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lgaud/Load a Notion Database in Pandas.ipynb

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This is an example of importing a Notion database into Pandas, created for a blog post at https://www.pynotion.com/load-in-pandas
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Load a Notion Database in Pandas.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is an example of importing a Notion database into Pandas, created for a blog post at https://www.pynotion.com/load-in-pandas\n",
"\n",
"Instructions to run:\n",
"1. Set up a Notion Integration and set the key to the NOTION_KEY environment variable.\n",
"2. Get the ID for a Notion database you'd like to load in Pandas and set notion_database_id in the cell below. \n",
" - The data analysis part of this sample uses a dataset of [Ted Talks from Kaggle](https://www.kaggle.com/datasets/miguelcorraljr/ted-talks-2022) which was imported into Notion from the CSV file for the purpose of showing some analysis on a larger dataset. It has over 5000 rows so it takes a couple minutes to load."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Set your database id here:\n",
"notion_database_id = \"312c0bbdea67435b87761098c6a24f47\""
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"from urllib.parse import urljoin\n",
"\n",
"class NotionClient():\n",
" def __init__(self, notion_key):\n",
" self.notion_key = notion_key\n",
" self.default_headers = {'Authorization': f\"Bearer {self.notion_key}\",\n",
" 'Content-Type': 'application/json', 'Notion-Version': '2022-06-28'}\n",
" self.session = requests.Session()\n",
" self.session.headers.update(self.default_headers)\n",
" self.NOTION_BASE_URL = \"https://api.notion.com/v1/\"\n",
" \n",
" def query_database(self, db_id, filter_object=None, sorts=None, start_cursor=None, page_size=None):\n",
" db_url = urljoin(self.NOTION_BASE_URL, f\"databases/{db_id}/query\")\n",
" params = {}\n",
" if filter_object is not None:\n",
" params[\"filter\"] = filter_object\n",
" if sorts is not None:\n",
" params[\"sorts\"] = sorts\n",
" if start_cursor is not None:\n",
" params[\"start_cursor\"] = start_cursor\n",
" if page_size is not None:\n",
" params[\"page_size\"] = page_size\n",
" \n",
" return self.session.post(db_url, json=params, headers=self.default_headers)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"from datetime import datetime\n",
"class PandasConverter():\n",
" text_types = [\"rich_text\", \"title\"] \n",
" \n",
" def response_to_records(self, db_response):\n",
" records = []\n",
" for result in db_response[\"results\"]:\n",
" records.append(self.get_record(result))\n",
" return records \n",
"\n",
" def get_record(self, result):\n",
" record = {}\n",
" for name in result[\"properties\"]:\n",
" if self.is_supported(result[\"properties\"][name]):\n",
" record[name] = self.get_property_value(result[\"properties\"][name])\n",
"\n",
" return record\n",
" \n",
" def is_supported(self, prop):\n",
" if prop.get(\"type\") in [\"checkbox\", \"date\", \"number\", \"rich_text\", \"title\"]:\n",
" return True\n",
" else:\n",
" return False\n",
" \n",
" def get_property_value(self, prop):\n",
" prop_type = prop.get(\"type\")\n",
" if prop_type in self.text_types:\n",
" return self.get_text(prop)\n",
" elif prop_type == \"date\":\n",
" return self.get_date(prop)\n",
" else:\n",
" return prop.get(prop_type)\n",
" \n",
" def get_text(self, text_object):\n",
" text = \"\"\n",
" text_type = text_object.get(\"type\")\n",
" for rt in text_object.get(text_type):\n",
" text += rt.get(\"plain_text\")\n",
" return text\n",
" \n",
" def get_date(self, date_object):\n",
" date_value = date_object.get(\"date\")\n",
" if date_value is not None:\n",
" if date_value.get(\"end\") is None:\n",
" return date_value.get(\"start\")\n",
" else: \n",
" start = datetime.fromisoformat(date_value.get(\"start\"))\n",
" end = datetime.fromisoformat(date_value.get(\"end\"))\n",
" return end - start\n",
" return None\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"class PandasLoader():\n",
" def __init__(self, notion_client, pandas_converter):\n",
" self.notion_client = notion_client\n",
" self.converter = pandas_converter\n",
" \n",
" def load_db(self, db_id):\n",
" page_count = 1\n",
" print(f\"Loading page {page_count}\")\n",
" db_response = self.notion_client.query_database(db_id)\n",
" records = []\n",
" if db_response.ok:\n",
" db_response_obj = db_response.json()\n",
" records.extend(self.converter.response_to_records(db_response_obj))\n",
" \n",
" while db_response_obj.get(\"has_more\"):\n",
" page_count += 1\n",
" print(f\"Loading page {page_count}\")\n",
" start_cursor = db_response_obj.get(\"next_cursor\")\n",
" db_response = self.notion_client.query_database(db_id, start_cursor=start_cursor)\n",
" if db_response.ok:\n",
" db_response_obj = db_response.json()\n",
" records.extend(self.converter.response_to_records(db_response_obj))\n",
" return pd.DataFrame(records)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loading page 1\n",
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]
},
{
"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>speaker</th>\n",
" <th>published_date</th>\n",
" <th>views</th>\n",
" <th>likes</th>\n",
" <th>talk_id</th>\n",
" <th>recorded_date</th>\n",
" <th>event</th>\n",
" <th>duration</th>\n",
" <th>title</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Antonio Damasio</td>\n",
" <td>2011-12-19</td>\n",
" <td>2396029</td>\n",
" <td>71000</td>\n",
" <td>1308</td>\n",
" <td>2011-03-02</td>\n",
" <td>TED2011</td>\n",
" <td>1105</td>\n",
" <td>The quest to understand consciousness</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Farish Ahmad-Noor</td>\n",
" <td>2020-06-23</td>\n",
" <td>2074509</td>\n",
" <td>62000</td>\n",
" <td>64428</td>\n",
" <td>2019-09-28</td>\n",
" <td>TEDxNTU</td>\n",
" <td>729</td>\n",
" <td>Why is colonialism (still) romanticized?</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Harald Haas</td>\n",
" <td>2011-08-02</td>\n",
" <td>2769918</td>\n",
" <td>83000</td>\n",
" <td>1202</td>\n",
" <td>2011-07-13</td>\n",
" <td>TEDGlobal 2011</td>\n",
" <td>755</td>\n",
" <td>Wireless data from every light bulb</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Esther Ndichu</td>\n",
" <td>2018-05-04</td>\n",
" <td>87610</td>\n",
" <td>2600</td>\n",
" <td>13014</td>\n",
" <td>2015-09-02</td>\n",
" <td>TED@UPS</td>\n",
" <td>698</td>\n",
" <td>Hunger isn't a food issue. It's a logistics issue</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Paola Antonelli</td>\n",
" <td>2008-10-15</td>\n",
" <td>403983</td>\n",
" <td>12000</td>\n",
" <td>372</td>\n",
" <td>2007-12-12</td>\n",
" <td>EG 2007</td>\n",
" <td>1038</td>\n",
" <td>Design and the Elastic Mind</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",
" </tr>\n",
" <tr>\n",
" <th>5696</th>\n",
" <td>Martin Rees</td>\n",
" <td>2014-08-25</td>\n",
" <td>1315891</td>\n",
" <td>39000</td>\n",
" <td>2067</td>\n",
" <td>2014-03-13</td>\n",
" <td>TED2014</td>\n",
" <td>403</td>\n",
" <td>Can we prevent the end of the world?</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5697</th>\n",
" <td>Matilda Ho</td>\n",
" <td>2017-11-28</td>\n",
" <td>1522508</td>\n",
" <td>45000</td>\n",
" <td>3671</td>\n",
" <td>2017-04-24</td>\n",
" <td>TED2017</td>\n",
" <td>294</td>\n",
" <td>The future of good food in China</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5698</th>\n",
" <td>Stephen Bax</td>\n",
" <td>2019-02-22</td>\n",
" <td>8975610</td>\n",
" <td>269000</td>\n",
" <td>24485</td>\n",
" <td>2017-05-25</td>\n",
" <td>TED-Ed</td>\n",
" <td>262</td>\n",
" <td>The world's most mysterious book</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5699</th>\n",
" <td>Ethan Nadelmann</td>\n",
" <td>2014-11-12</td>\n",
" <td>2309479</td>\n",
" <td>69000</td>\n",
" <td>2130</td>\n",
" <td>2014-10-15</td>\n",
" <td>TEDGlobal 2014</td>\n",
" <td>1036</td>\n",
" <td>Why we need to end the War on Drugs</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5700</th>\n",
" <td>Simona Francese</td>\n",
" <td>2018-09-17</td>\n",
" <td>2611782</td>\n",
" <td>78000</td>\n",
" <td>20390</td>\n",
" <td>2018-04-10</td>\n",
" <td>TED2018</td>\n",
" <td>596</td>\n",
" <td>Your fingerprints reveal more than you think</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5701 rows × 9 columns</p>\n",
"</div>"
],
"text/plain": [
" speaker published_date views likes talk_id \\\n",
"0 Antonio Damasio 2011-12-19 2396029 71000 1308 \n",
"1 Farish Ahmad-Noor 2020-06-23 2074509 62000 64428 \n",
"2 Harald Haas 2011-08-02 2769918 83000 1202 \n",
"3 Esther Ndichu 2018-05-04 87610 2600 13014 \n",
"4 Paola Antonelli 2008-10-15 403983 12000 372 \n",
"... ... ... ... ... ... \n",
"5696 Martin Rees 2014-08-25 1315891 39000 2067 \n",
"5697 Matilda Ho 2017-11-28 1522508 45000 3671 \n",
"5698 Stephen Bax 2019-02-22 8975610 269000 24485 \n",
"5699 Ethan Nadelmann 2014-11-12 2309479 69000 2130 \n",
"5700 Simona Francese 2018-09-17 2611782 78000 20390 \n",
"\n",
" recorded_date event duration \\\n",
"0 2011-03-02 TED2011 1105 \n",
"1 2019-09-28 TEDxNTU 729 \n",
"2 2011-07-13 TEDGlobal 2011 755 \n",
"3 2015-09-02 TED@UPS 698 \n",
"4 2007-12-12 EG 2007 1038 \n",
"... ... ... ... \n",
"5696 2014-03-13 TED2014 403 \n",
"5697 2017-04-24 TED2017 294 \n",
"5698 2017-05-25 TED-Ed 262 \n",
"5699 2014-10-15 TEDGlobal 2014 1036 \n",
"5700 2018-04-10 TED2018 596 \n",
"\n",
" title \n",
"0 The quest to understand consciousness \n",
"1 Why is colonialism (still) romanticized? \n",
"2 Wireless data from every light bulb \n",
"3 Hunger isn't a food issue. It's a logistics issue \n",
"4 Design and the Elastic Mind \n",
"... ... \n",
"5696 Can we prevent the end of the world? \n",
"5697 The future of good food in China \n",
"5698 The world's most mysterious book \n",
"5699 Why we need to end the War on Drugs \n",
"5700 Your fingerprints reveal more than you think \n",
"\n",
"[5701 rows x 9 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"client = NotionClient(os.environ.get(\"NOTION_KEY\"))\n",
"converter = PandasConverter()\n",
"loader = PandasLoader(client, converter)\n",
"df = loader.load_db(notion_database_id)\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 6,
"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>views</th>\n",
" <th>likes</th>\n",
" <th>talk_id</th>\n",
" <th>duration</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>5.701000e+03</td>\n",
" <td>5.701000e+03</td>\n",
" <td>5701.000000</td>\n",
" <td>5701.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>2.147123e+06</td>\n",
" <td>6.386154e+04</td>\n",
" <td>26577.133135</td>\n",
" <td>706.021751</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>3.711874e+06</td>\n",
" <td>1.098655e+05</td>\n",
" <td>30530.857641</td>\n",
" <td>519.196825</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>4.560000e+02</td>\n",
" <td>1.300000e+01</td>\n",
" <td>1.000000</td>\n",
" <td>60.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>6.859920e+05</td>\n",
" <td>2.000000e+04</td>\n",
" <td>1660.000000</td>\n",
" <td>354.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>1.405696e+06</td>\n",
" <td>4.200000e+04</td>\n",
" <td>10368.000000</td>\n",
" <td>679.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>2.189406e+06</td>\n",
" <td>6.500000e+04</td>\n",
" <td>51783.000000</td>\n",
" <td>924.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>7.393596e+07</td>\n",
" <td>2.200000e+06</td>\n",
" <td>98843.000000</td>\n",
" <td>20404.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" views likes talk_id duration\n",
"count 5.701000e+03 5.701000e+03 5701.000000 5701.000000\n",
"mean 2.147123e+06 6.386154e+04 26577.133135 706.021751\n",
"std 3.711874e+06 1.098655e+05 30530.857641 519.196825\n",
"min 4.560000e+02 1.300000e+01 1.000000 60.000000\n",
"25% 6.859920e+05 2.000000e+04 1660.000000 354.000000\n",
"50% 1.405696e+06 4.200000e+04 10368.000000 679.000000\n",
"75% 2.189406e+06 6.500000e+04 51783.000000 924.000000\n",
"max 7.393596e+07 2.200000e+06 98843.000000 20404.000000"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Analysis Example\n",
"This code assumes that your data comes from the [Ted Talks Dataset](https://www.kaggle.com/datasets/miguelcorraljr/ted-talks-2022) available from Kaggle. But you can adjust it to something you already have in Notion!"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"speaker_count = df.groupby('speaker')['speaker'].count()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"47"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"max_speaker_count = speaker_count.max()\n",
"max_speaker_count"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1e6dabcf8b0>"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"speaker_count.plot(kind='hist', figsize=(15,10), bins=max_speaker_count)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So the vast majority of Ted speakers have one talk but there's a long tail out to 47. Who are those prolific speakers?"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"speaker\n",
"Alex Gendler 47\n",
"Iseult Gillespie 37\n",
"Matt Walker 18\n",
"Elizabeth Cox 15\n",
"Alex Rosenthal 15\n",
" TED-Ed 15\n",
"Emma Bryce 12\n",
"Daniel Finkel 11\n",
"Jen Gunter 11\n",
"Juan Enriquez 11\n",
"Hans Rosling 9\n",
"Bill Gates 9\n",
"Wendy De La Rosa 9\n",
"Dan Finkel 9\n",
"Greg Gage 9\n",
"Mona Chalabi 9\n",
"Fabio Pacucci 8\n",
"Dan Kwartler 7\n",
"Al Gore 7\n",
"Marco Tempest 7\n",
"Name: speaker, dtype: int64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"top_20_speakers = speaker_count.sort_values(ascending=False)[:20]\n",
"top_20_speakers"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1e6dae25220>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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AAIAJCGcAAAATEM4AAAAmIJwBAABMQDgDAACYwPFrFwAwuxNPOW3Xf+aZp5606z9TnQCwt7lyBgAAMAHhDAAAYALCGQAAwASEMwAAgAkIZwAAABMQzgAAACYgnAEAAEzgsOGsqp5cVR+rqrdvue9SVfXiqnrP8vGSR7dMAACAc7cjuXL21CS32nbfKUle0t1XS/KS5RgAAIBz6LDhrLtfmeRft919uyRPW24/Lcntd7kuAACA85Rzuubsst39kSRZPl7mYF9YVfeuqjOq6oyzzjrrHP46AACAc7ej3hCku5/Q3dfv7uufcMIJR/vXAQAA7EnnNJx9tKoulyTLx4/tXkkAAADnPec0nD0vycnL7ZOTPHd3ygEAADhvOpJW+s9M8tok16iqD1bVPZOcmuQWVfWeJLdYjgEAADiHjj/cF3T3XQ/yqZvvci0AAADnWUe9IQgAAACHJ5wBAABMQDgDAACYgHAGAAAwAeEMAABgAoft1ggA50UnnnLarv/MM089add/pjp3z16oMVEnnJu5cgYAADAB4QwAAGACwhkAAMAEhDMAAIAJCGcAAAATEM4AAAAmIJwBAABMQDgDAACYgHAGAAAwAeEMAABgAsevXQAAAKzlxFNO2/WfeeapJ+36z+S8wZUzAACACQhnAAAAExDOAAAAJiCcAQAATEA4AwAAmIBwBgAAMAHhDAAAYALCGQAAwASEMwAAgAkIZwAAABM4fu0CAACAQzvxlNN2/WeeeepJu/4zz6t17laNrpwBAABMQDgDAACYgHAGAAAwAeEMAABgAsIZAADABIQzAACACQhnAAAAExDOAAAAJiCcAQAATEA4AwAAmIBwBgAAMAHhDAAAYALCGQAAwASEMwAAgAkIZwAAABMQzgAAACYgnAEAAExAOAMAAJiAcAYAADAB4QwAAGACwhkAAMAEhDMAAIAJCGcAAAATEM4AAAAmIJwBAABMQDgDAACYgHAGAAAwAeEMAABgAsIZAADABIQzAACACQhnAAAAExDOAAAAJiCcAQAATEA4AwAAmIBwBgAAMAHhDAAAYALCGQAAwASEMwAAgAkIZwAAABMQzgAAACYgnAEAAExAOAMAAJiAcAYAADAB4QwAAGACwhkAAMAEhDMAAIAJCGcAAAATEM4AAAAmIJwBAABMQDgDAACYgHAGAAAwAeEMAABgAsIZAADABIQzAACACQhnAAAAExDOAAAAJiCcAQAATEA4AwAAmIBwBgAAMAHhDAAAYALCGQAAwASEMwAAgAkIZwAAABMQzgAAACYgnAEAAExAOAMAAJiAcAYAADAB4QwAAGACwhkAAMAEhDMAAIAJCGcAAAATEM4AAAAmIJwBAABM4CsKZ1V1q6p6V1W9t6pO2a2iAAAAzmvOcTirqvMl+b0kt05yrSR3rapr7VZhAAAA5yVfyZWzGyZ5b3e/r7s/l+RPk9xud8oCAAA4b6nuPmffWPUDSW7V3T++HP9wkm/r7vtt+7p7J7n3cniNJO865+Xu6NJJPr7LP/NoUOfu2Qs1JurcbercXercPXuhxkSdu02du2sv1LkXakzUuduORp1X7u4TdvrE8V/BD60d7jsg6XX3E5I84Sv4PYcuouqM7r7+0fr5u0Wdu2cv1Jioc7epc3epc/fshRoTde42de6uvVDnXqgxUeduO9Z1fiXTGj+Y5Ipbjq+Q5MNfWTkAAADnTV9JOPv7JFerqqtU1Vcl+cEkz9udsgAAAM5bzvG0xu7+QlXdL8kLk5wvyZO7+x27VtmRO2pTJneZOnfPXqgxUeduU+fuUufu2Qs1JurcbercXXuhzr1QY6LO3XZM6zzHDUEAAADYPV/RJtQAAADsDuEMAABgAnsqnFXV+arqZ9eu49xiL/89lyY0wGHUcMXDf+X6dqqzqr52jVpgr6uqC69dA0dfVR1XVTdeu44vh8fmoe25NWdV9fLu/u616zicqrp6kscnuWx3X7uqrpPktt39yJVL289e+HtW1cuT/Gh3n7kc3zDJH3X3ddesa6OqvuVQn+/uNx6rWg6lqn7uUJ/v7t8+VrUciaq6UJIHJrlSd9+rqq6W5Brd/dcrl7bnVNUbuvtb167jcKrqC0n+LMk9u/szy31v7O5DPseOtap67A53/3uSM7r7uce6niNRVZdMcsXufuvatWxXVSckeUiSayW5wOb+7r7ZakVtUVWXOtTnu/tfj1UtR2I5UX9ikot095Wq6rpJfqK7f2rl0vaMqvqd7n5AVf1Vdt7D97YrlHVQVfXa7r7R2nUczl55bFbV/bv7MYe772j5SjahXsurq+p3k/zfJP+xuXOWE+At/ijJzyf5wyTp7rdW1f9JMlU4y974e/5GkhcsJ0SXT3LrJD+2bkn7+a1DfK6TTHGCkeSiy8drJLlB9m19cZskr1ylokN7SpI3JNm84Xww48R9inBWVZ/OvjftWj72cru7+2KrFLaz11XVDbr779cu5DDeluRVSV5VVXfu7n/Mvr/tTC6Q5JoZj8ck+f4k70hyz6q6aXc/YLXKtlgGtm6b8V7/5iRnVdUruvuQAzUreEbGe9BJSe6T5OQkZ61a0f7ekH3P7e06ydcf23IO638nuWWW1/jufktV3WTdkvapqmd1952r6m3ZP/hsXjuvs1JpWz19+fjoVas4ci+qqu9P8uye+6rL1I/NLU5Osj2I/egO9x0VezGcbS7d/uqW+2Y6Ad64UHefXrXfa/kX1irmEKb/e3b3C6vqPklenOTjSa7X3f+yclln6+6brl3DkejuX0mSqnpRkm/p7k8vxw/PvpPMmVy1u+9SVXdNku7+bG17Qq2puy96+K+axk2T3KeqzswYhJnpJGir7u7fr6q3JPmrqnpIdhi1nsA3JLlZd38hSarq8UlelOQWGQFzFhfv7k9V1Y8neUp3P6yqprtyluRruvtJy8j0K5K8oqpesXZRG919lbVr+HJ19we2vVx+ca1adnD/5eP3rVrFIXT3G5abZyT5bHd/KRnLQZJ89WqFHdzPJblwki9W1Wcz5yBhkrkfm8v5xg8luUpVbd27+WJJPnGs6thz4WyvnAgn+XhVXTXLiUVV/UCSj6xb0oH2wt+zqn4pyZ2T3CTJdZK8vKoe2N2nrVvZgarq2jlwas4fr1fRjq6U5HNbjj+X5MR1Sjmkz1XVBbPvOXTVJP+1bkk7q6rvTHK17n5KVV06yUW7+5/WrmuLW69dwBGqJOnuV1fVzTOuplxz3ZJ2dPmME6F/X44vnOTruvuLVTXTY/T4qrpcxuvn/1y7mEP4/PLxI1V1UpIPJ7nCivXsaBkculuSq3T3I6rqSkm+trtPX7m07T6wTB/rZX32zyT5h5VrOlt3f2T5+P5lTekNM17n/36mgdfFS5L8jyT/bzm+YMZAzFRrvPbQYOHUj80kr8k4V7909p8V9ekkx2xga081BEmSqrpsVT2pqp6/HF+rqu65dl07uG/GlMZrVtWHkjwgyU+uW9KB9sjf89JJbtjdr+3uP8y4JD7FtKGtquphSR63/LtpkkdlTCmazdOTnF5VD19qfn2S2QJkkjwsyQuSXLGqnpHxJvngdUs60PI3fEiSX1ju+qokf7JeRQfq7vcnuWLG1Z73J/lM5nz9/97NjeUE7mZJbrVeOQf1qCRvrqqnVNVTk7wpyaOXRe5/u2pl+/vVJC9M8o/d/fdV9fVJ3rNyTTt5ZFVdPGON6YMy1qTM2Kzq9zOmWf/QcvzpJL+3XjkHdZ+Mc5DLZ0wH/+bleCrLFd3Tk9wxyQ9kTL++x7pVHeAC3b0JZlluX2jFena0NH66+zKYnaq64rI+fzZTPza7+/3d/fKMQP6q5Ur+RzIGi47ZzJ292BDk+RlrUf5nd1+3qo5P8qbu/m8rl7aj5c36uM0Ustnslb9nVV02Y51Ukpze3R9bs56dLPPnr5vx97vuUvMTu/s2K5d2gKWJyXcth6/s7jetWc/BVNXXJPn2jBfF13X3x1cu6QBV9eYk10vyxu6+3nLfW2eaMrgEyOtnNFS5elV9XZI/6+7vWLm0/SzPmV/PuAp166q6VpIbdfeTVi7tAMsVqRtmPDZP7+4Pr1wSR9mmOU1VvWnLc/0tszSn2muq6l1Jbtzdn1iOvybJa7r7GutWtk9VvTrJT2/W4VfVtyb53dmabyxTq7+UMQD3jTUaAL2ou29wmG89ZpYpoU/r7ruvXcvhVNUbMs6RLpnkdRnTWz/T3Xc7Fr9/xpHTw7l0dz8r40GYZc7/TPNV7758/Lka3fF+Ism9thzPZuq/Z5JU1Z0yRtfulDE95/XLNNHZbOalf6GqLpbkY5looXhVbV1H+Mnufszy701VdcfVCjuIqrpDki9092lLh8YvVNXt165rB59bFmBvpl/O2CL4DhlXcf8jSZYgMeM0mKdmXOn5uuX43ZnwKvniuIymFf+a5BtmXNReVVevqpdU1duX4+tU1S+uXdd2VfWoqrpYVZ1/qffjm/fSyXx+OcHcPNdPyPLeOZOqeuwO/x5RVbdbu7ZtPphx9XHj00k+sFItB/OAJH9WVa+qqldlTLW+38o17eTbuvu+Sf4zSbr7kxmzOKbR3V9MckLtja2QaukYfMckj+vuO2QsWTkm9tyasyT/sYyubF4cvz375v3PYHNiNuOJz05m/3smyS8mucHmatnyhvi3Sf581aoOdEZVXSKjU+cbMuaoz7QW4dFJNi3J/2LL7WT8jZ99zCs6tId193M2B939b8sVoL9csaadPKuq/jDJJarqXknukTEtayaf6+6uqpkDZLIMFlXVLyRjsKiqphosSpKq+s0kd8no0Lg5Oe/M1/V0r3QN/p7ufvAyIPPBjIG4l2Wy6cFJHpvkOUkuU1W/ljEVb7qwm8m7iW4ZqP5QxmDrczOeP7fLXO+ZWaYDXzOjy3EleWd3f/4w37aGPTFwkOTMjC7hz8v+HcKn2sonY6bojTLWmG6W+hyzzLQXw9nPZbTgvOpyufmEjBfIKSxros7ujLcHTP33XBy3bRrjJzLhVd/et0/HH1TVC5JcrOfaU6gOcnun4xns9P94utes7n50Vd0iyacy3sB/OfOdpO+FAJnsjcGiJLl9xhTRmZp/7GSvdA0+//Lxe5M8s7v/teZpzLrVn2cMvN084zXz9kk+umpFO5u9m+hm8Pofl38b0+0RWFX3TfKM7t5cfb5kVd21u39/5dK22ysDBx9e/h2XuS9iPCBjHflzuvsdy3rdlx2rXz7dic7hdPcbq+q/Z98oxrtmHMVY/kc+JmO9TCd5bZKf7e73rVrYgf41yX5/z4wFmjN5QVW9MMkzl+O7JHn+ivUcVFVdPsmVszy3quom3T3LiXof5PZOxzM4o6p+O2PBfSf56YwTo6lU1ZO7+x4ZWz2kqi6S5G8yTuCmsFOA7O4Xr1zWTvbCYFGSvC8jUMwezvZE1+CMbRPemeSzSX5qGfX/z5Vr2smzk9y+u9+ZnL3u8MVJZtvgfepuonto8DpJ7tXdZzd96e5PLgNcU4Wz7n7Gsk7q7IGD7p6pC2KS/bb0ueg43NdsZSZbtvS48HL8vozOksfEnmkIcrg1Md091ZSsqnpdxknlJlD8YMai0m9br6oDLU/m23b3h5bjmyT5vQkbgtwxyXdmvOi8cut0t1lsmer0/2Xfur3u7ik6NlbVv2Vc0amMha6b0FhJvrO7L7lWbTtZXhR/KaNrUjJGfn+tu//j4N917FXVIzKm4/3ksgj7tCR/1N1PWbm0s1XVb3b3Qw533wxqNCWaffDtLzKa/7wkWwJadx+zN+8jsQwSPiGj7fcnk/xTkrstHTunsjx3PrUEiAtlzDyYqq36clJ+UsY0wStmDCQ8qLtftGph29TouPyLSV6e8Ty6SUajnWcmeXh3//x61e2zhPAHJ/mm7L/9zDT7rNbYF/C6y7riTVOLt3b3N61b2VBVlzrU57v7X49VLUeixnZDT0+yqfvjSX6ku9+xXlUHWqY0PinJRbr7SlV13SQ/sWWG1NH9/XsonB3qRKeXketpVNXrtwexqnpdd3/7WjXtpKpukDECdJuMNUi/nuQ23b36otyq+oYkl+3uV2+7/yZJPtTd/7jzd66jRuep68w61Wm54nxQy0jRNKrq2pupJLNbggxvjRcAACAASURBVPnFM0bQT+3uv1i5pP3U0mVu231TdZRMkqr6kZ3u78n2Cqyqk3e6v7ufdqxrOZSqukp3/1Nt6Rq8uW/t2raqqvNnbDWzaaryiiR/MGkwv2/G9g4nZpysvWbdinZWe6CbaFW9KKPBxoMyWqyfnOSsmQaNqup/Zfy//oOMK9D3SfKB7n7gmnVtVNU/ZdS1mQe8OanfbEI9TVOyJKmq12R0B3/ZcvzdSX69u6faN66qXp8xa+N5va8z69u7+9rH5PfvlXC211TVqUn+LcmfZjxZ7pKxq/zvJXONZiwjBH+YMY3kpO4+a+WSkiRV9ddJHrp93VZVXT+jWcRULeprbEtwp1kv0++kqr6llxbBs6mqv8voNvWUjHUo/7ZySfvZdjW/Mq7ynZ6xN9sUV/Or6ieT/FRG19CtgxkXTfLqnqylcVU9bsvhBTKm6Lyxu2ec2ji9g4TyN3T3VNPwquqJGdNEN+H2h5N8sbt/fL2q9qn9Oy1XRn1vy9jfbsZmBpsrkVfL/lekZplin2TfY3HrQFFVvaK7DzmQeCxV1XEZXbc30wVflLFFznSNivaC2mHriZ3uW9vmAkuttG3GnllzVodpQz/hi+Ndlo8/se3+e2SEtVVHM6rqr7L/OqMLZcxPf1JVZZKpeCfu1FCju8+oqhOPfTk7W04oO2Nj3zdX1dRTnbZ5Yvbv2jiN7v7Oqrp6kh/LWH92epKnTLRWavvgwJsyTjBvk/F4WD2cJfk/GeszfyPJKVvu//RMA0Qb3f3TW49rbEz89JXKOUBVPau771xjT8MDRjZnuRJZo7vcNyW5+LZBhItly8n6RG6w7aTnpVX1ltWqOdD2xgXPOcj9U6ixufP9MzbOfXPG2vfXZmzqPpPNldGPVNVJGY0irrBiPQfosT3O45d/06qql3T3zQ933wTeV2Oj7M3r+t0zplvP5gNVdeMkXaP1/88kOWZr+PZMOMu+F8FrZGxG/Lzl+DaZrzNauvsqa9dwGI9eu4AjcKiTiAsesyoO74zl4xuy73G5Mful6Slbom1097tr7Mt0RkY3quvVaOP20LWvTHX3j635+49Ed/97xqDLXZe1EpfNeN2/SFVdpLv/edUCD+8zGaP/s7j/8vH7Vq3i8K6RUeMlsv8gwqeT3GuVig7ti1V11c1U9WWt3DRXJvZYA4tkPE5vkOR13X3TJazP+N/wyGUA5oFJHpcxePCz65a0vy3TBvczy3TBqrpARsOXSy9XSzfv6RfLvv0iZ3KPjMfis7P0EMgYgJ3NfTKa+l0+Y8uHFya577H65XtuWuMyR/n7u/vTy/FFk/xZd99q3cr2V2Pj5Bcsc/x/MePqxCO6+00rl7ZnVNUzk7y0u/9o2/33zNgX5y47f+c6qur+3f2Yw903k6q6fXfPtm9YkqSqrpPxon1SRke0J/Xo1vp1SV7b3VdetcDFsqj9XhnrEs4e8JppHWxV3S/JwzPafp+9L9csV3o2tl3RPy5j089ndfcpB/8uDqaqbtTdr127jsOpqptnTF9+X8YJ25WT/NhmXcosliv5D8qBz/WprkhV1d939w2q6s0ZmxP/V1W9ubtn68Q8vRpbe2xcIGMPvkt19y+vVNJ+qur+GW3fvy4jRGzC2acyGlP97lq1cc7txXD2zozOOf+1HH91krd09zXXrWx/mznUVfWdGVOKHp0x2j9Ft8aq+nR2vqqzWUR6sWNc0oGFVF02Y/rI57Kvhfr1M9Yh3WHCTl47re84e77yDGp0wrt1xgalybhM/4Je9sOZSVW9MmMT3T/v7s9u+9wPd/cU092WBc6vyniMnj3aP1NTkKp6b8ZJ2ifWruVQtjWt+UKS93f3B9eqZ7u98Lq51TKqfs8c2A1vmoGDjeW9/OyNfpNcf3szqLUtUy3/IAc+16fa4qOqnpMxsPWAjKmMn0xy/u7+3lULW2xZCrCjyZcCpKr+rru/c+06NpZZEQ/t7kesXcvBLOfCX79p7lRVf559HRsf2d0vXa24HdTK22HtpWmNG09Pcvry4tNJ7pBkqk5ei80L90lJHt/dz62qh69Yz366e8q58lt190eT3Liqbppk0yHntAmfxHdN8kNJrlJj1/uNi2ZsmD2F5YrTyzL2OXpTxknQ9yX5raq66UzdvJY3mw8cLIDNEswWF5qpu9hBfCBzbua8n56sY+h2e+F1c5unZwSdWyb51SR3yzFcN3E4y/P8zhlTh57f3W+tqu/LWN9zwSTTDGwtvtDdU689SpLuvsNy8+FV9bKMTrIvWLGk7c44/JfMoaq2DrgelzFAPNXrQI/tJ743ybThLGMq49Y1xddI8qMZUzIfmmSq87qM9dq/l5ExkrEd1jOTHJMLLHvuylmSVNW3Zux5lYw9r6abKrh0GvxQxh5N35qxuebps3Wk2aiqy2T/kdXZ16JMo6qunOQq2aHpQsZ+KFNclaqqpyZ5c3f/zrb7fybJt3b3ju3B11JVL8jYg+9za9dyKFX1yCSv6e6/WbuWg6mqJ2W8GZ6W/ZvVTNVIaa9cmaqxsfMHl+li353kOkn+eMKOom/q7uttmclx/iQvnGUa3vKadMWMLqffluT9GSPVvzDjdOtlgPVjGTM6tj6PpmuukyRVdfkk51sOPzzLe9FesoTbjS9kNK/4re5+10ol7aiqfiXJW5M8uyc8sd9Mtd1y/OzuvuNy+9Xd/R3rVXegWnk7rL0azrYubE8yX5iosYnmrZK8rbvfU2PPkf/W821Wedskv5UxX/ljGXP9/6En2WCR3VNV7zzY9N+qeld3X+NY13QoVfWHGWs1n5fk7I2nJw0UF844Wft8JgsSSVJVD9vp/tkaHVTVryb5l4wrPpVxpeei3f2oVQvbZlnLc/2MtUcvzHiMXmOWaWMbVXV6d99wmSL8Uxl/29Mnambw9oy9Ib+0TMH8eJJvmG3K+sbSHGK7nujv+QsZ0xd/dTn+54wtfb4qydO6+zfWrG+7Zb3uQzLWlk65CfVeseV96AsZ2yJN9T5UVe/p7h2bO1XVe7v7G451TYdSK2+HteemNVbVTyd5WMbC9i9meQBmjFxOo7s/U1Ufy7jC956MJ8x71q1qR4/IGKn822WE9aZJ7rpyTXtSjZbVv5nkMhmPy6leHDOu3h7MZ45ZFUfuw8u/4zLZNJKt9sJUt9lC2CHcctto5eNrbAY6VThL8qXu/kJV3SHJ73T346pquhkcSZ6wdHD7pYwAeZHl9iw+16NVebr7P6vq3bMGs2RPdGG+U5Lv2nL8ieV9/XwZG3tPFc6SPCNjE+qTsmUT6lUr2qaqfj3JozZXxZfn0wO7+xfXrWx/e+B96J1VdVJ3n7b1zmUa81RXIRerboe158JZRovYa+yBhe0PyxhZvUZGF6rzJ/mTJFNduk3y+e7+RFUdV1XHdffLquo31y5qj3pUktt09zRrOrbZvufRRmW03Z3K7IGiqq7Z3e/ctibhbD3R5t7L1Jyd2kHPNkL9xaq6W/aNVt41E7VU3+Lzy1rTk7OvVf35V6xnR939xOXmK7Ly3poHcc2q2uxlWUmuuhxvBramGHStqpt190sP8vo5xYbzG939H1sOH7Pc98Wqmmn7mY2v6e4n1ehq/Iokr6iq2dad3rq7H7o56O5PLuu7pgpnydnBcdaNx382yWlV9QNJNu+N35rkxplwa5K1B2L2YjjbEwvbMxYRXi/Lg7C7P1yj7f9s/q2qLpKx18Qzlqt9U81L3wNXpDY+OnEwS8b/4+0bJ2/93BSq6tIZ+4l8MsmTk/yvjNHgf8wYsXzviuVt9XNJ7p0xLXi7zlwbvj5oy+0LJPn+TPY8X/xQxgnlYzL+hq9e7pvNj2WM9P9ad/9TVV0lY/BtClV1hSQndvffLcc/l3HVLEn+z0TPoW9cu4AjdJOMhgU7vX7OsuF8MvYvPH93fz5JuvupydmdMGd7v0z2wCbUSc5XVV/d+zqEXzBjettUavKNx7v7vTW2x7lbRvfYZJx33Ke7/3O9yna2XG0+KQdum3FMllXsuTVne2hh+2au/xu7+1uq6sIZezPNMhJ4yWUE6MIZ092Oy3jSXDzJM2a6MlmjDfjMV6SSJFX1mCRfm+Qvs/9jc5Y37j2hxl6GZ2RMZdzsf/RXGQHtbt393etVt09V3XHz/7aqLjVrU4CDqapXdPd/P/xXspOq+qokV18O37U5IZ5BjT0in9Hdf70cvyvJE5JcKMk1u/tua9a311TV/XrZL6qqvqm737F2TTtZpuB9bZL7dfdnlvsunOR3k/xLd//CmvVtt0xpe1VGU5jNJtS/0t3PO+Q3HkNV9eAkt814H+qMaW3Pm3Ad7Nuyb+Pxb65l4/GebD/YvaKq/iZj7d7bsm9v0GM2o2cvhrO9srD9QRmXl2+RMc/7Hhkjlo9btbDFcoXsrCSvyRidfk13v3vdqnY2YyefnVTVU3a4u3uSPYWq6ne6+wHL7f02x66qp3b3j65W3BZV9Zbuvm5VVcY+V1fa8rlpNlKtLfva1Q573M2kqi615fC4jOkkj52lCUxVPbi7H1UH2f+oJ9v3qEaHxqclOTPjSv4Vk5w8yxSi7Y/H2rLfYlW9qru/6+DfzXZ75bm+jPb/WpIfz+h8mSRXSvKkJL/YujWeI1V164yBwkryou5+4colHaBsPL6raulwu9bv33PTGjchrKouvG1u9VS6+9FVdYuMXdqvkeSXu/vFK5d1tu6+TFVdPWO+742TPGjpnPS6JK+eYVRoy/z+M6rq/2byK1Ld/WNr13AYN9ly++Qs6xEWU1zRXXwxGam2qj6+7XNf2uHr11IHuT2jN2SEnsq+dtD3XLWi/W2uiu+V/Y9+K8n39NJOe3ktfWZG6J3BBbYd33zL7a85loWcS+yJ53p3fzHJKTXaqm+63723uw/VDGo1yznHvXLg1LEpBjQ3uvv5SZ6/dh2H8cGqukTGedKLq+qTGdNEOWeeX1Xf0yt1WN9z4ayqbpQxCnSRJFeqqusm+Ynu/ql1KzvQEsamCWTbLVfK3p3kqTX27fnejDnL35M5uqNtnd//mYy6Nmaa55/k7BO0xye5bHdfe5lffdvufuTKpW3siROMJF9fYzPv2nI7y/FM3dIuWFXXy7gSdYHl9tl/15kagqy9uPlwuvuvllH/a3f3z69dzxE4f2/Z56i7311jD7FZfLqqrr6ZDbGZcrtMdfp/q1a2N1186cx5XJKLbW8MMuFA4WczpmPN7rkZ0xr/NnM2/klVfXvGlMtvzNiS4HxJ/mO2Ne89/8bje83rkjynqo7LClvk7MVpja9P8gMZc3430zTe3t3XXreyofbOJqqbK2Y3ypiS876MB+PrkryxJ9r4t6q+o7tffbj71rZ0mfr5JH846WPzLUm+O+ME46XL7U2YeFlPskF6VR1yHdTS1Wt1tf/mpNt1T9AJsaouljFY8J7l+E5JNl3bXtjdH12tuB1U1Utn+LsdTlU9OeN1/unLXXdPcr5Zrp5X1a2SPDZjitvWzmgPTXL/5UrANKrqahnT/7fvdzVFh8mDTFnfmGbq+l6zF6bdVdUZSX4wyZ9ldOD+kYy9+P7nqoVtU2OPyFdlLFGZblbZsibuUOfGM83eSVW9L8ntM/YqPuZBac9dOUuS7v7AWI5ytmlGXHr+vSY2/i7jTfu3k/zlZvHwpB6XsRnx4e5b24W6+/Rtj82Z5vhfPGN626bArVd2phmlmSV8HU5333TtGo7AozPWlW72WPyNjOk5F8wYnLnPSnUdzJuWK6V/lv03Hp/qykSSn8zoKPozGc+nVyT5/VUr2qK7X7Bc3XlwRo1J8vYkd+zut69X2UE9JWP/0v+d5KYZ3TCnubo/S+g+F/rrqvre7v6btQs5lB6dBs+3TBt9SlW9Zu2adnBmxtYjj10uErwqySu7+7mrVrXPdO3yD+M9Sd6+RjBL9mY4+8By1aeXblk/k33rFVa3beH9ASbq6PZ12bfe7D5VdXzGyfprM7pKvm/N4pKzp7DeOMkJNVpBb1wsY2rBbD6+TA/tJKmxn8dH1i1pP/+9u99/+C/jXOQG2X8TzU93908nSVX93TolHdKlknwi+7d/nm4Kc4+22r+9/EtVfU9GB+FbrFnXVksI+5G16zhCF+zul1RVLa9RD6+qV2UENr5MtfPei/+e0WBp9QHDLTOMKslDq+q/ssLUsSP0meVc881V9aiM9/QLr1zTAbr7yUmeXFVfm+TOGdun3Duj6/HqDnbuUVXfkbFdyn2PbUWH9ZEkL6+q52eFzvB7MZzdJ6ORweWTfDDJizLX/9StC++3O+q7ih+p7v6XjBOeTSvwC2V0lPyVjHU9M4Sfr8pYW3h89n+B+VTG1NbZ3DejXfU1q+pDGU0X7r5uSft5Tua72sjRdfy2kb8f3nL7Ese6mMOZ/QpFVd0syR9kDG79ZZJfT/LHGa/3v7ZiaXvdfy5rO95TVfdL8qGMfS05Z34/47V+s6H3tZfbX1NV91mrycHGHpphlIz38OOS3C9jI+UrZuwTOZWqemLGtOCPZlw127rZ81Sq6pszAtmdM86Tphp8W/zT8u+rln/H1J5bc8buqKqLZ6w321w9u16S92Zprd/df75iefupqit39/tn79C5UWNfmeO6+9Nr17LV1nbanDcs6wxvuQzGbL3/8kmeP+E8/6m7t1XVmzJO0F6b5NYZweyXesu2FHz5quoGGTNgLpHkERmzIx7V3a9ftbA9qqr+NMkjetmPraqulbEe+hFJnr32Oq+qumWSi24/z6iqH0py1gydrZd1kI9OctWM5ioP6u4PrVvVwVXVczIGjf6/jGnWr5xhBtTG0jDtBzOmXn4iyf/N+JteedXCDmOt8849E86q6puSXLWXzQmr6n9nrKFJkt+dpTNaVV2zu995kGkF03Rwq6qzMpp/vGb5d/rE7XbP7tDZ3dN26Kyq+2esnfh0kj/KGLk8Ze1Ryo0ae9v96cE+3/PtJXVCkofkwCYBUzSMONhzfGOG53pV3T2jA+sDk7xpuftbMk46HtvdTz/Y965hWcvxqowZCGevJe7uv1itqC3qwP3D/rG7r7pmTedWVfXo7n7Q2nVstyyrODH7Dx788WoF7WCnRhub+2ZowlFVr0tym+4+a9v9X5vkOd19o3Uq26+WV2UMvrwyYxPqG3X3HQ/9Xeurqm9McsuMQaTzdfcVVi4pSVJVX8p4bb9nd793ue99szT92W7t8869NK3x1IzF7Bu3TPJLSS6U5JczuqrM4IEZI7+/tcPnOvuvpVhNd5+wdg1fht/J+P/9vCTp7rdU1U0O/S2ruEd3P2YZFbxMxqL2p2RMvZ3BZzNOeveKZ2SMrp2UMZ355IyN02ex03N8Y4rnenf/SY294h6Z5Jsy6npHxr6LU3XsW1youx+ydhGHcIltbdRr6/EsjUvqIJt5b8w2EHMQm3Uz06iqp2dcSXlz9g0edMZJ/EzeVVWPz77BuLskeXdVfXXG2q61XWh7MEvGcotl5skMLtrdf7Tc/l9Vtfpg26FU1fcl+a6M/UwvmdGR+VWrFrW/78+4cvayqnpBxmNzmqY/O1j1vHMvhbPLdffWDjmf2oymVtVPHOR7jrnu/7+9Ow+zq6rSP/59CUMiQpChoWlmhNgYmYcwNKINPii0oogIIuIPQX8qQ+h+bAZpBBUQ7KaZBEFAEAiDDcqgUcAwT4IMiYqKICpgIyAQGcTA23/sfZNTN7cqCVbdvU+xPs9TT91zblVqpW7de88e1lreJ39uQyW31qi5QmdDJ8D3AOfkJ3NNLz5P2T63dBALYBnbZ0k6IFdwvCG3K6hCW57jtqfSnn43tVdvu4GB/RebxzUVLmlLM++h1PTa2bExsE6pCm4LYC/g08CBpN/jzaSB7l9J1TBLGytp4e7iJEq9AscN8j391t27clzzuIadEV3eTVrlO9F2dc2nbV9O6hu2OGkxZTKwfJ5EuLyWHUZNJa872zQ4G5BAantS47CaxOG29RVqiaordDbcLemHpIIqh0haAni1cExN1fSum0+dGd7HJe0APAZUsUWjKRfTOQhYxfa+OVdhgu2rCofWRgdQcfW22guWdLRlEmaI6saizsHZDGAF6qrCOxfbL0r6GnCVG83SsxqakF8GnCnps518nnzRfhL1THA8Tq7Gmv2hcVzFzggASR+zfa7tz3SdXxj4lu3dCoXWU368LwAuyM//XYCDqWSHkaRJtm+n8HVnm3LOppHyd+7oOj8JONb2NkUC6yLpDFITwG/m4weZ01dolu2q+gqpBQ2eJS1LqtC5Lalq0g9IjVSfKhpYl1xtbH3gIdvPSFoG+Afb9xcOrZXyNo2bSNWxTiYVCTiyk3daC0kXk7aL7ml7oqRxpHYUVTdXDaOXpCsZelvje/sYzqAkPcwQ1Y1ry0fJ1yHrA3cysLx2Fb/PDknvBY4HFrW9eq6Od1QtceaBw5eATwCdEuurkHJ8Drddw9bLVsjbLU+3fUbj3OKkarK/tb13seBaqJNX3HXdKdLgsW/XnW0anG1Kyj/5JnPKg25EykPZ1fadhUIbIFfz2rCz7aFZIU/Szba3Khpgl+4E98HOhfmT3xQ7+5JvsH1lyXjCyJN0l+2Nu57r99ler3RsbSFpD9vn59sDJofy7Pop5aJrH0lvH+p+t6TRe20G+73W9vuUdDdpZef6xmvS/a6vOus44M358MFai5LVLK8+TQXOt31SLqT1PeA62weXja59arn+bc22Rtt3StqM1Gtir3z6p8CkyrYKtqKvkFrU4FnSGqQZjEmkWdbbgMmuqEwsgKRjSU1/L8in9pe0he1DCobVWpJWB/Zj7spoVcz+NrycLzI6EzJr0phVr0EuBLAzc/8ujyoVU5eDgPPz7ZMZ2I/v/wExOFsAtQ0WRosW/V5n2X62rpTnueXB2PTScbSZ7aclbQt8X9KKwPuA02yfVDi0tlpD0qC7c/p1/dGawRmA7SdIlRlr9qqkFZz7CtmeAbP7CtWUf9SmBs8XAqcC78/HHwamAJsVi6i39wDr234VQNK5pPLlMTh7bb5D2uZyJXU9d7odQZq5XFnSBcCWzJlAqsV3gWdJ2y+rGjhmGuR2r+Pici7xVNszJX2eNJj8Ui1FAiRdYvtDkqbTY3tjbSsobZHTKE4G/pH0HjoGeL6WnMiGGUo9w8bkHNj9SS1zwijTqBZ7Bikn7jrg953ztVSQbZE/MnQl5r5o1eCsJY4HrpTUq6/Q8cWi6tKofvei7eOa9+ULj1+ViawneWA/pvMlfbZYNENbCng63x4/1BeGeXqpDbN/tq/J+/4nkQYSB9h+snBY3VayvX3pIIbgQW73Oq7B4bYvlbQVqdzyV4HTqGfC6ID8eceiUYw+p5AmBy8lVW7cE1iraES97QccRpqIuZCUp/2lohG1WOXpCs3qsVd0naupgmxbzKxhhbw1OWdtIml74FAG9hU61hX2Fao556xRyetzwDOkvhgm9WxZzPYXS8XWi6TdSP34ppEu0rcGDrE9aOPnMLg887sWKRG3mXxfy+pEKxrOw+xCRSfbrnILkaQXgAdJz5s1823y8Rq2a+l9BMzJJZZ0DDDd9oXNnMMa5QT3p2otA58HumvZPifnzbzR9sOl42pq5JfOzt+SdKvtLUrH1iFpDKky9LalY5kfkt5Eep0f2zln+8ZyEQ2Un+ObMiddYTfgrkhXGJ0kXeYKmo23bnAmaaztl7rOLVvhTHXVJL2btA3vQ6RCKx1Lkvq4bFoksIa2VfICkPT3pLwzAXeQBpGPDP1doZf8pvhR4NfM2dZo27WUMD7DqXT+tB53VxMngKSfkRLvHyYNdDsl6qvY3iZp1aHur+05JOkq4FFSJa+NSA3e76ylCEynijFpFf+LwLeAZUnVbvd06n1XDUlHkFaiJtheO+fOXGp7y8KhDSDpRtJj/g1SafXHgb1qedw7cs7MR20/WzqWoUj6BGmVdyVSY+9JpEq3Nb123s/AdIUxwD21vHaG0amNg7PpwD5OfQiQtDNwjO21y0bWLpLWI5UEPoqBeXwzgWm2/1QksJbKBVb+AbjR9hOS1iX17vgn2yuXja6dJD0ArGu7bf3ZqjPY4Ke2QU9bKPW22560avarPCnzNlfSSFXSXaTdG+NJuSjvtn27pLcAU2pb4ZN0L7AB8JPKqwuuCvwvKd9sMun3+zXbDw75jX0m6RLSQOca4PnOedv7Fwuqh3w9twlwu+3189/nkbZ3LRzabHlwto3tp/Px0qQqmFX9bYbRpY05Z7sDZ0u6HlgRWIZKmgG2ie37gPskXegW9BSRNBFYh4FbH84rF9Ecko4n5XbcC/x7nlX/NHA0qdJceG3uI+XwPVE6kHlRala5GgMrIVbx9wlpENZr21jpuNrK9guSvgssL2mVfPqBkjF1WbgzUJR0VGcyM2/DLRtZby/btqROxdOqtrF25OfRcvn2kaXjGcLV+aN2L9l+SRKSFst/nxNKB9XlGOCevENidrpC2ZDCaNe6wZnt6ZK+TNqmMRPY2vbvC4c1F0mrd++X73WuAqvl7WPdA59qtgzmLS/bkGL8HvBu4GaglovfHYAN8pvMm4DHSCs+NRVVaaPlgQck/Zi6G75+i5QndS/wSj5t6vn7HLBtDDgHWIRUur6qbWNtIWk/UpXO/6Wx5RaoZTa9Wd20u3dUjdtlLpH0dWApSfuQJrXOLBzTbEoj2iNIrXwELCRpFimPs5Z2FLPZPrd0DPPp95KWIlXmvUbSn0jvn9WwPSUvBnTSFf69U427NrVPErZNyUIwbdzWeBbpQujjwNrAfwOn2D61aGBdBim0cbftjUrF1Iukm0lvOieQKvx8nPR3cUTRwBry1of1SPu815O0PPAN2/8yj2/ti+7HVdK9ttcvGdNooPY0fP05KU+z2hfTtmwbawtJDwKb2X6qdCy9SHqFtJ1NwDjghc5dwFjbi5SKbTCStgPeRYrxB7avKRzSbJImk3K0esvrjgAAEudJREFU9+1MsCr13zyN1FLhhJLxdUh6H6ky66n5+A5guXz352x/u1hw85Bf78eTfp/Ft7K3qeATDD5JWNtW1rYoXQimdStnwAzgE/lC6OGc+PxfhWOaLe+ZfiswXnP6T0AqtDG293cVNc72dZKU80++IOkm0oCtFi/aflXSLElLkra5VbOyB6ypgU0LV2se17bS0xadQVh+zGt+rZoBrEAqDlCrVmwbk7Ql8AVgVdJj3ilcUtPzHeB3pL5xVbI9pnQMCyKvnjwDXAL8ssJCFnsC2zULj9l+SNIepGqyVQzOSJWNP9w4Xoy04rM4acW8usFZLrCxPKlYEaTX0t+Wi2i2g4B96d3zytSXTrMxlU8StswOFOxbW/MFT0+2T5C0qqS1bF8LvAwcWDquhgmk/KOlGNh/YiawT5GIhvaSpIWAXyn1DnsU+LvCMXW7K795n0lqovtn4M6yIQ3wvq7j4g0MRwNJ+5Iqzb1I2qYl0ptibRfqywI/k3Qn9W6/7N42tjep4lxtziIVWribObO/NXoIuF7S1Qx8zKuZKGwDSYuSCpbsRPqdLgSsKuly4FM1rKBki/SqCG37j5JqWoVc1PbvGsc359Xdp2qckKl5e7DtffPnd5SOZT61YZKwbYr1rW3jtsZ9SLMZS9teU9JawOm2/7lwaANI2tz2baXjmBdJmwA/J/0RfpH0B3hcJ4G8NpJWA5a0fX/hUMIIk/QrYPNeF0U1adH2y862MUjbxq4tGU8vku6wXUsj50HlHL65VF4kojqSjiJtxfqU7Zn53BLAqcAjtg8vGV9HrzSF+bmv3yQ9aPvNg9z3a9tr9jumodS+PRhS+yZSga+tSAPHm0jXnC8N+Y19lguWrE+auK51krA1VLhvbRsHZ/eS9oHe0cidmG77bWUjSySdzBAJ17H/d8FJug74T9vfa5w7ozOzFUYnSVOBD9h+YZ5fHHqSNJM5r0fdZfpeIvWQO8z2dX0NbBCSjgXGAJdRYePxMLwkzQA27X6OS3ojqbz6xDKRDdTI4ZvrLirK4ZN0AanM+5ld5z9JKge/W5nIessDiu1szyody2CU2hLMJBVQgpR79Cbbu5SLam5tmSRsE3X1re1nIZjWbWsE/mL75U45YEkLU1f1qbtKBzA/unKk5lLZbMvqpBL1mzRmpjcuGVDoi0OAW3NSe/NCvaoJjpz3ejLwj6T+R2OA520vWTQwwPYSg92Xcz0mkhKeq7gIBjqrZs3nd3X5Hbmc+udI+cXNKrdVxdkCr/aafLH9505+ZA1alMM3GfiOpN2BzoTGRqTcs52KRTW4NmwPnuCBTcanSbqvWDSDiEHY8JL0fuBHtq/Ix0tJ2sn2d/rx89s4OLtB0qHAuLxN59NA38pbzkuLSthuTkpqnwLcwdyz6jV5Bvhn4CRJVwJ7FI6nJ0lju7c6SFq29m15Ffs68CNgOgNLg9fmFFIS/qWkQcWewFpFI5oPtl8h9To8uXQsHS3K77gAuJiUX/wp4GPAH4tG1E5Waj/S6/2n5ud8lWw/AWwh6Z2kiQOAq23/qGBYQ/lt/lg0f9ToHkmTOqkekjYDbikc01xqniRsqSNsX945sP1M3s7el8FZG7c1LkRKZp9dcpdUVr2q/0herp8rplpmVvOs+XakJfp1SQ0rp9j+adHAepB0T2ML617Av5K2FaxUNLAuueT/Po0X8Z2BY2yvXTaydpJ0q+0tSscxL5Lusr1xszR9W2KvkaQdmHtFqqpeUp32GV2P+Q22e24tCr1J+g1ziv10q7FKZxgBOc/Qtv9cOpaO/H5uUk/ICaRBpEmVZH9Wy5bbDkl30WOS0PahRQNrKfVoNdPPFKrWrZzlspZnUlGDykH8W+P2WGBnoJp91XnWfCowVdJipEHa9ZKOsl3NTHp2eueG7W/mF83PFIxnMLsDZys1rFwRWIbKtmO1zLRcsfFKBm55eXrwbynihVx17l5Jx5GqZVVXGa0NJJ0OvAF4B6ma5AepqzJrx1/z58fzYPIxoKrJojawvVrpGEI5kiYC3wKWzsdPAntWMkm8Y+kAFpTtByWNydd350i6tXRMLXaXpP8iFScysB+pinBftGblrDGL0VP3CLdGtc2s5kHZDqSB2WrAFcDZth8tGVeHpCVtPydp6V73V3iRjqSdSG82M4GtbT9YOKTWkvRwj9PVzaZLWpVUCnpRUs7HeOBr8dgvuM5sZePzG4HLbL9rnt/cR5J2JFVtW5m0lWhJ4MhOfkIIYd7y4OEw29Py8TbA0TXuOpD0dwxcza+hF9tskm4EtiVNav2BNEm4V1e+XJhPufXE4aTfKaR+hl+23asw0LBr08pZq2YxugYUC5GSclcoFM5clBrqTQS+T7qomFE4pF4uJD3ud5MG5s2tL9X1u5J0Fqks9LrA2sCVkk6xfWrZyNrJ9uqlY5gfth/JBSKilPrf7sX8+QVJKwJPkQoCVcX2Vfnms6RVvhDCglu8MzADsH19bf3YJL2X1Lt0ReAJ0rbGnzMnp68WHyVda36WNEm4MmnHVlhAOe3nu7a3necXj5DWDM5sP9LrvKQtSdvJatvm1hxQzAIeJuXK1eKjpNLAawP7d6pfkhv91pBEanvH/Lm6i7NBzAA+kfMfH84JujVVnWoFSZ+zfVy+vYvtSxv3HV3LHnqlJ80RpDdDAQtJmgWcXFuOVItcpdRw/nhStTlTUbPsaJUSwrB6SNLhpN0mkIp99doxUdIXgUnAtbY3kPQO0m6jqsQk4fCx/YqkFySNt/1siRhas62xSdL6pAHZh0hP5MsqzJMKfyNJQzb2rLH3Ud7itpbtayWNAxZ2bq4a5o8aTV3V1eC1+7gkSZOB9wD72n44n1sDOA2YavuEkvG1Xd52PbbUm2Mvkj7WODySNDifrUXVeqsi6avAOZXkGoU+yZU6jyQ1eBZwI/AF238qGlhDo+DTfcAGtl+VdKftTUvHBr0nCUkLAjFJ+DfI/e0mAdfQ6HHYrwm41qycSVqbVIlmN9JWl4tJg8sqt5RIegNwELCK7X0lrUXql3HVPL41zPGfQ9xXY++jfYB9ScnNa5IKBJxOagMQ5p8Gud3ruKQ9SQ1UZ7dKsP2QpD1I+9NjcLaAJO3Z4xy2zysRT7fm4EvSgTEYGzYPAGco9S09h1Q5uJpBeRgZeRBW+2rzMzn39UbgAklPUFFxN+BAYEtgk+5JQkmTY5LwNbs6fxTRmpUzSa+SErD37iTaS3qotuIAHZIuJm1t3NP2xLyKcpvt9QuHFkaIpHuBTUmd5Dul//tWenW0aNHK2YzByikPdV8YnAb2XBtLmtj4ie0PFgppUDX9LY4WkiYAHydNwt4CnNnMSQqjg6QhC+fYfm+/YhmMpFVs/zbnwL1IWpH6CKng0wW2nyoaYCbpHromCfP55YAfdq5FQru0ZuWMlNj4YVJ57anARdQ1i95tTdu7StoNwPaLaiR2hXlrS+5Rw19sv9x5mPMscDtmP+qynqTnSM/vcfk2+Xjs4N/Wdy+/xvvCIGzv1zyWNJ45+ShhFMtJ+G/JH08C9wEHSfqk7Q8XDS4Mt82B3wFTgDuo81ruO8CGtp+X9D+2dwZqXClfpHtgBmD7j5IWKRHQaJB3ux0DrMPAKp19WRBaqB8/ZDjYvtz2rqQX7utJ1WiWl3SapKrKLGcv59UyA0hak0avpjBfmm/Ih3Tdt30/A5lPN0g6lDSg2I7UDPLKwjG1ju0xtpe0vYTthfPtznFNbzbrSXqux8dMIFZLh8cLwFqlg+iQNLPzOAPrNh/zxiRCWEBK/YR+QcrhPNr2Rra/YvtfgJj5H31WAA4lVYw+EdgOeNL2DbZvKBrZHM0BY5U7tLKYJBwZ55Dyx2eRKvKeRx8nCtu0cgZA7jFwAWnv79LALsDBpByPmhxBavK8sqQLSHuC9yoaUfu0Jfeo42BSRc7pwCeB71FRpbkwvGyPKR3DaCPpSuasNo8hzVpeUi6igWwvUTqGUWoG8HnbL/S4r4rCC2H4ODVJngpMzYV/dgOul3RURcXdPMjt2qw3yMRQbTtN2mac7eskKVeL/4Kkm+gqAjVSWpNz1kaSliFVexFwe6+l5zC4tuQehRCGh6S3M+dCaBbwiO1HC4YURlAbK/KG4ZEHZTuQBmarAVcAZ9fyfJf0CqlKn4BxpFV8qKjdUBg5km4B/gn4NvAj4FHgWNsT+vLzY3A2MnL/tXvzfuU9gA2BEwfr1xbmNo8Xx7G1bHGTNJ2hex+t28dwQmidvBW0u9E8+dxfgF8Dh9m+rt+xhZEjqVPsYyywMSnPTMC6pMJKW5WKLYwcSeeStjR+H7jI9ozCIYUwgKRNSM3GlyL1uhsPHGf79r78/BicjQxJ9wPrkd5kzgPOBj5g++1FAwvDLvc2G1QMyEN47XKhiImkCmlRAXMUknQR8GXb0/PxRODfbO9VNLAwInL17U7vqOZFaKxKhUALc85aZJZtS3ofcJLts7oamIZRYrDBV1493R34TH8jCmH0yPkp93WV2Q+jy1s6AzMA2zMkRduZUcp2a4rRhdeXWto8xOBs5MyUdAiwB7B1nv2tYhteGDn5gmJ34EPAw8BlZSMKYXSw/fXSMYQR83NJ3wDOJ62k7EHaUhRCCP1URZuH2NY4QiStQLpI/7HtmyStAmxj+7zCoYVhJmltUtn/3YCngItJW3KG3O4YQggBJI0F/j+wdT51I3Ca7ZfKRRVCeL3JCynbka7n1gWuBqbY/mlf44jBWQh/m7x//iZgb9sP5nMP9atZYQghhBBCGD6NNg/HA31t8xDbGodZo+rYXHcRia6j1c6klbNpkqYCF1FnH7YQQqhOzs/9ArAqjeuSmOAKIfRbjzYPJ9HnFJVYOQthmEhaHNiJ9IR+J3AucLnt2hqkhxBCNSQ9AEwG7gZe6Zy3/VSxoEIIrzu1tHmIwVkII0DS0sAuwK6231k6nhBCqJWkO2xvVjqOEMLrWy1tHmJwFkIIIYRiJB0LjCFtHfpL57ztnxQLKoQQConBWQghhBCKkTStx2nHroMQwutRDM5CCCGEEEIIoQLRpT2EEEIIxUhaXtJZkr6fj9eRtHfpuEIIoYQYnIUQQgihpG8CPwBWzMe/BA4sFk0IIRQUg7MQQgghlLSs7UuAVwFsz6JRUj+EEF5PYnAWQgghhJKel7QMuXS1pEnAs2VDCiGEMhYuHUAIIYQQXtf+FbgCWFPSLcBywAfLhhRCCGVEtcYQQggh9J2kA4FbgHvyqQmkZq+/sP3XYoGFEEJBsa0xhBBCCCWsBJwIPAFcC3wEWBVYomRQIYRQUqychRBCCKEYSYsCGwNbAJvnj2dsr1M0sBBCKCByzkIIIYRQ0jhgSWB8/ngMmF40ohBCKCRWzkIIIYTQd5LOAN4KzATuAG4Hbrf9p6KBhRBCQZFzFkIIIYQSVgEWA/4APAr8HnimaEQhhFBYrJyFEEIIoQhJIq2ebZE/JgJPA7fZPqJkbCGEUEIMzkIIIYRQlKSVgC1JA7QdgWVsL1U2qhBC6L8YnIUQQgih7yTtTxqMbQn8ldTz7Lb8ebrtVwuGF0IIRUS1xhBCCCGUsBrwbWCy7ccLxxJCCFWIlbMQQgghhBBCqEBUawwhhBBCCCGECsTgLIQQQgghhBAqEIOzEEIIr1uS9pJ0Suk4QgghBIjBWQghhPCaSBpTOoYQQgijSwzOQgghVE3S4pKulnSfpBmSdpX0G0lfkXRn/nhz/trlJP2PpB/njy3z+U0l3Srpnvx5Qo+fs4Ok2yQtK+ld+fZPJF0q6Y35a34j6T8k3Qzs0tdfRAghhFEvBmchhBBqtz3wmO31bE8Epubzz9neFDgF+O987kTgBNubADsD38jnHwC2tr0B8B/A0c0fIOn9wMHAe/KpzwPb2t4QuAs4qPHlL9neyvZFw/mfDCGEEKLPWQghhNpNB74q6SvAVbZvkgQwJd8/BTgh394WWCffD7CkpCWA8cC5ktYCDCzS+PffAWwMvMv2c5J2BNYBbsn/zqKk5sgdFw/z/y+EEEIAYnAWQgihcrZ/KWkj0qrWMZJ+2Lmr+WX580LA5rZfbP4bkk4Gptl+v6TVgOsbdz8ErAGsTVolE3CN7d0GCen51/6/CSGEEAYX2xpDCCFUTdKKwAu2zwe+CmyY79q18bmzsvVD4LON710/3xwPPJpv79X1Ix4BPgCcJ+mtwO3Alo08tjdIWnvY/kMhhBDCIGJwFkIIoXZvA+6UdC9wGPClfH4xSXcABwCT87n9gY0l3S/pZ8Cn8vnjSKtutwBzVVm0/QvgI8ClwJKkAdwUSfeTBmtvGYn/WAghhNAk2/P+qhBCCKEikn4DbGz7ydKxhBBCCMMlVs5CCCGEEEIIoQKxchZCCCGEEEIIFYiVsxBCCCGEEEKoQAzOQgghhBBCCKECMTgLIYQQQgghhArE4CyEEEIIIYQQKhCDsxBCCCGEEEKoQAzOQgghhBBCCKEC/welOea2lalLZAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"top_20_speakers.plot(kind='bar', figsize=(15,10))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I looked up Alex Gendler, and it turns out he does a lot of something called [TED-Ed Lessons](https://ed.ted.com/search?qs=gendler), which seems to be different from a typical Ted talk. Let's exclude that event - we can filter it out by looking at the event column."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['TED2011', 'TEDxNTU', 'TEDGlobal 2011', 'TED@UPS', 'EG 2007',\n",
" 'TEDWomen 2021', 'Sleeping with Science', 'TED2018', 'TEDxOgden',\n",
" 'TED2017', 'TEDxUSC', 'TED-Ed', 'Small Thing Big Idea', 'TED2007',\n",
" 'Countdown', 'TED2009', 'TEDxMidAtlantic', 'TED2019',\n",
" 'TEDMED 2009', 'TEDxStockholm', 'TEDGlobal 2009', 'TEDSummit',\n",
" 'TED1990', 'TEDGlobal 2017', 'TEDxMileHigh', 'TED@BCG Berlin',\n",
" 'TED2020 ', 'TED2016', 'TED Salon Zebra Technologies',\n",
" 'TED@BCG Paris', 'TED2013', 'TED@NAS', 'TEDxDoha',\n",
" 'TEDxManhattanBeach', 'TED@BCG Mumbai', 'TED in the Field',\n",
" 'TEDSummit 2019', 'TED Studio', 'TEDxAmazonia', 'TEDxBeaconStreet',\n",
" 'TEDxRiodelaPlata', 'TED@IBM', 'TEDGlobal 2005', 'TED Membership',\n",
" 'TED Residency', 'TED2002', 'TED Salon Brightline Initiative',\n",
" 'TED-Ed Weekend', 'TEDGlobal 2012', 'TED2004', 'TED@Unilever',\n",
" 'TED2014', 'TEDMED 2018', 'TEDGlobal 2013',\n",
" 'TED@BCG San Francisco', 'TEDxJacksonville', 'TEDMED 2020',\n",
" 'DLD 2007', 'TED2022', 'TED2010', 'TEDxLusakaStudio',\n",
" 'TEDWomen 2020', 'TEDMED 2016', 'TED Salon: Belonging', 'TED2008',\n",
" 'TEDIndia 2009', 'TEDxMaastricht', 'TEDxKakumaCamp',\n",
" 'TEDxCopenhagen', 'TEDCity2.0', 'Body Stuff with Dr. Jen Gunter',\n",
" 'TEDWomen 2010', 'TEDNYC', 'TEDxNASA', 'TED@BCG Milan',\n",
" 'The Way We Work', 'TEDxCambridgeSalon', 'TED2003',\n",
" 'TEDWomen 2019', 'We the Future',\n",
" 'TED Countdown New York Session 2022', 'TED2015', 'TEDMonterey',\n",
" 'TEDGlobal>London', 'TEDWomen 2015', 'TEDSalon Berlin 2014',\n",
" 'TEDGlobal 2014', 'TEDxAuckland', 'TEDxVienna', 'TEDxInnsbruck',\n",
" 'TEDxPhoenix', 'TEDxMarin', 'TEDxGroningen', 'TED2005', 'TEDxTeen',\n",
" 'TEDxBoston', 'TEDxCambridge', 'TEDxFrankfurt', 'TEDxJaffa 2012',\n",
" 'TED@NYC', 'TEDSalon NY2013', 'Toronto Youth Corps',\n",
" 'TED Talks Live', 'TED2012', 'TED@Tommy',\n",
" 'TEDxOhioStateUniversity', 'TEDSalon 2007 Hot Science',\n",
" 'TED@State Street Boston', 'TED2006', 'Skoll World Forum 2007',\n",
" 'TEDxBG', 'DIY Neuroscience', 'TEDWomen 2018', 'TEDxDelft',\n",
" 'TED@State Street London', 'TEDxPenn', 'TEDxUSU', 'TEDxTysons',\n",
" 'TEDxOilSpill', 'TEDGlobal 2010', 'TED Salon Border Stories',\n",
" 'TEDYouth 2013', 'Your Money and Your Mind', 'TEDxDanubia',\n",
" 'TEDxCSU', 'TED Salon: Education Everywhere', 'TEDxMadrid',\n",
" 'TEDxChange', 'TEDxEastVan', 'TED Salon Doha Debates',\n",
" 'TED Fellows: Shape Your Future', 'Taste3 2008', 'TEDxExeter',\n",
" 'TEDxOU', 'TEDxOxford', 'TEDxSanDiego', 'TED Salon Optum',\n",
" 'TEDxManchester', 'TEDWomen 2017', 'TEDxRainier',\n",
" 'TEDxBoston 2012', 'TEDxSantaClaraUniversity',\n",
" 'TEDxImperialCollege', 'TEDxNewYork', 'Mission Blue Voyage',\n",
" 'TEDxIndianapolis', 'TEDSalon NY2014', 'TEDxCannes',\n",
" 'TED Salon Novo Nordisk', 'TEDxCharlottesville',\n",
" 'Countdown Summit', 'TEDxMtHood', 'TEDxMaui', 'TEDxWrigleyville',\n",
" 'TEDxCanberra', 'TED Audio Collective', 'TEDxBerkeley',\n",
" 'TEDxDayton', 'TEDxNewcastle', 'TEDxUCincinnati', 'TED@Westpac',\n",
" 'TEDSalon NY2011', 'TED1998', 'TEDGlobal 2007', 'TEDMED 2012',\n",
" 'TEDxCordoba', 'TEDWomen 2016', 'TEDxPSU',\n",
" 'Business Innovation Factory', 'TEDxShimizu', 'TEDxSydney',\n",
" 'TED@DuPont', 'TEDxGeorgetown', 'TEDxSingapore', 'TEDxZurich 2012',\n",
" 'TEDxWarwick', 'TEDxCERN', 'TEDxKids@Brussels', 'TEDxStanford',\n",
" 'TEDxRockville', 'TEDGlobal>Geneva', 'TED@BCG London',\n",
" 'TEDxDublin', 'TED2001', 'TEDxStCloud', 'TEDxUppsalaUniversity',\n",
" 'TEDxCreativeCoast', 'TEDxHousesOfParliament',\n",
" 'Carnegie Mellon University', 'TEDWomen 2013', 'EG 2008',\n",
" 'TEDxParis 2012', 'TEDxSFU', 'New York State Senate',\n",
" 'TEDActive 2014', 'TEDxCornellU', 'TED@Cannes',\n",
" 'TED Salon Verizon', 'TEDxGateway', 'TEDxWomen 2011',\n",
" 'TED@BCG Toronto', 'TEDxToronto 2010', 'TEDxSummit',\n",
" 'TEDxDeExtinction', 'TEDxLondon', 'TEDxLinnaeusUniversity',\n",
" 'TEDxOslo', 'TED@Merck KGaA, Darmstadt, Germany',\n",
" 'TEDxBinghamtonUniversity', 'Am I Normal? with Mona Chalabi',\n",
" 'TEDxUCLA', 'TEDxYouth@Manchester', 'TEDSalon NY2012',\n",
" 'TEDSalon London Fall 2012', 'TEDxVancouver', 'TED@WellsFargo',\n",
" 'TEDxYouth@Beaconstreet', 'TEDxDirigo', 'TEDxCaltech',\n",
" 'TEDxUCDavis', 'TEDxPortland', 'TEDxMidAtlantic 2013',\n",
" 'Torchbearers', 'TEDxKlagenfurt', 'TEDxZurich',\n",
" 'TED Salon American Family Insurance', 'TEDxLondonWomen',\n",
" 'TEDxYouth@München', 'TEDxAthens', 'TEDxTarragona',\n",
" 'TEDYouth 2014', 'TEDxManhattan', 'TEDxVermilionStreet',\n",
" 'TED Talks Education', 'TEDxRoma', 'TEDMED 2013', 'TED Connects',\n",
" 'TEDxPurdueU', 'TEDxToulouse', 'TED@BCG', 'TEDxVirginiaTech',\n",
" 'TEDxSMCC', 'TEDxKids@Ambleside', 'TED@State', 'TEDxAustin',\n",
" 'TEDxBerlin', 'TED Talks India', 'TEDxBoston 2011',\n",
" 'TEDxSaltLakeCity', 'TEDxSanFrancisco', 'TEDxGatewayWomen',\n",
" 'TEDActive 2011', 'TEDxSeattleU', 'TEDxKC', 'TEDxMileHighWomen',\n",
" 'TEDxGöteborg 2010', 'TEDxCHUV', 'TEDMED 2011',\n",
" 'TED Fellows Retreat 2013', 'TEDMED 2017',\n",
" 'TEDxUniversityofNevada', 'LIFT 2007', 'TEDxBrussels',\n",
" 'TEDxOrangeCoast', 'TED@BCG Singapore', 'TED@Intel',\n",
" 'TEDxPennsylvaniaAvenue', '2015', 'TEDxAtlanta', 'TEDxToronto',\n",
" 'TEDxOshkosh', 'TEDxSeoul', 'TED Legacy Project',\n",
" 'TEDxHopeCollege', 'TED Salon DWEN',\n",
" 'In the Green: The Business of Climate Action', 'TEDMED 2015',\n",
" 'TED Salon U.S. Air Force', 'TEDxWanChai', 'TED Masterclass',\n",
" 'TEDxSanFranciscoSalon', 'TEDxChristchurch', 'TEDxUND',\n",
" 'TED Salon UNICEF', 'TEDxDubai', 'TEDxColumbus', 'TEDxKrakow',\n",
" 'TEDxEast', 'TEDxDebrecenUniversity', 'TED Talks India: Nayi Baat',\n",
" 'Build Back Better', 'TEDSalon London Spring 2011', 'TEDxSeattle',\n",
" 'TEDYouth 2011', 'TEDMED 2014', 'Serious Play 2008',\n",
" 'TEDxToronto 2011', 'TEDxPerth', 'TEDxNextGenerationAsheville',\n",
" 'TEDxSoMa', 'TEDxUofT', 'TEDxNashville', 'TEDxNorrkoping',\n",
" 'TEDxUofM', 'TED Fellows Retreat 2015',\n",
" 'Justice with Michael Sandel', 'TEDxRosario 2017',\n",
" 'TEDActive 2015', 'TEDxSMU', 'TEDxGlasgow', 'TEDxPeachtree',\n",
" 'TEDxNYED', 'Chautauqua Institution', 'TEDxOakParkWomen',\n",
" 'TEDxYouth@Sydney', 'TEDSalon London 2010', 'TEDMED 2010',\n",
" 'TEDxSandhillsCommunityCollege',\n",
" 'How to Deal with Difficult Feelings', 'TEDxBloomington',\n",
" 'TED Dialogues', 'TEDxLondonBusinessSchool',\n",
" 'TED Salon Bezos Scholars', 'TEDxTokyo', 'TEDxStLouisWomen',\n",
" 'TED Salon The Macallan', 'TED en Español en NYC', 'TEDxYYC',\n",
" 'TEDxUniversityofRochester', 'TEDxSurrey', 'SoulPancake',\n",
" 'INK Conference', 'Full Spectrum Auditions', 'TEDxLeicester',\n",
" 'TEDSalon London Spring 2012', 'TEDxBeirut',\n",
" 'TEDxHampshireCollege', 'TEDxBristol', 'TED@Bangalore',\n",
" 'DICE Summit 2010', 'TEDxOrlando', 'TEDxZurich 2013', 'TEDxSBU',\n",
" 'TEDxFiDiWomen', 'TEDxSalem', 'TEDxKyoto',\n",
" 'Countdown Global Livestream', 'TEDxUF', 'TEDGlobal>NYC',\n",
" 'TEDxBend', 'TEDxVeniceBeach', 'TEDxCoventGardenWomen',\n",
" 'TEDxIslay', 'TEDxSeattleWomen', 'TEDxLSU', 'TEDSalon London 2009',\n",
" 'TEDSalon 2006', 'Monday.com', 'TEDxGalway', 'TEDxMiamiUniversity',\n",
" 'TEDxVCU', 'Design Matters with Debbie Millman',\n",
" 'TEDxColoradoSprings', 'The Hartford', 'TEDxOakland',\n",
" 'TEDxPittsburgh', 'TEDGlobalLondon', 'Princeton University',\n",
" 'TEDxMemphis', 'Far Flung', 'TEDYouth 2015', 'TEDxSanQuentin',\n",
" 'TEDxParramatta', 'TED Salon Belonging',\n",
" 'TEDSalon 2009 Compassion', 'TEDxMICA', 'TEDxAmsterdamWomen',\n",
" 'TEDxThessaloniki', 'TEDxBerkleeValencia', 'TEDxHogeschoolUtrecht',\n",
" 'TEDxMidAtlantic 2017', 'TEDxHouston', 'Mission Blue II',\n",
" 'TED Salon: Border Stories', 'TEDxPasadena', 'TEDxFoggyBottom',\n",
" 'TEDxBoulder', 'TEDxSanMigueldeAllende', 'TEDxYouth@CEHS',\n",
" 'TED@Nairobi', 'TEDPrize@UN', 'TEDxSydneySalon', 'TEDxParis 2010',\n",
" 'TEDxLeuvenSalon', 'TEDxCMU', 'TEDxPlaceDesNations',\n",
" 'TED Salon UNDP', 'TEDxFondduLac', 'TED@PMI', 'TEDxBasel',\n",
" 'TED Fellows 2015', 'TEDxEuston', 'TEDxDetroit', 'TEDxBoston 2010',\n",
" 'TEDxSiouxFalls', 'TEDActive 2013', 'TEDxValladolid',\n",
" 'TEDxCuauhtémoc', 'TEDxColbyCollege', 'TEDxZurich 2011',\n",
" 'TEDxMinneapolis', 'TEDxSussexUniversity', 'TEDxUM',\n",
" 'TEDxVillanovaU', 'TED Salon: Radical Craft', 'Bowery Poetry Club',\n",
" 'TEDxNaperville', 'TEDxGreatPacificGarbagePatch',\n",
" 'The TED Interview', 'TEDxHull', 'Arbejdsglaede Live', 'TEDxUMKC',\n",
" 'TEDxSouthBank', 'TEDxNSU', 'TEDxOrcasIsland', 'TEDxUFM',\n",
" 'TEDxCUNY', 'TEDxBoulder 2011', 'TEDxNorthwesternU',\n",
" 'Web 2.0 Expo 2008', 'TEDxUniversityofMississippi', 'TEDxCU',\n",
" 'Global Witness', 'TED@New York', 'TEDxMidwest', 'TEDxAmsterdam',\n",
" 'TEDLagos Ideas Search', 'TEDxParis', 'TEDxHultLondon',\n",
" 'TEDxWomen 2012', 'TEDxABQ', 'TEDxBratislava',\n",
" 'TEDxRotterdam 2010', 'TEDxMidAtlanticSalon', 'TEDxMalvern',\n",
" 'TEDxSaintThomas', 'TEDxBoston 2009', 'TEDxEindhoven',\n",
" 'TEDxBrighton', 'TEDxStLouis', 'TEDxConcordiaUPortland',\n",
" 'RSA Animate', 'Gel Conference', 'TEDxWinnipeg',\n",
" 'TED Salon Samsung', 'TEDxBrisbane', 'TEDxGoodenoughCollege',\n",
" 'TEDxRiga', 'ZigZag', 'TEDxDU 2010', 'TEDxRosario', 'TEDxLeuven',\n",
" 'Stanford University', 'TEDxStormontWomen', 'TEDxMuncyStatePrison',\n",
" 'TEDxProvincetown', 'TEDxBoise', 'TEDxYorkU', 'TEDxCrenshaw',\n",
" 'TEDxMonashUniversityMalaysia', 'TEDxSF',\n",
" 'TED Salon Education Everywhere', 'TEDxHerndon',\n",
" 'TED Salon Dell Technologies', 'TED1984', 'TEDxSalford',\n",
" 'TEDxDU 2011', 'TEDxUTAustin', 'TEDxMIT',\n",
" 'TEDSalon London Fall 2011', 'TEDxUIdaho', 'TED@SXSWi',\n",
" 'TEDSalon 2008', 'TEDxColumbusWomen', 'TEDxMalagueta',\n",
" 'TEDxUWLaCrosse', 'TEDxMet', 'TEDxWellington', 'TEDxNantes',\n",
" 'TEDxNijmegen', 'TEDxDePaulUniversity', 'Handheld Learning',\n",
" 'TEDxFIU', 'TEDxGhent', 'TEDxIEMadrid', 'TEDxWaterloo',\n",
" 'Fort Worth City Council', 'TEDxMcMinnville',\n",
" '2021 US Presidential Inauguration', 'University of California',\n",
" 'TEDxEastEnd', 'AORN Congress', \"TEDxO'Porto\",\n",
" 'TEDxGoldenGatePark 2012', 'TEDxNashvilleSalon', 'TEDxRC2',\n",
" 'TEDxUWA', 'TEDxPitic', 'TEDxNASA@SiliconValley', 'TEDxChapmanU',\n",
" 'TEDxFargo', 'TEDxBahiaBlanca', 'TED@Johannesburg',\n",
" 'TEDxSantaCruz', 'TEDxGatewayArch', 'TEDxNashvilleWomen',\n",
" 'Harvard University', 'TEDxLivoniaCCLibrary', 'TEDxPortofSpain',\n",
" 'TEDxJaffa 2013', 'TEDxUSN', 'TEDxTemecula', 'TED@MotorCity',\n",
" 'TEDxUIUC', 'WorkLife with Adam Grant', 'TEDxTufts', 'TEDxJHU',\n",
" 'TEDxCreightonU', 'TEDxUofSC', 'TEDxBroadway',\n",
" 'TED Global Idea Search 2021', 'TEDxArendal',\n",
" 'TEDxCambridgeUniversity', 'TEDxCaFoscariU', 'TEDxLincolnSquare',\n",
" 'TEDxClearBrookHighSchool', 'The Do Lectures',\n",
" 'Elizabeth G. Anderson School', 'TEDxTelAviv 2010',\n",
" 'taken for granted', 'TEDxPuget Sound', 'TEDxBellevue', 'TEDxNewy',\n",
" 'TEDxTC', 'TEDxCesena', 'TEDxAmoskeagMillyard', 'TEDxTinHau',\n",
" 'TEDxUofW', 'TEDxSuffolkUniversity', 'TEDxEQChCh',\n",
" 'TEDxCapeTownWomen', 'TEDxObserver', 'TEDxRapidCity',\n",
" 'TEDxJacksonHole', 'TEDxSkoll', 'TEDxBariloche', 'TEDxProvidence',\n",
" 'TEDxEdmonton', 'TEDxMonterey', 'TEDxKeene', 'TEDxQueensU',\n",
" 'TEDxSnoIsleLibraries', 'TEDxAustinWomen', 'TED1994', 'TEDxSSE',\n",
" 'TEDxGuangzhou', 'TED and Minderoo Foundation',\n",
" 'TEDNairobi Ideas Search', 'TEDxTaipei', 'TEDxAsheville',\n",
" 'TEDxCapeMay', \"Eric Whitacre's Virtual Choir\", 'TEDxGrandRapids',\n",
" 'TEDxUCSD', 'TEDxOmaha', 'TEDxDesMoines', 'TEDYouth 2012',\n",
" 'TED@London', 'TEDxIndianaUniversity', 'TEDxNatick',\n",
" 'TEDxWitsUniversity', 'TEDxConnecticutCollege', 'TED Prize Wish',\n",
" 'World Science Festival', 'TEDxFergusonLibrary',\n",
" 'TEDxCoconutGrove', 'TEDxSHHS', 'TEDxUTFSM', 'TEDx SHORTS',\n",
" 'TEDxUCIrvine', 'TEDxUW', 'Checking In with Susan David',\n",
" 'TEDSalon NY2015', 'TEDxConcorde', 'TEDxYouth@Bath',\n",
" 'TEDxEasthamptonWomen', 'TEDxMonroeCorrectionalComplex',\n",
" 'TEDxAmericanRiviera', 'Michael Howard Studios',\n",
" 'TEDxBeaconStreetSalon', 'American Family Insurance',\n",
" 'TEDxWalthamED', 'Conversations with People Who Hate Me',\n",
" 'TEDxTimberlaneSchools', 'TEDxHelvetia', 'TEDxHamburg', 'BBC TV',\n",
" 'TEDxMIA', 'TEDxMontreal', 'TEDxTAMUSalon', 'TEDxUdeM',\n",
" 'TEDxFulbrightDublin', 'TEDxBerkshires', '', 'TEDxSiliconValley',\n",
" 'TEDxSonomaCounty', 'TEDxBocaRaton', 'TEDxCherryCreekWomen',\n",
" 'TEDxSavannah', 'TEDxUCL', 'TEDxReus', 'Currently',\n",
" 'TEDxAlbertopolis', 'TEDxPennQuarter', 'TEDxSanJoseCA',\n",
" 'NextGen:Charity', 'TEDxAarhus', 'TEDxCalzadaDeLosHéroes',\n",
" 'Royal Institution', 'TEDxUniversityofGlasgow',\n",
" 'TED Senior Fellows at TEDGlobal 2010', 'TEDxClaremontColleges',\n",
" 'TEDxPaloAlto', 'TEDxParcDuCinquantenaire', 'TEDxUGA',\n",
" 'TEDxYouth@Valladolid', 'TEDxUHasselt', 'TEDxVictoria'],\n",
" dtype=object)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['event'].unique()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"speaker\n",
"Matt Walker 18\n",
"Jen Gunter 11\n",
"Juan Enriquez 11\n",
"Hans Rosling 9\n",
"Wendy De La Rosa 9\n",
"Mona Chalabi 9\n",
"Bill Gates 9\n",
"Greg Gage 8\n",
"Marco Tempest 7\n",
"Al Gore 7\n",
"Michael Green 6\n",
"Rives 6\n",
"Jacqueline Novogratz 6\n",
"Dan Ariely 6\n",
"Barry Schwartz 5\n",
"Paola Antonelli 5\n",
"Julian Treasure 5\n",
"Kristen Bell + Giant Ant 5\n",
"Clay Shirky 5\n",
"A.J. Jacobs 5\n",
"Name: speaker, dtype: int64"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"not_ted_ed = df[df['event'] != 'TED-Ed']\n",
"not_ted_ed_speaker_count = not_ted_ed.groupby('speaker')['speaker'].count()\n",
"not_ted_ed_top_20_speakers = not_ted_ed_speaker_count.sort_values(ascending=False)[:20]\n",
"not_ted_ed_top_20_speakers"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1e6daea3a90>"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"not_ted_ed_speaker_count.plot(kind='hist', figsize=(15,10), bins=not_ted_ed_speaker_count.max())"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1e6db3c37c0>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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ddfHFF+9QWQAAAAeObQe4qjosyf2T/MUmd78zya26+6gkT0ny11s9Tnef2t1Hd/fRhx9++HbLAgAAOODsRA/csUne2d2f3HhHd3+uu/91vn1GkqtX1Q134DkBAAAOOjsR4E7IFsMnq+rrqqrm28fMz/fpHXhOAACAg84+r0KZJFX11UnuleSn1517RJJ099OTPCjJz1TVZUn+PclDuru385wAAAAHq20FuO7+fJIbbDj39HW3n5rkqdt5DgAAACY7tQolAAAAVzEBDgAAYBACHAAAwCAEOAAAgEEIcAAAAIMQ4AAAAAYhwAEAAAxCgAMAABiEAAcAADCIQ1ddAAD71xEnnb7jj3n+ycfv+GOOUicA7E964AAAAAYhwAEAAAxCgAMAABiEAAcAADAIAQ4AAGAQAhwAAMAgBDgAAIBBCHAAAACDEOAAAAAGIcABAAAMQoADAAAYhAAHAAAwCAEOAABgEAIcAADAIAQ4AACAQQhwAAAAgxDgAAAABiHAAQAADEKAAwAAGIQABwAAMAgBDgAAYBACHAAAwCAEOAAAgEEIcAAAAIMQ4AAAAAYhwAEAAAxCgAMAABjEoasuAABGdsRJp+/o451/8vE7+njJzteYqHOnXRV1AgcmPXAAAACDEOAAAAAGIcABAAAMQoADAAAYhAAHAAAwCAEOAABgEAIcAADAIAQ4AACAQQhwAAAAgxDgAAAABiHAAQAADEKAAwAAGIQABwAAMAgBDgAAYBACHAAAwCAEOAAAgEEIcAAAAIMQ4AAAAAYhwAEAAAxCgAMAABiEAAcAADAIAQ4AAGAQAhwAAMAgBDgAAIBBCHAAAACD2FaAq6rzq+q9VXVOVZ21yf1VVU+uqvOq6j1VdaftPB8AAMDB7NAdeIy7d/entrjv2CS3m7/ukuSU+TsAAABfoat6COUDkjy3J29Ncr2quslV/JwAAAAHpO32wHWSV1VVJ/mj7j51w/03S/KxdccXzOc+sfGBqurEJCcmyS1vecttlgUAcHA74qTTd/wxzz/5+B1/THXunBFqTNS5Xdvtgbtrd98p01DJR1bVd2+4vzb5md7sgbr71O4+uruPPvzww7dZFgAAwIFnWwGuuy+cv1+U5MVJjtlwyQVJbrHu+OZJLtzOcwIAABys9jnAVdW1quo6a7eT3DvJ+zZc9tIkPz6vRvltSS7p7isMnwQAAGDvtjMH7sZJXlxVa4/z/O5+RVU9Ikm6++lJzkhyXJLzknw+ycO2Vy4AAMDBa58DXHd/OMlRm5x/+rrbneSR+/ocAAAA7HJVbyMAAADADhHgAAAABiHAAQAADEKAAwAAGIQABwAAMAgBDgAAYBACHAAAwCAEOAAAgEEIcAAAAIMQ4AAAAAYhwAEAAAxCgAMAABiEAAcAADAIAQ4AAGAQAhwAAMAgBDgAAIBBCHAAAACDEOAAAAAGIcABAAAMQoADAAAYhAAHAAAwCAEOAABgEAIcAADAIAQ4AACAQQhwAAAAgxDgAAAABiHAAQAADEKAAwAAGIQABwAAMAgBDgAAYBACHAAAwCAEOAAAgEEIcAAAAIMQ4AAAAAYhwAEAAAxCgAMAABiEAAcAADAIAQ4AAGAQAhwAAMAgBDgAAIBBCHAAAACDEOAAAAAGIcABAAAMQoADAAAYhAAHAAAwCAEOAABgEAIcAADAIAQ4AACAQQhwAAAAgxDgAAAABiHAAQAADEKAAwAAGIQABwAAMAgBDgAAYBACHAAAwCAEOAAAgEEIcAAAAIMQ4AAAAAYhwAEAAAxCgAMAABiEAAcAADAIAQ4AAGAQAhwAAMAg9jnAVdUtqup1VfWBqnp/VT1mk2vuVlWXVNU589fjtlcuAADAwevQbfzsZUn+R3e/s6quk+Tsqnp1d//9huve0N333cbzAAAAkG30wHX3J7r7nfPtS5N8IMnNdqowAAAAdrcjc+Cq6ogk35LkbZvc/e1V9e6qenlV/ec9PMaJVXVWVZ118cUX70RZAAAAB5RtB7iqunaSFyV5bHd/bsPd70xyq+4+KslTkvz1Vo/T3ad299HdffThhx++3bIAAAAOONsKcFV19Uzh7Xnd/Vcb7+/uz3X3v863z0hy9aq64XaeEwAA4GC1nVUoK8kzknygu393i2u+br4uVXXM/Hyf3tfnBAAAOJhtZxXKuyb5sSTvrapz5nO/nOSWSdLdT0/yoCQ/U1WXJfn3JA/p7t7GcwIAABy09jnAdfcbk9Rernlqkqfu63MAAACwy46sQgkAAMBVT4ADAAAYhAAHAAAwCAEOAABgEAIcAADAIAQ4AACAQQhwAAAAgxDgAAAABiHAAQAADEKAAwAAGIQABwAAMAgBDgAAYBACHAAAwCAEOAAAgEEIcAAAAIMQ4AAAAAYhwAEAAAxCgAMAABiEAAcAADAIAQ4AAGAQAhwAAMAgBDgAAIBBCHAAAACDEOAAAAAGIcABAAAMQoADAAAYhAAHAAAwCAEOAABgEAIcAADAIAQ4AACAQQhwAAAAgxDgAAAABiHAAQAADEKAAwAAGIQABwAAMAgBDgAAYBACHAAAwCAEOAAAgEEIcAAAAIMQ4AAAAAYhwAEAAAxCgAMAABiEAAcAADAIAQ4AAGAQAhwAAMAgBDgAAIBBCHAAAACDEOAAAAAGIcABAAAMQoADAAAYhAAHAAAwCAEOAABgEAIcAADAIAQ4AACAQQhwAAAAgxDgAAAABiHAAQAADEKAAwAAGIQABwAAMAgBDgAAYBACHAAAwCAEOAAAgEEIcAAAAIPYVoCrqvtU1blVdV5VnbTJ/VVVT57vf09V3Wk7zwcAAHAw2+cAV1WHJPnDJMcmuX2SE6rq9hsuOzbJ7eavE5Ocsq/PBwAAcLDbTg/cMUnO6+4Pd/cXk/x5kgdsuOYBSZ7bk7cmuV5V3WQbzwkAAHDQqu7etx+selCS+3T3T83HP5bkLt39qHXX/E2Sk7v7jfPxa5L8YneftcnjnZiply5Jjkxy7j4VtrUbJvnUDj/mThuhxkSdO02dO2uEOkeoMVHnTlPnzlLnzhmhxkSdO02dO+uqqPNW3X34xpOHbuMBa5NzG9PglblmOtl9apJTt1HPHlXVWd199FX1+DthhBoTde40de6sEeococZEnTtNnTtLnTtnhBoTde40de6s/VnndoZQXpDkFuuOb57kwn24BgAAgCthOwHuHUluV1W3rqrDkjwkyUs3XPPSJD8+r0b5bUku6e5PbOM5AQAADlr7PISyuy+rqkcleWWSQ5I8s7vfX1WPmO9/epIzkhyX5Lwkn0/ysO2XvM+usuGZO2iEGhN17jR17qwR6hyhxkSdO02dO0udO2eEGhN17jR17qz9Vuc+L2ICAADA/rWtjbwBAADYfwQ4AACAQRyQAa6qDqmq/77qOvZkXtjlFnu/cvU2q7Oqvm4VtcDIqupaq67hQOL1hH1TVd9VVYdsOHenVdUDfGUOyADX3V9K8oBV17EnPU0+/OtV13ElfaSqTquqr1537oyVVbOFqnryJl//u6oW9W+hqg6vqt+pqjOq6rVrX6uu60BQVdevqm9edR0bVdV3VNXfJ/nAfHxUVT1txWVdQVU95sqcW7VRXk92TlX9WFVdZ8O5+66qnj2pqhdV1fFVteTPWK9M8tqquvG6c3+yqmI2qqrrzt+/drOvVde3maq6VVV973z7mhv/vS5BVf32lTm3alV134X//iRJquoH1/4/V9X/qqq/2l8NIYt/cbbhTVX11LmV6U5rX6suaoO3VtWdV13ElfDeJG9I8oaqus18brNN2lftGknumORD89c3J/naJA+vqt9fZWEbPC/TB89bJ/m1JOdn2pZjEarqhfP391bVe9Z9vbeq3rPq+jaqqtdX1XXnN/V3J3lWVf3uquva4PeSfF+STydJd787yXevtKLNPXSTcz+xv4u4EoZ4PavqB6rqQ1V1SVV9rqourarPrbquzVTVbarqq+bbd6uqR1fV9VZd1zpPyfQe9J/Wnfv1VRWzF6ck+eEkH6qqk6vqG1dd0CbOTfJ/k7y+qr5jPrek9/Xnz9/PTnLW/P3sdceLUlX/NclfJvmj+dTNs8xG+nttcu7Y/V7F3j0k0+/PEzf8zi/Nr3b3pVX1nZnek56T6ff/KrfP2wgMYO0P0vo/8J3kHiuoZSt3T/KIqjo/yb9l+uPZ3b20HoTu7qdV1buTvKyqfjHTa7k0t01yj+6+LEmq6pQkr8r0B+u9qyxsgxt09zOq6jHd/XdJ/q6q/m7VRa2z1uOyyNbtTXxNd3+uqn4qybO6+/FLDJrd/bGq3T4ffWlVtWxUVSdk+sB566pav5/ndTOHpKVZ8uu5zhOT3K+7P7DqQq6EFyU5uqpum+QZmfZxfX6mrYCW4CNJHp7kL6vqCd39F1lW4Lhcd/9tkr+tqq9JckKSV1fVx5L8cZI/6+7/t9ICJ93df1NV5yZ5QVU9Mwt6X+/u+87fb73qWq6kRyY5JsnbkqS7P1RVN1ptSbtU1c8k+dkkX7/h/fE6Sd60mqq21t0/OvfCnpCpUbaTPCvJad196Wqr283a+87xSU7p7pdU1RP2xxMfsAGuu+++6hquhCW2emymkqS731RV90zygiRLbFG8WZJrJblkPr5Wkpt295eq6j9WV9YVrL15f6Kqjk9yYabWukXo7k/M3z9a01zHYzK9sb+ju/95pcVt7tCqukmSByf5lVUXs4WPza3cXVWHJXl05uF/C/HmJJ9IcsMkT1p3/tIkiwvDWf7rueaTg4S3JPnyvL/rA5P8fnc/pareteqi1unufmdVfU+S06rqLpn2oF2kqrpBkh9N8mNJ3pVp5MV3ZurlvtvqKrvc2vv6h+beg2dnGrWyCHsbMdXd79xftVxJ/9HdX1xrVKqqQ7OgQJypMeblSX4ryUnrzl/a3Z9ZTUl7NjfMvijJNZM8NskDk/xCVT25u5+y2uou9/Gq+qMk35vkt+dRDPtldOMBG+Dmcd2/mekD/LFVdfsk397dz1hxaZebPyB/Z5LbdfezqurwJNdedV2buLwFtrs/UVX3yK4eziV5YpJzqur1md6cvjvJb9a00MHfrrKwDX5jbpn9H5mGBV03yeIW3Zl7tB6X5LWZXs+nVNWvd/czV1vZFfx6pvkcb+rud1TV12caQrskj0jyB5kaGS7I1DP8yJVWtE53fzTJR+f5G//e3V+uqm/I1FCzpN7rNYt+Pdc5q6pekGko1eWNSN39V6sraUv/b+6JfWiS+83nrr7CejZaa1j6VFV9X5LfTvKfV1vS5qrqrzL97vxpph7YT8x3vaCqljL877+t3ejuzyd5cFUtaRjyk/Zw39JGUyXTSJpfTnLNqrpXpt6ul624pst19yWZGrdPqGnxmhtnygDXrqprd/c/rbTADarq/kkeluQ2mX6Pjunui2pai+EDmT47LcGDk9wnye9092fnxuRf2B9PfMBu5F1VL8/U3for3X3U3Bryru7+phWXdrmqenySo5Mc2d3fUFU3TfIX3X3XFZe2mxHC8Jr5l+eYTIHj7d194YpLGtY8tOY7uvvT8/ENkry5u49cbWVcVarq7CTfleT6Sd6aaa7J57v7R1Za2Drzh4/ndPePrrqWvamqZ21yurv7J/d7MXsx/11/RJK3dPdpVXXrJD/U3SevuLQk02IB87DJ9ece3N0vXFVNW6mqe3T3ohemqqp3dved9naOK6emrrefSnLvTJ8/XpnkT3phH7Kr6lFJnpDkk0m+PJ9e3NSdqnpuptfvzHXnvqq7/6Oq7tndr1lhebuZe4u/M1PDwpv2V+/wgRzg3tHdd66qd3X3t8znzunuO666tjVVdU6Sb0nyznU1vmeBv0iLD8NrqupmSW6Vdb3L6/8ALEFVPTHJbyT59ySvSHJUksd295+ttLANquo1SY7t7i/Ox4clOaO7v3e1le1u7ik6JcmNu/sONa1Cef/u/o0Vl3a5qnryJqcvSXJWd79kf9ezlbUPcFX135Jcs7ufuP5v6FJU1Ssz9Wx8cdW1HEiq6ppJbtnd5666lo1GCBxV9QN7un8JPa9V9e2ZRtA8NtNiQGuum+SB3X3USgrbYITXck1NqyW+p7vvsOpa9qaqzktyl7WG2aWqqmd198PWHV87yUu6+89eUEwAACAASURBVJ4rLOsKqupxSX4wydq/x+/P1BFzlX/+OGCHUCb5t7nHoJOkqr4tu+ZGLcUXu7vnyZlL3tPoht39wqr6pSSZ50ksbsGAmpbC/aEk78+6lqUkiwpwSe7d3f9znmtyQaZf/tclWUSAq6qfm29+PMnbquolmV7HByR5+8oK29ofZxqy8EdJ0t3vqarnZwrJS3GNTEOq1noQ/kumf6cPr6q7d/djV1bZ7mr+gPcjmRaMSJb5PnF+ppWGX5ppAagkSXcvavXRERoX1lTV/ZL8TpLDMi1mc8ckv97d919xXcdmGsZ/sw0NIddNctlqqtrS/fZwX2fXh7xVOizTVI1DMy1gseZzSR60koo2N8JrmSSZh5y/u6puubShiJv4WJb3WXgzH6uqU7r7Z6rq+klOz/RevzQnJPmW7v5CklTVyUnemf3w+WOJb8w75ecyraJ1m6p6U5LDs6w/Tknywnny4/VqWoL2J7OgfVjWGSEMJ1PLx5HdvaQFSzazNq/kuEwrKn2malGLqa29qf/j/LVmMT1FG3x1d799w2u4tA92o6yQ+tgkv5Tkxd39/nk+4etWXNNmLpy/rpbdP4QuzQiNC2uekGn4+euTpLvPmYdRrtqFmYby3j/TEvJrLs3C5g6v7zFYqu7+u6p6Y5Jv6u5fW3U9WxnhtdzgJkneX1Vvz+6NSittANnEhzNtHXF6dp+Xu6jGr+5+XFX9dlU9Pcm3Jjm5u1+06ro2cX6mBtovzMdfld0/N11lDuQA95kk35PkyEzjkc/NtEfYYnT378yTXT+Xqc7HdferV1zWZkYIw8n0h+nqWfdHaaFeVlUfzDSE8mfnxWu+sJef2W+W/Ka+hU/VtD/hWgPDgzIveLAgQ6yQ2ru2tbjWfPzhTCs8Lsrav9GaNlDt7v7XFZe0lREaF9Zc1t2XbKh15XMsetrj791V9fxexvL7e7X0eePz351Fboa90dJfy3VGed/8p/nrsPkrWcDv+ZoNQ2ffnuRX5+9dVT+wlKGzVfWUTK/bf2QK7q+ej++V5I37o4YDOcC9KNNQlfcnSU2rK/1hksXM26qq3+7uX0zy6k3OLUbvWrr58jC80DfSz2dahfI12b1laVEfQLv7pHm45+fmN9J/yzQ8cVHmYPk/M630do218929tNW/Hpnk1CTfWFUfz7Rf1GIW3ZgNsULqPHzyGZmGWN2yqo5K8tPd/bOrrWx3VXWHTCuTfe18/KkkP772935BRmhcWPO+qvrhJIdU1e0yBfc3r7im9Y6oqt9Kcvvs/vfo61dX0paenXne+Hz8D5m231lS6HjXPAT5L7J7j9EiPiCv8+ws/7Vca/xavI0NtFV1jex5uOr+trGWd2VqmL9fljV0dm012bOTvHjd+dfvrwIO5EVM7pzkaZn+p98pUwvO/br7YystbJ0tJmUvcRGTH9/sfHc/d3/XsidV9dDNznf3c/Z3LXtSVVdP8jOZPsQnyd8lefrSQnFVvSrTG+XPZ1qd7qFJLl5aA0NV3bq7PzKHoat196Vr51Zd23o1wAqpVfW2TL3rL123sNL7ljY5v6renGlRpdfNx3dL8pvdvajtTeYhqKdmWjTiXzI1Lvxod5+/yro2U9Py3L+SaRW9ZFpF7zfW5nas2jzs7/GZFt64X6Ylxqu7H7/SwjZRYyyiNsQKqSO8lklSVZdmV0/WYZlCx79193VXV9XmalrJ996Z5m/dO8kbu3sxo6rm+h7d3b+314sXoKYF3r5hPtxvHRwHbA9cT/tBPTrTPJMvJLlXd1+84rKSJFX1M5n2CPn6qlq/Se51krxpNVXt0Z3X3b5GkntmmqS5qAC3tKC2B6dk+uP+tPn4x+ZzP7WyijZ3g+5+RlU9Zt3QuiW2Mr4oyZ26+9/WnfvLTOPml+QLmXpfrpHktlV126WtkJok3f2xDcPoFrdgUZJrrYW3JOnu1y9xEah5COr3rm9cWHVNe3Bkd/9KdvV0LM01u/s1VVU97Vv4hKp6Q6ZQtzSLnzc+0Byzxb+WSdLdu83Frarvz9RgtxjzSLQfTnJ8pmGJd03y9T3tA7gY88ik+2f3VVIXaW48fE6muXCV5BZV9dD98d5+wAW4qnpZdh/P+9WZftmfUVVLmVD6/CQvT/JbSU5ad/7S7v7MakraWnf/t/XHNW1C/acrKucKquqF3f3gqnpvNhnLvbQezSR37t2Xan5tVb17ZdVsba0V6RNVdXymxQRuvsJ6dlNV35hpeOfXbBg3f92sG2K1BDVtiv6YTK/fOUm+LclbsrzNaD9WVd+Rab7BYZmG0X1gxTVt5sNV9avZ9XfoRzP1bi3KQPN3kuR3517iv0jy5wscjvqFmpZr/1BNe1l9PMmNVlzTVhY/b3weOvfwXHGI/KJ64DLAa7mZ7v7rqjpp71fuH1V1Qaa5b6ck+YV5pMpHlhbe1nlzVT010yig9UN898sea1+BJ2VaWfzc5PKVh0/LfmhAPuACXKZlkBetuy/JFCpPmLuKb5zp/8W1q+raAyxD+/kkt1t1Ees8Zv5+35VWceV9qapu093/mFw+zGqJvRy/MYf1/5HkKZmC0ZJWfTsy0//z62X3cfOXJvmvK6loa4/J1JP91u6++xw+lzjp/RFJ/iDToisfzzSM7pErrWhzP5np9furTK2eZ2YaUrc0z84A83eSZP53+XVJHpzk1Kq6bpIXLGjLg8dmapB9dJL/neTumYZ1L84g88b/NMkHk3xfkl/PNG94cY01g7yWGxffuFqSo7OgxUEyjVT5/kxbLX2pdm0PtFRrw+F/fd25zvIaPa/e6/bN7O5/mKfJXOUO2DlwI5hbEZ+Q5JNZt2/Z0nqMNvRqXi3TJPIXdvdiWpdGUlX3zPSh7sOZ3pBuleRh64eEceVV1bd391tWXceerJvHcU6mTVT/Y4nzONhZo8zf2aiqvinTAkY/1N2H7e36/VDPIZmWEf+FVdeyJ1V1j+5+bW2xCfWSFghZ+ze5Nu9+/tD5ygUuUpV5VMARWdfpsMA5+OvnFF6WaUjdH3f3Raup6IpqGht/90xz347L1Cj78CRnLHgl30Wrqmdm+ny8NhrkR5Icuj+GKB9wPXAbJpLudlemcLSkCaWPzTTv4NOrLmQv1vdqXpbko919waqK2Wiw/+eZ53HcLrtaFD+YqbVuEWrX8ribWtqqnplWU3tklj0U6IKqul6Sv07y6qr6l0xDUhdl7g3+g0xDPDvTMM//Ps/lWrmq+s5MczaeOx//ZeaVKDMtuPHalRW3uSHm7yRJVf2nTK3zD0ry6SR/nqn3feXmOTHfOs9/W3Kr8/ckeW02X9VvSSvoJbuGyH+2plVd/zlTSFqUqvrTJLfJNPR8baRKZ3lz8Jc4AmA38+/OazNN27h6kvtkCnNPS3LDVda2pqp+tLv/rKp+brP7e2H71WVakO6RmUYGrI0Gedoef2KHHHABbuNE0oX7WBb6Zr7e0pfHHeX/+dyK/OBMw9Ne3tOmvvfNNCb9mkm+ZZX1rXPW3i9ZlMUPBeruB843n1BVr0vyNUlescKStvL8TNutrNX7kEzj+e+ysop292tJ1s/JPTLJT2TaV++XM304WZKR5u88K9P/63svcYXUTMuJv6SqFrvsfXc/fp6n9/LufuGq69mLU6vq+pn22Xpppq1DfnW1JW3q6CS3X3hwT1U9MclvZNrf9RVJjkry2O7+s5UWtoV5GOrLMu1Le81V17PO2mJUQ3yuy5Sj/mAtWM6f875qfzzxAT+EsqpulN1b5Rczv6yqnpHpA8jp2X3fskW1MIzSw1XTfksXzMPT7pbkm5M8t7s/u9rKJlX17CS3yLT6012SfDRTT8cvdfdfr7C0oQ02FOhmSQ6ZDy/s7kVt6lxVb+vuu2w499bu/rZV1bTe2pDEdcd/1d0/MN9+U3ffdXXV7W5+I390pvmji56/M4IaZNn7JKmqM7v7u/d+JXszB/ZHd/dS909MsmtodFU9MNNcs/+e5HUbFizjAFNVb03yvWtDUKvq2kle1fthS5sDrgduzbwE6ZOS3DTJRZnmGX0g0zCrpfin+euw+Wupfi/T8Io/zfQh5EeSXKe7n7jSqq7oRUmOrqrbZlok4KWZehSOW2lVuxyd5Ju7+8vzCmCfSnLb7v7nFde1qZo28v7FXHHj3KUFo8UOBaqqX8o0yXltIvZbknw20+/7czKtRLskr5tXTvvzTI02P5Tk9Kr62iRZwCq511t/sBbeZjfez7Xs0Tzs7wE97WW0tBUdL7eHVXzXGugWMSd7hCFq67y6qn4+V1xBb9W/P5erqn9M8tYkb0hyZnf//YpL2soNk/x9Vb09uzd0L2FF8fXWFq44Lslp3f2Z2n07Fr4C8+eP/5orzn1cWoPNNdbPH+zuf61pT82r3AEb4DKtUvVtSf52bp1fm7i5GN29xFXoNvN9G1rlT6lpw9+lBbgvd/dlcwvY73f3U6rqXasuap0vdveXk6S7v1BV/7DU8DZ7XqYPIMdn3UbeK61oc0seCvSDSb5r3fGn579Hh2TawH1pAe6H5u8/veH8T2b6cP/1+7ecK/hgVR3f3aevPzkPRT53i59ZpTcNsBT2EKv4VtWTNzl9SZKzuvsl+7uevVj7kLl+Bdcl/P6sd/tMI0G+K8nvzCvjvnvdcO+leMKqC7iSXlZVH8w0hPJn5wDyhRXXdAVV9YPd/Rd7O7cAL8nUuPC3WeYq3Wv+rarutPY3vaq+NdO/gavcATuEsqrO6u6ja9pf61vmXo+3d/diNlac58Jstm/Zono4qurNmebFrLXKn5Dkkfuji/grMYfK38+0ZPf9uvsjVfW+7r7DiktLklTV55Oct3aYaWL2eVlYS/eaqjq7u791bWjifO7vuvt7Vl3bKKrqnd19p3XHP9Hdz55vn93dS9tsfNHm3vXTk7w5yVoI+tZMS07ft7v/YVW1bWb+G79RL+1v/GbmRoaHdPfzVl1LklTVqUm+MdM+dUnyXzL1bN4iyYe7+7Grqu3KqKrDuvuLq65jTVUdmmlrk+9J8p1JbpDkPd29sfFm5WraT3Ft6PTbl7Sy43pzQ+Ln5t73r05y3aU10m58T9rq3KqNsFpvklTVnTN9Nl6bN3yTTKv3nn1VP/eB3AP32Xks6plJnldVF2VaQXFJfn7d7WtkekNaWo1J8sOZVqb7g0wB7k3zuaV5WKaeov8zh7dbJ1nSBOL/tOoCvkJL38j75kmO6O43zsc/l6n3LUme393nbfnD+8+1q+rqa/Oe1oW3r8q0hPOizB/aj88Vh60sYl5ud59XVd+caRj32nD4M5M8orsX19rd3XdfdQ17U9N+b4/MtLjSS5O8OsmjMr0/nZOpJ34JbpvkHmvzRqvqlCSvSnKvJO9dZWFbqbp82fYfzrQy5ZKG+X4u0+v2u5mWu1/kathV9eAk/zfJ6zM1dj6lqn6hu/9ypYVt7mZJ7jVPkViziNUyq+rYTMM7b7ahN/u6Webnzr+pquO6+4xVF7In3f2Ouff68lXF99c85wOuB66qrt/d/1JV18rUjXm1TG/2X5PkeUv9I7VGD8f2VNVhSb5hPrRgwDbMw9LekKmFe20j71/r7peutLBZVZ2W6Xf6b+bjc5Ocmmmz32/s7h9ZZX1JUlW/meTrkjyquz8/n7tWkqcm+efu/qVV1rdRVZ2RadjPe7Nrb8qRhnsvwiCNC0mSmjb0/ZdM8zPvmeT6meZoPqa7z1llbevNv9/HdPcl8/HXJHlbd39jrdtnbwmq6i6ZQtsDM21z8cgkL+3uf1lpYetU1QMy9bwdk+SLmXq1z+zu16y0sA3mUVT3Wut1m4cm/u3SFgepqscnuVumoalnJDk2yRu7exGrzlbVUUnumGml5setu+vSTIutLOLf5rpF8yrTipT/kV0Bs3shi+atN8+937hWwFUe3A/EAHdRpnk6b87UU/TmpQ2rWbO2MMDsapmGAj25u49cUUm7qar/2d1PrC32BeuF7QdW08qTz8m0gWZlCh4P7e4zV1gWV5FNhieu3yz5Dd39XVv/9P4x92j9nyQ/lWnV0SS5ZaZFdv5XL28VysuHy7LvRmhcWFNV7+3ub5pvH5JpcaVbdvelq61sd1X18CT/K7t6Yr47yW9m2vrgCb2ATb6r6v9k2irmnzLV9eJMc/RuvdLC9mDuPTg20760N+ruJS0pv9u/z/n4apnm6n3THn5sv5sXAToqybu6+6h52OefdPdmewKuzPoRIWzfKoP7ATeEsrtvVFXfkGlOxHck+fm5xeatSd7Uy1o58ezsamm4LMlHkjx8pRXtbm0vrVH2BXtSpj2Mzk2S+d/BaZmCMV+hAVaBusaG43uuu32D/VnIVrr7S0lOqqpfyzQELEnO6+79Msl5H7y8qu7d3a9adSGDO3ItvM0+391PSqbGhRXVtJXLP8zNc3c+srTwliTd/Yy5h/iYTO+Zv9y79qtbeXibnZhpMZ1TkvzNvFjVIlvJq+pFmXpkzss00uLHk7xtpUVt7hVV9cpM7+XJtNDSy1dYz1b+fV5r4bJ5WPJFWdaiNWuOqaonZFqZ/dDsmoO/iFqr6lZJPruup/3umbZlOD/JHy5pHunsQdkV3B+2Ftz3xxMfcAEuSeYet39I8uya9gY7LtNKW/fOglZOXHKrXJJ098vmFtk7LKF180q4+lp4S6Z/BzXtCca+WfoqUJdW1Tes9bD3vET33KL8r3v8yf1sDmyLnKezwVuTvHhu5f5/WdhejwNZfOPCOkdV1efm25XkmvPxEv/f3zm7VnX9UnYtHLAUX5fpc8YJSX5/XsTmmlV16NJ625OcnOSdcyPTYnX3L1TVD2Qa7llJTu3uF6+4rM2cVVXXS/LHmRrn/zXTnq9L84xMe9SdnWW+r78w09DjS6rqjpkWLfqtTI0NT8s0mmVJ/n979x0nd1XucfzzpUkvXoqiNBFEjDQJhHJVRFHqFRUBRQTL1atIu5YrqAhYqCJgQVEQEWkCCihNEKS3BEIUEOmCVwGlXDCU8L1/nDPZyWRmN7tJ5pzf8Lxfr33tzG92kydlZ+ac85RiC/eBW8BJap28bUTuTkV6U7ILQ13Lisr/yMvZvivf3wFopS1cZPtvxYLrkHdkm3KCdZPScPST8/1dSE9SVZG0GukJqTNnuoodsDYL2/5C6SCGcQCp0PnrzNiRcD+GWqOH0TmS9Nx5myvMr9fMs8qmP0RdnVybtLkw78hfVZ6kQ0gLuFZTlT0lbVxTHWleDF1AOslekDSaYWHgIUmX2q6m+VduvrCxpJWZMcOiiqYbLZIOza9DZ3e5Vg3bn8o3j5N0IakD5eSSMfXwhO0aTzBbFmo7Wd8FOMH2kXlTsZqa3DbFFu6DWAP3IunN3LeAX7YaB9REqR3yNW0d6f5MetJfCHjB9icLhjcTSUcCq5F2QtpnGZ3d85sKyJ39Ps3QTt0VwPdqO3KXdBVp8XEUqTPZ7qSfxQOKBtZB0tdI/0+r7QKVi4c/z1BHwinA4banlIuquXKq0pbO8wprk9NrerJ9/3CP94ukdwHHkOofZ9pcqPwNVJUkTQbWaf3fzNkhkypatPeUN223t31S6VhaJJ1MGmVzC0MnMa6wtr1b2/vqanVzx9EPAq+xfZCkFYFX2K7qFC5vhMxLWhC3D0av5YCjvSZ3IvBF2xfl+9X9u7fLmyF9W7gP4gLuFQzVv21A2lmaSOqwda3tewqGB6RmC8B6rR3ujuYLV9netGiAHSSd2OWyK6qF6krSFsDnbL+jdCztNDRfrf2JqoqmG9CzC1Sk080GSd1m7DwB3F9TapWkn5DSPy5gxhf3KsYI9CJpE+ADtj894hf3SWwuzFl5AffWttPMlwOX1/yGrmaSbgfWrPGkHUDSfwGfIj0f3d320GKkfga7FAmsB6WxFi+SRl28Xmkm3MW2x4/wrX2lymdTSjqaNEvtr8B2wOq2n5f0SuA82+sXDTDr8Zre8izwwNyuJR64FEqnoYln5w+Uhil+BDgQWIW081DafB1Pmh9qu71kv4MZie3dS8cwHElvA44Dlgd+SepM9lPSguPrBUPrZWpOB7hL0h7AQ8CyhWOazvZipWMYQN8D1gMmk/5fjsu3/03SJytqGnJv/lggf1Qr10d8gNT1717aUqxqkBdqu5aOY4B8E5iU34C2ulBWkz7ZQFNINXt/LR1IDz8nbSR9E/iftutPtRbxldnQ9np5gx6ncVbVPYe6/tmUe5Ma1bwS2NRDHTNfAexfLKqZHTnMY/MBK0r6rudi48RBPIFbglTD0TqFW5fUZeka0q5N8eGPSnNN3pkXm+3XXwVcUNuOYu3dCPMT5j6kU9YtSYu3L9s+umhgPUgaT+rwuSRwMGm+2mG2q+gAJumdwGKdPyuSPgA8YvuSMpE1l6TTgINt/yHfX5PUOe9g4Gzb65SMr5OkRWw/PfJX9lfuLLsTqUnEY8DpwGdtD5taGQZD3oUfT1rAXd/5GhpGJuk8UobFYqTGEDcw42n7doVC6ymnyy7HjO8/HigX0cwkXU96z3ljXsgtQzqBq2Y+YYukrUmZAe01+AeVi2jw5JKeSbbXnFu/x8CdwJEWa9eRFmwHAze4vpbdhwPnSfpvYFK+th5wRH6sNrV3I7Tty/PtX0p6pNbFG6Ti8Xzz/0j1b0g6gnpaOB9Iqs3rdBlprlEs4EZvjdbiDcD2HyWta/ueVDpRB0kbkbqULUraQVwb+ERbgX5pd5Cei7Z1HoYtaZ+yIYV+kHQuqZX8uTVuLnTKDdVWpr4GIUeUDmA0cpbKV4G/kVIUIS1Aq9roJtW8ngMsmxtrvY80t7Aqko4jNdbZjNTu/n3U2S2z0Ww/K+lDI3/l2A3cCVxT5CL3/Ui7IAb+ABxSY3G7pFtqOyFoJ+ke4LNtl45ov19bs5VuJD1ge8XSccDwhcI1FRGrx4D5lpqK8SWdDvwDOC1f2hFYmpQ+fVUtdRJ5F/l9pDfJrbrcKbbHlY0skbQ96QRuY+BC0t/nj1z5SJYw+yS9hfRzszXpDefp5FlrRQProgkNQiStAvy19fcnaSFSd+z7igbWITd529D2Y6Vj6SWXREwgPcdvTjohvtT27cN+YwGt1/C2z4uSskC2KB1bGJ1BPIFrBNsXkt6ANMH5kraquBvhFcx4YtR+31RWG9NDPccwsKC6zC1Smqm3UI/vKaEpA+YBdiMV5O9N+re+irTJ8DxpJ7Qath/sOBWs5tTdaf7TOZIWIQ133QdYLjcQOKeWWsImbS40he0rgCtyOt3bSGn9J5BS0GuzPhU3CMnOJG2EtEzL16rYTGrzIKnhU7Wc5oAdaXsjUpZAzVoZac9IWp6Uil7dBpikbYDf1NoRuQaxgAuzYi9gP0lVdiOsvclKS+6a1vUh6lrAnQ0cL2mPVqpSfsN8DBUthmtqyT0S2/+S9D3SicGdHQ8XnwsmaYLt64AHc+qXcwH+nqR6zark/5enAKfkn6sdSI0OqljA0azNhcbIp0Tbkk7i1gNqfQ6ovUEIpGZq00fs2H6uxqYbpFm+l0v6NXV3xr1Y0ntJp1k1L9zPV5pbdjipQ7tJqZS12Qk4WtJZwIk1nmaWNrAplJI2sX31SNdC6BdJ9zLUnr+TXckgb0nzAV8DPga05mqtSKqN+nJbV6ii2orxu6qpGF/SdqQXzAVsr5I7KB5US4zKs5YkLQ0cDbyd9P/0YtLcsmrTl5qg1qYwTZLTkDckZa6cQRohUOXufO6UWXWDEEmXAMfaPjff/w9gT9ubl41sRpK6zUd1LU03JH3D9n55/M4iwAvAVCrb6O4mN9pY0HaVJ5xK8xN3JvUKMHAicOrcbs8/u9RlduFc+X0GeAHXbfhjX/5SB4WkXWz/LN+eYfGbT2e+Uy66MLfl3e7X5rt/rq0ZUK6J6SmnXFVB0s2ktK/L22rLaqonjOfGuaC9KYztGpvCNEauG7/EdjUpvb30em6q7DlpVdIp9vKkxcaDwK6t5kC1krQgqYnRmaVjgeY8d0p6m+3LJL2n2+O19grIm4q7kMoPbie9JznG9rFFA6vAwKVQ5hfMjYFlJO3b9tDi1DEDbrq8+/FeZu5UVcXOErAv8LN8+1hSykrLR4BYwA2wvGC7rXQcvdT0ZmgWvGD7iZo6TnZ4Te7y11VNJwcN823gncC5ALZvlfTmsiE11qXAp9v+/q4AjqslI6BdE56bbN8NTMhNLFTzqUaue9yCdBqzBamGuIoFHDCv0tDurk/urmdm3VtInaS7dZiurleApG1J7zNXBU4GNrD9d6XZzreT3pO+pA3cAo40fHZR0p+tfSDxk6TuajX5Fak492ba0iwqoh63u90vTtIOwIW2n5L0JdKC82u2JxYOLcwFks6w/X5Jt9EllbKW061sitIcvXklrUaqLbumcEztHmH4waRhjGpuCtMw3wfmB76X738oX/tYsYh6kDSB9Abz9aT3JPMCT9eQTpffGE+23UqP3xd4r6T7SenS95aLbkZ5sf4BhjqPbgK8xvYzRQOb0Rqk93BdSyOAKkojbB+QPzeiZwCprvko279vv2j7GUnFZxDnlNleKYzPAncD+9u+dG7FMHALuLZOVf9yxwT0/Ab/rjKRdfVq2+8qHcQw3ON2t/s1+LLtMyVtStr1PoL0Ar9h2bDCXLJX/rxN0ShmzWeA/UlP7D8HLiLVGdbiqSacGjRQI5rCNMR422u33b9M0q3Fohned0hNGM4kdaTcFVitaERDvk5qed/q9LcL6WRrXeA40mtncZL+AjxAeg3/XN6YvbeyxRvAH13hsO5Okl4NrGz7qnx/X9JhB8DPa0udtb3rMI/NtUXRrLK9WK/H8onxOFKK8lwbwTPP3PqFK7BTl2tf7HsUw7tG0htLBzGMNSRNziccrdut+68rHVwXrZ3trYHv2/4VafezOpI2ldQa4r1MnslTHUlLSdpA0ptbH6VjarH91/z5/tYH8DTwQNvucnH5yfxc2/vbHp8/H9oAIAAAG7dJREFUvuS65lfdVzqAAfVJ4NPAq4C/kBpbfLpoRM01LddtASDpNVR8mpnfEM9re5rtE4G3Fg6pxW2LoPcAP7Z9s+0fAcsUjKvTWaSfmx2BbXMn5Bo3jpvicGDJtvufIL1eGjiwSETDkDRB0o2S/k/Sc5KmSXqydFyzIv/M38pcTvMcuBM4SVsCWwGvknRM20OLk7oD1WRTYLfcnfBZhroW1ZL69frSAYzSQ5J+QOqgd2iuMaxukyJ31VqftAg+kZQW9DNSekg1JH2MdMr1atJA2gnAtaRmHMXlNKVDSMNTDyblyS8NzCNpV6dZi8XZnibpGUlL1Nrty3bXwvYwe2w/CnywdBwD4nPA7yTdQ3qtXInUna5Gz+QT11skHUYaJ7BI4ZhalOveniENnf5e22MLlglpZrb3krQ3aU7mzqQFyOKS3k+aD1Z8/Ep2dOkAZtHrbJ/fdv8Z20cCSLqyUEzD6XaK/dphv6MSks63vY3tH8zN32fgFnDAw6QZPNuR8pJbniINfa3JlqUDGE5Npxiz6P3Au4AjbD8u6ZWkF/3abE9KV5kIYPthST2P4wvaizTU9Trbm0lag7p26r4D7AcsQSrO3tL2dTnOU0ntxmsxFbgtt+6e3k7eMdB5oOWOeR8F3kDbm2PbxWs4msb2pbl+9HWkBdwdtmusHYdUnzcPsAfpfccKpIZlNfg2aUPuSeB22zcBSFqXyubWObVJv4yULjs/6fV9Z9Kic+mSsbXY/knpGGZR5+K8fVzEv/UzkFll+8+S5s2dZ0+UVFPd+HA+3o/fZOAWcPnY8lZJP6+xO1U72/fneq3VbJ8oaRmGcpLDKOXi1l8By0laMV++o2RMPTxn25IM04dk12iq7amSkPQy23dIqil1dj7bFwNIOshpEDU5zrKRzezX+SO8tJxMeg56J3AQ6TQuauBGYZi07Q0l0dnkoAb5tX2ZfLumTS9snyDpImBZoL2G8H+p90ST/H7uPOC8POImjM5Tkla3/ScY6o6ZNzxrOc1sV/Mpdk+SNiE13pnrqfIDt4Brs7KkbwJrMuPOZxUdgaA5qXRNIekzwAHA34DWgFcDtaSktpyRUz2XlPRxUqvc4wvH1M1fJC0J/BK4RNI/SSfctWgf4ts5o66qWgnbJ5WOYVYpDR2f3qrd9nkl42m419reQdJ/2D5JUquBTZh13bIoDKxNSu+uZjyQ0s7RAaSTN5HSuV8gDcyuZTwQth8CHuq4VtXp23Bc2UzShjgAOF/S18nZP8CbSFkse/X8rnI+RPrZrvEUewaS1iEt2t4P3EufRjIM8iDvq0j/YY8izb3YnfTnPaBoYG0k3UJOpXOFw32bRtKfgQ1tP1Y6lpFIegdpno2Ai2xfUjikYSkNpl2CNKbhudLxAEiaRkpHFLAQqaaDfH9B2/OXiq1F0n+Qus1+N9+/nqFGAZ+3/YtiwXWRN702IHXPgpSudJPt2hpANYKkG2xvIOn3wKdIpxw31LSR2DQ5a2V/YCng6zVtMEjah1SD/5+tdvy52cr3Sc+dR5WML8w9+cT148w817eadGlJ44DPk1K6AaYAh9ueUi6qZpK0OqlGb2fgMeB04LO2V+pbDAO8gLvZ9psk3Wb7jfnalbb/vXRsLW0v7hNtr5dT6a6tbQGXj4S/Sioan4+hZitVvQmR9DvgHbZra1Yzg3yq1Wop/adaG1vA9A6KyzHjC9ID5SJqFklXAzvZfjDfv4VUe7AIcKLtzYf7/n6TNBlYx/aL+f68wKTanpOaIjcCOouUBXAiKUX+K7aPKxpYA0naHPgy6fTtGzVuekmaRHoNerTj+jLAxU1oNx/GJtdnXUnqvTC9O6rts4oF1UDqMde1pZbXIkkvkv69P9oawSDpnn6+Lx7kFMqpkuYB7pK0ByldYNnCMXXqTKX7KPCjwjF182PSEfYMT0wVuge4XNKvaRuMbvtb5UIakvO5fwi8mxTrPMBKks4BPlnLyVZLg1JSa7ZAa/GWXZVPiB+ruPZxSVJnT0inrmGMcmt2gCuoZKBv00jamnTi9gRpMO7VhUMazvydizcA24/kJhzVkHQEaRPpD6VjGU5e/H6BmcthquiG3GZh218oHcQAaMJcV0jpnDuROuNeCJxG92Huc80gL+D2BhYmDU49mNT6/MNFI+pg+4icSvcksDrwJdu/LRxWN0/YvqB0ELPggfyxAHXOf/sSqc5xBdtPAeTuk98l7Sx/uWBs3exFaj1cfUpqxZZqv2N7j7a7Nc1cavkmMCmfZotUCxfpk2OUR5m8l5nTqqqph2qA80gz9B4DvtDZoMj2diWC6mG4TbiqNuhIzXV+KGk+0unwqZVmg5xCSk/bmjRX8cPAI0Uj6u58SVvZ/k3pQBpufmC5zo0aSf9ORTX4ts8Bzskbse8mHXIsJ+n7wDmtBmtz08CmUNZM0lMMHRF3rtinAneTdhqLT5sHkHQIqZj0bGY82ZrY85vCTCRNATbw0BDV1vVFSa36x5WJrLumpKTWTNIpwOW2j++4/gngrbZ3LhNZb3n8xnjSc9P1tv+3cEiNlXdmn2DmtKojiwXVMLn+tifbV/QrlpG01eXO9BCV1OV2yp2FdyfV8lwNHG/7d2WjGtJWDjO9P4CkK2wP+/+i3/L7ukVI75GeZ6jUZPGigTWMpPOB/WxP7ri+PnCA7W3LRDYySS8HdgB27McJ8cAt4CSdO9zjle3WzSTXnIwDTqnlDX1+I9/JtaUw5FSLVoFudakWwzWoaa/VrIWkH5M6pFaZktoEkpYldfF8lhk7f70MeLftv5WKrRtJ2wOXtXbic73mW23/smxkzSRpSi3P4yF0yu83tiEt4FYAzgA2BZ62vVPJ2FokXWd7Qh59cAzpFOYXtlctHFqjSfpwjd2Rh3vOrPF9UkmDmEK5EfAgaZDv9fQ5J3V2OQ0svFXSsaVjabG9WekYZlEr1WIb6ky1sKSl6P5/8sUu10qrPSW1erb/Dmws6W0Mdf76te3LCoY1nANyaggAth/P405iATc210h6o+3bSgcSQjtJ3yJ16L6M1BTmhvzQoZLuLBfZTL4maQngv4FjgcVJ6WrVya/vqzHjBnJ1cwqzvYDqFnDMPHC8Xcz/azOIJ3DzAu8gpQOsRTo9OLX2Qt3a5ULyzpOtquo4ak+1kHQfaaHWbQFXXVfPllynZ9s1DvsMc1C3U+LY9Ry9tk5q85He0N1DOoVtpVVFI6BQTJ5X9yXgyM6U/vz4EpXWw1Urd5zdizSb8BZgAqmreBUZQJ1a3c9Lx9FJ0qmkLJDOsoOPAlvY3rFMZPUZuAVcu1xAvjNwOHCQ7WpOtZpE0nGkhjCbkbpkvo80y+ijRQPrEKkWc1aeGXMy8PJ86VFg19gMGVySTgAeJzXWMfAZYCnbu5WMq2kkDTsLyPb9/Ypl0EhaxHa3OrMwCq0Nz9Jx9JKzkIZrJ79nH8MZUd60GU+qZ19H0hrAgTUtOHI5jEkbSW8CbmJoU6mKhaak5YBzSE1/bs6X1ydlAW0fNdlDBjGFsrVw25q0eFuZ9Ga+L5PRB9TGttfKu/MHSjqSOv8+G5Nq0RA/BPZtFbRLeitwPLBxyaDCXPUZUjfU0/P9i0k79WEUWgs0SROAP3R0nV0TiAXcKEnamLSBuCiwoqS1gU/Y/lTZyBrrOknjbd9YOpAebiodwChNtT1VEpJeZvuO3CCmJrvlzyJlp+1eLpTucl34xpI2I/WDgLrLDooZuBM4SSeR/tEvAE5zTJifbZKut72hpOuA95DaOU+xvdoI3xoaTNKtttce6VoYDDn9/CLbby8dy6DIg53Xc36hzbNJb6oxdal2kq4nZX+c6zwQO5rEjJ2kP5LGF91P6pxZdXpv7an8eZ7r7qQRVm8D/kmaC7hV0cB6qDWFMsy6QTyB+xDpyWh1YM+2mTHR0nXszs/d6A4nddIzFQ0cb1qqRYPcI+nLpDRKgF2AewvGE+Yi29MkPRP1L3OU3LZLavvFPHcrjIHtBzvmwE3r9bWht1wD90kacBLckcovSY9QYSq/7e3zza/mVMUlgAsLhjSS+0oHEGbPwL2Q2J6ndAyDxvbB+eZZeUbHgpW9wWtPtTgQOKBUILNC0hHAibW9AHXxEdLf59mkDZDfU2HKRZijpgK3SbqEtnlWsQkyZvdI2hP4fr7/KVJDkzB6D+Y0SktaANgTuL1wTI1k25KOqrkGrk3VqfySFrf9ZJ4B1tLqOrso8I8CYY3I9ntKxxBmz8ClUIY5T9Ku3a7b/mm/YxmJpEmt9Jpa5W5Vu5M2UE4kdUmtaUEcXqIkfbjb9RrnBTVBngN4DCmlysClwN55vEQYBUlLA0cDbydtKF0M7GX7saKBNZSk7wI/qbgGDqg/lV/S+ba3kXQvQw1CWqrtLh2aLxZwYUQdM+kWBDYHJtp+X6GQempSXncucN6d1GznauD41i5jSZLOHe5x29v1K5YQQghzXlNq4HJt2URmTOVf3/a7y0UVQnkDl0IZ5jzbn2m/nzs9ntzjy8MsyA0j1sgfjwK3AvtK+oTtnYoGBxsBDwKnAtfTfW5dGECSVgO+SeqU2D7zMXaRR0HS520f1qs+N1JSR0/SMsDHSZ2lp793sf2RUjE13JalA5hFVafySxp2w9j2xH7FEl5aYgEXxuIZ0nDaKkh6iqE3SQtLerL1EBU2rpH0LWA7UjrVN2zfkB86VNKd5SKb7hXAO0gngx8gtRs+tQE1e2H2nUiqIT2KNPdxd2IBPxat2qymtUKv2a+AK4HfEs1LZlvbqItladusqY3tf5LqHWt15DCPmZQ+XVxHjd5MbFdZqxd6ixTKMCJJ5zG0QJqXtDt/hu0vlIuquSR9hDTi4pkuj1XVATDPVNyZ1IH0INvHjvAtocFaw30l3Wb7jfnalbb/vXRs4aVN0i221ykdx6CQtB1p8bE88HdgJeB2228oGliHfPL6eeANzJgVUMXCqCl61Oi1RK1eA8UJXJgVRzC0gHsBuN/2QwXjaaS2VItbgDU62mFje2Iti7e8cNuatHhbmdSIocbh7WHOmppnld0laQ/gIWDZwjE1TtSRzhXnS9rK9m9KBzIgDgYmAL+1vW4enLxz4Zi6OQU4HdiGNPrgw8AjRSPqovZmb7ZXKR1DmLPiBC701Jaa2LljY+BZ4G5gf9uX9ju2JsqzYSDtIq5PqnsTsBZwve1NS8XWTtJJwDjgAtJJ4ZTCIYU+kTSelP63JOkN3hLAYbavKxpYw+RZVT3rSG1fUSKuJsuvR4uQXnuep9IU+aaQdJPt9SXdCqybZxTeYHuD0rG1a8sKmNxqsCLpCttvKR1bu9qbvUWt3uCJBVwYk9yEYxxwiu1xpeNpEkmnAV+3fVu+Pw74rO3digaWSXqRoRlg7U8Q8YYphFmQnx9bdaRrEXWkoTKSfgu8m9S0aGlSGuV421XMV2uRdJ3tCZIuImWCPAz8wvaqhUMbVqvZWy2n7W0byN04UlKbJxZwYbbkrok/KB1Hk3Sr5Yj6jlBSpPzNPVFHOnskrWH7jl4nCHFyMDaSFgH+BcwDfJB02n5KbXP1JG1Dal6zAnAssDhwoO1hn7NKkzQ/MNn260vHEgZTLOBC6DNJp5JOuH5GOuHaBVjUdo31B+ElIFL+5rwudaTnAidE/fDoSDre9sd7nCDEycEckIekP+aK3hBKWpBU8/Za4Dbgx7ZfKBtVb01p9iZpYWBfYEXb/5lHx7zO9vmFQwujFAu4EPosvzD9F/DmfOn3wPdtTy0XVXgpi5S/OSvqSEOtJE0ADgH+QapzPZmUQjkPsKvtCwuGN52k00m1jleSZtbdb3uvslH1JuktNKDZW/57vZn0bz1O0kLAtZEB1DyxgAshhDBdpPzNvqgjnXMkvWe4x21Hd9xRkHQTsB8pZfKHwJa2r5O0BmnTZt2iAWYdo0zmA26wPWwjjhKa1uytrXnNpNa/taRbba9dOrYwOjFGIIQ+k7QJ8FXS3J3pP4MxhyWUFKMj5hzb85SOYYBsO8xjJv6PjtZ8ti8GkHRQq8NsrjMsG9mMnm/dsP1CZbFNZ3uxXo+1N3vLn2vwXD51M4CkVUkLzdAwsYALof9+DOxDSmOYVjiWEDpT/g6MlL9QC9u7l45hwLzYdvtfHY/VlJK1tqQn820BC+X7jTnFtj0NuLVjxEBpBwAXAitIOgXYBNitaERhTCKFMoQ+k3S97Q1LxxFCS6T8hdpJWg74BrC87S0lrQlsZPvHhUNrFEnTSD/rAhYCnmk9BCxoe/5SsYX+kPRvpCHuAq6z/WjhkMIYxAIuhD6TdAipS9XZtKUuRDvsEELoTtIFwImkeqK1c13UpFadVAhhePlnZpptS1oB2BC42/akwqGFMYgUyhD6r3X6tn7bNQPRDjuEELpb2vYZkr4I0+uiIgU9hFkg6ePAocD/SToY+BwwEVhX0gm2Dy0aYBi1WMCF0Ge2NysdQwghNMzTOfWr1XxhAvBE2ZBCaIy9gVWBxYDbgZVsP5rnwt1IWtyFBokFXAh9FrUcIYQwavuShqGvKulqYBngfWVDCqExnrP9T+Cfkv7cqnuz/Yyk5wrHFsYgFnAh9N9PyLUc+f6fgNNJ3SlDCCF0sD0xD0t+Han5wp22nx/h20IIyUKS1iUNbF8g31b+WLBoZGFMoolJCH0m6Ubb4zsGad5ie53SsYUQQo0k7drtuu2f9juWEJpG0u+GezxKO5onTuBC6L+o5QghhNEZ33Z7QWBzUhOGWMCFMIJYoA2eOIELoc8kvQk4hjQ4eQq5lsP25KKBhRBCQ0haAjjZ9nalYwkhhH6LBVwIfSJpb+BqoDVzJWo5QghhDCTND0y2/frSsYQQQr9FCmUI/fNq4GhgDWAycA1pQfcw8I+CcYUQQtUknUdOOyc1YlgTOKNcRCGEUE6cwIXQZ5IWIA3x3hjYKH88bnvNooGFEEKlcgfKlheA+23/pVQ8ITSVpFcBK9F2iGP79+UiCmMRJ3Ah9N9CwOLAEvnjYeC2ohGFEELFbF9ROoYQmk7SocCOwB+BafmygVjANUycwIXQJ5J+CLwBeAq4HrgOuC4P1wwhhNCDpKcYSqGc4SHAthfvc0ghNI6kO4G1bD9bOpYwe+IELoT+WRF4GXAX8BDwF+DxohGFEEIzHAX8L3AyadH2QWAx24cVjSqEZrkHmB+IBVzDxQlcCH0kSaRTuI3zxzhSA5NrbR9QMrYQQqiVpOttbzjStRBCb5LOAtYGLqVtEWd7z2JBhTGJE7gQ+shpx2SKpMdJw7ufALYBNgBiARdCCN1Nk/RB4DRSKuXODNXwhBBmzbn5IzRcnMCF0CeS9iSdum0CPE8aIXBt/nyb7RcLhhdCCNWStDJpDMsmpAXc1cDetu8rF1UIzSNpIWBF23eWjiWMXSzgQugTSd8iz36z/dfS8YQQQgjhpUPStsARwAK2V5G0DnCQ7e0KhxZGaZ7SAYTwUmF7X9u/iMVbCCGMjqSTJC3Zdn8pSSeUjCmEBvoqqWTjcQDbtwCrlAwojE0s4EIIIYRQu7VsT+/am8evrFswnhCa6AXbT3Rci1S8BooFXAghhBBqN4+kpVp3JL2caMQWwmhNkfQBYF5Jq0k6llTaERomFnAhhBBCqN2RwDWSDpZ0MOlNZ8yAC2F0PkMaZfQs8HNSJ+y9ikYUxiSamIQQQgihepLeAGxGGuR9qe0/Fg4phEaRtIPtM0e6FuoXC7gQQgghNIKkZYEFW/dtP1AwnBAaRdJE2+uNdC3UL/LHQwghhFA1SduR0iiXB/4OrATcTkoHCyEMQ9KWwFbAqyQd0/bQ4sALZaIKsyNq4EIIIYRQu4OBCcCfbK8CbE4a5h1CGNnDwE3AVODmto9zgXcWjCuMUaRQhhBCCKFqkm6yvb6kW4F1bb8o6QbbG5SOLYSmkDS/7efz7aWAFWxPLhxWGINIoQwhhBBC7R6XtChwJXCKpL8TqV8hjNYlOR15PuAW4BFJV9jet3BcYZTiBC6EEEIIVZO0MCn9S8AupNqdU2z/o2hgITSIpEm215X0MdLp2wGSJtteq3RsYXTiBC6EEEIIVZL0FNC506z8+SuS7gb2t31pfyMLoZHmk/RK4P3A/qWDCWMXC7gQQgghVMn2Yr0ekzQvMA44JX8OIQzvIOAi4CrbN0p6DXBX4ZjCGEQKZQghhBAaS9InbP+gdBwhhNAvsYALIYQQQghhQEn6vO3DJB3LzCnJ2N6zQFhhNkQKZQghhBBCCIPr9vz5pqJRhDkmTuBCCCGEEEIYYLlm9BDbnysdS5h985QOIIQQQgghhDD32J4GvKl0HGHOiBTKEEIIIYQQBt8kSecCZwJPty7aPrtcSGEsYgEXQgghhBDC4Hs58BjwtrZrBmIB1zBRAxdCCCGEEMKAkvRq23/p8di2ts/rd0xh9kQNXAghhBBCCIPrUkkrd16UtDvw7b5HE2ZbLOBCCCGEEEIYXPsAl0harXVB0heBfYG3FIsqjFnUwIUQQgghhDCgbP9G0rPABZLeDXwMGA+82fY/y0YXxiJq4EIIIYQQQhhwkjYFfglcA7zf9tTCIYUxigVcCCGEEEIIA0rSU6RukwJeBjwPTMv3bXvxguGFMYgFXAghhBBCCCE0RDQxCSGEEEIIIYSGiAVcCCGEEEIIITRELOBCCCGEEEIIoSFiARdCCCGMQNJukr5TOo4QQgghFnAhhBDCXCRp3tIxhBBCGByxgAshhDAQJC0i6deSbpU0RdKOku6TdKikG/LHa/PXLiPpLEk35o9N8vUNJF0jaVL+/Louv8/Wkq6VtLSkLfLtiZLOlLRo/pr7JH1F0lXADn39iwghhDDQYgEXQghhULwLeNj22rbHARfm60/a3gD4DvDtfO1o4Cjb44H3Aj/K1+8A3mx7XeArwDfafwNJ2wP/A2yVL30JeLvt9YCbgH3bvnyq7U1tnzYn/5AhhBBe2uYrHUAIIYQwh9wGHCHpUOB821dKAjg1P34qcFS+/XZgzfw4wOKSFgOWAE6StBpp8O38bb/+ZsD6wBa2n5S0DbAmcHX+dRYArm37+tPn8J8vhBBCiAVcCCGEwWD7T5LeRDod+6aki1sPtX9Z/jwPsJHtf7X/GpKOBX5ne3tJKwOXtz18D/AaYHXSaZuAS2zv3COkp8f+pwkhhBC6ixTKEEIIA0HS8sAztn8GHAGslx/ase1z64TsYmCPtu9dJ99cAngo396t47e4H3gP8FNJbwCuAzZpq6tbWNLqc+wPFEIIIXQRC7gQQgiD4o3ADZJuAfYHvpavv0zS9cBewD752p7A+pImS/oj8Ml8/TDS6d3VwEzdI23fCXwQOBNYnLTIO1XSZNKCbo258QcLIYQQWmR75K8KIYQQGkjSfcD6th8tHUsIIYQwJ8QJXAghhBBCCCE0RJzAhRBCCCGEEEJDxAlcCCGEEEIIITRELOBCCCGEEEIIoSFiARdCCCGEEEIIDRELuBBCCCGEEEJoiFjAhRBCCCGEEEJD/D+f7OS6KqAWEwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"not_ted_ed_top_20_speakers.plot(kind='bar', figsize=(15,10))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So the most prolific Ted speaker, excluding Ted-Ed content, is sleep scientist [Matt Walker](https://www.ted.com/speakers/matthew_walker)."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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