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lab_pokemon/lab_pokemon.ipynb
tsmith37 bfcd168d31 learned how to sort through data and make different plots 
If a super hero joins marvels avengers do they death and if they do how long does it take for them
to die after joining.

i can use the data set from avengers in FiveThirtyEight
2025-10-19 17:35:56 -04:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "90041b00-672b-4bd4-a8e8-0cab3f0548af",
"metadata": {},
"source": [
"# Lab 04: Data Science Tools\n",
"\n",
"## 0. Jupyter Notebooks\n",
"\n",
"Welcome to your first Jupyter notebook! Notebooks are made up of cells. Some cells contain text (like this one) and others contain Python code.\n",
"\n",
"Each cell can be in two different modes: editing or running. To edit a cell, double-click on it. When you're done editing, press **shift+Enter** to run it. You can use [Markdown](https://www.markdownguide.org/cheat-sheet/) to add basic formatting to the text. Before you go on, try editing the text in this cell."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "5923b0d7-c0e0-48fa-b765-4aa6002c2d4f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"16"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Other cells are code cells, containing Python code. (This is a comment, of course!)\n",
"# Try running this cell (again, shift+Enter). You'll see the result of the final statement \n",
"# printed below the cell. \n",
"# Then try changing the Python code and re-run it.\n",
"\n",
"5+10+1"
]
},
{
"cell_type": "markdown",
"id": "257ef44f-8f53-4136-9d0d-23a811ec53e9",
"metadata": {},
"source": [
"### 0.1 Cells share state\n",
"\n",
"Even though code cells run one at a time, anything that happens in a cell (like declaring a variable or running a function) affects the whole notebook. Try running these two cells a few times, in different orders. What happens when you run *Cell B* over and over?"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "0e2a2927-f6d1-4b13-97ae-ff97416723e9",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"15"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Cell A\n",
"x = 15\n",
"x"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "69dd7908-b213-4d0f-8016-e46a4a491961",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"30"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Cell B\n",
"x = x * 2\n",
"x"
]
},
{
"cell_type": "markdown",
"id": "adc581ac-db13-40a8-bcfc-bf5d6e5472c5",
"metadata": {},
"source": [
"### 0.2 Saving your work\n",
"\n",
"When you finish working on a notebook, save your work using the icon in the menu bar above. Your notebook is stored in the file `lab_pokemon.ipynb` in the lab directory. You can commit your changes to `ipynb` files just like any other file. Once you finish with Jupyter, you can stop the server by pressing **Control + C** in the Terminal. \n",
"\n",
"*If you're doing this lab on a cloud-based platform like Binder, then you can't save your work. So don't close the tab!*"
]
},
{
"cell_type": "markdown",
"id": "c9c4aec2-949d-4a2e-b736-f5182b1f9ff7",
"metadata": {},
"source": [
"---\n",
"\n",
"## 1. Pandas\n",
"\n",
"Pandas is probably the most important Python library for data science. Pandas provides an object called a **DataFrame**, which is basically a table with rows and columns. Most of the time, you will load data into Pandas using a `.csv` file. CSV files can be exported from Excel or Google Sheets, and are a common format for public data sets. \n",
"\n",
"In this lab, we'll be working with two data sets: The first contains Pokémon characteristics and the second comes from a wide-scale survey conducted by the US Centers for Disease Control ([details](https://www.cdc.gov/brfss/annual_data/annual_2020.html)). We will demonstrate techniques with Pokémon; your job is to replicate these tasks with the CDC dataset. \n",
"\n",
"**Note:** Pandas has *extensive* capabilities, and there's no way we could possibly present them all here. If you have a clearly-formed idea of what you want to do with tabular data, there's a way to do it. This lab introduces *some* of what Pandas can do, but expect to spend time reading the documentation and Stack Overflow when you start working on new tasks. \n",
"\n",
"### 1.0 Getting started\n",
"\n",
"First, we'll import pandas (using the conventional variable name `pd`) and load the two datasets. *Run these cells and every code cell you encounter in this notebook.*"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "ba09a0f8-27d9-456f-aeff-3980e3362d5b",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "a29d508a-2d9a-4d62-9ff6-7a0ecfd5eba4",
"metadata": {},
"outputs": [],
"source": [
"pokemon = pd.read_csv(\"pokemon.csv\")\n",
"people = pd.read_csv(\"brfss_2020.csv\")"
]
},
{
"cell_type": "markdown",
"id": "d4e0b811-b8bf-4e9a-a934-3aad8f0520bb",
"metadata": {},
"source": [
"### 1.1 A first look\n",
"\n",
"#### Demo\n",
"\n",
"Let's start by learning the *shape* of the data. How many columns are there? How many rows? What kinds of data are included?"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "579d8dda-ca39-48b1-8819-b17651029729",
"metadata": {},
"outputs": [
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" <td>Diancie</td>\n",
" <td>Rock</td>\n",
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" <th>796</th>\n",
" <td>DiancieMega Diancie</td>\n",
" <td>Rock</td>\n",
" <td>Fairy</td>\n",
" <td>700</td>\n",
" <td>50</td>\n",
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" <td>HoopaHoopa Unbound</td>\n",
" <td>Psychic</td>\n",
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" <td>680</td>\n",
" <td>80</td>\n",
" <td>160</td>\n",
" <td>60</td>\n",
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" <td>Volcanion</td>\n",
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" <td>80</td>\n",
" <td>110</td>\n",
" <td>120</td>\n",
" <td>130</td>\n",
" <td>90</td>\n",
" <td>70</td>\n",
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" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
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"<p>800 rows × 12 columns</p>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"0 Bulbasaur Grass Poison 318 45 49 49 \n",
"1 Ivysaur Grass Poison 405 60 62 63 \n",
"2 Venusaur Grass Poison 525 80 82 83 \n",
"3 VenusaurMega Venusaur Grass Poison 625 80 100 123 \n",
"4 Charmander Fire NaN 309 39 52 43 \n",
".. ... ... ... ... .. ... ... \n",
"795 Diancie Rock Fairy 600 50 100 150 \n",
"796 DiancieMega Diancie Rock Fairy 700 50 160 110 \n",
"797 HoopaHoopa Confined Psychic Ghost 600 80 110 60 \n",
"798 HoopaHoopa Unbound Psychic Dark 680 80 160 60 \n",
"799 Volcanion Fire Water 600 80 110 120 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"0 65 65 45 1 False \n",
"1 80 80 60 1 False \n",
"2 100 100 80 1 False \n",
"3 122 120 80 1 False \n",
"4 60 50 65 1 False \n",
".. ... ... ... ... ... \n",
"795 100 150 50 6 True \n",
"796 160 110 110 6 True \n",
"797 150 130 70 6 True \n",
"798 170 130 80 6 True \n",
"799 130 90 70 6 True \n",
"\n",
"[800 rows x 12 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"pokemon"
]
},
{
"cell_type": "markdown",
"id": "ee8b0718-56f9-4fc8-bd35-fa0ccb445179",
"metadata": {},
"source": [
"OK, 800 Pokémon, with 12 columns for each. And you can see all the columns. Not all the data is shown in this preview, of course. If there were more columns than could be displayed, you could see them all by typing `pokemon.columns`. \n",
"\n",
"#### Your turn\n",
"\n",
"Now do the same for your data set, `people`."
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "c9e5e4ec-b197-450c-ae2d-318006fa0a2f",
"metadata": {},
"outputs": [
{
"data": {
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>age</th>\n",
" <th>sex</th>\n",
" <th>income</th>\n",
" <th>education</th>\n",
" <th>sexual_orientation</th>\n",
" <th>height</th>\n",
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" <td>8</td>\n",
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" <td>1.80</td>\n",
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" <td>1.63</td>\n",
" <td>86.18</td>\n",
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" <td>False</td>\n",
" <td>False</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
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" <td>25</td>\n",
" <td>male</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.78</td>\n",
" <td>86.18</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
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" <tr>\n",
" <th>166422</th>\n",
" <td>25</td>\n",
" <td>female</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.91</td>\n",
" <td>45.36</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166423</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.60</td>\n",
" <td>68.04</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166424</th>\n",
" <td>35</td>\n",
" <td>male</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.75</td>\n",
" <td>86.18</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>166425 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" age sex income education sexual_orientation height weight \\\n",
"0 55 female 5 2 other 1.55 83.01 \n",
"1 65 female 8 1 heterosexual 1.65 78.02 \n",
"2 35 female 8 4 heterosexual 1.65 77.11 \n",
"3 55 male 8 4 heterosexual 1.83 81.65 \n",
"4 55 female 8 4 heterosexual 1.80 76.66 \n",
"... ... ... ... ... ... ... ... \n",
"166420 45 female 8 3 heterosexual 1.63 86.18 \n",
"166421 25 male 7 2 heterosexual 1.78 86.18 \n",
"166422 25 female 1 2 heterosexual 1.91 45.36 \n",
"166423 35 female 5 4 heterosexual 1.60 68.04 \n",
"166424 35 male 7 2 heterosexual 1.75 86.18 \n",
"\n",
" health no_doctor exercise sleep \n",
"0 2 True True 7 \n",
"1 3 False False 8 \n",
"2 4 True True 7 \n",
"3 5 False True 8 \n",
"4 4 False True 8 \n",
"... ... ... ... ... \n",
"166420 1 False False 6 \n",
"166421 4 False True 6 \n",
"166422 1 False False 8 \n",
"166423 4 True True 6 \n",
"166424 3 False False 8 \n",
"\n",
"[166425 rows x 11 columns]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people"
]
},
{
"cell_type": "markdown",
"id": "7fab76ef-d453-4568-a916-4d4c29535a42",
"metadata": {},
"source": [
"### 1.2 Descriptive Statistics\n",
"\n",
"#### Demo\n",
"\n",
"Let's get a sense of the data contained in some of the columns. For categorical data like `generation`, it makes sense to look at value counts--showing us how many of each category there are. You can use the optional keyword `normalize=True` to see percentage of total instead of frequencies. "
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "9afca362-9edc-423c-981b-dc42107d5de0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"special_attack\n",
"60 51\n",
"40 49\n",
"65 44\n",
"50 39\n",
"55 35\n",
" ..\n",
"78 1\n",
"31 1\n",
"194 1\n",
"29 1\n",
"175 1\n",
"Name: count, Length: 105, dtype: int64"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.special_attack.value_counts()"
]
},
{
"cell_type": "markdown",
"id": "a9b98eee-bdc2-4c63-bab2-ee82e2466d0f",
"metadata": {},
"source": [
"For numeric data, we could start by looking at the mean value. We can select multiple columns and get all the column means at once."
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "5fe580d0-5939-4152-9f8c-4c32d35a4479",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"hp 69.25875\n",
"attack 79.00125\n",
"defense 73.84250\n",
"speed 68.27750\n",
"dtype: float64"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon[[\"hp\", \"attack\", \"defense\", \"speed\"]].mean()"
]
},
{
"cell_type": "markdown",
"id": "0d8e6e78-fcfc-4c38-a418-545fe4216a44",
"metadata": {},
"source": [
"We can also compute the mean of boolean data. In this case, True will map to 1 and False will map to 0. So the mean value equals the percentage of data which is True. "
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "dc69ef53-70cd-4ae0-80e7-c9c8e28de76f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"np.float64(0.08125)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.legendary.mean()"
]
},
{
"cell_type": "markdown",
"id": "69333e87-8df2-4b46-9005-2b8c9df3a7b4",
"metadata": {},
"source": [
"Just over 8% of Pokemon are legendary."
]
},
{
"cell_type": "markdown",
"id": "f563d97d-d9d3-4f2d-a46a-5d5dfc6382de",
"metadata": {},
"source": [
"#### Your turn\n",
"\n",
"**1.2.0.** In this survey, people are grouped into age bands of 18-24, 25-34, 35-44, 45-54, 55-64, and 65+, with the lower bound reported. What percentage of people are in each age band? (When we talk about \"people\" in this lab, we're referring to the people who responded to the survey, not the whole US population.)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "8fbcc766-8399-4f93-a6c8-e0607250a72a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"age\n",
"65 55973\n",
"55 34345\n",
"45 26240\n",
"35 22555\n",
"25 18118\n",
"18 9194\n",
"Name: count, dtype: int64"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people.age.value_counts()"
]
},
{
"cell_type": "markdown",
"id": "38006e7b-4771-4c29-86a8-19d04a50fc25",
"metadata": {},
"source": [
"**1.2.1.** What are the mean height and weight of people in this survey?"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "b7f910c8-3d40-49ae-b270-678734c04100",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"height 1.705082\n",
"weight 83.053588\n",
"dtype: float64"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people[[\"height\", \"weight\"]].mean()"
]
},
{
"cell_type": "markdown",
"id": "f74634bb-8664-46e4-b371-6f45cbb7c8ef",
"metadata": {},
"source": [
"**1.2.2.** The `exercise` column indicates whether a person has done any physical activity or exercise in the last 30 days, outside of work. What percentage of people have done exercise?"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "f3891188-a85f-4089-8388-d4d81c7438ad",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"np.float64(0.7858014120474688)"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people.exercise.mean()"
]
},
{
"cell_type": "markdown",
"id": "f6082e65-321c-4ee0-9457-74f9bb1b0363",
"metadata": {},
"source": [
"### 1.3 Filtering\n",
"\n",
"Sometimes we're just interested in a selection of the data set. The way to do this is to create a boolean series, and then use this to select which rows you want to include. Vocabulary note: A dataframe is two-dimensional, with rows and columns. A series (a single row or a single column) is one-dimensional. \n",
"\n",
"#### Demo\n",
"`pokemon.legendary` is already boolean, so we can use this to select just the legendary pokémon. "
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "12c0c6c9-c07b-4183-82f6-5e346c74aac9",
"metadata": {},
"outputs": [
{
"data": {
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"<div>\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>name</th>\n",
" <th>type</th>\n",
" <th>subtype</th>\n",
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" <th>hp</th>\n",
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" <tr>\n",
" <th>158</th>\n",
" <td>Moltres</td>\n",
" <td>Fire</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>100</td>\n",
" <td>90</td>\n",
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" <td>680</td>\n",
" <td>106</td>\n",
" <td>110</td>\n",
" <td>90</td>\n",
" <td>154</td>\n",
" <td>90</td>\n",
" <td>130</td>\n",
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" <td>MewtwoMega Mewtwo X</td>\n",
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" <td>780</td>\n",
" <td>106</td>\n",
" <td>190</td>\n",
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" <tr>\n",
" <th>795</th>\n",
" <td>Diancie</td>\n",
" <td>Rock</td>\n",
" <td>Fairy</td>\n",
" <td>600</td>\n",
" <td>50</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>50</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>796</th>\n",
" <td>DiancieMega Diancie</td>\n",
" <td>Rock</td>\n",
" <td>Fairy</td>\n",
" <td>700</td>\n",
" <td>50</td>\n",
" <td>160</td>\n",
" <td>110</td>\n",
" <td>160</td>\n",
" <td>110</td>\n",
" <td>110</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>797</th>\n",
" <td>HoopaHoopa Confined</td>\n",
" <td>Psychic</td>\n",
" <td>Ghost</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>60</td>\n",
" <td>150</td>\n",
" <td>130</td>\n",
" <td>70</td>\n",
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" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>798</th>\n",
" <td>HoopaHoopa Unbound</td>\n",
" <td>Psychic</td>\n",
" <td>Dark</td>\n",
" <td>680</td>\n",
" <td>80</td>\n",
" <td>160</td>\n",
" <td>60</td>\n",
" <td>170</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>799</th>\n",
" <td>Volcanion</td>\n",
" <td>Fire</td>\n",
" <td>Water</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>120</td>\n",
" <td>130</td>\n",
" <td>90</td>\n",
" <td>70</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
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" </tbody>\n",
"</table>\n",
"<p>65 rows × 12 columns</p>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"156 Articuno Ice Flying 580 90 85 100 \n",
"157 Zapdos Electric Flying 580 90 90 85 \n",
"158 Moltres Fire Flying 580 90 100 90 \n",
"162 Mewtwo Psychic NaN 680 106 110 90 \n",
"163 MewtwoMega Mewtwo X Psychic Fighting 780 106 190 100 \n",
".. ... ... ... ... ... ... ... \n",
"795 Diancie Rock Fairy 600 50 100 150 \n",
"796 DiancieMega Diancie Rock Fairy 700 50 160 110 \n",
"797 HoopaHoopa Confined Psychic Ghost 600 80 110 60 \n",
"798 HoopaHoopa Unbound Psychic Dark 680 80 160 60 \n",
"799 Volcanion Fire Water 600 80 110 120 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"156 95 125 85 1 True \n",
"157 125 90 100 1 True \n",
"158 125 85 90 1 True \n",
"162 154 90 130 1 True \n",
"163 154 100 130 1 True \n",
".. ... ... ... ... ... \n",
"795 100 150 50 6 True \n",
"796 160 110 110 6 True \n",
"797 150 130 70 6 True \n",
"798 170 130 80 6 True \n",
"799 130 90 70 6 True \n",
"\n",
"[65 rows x 12 columns]"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"legendary = pokemon[pokemon.legendary]\n",
"legendary"
]
},
{
"cell_type": "markdown",
"id": "b4ad804a-f5f0-441f-bb83-51f360c1c154",
"metadata": {},
"source": [
"Let's get all the ice pokémon. We can create a boolean series from another series..."
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "5d089acf-7b76-4f91-8803-42a4a9a11e3e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 False\n",
"1 False\n",
"2 False\n",
"3 False\n",
"4 False\n",
" ... \n",
"795 False\n",
"796 False\n",
"797 False\n",
"798 False\n",
"799 False\n",
"Name: type, Length: 800, dtype: bool"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.type == \"Ice\""
]
},
{
"cell_type": "markdown",
"id": "a5ea9e89-f466-48de-9133-346c99f4a6c1",
"metadata": {},
"source": [
"And then use this series to select just the ice pokémon. "
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "510fa0fc-2b38-4725-9bbf-ec57d62792be",
"metadata": {},
"outputs": [
{
"data": {
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" <tr>\n",
" <th>239</th>\n",
" <td>Piloswine</td>\n",
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" <td>450</td>\n",
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" <td>100</td>\n",
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" <tr>\n",
" <th>243</th>\n",
" <td>Delibird</td>\n",
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" <td>330</td>\n",
" <td>45</td>\n",
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" <td>45</td>\n",
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" <tr>\n",
" <th>257</th>\n",
" <td>Smoochum</td>\n",
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" <td>305</td>\n",
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" <tr>\n",
" <th>395</th>\n",
" <td>Snorunt</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>300</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>396</th>\n",
" <td>Glalie</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>480</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>3</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>397</th>\n",
" <td>GlalieMega Glalie</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>100</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>398</th>\n",
" <td>Spheal</td>\n",
" <td>Ice</td>\n",
" <td>Water</td>\n",
" <td>290</td>\n",
" <td>70</td>\n",
" <td>40</td>\n",
" <td>50</td>\n",
" <td>55</td>\n",
" <td>50</td>\n",
" <td>25</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>399</th>\n",
" <td>Sealeo</td>\n",
" <td>Ice</td>\n",
" <td>Water</td>\n",
" <td>410</td>\n",
" <td>90</td>\n",
" <td>60</td>\n",
" <td>70</td>\n",
" <td>75</td>\n",
" <td>70</td>\n",
" <td>45</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>400</th>\n",
" <td>Walrein</td>\n",
" <td>Ice</td>\n",
" <td>Water</td>\n",
" <td>530</td>\n",
" <td>110</td>\n",
" <td>80</td>\n",
" <td>90</td>\n",
" <td>95</td>\n",
" <td>90</td>\n",
" <td>65</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>415</th>\n",
" <td>Regice</td>\n",
" <td>Ice</td>\n",
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" <td>580</td>\n",
" <td>80</td>\n",
" <td>50</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>200</td>\n",
" <td>50</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>522</th>\n",
" <td>Glaceon</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>525</td>\n",
" <td>65</td>\n",
" <td>60</td>\n",
" <td>110</td>\n",
" <td>130</td>\n",
" <td>95</td>\n",
" <td>65</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>524</th>\n",
" <td>Mamoswine</td>\n",
" <td>Ice</td>\n",
" <td>Ground</td>\n",
" <td>530</td>\n",
" <td>110</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>60</td>\n",
" <td>80</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>530</th>\n",
" <td>Froslass</td>\n",
" <td>Ice</td>\n",
" <td>Ghost</td>\n",
" <td>480</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>110</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>643</th>\n",
" <td>Vanillite</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>305</td>\n",
" <td>36</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>65</td>\n",
" <td>60</td>\n",
" <td>44</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>644</th>\n",
" <td>Vanillish</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>395</td>\n",
" <td>51</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>80</td>\n",
" <td>75</td>\n",
" <td>59</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>645</th>\n",
" <td>Vanilluxe</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>535</td>\n",
" <td>71</td>\n",
" <td>95</td>\n",
" <td>85</td>\n",
" <td>110</td>\n",
" <td>95</td>\n",
" <td>79</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>674</th>\n",
" <td>Cubchoo</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>305</td>\n",
" <td>55</td>\n",
" <td>70</td>\n",
" <td>40</td>\n",
" <td>60</td>\n",
" <td>40</td>\n",
" <td>40</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>675</th>\n",
" <td>Beartic</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>485</td>\n",
" <td>95</td>\n",
" <td>110</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>50</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>676</th>\n",
" <td>Cryogonal</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>485</td>\n",
" <td>70</td>\n",
" <td>50</td>\n",
" <td>30</td>\n",
" <td>95</td>\n",
" <td>135</td>\n",
" <td>105</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>788</th>\n",
" <td>Bergmite</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>304</td>\n",
" <td>55</td>\n",
" <td>69</td>\n",
" <td>85</td>\n",
" <td>32</td>\n",
" <td>35</td>\n",
" <td>28</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>789</th>\n",
" <td>Avalugg</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>514</td>\n",
" <td>95</td>\n",
" <td>117</td>\n",
" <td>184</td>\n",
" <td>44</td>\n",
" <td>46</td>\n",
" <td>28</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"133 Jynx Ice Psychic 455 65 50 35 \n",
"156 Articuno Ice Flying 580 90 85 100 \n",
"238 Swinub Ice Ground 250 50 50 40 \n",
"239 Piloswine Ice Ground 450 100 100 80 \n",
"243 Delibird Ice Flying 330 45 55 45 \n",
"257 Smoochum Ice Psychic 305 45 30 15 \n",
"395 Snorunt Ice NaN 300 50 50 50 \n",
"396 Glalie Ice NaN 480 80 80 80 \n",
"397 GlalieMega Glalie Ice NaN 580 80 120 80 \n",
"398 Spheal Ice Water 290 70 40 50 \n",
"399 Sealeo Ice Water 410 90 60 70 \n",
"400 Walrein Ice Water 530 110 80 90 \n",
"415 Regice Ice NaN 580 80 50 100 \n",
"522 Glaceon Ice NaN 525 65 60 110 \n",
"524 Mamoswine Ice Ground 530 110 130 80 \n",
"530 Froslass Ice Ghost 480 70 80 70 \n",
"643 Vanillite Ice NaN 305 36 50 50 \n",
"644 Vanillish Ice NaN 395 51 65 65 \n",
"645 Vanilluxe Ice NaN 535 71 95 85 \n",
"674 Cubchoo Ice NaN 305 55 70 40 \n",
"675 Beartic Ice NaN 485 95 110 80 \n",
"676 Cryogonal Ice NaN 485 70 50 30 \n",
"788 Bergmite Ice NaN 304 55 69 85 \n",
"789 Avalugg Ice NaN 514 95 117 184 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"133 115 95 95 1 False \n",
"156 95 125 85 1 True \n",
"238 30 30 50 2 False \n",
"239 60 60 50 2 False \n",
"243 65 45 75 2 False \n",
"257 85 65 65 2 False \n",
"395 50 50 50 3 False \n",
"396 80 80 80 3 False \n",
"397 120 80 100 3 False \n",
"398 55 50 25 3 False \n",
"399 75 70 45 3 False \n",
"400 95 90 65 3 False \n",
"415 100 200 50 3 True \n",
"522 130 95 65 4 False \n",
"524 70 60 80 4 False \n",
"530 80 70 110 4 False \n",
"643 65 60 44 5 False \n",
"644 80 75 59 5 False \n",
"645 110 95 79 5 False \n",
"674 60 40 40 5 False \n",
"675 70 80 50 5 False \n",
"676 95 135 105 5 False \n",
"788 32 35 28 6 False \n",
"789 44 46 28 6 False "
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ice = pokemon[pokemon.type == \"Ice\"]\n",
"ice"
]
},
{
"cell_type": "markdown",
"id": "0af5f534-0bec-4577-beee-29b350102265",
"metadata": {},
"source": [
"Let's get the high-speed ice pokémon. You can join conditions together using the `&` (and) and `|` (or) operators. `~` means \"not\", so `pokemon[~(pokemon.type == \"Ice\")]` would select all the non-ice pokémon. Due to order of operations, each condition needs to be wrapped in parentheses."
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "05d4c5c2-c6b4-4795-9799-c884b15445a1",
"metadata": {},
"outputs": [
{
"data": {
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>name</th>\n",
" <th>type</th>\n",
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" <th>total</th>\n",
" <th>hp</th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" <th>special_attack</th>\n",
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" <th>133</th>\n",
" <td>Jynx</td>\n",
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" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156</th>\n",
" <td>Articuno</td>\n",
" <td>Ice</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>85</td>\n",
" <td>100</td>\n",
" <td>95</td>\n",
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" <td>1</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>396</th>\n",
" <td>Glalie</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>480</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
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" <th>397</th>\n",
" <td>GlalieMega Glalie</td>\n",
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" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
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" <tr>\n",
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" <td>Ground</td>\n",
" <td>530</td>\n",
" <td>110</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>60</td>\n",
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" <td>Froslass</td>\n",
" <td>Ice</td>\n",
" <td>Ghost</td>\n",
" <td>480</td>\n",
" <td>70</td>\n",
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" <th>676</th>\n",
" <td>Cryogonal</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>485</td>\n",
" <td>70</td>\n",
" <td>50</td>\n",
" <td>30</td>\n",
" <td>95</td>\n",
" <td>135</td>\n",
" <td>105</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"133 Jynx Ice Psychic 455 65 50 35 \n",
"156 Articuno Ice Flying 580 90 85 100 \n",
"396 Glalie Ice NaN 480 80 80 80 \n",
"397 GlalieMega Glalie Ice NaN 580 80 120 80 \n",
"524 Mamoswine Ice Ground 530 110 130 80 \n",
"530 Froslass Ice Ghost 480 70 80 70 \n",
"676 Cryogonal Ice NaN 485 70 50 30 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"133 115 95 95 1 False \n",
"156 95 125 85 1 True \n",
"396 80 80 80 3 False \n",
"397 120 80 100 3 False \n",
"524 70 60 80 4 False \n",
"530 80 70 110 4 False \n",
"676 95 135 105 5 False "
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"high_speed_ice = pokemon[(pokemon.type == \"Ice\") & (pokemon.speed >= 80)]\n",
"high_speed_ice"
]
},
{
"cell_type": "markdown",
"id": "c84dc7ce-24f2-4ac7-92d7-99ed331488e0",
"metadata": {},
"source": [
"You could get the pokémon who are fire or ice by selecting `pokemon[(pokemon.type == \"Fire\") | (pokemon.type == \"Ice\")]`."
]
},
{
"cell_type": "markdown",
"id": "1f0e9625-b194-450d-b003-b88798cc2f45",
"metadata": {},
"source": [
"#### Your turn\n",
"\n",
"**1.3.0.** `no_doctor` indicates whether there was a time in the last year when the person needed to see a doctor, but could not afford to do so. Create a dataframe containing only these people. "
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "198cb0c6-3f43-43c2-9eee-3939c12ea537",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" <thead>\n",
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" <th></th>\n",
" <th>age</th>\n",
" <th>sex</th>\n",
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" <th>education</th>\n",
" <th>sexual_orientation</th>\n",
" <th>height</th>\n",
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" <th>sleep</th>\n",
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" <td>8</td>\n",
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" <th>259</th>\n",
" <td>65</td>\n",
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" <td>4</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.57</td>\n",
" <td>56.70</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
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" <td>35</td>\n",
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" <td>4</td>\n",
" <td>2</td>\n",
" <td>bisexual</td>\n",
" <td>1.63</td>\n",
" <td>58.97</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
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" <tr>\n",
" <th>166401</th>\n",
" <td>45</td>\n",
" <td>female</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>heterosexual</td>\n",
" <td>1.45</td>\n",
" <td>72.57</td>\n",
" <td>2</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166407</th>\n",
" <td>18</td>\n",
" <td>male</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.68</td>\n",
" <td>68.04</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>8</td>\n",
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" <tr>\n",
" <th>166416</th>\n",
" <td>65</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.50</td>\n",
" <td>55.34</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>6</td>\n",
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" <tr>\n",
" <th>166423</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.60</td>\n",
" <td>68.04</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>7288 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" age sex income education sexual_orientation height weight \\\n",
"0 55 female 5 2 other 1.55 83.01 \n",
"50 35 female 4 2 heterosexual 1.78 81.65 \n",
"146 65 female 5 4 heterosexual 1.55 72.57 \n",
"179 65 male 4 3 heterosexual 1.70 84.37 \n",
"259 65 female 4 4 heterosexual 1.57 56.70 \n",
"... ... ... ... ... ... ... ... \n",
"166387 35 female 4 2 bisexual 1.63 58.97 \n",
"166401 45 female 4 1 heterosexual 1.45 72.57 \n",
"166407 18 male 5 2 heterosexual 1.68 68.04 \n",
"166416 65 female 5 2 heterosexual 1.50 55.34 \n",
"166423 35 female 5 4 heterosexual 1.60 68.04 \n",
"\n",
" health no_doctor exercise sleep \n",
"0 2 True True 7 \n",
"50 4 True False 10 \n",
"146 5 True True 7 \n",
"179 3 True True 8 \n",
"259 3 True True 6 \n",
"... ... ... ... ... \n",
"166387 3 True True 6 \n",
"166401 2 True False 6 \n",
"166407 3 True True 8 \n",
"166416 3 True False 6 \n",
"166423 4 True True 6 \n",
"\n",
"[7288 rows x 11 columns]"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"no_doctor = people[(people.no_doctor) & (people.income <= 5)]\n",
"no_doctor"
]
},
{
"cell_type": "markdown",
"id": "9d213707-a15b-4751-8df9-48aa568af209",
"metadata": {},
"source": [
"**1.3.1.** `health` asks people for their general health, with the meanings of numbers shown below. Create a dataframe which contains people whose general health is good or better. \n",
"\n",
"| number | health status | \n",
"| ------ | ----------- |\n",
"| 1 | Poor |\n",
"| 2 | Fair |\n",
"| 3 | Good |\n",
"| 4 | Very good |\n",
"| 5 | Excellent |"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "8a8c1ad6-4c1e-4996-ab5e-5212dadb1851",
"metadata": {},
"outputs": [
{
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" <th>sex</th>\n",
" <th>income</th>\n",
" <th>education</th>\n",
" <th>sexual_orientation</th>\n",
" <th>height</th>\n",
" <th>weight</th>\n",
" <th>health</th>\n",
" <th>no_doctor</th>\n",
" <th>exercise</th>\n",
" <th>sleep</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>65</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>heterosexual</td>\n",
" <td>1.65</td>\n",
" <td>78.02</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.65</td>\n",
" <td>77.11</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>55</td>\n",
" <td>male</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.83</td>\n",
" <td>81.65</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>55</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.80</td>\n",
" <td>76.66</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>55</td>\n",
" <td>male</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.80</td>\n",
" <td>74.84</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166418</th>\n",
" <td>55</td>\n",
" <td>male</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.57</td>\n",
" <td>63.50</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166419</th>\n",
" <td>45</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.52</td>\n",
" <td>68.04</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166421</th>\n",
" <td>25</td>\n",
" <td>male</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.78</td>\n",
" <td>86.18</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166423</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.60</td>\n",
" <td>68.04</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166424</th>\n",
" <td>35</td>\n",
" <td>male</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.75</td>\n",
" <td>86.18</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>142249 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" age sex income education sexual_orientation height weight \\\n",
"1 65 female 8 1 heterosexual 1.65 78.02 \n",
"2 35 female 8 4 heterosexual 1.65 77.11 \n",
"3 55 male 8 4 heterosexual 1.83 81.65 \n",
"4 55 female 8 4 heterosexual 1.80 76.66 \n",
"5 55 male 8 4 heterosexual 1.80 74.84 \n",
"... ... ... ... ... ... ... ... \n",
"166418 55 male 7 2 heterosexual 1.57 63.50 \n",
"166419 45 female 8 2 heterosexual 1.52 68.04 \n",
"166421 25 male 7 2 heterosexual 1.78 86.18 \n",
"166423 35 female 5 4 heterosexual 1.60 68.04 \n",
"166424 35 male 7 2 heterosexual 1.75 86.18 \n",
"\n",
" health no_doctor exercise sleep \n",
"1 3 False False 8 \n",
"2 4 True True 7 \n",
"3 5 False True 8 \n",
"4 4 False True 8 \n",
"5 5 False True 7 \n",
"... ... ... ... ... \n",
"166418 3 False True 8 \n",
"166419 3 False True 7 \n",
"166421 4 False True 6 \n",
"166423 4 True True 6 \n",
"166424 3 False False 8 \n",
"\n",
"[142249 rows x 11 columns]"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people[people.health >= 3]\n"
]
},
{
"cell_type": "markdown",
"id": "7add542b-bfd2-481a-b5b4-4e1ca744078a",
"metadata": {},
"source": [
"**1.3.2.**. `education` indicates the highest level of education completed, with codes as follows. Create a dataframe which only contains female college graduates who needed a doctor but couldn't afford one. (The survey asked people for their current sex, and only had options for male and female.)\n",
"\n",
"| number | education level | \n",
"| ------ | ----------- |\n",
"| 1 | Did not graduate from high school |\n",
"| 2 | Graduated from high school |\n",
"| 3 | Attended some college |\n",
"| 4 | Graduated from college |"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "315682ae-7d54-4d78-9a63-d23c83ba1576",
"metadata": {},
"outputs": [
{
"data": {
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>age</th>\n",
" <th>sex</th>\n",
" <th>income</th>\n",
" <th>education</th>\n",
" <th>sexual_orientation</th>\n",
" <th>height</th>\n",
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" <td>heterosexual</td>\n",
" <td>1.55</td>\n",
" <td>58.97</td>\n",
" <td>4</td>\n",
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" <th>166368</th>\n",
" <td>55</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
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" <td>heterosexual</td>\n",
" <td>1.60</td>\n",
" <td>69.85</td>\n",
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" <td>False</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
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" <tr>\n",
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" <tr>\n",
" <th>166423</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.60</td>\n",
" <td>68.04</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5359 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" age sex income education sexual_orientation height weight \\\n",
"6 65 female 5 4 other 1.63 90.72 \n",
"23 65 female 4 4 heterosexual 1.68 84.82 \n",
"30 65 female 5 4 heterosexual 1.65 66.68 \n",
"65 65 female 5 4 heterosexual 1.70 64.41 \n",
"120 65 female 5 4 heterosexual 1.55 58.97 \n",
"... ... ... ... ... ... ... ... \n",
"166352 35 female 5 4 heterosexual 1.57 47.63 \n",
"166368 55 female 5 4 heterosexual 1.60 69.85 \n",
"166381 45 female 5 4 heterosexual 1.52 49.90 \n",
"166404 65 female 1 4 heterosexual 1.60 68.04 \n",
"166423 35 female 5 4 heterosexual 1.60 68.04 \n",
"\n",
" health no_doctor exercise sleep \n",
"6 3 False True 7 \n",
"23 3 False True 8 \n",
"30 3 False False 12 \n",
"65 3 False True 10 \n",
"120 4 False True 8 \n",
"... ... ... ... ... \n",
"166352 5 False False 8 \n",
"166368 3 False True 7 \n",
"166381 5 True True 6 \n",
"166404 3 False True 8 \n",
"166423 4 True True 6 \n",
"\n",
"[5359 rows x 11 columns]"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"education_female_low_income = people[(people.education == 4) & (people.sex == \"female\") & (people.income <= 5)]\n",
"education_female_low_income"
]
},
{
"cell_type": "markdown",
"id": "646d1148-7d94-4521-a04a-fbf17ade1235",
"metadata": {},
"source": [
"### 1.4. Grouping\n",
"\n",
"Now things get crazy. You can group a dataframe using one or more columns, and then compare their statistics. \n",
"\n",
"#### Demo\n",
"\n",
"Do different types of pokémon move at different speeds? We'll use `sort_values` to put these in order from slow to fast."
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "069ea0ab-eff6-4985-9f46-db956fe1df91",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"type\n",
"Fairy 48.588235\n",
"Steel 55.259259\n",
"Rock 55.909091\n",
"Bug 61.681159\n",
"Grass 61.928571\n",
"Ice 63.458333\n",
"Poison 63.571429\n",
"Ground 63.906250\n",
"Ghost 64.343750\n",
"Water 65.964286\n",
"Fighting 66.074074\n",
"Normal 71.551020\n",
"Fire 74.442308\n",
"Dark 76.161290\n",
"Psychic 81.491228\n",
"Dragon 83.031250\n",
"Electric 84.500000\n",
"Flying 102.500000\n",
"Name: speed, dtype: float64"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.groupby(\"type\").speed.mean().sort_values()"
]
},
{
"cell_type": "markdown",
"id": "bdc801b7-d3ae-45bb-80f4-ebeb474e20a1",
"metadata": {},
"source": [
"Do types differ in other stats? Let's sort by hit points. "
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "5c420c0e-b5d2-49ae-ab98-3305ee076169",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" 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>hp</th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" </tr>\n",
" <tr>\n",
" <th>type</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" </thead>\n",
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" <tr>\n",
" <th>Bug</th>\n",
" <td>56.884058</td>\n",
" <td>70.971014</td>\n",
" <td>70.724638</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <td>59.795455</td>\n",
" <td>69.090909</td>\n",
" <td>66.295455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <td>64.437500</td>\n",
" <td>73.781250</td>\n",
" <td>81.187500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <td>65.222222</td>\n",
" <td>92.703704</td>\n",
" <td>126.370370</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <td>65.363636</td>\n",
" <td>92.863636</td>\n",
" <td>100.795455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <td>66.806452</td>\n",
" <td>88.387097</td>\n",
" <td>70.225806</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <td>67.250000</td>\n",
" <td>74.678571</td>\n",
" <td>68.821429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <td>67.271429</td>\n",
" <td>73.214286</td>\n",
" <td>70.800000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <td>69.851852</td>\n",
" <td>96.777778</td>\n",
" <td>65.925926</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <td>69.903846</td>\n",
" <td>84.769231</td>\n",
" <td>67.769231</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <td>70.631579</td>\n",
" <td>71.456140</td>\n",
" <td>67.684211</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Flying</th>\n",
" <td>70.750000</td>\n",
" <td>78.750000</td>\n",
" <td>66.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <td>72.000000</td>\n",
" <td>72.750000</td>\n",
" <td>71.416667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <td>72.062500</td>\n",
" <td>74.151786</td>\n",
" <td>72.946429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <td>73.781250</td>\n",
" <td>95.750000</td>\n",
" <td>84.843750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <td>74.117647</td>\n",
" <td>61.529412</td>\n",
" <td>65.705882</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <td>77.275510</td>\n",
" <td>73.469388</td>\n",
" <td>59.846939</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <td>83.312500</td>\n",
" <td>112.125000</td>\n",
" <td>86.375000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" hp attack defense\n",
"type \n",
"Bug 56.884058 70.971014 70.724638\n",
"Electric 59.795455 69.090909 66.295455\n",
"Ghost 64.437500 73.781250 81.187500\n",
"Steel 65.222222 92.703704 126.370370\n",
"Rock 65.363636 92.863636 100.795455\n",
"Dark 66.806452 88.387097 70.225806\n",
"Poison 67.250000 74.678571 68.821429\n",
"Grass 67.271429 73.214286 70.800000\n",
"Fighting 69.851852 96.777778 65.925926\n",
"Fire 69.903846 84.769231 67.769231\n",
"Psychic 70.631579 71.456140 67.684211\n",
"Flying 70.750000 78.750000 66.250000\n",
"Ice 72.000000 72.750000 71.416667\n",
"Water 72.062500 74.151786 72.946429\n",
"Ground 73.781250 95.750000 84.843750\n",
"Fairy 74.117647 61.529412 65.705882\n",
"Normal 77.275510 73.469388 59.846939\n",
"Dragon 83.312500 112.125000 86.375000"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ptypes = pokemon.groupby(\"type\")\n",
"ptypes[[\"hp\", \"attack\", \"defense\"]].mean().sort_values(\"hp\")"
]
},
{
"cell_type": "markdown",
"id": "cc9a3d19-0ecd-487b-b34f-b748c44fc9c9",
"metadata": {},
"source": [
"Which type/subtype combinations are most likely to have legendary pokémon?"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "444a580d-e70c-48a1-bf87-77f98b8c9f85",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"type subtype \n",
"Electric Flying 0.600000\n",
"Rock Fairy 0.666667\n",
"Ghost Dragon 1.000000\n",
"Ground Fire 1.000000\n",
"Fire Water 1.000000\n",
" Steel 1.000000\n",
"Steel Dragon 1.000000\n",
"Dragon Electric 1.000000\n",
"Psychic Ghost 1.000000\n",
"Dragon Psychic 1.000000\n",
" Ice 1.000000\n",
"Rock Fighting 1.000000\n",
"Steel Fighting 1.000000\n",
"Dragon Fire 1.000000\n",
"Psychic Dark 1.000000\n",
" Fire 1.000000\n",
"Name: legendary, dtype: float64"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"legendary_percentages = pokemon.groupby([\"type\", \"subtype\"]).legendary.mean().sort_values() \n",
"legendary_percentages[legendary_percentages > 0.5]"
]
},
{
"cell_type": "markdown",
"id": "de23775b-8670-4371-913d-d8fa1d1f3a76",
"metadata": {},
"source": [
"#### Your turn\n",
"\n",
"**1.4.0.** `income` records peoples' annual income, in the following bands. `sleep` records the average hours of sleep someone gets per night. Is there a difference in the average hours of sleep by income level?\n",
"\n",
"| number | annual income, in $1000 | \n",
"| ------ | ----------- |\n",
"| 1 | Less than 10 |\n",
"| 2 | 10-15 |\n",
"| 3 | 15-20 |\n",
"| 4 | 20-25 |\n",
"| 5 | 25-35 |\n",
"| 6 | 35-50 |\n",
"| 7 | 50-75 |\n",
"| 8 | More than 75 |"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "75c1ac4f-3914-4c0a-a156-2e084002df66",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"income\n",
"1 6.952208\n",
"2 6.985627\n",
"6 7.055784\n",
"8 7.074626\n",
"7 7.078495\n",
"4 7.079627\n",
"3 7.083274\n",
"5 7.100286\n",
"Name: sleep, dtype: float64"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people.groupby(\"income\").sleep.mean().sort_values()"
]
},
{
"cell_type": "markdown",
"id": "f6413f2b-26a0-4b70-976f-90e45558c4bb",
"metadata": {},
"source": [
"**1.4.0.** Is there a difference in peoples' income or general health, by sex and education level? "
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "d46df8a1-bbc2-45a4-9be1-cee1858cbf21",
"metadata": {},
"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></th>\n",
" <th>income</th>\n",
" <th>health</th>\n",
" </tr>\n",
" <tr>\n",
" <th>sex</th>\n",
" <th>education</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"4\" valign=\"top\">female</th>\n",
" <th>1</th>\n",
" <td>3.554701</td>\n",
" <td>2.848040</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5.049022</td>\n",
" <td>3.315797</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>5.779390</td>\n",
" <td>3.483379</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>6.960652</td>\n",
" <td>3.844340</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"4\" valign=\"top\">male</th>\n",
" <th>1</th>\n",
" <td>4.433009</td>\n",
" <td>3.031525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5.742876</td>\n",
" <td>3.440818</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>6.270230</td>\n",
" <td>3.549105</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>7.190582</td>\n",
" <td>3.826512</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" income health\n",
"sex education \n",
"female 1 3.554701 2.848040\n",
" 2 5.049022 3.315797\n",
" 3 5.779390 3.483379\n",
" 4 6.960652 3.844340\n",
"male 1 4.433009 3.031525\n",
" 2 5.742876 3.440818\n",
" 3 6.270230 3.549105\n",
" 4 7.190582 3.826512"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ed_sex = people.groupby([\"sex\", \"education\"])\n",
"ed_sex[[\"income\", \"health\"]].mean()"
]
},
{
"cell_type": "markdown",
"id": "931d602b-ddf4-4c8b-80e0-f886267cce76",
"metadata": {},
"source": [
"### 1.5. Plotting \n",
"\n",
"Pandas has excellent built-in plotting capabilities, but \n",
"we are going to use the [seaborn](https://seaborn.pydata.org/) library because it's a bit \n",
"more intuitive and produces more beautiful plots. `set_theme`, called here without any arguments, assigns the default color palette. "
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "b1e06e4f-6b9e-42af-a27c-dbb525a259ce",
"metadata": {},
"outputs": [],
"source": [
"import seaborn as sns\n",
"sns.set_theme()"
]
},
{
"cell_type": "markdown",
"id": "a15ad672-13e8-4bdd-bc31-a489a1730daf",
"metadata": {},
"source": [
"#### Demo\n",
"\n",
"**When you want to visualize the distribution of a series**, a [histogram](https://seaborn.pydata.org/generated/seaborn.histplot.html) puts data into bins and plots the number of data points in each bin.\n",
"\n",
"Let's see the distribution of pokémon attack values. Note how assigning `x=\"attack\"` spreads attack values over the x-axis, while `y=\"attack\"` spreads attack values over the y-axis. The number of bins is selected automatically, but you can specify this with the optional `bins` argument. "
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "5ce066fe-f81d-4b78-a394-c5c2f4dc9f46",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='attack', ylabel='Count'>"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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AAKifYDN06FBzJpQGnGMNFC4qKqpN0QAAAPUbbCZOnMiZTwAAIO3UKthccskl7tcEAAAgFcFm1apV1T6nV69etSkaAACgfoPNiBEjzKEoneU7ovKhKcbYAAAATwSbuXPnHrWsvLxcVq9eLQsXLpTp06e7UTcAAIDkB5vevXtXubxfv37mFPAZM2bIzJkza1M0AABA/V6g73h69uwpK1eudLtYAACA+g82b731ljRq1MjtYgEAAJJzKOrKK688aplesK+4uFg2b94s11xzTW2KBQAAqP9gE3s2VITf75f27dvLmDFj5NJLL61brQAAAOor2Dz77LO1+TMAAID0CzYRy5YtMwOFy8rKpKCgQHr06CFnn322e7UDAABIdrA5ePCg3HDDDfLee+9JIBCQ/Px8KS0tNad49+nTx9w3aNCgNkUDAADU71lRegG+Dz/8UB566CH5+9//bgLOmjVr5Le//a188skn5jo2AAAAngg2r7/+uvzyl7+UH//4x6bHRgWDQbn44ovN8kWLFrldTwAAgOQEm507d8qpp55a5WO6fOvWrbUpFgAAoP6DzUknnWQORR1r5u/WrVvXrVYAAAD1NXj4P//zP+WBBx6QnJwcufDCC6V58+ayfft2c4jq97//vTkcBQAA4IlgM3ToUFm7dq1MmTJFHnnkkbgL9w0ZMkSuvfZaN+sIAACQ3NO9J02aJKNGjTLXsdm9e7f4fD7p37+/tGvXrjZFAgAA1O8Ym/Xr15vpEubMmWN+1xCjvTfDhg2Txx57TG699VbZuHFj3WsFAACQzGDz9ddfm8kvdSxN27Zt4x7LysqS8ePHy65du0zI4awoAACQ1sFm1qxZ0qxZM3n11Vdl4MCBcY81bNhQrrrqKnn55ZclOzvbXHkYAAAgbYPN+++/L6NHjzZzQh1LixYtzLib5cuXu1U/AAAA94NNSUmJtGnTptrntW/fXoqLixOvAQAAQH0HG+2p0XBTHZ0Ms2nTpnWtFwAAQPKCTa9eveSVV16p9nmvvfbaMadbAAAcze/3STDod/UWCBzeveulOIBMkvB1bEaMGGFO7dYrDt9yyy1mkHDla9tMmzZNli1bZgYaAwASCzXN8nMl4K/VDDfVapKXI7tKyyUcdpJSPuDZYNO5c2eZMGGCTJ48WRYuXCh9+/aVE088UUKhkHzzzTfywQcfmMNQY8eOlbPPPju5tQYAi4KNhpr5i4ukZGe5a+VqT02r5o3l8vPbm/9BsEGmqNGVh4cPHy4dO3aUp556Sv7617/KgQMHzPJGjRrJWWedZc6I6tq1a7LqCgDW0lCzedseV4NN5HAUkElqPKVCjx49zE3t3LlTgsGg5OXlJaNuAAAAyZ8rKuJ417QBAACob/RTAgAAaxBsAACANQg2AADAGgQbAABgDYINAACwRloFm40bN0r37t3jpm4oKiqSK664Qrp16ybnnXeezJ07N6V1BAAAlp7u7aZDhw7JuHHjpLz8/6+8qVcyHjlypAk09913n3zyySfmXi8IeOmll6a0vqieXu1Ub27jomMAgLQPNtOnT5fGjRvHLXvxxRclKytL7r//fnMhwHbt2smmTZvMXFQEm8ye/wYAgLQNNqtWrZIXXnjBzAzer1+/6PLVq1dL7969TaiJ6NOnj8ycOVO2b98uzZs3T1GNkar5b1SHNgUy6My2zFoMAEi/YFNWVibjx4+XX//619K6deu4x4qLi6V9+/ZxywoLC839li1b6hRsgkF/Qoc7Mumwh5ttjpSxrXSffLN9r7ipsCD38A++w/Ph1Enkz2PLcqPcyv8mSWXXqtzYNkd/cansRP59Kl7nBNtcXbnJ2B9EytT/4errEVNUpuzH2G8jLYLNvffeawYMDx48+KjH9u/fLw0aNIhblp2dbe4jE3DWtjchP79RQs/Ny2somcbNNuvGFgwGXCvPlHnk8Jbeu1V2MBBISrkRySq7LuVqm5NVdirKTaTs6tp8zHKPfGgkc3+QjG0lU/djmdbeTG1zWgYbPfSkh5sWLVpU5eM5OTly8ODBuGWRQJObe+Rbey2Ew46UlZVXu5PRN0pZ2T4JhcKSCdxsc6QsLaeiIiRuCoXD0fs6l+07/GFXEQq5W24lySq7VuXGtFkcl8tOQEpe5wTbfMxyj2wPydgfJG1biemxyZT9GPttu9us7UykZyqlweaPf/yj7NixI25cjbrnnnvkT3/6k7Rq1UpKSkriHov83rJlyzr974qKxN4Ah3c2dr9Zktlmx3HMzU3R8pyYn2speljCcbfcypJVdm3KrbLNLpWdiFS8zom2ubpyk7k/cHtbiT3klmn7sUxrb6a2OS2DzZQpU8zhplgDBgyQm266SX784x/LwoUL5fnnn5dQKCSBI13IK1askLZt28oJJ5yQoloDAIB0ldLRRtrrcvLJJ8fdlIYWfUxP6d6zZ4/cddddsmHDBnPhvmeeeUbGjBmTymoDAIA0ldbDqDXgzJ4921yReMiQIfL444+bM6j0ZwAAgLQ7K6qy9evXx/3epUsXc40bAAAAT/fYAAAA1ATBBgAAWINgAwAArEGwAQAA1iDYAAAAaxBsAACANQg2AADAGgQbAABgDYINAACwBsEGAABYg2ADAACsQbABAADWINgAAABrEGwAAIA1CDYAAMAaBBsAAGANgg0AALAGwQYAAFiDYAMAAKwRTHUFAMArAgG/J8oEMhnBBgCq0SQ3S8JhR/LyGqa6KgCqQbABgGrkZAfF7/fJgiXrZOuOva6W3aFNgQw6s634fD5XywUyFcEGABJUsrNcNm/b42qZLfLpBQLcxMFdAABgDYINAACwBsEGAABYg2ADAACsQbABAADWINgAAABrEGwAAIA1uI4NzIXH9Ba5tLsbl3jnMvEAgFQg2GQ4DTTN8nMl4P//IMJl4wEAXkWwyXCmp8bvl/mLi2Rb6T7T0xIKhcVxnDqVy2XiAQCpQLBB9FLx32zfK8FgQCoqQnUONlwmHgCQCgyEAAAA1iDYAAAAaxBsAACANQg2AADAGgQbAABgDYINAACwBsEGAABYg2ADAACsQbABAADWINgAAABrEGwAAIA1CDYAAMAaBBsAAGANgg0AALAGwQYAAFiDYAMAAKxBsAEAANYg2AAAAGsQbAAAgDUINgAAwBoEGwAAYA2CDQAAsAbBBgAAWINgAwAArEGwAQAA1iDYAAAAaxBsAACANQg2AADAGgQbAABgjZQHm127dsndd98t55xzjpx++ukydOhQWb16dfTx999/Xy655BLp2rWrDBw4UN54442U1hcAAKSvYKorcOutt8q2bdtk6tSpcsIJJ8izzz4rV199tbz66qviOI6MGTNGRo4cKQ8//LC88847Mn78eCkoKJC+ffumuuoA4AmBgPvfYcNhx9yAdJPSYLNp0yZZvny5zJ8/X3r06GGW/eY3v5G//e1vsmjRItmxY4d06NBBbrnlFvNYu3btZO3atTJ79myCDQBUo3FulgkfeXkNXS87FA7LrtJywg3STkqDTX5+vsyaNUs6d+4cXebz+cytrKzMHJLq379/3N/06dNHJk2aZHpz9HkAgKo1bBAUv98nC5ask6079rpWbmFBrgwb2MmUTbBBuklpsMnLy5Mf/vCHccuWLFlienLuvPNOcziqVatWcY8XFhbKvn37pLS01BySqq1g0J9Q120yunDTSaR9JiRGcqL5sW6hMRo6tSyXA6irZce22St1rmu5Ca7ntKpzXcuu43vbi++N2GaWlJbLN9vdCzaReqbb/jFT9tuZ3ua0H2MT66OPPpIJEybIgAEDpF+/frJ//35p0KBB3HMivx88eLDW/0e/ZeTnN0roucnowk1HulEEAwHzc+S+TuX5j2xsfr8Eg3UvL9lla5u9Vue6llvdek7HOte17Nq+t7343qj8P1xdh0c+RNN1/5iu9UqmTGxz2gebpUuXyrhx48yZUVOmTDHLsrOzjwowkd8bNqz9StSu07Ky8mo3XH2jlJXtk1AoLLaKtFPbWBEKmR2/3otT9+PvkfuKipA7lU1G2T6Jttkzda5ruTFtPt56Tqs617XsBNtc43JdkLSyY3psXF+HR/aJ6bZ/zJT9dqa2OS+vYUI9U2kRbObNm2fGzejp3A8++GC0V6Z169ZSUlIS91z9PTc3V5o0aVKn/1lRkdgbwHzgJ/hcL9MxS9EdvnPk97qW51JZySw7eljC8U6d61pulW12qexEpOJ1TrTNNS3XDckqO+6QW5LWYbruH9O1XsmUiW0+lpQflNMzoiZOnCjDhw83p3zHHnrq2bOnrFy5Mu75K1asML06/iPdtwAAAGnRY7Nx40aZPHmynH/++eZ6Ndu3b48+lpOTIyNGjJAhQ4aYQ1N6/+6778rixYvN6d4AAABpFWz0DKhDhw7Jm2++aW6xNMg88MAD8uSTT5qL8/3hD3+QE0880fzMNWwAAEDaBZvrrrvO3I5Hp1rQGwAAQHUYqAIAAKxBsAEAANYg2AAAAGsQbAAAgDUINgAAwBoEGwAAYA2CDQAAsEZazBUFAECE3+8zt5qKTJB4rIkSdQJkvcFuBBsAQNrQQNMsP1cCdZgPUGeBrorOcr6rtJxwYzmCDQAgrYKNhpr5i4ukZGd5jf7W5/OZ3hqd6brybOaFBbkybGAnUz7Bxm4EGwBA2tFQs3nbnhoHm2AwIBUVoaOCDTIHg4cBAIA1CDYAAMAaBBsAAGANgg0AALAGwQYAAFiDYAMAAKxBsAEAANYg2AAAAGtwgT4AQK0ca06mdCsTmYVgAwCokSa5WWZagmPNyQSkEsEGAFAjOdlBM+fSgiXrZOuOva6W3aFNgQw6s62ZHgGoDYINAKDe5nOqTot8eoFQNxzMBAAA1iDYAAAAaxBsAACANRhj4xE6UE9vbuPUSgCATQg2HqCBpll+rgT8hBAAAI6HYOORYKOhZv7iInMWgps4tRIAYBOCjYdwaiUAAMfHsQ0AAGANgg0AALAGwQYAAFiDYAMAAKxBsAEAANYg2AAAAGsQbAAAgDUINgAAwBoEGwAAYA2CDQAAsAbBBgAAWIO5ogAAGSMQSM73+XDYMTekHsEGAGC9JrlZJnjk5SVn4t9QOCy7SssJN2mAYAMAsF5OdlD8fp8sWLJOtu7Y62rZhQW5MmxgJ1M+wSb1CDYAgIxRsrNcNm/bk+pqIIkINgAApOn4Hcbu1BzBBgCANB2/w9idmiPYAACQhuN3GLtTOwQbAABcwPid9ECwcZGmar155boLAADYhmDjEg00zfJzJeAnhAAAkCoEGxeDjYaa+YuLTHekmzq0KZBBZ7YVn8/93iAAAGxCsPHAMdYW+cm5UiYAALbhuAkAALAGwQYAAFiDYAMAAKzBGBsAANLY8S75EXmsNpcFCVs6XQPBBgAAj0/VUJvpHEKWTtdAsAEAwKNTNehlQLS3JhQKi+MkHlBsnq6BYAMAgEcvI6LBJhgMSEVFqEbBxmYEGwAAMlQgCVP2pHrsDsEGAIAM06QG43e8NnaHYAMAQIbJSWD8Tm2kw9gdTwSbcDgsjz/+uLz00kvy7bffSq9eveTuu++Wf/u3f0t11QAA8KySJEwDlGqeuEDfk08+KfPnz5eJEyfK888/b4LO6NGj5eDBg6muGgAASCNpH2w0vDz99NNy0003Sb9+/aRjx47y6KOPSnFxsfzlL39JdfUAAEAaSftgs27dOtm7d6/07ds3uiwvL09OPfVUWbVqVUrrBgAA0ovPSfMT37VX5sYbb5Q1a9ZITk5OdPnYsWNl//79MnPmzBqXqU2ublCTzyfi9/vNYa9EXqHI8/eUH5SQywOmsoJ+yc3J8lTZ1Ll+yqbO9VO2F+uczLKpc/2U7cU6B/w+aZzbIOHPzprQAcl63R7PDx7et2+fuW/QoEHc8uzsbNm9e3etyjx8pcbqXxylYaUmdIUmixfLps71UzZ1rp+yvVjnZJZNneunbC/W2V/Dz05X/7ekuUgvTeWBwgcOHJCGDd0//x4AAHhX2geb1q1bm/uSkpK45fp7y5YtU1QrAACQjtI+2OhZUI0bN5YPPvgguqysrEzWrl1rrmcDAADgmTE2OrbmiiuukClTpkhBQYF897vflYcfflhatWolAwYMSHX1AABAGkn7YKP0GjYVFRXy61//2pwJpT01Tz31lGRlZaW6agAAII2k/eneAAAA1oyxAQAASBTBBgAAWINgAwAArEGwAQAA1iDYAAAAaxBsAACANQg2AADAGgSbKuh06//1X/8lZ599tnTr1k2uueYa+de//iW22LVrl9x9991yzjnnyOmnny5Dhw6V1atXRx8fOXKkdOjQIe42YsQI8bKtW7ce1Sa9vfLKK+bxoqIic4VrXd/nnXeezJ07V7xMpyCpqr16+9GPfmSeM2PGjCof96qZM2ce9T6tbr16fVuvqs1vvfWWXHrppdK9e3fT5gcffNBc2DTiww8/rHK9x05b47U268VbK7dH227retafj7V9v/baa+Y5oVBIunTpctTj06dPF+vpBfoQb/r06c4ZZ5zhvP32205RUZEzatQoZ8CAAc6BAwccG4wcOdK56KKLnFWrVjlffPGFc9999zldunRxPv/8c/N43759nfnz5zslJSXRW2lpqeNl77zzjtO5c2dn69atce3at2+fs3PnTrO+J0yY4GzYsMF5+eWXzXP13qv0vRrbTr395S9/cTp06BBt19ixY51f/epXRz3Pi+bNm+d07NjRueKKK6LLElmvXt7Wq2qzbtOdOnVyZsyY4WzcuNG878855xznjjvuiD7nueeec/r373/Uevdqm9Vll13mTJ06Na49O3bssHY96/44tq26Xxs2bJhz4YUXOnv27DHP0fd8+/btTXtjnxt53GYEm0r0jd69e3ez8Ufs3r3bfPAvWrTI8bovv/zSvNlXr14dXRYOh82Obtq0ac727dvN459++qljk1mzZjmDBw+u8rHf/e53zllnneUcOnQouuyRRx4xOz5b7N271zn33HPjPuAGDRrkzJkzx/Gy4uJiZ8yYMU63bt2cgQMHxu38q1uvXt3Wj9fm2267zbnqqqvinv/qq686p512WvRD/J577nGuu+46x0uO12bdf+lyDe5VsXE9V/bss8863//+96NfTtUbb7zhnH766U4m4lBUJevWrZO9e/dK3759o8vy8vLk1FNPlVWrVonX5efny6xZs6Rz587RZT6fz9x01vT169ebn9u2bSs20Xa1a9euysf0MFzv3r0lGPz/qdP69OkjX375pWzfvl1s8Lvf/U727dsnt99+u/n94MGDpn3//u//Ll726aefmjnj/vu//1u6du1ao/Xq1W39eG0eNWpUdB1H+P1+OXTokOzZs6fabcGLbf7qq6+kvLz8mO9lG9dzrJ07d8q0adPk+uuvj3sN1ntwPWfUJJj1qbi42Ny3bt06bnlhYWH0MS/TDfqHP/xh3LIlS5bIpk2b5M4775TPPvtMmjRpIvfff78sX75ccnNzZeDAgXLDDTeYmda9StuloW748OGyceNGOfnkk82OQMcZ6Xpt3779UetbbdmyRZo3by5epju+Z555Rm677TZp1qyZWbZhwwZzDF7X/aRJk+TAgQNmctlf/epX0bZ7gY6jiB1LEau69erVbf14bdYP61gaaHTdf//735eCggKz7J///KfZFi655BIz9kxfo1tuucWMx/Bim3XbVs8++6wsW7bMBDndrrVNui+zcT3H+v3vfy85OTly9dVXH/W6VFRUmOUa7lq2bCk///nP5Sc/+YnYjh6bSvRbrar8IZ6dnW12/rb56KOPZMKECTJgwADp16+f2Ri0nbqTmz17tvnwf+mll8zgPK/SjfuLL76Q3bt3y4033mh6rHQA4bXXXivvv/++GVhZ1fpWNqzz+fPnmx385ZdfftSHQcOGDeWxxx4z4UZfoyuvvDJuoKmXVbdebd/W9X0/fvx4E2TuueeeaKD79ttvTQ+HbtNPPvmkCe46wFrDrhfpe1nDjAYV7Zm844475L333jNfxnTQsM3rWXvhXnzxRRNeIu/tCF3veqKIDjR+6qmn5D/+4z/Mvv7ll18W29FjU4km30hXfeRnpRuAfgjYZOnSpTJu3DhzZtSUKVPMMu2p0a7spk2bmt/125x2h+q3H91JerH3Qg9F6BkfgUAguk71G6xu+LrB6zJd37EiOzztsfI6PUvi4osvjns/6+/6rTbyLV5973vfM8v0rJoLLrhAvK669Wrztq4feDfffLOsXLlSHn/88WhvjPZa6OEXbZ9u10oPS69du9b0eNx3333iNfrla9iwYaYXKrLPatGihfzsZz+T//3f/7V6Pes+XNulZ8FV9vrrr5te2UaNGpnfO3bsKN98843Z51122WViM3psKol0V5aUlMQt19+1K88W8+bNM70X5557rvmWE0n7GgIioSb2A0+lc7dtdXTjjt2pRdqlXfGtWrWqcn0rr69z7YLW01oHDx581GOxoUbpN149VOXl9RyruvVq67au9ddDrp988on5EKt86FkPR0dCjdLeDh2LoduCF2n9I6Gmqn2Wres5Emx0/eo6rSwnJycaaiI09NmyfR8PwaYSTbWNGzeOu6aDDqrVbzQ6BsEGemhi4sSJZuc3derUuC5a7bbU7spY+q1Hd4Rt2rQRL9KeGe2Vqnydjn/84x9yyimnmPWq1/bQbzcRK1asMAOoTzjhBPEyHUCrbdD3daxHH33UdE3rmZERX3/9tZSWlprXxAbVrVcbt3U93KrjKHRc1XPPPXdUO3QMil7fJvYaLnrISgOwV9e79iRfddVVR+2zlLbJxvUcu33HDoqObV/v3r2j1+mKfV0ioc9mBJtK9ENejzfroZm//vWvZoPXwzD67U/HoXidDpydPHmynH/++TJmzBhzdsi2bdvMTY+964fdwoULZcGCBWbn96c//UkeeughcwxXdw5epN9G9WwBPcymO4LPP/9cfvvb35pvtNqNrd242nV/1113mXEGujPQAZf6+nid7ryruuierv/NmzfLvffea94TenhCe/A0AOpFzGxQ3Xq1cVvX97Vutw8//LDpkYts23rTgKfrV3s39HCzBns9c0Z/1rEYlcOBV+g+S8fK6SE3PUPq3XffNSdCXHTRRWbbt3E9R8ZL6ReRyl9alPbg6BmA+gVGXw89E1DHFuoZVrqd244xNlW46aabzLcYHVynAxA11WuXbmz3rVfpWTB6psSbb75pbrGGDBkiDzzwgDndW4+3awDSY9W6w9OBtl6lXdV6uO2RRx4x4w7024yePTJnzpzoWTM6UFoH0OproG3Wb4H6s9fpB1rkTKhYOsZIz6bQgcN6dozu/PWKxPohp+vfBtorU916tWlb1+CiX0R0+9Zem8r0Q/3EE0804U4/5PXLio4z6dGjhzk07cXxc0rft3q6s35w63taB8rroVfd1m1cz7Hbtqpq+1a6/9arDOvA8R07dpiQF7n6su18ejGbVFcCAADADRyKAgAA1iDYAAAAaxBsAACANQg2AADAGgQbAABgDYINAACwBsEGQFqr6ooUXKUCwLEQbACk9XQYQ4cOjVums80/+OCDrv+v8847z8wMDcDbCDYA0tbixYvl448/jls2Y8YMMwUAAFSFYAMAAKxBsAGQMjpvj87hpZMR6vxVOknjyJEjpaioyMxzoxMbKp3IU3/Xw0U6eeerr75qlumM5Eon8dS5j3QOIC1Hn6fPD4fD0f+lE2LqrPY6V063bt3MJJnvvPPOMev28ssvmwkGn3jiiXp4JQC4hUkwAaSMTkqpM67feuutctJJJ8mmTZvMxJy33XabmaSwuLjYBIwXXnjBzMasEx7qhKw6iekNN9wghYWFZrZmnah14MCBZjZjHVi8aNEiE4p0VvcLL7zQTBA5atQoM8uxToioyzUc/eIXv5A//OEP0rNnz7h66WSSv/nNb8z/0OcA8A6CDYCUOHjwoOzdu9fMuHzBBReYZb179zY9KzrLfDAYNGFGaQ+L0t91JvKCgoLoMg02Z555pjz88MNmJnf1gx/8QN566y354IMPTLBZtmyZrFmzxvS+9O/f3zynT58+8q9//UtWrFgRF2zefvttE7g0QGkIAuAtBBsAKaEBRXtl1NatW2Xjxo2mR0WDRST4JOLiiy82twMHDpgytNdHD2VpL82hQ4fMcz788EPJysoyh6giNAQ9//zzcWV9+umnprdGe4LGjh3rYmsB1BeCDYCU+dvf/iaTJ0+WL774Qho1amTGtOTm5tboWjU6TkfHzixcuFAqKirkxBNPlO7du5sen0gZehZVs2bNoj06x/LZZ59Jv379zNib5557TkaMGOFCKwHUJwYPA0iJr776yoxf6dSpk7z55pumV2X+/Ply7rnn1qicSZMmyZIlS2TatGny0UcfydKlS81hKQ02EU2aNDHhpnJYWrt2remlidCBxTNnzjSHxqZOnSpbtmxxoaUA6hPBBkBK/OMf/zCHj3Qsiw4c9vl80V4cpSGkqh6Wyss0EJ1xxhlm7Eykt0fL3rlzZ/SsKB1Do4eldKxNhJY/YcIEE2Qimjdvbu51eSAQkHvvvTcpbQeQPAQbAClx2mmnmV4V7V1Zvny5GVtz4403Rk/BLi8vl7y8PPPz66+/bgb6Kl2mPS0rV640h6G6dOki7733nixYsMAsmzt3rlxzzTUmKO3bt8/8jR5e0sNTemVhPcPqf/7nf8zPn3/+uYwePfqouukYm1tuucXURf83AO/wOUy6AiCFVxbW07L1sFTTpk3NmU5XXnmlGduip1trL4wertIzny677DLTg6JBQ8flfPvttzJnzhw55ZRTzBgbDTc64FjH2Pz0pz+VDRs2mDOj3n33XdP7os+fMmWKOeylgUevg6OnmeuZWEoHFuvPekaW0t6eyy+/3FwrRwcU5+fnp/jVApAIgg0AALAGh6IAAIA1CDYAAMAaBBsAAGANgg0AALAGwQYAAFiDYAMAAKxBsAEAANYg2AAAAGsQbAAAgDUINgAAwBoEGwAAYA2CDQAAEFv8Hw3bARsCmCz+AAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.histplot(data=pokemon, x=\"attack\")"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "bceb253b-ef4f-4aa2-aef4-cab2b3ca6d59",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='Count', ylabel='attack'>"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.histplot(data=pokemon, y=\"attack\", bins=5)"
]
},
{
"cell_type": "markdown",
"id": "2aac9186-86c0-41db-a1c4-8719bb78b46b",
"metadata": {},
"source": [
"**When you want to compare the distribution of a numeric variable across categories**, a [barplot](https://seaborn.pydata.org/generated/seaborn.barplot.html) is a good choice. Choose one numeric column and one categorical column. \n",
"\n",
"Let's see pokémon hit points by legendary/non-legendary. `errorbar=\"sd\"` shows the standard deviation for each category. "
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "92be1ad0-12bb-49f0-a3f6-85fcfd98e943",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='legendary', ylabel='hp'>"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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Gct9998mHH37o3nbs2DHp27ev3HzzzXL77bfL1KlTJS8vr9jbAAAALK38TJgwQapWrSrJyclSpUoV9/pTp05J7969ZeLEifLqq68WWyNXr14tw4cPl+eff17atGkj77//vgwaNEji4+Plpptukl69eknt2rVl6dKl8sMPP5h9HQ6HDBgwoNjaAAAALA4/X331lUyePNkj+Ki4uDjp37+/jBgxorjaJ/n5+SZIPfbYY9K1a1ez7umnn5YdO3aYLrfjx4+bStOyZcukfPnyUq9ePTlz5oz8/e9/l6eeekpCQkKKrS0AAMDSbq+YmBj5+eefL7tNu5u0K6y4HDp0yAQc7U4raO7cuaarS0PQjTfeaIKPS0JCgpw/f1727t1bbO0AAAAWV3769etnKj81a9Y042xcDh48aKo0Wv0pzvCjLl68aLq39uzZI9WrVzfVn8TERDl58qTp/iooNjbW3J84cUKaNm1apPcNCiq5iXCBgUyyA8rq8eHv7QdsOD6Cijr4OCsry3RDaRDR7q7U1FQ5fPiwOJ1OmTNnjrmpgIAAWb9+fZEbqBUcNXToUBOqkpKSZO3atfLMM8/Im2++KZmZmZfMLgsNDTX32saicDgCJCYmsshtBlB00dHh3m4CgDJ+fBcp/Gjg0VtBNWrUkCZNmkhxCw4ONvda9enUqZN53LBhQ1MB0vCjXWzZ2dkez3GFnoiIiCK9p9OZL+npF6Ukk6+v/AMAfE16eobk5TnFX3F8A945vvW4u9rKUpHCz/jx4839hQsXzNgfrfYUdt1110lx0KqS0oHMBd1www3y2WefSatWreTbb7/12JaSkuLx3KLIzfXfL1/An+kXI8cfUDbl+cjxXaTwc/ToURk4cKDs3r37ivsU12BjHcwcGRlpZpjdcsst7vUaeHTMUcuWLU03nHaPRUVFmW1btmwxz2nQoEGxtAEAAJQdRQo/o0aNMgFIp5Jr95eeU6ekaLeWnjto5syZppKjXWt6np9NmzbJ/PnzpVmzZuakhs8++6wZD6QnPHzllVekZ8+eTHMHAADFE3527dolI0eOlAcffFBKgw5uDg8PlylTppgTKdatW1emT58uf/jDH8x2PdniSy+9JI888oiZ8v7oo4+a5wAAABRL+NEupcInOCxpPXr0MLfLqVWrlsybN69U2wMAAPxTkfqrHnjgAXNRU66fBQAAymzlZ9iwYe7Hubm5snHjRmnfvr0Zg6NdUgXpuX3GjRtXvC0FAAAozfCzdetWj2XXWZW//vrrS/bV8AMAAODX4WfDhg0l2xIAAIBS4BsX2QAAACglhB8AAGAVwg8AALAK4QcAAFiF8AMAAKxC+AEAAFYh/AAAAKsQfgAAgFUIPwAAwCqEHwAAYBXCDwAAsArhBwAAWIXwAwAArEL4AQAAViH8AAAAqxB+AACAVQg/AADAKoQfAABgFcIPAACwCuEHAABYhfADAACsQvgBAABWIfwAAACrEH4AAIBVCD8AAMAqhB8AAGAVwg8AALAK4QcAAFiF8AMAAKxC+AEAAFYh/AAAAKsQfgAAgFUIPwAAwCqEHwAAYBXCDwAAsArhBwAAWIXwAwAArEL4AQAAViH8AAAAqxB+AACAVQg/AADAKoQfAABgFcIPAACwCuEH1gpwBOqfrqX/WwYAlHWEH1grwBEkEbENTfDRe10GAJR9fhV+Dh06JM2bN5cVK1a41+3du1e6desmzZo1k8TERFm4cKFX2wj/Uq5GgsS16GHuAQB28Jvwk5OTI0lJSXLx4kX3utTUVOnRo4fUrFlTli9fLv369ZPJkyebxwAAAJfjN3X+6dOnS1RUlMe6ZcuWSXBwsIwePVqCgoKkbt26cuTIEZkzZ4507tzZa20FAAC+yy8qP9u3b5e3335bJkyY4LF+x44d0qpVKxN8XBISEuTw4cNy+vRpL7QUAAD4Op+v/KSnp8uQIUNkxIgRUrVqVY9tJ0+elHr16nmsi42NNfcnTpyQypUrF/l9g4JKLhcGBvpF5gS8wt+PD39vP2DD8eHz4WfUqFFmkPP9999/ybbMzEwJCQnxWBcaGmrus7KyivyeDkeAxMREFvn5AIouOjrc200AUMaPb58OP6tWrTJdW2vWrLns9rCwMMnOzvZY5wo9ERERRX5fpzNf0tP/f2B1SSRfX/kHAPia9PQMyctzir/i+Aa8c3zrcXe1lSWfDj86a+vMmTPSrl07j/UjR46UDz74QOLj4yUlJcVjm2s5Li7umt47N9d/v3wBf6ZfjBx/QNmU5yPHt0+HH522rl1bBXXo0EEGDBggf/7zn2X16tWydOlSycvLk8DAX87Ou2XLFqlTp45UqlTJS60GAAC+zDdGHl2BVm9q1arlcVMabHSbTmc/f/68DB8+XA4cOGBOfjh//nzp27evt5sOAAB8lE+Hn9+iISg5Odmc+blTp04yY8YMMzNMHwMAAPhdt9fl7N+/32O5SZMm5hxAAAAAZb7yAwAA8HsRfgAAgFUIPwAAwCqEHwAAYBXCDwAAsArhBwAAWIXwAwAArEL4AQAAViH8AAAAqxB+AACAVQg/AADAKoQfAABgFcIPAACwCuEHAABYhfADAACsQvgBAABWIfwAAACrEH4AAIBVCD8AAMAqhB8AAGAVwg8AALAK4QcAAFiF8AMAAKxC+AEAAFYh/AAAAKsQfgAAgFUIPwAAwCqEHwAAYBXCDwAAsArhBwAAWIXwAwAArEL4AQAAViH8AAAAqxB+AACAVQg/AADAKoQfAABgFcIPAACwCuEHAABYhfADAACsQvgBAABWIfwAAACrEH4AAIBVCD8AAMAqhB8AAGAVwg8AALAK4QcAAFiF8AMAAKxC+AEAAFYh/AAAAKsQfgAAgFX8IvycO3dOXnzxRWnbtq3cfPPN0qVLF9mxY4d7++bNm+Whhx6Spk2byj333CPvv/++V9sLAAB8l1+En0GDBsl//vMfeeWVV2T58uXSsGFD6dWrlxw8eFC+//576du3r7Rp00ZWrFghDz/8sAwZMsQEIgAAgMKCxMcdOXJENm3aJEuWLJEWLVqYdS+88IJs3LhR1qxZI2fOnJH69evLwIEDzba6devKnj17JDk5WVq3bu3l1gMAAF/j85WfmJgYmTNnjjRu3Ni9LiAgwNzS09NN91fhkJOQkCA7d+6U/Px8L7QYAAD4Mp+v/ERHR8sdd9zhsW7t2rWmIvT888/LypUrJT4+3mN7bGysZGRkSGpqqlSsWLFI7xsUVHK5MDDQ5zMn4DX+fnz4e/sBG44Pnw8/he3atUuGDRsmHTp0kHbt2klmZqaEhIR47ONazs7OLtJ7OBwBEhMTWSztBfD7REeHe7sJAMr48e1X4Wf9+vWSlJRkZnxNnjzZrAsNDb0k5LiWw8OL9pfsdOZLevpFKcnk6yv/AABfk56eIXl5TvFXHN+Ad45vPe6utrLkN+Fn0aJFMnbsWDOVfeLEie7qTtWqVSUlJcVjX12OiIiQcuXKFfn9cnP998sX8Gf6xcjxB5RNeT5yfPtG59tv0JleY8aMka5du5rp7gW7uW655RbZtm2bx/5btmwx1SGHwy8+HgAAKEU+X/k5dOiQjBs3Ttq3b2/O53P69Gn3trCwMOnevbt06tTJdIPp/eeffy4fffSRmeoOAADgd+FHZ3bl5OTIxx9/bG4FadiZMGGCzJo1SyZNmiQLFiyQ6tWrm8ec4wcAAPhl+HnqqafM7dfoZS/0BgAA8FsYFAMAAKxC+AEAAFYh/AAAAKsQfgAAgFUIPwAAwCqEHwAAYBXCDwAAsArhBwAAWIXwAwAArEL4AQAAViH8AAAAqxB+AACAVQg/AADAKoQfAABgFcIPAACwCuEHAABYhfADAACsQvgBAABWIfwAAACrEH4AAIBVCD8AAMAqhB8AAGAVwg8AALAK4QcAAFiF8AMAAKxC+AEAAFYh/AAAAKsQfgAAgFUIPwAAwCqEHwAAYBXCDwAAsArhBwAAWIXwAwAArEL4AQAAViH8AAAAqxB+AACAVQg/AADAKoQfAABgFcIPAACwCuEHAABYhfADAACsQvgBAABWIfwAAACrEH4AAIBVCD8AAMAqhB8AAGAVwg8AALAK4QcAAFiF8AMAAKxSJsKP0+mUadOmSZs2baRZs2bSp08fOXr0qLebBQAAfFCZCD+zZs2SJUuWyJgxY2Tp0qUmDPXu3Vuys7O93TQAAOBj/D78aMCZN2+eDBgwQNq1aycNGjSQKVOmyMmTJ2XdunXebh4AAPAxfh9+9u3bJxcuXJDWrVu710VHR0ujRo1k+/btXm0bAADwPUHi57TCo6pWreqxPjY21r3t93I4AqRixUgpKQEBv9wP7ZUoeXnOEnsfwJ8EBv7yu1j58uGSny9+i+Mb8M7xrf93WxN+MjIyzH1ISIjH+tDQUElLSyvSawYEBEhg4NX/JRZV+aiwEn8PwN84HH5fkDY4vgHfPb59oxXXICzsly+YwoObs7KyJDw83EutAgAAvsrvw4+ruyslJcVjvS7HxcV5qVUAAMBX+X340dldUVFRsnXrVve69PR02bNnj7Rs2dKrbQMAAL7H78f86Fifbt26yeTJk6VixYpSrVo1mTRpksTHx0uHDh283TwAAOBj/D78KD3HT25urowYMUIyMzNNxWfu3LkSHBzs7aYBAAAfE5Cf78+TSgEAACwb8wMAAPB7EH4AAIBVCD8AAMAqhB8AAGAVwg8AALAK4QcAAFiF8AMAAKxSJk5yCHt1795dtm3bdtltPXv2lKFDh/7q8/WyKI899ph88sknUr169RJqJYBr8dxzz8nKlSt/dZ/9+/eXWnvg/wg/8Ht/+tOfZPjw4ZesDw8P90p7ABQvPb4HDx7sXr799tvl+eefl3vvvder7YL/IvzA74WFhUmVKlW83QwAJaRcuXLmVngdxz2KijE/KNPS0tLMNd/atGkjN954o7Ru3dosZ2RkXHb/w4cPS69evaRFixbSvHlz87hgOf3nn3+WF154QRISEsw+2mX2zTfflOInAlDYihUrpH379vLyyy+b4/KZZ54xXdr169eXY8eOufcrvE6v7vTGG2/IXXfdJU2bNpUHHnhA3n33XS9+EpQWKj8o82MFTp06JTNmzJBKlSrJrl27TLn8hhtukCeeeOKS/QcNGiQNGjSQ5cuXm4vlTpw4Ufr37y8ff/yx+aLs06ePqTTNnj1boqKiZPXq1dKlSxdZtmyZNGrUyCufEYDIDz/8ICkpKbJq1SpzgeuzZ8/+5nOmTJki7733nrz44oty/fXXy/bt22XUqFHml5yuXbuWSrvhHYQf+L01a9bI2rVrPdbpb3/Jycly2223ScuWLc1ve0oHNS9atEi+/fbbK36B3nrrrVKtWjUJDg6WcePGycGDB8XpdJrfGr/88kvZsmWLVKhQwR2WNFAtXLhQJkyYUAqfFsCVaMWnRo0a5rEer7/m4sWLMn/+fHnllVekXbt2Zl3NmjXl+PHjMnfuXMJPGUf4gd9LTEyUpKQkj3VanVGPPvqobNiwwcwU0S6tAwcOmJK3/pZ3OQMHDjSBZ8mSJdKqVSvTXdaxY0dxOByye/duU/258847PZ6TnZ0tWVlZJfgJAVyN2rVrX/W++l2gx60OpNbj20UrvnpMa/XI9T2CsofwA78XGRkptWrVumS9Vmv69u0r3333nQkwOjNEx/3omJ0r0d/27rnnHvn8889l8+bNMm3aNHnttddMKV1fT7u6dHxBYSEhIcX+uQD8Pr8VVvLy8tyP9RcZNXXq1Mv+MsQxXbYRflBm7d27V7744gszHkcHM6qcnBzTteUqjRd05swZmTlzpjz55JPy0EMPmZuOF2rbtq05l1C9evXk/Pnz5jV0zJCLDqDWcULdunUr1c8H4Mq021rpMeui1V8XDTxBQUHy448/elRztQtbq0KjR48u5RajNDHbC2VW5cqVzZfbhx9+KEePHjWzsp599ln56aefTFm7sPLly8tnn31mwowGJ33O0qVLzZfoTTfdZLrAGjZsaLrGdNzPkSNHZPz48aYSVLduXa98RgCXp7+sREREyJw5c8wvPBs3bpQ333zTY6r8X//6V3n11VfNxAU93t955x2ZNGmSxMbGerXtKHlUflBmxcXFmUHI06dPl8WLF5tzgujARp3lpeOACtOgpNNedYaX7qPT4TXs6JenDoRU8+bNM1+OGqJ0u4YenUmmU+gB+A7totZjdfLkyabLW6uzesb3fv36ufcZNmyYxMTEmACkM8WqVq0qAwYMkN69e3u17Sh5Afmujk8AAAAL0O0FAACsQvgBAABWIfwAAACrEH4AAIBVCD8AAMAqhB8AAGAVwg8AALAK4QdAiatfv7452aS/6d69u7kBKFsIPwAAwCqEHwAAYBXCD4BSd+7cOXnxxRfl1ltvlcaNG8sjjzwimzdv9thHr8at++h105o3b24uKDt//nzThVbQ+vXr5aGHHjKvc9ttt8nLL78sFy9edG/X7rb27dubi9bef//95iK1d999t6xatcrjdfTq3v3795cWLVqY1yl4EUyXzMxM+cc//iEdOnQwr3PzzTdLjx49zIVwXZ577jl5/PHHZeTIkWa7XldKrxfVtm1bcTqdHq83fPhw0xYApYsLmwIoVVlZWSYcnD592gQavYL28uXLzcUkk5OT3ReJfeaZZ0yo0H2uu+46WbJkiQkeBa1Zs0aSkpJMqNGLzR4/flymTJkiBw4cMOElICDA7PfTTz/J6NGj5emnn5Zq1arJ3LlzzUUuNTDpxWk1LHXr1s1c3HbMmDHicDhk2rRp5mrgGrxchgwZIjt27JBBgwaZi90eOXLEXBRz8ODB8v7777vfT/cJDQ2VmTNnmtcODg6WtWvXytatW92fT4PURx99JH369CnFv30AivADoFStXr1a9u3bJ8uWLZOmTZuadVoV0YHFegVuDUJaBdKgoFUbrbK49unYsaN8//33Zlmvyaz7t2nTxty71K5dW5544gn5/PPPpV27dmZdRkaGjB071h08dJ8777zT7KPhZ+XKlaby895778kNN9xg9tG2acXIJTs7Wy5cuCAjRoww1RzVqlUrU6GaMGGCCXNVqlQx63Nzc03Yio+PN8ta8dHHWm1yteHjjz82wejBBx8shb91AAXR7QWgVGmw0ZBw4403mpCgt7y8PBNG/vvf/0paWpps2bLFVEv++Mc/up+n1RhX6FAHDx6UkydPSmJiovt19NayZUuJioqSTZs2ebxvs2bN3I9docTVPaaVGq3kuIKPqlq1qsdzQkJCTMVI23Dq1CnTxqVLl8qnn37qDkcuFSpUcL+Hq+2dOnWSdevWmSCmNHBpt1/B/QCUDio/AEp9vI92Q2n4uRzdlpqaagKEhoaCKlWq5PE66qWXXjK3wlJSUjyWw8PD3Y9dr6vVI6WBKyYm5pLX0JCmFR2XjRs3yrhx40zwioyMlAYNGkhERITHayndVljnzp3l9ddfNwEoISHBhMCCFSsApYfwA6BUlStXznQ7Xek//urVq0tcXJwJQNpdVDAAnTlzxv04OjraPQ5Hu58KK1++/FW3SYOPjt8pzBWwlI7/6devn6lGzZ49W2rUqGHG+CxevNiEot+i+2s7P/zwQ/O6Wp0qWNkCUHro9gJQqjQAnDhxwlRxdMCx66bdVDrgOTAw0OyjXVgbNmxwP08rKzqzy+X66683r3Hs2DGP19HgpAOj9+zZc9Vt0kqMvs4333zjXnf27Fn58ssv3cvaJaeDtZ988knTReYa3OwKPgUrP1fyl7/8Rf7973+bsUXafaaDogGUPio/AEqVTktftGiRmSL+1FNPmbE1GgjeeOMNM+NKx/rouB2dbq5TwbXbSWd7vfPOO7J//3536NCQpDPBdDq8PtYxQ+np6TJr1iwzJudK3WqX88ADD8jChQvNVHd9Ta3KvPbaax5T0/X1dDbYpEmTpGfPnmaMz4oVK8wUelVwev2V6LR2nU329ddfywsvvFCkvz8A147wA6BU6RgZ7SrS6owGiZ9//tlMP9fp4hoqXHTKus6i0v20CnTXXXdJly5dPM7P8/DDD5vxNVoxevvtt81r67l1tEtNu5mulg5mXrBggRnPo7PCNGDpuYf0NVxdbbVq1TJtmTFjhpkyr91qOiD6rbfeMjPVdNB04XMQFaaVHq0y6ZihJk2aFOnvD8C1C8i/mlotAJQiPV+Pdjlp4AkLC3Ov15MFHj161MyU8kd6bp877rjDnMNIz3UEwDuo/ADwOTrIWc+UrOFHx8lot5aOrdGZUuPHjxd/DHMa2LR7T6tKOvMLgPdQ+QHgk/Q8OnqGZD3Ls3Z76ckIdZyQnujQ3+gAbz2ZoXbRFTzZIgDvIPwAAACrMNUdAABYhfADAACsQvgBAABWIfwAAACrEH4AAIBVCD8AAMAqhB8AAGAVwg8AALAK4QcAAIhN/hcVyzcDEXbUKQAAAABJRU5ErkJggg==",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=pokemon, x=\"legendary\", y=\"hp\", errorbar=\"sd\")"
]
},
{
"cell_type": "markdown",
"id": "4f75e1fa-a5d7-4d2c-a458-8190a7cd700e",
"metadata": {},
"source": [
"Here, we use a barplot to show average hit points by type. `errorbar=None` removes the standard deviation bars, because they clutter up the plot with too much detail. "
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "17f1c289-5990-4420-bfcb-e50eee0b8af6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='hp', ylabel='type'>"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=pokemon, x=\"hp\", y=\"type\", hue=\"type\", errorbar=None, palette=\"muted\")"
]
},
{
"cell_type": "markdown",
"id": "213d6139-203f-4d81-a4b1-6f98cb184662",
"metadata": {},
"source": [
"**When you want to show how many observations are the intersection of multiple categories,** a [countplot](https://seaborn.pydata.org/generated/seaborn.countplot.html) is a good choice. \n",
"\n",
"To demonstrate this, let's convert the numeric variable `speed` into a categorical variable, `speed_category`, using the built-in function [cut](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.cut.html). "
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "3c8e9f47-9aea-4bf0-a628-7aa1a66a8eee",
"metadata": {},
"outputs": [],
"source": [
"bins = [0, 50, 100, 200]\n",
"labels = [\"slow\", \"medium\", \"fast\"]\n",
"pokemon[\"speed_category\"] = pd.cut(pokemon.speed, bins=bins, labels=labels)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "22f78bec-3d18-4133-ba9f-6595d7181ded",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='speed_category', ylabel='count'>"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.countplot(data=pokemon, x=\"speed_category\", hue=\"legendary\")"
]
},
{
"cell_type": "markdown",
"id": "fd508c13-9900-4be1-958f-4f9e9e9b633a",
"metadata": {},
"source": [
"**When you want to show the relationship between two numeric variables**, a [scatterplot](https://seaborn.pydata.org/generated/seaborn.scatterplot.html) is a good choice. \n",
"\n",
"Here, we plot pokémon hit points against their speed. "
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "444d9832-bd57-4238-9ea4-5ee898847170",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='hp', ylabel='speed'>"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.scatterplot(data=pokemon, x=\"hp\", y=\"speed\")"
]
},
{
"cell_type": "markdown",
"id": "03e81709-393d-4c41-bce5-2dffc9cf5553",
"metadata": {},
"source": [
"You can distinguish between categories within a scatter plot by assigning a categorical variable to `hue`. We set the marker size with `s` and their opacity with `alpha`. "
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "86f9747b-00a3-407f-9b73-0bce40bac50d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='hp', ylabel='speed'>"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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pu+3bd+Btb3sXWlpaJwaWf/nLn8djj/0emUwGGzduxlvf+g5s2rTlkpyPKnhWKBQKhWIFiSazEvGZD94fS2axUnz84x9GW9spfOxjn8aPfvRTvOMd/xv33/8r/PznP5l1+w996P0oLy/HN7/5fXz969+BVqvF+9//93IfU3jvec870N/fh3/5l3vw9a9/F1u3bsdb3vImtLWdvCTnoyI/CoVCoVCsYHHz4Fh8wSGpvJ/bra91LlsR9AMP/BoPPzx19taOHbvwr//6Bezdey2uuurqichNdXUN/uu//h/Onj0z6776+3vld7idXq/HP/7jB9HV1SkT2VkcffToEfzqVw/C6XTJ9n/zN2/DkSPPy+DTf/qnD2O5UeJHoVAoFIoVgl1dLG5eDNyO2y8XN910C97ylnfMqAMir3rVH+Hxxx/Ffff9Ar293ejoaMfAQD8aG5tm3ddf//Vb8YUv/Ct++tP/wq5du3HttTfghS+8SyJAjO4w+vOa17xsyu+k02mkUilcCpT4USgUCoVihWAJD7u6FgO3W86SH6vVhrq6+hm3M1rz3ve+C+3tZ/GiF70Yd9xxJzZs2IRPfepjc+7rNa/5Y9x++wulRui5557FN7/5NXz3u9/Ev/3bD2V/NpsN3/rWv8/4PYPBgEuBEj8KhUKhUKwQTGFVea04rtPMm/rS6TSy3aXy/ZnM6dNtePrpJ3Hvvd/B1q3b5LZsNou+vh7U1NRiOmNjY/jmN+/F61//Rrz0pS+Xr5GRYbzqVS/FwYMHsG5dK2KxmBQ6Nzevm/i9f/mXf0Zr63q85jWvxXKjxI9CoVAoFCuI3ayXdvbZur1KNNe4YDPrV6Tby+fzQafT4aGHfguPx4NwOITvfvfbGB0dlUGj03E6nRLx6evrw5vf/DaJKP3617+UqM6mTZtRVVWN9es34EMf+ke8613vQUVFJX760x9LSu2zn/3SJTknJX4UCoVCoVhBWP9CHx8y3edHr9OiqcaJzY3eFWtzLysrxz/900fw7W/fKyLF6/Xhhhtuwmtf+zqpA5oOC5w//enP48tfvgfvfOdbkUwmRex86lP3oLa26P78uc99BV/5yufxwQ/+AxKJBJqa1kkn2dVX770k56QpXArbyDVGLpfH2Fhsyfan12vh8dgQCMSQzeaXbL+Kc6g1Xn7UGi8van3X3hoz6jE6OgCfrxoGg3FpHJ6TWenqmnB49lpXLOJzMeu8XK/h+dbc67VBp1ucg4+K/CgUCoVCsQpgLMJm0kk7+5TZXmtI+KwVlPhRKCZ96soXCoilcsjlC9DrNLCZ9NCgoN57FArFJWMlipqvNJT4USjGhc9QMIG2rgBGwwkROzqtBmVuCzY1eeF1mFBQb0gKhUJxWaDEj+KKR6PVoGc4igOnhqd84mL0Z2gsjrFwEtdsrUal26w+kSkUCsVlgJrtpbjiiadyOHLGP6ewyWTzOHx6BClVhKpQKBSXBUr8KHClz9UZDsSRyuTm3S4STyMUnelnoVAoFIq1hxI/ClzptT5joeSitg1GUyKWFAqFQrG2UeJHccWzWEGjXc6JggqFQqG4ZCjxo7ii4YC96jLbgttR95SpgmeFQqG4LFDiR3FFw5Z2trE7bfO7s5Z7rHBYLs20YYVCcWXDaDQHmao0+/KhWt0VVzwGnQZ7Nlfi6aMDiCezM+532U3YtaEc6m1IoVAsJ3ptAbp0BNngIPKpBLQmC0zuKuSMDmTzy/cO9LGPfVgGj87H44/vx+WEEj+KKx5Gf1xWI27ZVYfekSh6BiPI5vIwGnRornGiymeDSadRLs8KhWLZMGgyyPYcQ3yoG4X8ue5TjfYkTJUNMNRtRaawPNHnd77z7/HmN7994udXvvLFeMc7/g533PEiXK4o8aNQjM/UMeu12FDrQnOVU8Zc0OFZr9VInY8SPgqFYjkjPhQ+yYGOGfdRCPF2MwBd/U7kliECZLfb5Wv6bT5fGS5XVM2PQjEJCh2dBjBoNfLHoQqcFQrFcqNLh5Ea6p53G96vT4exEtx33y/w2tfejXvu+QzuuutW/OM//h0OHNiPm27ag4GB/ontSrf19/dPfKj8wQ++iz/6o1fijjtuxBvf+Do88MCvsRpQkR+FQqFQKFYIFjVng0NTUl2zwfu5nbbCvSIfyvr6euH3j+Db3/4BUqkUgsHAgr/z9a9/BQ8++Bu8+93vRWNjEw4dOoDPfOaTiEajePWr/wgriRI/CoVCoVCsELTRYHHzYsink1jJBrA3vvGvUFtbNxHlmY9EIoH/9/9+iA9/+GO44Yab5Db+7uDgAH74w+8p8aNQKBQKxZUK6wnZ1bUYtEbzitYf1tfXL3rbzs52pNMpfOQj/wSt9lyFTS6XQzqdRiqVhMnESqaVQYkfhUKhUChWCKawTO5K6eqaL/Wl0eqgd1citYJ1iKYFxAqFTYlSau6jH/2kpLymYzDM76223KiCZ4VCoVAoVpCc0Snt7PPB+7NGJ1YLBkOx7T4Wi03c1tvbM/E9BY9Op8PQ0CDq6uonvp566gn8x398f0o0aCVQ4kehUCgUihWEBob6uq0wVzdLhGcyGp1ebuf9y9HmfqG0tLTCYrHi+9//NymGfuaZp/CjH/37lFb5u+9+Db7xja/iN7+5T7b55S9/hq9+9QurooVepb0Uaxp+ejAWEtAm40iPhmDQ25DXapHPT95Gg0wuj0w2L9WFFqMOhVXews5p84lMTgoCDHqduFCrtnuF4vKFBob6+p1wVDZLV5cUNxvNkupixCezioQPsVpt+D//56P42te+iNe//o/Q2roeb3/7u/CP//j3KPG3f/u/4XZ78M1vfk06xSoqKvGmN/0NXve6N2Cl0RTYiL9KuPfee/H444/j+9///sRtH/jAB/DjH/94yna1tbV46KGHJgZTfulLX5JtIpEI9u7diw9+8IPnVZg1nVwuj7Gxc6G8i0Wv18LjsSEQiCHLC7BiSTAjgfxIOxLtzyMT9kNv0EPnqoJl3U4UvI1I5fTI5gvo9cfQ0RdCIpWRyew+twWtdW547SbxoVhVaDQYjSRxtjeE0VBCihttFoM4TdeW2cWDaKVQr+PlRa3v2lvjTCaN0dEB+HzVS1rDwg9s7ALj3/9a/NCj12uX7TU835p7vTbodNq1Ffn5wQ9+gHvuuQd79uyZcvupU6fw5je/Ga9//esnbmMescRXvvIV/PCHP8QnP/lJVFVV4dOf/jT+6q/+Cr/4xS9gNK5sQZVi+bAggfjR3yHefuRcu2hOh3TkFOK9bXBuvwX6dXvxxFE/RgJT20j7hqMY8Mewc305mqrsKKyW64xGg/b+MI6cHZnS0ZHO5BAIJ9FfFsOeTRXQ82QVCsVly1oUPGuNFa/5GRoaEnHzmc98Bk1NUyvC+an8zJkz2LZtG8rLyye+vF6v3M92uW9/+9t4xzvegdtuuw2bNm3C5z73OQwODuKBBx5YoTNSXIpPFZm+YxPCZwaFAiJHH0NupBuRWGbON5fDp0cQjs8cZLpSBGNpHD3rn7OVddAfw5nekJr0rFAoFGtd/Bw7dkyqxn/+859j586dU+7r7u5GPB7HunXrZv3dkydPSqX59ddfP3Gb0+nEli1bsG/fvmU/dsXKYMhEEG8/vGDLZfj0QbRUW+feJl9A12BkVYgJjVaDjv6QzBSbj+7BMBLp+Z1gFQqFQrHK01633367fM1GW1ub/M8aoEcffVSKW2+55Ra8+93vhsPhkAgPqa6unvJ7FRUVE/ddTHRhqSjlIBebi1TMjzYek4LAydkfFgif+78gqazEcC/KmtPzihvW1eSX+Pm+ENLZPAKR5IJCLJnOIZ3Lw2a+9H+66nW8vKj1XXtrnF9lRcirAc34kpRqlpYLnU5zUe/bKy5+5oPih4KHYuZrX/uaRII+9alP4fTp0/jud78r9tlkem2PyWRCKBS64MflBYhFcUuN07k4F0/F/KTSWugNU9tBS+jG/xhyhZwUN/Nni2Xu2i+TyQC7zQSLuehZsVJE42mYTUbkCgu/mfKYl+P1uVjU63h5Ueu7dtY4mdTB79de9IX4ckS3TCKegpO6wOWywmw2X57i5y1veQte97rXwePxyM8bNmyQmp8//uM/xpEjRyZOnLU/kxeBQ9cslgt/cbMeJByOYylfBPxjC4cT0kmmuDiMGhNgcSMbHp24TTMudHLZ/HgHVwEmTwXGkvoJkTwblR4LUskMkok0VhQNYDJo4Q/Mfxxmow6afF66VS416nW8vKj1XXtrzGsPO47Z2aTVquesFPHhOnN9lyPyw7XmmodCCSQSU0sA+NyuuW6v2aC6KwmfEuvXr5f/mdYqpbuGh4fR0HDOHZM/b9y48aIeezna9PhiUC2sF4/G6IKlaRvCzz8y6dbiXxmFD//gdBoNrBt245nu+JydE/wjbax0IEM/nVVAc7UTvYPh8TOZnZoyu4iklXwdqdfx8qLWdy2tcTFSyxlWRqNpCfa39imMv4EtV8qLa13k4t4HV7X4ee973ytC5jvf+c7EbYz4kNbWVvHyoYvkM888MyF+wuEwjh8/PqU1XnF5kcnkYWncCfNIH5L9Z2bdxrbxGugqmqDv91PKzip8tqwrg8tmKOmmRbOYXPaF5LvpO7ShyYtTnWPys0GvldRdOpuTfXmdZmxo8CCfU22wCsVqQKvVwWKxIxoNyM8UQKX6wyuZfF6D3BK/T/GDLYUP15prfrHjMVa1+Lnrrrvw1re+VUwMX/GKV6CjowMf/ehH8bKXvQwtLS2yDUUO2+TZ/k7zQ/r80O/nzjvvXOnDVywjCdhg3/MSmHqOI955pJgC0+phKq+BpeUqaCs3IFUw4obt1WjvC6FnKIJEKitigiKitd4jKa/FKhTm9BPpPEKxlBQdmww6uGxGcYsuRZZYKxZP5xCKppCmQDPr4bIaJVKzON+OAjbVu1HptWIkmMBoMIlcPg+3wwSPw4wqjxWqrEChWF04nUXrlZIAUkCECVNTywGFT2nNL1vxc8cdd4jx4de//nV84xvfkA6vl7/85XjXu941sQ09frLZrDhBJ5NJcXj+1re+NTF0TXH5koAd+ubr4KrbAk0uCb1Oi4zOhrTGIh1RxKTTYmuTFy21LmRyBQlSU7CwqWrx7s4anB2IoK1rDPHkuSiSxaQXEbWuxiEaqq0niPbeoIijEnRn3tzkRV25bVERJh5jZ38YfSPRif3QpLHMbZYOL6/duKwdFAqF4vxgpMfl8sHh8CCXWz2+YSuFTsf1sCIUii959Een0y/ZQNRVNd5itaDGW6w9lmuN6b9zdiCMI20jc2qXPVsqEY6m0dY9+yc/RsF3baxEU6V93ghQtgA8c2xghiN1CaNBhxt31sBlWRlhr17Hy4ta3+VHrfHlvcbe8xhvoYLoCsU8MI3FGpy5JAsjSYFICie75g558+PFyc7Rec0J+elxKBCfU/iUxlyc7AxAo/5qFQqF4qJQb6MKxTyChCaIqXlEi8NmRN9IDKFYet5CR6bLgtHUFGPGyeRRkNqkhRgeiyGaXB3daQqFQrFWUeJHoZgDCpVofPbZYCUMeh0isbREZRZq8ogmMnMKpGyugGRq4XoBjuTIKg8YhUKhuCiU+FEoFhA388GOBtbi6BYxH8yo181ZrMwuNBZsL4RmfFuFQqFQXDhK/CgUc8DiZLadzydswvE06ivtkv6ar5iZnj0+l3nODjOjXoPaCvuCx+R2Fru+FAqFQnHhKPGjUMyD3axHzTyihK2cdosRteXzC5f6Sue8ooX7qa+wy/iKuWDAZ329G/pVMIVeoVAo1jJK/CgU48JCq9NIVxfb2yemqxcK2NFSJlGZ2SRHhc+GpioH9myqQBlNE2fZb0OVE1uavSgsYHRoM+lxzbZqWGcRSfTO2NZSjmqfdZGGiSsD102vzcOgyUE3f8ZQoVAoVgwVP1dc8bB8eCyckm6reDIjPhGNVQ5Uem0w67UwaIGrN1agtc6NroEwYskMzCY9mqqdcNuMMkeM1TjXba2Wji5uk0xnJSLUWO2Ey2qYVTjNOI58AWUOE27dVYeRUBK9wxG5jY7UdZV22E368x7FcalgIbcxF0NubABpfy8KuRy0ZitMlc0oWL3IQJmOKhSK1YMSP4ormmyhgINtI+gbjk65fTSYEHfma7dWyYgKbaEAj82Iso0Vcj/1znQDL70GIl6qPJUThc3nOzmaYsek16K+zCamiMX9FIpOqatY+BhSo4ieehb51CSfolgI6dEBGMtqYGq6CmmowY8KhWJ1oNJeiisWpmiOdwRmCJ8SsUQG+44PITVJ5FDMLDQRmveVtrtQWBh9bj+rVPWMY8jHEW/bN1X4TCLt70e27yQWabyqUCgUy456O1JcsURTWfQMhefdJhJPYzScVJOa54Drkg8PI5eMz7td0t8LXWZ2kalQKBSXGiV+FFck1DKhaBqZRcye6RoMS8GxYiacMZgZ6Vlwu0ImjUJifqGpUCgUlwolfhRXLItNS3E7Nf53dtgfV8gvbtxGIZ9d0AVboVAoLgVK/CiuSChmWNC8GFx287Ifz1qlAC10VucittRAa7IpEalQKFYFSvworlgcVgNcdtOCRdFse7+Y4uXLGa6LoaKxmEecB73DhYJpMSJJoVAolh8lfhRXLAatFttbyuadqbW+wQOHRTlCzEfe7IKlZt2c92t0eljqtyCrMV7S41IoFIq5UO/qiisWtpOXu824fns1TnSMYTScmEjLMCVGU0O6N9Nfh4GNAjSIJbPI5gvStk1HZhpBl36HnU+5QgHxVA65fF5EFbeRupjLON2TzetgqNkCq8GM1GDHuc4v+v84vDDXb0LWVrGgw7VCoVBcKpT4UVzR8IJc5jThhh3VImxSGY5l0IqbstmoFY8diprRSBInuwLwBxNiREgxVOayYEOjF+Uups40GAomcKorgLFxEcWBqOVeKzY1euG1zz/4dK2TKeihq9wIq68eSEWZDwOMJhSMTmSgQ0FlDRUKxSpCiR/FFQ+FChNfDrNevkpQ+LDmZzCQwLPHBpGdVPfD3xkJJjAW7sfuzZUSCXr26BDyk0I8uXwBg/6YuEVfu60a5c65p7pfDnC9choLYJ404+zyPV2FQrGGUTU/CsU8JDM5PH96ZIrwmQwFzoFTwxgKJKYIn8nQS+jw6RFkVNG0QqFQrAqU+FEo5oCprUAkLWMu5t5GA38wiXAsAwsHj85BOJZGKJ5epiNVKBQKxfmgxI9CMY+wCUaSC2wDJFJZBEJJmIy6ebcNRdKSRlMoFArFyqLEj0IxD9pFjLWgnqGoWaich/u6jEt+FAqFYs2gxI9CMQfszip3W+f172MBs8NqRFWZbd70GMWR7zIveFYoFIq1ghI/CsU8uKwGlLmsc95PLVNdZoNJr52zKJpUeKxwLHKchkKhUCiWFyV+FIpJ0Rl6/Eye4M6U1q5N5XCOj8FgHRC3K9Xu0Azxmi2VaKp2wjKpTX4yHocZV20oP+eGuAgYbSoei3bOOqHJ2/C4VgsGgxZGow56vXp7USgUqxPl86O44tFoNYgmsxjwxxCJp2E06FBbbofTaoCWA1CNOty0owZdwxEcOzsq6S2zSY+t63wy98uiLxY633pVHXpHougZikgUyGTQoanGiWqvDUb94up9qGEyuQKC0TQG/FHkCoDXaUKF2yLdZDRlpBhiC/5YJI2h0Zj8XpnHgjKXGWa9dsXqiszaFDSREST7zwDZJHR2L6yVzchYfMjklBBSKBSrByV+FFc0TFSd7g7gdHdwStrqTHcAFV4rdm+qkDEVRXfnOKp9rAGikCmgbyiCWDyDHa0+6DUamA1abKhzobnaKZ4/dHjWazVSO7Q44aNBOJHB/hNDCEVTE7d39kM6yTiHrLHSgZFQAgdODiM6qcaooz8Eq1mPqzZUoNJjueSjJCy5AKLPPYhk/9kpES6t0QzH5uthbt6NZF7N9lIoFKsDJX4UVyyMoJztC8tcr+nw8j00FseZ3pAYGbb3BSf8eiZT+nn3eFqLQodZM914Gup8RlokMjk8fXRg1sLpVDqHg23DMBn1eO7kEJKp7Ixt4sks9h0fxE07a6VW6VJhRgzRA/cjOdA54758OonQ8w/DrTfA0LQXmYwyelQoFCuPikUrrlgS6RzO9ATm3YbRIEZ95qN3OILIPJ1eixVi/f7YvB1jTpsRh9pGxFdoLugmfbo3KKm8pUTa9GWERX5K95uW7yChwVmFzzkKiJ7eB32qKCAVCoVipVGRH8UVSyiWnldIMI00Fk7KbK7actucURze3u+PYnOD54KHl3JSfPdgeN5tbBYjjncMwue2wjiP/9DwWEwmy1sMF//ZJj++Tu19IVkrK9v6vVaUOc0w6YsF4omuowvuJxsOoBAdBZzOiz4mhUKhuFiU+FFckTB6kc7k5t1Gp9Uimc4taiZXMpUb77i6MPHD1BqjNvOh1Whk6nzRK2hu8cP9LIWfEIutnz/jR89QWB5Nq8kjnkxLrZPVpMe1W6vgc+qRTyUWtb98OiGRorzKfCkUihVGpb0UVyTUBuzYWijlZTUbYFxEy7bVYrgowcHCaHaZzQeLqM0mw7ymi4T7udgxGvx9pvv6BgPQpiLIj3UjM9yF1FAnEPUjHovi2RNDSKQBncWxuH2aGD27qMNSKBSKJUGJH8UVC1vZ6dMzF0zzuO1GVHgt86az6AvELrALTXkRg16Lzc1e1FY4UFNuh2vcV2gykVgKGxs8MI631s8FTRetC8wZW4hYKofewTHkAv1I+/uQS8RRyKRRyKSQCY4gM9yNWDCA4WAC5uYd80ai5Pzc5dDYfBd1TAqFQrFUKPGjuGIxG3TY2OiZN5JCr54tzfNftJtrXHDMYXC4qPRbvoCz/WEcPTuKw2f8eP7MCFLZPJprXVPEWTyRxc71ZbCZ5xY2bIlvqXVflBAjkXgKydFB5BJFH6HpFHJZZMYG0NM/Bo2zCtaGjXPvTKuFfdN1yBhVvY9CoVgdqJofxRULBUJ9hR3UCb1DEREOpQGl6XQWFosBrbUu8evhv7O9AaQntWozWtNU7cKmJs+EtY3eoEGegqGQB3R66EzWedu7E5k8njk6iEAkKULIZTdiYDSG59uGcdpiwI07aoqeQRoNdqwvR5nDjOu21eDgqWEpxp4Mf5c+P2xzvxjxw+PIZVLIxqPzblfIZpBJxpDRmGG96oXQ6I2Id5+Q20vobC44t94ITdVmZBeoaVIoFIorUvzce++9ePzxx/H9739/4raHHnoIX/7yl9He3g6Px4O77roL73znO2E2m+X+5557Dq973etm7Ot73/serr322kt6/Iq1GfqsLbNJYXNb9xjCsQxMBi2aalxoqXWJwKFh4OYGNxoqHfAHE4insjAbdSh3W2Azl1yXgUI8gOETpzDW14NsOg2jxYKyxnXwNLSgYHTOFCQaDZ4/7RfhQyigWPtTX26XyE88mRGfoRfurZe5YJwfls/n4bTocdPOGunC8oeKxcZepxkumwmGcVPFi8WqKwD5+QvCiV2XlXNPwAHTzhfDun4v0v4eSY/pHB7o3NXImDzIZtVAV4VCsXpYNeLnBz/4Ae655x7s2bNn4rb9+/fj7W9/O97xjnfgxS9+Mbq6uvDBD34QwWAQn/jEJ2SbU6dOoaGhAT/84Q+n7M/lcl3yc1CsPeJpGgsOiqMyIx6l4aPsaBoejWHP5ipUe80iKNg63lBhl+0oVFjgTOHDGVbp0V60PfEIUslznU+pZAqRwAH4O86i5cbbobWyFf7cY0eSGQyNzZ5WotAxO8wTBoc+u2lC1PCxKdo8NiN8jmJt0Ln7lkZkOI05uNwOhIKRObdhlKyxwob8eDdcKqcDTBXQNVTJGmXzeaR5lxI+CoVilbHiNT9DQ0N485vfjM985jNoamqact+PfvQjid7wft5366234t3vfjd+8YtfIJ0uOuu2tbWhtbUV5eXlU76MRmWlr1gAjQaHz4xOjJKYEDTjAoIt4wdODSGWOqdYeF9xXMW5C3o+FUH7viemCJ/JREIh9B16BprCOU8htsUHwsl5ozSlY+kbiU4ZtjoZ/v5SRHqmPi5gNuqxrbUc+nmKq9c1VcJtKqAwrdiZRohMcanOLoVCsVpZcfFz7NgxGAwG/PznP8fOnTun3Pe//tf/wvve974pt2m1WmQyGUSj0YnIT0tLyyU9ZsXlAYeZ0hBwPhh1GRyNzdk6LkNGR4cQC88dISGjAwPIRac6RS9Ws5QiK9MfN5MvIJrKIZrKIp3Li+HgUpE32FBpiODaqxrh8TqnTI23Ws3YsqkOm8oBg8MlYkehUCjWEiue9rr99tvlaza2bNky5WeKnu985zvYtm0bvF6v3Hb69GmpBXr1q18tUaQNGzZIdGjHDrbfXjhMZSwVpYvSUl6cFBe/xpFAQiwJF/LEGQrEsbFh9g4qg0GH4cG+KeJgNvib8YAfbk/VxH7cDtOi/HjKPFbZrvSa5NT3M/1hdA6EEI0Xi4vpR9RQ5ZAC7cX4Ei2IxgRLZRMqOp6Ht9WDmK5C6qJMJj0shSRMcT+MtipoLG7oV/4z1GWBep9YftQaLz+6NbLGKy5+Fks2m8V73/teETusDyIDAwOIRCKIx+P4wAc+AJ1Oh3//93/H61//evzkJz+RdNiFwAuNx2Nb4jOgs79lyfepuPA1Hg6nYLEsnB7lMFGHwzKnUGFKyjAtPaTRaGHxeKF1VSGrLT5G3uqV4ysJJaPZiMoy+4xhqZPhRPl1dW64XFb5OZpI4+CxQQyOxsVbp3T8lFNdQ1HEkllct70aTttMn6DzpeBqhslsQrLnBCzR9mIbWKwArckCU2MrTFUt0Bov/nEUU1HvE8uPWuPlZ7Wv8ZoQP0xxvetd78Kzzz6LL33pSxNRnerqauzbtw8Wi0VSZ2T79u04fvy4dIx95CMfuaDH4yfzcJgXl6WBCpgvhHA4oVIEy8SFrLFRp0UqmZFW8vlwVjsQiSRmjfxQEFl9lci0nT53LHoDHE2b0T6cRtfBfiSTRXHTuFmP7mivRJFY0EwtsbHeLZPcZxu1wXEWmzaUw6ABAoGYiKbOwQg6euceENqTSMNlM2LTHJGq80Wjd0PbdA2MqTCQy4pgy2jNSGvNSMayAL8US4J6n1h+1Bpf3mvsdFoWHXFa9eJneHgYf/3Xf42+vj5861vfwt69e6fc75w2KJE1QawBYgrsYlgOT5JSIahi+TifNbaZdPA4zRgJzC102epe7bMhnZ677dviq4LZYkEiXtyPo2kT9p8OYGTk3KBSs82GdEGPtq4xBMNJXLOlUtraPTYDrt9ejVNdAfiDceTSaWjyGWld39BUhuoys5wPhVIql8PxzjGZIM+5Y0xv0YNoeodXR19I/IvY9r40aACdC3qTFnaPDbFADNl51kNxcaj3ieVHrfHys9rXeFUn5UKhEP7iL/4CY2NjkuqaLnweffRR7Nq1Cz09PVPSYydPnrzglJdi6eAFe6E5VCt5PNQGO1vLZHr7bFBY7FxfDtsCM8A0Zgea91wHvcEAq8uN3lB+ivDRGw1wVdWioCn+uQ0H4uj1F4uoqVtcFgNu2FKO2zfbcXOLHres02OPyw9Xz5NIHn8E+mgfhoMxnOoO4ljHKHqGIlLv0zUYRjienjFZIpbILDgkdaG1We2steNVKBSri1Ud+aGXD4XNN7/5TSlwHhkZmbiPP+/evVuKndkR9v73v19SX1//+tfFB+iNb3zjih77lYxGq0EslZUW8myuAJvZAKfNCKNuaQz4zutYNBrxmwnHM4hKxEQDt900YU5IX5+brqoVM8H+4Yh0dzFsWuaxYH29W3x0FvLOyeUAc0UztrzAgjF/EPuf6ZIp7QajATa3CzZPOTTGqfPBJDpTbhPnZp02j/zASWh6TqGUJS+Mf+WzKfQdeBLZqq0o6Cun6BxOeO8fiaLKZ5NzKh3nYkXBQmuzGtFrC9Clw8jFQpyxAa3FgYLJhazGuGQeRwqF4vJn1YqfXC6H++67Tzq8GP2Zzu9+9zvU1dVJ9xc9gt70pjchlUrh6quvlqLnsrKyFTnuKx362R0/O4qewfCU6APFz7aWMlS6LZfsIkURNhJK4sgZ/4SXTymVVVtux9Z1Phi0gNWgw1WtPqm/ydKtWaOBxaiDBvTZWdxjse28M2qFyWGH1pOBz11ArgAkcjrk0jo4DFN3RPdmdm3p9BroU2GE+87Mvt9cHiOjUeiTx+DeWo4Kj1UiPiW415FgAnaLQcQLcTnM4kC9mLU5etaPYGTq2nCw6jZZm9UVWjEVEkh1HEV8bFBmixXRQO9wwdK4FRlLxaKfL4VCcWWzqsTPJz/5yYnv2bl1+PDhBX+H7s5f+MIXlvnIFIuBUudQ2zB6h2fOhGJH0zPHBmQuVYXLvOwCiNGP0UgKzxwdmJEC4s+dA2Fp3d67uRL0D8znClKEPNG7RIPB83isk50BtHUH0FjjQs9YBtlJhX6UEFWww207F51gyksz3imWGeqffZSERoN4Mi3RmWwkDGc6hPUNbkl7TS7S5mMx0uayFvffWueSiNJca8zjHZtnbbomrY1+legfI1JInNmPTMg/7Z4CspEgoiefhX3z9ciYfUoAKRSKtV3zo1hbBKKpWYVPiVyugOMdo8hegqsTszYnOsbmrX2heeFouDhQ9GKIJHM4O96BlUplUemdapPAs2Ux82RB5HNZZKo8U0+SwuEfo8kCvc0JncUuCkWKnCcVFmejIWgKwO5NFRKdmkxpO6bqqr3WecUlj+L4AmszxLUJXfzaLAVco0J4eBbhcw4OU031noROs3oLLBUKxepBiR/FksBIRkf/uXTMXLDTifUlyw0jIaPB2cdNTKa9j6JFc1Hn3TsckRofwiGlGxrcM0QDhQajKbydwqWlzjU+vgLQ2t1IV2xCF2pwJOrG6Uw54mWbxSOI3YsT6PRSLG0x6nHH3gYZvMp0osNqFIPDG3fWYEuTd8GziSVzi1qbs1ybVSB+dMghNdix4HbpkB+69PxO2wqFQrHq0l6KtQuv/ewyWghKhCRTNOMDRJeLdCa/oH8PiSezUuczx+isRYmfCDuuJkVgOI7i6k2VOHByeMoxpLM5aLWsffLBx6GlhYKktM7E3Dhx8AgymXOeOSe1WtTW+LB53VaMHXoOGq0OeYsbKX8WI+m4mB/WlNnRWO2EFhpsXueF3ahbVMqHx7GYteHzxLok/QqHf9j6n88UJ9/PSz5frAVS72oKhWIB1NuEYkng9ZEX5MUw3Q15OZhrEOh0eMwSXLnATBw1hHHa+QyNxVHutuCF1zaisz+M0VDRjXlDgxfb13knanMonE71hnCyN4qchn+K58RPPp9HT+8IcvkyNDWtE5+hgdi5bZhCK/kTsduLRduLzSbSX2gxsOuNtUMrjkYr4m+x2yoUCsVCqHcKxdJQgEQhFoKeOuxMWm7Yrs100ELUVzomLvC82Gt1GhFOi73m08iL+5gOO7B6B8Mod5uwo6UMuzaUY+/mCjjHz52Plcjk0dEXRF6jg8FbDY1h5qiIgYFRmKqaYWjYiqHAzOhHmdsi+z4fiWI16eGwLXJtVkHHV05rhMFXs+B2rJcqmOyX5JgUCsXaRkV+FEsCIxkVHosIjslpoOlwThXbyJfb9pyjK1ob3Dh4cnheIVZdZpN6HXrdsAOMx85276ZqF7xOk3gTLRRRcdkMKPdYZzhF09dnNFgULOtq3TAbtEil8/CHE+gbjkKn16JjICIDTs0GMwzl9UAqhiwLoPN5aPR66Gxu9CfM2LauAteZnWjvD8koDJNBh+YaF3wu03mnpegMvb7egwMnh+Zdm5oy2yX3ZZoNHoPJV4/UYCfy6bnSXxqYa1qR0xiL4TiFQqGYByV+FEuGSafBtduqsO/40BRfHcIi39Z6N9ZVOy/JvBdeMBvK7UilcjjTE4DTboRex9RQQep8+P/erVUidA6fHUXXYAgFOvvkC9JdxMGhLrsJe7dUwm4qppQkPabVimW7pPgKBXkcRo6u3lSB/SeH4A9MLSSmLqmvdGLrOi9CsQyePTYo+/c4jSJiWH/TPRgWc0FGcbRmN3QWV/ECrtGKMIsm+XgaVHnMqPZZ5DZGZCh5WK/ETfnzbEJFp2PNDFNlGhS0Bll7bldfYUMy7cOpzrGJYu0SjMzt3VIFi6TSFickeJ46TQGaQl6crHMF7ZLaGWQMDtg27EX8zHPIJaeNI9HqYK3fiIKnflWINYVCsfpR4kexZPBa5zDrcdOOGoxGknJRz2QLcmFnN5LDor/g2poLQTPe+u12mnHkrB+9I2FJN21q9KK5xgm31YjD7aMSTUmkcwiEk9KVxVocl90owoJC7sYd1XJufcMxPN82glgyA4vJgB2tZTJDy2LQwKzX4rqt1QhGU+M+OVnYLUZJBbqsBikc5jH4XEaMBaI4cmIQtdU+BINR+Dx2EUH03ilzmhn0KR79uHiwmg3yrXzlWCsEhONZdA+FMUKxVShI6zzXuFRPxJZvXSqIzHAXstGA7M/groCprA4Zo0seY0OdW6I79A0KRFJy3g2VTvhcZjmfxYoXA1JAxI/0ECMzKWj0RpgqG6FxlMsQ1KXQQBQ1WWs5rFtuRj4ygsxon0THdA4PDN5aZI0uZPMrn6JTKBRrAyV+FEsKL3QGnQbVHgvqymwTFz6J9lziD+XUEEfPjkpdDR2NWetC2nuD6B0K45pt1egaCGFgNCYmjNMdmI36pBw3nZCfPT6Ik51jE/cz0hJNpNBc7cZVG8vhNOuhzxdQ5jChylM55bwZ6QnGUjDpC3jgkWMYC8bkPrfTikQijRP+AVRVOFHuc0j31+QiY35LUTMRLdMA3UMxPH96ZIpvEMULRdy2dWVYX2cHBtoQ6TkFFM5tk40GkRxoh23dTsDdIB1fdpMe25q9smM+Fr2Yii34i3uyTPk4Emf3IRM6tzYkExqB3u6Cdf1epPWOJRNAaa0VGncTDL7m8X0WkKKVtgr4KBSK80AVPCuWBV6YmB7iRftSpLmmw6Ll9oGw+PjIjKx8YeKLF3Ze5Nv7QhgOJmcInxKMxlBUPHN0cEobf225DXs2VyFf0ODJI/349/tP4pkTQxiLplDQzDxvNiCFIgk89MTJCeFDOrv92LG+XATNwHAYwXB8RgqKYzhKRdIkEE2Li/Zk4VOC53a03Y/h4TEk+s9OET4l2AoeO3sI+tQ5scK1KE1gPp9UlV6TQ7Lz0AzhM9mUMXH2APSFpfV14jGeW2OlehQKxfmjxI/isoRpLA4PnQtGblj7MxZOSvHwbDD+wujIaCgBw3gbf12FHW6HBQ880yVzsdjVxUhSW08Qjx7sw4nOgAigKY+l08E/FsVooCh8dAYDDBYrRiIZaWm/fmcdLGY9hkeiyGZzE8fXUOXEVevLJ/5IGb2ik/R0gTTlmAs5nDzZBY3DN+c2hXwOmaGOi+7k0qbCSAfODRuejUx4DJpE0f1aoVAoVgtK/CguSxKp3Lymi0wvmYw6Kcyey3fIYNAhGs/AyMLfcU8gDv184nCfDBwtwfvGQkmJNnG+V78/LvUzJTTaAnoHA9Dp9TDaHMhoDIgkcgjHc9h3YgjBSBK3X9OMa7ZVSY0SB8C+YE8Ddm8on+LJQ4doiq350OQy8A/5kdTPbzuQDo5Am5tWOHwe8Pyy4ZFZo0vTyQQGFu27pFAoFJcCVfOjuCzJLZC+YYqIxc1el1l+Nhv1InKoNfibklZhka2mgNoKu9T71JTbZIRHdpZUSzEaU6ybOdUdgNdlkagOW+U16QJsFiM0RotMUJ/srkwNdfysH2e6g2ipd+EFe+pR6XUWu5amnQNvWkw3Uz6XQ2Gh9vdCHhrpKMOFMzFZfaHtKEL5QCpFpVAoVgdK/CguS4wGraR15koR8brPiMu1W6pwsmtMIip+f2Ki28tpNYow2lHvkagOb3fZTDjbN3uax2UzSqptLJTAia4xSWMdPj0iqas9mytQ5rHBbNLLY85GLpeDTquVYadzCRy25VtMemSyc/sosc3cYrdBn597G6I1WlDQ0RNn3s3mfpxCAXrrwqaWhF5FixmnoVAoFJcKlfZSXJbYTQaUe63zbsPrcWO1A43VxdZvppUolih0UpkcfE4zWutcMJt1SKWzErxgNGc6NHZk6owt7oNjcZmGzn2xWJpdWY8c6EW51w6HSYPaCseUcRiMh9itRjTVuFDlNsPtMMKSGYU1PQxLNgDDpI8njCJxu3nPSWdAY1MNjPHRebczVTYhp7lwp20JGtl9Mol+PjR6A7SuSuW/o1AoVhUq8qO4LNGgIBPO6d3DYaOzsbXZh1NdQZzsGMXmJo8YFcZTWXFApilj/0gETxzuxy276nCyfUwEDT2LIvHMlE8PTdVOmbZO00LWGTntpqJYGod+Qb3+GOqrXTh1dgiN1Xbk8oxK5UUIpdMpbKmz466tJiSf/R9Eh7uQz6ahM9tgqd8A67pdSNuqJRXHguu+4YgIrNmwW01Y3+oDTrXPuTYGVxm0nho5roshq7PA2rAZ0bOHxHNnBhoNLPWbkDXYi74DCoVCsUrQFJbShvUygS20Y2PnWpIvFr1eC4/HhkAgJhcwxdJBB2NdJgZtPg2TyYBUXo+M1iIt0ExfBWNpHGsflbRWKfrA1BHNB2sq7HjkuV5EExm5n94+en1x9AaLm2n257YZsWNDOUxGPQ6dGobJpMfDz/VOjIBoqHRInQ8Lo1lnxEjO5iYv7FaDtNDThJBiiuMsrtpQhkQigZ7+EKKpLCuEpA5m98ZK3FARwuATv4BFBynE5iRz5CnaCtDaPPDc9MdI2GpEY9DX5kTnKPpHojK9vpQS44DTLc0+2ExaGDJhJLtPIBMcLk465x+7wQiTrwaG2k1Ia+aP2Cz2dUxXZ22kH8meU8jFw9JtpsmnobM4YK7bBJQ1I5Vb/kG2lwPqfWL5UWt8ea+x12sTI9vFoCI/ijUJBYchF0Om7zSS/n4gl0bGYkS6oIehrAHGinVI543irnz9tmpEk1lxXaYgspn0sJp06B6OjU9XL/7B0kmZ/jl6o2582nuxgHnQH8PuTRVoqXOJCEqmsugbiYqIYhRoaCwm2xaLposjKX7/XC8CoSTqqx0SUaLuGo2kUea2o3WdRVra+VgUU3sbtQg8+iDymQx0RgMK8SCy8RDy6WJnl1bbj7DhZ/Dc+lokjEVDwl3ry7GxwYt4KiMpKBo4cpgrx3OIQNI5YWi5BuZ0BIV0vLhgRhtyBjvSS/h+lCtoUHDWwbq5DNroIDIhv+TEctks4oNd0Ab9MNVuRNbsVakvhUKxalDiR7EmMebiiLc9I0Z6pNRank/Gkeg+AWM8BGPTLmQKnF5OJ2OdfE3Zh1GHyjIbAuGUpIt6hsIYHotJp1ZNpV3EDaefe1xmdPaHcaYnWJwZVu2E12nGU0f6Jf1kMRskHcboS4XXivue7ITDapB5Ymd7QxKhedMrtkvk6Af3n4DTZkI0noZeXxwnsVUbxdDACKq8VmjTUWSCg1OOM5/PIHp6P6ybrofJl0HGUCkix2LQwjJpEjxvmwzHPWTZ8j657X0ZPohpkEN2pBPxrhNFkTW5/T0WRjY8Btuma5Ex+9TMUYVCsSpQ4kex5qDQyfSfnRA+s5H298PorYHG1TDDtZi1Lsc6x3CmP4zHDvWJ2aHZqJPIzh/esVG6tZ47OSQFyxQx9ZUOVPtsaKl1iTgKi5OzBlvXlYlAouChW/TJzlH8fv+ojLNgRMjlMMlAUqamWBPEYmipRuJA1AKQzhRQU2ZH1n9Cmq5YJ2TMRmc/oUJO5lmlwyOwbr8T8dT5qwhGuGYrzblYdKkwIj0ni63ss6ibfCaFZNcxmDbeiAxUCkyhUKw8Svwo1hz6bAwxf7HuZj5Sgx0wuWqmXHCzhQL2nRzG0GgMqWxeUlUUPyxmZvHx/hMUPUkxP5R0mE4r0R46Kw/4o7hpZ614AT18sFd+jxEf1gz9fn8PKr0W3LizRlJj6XQWLocZLTUujIbiMmOMRn+sB/IHE+IVVGxd18FQ0MPOlFsqibx0T1EAzSJutFrE24/B2rwDMFQuaq1o1JhOJeEPpxCOJOTYfG4L3C4rUsmLV0LMr2cHehZUVZnIGMypECBpO4VCoVhZlPhRrDlYDJxPz97tNJlcMgZNLgVoiy3vjMgMjcZF+DA7w+nsZS4zEqmsRGPKPFbc90QHqnxWSXdREFV6rfCHEiJOKHJoYLhnS6UIH2KzGDA8FpfbqFc49Z2pMEoXg14jnWDXbK2S25gCYySJZomldnrOA9M3NyF54gC0hTzsVjP0Oj0KYgw4Ca0ReqcPib42FHjui+hSZ/3R2V4/HnnyJLo7eyeCMm6vC1fv3oDrtteyChoXgwZ5ETYLwmgXnw+TV6W+FArFiqN8fhSXLxo2vJ+zMKbRHtNTkzbAUCAu7eO7NpajezAsUR1GfarLbGiucUpRcmJc6JCeoYi0wU/eJ8USxdO+E4MiqFg8zagRtwvF0jh4chguuxHVZVYZi8FjON4xJmJo37EhBPQ+WNw+aX2nKILFPe4AdA5r8zak/ANAnseysC2zwaBFe+8ofvyTx9HVcU74kOBYCL97cB8eeqYdWu0iXZrnQNZ3ITfpcTQarRI+CoViVaDEj2LNkddboLct7C5scPqQNxTHVxAKC7azE16ES91RLEimSWEmk4fbYZY6Hg4y5e2MFrGlnXVGHIBKQcPtWPBMQpEU6qscYmbIbbkNf99uMcLtMMFhMUgUqKMvLPU98UR2ik8Q+cn+MLzXvhQWh0eKhRPpPLT6c4XMxspmWDddh9DRx2CpbobG4pjy+9QePL7J88TSqRQefvoUEom5I2TPPnMUw2PzzwpbCK6j0Ve74HY0O9Qs0hFaoVAolhslfhRrjpzWBFP1uvk30mpFNORyk6IS4yKhBIucyz1WESdMfTENFYmnJb3F71mXw4JlFjyzVkZGZbDFXq/FDdurpR6IYyzo5VMajioTvvg4mqKfEKH5IR+XNUUl8TWZM70hfG9/GrUveQOcm6+Fxu6F1l0l7fru6+6G8+oXY/SJnyEfD8Ox9UbkbRXjp6gRz5+BQALHuwI41RtEKJ6Rhi621Xe398y/jrk8Dp/sh8Vy4dlv1kNp3ZXQGs+JzNkwequQM9ov+HEUCoViKVE1P4oVoxixKOpv6YBapA8Mt9N56mGpDiMxMIuTsVYLa9NW5Ky+Ka3dnJtV4bGiI1FMfTHq01DlEAfo0WBCRlkEoymJCFGw0OSQNT2jwSRGw0kRC3WVDjFEzGRyuOvaRpzsCkg9T225DT1DUUmT8TGcNqOcH/fLomqPwySt76wl8s/izqzR6XEyaIXGtAUV2xvg9NmR97N9/BgSz9wn23j23gnLuqsRSWSg0QJ9o3EcOTMyUX9EjmtGRdA1V9thNBqQSs092Z74x6IoXGQLWFbvgK11F6Knn0Mhk57VUdpUvxWpyUJUoVAoVhAlfhSXHIqCTL6AYDgtHVQcku51muSibTXqZvjVzEaGZoZ12+DwVEpXVyEZgdZkhMlRCX15E3IWr4yQmC6aWMfDuh2KFGLQarC52YN4MofqMjssxlGUuS1w2U0yGJWpL87zqi2zQavTYkODB73irJzDNmcZXnbTOjxxuA9D/ihu3V0rRondgxERJBQ621rKkMnmMBZMSN3Py25qxrGzYzjdE5A0nNtpwo6WctgsenQMsJ7IgL6sHnZ7DpqzB1HI5+Dacj1sm6+FrqwRkbxN1m8kmML+44MzBrcyDcUC7NFgHNu2NuO5A23zrqPRqJfzuhgDIK5r1l4Nx9abkfH3ID3G2qScRINMVc3QOCuRwrk0nkKhUKw0SvwoLimsiwknMtJSzsLiEp39xbEO21vKUFduW9S08UxBB1irYGithL6QhtVmRjRV9NWZ61rushqxa1OFFCFTAPFh+v0x9A5F0TscwUtvXIenj/TjVNcYjOORIkal2J5e7rbINs8eK5oQPnawF6+4pRXXbquSGqDnz/hxvH1UfIQ048XQTx2BOEy31rlR4bbIVPfrtlbilt21CEeSMgm+fziKYLhYe8PD9voq4F5XDX11tagZjdmOVMGAUoCHeoeT6OeaWE9SmSyMRjOcDou0uM/F9k01EsW6WCiAUnondLXbYa5aD00hL0NWswX9DJ8lhUKhWGmU+FFcUhKZHJ4+OiADQKfD9NOBU8MwGmpQ6TYv+qJJJ2PoLdBZbNJOPR/cZ12ZDa6r6ySCc5QDS1M5bGz0oLHKidFgDDvWl4sDMzuyTAYtPE4LKn02GWmx//n+KR1Lv9vXDbtFL4LnycMDsz7mowf7cM2WKhmxcbwziNEQ/XZ02Nzkk0hRdYUNkUha0mksqF5f70EmXUBa6x5XeVP3F0vlZB/zYTYZEE1lUFnhmVP81NRXo77SiUxm6cQJU4OAsdiQJgJUCR+FQrH6UOJHcclggS4FxGzCZ3IEoa17DOWu6kU0dC8eGgzyusyUEfdrN+nRXO1ER39IvHjiyTT2nxyUgai8v6HahQqvRdJWPcMRPHKgT4aXzjzePE51BbBlnU/qeugKPRmKp7+6exueOjqAjoEQIrFiMTXTZg/u68bVmypx3bYqKbiuq7KjzGVFBYXfPFGdbC63YMt4NluQzrWKuma0d/K88jOEz6tevAs2qwmZ+cuCFAqF4rJDiR/FJYPREdbDLASjGoxuTJ/FdWFoEIqn0TkQRiiWksgKu7doXjgWSeH50/4Zv0FdwZQc63SY+jrZOQa7xTCr+KHAGA4mYOkPY0uzF0NjcSmaZqcYTQZfen0TjrUXx2Vwiju7wPRsS5fusTwOnByWqe90frZaDGipcSK3wCRknVY7Pg9+fvR6PbZvqER12Z3S1eUPRKVrbdvGGon4KOGjUCiuVJT4UVwyGFUpFRrPB6MaFAa4yDlQFAfHu8ZwpicwJVLC+h1697Q2eKWweXLt0eQIlN1ulJQYC5MpgmaDXj5sdae5Iae9s36IQslspKFfHnabEU8dGRD/n3Q2Jx1nLKQ2UMBodHJcx9pHcf32arT3BtBc5YRJN3/Mi91oHpcFYwukvhjR0kKPMrcDf/CCrdLVxeJm1vgw1XUphI/MYWM0bVz0qcnuCoViNaDEj+KSwdQToxyxRVww9eMt8BcK98HBpae7A7Pez24sRmPYvbXv+NQp6oRCxusyS6SEwofCbToOm0Eu5nR0dliNIkYolEqpr/X1Limklv2ls1LnYzaxjT6PeCojwoeCgLf1Dkdlsjw9hkx2TqKfG51Gg02NHjx9NDmnmGCnGYexlu5PJErt8Msw2XQW+KjBWBrt/WGEIkkpdK/0WWWKvcNSNJdUKBSKlUKJH8Ulgxf6phoXAqeG592OXVWMblzMLAQOLW3vDc67jWa8yJqdWmPhqd47jNJEYmk017oQjqUkPTXxexpIO/z2Vp/U1nC6O4easvV8MmajQWp5uD1TVRajHsFISgRJ8cwKyEAjM8TCsTR2tJRJbY4BaZniDq0eOY1xQsAUoyh5EWJ8/N2bKsXnh+cwGZ4PZ43ZdWmJ9hT0JuQKl260RDHiFsCZ7sCU1BwjbO29IezeVIFan011gSkUihVDiR/FJYMX8WqfFe1zpJoIXZM3NnrBqVwXc2mMp7ISRZkPRqEocsqYQpomfghTWRajDtduq5YxEIzeUICwPocC7XjnWNEHqFBAIpXBDTtqJAX2/JkRERo8xw0NbolyOJ3Fc2bajy3qJQFUTAdpxUyx3x/GjjozEsf3o5DLQWswwlTRCIOnFuG8ET0DUfQMhiW6REfp9Q1u3LyrDsFwEoFwUlJaNWU2eI1paIYOIx7kceShs9jFbwf2CmQWMxH1IuD6dA1F54y48fwpJB276+CgwFUoFIoVYFHvPv39/ee105qamgs9HsVljkmvle6mw2f90ill0OuL87KyxdoapqF8TtNFp0VmS1NNhwLEYTeipc6N4UBc0lUUMkzRUPSw02vn+nKJWMXiaTz0XK+YMfLQ/uuh05LGa63ziJszhVHXQAQepwlXb6rA/hPD6B6K4A9uahYX6Vgii3Q2L3PBJh8ZRZLZQj8hCx576gQ2e+uRi0Zk9EYsFkc0GIDF1YVM9U6caA9PePvYLEA0nkU2l4DPbZbH0GsKyI+0I3bqME9OzkOHLAqJMSTHemCsboGx8Sqk8+fSakzZ0WuIHWhUYk6rAflpBddWqxH5iB+FdBrhhA4mZwWy07aRURuZvBRrn+oJyGNPjuxQ5HnYfWbNQa8FEpEQPI5yZOnJNAn6LeqycRFt0BqQ05mviDohrU6DZKZoYSA1ZjrtjA49hUJxicXP7bffLm9mi+XEiRMXdDD33nsvHn/8cXz/+9+fsq+PfexjOHr0KLxeL974xjfiDW94w8T9vIB+6Utfwo9//GNEIhHs3bsXH/zgB1FfX39Bx6BYXng9pIszTf8YOenqDUoXWJnTgs3NXpS55m/zXiys0+EFeaELp8NiRGOlA6+8tQW9IzEZR2Ex6dBc40aZ2wwLC5dzwK1X1Uo7+0gwid881YGrNlRIsbNWU0AvHaMzeZT7rJLe4nlsW1cmtTwb6NmzN48f/+6UiIHpR8M/qxdf14i2030yRyxKT554Bm1dAUmFURRazX5s3Aa86Jqb8PChQWnRT2cLeOb4oESCdDot1jd48AfbLUDHYWjzeeg1WRRiAaQDg8gn4/JAmaF2OPU6mOt3IZnVylywY12jONg2gkA4Ab1Oh8ZqJ3ZvrEC11wKdtgB9MoDw4WMInDyARCgAvckET/NmuDZeDZQ1IJMqIE7hNxgR5+yqMjsOnx6R+iW2/jO6xhTmxrI88v4ziJ8dQCqbQdRqRTa3EcaKRmR0Don06ZOjSA92IBkaEWdrcYiuaIDRV4+M1nJZToTnazSSyIrlwuBYDHqDHvlsDjXldjRVOUWEq/SgQrFC4ufjH//4hPgJhUL4zGc+g+uvvx4veclLUF5ejmAwiIceeggPP/ww/uEf/uGCDuQHP/gB7rnnHuzZs2fitkAggL/8y78U8fWRj3wEhw4dkv9tNhte85rXyDZf+cpX8MMf/hCf/OQnUVVVhU9/+tP4q7/6K/ziF7+A0Th/4ahiBdAUC5GPni2mhlgHQ1LpDA6eHMKg34arN1ZItOVisJv1kppi6zk7uhjhYUqNj5lKZSXNRa8dzur60W/b0DUYlloZp82A4UAezxwZEPHyiltaUOW14JFn+2RSO1Np/J9Cpb0viFA0LZGf0hR4YtRr8JIbmjliTC5qTE/9wU3r8OC+Lgz4i5/sSaXHgluvZvpHi9NtQSAeQDbrxMETw0inWQ0EMUEcCSUw/MRR7LQ345bdjXjsUD9+90zXlNLl2ngKpw6dhjkWQnOVDdmhDqQDQ1PWJJ8ZQ+i538BtsKDg3YBfPNEtnXDnyOLwmREc7xzFq25eh61lGfQ8+B8IdE+anxbRIOofwuDR/Wh96euAqs147FDfxHwxfhhhhGssnJBaqQ2NHmz2JhE8+iyy6XOpzmQ+i3jPKWT9vbBtuhb5ZBTR0wdRyJ2bU5bLZhDvPAa9vw+WDdcgrbWd12vAYNBClwpCk01LgVfB5EQarKHCqhE+I+Eknj06KJE3/mzRaJFIZMRegWKSXYBMDyr9o1CsgPh59atfPfH92972Ntx9993453/+5ynbvPzlL5cIza9//Wu89rWvXfQBDA0N4UMf+hCeeeYZNDU1TbnvP//zP2EwGPDRj35UPEtaWlrQ1dWFr3/96yJ+0uk0vv3tb+Pv//7vcdttt8nvfO5zn8PNN9+MBx54AC972csWfRyKSwM7gI6d9U+8mU//VDvgj+GsI4wtjZ6LCvszksBIDbue2H6+//iQTGxnm3mFzyYRGZfDKIKFwodQEE2u/WHd0K+e7MArb25FIpmVQaeHTgdFvDA9Vurqohs0BRY/H7B2h07NHHjKURcjgXix+NhixKtv2yDpMQoFzvJi+zvHZRw/3o3k2CCv9jDoNNCOy5rCeNcZRRgLp4PDQzKs9enD/TN6tspsQHJ4BKFoDB5zAfZ4cXjrdLKhUWTDfowlTOidw3OJKS2XBRg98LupwmcSmUQUnQ/+F1pe/eYpg1X5fFrGj1eGvJqzCLcdmCJ8CCfcM0qWS8aRPrMPsDinCJ8pxxMNIt19DLp1e2fMa5sLSz6M9NljiHUcRSYahFajhbG8FtbW3YBvHVL5la83SmSK9U+ScpwFmoEePDWCG3dU4+J6HxUKxXTO+2/qiSeekIjPbFCAHDx48Lz2d+zYMRE4P//5z7Fz584p9+3fvx/XXHONCJ8S1113HTo7O+H3+3Hy5EnEYjGJQpVwOp3YsmUL9u3bd76nplhm+Mm2oy8kwmE+ugZCUodyMUgtjVGHPn9MhAiLjVkvw6jEoD+Gw6eHwbISui7PRyCcQtdQGOUei0gqHjtb1ieLJKbteKFnuzsZGI1LVIniyWEzoWc4KlPhv3ffcekIoyg6cGIYD+7rQVt3CLl4BPlMBlWVHhgSo1IDVSLHVFmhIKKNkaKnjw2MDyKdipge5gtgIG14eAwFq3fq/TodtHYv8t4GZJw1UsN09aayWf2L+NdWZYhh+OTzU45lOvHQGJL9Z7BnS9XEbeyQo78QsZkNcBTCiIUjM9y6PU6zyDtGlFPDXfLakFH1c8Aolj69sEEmseZDiO77JcKHHkYm5BdRmc+mkRzowNjjP0G2/VmYtBc/z+xi4LLyNTSf2zmhfUJ4FnNNhUJxcZz3xx+Px4PDhw/jxhtvnHHf008/jcrKyvPaH1Na/JqNwcFBbNiwYcptFRUV8v/AwIDcT6o5AHLaNqX7LhQWgi4VrMmY/P+VCoVHIJosXujmga3f7MKymowXvMa8uDzfPop0OovGKocU47J+hhdzXvBZi8IZY6xx6RyIzFobxKPk7zB1tXtDOSLxDDx2E2KprLSXTz4LCiKLWY9jZ0flf84Na+sOoLrMBpNRKxe5Ha1lGBiNSRSJYz4o0CiYtlZYUVWek/sL0W4RTZOhsOKa2dweHH2kV0wUp69gOKVBldOJzGgE0XAUOZ8XJa9EjdmGlLlcBFg6moGuO4jf7+9GzaatUrvE9N1o6JyYq6mwIxMaQSaZgJa5u7nEagGI9Z5B5c3XTDynTAM217gk3ciIVSbYL887o1wlnFajnIPoHQ2QS0aRjwWhN5mRT89h3MjCq1QUevP4vLM54Oek5JHnRFDNrtsKiBx7HGUVDdA7G7BScL1YZD/5b6H0/fS/D3bylbMWTuW+Lhr1Xrz86NbIGp+3+PmjP/ojfPnLX0YymZRID8UQozD3338//uM//gPvf//7l+zg+BjT63ZMJpP8n0qlkEgU3yhn24a1SRcK33w8nvOrL1gMTiejB1cuTDuZTAbkCrOLHwoIl80owjOVLSCZY4eQSS6i57vGdHHm+IoCtMjkchKxMRh0UpvDNnE+ViGcRN9wFHXldonWzIZ2PEJAs0N/KIWNTT4cahsuioJx6BbtsJrQMxQVkbVzg1cKkXmB50U/HMvIY7KY22zUY5T1MPE0vA4zzCYdGpqcWO9MwBrsQCw6+3G4y3yIaGwixgDDlMfn63UwlMbO9S3IjvaJamNEhbdrjBbEzOXoHwxKPY573RacHo4hm8mheyAM/5kQbtlVR9kiBdZET6Eyfp0tPlPTn6/SzwURRjqNFhbLub/BQDSFm66qk7ofg794HHq9TuqknHaTeBRNRJzyeaR0Wnmj1Bm0KOjmjsjwtWNa4O8yPdqHWP+p4jnMQ6r7KNzXt0KrX97W//kwGvVT1m3yeU752WyA2229hEd2+XOlvxdfClb7Gp+3+HnLW94iXVXf+ta3pPaG8BOJ2WzGO9/5TvzZn/3Zkh0c98m6nslQ9BCr1Sr3E25T+r60jcVy4QvPKEA4PPtF6ELgGztfCOFw4spuX9UAZoMWo4GpzylhsTEviBQWbPdtrHJJ4bDXacGmJo+kfOYz/pm+xv5QEmd6gghEknJRZxqKBc+cxcV2dYogpsWYAmP0pygqZtmvVoO6Crt0gQXDCdgq7GioYrQoLPskLHhmcW80kUZthQ0ep1G25zGVtmutd8vEetYN/emdm7BrQ0yiLaz3GImmUamJI+4PSHcPj41mhiWsNivMjdtwdiiJdTVumR1GISNLqoFEyFjE3R5xoLWhFYmOBDS5ovtzwezFwHAYuVwOFk85sq46BNtGYLRaEMzQ6TojqbhtrWUTk+J7h0IwXF0Bnd6IQo4pl8kLP2mqmAawVDdhJMQPIueeU34miUZTqCqzoa6Z3VwhqfEx6LVybuxmSo6vN0VaXm8GzE4kRgdFDM2KVgejxoR4YH5/cGMsglR4fnNLkvT3Ix4cQ0Znx0rA5422ApPXjSKRwieVykyJRLI7MrDAeSsWh3ovvrzX2Om0LDridN7ih29W73vf+/DWt75Vuq8YYWH0Z9euXSJIlhJ2bw0PT3UDLv3M9Fo2m524raHhXAibP2/cuPGiHnu6j8lSwBfCcux3LcF6EBbaTr6cUjxotBo8crBH/HkoeNjtxe9ZMMy6h6s3V6LWZ12w64VrzHqhodG4pBUofEreOEy/8DYW49KRmREmp80kxzJXSoEjLFpq3Xhu3L2Zbe0bGr140TUNeProoAgepuhYwFxfWSHRnq6BsKR9EumsPN92m0Fqh2RivEYjXTw/feQMwtG0XPDsVgOyLV5cXbsTibFONNVkcKZnDDqDAb6aWtgaNuIXh6LQa/vx8lta8LNHz8ixUEywG0wERaGAI11hWDa04poby2E4+wjSOgPiOR00OiM89RtE+Bw73gUttLCXNaOzPyvnzm4yCkMOYmU6L50BRrJ2lG/chsFjB+Zca5PNDlv9Rvxy30wfMF68ewYjqGhyosxhgzZTvMjPfDMswFTeIGtDUTQXRpcPGYN9wb8fxkwWkx3iNnxZrOTfo89plsggX4/T164kfqRT0WK44t83lhr1Xrz8rPY1vuCWB7abs82dFw0WKjP6stTih549P/rRj+RTq06nm6gram5uhs/ng8PhgN1ul06xkvgJh8M4fvw4Xv/61+Nyo1TDsJZT/z67WcTDqa6xids8LjMef75fLoBWk0GiI5PFCC/sx9r98LnqYJpD1ZfWhmKC5oKlqExJ+ExPv7HWJpNJ4rrt1egbLhbS2i16iQzxYsSoDOuC7rq2GT6HSS5SjNKwFT6ZzGBdrUPEE6NHFDQ0L6SI2H9iECaDHskMO7eKRnX8XUZYaIpoZ+t6MCEiiWkvwsd7/PAQeqocuH7zDtQ1AK0tSYTjBfRFtDi6nwXbaWxvLcPGRg+u314j3WuS1hqXkXSJpotQLKOFY912aHUJWPMF5OCAcSSM9sEgxjrPyLpK15PTDetYSCbdk0CEw14NIn5YcjIcBXbseSHiI4MID88UNzqDCc23vxoZawVMhm5ZG6NRC7OBs8tyUrdFcWb3+OD27kK0/TDyqZn1PFqjCabWPcgnogAjP6xCn/5YZptEvlL5RXyiM9qhs7mQi4Xm/XsxldUir7cB2ZX7Y7IYtNi5oVyey9kG/jI1u2vc9kHV+ygUq0D8/OxnP8O//uu/YmRkRN74aTD4xS9+Ubq2ePtS+euwnf2b3/wm/umf/km8e1ho/Z3vfEe8fggfhyKHvkM0QKytrRWfH0aM7rzzTlwOSEFogRfsjFy0mWpwy6dBDofEGqSATQ1uuOxGnO0NyVgIuh9TPJR7rHJuE0PNNRqJnrCVuhBKoX80juZqO7T81J6ftDaJDKJjGZiDKTEoLLaua9BY5UQgMjLrUTAdVldhQ4XHiqs2lOH6nbUSieGoCLNZL/U5PBaaHGoKwMtuWYfRcEpqiUKxNFKZAra3lCGTyeKpI0M41TWK63fUyv5Y+1OcTM/OML1EVfh3wkLfMo8FXX1BpJJpmKx0t6bRoh4ajQU9wxFUeC0YjZlw1YZadHeOQW/K4UXXNqLSY0NTrQsWHXD71XWSinu+bUTEC9u4GXna0uwTh+wCU0SNO5Ad6ULH6SBOHmO7ugYGmwMmXxU0Nh8lhaQTGaEaHotL3Q4vsjSf3LO5Ek1VDhT0XjT9wV8gdOo5+E8eRDxYNDksa9kMz9broCtvRiavxQuvbUQ4HJF6pVg8BYvZBJfLJuLOmAkjH0/DXtssF/BUaAzpoB9anR5GbyWMVa3ImNzQmL2wbzYj1X8G2fBYcQK90QRjWQ0MlS1I6+3zpj1LZEwe2Ju3IHr4YRSyxZSdVm+kWkMe4/PNdHoRU4kVFD6Ex1LtteKmq2pxuicgry2+9Jn+rfJZi+7hFv0V4XCtUKx68XPfffdJ2usVr3gFXvCCF+Dd73633P6iF71IRAlNB9/1rnctycExukPxQ/+gV73qVRJpeu973yvfl3jHO94h6a8PfOADUiDNaBHrkSjE1jr8ZB+IpXHktF+KZEsf/liHUuWzSSSAnx7X2odCvsFzsCXf+DP5Ao52jEndDT1u+EZPUZPM5KVehh1KpTd/pofO9ppx9aZKlDlMUlh7+IxfalVkJIXFiAq3GWd6QyJc2GnF+9hqPh1GZPZuroLZqMXZ3jB++2yXdH0xeqIZr0G6cUctbthRDaNGg30nhvDrJztlmxIUT6+8tVUGdaayOQwF4tjRWi4dX5nx8Rp8rphOYuF2Y40TdpMW7d3DciE3wIBULCZ1HlanE+vrXJKGY2QoNS76iD+QkHEH1T4LbDRrLAA7mr2oKbehfySGVConRd1MD/5+XwS1FXapMRpK18PXUgN9tFgknMjpMJbRwZNj7Q1g0GrE3brKa5UZYVaDTkQUGx255ul0ATBVwHXdy+DcfI20jGs0WmgdPqRyLEovFoQP9g7h2LEziASL6Uy73YJd630YO9UNmy4zIdIZvTW6vfDsuAlZrQk5vR0pPrfy/GqRt1XBuL4C5mwMGrb4a/XI6m1I8/5FvMYZHDYlBpH3VEPvLEOi/dC515zZBr3dg7zBCufO25BzVAEr2+0u0J7AbTXgmk2VSHKshVEvgtqs105JfykUiqVFUzjPeCpFz+7du/HhD39Y0lFbt27Ff//3f8v/3/jGN8SY8Le//S3WMrwwjo0tXYEh0yPsHmPR4vnkQKNMhxzqkxTCbNAr5Ybt1XIRW6swFXSkfUzawktQOBzrGJ0xmHTvlkqZik6RdPdt6/Hs0QExASTijmsxosxlwiMHesEsAqNL9ZUOERFneunGnBJjvZoKGzbWe2ToaCCaxg/uP4H0tBlTJV59aws8Lgs+/6MDss/psOnqvX++F/uOD2L/iSG86rZWSZlxsGfvcFSiPyywvuu6JtjNWvz4gWNSDM1uLZdNL+JH9qPRYNOWZsSSeYmGMdrT2Te1Y5ERgRt31sjFMhDL4MnDfbMedzqXl4vm+noOVQUOnRmRqEIJumrT2boUYfO5LCLydOf5OtbpNTjb3ocDTx8uzuKSbYqpGraTs1W+orocZT73FIGud3pg2XAd0jjXpLAU2LJjCD787+IJ5L72ZcjHQ4i3H0QmMCw+R+a6TXBsvxU5D00OFzrbS8+Fvk8oFo9a48t7jb1e26ILns+7Eb+jo0OiPLPB2h86NisuHl7M27qDcwqfkv8HTfwW8s1ZzbDOh1GsyWJoOJiYIXwoDphSYlcVa2jo0VOq65kMa1YqvbaiyWAyK1GY4bEYNnIC+lW1uH57lbTTDwcS0nb+4DPdknKbC384WWxt17G+pih2GM3h35esegE4cGJQZnmxjoiip6M/KELlmm1VIlZYp5NKJJBNxFBT7pD9GmWG07lCV7fbJj/HEik5fkZzJtrVx4tXeE4nOwOS7zvRMTqr8OG2Y6Fkscssm5f1YqSMReUlmEpkITi3Ze3Rrk3l0F/ASygZT+D44bYJ4UPKypzIDp4R4SPrNzyGTGbqc5kNB5APDCzp69Zo1CHVfQTJoS7k00mMPfZfiPe0wbr+WnhveS3c178aOmclksNdkLCXQqG4otFfSCrq7Nmzs5oc8nber7h4aKQ34J+ZrplOZ38I9eX2c3UyaxCXjUXOFklR0SeHNSjT4dRyRn0oljie4tljgzKiglGg6YKQKR9GXSh+HIySRFIToyhKQuqOaxqkVojF0XOZGLMVOZnKSaprXY1rwgyRwVKmf/TSim9Ce38YZrMBd17bIDU0HEr5m6c7pYaHdS+s3+hoOwt9IYubrtkpx8gC11QsDbvNDK/LLCKkt38ERptdZoHRDJHRGmY9WMdkNbF2SCNCjqlQpsZmgy3yUhvGv8feENbVODE8GsONO2rk2FgPRdGk10HGfzRU2MV+4HxTpxSB/tEwErGpz1WN14zokb6Jn/O5HCKRBHw+ztQ69yA0ITR765G/8J6LKejTAQTPTnWXTw93ydeU7Rxe+Jp3AXr1PqVQXMmc9zvPS1/6UnzhC18QF+Vbb71VbuMnSE5dZ72Pmqe1NDBdUhqAOR+MdPBCqltCR+pLDQttWTfzzNFB+MOJGREd1qSwmPfQqWJUkV1U7H4qjsmYqly4ZnR1vnpTBZ4/PSIdTCUxQBhtYCSEhcyhCIuF5y4nobkiIyRMQzmsFkmxTRYJFE0mg02ic6y9YcSFKVOKnT+4sXlinlg2a0Q2kYA/FMHx54/jruvW41jbIFIOIM8J54ERJHJOec53bKjCSCCJk5O64UrnXOG1iiBjRGeuWhDeXOpwkw4zrVa6yThWhNGfna3lIlyYdmuudkCvKUaWGHGT9u98flFCiL8ficwUqXwZ5sbb2osb6sQKgNvn6dI8vm9GZ0APIe3SiB9NJoVsdGFj02wsAA0fd+VHeykUihXkvN8CWMzc1tYm/5dcZv/8z/8c8XhcJrLT6FBx8TA6wYvrQhcipmDWctqL8BztJh1u2lmNHn/R/I+igwMy19W6pGX6+dPDctEvbl+QIuIZxsPjjAQS8LktUjfDFuxBv1W6opjuaqpxim8Ku6p6h+Pz1tEyX83H0et0Ei2Z/lzwZw4qZUsyW97zuaKP0PBzcek040DTroEIbBYdtHkn6qtd2NRaA6MhL4XRnUNhBMMpuD0u+JwmXONzo3MgijP90VkjOhz6qq90iBCaCy4JxQzXiOvGAu4SXNOSizMHsJJ4OidRJkajmCuvLbfD66AJZFEMzfecsTh3xu3g61aLgkaLvM4o9VvJrAZDYzHpfGMUi4KMNTjzzfI6b7Q6aA2mBWuYtUbr0j6uQqG4MsQP28vZgcUBp0899ZSYHNJvhwNIGQkq1ScoLg46/Za5LHOmN0pUl9thGu8MWcvIxVSnxcY6F8LbqtE5EJIUFw0DJ0duCAdCMhJkNuikW4aFzRRKRpMBAc5uiqWlqJgdW9duqigKl/FUDR+n5L/DYaXcpjSkdPorl91kOzdUiPBg7dBsMDXF+VgNlXaZ50UTR+6bnV+9IxFU+2yoLXNgx3YHRv1jeHz/afQPBESwcpCpy2kXj576Ci8iWeAMi5w1s9ekMNLFPy+m8njOjH5Nx6DXSIqMkZyrNpRDW+D6mKTYezLr6z3oGY7heLt/SoSR6+1ymLCHdUK0U5jjZcVzrKz0QqfXIzepdskfycBZUY1RfwAxPmYBqKo0iON2UbTqUFNmh7euBjmdebzT6+LJmn2wNGxG5sjs1gYlrPUbkefQ19kHyCsUiiuECw7+suaHXxwlwbbyybOGFBcPgznrGzwSBZlrCjovJE1VzjUvfCaTzeTFw+aRAz1zFnsPjyXwkpua0d0XgsthxuBoDANjEYl0lLstaKpxIRThiAynRG8mAmOFosApuQz7XCaphfnF4+0iohilKAkMevNQoDACx9qiJ58fmPVYKBxa6lyoq3KgeygKf7Rojri5ySfpyLbuMak/2tW6BfseOynCRz4fFICBwTHkB4qiqnswjBfesRc+t23KkNHJ8FhK58TXxnPHh2ZErlg7dOcONxAdhi98CJFoCh67F5r6GnSH9TKKwu0wygvs8KmhWcUN04EsKOfML9M8xWRsaW9oqUfHqY6J2wZH4/A1bkGs52ERO26XbaJOijClORTKwOupW9LXLX2XrK27ET39HPLJ2Ts1tQYjrJuuQyqvcl4KxZXOBb0LtLe3S93Pk08+iWg0KiaH//Vf/4V169ZJCkxx8fBaUeG2YMeGchw945/hAMtIB2tX7Gbdkvr8yIVZUxwtwQJb7vtC3GUpHMSehYMv+f0sFzp26DAqQ8FhMumQSRXFDud4vfKWVtz3RAcik2YfEZtZL8XK66ociMbSePDZLnksZsH4f/9IVETQy25qgdOim3NUFMmmcrh+e7VMXH/icJ+k2Ogwnc3n0dEflgGc12ytlP2+YE89HjvQI6aK584RuOvaJjRUOnDgxJA8Ns+FkQ0WbdttelyzpUoECvWM3lUOlyuKSDgqj8FlLXaQaeDyebH/5Ahu3FmLR57rlfRU8aGKIzH4XOzaUCHryFRenc8OzRbIdHieI0UFvX42uZJItB+Ey4wJ/yNNdBQafzvWN2yBraoajTU+SSPO97RyTSgqm6sc8ph2qwaZVBypSE6Ku6PRPHI5DXbtWC9DUns7e+W5TuS0ODQIrN+yG6n+NlnDYPRct5fRaoVtw9U4G9Chpab4OlsqMq56lN32Jxh74ifIRs5ZJ8hzZbHDe8PdyPtakJ/afLYq4IdHgzaHXDws1hU0s57vtatQKC6x+Dlx4oQML2VXF4ubOcm9ZGD28Y9/XMZNTDYhVFwEhQKaq+wSzegbYfdPXD7909yObd8ceLiUn56z+QL84ZS0arOQmsMoGUWhceBCNSAleCGXOhJ/TLqd5MJpMWBdrRtuu1G8FfR6YCScwYkTw9KyzSJbpu+u3liJKq8Z+WwerTV2/PlLN0vLdkd/SB6bRogttS54HEYM+OPo6BtDk0+PeGAUyWhchJvL4YLZ6cax9hF4HXVSSzTfsbZ3BnD9jmrpfHr2+KCsscVkwN23tKK+yi6Fwlzz23bX4sYd1TKclF1nDpsR126pkiLo+x4/i6pyO+68rlGGjh5vH5MiaWfKhPoKJ7a1+PD7fT0YjhRQ1rwe7kQUscCYdEIZLGbY3D6kNUa09QRlvVn8HUtm5LGpecvdZjRUOxGLZSSdRx+NQDyNXn8MA6MJESo0UbxlgwW5Mwfhduth1GngMmSRpKNyPF4cKtsbwTVXvwghY7mcw0L0DofRWqHHmD+EZ0/QxDAEvcGElo3NqK2rgMXhRDKpx969W9C6vh7tZ3sRyeowxmOsWY/qdc2ID/fAYQlKnY3eV4uU0YPjY4AuGERduU2K3ZcKdtTnK7ag7CXlyAy1I9V3WsSjsaIZxtr1SFsqZZvVBAW0KRdBbqgbse5jiOfSgNECc9MOaN01SGD+KfYKheISmRy+8Y1vlIvVt7/9bfl527ZtEyaH/+f//B/p+vrpT3+KtcxqMTmcTMnvhRf45XB+TWXzePbEkFxcZzNTvGZLJSwL+KPwGEejKWlDT4y7E0+G4mXPpnK09Ybxw9+clDERk2Hn0UtubMbNO6tlhIXcpmf6id8Vo0dcP9711NEB9HZ0Ijg4ON69xMJvLbIcjqnRwltbhw0b12FHixf5OaILSU5UDyXx+OF+HDw1DI/DLBEWLi0LpDl4kg7OFDhPHu4XJ/Frt9XCYtJKmoXdVL/b1yNppBt21OK3z3ajbyQis734PPGyHk9l8dIbmlFbbsOjB3sRjLJ7LCuFxTQbpOdO72AYNqtRurFYi3Oi3Y8NTR647GbZTzSeQVvnGKxWI7Y0e2Wq/H/9rk0iQITF1pUeK3bZB2GN9qLKawEifmTCoxOzv0oYPFXArlfhvoNj84pZPtN3XF2OoweOonP/0zPud1TX4baX3gG71yfjPeosCRhjQ9D66vDUoW4MD/rFt6iuxguH2w2Nw4dwIjfxurCa9bhtV52kCJcDg0Enjs+l1016Hr+slYKvW3PKj9Czv0B6dLCYbjXoJJLG58Zc0wLH7rsQ17pW+lAvG5TJ4fKjXyMmh+cd+eEk989+9rPQs9Axl5vRBv/LX/7yfHepWARFsbM8tT3c68G2kVmFD2En0IFTI7huW9W8LsCM+MwlfEjvQBg1FQ78+/0nZFbZdLKFAn71eLuIkKs3cG5WbtY/ngS9gAYGERgckIPny5Dt3XzNS5t3IYfR3h4MOh3YUO+SQurZ4Gin58/48dzJYfmZozQmMzAaxy8fb8crb2mR7qieoaSMwSgJDg5oDcfTuOmqGjx2qE+mtcvxpbLFDrxCQdJ6R8745TZGvx7aX6xlCkXHRGhxnAWPg2kuFl9X+KzQasulyPvE0QFJfbidJmxtLZN1pUnib57qmBA+hPvzWgsIDfRiIBSSkSe2WEgef/orhu7HtnQQulwSWe3cDss7N5Wh7fhZdB56btb7IwO9eOT+3+PFd98JjzGN8MlnkIpF4dpgwGDfUFGEAugbGIMzHIXBEYPGWTmlXo1vkssFXzurLcozHWM+jshzvxHhMxvJ/rPQmh6B+ao/QCqnjBkViqXkvN99TCaTzNCajWAwuGRDTRWXDpr9sRV5PvyBuFzo54IXe5rozSV8yPpGj0RYwrG5r0qUOo8/34tocp5P6vkswiPF+VhzbpLLIxoYnbP7UOaHpXN47uT8juQUNOyq4vBTXrBL8NMFI4Ss9zHodVIjNPmRqH3YJUYoZFgDxPqXyYHWbK5Q9GiiY7ROIxE2drAxqsWZZXSh9ocSONMTxO+f64XVakA0np5o+Z8M00fsuqLbct9wCBqre/YTKhSgzybgNmYlnTcXHmMOHceOyzyvuQj1dWNoKIiGcosIH5IPDaO6yjOlIJznmUuE4bYVW+k5WmNzs2/Zoj5rhvAwksPd826S6GmDLu6/ZIekUFwpnPe7Dzu8WOw8OHju0wovMLFYTFJhN9xww1Ifo2IZEdESiC9Yz8O7B0ZicpGei1LkYy5sNhOOd4wuWEDd2R9GOD53TYqukEUhO7cQK0EzO0NhdqHF6z4nu88WgZrYZnz8xonOUVS4rbhjTz2u3Vol09z5xQnq9VUOnO4JIpfPT9jHlFaoVLDKzjEKINZRTR7lQXgbxQ9TYNtayvDTR86ID1FztVPMEiu9VunoYwfc2Z6gzECjBcJ0qCeNFouIm1AojvQcUR0NJ5xnkthQY5UC29mwW4yIRuPI0DRwgeeq/XQn3F7nxM/x0WFsaHDJsNYSJrMJ6za0iOP2gbZhqZs6fGYEJ3uCSOXyczpsX87IOI5+1iTNDyfTZ0b7Fh3KVygUi+O8/6Le8573iKHhi1/8Yil8pvD55Cc/KT8PDAzgf//v/32+u1SsMFnmXRZBsUV89isVL/QlZ+G5YP3JbFGLGfsad7ieC4s+j7pq74R4Y0SGc7poSMgi7VJEg8XDunkMXRiRWEzBLa//LIRmATLTKfRg4v/0E5LvmeKRw9XMWtfBmV+dg2Fxm6bzNGeTTewbBUnzvfTGZpzqGsNYOCXnztlmOnZ5aTVSc0SfHh7vic4xlHusMx6n25+EpXqdfE8hNhem8jqkY1H4MoPYu6VKjm0yFGL1VTaGzkQkLUQ2mwEK5847l80gN3AGN+xqhNfrhM1mRlVjAx490IvDp4eRyXLQqxnxREa6GB9/vh9RmWOGKwyNCJvFwO2uvPVRKJaX8675qa6uxs9+9jN85zvfwdNPP42GhgYRQ+z8+su//EsZe6FYOzAKQ8O8xeC0m+aM2mh1kIJd1gfN/WDF4aQjgZljESbD7jDW1My9H8ig0rFgFOFIQjqjKMyKLeFasQEo8zlR6zGygnTW9Bj1AedusZbnXFv5TKwWg0Ra4uNt+IxeTIZT42PJLDTjNT7jh0efY7lgcUgpo1is2aI4YzHy3be2iB8OW9O5HvxVFk9zFhfFlNtuQjCSnHFMXHt2dplMM/9sWRTtL7jgrKhCemwA2lm8jrUmK4zVLUgM90NndaDGZ4HLaZPC8zAn3uu0MmPNbtYjEsgXw2MLRH48Xk9xbMUkkpEQjNnj2NNUC2PVZjx+eAgOhxnVbjcMTIuLBUJxWwrIQ20juGFb1VyG3ZclbBrRu8sXta3O6UVG9b0rFCvv8+PxePDud797aY9EsSLwIsSuJgoGFuXOBaMVvFDPOVMqV0BzjQvdA+E5hQRb6Omrw9TXfOzaWAGfw4TcHFEirdWBMlMWuzdVwuiphNXlGfff0UCnyWN0cBCWTBBupxkFjQmYNHV8Mh6nUY65vT8kkQi2+k88hkYDs0knbspMbx0+PbM2iEJkNJDA3s2VOHLWL+aLJVjM2+B1yPoO+mOSxmKB8wPPdMtoi0wui77hmKS9WGjOVntGRNwOk9T1zLaG9PKpLrNJPdNs7D8bwU2brkJLrQ/GUNu5mJdGC6O3EuaGrUgFR1HI52CqbEK2oIdBW0CZw4QKl/mcp1OhAK/LgrKWDfCfOTXn86QzGNCyoQlnzw5Ao9WiMOkCnU7EkR/qRkLvlJoVj9EEnUE/xSepBKNq4UQGrvGRG1cCLOS3VjZDazQX55zNgcHpg9ZZqTx/FIrVIH78fj++973v4dlnn5XxFvT8uf7668Xg0Ok8l/9XrA0Ybdi6zocDJ4dndZNmAGDzOp/4Cs1Xr8Ohm821brT3BWe9n3UvV2+pkrqZZ47N3uHCGpebdtbMKXwIMzKa8iZUVFlw6PQoHn/4mHgBMQW2qdGDW3fXoW5dNXJgy/Dc+zHrdLItzQBl5MW4hcBkh+ebd9aJr1AxtTPz3Fk3dJW9HHff3IKHD/ZKdxdTR6WCas7N4uyvu65vQvdgRMQOi77rKu148fVN8niMJtWU2eB2mHH0zMhEofSM884X0FzrEKE6GywuPj2cx57bb4J5xIdcLCjPl9ZsRS6dQWJ0WGqlDK4yaD01U8TedFGrs9ix67qr8fBgPzLR2Wu5tt18KzwuK472JlDZuB6BjqlCyWyzYzCclBEbOrsXeY7tmOX1w5voau2xTZ38frmTMXvh2HYjQgcfmnVdNHoDHNtuRsbopgnXihyjQnG5ct4+PydPnsQb3vAGGWuxa9cuET4UQwcPHpSIEE0Pa2pqsJZZjT4/yw3TNgNjcZzoGJsyB4qprI1NXtT5rEVHYro/FwqSBqJYYDTDZtJLPY9MBQdwtj8k9TGlFBGjKBw0So8ar92IZK6Atu6gXKzZKVWsfGE9UA5NVS5UuiwzbBQmI8Myc3n86LenZBL8BBMvZQ1eeWsLbr+6HjaTFkYTi7ozMoSUwoRpNa+dXYsZaPVa9AxH8cThfrT3hSfqZZiuorfRtmav1N6EEhkpaE7wvHMFKfzmDC1GYSj6+JhHO8dE1BVdl4vO1qw7YmQolkjjTG9I6pNYyMwoGkVRKV1HA0gKp0cP9smssbFISiI9PCPuh6kwml021zilU4pFwxydMRZijVBejoWt9xzX4bbqoE+HkelvQzbQXxz3wOfObIWhrAH6mk1Ia2YWTU/HYtFgoHcIh/c9j6HTJ1AYf06ctfXYdNVV2LixHqmCCUOBJCLhMCzhHkT6zkrnFyOFNY11OJ2uQH8EyBts82bQtreWYX2ta0HxQ0FKTyoKS25q1Bdff2tVNJm0WRQGTyB2ah8ywaGiz0+2AGNZDewbr0OurAWZnCp2vpLei9c6+jXi83NBJoeBQECGm5aXn8tZDw0N4a/+6q9kxMXnP/95rGWuRPFTurCkc3mpYeGFlxdqm9kgbsFycdFQRCRwqjuAQDghFzNemMu9VmxqpLAxSHieLz56/rCOhQKJF0K7RS/V9fwdSqJjHWPYd3xIhAJfgLz472gtwzWbqxYcS2E06yV99L1fn5y4bXwqx0SZCr/e94Y9qC+349fPdOGZowNSTEw2NxWjQ1e1lskogWgqiwDFRjYvqT+eN4/ZaTNIKobjMs4MRMSjh9ExijQWIl+1sQJ37GnAulo7OI/AH05IBIOBGwotWTuDVoqxmcriQbK77GTnmDhBU/zxtba5yYtrt1WJIDtwekRqYGKJ4nPA9bOPH4NWp5EuM6bRmKpk67zFbBD3bT4W15BijGtgzMWRC/YByRgKLFzm2hgsgNUlzsHpwsJ1XlJMrknK8NFgJIFEIgW9QS/eRE6nHbFUAdl8MULGaBXXT5uNw5RLQK/Jw2C24vSYBs+dGlmwm/DmXbXw2U3zbsOXROdgRIR1aditDEott2Fjg2c8Mok1B98f9NkItPEgNIUMCjoT8mYP0lqmmVfv+8VaZK28F69l9GtE/Jx32uv555/HZz7zmSnCh1RWVuLtb387PvCBD5zvLhWrBAocuixL7cWk+otiKkiDzqEInm8bmZIa48WZF2PWrVy7rRrlTrNc0DkQ02SbdIGlIGGtA4BHDvVh33jay8ShXCySTWXFIJHt8q+5bf2cYyn4pzQcTOCxw/1TbhcLyHEfSGng0kCiOX9wQxN+/WTnlG1PdAbk64/uWI+bdtTgkQO9ko4inLBus+rFXdkfBKrK7BLpefxQn+z7Rdc0SLqI4oc+PN+77xj+/CVbRHD85KEzMrOLZyQdaGYaI0bEfPFP79qELgqofd1yDjxEtr3T6+b50yNSK/WaOzZImzmnsPcMRTEciMssM6PBLsfWVOFCe18IY6GErDELx/V6DfZsroLLWoxCEQqfeNszyEbH04+iCEurBBjLhmBs2oUM5hZAkvpL+BE5+QzymZQcr93qgFmTRjKZxajNg2zlJiR0LtkrU3ESgTE46P8szzO/ytxFEV1a39ng+bptCwufo+1jM1KqFIi0RvAHExL1WsiFfDXCC0QWNuidjqkXDSV8FIpl47zFD1NbkcjsNQBMVZjNc7vGKtYu8XQWR8/655wwzyjGkTMjuPmqOujnaNth2/fAcHxC+MwGZ4Jxxtade+tnfGrgBXkkkIRGp0FHX3jOffAQGY1gHdB8czN/83Qn1tW4ZKK7HJ8GMp19JJjA08cGpAuMoyRC0SRa6jwSpXrg2S4kksXWbA4w3dpSJmKkaygiwofkxz/98IJMJ2YKJX8wiWPto3Jf8Vx4WwJN1U5JDzISxMgSTQD7R2ISDeJQ1Koyq/zMaNH9T3VKlMNjN4kxpctqlBTJ4dMj8OyuF8EpUZiB9nPCp7Qgk0j7+2H01kDjapizhkuPDJJdR0X4TJCMUgEhW96M470x9B8/DI2nWpyiGeGqKbfLcZsmffKiKNqxvlwGv85mX8AI284N5bJG8wWhmQacq5as1O12siuA3RvKJ55PhUKhmIvzTia/7W1vk8jPgQMHZkx6Z7qL0R/F5QUvqBz1QIEzH3RC5kysOdFATO4W4njHGAKxdNE8M53DYCAhX/FMHmf7QnJ7cd7X7JxrOJ/LlagopHRaLZ49MYjWBo+Ijq2t5Rgci8uAUdYpcVgoL+oepxX/9dAZiUzVlTsmpt1TDD11uB8hGiUWmLo7F71gLRPFE6mpsONU95gcjMtmlI4tFnZ72WHFUK2LM8W0OHR6WL7vH46IAHzm2IA4R//qiQ45b7pB0ymatUK0FCgJUYon1glJtCYbQ8rfu+AapwbboZ/HA0mTDCMzbTK6/J6zEU+f9KOzaxjpVEqmkEu6NJOXCAxrsNKTxAeFSF2ZFTfsrJFaJ6ZJi+ujFafnG3fWwGc3zit8+HzTBmAh+keiE5YECoVCsaSRn//5n/+RYmcaHNbV1Um6izVAnZ2dkp/++te/Ll+lN60HH3zwfB9CscqQgaWh2ed+zSaAmPqarQA1nsrDH1h4PywOTqRzONkxhsGxmKSdSp46dFPess6LjY0enOiYeXGezKZGH+Kp2Y3kKG4YiSh2lWlwvGsMtXE7HtxXHDfAdFRthUMKk3/2aLsID3oZUmSwhb50HozwPH2kH7furhchUxR/GkmNlcQJC6IHxxJiKMg0DVNhFAultB+Lwek5pImkxNyQHkeZZBZ2q1GiSpNhoS93m8nkJ4qqCae01/qs4mqdTy28xrlkDJpcir4BM+6T4bmM8kwTJPQGavdnEBgrjrIg+XRiyrw3rg+72jbUnSteZsMd2+l9W6tl0Ctv5nFbTToRRwvV6bCeSGqmFoDinPVYnG2mUCgUSyp+KHj4NZn6+nrs2LHjfHelWCMUC5sXd0HhRW2uixkFx2Jq0Xhx5IwwRlam3J4vIJHOSN3LLVfV4mRHYFY/HM24KKGn0A9/c2L2cwKdhk2oLrfjySN9kn5hl1oJFu9GoikpXKZgKcGIy7o6t4gfRmDYgWVmrUuhgGqfTYqQOQctEE1POR8aJTLNxbQenZonQ48hmv3RuZmiayJ9li/IpPpZT3BaSGvCqFqsgGdvy5++k/m2oG/PdNJmL7pPT0090cxxOl0DYTRWOaSYvETxNVGQouSJ2xabnhovZF/0xgqFQrHU4ucTn/gEotGozPJi1CedTuP73/++jLa48847cc0115zvLhWrHEb0WGvSPTh3nU0pQkSjvrlSGFazDo01LkktzQUvpi6nadYuAQqRKq8NDzzThbe8ZideelMz7nu8Y8Z2FD5/dtcmiap0Dsxen0Z90VLrligMi3FdNhN6hqd2+LENfiSQEHHDbUouzvzPZtGjuswuw1wp6jiPi3U4LP5uqnFi27oy9PujUovCqMzVmytxpjc4EcUqYTQU27T5lc5kxeRwfCC6uDzTf2my0bK01RcKUkvDVBnXmpf7Cm/RgDKvt0BvcyLLqe7zoHd5kWf3V47defwqdkpxbIfUTFlc0Oj0KEwabJrRmpBITDWo1FqdM8QuO+b4/Bnmc+k+D4w6rUTgSmnEuaBb92RxpVAoFHOhvZBurxe84AX493//d/n5Yx/7mNQA/fznP5c2+N/97nfnu0vFKocXN6/DNGMO1HRYx0IRMBfZTB7b1/mmzLaaDiMoO1vLxPV3OoFwCo3ilKzFD+87ghftrcff/dluaROvKrOgtsKG2/fU4x/esKcYGeqaOy3GfXicJolUUZxIKmba0Fa5gI/PCuO2jPRQCNGMsLXOLRGOYDQtYsts1kuEiCkapuY4Lf6G7TUT9S2lkR2TdQIfuxjpYRwKUlSdSmdhNesnok88Nqb7SrComFGxySKTbsz0YyI5rRGm8Rlfc6LRwlTJbTSIpnM43h3Gb5/rxSPP92MwlJSi7KzRAaOvauqvFfJTIlEURxoT/Xumqh/ZZAmHUVHUlZ73+aAHktmoUl4KhWIZIj/33HMPWlpa8Md//MdIJBIy5+tP//RP8cEPflC+vva1r+GOO+44390qLhG8UDNCwwsW60YWi0mvk+gF/XL4yZ77IKWRCBzOuXN9+YKzoCrcJrzkhmb8+skO6YSazp4tleJ2fOjU8KzCiDOorttWLYW1v3mqC611TvzxC1slWsKoEdutzXoN8pmciA92bj34bLcULpciJay3KfeYikIilUU4akQoksKGere03PNiyyhOUWSYJPJFIcIojsWkQzSRFlHCSIM+nRVhuHVd2Xj6KiVFt4wosS6podIhX7QCuH5HDX73bLfUvdCUkHPDsuNhHo7Q2FDvkuWj0GqpdeKGHTUwGvVIJLL47q9PiCiiyOE2jPzQO4mF2hsbvWCZC6NKUgfkrYOlJoxE/1nobS7obQ5oDSZkEzEZpWCsaEDOVo6jXSH88vF2iV6VoGfQ9tZyvOzGZpQ3bEc+lUQm5IfObIPZUEBdfSXaz/QiV9DA4KtGXmuc8Zx7XVZYTRx3MfP5Nxi0UgvI4zwfDxCnxSBjTw6cGpoRPSMUR83VrlnvWyuU/qZK/ysUiuXjvE0Od+/ejc997nO49dZbpZj5b//2b/GjH/0IO3fulEGnb37zm3Ho0CGsZS5Hk0Ma5I1F00WfmHBSjPfWN3hQ7jQtOvzHN+VYKof2gbC0XjNKYbeasK3FK2aCk2s85j8WYCSUxuGzfnSxHZ0FsW4zdm+sRIXXjEf29YhJ4lx4ZAaWWYqQg+NdT/SK2dJSBodZh8KkC2CmUDTGe/rogKSkePHd1lKGq9aXI5nJ4ie/O4MNjR7psqIfDdvJWTjLTi/un49FUdM1GBHTRqaXGAHjBHYOAaVQ4zYUOGxJL/dYxIDvRMeoiIC7rmuQY6MAC8dS2NTkw4A/ijPjE+J5HlubfbBZdOgbioppokOfRDo4gtHuDkk7OcqrYK+qw2jejH1H/XKsVV6rrFHvUESCLIwO8VgcpqJBpElXQCCWFBHWPRRDHhppq+ex0qRwKJDCt35+RITYbNA08PUv3gynIYtwOIK+3hE5fljd0Gp1yBY0GAykZY2mPLcajXRwlTk5BPfc7dxqNJLG6Z6ArCPXhNEzGmPOM4Fk6r61Gums6xgIY2QsLs87I2otdW6UucznH8ZeJXCZIoks+kdjUrJEry16QMlree1quVXJangvvtzRX64mhwx7m0zFlt7HHntMZnmVip1ZC6R8flYffPk9c2wITx7unxJtYZs2L/wvvKYRtkV0yCQzeRngyW6sunLbxCf49t6gREk2N3oWdQHibC62N79oTx1iiSp582e6QhygoYHPa0N8nvoiFh0z/cRJ4KzF4QXCbNbB6x7/gysll7TAqc4gDrcNYn2dF9tafHKlGR6L4SePnMZLrm+WgaJjkSTue7JDWtV3b67Eowd6pTCZ0+61Gi12byyXKFkyk5OLLc+70mOVyA27sxh14O+zE4vRJUZj7ryuSaJMFIXMpnHEBU0XH9rfDbNBh0p3se2bAuyxQ73wOi24ZmsFbLlRnHjwN+htZy3TOTHp8Liw4wUvxCtu3Ir2wbh4FLEeqZgwg7ThUxTddW0TWmocONkbxgNPd6J/NI5EKj1+EdWgrsKBu29rEXdtCqHUaGxW/x26ePtDCfQkszjdHUEup4MWFuhyOYyE4jDodDKuhHVgpWgLz2dba5m4T0/+TJXM5vHQc7041u6f8liPHezDNVsrJZK3mDcivtYcZj2uavUhnfHIOTGlWBqtshbJ5Aticsnifr6uLBYjEomieG6udYlvkqpiUiiWnvMWP9u2bcOPf/xjETn3338/brvtNvmjHR0dxTe+8Q25X7G6VPizJ0fw++d6ZtzHGV0nOsfkgvTym9bBME/ghtcWjl1gEW+ppX0yp7sDcvHb0uhZ9Jwl1gCZ9ONyiYa244/UUutC/wgvuLPvh4/DqAEdjWmORzSFmed9sieEXz/RLufH6Iecc74gXjmcD9Za44LNYsQPHygO5IwmssjkBnHrrjpExmdx8Xj4Oy+7uRmRWEaMCln7w9QU3aCpT547MSTChzAdxeJwXswohJ440g+f04JKHz+R0DKgOMG7zz81ssg02t/cWYNj9/83BnpL7tXnTiocCOLZX/0cN/yhHY8cSIr783TGQklJJ77slhb88vGzGA2nEEuy1f/cE9szHMGDz3Sjtd6FA21D0p02Oe1VotpnlTlvYhUgz6dWWspMBiPc9uKMM7a0s/ONURh2s1EEOiz6KWkwrgqFz+EzIzMeg23pjz/fD51Whxt3VCKfXdzrJp8rOmwXl6gk/9Ye8jdF4TNc/JuaXCbF19yZcb+prc1eZdyoUCwx5x0pfs973oMnn3wSf/InfyIdIm95y1vk9pe97GXi9fOud71rqY9RcREwTbDv2MC821C4cFTDQvthumY+OHOJabGLhcNPr95UKZ/qp0NBcdWGCvgcxdqXuYhncpLqmhxp4IWEhoAUPoQZG5oH1lXYJuQBhcB9T3VgaDSOmjIr6irsqPBYcKpzTARZU7UD126pgsNmwv6TQzL2gnVDhAaGezZX4vnTfvzy8Q6c6gpgNJjEyc5RiQyxU23v5qlFxKXj+pM7NyLa34HRwSG5bTYdajUZ0HP4AOp9RrmfrfF0qF5X65Z0HG9jIfRjh/qKtUJzpLRCsbQMc2WbPlNJNG2cTnONG4fahiUFPIMCa8C0InIr3FbctqsWO1p8EpWZrkTozHzsrH/uJwrA/hMDCMVm92O6nAknMmLMOB90KY/N8TwqFIpLGPnZunUrfvvb3+Ls2bNYv349rNaiSdqHP/xhqQeaPvNLsbL4Q0kEJk1pnw1erzi6Yl11M1KzvNEyh9o9FFnwEzZTaqwnoqPvxaQheFGtLbPBba9Hvz+GQdZCjF/sKUbsrIVYIJUcjmXQNzy1zZ1CqBgJKbbdUy1wNARrZaxmg0yzZzG0TGy3GEQQPt/ml6GnTPEM+WMSNbJZjTJRncZ7rBMqwUGnTG0xisPoFAuj2f1l0GnRMxTE8fZRvPyWdaj0WqRmikNk2WLPeqGNVSb0PXJ84tP/ufn05362263oaOvAphfvQnpLFYbHEiJieB9rgPZsqZK03E8ePiNF0LOls2SfGogw272pQga1cigqBVEJik5+saZI/J3meDKZ2uocCKPaWzlrbt9g0OFUZ0AijPPBQbp9IzFsaXCv2ens5wtfY7187hYyeMzmRUDbKuzzumArFIplFj/EbrdLgfNk7rrrrgvZlWIZ4XVrroLW6VAUzPXmyoslu6AWg/jhaOaf07QYGOanZwudgktdUMx0MBW2mAJZ8auZvk92po1fXC1Gg0RGeHFhZxdrfCiC3A4WDBeKRe+hpHR5MVo0OQbFIt/o+NwvFjfznJk+og8NhQ8jKezK4u2yL01BHoc1Q48f6hfvHqfdWKz5Sefw3IlB7Go0I5lIyDFOtiicLILoM8SUm1Gvwa+f6pTjKsFCdvoavfFlW6V9fnIsR47HyunvpVmZBRFk0mbPIbTTvHEofFiLxPVgVGqueW6ERe9z3c/XQTS5sDMzYRE0o1BXivjhM1pKlS4En4vJXk8KhWKFxI9ibcALHSMBi4HFvXO54/JNl9GBxWAx65f0E+rki+H5JNQYkdFxhMWkY+EFRHxqcjmpZbGZjXLhp1ChEGGEh4KFYsGgs0sx+PH2Mbl/cvaHLfUs8OZjsD6Jv1df4UD3UFiKpvkQLJCmnxH3y4t6KULEKNbVmyqkXqYEDzGd18JqtyHsn92buTi1voDycjd6/YkpwqdEivO1BsKo8LIYvSgWK90mOPUZZKN+5JMZcW42GZxoaamSomWjvij2JsNjr/TY5EHZ5r/Q8y0CaZajLhSKka3FwA66hR7r8qIA27if00Iw3amiPgrF0rJWu0MVi8TnNEkx6nzwIklH4nR69ugOoyBspV7It44dWGwRX8r3aUY7mB7iFyMJM+4fn+bATjR67GjGX9EeuxEN1c4p21KE0JuHsGA3k8th14YKaYFncTOLkdm9xSjY2f4gzvYGsaXZI/5Fo5NMF7lO21p9InRGAnG5MNGDh+fNSAo/0VN00fRRxn3k8zLUc0LETBIKPHxGlx45MorqzdvnXTsp8Hb6cGp4bhlI40W223M3DWVmWFN+RAd6kIxEkE4mkYrHER4eRL0lgesa9eJFFEucq7fRjnsO7VxfBq9jflNLQm+dudpZKaK4LykMnwfn+LDXK0n7MILJrsCFPH0ozmUArtI+CsWSoiI/lzk0h6O53q8eP1ts2pmFbS3l4pMyHw6rXtI8vLjOxYZ6j6SqliR1oWGxLH2JghJZIYwitNS5xHiQ3V3iHRNKiUhhfQ3bhDksk342ZU4zrt9eI5007CoiJZESTWiltoffs0D4t+PDTMcfVlyd6dYcjKSlG2xDg1vEFGuCpJW9wo7mOhf+87dtxeGo+Zw8Pi9UpRQQIxncd2kt7GaDiNBgNAkUzl3wKOiY8nn8+T788Y27UNFQj972zlmXRG8yw1S7AW2PTZ2vNZmB0ahMUOdQWGs2hLFgcErqjBfbMq8TtU4N4m1P409vfiG2rfOJRxE9kCiGWOBtM2qxod4rpoJzXXhpEski7/nw2U3YtbkC+44NzvU047ptNXBZDeNDZq8c6IbODjk2CsxFa70HtqX6m1IoFBducnglcLmZHBa0wNGOAB4/2Dc+dbwI0zLbW8pw81W1MM3S8TMddiIf7xgTb5fJ5na86NMwsaXaOZE440WWk9n58uL5cz7Tot/ANRq09QalSypf0EhkpOQ+zMNc3+DFxgY3jraPiTgqPV7JI4VX+23ry9Ba60RbbxiH20Yk4lOqbWGxKdNQjdUu9AyFEYtn8djzvSJsTAY9cvm81DhR7G1vLUOV1yJDSxllYmqJrw+9XidRH84ZY4cY04Kt9W6xFKBx4bpal3REMfJTOm+eBvfNWhv66JSOm2tGXyC304hGexYjh5/CaG/XhBjIZrIwOZxovfE2PNKlRfdgHO39IalJmixsXA46Q7tgN+txy64aPPq7pzA4FBAhJ7VEGg0a68pw4/ZKYKgNHosGztargPL1Mt+LC5ea3K2nATqHolKczfUorXE6lUFVmQ07WsoWZWxJL5snjw7i4KlzlgDEYTHi+h3VuKq17IoNQTNCeLwzIB8qKJxLr2HWZLU2uMWOQfk947J5L74S0K8Rk8NVL36eeeYZvOENb5j1Pk6X5yyxr371qzJ2YzqnThX9W6508VMa0hmJZ6R7ipEUzpmqr3LAZzeI6eD5pKGiyawY7LG7iwM+6XRc+nTKC2TJSZpeNKzjoJt0U40L9RULu0BTYAyHUnjicB+C0QwGR6Pir0NsVoOIEKab6NJ8tmds4mI6WfzIcWg0uPXqWqmXaOsNSVcXhUdTjVsGhmayOUk9cMjqNVurpMaFHVz8mWvTXOOSOigKvUJBI2LrYNuIDCflYzE6QmdmbsdC54HRmKxDW3dAvqfzdGE8WsX98GLGWqIbdtbKxYyO0Vy/Sh9HQRiw/+SgdJbVVlqxpc6JWlsGhuQYorEkjA4P7GWVsLg9+I/7T2EklJA1EGfgeFr+Z6SJf/I8Fgq7v7i9FpHuU0jqHDJNnuta6bHAmA4iGxiAw6QRQWpwl8Gw8ZY5PZVKInY0nJQ6I7vNCKfVCNsc4yvmfP3ptAiwxX6ITtlZWRMpMGc91RV+EeLfFDve2JnJHDQFvs9hliimivgsLavhvfhyR6/Ez9LAqfGh0NSwMMdncKwGh6q+5jWvEW8ho9EoHkSTudC2+8tR/JRg+QWLfvmsz+rhsuj9TJ3tRRhZ6PXH5py/xDQQh5Ca5ntxajR48ugAnjs1LEXBs70462SelQdeh3nCe2iG+NEC12yvwUPPduNAG9vZrdjU6MPDB3sRi2eko2lzsw88FAoat92Mm66qQWdfSC72jOpwna7fXi37YuH4sfYxKSgORlMirth2T/H3yptbpHj1aPuoCL3TvUHxZ2GHV2ku2tZWH67eWCHjRFjbwtdEyevl98/14tFDfeLVw/OgpxCjQxzbcN32ajFRbOsJ4hU3rxOzxF88elZ+l1ElPl6pI0g64TgfbXMl9lZl0fX0QzAYjDBbLcXaqXgMuVxOXoMOG8WHHQaHB8ZNt0pUaj4onti67nJZZ30d87jZGl8SnpyBNpsxH9eU61maZK84B9fX7bYiGIyd19w9xdp8L75c0a8R8bPqa34oaiaLmHg8jk984hN41ateJcKHtLW1yaBV5TG0MLzwLkVXzWwXrmgqO26MN/tFjR5AFBBXbyyf07E2lc2ii/Oo5hA+hN429OHhFO+BOfzzmNLaf3wIxzrG5Gemyh4+0CsFzYT+O5FYGjkJX2gwFIjjuZPDIiho+shJ6W6rHk8fGcAL9tbjgWe7RcxQdPF/ul3TxZkmgxQvrAtifREv/Cx0ZtqLURkutcNqgMWol0/zEymwbLE/ivthFKqxyiG1RpwGT02aSOclrdc7EsO1WyrFc4gjKV7zgvVyDPTpmexbVIKmgxzQGouNiBjNZNLIhGa2m7NbjeLXbHOhIFXi878mqG9ne84pesKJrAhIClFetPnmR5HWWueCx2ac8nt87V1Jhc3nQ+lDxOr+OKpQXB6sevEzHU6N5zT5973vfRORITpLr1u3bqUP7YqmZNpWinbMBS+QscZiYfRssMaHnjsLvf8PjERht85dbEsH5n0nihESn8ssE9lLwkfgPDCTDsEIJ7cXi70p2q7fVi2zw1jHQ/ddiphsroBEMoPhQFIKg7e3+nDVhnIcODU8sU+mLTg5noXUHPcwMl5TxYhJKJKUCxvTPCzsLVFMH8blWNj5c6qb9UvnXH74HY0UKYroxkwx9cTzvXjVC9bDwnRe16gMCK0us8tYDdYaNVY7cPS0Hxa9EU6PD9Gx2dWhdJ1ptTCUN0gn3YUgY22iKRGItAgowRqjnsEwBv1R7N1SjSrPOdGnUCgUq4E1JX7Gxsbwne98B3/3d38Ht9stt505c0ZC+b/5zW8kDZZKpbB3715JgVVUVFzwY5XSEktBKQy32HDcWoSXtpEgU0Xz1/QwWhFPZ8V0b9b9MHKgm2rSNxtcS25Xerzp/1OEsf7FSlFgN4m/jmaaPw1TRrl8UuaVleqK2E3GYZLs6OJ4DEarKNg8DjNGAsW5XEfPjOKOvfXS6USjRNbYMOrDiA/riUowujRZKDBdxq46CiGKoqA/Jbfze47cSNB7yGKQwlduwygSz2ckmBCRQ6E1OJaQ6MrLb2yEf3u1FKCzjoZjJDiglXVW0s5v0MPctA2p2NPIpmc6fFOYOevXQ2PzQs+K+At4HVM0PS+Rq/yszzuf68NnhuHZVQfLHGJXcWW9T6w0ao2XH90aWeM1JX5++MMfwuFw4LWvfe3EbUx5EYvFgs9//vMyYPWzn/2sFEn/z//8zwVNmecbOXOWS43TOb/fzlqBvjDsGmOkhLUpjDgwc2IyGWCxLBxFMBkNc65vIhsRc0GOO5ibAjY1eeU71vlM2bdpXFRpOMJCP+Ejo9Vm5H/ezigEfWUoaiha2OLN55yCg8W4Hf1BXLe9Roqq/cGk+KywyJdFyozskNM9QSl2ZopObGw0GphMeliyc0ejjBRibuu5Yx1LTBx/gQaE4Jwt7QyRwkLxMo9l3GtJA71Bhxy0MniUgojT2ScLjpOdAdRU2GAq98K38yake08iNjosfkPEbHegYes2uNdvgdZovuDXMeufuBzTn4PpojiayqGmcqrnkuLyf59Yzag1Xn5W+xqvKfFDMXP33XdPETT8+ZZbboHXW7wYEs4c420PPfQQXvrSl5734/DiGA7PnHR9oVAB84UQDicuqsh4peGFjAXNbV0B8bwhjE743GbsaC2XFuuBafO0ZkuP6TWQYrjZYMCNhcys56F/z2zQG6W23CYjLKS1fVywUvikUhl5/uih4nWYZO3ZqcSuq9JEdY+rGEVhYTOPp1QgzfQS61RYl/Lgs93SQdU7HJHUF7vMbttdJ9EgTrTnjC8a+LGdnSZ+nNcVCifmHVnA6Mfk8zZzjESi2K3F6A/rmJjawvjPjDbRYJERo2eODSCZyklE0mwsptdGQ4lZI2ROmwGnOsbE6+j5AOBzb0dldQbaQgYajQ4wO6CvLkcolgNisQt6HVMo8rkurf989A6GUeliobdKfV0J7xOrGbXGl/caO52Wy6fgucTJkyfR09ODl7/85TPumyx8CNNdTIsNDs5urLYYlqNKnS+EtdphwMhO+0BEWsYnF2SybJcT0B8O9mDvtmqc1QSneABNp8pnk3qf0jpwv9FkToz+GNVgyqa2woZgxCm1OoywMPVEmL6il47PWYzEsE6Gqa3eoWLbOGG0p7HKiboKqwwa/dXjHSJI7rq2ESaTTgQERQ1dnTnMlI/HffCcrlpfLm3hDz3XK6KC6RweA9vUj3AyeQFiGPn7/d2iTihQWHfEOV1OmwljwcSc583oDA0nJz//7CBj1IwihlT7zqXNmJLbvYkT4oclDbd3a7XU0nANyr1WPPl8vxQtl7nNM+ZhaMcNCNk6zcdlgXgPH89qlGhVU6UTBb4WF/G8U1TSpycQSUtxtcUch8Oih4vjKAqL69iiUGKUUF1sLv/3ibWCWuPlZ7Wv8ZoRP/v374fP58OmTZum3P65z30O999/v3yVxh/09vYiEAigtbV1hY728iOWzMlU8pLwYXqGURO+uJlqYX0Li1y3rPPhyJmiQGI7uVw8s+zwKcBuNYibcKnmJZbK4VjHKEaCMaTTxR3zd6rK7airdMDfNozrtlbJY9EMjkW1fSMRieqsr3dDWyhge7MXrbUuyXMZTDrmfaBnCisLmZbOsRKdAxGc6BzFLVfV4dGDvTLPioKIdTQ8B6a6OJaDU9G/88ujxSGSeSCZzopbdDabk9oe+iSxhZ3mfmxR1457sty0k35COolwUPhRMFHY0OsnFM+IbxAjONx2snDkzxwj8dSRAdk/7+MxdfaHsb3VgVAsiVt31WHfySG0dQflvDhAtXvIIVEk1hyx0JrRp+lw33qNRkwsd7aWF2uIGB3Tz242OTFNvjC1Lb3bH5VhrDSDlPPV6WC36KWdnvPMFkOll6MrVu+boEKhuPJYM+Ln+PHj2Lhx44zbX/SiF+Fb3/oWPvzhD+ONb3wj/H4/Pv7xj2P37t24+eabV+RYLzd40esfjYmIoUhwOkxIpfMSiWCkRYp3wykpvF3f6MZtVzdI4a0/lJDf4QXdYzeJEKGTNC+wiWwBv3uuVwwBi2MnDOKVU0AeiUSx8PeaLdVSZ1Ns6U6LYNm7uQqbG70waFmUDiSzBTFVLPny0DSw0mNENJZDe28AL7mhWaI8nYNhKSi++7YWETuJdEYEDoUV01nrap147vgQYomspLEMRq0cs1y0NRoZTcFIE3/esaFCDAspAl6wu046uLivP7ilGcFwWtrmuZ/Geo+knjwOIwq5mVESrgNN/m666v9v7z2gI8vPMu+3pCqpSiqVSjnHVrc65zDTk8fj8YwDYJtsA7YxsLDLfsviQ9hDWODgZcln4bCsF7Mf2PhjwQZjMzb2jO0ZT+wwPZ2TupVzVimUKkj1nd9766pLUpWkDupW+D/n9Ey3VKq6919X9X/u8z7v81bI6av90tE/oOF/n3z/NjlQJhIdG5DxiSFpPOSX1sZqOd08qcoUnqtzTQNaaizyu7X8t/C5NUtHYjIZiqqviZyf0vxsKfLfGjTKzUJ0dlYC8U442vxRlngf8B+19U/IV169qY/j/SFpm2shGo3Jd9/pkncfqxa/L1Pf+1SABOr5m4qXgYHBGsK6IT8DAwNzHV6J2L17t/zv//2/1ez8oQ99SHOB3vWud2krfLJBmAa3Dza8kbFp7YCi/PHaue55wzD9OZmqMLgz0yQ4bQUEQlrsyeO0ftNOjgJS4vdIcHZWXjzZJl9/o3XOQMxbRanm+eO1MjQypWpHvs+jJmW73HN4b4lUqddnVlwup6oSL7zeYqU3z6AmEfqXJkd2lcoTB6q0XBUKRZU4VRR6dbwFfWTbayxSwogtpFnUHA0vnKQby6OmaG3dRj1BdZq1ZoL1Dk0pATvYGJYrrcM6tfzwjlLNLYJ7vHm2V1480SY9Q7f8YviF3vdIrezdkp8i7G/WGgHiECVSe8pEgldek+HvXJPBwVGrnIevqqJOfmjvE/K1phydeYYR+sLNAfnAo/UyqtLyLXZBzXtsKizhmZj89VcuSkuP5cMieJDjfe/xOsn3OqVvZFou3hyU0fjsNFt5433YUZcvJy736Lnje4Ic6QxZh0MfQyDjyYu98tzxWjl7tV+Vq4XgGA9uLxa3yyQVGxgYrC2s+YTnB4GNnPB8J2AzvdoxKk0dI3L+xmBKgvTMkWolIeTjJLusKDE9frBKn+OfX76hxuFEMGYC7w+mX7rI8L0Q/mdTWIgIicdFPrcMjIfkL754TsdRAHtj5nV55Y+9b6f++7VznfMyaABEjM374s0hnYCOyoE35mqb1TYO8BRBAPC5oF4xtoLXJ0/nuYdr5V9eviGZGU6mEchPvH+X+m/+15cvJF2bDKdDfuqDe+RoY6FmBg2NRzQTKRyJ6kgMVJWWrlHZV+WSsRNflZ7rl6W8IFu6yDtKWMcsn0/Kn/5h+b9npiUwFVXVjHJabWmODCX4jaYiM0oIj++pkG+ebFtEPCBrH3h8i5y62JMyl8mX49Zr9auvNSsBSrbG5BY9/3CtljIJOezqH9fn43one4gASJ/HaYjPJvmcWA8wa7z6cJqEZ4ONAtQJDL1kyqREfOgpHVCp+DTlLzZJDMYLiQ+qUIHfIyde7xW/N0Mzc/DPsHFSjgH8m/buokNl8trZrjnikwyMe7jRMZp0TAAGajZufEUoWBOTISU5mowcjOjx8/p8jREQbb0BNQuTSk2mD3PN2M+1SytN5BJjLfAbJQElJM77zNV+aaj0y+tnu/Xx9qR5yESmK03VGPdEh1y5dlkJFYTjVtxh/JzGx2Xq+knZU/uonG0OaDcbigsKl420dIf0dE/KwcYSudwymJR4UL7CME3pLhlQ4Vp7xqTIn6UEdGGKtA2yk5gV9/CuEtnfUCCNVX7NK0LRwpM0m6TUt5rQIbFxcmYIl4GBwVJY2ylEBmsCbCpDY1NzJCQZ3JmUhSylgrJIMtClhLkXLMyzYYJ6a7c1ww3lBwUhWdVyOBCUgZGwnLrSt+Qxc8dBaztG6WTAaE1JDeNufWWubvJ4esoKs+TJw1VyZGepqjKU3Jjh9dDuMg1mZIzFTSbJx4+tvtyvYy54LVKYE9Wlx/dXyCP7ytWHxBDUl9/u1GnsdEklgq6s4aERmbhxdi4MkM170To6RAZuXpXGglmNGuD4akt9eh6ENuKTKinwaj4Rpbz2Pmvu2UJUFOXI6at9OqE+GazDc6gSVl2a2tRMaz5kq380KO9cH5SmzjElnZAxiM/9AtfJRDiqA2zP3hjU//NvU/U2MDBIBaP8GCwL7qYZBooXBPOsrVosJD9s2CgnyJ7JyimUl1BdMMGyqTL53Qabt53DQ0c0BCHb7VKSlKgk8dcp7bxKnS/DpkdnFsdD+SrZY8knYoxFJBpV4/C5pkEJTIbk2WO1avJtah9VUkH2z8j4tP792WM1eizMAMODhKeFSfNMWUdqRb0CZP6gvJy41KsGZYzRW6vy5BtvtUm+D+N3tio2c4NPXemSkxGT0UEIWab0jVjmcs6ddbAfx14eDU2LU6JWlkZ2huyqz5eqohztfuPYMID/2l++sWTcgAYPBiP6mPQkRFWHmJJBFIrqeSYDxnfIFuXJE5d7JRi0PD/X24al0J8lB7cXaaTBahfVuRKZF9fWPTZXngNX29KktixXdtXla+ebUYIMDAwSYZQfg2XBBka5B+MqpIXWZQZ16ubvdqmSQNcRyhCbZuqNJqYEATN0Y23evJEIKDVspDbS09I05C9ZCY3H4R9a6ngxFEOmKF9Vl/i0bMXxovDQLs7GiAGYFntmU9G9NB6MyFe+e1NJGgnQnA8maZ6DPycv9Shx2Fmbr+epnVITYVV8iv0e3Xz5Oqbil9/uUOIDrEGkw0oiMYFz/qwnpIx/Q2Qisw6ZcUD2eHWL4On4DiakZzi1Pd9Od3Y6LfKICRvD+Mkrver/Ydnxqy21NoB15zhTNQSwfpx7WZF3HqGwwXvIVPhQxCI84QRPlT3m5OSlPjVcryY4fAbXNneO3vIlORyq9o2Mh+TVs13yMuXR0aAEtVNtVQ/HwMBgHcEoPwbLgg2V0QqUUsiawWuS5yXkLu6ziD8O8zBqRKL5NhFTwYgcaCyWf3uzTdp7AvKuo1Vy/vqAEgGHI6Ykob03oIpCVYlXN9mF5Ifv0YK+d0uR3Owa00wdLXtMRXQYqf3wkUBQwwF5Dle6Q7LdXt0UOVY2dgjarEDe0uVG16gqHLSr3+gc002SIERKUHiDICkcF8bkd671K9lhyjrAv4TSgfGYDivKXahbKFkuV7p+nyGktL9DbOgWm5mNquoEuUGBQWG5PjAjz9Rsl9DVV5W4hcJRJWsoT+QNUUpyxETya+pldNYjYxMTcnh7iSotqEgEPXKujxyokAPbiuSti6kDPq21KVDyN5PCkMixYWRu7x1XD1IiB6K7j4XGUD08Ni1ucgcWvgZzxkaDUlmQndIDdrcYD0WlreeWemhlR0Wt6fLx8zpD12COW84M9Mm+bcVSnp+1asdjYGCwfmDuhQxWBAL1IDfA3jxUuIkP4eQP87bo9koFNlJKTHQnVRTnaPv5h57eKnsairTcw0TyY7vLNNkYgpVsk9pS6RdfVrp2XO2qL9DSDZlDlJLefaxGx2IAUpPx26Ao8TQa8hcvHdnKFEoWXV5s4OT84McBRPuMT4ZlYHRah4ry+GxPhhIVfEklBbfmkqG88JqoOTUlOTrwlEBAurqY8s6gVEgGpJDN2VYoGFmBagYgZacv94mUNIjHl6dqD2pQME6AIFSoOWlp6VK466hEnFmad8SIjcQWc4jV25d7NTcoMyP1rzaK1KP7y1MSH5Dvy1CSx6iMH3p3oxxsLNI12l6bp3EE+IoutwwpoUvFJQhrXHZC7R0C0k2yeOL1ForOalk2seTK3zlf1vPtK30yHB/LYmBgsLlhyI/BikAl5dD2Ei0ZLQSbOoblPXUFagimu0nNt/lZSkr4GcosDCytKvLK9z6xRXoIHuwOaDmIbJ7ivCy52jIsD+8pkzRHTMYmw1rCYNMnj4eQPtKj68pypGswqBk3mH77h2n3ztfNubIoW559qEaO7ymT7328QbZX+WRnXUFSo3ZOlksO7yiWyWBYSR1lHJ2v5XbqH1ra+RrEh+9zfHzfnYnPxUpXpksLAkYZjO+RmUMn1XRoVkkLGzPKBCoRZIHOM46Fw7EnoXNkqDooLa/ciErRo98rucXF1jFr+WZaiZwzI1Man/mAzBRuk8mpqHpcIFcQMdYYD46GTY6HNQDy4+/frcRlIUrzs+T7nmiQHaxNvbU2c+UvHdlBeKNLjmwvlboyn7gzULv6VO1prMmX2nKfnsc71wZUFUMJTAXM4ollM802wsfE3zX9+86vRw45GLpVbuP6GAmEZCZJkjTKGSQNosy4FPt8MWtzdFxfa30C9b2EDvHl8oqvgYHBZoQpexmsGAzipOsJ1aKtJ6CbiteToYNGSTnmY5T/H91VJm19AbnSMqTKCC3sh3aUSk62S1p6A3K9fVge2VumG1FLz5gSjGJ/lqo6fA9Vg+ceGg9pQCKbVXFhlhKiwUBIB55OTUXkPQ9VizO9Ts5c69fgRTbAHTUF8p6HaqWyKEtC01FtX8eojRqDD4QPfjxAlMvIFCIEkTEYuTmZSlKco0H1BXEyqEY8hnlgjObYXpOvKgKKDTPGIANs/p19AT1OCB+G5pxsp74Wz1NVUhgPM4ypT+dGl1U6hByx+WAOZ40ITKQbrseRL3Xv/QmJDHbKWOtlncTuKSwXb8126Yt65XNfuSbve7ROaitypXtgUtr6RlTVQqWpKcuV8cmQnG8alOeOV8sv/dhhudIyIs09YxruuLMuX2d7lfjdet5bK/2Sn+vR+ID+kUk9Ls6JKfLMIaPc+eS+ctldn68xBkOBoGTF32+eC4vWUhUkzhFOwXUxGZ6Vjv6AXLgxqO8tZUVKhQyMXUKkSgleF4Jqg/dqIsWQVcz4tgGcAM6p8IyST1K/R5ir5nAoUa8s8UpOpmvDlsX4PZqYjkp7X8Aq28Zi+v4zwoWRMSaG22AzwYQcJoEJOVwajvidsn3l2AMrtSV+IiQnL/Wqj8W+w6YywYiJA9uLJSvTKYHJiHzl1RsyOBZaHIK4r0J21ltpyJduDmnr9MDItBp6ycyhPHagsUhVm8stI/JP37muioL9WmTxoCT9+Pt2yd66Ap3LZT23tcNq6WnGKtNhyP3W2x3yzvUB3TgZp2FNbQ+pgoOHBmVkb0OheoEoK5EOzUR5Ep45LlQiyn38DJ6o9z9aJze72OQHtMhmb/R4pg5tL5ZX3+mSax0jUsNwUSEQclLLYozhsFKbB/UcvuexOiktzNbjZ71OXOyVKNPqszM0hfqVMx16jAvXj2TrnCynErzsTKd43JZRmj8oNuGwVSbjJzELt3SOSo43U1Uk7QJjyKuIEtBiv3uuRJjBWjDSw+uRgaEJeeWdLvUtLQVIcFVRlgxNhOUr322W7sHFrffkQhGU6EkRj7AUmA337bfb9f1kbVj/hQZtzPFPH6mW1nhnIetwaGepnLncuyhyAPVtf2ORVOsYk/v/sbianxPkUXX0T8rZ6wOLOgH5vd1VXyhbynMWDcndaNhon8VrEU4TcmiwUcGekeyi5o4a4kPasfU4a+SE5v+IaAloR12hfPNE6yLiA9jE3rrUo+QHEnKtbUSTmCEIgHIMHhy6s1CJXjrVFjcHz1jeD1q0MQY7HPKFb1yT/B/YL6W5Vqt2soni3my6ljI1kRolACWB7i7yb/j9YSNlgjxeHz2/6aiqHhwbx6SVKYnJ4OiUKj201zPTCxXhSnqatv2j6uApgkRlpDtkW41fju8t17gAUp4p81G2wrj8ZvOwlpKGx4Lyz6/clKcOsWmPzu1HkDE8RP/63eZFxAdPEcpUe9+4hlLy/+xMl9RV5GonmiuhPAWJudk5pgoagLgtxKkrvfLEwUrJcqXPdXTxoQZYY8zpjLdYSCDmpWj73RIMz8jX3mhNSnwAydmYw58/VjPfVb0CQIZRsgizVJ9UGqNI5scwoGRNxKMOlADOzEq/dsYtfi1IAYb2HE+GKpgbCSMTET23ZN17EL2LNwe0FIwqaG6HDTYDNk+h22BVoQZUDLhx4mMjHC8d4cXYtaVQmtpH5nk1FoLN7NTlPu0AY9dnIyJ8kD+oPuzhJDO/fq5LDdOoIpAV7vwxGbPZUh6jy+rtq72SQQkrBfpHQjqJ/vi+cinM88iZa31qvoZgUCrBR8PX2aAJOnzX4Sq53Dw45yHSbjeHQwkOxuOygiydk3X2er88dahKzdQ28O3Az663jUiWx6ndXJBD2vH/74vX5M14dxZ+KbrDIHSQMp83Q78OQXhkX4V09k7INPO+EoCy1FibL6+d71Zi1to9LtPTM1qiO3WpVwlpKMEYPB2enZexlAy8fhcEL4mnh+MuyyPLp1jXKREoaxDWoztLtYzWPzatnXJL4UrzsIwsSPxeEWIx7eijBIna50vIJELx2bulUInoYLwzD8LDWuHzSgVINMZ3SqgbBZwLnZHJiI8NCA9laBOHZLBZYJQfg3sGey6WDe60maSOQRhlpMDnkfbedt2EFrZP2yBf59TlXtnTUCh5uW4JRWfmVAOdrF7sVc/N6Su98tCe8pTHglpzuXVYnjhQKd54+GAi8OH0jQTVL4SZ+fmH69QPMhSYlod2laoao96i6agUH8jSUhebA6U2VA8bLleatsKjGhxoLJHzNwa0HMT/G6vztLVf835iot1nbb1jMjIWkq+82qI/zxR3FC3MwfiQIBa0+TPQdCoUkV31pWoWp/vNOi/mnqXPC5rcUpWrZTEIH2RsJjarCodtRkYtw4x9uLFYn38qHJ03mDYVmNW1pdyX9A6J56ku9qrXaDAwLWPjIZWbMVSjIKTFS2WQveXAuZCSXVBXoKrV7YB3dg9G+PJcHbXR0h0Ql9OhyhMlPCIAEstavK+YxZdC/8iUkr/E3Kn1DMjy4EjqUTA2UBy5eSCc0sBgo8OQH4N7AvasZHeW+rW4zyY6O6MjEfDBUGKaXKASAQ0WdKWrP4V0Zn9OhlQWV6hpFjMvJTRHPCGZjX4pTAWjKS0M/CiEA3T0j4u/ZUgn1kNkWrrGJD83U8+J/B9aunns8X0V6jdKbKVmjIM/N1MO7SiRwbFJzfjhqJhd1trTo+dJSYpuo7HJkHT2T6rBOvGOm/PFo0NpjufOZKgrqc9ZGVKhHVXW44KRWT1njLm0eaOosZ5UeiBclKMwZvOYhaULCOREbb5kZ6QvqQAsLIfo8zhSf59jJcunqtBq/5/vlXEsKs+lAutrGcPltoFHivPaXuVXszZeMSIJ7DXg8P0+t/pazlxNXapLPK+N5AbhfFbynpsUbIPNBEN+DO4J0tIt30miCRZ1AA/N2ERMyzaQkQJfppqe+Zi1Av/mf+CieOB7oTOKPYpREn3Dg/pcKDQE79G9db09Wzf/pVDgd2vAYTLMzFi+FL5LaYfhnenp1rBOQImNv3P8kDQe9913OmVXbb48fbhKjyUSndFjoTyGP6m50yrvaAuxmoxpx45qiQvDsx5JvPSCDwcSSAwAP4/vJhKZmTfPizWDDNo9CXwP3w+vSxkOYsGaMxuMcpmdDs3/F7aRQz55b7xF2fEuLMeyGyLZRprjs8zjrJynxV9HxSmOZ0MtB+aU3a7qsxCQR48rTQlqQ7VfhgMhPTbWl2gC1mAl+zuENXFY7HoHChbnZJP9VKCEudT8PgODjYSN8xtu8ECBAkLpYeFHJwoGd9pszt861a6+H7wwbOKQD3seFmCaOxvtU4erNLH562+2Sp+aUy1FBBPv195sk56hKfngkw3qY1gKx3aWLqkOFfrdUl/pV6MsJbv6Cv/c95jz5XRaJlrICkSBvZmp5XRs0ZWF0fbEpR5rnlm6NY4DYgF4POUpusEwSVPaggihDFH6IheJfZivk4jNxoTXJ7HUsqXCL1YSjQUM07XluUo0OCtUFzb1DM0Jine7aSBlpjiThOjYA0u97nRtq18OeJ/4IcjhdHRWxoN03k1Z0+xXsEdiiuccEt/jZGB6fEke5EfuGjrahDXwuKS+NEcayn2Sl52hXyOXqbLIu+xz1FfkpiTN6xEQOTv8cyngpbMH6xoYbHQY8mNwz8DU87oEAgG4k0QloWUbQ3JpvkdqSnPUpEwmDl1bjGOgdR3yBDFijAReHPw2eBDCYSsQkE2UTRcvDnepRf7kQzfBsZ0lqsosdSeb5UyX5x6qlRyPU8kKnoc9DQX6PTxKeIxQlyABdEhBNDDXYojFX4NKFQnPalr17i0EBooqMmw0eJf4Gv+H9OzdWjQ3uJVOMR7DOkAQIIccZ1G+x0rNZvJ6sVfJWaKiQlmC58cbZINIgTzfrXXIzLCM2skSLCiJqUoza80nW4qUQM600y00I+80Dcp33u6QF0+2ybdOd8hr53ukfyy0IlNwbrZTnjhYNXdeCwHZe+JQpXjd916E5lwTSzn8vaHSr+uQCgRalhdkb6gSEOdCwwB5W6mA0rmlIndDnbeBwVIwOT+bKOfHkZYmo5NhLZcgMJAZk5HGINKVHxMkJDIbk7GpiJYRKMX4szG4WsoIz9QxMKFdT0BVCjY+h0PNsJPhsBT4sjR8b3ScsQPpqmLQMo5qQqbOP37rugSmImo65fK0cxv4YOb1CMajHPXEgQr57tkuTYqm2wvwHBiSSXYOhSOyq9YyJw+PW11hOreLFGeC76Kzku5K01lQaekoVJZiw3lNTIXkRueojE6E9XEoJXSXMbST4yKpmCTl7bWFUpibqcrUhHqMrAwh9STFZ4jx8xhOKU/RxUZJz5/j1u/zXJTXeocmJN1h+Z2qSn3SWOVPmp7Mz0yFZ+Vi85AqYZiFMVYzSNUihB5VLXTdea+is3pOqGysF2Uhzo/n4Vro6J/QsRAobrxPKGX4nKpLsmVyekZOX+uV4txsyVLiZJXUyArqGZzS86gt9SqZWubKkyudo3MRAbzbvA7herT915Vmq2/pfsCa/zWjSh/DYzl0XWUH5D1DqotzVGF7EFjtz4nwbEzzqRgBYpfA1ARemC276vLV6GwNBeYam9EuRtYLxQxFaKnRNesFa+WzeCPDaXJ+DNYKtLNpLCQnLvVqqzmKBftqVYlPju4qtcLNVnKNpqVJc29An4fBpMyk4s59S1WePLS7VMrz3BKbsSayMxeL/BsIBX4DWo4DU2Fp6xwVz1aXeDLTpLMvIkOBcf3A5W6czRQChepiTxaHUIQjVvAexMCZniGjE9a0dtrcUXc4DxQQPrTpMJqdscjG1mq/XG4b1ZZtcnR4XoAaw1DQHTV5mmMzI2nyrZPtel6UsNyZkLBieXRfudTEN3cIAqUuknEhLJSrdm0pkM7+cbl4s1/niw1r1k9Yj43t81LLkJKwx/ZX6NgPxl6QfH36Sp92IbE2lMXIonl0f6VkZaZruYpNKNkduGYl9U/Ijc4RmZqekTxfhs5mQMF519FqOd80kBAsGZOh4aAqVHwYoXhAPuh22lKea0m+DocSMszB6mtyUAr0yJ4thcIIWAhCdUmunLzcqwnPrDHPBWmhpAjBm5ieUbPxcgF7jB555kiVbqh4vThvyjF5ORkSY9bCfUrXswzcDp3xhYLINcR5U7LULr6V1PPWKTLSHHKgoVC2VeVpJyFrwU0AeUmQX/5N8Of11mG9PnmfAMnlKIEoQ86NuzwGmwxG+dngyg/Ep3tkWr70rSYZT5Jvgtrw7odqZX9D/pIEiDDBC63D8vXXWySaRCniA/SHn92ugX6MtbDBZswdNiQBA+8PPtOoJOPrb7Raz8udZUa6lZcTnZXvfbxe283PXO2XwVGrTGTvR7aKBLnYs6VAZ1O98HqL5gtBRvgD60fC37ulQL02/++/XlLSQ4cVpCWxRfx9j9RpvP+f/8NZbXtfCDw/n/zAbtlakyt/8nfv6KBR9mjuhI/tKdfQONrYj+0q0xZ0zNmoLCgItLXzmp0DEzrmgrIex/Hl7zQl3eaZVP/hd22TYh/zxJI8wCFypX1UR1F0D03OBffZniZSpgk0vNQ8pIoRreOoPpTJUIbIGcJHBarwwlTlyRe/dV3b4ONPP3dc/P2pI9Xqj/nrf700p+JZ5nBLKeR13/9YvSpUperXSf4xwvvf1j8uZ68NzHVZQfDsawglj/VLTJNeTQSjs/LlV25KWzx7yN7L7Vdm8O4zR6rvaOTGelclUIYIEMWXlgyUYg9uK9Y5f+sVD3qNNwOc60T5MZ6fDY7IrMjLb3cmJT62QvCd0+0yOrF059ToVFi+faotKfEBeHNaegLaFp4INry+4UmrsyhmZQGR43Pr+1bXF/simx+bUjQamze3yZrKfuvvyO8ENmO+ZYM+sK1YDdU8D8oNSgZBg0T5Z7osPw+lJfcCXwm/JN94q82ac5QEHMe/fPemjAbCEg5F58o+kCpSgnuHpvSY6b6i20vnd5XkaDnx26c7dNI7Xpl/e6NZvvFmq5ISb5YVWrgQIxMhefWdTplVFWQxxiYjqtrxPtrEx15f/rDuzZ2j8tDOEtm7rUjTmZ85Wq2T5glLtIkPCIVm1KhtK2F2x5tNpFiXa63D+n6mygPiuvm3N1tVEZsbjJoElE/IGEpsL0+8hiBo524MrLglfjksJdzwocw1YRMfoINNEx5DPhMzvyB5mwm8581dgZTEB1Au64nP2jMwWO/YXL/hmxBDgZC09y6T5huZkWvtIxrYl2rTaO4OJM3lsUG3zrXWER2cmAgIiS2fYxwmcZjuqUQooYlvjkzmpgRG6zNGXmZO2R+1/J3p4iQk0+LNhzBlHco9zZ1j0j8c1PwbNvWSAq+8fr5bMjPT1cMStP1DcR9NRoY1SZ3NjjJXMrD/oRbhk/ieJxvkXYer5T0P1cmx3WVK2phLhQEaXxBriMpCKYixFfy7a2BcHt1XIWVFKECTcuZqnypCicQuETe7x3Q22qLjSHdIK2XGWdrVF3/fBiGM7P6vnO7Q9WCeFapYYi4RgASeuTagYZG8F7k5bp1WT0KyToj3ua006vYRLYHZHWwLwTle7xidG3uxeP0c0js8qaWupTA+GVb/0Z1CfWgzMRmeCEvX0JT+n/LNwnTqQDAiF5sHl30+FL3IvWg9W0dA1WT473IgGdz+XTUwWM8wnp8NDDZv7uRWUk0gHTfVHR13hd2D89Ob2cAhDxgn2QQ9bpf0DE5qiYe5SKggPB/fs5GZ4ZLh8WklI3SGYWq2weMhJmyU/cNTWqph9ASPtY+L//G4rXgWpiPiy3bpYxdurjyOPyPx14JMETDIdHbOhflPxbkeXRtGbVDGWrhuqCCoPCQlQ6iYYo5KxGb+fU80yOmr1ggOyAEKFEeI4RgDMaorShTdXUy9Z+Amx037PDzk8QOV8vKZDiVWiUAihggUZM8nh+zDoxMhJT+oTKlAyrQSpPGQZahOlXE0G9PsoQy/R4kaShLnws9DlPJz3VpapFTZUJmn/+a4kqlATLNPtRfyvpG1sxKQc1ScewelL4dDWvrGNUk68fjwqeDhwcBsHyDqEmXZ5UCJELKcLBl8owLyuJLUb0aD2EGcBgbrGYb8bHAkm82UDBCPVORHyz2kGFL3L8qW8qIcvVNk2CWbDB1O+IV606a0wyhxM7SfsiC+oe7fVqyEiLZbV3q6NHeNankFVcbpTNfn4s77sQMVShLouILEgDyvW2dYofq8fq5TwxAnCDpccNh2Dg6Rf5RbJicjqnLoscSPbZrhpfFQQPtw8R5pAKOWkiw/CqoHpIbUYAgi4yggKZEoRCSqJT1nerqqJWysvHZuTqYqUhCtxHIPf6UcV1qAZ6lQjc8rfb/sdbTeoyUIQjxccSnYmUTM3ELNw7SOF4qhrACyh2m9NN8KkqSbDpOzRY5uvTYEUWewLXE8K83M47xvV1DgZ250B+RC08CiI2Ajf+dqv8YrbCnzWUN2xSrtLadc4IPbbIWdeEPmsu+BXn+bbXEMNiQM+dnAQDEgSZgNPFGBSQY6jhgpkQzRaFTLO+FoVLuvXjnTqSZmG6grlHMYMokB2PbQ838UIoL5IB+vnOnQMhwKyOh4WE3SzPBiEObZpgHdKNmseK3+oSkdZ3GwsVhnE7GZsRHf6BjRuV0l+dlaAqNjSEdnLDhmyBndY/wMLe68FvlBzKBia6OM9NThai2tUUpiHpWtQCSKD5CdhspcVUEgQ5AZTMIQOUpKmLJRqVBTMAajIqFEcR74kQZGgqpmoCJRtkMNQoGanA5r+3mixwKViIyehWBdygu9mtAMEbM9PxwPHiL2ItZEk52F182ZCz1MBjqtOEXu4HkUJI2J9DqlPt7uj9LD4NLLNwf135wrnWB2VhGPZc121OalbIHGGM1xt/UsXU6BkJApdLu9F7SsX20dTkm9+DreJaIRaPHP9jiloiRn2UGr1WU+PbfZTWSIhfijFiYmtCcDNzEEly6X+m1gsNZhtMsNDrqIdtRZwX2pQFmDVuRUeT98GcWHsEHUikTiAyjJ0L1VU+rT10tEYa5bydGr5PH0BFStsTsAGCnx5oUeDTPcXp2nGy+loPc/Wq+bD6U0UpxpH4fksCHzd24+a8t9cupKnw4OZfNcqJiw4R5m3tbotG7UkDC6+FCWuPOnXBeYCMlDu8tVAeKjHAKQ+JnOM0JQ8EJB+urKfOrpIdmZ7iqgpEHnkaWpegY54TGoKZXFOXrOPGc2KdEzt2Zl3ewc05b7ROwm/XpBycta/5iuGyoLxwORowy3T43eGTr5HRKJvwhyx5yxpZKtOU4NtIvFlBBSDrIVKogQ60HpjmGqfB/SBonknCBVnCNlPUgrBm/WNRl4SoIsMYAvBZ7HJp8rBQoEmUvLjWyA9PM4Hp+ZniaHGouXFC7oRNu/rWhTER/gdDg0DmEpcE1x3RjiY7ARYMjPBkdsdlYe31+hkf3JQAkJsuHzLL35oGZQGiHszJ4fBSGxg/gwzmLwZeNgswSQAspBlK7YcGlBt0II8+c2UTqnAlMhbb0WR0x+6Jlt6iN55/qAvHWpVy7cGJTXz3XL21f7lEww8XxfQ5F6DuhgYkOGADDgk9flNVFEGGKJ12dHXb7k+6z5WSgYeJI4YspbGRkOefpwpRzdWSqTU5ZywnMwFZzHlBVmyYefapALTYPaYk5WDwRGTcSRGZ0hxWNRgjAKo4zw+pwr3VaYa3lNyEp+jlvJC0GPkDiUGqtkZGF7Tb48tLskZWtodma6HNpeImX5Hjmyq0xudI5pB9npK/36h6nuGJ5zvJmyrTJXGqv9qoxBsCpKrHRfd2Z8fVzpUl5EsF2hkhodKqrlMsujxXvKEFdUKcpdvM9cJ7xfqGkkXbOeH3i0Xv1dNvTc4+TJBqM3juwo0ZiDZKD8tn9rEW/9bQFfFhk9K4FFUK0Ii62VufLofmtQbjLi8+zDNVJRMJ+UbgagupUXZqmJPxm4PnY3FOp1bGBwN7j1OZH2QGO1TM7PBs/5sRGemZWW3gk519Svmy8EYXttgWyvyZP8uI8lFdjMLrQMq+KBV4ZNEQKAB4SAPTZ+5nLhlXj8QIWOWGjqHJWW7oAOtnzzYq+ODWATpQzE2IbaslztAsMMPDM7q2GAu+oL5GbHiG7sEANa0IcDQRmfjKhig4L0vkfrdVQGIYv4i/gF4rEoUpAOBojSVdYzNCkdPePy0J4yKSnI1k6rvuGgnjdG2NqyHG1XR+2qKc9T39Hpy71q0GWTJ0eIu9x3rg3Iza5R3bwpwVHy47ggSsf3VijBuHRzUNUXxmFwTqwJredMcIc0qOo0O6vED1WGeWW03h/ZWaqGbVr1q0u84lrGIMMGPjIZlRfeaNEcHw12dDgkL9ctngynvi7K28N7y/T9xA9DGc/lTFeDuTfbJSV51pT4r77WrMQUde1y87D0j0zpOdWV+1VlunBzQPOKHt1frp1q5AeRo8SHFe8VRDAvK37dOETDDmmpR82DYNL55vU4ldRAqjAQk3lE1AHXDe8ZIz64djLjidS3+wFq5R7Nj1ZIBvKgmPhum6m50nuGg/LO9X71NxHCiIJFxk9pnlvn1D0IrIXPCZIWCOtEmeTa4f2m81JHz8Rn761nrIU13uhwplhjPq9RxftH+VwPaV5UWZFX/NkZc6n09zPnx5CfTUJ+ANklZKyQzcLdPYnCqXw+C4//jYu92snEpo1XxJ4+ztVDBxLek6Jct+ysL5TAxLSWp/J8HlUSyPVBOUJ9KMjNVL8OM6IGR4KW+uGwfEOUdPAHEalMhg4bLv4UWyGxX4d0ZuZw4R9CeWFzQ/Xgg3o0EFJyRupzkd+tJb+27lEdX6HqBqUQxjPQUUY3UGmOvHG+RzdRykiQhKlwVJraRqW9d1wVEpKaOcgPPrlFs3/4N8oP5T5AuQClh0iB+nK/doUNjAVVJYIM8Lr4TQ40WsoNXXH80u/fWqiEjZLDSrqc2PAvtgzruaIo0fJPWYrzJrsHXxT+KM0SisXk2293qPeI10AFO7S9WEuMzx6rke+c7tD3E3LJxqajSWIxJUHjE2EdebC7vkDXko0QBWj3lnxp6RmXkbGgtsc/e7Ra/R+XWoalrQcSO98MTSjevobCOXXQbkm3Z5nx9bsJNqR1nRylpT7BWJunDlUlVTYZ94I3jKPzuNNlNsHM/SCwVj4nAISVcijrx+/6eic9a3GNNyqcSdaY64mxRyj5C/2neM0Oby+WHJpn7pKOmPEWBkmhybx80MeJy0qID+B6RLWA+EBqwPSCWJbQWFBJTDAU0TIQ3h2MvZRhKPEAZmgx7POfX74h3YNT834ehQQVCAXnx967Q18ThWBsQf7L2ERYfRvMFrvWPqzKAcSK0lZrD/6giKoZ+bmZcmh7qbx9xfIUJYJfRAhcJBLV0RcoEtc7xjTlGQLBJg5pYFNkhZj2TtkLtauqOEfviK1ZXhF11XJHg9LzzRPtqij9wLu2yatnu9V3pCZmX6bs22qRANQROqm2VfrFpe01FulYCVDdUHwghChpBB9CpGLxnCWSmy/cGNCZX/ivEstCrMs33mqXdx+r0W46RpJ8951Obb0PhUeUpCVGBkCsIC8QV5SAugqfnGsa1LElkNDe4Sn181C2omNvITgnVB7W+sC2QlWANM7AYXVT6WPuckPlw7K0wKvXVSrwfR6XqiTsjv8uPGjis9bAJmRPtt8oxMfgwcDhcEjfaFCHVSf7nR8dn5Y3L/ZYVYMVEpd7AeP5MViREkbpaDIhWXgh+JiknEZQnp1fA8NHcbCnhzPBnZTYhcQHUFKBpKAOQIAK/JhtF3NzfnUYYgqJ4JeKTZ72cUpPqEeUUpjKPTQalJNXerUEt+g5YjEtyZQV+eSF15t1YCleH5twsXHbBSjKUviKSvI9kpXpUpUIIzW/xHx9a3Wetq2/QaCiK01qynLlbFO/+oVQjfg/dz9fe71V2vomtARFFxVS722/D7MMf8XjlCmvnuuWNy90K2Ek0frkpT4lX8UF2XqnTjv7QkDYrrUNKyFlffD1UOrCwI5ny/ZqQdbwF2HWpjRGOZLXhGjNPx5rftlSdXtmREG8VgO8LB6z4ryspN/n63zfdGYbGDw4zMRicjWegJ8K3HRyI7rSaJZ7AaP8GCwLZMTpcFQqaRPumx92OAeH5beBICW21tOujony/I1BLXe9dq5r0Y+iIFALxluUKenavky5pNCfJVO9gUWtzJTB2IjxldBJxIausmof86ysJGcUid6hQR0qmgyezHT9hcOXgw8GHwvqDeUae0I84G8oWQ/vKZdQlLTqiBTlZenQU86LdeH1KfdhZiYVmTWiOw5jN91meJboaNpW5ZfdTM8mS+gO7qa5Ec/3Z8mLJ9sWBSTiiaIMxygTfDqpUpXJ7MGw/PffvKrdYc89XKtqErlElLYqS7waBXCldUj8Xrc8c7RGE7RRlBIDXiBLBEcSksiA2FQlBIgk+Uj+mrxVmd2FX+jYrlIdD9LcPablP1K969Wjkrmu51AZGGwETIWiMhJIPkIoEURQ1Jbm3DdFxpAfg2XBnT35PXhrAOWMxG0M/8a26nw1BWMG1mTh+M3+0Kjlv9lZF9OvQ3ISQdcQXh9KRGWFXk3XRaFQAhKLSUWRV83Ltp+Eu3mMvigSEJJ3ri0OCrQ3XQhYrtclrnSftvMjhgSDURmbCutzUOrhNSifPXOkRsuA/D2x351zI1Ea4/aXv3tDcuJZPFbOjfV3SBTdVmTKkAgNuIvpHphU0kNJD+jwVbcrZWv4ckAJs6fKL4Q9/4y1w8Sbk704LwhoSQ+iEnMocUFBo3RIqznfu3hzSI8PhQoliJJWU8eI/myiwoO6hHeK11uubIcJfNlwxrsAl1uRL1NK/CX61vHeQLSMm9HA4MEjusLfRT6X+L29X+qPIT8Gy4ILl24iNsKtlX5NWaacwSaMuZbuIBQQJrGTuxOEVCSAmUGQALJpUElQJazW9wwlIKgRbLx0RGHgtVUjvkenFHfx/J3XO763TBWWqeki3ZRtP9FCcEyUa0YCYekZmpJTV/u0BEeXmScjTWorcjWtmE0ZYzKt9NUlPqmv9KnRmQ2bFnUIWZY7Xa62Dat/B1P04FhQ1RCOm/DG8mKvqmJ8fd66kZY8PKV/IC4Qiljszk2WkxC2YFhLWpTnFo/0cKjZkKRmTITJoObVOOlEIWPdUX4SwWcP5JLWbzxWyUB7PGVAwvFQy0hQWjJUcZWZiD3wFiyd/GNgYHA/gddRPyOW+QzAomDPXrwvx3XfXslg3QIlgJLWjc4R3SgpT+Gv4UJlE6bTB0AU8PcsHKRpe2cK/Lj6S3QCOgSnudvqiLLBc1Mq2sqw0PhIC5Qi/uA5eWQvQ0HTNYWWbGJ8O5Sr2PgxV9NCSdmLDi5GZfA6kCMd+BkHCs3xveXaofTcw3XSUJUrnX0TamLuTBvXcpp6SByiKgvdCT/8nu3aJs9oDkgP38O0HIlMSigSlaFAUAndQ7vLtDWesouOUZidlalgRElJWX62jrW4m3mZ/CxmYcp9HGdi1wSlKsgkrfdqzC7JSfoceKLwXdEFNzYxrWQo8f3ioyfbk6GZShieb3aO6vPyucWHF0ZwwLoy2oTZWUvGJKQ5lIiuRsnLwMBg7SPb7dROX2YgLgWCa/m8uF+fFcbwbLAi5GQRcOfTv0NYICCUwhjpYJdc9jYULtlmeK1lROrLfTpugE4knbcUH0JKhg2bOx1lzz5UrSoRuSs7awu0vPXw7jJVlJhWzs8d21ki0+FZudg8pH6iwbFpbV2nmwxvEaQFFYRsokSweROaiDLy5vkuefpwtRIKbetN8BO1dI1pWWjP1iJNgiY08MTFHlU6UKDwzVD24bwhEFMhxmjMyLaaXH08a4MCk5/r0dIdhIs2+ruBHcKICofRG4JDyZA/EBU8RWTUQBQXKkOA6fX4lBjV8fCeUvXH1JQSHJkjRX6PlORlaRgmEQEkc/N3Igco4VF65HwgPPZUeogoydJLgeiCnBQBhwYGBhsfaYS41uYlbcKwwU0bI4Pu502S+VQyWBFoVaarCcWjoz+gSguXqWbYuJ2ypcov9WU5EmHyeGRG82YwPkNsIEukQzMDy5vllI+9f5d85dWbcupyn5ZPeAzlI9KY33WkWsta/iyra4yyC6ZpNl+6q9j0USJOXurR12fW0JYSt/jd1JWnJaskV7DEkBzNHLAMlKjIzLyxFfyCQaJQYiAKP/zcdnntbJeWgFCd8PBMBMM6l4oONUzMqEnlRZayRQkPRYcSHYF+HLur0CJNjx8ol4qiHCWBKCLk5kBOCJO0RyakO9M0owaiws9ThluonnhcM+IIjli1M1eWhJ05kh5DgfNpJhGfI/iHbCKCWoz6wwcIHySRmRlthyfBmfIVd177txWq14mp9GX5mfL88Vr57tkukRglLJ4npu9VfaVfSVJXX0CO7CpRApmbnankic4Np8MiWwe2FWnpkHVD/eP94u+8nxZBy9HkalvtxvNFOZH3QkeBuKy5bBsVVq4Rw2DJy3HotWPaxg02Khzx0tZUeEZi8Rlx9rDcwhy3HN1VKueaBvTz9dbPiDaQEPR6J2Gnd3W86yHksK+vTx5//PFFX/9v/+2/yYc+9CG5cuWK/O7v/q5cvHhR8vPz5WMf+5j8+I//+B2/3kYNObxbcKFOxQ21qCKUoyAiKBu0gmfEJ8MPT4TlavuImpj54GdD3rWlQAITYensC2i7dkNVvkCfOnopo6VpCQtChT+IX6Dq0lwdzcCkdMZEcJWiGuGt+dbJdukfnpTjO/OlyDEqo23XJTAyZpGhkmKp27NHhiRP/ueXL1tT2+MlG72r0JKVQ0kDuRLToYiWvzif1t5xNWhj/tVE25xMa66YK03OXhuQiy1DOgYDDwuEBnJHtxk1bTqtqFlD4Gg7Z3grpUHUsG01eTI4PCmN1fnSOxKUs9cHpKVrVAkh0QD7thZLY41fPOlp4nbOiGOoVaaaTsp0902R2Rlx5pVI9tYj4ipvlOFolrx2vlsVmeHxaVVvOG8UKY4J1YbxDdEZkfa+gHaaoUxRqsRwXeTPkkKfS2aiMYmlOTSvh3OnVMbjOG/IU1PbsJYCayv9MjI2LdfbR2VkfFo3cNYLkkMJEKUOMzg/x9gMyCx/KJuV5nvEwxDMWEzGpylzjknv4ISV8OxMl8oSn+Yi2Y/ZaCZP8qNIOSf7ipsExp9ApklKTmaR2iifE2sZZo1XB7Ps0yNBLZNTEvcwbig9TVPyCb91xG8GGDJNZyafl3wO8ztBAOm9cvpsuITnV155RX7+539eXnrppXjXiIWcnBwJBoPy/PPPy9NPPy0/+ZM/KWfPnpXf+q3fkt/8zd+UD3/4w3f0eob8LAYXbv/otJy83KP+Fjq7KBdxZ8sdP+WQx/ZVyND4tI6S4I6e94oNFZXgrYs9etfPpkhbNQbp2ZlZeexgpW7kupEOT8Vnf+Vpizim6scOVGiZhqyYLZU+6R+ZVkL03iMlIp3npeXq9fissTQlKVqGSk+TY089IqdH8uQbp6zW+sRfLhVTnGnynodqtOTzrZMdOlUe8oAy5Uq3xkE01hVoqCFPeuJyj7x9pX9RgjGKC6oKv9RvX8FPVKHnrx1rrE1kVknbJz6wSxOF/79/u6yjHhaipsQnH3l3jaS3nZbhN77MRbjoMd6GA+J+6PulaWBGXjvXLV3943NdcBwPnqtH9pVJLdlHTQOa5cO62CoUahbKw/a6fE2i5r1k3AiltEyXUwkixnIM3we2l6j36Z9fuaH/hvRQEnzfI7VqIKelHtID6aL0yXHkZmXI44cqpaYkR85e69fvPbKvQpW3E5dI+V58Tlw3D+8p09LY2v8kWhnCszENh2Rtk/0eMcusptRLkPmG+5xY6zBrfO8xKyLnbw5qA4h9jXs8GRIMhvWGc1tNvuyo9s99BtvNGfqz91gJ3XAJz9evX5fa2lopLi5e9L2/+Zu/EZfLJb/9278tTqdTtmzZIm1tbfKZz3zmjsmPwWKwYb99jTKV9YERXJCajJTZPjChioFdyoBXQygu3BySkXFrFATlKxg/GyGbI0nI3C2gHgE2YsiUnd3zyjud8uTBKv13MDSj5mRftktygj1y6XqT9ToE+MU9LhAgjqX36gXZvfu4vJmVIYGp8KIbbcpdyK1vXezV2V2AUQ4l+flKaijj/OurzarOHNtdJj5PpioqbGqQOMo/GLTxxaBoMSoCDxKKEuQu8Xe6uTsg//Jqs3z4qS1a8tK63AL0j05K+miXjLz5laTEB0x1XJOBsi651OPUCfM7a/P1tXgpPEgQyqstw/peDY5MLUq2tsFssfFgRH1Jc0NrI1ZXV3gmprkcl5oHxLm1RFUhwDkzu8zhSJNvvNmmHi3WC6+QTcCIEPjqq83y0ed2qCLIsaE+8Z6lmr7Oe8UQ20f2lG0IAyKlvavNw0mJj/1hj/RPN53xQhmsd6SlWflqNvFJhuttw+ohLPG75/yha0FzWRefN9euXVNSkwynT5+Wo0ePKvGx8dBDD0lra6sMDg7ex6PcuICEYCheSHgSwWR1xktMJDwGcs+Q0O74+AE8KWwK+FyG4vO3ID5KJkhMdqUpCSJHiP2Ur/GalJ4gK2wcqBNHGnKk98Y1VSLUO5KRrqRDk43TLAUIAjbccl2O7khuyMWvUuBzq+/nsf2VWgKjjd7vy9TZXATzIc1CIBii2tIzJpdbhjVQz27HtI/PCj+MakggoxYW3szwaKLdgyGrld8Gag2vTzzABx6tk8GxkEjVPkn3Jp+s7Siqk6sXm2R2ekJJCa3+BA1iBIes9Q5O6lqiuqRqdQckPJ9vSvW7YRNXh1y4OaidZTaO7CxR8meDNYZo2QneNt6+0qcEEnJL2W1obHrJFGjmtAVWKQX6fmMyNCNdAymCQONQj1Tv+H1NszUwWA1EZmblRufi8TYLwWNu5eavDawb5ScvL08+8pGPSEtLi9TU1MjP/uzPqg+ot7dXtm3bNu/xtkLU09MjhYVLd6MsJY/eK9gy3ErluLUGjrtveOnocU+mSzo7R5WcZGWSISO6KUIg+DsECrZPaziqCUSGtnRUHkdcAXC7nNqijqKgmcWWo1pbJCFXE1MRVRpKc9LkWt+ghgyykaBc2BkSmKL5Oj8fGByUqn3Oeb9ybMJPH6kWX3amvHymU14/362+GUY6oDBRGsKTBFHjGHk8pmt8PvwbU3MVylCvtcFR2gqHZnUOEqMUvn2qPemvOAGKlO/wMVkEMF12NxTq89F+PzQwLOndFyU3O1221jws5UU9MtN6dl4wYCS7SIZv9Eh6bYm09IX0OxAxzhfjN8cdjcyqukbGUar3i/cCJQ5PEh1kiXBKmnqXIFFjE1Nq+u6InytqBV1wnCDPzZpD/vw5dL7dUnY6+sfF5azUDCi8RJTSrHb51Hd7+InwBqyFO8K7QWgqoiXP5YgNYZ5sBk6nY8N8TqwHmDW+t5ieJnssMu96t/+e+DVU4PDMrGQtuFF6kFjz5CcajUpzc7M0NDTIr/zKr4jX65UXXnhBfvqnf1r+z//5PzI9PS0ZGfPnJGVmWum2oZBVarld8KZRF77X8Pk8sl6RkenSOm7q7zslPT0dE5m43dbjbEWAcD/ARPk0B8RCdPwDLel1Fblzj9WumAU5wNYcdozUaaq+HN9TIQ4HaoNTS1ILyykQFL7HZszrMjqDuWQQKiaQP3W4UstnjG/gsbppxzsSGL2BmsTYB0IPLRbj0NERKEBMkMfDQ7ZQR7/lCcNTA6Ep9Jeo14dyUjL2Y3U9xFTtgVzs21akoZCQA5DmyNTXGRsalTMjYxLYViPbq3dLrPOifp81wSPCGqbHIOe3PkQmVX0i28erZTU8S5x7qveLD37IPQZllLlE2KVKi4Bavwt2fV67OeKP4zVYf46Mr6dRB5s7V4e+RnF+tkYIjMY/+DA5owYl+vZsZGa6xO9PPqNrPWE8NLPk70ni+WZ7M+e69TbK58R6gVnje4PoyJS4dRp78mvcBqo8vxfcQK0VrHnyQznrxIkTurG63dbC7d69W5qamuSzn/2sfi0cnp9Ca5OerKw7+zBlUwwElg5kuh2wEfDLFggQ6rf+THZsVrlZLmkOph5sOp5OarDl88DoBkIhAvlyJDrDvC2ZU2asrJkJLWe1do3pBsn4CdQVFAzUHbJlHA7oQEy/BzEam7B8KhlVeZLj98nI0GK5FRUEM3Zz15gcOrRDysoL5ae+N1/C4Rn1Y0AUTl3qkWK/RyfDq4IxE4uXaMJqviaHiJEPEAD2aZ6TshbKkyczIoUHKrRNnOuklAC/mVmdt6VJycmEC4flZSor8sr5GzfVKIwXJnEa+eRMmuR5/RKZnlAC0nStVcoe3i456dclFkE9i4lMDIq/qEgmHBDF+SVIVLSegQkNFESJoRRmvw8LMTPjlmydLzab9DF0u9meLMImbTWGDrbqkhzt2uJr/IE86YiLhPRGyCBt8Vdah1UdYmYPxBPCRfmScuNCYSSL8MqRe9dk8KBAfnY0Yo39WAoleR4JTYdleiq0YT4n1gPMGt9bzEZnhduw8YTPET5TIT6hUGTO0JyV65FYdGbVf8d5bzeU4Tk7e7EKs3XrVnnttdektLRU+vtvdeEA+98lJSV3/Jqr0QnAL9t67TCgJGHNc0puXB0NhLQ7CnObfcHzfzZRwvMoxYBje0qlrTcgF24MqVKB8tNEPTgWU+LB8zMpnb/DGtgwIUTMzaK0hCLzzJEq2bF/t5x59U2JBK31pEuMtknauSE+oGTbDglHRcL8R7NznOqLoQWT9wEJlkwhiFYirrWPyLFdJToxnbIaJRsmnAPMwHhU6F6iffzdR2usX/YM51zGjRr64l4fR5qVynywsURyPC7ZVs3AVo9OgcdPA7ErzM2SmdislNbvFxktlrHuThnuH5CbXWNysKBaZnqbdDON9d+Q7YcflhevQyYXe2QgZ5GZmOxvKNJSYapOionJkJbFiAtIdsdGJazQ71bi+g8vNc3xuUvNg9qZxftHGY8PGfKBxiZvffBxzkd3luj5kbB9ZGepltfIG+Ja4LgIh4Rg2vyH1nrMv+v1dyMRtO1DnIl5SAWuETriIil+l9bz58R6gVnjewNiPshU0+T7BVCPZvwziBFFdJpG11BZe80XPlF4Dh48qOpPIsj0oRR25MgRefvtt2UmoUPmrbfekrq6OikosAZxGtw+HEnuzPG0sOEnQ2amU6qKsmXv1sJ5P0u7NVk3kBIycZgU3tQ+qiUkxixAdBi5gMcEoBwRarizPl/Vksf3V0ggPoaBzAiJT1mXwjrZsatBgxP5U1nk1Q8ze5TFU888LK0Tbvn6m+2a6MyfF0+1K9GqLvNZ2TdpoioUfiLC/5j9BWjdhsxgTua5IWSUqyTeVYUSBtk61FiiCkt1sVdJEAqRZhZlOSXPl6FKFgbsrdV+efexajl5qVe+/kardj91x0d5kJr8nbc75KUT7fKtM73yZvO0THpKpW73HpkYD8qM26/kAwXFU1ghFVXlkp+bXNHkMbSnkzWUpb6nuOk8g3LTrV/1XK9bDd/8PyliIrvrC2R7bb6+D9uqrdBDcpgIdDy6s1RJHQodZT97bVD1njpcJf5stxIf/EhTwbCaxPmeDd5jFDj72BgbwjrdDuxk8LUC+3j4sN9Rmy+5OckHy/KYnfWFkpt9d2nfBgZrAbOzMVWDidlIBRpByIFba36+NZ/zg5z+gz/4g5rnQ34Pxud/+Id/kC984QvypS99SQmOnfPzyU9+Us6fPy//9b/+V33sBz/4wTt6zc2a8wOxmQrPanmDjY6yB8SAu1nL/EuAYUgJBnfwnAsJypqEXJUrPrdLO50Gxqa1EwlTJz+Xl+OWmvJcTR0+c6VfFRVC4PA70G5eUZitBmI8PSgceE6O7S7RLBo2UMIHuUzxCKGehKKz8r//6bx87NkacYx2Sm/TNRkZHlEPSmVlmew8fFBuTmbLqxcHJcvjUqKCOkOwH+UmRk4wHgPzLl+fooV+YEI3cbxA6Bc//Ow2Lc3xeuQKTYYYxyGaWFzgyxS32yV5XibSZ2oJieTrntGgtHaPaacYJkDOoxxvU0G2XLoxoCM9GIFBgjLq0avvdKlHCEJFqS4tXjaJRaakKs8lO0rTpS5yQzLGu8Vdf1AclXvkW1dDurGiQJG8bBlnrUGlDZV5cmB7kfh5Hxwx6R0OyuBoSPpGprQ1nfVD6cr3Zqi6Mx2ZlZaegJalCKzk/Dnmhqo8Lcuw9kMTYVXbyA0i7NDrdckPPL1N2/sv3BzQmWe8NpPvUbQglRA7NnmM5FYQpktyczxys3NE15T3qcDnkcM7SqSh0i8+j2UmXwkcaQ7tKISgQvYgnJTpnHFD/f0E1w4lW1r88YRBBFG5vO50TblFgaRzMdnaJpPc1svnxHqGWePVQTRGqOq4fraj8mZ5rPBXwk8ri7Lvm8qy4UIOaVn/oz/6I3n11VclEAjIzp075VOf+pQcPnxYvw/hIeH58uXLUlRUJJ/4xCfkox/96B2/3uYkPw5p7R/XslViPgwEhY2triwnIaQKkhSdG1NA+Shx89LSj0Aqoroxc9fvyUjXzfalU+0aWMhj2Czs9nVKH/hBdNDmzIxsrcqXb55oUxOx2klIZnY4ZEd9vrz3eL28cb5LR1Ts3VokjWUZ4nXO6n6SnpUtF9sm5F++e1PVBEgF5SBUJGaT4RmCMBzfU66bJr6j0XHKNjFVryaCUe3gQvmACJFtw+tC6Ci70aFFCQzFhzLX/oZi2dOQr2tx/saQkivUHHsddNioFxUgpkQBknWwsUizj965RnnWmtdFCnamM02ISOLDA6/4h59qkD1lqCcRaZ/KUuUox2OFAaIq+X1uNWjzvlBS4n1DlYGwdQ1PyrdPd0h3/4SkxT8M+DlUNkaI5GWla5wQHxTBcFTLZTwP7xN+HP1UcIj0DAeVDGOwtrs3uIZJ5EaBwmtEiZJRImzyjDUh1RhCh3LECA68TbzXmB05bggMH4woJOm3GR5I+33PwOTc7DKOiHVgxliB1xrAel/gEE3rvtQ8pF4xG7wfjGDZXuPXsM1gZEbnyS1a23X7ObG+YdZ49W8GIjSdEOkxM6s3WfdzXteGIz/3G5uN/EBmbnbjwxlI6tcFO+sLZFtlbnJDb9LnFN3IyW+BbADKLGyEJBPbZa5E8NR4g/CJYJZ9+YyVzpwIyNbWqlz50fdsl89/7bLUlPuVxKAEMHuLGVwQLBQYylYQn8Q2eMYLNLWP6FgJvCmaLn1zcO4XlE2bVnjGbFxpGdH5VD5vhpZ4CnIxKo/Hjc/p+vycD9PchwIh+c7p9nnHyobPZogS8tzxOh1pwTT59x2vkxOXe+Vmp+VNmvO9ZLmUwFAW4jwfP1ipOyVZSMd2lWmq85bK3JTtovUVftnfUCADEyH57Jcv6pT7ZGAA6kee3ynZCW3WyT7Iuoen5NSl3lsp0guSWymJQYouXL913dDVZXuuwKHtJTrDi6yfRFAGfeJApRLKlYBfG1K2U4UHQiBJ187LTt55ci+RbG2STajet6XwtpJN1vrnxEaAWeONvcb5Gy3h2WB1wZ0/CcpL7RkQBnw1K8lpgEyNT0fknWsDWt6xn5c7fu7YkULxAiUOuLOOY0bNooy5wOybDGy6zJmitPTBp7fK/32xSdOM8RNhvJ0MhqV3gCyeHBmk7JawE2rb9XhIR1po8GLMoR1d3I3bv6KoQ0xlB0w+ry3L1Q2O4/n26U7NrEncwPFB4Q+63t6z6FghMPiFOIYz1/p0hAXQUMeZmA4etTdz1gUVinZwfo5jhFjVlubo9290jsjRXSWa4FxbnjNvNII7XnrcvSVfHOkib57vSUl8wPWOUR2OenxXiXbBJQNrdbl5KOXmDiBqbT0j864bCB9lRsp7AKXmXYeqFpGfIpSujDTttFvJ9dQ/OpWS+OjxRmblatuwPLSzdEFYwr3HStYGwzPXjj/uIzMwMFhbWPOGZ4PVBRvLwOj03GaVCnhxyKRZSSotJObNCz1zfhQbuP3Z9OkEYjJ64nNBjEYYl5CXpUoJPptk4Plor2boJspMWWGWVJXmqJ+Ckhb7EVk4PcNTGmS4EL3Dk1oK21KRp4oO5SIUI8ZFYFrG43T+xoDGtbd0BZQsXW4ZkjcvdM8RH0pztKtT0rraNqIb/PbaPFU5UHASj1U7wVxO6eqf1FZ7Sh8AYkNJESWHgEUIDMTOGn6Zq8Mw7SnpAPLArLMD24ulotinM7EgT9vrCqS+Mk/nhl1rG5W+kZAmbS8ML1wIkpoT07gXAsUOBSoV8IPx8xDVxPeREiHvhQ3Wl3RwiOLcY9IdUleWuyLiY68jqtlyGCBQMZT6nO4V8GkttTYAzo36aML0DAzWJozys8lBeYopvCsByoQVUJd602Jja+3A95L8OVEF8Pa09oyrWZgp6kDbIKOzash941y3khgtOWVnqBKCQoOyQ9oyk8Cvt49oGQ01ADNpdrbl34FUQKDw5dCZBMHAi8Jz2F1JbMhkzfBPlBuyehhh0dw5ot4XOyQRksSoDEZT2Nu73VJPec4qfzm1W4t06Ms3B2VfY7G0947pYFYGeubmuHWjVGVnMqLPTZoxAYCkO1OuwRMEAYNc+rIypLl7VMMU6bCywwbtLjfGgvzMB/eId2uhtuhfahlS9cauXkM8IVql+ZaCZntjFgJShz+HcMpk18RUaOlrAgI4MRVW0jyP4MZiWjrk6/axkwGSl50xpwztbywSf7ZrxV4AzgF1cjlAFK0Zb6uXIqtrswRpTAS/V4nKo4GBwdqBIT8GugGv7HHpy3bUYGpGoUgFfp4NHlSX5irhYQ9EhWmopmPILVuq/LJzS4F2FNEZBMFA4RgOBFURQqXBM6PdZ/ENlk2GcgQlsScOVmonFEZdVSFiVqmCP2xePN/uLUVy/uaAkimehwRpXoOf4zltozJqD23w/AwECO8Pvh/bs8T5kDeox5HmkO++0ylPH66SwOSAkiw2brw8ECDWeWZ2VokZQ0kZGUK5BlUNlQzFC0UJAkZ+DgTm5KUF5TQNEXKoEnT2en9SAoHRvGtwQkuIEKxkwLNkzyhb/B7hj1qaQPC6dokuGR0mRJJOLIgeKhVddwX+LIvQelZOfOYSo1fYCo/ytJpgbSB+K/U+QLjn00MDA4O1AEN+NjnYhChBsYkt5WFgTyHLYblNC7O4NfYgNSAMjMGASFQWZmuKc6YzXZq6x5Q8cWdNJxSenQg9lPEyC51MbDu0epMYbPtVKPHQdQTRodSAKvTY/gptz+a82IBtzub3ZqgxGOJDuCDqEN1Jk9PM9HKqHwmVAdOulS5tBSeiZGBwVjKU4JOB4OA3Qimig4nvkSVEizulMzq1MEpr/o+HCfMoKhF9PfJvyMNBSWLSOooYgGg9srdcrncs9mFVllDycmqoWLL3IhyJytYqvw5hhXgl+m8SsYusGW+GREPJ3yvIH6W4ZMZ0wHtUV5GtAZSpCDElvuwirxzeXiw+T4aamznm2+2x4OcqS3K01LkUWD/yqFYby62NDS3tJSRfGxgYrB2YgrSB5LhdWnZZCmUFXs1jWQ74PyhtrOSumKlZWFPIaEG5oST0le/e1EwalBSb+ADIxevnunQiOUoJ2Tlshp4Mq/UbBQchA+LQ0Teh3VrvOVajQYKVJV5NU8Yv8wPPNEpz16icutQn/SOTOmML6WI6ZBmOeV2UI6aSD4+FlPRhzoVnQDoYCJoIvk5LfU62K15ywew6LkXxOVWcF6rOo/srVPUg14bJ9QwE3VmXLz/07m3WsNbCbJ2aTo7QE/sr1OMyEggtUjUggKwFKlgy4JtiSjwDM0ndTvTa2KAsxVqkIj4AElFbboVKpgKaT0OVf8nuKoh1LuGPd9Hyys+RFbJwDtn8YxHZVpOn7eWrDUz/9ky6VPDnuLWsa6peBgZrE0b5uU+w8my0YqGb5ZqaKxOLaQozyg+ll4VgVtOhncXxmQ2UICyyYpc7+DsbszVU1Oo8utG5tEGVTTFLiYu1O/C/3qFJLfdAQNhcmPtVlJ89Z6BlztT1thE5vqdMyzl4cihBMWQT0oXhGRJBgjImbqaLZzgd6u9BfaGTSxwxJTmkLuMZ+pdXbmrnFwoO+SyjE9PayfOeh2rl9KUeJU39w9bYDW1dp5Shg/yYUD+jpUCSoclCwiBtpSk7tWTG642MTcnW6gI50FCoqca9FVapz+Nx6jngjULZePZojeysy5PBsZD888tNi0gWCs6Th6pkSwUKSFgXHuXGnenS94GREaMTIT1OZnZ94NF6ee1sl65Rvljrx/ey3Onyg89sl9LcDC3XpQJmZBQkynIt3Ywfmf99MnsaqnJ1PfBrMVeMK0JVvXjpCUP2wW3Ft3WHZU2Lt9RB/GO2KZogyWO7S+X05b5FfjKuxx31BVJRkH1fMkV4ja2V1tpApBeuDcQHIpuRznqs+uEYGBjcAUzOz2rn/GAono5K93BQegdIKiZpN0vViJxMaxNdK4COYSqmTZfyjieTTT1X05j5GkrLbMwhZQVZ4s3OVGMv5lo2f86J+S3+rAyZCEU0vThVBxkk4pH95ZIX9/4Agvi++PINff2rrcOa17O7vlBDAfEQxeKT4GtKc6W80CM3OgOakwPBwdBM2YvFptsK0zSlMVQWvDEEFVI2I30UgrV/a5GqOf/40jVNd95ek6clDMzS1vT2NFU0vuexegkGI9LUOabPg5eGSACSmim14WnheRur/VJV7JW2vgn19tDd9Oi+cp0jdnhniXpvMh2i5unhyYiW1N65PqCEhdRlko7LCzySRkhjepoEghHpHJjU14KQMgersTZPM2x4k4LqbRqR7oFJTW+O2SXE4hwdDcKx+nMzpSgvWyYmI5qZhJpGqCBrUuJnGPDSJZtbcEggGJb23nE1LvO+s74YmCFtXL7M6+kfndauNwL/8Pjs3lIgpXlZKyYAECYCAXl/ILQQDFQrSDBJ2pp+nWY9BjM57zuPgRhDUFEv7//v0q214brl/a0t9Ul+Tubc2twOTAbN6sOs8erDuU5yfgz5WU3y43BIU9eYDuXMdLvmwuEAGywzjZiHdT8TMFcC++LhqAjlu94+rP9mrMRUMCrlxV45cbFHNx4UE0gOfhZ8LszC2l2XL4OBaTlztX/RXTplKUpNZflZqhjYQBH7+lvt2vE0NjGtE9BfO9ut5NEuo+FhYa0IOGTeV2mBV/7ma1fm2o7ZcPDfQEh++JlGHavARvrtUx3anYUiQ8mMjZlOLbwbkCYSeElcTgQKzvG95fLe4zXicqbLiyfbtZsrXcc3WNcG+gaJz4e2F8mNjjE5c21A1SnIDJPVm9rHdJzDkV2l8sPPNuoxozTRBcTGjkDCa0NYDjSWyJMHKsQVNyGnpaXpZmpPT2eQqP2i7f2T8sLrLTI2uaAslu6Qw9tL1ViNlwjlxm55h1xod1Z4Rq879Vrdxq8+1wSlNJ8va96HWmhmVk5d7tNyG4RTVcFZypAh8WZlaJBkdiZG+QVJsCifah6meMbYlLCau5N1UlWV+mR/Q6GWzuxz4Vyt57TiE9bC74sGe85YSeN3ArMxrz7MGq8+nOuE/Jiy1yqBD+iekSndMMmwWQg2YYLvvJ5KyV1jQWh8gLNBoWSgPgB4CmMFGCdBazcqCOoQpk4I0EQwLH3DDi1/YSLeUu7TBF9as7mbB6gTmHs9bOoLCB9dMcyIotyzrSZfvvpqS0KbtqVSsIrpTmuy+8HGYiUupCvb3VKYmdlwKS+xOTZ3BeT/e/Ha3ObocNASbvmXXrjWIl63RcSuto4kXYeLNwelodI6v5norDyyv0LLMC3+gPqLMICTG/TauR49Bspu9ryyl062zylf5Brt21qgXV52d9rwAlWMc4IQPbqvTGYikLxZCYUWf3CMTITV7Iy5l/JdYis153n6Sp88sq9cyTWKXFv34uniet1lVUnuCjxcidcEHXGJgLCevT6o563ntCCbCSIIASYskuuC34PxIMGIAe1049ghzbzfpy73qA8qGTp6A2qe3l2fr+tvdditnRuGNVXCNjAwWBGM4XmVMBOL6fTypT6i2ayau8eSkqMHDdqtSRW272gpC7GZstlDfACqRWAqrIoKoORBOznjGDRDJt0h5fkeOdxYrH+qirzixiOSbFFiMZ3aTkoxvh98PXRD4TeyJ2ZDaHKzMrWDCkUFH8+5pgE5d71f7zAgKXiNaC2HaEEO+HkbEK+ju0q1TFJemK3KCgrFwtZl1BKIF89JizXdW0OBoI4z6BuZVOKFAvTKmQ5Nvkb14PGU/p46XKnzyBJLfrTvN3WMzc38SoWz1wdkbDJ1vg7XCWvLa2W70/XcFhp8aaUnjZqyG3O9Ul13+HhWEli5FJjRRpfaUqBjj3Pi2LuHJq016xhRtQ71jTiCS82D2nG31O9KW29AS5QGBgYG9wJG+VklsPmn6shJBNPReWzmGkuCheCosTauYrFJsbnfWDB2AsLD16fDlvGZcDxMsMHQjLjiQzhXdmfsUK8IJOv01X41Gbvis7gObCuSE5d6tYRWlG+RGnw+bPKHthfr61HqwePCeuKH+eZbbXKze0w9GCQvcxwoFLSf055Ndg8KFeSGfzMuwwZlNo6jMM+jpSV8TTtq8zQYEH8HwYoMCH3mWI0+Dxs5vhz+/+ZFkq3nKyClBVk6QZ6OMNSdVKGSvBamZW++1Sm2EBwTQYeA8/FluSTL7bMGioZmrAwj5pkFw/q+oEalAutLrAAE9U4AceJYVhLih7HbnZmuKtDCY0KpI/CS83a50qUo1520DEy5DrLk9i1O7TYwMDC4XRjys0pg9tJKav8YWtei62rh/sNxcve+0F+xcPOzY01mbyPYDXI1NhXWkRhjUxHduHm9ifGQvHWxR7u1yO2hXEIGD6ZdFBA6qphczoiL9x6vkxdPtqmZmM0T301X/4SqE4QO8rNkB6Fo5eZkaCs7RmAIHqMp6KaijEb3lq3a8DoMPkVNSYzxg2yQowM521FXYKkYwYganBcSH4APhjZ4lLLlyMZShIX3JJEY6BR7h0OnuOd4MuZ8WZC05ejmrbydO1d/OJ+VAIWtrXc86bmp7yl+0YyNh7R0mSqoMFVatYGBgcHtYm3JDRsIlGgwzS4HPCL3I5vkdoF52C4HsUeSscLdNybhpVKfIRFs9hm3cU4QAzwvkAqCAjELF/gyNe0YVQlFgDLXvq2Fmu7Ma1hmZWszxHf08tsduulDzjgcPESoE1src5X0oBKRZcR7AkmhM428G4IMeW6671B8tFU8Rvp0jhIEu6srMXNo7rijs9I/MqXlNjKKEoeeJgLFii40lC0UsVRQIpPQAbcQvB9cLwuhoc9xYzSVLEjhcmobCtFKk4pTJnUvuBZSgcf1DU0l/R5G7tz4DDbCMVMRKlvVMjAwMLgXWHu77gYBIXG0Hi+H+opcJRprDdlup5QWeueNpMDfQRkqEXR8UXKxiRDkoqSA5GTnsmoPPzVF63IgJMPjISUrECc2b/5OgKHX7dKMl7HxaSVgdEPxGnsbipR0UG6CVNzoHFPDNJskmzoJyrTGM0MLNQgzLj/H9zFEozI9fqBSdtYVaDkMAoqnCV/QQ7tLtUsJozKP5z3q6l9sHAYQKUILUSyGF4QS2mjrnZA9Wwrnhpdi8iULJi/HrcZle3RGTblP8rypCQWq0XLBg5z7rnpGgyydhkzZDqJ5p4BwEeJHjtBSoBzJgFlLPVsMCCvhj/bctVQdaPk+j+TchkHbwMDAYCmYT5NVAl0pEAU1CKfoYiEErvw+BbPdLujG2l6dJ4OjU9qFg68Gf0YoHJHGmjxtpdb8FYdDyxb8vzgvSz0tO2ryF3VzzXtuh0jX4KSak2djjLOY0U4oiACEgM2SUhJK0NzPxCx/FJstPp2DO0rkcy9c1vZ6/Em2YlJdkqNt7f3DQTm4vVjzV+z9dCru86FEhdGZFOV9xA0Ue8XpTNfcHQaKQpautXWIz2tlBUGImjsIbZxNqtbgSRqfjghiVzLBhaBFzNysDaUdSmP4clgi1hWyRxYQZIwxa6kmImjScbFXuvrHk5bXAOuwb2uRvHW+O+X636vrjq49iBZenmTPBZ+hLJjjdupxUc5cdE6xmASnI7KzvkCutAwlneFlEzruEdZiidjAwGD9wZCfVURWRpoc31MuV9qG1ctig7JNRXGOek3u5u57tUErODOmLjYPy8DwpN7p45HZVuVXkkG7cu/AlCoXlKdQE3bWFujjJkIzauCdnbHu/gt9mbpBEviIUZbnIY+H4eGRmYiSDjZ0SkRlRdlKBmgLhwRRXmLPi8Ucum51pT7xetLkI8/vkOGxoAYCQtDYbCldkR7Nz01NR3Q2F3k/EB++RwYEKg1t6pXF2eojQYXBB0TyNqGBHX3jqgI9vr9CZ0qV5rvlQ083yBvne5R42PsvHWMP7SmX+jIUPof8uw/vlZdOtMu1dqtLDjK0d2uxPHusRmrLsnQTH6nOl5tdo+ILZ8wpYKhne7YUqOqz3CiojDSHHN1VJldahzSNm5RhwHOzZihZ2ZlpmlHExHfKTbZXJtl1h4+LtQlHrZIZLeUQspUQI46VvCBX/HhQcRJLXYyb4PuU4LZU5iZNDwdkO+HBKvRXyvhEWCaDttFeNKASYlSQs/zaGBgYGKwUJuRwtROeYZiYaWMiI2NBlfWzMinlWCWQ9QDiXcanrY4iylGUbyAREBW8MNys055OeQoPzaXWUXntXJc0o+yoGuOVR/dVapcW5IKvs2kzImH3lkIlCf/2ZquGCVLKKvBTEmKiOv4ba4wGCgHGZTbmmrJcyXY5JDA9o0nJPO/X32zVx6FOoY7gF4KlsNmTuUPZBSLDmnMOtMND4i7cHNYhpyV52RIMRfR1D+8oldoyn3z9rRZp7xmX/+eHDkhhTqZMR2dkdCKs63Aa1MQAAD+eSURBVMAa5Ga79Lw1yCstTULRGVX5IBN0gTEIlfKfy8WYBtGW7kxKeBC6yKwmZ/M86nPyZmpMwMGthUuqZrfeE0jLjHbX8Rus6+92zvtZHgPZREGDSCRed5CuSU2sHtHxHrZ/ipBI1C7UsLQVhpexnvi2KCfqyA9nuh5LIoni0ZBoxkEkA6XLxw9W6sBbngfDO2QNAg4p2wyfUiaAb/Vh1nj14TQhhwZziMWkOC9bXBKbuxjWC/GxO9e8+G/ieT42MhcZXmPy+sVe+corN+cKRCgATFH/wjeuKrHwZmfoZswGR0ZQZ/+4JjaTWXO1bUTTfhk90T8S1AGlAB8QRmdapjEvN1TkynserpMvvHhNc3ZQp+h4YuwEZSUUCAzLlJpQcSAVEKQM15R2gKWlO+RDTzTIt093yuXWYd2kQ9lRbbmmlf2d64PyxMEKqS3xydlrg3KlbUSe3FcmrhmHFOVkiiRYuXg/SWO+2DYsX3utRUuA2HKzslxzal9NWY4mOJN3c+btTv0aapnb7ZozJtOtxTwoTNPMPFv+PYlp2cnjutX6vZA08e9sJqsnGO/t624iFFVP08IEbkpTrDHrtbM2f0WmQJ6T8p+PIaoJg1QTr3Geh5BCFDXa/nl+W7FChaOU6k63Eq0zFlxXm4H4GBgY3F8Y8mNwz9A/FpIXXmue54xBRUCdQQ3B00OJgzt6G9zhv3q2U8uDBN1poGIoOrc52kbq7XX5mq8DUJdOXu6Vrr5x/ffVtmFNen7lTJdMhy2fEEQJNYXk52O7StTHg6+IfRTFh9lQEB28ShjT8WYBe7/muT75vbs0m4eZYE8dKE953mPBsHz7ZNtcyzZ0IrHMSbmN5GpIBYoLXiJyk3qGpuYmwesYijSRsqJ6XYPV3PBRhPDXLCQ+ibjRMaoDavOXMGDfLiBADeU+qS72qmrF+6hGc7czofXewCA5Vvv3wmBzwXR7GdwTZGamyzvXrRwdG9zVo/zY4y2gLaQzJ8a4QD7sAZ3ve6RODjRiUg6pAgRJwp/yriNVOmqCIDxUoLKiHO3WosQF8AqR+/Ouo9U6rR0lh9eAaFFWg8DsaSjUri3KTNuq8zXjJ8+XqV+j2ytZ+jJG3mM7S62p9Qu8WRCIyfCM9I9NazfXroYi2VLhn0fsbEDCIF6EFLIeBAyibNnEB9DizTm29YxL0J7jtUrQ6fIpWs8TsRrp4xofkIZK5JRcj0uy4h1wBgapIkPCMzEZGg9J19CUDFMyjpeuDQzuBkb5MbgnIFyPklIi6JJiw+eDivwdMm6yPC7d6CmTMALE9ouQw0M20C6Mv9rxlaHlK/wor53rVi9Qab5DVRSUILJ5tlXnzb0WCc34cfD7QIJokyc3BqPt3/zrZX1MVWmOPHmoUksszMeiNo3nhbJYqjZ2SBOt+4lhjgzzvHh9SNUljEY3ukbV64MB+sC2YrnYMqhpxDZmZkRC6rtB3XHE/TfOuTEhNiAB48GItPQEZFdN3qqRAnw5KwkMpF3eeq/uzevq+aP3GK5jsAJwmTR1BeRGx8i8jlk6B7fX5ktFYVZi9qiBwW3BkB+De4I0R5q2KaPk1Ff4pKrEpyZjWsurinPUUDs6MS1F/qw5k65CDc0O/Tk2ZdQaSlQ83h4Cmrh5xgd5q8maskkiIFqMtqDbiteljZ50aJvc3Owc0z94kFA1CD3EexOOLm7Btu861WBd6tPoAsBd54mLvXps5A5xPihQlLB0qncspl1i3zrVMZcUPTY5rS351WU+Vb7ITOJnUZMoqUHkAKSOzKfOvnENYcxcpfwnO1NnObDeK3xo6tdKc+j4FogpihNT3HlPMMcbxcdgqWvveueoXG4eWvQ9SuKnr/TKbGOJ1JR4zXVkcEcw5MfgnoCw4B31+eLzZmgJ61un2lWtefZYrXp5Ml0YW7OV7BAKiFEZ7qJdPRnpGkj4zrUB2VqdJ9WlPlVmEsEeTPfU+GRIyRMt3Ym+oKQZM7UF0j9qlXey3HRDufT1xidCUlPm0/Z4kpdRnpJlMaEQQZQcsRmdIs5Gjs8I4oNxN89nDVbFVN0X9yNR6mO0xiP7y+X1s91KgGilz3A5deApa8ExADrO9m4t0q63qy3D2taNBwYvDspMZvryCeF3AuZskZeUaop64kwySlR3vLk4HNLeP6ElxkR/EWvEe4yheg3mexqsAWDIv95mRUYkAzdPl1uGpDjfs+bmIhqsD5irxuCeIBye0c0M5eZ806CqMOyZHf0BaajK1bt+Nv4cb4aWfOrKczXfhrlPhCNS6jq6q0Q3Q4jQQvMrUvfs7KyWn1q7xzQQMFlong0sAZigCSfETL1/W7Hm/2BuphWSn2eWF89JRlFpfpYSJDKJ8AWVFWTJEweqpKVzVLI9ZBTNqurDOVB6Y6L8q+e6dLwF4zf4OYBi9faVPi2nkU9DKYwS2LW2YS39aWt7OkqXaNgi3iV8Qjvr8rVEB7mDZK0mJ/C40qW2bPmk6Kp4NMCdgHPoHJzQsSULjdWsER6tC82DpmphkPTaoaS8XGmWrlFS1e9WnTTYnDDkx+CODc5uyEJCG3U4HNUZV4kzzZraR7WEU1Xi1ewXCADkAeJRxCiJXaXyI882yv6thTqCQk22sZgOMkV1oAV8a5VfFZL0OGnYXlMgu+rzNPeHC5gyCmMfGJNAXgxE5P2Pb5Ha0hw5vKtMTl/tU/MyJl9Umn946boU5GTK00eq1aA9NBrU42G6O2oHGTc/9Mw2bcOnVJWb5Zpra8cnVFOeo0oPhA/gX4IMQRi0IwW/zGRECYyW2LrG9BgJ8kN9guxQ9tJ294x0uXRzUJOQeV1UJUghYYP3ArTh8x5B0OzwZAgNcQH4owAqVoHfo4GQvDf8IR2b+IBbz2PNSlspmBh/pWV4kb/Hfh7KGgybDSQQIx1vkp5mzKx3CdZwPa8j18ZSNzaJICnd8pIZGNweTNnL4LbAvRgdTnYpg426sTpPCv1u9dPk57g0rwYFiNZ0fD+oIN/3xBYd/UANn7IPygOhg5RfKHcV5nnkA49tkXA0KpdvDikR+Hffv08GR4LS3heQUCQqBxtLtDurxO+RmeiMvPtIpexuKFSfT2t3QD00x3aVSm25T1OZu/qnJBqZkQ88Wq93koNjU+pLwvRMmF+jJ09LcGevDygBorOJf++sz1ciw2v5s1xWNhMt+JEZLZH1DU9rR9qRXaX6c81xszYKEmUuykn4alB2qsp8+jyUBV3p6dJYm6f5RYNjQSUh6hvK86jSNThqJSQ3VOXpz99N6zdEhxDIroGAkjgIGgSxNN9j5QjNzsqRHaVSXR6Uq61W0CHEDvWO9yUvi/BGKwyREgQde5yPNztT07ohRkvdOZHhtFDxwRTPpsYdPWSMsh/T3g9sLZLRyZAmQFN+hBSimOGNMu7olYH9HyI/OhnWa53fMXK1UFWZM7iS4My1BK6PFT1ulUrDBhsfJuH5fiQ8b5BU0cloTL72eoucudo7r6WddmVCB/HPNLUN69dQaUIRK7sFMsJm39E7rmMx6qv8qnacuTqgZuRcb4ZugkW5bvnhZ7fL7i1+6R4Myitvd6pSlOVxxu8GQ5oM/exDNbKl3CcXmkfky680qVKBb4gdgNEIdHr90LONMhoIaVmKfJ0gZbiZmJbZIGz4kfCdjASCUlGSoyqNMz1d2+JfP9ulpulH91XI88frNEzwUvOwkrCugUlVdphLBtlqrMnXMt3ZawO64fO8lOhoo0fZIsDvetuw/p3NH+WJtWH8Br95kKmJqbA8vKdcSvI9Ulnkla0V/rva9FF7bvYE5JtvtcrIggGnjMB4/nitlBdkydvXB+XfXm9RkzZryCuGQ1GpKPHK9z2xVQp9LrnWNqbk0iIsaVJc4JWZSFRN3lsr/ZKZZDK8I+71oeQF2HfJUYL4JJ4VBI9yJGXRizcG55XYIKkEVe5pKBCn4y58R+sId/o5AfEhgf3tq/0ysqBJAJWRuAdS1tcTARqZDMsrZ6xA0FTg9++pw1XizXRuus/itQynSXg22EigwPO115rlxOXeRd+bCs/Id97ukCM7S7W9ndwcLW+lWdO4KeWcu24ZmPHB/P03rynZubUTxqQkz6MdU5/58gX5zz9yUC63DKoiYmXSWESUu1ha4E9d7lGV5v994YIEJi3TrsPuBotZPWD/9mabPLK3TE5c7JkzGKOGoCZ0DUyoMjU6HpZDO4rl/37z+tx4Bzqu3n2sWq61j6ofB59QbnamtMbHMnA3Td4Qr8fzYrrk76VF2TJwI6gbESWkYDCiZQcUpKHAtOR4MzVYcGB0Ws+BEhtKCqMyIF2ezHTZWpUntaVeiYbv/AODc+wenpIvv3JjrtssEazlv77arKTuH168qjO9FiLQOiJZ7lY5uL0kPmzUUsTSnWkaKTA5FVHFjmGwWytzZfG9t0Uyrb9ZxAeytxAoPBPTYbnYPDTH9XgPIVpjUyFpPz8uvSNTsq+hUHKzM1SxMvdqyUuMb13o0etpIbgGIP9c16VxhXE9gPe7KC9LhxmnQnmxV3I8jHS5r4dmsEFgPD8GK0Lf6LScurKY+NhgiChzmzwJPhFAmvHVVksNKivI1lKYBuwlfAYTUpjtydBNNjMjTc7dGNCZXK+f61bVwWq5dmh56bvvdEpDdb6SGpczOXeHjFB6opxFOU2DEQuzZXtNvs4Nw3fDHjAyMa3EDJXGBsoNr0mpik2YO5dLzUOWf8LB8aXr1HkIjA1KgMV+q1ML5QblkLRnpt4TcEh5h840iA+ACGjooU6jd+mgVUgiY0FsMnfHcIgS1GTExwZmdBKy1fydRsK1V7bX5Km3CnIHMl1OOX25V+et4Xtq6hrTGWnX20eltTegpO8r370pb13uk+iCDZV/kubNWulokRT+DUobFrEcUwUM4gjZZW16Bid0zc7fGJDe4Sn5zukO6WAwqrF3zAPXJYQ0GfGxQZOAGu7XCfGxN6ZD24v1RiIZUFT3bmEO3n0/NIMNAkN+DJYFxuYLlCWW+Oxkk2PjIsjQNjxztwkpoisDMLOrqcMqoSSCz+TAVEjNynR98YEOkTq8s1RK8rM17JA/fBAe21WmxKazb0LvDpOBw6S0xDFDeBhUyq7ZMzQpnf2T2ub+zJEqJSZ0HTHGIREtXQHtdOL12FRQS4bHQ9LWG1DFis4vhqtS3iIHiLvp8amI7N9WpD/POXs9LlWNRsenZXdDkfow7CGt9jnzMyQ95+W6lXA19wRkeHx+2eJ2MToZ1cGxSwHVDJ8Vys4TBytVgYGAcjwNlXnqiaIU2dQxquQRctfea40GWbipouhdbhleZDplgGp9pV8CE/NLXTZQxHgN1oqwR7w+JPl2DYzPS75GQSQROzMDb1i/DJnunnlAfWyPj3lZCpTD+P1cT3A70+Th3aVyfG+5esBoKuD38rEDFXJkR7G41qmh22BtwJS9DJaFml6XyNSxQbkLJYMPJe7cISCoDLa/gxZ3yBEb2kLwNVuFIAgwP9ctX3+jde7nAYoAnVwff/9umZhmArs7+fHGFRxSYMcmwvLt0x26UeN/wJcD4YG4HN9XrqRD52olAHLG8WK6ZnOGGEDobBLXPh1R5YcP4uFAUMYnI/p6dIzxGLxPR3eWSt/QpP77+L4KnQ6PgpHIBPjs3laD6TpH3rrQrV9jfe52M1xK9QGQsIYqvypQrLFdFgSoa5jXMZ9DTiApzEBLBdaKOWmM9oDw2MBf1Vjpl57BKRm9Mj3vPWe1OefdWwrUl2Qd96wSpcRjsaFjQbKsjCber4LdZXGKa8CarMRXEYuv8XoDfq8Sv1uN+tww8DuT7PPDwOB2YciPwbLAbMqGvhzYCFER9tTnyfBYrnYQcZtOCjJGYu7e8bYkA5ssd/94htgcKXklEh8bGJ5RIZRkOZPf+fHRCLnhMWebBuaNpoDUUJJC0WGq+buOVGtQYSJQrCBumIAZ70D5ZuGeDHFgXTBwD45Oqz+B/GmUJh4/MDw1R5aCwbCaviF0kELOky4viB6GbIiPvekTB3A3gEAmG52RCAzfRBIwiy0Z2RgJhOTkpV5V2VDLEtcv2fvGZjQwGhRvac48Twm+w/pyn/hzMqRnYFLGg2HJcKYraYRwokbY6dsYnMcmkqte5C/ZniwI9lQ4Klkr7Aba6NAU8hWsBWoZ3rL1CC6pWJzw3N2tgYHBLZiyl8GyYC7Vni2FOnphKRRxh1aQJWkxhxTlZmoL846aPKkqztZW8KlgWPZssUpDCz+Y6R5CXcKQ3D04lZT42KD8lJfjWTLfA7KGx8aRMM4BLw6bvrU/x9Rzw2a9MOmYYaowqAs3hnTjxewbnF7sqYBATQWj2u1VV+bTLjPKXO09gTniA5o6xnRd8CtRWqKsRxs4/75402r9B3UQpBWQzKXgz87QlOylUOzPkuGxoIyNz+8Es8HxYOqGzLpdS5MxSoeQQOaoLXw7IEX4mTp6AqqclRdk6/n1DExIS9eYqmcQRUgmZDBZqB3kCvJst81zbOvIurLqSBOHXjfLoTA3a54yZ2Cw2WHIj8GKUJibqeWbpS6kp4/USIHX8uGwQUE2aIXGRwIwvhble6SuYv6HNd6YwGRI1RWnCwXIahlPhbaeMQ00ZGNMBTZZNlxHnAhZSlG6khn8ONwtY8rFgF1eyHwul/4hiHB3fYESLAgACgVjLlKpH+T9EGRIl9XQWFBCSUgbxl061fZtLdJOM8p3/B9VyQbE8l2Hq+cFC94JZmfI7ylZUkEi48id6VrSJMu68X260lI+DzPK4v4u/FrJOol8ngypKvXJ2ERIVRsM5jbJ4Ws7awuspG+nQ1WrhdhRky/jU6H5qpwx/cyBNS+JJ6QvpQ6RL2UsMgYGt2DKXpsIKA6UGaKzhNdZYw5Wmp+SFhN59kiNKjivn++eV1Zh83rmSLUc2lookcjs3GuRrWPl/ORoKepy65D09o/L+47X6XOofyPXI9kep+bnbKv2S22ZT260j8ioz61lEciEfYR8dmfEu60GR6f0NRkdQYZQptPK+QlFIlJd4lOz7ch4UMpoQR8OWhtm3B+NSRnTL51NKDq0zF5pHdENHNPy6+e7xJeVKY/sLbcGtEZn5ND2ErnUMqRqkQ08RLvqC2RHbZ44YlaHGSSO8h4vx2aO0uTNtozRH3pqq/iyXfLmhfndWLT5P3+8XrZX50kk/nVHWpqMozbFGInhVBIJmbRhJUlbQ0P1WJzWUFnWuzg3Uz789DZ58USblq3m3kOHaNAh+Tm9QxNKxngPUKNscMxMsd9S6Re3K00qS6zhr4lKFs9D2CGbLu8JBIgE6+T8MCZ76vP1ekARS1R3aJnf31isRBavUW5Oppqb9Xwy0rWESD4Sg15tMCCW0L7NkPuzUmQ4rXDPM9f7tTU88X3gmt7TUChF+v6YNTMwWFchh6Ojo/LHf/zH8vLLL8vExIQ0NjbKL/7iL8rhw4f1+x//+MfljTfemPczR48elc997nN39HobLeSQjZIsEILn2IBIS8ZjUVKQrZ4MuqZWGoCW7krXchLqxWQoIvk5bvWuFPgyJRqe0U1ueCKsmxmkhNRjTLyYgWl7x0DMjonhlXIHycwEEzJhndIQ7eEvnmrXJGhKX3T+oALF4mSDdnL+z53ss0drtTsKFYUNkteGPPHcmU6HvHSqXTcCPD7k6fB8KDS0umOcDkVmlbjtrs+XWXHo+w5ZoJxWV5YrNzuHpW/I2kzw60C6MExDcijTUNLRuVy1ebp+4yGrTf5m15j+Oy09TQpz3bqBY37mZ7ZU+ZXM0DLO+0BJhw3dTlTmALuHJuXMtX71NuFR5bUhZYQfEp/DWvSPTsvNrlEtXfFvSkgQFohUWjzoMBiJysDYtHaaQYxIbiadeToclW+f6tALA/IE+WFMAMTH7yUKIF1fhEBEOm3O3xzUTit8N5BPzjkjHaJlEdK924qkvsy35DUE2ZwMRVVp432A8Bb63OpPIplpKjSrA3FbegJ6rKwtvioStG1AwhgY6yWhegPibj8nWP3xYET9V5QHKUny+8RQYUMW18Zn8WaAc52EHK4L8vOJT3xCBgYG5Dd/8zeloKBASc2XvvQl+ed//mepr6+X48ePy8///M/LM888M/czLpdL/H7/Hb3eRiM/wciMvHmxVwIL0n7nppDvLJVSf6o79+Qg4A4iwVrZ3ReQhs5BNu4+7fapLvfp6ARKSPbmRZYMZGhwZEp21OXrxo56w7FhBGa4Z2amS1uoCcfDU5PYH85kdwgVqbUYjBmdAYnKzsrQ3JjRQFBmorN6TrQAQzqsY9P/xp/m1ok+ur9CinPdujkQG5Se7lTCwZiNNy70LgpZg8Awc4zNBTWEtlvuqhn5gUnYKtc5dCOnPZ+NnbIbQ1aZCA+B2Fadp3fjHMfkdESzSijn8OfM9QF58cT8DiwbTLJ//uFaaWofUZKVDCg7e7cUzKtnc/2BuWvP4ZA3L/Zo0CPgfXQ4rMckqkuP7GNtMoW3F0IH4eXBGLhZL0qI22rypbYkZ8WJ1FZmU9zEuuBnIK/T0Rm5eHNYR3LYGzaPJwdp39ZC9TRt1I38Xn1O2DO9NPBzYy7Vuv0s3gxwrhPys+Zvodra2uT111+XL3zhC3Lo0CH92q//+q/Lq6++Kl/96lflox/9qAwNDcm+ffukqGixmXbTw+GQc02DSYkPYDM+c7VPniTv5TY6aKLRxd4WZkCdpYNIja6Z0jcUnCM+gDt+Ag7xfuChOXGpV545WiP9Q1Nznhrmgx3dXSbF+QwKpYw1O+ejoRRCecenoYBuORFvD6eUwugLj8faGHmmc9f75eCOUqujCOUobnJOBP4evEH2ZhqN8scq77B/MGn9zQl+/tYvcGLZCy8Ld9aQS9aQ12FzH5sMy0hCXg8kCPP0tiq/9A5OKOG52jYq3QPj+r7w6viQSoty5shaMrR0j8nVthFpiadNJwMT7ylB1ZR4E85r/gcQpJGkbY6L8pvVAT2bZG0yrPZiEWms8ms+Emne4xMhVX/wTGVlWN1eK8VSGzLHm5GWJgdRuar86rlicVC18Gzht9+oxOdewqyRgcEGMDzn5eXJZz7zGdmzZ8/c1+zE30AgINeuXbPKFHV1D/Q41yrwjSwVEQ8gF6gAdzMFGlNlZ//EXEsyJS7KMolA+SHUzzb6akBbT2BewjK42jqkwYQkEGdnOiU322WNN8hM1/LY0Z1lOi9rqY94vE39w5NattH2+fipca1Quqmt8KuSArlKdt5a6vJm6MytwtxbP4+/pbosRw7uKNENmrIcJl5UKwCJSyQ+Nmhx53XxF5H3829vtejjWAOeG0WJ483xZujoCZ6b9UoEXWcnLvXojLCl0Nw9pr6uVODcGNj68N5yNaBzzKwX89o4RrrF6NRLNBar0sP3qvKkvixH1bLMdEqFq7DRxmKS43ZKdVG2VBd7JTfLGqJqVAwDA4N7hTWv/Ph8PnniiSfmfe0b3/iGKkL/5b/8F7l+/brk5OTIb//2b6tClJWVJc8995z83M/9nGRkJE8AXgnsUsG9gC3DrVSOu1fQgYfDESUJyxGbvuGgKhN3etfITw2M3iJQkCG6hRLb0emcQvWwOnastegfDeroicTjowyGHPHQrhIZD0atf8fVEW+WUyaCUVUFEn/G/nvi1yB0TGh/fH+FBKYi6jeajs7K9DTek0n59ql2fZ9LC7N1Mn1uFkrH/PMv9rsl/0CFdmzpzKnJiCow3QMDulZ0cQWCESUbqCEoKfxZ2IbPs/L6+H1IRMZfQ4UpDxXL75Gm9lE5fa1PJiYjqrCgbKHOYACGVNpdWhduDmrpL3OJbi6OFYIEgUgFDg/fDQQzN9utoZG8P15PhkYW8B4tvGTs6xc/UYrJIquEzdGm9KA+JzYTzBqvPtLXyRqvefKzEGfOnJFf/dVflWeffVaefPJJJUChUEj27t2rxucrV67I7//+70t3d7f+/07ABkrN8l7D50s+p2Y10TNqlYOWg3ZR+ZbOzlkK5Lzg1fF44qF1znRtLU8EvwysLYZW+3v4dTIIP1xwjBmZLsnzZ0teEttWZGYy5TlxDHN/dzGpHOPvrA7lTHOmycDAuIyMWxPV3fHnGBwLyfi1AXl4d5kqS8ng93m026upc1R/1n4dDODTY0Gdr4ShGC8U55ZMpcjNceucM77POnizXVKUny2vnevWLrFwmPlWDi0LskaQLDxJlKUwsWJSx5vDzy71nkJaPG6X5OVlpXwMr3Hqau9cfg5kTOedjYelo39CGir9sn9rkV4Xa+E63kww67v6MGu8+ljra7yuyM9LL70kn/rUp+TgwYPyh3/4h/o1FJ9f/uVfltzcXP33tm3b1Oz8C7/wC/JLv/RLUlhYeNuvwx19ILB0qeh2wKbPhRDAjJskyG014XY6ZHra2uyXQm65T4/vTpUfDSp0O6Wn32pLjkat7Ba7HATCEYe4XemqgtD9BfBzTNFBFbw1PoPSUmx2Vg1zyRBj/ITE5jZuACGAkIRCET0HlJiwyynnm/qlq39Cyzp9w5NSU5orVaU50tVH2/Wtcw0GRU5d6pFH95YnzUNBOXrnSu9iI3J8gOmVUFS6+yekojjbGq+xwBPF1zwZ6dI3RGlwRktadMq9fbVPiQ9gEjq+ocm4CsPf3zzfLU8cqtS0bDrNSvOzlKgkrtdCoBDNzsykXD8O5szVfhlcwtR/salfPT8FCaGLD/I63gww67v6MGu8sdfY5/NsHMOzjc9//vPyu7/7u1rS+u///b/PlbScTucc8bGxdetW/X9vb+8dkR+wGi51nfZ9n93veGbyczxakkoFOr7YVMNLpCqvBLS8k9EDQQiMh7TtnInoNmgRZwwE7cs65NNhpRrTBZVIusqLcnSoYaq1IteEEQm0wy+EEp+ZmHQOTMhDu635WmB0Iqwt3RebB2UoMC17GwqkrfuWGRvgjaKc5lsQNMgvE5PMbT9TIiBgRXkebdnm7zwGszedaolgQCvHhorDudMCj+rF8dlnTlmP7Jt5pbJQVMbGw9r63d0/rj6dLjqhlvDa1Jb6dCZSqvWbiswoUVuO6GI+z2ssWvS4B3EdbyaY9V19mDVefaz1NV7bRbk46PT6nd/5HfnIRz6ieT+JXp4f+7Ef0zJYIi5cuKDqT21trWx2oGLs3VqobcnJgIpA2B0k6W6Bx2R3Q6GSGsy89RW5Gjho+3Dw1zDnidRgHrN/W7GEwtF56cmEHhJ2mLjh0orNHxuYbMmVwW+T+BhgdVuFlFTRQm53amm+UIL5eGgspAnFieAwLJ/S/PPi+BhuulQJ6cjOElW6eD2I5JaKXM0TsoPmaNMm0ZgAwbKCbB0eCtFKpBXMvSLoj59LDEEcHJvS58B4jUm7ujgn5bEwoZ55Y0sRGwzuyYjcQjCqAxP0/Qbrb0KcDQwMVhNrXvlpaWmRT3/60/Lud79bfuZnfkYGBwfnvud2u+U973mPfh/Pz6OPPqrEB6/PT/7kT4rXm9y/sZnAho6SgXfkRueYqgdsfqgZhXke2VaVJwW+lYccLv1iInWlPlU5RsZDMhQIyrE9ZbJ1LE/LNrOzszrxHXNxeXGVGnPPXh9QpYggQCacN5RbqoUizSFD49ZYBM4DtaQgN1NwoTjFIcd2l0hzz7hcaR2W3uGgpKWFtEX70I4SCYej0tlnGYXBws20uWtUW6o5hhVtxkt8H0O2My1NfuCZbZq6PDI2Lb7piOzcUqhdaihrLZ2j6hsiKRoDMx1sKMK0798aiRHT6eWYnZlGr6SRLqtMlxzeUSI1pT7xpDtkb0Oh5Od6dDo9I0No7mc2Wn15ripiy4xgWzGxsDN57hcIQpwKzcjoBCMwYkoCWQ/SsU37toGBwaYiP3R2RSIRefHFF/VPIj74wQ/K7/3e7+mHNMGHkCCyfj72sY/JT//0Tz+wY15roMzCFOz9DQWa14IfBkMtHhQyX1BI7hXCMzE5daVPzjcNaJmJvZN26h21+ToDi5A6NjkSjBmuyWbNHk8GUGtXQEtGlQVuGR6Pynfe6ZSmjpE56RSCQQjik4eqpMTvkfbBCbnUPKzeGDrGAJsk3VQECZLijBKjBDArY55HiPRgTNmJoAxFds0if1SMUpxXSVgqVJbmSFPHaDyccUqvSZ27VJAlH3xiixQXZGswIUnTmJeHA0F5dF+lvqbLk64Jy4DXR9GCDDKGAjy8p0waynPUEA0QuWpLvDqTzFa2IAgrJQkMYF04siIZmLlGoOP9IB6EW1+5OSQdfYF5uUp4wnbVF0ppvvueXqcGBgabG+si4fl+Y6MlPN8voF9882S7nGsaSPp9WsE/8vwOeeNct1xtG076GAZh/ujzO+TLr9yQ3hSBf5SV3v/YFvnsVy7oqA2g09vT0jQcsb13XEdcPHOkUnOEAISvNWG2FMfyxMFb3wd0ax1pLE46A4nxIN8505F0cGlDtV/aeifkxZNtSioTJ9JXl1CG8kkgGJaKgqy5XJzJ6ahu7IzT4O8Q0SyPSwebJootlLueOFChM9XuFVCULrYOy/W25CnRAFIGyfQmTAJfreuYZzrbNKjjPFKVZo/tLlPCu5E/rjbL58SDhFnj1YdznSQ8rwvPj8H6QN9IUBWfVCA7BqWGUMBUKC3KVlWImVqpQMmHwaioKAsBOSENuLVnTBUYOp8AM8Hww9AuDphrht/o1nO6Zc+WgpSbqycjTUtWCyfJ8y+PO0O+83bHXM5PIrZW58vJK32a4zMVV26A1+Pk1kOO7CzV0liB36M5Q4nEh5IYr0mH3L0ESs62Sr+UFSYvC5PRtL+xaMmcoHsJErFTER9AWfRyy5DOaDMwMDDYFGUvg/XD9s/dGFgydZmZXG9f7ZWCJfIfCPh76WSbRJi1lSKYke6qr77aLHk+tw5yTATlrOI8j45uuNg8pAGH6ouJ4SFJ1w40DNHMFRsZDercLYzZmJDxI6UCnKg0zy1PHKxSBYkxFWzKNeU+6YgPVaWslsidKOFBsOxy28RUWDy5jNOwnm8mGlMP1sHGYlWtKAPyeFQXhp3i8SE+YDXKTqzt4e3F0jfCRPVRPUbOgZIb88Hysl33pdwF0WII7nLg/STwkmRqAwMDg7uFIT8G9wQYVJkwvhQYPAoRocvKSjhevLniW6GzKid7/siLRCBr0q5e6M9KWrIkW4jk4onJ8DzDLoSDNvmnDlYqsZidmVXStlJfC6SFMtDe+nxprParSdzny5TP/9u1uRTqRDCyItFQjcfG4YD43VIw6LpiHhdpzk8crJBIeEY9Ucwws1rjV4+AYIymFFeW79EcJB2z4Upf9ddNBC9DrtFKoHPVDPkxMDC4BzDkx+CeIC3dIS7X0peTdns501XZSGxvTwSEyJM53/eyEKg4lISsEaaLQQs5pSTmY9FWPzkZnitt1ZXlaqeV/mi8hHW7Gz2PV5WItOp4eGEy4C9KTLnmvFOV1fg6j3Tc4THdKTRviRLbfX5dG5r2nb6yst7CkqOBgYHBncJ8mhjcG8yK7N5SsORDhgMh2VWfr+WVVL5VggZp5aYckgpMQj+4rXjehPVkPhI8Lbtq8uSJA5Xy+IEKObi1SIdkLlmbu01MTUVk79aipKnQeJvI5oH0ZGZYnWTJyAUEgLLbZmzn5pwpdS4Hj9spXqP6GBgY3CMY8mNwT4CqwwRuOrFSYXBkSvZtK7YFl6QgtfmhPWWamJwK7b0T8viBKk2MTgWUnwONRRIKzWh5h+yg1SIXJflWfs9C8Hqd/eOyvTZPy2x4jpKBwap0eW1GoDwV5brF501d5gT4sjz32PhtYGCweWHIj8E9Q3ZGmnzvEw3aVbUQZPQ8dqBS6kt98q6jNVqCWghtPz9ULVXF2fI9j22RnCTDO7PdTnnsQIVsrcqR739mm/4br0osTsDI12Eq+Uef3ynFvls/j7dHnTZpDv37vUSGwyEffnqrvP/ROlWtdtblq5EakFOE6vTI3oqkIykgPgwQXa0swXSXdd6zDstztRaBD+vozhJVxpKpYpQvt5TnbkplzMDAYHVgcn6SwOT83DnoJKelu3toSq60DGkAIfO86K4q8GYoS8GwHAhGpHNgUq61DavPp7wwWxOe6TJit8YGMjIZ1c4qpptzlVIeYWwEc65mo7OSliHSPxLW9nkeQ+lpV32BqgQoUKFgRDf+/rFpOd80qPPNKEERgMjUcl7rXrwfcBoSra93jcngSFA9RxVF2RpUSIcbydR2Jxrnw6gNfE10nnEuq3IHkiYyGAjLxZuD0jMwqf+uK/NJY22+Ditl/dbSdQyBJSCT0mibzlGbkVyvW3OSiC5wbIJPqc30OfGgYNZ49eFcJzk/hvwkgSE/94YEYYDm8uIKiyzIv7Eek6aTzK3HxCSSkOybuHZWNI9Vtrq1fg557VKPfPHbTXJ0Z6lUFGYxH0Gutg5LS8+Y/Ph7d8rO6nx5+WyXnLzUrV1FiSBg8Hse3yK1xd67ek9oyT9zbUDnhdnIwIwdswIKDzUWi8/DOljfS/zFXLWJx2kOefvagHzndMeibBzKic8dr5PtlcxPm11z1zEkiDWy12szTd7ejJ8T9xtmjVcfznVCfky3l8GqgH01tMz4BDbfUGjpX45kvzz8cl1oHZG/f/Gavs5r57q1bGSPlGDf/MabrdptdepS7yLiY6swX/nuTfno8zvEd4dDXWlJv3RzaB7xAeF4wvNoZEZOXe6Vx/ZViCtu4F7tzRwz+Y2egHzrVFvS82ZK/AuvNUve8zulKGdxWfFBA9JjNiUDA4PVhvH8GKw7TEdn5dV3upT4pAKdXm+c75HCvMXeokQCxDyuO/UAMZaiq398ycfwGsPjofs2IBQl6tTlvqTExwYp1Odu9N9z75OBgYHBeoH59DNYdwhMReRi8+CSj/FmZ8j1jhFxLpMhc711RAP+bheQGXw+hBQuh7a+wIql2LvFRDC65KgIG6Qqk5hsYGBgsBlhyI/BugMGaRKlU0G7v2IxHSKaKgjRBp6YOxsZRUL1yn4wysjy+wTCI5MlZy8EozVSBU0aGBgYbHQY8mOw7sAIDOZ3pQJ7uiM+W2u5ahPzwTJct/9rALnyJmnFT/oaORn3bRo5Kci5S4wGsZGbk6kp2QYGBgabEYb8GKw7kONDh9dSYNjokZ0l6rlZCvu3FemMrzsBHWP8WQrMMKsq8akKdT/A6I4d9fnLPo7zzrxPpTgDAwODtQbz6Wew7hCejsrxveWak5MKkJKH95QvaTQmlblsiUTq5ZCR7pDdWwo1OygVtlbniTdFsvNqYCYyK4caS3Q6eyo0VOVJQ0XupmojNzAwMEiEaXU3WHOgXTsyE5NgeEYiM9a08UxnuoYYMkSUvJ/CHKd88nt3yzvX+mUiGNEkYB44MzMjBbkeOdhYLLkep/zAu7bJ6+e65UbX6FwLdV5OpuzfViyHthfrMNE7BcdR4vfoOI4rLcMyHAjO5dN4PS4lGTWl3ns6S2wlyPWky/c/tVVeO9+tIZJ0dwESs3dtKZRju0skI9kwMgMDA4NNAkN+DNYUYg6Rtv4J7dRq6R6XsYlpJTbVpT5prMnT6eMkPTtmHJKdmS4leVkSmByVkcmQkqN8n1vTot3ONCU7JbmZ8n2P18vIRFhJkjPdIb6sDB1wei/yZHQ2lc8t+XvLtPUdooESxNgNjvVBjGTAh02w4vsfqZVH9pbLeDCsa0hScl52hsnRMTAw2PQw5MdgTRGfq+2jcqV1WLoHJmUieMuvw4ys3qFJ3czfvton+7YWy8lLvTI6Pq2m5nxvhng8GRIMhuVC04CMjAXlQGOxjspAeslj40+YCn4vCQAEiMJXjtupf2w86FlUjLBA/eKPDUN8DAwMDIznx2CN5fc0tY/I+CQqzWKj8vhUWK62DUuW2yXnbgzK2EQo5XN19k9I/0hQU58NDAwMDAwSYciPwZpAWrpDh5OSUUN44FKkJicrQy7eHFg2z+Zm56jJsjEwMDAwWARDfgzWBGgFHxsPKaFhoncqMK8LE/TYRHhZ8jMZjNxRerOBgYGBwcaGIT8GawKUp26VqJYuVWln1woUHX06U/UyMDAwMFgAQ34M1gTo1Cor8mqnlCfBNLwQ2W6XPra8OGduUnoqFPizxO0yKcYGBgYGBvNhyI/BmgCdURWF2ZLpSpP8HHdKwWZLRa4MjQbl8PbiJc3MZAXVV/gk9oA7rgwMDAwM1h4M+dlkgBQwYTx9GdXkQYAkZFKXc70uKcrLWkSA6spypbwoW3K8mdJQmStbKnNTnuPerUWS711+xpWBwcp+X8xHpYHBRoLJ+dkkcKQ5ZGI6Kj2Dk9oynuFKl4oir4b9rRUaRDhfaZ5HnjhQJe19AWntCWjnF6UwiE6eN1PyctwWqYnFZFdtvpQWZEtz55gG+XncLin2u6W21Cf+7Ayj+hjcMVAVp8Iz0j8ypdcgM9oIz8z1ZgpzcE0ToYHB+oYhP5sAfE5fbRuRGx2j2i1l40bHiJTkZ2kY4FoZckn5y5uZLrtr82VbpV+DDx1Kz2LiSk+LExpr5+GrhTmZUrSzRKJMWc/OlGg4KpHIzH2bom6wAeFwSFvfuFxsHpJwfDSIHZ2Q53PrWBTCLM0lZmCwfrE2djyDVZXtb3YH5Grr8DziA/jw7h2akrev9Mt9Gjp+WyTImeYQl8MhToeI0+FIqeRAdBgl4c3KMKTH4K5/X3pHpuSd6/3ziI+NkcC0nLjUK6Gouc4MDNYzDPnZ4GA4KHesSwFpf3QydbCggcFmQXQ2JtfaRpZUdUgg7x2eVKJkYGCwPmHIzwbH2GRYgqHoso9r7Q6I02kuB4PNDYbTjgamV/T7MmNURgODdQuz221g0AnOlPGVYDocNR4Gg00PSsMr+TUgZXy5hHEDA4O1C0N+NjAgM56MlXnasz23Jp4bGGxW0Fm4klm4ma50caaZj08Dg/UK89u7weHLdi1LbPisrynzycwCQ7SBwWZDttspBT7Pso+rK89dMxERBgYGtw9DfjY4GO+wrTpvyQ/q8mLyfjLu41EZGKxNpDscsr02f8kQUNrdi/M8prPQwGAdw5CfDQ5axqtLvLKvsVjcGfPnXPEBj+JzYGuRuRAMDOKxCUX+TDmys3SRYko5rLQgS47tKhWX6fQyMFjX2BAhh7Ozs/Lnf/7n8o//+I8yPj4uR44ckd/4jd+QqqqqB31oawKOmEhdaY6U5mfJcGBaxqcikuFKk6I8jxXWZqpdBgZz4PehPD9L8g9UyMh4WMYmrYTnIr9HcjxrJxHdwMDgzrEhbvj/4i/+Qr7whS/I7/zO78jf//3fKxn65Cc/KeFw+EEf2poBAYFuZ5pUFGTJjmq/bCnziTfDEB8Dg1SKaUZ6mpTmuWV7lV+2VuSKzxAfA4MNg3VPfiA4f/3Xfy3/8T/+R3nyySdl+/bt8id/8ifS29sr3/zmNx/04a05YFPgg50/BgYGS8P8vhgYbEyse/Jz9epVmZyclIcffnjuaz6fT3bu3CmnTp16oMdmYGBgYGBgsPaw7j0/KDygrKxs3teLi4vnvncnuJdpx+nxoaH2/w3uPcwarz7MGq8uzPquPswarz7S18kar3vyEwwG9f8ZGfNbtTMzM2VsbOyOnpOZPXl52XKv4VtBfojB3cGs8erDrPHqwqzv6sOs8epjra/xuic/brd7zvtj/x2EQiHxeO5s8anvBwJT9+wYYcBcCIFA0AQJrhLMGq8+zBqvLsz6rj7MGm/sNfb5PCtWnNY9+bHLXf39/VJdXT33df7d2Nh4x88bjd77N40LYTWe1+AWzBqvPswary7M+q4+zBqvPtb6Gq/totwKQHeX1+uVEydOzH0tEAjI5cuXNe/HwMDAwMDAwGBDKT94fT760Y/KH/7hH0p+fr5UVFTIH/zBH0hpaak8++yzD/rwDAwMDAwMDNYY1j35AWT8RKNR+bVf+zWZnp5Wxeezn/2suFxmUrmBgYGBgYHBfDhiZjrfIrAk9zrUDBOWMditLswarz7MGq8uzPquPswarz4e1BrTqe1gCN8KYMiPgYGBgYGBwabCujc8GxgYGBgYGBjcDgz5MTAwMDAwMNhUMOTHwMDAwMDAYFPBkB8DAwMDAwODTQVDfgwMDAwMDAw2FQz5MTAwMDAwMNhUMOTHwMDAwMDAYFPBkB8DAwMDAwODTQVDfgwMDAwMDAw2FQz5MTAwMDAwMNhUMOTHwMDAwMDAYFPBkB8DAwMDAwODTQVDfgwMDAwMDAw2FQz5WWXMzs7K//gf/0Mee+wx2b9/v/zUT/2UdHR0POjDWrfo6+uTxsbGRX/+6Z/+Sb9/5coV+ehHP6pr/fTTT8vf/u3fPuhDXlf4X//rf8mP/diPzfvacmtqrvG7W99f+7VfW3Q9s842zPouj9HRUfmN3/gNefzxx+XgwYPyIz/yI3L69Om577/55pvyoQ99SPbt2yfPPfecvPDCC/N+PhQKyW/91m/Jww8/LAcOHJBf/MVflOHh4QdwJut3jT/+8Y8vuo4Tr/U1t8Yxg1XFn/3Zn8WOHTsW+853vhO7cuVK7BOf+ETs2WefjYVCoQd9aOsSL7/8cmzPnj2xvr6+WH9//9yfYDAYGx4e1rX+1V/91diNGzdiX/ziF/Wx/N9geXz+85+Pbd++PfbRj3507msrWVNzjd/5+oLv//7vj/3xH//xvOt5aGho7vtmfZfHxz/+8dj73//+2KlTp2LNzc2x3/qt34rt3bs3dvPmTb1uuWZZY/7+V3/1V7GdO3fG3njjjbmf/5Vf+ZXYM888oz9/7ty52Pd93/fFPvKRjzzQc1pPawwefvjh2Be+8IV51/HIyEhsra6xIT+rCD6cDhw4EPu7v/u7ua+NjY3pBfPVr371gR7besVnPvOZ2Ac+8IGk3/vLv/zL2KOPPhqLRCJzX/ujP/oj3SgMUqO3tzf2Mz/zM7H9+/fHnnvuuXmb83Jraq7xu1vf2dlZ/fo3v/nNpD9r1nd5tLa2xrZt2xY7ffr0vHVlo/3TP/3T2K//+q8rwUzEf/7P/1lJpP3+QEq5sbLB5s5znjlz5j6eyfpd48HBQf3+pUuXkv78WlxjU/ZaRVy9elUmJydV5rPh8/lk586dcurUqQd6bOsV165dky1btiT9HhLs0aNHxel0zn3toYcektbWVhkcHLyPR7m+cOnSJXG5XPKVr3xFywK3s6bmGr+79W1vb5epqSmpr69P+rNmfZdHXl6efOYzn5E9e/bMfc3hcOifQCCg13Di+tnX8Ntvv83Nv/7f/pqNuro6KSkpMWu8wjXmc5m/s27JsBbX2JCfVURvb6/+v6ysbN7Xi4uL575ncHu4fv261ok/8pGPyPHjx7Xu/N3vfle/x5qWlpYuWmvQ09PzQI53PQB/yZ/92Z9JVVXVou8tt6bmGr+79eV6Bp/73Of0cc8884z89m//toyPj+vXzfouD8jgE088IRkZGXNf+8Y3viFtbW3qk0p1DQeDQRkZGVEfIZt7ZmbmoseYNV7ZGnMd5+Tk6LWLJwhf1Z/+6Z9KOBzWx67FNTbkZxXBLxdIvGAAFwDmL4PbQzQalebmZhkbG5Of//mf1zsRDKA//dM/rYbG6enppGsNzHrfGZZbU3ON3x3YNNLS0nQT+Mu//Ev5lV/5FXnttdfk537u59TobNb39nHmzBn51V/9VXn22WflySefTHoN2/9mc2aNF34fmDVe+RpzHbNWe/fulb/6q7+Sn/3Zn5V//Md/VDM/WItrfEvLNrjncLvdc79g9t8Bb7bH43mAR7Y+QenlxIkTkp6ePreeu3fvlqamJvnsZz+rX7PvNGzYv1hZWVkP5JjXO5ZbU3ON3x3YJH70R39U74rBtm3bpKioSH7wB39QLly4YNb3NvHSSy/Jpz71Ke1G+sM//MO5DXbhNWz/mzVMdo0Ds8YrX2MUn1/+5V+W3NzcueuYUu8v/MIvyC/90i+tyTU2ys8qwpaq+/v7532df1PrNLh9ZGdnz9sEwNatW1VWRdpOttbArPedYbk1Ndf43QHVxyY+idczoBxg1nfl+PznP6+K8FNPPaUqmq1QsobJ1g/yTqmGa5w27oWbs1njla8xN6Y28Ul2Ha/FNTbkZxWxfft28Xq9qlbYwBx2+fJlOXLkyAM9tvUIFB7uNhLXE1y8eFEaGhp0TTHWzczMzH3vrbfeUmNdQUHBAzji9Y/l1tRc43cH7oo/9rGPzfsaig/gmjbruzJ84QtfkN/5nd9RL+Af//EfzyuxHD58WE6ePDnv8VzDfJZAPg8dOqQlRtuUC1paWvSGyqzxytaYPB/KYAuvY9Sf2tratbnGD6THbBOBbImjR4/GXnrppXkZHeFw+EEf2rrDzMxM7MMf/nDsve99r2ZFkNnx6U9/OrZ79+7YtWvXtN3yyJEjsV/+5V+ONTU1xb70pS9pvsc//dM/PehDXzdg7RJbsVeypuYav/P1Zc1o9yXLp62tTVuBn376aW3FtmHWd2nQMr1r167Yv//3/35exgx/AoFA7Pr16/r9P/iDP9DPjM9+9rOLcn5Yb9b9rbfemsugWZjHtJnRvMwaf+5zn4vt2LFDc37a29tjL7zwgmZTce2u1TV28J8HQ7s2B7hjhiWTQIzxDpZLSmZlZeWDPrR1Cdqr/+iP/kheffVVvQOm5Zf6M3d34Pz58/K7v/u7emeMd+ITn/iEphMbrAwYbru6urT7yMZya2qu8btb369//etq3sfMTxnmAx/4gPyn//Sf5koKZn2XBuWXP/mTP0n6vQ9+8IPye7/3e9oR+gd/8Aca0cC6Ubp573vfO/c44gY+/elPawcToGMJs+7CkuRmxV+uYI3/7u/+Tv+QPm771mhGQV1bi2tsyI+BgYGBgYHBpoLx/BgYGBgYGBhsKhjyY2BgYGBgYLCpYMiPgYGBgYGBwaaCIT8GBgYGBgYGmwqG/BgYGBgYGBhsKhjyY2BgYGBgYLCpYMiPgYGBgYGBwaaCIT8GBgYbCk8//bSGCRoYGBikgiE/BgYGBgYGBpsKhvwYGBgYGBgYbCoY8mNgYLDhEIlE5Pd///flkUcekf379+s8sra2Nv0eJTGmUH/xi1+Up556Sg4cOCA/8RM/IVevXn3Qh21gYHCfYMiPgYHBhsPXvvY1aWpq0oGLv/mbvykXL16UX/iFX5j7/pUrV3RQ43/4D/9BB16OjIzosNb+/v4HetwGBgb3B8779DoGBgYG9w0lJSXyF3/xF+JyufTfqD7/83/+T5mYmNB/j4+P66Tqw4cP67/37t0rzzzzjPzt3/6tfOpTn3qgx25gYLD6MMqPgYHBhgNkxiY+oLKyUv8fCATm/m0TH1BcXKzlr1OnTj2AozUwMLjfMOTHwMBgwyErK2vev9PSrI+62dnZOWVoIQoKCmR0dPQ+HaGBgcGDhCE/BgYGmw54fBZicHBQCZCBgcHGhyE/BgYGmw6tra1y8+bNuX/39fXJO++8Iw8//PADPS4DA4P7A2N4NjAw2HSIxWLy7/7dv9MOsPT0dPnzP/9zyc3N1RZ4AwODjQ9DfgwMDDYdysvLNfvn05/+tASDQTl+/Lh2g/n9/gd9aAYGBvcBjhi3QAYGBgabBIQcnjx5Ur797W8/6EMxMDB4QDCeHwMDAwMDA4NNBUN+DAwMDAwMDDYVTNnLwMDAwMDAYFPBKD8GBgYGBgYGmwqG/BgYGBgYGBhsKhjyY2BgYGBgYLCpYMiPgYGBgYGBwaaCIT8GBgYGBgYGmwqG/BgYGBgYGBhsKhjyY2BgYGBgYLCpYMiPgYGBgYGBwaaCIT8GBgYGBgYGspnw/wNefxMuaHSBUAAAAABJRU5ErkJggg==",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.scatterplot(data=pokemon, x=\"hp\", y=\"speed\", hue=\"legendary\", alpha=0.5, s=60)"
]
},
{
"cell_type": "markdown",
"id": "f3741251-2a2b-437e-b68f-084fb4399e9f",
"metadata": {},
"source": [
"Finally, if you want scatter plots across multiple categories, a [relplot](https://seaborn.pydata.org/generated/seaborn.relplot.html) lets you distribute categories across rows and colums in a grid. "
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "7385237c-6a5c-4041-af46-559d6d84d1fa",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x131a01e80>"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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siSsZxheP19hkObcV4dgSE8eWuJJ5fBxbw7jGUt1jxkUd/SPXaDTqz2TDsSWuZB4fx5aYODaqjmQ+t8k8tmQfH8eWmDi2xJXs46tPyXxuObbExLElrmQeH8dGVDsYuCAiIiIiIiIiIiIiorjBwAUREREREREREREREcUNBi6IiIiIiIiIiIiIiChuMHBBRERERERERERERERxg4ELIiIiIiIiIiIiIiKKGwxcEBERERERERERERFR3GDggoiIiIiIiIiIiIiI4gYDF0REREREREREREREFDcYuCCKExpNyQcRERERERERERFRQ6av7wMgasj0ei0MRj3MZgP0upI4otcXgNfrh9fjQyAQqu9DJCIiIiIiIiIiIqpTDFwQ1ROL1QijUY8/Fu/Aj7M2Y+c+OzQaDdq2SMP44e0wuGdzuFxeuF2++j5UIiIiIiIiIiIiojrDwAVRPbDaTNiT78KDb89Bgd1T5rVVmw+qj+aNbHjs2qGwWo1wOb31dqxEREREREREREREdYk9LojqmJSFKnL6cM/rM48KWpS2+4ADd746AyFoVGYGERERERERERERUUPAwAVRHdMbdPjg+5VwuP1Vbru/wI3Pf1sLnUFXJ8dGREREREREREREVN8YuCCqQ0ajDj5/EPNW5kW8z28LtsNk1EN3qHk3ERERERERERERUTLjTChRHdLrdVi0di8CwVDE+zhcPmzcUQCDgf9ciYiIiIiIiIiIKPlxJpSoDmk0GhWIiJbLI2WlNLVyTERERERERERERETxhIELojoUCoWQmWqOer80m1HtS0RERERERERERJTsGLggqkNerx8DumbDbIy82XaTTAtyW6TB5wvU6rERERERERERERERxQMGLojqkN8fhD8QwOj+rSPe55QhuXC5fAhG0ReDiIiIiIiIiIiIKFExcEFUxwK+AC47tRuaN7JVuW2nnEycMbI9fF5mWxAREREREREREVHDwMAFUR3zePwIBgJ47sYR6NY2q8LtBnVvhieuHQqX2wu/n4ELIiIiIiIiIiIiahj09X0ARA2R2+WD2WzAY9cMxc69dkyauRk799mh0QBtW6TjtBHtkJVmhtvlVYEOIiIiIiIiIiIiooaCgQuieuJ2++Dx+NAo1YTLx3WDTquBdLEIBoLqo7DAWd+HSERERERERERERFTnGLggqkehUEkAg4iIiIiIiIiIiIjisMfFW2+9hYsvvrjC1++77z6MGTOmzOeCwSBeeeUVjBgxAn369MFVV12F7du318HREhERERERERERERFR0gYuJkyYgJdeeqnC13/77Td8+eWXR33+9ddfxyeffIJHH30Un332mQpkXHnllfB6vbV8xERERERERERERERElHSBiz179uCaa67Bc889h9zc3HK32bt3L+6//34MGjSozOclOPH+++/jhhtuwOjRo9GlSxe8+OKLyMvLw+TJk+toBERERERERERERERElDSBi5UrV8JgMOC7775D7969j3o9FArhrrvuwumnn35U4GLNmjVwOBwYMmTI4c+lpaWhW7duWLBgQZ0cPxERERERERERERERJVFzbulZcWTfitI++OAD7Nu3D2+++abqgVGaZFaI5s2bl/l806ZND79WXXp97GI6Op22zJ/JhGNLXMk8Po4tMXFsDUusrrPJfG6TeWzJPj6OLTFxbIkr2ccXLT7LRoZjS0wcW+JK5vFxbERJGriojGRUvPrqq6r/hdFoPOp1l8ul/jzyNZPJhMLCwmq/r1arQWamDbGWlmZBsuLYElcyj49jS0wcW/KrjetsMp/bZB5bso+PY0tMHFviSvbxRYLPstHj2BITx5a4knl8HBtRAwlceDwe3Hbbbbj22mtV74rymM3mw70uwn8P72uxVP8fVDAYQlGRE7EiUUn5B15U5EIgEEQy4dgSVzKPj2NLTBxb/IvVREgsr7PJcm4b2tiSfXwcW2Li2BJXMowvHq+xyXJuK8KxJSaOLXEl8/g4tvhWGwF9auCBi2XLlmH9+vUq4+K1115Tn/P5fPD7/ejbty/eeeedwyWipHl3Tk7O4X3lvzt37lyj9/f7Y/+PUf6B18bXjQccW+JK5vFxbImJY2sYYn0ekvncJvPYkn18HFti4tgSV7KPL1J8lo0Ox5aYOLbElczj49iIGkjgolevXpg8eXKZz3388cfqc/JndnY2tFotUlJSMG/evMOBi6KiIqxatQoXXXRRPR05ERERERERERERERElXeBCSj+1adOmzOfS09Oh1+vLfF4CFM899xyysrLQsmVLPPvss2jWrBlOPPHEejhqIiIiIiIiIiIiIiJKysBFpG644QZVPuq+++6D2+3GwIED8d5778FgMNT3oRERERERERERERERUSIHLp566qlKX//Xv/6lPkrT6XS4/fbb1QcRERERERERERERESU2bX0fABERERERERERERERURgDF0REREREREREREREFDcYuCAiIiIiIiIiIiIiorjBwAUREREREREREREREcUNBi6IiIiIiIiIiIiIiChuMHBBRERERERERERERERxg4ELIiIiIiIiIiIiIiKKGwxcEBERERERERERERFR3GDggoiIiIiIiIiIiIiI4gYDF0REREREREREREREFDcYuCAiIiIiIiIiIiIiorjBwAUREREREREREREREcUNBi6IiIiIiIiIiIiIiChuMHBBRERERERERERERERxg4ELIiIiIiIiIiIiIiKKGwxcEBERERERERERERFR3GDggoiIiIiIiIiIiIiI4gYDF0REREREREREREREFDcYuCAiIiIiIiIiIiIiorjBwAURJR2NRlPfh0BERERERERERETVpK/vAyAiigWjUQezATBaLIcDF2k2PVzeEDweP4LBUH0fIhEREREREREREUWAgQsiSmharUYFKDQBL4oW/Ig9f/4Bv/0gNDoDzG26IX3QacjK6YZih1cFMIiIiIiIiIiIiCi+MXBBRAlLMivSU/RwrZ+PfZNeA4J/BSZCwQBcGxarD3Prbsg+7x5oNHq43QxeEBFRzen1Wuj1OkiSn2T1+XwBZvcRERERERHFCHtcEFHCSrFo4dnyJ/Z9+0qZoMWR3NtXIe+zR2GzGqDTsf8FERFVn8mkh9Vmgi3FjO37HFi7vRD7ijzIyLTCYjWqgAYRERERERHVDDMuiChhS0SZLCZsn/y+5FdUub1nx1o41s6DuU0/OJzMuiAiouhJYMIfDGHCT6vx+6IdcJUqQZidZcUpQ3Jx2sh28Hp89XqcREREREREiY5LwogoIZlNejg3L4e/aF/E+xTN/0HtR0REFC2zxYhCpw//ev4P/Dh7S5mghdhz0IkPfliF+96cDYPRUG/HSURERERElAwYuCCihKTXBFRvi2h4dq4FggHodPzVR0REkZPyT2azHve9OQsFxZ5Kt121+SBe+mwJvL5AnR0fERERERFRsuHsHRElJOlUEfRWPnlUnqDfpxqpEhERRcpg0KvSUPsL3BFtP2vZTthdPhgMulo/NiIiIiIiomTEwAURJaQgAJ01NbqdNFpojWaEqm6JQUREdJjZYsAPszZHvH0wBEyasUkaMtXqcRERERERESUrPk0RUULyBXVI6TUmqn2snQYiGAggEJCwBxERUdW0Wg30Oi227C6Kar/NuwqZ4UdERERERFRNDFwQUULyeHwwZLWAqXn7iPdJP+Y0uH21elhERJSsqpWux8gFERERERFRdTBwQUQJO3/kcvvQ5LQboTFZq9w+te8JKsjhdvvr5PiIiCg5BIMhBIIhtGiSEtV+LZukIMTahERERERERNXCwAURJSyny4+QNQstLn0Shqzm5W+k0yN9yJlodOKVKLL7OIlERERRc7m8GDu0bVT7nDayPTS85hAREREREVWLvnq7ERHFhyKHHzZLFlr982W4d6xF8ZJf4S86AI3eAEtuT6T2PREhjRaFxR74/extQURE0fN5AzhhUA4+nbwGxc6qaw7269wUWWkm2IvddXJ8RERE8UKv18Jg0CNUqlpiKBCEx8PMdyIiig4DF0SU8ByuAJxuF8xZ7ZB5wpXQ6LTQajTwBUIodofg87GxBRERVZ/fH1AfD181BPe+ORuuSiZfcpql4s5LBqiG3kRERA0pYGE0G9T1b8qC7VizNR/BYBDZWTacMjQXqekWeN0+BjCIiChiDFwQUVKQElAulw8uddMMZGba4Mx3MMuCiIhiwuX0okVjG168eRQ+/GEV5q3MU/0vwmxmPcYMzMElY7si4AtAo2FjbiIiahgMBh1sKWZ8NnkNvpuxCW5voMzrX05dhwFds3Hr3/vDrNHA7ebCMiIiqhoDF0REREREEXA6PEi3GHDzBf3g9QWwZO1elX2RlWZGvy5N4fUG4HH51ApTm81U34dLRERU67RajbrmvfrlUkxduL3cbaTl04JVe3Dry9Pxwk0jYQqFmHlBRERVYuCCiIiIiChCkt0Hlw9Gow4DuzSFJFYEg1D9LMJZflIug4iIqCEwmQxYuGZPhUGL0nbus+Otb5bjn2f0ZOCCiIiqxKcqojhgNOphsRhgNhvURAgRERHFN8mucDq9cDi8cLm8LE1IREQNktGkx8RpGyPefsbSnYCmpLwUERFRZRi4IKrHlFqLxYj0DCvc/iDW7SjEhl1FCECjGpfJayyPTURERERERPFIgg8Olw+rNh+MeB+fP4jpS3YycEFERFViqSiieqDTaWFLMWHZ+v346vf1ZW70JFjRt1NTnH9CJ+Q2T1P1tEs3/yQiIiIiIiKKh8V4B+2eqPfbX+ACH3GJiKgqDFwQ1UfzshQT/jd1Az77dW25jcsWr92Lpev24rpz+mBE7xZw2N3q80RERERERETxIBQKwVCNvk5Ggw5aVhcgIqJEKhX11ltv4eKLLy7zualTp+Lss89G3759MWbMGDz99NNwu92HX/d4PHj44YcxZMgQtc2tt96KgwcjT1Mkqo/mZfNW5pUbtChNVqC89uVSbNldrHpfEBEREREREcUL6e/UrJENGSmmqPYb0LUpqwoQEVHiBC4mTJiAl156qcznFi5ciOuvvx4nnHACvvnmGzz44IP48ccfVaAi7KGHHsLMmTPx73//Gx9++CE2bdqEG264oR5GQFQ1KQNlthjw5ZT1EW0v93JfTFkHvYHJUURERERERBQ/JPjgcvtw4jE5Ee/TvmU6crLT4PH4avXYiIgo8dV74GLPnj245ppr8NxzzyE3N7fMa5999hmOOeYY9bq8NmrUKNx8882YNGkSvF6v2nfixIm47777MGDAAPTq1QsvvPACFixYgCVLltTbmIgqy7bYursIW3YXRbzP4jV74Pb6YTSyeRkRERERERHFj4A/gDNHd0BWmrnKbaU81GXjusHt8bEUMhERVanel3GvXLkSBoMB3333HV577TXs3Lnz8GtXXHEFtNqysRX5b5/PB7vdjkWLFqnPDR48+PDrbdu2RXZ2tgpeSOmo6tJXo05jZY2YS/+ZTDi26H+u1m8viGofybrYvseOds1TY5pOy+9dYuLYElMyj62+r7PJfG6TeWzJPj6OLTFxbIkr2ccXLT7LRoZjiw15RpWJpaeuG4Z73piF/QV/lfYuTa/T4OYL+qFzTiY8bm+1f075fUtcyTw+jo0oSQMX0rdCPsrTrVu3Mv8tAYsPPvgAPXr0QFZWlsq4yMzMhMlUtp5i06ZNkZeXV6PmyZmZNsRaWpoFyYpji1x1V5bYbCb1EWv83iUmji0xJfPY6vs6m8znNpnHluzj49gSE8eWuJJ9fJHgs2z0OLbYMJn0ePOu4/HbvK34ftZm7NhrV59PsRhw3MAcnDGqPVJtRpgMOlhi0MOR37fElczj49iIkixwESm/34877rgD69evV/0whMvlgtFoPGpbCWRI0+6arBgoKnIiViQqKf/Ai4pcCASCSCYcW/Q3c7ktUqPer3ljG+x2N3y+AGKF37vExLElpmQZW6wmQmJ5nU2Wc9vQxpbs4+PYEhPHlriSYXzxeI1NlnNbEY6tdt53dL9WOHloLvz+EIKhEExGneqDEQoE4bS7UdOfTn7fElcyj49ji2+1EdCnupEQgQspC3XTTTdh/vz5ePXVV1UvC2E2m1WviyNJ0MJiqVkk0O+P/T9G+QdeG183HnBskX4tHzq1zlSBiN37HRHt06tDY6RajSgqjN0DSNlj4vcuEXFsiSmZxxatWJ+HZD63yTy2ZB8fx5aYOLbElezjixSfZaPDscWOei+PHy6nR5X51mgApz0U05LHYfy+Ja5kHh/HRhRbcV+gbO/evbjwwguxdOlSvPfee6pBd1izZs1QUFBwVPBC9pE+F0TVodNpYLEYoTfq4fL4YTDqYTYb1E1XTYVCIbXa5KzRHSLe529jOsLn9dX8zYmIiIiIiIhqmZRHDk9y1kbQgoiIGoa4zrgoLCzEpZdeqjIupDxU586dy7zev39/BINB1aR7yJAh6nObN29WvS8GDhxYT0dNiVwP1mQxwGIyYO6KPCxYvQcerx8ZqSacMCgHOdlpcLm9cLtqFkTwevw4bkBrbNxRgJ/nbq1020vGdkXXtlmwF5Xf4IyIiIiIiIiIiIgo2cR14OLJJ5/E9u3b8e6776pm3Pv27Tv8mvy3ZFWceuqpuO+++/DEE0+o8lAPPvggBg0ahD59+tTrsVPiBS1SUs2YtWwX/vP9KhTYy/ZI+X7mZrRvmY7bL+qPdJsRLufRJcoiJStPHA4Prj6jJzq0zsA3f2zEzn0ljcvC2rdKx3nHd0Lfzk3htHtUpgYRERERERFRVTSxKBeQhM/8ghkgRESJI24DF4FAAD/++CN8Pp/KujjSlClT0KpVKzz66KMqaHH99derz48cOVIFMoiiYbWZMHneNrw9cXmF22zcWYhbXp6O528ciXSroUaZF9Jku7jYjWE9m+P4gTnqa2/dXQSNVoOOrTLQskkK3G4fHMVu3lgRERERERFRpfR67eEyx3pdSVVwaagrpYp9Xn+DrE1f3jmRhYQN+ZwQESWSuApcPPXUU4f/rtPp8Oeff1a5j9VqxWOPPaY+iKrDZNKj2OnDO99WHLQIc7r9eOrDBXjpltHwuH2qdmd1qRsmZ0npqeaZFrRsZFWfl0BFQYGjRl+biIiIiIiIGgaL1aiea39ftAM/ztqMrXlF6nmyVdMUjB3WFscNyIHP569R5YBEPCdGox5/LN6BH2ZtxrZS5+TUYW0xpgGeEyKiRBNXgQui+qDV6zBx6tqIAwVb84qxcUchWjaywFXDfhdCykBJdgURERERERFRtBP0BQ4v7n3uDxw8ojeiPLu+8dWf+OSXNXjk6qHIzrTA6ShbFrkhnpPXv/oTExrYOSEiSkQluXJEDZSU/kyxGvHHou1R7Td53haEWDeUiIiIiIiI6onZrIc3EMJdr808aoK+tEK7F/e8PhPFLh8sFgOSmZSF8vojPyd2d/KfEyKiRMXABaGhNy2Tkk1SKioaBwrd0DJwQURERERERPVYPUCyKWQSvioOtx8f/bgaOr0OyX5OJkR5TmQfIiKKPwxcUIOn02mh1UYXhDAZdAjWcxMKWUlithpLPixGWCxGNRYiIiIiIiJK/sbT0nBaejhEas7yXQgEQzAYdEl7TnQ6DaYtifyczP5zt+ozmaznhIgokbHHBTVocoPi8QbQs31jLFu/L+L9+nRuAk2o/gIWJrMBew868fPcLSr7w6DXoXfHxhjZtxW8Xj88bi8CAXb3JiIiIiIiSkZ6vQ5rtuSr59lI+QMh/LlhP3q1awSfL/L9EuucHIzynAST+pwQESUyBi6owfN5fTh9ZLuIAxcWkx7HDciBw15xvczabDLm9gXx6JuzsXrLwTKv/b5oO975dgXOP6Ezxg7Nhb3YrcpgERERERERUfKVPXZ5/VHv53T7Va/HpD0nnmqcE0/ynhMiokTGujLU4Hk8fvTr3BRdcjMj2v78EzqplRh+f90GBSTLwuMP4uYXpx0VtAhzuHx477sV+OK3dbClmHjzRURERERElIRCoRAyUkxR75eVZlL7JiMZV2aqOer9slKT95wQESUyBi6owZNyUU6nB49cPbTK4MU5Yzpi3PB28Lija+YdqxJRz09YjAK7p8ptP/9tHbbvtat9iIiIiIiIKLlIieCOORlolB75RH2q1YBeHZrAG0UppUQ8J1lpPCdERMmAgQsiAG63H36vD0/+33DcfelAdGubdfg1o16LMQNa45VbR+O8EzqpElF1XYLJZNLjYKEbyzfuj3ifiX9sgE7PBmNERERERETJuADP5fLhlCG5Ee9z3MAcuL3+pC0pXJ1zcvyg5D4nRESJjD0uiEoFL6QElDTlGtA1G1qNBr5AECaDDm6PHwF/AMVFLtRHBqlGp8Uv8zZHtc+sP3fjpvP7QafT8iaMiIiIiIgoyfh9AZw5ugMWrNqDtdvyK902t3kaLjq5C9wuL5L9nJx1bAcsWL0H6yI4JxeelPznhIgoUTHjgqiUQEBWaHhRWOCEw+FWjbiLi10qy8Lt9tVL0ELI++YXR9cM3B8IsskYERERERFRkpKFd263F49fOxSDezSv8Nmvf5emePr64fB6/ElfEil8Tp7gOSEiSnjMuCCqJM209J/1zViNsk8GvRb+qltiEBERERERUQLyuP1ACLjtwn4ocngxaeYmbN1djBBCaNU0FaeNaKd6PkhWgcfjR0PAc0JElBwYuCBKAFqE0K9LU/w0Z0vE+7RtkaYCF44gy0QRERERERElK5l8lw/pjXjumI7QaLXQaTUqCz/oD6iKAg35nJwzpiO0Wkm90CAUDCIYCDbIc0JElGgYuCBKAHLDNbBrtloVcrAospJRsorE7aq/8lZERERERERUd8LZA3q9FpmZNuTnO+D3N+yFbMyoICJKXOxxQZQApFyVxxvApWO7RrR9m2apGNWvNXw+3qQRERERERERERFRYmHggihByKqZfl2yccX47pU23M5tnoaHrx6CQrsbBkP0fTGIiIiIiIiIiIiI6hNLRRElAKnLebDQjQfemYOHrhyMvp2b4sdZm/HH4h1wHUp97dg6A6cOa4vhfVrii9/WYc8BB/7vb70B+BAPJNhiNOoP1RYFAoEgvN5AfR8WERFRpXj9IiIiathkEaHFYlT3BFKK2est6Z9BRES1i4ELogSg0Wnxy7zN2L3fgRue/wMj+rbEqUPb4p9n9YLL7VOZFYFACL8v2o5bXpyGbXuKoddpcdP5/eDWadUkS32RiR6LWQezyQB/4V74Du4GNFrYsnORkm6F2xtSY2AvDiIiiic6nQZGkwFmswG79tmRd9AJvVaD9q0ykJJmhN/nV72kiIiIKDlZLAZo9TqYDDqs3ZaPIrsXFrMeXXOzYDDqEQqG4HB46vswiYiSFgMXRAlAJvXzi0uacnt8Afw2f5v6aJRuRqrVCJ8/iP0FLvVamD8QhNPjr7SsVF2sTElPMcKxfj52z/0Wnt0bS72qgaV9H2SMOBfpjXJQ5PCrXh5ERET1TRYE2FJMmL5kJyZO24gtu4vKBOQHds3GBSd1RvMsG5wOD0KMvhMRESWVlBSTClr877d1+HneVhQU/xWgsJj0OHZAa/z9xM5ISTXDfuhZnYiIYouBC6IEYdQf3a/iQKFbfVTEoNfC76m/larpqUYcnPoxihb8UM4WIbg2LoFr0zI0Gf8vpHUchEI7My+IiKh+6XRaFbR4/as/1SKBI0mQfd7KPCxaswd3XjwQvTo0gsPO1ZZERETJwmYzqioBd/x7BjbtLDzqdSnXLKWb5y7fjWf+NQLpqWYUM3hBRBRzbM5NlAC0CKF/l6ZR7dOuZboKXASD9VMmymrSwv7nHxUELUoJBbFv0r8RKNilynEQERHVJ6NJj0kzNpUbtCjNHwjh6Y8XosDu5fWLiIgoiRiMBjz54fxygxalHSxy4743Z6lMTYOB02tERLHG36xECUAafw3omo2sNHPE+4wf3lbV3q6PDAYpo2GymFAw55vIdggFUTjra3Deh4iI6lNJXyYDvplWurRhxaQs4/+mrodWH9tbao1Go46lPss9EhERNUSpqWbkHXBgybp9EW2fd8CJOSt2w2w21vqxERE1NAxcECUAKUshDawvPbVrRNvnNk/DqH6t4PX6UR9MJj1c29fAX7An4n0c6+ZDE/Sr1SpERET1QTInFq7eU6aOdVWkD4Zep1V9nWpCghTSBFRqZTdunIKsLBsaN06FNcXEjA4iIqI6EggB383YFNU+38/cDF05pZ2JiKhm2OOCKEF43D4M69UCdqcP7363osJMCglaPH7tULjdPgQC9VMmSlaJendviG6nYAC+/D3QprSorcMiIiKqlFxaN+woiGofjy+A/QUupJjktjpYo2bgm3cV4dvpGzF/ZR7c3gBsZj2G9W6JM0a1R9NMK5wON/z++rm2ExERNQTSq3Hr7qKo9tmyu0iVadZqZdFhrR0aEVGDw8AFUQJlXdiL3TjhmBwM7JaNidM24vdFO1RjMNGxdQZOH9kew3q3gMvlVWWi6lW1SlSxMzcREVXcNFsm+KWMUigUgs8XiHmAXhYFVKfEYk2uXiVBCzNe+myxyt4ozeH2Y/K8repDgheXjO2K4iJ3vS1MICIiOnLBmtGoP3xt9vsDSRFgD0V7Za+P+sxERA0AAxdEiRa8KHLDZtKryYtrzuqlVnpKiQq5UfS4/SgqdNX7hIasMjFmt41uJ40W+oxsuL286SMior/IhIjOoIPJqMfarQdR7PQizWpE5zZZcHv9CPj88HoDMXkvraYkczEassKycboFLmfk5aVKs9pM+PcXS44KWhxJFiyYDDqcfWwHtZCBiIiovkjQXW/Qqb5Q67cXoMDugcWoR5fcTNX/KegPwO2un7LFNRUIhNC6aSrWbMmPeJ9W2akl4078mA0RUVxh4IIoQZt1w+OH2+lVq1tkTYjcYMULj8eHrNzu0KU1RqBof0T7WDv0g0ZvgM9Rz5kiREQUN6Tng0anw6eT12LKgm2wl8omTLMZcfzAHJx3QidoddqYZBrK9XVwj+bqaxc5vBHtM7x3CwTVKtPoZyukd8Weg06VQRmJr35frzIvZMJIMk6IiIjqmsmsV42ov/59A36aswUHi/4KppuNOtVr8e8ndYHFaoTLGdm1NJ7oNMD4Ee3w6/xtEe8zdmhb+HldJiKKOQYuiBI8AyMeyyvJcXncHqQfMx4Hf/1PBHtokD70bLgS776WiIhqiUzq+0LA7S/8oSb3jySBha//2IB5K/PwzL+Gw2zW13h1p2Qsuj1+XDG+u6pxnZ1lU02z84s8mLZ4B+au2I2Auvb+VSLj7GM7IlDNyQqtXouJ0yLvCeUPhPDj7M0YOySXgQsiIqpzJpMeJpMBd78+C+u2HZ2RIP2Zfpm7VV0vn7puODIkeJFgD3kOhxuts1PRrW0WVm0+WOX2WWlmjOzbEg47syGJiGJNG/OvSEQEwOkOIa3fSUjpdWwVW2rQ6KR/wNAkRzUUJyIikoCA1WrEA2/NKTdoUdrOfXY89M5cWKymQ1mI1SeZDBKwGNKzOQ4UujFpxiZM/GMj1m/Px2XjuuG9+07EcQNblxyjBrjxvD5ommmp9vXLZjFiydp9Ue2zaM1e1e+DiIiorpnMRjw3YXG5QYvSCu1e3PfmbJWdodcn1jVLyj35vAHcd8UxaNkkpdJtJUPzsWuGqsUEsSpbSUREf2HGBRHVClm1WmT3ofEp/4SpZScUzfsOvoO7y2xjatUZmcPPhbFVVxTafexpRkREh1d0rth0AFt2F0W0vdTX3rC9AK0aW+GqZsko6aVhtRnx7ncrMXnuVlWrurT/TV2PY7o3xw3n9UHnnEzkNEtFuxbpcDqq19siTPp0RLd9gIELIiKql2tzod2DeSvLPtNVRBYATFu8E4O7ZcPvT6ysC7vdjZRUM168eRQ+/nE1pi7cBkeprE7pbzWsVwtcemo32Mx69p4iIqolDFwQUa2RlScFRSFYO49Aq97HwZO3Cd4DO6HR6mBq3h769CaqJEdBsQQtGLUgIqISOr1OZTtE49sZG/Gvv/WRq0/076fTqqDFkx8uwIJVe8rdRi5TUvoi74ADz94wAqFASJWFqMnlS0orpqeYUOyM/JjTU4xHBVWIiIhqm/STmvTH+qiue9/P2oTR/VslXLkoIcEIyf686JQuuHx8N5UhKU3IJVDRt3NTleWpCYVQzKAFEVGtYeCCiGo986LYGYTdFYAprTV0GTnq8+5AEJ583uQREdHRTEZ9xNkWYdt2F8No0MFRzWyLqQu3Vxi0KE2O68MfVuGik7rUOFPQ6fJidL9W+O/PayLeZ0z/1ggycEFERHVMo9Via5TX5q27i6HXadUkfyIuVHMeai4u2Sa9OzQ6NA5ZoOevdoYnERFFjnnmRFQn5EZVaoDLzZ98eDw1a6BKRERUmpoOqUaLC2mLYbYY8F0UGR4S5JB+GDWt2+33BTB2WFvodZEdeKrVgOG9W8LLaygREdWDUDX3qGELqnonz65FRW4UFrpQVORi0IKIqI4wcEFEREREccXjC6BV08obYh5Jtq9OY0yDQa/KP23LK454H6fbjwWr8lSmRk1LKuo0Glx7du+IGpbfdtEAuD0+lc1IRERUl4LBIFo3TY1qn1ZNU9U1S0ojEhERRYuBCyIiIiKKKwGfH+OHt4tqn9NGtEMwEH3gQgICBcXRN9jem++KyQpSl9ODkX1a4pa/91MZFeXJSjPjkasGo0ubTLgTsE44ERElvlAgiPEjors2jx2WC5eb2QlERFQ97HFBlIBkosRkMgBamTGRj5D6v9/nh9/PVZhERJT4JRn6dG6isih27LVXuX2bZqnompuF/HxntUoZSm+MaJlrmG0RJqtQpcn3wK7ZGNG7JWYu24nZy3fD5fEjxWrAsf1ao3+Xpmrix1nDZuBEREQ1uTY3yrCiX+emWLx2b5Xbp6cYMaZ/DpwO91ELBuRZVi5nf/W+CMHj9idkHwwiIqo9DFwQJRiz2aBqce/e78DPc7biQKFL1dnu1aExju3fSpXJ8LhZRoKIiBKXTOZLP6RHrh6C216ZgYNFZSc9SmuSaVHbSaPr6kx4SMA/t3karGa9KgEVKQkmxGqxgIzX5fDA6/ZhQJemGNA1u2QyR0prhIIoKHCyzAYREdU7yfq785IBuOPfM7C1khKLNosBj1w9VDWxDl8r5bomz7EWswELV+85HKRPtRoxZkArdGmTpa7lbvaPICKiQxi4IEogFqsRLm8AD782C2u35Zd5bdriHXjvuxU47/hOGDe8nVq92RCzLyQbRVbxEBFRYpOJC7nuvXLraHz042pMW7IDnlI9LCwmPUb1a4VLTukKTSgEVzVLKEmgX3pNHNu/NX6YtTmifXp1bIz0FJNaRWoy6REIyMTMX69X9zokx+JyshRUTcnkmNwPSByLq3eJiGKbdSG/YJ+7cSQ++WUNfpu/DcXOvwINep0GQ3u1wCVjuyLFbIDT4Tl8XbSlmFWmxlvfLD9qQcLkeVvRorENt17YHy2b2OC0eyr9HV9X5K3C71cXCwjCQ0v0ZuZERLHCwAVRAmVaSNDi5pemodBe/qSGrBT9z/erUOTw4YITO6G4yNVgSkpIg1SLIQSj1YpQqCRgk55Scs7c7gBXqhIRJSCZxJfAwBXju+Oq03tg2fp9aoIkzWZA745N4Q8EEPAF4JaJlGpeW7V6nVoZev4JnVWZpoqusWF6nRaXn9odWi2QmWlDMBSCVqOBx1tyDJIFGZ5vSEm1wOPxwevxMxOylskkj8pK1YegN1vUvYBGo4XP7YLbp1Hfh4ZyT0REVJskuz8UDOLc4zrhklO6YdmGfcgv8qjMRakCoNNqEPAHDgcthCxEmLNiN178dHGFv4t37Xfgrtdm4olrh6FlY1uZnk6qvJTZoJ75pLyjXHvlGmx3eNV7eQ9dg2PFaNTBbACMFosqYyXXk6DfB7fbD7c3gEAgdhcUlYli1kOn16lsFBlbRoYNDpcXQX8QbvYIIaIGjIELogQhN2pPvD2nygkV8dXv6zG8d3M0y7TAleSptnITm2bTQ+NzoXDO97Av/wMBRwGg1cOS0w1pg8Yhq30fdVMrN5pERJSAqzs9fuj1OnTPzTq8kl6yHaqbWajXa2G1mbE334mJ01ajR/vG6NAqAw9fPQQPvzMX+RU06zYZdbjjogGwWfTYc8CJG174A0a9FvdefgzaNE/D5Llb8PPcrerrykRE+5bpqpGp9K5wuVn+orZIsCgtxQDvvu04OO87ONbNR8jngcZohq3LEKQfMx7WzBYosvvg90ffwJ2IiMqS8sTwBlSJw86t0g/1qgD8Xj9cvsBRv6NlDdkrny+tMoDs8wfx5IcL8P59J8Dr8anFZxKUtlqNWLB6D76dvhGrNx9EIBhCVpoZxw9sra6zks3hcnpqvFhNxpFm00Eb8qNo4Y/IWzoFgeIDgEYLU8tOSB94KjI7D4LT5YPT5Y9JgMRmM2PDjgJMnLZRldDy+AIqCDSiT0ucOao9GmdYVBCoIVZTICJi4IIoAchqU+llsWLTgYj3+WbaRlz3t95y+4dkJTeW6akGOFfPwv4f3lB1wA8L+uHa8qf6MLXoiGZ/f0D9ymPwgogoMcmEcywmnSVokZJqVuWnZJIgxWLA1Wf2wu2vTMdpI9rj9TvGYMqC7fhpzhbs3FfSGDwz1YSTBrfBSYNzsWu/Hfe8Pguv33mcCnZccVp3OJw+/OOxyWoVZpiUKFq/vQAvfLIYn/6yFo9fOxQWi7HaJa2okqBFqlHdB8jihdJCXjfsf/6uPlL7nYRGJ16BwiJO/hARxYoqceiq/Heq3qDDj7M3wx9h5qGUkZIgRY/crJJyfzotbn15OjbuLDxquy+mrMfXf2zATef3w6Du2XAUu6udXScLI9JT9PBuW46937yAkL/U9ToUhGfHGuzdsQaGxq3R/KKHAYuxRsELCVpYbSY8N2ERZv2566hKCr/M3ao+zj62Iy48uTOKi9zM3iSiBkeLOPLWW2/h4osvLvO51atX46KLLkKfPn0wZswYfPTRR2VeDwaDeOWVVzBixAi1zVVXXYXt27fX8ZET1S6NVovJ87ZFtc/sP3fBqNdBp4urf+YxlWLVwr1hEfZ//1rZoMURPLvWI++Th2GzGpL6fBARUdXMFiM+/3WdClqI3h2bYMfeYmzeVYSXP1+CR96bh/RUI/5927H435On4vPHT8UHD5yEzm2y8PpXy3D/m7Oxv9CN+SvzcNm4bmqC5PEP5pcJWhxp94GS8hcanVZNVFDspNr0OPDzO0cFLY5UvPgX5E/9r8rSJCKiumO1GDF14Y6o9vl1/jZodVqVbSGLBY4MWpTmD4TwwieLsHLTAXWNry7JpvTv2Yg9/3umbNDiCL7927H74/thMWlV8Ly6QRIJWrzw6eKjghblVVP4auoGVW6LiKihiZsZvAkTJuCll14q87n8/HxcfvnlyMnJwVdffYXrrrsOzz33nPp72Ouvv45PPvkEjz76KD777DMVyLjyyivh9XI1GyWX/OKyDcyqIjdwTo8/aRt7ldQ5NeHAbx9EtL1n1wY4Vs+B2RQ3v/aIiKiOyQSDlJeQSYCwVKsBBUV/lYZaveUgnp+wGBc+8BNuenGaysS4+KGf8fC7c7Fg1R5V7iK80lNKQX30wypV2qIqe/Nd+OaPDaqGNcUuIzXoKEDx0t8i2r5wwQ8IeV2qRjoREdU+eRaV57Zon2Xzi9xqwdmUhduxZXdRldvLtfmdiStUj4jqNO+WXaQ084Ff3690QVyY78BOFC36RfXBqA6TyYAde+2YubTyoEXYF1PWqTFWN1BCRJSo6v2ufc+ePXjwwQcxb9485Obmlnntiy++gMFgwCOPPAK9Xo/27dtj69atePvtt3H22Wer4MT777+P2267DaNHj1b7vPjiiyr7YvLkyRg3blw9jYootmSORLInomXQa+Evv0x3wjOb9HBuWlZSczRCRQt+QPMug+FwslwUEVFD9Fe5ir/qSHh8QdXo80guj19NKlRE+l1IlkU0ZRx/mbcVF5zYWTU2rWkdbgLMhhAKp38X+Q6hoLoXsB1zJrjGiYgoNk2lQxrNoR4XIWhCIdUoO9y8Oly2Sa6zUv5INGtkxclDctE5JxNmox5Ojw/L1u3H5HlbUWAveXg1GXTq630/c1PExyPNvWXxQZvslKh7Sklmh3fvNnj3bIl4n6JFPyN90KlwuF1RX9NlEUM48zMSskDi5zlbcNIxOfAd0UOEiCiZ1XvgYuXKlSo48d133+G1117Dzp07D7+2cOFCDBo0SAUtwgYPHqxKSu3fvx+7du2Cw+HAkCFDDr+elpaGbt26YcGCBTUKXEj941gJl6ZJxhI1HFvdkB/HAV2zVb3tSMkqUAlcuDXl/zzH0/iqw6ANoHD9wqj2kZJRCAZhMukO30wnmkT/vlWGY2tYYnWdTeZzm8xjq6/xyUTBojV7y3xu865CdGydoRphhidVItGvc1PVwyIaBcUe1TcjK8WYsBMP8fRzaTCZ4Nq0LKp9nJuWImP4OdDrQ3E9tlhL5rE1hPFFi8+ykeHYqk8y1yRDYcP2AkxZsA0Fdi/MRh0GdW+GIT2bw+P1w+fxq+CD0+1TZRmXrtuLG87ti76dm2DeijxVClkWCaTZDBjeuyXOP7ETfl+0A29/sxx9OjVRwYCtecVRHde8lXnIbdYx6n8Dem0IzvXzo9rHX7AHfnsBjEZr1L2TrBYDlqwtez9SFbl/OWVobkz/fdc1/ptLTMk8Nop/9R64kL4V8lGevLw8dOrUqcznmjZtqv7cvXu3el00b978qG3Cr1WHpDJmZtoQa2lpFiQrjq329e/SFFlpZlWaIhLjR7RTf1b1sxwv44tW0OtCyBd9Okko4EVaWioSXaJ+3yLBsSW/2rjOJvO5Teax1fX4vP4APEf0opASFPIxZkBrfD9zc0Rfp1fHxkhPMWLGkoprbldEMjxSUsxIdPHycxn0RVd+RO4dNDodMjONcT+22pDMY2sI44sEn2Wjx7FFx+sLYNc+O555bRa27ykbWPhj8Q51ffzH+B4Y1rvF4YzGv43pgAtP6oJ12/Pxj8d+RX5x2ec4CWI0b2zDDef2wWPXDEWrpinwB6NvRC2ZkHq9Dik2U1T7BX0eOHzVSMXze5Ga1Sj6/Q4da3Tb+6HXaWGthX/fdY3/5hJTMo+N4le9By4q43a7YTSWfagwmUouQB6PBy6XS/29vG0KC6N/kAyTyH5RkROxIlFJ+QdeVORCIBD9xTeecWx1x2gy4LJTu6kGXlXJbZ6GkX1bwunwVHjs8Ta+aNlMGuhs6dHtpNVBYzCjsNCZsCU6Ev37VhmOLf7FaiIkltfZZDm3DW1s9TU+adqZnnL0ZMYPszbjkrFdMWPpThTaK5+4kEmDi07uqoIdqbboG2Wm2Yyw290JnXERLz+X6akmdS8QKD4Y8T46azqCfj+KHO64HlusJfPYkmV88XiNTZZzG83YdDqNqvggGQWysl09M2gAl8uHYCAQ9cr6aHosyHtqtFrVp0HeV4JQkq0gGeMejz8uvm8Gkx778t24/dUZRy0ECJPrqDyzSgkoWRTgcXnRvJENM5ftwsufLzlcPupIu/c78MDbc/DoP4eqa63Qakr6V0QqI8WIQCCA/PzoFrhZzLrony3l+2ZOQXGxK+qfi/QMKzJSTCrjJFKyvbyPwx5dwD6eNLTfJ8kiGcZWGwF9qhtxHbgwm81HNdmWgIWwWq3qdSHbhP8e3sZiqVkksDZuSOQfeG3d6NQ3jq32BYNeDO3VHHZXT7zz7fIKb/jatkjD49cMg9vti+gGN17GFy2P3oCU3sehcO63Ee9j6zRIPXB4o1zdEo8S9fsWCY6tYYj1eUjmc5vMY6vr8QX8QTWJsviI8gzTluzAgG7ZeOTqoaoJd0XZjdLX4s6LB6gJpk9/WYdbL+yHtycuj6g5t2jXMh2N0swoKHBUeB1PFPHwc+n1eJHSfSQO5kWWKSNSeo2G11f5scfD2GpLMo+tIYwvUnyWrd7YLBajKn80Y+kOTJqxGZt2Fqheg00zrThpcBuMHdoWRl0ILqcnpr/DpeGyLcWkAuLS90DKKHl8AVhMelV26cxR7dGiSQocdg/8/kC9fd8kkGIxGfDEh9MrDFqUJiWfBvdoDrNBr66Tr365rMrzJts98/FCvH/fCeq4+3XJxsLVeyI+xhMGtVHX+mjH7PFqkdJzNA5O/W9EzbmFOacbtAYT3I7oqwA4nV6M6tcSn/26LuJ9jhuYg2CS/DtsCL9PklEyj43iV1wXKGvWrBn27i37YBn+7+zs7MMlosrbRl4nSiay6sZe7MbxA1vj7buPx6nD2qqb2TBpbnb7Rf3xwk2j1KqcaBuSJRoJzBgymsLUsmw5ucqkDT4NsmiJiIgaJmkYKqUrJOuhNJlIeenTxdi0sxCv3TEGV57eAy2bpBx+PTPVpJpqv3nncSp48dA7c1XwQ1aVSl3uSI0f3k5dvxI9aBEv5Jqe2vcEaPSRZb5oTFak9BgBt5cP3URUlsVqhNMbwLVPT8GLny7Bhh0FaqW//L7ec9CJj35cjcsfnYwNOwthjbIMUdVBCzP+/cVS3PLSdExfslMFLYSsxp+6cDv+9fwfeO+7FUhJNddrfwOTSY8Vmw4g70BkGT1y/ibN2ASNTosfZ2+GP8KV2rJ4YMHqPao/xhmj2kd8fCVlHE1RZ6eE7w8kM9/asX/E+6QNGg9XNa8nAX8A44a3g05SSiLMthjcoxm8Xj7MElHDEteBi4EDB2LRokUq1S9s7ty5aNu2LRo1aoQuXbogJSUF8+bNO/x6UVERVq1apfYlStbghdWgxcUnd8EXT5yK/z05DhOfGY8nrxuGfh2boKjQpSZFGgKX24cmp90IrbnqtL+0gWNhbJrbYM4NERGVv1JMrgMS6D9yssAfCKkSFg+/O0cFNv5922h8/fQ4fPXUOHz44Ek4c3QHrN2aj/vfnA3HocUBX/2+HpeP74ZmjaxVvvfArtlqdaVMjlBsSLktmQdrPO46CUtUvrFGi6an3Qif18/VgkR0VPBAUunuem2mClJURAIJkpW3a78TFoshJu8tQZA3vlqmmlJX5sfZW/DxT6tgscYuaBI1rRa/ztsa1S5/LNoBs0mPqQsrH9+RJs/bikAI6JqbhRMH5VS5vVy3bzqvL7ye6j/rOT1BND7lGuhSs6rc1tZtOKzt+8Ltrt41XSoAGPVaXHNWryq31es0uOPiAerZNyAnhYioAYnrwMXZZ58Nu92Oe++9Fxs2bMDXX3+NDz74AP/85z8P97a46KKL8Nxzz2HKlClYs2YNbr75ZpWpceKJJ9b34RPVGllFIv0rDhywqxqXBQVOFOQ74XJ5E7bmYHU4XQEEzelocfnTMDQp/4ZWVmFmjDgPWWMuQZGdq1yJiBo6t8uLTq0z8cjVQ9A44+gm2Wu25OPdb1dg7vLdasGA0+FW19uAz4+B3bJx1Rk9YTOXZDxOWbBdTco8dd0I9GhffnNOCZCceEwb3H3ZQDgdDes6XReKHAFYOgxA07Nvq7A+uS4lE9nn3gNjmx4odiZ+uUgiii3pK/HV7xuwr6Ckh2ZVpYzen7RS9R+MRQbDgUIXfp2/LaLtv52+STVoll4Y9UFKRR3ZVLsqHp8fWo3sF11fhoJij5qwl2fea87uhbPHdFAT/eVp3zJdVR2wGHU1WqQmQQifxoSWlz8NU4uO5W+k0yNt4Kloctq/UOzw1ahvooxtdP9WuPn8vki1lv/z1CTDonp+yBjl/oWIqKGJ6x4XklXx7rvv4vHHH8eZZ56JJk2a4I477lB/D7vhhhvg9/tx3333qWbekmnx3nvvwWCIzQoIqn9SR9okN4ZaDTQajUoZ1YRklV18rZiTlTp6g07VQdVAg5D8LxB9I7VolNwoNeyZ+GKHHzZLBlr94zl48jaheMmv8BcfUAELS25PpPYeg0AwhIIiThYREVFJ2Q8JRkhPqHfvPQFL1u5VK12LnV5VgnFozxaqnJTb41dZjuFJCWnMKvcgUmNaap3LPlJ3e8m6vchINeGhq4Zgf4FLlcXIO+BQEzwdW2eq0o4GvVbVJo9lQ275+jLpFZK7Du1f90ceT80mUmJNjlHKhITvjUTAF4jZuZBxFxT7kZrTCzn/ehuOtfPhWDMHQY8TWlUaaiSs7fvB4/agsJgLGIio/N9Tv86PPJNg+cb9yC9yq2tGTZ71dHodJkbR40B+t0+auRlnjmwH1MMctry/UbJToiDXKCH7OaPITjAZdOoZTq4Vci0+97hO6uOXuVuxctMBFUBqnGHB2KG5aNMsTS3gczlrflLsTj8sZguaX/wYfAd3omjRz/AX7oNGq4OpVRek9TsRIY0ORcXeGl/H5Hw6it0Y1D0bI/u2wsxlOzFnxW6V2ZNmNeLYAa3Rp1MTOF0+dd/C6xcRNURxFbh46qmnjvpcr1698Pnnn1e4j06nw+23364+KPmYzQaYLQbs3GvHz3O34kChG0aDFr06NMax/VurmwWPSpmsvwlpvV6nmrjJPZmktK7dlo9gIITsRlacOrQtMjOsanVEbQYwGjqHy69uhM3prZE+5lI1mSMre+RestAhDaS4upKIiP4iD/9upxdetw9dWmegS06WVBIq6ccZCqmyi+XdW6iSEG4/bDYjRvVtiWG9WqgFFvL1ZB1ops2IC0/qXHId0mrV15BMDXsMV/nL+5ktRljMBhU0mblslypdZbMYMbJvS/Tu0BhOtw8el7deJzlMZj1MJiMK7R78MH0D8vaXBHM65WSqwI+sVpaSHrEIYEjwQjIvdG43zDl9kZnbW72XTAr5QjocLHDFVTCHiOLLjr121bMoGvNW5uH4Aa3gib4v82Hq9/jafVHts3jNXpx7XEdUnRtSC0Ih9O3cJKpm2T3aNVILAXp3bIJpiyMvFyUT9tKIWshiRX+xWy0UlH6PJwzKgU5Xco2V3o4FBY6YXu9cbr86ZpMlG+mjLlKLJyUEEwhqIIkjPl/sSg/LtcnlkPsRPwZ0aYoBXbPLji3fyesXETVocRW4ICqvQdpDr83Cum35ZV6TpmXvfbdS3bSdNrK9KpdUH9kXRqNO1SX96IfVquGY94hj+OaPjeqmS2pSmjUa9leoRXKzKqth5SZemtZlZlrhzHfEVVYOERHFFzVhcKhfRTQcjqMnuEpXRS+5DtmQH+PrkEye2FJMWLX5IF7931LsLyhbemPKgm1ommnBjef3RYeWGfW2QlMWnmj0Wjz54XwsWrO3zGsSaPn4p9U4eXAuLh/fXR2j1PqOBan9LYsZyuJ9ABFVzlON3kNub6DGv18lwBpuxB0p2V6nrZ+K3z5vACcMaqOefSM9bmmuLfl2Z45qH3HgQkpEjR3aFn5f2e+LBLrlQ66xKbVwjT1qgYPbh+gKXFWfBCokY6QuxkZElEjiuscFNVzywOvyBnDLS9OOClqESQrlhz+uxoSf16jggVoIUYfkRlPe98VPl2Di9I1HBS3Clq7bh1tfmg6tZGaYGCskIiKi6i/qWLZhPx55b+5RQYuwvfkuPPDWHKzZlq8yM+qa3OvoDDrc9vKMo4IWYVLiY9LMTXhuwkJYbWbodHV8E0dEVEp6SvQNr7PSav78KRPT6SnR/Z6W7f31VG2gJIs9hHOPr6D/wxEky0Kaa9vtHlXOaXCPZhHtd/rIDip4EcvyikRElJgYuKC4JKWXXvhkcUQpu1//sQFb84pVsKOuj3HeijzMWLqzym13H3Dgza//hL6eGqkRERFRYpNVmFI+4vkJi1BV1QipC/7MxwtLggi6ur3d1xv0eOfbFdi5z17ltrP/3I1Zy3bGpMktEVF1Sa+E3OZpEW8vTaKH9W5Z42wxt8enyh9H47gBOfVWBlcW7hn1Opw6rB3OOrZDpdv26tgYd186EE6PX5VWdjg8uP2iARjYNbvS/aRnxYUnd2YjaiIiUhi4oLgjD9kHCl1YselAxPt8M22Dam5Wl4xGvcq0iJSURpCUU6nNSURERNGRCXhZpGCxGNWfdT0hX98MRj1+W7BNlSeJhPS9mLZYggJ1t2hC7nGkUfj0KOqYfzdjE0wmQ51nzhIRhUkvwvEj2kW8/Yi+rRA61Di6Jvy+QEnPH31k1zObWY9R/VrCW0+9E+U5fcXG/bj3jVk4fWR7vHDjSBw3sPXh45ff41Im+d7LB+GBfwzG2xOX46up69VzutfrV6WQ7rl8EB795xDVy0F76Pe+XqfFqH6t8NLNo/CP03rAXuxhmSQiIlK4/JvijkanxeR5m6PaZ+7y3bjlgn5/NbKqgwdzu9OHtVvLL2NVHknpnbZkB0b1bsG0VyIiogiprAG9TvWVWrXpIOwuL1KtRnRt20jVJQ/4AmpCJNmZjHpMXbg9qn2k58Xw3i1Ql4s6Zi7bWWH5zPKs316AgmI3jAaZ2OL9ERHVPemlMKZ/a8xZvrvKxtPNG9lw1ek9juq/UB3yTGgw6XHDeX3x/CeLKu2ZIdkOt13UHx5PoE6edys4CPw6fxs27izENU9Nweh+rXDmqA644dy+cHv9MBl0KHJ6MXnuVrz9zXLsK3AhK82My8Z1h8vpUddqf0EAHVqk4c6LB6jf+1I60GjQqjLQQX8ARYXOeunNRERE8YmBC4o/ISC/OLo2WP5ACC63v85W68mNY77dE/V++UVuGR4RERFFQHo0yAr+Cb+sxdSF2+Bw/zVRlGIxqJWefz+pC7Q6DdzVaLKdSGTRRLT3RwV2DwwRruSNhWAohAOF0bcyldKgTdOjrzFPRBQLwWAITqcH91w2UJX3nbJguyq5d6ReHRrjrksGIhgIqCyNWHA7vTimezM1kf/G13+WWypZJv9vPL8vurbJhMNeV+2iK3gGLi55BpZAw09ztqiPRulm2CwGeLwB7C9wlTl3EpgO7yvnWT5ccr12+dTnNBoN7KGSzxMRER2JgQuKS7JaI1ryYB6oozkLWQUSaUpvabKqhJUQiIiIqma2GOALhnD7S9NUw+kj2V0+fDt9E+av2oNn/zVClY9yu5M3eCErbKW2eLT3HeVNvtUWKftRnXs4WW3LFbZEVJ8kECGT51ee3hOXntoNP8zagg07CtTnJMti3PC2qheGx+2L6bVGvr692I3eHRrjgwdOwtwV0vtnF5xuP1KsBozq2wr9uzSFy+1TQYv6/F0pxyrXlSNJwLqioHW4THKonAMvCVbwlz8REVWMgQuKOxqE0L9LNn6cvSXifdq1TIdBmn7VUdqsNERr1siGzFTT4VUnkRjUrRlXkxAREVVBVmFaLUbc+MIf5QYtStu934EH35mD528YqSaeypscSQZuj1/VDt+13xHxPr07Nq7TMlqBQAgDu2Xj/UkrI94nPcWIFk1SVHkQIqL6JKWbfD6XKk04bliuygbQHMomQzCIwoLa+T0l1y3p/+D1+NCnfSP06dAEGi0QkkfbUAgFBc74eIYMhdCvc9Mqy2mV1qdjE3X9StJLMxER1bKG1dWQEoJMOvTv2lSlnEZq/PB2cHt8dXZDpFJc3T7VTC1SHVtnoEUTGzye5F0NSkREFAvSrHn5xv3Ymlcc0fYbdxRi3bZ8mM3JuyYn4A/gjFHtI95eymdK89RAHTY4lVXITTOt6JKbGfE+Jw5qo/aToAcRUTyQfjtSwsnl8MDp8Ki/u0uVKqwt8ntQyihJPwin3aP+dLm88RG0kMCON4ATBuXAZNTBYtIjO8uKJhmWSksSynUrFv1AiIioYWLgguJOuO7l5eO6RbR92xZpGNWvJbwxqjMa3QRCB3WzVhWdVoMrxnc/tBK0Tg6PiIgoYen0Wnw3Y1NU+8j2Wl30ZYoShdxDNEq3YMyA1hFtf/LgXNUHpK4bl8uK4SvG94BeV3VxTFmkctaxHeo0uEJERNWvOiBeuHEUPntsLN666zi8e+8J+O/Dp+Das3qhTbPUMttLlmCX3Kw6CfoQEVFyYuCC4pLUDj2mR3Ncc1ZPVS+5shJRj18z7NBKvWCdr8QJBYJ48rrharVJRWQFyp2XDFDH6nYd3WyNiIiIyjIZ9dgWYbZFmGxfXu3tZCIrf68/pw9G9GlZ6XYS3Lj6jJ6q9Ehdk3uyNtmpuPvSQZX2A2uSacFT1w1XpUfqOrhCRETRkSw+q80EXyCI2ct34R+PT8YZd0zCGXd8h3vfmAW9XovnbxypFuvJtr06NsZ9lw9S161kLeFIRES1L3nz6Snhsy4cxW6M6d8aA7o2w7fTNmLqwm1wHFqtISUIThvRHkN6NlcptLFexSFNxKS2qTAa9QgGfeWm6ErqrtTgfv2OMfhj8Q5MmrEJW3YXqdcyUkw48ZgcjBvRTj24S7pvefdscmMn76HVysN9SKUI8wGeiIjqklyHdGqFvAbBYFBdhxJtniHBDrfa9dedDjduvqAfxg1rizkrdqv7Eynb4fb6oddqMax3C7VYwm53q+3rmvzcyDF2b5eF9+4/Ed/P2IRf5m1FwaGeYLIiV+6N5B7P7wvA4Yi8VxgRUSxI7wqTSQfdoSw9efbzN/DMr/A50WjCz6RyL/DXNcRqM2P1loN48sMF8JS6tsjvfGli/u8vluJ/U9bjkX8OweCezdAkw6qCFpItSJExmfQwmw3q7zabEU6nr16u40RE8YSBC4pb8iBuL3ar+pkXntQZV5/ZE15fADqdFsFAEB6vH0WFrphmWsiNgk6vk3kbrN58EG5fQDXg7pyTqXpayAP2kTcPkkUhdTuH9mimVjjKtE8gGFKrPu0OryopJUGL8hqPSg1vk1mPvANO7NhbrG4Y27VIR0aGVZW+klWLXKFCRES1QQLnct0zGA0ocniwaXuBun61apqCFo1TVO8oyYCsj9raMinSOjsVew5G3gi1ddMUdZ+Q7GQiSaPxolMLK7rkdIZnxxoEXAXQWdJgbt0Ffp/UR/fW62SHCl7YPWoRyBkj2+GiU7rC5w9AKz90MobCfQjs2QBTkxwYUvVw+zTqnoeIqDbJc6TRpIfFbMDWvCL1DCbZ8R1aZSA1zaKe6aRkcUM/J3qdFh1z5JwYD/en2LanGI/9Zx78lfQj2n3AobIv/n3bsQxaRCElxQSjNgCNVgv3tuXwepzQWdOQ3rorgn4f3H6NCmIQETVEDFxQ3FM3PB6/egiXyX6ZyK+NSRSLzQSnx4//TlqFmct2wldq1U1WmhknD8nF2cd2gNvtheeIDA9ZoeP3ew8fowQg5BgrCjpIKq0txYz5q/Lw1dQNapVKaT3aN8L5J3RGp5xMOO3uuGnIRkREyUGuVVLyYcPOQnz261r8uX5/mddlxf5ZozuozEaH3V3nK1EDPj/GD2+Lhav3RLzP+BHtEAgkf+DCZtHDpPMjf9pnKF4+DSHPX8EdrdmGlJ6jkTnqfOi0ejhd/noPspi1GgT9XjiW/AbHqhnw7tmGkM+tXtfojbB1G4bMURfAYLOi2MFJLiKqHZJVYUsxYcqC7fh2+kbs2Gs//JqUJu7fJRsXnNQZLRunNJjyRuFz8tv8bapPVHnn5MKTuyCnWSre/W5FpUGLsL35LkycthGnDW9by0efHDLSDND4nTj4+2ewr5hx+PootNY0pPYeg8wR50KvM6KomGWniajhYeCCEobcPEoZpdpgsRqxr8CFe16fBXs5q2wOFrnxyS9rsGjNHtVTQ+pRVLSCpCTIEKp0skiCFhN+WYOvf99Q7jYrNh7A/Ztm459n9lRZHFI2qwHcOxMRUR3WqZ6+dCde+9+ycq8vm3YW4rkJizB+eDtcNq4b7MWS4Vh3FyK5xvbu2ERlf5SeSKlIbvM0dM3NQn5+5Bkaichq0cMYcmHne/fAX7jvqNeDbgeKFvwA54bFaHHp4wiZjXDVY1NUKXthM2ux++P74dl19D1PyO+F/c/f4Vy/AM0vehQptiawOxm8IKLYKlk0ZsLLny3BtCU7j3pdHt8WrN6DJev24o6LB6B3hyYqaJ/MwgvpXv5scaXnpFGGGeOHt8farfkRf+1f5m7Fecd3qreszUSRnmoAnIXY+dE9CNjLLmQUQWcRCudMVNf0lpc+jpQUI+x2Bi+IqGFhc25q8OSmTW/Q4f63ZpcbtChNbthe+nwxjKaS2pPVYTIbMHPZrgqDFmEykfTWN8uxcUfh4VqXRERENSXXFCn58HoFQYvSJs3chN8Xba/Rda86ZKLD6fLi0X8OReMMc6XbZmdZ8cjVQ+B0epN6hazKkrEasfvTR8oNWpTmz9+NvM8fh81qVFmg9cVm0WHvty+XG7QoLeiyI+/Th1WvDrkvIyKKJYPJoJ69ypugL00yCp75eBEK7J6kf/6Sc/LV7+urPCe5zdOxYHVeVF9bFv1J2Si9lGCmCrNdDAYDdk94qNygRWm+fduQ979nYD7Ug5OIqCHhkwE1eAajXqXHFka4emH2sl2qpJQ0Mo2WTB5I/dD/TV0f0fYy//LllPXQV+O9iIiIyqM36PHFlPVqNWUkvvp9g7p21fUEuNvlg0mvxcu3jFblGo98YJceWGOHtcVLN4+CXpv8PRLMJj1cW1bAt297RNt7d2+Ee/cGmM36esu2CLqK4Fw7P6LtZeKmePkfMBv5eEJEse3hIL8/pRRSJPyBoJrQ1yZxEDV8TiZFcE5MBh08pZp0R0r2qce4edyTwL5jzRz4C/dGtL17y3L4Du5GamrlizmIiJINZ0OpwbNYDPhh1uaIt5eJnh9mbsKZo9oD3ugf4qX8xvY9xRHvIynLTrcESnSqVjQREVFNVvhJ4+uFqyJfPbl7vwNrtuajTVNbnTctdbu86tp52aldceVpPfDnhn2wO31ItRnQq0MT1YA64A80iAagkvSyf8EPUe1TNP97ZI39P7hQ90z6EIrm/Fhp+cwjFS/6GS17H8dyUUQUM3INmbdiN4ockT+4SRbC1Wf0UhP8gUDd9niqC0aTDnOXR3ZO7C4vMlJMUb9HeoopqbMga0oaoO9b9HNU+xQu+AFZYy6ptWMiIopHybuMgCgCqpE2NNi5r+r62aVtzSsuKRIeJZ1Og407C6PaR+73du61Q6vlP1ciIqoZuQ7t2m+PONsibOOOAnXNrA8SlHDaPXA63Oiak4FBXZuiS+sMVX9cGqg2hKCF0BmM8EaYbRHm3b8dOn39lDuRHxfvvm1R7SPj0+h09fazRkTJR6530T5/SbbAwSKXumYmo1BIg027IjsnC1fvxdBeLdREe6Q6ts5AeopRLS6g8mn0huiv6fu2qWskEVFDwplQokPBgai2r8P3KtmHq1WIiChGqnMdQv3z+4Mq40N6Wcif8t8NilowUYc3LEREDViyP35FOj6V6ejyYVjvFhF/7dNGtFOLCpL9HFbXX+sReU0nIqoKAxfUoEnzT7n+t2ySEtV+Odmp1QomBAIhtGuZFvU8RcumKQgGG9gEDRERxZxch1o0SVGr4aPRvmW6umZS/Ql4PTA0bh3VPsbGLRH010/vD/lxMTZuFdU+hsYtEQoG+LNGRDEj17u2zdOj2kf6OjRKNyft7yJ5vmzbIrJnUnnklZ4f/xjfHdlZ1iq3H9yjOYb1bgmvJ7n7TtWEPNaHAj4YorxGGpu0UtdIIqKGhIELavBcLi/GDs2N6kZv3PC2CFZjpaesPOnQKgOtmkYeKOndsQlSLAb2tyAiohqTsg0yIdO/S3bE+zRrZEXX3KwGU5IpXskcUNrAsVHtkzZwHNz+eirx5dcgbeCpUe2T1v8U1deEiChW5No1pGdzpFojL5s3om9L1aQ7WTP7vB4/hvZsEfE5+W3+NlVa6oWbRqJH+0blbqPXadQz9R0XD1BlHGWhBFVMfrbkmheN9IGnwheqn/KPRET1hYELavB83gBOOKYN0mzGiLYf0qP5oUBC9BM4kqXhcvtw9rEdIt7nnDEd4avGexEREZXH7/PjnOM6Rdyq6cxRHdS1K1lXniYKt8cPa9teMDRqGdH2xuxcmFt2gtvtr7fJQq01HdaOAyLaXmtNQ2qv0XB7k3OikIjqhzTXdnv9GDe8XUTbywS8PKtVZ5Faop2TU4e1jficNGtkg0GrwSNXDcGbdx6H8cPbYWDXbAzu0QyXjO2Kjx86GZed2k31n6rOc3JD43AFkNJ1CHRpjSPa3pzTTV3/HQ53rR8bEVE8YeCCGjy/P4CAP4BHrh4Cm1lfZaOxW/7eDx539VNfJW12ZN9WqvZnVa48vQc65WTW26QDERElH7fbh9zmqfjnmT2rDF6cPCQXxw/KUaszqX5J4Ej6ezS74AHoUstf8RqmT2+KZuffD4fLW699smRipukZN8PYrPLJMa3ZhuZ/fxBeb/KucCai+uPz+HDOcR0xrFflfRp0Wg1u+Xt/ZKWa1bUy2c/Jucd3wtBezas8J7de2B+ZKSbY7R4UFDiRZtHjghM7qefiG8/ri1MGt4Hf64e92M2G3BGS8yTzEHLt09kqL2UmJaWyz7kTHp+UUqyzQyQiiguVz9ISNRAumQjIsuKlW0bjvz+txqw/d6v04LCMFBNOHNwG5x0vKxd9NSqXIWmzshLl0lO7oWNOBr6augFbdheV2UZKcpx3Qid0b9sIToebzbmJiChm5JIiZRzGDMhRPZ4++3UdVm46UGabNs1SceboDhjRpyUcdin5wCfleOB0SRaDDS2vfB750z6BfcV0hLx/rb7UmKxI7TkKmSMvgCeghctVvwEnuV/SaPRocckTKJj5JYqW/oags9Q9j06PlC5DkDn6QgSMKSh2MEBG1JBptRoVUFd9CGP4+CMBUbnu3XphP1Xq6LsZm1Bk9yDNZoI/GESh3YPu7RrhwpO6oHXTVLicHsQLvV6rzolch2M5aR0+J7dd2B+/tN9a5TmRbcNiFdT56/tdUpkgUppDqy4izRyNVwVFXmSmZZVc0//4BPaVMxHy/1UuUWtOQWqvY5E56nz4gxoUF7OUIhE1PJoQZ0SPIjcFBw86YnqzkZlpQ36+I+lWkSXb2CwWA3R6HQLBkJrEcXkDyEozqQCClMnw+wIxW0UiN2oWixFGkx4799qxbU+xah7XrmU6GmdYVIqty+mrtaBFsn3vSuPYEhPHFv+aNEmNu+tsspzb+hibPPibzQZ1HTpY5MbGHQXq+teqaSpymqXC7fLB6/XVWp1qfu+qz2TSw2KQeX8tXFtXIuiyQ2tJhSW3uyoF5vZpaq0nSXXGZjDoYDECRpMRrm2rEbDnQ2OywJLTHSFo4PJp4mJ1M38mE1cyjC8er7F1cW51Og2MxpJrkUGvVUELnU4Lu9OLgC8Q07JD8nUtViM0Wg3MRr1aqCYZBf5ACKFgCH6/X2W21fcMicGghdlsVL/j9TotgqEQdFotnG4fQoGgOsZYfd+qOic+n1/1hIzVOZF7D5NZD71BD4up5P1kjE6XT1VB8Hjk+beinxM9jCZDyc/JoXNid3jVfolcnio11QyjtmSOwbVlOYIeB3TWDFhyeyDo96mFCA5HcgQtkuF3dUU4toZxjaW6x4wLolJcLnlo9qkH7J7tsmC1muB0elBY6Iz5xI3ZYkRIo8EPszarCSO9tuQGbP32ArRobMOofq1htpRkgxAREcWa6rvk8qoPq0mP3u0bH17pWpDvqPeJG6qYBCU8npIHSUOzbtBqNOr7WVjsi8sHSln04fMBOrcHxiYdoW1acrzF7qCaFCOihsls1sNiNWHeijx8N2Mj1mw5CGmnlJ5ixHEDcnDayHawpZrhcnhq3GdJBestBnj8QXw/YxN+nb9NPYPJda9DqwxVxnd475YqgC+B+/qSkmJSE/RzVuzGpBmbypwTyZQ8fWQ7pKZZVFZITX/fqyCCnBNfAJNmblZNuMPnpGPrTIwf3ladk5L7hZqfExmXzWbC2m0HMXHaJixcnacCJGajDsN6t8QZo9qhRaMU1ceh9NhkkYUEV+aWc06OH5iD8SPawZZiVuck0fpxqWCMQQPPzk3wHtgBfUqWKgcp2ZSFiyfD0qYHTJnN4NFr4/L6TkRU25hxkQSrVOoTx1Y9VpsJW/OK8fB7c+GsoH9FVpoZj10zFJkpxloJXvB7l5g4tsSULGOLx9WgyXJuG9rYyhuf0ahTKz9lIkUmHmRyPlFvU5P5e8exJaZkHluyjC8er7G1eW4liACNFve+OQubd5Utm1s6Q/1f5/TB8N4tVP+E6l4TZCJeJraXrNuH5yYsgq+CcUj5xCeuHQqjThOTifpopaSaIMn991VyTiQb4vpzeqtSjnJOKpqor+r7Fj4ni9fuxXMTFpcpk1xaq6YpePzaYTBqw4v8qkeu8fIM/MzHi1QAoiISmJGSyjI2OW75OZHFfve+Mfuo8sqlz8kN5/XB0J41+zmpa3JOUm0G7P3mBTjXza9wu/RB45F57IWqtFSil+5Mht/VFeHY4hszLhIXm3MT1UM5qgNFbjzwzpwKgxZCVrvc/fpM+AIhVRKCiIgoGck1TlaPBrVarNySjyXr9yOvwIXMTKtaYSnBDCIiSq5JMJPJgHveqHiCXsik/CtfLMHS9ftKAh3VZDIbVVb70x8vrDBoIXbus+Ou12apMkaSgV/X10K9Xod7Xp9Z6TmRjJBXvliqgjAWm6na7yelqNZtL8Az/11UYdBC7Ngr52Rmjc6JBEkkaPH8hMWVBi3Et9M34fNf16nqBId/Tl6fVWHQInxOXvpsCZZt2F+jn5O6JOckNcWIfd++VGnQQhTOn4SCWV8hzVa3P5NERPGAT4JEdUxu+j74fhU83qp7ZRTavfjs17Wq7wYREVEykYd2KU+Rl+/GsxMW4bKHf8Fj/5mvJpZueWk6rn1mKn5fvBOpaWZVSoGIiJKDwaDH1IXbK52MDpPF8+99twIWs0FlYFTnWiMLx979bkVEZYR2H3Dg+1mboa/jwIXBqFelmiQrP9JzYjqUqVidcyIT/O9+G+E52e9Q5Y2re04k+LBjjx2z/twV0fZf/b5BBSOkRNSUBVGck29Lfk7CzbvjmZwT777tcKyZG9H2BXO+gSYUqPOAGhFRfWPggqi8BmUWIwwmA1wev/pTbnZjcQMkEy/yNRet2RPxPr8v2qFuUGTFCRERUUXkOiHXL7PVqFZhqj/V9QtxyWg24s/1+3Dry9Mxf2Weqld95ETJ2xOXq7ISslJTVqLW2bEZdSrbQ2qvh88lsx+JiGouPGk+aeamiPfJO+DEik0HqvV7WCa/t+4uqjSL4Ug/zd5c7UBJdWi1gNGgw/czN0d3TjYegNVqrNY52bKrKKLAUdhPc7ZU+5zIIrxvpm2MeHvJAJH30+q0UZ0TCTqt2nxQ9U6Jd2ZDCEXzJkW+Q8CPosWTYY7+201ElNDi/zc6UR2RmzBJSZXgwoylO7Bw9V64vX5kpppw/KA26NQ6A06Xt0bN2mRSae6qPUdNzlRGAh0bdxSgVWNbwtYTJCKi2g24m8wGFeT+fdF2LF23T2UyNEoz46TBuchtkaYacNdns9EjyeST3enDUx8uqLREhZCyEp/+sgZnHdsBfn/V2Yo1IedQzqU0C/1h9mZs3FmoamU3b5yCccPaIj3dAo/bp/pvEBFR9a5Z8nyzLYJV9KUtWJWHds3TqvGOGsxflRfVHnvzXThQ6IZRp0UwWLvXnXAGilPOyZ7oz0mHVunRv6Em+nOy56BTlTuuzjmxWgxYum5vVPssXrMX44a3i/qczFuZh9xmHRHvDGYLXJuXRbWPa+MSpPY7udaOiYgoHjFwQaRuoDWwpVgwdeE2fPjjajiOmNyZPG8bWmen4s6LB6BxuhlOh6da7yNZG3KjHi13BGWliIioYU4ApaSa8f3MTfjs13VHXWN+nrsVbVuk4a5LBiLNaoTL6UU8kNWXX/+2Bt4IA/I/zt6MC07qDJ9HW2tBfAmmSJbFm18vV6UppExFad/8sQEDumbj9ov6q+u52x0/gSAiokQhvz990oG6Gs9D1Wm5HKrms5QsADDV0cp9WUAn7xctKT1cnT7Usk913s8r5yTKrJdw1me07yfbVyfhRfaL99bc4XMS9EU3pxDye6CR9BwiogYkot96u3btiuqDKNFYbCWTPq9/9edRQYuw7XuKcdsr07Gv0F3tpl+yarNxhiXq/STrQ/YlIiIq/eBrSzHhs8lr8Z/vV1UYGJfyGLe8PB3FLp8qDxEPiwVMRr3KDomUw+3H9CU7VQ3w2jkmrSoL9fh/5mPyvK1HBS3CFq7eg9tfmQG9Uc++G0RE1SA9FWwWQ9ST0vI8VJ3Sh/I+sm+00mzGOnv+qu45yUg1Vat0U12eE9k8GAohIyW695Pt5VJcrXMSpyUyS58TOY86W0ZU+8n2oTrIACIiSrjAxZgxY3DcccdF/EGUSGTVSKHdgw9+WFXltrJa5+mPFsBqMVar54WUlujfpSlsUazead7YprI9vMy6ICKiIxo77trnwJdT11e5rQTln/3vIhV4r++eF1qtFgV2D5zu6DIQN++Ssk21c0xGkzRF3YpFa6ouZSFlKz74fmWdN24lIkoGgUBQTUgP6NYsqv1OGNQGoSpKC5ZHSgwe2791VBP8Pdo1gsWkr1ZmSHXIM6IcXf+u2VHtd8IxbSQqUDfnpH0jmI3VOydOpxej+7eOap/jB+VA+o5Hc07k/ubEQTkIVuPnpK55XS6k9BgR1T4pvcbAG4jzqAwRUX0ELp544onDH3feeSd0Oh2GDx+Oxx9/HG+//TaeeeYZnHzyyTCbzXjooYdifYxEtV6uYmIUzcJ27LVj3bb8ajX9kht1SekdMzAn4n1OHdYWLrePGRdERFSjZpfrtxeoQIcEPBJVdRYNVP01SxqVToqiAejvi3aofhjSu4qIiKIT8Plx5qj2EW/fq2NjpKeYqtVfSBZ/SePrY7pHHig5fVR7eL1128soFAzhjCjOSe+OTVRWgqMaJYzD52RQFMGjM0a2h7ea/Z0C/oB6ptXrNBFnTcj3y+cNqPeN5pyk2ar3cxJLJpMOGRlWZGaWfNhsR3fUlmqTaQNOAbSRLYLQpWTA1nEAXG4uZiSihiWip62zzjoLZ555pvpYsGABzjjjDLzzzjvq8yNGjMD48ePx4osv4m9/+xt++umn2j9qoliW2bAa8cfiHVHtN3n+NoSqOXkiN+qXjO2K3Aiay8lN+tihbeGr4xtnIiKKb7JKUjIGZy7bGdV+UgapvlMupCSGTLbIatZotGmeBp2+pKeHpZolG8sjJZ/y9jtUSchISVmueSvyWC6KiKga3G4/OuVkYuyQ3Cq3TU8x4ubz+8HjqX5fIb/Xh+v+1huNM8xVbjuqb0uVIe+p4z5GDocXXXOzcHIE50SuoTed31cFBGpyTq4/J8Jz0q8V+sk5qeb3QAIleq0G//e33lVuK8EN6SspC/dcLh+6yDkZ3Cbic+Ktwc9JTaWkmJCSZobVZsbqrQcx68/dWLx2HzQ6HVLSLCqYUfqchLQGND7ln1V/YZ0eTc+8FR63R91DERE1JFE/bc2aNQuvvfZaua+NHj0aX3zxRSyOi6jOVm5KFkRFfS0qUlDsgbaaEz9yk6LR+vHM9SPw7ISFql72kckUMiE1ul8rdYPtcnpqrREpERElJtXI0+OHL8rrg5RoUvUo6lFJ9qEfxw5ojR9nRZblYDXrMbx3S9z7xiw0ybTg4lO6IjPFpK6RNU1IlHsBdV6itL/QVd8xICKihCSZ5A67B1ee0QNpKSZ8M22Dyko/UsfWGbj70oEwG7RwOb01CpRIqcQXbhqFpz5cgFWbDx61jUGvxalD2+KSU7uqY6vrCeJgMAiX04erz+iJdJtRVQQor6F1+JxI6WF7sbvWz8m4YW1x8dianxO5Xo/o3RJGvQ7vfLschfajv5/ZWVbcckE/5DZPhdNRcn2XP68+s6fKuKnqnJj0Nfs5qYm0NAs0Wg0++3WtWiRSenxGvRbD+7RU9y6paRYUF7nU54scAaR3G44meiMO/Po+gs6io76uPr0pmpx+I3RN2qCwmIsZiajhiTpwkZmZiT///BPDhg076rW5c+ciOzu6uoxEtb0aVTIjZFJCbpA1Iakh6itz0yUNOXVaTYWNOMtjNGhVk7HqUit4QiHcefFAFDk8qjzFzn121UisbYt0lUprMujUDV4se1tIWQur1QhfIKQmWyRgI41d5QavNnpoyPvpDDpoZJZMU/KQIrVp6zt9l4go0cklqDpliqQ0BOpoLkayIrR6XanAQgg6jQbFxW61SvTs0R3w67ytEQVfThmSi627i1S5K/mQXhQPXzUYuc3S1KRGTci1yWSMvl9FeRkjct+h0WnV4gbJypDeGRpNoM7qpBMRxaoXkZS3Ccjzk0ajnhksVhM87tg9M0ifBZl4l5JRZx/bAb/O34YVG/era0KjDAvGDs1Fq6apcLu8MZmMdrt8MJkNeOyaocg74MSPszdjz0En9DoturTJPJzpYC+WRWP18zu7JKMhhLPHdMTfxnRUE+ArNx1Q56RxhgWnDM091PvQX6OgRUXn5IdZm7E3v3bOiTx/O+xu9O/cBMMeOAlzlu9WH3KtTLUaMWZAK/Ts0BhOp08FScLk+iljPWt0B5xzXEfsPuCATlvy/O71B5FiMahsC1eMfk6qIy3NDLmTuevfM7BpZ+FRr8txTl24XS1YfPL/hqFplhXFhS51TgqLfUhp1x9tbhgC+9p5cK6dh6DXBZ0lFSk9R8PSpjs8Lg+DFkRxqnPnzrj++uvxr3/9C4nk4osvVn9+/PHHSLrAxTnnnKMyLtxut8qwkEDG/v378fPPP+PTTz/FPffcUztHShQhmZA3WYywWgxYtm4f/li8E3anV63WHNa7harlKamncqMmNwtur1/Vw1y8tuqGnGH9u2SrIEhNyOS9fMgkxzljOpTU7VZfM6QmdIpdsbvx0ukAi9WsSlosWbsX05f8dU6G9mqhaoh6/QG4HB4EAqGYBCzkJlhiQT/N2aJ6gkhgqFmWVQVlGmdYVfDGXccp2EREyUKyFkSX3Eys2ZIf8X4Du2bXesKF9NCQCXsJ8P88dyvWbDmorgHZmVaMHZaL7Cwb/D4/9EaNWiH5xAcL4K+kkebgHs1w/gmd8eA7cw5/TlbmPvzuPLx77/EwGnU1mkiTrEYp3yirVx0RNgyXS3b/rk0PZ0TKtdxsMeJgoRvfz9p4aGJFg06tM9TEj1wT5brHAAYRxTtbilkFc1dvOYgpC7ejsNijavYP7NoMI/u2hNEXUMGEWGSEy9fw293Q63UY3a+l+ggvOJMHicICR42z6kqT38PykWE14O8ndlZBZgnSSLaDN05+R//1jGhQDaqPGyhNrTWHg/9yToLB2jknF57U+dD5l1dCMT8n8uytFsx5/OjbsTH6dGxcZoFhQb6z0qwOeWXFxgNYfijA1UQFc9qqcmL1SaPV4pkPF5QbtCityOHFfW/Oxrv3naAWd0gpLBmvZF7o3B6Y2/RDVm4fVRYz4A/CG9ThYH5JgIOIqKGKOnBx7bXXori4GO+9955qzC3kQiONuW+88UZceOGFtXGcRBFPJEhNyQ07C/DSZ0uwL78kDTNs2pKdqtnX/53dC306NYFDVo94Azh9ZLuIAxcy2X9s/1YxWeUiajv7QIIW1hQL1m7Nx8tyTgrKPyfXntVL1XN12L0IBKp/gyoTSFabCe9PWomf52w9ajLquxmb0KtDY9x5yQCVniwBJCIiip48+J82vB3WbFkUVbPLwkJnrR2TPIibzUZ88MNK/Dh7y1HZFJNmbkL3do1w1yUDYTJo1MKB524YgQk/r8GiNXtUwDusWaOSYPdJg3Px/CeLjipjIas0v5+5GacNbwvUIHBRUroqgDEDczBpxqbIG4BajSgqdKlrGbRaPPr+PCxdt6/MdrKadMIva3DiMW1w5ek9VXZIXTd8JSKKlNTn37nPgef+u0hlg5c2c+kuvDNxOS4b1w3H9m+tVs/HqpytrOavyyyH8OIpyVzMzLQhP98Rd6V5JfuiJn09olWXC8rkuhtpdoQEtVJSTfj813WYOH3jUSXF5F5D+qXcdelAWKzGOs+6SE+34GCRW2VTRCK/2IM/Fu3AyD4tgVLPwap8tTNY8jNptaDQIT+TfE4mIoq6xoBExO+8807MmTNHBS6effZZFcSYPXs2rr766lo5SL/fj5dffhnHHnss+vbtq4IjS5cuPfz66tWrcdFFF6FPnz4YM2YMPvroo1o5Dop/ZosJ67bn44G35hwVtCjdn+LJDxdgwco9sNiM6oawV8cm6NG+UUTvceHJXdTKzni7ua2I1WZRkz0Pvj3nqKBF6XPy1EcLMHdlHqy26q9Y0ek0Kmjx3IRFajKpohW0f27Yj1temq5Wp8gqVSIiip5MgA/p1ULVdo7Epad2UxmHscisK488bEvQ4qXPFuPb6ZsqLAElZS9ueXmaKlsoTTibZ1lwx8UD8MEDJ6kMjJsv6Icnrh2G1+8Yg0bpFtz12kzMXZFX7tf6ec4WWC3GkqzFGgj6Azj3+E4quFMVqVUtE3c+b0nWpE6vw60vTz8qaBHmD4TUxMozHy9Q10gpUUlEFG+kfKwELe56deZRQYswu8uHV79chp9mb1G/z4hqk1zb5efynYkr8Plv68rtgyIku/+WF6fB4w/CbK7bZ0t/MKQW5kVD+ntJ/xAiSj4FBQV44IEHMHToUPTs2RPnnnuumj8vzW63q22GDBmi5rhvvvlmfPDBB6rsVGm//fYbzjrrLPV1pF3DY489BqfzrwVo//73v3HCCSfgjz/+wPjx49GjRw+cdNJJmDhxYpmvs2vXLlXOqn///urr/Oc//znquKWq0vPPP48TTzxRfZ1+/frh8ssvV/PtYXfddRcuvfRSPPjgg+r1sWPH4oYbbsDIkSNV5mJp9957rzqWWKj2b0ubzYYmTZogLS0NvXv3htdbe5HtN954A19++SUeffRR9Q1o27YtrrzySuzduxf5+fnqZObk5OCrr77Cddddh+eee079nRoWmQgwm/R45uOFVfarkPTXlz5fom6GZD9ZAfnglYPRs33jKoMWJw/OVenRiUBu3GQi6bn/RnZOXvlsiSrtkZJSvQcRo9GAOX/uxuw/d1e5rdSUfeub5dAbGbggIqoOWZ3ndHpVbWpZbVgRmdO/6oweGNG7RUmPpVpisRgxf1WeyuSriiwueP1/y1TdZ8k8lEaV0ttJAt4yYTZ9yQ7847Ff1TW9stILsnJRSj5K4Lwm5Bj0GuCp64ajUbq50r4WD1w5WJU+lBIPeoMeb09cgd37HVW+hwRfZi7docpoERHFE3kekkDs0x8tKLf58ZHem7QCRU4fbAxeUC0/y0rVACk9XJUCu0dVFzCaDKhLcvexLa84qn225hWX9NnkQgaipOLxeNTE/pQpU1Qw4tVXX0WzZs3U/HXp4MX//d//4aefflJ9MV588UU4HA4VNCht0qRJan67Xbt2ql2DBB6+++47ta8qp3jIvn378Mgjj+CSSy5RyQWtWrVSyQYbN25Ur0ugQxb6r1u3Ts2p33///Wp+fcmSJWXe74477lDz6JKQ8P777+Puu+/G+vXrceutt5Z5v4ULF2L37t3qmOS1v/3tb9izZw/mzZtXJggi7STOPPPMmJzXaj05ffvtt+qkygmSiV8ZtER6DAaD+rzRGNsagxJlGjduHIYPH344yiPvKVkXmzdvVu8r3yi9Xo/27dtj69at6ht29tlnx/Q4KL7JRMCMZTtR7IxsUkZWgspKzRMH5aiUUpnYefSfQ7Bs/T5MnLZR/Slz/TJJMapfK9U4LivNrEpEJUqdSYPJoCZ/Ij0nMoEk9chPGdKmWu9nMuvxbRQrTmYu24VrzuqlemLEQ01ZIqJEUxKICOHp64dj0eo9qoyCZDTI/aX0bDh2QGucMbI90mzGWr9+SU3maFYdzl2xGz5fb1XH2++XHktB1XRbGljWB7kXSLcY8fbdx2PKwm0qczA8GSF1tE8e0gZjh7ZVkxTSE0quXfIfM5bsiPg95Bo5ok8rtQAilnXbiYhqwmo1YvmG/apBcyTk99e30zbi7yeVXR1KFEuyOOCbaRsi3n7p+n2qj4QE4Y4sxyyfk34mQvU08fp5HSaimJK58jVr1uCLL75QC/yFZCNII+zwAnsJYMgkv8yhS3ZDeBuZ8w4HGyRQINuPGDFC/RmWm5uLyy67DNOmTVM9p4XL5cLjjz+usjfC20i1ItlG5se/+eYblXHx/fffo0OHDmobOTbJ1AiTRAQJntx3330qi0IMGjRIZYY89dRTqq+1JC6EKyLJ/LsEZMK/T+XvkmQQPoZff/1VBUzOOOOM+glc/Pjjjyp6c9ppp6mTIVEkIYN++OGH8frrr+Omm25CLDVq1Ai///67ihI1b94cn3/+uQqOdOnSRQUw5IRK0CJs8ODBeOutt9TJbdy48hX0lDxkxcKUBdFNdvy+aAdOH9leTVa43X5VAqpTq3Tce/kgGNXKz5BK43S4vKqMhKwITTTSVC8avy/cjtNHtIv6fWQCR24UJVU3UrKydtqSHRjVpwUDF0RE1eRx++HzBtA9Nwt9OzeFXqdVWXZy/bI7S65fserLVFlvC6fbr4ImkZJjnLpoO04eXBIslwUE0iQ7GpmpJpiNejjtHsSCy+WFz+fHiF4tcMKgNoebhmq1GpXd4vf6D1+vpKfTrD93qaB/pDbuKFS1sCW7pCYNxYmIYkkqCP4W5XPUtMU7cOXpPeBySFC81g6NGiipGiCLA2RRRqQkEDF5/jacLr2vpLyIVqMWR8jiur35LmzZdVA1+G6TnYZmja3q/knKRtdkUYfsmdMsVS16jJRsL4s15IOIkocEJWSCv3v37mqCP0zmzp955hkUFhZi7ty5avH98ccff/h1CapKwECCGWLTpk3Iy8vDP//5zzJfZ+DAgUhJScGsWbMOBy6EtE0ICwcUwiWlJENCKhSFgxZC5tVL7yPz69ICQkj2hCQIbNmyRc3Di9IVljIyMg6/R/jYJbPiww8/xEMPPQSLxaKCJVIqq/R2dRq4ePPNN3H++eerAyrdwFeyGw4ePKgiS7EOXEhtLGn8fdxxx0Gn06kTI99QOfnyzezUqVOZ7Zs2bar+lPSV6gYu1IUyRsIpgMmYChhPY5PvWUGUEzPS20GOvfT3WyYk5MOr1yE11YziYtfhfhax/LmoC3qtnJPoJnMkzfbIcxLRe+m1OFgY/cSRlPmQu1L+m4sMx5aYknls1RWrf/PJfG6jHZtMuMuHTLZLEEAm3MOrCWv7+iXHmF8U/TVArlESwJDjCwWDqon1Rz+urrBH0pFOGtJG9e0oKRVVs3JRpUn/CvmQSQ9RelLjr3OpwcHC6ANChQ4PWmRZEyZ780j8N5eYknlsDWF80Yr2d75Wo4n6mUF+l5W8l/6o2taJIpl/bhJ9bDabGcWyeDDKS2XhoZ9jWVxgthhVb0XpjyElp0rr0CoD5xzXEf27ZMPj9lY7iGDQaXDaiHaYFEXG6dihuar6Q3n/ThP9+1aVZB4fx0bS30IqE0ngojzymrQ7kMn/cAZY6QX7pb+OkOSAhx9++KivI20TSpNgQVj464bLO0mwJDPz6JLCEmCRxf5hM2bMwBNPPKGCJtIaQhIFrFZrma8l5LUjSTxAYgWTJ09WiQQSwCmdKVLngQuJvEjGRXkk3SQcIYqlDRs2IDU1VdXQys7OVlkWt912G/773/+q2llHlqYymUyH64tVhzykZmYe/c2oqbS0v36Ykk08jM3rC8AUZb8Ek1Gn/hFW9v1OTa3/sdXonEgpiyjI9tLnojr/BopcZVNyI30/s9kAmzW2Jebi5eeytnBsiSmZx1bf19lkPreJMjZjNa8BkiFiPfTz4PH6MWZAa0yet7XKfaWU4/jh7dX1ozauIVWRa6XcR0RL7lWkLnysa8MH/T4g4D8Uv9FAa6y4V0dD+rmsDo4tcSX7+GrrGut0+6L+fWbUl2yfnp745zyZf24ScWw+yRSNsNTxkaRqgsGgh9Gox3fTN+LDH/9qLFvahh0FePLDBSp4ccGJnWE49PNcHY3SNRjQNRsLI8gOkUxRKeMp/36kP2cyfd+ikczj49gaLpm3llJNFU3aS/8JmdOW4IUE/EsHLw4c+CtrXXpJh/tODBo06Kivk56eHvExSdBC2ikcKRwcEdu2bVP9NCQLRKoXtW7dWi2EmzBhggpoVEW2l+OUvh3ydSUrpHRGSZ0HLiQKJHW3pBP5keTzpaNEsSBZE9LwQzqsDxgwQH1OOqpLMEOCJGaz+ajG4OGARTg6FC1ZAVdUFFl9z0hIVFL+gRcVuZIuHTCexiaNuPp0ahJVqSLZXkpbeN3euB5bdckqk76dmmD99r9+KVVFtpeaoNE2IJeHpOwsq+oDImUwInVM92bqvaTOaKwkw/euIhxbYkqWscUq2BDL62yynNtEH5vceDfOMKteEPsKIi+rOLB7tqrtkJ9f0txar9fhmrN6Iu+AQ62SrIhMsD145TGQxYrhfeuaTIoM6tYM7323MuJ90lOMaNnYhsJCZ0wyLuRnxGIEdFoNiv/8He4tKxAK+qFLzUJa35NgaNJK9UFxe4MN8ucyWhxb4kqG8dXnNTb8zDB/ZV5Uz1ESbHYeyrxIRMnwc5NsY5PjtqWY8eh78/Dk9cORk52KbXsib3496NB9xZ8bD1QYtCjtyynr0bZFOvp1agzvEX0xoukRc8fFA3DXazOxaWdhhdulWg147Jqh6t9oRfcuifp9i1Qyj49ji2+1sTj9SDJ5/8cff6h58RYtWhz+vGQjrF69WgU0ZJtXXnkFU6dOPTy5L4uppbdzmDTklq+xY8cO/OMf/yiTaSHBDKmCJBWIIiEZENLfYvny5WouXUi1JOkZ3aNHD/XfK1asUPPo0pi79NcNBy1KZ1xURJp0S48MCcBI2atwQkG9BC7kAOQkSzmmUaNGqc9JJEYGKv0tpKFILC1btgw+n+/wCS6d3TF9+nT1w3Bkmkz4vyWSVV3h0kCxJP/Aa+PrxoN4GJtW68f44W3xv6nrI54MOGNUe1X7u7Jjj4exVZcsuhw/on3JOYlwfuSMUR2g12mqNWYp13Hi4Bx8NnldRNt3yslEs0ZWFOTHLlCYLN+7qnBsiSmZxxatWJ+HZD63iTG2IDxevSrd9N+f1kS0R7uW6WjTLE31jwqPT/6Um+OHrhqMidM24qfZW8oEQmSCfnCP5rjw5C7ISjWpCbP6aq7p93vROMOKbm2zsGrzwYj2OXFQG7g8JT21akpKTKRY9SiY/Q0K505EyFd28rB48WQYm7dH9tm3w2JMQbEzdgsEEufnsno4tsSV7OOLVLTnQErjSV+fD39YBXeEv5+kT2AoGEqK853MPzeJNjaLxaj6WqzfUYCZS3filKG5eOub5RHtK8+V3ds2UiUov5wS2fOo+GrqenVvIX0vq3NPUVTkVpO6z/5rBD6dvBa/zt+KQvtfiwCNei1G9G2Ji07uihSLAcWFrqT7vkUrmcfHsTVcZ511lqoMdPnll+Oaa65RvSRmz56Nd955R/Vslt4W0qdCEgGkJYKUapI57f/9739Yu3atmlsX0iJB+kk/8MAD6u/SI6OoqEjNuUsPiopKUZXn9NNPx0cffYTrr79efU3JhnjjjTfKlHiUrydlH5999llcccUVKjng66+/VkGY0v0yKnPSSSfh0UcfxZ9//on7778fsRR14EL6V6xbt079GU5rkQ7pMhDJiJBeFLEUbuYh38RevXod/rwcg6TgSADjs88+U/025BsqpNlJ27ZtY579QfFNJgFS04yqxqRMdlRlVL9WyM60oqCgdibN40FxsRtpGVaMH9EO306vuu7m6H6t0DRLAgnVW70a8AdwxsgOqkn6vvzKb8hk8ukfp3VXTdGIiCjxyUKA00a0x2/ztyHvgLPKLL1/jO9e7kIDyfqTB6NTBrfBWcd2wLqt+Sp4IVkWXXMbqXrScr2Jh1W+sjrzivHdcddrs6rsyyEZKTKewKHm3jUhDzZpKUYc/O1DFC36qeLj270RO9+/Ay2veBYWsw0uXnOJqBzye9dg0uP8Ezvjg+9XVbm9ZGdI0LYgigw7okhotFp8P6vkufWHWZvx2DXD8NOcLdiWV3nWhcz3XXlaD5UFVOz0RbygQGzcWYid++xolGKAu5rXSVmJnpJiwrnHd8RFJ3fByk0HcLDYDavJgJ4dSvqu6rWapJ57IGropOqPlFd6/vnnVRCguLgYLVu2VFWEJCAQ9uKLL+Kpp55S20nzbennfMEFF2DixImHtznnnHNUP4l3330Xn3/+ufra/fr1U1kbUpopUtJaQRpnS/+Kxx9/XD1DnHvuueprhMtTtWnTRh3Lq6++imuvvVaVopLm3R9//LGa75cG3507d670fSTDQrI7pEdG6bn7WNCEIsn5KId0MZeGG9LoQ+p4SbqLZGCEI0SxIlEgiUxJDbAHH3xQBTLkm/n222/j008/VTXCTjnlFIwZMwZXXnmliu5I43BpYCKdzatDHpYPHoxd2QFZESdpSZIOmGzRyXgbm1p9mGrG298sx89zK66PPbx3C9zy9/5w2N2qEXcijK26rFYDTGYj3vr6zyrPya1/768au9rtnhqtknH5ArjnjVkVTlzJqpM7Lx2IHm0bwelwx3y1bLJ878rDsSWmZBlbkyapMfk6sbzOJsu5TZaxyTXY6fHjntdnYdf+8r/H0tPitov6qYaYZqO+0vFJgENKMsmfcssq21V03a4vUtJi9daDePKDBfBUcGxSSvHxa4bCZtarFZ01ZbEYoDu4Gbs/vi+i7c1teqDZeffiQIGnQf5cRopjS1zJML76vsYaDDrYUkz4/Nd1qplxZUGL+644Bn5fAI44CCA39J+bZBub/Du47JFfcKCwpPTw+Sd0wslDcvHQO3OxZXdRhQvi/nVuHwzt1VwtDli1tQCPvj8vqve99e/9MLBLUzhjcI02mXSwWEwqmCKkJLLD4U3q71ukknl8HFvDuMbW1M6dO1WZJglWSOuDsBtuuAHbt2/HN998g0TkdrtVTOD//u//cOmll9ZvxkWYpLbIh9TBknSXIzuix4p8XUljeemll3D33XerQEmnTp1UzwvJthASgZLIkQQqpDO61PyqbtCCEpv8ErUXe3DVGT1VWqlkXsxatgtef1CVP5Ja1GeM7oAOrTLUhHm8TX7UBqdqbKbB1Wf2VDd9ck5m/1n2nJw+qr0q2+SvYdBCuFxeNaHy+h3HYfqSHZg0Y5NaxSKk/4WUkho3rJ1679oIWhARUf2xF7tV8OK1O8Zg+pKd+H7mJtUAU37XS0NKKUUiWYCSPeFxeVTgojKSkeF2V69BZ12Ra1mXnEy8f/+J+HHWZvwybwv2F5RMuLRtkabGKxmNsoozFkELYTYA++d/F/H27q0r4Lfnw2RKUyuriYiOJM9Fksl27vGdMLp/K/XMIL/HpbydBI8lYCHloXp1aHxoIjaxgxaJwGjUqaoSMgEu10M577Hoj5RIPvt1HaSiyfM3jsTs5bvw46wtWLP1oLqvSLMZcdzAHIwdmqvuMeQexFRJw+u64vEE4PEws4KIyp/jvuuuu1TgQvpCyO946SUxefJkPPnkk0g0O3fuVMEWKYkliQxnn312zN+jWhkXkvohfS7kwOx2O7788ktVk0saiEgaSaJjxkXij01u7kwmA3QGHaxmA3z+IAx6LVwen1qFIZMHVf3ox+vYqksqqaWlWeELhGAx6VVJC1n16vb6odOUlJUKBEIxbeBkNOlhNklgU4NgKKRWwzicXlXiIxb1vRvK9640ji0xJcvY6ns1aDKf22Qbm0y2GE0GtYJXZUsEQ+q64HT7EAoE1YrGRB5fhRNMeh1sVqOqr63VlFz73C6fymaM1RjlPGakGrDl2QuBUORfM2PY2bAOPAPFzppdf5Pt+1Yax5a4kmF88XSNTU01Q54KLGbD4WcGlVEWDMHp9CTsOU6UnxtZBKY36NVz2uotB+H1BVXmXsfWGaqnoPQkqep443VsVUlLt+LxD+Zhydp9ZT7fskkKThmSi+MG5ahnWfk5Nxp0WLZ+H7buLsLxg3LgOBS4cPmCuPKJvxrdRuLV245Fps1Q78H9RP2+RSqZx8exxbd4ybgItzd47bXXVMNuKRXVvn171Rcj1j2j68Lu3btxxhlnqLJWklAwZMiQmL9H1OFoObEXXnih6h8hJ1XKNQmJEknNLGn0wWwHqm8Sk1ArNN0+uBweFciQzzW0FSqlBQJA/qEm2G69DgaDFikpZnV+aqsZvawslQ+ZtAqvFGKGBRFR8pPgdDhALQ87cg2Q60KpPnBJR43XG4Db5VUBm/R0KwrznTG/xqrFALKSM4qghQg4CqBBEn8DiChmZEGTcDq8MBq1SE21wGl3J+yEVaKQa6XVZsKefBc+/mmpalJd+vFVghenDmuLccPbqu+NZGAkm1AwiHHD2x0VuJAeFO9+twIf/LBKZVfIvUWxwwu7y4fnbhihFuIJCTxkZlhVD5ZI+1y0b5mOFk1SUFgQu8WrREQVkV4Q8pEMmjdvjnnzoivNF62o6zs9/fTT6NGjB3766Sfcc889h1et33fffSrNRbqVE8UTmSyXTIKGHLQ4kt8fqNMyWeHvAYMWREQNT0lfiuQOWpRW2wsl5N5bozdEvZ9Gb0IoFNtedESU3KTfJIMVdcdiM2H1lnzc+vJ0LFhVNmgh9hx04v1JK/H4f+bDajOqIHmykbLD0gNLMizKIxlA+wpc2L3foYIWkoUiZaDt9pJgm/B6/KrkWaT+dlxHeDy+hHxWlZ8Bi9UIi9Wkfn7MViPMZsPh/hpERIku6sCFNBG57LLLoNfrj2rEPXbsWGzZsiWWx0dERERERIdI5orGYIKxaZuo9rN2HIgAkm+Si4goGagSR54AnvxwgSpzXJlFa/biwx9WwRAH/RxiTQJlXq8Pj14zFI0z/mpcW57mjW146KrBh3p//PV5qbzQvW0jXHpqtyrf77zjO2Fg12x44ryf1pEk48SWYobJYsTURTvwypdL8cIni/HxT2uwv9iD9AybCmAQESW6qK90JpNJdQsvT0FBAYxGYyyOi4iIiIiSiKx3Uf0uGnjpxpqS8ycTLGkDT8X+H16PaB99elNYcrvjYL6r1o+PiIiip9Xr8M3ktSW9RCLwy9ytuPiUrmoCO9myYuzFHqSkmvHyLcdiws+r8fuiHapJfJjNYsDxA1vj7yd1gQYhtf2RmYnSaF5KarVploovp6xXvUJKk0yNv43piP5dmsJh9yTUfYlkWdhSTPj813WYOG3jUT8zP83ZosZ392WDVDaGlG4mImowgYthw4apxtz9+vVDkyZN1Ock88LhcOD999/H0KFDa+M4iYiIiCgByQO23qCDVZpWB6Rpdcnn3fXcADORub1BpPcYiaIFP8C7d2sVW2uQdfxl8LgSa2KGiKihkKC+NJyesnB7xPu4vQFMXbgdI3q1gN+ffBPT9mI3UlJMuOzUbvjHaT2wfON+2J0+pKcY0b1dY/ilgWMwBLu9bNCidHaiNOvumpOBx68Zin2FLmzdVaSazuc0S1X9QqQfhrxPIl0b5WdF+qC8/c1y/Dy34uv/+u0FuOXFaXjpllEq80L1/yQiagiBi9tvvx3nnXceTj75ZHTp0kUFLZ566ils3rxZRbZfeOGF2jlSIiIiIkqoDAupuSzTAT/M2oyf527B/oKSrN3W2ak4dVgujh/UBiaTAX5/+RMPVD5ZXet0+dH8okew+5OH4M3bXP6GGi0an3otzG37oKCYkxZERPFIp9OiyOGFwxXd7+ktecUY1gtJKxyUkDJaPdpmqbknmXPyuD1ISbEgP7/yZtoSkHC5fOojxaRHz3aNDn0+iMICZ0L2tJBzIdkjlQUtwgrsHrz82RLce/kgBi6I6smBQheWrN0Hp8cHq8mAvp2boFG6pb4PK7kDF9Ix/Ntvv8UHH3yAuXPnIicnB06nE+PGjcPll1+Opk2b1s6REhEREVHCkCaRG3cU4rH/zC9T4kFs31OMN79eji9+W4/Hrx2KDJsRAX9QTd5IwEMmG0pqVifgrEIdcbn9gFmPlpc9Dcf6hSiaPwnu7WukSAa01jSk9jwWaYPGAUYrCu3SdJTnkoiIEo9kRshHmJTHqs7XSAZ6gx7fTtsY8fZL1+9TQTEJeCTLOSBKBOu356sydfNX5iFQ6nlGp9VgUPdmOOe4jujYOrNejzFRVKubU2ZmJm6++ebYHw0RERERJTyLxYC9+S48/O5ceCupve1w+zBvRR5OHd4W3kAIKzcdUE1JmzWyokOrDLjcPvi8/qSr3x3L4IXXF4C5dS8069APGp1eoj7Q6HTwOp1w+jTwMtOCiCiuSVmjjFQzUiwG2KPIumjbPO1w+UVKfhKwkenPRWv2RLyPrFn4df42nDa8ba0eGxH9Zc7yXXj2v4vUM82RJIgxZ/luLFy9B7dfNABDejavteO4+OKLMX/+/HJfu+KKK3DnnXdWuv+8efNwySWXYMqUKWjVqhUSKnCxf/9+fPTRR+oEFBYWolGjRhgyZIg6KWlpabE/SiIiIiJKGAajHv/5fnGlQYs0mxEPXTUE/kAQT324AEvW7pVy1YdJ/WlprHnqsLZwOrwqA4OOJn1DHE6/+pDa1+GMFSZYEBElBlXSyOPHcQNz8O30yFbTS0+MY/u3htNRUoKRkp/qLevylblXikRBsSfqfYio+pkWFQUtSpPXn/3vQjx9/fBazbw45ZRTcO+99x71eYslccpVRZ1jt2bNGowdOxYffvghzGYzunXrBp1Oh7feegvjx4/Hrl27audIiYiIiCjuSTmCYqcPS9ftq3AbvU6L+684Bvvynbjn9ZlYtKZs0ELsOejEe9+txNMfLVSNKKXJN1U9+SWBDAYtiIgimwgOhkIwmAzqOmO2mmCxGlXZwroW9Adw5uj2MBkju9adNLgN/P4AMxIbECn5aDRE/7MpP1NMzCGqG1IeqqqgRZhsJ9vXJrPZjCZNmhz1kZKSgkQR9W89acQtfS5+++031efi+eefV0GMX3/9VWVbPP3007VzpERERESUEKUMpIxBZZPno/q1hM1iwHMTFsEfqHyWfd7KPEz4ebXK4iAiIooFs9WI1FQz/ly/H29PXI5nJyzC618tw6K1e5GWZlF9miSLra5I/wGzQYd7LxsEQxU9HAZ2y8YlY7upUorUsEqKWc0G5GSnRrXfMd2bqf5XRFT7jbjluSUa0gND9qsPhYWFuO+++zBixAh0795dVVKS/3a5yj+eLVu24B//+Af69++Pvn37qr+vXbv28OvFxcW4//77MXjwYLWNlJlavnx53Qculi1bhhtuuEFFaErLzs7G9ddfj9mzZ9f4oChxhG/mpCxB8o5Nk5Rjq8sbcSIialjcnkClr48d2hbfz9oc8Yqkn+ZsURkX1WnIWdfktoHXWCKi+GVLMWHHPgf++dQU3P/WbPy+aIfK/Ju5bBeem7AYlz7yCxasyoMt1Ryz3+fydSSTo7Kv53J60DknAy/eNAqDezQ/alvp/3Tl6T1w96UD4XR44PNVfq2Nljz3VnWMDW0OQqfTqExSY4SZMNF8vyvar6I5CFkQ4nb7VBnNSDVvbEPX3Cx43AxyEdW2JWv3qeznaEjPi8qy1GvTXXfdhVWrVuHVV1/FL7/8grvvvhsTJ07E559/Xu72t9xyi5r7/+qrr/Dll19Cq9WqOEA4I+yqq67C9u3bVUWmL774An369MEFF1yg3qMm9NVpzC1RlPIEAgGVhkLJTSYNDAY9zBaDSjmUSYeMDBvsDi8C/kBC16CWGwW5MTEYDWqli9cfQEaGFQ6XF0F/UN0oJCq59zGbDdDqdWqlhjTzlF8uFqsJPp9f3czIfxMREdWEXEoaZ1RcN7VV0xS0aZ6G3xduj/hrOt1+TF+yE4O7Z8Pv9yIeyaSG2QCYrFYE/T6EggFkpJnhdnvh9gZZzoOIKA5YU0zYkleMe9+YrXoslafI4cULny7Bdb4gRvZtCUexu0bPlnqDXpXrkedmo0EHp/QpCATUs2Xpxy/5u8PuQaNUI279ez94fAGs3ZqvnkmbZlrRvmU6XG4f7MXumF5TjEY9dAYtUuS50B9Qxx0KyiIEH7wev1rpX98kCCDHaTLr1WSZHKeag3DKc3pAZazEkmTjhDTSS8Sgvm/qnIRCCPiD8Hp9cJcTCJDnbZPJAJ08b1tKnrelNKZ8//xevzrG8iY1j/w5Cc9BON0+NbbSPyeSZSO9UH6YtRlb88qflyt9PFee1kP9zPA5n6j2OT3Vmy+U55zaMmnSJBWUKE2yId59910MGzYMAwcOROfOndXnpQH3f//7X6xbt67cr7Vt2zYMHToULVu2hMFgwBNPPIFNmzYhGAyqRt5Lly7F3LlzkZGRcTjQsXjxYtUjW6o31Vng4rrrrsNzzz2HnJwc9OvX7/Dn5WBffvnlw9EWSk4WiwEms0GtSvl+5iZs3lWkPp+RasKJg3IwfkQ7tYJFmmgm2sVRJvWtViMWr92Lb6dvwp8b9qkbBLNRh5F9W6mao43TLWp1SzzcvEVDVqlK3dateUWYOG0jZv+5W92o67QalWp8+sj26NwmSzV383pju3KHiIgaFlnAINcWaRwqzUaP1Cjdgv0FrnJfq8yW3YU4pls24o1MDKTZ9NAGfSha8CPylv6GgD1fvWZs2gap/U9Bes9RcHsDqoE2ERHVPVnBLs+pEjiQ3kkVBS1Ke+PrPzG4Z3MVmI72GUkm2eX9Vm06gInTN5b0cgqG1OK4Yb1a4IxR7dE6OxUO+9FBCJfLB7h86n27tZEJoJJJ84ICZ9Sreas6J/KM6PYF8M3UDfhtwTYU2ksWB7RvlY7xw9up52CZOHe7vPX6nC69R2Yt24VJMzZh7baSa2yq1YAxA3Jw+qh2SEk1q+f0mp4fvV4Hi82oJhK/m77xqHMi2Q6j+7aG0WRAUanyLrK4U85l3kGnet6esXQnPN4AJIGiT6emOH1kO/Tq2EQdY+kgS/jnZOWmA6oxe/jnxCg/J71Lfk5aNf3r50Q+PG4fnvi/YbjvzdmH52OOJM/5N57fFz07NIKj2FOjc0JEkbGaDNXbz1x75XDHjBmD2267rcznwgkHf//73zF16lR88803qgzUhg0bsGPHDrRr167cr3XzzTerYMUnn3yCQYMGqRJT48aNU8HklStXquvUscceW2Yfr9cLj6dmv4OiPjuSNiJveuGFF6pojKSJ5Ofnq0FKlOXtt99WH+ELofTCoORgsRjh9AVw08tTVcPM0gqKPfhiynp8M20j7rhoAHp3bKwurokSu5CbIYNJry7+KzYdKPOaTDRMnrdVfVxwYmf8bUxH2ItdqvllIpCbKFuKGW9+vQz/z95ZgMdVZn38Py7xNlZL2qbu7kZbSila3GXx3WVxX3aBZQ1YZFmWZVkcdpEPKZRiLdTd3VJJU0nSNjpu33NOOiGee6fJZGZyfjzzpCT3ztz73jv3Pe+R//l+VV6dsrSVW4/xa9zADrj/muGksCrBC0EQBCFkaFFN8hXTRnbB3KX7m/GdI1O6IineAHf+NhR++hwCtapB3IUHceKbf6F02afIvOZJxFsTUSHBC0EQhLAHmMk5TEFzylI/WaasgoIcyHOX7MOFk7oDKtZH5Iy2xhnx53fWsH55dSh7f+H6fH6dM74bbjq/f4MVFJVrMl+LjsnaHYV4/n91+03l5pfixQ834OP5u9lJTgmMHFBpJoLyj+QzImcXnWt9yYGk8uCHBnc9vxB5tSoMyu0edvZ/tXQffn3pYEwc3InHMtQESp0OfN1Io/6F/62vd0xe+nAjPpm/h8ckMcnCwQuqBqHAyQff7sKnP9VstEtxFEqMpNfgnml4/KbR/HsKXvB9YjXiT2+txpodBTX2c3v9nCxKLwqW/OK8n+8TCiSR/+L5uyfz/UVjsPPASf6s5HgTpo/KwvkTu8NE1T0VrqhLKBWEaGVo7zQOGpKfTSm0/ZBeNVsxNCdxcXHIzs6u83vy3992223Ys2cPBx9mzZrFfS6oR0VDUBxg5syZWLRoEVasWIG///3vePXVVzlOQO9HDb8/++yzOvsZjcbwBi4oWEGv6nTp0gWDBg06rQMRIhvK9tDotHj4xUUoKm64cQwZYn95dw2evn0cumYkwNGKmRlKodJMMhjqC1rU5n/f7+JmotNHdOFsiWiApKDe+mpbnaBFbZZvOYqXPtyAuy4fCre7ZmBKEARBENTg9fhw/Tn9sGXv8TpSBuQ4Iikpyi5SUxrdvWNixIUu4ix6eI/noeCTZwB/w+fiLSvC0fd+i863vMCOimiW1RQEQYg2zGYjZ+m3SzRzwEANtP3VM/vAYXcrDwjEmfDM+2vrBC1qQ3I/VJ142TRKjAtNjipUzBYjduYV47kP1rLDuyGOHLfh4VeW4u/3nQHDqcSE0/pcc6WUkkarwZbc47A5PEiKM2Fgj1S43F74PD9LT1Ngg6SX7n5hEQ4VlDcaYHr5442ItxgwsHt7xdeqNtY4C7btO4m/fbCuyTF55JVl+Pv9UxAfb0IAGny+cG+doEVtNu0pwh/fXIXf3TyGx5EqNJ55b22doEVtKAmE7pNLp/58n1DwguSeB3VvjxF9M7iSiAI/FESpIIUIr58TSQVBCB9UVT6qfyZWbDmqeB/anvYLNzt27MDixYu5F8XgwYP5dx6Ph+WgyMdfmxMnTuCVV17BrbfeiosuuohfBQUFmDRpElavXo1evXqhoqKC36NHjx5V+1Gz7z59+uCaa64JX+Diz3/+Mx+MzWbjagsq+3jvvfdw9OhRzJgxg8tFhNiDjAuK5DcWtAhC0cU3vtyGZ+6cwLrOkR7gJz1JMiKaCloE+e93O3H22K5sSEW6XjU5RxxuL75etk/R9os2HMYVZ/ZGktUQ1f08BEEQhNaFnA7klHjmzon423/Xc5PToD1wuKgC+4+U4ozhXdhpo4Q4sx4Th3ZCucIs2XBhNutxdMHbjQYtgvjKT6JkxReIH3MR3JGf1yEIghATcJ8/i4HXp0/cMhYlFeqSz2h7qgqg91GyriVHe15BmWLH1ReL9uKiKT24AqG5m2031fvwjTlbG3XQBzl2wo6vl+7DzDHZp3WMJPfk9gX4c5eSlFK196KgA1VqXj2zL7Q6DZwODwxGPeavzms0aBGErs2bX23Dvx6axlJKaiWjqNqCZLze+ErZmBw9YeNqHJLKpu0/nt940CLIht1FXB3Ro1MS8o6VYeVWZfcJBUZq3yekAEGJovQKNvWm6opI978IQixz6bSeWLujgJO6m4Ik4Wj71iA1NRV6vR7ffPMN2rVrh5KSEvzrX/9CUVER+/lrk5SUhIULF3Jg47777quqrqBeFwMGDOC+F3379mU5qcceewwdOnRgSSna5o033jitY9Wq3WHTpk2sWUUNO4g//vGP3PPiyy+/xA033IAFCxac1gEJkQdNghazAd+tPKh4n735JThSZGPDLdIhg4h0R5VC2aGUeUMNyiMdnV6LrxbvU2R8BaGx0OpUPxqEVoaMWLPVCEucibN36N+0IKGFiSAIQmtAjgNqRvngNcPx5m9nsNTimAEdMG5QB5RWuHDRGT3YYFfCrHHdWCs6knpMUdDCW1oEV/4uxfuUb1oAo8kInU4ezoIgCOGA7OEDR0px4GgZXB4vNz9WA8ntEEqdwZTwRz0OlEJyRPOW74fu1OeEa0wogaCp5s7VmbfiAMtFBR3kaqF9y+we3PW3hViwJq9G0IKocJDs0z7c++IiaLRaDjaRD2KuwgSHYICFkhEpMVEtiYlW5B4urSNH1RjfrDjAUaAfVh2scz6NQedJzS9IZlvdfXIA+gbuEwrU0EuCFoLQuvTskoIHrhnBgdDGoL/ff80I3r41yMjI4IbZ1OOCZKLuuusu/h359bdu3VpnewpyvP7669zPgrY555xzsHz5cm4VQT2wdTod3nzzTQ5i3H333Tj//POxZs0a/OMf/8DYsWNP61hVP9FffPFF5OTk4LLLLoPD4cCcOXNw5ZVX4ne/+x2/KEIzbdq00zooIbKgygLqaaFUCzQIaUOeM7aullokQYaXyUgVF8dV7bduZwHGDshENDizN+4pUrXPxt1FsFxsiBoprLYOl1BbKjUDqQ8LNXaj6H5asoUdfZ0zEriZnlTQCILQGpCGM73IiXDRlBzOWkWgMiOQnl+P3DAKf3xrdaNNUscO7IArz+oTdhmNpiA5Bvuetar28dvL4D5xFDpTKnw+kYsSBEFocTQarN5eKcWz73AphvZKx2YVa7+hvdNhV2FHWy0GXk+pgbLwqSdBa4yJUkh54USpE0adFn6/T/V8SdJUv3lxcZMVL/mFFXj6rdX4w23jYHN6FVVbVGfN9gJ075AItVBggKpD1VBY7GAFBupfoYaNuwthNuqx91CJqv027C7kfheCIEQ2tHb5668n4JMFe1gysHrPC+ppQfJQVGnR0kGL9957r9G/n3feefyqzSOPPMI/R48ejV27fk7QolhAsKd1fVDlBqk0NTf6UCouXnjhBda8osbb1Kj7ggsu4L9RlIYqL4TYgpwM7hBKQmmfaAj4U/am2lJSt8cPbRSkslNgRk32B0Hbh5pJI4Q/MEWN10m+7MvFudzErTrfrjyInl2S8cj1I7k0O1S9V0EQhNOFghe1MRi0GNQjFc/fPYmfY+REqT4fd0yNYwmGs8Z0hd1GDSnDI6GhFA3JMdRqxq0E2kdjbpFDEgRBEGpBGejB9dA3yw/goetG8JyjRMaDmD05B36F809weah27ewO8/qLxiSU9T1JFIVSzUDyxSs2H1EkO01QItbhonKkhqD7Hsp5Ef5AAC6P+qpOuubkGwjlGAMIwQfRBtfpdM7BJu5q/TaC0FpQUOLRG0bhRKmDg9mk3EL9/agRd2v0tIhmVM86VBZiMpn430uWLEFiYmJVY27qfWE2y0os1qDJITG+8pqroV2SOeKaaNaGJj/KAKGG29QYTCnJCSY2biIdygBJSTCrKnlNSTA1mvkqRAZkvJEk1D8/3cTarw2x51AJ7n1xMV68dzLLmjhVNMIVBEFoSWgapWaSGclm3HfVcDjdXuw+VMKOkYx2cejWMREOpwflZY6IkogKEtBooEtop3o/XVwi2x+CIAhCy0N+3nYJlT6KzXuPo6TcxdKF//t+l6Ks2ezMRJSU2BR9Fj3aae2cnGCGzVmh+BiT403cryCcY0JrPrUkxBnhDyEwYDLrVUk+EV8u3oebLxjATms1zmpap4eSX0hZ0KGMCV3zlER1+9H9QSiVy/x5v/DeJ62ujGHSQ2/Qs7wbBRrJZrQ7PPD7fKwmIKaUEA1QkGLayKzWPoyoRrWQPelVffLJJ9i4cSO+/fZbTJkyhR1o1GGc9K7o70JsQQ4EapbVp6vyMia9TovJQzuHrcFYqNBkZ7O7MWVYZ1X7zRidzZmWkQ45eqjJmRqmjugiskJRAGUubd9/otGgRRAqyX7pow0wRkHPGUEQ2mY1BgUnNH4/+mUlY3BOKgcziovtXCkWiUELwu32Ia7PWGj0lXJ9SjB1yIEuLiXi7SNBEIRYgar1zhjemR3TxLPvr8MFk3Iwe0qPRvcbMyATD1wzHDabS5WD1O5w8+ep4czRWfCHca6jMZk6vEvVmCiBKiRNBn1I85dBr1OVSEfkFZTz8Y3om6F4HwpY0Do9lLEM+AO8DlZT0TCoZyo7088cpc4pSfcHyY+NH9RJ1X70OQF/ZNpEzb3OTUqyIvdIGf763lpc+MCXuPjhubjooa/w6mebUVjqRGKSlSVHBUGIfVR/0x944AFuwHHFFVdw84077riDf3/uuefiwIED3IRDiD3cbi8umJhTo5HMhMEdWZftihm9MXNsV84UCTJ+cEc2HKJhYe7z+nDhZNLdVrZ9l4wE9OqSHBWZ626XFxMHd0KCVZnDmrI+yNjzRsF1a+tQ43U1jf+oPLHM7g6pvFsQBCFcgQCHwwPHqb48kV6VQDYOJYHG95+geJ/EkefC6ZIsQUEQhHDOLbR2HX2qPyE16X7sX8t4/ffiPZMxY3QWLKfsY0q+GzOgA/78y/F46LqRsNvcvA5WA62jzhnfDVkZ8Sx3eOWM3rj4jB4Y2jut3vUmZfmP6pcJl8sT3jEx6DC6v/KejRTs8bhDP0a1VRDB7c9T0dOBJFgSrMqTCapTXu7kzH5VYzIxhwMJAynhop1V0T4UF6H7IuDz832i1ykbmHaJZozsmwFXjCcYUtCCJI7/+PZq/Pa1FVi7o4BtLYKqLhauz8ddzy/CW3O3IT7BLMELQWgDqPZg9e/fHz/88ANyc3PRs2dPWK2VD+gnnngCw4YNQ1paWkscp9DK0ARJxt70kVnolB7P0f5yuwd7DhVz6ebgHqm49cIBWL7lKH5aewi3zx4Ir0ojrzUzPZMTLbjhnH54a+72Rrclo/aha0dwJk2kO1QIylIlBwkd8+9fX1mjKVB9xuE9Vw7j84qGgFNbh753ahrB0e26YPUhnDu+a4selyAIQlvC4QbanXkjnId2wnPySKPbWnuPRlzfsSgpk35DgiAI4cTj9uJXlwxmCVXqs5CbX4rb/jwfk4d1xrkTuuPOy4ayU5QCHMXlTk76KisNXaaQKgVeuu8MbNhVyJXPJoOOHf9Otw9fL9uPuUv38bqMAiUPU4DE6Qm7dr/H5cGvLh2MPfmVY9IYZwzvgqG90lBWpqxHRX09HbIyE7l3hVKyMhJ5jLp3SsKscV0xb/mBRrenANCvLh6MrfuOc5JhKGgRwK8vHYy9CsaEqjOocbutwskJZXQdH35laZP9JW+dPRBWkx4V5U7uVfjrS4fgxQ83NLpP1X1CMkkx3OOB/BFxcSb85d01HLBojLlL97Nv5tKpPXksBUGIXUJKvY2Pj8fgwYNr/O6ss85qrmMSIhCaIEmu4faLBmJ3XgmeeW8ta4RWJ9hE87EbR8Pj8cJRTyPOSIWaflLGg9VswLvztnNQpjZZmQl48JoRSE0yw25zIVpwOtzcGOgPt4/DSx9uQMFJe70ZHL+8eBCXANsqoufc2jIVDvUZu8UV6krdBUEQhKaTH3RaPTre+BcUfv48HPs21tlGozMgYeh0tJt2A8ptkSt9JQiCEMvParPFiBfunoy/vrsWW3KPcxDhu5UH+ZUYZ2TH98QhnXDRGZWO0FCe1dTLwWw24qP5u/H9yoMctAhCmfVUzUEVGFR98daX2/Cry4ZwZYa9FdZf9Y1JbSjgcu7Ebrj6rL7soA/VaU7STeeO76YqcMGKCAD+8OYqPHnLWO65+cXCvXzdakOS1tQra3PucfZV9OwcWuCitNSJhEQznr9rMv763hpszT1R/5hM6IZrzu7LATFK+KNXh/ZW/PXOCXju/XXIL6zb34TusV+c15+VKWynHO0OuwvjB3Xk93ztiy3cf6U2HdrH4d6rhyErPT7m1+lms4ErolZtO6Zo+88X7sVFU3pw9ZAkXgpC7CKaIYJiDEY9lm8+ihc/XF9VrledI8dteO3zLdh54CTuumIY9HoPN4dujsg7TWLUBFOr0YA/mqoC3D7W52wOqMkVGagkf0VVJUs3HcaaHQVwuX3cBOvMUdnI6ZzE8hXRFLQgyFFNgZmuGQl47eFpbJRSiWWF3QOrWY8JgztheJ90boBKxlA0VJIIlQ1t1UJGsSAIkQXJt2l0Wu4XRpmeXl+A5z16FKuQWY55dDoNjEYDGwUaLSVUgHtNkbRGa2cf2h1e+M16pF/yEPy2UpStnQdPyTFoNDqYOvZAwtAZCECLsgp3vQtruvZms77SztFqKgPMfqp+9DaLHRWNyJgIgqBUVkarr5xDCVrHkAQPOeXrS+aiwMITt4zB8RIH5i3fj4KTDg4o9O3aDmeOzuY+BxXljnqfM8FmwVXPJd4kwNK8FOSgv5lMBs66p8qO2tD8vnTTEazbWYg/3DYOf7tnMu/b3EGL4JjQMVIiocFkgE7nUzQmVA1SWFw5Jn26tmMJ4cbGRCkBDTB6QAeWU6ovia42lEyXnmKFz+/HzgPFPKa/uWwoLpyUgx/XHsL2Ayf4eFKTLZg2IgsdUuPYif3xgt04f2JlwCNUyssqgxdP3TqWx2JerTE5i8aEFSncsFdLdiQfQXqSBf+4/wzszivG/DV5KK1ww3xKfmrsoI4sNU1Bi6DdQj/JBzGkZyrefnwGO+xXbDnK140aoVMfkn7d2nGlRawHLQitXocvFu1VvD19p6gS5+yx2TXsKwpk6GndSzYjmw8BtiHIZhRXR8tDj2N6FtJCJui/o2ez71SQTxDUIoELQREWiwEFxXa8+NGGeoMW1Vm04TCXgs4amw2v9/TkEMwWAywWI/YdLsV3Kw/gRKmTm3uRMUNyVTTZk8HVHNmLXFVic8Ht9GBEn3R+6fQ6+MhIC/hRUmyL2omOjpvGye3yoEfHJOR0SuJJRKvTIuDzoaTE3uqOH0Ed8RYDOqfH15vR0xBj+mfiVOhPEIRWhh0cZiPKbC4cLSxDn+x22HuohBe6NNdRcHJQj/bsSDFbTXA7SWfb1zYd2GQLmA28oF+y6TAHCuKtBs6MJb1nCrzTHNeaczQ5I+hlMsUjfuyl0GoD0Gm1oPVZuZMc7vVrUtO5WS1G7DpYjO9X56G4rFJjm7JxyRnj8frgYjun7Ty7g2Oy8+BJ/MBj4uIxGdY7naU52uKYCIJQ1zlPzwqb04svF+Vi/5Ey/n1n6isxoTs37iXHcm1nvcvp5Ve8SY/Lp/fiOUan03JFgNPubjApjioTrBYDtu47gQVrDqG0wsUO6ZH9MjF5WCeen0ku6IX/bag3aFEdcko/8foKvPHbM7nXYnPaFUazgefIOQtzOXO9ckwSuE+EkjG54szKMQkmsjU2JmqwmAy8lqcAyWOvLsfJsoalfbJJ5eDaEfhmxX7MHNOVVQ/o+t7z4iL0ykrBzLHZHJww6LQot7vx7coDWLQ+v6oSg5qqU0AJpxm8INKSLLh6Zp9T9kWAg0F0zez2+n0cZIuQxHaXtDiWoQ6OpSaABqXH6O+kbEHr9EHd27Ofg+5J3tbvR3Gxvc0kFpL6xcY9Rar2oT6OVAFDUL8Lk6Wyx8n3qw5yxYzX50dasgVnj+vK8mPBPmpCy0AJx/RsPlxYwUGlwmI7S51RcJj64prMBv6eSBKKoAYJXAiKo9//t2CPYuf2V0v3cRMymoBDXVhSU6ZyhweP/msFG15U+ZBoNcLt9WHdzgK88/V2XHRGD24QTpkKzfXwIyOBjAea+OLjTCi222LmwcrBGRLkPjWxp6TEobjY1WxBCzLmggaaBEJaFqfLy0bavz7bomh7CnL0zk5h41cQhNaFshsNRgOe/WBtVabgvS8uwsFj5TW2W7n1KN6Zt4Pn00umkjPBVW/GZHNlR9EzHNDA7/dHRKCe5pO4eBM27TmOVz7dVEdCYfGGwyx1eOdlg9G/W/uIqBqk6+OqmmMtsBc3bENY40w4XurEg68sqxOEpozLt77azpIiJGUZqmxJtNHUmLz51bY2NyaCINQf+H/xo/VYvulIjaQ6qpj/YlEuBxTuv3o4TWnslK9NcC7l9R6vhxp/VpOywDPvr8WxEzXtaOrv+J85W/DgdSPQtUMSVmypv9cRfU7Pzkksd0QBapIzIsfqdArGNkMGctNjslfxmDQ3wSbb1Ez55vMH4rm7JuHj+bs52FBdWjop3sgqBxdP7cnVE9Qf5Oyx3Xi988//28zbUCUDvRqC7ClykDbXeqe0VH1PDw5EONQ7xslnQut0JfdkLBK8T9wev+r+KZSQSVUWZDN+8N1OfLV4H9y1xu7blQfRo3MyHrlhJKxWI/t7hOaFEo5dPj+eeGVZne8pJR+9/+1Oloy77hySnnO1meoLb9kJOPZvgt/tgNZogaXbYOgT27f2YUUVErgQmoQmT2LZ5qOK9yHnwprtBRjYvV2DGQlNRWornF489I+lGNIrjRuHUTaq3emF0aBlCacFa/LwzYoDrBd943n9OYuhtR0WbbkUkKpTKBOJjAeKqlNGJOl+khEsQYzmh7J9yLj/ZvmBOs7O2pAv8qbzB3BWsnxHBKF1MRp1/Mx84OUlLNVH/aEeemUpbA0scmm+++93u1je7/pz+rFUDskkNeccT1KQVFlJjwd6RtAz3GZ383OmNas8KIGBJDXIWdTQo4uyNv/wxio8esMo9O/enisnowGyc8hBf//fF9er102QQ4cc9dS0lRw55SE4UKIJytBTOib0k5JXYn1MBEGoiV6v47mBsvZ3HDhZ7zY0X6zedgwP/WMJnr1zEksdhTqXUaXF4eM2PPLK0jqO0CBU9UHOVmq4XXvJ071jEn5xfn9OHqJKSnJEkyyk3eXF7oPFXF12uhWD5LAlh+Fj/2p6TEhy6ZlfT4TfR5WA4ZnfWaXHH0ByvBkvfbSBK+eoKubGc/uxhDHLIlmNGJiTiu37T+K599fy3D+yXwYHpynBY96yA1UVJI2tSW+W9U7UUqnmFOBkVTW9Uml7khSjAOM/P92M+avzGtyWmq5TotCL90xhO0wqL5oPGk+PP4B7X1zcYEUVVb98sTiX+27edfkQ9t/Fsp/IdWQvipd/BvuetdTo5+c/aHWw9hyBlHEXsaSs0DQSuBCaRKvVoqjEwQ8aNew7UooB3duF9JlUQvbKZ1vwp1+OZwcNaZD+/t8rOHBBkPE3a1w3vHjvFHz4/S6Wkuqcag0pu0E4PYcXGQlHj9vw+aJcLN14mI16MhyH9EzDBZNyMLhXGmt+tlQWT1uFDHkqRabvCC3eGjLmSY/17iuGoX+3dtxUTxCE1kVn0HMggrI2KYvw8ddWNBi0qM6XS/Zh8rDOyM6IR1kjEgtqIOcPaQAvWJ2Hucv2V2W4UxXDWWOy+fisBj03jwy3D4CcUyRn+OKHG5r8bFrz/O2/6/H+kzPhoT4hEZ6hSHMkjf0zry5v0EFfnQ9/2I1JQzsj2Rq7i2yqriEH3sP/VDYm//t+F0uFxfKYCIJQF4ORNPBzG3TQV4fkhf73/U5cMrUnEELggqoQrVYDnnlpbYNBiyCpSRYsKKjpML3xvH4sabQ19zg3v16/s4DnK0oOGD+oAy6YnMMOV3L4nc4alubxzxWOCa2ZeUzO6BnWbGe7w40zhnfmjGvqUUEvkn3qnZXCUoAUyPnPnK01Ku0qZaGpX4kPf7pjPH772nI+/vrQaTW464qhGJhTWX0pRCeU8HrG8C7473c7Fe9D94lOo8H2/ScaDVoEob4jf/9oAx67cZTYD80IJUG98P7aRmXgglC11aQhndAvOzlm/Xe2natQ+MULCPjqOT+/D/Zdq+DYux7ps+9BXO/RLXIMDz/8MD7//PNGt9m1axeiAQlcCIrQnEa5X+3fUaZppRzFKedrLYd2ZRaiAzddMAArNh/BG19urZO9QlrQ9KKy1yduGYvNe4tYDxOIzQdfJELam/HxZjZAP1tYs4kWOZk27C7i1+CeaXj8F5UPYwleNC9kbNH35YV7JnMW1ZzFudh5sJgzF1K4qXwWzp3YHSa9joNHknwkCK3/3DQb9fhh9UEOQhwusjUqeVAbctb85rIhzXIs5Dgvsbnr1Zqm/yfHMD3bH7thFHpnJYfdEUDOqR9WHYRLoWOFsvPIETJhUIfT7q/V0pAdlJtfgryCxqvlqkP2zi/O649YhRpxky68ujHJxS/O69eixyUIQuRA60eqDqRqY6VQn5xrZvblHoZqpeXoWb15z3FFzaQr+Xnxe/2sflxV8Ke3V7MKQXUoGZB6QtJr1riuuOWCgWy7h7JOqhqTFfvVjwlLOocn0O/1+DBrfDd8+MMubqjclOwTrWNG9cus6sNI652/3TWJ1zuUyEFBmuB6Z/rILJxH6x1DcL0jC55ohSp9SQry4/k/3yeNQYk2I/pmcMIK2QRKoT4aZTY3S6yJf6J5eg6RHb5uR81nXWOQ32LwTWNiMnBBlRYNBi2qQX8v/PwFdLzu6RapvHjsscdw3333Vf3/hAkT8Oijj2LWrFmINio1gAShESjTIT3FymWtasjplFxlvlUaVUYkp8ShqMyFtbsKsXZXEcqdXiSnWPlvwWAGRTeonHfzniK8Pqdu0KJ2Jg1VYozp34Gz/8kpJIQHKp0mp1btoEVtNu0pwh/fWsWVGZRRKTR/8KKs1M7N3P5w2zjMefZ8fPHs+Xj3iZmYPbkHtP4AV1rEchmmIESTTNSmvUUot3swvE86ZxypgbSzWdrJcHpzHS3UKHn0kVeWNZoZRTJVf3hzFY4ct7NjJJyYjHr8tE7d+Py07hBnnkY8Wo2irMDqkIMrrrqtFGMEoOHG9GpYvCE/psdEEIS6zrHc/FJWAlAKOSdp3qX5VzUa5c8lSrqjJtJEWrIZF07JwTPvrasTtKgNNa9979sdrDYQ6pjsPVSC4yVOVWOyOdQxCRGq7qCseEq+aGo5SBUpj1w/imUSg+uX6uudp24dW2O9c9GUHGgDst6JBcgHpNdq8OtLm07SId/UI9eP5L6PFH5bv6tQ8edQbIsCeFTZK5w+Or0WC9YeatRvV5vNe49z71qqsI41SB6qqaBFENqOtm8JEhISkJaWVvVq6HfRgHxThSahCDYZAaTFrRSKfpNThowMcrIkJFqwemch7n5+Ie56fiGe+2A9nvtgHW7/64/sONmRV4y4eDMHHsiY6ZyRgPe+2aHos0giZ9GGfHhOSRQJLQ9pqWq0GnyyYI+i7anyYtfBk5xRKTQ/wWZupSV2nDhRgZJiG44fL2d5F7dbskgEIVKg4O3J0krnQrzFgFKVVQyUfUYLNJJwPB20eh0+XrAbJQo+n+bWt77exs3Ewz3PqB0f6q9liIJFKN0HSsa+dhCJekjFagIA2RS1m683hTPGx0QQhJrQV50aW6uF5t1QnhMUFFX6rKbei2eNzj7VV24gr09XblXWH/LLxbksRUWyVGqh8ypW+ewkTpa5wv7spHXJ2IEd8dC1I7hSoqHm2n/+1XhkZ8bDWatPZvX1DlVikDxUSYmNmyzLeid2oPtk/KDK+4T6VzR4n/xyPLIy4rmnJkmuqi20IRtT4lzNA429WhuOqLC7cZpLmohsxG3fvUbVPtQDg/YLN5999hnOPPNMPP300xg+fDh++ctfYtWqVejduzfy839OHqv9O6pqe/311zFt2jQMHjwYF1xwAb788ssWPVbxIgqKy/YundYTSzbmKyrbu2BSd26MRfYQBSTenrsdXy3dV++2u/KK8dQbq1gC4eyxXRFAAGt3FODEKeeOEihbZdrILDiVVvIKp4XOoMP3KiQ8iC8W7cO9Vw0DYrAcMJKQTCNBiGwspkrTi56fpOusFoNeB6cn9AU6JQjQ5/6oIrudpDJogWcOY0k9yVeoHR/a3hcFz0Ay+KmiRA1kT1EWaqxKYNB5mVVe71gfE0EQakJfdZqH1GIJMXGKGgWT/JASVm8vwK2zB3HvnSG90vCvzzYr/hxaW3+9bD/On9hdtexx5bMzhDEx6cIuIUtrlIpyJwb3SMVbj8/A6u3HsGLL0arm3NS0u2/XdrA7PE3KUwaf+/L4jz2C98mQnql4W8F9Qhn7xhAqkclmlLSH5oHl4ENY0xgN9ByKrS+xY/8mIKBSgs/vg+PAZiQMOgPhJi8vD4WFhfjiiy/gdDpx8mTTvZJeeOEFzJ07F7/73e/QvXt3rFmzBk888QTKy8tx9dVXt8hxxlh8S2gpqHKifaIZ9109nLMbGmPaKZ1Jt8sLo8nA1RANBS2q8+ZX2ziIQd/zDSpK/Qhq1CUVF+FDq9GovkYkGUUOO7lGgiC0VbxeHwb1TON5lOQuhvZKV7U/NbGkDFAqpQ8VqoKkTFCbU10AYt3OAt43XNACVe34DOudDvdpBHXCRgAY2TdD1S6DeqTB4/XFbHBaEwDrVKuBemjF8pgIglB3Du2dXdnMWSk03w7ukcb7qiYQUPxcoufQf+ZsYYmbOIuB1z1q2Li7iNdXaqHz6hPCmAwKdUxOE3JSUoUEVUwM7N4et1wwAHddNhQ3ntsPXTPiUVxsh9MR2X2qhDDfJ90av098Ph+sFgOyMiql2pQyun8mNGSQCadPIMDjqQaqmkmON7G6SyzhdztC288V2n7NAVVadOnSBT179mxyW7vdjrfffpt7ZUyZMgVZWVm4+OKLccMNN+CNN95ASyGBC0Ex1OxqWK90PHPnRDbiascvqDk26Vb+8uJBHP0mA85iNuCznxrvgVAdkh4KaCozUdVCgQshfJIOaq9RcHuRdBAEoa1CAQeDToPRAzLx3coDGNU/g6UVlUJJAVQBWR8U0KBqiqb0/ukZTLJDaiFZnnDi9/pw4eQcxdvTafP4eCLfFiBZA5JBSFAhC0KVrLRfrEIyHyRJKmMiCEJDkIOLqvEmD1UuXzxmQAfodaEF/MmpOW1EluJqsOWbj+JkeaXziWTs1EDbh9Kvh8fE78ekIerHhPpOtBbkJyDHNMlBkTQQ/2S5H3EkC7XuE0fj9wn9k5Jsz5nQTfH7dkqLR5/sdnCqTOIR6ofGv3unJPYHKmXWuG6s0BJr33mt0RLafqbQ9msOunbtqnjbvXv3wuVycdPvoUOHVr1IOurw4cNctdESiFSUoBh6qNhtTnRsZ2HNQbvLi9z8EpZlyGxvRef0BDgdHlSUO1iD0mw2IPdwKfILKxR/BjUKC/gDSElQ7sghyPiiktdyl8gQhcuIUONsIyiiHtxXEAShreL1+HD9rH64+4VF3EjwhnP64fn/rW9yv15ZKRg/uCOXz1cPQlDvIJ1ex9JDlH1OUlLkAPF6vLwgq70g8IcwxxKpSZawSjKQJFVSkhVnjcnGdysPNrn9OeO7c5ZreWnrZSwphRxvTrcXN5zTHy9/srHJ7Qd0b4+hvdNZ1ztWCY7J9ef0wz8+2dTk9gNy2mNIr9geE0EQ6uL3+nHVWX2wcusxbjLdGFTpfd2svjzvhvRZoP4RTlw5ozfemru9ye2pv2P7JCtLTKUkmmFzKl8Dc+axzx/ymFw9sw9WbWt6TKxmPa4/J/QxEYRIhJIYpo/Mwrxl+3HwWHmj21J88OYL+sek07y1oGGkgNItFw7E7/69okl/T+f0eJw9Nhv2Jp5X0Yil22BAq2P5J8VodbB0HYTWwmxufF1IVU1Bgt+ZF198kWWiamM0GlvgCKXiQgjxoVRe5oAu4Ef/rimctZGWaOaGwBQRp6AFodNpWMJJ7fufLHNixuhsVftRo69gFo4QBvwBnDkqS9UupEdZYVPftEkQBCHWspKS4oz44+3j8M7c7ejfvT3uuGhQo5mWJBH1h9vGclZ6MEOSmlcnJVuQf9yOlz7aiIse+gqXPPI1Zj/0FZ77YB0OFFQgKdkKY61MUY/Hi4z2VlVZUeT8oSqRcDe/pOy622YP4vmjMWaOycaN5/WHI4rmGJfDjcnDOuGm8/s3KqFIDvrf3zKGM1NjPfBPYzJlWOcmx2RgTip+fzONSWV1ryAIbWsONem13Ji3oQbPBFVv/fGOcTzf0j6hQPPyRz/swvRR2Ry8aCpo8eC1I/H3Dzdw8gA9y9QwfVRWHTWDlhiTp28fh0Rr6GMiCJEI+YFcTg/+/MsJnPnfWLLrvVcNR/9u7UWSrJlxOd3o1SWZE5yp/1hDZGUm8HWiNUVryNW1NPrE9rD2HKFqH9qe9osEDIbKyueKip8D7wcOHKj6NwUr9Ho9jhw5guzs7KrXokWLWCpK20Ld1qXiQggZKrmlBaPVauIHT30B61BUgagBaO/sdpxhuHXfCUX7zJ6S06B8RihYLAYYTzU6i4szwW53KyqnNZn0LNVB0NhQxmhTkXxuZmQyVDmtKPiipPkpbU+fF5Reogf/6eieq8Hl8rDjIKOdFQUn7YqOlRrOkaYqHa9kNwiC0NalFzu0t+Jvd0/G0o2Hue/Fvx6ahm9W7MePaw+htMKNvt3ascOenrW0LT3fy081q6SgRXy8Gf/4v41YsOZQjfemuYeyLulFckT3XT0MgYCrag7jknqHh2WVlGS2E2eM6ML719ahpec5zUNq5y+l0GfaKpz49aWDcd6E7vhi0V7Osg02Nh83sCNmT85Bp/R43i6adHLpOtExU0UJnccXi3OxcN0hlNs9PFdSc9cLJuVgUI9U2EkeoQ3IGagZE5vNFbZG8YIghAdaewV7KdHzgNaX9QUnKZDbLsGE1x89Ez+uzcPcZftxqKAyy7pjajxmjeuKM0dn89qQ5tvT4USZE4/8cyl+f9MYnlPnLd+PRRsOw+bwsBN0WJ8MnDO+G/p3a4cXP9qAFZuP4oFrR/DvPvxht6IqCgo2kD58WVnoFYNNjsn4rpgxKpvXi6c7Js0F2TLUWJmWsrQ2JDunuZMQKXmDPoOgz6B5I5ID3rV9EJQw2lJJIzTu9Fk1fRdUhYCohIJxpPjx/F2TsGbHMew5VJlAS99Try8Aq0mHqSOzYNLr+DsQrecZqdB4klz8YGqq/rsZmLt0H75flcdJybROoCSs8yd156Rnlolz1B88pfuRvreVPqNKH1drytqFQsq4i+DYux4BX9MBYo3eyNtHCr169YLVasW///1v3H333Th48CDeeuutqr8nJCTgiiuuwEsvvYT4+HgMGzYMq1atwrPPPovbbrutxY5LAhdCi0GVFzmdklVPoJ3SE1ji4t6rh+OeFxayA6cxLprSg5sxURXI6ZJA8hlaDffLWL2jAE6XF+2TLBjYI5WzZ0hzmwyI2sdsNhthNOm5nHhX7gk+945pcejROZnLEKlReW1DjAMPZgNPsAePlrFxSe+V0zmZAwIup5eNh9rGFRlfBqOO+4ds338ShcV2duBQ5kBCopHHrvYxNjd0THaHB49cPxIPvbK0Sb3022YP5PPNK6xodEwEQRDaCmS00/N87IBMWCxGkOuf5C9+cd4AlszRQMPNPXfsP4nDRRXcXNQab4KPnPZmA16fs6VO0KI2yzYfgUGvxZ2XDakhqUOLYNLtpuDGmu0Fjb4HVWZQM0RXtXmFFxUmPc9DJAl5uLCCn/EkZ9U+2crPd1pANkeQmhYrdOyZKWb88pLBuP+aESxRSY5smofIMVVWao/KBSjZChVlTphNelw1ozduvXBg1bmR/UFSHtSYMpKdLGEdE8rOc7e9MRGEWIfmQL1Rx8GAzXuO85qL1kJ9u7bjNQPJwNQOTNMc6tF7MXFwR67UpzmI5gF6MgQ18U83m5eeM9mZidiwqwh3/HUBJg7txLrsd1w8mAMSlFVcVGzHtysO4oX/rUdJuYuzvYN/o7n3xQ/XNzo/0Rz98PUjOSB/usH3esekSjGBegSc/pg0B7T2JYlLMnzoetuoEjXeiME90zh4QXPf6TrrKQCgN+jhcHuxYe9xXqump1jRr1vwnvJFxFhU90EEOIIDrN1ZCDuPiYkD9gaTHgGfnxMpm4PK5EcDTGY9jh63Yf+RUr5HsjskogtJfzs99fogogE6dgrGDOudgV5dUthX4vb6WdacHOducoJHePAq6qXlK1wceLhgYnde19C9Rfcc2fN0X5HNHlRoqQ7tozPoWfp2y94iFJe7uOKbngtGs4HXP9FSKWbq2APps+9B4ecvNBq80OgMSL/wbt4+UoiPj+cgxHPPPYdZs2ahT58+eOihh/CrX/2qaptHHnkEKSkpHLwoLCxEhw4d8Jvf/AY333xzix2XJiCpz3UgZ+rJk7Zmez/KHElJiUNxsS2qsgFP99xo7k1OicNdzy9EXhNag0GG9U7HIzeMZI1qi9UIh9uHv767FrvyiuvV6LxsWi/OGm2OTMv4RAtKyp14d94OrNhylBfKQRLjjGwAUpmwz+tHRUWlxjg9hK1xJnbcfPDdTmzNrVkh0qF9HEeWKXuQItDBaDGNW1y8GUs2HsZnC/fWGR9y/lxxZi/OtKWMgKCDnzJbaVyo4fm85Qc4gh2EEl6H983AdWf3RXqKpclMgua4L+ncC4odePb9tfX2MiEjlDS8B/dKw8P/WILCYgc6pMZx9UXtMWlO2up3LtqRc4t80tKUywuFa56NlbENBrNp6nln3g4s2pBfIyhMxjs1JL3unH78vL/y8W8UO+tfe3gaEsy6Gln7tLCzxhnxnzlbOSOqdlYozeGj+mXivquGn+qX4anKkIyLN2H+6jzMWbyPgyrVIacALVR6ZSXz4qWxxWEo144ysCqzM3/WWY1EQju3yvMjInlRHc7vXLjHJFaeJ23t3GLl/CJxjm3JsaWvNq0ljp6w471vdnDfp+qP9dRkMwcKLpzcg6XhGquyClb+qX1ONHZutO5y+QK46Y8/1DguklyinkpOtw9lNM9V+xsFK8aRtKLLy2u9tTuP4d+fb62xZgvSMTUO91w5DF07JDZLAl5taL5OTrZG1HeC1rEurx/vfL0DyzYdZqdykDizHlNHZOGas/twUkJDGdmNXTe6pyxxJhQVO/DuNzuwbkdBjetDPRrPHtsVF0+le8odEZV78Qlm7h1KY7J002FOoKwxJiOzcO3ZfVmqOeiDCBVKPCEbbt3OQnyyYA/25pfU+Hu3jom4ZGpPjO7fgXubtsR901LPE3oG0HfuUGE53v9mJzbsrvk8SUu2cDXWhVN68PeTKjebm1iYh1rDrqVgJgXoPvh2J68vKqp99ykIPH5QB17/WI06/t629hyrFNeRvShe/hnse9bW7Hmh1bE8FFVaRFLQIpKJmsDFF198weUqhw4dQlZWFn7961/j7LPP5r/l5+fjD3/4A9asWcNlLZdccgnuvPNO6HQ1dZ1jzdiLBJo6NzJO1u4qxN8+aLrxKD3TSJszOz2Bs0KCDzGzxYAjx234dsUBnCh1wqjXsqwGaYdy5NbpOe3MfTIY8osq8Niry+FoxIDJ6ZyEv/xqAmc90GRHk+OyLUfx8kcbahhFtZk0tBPuvmIoN1Wlr1x8ggVvfbWNy3gbg7JcyWCn/QwGLSxWE554fSW25B5vcB8an8dvGo2enZMbLQVurvuSro/VYsTuQyVYsCaPK2TMRh2G901nqQc61r9/tLGOwU4OuLtOjUlzfy/a8ncumpFzi3wi0akSK2NLz1KnN4AH/r6Y57qGSEux4JlfT8QPqw/iv9/tUvTeM8d2xQ2z+taZE8ipEQyWfLPiAHIPl/DColNqPM6Z0A3xFgPPscGFPS14ExLNLDFFklaNzee/vHgwP+cpsaAhSzNWrl19yLlFJ3Ju0UssnF8kzrEtObZURUgZ0X96e02jkkpDe6Xx2qYlEp6aOrfEJCue+2AtyxQ2BTnFX390Os97lO1PzmitToN2CWas3n4MK7Yc43VmYpwBU4Z34UB/wQk7EqxG8uo1ezZxuL8TZCMYjJUyxhqtBn6/H5pApcQw2RZmixFlDg8e+seSRhUVOqXF49nfTAR8DY9JQ+dGgbA9+SX4wxuragRF6usf9eQtYzkgFi6p5YZ8ECRH9tA/ljbaWJ2aGT9z50ToNaQ97wrdsZ9gxhcLcznhsjEuOqMHrprRBxXljmZPGmip+zIh0cKVyn95l54ngUb70fz2xtFwOt3NrlIRC/NQuM+NpdYNejz4jyWNJjvTmuTPv5qA1ERTyMGLcAcugnjLTsBxYDP8Lge0Jgs34o6UnhbRQlRIRc2ZMwePPfYYHn30UUycOBFff/017r33XmRmZmLAgAG46aab0LVrV3z44YfIy8vjbakpCJWrCK0LOTzGDuiIi6eW4dMf9zbq5CA5oe4dk9jYCxIsVWwXZ2TJAJLOCCDARlBz6VlTcIQO4Pf/XtFo0ILIzS/lIMz91wzn/Y6dtOPljzc2GrQgFm84zI2Izhnblf9/0fr8JoMWxFtzt7N0VE6HBGj1Ovz7iy2NBi0IMtKefms1Xn9kOmfUtnQzVcqGIVmrLqlW3HhOP/gCAZa92nuoFL/528I62bhBSB+Wyq/PHkt6q9IcSxCEtgtX71mNePDZnxoNWhCURfjkf1bi+bsnceUdSVM0BS3kzOaBdQIX5ACiFwUwzhqdRS3zqv5GAfqy0poZoCQPNXdpZR+OxqBAxaufbuJgf4cUS4vLFwqCIAjRBTmryLH/l3caD1oQG3YX4c2vtuHamX3DrnVODWfvu3o4Hv3nMuw5VDM7vTpUnU+Nr4N9H0mq6K4XFqGoxIGBOe05W/iGc/ux7J3P78fBo+WsSkA/SRLrj3eMj9r+AmTDUFCCpF5ojbt6ewFL+yXGmTBtRBfuS8QNxM2VY9KUDDStHZ9+cxX+eLu6MeF1r69yHdxY0IIglYTXPt+Cm87v32qBC7K96PX4a8sbDVoQpGzAY3LHeGi1VM2q/vNIHoqkuZoKWhCk7pDTKQnDeqZVJZRGMvHxJpTa3Pjre2sbDVoQVG3y9tfbcPXMPoDYpxEhFfjUm6uaVGihKgz6rrzx2Jn1ygdGMhSkSBh0RmsfRlQT8YELyk4n7azrrrsOV199Nf/ujjvuwNq1a7F69WocPnyYO5p//PHHSEpK4mYiJ06cwDPPPIPbb78dRqOxtU+hTcO9EGxOXHlmb9YZ/PSnvdhdS/ZpUM9UXD6tF3qekpWobZxwI9EW1LPTG3T4buUBbv6ohFXbjqLc5mYD9f9+3Ko4C2Hukv245Iye/G8aB6VQGefvbhrNZaNNOYuCkLzIl0v24eIzcgB3eL6n5JiirJFXPtnMElhK+HLpPs7ooABXJMtiCIIgtLQDZ9Oe4/VK7tXHgaNl2JJ7giUMP56/u8ntSS9cp61svlgfwQBGU44J6mkxZ3GuomOkR/r/LdiDu68cJgtDQRAEoQaUkPXF97uadDAH+WF1Hq6f1Y+zfsPpsOKKQ42GK+7/78c9+G7lwRpV5NRnkKoLSSLRpNdyJjA54pZvPsJBC4Lm6wf+vqTBz9hx4CTyC8o5k/h017w6HcmyUL+P0NZVVC1RKbsVqFeHvja0La3/flqXj7fnboOtmiQlQYEMkjB+4JoRSG9nRZnCTGmqxCHJn9QE5WOi02u5mqCp3otBflp3CL84rz8HD1qj+S8lQZI01PESp+Ixofsks50V5eXqJaMo+eSTH5u2GYPQ/U7qCVSZEOkBNeoP8vnCvTVkthqDJFKvndWvUg4uAuTC2ir0HSAp8Y27ixRtT8laC9fnsxyfJL62LSI+cLF//34OTpx33nk1fv/GG2/wzyeeeAL9+/fnoEWQMWPGoKKiAjt27MDgwYPDfsxCTci4JDmgQTntMbJfBj+caNIlw4h0FCkbw+P2wFZOQYvwz4rUAOib5QcUb0+HOHfpPlw2vRcbpUopqXAhr6CcHUgNVSHUx+a9RdxIivT+lE7GxPerDuKas/tyQ9Vw6ULTp6zYomJMyl1Yu6MAA7q1a7aGY4IgCNEGNan8ask+VfuQfOL15/RTFLhISTDDc5pNKGlxsXFPUZMVIdVZue0YS5a0llNAEARBiDw4EG7Ss8SsUsgZ/eO6Q5g0uGPYHVacYOXz4/wJ3XD59F6chBdsHEvVEtQX0e/1VcmXkIP4awWV9dWZs2Qfbj6/f8gSTVRtQM2WaX1N8y6tb+0qkgbIgUvBpHjqQeH28TUiRQQKGjSW3UxyX9+uPMj9shqC1v6PvroMT906Fr+6ZDCe/2/TEtIEJeHddF5/5ZWrFiPLaCqF1tW0Xj5zZJdWsVH0ep3q+4TG5OYLBqj+LLq+J0od2Hmgbt/Qhth/pIyltNvHG2r0SIs0SE7baNBxIEoppLLx09pDmDKskwQuWhOthhNZ1TBv2X5MHdHltHpdCNFHVAQuCLvdzpJQ27dvR+fOnbnqYurUqTh27BhLRlUnPT2dfx49ejTkwAU5YZsLMiaq/4wl1JwbGT30SrLokdK9XY2KjOoZIuGEj1sD7qGhhkOFFZyF0lQpYn2TpNJG5dUDJWRAqt2PSk4dTg87jOrrAdLc9yV9DkmYqB0TMoqohFq+c8qQc4tOYvncQqW5vvOxMLbkYCCJPTXQ9u0TzYq2nTayC0shnM6Yk1OAntdqoDm+4KQdmSnmehMTYuHaNYScW3Qi5xa9xPr5qSWS7Wo6tnK7u052flMcPFoGDO7YKudGcxitY6lpdFZ6PLIzSCs9ALfr516LweMiJ6raOZ2S+qgJrdpzqwxYGDiZ7svF+7DrlLIBBVXOGN4Zs6f0QHK8iSWv6ktko0AH7U+yXXMW7OZEuaAKATUNP29i91N9Jb3c0Lj22s/u9OKNLxsOWlQPEvztv+vw70fO5EbstGZsikONjEnt60Y/7S5PkzJUtaGkQqI57yml0GceKlCezEhQFQrZY2qPl7bPa0TqrCEOHi1FRt8M6PX+iH2e0HegrMLN96IayLdCQcdIflZGEi1xbvRe9OxTQ/C5QAGrSK8EEtpQ4IIqJ4iHHnqIG3Lff//9+O677/DLX/4Sb731FpxOJxITE2vsYzKZ+KfLFXrjImo809wkJloQq0TzufkDAc4oqe/BZzLoMHZgB2S0s/J9Qdk1VFEQcnjlNB6udIzq99E0eW2a89qdVGksMppKg4OyZJqbaL4vm0LOLTqJ5XNr7Xk2mseWnAlqn/H0fFcCyVhMH5UFs1GPOGoAGiK0uAsFOs64ODPi4mLz2jWFnFt0IucWvcT6+cXKWrY0lAbDGg1L/MbHVa71I/m+UTpH/7wDuKG1mutGza8p+HPfS4ux73BpnWQ56oP1zYoDuPn8AZg5tisHVGpDSgArthzFix+ur5N8RrKU1MuRZB//9MvxSE60sMMwiMvtxcff7VTsPCRJJKq0nzmmKwcvmkKjYEyqXzdbCLKUmlNVry1xTyn9fHXb038I6futDcGZQPcxSZ/RK5K/c85q8m2KoftLE/nPykijWa8b9WINcf2TnNz8102IXCI+cGEwGPgnVVvMnj2b/923b1+uvKDAhdlshttd01kaDFhYrdaQHQhlZXY0ZySRvuBlZY56M9+jmVg4t8QkKzqnJ9TIjKH+FZdN68VZqsdLncjNL2GnDTUXu+WCARyhpyivQa9VJd9kNevRo3OyquOjZ7PZqEO3Dj/LoSkhOcHE2TYlJfYGM12b89rR+6WlWFWPCTX+ogym8mbsYxIL92VDyLlFJ7Fybs1l3DfnPBsLY2u2GpGdmYhjJ5SPSVZGQpV+dkOQTPX9Vw9niYviYnWVhfU1dezRWd08pNdpOPBfXu6oV2YiFq5dQ8i5RSdybtFLLJxfJM6xLTG23Bch3owEq0Fxj0Gie8dE+L1+FNtObz5r6fsmLt6MrMwEbgCtlOzMBHg9PtgrlDlgSanAYjXjsVeXNVoNSUvA1+dsRbzFgNH9M7lCJIjRZMCuQyV4/r/ruC9VQxw9YcPDryzFy/edAYfdVTWf0/26aL2yvobVe15cOr2nosBFVkZig2NS+7oFk/VSEkycaKgUqippDhspFKg3SHaHRGzbp/w+ofuKfBJqj5eqY2hftXTrmASbzcVN5yP1O0cVE0lxJr7HqYGzmmtPgh/Nee1jYR4K57kZTAZe/1DTeKXQfUzPIFpbqKUlglRCeIj4wEVGRgb/pKbb1enRowcWLlyIUaNGYffumvrOhYWFNfYNhZZo+kVf8HA2Ewsn0XxuNBHPGtcVr32+hf+fnCx/uG0c8gvL8dQbq7hhWnU6pcXjwsk5bGhceWYvvPvNTkWf0y7RjC4ZCVx0QQ6nYGlqUwzrnc4T8rRRWXhr7jbFTezOGp0Nu8PdpGZnc107eg+9UY8JgztygzalY0LnR8GVlujDEc33ZVPIuUUnsXxuamnucYjmsfV5fCzHsGrbMcX7XDC5e1VggOSYapOWbGEt6X7d2sFWcfo9pPx+Nwb2SEVaikWRxAMxZmAHDp40Vb4fzdeuKeTcohM5t+gl1s8vVtayVBFA1YCfL8xVtH2l9FEX2CqcEX9uJKl03oTuqgIXF0zKYQe60mMwGI1YvCFfsYTjO/N2YPKwznA6KiWjKDGO+h6QzJOSJRjZGXOX7cPZY7Lh9XpPNfBWXzlD28ebKxNTm4LW202NSfXrRuves8Zk48MflDWgNuq1OHN0NlwOd6s8M3xeP84Z301V4ILuE6p5UXu8tH1KshX9u7dX/Hk9uyQjs70VpZwEiWanOX0QOoOeE07nLN6nOJl0yqnvQ6Q/TyKN5jw3nc6H8yd2V9Xn79wJ3bj3TqyOr1A/ES++Ro234+LisGnTphq/p2BFVlYWRo4cydUXQUkpYuXKlbxPnz59WuGIhWiDsv3JcCb9zziLgRuHURnrH96sG7QgqLH2K/+3Ca/830ZcOKUHuneqKVXWmPFFPSfoQXvJtJ6K9iGj8tJpPeFx+RDwB9i4UjoZkxOMdFjDCTWmu2RqT3amKWH2lMoxqR20IEPaYjVywzdrnImzkUlOShAEIRahxoADurfn7C8lUOVery4pSDAb8NrD0/D07eNw5qgsljakhdsTN4/B649NR++sZHbynG7QgqDntMPhwUVTeijanpwal03tFfZ5SBAEQYh8aM1w4eQeXFWuhJljszkZKxqcVW63h6sbyOmrBKro75AaB1e1aogmq/FNBnyloqntyTIn1uwo4OpJwmw2sLyUmh6KJDtlsRh4fg/aFSRHqQba3ulu2i4Y1DOVx4/WzUohe+PcCd15HawEWlfT+ro1GnMTTqcb405JUithcM80ZLaPQ3m5M+SAGjWXVwr5IMg+jYo+Av4AP0+U3o+zxnWD1+eXxtytDI0/JbKO6Kss4Tw12YyJQzo3awWQEB1EfOCCpKBuvvlmvPLKK5g7dy7y8vLw6quvYtmyZbjxxhsxffp0pKWl4e6778bOnTsxf/58PP/88/jFL34Bo7H5tfiE2IMnZH8Af7h9HGZPzsGJUiden7OlyUl6wZpDrB36yPWjoDuVddIQ5FCi6DAZDC6nB+MGdsTFU3s0aZTecdEgdO+YxIYNlfbedH5/DO9T2Xy+IWgB8LubxkCv1XAz1nBCTq3UJAvuvXK4ojGhLJPqjd5MZj2Skq2wuf347w+78ez76/DsB+s4G8uv0SAhySIBDEEQYg4KCtjtbg6cN7WA7ZgahyduGcPbOxxurljL6ZCAG8/th99cNgQ3ndcfvbskoaTYDofd3awLTnpezxidjVljuza6HTk17rliKDJUOh0EQRCEtrP+Mum1+O0vRnNPwcagIMC1Z/fjZLNowOejQL8bT98+np1yTUlEPXbjKM78Vjpfa7Vadrrm5tfsa9EU63YUoCrso9FwIEMNVG1J62SSjKFjpeSzob0aX5fWZmTfDG4w3RiUxPHYDaPYhlEDrXtp/fv7m8Y0GRCj9TStq6tLZ4Ubj8fPPUb+eMe4Ju8TGpNHbxgJryf07wDZY327tsMvzuvf5LZXn9UHQ3uns98iGiA5qziLnu8bqqRpDEryueqsPvCG2U8i1A89+x68dgRympCjpSRjeqbSfRxrMlxC02gCzZGGFwaon8X777+PgoIC5OTk4M477+SgBXHw4EE8+eSTWLt2LZKSknDJJZfw32lSDwX6Ipw82XxadyTzQ3pqpJ8XDVkiSiHHOuklJiVZUVJi48k3molPNHO7K3KUr1Yo10FSHK8/dibyjpbivW92Yt3OghrltmRkUKXFpCGdeEINZnTQPUGVBOt3FuL/ftqLo8crkJJg5kbhlBHTs0sKZ0SQnrjd5qqqSKisRDDhm+X7MXfpftYcDULN0sYNqpyIk+OMrEHa2Le7pe5LcljRMVJlyv++31XvmFClxYTBnfjcgmNipgwenQ5/fW8NNuwqqvu+GmDikE74zeVDeYJrLEMiVr9zhJxbdBIr55aWpl4ft6Xn2VgZW4IyGTU6Hf73/U7MX3OoRqNJ0gKn6sArzuzNWYXOEJpQNgd6vQ5x8SYs33KEg8rVG4LSc5oWulfM6I3sjIQa81d9cwX1ikpMtMbEtWvN+5LGkvS9yaRvCdnF5jg3Or6gtAg1lI3U1UcsPU/a0rnFyvlF4hzbkmNLa0laM5wsd+G/3+3Eyq1HazSIpkA9VZCT/I/d5m6RLNuWvG+oepweyR98vws/rT3E8ljVnXAzRmfh0um9OCCjZk6nY9YbDbjqd9+oOh6S2rr1wv5wO70wmvT4fk0eflxziPsCUEBCCf96aCriTXq+FlS1cfiEHQ+8vETRvpQN/8GTM7kXIvW4IGnh+sbksum9OFGiscSHxq4brbFLbW588N1OLN9M99TPf6cqDqrKoIx7WitHQsY99bogKWj6DtQ/Jtk8Jn6fDxWhNLWv1RvFGmdmVYmP5+/G1lqyURTYoEoLkga1V7haxEHccj4IwBpPcqZ2vvarth7jfiBBOqfH49zx3XDW2K4ckKEEoOYmFuah1jg3epaYzAb834978O2KAzX61FAQkmS9yMdl0GlUBzRbYo4Vwk/UBC7CSbQYe60FnY/BqOcHDN0+dAdRQ2ab3cPOlGgt3aIgjNagx7W//0aR1meQP9w2Fv26tuPeFQ6XD7mHS/geolLOjmnxPB7kaKfsm+rQAt5qNUGj1cBo1FUGfjSVAQhy5pNxYrd76kh8VBqreljNBuw/WsaTM2Uq9cpK4fek0muqfGjN+5JLmM0G6A16Nr5yD5fymFAZNI0JGedURh0cE6qiMJoNuO+lxTWapNcHyak8ddtYVJQ3rHEba9+56si5RSexcm6R6FSJlbENQs9DnUEHk1GPnQdPosLu4aBFn+x2cLq93A+jtedZmmtogUFSFRRAP1JUwYvh7p2SWaKBstioUrA+C5PmBi0F780GuDw+GHRaXliSk6L6vBDttPR9SYEAs1nP86zRoOOsTfpJY+rzkMOH5B0CrX5ufD/rtYizGuH2+NmxoNVoOFOXnHWR9p2NtedJWzm3WDm/SJxjwzG2lWsGHQct9hwq5udYeoqVk53oWUHzQ0tl2Ibj3GhOp/XdroPFHCRIjjfyus3l9sHjpjWRusxvmm8Tk6y49JGvazjlG6Iy8SGbE8eoibHb64NBT+NNQeQAjHod9h8txbxlB7BoQz4fV0P896mzeY6htSqt95JT4vDnd9YoSvqjylAKQpEdo9PreO2988BJTtJISjChd1YKHE4vVxU0Jd/U1HVjSSu9ju2QXQdP8j2VlmxFt46JETn/xMeb2PNOigVk+9kcXiQnGFkWlIIafq+X/QLNZj9YDDw/l5S7cPBYGY8T9eJMTTKzZBkFdFoqEaKlv3OJiWYENBr2rezKK2b7iCqAu2Ym8r+pyqalVCliYR5qrXOj5wHNAxazAbvzivnepH9TMM3rI9vWd9qBRglcRC+iuSKowmIxcobGgjV5nPEfbDCdGGfE9JFZOH9Sd87EpKyYaIuJkSPm2HGbqqAFQdmm5EyfvzqPAwlkmFIJ7bqdhUiKN2LmmG4wW4w1xoQd+xYjPP4A5i7OxXcrD3KlRTAThCSUzhrTFWYL6kSVaaLwet1wOTzISDIjM9kCIACvu2kjL1xw+TAFTxweDsr06VJZ+kcGUEmxrY4ziyapd77e3mTQgqDMkK+XHcC0EZ15HARBEGIJDkq4vXA7PSwBRQFuu92FsjJHxJRGc78Lu5uD8kkWPVK6pvDv6fjKS+tv3E3zImVBFpU48MWivVi04XCVc4QaiJ8/MQejB2RyBly0SBO0FjSvUsYkOXy+WJyLtduPse1CdgxJqlClJzXVpKbsrWUXkGPEGmeEy+vHFwtz8cPqgyitcP+c9TihG6aPJM1672llzwmCEP1wZr3Tw46rXqfkQmjNVFxsj7r1ZHW4Ut5ixJbc4+zYD5zKHqYkhKWbjnCzbArOBALqntUU4CcH7PjBHbFofX6j2w7MSWWJoX1HSvHaZ1u4qoWSBagAblifDMwa1xUDclJ5Ppk1vitn9j/5n5X1rsmo7wQFyMvsldnQdGlonnn42hH4y3trGw1eXDmjN1c6UOIZ2zIuLztCu2UmVFUMlpbamy15oTKJr/o9pYnYe4ruE0oK3bz3ONacuk+oOsVF98nGI5gyvDOyMxOhd5MP4PTndDp/mnfpRUkyfbOSf16nl9gR7ZSd8qlQ8Gpg93Y1zi0cValCaNAzkF60BuicGocuafF8r9ptDSerCm0HCVwIqspdbU4v7npxEQqLazomymxufLZwL75csg/3Xz0Mw3qnn2oIiuhCE8IuGg1+Wp+PVz7dXO/fP1mwl8eE5DPsp8bEEmfC3vxSPP3mqjoNyo6dsOONL7fh0x/3cjUHZT7Ut6inB3k0aIdXZjT4Gq/gMejw49pDit9z3rL9OI96htTT2FsQBCEWoIU9ZRZR4IJ+RkrQojo0nynJfiKHOkkhfPbTXi7fr832/Sf5RRmoNO9RMN7ljM7qzZaG5ksKAD33wVqWwKgOzYcrthzlF5XVk7Qi2WLhDl5QcgYd4+bc43jmvbUsC1Kd/MIK/OuzLSwJ8Kc7xiPBSvKWErwQhLZO0HEVC1A2OyWpPf3WKk5mqw9aN88ck41bZw9CRblDlXOOKuypN2NjgQvKVH78ptH49xdbOMGuxv4BYO2OAn5RwPu+q4fj2ffX8jxMz+UHXl7Ma9LqXDgphytEqhOsAH3k+pHYfbC4Mpi+o4Cf+/EWAyYN7cTBdJJErgpa1EjG87fpe6rqPnmz8fuEeovdfOGARhUHQqG1K3hbEgpeKVGhECILsmWjwcclhJeIb84tRE52n0arxcP/XFonaFEdKjl95v112HOoBGazMeoekqSl2lRT6dpQpkxjlQLBMdmbXzkmlHlDY/jUf1bWCVpUp6TChUdfXQaXx89yELEKGWzUB6O6nmdTkDQJjTk5cARBEITIhhbl3686WG/QojpUGv74ays4WBPshyDUhAICf/9oY52gRW0Wrs/Ha59v5qSTcEO2zoFjZfjLO2vqBC2qc7zEiYdfWYYASDIzdu0cQRDaFhS8jYszceC2IWd0kG9XHsR732yH2WpS9Rnk2KPqNepHUB80hz5wzXC8O297naBFbVZtO4aXPtyA+64ajk9/3IMlmw7jN5cNrbHNtJFZGNIzrd5kBXJ+lxTbkZUeh3uvHIbP/noe5jx7Pv739Cxcd3ZfxBl1KI+gqtFIu0/+quA+mbfiAD74difbU4IgCG0NCVwIiiAdys8X7uVFppIAwJtzt7GmJ03I0QJlY1DQgqQqlEKyTgNy2mPR+sNNj8lX22AiPWqjDm/P3c56lU1Rbvfgwx92sUZnrEIVKycU3Ff1BXZoX0EQBCFyIYkockq//23jQYvqwYs1249xDw2hJpTEcLzEwUEJJVCwiOwIkqEIJ2TrvPnlthpNMRuCZDI//WkPdAZZkgiCEBvQGpj6BlBAQAlfLt7HQV5KFFQKVTzabS5ccWZv/OK8/oirleQ2ql8mb0NV6kpYtvkIjhy3YcrwLvjfdzvRKzsFWRkJLFl02bSe+NUlg2CzuRqsdGf5IYeHAxTHj1ewDv7x4+V8jJHQADtS7xPqLaKkPwgxZ3Eu94GRxD1BENoaskoQmoQyNqgxznerDireJze/FIcKy2EyRZfjgZqLXzatl+JMz9mTe2DV1mNV/SmaGhPajhqQbdjdeFZFdchBodfpWFIpFuEm5SFUlFhMesnIFQRBiHAoaLF4Qz7PfUqZs3ifZODXg1anw+eLchVvT04rcnSEM/mBHDEkL0INMZXyw+o8bvRODWcFQRDa2rOagrxfL9vPiYJqIMkgkg6aMSoL7z05E3ddPpRlAscN6oCrZ/bBtysOqOrdOG/5fu55QQHvpRsP496rhuH9J2fi4jN68ucolVyiIAYFOKJOMjrM0Nz8hYr7hIIWdI2oN6QgCEJbIjY9oUKzQg7zgpN2lJRXNuJSyprtBVHnWKay2w6pcbjr8iFNHjs1lpw4tJPiLFLiRKkTG3cXqTLkSE5q3+ES6GO46mJI73RuEqcUyirq1pEarYlFLAiCEMkENMCGXcqD9cS2fSe4UiPabIiWxmzSY/OeIlX7ULNPaqYaLrQ6Deubq4H6pB0pqoBOF7t2jiAIbQerxaD6Wb1pTxHPe2oh+SWqaigvc2JMvwzceuEA3HnJEHRob8WmvcdVvRcdc1ZmIism0PFktLPCYXNxryRpjtv8WM10n6i7Rhv3FEEbwn0iCIIQzUg6m9AkJMfjDqGpFe0TbW5lCiiQgTZ2QAd0TI1nmab1uwprBBpyOifhoik9MHpABzz26jIcLqqo970S44xITjBxxglVWthPNRp1hlAu64zgpmKnC42PUa/F8L4ZHOxSwtQRWbA5PfIAEwRBiHA00HCvplCcMZVygNFmSbQc5NRye32qbTG1vbtOu2F7SDajHxprixySIAhC2Aiq2KpdO9P2DQXrDQYtz4c+X6DBPhH0e4fDXfX/xmRrCMfg5/lCr9NWPscDlVUdQsvdJ64QrpEkdQiC0NYQv5+gyLGcFK+uYRjRPskMTZSeL2WWZKXH49EbRqHC7sG+I6X8e6rGoL4WHrcPDocXuw7WlEIgQ2JUvwzMGtcNg3umccNp+p1ep2Ht0HiLAWkp6lfm7RLMXHYbi9B5nSx34ZqZfbFl7/FGG5YTKQkmzD6jBzc9D6czRhAEQQjtGU/PbTWYjTquEojVeS9UyAmVkmBW1G8sCCVQNNYgu7nRajRs/6klKcEo11sQhKiHHmO0ZkxJNMPmrD+5raFnNUkBBaF+F0aTobKfAQUQ/H6YDLrKBLhAABUVjSshUCCD5t4DR6HqGFxuL88ZNNfIMzkM90mCif0FSqHtpcm5IAhtDakzE5qE9CzjLAb07dpO8T4GvRaThnZWrIUZaXDGoMvDjhPqk9anSxL6ZScjyaJHaYmdm5PFWfTo0zWlap8EqwF/umM8br1wILbkHsf1T36HK347D5c9+jXufG4hSsvdSG9nxZBeaUiMNyo+ls7p8fxyN+HQj1aoYRsFhKiC4vc3j+F7rSHSki34w23jsPdQMQdzYnVMBEEQYgUNAjhrTLaqfUij22Z3N9gEtK3idnsxbUQXVftMH5kFr8oqjdM9xgmDO7GDTSk9uyQjOd4UtTajIAhCdewON84Yru5ZfeaoLAT8lQ7p+AQz4uLMWL7lKB74+xLMfugrXPrI17yufGfeDpTaPUhIsjTa/9Dn9WP6qCxVx3DG8M5Yfar6/azR2ZULYqFF75OpI0K4T6oFuARBENoCErgQFOF2eXHh5BzF208Y3JFLIGNhEUrn4HB4+EVO9qANR4GNCyf1qMoOffLWcazTfPtfFuCTBXtQUi0ThuSk/vPlVtz25wUoLLbj9zeNUfz554zvBofTE7NZL5Q14nL7sG5HASocHrz+6HT84rz+6JQWz30vqGIlp1MSfn3pYPzzwanYtv8EisucVWNC9xk1A7VajfyifwuCIAiR0zsqOzMR3TtRXyJlXDi5B/y+6LcfmhsPBS5GZcFiUlYwTYkAk4Z2YhsunDZTwB/gz1XKBZNyathXgiAI0YzX4+Mm1yS5pIR2iWaM6pcJl9PDQQuSD/rN8wvx4ocbsDe/pGo7kh2mJt63/Xk+flxzCNY4c4N9MSiIPG5QRyQpTJYj2d7po7Ixb9l+lkXunJHAa12hhe+T8d1U3Scj+mbIdREEoc0hgQtBETRBjuyXgcnDOje5LWXP3zZ7ELzu8C2UWwNaZI/qn4HJQzvhyhm9ubT2mffWwN2IJAP1unjklWXc7OySqT2b/IzhfdJx1piu7KyIZXweL66c0Qcffr8LT7+5Cu2SzHj5/jMw57kLMOfZ8/GXX01gh8aD/1iC1duO4czRXdnYs1iMSE6JQ1GZE6t2FGD1jgKcqHAjIcHCUlKV+uiCIAhCq/aOcrrx0LUjGq2oC3L9rL4sNeQ81RdK+BnSGqfX/VcPb1LjmqQUH75uBNsq4ZaV8Hq8uOWCgVwtqiTRZdygDnCLI0YQhBiBArj0iL77iqFVvQwaUyl45PqRsDs8LAtFgYhH/rkMhwrKG9yHihFf/Wwzr4nMVmPDiWEuLx65flSTjnE61t9cMRT5heU4cLSM52unwy3B5DDcJzoa+8uHKLtPbhgJu9Mj1aiCILQ5pMeFoKLvgwt3XT4EqUlmzF26v04zKZpwh/ZKxwPXDOdMSTKW2sSYXDEUXm8AT76xsoY2aUNQJcYnC3bj6pl9cPS4DSu2HGEDtDpkYE4f2QW3zh4Ih90V843RSPJJq/VwgIKyi57/YB3+rtvAklpUNU2VLASVPN964QC4nG5Y40xYvuUIPv1xLxvZ1aEKjcum9+LAj7/CJVqggiAIrYjT4UGi1YTn75qEZ95bi9zDpXW2IbnFa8/ui6kjsrjPlFA/TrsLA3Pas7TiPz7ZiKJiR51tqBfXby4fipyOSbDbwj+WZP9R4sBzv5mEv32wDmt3FtRxgFF2L/UDu+6cfnyM1HRWEAQhVnDY3RjdPxOPXj+KgwyUvFYbqi6/96ph6JQWB3uFi6stvl91EPmFynpjvP31Nowb3BEuvbbetSIFhEmK7093jMMLH27gdWdtUpPNHGjOykzAa59twfN3T0KCxcDHL7Q8NM5jB3SA+bqR+NfnW+q9TygJ4N4rh6HjqftEEAShraEJxKr+zGlATs6TJ+tO7KFC+pMpKXEoLrZFnAOajs1g1HPUgRoqcgQ/UJmhUV80n7Y3mY3QaDVYsCYPOw+chM8f4AoCWoBSOSpVZ7hiIFNS6XUjeaIyhxe3/nm+4vemrNP3npgJv98Pu8vLZbn5RRV8Dbp3TMLMsV05+4VKhuuT26JMy/h4E+iwKGBEV4oSNXweH8tyNOf5hROTSc+N6BzBMTled0yo+sRsMeL9b3fg84W5VfsmxhlZ93PMgA6Itxrh8fr4Hu6SEY/yMmfMZKdE4nVrLuTcIp+0tISIm2djZWzbwrmRlB89v/MLyvHdqoMoLndyL4ThfTIwflBHON1euBzN29uCMlj11G9Bo6mcL2kYA36u6GhJE7glrx1LJFqMsFgM2LznOJZsPAybw4N4K0lDdcaA7u1ZTrGlMmaVnhvN6SazAeV2D8ubHDth40qQXlkpOHN0No+/uwE7p7WIte9cWzm3WDm/SJxjwzW2tZ/VNA9oAgFe17Skt0LNudH6y2QyVK6btRr46cACAV6b1LcvBXDNFgM/q9ftKOSeFfRspjUL9cDonZ3CfQ4ouK/VAsnJcfj1cz8pDlwQT946Fv2yU1Be7qzx7NXotNBq6aXhZ63JqMOO/Sfx07p8VNjdsJgNGDswk+df+n+q9KDEOVqb+r20nlS2lq8cE/IlaBWNSXMRC9/3hu+TI3A4vXyfUA8MmjOpIofm9Fgglq5dbeTc2sYcK4Qfqbhoo+h0GpgsRuh1OixYm4d1Owu5z0ByvJGz2gfmpNY7QbJMQYUTer0OU4Z2wpShnaHTa+EjJ7HPj7LSupl/sQ4Z19SfQQ3kYDhUUIbUBBO0AeD8id1r/N3janghHxdvgsmox668Yny38iBOlDo5c3Fgj1R27icY9ZxhE40VL3TM9DIa9Th/Uv1jYrEasWLL0aqgBTlBbjyvP84e2xU7DpzENysOVI3JgJz2yEyNgzXezFmq0TrJCoIgxALkgKLkhtREE66e0ZuTIMhZQlWaZWWOZq2Oo/cl5z59BmWwbtpdxFKOpBFNzcL7VHMYRaX8lt3NyQ09OyWiR6ckdnxw3ycEUFJij4hgfXBOJ6fWRdQnrZoUBgWoIilgIQhC68BJcRYjP9e+XXEAW/edgMfrR2qyhW176rfgiIBnNUkyWS0GbNpznJP3Sivc3OOQeg6Qc5meZ7Rurv7spWdy8FndLzsZfbNTajyri4vtVQF0g0EPm9OrKmhBrN9ZgN5dkmsEi8vsbny1aC8OHi1DAAF0SU/gXkIUKOnaIZG3peOgtRIFLeYs3of9R0o56EBVIOdN6I7UZCucTjr2hteTNMdWjkkRFqw9VDUmJC9NgZn6xkSo35dA14PGKS3Fwn4BsmFo3UoSUTx38jbSL10QhLaJBC7aIDQRUinqvOX78d/vdnF2e3UWbTjMFRQPXTcCHdvHwW6rW5Lo9fr4RcZmfFwcituwU5gMCGcIi2+S2iIjhRtsKUygiE8042SpE396eynyammfrtlRgPe/2YELp/Tgnhv8GVEYvAg2lKtvTIKNuP/vxz38/5TZ8/D1I/l+vfuFRXX0YGlMPvh2J2ZP6YHLz+yFinJnm71PBUEQImbOPFUZyDYEZ281r6Qfv2+CmecKkhOsLW3507pDLL3wyA2j0C7BBEc9dk40QE4ORxQEXqLVFhEEoWWhKgtKyHr/2534ask+DlhUhwIE5Gh/9IZRSLAaW02+iI4xr7ACz763FoW15PlWbTuGN7/ahutm9cWMUdmoqCDpO7/qZzWtaVzeUNaTlZ9lMuu5GuT5/67Hiq1Hazi4N+wqwpdL9rGE7kPXjuSqQ0o8fPGjDVi68XANyWLaliShB/dM4zWW2aypt5rfGm/CoYIKPPP+2jqShTQmb3y5jXtWUXVdRTklJojHvT5YRSHBjCUbj+A/X27l5MbaUN8vkhTr0SmZpRUleCEIQltDmnO3Qag3wKc/7WGDonbQIkjBSTse/sdSHD1h59JFoXHSki2q90mJN6vKQCGjubjMhfteWlwnaBGEskk/nr8b//58C1cmNNW8M9ogg5yCE8GeFlef1Qcd2sfhkVeWNtjEjsbko/m7+X6PizdLw25BEIQYhh7x1jgz3p67nZMzagctglBW6/0vLea+U2LnCIIghBdao9Ca9J+fbsZnP+2tE7QIQjb/fS8tgs3l4+SlcENVBRS0ePSfy+oELYLQevq1z7fgy6W5fE6hQI79eIv6tVsKVe9rNTCbjXjs1eUsR9WQY5sUFl75v03QG/T4/b9XYPGGmkGL6lAVxQN/Xwy9Uc+V8LXHhIIW1ES8vj5LwTGhng0UkKI5Wagful+oWuWljzbUG7QgSEngd6+twF/MHiUAAGxaSURBVJ78Eh57QRCEtoYELtoYVEJKTZ9oMd8U5PClJppWkloQZ2+j1QHUV8FC+p4KoebRVALt8SjPQqQS4uf/t57LiJuC5JL2HCrhPhixBBnmVPZMUCnyuRO64eWPNyoaE9LX3ne4FGazFJoJgiDEKuTYIilGyi5tCnKsPPf+Onb4iJkjCIIQ3jUpSbzOX53X5LbUJ+fFD9ezDFLYgysWA6+HGwqsVOfdeTtQZnNX9nwIpdocAYzql6l4H5q3ZozOZtnczxfuZRnhphg9IBNzl+5jSa6moAD/23O3VfYeqWdMvAoqJd+Ztx3l9tDGJNYxGnVwef0c9GoK6in67Ptr2cYhyW9BEIS2hAQu2hg6vQ5fLPq5oXFTHD1hw/b9J8XZ2wjc98PrwxnDOyve57yJ3eF0KW82l5Bg5mux62DTBmmQOYtyEYhBT0zwlKYM64wjRTZFRnqQzxft5e+AIAiCEJto9Tp8rsLOyT1cys3CueGqIAiCEBYo61/NmnRr7glOvgunA5w+iyoPGqoqqA2t6+YszuV5KCQCAVxI/YAUMrRXOjdwJtknSlpTUp0xZkAmy0UrhZp5c+N06rVwakw27i5CUUmYxiSGoTXp3CX7FCswUA+RlVuP1qmAEQRBiHUkcNGGIIdvnNWIxRvyVe03f01eTDrAmxOvx4cbz+2P7MyEJrcdO7ADJg3tDLcKzWdfIKAoI6m2vihl4JCxGSuQZmz3jkn872F9MrB4o7p7edXWY2x4U58XQRAEIbagTFCTQYflm4+q2u+HNXk/R8UFQRCEFiXoBKfG0mqgtZBGG0YbXqPF/DWHVO1C8kvx1tCq+CoqXOjZJZmbMzdFu0Qz7r5iKAL+APbklbCcUFMM6pnGwfpjJ+yKj4kqE9fuKPjZWa7VYv5adWvSRacxJrEM+WUWqfTL/LjmEDS62FnbC4IgKEG8d20Iknvy+f2KZHWqU1rhglYsjSbLe+n17G8mcSZLfcNl1Gu50uKBa0ZwYy01jUgpW6VMZfNQKil1uHwx1eeCxjgzNY6N+niLgTNPQhkTuZ0FQRBiD5rvnG6fIvmK2nYOZF4QBEEI25rU7vQ02F+hsWd1IMxzSqnK9Vdw+1Bklinz3ulw44Zz++O6s/vC2oDiQf/u7fHCPZNZNtfj8XGvJiXEWQwoU7l2Io6XOqrOh8ZE7XvwHBvimMQqNBQ0HmrXsnStRSpKEIS2htSZtTF0Wi30Og28PuVmn8mog1+pplEbxuX0cIThvquHc3OtecsO4MiJCug0GvTokswapIStwslGplpMIZSFUrDE5VX/WZEK3YYupxeXTesFp9vLBrtajAYt7OrWIIIgCEKUzBGGU5m8aqC5RMwcQRCE8BAIBEKSu6G1UDhdtrT+Nas8Tqr6C55jKLhcXt6X+vhdMDkHP607xDJZ1GOD+iOePa4r0lOoT6IPFeVO7nlgUXiMLreP1/VqsZoNVedDwRW17xEcw1DHJBYJDgXZH1TVomYslUpLCYIgxAoSuGhDcBaHy8t6mGt2KC/NpSZhEtdXbmzSi4zx2ZO7V2UF0fi5nZ6QAhaEXqvBqL4ZmLdMuSZpr6wU6HValHOzt9jB5fJgaO807D1UgqG90zFvedOarkF6Z6WwfJaaahdBEAQhOgg+2/t1a8f9uZQyun8HaMOaxysIgtC2n9UJRj26dkjEgaNlivfjqvZwPqv9AYzom47V244p3mVY73Q4nMr7GNaH2+3jF/WTmDSkE8YP6siLSQ00PFeVFP8s9UR9Fnt3TeFgAgUmGiM3vwS3zx6IOLNesQIDFe4P75POPR2ZQAAj+2ZgzXblvgRat53umMQidocHw/qkY4EKOTK6H/2yjhUEoY0hUlFtDK/Hy9kbSqGS0klDO6nqxyBUSho57G44T73o36EGLQiHw40hvdORlmLhJmzUSyMrM4HlkhrivInd2JiNxQCcrcKFnC7JGNE3A2nJFsX7nj+pO1dsCIIgCLEJ2SvnT1Ru55BO+PC+6Zx0IAiCILQ85MB2Oj0soauUDqlx6Nu1HZxhtOM9Hi+mjciCRUVDcGqu7Wum9RfNS1RV4bC54KhwwV7h5D4Y1aGAAgWCJg/t3OT7UZBo/9EyTB2ZpfgYhvfN4IoOWtsSHrcXU1WPSY9mG5NYgsbkwknK7RWqKJ05tiv31hQEQWhLSOCijUEGEOliUjaIEq4/py9nb0iGeutCRqnH68NffjUB7z4xE3/99UQ8e+dEvP/kTDx6wygM6ZVWo28DVRZMGNyJFwWxCN2PtnInZyPdcuEART0raEzGDepYZXgLgiAIsYfb7cHoAZns4FLCzecPgMPhEekFQRCEMEL2+BnDOyOnc5KirP9bLxzAfTHCKTcUXH9de3ZfRduP7JeBnlkpYQ2uEH6vH1fP7IOkeGOT2/6w6iCumN6Lg/ZNQTJGN57bnwM41cfE6/PhmrP7KDq2Uf0zuTdhuMckWlQEOqXHY/LQToq2v3x6L/55OsmQgiAI0YgELtoYtDC321x49MZRjQYvyBFMhsrU4V3gcqhv4iU0H3QtrHEmeDx+/Lj2EG56+ntc8dt5uPyxebjlz/NxqKAc9141jAMYpKvaOzsFT902lhcEsWzYBO/lIb3ScdflQ1kCqiH6dK0cE7vdJUE4QRCEGMbnq5wbnrx1LCdqNAQ1GP31pYPZ0cQ9qgRBEISwQfa40+HBH28fz47thqDejPddNRz9u7VvlTUpVc6fNSYb181qPHhB8kkPXzeSq8LD3cuBEtWMOg3+/MsJjQYkqGr/nAnduN8fJcNRJX9jqgt/uH0c2iWY+DpVh67DzDFdcW0TwQuaXx++dkSrjEk0QENC9spdVwzDhMEdG9320mk9cdEZPfh+FARBaGtoAjKL1GtInTxpa7b30+u1SEmJQ3Gx7Wd9yFaGNDPJGb7zwEnMWZyLDbuK4PL4kBxvwuRhnXDBpBwkWI2w25zsBGiucyNHQVyciX8Gx5qcyf7IGJaIvG50nQ4cK8eT/1nZYPMukox6/KbRyGhnRXKCiaUyapcSR+r5nS50L1msJm5CPnfJPixYewgny5zc32NgTioumNQdg3um8X0WC9k+sXLd6kPOLfJJS0uIuHk2Vsa2uc6NeizRfgSZeBTEbmwej6bzMxh0/KKAPtkNlAXa0H5k55C9sXnvcbZz6KfX50dKgpmzfM+flFPZFNNGNkjzj4/cl9GJnFv0EgvnF4lzbEuPLTWXtlqNWL+rEHMW78P2/Sf4Wd0+yYzpI7Nw7oTuMOi07OBtCbeFknPT6bS8HiutcPExLtqQjzKbm/tKDO+dzvJQVGlBDvrmruyuPaeTekJDc5bFauTtF67Px9fL9uPg0TLuCNI5PR6zxnXl8aSkNpIwtliMMJkNWLIxH3OX7se+w6W8bcfUOG4APmNUNvwBqnB3tdiYqJnTY/H7HsRo1CEuzox9R0rxxaJcrNl+DE63DwlWAyso0FjS94HGMhYS8GLp2tVGzq1tzLFC+JHARZQbe6eDRqOByayHwaCH2aRnY4h+V2F3w+/1KdJ7VnpuBoMWJrMRRoMOuYdLcfBYGTes7tklhUskyYhyOtwRNT6RcN0sFgOKbR7c8+KiJhuukdbo3++bgkSLHjabOyrOrzkhQ11n0CHe+nOZtIuqTtyVDdNjRQYk1q5bdeTcIp9IdKrEytie7rnRfKE36DnAvXlvES9601OsGNgjlbMxSRM50qrwlJ4fObZ0eh00Wg027Cpk5whJYgztlQ6f3w+fp36bhQLbJpMBBqMOJuPPetwVVH3n8beodKDcl9GJnFv0EgvnF4lzbDjGtvJZrYfBaGDHd5AKm4v7AJA0bEuh5tzoGLX6yrVGcN1Mc67P4+XkqOZ0q9CcbjDqUW73YGvucbi9fk5QG9C9PTe69rh99fYypPOh/WjepCQuguZJkkSkNVH1c6Tgg9FEfgBDVXCEtj163IbCk3Z0TItHSqIZHhedn7ve5tr1jonTw9etoTHhOd2g4/fbsLsQNoeHkyeH9k5nO8WnwA8RC9/36lDwJmjrWMyGqrG0kV/GVzmWsUKsXbvqyLlFNhK4iF6Ud1USYg6aEKn0k14VGg1PmPS75g5lkdPAYjXgp3WH8PnCXOQXVtT4e4/Oybhsek8M65PBmY+R5lhpTXQGPd77ZnOTQQuCDOcPvt2JOy4ehLYIO6DcXjjtLuj1OiQnWzk7K1onVkEQBCXQ3G2JM6Go2IF3523Eup0FqB6nJQf/WaOzcfmZvdnx4IqyxS9lhXoDAbwxZyuWbMhn500QcnCRNvT15/Tj7Ry1ZEQoYE2/czgqkzVays4RBEEQQqfyWe3hV/BZHYkJR+xMJye+3cXHSXNJc+eA0vtSJUN+UQXe+2YHNu0pqjFnkRQUVU+QbBBVTtR28HMPCq+b/0bVDLQeKit11LseogCXz+tHwBTAvGX7MH/tIRw4UgZPtW0pUEL9LLp3TOJ1Ve3ronZMqCrE6fHj7TmbsGzzUa6uqfqbSc8VkTSnU6JCbYmqWIaGjO5/wAOX043k5DiUlNhYKloQBKGtIz0uBIYMDDJEmnsxT5UWFLR4/YutePnjTXWCFsTe/BL86e01+HJRLjtftFq5LYNlo26PD6u2HVO8z7LNR/gakqHaVmmJRYQgCEKkQlJ5e/NLcd9Li7FmR82gBVFa4cbHC/bg0VeXwUyVj9UqDyIds8UAm9uHu55fhAVr8moELQgK6n+/Kg93P78ILp+fsxXDbecIgiAIzUfwWR3J0DxSOZ8oO06qbCCHPa1z4xLM/JOC7UHp5OpY44zYnHscD/1jCTburhm0IEgO9/1vd+LJ/6zi92xszdfU8VGiFwVJ/vLuWrz62RbsySupEbQgtu47gUdfXc7rUbI3TmdM6JyLK9y46/mFWLThcI2gRTAJb97yA7j7hUUInFKGaIsEh1DsFUEQhErEQyy0KCQPtWDNIXyz4kCT2777zQ5syz2BuLifpX7aMjqdDtv2nVBlvJOxuTuvmA1kQRAEIfYD3F5/AE+/uaqOU782uw4W4x+fbGRZiGiAHDqke/6715azo6Yxikoc+N2/V/D2lPEpCIIgCBExj8WZkJBoxsptBXjxww3441ur8Y9PNmHrgZNcDUHBh+C0RbJLFQ4vnnlvLbxN9KaiSow3vtwGg6nhgH1TGEx6/O+7nVjdRJIcrUXp2E+UORtNEGgMWpvSvo+/tpzlHhuDpKr+8OYqWC2mqrERBEEQ2i7i3RRaDKqcIKcKNZlSyqc/7YFWnO4MGWpOBX1GauN0e8VxIwiC0AYgLeS5S/dxPwslLN5wGB5fgOfmSIccONTP4shxZTrtecfKsW3/CZjbaIamIAiC0LJBCHK+00vJMou2j08wY/nWo7j299/ipY82cNXC5r3HuUKeAhi/ePoH7D1cCmu8md+T5vTPF+2tU/XQEPNX50Gn1XDlhFroPEhucZ6C5ELC5w/wOp2OMRQoaWLppsM4Udp4IkKQnQeKkVdQxpLTgiAIQttGPMRCi0GVE1RyeriorjxUQ5AxR1kYlDXZ1qFS29Rki+r92idZRCpJEAQhxmEdbKsR3608qHgfcjx8u+IAtDpdVPR4mrt0v6p9vlqyn5uECoIgCEJzBdFJ2imlXRxXT1AwghrUUqVEsKF1fdC2C9Yewt8/2ghbA72lqJrw96+v5IpIej/6rB/XHlJ8bC6Pj7c3hJCMQJ+1fPMRboytlCUbDkOno0CJNqTP+3q5ujn9yyX7oZGERkEQhDaPpKUJLQYZNvuPlqneL7+wHH2yUtDWoWZn/bu3R0qCCcXlLkX7pKdYkNM5CSXF9hY/PkEQBKH1oGxOt9uneH4IcqigHIiCojyTQVdvX6zGoEQJo0EHZTUagiAIgtBYk2wjHG4f5izYzdUN5fZKJ3/n9HicM74bzhyVBY/bB4fDXbdPodeP1z7f0uTnkAzTcx+swzu/P4uDCPYGghwNcbCgPKReCKREfOBouap96Jwo2GI1qA8mGPQ65BdUqPYJ6CVwIQiC0OaRmUBoUULxjYjM0c+GrMPpwcyxXRXvM2tcNzgcnohvaicIgiC0DjzFxugUwacWo+cmCIIghG+etMabsGF3EW7+43x8vjC3KmhBUFCdghK3/3UByhwerpaoT8ZR6XqM1AZWbD4CQwiVDKczpYe25A59na7282h7mdIFQRAECVwILYbPF0CPLsmq9tFqgKzMBPh8yvS6Yx2vx4dLp/ZE367tmtx2UI9UnD+pOzxu9X0xBEEQhOiCHCJUXZCmUlKwW8ekqGh26XJ70bVDoqp9sjokwO2ROVAQBEEIHbPFiNz8Ujzz/jp4fQ33mzhe4sQj/1yGADQwGn8WsiAZx0UbDqv6TJKV0mo0SIxTJ5fcvVMSr5/VQvvkdEpStY/FpEf7JDOv8dXi9viQrXJO75qZCF8j4y8IgiC0DSRwIbQYNpuTnQ5qHA9De6fDajbAXi2rpS3j8VSWHz99+zicMbwLN2CrjV6nwYzRWXji5jFw2N3wKmzoJgiCIEQv1MvI7nCrqsqjbM4Zo7M5KB7p+Lw+nD+xu6p9LpiYA7/MgYIgCEKIUGCf+jG8NXeboooJkk76bOFe6E5VS9D+FIAoq1An41ha4YZGq8H0kVmqAglThnUOKWnN5fJg9IAOSIpXHiiZTJ/l8YUUTHC7vKrn9PMn5SAggQtBEIQ2jwQuhBbD7690vF8yraei7cknf9n0XpWim0KNXhcUkLjj4kF494mZuGZmH0we2omNx+tn9cV7T8zEzecPgN3u4m0FQRCEtgEFIGaN64p4i0HR9uQQIacKzc3R0uepW0dlyQ+9slK4ypOcMYIgCIIQCiaTAUeKbNhzqETxPj+sPgiz2cD9HYNyhaZqFRhKMBt1HCi5cHIOBySUQH02aD4PJWmNqiacLi8H/JVg1GtxyRk94A9RFYHm5lH9MtEhNU7R9kN7pSGzvRVOp8zpgiAIbR0JXAgtitPhxtgBHXA5BSQagRwpt180mEtWKyocYTu+aMHt9qKizIGA14tzxnXFbbMH4rYLB+CsMdnw0t/KndykVRAEQWg7VAYgAnjq1rGwmht3dAzrnY5bLhwAd5Q4AciBY7e78dSt49ChfeOODmqUGqw6lB4XgiAIQqhotRqs3Vmgulri6HEbdDod/7/T7cWwPumq3iO4PQUIHr9pNEzGyvdqiHEDO+Cqs3pzJUOoeFweXDglB1NHdGl0O2qQ/fD1IxFvNcCpsnl4jTnd4cYfbx+H1GRzo9tSwgJ9Hs3pgiAIgqAuFUAQVEIZIGR0UCVFz6wUfPbTHmzff7JGwGJor3T+e4/OSbDbXFyp0ZAhSS9ySoRD79J4ymDU63URI7/EwQkJUAiCIAincNjc6Jgah5fvOwP//X4nlmw4DHe1OYuyG88d3w1nj+sGh90VFdUWQSjT0mIx4MV7J+OjH3Zj/po8bmIahCQuzhyVzTaE1+NtNDNTp9OyzUHOE6UNUwVBEITw0trP6sCpfgxqoX00Fj0fu9mo52qI+avzFMs4UjIaSQI77R7kdEzES/dMxn+/34X1uwqRkmDmbcpsLlhMBpw3oRumj8ridbPXG/qcTutbW4ULv750MPdK/GJRLg4cLav6Ox3P6AGZuHJGb6QnW/jzGkLJOt15qpH5S/eegQ9/2IUf1+TBVi0Q0i7RzONw8dSenGQhSgKCIAgCIYELISzVAn6/H4Nz2nPG54lSB/ILy6HRaNCtQxJnb/h9flSUO+oNWlDprVavZUONMlgo64O0Q50uD2eZNGcQw2TSwWQ2QqutLEayOz2wxplgMOq5l0RZmR3SN1wQBEGIJMiZYDEbcOsFA3Hb7EHYk1cMp8eH1CQzsjMT4XB6eI6NlCC8GhwOD4zGAC6d1hPXnt0Xuw8Vo8LuQYLVwAkRFKxwO931Vh2SA8xo0rP0B/UEoSar5FByuDzcC0MkKARBEFofvV4Lg0HPaz5/9We108PSRKFm+YcCSRe3T7Ko3i85wcSBFnLc00+qFKT+EwvX5ze5L81vtL6ll8li5J+Z7eNw52VD+N8k6+TzV45JZVAlgPIyZ7OsgSmZobzMgdF9M1iGmCpHCk7YOHGPGn8b9Br4PD4OcNSGgzS8TtexNJbL7eUAC40BrdFJHqp28IkSGqmHyFUzeuPGc/thd14xbA4vJyKQ3CPN+Q5bdCVZCIIgCC2LBC6EsEDOkvJyJ/87wWrEwO7tqzIySkvs9e5DOqHWODMHOj5flItF6/PhPOWYyOmchPMmdMekoZ1Zjqo5nA+JiWbo9Dqs3HoUXy7ehx0HKitDyACbMLgjLpzcg+Uo3C4PG1WCIAiCEClUzoMeGAw6dMtMqMpYLS62s9M+2hMg4PZyBmaX1Dg+NzqlslJHg44bcqZQZueSjYfx1ZJ9VXrlJL8xaUgnzJ7SA2mnMkjDUcUpCIIg1P+sNlsM7OCnZ/X+I5UZ/9TngRzpsyfncMVBZVV+y89lFASfOKQTXvtsc43qxcbo0zWF17fBNS1JIm3YXYRfXzaE599FGw43GrS4+Iye+HjBbnyxMBcuj4+D9BdM6o7FGw5j7tKaY0LBkNlTcpAcb2q2MaHAiIPX024kWfRIyUquXKd7vKiw+xoMNsXFm5F3rIzX6cs3H+WAE0H9qej4R/bL5GOsXTnB/++iOV2LrLT4qjm9pNguFZGCIAhCHSRwIYQd0qxuCio1JWPomxUH8OZX2+poVufml+LFDzfgs4V78ac7xrPBS+WnoZKUZIYvoMFjryzFroPFNf7m8frx07p8fl08tQeuPqsvG6HhzP4RBEEQBCVQlmKsZipSgEFJkIEcYdBqce+Li6ocPkFcbh9+WJ3Hr+tn9cV5E7tznyhxlgiCIIQXWr9RbOA3f1uI/MKKGn9zuLz4dsUBfL/yAG65cCBLI9nC8Kym+dNoCmDSsM6KpZ6owTUH2E/h9fgwsn8m60796tIhmDW+G+Yt24/V2wtYPYCCHMGkOKoefODlJdh3uJT3vf6cfhxcv/uFRfWOCa2Nv1t5ALdeOBDTmnlMaL2tRJ6JqhnjE8x4e+52fLlkX52/b9t3gl8UwHjiljEcmKhv3ax0ThdaHvK9UCVMdbkvkeoSBCFSiKrm3Pv378fQoUPx2WefVf1ux44duOaaazBkyBBMnToV7777bqseo9A8mMwGLNl0BG98WTdoUZ28Y+V49J/L2ElBmR+h9rKgZmq/+/fyOkGL2nz6417MWbQXeqMhpM8SBEEQBKHlIIeK2WLEo68uqxO0qM0783ZwUgJJcwiCIAjhg9ZtRpMBj/xzWR0HfXXIJ//a51uwausxXh+GA+qZRIEBqrRvCqoKoT4QrmrV/9R3giSe/vruGtz4h++xbNMRXDGjDz7+0zn48rkL8MFTZ+Oqs/qg4KQN1z/5XVXQond2CmaN64rf/XtFk2Pyr8+3YM228I1JdcxWI/7vxz31Bi2qQ8GLJ/+zElariR3iQuRBkmBUnZqcbMXeI2VYvOkoVu0ogNMbQGKShfuMUeBJEAShNYmaiguPx4P7778fdvvPskLFxcW48cYbOWDx5JNPYuPGjfwzLi4OF198caserxA6ZNiQVvd783Yo2j6voBw/rc3HuIGZ8HqbruaojcVixNqdhdh5oPGgRZCPF+zB+ZNyeCIXyShBEARBiByMRj2Wbjxco8FoY7z/7Q7O5CUZKsn8FARBCA/UP3D+qoM4XNSwg74678zbjglDpnOAoKWrLijTXKPV4G93TcLz/12P1duP1UmkI9nBc8d3w9Uz+3D/h+rHRAl1+4+UYs2OAv5/cvDTK85igMWkY+mrP/9qAp59f10NOSpq6E3VgErH5K2vt2Pc4PCMSRCSo6Q+lf+3YI+i7bfmnsDWfSeQ0yFB1s0RBlVYUNCCEjOpkudkWaWsd5BBPVNx7cy+yMpIYMmvaJcdFQQheomawMXLL7+M+PiaWQ8ff/wxDAYDnnrqKej1euTk5ODgwYP497//LYGLKJ9EydCrPXk2xldL92HqyC7c76K+OZWMLP0pQ4sMUTbu/KdKIDUafLkkV/FnUZnugjV5OGN4F0AMMEEQBEGIGExmfZNZoNUprXBjxZajGNqjPRwOCVwIgiC0NJTBTUlqc5ftV7xPUbEDm3YXoVfnpLA4wEmC2GQK4P5rhsPm8GDesgM4dtIGnVaL3tnJmDYyC36fn6UGqZdjdahZ9ReL6q4t6X3oNXtyDw6wl9l+TrgjyajxgzqybJaqMdlzHL060ZioT94LBVpPf7fyoOL+H8ScRbl48NoRsm6OIMg3QkGLJ/+zCpv2FNW7zeY9x/Fw7lK+dkN6ptbboF0QBCEcREXgYs2aNfjoo4/wxRdfYMqUKVW/X7t2LUaNGsVBiyBjxozBa6+9huPHjyM1NTXkzwxVdqgh2YLqP2OJlji3gEaD9TsLVe1DmZVu0iQ16mtkTNJxUUYPWcjfrzyIDbsL4fb40S7RhBmjs1l7k2IYSqstgmzcXcSNwZvzPgk3cl9GJ3Ju0Uksn1uoNNfzM5bHNpbPrSXOL6jNvDe/shG3UtbvKuRFudh+ypBzi05i+dzawvmpJZKfZ/Q+Nqe3UTmk+li3sxC9uiSH7dxoTemwuWAy6DB7SncKuXDWuVajqVGlV/t4rGYDNu893uBnZndIxI9rD9X4Xce0eA5kKK22CLJuRwEHc+obk5b4TlAC4Mbd6tbpm3OPw2zSw2nQNioBrYZY/r6H49yMZgNLcjcUtAji8we4MuhfD01FvNVYo5dLqMi1i05i+dyEyCfiAxdlZWV48MEH8dvf/hYdOnSo8bdjx46hV69eNX6Xnp7OP48ePRpy4IIWvikpcWhuEhMtiFWa89yoosHtVd9Y1OsL1DkOyoAhDc5PFuyukxmyaMNhdGgfh0dvGInHfzGaNTi9CmUiXB4fZwu1xH0SbuS+jE7k3KKTWD631p5nY3lsY/ncmvv87NV0xpVCiQ96nQ4JKSY0N7F87eTcopNYPre2cH6xspYtVlFZX/1ZrdPrEB8X+c9qavLdEEaDrs5a16iv+7vmGpPmPDenywuPimqL6mORnBzZ92Sk0ZLnRk3i569R1nye/COfLcrFjef2Q0ozfvfk2kUnsXxuQuQS8YGLJ554ghtyn3feeXX+5nQ6YTTWbKhoMlU+TF2u0EvZSEaorOznXhqnC0Ul6QteVuaIOf3kljg3g8mAdolmVftQAzSLSY/SUnuVxmdcvBnvztuOOYsblow4esKGB15egj/9cjx+cX5//PvzLYo+r32SmTNGiottiFbkvoxO5Nyik1g5t+ZyhDTnPBsrY9vWzq0lzo+cdfEJFs6OpQQDpZDN4fP5UFzcfDIIsXzt5Nyik1g+t1g5v0icY1tibOn9rGYjdFoNZ3QrpV2SGf4oeFYnJVmRkmiGzVl/9USF3Y12CTXXuhUON5LiTM06Ji1xbtRQnc5NDcHtm3PdHAvf99Y6N5PJgIUbD8PlVm4n/bT2EG45f0ANX0uoyLWLTmLh3GIh6bitEtGBC5KGIjmor776qt6/m81muN019RyDAQur1Xpan11bq7I5oC94S7xvJNCc56bT+XDW6Gx8orDpFzF+UAfO5nCfmoCpcXZ+YXmjQYsgTrcPL324AX+7ezL+991OlNubztYkmSmTQQt7RfRfT7kvoxM5t+gkls9NLc09DrE8trF8bs19ftS7asKQTtyLSikzx2Qj4A+I7acSObfoJJbPrS2cn1Ii+XlG70FSvqP7Z2L5lqOK9qFKd1p/+bwtc32b876xO9yYNqIL3pm3o96/r9p2DGeP7VqjH9PBo2Uc0BjVP5P7LqkZE6+n8WNvznMzGPy8Tl+0Pl/xPlOHd+Fzi/TrFmm01LnpDAEcKihXrYhRZndDG2i+Z4tcu+gkls9NiFwiWqDs008/xYkTJ7ivBVVd0Iv4/e9/j5tvvhmZmZkoLKypsRj8/4yMjFY5ZqF5nA6UmTGop3Kprwun9OBsk6aaojXEwWPl2JNXzI3WmiI7MwE9Oic3ayZTKOh0Gg7QxMUZYbUaub+HIAiCILRlfF4fZk/JUbx9v27tkJZihTMEiSlBEAThdJ7VPRRvP6x3OuItBl4nRjpejw9nj+sGQwO9OMjp3yE1Dr2zU6p+R0ns3648iHPGd1M1JnEWQ7P0HVCK0+nlebNjapziSsjzJnaHT0UVpNDyaKAJYR9BEITWIaIDF8899xzmzZvHlRfBF/Gb3/wGf/zjHzFy5EisW7eOy/uDrFy5Et26dUP79u1b8ciF04UcCPddOQwpCU3rKF4+vRe6pMdXOR3IQDIb9Vi66Yiqz1y84TAbgI0RZ9bjketHwuP1odptF1YMBh0scSYkJlmxO78UizYeweodBfAEgMQkCwczBEEQBKEt4nJ5kJFixdUz+zS5bWKcEfdfPVyCFoIgCGGGHODdOibiIgXBC5Lzu/uKoXBHQdDi554OAdxz5TCuiqiv2n/O4lz+O81DQb5fdRBZmQm4cHKOItniu68YBk+Yx4Sak9sdHjx6wyiWaW6KX148CGajLqzBFaFxtBqge+ckVfvQfUqvaJUIEgQhuonowAVVTWRnZ9d4ERSUoL9dfPHFqKiowGOPPYa9e/fis88+w9tvv43bbruttQ9dOE1cTg+MOi1euGcy+nevPwhFWTc3XzAAl03vBVuFi3tOEBqNhpubqW0cVmpzoUtGApIbCJbkdE5iOan2SRaUh9BQrjkwmfSIizPh84W5uOGp7/D711fin59uxvP/24BfPP09/vjWahwtdiAu3lSvoSwIgiAIsQzZAnabC7Mn98AdFw2q4RSqTp+uKXjxnsmwGHVscwiCIAhhdoDbXBxkpqa/VDlQHwNzUvlZrdNooirI7LC5MaJPOn77i9FIS67bzPZ/3+/C4cIKvHD35KrKizKbG0/9ZxUn5V1/Tj9OmGtoTGg/naYy2S/cOB1upCaZ8dxvJnLwqaFg0wPXDMfkoZ35OguRg8ftxeShnWBt4P6qj+kjs1gu6nT7WwiCIIRCVGvLUADjP//5D1dfzJ49G2lpaXjwwQf530JkYjYbOMxPzX3IuRDw++H3+est+3U43DCZDXjq1rE8UdKLSm6pYZnX50c6STu4vKgopwZBgRqGsEGnPiZHVRqUOfL24zNYe3TNjgJuWkWBjDNHZaFLegK8Ph/KyxxoDUgKymwx4revLcf2/Sfr/J3Gc8PuImzJPYHHbhyJvtntxFAUBEEQIgqqiqTGkGQL0L9pbqdmnxqN91SW6ulDGYFkG0wa2on1v5dvPoL1u4u4WjIlwYyzxmQjo12lPJTDXrNXmiAIghAeSCe9otzJPRNIToiq37fkHufkM0oUmzW2KzefdjrdcDo8YV936fRaaLQaToqj9Sr1QqKqvmCyXGPQepQS6/plp+D1x6Zj4+4iLN98lOe8hDgjpg7vjJzOyTzv/fmX43HshB3frTyIk2VOfLYwF+eM74oLJuVg8Yb8qjFJTbZwbwwKClDwINxjUh1aY6bEG/H8XZNx8FgZ5q/JQ2mFm6srqHfJiL4ZcDg9sFU425yzu9LO0dM/uNk6nT/dDxQwiITeAHQM5OM4d3w3fKygpyj5R+heFLkvQRBai6gLXOzatavG/w8aNAgfffRRqx2PoAwKQJCEUcFJO75asg/5RRWsrUhZGudP6s4SR5TxWDuAQVUDNOFTAynS/TxR6oBRr8PAHu1x9thu/DcyJqkcNwgZB15fgHtkbN5zXPExjhmQCb1Ow0ERyoyZNa4r9Dot/79OS4Yr4HG2nrFhNOnx6meb6w1aVIeO9y/vrMVrj0xjo1tKcwVBEIRIgILvVosBm/cexw+r81Bc7oTJoMPQXumYMSYbRlOAnTHNIUVAtoDD5oLb6cGwXmkY0isNVeZCIIDSktbtUyUIgiBUBprJCe5yajG6bwZG9s2oelZTglu4n9W0djJZDLA7vPhiYS725pfwfJLZPg7nTeiGTunxcDg8iir1yFlNwXHatnfnJPTqnFzZKCBAPwIoKbZVBUGSrQZcPr3nz8dh0MHr9XHiXHZmIjvDaY1Hx8LrX9L7aWUocELnlpFsxlVn9uZzo/Oh9MGSEnubC1hU2TlWA9btKMSPaw+xogMlR47sl4FpI7I4CdLFdk7rjo3H5cEVM3rjyAkblm5sWF7bZNTh8ZtGw2TQSkKkIAitRtQFLoTorLLQ6LR44vWV7KyozqY9RazxOXZAB9x71XD+XTB4YbEaUVzhxoOvLEN+YUWN/dbvKsQH3+7CBZO6c4kxZbRUz9T0uD24YGKO4sAFVVWM6pfJjpT/fLmVsxBqk5ZiwcPXjUSntDjYK1xh72tBlSYL1+Ur2t7l8eHLxftw6bSegAQuBEEQhFbGGmfCsZN2/PmlxZzEUJ11Owvx7rztuHR6L1w8pQcqKpzNlpVITjGq4BQEQRAil0h4VlOWPDmeX/54I1c6VPe70xqWelCQzOBjN4zm7SjQrjiQ3kR1RFDyidZ8JPn7ztfb8fWy/ZyMV5usjAQ8duMoJFqNrV41SIGKps5NCRSs0lKioKZyvKIx6EHXbf/RMjz7/jqcKK0pK712RwHe+mobrj27L2aO7cqVRq3ZL4JsLApE3HvlME4eIX9M3rHyqr9T8ub4QR1w5Yw+SE4wciKIIAhCayGBC6Hly2wNOtz30uI6wYfqBs/yLUdx8rVl+NMd4zkDQW/QotTmxv1/Xwy7s37HO2WdfPrTXlTYPbh19kCUlTo4syUY/BjWJ501QKm8tiluuWAADhdV4JX/29TgNkXFDjzyylL85VcTkEkSE2E0rvUGHQdV6JyV8sPqg7junH6c1RGNxp8gCIIQG5ip4rLYjof+sZQD6/Xh9vrxwbc74XB6cdVZfVBeZlckxyEIgiAIpwvJGFusJjz1xkqWdWqInQeKcd9Li/DiPVM40FGf3HGoUFUFOb9f/ngTflp3qMHt8grKeW1NvSCpN0hrSkadLnq9FgaSazYbeJ1LfgCzSc8yUz6vr1nHtyUxW40ctPjtv5bXG2wKNmV/fc5WtoPOm9C91eSng7jdPvh8Tozrn4mpI7rgSFEFCosdMBq0yOmUXBlE8vrCnrApCIIQVc25heiHHO7vzNvRYNCitiFIVQIGo46rNF7434YGgxbV+W7VQew5VAxTtQZT5KinLILf3zwag3umNWog/vrSwVxt8fhrK5r8LHKsPPP+Wpa6oH3DBTlvSC5LDeV2Dxt94TxOQRAEQagOyTlaLUbOQGwoaFGdzxbuxdHjFZV9MARBEAQhDOj0Osxfc7DRoEUQcu6+PmcL9IbmzQGleW9r7olGgxZBKhwevPThhqieK1lWKc6MxZuO4M6/LcQlj3yNy387D1c+Pg/vfbsTdo8f8QnmiF/L0vFZzQa2cxoKWlTnvW92cCN27oMRIZVOJFtGcmV9uiShW0YCS0nZyp3NUk0jCIJwukjgQmjZDAqDDj+tbdr4CjJv+X7uhVF40o5decWK9/tiUW4d45EyNEh388lbxnDTM2oURs2lyLhon2TGpVN74u3fzcDkYZ3x0fxd3AxNCdQ8bdu+E2E1NsgEYr1XtUS2nScIgiDEOGazHrvzihUlMAT5fFEuO5EEQRAEIRzQum7ukv2Kt1+66Qivs2it21zojTpe0ypl674TLEkUCQ5wtVgsRjjcPvzq2R/x6qebayToUeIiyWTd9pcFWLLpCKzx5lM9LSMTGv91uwrryEM1lpBI0kzaCLJz6JjId0KBCpItqy7BLQiC0NpE3ywnRJVM1LqdBXCoKPGkDJaDR8uRX6iuumD19gJuVEZlvtX1ImkCpjLIrhnxuP/q4Vx6GqTC5oLf5+eGWV8vO6Dq8xasPYRu5/dHOCOM3TslqdqnXaIZVpMBxa2sfSoIgiC0XQIaDeavUZ7AQCzdeBh3XzEUDrtGpA4FQRCEFqeo2M4STErxeP1YtvkIxg/IbBYnLyX8kfN4w+5CVfvNX5OHCyd2RzRBwR6dXotHXlzEa/+GoPn/H59sRFKcEf27tWv1fh4NotXiR5V2zuKNh3HLhQOld4QgCIICpOJCaDEoM+JkmfrJuKTCpdpRwU3PXN56szGo7wVlD5CO5PHj5ThxogJFReVs/Hi9pO3oVxVcIUorXNCGMfPD4/Fi2ogsmIzKMzPOGpMNu/S3EARBEFoRmpdJEkENJMvo9vgjOsNSEARBiB3UzlNEcZmr2Xox0Xxnd3pUv19ZhYsr86NNSvqrpfsbDVoEofF4a+527oERqTYBqTmovX/ougX3FQRBEBpHAhdCi0EBA2u1vhNKsZhCK5s0GnRVzbkbPqbKIEf1/6cqDb1OndFAVRrhjAd4vX4+7pljshVtT43azp3QnZuaCYIgCEJrQfOyWUXQnSDfhIGzT6PNHSMIgiCEE5LpocbIcfFmflmsRu6VqBZa26nex6QLTcq3Hmi+o7WsWkxGfdQoA3MvCKuR195ThnfGKw9MxX1XD0O/bu0a3e9wUQV2HSxm6clIhNboau0cum6E2DmCIAhNE5lPfyEmoGqGYb3T2UhRmvUfZ9ajR+dk1dUMvbJSOPhQXSZKCXRcTpcXQ3unY832AsX7Ub8MTZjzW9wuD64/pz8KTtqxcuuxBrejPh7U14NiMXa3BC4EQRCE1kMTCPCcuXB9vuJ9hvRMg8frk4pBQRAEoeGAhcWI4jInvvxxLw4cK+OmgJ0zEnD+xO5IS7bC6XTD5VRWVd85PR7JCSaUlCtTC6Cl6tgBHTi5rDmgNWyCUY9uHROx/0iZ4v3GDuwQ9jVpyI24LQZs3FOE+avzeJxJSWBwzzQ8/ovRXH3xtw/WNSjXtW5nIbpkRKgklj+Akf0ysGaHcl/C8L7pcIRQYSMIgtAWkcCF0GJQb4mERCM7LFZsOapon6kjs3g/Cl5ktLOyk14JF0zq3qBhqtNpuLSUDIP6AhtejxcXTs5RHLhIsBowcUgnlJU1Xd7anJB+qt3mwoPXjmCDj0psqzcyM+q1mDi0E644szcSLAbeVhAEQRBaE7fbizEDOyAp3ojSCmVSCjQne9zqJBwFQRCEtoHJbOBein99by1Wb6uZzLV573HMW7YfQ3ql4eHrRsJs1nCz4aagRLazRmfjo/m7FR3DoB5pSIwzoqy0edaDtE6l46Sgy0sfbVS0T6e0ePTJTkFxsbL1cmthjTPh8HEb/vLuGhTVkoeigMQH3+7EpdN64q+/noBHX11Wb+DGTSoCEerkJ0nnqSOyWNJKqfz07Mk9RBlBEARBISIVJbQoFBS48dx+iiSjqJn0FdN78SROGQjUsEpJ4UWfrikYN7AjO0eCUKDCYjEgIdGCxCQrDGb6txmJSRb+fXU9SWrg3a9bewzvk67onG44tz9cbq/q6o7mgM6xvMyJiYM74uX7puAf95+BJ24egz/9cjzee3Imbr1gIOKMOglaCIIgCBGBzxdgZ8zN5w9QtD05mwb1TOO5WRAEQRBqN3YmKShycNcOWlRn4+4iPPjyEhiMeg5yNEXA78dFZ/TgxLmmMBl0uPn8/jXWns0Bvd/kYZ05ga8paCl76+yBp/piBCK40sKAI8dteOSVpXWCFkFcHh/e/3YnPv1pL35/85h6ZZfITxChLS646sbr8+G6WX0VV8l075ikKKAmCIIgSOBCaGGoKXai1Yg/3TGes1IaIj3FwlkWZISRs8Lp8GBQTnvcd9XwRvtPkCbmU7eOg8PhqgokkEGblGzB/mMVePaDdbj44bm48rff8M+n31qNnYdKkJRk5RJjgqQoyNH/6A2jMLJvRuMG4oUDMHloJzgd6hu4NRfcTNzu5uyalDgDendJQtf0eLgcHtgqnGIECYIgCBGFy+nhqotfXjyY59KGGNorDb+9cTTPySITJQiCINTX2Pmzn/Ziz6GSJrcl2aH3v90BnYLeEVTZ7vP6eT1KlQyNyRo/detYpCVbeL3a3Gs8es+nbx+H3lkpDW6n12m5Ar9vdgpcrbgmbQpKJLRajLwedyuQ1Pq/H/ewhBQFb6qj02owbWRWRFcoOO1uzBiVjevP6ddogIWCFg9cMxw2W/M1dhcEQYh1RCoqhtDrdTAadadkkQJsgNGrpSDHPwUJgv/2+z31OhrIAZGRYsGbv52BpZsO42SZkw0QbpQdADLbWzB2QEd2uJNDnqDjp/1G9k3H2787C3OX7cOPaw7hRKmTG5f1796e5aEG5qTyxB/MzKTjocZsL324Hos2HK5xHPR5lH1DL6quoEAF/Y6yW4L7P3rjKDaEv1i0Fxt2FXEGSHK8CVOGdcb5k7rDatKjotwZEQ4VqhrRarX8k8aLJLG8EZigSvcGNWEjI47GjcY6EsYv3NB3k76jwe8n3XfNpYsrCIJwOtDz2WSqrEZsiWc1vY+t3IkpwzphzIBMfLlkH35ad4gdFDSnk8b1hZO7o3d2O577pdpCEARBqA3NURazAd+sOKB4n/lrDnGPQLfTU6Nant6L1ih6fWUeJ1Vl2O1urhD4xwNnYOXWo/hqyT7k5pfC5w+gQ2ocZo7Jxpmjs+H3+Vusup3WwyYzOICyaU8R5izeh+37T8Dj9SM12YLpI7Mwa3w36LSArSKynd/UTHv7/pM4etymeJ95yw9g1viu+G7lwarfjRnQAQadBhX2yA1ckJ1TUeHEueO7cZLj0k1H4PX5OchEP6l/54CcVOR0SmLfRXNX6wiCIMQyEriIAdgxbNBBp9Vi7c4C1pCOtxgwom8GjGYDfB5fs2Xhk9OVynNNZj33n9ixoxBeX4AbmvXr3o4rLDz1OGS9Hh90ei2mDO/MgYEDR8rYOUJNtbtkJPD2pA9Zx9FR4WKH7wUTuuOqGX3484M6pCRDVVJir+FYsViN+PcXW+oELWpDeprPvr8OD147nD+XjD5ylFB/jS6pVtx9xVBYTIaq7Svsbh5HClq0NhSc0Rt1MJsMHISh68DNzXqkshQWjT9dh9akxn1ywo4dB06y0VZ5n7Rv8D6JRWgBpDfo4fb4sHpnIexOL9onmjCsTwYHFum7IcarIAitATtu6FltMuBwUQV25xWztFN2ZgJ6Z6ewbKPb1TzSiLyoL3eyc+jiKTmclRikak4vtke05IUgCILQetD8QetISoJTis3h4QBAny5JcDj8HKgg+SiSDt6ae4LnPoNei/7d2iM12Qq3y4OyUjuG5LTHqH6ZHFwnKHjhcLg5s97bwpn/VKVI66RenZPw6A0jYToldUXzo40+3+Pl5LpIJ6DRYMHaPFX7LNl4GHdeNoQTB0sqXMhsb8WvLx0cFX2v2FYKBBBvNeKc8d2wflchJ12mJJgwtHc6S2AFAn5Z9wmCIKhEAhdRjsViZKPgjS+3YfHGw3C5fzZiKMI/blAH3Hhuf3boB6sZTsfBQc21dh4s5iZau/KKa/ydSmbPndAN503sDrvNXTUpkwPbbDFi/uqD+HxRbp2si24dE3HZtF4Y1T8TDjtlINQ0xPj/3T4+/mB1QX1+DTJmKxwefL9SWRYOZdIcLqxA+wRTVWCH3pud/g4PXAY3kpPjUFxsixgHOwWp6Jp/+MMufLvyIMpsP19TiulQ1irpa3ZKjYfd5myVLBy+T+LNHKz4bwP3Cd0jdK9QtlLt6x1L0PelxObG259sxurtx2oG2Ux6TB3RhZ13Wp2m2cvNBUEQGoMq4egZRQ6d//2wi7NKq0POggsm5eCsMdmcRNBcFZxsG7jBczoF4pOTrTz3R8o8KwiCIEQmtNYprVBf6VBc5oRGk8xrRZr3qLL+62X72alcnb5d2+GamX3Qs0syr1FoTRhMmgt3UJ3WDPT5lcdQmRQWbRXrdMxlFer8D9TcmoIy8VYDcjonsWw09R+JhkrMxEQLyJJ55+vt+HHtoRqNuml9TIEw6v3ZLtGC8rLmaeouCILQFpDARZRncrv9Adz/90X1NruiDPfFGw5zVv4zv57AvSZC7c1ABhMZelTJ8M9PN9XrEC8qceCtudux40Ax6276/f7KzHuLEf/6bDO+X/VzyWd19h8pw1/fW4urzuqNi8/oCZ/P2WB2Z2MGG1V0fP7TXpafUsoXi3NxywX1NwyNtKRPMrZpLB/713IOCtQmKIVF2UOUnUP9P+whGPenQ/A+WbjuEF79bHOD98mbX23DzgMncf81w+H3O2PSYUXBwiMnbHjs1eU1DNcg9DtaNJHT8NnfTILJHIDLGflGuSAI0Q/rTseZMG/5fp636+PYCTte+3wLdueV4M7LBqO8rOG5OVSkukIQBEFQCk0ZlPijFqulUgqR5r0/v70aa3YU1Lsdra8ef2057rx8KMYP7MC9AyNhnqJDiITjUAsds8nUdH+R6pCcNDU/f/q2cRy8oOqT6AhamOFlv8xi5BdW1OvDoKRJWvf96Y5x6JyeIMELQRAEhUhz7igl2Ozqyf+srDdoUR3Kyn/8tRVstFEfhFCgqokjx214tYGgRXVoUv5kwW4YTAaWqqJKi4aCFtX573e7sHnvcVitDTfxbqpZG+2vBtqetFKjAaNJj39+urneoEXtgNVf3lkDp9tX1YA8XNB9crjIxoGqpu6T5VuOchM2KteONbgM3aDDE6+vrDdoUR0ybul6mc2h3feCIAih6E6T3EZDQYvqUC8K0pymOUgQBEEQWguSaKJeSGqCF6RAQHK6lF313+92Nhi0CEIJcC9/vBGFxQ6WURRCRxMARvfLVLXPsN7pcLm9MGiBslJHVAQtCK1Ohz+9s7reoEV1aF34+9dXVvpyrHJ/CYIgKEECF1HsdCAt6n2Ha0o7NARlua/ceoyz9kNBp9exk1lpNQNlkptNeu69QPJQSvn0pz1cOREK1PSK+gioweOpbJYV6ZATnLRVF63PV7S92+vHnMW50OrVZbmcLiHdJ+bQA2qRCgVj5q/OqyHl1RiUfXO8xMHfa0EQhHA8oz75cbfi7Wk+sZzKWBUEQRCE1oAqtCl4MXlYZ8X7kGwyZfFTUpHSpt6UHV+5Jg3vOirWIGnICYM7IUGFg/6CyTnczyJaAhZEcrIFBSdt2LxHWQIlrQ/nrzkInV7WfYIgCEqQwEWUotFp8dXS/ar2mbtsHwxG9ZF9MvTIEU2VFEqhCTnvWBn25JXU6WnRGCRzRI24Qqm6oEqDdklmVfvQ9rRfpEPN139YnafqWMlxTtUk4XI06fU61fcJNZJfve1YzGU0kYNvnsLFUZAvl+wjAdQWOyZBEATCaNTB7vSytKBSqLKT5udwV/EJgiAIQnV8Xh+uPqs3khNMTW4bZzHg+ln9OElt+eYj3KhbKUs3HeEedLQOFkKD5CWdbi9+cV79ssy1Gd4nHf27t4+qoAXh8QVU+2W+WX4ABiorEQRBEJpEnpZRikGvw+GixksRa0ONqKkCQi1arRbHSx3w+tRpazpcPhw4Wqb68/ILKrhpqFr8Xh/OHJWtap/pI7OqGnNHNAHgUEG5ql3K7R7YnZ6wBS6oaqKoxM6VIWo4eKyMTi9moPHWabX8fVMDfZ8lm1kQhJaG5vRjJ2yq+zgdOFIGjTyjBEEQhFaEnNp6rQZ//dUEpCVbGtwuOd6Ev/xyPKxmPdxeWpOqW0d5vH6cLHWKbX6auBxuTBzSEbfPHojGhpKCFo/eMIqbokdjE/JQ1n20XtTppKpHEAShKSR1Lkohh4MmhEk1VELbM8DNmtUSqoFI5ahjB3ZgQ5WqNpqCgjjTR2XBaQ+tYXk4IfMtlLEMpwpW5T2p/gNP576MRILOQLWnFWPDIAhChMINPkOcT+QxJQiCILQ2DrsbiRYjXntkOpZuPIyvlu7DwaOViVBdMhIwa1xXnDG8C68NHTYXzBZjxK+jYhUKQlSUOzF1RBeMHdQRXy7OxcL1+Sgpd/FafEivNFw4uQd6dkmGrcLF1ywa7Sr1677gDtEVpBEEQWgNJHARpZC+Z9eOichV2OOC6NYxEc4QSi/9fj/S21lhMujgUtFDIt5iRM8uKao+i2IW2ZmJ8PnU9aogfL4AHE4PZ2s89q9lnCnT4OdoNXjgmuHw+yq1UiMdqj/p3ilJ1T7tEs2wmgw4qbDPwulC90lGeyuMei332FAKGaqxtC4g45U0eLt2SMLe/BLF+9H20ZZhJAhC9EHPmc7pCaz5raZCrldWijyjBEEQhIjA4XCzk3tkn3RMGNIJhlOSTiRPROtBW4WT7XFCc2q9oQZqAN4+ycJOd6F5ghfUa/OSqT1ww7n9q/7mcHng8/hQUmyvTKyIUrp2SFQlwUnbkwQ03a+CIAhC44hUVJRCDvcLJuWo2uf8id3h9agPXJDRR5PqxKGdFO/TPsmMzhnxyMpM4IlZKcP7ZLChaLeHJt9E1RNZmfH4y68mICsjod5tMttb8eQtYzAwJxUOe9OVGZGAx+PFtBFZqqS+Zo7tCrvDHTYjkO4Tvy+g6j6hEu8hPdOiQ65LBU6XB+dN7KZ4e0q6oe9nQIxXQRBaGI/HxzIbo/tnKt6nc3o8O32czujLhBQEQRBiEw5SONwoKbbh+PEKfp08aeOKjGDQgnC7PRjVL1NRX4wgU4Z15vlSHMvNR2UFjBtFReU4cYKuVzkqypxwODxRHbTQaTQ4f1KOqqqLcyd0i4o+m4IgCJGABC6iFJfLgy7pCex8VwIFEAb3TAu52ZXf68elU3tWZbM0xcVn9GAjhAy+y6f3Ulxtcdn0Xgj4T28St1e40KGdFS/dNwXP3jkRs8Z3w+ShndiR//Tt4/Cvh6Yhp1MS7BVO1RrfrQUHj/x+nD2mq6LtqRndueO7cQO7cEKfd8nUntAr7FFyEd0nTk/MZfG6XV5MHNIZaSkNa+9WZ9zAjoi3GqKuGZ0gCNEJPatpvqWqCyVcOq0XP6uj2bEgCIIgxC40PzU0RwWr8mdPVpb0RyoDtJYN9zqqLUFrv1gxKcrKHEiKM7JktRJofThpaGd4XLGVuCcIgtBSSOAiSqGJ3uFw4be/GNVkRQNVGDx92zjOvg/VQUwZ8cnxRjx03cgmndKkKzpzTFd23jodbozqn4mrzurd6D7kO/n1ZUNY/spmO/2SXOep7JvOqVZcM6M3bps9ENfN7IOcDgkoKbFzZUa0GUselxfXndMPYwY0bhRRE7qnbh3LWR9ud3gNbrpP2iWY8PB1I5q8TyiwMmN0Nt8nsQZlZ7mcHvzx9vEs2dUY/bq1wz1XDoM7xqpOBEGIXOhZ3SE1DvdcObTJvlKXTuuJ8YM68jNNEARBEKIRWm+cN7E7ZozOanQ7StJ75IaRklAkqCLgD+C+q4ajb9d2jW5H60JaH1K1hVSxCoIgKEN6XEQxNNmZocFzv5mIT3/ai+9WHsTJsp+d/olxRpw5KoszJQM+H1dAnA52mxsDu7fDC/dMwoff78bKrUdr6GOTjMTsyT0wekAmKipcVaW1JMd08Rk9ud/Fpz/twdbcE1X7kL+E5KEund6Le3BQA7XTLLioFdyJHUcLVa/YbS48eO0ILFiTh6+W7ENeQXmN7CDSeL1yRi/Emw28bWvA90lOKp6/exI+/GEXVm09VuM+IZ302VNyuGSb9GdjtQSbStcTrEb8/b4pPA4/rj0EezUDNaOdFWeP7YrzJ3XnknZZHAmCEC54frS5+Dn83J0T8dH83Vizo6BGcgMFVS86oyeG9EyF3eaMuco4QRAEoe1A6w1q/nzb7EEY1CMNny/ai9z8n3tF6nUajB3YEVec2Yslj2mOFARVVRdJZvzxjnGYsygX36w4gMJiR9Xf48x6TB2RhcvP7MVr9vLSn/8mCIIgNI4mIHX/9Ro2pI/ZXOj1WqSkxKG42FZDb7O5MBh00Bt0sJgN2HekFOU2N0sF5XSu1KOmMlfSlGwuLBYDdHodvP4ADh4tg9cXQEY7C1KTLXA5vSxjVdvBodNpYbUaodNrUVLuQn5hBWd5UiNu6mlB8lBUadFcQYtouG6hQmNpNOlhNhtwpKgCJ0qdMBq06N4pmbM96Hor6RnR0udXdZ/4AjhwrIy/Vxnt4pCabG7wPonFa2cy6aHV67g/yd5DJXC4vEiKN3GlFJWte9xeVccYSefW3Mi5RT5pafX3DmrNeTZWxrY1zo0q82gu0Rv0cHl8yDtWzoHmDqlWpCSYOUO1rTyrmxs5t+hEzi16iYXzi8Q5NlbGNgitP00mA0xmPYqKHSgstnOVONnlJJ9I66hYSXyLpesWLedG/g5a99Ha/MCRMvZ7kK+jZ1YyPF4/98OgIEc0nltzEcvnJ+fWNuZYIfxIxUWMZOLTi2QcMpLM6JBiYY3PslJHi2SzVxpzHg6YdMtMQFycCRUVTpSW2BuUX6LjKC93Vk3ofbNTTv3eh7JSe7MfY8w3orO7WQ4r2WpASpyRf++0uyJqEql+n3RNj+ffkfOrpLhtXW+upHB54XZq0Tk1jh2FPA4ldslgFgShVamqTHScelZn/PyspjldEARBEGIJmt+oKtrpdCPepEdy5yRYrSaUlztQYZPqZ+H0sNvd/JNsqi7p8cjOTGC/jNPhUZRYKAiCINRFAhcxZoiFU26GgiU0EVPgovLf6iZ04fSg8Y4GeaFgYK2tQwGnWJXFEgQh+pFntSAIgtDW1lE+H6kCmCIq+UuIfsieKhU5KEEQhGZBmnMLgiAIgiAIgiAIgiAIgiAIghAxSOBCEARBEARBEARBEARBEARBEISIQQIXgiAIgiAIgiAIgiAIgiAIgiBEDBK4EARBEARBEARBEARBEARBEAQhYpDm3IIgCIIgCIIgCIIgCBGATqeFRlPZRNznk8bhgiAIQttFAheCIAiCIAiCIAiCIAithFargcmkh8Fo4KCFy+2DyaiDPxCA1+2Dy+WB3x9o7cMUBEEQhLAigQtBEARBEARBEARBEIRWgAIWVqsJG3YXYs7ifdi0p4h/r9UAQ3un48LJOejfPRV2mxNut6+1D1cQBEEQwoYELgRBEARBEARBEARBEMKM0aiH2WLE02+twrqdhTX+RgUW9Dt6TRjSEfdeORyBgBMejwQvBEEQhLaBNOcWBEEQBEEQBEEQBEEIIyQJZY0z4m8frKsTtKjN0o1H8Oqnm2CxGsN2fIIgCILQ2kjgQhAEQRAEQRAEQRAEIYyYTAYcOW7D8i1HFW0/f00eyu0elpYSBEEQhLaAzHiCEEWYzQZotFrodBpQaza/LwC/j5q1eVv70ARBEIRmQqfTwmjS8/OemnMazQYYfAG43V74fP7WPryowmIxQKvXUV4ra4VTk1OdRgO73QWvV8ZSEARBaD20ei2+WJSrePtAAJizOBeXT+vZosclCIIgCJGCBC4EIQowmfWwWIw4dsKOr5bsw6GCcvLBIDszERdM6o72yVY4HW4JYAiCIEQxWq2Gda6NRh0WrT+MZZuPwObwIN5iwIQhnTBxSCe43F447W4EyHshNAhlo1LAx+cLYO7S/di89zg8Xh/aJZpx5uhsDO6ZynOmrcLV2ocqCIIgtFEsJgO27D2uap8tucdxzcw+cLTYUQmCIAhC5CCBC0GIgioLyhZ94j8rsXlPTcN2a+4JfL1sP4b3ScdD142ERqOB0+lptWMVBEEQQg9axMWbsXLrUfzrs82wOWsGotfsKMDrX2zBry4ZjBF9M2CrcMJPXTuFeqU3rFYj3v92B+Ys3gdvrSqVpZuOIKOdFY/eMAodUq2oKHO22rEKgiAIbXvu96is/vN4/NBqRfFbEARBaBtExYxXUlKC3/3ud5g0aRKGDRuGK6+8EmvXrq36+4oVK3DRRRdh8ODBmDlzJr7++utWPV5BaC4o69Zg1OPBl5fUCVpUh5q5PfzK0ko5EQNJYgiCIAjRhMVq4gqLv/13fZ2gRZAKhwfPvL8Wq7Ydg1mac9YL+XIsVgNe+2ILPv1pb52gRZCCk3Y89I8lKDjpQFy8KezHKQiCIAhUCdg+yaxqn3ZJZnh9vhY7JkEQBEGIJKIicHHvvfdiw4YNeP755/Hpp5+ib9++uOmmm7Bv3z7k5ubitttuw8SJE/HZZ5/h0ksvxYMPPsjBDEGIdvQGPT74bifySBqqCfYdLsUn83dDL4ELQRCEqIIDzhrgn/+3qcltSSHq5U82ch8MvT4qzLiwEhdnRm5+Kb5dcaDJbZ1uH/72wToYjXoOeAiCIAhCOCHJwmkju6jaZ8aoLPikR5MgCILQRoj4ZdrBgwexbNkyPPHEExgxYgS6deuGxx9/HOnp6fjqq6/wzjvvoHfv3rjnnnuQk5PDAQ2quvjPf/7T2ocuCKcFOaVMRj3mr85TvM93qw7CQtJS1IFUEARBiAoo4PzdyoNwK3REUMPuBavzuCJPqIVWw41LlXLgaBkOHClDfLy6jFdBEARBOF08bi+mj8yCxaRsPk+ON2HsoI5wS19DQRAEoY0Q8YGLlJQU/Pvf/8bAgQOrfkc6/vQqKytjyaixY8fW2GfMmDFYt26dNK4Uol4mavPeIpYGUUpJuQu78oo5e1QQBEGInkbSizbkq9rnp/X5Ig1YC4NBC4Ney31C1LBgbR680i9EEARBCDNer597XDx07Qjomkg8o/ntkRtGcj9DXwMyiIIgCIIQa0S8dzMxMRGTJ0+u8bvvvvuOKzEeffRRfP7558jMzKzxd6rGcDj+v707AY+yOhc4/maZbOw7ShAVRHYhUhZBNpFyBTe01bLUSlFsa3tFaAtaq9QroijgUsBea6sXfNp7EbRWFFG0LhVBEbBsAgIiImEJJCSZ/bvPe+zEhHUCM5nvzPx/z5OHZOYb/d45yXnPN+855yuXoqIiadiw4Wn9f2O5/YLOnK/8bzIhtvj+/7UQUV2HS3xybrM6p/wdTnR88URsdiK21BKrPJsM760nM0OKS/3Veo0er++hzdtFxbrtMjMzzGqUYMip9nupc10Y+0WH2OyUzLGlQnzVRX9mT2xBf0A6nNdQfje+t/z+/9bKV/tLjznmnOZ15D9v6Cb5TWuLr/yb/G9DbPFCbPZK5viIDUjRwsXRVq9eLVOmTJEhQ4bIgAEDxOv1SlZW1RtURn72+6v3IUCEbrPToEEtibW6dXMlWRFbfOTlek7rNXl5WeYrGrSdnYjNTskcW6LzrM3vrd5AOqeaK+V0W4lw2InLeKWmxbLtdOZqdel7ryt5GftVD7HZKZljS4X4osG1rJ2xtT+3ocz59SDZtKNI3lmzW8q9AamdmyUDLs6X1i3qSdhxzESHvByPdbHFC7HZK5njIzYghQsXb7zxhkyaNEkKCgrkkUceMY9lZ2cfU6CI/Jybe3p/VPpBQHFxmcSKViX1D7y4uDzplnUSW/zoTJrOrRubZcHRfhCTk5Uh7Vo1jOqcEx1fPBGbnYjN/WL1QUgs82wyvLdZOR7p3r6p7NpbEvVrurdvJn5/SI6UeMVW8Wi72nVypFPrRvKvbQeifk2vTs1FJ68WFR07yzWVfy9PhNjslMyxJUt8bsyxyfLe2hJbWprIec1ryznfvVAiG0fpDlIlJeVmZaDNscUSsdkrmeMjNndLhsleqcqawsX8+fPlgQceMDfefuihhypWVZx11llSWFhY5Vj9OS8vT+rUqXNG+03Gmv6Bx+O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"text/plain": [
"<Figure size 1592.5x500 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"favorite_types = pokemon[pokemon.type.isin([\"Fire\", \"Water\", \"Grass\"])]\n",
"sns.relplot(data=favorite_types, x=\"hp\", y=\"speed\", hue=\"legendary\", col=\"type\", s=100)"
]
},
{
"cell_type": "markdown",
"id": "c6a20904-416d-44be-a4f3-2107200fb3c2",
"metadata": {},
"source": [
"#### Your turn\n",
"\n",
"**1.5.0.** Plot a histogram of peoples' heights."
]
},
{
"cell_type": "code",
"execution_count": 62,
"id": "3b268a30-42ff-4ab8-b2cd-c58a76121f9c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='height', ylabel='Count'>"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import seaborn as sns\n",
"sns.histplot(data=people, x=\"height\")"
]
},
{
"cell_type": "markdown",
"id": "9b0c9120-fff4-42b2-8ab6-3aa2eba47806",
"metadata": {},
"source": [
"**1.5.1.** Plot a bar chart showing peoples' average hours of sleep by age. "
]
},
{
"cell_type": "code",
"execution_count": 69,
"id": "ee30c851-14b1-4901-9182-4304d54d53a6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='age', ylabel='sleep'>"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=people, y=\"sleep\", x=\"age\", errorbar=\"sd\")"
]
},
{
"cell_type": "markdown",
"id": "15d94323-2d65-4100-9916-101516f6ccf1",
"metadata": {},
"source": [
"**1.5.2.** Plot a bar chart showing peoples' likelihood of getting exercise by income. "
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "13eeecd8-2518-4ed9-aac5-727a96b5bf80",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='income', ylabel='exercise'>"
]
},
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=people, y=\"exercise\", x=\"income\", errorbar=\"sd\")"
]
},
{
"cell_type": "markdown",
"id": "b2705fef-470d-494c-86c1-8b3bd34b3660",
"metadata": {},
"source": [
"**1.5.3.** Plot a bar chart showing average reported health by age. For each age, show average health for those who get exercise and those who don't."
]
},
{
"cell_type": "code",
"execution_count": 72,
"id": "4ee2eb69-2f9a-42e7-b5d3-9499631bfd06",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='age', ylabel='health'>"
]
},
"execution_count": 72,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=people, x=\"age\", y=\"health\", hue=\"exercise\")"
]
},
{
"cell_type": "markdown",
"id": "84b1e240-4f75-4c86-8c1f-1026aa223717",
"metadata": {},
"source": [
"**1.5.4.** Create a plot showing the number of people at each income level, for each education level. "
]
},
{
"cell_type": "code",
"execution_count": 77,
"id": "d7e02da8-beab-40e7-95d0-74a5c2bc838e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='income', ylabel='count'>"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.countplot(data=people, x=\"income\", hue=\"education\")"
]
},
{
"cell_type": "markdown",
"id": "ac717580-4157-402c-9262-b2b50dfe606f",
"metadata": {},
"source": [
"**1.5.5.** Plot side-by-side scatter plots showing the relationship between height and weight for males and females. (There are so many overlapping dots that the plot will be more informative if you lower the opacity of each dot. Try using `alpha=0.1` and `edgecolor=None`.)"
]
},
{
"cell_type": "code",
"execution_count": 84,
"id": "b00dd7d6-226b-469c-86d8-b71b328aa576",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='weight', ylabel='height'>"
]
},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.scatterplot(data=gender, x=\"weight\", y=\"height\", hue=\"sex\", alpha=0.1, edgecolor=None)"
]
},
{
"cell_type": "markdown",
"id": "e9ff7225-5d08-428b-90e8-ee60f4a4049a",
"metadata": {},
"source": [
"## 2. Crafting a data argument\n",
"\n",
"Everything up to here are just tools, worthless without a clear research question and a convincing argument. Choose a research question that interests you which might be answerable using the `people` dataset. Then do your best to find the answer in the space below. This answer should include data analysis (code cells) as well as written argument (text cells) explaining what the data means and why you believe it answers your question. \n",
"\n",
"Examples of research questions might include:\n",
"\n",
"- Do older people tend to have higher incomes?\n",
"- Do people who sleep at least 6 hours a night tend to report better health? \n",
"- Is it more common for males to be bisexual than females?\n",
"\n",
"**A note of caution:** this lab has given you tools for exploring associations--patterns that tend to co-occur. These tools *do not* equip you to argue that one variable causes another to change. For example: Plot 1.5.4 showed that people who are taller also tend to be heaver, with a lot of individual variation. But are people heavier *because* they are taller? Are they taller because they are heavier? Or maybe neither variable causes the other--perhaps they're both caused by something else. If you want to be able to answer questions like these, take a course on statistics."
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "6f934273-b829-4bc2-a7f4-a27a3fc44a99",
"metadata": {},
"outputs": [],
"source": [
"#Do heterosexual males make more money on average than every other group of people?"
]
},
{
"cell_type": "code",
"execution_count": 88,
"id": "c84e300a-0498-4d22-9b9e-7491b3b0ba20",
"metadata": {},
"outputs": [],
"source": [
"sex_gender = people.groupby([\"sexual_orientation\", \"sex\"])"
]
},
{
"cell_type": "code",
"execution_count": 101,
"id": "6078dcbd-bc5d-4002-b763-51496adc2f20",
"metadata": {},
"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></th>\n",
" <th>income</th>\n",
" </tr>\n",
" <tr>\n",
" <th>sexual_orientation</th>\n",
" <th>sex</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">bisexual</th>\n",
" <th>female</th>\n",
" <td>5.454545</td>\n",
" </tr>\n",
" <tr>\n",
" <th>male</th>\n",
" <td>5.812060</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">heterosexual</th>\n",
" <th>female</th>\n",
" <td>6.046153</td>\n",
" </tr>\n",
" <tr>\n",
" <th>male</th>\n",
" <td>6.454184</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">homosexual</th>\n",
" <th>female</th>\n",
" <td>6.134661</td>\n",
" </tr>\n",
" <tr>\n",
" <th>male</th>\n",
" <td>6.142539</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">other</th>\n",
" <th>female</th>\n",
" <td>4.978906</td>\n",
" </tr>\n",
" <tr>\n",
" <th>male</th>\n",
" <td>5.359694</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" income\n",
"sexual_orientation sex \n",
"bisexual female 5.454545\n",
" male 5.812060\n",
"heterosexual female 6.046153\n",
" male 6.454184\n",
"homosexual female 6.134661\n",
" male 6.142539\n",
"other female 4.978906\n",
" male 5.359694"
]
},
"execution_count": 101,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sex_gender[[\"income\"]].mean()"
]
},
{
"cell_type": "code",
"execution_count": 104,
"id": "cfff906a-da14-401e-a621-2048f331f7fe",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='sexual_orientation', ylabel='income'>"
]
},
"execution_count": 104,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=people, x=\"sexual_orientation\", y=\"income\", hue=\"sex\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "80f73270-20e8-4039-9705-0f48bfe92c54",
"metadata": {},
"outputs": [],
"source": [
"#The data tells us that heterosexual men, on average, make more than all other groups. \n",
"#Heterosexual men earn more than $55,000, and the closest group is homosexual men with around $51,500 a year.\n"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "dd2a4b37-18b7-4528-8ca5-ce7e8ec2b206",
"metadata": {},
"outputs": [],
"source": [
"# Your code here. Feel free to add new text cells and code cells as necessary."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8b4b852b-402c-45d4-b3bb-840e47b249ed",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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