{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# CS109A Introduction to Data Science \n", "\n", "## Lecture 1, Exercise 1: The Data Science Process\n", "\n", "\n", "**Harvard University**
\n", "**Fall 2021**
\n", "**Instructors**: Pavlos Protopapas and Natesh Pillai\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Title :\n", "Exercise: The Data Science Process\n", "\n", "## Description :\n", "The aim of this exercise is to understand all the steps involved in a Data Science setting.\n", "\n", "\n", "\n", "## Data Description:\n", "Hubway was metro-Boston’s public bike share program, with more than 1600 bikes at 160+ stations across the Greater Boston area. Hubway was owned by four municipalities in the area.\n", "\n", "By 2016, Hubway operated 185 stations and 1750 bicycles, with 5 million rides since launching in 2011.\n", "\n", "In April 2017, Hubway held a Data Visualization Challenge at the Microsoft NERD Center in Cambridge, releasing 5 years of trip data.\n", "\n", "## Instructions:\n", "- Read the data files hubway_stations.csv and hubway_trips.csv into separate pandas dataframes.\n", "- Get a quick understanding of the columns present in the data and their types.\n", "- Remove all the data points with null values in any one (or more) of the columns.\n", "- Create a new column age that gives the age of the rider using their birth date.\n", "- Perform relevant EDA to answer the questions asked on the scaffold.\n", "- Create a simple linear model to predict the number of checkouts based on the distance of the bikes from the centre of the city.\n", "- Visualize the prediction against the data.\n", "\n", "## Hints: \n", "\n", "pd.read_csv(filename)\n", "Returns a pandas dataframe containing the data and labels from the file data\n", "\n", "pd.describe() \n", "Generates descriptive statistics of the dataframe.\n", "\n", "pd.dropna()\n", "Removes missing values from the dataframe. It removes either the columns or rows based on the axis parameter." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Import necessary libraries\n", "import numpy as np\n", "import pandas as pd \n", "import seaborn as sns\n", "import matplotlib.pyplot as plt \n", "from helper import get_distance\n", "from math import radians, cos, sin, asin, sqrt\n", "from sklearn.linear_model import LinearRegression\n", "%matplotlib inline\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# Read the data from the file \"hubway_stations.csv\"\n", "stations = pd.read_csv(\"hubway_stations.csv\")\n", "\n", "# Read the data from the file \"hubway_trips.csv\"\n", "trips = pd.read_csv(\"hubway_trips.csv\")\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idterminalstationmunicipallatlngstatus
03B32006Colleges of the FenwayBoston42.340021-71.100812Existing
14C32000Tremont St. at Berkeley St.Boston42.345392-71.069616Existing
25B32012Northeastern U / North Parking LotBoston42.341814-71.090179Existing
36D32000Cambridge St. at Joy St.Boston42.361285-71.065140Existing
47A32000Fan PierBoston42.353412-71.044624Existing
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" ], "text/plain": [ " id terminal station municipal lat \\\n", "0 3 B32006 Colleges of the Fenway Boston 42.340021 \n", "1 4 C32000 Tremont St. at Berkeley St. Boston 42.345392 \n", "2 5 B32012 Northeastern U / North Parking Lot Boston 42.341814 \n", "3 6 D32000 Cambridge St. at Joy St. Boston 42.361285 \n", "4 7 A32000 Fan Pier Boston 42.353412 \n", "\n", " lng status \n", "0 -71.100812 Existing \n", "1 -71.069616 Existing \n", "2 -71.090179 Existing \n", "3 -71.065140 Existing \n", "4 -71.044624 Existing " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Take a quick look at the stations data\n", "stations.head()\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Unnamed: 0hubway_iddurationstart_datestrt_statnend_dateend_statnzip_codebirth_dategender
04260154820776758/18/2012 19:48:008.08/18/2012 20:00:008.0'021341983.0Male
11930802206122044/26/2012 18:14:0031.04/26/2012 18:17:0064.0'022101953.0Male
25300515987218889/23/2012 09:26:0039.09/23/2012 09:41:0039.0'021181985.0Male
34845945476455269/8/2012 12:55:0088.09/8/2012 13:04:0072.0'021391985.0Male
42912653321635546/21/2012 18:53:0047.06/21/2012 19:02:0054.0'021131986.0Female
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" ], "text/plain": [ " Unnamed: 0 hubway_id duration start_date strt_statn \\\n", "0 426015 482077 675 8/18/2012 19:48:00 8.0 \n", "1 193080 220612 204 4/26/2012 18:14:00 31.0 \n", "2 530051 598721 888 9/23/2012 09:26:00 39.0 \n", "3 484594 547645 526 9/8/2012 12:55:00 88.0 \n", "4 291265 332163 554 6/21/2012 18:53:00 47.0 \n", "\n", " end_date end_statn zip_code birth_date gender \n", "0 8/18/2012 20:00:00 8.0 '02134 1983.0 Male \n", "1 4/26/2012 18:17:00 64.0 '02210 1953.0 Male \n", "2 9/23/2012 09:41:00 39.0 '02118 1985.0 Male \n", "3 9/8/2012 13:04:00 72.0 '02139 1985.0 Male \n", "4 6/21/2012 19:02:00 54.0 '02113 1986.0 Female " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Take a quick look at the trips data\n", "trips.head()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### **UNDERSTANDING THE DATA**\n", "\n", "It is important to completely understand all the information provided in the data. The first step for this is to take a closer look at all the columns and understand their types." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "id int64\n", "terminal object\n", "station object\n", "municipal object\n", "lat float64\n", "lng float64\n", "status object\n", "dtype: object" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Getting the data type of each column in the stations data\n", "stations.dtypes\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Unnamed: 0 int64\n", "hubway_id int64\n", "duration int64\n", "start_date object\n", "strt_statn float64\n", "end_date object\n", "end_statn float64\n", "zip_code object\n", "birth_date float64\n", "gender object\n", "dtype: object" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Getting the data type of each column in the trips data\n", "trips.dtypes\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ⏸ Based on the datatypes, do you see any possible issues?" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "### edTest(test_chow0) ###\n", "# Submit the questions as a string below. Separate each question by an eroteme (question mark) \n", "answer0 = 'Yes'\n" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idlatlng
count142.000000142.000000142.000000
mean74.32394442.354820-71.089087
std41.3890980.0200890.027111
min3.00000042.309467-71.146452
25%39.25000042.341652-71.113183
50%74.50000042.353373-71.089191
75%109.75000042.366265-71.065210
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" ], "text/plain": [ " id lat lng\n", "count 142.000000 142.000000 142.000000\n", "mean 74.323944 42.354820 -71.089087\n", "std 41.389098 0.020089 0.027111\n", "min 3.000000 42.309467 -71.146452\n", "25% 39.250000 42.341652 -71.113183\n", "50% 74.500000 42.353373 -71.089191\n", "75% 109.750000 42.366265 -71.065210\n", "max 145.000000 42.404490 -71.035705" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Getting some statistical information from the stations data\n", "stations.describe()\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Unnamed: 0hubway_iddurationstrt_statnend_statnbirth_date
count210239.000000210239.0000002.102390e+05210239.000000210239.000000210239.000000
mean283491.142771321401.5428067.794459e+0236.72756736.6622611976.285594
std153204.497985173059.8759741.349006e+0418.59271618.55193411.002281
min0.0000008.0000000.000000e+003.0000003.0000001932.000000
25%153899.000000174103.0000003.460000e+0222.00000022.0000001969.000000
50%280081.000000319856.0000005.320000e+0238.00000038.0000001979.000000
75%414740.000000469290.0000008.280000e+0250.00000050.0000001985.000000
max549285.000000620312.0000005.351083e+0698.00000098.0000001995.000000
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" ], "text/plain": [ " Unnamed: 0 hubway_id duration strt_statn \\\n", "count 210239.000000 210239.000000 2.102390e+05 210239.000000 \n", "mean 283491.142771 321401.542806 7.794459e+02 36.727567 \n", "std 153204.497985 173059.875974 1.349006e+04 18.592716 \n", "min 0.000000 8.000000 0.000000e+00 3.000000 \n", "25% 153899.000000 174103.000000 3.460000e+02 22.000000 \n", "50% 280081.000000 319856.000000 5.320000e+02 38.000000 \n", "75% 414740.000000 469290.000000 8.280000e+02 50.000000 \n", "max 549285.000000 620312.000000 5.351083e+06 98.000000 \n", "\n", " end_statn birth_date \n", "count 210239.000000 210239.000000 \n", "mean 36.662261 1976.285594 \n", "std 18.551934 11.002281 \n", "min 3.000000 1932.000000 \n", "25% 22.000000 1969.000000 \n", "50% 38.000000 1979.000000 \n", "75% 50.000000 1985.000000 \n", "max 98.000000 1995.000000 " ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Getting some statistical information from the trips data\n", "trips.describe()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ⏸ Based on your understanding of the data, what questions would you like to have answered?" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "### edTest(test_chow1) ###\n", "# Submit the questions as a string below. Separate each question by an eroteme (question mark) \n", "answer1 = 'Most common station, Who take more trips (male or female)'\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### **DATA PRE-PROCESSING**\n", "\n", "Let us clean the data before breaking it down further. There are many pre-processing techqniues which will be covered later in the course.\n" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# Delete all the rows of the stations dataframe with null values \n", "# axis=0 indicates that the rows with null values are to be deleted\n", "stations.dropna(axis=0, inplace=True)\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "# Delete all the rows of the trips dataframe with null values \n", "trips.dropna(axis=0, inplace=True)\n" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "# Create a new column that gives the age of each rider\n", "age_col = 2021.0 - trips['birth_date'].values\n", "\n", "# Add the age column to the trips dataframe\n", "trips['age'] = age_col\n", "\n", "# Drop the 'birth_date' column\n", "trips.drop('birth_date', axis=1, inplace=True)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### **EXPLORATORY DATA ANALYSIS (EDA)**\n", "\n", "As you would have noticed, the information extracted above is not sufficient to answer most of the questions and is definitely not sufficient to ask relevant questions. Hence, we will need to perform additional data analysis. \n", "\n" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Find out if there is any relation between the predictors of the stations data\n", "sns.pairplot(stations);\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ⏸ Based on the plot above, do you notice any recognizable relationship between any of the columns?\n", "\n", "#### A. The latitude and longitude are directly proportional to each other.\n", "#### B. The latitude and longitude are inversely proportional to each other.\n", "#### C. It is random. There seems to be no relation between the latitude and longitude.\n", "\n" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "### edTest(test_chow2) ###\n", "# Submit an answer choice as a string below (eg. if you choose option A, put 'A')\n", "answer2 = 'C'\n" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Users by Gender')" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Get the unique number of male and female bike riders\n", "gender_counts = np.unique(trips['gender'].values, return_counts=True)\n", "\n", "# Plotting the genders of riders as a histogram\n", "fig, ax = plt.subplots(1,1, figsize=(10, 6))\n", "ax.bar(range(2), width=0.5, height = gender_counts[1],color=['#e4a199', 'green'], alpha=0.5 )\n", "ax.set_xticks([0, 1])\n", "ax.set_xticklabels(gender_counts[0])\n", "ax.set_title('Users by Gender');\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ⏸ Based on the plot above, who uses the bikes more, men or women?\n", "#### A. Women\n", "#### B. Men\n", "#### C. Can't say" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "### edTest(test_chow3) ###\n", "# Submit an answer choice as a string below (eg. if you choose option A, put 'A')\n", "answer3 = 'B'\n" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plotting the usage of bikes based on the ages of riders\n", "fig, ax = plt.subplots(1,1, figsize=(10, 6))\n", "age_counts = np.unique(trips['age'], return_counts=True)\n", "ax.bar(age_counts[0], age_counts[1], align='center', width=0.4, alpha=0.6)\n", "ax.axvline(x=np.mean(age_col), color='red', label='average age')\n", "ax.axvline(x=np.percentile(age_col, 25), color='red', linestyle='--', label='lower quartile')\n", "ax.axvline(x=np.percentile(age_col, 75), color='red', linestyle='--', label='upper quartile')\n", "ax.set_xlim([1, 90])\n", "ax.set_xlabel('Age')\n", "ax.set_ylabel('Number of Checkouts')\n", "ax.legend()\n", "ax.set_title('Users by Age')\n", "plt.tight_layout()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ⏸ Based on the plot above, who uses the bikes more, older or younger people?\n", "#### A. Older\n", "#### B. Younger" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "### edTest(test_chow4) ###\n", "# Submit an answer choice as a string below (eg. if you choose option A, put 'A')\n", "answer4 = 'B'\n" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Get the hourwise bike checkouts\n", "check_out_hours = trips['start_date'].apply(lambda s: int(s[-8:-6]))\n", "\n", "# Plotting the bike checkouts hourwise\n", "fig, ax = plt.subplots(1, 1, figsize=(10, 5))\n", "check_out_counts = np.unique(check_out_hours, return_counts=True)\n", "ax.bar(check_out_counts[0], check_out_counts[1], align='center', width=0.4, alpha=0.6)\n", "ax.set_xlim([-1, 24])\n", "ax.set_xticks(range(24))\n", "ax.set_xlabel('Hour of Day')\n", "ax.set_ylabel('Number of Checkouts')\n", "ax.set_title('Time of Day vs Checkouts')\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ⏸ Based on the plot above, when is the biggest rush hour?" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "### edTest(test_chow5) ###\n", "# Submit the integer value below within the quotes\n", "answer5 = '17'\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### MORE QUESTIONS?\n", "\n", "There are many questions that haven't been covered here. \n", "1. For what reasons are the bikes being used? Recreation, traffic or for health benfits?\n", "2. Is the usage more during the weekdays or weekends?\n", "3. Are people using bikes more in Boston or Cambridge?\n", "\n", "Feel free to add new code cells and find the answers." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### **DATA MODELLING** \n", "There are some questions that cannot be answered with simple graphing techniques. It requires combining different variables.\n", "\n", "1. How does user demographics impact the duration the bikes are being used? Or where they are being checked out?\n", "2. How does weather or traffic conditions impact bike usage?\n", "3. How do the characteristics of the station location affect the number of bikes being checked out?\n", "\n", "\n", "\n", "Let us try to answer the question: *How does the distance from the center of the city affect the bike usage?* " ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idcheckoutsterminalstationmunicipallatlngstatusdist_to_center
03.01878B32006Colleges of the FenwayBoston42.340021-71.100812Existing2.335706
14.03376C32000Tremont St. at Berkeley St.Boston42.345392-71.069616Existing0.853095
25.01913B32012Northeastern U / North Parking LotBoston42.341814-71.090179Existing1.802423
36.03616D32000Cambridge St. at Joy St.Boston42.361285-71.065140Existing0.467803
47.01384A32000Fan PierBoston42.353412-71.044624Existing0.807582
\n", "
" ], "text/plain": [ " id checkouts terminal station municipal \\\n", "0 3.0 1878 B32006 Colleges of the Fenway Boston \n", "1 4.0 3376 C32000 Tremont St. at Berkeley St. Boston \n", "2 5.0 1913 B32012 Northeastern U / North Parking Lot Boston \n", "3 6.0 3616 D32000 Cambridge St. at Joy St. Boston \n", "4 7.0 1384 A32000 Fan Pier Boston \n", "\n", " lat lng status dist_to_center \n", "0 42.340021 -71.100812 Existing 2.335706 \n", "1 42.345392 -71.069616 Existing 0.853095 \n", "2 42.341814 -71.090179 Existing 1.802423 \n", "3 42.361285 -71.065140 Existing 0.467803 \n", "4 42.353412 -71.044624 Existing 0.807582 " ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Helper function within helper.py to compute the distance of the bike from the city center\n", "# It returns a dataframe that has the column of the checkout distance from the center\n", "counts_df = get_distance()\n", "\n", "# Take a quick look at the dataframe\n", "counts_df.head()\n" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "# Let us use a straight line y = ax + b to model the relation \n", "# between the number of checkouts and distance to the city center\n", "\n", "beta0 = 4394\n", "beta1 = -1175\n", "\n", "y_pred = beta0 + beta1 * counts_df['dist_to_center'].values\n" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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73b59+6J+/fqYM2eOWgKSwnbt2oVnz56VWLeSWpbGjRuHixcvYsiQIbC3t8fIkSOLLVugSZMm6N69O77++mvs27dPa5kzZ87g7t27AIBevXrh0qVLqF69utZza0hAVtw579WrF4QQ+Pvvv7Xuq379+nrvq7A33ngDGRkZ+P777xEZGYnw8HDUrl1ba1lJktCwYUMsWrQIFStWVJvEuyiFQoGpU6fiypUr+Pjjj7WWiY+Px9GjR/Wqrz7Xdvfu3bF//36dutE6Ozvj119/Ra9evdCnTx9s2bJFta5jx45ITU3F5s2b1T7z7bffqtYDgL+/P5ydnXHx4kW1coW3VUCXVtLifm+IyLKxhYyIbNKlS5dU40zi4+Nx+PBhrFmzBvb29ti0aVOJc12tXLkS+/btQ8+ePVGlShVkZGTgm2++AQB06tQJQP74peDgYGzZsgUdO3aEl5cXfHx8ULVqVfTq1QuRkZGoXbs2GjRogLNnz+Kzzz4zeK4zd3d3LFiwACNGjECnTp0wcuRI+Pv748aNG7hw4QKWLl0KAFi1ahW6d++Orl27YujQoXjuueeQmJiI6OhonDt3Dj/99FOx+yjpeObMmYPOnTsjIiICkydPhqOjI5YvX45Lly7h+++/L7ElpOB8d+nSBeHh4XjrrbcQEREBNzc33LlzBz///DO2bduGpKSkYrdRv359/Prrr1ixYgWaNm0KOzs7tTnmOnfujLCwMOzfvx+vv/46/Pz8dDqv3377Lbp164bu3btj2LBh6N69Ozw9PREbG4tt27bh+++/x9mzZ1GlShV89NFH2LNnD1q1aoWxY8ciNDQUGRkZuH37NrZv346VK1fq/f0WBFbz5s1D9+7dYW9vjwYNGqB169YYNWoU3njjDZw5cwbt2rWDm5sbYmNjceTIEdSvXx9vvfWWXvsqrHbt2ggPD8ecOXNw7949rF69Wm39b7/9huXLl6Nfv36oVq0ahBD49ddf8eTJE3Tu3LnEbb/77ruIjo7GjBkzcOrUKQwcOBBBQUFITk7GoUOHsHr1asyaNQutW7fWq866XtsfffQRduzYgXbt2uH9999H/fr18eTJE+zcuRMTJ07UCDwVCgW+//57jBgxAv/5z3/w7bff4tVXX8XgwYOxbNkyDBkyBLdv30b9+vVx5MgRzJ49Gz169FD9DhSM9fvmm29QvXp1NGzYEKdOncKGDRs0jqHg+/7iiy8wZMgQKBQKhIaGYv369aX+3hCRhTNfPhEiovJXkKWv4OXo6Cj8/PxE+/btxezZs0V8fLzGZ4pmWTx+/Lh48cUXRXBwsHBychLe3t6iffv2YuvWrWqf++OPP0Tjxo2Fk5OT2rxdSUlJYvjw4cLPz0+4urqKNm3aiMOHD4v27duL9u3bqz6vbT4kIYrP3LZ9+3bRvn174ebmJlxdXUVYWJiYN2+eWpkLFy6I/v37Cz8/P6FQKERAQIB44YUXdMp8V9zxCPHvPGRubm7CxcVFtGzZUpWVTxdPnjwRH3/8sWjSpIlwd3cXCoVCVKlSRbz++uvi6NGjqnLasiwmJiaK//znP6JixYpCkiStmQlnzpwpAIgTJ07oXCchhEhPTxdLliwR4eHhokKFCsLBwUEEBgaKl156Sfz+++9qZRMSEsTYsWNFSEiIUCgUwsvLSzRt2lR88MEHIjU1VQihPrdWUSiSdS8zM1OMGDFC+Pr6qo6r8HF/8803okWLFqpzXr16dTF48GBx5swZVZmCecj0tXr1agFAuLi4iOTkZLV1V65cEa+++qqoXr26cHFxEUqlUjz//PMiMjJS5+1v2bJFNY+Zg4OD8PT0FBEREWLlypUiMzNTCKHfuRJC92v73r17YtiwYSIgIEAoFAoRGBgo+vfvLx4+fCiE0P53l5eXJ8aOHSvs7OzEV199JYTIn4fszTffFJUqVRIODg4iODhYTJs2TSNjaHJyshgxYoTw9/cXbm5uonfv3uL27dtaj2HatGkiMDBQ2NnZqeYh0/X3hogslyREKenEiIiILFyzZs0gSRJOnz5t7qoQERGpYZdFIiKySikpKbh06RJ+++03nD17Vm3iaCIiIrlgQEZERFbp3LlziIiIgLe3N2bMmIF+/fqZu0pEREQa2GWRiIiIiIjITJj2noiIiIiIyEwYkBEREREREZkJAzIiIiIiIiIzYVIPI8rLy8ODBw/g4eFR4kSoRERERERk3YQQePr0KQIDA2FnV3w7GAMyI3rw4AGCgoLMXQ0iIiIiIpKJe/fuoXLlysWuZ0BmRB4eHgDyT3qFChXMXBsiIiIiIjKXlJQUBAUFqWKE4jAgM6KCbooVKlRgQEZERERERKUOZWJSDyIiIiIiIjNhQEZERERERGQmDMiIiIiIiIjMhGPIiIiIiIhMTAiBnJwc5ObmmrsqZCT29vZwcHAo83RXDMiIiIiIiEwoKysLsbGxePbsmbmrQkbm6uqKSpUqwdHR0eBtMCAjIiIiIjKRvLw8xMTEwN7eHoGBgXB0dCxziwqZnxACWVlZSEhIQExMDGrWrFni5M8lYUBGRERERGQiWVlZyMvLQ1BQEFxdXc1dHTIiFxcXKBQK3LlzB1lZWXB2djZoO0zqQWYhhDB3FYiIiIjKjaGtJyRvxvhe2UJG5UIIgexH8Ui9ehkZd+9A5GRDclDAuUow3EPrQuHjx+Z7IiIiIrI5DMjI5EReHpKOHUT6reuAJAH/tI6JnGykx9xE+q0bcKleC57h7SDx6RERERER2RDe/ZJJCSH+DcbyFxQtAABIv3kNSccPsSsjERERkY2ZOXMmGjVqpHo/dOhQ9OvXr0zbNMY2ygsDMjKp7Efx/wZjpUi/eQ3ZjxJMXCMiIiIi0sXQoUMhSRIkSYJCoUC1atUwefJkpKWlmXS/X3zxBSIjI3Uqe/v2bUiShKioKIO3YW7sskgmlXr1slo3xRJJElKvXoaXr5/pK0ZEREREperWrRvWrFmD7OxsHD58GCNGjEBaWhpWrFihVi47OxsKhcIo+1QqlbLYRnlhCxmZVMbdO7oFYwAgBDLu3jZpfYiIiIhId05OTggICEBQUBAGDhyI1157DZs3b1Z1M/zmm29QrVo1ODk5QQiB5ORkjBo1Cn5+fqhQoQJeeOEFXLhwQW2bc+fOhb+/Pzw8PDB8+HBkZGSorS/a3TAvLw/z5s1DjRo14OTkhCpVquDTTz8FAISEhAAAGjduDEmS0KFDB63byMzMxNixY+Hn5wdnZ2e0adMGp0+fVq0/cOAAJEnC3r170axZM7i6uqJVq1a4evWqEc+mdmwhI5MRQkDkZOv3mZxsCCGYcZGIiIis2urVQGpq+e/X3R0YNcrwz7u4uCA7O//+7saNG/jxxx/xyy+/wN7eHgDQs2dPeHl5Yfv27VAqlVi1ahU6duyIa9euwcvLCz/++CNmzJiBZcuWoW3btli3bh2WLFmCatWqFbvPadOm4auvvsKiRYvQpk0bxMbG4sqVKwCAU6dO4fnnn8cff/yBunXrwtHRUes2pkyZgl9++QVr165FcHAw5s+fj65du+LGjRvw8vJSlfvggw+wYMEC+Pr64s0338SwYcNw9OhRw0+YDhiQkclIkgTJQaFXUCY5KBiMERERkdVLTQVSUsxdC/2cOnUKGzZsQMeOHQHkT3q9bt06+Pr6AgD27duHP//8E/Hx8XBycgIAfP7559i8eTN+/vlnjBo1CosXL8awYcMwYsQIAMAnn3yCP/74Q6OVrMDTp0/xxRdfYOnSpRgyZAgAoHr16mjTpg0AqPbt7e2NgIAArdso6GIZGRmJ7t27AwC++uor7NmzB19//TXeffddVdlPP/0U7du3BwC899576NmzJzIyMgye9FkXDMjIpJyrBCM95qbOY8icq1Q1eZ2IiIiIzM3d3TL2+9tvv8Hd3R05OTnIzs5G37598eWXX2L58uUIDg5WBUQAcPbsWaSmpsLb21ttG+np6bh58yYAIDo6Gm+++aba+vDwcOzfv1/r/qOjo5GZmakKAg1x8+ZNZGdno3Xr1qplCoUCzz//PKKjo9XKNmjQQPX/lSpVAgDEx8ejSpUqBu+/NAzIyKTcQ+si/dYN3QoLAffQuqatEBEREZEMlKXbYHmKiIjAihUroFAoEBgYqJa4w83NTa1sXl4eKlWqhAMHDmhsp2LFigbt38XFxaDPFVYwrVLRXljahskUPr6CdXl5eWWuQ0mY1INMSuHjB5dqNXUq61K9FhQ+vqUXJCIiIqJy4ebmhho1aiA4OLjULIpNmjRBXFwcHBwcUKNGDbWXj48PAKBOnTo4ceKE2ueKvi+sZs2acHFxwd69e7WuLxgzlpubW+w2atSoAUdHRxw5ckS1LDs7G2fOnEGdOnVKPKbywBYyMilJkuDZqj0gSUi/eU0zBf4/712q14JneDuOHyMiIiKyUJ06dUJ4eDj69euHefPmITQ0FA8ePMD27dvRr18/NGvWDOPGjcOQIUPQrFkztGnTBuvXr8fly5eLTerh7OyMqVOnYsqUKXB0dETr1q2RkJCAy5cvY/jw4fDz84OLiwt27tyJypUrw9nZWSPlvZubG9566y28++678PLyQpUqVTB//nw8e/YMw4cPL49TUyIGZGRykp0dPFu1h3utMKRevYyMu7chcrIhOSjgXKUq3EPrQuHjy2CMiIiIyIJJkoTt27fjgw8+wLBhw5CQkICAgAC0a9cO/v7+AIABAwbg5s2bmDp1KjIyMvDyyy/jrbfewq5du4rd7ocffggHBwdMnz4dDx48QKVKlVTj0BwcHLBkyRJ89NFHmD59Otq2bau1y+TcuXORl5eHQYMG4enTp2jWrBl27doFT09Pk5wLfUhC6DpJFJUmJSUFSqUSycnJqFChgrmrI2tMbU9ERES2ICMjAzExMQgJCTFppj4yj5K+X11jA44hI7NgMEZERERExICMiIiIiIjIbMwakB06dAi9e/dGYGAgJEnC5s2bVeuys7MxdepU1K9fH25ubggMDMTgwYPx4MEDtW1kZmbinXfegY+PD9zc3NCnTx/cv39frUxSUhIGDRoEpVIJpVKJQYMG4cmTJ2pl7t69i969e8PNzQ0+Pj4YO3YssrKyTHXoRERERERE5g3I0tLS0LBhQyxdulRj3bNnz3Du3Dl8+OGHOHfuHH799Vdcu3YNffr0USs3fvx4bNq0CRs3bsSRI0eQmpqKXr16qaW+HDhwIKKiorBz507s3LkTUVFRGDRokGp9bm4uevbsibS0NBw5cgQbN27EL7/8gkmTJpnu4ImIiIiIyObJJqmHJEnYtGkT+vXrV2yZ06dP4/nnn8edO3dQpUoVJCcnw9fXF+vWrcOAAQMAAA8ePEBQUBC2b9+Orl27Ijo6GmFhYThx4gRatGgBIH+ug/DwcFy5cgWhoaHYsWMHevXqhXv37iEwMBAAsHHjRgwdOhTx8fHFDsLLzMxEZmam6n1KSgqCgoKY1IOIiIiIADCph7WzuaQeycnJkCRJNdP32bNnkZ2djS5duqjKBAYGol69ejh27BgA4Pjx41AqlapgDABatmwJpVKpVqZevXqqYAwAunbtiszMTJw9e7bY+syZM0fVDVKpVCIoKMiYh0tERERERFbOYgKyjIwMvPfeexg4cKAqwoyLi4Ojo6PG/AH+/v6Ii4tTlfHz89PYnp+fn1qZgrkRCnh6esLR0VFVRptp06YhOTlZ9bp3716ZjpGIiIiIiGyLRUwMnZ2djVdeeQV5eXlYvnx5qeWLznGlLcW6IWWKcnJygpOTU6n1ISIiIiIi0kb2LWTZ2dno378/YmJisGfPHrX+lwEBAcjKykJSUpLaZ+Lj41UtXgEBAXj48KHGdhMSEtTKFG0JS0pKQnZ2tkbLGRERERERkbHIOiArCMauX7+OP/74A97e3mrrmzZtCoVCgT179qiWxcbG4tKlS2jVqhUAIDw8HMnJyTh16pSqzMmTJ5GcnKxW5tKlS4iNjVWV2b17N5ycnNC0aVNTHiIRERERkV5kkpOPjMSsXRZTU1Nx48YN1fuYmBhERUXBy8sLgYGB+M9//oNz587ht99+Q25urqoVy8vLC46OjlAqlRg+fDgmTZoEb29veHl5YfLkyahfvz46deoEAKhTpw66deuGkSNHYtWqVQCAUaNGoVevXggNDQUAdOnSBWFhYRg0aBA+++wzJCYmYvLkyRg5ciSzJRIRERGRWQkhkP0oHqlXLyPj7h2InGxIDgo4VwmGe2hdKHz8ShxmY6ihQ4di7dq1AAAHBwd4eXmhQYMGePXVVzF06FDY2enWthMZGYnx48drzANM+czaQnbmzBk0btwYjRs3BgBMnDgRjRs3xvTp03H//n1s3boV9+/fR6NGjVCpUiXVqyA7IgAsWrQI/fr1Q//+/dG6dWu4urpi27ZtsLe3V5VZv3496tevjy5duqBLly5o0KAB1q1bp1pvb2+P33//Hc7OzmjdujX69++Pfv364fPPPy+/k0FEREREVITIy0PS0QNI2LEF6TE3IXKy85fnZCM95iYSdmxB0rGDEHl5Jtl/t27dEBsbi9u3b2PHjh2IiIjAuHHj0KtXL+Tk5Jhkn7ZGNvOQWQNd5xogIiIiIttQlnnIhBBIOnoA6beul1rWpXoteLZqb9SWsqFDh+LJkyfYvHmz2vJ9+/ahY8eO+OqrrzBixAgsXLgQa9aswa1bt+Dl5YXevXtj/vz5cHd3x4EDBxAREaH2+RkzZmDmzJn47rvvsHjxYly9ehVubm544YUXsHjxYq0Z0uXK5uYhIyIiIiKyFdmP4nUKxgAg/eY1ZD9KMHGN8r3wwgto2LAhfv31VwCAnZ0dlixZgkuXLmHt2rXYt28fpkyZAgBo1aoVFi9ejAoVKiA2NhaxsbGYPHkyACArKwsff/wxLly4gM2bNyMmJgZDhw4tl2OQE4tIe09EREREZGtSr14GJAnQpUObJCH16mV4+ZZP61Lt2rVx8eJFAMD48eNVy0NCQvDxxx/jrbfewvLly1V5HyRJQkBAgNo2hg0bpvr/atWqYcmSJXj++eeRmpoKd3f3cjkOOWALGRERERGRDGXcvaNbMAYAQiDj7m2T1kd9d//O17t//3507twZzz33HDw8PDB48GA8fvwYaWlpJW7j/Pnz6Nu3L4KDg+Hh4YEOHToAAO7evWvq6ssKAzIiIiIiIpkRQqgSeOj8mZzsckuJHx0djZCQENy5cwc9evRAvXr18Msvv+Ds2bNYtmwZgPwprIqTlpaGLl26wN3dHd999x1Onz6NTZs2AcjvymhL2GWRiIiIiEhmJEmC5KDQKyiTHBQmSX9f1L59+/Dnn39iwoQJOHPmDHJycrBgwQJVGvwff/xRrbyjoyNyc3PVll25cgWPHj3C3LlzERQUBCA/A7stYgsZEREREZEMOVcJzh9DpgtJgnOVqkavQ2ZmJuLi4vD333/j3LlzmD17Nvr27YtevXph8ODBqF69OnJycvDll1/i1q1bWLduHVauXKm2japVqyI1NRV79+7Fo0eP8OzZM1SpUgWOjo6qz23duhUff/yx0etvCRiQERERERHJkHtoXb3GkLmH1jV6HXbu3IlKlSqhatWq6NatG/bv348lS5Zgy5YtsLe3R6NGjbBw4ULMmzcP9erVw/r16zFnzhy1bbRq1QpvvvkmBgwYAF9fX8yfPx++vr6IjIzETz/9hLCwMMydO9dm5wDmPGRGxHnIiIiIiKgwS56HjErHeciIiIiIiKyUJEnwbNUeLtVrFSwoWgDAP8FYeDsGYxaKST2IiIiIiGRKsrODZ6v2cK8VhtSrl5Fx9zZETjYkBwWcq1SFe2hdKHx8GYxZMAZkREREREQyJkkSHH39VJM+F54DjCwfuywSEREREVkQBmPWhQEZEREREZGJMY+edTLG98qAjIiIiIjIRBQKBQDg2bNnZq4JmULB91rwPRuCY8iIiIiIiEzE3t4eFStWRHx8PADA1dWVXQ6tgBACz549Q3x8PCpWrAh7e3uDt8WAjIiIiIjIhAICAgBAFZSR9ahYsaLq+zUUAzIiIiIiIhOSJAmVKlWCn58fsrOzzV0dMhKFQlGmlrECDMiIiIiIiMqBvb29UW7gybowqQcREREREZGZMCAjIiIiIiIyEwZkREREREREZsKAjIiIiIiIyEwYkBEREREREZkJAzIiIiIiIiIzYUBGRERERERkJgzIiIiIiIiIzIQBGRERERERkZkwICMiIiIiIjITBmRERERERERmwoCMiIiIiIjITBiQERERERERmQkDMiIiIiIiIjNhQEZERERERGQmDMiIiIiIiIjMhAEZERERERGRmTAgIyIiIiIiMhMGZERERERERGbCgIyIiIiIiMhMGJARERERERGZCQMyIiIiIiIiM2FARkREREREZCZmDcgOHTqE3r17IzAwEJIkYfPmzWrrhRCYOXMmAgMD4eLigg4dOuDy5ctqZTIzM/HOO+/Ax8cHbm5u6NOnD+7fv69WJikpCYMGDYJSqYRSqcSgQYPw5MkTtTJ3795F79694ebmBh8fH4wdOxZZWVmmOGwiIiIiIiIAZg7I0tLS0LBhQyxdulTr+vnz52PhwoVYunQpTp8+jYCAAHTu3BlPnz5VlRk/fjw2bdqEjRs34siRI0hNTUWvXr2Qm5urKjNw4EBERUVh586d2LlzJ6KiojBo0CDV+tzcXPTs2RNpaWk4cuQINm7ciF9++QWTJk0y3cETEREREZHNk4QQwtyVAABJkrBp0yb069cPQH7rWGBgIMaPH4+pU6cCyG8N8/f3x7x58zB69GgkJyfD19cX69atw4ABAwAADx48QFBQELZv346uXbsiOjoaYWFhOHHiBFq0aAEAOHHiBMLDw3HlyhWEhoZix44d6NWrF+7du4fAwEAAwMaNGzF06FDEx8ejQoUKOh1DSkoKlEolkpOTdf4MERERERFZH11jA9mOIYuJiUFcXBy6dOmiWubk5IT27dvj2LFjAICzZ88iOztbrUxgYCDq1aunKnP8+HEolUpVMAYALVu2hFKpVCtTr149VTAGAF27dkVmZibOnj1bbB0zMzORkpKi9iIiIiIiItKVbAOyuLg4AIC/v7/acn9/f9W6uLg4ODo6wtPTs8Qyfn5+Gtv38/NTK1N0P56ennB0dFSV0WbOnDmqcWlKpRJBQUF6HiUREREREdky2QZkBSRJUnsvhNBYVlTRMtrKG1KmqGnTpiE5OVn1unfvXon1IiIiIiIiKky2AVlAQAAAaLRQxcfHq1qzAgICkJWVhaSkpBLLPHz4UGP7CQkJamWK7icpKQnZ2dkaLWeFOTk5oUKFCmovIiIiIiIiXck2IAsJCUFAQAD27NmjWpaVlYWDBw+iVatWAICmTZtCoVColYmNjcWlS5dUZcLDw5GcnIxTp06pypw8eRLJyclqZS5duoTY2FhVmd27d8PJyQlNmzY16XESEREREZHtcjDnzlNTU3Hjxg3V+5iYGERFRcHLywtVqlTB+PHjMXv2bNSsWRM1a9bE7Nmz4erqioEDBwIAlEolhg8fjkmTJsHb2xteXl6YPHky6tevj06dOgEA6tSpg27dumHkyJFYtWoVAGDUqFHo1asXQkNDAQBdunRBWFgYBg0ahM8++wyJiYmYPHkyRo4cyVYvIiIiIiIyGbMGZGfOnEFERITq/cSJEwEAQ4YMQWRkJKZMmYL09HSMGTMGSUlJaNGiBXbv3g0PDw/VZxYtWgQHBwf0798f6enp6NixIyIjI2Fvb68qs379eowdO1aVjbFPnz5qc5/Z29vj999/x5gxY9C6dWu4uLhg4MCB+Pzzz019CoiIiIiIyIbJZh4ya8B5yIiIiIiICLCCeciIiIiIiIisHQMyIiIiIiIiM2FARkREREREZCYMyIiIiIiIiMyEARkREREREZGZMCAjMiMmOSUiIiKybWadh4zI1gghkP0oHqlXLyPj7h2InGxIDgo4VwmGe2hdKHz8IEmSuatJREREROWEARlRORF5eUg6dhDpt64DkgT80zomcrKRHnMT6bduwKV6LXiGt4Nkx8ZrIiIiIlvAuz6iciCE+DcYy19QtAAAIP3mNSQdP8SujEREREQ2ggEZUTnIfhT/bzBWivSb15D9KMHENSIiIiIiOWBARlQOUq9ezu+mqAtJyi9PRERERFaPARlROci4e0ezm2JxhEDG3dsmrQ8RERERyQMDMiITE0JA5GTr95mcbI4jIyIiIrIBDMiITEySJEgOCv0+46Bg+nsiIiIiG8CAjKgcOFcJ1msMmXOVqiatDxERERHJAwMyonLgHlpXrzFk7qF1TVshIiIiIpIFBmRE5UDh4weXajV1KutSvRYUPr4mrhERERERyQEDMqJyIEkSPFu1h0v1WgULihYAkB+MeYa34/gxIiIiIhvhYO4KENkKyc4Onq3aw71WGFKvXkbG3dsQOdmQHBRwrlIV7qF1ofDxZTBGREREZEMYkBGVI0mS4OjrBy9fPwD5KfEZgBERERHZLnZZJDIjBmNEREREto0BGRERERERkZkwICMiIiIiIjITBmRERERERERmwoCMiIiIiIjITBiQERERERERmQkDMiIiIiIiIjNhQEZERERERGQmDMiIiIiIiIjMRO+ALD09Hc+ePVO9v3PnDhYvXozdu3cbtWJERERERETWTu+ArG/fvvj2228BAE+ePEGLFi2wYMEC9O3bFytWrDB6BYmIiIiIiKyV3gHZuXPn0LZtWwDAzz//DH9/f9y5cwfffvstlixZYvQKEhERERERWSu9A7Jnz57Bw8MDALB792689NJLsLOzQ8uWLXHnzh2jV5CIiIiIiMha6R2Q1ahRA5s3b8a9e/ewa9cudOnSBQAQHx+PChUqGL2CRERERERE1krvgGz69OmYPHkyqlatihYtWiA8PBxAfmtZ48aNjV5BIiIiIiIiayUJIYS+H4qLi0NsbCwaNmwIO7v8mO7UqVNQKpUIDQ01eiUtRUpKCpRKJZKTk9laSERERERkw3SNDfRuIRs2bBjc3NzQuHFjVTAGAHXr1sW8efMMqy0REREREZEN0jsgW7t2LdLT0zWWp6enq9LhExERERERUekcdC2YkpICIQSEEHj69CmcnZ1V63Jzc7F9+3b4+fmZpJJERERERETWSOeArGLFipAkCZIkoVatWhrrJUnCrFmzjFo5IiIiIiIia6ZzQLZ//34IIfDCCy/gl19+gZeXl2qdo6MjgoODERgYaJJKEhERERERWSOdA7L27dsDAGJiYlClShVIkmSyShEREREREdkCvZN63LlzB4cPH8ahQ4e0vowpJycH//vf/xASEgIXFxdUq1YNH330EfLy8lRlhBCYOXMmAgMD4eLigg4dOuDy5ctq28nMzMQ777wDHx8fuLm5oU+fPrh//75amaSkJAwaNAhKpRJKpRKDBg3CkydPjHo8REREREREhencQlagQ4cOGssKt5bl5uaWqUKFzZs3DytXrsTatWtRt25dnDlzBm+88QaUSiXGjRsHAJg/fz4WLlyIyMhI1KpVC5988gk6d+6Mq1evwsPDAwAwfvx4bNu2DRs3boS3tzcmTZqEXr164ezZs7C3twcADBw4EPfv38fOnTsBAKNGjcKgQYOwbds2ox0PERERERFRYXpPDJ2cnKz2Pjs7G+fPn8eHH36ITz/9FB07djRa5Xr16gV/f398/fXXqmUvv/wyXF1dsW7dOgghEBgYiPHjx2Pq1KkA8lvD/P39MW/ePIwePRrJycnw9fXFunXrMGDAAADAgwcPEBQUhO3bt6Nr166Ijo5GWFgYTpw4gRYtWgAATpw4gfDwcFy5ckXnya45MTQREREREQEmnBi6oEtfwcvHxwedO3fG/PnzMWXKlDJVuqg2bdpg7969uHbtGgDgwoULOHLkCHr06AEgfzxbXFwcunTpovqMk5MT2rdvj2PHjgEAzp49i+zsbLUygYGBqFevnqrM8ePHoVQqVcEYALRs2RJKpVJVRpvMzEykpKSovYiIiIiIiHSld5fF4vj6+uLq1avG2hwAYOrUqUhOTkbt2rVhb2+P3NxcfPrpp3j11VcBAHFxcQAAf39/tc/5+/vjzp07qjKOjo7w9PTUKFPw+bi4OK1zqPn5+anKaDNnzhym+iciIiIiIoPpHZBdvHhR7b0QArGxsZg7dy4aNmxotIoBwA8//IDvvvsOGzZsQN26dREVFYXx48cjMDAQQ4YMUZUrmvFRCFFqFsiiZbSVL20706ZNw8SJE1XvU1JSEBQUVOpxERERERERAQYEZI0aNYIkSSg69Kxly5b45ptvjFYxAHj33Xfx3nvv4ZVXXgEA1K9fH3fu3MGcOXMwZMgQBAQEAMhv4apUqZLqc/Hx8apWs4CAAGRlZSEpKUmtlSw+Ph6tWrVSlXn48KHG/hMSEjRa3wpzcnKCk5NT2Q+UiIiIiIhskt5jyGJiYnDr1i3ExMQgJiYGd+7cwbNnz3Ds2DHUrl3bqJV79uwZ7OzUq2hvb69Kex8SEoKAgADs2bNHtT4rKwsHDx5UBVtNmzaFQqFQKxMbG4tLly6pyoSHhyM5ORmnTp1SlTl58iSSk5NVZYiIiIiIiIxN7xay4OBgU9RDq969e+PTTz9FlSpVULduXZw/fx4LFy7EsGHDAOR3Mxw/fjxmz56NmjVrombNmpg9ezZcXV0xcOBAAPlJSIYPH45JkybB29sbXl5emDx5MurXr49OnToBAOrUqYNu3bph5MiRWLVqFYD8tPe9evXSOcMiERERERGRvgxK6nHw4EF8/vnniI6OhiRJqFOnDt599120bdvWqJX78ssv8eGHH2LMmDGIj49HYGAgRo8ejenTp6vKTJkyBenp6RgzZgySkpLQokUL7N69WzUHGQAsWrQIDg4O6N+/P9LT09GxY0dERkaq5iADgPXr12Ps2LGqbIx9+vTB0qVLjXo8REREREREhek9D9l3332HN954Ay+99BJat24NIQSOHTuGTZs2ITIyUtUyZYs4DxkREREREQG6xwZ6B2R16tTBqFGjMGHCBLXlCxcuxFdffYXo6GjDamwFGJARERERERFgwomhb926hd69e2ss79OnD2JiYvTdHBERERERkc3SOyALCgrC3r17NZbv3buXc3ARERERERHpQe+kHpMmTcLYsWMRFRWFVq1aQZIkHDlyBJGRkfjiiy9MUUciIiIiIiKrpHdA9tZbbyEgIAALFizAjz/+CCB/XNkPP/yAvn37Gr2CRERERERE1krvpB737t0rtmviiRMn0LJlS6NUzBIxqQcREREREQEmTOrRuXNnPH78WGP50aNH0a1bN303R0REREREZLP0Dsjatm2LLl264OnTp6plhw4dQvfu3TFjxgyjVo6IiIiIiMia6R2QrV69GiEhIejZsycyMjKwf/9+9OzZEx9//LHG3GRERERERERUPL0DMkmS8P3338PZ2RkdO3ZEnz59MGfOHIwbN84U9SMiIiIiIrJaOiX1uHjxosayp0+f4tVXX0XPnj3x1ltvqZY3aNDAuDW0IEzqQUREREREgO6xgU4BmZ2dHSRJQuGihd8X/L8kScjNzTVC9S0TAzIiIiIiIgJ0jw10mocsJibGaBUjIiIiIiKifDoFZMHBwaauBxERERERkc3RO6nHnDlz8M0332gs/+abbzBv3jyjVIqIiIiIiMgW6B2QrVq1CrVr19ZYXrduXaxcudIolSIi89FhWCkRERERGYlOXRYLi4uLQ6VKlTSW+/r6IjY21iiVIqLyI4RA9qN4pF69jIy7dyBysiE5KOBcJRjuoXWh8PEDkJ+8h4iIiIiMS++ALCgoCEePHkVISIja8qNHjyIwMNBoFSMi0xN5eUg6dhDpt64DkgT80zomcrKRHnMT6bduqJYXDdIYoBERERGVnd4B2YgRIzB+/HhkZ2fjhRdeAADs3bsXU6ZMwaRJk4xeQSIyDSHEv8FY/oKiBdT+WzhIc6leC57h7SDZ6d3rmYiIiIgK0TsgmzJlChITEzFmzBhkZWUBAJydnTF16lRMmzbN6BUkItPIfhT/bzCmq3+Cs/Sb1wAAnq3as6WMiIiIqAx0mhham9TUVERHR8PFxQU1a9aEk5OTsetmcTgxNFmSxCP7kB5zU7NlTA++3fvB0dfPiLUiIiIisg66xgYG9zeKi4tDYmIiqlevDicnJ2ZmI7IwGXfvlCkYgyQh9epl41WIiIiIyAbpHZA9fvwYHTt2RK1atdCjRw9VZsURI0ZwDBmRhRBCQORkl3UjyLh72yj1ISIiIrJVegdkEyZMgEKhwN27d+Hq6qpaPmDAAOzcudOolSMi05AkCZKDoszbETnZbB0nIiIiKgO9k3rs3r0bu3btQuXKldWW16xZE3fu3DFaxYjItJyrBJd5DJnkoGBSDyIiIqIy0LuFLC0tTa1lrMCjR4+Y2IPIgriH1i3zGDLnKlWNVh8iIiIiW6R3QNauXTt8++23qveSJCEvLw+fffYZIiIijFo5IjIdhY8fXKrVNHwDQuQHdURERERkML27LH722Wfo0KEDzpw5g6ysLEyZMgWXL19GYmIijh49aoo6EpEJSJIEz1btAUnKn1dMkvRqMXOpXgsKH18T1pCIiIjI+undQhYWFoaLFy/i+eefR+fOnZGWloaXXnoJ58+fR/Xq1U1RRyIyEcnODp6t2sO3ez+4hNT4N9FHcePC/lnuUr0WPMPbcfwYERERURkZPDE0aeLE0GQNCn4Ssh8lIPXqZWTcvQ2Rkw3JQQHnKlXhHloXCh9fBmNEREREJdA1NtC7yyIAPHnyBKdOnUJ8fDzy8vLU1g0ePNiQTRKRTBQEWo6+fvDy9QOQH6QxACMiIiIyPr0Dsm3btuG1115DWloaPDw81G7SJEliQEZkhRiMEREREZmG3mPIJk2ahGHDhuHp06d48uQJkpKSVK/ExERT1JGIiIiIiMgq6R2Q/f333xg7dqzWuciIiIiIiIhId3oHZF27dsWZM2dMURciIiIiIiKbotMYsq1bt6r+v2fPnnj33Xfx119/oX79+lAoFGpl+/TpY9waEhERERERWSmd0t7b2enWkCZJEnJzc8tcKUvFtPdERERERAQYOe190dT2REREREREVHZ6jyEjIiIiIiIi49A5INu3bx/CwsKQkpKisS45ORl169bFoUOHjFo5IiIiIiIia6ZzQLZ48WKMHDlSa/9HpVKJ0aNHY9GiRUatHBERERERkTXTOSC7cOECunXrVuz6Ll264OzZs0apFBERERERkS3QOSB7+PChRor7whwcHJCQkGCUShX2999/4/XXX4e3tzdcXV3RqFEjtcBPCIGZM2ciMDAQLi4u6NChAy5fvqy2jczMTLzzzjvw8fGBm5sb+vTpg/v376uVSUpKwqBBg6BUKqFUKjFo0CA8efLE6MdDRERERERUQOeA7LnnnsOff/5Z7PqLFy+iUqVKRqlUgaSkJLRu3RoKhQI7duzAX3/9hQULFqBixYqqMvPnz8fChQuxdOlSnD59GgEBAejcuTOePn2qKjN+/Hhs2rQJGzduxJEjR5CamopevXqppegfOHAgoqKisHPnTuzcuRNRUVEYNGiQUY+HiIiIiIioMJ3mIQOAd955BwcOHMDp06fh7Oysti49PR3PP/88IiIisGTJEqNV7r333sPRo0dx+PBhreuFEAgMDMT48eMxdepUAPmtYf7+/pg3bx5Gjx6N5ORk+Pr6Yt26dRgwYAAA4MGDBwgKCsL27dvRtWtXREdHIywsDCdOnECLFi0AACdOnEB4eDiuXLmC0NBQnerLeciIiIiIiAjQPTbQuYXsf//7HxITE1GrVi3Mnz8fW7ZswdatWzFv3jyEhoYiMTERH3zwgVEqX2Dr1q1o1qwZ/u///g9+fn5o3LgxvvrqK9X6mJgYxMXFoUuXLqplTk5OaN++PY4dOwYAOHv2LLKzs9XKBAYGol69eqoyx48fh1KpVAVjANCyZUsolUpVGW0yMzORkpKi9iIiIiIiItKVThNDA4C/vz+OHTuGt956C9OmTUNBw5okSejatSuWL18Of39/o1bu1q1bWLFiBSZOnIj3338fp06dwtixY+Hk5ITBgwcjLi5OVbeidb1z5w4AIC4uDo6OjvD09NQoU/D5uLg4+Pn5aezfz89PVUabOXPmYNasWWU6RiIiIiIisl06B2QAEBwcjO3btyMpKQk3btyAEAI1a9bUCHaMJS8vD82aNcPs2bMBAI0bN8bly5exYsUKDB48WFVOkiS1zwkhNJYVVbSMtvKlbWfatGmYOHGi6n1KSgqCgoJKPigiIiIiIqJ/6NxlsTBPT080b94czz//vMmCMQCoVKkSwsLC1JbVqVMHd+/eBQAEBAQAgEYrVnx8vKrVLCAgAFlZWUhKSiqxzMOHDzX2n5CQUGKrn5OTEypUqKD2IiIiIiIi0pVBAVl5ad26Na5evaq27Nq1awgODgYAhISEICAgAHv27FGtz8rKwsGDB9GqVSsAQNOmTaFQKNTKxMbG4tKlS6oy4eHhSE5OxqlTp1RlTp48ieTkZFUZIiIiIiIiY9Ory2J5mzBhAlq1aoXZs2ejf//+OHXqFFavXo3Vq1cDyO9mOH78eMyePRs1a9ZEzZo1MXv2bLi6umLgwIEAAKVSieHDh2PSpEnw9vaGl5cXJk+ejPr166NTp04A8lvdunXrhpEjR2LVqlUAgFGjRqFXr146Z1gkIiIiIiLSl6wDsubNm2PTpk2YNm0aPvroI4SEhGDx4sV47bXXVGWmTJmC9PR0jBkzBklJSWjRogV2794NDw8PVZlFixbBwcEB/fv3R3p6Ojp27IjIyEjY29uryqxfvx5jx45VZWPs06cPli5dWn4HS0Syo8t4VCIiIqKy0GkesiZNmmDv3r3w9PTERx99hMmTJ8PV1bU86mdROA8ZkWUTQiD7UTxSr15Gxt07EDnZkBwUcK4SDPfQulD4+DFAIyIiIp3oGhvoFJC5uLjg+vXrqFy5Muzt7REbG6s1TbytY0BGZLlEXh6Sjh1E+q3rgCQBhX8a/3nvUr0WPMPbQbKT9fBbIiIikgFdYwOduiw2atQIb7zxBtq0aQMhBD7//HO4u7trLTt9+nTDakxEZCZCiH+DsfwFRQsAANJvXgMAeLZqz5YyIiIiMgqdWsiuXr2KGTNm4ObNmzh37hzCwsLg4KAZy0mShHPnzpmkopaALWRElikr4SESdmzRubxv935w9GUvASIiIiqeUVvIQkNDsXHjRgCAnZ0d9u7dyy6LRGQ1Uq9e1uymWBxJQurVy/BiQEZERERGoHeWxby8PFPUg4jIbDLu3tEtGAMAIZBx97ZJ60NERES2w6C09zdv3sTixYsRHR0NSZJQp04djBs3DtWrVzd2/YiITEoIAZGTrd9ncrKZEp+IiIiMQu9UYbt27UJYWBhOnTqFBg0aoF69ejh58iTq1q2LPXv2mKKOREQmI0kSJAeFfp9xUDAYIyIiIqPQu4Xsvffew4QJEzB37lyN5VOnTkXnzp2NVjkiovLgXCUY6TE3dR5D5lylqsnrRERERLZB7xay6OhoDB8+XGP5sGHD8NdffxmlUkRE5ck9tK5eY8jcQ+uatkJERERkM/QOyHx9fREVFaWxPCoqipkXicgiKXz84FKtpk5lXarXgsLH18Q1IiIiIluhd5fFkSNHYtSoUbh16xZatWoFSZJw5MgRzJs3D5MmTTJFHYnKhMkXqDSSJMGzVXtAkvInfy6aAv+f9y7Va8EzvB2vJyIiIjIanSaGLkwIgcWLF2PBggV48OABACAwMBDvvvsuxo4da9M3KpwYWh6EEMh+FI/Uq5eRcfcORE42JAcFnKsEwz20LhQ+fjZ9nVLx8q+dhH+unduFrp2q/1w7vrx2iIiISCe6xgZ6B2SFPX36FADg4eFh6CasCgMy8xN5eUg6dhDpt66X3sphp3ePXZNgC5588bshIiIiQ+kaGxg0D1kBBmIkJ0KIf4Ox/AVFCwBAfpc0AJ6t2pvlZpsteJaD3wMRERGZWpkCMiI5yX4U/28wVor0m9fgXisMjr7lm4imuBY8kZON9JibSL91Q3YteERERERkOrzjI6uRevVyfpCjC0nKL1+O9GnBSzp+CGXoTUxEREREFoIBGVmNjLt39JpLKuPubZPWpyh9W/CyHyWYuEZEREREZG56BWTZ2dmIiIjAtWvXTFUfIoMIISBysvX7TE52ubZCyb0Fj4iIiIjKn14BmUKhwKVLlzjQnTSYu3udJEmQHBT6fcZBUa7Xstxb8IiIiIio/Omd1GPw4MH4+uuvMXfuXFPUhyyEHDMFOlcJRnrMTd2CHkmCc5WqJq9TgbK04PEBCBEREZH10jsgy8rKwv/7f/8Pe/bsQbNmzeDm5qa2fuHChUarHMmTXDMFuofWRfqtG7oVFgLuoXVNVpeigVRBC54+QVl5t+ARERERUfnTOyC7dOkSmjRpAgAaY8l482j95DzXl8LHDy7VauqUOMOlei0ofHyNtm9dWgzl3IJnK9jiSERERHKjd0C2f/9+U9SDLISc5/qSJAmerdoDkpQfEBZqvfunACDEv613Rrox17XF0K1mHdm04NkKOXatJSIiIirM4Imhb9y4gZs3b6Jdu3ZwcXHhk2cbocoUqGMrT+rVy/Aqx8mXJTs7eLZqD/daYf/chN8udBNe9Z+bcF/jBWP6tBgKAeeQGsiIKT0oM3YLni2Sa9daIiIiosL0DsgeP36M/v37Y//+/ZAkCdevX0e1atUwYsQIVKxYEQsWLDBFPUkmLCFToCRJcPT1UwWChjws0PUzerUY3roOn259INnZlWsLni2Sc9daIiIiosL0DsgmTJgAhUKBu3fvok6dOqrlAwYMwIQJExiQWTFLzRSoy74N7dqmb4th2rVoeLbuUG4teLZKzl1riYiIiArTOyDbvXs3du3ahcqVK6str1mzJu7cuWO0ipH8WGumwLJ0bTOkxVBqU/YWPCqZ3LvWEhERERXQe+BEWloaXF1dNZY/evQITk5ORqkUyZdzleD8G11dWECmQH26tiUdP6Q2AXZZWgwLYzBmfJbQtZaIiIgIMCAga9euHb799lvVe0mSkJeXh88++wwRERFGrRyVTdEbf2NwD62r142u3DMF6tu1LftRgup9QYuhPiyhxdDSGStQJiIiIioPendZ/Oyzz9ChQwecOXMGWVlZmDJlCi5fvozExEQcPXrUFHUkHZVHim9zzvVlCmXt2sa5xeTHWrvWEhERkXXSu4UsLCwMFy9exPPPP4/OnTsjLS0NL730Es6fP4/q1auboo6kA5GXh6SjB5CwYwvSY26qbkYLxkEl7NiCpGMHIfLyyrSfgrm+XKrXKlhQtAAAWEymwLJ2bbO2FkNrYW1da4mIiMh6GTQPWUBAAGbNmmXsupCByjvFd3nP9WUqxsgaaW0thtbCPbQuJ+G2IExsQ0REtsyggCwpKQlff/01oqOjIUkS6tSpgzfeeANeXl7Grh/pwBwpvo0x15e5GaNrW0GLISSJc4vJCANleSuP7tVERESWQu8uiwcPHkRISAiWLFmCpKQkJCYmYsmSJQgJCcHBgwdNUUcqhWoclC7+GQdlbEVvniwlQYIxurYVtBj6du8Hl5AaqkQfkoMCLiE14Nu9X36rpJ3ef25koFK71haSfvsWko7uR1bCQ1lct3KogymVV/dqIiIiSyEJPf/1r1evHlq1aoUVK1bA3t4eAJCbm4sxY8bg6NGjuHTpkkkqaglSUlKgVCqRnJyMChUqlNt+H2xYo3crT+DAN4xaB0t94p2V8BAJO7boXN63ez+dWhctscXQGuVflwlqXWu1KtqSWY7Bs6X+7RhCCIGkowd0brksa/dqueLvAxGRbdA1NtC7y+LNmzfxyy+/qIIxALC3t8fEiRPV0uFT+TDGOKgy16EMEyubm6m6tvFmSx4KutZ6+vgiCSUEAkYeZ6krS/7bMYQ5ulfLgS0F3UREpD+9A7ImTZogOjoaoaGhasujo6PRqFEjY9WLdKRtHFROroST1wJw4kogAr1SUS/4EWo9lwQnRX4XIGOm+C7vhCLGxjFgtkGOgYCl/+0YoqzTTFgiWwu6iYhIfzoFZBcvXlT9/9ixYzFu3DjcuHEDLVu2BACcOHECy5Ytw9y5c01TSypR0bmwou954cSVQADAg0R3PEh0x+7zVVXlfYIqoPVzQMOGQMWKZdu3HG909SWXrJHsxmQ6cgwErOFvR19lnWbC0thi0E1ERPrTKSBr1KgRJElSG2w+ZcoUjXIDBw7EgAEDjFc70knRFN/+FZ+VWD7dKRD79wP792uu69oVaNlS9zwXcrzR1UdBEGSOrJHsxlR+5BgIWPrfjr7k0L26vNli0E1ERPrTKSCLiYkxdT2oDIqOg/KrmI7R3S7i4m0fXL7jg5R0x3/LenrDztW12G3t2pX/KqxePaB3b8DJSbO8HG90S66CbkGQyYMxdmMqN3INBCztb6esjDHNhKWxtaCbiIgMo1NAFhwcbOp6UBloGwfl7pKNVnVi0apOrOqGQKpcGw88GiPqgoT793Xf/qVL+a/CPD2BgQPleaNb7L5lEgSxG1P5kmMgkJeXZ1F/O8ZStHt1iYqZZsKS2FrQTUREhjFoYui///4bR48eRXx8PPKKzBUzduxYo1RMmzlz5uD999/HuHHjsHjxYgD5N7ezZs3C6tWrkZSUhBYtWmDZsmWoW7eu6nOZmZmYPHkyvv/+e6Snp6Njx45Yvnw5KleurCqTlJSEsWPHYuvWrQCAPn364Msvv0TFsg6yKie6joMKlCQ0a/7v5/LygBs3gM2bgWcl93RUk5QELFsm4emfzdXmC6oT9Bg9mt0uvp5meuItpyCI3ZjKn9wCgZzHCXp/xtJbiwDN7tUlEgLuoXVLLydTcm2ZJSIi+dE7IFuzZg3efPNNODo6wtvbW+0fDkmSTBaQnT59GqtXr0aDBg3Uls+fPx8LFy5EZGQkatWqhU8++QSdO3fG1atX4eHhAQAYP348tm3bho0bN8Lb2xuTJk1Cr169cPbsWVX6/oEDB+L+/fvYuXMnAGDUqFEYNGgQtm3bZpLjMQVDxkHZ2QG1agFFhwSePw9s0WF6LgdlRWQnJareR9/zRvQ9b41y7/Q+D0eFMNsTbzkFQezGVP6MFQgY62bZkMnZLb21CDDdNBNyJMeWWSIikie9A7Lp06dj+vTpmDZtGuzKaWxLamoqXnvtNXz11Vf45JNPVMuFEFi8eDE++OADvPTSSwCAtWvXwt/fHxs2bMDo0aORnJyMr7/+GuvWrUOnTp0AAN999x2CgoLwxx9/oGvXroiOjsbOnTtx4sQJtGjRAgDw1VdfITw8HFevXtVI8W8pyvIPe+PG+a/CHjwA1q0D0tP/Xebo7asWkBXny235G3OrURv2f+QvGzIECAkxuIp6kVMQxG5M5c/QQMBUiVcy7t7R+zOW3FpUwNammZBbyywREcmT3gHZs2fP8Morr5RbMAYAb7/9Nnr27IlOnTqpBWQxMTGIi4tDly5dVMucnJzQvn17HDt2DKNHj8bZs2eRnZ2tViYwMBD16tXDsWPH0LVrVxw/fhxKpVIVjAFAy5YtoVQqcezYsWIDsszMTGRmZqrep6SkGPOwy11pT/8DA4GpU9WXpaa64eOxXjoFZUUTiqxdq1mmQQPgn9jaqOQSBLEbk3kYEgiYasyhIdcAADh4++j9GTmSyzQT5cGWumgSEZHh9A7Ihg8fjp9++gnvvfeeKeqjYePGjTh37hxOnz6tsS4uLg4A4O/vr7bc398fd+7cUZVxdHSEp6enRpmCz8fFxcHPT7M1xM/PT1VGmzlz5mDWrFn6HZCMGOPpv7u7hLn/LxhJx++obnRzc4HFW5qolVN4esM5KLjU7V28mP8qasYM3VPxFyWnIIjdmMxHn0DAlGMODbkGYO9Qrg/BTM0c00yYgy110SQiIsPpHZDNmTMHvXr1ws6dO1G/fn0oFAq19QsXLjRa5e7du4dx48Zh9+7dcHZ2LrZc0X/IdfnHvWgZbeVL2860adMwceJE1fuUlBQEBQWVuF+5MObTf203upNePKtxo7tggYTUVMPqqy3uHT9et4mt5RYEsRuT+egaCJh6zKFe1wAAl+By6ttrJtYYjAG210WTiIgMo3dANnv2bOzatUvVja+0oKYszp49i/j4eDRt2lS1LDc3F4cOHcLSpUtx9epVAPktXJUqVVKViY+PV7WaBQQEICsrC0lJSWqtZPHx8WjVqpWqzMOHDzX2n5CQoNH6VpiTkxOctE3OJXOmePqvy43u5MmanztxAvgnj4re/km0qaZLF+Cfr1WNnIIgdmOSj+Kua1ONOSz4u9DrGoB1jB+zVbbURZOIiAyjd0C2cOFCfPPNNxg6dKgJqqOuY8eO+PPPP9WWvfHGG6hduzamTp2KatWqISAgAHv27EHjfzJQZGVl4eDBg5g3bx4AoGnTplAoFNizZw/69+8PAIiNjcWlS5cwf/58AEB4eDiSk5Nx6tQpPP/88wCAkydPIjk5WRW0WZPyyDio681Fy5b5r8KSkoAvvtBrdyq7dgns3q257/fflk8QxG5M8mesMYfFdgsOCoZTYGVkPih9QkBeA5bPVrpoEhGRYfQOyJycnNC6dWtT1EWDh4cH6tWrp7bMzc0N3t7equXjx4/H7NmzUbNmTdSsWROzZ8+Gq6srBg4cCABQKpUYPnw4Jk2aBG9vb3h5eWHy5MmoX7++KutinTp10K1bN4wcORKrVq0CkJ/2vlevXhabYbEkcso4qI2nJzBzpvoyIbR3WxRCIO9ZGrIeJyAn+QlEXh4kOzs4KCvC0dsXdq5ukCQJny71Q8a9zmrJR8b2PgeFg+Y5MPUNMLsxyZuxxhyW2C34dn5rrb27B3JTn/IasDH8PomIqDC9A7Jx48bhyy+/xJIlS0xRH71NmTIF6enpGDNmjGpi6N27d6vmIAOARYsWwcHBAf3791dNDB0ZGamagwwA1q9fj7Fjx6qyMfbp0wdLly4t9+MpD3LJOKgPSdISpOXlYcG71/HgVqrG8uykRGQnJaolE3EOqgpAQnbSYwDAkm3qiUcA4NUBOWgW3tzkN0zsxiRfxhhzqGu34NzUp3B6LgiSoxMy793hNUBERGSDJCF0vTPP9+KLL2Lfvn3w9vZG3bp1NZJ6/Prrr0atoCVJSUmBUqlEcnIyKlSoYO7qaCWEwIN1X+n9ucBBI2V1YyiEQOKR/ciI0eyG+Odtb+w+X1X13sHTK3++tMcJyH7yBBB5auX/bVHzg52rq8Zx+vsDb71liqNQx25M8pF4ZJ9eYw5dQmrAq02EalFWwkMk7NBhZvV/+HbvB0dfP14DREREVkTX2EDvFrKKFSuqJmEmyyO3jIP6UBuPc+c2RG6O1nL1qz5G/aqP1ZY9y3TAiu0NtZZ3UHqWmJL/4UPN1jlA+7KykMM5pnxlTbxiaLdgXgNkTnwgQERkHnoHZGvWrDFFPagcySnjoK6KG4+jK1enHEx68azG8gWbmqq6MOoyT1ph2gKyCRMApVKvqpEMlTXxiiV2CybbY4y5KImIqOz0DsjI8lla2vVSx+OUQeEgraDb2NdfA/fuGba9RYs0l7VtC3TsaGAFLZSlP2kvS+IVOU1ETpZ/LZqKMeeiJCKistE7IAsJCSnxH7dbt26VqUJkepaWdl2fNP0GK9RtbPhwzdU3bwLr1hm26cOH819FGbvLozlvPK3xSbuhiVcsuVuwNbDGa9HYTDEXJRERGU7vgGz8+PFq77Ozs3H+/Hns3LkT7777rrHqRSZkaWnX9RqPY6hSuo1Vr64ZQOXkAJ98YnggpC0gmz4d0PVhtFxuPK35Sbuh80dZYrdga2DN16IxlcdclEREpDuD0t5rs2zZMpw5c6bMFaLyYUlp1/Uaj1MGunYbKxwIjaqlGQh9utTwQOijjzSXDRwI1KpVpA4yufG0tSftutbd0roFWwNbuxbLQu5zURIR2RqjjSHr3r07pk2bxqQfFsTQp//lyZDxOIbSpduYLoHQuC6agdC2bcBZzZwiOtmwoUgdhIAUH4OR4ea/8ZTjk3Y5XMeW1i3YGsjxWpQrJp0hIpIXowVkP//8M7y8vIy1OTIDc9/EamPIeBwDd1Rqt7GyPIHv3Tv/VdjDh8CKFfpXNe9ZGtLinmDBpqYa64pmkjT1jaccnrTLpetmYZbWLdgayOFatARMOkNEJD96B2SNGzfWyCgWFxeHhIQELF++3KiVIwL0HI9TQN8xZzp0GzP2E3h/f8PmN8t6nFDsOm1B2viAK6jSxTQ3nuZ+0i6XrpvaWFK3YGtg7mvRUjDpDBGR/OgdkPXr10/tvZ2dHXx9fdGhQwfUrl3bWPUiUtFrPA4A2NvDJbga3GqFIe3aX0brNlZeT+BLC9Jykp/otb0vVnnA45j6slatgC5d9K2ZOnM/abeEMUP6dAtmC4ThzH0tWhomnSEikhe9A7IZM2aYoh5ExdJrPE61mvBs3UF1k+Xo42u0bmPmfAJfEJAJIfBg3WkAwKlr/jh8uXLpVcnL07jxPHYs/1XcfnRh7iftljhmqGjvArl1tbRU5r4WLQ2TzhARyQsnhibZK8t4HGN1G5PLE/jCN57P13qI52s9VFufnmmP5dsbqX/Gzk7nOmgLyGbMyD/F2pjzSbsljxmSc1dLS8VWH90x6QwRkbzoHJDZ6XBTJ0kScnJyylwpoqLKElgZI5uknJ7Al3Tj6eKUq57YQ5LgElIDS/4wfH+zZmkue+MNIDjYvE/aLXXMkCV0tbREbPXRHZPOEBHJi84B2aZNm4pdd+zYMXz55ZcQ5TBXFNkuY6XpN/TmQi5P4A258ZzZRnPVp58C2QYmryyY3UIIP2Tc64zspERUcMnCyG5/FvsZYz5pl0uLpSEssaulJWCrj36YdIaISD50Dsj69u2rsezKlSuYNm0atm3bhtdeew0ff/yxUStHVJLyvlGQyxN4Y914fvCB5rJr1zTnPSuJJElwDqoKQEJK0uNiU/Eb+0m7nFos9WXJXS3ljK0++rOEuSjJePj9EsmXQWPIHjx4gBkzZmDt2rXo2rUroqKiUK9ePWPXjUgWVMkXruh+I23KJ/CmvPGsVUtzHFleHvDRRyXXxzkoGI7evsh6HI+c5CcQeXmQ7OzgoKyIlX++BrubrpD2/FuPadMAJyedq6WVXFos9WWpXS0tAVt9yobnxbowcRCR5dArIEtOTsbs2bPx5ZdfolGjRti7dy/atm1rqroRmV1xyRe0Kscn8OV542lnV3oqfkmSYO/mBhe3EAClP4mdM0dzWXg40LWr7vWSS4ulPiy5q6WlYKsPERMHEVkanQOy+fPnY968eQgICMD333+vtQsjkTUpNflCYZIE56rV4VG7Xrk9gTf3jae2IC0yErh927An7ceP57902Q9gmWOGLLmrpaXiuSNbw8RBRJZHEjpm4rCzs4OLiws6deoEe3v7Ysv9+uuvRqucpUlJSYFSqURycjIqVKhg7upQGWUlPETCji06l/ft3o/JF7RISACWLTPuNlXzsuXlIen4Id26bsrkKXDikX16dbV0CakBrzYRpq8YEVkF/ttFJB+6xgY6t5ANHjyYT1DIpjD5gnH4+pbe5VFf/37WDkK0R96z5ni1dRQqPrsm+zFDltjVksyL3S6NxxbOJf/tIrI8OgdkkZGRJqwGkfww+YJpGStIKxi/9mNUawCt/73hugZ4nAQmTSpjRY3MErtaUvliMgbjscVzyX+7iCyPQVkWiawdky+Yh7aA7I8/gCNHdN9G4fP/9KnxW+fKiunZqSRMxmA8tngu+W8XkWViQEakhdySL9jyP5adOuW/CsvM1J6pUVfaArIPPwRKGB5rVEzPTtpYUzIGc/9mWdO51Ifc/u0iIt0wICMqhjnnubLFbjb6cHIyfsuXtnnte/YEmjc3fJslMXeWTJKf7EfxOnVlBfIDCfdaYbJJxiC33yxLPpdlZalzNBLZMgZkRMUwV/IFW+xmYyzGDtJ+/z3/ZcxtFofBGFlqMgY5/mZZ6rk0BiYOIrI8DMiIimGO5Au22s3GlLQFT9evA+vXG3eb5hyXRtbBEpMxyPU3yxLPpbEwcRCR5WFARlQMcyRfsOVuNuWpZk3NAEoIYNYsw7epLSCbMAFQKg3fJtkOS03GIMffLEs9l8bCxEFElocBGVEJyjv5gi13szE3STJ+y9eiRZrLqlYFhg41fJtknSw1GYMcf7Ms9VwaExMHEVkWBmREpSjP5Au23M1GrrQFZGvXAjExhm3v9m12eSTtLDEZg1x/syzxXBobEwcRWQ4GZCRLcv6Hw5Sp7W25m40lGTJEc1lysvYWMV1pC8hmzMhvfCDbYGnJGOT8m2Vp57I88N8JIvliQEYmpes/vHJLmWwO7GZj2ZRK47d8aRvT9tpr+WPgyPpYWjIGOf9mWdq5JCLbxoCMjMqQwEqOKZPNhd1srI+xg7TiskOyy6Pls8RkDHL9zbLEc0lEtksSQtfO31SalJQUKJVKJCcno0KFCuauTrkrLrACoPmP3z+BlRACSUcP6PwU09rTvGclPETCji06l/ft3o9ZFq3EyZPAjh3G3SaDNMuU/2ArwSKSMcj9N8uSziURWR9dYwMGZEZkywGZoYGV3P8xL28MUKmwvDzgo4+Mu8333gOcnY27TTItOY8TtbTfLDmfSyKyPrrGBuyySEZh6Fw0ckyZbE6W3M2GNzrGZ2dn/C6Pc+dqLmveHOjZ0/BtlhdbvcbkfMyW9ptl7v0TEWnDgIyMwtDASq4pk83JUuaPYSIW89EWkC1cCKSkGLa906fzX7rspzzxGrMMlvKbRUQkVwzIyCgMCazknDLZ3OQ+fwwTscjPxImayx48AFavNnyb5pwvjdeYZZH7bxYRkZwxIKMyMzSwAiDblMlyI6djFkL8e6Ocv6BoAQD5XVMBmH3MiC0LDDR+UKXts2++CQQEGL7NoniNWT5+H0REumNARmVWlrlo5JoymYpn6HhBkg9jB2krV2ouUyqBCRMM2x6vMSIisiUMyMgoDA2s3EPrIv3WDd12IgTcQ+saXkkyCiZisU7aArLt24FTpwzbXnKy4YEfrzEiIrIlDMjIKAwNrBQ+fnCpVlPnlMkKH9+yVJOMgIlYbEePHvmvwjIytGdq1JW2gOzDDwF7+0L74DVGREQ2hAEZGYWhgZWlpUy2dUzEQs7OwIwZmt9nWbo8fvzxv/8vhMDTiw0Q0eAumlRP0OnzvMaIiMiSyTogmzNnDn799VdcuXIFLi4uaNWqFebNm4fQ0FBVGSEEZs2ahdWrVyMpKQktWrTAsmXLULfuv13bMjMzMXnyZHz//fdIT09Hx44dsXz5clSuXFlVJikpCWPHjsXWrVsBAH369MGXX36JihUrltvxWrKyBFZMmWw5yjJekCyXLunnZ87U/I4NCdIkSYJkZ4f9F6tg/8UqGusnvXhW8zNWdI0xsMzH80BEtkQSQtd+IeWvW7dueOWVV9C8eXPk5OTggw8+wJ9//om//voLbm5uAIB58+bh008/RWRkJGrVqoVPPvkEhw4dwtWrV+Hh4QEAeOutt7Bt2zZERkbC29sbkyZNQmJiIs6ePQv7f/rJdO/eHffv38fqf3JEjxo1ClWrVsW2bdt0rq+us3Fbs/wbt4QyB1b8x1i+Eo/s02u8oEtIDXi1iTB9xcgkiks/D0DzQYsO6eevXwfWry+5TPrdGGQnJepcx/9NSrHYa4xzreXjeSAia6RrbCDrgKyohIQE+Pn54eDBg2jXrh2EEAgMDMT48eMxdepUAPmtYf7+/pg3bx5Gjx6N5ORk+Pr6Yt26dRgwYAAA4MGDBwgKCsL27dvRtWtXREdHIywsDCdOnECLFi0AACdOnEB4eDiuXLmi1iJXEgZkmhhYWZ+shIdI2LFF5/K+3fsxA56FEkIg6egBnbsiG5p+Xghg1qx/3+empSLtxlWdP+9Wozbs/3lIV2DChPxMj3Jm7GDXUvE8EJG10jU2kHWXxaKSk5MBAF5eXgCAmJgYxMXFoUuXLqoyTk5OaN++PY4dO4bRo0fj7NmzyM7OVisTGBiIevXq4dixY+jatSuOHz8OpVKpCsYAoGXLllAqlTh27FixAVlmZiYyMzNV71NSUox6vNaAwZj1YSIW21Fe6eclSb17oxBuSDqagk8WlP5gS+HpDTtXV43lixZplg0NBV59Ve/qmQTnWsvH80BEZEEBmRACEydORJs2bVCvXj0AQFxcHADA399fray/vz/u3LmjKuPo6AhPT0+NMgWfj4uLg5+f5k2En5+fqow2c+bMwazCj3WJbAATsdgOc6WfL7jG/icd0rjGfjxcC/ce5XdHV3h6wzkoWOdr7OpV48/BZijOtZaP54GIyIICsv/+97+4ePEijhw5orGu6D/GunSTK1pGW/nStjNt2jRMnDhR9T4lJQVBQUEl7pfIGjARi20wZ/r54q6xARExGtfYkyfA4sWG70tbQDZjRn4caCqcay0fzwMRkYUEZO+88w62bt2KQ4cOqWVGDAgIAJDfwlWpUiXV8vj4eFWrWUBAALKyspCUlKTWShYfH49WrVqpyjx8+FBjvwkJCRqtb4U5OTnBycmpbAdHZKEkSYKjr5/q5ojjBeXBWN+DHKY40PUaq1jR+C1f2jo/vP46UKOG4dssjHOt5eN5ICKSeUAmhMA777yDTZs24cCBAwgJCVFbHxISgoCAAOzZsweNGzcGAGRlZeHgwYOYN28eAKBp06ZQKBTYs2cP+vfvDwCIjY3FpUuXMH/+fABAeHg4kpOTcerUKTz//PMAgJMnTyI5OVkVtBFRyRiMmYepstPJcYoDfbetT5CmSyD53Xe676ckcgh25YDngYgon6wDsrfffhsbNmzAli1b4OHhoRrPpVQq4eLiAkmSMH78eMyePRs1a9ZEzZo1MXv2bLi6umLgwIGqssOHD8ekSZPg7e0NLy8vTJ48GfXr10enTp0AAHXq1EG3bt0wcuRIrFq1CkB+2vtevXrpnGGRiKi8FZedTuRkIz3mJtJv3ShTdjrnKsF6TXHgXKWq3vsobwXBU+FA9ti+NOw7HwjJzg4Oyopw9PaFnaubzjf9+rbOyTHYNQeeByKifLIOyFasWAEA6NChg9ryNWvWYOjQoQCAKVOmID09HWPGjFFNDL17927VHGQAsGjRIjg4OKB///6qiaEjIyNVc5ABwPr16zF27FhVNsY+ffpg6dKlpj1AIiIDlUd2OvfQuki/dUPXCsE9tK5e2zeXooFs46oCjavG5q/8J7B1rFoLS/cantFPW0D2/vuAo2P+/1tjsGsIngciIgubh0zuOA8ZEZWX8pgPrrzmIStPZT0mY2VkLJhrrW3d+3i+luYY5qKsdT4/zmtIRNbMKuchIyImz6B85ZGdzhqnOChrmnVtAdmCBcDTp/rVw87VDQpPLxy+DBy+XFlj/aQXz6r+35rn8+O8hkREDMiIZM9USRvIspVXdjprm+LAFIHspEmay+LigJUrS9q0BOegqgAkZCc91li/YFNTAP/MtXYzGNIeqcTWOUt9UGONQT8Rkb7YZdGI2GWRjK24pA0ANG9UDEjaQJZJCIEH677S+3OBg0YaLSW+pd4YP9iwRu8kEoED3zDa/osGVUII5D17hqzH8chJfgKRl1couYgf7Fxdi50nM+9ZGga1Ow/3pzcs/kFN/oOnBKsI+omICrDLIpGFK4+kDWSZzJ2dzlKvMzmkWdds5ZIwc6YbXNxCVHUsbV9CCGTcu43spESsvOEKoIHaev+KVzFyRLRFPajhvIZExePfg/VjQEYkU1nxD8s01oWsG7PT6c/cgWxx1IO0/H0dOgTs26dZtnAwVpyHT9zwyeeAwvMunIOCVfU3VkKS8sCbT7JlHKpgexiQEcmQEAKJR/fr/gEDkzaQ5bLWlPSmZimBbLt2+a/CMjOBT/6XVmIwVlh20mM4evvC3s0NgPaAbPp0wEIa0YhsgqnnlyR5YkBGJEPZj+KRl6pH2rYyJG0gy8TsdIax5EDWyQmY0PeURkBZkABEm6zH8arukNp89JHmsl69gGbNylRVIjIAhyrYLgZkRDL09MolvT9j7LEuJG/MTmcYSw9ktWXXLJwiv0BBkJaT/ETvffz2W/6rKEvq8khkico6LQdZLgZkRDKUee+u3p8pj7EuJC/WlpK+PFhyIKtPUpLCQVrgoEaQJAlXrwLff2/4/rUFZAzSiIynPOaXJHliQEYkM4ZkggPApA02itnp9GepgWxZk5KEhmpLuw/MmmV4nbQFZBMnApz5hUh/5TW/JMkPAzIimTHkpguArMa6kPnokjJdboGGOVhqIGvspCSSZPyWr4ULNZfVrQv83/8Zvk0iayeHaTnIfBiQEcmQc5Vg3RMPALB395DdWBeSB6ZP1o2lnIPySkqiLSBbuxaIiTFoc7h8Of+ly36IbJFcp+Wg8sGAjEiG9LrpAuDZOoI/yqSB6ZOtjzmTkgwZornsyRNg8WLDt6ktIJsxI/9yBSyn5bKsbOU4qWSWMi0HGR8DMiIZ0uemy7laTTj6+ZdDrciSMH2ydZJbUpKKFY3b5VEIgelT0pD1OAE5yU8g8vIg2dlh0CvpCOtQ3WpadNlyTdpY8rQcVDaSELqOHqTSpKSkQKlUIjk5GRU4opnKSOTlIen4Id1uuti6QUVkJTxEwo4tOpf37d6P6ZPLqDxbOfJv6BMsKilJaUGaEAIZ926XOPG1wtMbzkHBkCQJCgXwwQfGrWN5KK7lGgB/222cEAJJRw/o3ALOB2nyp2tswIDMiBiQkbFZ4k0XyUPikX16dX1xCakBrzYRpq+YFZFTK4eldnk7fRr4/XfdgrEChYMybeQ8Lo033FQaPoy1LgzIzIABGZmapd50Ufl7sGGN3oPDAwe+YcIaWRe2chhX4Rbd3DwJi7c0KbG8W43asHdz03n7H3wAKBRlqqJRsOXaNKzt30ZDHsZa2zmwFrrGBhxDRmRB+GNLujA0ffLjw3vhUbsex6+UguPzjK/whLj2dkJtYusCCzY1Vf1/1uN4uLiF6Lz9Tz/VXNazJ9C8uUHVNRgn/jUOObVOm4Iu03JY+zmwNQzIiIgsTGlPQg2dyy7j9i1kxNxky04psh/F69TlDMgPytxrhbGVoxS6TIhbOEjLb9ENwfLlQHy8Yfv8/ff8V1Gm7PLIiX/Lzhazx2oEYzZ4DqwdAzIiIpkz5EmoXumT/90RALbslIatHMZVlglxx4zRvD4fPgRWrDC8PsaeKLsAJ/4tO7ZO8xxYKwZkREQyZuiTUH3nsivK1lp29LnpZSuHcRl7Qlx/f+MHVdo+O3Ys4OWl+zbKa+Jfaw7g2DrNc2CtGJAREclUWZ6E6jOXnVZW3rJj6PgLtnKYRnlMiGvsIG3JEs1ldeoAAwYU/xlTHKctjSVi6zTPgbViQEZENsdSbo7L8iS01AmES2PFLTtlGX9RXq0ctsZcE+JqC8iOHgX27DFse9HRJQd+xj5OWxtLxNZpngNrxYCMiKyepT5BLuuTUMnODp6t2sO9VhhSr17Wu7XMGlt2jDH+oiytHNZ2Po1FnxZdl+q1oPDxNVldWrfOfxWWmQnMmWP4NgsCMiH8kHGvM7KTEjGh71mUFCOVdpy2NpaIrdM8B9aMARmVGf/QSc4s+QmyMZ6EFk6f/OCf+Wx0ZY0tO8YYf6FvK4eTXyUkHtlXLg8DLPX3uNQW3aJzu5XzMTo5GafLoyRJcA6qCkDCoi1NNda/1PoGQvySdTpOc40lMtc1xtZpngNrxoCM9GaprQ1keyz5CbIpnoSWxzgduTPG+At9WnPs3T3w5MQhkz0MsKbf46IturpOiGtO2gKyBQuAp0+L/0x+UBYMR29fZD2OR07yE4i8PEh2dtj21/NwfOgHu5uukPbkH6ezM/Dee5rbKa+xRHK6xvgbxnNgrRiQkV4subWBbI8lZ6MyxZNQc43TkRNjtTrq0ppj7+6B3NSnqm0V3TZQtocB1vh7rMuEuHI3aZLmsnv3gK+//ve9JEmwd3NTTW5d0nFmZGgP/EbVMv1YIrldY/wN4zmwVgzISGeW3NpAZWOJN0WA5WejMvaTUDmN0zEHY7Y6ltaa4+RXKb9lTAeGPAywld9jS6yzNkFBmkGVEMCsWfn/b0hq+89/aqCxfEyPKLg45Wr/jJ5jieR4jdn6bxjAc2CtGJCRziy5tYH0I6cuKmVh6dmojP0kVO7jdEzN2K2OJbXmJB7ZZ9KHAVkJD/l7bOEkyfBxaZIkQbKzg8jLU1u+fHsjjbLhtR+gVZ1YvccSyfHffFv/DQN4DqwVAzLSmaW3NpBuzNVFxditcNaQjcoUT0ItcZyOMZly/EXhc2bshwHaHpLoUTH+HlsQbQHZ7t3AsWPqyxyUFZGdlFjq9o5fCcTxK4FQeHrB5VrJ+ykghEBK1Fmd6gugXK8xW/8NA3gOSiOnf8d1xYCMdGbprQ1UuvLsomLqVjhryEZlqieh1jBOx1DlMf7C2A8DintIokeF+Hts4bp0yX8Vlhjjhk8mlh6QFXD0Vg+WNLtQCrz/djxSr15Cxu1b+l1n5XyNyfE3rLzrIMdzYC7W0KuHARnpxBpaG6h05dVFpbxa4awhG1V5PAm1pb/R8hh/YcyHAaU+JNERf4+tj2dVX/xvkub8ggs2aabTV3h6w87VtdhtCSGQce82po1OBFARQBPVuhFd/oTSLavU+pjzGjPHPuUWBNjq37bcEs8YigEZ6cQaWhuodOXRLbU8W+GsJRuVOZ+EWttNfHmNvzDWwwB9HpKUuAv+Hlud4q7lSS+eLSigupZXHGiM7Gzt339BMFZc98f/t7u+xrKODe+iUbUE9frY0DVmLUGApZNj4hlDMSAjnVlDawOVrDy6pZbnQHFDWkMsIQAxZf3k9tTXFMqj1dFYDwP0ekhSAlv9PbaEv+ey0PVa/qB1/jkofD5u3wYiI4G8Z2k6jUUrbO+FKth7oYraMmUlJWYMNMZRyZs1BQGWTo6JZwzFgIx0Zi2tDaRdeXVLLc/kMLq2hjg9FwTk5SH2+0irDEB0ZUtPfU3d6misrpF6PSQpQfqdGCRCWP01bQsPFIoq6Vou6XwEhtbFjBl+SDp6SvVve14esGiLZpdHXeS4VVIbl1ZQj+nTAQv/uVBjTUGApbOmZHMMyEhnnPvCupVXt9TyTg5T0hNkp6BgiKxMZP59z+oDEG2K3rjZ8lNfYx+LMbpGGvKQpFi5OVZ/TZf4QOHWDas+9sJUf9M6PmBJvx2j+qydHf7t8ljIwk1NIFD830jBGLXctFRkPU5ATvITiLw8SHZ2mDaiIhy9fWHn6qaq2zvvAN7exjzq8mNNQYCls6ZkcwzISGec+8L6mbJbqhACWQkPzZIcRtsTZABIOnoAGX/fK6hg0QoDsK4ApKSn5U5+laz2qW9p14+purWVtWukIQ9JSmSF13QBXZOfpN+8hryMdHhFdIWdFQdl+j5gKc3EF89pLPvrrhd2nA2BwtMbzpWraB2HJvLykJ2UiOykRDh4esElqCokScKXX2ruo0cP4PnndaqOWVlTEGDJrC3ZHAMy0gvnvrBupuqWqvakVk+mGCguSZLBE+vK9ce8NLo8LdeZzJ/6ltZtzcHbFzmPE8qlW1tZu0bq9ZBED5YWVJdGn25kmX/fw8NfNsCrXSc4+vmXy99zsVMamOj3xFjJYEoSViURjVu6weuFxnjyz2/Ls0wHrNjeUGv5nKREPE1KhKKiFxx91FvMAGD79vxXYT4+wH//a8qj0I+1BQGWzNqSzTEgI71x7gvrZYpuqRpPavVhwuQw+iZLeHx4L0RGhkWOSdH1abkeG5TtU19dAk97dw/kpj41SzdVfa8VvR6S6FcRWQfVuioIvh8f3qvX5/LSn+HRrq1wqVYzv6XQyN91sQ8FgoLh5F8JGQ8fIPPeXZP9nhgrGUxpKjRsipzHCarfFlenHK1dHhdvaYzcvPxznP0kEdlPEvNb1oKCSzzeR4+0T2D9/vuAo6NRDkEv1hYEWDprSjbHgIzKjD801sMU3VLL9KTWhMlh9E2WkJf6VPX/ljbGzBRPy+X41FfXwDO34Lu0gG6q+jwk0YuMg2pdlaXlvUBB4G7M77rkhwI3kB6jHmCb4vfEWMlgSlLwUC7p6P5Sg7/xfc9rLDtz3R/H7qHUoEyb2bM1l735JhAQoNdmDGJNQYCls6ZkcwzIiEiNsbulluVJramSwxglWYIMb96LY4qn5XJ86mvMwFMuXfpKfUhSBnIMqnVVppb3Ioz5XRs8kbcRf0+MmgymGIUfyhka/DWr+RDNau6Gb/d+qnOfkAAsW2ZYnVau1FzWuTPQurVh2yuONQUBls6aks0xICMiDcbslmroP9amTA5j7GQJcrl5L47Rn5bL9KmvUQNPGXXpK+khicjNMfx4LTAQK2DUVl8jftfGqFdZf0+MngymCKfAIFXAWObgr8i59/XV7KKYmwt8/LFhm9+zJ/9VmLd3/rg0Qy9/awoCLJ01JZtjQFbE8uXL8dlnnyE2NhZ169bF4sWL0bZtW3NXi8isyvtJrU+3vnD0Ne3YLKMmS5DRzXtRJnlaLtOnvkYNPGXWpa+4hySJR/YZfh0LgexHCbJ9kFASowbfRvyujVIvI/yeOFcJNs3YQ+SPGyv4bS5z8KfDube31z6ObMMG4JpuSSLVPH4MzJqlufzddwE3t9I/b01BgDWwlmRzDMgK+eGHHzB+/HgsX74crVu3xqpVq9C9e3f89ddfqFKlSukbICI1hg6AdvLzN2Gt8hk1WYLMbt4LM8XTcjk+9TVF4CnnLn0FdSrTdSzjBwmlMXarr7G+a6PUywi/J6ZKBqPtb7+sD7cMPfcDB2oui4kB1q41qBr47DPNZa+/DtSoobncWoIAa2ENyeYYkBWycOFCDB8+HCNGjAAALF68GLt27cKKFSswZ84cM9eOyDLJdQC0sZMlyPnm3aAbJgt76muKwFOO4+SKKtN1LOMHCSUxRfBtjO/amPUq6++JwsdP/5a6gvJ6/u2XNfgz5t9ZSIhma1p6OjBvnmHb++47zWXNmgG9ellHEGCtLPF7YED2j6ysLJw9exbvvfee2vIuXbrg2LFjWj+TmZmJzMxM1fuUlBST1pHIEsl1ALSxkyXI+eZd3xumiuHtkPkw1uKe+hq7G6ocx8kVpXEd60nODxKKY/Tg20jftTHrZZTfEwOms/Dp1hdp1/7S62+/TA8FyuHvzMVFM0gTAvjqK+DBA/23d+ZM/quoDz+UYG9vUBWJGJAVePToEXJzc+Hvr95Vyt/fH3FxcVo/M2fOHMzS1hGZiFTkPAC6pG4nkrMz8tJSZdeyZwh9vwPXGqFwq1kbgGU99TV2N1Q5jpPTpvB1nLBzi1434nJ+kFASowbfRvyujVIvI/yelKW7eEGXcV3/9sv0UMBMf2eSBIwapbn85Elgxw7Dtqkt8cjEiUCFCoZtj2wLA7Iiiv74lPSDNG3aNEycOFH1PiUlBUFBQSatH5GlkfsA6OK6nWQlPETCji26bUTmN+9l+Q4s6WbdmN1Q5ThOriQF17FLSHVZdhE2NmMG38b8ro1SLyP9npS1u7g+f/uFHwo8vXIJGbd126/c/s5atMh/FRYfDyxfbtj2Fi7UXDZwIFCrlmHbI+vFgOwfPj4+sLe312gNi4+P12g1K+Dk5AQnJ6fyqB6RRbOkAdAFdZBzy54hLOk7MJSugae9u0f+5NAyezhgDHLtImxsZQ6+TfRdG+OhgLF+T8r7Wih4KODt+wJE6w5aJ8f+p6BF/Z35+Wl2eczJAT75xLDtbdiguaxlS6BbN8O2R9ZBEsLEU7lbkBYtWqBp06ZYXuhRSFhYGPr27atTUo+UlBQolUokJyejAtuoiUpkCV3hRF4eko4f0q1Vyc7OfBU1kCV8B4YQ/6RzLy7wdPD2Qc7jR1YZmAohkHT0gM4PEuQ8oXlpdPn7dK5WE+616iDtWnS5fdcl1qs4Jvg9Mfe1UNrfoSX/nRXn8GFg717jbEupBN5+G3B0NM72yDx0jQ0YkBXyww8/YNCgQVi5ciXCw8OxevVqfPXVV7h8+TKCg4NL/TwDMiLrY4s3FdamtMDT2gJTa3+QUJi+f5/l9V2XVC8n/0rIiHuAzHt3TP57Iqdrwdr+znR15w6wZo1xtlWpEvDKK/nBGlkGBmQGWr58OebPn4/Y2FjUq1cPixYtQrt27XT6LAMyIutnqzcVZFls9UGCXP8+i6tXedTXVq8FOXv2DFiwAMjNNc72Bg8GqlUzzrbIuBiQmQEDMiIikiO5BipU/ngtyJMQwM8/A5cvl207kgQ0bgw0agQEBeW/J/NhQGYGDMiIiIiIyFiiooDNm8u+nRo18gO10FDAgSn9yo2usQG/EiIiIiIiGWrUKP9VWEoK8OOPwP37um/nxo38V2H+/vlBWv36gJtbWWtKZcEWMiNiCxkRERERlbe8PODmzfwWtbJ0e3R1zQ8AGzcGfOU9m4tFYJdFM2BARkRERERy8fAhcP58fqCWkWH4durXzw/UQkIAC0/OWq4YkJkBAzIiIiIikrPUVODixfxALSHB8O0EB+e3pIWFcb604jAgMwMGZERERERkabKzgStX8lvSbt40fDteXvktaQ0bcr40gAGZWTAgIyIiIiJrIARw9+6/XR4N5eDwbyr+wEDbSsXPgMwMGJARERERkTV7/Bi4cCE/UHv61PDthIbmB2o1awL29sarn5wwIDMDBmREREREZGvS04FLl/Jb0v7+2/DtBAbmt6TVrw+4uBirdubDgMwMGJAREREREQG5uflzn50/nz8+zVDu7v92efT2Nlr1ygUDMjNgQEZEREREpJ0QQGxsfkva+fP5yUQM1bBhfqAWHCzfcWkMyMyAARkRERERkX5SUvLHpUVF5Y9RM1S1akDLlkCtWkarWpkwIDMDBmRERERERGWXlQVER+e3pN2+rd9nO3UC2rQxSbX0omts4FCOdSIiIiIiIiqVo2N+t8SGDf9dJgQQE5PfknbxYvGfLUtiEXNgQEZERERERLInSfndEqtVA1566d/lCQn5QVpUFFC9OhARYa4aGoYBGRERERERWSxfX6Bz5/yXJbIzdwWIiIiIiIhsFQMyIiIiIiIiM2FARkREREREZCYMyIiIiIiIiMyEARkREREREZGZMCAjIiIiIiIyEwZkREREREREZsKAjIiIiIiIyEwYkBEREREREZkJAzIiIiIiIiIzYUBGRERERERkJgzIiIiIiIiIzIQBGRERERERkZkwICMiIiIiIjITB3NXwJoIIQAAKSkpZq4JERERERGZU0FMUBAjFIcBmRE9ffoUABAUFGTmmhARERERkRw8ffoUSqWy2PWSKC1kI53l5eXhwYMH8PDwgCRJZd5eSkoKgoKCcO/ePVSoUMEINSQyDK9FkhNejyQXvBZJLngtypMQAk+fPkVgYCDs7IofKcYWMiOys7ND5cqVjb7dChUq8I+LZIHXIskJr0eSC16LJBe8FuWnpJaxAkzqQUREREREZCYMyIiIiIiIiMyEAZmMOTk5YcaMGXBycjJ3VcjG8VokOeH1SHLBa5HkgteiZWNSDyIiIiIiIjNhCxkREREREZGZMCAjIiIiIiIyEwZkREREREREZsKAjIiIiIiIyEwYkMnU8uXLERISAmdnZzRt2hSHDx82d5XIBh06dAi9e/dGYGAgJEnC5s2bzV0lslFz5sxB8+bN4eHhAT8/P/Tr1w9Xr141d7XIRq1YsQINGjRQTcIbHh6OHTt2mLtaRJgzZw4kScL48ePNXRXSAwMyGfrhhx8wfvx4fPDBBzh//jzatm2L7t274+7du+auGtmYtLQ0NGzYEEuXLjV3VcjGHTx4EG+//TZOnDiBPXv2ICcnB126dEFaWpq5q0Y2qHLlypg7dy7OnDmDM2fO4IUXXkDfvn1x+fJlc1eNbNjp06exevVqNGjQwNxVIT0x7b0MtWjRAk2aNMGKFStUy+rUqYN+/fphzpw5ZqwZ2TJJkrBp0yb069fP3FUhQkJCAvz8/HDw4EG0a9fO3NUhgpeXFz777DMMHz7c3FUhG5SamoomTZpg+fLl+OSTT9CoUSMsXrzY3NUiHbGFTGaysrJw9uxZdOnSRW15ly5dcOzYMTPViohIXpKTkwHk3wQTmVNubi42btyItLQ0hIeHm7s6ZKPefvtt9OzZE506dTJ3VcgADuauAKl79OgRcnNz4e/vr7bc398fcXFxZqoVEZF8CCEwceJEtGnTBvXq1TN3dchG/fnnnwgPD0dGRgbc3d2xadMmhIWFmbtaZIM2btyIc+fO4fTp0+auChmIAZlMSZKk9l4IobGMiMgW/fe//8XFixdx5MgRc1eFbFhoaCiioqLw5MkT/PLLLxgyZAgOHjzIoIzK1b179zBu3Djs3r0bzs7O5q4OGYgBmcz4+PjA3t5eozUsPj5eo9WMiMjWvPPOO9i6dSsOHTqEypUrm7s6ZMMcHR1Ro0YNAECzZs1w+vRpfPHFF1i1apWZa0a25OzZs4iPj0fTpk1Vy3Jzc3Ho0CEsXboUmZmZsLe3N2MNSRccQyYzjo6OaNq0Kfbs2aO2fM+ePWjVqpWZakVEZF5CCPz3v//Fr7/+in379iEkJMTcVSJSI4RAZmamuatBNqZjx474888/ERUVpXo1a9YMr732GqKiohiMWQi2kMnQxIkTMWjQIDRr1gzh4eFYvXo17t69izfffNPcVSMbk5qaihs3bqjex8TEICoqCl5eXqhSpYoZa0a25u2338aGDRuwZcsWeHh4qHoRKJVKuLi4mLl2ZGvef/99dO/eHUFBQXj69Ck2btyIAwcOYOfOneauGtkYDw8PjbG0bm5u8Pb25hhbC8KATIYGDBiAx48f46OPPkJsbCzq1auH7du3Izg42NxVIxtz5swZREREqN5PnDgRADBkyBBERkaaqVZkiwqmAenQoYPa8jVr1mDo0KHlXyGyaQ8fPsSgQYMQGxsLpVKJBg0aYOfOnejcubO5q0ZEFojzkBEREREREZkJx5ARERERERGZCQMyIiIiIiIiM2FARkREREREZCYMyIiIiIiIiMyEARkREREREZGZMCAjIiIiIiIyEwZkREREREREZsKAjIiIiIiIyEwYkBERWTFJkrB582ZzV8PizZw5E40aNTJ3NSzCoEGDMHv2bIM/X7VqVSxevFj13pjX8NKlS9GnTx+jbIuIyFgYkBERWZihQ4dCkiRIkgSFQgF/f3907twZ33zzDfLy8tTKxsbGonv37jpt15KCt6FDh6Jfv35G294vv/yCDh06QKlUwt3dHQ0aNMBHH32ExMREAMDkyZOxd+9ek+w/KysL8+fPR8OGDeHq6gofHx+0bt0aa9asQXZ2tlH2AZRPUHnx4kX8/vvveOedd1TLOnToAEmSMHfuXI3yPXr0gCRJmDlzpmrZ6dOnMWrUKJPUb+TIkTh9+jSOHDliku0TERmCARkRkQXq1q0bYmNjcfv2bezYsQMREREYN24cevXqhZycHFW5gIAAODk5mbGm8vfBBx9gwIABaN68OXbs2IFLly5hwYIFuHDhAtatWwcAcHd3h7e3t9H3nZWVha5du2Lu3LkYNWoUjh07hlOnTuHtt9/Gl19+icuXLxt9n2VVUpC4dOlS/N///R88PDzUlgcFBWHNmjVqyx48eIB9+/ahUqVKast9fX3h6upqvAoX4uTkhIEDB+LLL780yfaJiAwiiIjIogwZMkT07dtXY/nevXsFAPHVV1+plgEQmzZtEkIIkZmZKd5++20REBAgnJycRHBwsJg9e7YQQojg4GABQPUKDg4WQghx48YN0adPH+Hn5yfc3NxEs2bNxJ49e9T2GxwcLD799FPxxhtvCHd3dxEUFCRWrVqlVubevXtiwIABwtPTU7i6uoqmTZuKEydOqNZv3bpVNGnSRDg5OYmQkBAxc+ZMkZ2drfX4Z8yYoVZXAGL//v1CCCEuXrwoIiIihLOzs/Dy8hIjR44UT58+LfZcnjx5UgAQixcv1ro+KSlJtc+GDRuWuP+IiAjx9ttvq33+0aNHwtHRUezdu1fr9ufNmyfs7OzEuXPnNNZlZWWJ1NRUIYQQeXl5Yt68eSIkJEQ4OzuLBg0aiJ9++klVdv/+/QKA+OOPP0TTpk2Fi4uLCA8PF1euXBFCCLFmzRqNOq9Zs0YIIcSTJ0/EyJEjha+vr/Dw8BAREREiKipK7Xw3bNhQfP311yIkJERIkiTy8vI06pubmysqVqwofvvtN7Xl7du3F2+99Zbw9vYWR44cUS3/9NNPRe/evUXDhg3FjBkzVMuDg4PFokWLVO8LX8NCCHH//n3Rv39/UbFiReHl5SX69OkjYmJi1M5F8+bNhaurq1AqlaJVq1bi9u3bqvUHDhwQjo6O4tmzZ1q+ESKi8scWMiIiK/HCCy+gYcOG+PXXX7WuX7JkCbZu3Yoff/wRV69exXfffYeqVasCyO8mBgBr1qxBbGys6n1qaip69OiBP/74A+fPn0fXrl3Ru3dv3L17V23bCxYsQLNmzXD+/HmMGTMGb731Fq5cuaLaRvv27fHgwQNs3boVFy5cwJQpU1TdK3ft2oXXX38dY8eOxV9//YVVq1YhMjISn376qdbjmDx5Mvr3769qJYyNjUWrVq3w7NkzdOvWDZ6enjh9+jR++ukn/PHHH/jvf/9b7Dlbv3493N3dMWbMGK3rK1asqPP+R4wYgQ0bNiAzM1Nt+4GBgYiIiCh2/506dULjxo011ikUCri5uQEA/ve//2HNmjVYsWIFLl++jAkTJuD111/HwYMH1T7zwQcfYMGCBThz5gwcHBwwbNgwAMCAAQMwadIk1K1bV1XnAQMGQAiBnj17Ii4uDtu3b8fZs2fRpEkTdOzYUdVdEwBu3LiBH3/8Eb/88guioqK0HsvFixfx5MkTNGvWTGOdo6MjXnvtNbVWssjISFX9dPXs2TNERETA3d0dhw4dwpEjR+Du7o5u3bohKysLOTk56NevH9q3b4+LFy/i+PHjGDVqFCRJUm2jWbNmyM7OxqlTp/TaNxGRyZg7IiQiIv0U10ImhBADBgwQderUUb1HodaFd955R7zwwgtaWzeKli1JWFiY+PLLL1Xvg4ODxeuvv656n5eXJ/z8/MSKFSuEEEKsWrVKeHh4iMePH2vdXtu2bVUtdQXWrVsnKlWqVGwdtJ2D1atXC09PT1WrkhBC/P7778LOzk7ExcVp3U737t1FgwYNit1PgcItZMXtPyMjQ3h5eYkffvhBtaxRo0Zi5syZxW7XxcVFjB07tsR9p6amCmdnZ3Hs2DG15cOHDxevvvqqEEK9hazA77//LgCI9PR0rccgRH6raoUKFURGRoba8urVq6taOWfMmCEUCoWIj48vsZ6bNm0S9vb2GtdX+/btxbhx48SFCxeEh4eHSE1NFQcPHhR+fn4iKytLrxayr7/+WoSGhqrtIzMzU7i4uIhdu3aJx48fCwDiwIEDJdbV09NTREZGlliGiKi8OJgzGCQiIuMSQqi1BhQ2dOhQdO7cGaGhoejWrRt69eqFLl26lLi9tLQ0zJo1C7/99hsePHiAnJwcpKena7SQNWjQQPX/kiQhICAA8fHxAICoqCg0btwYXl5eWvdx9uxZnD59Wq1FLDc3FxkZGXj27JnO44mio6PRsGFDVasSALRu3Rp5eXm4evUq/P39NT5T0vnSl5OTE15//XV888036N+/P6KionDhwoUSE6Xosv+//voLGRkZ6Ny5s9ryrKwsjZa1wt9Dwdis+Ph4VKlSReu2z549i9TUVI3xcenp6bh586bqfXBwMHx9fUusZ3p6OpycnIo9ngYNGqBmzZr4+eefsX//fgwaNAgKhaLEbWqr740bNzTGqGVkZODmzZvo0qULhg4diq5du6Jz587o1KkT+vfvrzFOzcXFBc+ePdNr30REpsKAjIjIikRHRyMkJETruiZNmiAmJgY7duzAH3/8gf79+6NTp074+eefi93eu+++i127duHzzz9HjRo14OLigv/85z/IyspSK1f0xlqSJFWXRBcXlxLrnJeXh1mzZuGll17SWOfs7FziZwsrKbgpbnmtWrVw5MgRZGdn6x0caDNixAg0atQI9+/fxzfffIOOHTsiODi42PK1atVCdHR0idssOI+///47nnvuObV1RRO2FD6GgmMumnmz6LYrVaqEAwcOaKwr3F2zcJBbHB8fHzx79gxZWVlwdHTUWmbYsGFYtmwZ/vrrL4O6DObl5aFp06ZYv369xrqCgHHNmjUYO3Ysdu7ciR9++AH/+9//sGfPHrRs2VJVNjExsdQAk4iovHAMGRGRldi3bx/+/PNPvPzyy8WWqVChAgYMGICvvvoKP/zwA3755RfVWCGFQoHc3Fy18ocPH8bQoUPx4osvon79+ggICMDt27f1qleDBg0QFRWlNiapsCZNmuDq1auoUaOGxsvOTvs/U46Ojhp1DQsLQ1RUFNLS0lTLjh49Cjs7O9SqVUvrdgYOHIjU1FQsX75c6/onT57ovH8AqF+/Ppo1a4avvvoKGzZsKHWM1MCBA1Xj84rKyclBWloawsLC4OTkhLt372qcn6CgoBK3X1qdmzRpgri4ODg4OGhs28fHR+dtA1Cl1P/rr7+KLTNw4ED8+eefqFevHsLCwvTafkF9r1+/Dj8/P436KpVKVbnGjRtj2rRpOHbsGOrVq4cNGzao1t28eRMZGRlax+0REZkDAzIiIguUmZmJuLg4/P333zh37hxmz56Nvn37olevXhg8eLDWzyxatAgbN27ElStXcO3aNfz0008ICAhQtYRUrVoVe/fuRVxcHJKSkgAANWrUwK+//qrqfjdw4MASW1y0efXVVxEQEIB+/frh6NGjuHXrFn755RccP34cADB9+nR8++23mDlzJi5fvozo6GhVy0ZxqlatiosXL+Lq1at49OgRsrOz8dprr8HZ2RlDhgzBpUuXsH//frzzzjsYNGiQ1u6KANCiRQtMmTIFkyZNwpQpU3D8+HHcuXMHe/fuxf/93/9h7dq1Ou+/wIgRIzB37lzk5ubixRdfLPHcjB8/Hq1bt0bHjh2xbNkyXLhwAbdu3cKPP/6IFi1a4Pr16/Dw8MDkyZMxYcIErF27Fjdv3sT58+exbNmyYutXXJ1jYmIQFRWFR48eITMzE506dUJ4eDj69euHXbt24fbt2zh27Bj+97//4cyZMzpvG8hvoWrSpEmJc3x5enoiNjZWbU43fbz22mvw8fFB3759cfjwYcTExODgwYMYN24c7t+/j5iYGEybNk31Pe7evRvXrl1DnTp1VNs4fPgwqlWrhurVqxtUByIiY2NARkRkgXbu3IlKlSqhatWq6NatG/bv348lS5Zgy5YtsLe31/oZd3d3zJs3D82aNUPz5s1x+/ZtbN++XdUKtWDBAuzZswdBQUGq1oNFixbB09MTrVq1Qu/evdG1a1c0adJEr7o6Ojpi9+7d8PPzQ48ePVC/fn3MnTtXVc+uXbvit99+w549e9C8eXO0bNkSCxcuLLGr38iRIxEaGopmzZrB19cXR48ehaurK3bt2oXExEQ0b94c//nPf9CxY0csXbq0xPrNmzcPGzZswMmTJ9G1a1fUrVsXEydORIMGDTBkyBCd91/g1VdfhYODAwYOHFhql0snJyfs2bMHU6ZMwapVq9CyZUs0b94cS5YswdixY1GvXj0AwMcff4zp06djzpw5qFOnDrp27Ypt27YV2z1Vm5dffhndunVDREQEfH198f3330OSJGzfvh3t2rXDsGHDUKtWLbzyyiu4fft2sUFsSUaNGqW1O2FhFStW1KkLpDaurq44dOgQqlSpgpdeegl16tTBsGHDkJ6ejgoVKsDV1RVXrlzByy+/jFq1amHUqFH473//i9GjR6u28f3332PkyJEG7Z+IyBQkIYQwdyWIiIisxb1791C1atX/384d4lYIBWEYndWAwoMkbIr1XIVgEXgsigWAYQEkmIqqpjVNXjJ96Tkr+O2XezOxruuv4/Xd3fcddV3HNE3RdV32nG+2bYthGGLf9y9fHAEyOeoBAC/wPE+c5xnjOEbbtv8uxiI+j7CUUuK6ruwpPzqOI0opYgz4U7yQAcALLMsSfd9HVVUxz3M0TZM9CYA3IMgAAACSOOoBAACQRJABAAAkEWQAAABJBBkAAEASQQYAAJBEkAEAACQRZAAAAEkEGQAAQJIP2szrma6o9o8AAAAASUVORK5CYII=\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plotting the true data and the prediction\n", "fig, ax = plt.subplots(1, 1, figsize=(10, 5))\n", "ax.scatter(counts_df['dist_to_center'].values, counts_df['checkouts'].values, label='Data', s=70, c='#e4a199')\n", "ax.plot(counts_df['dist_to_center'].values, y_pred, c='blue', alpha=0.5, linewidth=2, label='Prediction')\n", "ax.set_xlabel('Distance to City Center (Miles)')\n", "ax.set_ylabel('Number of Checkouts')\n", "ax.set_title('Distance to City Center vs Checkouts');\n", "ax.legend();\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ⏸ Based on our \"linear\" model, what would most likely be the number of checkouts for a distance of 2.5 miles from the city center?\n", "#### A. 45000\n", "#### B. 12530\n", "#### C. 1450\n", "#### D. 650" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "### edTest(test_chow6) ###\n", "# Submit an answer choice as a string below (eg. if you choose option A, put 'A')\n", "answer6 = 'C'\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 4 }