiVL6OzsLHaTJgQ5wwshhBAC216XDWWUdhAKwDQ1olDh2KWRwSEmpnY7wPZC4mXwndkUU9doSFt82GaT94pXuDxSiqacT6cTUCUFygEw7BzK9wmNsavnEyYrcCdNQ1+7ksTSd9F8D03TSMcMWnKhDBRRxlzXxXVdYrHhjzo7XmmaRnV1NZZlsXTp0j6DqonRIYEoIYQQYoJTkcKxu0fLM8ugfqlhgm5AVrrniSKJlKK14JPzIyrHQReymoSBpsGiJrtobWgrBOTcAF1D6hCtYxSyKNse9W55GwoTKZyttkVrWUN8yVtonkvS0in4IXlPzrvlyvM8oijCNIdQe01FEE2Mv7mmaVRVVRGPx1m2bBnZbLbYTRrX5CwvhBBCTHCOo/D9CEOnLEao0jSNWEzHKUyMi2NRejrsAMePMLTy+M5sjq5pTEpbrOpyaSuMfR0gP1Q0532ybiTZUD2iCLOQI9R0KEJXqiiWwNlqW2hrJf7BItJRd7e8xpx0zytHw60PZbY0oq1YDBMkE64nGGUYBitWrChKBuBEyTqUQJQQQghRJEopsl0hmc6QfC7EsSN8f2xrHymlsAsRvqewEuVzQ21a4LmKwJdglBhbSilaCwGdbjiugiYVMZ2EpfPvtXmiMb4Rasp75NyQmKmhj4PA3kgwnHx3t7yhZK+MsMiK40zZDjKdpD9cRIXyWJ2RguXlaDj1oTTXRstlCJd9CPncKLau9FRUVFAoFMa0XpQbRKzJeLzbahNOgBqYMiaqEEIIUSRhCI4dkcuGaJqGroMVA8PQMU0wTB3DBMPQul8bGvoI16PpDuYotDLL7DBNDZQinwuprpXnamLsZNwQ248wYFwFTbR1WVHLO11Wd7lMr0mMyXptP6KjEGD7IfVpa0zWWQ6MfBYcmzBdU9R2KNPCmbItieYV1Kx6l+YpOxFGVRj6+Dn2J4Ke+lDx+OD73xsdrSjHRimF3rSKqGK3UWxhaYnFYiSTSVatWkV1dTW6PnrXGTk3pLXQPVpozgtxg4jta+Ik9fHzoKM/EogSQgghiiTwFUEQEU/qWBaEgcIPNHw3RKGhCCHS0A0wLDBNHdMAw9QwTA3T1DCMngDV8AJJdj7C8yLKrXapbmgYMUU+E1FdW+zWiImkJR/Q5QTjojbUhpKWTnXCYFGzzZTKONYYFGJvzHlk3JC0Nb5vuoZEKYxCllCp7vTPYjfHMLG32o5E0xq05Yvp2DpJw5SGYjdLDIHrukOqD6XZebRCHl8pqK5Fb28m2mHn7gKNE0Q6naalpYW2tjYmTZo0osuOlKLTCWkr+BS8iIwbEEaQsnSsmIE5ioGvUiGBKCGEEKJIfE8RBJBIdgeRTEtbd8/R90IvDCMCD1w75KOB4jQ0FKalYVg6hgHWugBVTxaVYXT/e6AAled2dwUE0MuwOLBl6TiOQilVVtlconzlvJC8FwLjt6B2Q8pkSYfLknabXSalRnVdGTck44T4YURVovgBl1KhOwXwPQKjhPaJbsDkqeiNbTS+9hp1B3wCvba+2K0SgxBFEb4/hC6VSmF0tBHZeaJUBVEyCY1roLMN6iaPXkNLjGVZpNNp1qxZQ11d3ZC6NQ7EDyPa7YD2QoAdRGTcEE0pKuIGMbP7N8WZICUHJBAlhBBCFElPEGhzQRTD0DGSG78fhRFBAJ4XoUKFUh8txzDXBaYMDTP2UVBq/QCVXVC4jsIqs2yoHqalYecjXEeRSEogSoy+1rxP1g2oiI3f480ydBpSFu+22EyvjpOKjU4GhFKKxqxHlxuMq1pbI8EorOuWl6wqdlP60A0Dq34STR0t7PbvV1AHzkazSihYJvo11PpQeiGHZhcINA3NtCAWR8UTGGtXEU6gQBR0Z0W1trbS0tLClClThr2cgh/SVgjockLyXkDBjzB1jdqkMa66eA+FBKKEEEKIIghDRRgq2IJ6lLqhEzNgwziSUoogUPgeuG6IymlomgJNQ9PAsrrrT2k6KBSGWZ6ZHaYJmg7ZTEgiWZ7bIMqH7Xc/vQ4iRayIBaTHQk3CoNMOeLulwL7TKkdlHe12MO6zy4bLLGS7fx+swdfzGSspQ6MpVYeTW0xixRKMHXcpdpPEZriui+M4JJP9PNHakFIYneuyodKV9IRIVLoCvbMN5blosdI7LkeLaZqk02nWrl1LQ0PDoLs2Qve1WMbtDkDlvJCMG+CHirihU58yJ3wmt5z1hRBCiCIIfEUYKHRz5C9ENE3DsnSSaY10pUFFtU66yiBVoRGPQxiBbYcUchFWGWd2aJpGLN6dFSXEaGstrMuGmgC1jAxdY1LaZEWnS4c98qOkhZGiOefT5YRUSzZUH7prg+cS6qUZ7EwaEBkWLal6WPoeaihdvkRRuK6LUmpQGVF6LtOdjacZaOsFXcJkCpRCb2kczaaWpFQqRRRFNDU1DWr6MFK05H3eb3NY0u6yssulveCTMHQa0haVCWPCB6FAAlFCCCFEUfi+wvcUljl2Q/RqWnc9qURSJ11hkK7Uu0efK2OmqeE63UXfhRgtXhjR5YR4oSIemxiXz5VxA8vUebOxQKRG9jzVnPfJeSExQ5uw3VIG0j1ankOQHN36XMNl6ZDQFavMavA9opVLi90ksQlhGOJ53uAmVlF3NlQhT1RR0fczw0SlKzGaV8MInw9KnWEYpNNpGhsbN7kv3SBiTcbj3Vab5R0OazIeGTegKq5Tn7aIWxPjt2OwZG8IIYQQRRB45VskvJSYpoYC7IIEosToaSsE5NyQ1ATIhuqhaRqTUybNeZ+m3CBvZAfBDaLerioV43DkwS1lFLJEQQixRLGbMqAKE9oii7C6Dpa8hwokK6pUeZ5HGIaDy4bKdKJcm8C00PoZtS1KpqBgQz43Gk0taalUd2B47dq1G32Wc0OWdTi812qzvMuhOefjhoq6lEFdysSU67x+yV4RQgghxlgUKfxgYj1RHC2GqWGailxGAlFidASRot0OsMOI1ATJhuqRihlUxnX+3VggiEbmnNWY88k4ASlLuqdsSPNcNNchGIHRuUZTpQlepLHaqgXflayoEtZTHyoe30xdpyjE6OogchxUuqL/SRIpMHX0plWj0NLSpus6lZWVtLa24rou4brfhQ/abBa3O6zocmkr+BhoNKRNqhITtwj5YE2sX1MhhBCiBAS+Ioq6C22LLWdZOk4hQk2w7gJibLQVfPJewASLQfVqSFtk3YhlnfYWLyvnhXQ5Ac4EDOoNhlHIgucQxgZRVLqIYjpUmYr3XQuq6mCxZEWVqsHWhzK6OlCOTWhuooi2phGlK9HbmyEKR6G1pS2ZTBIpeHPxCt5vtVnW4bA649HpBKSt7vpPSTmvDZrsKSGEEGKM+b7CdyNk1OuRYVoaQaDwPAlEiZEVRor2QkDeU1TGSztLZbTEDJ26lM47TQ7uFtRiU0qxNuvR5QRUT9B9uTlmIUvkBahEaQeiAKotyPjQnqwB3yFavazYTRIbGHR9qDBAz3QSuQ4q1X82VI8omQbPh862EWplebADRWNB0aGlWbK2nZWtGfJeSG2yu/tdrExHHy4m2WNCCCHEGAt8hYrAkAuXEWGYABr53MR7QitGV6cTUPBDTJ0J3Y2sNmnhR4p3mgvDXkanE5JzIyKl5KatH1rgozk2oaYDpX+sJXVIGPCeY0FVrWRFlSDXdQmCAL2fek/rM7raUW6BMBbf7HlOxeKoRBJj7fjvnqeUIutFrMiGrMiGNOZ98qGOqUfouRaqR6P7nVIYTn5kl1mi5FdACCGEGENKKQKfcrjPKBu6rmHGIC91osQIUkrRWgjIuiFViYmdwWPqGpMqTJZ0OmTcYMjzh5GiMefR5QZUJ8zNzzABdXfLcwnipVukfH2aBjUmNHsadroWXIdo9fJiN0usx/M8XNclkdjEMRX4GJlOIs9DDXKkxiiVRst2gOeOUEtLi1KKDjdiaSZiVS6kJe+TdzySWkh9Uqe6qgonn8G1hx+Y71cUEW9aSWLNMnCdkV12CZJAlBBCCDGGAh/CUMkv8AizLA3XVUQjVFBZiC43pOBF6JomRWeBqriBqWm82VgYcj221oJP3gsxNTB02Zf9MfJZlOsOOhhQCipMQIPFXgyqamDxO6hg6IFKMToGUx/K6GwjcmyCWHLQWZ9RMg0KtJbGkWpqScn6iqZ8RHvBx3F9qsyImoTem8lpWjEMM0ZH85oRq02p+R6JNUvRu9pxbQdV4gMWjAS5DBZCCCHGkO8rfD/ClKSAEWVaGlGosG3JihIjoyXv0+UGVMblchlA1zQmVViszXq05AcfbPDDiNZ8QNaNJnxm2YDCAMPJE2gG5XR7ZmhQa8JyWyOorAVbsqJKxWDqQ2mei57tIvQDtOQQ6pIZBipVgdG8GsbZICGRUrTairwXUG1FVCd0DKPvd1LTNOLpNG4+j5PPbfE6ddcmsXYZWjaDE2r46aotXmY5KJ8znRBCCDEOBL4iDME0JStgJBlGd62oXKcEosSWy63LhkIpTEMul3tUxAzSMZ03GnOEg8w+bMz5ZL2QpKlN6Dpbm2IUcijPI7TixW7KkFWa4EYaa8IY1NTC4nclK6oE9NSH2lw2lHJswqEEodaJkmko2JDPbkkzS06Hq3CCCEsLNwpArc+0YpjxOB3Na1HR8K87jHyGxJplqEwGWzOJKiZGEAokECWEEEKMGaUUvq/QmNiFj0eDpmlYMV0yosSIaCn4ZNxgwo6UtykNaYtOJ2RF5+brwxT8kA47wPYj0rIvB2QWsijXIUqli92UIYvpUGUq3stpUFkLdoFozYpiN2vC66kPFY/3H9zUXBstlyEMI7Rh1CWLEkkwdfTG8VO0PIgUHY6i4AWkrc2HSRKpNJ5dIJ/tGtb6zM5WYk2rCHM5nHhqsyMWjjcSiBJCCCHGSBhAFCokBjU6TBN8LyLwJBglhq/gh2TdkDCS0d36kzB1apMGb7UU8MJNf9casz4ZN6QiJvtxQFGEUcgRahpo5bmfqi3IBhrtxKC6RrKiSoDrukRRNGBGlNHR2p0NlRhmTTJNI0pXoXe0QDQ+RqxtcxQFPyRhRIN6WGiYFlYiSVdLI9FQsqKiiFjLGqzWRsJcFiddhYoPPSut3JXn2U4IIYQoQ76vCIIIXbrljYru7o4a+fz4uCgWxdFaCMi4IWlLMngGUp+ycIOI91sHHtmpywl6A3qJQWQXTFSGnUMFPoEeK3ZThi2pQ8JQvJMDrboO7DzR2pXFbtaE1VMfaqBgimYX0Ap5AqXQ4sM/7qJUGjwP2luHvYxS4YaKLjfCD0JSQzj3x5MpfNcl39UxuBnCkHjTSozOVnzbxq2sB7N8v/tbQn4VhBBCiDES+IogAMsqdkvGJ93QMC1FLiMZUWJ43CCiyw4IIkVCsngGZOoaDWmLD9ps8t7GmS+RUjTmfDodKfa+OUY+i7JtojLulqNpUGNCq6dR0NcbQS+UhwLFsLn6UEZHK5Gd3+KuoMqKoRIpjHHQPa/VjigEISlzaMXXDdMklkzS2dpEtJnjXfM9EmuXond14Lk+fnVdd4HLCUp+GYQQQogx4vvdFzhSH2r0mJaO46gRG1JZTCythYCcH5KULnmbVZMw0DVY1GRv9FlbISDnBmiAJcXeB6YURiFLiNY92kIZqzABDT7Mg1ZdC4U80RrJiioG13UHrA+l57NoToFQ09DMLX8qFqXSaNlOcAfOjix1eV+R8xRhEBIfxrk/nkwT+j7ZjoEzw3SnQGLNUsh04UQQVNUx0UMxE3vrhRBCiDEShoowVCDxkVFlWhphqHAcyYoSQ+OHik47wPEVKcmG2ixd05iUtljV5dJW8Hvf90NFc94n60ZUJyfu0/7B0J08BD6hXt5BKABDg1oTltsagRlflxX1tmRFFYHruiilNs6IUgqjs42okCdKjkwGXpTszqrSWhtHZHljTSlFqx2R94PuYOow6IZBPJUi09ZM2E9tNCPXSWLtclQui2MmiCqqt7DV44P8ygohhBBjIPAVYaCkPtQoM03QNch1SSBKDE277ZPzAmRwt8GriOkkLJ031uaJ1mUhNud9cm5IzOgOVomBmfks2DZhGY6W158qE7xIY6W9LisqL7WixloYhvi+32/mtZ7LgGMT6gaaOULBT8NApSowmtZAGWYid3mKQqDQVIS1BZmwsUSSKIrItLf0ed/qaCHWtJowl8WOp1HDLQ4/DkkgSgghhBgDvq/wPYU1xPoDYmg0TcOKa9gFCUSJwQsjRVshoOBHVEgkatC0dVlRbXbA6i4XJ4hoL/gU/JDKRPln+Yyqnm55inFTrNjSodpUfJDXUFa8ewS9DyUraiwNWB9KRd3ZUHaeKD2y9ciiZBrsAuQzI7rc0RYpRbujKHgBldaWBc113SCeqiDb3orved0j4zWvwmxrJMjncdI1EEuMTMPHCQlECSGEEGMg8LoDULrUSxl1pqnhOt0jFAoxGB1OQMEPsQxNargNUdLSqU4YvNlUYE3GI+vJiIODobs2eB7BOOiWt74qC7KBRqvXkxWVIxoHxazLRU99qFisb3BTz3SiXJvAsND0kb0OiRJJsEz0xtUjutzR1u4o7CDCJETXt/y8H4snQCkyLWtINC7H6GzDt1286noYgXpc441cDQshhBCjLIoUfiCZUGPFtDQUYOclECU2TylFaz4g60ZUSjbUsDSkTApBRFPOwwsiklJja7OMfLa7m1QiWeymjKikDglD8V4OtNi6WlEfvIOKJCtqLPRbHyoKMbo6iBwHNcLZUABoGlGqEr29Bcrk7+xHig5XYXsBFSN0vtJ0nWQsTrTsffyONlw/6h4ZT5PzYX9krwghhBCjLPAVUSTXImPFMDRMU5HLlscFsSiuLifE9kN0TWoaDYtSxH2HaWGW9sYWCeYNklnIEkbRuOuuo60rWt7iaeQC0GrqIJ8halxT7KaNe0EQ4Pv+Ru8bmU6UYxOa5qhlfEapNPg+tA88clwpabMVth+S1KMR2yeGU6Am04LmeTRlcoSVNYD8pgxkfOWCCiGEECXI9xW+G2GNjzIgZcGK6dgFhVJKulqJTWop+GScUEZ4GwLNdTCcPIadx3AKqMBnkmMzyXVwJlWizPFRfHu0aJ4Dnkuoj89jrsKEFh8+yMM+1XFUVTV88BZqylS0cbrNpcDzPIIgwFy/EHkYoHd1EHoOqqp21MIiyoqhkkmMxlWEDVuN0lpGhhMourwIPwipSIzM8WjlMyQ7mgkdlyhZiR0pKj1voy6S4iPybFYIIYQYZYGvUBEYWzAiixga09QIA4XnSZdIMbCMG1LwIpSmMEagRsh4pfkeZraDWPMqkiveJ7HqQ6zVy9Ca1uBnMriOjx2vQHk+sRUfFru5Jc/MZ8FxCGPjcwQtXYMaE1YUNPwItOo6yElW1Gjrrz6U0dWOcguEVnzUH8pEqQq0bCc49qiuZ0u1OBEFLyQ9EoPHKEWis5VkWxO+45JLVmCkKtB0jc5MO6oMRxIcK5IRJYQQoiS4TkRri4NifGWwKKUIfCQ7e4wZ665w8pmQ+CQJAIr+teZ9Ol2fKulO1lcY9GY7GXYePBd8D+U6BJpBpBuEsSSqopb1T25+TQOxtib0XBdRRXXx2l/ijEKGKAxQleOrW976qkxo9TRWFBQ7ViS6s6I+lKyo0bRRfajAx8h2EXjeqGZD9YgSKQxAa21EbbPDKK9teHK+ouApVBQS29LaUFFEqqMJM5/F9QKcVDUYBhoQjyew7QKu55KIj9/v+ZaQKzMhhBAlwS5EtLe44y6DJfAhDJX84o4xXdew4hr5nBQsF/0r+CE5L0RFYE300SyjCL2Qw2prIrF6Mcnl7xNbswxj9XLCjjY8u4CtTOyayXg1kwiq6lCJJBtG2INUJcq0sJa/D5IJ0C/N99Bcl0AzGM9PKCwdqk3FB3mNSK3LispmiJrWFrtp41J/9aGMzjYiu0AQS47NAz7DQKUrMJrXlOT3P1KKFjsi5wVUbOEgdloQkG5djZntwvZDnIruIFQP0zAxDJPOTIdkRQ1AMqKEEEIUXRgqfF/h2QERIfHJ4+em0PcVvhdhyi/umDNNDcdWRJEakaGZxfjSkg/IOCEVEzEbSil018aw8+hOT52nABybSEGATmjGiKoa+txcbZam4dU0EG9dg57pIKquG71tKFNGIQuuQxgbX6Pl9afaghW2RqunmBxPoCqrurOittpasqJG2Ib1oTTPRc9mCIIArbpyzNoRJdMYzY2Qy0BlaWVFdnkKJ4gwiDC34OGD7rmk29aCbZNHJ6ioYsOgsqZpxGNxCnYex3VIjrPRMUeCXBYLIYQoOs9VhL7CMDRy2YiGycVu0cgJfEUYQiwhgZCxZloaUS7CzkekK+WmR3zEDSK6nIAgUsTNiXFsaJ7T3d1uvQLjODZRqPB0nUg3CVM1bOmoCmEiTRRPElv2Hs5es0AfPw8WRoKZzxB5Hqq2pthNGXVJA5KG4r0cTI6DVlOPWrWMqKkRY+tpxW7euOK6Lo7jkEp11x0zOttQdoEwkRzTvLsonsSwTPTG1UQlFIgKlaLdUeS9kNrY8PeIaedJtTcRuTZ5M0EUH7jOm2mamKZJR1cHiXhiXJWdGAkSiBJCCFF0ntudEVVdY5JrVAR+hGmV/82LUt3bpWnIBUgRGEZ3rahcRgJRoq+Wgk/OC0mNg/PMQDTfw3Dy6OsCT/geuC7K9/A1g9AwCROVEIszol3ENA2/qp5480qMjlbC+nH0ZGFLBQGaYxNoJuO5W976aixodDQygaIqnkBVVMKHi9ZlRY3f799Yc10XAMMw0FwbLZ8liCK0sa5PpGlE6Ur09haiMBxaRuUoancUth8R1yI0bXjHXSzXSbyzlcB1KcRSqNjm9208liBXyJEv5KlIVwxrveOVBKKEEEIUVRR1B2sA4nEDFUE+F1JdW/4XqGEAUSi1AYpF0zSsmI5tS50o8RE/VHTZIW4QUZnewkIhpSYIiHW2dBcY9z3wXJTrEmh6d4FxK7FRgfHRECZShKkKrOXvEdY2SFbUOqadBc8j3MKss3JSYYChw4d5+I/q7lpRavVyoua1GFMkK2okbFgfyuhoQxXyhIlUUcKdUTKN3tkBHS3QMKUILejLCxWdrsL1A2riw9gjSpHoaiWW6cD3fAqpSjAG99thGAaWadGV7SSVTKHLubCX7AkhhBBF5bndGVCGrqEbGmZMkekcH4ED31cEQYRhTYwn36XINMH3InxvfBxTYsu1rcuGSoy3AuVhQKJxOUZrI2F7G14hv67A+KSPCownU4xVJo5f1YBWyGO2SnHqHkY+g3IdolS62E0ZM7oGtSasLGj4EWiJJFRUwgdvoSI5L4+EnvpQhmGg2QW0Qo5AKbR4cQKeyoqhkkmMtauKsv4NtToRBT8kaQxjVOYoJNW2llimA9fzKaSrBx2E6hGPx/GDgHwhN7R1j3Pj7BdYCCFEuekORCmsdRnOVkzHdbsLTJe7wFcEAVjjLOminJiWhkKjkAuL3RRRAsJI0W4HFPyIdHwcXQaHIYnGFWj5DE6k49ZOJqhqQKUrYJjdULZUFIsTVlRjLf8QgqAobSgpYYhhFwh0vWh/k2KpNCEAlhe6X/eMoKdaG4varvHCcRwcxyEej2N0tBLZBaIidwOLUhVouS5w7KK2ww4UWU8RBCGJIXbF1gKfipbVGLkMdhDiVNbAMIrsG7pBzIrRlekikuBrr4l1FhRCCFFSokjhewrFRzWULEtDhYyLwEFPl0OpD1U8uq5hWYpMVi7+BN1BKC8kZmjj53sZRSSaVqDlMrgBRBVVxW5RL6+qDlwHq2llsZtSdIadQ/keoRkvdlPGnKVDlQEf5DUitS4rKp1GvS9ZUSOhpz6U5RTQnAKhBppZ3CdgUTIFCrSW4gYbW+yIgheSNof2cNPwHCpaVqEVcuSVgZeuZktCJ/FYnDAKyeQzw17GeCOBKCGEEEXje4og7C7m3cMwNQxLkc2UdyAqDBVhqKD8E7vKnhXT8RyFGgdZdmL4IqVoLfjkvIiK8ZINFUXEm1auC0IpwsqaYreoD2XGCKpqMFcuQfO9YjenqIxCFmU7RMmJ0y1vfdUW5EON5nWHgVZTD12dqLam4jaszAVBQBAEoBRGZxtRIU+ULIGi2LqBqqjAaF4Dqji/vVkvwvYVRAExc/DnfN1zSbesRuUL5PQ4YaqCLe3SrOs68VicbDZDGJb39e1IGSe/wkIIIcqR5yo8VxHboIyBFdOxCwpVpIuXkRD4ijBQ6OY4ybooY4apEQUKx5Un7xNZpxPi+BG6Dvp4yIZSinjzKvRsJ54XEJbQUOnr8yvrIAoxVy8vdlOKJ4owCzlCTR9W157xIGlAylC8l+3+7nXXiqpAvbdIsqK2gOu6+L5PzLPBsQl1A80sjfHIomQanALkxj4LKFKKVkeR8wLSQ6nTGUWk2huJXIdcIk2USI1Ym6xYjEgpurJdI7bMciaBKCGEEEWhlMLzFKDQNygabFoaQaBwyni0M9/vHg3QGmI6uBh5ptldkiXXVb7Hk9gySila8z5dbkh1YhwEApQi1rJ6XRDKJ6ga/ZHwhksZJn5VPebaZWiOU+zmFIXh5FG+T1giAYJiqbGg1YPMugHetOo6yHSi2pqL27Ay5rourm2TymeJ7HzRa0OtL4onwbLQi1C0vNNV2H6EoYWYQxiYItnZgubYFDQLZY1sN1pd686KyuWzBIG/+RnGOQlECSGEKArP684Y6i8xwTS7R/vOlnHgIPC6u+VtGGQTY0/TNKy4TiFfvseT2DJZN6TgR2iMg2wopYi1rsHIdOA5XkkHoXr4Fd3ZWtaqJUVuSXEY+Wx3tkpiYnbL65E2wNDgg3z3ay2ZglQF6n3Jihou13XR8lk03yXQTTS9hK45NI0oXYne2QJj2B0tjBTtrsL2QiqHUKDcymewcl24YbSuO97Ii1ndXQAkK0oCUUIIIYrEcxWuG2H1M7qwpmnE4jqFXFSW3fOiSOEH5dfu8cw019UkC+RmZyJqKQR0OT6V46A2VKytEaOrHd921gWhymCbdAO/ugGjeTVaIV/s1owtpTAKWQIFFLmAdLHpGtRasMrWcNfFJbSaOuhqR7W3FLdxZSgIAnzPw8x0Ejk2qqKy2E3aSJRMg+9Dx9j9fdscRcELievRoAel0H2PZGcrgefhpqoYreC+pmnE4wlyhTz+BK+bVwa/XEIIIcYbpbprQ6HAGCBjyLQ0fD/C98ovoBP4iiiacCN0lzTT6h6tqZCTQNREk/dCcm6IQsMq8wxFq70Jo7MN37bxq+rK6iTjp6pQuk5sxQfFbsqY0p0C+B6hMbG75fWoNCEAltvdr3uzot57sywfPBWT67oEHa1YoU9oxkpyJFBlxVDJFMYYdc/zQkWnG+EFIanYIM+Pal1dKMemEE+Peh03y7TQNY3OzMTOiiqfXy8hhBDjhu8pogG65fXoLqWhkcuW3+givq/wB8j2EsVhGBqmqcjlyu94ElumJe+TcUMqB3tTUqKsjhbMjhaCgo1fVV9WQSgAdB2/pgG9vQl9At2AGQXplrc+S4dqEz7Ma4Tr4k7dI+h1oNokK2oonEKBoK0VMwpRqZE/viLVPdJhYQt/NqNUBVquCxx7ZBq2CS12hB2EpIdQnzPR2YpuF7CNGCqWGMXWddM0jXgsQcEu4HoTs24eSCBKCCFEEXiewvM2HajRdY1YHLKZ8stgCXyFigbO9hLFYcV0nDIfjVEMjRNEZNwQP4qGNHx3qTG72jDbmwnyBbzKmvILQq0TJCtRZhxr+ftFG9J9rJmFLGGokCcTH6k2oRBqtKzrmdSdFZVGfbBIzs9D4LY0gusQxeIjlg0VKsgEGms9gyWOxQrH5O2sTpNnEA3zTxMlU4CG1rx2RNo4kIKvyPmKwA+JD/J8bxZyxLJduEFIkBy7YLFpmui6RmdX54Q95sckR9TzPK6++mqCICAMQ/bff39OPfVUcrkct956Ky0tLUyaNImLL76YioruwmCPPfYYzz77LLquM3fuXGbOnAnAkiVLuOuuu/A8j3322Ye5c+eiaRq+73PnnXeyZMkSKisrueiii5g8efJYbJ4QQogh6OmWF0UahrnpCyfT0ijkuuv6mGVyE6mUwvcp9drBE5JpajiFCNeWrKiJojXvk3NDKq3yHSnPzLRjtTYSFgp4FbVQzl28NA2vup54yxqMrnbCmvpit2hU6a4Nnkuol/HfbBQkDEgZineyGlPi3TfhWk09as0KVFsLWoPcw22ObxcIujrB91A1NVt0yeFFkI90cqGOE2l4EdihQlMROgpND3jX0cnFNaYnAoacXKobqHQFRssaguk7sMl0+GFSStHiROS9kMpBlmLTA49kZzOB6+KkqxnLC7eeWlHdWVEuifjoZ2KVmjG5qrcsi6uvvpobb7yRn/zkJ7z++uu8//77PP744+y1117ccccd7LXXXjz++OMArFq1igULFnDLLbdw5ZVXct999xGtG0nhZz/7Geeeey533HEHjY2NvP766wA8++yzpNNpfvrTn3L88cfz0EMPjcWmCSGEGKLAZ91oeZt/AmRaGoryqusT+BCFSnKOS5BpAhp0dHgT9gnkROKHEZ1OiBdGJMq0W56R6+wOQuXzuOnqnj7LZS1MVhAlkt1ZUeN8pLTu0fIcgmSq2E0pOTUWtHuQWTeKvZZMQTIlWVGD5K5djZ/LQiI15GwopcCONFp8g2WOyTLHYoVj0ORAxgsJg5BqLaTWjKg2FVvFocEIWeFovJO3yIZDD9iEyTQ4DtoojRaX8RUFX6GpYHAPLlVEsr0JXKe7LlQRAvymYWIaJh1dHRPymB+TX2VN00gkuqN8YRgShiGaprFw4UIOPfRQAA499FAWLlwIwMKFCznwwAOxLIvJkyczZcoUPvzwQzo6OrBtm5133hlN0zjkkEN653n11Vc57LDDANh///1ZtEhOYkIIUYo8N8LzIsxB9FIwDA3LUmS7yieDxfcVvheNh/vFcUfTNeJxnbYWj9amgGxXiOtEqOH2NxAlrbUQkPdCEmWSTbkhI58h1ryGKJ/DrageVyOuedUNaNkujDEcSasYjEKWKAhhDOrOlJu0AYYG7+c+ek+rqYeO0h1BL4xKo2u3cl2c9jZ8xyZRWTGoeSIF2VCj0TNY4lost01WOTqtriLnh5gqoM4IqTUVFaZiw8oCSUMxLRaQDWBR1hxyVz0VT4BloTWuHMKWDk6kFG22ouAFVFqDO98nutox7AIFjO62FUF3VlQcz3Ox3dGvn1VqxuwyOYoivve979HY2MjRRx/NTjvtRFdXF7W1tQDU1taSyWQAaG9vZ6edduqdt66ujvb2dgzDoL7+oxTe+vp62tvbe+fp+cwwDFKpFNlslqqqqrHaRCGEEIPguYowhHhicBcLVkzHcRRRpND10u/vFvjd2xdLlH5bJ6JkWiOZMGhpCclmQkxTI5nUSaR0YnENK6aVxXEmNk0pRacdkPdDJqXLL4CjF3LEm1cR5vM4qSoGFbkvI1E8SZiqwFr+PmFNAxjl23VyIJrnorkO/jjctpGga1AXg9WOxl6hIm6AlkqjkknU+4tQ+x9eUqPAddoBK7tcFJC0dOKGTtzUiJs6CVMnZmjoY9Xe1ibcbIbQ2vRIeb6CfKiTDzXsSMePoBCCIsIkIqlBbAjRAFODra2AjlDnnfwQu+ppGlG6Er2zjSgMR/Q73+EqnCDCJEQfxIh3pp0nlu3E9UOCyuoRa8dwmIaJaZp0dnWSjCdL6pgfbWMWiNJ1nRtvvJF8Ps9NN93EihUrBpx2oEjzpiLQ/X3W3x/y6aef5umnnwbghhtuoKGhYXNNLwumaY6bbRGlS44zsaV8L8KzHTQC0pUb/wQZhkF1dd+LglQqoqPVJZmoorKqtG8olVKEnkMU+P1unygNhmGwTaKuu16ZF+EUIgp5he/ppNMGybRJImGQSBjoxsS5KBxP8l5Awrao1jyqK4sTxOnvfDYYWiGHlW8niBTupK2oGKfZNFpsW6xVS0g4WdTU7YrdnBFntDejmwbU1pMYpSLIuq5TUVG+o/ElIkU2E9Gm6+xW3f2bGZnbE6xaTpIIo2GrIrewW0vOpcu28UwNx4/IeoCCCEjFdNIxg4Spk4qZJEydhGV89H9LH9EAVWTnKaiAmKGTrq79/9n78yDL0vq+838/z1numntWdXf1CjS4hRbT0EgIGWhDW+ERDsWEgwmCCDustmRjY2MjbM9MjGwpsEeBZAXIEt3IDgnZw4xCg+ywHAqPLexWh2gspJ/RgmSERO9L7ZXr3c45z/r742ZmV3VtWVV58y75fUU0dOfNzPtk5l3O+Z7v9/PQajUuub3ww53uuk5RBSiBkoBWgTQbjtklN5hZprWm0Xj1dagJDByctQnWw/31yMJ+Ds/yjKQcoGyBWr7zhtZwNdZHzjgDacVt7euHtitnaW6ewamIWT5GYwLa17M8pdPtEFVgrj2PTlJWV1bI67VxL22kDv0332q1ePOb38zXvvY1FhYW2NzcZGlpic3Nzb3upZWVFdbX1/e+ZmNjg+Xl5cs+vr6+zvLy8iVfs7KygveewWCwF3x+sUceeYRHHnlk77/X1tZG9aMeqtXV1Zn5WcTkkseZuFWDnmdrw6G0woXLDxYWFhbY3r40PyDGSFl5Xnyh4o47J7srwNnI5oajKgMuTOc40FFw2eNMg1aRqop0tiMhDKN4anVNo5mQ1xR5rqQoNUXO9yyn1wsyrdgO4xl5uNLr2fXockD97MuU/S5FrQ3Gg+mPaIXjV8vqJN/42vBnnYATwoNUP3eauLVNuXQMeqP5G7bbLXoj+t6Hpe7hD87DbUQSNXzPjz7S/50vo9/xnrF3iFzoW850DRuFZS5PmL9o1DfESFEEznYiNgRChEgEFPVE0cg0eZLQzDW1RFFPNbV0p5Mq0SQ30X0bX3mB7isvsW08MVZ0Y6AIip7X9IPCBkXhwcVh2HiuI021kw/uwdzE76DRqFMU5SUfU8CxCOd7KRt9eH0jcDz3XO9HSpWGZ/4EX9/fSOH1nBsELvQdSbAMwnW6oWKktXaaotuhl9QI1oF1B7KOWxbgzNkzcFxhrGNtfZ28NtnHvPtx4sSJq952KEfJnU6Hfn/4ImmM4X/8j//BnXfeyUMPPcSXvvQlAL70pS/x9re/HYCHHnqIr3zlK1hrOX/+PGfOnOH+++9naWmJRqPB008/TYyRp556ioceegiAt73tbfzmb/4mAL/zO7/Dt37rt479hUsIIcSlqp2xvCzf/+uzUoo815T9MBHZDNdi7XCHP32d3QDF5FFKkeWa9nzC/OKw+FQUgbULlnOnDRfOWbY3HcUgDLdiFxOtZ3ZCyrPpeS6qqqR29mVCv0+Zt45ErpCZWwZTkZ07+NyYcVLOosoCrzSyheq1zadQeMW5avjfSinU0gpsXiBurl/7i0fsXM9wpmtYLyxzeUr+mrw5rRStPGGllXL7XM6J+Zw752vcMZfRzDWFjawNDC9ulnxzbcDXzvT5g9M9/uhsnz862+ebawUvbpY7hS7HwHr8NYKXYr9H7HUYFCWbQbERazxfZrxcppwqNZtVZGA9NV7Ne2rpkWxSB7w6qperwJ/2Nc8XKeY6+w+EZgvV7UB56xcISh/ZqgLWehr59Ufyat1NkqJPgSLUG9f9/MOU12pY5+j1e9f/5BlxKJceNjc3efzxxwlheBLx3d/93bztbW/jTW96Ez/90z/Nk08+yerqKh//+McBuPvuu/nu7/5uPv7xj6O15gd/8AfRevjE/6Ef+iE++9nPYozhLW95Cw8++CAA733ve3nsscf46Ec/Srvd5mMf+9hh/GhCCCH2ybmIc/GmDojSTFEOAqaM1BqTe1DvbMQ5mLDjG3ET0kzT3hk1cDZQFZF+z5HoYadUvamp1Ye5Uol0Sk0UHyIDOzwbmpaLkspU1M++RBz0KNMGsXY0XkRimuHmlklfeR53/E5iNv0dADAMKcdUuCO4JfuNqifQSiLf7ClO1HeKMI0m1JvDrKjvGk9X1Jmu4XzPslFaFmoJ2Q28zmulaGQJjdeMq8U4zDIqbaRrLL5nhlWiCFkCzd2RvlRTz17Nnqqnw/G+7qkzbF8YcNY32LCBEDUqBhIibR1JxxBHphQsp4GGirxSJvR8xusbnvn0yhWp0GiSKIU6f5p4zxtu6b7XikBhPa1s2IV2LUlVkHc2MMZi24u3dL+jkOiEPMvpdLdZXpqN18HrUXHSLy+P2OnTp8e9hAMhI1PiMMjjTNyKQT+wtWF3Ok+ufMBwtVGWGCNbG57F5ZRjt01uTtTGmqPf8zSaMpY3yW5mZGqXc4GqBO+HRdVGXVNrDItStZoikW64sdsuHc9tlPSMZ6kxvnGv/T7OlDXUz7xI7HUpkxpxRHlCk0p5R+P0i7g778Xe96ZxL+dA1M68hDp/hmLpGKMcQJmF0TyAroMzJTxy7NWsodjvEc+eQr3jYfTy4eWTxhg51TWs9R2bhWWxnpC+dgu5Edxn5SID53EenA/EneJbpqGRJdRNgT13hn6nS4+At5bFRu26o3AH4UqjeVfiIlywCUopXtcI3HaVUb10cw1lDe6t7wR1c7/bno2c6np6lWHpOpvfKO9pnx92m/aa85BM5nFkCIFev0uz0eJdf/57ZDRPCCGEOAimCnh3czuQK6XIa5p+9zo932PkfRyObB3pyzuzL001rbZmfiGh2VRUJrK17jh32nD+rGFz3TLoe5yTB8K4dI2nU3nm9rWV03gpZ1/thNL5kStCAcQkxS4sk555CVVe/2R34nlHUvZxKkFOtfanlQzHvJ6+eCqp2YJ6nfjM1w9tLD/GyCsdw4WeY7NwLDXSkRehYHiMU880y42M4+2MEws17pzPOTGXsVBP8T5gzp2h3tug3cxpKc9crg6lCHUjUgW3Z55cBb7Z1zxXpFRXOGzzjRaU5XBE7ybEGFkrAj3rmLveMWWMNDbPQVkyyOoTW4SCYSh8rVan2+9h7M2keU0XeXUUQggxct5HrB0eSN5si32WgTURe70AgjFxNuJtlHyoIyTZKUrNLSY0WwpnYGvDc+605fwZw8aaZdDzOCtFqcPUq4ZREIdxAnlLnKN29iXodanIiM2DCe+dRra9QFSK7JVnxr2UW5YMekRj8Nls73h1kLSCpRxOlorSDz+mlEItrsD6GnFrY+RrCDHy0lbFWt+wVTqWm8lNhYkfJKUUDTvgtu3TrFKSZjkecN6TTmhBZXdU73jqOVXBN/oZHXfpa3Gs1SHLUGdvLhtu20QKF0hiuO7rfN7bIh30KCOE+uQX+rMsI0tS9E12ik2T2f8JhRBCjJ2pIs5G0lso0qSZIgK9rj+4hR0gayPWRbJUig5HUZJqGm3N3EJCs61wDrY3PefOOM6dNWxcsPR7nnCNIFpx60oXqFxg4gOivaN+7iVUr0tJQjjCRSgAdIKdXyG5cBY15WG96aBLrEpCc/JPeifJXAoBeOniDOtmC+q1YVbUCLuifBgWodYHlk4VWG4m6HHmy8VI0u9QP/0CtdMvotbPY8oK357H+eEub5Oef1dPIndmnoGLfL2XcKZK2Hv7U4rQmkNvroO/sV3rfIysl5FBNewKu5akKqlvr2ONwTTnb/InOVxaadIsm/i/70GQQpQQQoiRM1XA2kh6C+PuWiuyHHqdCe2IMsOxPD3pXRhi5JJE02wNi1KtOUXwsL0VOHfa0dmckK2iZ1S38gysp5lO8PPQe+rnXhkWobwitKbjBGnUXGueqBPyl6e4KyoEkkEPr9RNZ98cVamCxRSe7St2NyYddkWtwsYF4vbmSO7Xh8iLO0WorgksN8ZYhIqRpLtF/dRz5GdegvULmKKkaM7j5lfwIRK8n/g6+65kZ1SvdoVRvdBognOwfuGGvudmGSlsINP+2sWa4GlsnCWUFYPGvDwfJ5D8RYQQQoxU8BFjhsHOt3qFJ88VVRnxbrKKUSEMu6GEeC2tFY2mZm5Bk2awuR6I0hU1Mj3jKWygcZ0r5WMTArXzr6C621QewtzCuFc0OZTGLq6gN86jOze3mcC4JUWP6CxOy1jezZhPofCKs6/tisprxKf/+MDvz/rI85sl6wNL33iWG8l4OlFCIO1s0Dj5LPnZV4gbG1SlpWgv4eZX2L2K57zDeUeip+cUXilYes2o3rbTxCwnNpokNzCeZ0Nks4qU1tHKrv07aGxeQFUlg7R2c+GkYuSm51EshBBiKhmzk510AFvcp5kiBBgMJqsQ5WwkBFBj2DpZTI+8pnAuUEzY43dW+BAZmAAHUPQeiZ0ilO5uU7mAb0sn1Gu5xhwxq5G/9KcwhRt7J/0usShkLO8m1RNoJZGn+2rvz6+UQi2twMY5wgF2RVkfeGGzZHPgqFxkuTmGcSjvyTYv0HjlGbKzrxC2NqmMo1xYwc8vQXLprp/OuYnOh7qW147qna4SXLON6nehGOzre6wXkYH1NJJwzb9V3tsm63eofBgGo4uJJIUoIYQQI1WVw6Dy/AB2oU0SRZpFutuTlRNlbcRWgWz6jg3FIUpTRZrBxoaM543CwAaMD6STtpUUQIzULpxCd7YwxuHnFpma+ZrDpBRmcRW1vUmyvT7u1dyYGEkGXTxcVkAQ+7eYwbqF7YtfJpttyGrEb379QO6jcoHnNys2CocJkcXGIV9Fco5s4xzNV54hPX8Kv71N6aGcXxm+NlxljGxa8qGuZndUr64CT/c1T8cFypigzp+57tcWLrJtAt55GtnV/17aVNS317CVoZqSXKijSgpRQgghRiaEW98t77WyXFMO4kSNNzkbiWGYDSTEteQ1TdmPWCtdUQetZzxd4687snHoYiS/cHqvCOXml5Ai1NX5eovQaJG98E0I0/M80WUfnMVruSJxK5oJ5Aq+eVFm/UF2RZUu8PxmycbA4kNgoX54RShlDfnamZ0C1Glcp0MZNdXi6jAr7ho5Rt57gvdMaQ1qz8Wjeqet4hvpKt3zFyBe+7m+VgQGxtO81oYwIdDcOEsoC4pGG7S0qU+yCXunFkIIMUuGu+UFDjLOIMsU3kXKYjJOUGKMWAtxyg8OxeHI8uHuj52tyerqmwXdyuNDJJ+woPJ87QxJZwNbVrj5RaQIdX1mfgXV65Ksnxv3UvYt7XehKPAylndLtILFHM5UivLil8lmG9Kc+OzNZ0UNrOeFjZLNwhGB+frhdK4pU5KfP0Xj5LMk589guz0KlQ0LUM059vOaMBzLc+gpyoe6lr1RvaTGN3ua0+e28VcZx+2ayMBGYvDXfH1vbF1AFwMGOidmktM26WbjkSyEEGIiDQtRkbx+cCdeSQo6hc72ZBSinB0Gss/IsaEYMa0VtbqisxlGuh35UWN8oHQBJuxXmq2fJdlexxYldn4JOfTen1Br4Ntz5C89A34Kira7Y3kRbml7WAHAXAohwgsXRQftdUWdP0dYO0909oa+Z994XtwZx1Mo5mqj75bR5YDa2Zepn3ye5MIZTK9PkdYxi6vERosbKUo7b6c2H+pqEgWrjYQ57XnxlXM8u+ko/aUv4iFG1spAzzja1/jRs0GXrLdN6SO+2R7xysVBkAFmIYQQIxFDxJpIjAebZ6CUIss1g/7wRH7cWQnWRqwJEgki9i3PFZ3CU/QDzbaMDhyEbuUprKeWTU63UbJ2lnRzDVeU2Pll2T78Btn5FZLTL5KeP4W7455xL+eadFWAMTgtbwQHIVWwkMLzfcWb2pG9vU5abchz4h//PiwfIzYaqHoTanWoN4b/n+WXHRf0Ks9L2xWbA0eqoVUb7XNRD3pk22voQZ9YDLARbLMNWf2mv6dz050PdTVKK5qtOnf3L/Bc5wR9W+P1ixmLO3+jbRMpXCAhkF4l/kBbQ2PzAs4YquYi0nU6HeTVUgghxEgYE3E+juTcK8sU5cBjTKRWG+8Bh7MR7znQri8x29JMkaawueGkEHVAeiYwMIHl1mQc2qZbayRFF1cUmDkpQt2MkNVw84tkLz+HO3YC0sn4215J0u9CWeDr0olxUBYy2LSKM0XkrubwY0ppOHEPcdAjdjdhY+3VztJaDZptVKMO9eZOYapBh4xXCtgoPPVU08hH9FyMkaTfIdteQxUFsRhglMY15iG7tS457z0hhKnPh7oaW28x193gPrvJqfQYX78QeN1CzvGWZr2MFJVn8WrHejHQ3DhHqAoGtRYk8p46LSb3FV0IIcRUM1XEVJF8BGP6aTo8r+tte2rHx3eCN8yHiqhJ3S5eTKxaXVPshJZnkxauPWVCjPSMBwV6Ap6HylmyjfPY4DHtRWRu9+bZuWXS3gtkZ17C3v2GcS/nqtJBFx8C5Dff8SIuVdPQSiLf7CvubMS9IozSGtWeh/arO6LFGIhlAf0ucXuDuBN8vaVrnGKOXtAsNTLyZp1QaxDyOiGrHUzRIgTS/jbZ1jpUOwUoneJaCwc2plmZCucdiZrNIktIM1ytSWPjLLe/8TjbVeTpTcNWlRKJ5DoMi5BXUN9eRxd9+qREef5NFSlECSGEOHAxRoyJQBzJTnJKK/KaotcLrBw/8G+/b94N86Em4NxXTJksVwx6kc6WZ+WYFCpuxcAGjLtofGfMdNEHU2Fa8xDlb3srYprh5pdJT72Iu/1u4i12loyCMiWYCi87dB24xQxOV7BlYekaf3qlNKrRgsarQfHrVeRU17Ldr5j3A/K+R0dPkiTDgmGeQ71JyGuEvI7fKVDtu/MuBNLOJllnHaqKUAywSY5vrxxoV461lqoq8d6Tj+LK3oSwjTaN7QskVcFivUk9DZwfGBqJYrVx5Rf3dNAj72xROY+bWzrkFYtbJYUoIYQQB86aiHejLdCkqaLoD3flS8fUUWJtxLmATifkDFhMDa0VtYaisxVYXh1/1tk061WennE0JqSzLCn6xKpCrbZgUIx7OVPPthdJO1tkJ5/DvO5bxr2cy6T9LpQlPm+Oeykzp5VABjzdh++6gRrkBQNnKs0GOXMLNbSep9q5TXmDLgp0v0B3u+jgSYG0VodajVhrEGvD4lTIhx1UMc3YO6DxjqyzSbq9DqYilCUmrREWVg98BDeEwKAcYKwhS7OZfp8wtSZ1FNnGBaoT91JPNffMXf3zlbM0ts7jKkPZWkByoaaPFKKEEEIcuKqKVFUYyVjerixTDEKk3wssLI3nBNTZiHPDKAohblSeKzoDTzEINFvSTXGzusbjAtSzyfgdJmUfrxSJjOQdiJik2IVlsjMnUXfcR5ywF9xk0CF4S5SOjAOn1LAT6nSpKH2kvo+n+LkKzlaKTROZTxWvrU/HJMe3cy7ZizE4dFmgyxLd66FjII1hmO1Uq0NeI9YbhDQjHfSIZYE3FpvVCIurjGo3zKIssNaglELPevaR1thGm3zzAtUdd1+7qBcjzY1zUJUUtYbkQk0pKUQJIYQ4UDEOs6GIjGQsb5dOFGke6XQ8C0vjeTuzdhiSOstXKcXoJCmkGWytOylE3STrI4UNQLzu5x4GZUqwBq9TZmeT9fGz7QXS3ibZK89i3vjt414OhEAy6JBtb6DKAqsTpCNjNObSYYfT83148/y1P/dMCeeNYsNGFq5QhLoqnRKac4TmRS04MaCrcligGmyj4zoasFkNmzWIi6PtwjHWYEyF857aDI/kXczWW+SDDkm/i28vXPXzap0NknLAICaE2mQVpsX+SSFKCCHEgbI2Etxodst7rSzXlEUkhIjWh3sS4H3E+zgp579iCimlqNU1g8F4R0ynWc94jAvkExIQlezkQ/lb2KZdXIFOsPOr5BfOok7cR2xdY2ZnhJSzpJ1N0t4WVNVOMHWCa0o31KgkapgV9fxA8WfmrpwFF+MwS+pCpdi0kcVUkd7qy6nShHqTUD/8kcsQAkUxHMlLk6Nzuu7yOiHNyS+cobhKISot+9Q6m1TGYeeuXqwSk0+OeIQQQhwoU0WMCWSH0A6QZooQIoOev/4nHzBnI95GyYcStyTLFTFAZ/vwH8OzoGs8XeNpjWpL9huUFH2iscSGXKU/aK41R0wS8peePvT71uWA/PxJGq88Q3r+JH5rk9IGioVV3PwKpNLROErzKZRBcfoKkWsxwslyWITaspGl7ACKUGM2KAYYZ1BaD8PVjwqlMI02aXcL5d3lN3tHY+M8vqoom3NIKWO6yV9PCCHEgdkdywsBkkM4EkyS4fF/txNGfl+vZW3EukiWSkuUuHm7oeXbm4EY5bF0I2KM9KthAW8i8phiJCkHeCVjWiOhNHZhFb25hu5sjf7+QiDpblE/9Ry1U8+TnDuN6fUpVE61eIzQnj/wcGpxZTUN7STydF9x8ctkiPBScWkRakKaI29aZSqMrfAukKVHb8DX1luo4Em31i+9IUYaG+egLBhk9eFsu5hqN/XqaYzBucurlEIIIY42Z8G7wzuZVkqR1TTF4PBP4p0ZjuXpEeZgiaMhzxXOBIrB4RdUp1nhAsZH1IQUfXRVEJ3FH6UOhkPmGm1CXiN/6Zswotd85SzZxjkarzxDfvYV4vo6pigZNBewC6vERgspNB6+xQw27fAfAL9ThFo3iq4bFqEOeUL/wHnvKcoCYy3ZYbSVT6CQZrhak3zt7CUfr3U3SYs+RVRjGZcUB29fR8+f//znefbZZwH4/d//fR599FF+4Ad+gN/93d8d6eKEEEJMF2PCcCzvEHM100zhbKQsD+8kPoRhN5QQByFJQWewtS7jeTeiW3l6xtOckGytpOhDWeAlPHd0lMIuHENtb5Fsrl//82+ALvrUzr0yHL87dwq/vU1pPeXCynD8LssP9P7EjWkmkGt4uj8sQr04GBahen42ilAxRgblAGsNidLoSejyHBPbaJOUfXQ5ACCpCvLOBqay2NZ1EuvF1NhXT9t/+2//jQ9+8IMA/Lt/9+/46Ec/SrPZ5P/6v/4vHnrooZEuUAghxPQwZcR7qNUP7wAqTUFr6G0HGo3D6URwdjh+qKTxQRwApRT1umYwCBJafgP6JmBcYL49GZ0DuuwTfIQjssPVuPh6k9Bokr30Tfzi8vAN4GaFQNrfJu0Md79jMMCgcHmTuLiIdD5NDqVgKYMzpeLZPmw7KH1kKVXMwsa1lamw1uBDODK75F2NqTWpo8nWz2Nuv5vmxjlCWVK05mQcdobsqxBVVRW1Wo1ut8u5c+d4xzveAcDa2tpIFyeEEGJ6OBtxLh76AaFSirym6fcCxw7pPq2N2OpwO7/EbMtyxaAX6Wx7llflQPt6fIgMbCBOygloCCTlAKMVUrwYPbOwSv3sS6Tr53DH7rjhr1fWkHY3SbtbYCpCUWKTBNdckM6nCTaXwpqFkwXketgJNQu895RVQWXMkS9CAaA1ttkm31ojqeVQFhRpHRJ5bs6SfRWiTpw4wZe//GXOnj3Ld3zHdwDQ6XTIc3kwCCGEGDJVwNpAOoZd5NIM+t2ANYHsEHbPcjYSAySSDyUOiNaKWn0YWr60ElGzcIl/hHrGU/lANiHzOLocEJ0j6Mnozpp1Ia/j23NkLz2DWz4+3LliH3TRJ+tsoPtdqAq89dg0JyysSKfFFEgU3FkDG2F+RnasjTHSL/oYY0jSRF77d5h6i7y/TdrbpggR326Ne0nigO3rFfcHf/AH+eIXv8gf//Ef743o/eEf/uFeUUoIIYSoqohzw86Ow5Zmwy6Ebnf0GTsxRqxlcjoxxMzIajuh5YWEll9P13i6lad9CIXn/djLh5IQ3UNj5lahGJCeP3XtTwyBtLNB/eRz1E6/gDp/BtvrU+j6zu53C1KEmiKNBOZnaMO0siqxzhJiJEukkL3LZzV8Xsf0B5jWwriXI0ZgX0/j1dVV/s//8/+85GPvete7+PZv//aRLEoIIY66sghkmSKZkit+zg3H8sbVnKC1Isuh3wksr4z2vpyNBB9vKZZEiCtJLwotbzYlgOxaetVwp8x0QroSk7JHiMhY1yGKWY6bXyR7+Tn8sTuIr9nqXllD2tkk7W6CNYSiwCYprrUAqfydxPg55yirAiMjeZdTit7yHaAi++ydEVNmX3/Vv//3//4VP/7DP/zDB7oYIYQQw0JHt+NZO2+JYTp2ZjNVxJow1sJZliuqMuLcaLtJrGXnZx3p3YgjaC+0vD8MLRdXVrpA5QITk8XkHaqq8HKydOjs3DJ4Q3r65b2P6aJH7dwr1F95lvT8SXynQ2kD5cIqbm5ZilBiIsQYGRQDjLVkaSojeVeiFFKEml37OoyO8fITocFgcKS3lRRCiFEpi4CpAr1OIK8rlpYnv1XbVAHvYJxTKWmmCDEy6AXmF0f3/uTscGfAvC4HjeLgSWj59XUrz8B6GhOyu2BSDsBZvBQ4Dl1MM9zcCunpF4lz86T9DqosiMUAi8LVWsRWY9zLFOIyRVlgrEHFSCJXtsQRdM1H/d/+238bAGPM3r/v6vV6fM/3fM/oViaEEEdQCJGqjAQPzbZi/byn2dTU6pM7puN9xNrhBYtxXtFLEkWaRbrbnvnF0RzUDfOhhjsDytVLMQp7oeVbElp+NT3jKVxgtTkZJ29J0YeiIMyvjnspR5KZWyTtbpK9/BxBKayW8Tsx2ayzVFWJc5ZcRvLEEXXNd/CPfvSjxBj55Cc/yUc/+tFLbltcXOTEiRMjXZwQQhw1VRmxNqBTyHONM4Fzpx133qtJksk8ITVVxNk4lt3yXivPNWUZiSGiRhBY5R0EPyxECTEqWU1RbXuKIkhW1Gv4EBmYgEJNTJEuKfp4pfa9c5s4YDqhPH43mIrQakvwuJhoIYbhSJ4zZGk2Ma9jQhy2axai3vzmNwPwuc99jlpNqrVCCDFKMUbKQcDaSL0xPMlqzmk6W56NNcvq8ck8YDHVcM2N5vjXlqaKgQsMikCrdfAnhdYOM6j0BBTdxOxKU9AJbG1IaPlr9W2g8oEJyShHWQOmwktcxViFvAbSWSKmQFEWWGsgKrQUr8URtq+e5iRJeOKJJ3jxxRcpy/KS2/7u3/27I1mYEEIcNdYMd55TvDr2lSSKVluzvRFotgKt9mQdtAQfMWZyRtWSdPhPd8uPpBDlbMQ5qEvkiBghpRS1umbQCzgXSFMpcuzqVZ5e5WnVJuN3kpR9sAaf1Me9FCHEhDPWYKpqZyRPXjPE0bavQtRjjz3GSy+9xNve9jYWFhZGvSYhhDiSymKYD5W95qJuXtNY4zl/2nH36zRpNv6Czy5jIt5F9AjG4G6GUoos1xT94dbuB10cm4QsLHE05DVF0R9mni2tTEbRZRJ0jcfHSD4hLVG66BOrkrh4fNxLEUJMsBACRTGgsoY0zeU4Qhx5+ypE/eEf/iGPPfYYrVZr1OsRQogjybtIVQUikeQKJ1iNlqazFbhw1nL7XZMzoleVEWsi9QkYy9uVZYqqCBgTqdUObl3eR7yPcPlGskIcOK0VeQ22NwOLyxJaDlC5QOXCuJdxiaQc4FQiuURCiGsalMNcKK01iYzkCcG+3jVXV1ex1o56LUIIcWSVRcCaQHqVQHKtFa05Tbfj6Wy5Q17dlYWws1vehIzl7UozQEF32x/o93U24m2UfChxaIbdkIGqmKziy7j0jKewnvqEnMQpU4I1BD0Z6xFCTKbKVBhT4bwnS7NxL0eIibCvjqh3v/vd/NRP/RT/0//0P7G4uHjJbd/2bd82inUJIcSREUOkLCPeq2sGfmfZ8Pa1c556Q1Orj/fkZ7hbXmDSMnqVUuQ1Ta8bWD3AaRlrI9ZFhnt3SDFKjF6aDUPLNzc8d0hoOd3KM7CR5eZkvOgkRR+qCp9J1osQ4sp88DsB5VaKUEJcZF+FqF//9V8H4Jd/+Zcv+bhSiscee+zgVyWEEEdItVPQUTpyvQJHvakxNnD+jOfOezT6Kh1Uh8FUw46oen3yijJpBkVv+HtNs4M5aXVmOJanJySbRsy+3dDyvoSWE2KkbwMQ0RPSgZkUfaI1xPbSuJcihJhAMUaKYoC1Bq0TEumeFGLPvgpRjz/++KjXIYQQR1ZZBGwVqe0jZ0kpRXtO09n0bKwrVo+P5+paDMNsKCKoCQkqv1iWKQYx0u95FpZu/eQ9hGE3lBCHLc+HoeW9TmBx+egWogYmYFxgYl5uYiQpB1iVIB2SQogrqUyFsQYfPDXZJU+ISxzdIxohhJgA1uwUdG4gZylJFM22ZmvdM+gfbA7SfhkTcT5O3FjeLq0VaRbpbB1Mto6zkRBAycVMcch0oshqsLXpifHoFkN7xtM1nlY+GS86uiqIzuL1vq7pCiGOGO89ZTUcyctfux2yEGJ/HVGDwYB/+2//Ld/4xjfodruXHAj93M/93MgWJ4QQs64sAqYKpPmNfV2trrHGc/6M4677NOkhB2ibKmKrwCQfW2W5piwiIUT0LbZRWBuxJpDd4N9JiINQq2l6HU9VBOpHNCuqazzOR2qNySj8JEUfygJfnxv3UoQQEybGyKAYYK1FJXqiNnQRYlLs67LSL/zCL/DCCy/wgQ98gF6vx1//63+d1dVV3v/+9496fUIIMbOCj1TVsNPmZrJfmm2Ns5G1c/ZQOyVijBgTiUAywXlJWaaIHga9W+8asyYSw2T/vGJ2XRxafhRZHyhsYJLO5ZKiR/ARZNxGCPEalSmxzhBCIEskoFyIK9nXEfUf/dEf8Q/+wT/g7W9/O1pr3v72t/PDP/zDfPnLXx71+oQQYmaVZcCZQHKT3UxaK1pzmu62p7N9eCeo1kS8ixN1UnglSapIskj3Fn83MUacg6M7FCXGbTe0fNAPeH/0Hok9E6icJx/j5gyXCAFdFfhJnU0WQoyN846yLDHGkEkbtRBXta930BgjzWYTgHq9Tr/fZ3FxkbNnz450cUIIMatijJTFcNe5WzlOyXJFraFYO+uoqoPJQ7qeqoqYKRlTy3JNUcRb6hhzNhImOA9LHA15rvAeeodYdJ4UXePpmUC7NhljibocEJ2TfCghxCV2R/KMNaRpJiN5QlzDvg6r7733Xr7xjW8A8MADD/C5z32OX/iFX+COO+4Y6eKEEGJWmSribETp/YeUX02jqUHBhTOOEEbbLRFjxFaRGNRUjKmlmcK5SFncfJHOWrAmkMg5pxgjnSjyGmwesdDyGCO9alh80xNyUrebDxXqzXEvRQgxQcqqwFhDjJEkmYzCuRCTal9nER/+8Ic5duwYAH/9r/918jyn3+/zd//u3x3p4oQQYlYNQ8pvrRtql1KK9pxmMPBsrbtb/4bXYO3OWJ6ejhPhNAWtobt984UoZyPec+iB8EK8Vq2mMWWgKg+n+3ESFC5gfEQxOc+/pOwRIkxFW6gQ4lBYZynLEmdlJE+I/bju9d0QAr/5m7/JX/7LfxmA+fl5/tbf+lsjX5gQQswq53bCvmM8sK6iJFW02pqNNU+jpWmMaGctU0UqE0inJHtTKUVe0wx6gRjjDXefxTgcn1Tq1jvXhLhVaQZJCpvrnjvuOhpX27uVZ2A9jWxCnn/eoaoKt79ruUKII2BvJM9ZGckTYp+u+y6qteaLX/yitBcKIcQBKYuArQLpAZ9Y5TVFksG5Mw7vDr5jKcaIqYa7x93MLn/jkmYKawPW3PjvxLvh7oZyTCkmwVEMLR8GlQea+WQchyZFH5zFS8eDEGJHUQ6w1gCQyBy/EPuyrzOJ97znPfzX//pfR70WIYSYeSFEqjLigyLLD7a6odSwK8qZyNp5e+A5Ms4xkgLXqKUpgKLXvfGQZ2sjzga0jOWJCZHthpZ3Zj+03IVIYcNE7Vj5aj5Ua9xLEUJMAGstVVXhnCOblnZxISbAvkq2zz77LL/+67/Or/3ar7GysnJJu+EnPvGJkS1OCCFmTVVGrAloFWEEmSdaK1pzms5WoNkOzM0fXBeBqcJwt7zagX3LQ6H1MOS52wksr97Y1zobcQ4kk1hMimQntHxrwzO/mMz0CEjPeEoXyPXk/IxJOcCjQCYFhDjyQggMyuEueZmM5AlxQ/ZViHrf+97H+973vlGvRQghZlqMw93brInUm6M7WMlyRa0OF85YarVhRtJBMNUwtLtWn56xvF1pphj0Is6FGxortDaC5EOJCVOraXodT1UF6vXZLYj0Kk/POBZqk/EzKmvAVHg9GesRQozX7kieUgotxWkhbsi+ClEPP/zwiJchhBCzz5qIO6Tg60ZT090KnD/rOHF3hr7FjgJnX137NEozRSQy6AXmF/dXiPI+DnN4JmkuSAiGoeU6ge0NT/3E7J78dI0nBEV6QJs63Kqk7IOt8OmUtYUKIQ6csQZjDM57arm8Jghxo/ZViHryySev+PEsy1hZWeGNb3wjWXb1mdi1tTUef/xxtra2UErxyCOP8H3f9338yq/8Cr/xG7/B/Pw8AB/60Id461vfCsCv/uqv8uSTT6K15tFHH+Utb3kLAM8//zyPP/44xhgefPBBHn30UZRSWGt57LHHeP7555mbm+NjH/sYx48fv5HfhRBCjFRZRKoqHsqO30ormvOa7pZne0OxtHpruQWmClgbSKc0KylJFFkW6W575hf3FyTqbMTbKPlQYuLshpb3OoFjt0V0MnuP0cIGjItM0o+miz6xqoiLC+NeihBijEIIw13yrCFNJZxciJuxr2fOU089xdNPP83CwgIrKyusr6+zvb3NG97wBs6fPw/A//q//q+84Q1vuOLXJ0nCX/2rf5XXv/71FEXB//6//+98x3d8BwDvf//7+f7v//5LPv/kyZN85Stf4dOf/jSbm5v8s3/2z/iZn/kZtNb8/M//PB/+8Id54xvfyCc/+Um+9rWv8eCDD/Lkk0/SarX4zGc+w2/91m/xS7/0S/zwD//wrfxuhBDiwHgfqapADJHkkHacS1NFvalYX/M0mpp68+Y7J0w1zEpqtiborPAGZbmmLCIhxH11iFkbsS5Sq8Eo8ryEuBVZPhw37XY8C0uzdyLUM56B9dSyyeiGIkaSoo8jATUhaxJCjMWgGGCdQWlNIqO6QtyUfR253HXXXXznd34n3/d937f3sV//9V/n1KlT/NN/+k/59//+3/OLv/iL/PiP//gVv35paYmlpSUAGo0Gd955JxsbG1e9v69+9au8853vJMsyjh8/zu23386zzz7LsWPHKIqCN73pTQC8+93v5qtf/SoPPvggv/u7v8v/8r/8LwC84x3v4Bd/8ReJMUquhxBiIpTFTkdRdrivSfWGxtnAuTOOu+7TJDfRXuDcsCAzQXnBN2WYExUoBoFW+/oHjs4Mx/L0hIwFCXGx3dDy7c3ZDC3vVsOg8pXmZBTZlKnAWoKcdApxpFWmwtgK7wK1mozkCXGz9nV0/Vu/9Vv8xb/4Fy/52Pd+7/fy3/7bf0Mpxfd///dz8uTJfd3h+fPneeGFF7j//vsB+OIXv8g//If/kM9+9rP0ej0ANjY2WFlZ2fua5eVlNjY2Lvv4ysrKXkHr4tuSJKHZbNLtdve1JiGEGKUYI1UR8XbYxXCYlFI02xprIhsXLDHeeOCRqSLOhpsqYk2SJIEkhc729be9D2FYfLuJX5cQh6ZW11RlwFSz9UD1ITKwgcjkbBSQFP1hUHmtMe6lCCHGxHtPURYYY8jzQ8hZEGKG7esy08LCAr/3e7/H29/+9r2P/f7v//5etpO1dl/zsWVZ8qlPfYof+IEfoNls8r3f+7184AMfAOALX/gCn//85/nIRz5y1ROla51AXem2Kx28PPHEEzzxxBMA/MRP/ASrqze4l/eEStN0Zn4WMbnkcXZzBn1H1apI0kDzFsbjbkWr6dnesuRZm4XFGzt4WgslpqhottORnxQmScLCwujyV9LEYk1gZWXxmj9LWXqqoqSWeRqtyejIEAdn1I+zwxJjRGGILmN1tT3u5RyY7cLSKBKWEsdCezJO9tLeBiHNUCsr+34d1FrTbrdGvDJxlMlj7PDEGOl0OySJptVukaW3lr05TbTWNBr1cS/jyIjA6soKjVZz3EsZqX0dXT/66KN8+tOf5p577tnLiHr55Zf5+Mc/DsAzzzxzWcfUaznn+NSnPsW73vUuvuu7vguAxcXFvdvf97738ZM/+ZMAe/exa2Njg+Xl5cs+vr6+zvLy8iVfs7KygveewWBAu335QdkjjzzCI488svffa2tr+/kVTLzV1dVD/1lijFgTyXI1MVcsxWiN43E2C7Y2HL2Op1ZXWDu+54rznqe/UXD36/J9jwh6H9lYc5SDgAujH1FbWFhge3t7ZN/fmkhv23P6pKXWuPrP0+95NtcdWQ7GyWjerBn14+wwOR84dTKSN4qZCS0/3TGcXC9o1zTb28W4lwMh0Fw7j61KTH+w7y9rt1v0ev0RLkwcdfIYOzzGGnr9LsZaankNZ6/fXT0rGo06RVGOexlHRlVVrK2v0yj2/34zqU6cOHHV2/Z1dP1n/+yf5TOf+Qx/4S/8Be677z4eeeQRHnvsMf7sn/2ze7fv5jNdSYyRf/kv/yV33nknf+kv/aW9j29ubu79+3//7/+du+++G4CHHnqIr3zlK1hrOX/+PGfOnOH+++9naWmJRqPB008/TYyRp556ioceegiAt73tbfzmb/4mAL/zO7/Dt37rt0pxZMR63cD2hqfbOTovxELcKGuHBdsYhzvZjVOzqfExcu6sJYb9jfKYarhzXDIjO8elGaChc53XLWsiMUAi+VBiwmW5InjodmfnvbhrPCFG8gl5/mlTEp3FK+mOFOIoijFSliXGmiPVCSXEKO37HXV+fp53v/vdN3Un3/zmN3nqqae45557+Ef/6B8B8KEPfYjf+q3f4sUXX0QpxbFjx/ibf/NvAnD33Xfz3d/93Xz84x9Ha80P/uAPovXwYOSHfuiH+OxnP4sxhre85S08+OCDALz3ve/lscce46Mf/SjtdpuPfexjN7VWsT/9nqccBLpdT7eraLaSqd3WXYhRKouAMYGsNv7nh9KKdlvT3fZsbSmWlq9/MGWqgLGRRnP86z8ISinymqbfDRy77cqfE+Nwh8DZSt0RsypJFFkNtjc88wvTH1peuUDlwriXcYmk6ENZ4uuzM/4ohNg/6yzOW0DtnZMKIW6NilcJXvrxH/9xfuRHfgSAH/3RH73qgc0nPvGJ0a3uEJw+fXrcSzgQhzkyNegH+l1PWQTyGnS3I3OLmtvumIwcBzE6Mpp3Y4KPbK57+n1PszU5By7FwFOVcPd9GbX61TOrgo+srznKItBoHs76D2NkylSBfjdy3/05WX75z2VNYHPdY0ygfo3xPTG9Zmk0D8CYSL/juef1NWr16X7Mrg8sz64XhKBoT8jPUj/9AvHCOcqlq1Svr0LGpsSoyWNs9GKMdHtdBmWfLM2PZCFKRvMOV1lVvPvPfw+N5vRvjnGt0byrdkS95z3v2fv39773vQe7IjG1yiIMu6HKQF4fjq002oHuVmB+wdMYUxCzEJOoLCPWBtIJy22pNzTOBM6ddtx5r77qbnjGRLyL6DGPFB60NFNEIr2uZ2nlCoUoOyxGJTKFI6ZEloHWwzy6205M90WhbuUZ2MjyIRW/rysEdFVglBzfCHEUSTeUEKNx1cPsP/fn/tzevz/88MOHsRYx4aoq0Ot4qiKQ52rv5DXPFVUaWDvnuOtePfYcHCEmQYyRsghYE6lP2FibUormnKaz5dlcc6wcv/JueKaKE7n+W6W1Isuh1wksrVx+u7MR7yGvz9bPLWaXUoq8rul1A8fC9BaPQ4z0bQAiekJGDJOyT3QOn0gujBBHzaXZUNNd5Bdi0uz7eu+f/Mmf8MILL1CWl7bl/eW//JcPfFFi8lgT6G0HyjKQ5eqS4GKlhhlRnU1PZ9uzsCRtBEIYMwz5VpqJzGxJEkWrrdna8DRamlb70qv9IUSMiaAmc/23Ks8VRT/iXSBJX73CGWPE2oia0Z9bzK68pij7kW7Hs7A4ne/DAxMwLjBJdTRd9KEsCK2lcS9FCHHIpBtKiNHZ15HKL/7iL/Lbv/3bPPDAA+T5q9VgOUg/GpyNdHaKUEmqrrh7Vpoq6k3F2nlHa06Cy4UoB5GqimS1ca/k6vKaxhrP+dOOu1+nSbNXn7fWRJwLzOpxV5opQogMBoG5+Vd/SO+G2Vjy9iamzcWh5dNaiOoaT894WlfIbhuXpOzjIztbbgohjgrphhJitPZ1pPLlL3+ZT33qUywvL496PWLCOBfpbA2DybWGLLv62Vm9oTFVYP28nfqMCiFuhXMRYwKRSDIh249fTaOl6WwF1s5Zbrsz27vAUJURa6A2wYW0W5EkijSLdLc9c/OvvhVaG3E2oKWYLqZQXlP0u5GqDFMZWt4zHhsii+mEFNKcQ1UVQU3f71IIcWuslW4oIUZpX8+q1dVVskyuBB013ke6W56y9KAiWX7tEzOtFc2WorMVKAb+kFYpxOQpizAMKZ+CYobWitacprPt6Ww5AGIYZkMRI3rCC2m3Iss15SASw6ubxzobcW4Y/izEtMlyhdKR7U037qXcMOsDhQ1M0qtmUvbBGrx0QwhxpMQYKavdbig5IBBiFPZ1yelv/a2/xb/6V/+K7/me72FhYeGS29785jePZGFivELYKUJVnhjZ95XVLB92GVw467jrPj21galC3KwYIlUZcXZYmJ0GWaZoNBVr5zz1hgYU3seZHcvblWWKsh8oi0CjNczIsnZ2c7HE7FNKUdsJLV+9bbpCy7smUFpPPkG7jCZFH6qCMHds3EsRQhyi3W4oJd1QQozMvgpRzz//PH/wB3/An/zJn1ySEQXwcz/3cyNZmBifGHbG8cqAd+ycmO7PMLh8uBtXZ8uxuCxXEcTRUpZx2A2lI0zUtf1rqzc1xgbOn/UsLCaYKkx0vtVBSFLQKXS2h4Uo7yPeR4jX/1ohJlVeUxSDQL/rmVuYkBG3fehVnp4NrDQnZ81J2cejIUmu/8lCiJlwaTeUdEMKMSr7erf/5V/+Zf63/+1/4zu+4ztGvR4xZjFGup1AVQashUbzxq8CJKmi1lCsX/C02gnZBIWOCjFqVRGwJlJvTE8RCoZF5PacprPpyXbeGSY93+pWKaXIcs2gF4gx4uxwp0PJhxIj4R3J6eeJtQZh+faRhV8niSLPFZvr01OIijHSMx4VQU9IN6KyBozBKylCCXGUSDaUEIdjX8+uWq0mI3hHQIyRXidQFH7nRPrmv1ejoSHC+nlHjNJeII4Ga8JwtIvpHO1KEkWzrel2w7iXcmiyTOFcwJiItRHrIlkqr1ni4OnOBvR7qGe/QfLc11GdTRjR+2NeU1RlxFTT8Vwe2IDxkUnKBE+KHtgKn894a6gQYo9kQwlxePb1lv/BD36Qf/Nv/g1bW1uEEC75R8yOfi9QDgKmitQa6pZOpJVWNFqKbidQDORxIo6GsohUVSCb4k7uWl0ztzDsajwK0hRQ0Nv2ODMcy5vlgHYxJsGjOhtEY3G33Uvc3kY//YfoU8+BqQ787nZDy7c2piO0vGc8feNpZZPz3NPlgGgMsdEc91KEEIdEsqGEODz76tnezYH6r//1v1522xe+8IWDXZEYi0HfU/SHI3n15q0VoXblNY0pPRfOOe6W4HIx47yPVFUkBkjT6T54mfb13wilFXlN0esGmm09qgYVccSp7hZUJSGtQVbD334vqrdF8srzJJsbxLvuIyysclA7BOyGlnc70xFa3q2GHVHz9QkZJYyRpOjj0Ozzmq0QYsq92g1lpRtKiEOwr3f8xx57bNTrEGNUFmHYDVUE8vrBjhQ12sPMme0Nx9KqvKiL2TXMhgok2WSf8InLpami6EeCH4aXC3GgQkBvrxHLkrj46u5rsb2Ia7TRG+fQ3/wj9G0niLffS2y0DuRu83w6QstdiAysJ07QLgHKVGAtQfKhhDgyXu2GQrqhhDgE+zoyOXZMtq2dVVUZ6HY81U4R6qDDiZNEUW8q1tc8rfmEXILLxQyKMVKWEeemL6RcDHOiBiFS9AON9rhXI2aN6m9DVRHSnMu6a5KUcOxOYtlDnz2N3t4knLiXuHL7cFvHW5CkiixXbG5MdiGqZzzGBfIJ6tpKij5UFb52C2GZQoipId1QQhy+fR2ZDAYD/tN/+k+8+OKLlGV5yW3/+B//45EsTIyeqcJwh7wikOaKJBnNQWC9oTFlYP284/Y7s6kMcRbiWkw13HFNM50h5UedThRpHrEW2rJNuzhIMaK31ojFgLhw9Yt6sd7G39FEb19AP/cN2FofFqTai7d097WaYtAbhpbntcm8ENSrPD3rWahNznMvKXtEZ4hzS+NeihDiEEg3lBCHb1+FqE9/+tOEEPjO7/xO8nyKU3jFHmvjXhEqyxXJCLcrV2q4E1evEygWA8325BxsCnEQikHYOdEb90rEzWrNJYQwOaNBYjaoQReqgqBzrrslnNaEpdsI7UWSC6fR3S3i7XcTjt8J2c29uGS5AhXZ2nQcv33yjt9ijHSNJwRFOimbBIRAUhZYlQByYUGIWSfdUEKMx74KUc888wyf+9znSNPJbe0W++dcpLvlKcuAThhpEWpXliuyHM6fc9zT0OgRdV8JcdicjVg7TDeR3daml9Zq4gOdxfTRW2vEQUGcW97/F2U1/B33oXqbJC8/R7K1TrjzPuLCKtxgx+UwtFzR2w6sHp+80PLSRYyLTNIhga4KorP4RE5IhTgKpBtKiPHY17PtgQce4NSpU6NeizgE3kc6u0Uodq6WHpJGS2OqMDXbSQuxH2Ux7IbKJKRcCHERVfSg7BOGV3xu8IsVcW4Zd/t9xLJEP/1H6Je/CeXghteR5wrnIv2uv+GvHbWe8fStp5FNzslfUg6gLPH1+riXIoQYsYu7oVLphhLiUO3ryOgjH/kIn/zkJ7n//vtZXFy85LYPfOADo1iXGIEQhkWoqhgejGaHnBeRJIpmS7Ox7mnPJxObVyHEfoUQqcrhbmu1uhSihBCv0ltrMCiIrYWb/yZJij92F6rokpx+hWRrg3DiPuLybbDPPLMkVWS1yQwt71aeygXazclZV1L0CMFDJoUoIWaddEMJMT77euf/5V/+ZdbX1zl27BhFUex9XEJ5p0fcKUKVRSBEqNXH82JbqyuqMnLhnOPE3RJcLqZbVUasDejJOYcSQkyCqoBBl4CC9NazmWJjDndHC711Hv3s12F1bRhmvs8i125ouTWBbEJ2r/UhMrCBqCboeNJ7dFVglGRZCjHrht1QhWRDCTEm+zp9+spXvsLP/MzPsLQku4dMoxgjne1AVQa8j9Qb4zsIVWrYFdXrePq9hPacHOyJ6RRjpCwC1kbqjQk5iRJCTAS9dQHKgtCYP8BvqgnLtxPMAsn6mVfDzI/dCdm1i11JqggxUgz8xBSi+sZjfCC7Xoj7IUqqAdE6vJaTUiFm3bAbykk3lBBjsq9n3W233UYiW1pPpRgjvU6gLDzWTMb4UJYr8priwlmH97JLlZhO1kScjSgm6Gq+EGL8TIXqdQheMZKtNPMG/vbXEbIm6qVnSZ79H6jtdYhXfz9NEkWSRAY3HjE1Ml0T6Fae5iFmVV6PLvo7BcTmuJcihBihvW4oI9lQQozLvjqi3vWud/HP//k/5y/+xb94WUbUt33bt41iXeKA9LuBchAwZti1MSknzPWmprMV2Fy3rB6fvC2lhbieshjmQ93krupCiBmlt9d2ihmt0d2JUoSFFUJrnmTjDPrpPxx2Rx2/C2qNK35JmilMGUa3phvUMx4fI/kE7TaaFH18BOTEVIiZttcNpaQbSohx2Vch6otf/CIwzIq6mFKKxx577OBXJQ7EoOcpBoGyChNVhILh1dlGU7G1EZhbCNQkuFxMEe8iVRWIRJIJOokSQoyZs+jeFj6EqxaEDlSa4Y/fgxp0SE6+SLK1TrjjXuLycdCXdrIniaIsIjHGsR8PVC5QuYCeoOMSnEOZiiAnpULMtIu7ofJcLoYLMS77KkQ9/vjjo16HOGDFINDvDXOh6vXJKkLt2g0uXzvrOHGPBJeL6VGWAWsCaSKPWSHEq/T2GrEsCfkIu6GuIDbncfUWeusc+tmvE4+fIN5+D7E5t/c5SaKIPmCrSD7mMf2u8fSNpz5Bhfyk7IE1+FTaXIWYZRd3Q8m5hxDjMzlHAOLAlEWg1x3ukJfVQOnJfJFVStFsa/o9T783OeMCQlxLDJGyiHg/3BJdCCEA8A7d3SQ4B6Mcy7sanRCWT+BXTsD5s+g//Rr6zMvg7O7NRKUoS3/4a3uNXuUpXKQxQflQSTGASvKhhJhlF3dDZdfZ5EEIMVrX7Ij60R/90etWij/xiU8c6ILErTFVoNfxlGUgqymSCe/YyDJFra64cMbRaOqJX68QVRVxLqJ0BOTxKoQY0p2NYTdUOt5CRqw18Xfch95eR7/wpyTba4QT95HMLQ0Dy/swvzi+9YUY6ZuAIk7UaF5S9vEkl400CiFmh7Fmb6c86YYSYryuWYh673vfe1jrEAfAmkh3O1CWgTxVJOl0vMA2doPL1yyrt8nVCTHZyiJgy0CtOR3PLyHEIQge1dkgGguv2dRlLJQmLB4jtBdJ1k6je39EvP0u0rl7MdV4O5D7JmD8ZOVDKWvAGLySQQEhZlWMkaoqJRtKiAlxzULUww8/fEjLELfKmkBneziOl6SKJJucA7zr0Ymi0doNLvfU6nI1UkwmayLWRJBcASHERVR3C6pyJ19ogl4b0gx/+72o/jbJi8+Q3tOgaN8+1sDynvF0jaeVT07RJyl6YCp8LvlQQswq6YYSYrJMzlGAuGneRTbWK6oioNPhuNu0yWsKrSMXznlijONejhBXVBYBUwXSCco1EUKMWQh7IeW0567/+WMQWwvE9gLZ2ReI1mOr8b3P9ozHhUgtnZxD0KToE40hSj6UEDPp4m6oTLqhhJgIk3MUIG5KCHGnE8oDcSqLULAbXJ5Q9D3d7fEHqQrxWsFHqioSAqRTMvYqhBg91d+GqiKkNSb5sMrPLaPLPmyvURTjeZ81PlDYAJN0wSlGdDnYGcub3L+fEOLmSTeUEJNH3nGnnNaKWk0RQySvT/efM80UeV2xdt7j3QQdpAoBlGXAmSCB+kKIV8WI3lojFgNia37cq7m2rIaenyPbOE3RdWNZQs8ESuupZZNzvKJNCdbi9TXTKoQQU0q6oYSYTFc9EviRH/mRvX//t//23x7KYsTNabYT0gk6qLsVjaYm+Mj6mh33UoTYE2OkLCLWRjKJEBFC7FCDDlQFQecwBUHXfm6ZxA4wZ8+N5f57ladnA+18crIgdTEYdrTl9XEvRQgxAtINJcRkuupR0+nTpzHGAPAf/+N/PLQFiaNN62FweWczUI1pdECI1zJVxNmI0nIQI4R4ld5aIw4KYmsys6Euk9VImk3cmTMEe7gXfGKM9IxHRSZqx7yk7BGcIdalECXErJFuKCEm11X7kN/+9rfz9//+3+f48eMYY/ixH/uxK37eJz7xiZEtThxNeU1RlYHz5xx33aNRenIOWMXRNAwpl24oIcSrVNGDckBQCSRTNNY1N088s455+WXqb3jDod3twAYqFyercSwEkmKAVQkTtduhEOJASDeUEJPrqkdOH/nIR/jTP/1Tzp8/z7PPPsuf//N//jDXJY6w3eDy7qan0/EsLE7RAb6YOc5FjInEGEmSSTqDEkKMk95ag0FBbC2Meyk3JMkzYqNF+czz1O69F5Uezntsz3j61tOaoCgBXRVE5/DTVEgUQuzLxd1QuXRDCTFxrvnO+8ADD/DAAw/gnOPhhx8+pCUJMdyVrNZQrJ/3tNqJ7FImxqYsArYKU7sjpRDXZCrIpdXvhlUFDLoENKTTdYKjNahWm2pzjXDqJZJ7D6crqlsFrI8s1Cen6JMUfahKfKM97qUIIQ6YdEMJMdn2dTTw3ve+l69//es89dRTbG5usrS0xLvf/W6+7du+bdTrE0dYvanpbAXWL1huu2O6DvTFbAghUpUR74c7OgoxS1S/gz7zEmHxGHH19nEvZ6rorQtQFoTGdHVD7UryjLKxBM/9KfHO0XdFWR8ZWE9ksnbETco+wXvIJB9KiFmy1w1lpRtKiEm1r/7o3/iN3+Bf/It/weLiIt/5nd/J0tISP/MzP8MTTzwx6vWJI2w3uLy7FSgGElwuDl9VRqwJaD1ZJ09CHATV34beNvrZr8P2xriXMz1Mhep1CF7BlJ7gJDpgaovEwYBw6qWR31/feIwL5JOU+eg9uirwenJ28BNCHAzphhJi8u3rEtiv/dqv8Y//8T/mvvvu2/vYO9/5Tj71qU/xyCOPjGptQpDnCpNGLpxz3HWvRk/SQayYeVUZsCZSb8rjTsyYENCDLl5lqDSQPPNH+G95G0zL7m9jpLd3uqGa0zvOlehISHLc3ArZc38y8q6orvH0jGehPjlFn6QaEK3DJ9m4lyKEOECXdENl03mxQIijYF8dUd1ul7vuuuuSj504cYJerzeSRQmxSylFo6Upi0BnS7qixOGJMeIdRORqmpg9quwTrSVmOX71TmIYFqOoinEvbbI5i+5tE0KAfHrHuRIVUQrK5ioUxUi7omKM9CpPBNIJ2vBBF/1hQbHeHPdShBAHSLqhhJgO+zoieOCBB/j85z9PVVUAlGXJ//1//9+86U1vGunihIBhcHm9oVi/4LA2jHs54ohwDoIfnqwJMWtUfxuKgthogdb4Y3cTy4Lk6f8B1ox7eRNLb68Ri5KQT283FAwDyxMVKWIdFpfguT8hOjuS+ypcwPg4cSeESdHHoyCVjighZsXF3VCZdEMJMdH2VYj6G3/jb/DSSy/xAz/wA/yNv/E3ePTRR3nppZf4m3/zb456fUIAUG9oYoSNC27cSxFHhLMR6wKJ7NgoZk2MqH6XgILdsaQkxR+7Czqb6Be+AV46UC/jHbq7SXAOGtPfRZPogLEJamEJqpJw6sUD+94+DLugzvcspzuWnvE008nphsI5lKkI8vIuxEyRbighpse+AgGWlpb4xCc+wfr6+t6ueSsrK6NemxB7tFY0W4rOVmBu0dNsTk7OhJhNzkVm5HxTiEuoogfOEvVrOkGyGv743STnX0ZndcK9bxq2zggAdGeDWBSEbDZeFBIdKW0CaQ7zi/DsnxLvvA91Ex1CxgcGJjCwgb71VC5ifKBvPDYMN3uYq412Z74bkZQ9MAafTu94pRDiUpINJcR0uaGjgpWVFSlAibHJckWaRS6cddx9nwSXi9FydnjyJFfUxKxRgy4UA2Jr6bLbYq2BXz1BcvpFVJ4TT7wOmU8FgkdtrxOtG46yzYBER0JUGKfIF5aInS3CqRdJ7n3jNb8uxEjpAn0TKHYKT9ZHSuvp28DuHqOZ1tRTxWI2OQWoXUnRJ5qSML867qUIIQ6IdEMJMV0m7+hAiKtQStFsaTpbns6WY3FZch3EaIQQcS6yd0YlxKyIEdXvEIMadsJc6VMac4TFY+gXnyHkdeKxE4e8yMmjultgKnxWB2bjBGcvsNwm1Jo58SpdUdZHip0iU7Hzj9n5WOkjarilA3kCi/VkogLJr2aYD6VBS3e1ELNAuqGEmD5SiBJTJUkVtYZi/byn1U7I8sk/4BXTx9lICHKOImaPKgdgDSG59tt/mFsGb9HP/TE+y2Dx2CGtcAKFMAwpL8uZ+j3sBZabhIWmQy0sE7afY/Di85QnXs/ADkftqp2w8YFx2DgswyUK6qlmtZZMXeeBsgasxcvYqRAzQ7qhhJg+1y1EhRD4xje+wQMPPECaSt1KjF+jobFVYP284/a75KqHOHjOgTNBNlMSM0cNOlAWxMbCdT83LBxHWUfyzNfx3/I2aM8fwgonj+ptD8O80xr73ONlaigV2DYaVUHhM/q127FPv0KZHKeIihhBEckSTauWkE9Bt9P1JEXvou42IcS0izFSSjeUEFPnukcUWmv++T//51KEEhNDaUW9peh2As6EcS9HzCBnI95DOkm7PAlxAFS/Q/QRsto+PlnhV+4gRkXy9B9CORj9AidNjMNuqKIgtqa/EGdCZNtFzprIi2XkZRN4pdB8s6t4vq+4kLax/T7Z+ZOsNFOOtzOOtXMWG+lMFKFgNx/KEBuNcS9FCHEAjDV46YYSYurs66jiW77lW3j66adHvRYh9i1NFUQYFFKIEgfP2Sj5zGL2lAMwhpAMW/2cd6x3t+gUfaxzV/4arfHH7iSaiuSZ/wG2OsQFj58adKAqCEkOajoLMSZEzpvIs0Xk+RJeKuDlEi5UMPAR7xU1FMdqsNLMmF+cY/HcS2jvx730gxcjuujjlWbWutuEOIou7obKpBtKiKmyrzanY8eO8clPfpKHHnqIlZWVS6rNH/zgB0e2OCGuJkkUSRYZdAPz158wEWLfvI/4EJGkcjFr9O5YXn0OgMJU9KqSorNFPa/RqtVp1urUsxrJxfk5SYo/fg/p2RfRz32D8MZvh+tkTM0KvbVGHAyIc9O1u1qMkX6ALQc9D2UA64ell1wpljSkejh6V0VNEhJgWIy07SXS7hbZuVewd75urD/HQdOmBOfwEgAoxEyQbighpte+jiSNMbz97W8HYGNjY6QLEmK/0lRTllIsEAfL2Yh3ET0jYyhC7BqO5QXI68OryNbgg2eh1aYyho3+Npv9Ds28TqvWoJHXqGX58OA+zXDH7yY99xI6rxHu+zMzn+avih6Ug2GwezIdP6uLkY4bFqDKAAM/DBevK8VCdvlJmlLDnCjvXi1ExTTDzS2RnnwRd9tdxBkKy9NFH6qKUJOxPCGmnWRDCTHd9lWI+shHPnJLd7K2tsbjjz/O1tYWSikeeeQRvu/7vo9er8dP//RPc+HCBY4dO8YP//AP0263AfjVX/1VnnzySbTWPProo7zlLW8B4Pnnn+fxxx/HGMODDz7Io48+ilIKay2PPfYYzz//PHNzc3zsYx/j+PHjt7RuMdmSFEw/4lyQLB9xYJyNWBPJ6zAr27QLQVWAqQh6+LZfOYvzHq0UWikatRoNajjvKUxFvypIk3SnS6pBI6uR5XX86l0kp18eFqPufD2zPMOqt9agGBCbi+NeynWVIbLloOOg8lCF4c52C0qRJtf+G2kd8eHSQpttL5J2N0nPvoK96/WjXPqhSoo+wRni3NK4lyKEuEXSDSXEdNv32fvJkyf5d//u3/G5z30OgNOnT/PSSy/t62uTJOGv/tW/yk//9E/z4z/+43zxi1/k5MmT/If/8B/49m//dn72Z3+Wb//2b+c//If/sHdfX/nKV/j0pz/Nj/zIj/C5z32OEIZZQD//8z/Phz/8YX72Z3+Ws2fP8rWvfQ2AJ598klarxWc+8xne//7380u/9Es38GsQ0yhNFSFAITlR4gA5N+yyS6QjSswQPegOx/JqTQBKU1E5Q/6ajUjSJGGu0WSh2SZLE7pFnzObFzi1eYELnU16WmMWV1EvPYO6cGocP8rhKAcw6BJiAulkXmkPcRg8/lIZebGEMyV0LBAVS6lmMdXXLUIBaBXxQRMvajDe64o69SLK2dH9EIcpBJJyQFApcpFBiOkm2VBCTL99nWn99m//Nj/2Yz/GxsYGTz31FABFUfD5z39+X3eytLTE618/vKLWaDS488472djY4Ktf/Srvec97AHjPe97DV7/6VQC++tWv8s53vpMsyzh+/Di33347zz77LJubmxRFwZve9CaUUrz73e/e+5rf/d3f5eGHHwbgHe94B1//+teJUca2ZplOQCeRQVf+zuJgxBiZlXMuIS6m+h2i81Bv4EPAOEuMkeQq43VKKWppznyzzXyzDTGy0d/m1MZ5TlvHWlajevqPYOPcIf8kh0Nvr0FZEBpz417KZWyIXDDD4PGTFZw3MLDQ0IqVTNNOFfoG6ixKR4gQwqVfZNuL4CzpmVcO9gcYE10VROfwRyTfTIhZJt1QQky/fb0b/8qv/Ar/5J/8E+677z5++7d/G4B7772XF1988Ybv8Pz587zwwgvcf//9bG9vs7Q0bI9eWlqi0+kAwxyqN77xjXtfs7y8zMbGBkmSsLKysvfxlZWVvcyqjY2NvduSJKHZbNLtdpmfn/7tlsWVKaXIckVZSkeUOBjeQQiyY56YMaba2fltZyzPGqxzlwaSX8NrR/dKY+iHSN1Ymn/4/6P+wIM0Vm+bnavSpkL1OgSvIJ+cn6nv4174eOHBBsiUYnEnePxmKRUBhbMJSfLq7ol7XVGnX8TdcffUZ0UlRR+qAj+BxUUhxP5JNpQQs2Ffhajt7W3uvffeSz6mlLrhCnRZlnzqU5/iB37gB2g2m1f9vKt1Ml2rw+lKt11pfU888QRPPPEEAD/xEz/B6up07YRzNWfKgoWFo7d9XJ45eh3H0uIiieREjVyapjPznLmSQd9RDgoaDUWtLo+ncUiS5Ei+lo3UxjlikmCXVtGNFoU36EzTrrVu6kryHMP3XDO/iDv7Mt1v/h6l/3baK8dpt+ZoNlskE951cs3H2dmXCVrhV46jGuMNtfYxsm0jGzZSEBgoRUgi85mikdz4cdjVKJWQZZp22116Qz0nf+UZ6p11wuv+zIHc17hknQv4vIZeWrn+Jx8QrTXtduvQ7k8cPUfxMVZWJVmeAjVqtfq4l3MkaK1pNOR3fVgisLqyQqN19XrJLNjXkeLrX/96nnrqqb0xOoDf+q3f4v7779/3HTnn+NSnPsW73vUuvuu7vguAhYUFNjc3WVpaYnNzc697aWVlhfX19b2v3djYYHl5+bKPr6+vs7y8fMnXrKys4L1nMBjsBZ9f7JFHHuGRRx7Z+++1tbV9/wyTzPsGvX5n3Ms4dM5Gej3PqVOWZms6djWaZqurqzPznLmSbsezteGoNxVlJW1R47CwsMD29va4lzFTkrOniNsd/FIdu73NdrdLWVXoeOuPcb1yB7W105hnvs7Jzt2Q5TTqTVqtORrNFrW8jt5n59VhuurjzBrSsyfxvT5hoQm9/uEvDqh2wse3HRg/3AFPA22tyBIFHsoDHCO2NsFa0MngstvyrEX69B9Tzi0Tp7X7wHua6xcwlcEe4t+03W7RG9NjSBwNR+kxFmOkMhVlVVJWJXmWUxTluJd1JDQadfldH6KqqlhbX6dRXP6ePG1OnDhx1dv2dXT46KOP8v/+v/8vP/ZjP0ZVVfz4j/84X/jCF/hrf+2v7WsBMUb+5b/8l9x55538pb/0l/Y+/tBDD/GlL30JgC996Uu8/e1v3/v4V77yFay1nD9/njNnznD//feztLREo9Hg6aefJsbIU089xUMPPQTA2972Nn7zN38TgN/5nd/hW7/1W2Vm+AhI0mFWVL8r43ni1nkbQUnegJgh1gxDynUCKEprMM6QHdSYlU4wK3dQd57jnXVatQbGVpy/cIbTp17i3LlTdDqbGFMdzP2NmO6sE4uSkB9+h0GMka6LvFxGXijhdAnbFsJO+PhSpodFqBG4UmD5LtteAO9Jz7w8kvs+DEnZJ1qH19M9XijEUWWsodvr0C/6lFVBohM5VhNiyu2rI+rOO+/kX/yLf8Hv/d7v8ba3vY2VlRXe9ra3Ua/vr0Xvm9/8Jk899RT33HMP/+gf/SMAPvShD/E//8//Mz/90z/Nk08+yerqKh//+McBuPvuu/nu7/5uPv7xj6O15gd/8Af3rqj+0A/9EJ/97GcxxvCWt7yFBx98EID3vve9PPbYY3z0ox+l3W7zsY997EZ/F2IKKaXIMkU5kEKUuDUhRJwfhvYKMStUvwOmImSNYa6GqfAhUKsdXGdLTFKqlduorZ2hlZ4kvfP1xKbaOXHYptPdopbXabXaNJtt6vXGZI7ueYfubuKdg/bhtcO7GNl2sOWgCjDwoCI0taKeHs6JltIRnCIERZJc+iL4albUS7g77pnKrqik6A/D5+eWxr0UIcQNcN5RlAXOWiprUECe1aQIJcQMUPEGtpbb2NjYG5PbHYmbdqdPnx73Eg5E2T+ao3kAZREoi8gb3lRD3UJgq7i+WR7NMyawte4xVaDenLxRoqNCRvMOVnL6eeKF8/il41TWstHrUFlDo1Y7+PuqBtQ2zuGPn8Dcfi+7qf8xRopygDEVSqm90b1Wa25s+R5XepzpzfOos6/gVA7Ny0f7D9pgJ3y866HywyJUCrQTdUvh4zcjRqiqnEajoFZ3l92uvKNx+gXc3a/H3rP/WIZJUT/5LGFjg2rx2KHe71EamxLjMauPsRACZVVQVRXWWUKIpGlKkkgMxzjIaN7hKquKd//576HRHG9O5UG41mjevi5Jrq2t8bM/+7M888wztFot+v0+999/P3/v7/09jh073Dd1IV4rSRUhBKoqUm9IIUrcHGfBmkAikxtiVjgLxYCoNcOxvIrKGvJ0NN1IvtbELB4jv3CaLKthV+8Ahp2rzUaLZqOFc46y7NMf9Mi31rnzzvsmI2w2eNT2OtE6WBxd10yIkY4fdj8VYbj7XQhQV4qVVI1tx06lQKuAdwlweSEqJunUdkUpZ1HG4KWDQoiJd3EOlHMW5x1pkpJlE9hFK4S4Jfu67P/444/z+te/nn/9r/81v/ALv8C//tf/mje84Q08/vjjo16fENeVJsOD6EHPj3spYoo5G/EB0kMahRFi1C4eywshUFlLII70irJrtLHtRdLTL5JsrV92e5qmtNsLLC4sY2zFmTMnCWH8o9Wqswmmwmd1YDSvAT4Os59OVXChgoGFllKsZJrWGItQu5SO+HD1x4adW4TgSU9PV1aULvtgDCE9+C5AIcTBMdbQ6XXoDXqUVUGIkVpen8xRbiHELdtXIer555/nr/yVv7KXCVWv1/krf+Wv8Pzzz490cULsh9LDnKh+f/wnM2J6OTecUpbcATEr9KBLNAaaTUpnsN6RqNGPndr2Eq7eIj/5LLp35TFLpRRz7QX6/Q6bm2Me9w1hGFJeFtAa3UjehoW+g8opllPNcqbJJ2ic/FqB5XBRV9SZl1DWHO7ibkFS9IlVSWjM9jbYQkwr5x3dfpdev0tRFnjvyLPawW2qIYSYSPs6In3jG9/Is88+e8nHnnvuOd70pjeNZFFC3KgkVZgqcgORZ0Ls8T7ifRxRH4QQY+AdquwTVQpoSlNhnKWWHc6BvVlYxac5tVeeQZdX3n44TTOazRbnzp+ivMrnHAbV24aqJKQN9nlYdMNcjGw6MAEWU8UE1Z/2KB0hDgPLr8a2F6euKyop+gSlhlvsCiEmRgiBftGn2+1QFAOMtaRpKmHkQhwRV+11/MIXvrD377fddhuf/OQneetb38rKygrr6+v8wR/8AX/uz/25Q1mkENeTpsOd86yJ5DV58xI3xtmIdxE9iWeHQtwE1e8STUXIc5z3GDfM/Tm0g3ulqBaPU984Tf7y01T3fQsxv3w0qtFoUVnD6TOvcO899x9+EG2M6O0LxLIgzo8u83LTQumhpsY/gnc1Sg0v5DibkCSX50TBpV1R7sTkZ0UpU4E1eCVFKCEmRYyRsiqpTIV1Bu/9MAdKRvCEOFKueulvfX197x9rLd/1Xd9FlmV0Oh2yLOM7v/M7MWZ6WrPFbBu+dykGfcmJEjfOuYhzkTSXjjoxG9SgQ6wqaLQpbYX1luywizxaUy3dDqakdvJZlLOXr1Mp5tvzFEWftfVzh7s+hr8nqpKgcxjR2OJeN1SEVjKhVSheDSx37tqPE9teBO9JT794KOu6FclOPpTPJyAQX4gjLsaIMcMcqP6gT1EWEJAcKCGOqKs+6z/ykY8c5jqEuCVaK5IsMugFFpfHvRoxbZyNRA9JMvr8HCFGznt00cOrhLizW54LnuYYTsZjklIu30F97TT56Reo7nrDZSNSSZLSbs2zvn6Odmue1ghzml5Lb60Ri4LYXhnZfex1QzG53VC7lI6EawSWw05X1Pwy6ZlXcCfum9yuqBhJ+sOctLi0MO7VCHGkOecoygLrDMZalFLUchnBE+Io23f5uaoqzp49S1mWl3z8z/yZP3PgixLiZmSppiylo0XcmBgjzkGUYyExI1TRJVpLTGtY73DOwxhfGmOaUy3fRn39LHmaYu6477Luo1qtTlWVnDn7Mq+7702HcnVcDbpQDAg6gRF1i+12Q1URVia4G2qXVhHrE2LkmkUz214g7WyQnn4Re+/k5YUqU1G7cAo16GP1MCdNCHH4fPCUZYnZySmMMZKlGVrLc1KIo25fR3pf+tKX+MVf/MVhgFx+6ZWvn/u5nxvJwoS4UUkKZRFxJpDm8gYn9sd7CD5OZHiwEDdD9TtQFMSFYxRlQeUM+Zh3Hwp5g2rpOLULZ8myGvbYnZfcrpSi3Z5nc3ud8xfOcPttd438SrneWoNiQGwtjuw+druhGlPQDQU7geVOEbwiSa9evZzYrqgYSTsb5BvnCYMBFRo/vzTuVQlx5LyaA1VijcUHT5qmMoInhNizr1eD/+f/+X/4B//gH/Ad3/Edo16PEDctSRVERX8QWJBClNgnZ4f5UBJULmZC8OhBF681QWkqZwgxkh52PtQV+HoLM79EfuZlYpbjFi8NB0+ShLnWPBsbF5hrz9Nuj3CcquhD0SOgIR1NEeXibKjlKeiGgosCy11Ckl45sHzXpHVFKWvI106j+13coMA02sRaY9zLEuJIiTFirKGsSqy1OGfROqFWk5w2IcSl9lWIStOUN7/5zaNeixC3JElezYlaWBz3asS0cDbibKTenI4TRSGuRRW94ViezqmswTqHnqBWHNdaRDtHdvJ5otLDQoHWRKVBKWpZTpXlnD79Cq9/fZN0VJ1cm+ehKAiN0RW7NiwUAepT0g0FlwaW17h2Ieririh7x32Qj68rKuluUVs/SywGGB9xCysjC58XQlyZdZaiLHDOYq0FFLnkQAkhrmJfhagPfvCDfP7zn+cDH/gA8/Pzo16TEDctzTSV5ESJG+Dc8PEiB0piFqh+F8qCOHeMsuxjnKWR18a9rEuY+RXUpic/+Rw0W4ACrfdCiWrARlmw0d/g9pXbUUkCShN3/h+984/SRJ1c+b+VHoaiX/R9X11ASextE6IaWfHExciWAxtgbkq6oXbtJ7B8125XVHbqBezrxpAZ6hy19TPo7ja+GFDlLWKrefjrEOII895TVgXGmJ0cqECeSQFKCHFt+ypEnThxgl/5lV/hi1/84mW3feELXzjwRQlxs5IETBlxLpCmcjVUXFsMO0HlUrsUsyAE1KBLQOMVVNYCE1hkVYpq6TjKGJS3qBDBeVSMQESFQCPAxoULNCrLQm2nkBaH/6OIe+HrKtGgdgpOyUVFqouKW0q/pkAVAjFYQmN0u/NNYzfUrv0GlsOwK8ouLJOdewV74j6oHV7RM+l3yNfOQDHAOI9rL48sdF4IcbkQA1VVUpkKay0+BLIkRScTkhknhJho+ypEfeYzn+Hd734373znOy8LKxdikqSpIsRIMQjMzUshSlybc3EYVC4PFTEDVNkHa4lJTrGzQ9EkZENdkVLEWo3IlQsXCkjLAae8J58/Tp5dYUQvBgh+d8cBVAjgHbgwvC1G1M7/s1O8UjsVLDe/BPloMkv2uqE8zKVTVoVi/4Hlu1xrgayzQXb6BezrHhj9Ar0nXz9L0t0aBpJndeL84ujvV4gjKoRAjJEQAiEGYgyEELHWYJ3FOYdOEmoT1n0rhJhs+ypE9Xo9PvjBD07eVVUhXkMnkOjIoBeZkylScR3OgbWBZLwbiglxIFR/e7gLXHuZsujjg5+4sbwb0aw12O53Obu9xl0rt1+edaV2uqB2nsBXKplcrYyi2y3o9Q90vbvWd7uh9PR1Q8FuYHncV2A57HRFzS+TnTuJPfG6kXZF6aJH7cJpGAywxmLbi5DKLlxC3IxLikshEmJ4tei09+87txGJIeKDJ4SdQr9SaK0lB0oIcVP29e798MMP89RTT/Ge97xn1OsR4pYopUhzTVmGcS9FTAFnI8FBXpMDKDHlYkQNegQUBnDeodQEjuXdAK0U7UaT7X6PrX6H5VHuondAXIxs73RDzWfT+bsfBpbHfQWW7xp2RW2OrisqBPKNcySdTWK/T5XVCIsrDHvnhBAXizFeucgUAzEEws5tMQQikRAjMQS89wQiamf6WcHOfG5EoYfvKVqTZzlaWsmFELdoX4WoZ599ll//9V/n3//7f8/i4uIlt33iE58YxbqEuGlpCkU/4n0gSeSNUlydtRGm/GRdCNgdyzPEJKO0FZWzZMn0d4pkSUqjVuPc9gbNvE59wju8Lu6GmmY3ElgOF3VFnX3lwLuidDkYdkEVfVxZYdoLkEpMhBAhBopiwKAY7HUv7RWZYiBGCDsdTCGEneLSsLC0W2AChVYKpTRpmqG1lmMiIcSh2NdR6vve9z7e9773jXotQhyIJFHDAMUyDjdkEuIKgo94H+WCupgJqt+BYoBvLFKWw7G8ejYbJ+vNvI51jrNb69xz7Ha0mswLDDZMfzfULq0i1u0vsHyXbQ+zovJTz2Ne/y23vogQyLYukG6tEwcDKp0SFleRF20hhoqyoIiBTrfLbn1paGcsWA/LTjpJ9opMQggxKfY9mifEtEjS4eZI/W6g2ZrQoF4xdtZFgpduKDEDYkT1O8SoqADn/cQWa26GUop2vcnWoMt6t8OxCQ2m3nDDbqjGlHdDwU5gOfsPLAdAJ3tZUdz5OqjdfBi8qkpqa6dQ/R6uMphmG7LRhMsLMY2cc5iqAg31emPcyxFCiBu2r0LUk08+edXb3vve9x7YYoQ4CEopskxRDiQnSlydtxFrAlkN5Aq7mGrVAKwl6IzSGiprqV1pl7kpliYJrVqDC50NWvU6zRHteHezZqkbCm48sHzXq11RL9xcV1SMpNvr5JvnhzvikeAXloHZKawKcatijAzKAdZZWq0mxuz/OSqEEJNiX4WoL3/5y5f899bWFmfPnuWBBx6QQpSYSEmqKIvhDh9qBq5Oi4Nn7XBXd8kRE9NO9ztQDnC1NqYogEgygyMY9SzHWMvZrTXuXT0xUT/jhoPBjHRDwc0FlgO31BWlrKF24RRq0MMVBVVjDias4CjEJKhMhXOWECNJksKNPEeFEGJC7KsQ9WM/9mOXfezJJ5/k1KlTB74gIQ5CkiqiD1RVpN6YjRMDcXBijDgXr7q1uxDTRPW7xBApUVjvSPRsjiQrpWg3GmwNuqx1N7ltYWXcSwJe7YZyHhZmoBtq140Glu/a64o6+QLmDfvriko7G+Qb54mDPlVU+PkVmKHxUiEOig+esiox1pBnk715gxBCXMtNv8s//PDD1xzZE2Kc0gTQ0O/5cS9FTCDvh2Hls3PKKI6sqgBbEVRGaSqsd+Tp9O+WdzWJTmjXmqx3t+lXg3EvB4D1GeuG2qVVxHtNvNGK/U5XVHLuJFTlNT9VOUvt7Etk50/hOh2KtIGfW5IilBBXUZQF1hgSlUjGpRBiqu3rnX5328/df8qy5IknnqDVki3JxGRSepgTNehLTpS4nLMR7yJJIgdxYrrp/jYUBSbPsd4TUTN/cpKnGVmacHpjDefHe7Hh4m6o5oy9nlwcWH6jbHsBFOQnX7jq5yS9Leonn0NvrmPKimphhSihy0JclbUWaww+etIZywEUQhw9+7ps+qEPfeiyjy0vL/PhD3/4wBckxEFJUoWpIjHGmT8xEzfGuYixkXodJKhcTDPV7xJ9oMwUxhpqM9wNtUspRbvWZKvf41xngxOLq2N7jV93UM5gNxTcfGA5MOyKmhtmRak7X0esX5T15B21tTPo3vYwkDxvEuXCphDXtBtQXllDmkgRSggx/fZ1xPrYY49d8t+1Wo35+fmRLEiIg5KmirIfMCZSq83eSYK4ec4Ox/K0BJWLaWZKMCVeJ5TW4GKgluTjXtWh0FoP86J6XebqTeYbh1/IuLgbahZ2ynutmw4s32HbC2TdDbJTr2ZFJf0O+fpZKPpY47DtJUhmv3gqxK0qqxJrLUopkmQ2cwCFEEfLvt79jx07Nup1CHHgkhRQUPQ9tZoUHMTQMKgcCSoXU2+4W15JqTOcs+gj1vmZpxn1LOPM1gUaeY3skAsas9wNtUvfZGD58IsT7PzKsCvqxL1kvU2Szhah6FMlDeLC4oGuVYhZ5b2nqkqcs+S5BJQLIWbDNY/aPvGJT1zzi5VS/OiP/uiBLkiIg6K1Islg0AssLo97NWJSOLsTVC61STHlVL9DdI4yz6mcmemQ8qtp1uts9Xuc3VznrpXjhzaiZ2a8G2qX2umIinHYIXWjbGuerLNO/dmvQ55jjcW2FiGV0SIh9qsoBxhn0akElAshZsc1j1rf9a53XfHjGxsb/Of//J+pqmokixLioGSppiwlJ0q8yrmIdWG4s6IQ08pWUBVYlWCcI8ZAoo/eg1orzVy9yfagz1a/y1L7cGID1i0UHuoz3A0FrwaWe6dIs5voI9UJZvEYaWcTk9YJCytILp8Q+2eswVhD8IFaTbqhhBCz45qFqPe+972X/He32+VXf/VX+Y3f+A3e+c538oEPfGCkixPiViUpFIOIs5Esl4NfMcyHChbyljwexPRS/Q6YilIlWOeOZBFqV5amNPKcc511mrU6tWy0OVkmRDoeXICFGe6GglcDy71PSLMbz4kCcK0FXGvhYBcmxBEQYqAoC4y1pNnR63gVQsy2fb2qDQYDfu3Xfo0vfvGLvPWtb+Unf/Inuf3220e9NiFuWZIqQDHoexZymcUSw44oFNIhJ6aa7neJxlJkdUxlaRzx3JBmrY4dOM5srXHP6h0jzcva7YZqzng3FNx6YLkQ4uaVZYm1BqU40hcbhBCz6ZqFKGMM/9//9//xH//jf+TNb34z//Sf/lPuvvvuw1qbELcsSYbjBIN+ZGFp3KsR4xZCHBaihJhmzkI5wESFdR6QwqpSina9wdagx2Zvm5W5xZHcz1HqhtqldSR4OQkW4jA576hMiXNOAsqFEDPpmoWov/N3/g4hBL7/+7+fN7zhDWxvb7O9vX3J53zbt33bSBcoxK1KM01VSvFB7IzlBSSoXEy13bG8gdIYZ8kSCX4GSJOUZl7nXGeTVq1BfQQnb2sWBu5odEPtUiri/M0HlgshbkyMkaIYYK0lTdMjf6FBCDGbrlmIyvNhzsJ/+S//5Yq3K6V47LHHDn5VQhygJIWqiDgXSFOpQBxlzkWsCWRy3i6mmO5vE6qKMq3hraFWkwf0rkZewzjH6a0L3Ld6Aq0P7jW/CpGuBx+hkR6dE8NbDiwXQtwQYw3WWUKMZIlkQwkhZtM1X90ef/zxw1qHECOTJopIpOgH5hakEHWUOQvBQ9KQx4GYUs5CMaAKCucDSnYgu4RSirlGg81+l7XuFscXlg/se6/vdEO1jlA3FAw7ohTDrqibDSwXhyPBUtc9Mm2oQpMitAB5v5smIbwaUJ6PeOMFIYQYJ3l3EjNPJ5Akw5wocbRZG2W0REw1NeiCNQyUorKGPJWr5a+V6IR2vcFab4t+VR7I97y4G6qeHK0XEaWGxSjvJCdqUmkcLb3FfLpOS3do6A4r6UkWk/Okqhr38sQNKKoC5yxaaxnJE0LMNClEiZmnlCLNNGURxr0UMUbeRYIf7pgnxLTS/Q6+LKnShEAkSaQ4cCW1NCfVCWe3LuCDv+Xvd1S7oXZJYPlk0jiaepv5dI2G3iZXAxyaMsxThjZzySar6UmaegvFrT8PxGhZZzFVhXOWLJWRayHEbJNClDgS0hRMFfFeilFHlXMR7yL6iJ5IihngHarsU/iA9YFEUvevariLXpPKWs5vbxDjzXfEVjs75R3FbqhdSkV80NzCr1EcIIWnqTt7HVA11SeiMbFFZDjO5cnphSUisJKdZik5Q66K8S5cXFWMcTiS5wxZKiN5QojZJ0ex4khIUkWMkaqQo+ijytqItVHCdsXUUoMu0RgGDHfLq0nq/jUlWtOuD/Oi+uXNn4CvWyiOcDcUXBpYLsZH4WnoLgvpGk29tVOAAhPbBK5UvFCY2GbgF2kmXVazk8wl62gk62vSVKbCOguAlk5XIcQRIIUocSQkyTArqteTjqijytlhASpJ5GVPTCfV72CLAWYnF0ryQ66vluVkacqZrTWcv/HRJOmGGro4sFwcPkXYKUCtv6YA1cJfsQB1qUBCPyzhYsZico6V9BR13QPkwswk8MFTViXWSjeUEOLokDMycSQopcgyRTWQQtRRFGPEOznkFlMseHTRY+A9NngyuWK+b+1aAxc857bXb3hEb026oQAJLB8XRaCue8wnazT1NjXVQxExsUmgdsPfzcYG/bBEpipW0pMsJBdIsCNZu9i/oiyw1pCoRC4wCCGODNluRxwZSaooi0gMEXXETyqOGucg+Ij82cW0UoMewRiKoHF4mnl93EuaGnpnRG9r0GWu3mK+2drX112yU14qLx4SWH6YAjVVUNd9UmVIlSHEBBOb3OqOGxFNERdIomE+WaOue3T8CmWYI8r16UNnrcUagw+emryuCyGOEHnHEUdGkiqij1Sl9MUcNc5GrAtoOZkUU0r1tzH9Hi7NpLXvJuRpRj3LObN1AWP31wGyZqHw0D7CI3kX2w0sD9JYPEKRmhqwkKzTSrao6x4aj4lNHHUOctvXYZj5MprASnaaxeQcmSoP7PuL64sxMigHGGtIE8n8E0IcLVKIEkdGmgAa+n3ZwviocS7iHEi2s5hKIeyN5VXBkcu23jelWWsQYuTs9jrhOiN65U43VAhQk1ZK4NXA8uDl93HwIrkqmN8rQHVJsCMpQF1KUcY5Cj9HK9liNT1JS2+gkOOkwzDMhbKgFImMWwshjhgpRIkjQ2lFlisGfbmce9TsBpVL9oKYRqro4Y2hjIoQI6mcsNwUrRRzjSbdos96Z/OaeVHr0g11GQksH4WLC1CbNHSXFLNTgGowugLUpQIZ/bBEIGE5O8tKepqaGiDtl6PjvaeqSqyzZHJxQQhxBElGlDhSkkRhqkiMUYoSR0QIEeeiHE+LqaX6HcpeF5Nm6BsM2xaXypKUVq3O6Y0LLNbnWGrPodWl1+R2u6F8gDyT94ldlwaWu3EvZ+plqqSh+yTKkKtyZxe8OuO7RqwwsYn1NRq6S00P6Ppl+n4RjxRKDtqgHGCcJU1TOR4VQhxJUogSR0qaKsp+wFSRWl3e+I8CZyMhgJaL+GIahYAadOlbh0kUjfxGd8oSr9Wo1SHRnNtaw3rHsflFkoteIHa7oeakG+oyElh+61JV0dA9UmX2MplMrAGT8XuNJAzCIqkqWUwvUFd9umGFIrQ5rA6tWWeMwVpD8J5aTQLKhRBHkxSixJGSpICCQd9Tq8tk6lHgHDgTkM53MY1U2cdXFVUcngDKlfOD0chrzDVabPS2cd5x2+IKWZJekg0l3VCXU2o4mhcCaHkLvSGpMjsFqIqMCqUCNtaJE1KAei0X63R9Tl33WNEn6fklemEJF6UYfitCDBRVgbWWLMvHvRwhhBgbKUSJI0VrRZrBoBdYWhn3asRhcDbiPdQactYkpo/qdxh0t6nSVLKhDlieZiy22mwP+rgNzx2Lq6yFjMJDS7qhrujiwHKtZUx0PxIsjaRHpioyShQRS40Yp+H5rCnDPAmGuWSTuu7T8SsUYZ4oMbM3pSxLrDUopdBSzRVCHGHyCiiOnDTTVDs5UWL2ORuRJhIxlWJEDboMnMMzzDcSByvRCYvNNpU1PLd2jvVBITvlXYMElu9fgqXBBvPpOg21TcYAS4ahObFdUFfjyemFJSKwkp1mKTlNropxL2vqOO+oqhLnHKm0aQshjjgpRIkjJ0mGxQlrpRA167yP+BCRpHIxjVQ5wBQDDGonKFqKI6OgtWah2abjFee210lsXy5UXMWrgeVSFL0WjWMu3aCuNsnVAE+GpcV0DyIoTGwz8Is0kh6r2UnmknW0BNfvS4yRopCAciGE2HUo74if/exn+f3f/30WFhb41Kc+BcCv/Mqv8Bu/8RvMz88D8KEPfYi3vvWtAPzqr/4qTz75JFprHn30Ud7ylrcA8Pzzz/P4449jjOHBBx/k0UcfRSmFtZbHHnuM559/nrm5OT72sY9x/Pjxw/jRxBRKUgVKUfQ9eS612FnmbMS7iE7k7yymj+pvU/S7VDqRbqgRq6LCZ22079PrXiCJnlZzQU4Wr2AYWC6vqddS0wNSDJBjYmvcyzlQYSfMPFMli8k56qpHx69SxSYSZn51xhissxAjibyeCyHE4XREPfzww/wf/8f/cdnH3//+9/NTP/VT/NRP/dReEerkyZN85Stf4dOf/jQ/8iM/wuc+9zlCCAD8/M//PB/+8If52Z/9Wc6ePcvXvvY1AJ588klarRaf+cxneP/7388v/dIvHcaPJaZUkijSNNLvyxXvWbfb+ZZm8rcWUyZGYr9DaSxea1I5cRmpLZ9gIyzUGuRZne3eOp3eBiH4cS9t4igd8UGzc2gmXkPhqemCRFk8s7ojmsLGBv2wRKYqVrNXWEgukGDHvbCJFMIwoNxIQLkQQuw5lELUm9/8Ztrt9r4+96tf/SrvfOc7ybKM48ePc/vtt/Pss8+yublJURS86U1vQinFu9/9br761a8C8Lu/+7s8/PDDALzjHe/g61//urTVi2tKM40p5Sh61jkXIUIiHVFi2lQF1aCPUQqt5PE7SmWAflCoGMgU5FmNet6iN9hiq7uG9zJ6dDGlhsdX0hV1ZTVdkGDwUxFGfmsimiIuUMUm88kaq9krNHQHGYe/VFEWWGfQWkuXpRBC7BjrUcQXv/hF/uE//Id89rOfpdfrAbCxscHKyqvbmS0vL7OxsXHZx1dWVtjY2Ljsa5Ikodls0u12D/EnEdMmScEacE6KUbMqxoiTi7NiSul+h7LXpSQhl1DbkdryCcZHmhedH6ZpRrM+R1H22eicxzozvgVOmGFgORJYfkWBmhqQKounNu7FHBofa/TCMhrPanaKheS8ZEftsM5iTIV3nkxey4UQYs/Yev2/93u/lw984AMAfOELX+Dzn/88H/nIR67ayXStDqcr3Xa1Kw5PPPEETzzxBAA/8RM/werq6o0ufSKdKQsWFhbGvYyp4VyAYKjnTRaXZ7V1/uClaTo1zxlrArYoSRNLsy0Hf9MiSRJ5LQP82stsaU2t0aBdb457OTNHK0Wj0aAI4KKijqd9hSOiWr3GoOjQG6yzvHgb9Zr8LQC00qRpSrst1f6L5fRoKE1Ck4QGSikajaN0jNEAKo7lHeaBbrwDR2PcixqbGCNbnS10opiba48kG0prfcQeY2Ic5HF2uCKwurJCozXbxxxjK0QtLi7u/fv73vc+fvInfxIYdjqtr6/v3baxscHy8vJlH19fX2d5efmSr1lZWcF7z2AwuOoo4COPPMIjjzyy999ra2sH+WONjfcNev3OuJcxNWKMlKXn5CsVLkiRYr9WV1en5jlTFoHNdUtEYb20wk+LhYUFtre3x72M8aoKyvPn6BQlXmUUUbZJP2iNRoOiKDhjE7oWWipQXSUOKtUNKjPg9NmXWZxfpV5rHfnxGmcTjIEkHYx7KRMkspCs4XWXQfz/s/cnMZKt533/+X2Hc07MOdRwB/JqsEh1Q2p1kxDZsNSGqDZotAG7AS0MrbwwLcEyYBiQuLQXXsiGtbBFWZa4Ebz01uKmNw2CFrVg628ahixLlEWRl8MdasoxpjO8w9OLE5mVVbeGzKrMjIiM90MUb1VWDiezYjjnF8/QAyq63Q5lWS37wK7djB5dfUiPMYf+LmUcsYmDzKu6YlbO8M6R58AVVIlt6m0suV7pdna96rpmb3+fbrn+z7Fvv/32c/9uaa15h4eHp7//b//tv/HOO+8A8JnPfIZvfOMbOOd4+PAh9+7d4xOf+AQ7Ozt0u12+/e1vIyL88R//MZ/5zGcA+Nmf/Vn+6I/+CIA/+ZM/4ad/+qc3/iQxeTGlFDbT1GlO1I3lnOA9pLmgybrRszHlbEpjM3KbhpRflSrCPCoU7Wyo51FKUeQ9jDEcjh8ym483fg5lGlj+UbmqMMoRRbOJoctZstisF0RzO/twI1v1QgxUdUnTNGlAeZIkyTNcyxnu7/zO7/Ctb32LyWTCP/2n/5Rf/uVf5i/+4i/4/ve/j1KKO3fu8E/+yT8B4J133uHnfu7n+OIXv4jWml/5lV9B6zYv+9Vf/VW+/OUv0zQNn/rUp/j0pz8NwN/+23+b3/u93+Of//N/zmAw4Nd//dev49tK1py1MJ8KwUeMTUNXb5rgBNTz23STZFX54wOaxiGp8uZKHS5mQ/XP8SM+CaOUqxlP9wnRM+xvo/Vmzkk6O7Bc65RGgdDRMzJV00hqX2kpGhkQYs2W3SNTNcfhLm5Dfj5lWeKcw2qTHseTJEmeQcmGv6z34YcfLvsQLkU1S615F+W9MDmMvP2jGf3BZl5MXNS6tObFKBzsecpZpNtPIeM62fjWvKZm9tf/k4PDQ9RgG2vSY9OVyLt8d+LwITC64EOE946qmdHtDNga3LqSuS+rTgSaOqPo1nQ6aU5UpioG5pBMVTh5PNMjtbO0FIGeHhMxHPo3KOOQm1w11riG2WxK5Wo6+dUGb+k2llyHdDu7XlVd8wv/z/8H3d76z9hbyda8JFk2Y0AZYTZNr+beNN4LMUB6ETJZN2p6RDWb4nSWQqgrdODVuauhnnZ2o97hhm7UU6qtivI+3UYBOnpORoWXzdmUdxGCYRa3iaK4nX3AyDxC85yhbGtORCirksY1ZCbNIE2SJHmeFEQlG0spRZYp6nkKom4a79qteekcMFk3zfE+3jlUkWaKXJUyKuYBNBHzimG11oZed4hzDQfHD6ibzRsor7UgIZ1GWtVgVY2iDVyS51HUMqSKfbbtI3btB2Tq5lVYVHWFcw6UwqQXE5IkSZ4rnUEkG81YRd0IMW50h+qN450QIlibSqKSNeJqyumEKgZym1LUyyYC06B45DVV4JWqoc7SStPtDBCJHBw9oKymGzXEPA0sb3X0DEuNI4XH5+GlYBp26Og5d7L36eox7bLy9RdCoK4rnHdk6TE8SZLkhVIQlWw0axUxSNqed8N4LyjSoPLk/EIU4pJDBJkc01Qzgs0xGzoE+yqcBFDvO8MDb5h6KPCvXA11llKKTt7HGMPB8UNm5eZs1FNKENqB5ZvK4MhUjSYi17P/50Z43KrHolVv70a06s2rOc0ihLra8w+h0DWjbMx2tk/fzlGk89gkSdZLetZMNpqxoDTMZ5FuL1343QQhCCFsxoVgcnnem9S4AH9ju8Do5QSY9dEerq4xvdFSvv5NIwKzqDgMmkYUdRRsbIeT94ylvqRt8qcb9VTNeLJPCJ5hf+d04+9NpZSgAR8MNtvMi+COni+qoVL1y8W1rXoh1mzbh2SqZhzu4NZ0zlbTNDjXEGMgy6/i9iBk2lPomsI0GBUodE3XGHqdmlnoMnV95qFLlHQ+myTJ6ktBVLLRlFJkuWI+i9y6s+yjSS6Dd+2gcr2kMCFZP3MXKL3ww+Mao+FvbC9hvbh3VNNjmhDJbWrxeR0nAdRR1NTxyQDqKke25FmBVprp/IgYA6PB7o3eqPfkwPLN25yn8WS6RKuAlyU8ZtwQbauepaePyVTFcXiDMg5Yp616USJlNcc5R3bJj99GeTqmoTA1Vnky3aARRDR1zJHQxXlDz5T0uzNK32Xi+8x9jyA39/EnSZL1lx6hko1njKKpBRFJrVw3gPdC00TyAtbpRDZZnqM6MHOB3cLw7lHNdmHZ7V7v06M/3qepK6LN0+PQK1pWAHWWtRk9PaSspoTo2R7ext7gYFFr2djWvELPsTQESdVQr6tt1duhUFNu2fc5DneYhp21Gf5eVe1cKJS6lEpIRaRjajqmxmpPphxGBUDRxIz41M8lYpiGASpEeqbijWKfKpswcQPmoYeL6TaaJMnqSUFUsvGsVZSzSFMLRSddAK477wQiGLOZF0fJxfgoTJoAEXY7Fhcdf7E357NvDejY67sNNUf7uHKOHe5e29e8KURgLm0LXh0VVRAyud4A6iytDd3ukKqasn/8gO3hbYq8e/0Hcg2UFqIzxAg3vBPxCYpAoUuM8jTSX/bh3BCLVj1qts0DclVxHO7gV7hVz3tPVZc45/Dek+evc6xCoRs6pibTDqscmfaAwkWDk5c/hgiaWeihEDq65E5nnzpOmbi2QqqJGekFuiRJVkUKopKNZ2zbYjCfBYrOBp1J30Aigvcg6TwrOafj2lP5QGEUSinudDPemzb81X7Jz9ztoa+hOkm8o5odEwJpW94FPC+A2tKw7By63ag3pGpmHB49YGt0h07Ru3HVbmcHlmu9OXOiCl1iaAgrOosnilzLY9dV8FIwE0tfH5GpiqPwBtWKteo579rteM7ROEeUSP5KA8rbuU8dU1PoBq0Cua5RQIiGKnZ4le9bUJSxRxmFjq65XRzisjETN2AW+tQhf6XPmyRJcplSEJVsPK0VNoP5NLJza9lHk7yOECAGIY2HSs5DRDiqA42HW4sQ2mjFm72MD2YN741rfnTr6me/uKN9fF0RixRCnccqB1BnnWzUq13J4fgho8Et+t3hjQqjNnNgeaRQc6xyNNJb9sF8xLxqmJYN/U5Gv7u61UQvIhimcZeOmnJ7hVr1nHdUdYV3jsY7JEYym6HNxdpv27lPNR3TYJQn1w5FJKJoYoFc2lJzRRU7VLEg1w07xTGjOGXq+8x8jzK8WtCVJElyGVIQlSSAzTR1mhO19rwTvBdUSqKSc5i5SB2ELDi6jz5ENyUoTU8plFe8f6jZ2cnZKRSgQCsEtZjSrNvzd7W4YHjqz6L0yTTnJ3/x+Pey+HN9+JCmnJMNby/nB7Em1iWAOqsNo3o0ruZ48ogQ3I3aqLeJA8sLVWKUW2wmW63nmtp5pmVD4+o2MImRUa+zpuc1ikqGWKqlt+o556iaxwEUUbDWorPzB1CaQGGa07lPuWowKhJF4Z4x9+lytQFXEwsy5djKxozslEnoMfN9St+5xPArSZLkfFIQlSSAsYpqHnFOyPN1PGFLYBFEOaHTS/+Gycsd1Z766JC7kwdo3+C9gAgKGIkwjZa/msOnep5CRdqLTln0frbVH0rRJiRy5hMrhVoEV49DKEAtLjS0al/5Dp7Se+rgiVGR2/SU/Dyz+DiAqoNgVzyAelqeFSilbuRGvc0aWC509Jxc1dQrVg3lQ2QyrwnRMewYKh85Go/xIbIz6K5t+Omlw0yyxVa9mqNw99pa9ZxbVEB5R+Obdv6ktZjsfKGRIpIbR0fX5KZpt94pTwR8tDTLCNUkw/kMoxxDO2Nop8x8LAqkXgAAgj1JREFUn+kikLraQCxJkuSxm3EWlCSvyZpFT/0skOfrebKWtBvzgDV99Te5Tq6qmd//kOLoEB0d8+4IGTw5DHZLhPcq+FYu/F8GnH/mioRFOCUQI0ShDbAijXdUTU3tGnzw1K5Bi2CH25f+Pd4EzwqgRmsUQJ2V2RytzelGva3h7Utf9b4MmzSwPFfVohpKs0rVUDEK41lbsdOxCm0MPWMwSjGZzQjBszsaYtfxjsPjrXodPeG2/YDjcPtKW/Ua17QzoLzDOYcI2HMHUEKuHYWpKbTDKEeuPSjBB0spq9EOFyRj4jO08vRsycDOmYUuM99n7rsrO/8sSZKbIwVRSQJoo7BWmM2ErZ1lH03yKiQuBpXLy9832WxqfMD0wX2a44osKsrRncctdmdYpXgzFz5s4IMa3jnvuChlHl9nGAgxUjU1pXP4EKhjJCiFzgry7gBz06/eX8FNCqDOMqcb9WYc3JCNekq1D7rhxg8sFzp6RqZqGrn62XHnJSKM5xXOezIr2OzxqX2RW4zRTGY1j4KwuzWgyNb11F9RxRFWVeyYh+Sq5jjcvrRWPRF5PAPKt0PIAayxmHOs37SLuU+FqTEqkOuGtnZWUcWCVQifniWKZeoHaCIdUzLozJn7DlPfbtrzsq63lyRJVl16dEmSBZtp6uomn0TfbN5LO6g8vYiXPI9rMHsfEqdjDo4bSt2j2++98PqgaxQ7Fv56LoyssGXPdzEhItSuoXQNtWtwweODRynIjKVzgdkim2S+CKCqGxZAndVu1BtQN3MOjh6wPbpNp+ivbSWnUm07a/CG7AYPLM9UjVFu0YW7OjfIadlQO4cWT559dOGBNZqtQYfxrGbvcMzOaECvs76PP0+26lWv3ar33ADKGqzWaCUoHFoJWkUUsnhbPH2bVhGjAplyWBWIomhitvTh6hcR0cxDHxUiXVNxt9ijygsmzYB56OFiWqaRJMnlSkFUkixYC3UpeBex2eqcZCbn4z04F7khY1eSS6bGB5iD+0hZclxD2d3BRs15rv13LJRB8RdT4TMjIX/BMHznPaV73HpXOQdIWwmTF2sbNly1ZwZQCs5RiLCWlFIUeY/GlRwcP2RrsEu/N0I9ozJv1W3KwPKOnpNRLWVY9vOUtaOsHURPUTz/yU9rxdagYFI27B21YdSgu76PRxHDNO7QPXerntCumoiLACmCREJocE2Jig1ZcBQ6st3XWK3QSs583CJwIqJ1RCOPxwIKoEAW4ZOT9Q35AATNPPRoKwAr7nQOaOKEsRsw912amLOq1V1JkqyXdMmWJAvGKkQU5Twy3Fq/i4FN550QPeRFOkFKzlhUQTGbEMuSkPc47PUoG9g6Z8ihlOKNQvhhpfj2XPipvjwxLyrESOVqqqbGhUDtGqJEUIoiy1Lr3QtsWgB11kkYpVXN8WSfEDzDwQ56Dcs6tRZivLm3c6sarKoX6wpW49+ncYFpWRNCQ7fQLw2VlFIMuznz2nFwPMaHAVuD7vln360cRXnSqmcfkKuaeRwtwqaT6qV4WrnUJkYRJREfHN5VmBiw0qBNWxWvFttPF2spgPa8UAREKYJoXLCLDXPr+nM7L0UVu1SxQ0fX3CoO2MosUzdgFnpUYXXbDZMkWQ8piEqSBa3BWGE2FYZbyz6a5KK8E9BpUHnymBofYg7uIWVJCIIMdqmVZl6BErAvqGx62um8qBq2LXyseNx653y70rsJHgXkNsOa9X5V/KrVEfaCOQ2gzAYFUE/LsgKlNNNyjI+ereEtrFmvNpibPrC8o2dYahyrcb8OJxvyvKOTa8w5w0ulFP1OjtGe4+kU7wO7oz5mjXtfvXSYBUtPjyn0jIhepEhnHt9FEBS1i0wrjwuCjwGlFJnto5XBn2RVz7Ox8ycVVexQxYJcNewUx4zilEnoMXUDqrA689KSJFkvKYhKkgWlFFmmqcqbO+PipopB8EE2+EQxeYJ3mL0PYDohlnNCPoB+u2r9qBHKAL0LhFAnekYxUp6/PKrwRUNBoHYOWbTe9VLr3bkEgQfeMAug4+YGUGdZm9HTA8pqymEMbA9vk2WX1wJmlKNvxkz9FvEKTv1u8sBygyNTNZqIX4HT5ijC8bzCBUeeKewr3Hk6ucVozWReEiSyOxqQ2/W9E0Ys07j7zL9r5/V55pXDByEEhdWQZwX6JqamV0bRSEHjCqxybNkJQzPnw+oudQqjkiR5BekROEnOMBZcIwR/s06kbzrnhRjaORjJZlOTQ8z734HDfUJVEQa3oNuGUFGEsQcv0DHnv63EGKmbkun8iLw5JlRT/ve4ZuYceWbpFR2KLEsh1DmIwCPfVkLlEhmZmzWI/HVobeh1h3jv2D9+QFXPLukzCwN7RN8esp3fv6TP+aSzA8tvmkLPF9VQy69SExEm8xrnPJZI9hrhUWY1W4MC1zQ8Ojimam7WfC8Roawdh5OS8ayibmq0OPodQ6fIUgj1GrxkjP0QpYS3uw+w6mbddpIkuR7pUThJzmjnREFVpdKadRKc4JqIzdO/28byDn3/B+gH7yOTCV4XyOj2E6U2kwCNQH6OuRbtJqWaeTlhOj9kNh9TllOcr9jNNc70eCQ9tLp5F95X6ShqZlEhMdBLZyAfoRYb9RRwcPyQWTlG5PUe17pmSqYqMt2wnR3Q0dPLOdgznhxYfnNoArmu0CogK9CWN68cdeNQ4snz1/9ZG60ZDQqEwKPDY6bz+rVvb8t2EkAdTErG85K6qdDi6XcMRZFeMLg8iqnvY1Tgze5DtArLPqAkSdbM8muMk2SFGAPaCNNJpD+4WSfUN5lzEIW1nnORvDo1OUTv34f5jBBBBrvP7PU69FB62LHPvxAJwdP4Gu8aQvQ43yAiaG3Iss7pRcwtFXnkNCOjuX2DV9ZfpjIqDr2mDpHtdFd9LqUUnaJP01QcTfYIwTPobb9SBYdRjq6Zkuuamd+ib8bcLj7gg/KTi4HLl+cmDiwvFrOhgiy/GqpqPLOqIUZHr7CXFqhopRj1CmZVw/74+HSI+boFNiJC1XjmtcMHT4yeTCu6ncv7WSVPEhQTN2SUj7lT7POwun3pjytJktxcKYhKkjOUUmS5SnOi1oiI4P16v4KbvCLv0HsfoqZjpJwT8j4M+s981yoKVQSFgARCFKJERASRiCw2KYXg8d4RJaBQWJM9c4tZTwtDEb5XaXpG6Ol0G3wRL/DQa+ooDBZtXMmL5XkH5TWT6SEhekb9XYy5yGmb0DdjMlXjJQM0ZRgwtAeM7COO/RuXerw3bWC5IlDoEqM8jTz7ceW6ON9uyIuxoZu9fEPeRSmlGHQLytpxNJ0SYmR72FuLjZ8hRqraUzUeH88EUJcY1iXPF9FM3YCtbIKLloNmh7RNL0mS80hBVJI8xRhFNRdilDRzaA2E0A4rT/9Sm0VNj9B794jzGY2PxO6IqDWxqYkSiSJIjIRF0PSoiezXQoYw1iCxDaEicfH7CCiUUlhjsfrlbTjbOlKJ4d1K83/uBl5QaLXRROChN1RBUUggW/1r25WR2RytDWU5IYbQbtSz52sR6+g5ma4weOpFkBKxVHHAbvGQedjCyeUNGb5pA8sLXWJoCLLcU+UQI+N5jfOOTqbRVzjZv1tkGK2Yzue4ELg1GrzWHKqr0rZOB8rGUzeeED1KIplRZCmAunZeLLPQ43bnAB8tYz9a9iElyRoTMu2XfRDXIgVRSfIUaxUxRqoq0uut3glY8iTvhOAFc4Hh08nqijHivUckEmJAYiSe/eVqOHyIzCeEssSbDpIXyHxMXFQ5hRiIIoBqBygvtrRVXtgyggNQup1rg8aYDKUuXmWgFNw2gfve8F5j+LE8kK5/PuogaOZRoWKgmx5SL8xoQ7czoqqn7B8/YHt4myLvvvBjNIGenVDokjo++b517JLrktv5h9yrf5zLql44HVjuDNnat6tGCjUnU45aeks7ChFhPKtxzlFowV6oIu7V5JllS2vG85pHh5FbW0OKfDUuF2IUKuepaocPAR88Rgkdq7F2+e2Tm6yJOToE7vb2aGYZVXjxY1SSJB+V6YaBnRP1HBUdcLPvR6vxzJIkK8TYtq1gPk1B1DrwXnBOKDqQysHXTwiBxtW4pqZpaibTI6aTSds2FyMhBIK0gZQuZ9jJIapp8CKEzgBRgnY1SikUCq0Vhc3R+nGwdBwUShkGJlBccjVOpmDXRB427byoW3bdL8Av1ywqjoLG+chWejh9ZVprup0hVTPj4OgB26PbdIr+c8PTvj3GUuPF8tG9NIp5GDGwh/TDITP/7LX3F6VUOyfKBwOs9xatQpUY5QhiWObzyqRsaJzD6ECWX1/QYoxma9BhMqt5dHjMzmhAv1tc29d/mvOBqvHUzuNDQKLHaujl+oLtqslVqkIHowJvdx/w3vwtXFzebSZJ1olRnoGdk5uGQjcEGjah1yM9eifJU5RS2FxRztIF5Trwrm0H0WlQ+VoIIeBcTdM0NK7Ge4f3HtfUCNDzDWVVopUCNMZqMtF0Z3uYckYMkbq7he2cv6VoHDQ+CFe1f6CvhfpkXlRP6KZ5UQA4gUde0wRhqDfhlOpqKaXo5H0aV3I4fsiof4t+b/SRMCrXJbkuMcbRhGfPNgqSUccut/MPqcLw0oZxK3UTBpZL29aoapolVkPNq4aqbgBHkV1/tY9WilG/YFY27B9P8DEy6nWure1NRKidp6w9zgdi8KAiuVHYPLXfrSbFzPcZ2Slvdh7yYfnW0ltbk2SVaRXo25KOqci1QxFxMcPFyCaU2KdHhyR5BmsVdSmISDrZWWHtoHJIl/2rK8ZwGjq5psH5pq2CqmuECKLQxlAUXYwx9Ad9lHqcGJn5hPzoEVJXNAK+v/3MjXjPU0ZFIwpLuNIgZFtH6tDOi/o/pXlRxJN2yABdIqlz9nIopSjyHsrVHE/3CMExHOycDtRXRPpmTK4rXHhxWFuHPnlWs5vd41HzDpdR+XMTBpbnqsIoh4hmWdVQtfNMy4YYHL1OtrTzEKUUg95iiPl4jA+RnUH3lTY4nlcIkbLxVI1r26xDwCihyDXWpPa71aeY+j6jbMzdziPul2+kTXpJ8hRFpGdLuqYm0zVWBZqYEznfDMibIgVRSfIMxihCiNS10OmkK6hV5f1iUHk6x1kZMUaca2iaug2fXEMMgbqpkdhWGRpjKIoO5kWBUvDkR48w8wmxbqjzHtK5eK/8JCrqIAyu+G6sFdxazIv60BneyTZ7XtRB0JRBYWKgSC15ly7PCrTSTMtjfAxsDXexJqNnx1hdEUUhvPgHL2hKP2SYHTLx21Tx9QcMr//AcqGjZ4tqqMsb5H4RPkQm85oQHb388jfkvYpukaGVYjKbEYJndzTEXmIVsojQnLTfnRk+bo2i2zEr8TNIzi+imfgBIzvB5QfsNbdIoxOSBEDomoqeLbHKkWuHi5ZKbvYsqOdJQVSSPIOxoDTMJ4FOJ6Ucq8o7wfnICi712RhngyfnGpx3BO/a4EkEhaCNpchfEjyd8bgKqqaJcuEqqBNeYBb1YpvShT/8wvLFvKh7tWagFbt2M2v1pkFxHDQ+RLbTffPKWJvR00PKasph9NzZGtLJFwO247Nb8p7mpMDFnDudD/hg3ie+JLx6mXUfWJ6puq2GAj46W+vqxSiMZxXeOzpGXemGvIsqcosxup0bFYTdrQFF9nqXETEKVeOoGn9m+HikY00aPr7mglimYcCtzhFOMo7d1rIPKUmWSChMQ9/OFwFUQxRNFTtsckibgqgkeQatFdbCfBbZvbPso0mexzshOsj7m/sgft3arXaurXhq6kXw5BcVTwGUQmtNkRcXHyIbAvbRB+T7DxdVUF2k/+ozWqZR0UQo1PUFQgMtVCJ8vzL0ep5Ny7GbCHvBUHthdI0/902ltaHXHVJVU2L1A6LNaLLzhVAnqjBkaPfZzh5y4N56reNZ94HlHT0no8LL9Q9ZFhHG8wrnPZkR7GuGPFfBLoaYj2c1e4djdkYDep2Lt5I4HygbT+M83gdEFsPHC43Rm9WacpO5mDEPXe5293DRMn/OzLokucly3QZQmXYUuiEK1BseQJ1YvWe5JFkRNtM0dZoTtcq8F1Ckf58rJCJPVjy5hhA8ddMshseCVoY8y7H21Z9STqqgtIKmCa9cBfX4uB8PKR9dc1HBro7cD4bvVYaf7IaNmY/0eC6U0FeRtD/geiiluT3U5MpxMC4puhmD7vnbmSKGMg7ZzveYhC1cfL0B3es6sNyqBqtqFLy0rfEqTMuG2jk0nnwJw8nPS2vF1qBgUjbsHbVh1KBbvPT29vTw8RAdGiE3YG0aPn5TVaGDIfBW7yHvzd6iictpeU2S62aVp5/NyXW7CQ+EOhYbsQ3vvFIQlSTPYayimkecE/I8PWismhilDaKSS3c642kRPoUQaJqaED3QXvjmWYF9hZlNHxEC+dHD01lQ5WgbP3z9z1uKwokiI7z+MV6QVnD7dF6U5p18/VqUXsVe0JRRYSWQr18OsbascvSzkq5VHMYOx9MxPka2en20Pt9zVxM75LrkTv4B96qfeK3hwus6sLyjZ1hq3BKGxZa1o6wdRE9RrP6puVKKYTdnXjsOjse40Gd70FtsO32SD/G0/e50+LgWeplGX7RqNllLs9BjyIS3u494f/4WPm3SS26wdhPenI6pF5vwAi7mr936fhOlR4IkeQ5rQFCU00C+u0Zn0xvCOyFGUOlx/VLN51OOx0c0TUXwbYijtCLLMjr2cocpmnJKfvQQ6oomtBvxut0BlOVrf+5xUFRB2FpShnx2XtTQCNvmZoemx0ExCZoYA8P0cHmNhFE+pdANLmR08gytPdP5lBADO/0h5lylaYoyDBnaQwb2gIm//cpH9HhguUHr6w+CX4XBkakaTcRf86lx4wOzsiHGhs6KDCc/D6UU/U6O0Z7xdEbwkd1RH2P04+Hjtad2j4ePZ0aRpeHjG0gxDQNG2YQ3ug+5N38jXZQnN87jTXgVmXZkKlBHu3Gb8C4iBVFJ8hzaKKwVZtPI1u6yjyZ5mveCayIr3MGwdpqmZjIdU1YzMpNT9DpXc8EQAvnxI8xsTKxr6qyHDF+vHegsJzCPGiPxdbr7XttAC6UI75aGn+55ihsa0FQRDoKhDpFRur68Vj1bkpsGpQQf2wfD3Fp0VzOt5uyFwO5wRHaOttkgGVXocau4RxmGrzwn6fHAck2WrUcQVej5ohrqep9QQohMZjXOtyGU0a//gCWiCDHD6OZaNnd2cos1mvGsJMTIsNelcp6wGD6udRo+nrRbOid+wJadcKvY51F9hzQjJ7kZhN5iE545swmvXNLm1XVyQ0+Lk+Ry2ExT1ze7kmFdeQcxgLHpYewyhBA4Hh9SlnPyLCfP8ysJoXQ5o/vwB5jxAa7xVP1tpHt5IRTAJGgaud4h5c+zqyNR4PuVISz/cC5dEHjoDZUX+sjGzMNaBUYFBtmcQjdU4cnQyBrNqNslhIZHx0eUdXOuz1nFHohiN78HvNoN9smB5atPE8h1hVYBucZXrtvh5O3ChyJT2EtIzUWgcX3qpodz13cR1A4xL3Cu4XAyoWkqlDh6haJf5Ni02jYBohgmvs9OMWE7P+JVH2OSZDUIHVOxWxwxzCZ0zRytIlXsEK75RY11lSqikuQFrIW6FLyL2CwFHqvEO7mWV3s3gYgwHh9SVyVaKzJ7BRdjMZAf7WFmx8Smoc66SO9yAyhoB2ZPoiLGuBIb64yC2zbwwBvuO83HbtC8KBF45DVVVOSkuVDXbZRPyXWDi5ZnVRZorRl2u0zrmsPJESGO6HdeNlRaU4YhA3vE1I+Zh1dbub5OA8uLxWyoINd34SAiTOY1jXNYFc9VsfbyzwmN7+ODhSjUoYcxDmOupyrN6DaM8iFizfq0GCbXy0vG3He52znAx4ypHyz7kJLkwj66CU9RpU14F7YeZwlJsiTGKhBFOb85F483QfBCCHIzH+9jQB09wvzgf2M+fBc1n1z5l5xOx1RVifeOIr/8V9F1NaPz4IdtFVTtqHrbSOfyQyiAeVR4UWQr9EJroWDHRD6oNcfh5txoj6NiFtu5UL10NnGtOqYi1zVGBfwLAhSlFIOiwBrF0eSYaVW99HN7yWlih9vFB2j8Kx2f0m0QFVf8qVMRKXSJUZ5wjdVQ88pRNQ4lnjy/nGohF7rEkKFpyOwMpYS66SPX+FiolCKzaQZU8mJ1LKhCzpvdRxTm5Y9JSbIqrHJs58ds5WP6Zkaha+pY0EjBzbwouVrp1DFJXsAYhcmE2WTFz6Y3jPdC8HLujVBrIUbU8T7mvb9GP/wAOTqCH34P/e3/if7ht1HTI67iiqKq5szmE8pyRueyw6EYyA8fUDz6AJnPqVSOG+1ylYObxlFTBaGrVyiJAgZKKHQ7L6q+AQ8nZVQcBkMTYhpOfs00kWE+o7A1VXh5eKKUolcU5JnheDJmXtUv/Zgq9LHKsZPff6VjPDuwfJUVeo6hIVzjFq+68cyqhhgdncJeSmjjfUHwBSIOa9rZUJmZE0JG464m9E+S11GGLlE0b3ceYJVb9uEkyQsZFRhlE3aKY/p2RkdXNJJRxS6SAqhXlk4fk+QlrNVU1Wpd1G467wTnhGyVyl5elQhqeoR5/zvoh+8j4yNCUISdO/i3fpyQ9eHee+i/+jP09/836ni/HY51Cbx3jMdHVOWcotO71FexT6ugjg9wtafqbREveRbU0xqBKioMceVmFSkFt3QkCHy/NsQ1vul6gYdet3OhlKQTiWs2zKdkqiFGjVxg81Q3z8is4mByRNW8eGaUYCjDiK3sgELPLnyMZweWr65IoeZkyl1bNZTzgUlZE6Ojm11O+5oPGc53iTFg9eOQUeuAMTVN0yGENIkjWTWKqe9jdODN7kO0Wo/FBslmUUQGdsZOfnQaQLloFgHUar/Qsg5W+QwhSVaCsW3wEfwNKGO4IZxrr+L1udaSry41G2M++C76/g+RowOCi4TRHaQ/AjQohQy3CW/+OGGwDY/uo//6f2He/Rb68CGEV2ubAYgxcnR8QFWXGGsvZVDu4hOTHT5sq6BmMyqV4UY7V1oFdWISNHWE7pV/pVdjFNw2kUOvuL/SF+jPJ4vh5HVUFESyFQv8brrC1BSmJteeJl5sq91JZZTVcDA5pvEvfvxoYoGPGXeK91Fc7PlvHQaWF6rCKEcQw3W0VIQYnxhOri/hMTFEg/M9JAYyM//I3ESrK5QKVE0fkXRnTVaLoJi4IV1bcafYv/DjTJJcHaFnSm4VRwyyKV0zB2ERQKVg/7Kkn2SSvIS1ihiFsowMUg/K0okIwa/3rhVVztAHD6CcIWVJVBYZ3n5+WKMU0h0SukNUPUMf7KEOHmG2dpDbbxJHtyA7/yv6Z4eTi0SK/HIqlXQ1Jz98gKpKXBRcf/taAih4PKRcJK700OxCCzsifFBrBkYYmfW6JR8GTRkVEgLd1c0YbiRFZJjN6JjzteQ983MoRb/TYVJV7B8fcWd75wUhtKIMA4b2gJF9xLF/44Jfa5UHlgsdPSNTNY1cfevayXBy5xy5Fqx5/dPvGDWNGyARrKmeWV3VtuhVNL7dpNcpLl7dliRXKaKZugFb2QQXLQfNDmnWTrJsXVMxyKYUpiZE026UTS5dCqKS5CW0AW2E2UQYDJd9NEnwEIOwluOh6hJz8ADmEyjnBGWQ/k67nvGcpOgT3uyDq9GHj9BH38IMt5HbbxC3b8M5ho3P51PKak7tanqd/ut8R60YycZ72Okxsa6obY/Yv94n7WlUOFHkaxBRDnWkEsO7leGnep58TW7L86g4CpraR7ZTCHXtBtmcTDcIEF+jJaAdYN5hUpbsj4+5vbWN0c8OjCKWKg7YLR4yD1s4Of8yA6WF6AwxwnM+/dLkqkIrh4jmOi56J2VD7RxGB/L89bfziSga34ZQRpenM7meReuANTXOdchMg7FpHk+yWrxYZqHH7c4BPlrGfrTsQ0o2mFGBvi3JdU0dOmkG1BVasVODJFk9SimyXFFVqWR4FTgneB/Rdo2eGJoa/eCHmPe/C/sPifMa39tBhrcuFEI9ISuIdz+Ov/MOsa5R3/vfmG//GfreD6B6/qveTVMznY4pyznd4vXnQul6TufBD7BH+7iqoepe/SyoZ5lETROE3ooNKX8WpeCWCbgIP6jWY16UO5kLFYWRTqdl1y3Tjq4tyU1DHS7WkvcsWisG3Q7O1xxMxsQXrLerYxcRxe38Qy5Si7q6A8vbaqhc1The/2f5MvOqoaobEEeRvf7rvyLQuD4haIyq0Orl5yZG12jlKVOLXrKimphThg53e3t0TLnsw0k2ljDMpuS6wkebQqgrloKoJDkHYxSuFuI6XDHecN4LzkP2+i8qXz3XoB+9j3n/O6i9h8R5ie8MiVu3wF7SN2Az4q238Hd/jBgF9YO/xvzVn6Hf/y5qPnli014InuPjA6pqTqfooF+nTCFGsqPFLKj5ySyo3cv7vi6gjo+HlK/LKcPJvKh9r3i44vOi4ulcKOjK6g2Cv/mEUT6lMA11yLmsCh6jNYNOl6ouOZxOkedu5VTMw4iundC3h+f+/Ks6sDxTNUa5RaR2tcdWN55p2RCDo5tnrx38i0Dj+/hg2xBKn2/As1JgbYlETV1fQhVsklyBKnTw0fB29wGZfvl2zyS5bF1TkesGrYTAOlxorLfUmpck59DOiYpUZaTXX7VXdzeLXwwqv8wNb5fOO/TxHnp80M6ACpHYHZ6rbe6VGUPcvksc3UZND9EffB+9dw/ZvYvs3CH2tzg+PqSqSpQ2mNeYUaLrsp0FVVc4H3Dd0VICqBPjqGki9Ff4JvEsHS1si/BerTEatkxcyTa9g6CZB4UKgU56+Lt2/WxOrhtAiHK5p23WaAadDtNqhlGarUH/mY+tQTLq2OV2/iFVGBLk5ff3xwPLLbA67WAdPSejxsvVVkP5ECmrkhg9nfxyNuS50CWGDE2D0RdbVqFVxJoK57tY32DtizcnJsn1U8x8n5Gd8mbnIR+WbxEu+TEvSZ7npCWvMA3VJVQeJy+X7t1Jcg7GtjMu5tMURC1TjIL3srqTykNYBFD7SFUSGk/sDGFwjXvctEZGtwjDXdT0GH3vPfSj+0y6fWqbE7Kcbm/wap87RrLxPnZ6RKxqalsQh1uXe/wXFASmUSMxkq3hXXOkI040P6g0faPZssJIR3p6NeagTYPiOGhCiIzW8Oe77ozyi1kVDWW4miA7s4ZekTMpJyitGPWe3bJbhz55VrOb3eNR8w7nqcxqB5avwA15waoGq2oUcmWrt0WE2nnmlQMFhQFzCUsbvC8IvkDEkZlXC5GMboiSUdV9esafq60vSa6XYuL7bGVj7nYecb98A0kNPMmVW7TkqRoXrmeTapKCqCQ5F6UUNleU83TStkzeSTv4dtUuiGNEjQ/Qx3tQzonOEfIebC9x+4tSyHCbMNymGu8ze3gP8RXbW7eI27cuvNGurYJ6iKrLtgqqt9wqqBPTqHARihcM611lSsFtGwmLrX/3asUjbdhabNQbmki2pJtQI7AXDE0QhipNSrh+bUtebhpctFzlY0mRZe1mt9mkbdnrfjQ8FzSlHzLMDpn4Har48u0dqzawvFAzLDUNr7Z18EV8iFSNo2o8IQZiCAx6+aU8YfmQ4XwXie3g8VfVbtGbU/shdd2nU0xY5eLiZDMJmokfMLITXH7AXnOLFAwkV+m0JU9HXLzC7oXkCSmISpJzslZRl4KIrHZb2A3mPfgmrkL+0RJBTQ7RR4+gKpGyJuRd2NpmVU6aXPCMRTEbbNOVgMzG2MkRpj8kbN/CD3aQF/1AJZIdL6qg6oba5EuvgjprHDQuCINVCycvyCjYNsKWCKUojp3iwGm6VrOzCKR6Sq7tojEKPHCGKgg9ImYFQoRN07UVhW7QKtDI1VdVdvKcKHA0GaO1pld8tDXBSYGLOXc6H/DB/JMv3d53dmD5eecZXRWDI9d1WwV0Se0+bfVToGocjQuEGFDSVmdmHUORWerm9VrgQjQ431uEUPPXPv9QSshMifM9gi2wNs3iSVZPEMs0DLjVOcJJxrFbnfOO5GY5qTwuTE11RZXHybOlICpJzslYRYiRuhI63dUIGTaNd0IIUHSXfFUsgpqN0YcPoKraOVC2g+zcZpV2QMQYOZ5PqFxNZi3KdKg7fZRvyI4PsbPvYbuPCNu3cMMdJHvywvNsFZR3gaY3XIkqqBNlVDSiyAgrEvu9PqWgp9rtf0HgOGg+8JBpw8gIW1YY6shVL43cC5oyKqwE8tW5SW8MrQKDbN6eGPvrOzHu5hkikYPxMXprm07+0cqhKgwZ2n1G2SOO3Jsv/HxqEZ56p8my5QZRhZ5jqXHnmG/1MiFEysZTNx4fPSF4jBI6mcG+xvy9p8WoadwAiWBNdWkvghntCNpRVj36PYfWqdo7WT0uZsx8l7vdPVy0zEMatJ9cNmGYzch1jQtXW3mcfFQKopLknIxpLxLn00Bn2UHIhvL++ipCnkfNJ+iDB1DNkXlJNDmydRvUat0mRITjckrlGkQgO3NxJDanufUGLnjs5Aj74Q/pdNpAyg93iHlBNj7ATg6RuqEyOXE0YtWeoCdRUQdhuFqHdWmMgl0TEYG5KI4WVVJ9q9k2kZEROldQJTUOiknQxBgZrtbNemOMshm5aghirnV9tFKKXlEwqyoOJsfc2dohs0+eKkYMZRyymz9iFka42HvB56PdPrTkgeWaQK4rtAp4ebVgT0RofKBaBFAhepRErFF0CvN6W0if+fUUjV+EUHp+Wl12WTJT0siAukktesnqqmMHGwJv9R7y3uwtmtQ2lVyi3klLHhFHum1dtxREJck5aa2wFuazyO6dZR/N5glBCEFY2qTyaoY5eADlDCnnRGWR4a0LzVm6TrO6pGoafPB0n7OtT4zFbd/GxYCdHZPdf5/i4BHS76O8x/tA012tKqgTXmAW9eJCcNlHc7WUgr4S+lrwAsde84FXPNKakRVGJjLUgrmEC8k6wn4w1F4Y6fWcu7XuClNTmBprHKV/fshzVZRS9DsdJmXJ3vERd7Z3sE89zjWxQ65L7uQfcq/6Gy8cJqy0EKJGhKWFHYVuZ0OdZ9vf00KMVI1vZz+FgA8eoyIda7BX9NgoAo3rE4PGqPLSQyhoq9WsKXG+jzcdsqy69K+RJJdhFnoMmfB29xHvz9/Cp016ySUwytOz89SSt0TXck/+8pe/zP/4H/+Dra0t/v2///cATKdTvvSlL/Ho0SPu3LnDb/zGbzAYtJuc/vAP/5Cvfe1raK35whe+wKc+9SkA3n33XX7/93+fpmn49Kc/zRe+8AWUUjjn+L3f+z3effddhsMhv/7rv87du3ev41tLNozNNE2d5kQtg3dC8IK+7mE1dYk5fACzCcxLgtJIbxfs6p4IVa5hWpVUrqabn2MFrTb44S6+v42dTzCTCb4YEIarVwV1YhI1zRoPKX9VVsEt21ZJTaNiv1HsYRhY2LaRkY50XvEuEgQe+DaE6qt4KcFWcjGKyCifUpiKyi9vfbRSikGny6Qs2R8fc3trG/NExY+iDEOG9pCBPWDibz/3c2kd8d5SVxmd7vVXRSkihS6x2lPH87X2iAhuUf3UuIALHiRgNfQKjdGXP+z88deGxvfxwWJUdaWztYz2RN1Q1T2Mdmiz3PbJJHk2xTQMGGUT3ug+5N78jZfOp0uSFxNG2ZRcN6klb4mu5YruF3/xF/kX/+JfPPG2r3zlK/zMz/wMv/u7v8vP/MzP8JWvfAWA999/n2984xv89m//Nv/yX/5L/tN/+k/E2Pau/8Ef/AG/9mu/xu/+7u9y//59/vRP/xSAr33ta/T7ff7jf/yP/L2/9/f4z//5P1/Ht5VsIGsVIQiuufyLXxEhBsF7wTmhqSN1FanKSDmPzKeB6SRQziPetWHYJjn5udjs+r5vvX8P8/53Yf8hcV7he1vI6NZKh1A+BMbllMrVFDa/WGCqNX6wRb37JqE/YFWfmEVgEhQ+CJvaJasUDI3wpo3cNoHaC+9Viu9Ulvec4TgowgXvKnu+nQuVEdNcqCUZ5jMy3RBEI0u+0NJaMeh2cK7mYDImxidvUEEyqtDjVnEPq54/8FprIcsCdVXg3PV/T4WeY3D4+PLH7Rgj86rhcFJyNC2ZlSUh1BRG6HcsnSLDXPHaVue7xJChaTDaX+nXArCmrbiqmj4bdlqRrJGTTXp9U3Kr2Gdp1fHJjdCzJZl2KBUJrF7V/6a4llPNn/qpnzqtdjrxzW9+k8997nMAfO5zn+Ob3/zm6dt//ud/nizLuHv3Lm+++Sbf+c53ODw8pCxLfvInfxKlFL/wC79w+jH//b//d37xF38RgL/5N/8mf/7nf75xF+nJ9TAWBMV89tFXDSW2rWPet0HVSZBUziPzWWS2CJImx4HxUeDowHO47znY8+w/9Ow99Ow/8hyc/NoLHDxy7D907D107D30HDz0PPyw4eH9hv2HnvFRYD6LuCbe+Nu8dwIRzDVVRKmjPdThHnE2w3eGxK3bkF3dq+CXIYoshpM3GKWv7Wd13UpROGkDkwQyBbdt5E0TySSyV8P3SsP3assjr6nP8WM6Copp1BACvZt5s1l5uW7omIpMOVxcXjXUWUZrBt0uVV1yNJt85Hmmij0QxW5+jxddGBoT0TpSzgpCuM6AO1KoOVY1BJ7/+N34wHhWcTAuGc8q6qZCiaObK3qdjCwz11IF7XxBCAWIw5rX27Z3XkpBZuaEkNG4628FTZLzimKY+D47xYTbxT4dU5ECqeSirPL0zJyOqWlW5Ll2Uy3tZf3j42N2dnYA2NnZYTweA3BwcMAnP/nJ0/fb3d3l4OAAYwy3bt06ffutW7c4ODg4/ZiTvzPG0Ov1mEwmjEaj6/p2kg3RzokSxkcR8IiAxHbVuYiAtNUaIhCjEEXavw98dD6Gon1/TupO2qHD7cmuAgVag7Zgdfu1lVKEEHG1aoOtcUCAPFfkhSYvFDZTZFn7X61Xs6LlokQE77i2Ap2TgeQynxNXeA7U0yaL4eQxxvO15K2pcVBUQdi6GTfvS6MVjIwwQqgFJl5z7DVdrRllwkhHBlp4+mGhjIrDYGhCZLQeN/UbRyEM8ykdU1PH1Qq8rdEMOh2m1QytNFv9/plQRlOGIQN7xNSPmYfnr1i3WaBpLOW8oD+ormVeVKFKjHJEMTz9BBJFqBtP2Ti8fzz7KTcaa+21t9/7kOF9F4kBa55fYXYVtA4YU9M0HaxpMObqK7GS5FV4yZi6Htv5hIGdMw095r5H6TsvnFWXJC1hmE3JTUMdMla18n9TrFx/yfOqOl5U7fGsv3veCcRXv/pVvvrVrwLwW7/1W9y+/fy5BuvkXlWytfX8E8Dk8hR5oJwHJGgEAVEYtUiZ1GJdNardFmTbMEifCZIuWwiRuo74RnCV0FSQ55pOx1B0DXmuyQtDlmvMaw59sdYu5T7jmogrK6xx9AZXXEJbl/DokCCReOdjqGK1LgqfZ1rNQSu01ez0t9Z2hplWim63+9y/dxG8KDoEeiv3DLY6CmBEG5KPAxxExbEotrRi27aBVaHboe/3a0WMwk4RyG9IeP0ySimKFbpv9+2Uvo1YZYmvuNXtKuW5xVjNrJxTFAVbg7OzlnJEB94aPOR+c4v4glPLTgfKqkCpnH4/XEkYpQhklGSqxODIBJzaIltccDgfmNeOuvb4EBAJFBkMe8Wlt90prSjyl9/OQjD40MeYQJY7tL7+B7dMPFVT4MMW3U7aorcuznsbu1lyKgYY67iVz7lNxTz2mYcBZei+8DEoeTVaa7rd1XtuuqiemdHTkOlspTcwOgK3d3fpDm92Uc3S7qlbW1scHh6ys7PD4eHhafXSrVu32N/fP32/g4MDdnd3P/L2/f19dnd3n/iYW7duEUJgPp9/pBXwxOc//3k+//nPn/55b2/vKr69axdCl+lsvOzD2Bja8uT8FXnqvyeu80VFBRhAhNlMODoSYgSFQlsoCk2WtyGVzRRZri4cTN2+fXsp95mqjBzuOwSFu8q2juAxH7wL02N81gPn2l8rrvGOw+mYeVPSyQuqan23H3W7XcqyfO7fH3jN1Gs6MVCnubrn0l38qiIcNJoHKHoatjJBgFlQ2BgQDddbh7E8RZFT19fT+vQyVjmsPkbHkqnvcr1PHOenUWRGs3+4T/CewZnA2JEzyvbphO+z33z8hZ9Houbo0OCaiiy/rDtxJFc1ua4wqkHRgHIEgYqMKNXp5jvnAzF4UJHMKDLbtt15H/Bc7oNKkefUzYtvZzFqatdFosPqOX6JbfZKpjSuz1gyOsVsaceRnN95bmM32ZwuGk/PTthSh+R0mfo+ZejiYpr9c1m63Q5lub7nltA+16r8GEzFJHaA1b3fBN+wd3BAd0XOU17H22+//dy/W1oN42c+8xm+/vWvA/D1r3+dz372s6dv/8Y3voFzjocPH3Lv3j0+8YlPsLOzQ7fb5dvf/jYiwh//8R/zmc98BoCf/dmf5Y/+6I8A+JM/+RN++qd/em2rAZLkdSmlyDua/tAw3DL0RwqbQV1FxkeRvYeeh/ccj+45Dh45JseBqox4v7oD0J0TvL/iEU0xYh68B/MpXhVQrMesjBAjx/O2JS83OVrd3NL0KDCJihgjxc39Nq9MR8EdG3nDBJRE7tew5xTEsLFD35dPGOXt5p5mDdoEOnlOnlmOJmPKMyfIgqEMI7ayAwr94gDDmIgxkXLewfvX+X4Fq2p6+phtu8fAHNLXhxTMgEgjPeahw3gu7I/njGclVV2BNBQ59DsZeXb9LXhPfAeiaPwAiWD1HLXkLaBat22BzhUEny7ik/UQsUx9n4kbYrXnbrHHm92H7ORHFLomzZFK2pa8GYVpaGLOqj/Xbgol13Dl+Tu/8zt861vfYjKZsLW1xS//8i/z2c9+li996Uvs7e1x+/ZtvvjFL55WMf2X//Jf+K//9b+iteYf/aN/xKc//WkAvvvd7/LlL3+Zpmn41Kc+xT/+x/8YpRRN0/B7v/d7fO9732MwGPDrv/7rvPHGG+c6tg8//PDKvu/rVM1SRVRyPiJC8ELTQPSAErSGLFfkuSbLNVnezpiy9sk212VVRB3teyaTQPcKpyjrRx+gDh8RXECGu1f2dS6TiHA4GzOrK0SEIlv/C4cXVURNg+KBN0QfGZh0Yvm6RMDRDjvftFOyVamI6tk5o3xCrh1VWN02gbNEhFld4wPc3tqhk5887gh9c0zE8EH5iRfOaxEB1xi0EfqD8kJtYAZHrityVaGVI6NGKSGKwZMhoqldW/3UuECIASWhrX66pqHjJ15UrSICjRsQgsWoEq1Xo8RTBJzvI0rR7x4vPRxLXmzTK6KeTejomlw3eDHMfJ+Z71GFIs2RekXrXhHVtzP6dkauPfUaDCgPvuQTn/1/0+0/u8NrnbyoIupagqhVloKoJIHgI00N3rcPB1pBVpwNpsBmiju3b7N/sL8Yqr64eFXPn8l2GWIUDvY85SzS7V/NCYQ63kfvfUicVcTtXZZYLHoh43LGtJpRO0evWI+L2Jd5URD1oTMcOthSkdccd5ZsuFUIoozy3Ooc0bVzSt9lneJAEWFaVQiGO1vbZLad9KDxDO0B+82bHPsXvyAoAnWdkRcN3W7zwjBKE8h1Sa4qjHJYGrSKCOClQDA4H6gaT+08IQRiDBgVyazB2uVM4X9eSCACje/jfYZRFUavVjtmFE3jBmS2odOZLvtwkhdIQdSLZcrRNSWCZua7zHyfeegsFhgk57XOQZRVjp3imI6uqGKHdXiu3ZQgKk1zS5IEYzXdM48GZzfzxdi+SpvnitCUjCeexV4/Tn6jTwe1Px1QtSHV6SLAp8Krk/eHxx/bLgx8/DHBCzHwkU1fl0XNJ+j9+8hssSFvTUKosqmZ1xW1czd6Q96JJkIVFYaQQqjkBhBG+Yzc1Lg1aMl7mlKKfqfDtCzZPz7m9vY21hgilioO2C0eMg9buBcMXlcK8szT1DnWBPLiyYogRSRTFYWusKpZBFAOAZxkeOmcbr6rmgbn2+onTcBqRdYxKLWap7nOd4khQ9OsXAgFoFXEmgrnu1jfYG0KOpL15CTD+QyjPD1bMrBzylAw9X3mvouX9a8kT15EGGWztv09teStnNV8hk6SZKmM0ZgetNPPQaLQNEJdB1wltK9DL4oppZ1zoVT7Ku8pxeINj/t+Tt8kgJK2kkq1IZNSoPTZ8EqdfqhrIvoqzhWaGv3wfWQ+I/S3wazHK2QueCbljKqpKWy2ETPxxlHTxHbodpKsu46pyXWNIdLIegbJWikGnS6TsuRgfMytrW2M1tSxS65Lbucfcq/+cV504q+NYGKkmnfQpsTaQKZqclWR6RqDw6oGBIJYanqAWlQ/1U9WP2mhk2msWe0LS+cLQihAHNasbsBjdEOUjKru0zMereKyDylJXlkQy9QPUES6puJusU+V50xdn9J3qVNIcSP17ZxMt88hkfU4x98kKYhKkuSllFYUHUV/YPHhtB7qtcQY2ycGOfkzEBfbCCOIElQEQdAKrL3kE4TgMQ9+APMZoehf8ST0yxPPDCe31mDWJDx7HVFgGhVRIvl6FKwlyXNpFRjmMzq2pvLrGUKd0Fox6HYYz0sOJhNuDUdorZiHEQN7SN8fMgsvnrlnrUeI2KZklB9jtCenHTAc0TTShk8xyunsJ+cDITiUknb2U369s59elQ8Z3neR2A4FX2VKQWbm1G5IXffoFNMLzfJKklUkaOahBwiFqrhdHOKyMVM/YO67aY7UDZJpR8+W7QzGNZgLtYlSEJUkyVJo3T7Rv/zp/grOfE825M2meJWvzYY8EeG4nFE1DSJCtuKv/F+WaVS4qMhJr8gn62+YzchUjY/mRlzwGK0ZdrtMyjlHWrEzGBLIqGOX28WHVOWQ8Iz2F608hS4pdInJHdEL0gRsUeNUO/cJoPGBqnY0PuBDQKLHaOjlGm3W5zQ2RIvzPSRGrJmvRXCmlJDZEud7BOuwdrXDsyQ5P0UtXWrXIVOOrWzMlp0wDe0cqTLNkVpzwtC2LXl1tKRqt9W0Ps/gSZIkl0Qf3IfpMSEIDIfLPpxzm9UlVVPjws0ZTn4ek6hporCz/tfsyYYrTE3H1GTaU4b1CMDPwxrNoNNhWs7QSrPV71OHPnlWs5vd41HzDu30v0ChKwpTYlWzmP3kEYFK9ziudmko6eQlVdNQNR4fAj54zGn1k12LEOesGDWN6yORtQmhThjtCNpRVT16PYfW6QWB5CZROMlxPscoT9/OGdo581Aw9QNK30lzpNbQwM7JdN2OD0lxx8pK/zJJkmwUdbyPOt4nVg2yfWvZh3NutWuYViWVqzdiOPmJ+syQ8vW5dEuSj1JEhtmMwtRU4ebdhzNr6BU50/kErTWjXo/SDxlmh5Rh2FbX6Bqr3OICQeEko459AJQWlJTsH0Vs1qBoEPHYRfWTWaPqp7NEFI0ftCGUnq9le1tmShoZUDd9OsVkLb+HJHmZdo7UEEWkZyr6xd7pHKm576Zh12si046uLcmNowqb86LtOlrPZ/UkSZJX8HhDXkkc7rAuG/J8CIzLGZXbnOHkJ06GlPc351tObqhB1g5NFdRp29lNU2QZUYTxdIzRmn6ng4s5t4p7uJgDQhBLFfqcXNCFGKmdp3YO5wONMzhvGfVr8mz9qp/OEoHG9YlBY1SJUvLyD1pBSgnWlDjfx5sOWbaea9yT5DwEzexkjpSuuF0c4DLL1A2Y+R5lKDh5/Frjh6cbqX3BZ0qhG2qfpX+gFZeCqCRJNsMTG/K2YE1eXY8iHJdTSldjlN6I4eQngsA0aiRGss35tpMbyKr2FdrCNMz9zd792M1zRITD8TFaaShGWOXwYjndxCqC855qET6F6EHazXejnsWHLWLMgPFSv5fXIQK16+EDGFWhdVj2Ib0Woz1RN1R1D6Md2qz395MkL6eoQpfS9zFEetrTsVOmRI7qHYJYOA2XpY2mngibF79Xi7/j8fu2b5DFVzl5v6feh5SjXFTfzslUgwiIWo/z/E2W/oVuAPnu/0ZVHUxTI9aCNmAMYrJ2Hb02iLHthbc2oNejCiRJLs3ZDXl5b2025AFMyhlVUxNj3KiWPDgZUg6dNa0iSJKWMMpnFLqhCRmb0NrRzXOi1OyPj7i9tUNn8djVVj856sbjYyAEj9GR3CiseTxQVjGn8QNq1adTzJb4nbwaEXC+i9IWzRyj/bIP6VJYUxLFti16nXG6SE5uJBGI0RJiRowZIpooMJNIbkq28kNyVbJf3mLuuohSKPTjDAkAdeah/vEd5eQ+o5585/btz/m7J8Iu9WSY1b6vcDbcUk8EXZsTaGW6oWur1JK3RlIQdRMMR7gPPkDKafs4JJH2wUq34ZO1i0BKt0HU6Z8tYkz7PsYgevG+KbhKbhKRxxvyyKDTX/YRndu8riibisa7jQuhAMZB44IwSNVQyRrrmopcNygd8X4z7sdKKfpFwbQqOZgcszMY4UKgcZ4YA9BuvusUBqU++sKA1gFrKpzrYI3D2ub6v4lXFEXjXI8YLRaHNetz7C+jFGSmDQkb16XIy2UfUpJcChFFiNkifLIgiigAAaPaBRNKCQJMXI9hPuOd7IfsVbscN6Nzb9iTRY50UiOFqPb3InDmbY+1gZagUKjF38mTyRXtH88GWEqffPTjqqzTPz8RZsmZj3s6zHqyOmuVnc5gVDW1zzcjebsBUhB1A6i7bxPvOUJv68m/iA6cRwUP3oE4VKxAIsRFqv7M4GoRTmnd/joJs54TXElWQN5Jd/pkJen9e2c25I2WfTjn1njHtJpTNjVFtllzoQDKqGhEkaUh5cka00QG+ZzC1lR+s16hVUrR73SZzEuOpmOUUlgdKazBmJdXhhldE8VS1X16OqxFa5sPGc73kKjQqiazgnPLPqrLpXXA6Jqm6WKNw5ibUe2VbJ4YDSFa4iJ8igKIoPAY7TE6PPPSRtCMmyGFrnmju0fXVOzXu9TnWELx+PM93bb36p4Ot0Q0hJMv8biYQJRCnYZcJxVbJ1WoJ296OsxqP6urLSL1ys65G2RtS15EIyq9erkuUhB1k+kMiuyJHPuFDx/RgQuo4MB7iE0bUj0dXBHbB+qT4CrPIS+g20OK7ukvss145TdZXacb8uoG2VqPDXkiQtnUzOqSsqnJbYbRm/ekOomKOgjDlEIla2yQz8h0Q4ia17/cWD9aKYbdLlE8RmuUOv8a9LPVN1Xdp9uZrOxFkIjC+S4h5MQYsaZEq4i6oTNKrKmIYqiaPr3OeGX/XZLkLBGIYgnhTMtdBIho5bDaoVU89+erY4FrLKNsSsfW7Fe7jJsBcs2LcJ4Ot5Q6G9qfL8A/G2aJLKqtTsMsRVVahC42X72lC7lu6JjUkreObuYzZPJqToOrx3fiFwdXbaWVKueo6hh1dICSiLIZFB3odKDTR4oOUrQhFfb8J6FJ8jrWbUPe2QCq8Q7nHcYY7AYNJz/hBWZRoyViN+/bT26ITDs6piJTjjL0ln04S6O1QvNqz/1KySKM6lM3vZWcFxWiwfk+IWg0DZlpbnyBeBsSVu2/i+vSyefLPqQkeaZntdyJgJy03Bn/WsFKFMNRM6JrSt7sPaBjKg7qHVxcr+uds2HWs34eNqspKwvNaoVRJy15eWrJW0spiEpenbaQWyTvPg6sRKCpUOUUVR2h4h5KBJUV0O1A3kE6PThbObUm28uSNXK6IW9O6I9W+jZ2EkDNm5LGe2rXoJWikxcb1453YhI1TYR8RU50kuTihFE+pWNq6rg+yxFW0eN5UV2s8VhbL/uQgPZ0x4cO3hdEEawq16J98LK0/y41rumQaYexN6wHMVlbMerTQeNPttwFtG7b7i739EpRhh5NzNjujOnair1ql6nrc1OWUygtaF3jQ4E0XbIVCaMG2RyrGkgteWtpda/OkvWk1OOQ6eRtEqEq28qp6QwVH6GIqKJo37fTg04XybuLj+20Q9KT5FWc3ZCX9Va2RVREKF3NvC5P15grBd0NDqCgvbibBIUPwig9DCRrqmdLMt0gCFHSqdbrsqZp50VVfbq9dnbLMp0dSC7Rk5lqI1+IN7omxKxt0TPHK3Fhmmyek5a7uKh8knjSciev1HL3qoJkHFZbDLMZb/cfsF9tc1RvEW7Ic4BSEa1rQihgBcKo1JK3/m7GPSNZbUpDt490+4/DqRhQ1Rw1L1HTCcSIVkDRbWdO9QZtS1++qJrKO2l7X/JyIpiH78NsRlAZdFevHUZEqFzNrK5w3lG7BpSim+cbHUCdmEdwiyHlSbKOtAoMsjmFbijTyfGlycycRgZU9WCpc4l8yHG+i0TQqsZucCWQUpDZOY0bUNc9Op3Va51Mbqa25e5x+HR2y13bIuuW9BihmLgBmW642z2gt6iOKn13Ccdy+VYljDrdkqdrmpBzUyrPNk0KopLl0AbpDZHe8PHbgkOVM9SsQk0mKAkordtwqug8HoaeL6qm0qa+5CmnG/J8REbbyz6cJzwZQHlqV8OGt+A9y3FQVEHYSj+SZE0NsxmZcgQxpJPjy9POJSoX86L6FPn0Wk8Bzg4kl8VA8lQBBFrFtnXSd7HeYW2z7ENKbigRiDHDx7xtuYuLjW/i0dqTXXrL3atzMeegsgzzKR/r32e/2uG4HhFXfF7peaxCGDXIZljVEEUTSeXz6yoFUcnqMBky2EYGZ97m67albzJFHR+286a0aedNFV1kMEL6I6Q7SO18G+50Q15Vr9SGvDaAapidtuDVKKUo8gK9KmdMK8IJzDwYETZwRntyAxSmpmNqjHZUGzyg/KqcnRdltCPLrmdeVIgW53qEqNE4rKlX5oJ3FRjdEGNGVffpGX8tbVDJ5hBR+JATYtG23Ymg8VjlUSqs7H1R0IybER1T8kbvER1TclDvUofVHBlxEcsMo3LdPs/m2lPFVHW8zlIQlaw2WyDD4slh6L5GzWeo8hC99wCV59AfIaPtx1VWKzycOrl8qpy2G/Lmc+Jgl1XYkPe8AKqTAqjnOg6aRkEnVRkka0ghDLIZhalvxIXGqrKmQcRQ1X20Dhjjr+xrPR5I3kE2cCD5eSkF1paLFr0+RT5PP6fktcVo8KFYDB5XKIloXa1U5dN5VKFLE3NG2ZSurXlU3mLqBsiaV8wuI4x63JLXUK/ZZsLko9LVerJelIKsg2x1ECCKtLOmJsfowz2UtdAfwWib2B+1oZRND1Q3WlOjH7yHzGaE3tbSQ0gRoV4EUI331L4BIQVQL1FGxThoRAWK5eeISXJh/WxOrhsEkNQqcKWsKYmiqZoBvc7VDMmOUeN8jxAsiF+04qXH8OfRKpLZOS70iNUQax2ZrVIglVyICISYEULRLgMQFve/Zq0r7aIYjpoRPVPysf4D9uuKw3obv+ZhymkY5Qvg6sOoYTbDKkeU9Dx7E6QgKllvSrVD0Lt9IkA9R0/HqONDtNHQHyLD7bZ9rz9c2Q1qySsKAfPghzCfE/L+Uv99HwdQ7RDyyteIQJFlmNQ2+kJB4JHX1EHYLWSx7SZJ1odRnp4tybVLA8qvQTsku63AqeoBnWJyqRUSTw4krxZVVymEehmjPVqNCbHAuRzvsxRIJedy2n4XCkQ0IoKiwepmraqfXkwxDz2amHGrOGoHmZe7zHyPdX58USqizdWHUYWuKUxNrhyV3Izh75suBVHJzVL0iMViLoer0NNj1OSH7Ua+/gAZbkN/ROyP2mHnyfoSwTx8D2YTgrJL25AnItTeMavK0wAKILcpgDqvg6CpoiInkGnL9Ux9SZLLM8rbljwXLet8QbFO2gqcEud7eNMhy6rX/pwiisb3iCFDJGB1lQaSX5BSYE2N0TUh5jhXnAZS1laYFEglZ3yk/Y7Qhr9r1n53EV4yDuttBtmUtwf3Oah2OKq3Fgsu1tNVh1GK2La+65o65pf2eZPlSkFUcnNlHeLOImzyDXpyjLr3PoqI6Q2R4RYMRsTeCDppqOy6aTfkjQlekNFoKcdQu4ZpXeKco/Q1CshNhkmTts9tvmjJCyEyTD+2ZA11TEWuazSRWlLV7XUy2hF1TVX30Nq/1ryoJweS37RKjOvXBlINRjeEmOFcB+czMusXgdTVzfZKVtuz2+8c1ri1br+7CEExcUMyXXOnu0/XVOxVu1RrXFF7lWHUMJuR63ZLXmrJuzlSEJVsBpsTd+60vw8ONR2jH95D3X8f0xssWvi2kP4W0umRzj5XmxofLDbkVUvZkPd4BpSjbhxRRYoUQF1YENjzmiYKQ52qDpL1o4gMF9VQVUiv0i6DNRVRDFU9oNsdX/hCth1I3sX7AiFi9XxjLoavQxtIOYx2ZwIpmwKpDdS23xWEkD/Vfldv7Pw1FwsOq4xRMeHj9h575Q7HzQhZgaU7r+IqwqiTlrxMecqYWvJukhREJZvHZMjWLQK3IATU7Bi9/wj16B6q22038J3Mler0Qa/nk8FNpcopeu/eUjbkfTSAEgprMSZdgL6K/ZOWPAmYdDdL1tAgm2OVQ0iv0i7L6bwo325su8i8qBg1je8TgkHhFq14m3lBfNVuYiAl0g6hjtG2DbkqolREKUER02uaCyEawkn7XVBAwOiz7Xeb/YMSNMf1iI6peLP/iK6t2a92aNa0Be0ywyhNYJDN6Oiaak1/HsnzpSAq2WzGIKNdwmgXYkTNx6jDA/TeA1TRgcFoUSk1QroDSDN/lsud3ZA3urYNeWcDqMo17RBya1MF1GuYRcUkaGJqyUvWlNWOri3JTUPp06u0y6RVJDNznO/T6C5FXr7w/dvWoALnO0gEo06CkM2+IL4OTwZS7Qwp5y2Z8dhs9QMpEUWIlhgzQsxAFDG2rVaK9mJb6faWpBbBFEra33MmqDr983K/n6vS3sdyfCiQaBARwG9U+93FKKrQpYk5o3xC11Y8KneZugGyho9LrxtGGRXItKNjanLd4MWkF3tuoBREJckJrZHBNjLYJkpEzWeo4yP0/kNUnreVUqNtpDdEeiNIIcT1CgFz/+yGvKvvo3feM6nmiwCqTgHUJTlpyaujMEyDgJO1JIwWMytcyEkBxvIZ7Ymmpmm6GO2x1j3z/Z4YSB4D1qSB5Mvw5AypHOcLXMjIzGKo+WvM+7psMZrT8CmKPd3sqsSjtSdbHKugEdEgCkETo168TQFtOvV0WAURpV8UVMla3T6jaELI8aftd3Exc21z2+8uIorhqN6ib+e83X/AQV1xWG3jJVv2oV3YRcIorQKZ9uTakWuHVgGrPJnyRBR1XN/ZWcnzpSAqSZ5FaaQ/RPpDogiqmqMmY/ThHspaGO0Q33wHGWwv+0g3gwjm0cmGPHMtG/J8CBzOx1RNQwiBPMuwKYC6FCcteR0J2NSSl6yhrq3IdYPWkcanAeWrwuoKiYaq7tPTY7R+svIihIzGd4mLgeSZbZZ0pMmJs4FUjBnOd84EUjXGPDtQvEoiihjtafgkohfhk6CVwyqPUuEj1UyKCC+o9hFpw6qToKoNalQbWIldzCfVQGwrqk7DKkHpRUiFnFZaKSIhaqLoRcC1CLmWkPeEaPGhIAZLFAUSsLpEm5MtiSmEOj/FzPepg+NWcbQYZH6Lue+ybj/H54VRikiuHZl25NpjtMfgybQHJYAiBEspHdbte07OLwVRSfIySiHdPtLtEwHqOWbvPvr4AHnzR4h3PwZZ6lu+Snr/HkzGBB+R0c6Vf70owvF8QuUaFNDrpFdiLstJS57ESDeFUMka0kQG2ZzC1JQ+PTasknZe1LydF9UM6BRjlGoDAOe7hFAgkgaSryKlwBiH1o4o2WmFlDWezFZo7a40YIlRt+12Yheb3NSinSxiVE1m/GtXJil1ElYBhGe+jwiAakOqRTWVoIlegxhEadqwSlAIQSze+ycv1VX7dyyO9+T3J9VYj38vi5+pnH6+x1VbZyux5Jk/+6fb76IIGk+mm7Wq4lpVXjIO6y0G2YyP9e9xUO1QxwIfDT4agti1aNtTKmJMiRVNIYFePiEzDr0Io04C1CCaKqbgaZOkICpJLqroEd76cdTkAPPDv8aMD4hv/xgy2k3b9q7AMjbkTcppOwsqRoo8VTtcFn+yJS8IQ9JJarKeBvmUTNV4MaQT5tWjlGBNifN9at0jtzWN7xGCQaeB5CtPKTDKoVUbSHlf4MPg0gOpdtC4bQdoxwyJZ6uePEZ5lP5o1dNVOwmGlAqcJ6zSZGjCov3v5O3q8fu0tVUgIOrk9+qph64n4wx15kWi07erJ4MrhSwGtbdJr1E12RWHhZtI0EzckFzX3OoeEqImiMFFu/hvRpBFMBUNXiw+mhXYuidtxZNxi8onjyai0WiJ5KpBFNQxS7OfNlgKopLkVSiFjG7heyPM/ofob/9P5K0fId59B1JwcWnUfHLtG/JmdUlZ1zTB0c3Sv+Vl2veaOioK0pa8ZD3lulkMT/XMw9W3CCevxmiPmArXdJCYIQJWlWgdSOHhenhRINVu2bt46BFFL1ruMmK07aBxAQhtq6Zxa1HJczasyqxC4qvN05LTb3URWMlpIyCn4dXZ34taRFBq8VEBq92Z9rvkqjSxoKkLQDDKk2tPbhx92lY3EYjoNqCKFi8GH7O2ekpOQipDlKsKfQSrPYV25KZtudOLgeNGxbbGLmrKUNDUW2g3pNOZpMrUDZeCqCR5HTYjvPGjqNkx5ofvYo4OkI/9GHH7TqqOel11iXn4HnE+I/S2rmVDXu0apuWcuavp5kV61fwSTYNiGjUxhtSSl6wpYZjPKEyV1kivAaPrtr0pkgaSr7HXCaROqp5OwieJ5rTqSeHRuh2QvKlP9Y+/78dtecmqUwTJKEP2VMGcoIlkxtExFVpHlLTZoojCx+y0isqfBlXmcTXVhSt8BasCmXEUi8onTftnq9rAPyI0IaeWx+fvbfv0DOf7VFUKozZdCqKS5BJIfwvf6aMP7qP/+n+h3/g48c0fgSKt9H4l3mEe/BCZzQnFAK6hMinEwLicUbmGjs3Qm3pmegW8wF7Q1EEYpR9rsqb6tiTXDQpFlHT6tOraC55y2YeRXJInAymL950zgVSN0c1iHpg6rXgKMXtc9SQRrRqs8enCN7mBFBFDHQz1R/6mDVwLU6MXA+9hEcdGg5eTyil7Wjnl4+PfnwRURgVy3VYOFifBk/ZYvdgaKQoXLXN58SZZrWIKoxIgBVFJcnmMJd75OFJOMB/+EHN0QPzYjyO7d0Cn/udziwFz/wcwm+JNfi1hXhThaD6lcjVaK0zajnep9hYteR0CJgVRyRoyKtDP5uSmpvTpBYYkWZY2kPJoNT0TSPWxpkApIUa7aLcDJR6t/UZXPSWJYGiioXkq61FErPLkpqajI2jQohDkdNbUyRyqPM8IuiLTDqsDi77NNnh6hW1+KYxKIAVRyWvyItj07P4E6Q7xb/XQhw/Q3/lz5O7byFs/gnQHyz601SeCfvg+zKaEqGE4vJYvOylnVE1NiJFumvF1qSZBMYsaQqCb8r1kTQ3zKZlucNGS+leSZPlOAimjp4Ro2/XwStDKtXOL0kVtkryQoHGS4/zTreaP51AVxqGYo21OI4EQzWJb7Os/D6YwKklBVPJKXBQeOpgEuJMJt7J0Yv4EbYi33kbqOfrBB+jxAfHtH0duvQmp2ua59MF91OSY4Hy7hfAazOuKsqlovEsh1CXzAvthsSUvzYVK1lRhagrdYLWn9GlAeZKsGqM9Rr/awO4kSZ720TlUubI0/vLvYymM2mzp0iC5EBHhwAnfq2CvgUc1/MUUypCGgD6LFD3CW3+DqCz6u3+BefcvULPxsg9rJanjfdTRHrGqkOEO11F10HjHpJxRNjVFlqXh5JdszxvqoOgQU0tespYUwjCbUZiayqegOkmSJEku00kYFaOmqoZESfHEpkj/0sm5lUH4QQ33Gxg7sCjeyhVRFH85gyApjHomrYk7b+DvfBzZf4j+qz9F3/sBeLfsI1sZajZG791DZiVxsAPq6h+aQowcz6dUriE3GSbN8bpU46CYRYVIoJOeaZI11c/mZLoh0s7ZSJIkSZLkcqUwajOlf+XkpYII95s2hDpsoPawYzU9ozBK8WYOB07x/bSc5sXyblsdZbuo7/0V5rt/jpocLvuolq8uMY/eR+ZzQn8LzNV3DIsIx/MJlWu37FibLjAvkxM4CIbaC4NUCZWsKas8PTsnNw1NSNVQSZIkSXJVPhJGxRRT3HTpXzh5oWPftuE9amDmoacV25lGn7m4LLTiTgbfL2HfpaqoF1KKuH0b/8aPIsfH6L/6M/QH74Jrln1ky+Ed5v4PiNMZoTOA7OmBiVdjUs0pmxofPMU1fc1NIXLSkgddlVryknUlDPPpIoTKSAPKkyRJkuRqPRFG1SmMuunSsPLkmeooPGhgFmHmoFCKHaOeu/52ZBWzCH8xFf7vW0JHp5P2F8pywhs/gpoeYX7415iTYeajXTZmx3AImPs/gPmcYDtQXM9K9LKpmNdpOPlVGUfFPCpILXnJGuuYmlw3aCKNpMeJJEmSJLkOTwwwr4fk+dMtNy8venj5ldQzPsczPkipiCJuzKXZdUtBVPKEKMK+gwMP89BWN2wZhT1HsHQ3g/drxbemwv9tKJh0r30xpZDhDr47wBx8iP72/0TefIf4xjuQd5Z9dFdLBPPoPZhNCGKgP7iWL+uCZ1LOKZuKwqbh5JfNCRwuWvK2UrdjsqYUkWE+o2Nrqo+stU6SJEmS5Co9GUb1UecIn66C0u3SEqUjSkW0iigV2oAqhVSvLQVRN8B4PGZazXHeoZRqfwFKKfTpn9Xp3z3PNAgPmzaAqiL0lKJrz3/vaudFCe/Xiu+Xwk+kLdfnYzPC3R9FzY4x738Pc3SAfPzHiVu3Qd/MkhK9fw8mY4ILyGjrWr5mO5x8QuUqMmsxJiUll0kEHnlDFYSeiqnvO1lbg2xGpht81GlAeZIkSZIsgVaR3E44KVWSy2iRl4t9DkEjogneIGIBDeoknHo6pHocUGkV2iNOIdULpSDqBphOp9w72sMvgiitNEopjD65szwOok6DqTMBVRA4Wmy4KiNYNH2jMVrRxCeDLF4SarXzooTvl7CdCbeydA88L+lv4TsD9OH9dnbUmx8nvvkj0LlZiZ462kMd7xOrCtm6xXXMXhERxmW7IU+hyK5hIPqmGUdFGRVaAkVKoZI1lWlH11bk2jP319MunCRJkiTJR7WXmm011KVURV34kiN85C0iCpE2oBLOhlT5M0OqswGVUmFRVZVmKkMKom6Et99+m8O/fA+vFTEKQiRGoQkOEUGhEBHa/3HaFisCc1GMg6aJQoxCTwtBwVgpNAqURumT3z87kDLGYk2GNRnG2DQv6nUYQ7z9MaSaYO69hzk+IH7sx5Hdu6DX/5V5NTtG799HZnPi8BbXtS9hWpdUTYP3gW6R5r1ctmaxJa8JkVEKoZK1JQyzKYVpqEK27INJkiRJkmTFKCUoFXg6pBIBaEOqKAZBE73GSwbK0NZ0PQ6ptH5WQLVZIVUKom4IrRRGG8w5LwLrCHvBUEWFR+jbeDpYWEQWwVVEooAIIYZFLC2IRNo7Wly8fwSlyWx++mtHW+4Hy19ONf/XNC/qwqQzxL/VQx89QH/nz5G7byNv/SjSvZ5ZSleimmMevk+czwmDbbim1riqqZlVJVVTpxDqCpy05NVB6CGpJS9ZWz1bkZsGhRAlnR4lSZIkSXI+J9VbSgX0M0Kqkza/uKimatv/LYgGFduxOrqdUymSEcPND6TSmdaGCQKHQTMOmjoIRgLb5slKxcdtd/rcBSshBkJwzMsJgqC1oaNz7pUZRcj4iUFOZi1apcvUc9OGuPs2Us/RD+6hx4fEt34Muf0mrFtrmWswD37YhlDdIdjrGQDsgmdczqhcTZHlaTj5FTiOiioqdAzk61+0l2worQL9bE6hG8pww5dFJEmSJElybZRqAyZU/MjkybMh1cmvEPRJH9ONtmZXs8nrmAbFftDUURFCpK+F7JJyobYay8CimyEEjw+OIjR8ex98qbjTzSmynNxm5DYjMzYFA+cgRY/w9o+jj/bQ734LjveJb76DDHdO4vfVFgLmwQ9hPiXYzrVtBIwSOZ63c6GsMZjzlgsm59bExZa8ENlOIVSyxobZjFzVeLFcx9y6JEmSJEmSsyHVCUO1EdfIKYjaAE5gzxvmUVEHoSAwvOKLRmMsxlgKIHjFe8FjqxpblQDkNqOTZRRZQW4tuc2w2mzEne6VKE3cuUscjDB799HjQ+SNjxHvvA2d/rKP7vlixDx8D2Zjgli4ptZCEeF4PqNqGkSEzKR5L5dNBB6FtiWvfzm7TJJkKXLdUJiaTAfmIQ0oT5IkSZIkuWopiLrBosBx0BzFtg1PSWCkwFzzFeMtI9yXnEdkfLIbUAiNa5hWcyblDKUUuc0ospzOmWDK3IDh3Jcu6xDe+jHUfIx5//uYg0fEt34E2X0D7OqFLXr/HkyOCE6Q0da1fd1Z3c6EcsHRK1KbzVU4ijq15CU3gDDMp3RMTRWup2U4SZIkSZJk06Ug6oYqo2LPtxeKLkb6CPmSOpOMgjs2cN8b7jnNx/NIJy/o0A6ODiHQeM94PmPMFKU1HZvTyXLyk1Y+Y9E6tVadkN4I3xmgjx6h3/1L2H/YBlKjXViRn5M6eoQ6PiDWDbJ169q+bu0aplVJ6Sp619QGuGmaCEdB04TIVgqhkjXWtyW5diDw0ckNSZIkSZIkyVVIQdQN4wUOgmayGEaePWMY+TLkCnZM5MNaMzTClnk8gM0YQ9cYuotgygdP7RzzpkYQMm0o8pyOfTxjKs2XArQm7r5B9LuY/Xvob/9Zu13vjY8vfbuemh6j9x8Q53Pi6Dbnnnr/mnwIHJdTKlfTsUW6jVwBEXgYHm/JSz/hZF0Z5elnc/I0oDxJkiRJkuRaLT2I+mf/7J/R6XTQWmOM4bd+67eYTqd86Utf4tGjR9y5c4ff+I3fYDBoL6z/8A//kK997WtorfnCF77Apz71KQDeffddfv/3f5+mafj0pz/NF77whY26CBWB46A4DJpmMYx8pIVVms881EIlwndLw0/3PMVzjs0ai11shRMRXPBUTc2sqgBZzJd6cvD5Rs+XshnhjR9BlRP0vffRR3vIG+8Qb78F2RJaTaoZ5tH7xPmMONi5tgqtKMLxfELlGozSaTj5FTkKqSUvuRmG+YxcN7iYBpQnSZIkSZJcp6UHUQD/6l/9K0aj0emfv/KVr/AzP/Mz/NIv/RJf+cpX+MpXvsI//If/kPfff59vfOMb/PZv/zaHh4f85m/+Jv/hP/wHtNb8wR/8Ab/2a7/GJz/5Sf7tv/23/Omf/imf/vSnl/hdXZ+5C3zgNfOgqL3QUVc/jPxV7erIfW/4XmX4ZDe8dF7VyfyofDH/SESovWNSlYwX86WKJ+ZLZYv5UpsXQkh3SHi7jz4+QH//rzCHj5C3foS4dfv62vVcjXnwHnE2J3RH1zq3alK2G/IkRoq8uLavu0nq2M6GatKWvGTNFbqioMboQOPTgPIkSZIkSZLrtJJX69/85jf53Oc+B8DnPvc5vvnNb56+/ed//ufJsoy7d+/y5ptv8p3vfIfDw0PKsuQnf/InUUrxC7/wC6cfc9OFKHzvsGbsIfjAlol0V/JftXUyL+o4KO65ix+oUopOljPq9tjqDegXHWIUxvMpD473+ODwIfcOH7E3PmRSzqhdQxR5+Se+KZQmbt/Gv/njxHmJ+vb/Qn//L1Gz8dV/7eAx938Isxkh68E1zmea1SVlXdMER7GMKrANEBdb8qq0JS9Zc4rIIJtSmJrKp8eLJEmSJEmS67YSFVH/5t/8GwD+zt/5O3z+85/n+PiYnZ0dAHZ2dhiP24vog4MDPvnJT55+3O7uLgcHBxhjuHXr8TDkW7ducXBwcI3fwfIYrfiRrYL3JGDWpELhRfOiLspoQ7d4PF/KBU/tGuZNBUBmLJ0sp5MX5CYjzzakjc9Y4t2PI/UM/fA++ugAeeNjxDsfg6uoFooR8+A9mE0JykC3d/lf4zlq1zAt58xdTTdPc6GuylHQlEFhU0tesmY0EaMDRgWMiuTGYZVD0EgaUJ4kSZIkSXLtlh5E/eZv/ia7u7scHx/zr//1v+btt99+7vvKcypbnvf2Z/nqV7/KV7/6VQB+67d+i9u3b1/sgFfQbeD/0Io8v742qNdVANHBeyFjuwedS6riOttgISLUzlG7mnE9Q6Ho5AXdvKCTFxRZRm5z7LokeK9i0IfdO8jxHurhB+hmhv7Y34DdN3iV5NIYw9bW1kf/4v4PEPG4vIve3r2EAz8fHwJTVyIGtgdDrF36Q9qNVEUoUSCB3VxfadinlKIoUpVKcn6KiFZxETS1v87+WamIJqJVwGqPQkAUJT3yl/WHJ8lrUeR5el5KrlK6jSXXId3OrpNXmlu7uwyedc11gyz9FrW72160bm1t8dnPfpbvfOc7bG1tcXh4yM7ODoeHh6fzo27dusX+/v7pxx4cHLC7u/uRt+/v759+3qd9/vOf5/Of//zpn/f29q7i27p2UYS6bpZ9GBcyELjvDX/p5Vzzol5VrtubeYiB+bzkeDIBBKU1HZs/Mfg8sxn6JlbU2B5s5+jDh+gH/z+4dZf45jvIYBsu8P1ubW1xfHz8xNv04UPU/n3ivCZu34Lp7JIP/tmiCIezMfO6BEBZcM5dy9feJFHgA2eYeeipSBOu9usVRb52j2XrTVj9Qd1yWs1kVMDo+PjPOpwGUVpFrPJotXhxSgHSLvMQUTjRlNEiGPLc0jR+qd9VcvOl21ly1dJtLLkO6XZ2vaKP7B8cUN2A65oXFRktNYiqqgoRodvtUlUVf/Znf8Y/+Af/gM985jN8/etf55d+6Zf4+te/zmc/+1kAPvOZz/C7v/u7/P2///c5PDzk3r17fOITn0BrTbfb5dvf/jaf/OQn+eM//mP+7t/9u8v81pJzOJkXdd8b7jnNx/N4tV/vqTY+Hzy1c2fa+AydrKDICoqTbXzmBrXxGUu8/TaxKTH799HjQ+Tu28S7H4fi1Yb1qukR6uABcV62Q9Gv8YJ2Us6ompoQI900nPzKHC625BkJZCs8fy45LyHTntw0FNphtQekbVMThcDiv4tf8qz/8py/4yMfd77HBFlUMD0ZMJ38XqvYhk06YlXA6NCmSydJkwIRTYwaF3IC+pxfN0mSJEmSJFmGpQZRx8fH/Lt/9+8ACCHwt/7W3+JTn/oUP/ETP8GXvvQlvva1r3H79m2++MUvAvDOO+/wcz/3c3zxi19Ea82v/MqvoBfbwH71V3+VL3/5yzRNw6c+9amN2Zi37i5zXtRFWWOxpr0LiAiNd8zqkmk5BwVFllPYnE6ek9mMwmYYfQPa+PIu4c0fQ83GmPe/jzncI771o8juXTDnf0hQ5Qzz6IM2hBrsgLq+lGJeV5RNReNdCqGuUBXhOGhc2pK31rQK5NpRmIbcODTtn40Oi7//6IsAgjoT5Tz9uKyI0oZNEX0aQkU0LIIqzoZZzwmygNOwSZ2GUQGj26qm9n0FDYRFUOajoQ4ZK7prJUmSJEmSJDkHJRcZsHQDffjhh8s+hEvx//3//B+oj1wsrAcR2IuaIIqf6nmKFbi+CDFQO4cPgafb+PIsp7gpbXwxoI8eossp7C7a9Ua7z23XO23Na2rMh+8i0wmhM7zWDXmNdxxOx8ybiiK7IeHgCjppyZt66KtIdk039dSadxmEXDvyRfBklcdqT7aYjyQCTcwJ8iqvRbUxkiailKBU+3sNaB3bgEkEpQUloBZtcnLyf+qkVulx9RWLmU0RTRCNj+bKh4inNoPkOqTbWXLV0m0suQ7pdna9oq/4yZ/7f9EfDpd9KK9tZVvzkgTazGNXR+57w/cqc6Xzos7LaEOveHwh9LiNr0YQcmPoZB26eUGeZRQ2x+gVSNAuShvi7ltEV2P277Xtem98jHj3Y9DpP/tjgsc8+AHMZ4Ssd60hVIiR4/mUyjXkJoVQV+mkJS8jXFsIlbw6ozy5WVQ9aXdaBaVVQFAEMZS+w+u3rLXtdm31E08WS50trLriWWJJkiRJkiTJ+kpBVLISrnte1EU9u41vzricYoyhY3O6edG282U5Vq/ZbKmsaNv15mPMBz9o2/Xe/BHk1htgz2xjjBHz4Icwm+JVDt3nhFVXQEQ4nk+oXINSYG0Koa5KGRXHQeNTS97KUkRy404rn8wieDLKoxREUTQhJ3J9QXGSJEmSJEmSnEcKopKVscx5URehlDoNnKCtlqpcsxh6ruhkGZ28aLfx2XytWvikN8J3BujxHvp7fwkHD4lvvYOMbrWlaw/eg+mYEIBrLhedVHPKpsYHT69IF9dXxQvseU0VhIFezfvgZhKs8hSmDZ4y7dvwyTSLdjtFiIYydkmDupMkSZIkSZJVloKoZKUMlFBp4d3SrMy8qJexxjJYVEtFidSN42g2PW3h6+adxTa+jHwdWvi0Jm7fJQ52MAf30d/+X8jdt6E3QEJNrB2ydetaD6lsKuZ1Gk5+lURgEhUHQVNHRZ5a8pZOE0/nPBWmQRPIjMOotu8tRk3l8yufp5QkSZIkSZIklykFUclKOTsv6vuV4RMrMC/qIrTSdIuCLsVpC9+kmnM8b1v4uragk+enFVXZBbbUXTubEe6+g6qm6HvvozodwnCLONrluiouRITKNUzKOWVTUdhsvVoe10QdYS8YqqiovdBRge6K56U3k5Bpv5jz1GD//+3df4xcVf3/8dc5587sTostbalFoMZQFAEhUOsvIiARjDGKmBAS/STQQjSIhESiQEwDmIhBk1rQ0ICiJELiHxJITIwhQQkoiJZfIZQf0gIJ/YLUdvu7OzP3nvP+/nHvzG5/bNttd2d/PR9JmdmZ2eHO9PS089r3+327VU+5nJUjmIoU1DaqngAAADB1TeJPwZipgpOOy6Len6Tzog7XgVv4WtrdGpSc1F+rq7/eX7Xw1VSfpCGL9R+jeMIsucFdZYteszXu/88iRg3mLTWrVrxm3lYtyxQClR9jKVk5lHxHKlvxQoqaGyQyqN5xSuoL7TJ8CrmComqhLe/KfS9ZULPok/G7AgAAgGmCIAqTUt8UmRc1GsNb+GKKaueFtu/eoa2S6iFTo943eVv4nJfNmiOXZZLGJ4gyM7Xytgbzllp5rjzmKmLsBnqT6v2YBnYnpy1F2YaXx6TZzlQn5+uZms/VyJrqDy0FV1ZBlbGUlMeaovHXMwAAAKYn/qWLSWsqzos6XMEHNfrC/i18g7sVvK9a+MqB5/VabXK38B2l/aufckmmWggMJR8HuUkDhdeu5NVKprpFzSOA6gmnpEbWUiNrKnOF6qEl75JSCtpT0G4HAACAmWH6frrFlDfV50Udrn1b+PJhLXzOSX1VC1+jVld9ErfwjcbBq58yBU8yMtbMpO3JaVsMakXJLGqOpDCNAt7JyVSvqp/6QlvB56r7QjKplWpKVD4BAABghuFfwJjUpsu8qNGohaxbARVTVOsALXx9tbrqoaZaVj52qgRTRYxq5i0NtlvV9fLU8xnVT+OqWQ0jbyWnVkxqyNRPADWuvItqhJb6q+qnvtCWc0nRggaLflH9BAAAgJmKIAqT3nScF3W4gg+a1RekqoWvlefa2RzUjsE9crIykMrq1WWmelZT5sOkCqbMTK0i12C7SfVTj8XOMPLo1YqmYFHHBiKQ8WPqC201Qkv10FLN56q5QklO7VhXEmsdAAAAIIjClDCd50UdLuec+ut19ats4Yspql3k2tXcrZ2Du+ScUz2rlW1+WaeNL1M2QfOlYooabA9VP7XytiRToPqpJ3ZFpy3Rq5mcUkya7U21GfjnpheCi93B453ZT05SYUF7IrOfAAAAgOEIojAlzJR5UaMRfFBj2GnOOmfi27Fnt6ROMFVXf70MpmpZpnqoKQvjV5UxVP3UUitv71X9VKf6qSfaJm0uggaTUyua+hXV4G0fB6b+0FIja6nm26r5XJkvZObUinUZ1U8AAADAARFEYcqYifOiRmP4mfikch5Tu8i1ffcumZK8D+qv2vj6sppq1eDz4I++TGa/6qeiLTNmP/VSMml79NqWyjY8Z1FznGZ8YDvWgivUyJpqZC2FzuwnSXkMGixmTfThAQAAAJMeQRSmlJk8L2q0shD2qn4qYqFWnmswb8pMynxQX1ZXX62meq2ueshUG0UwZWZqF7n2VNVP7SJXtCgnp3rIFMax8gp7G0xOm4uyDS9PSbNkM7J9dbw4mfpCS42sqZrPVfdtZT4pmVOz6JOJNxsAAAA4XARRmHKGz4ta3J80LySqPg5DFobmRZmZ8hTVylva3W5KsjKYqtr4+qpqqVqWybu9P2R3qp+aeUt5sXf1UyPrm1SD0qe7wqSB6LWzGkZeV9SxnolEYyXzuRqhqf6srcyVAZSclMdMe4rGRB8eAAAAMCURRGHKcU5a4JO2J6+3m15bM6eFtaQ53uT5BH5YnCurlurDg6lYqNlua09zUCapFjL11zpn5Ksp+KD2zkJbd2xXOxYqYlFWP2VUP/WambQjOW2NXu3kFGO5/glkj55TUn9WVT9Vg8e9kqJ5DTJ4HAAAADhqBFGYknzVoneMSQOF184iaH7dtDArzw6G0emcca+e1SQNtd3tbjW1szkoyVQLNTX6+zXYbirzQY061U8ToZWkzTGomZxahanfRX2AHPCoOCXVfKH+rKX+UM5+qoe2JKkd64rGX5UAAADAWOFf15jSak5alKVyRk7LaXsRtLBmOi5E1RnbcsScc+VQ81pdUieYKtRXq8kZQd9ESCZtjV47klczmkKKmhvEdKIj4JVUC7nqPq/OdhcVXFTN5/IuKaagwYLqJwAAAGA8EERhWmh40wnOtDM5vdty2hYyfbDG/KixUgZTNVrwJsju5LSlGkZexKRjvKnGb8Vh8y52Q6d6KBRcoeCS6qElJ5NJshTUijWZeGMBAACA8UQQhWnDOWlOMM020/bo9XZkfhSmttykLYXX7uTVSqY+ow3vcARXlMFTKC+9i8p8oZrPuzVO0Xx1xjveUAAAAKCXCKIw7QQnzc+ScuZHYRIyk5IkU3VpUpIrvx52X2FOO5NXK0pmUXMkBfrwDsCUuaIbOtVDLq+kzOeq+SjJZHJV8NQvo5kRAAAAmFAEUZi2mB+Fo2UmRR08MCq/dkPBUvf+occO3edk1dfqfL8Nex5JlsrLJClTUkOmftbrMKaa71Q85ar5Ql5RNV8o80X5CJOiZdpT9Is5TwAAAMDkQhCFaY/5URiNdpIGzWkwOTXNK9qhAyMzVbFT2SIqGx5/lDU4pmGPkcnJdWtzvOvcVg4f9668ZH2W70utCp3qVXtdp9Uuc1FS+f7nKdMeBowDAAAAkx5BFGYE5kdhJIVJzeS64VNuTm2TYjIFS93QyOkAgVF125G1zNEmeiBOSX2h1a16ynyh4KIynyu4qM7vQDtmaltdBE8AAADA1EIQhRmF+VFIJjWr0GnQnNrJqTCpnUxeJm9JDSfV/d5VTThS1fvqkrxLcm7o+vDbfXV7X90r5m3VQ1ud9z2ZV54ytax/Yl8KAAAAgKNGEIUZiflRM4eZ1LZOu51X05yiSa0kKZmCi6pJOtbRCnd4bL8QqRsuaShQ6lyW9Uvl13KmoKTgorxPVc5U9jKac3IyZT5T05maRZ0z2gEAAADTEEEUZjTmR01PhUl7kutWPhWddrtYBiGZpA84U42cYz/eRfWFtoJL3QBpeNXS8GCpDKCiglIZLMkkKydidTImJ8lS+V0mKZpXO9YUY6e5cW91l6mdil6+ZAAAAAA9RBCFGY/5UVNfHN5uV815yqt2u6By1lPDSX0ETwdUzmVqq5E1VfN594x0ksnMy40QLJVFZV6tVFMaIVgCAAAAgOEIooAK86OmDjOpZdJg8ho0p5Y5Fak8453MFBRVd9IHPKOsR2aq+1z9WVP9oa3gCtV9W3JORcy0O58l3j0AAAAAY40gCtgH86Mmp7zTblcNGY/m1I5SsrI2p+6kuTIFqp4OKnNFN3zKXKF6aMk7U0xBg7EhwicAAAAA44kgChgB86PGnplUTRJSqq4nuWHXpWRun8eUbXa5lWe3y5PJmymTqeGMdrvD4F1Uf2irP2uW4ZNvK/gomVMzMhQcAAAAQO8QRAEHMdL8qPmZKXOmmpMyZ8qkaT9LKlk5BLxtnUCpMyNo/0CpDJGcovYJnawcWC2VX2t4AFWdRC1KcmZy5cnU5CQ5V8556qPd7rA5mfpCS/1ZS3XfVuYL1XwumVOeMrWLvok+RAAAAAAzEEEUcBj2nR+1q/AKvvwDVPNlCFVzpmz4pcqwKnNSNsmTEzOpUDn0uzCnQuVlNClXeRnNqSanVjuTWRUwqQyQOmFSGRyVIZJZJzCyYSOsO2ddc93bgjPVJAWV72NwBE1HrjP3qaW+butdWzJTtEyDBa13AAAAACYWQRQwCp35UWZl5U7bpCI6teW0RyYzp+ScJFcGUL4MVjoBVRlOqafVVJ1jjSYVKtvbiqrNreiETJ1qpuqxRerMXpK8M7kqYDIXFYskXx1zVoVMXuXr9Ic9Q4vh72MpuEKNrKX+0CqHjodc3kUl82oWfXtFgQAAAAAwkQiigCPgXPmHp6x0Mg0FK+VlMimXlMeyuqhlkrmyfc3k5JxU01BQdTTVVGW10j4hk4YqmorhM5isDJmiJK+hgKlTtRQk1Z1ptqTsAGOD+mpSKxEiTQZOSf1ZS43QUubzcu6TizI5tWNdSbTeAQAAAJh8CKKAceCd1CepL+wb2pRfd2YtFdGpKac9ZmXTmiuDqm41lcrL4dVUSWWbXCdsOlDIpGEhU+dXkFPNmfpVthPSoDUVmfpCW43QUj20FXyuPp/LJOUxUzvNmugDBAAAAICDIogCJsBQpdP+1VRmUlvDqqkKKbmh6UpB1h3g7WwoZArO1Fc994Fb/ahkmqpqPld/NXg8VHOfvKTCvPYw9wkAAADAFEIQBUwy7hDVVAdGyDSdOJm8i+oPbfVnze7Q8aCkJK9WUZfpAL2TAAAAADDJEUQBQM+YvEvyLinsczn8ulOSlynzhTJXyOTUSjW1jC0bAAAAwNTGpxpMAXt/eHey8tKZonnFFJTMK5rn7GCYME4HDpXKyyjvbChkcmXFU3BRwafuM1TNmeV/zSvGoD2J1jsAAAAA0wdBFCbIPpUh3Q/naZ9fJleda67z4d07U3BR3iWZnGLKVFhQMqdoQdGCUgplSGW+/Lq6nsyLD/UYDbfXWo3DQqS9Q6ehNV3en7kop3IIvVMZLzmZzFTWO5lXnjI1Y5AIUAEAAADMEARRGDNOJneE4VKoLt2wWUcmJ7lyMHeyMjxKKahIXm2rVR/wkzJfqOZy+VA+t0ly1nkOKaZQBVVlINW53g2q0vCgqjMKHDNLGW5mPu532WmTc1UA2glBh75zSDJfrblMg5YxxwkAAAAA9kEQNQ1kzf+nBf1b92nsOYCDzrMeOXw51BjskcOlzryb4eHS0P/KrDwLnCWvPHklq426tc4UlKegXJLigV5V2RZVhlVFGSC4zn3lM0Qrg6poQZa8ooLigSqqUnmd9r+pq1OpVLbEDQVOoWqZCz5210lZweRkziRzVVjp1Ip1JVFZBwAAAABHgiBqGjBf0wdqO+WVDvLZ+FBx0pF/qDbTCOFSULL6hAY3pipMirURHxGUFHyhui+rqpxLkrnuO2JyKlInkApV+1/Z5jf8Vzmjyu11H2FF75WzmqqQqVPZVM1i6sxxCr5QzcVu45zJqnY5p3asKxI0AQAAAMC4IIiaBmL9g2WVhtEGNHquWwGlNPIjMle2AHqflxVerlMvUzKpCqPKWVWpc6kwLKxye4VW3dtEaDV61q1kKquaCmW+M8Mpduc5dVrrVLV5WnIyeRUpaLfVxXsOAAAAAL1FEAUcgikot6B8xKqq8lG+au0Krmzvcr6cK9QpRuuMrDapO48qWjm0et/QKg4LrdKMC62smsnUafm07tnlysqmottK531SzeUK1eB6J8mclWecS17Nos6cJgAAAACYRAiigDFRBUmdeVXSAWdWlZKCknw1j8i5MrBy3vbqoOycaW2oFTDIzClZWdWTqlZAs2o617D79r5t/8eVA9nHN8zqDq+vBn135oUNnylWzhMbuu6q4MkpVdc1dKZEH1WNayr7Qc0pqjrznGXj/noAAAAAAEePIAroOa8or5iyodBqRMNDq7wKrZKckzqjufZvEixvSebKyqBOMFVVUnUDKfnqMcOu7xVY7X9bzUsKre4ZEfcNmJwrq5nKs8pZd3i9XFUx1nlMdb+smh/mTGZVlOTKnGn48cbk1Yo1iUHxAAAAADClEUQBk9poQqvhOlVGZWAUlJSFKGedyiuT89WgeY1US+Sq1sGqTVBetSxT7AZR1RkRq1TMSUrOdZ/UOSmZk8x1Z2iVA+x9NcCeCiYAAAAAmGkIooBpycnUOcOfyhCrM4x9xJbB4axTMyVfnW0uc1HBSYVJeaqparoTgRIAAAAA4HARRAE4gLIlr6zGGrq1HjLlqZi4wwIAAAAATGnTKoh68cUXdf/99yulpC9+8Yu69NJLJ/qQAAAAAAAAUJk2k39TSvrtb3+rH/3oR1q9erWeeuopbdy4caIPCwAAAAAAAJVpE0StX79exx9/vBYtWqQsy3Tuuedq7dq1E31YAAAAAAAAqEybIGpgYEALFizofr1gwQINDAxM4BEBAAAAAABguGkzI8o656Efxrn9z+b12GOP6bHHHpMk3XHHHTrhhBPG/dh64YT/++5EHwIAAAAAAMBBTZuKqAULFmjLli3dr7ds2aJ58+bt97iLLrpId9xxh+64445eHt64u/nmmyf6EDADsM4w3lhj6AXWGXqBdYbxxhpDL7DOMB6mTRC1ZMkSvffee9q0aZOKotDTTz+tZcuWTfRhAQAAAAAAoDJtWvNCCLrqqqt0++23K6WkCy+8UIsXL57owwIAAAAAAEBl2gRRkrR06VItXbp0og9jQlx00UUTfQiYAVhnGG+sMfQC6wy9wDrDeGONoRdYZxgPzg405RsAAAAAAAAYY9NmRhQAAAAAAAAmt2nVmjedrFmzRs8//7zmzp2rVatWSZLefvtt/eY3v1Gz2dTChQt1/fXXa9asWSqKQvfcc4/eeustpZR0/vnn6xvf+IYk6c0339Tdd9+tdrutc845RytWrJBzbiJfGiaRsVpnt912m7Zu3ap6vS5JWrlypebOnTthrwuTy2jX2a9//Wtt2LBB3nstX75cZ5xxhiT2M4xsrNYYexkOZvPmzbr77ru1bds2Oed00UUX6Stf+Yp27dql1atX63//+58WLlyo73//+zrmmGMkSY888oj+9re/yXuvFStW6Oyzz5bEfoYDG8s1xn6GkYx2ne3cuVO/+MUvtH79en3hC1/Q1Vdf3X0u9jIcMcOktG7dOtuwYYPdcMMN3dtuvvlmW7dunZmZ/fWvf7U//OEPZmb297//3VavXm1mZs1m06699lp7//33u9/z+uuvW0rJbr/9dnv++ed7+0IwqY3VOrv11ltt/fr1vT14TBmjWWd/+ctf7O677zYzs23bttmNN95oMcbu97Cf4UDGao2xl+FgBgYGbMOGDWZmtmfPHrv++uvtnXfesQceeMAeeeQRMzN75JFH7IEHHjAzs3feecd+8IMfWLvdtvfff9+uu+469jMc1FiuMfYzjGS062xwcNBeffVVe/TRR+2+++7b67nYy3CkaM2bpE4//fTuTzo63n33XZ122mmSpLPOOkv/+te/uvc1m03FGNVut5VlmWbNmqWtW7dqcHBQH/vYx+Sc0/nnn6+1a9f29HVgchuLdQYcymjW2caNG/WJT3xCkjR37lzNnj1bb775JvsZDmos1hhwKPPmzdPJJ58sSWo0GjrxxBM1MDCgtWvX6oILLpAkXXDBBd29ae3atTr33HNVq9X0wQ9+UMcff7zWr1/PfoYRjdUaAw5mtOusv79fH//4x7vVdR3sZTgaBFFTyOLFi/Xss89Kkp555hlt2bJFkvTZz35W/f39+s53vqNrr71WX/va13TMMcdoYGBACxYs6H7/ggULNDAwMCHHjqljtOusY82aNfrhD3+ohx56SMY5EHAII62zj3zkI3r22WcVY9SmTZv05ptvavPmzexnGLXRrrEO9jIcjk2bNumtt97SKaecou3bt2vevHmSyg94O3bskKT99q358+drYGCA/QyH5WjWWAf7GQ7lcNbZSNjLcDSYETWFfPe739X999+vhx56SMuWLVOWlb9969evl/de9957r3bv3q1bbrlFZ555Jn/h4IiMdp0tWrRI119/vebPn6/BwUGtWrVKTz75ZPcnKsCBjLTOLrzwQm3cuFE333yzFi5cqFNPPVUhBPYzjNpo15gk9jIclmazqVWrVmn58uUHrQwead9iP8OhHO0ak9jPcGiHu85Gwl6Go0EQNYWceOKJWrlypaSy5eD555+XJP3jH//Q2WefrSzLNHfuXJ166qnasGGDTjvttO5PgCVpy5Ytmj9//oQcO6aO0a6zRYsWdddVo9HQ5z//ea1fv55/7OCgRlp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| |
| "text/plain": [ | |
| "<Figure size 1440x720 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "df_top5.plot(kind='area', \n", | |
| " alpha=0.25, # 0-1, default value a= 0.5\n", | |
| " stacked=False,\n", | |
| " figsize=(20, 10),\n", | |
| " )\n", | |
| "\n", | |
| "plt.title('Immigration Trend of Top 5 Countries')\n", | |
| "plt.ylabel('Number of Immigrants')\n", | |
| "plt.xlabel('Years')\n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "### Two types of plotting\n", | |
| "\n", | |
| "As we discussed in the video lectures, there are two styles/options of ploting with `matplotlib`. Plotting using the Artist layer and plotting using the scripting layer.\n", | |
| "\n", | |
| "**Option 1: Scripting layer (procedural method) - using matplotlib.pyplot as 'plt' **\n", | |
| "\n", | |
| "You can use `plt` i.e. `matplotlib.pyplot` and add more elements by calling different methods procedurally; for example, `plt.title(...)` to add title or `plt.xlabel(...)` to add label to the x-axis.\n", | |
| "```python\n", | |
| " # Option 1: This is what we have been using so far\n", | |
| " df_top5.plot(kind='area', alpha=0.35, figsize=(20, 10)) \n", | |
| " plt.title('Immigration trend of top 5 countries')\n", | |
| " plt.ylabel('Number of immigrants')\n", | |
| " plt.xlabel('Years')\n", | |
| "```" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "**Option 2: Artist layer (Object oriented method) - using an `Axes` instance from Matplotlib (preferred) **\n", | |
| "\n", | |
| "You can use an `Axes` instance of your current plot and store it in a variable (eg. `ax`). You can add more elements by calling methods with a little change in syntax (by adding \"*set_*\" to the previous methods). For example, use `ax.set_title()` instead of `plt.title()` to add title, or `ax.set_xlabel()` instead of `plt.xlabel()` to add label to the x-axis. \n", | |
| "\n", | |
| "This option sometimes is more transparent and flexible to use for advanced plots (in particular when having multiple plots, as you will see later). \n", | |
| "\n", | |
| "In this course, we will stick to the **scripting layer**, except for some advanced visualizations where we will need to use the **artist layer** to manipulate advanced aspects of the plots." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 17, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Text(0.5, 0, 'Years')" | |
| ] | |
| }, | |
| "execution_count": 17, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 1440x720 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "# option 2: preferred option with more flexibility\n", | |
| "ax = df_top5.plot(kind='area', alpha=0.35, figsize=(20, 10))\n", | |
| "\n", | |
| "ax.set_title('Immigration Trend of Top 5 Countries')\n", | |
| "ax.set_ylabel('Number of Immigrants')\n", | |
| "ax.set_xlabel('Years')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "**Question**: Use the scripting layer to create a stacked area plot of the 5 countries that contributed the least to immigration to Canada **from** 1980 to 2013. Use a transparency value of 0.45." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 19, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 1440x720 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "### type your answer here\n", | |
| "\n", | |
| "df_least5 = df_can.tail(5)\n", | |
| " \n", | |
| "# transpose the dataframe\n", | |
| "df_least5 = df_least5[years].transpose() \n", | |
| "df_least5.head()\n", | |
| "\n", | |
| "df_least5.index = df_least5.index.map(int) # let's change the index values of df_least5 to type integer for plotting\n", | |
| "df_least5.plot(kind='area', alpha=0.45, figsize=(20, 10)) \n", | |
| "\n", | |
| "plt.title('Immigration Trend of 5 Countries with Least Contribution to Immigration')\n", | |
| "plt.ylabel('Number of Immigrants')\n", | |
| "plt.xlabel('Years')\n", | |
| "\n", | |
| "plt.show()\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "<details><summary>Click here for a sample python solution</summary>\n", | |
| "\n", | |
| "```python\n", | |
| " #The correct answer is:\n", | |
| " # get the 5 countries with the least contribution\n", | |
| " \n", | |
| " \n", | |
| "```\n", | |
| "\n", | |
| "\n", | |
| "</details>\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "**Question**: Use the artist layer to create an unstacked area plot of the 5 countries that contributed the least to immigration to Canada **from** 1980 to 2013. Use a transparency value of 0.55." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "### type your answer here\n", | |
| "\n", | |
| "\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "<details><summary>Click here for a sample python solution</summary>\n", | |
| "\n", | |
| "```python\n", | |
| " #The correct answer is:\n", | |
| " \n", | |
| " # get the 5 countries with the least contribution\n", | |
| " df_least5 = df_can.tail(5)\n", | |
| "\n", | |
| " # transpose the dataframe\n", | |
| " df_least5 = df_least5[years].transpose() \n", | |
| " \n", | |
| " df_least5.head()\n", | |
| "\n", | |
| " df_least5.index = df_least5.index.map(int) # let's change the index values of df_least5 to type integer for plotting\n", | |
| " \n", | |
| " ax = df_least5.plot(kind='area', alpha=0.55, stacked=False, figsize=(20, 10))\n", | |
| " \n", | |
| " ax.set_title('Immigration Trend of 5 Countries with Least Contribution to Immigration')\n", | |
| " ax.set_ylabel('Number of Immigrants')\n", | |
| " ax.set_xlabel('Years')\n", | |
| "\n", | |
| " \n", | |
| "```\n", | |
| "\n", | |
| "\n", | |
| "</details>\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "# Histograms<a id=\"8\"></a>\n", | |
| "\n", | |
| "A histogram is a way of representing the *frequency* distribution of numeric dataset. The way it works is it partitions the x-axis into *bins*, assigns each data point in our dataset to a bin, and then counts the number of data points that have been assigned to each bin. So the y-axis is the frequency or the number of data points in each bin. Note that we can change the bin size and usually one needs to tweak it so that the distribution is displayed nicely." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "**Question:** What is the frequency distribution of the number (population) of new immigrants from the various countries to Canada in 2013?" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Before we proceed with creating the histogram plot, let's first examine the data split into intervals. To do this, we will us **Numpy**'s `histrogram` method to get the bin ranges and frequency counts as follows:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 20, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Country\n", | |
| "India 33087\n", | |
| "China 34129\n", | |
| "United Kingdom of Great Britain and Northern Ireland 5827\n", | |
| "Philippines 29544\n", | |
| "Pakistan 12603\n", | |
| "Name: 2013, dtype: int64" | |
| ] | |
| }, | |
| "execution_count": 20, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# let's quickly view the 2013 data\n", | |
| "df_can['2013'].head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 21, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "[178 11 1 2 0 0 0 0 1 2]\n", | |
| "[ 0. 3412.9 6825.8 10238.7 13651.6 17064.5 20477.4 23890.3 27303.2\n", | |
| " 30716.1 34129. ]\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# np.histogram returns 2 values\n", | |
| "count, bin_edges = np.histogram(df_can['2013'])\n", | |
| "\n", | |
| "print(count) # frequency count\n", | |
| "print(bin_edges) # bin ranges, default = 10 bins" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "By default, the `histrogram` method breaks up the dataset into 10 bins. The figure below summarizes the bin ranges and the frequency distribution of immigration in 2013. We can see that in 2013:\n", | |
| "* 178 countries contributed between 0 to 3412.9 immigrants \n", | |
| "* 11 countries contributed between 3412.9 to 6825.8 immigrants\n", | |
| "* 1 country contributed between 6285.8 to 10238.7 immigrants, and so on..\n", | |
| "\n", | |
| "<img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DV0101EN-SkillsNetwork/labs/Module%202/images/Mod2Fig1-Histogram.JPG\" align=\"center\" width=800>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "We can easily graph this distribution by passing `kind=hist` to `plot()`." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 22, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 576x360 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "df_can['2013'].plot(kind='hist', figsize=(8, 5))\n", | |
| "\n", | |
| "plt.title('Histogram of Immigration from 195 Countries in 2013') # add a title to the histogram\n", | |
| "plt.ylabel('Number of Countries') # add y-label\n", | |
| "plt.xlabel('Number of Immigrants') # add x-label\n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "In the above plot, the x-axis represents the population range of immigrants in intervals of 3412.9. The y-axis represents the number of countries that contributed to the aforementioned population. \n", | |
| "\n", | |
| "Notice that the x-axis labels do not match with the bin size. This can be fixed by passing in a `xticks` keyword that contains the list of the bin sizes, as follows:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 23, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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TScutq6srHjx4oNFNVFSUvqMk0ec7ostrr70Ga2tr3Lx5U+tGS/4ejuLWX+Xtiy++wFdffYUDBw5oPdO9TZs2+OuvvzR+JPz555+wtbVFkyZNyjTs/H5mZ2eXqT/lhcW9kp08eRLz5s3DmTNncPfuXRw6dAgXL16UFnIvLy/I5XIcOHAACQkJUqGYOXMmVq1ahfXr1yM2Nhbr1q3DmjVrMGvWLACAj48PevbsifHjx+Po0aOIjo7G6NGjkZ6e/sKtCi8vL1hZWWHVqlW4ceMGDh06hEmTJpXbTUpeNC4vq8GDB0OhUODDDz/ExYsXcebMGYwcORI2NjYvnJZ169ZFYmIiNm7ciJs3b2Lbtm0ICQnR6KZWrVoAgH379iExMREZGRla+2UM03fmzJn45ZdfsGjRIsTExGDXrl348ssvMW3atHK5rDEuLg4XLlzA3bt3AUDa6iw4jYKDg3Hu3DnExcVhy5Yt6NevH4YMGYJOnToBAG7cuIHAwEBERkbizp07iIiIQK9evSCEwPDhw3UOe9y4cVCr1XjnnXdw4sQJ3Lp1C/v375d25U6fPh1RUVGYOnUqrl27hj///BMTJ07E4MGDpcNfAQEBuHbtGlavXo0bN25g/fr12LVrV4mng77fEW0UCgVmzZqFWbNmYfXq1bh+/TquXLmCHTt24LPPPgPw4vVXeZo8eTKWLFmC7du3o27dunj48CEePnyo8WN67NixSEtLw8cff4wrV65g3759mDt3LiZOnKix5yL/+5GSkoKMjIwih1R/+eUXbNu2DZcvX8adO3cQFhaG/v37o1q1aujcuXO5j2upVNbBflNT2rPlL1++LLp37y7c3NyEpaWlqFGjhvj00081btKyePFi4eHhIeRyucalcN9++62oWbOmMDc3F7Vq1dJ6Kdx7770nbGxshIuLi5g7d67o27evePvtt6VudF3qs3v3blG7dm1hZWUlGjduLI4cOSLMzMzE5s2bhRDaL/u6d++eACAOHz4stcXHxwsA4q+//tI57fQZl7KcUFf4pjYFxyOflZWVWL9+fZnGrbhL4SwtLUXt2rXF7t27hYuLi8aJedoyCvH8xCxXV1dha2srunfvLn766aciJy9NmjRJuLq6CplMVuylcC+avoUvzxNCiJEjR0rfN110nVCnbXy2bNkifH19hYWFhfDw8BCzZs0qcilc4X516dJFGq98Xbt2FYMHD35hLhS6DKzw/Bs+fLhQKpXCwsJC+Pj4iIULF2pc+nf37l3RsWNHqZsaNWqIQYMGidjY2GKHLYSQrrCws7MTNjY2omHDhtLZ8kJoXgqnVCrFmDFjipyAN3/+fOHh4SGqVKkiBgwYIJ35nk/bMqHtBFxt3xFdy7229g0bNohGjRoJKysr4eDgIFq0aCFCQkKEEPqtvwrTdSnci8ajMG3zFwUu98uXf5WKlZWVcHNzK3ITm+L6le+3334TLVu2FPb29sLKykp4e3uLMWPGiLt37+rMV9lkQpTDvlYySnl5efD19UWvXr0QFBRU2XH+le7cuYOaNWti3759xn0DDCJ6qZlXdgAqPxEREUhISECTJk3w5MkTLFu2DLdv38awYcMqO9q/xg8//ABPT0/UqlULd+7cwYwZM+Dl5YU333yzsqMRkQljcTdheXl5mD9/PuLi4mBhYYEGDRrg8OHDeP311ys72r9GcnIyAgMD8d///hdOTk5o06YNdu/eDSsrq8qORkQmjLvliYiITAzPliciIjIxLO5EREQmhsWdiIjIxJjUCXWF7+hUVkqlEklJSQbtpyEZez7A+DMaez6AGQ3B2PMBxp/R2PMBxp+xPPJ5eHhobeeWOxERkYlhcSciIjIxLO5EREQmhsWdiIjIxLC4ExERmRgWdyIiIhPD4k5ERGRiWNyJiIhMDIs7ERGRiWFxJyIiMjEs7kRERCbGpO4tb2iP3vWv7AjFCz1Z2QmIiMgIVUhxDwkJQVRUFOzt7REUFAQAWLZsmfSgl2fPnsHW1hZLlixBQkICpkyZIt0M38fHB6NGjaqImERERCahQop7x44d0a1bNwQHB0ttU6ZMkf7etm0bbG1tpdfu7u5YsmRJRUQjIiIyORVyzL1+/fpQKBRa3xNC4NSpU2jTpk1FRCEiIjJ5lX7M/erVq7C3t8crr7witSUkJGDGjBmwsbHBgAEDUK9ePa2fDQsLQ1hYGABg0aJFUCqVBs32yKB9Mzxzc3ODj7OhGXtGY88HMKMhGHs+wPgzGns+wPgzVmS+Si/uJ06c0Nhqd3R0REhICKpWrYqbN29iyZIlCAoK0thtny8gIAABAQHS66SkpArJbCxUKpXRj7NSqTTqjMaeD2BGQzD2fIDxZzT2fIDxZyyPfPnnpxVWqZfC5eXlITIyEv7+/zsr3cLCAlWrVgUAeHt7w83NDfHx8ZUVkYiI6KVTqcX90qVL8PDwgLOzs9SWnp4OtVoNAHj06BHi4+Ph5uZWWRGJiIheOhWyW3758uWIjo7GkydPMGbMGPTv3x+dO3cuskseAKKjo7Fr1y6YmZlBLpfj448/1nkyHhERERVVIcV98uTJWtvHjx9fpK1Vq1Zo1apVOSciIiIyXbz9LBERkYlhcSciIjIxLO5EREQmhsWdiIjIxLC4ExERmRgWdyIiIhPD4k5ERGRiWNyJiIhMDIs7ERGRiWFxJyIiMjEs7kRERCaGxZ2IiMjEsLgTERGZGBZ3IiIiE8PiTkREZGJY3ImIiEwMizsREZGJYXEnIiIyMSzuREREJobFnYiIyMSwuBMREZkYFnciIiITw+JORERkYljciYiITAyLOxERkYlhcSciIjIxLO5EREQmxrwiBhISEoKoqCjY29sjKCgIALBr1y4cOnQIdnZ2AICBAwfCz88PABAaGorw8HDI5XIMHz4cjRs3roiYREREJqFCinvHjh3RrVs3BAcHa7S/9dZb6NWrl0bb/fv3cfLkSSxduhSpqamYN28eVqxYAbmcOxmIiIj0USEVs379+lAoFHp1e/bsWfj7+8PCwgKurq5wd3dHXFxcOSckIiIyHRWy5a7LwYMHERERAW9vb3z44YdQKBRISUmBj4+P1I2TkxNSUlIqMSUREdHLpdKK+5tvvom+ffsCAHbu3Ilt27Zh3LhxEELo3Y+wsDCEhYUBABYtWgSlUmnQjI8M2jfDMzc3N/g4G5qxZzT2fAAzGoKx5wOMP6Ox5wOMP2NF5qu04u7g4CD93aVLFyxevBgA4OzsjOTkZOm9lJQUODk5ae1HQEAAAgICpNdJSUnlE9ZIqVQqox9npVJp1BmNPR/AjIZg7PkA489o7PkA489YHvk8PDy0tlfaWWqpqanS35GRkahevToAoFmzZjh58iRyc3ORkJCA+Ph41K5du7JiEhERvXQqZMt9+fLliI6OxpMnTzBmzBj0798fV65cwe3btyGTyeDi4oJRo0YBAKpXr47WrVtj6tSpkMvlGDlyJM+UJyIiKoEKKe6TJ08u0ta5c2ed3ffp0wd9+vQpx0RERESmi5vEREREJobFnYiIyMSwuBMREZkYFnciIiITw+JORERkYljciYiITAyLOxERkYlhcSciIjIxLO5EREQmhsWdiIjIxLC4ExERmRgWdyIiIhPD4k5ERGRiWNyJiIhMDIs7ERGRiWFxJyIiMjHm+nR0//59KBQKODg4ICsrC/v27YNcLkfPnj1hZWVV3hmJiIioBPTacl+xYgWePXsGANi2bRuuXr2KmJgYfP/99+UajoiIiEpOry33xMREeHh4QAiBs2fPIigoCJaWlpgwYUJ55yMiIqIS0qu4W1hYIDMzE/fv34ezszPs7OyQl5eH3Nzc8s5HREREJaRXcW/Tpg2+/vprZGZmolu3bgCAW7duwdXVtVzDERERUcnpVdyHDRuGf/75B2ZmZmjQoAEAQCaTYejQoeUajoiIiEpOr+IOAI0aNUJSUhJiYmJQp04dvPrqq+WZi4iIiEpJr+KelJSEFStW4Pbt2wCA7du34/Tp07hw4QLGjBlTnvmIiIiohPS6FO77779HkyZNsHXrVpibP/890LBhQ1y8eLFcwxEREVHJ6VXc4+Li0Lt3b8jl/+vc1tZWuvadiIiIjIdexd3e3h4PHz7UaLt//z6USmW5hCIiIqLS0+uYe8+ePbF48WL07t0barUax48fR2hoKHr37q3XQEJCQhAVFQV7e3sEBQUBeH7c/vz58zA3N4ebmxvGjRuHKlWqICEhAVOmTIGHhwcAwMfHB6NGjSrd2BEREf0L6VXcO3fuDIVCgUOHDsHZ2RlHjx7F+++/jxYtWug1kI4dO6Jbt24IDg6W2ho2bIhBgwbBzMwMP/zwA0JDQzFkyBAAgLu7O5YsWVKK0SEiIiK9L4Vr0aKF3sW8sPr16yMhIUGjrVGjRtLfderUwenTp0vVbyIiItKks7hHRESgffv2AIDw8HCdPejcuXOZQ4SHh8Pf3196nZCQgBkzZsDGxgYDBgxAvXr1yjwMIiKifwudxf3EiRNScT927JjOHpS1uO/ZswdmZmZo164dAMDR0REhISGoWrUqbt68iSVLliAoKAi2trZFPhsWFoawsDAAwKJFiwx+gt8jg/bN8MzNzY3+pEZjz2js+QBmNARjzwcYf0ZjzwcYf8aKzKezuM+cORMAIITAmDFjoFQqYWZmZtCBHzlyBOfPn8cXX3wBmUwG4PlDaiwsLAAA3t7ecHNzQ3x8vNY74gUEBCAgIEB6nZSUZNB8xk6lUhn9OCuVSqPOaOz5AGY0BGPPBxh/RmPPBxh/xvLIl3/yeWEvvBROJpPh008/lYqvoVy4cAG//vorPvvsM1hZWUnt6enpUKvVAIBHjx4hPj4ebm5uBh02ERGRKdPrhLqaNWsiPj4enp6epRrI8uXLER0djSdPnmDMmDHo378/QkNDoVKpMG/ePAD/u+QtOjoau3btgpmZGeRyOT7++GMoFIpSDZeIiOjfSK/i/tprr+Gbb75Bhw4dihwv0OeY++TJk4u06fpcq1at0KpVK31iERERkRZ6Fffr16/D1dUVV69eLfKeIc6WJyIiIsPRq7gHBgaWdw4iIiIyEL3uLT9jxgyt7Z9//rlBwxAREVHZ6VXcCz80Bnh+idyjR8Z+JTgREdG/T7G75VevXg3g+fXU+X/nS0xMRPXq1csvGREREZVKscW94PXlBf+WyWSoW7cuWrduXX7JiIiIqFSKLe79+vUD8Pwa9MaNG1dEHiIiIiojvc6Wb9y4MR48eIDbt28jKytL4z1eCkdERGRc9Crue/bswS+//AIvLy+NW8UCLO5ERETGRq/ifuDAAXzzzTfw8vIq7zxERERURnpdCmdpaVnq+8oTERFRxdKruL///vvYtGkTUlNToVarNf4RERGRcdFrt3xISAgA4NChQ0Xe27lzp2ETERERUZnoVdwL38CGiIiIjJdexd3FxaW8cxAREZGB6FXcV61aBZlMpvW9CRMmGDQQERERlY1exd3d3V3j9ePHj3H69Gm0a9euXEIRERFR6elV3PNvQ1tQ586dsXv3boMHIiIiorLR61I4bWrWrImrV68aMgsREREZgF5b7pcvX9Z4nZ2djRMnTqBatWrlEoqIiIhKT6/ivmbNGo3X1tbW8PLywqRJk8olFBEREZWeXsU9ODi4vHMQERGRgehV3AEgIyMD58+fR0pKCpycnNC0aVMoFIryzEZERESloNcJdTExMZg4cSL++usv3LlzB2FhYZg4cSJiYmLKOx8RERGVkF5b7lu2bMFHH32ENm3aSG0nT57E5s2bsXDhwnILR0RERCWn15Z7fHw8WrdurdHWqlUrPHz4sFxCERERUenpVdzd3d1x8uRJjbZTp07Bzc2tXEIRERFR6em1W37YsGFYtGgR/vjjDyiVSiQmJiI+Ph6ff/55eecjIiKiEtKruNetWxerVq1CVFQUUlNT0bRpU/j5+el9tnxISAiioqJgb2+PoKAgAM/Pvl+2bBkSExPh4uKCKVOmSP0LDQ1FeHg45HI5hg8fjsaNG5du7IiIiP6Fit0tn5OTg7t37wIAFAoF2rdvj3feeQft27dHSkoKcnJy9BpIx44dMWvWLI22vXv34vXXX8fKlSvx+uuvY+/evQCA+/fv4+TJk1i6dClmz56NjRs3Qq1Wl2LUiIiI/p2KLe6//vorwsPDtb535MgR7Nu3T6+B1K9fv8hW/tmzZ9GhQwcAQIcOHXD27Fmp3d/fHxYWFnB1dYW7uzvi4uL0Gg4RERG9YLf8yZMnMXfuXK3vvf3225g3bx769u1bqgGnpaXB0dERAODo6Ij09HQAQEpKCnx8fKTunJyckJKSorUfYWFhCAsLAwAsWrQISqWyVFl0eWTQvhmeubm5wcfZ0Iw9o7HnA5jREIw9H2D8GY09H2D8GSsyX7HFPf9udNoUV3TLQgihd7cBAQEICAiQXiclJRk8jzFTqVRGP85KpdKoMxp7PoAZDcHY8wHGn9HY8wHGn7E88nl4eGhtL3a3vLW1tc4gSUlJsLKyKnUge3t7pKamAgBSU1NhZ2cHAHB2dkZycrLUXXE/MIiIiKioYot7kyZN8PPPP2t9b8eOHfDz8yv1gJs1a4ajR48CAI4ePYrmzZtL7SdPnkRubi4SEhIQHx+P2rVrl3o4RERE/zbF7pYfMGAAZs+ejenTp6NFixZwdHREamoqIiMjkZmZifnz5+s1kOXLlyM6OhpPnjzBmDFj0L9/f/Tu3RvLli1DeHg4lEolpk6dCgCoXr06WrdujalTp0Iul2PkyJGQy/W61w4RERHhBcXdwcEBixcvxv79+3HhwgVkZGRAoVCgadOmePvtt/W+zn3y5Mla27/44gut7X369EGfPn306jcRERFpeuFNbBQKBQYMGIABAwZURB4iIiIqI+7vJiIiMjEs7kRERCaGxZ2IiMjE6Czus2fPlv7evXt3hYQhIiKistNZ3B88eCA9GGb//v0VFoiIiIjKRufZ8s2bN8ekSZPg6uqKnJwcBAYGau3uq6++KrdwREREVHI6i/u4ceNw7do1JCQkIC4uDp06darIXERERFRKxV7n7uvrC19fX6hUKnTs2LGCIhEREVFZvPAmNgDQuXNnXL58GREREUhNTYWjoyPat2+PBg0alHc+IiIiKiG9LoU7dOgQli9fDgcHB+ke8ytWrJCepU5ERETGQ68t93379mHOnDmoWbOm1Obv74+goCCN56kTERFR5dNry/3JkyeoVq2aRpuHhwcyMjLKJRQRERGVnl7F3dfXF9u2bUN2djYAICsrC9u3b0edOnXKNRwRERGVnF675T/++GMsX74cw4YNg0KhQEZGBurUqYNJkyaVdz4iIiIqIb2Ku6OjI7766iskJydLZ8s7OzuXdzYiIiIqBb2Kez5nZ2cWdSIiIiPHp8IRERGZGBZ3IiIiE/PC4q5Wq3H58mWoVKqKyENERERl9MLiLpfL8e2338LcvESH54mIiKiS6LVbvl69eoiJiSnvLERERGQAem2Ou7i4YOHChWjWrBmcnZ0hk8mk995///1yC0dEREQlp1dxz8nJQfPmzQEAKSkp5RqIiIiIykav4j5u3LjyzkFEREQGovdZcvfv38fp06eRlpaGkSNH4sGDB8jNzYWXl1d55iMiIqIS0uuEulOnTiEwMBApKSmIiIgAAGRmZmLbtm3lGo6IiIhKTq8t9127dmHu3LmoWbMmTp06BQDw8vLC7du3yzTwBw8eYNmyZdLrhIQE9O/fH0+fPsWhQ4dgZ2cHABg4cCD8/PzKNCwiIqJ/C72Ke1paWpHd7zKZTOOs+dLw8PDAkiVLADy/Wc7o0aPRokULHD58GG+99RZ69epVpv4TERH9G+m1W97b21vaHZ/vxIkTqF27tsGCXLp0Ce7u7nBxcTFYP4mIiP6N9NpyHz58OObPn4/w8HBkZ2djwYIFePDgAebMmWOwICdOnECbNm2k1wcPHkRERAS8vb3x4YcfQqFQGGxYREREpkwmhBD6dJidnY3z588jKSkJzs7OaNq0KaytrQ0SQqVSYfTo0QgKCoKDgwMeP34sHW/fuXMnUlNTtV6OFxYWhrCwMADAokWLkJOTY5A8+R6962/Q/hma52+RRn/Pf3Nzc6POaOz5AGY0BGPPBxh/RmPPBxh/xvLIZ2lpqX1Y+vbAysoKvr6+SElJgZOTk8EKOwD8/fffqFWrFhwcHABA+h8AunTpgsWLF2v9XEBAAAICAqTXSUlJBsv0MlCpVEY/zkql0qgzGns+gBkNwdjzAcaf0djzAcafsTzyeXh4aG3Xq7gnJSVh5cqViI2NRZUqVfD06VPUrl0bn3zyiUGOkRfeJZ+amgpHR0cAQGRkJKpXr17mYRAREf1b6FXcg4OD4e3tjVmzZsHa2hpZWVnYsWMHgoOD8eWXX5YpQHZ2Ni5evIhRo0ZJbT/88ANu374NmUwGFxcXjfeIiIioeHoV95s3b2L27NnSY1+tra0xZMgQjBgxoswBrKyssGnTJo22iRMnlrm/RERE/1Z6XQrn4+ODuLg4jbYbN26gTp065RKKiIiISk/nlvvOnTulv93c3LBw4UL4+fnB2dkZycnJ+Pvvv9G2bdsKCUlERET601nck5OTNV63bNkSAJCeng4LCwu0aNHC4JeeERERUdnpLO58zCsREdHLSe/r3LOzs/Hw4UNkZWVptNetW9fgoYiIiKj09CruR48exaZNm2Bubl7kbjhr1qwpl2BERERUOnoV9x9++AHTpk1Dw4YNyzsPERERlZFel8KZm5ujfv365Z2FiIiIDECv4v7+++9j27ZtSE9PL+88REREVEZ67Zb38PDArl27cPDgwSLvFbwenoiIiCqfXsV91apVaN++Pfz9/XU+Xo6IiIiMg17FPSMjA++//z5kMll55yEiIqIy0uuYe8eOHREREVHeWYiIiMgA9Npyj4uLw59//ok9e/bAwcFB472vvvqqPHIRERFRKelV3Lt06YIuXbqUdxYiIiIyAL2Ke8eOHcs5BhERERmKXsU9PDxc53udO3c2WBgiIiIqO72K+7FjxzReP378GA8fPoSvry+LOxERkZHRq7gHBgYWaQsPD8d///tfgwciIiKistHrUjhtOnbsWOzueiIiIqocem25q9Vqjdc5OTmIiIhAlSpVyiUUERERlZ5exX3gwIFF2pycnDB69GiDByIiIqKy0au4r169WuO1lZUV7OzsyiUQERERlY1exd3FxaW8cxAREZGBFFvcX3RrWZlMhi+++MKggYiIiKhsii3u7dq109qekpKCP/74A9nZ2eUSioiIiEqv2OJe+AY1T548QWhoKA4dOgR/f3/07du3XMMRERFRyel1zP3Zs2fYt28fDh48CD8/PyxevBju7u4GCTB+/HhYW1tDLpfDzMwMixYtQkZGBpYtW4bExES4uLhgypQpUCgUBhkeERGRqSu2uOfk5OD333/H/v37Ub9+fXz99deoXr26wUMEBgZqnH2/d+9evP766+jduzf27t2LvXv3YsiQIQYfLhERkSkq9g5148ePx/79+9GrVy907doVaWlpuHz5ssa/8nD27Fl06NABANChQwecPXu2XIZDRERkiordcre0tAQA/Oc//9H6vkwmK3INfGksWLAAAPDGG28gICAAaWlpcHR0BAA4OjoiPT29zMMgIiL6tyi2uAcHB5d7gHnz5sHJyQlpaWmYP38+PDw89P5sWFgYwsLCAACLFi2CUqk0aLZHBu2b4Zmbmxt8nA3N2DMaez6AGQ3B2PMBxp/R2PMBxp+xIvPpdUJdeXJycgIA2Nvbo3nz5oiLi4O9vT1SU1Ph6OiI1NRUnXfDCwgIQEBAgPQ6KSmpQjIbC5VKZfTjrFQqjTqjsecDmNEQjD0fYPwZjT0fYPwZyyOfrg3iUj8VzhCysrKQmZkp/X3x4kXUqFEDzZo1w9GjRwEAR48eRfPmzSszJhER0UulUrfc09LS8N133wEA8vLy0LZtWzRu3Bivvvoqli1bhvDwcCiVSkydOrUyYxIREb1UKrW4u7m5YcmSJUXaq1atytvaEhERlVKl7pYnIiIiw2NxJyIiMjEs7kRERCaGxZ2IiMjEsLgTERGZGBZ3IiIiE8PiTkREZGJY3ImIiEwMizsREZGJYXEnIiIyMSzuREREJobFnYiIyMSwuBMREZkYFnciIiITw+JORERkYljciYiITAyLOxERkYlhcSciIjIxLO5EREQmhsWdiIjIxLC4ExERmRgWdyIiIhPD4k5ERGRiWNyJiIhMDIs7ERGRiWFxJyIiMjEs7kRERCaGxZ2IiMjEmFfmwJOSkhAcHIzHjx9DJpMhICAAPXr0wK5du3Do0CHY2dkBAAYOHAg/P7/KjEpERPTSqNTibmZmhg8++ADe3t7IzMzE559/joYNGwIA3nrrLfTq1asy4xEREb2UKrW4Ozo6wtHREQBgY2MDT09PpKSkVGYkIiKil16lFveCEhIScOvWLdSuXRvXrl3DwYMHERERAW9vb3z44YdQKBRFPhMWFoawsDAAwKJFi6BUKg2a6ZFB+2Z45ubmBh9nQzP2jMaeD2BGQzD2fIDxZzT2fIDxZ6zIfDIhhKiQIRUjKysLgYGB6NOnD1q2bInHjx9Lx9t37tyJ1NRUjBs37oX9efDggUFz5X1s3IcF3EJPIikpqbJjFEupVBp1RmPPBzCjIRh7PsD4Mxp7PsD4M5ZHPg8PD63tlX62vEqlQlBQENq1a4eWLVsCABwcHCCXyyGXy9GlSxfcuHGjklMSERG9PCq1uAshsHbtWnh6euLtt9+W2lNTU6W/IyMjUb169cqIR0RE9FKq1GPu169fR0REBGrUqIHp06cDeH7Z24kTJ3D79m3IZDK4uLhg1KhRlRmTiIjopVKpxd3X1xe7du0q0s5r2omIiEqv0o+5ExERkWGxuBMREZkYFnciIiITw+JORERkYljciYiITAyLOxERkYlhcSciIjIxLO5EREQmhsWdiIjIxLC4ExERmRgWdyIiIhPD4k5ERGRiWNyJiIhMDIs7ERGRiWFxJyIiMjGV+jx3KptH7/pXdoQXCz1Z2QmIiP51uOVORERkYljciYiITAyLOxERkYlhcSciIjIxLO5EREQmhsWdiIjIxLC4ExERmRgWdyIiIhPD4k5ERGRiWNyJiIhMDIs7ERGRiTHqe8tfuHABmzdvhlqtRpcuXdC7d+/KjkRERGT0jLa4q9VqbNy4EXPmzIGzszNmzpyJZs2aoVq1apUdjUwIH75DZDqMfnmuwGXZaIt7XFwc3N3d4ebmBgDw9/fH2bNnWdxfMka/sBGRXrgsv1yM9ph7SkoKnJ2dpdfOzs5ISUmpxEREREQvB6PdchdCFGmTyWQar8PCwhAWFgYAWLRoETw8PAwb4vdzhu0fUSkZ/LtdDow9o7HnA4w8I9eHBlFR89hot9ydnZ2RnJwsvU5OToajo6NGNwEBAVi0aBEWLVpULhk+//zzcumvoRh7PsD4Mxp7PoAZDcHY8wHGn9HY8wHGn7Ei8xltcX/11VcRHx+PhIQEqFQqnDx5Es2aNavsWEREREbPaHfLm5mZYcSIEViwYAHUajU6deqE6tWrV3YsIiIio2e0xR0A/Pz84OfnV2nDDwgIqLRh68PY8wHGn9HY8wHMaAjGng8w/ozGng8w/owVmU8mtJ25RkRERC8toz3mTkRERKVj1LvlK0tl3fY2JycHgYGBUKlUyMvLQ6tWrdC/f3/p/X379uGHH37Ahg0bYGdnhydPnmDp0qWIi4tDx44dMXLkSKnbBQsW4PHjx8jLy4Ovry8++ugjyOWG+S339OlTrF27Fvfu3YNMJsPYsWNhaWmJ9evXIycnB2ZmZvjoo49Qu3ZtXLx4ET/++CNUKhXMzc3xwQcfoEGDBgAAlUqFjRs3Ijo6GjKZDAMGDECrVq1KlSkkJARRUVGwt7dHUFAQACAjIwPLli1DYmIiXFxcMGXKFCgUimIz6ZpuiYmJWLNmDdLT06FQKDBx4kSN+zCUJt+OHTtw7tw5yGQy2NvbY9y4cXBycgIA3LlzB99//z0yMzMhk8mwcOFCWFpa4ssvv0RqaiosLS0BAHPmzIG9vT3279+PQ4cOwczMDHZ2dhg7dixcXFzKPA2XLVuGBw8eAACePXsGW1tbLFmyBAAQGhqK8PBwyOVyDB8+HI0bNwbw4vl6+vRpLF26FAsXLsSrr76qd76kpCQEBwfj8ePHkMlkCAgIQI8ePXTO54KfmzJlCvr164devXohMzMTX3zxhfR+SkoK2rVrh2HDhmHLli24cuUKgOfLY1paGrZs2VLmjLrmtUqlwtq1a3Hr1i2o1Wq0b98e7777LgDg5MmT2LNnD9RqNfz8/DBkyBAAQG5uLlavXo2bN2+iatWqmDx5MlxdXcuUT9d8jouLw7p166TP9+vXDy1atAAA3Lx5E8HBwcjJyUGTJk0wfPhwyGQy/Oc//8HBgwchl8thbW2N0aNHl+jmY7rWg7rm87Fjx7Bv3z7p83fv3sXixYtRs2ZN/Pzzz4iIiEBGRga2b9+uMZyTJ09i9+7dkMlk8PLywqRJk8qUL5++6+ns7GwsXboUjx49glwuR9OmTTF48GAAKPP6BgAgSENeXp6YMGGCePjwocjNzRWffvqpuHfvXoUMW61Wi8zMTCGEELm5uWLmzJni+vXrQgghEhMTxfz588XYsWNFWlqaEEKIzMxMcfXqVXHw4EGxYcMGjX49ffpU6ueSJUvE8ePHDZZz1apVIiwsTMqZkZEh5s2bJ6KiooQQQpw/f14EBgYKIYS4efOmSE5OFkIIcefOHTFq1CipPzt37hQ///yzEOL5dM8fr9K4cuWKuHHjhpg6darUtn37dhEaGiqEECI0NFRs3779hZl0TbegoCBx+PBhIYQQly5dEitXrixzvvxhCSHE77//LtatWyeEEEKlUolp06aJW7duCSGESE9PF3l5eUIIIQIDA0VcXFyR/l+6dElkZWUJIYQ4ePCgWLp0aYny6cpY0NatW8Xu3buFEELcu3dPfPrppyInJ0c8evRITJgwQcpY3Hx99uyZ+OKLL8SsWbO0jkdxUlJSxI0bN6T+fPLJJ+LevXs653O+JUuWiKCgIPHrr79q7e+MGTPElStXirQfOHBABAcHGySjrnl97NgxsWzZMiGEEFlZWWLcuHHi0aNHIj09XYwZM0aadqtWrRIXL14UQgjx559/Sp8/fvx4iea1rnwFFZzPWVlZQqVSSZ8dOXKk9Przzz8X169fF2q1WixYsEBa/guO69mzZ8X8+fP1zieE7vXgi+azEM+X5/Hjx0uvr1+/LlJSUsSQIUM0unvw4IGYPn26ePLkiRBCiMePH5c5nxAlW09nZWWJS5cuSf2ZO3euNA3Lur4RQgjuli+k4G1vzc3NpdveVgSZTAZra2sAQF5eHvLy8qQb92zduhWDBw/WuJGPtbU1fH19pa24gmxtbaX+qFSqIjcAKq1nz57h6tWr6Ny5MwDA3NwcVapUgUwmQ2ZmptRN/j0JatWqJW2NVq9eHbm5ucjNzQUAHD58WNorIpfLYWdnV+pc9evX19haA4CzZ8+iQ4cOAIAOHTpI87G4TLqm2/379/H6668DAF577TWcO1eyG3poy5c/LOD5r/j8Yf3zzz+oUaMGatasCQCoWrXqC/e6NGjQAFZWVgAAHx+fUt3NUVvGfEIInDp1Cm3atAHwfNr6+/vDwsICrq6ucHd3R1xcHIDi5+vOnTvRq1cvWFhYlDifo6MjvL29AQA2Njbw9PRESkqKzvkMAJGRkXBzc9O55RgfH4/09HTUq1evyHsnTpxA27ZtDZJR17wGgKysLOTl5SEnJwfm5uawtbXFo0eP4OHhIU27hg0b4syZMwCAc+fOoWPHjgCAVq1a4fLly1pv+lWSfPkKz2crKyuYmZkBeL7HID93amoqMjMzUadOHchkMrRv316a7gXHNSsrq8TrHl3rweLmc77jx49L2QGgTp06Re6PAgCHDh1C165dpe+7vb19mfMBJVtPW1lZSXsMzc3NUatWLeneLmVd3wDcLV+EttvexsbGVtjw1Wo1PvvsMzx8+BBdu3aFj48Pzp07BycnJ2llr68FCxYgLi4OjRs3LvXu7sISEhJgZ2eHkJAQ3LlzB97e3hg2bBiGDh2KBQsWYPv27VCr1Zg/f36Rz545cwa1atWChYUFnj59CuD5yj46Ohpubm4YMWIEHBwcDJITANLS0qQF29HREenp6cVmyqdtunl5eeHMmTPo0aMHIiMjkZmZiSdPnqBq1aplypi/29DW1haBgYEAnhccmUyGBQsWID09Hf7+/njnnXekz4SEhEAul6Nly5Z47733iqw8w8PDpV3khnL16lXY29vjlVdeAfB8OfHx8ZHed3JyQkpKSrHz9datW0hKSkLTpk3x22+/lSlPQkICbt26hdq1a+ucz1lZWfj1118xd+5cjd22BZ04cQKtW7cuMg0TExORkJAgrXzLmhHQPq9btWqFc+fOYdSoUcjJycHQoUOhUCjg7u6O//73v0hISICzszMiIyOhUqkAaK6jzMzMYGtriydPnpT4x3HhfEDR+QwAsbGxWLNmDRITEzFx4kSYmZm98Pbgf/75J37//XeoVCqNQyD60rYe1Gd5PnXqFKZPn/7C/ucfgpg7dy7UajX69etXomXGkOtp4PmhzvPnz6NHjx4ADLO+4ZZ7Idp+ARtqq1cfcrkcS5Yswdq1a3Hjxg3cuXMHe/bswfvvv1/ifs2ePRvr1q1Dbm4uLl++bJB8eXl5uHXrFt588018++23sLKywt69e/Gf//wHQ4cOxZo1azB06FCsXbtW43P37t3Djz/+iI8//ljqT3JyMurWrYvFixejTp06RY6JlbfCmfJpm24ffPABoqOjMWPGDERHR8PJyUnaoimLgQMHYs2aNWjbti3+/PNPAM+nzbVr1zBx4kR8/fXXiIyMxKVLlwAAn3zyCYKCgvD111/j2rVriIiI0OhfREQEbt68iV69epU5W0EnTpzQ2CLStaWoa76q1Wps3boVH374YZmzZGVlISgoCMOGDdPYSixs165deOutt6StLG10bZ2fOHECrVq1KvV5KtoyapvXcXFxkMvlWLduHVavXo3ffvsNjx49gkKhwEcffYTly5fjiy++gKurq/R9M8Q6Stc0LDyfged7gvLPkQgNDUVOTs4L9xR069YNq1atwuDBg/HLL7+UKBtQdD149+7dF34mNjYWlpaWqFGjxgu7VavViI+PR2BgICZNmoS1a9dKP0xLk68s6+m8vDysWLEC3bt3lx6UZoj1DYt7Ifrc9rYiVKlSBfXr18fZs2eRkJCA6dOnY/z48UhOTsZnn32Gx48f69UfS0tLNGvWzGCHFpydneHs7CxttbVq1Qq3bt3C0aNH0bJlSwBA69atpV20wPNp+N1332H8+PFwd3cH8HxXs5WVlXRyTn5/DMne3h6pqakAnu9GLLhloy1TQYWnm5OTEz799FN8++23GDhwIAAUW1hKqm3bttJuV2dnZ9SvXx92dnawsrJCkyZNpGmTfzjBxsYGbdu21ZjOFy9eRGhoKGbMmFGq3d665OXlITIyEv7+/3sqWOHlJCUlBU5OTjrna1ZWFu7du4evvvoK48ePR2xsLL799lvcuHGjRFlUKhWCgoLQrl076fumaz7HxcXhxx9/xPjx43HgwAGEhoZKRRUAbt++DbVaLe2mLujkyZNFilxZMhZUcF4fP34cjRs3hrm5Oezt7VG3bl1pmjRr1gzffPMNFixYAA8PD2lruuC0z8vLw7Nnz3QeTilJPm3zuaBq1arB2toa9+7d07qezP9uFlTWw5r568ELFy4UuzwD2n+Y6OLk5ITmzZvD3Nwcrq6u8PDwQHx8fKnzlWU9vW7dOri7u+Ott97SyFfW9Q2LeyGVedvb9PR06ddjTk4OLl26hFq1amHDhg0IDg5GcHAwnJ2dsXjx4mJ3X2dlZUkLQV5eHv7++294enoaJKODgwOcnZ2l3VqXLl1CtWrV4OTkhOjoaADA5cuXpYL59OlTLFq0CAMHDoSvr6/UH5lMhqZNm2p8xtCP823WrBmOHj0KADh69CiaN29ebKbiplt6ejrUajWA52eJd+rUqcz5Cq5Mzp07Jz1QolGjRrh79y6ys7ORl5eHq1evolq1asjLy5N2RapUKpw/f166a+OtW7ewfv16zJgxo0THD/Vx6dIleHh4aOyGbdasGU6ePInc3FwkJCQgPj4etWvX1jlfbW1tsXHjRul77OPjgxkzZpTobHkhBNauXQtPT0+8/fbbGlm0zeevv/5aGl6PHj3w7rvvolu3btLndBWDBw8e4OnTp6hTp07JJlQxGXXNa6VSKR0zz8rKQmxsrPSdS0tLA/D8qo+DBw9K57k0bdoUR44cAfD8yoPXXntN7y13XfkA7fM5ISEBeXl5AJ4fqnjw4AFcXFzg6OgIGxsbxMTEQAiBiIgIaT1ZcFyjoqI0dvHrQ9t60NPTU+d8Bp5viZ8+fVrv4t6iRQtpr1x6ejri4+OlrebS5CvNehp4fsXMs2fPMGzYsCLDKOv6hsfcC6nM296mpqYiODgYarUaQgi0bt0aTZs2LfYz48ePx7Nnz6BSqXD27FnMmTMHCoUC3377LXJzc6FWq9GgQQO88cYbBss5YsQIrFy5EiqVCq6urhg3bhyaN28uXT5oYWGB0aNHA3h+7O3hw4f45ZdfpN1z+ZdvDR48GKtXr8aWLVtgZ2eHcePGlTrT8uXLER0djSdPnmDMmDHo378/evfujWXLliE8PBxKpRJTp04tNpMQQud0i46Oxk8//QSZTIZ69eppXHZY2nxRUVHS8XWlUolRo0YBABQKBd566y3MnDkTMpkMTZo0gZ+fH7KysrBgwQLk5eVBrVbj9ddfl+549cMPPyArKwtLly4F8LxofPbZZ2XO2LlzZ61FsHr16mjdujWmTp0KuVyOkSNHSruwDTlfC7p+/ToiIiJQo0YN6bjqwIEDdc7nFzl16hRmzpxZpP348ePw9/cv1eE4XRnDw8O1zutu3bohJCQE06ZNgxACnTp1gpeXFwBg8+bNuHPnDgCgb9++0g+Czp07Y/Xq1Zg4cSIUCgUmT55c5nx+fn5a5/O1a9ewd+9emJmZSfM5f4v5o48+QkhICHJyctC4cWM0adIEwPPl69KlSzAzM4NCocD48eNLNA11rQfr1Kmjcz5fvXoVzs7ORQr0Dz/8gOPHjyMnJwdjxoxB586d0b9/fzRq1Aj//PMPpkyZArlcjiFDhuh9PNtQ62kbGxvs2bMHnp6e0rLarVs3dOnSpczrG4B3qCMiIjI53C1PRERkYljciYiITAyLOxERkYlhcSciIjIxLO5EREQmhsWd6CUQHByMHTt2VMqwhRAICQnB8OHDtV46VpGOHTum9dbGRKSJxZ2oFMaPH4+PP/4YWVlZUtuhQ4fw5ZdfVl6ocnLt2jVcvHgRa9aswcKFC4u8f+TIEcydO7dCsrRr1w5z5sypkGEVduXKFYwZM6ZShk1UUizuRKWUl5eHAwcOVHaMEsu/85W+8p+fXdw92l8G+XdaI/o34B3qiEqpV69e+PXXX9G1a1dUqVJF472EhARMmDABP//8s/TAhy+//BLt2rVDly5dcOTIERw6dAivvvoqjhw5AoVCgYkTJyI+Ph47d+5Ebm4uhgwZIj3aE3h+S8p58+YhNjYWtWrVwoQJE+Di4gIA+O9//4tNmzbh5s2bsLOzw/vvvy/dIzw4OBiWlpZISkpCdHQ0pk+fjoYNG2rkTUlJwfr163Ht2jUoFAq88847CAgIQHh4ODZu3AiVSoUPPvgAPXv2RP/+/YudLuPHj0fXrl0RERGBR48ewd/fHwMHDkRISAiuXbsGHx8fTJkyBQqFQppOY8eOxa5du5CVlYWBAwfC29sba9euRVJSEtq1ayfdoSt/us2bNw/A88fjbtq0CY8fP0a7du1w7949tG/fvsg0Pnr0KLp27YqOHTti3bp1uHPnDmQyGRo1aoSRI0dK869g9sTERDRu3Bjjx4+HWq3GN998I00HAFixYgVSUlKwYcMGxMfHw9LSEm3btsXQoUNL83UiMihuuROVkre3N1577bVSP740NjYWXl5e2LRpE9q2bYvly5cjLi4OK1euxMSJE7Fp0yaN3f7Hjx/He++9h40bN6JmzZpYuXIlgOf3xJ8/fz7atm2LDRs2YNKkSdi4cSPu3bun8dl3330XW7du1biffr4VK1bA2dkZ69atw7Rp0/Dzzz/j0qVL6Ny5Mz7++GPp6W4vKuz5zpw5gzlz5mDFihU4f/48Fi5ciIEDB2Ljxo1Qq9X4448/ikyLFStWYPLkydi6dSv27NmDuXPnYunSpTh16pR0r/qC0tPTsXTpUgwaNAibNm2Ch4cHYmJiivTXzc0NGzZsQJ8+fQAA7777LtatW4dly5YhOTkZu3fv1vjMqVOnMGvWLAQHB+Pu3bs4cuQIrK2tMWvWLDg6OmL79u3Yvn07nJycsHnzZvTo0QNbt27FqlWr0Lp1a72mD1F5Y3EnKoP+/fvjjz/+0Pps6RdxdXVFp06dIJfL4e/vj+TkZPTt2xcWFhZo1KgRzM3N8fDhQ6l7Pz8/1K9fHxYWFhg4cCBiYmKQlJSEqKgouLi4oFOnTjAzM4O3tzdatmyJ06dPS59t3rw5fH19IZfLYWlpqZEjKSkJ165dw+DBg2FpaYmaNWuiS5cuRR4nWxLdunWDg4MDnJyc4Ovri9q1a6NWrVqwsLBAixYtijwBsG/fvrC0tESjRo1gZWWFtm3bwt7eXvq8ticG/v3336hWrRpatmwJMzMzdO/evciDOhwdHdG9e3eYmZnB0tIS7u7uaNiwISwsLGBnZ4e33nqryA+H7t27w8nJCQqFAk2bNsXt27d1jmf+PEpPT4e1tXWpHjZDVB64W56oDGrUqIGmTZti7969JX7yXsGnt+UX3ILFydLSUmPLveDTuqytraFQKJCamorExETExsZqPFkqLy8P7du31/rZwlJTU6FQKGBjYyO1KZXKEj+OtaDC41b4dXZ2dom6LzgdCuYuOF4ymazIY0eVSqXG67S0NGzevBlXr15FVlYW1Gp1kcelFp4HKSkpOsdzzJgx2LlzJ6ZMmQJXV1f07dv3hQ8RIaoILO5EZdS/f3989tlnGo/QzD/5LDs7W3oOsz7Pdi5OwednZ2VlISMjA46OjtLz34s7Y724J5w5OjoiIyMDmZmZUoFPSkrS+nxuY+Lg4KBReIUQxRZiAPjpp58AAN999x2qVq2KyMhIbNq0Sa/haZuGr7zyCiZPngy1Wo3IyEgsXboUGzdufOlPPqSXH3fLE5WRu7s7WrdurXEc2c7ODk5OTjh27BjUajXCw8Px6NGjMg3n77//xrVr16BSqbBjxw74+PhAqVSiadOmiI+PR0REBFQqFVQqFeLi4nD//n29+qtUKlG3bl389NNPyMnJwZ07d3D48GG0a9euTHnLm5+fH+7evYvIyEjk5eXh4MGDL/wBlZmZCWtra1SpUgUpKSklOl/C3t4eT548wbNnz6S2iIgIpKenQy6XSz/i8h99S1SZuOVOZAB9+/bFsWPHNNpGjx6NDRs24Oeff0bnzp3LfDy2TZs22L17N2JiYuDt7Y1PPvkEAGBjY4M5c+Zg69at2Lp1K4QQ8PLyKtFZ25MmTcL69esxevRoKBQK9OvXr8gZ9cbGzs4OU6dOxebNmxEcHIx27drB29sbFhYWOj/Tr18/rF69GkOHDoW7uzvat2+P33//Xa/heXp6ok2bNpgwYQLUajWWLl2KCxcuYNu2bcjOzoaLiwsmTZpU5JwGosrA57kTkUlQq9UYO3YsJk6ciAYNGlR2HKJKxf1HRPTSunDhAp4+fYrc3FyEhoZCCMEz1onA3fJE9BKLiYnBypUroVKpUK1aNUyfPp27xYnA3fJEREQmh7vliYiITAyLOxERkYlhcSciIjIxLO5EREQmhsWdiIjIxLC4ExERmZj/B//ETLNrNxJoAAAAAElFTkSuQmCC\n", | |
| "text/plain": [ | |
| "<Figure size 576x360 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "# 'bin_edges' is a list of bin intervals\n", | |
| "count, bin_edges = np.histogram(df_can['2013'])\n", | |
| "\n", | |
| "df_can['2013'].plot(kind='hist', figsize=(8, 5), xticks=bin_edges)\n", | |
| "\n", | |
| "plt.title('Histogram of Immigration from 195 countries in 2013') # add a title to the histogram\n", | |
| "plt.ylabel('Number of Countries') # add y-label\n", | |
| "plt.xlabel('Number of Immigrants') # add x-label\n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "*Side Note:* We could use `df_can['2013'].plot.hist()`, instead. In fact, throughout this lesson, using `some_data.plot(kind='type_plot', ...)` is equivalent to `some_data.plot.type_plot(...)`. That is, passing the type of the plot as argument or method behaves the same. \n", | |
| "\n", | |
| "See the *pandas* documentation for more info http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.plot.html." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "We can also plot multiple histograms on the same plot. For example, let's try to answer the following questions using a histogram.\n", | |
| "\n", | |
| "**Question**: What is the immigration distribution for Denmark, Norway, and Sweden for years 1980 - 2013?" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 24, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
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| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>1980</th>\n", | |
| " <th>1981</th>\n", | |
| " <th>1982</th>\n", | |
| " <th>1983</th>\n", | |
| " <th>1984</th>\n", | |
| " <th>1985</th>\n", | |
| " <th>1986</th>\n", | |
| " <th>1987</th>\n", | |
| " <th>1988</th>\n", | |
| " <th>1989</th>\n", | |
| " <th>...</th>\n", | |
| " <th>2004</th>\n", | |
| " <th>2005</th>\n", | |
| " <th>2006</th>\n", | |
| " <th>2007</th>\n", | |
| " <th>2008</th>\n", | |
| " <th>2009</th>\n", | |
| " <th>2010</th>\n", | |
| " <th>2011</th>\n", | |
| " <th>2012</th>\n", | |
| " <th>2013</th>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Country</th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>Denmark</th>\n", | |
| " <td>272</td>\n", | |
| " <td>293</td>\n", | |
| " <td>299</td>\n", | |
| " <td>106</td>\n", | |
| " <td>93</td>\n", | |
| " <td>73</td>\n", | |
| " <td>93</td>\n", | |
| " <td>109</td>\n", | |
| " <td>129</td>\n", | |
| " <td>129</td>\n", | |
| " <td>...</td>\n", | |
| " <td>89</td>\n", | |
| " <td>62</td>\n", | |
| " <td>101</td>\n", | |
| " <td>97</td>\n", | |
| " <td>108</td>\n", | |
| " <td>81</td>\n", | |
| " <td>92</td>\n", | |
| " <td>93</td>\n", | |
| " <td>94</td>\n", | |
| " <td>81</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Norway</th>\n", | |
| " <td>116</td>\n", | |
| " <td>77</td>\n", | |
| " <td>106</td>\n", | |
| " <td>51</td>\n", | |
| " <td>31</td>\n", | |
| " <td>54</td>\n", | |
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| " <td>73</td>\n", | |
| " <td>66</td>\n", | |
| " <td>75</td>\n", | |
| " <td>46</td>\n", | |
| " <td>49</td>\n", | |
| " <td>53</td>\n", | |
| " <td>59</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Sweden</th>\n", | |
| " <td>281</td>\n", | |
| " <td>308</td>\n", | |
| " <td>222</td>\n", | |
| " <td>176</td>\n", | |
| " <td>128</td>\n", | |
| " <td>158</td>\n", | |
| " <td>187</td>\n", | |
| " <td>198</td>\n", | |
| " <td>171</td>\n", | |
| " <td>182</td>\n", | |
| " <td>...</td>\n", | |
| " <td>129</td>\n", | |
| " <td>205</td>\n", | |
| " <td>139</td>\n", | |
| " <td>193</td>\n", | |
| " <td>165</td>\n", | |
| " <td>167</td>\n", | |
| " <td>159</td>\n", | |
| " <td>134</td>\n", | |
| " <td>140</td>\n", | |
| " <td>140</td>\n", | |
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| "<p>3 rows × 34 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 ... \\\n", | |
| "Country ... \n", | |
| "Denmark 272 293 299 106 93 73 93 109 129 129 ... \n", | |
| "Norway 116 77 106 51 31 54 56 80 73 76 ... \n", | |
| "Sweden 281 308 222 176 128 158 187 198 171 182 ... \n", | |
| "\n", | |
| " 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 \n", | |
| "Country \n", | |
| "Denmark 89 62 101 97 108 81 92 93 94 81 \n", | |
| "Norway 73 57 53 73 66 75 46 49 53 59 \n", | |
| "Sweden 129 205 139 193 165 167 159 134 140 140 \n", | |
| "\n", | |
| "[3 rows x 34 columns]" | |
| ] | |
| }, | |
| "execution_count": 24, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# let's quickly view the dataset \n", | |
| "df_can.loc[['Denmark', 'Norway', 'Sweden'], years]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 25, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<AxesSubplot:ylabel='Frequency'>" | |
| ] | |
| }, | |
| "execution_count": 25, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "# generate histogram\n", | |
| "df_can.loc[['Denmark', 'Norway', 'Sweden'], years].plot.hist()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "That does not look right! \n", | |
| "\n", | |
| "Don't worry, you'll often come across situations like this when creating plots. The solution often lies in how the underlying dataset is structured.\n", | |
| "\n", | |
| "Instead of plotting the population frequency distribution of the population for the 3 countries, *pandas* instead plotted the population frequency distribution for the `years`.\n", | |
| "\n", | |
| "This can be easily fixed by first transposing the dataset, and then plotting as shown below.\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 26, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
| " vertical-align: middle;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe tbody tr th {\n", | |
| " vertical-align: top;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe thead th {\n", | |
| " text-align: right;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th>Country</th>\n", | |
| " <th>Denmark</th>\n", | |
| " <th>Norway</th>\n", | |
| " <th>Sweden</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>1980</th>\n", | |
| " <td>272</td>\n", | |
| " <td>116</td>\n", | |
| " <td>281</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1981</th>\n", | |
| " <td>293</td>\n", | |
| " <td>77</td>\n", | |
| " <td>308</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1982</th>\n", | |
| " <td>299</td>\n", | |
| " <td>106</td>\n", | |
| " <td>222</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1983</th>\n", | |
| " <td>106</td>\n", | |
| " <td>51</td>\n", | |
| " <td>176</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1984</th>\n", | |
| " <td>93</td>\n", | |
| " <td>31</td>\n", | |
| " <td>128</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| "Country Denmark Norway Sweden\n", | |
| "1980 272 116 281\n", | |
| "1981 293 77 308\n", | |
| "1982 299 106 222\n", | |
| "1983 106 51 176\n", | |
| "1984 93 31 128" | |
| ] | |
| }, | |
| "execution_count": 26, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# transpose dataframe\n", | |
| "df_t = df_can.loc[['Denmark', 'Norway', 'Sweden'], years].transpose()\n", | |
| "df_t.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 27, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 720x432 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "# generate histogram\n", | |
| "df_t.plot(kind='hist', figsize=(10, 6))\n", | |
| "\n", | |
| "plt.title('Histogram of Immigration from Denmark, Norway, and Sweden from 1980 - 2013')\n", | |
| "plt.ylabel('Number of Years')\n", | |
| "plt.xlabel('Number of Immigrants')\n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Let's make a few modifications to improve the impact and aesthetics of the previous plot:\n", | |
| "* increase the bin size to 15 by passing in `bins` parameter\n", | |
| "* set transparency to 60% by passing in `alpha` paramemter\n", | |
| "* label the x-axis by passing in `x-label` paramater\n", | |
| "* change the colors of the plots by passing in `color` parameter" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 28, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 720x432 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "# let's get the x-tick values\n", | |
| "count, bin_edges = np.histogram(df_t, 15)\n", | |
| "\n", | |
| "# un-stacked histogram\n", | |
| "df_t.plot(kind ='hist', \n", | |
| " figsize=(10, 6),\n", | |
| " bins=15,\n", | |
| " alpha=0.6,\n", | |
| " xticks=bin_edges,\n", | |
| " color=['coral', 'darkslateblue', 'mediumseagreen']\n", | |
| " )\n", | |
| "\n", | |
| "plt.title('Histogram of Immigration from Denmark, Norway, and Sweden from 1980 - 2013')\n", | |
| "plt.ylabel('Number of Years')\n", | |
| "plt.xlabel('Number of Immigrants')\n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Tip:\n", | |
| "For a full listing of colors available in Matplotlib, run the following code in your python shell:\n", | |
| "```python\n", | |
| "import matplotlib\n", | |
| "for name, hex in matplotlib.colors.cnames.items():\n", | |
| " print(name, hex)\n", | |
| "```" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "If we do no want the plots to overlap each other, we can stack them using the `stacked` paramemter. Let's also adjust the min and max x-axis labels to remove the extra gap on the edges of the plot. We can pass a tuple (min,max) using the `xlim` paramater, as show below." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 29, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 720x432 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "count, bin_edges = np.histogram(df_t, 15)\n", | |
| "xmin = bin_edges[0] - 10 # first bin value is 31.0, adding buffer of 10 for aesthetic purposes \n", | |
| "xmax = bin_edges[-1] + 10 # last bin value is 308.0, adding buffer of 10 for aesthetic purposes\n", | |
| "\n", | |
| "# stacked Histogram\n", | |
| "df_t.plot(kind='hist',\n", | |
| " figsize=(10, 6), \n", | |
| " bins=15,\n", | |
| " xticks=bin_edges,\n", | |
| " color=['coral', 'darkslateblue', 'mediumseagreen'],\n", | |
| " stacked=True,\n", | |
| " xlim=(xmin, xmax)\n", | |
| " )\n", | |
| "\n", | |
| "plt.title('Histogram of Immigration from Denmark, Norway, and Sweden from 1980 - 2013')\n", | |
| "plt.ylabel('Number of Years')\n", | |
| "plt.xlabel('Number of Immigrants') \n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "**Question**: Use the scripting layer to display the immigration distribution for Greece, Albania, and Bulgaria for years 1980 - 2013? Use an overlapping plot with 15 bins and a transparency value of 0.35." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "### type your answer here\n", | |
| "\n", | |
| "\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "<details><summary>Click here for a sample python solution</summary>\n", | |
| "\n", | |
| "```python\n", | |
| " #The correct answer is:\n", | |
| " \n", | |
| " # create a dataframe of the countries of interest (cof)\n", | |
| " df_cof = df_can.loc[['Greece', 'Albania', 'Bulgaria'], years]\n", | |
| "\n", | |
| " # transpose the dataframe\n", | |
| " df_cof = df_cof.transpose() \n", | |
| "\n", | |
| " # let's get the x-tick values\n", | |
| " count, bin_edges = np.histogram(df_cof, 15)\n", | |
| "\n", | |
| " # Un-stacked Histogram\n", | |
| " df_cof.plot(kind ='hist',\n", | |
| " figsize=(10, 6),\n", | |
| " bins=15,\n", | |
| " alpha=0.35,\n", | |
| " xticks=bin_edges,\n", | |
| " color=['coral', 'darkslateblue', 'mediumseagreen']\n", | |
| " )\n", | |
| "\n", | |
| " plt.title('Histogram of Immigration from Greece, Albania, and Bulgaria from 1980 - 2013')\n", | |
| " plt.ylabel('Number of Years')\n", | |
| " plt.xlabel('Number of Immigrants')\n", | |
| "\n", | |
| " plt.show()\n", | |
| "\n", | |
| " \n", | |
| "```\n", | |
| "\n", | |
| "\n", | |
| "</details>\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "# Bar Charts (Dataframe) <a id=\"10\"></a>\n", | |
| "\n", | |
| "A bar plot is a way of representing data where the *length* of the bars represents the magnitude/size of the feature/variable. Bar graphs usually represent numerical and categorical variables grouped in intervals. \n", | |
| "\n", | |
| "To create a bar plot, we can pass one of two arguments via `kind` parameter in `plot()`:\n", | |
| "\n", | |
| "* `kind=bar` creates a *vertical* bar plot\n", | |
| "* `kind=barh` creates a *horizontal* bar plot" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "**Vertical bar plot**\n", | |
| "\n", | |
| "In vertical bar graphs, the x-axis is used for labelling, and the length of bars on the y-axis corresponds to the magnitude of the variable being measured. Vertical bar graphs are particuarly useful in analyzing time series data. One disadvantage is that they lack space for text labelling at the foot of each bar. \n", | |
| "\n", | |
| "**Let's start off by analyzing the effect of Iceland's Financial Crisis:**\n", | |
| "\n", | |
| "The 2008 - 2011 Icelandic Financial Crisis was a major economic and political event in Iceland. Relative to the size of its economy, Iceland's systemic banking collapse was the largest experienced by any country in economic history. The crisis led to a severe economic depression in 2008 - 2011 and significant political unrest.\n", | |
| "\n", | |
| "**Question:** Let's compare the number of Icelandic immigrants (country = 'Iceland') to Canada from year 1980 to 2013. " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 30, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "1980 17\n", | |
| "1981 33\n", | |
| "1982 10\n", | |
| "1983 9\n", | |
| "1984 13\n", | |
| "Name: Iceland, dtype: object" | |
| ] | |
| }, | |
| "execution_count": 30, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# step 1: get the data\n", | |
| "df_iceland = df_can.loc['Iceland', years]\n", | |
| "df_iceland.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 31, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
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\n", | |
| "text/plain": [ | |
| "<Figure size 720x432 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "# step 2: plot data\n", | |
| "df_iceland.plot(kind='bar', figsize=(10, 6))\n", | |
| "\n", | |
| "plt.xlabel('Year') # add to x-label to the plot\n", | |
| "plt.ylabel('Number of immigrants') # add y-label to the plot\n", | |
| "plt.title('Icelandic immigrants to Canada from 1980 to 2013') # add title to the plot\n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "The bar plot above shows the total number of immigrants broken down by each year. We can clearly see the impact of the financial crisis; the number of immigrants to Canada started increasing rapidly after 2008. \n", | |
| "\n", | |
| "Let's annotate this on the plot using the `annotate` method of the **scripting layer** or the **pyplot interface**. We will pass in the following parameters:\n", | |
| "- `s`: str, the text of annotation.\n", | |
| "- `xy`: Tuple specifying the (x,y) point to annotate (in this case, end point of arrow).\n", | |
| "- `xytext`: Tuple specifying the (x,y) point to place the text (in this case, start point of arrow).\n", | |
| "- `xycoords`: The coordinate system that xy is given in - 'data' uses the coordinate system of the object being annotated (default).\n", | |
| "- `arrowprops`: Takes a dictionary of properties to draw the arrow:\n", | |
| " - `arrowstyle`: Specifies the arrow style, `'->'` is standard arrow.\n", | |
| " - `connectionstyle`: Specifies the connection type. `arc3` is a straight line.\n", | |
| " - `color`: Specifes color of arror.\n", | |
| " - `lw`: Specifies the line width.\n", | |
| "\n", | |
| "I encourage you to read the Matplotlib documentation for more details on annotations: \n", | |
| "http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.annotate." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 32, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 720x432 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "df_iceland.plot(kind='bar', figsize=(10, 6), rot=90) # rotate the xticks(labelled points on x-axis) by 90 degrees\n", | |
| "\n", | |
| "plt.xlabel('Year')\n", | |
| "plt.ylabel('Number of Immigrants')\n", | |
| "plt.title('Icelandic Immigrants to Canada from 1980 to 2013')\n", | |
| "\n", | |
| "# Annotate arrow\n", | |
| "plt.annotate('', # s: str. Will leave it blank for no text\n", | |
| " xy=(32, 70), # place head of the arrow at point (year 2012 , pop 70)\n", | |
| " xytext=(28, 20), # place base of the arrow at point (year 2008 , pop 20)\n", | |
| " xycoords='data', # will use the coordinate system of the object being annotated \n", | |
| " arrowprops=dict(arrowstyle='->', connectionstyle='arc3', color='blue', lw=2)\n", | |
| " )\n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Let's also annotate a text to go over the arrow. We will pass in the following additional parameters:\n", | |
| "- `rotation`: rotation angle of text in degrees (counter clockwise)\n", | |
| "- `va`: vertical alignment of text [‘center’ | ‘top’ | ‘bottom’ | ‘baseline’]\n", | |
| "- `ha`: horizontal alignment of text [‘center’ | ‘right’ | ‘left’]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 33, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 720x432 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "df_iceland.plot(kind='bar', figsize=(10, 6), rot=90) \n", | |
| "\n", | |
| "plt.xlabel('Year')\n", | |
| "plt.ylabel('Number of Immigrants')\n", | |
| "plt.title('Icelandic Immigrants to Canada from 1980 to 2013')\n", | |
| "\n", | |
| "# Annotate arrow\n", | |
| "plt.annotate('', # s: str. will leave it blank for no text\n", | |
| " xy=(32, 70), # place head of the arrow at point (year 2012 , pop 70)\n", | |
| " xytext=(28, 20), # place base of the arrow at point (year 2008 , pop 20)\n", | |
| " xycoords='data', # will use the coordinate system of the object being annotated \n", | |
| " arrowprops=dict(arrowstyle='->', connectionstyle='arc3', color='blue', lw=2)\n", | |
| " )\n", | |
| "\n", | |
| "# Annotate Text\n", | |
| "plt.annotate('2008 - 2011 Financial Crisis', # text to display\n", | |
| " xy=(28, 30), # start the text at at point (year 2008 , pop 30)\n", | |
| " rotation=72.5, # based on trial and error to match the arrow\n", | |
| " va='bottom', # want the text to be vertically 'bottom' aligned\n", | |
| " ha='left', # want the text to be horizontally 'left' algned.\n", | |
| " )\n", | |
| "\n", | |
| "plt.show()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "**Horizontal Bar Plot**\n", | |
| "\n", | |
| "Sometimes it is more practical to represent the data horizontally, especially if you need more room for labelling the bars. In horizontal bar graphs, the y-axis is used for labelling, and the length of bars on the x-axis corresponds to the magnitude of the variable being measured. As you will see, there is more room on the y-axis to label categetorical variables.\n", | |
| "\n", | |
| "\n", | |
| "**Question:** Using the scripting layter and the `df_can` dataset, create a *horizontal* bar plot showing the *total* number of immigrants to Canada from the top 15 countries, for the period 1980 - 2013. Label each country with the total immigrant count." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Step 1: Get the data pertaining to the top 15 countries." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "### type your answer here\n", | |
| "\n", | |
| "\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "<details><summary>Click here for a sample python solution</summary>\n", | |
| "\n", | |
| "```python\n", | |
| " #The correct answer is:\n", | |
| " \n", | |
| " # sort dataframe on 'Total' column (descending)\n", | |
| " df_can.sort_values(by='Total', ascending=True, inplace=True)\n", | |
| "\n", | |
| " # get top 15 countries\n", | |
| " df_top15 = df_can['Total'].tail(15)\n", | |
| " df_top15\n", | |
| "\n", | |
| "```\n", | |
| "\n", | |
| "\n", | |
| "</details>\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "Step 2: Plot data:\n", | |
| " 1. Use `kind='barh'` to generate a bar chart with horizontal bars.\n", | |
| " 2. Make sure to choose a good size for the plot and to label your axes and to give the plot a title.\n", | |
| " 3. Loop through the countries and annotate the immigrant population using the anotate function of the scripting interface." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "### type your answer here\n", | |
| "\n", | |
| "\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "<details><summary>Click here for a sample python solution</summary>\n", | |
| "\n", | |
| "```python\n", | |
| " #The correct answer is:\n", | |
| " \n", | |
| " # generate plot\n", | |
| " df_top15.plot(kind='barh', figsize=(12, 12), color='steelblue')\n", | |
| " plt.xlabel('Number of Immigrants')\n", | |
| " plt.title('Top 15 Conuntries Contributing to the Immigration to Canada between 1980 - 2013')\n", | |
| "\n", | |
| " # annotate value labels to each country\n", | |
| " for index, value in enumerate(df_top15): \n", | |
| " label = format(int(value), ',') # format int with commas\n", | |
| " \n", | |
| " # place text at the end of bar (subtracting 47000 from x, and 0.1 from y to make it fit within the bar)\n", | |
| " plt.annotate(label, xy=(value - 47000, index - 0.10), color='white')\n", | |
| "\n", | |
| " plt.show()\n", | |
| "\n", | |
| "```\n", | |
| "\n", | |
| "\n", | |
| "</details>\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "button": false, | |
| "new_sheet": false, | |
| "run_control": { | |
| "read_only": false | |
| } | |
| }, | |
| "source": [ | |
| "### Thank you for completing this lab!\n", | |
| "\n", | |
| "\n", | |
| "## Author\n", | |
| "\n", | |
| "<a href=\"https://www.linkedin.com/in/aklson/\" target=\"_blank\">Alex Aklson</a>\n", | |
| "\n", | |
| "\n", | |
| "### Other Contributors\n", | |
| "[Jay Rajasekharan](https://www.linkedin.com/in/jayrajasekharan)\n", | |
| "[Ehsan M. Kermani](https://www.linkedin.com/in/ehsanmkermani)\n", | |
| "[Slobodan Markovic](https://www.linkedin.com/in/slobodan-markovic).\n", | |
| "\n", | |
| "\n", | |
| "## Change Log\n", | |
| "\n", | |
| "\n", | |
| "| Date (YYYY-MM-DD) | Version | Changed By | Change Description |\n", | |
| "|---|---|---|---|\n", | |
| "| 2021-01-20 | 2.3 | Lakshmi Holla | Changed TOC cell markdown |\n", | |
| "| 2021-01-05 | 2.2 | Lakshmi Holla | Changed solution code for annotate |\n", | |
| "| 2020-11-03 | 2.1 | Lakshmi Holla | Changed the URL of excel file |\n", | |
| "| 2020-08-27 | 2.0 | Lavanya | Moved lab to course repo in GitLab |\n", | |
| "\n", | |
| "\n", | |
| "\n", | |
| "## <h3 align=\"center\"> © IBM Corporation 2020. All rights reserved. <h3/>" | |
| ] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python", | |
| "language": "python", | |
| "name": "conda-env-python-py" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.6.13" | |
| }, | |
| "widgets": { | |
| "state": {}, | |
| "version": "1.1.2" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 4 | |
| } |
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