{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Основы анализа данных в Python\n", "\n", "*Тамбовцева Алла, НИУ ВШЭ*\n", "\n", "## Линейная регрессия с `statsmodels` и `seaborn`\n", "\n", "### Подготовка и описание данных" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Установим библиотеку `seaborn` для более продвинутой и при этом более удобной (по сравнению с `matplotlib`) визуализации данных:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!pip install seaborn" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Оператор `!` дает понять Jupyter, что выше мы написали не код на языке Python, а команду для установки, которая обычно пишется в консоли.\n", "\n", "*Примечание.* Если некоторые строки кода ниже, в частности, `set_theme()` не работают, это, скорее всего, из-за того, что на компьютере уже установлена более старая версия `seaborn`, в которой некоторые функции отсутствовали или выглядели иначе. Поэтому при запуске `!pip install seaborn` новая версия не была установлена. Чтобы это исправить, можно установить новую версию явно, написав `!pip install seaborn==0.12.0`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Импортируем эту библиотеку с сокращенным названием `sns`, так часто делают в официальных тьюториалах:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import seaborn as sns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Заодно импортируем остальные библиотеки и модули для работы: `pandas` для работы с датафреймом и `pyplot` для базовых графиков:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "from matplotlib import pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Загрузим данные из CSV-файла по ссылке (можно сохранить файл и загрузить его локально, просто по названию):" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(\"https://vincentarelbundock.github.io/Rdatasets/csv/carData/Salaries.csv\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Посмотрим на первые несколько строк датафрейма:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Unnamed: 0rankdisciplineyrs.since.phdyrs.servicesexsalary
01ProfB1918Male139750
12ProfB2016Male173200
23AsstProfB43Male79750
34ProfB4539Male115000
45ProfB4041Male141500
\n", "
" ], "text/plain": [ " Unnamed: 0 rank discipline yrs.since.phd yrs.service sex salary\n", "0 1 Prof B 19 18 Male 139750\n", "1 2 Prof B 20 16 Male 173200\n", "2 3 AsstProf B 4 3 Male 79750\n", "3 4 Prof B 45 39 Male 115000\n", "4 5 Prof B 40 41 Male 141500" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В этом файле сохранены данные по сотрудникам университета в США, а именно следующие их характеристики:\n", "\n", "* `rank`: должность;\n", "* `discipline`: тип преподаваемой дисциплины (`A` – теоретическая, `B` – практическая);\n", "* `yrs.since.phd`: число лет с момента получения степени PhD;\n", "* `yrs.service`: число лет опыта работы;\n", "* `sex`: пол;\n", "* `salary`: заработная плата за 9 месяцев, в долларах.\n", "\n", "Для удобства дальнейшей работы давайте переименуем столбцы с длинными названиями: вместо `yrs.since.phd` запишем просто `phd`, а вместо `yrs.service` — `service`. Для этого нам понадобится метод `.rename()` для датафреймов:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "df.rename(columns = {\"yrs.since.phd\" : \"phd\", \"yrs.service\" : \"service\"}, inplace = True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Метод `.rename()` по умолчанию работает не со столбцами, а со строками, поэтому, чтобы переименование применялось именно к столбцам, мы обязательно указываем название аргумента `columns`, внутри которого помещаем словарь с парами *старое название-новое название*. Метод `.rename()`, как и ряд других методов на датафреймах, возвращает измененную копию таблицы, но не вносит изменения в сам датафрейм. Поэтому, чтобы сохранить изменения, мы дописываем аргумент `inplace = True`, который заменяет названия прямо в исходном датафрейме. В общем, строка выше эквивалентна обычному присваиванию через `=` (только более элегантна):\n", "\n", " df = df.rename(columns = {\"yrs.since.phd\" : \"phd\", \"yrs.service\" : \"service\"})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Прежде чем приступить к построению регрессионных моделей, которые покажут нам взаимосвязь между заработной платой сотрудников и их характеристиками, давайте посмотрим на их распределение. Построим гистограмму для заработной платы, для столбца `salary`:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# несильно беспокоимся о настройках графика, добавим тол\n", "\n", "plt.hist(df[\"salary\"], color = \"cornflowerblue\", edgecolor = \"white\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Проинтерпретируем полученный график. Распределение заработной платы не является симметричным, оно немного скошено вправо – в выборке есть несколько сотрудников с нетипично высокой заработной платой (200 тысяч долларов и выше). Больше всего сотрудников с заработной платой около 100 тысяч долларов. Небольшую скошенность распределения можно заметить и по описательным статистикам:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 397.000000\n", "mean 113706.458438\n", "std 30289.038695\n", "min 57800.000000\n", "25% 91000.000000\n", "50% 107300.000000\n", "75% 134185.000000\n", "max 231545.000000\n", "Name: salary, dtype: float64" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[\"salary\"].describe()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Среднее выборки равно 113706 долларов, а медиана чуть меньше, 107300 долларов. Среднее здесь немного «завышено», как раз из-за наличия сотрудников с нетипично высокой заработной платой. Отсюда и скошенность – распределение симметрично, если среднее и медиана совпадают. \n", "\n", "Теперь построим гистограмму для стажа, числа лет опыта работы:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.hist(df[\"service\"], color = \"cornflowerblue\", edgecolor = \"white\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Тоже имеет место скошенность вправо, при этом большая часть значений сосредоточена в интервале от 0 до 10 (примерно). То есть, довольно много сотрудников с относительно небольшим опытом работы, не более 10 лет." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Изучение взаимосвязи: диаграммы рассеивания и корреляция" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Приступим к изучению взаимосвязи между опытом работы и заработной платой. Начнем с диаграммы рассеивания, только построим ее не с помощью `matplotlib`, а с помощью `seaborn`. Сначала настроим общую тему графиков – чтобы на них присутствовала сетка, а фон при этом был белым:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "sns.set_theme(style = \"whitegrid\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Настройки сохранены, они будут применены ко всем типам графиков далее. Полный список настроек можно посмотреть в [документации](https://seaborn.pydata.org/generated/seaborn.set_theme.html) функции `set_theme()`. Теперь построим диаграмму рассеивания с помощью функции `scatterplot()`:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.scatterplot(data = df, x = \"service\", y = \"salary\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Устройство этой функции простое: в `data` указываем название датафрейма, столбцы из которого мы используем для построения графика, а затем в `x` и `y` перечисляем сами названия этих столбцов.\n", "\n", "Что мы видим на диаграмме рассеивания? Связь между числом лет опыта работы и заработной платы есть, но не то чтобы линейная. В целом, если стаж сотрудников меньше 30 лет, связь между опытом работы и заработной платы прямая (чем больше опыта, тем выше зарплата), а если стаж выше – связь обратная (чем больше опыта, тем ниже зарплата). Это вполне объяснимо: опыт работы естественным образом связан с возрастом, а с определенного возраста заработная плата может становиться ниже в силу разных причин (меньшая активность, неготовность обучаться новым технологиям, состояние здоровья и прочее).\n", "\n", "Действительно, если мы вычислим коэффициент корреляции Пирсона между этими показателями, который показывает линейную связь, он будет невысоким:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
salaryservice
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\n", "
" ], "text/plain": [ " salary service\n", "salary 1.000000 0.334745\n", "service 0.334745 1.000000" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[[\"salary\", \"service\"]].corr() # 0.33" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Можем дополнительно сгруппировать точки в зависимости от должности (`rank`) и учесть это на графике:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# hue отвечает за цвет точек, если это не фиксированный цвет, а зависящий от какого-то еще показателя\n", "\n", "sns.scatterplot(data = df, x = \"service\", y = \"salary\", hue = \"rank\"); " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Можно заметить, что характер связи между числом лет опыта работы и заработной платой примерно одинаковый у преподавателей (*assistant professor*) и доцентов (*associate professor*), увеличение стажа сопровождается увеличением заработной платы. А вот у профессоров ситуация более разнообразная: их больше, и у кого-то связь между стажем и заработной платой прямая, а у кого-то – обратная. \n", "\n", "Функция `scatterplot()` довольно универсальная, в `hue` можно вписать и количественный показатель тоже, например, число лет после получения PhD:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.scatterplot(data = df, x = \"service\", y = \"salary\", hue = \"phd\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "На таком графике более темные точки соответствуют более высоким значениям `phd`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Парная регрессия и множественная регрессия" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Теперь приступим к построению линейных регрессионных моделей. Для этого нам понадобится функция `ols` из модуля внутри библиотеки `statsmodels`. Вспомним, что *OLS* расшифровывается как *ordinary least squares*, то есть метод наименьших квадратов (МНК) для оценки коэффициентов линейной регрессии, и импортируем эту функцию:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "from statsmodels.formula.api import ols" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Теперь построим модель парной линейной регрессии, которая покажет, каким образом заработная плата зависит от стажа:\n", "\n", "$$\n", "\\widehat{salary}_i = \\hat{b}_0 + \\hat{b}_1 \\times service_i.\n", "$$\n", "\n", "Запишем внутри функции `ols()` формулу вида `y ~ x`, где `y` – зависимая переменная, а `x` – независимая переменная, а затем укажем название датафрейма, откуда брать эти переменные `y` и `x`:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ols(\"salary ~ service\", df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Python создал объект «линейная модель, оцененная методом наименьших квадратов», но пока ее не оценил, то есть не вычислил коэффициенты $\\hat{b}_0$ и $\\hat{b}_1$. Чтобы он это сделал, нужно применить к этой модели метод `.fit()`:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "model = ols(\"salary ~ service\", df).fit() " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ура! Модель получена, выведем подробную выдачу с результатами, применив метод `.summary()`:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " OLS Regression Results \n", "==============================================================================\n", "Dep. Variable: salary R-squared: 0.112\n", "Model: OLS Adj. R-squared: 0.110\n", "Method: Least Squares F-statistic: 49.85\n", "Date: Sat, 08 Oct 2022 Prob (F-statistic): 7.53e-12\n", "Time: 15:49:22 Log-Likelihood: -4635.7\n", "No. Observations: 397 AIC: 9275.\n", "Df Residuals: 395 BIC: 9283.\n", "Df Model: 1 \n", "Covariance Type: nonrobust \n", "==============================================================================\n", " coef std err t P>|t| [0.025 0.975]\n", "------------------------------------------------------------------------------\n", "Intercept 9.997e+04 2416.605 41.370 0.000 9.52e+04 1.05e+05\n", "service 779.5691 110.417 7.060 0.000 562.491 996.647\n", "==============================================================================\n", "Omnibus: 25.187 Durbin-Watson: 1.843\n", "Prob(Omnibus): 0.000 Jarque-Bera (JB): 28.656\n", "Skew: 0.593 Prob(JB): 5.99e-07\n", "Kurtosis: 3.570 Cond. No. 36.9\n", "==============================================================================\n", "\n", "Warnings:\n", "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n" ] } ], "source": [ "print(model.summary()) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В первой части выдачи сохранена сводная информация по модели. Из самого актуального пока здесь только число наблюдений (`No.observations`), коэффициент детерминации $R^2$ (`R-squared`) и его скорректированная версия (`Adj. R-squared`). Можем сказать, что наша модель объясняет примерно 11% изменчивости заработной платы сотрудников, это не очень много, но вполне объяснимо. Во-первых, странно ожидать, что кроме опыта работа на заработную плату ничего не влияет, а во-вторых, мы уже видели, что связь между этими показателями не совсем линейная. Но мы все равно изучим линейную модель, так как она проста и удобна для интерпретации.\n", "\n", "Перейдем к основной части выдачи – коэффициентам. Используя значения из столбца `coef`, мы можем записать уравнение модели. Здесь `Intercept` – это константа $\\hat{b}_0$, а `service` – коэффициент $\\hat{b}_1$ при независимой переменной `service`:\n", "\n", "$$\n", "\\widehat{salary}_i = 99970 + 779.5691 \\times service_i.\n", "$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Проинтерпретируем полученные результаты. Значение `Intercept` – это среднее значение зависимой переменной в случае, если значение независимой равно 0. В данном случае это среднее значение заработной платы (в долларах, за 9 месяцев), которое может ожидать сотрудник без опыта работы ($\\text{service} = 0$). Коэффициент при `service`, чисто математически, показывает, на сколько, в среднем, изменяется значение `salary` при увеличении `service` на 1. Однако в реальной жизни, если мы не имеем дело с контролируемым экспериментом, такая интерпретация не всегда корректна, так как она намекает на причинно-следственную связь. Мы не можем остановить или ускорить время, чтобы влиять на число лет опыта сотрудников и изучать, как его изменение отражается на заработной плате (и при этом гарантировать, что другие факторы, не включенные в модель, не изменяются). Поэтому поступим более аккуратно. Скажем, что у тех сотрудников, у которых стаж выше на 1 год, заработная плата, в среднем, выше на 779.57 долларов.\n", "\n", "Теперь проверим, а можно ли считать связь между опытом работы и заработной платой статистически значимой. В рамках модели это означает, что мы должны проверить гипотезу о равенстве истинного значения коэффициента $b_1$ нулю:\n", "\n", "$$\n", "H_0: b_1 = 0\n", "$$\n", "\n", "Посмотрим на p-value, полученное в результате проверки этой гипотезы. Оно находится в столбце `P>|t|`, так как по определению это:\n", "\n", "$$\n", "\\text{P}(|T| > |t|) = \\text{P}(|T| > 7.060) = \\text{P}(T > 7.060) + \\text{P}(T < -7.060),\n", "$$\n", "\n", "где $T$ – случайная величина, имеющая распределение Стьюдента с $n-2$ степенями свободы.\n", "\n", "Здесь p-value равно 0, поэтому гипотезу о равенстве истинного значения коэффициента при `service` мы отвергаем на любом разумном уровне значимости (оно меньше 0.05 и 0.01 тоже). Значит, связь между показателями есть, изменение числа лет опыта работы сказывается на заработной плате (опять такая осторожная интерпретация, лишний раз не делаем громких заявлений о влиянии). \n", "\n", "Коэффициенты модели можно также запросить отдельно, извлечь их из объекта `model` как атрибут:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Intercept 99974.652866\n", "service 779.569114\n", "dtype: float64\n" ] } ], "source": [ "print(model.params)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "С таким же успехом можно извлечь и другие характеристики модели, например, коэффициент детерминации $R^2$:" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.11205399790940596\n" ] } ], "source": [ "print(model.rsquared)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Выше мы получили уравнение модели:\n", " \n", "$$\n", "\\widehat{salary}_i = 99970 + 779.5691 \\times service_i.\n", "$$\n", "\n", "Это уравнение можно использовать для предсказания заработной платы на основании стажа. Мы можем подставить вместо `service` любое число лет опыта работы и получить ожидаемое, согласно нашей модели, значение заработной платы. Можно, конечно, проделать это вручную, но удобнее и универсальнее будет воспользоваться методом `.predict()`. Если мы применим его к исходному датафрейму, Python вычислит предсказанные значения заработной платы для каждого наблюдения в нем:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 114006.896913\n", "1 112447.758685\n", "2 102313.360207\n", "3 130377.848300\n", "4 131936.986528\n", " ... \n", "392 123361.726277\n", "393 114786.466027\n", "394 119463.880709\n", "395 111668.189572\n", "396 103092.929321\n", "Length: 397, dtype: float64" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model.predict(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Если мы хотим использовать модель для предсказания на основе каких-то своих значений, например, тех, которых в датафрейме нет, их можно записывать в виде словаря и помещать его в аргумент `exog` (от *exogeneous*, внешние данные):" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 123361.726277\n", "dtype: float64" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# значение заработной платы для человека с 30-летним стажем\n", "\n", "model.predict(exog = {\"service\" : 30})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Если значений несколько, их оформляем в виде списка:" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 123361.726277\n", "1 138953.108551\n", "dtype: float64" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# значение заработной платы для человека с 30-летним и 50-летним стажем\n", "\n", "model.predict(exog = {\"service\" : [30, 50]})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Теперь давайте, используя `seaborn`, построим диаграмму рассеивания с добавленной на нее регрессионной прямой. Для этого нам понадобится специальная функция `lmplot()`:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": 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ahdrj8bBs2TKeeuopjh07xubNmyOPtba2cvnll/P000/z5JNP8sorr1BQUADAt771LVasWMHhw4d58MEH8Xq91NTUsHHjRmRZpqWlhTVr1tDR0cEll1zCpk2byMvLo6enhx/+8Ic0NzdTXFzMli1bKCsrS/dlCkZBqjp8CKtcMF5J62biX//6V5YvX05TUxMA8+fPp76+nvr6en71q1/hcrl44IEHAGhsbGTz5s2Rx1esWAHAmjVreOihh3jzzTfRdZ3t27cDsHHjRu644w52795NdXU1W7duBWDLli3U1NSwa9culi5dyiOPPJLOSxxT3j/cyrpt+7j3kT2s27YvZzP7UhGdIrIdBeOZtAr19u3b2bBhA+Xl5f0ee/zxx1m2bBkXX3wxYAj1008/zZIlS3j44YcJBoOcPn2aQCDAFVdcAUBdXR27d+8mHA5z4MABFi5cGHMcYO/evSxZsgSAxYsX8+677xIOh9N5mWPCeBKmVESnZGvMuECQCtLq+hjImm1qauK9996LPO71epk1axZr1qxh6tSprF27lq1bt3LdddfFuC3KyspobW2lq6sLl8uFLMsxxwHOnj0beY0sy7hcLjo7O6moSG4J3NjYOOLrBWhoaBjV65Pl399uI6woSJjwKcaxsKLx7//7AyRfcq6edI710xY/+w97OOdRKHTJfHWWi8smORI+d84UnV0HAvgDYDFLhFUdTYXaL9ojYxxqrM1nurBbJbxKKHJM13WazwQy9plA5j7/VCDGmnpGM8558+YN+NiYbCa+9NJL3HHHHVitVgDy8vL45S9/GXn8nnvuYd26ddTW1iJJ55OddV1HkqTIz2jif49+jcmU/MKhuroam802nMuJ0NDQMOjNTiVbd++hMN8Wc91OXcfjV5IaQzrH+v7hVt45eBBZlikptBmp6wf9zJg+I6HPeN48mDG9NRKdMqk81r+czFir3ttHS5sbX0AhrGhYZBNOu0zVxPyMfSaZ/PxHixhr6knnOMdEqN9++22effbZyO8tLS3s37+f22+/HTDEVZZlKisraWtrizyvvb2d8vJyiouLcbvdqKqK2Wymra0t4l4pLy+nvb2dyspKFEXB6/VSWFiY2QvMANlcwnQkm4OjjU6ZM62Ejz7rAAnMEoQUjZA7xMJrSmKeJzYcBblIxjMTOzs7CQQCVFVVRY7Z7XZ++tOf0tzcjK7rvPDCC9x4441MnjwZm80WWU7U19dTW1uLxWKhpqaGnTt3ArBjxw5qa2sBY8Nyx44dAOzcuZOamhosFkuGrzL9ZHMa9likrh861kFhvg2rbEbTJayymcJ8G4eOdUSeM578+oILi4xb1KdOnaKysjLmWHFxMQ8//DCrVq0iHA5z5ZVXcvfddwOwadMm1q9fj8fjYfbs2dx1110AbNiwgbVr17Jt2zYmTpwYCftbvXo1a9euZdGiReTn57Np06bMXmCGyGRD0OFaoWNh7bd2+ih0WSnKP++20nU9ZnJIVRigQJBpMiLU77zzTuTfc+fOjYTYRbNw4cJIFEc0M2fO5OWXX+53fPLkyTz//PP9jhcWFvLUU0+NcsS5QSaSWUaSjJKu5rWDTRjJTA6ivKogVxFFmQSDMpKwt3QUXRrKbZGMKyhbi1QJBEMhUsgFgzJSKzTV1v5QbotkXEHpsvQFgnQjhFowKNkSXZLMhDHU5FAzq4IjV1VR/+5n+IMKDpvMLbWXDjmhiEgRwVgjXB+CQcmW6JJUuC2iW5NdMjGfonwr7xxoHjTqQ0SKCLIBIdSCQRmpvznVdUhSMWGMxN8uUtMF2YBwfQiGZCiXQrxrYM60Et450DysSJGh3AupCEccib9dRIoIsgEh1IJRkSh877/ePkJBngWX0w4MHa+cbAjgaDcoR+JvzxYffbIIf/r4RLg+BKMikWtA03S8fiXmeYNZoZlyL4zEfZItPvpkEP708YuwqLOYXLCOErkGLLKJsKLFHBvMCs2Ue2Ek7pNMZoCOFpF5OX4RQp2l5Ep7qkSugTyHBbc3RCCUXLxyJt0LI3Gf5EI7MxD+9PGMcH1kKbkSbZDINWAxm7j972YkHSmSS+6FbEZkXo5fhEWdpeSKdTSYa2D5KM8BsG7bPprPdFH13r6MuRxyweWUCJF5OX4RQp2l5FK0QSpcA/HniHb92K1Sxlw/qXI5/fatj/tlQC5fMDPmfVI9GeSSP10wPIRQZykXunUU7frxKqGMbYylYkPut299zEt7PgUJZBMEQorxO7B8wcy07j/kij9dMDyEUGcpuWQdpcM6HCvXTyret/7dz3pF2tgCkiVQNI36dz9j+YKZIjpDMGyEUGcxuWAdJWsd5kLzgVS9rz+oIMdt05sl4zjkzv6DIHsQUR+CUZFMdMpIEjHGKhIkFe/rsMmoeuwxVTeOg4jOEAwfIdSCUZFMf8TRNh8IhPSUNB9IhlQ0Pbil9lLQDXeHrmsomgZ673FEOKJg+AjXh2BUpLMFVp/rp6GhgXnz5qV24Em870jpi+4YKOojl/YfBNmBEGrBqEgmOiWXQg1TxfIFM2PC8eLJhf0HQfYgXB+CUZGMq0As9QXjHV3Xkczps3uFRS0YNcm0wMqlpX6uZiYKMk9Y0QgEw/gCCh6/NvQLRogQakFGyJWlfq4UwxKMHX2rQp9fJago6HrfcSHUAkFaLN34c7q9IZGMEodYYRiEFRVfQMEfDKOmT5MTInzUgpwgHUXxE53zZKsbJS4I+kJORrnQmxHouo4/GKb9nJ+2c348/syLNAihFuQI6Sj7muicFrNEV08w5nnjPUJlMHKl3G6qUVQNtzfI2U4fnT1BgmE14uIYC4TrQ5AVDLW8TkfadaJzFuXbaDsXSLrpwXjnQkp313WdYMhwbwTCypgKczxCqLOYC8U3mMwGXjpisROdU5ZNTKlwUZBny4kIlXRzIcTAR0duKFoWqXMUQqizlPEWfRA/6cyZVsKhYx20dvrw+sPYrWZcThuQeAMvHWVfBzrnvd+YnRP3OBMT+XgttztQ5Ea2IoQ6SxlPpTDjJ52WNg8ffdZBYb6VQpeNjnN+/IEwbl8ITTOa405wWWOW1+mIxc61+O5oMjWR5/I9SkRY0fAHwviD2Ws9JyIpoX7sscdYvnw5U6dOTfd4BL2MJ99g/KTjCyggGT+L8u2YzRKhsE4obGynK6qGP6hw8cSCmPOkIxY7V+K743l171HCqkq3VyGsaFhkE067zK9/92FaOsfk4j3qI9es50QkJdQTJkzgnnvuoaqqimXLlnHjjTdiNpuHfqFgQIZato4n32D8pBNWNMyS8ROICHQ8nT3+jIwvnsHcNNmyV3Dy8x68/jASEiZJQlF0unqCdHQHsVm8qJpOtzvA/3rxL6xeduWYj3csUFTDes5m33OyJBWet2rVKn7/+99zzz33sGvXLm666Sa2bNlCa+vQsZQej4fFixdz6tQpAB544AEWLFjALbfcwi233MKePXsA2L9/P0uWLGHBggX87Gc/i7z+8OHD1NXVsXDhQh588EEUxSi+3tLSwooVK7jppptYtWoVXq8XgJ6eHu6//35uvvlmVqxYQVtb2/DuSAZIJjZ1PNXHiK+/bJFNqLrxczB6vOFBH3//cCvrtu3j3kf2sG7bvpTE9sZ/Ni1tHl7a8yktbe6MxxEPdn2KqqMDJpOEJEmYTBJ9WqRpYJIkNA3cvjC//t2HaR9rNhEIKnR2Bzjb5aPHF855kYZhxFFLkkRFRQXl5eUoisKxY8dYsWIFL7744oCv+etf/8ry5ctpamqKHGtsbOQ///M/qa+vp76+nhtvvJFAIMC6devYunUrO3fupLGxkT/+8Y8ArFmzhoceeog333wTXdfZvn07ABs3buSOO+5g9+7dVFdXs3XrVgC2bNlCTU0Nu3btYunSpTzyyCMjuS9pJZnY1FTURc4W4icdp10GHZx2GX2E69B0JWLEfzbRbppMxhEPdX0Wswl00HQd0Ht/GkSLt0mCljZvWseaDUTHPXf0BPCHctPFMRBJCfV//dd/sXTpUlatWkVZWRmvvPIKP//5z9m+fTtPPPHEgK/bvn07GzZsoLy8HAC/309LSwvr1q1jyZIlPPHEE2iaxsGDB5k6dSpVVVXIssySJUvYvXs3p0+fJhAIcMUVVwBQV1fH7t27CYfDHDhwgIULF8YcB9i7dy9LliwBYPHixbz77ruEw4NbZpkmmWL7YIj1o6uu5VcP3sijq65Ni0inwyqNJ37SmVTm4u9vvIxJZfl4/MqIzpmuRIz4zybeTQOZ2SsY6vqqKvMpzLchm02oGsjmxH/K40ir+tGXNRhtPYfHIm0wAyTlo961axcrV67khhtuwGQ6/4UoLi7mX/7lXwZ8Xbw1297ezjXXXMOGDRvIz89n5cqVvPzyyzidTsrKyiLPKy8vp7W1lbNnz8YcLysro7W1la6uLlwuF7IsxxwHYl4jyzIul4vOzk4qKpITucbGxqSeNxANDQ1DPsdpUTnnDmKNWvqHFI18h5zU61PFb//3n9h14BwmM1jMEi1ngzzx2wPcfFUhl01ypPS9JOC2L9sBe+8RL5eVGL//9BU/3mB/ScmzSZH7EX9fms90YbdKeJVQ5Jiu6zSfCYzqHsZ/NiZJR1F1ZLOE12eIs9uvoChw50NvUOiS+eosV+R+perzG+r65kzROXUmjNMGFqeJsKoTDIGug6KqSJLxb12HsgnmhOPK5HdttPSN1dAfEyEN/AGFUFgZ8aos1dhtFj744AM0bWSTxWDNMZISalVV+drXvpbwsaVLlyY9kKqqKn7xi19Efr/zzjvZsWMHCxcuRJKkyHFd15EkCU3TEh7v+xlN/O/Rr4meXIaiuroam82W9POjSbYTie40lrVmWYrEplrQ+cclc5mXIddGQ0MDh05J5OXZYzYsAyGFQ6ckli/JXEeV0j904/vcHbNUlSQoLXYxb968hPe16r19/TZbAyGFqhLHqLrBxH82ITXEOXeQ/DwrToeNc54g/iAU5tsodFkJhlXeOehnxvQZSL5TKetEM9T1zZsHM6a3RsLmJpU7WfiVEnbtbzI2z1QN2WxEgnz79i/1+16lsmtOuuO5//KXv3D5FV8iEFLw+xVC6timcw/E0SOf8KUvfSkt505KqN1uNz6fD6dzdBEHn3zyCU1NTRGXha7ryLJMZWVlzKZfW1sb5eXl/Y63t7dTXl5OcXExbrcbVVUxm82R54Nhjbe3t1NZWYmiKHi9XgoLC0c17lSTLbGpIw0BTPUfpj+oUlHkoNsbioSaTcizEgiqA74mXYkY8Z/NpDIXC6+ZyqFjHZzt9BEIaRTm2yjK75+cY6wYUkMy15cobG5GVVFGv1fvH27lf734F/xBJS2RJoGQQkg1c7bTyzjYExwxSQm1w+Hg+uuv5wtf+EKMWD/11FPDejNd13n00Ue55pprcDqdvPTSS3zzm9/k8ssv5/jx45w4cYIpU6bwxhtvcNtttzF58mRsNltk9q+vr6e2thaLxUJNTQ07d+5kyZIl7Nixg9raWgDmz5/Pjh07+Pa3v83OnTupqanBYrEMa5zpIJG4Pbrq2lGfYzR/DCMJAUxHokXfOCaXuSLHAiFjA3Ug0jnZJRLA5b0/731kzyCTW+qEeqTXl+mY51//7kPcvjAmSeoXaTLScaiqhi+o4O9dGXR7/Be0SEOSQn377ben5M1mzpzJ/fffz/Lly1EUhQULFrB48WLASKr57ne/SzAYZP78+dx0000AbNq0ifXr1+PxeJg9ezZ33XUXABs2bGDt2rVs27aNiRMnsnnzZgBWr17N2rVrWbRoEfn5+WzatCklYx8NqRC3dAhk3XXTeeKlD2jrCsQsle/9xsBWaToyJkdqHY9FIkYm49tzIdGkpc2LSTIiTcBwWaHpI4o0CQQV/EEl5yI2AiGFw8c7+fSYm6trlJjvRqpI6ozf/OY3Y37XdZ0TJ04k/SbvvPNO5N8rVqxgxYoV/Z7zla98hddff73f8ZkzZ/Lyyy/3Oz558mSef/75fscLCwuHbemnm1SIW6oEss8qbz7TRWFBD75AmJCioeug6SpyWOJIc9eAlns6MiZrZlVw5Kqqfl27468rG4pUDTqp+E5ldCzZQrym6hibx8kQbT3nUqKR44QAACAASURBVMRGZ3eAg0fbOHi0nU9PdkVqmH9hejOLrr0k5e+XlFC/+OKLPP744/j95zPFiouL2bdvX8oHNB5Jhbil4hzRVrndKnHqrFEk32QCq2xC04144e2//5TKEmdCyz0dFuX7h1t550AzRflWKosdxgbdgWYADh3roPlMFxP+8A49nhB5DjmltS2GK/6DuSQaGi48oZ5c5qK51Y2m65gk0HojTaaUuwZ8ja7rhEIqvqBCIKTkhFtD03VOnOnh4NF2Dh5p53SbJ+Zxk0niojIrV8+uTMv7JyXUzzzzDM899xzbtm3j+9//Pn/4wx/4/PPP0zKg8UgqxC0V54i2yr1KCLXXCjCWmUZyBBhZbwNZ7unYxEu0WugKBnn57SOUFzuwWyU+b/ca47KdjysercslWXdSKvYXcpnBUuqdNhm71Yyi6hH3mSvPwj8u+mK/86iqhi8Qxh9Uc8J6DoZUDjd1cvBoG43HOujxhmIez7PLVE8rZc70UmZfUsLp5mOUFqY2rLWPpIS6sLCQyy+/nFmzZtHR0cGqVav4+te/npYBjUdSIW6pOEciqxyI8QcmMm6iLfd0bOIlGpfXH0bV9POTiqYjSXDOHSTPLvcb10hIxp00XsvNNp/pouq9fUN+dv0rH7p7Kx+eD0+0WsyUFhlROom+D7nke+7sCXDoaDsHj7bzyYkulLgJpbLEyZzppcydXsqlkydgHkbo72hISqhlWaa7u5upU6dy8OBBrr32WlR14NApQSypELdUnCPeKrdYTITCGhLGcrTvj0g2x3oY4y33VG9yJVot9IXp9WGRTSiKFpMhOFqXSzLupPFabtZulZKadAavfGiLHC/Is/HkD8+vMlRN7y3GrxJW1KzNkNR0nZOfuzl4pI1DR9tpPtvfpTFjSqEhzjNKKS8am6JoSQn1t771LVauXMlTTz3Frbfeyp49e7j00kvTPbZxRSrEbbTniLbKdV0n32mlszuAjpEZKUlgs5hw2i0ZbUWVaLVgMknkRYloocvG2S4/stlIeErFuAZyJ2m6xrL1O/EHjfs0Ic8a85zxUG7Wq4SSmnSGqnwIsfcjFFbx93XqzlJ1DoX7XBrtHDra3s+l4bTLzL60hLnTS5l9aQlO+9iH9yYdnvf1r389Evt86NAh/vZv/zbdYxOkmGirvPlMgMICK/6A4WJQNR2zScJhk7n5qxdHEjwykTSRaLVQ+6UpvHOgOVLISZYl8p0WCvPtePxKSsaVaILo7A4QCKlIJgnZBCEFznlCSJJEyQQjTnq8lJsFYz/i46ZO7n1kT1Lldi2yiZCinU+xN0lIwIyqQtq7/ISy1HruchsujUNH2/n4RFfMRAPGdfa5NKZNyZxLI1kGFernnntuwMd+85vfcPfdd6d8QILzpCMcrc8qb2ho4JX3Aiiq2j+F/FhHxjfLBsuyaz4ToKrEwb3fmJP27iXt5wK9Im38oVrMOmFV45wnSHGBLadbUcWLrjeg0Na7ShnI/x4/mTntMiF3iEKXlXynjKpBjyfEl75QRlDJHneoruucbHVz8Ighzidb3TGPmySJ6VUTmDOtlLkzyqjI8ol3UKH+9NNPMzUOQRyZ2MTK9i4y0ZNKoroUqZjI4ieIW9a8TnSZbJNJwqyDqpEyS36siHd9dXUHACgusA8YSRM9mbV1+rh0ciHVl5bw8YlOmls9OO0WFv/tpcy+tHQsLw0wXBofn+ji0NE2Dh7toNsTjHncaZOZPc1waXzx0hLyssClkSyDCvVPfvKTTI1DEEcmNrHGsovMaEV2pBPZUO/rsMkEQgpy9H6qZPjLf/XgjSO51Kwh3vWl6TplhXbyHOcFa6Byu1+6rAx/SMHnN9K6r66emOnhJ6TbE4z4mg83dfZzaZQXOZg7vYw500uZPmUC5gHKwWY7SfmoP/jgA5555hl8Ph+6rqNpGqdOnWLv3r1pHt6FSyas3bHqMJ2K1cJIJrJk3veW2kv57ZufEIyKapJ6j48H4l1fXXHtzqInal3XCYbUrAqt03Wd5lZPr9XczonP+7s0pk2ZEPE3V5bkjdFIU0tSQr1+/XpuueUW3nzzTZYtW8bbb7/NggUL0j22C5pMWLtjVcUvFauFkUxkybzvjKoinA4LPn84kgrtdFiYUVU04HmHG5ucLSSMtpEkbr9+Om5vMGsSUxRVNzYCjxmWc5c71qVht5mZfUkJc2eUUX1pScwKYbyQlFBLksT9999PV1cXl156KUuWLOG2225L99guaDJl7Y5F4Z9kRXYwARzJRJZs3HRRvpWJJefPEwgNPImMJDY5W+ibqHe8ewy3J8jFkyZw7dxJVJbm0eMb265I3Z4gh44Z6dofHW9HUc/GPF5a6GBur9U8o6owZ10ayZKUUOflGcuHiy66iCNHjjBv3rxhFeMXDJ9sqVmdDIn8vsCAvuBkRHYoARzJRJbM+w7XUh9JbHI2MXd6KZdVFeILhukznsfCxaHrOqfOeoxaGkfbOXGmJ+ZxSYJpkycwZ3pZr0vDOWCzkPFIUkI9Z84cvv/977N69WpWrlxJU1NTpA2WIH3kQpnLRH7fJ176AF3XcTktCX3ByYjsUAI4koks0ft6fGFkszkSR+y0yQTDatKWeiYjZ5LZgE3mOaqmo0sWI+55DLulhBWVT050GZuBx9rp6olzaVjNfPHSEortAW6qvRyX0zo2A80CklLbBx98kIaGBi655BJ+/OMf88///M+Ddh8XXDgk8vu2dQUAPVKgJpHIDlXWNBkBHO5EFi/udpsZSZJQVDUyoXh84YilloylnqnImWQ2Qod6TiCkEAiqRkPYHj8TxyDuuccbovGYYTUfPt5JMBw7htIJ9t507TJmVBUim000NjZe0CINSQr1hg0bACgqKuJf//VfufXWW/nVr37Fz3/+87QOTpD9JM5209CB023e8621XNaIyA5U1nRGVdGofNDJEC3u67btQ1W1mEkGwGw2UZBnS8pSj49NDoSUtOwlJLMRGv+cfIcVJJ233z/JRRX5kc8FyFhDWF3XOd3miYTQNbX0xGQuSsAlkycY/uYZpUwsybugXBrJkpRQNzY28vLLL/PMM89w66238oMf/IC6urp0j02QA1QUO2lp8+ALKFGFlHQ0zRBss8n42dblp6oiH0hOdEYigL996+N+VvryBTMHfP5AVrvHr8QUGBqM6NWBL6DgtEuRUL512/alLKs0mRVGa6ePAqeMwyZjs5jRdB2PL8THTZ0Zjd4IKxqfnuyKiHNnTyB23FYzX7ykmLnTy6ieVkL+BW4tJ0NSQt3XyXvfvn18+9vfBiAQCAzxKsGFwJxpJXz0WQdIYJYgpKiRTSlF0WK6fei9tlSybo1EAjiQ2P32rY95ac+nIIFsMiI1XtpjZNYOJNapsNqjVwf5dh3ZYmXnvuNIUlNKmxwkM9ZLJxXgC4bRNKO2RVjRCIZVigfpPZkq+lwah46281FTJ8FQrEujuMDO5TOM2s0zqopiKiMKhiYpob7ooov4p3/6J06dOsWXv/xlfvCDHzBz5sCWiuDC4dCxDgrzrRGL2iqb8Pcmi0SW2YDZZNSShuSjPuIFMN49Er1x1n7OD+hYTGYAZAkUTaP+3c8GFOpUhEC+uvcoYVWj26sQCitYLb0V5kznizils6/k7TfMIBAyWlldUz2R595oxBdQUVUNs9mEw2Zm6d9dNKL3HAxd12lp90ZqNx8/3T2gS2PO9FImlY5vl4YkkdZCTkkJ9U9+8hP27NnDvHnzIh3Ab7311rQNSpA7tHb6KHTZKMo/34H72Cnjj9ZmMUeOKZoW6SuXiqiP+I2zs53GuTVJjzRaNUvgDyox442PirjhqqpRVQps/tyN2xcyqshJhptHUTW0OE9DKvpK9m2EdpzzM6XCxc1fuZiLyvMjpWrPv6/RZAH0lEZ0KKrh0ugT547uOJeGxXBpzJleSvW0UgryxqdLQ5JANklYZDOy2YRFNiHLJs7a0zcRJSXUTqeTW265JfL78uXL0zagC5VsaNyaLNFj9frDqKpGUb4t8rgk0dss93wfPXSw9CYlJBNaN5R7JN7PbZIkNF1H0TSsvVa1qhu1O6LHHR8V8c6BZlaOwiURVjWQ+t5fwtRrNcYLZKo2QqunlRAMqvhDRtxzdMW6t/58EqddjvksgmGVt/58kuppIyua5PGFaDzWwcGj7Xx0vINAnEujqMDWm3hSxmUXjT+XhiSBWZKwWsyGIPcKc6IEm3Q2UxHB0FlAtrV7GmzSiB+rqqoRl0Zfayaz2YTTakZV9cgGozNPZlLZ+YanQ4XWDeUeiRfyCS4rXe4gug66rhlF6/XYGh3pKHQlmyV0TTfikQGp749VImXNF5LtltLe7SfPZo45ZpVNdHT7B3hFf3Rd50y7N5J4ksilcfGkgkgtjcllrnHj0ugTZYtsiHLff9mQ9SiEOgvIpnZPQ00a8WPtc3kEQmqkDGhf0X9ZllLSIzJR1Ee8kJdMsBNWNXwBBUUjYdRHOpJTCvNtuL2hGH+8SYJ8p4Uud2jAOPFkiI57TqZTd+kEB92eQIzLKaRolEwYfDNRUTWONJ+LtKNqj3NpWC0mZl1c0utvLqEgzzbAmXIHSTI+J4tZxmqRkGVTxJWRjQihzgKyqS70UJNGorEWumx4/EpMGdC+ov/J+n4TWfEro0pyVpU4Ys6RyM/tslv4wR3zBnyfdMRmS0hIkoTFLKHrGpJkQlU1vAGFyhLngHHiAxFWNAJBo1N3dNxzMiy4+iJefOsTgqhYezuxqKrOgqv7byb6Qxp/bjzDX/tcGsE4l0a+LWI1f2FqERbZ3O8cuYIkgQmwyGasFsOfLJvNOeWmEUKdBYxlXeh4hpo0kh3rcLIGB7LiV9bN5dFV1yZsHJCqFPLRJqf4ggplRQ66PSFC4dg48mRXSJqm90ZuqASVkZcTrZ5WyrIFhq+6o9tPyQQHC66+iOpppei6Tmunz3BpHGnn2Klz6LTFvH7qxIJIoaMp5bnp0pAwhNliNmOxmKJcGLk70YAQ6qxgpAKSjg3IoYQ4HWI3kBX/6999OGj50NGmkKei0FXf/ZpclofX5yPP6eR4S08/ay3RCimsaPgD4ZiCSKOlelppZONQ7XVpbP/9pxw62k7buVhftUU2MeviYubOKGXOtFImuHLPpWFEYJh6N/skZNmMVTbl5CQzGEKos4CRCEi6NiCHEuJUiV30JNPVE4jEHPehKBpn2n1MLNWSLh+azMSV6kJXiXzp8R3UwZjsJpbmRZ7j84/Oeh4Irz9M42cdHDraxoefdfYLTyzMN6I0CmQvC2qvwGrJHUszYQSGxYzZNL5EORFCqLOE4QqIkWih0u09n7rttMuj3oBMpmDSaMUufpLpdkNblx9JksizG1/JLncQ2WxKunxoshNXqlch8e2tqkocMR3U7Vaj8FO+w8qir15Ma6cXVYPGY+289eeTtHf7KY1yUYyEzzu8kXTtY6e60eLUf2plfu9GYBlVFYZLo7GxMatFOnqzr6jAQXGBLas3+9KNEOoc5eTnPXj9YSSM2F1F0en2hFDUnqFfPAjJFEwardjFuzqKC+yc7fLT2R3AacsjGFYJqzrlRbFWdrJ1oSGxXzhdq5BETXgvu6iIN/+7iR5PCIfdwlfnTqSqsiAi0i++9Qlms0SezUy3J8CLb33CsgUkJdaqqnH0VHdv4kkbZ7sSuzTmTDdcGoX52e3SGMqv3ISCwzb+urYMByHUOYqi6r2p2cayT5JA0fRI9t9IGUrwUmG5xm9Y5jkslOk6HT3BSIifbDajxCUQDFUX2iQNXLEvmWtLFYGQwqWTJvB/LJ6d0LXx1p9PYjZLkTA6m8VMkMETU7yBMB99ZiSefHisA1+cS2OCy8qcacZG4MyLi3PCWrZZZCwWw4Vhlc2RjFJBf4RQZ4hUL7ktZhOBQbL/Rjquk5/3UDphYEs2FZarUXHPHVNxz2w2fI99uvbVuRMN90GS1fOcNpnmVjcmk5SwYh+MPAwymc9O6y3G39blHzQpBZJPTGnt9EWs5qPN/V0aVRX5kSiNqsr8SFZkNtEXGiePsyiMTCOEOgOkY8ldVZnfr7xofPbfSMblCyicMwdjancMlhEIifsODibm8RX3gmEVLUhMR5h3DjRH6nAkiqOOp68yH3pvMSg97jgjC4Mcshh/UCEQ6l+MfzAf9ECJKcUF9pjyoK1xE4hsNjHz4iLD3zytlKKC2Al1rEmURCKbjf/GWxRGpkm7UHs8HpYtW8ZTTz3FlClTeOmll3j++eeRJInq6mo2btyI1WrlySef5JVXXqGgoACAb33rW6xYsYLDhw/z4IMP4vV6qampYePGjciyTEtLC2vWrKGjo4NLLrmETZs2kZeXR09PDz/84Q9pbm6muLiYLVu2UFZWlu7LHJR0LLn7og1KJthGVfktflwFeVbc3lCkpnH8eVPRd9CouGeLTDLoYDLpqKqGJEmR+3PoWEdMHPX7h1sHrPHsD6qUFdrp9obOuz7ybDGJHCMJLYy+RxIYIWz64MX4G4+18x87P8IfNKrYub0h/mPnR9z19S9SPa00JjFFNkl4/GECIZVz7hCbf/OXmPcvyLNGEk9mTi3GZs0OS3S8xitnK2ndQv3rX//K8uXLaWpqAuD48eM8++yzvPjii7z++utomsZvfvMbwGhOsHnzZurr66mvr2fFihUArFmzhoceeog333wTXdfZvn07ABs3buSOO+5g9+7dVFdXs3XrVgC2bNlCTU0Nu3btYunSpTzyyCPpvMSkaO30xVhPkJpqaivr5lJU4MDjVygqcAy7uFCicRW6rDjtlgHPW3fddBTFcEX0uSQ8vjBub4h7H9nDum37cNjM/VosxVvlhS4rk8vyuHhiPiaThGySDNHuJf7+9Fm2XT3+GMv2/cOtgDGBhNW+6tfGf2FVj5lARnLPWjt9uBwWXA4LhQV2zCaJYFjl8HGjGH8iF8dre4/i8YXRdR2zWULXdTy+MK/tPRoZ68yLi+nxhjnd7qPbGyYY1iL3rKrcxde/ejFr//EqHvvnv+HOm2dx+YyyMRXpvopxTptMoctKSaGDypI8SoscTHDZcNotQqTTSFot6u3bt7NhwwZ+9KMfAWC1WtmwYQMul7E8v+yyy2hpaQEMoX766ac5ffo0V111FT/+8Y9pb28nEAhwxRVXAFBXV8cTTzzB0qVLOXDgAL/4xS8ix//hH/6BNWvWsHfvXl544QUAFi9ezMMPP0w4HMZiGbtd40y0lUrluKoq83l0VeIOJ8n0HfT6lYh1maiJrFFxT424VyyyiZBipD1HjyP6/gzXnRJSVEJulYXXTB3xPdM0ncsuKqSz248/qNDlDqDrxtgGq5/R2ulDkoha7utourHR+X8+/g5aXOEO2WziC1OLIrWbi7PApSFJYO21lq2W3Eu5Hm+kVajjrdnJkyczefJkADo7O3nhhRf4yU9+gtfrZdasWaxZs4apU6eydu1atm7dynXXXRfjtigrK6O1tZWuri5cLlekE3rfcYCzZ89GXiPLMi6Xi87OTioqkvvjbGxsHNU1NzQ09Ds2Z4rOrgMB/AGwmA1LT1Oh9ov2hM/PFCMdlwTc9mU7YOfXb7dhkhRURcPXG4hgkjRks4QsKXScC2CVDWvZ7fViMUuY0ejqCRMMhXDZzVhMGkFNx2zS8Hi9kXFMr5D47uO7OedRcPtVChwmVOW81abrOs1nAjQ0NLD/f9pw2CAUNqrNmU0SVivs/58mLivxJn1PTCYTGibCCvhDCsV2Pwc/6cZkMirlKaqRHn7VdFvC70pjYyO6ZgizrmtGNb+ox/tEWgKmlFqZc7GDqlIbFlkCztFy8hwtSY92dDQ2Nhp+ZZMhxH3ZfSYJTJIOuo4WX1h7jBjLv5PhMJpxxpdJiGZMNhNbW1u57777uO2227j66qsB+OUvfxl5/J577mHdunXU1tbGbELouo4kSZGf0Qy0WdHXRixZqqursdlGFneaqCYFwLx5MGN6a8QKnVQ+9vWmGxoaWL7kb0Y9rq2791CYb4u5/05dx+NX+PmPjCJN67bti7HcXXlAlw+PX8EXVHHYZGq/NJGOnmBkHHOmlfRW4JOxW1X8IRM9fh27wxpJigmEFKpKHMybN4+tu/dQUZzf7/vi8SuD/gH0oaoa/pCCz6/E+J0vuwwuqmqP1M8oL+mfnNK3cXi69RxOhx3JJKGriYv2F+RZcNhkdF3H4XTwja9dmfS9TgVS7/+OHvmUy6tnI1tMWLPctzzQ31W2kc5xZlyojx07xn333cedd97JPffcA0BLSwv79+/n9ttvB4w/MFmWqayspK3tfOGY9vZ2ysvLKS4uxu12o6oqZrOZtrY2ysvLASgvL6e9vZ3KykoURcHr9VJYWJjpy+xHqlOXU81Io69HsrnoDRh+bU3vtVIVlf/5tI3Vy66M6RDel3kZCquYTMYEHZ0UM9xNzng0TScYNoohBcJDp3PHP6xpOm8fOMnO/ccjleq8wYFrP5cVOXD0+pl1XR9WneiREl8Lw9wbs9xql5iQ5YkwgvNk1Onk8Xi49957Wb16dUSkAex2Oz/96U9pbm5G13VeeOEFbrzxRiZPnozNZossJ+rr66mtrY20A9u5cycAO3bsoLa2FoD58+ezY8cOAHbu3ElNTc2Y+qezmaE26JIh0eZifCRFRbEzZnOxo9uPphvWnUmS0DRw+8L8+ncfRp5z8vMeI9NS0Q0rUDcsZUXTkt7kHCiiIxhW6XYHOdvlpbMniD80sEj3ZRF2ewLk2cx0uf38++8+4me//Qs/+vn/xyt/ONob3WGcwCRJ2K1migtsTJ9SSMkEO47eDTiHdXh1ooeL0bcPHFaZAqeFkgI7FcV5lBc7Kcy3keewYrfKmExS1rg0BMmRUYv65Zdfpr29neeee47nnnsOgBtuuIHVq1fz8MMPs2rVKsLhMFdeeSV33303AJs2bWL9+vV4PB5mz57NXXfdBcCGDRtYu3Yt27ZtY+LEiWzevBmA1atXs3btWhYtWkR+fj6bNm3K5CVmHYMla6QibDCZIk3xYXGhsCESZpNRy1mSAE2npe28Lzk681LTJENcMMYaXfc62XEoqoY/aDSBjXZtDFVz460/nwR0QmGNbk8o0orqkxNdkedYzBIOu4wJjfw8YyPQF1T54T/Mi7zHi299QjA8dJ3o4WCExxkW8vkQuex1YQhGjqTrQy34LgyCwSCNjY1p8VGPFdHJGtFxwyvr5iL5TrF1dyf5DjmhXzeRGI52LH0ierbLhwQxoqJqRgz1q/+2BIA7N+yONI3tK8ivaTr5TivPb7wpqffss6wHcm1E19yIFtBv3XgZeXYLB4+28/v3TqImaK9ikU3UXTed9z76HF8gjM1ixh8I4LDbCYZVJrjs/F93XBnzXonqRCdLJG5ZNmOzGII8mspx2fZdHYxcGeu48lEL0ke89ez2hga0mG/7sr03lTsuu9E+vOzGZIn20X930x84caaHkKKi64YAocPUiefTvaMzL/sK8iebeRkKqwSCypB1nqNrbmiajqrqePxhnn71UD9xNklGey+HTUYyQVG+g+trqigrckSSV3RdJxhWE1rL0XWikyGmpGevMKeiznLfd2SgGt+C7EQI9TghUapzS7uP8qJYP+j5RBJ70rHHqearcydy8vOeSB9AXTeE8KtzJ0aeU3fddJ546QOjhobe1wVFpccb5N5H9vRz42iajj+k4PcrRqPZJNaJrV0+JF2PcWlEM6k0j8rSPD5u6iAUNlwnIUXDYTNHhDi6q8qZtiATC+0jKlkacWNYzBEXRnzc8mjrxUR/R5Kt8S3IDoRQp4l0dF8ZjET+ZotZoqsniMtxfjM1OhLCSOW2Rixqa69FfehYB8vTNlLjfYsK7P0s+fj3Nbxyxq6jqmmE/Coeq5lClxW3N8DzOz9CAqZNKUyqAaym65w40xNpR9Xd2z09GqtsYkK+je/9/ZcoK3TQeKydIye7kCTNsPzpH3bXZy33uc6GIr4mRjJujFTUi4n+jiRT41uQPQihTgPpqns8GK2dPkzonO72RMTPYTPj9ikEQglqW/hO9aZy22IKMOm6nvamun0p5EVR4WHx7/vq3qO4nBZKCx14fT7OeTUkSSMUUvEFFCyyCVXX2P72Eb7391cM+F6BkMLHTV0cPNpG47EOeryhmMclyVhl5NllTGYJXYO//9pllBUaK5G3/nwSp12OGWswPHhJ0vjz9y9UNPwsv1Rs/GZTE2XB8BBCnQaSLQWaSovbYTNzqtWDSTrfSCAUVshzyHS5Q/26tTQ0nBqzprqJ3vecJ0ggpEXcGn3lVs0mCYdNRtXBZJIIBA33RzCsoWk6eZ7+VnFnTyBSge6TE10ocY7qyhInc6eXMXd6Kb5gmN+/10xHt5+i/P6bfMmWJAUwm02YJSJ9+ywpTL1Opt72UGRTE2XB8BBCnQaGslxSZXFHi32PJ4im6ZhkI9xNBzTVKAZkkU2YJFAUlZ37jjOjqgiJ9DSqTYb49z3nCXLOHaIw39bbmitgxFibjNKnXd0huj3BSCy2pW9TTTIaJfS5NIzaze2cOuuJeT+TSWJGVWGkdnNZUawwzZ0+cHXFRCVJFVVnYkler6VsbPbJsomifBsVJXlpKemZTL3toUjU3zETn7dg9AihTgNDWS6pWMbGi33HOX+kQ4aqGWKmaRqqBprWP7Hk7usnpKUrdzLEv28gpBkiV+zEZjVhlgwLtOWsl568MKoSioi0yURvDQrDURxWVNY++ad+Lg2nXaa6t+PJFy8pxmkfWdLTgqsv4uW3jyCbJfIcVsCo9bH0hhlUxouypqSt7nIy9baHIlF/RxH1kRsIoU4DQ1mqqfAVxou91WImpKjIZonJvSFsR091A0QEXJJAVTROfu5mS70vEp41UKW8gUiF2yY6XO9ftuyl0GUjHNbw+IzazLquYzKbmOCyc6YtaNTHQEcJa73lBHsHuQAAIABJREFUTA00VY+IdEWxM2I1XzplAuZh1HiJ5sPP2nn3gxY8/hATS/O4+SsX81FTB2fafRRNsFN3/TSuzLC4JVNvOxkS9XcUZD9CqNPAUJZqKnyF8WJfmG/jbKePUFiLxPNCrwXai6pqkciIkYZnJXLbPPHSBxS4rPiDatLCHVY0gmGFQEDFabNw6qwbqxybYl1Zksdt10/n9/s/oqlNo+1cf7/w5LI8vjJnEnOml1IxQl9rdDLJsdPn+P17J9F1HZts4sSZbo6ePDfsWt+ppu87MzkqjjwQMlLpByPT0UeC9CCEOk0MVoQpFb7heLHPs8sU5tsIhNRIg9iwonG2009Ij40rtlpMMZ1UhuNyibfkVQ16vCF8gTBTyl2Dir+qakamYFCNJLsA1H5pMi++9Qm6bqwIvH7jOW5fmJ/8+4GYc5gkCVmWKC5wMHdGCU0tbt5paObg0fak4pcbj7Xzh4ZTuH0hJpXmseDLU5l7WVkkmeRnL/4Fty/Ue306NouMro99CFuy35loYXbaZM65AzEtzvo+G9EYK7cQQj0GpMI33JcQ0tYVQFE1ZLMRi/zDFfMi5/ntWx/z4luf9IsvzrNbACMSYrgul3hL/pw7aLhUND2h+PeVDw3EiXM0U8rzqZ5eyoEPW/EGwucf6P1nYZ6ZmtmTmTOtlOlVhksjOv07z2am2xPgP3Z+hMtpJRBS+9XtkCQ41tzN3vebwQQFTpnWTi/P7DgUYy1/3tHfLaWoOh83dSZMtMkUyXxn4lc7p856UVTNyKa0Sv0yUwW5gxDqMSIVZU/7EkLOJ2LEqmB8Yomm6SAZu/12i+ETGa7LJd6SDysaEiD3hqBZZRN5djthVaPjXICg0r/Ghq7r/KGhmbcPNHPOE4xUnotmUlkeX6meyNwZZbS1fEZ19YyYx6PTv8Howu7xhQmGVaaU5aGqKm/99wmK8m3MnV6GxWLmmR2NdPuC2CzG2M0mE7KsxVjL8dfnDSi0dfmRzQNH6GQqLXuo70z/1Y7Rof6cJ0heb9JTdGaqIHcQQp2jRCeE9BEIxS7R4xNLvAElyo8tjSg8K34JbjFLmM1mJpflUeCyEQobcc5hRefRf38vUpXuhpopmE0mDh5t5y+fnMXrD/c7t0WWyHdaMZskQiGViaV5VBQ7aUvQ8qQvvlk2G62iwqrOxFInug4FLhuqouMJhKh/9zO+PNtITW9udQ+5iRu/UtE0YyIsLnAkXDFkU1p2/GrHIpsIK2pML0oRN52bCKHOUZKJHBnMjx0IaSMKz+pbgu/cfxy3N8Ssi4tpO+c3fM8dRpNWX0BBkoyJQ9c0Tpzp5qlXu/qdSzYbySyBoIqiaZgkKZLuPlj2nyTBtMkTCIYULGYTiqrh9nkJ9zYY6AvFk5BojbsfyRShil6p9LXLHeg+Z1Nadvzn3bfBLPc22I3PTBXkDkKoc5RkIkcG82NLvlPDDs/SdZ2QonFZVSFVt85B1Ywo3khN53M+XE6jdogvoNDj7W81y2YJTdMpcFnJd1iQJInTAS9ybxJHH9HZf2azCdlkVJKzWs3YLGYW/82lPP3KQUxmQzjDYQ1F1SmPagwbfz+SKUIVv1I53eYlpKgx7oP4juqJJsyTn/ewbtu+jEZbxK92zCaw22QUReX4GXe/zFRB7iDaCucoyXY0GcqPPRSKquH1h+jqCdDa6aXjnB+3P4zSK9JhRUXHSMvWgZOfu3H7wii9fue+WhoShmU6scSJ2SzR4wkR6G0gIJtNqLrxU8KISrFZzUwqy+OF3Yep/+9unt5xiM9ausmzW5DNJq78Qjn/9M05FBU48PgVJpbmke+0YO61HhPdj74iVFbZhKYbk0FhvpVDxzoiz2nt9MVkIRbm20AnEvYYf9747jVg+IR9AWVUnXNGQs2sClbWzY3cE9lsuKbKihxcMjGfonwr7xxoTvs4BKlHWNQ5SjJRAIP5sQfa9Vc1o0ZIOKwRDGuEE5QM/fOHZ9i5r4nOHsNSj3/cIpuwmA03hs1q5mxXAMlklPGUJIlCl42O7gDn3EHsxQ7ynRZCYROlRQ6K820EQgpdPUF6vGG6egIo4RBn2j089crBmAiN+M216OYEie5HMkWokgl7jD5vorRstzeMw2amozsY42LJhDsk+p6s27YPRVUHrEcuyB2EUOcwR5q7+Ox0N/6ggscf5khzVz9hGtiPff4PNRQ2QueCQW3AKI3TZz0cPNrOnz/8PMbv24ckGXWlbRYzc6cXc7zFjdSbERlWVCQJCvKsALgcFuxWM4GQiivPxkUTbcyoKuTg0Q5OnfVQVuzEYpGRTOqwfL9DRUUk6y6Kj1e2mE3884orEp47UVp2lzuI16/E1OU4504c3ZJOkv38BdmPEOoc5bdvfcxLez4FCWSTYSm/tOdTAJYvmAnEClNfYXpV05g2pRBNkunqCfA/n7bx1nsnONPujWkRFVY0Pj1plAc9dLSDzp5AzPtLEtitZnSd3pRvsJghrKo0fNxGzaxyznnCdHT7cdgt5DtlygqdEbeCNxCiosTFhvuuiZzztuvPn//eR/akvCRnMkkjI4lxj0/LXrZ+J0hGcg4YZU41SSc8WLuZNGBsnroTbJ4mX8hJkB0IoU4T6U7drX/3s16RNrYZZMno0F3/7mcRob79hhn8asdB/IEwSBKqpqEohktjy2te8vPa6PGGcNplnDYzXT1+fv3Gh5QX53G6zUMwrutJyQQ7Hn8Ym8VkJLCEtdiWVZJR5lPVND463sX/8/1abLLMZy3nePGtj/EHwwSCCv5eP++3vjZzwOsbSZr9UPc8WREebYy7bJaQIBLap/d2XJfNmc0H7L95qhFyh1h4TQngHfL1guxBCHUayETjAH9QIbrMsUU24TCbkEwm/MFwpMBRWNXo8RoCKQGqDl3uIJoGPT7jj1XVdBRVi3QH95w2ijlJwCWTJzB3eilzppcyqTSP//v//TNn2r2YTBImEzE9CU2SEWXgsBrjqCjOw2ySKCmsNBrXDsNKHW5JzmTveSoSjYbiosqCBJasJeOWrLF5akvYweeyktS5PkQ9kfQjhDoNpKKMaSIim2VdPuxWI9nDZjEjy0Ys8f/f3rvHR1Xf+f/PM3PmlskdEsIlogUsFrzwJdqifqHyW0AJiA/ULWjR1m5Xfazapb+mheADFl3F2qwoXaHrdh9t1xtS1hKliFBZ7C5QDdSKtGARuQQJSch17pcz5/vHmTmZTGaSmWQmGcjn+XgoycmcM585yXmdz3l/3u/XOxAIISHR2qmZ6df+/gSqCiMLtIuyocWFElRRQt1zg93eoP51JESyZO6XmTphpB5XjqDGfGEwSFjNRmwWGbtVxutXcHgCgNSttVS8hb/e0tdSteTM1DnvD5GbzIgCeUA+3wMVwN476aRHqPs7KRHinhpCqDNAJloe/fFYE6+88xdsFplxJXbqQyHcXoUOp49AVOaFxSRRvWkfIwtsNFxwYjEbOd/i7vYaIKGLsdVsoHxUATdeMybuz71+hdIiG4FwXnak64rbG8Th8qGE2xx+Y86VCT9LqrPfZCw5+3vOkxGMVEUlHV4u6XgqG4yOLv25QQ5Fq7qLHSHUGSBdF0hQCWklwIEQ2/d9jqqq4UISP81t3rhi6wuoBDq9dDq9BBWtUUAqeHwhCnPjm+wbDTB5fDEX2ly0O3043AFUVeuwEghqo4kUVUTi5PHIxOy3vzHtvgSjv6Iy0BBLOs5Rr4unaapM7M8NMpuefi4WhFCngVhTnqsnjGBPXX1KNqYffdrEO384RbvDR2GumRuvHsOV44v0WfCJLzowSOBwBbTc5V7GE1IhlJqfvI4kwScnWrWvAaNBu6AsZiMWs5EvjcnjgyMN+gJVZAa9ZM6VvYpzNOl64oie6dosRlyeoH6sZM55MoIxVKKSjnPU28x+IJWJ0efd5QmgKEq33PS+bpCiyW7qCKEeIPFMefbU1TP58iLqjjb1aCobIVKOHQgqHD6uWXYqaghJhdYOD8fPtOtxYgCb2cgXzf1bqTcZJT07I9byFLRFQKMx7H5nBJPZoOU6W+RuVXoAH3+WeIFqaZLjSdZzozdiZ7q+gILPH8TjC+IPhuKe81iSEYyhEpVknhCSCcmke/E09rwr4RxxgMJcS1I3SNFkN3VECfkAiZ5xRdzVAorCvsMNFOWZmTSugDEjc6j783kOHm3E4fJxod1DY4tWjt3h9PNf//0Zbl9A74dnMRkxGiV2fXBGfx+3L7UQRjSjR9oZV5rbbXEvgkECi1nGbjMxosCK3W7BJBspyLX0EGnoWqAaW2Ln8tF5jC2xU5hiN+yrJ4yg3eHDH1QwSKrmpeHwcfWEEUkfI/a8K4qKL6DF4ZMtl45X/h0rGMm8JhP0ZREQEczBLlOPPe9FeZZw5WYIp0frONNXN5xk7Q8EXYgZ9QCJnnFFfC0M4T/gMSPtBBSVQEDB6Qmw5Xd/5XtLpvU4RsSyM5qIKZGihDhe3067w99jv2SQ0ITFLBv0XoMGg4TNbMRmlTEZtTCBL6DgcPlRQipf/z9jEx4vHbOhiOdG9KzcaJSo/f3n/K6uPqkFux4NDJw+DL00MIjH4q9P5IXNf6S5zYMSUjEaNDe/mdPG6RkpORYZZzjOnyikkg4/6niz4wd7WZDMppBMYa4ZpyfIz1fNSeoYQ9VU+WJGCPUAiRauvBwzsmzA51cIqSqNLW49lqyqKk1t8WedIwtsdDi9+gxWCak43H5UFf7/Db9PuYFpBAkoLrBQkGulrdOL3SpjtciYZSMefxCHO4DP7+2x38mGzoTHTEcbsVjPDZcnQHO7B1WFsmJbUgt28RoYgJZPHiGZEIXWNVwKm1VJBBSVHftO6u2rfAEFSZIwGg1xvT4S+VEfv76cT060JJUpkmjB8sHF1yRsPNzY6saAyhcdzqhmt6k92fSHdIUtBiOf/VJChD4GSOxjXJvDqxWjGA3dFvz8wRAjCuI3Ip1zQzk+v0Jrp5fGVjdfNLvodAVwuAO6SJtkQ3hxD+SeEYkeSEB+rokci4mV91/PT3/wdUwmIy5PgIYWF+0OX7fKQ4vJqDcCONdLLLziqlHMvr6cNoefkw0O2hx+Zl9fntJFFxtOaHf6UNE6qUdmw7KsFcgkIva8Gw0Sqhp2uwvTl4C8ufcz7DaZ8lG5XDEmn/JRuQSDITy+YLdQlt0mk2+38PNVc3j64Zt6GF/1DH2F2Pre8aTDEvGO0dfnt1mMNLd7CQZVDJJEMKjS3O7Faknij2MAiLDF0CBm1AMk+jGus9NFQZ6VayaW8IdPGvSQgz8YQlFU5n71Mn0/RQnx2dl2Dn92gcOfXaDd2T20IRslvnLFCK6eOJJrJo6kvtHBf+74Cx6fghJVDqiZwqMvFmrmRyasZhmjwUBhnkV3z/N4NWP/3ohnlB/NwaON7KmrpyjPTFmxDV9AYU9dPZPKi/qdNhapiIwW2b5mw7GPz2Uj7XQ6/RgN9DTJjxl/JMTQ1ullRL4Fomp6Ihk1XzS7umaqvcTg44UCXJ4ASkhNOizRnwVLKfJbktAbHKBGbc8QImwxNAihTgORx7g/fvQxZeUTUFW4fHQ+uz44Q0uHRzc7umJsAR/++TyHP7vAXz5vwe0LdjtOQa6Fa8LC/OXxRZijFvMKci3MnDaO9+rqCSohTCYDsiSRn2sOx7O9WMwyNotMUFF0836X18+Sx3fg8QWJs5YYhUpI1XwpivMtCasG0xEbrbhqFMevL6f295/jCZ+DXJtW2RjBF1CwWWSqN+1LGPuNfXx+fdcx/Zjxsj5iQwwdDonmdi+SJOlNASQJFEUrqY843zW3eSgfFb/8O14oICLw0fQmvP0JJ7h9QUqKbHQ4/V03lAKzfj4TkY54ughbDD4ZFWqn08mSJUv42c9+xrhx49i/fz/r1q3D5/Nx2223sXz5cgCOHj3KqlWrcLlcVFRUsHbtWmRZ5ty5c1RVVdHS0sIVV1xBTU0Ndrudzs5OfvCDH1BfX09xcTHPP/88JSUl+P1+Vq1axZEjR7BardTU1DBhwoRMfsSETJ0wkqkTRtLY6ubw8Wbe/cNpTpztIBTjIXpZWZ4uzuWj8sIx054cOXGBP3zSQL7dxMgCSzi1L0RhrhWDUYut+vwBzre49BQ8kxE6nF3ZIpG5tClccm4xGfXYbKQDjNlsIBAM9Xhsj8SL05GuFjsrb3f6aOv04fZ2ooYbCMhhT2vNT7nvXoTJzPRjbzLFBVaaWt20dnrJsWrxaP2JQu2apWr/xM9cj+dJYjBI2GPOUW/Cmyjuf/WEEQlvmBFxH1ti14/j9WtZF72d98Hq7yhKxNNLxmLUH3/8MUuXLuXUqVMAeL1eqqur2bhxIzt27ODIkSO8//77AFRVVbF69WreffddVFVly5YtAKxdu5Z77rmHnTt3MnXqVDZu3AjA888/T0VFBe+88w533303Tz31FAAvv/wyNpuNd955h+rqalauXJmpj5cQJaTZg27dc5w1Lx1gzUsH+K///ozj9e2EVBWTbODqCSO5Z96XWfcPN1H9rRtYcPOXuKwsP6FIQ1fXbZtFJtdmYmxJLmNL7BTkmnn2kf8bjo8HuuVJR8LAUtR/oGV9rFk6jl+vW8CK+2/gyvFFjCy0ceX4IkqKcrDb5ITx0nSkq8XGZM0mWQ/fRDrReHwBjMbk47bJxHlju7fYrTIlRTatg3k4tSzXZmJUsQ1ZlgipKrIsUVJoTbigG91VxetXKcq3cff/NwlFUalvdHCqoZP6RgdOdyBhHDe2M0tRvo3Z15ezp64+YZy7P7Hi/sTC+8NQpQ5eymRsRr1lyxbWrFnDD3/4QwAOHz7M+PHjKS8vB2DhwoXs3LmTiRMn4vV6ue666wBYvHgxGzZs4O6776auro4XX3xR3/7Nb36Tqqoq9u7dy6uvvgrAggULeOKJJwgEAuzdu5fvfe97AFx//fW0trZy7tw5xoyJ71uRTs41O9n6v82cOH+2m8kRQEGumasnaLPmyZcXdwtpJIvLG6CsOAezyYg/oIRT2xSa2rSsjZZ2T+Kdo/VfBZ9f4fnaBv3RNzqzoC8f6HRlfXRLrXP4MIYtQC8fnQ/AyXOduDxBiqIiDr3N3PvT7Be0GP/ky4v1c1C9aV94ptpVfNPXTDXWk+Tg0UYk6RTR2SS93YSjjxGhetM+AkqIDlcwbpeY/sSKB6t4R5SIp5+MCXVklhuhqamJkpIS/fvS0lIaGxt7bC8pKaGxsZG2tjZyc3ORZbnb9thjybJMbm4ura2tcY91/vz5QRHq/3jrz3xyqitborw0V1sInFTCZWV5uol8KkiASTZitRi5bFQuTa1upKibQLvTj9ev8J2ndhNMwpM+OuqS6NG3r3hpOhaT4qXWSYAcFdc1yQY95S7eOPo6ZrzXJ3OTSceNKJJNMqKgq6w60gIt2fNUf96Bw+3vtUtMqrHiwaoIFCXi6WfQFhNDoVC3WYWqaoUJibZH/o0m0axEVVUMBkOPfSLbU+HIkSMpvT7CVaOD+L25FOUaGF9iJtdmBDw4W87wl5Y+d9eRJAmTbMRmMWGWJSQUQqEQV4wIcOxzFwajVhLu9oZwekPkWCUMMXHvyBnoyuHu/h5Gg/Y+SlBbiPrV2x8hubUb3NXjVN6p8+Lxau8TUFRCCsz8ipVDhw7px9d67oWFyH02Je+I2PeAEEoIck0qLrd2MZuNKsGgSlunE5NRoq3T2WMcscesPeDGF9QWRQ0SWGSpx7hnX2Nj/1EnLe1eCnNlZl6TixQ1/nivmTjWxK/e/ogXXg9SmCtz41W5XDkm/gz70KFD1De0YTVLuIJdmTyqqlLf4I079nh4fX5tNq52lf2rqorX50/6GPHOUfR57+uc9pcck1Zpao668fqDIfJscr/fJ53jyyQDGWdvDpGDJtRlZWU0Nzfr3zc3N1NaWtpj+4ULFygtLaW4uBiHw4GiKBiNRv31oM3GL1y4QFlZGcFgEJfLRWFhIaNGjaKpqYnLLrus27FSYerUqVgslr5fGMN04EtRWR+pIklglrVqQZtZxmCQeizIXPvlMuqONtHm1GbVOTYTZeHZkNzZqXf+hi6RlsL/i4xJAkqL7RDyY8/JIUdVcXqC+h/J9OkwaWJXk9gxpelfCIp9j3GlObQ7vNhzTPosNsemsmCmVjRS39BG+eiiHuOINWXCIGM0hFCVEEaDAbNZZtLESUyP2mf6dFi6sO/xRV7TtQAnM6JQ87LYc9jDpImTepyTSOij/MN9PWauXn+Q8hG2Pu1aI1jeaiIY0ny99S4xkopfUdm4s7VfC3TR5z3ROU0Hao52zoyy1NV3EpX7F17T7XeRLMnY3GYDmRznoAn1tddey8mTJzl9+jTjxo1j+/bt3HnnnYwdOxaLxaJ/yNraWmbOnInJZKKiooIdO3awcOFCtm3bxsyZMwGYNWsW27Zt46GHHmLHjh1UVFRgMpmYNWsWtbW1VFRUcPDgQSwWy6CEPZLhyIkL7PrgDBc6PIyM6k1oNECOxaSVc0dVssSmkp1rdvKXz7XS67LiPE41OPB4g7i8QW1RrNBGY6tbS7FDE+Qcm4lFM7/EJydaaGp14/QEsJqN2K0yLrc224v36DsY6VfJdhBfSvwL4ODRRl7Y/Ec8viBKSNUWIoFRI+x6ml+q4YZ49Cfemo7wSWyXGIMkEVK0oqCBeDin4vHdX0SudfoZNKG2WCw888wzPProo/h8PmbNmsWtt94KQE1NDY8//jhOp5MpU6Zw3333AbBmzRpWrFjBpk2bGD16NM899xwA3/ve91ixYgWVlZXk5eVRU1MDwLJly1i9ejWVlZWYzWaeffbZwfp4vXLkhOaOZzRK5FqN+ANBdv3hNCMKrEyfPCpuSCdWINzeICFVpa3TR4dTeyxW0Rbi7FbNVKkoXzPHybWZeogddIl/NlaVpXpz+OVv/4zDHcAgSVplXvh8tHR4sFu1Fch0xEX7E29Nh1DFdok52+TEYJAoLrAm7WUylIhc6/SScaHes2eP/vWMGTN46623erxm8uTJbN26tcf2sWPH8vLLL/fYXlhYyM9+9rMe2y0WCz/+8Y8HOOL0s+uDM+TYZApzLVjMRoLBEJ0uP2/uPUHFVWVx94kVCJ8/SDhkSSgqxOHxBTnV0KkbCv3g3ukJwwOjinOYfX0knJC4vVWqObBDkTN7rtmFQdJSDQE9PBCIqrxMx0JZfxfgBipUsWIfUqGkyNatKEgs0A0fRGVihjEawGiUGJFvxR8I0RbuZ+jyBjnT6OQ7T+2OK26xAhEd9pZivtfizz1TwOKZ/eypq+fBxdcguc/GffRNtaPJULZVij4HxqhZdW8l5KmSjjBGf4kW+0jaYDTCw3n4IEyZMkDE7rQoz0JpkR2zyUhzu0cvFHF5gzS3eTBIJCwIiC1oUGOVOoqIoZDdJncrXuhPgUOq+6SriOL1XcdY8vgOFlW9xZLHd/D6rmO9vn5sSS6qSrjSU0UyaC4XVrMxaV/kZIhXjJKO46aKMEMa3ogZdRqRJMi1mrFZjd0WBu+YOaHbrKy1QytSKc5PHG+MffSVpK6ZdLRoR2t2at1J4nehTjUmm46c2dd3HeON3X8FCWSDtgj4xu6/AiRs73V/5VfY8MZHuL1Bvfw9x2ZiZKEVTz9tYRPRVxgjHf4ZyYwhmbi3KN2+NBFCnUbUkEJ+rrnH9p7xRpWSQqtuBATxxS1aIB6p2cOZBkePY0cXicTrTpJqfDXVfdJRRFH7+8/DIq19FlmCYChE7e8/TyjUFVeN4rFvTNPPqc0i0+7woiihbk8pqfhC94fB9M9I5oYhuntfmojQRxpRe0mgrrhqFE8/fBM/XzWHyZcXdxNYgMY2N83tnoSP/jddM6bLzjIKi9mY8FG4P4/Lqe6Tjkdyjy+IMSacY5To0wku+pzm2c3k5ph6tET7dQq+0P3hzb2fEVAUWjq8NHcEaenwElCUlEM/B482Ur1pH995ajfVm/b1a4yD5eUhGHyEUKeByEX2fG1DUhfZ4q9PxOkO6KY9n5/twOkOEgqphEIqLk+A1979tJtYf3KihaJ8KzaLjGw0YLPI2CwG3N5gQgP//sRXU90nHTFcm0VGibkDKaq2PVliDZcAXB7tnGZSuM6c76TD6ScY1PK4g0GVDqefM+cTd8mJJV0mRvHOgcgMuTQQoY8Bkuyjb3TsMMci692ye6ti3LzrU/2xva3Ty4gCq25rGWlfJQGXj85LaODfnzSxVPcZaCraoplf4o3dfyUYCmGUNJFG1bYni9bZ3NGts7nPr2Axpy5cqcR5g4qWaWI0SIRCEgaDRDCkdqsS7Ytki2r6Gpfo7n3pIoR6gERfZK6gP+5FFhs7PN3gIBhupmo0SvgTOCqFVPRZVocDmts8msm9VY7bvqrN56Pm1UPYbaak47HZsPgUiUPHmv4nik/H4+oJI/jL5y0gaWETf1Dr1BIbYupLuFKN85qMBrzh7BMVVctCUbXtyZLMgmwy4xrKVEJBZhFCPUCSuchiZ0yRtlmR0ufe0E3u8600tXlo7fCSY7H3aF/l8gZp6/QSUsHrC9Lh8LHhjY947BvTEgpvNi0+LZ07OSVhjkXrbG7p1tncZJXw+hS8/uSFK9WS8fKyPM41O3F7g/gDYTtSu8yYKJvUvkhmJpzMuETpdnZMPDKBEOoBksxF1tjqxiB19eHrh2cTdpuJElWlpdOH0xPEapF13w7QSqdDqpYiKBs10/tOl59f/fYvCf9QLyXfYK2zuZmiqL6LqqrS0uGjKN+WULhiL+z68w5GFHQ35eotXNJV6m0hGADZZEl5FpvMTDjZNMjBKN3OVjHMpolHuhFCPUAWf30iL2z+I81tHgJKCJPDgc0i853br9Zfk2OROXO+s0cOdF/YLN0fnwNKCLPJiAqMLLTS6fTrs8XIDNsoab1cDBKoksoXzc6Ex7+UfIMT3TDLy/K6NUaIJt6F7fZqnWWKkuxmHj2XNtyBAAAcPElEQVSL7a0sP957xyvtT3RDiReDz7HKjCmJ38uxr/ftb853NovhpTTxiEUIdRoIKCr+gDZT9odCyHJ3NXZ7u7fI6guDQWLKFUU0t3l1IW53+mh3+CnMs5BnC/f3U1Vko1aJFymIMUbFRvtqVaBd/M44F3/yj+3ZQn/is/Eu7Dy7iU6XH5vFmPRxUnWk6620P5GgxIvB+x1+5n1tRJ/vF+99+5vznc1ieClNPGIRQj1AfvXbv+D1BZFlA6oaQpIMeH3BbiGHlk5vr8eIWHTkWE1s/uf5+vZo60+vP0RhnkWf6UUulDy7mZ/+4BYeqdnD2UYnoXDfQTVsOD+u1N7j/SL0vPgV/A6FeV8bP5BTMiSkqzVVYa6FoKL2Gi4ZKP3J8nB5AthtMoGgqsfgc6wyn5xo0d0RU3nfRAvffZHNYngpZ70IoR4gXzQ7kSQ0v2BVs9yMDTmEwtPpiCBHhz/MstRnOpoK+ANKrxfItyqndPNnNhok7BYT36qcknDs2gKcudsCXKoXfzaRrtZUl5XlJwyXpIP+ZHlEemKWFufo6xKqqqYkkOkQ2WwWw0s560UIdRqIDTFIaBdR9aZ9NLa6dWGOF58OhrTCjuuvKuWTEy38Luymd/WEEeypq9cv1A6HRHO7V0vPC5eex/Yy/N6S/5PyjLIw10JRXpfvR6oXf7oYigWqobqw+5PlYTYZ8AdDuv94vH3S8b59kc1ieClnvQihHiBjSuycbXRCSEVVtcpCJRx+iORAtxqlbgUQUthdafzofH76g1vixiy3vnc8XBathTqKC6w0tbpp7fSSY5XjXiDZ2uy0L4ZqgWqoLuz+ZHkU5lpobvfgD69N9Ecgo9+3v+X+2S6Gl2rDAiHUA+RblVP4yct1ePxKuK+dVm04It+iC2CkTZaqaguFslELMdxf+RUgfsxSCZeSR2LSdqtMSZGNlg4vTk8wLRdItsyOhnKBaigu7GTELvYmareZ8AcVvP5Qv3///c1QiXecS1EMsxkh1GnAYpZRQhAIKphkI/6g0q0yzW4zkW830eEK6NVy104ayZt7P2PTm4dp6/Ritxo1Q59w9oXRIBGIqViUjRKTLy9OW/w0W2ZH6Vqgytb83nj0JXbxbqImo5FH7k1cwJTK+14sDWMFGkKoB8ibez/DYNA8HqRwayijQaLN4SM3R7M8dXkCONxBzLKRcaV22p0+/udP5yjMs1CYa6a1XaXdGdBKyg0SwaBKUAkhGaC+0dnlt2yV+c7tA5vtxsujzeTCWTKkIwSTzfm9/SFbbqKC7EAI9QCpP+/A4fbrQh1UQoTCpjz1jY6uMnEViou1RgFubxAkrWFtUZ4Fg1GCkOYTIUuS1kVc77elhrNF1F5tVJNhML2TUyEdIZhszu/tLyLEIIgghHqABJQQxKTndbkoS3obLaNB0tM+AkHNJS4S2giF0+m0hUgwyQZAJRSC8lFdlWdef+/C8/quYz2MjSaVF3XLxbWaDeTmWPudR5sJ0jF7zOb8XoFgoAihHiCyUevVF4rK+kAFgwTlo7QKvy+aXfiDCu1OH3abSbPgDCigwqkGB6EQIKlYLbJuY3ryXGdYsLvoTXhe33WMzbs+1SsgXZ4Ar7/7KTlWmaJ8i56L6/ODOapNWKbELNV48UBnj9mSwSLoHxfT+sJQIIR6gFxWlq97MPgDYJIllJBmPxqhMM9CU6tbKzNXVYxGAyGfgsGgYpBAQUUNaftGUq8MBgl7zAyxN+F5878/61GmrqKFV0aP1MTfbDLi9QdpDPdgNLuc/fKL6It48eKfvFxHSNVKn/tjY9oX2ZLBIkidS219IROIDi8DZPHXJ2IyGhlRYKWkQGZEgRXZaOjWD9FulSnMs2C1yDg9QVQVcnNkLCYjIVXrnG0xG3B6urq13HTNaExGY9Itrrz++A1do7XbajbqpeVAuIDCz9UTkveLSIbYllAudwC3T8HrV7o1r+2r03gqZEu3cEHqiBZifSNm1AMkXm7qzGnj2FNX380H2etXCAYVmts14bWZDURqGiMLkBKS3q3l2Km2Ph3VUsXrD2IwAKq2UmmWjRkpGY+NF3e4/PrXkmRIqnltfxCLbxcnYn2hb4RQp4F4uamRRTztj00rXonG7evZ1cVskvQZhZcgn5xoSTp1TpISW6hGW6FKSJSOyIGQH3tOTkZKxmPjxZEZvBRVa59M81rB8ECsL/SNCH1kiOgO2a2dvoSvi/YJCQRCnGpw8EWzi6CSmoCOL8uPu720yKaHA6wWLQQT8YqAzFwQsZ3JIwItRxUBpdq8VnDpko5O9pc6QqgHgdgKw2jUmK+NBi0U0tzmSUnI7q/8CnarrIuiJGmx8YfvvFa/Yfzg3ulaj78MXxCx8eKRhVYMUrivoBoiGAql3LxWcOlScdUoZl9fTpvDr6/RzL6+XISxohBTmjQQr9oP0NONekOvawmjql0b1BSbdplNRoKKqlcyRmeeQPq8HpIhNl4cL8c7nfFpwcXLwaON7KmrpyjPTFmxDV9AYU9dPZPKi4RYhxFCPUAOHm3sZsrUceICfz3dis0ik5tjIs8m09TL/rFSHFJVTLKBArsFry9+Jkc8upWyhyT969hilqHyehho81pBehhoK65McClWlaYbIdQDZON//Ql3lKCqKvgCIQIBPyMLbYAWgnB5+144k4DLR2uxZq9fSzFLluhS9kj4pN3hQ1EGVnYuuHTIVguBbMv6yMbiGxGjHiAX2rU2W5GehZEYcXRUOqRqhS19ItHv2HF0KbvW3FYbUEBJHB8XDC+yNV95VHGOVqkbxVBlfURuZhEv+cjN7ODRxkEfSzSDPqP+9a9/zSuvvKJ/f/bsWRYtWoTH4+HQoUPYbNos8pFHHmHOnDns37+fdevW4fP5uO2221i+fDkAR48eZdWqVbhcLioqKli7di2yLHPu3DmqqqpoaWnhiiuuoKamBrs9cd/AgZKMT1IgGBZRtHBEsBfx7K/XcHQpeyRVTwpvFwgg+2auEbKpqjRbwzCDPqO+++67qa2tpba2lpqaGkaMGMEjjzzCkSNHeOWVV/SfzZkzB6/XS3V1NRs3bmTHjh0cOXKE999/H4CqqipWr17Nu+++i6qqbNmyBYC1a9dyzz33sHPnTqZOncrGjRsz+nms5vCCnaqb3enUNzo41dCJomgGS5JBy+pIRI7VxM9XzeHph29K+Y/isrJ8rBat4YA/GEIJad4hlyVI2xMMP7Jp5hpNNlWVNra6scQswmfDzWxIY9T/9E//xPLly7HZbJw7d47q6moaGxuZM2cOjzzyCIcPH2b8+PGUl5cDsHDhQnbu3MnEiRPxer1cd911ACxevJgNGzZw9913U1dXx4svvqhv/+Y3v0lVVVXGPsPiWyby2ruf6voc+TdSrq2qXbkbakhFlRLPcF2eAIuq3orrfNdXrCzSUVwygFnSGuZ6vMG0l4dnM9kYW8wm0tGKK1NkS1VpthbfDJlQ79+/H6/Xy2233UZ9fT1f+9rXWLNmDXl5eTz44INs3bqVnJwcSkpK9H1KS0tpbGykqamp2/aSkhIaGxtpa2sjNzcXWZa7bc8kk8qLsNtMuD1a9xYJkAxaA9pIG61TDQ5UNRT22eg9VhLxwti861Nsli7nu3gLP9HC5PIEsFmNKIp6SXQUT5VExj7Hw2X4QrwHNz3zYiWbwjDRDJlQb968mW9/+9sAlJeX67NggGXLlrFt2zbmzZuHFDUD1arcJEKhUNztkX+jif2+L44cOZLS63/1XjNWU4j8KBOmxrYA7Q4vDpcPJaQSUrti2VIfQq2qWjwqoGrOd/k5Eu5wwkggGOJXb3+E5C7hr+c8vFPXjsEIJqOExxtEkiA/x0ChXQ4fS6G+oY1Dhw7Ffa9E27ORvsb6q/eaCQSDSBj08+X2KGzZ/SkFuUZMRolzTT42vF7HbdcXcuWY5DNq0jnOoUYC7rzBCozWNrjPcujQ2aEcUlIM1nmVgNnX2Nh/1ElLu5fCXJmZ1+QiJXmeBjLO3tJlh0So/X4/dXV1PPPMMwB8+umnnDp1innz5gGa8MqyTFlZGc3Nzfp+zc3NlJaW9th+4cIFSktLKS4uxuFwoCgKRqNRf30qTJ06FYvFkvTrN+7cjclkpN3pxx8IYjbJ4QXDcGeXGIwGKe72CAZDOIitKKiAPafrkStHVXF6gkyfPp3/+nAfdrtVf0TrcGue196AxIhCbR+vP0j5CFvcP4CLqWdeMmPduHM3hXmWbjfmNqcTFYmi/Fx9m9cf5JOzEksXpv+zX2rnNMJQh5QG+7xOnw5LF6a+XybHOSTpeZ9++imXX345OWERUlWVp59+mo6ODgKBAG+88QZz5szh2muv5eTJk5w+fRpFUdi+fTszZ85k7NixWCwW/e5VW1vLzJkzMZlMVFRUsGPHDgC2bdvGzJkzM/pZciwyzW0ercdhuBVXsJfc5ZCa/Aw/9mEgOlYWu+hRmGcBFd3zOpvij4NBvIWySKPgaLJhYehiIlvT1YYbQzKjrq+vp6ysTP9+8uTJ/P3f/z1Lly4lGAwyd+5cFixYAMAzzzzDo48+is/nY9asWdx6660A1NTU8Pjjj+N0OpkyZQr33XcfAGvWrGHFihVs2rSJ0aNH89xzz2X0s6hd9d49ywzjcPnoPD4725H4eGoIJdwhxmaRu1mlRgtv7KJHxPPa61e6pfgBVG/ad8nHaOPFFlNtviDoSbamqw03hkSo58+fz/z587ttu/fee7n33nt7vHbGjBm89dZbPbZPnjyZrVu39tg+duxYXn755fQNtg88PoWSQisdLr/e4SXQR+W30QDxUqklCYIhemR9xPOjjidMJqOBR+69rttiY6LOGZdadnW8vovxfMGH01MGDDxska2518MNUUI+QCIz27Elubjcbuw5OX3MmFUK86y0dHi7bTfLEiu/9dUeF1Gii6riqlEcv768h9FR9Ot7mw1pC0qXFvFSvHq72V3qpONGna3pasMNIdQDJF5uaiIMBq3yMDfHhNPtxx/UUvYkCUyyMeF+8UjGcaz32dClJ9TxyJb83KEgHTfqbE1XG24Ir48BEl1V5fWrFOXbKMg1k2PpfmpzLAZKCnP4+ao5AAQVFdlgwCwbkA0GvH6FX/72z0m/bzK+DdlaiSYYHNJRZZdNVYPDGTGjTgOx1qHVm/bR1ulhTNTjYrQb3rlmF6D1DYzMqA2SpG9PhmRih73OhtzZnzsrGBjpClsM56eSbEHMqDNAX62FQmo4xzos0qiEC2OStyRNZrYsZkPDm8FqcXXwaCPVm/bxnad2U71pn0jdywBiRp0B4mUgRC9iyUYDihIW2ShtlntzbIoh2dihmA0NX3r7O0xXNWJvC5bi7y59CKHOEL0JpNVsJBhUuqXoGQ1RTnxJHr+3m4FAAJm/UYs868FBCPUQcFlZPueaHbi9Qb16LscqM6YkL6XjiNmyYKgRedaDg4hRDwGLvz4Rk9HIiAIr48vyGFFgxWQ0ipQnwUWHyCwaHIRQDwFikU9wqTBYC5bDHRH6yBB9le6KsIXgUkCslQwOQqgzQKZWwofablIgiIeYdGQeIdQZIBMr4SINqifixiUYLogYdQbIRIPMZErGhxPCJ1kwnBBCnQEysRKerd2Rhwpx4xIMJ4RQZ4BMrISLNKjuiBuXYDghhDoDZCL9TqRBdUfcuATDCbGYmCHSvRIu0qC6I3ySBcMJIdQXESINqgtx4xIMJ4RQCy5axI1LMFwQQi0QCC4KhnPevFhMFAgEWc9wz5sXQi0QCLKe4Z43L4RaIBBkPcM9b14ItUAgyHqGe968EGqBQJD1DPeCLyHUAoEg6xnuzTZEep5AILgoGM5582JGLRAIBFmOEGqBQCDIcoRQCwQCQZYjhFogEAiynCFZTFy2bBmtra3Isvb2TzzxBGfOnGHTpk0Eg0Huv/9+7r33XgD279/PunXr8Pl83HbbbSxfvhyAo0ePsmrVKlwuFxUVFaxduxZZljl37hxVVVW0tLRwxRVXUFNTg91uH4qPKRAIBGlh0GfUqqpy6tQpamtr9f/KyspYv349r732Gtu2beONN97gs88+w+v1Ul1dzcaNG9mxYwdHjhzh/fffB6CqqorVq1fz7rvvoqoqW7ZsAWDt2rXcc8897Ny5k6lTp7Jx48bB/ogCgUCQVgZdqD///HMAHnjgAW6//XZeeeUV9u/fz9e+9jUKCwvJyclh3rx57Ny5k8OHDzN+/HjKy8uRZZmFCxeyc+dOvvjiC7xeL9dddx0AixcvZufOnQQCAerq6pg3b1637QKBQHAxM+hC3dnZyYwZM3jxxRf55S9/yebNmzl37hwlJSX6a0pLS2lsbKSpqSmp7SUlJTQ2NtLW1kZubq4eUolsFwgEgouZQY9RT5s2jWnTpunf33XXXaxbt46HH35Y36aqKpIkEQqFkCQp6e2Rf6OJ/T4RqqoCcOTIkX59rgiHDh0a0P6DiRhr+rlYxglirJlgIOOcOnUqZrM5rmYN+oz64MGDHDhwQP9eVVXGjh1Lc3Ozvq25uZnS0lLKysqS2n7hwgVKS0spLi7G4XCgKEq31ydDIBAY6EcTCASCfnPkyBH8fn/cnw36jNrhcLBhwwY2b95MIBDgN7/5DT/5yU+oqqqitbUVm83Grl27ePLJJ/nyl7/MyZMnOX36NOPGjWP79u3ceeedjB07FovFwqFDh5g+fTq1tbXMnDkTk8lERUUFO3bsYOHChWzbto2ZM2cmNS673c6VV16JyWRKehYuEAgE6cRsNsfdLqmRZ/5B5Pnnn+fdd98lFApxzz33cP/99/P222/zb//2bwQCAe666y6++93vAnDgwAE9PW/WrFmsXLkSSZI4duwYjz/+OE6nkylTprBu3TrMZjNffPEFK1asoKWlhdGjR/Pcc89RUFAw2B9RIBAI0saQCLVAIBAIkkdUJgoEAkGWI4RaIBAIshwh1AKBQJDlCKEWCASCLEcItUAgEGQ5QqgFAoEgyxFCnSbefvtt5s+fz9y5c3n11VeHejg9cDqdLFiwgLNnzwKafezChQuZO3cu69evH+LRdfGv//qvVFZWUllZybPPPgtk71hfeOEF5s+fT2VlJb/4xS+A7B0rwI9//GNWrFgBaDbBixcvZt68eaxatYpgMDjEo9NYtmwZlZWVLFq0iEWLFvHxxx9n7bW1Z88eFi9ezG233cY///M/Axn8/auCAXP+/Hn1lltuUdva2lSXy6UuXLhQPX78+FAPS+dPf/qTumDBAnXKlClqfX296vF41FmzZqlnzpxRA4GA+sADD6h79+4d6mGq+/btU7/xjW+oPp9P9fv96n333ae+/fbbWTnWDz74QF2yZIkaCARUj8ej3nLLLerRo0ezcqyqqqr79+9Xv/rVr6o/+tGPVFVV1crKSvWjjz5SVVVVV65cqb766qtDOTxVVVU1FAqpN998sxoIBPRt2XptnTlzRr355pvVhoYG1e/3q0uXLlX37t2bsd+/mFGngUQ2rdnCli1bWLNmje57ksg+dqgpKSlhxYoVmM1mTCYTEyZM4NSpU1k51htuuIH//M//RJZlWlpaUBSFzs7OrBxre3s769ev56GHHgJIaBM81KRigTzU7N69m/nz51NWVobJZGL9+vXYbLaM/f6FUKeBRHas2cJTTz1FRUWF/n22jnfSpEm6eJw6dYp33nkHSZKycqwAJpOJDRs2UFlZyYwZM7L2vK5evZrly5eTn58P9Pz9Z4sdcCoWyEPN6dOnURSFhx56iEWLFvHaa69l9PcvhDoNJLJdzVayfbzHjx/ngQce4Ic//CHl5eVZPdbHHnuMAwcO0NDQwKlTp7JurL/+9a8ZPXo0M2bM0Ldl6+9/2rRpPPvss+Tl5VFcXMxdd93Fhg0bsnKsiqJw4MABnn76ad544w0OHz5MfX19xsY6JD0TLzXKyso4ePCg/n0q9qpDQSL72Gzg0KFDPPbYY1RXV1NZWcmHH36YlWM9ceIEfr+fq666CpvNxty5c9m5cydGo1F/TTaMdceOHTQ3N7No0SI6Ojpwu91IkhTXJnioOXjwIIFAQL+pqL1YIA81I0eOZMaMGRQXFwPwN3/zNxn9/YsZdRq48cYbOXDgAK2trXg8Hnbt2pW0vepQcO211+r2sYqisH379qwYb0NDA//wD/9ATU0NlZWVQPaO9ezZszz++OP4/X78fj/vvfceS5Ysybqx/uIXv2D79u3U1tby2GOPMXv2bNatW6fbBAO6TfBQ43A4ePbZZ/H5fDidTt0CORuvrVtuuYX//d//pbOzE0VR+J//+R9uvfXWjP3+xYw6DYwaNYrly5dz33336Tat11xzzVAPKyEWi4VnnnmGRx99VLePvfXWW4d6WPzHf/wHPp+PZ555Rt+2ZMmSrBzrrFmzOHz4MHfccQdGo5G5c+dSWVlJcXFx1o01HjU1Nd1sgu+7776hHhK33HILH3/8MXfccYdugTx9+vSsvLauvfZa/u7v/o577rmHQCDATTfdxNKlS/nSl76Ukd+/sDkVCASCLEeEPgQCgSDLEUItEAgEWY4QaoFAIMhyhFALBAJBliOEWiAQCLIcIdQCQYZ4/fXXeemll4Z6GIJLAJGeJxAIBFmOKHgRDHtcLhcrV67k9OnTGAwGpkyZwhNPPMHevXvZtGkTgUAAq9XKj370I6ZNm8ZPf/pT/vSnP9HU1MSkSZM4dOgQL774IlOnTgXgH//xH7nhhhtoaWmhra2N1atXc/LkSVavXk1raysGg4GHH36Y+fPn09jYyBNPPEFDQwOBQIDKykrd5U4giCBCH4Jhz+7du3G5XNTW1rJ161YAzpw5w/r163nppZfYtm0bTz75JI8++ihutxvQrEJ/85vf8Nxzz3HnnXfy5ptvAtDR0cGBAwdYuHBht/f4/ve/z6233spvf/tbXnrpJZ577jmcTidVVVX6/lu3bmX//v3s2LFjcE+AIOsRM2rBsGf69OmsX7+eZcuWceONN3L//fezb98+mpqa+Na3vqW/TpIkzpw5A8B1112HLGuXz5133sldd93FihUr2L59O7NnzyYvL0/fr729nWPHjnH33XcDMHr0aH73u9/hdrupq6ujo6ODF154AQC3282xY8eYP3/+IH16wcWAEGrBsKe8vJzdu3fzwQcf8Ic//IFvf/vbPPjgg8yYMYPnn39ef11DQwOlpaXs3r2bnJwcffvYsWP5yle+wt69e3nzzTeprq7udvyIoEdbXn7++eeUlJSgqiqbN2/GZrMB0NraisViyeTHFVyEiNCHYNjz2muvsXLlSm6++Waqqqq4+eab6ejoYN++fZw4cQKA999/n9tvvx2v1xv3GH/7t3/Lv//7v+PxeJg+fXq3n+Xm5jJlyhS2bdsGaIK/dOlSvctKpN9iZ2cnS5cu5b333svgpxVcjIgZtWDYc8cdd/Dhhx8yf/58bDYbo0ePZtmyZUyYMIHvf//7qKqKLMts2rQJu90e9xizZ89m7dq1fPe7343783/5l39h7dq1vPzyy0iSxFNPPUVJSQk1NTU8+eSTLFy4EL/fz4IFC7j99tsz+XEFFyEiPU8gEAiyHBH6EAgEgixHCLVAIBBkOUKoBQKBIMsRQi0QCARZjhBqgUAgyHKEUAsEAkGWI4RaIBAIshwh1AKBQJDl/D9ZTg67sL7R8QAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.lmplot(data = df, x = \"service\", y = \"salary\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "График получился вполне наглядным, построена регрессионная прямая с добавленным 95%-ным доверительным интервалом для нее (закрашенный «коридор» вокруг прямой, который показывает, где с 95%-ной уверенностью эта прямая может лежать, если мы учтем, что регрессию можно строить и на других выборках, на которых значения оценок коэффициентов $\\hat{b}_0$ и $\\hat{b}_1$, определяющих вид и наклон прямой, будут другими).\n", "\n", "В завершение занятия давайте посмотрим, как выглядит взаимосвязь между стажем и заработной платой, отдельно для сотрудников мужского и женского пола:" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# добавляем цвет hue в зависимости от пола sex\n", "\n", "sns.lmplot(data = df, x = \"service\", y = \"salary\", hue = \"sex\");" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# можем разбить на отдельные графики – столбцы col, для наглядности\n", "\n", "sns.lmplot(data = df, x = \"service\", y = \"salary\", hue = \"sex\", col = \"sex\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "На этих графиках изображены регрессионные прямые `salary ~ service` для каждой группы наблюдений, для каждого значения пола отдельно. Здесь можно заметить довольно интересную особенность: средняя заработная плата женщин ниже (оранжевая прямая пересекает вертикальную ось ниже, чем синяя), но при этом с увеличением стажа она увеличивается быстрее (оранжевая прямая более крутая, имеет более сильный наклон). Это можно воспринимать как сигнал, что в последующих более сложных регрессионных моделях стоит учесть не только то, что заработная плата связана с опытом работы и полом сотрудника, но и то, что характер связи неодинаков у мужчин и женщин. Этот разговор мы оставим на потом, для него нам понадобятся модели с эффектами взаимодействия, а пока построим обычную модель множественной регрессии с двумя независимыми переменными, стаж (`service`) и пол (`sex`):" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "model2 = ols(\"salary ~ service + sex\", df).fit()" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " OLS Regression Results \n", "==============================================================================\n", "Dep. Variable: salary R-squared: 0.120\n", "Model: OLS Adj. R-squared: 0.115\n", "Method: Least Squares F-statistic: 26.82\n", "Date: Sat, 08 Oct 2022 Prob (F-statistic): 1.20e-11\n", "Time: 15:49:24 Log-Likelihood: -4633.9\n", "No. Observations: 397 AIC: 9274.\n", "Df Residuals: 394 BIC: 9286.\n", "Df Model: 2 \n", "Covariance Type: nonrobust \n", "===============================================================================\n", " coef std err t P>|t| [0.025 0.975]\n", "-------------------------------------------------------------------------------\n", "Intercept 9.236e+04 4740.188 19.484 0.000 8.3e+04 1.02e+05\n", "sex[T.Male] 9071.8000 4861.644 1.866 0.063 -486.208 1.86e+04\n", "service 747.6121 111.396 6.711 0.000 528.607 966.617\n", "==============================================================================\n", "Omnibus: 24.056 Durbin-Watson: 1.863\n", "Prob(Omnibus): 0.000 Jarque-Bera (JB): 26.987\n", "Skew: 0.584 Prob(JB): 1.38e-06\n", "Kurtosis: 3.515 Cond. No. 100.\n", "==============================================================================\n", "\n", "Warnings:\n", "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n" ] } ], "source": [ "print(model2.summary())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Сконцентрируемся на коэффициентах. С добавлением переменной «пол» в модель в выдаче появилась немного странная запись `sex[T.Male]`. Почему пол сотрудников представлен здесь таким образом? Переменная `sex` в нашем датафрейме `df` является текстовой, там всего два значения, `Male` и `Female`. А текст в таком виде в числовую модель добавить нельзя. Поэтому Python упорядочил значения `sex` по алфавиту, за первым (`Female`) закрепил число 0 и метку `False`, а за вторым – число 1 и метку `True`, а затем уже этот набор из 0 и 1 добавил в модель. Чтобы мы не запутались, к названию переменной `sex` он дописал `[T.Male]`, подсказывая, что значение 1 или `True` соответствует сотрудникам мужского пола. \n", "\n", "В итоге получаем такое уравнение:\n", "\n", "$$\n", "\\widehat{salary}_i = 92360 + 747.61 \\times service_i + 9071.8 \\times Male_i.\n", "$$\n", "\n", "Проинтерпретируем коэффициенты (судя по p-value, они все значимы, правда, коэффициент при `sex` только на 10%-ном уровне значимости): \n", "\n", "* Среднее значение заработной платы за 9 месяцев для сотрудников без опыта работы (`service = 0`) женского пола (`Male = 0`) равно 92360 долларов.\n", "\n", "* При прочих равных условиях, у сотрудников, чей стаж на 1 год больше, заработная плата, в среднем, выше на 747.61 долларов. То есть, если мы сравним двух коллег одного и того же пола (смысл «при прочих равных» для данного случая), в среднем, заработная плата того, кто работает на год больше, будет выше на 747.61 долларов.\n", "\n", "* При прочих равных условиях, средняя заработная плата мужчин выше средней заработной платы женщин на 9071.8 долларов. То есть, если мы сравним двух коллег с одинаковым стажем, но разного пола, в среднем, зарплата коллеги мужского пола будет выше на 9071.8 долларов (смысл коэффициента при `sex[T.Male]` с учетом уточнения «при прочих равных»). " ] } ], "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": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 2 }