0. Введение
Национальный корпус польского языка — вещь достаточно неудобная. Настройки в одном месте, выдача в другом, скачать можно только в html (хотя обещают, что можно и в Excel). Как было славно, если бы можно было сразу собирать в R выдачу и ее там анализировать?
1. API для польского корпуса
Для того, чтобы решить данную проблему я написал API (в этом мне немного помог Даня Алексеевский, спасибо!). Так что я написал на R достаточно неуклюжую, наверное, функцию pl.corpus
.
Чтобы не заставлять читателя разбираться в коде, поясню, что в результате в вашем окружении появляется функция pl.corpus
со следующими аргументами:
x
— запрос (обязательный аргумент);
tag
— логический вектор, отвечающий за то, нужны ли в выдачи морфологические теги или нет;
n.results
— переменная отвечающая за максимальное количество примеров в выдаче
corpus
— вектор, определяющий подкорпус, в котором следует искать (возможные значения: "nkjp300"
, "nkjp1800"
, "nkjp1M"
, "ipi250"
, "ipi030"
, "frequency-dictionary"
)
Приведу пример работы функции:
head(pl.corpus("witam"))
head(pl.corpus("An*a", tag = T))
head(pl.corpus("[base = 'witać']"))
Как видно из примеров, функция понимает самые разные запросы:
- простые
- регулярными выражениями
- Corpus Query Language CQL
2. Данные
Данные о польских городах я взял из Википедии. Были выбраны все города с населением больше 35500.
library(lingtypology)
miasta <- read.csv("https://goo.gl/1zZgOa")
map.feature(languages = "Polish",
popup = miasta$town.names,
latitude = miasta$lat,
longitude = miasta$long,
control = F)
Как видно из кода, для создания данной карты требуется написанный мной пакет lingtypology
. Данный пакет позволяет рисовать карты на основе названий языков, вставляет ссылки на данные языки в базе данных Glottolog.
Для дальнейшего исследования следует построить список запросов, которые бы можно было вставить в функцию pl.corpus
. Здесь таилось множество проблем, связанных с особенностью корпуса:
- в самом простом случае достаточно было лишь написать название города
- иногда приходилось менять большую букву на маленькую
- все города, содержащие дефис, следовало разделить на два отдельных слова
[base = 'Bielsko'] [base = 'Biała']
- некоторые города либо целиком, либо частично совпадали с какими-то польскими словами и так хранились в польском корпусе, в таком случае я требовал написания с большой буквы
[base = 'rudy' & orth = 'Rud.*'] [base = 'Śląsk']
- несколько городов пришлось выкинуть:
- из-за совпадений (Chrzanów, Jarosław)
- из-за ошибки в корпусе
Radomsko [radomsko:adv:pos]
, но Radomska [radomski:adj:sg:nom:f:pos]
(Knurów, Radomsko) В результате каждый запрос пришлось проверять, так что результат этой работы записан в базе:
head(miasta$query)
[1] [base = 'Będzin']
[2] [base = 'Bełchatów']
[3] [base = 'Biała'] [base = 'podlaski']
[4] [base = 'Białystok']
[5] [base = 'Bielsko'] [base = 'Biała']
[6] [base = 'Bolesławiec']
119 Levels: [base = 'Będzin'] ... [orth = 'Żar.*' & base = 'żar' & number=pl]
После обработки функцией pl.corpus
всех запросов получилась база данных, состоящая из 99129 примеров, полученных по шаблонному запросу:
head(pl.corpus(miasta$query[42], tag = T, n.results = 1000))
3. Обработка данных
Для обработки данных я написал две функции pl.base
и pl.case
.
pl.base <- function(x){
out <- c()
for(j in seq_along(x)) {
if(grepl("\\[.*:", x[j])){
out[j] <- unlist(strsplit(unlist(strsplit(x[j], "\\["))[2], "\\:"))[1]
} else {
warning(paste0('No tags were found in the query "', x, '"'))
}}
return(out)
}
pl.case <- function(x){
out <- c()
for(j in seq_along(x)) {
if(grepl("\\[.*:", x[j])){
out[j] <- unlist(strsplit(x[j], "\\:"))[4]
} else {
warning(paste0('No tags were found in the query "', x, '"'))
}}
return(out)
}
Функция pl.base
позволяет выделять основу:
pl.base("Wrocławia [Wrocław:subst:sg:gen:m3]")
[1] "Wrocław"
Функция pl.сase
позволяет выделять падеж:
pl.case("Wrocławia [Wrocław:subst:sg:gen:m3]")
[1] "gen"
Для дальнейшего анализа понадобиться пакет data.table
, который позволяет работать с бальшими файлами и пакет dtplyr
, который позволяет удобно обрабатывать данные. Необработанные данные, которые будут дальше анализироваться можно скачать здесь.
library(data.table); library(dtplyr)
df <- fread("moroz2016_polskie_miasta_row_data.csv", header = T)
Создадим новый датафрейм с основами и падежом:
library(tidyverse)
df %>%
mutate(base = pl.base(query)) %>%
mutate(case = pl.case(query)) %>%
select(base, case) %>%
group_by(base, case) %>%
summarise(number = n()) ->
base.case
head(base.case)
Source: local data table [6 x 3]
# tbl_dt [6 × 3]
base case number
<chr> <chr> <int>
1 Będzin acc 2
2 Będzin nom 312
3 Będzin gen 286
4 Będzin inst 9
5 Będzin loc 385
6 Będzin voc 1
Построим простой график:
base.case %>%
ggplot(aes(case, number))+
geom_bar(stat = "identity", position = "dodge", fill = "lightblue")+
theme_bw()
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)
Для дальнейшей работы необходмо соединить изначальную базу (в переменной miasta
) и новые данные (в переменной base.case
).
base.case %>%
spread(case, number) ->
base.case
head(base.case)
Source: local data table [6 x 9]
# tbl_dt [6 × 9]
base acc dat gen inst loc nom
<chr> <int> <int> <int> <int> <int> <int>
1 Będzin 2 1 286 9 385 312
2 Bełchatów 3 NA 132 33 158 669
3 Biała 20 NA 357 NA 15 183
4 Białystok 3 NA 203 12 582 181
5 Bielsko NA NA 90 NA 169 160
6 Bolesławiec 1 4 254 21 284 433
# ... with 2 more variables: voc <int>, `<NA>` <int>
Теперь можно присоединить получившуюся таблицу к уже имеющейся, выкинув первый и последний столбец:
miasta <- cbind.data.frame(miasta[-52,], base.case[-73,])[,-c(6, 14)]
head(miasta)
Надо отметить, что не по всем запросам в корпусе нашлась 1000 примеров, так что абсолютные значения количества падежных форм для каждого города сравнивать между собой несколько бессмысленно. Поэтому заменим все пропущенные значения (NA
) на 0, посчитаем сумму абсолютных значений в каждой строчке, а потом переведем абсолютные значения количества падежей в доли.
miasta[is.na(miasta)] <- 0
for(i in 1:nrow(miasta)){
miasta %>%
select(6:12) %>%
slice(i) %>%
sum() ->
miasta$n[i]}
for(j in 1:nrow(miasta)){
miasta %>%
select(6:12) %>%
slice(j) %>%
prop.table() ->
miasta[j,6:12]}
head(miasta)
В результате данных операций возникли некоторые неправильные значения NaN
. Это связано с тем, что некоторые города в корпусе не распознаны должным образом и имеют один единственный тег ign
(Zawiercie, Chojnice). Избавимся от данных строчек:
miasta <- miasta[complete.cases(miasta),]
Теперь все данные (в итоге 116 городов) собраны воедино и можно приступать к анализу.
4. Анализ данных
Во-первых, конечно, хочется посмотреть, какие значения приимают получившиеся доли:
miasta %>%
gather(case, rate, acc:voc) ->
miasta.for.analysis
miasta.for.analysis_2 <- miasta.for.analysis[,-7]
miasta.for.analysis %>%
ggplot(aes(rate, fill = case))+
geom_histogram(data = miasta.for.analysis_2, fill = "lightgrey", bins = 17)+
geom_histogram(bins = 17)+
facet_wrap(~case)+
theme_bw()
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)
Данный график трудно читать, так что я добавлю такое же, но с отлогарифмированными осями:
miasta.for.analysis %>%
filter(rate > 0) %>%
ggplot(aes(rate, fill = case))+
geom_histogram(data = miasta.for.analysis_2, fill = "lightgrey", bins = 17)+
geom_histogram(bins = 17)+
facet_wrap(~case)+
theme_bw() +
scale_y_log10()
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)
Как следует читать данные графики? Серым цветом обозначена гистограмма всей выборки долей, без учета падежа. Цветом же показано, какой вклад вносит каждый падеж в создание общей гистограммы. Исследуя данный график можно сделать два наблюдения:
- во-первых, падежи делятся на те, которые чаще имеют маленькую долю (acc, dat, inst, voc), и на те, которые чаще имеют долю в промежутке между 0.2 и 0.6 (gen, nom, loc);
- во-вторых, некоторые города имеют в именительном падеже очень высокую долю близкую к единице (что в свою очередь означает, что они почти не выступают в других падежах).
Первый факт достаточно легко объяснить тем, что в польском латив и элатив маркируется предлогами do и z, управляющими родительным падежом, а эссив маркируется предлогом w, управляющий местным падежом. В целом есть множество разных значений, которые оказались вне данной сильно упрощенной схемы, однако в первом приближении такое объяснение принять можно.
Второй факт следует рассматреть отдельно. Вот список городов с высокой долей разных падежей:
- gen: Ostrów Wielkopolski, Siedlce
- nom: Ruda Śląska, Starogard Gdański, Zielona Góra, Kędzierzyn-Koźle, Tarnowskie Góry
Видимо, Siedlce, действительно представлены так в корпусе, а все остальные названия, видимо, неправильно обрабатывались морфологическим парсером. Избавляемся от них и строим графики заново:
miasta %>%
gather(case, rate, acc:voc) %>%
filter(rate < 1) ->
miasta.for.analysis
miasta.for.analysis_2 <- miasta.for.analysis[,-7]
miasta.for.analysis %>%
ggplot(aes(rate, fill = case))+
geom_histogram(data = miasta.for.analysis_2, fill = "lightgrey", bins = 17)+
geom_histogram(bins = 17)+
facet_wrap(~case)+
theme_bw()
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)
И с отлогарифмированной осью:
miasta.for.analysis %>%
filter(rate > 0) %>%
ggplot(aes(rate, fill = case))+
geom_histogram(data = miasta.for.analysis_2, fill = "lightgrey", bins = 17)+
geom_histogram(bins = 17)+
facet_wrap(~case)+
theme_bw() +
scale_y_log10()
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)
Может быть какой-то падеж коррелирует с количеством носителей? (Спасибо Ване Левину за этот вопрос).
library(PerformanceAnalytics)
miasta %>%
select(5:12) %>%
chart.Correlation(histogram = F, pch = ".")
![](data:image/png;base64,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)
Но все же в моих данных много размерностей, так что нужен способ их уменьшить. Так как данные числовые — PCA. Давайте посмотрим на биплот (более крупный вариант доступен здесь):
library(ggfortify)
miasta.for.pca <- miasta[,6:12]
row.names(miasta.for.pca) <- miasta$town.names
autoplot(prcomp(miasta.for.pca),
shape = F,
label = T,
label.size = 2,
loadings = T,
loadings.label = T)+
theme_bw()
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CJoYVzbB0PT19O0JWVcOYMrF4NfHy9HQqC/BjG+aMuwOTm5tbW1mpqav72LTc1NfHw8ODx+N++5f+Mw+FgXNOdYbPZTU1NAlwzxVLr95Z79g8ANDQ0CAoK9nYUnX76+0Mvuni+TmfpKPpFm21k76CZQt0TT683MZybG+7gQebbtyAt3boENbHvQE3sh37L9ycuLq6lpcXS0vL/n/ojrz133zeGe76L3NY2WiPhnniAy35bAQDDMK6K56e/QkQRkZwtK+2EcVRFx0Chbn4PvbaLWlpwwcEcc3OsfSoS1MR+CDWx7+vur9Aflp4xDMPhcN1xAN66We7pPbNYLADgnni6b8//N2w2m8VicU88AIBhGFfFw2azcTgc7sflmPASMzziZnR7PL3cxM6cgYoKzMmpIwDUxL4PNbEf+ukm9j3fye7o2jOCIH0dhwNHj8Ls2aCm1tuhIMjP+sN6zwiCIP/a9euQlQU+Pr0dB4L8C6j3jCBIX+ftDerqMKP7z+AjyO+Des8IgvRpb97A3bsQHg7cNKoIQX4I9Z4RBOnTDh8GSUlYsuT/nykJmTpgipHJEoNZ2ou9XtVkHLb2eN7UdYX/m8y8K05VrPGK2w1dllCT1xuHFKPJyJDfA/WeEQTpu8rLISYGtm8HXt6vPU0euzn07FzhuuvmJkmVehwaRsTqU/as9H/Px64hGvgdHsIqux+0K7lmwonIWXmupo9XeMkGbr9OxVMJs/ZtIl17mUa8/Jr3nUf7VOfGAJyGl74WvniXYw4juOUOZuQPhdIzgiB9l68v4HCwcuU3nm58dsje4kz968dUkwsS+DsAAAT5+U7OzZXJ/u53897VpzcP22k1/MiBpx8l7rybtrJ/XUQOc7DtytmqCtKKQnNG3eynVeQf2z7VedRbyaJwM0N+x6RbKDcjvwyd3EYQpI+i0SAoCJYvB3Hxb6xB1nQNPHn26vOUFfd3XKvmAEBTZuDO8LR6KQ0NKSJGklCWkxSWn6ZXHxVxslhHX5EkbeC+S48/M9x1+9VPLIDWqSk6pzrH+s045Dcs2juZ8ifNxohwJ9R7RhCkj4qIgJoacHT89hqNT/fbmJ7BNVZUy1sFCn+8CoDnlyCXJ8cGv2JQ86qKl4rxvAW87HTt3AmnzZ8MIMLbtKC96SQRlrS6shBvg2DB2QcDHMYecDC/RKsWt/YZ/Cibo6JrsPaimdezqe5je+6dIn3RHzbndl5eXl1d3bhx4377lqlUKolEIhC45XiFxWJxOBzuiYfNZlOpVO6Z8LZ1SiMikdjbgXSiUCjCwsK9HUUnBoOBx+N/cUqj36inmxiHA2pqoKICFy9+9fl/08Qot21XFG2PtRvQjcGjJvZDfbKJxcTENDc39505txEEQX7g0iXIyYHAwF/eUEteyIYAsl1of/RrifQo9IVDEKQv8vYGDQ3Q1v7lDZFUbE8k/IaAEOTfQekZQZA+Jz0dHj6EM2d6Ow4E+e+45boUgiDIb3PkCMjJgZFRb8eBIP8dSs8IgvQtpaVw7hysXQvcNKwJQf4tlJ4RBOlbfHyAhwdsbHo7DgT5JSg9IwjShzQ0QEgI2NiAqGhvh4IgvwSlZwRB+pCwMGho+O5UJAjyZ0DpGUGQvoLFAj8/MDCAgQN7OxQE+VUoPSMI8serv7FIWXPB0WnaUFCwhTSp4j8UdaQXX/YOTCxn/v7gEOQ/Qfc9IwjSB5CG2B1cF7EExqixPuXfDNma9qby/e0b/H4ZYXJnnQ88acbohImbnEVO7LlBxVMJsw4dGf/Qwy+1ouTuLX6/N8Eix2w9X7GaKVKSSg+ibs46ZX1rin5Z8PO1iWbHtWL9tFD5KaQXoPSMIEgf0ELyscSyHnsOEH9qtn6vvcr85D3WPIG+M7Eks6AP4rOH8TUUp959LtFeDlKMf4C5u5uy20reQN+ZnPsmae1FIe8MHPru3tMneYNHUxOfJqXLzV+NcjPSO1B6RhCkDyBt4OOHAQO2vDjx3jQhV7+/jy95R/gcSXwDB5OYvs7dSb4o/kLN0IGTR2BVD8Ndg7UiQibcc/Un74iYI4mv7VIUkqT6j8KpwARlS3uJ4BMJUmZnuKVEBfLXQekZQZA/A73w1Nq1MdWCfC2NIvO9/GxUeTuewpVTJ724yfY6iOOXkm284Wack6M8n3fjBtF+BQVTtJnrzcx46eKmR1SeurWVgxzQEGe3MU1obsjGDf0NNtk6jV3dVhQydNSYLOFUz4k+44VPrMzQ9RXBevEdI381lJ4RBPkjsMpuRhYbRlxaLs8puR5TSKmtO2LfesHY2nfz4Wc4POaSeKORV8/r0CxHT0nVxvccrT2qN8zPf1p2NX67Ik/rRsKjOzZ3o8S0s6DktujzHS8kH/NeFwDg8of5Pfn+EORzKD0jCPJHwCtYHHcICdjk3MIkKOo7jH7o2nbBeJvxaencymemjseC7A4Z+oTfLWu/kPxQecmocRL67bkZQf4kPXZjFacpN8JqnBwfxiszxiw4g8r5+motb3aOHHekgNFTYSEI8odoyTp5hrbY/fDhI4es6B7r7ja2XzCe+D6NwGSlmzkAhuGA1eVCMucbvzMI8gfoqd5zY4rLrFVPjeNeXVQt8l+6aNbawTmhOsJdr+owK9NvXL5ycp/7a77DPRQUgiB/Dh6lKVIHrXTDBEQILTB+TcAc0XerHcyvUqv8yzMqlYSjvTfePVDFM/+Y75iEde0XkoeI5BWcvVCobaGMOtDIn6aH0jP1RWhcw+ywbXNU+mEqmw8uCjEOSffRmU7uskpz8f0rDwsxaWGM0jMxIQjyJ8H41VdF3l7VZcm26PMAUVFw0+TFtFmr/M6ZSreeDhzW5ULyicSZPRwngvwePZOeWbU5GfVyS1TJGAAAv8rUAbSAzErmdHKXlyePcQmM5FTHTr3i/vkf5+XlhYWFtT4WERGZNm0ai/Uf5gT6ATabzWKxMIxbhmm2vsfueKf/DZvNbt1FvR1IG26LBwA4HA5XxcNmswGAwzXnd7upieGOHgWtSRRJUTaLxWL9izeLmtj3cVs80Eeb2Hf+vGfSM7uZ0oQJiPLjAQAALyDKD7TaJvbP/XF5efm5c+daH48ePVpLS6ulpeW3h8hkMjEM457PvvWDx+G4ZdbV1obRHXv+v+FwONz228FV+wcAWCwWDofjniNOJpMJvzsd4h494k1La4mOHjdv3jhg/Kvdj5rY96Em9kO/pYm1fg+/qmfSM45XmI9Dq6WxAHAALFotDfiEeH+yWUyZMqWgoKD1cV5eXl1dHT8//28PkcPhkEik9rsseh+LxeJ03vXR+1oPpbtjz/83rT8cRCKxtwPpxGAwuGf/AACDwcDj8VyVfn5/Ezt+HJSUSIaGgMd3LPv89uhDE644X9Tx36bB98Wffr2J0VI3Ln9mf9ZBucdbHmpiP9Qnmxgej2cwvj4Yume+g/h+Q9SFPqYV0mCQMEBz4ZMPfEPUJbgl8yAI8icqLITLl+Ho0a65GQA+vz26ETg0jIijZRxvn3nb1b5+++5nBFYzi9D0Lj2zTqC/irqqpOpE2fTYQil5Rmbl9Bknt3qnt03ZHa3Hl+1leUEvYutwUpcXYZYmbN3xSsdtyz/yHYPO6MWXA64Jm9hMlUK/bchv0ENfI4HRNoYCs3cdS9PcoFIcujsOWxA/lgysytQLtyqHzZ87VJBbTsAhCPKnOHIEhIRg+fIvFn9+e/Rk3FMAqE/y6Jh5O7FEGUQUWDR1/xDt6reVHy56eMZllTBLCXYeend942pzo8KbwvcMd5p1e/DEiDX7hLwNmOU3964uwJU3aHr6T4xf5/+ej11DNDjsxOfosPKCREtZvcY+/ymXHVFRDeS36qkTX+RJXrd8VM8byJNl/4mUOXDLT0cYg5b8E6vNt1yvQCXcEAT5FnrhKXt9faNlRvPn2Ybm1mUctvZ43gS1tRAZCfb2QCZ/sX7Wycjc6k+iph6HrOge627WAWR4r9mf/O7+mQf578uaRZUl+YR5CugTJgjnBe8Of863cONiOR4MwzGzjgRlvy+iYryNtzfrb86fH3vjbMAGTUILG/hGOvqeCF4nkJbTIjd/zdL+nzKexm2ztA/Pap7jvl6lsejW/YuH0+YFRsWd38Ubm9ZRVONTYlJEWA5BtHXy0ea2yBHk5/TYSRiMb4hVxDOriK7L+CcFV3x+VRwTM06iGvdUTAiCcL+vnqxm7FmBo9Fc8zIbjr9waNq29bWCREVGtYy6LOPje4Iy4dG1t8lLHzXlV5CGHzqdXGp6y4+YPO3ku+eP3+NHCG+/eOPZJxr7xWwt0YLk3KR4Yf7mygrSMov8C1n5LAFJSdbzu2kVTRA2c0i+q6+9zDX3c1lvU6xsdXQBx5MZuOP0u1LKAuvJtVM3k7fu+lDDBAzDcZqqcsNXW9/DF6SXTpo6ojDAbg9ZVk3pZkQiUWYJ+6WvhS/e5ajOl6fZt4WsUu/tvYtwL24ZNoIgCPeipe5afaK3JvNTsDjuUBewyXmDi3++lJIQDgDHrGaFXHuoosajLE9NTSyh8w6zPxLkOYsgb+8btH00VXG11XRLn5jzMWciDq+3sdLG5X3ES0lJjz74LOPYgFfPlYZNDUgNncCpeFVA5xXikZ4xlp+ANTzKw/Pyk/BEAZ5mHiW9E2eXiOPJkBRx4WRUOR8fWawf9dlrKhvPLyFI4wwSfHDh1ZXNO5OZ/YeJ4QEARKY5ziBTPrxKSi/Eqwo14fB1goY7tyzmTWXKNcaaG16c5mE/QgADaDvNLiIjJS1KTU3snR2K/CFQekYQ5Ef4x+85Zj2wl8bwfj6X5806gGHXL/DSGGUHwva7rTPUmyhDIpF5cRiOyCdIwgEO3/ar1pQZuDM8rV5KQ0OKCEDg4yXiATAcAHAAJ6A8crjuWLmBxh5LRLJTYNSYMf1lZSdNk5VU0hgkwlOXE7DpFmHgItu5/d/n1VD7jdZbvnyScGM/8ftegUlNEoPM9tjP0R4mJ8G5sfFkwadqBufalu0JFA27zYtV+iuKNdN5B0/p/2CtkYdo8H4VyRmH/IZFeydT2m5vbS1w2Rp57+zQLj6/cND8C1v6/ql7avJ645BiLrpH64+ARhgiCPI9eSfWud+rYnOa3929w3807+YyqR4+qP98Lk9joez4gadCWGMHXQr2un6SLm561O7rI0vx/BLk8uTY4FcMat7HlwKt2ZEso6L6qSFvy0QjHplBYzQVZNT+qap8Nmwa/UJ8QoOoiqygiIjaKAONsjOn+fk+3oo7J2sXuf7i/jt33dzU14TskwxZyRPotyLfRnfzK35ZIWCKKFenJFOGB4W43jde9Sg+lkJh0q+l1ZV8IOhO12S1lBU3SYgMUNE1WHvRzOuZhzAACGq56Ia3FbgMWNSDu/FrvigCVpWTeiwgtXXI+pvjAv6rvLNJJJyq4xHDfG+/tuUZYXJn20/Ob3UfcWnD0RwiEVQdvQ04NIzIzD44Z3O2vERLWb2GZ+DspG1ta25YCsBpaD3Jf2x124kE5AdQekYQ5HtUrH1OWbPKr6xdRgoKM5RsTNmzsn3o8ppix63PRYcscxkZdUQwIHJWnqvpY9t4e3bkpq0JFbx87CamsrmX++IBX5/vuiXDc/m1BZEb1XgAAJrfnt2y6dxHIo5ayxhk5XNwiVL7X305lyevDeTMhCtXYubObb2Xqcrk1C4pAsDWqOEAAB5RmgAwl11+dmvlTL8bq8WSzIeu+ej/Itvttaue7/gZgnXzHl/V4Gu/75mWoEGNW34vTtThtYFmjI+q2zrqVteP17KdR/JVRhtv4B/pGh2jd/ON5LQB9x1dyTvC5w7gb3CefuWerLi46c5B2Z8oF0q0hggOU9u98OXe+kFSZQKW88Vraj6xJA2cmL6U8d6xkhiAQshNfQCYrAkA4Bpzpfs+rn/liyJgOqraHnsH7rHmCfSdwbhtkmkYELmQJ/NuAQy0aF8+E0sy6xgDfz3mXqZR4Jn52Mu7BS1tw4jYmILVEb9Rj1esSLud3rFmcgVfUbiZIb9j0i2Um38aSs8Ignwfp+HZAUd3u3QAACAASURBVKsQZe+zS/oTgSY/38m5uTLZ3/1uUctAUFgVeEibr5TSvOvpR4k776atlMs4bHBjQkScqTz16ly11Q6T7wfLf3jySXWuVr8abMahw5qXHT1f0SvT3ygfi1YDAGgdKlWRc/v5kIiX0brCGD3RZuCw8RVPAxrcDr5sfHv7dr39hVWvAl+JDjH1sK4NYu08LcJDcMFPDErdZ7X5bOrHfvpfv5dJXEsft9x5knep7KCZqrU33lHnJb6UX7iQNyIw+sStBiw+JLUJo/Nozm7MrM/Yttj5U87Hq3kKcv1dlj57xtv/oXoIr5jsOH213FESjjxiYv2l+cuzq6UVH6qH8IrJTTAaVxwWVfl6y+jhYrUNmU/VBnlpTRiC4aSaKO/i7X0XDhImNWEE7r902F4ErD+Bnuulu+7mSB/qVl/yjvA5kvhKFhtHxADD4VjNTHpxlHPb8obWk/NO8kXx8SWUC6/xbeu0n7gmCMmIEAFweBx0rnmhipx8bcahXfUHvZMXe00VRgn6p6D0jCDI99CLTq3eUr0+6tBIAQyAlhm4M7z/GmsNDakcAIKwnCgRAC89Ta9+R8TJJh3XAU1pKfh/bGUJAAD8w1dat2SOd1YqXFO7wHJIuG+cb/itjFL81vNe/GMWHr5L/BjluvxuxrUcFV1ydgOvzMPtw6zejNDGP/zUUu2+fteEZQ4SvtvlJZqTT58qZB3I3iO+Z2PyNP9iz83SQxkhTjtaauduNyj3qq497vWiPDtW9xadVxZvbSOswk85qW4f+nx1/rtXqQx+fIvIRJX0I6aG58o/jFi8K/TRc0rag0gaW3oAsaYBUl5jbLFZ8zSro7Lz8jPfzot6eET6ypIVDWefmAmmOpvctJgx+tOGKztViw4ZelZxKMNTWpfftV02qdAocMYZw/1aW07tVVVQUS7bMt0lpUnV/VaolWSel+UFAZ3QWNKP9m7v+rwI2OqZN2zmpArN4924ob/BxhUOyjaWppelycorNlbZuLQv32TfeXLeb9saZVvTpQlS/MrW+xW+3DjveGfdzW1rHlpE6DzJP8Z9LLoN/Geg9IwgyPectHC8h9NlrTOPAJKKlfuirhd0xduGO+Flp2vnTjht/mQAjyBldIt3coXZYmmApszQcLb4i0O19NEHtMjp4RiwOBwAYJSl5zLJo+TEsCn/mEscuJ8runyjxt0dHNon1XEio0yVH51/MVrozdtqzej3RK3ZEhffqA3BXSqtevnwnV3eoUYcPnP5ZudFirkeXpQX6c2qsxvPJc71WZx8Nv1TqZJ0y/0LzYtGqo6uT3z6uHDIWOzBw0ohUh7bdKbI60Li4KzX4iT2h2lT2NdvNlTweqdFs25cOXYwpt+87YvSL2aqrNZ6E5pM2fpZxWgMR8BjrZWk2V9WksZJG7jvgqqH4a7BWgH2WL/2DuI+iV77uP6V/ysCNu+jRftDNnvPea32ST21P5p3rtT15Lxbgnb7wylRwwBgeNRQAIAZobEAAJ1rLoydCh0n+ZGfgtIzgiDfY5NEsen6/xlR8f+/EkFUZfjkFfr9CUAYvcVnsovd4lgy8eMLxqDtSZcsyxwnbw1z2JKVXrvMI2iip9/Ko1velfJP2sx6tuoZH+vAas0gN6/L/QVoT0+nKQ0TCFibzhYUG7tA4ML5E9caJdQfEvrrjlStjb128gKoel6NDxqgKvg2/qh7HWHMWPr5S2W1UaID5AeMmJOx4RFuqPJMXMI+So74qnWk4BMJUoZaPNfuSBlP4s8WnIsd26loKFXQhJGUl64c9Knk4uv3Rx22jjKaS8SAXXbe/w3Z+PLWNflrzLwKwp3GbmirGO0z+ObFUxuXPaV/UUk6YHD+9iKAhrSgvekkEZa0urIgLvWLUWAI8ksw7qk39zNaS2KMGzfut2+ZSqWikhjfwWazqVSqoKBgbwfShgvn66dQKMLCXPSr3IMlMVryQlZvzDIKPTxbvMurUa4aLSv3uWIl/GiNTcn2U1NS16+ObJAWoeXRlp/b/NTxtsEWwgH3dH5xMqMwT25P5DRfrf36T84J2406IDp8tNVBGStNd/zOzGc6fhapDlEGt3Qm8Iib2N45/naXwfZ8EREWTWF1gBPpsOVt4wCtC45eWRxatbh1qM+sLNMRnq3b8TV57J25SD+cd5Ra3fNMqpTGpNn6itnnrj19U8Y3cOTUWYrvHpYIiWHVTZPmM/3DhedpS/P3N9jsMlOqyxTe1MQ1NiXbz7RXku5GqIn9UJ9sYjExMc3NzZaWlv//FErPbVB6/j702/FDffK343doy3AGgk3/polRbtuuKNoeazegdX3KXSvLiVdS+efPhdDQ3xLWzzUxlJ5RE/um7k7P3PLrjyBIHyUw1T8KAKjUn/+TlryQDQFku9D+hI7/Zn9QmlF5Edau7Z4gv6UteATpeb1+ZI0gCPIFkortiQTvjlPlJBXbE2vK74GeHowY0buR9R3Nb886LV64ZOlifb3562OK6ND8crfxoWz6d/6EXnzZOzCxHNUw6iGo94wgCNe7cQNev4ZDh3o7jj6DkR+49vzwY7HeikSgv79yKquCIQOssocJ6RMuHD38itVMkbQK3CEeaueZLSbHyq1aFLntw44Dr1jNFClplcQzV2agipndD/WeEQThet7eoK4Os2b9cMX6G4uUNRcsM1m2ZPH8hRtvVPz/NM+01I3GAYVMAGCVhMwxvEoBVnWiu5HJkZQnXl/MGt2S4bnsYNb3+pN/LFrOw+ZpOvLElrwwp5Xbw+Lin1eWpqU3Dx1f4t9eGfNU2Cm/IruYuLD9hv0YDSne7cujU4eqd1TMfJqULjd/BMrN3QL1nhEE6QUcWvbnc3/qNxzuMsdnVxkZcPt2o72m453G8Fk/HDlFGmJ38LRdf3zT0436p1/eTw0Pa52C1GePqL/FvjwpeUZm5WyT1H3LDr5oePs8f05qgJfFQabOFEHXzVUVtESjRHFVZUZVM0YnTHRdyQEADiXFY5V368zSAesEz7i0l4P0sVfn/1Pnv+JV1sQiH5WtMlex8g6eenSmfRWTJKEsR+HHve+4t5vN5mAYBoDhMAy63AuOV9JTCDmeoGxpLxF8IkHK7Ay3jGbra1DvGUGQnteScdjxxgS/uJioqHMxe+XDHSPeswAAmMXRjsssrcwM7SKLGvNPbnV0sL0zeUK9cL/rDbVpMad9jS0uVnNoj10WHsl4c3DOghV2NibzjL0yutRaaskNXb/C0nTuBMOn81aNU5nv5Gy7eJLAq1spccfKHeMTTvquHEysvX8kTf/YqWN2MhWhjuFF2CCHgFDPGXRK+asCZZ47MR9EpPkqHkRu3XHhQdq9zA+3fDKNfPcuGqZAqi9P7CwHeefi2i+qMDEKjowUHH/8fVvXfJLQ8EP5/7oK58+Xfvr+mt9HUlvvo5e0csFik+U2jsfLFGVIBFElcR4Q0nYae9nBfMniPU0WNhar5QOXGFo4x9bxiExe377c3GSExhzh1MaJ48dPxyczdMeJ/KnHKNwO9Z4RBIFzmywvvM2/nciZOkt1sKH73kX9f+6nofH+SqvSPdFm7fcd0QtPrV0bUy3I19IoMt/Lz6xpv8XtJaddh37ZI+bUZ3TO/UlS0h1fusA6ZoGcCDAq3+QwB9uunK2qIMavbOHhIbqRL5hB375RZ2jGtX7LFpfdb5/cW4lwvqP6wpt6jjpvW5IgqdocDLfrj294YL8k6vKH5ykD11hraEhlYTgchmEAHAyHcdr6gkCSGDhvq94DN5/9T46QSUSSFP+z0jqyuYMV76akgQpKIlgGEJnF2Q9jnT3U6bn5H8cJFteUtnwS5jSJ6ywRK0xp+KIKE0F6hOCNhEKbdUrFV67zj5DF16fsWRbU2n33Wk8PO9ZeDypY5Jit5ytWM0XK3Ekq6uasU9Y3p+iXHE10fma1/gnfdF1c61TkrYWh3EZccm4rDHVwamfpp6M6HBpG/I9dLExA3Tb4mu1ny3bHjgIAtejzAABsdvPbC8Pc4jxH0xNWbCFLTzaNntyxpnzMe10AgMsf5v+3l0d+AkrPCIKA0YFIo5q4eRbs4DNGxMdu5iaf16Qy3WeZbb+trVDgPv8plx1bU4v1UYOW/EjXVQ/oH5q09jo3bd0Y+7JQ68JljUvH7j4/NnPgjS2mZVc26Z96U6c8btjEiZRbSaW5D8p4BZtpwuNG8BAO2l6v5hCouFEapURpAXxLbfKWVYylW3cOoiaGuwZrRYRNfpC46eUcIl7AYVXTPYfPJvdWJNK7VF/4Ch5x2abMEpJA+xSkFXKrJXwXzgsXhWr8bB2nsfsdV8TkvsMWLB0iUTh7eZOb1wc64KVmqVHPvUuyX/qyAsiCZB4AAFGtifwBr6o5A3kbM4vFVHkrU/LK5XiJYtK8uf9fhYlvmPHo1PM59Qa3U9SNhr+mEjoriHxUCOmo+8S5b5I2LzDeTDDV2eTOwKHv7j19kjdoVH3y86QMufkjWhqhPsmjvdzTk/gTt3KNQtsLQzE6XzTvVrd+KQjCQtnbbKyFcVSltcHoBHbPQ+kZQZDPEL5Sk4onO7Ojq5p0Ma0jtUS9FRSdusV3h8o7r0VH0kdhqh43nLKjw161sFkYWc9nEy7YrKIIJ8wnKC5Kffb4bW7lopkamKVp6r6yqbjXmfcu32GpDJUm3i612DAkwCM2h7r62b6aA+7HSSIsaXXFxngr538K6lIGqyS/ZNuJChacvfDev31ybyLkfy14odlR11ofkdR33o/74tkFhp2Pz07qmJYkej8ArIQCX4Ojw9cOe3+SoFihY2hVsDtVafykqQN5hQZr2qyJ2Kr4yMa6RNn+5PVVVQ8jfJNxGHROst1ZhYk0eKFGYmQstWKcoVXB6+TMwJ1Jym0VRBjFUS5tdZ9qu1zKJan+o3AqMEHJcqXI8fAEOZPtgnEPoUu5p/iiqvj89sJQTE7PzeyNE52259wsLpqW5G+Drj0jCNJVU2bgzvC0eikNDSliR02qroUCOZzPK0O0/svB8RCIgsRHcbTF7vvXabbUEGgVGFlKUYxXbOyEYf+sWbNgojSHAxiGIxBwGA7DE0QX+l26GbZ5oQpRTGuKDEF03snoOYkh1WZh0WGBgZEnt05UMTHc1Y/eohUbvWmmVL+ZJxLDLJT5Oyb35hnqErV1OAkEZ4TGLpP8XZc/iYr6M197PJo8X/nrRaob0oL2Hr/yplFaXVkQRxAZoKK7Y229h9cz6te3gOdvrSBy+hU188QWY+dUVn7Ixg0H7tCnOnVeyh01Zo5wauPEceO08U/aL+UKarnoPllvZma2KZFv2EJH5TDTpTbrj6YD79dfFOmL0KSebdCknt+HZhz8oT9+xsGauHkW7IjLCz4dXb6jbSpsiaVapRVGkVuHY9lelhf0WnuQ5ZvWF+043DrH9VGDa+YHaxTFCM38s/evrdt7ceCkwoDol6+fF+GkB4+dZaAv9DwbWI8vPy9tFho0VAjj4+TfLwJ+Fl145s6orZiPZzpJhEVTWH1oapRj9obTBq8dzFLt4lsLDnI4MGwYDBwIly8DQP2NRaO2M9TwWS9rJEYa7A7fP1sS///voTnjsMNFnf2Tghy6XhEHevHlgGvCJjZTpTobFGpi34ea2A+hObc/g9Jzb0G/HT/UJ387fiMqtfbjjfMPb94lLJb0tE0dMbl/S6PIfC9fg1eWrv1OfOWOqcuXYf58uHcPdHQAoP7GsqXFBy/b9cc3pViPWMHeaFwTEv6ad6Su/b55903XpClMUhNTX+ttkOyYoOen5jjYgTB/QtW9At2Em4tvrm27Un7MvmjN1ueiQ0x3Tj1r7MEcJfHyroB/RrTeZ58a5eq8kbvxEwcR6z9WyjueCTCU+9eN8GtHAz+EmtgP9ckmhubcRhDkK0qCJmudlp0sy6j8hNfzDZl9x/Wijv82Db7251syPL+4F5mavH5F1oYoW4WvdF0BAIBVEjT1G9skCAvnnrmfSntY8XFwzIuoucSS6zG5mTevvUwjXn5NzPcM/mw82tGsd4qDpMxDTvEG+RANfLd8fJ20V0tlP46IZwoNkSNeesNPpTZijXd3zkuoYSmNluNXqAlZoHVTqrbgkLokT0uzSHqpME9F+CKtkOpGpfHSnwrzvQ+V595JGbiAsGvqWdbQFRvkXmPT6CFrLCM/u6GZLUhXWxV+xkqWmeM5c8fLT/0jnduye8CaphPtQ6+f73plubljrNyk+HX+ncFvb13O0prqot7tHyHSd6H0jCB/M/LYzaFn5wrXXTc3SarU49AwYtdbelxsOQDALI523nSdiqcSZh06OKjzxp4AsyZfu7bUFepjJE/45jax+pQ91kcLBDCKivtDrwH7J9gcsjLyeJHJVhokIaWsojlXf5ByQdfxaBN11wyMnUT3dl+vNb0y2d/9ztPr+VSVHffPS7itvCvHk3KuRUNUSk248VYend48bLze5kjHOxa+WhoilPqq2hoVGZ5sAZLq8JrkJpWpSoUPSvpNXT+OcjClIIcJdDo0NYtI497fODvJiMxUCT47H3t5t6DyYftI6YLnGdnpa5c/4GliSpptG/7MM6R9HFw8dq5j6LVw9YvO27poRl0H03UuB0DpGfnvUHpGkL9Z47ND9hZn6l8/pppckMDfAeh6S09qYokSwGf3IuPLGEXhZoaUFh4xp0Vn857nVLK0zp6qcdEe6yqoOFGiZrDHlqyXd9/ZWpyhdtkmEOTn2/1zdM8FFuNu3l3arZYpoQ4S3qfHy6SczPpExQ2f25QZuDO8f9sIZyAIzNhr3EDm3fYiicGjaa2hIZXNYbEBA4KcvtN62fIrSafyyeSqF40EPkVZYiml6oOXxfaP6S9JuhOJbxkkpVkS2elvGt+ltVDq56yeQ3zhlpkQWVdeziaqipGpRDY23Gzgnb2JskV3X73MSixfoINjNTPZ7SOlT+/Mow7xjbCSxQEA1CR0GQdHL45ybht6zajuHCvXlBm484pCR/Dfvd0LQX7an5eeORxOd1wv57T77Vv+FdwTD7ftn9ZIuCeeVlwYz/dD4nDImi7HI+cKs8si9VdenTAFOBwOG5PQWevmJF8Uf6FGuijtLQeTWuC2E6oehrsGT/ZfifWbcXDnnXkGz0ccD2Sar6uqTYt+O5lRX0SV0qitePPgUi7WxGG01L8vYkoJHNVVc29slgxRDqZj5NGjma+efKpfZMluobXMM+BpobHEpi4fnBr8MCNdp0DmU1bZ0xvixKr35cUjNJ++++CrPOD105zqvM23y+tpVD7BFcMq3UeI7WRifJJDNIaM5wfyTMXcx45X9hW7bj6Tkk8av2AqrqXldTmfrHSVNIGFV162fdRJ91cBMUXlNJHB8qoS5fdoZpFrT1kcfImjztSdvWZD8Mrq/baH1tlc5Fey8lrrPOvUejMzXrqgKqnLjhOZtl7T3sH8Eq1a3HJP+uqFqULzeDdukF/gNJfTsRaOT5zcfnf1xxfiHS3l37UX1MR+BhfG030h/WFDw3Jzc2tqajQ1NX/7lpuamnh4ePD4b11R+9ux2eympiYBATT3/Tc1NjaSyeTejuLf+RCirX1WZrI8rrGyRnJ5gMPHXVd1Q9cwAuz2pBNJdHETL4uc7bfnH5/3wMntOUmERetv7zklxilnfeTIzTJT74ycLvzsQSUBB2IacuVPS8nqUwTf5ctKlj4ukNAe2/worZpD5CFihH7jRkF+GZ5e+rGeT1iER3Cc5aDHwS+bGVQAPFmAU1fHBoEBSjwUCrWGKiSCY+F21TFX0avV8FBlfnP7U8t7HpkXxudFezn5J9ZJaeqrNqXdKdQOm5lze/4Ju7qDq48V87FriAsOu8LRHTeoeCph5gHPgX6rsqxdmw/54zccnnbb8aLuic3qpN7e2T+AmtgP/YlN7Ifi4uLodHpfGBqGYRgOh+uO8cw4HA6Px3PVSGkOh8M9hwtsNrub9vx/w2az2Ww298QDAFy1fwCAyWTicLjvDytVXJX8flXXBdGjAQA2xV7pXDIGAIZHxHQsmHROG+CVirpYIq2RoLL2xOhwq1sNVWyx5TtFz+yg2obaXV8aRB4k9/612mTzhXzJsSVaa6Znn2cOrnmRSwWWbHX2e46WunBGBnvQbCuVVyceyhkOKE3hJUrNHFscdqehDtfcz4JZHU7AlfcT5rm96XDZp2qLoco8dPaAxTofo5MaE2o1FxksnsHTkNt8e/k68gxlOfJA2ZehDwrKJPPYKjb2s5WaY5xP5iTHTb4msysrY7Rw3l0cDt+S6mqV5XS264g21MS+DzWxH/qZJvZD3/lzLnqrPwnDMAz7/VOwY+1++5Z/BffEw237pzUS7omn1e+Mp/nt2S2bzn0k4qi1jEFWPgcNqIeXX1sQNOe60+eDq6H9Zt8vFrbF0027SGWhlqDX4dRGJUJYjbYa/cor0mzjRfOTdzg/+ThcS7gm7uFrFqOh/m0W6+OHD7eCLlRk8Y07s3+0p9dzIj+h8XVyNVNSEqt797yQ0kgWz6hl1ZSWSxI0l2kL+j9YBux+HI4/h4MpDuB98aIMp6o9lFCQU1DzMixBdoDkx3epZw49PnXogJCwILOxgXMVz2IyCGRhqUxXwsfsEsuLuxnEoePHVjdgAlL8wRP6uWPSvHW1F9iPax59IsY3l1/FuwSYNR6293/Py6omzD963FSJS34EURP7GVwYT/eFhEYvIAg3yg9ce3744diY6PNXLvvNbMypaK18hMNzaBgne5/+hse1mXvUlexTarP2z1ufVIkRMUqKh4mRuaWJ+b7H9dSM42uWW1lZmtgez/j1YM5tsjRZPElCYuJik+Wb40uYAPxjdp9cLq+0+tzNm5dOuE8TUdl0YIKs4THX2RLXQ98NNPaL3GY8Xo6fzZYaNWbiginiBNH+n6KiG6etDdoyd5LpofNXtowZMWuOer/h9jfeJEda6GxPvbFUtq5cdsGycWvZtHK9STIkPKOKh84EknHYagX1jY46ZlsmkaqqWzhAIBLFFMWxFuAlcjBeIgGHCQwZr8SqbWbyDhxA4JDkB9AoBH4WnQ+rLK5oGXJw7ygBfLOauZZgceiai9N2Trm9zrtOz8nZdtFEgdf33rV8/k45tOwIx4UGS5YtMzIw2nT+PR0AgF2TEuxzubD5i+uA3y8Y9SvlpBAE4E/sPSPI3yDnYfO0I/LElrywzZ7333/iXa7n2PEcz0C9ke9uPH2SN3g0NfFpUrrc/BEtjZyqWz6ZRoFnOm4TKhXVHcbfWJKaCKt+6faekiC9mKmxcS7xk7WCYYyDo2RYe8GMe/HFjkZLRYeYHrlrYb9p5UqJljL2xNaCGd6XmnHjHNZKRV0bOP5FZBRx6DAqnln+gVdU3SVKHQCGh0d3vkJroaSoeAA46QqRiZRtB0Ie2U26oa1e/+JRYkCmBk4Khy+JzRNUGzmqKSujSUh5AD2V9o/l2IehRQPFPjyuYRdWiw8YK0ArqcWkRhqPqL9FXjT2ZUBGPcbDk7V+o4yghFTi/usVLJJ41qbV9xyFKy64B4lKFqdklbzf5HQu2rFozfb2O5gd8hfuTFcbK14rar4G77nWTIZ/zOGlV4fPG1KSeLLsYn1EktgwCWr+e43o12sTjdtKS73xsXZJxIuRBlh6OwuGrmmrDO1twKFhRFae95z1rxQkKjKqZdRlGR8/SLteOzjlVz4O5O+Bes8Iwo2UNbGHj8qYJBUr7+BdU2lFVV3rBvMO+UchKTRB2NJaMfFEAnneGEEA4LDYuI7CCWxMYprjbs89aw31Jv6GaOill/YElfIv9dswhlBdWfWxOO9V2sXQJ4UvsnLrsLJIt8vVbCFZIT4y68meqfquyTOthxKFCJdsFp9tyn5cVPSspPbZ65KSHOJby+FaZm0Vmtv7l5Rsr2X73rR3Yo9fyRdWZmpp4UXEpcrDGzYc+QcSDty86LT32oMK2akawjh6cw214VlqNb32+kMaszHv/lsmRsCTeSgVZZV5mSUVFS/C3sjKyKoP4m2oY6poDpRgV3wo//COtXD2iKHDZw7rTzuTWIv148mKucdUVB+qqNoQcfZtM6ZgdSQ0aK3Ak6TTlxr+CYs/f34Xb+yLMeP5P166lsHPS2MqqkgNUU4vN1qqNnPd1AaGyKe2oyIBgPokz/OqXmdPH7eq8vcP8so0CjwZ5r9Bk9DCbn1HHN5h9keCPGcR5O19g7aPeP/mN3wcyN8BpWcE4UZq6330klYuWGyy3MbxeJmizOfjjgWGzxFObZw4fvx0fHJbEQVMXG9NR+EEiakuuqnOlubmmxN5pX7i1ZilCRut9lz/QP/qs42pni5Bz1hkYXESfDq15Tz7H5ejfobkgttvyppJg2fbbLYfIygydOnevUYSeJmlSySJBNl5TusWDBPFldUS0x5/gJFq9Jy3WVi/GmEpFV01IrvlhZ+d7fGsFjYNI+KAWX5z72rrZfpb1sfAk5zEEfIulsvcYK+tEI6WkqIc8LbswTYDfcN5mlIiU9eMUbG7kf1gg5K01f2c4FlDJ2sMHjlpzgQxyRn77iZmNWQfnr7gfGHm7RtuS9xWD5CY63c7NcZcbdI6l7EKGl4PEk9PIUmaH9AVlzM/tmncaKv94TevrJQjAKdLtQ8pEXbm0woWBhgQRISb6mvfyNhunE59eKP0Y14DQ2a6QlJkIklhbJejIuCw6l+d2LV536UmUU4Ts/MIqe1UOI5E5sVhOCKfIAmHboZG/g10chv5NU15pzdvvViBa66qkzD2CbAd+uXwpC/R24orDP/+jS7fHO70Bcql2cP38mkNJDZR6EPWBO6dI90+EvfbW6Clblz+zP6sgzLh371WT8IE1G2Dr9l+tixqBACoRQ0FANCNea8LAHD5w3wAgKhhAABuCdodK7ueTfj5CYEJcgYHwwy+9SzfKOfI+GEeyjpxqZTpPDz4+rTY4PwyRmN9rdLw6ZP4M8M3X68jmSMiHQAAIABJREFUjxsX4xzEO3q41vwN+Q6mCwrx0iONxpOuizNLGcICjURqZaNg9ofUfGZImLyqDKWyuCg5sUStbfvqs6UrS0dbHFhdx0e8Mny8qkB95qmNkYT+mhuCDukwLi75v9LIg0dTE1Pi4vLfVsu4xp+cFjHP9tgpMNoC0Ph0v43pWULD+/yqUfqSB5evaH5NARPtlfIHlhhGS7LqeAwwAIB+Ok5j7RwtL9OqJWyOD363Laftnfaz8Ft6027cgO1sfqXhBXLG46pThtOfXS55QVH8Z5HF0Duhj7JuZ6v4Hpt+aU6GrpdIaRyAoNYWu2t+z8pK8t/K7nZb8XC96dIEKX5l6/0KP/U5I8g3ofSM/JKiSNcEDf9oy/4ERnH8kWt3Qk7detk6KXFGmNzZ9rkht7qNuOR8tP2aHLP85t7VBbjyBk1Pf63Ljq2zQpo7SUXdnHXK+tYU/bLg5+0X9jBKiseqtot5nbMiEyZu87ZTa0/vvOqOgafNpXCNKS4G7lElwqmv22dF/nKKyi07lE/ZeOZJyTMyK6fPOLnVO73rmt98rZBfu3b7H3Bo2ZGbtiZU8PKxm5jK5l7uiwd0ljfkVMUu+XoNiS81ZxxZd3l6wPcPO+iFp9aujaki89CoMuZ+R5cpdi2B0Jxx2OFkDUaS5yGqH3kVtcHY9fHeRf2O3m6k0Dj6x0+uKN+79/bV90/eEj2uKXnNPCc0T1v6WTzNyWtl7u50fjFqBbkykSWvOmu+6LPYSlxeDWegUFWVwNKNis9vKRgNfrXv6OWKW0tfyROGDmS8D/ea3FhzVFS47F0G/ww7bcXXF7M+5WeW5ZQcC05/+WnygCuHvRrTE2RXTHlwYF/BgI2zLm4JrJZVYpU8eF6vzap5n3fBellyg+axd0n//2HRCxPi3OI8RtMTVmwhj9kYpQMAsO3suY6qM1HDAQBmhMYCgMnTQr/OPz0GALBxa/t/bQAASoL0nOwz78xmJu5jZtzOYK9ffXDtnsXHdM94zVAkzUiYBq0zk6dsiNqqgIfhUbsAgG5mcufak3obj6jfP2cD0leh9Iz8ksLU5olbpAkAQFRYtMkegDM1uXVSYizJrH1uyCfxJ27lGoW2jlpqYQPfSEdf35EpK2yeXEn9asfom8Od2iebvHWbffp+gbD+RtfxHaGQh0zkf89YfGmvulvbrMhv4LMpKlNijl0ud4xP0IdLS5e+H2zhsVd1T+ea33ytXx1a9R9kHHa8MSEizlSeAC25fosdI0YeFfLZ1jrr9b5NpGsv04jx11NjjmWIDjE9tFUy3P5rhzir7xs5pfHN0Ot6gNL1OClgy0QhDFhlNyOLDSMuLZdnZod6Pbnntub/DpLcr5yEwGV6iXgx0ngThYK4Fr4hBtss3nkc3rq7mSJl7WMsVJ+r0lQrPcveZb/ODdNNoVurTPfvEwsKSGXLsUtejjq3/rlHqtygT89zpSw8ptw74G15ugETi+XxmiN//eZg+qOE5xXkxuUttBYMjorL4l88z7pj+lR7jMaksSO0FYYMPxzY9HqSF7t/YJj4PP6IgxShjIZJbpNFjJ0kdmcdeDrHYo/thvqSfqsenVj3foVNztemuSaICGdtsrEWxlGV1gb/noJQ9NJLm3ZcH7k/zHxA0cE5znc/vGUt+fR4z9a2qh77Tb46M7mk0oPPjkHNjmvF+mmheUiQr0PpGfklCiOwwKcVLBU5PLM43NJN2EXnWtukxA2c9kmM4+OLquLzO6/JEYSkhQkAOAIOOMyOCY1Jqv8onApMULa0lwg+kSBlvF0w7iFwWGwcqctwp7YNXqDqGI/UZ7OIRAKlI5TG3CdNqgbV0Z2zIgMAQGcY5/NL42IxDICD4TBgdJ0/GQC+/Vo9v1czUvD/2MoSAABISrpTGt0yixXbZ72WVhSaM+pmP33F9BiFVYGHtL917vfpo+ey80fQqV0PUL48TgI84BUsjjuEBGxybmESFPUdxvd7E3Tzi4MkqIq2OZglPlWdUXLCcIqCzayxC7SK/GPnBcabCSZZjl/mMxgrMzPkd0w6V2I23O+5wBBtoeidYXNM+yUZve43Tj1t1RFFKU690DBRSVXsah2bQug3ZNVRP60He/wptKJbz1nDjwWNPysTXH1LnFdk/cMM62o37QWnP7yr0J3zxsXEhO9TVu3MyCO0/YfzyJ/KPhTkihHFpU7uv1OPCfXj79d/wNTJngvPzdzy7ICNVdbDt8bNALxf7k6cqM7eczq/8fNpTPV0aeIh6Fn35wUANihtTbmmLUArftlRGGMxT1G4mSG/Y9KtEYwr3/iAktLl5q9GuRn5JjRQAfklg2wPzXywynCJkb7eiruaiys3uqay8kM2bjhwhzbRRffJejMzs02JfMMWOnaMWuLt8p3rp+M09rKD+ZLFe5rMTUaN+fFwp7YN8krxd84E0JzhZ29msuR/7N11QBRNGwDwZ6/p7galEURFRRRRwgJRkZBQQgEJA7ELscEACzAACzFQX7sVUAQEQWmU7q47jqv9/gBF3898DYz9/XXcDXtzuzc3u7MzzzPTPoS4yOmV37I3FahnAwDwGb39L27d2d7i4TMsbTyiaqE+3uP9kh9/r5+9TwHUhvbcfdzABgBgVj16TDZQUbQO3mDBnRsduPZaHbu3EEFARpjYG4T43VOctzO6/+Gdpt87dwkRm7AoePumRTYWo8Tx/5q71JN3/BRtVvCuXbtD3BhbFj2S/MCccJK0opjyYHlhtB2Rs10+nMx8uWvzo7SoRTNG29zpQRmAFxrnM7lhrYX9zhccCXVz7fYONrvp6uLIapLiiEFIW0tdI7WuOCmtoSPrfnal9uDOxpJTvjZ+8U8elffgKOyWh84nF93kRjnxBHbBUmUeHq0tedyjxDjtl/9RnCNX+jSjIC18jvslIWPZ+gYcrjW9RmS6g0h5q4RU0VzFSSfyq4GMQxGBGTuPhM8gNld0/IwgxVx6AbGXzjg8W7TpcTv65kB050asj07rkNDXlyACIEITQ/ZpndnzuJ3zsQP0dnIZBvNBv1nM7aKiora2NgMDg+++ZSqVSiaTf52IcWz22xtjvwQsV/xnfcdc8WhnduSydTfbeLlRGl3GLmTbTOZRr40ZZEE2TX7hAZ/OxZanR68YdC/bMma1Dqk9ZatnaB5KaxZ1PxJmluc4ZNu0p+cEFuiF2SXtrV11ZVKMP3Of+/pnRApD1HHfGuGo+dsLhSW4ld13rx4rhAOUlhPhveRcA48goQc0fQ9uNXox580WwuekhFUvv2wR7c8+umxD9NX0FhGrI1dnHjH3LPcKt7gXFHk3nzjOWlsOwfN0luVzkMJX9Q2VPdJyXAT5saLpF4vE5JTkuErSq8SH6QhW55S0kwebjh6pxJV1KaleVGOoVtflE3WqXKhxkMnS5WfTqJzrqwzr+IcTa4z2B9TNNj8sK99NldEXYlGr8guL6wWmaCtOCZ+8UsutXc3GSIWnPSmhcsqhKNWoVQnSHjPpVVYxqxWTPdwbNqwqDLhrdzJQg/TRvds3E3ClLum/NbHKSIslsmfPT+VrubvUNt5wzaCLKVNiVutA7p556zK4RXmZJUWC5oq1QhtPWb/wcUqdHz3lztIPHaDwORm3HSTenq1iTeyzvmMT+y6YzC+ffflR8fHxdDr9gzG3se65D9Y9fxr22/FZH/vtKDq6KPh+Ewell927y7236Fb/L3LXA0+36qAzTpLffxCLUXLC1+9MCx8XgypkFbrPQ+3/RnwBvngWPTBKj89ziHit5ncmykGJWHfKdrnA4dgpjDjLubQVE+8lTwrX3zYnf9N1t8yJeps5CrjKJgFVMWYNU5DSg073FHuYJ01/+Bgh5b/sGGc2b/NBWS/9/SZRe/VPWi3mG8+4N2vlltn+DpYCZgGB5ZZ7KWMnqBObG0kSvOrW44q2hGch/GSVsRLdVVVpz7mkceWVVBaLKaYp1JBHFbW7EC+yxOHFqshBm5fkqKriyvJo864dqHNZx70tEN23pzcR9SGfKp9l7wUGWbRB7Mi9SVFW12xX58uIM+s79LedXTbwiZmxJvZZf1v3/Kv8+mMwfypV97AT7uz6q/4O5MhjNuJdT4I89/dOINpm01McG+j9kFHVbbQ5oHvNhkxhdcct7q2RB1L/f/b7100gr70VWznzyGVX+Y4TozWmz7ghX5WSWU+RUx+hIz3IRL30+us3s+hrzs3SuK6hIT1u+/7RCYv6Kha+Vf6EX98k9t02hUHeq6OetACufOdC631NLDll+uPrcsI4DhPl1aFmvmh+Rq8jVt5wsbtTl1ZFNVCXQQi8wpIikmWXTr9A83276SwcDiiDRipwE8sy79yM4anrytrlYMHLy6Hx1at1yvvPSSESH7Kyi/d3EblEi6tI9g4j0iPOXCyjaclzt+eLmQjTWwsHbzmoFnGgQEGiJDFP26juym2Dibz3N0bPkhziotNxUWn56XgnvtSAOQ8KHmfQNRZXHjz45nZv3KvRFC2v3cFcIfYJ08NXMjbOe9IkDAAAHETONfTAsHRX15cfmlCGwQww7N4zBvOjoZ3PdrgdVt6z306OCARZqyUB82cZ8mTfK+3BCY9bGX7k5O6htyMyOkHeOyLEUkHdZcvmOTKkqRHhpkjSlsgqQSkJSWFqauJXvaW8yyGvtkMrlwWsu8JQ8tjmJKSy9dJiWcWp+IzstJMFVotGc7HbHm32WP+Upair57JmasU+v6hO0/lmuNevXl5cY2MTkGqg1dxMb3n+OOfpzQ6PI6snWU8zDjjiK0iTVJcjdnZTdPz3uWmrqPM1KRmJtrdVN44JDVLrYgoPNxCSX3LMAX359NGDJh37VVaiQpoTw5PDh/GhHV1AozEKt+98rWqgriAtRKZImgcdGK45ElCNCH9TTUWzs/UtuUeMpIwHJxU63S3NuR0sVs0EgeGmPXlsE5fJs0P/2atHI0oPkW1v1dl459rpPWaEhgzcpNEiSP/NXSCJKcuI8+D7n0HRjwUG6Y9G8p2PNwbzXWBfTAzmx2KUnli4qnnx0SW6PMi/JxC96UFQHIlA7J1h9GZK+ZYp4vh3Z3WNBoDKSAuba+3Abk4Mnj1n97MOzrvv814OhrwjO4/el1q4fdcms56XWz1CUzMO7a53WqFLBuBw2IV7oqoExAQE+GnVNBynInp+cKXEDP2H2+Nq9N28pypLkSvqaRwOyLuvdRs5eMzIoo072DMkcBbTFfGI2IRFW8KCJonWxm27UlRWXqns4S5TWpLLPXW4qvVCK2m8IC4rkTl6qLS6Fj//ROeh3CQiUh05fWl2R309mwMS6qPkiQ1PUiurK9tJuLprXq8PJ5UC6MZkvM7NiHWUIohZJzw7Ff7o0VJ9OeXR3neqOnCspzsTslIP2ZmaOUQU9zSV1gtQUu+/frJzrstJPvrN9FZ+StmF2zeWzLCdPHT67RE2I9VESe9PORz88bvQGMyvDBvcxmB+rOMufvdx5uxFzjFAVnULninGW//4bFQ2k1pUliXc/miNYw6Bzm253b9tcy0AsGviPZal8ltSli+Vs17htcw8erGTE4Uh6nhgZu/m3q64tWPstlpq8u9ALtB0O3DO1iIR3tePUx44jDzUUF2FQ/nE/R3q91w+vjZfRp5ZLcCTcCO/QoimoizOZlN0iTwTg2dc8rz9mo/71entj4VVebuJYuqS/5xN6so+JL1kRf3FgvoKzs4a3imTmfOWmUcvdrpfk6O85u5l2wIHjYU5CZ1zcY2pY7SrIgMeqc4ff2/vkSc79moLiItKNadsPYSwAeE3MFesuiI6fXB5wvOcZ1xAInDx8aOd5OETuM5PoXOW43AtoMJPSEW6cLxcMurinI7XLAarraaHS5JDo7bizKUIlxqrCmvE7iVUUrnoRczhIwTrm7klKhJ7dOXqDkTeo4iKSY8y4b/4YtBEGV693gQbmmcuvD0CcRsAAFb3Bh/pDQwyFYCteUodRYHQG40Eg/nlYN0zBvNjeSS1e7z798S4hHf+Wtv/ME4PAEDa6XaNU/+TgfFX3/3nd1bckuADeavYtVcO1vslXJpGjxg1KkJYVVWQWt1I9FvIennPW79JP3TC9nFU311B4qn2zzTV+esymgXKq2GkXuCDwz5OqXN3uB/Y3jf3WMzednTD7MOrdcjo1XP3VC2viZhXHPXyUHYOTfBrXD7WK9rJaHtJt9oIK1/TyS+m46ZI8d7irU9PY8uM0mvnnTSy8/4rCX1pmuQYlfbj1dJyCrPMip7y+45pOovw0gtBT6LhXnPDSwclya62mvtTVNBH/7RpGQoVP28jDps7rPR4p+IwI+K1ZMMhnaefEkl4hKK7aa1gbIpAYVZ3dYeKGUlthH3n+VsNKE7N27ImMZFblTvn2IoqnX35o7BlxJg/Bza4jcH8Rt5dcUsmsEsPzl+fknP36urJix5lnziVnFRMx+EQBIHSuJgafuvVRhXlkgs3O4h0dTc8Sam/Yq/rmcV57DTc+mRVZ3d9GTJMXYybJTBGNNrULKiEnLpyU46AKK6xin/+3fu7PDadWa1DBujJCdtSqWGyNSHhzLn4zbLRfjEVRIlBtkcu77I09Nm/ViZ+ffLU/eYXFtyeEptw0IZWIySh2Hy3EEfo4IzeeHBmxYtaNt+jyKtP1B10ik5nNiGdHECgm1+QIqmgavKiLgZHEprtKUlr4QhyjRCggrBER2F5LdLz4Fo5rexCm4a42HDJtBpq2dVMzZmMpy2AAyAI8Nan3HtZVUdv7iCqTRZI7dKWlBmrSeHuSMv9v1XP/5e/GW06a+t6p/PL9jb18WLbwxXs734UMZgvgV09YzC/ETyZl0SUtdu7PNV22eWTO3YYxW3RMXod2obX3n05KF53xsbA9sakolGVcrUZtWiLU+DrKlL1wXJaXRuIyvCjrG4Gq4eBEnDEnq7ijNScNMBTRI359h3NKmOIsaubWsW3H19yxXRWoGudEmGYtcTt1KknLIO2JOdaxOmcnu439uwu87Fdm4rpvdOcmW8DY/HkXO6rH8qhVqencmZuXW+tLi/Crbz5WfbkIPfzbmfXT+VZ7pNgZ9W5/+lCkSRnDd/ddiPI2VdrZEQFpeYfP3JrbMy00Oer9rgkqhmO03/RewUvOnt4TbtzmC79/txXDa8zSUZrr27XOucfmofSOoxCLniVrbkiaRZZbvJ4satcfM2BFz5Ooc/GB494d3/9OzzqYTHb9Kw0dMeCENrc0663jS3rDz/3T3TcQRxKT3rFprdLuB/eJHP8zaz1neP6Y3Me9BmCXZpjfiqse8ZgfhtynrfOAwCAsOneu6YAgB65kGbtXsGlpN64YsTMNkREHVUfJfiK6WnPflI9+cIjOQfj7JUWSYEPJMSVJHka2xEaD6O0nDXeXPRBMpeZjwMzYdeVRzekVAVFOtsqCKNNhpBTdiQ0U7tLEE3CwW3EiUr3nxUiCoKEqkM77iv6+ZCqzjwmG0wj0wCgNzDWho6dISdr25/VMGXLT3n6hj0o4FZX1BxStdzcuG3IUr/0zVtaFGTu8JDSdyWkjdmgTcvdfaPJecjVrgmDdY/ta9MQOCsRcuq5vef9OrKSBiX/YS0nJSS6RDzg6jbN0357ci5dfEoZifhtdBu8ltt/IePAke0r77YITPeSOXvbbGJ3wtinxQ2TzRuIam5HZsc6LuJZcS7o3wkn3gmPitKq63Oz28e46hkILfJ86Hn92dPiwUNpielJGTx8Xblm0QlOfKkBDvsO4qv6456+cwryMw80BgNY94zB/L4YpScWrmpxdxl8soQBC5OjM23tb/OLDR+KPxqyv40MZyeO4+pp7Ag4BxykvYrDJjbROAiNzkJxj1KJHGrZrWN72V3dQJYXpzZTxQaRcpOz0w5svFdRT6dIqFub5l6PuVTRHnuTMMRBKefkDXZulqpoB3mImcGqLQRUrsl25YMSqDokLEd69pBqZKN2w3dReis/L/cgVc2uB/facAxq2ZXLO8n4tnY2T3eUfxTKf7cqgynYedBkSGWljZGDaFvdNISrrtDVgak3iMrBce4c9jl0hzpsJL5hsJdKO8ILd29Jzbz87OW9pf6h2dqXpDuvNNVUdNfnvWqyjRvZG7lar6m4sqleyej84rgR2485D2I8CXLoW7q9e1Gt77JseXxx6nPHeckybdWSPh4ltQRdJbTydUrUIhYh98GNxpFa3S/3e2eQ+SV5BaUOTJ1eRirNzGELaqxMD3I8ktXSSqUQuExC9nXt3PN4Vug4AeTDh+Grc6p+OufYl8aKwfzxsO4Zg/ldHXfxu48z6zz7PLGELHZnin1TTTs38qJAEl+bxTCetGD9kmY/l1M93EMmKb26Xi0uzOhmdiJAYEnYDYfraZ1EPJ5C4WIye6ofl7d117RTeMTECOpjVZVbSityDwTjWV184yYL3ErqLs+kAEc0MO3lrCfHswWVW08Gv3RdIbaHGZG9Ty/F1bVmqfnNx6NXzBM7l0XjFiKXXroM4mQODw+uo6h0t6a52TSrqamF2mo5aUTurOvdnaXVHbKLN9XfLeci1srJauq5DX4WBypNL0hK+U+pmqfiNt8dGZ/fTOIlMyozGvmIpWHeVEF57dGks6sucOZG7x123X7+vXLdysN+u3RWbZXdNT+xDkRx0tO85SgAHFmrt0kpejQoWl67Ny1ARvvl1wuRy88sC5WXt1wpkb28rLFOimeCGj45T8ZEsUehlu6xVeL4ufsXUyp4Nc23bWo5cuHE9idkPpKENm/mfZa5qrmd/2Wn0Gfj3h82f+tTOVWlY9yXJeJFyApzQz1at61+L+fYlReUsi27st+OqPvuzkcQlvbS/V+WcdVxB06bkdXExWkhWu87YC+H/ZT/ebBjisEMvJpjUxZJxJ2b+nUBC9/OCc89tDFv2trZcgRGYaj5Sm572azWbQkbBqeulPdMOGAuSWp6xB3+2CjqYPWqfyx6Y1PrzNS5w7MvYdoT06HBhmd2da2PeK08x7V1md95MbcNs6/ualo66ZlvqmvM9SNJc00OIUJtg834CmIibiJeQTP0JQr+P6YHWlVPF1mQmuPfduWIn+PqRklFflE+ucPPb7bhGIsLn8y5hyqbyhi+rrZjsoVKovBoZwwfISu/w0nrYUBxjlYeBxDvhxTuDasNHha83skBaG86P3fJYAoeJeDr6philafjq9vL93jM1RrM7AKiz+aR57dPsxjN3N35j8PxK8uz57ttenxuDSlifbScr7u+vkQBAI7MS8Hh8HIaDv6xPtQgt2RD3dRsMnBJ6q+NurhEtvT86GbpqrCHESWrFZM9bliun0J8PClmtWKyx5WpTiqXrsr7uuvkBDNHuMqTeOQP35r20aPwqZyqzhfUQu9slE/ydD6Rpv6vnGNvs369GVGPOjGhOyWt/kszrs7c4CA18c25CNY9/4mwY4rB/FreSc+8IkDwaNBNKp5KMAvZbZi0Nbwv2Gfmhuy5K/NlxXpqO/S37h97ZcO5q8/W7VumbDBEhDx4MFce2Zy81XUOrUnMfb9k1tbNGWRBtqS2Mh+u+u2bCJksGbHOx/lCeR57dIjesGbuhw7xxSylpvqGlujtlR31cKpVlTvTVV2RwAQB9TkjeC+t9NjBqCwTvBZFxVGLarJE358jjYjaWJGDgtUEdhLwFLGh46Rfp9Xg0NJuwBFEtWWrU3q6us1ul9AArBUHnWgrVWhDJPAwBppXxN3uFtZK3KB+ff3l5e20EIEJG2TqampoS0VEDTqYMhPGWHSlnq8R7Uwu8jq1+vHhpOdPy6YdumenLOtYbgHArvQxvi4rQ5ZV37s81XbZ1VVqb9eU12ZJfjCbAJ/Rm6XkIg6hrh8ersZz969Nb8rqGDuG/yPD2gDw6Zyq7I7soxtWkmndwnLCVsEbyE2PogOjjKL34OH9VGMcFgf3lRlXZy4+tT5a/s25COZPhHXPGMzAYlVfWh3wT2O3a++f76RnTr2XKfbmkkuEW9lly2aV3ssygebniLzb7n16Ka6uSZfT0qxPp53nSw2Yk7zrcuDb7b6J1x995u1TI+M0AQD6AnGcMeyvRPSRsQ7tkVedJXBdT5ZZn7NYJXjsqPgU8Rai9Tabm3N2sscYylR1G1040b1mQ6bw0CXLZolHe61zsaG3SzgveRQnZeZREnuBKhX4/Dp/QAhOm5HVIKF8t2rW2pHB/kWaY5coJhAP0wgGzsKpJ7zFmPLlHA6gXm2sWWQ8L8jfF2sJeohTGKoXzqHhuJsqUCkr0XLRIcMctPi49bReJfTwlbSrqnAzCotLXjXQqfXNfLy0/rjlR85MFYD+uXJ2E/+9e/8djeTtUnI2m42iJ/UIhDc7ZK5x/86Z9yXpoU9bmrbtu+ntMLtykIb2STMVemVJhcjkgMBU4TdRZVYtuL7vWW1l8SvpKfxZkZsze8+T+CmdfK9PP1TwGbHDx/kfWrOoe9QKsSMeTg7nRUhqXrvk+99ByGTJiNV9ZY7oDcsTSN02OmykwFHPHPMQ6bpLX34OgfkdYd0zBjOwCDLWO3e3TFn0pi32BvJcIluacLFFQ2XMEKT3kivm2JiHAX2XZczm/rHldy/CvjX7HKPkxGL/k9n5L24HjbUN9BtaGhF8r9QSJzwuMHydauEyPdtgQwV574gQY+Zlu38Pur6WFmQUZSUjMjM3zKLVbjpTi69LbwRA5cLsekT5AIjtzGciKGqfXo4A9EYjrePjzsZVOBXiZKpu3hVQppkIJRcWEfU0Wm+VtDX1cID06lT+7MgVXIvSjCy7bl7J7GyuBuOwcFMBQvU795gHblzXaBphUXqrs3SemI2p6JBt8ZZXrTeo+vtm1OwvpzWVljRRKzKvvq6uLgDPaINre+8iBCpndMhBw6Sta1Nxgslrd9i9jAoI89xf3n3ef+0UL318p9F2h+TJo/ZFZfpfmzEXp81AmjaHtwjMfntrWTa+3BwA4EqVFQDRYTMhAAAgAElEQVTAe/FtMH+en/bFRrsLY32c18SlNwvq2wTFRs7X5kG+rgAG86dhlJzw949v4iW1FmS9ILo5nqYARXPufLOni52cKN0IH+WhBKWhgVuQLaktkTzLYOGrMXaU5UvlrJdOBXZ9rOcWa6v6rBONO6bef3OB9Y31qb0VW2HpZ9hzU076yelLSVX5VSSN8riLT4onts265HW5hTGExE+6bDM9RoL2NLXz0EvzCbHX0lKyattfPW4zUFJRq064LDeIYecroM4j6+rVHXOthIMoI6DNi+drYBEy8jgIAgDF/BTV9m4OiVwuKbm9FQitr6Yr6Ou1J8IpSk5orrbbk1PKSfwiXBJz9xsEr8LzTTwcI3Zs+z48dDLJkkLp/o5njTe/XB8j9zXjurTU5fOeeZ32UeZUXDlwXWCOxziJ7/DTJ2Vi2r3jaZpElan/wlebb2aJJPFZzRGRlek/dVAB2VlTyU/o9TkfHgXpP89Iwjnolt3PTH+N3VrGvPGzooZ1PVlm5p0+Liq7JidmUsESM/+H7ejXFcBg/ji1t2IrbCLOnEm4FrdpUcACtXYJ31DrFL9DQqsjVg/vrm2lSzpG7rfnKylvzz8WU6uxbvewykoqtfjYwk2wcp5kDyIwfuUUeTHVKYY8hHE7LhywkQUAAEb+9ik+ydSvrAs9Z5/XmgfktvDlyXys9CoCqSW/vqesLj3+JTelbOvsuYcqRYarS1MAOIi82/7zxyY1HJ0/1f6iXPCVW5eXULLKJCREBuOeMCdocFMoLWWV6VezO1+9UuOwBdkswSZ6OwJJ2hPq+HgRFFVt764FHI7Rc62gZCHKy+BAg+AiRkVFlSZD6/gDeJvnAxG18JUL1VcYNz80h0MvT33eRCvPb6G9yi5+cCMn6/7Zg7uOpdw5fmHTFEt7p8Arta1PghzmuLnZW3ueef1yZ++TNfW3A83HT3deEHS3kd2RutXONjD21qX4u/c2TVv6tDUvWHeQ15PWvO1T/b56dwEAEOXNRlUcCn+pb6plYC1+Zc9x5qTRPPnvpjwhCCiM2pAQ7WNoE7zBgjs3OnDttTp6f8qTd/OjUNQnyT+JvSow110x8eglXlPKqfdSp2D+Qj+pe6Y+P3K+c9L2NVNUpQZZrNw5k335cAb1qwpgMH8ARskJr2nTZjvMtrKcf6Swm5uXxEzdsyJg6YoY2kjDkVN0+6bm1vXF0OaBNzG0j4d7DiaiwEHk3XYfifTnefqyL35ld06QkcXl8Vu8/h03A+1ICZ7j6O5mb+15/OamaUtTWnODtJW8nrTmbZ8yd9caO2s7m0mTfM6V9PZkm5HI274aSH0do5um5Ll1hT6tILOBxN1d09ylt8hKsLmsEkSlBYlS844tkBWUEiQJGDhNMJw732j0vGmyBAEDS7N5RjzEmbTGu0eeSAjpnm2pTz5/9klHGw+KMvC4TDtHIoBh4X3pjs7eITFxIADAOBdRz5rnLnRU4ckMEt+I7lesttbIJXeVrcU5zMKu9vWukaRFW61HuWxcrFyHn7k7cLiKtq7D8cRgE2sr3vrqxtKsZjW/JYJPn+U0sgBtuLQ9fZiHxzTponN7E6kckPeOCJmCXu/fe60PdqdZRsSdv7CBcjZNRaPs/rOnxe/u6v+AMthCJTdPw1yFzD/MWiCpfvQ4KVLftLKT2dSCG1lvgox2pkVuPnT1ZZektkLnOY9lqeziw8uX7rjbRH6ncLHCZIF06uiRIyfgHzPNR0uLf2A7mL/KzxkyYbcW5HTI2KnxIgAA3KrjFGgHchtZE3gJX1oAg/kT1N6KrbCJ+WeeLFp5I74w99jB1AIlh112JVtCT7oYnp44X6M0cHU1v6bI+f1nxcn0M0/pWV7t6bTA1KA5R5PTX9Z1iCiptthYhrHK6yynF2VFn3VM7GjkKMzSOvOBuBkEWcvFSxnNKQeDk3COuu+uyXknSNacuFfDQN47IsSYF2DLLuTFqLUsgYPzFxW0KfhcjTEMEBuf3PJAfNoQzos5G/hDg97/NH3Tv3snN43n27P8toh5atxyXIeouNLtXasNtswXAiCxcUoJUfyAp3PY+N7/I+LpTAYPAG9sPYvC3dND40YBaLUqastxj6bjFlxNoEjOKkvcKrvpEa4HZZZGO9lQHBaJ7z3fKTzjcIS9HLHtYiZBTNZATVKVeedSDUqQcDoQYkW6fjhz58WywCaijIoUgSAgI0wEBOmNQA4ogkPevUlPVpssf/zQZSXnBeJHj16ScDr1wQAhn8c9OqK8GAAAKJPO108CAIAlH7glrO7zzgS92zXObx+b9hfmcDh6eWP4+PiwW8uYXj+n++PQ27sRHmHu3taJ5xHmBlprN+fLCty6dWvSpN4vPhgbGwcFBbW1tX33KrJYrJ6eHhzuV8kRgqIoiqK/VH1YLBab/aukB/jV9g8AMBiMz34z+afvmBe7a7Evg0WQt/CYO2WqXOS5iMWb8N1UkoGZUEGBAl85U3FfuOcps+CGEW42Bu2GE5IqL8asv03g4nAJEF4XtckIkSTsFwidLHmYTBu258C8s3NWFyj4uxd6bn5wYY3+yaCYkSsdelp7WLT6Z/vWnZKd76ylIZzNkhor8eDQOQUbN/6YiHPiZtbkq90dbW1oF4PZ3cXiEiFS29pYzKrzyy+OPPn0hDYXs2if91Uj3h5515mWRvroA56dL9bzZaw7a71Qjg0ehxZCdxt7WGgUAEDE0bcfbkP4SQ3Q8lLFj+/hZJkHeiIcAjpcFnlWLtzMi/IhlM5OAECJeA4T7ZYV46lutcQZ0FLDO60MWlUiUzo3juXh4aZTGUxGhcKYy5ciLXC5jXmt3Ay+MRuWpbk4XcYpGBinbp7nPMhpqRZeUKUoLMN2t0FyQTcbz02gtbWxBDSk2s+G7ECIgrJXn8gw6J1tbR0UIyeB+ZaTooSghWPqPV8nbIHdBVqrsHO44qAC7qcZeps0BDhJWUbB0P4DflO+EtbEPutLmtjPxOFwEARBkG+aJcVkMj/20s/pnnEUAS6U1kpjA+AA2LRWGnDxU3BfVkBLSysyMrK3HB6P5+LiEhQU/O5VpFKpZDKZQPhVLtfZbDaKor9OfTgcDpVK5eP7j1cZ3x2Hw2Gz2UTiL3Rfrr29XUDgM3FFcuOuIE4h+/vihzw97KBqHLpv4QOPY3K+7jo5wad1160tvK2n6uCYxbFdLhAYO4URZykxc6nejRsKfQW8lI/eVrNendAca1MgMlLJwmB1rEPZILvYe3YAALKvt4zX2SNK4RJPDuAZxduaeS2umMUopTZoTSU8dKcuNppOWVo87aCjYov3Kr+7tGZR94N6ZWsq+QQpJast7E9Qh8w4s2WTnPXSqVwkCp+goAAviSg9dbHhulULL+Qlt7k+/GjTa2qC/HzIbwYyCj35jLZuMpsDwEGelQEAQBfyJkcUwmLjAUSrGgFwIDeJe5AokQD0l1tmtlXjODuKjZSktl6bL390/kKvOxLcyu6bjXlE1XRHyMghaV2KkrwkIpAovHJTVxgdmfMabp8E3wizspJuPXFBQfKYrefXJI466fw0yUfpbbMRnBl+f2Z/NcdNfvtQ83zZdBRFCTdrHL7+WP8IWBP7rC9pYj/Tm7WL33QGQyQSP3ZO9sW//qzOmooWoqSsWN8Vbh82tamxEyckIUz+1AkEXkhdm78mrYQGgwQA6CVPq7jUtcUIX1ZAVlZ2wYIFveWKiop+qbMnDOarKI2V2OlmfoxHkNADI32dRMlXXp/+p64/mMabcB848ckLZV3sbM6Is9tI03nE/r+A5FQv8TkzLKOFoRnf3+cMm6o/2fPs+akCbTecHYrWnbA557PjhSDp+emnHtuXT7gtJmq6bc2NHSuWIgw+0xUBgkeDrmzeQeUzm4WDdm6S6pJdCxkHjpTTjviVTPGSWbUq5YS7XJ7HLshcP8LWn61vNVmuN2QKhd4uJz3VA7n87EqRBK1LgYnyNtf11YAAwO7k4+4BFgJkEaA29T2PwwGHAwB9i78QBFAOtFRBZzqxkkOUMoX4BdBxZ7DrmtWPy8Fp0yXjNx9p7NmxAJDLWNK/F3uKDtcIWked3zVJFAcAcdp9by2sqjPGdRo2yRnzp0A/q6fy6uoJ4n3FhQy8TxXR3r7GKNyuATD+UtvnNtKZvFCOd9TW1GZ66/O9EwSkXO+1cVBWw9NzJ6/kdXA+VuD/FBYWpqamfr7OX6+rq4vJZP6ILf83LBbrl6oPm83u6OgY6Fr0Y7PZDAZjoGvxnra2zzaDL9fz+uKpjHYOpzFhrsft9nff5eo0heHT7e1tpowzXnCu6l9fkYoIQwVje2eHKbqKxlvTSxJmW52oZaNdT5ZaBZ/baOPtbLXIasg03xUrAhc6zA09tcRozGSPsFsZr9vpJZGThy9LbSzPTH325GrYnJEetx6tnrH51pG5VtP9FkfdHmWcPFH3peXsdmEuOoGIAqAAbByuS0GZYzG2xMUPjYxEk5LQ9mZ0owIKOJRCQQFQfUN0pgYKgAIB3TQOBQQFQLlIvf+OIgiKU0IPGKMIgi57gd5wRUcsQk84o1NDUPp/2GP0wii36YtvNLLffZJVEWE+62obymp6tMnGYVd6+zuvvtPEul+Gum3OoKEDCmtin/Vdm9h3wGAweoc5v8WZM2diYmI++NJnTzR7CsJnWm3NHeqxY4eJUNWj0/sOOY5sIOTE20rjP/ev7+I1DL0d5u1kLbu+TUBn5o7b+0wEEKAVH13onLKy2EKDj/jBAhjMX4ogKJC3wsNdAEdV8o96f7iToukddspNmlWwzXRdxvOS+ZsyhdUdt8zJWvnQNtaGTkfBcoVVSjAre5+l8yQ9Aa1za/xy8m7ce/iU30QXAZRFIVZVy60O0L4ZeeIumZuReSF0wdGmoUFLBLtOzFhcqT6oulZGTi2wIHYkV9bgsFuStG4EvQwALC5SkxJ08Qu+cPc10uO9W0UpTX0kcfjkNNyLgpfiSmOl+mr3VAigHHroIGEM7ApIKAUAQFhwtAoABUCAjw14BaCWA4oAlMLGOiAg8DwMTsWA6TWYMxmc/tseI6vOP3rpg68wqv9Zse6G7vZjzoMYqVvtejNMuB9a8HrhunwZcWZ9h/6m1UBDiKz8nVPehErddnyZNuW/VQSD+U4+1z13Z+3fnS7qdudulKkgAjDHdd54W+05Hj4J487PlvyaDhrhUneLeeYW8+5z3IZRDZxPFcBg/lI4YZPN5z4cWJKeH+U/7yGpmyXutGYBz80Iee+IEGNCdlbvq93NefsXby7J6xbT897mPer5rsgCRnUujN8VrH7rfG5pyuuScrIE1461tNqe6YYCnRlUUlqFjnjToKDOZ43tPPE1AACQ30Li7TYYnIv0VAWtYV3fc9D+0krm/ssW0f7MffvWP4soYYg67lszsmq+o/0lCW5l9939w+u7T4LuVNhRDvWPoB5g2HiofQLN+jCoGcoBAIUGBMbbQOhEcHeAYiI0NgEA3DsKUq4QbvEDVnp2pW5b1k0iWLjLUaDt1u63wc7iK4Yjcq6hB4alu7rmUEcCQO+S7t5QqS87UG0KdoGAGVCf654ZjcWNeG3LYYJ931SCrO2+AyfVnBZtTDI/NP4XukmPwfwlKBoLwmLcpHEAAIz8uwIywkQAFFAOmwMytivHJ/KGrpRmQdP9Y2G7m6Jj9iT6Bg69tGemdq263EPvWr2JfA9fqDEQrsIi5AkKACwcgSXIn84mF1jPaHxVkapgHxTnKczDDQCmvW+4bvVoAIAxWgBvA1YDAMA7d4jf0tACPRXA0QBpgf37wWsBRI8FX3FYtxfujQKcGCiLwINQABS2z4R1PCB1Fa6UwxhjOLcFBBG46QbrBeDBHvhP65D70V+dXrXiXA2hJ7+AKbt97wHeYM9Nj88FoKzWMwsOGp4chgCKvg2MCs2Pk16VjWC9k4arJ22Jbe3SuPnyXzVIiMF8T5/rnokiyiLsK3dfdkwf1xdxHS9ju3/3MU1POx+L7NiPZ1nDYDA/D0lmpPSjtQsKBKgdREf6nT3XEmmDmluX1wS0+l3eRsOLnQ0EgMEA8gLVOGnSHa7RY70VIp73VBJRju+JveYF+4dsm7b/kMACvTyHOQI83N9Ul1YScJrBdQUM1Yb93rD8CXRrQXIuAKBcjcirJrj+CIg5MD8GTK7B7mkwaBKkp4OWNgQ6wMEYMLkGXN+6O4oj/C/oHDy7R64ucpJnTc8rotO6iaGjNO4Z6bQ9eR7jbRZWStJ7FZ9SjZROZ66+k8FdL1RTdiVvRn1GfOKCPFxTJXMmAKCdWeEu4fhlB33+W9ASDObbfK575tZ1c1GJCLEY27bKd9YEM4sxitwIUcktJuqajsvsCehGdwoW2wuD+XkEpp673v8XScMvRuPVKziXJ1oieYWnGV6UQr4jxNP0AIBIhJZWMDQDLS1QVgZNTRgyhMzPDwBTAACgP7kVyL+fa+HbzI+GInuI3AYnjoCpKyRdB29HOHwZADjRW/C2a8BqPJBlYE4k7LIAfhw8T4C5gZD8GlYfAN1JEGb67UPcBY/o43fLEnte3ymQFSm/lpBuNCpFKyYndhr8Y29fti5iHK2VXp+0b/PL6p7BolbH4/fppbi6FoKqgir3VI9JavKqyrWrIrY42XD7Jd3G+mbMAPns1DDuEcH3r/H6+gZvWHAqds2LvM06ZACCnHN8Os5vtue6ZVQAUP4JFcVgMNDaCrm5kJcHJSV9D8rK+hYsCQn19cGzZ/c+YKqo4EmkAQgrQZCEPQ9hzzvPpLXApk3onkTUcilwbYb162Hlyv5XlWZA4gxgsWDzZggOhhlmcPo0SEt/SxWUhyOxybXezqpue6LG7TX1amYZ9ocP686NWP9QyddVf6hEAbwzoI2TtA7e0Jcf7IAXIjQxZEPHzg+EY8Ngfo4vWCJIlp+y/p+SdYz22jqGMOnNs5TBjoef2wRnJyZnVxB1vnkwCoPBvIfJhMrK9zrjFy+g8010Dykp0NICU1PQ1Oy7OFb+v7Pkj0cjGgBdXai4OBAIMHQo5OR8oACBABs3wrhx4OgIenoQGwuTJ3+g2JfRXBxmscRz+iVBMSF+ERFFqSGSU73EnfqWiU/oDYt9OItBLarJEu8PZ92ZFnmwLyUzHy5VUEHV3Nr/slPos3HBI/5zTTCY/wxB0d8p2HpvWBIDA4PvvmUsatinYSGNPuubQhq1tvZfEPc+KCyE3lhCZDKoqPQPUGtpgYYGcH/+9vB3CWn0HVG7usgUCqGjA4SE4BNxEBsawMkJ7t4FPz8IDYUfdoixJvZpf1oT+wG+SxOLj4+n0+lz5879/5e+8KvJai148E8iw8R1qjwRAJivj3quSJGaMMtt3iQVbmzgB4P5KjU17w1Q5+ZCbW3fS0JCoKkJRkbg4tLXGSsqwi/TxX6T3i5ZWPgzxcTF4cYNCA6GzZshNRXOnAFFxR9fOQzml/MF3TOz+uqqGbN3pdOlfVOde7tnwLHrko5GXzi6dZfD4WtHPdSxwW3MX4xRcsLfP76OQuD0iFmF7vNQeyegRU8PvHr1Xmecnw80GgBwCEScvBxoaoKLy9upW8DPP2Af49eBx8PGjWBsDI6OMGIExMTA1KkDXScM5mf7bPfMLN43Y/qu5zo+J46utx3W1w0TlRZcr3MuvbbZxW7rfFvtMc9Wa5A+vRkM5s/VmybyxAw+/srbD+7cph07cvdqmUJbowyLKNpYBSgKAFQufrIC3xMqoUJWtmfqQt3GG8+XB3eH7MfW7XyUiQlkZ4OzM1hagp8fhIQACfuZwfxFPtc99xQcP5iOH3/0SpiT3PsL9BEupWmb4qMyBjkdPV0YEKxD/nGVxGB+Pe9M3VIoEj31YDTXgnoik2kOAACTRUXaRYjJyJBhBnyXJ2z3NW31DeoyxN3mCu8NWXULxJuPudhi63Y+Q0wMbtyA8HAIDISUFIiPByWlga4TBvOTfLZ7rsyoAHXf8VIfDJ6DlzCepQW+z6t6AOueMX+yT07d6hHmp+obc0+XZUnWLbypYzc8+bzyInednOjTurLKRztMzUExGY8rQFFAAAABBFAUW7fzhRAEFi0CPT2YMweGDoUjR8DGZqDrhMH8DJ/rnhESNwmIFOJHfj9QVg8LCCQ89vOC+ZN85dQtdl7kmiXnaorolAKi5jJHsaKX/87/CAAgZLJkxDof539ozaLuYYOT81Fs3c6XMzaG7GxwcQFbW2ygG/OX+NzCKlZJ2AiVFaInS285Sv3/7FF2dcxERdfGzYVZK1R/yvR7bGHVQPljV318fOoWEIkgJ9e/sPhzU7f+yFUf39F3aGIo2jfQrasLZ86Aisq31AdrYp+GLaz6rIFeWEVQsAmYvNrZe16Y6hn/EULvDnFz2jMPuPs/AsMDtsq/0BHEYD7us1G3lJVh2jTQ0upqiRwaxT1cjYfTQ2Vwxke6TxLv+/J3PfB0qw464yT5rzZJz9/ve2/ynvHHF+ZhqRR+kN6B7tGjwc4O9PUhKgrs7Aa6ThjMj/LZM0e8jP3R04ljrZcaiO+fvMDZTFdVUYrcWVH04lHcoXMvacJWh2PdlX6V808M5q3/j7r18iV0dPS9+rmoW5ybCYM9d55cIIfvTl8+ZdeWGacnRMeaFQU6pjh49xTHBno/ZFR1G20O6F4T1JchOMgP7UaIOMBSKfxoBgbw7BnMnQv29nDtGkRGAhe2shPzB/qCjpUgNT3yZdnsQ+tXbTkYdKP/aXmzZSdD1tjrCmLXCZjPqTk2ZZFE3Lmp/xqY6rsSNb481uikpHZ7ajFZ32qckJBjxBr9vh9cetZGlzt2JwPfrtxj5IfOvWgRs1Lr/RGb1pa2SLvzLbM9cCXwKqczOZO3qQH5V9QtI6OvibrVU3hksetjSnNWMs31xjHhjVvSa8Tulo33VCbmCI8LDF+nWhY6c3eGXn+G4E5dAABglkZjqRR+NBERuHIFwsNh+XLIzYX4eBg0aKDrhMF8Z1923YtwKZgtjTVbGsNoryl5XUPnlx+kKMGLXTNj/gN6drDrfdvYJVL3nL3aZ5GKYwO9r+UXocO3bVQ4dF0Y7t1sNSmPsPfY9aSDwi0kq26k3lx8KXVYwqFDBUQiqPntsWbVZ6yZt7uzhE/Y3AV/51VSpWRXu1gXVRDAA+6y+bheEXkquCk0m7ndr5vVoryvOHvVRCX7JzodMlq3z+jLu0yymsfO6AVy+M6HXnZXaOEWHcExx7tNAhWJFW8mX6M4EoH4NqHCm//DpmT/HL0D3YaGYG8P+voQGQkODgNdJwzme/q6LhYhCcio68v8oLpg/kI44XGB4fMepeuud/OT7K5oU55jK1IeFV1PoYipT1BDCO0PnkgP1eWsPbXGbJpmQXKn20Te17kXmGwAYOMyUFlJucFKzeTWo/TJ88wyN+nutzi9ujOsd23xXf3xrdcbqwoHD6UmpidlyFgt/E+XsyRR6e4Xr3iDjQtHn3R+qkCECuh4tMYxh0Dnttzu37a59l/lCVgqhZ9oxAjIzIT582HOHLhxAyIiviQaOQbzW/iC7hmll9/au3HvpdTCWlRc08h+eZCPiTS2qAHzn6EcNgc41MbWHiJQeq9EuWUHDfcw66SONCjyPWzIy3HlI8pUFkkV5nI3NiPZCwGAmZ+HKErRpJTocpzHFqumG9G8duFmqVy8LO/rrpOTcnq4g3pFNzfPO2uLyWqT5U9EXFKe6yUWdfSShNOpr5kSyz8pri+tMll7/YNTAO13dMa4TpMjAMHkWLpJf8E4PQCAiUfOQnu79RQBAdh7dgwAyB++Ne177a+fof2ape5G/OhBxI6aRlm/UwdsZL5xcIzT8uTIiWZTTzPaHtfr02OXa/6wnwwBAYiPhzFjYPlyyMiAs2dBS+tHvRcG8xN9Pqhn2VErzfl3uokyOvoy7NKbR5bevJRxOTfWShy75Yz5Cl3p2z0cT5OAomFnIfVo7YJivk7envGSlRVNtsPzGoqiunKHPOvgZp/pLd1CwBfzNzfo6ZVWN5aM8/U2yfY43iAswa3svn1G6uJ881nT5ZM4SG1vZsCobCa1qCnPlPd13EMFnxE7+tYWH9EblieQum102EiBo5455uGC/32kuafo8NIDvAuOyP3BN3Qomt5hp9ykWQXbTNdlPC+ZvylTWN1xq3trxIHUxvI7N7n35RyTOR2w4ykdYRBGr/DtXr3qhbxYQ06zlLY0s6ZKwt2m8oLIgd7Zc267pA+tuUHFUwlkK5NhP6HuvQPdRkZgZwejRkFEBDg6/oS3xWB+qM9GDcs/vPVOt5L/3bTdE0XxwKy5PF/fOnZZxOpJ63/c6TDmjyM943KZ7pu1TOdrrAp6o24lAMCo3qlbJu8kTFRXF+bhGQkAAIZvtnDp7Y3FsXFaABzOhIiTbCLRedw77zJ5JgDAGeO3T8jGl5sDAFypsvqm6pNV5x+99E1b+PXR86P85z0kdbPEndYs4LkZIe8dEWLMC7Bls0qQOyki3BRJcoqsEp2kxdVZkZpUp0XR8todzBVinzA9fCVj47w0jUn0o32z52RbYwpYg+d7TlKTF8HTftonGDYMMjNhwQJwcoJbt+DQIeDBZudhfmOf657pFc8qQXOL7zhRPAAAUdpi8TzF2AMva3oA655/X8+fg7r6D1yO8q+oWyUlUFLS99IfnDDx90bRWBAW4yaNAwBg5N8VkBEmAgCzIi4gnHdd9BRxfCeKiE1YFLxEtjThYrtY3RNeCg7BEbn4yDhg4XE4UWOLjqDe2XNkinXwBmh6FB0YZRS18md+CH5+OHMGpkwBLy949gzOngVt7Z/5/hjMd/TZwTo2gwX8UvxvR7IJAlL8wGF/MtQY5pcWEwPe3rB8OQQFfYetfUnUrdmzsYSJvyV2TbzHslR+S8rypXLWK7yWmUcvdnKiMEQdwzT+704BXnqCceGo3tlzr9IiN2eQBdmS2sq8SNlPr7aLC+jogK0tGDXRGEMAACAASURBVBjA3r2wYMFPrwEG8x38wffSMP+HxYK1a2HHDrC3hxUr/ssWPhF1S1AQVFTeRt0CZWXQ1gYylinl9yAw9dz1/r9IGsviNAAApJ1u1zj1Px8Yf/Xt47gNAACr43QAALbEDQdoV30ze07dJ/rM24Ije4v8XEOHQmYmeHqCpyckJ2MD3ZjfEdY9/zWam8HODh4+hO3bv6hvfj/qFi43l/fFC+js7Hv1c1G3MH+ZX2/2HB8fnD4NkyaBtzekp0N8PAwZMtB1wmC+whe1pacukniX9555Yc7fP7glMPVq+dV/x4PC/FKys2HGDGhvhxs3wMzsAwV6Eya+m6OpqAhYLIC+qFuopibTwICkp9c7dQu7FsG871edPefiAsOHg60tjBwJ27fDokUDXSEM5kt9rnsmD7IN8NGif7IMRUvxZw1hoijK4XBYvd3Gd9WbnuW7b/ZboCj60U/acROvvAg9HgwR23B3ckBoKGfrCc48NQCAugc4/0DcrWxApVBTD86+lfD4Et7DDRgoGr4BXe+Bs6gH7amchVOQczuQpGJgU0BAGFpr+rYsJIRqaKCGhuDkhGpogJYWqqAAOByHw+nu7sa97ZV/wCH4Kr2Z1n7EN+E/+0HfzG/B4XA4vbcefgED1sRUVSE5Ge/jgyxejCYmsqOi4E3Wo081sZ+u92D9OvXBmtiX+PYm9omkkZ/rnila3qH7v+W9fwQE+VGxEn/clr9W7zH7aH0QBJilOO9QdGM4ZycJ9jjjPD3A9BEq/Bw33hwhu3HOHQRcDrLKD69zBbqyUd1BkFuMBB4EKX4go/AyAeedADg8SMugpA6khINuOYAaaaM6Ov8/dQvpe0PkU/UZCCiK/lL1QRDkl6rPZ75CA2Rg6sPHxzl+HDEzw/n6EgwNOXFxqK7ur7Z/sCb2WX9bE/tlbhR9GQRBcDgcHv/9Q6L0bvZHbPm/6b3O+Gh98DhgoTD3GDJfDwGA9QFwPATXxoHXe+C1JuQfwqmTAAzh/BnIegAASFYxIADyksh4PVBzgsRdkDEdCqOAj4BUHwHFIMTCDRlG+UR9ftye/296L8V+nfoAAIIgv1R9OBwODof7dfI9D3wTmzcPRo0CW1vcmDGwfTvb1xc+0cR+OqyJfdYf2cQ+0bv/Kk0X89VwPGD8Jh09mRdwAMCCF3kgaQzyb5aku7kBCQCHBxIB8ERwWwWRkRC4FLT5Qc4IeAgAACRuwAEAtlQO8xdQV4fUVFiwABYvxtnYQFvbQFcIg/korHv+beHIQPm/0y4UfTMaDQAA+loghcCy+xDsARwOrLEBeXlYuRbaWO8Vw2D+HlxcEBYGsbHI3buE4cMhNXWgK4TBfBjWPf9JCKCjCXWJUMnoe6ImGSopYKQD3jOAmxf23gIzM9gfARFVULATTp8CBuOTG8Rg/lAuLuzUVJSfH4yNISwMPj49B4MZKFj3/GcxXApKOTDbD26nwt1jMHsZSLuCsWDfqzqGEBMDNSUwTRQAB74+Az4BG4MZMGpq7CdPwNMTFi+GGTOgtXWgK4TBvAfrnv8sPCPh8R1QSQXrUTBtNUivhJQ9wP/+ODY/P2jzgvoyKCjCkuNi/moUCoSFwfnz8OgR6OlBSspAVwiD6febzdzG9OGfDNTm/j8l50LP3L7HUqZwMevf5fnMofPtLBgKbCvtf0lsDvTM+WEVxWB+ebNmgY4O2NnBuHGwZg2sX4/laMH8CrBvIQaD+eupqsLTp7BwIQQFgbU1tLQMdIUwGKx7xmAwGAAgkyEsDBISIDkZ9PTg8eOBrhDmb4d1zxgMBvPGjBnw/DnIyMD48bBxI/wyIVExfyGse8ZgMJh3KChAYiIEBMCmTWBhAfX1A10hzF8K654xGAzmfUQibN8OFy9CZiYMHw5JSQNdIczfCOueMRgM5kOmT4fnz0FeHiZMwAa6MT8f1j1jMBjMR8jLw6NHsGYNBAeDmRnU1Q10hTB/kT+8ez63Yu6cWYZiYqNnzZm3MqHye4TIoj5ebHu4ojdtLT1nl/uWzO4PlKK/Or1k1gw7+1nTLKwWx5f2hs5kVFzZE5FYjwXqwmB+HwQCbNwIly5Bdjbo6sKdOwNdIczf4g8PSzJ7R+zslvOWLpyoU7OJKZuc55RzcVqI1rt8K/xWZwqrO26afN7U9YWaoRqhZ8i6/eNvL9n5kk1vl3BeIhF3y+yE++2x02qjMv0T7VdVyXB3Ap5KMAvZOQgA7cwKdwnHL9trgtIQIo6Wcyhgx1M6wiCMXhPmpc2NMIsj/C/oHDy7R5EIjPKrJ/IaGCLVofO3ZbPp7RKy5kKlvqszhdUdlunG7eY7EGtWFOiYMv/iUrWB3lsYDOYjLC3h+XNwcIDJk2HtWli3Dn6lzIaYP9IffvX8LoKs1ZKA+bMMebLvlfZwQN47IsRSVkpDwyr8XNxhf560J1f2pFtGxJ2/sIFyNk1Fo+x++tOiwUPrEtOTMsRHI5WswZM8VvqMFcEDszTayeby+C1eQ3gQAICOpC2RVYJSEpLC1NTESiYA0Aoe0cebyBJ7io4t8Vx77HxCZtm93Wl9Gz8Z94oO8t4RIdN1TKbQr6TXZF0oG2+pPMB7B4PBfJqcHDx8CGvX9g1019QMdIUwf7jfrHuuqqrKzMy80ze+1FN0dJH9BHk+EWkxLpKkgdkEE4vVz94dau7J2eawM7sgP/NWOas7N2J9dFqHhL6+BBGAICBJO+c1zdovLjt2lu7JUlrHq+M3Wpmn1riN1rOOvB268uTdMJ8DiKO7YuLRCyTd6JOpPLK43OjAtdfq2IjQxJB96qdDF20La+6kAwCKiE1YFLx906KO+sfs2goAivJw5MiaoPTcLrc9URvG0UqbGCgKCAAggACKEgRkhIkAeMnxFh1xMccrTKYpEgdid2IwmK/RO9B96xbk54OeHty6NdAVwvzJfrPB7aamptzc3IyMDCKRGBUVxeFwLEbKPuvp6axV3LbM/GJAeMysQRdEBRQohNwShE1s5LS2M7iuM2lSU2Sk29u6gPLkLIlJpeJeieM7RLK6mru4O9tRDoRFlEgCkSrJbrgaX9ojKKc/SnG4emd0bGJIaPvzxG6eJEoX9Z+dIVdeZ9DiTUpEOZXXPDvqGukp/I/UJTV5b+Z2tiaOVX6kp1lNkGd1dbq4rA3w8VG9siZgRYaygryIiKKUmJDJkhHePs7/0JpF3Q8OLltTAAAAeOkJxoWjTjo/VcB6Zwzmd2FqCs+e9Q10+/lBaCgQsQaM+f5+s+5ZRkZGS0tLRUVFWVk5ICDg8ePku2duV2SRh4/RPr9l31MOy9JMH19TcS2/idbFUBKQn+hmcO3pa/4S5qiQA6TnVxOO3+niErLYEJngjChrLgt2HPeonP7o3t3OlsGhs+UXJnb5qKkWL9pbGu5xJyZLlY/TXNO8eIwhV8iJf2Zol1cVCo4ZKqY9e3DjU10ygdRTdquEt7qRM6k1X2Ck9ZINk1RVVVetWjXXycnPz0935MyRNiUWFhY6Ojpv6r7mzIW3nyOu71mCsKrOGNdpcr/ZYcBg/nIyMvDgAQQHQ3AwZGfDqVMgIzPQdcL8aX6zwe3IyMjeBxEREWlpaTpSjWnFqOREt0O7d19LPsbT2d3G4HAQURE5cW4e0SHiovwEBBCkrrspY4vXmVJ+EpkL39mSn9nYibJZ3c1lbU18Bg5KMuSmtPQOZgutgp3SUPLPlepVWxYq61gO4eWgeKSqvOCfRw0ABDyfLDm3UlhLp7MoI+VpagFZXlxchYJDpllbW1hYREdHX7t2DUGQkJCQM2fOtLe3v6kyuzLSwuZaO7CbE4Nnz9n9rKN/8WRP0eGl+4njmTfvldPpOdscduYxfvoexWAw/wkeDxs3wp07UFQEenpw48ZAVwjzp/nNLtssLCw4HE5cXJyamtrj5Dvx969VdCPkzAurVuaN9PMz4KekZBczappwCIGBE7/fnncrqoVO4RMVFS2qetVecaIZ4RDw3IYTNUiFxzgc9r7ou2x8EhGYQDy+5RK9R8CzoiW1+vS8MSc4CEm4h4+NFxS91VDYusYEYdFJOsPlK0/eWD5fhIdO6KaWXLjFptM5PPI7F/j1aGlJtKZGEsfIZl/b2dACPW2jbVa4WAzqrzej+p8V627obj/mPIiRutWudwq3+0E/soQ88vLWrpAkxYy1AADwdhI4fuSq3Qs0+QdoP2MwmC8yYQJkZYGzM0ydig10Y76v36x7HjFiRFtbm7Oz84dfruoPGnDp0qUJEyYwGIxVq1YdPhxRGTnO8KjAEBLB4vBZfw3GrTk5nskVG+X/195dB0SxdQEAP7PBEktISplPsJ6KAgYKNhaKiiKCoICiKKU8uxE7wUCkTATRZ7efT1AEDEDATuwkd9mc+f5YRPQp+BTYAc7vL5idnT17d+6cmTt37k3ycrnajHjQOmZnL368+4TXK1PytVKXuEcV67R18pKuPWUb0ml5v83aA9ooFeW+M3VxeHeie/wWGy4AVXBliUeCxda1A8R7nRbpBrmf97vmNaz/wb1brcJDO1ydMOF1D/U7kTtPDQo0aQXFqSsCSxRYth7GipB/Zn2aXdghF9XUGWMPwoHgZc2XeCiEhfRVf3cTSjuBaw9oo1T0LC3xxYTWrbGmI0Rzurpw+jSsXg3z5kFKCuzfD02byjsmVBfUsvT889TV1T09PRkMhq+vLwAAKHWYsfOQ1XkP96VXDsyipIWZkYtmc/glmjpkAUEQAEAwCJDkxs4I4c6Zp7s++OjttgCfe2UHGD059He+zourhppsABDnxs4I4S6IHqTLJKQ9bQsXxOwq6fVXE7aIpaavwQZgMBnsFp4rNhIAIH3+1UfPKN+FW/y8bDuid/DVxyUcLGqIuRmhWoEgYNYs6NwZnJ3BwgJ27oTBg+UdE6r1atm955/Xq1ev+Pj4/fv3d+vWDQAAmByuAtvIceNM/qLA/7WYNcm46N3rh+kP1awcp+iGDLdznhr9mlF83CswVfogJvxB+4kT2ysBgGr3wP4p/i4uLrMSFfWUCAAAkL6K8wxMlT7YMXP6qvNvwaC3zb2QTJtBP+59Xf6jE1v7WRybOs5x5JIS5z43p5Rt5x0JX31ckqKuMlED5YQQqiI9e0JGBlhYgJ0d+PmBCLuSoN9CUBQl7xj+g/v37+fn51taWv7+pgSZS0ZuNd0cMqYpBwCAx+NxOBwW6xeaEwrOTZzwZH78pMZV2RQhlUopivqleKoFSZI8Hk9VVVXegZQiSVIqlbLpdJ+voKBAXV1d3lF8IRaLmUwmg0GXU/DfqGLVorqqGEVBSAj89Rd06AD790Oznx1xCKtYpepkFYuLixMIBG5ubv9+iS5Vt+ZREoojes//3ZMT4f0d07dwJ43AZ6MQQgBAEODnB+fPw6tX0LEjHDgg74BQbVVj6ZkquRfjbmmoRCjqd3IJz+b9IC0Ksxa2t1z/SFz9ASl1Wnwo2qeN4m9uhmMyMfLwhgHa9fc8ByH0L9bWkJEBVlYwejR4eWFDN/oFNZVVipMD+025Zh2e+So7ZsDdgH6+/xR8k6Al728cj1oybnjQre/NAIUQQrWKtjYcPw4bN0J0NHTrBo8eyTsgVMvUUHrmpUckFA1YOW+Qif4ftrNXj5Ae2XGD9/UqgtyLxy89JhqqY4cohFCdIGvovnwZPn2Cjh0hLk7eAaHapGbumErz7mYXGjqacgkAAGUT68b8LTnvJb255T6e2ykwbCf1Md76eNDXb37y5El8fLzsb2Vl5c6dO9dIzAghVBUsLSE9HTw9YcwYOHECtm8HJSV5x4RqgZpJz6SgoIRQ0VSWTZDKVNFUBn5eCVnJu0rdv39/9uzZsr9tbGzat29fWFhY5SGKxWKxWEyfbq4URVEURat4xGIxffr50618AEAkElXHnvnLSJIkCEL2UD8d1OsqRhAQEaFgbq64cKE0M7MkJoZs3vzf8WAVq1idrGJi8Q+7WlVfepa+iOrdyiOxGBjaI08k2SpR/Dy+FIABIOXn8UFJTfEnf3ZbW9uyXVb2YJWaWtUPdllfnvr4VfjUR6UKCgqqY8/8ZfhgVcXkUMVmzYI+fZiOjlwbG9i+HZycyr+IVaxSdbKKsdlsqVT63Zeqr+oyjdwvFVEURUnfJwwwbtlW7VXaYz4AAAgep7xQatlWhy7VFCGEaoa5OaSnw8CBMHYsuLoCny/vgBB91dCZtYqZp4PKyUVb0z4J8zMiFicQw7wsuCB9n5qw9/idIrq05iCEUHVTU4O4ONi+HeLjwcICsrPlHRCiqZpq+OJ2W3t2k+lBeyOuwcCd+qvOhvZSJ0D4INJ73JxT7yQ1FARCCNHDpEmQnAwiEXTtCnv2yDsaREc11sBMKLV0j7nuHlN+mXK38Hdf9w8jtEYn8UbXVEwIISQ3HTvCjRvg5QXjxsHZs7Bli7wDQvRCl24jCCFU76ipQWws7NwJBw8yLC0ZOTnyDgjRCKZnhBCSK1dXuHwZpFKV3r1h0yZ5R4PoAtMzQgjJm5kZee2aeMgQ8PcHV1coLpZ3QEj+MD0jhBANqKoKIiNlDd1gbg63bsk7ICRnmJ4RQog2XF3h+nVgs6FzZ2zorucwPSOEKiZ9vt3W4UQBSD8mBo0au/564ZfnLagP8aMnnCuSY3B1UKtWkJYGLi7g7w8ODpCfL++AkHzgyF0IoZ8genl01oJT7VdGjTO+F+T0v9E7A/QvjJv0ppdiRhr78PnrsaH3jXSErws7Lt/c45jPikypoEDPI2LTKCM8xPwKJSXYsQN69ABvb+jcGeLioEMHeceEahpePSOEKlWcuiJwe4q4lbmxYvnFDO2egzpYjh5kSBCN3NdHbPdVSUk9vT7NLiw24eAixT2xD0XyCrhOkDV0czjQpQs2dNdDmJ4RQpVS6jBj5+H9Ttf9ll4poIAipSSQvPd5ws8D8rLU9DXYAAwmg6IoIACAAAJoM/tS7dWyJaSlgZcX+PvDiBGQlyfvgFDNwfSMEKoUk8NVYBs5bpzJXxR4mm1hcGn+pEnzjhWymQqaqo9ijzz/MuOOipW/xbGp4xxHLikZN7aFghxjrisUFWHTJti1C86dAzMzSEmRd0CohhD0mV70Z8gmlLS0tKzyLeNsdxXD2e4qVVBQoK6uLu8ovsAJJStW+6rYvXvg6Ai3b0NQEMycCdU8kzdWsUpVSRWLi4sTCARubm7/fokuVRchhFBFTE0hJQWmTIHZs2H4cPj0Sd4BoeqF6RkhhGoJWUP3wYNw6RKYmUFysrwDQtUI0zNCCNUqI0ZAejro64ONDSxeDCRZ+VtQLYTpGSGEapsmTeDSJfD2hiVLwN4ePn6Ud0Co6mF6RgihWojDgU2b4O+/4fJlMDODK1fkHRCqYpieEZK7CkbNRKhC9vaQng6GhtCzJzZ01zF0eagAofruy6iZjZ+sHuR8U7Ol85q5utGTSwfIDJshXTfvFI/JY/Vbs8HywKjZd3AQTQQAAI0bQ1ISzJ8PS5fC5cuwZw80bCjvmFAVwKtnhOjg61EzSWg0JWyNnWLilwEy96Vn3JW0GOA5e2oPLSaQOIgmKofFgpUr4fBhSE8Hc3NISpJ3QKgKYHpGiA6+HjWTpW6oyQYoP0AmaA0NWmSrnBP91/wTb6U4iCb6t6FDISMDGjeGXr2wobsOwJYwhOigbNTM1NGBxxa1kC1s0CvAwmvquKP8j9oeW3XSg4JucDSkDds24zJelr1RxcrfYn7pOhG/MYim9Pl26+57DKwMxO/fMG1Ddge2V/7d74RqnrExXLoEy5ZBUBAkJsLevaCvL++Y0C/CQT1L4YiDFcNBPStVy0cclD7fPijAKD5hsHr+qXFjHy1Yzfefc1OzpfNyj7ywLanvn507rRyaHWW4b8aqFAEhYnWds6R1gteyHC1D6b0PIw8dHadf2edgFatYFVex48dh/HhgMmH3bujf/9fiwSpWMRzUEyH6EN1ZOWjqZd6PXhZkLB695k6tvf9bfH3NZNexg3t6P+/ZXZtRev+7UUvX4GVjDRUGh4X0JZKCt7/Q0NdrqMlLObU/5MmkuISolQ4NxNLKt41q2JAhkJEBJiYwYADMng1S/I1qH7qcOSJUe1CFyUu8Nj9TIj+x7TfMgvWyDtXdFy4fD9LXlw6nWf4duqG0K/WWUUbyjvbncc3/Cts1WJ18vXPwpNPdrWX3v0GcGzsjhLsgepAus4gidHr7BQUYPTl0KPfToRyCACAY1Tw1A/pVRkZw8WJpQ3dqKuzdCwYG8o4J/Qd49YzqoIITdk0s7J2cRg226emV8ChjnUfwzZJyr1Mf4kdPOFf0+V/eFf/RO3LLXV6Ico9tCEt8K/nOpqUlj7Z5TQw6dPpU2r2HWccjrzzLKu1Q3VWTfJ12Q9Cq9Rn3LZpL98q6Uv9EsMLsFU6rb5e/5C4fjyD72+CrT/G1lZ7OYx2Hj9tt5NRZVZZ0pa/iPANTpQ92zJy+6jy/a2D/FH8XF5dZiUoth3obhTk6uM6Iz1dQwARNUywWLF4MZ8/C3bvQoQOcPi3vgNB/UPuunimKqo775dRnVb7l30GfeOhWPrJIfhQPRSm2nrxxj7uB5O6KfgtvCSz5wIKClOBJK29JBQV64xZ0OZeRxj54MiV+W45my7GLhwCQhembXEOZMza7lIR4yVbTaXJx/9l+u9zPWtu92X7DcJ7NvYX/BIoUTLw3uiQMTH0xeMl69eWzQpZe02zS/3W0k//DaWej+K9f3v1Akrykpd6eVHbyE3OHpU5XR8cE6F9wnVLi3T5y5V0jHeHrQrPg0G6H/LfkKpGf2MPWTKaAosTPYmfMPs1j8lh9V6/640s8G3qRfGD9Yh+R//KTMYwmXX46qfySfW0BKNB3PvPS+cvCwP3HZH+IHh9us+TAMjPRYfe5XKWfCJBuu5AMfeKpxvLp3RvS0wlXVxg0CHx8qDVr4CfuKFdcxeSFhvFUX0i1LD1TFEWSpETyvcua3yPrB1Hlm/1N1fFNfw1JktVU8r/jR/FIpCW3w33cLiqUSHSdZrkrX9hPSj9cWJc6KPTAWNW0meMSjR3amesOML4ZZzQxdLk1kXzqcbSLg/LUf062Ljk5tmy1C01NH59PSb7XvD3vnxTV9/xn23yXEZ2nTlPkNOAIP13duUef/+69Ups/eNnZbF02n1+Se1uoa2pqRmoeyS8oYDI02O+uFVOkVCKRSEmSlErAyHXVxvYpnp6ZRSMG+/gJ3idvXX7+Ib8pSUpL3ty6I2rmMcXWpJE69VpYFg/nwWmSlEokEuYvlI/sV/u9Mv4hLjdnpoe7OoPXaNo2pZ/YM7CKVax6q5iWFhw9yly+nLF8OaSnS3fvpn6uoZs+5QMANDwE/X4Vq+DttSw9EwTBYDCqo7Mlg8FgMpm06sZJURST+SsH5epAkmQ1lfyvkdWKH8XDYiq1nrRxp7sBAwBAdOcig8FkEgSDyWKx2Ewmg2AwGAwmi6mgYaSjxGJJmEzNvmsWFa4JTR01p9xqSq0GNdm3/Viz8V56O3ZmW244HGmnKWvGnepvnkZuCLN/t27837ZRc//kSHMjR80+elDqnbC8fe7kpo7Td81v8XjN6M0KjA9CgsUQfioQqzAV1A20lFgsNpslvBux9ITxVHfzTg0fMJkMBoOpYDg8aDF8uLRzTpTVZq8v8QTrMBgMJusXSl4ikTAYjN/sVloB3b7BCX3/w/pYxSpW7VWMxYIlS6iePQkXF5a5ORUTA4MGVRxPBVVMLmh1CIIqqmIVvJ1GX/UnEQRBVENfFOKzKt/y76BPPHQrH1kkP4qHIMrvKARBAEFo9g6w8Jrmeoz/Udsjoq3Gg0f7Dj/54/P3Ymk0NrW19z3qsu5xdIDF9M+rmZnfVndf0XVTF/Woydn9QxqU9YIq9wGlGzDsY/Ww88HxqU0UiOdQmDjfxYklULZbG2QcNnmB1z11XiF7bNnKACwVHe7b5AM7bol5919lqlMEQRRfCw+WPdbcXI2ZVhbPjWD1X9/n6faT0SoeGfrEU0Pl07s3ZGSAqythZwc+PrB27Y8auiuuYvJCw3iqLyR87rkUPpRZMXzuuTIFh91c3i39e1JjuvxkVfJQZhXCKlaxGq1iFAWrV8O8edCpE+zfD02bfrvCp09Uaqqkb186VTF87hkh9J8J7++YvkNl/Ahjuhzry6P4d2J8hts7OjmNsh816+Az0b/7igMAkJ+Swzcdeywof75ek/3GUQ0iCJg1Cy5cgBcvwMwMEhK+XSEkhBg5EqeRli86Hk0Qqm04JhMj9xUUqNPxdFeYvc7ndJeYBGcjFgjvhY70ifkzCAAA+NnbPg8BNjtQI2LxaR6Tx+IM7S38Mh3W0rnAJ9hEQXLwlA132Www9dk8ldo4ufSZ79AtY2h5PoJ+ko0NZGSAmxuMHg0+PrBmDSh8HhXWywtWrGBERsK8eXINsV6j4+EEIVRlqMLsZObAPga8E3ZNLBwXnslNXjBycTbvdcwE78BtuZJHKblEUeo/OZnfnQ4rm0cBUB/PbsoZFbYravN0c5aQYTQ0YMbEkd1UMi88Ecr7y6HfpaMDJ07Ahg2wbRtYWcHjx6XL9fWpkSMZW7eCWCzX+Oo1TM8I1WmEqqmZ8PyVd1JQbD0lJHhok04efXJv5UuoEmDo9Bxro61s0N44OzJdUZK4fv5cn3lfTYcl2wQlJRlMAggGQyoozglbGJ1WqNexox6Nbkqi30AQ4OcHSUnw4QOYmUF8vGwxNW0a8eoVHDki3+jqM0zPCNVtimZzNlmdnTRu1dXEv7r22fiR8Uhq10tHAdhNxve6NC/6zqPrzxrZj+tAfSz8+OCpkmkz7rcHBULLdlqzKOcxnv4bb4Cyig737ZX48D2ZvLunMgprU8dSVJHOneHaNejRAxwdwcsLhELo0oWytISQEHlHVn9hz+1S2K20Ythzu1I071ZacGKU09tNx8ueBV/r9rdtxPiHs7wfeszMlH1JXAAAIABJREFUW7jbeJrHn9lB+yz2bbVWqZ54sIpVjBZVjKIgJARmzoS2bcnYWColhenmBteugbm5PKP6jOZV7Ndgz22E0L+xNJtqKwBDGS+IkYysofvyZcjLY1hYAAAYGsLWrfIOq56iy5kjQqhaqQ8+cPLLfwqtAmNbAQAsju8AALGH5BQVooXEbeAbBFlvoXkvWOUBnjPhwHVq61SmmxtoqUBMNETHg40rhK6GP7lQeAoa+cDeYNgaDGezoEFHWLkX3FvK+zvUQXj1jBCSg8LTI5qZD3Ma6+Q4cujwmaffVTQaNz5+XZ3yzoOdN2S+BpKEBxdg5Fj49AbmOIMqg2rAhE98oABG9wK1v6H7WHglBQAQP4ZJq2FEKNxKhqF5MNEdntNuNPU6AK+eEUJywWk5afWeScbMkmszh0T+PX8nf/zOAP0L4yYLfC12LMpspPMu+6N+WwPxqxcN/Rbp8Ak2UW6abXzkuqqQcGYFiPvDjXDgP4fcZ3B0McS9AgUF4vI/kAcAFABA1iNIjYXmfeH4KxgDIKHALRI8OgAALJgBO9fARzEY02X08joDr54RQnIhvBfhP8HNeXAXh2t2Uzoql3uFUmwzef32Ff1YRpNDts9v9yzrgxQAgIWPXFc9IVy5A38MhHaNoXt3GOsMQZOAUId1CeSiPwCkoKgEHA48eQK6tvBeCvffAwAwVMCmeekGOFxMI9UET0ARQnLBMfVcHT3JmFn0z2THw487klISSN77PCEXGByuIoNgsJVUOQyQfH78uiQnbGG08TSPjh317so38rqEAgkJ5ed0YDCBAAAKpBSo2sPNrVC+K7+KNsBbYHBAkV5TU9RJeNqDEJIrBW2DkrvFrfQvzZ80ad6xQvaPDkpM7GFeDRTBsjk8PAcfZbMOk3DzApAAwAATMyhKh0IN0NcHfX1QeQozZsFTek23XLfh1TNCSA7UBsSW9iTntF14MRYAPJzLXrS3AACYG/snAEBwrDkADAaAP6ukh7nk5eG5CzJ7LZrZ35BGj83LCwPsZkPgUHBeAguHwPtTEHgFgAsEQAdvafvtzJHuEOIDio8gdCbctIOtivIOuB7Bq2eEULUrODqgpY3TOBen4YPs55x8U66bb/FFr9F73sgu3WqmhzbL0H511KKBRgqVr1pGmhs2yPlM4c+uLnoQ5jH3Ku8XgpMD7SGQvAcEMWBjBUE5EBUGGsp3tk10dp5k+KJVFJwvGG0FttOgxAn+twk0frVNW5R7bENY4tvvXnyLH61vr9p52zMJAEif7+im9ueaB/95qO+Kdx7eFf/RO3KlP7EmjeDVM0KoBii2nrxh53hjBUFaoP3qRO3G4QsSmVqcxm7Legkf7Pxryj+iFyXdl82gqneCLNHj3b6+cR+4CnyevvPGdY7lJucuODG49ZRs7TZd22pyDIctXdBomYWX1iKbx8WBsRMbMQHERZmLJoYY7/JtzQGqMHXFxBWZUkGBnkfYtBfeM77qZ+4f3OZ8VBbj2fqWY0KzwlU30b23+ZtkyGkMF5+BrC3h1gIQG7RatXsvkTDUTTLs+BgibYXjikyp4LZe5pupJ6YGZjbSsWn1cVegQeSrFw0Dw4c9/Wtkb6WVY9j2G2bB+nmneEweq9+a9d2Sloekvn927rRyaFa4xtbS4tJt+k/smX67Pc72GPI6/KZvosu27vGh3RWA1bCd6unDjz39muYeP6XczoBZmLzEabus3Nb6i6K2pr5/du40e+WVaMMtpZsaF6D31aZG+6co9e7PKDcP29yl7Y7O2CjbkVZbA1BFGSGuIczAjb0oPvHDeyg0UgtCRAjVHdyWXZWv75qfYLp2355t7h+27H8i1bSeHRKxZ73Z2bAbPADqQ/VNkPX6zM5ch7D9+w8dWm32KPXismGBV/NylrRtOjk57+6B60Jt09Groze56WZs9fUKuvjyZcb1a0lb/EZ1bWpsvvDW+3fvWa2MBMnBY0eNsR8dRnmGRc40uhDg4L8z42Xz6Vu+9DO/q+4cvGysocLgsJC+6rWgt3nxdXAaCMuPwLN3kHUYJq4DK0/QLLtKzr+4Ps0uLDbh4CLFPbEPhd92qs/XL/uC919klc17ptzCtawQqC9biE9r3urp/66l3G9h9ibxWtINw6HtZB3PlNqM7ph68G7hwyPJbUf9qVS+l/6rRp83tapnpZsqTAre/kJDX6+hJi/lUOTaLzsSKX4S7eJwpGfw5HYqtaVXG6ZnhFANKr6XUmLaVLEoM3LR7OVHSzRBRAIBBFAUxVBgEfD1BFlF2f9xgqzn260a9xg11tG+n83ItZmfvmnGbOS6bWKOUxub8YEx/M5dLQe2e1Z2fL94rSgv+/K6AS1Mhm552nXJor7qCtxmWmTJ25wbyn8tb5qVJdbTeLp23XKvHayAjdPMmjdjCRmGPcybW3RrqvApPVfEYCupkil/zcsSkJLc2Bkh3AXBg3SZJbVggq8/vOGQP+x3hyZ60HUqNAuGvU7w5RlmiqKAACj9kb7qVM9gMsp/QUZD+6BFtso50X/NP/FG8KUQym+BYzqwUVLEYXU3jyaJkYe5dp0+DzHOaTHcOmdn/N4MyxGmHPiq3MSfN6XzE5uiCJ3efkErl/o52HbRZZbtSBKKaNBnTWib/RuuFNSaToV0bGtBCNU5gtthfm4XFIVFkpbTt/rpH1oQev318wcPDWaOKP778DznbJZA2W6lb/6y14S27bRmE5zHHNZTbuaxYpist3ammHf/Q0ZhDyu1Sq98uBazI/YNVs8/NW5s0ntb6qvxTIpVmtmNsta9wx3Z+oSj9ZGeJk+v/lM0eFaATnjk30UUS7WBcfu2vAvnX53LLBjMK/l4ITafX6w1SHv7sv89L5Hw3r56LcyTfFTOetOTeLp9nOVuwbsSy+AgAa/gziqHITef2vX2AqBEd2d3j0ptM4bh2i3tU6OmeekZ3G13n6e+NnDNeCUJs/RpcTZ9YdNbf9mGDzkZbsOVxSzMXjH+hF20d+Pq/hW+iw2Dg2Bw0A9ebdArwMJr6rij/I/aHttavJib8dWrn7vTZ4p5918mnf907oGihrRh28ZFBzwDU9XsFGdON7afNTHAwrt0CxEdOt1WT13RdVNn9Uiv7P4hX+5ls5sM6XurR8zIf2YqbCi/2Tu35ow+m2o0VHHmdJ1+U3x+uKm1Gi8TAFS7B/aP9ndxURRpO4fO82k2sXRHCrJhaTQ26W/ve8Rl7fVgGk2rURGcsaoUTqdTMVpMp1MOzlhVqSqZTqcKfVPFBJlLRm413RwypimnKj/l+XarHrGNrA0Kb13ljf370JDzUw/bRvur38l+L3h/ZfOSRB3923suif/sbEToDgsYKdjgGZy38v453UkdVnOEKcd4XFWmgAccrdbNeelZwkZ/qry4LerYRznjkuL0BKcjTjvaBTQ9ujZXR0+BT3ae6/Js/sq7ajrMvCLVXh6dRdqBC965DT8KKsYjHPSf5ikUPynq6jdB5cDyrIkx5ivnaO7eZbBy7I4nVLuVcXbH7ReZRPjdmll6A3vLxIfzz9hFjXsTNCPqDU1uVGMVqxTOWIUQqoMoCcURvedX/dUB1/yvsF37TtxMnnBxwcmPFEC5llJ93aFrg8f0nLR2YVcVFTZLv+tAq3GbnPS1hx57cWJCz96zfLtZLU79UFjwLMpKuaHvzXs3MpY24TA5qnpO8QtsvUZosFhKGmp/rknaN7oJ+9FTrZYNtVuNX7kpLG6XG3E3dYOjU5Jha6fNm9tcftfLy6Wj4EHysdTrV7KeXQz6a/+TK0vWHD36oq+vd9PLpzP+OfrsSdqpdeXu6YoAAFiGgwJmuJkLs0/G3aXpjWpUg+hycYYQqleUOi0+FF0dGy6+ttLTeS+j+N1HI/cw9Vcnvm6A/ZA7RkvhIVNZh/s2+cCOTDHv4SdZm7no7bOcg5rRl5a3VyGA1GjTQnvfTNcx/DukwQC7todWTh0+UvtVEdUBGCxVVY6ytrLg4/VLxX8YS7NPb4tO4lh3EKu0DVyhtWaZWL+7fcNpnqvMglpqU/sjdyl0b93IdPb+lQm2HptvOq6xPrY7JfboVaAad7ueclMtjxpxJ/ToIy2Dkks70ycn3jt1r/XipQaqqh+IouQlnjTv8o2qGf7oCKG6w9jryjOv8gti28G345n0sQaA2ISv7x8dib4H2o1j/MbtBI6J+8opc/scWn5HomlgoKDfxmmgSVSeprpK657DepgLxc1V2/SZ1/fmc1frS1tvcrjSPl7eq61jfe8MdbRvkuiyP8ehazfzGzlXRK0MqPxeoXEbTJ5EzQ66U/DgdpMWOTvuBW6y9luo2Imr4+iqPnmiQ+bLqw2nn2924pDG8BWLnj4ZFRUXZ5AvIs/kaDgFzBC+v7I56MITIabnegl/dIQQAs+kAs+vFqw52//LP8cGl/05vAsAQJ+IeAAYb122uHN8dwBotOPMEADofggAQJhjPGhRxhvJnybuG6KsG+dOVm3BOUFw+x540+fYWKenTdz9Oz1/o2nQ96/JJiKh9eAODVr1/6tfTv4Ei5OXBsxV2+MahQOM1281du+ZKrkX425pqEQo6ndyCc/m/euWk+Tt+SD71lpsglA26uK5I6OQrKnQEEKo6nFa+2+yTfIaNnLseE+fba+b6CvqDJqsGzLczsEz/DWTyTTobXMvJNNmUOPv9L7CAcZRjV09FycH9ptybXRC5hHTJ5vHjOjn2+JuRC/1L89IkG+PTB69tnDOyadeLYsvBI0YMzCg+d2I3uq15flxhBD6BqHSdmL4yYlfLSt/UV5g8qfVhCHGLGC1CoydQ5I8Xs+IeFWAcVZQVQOMo1qshq6eeekRCUUDVs4bZKL/h+3s1SOkR3bc+GpA2uKMXf9TdAqeamWopmU6fGFQ98LzJx9h30WEUB0lvL9j+hbupBF4Wxn9QM3sGdK8u9mFho6mXAIAQNnEujF/S857SW9u2cerWG1NT1ExVgYAIPNvXXzIaD5e/78MWY8QQrUIx2Ri5GF5B4HorGbSMykoKCFUNJVlA8UxVTSVgZ9XUv7mMpNr2IwLANJP16NmjPM5bLL6ioO+7NI+KSlp/PjxstXMzMz8/PyKi4urPESRSCSVSukzhgNJkgBAn3goihKJRNVR8r+GoiiSJJlMZuWr1hSxWEyf8gEA2f5MEHS5QYRVrGJYxSpVJ6uYRPLDKbSrLz1LX0T1buWRWAwM7ZEnkmyVKH4eXwrAAJDy8/igpKb4TbWgirJ3z3TzP0AMW3T+3pTuup9D09PTGzVqlOxvDQ0NNputpKRU5eFSFKWgoECfUbqkUikA0KdukCRJkmR1lPyvkcVDn98LACQSCX3KBwAkEgmDwaBV+sEqVgGsYpWqk1WMyWT+KENXX9EzjdwvFbmX/sNLilN7lfaYD3+oAwgep7xQatlW56vPFtxeP8QmRGvR2YfTzDW++rYmJiYrV66U/S0b1LM6ahSDwWAymfSpqwBAURR94iEIQlZE8g6klOyMlT7xAABBELSKR3bpQ5/0jFWsYljFKlUnq1gFF981VHVVzDwdVE4u2pr2SZifEbE4gRjmZcEF6fvUhL3H7xRRQOVdWLD84bBNy4Zofnr6+PHjx4+fviz4z/NxI4QQQnVDTZ1Zc7utPbvJ9KC9Eddg4E79VWdDe6kTIHwQ6T1uzql3EhDlXkn/9Cp6eJvmnzXtHSIbhhYhhBCqd2rsvgKh1NI95rp7TPllyt3C35X2D2u//DG1vKZiQQghhOiNLvelEEIIIVQG0zNCCCFEO5ieEUII1Quix7snDxkyymnUULuJEffys9d5BN8s+c56/NSZozedDnZafVuePaBo9EwbQgghVG2kr8/szHWIOTreiHp+Ku4xDyg+wWbws7fNWJUiIESsrnMWNtvtseK+npE4532/3gAAVEFy8JQNd9lsMPXZ4qe6N7B0zXmbJrf9zlQmVQqvnhFCCNUHzEau26bmb5k1Y3rg5gd6TVUZAACFScHbX2jo6zXU5KUc37Plrc+hw7tCvFqwKQAA6sPZTTmjwnZFbZ5uzvqQWLZmauLz6n/yF6+eEUII1QfC27v28kcGrTNmie6t7e93bpUVAABF6PT2CwowenLo0NN3CfcIAoAiGJ8HC5GSDA4BBIMhFUjIsjX/5umzAX44HGfVwPSMEEKoPlBo2kNvtXv/KBUNlhA6T3NUuZMAoNo9sH+0v4uLokjbOXT2ZF3X4XbRmvCR2Q8AgNCyndZsgvOYw3rKzTzW+Qb231W65pahBFT3LNwERdWmib5lg3paWlpW+ZZ5PB6Hw6HPALNSqZSiKPrEQ5Ikj8dTVVWVdyClSJKUSqVsdnXf/fkPCgoK1NXV5R3FF2KxmFaDemIVqxhWsUrVySoWFxcnEAjc3Nz+/RJdqi5CCCGEymB6RgghhGgH0zNCCCFEO5ieEUIIIdrB9IwQQgjRDqZnhBBCiHYwPSOEEEK0g+kZIYQQoh1MzwghhOhJdGfloKmXeeWWCLNXVDCRlOCHk1AJHu4LGDnccczIIbZD/eOeyDYgyj22ISzxbTUPzvmr6DJiDkIIIfRdskmlCiU8Zeu5XtSXJQJCxOo607tw3uK7RjrC14Udl84FPsEmCpOXeG1+pkR+YtuHbhljzALxgzDfg39ujd/QhA2iZ8d3334n0nq5duKKTKmgQM/IVvPJ1Dk3NVs6r5mrFe791RvlCa+eEUII0VmRbFIpXd0GvNTLb0j4apqp1KTXEqKR+/qI7b4qKdk8CgCAZTQ0YMbEkd1UMi88EQIA8O9eEvTsZcQW3o8K8JoflXDo5rP/rU+zC4tNOLhIcU/cMzE0mhK2xq4h59s3yhOmZ4QQQjQjehA1O/yukBKVSJkMQjap1OK5kx1sO2szAD5PM7VyqZ+DbRcdBTV9DTYAg1ma0EpywhZGpxXqdeyoVzpkuGIzc+LS5dcSjon7hvBF1vwnH8QUBQQAEEAABSx1Q032994oT9i4jRBCiGbYeq1U/rfAI4mQdPUJ0DEL7B/t75LC5OmP3zyBgK+nmdroSXzzZqayDvftlfjwTDHv/oeMwh5WapzW/ptsA7yGHdbQaaCmpdVEX0e9Z4DFlKnjjvI/antsa/z0Vub33/jtpmsSzlhVCqfTqRhOp1OpOjmdThXCKlYxrGKVqpNVDGesQgghhGoTTM8IIYQQ7WB6RgghhGgH0zNCCCFEO3TpFvGTKIqSdVio8i3LNksQ8uynVx5FURRFVcc3/TUkSVZTyf8aWZdG+sQDALT6vWRIkqRP30+sYhXDKlYpWv1eMr9fxSp4ey1LzzLVd8Shz7FMhj7xyCLBeCogO9zLO4pv0S0kjOdH6LZL0y0eqH9VrJalZ4IgGAxGdTwLwWAwmEwmfZ6ykJ0k0icekiSrqeR/jew6gz7xAACtygcAxGIxg8Ggz4NVWMUqhlWsUrQqH6iiKlZBexJdqi5CCCGEymB6RgghhGgH0zNCCCFEO5ieEUIIIdrB9IwQQgjRDqZnhBBCiHYwPSOEEEK0g+kZIYQQoh1MzwghhBDtYHpGCCFUF/D5fB8fH0dHx1GjRs2aNUskEpV/NT4+/ty5c+WXiESiDRs2vH379t+bIknSzs7u6dOnRUVFRkZGt2/fLikpsba2XrJkyc2bN8uvuWLFitu3b/v7++fm5v58qLJ3VbwOjQZIQwghhH7ZunXrunTp4uzsDAChoaExMTFqamqnTp3i8XjLly8/efIkm81OTU3Nzs52dnbW1dVdsWKFQCDQ1dWNjY3dvXt3jx49wsPDExMTu3fv3r179yFDhly7ds3AwKBv376nT5+2s7MzMjJSUVFhs9nZ2dmrVq2iKKpbt25lY24XFRW5uroGBgaWlJTItuzh4XH+/HmhUMjn83v16tWxY8ey5bK37N+//8aNGxRFPXnypGnTpt98HUzPCCGE6oLk5OSJEyfK/u7fv//SpUubNGnSokWLAQMGNGzYcNCgQQ0aNLhx48aUKVNsbGwcHR3DwsJUVVXHjh3bqlWra9eutWjRIjEx8caNG97e3gDQq1evVatW6enp+fr6Llu2TEtLa+jQoS9evACA4OBgbW1tDoeTmprarFkzABCLxS4uLj4+Pu3atSu/ZU1NzRkzZpiamjo4OJw8eXLHjh2y5R07dgSArKwsLperpaWlpaX176+DjdsIIYTqAjMzsytXrsj+vnTpkqWlpb29va2tbXR09IkTJ2TLWSyWpqYmfJ5pSjYjxcCBAyMiItzc3BITE7lcrqqqKgA0atQoNzc3KyurTZs2urq6u3bt6tq1q2wjBEH4+fktWrTI1taWzWbLlqxZs2b//v0FBQXlt0wQBJPJlP1dfrmMvb29np7eq1evysIrD6+eEUII1QVz5swJDAyMj4+nKMrQ0HDFihWRkZE3btyQSqXNmjUrKirat2/fH3/8IVs5ICBg6tSpfD7fw8OjU6dOqampmzZtioyM7N+/vyyDKioqNm/eXE1NjcPh2NvbBwYG6uvry94bGBjo7++voKDg4uIiW5nFYpmYmPj6+q5du7b8ls+cOTNz5kyRSDR06NBOnTqVLX/w4AEApKWlPXv2jCAI2SX4NwgaTp9Zgfv37+fn51taWlb5lnk8HofDoc9sZVKplKIo+sRDkiSPx5OdVNKBbLY72XkrTRQUFKirq8s7ii/EYjGTyaTPhJJYxSqGVaxStbGKTZs2bf78+Q0bNvzRCnFxcQKBwM3N7d8v0aXqIoQQQqgMXc4cEUIIoTpm8+bNv/xevHpGCCGEaAfTM0IIIUQ7mJ4RQggh2sH0jBBCCNEOpmeEEEKIdjA9I4QQQrSD6RkhhBCiHUzPCCGEEO1gekYIIYRop/aNGvb8+XMmk1nlmxUKhWw2mz4DFJMkCQD0iYeiKKFQqKioKO9ASlEURZJkdewJv6ykpERJSUneUXwhlUoZDEb56XHkC6tYxbCKVapOVrH8/Pwf/ei1Lz1nZWVlZWVV+WaPHDmir69fHZNt1A0ZGRkPHjwYNWqUvAOhqby8vOPHj9va2urq6so7Fpo6cuSIgYGBhYWFvAOhqYyMjIcPHzo4OMg7EJqqw1XMzMzsu8tr2YxV1adVq1Z9+/YNDQ2VdyA0tXDhwvDw8Ddv3sg7EJq6detW+/btL126ZG1tLe9YaKply5b9+/cPCQmRdyA0tWDBgoiIiNevX8s7EJrKzMzs0KFDYmJijx495B1LDaFLww5CCCGEymB6RgghhGgHG7dLXb16VVNT09TUVN6B0NSjR49evnyJLbc/UlxcnJKSYm5urqGhIe9YaCo5OVlLSwur2I9gFatYPaximJ4RQggh2sHGbYQQQoh26m16pkruxbhbGioRivqdXMKzef9qQxA+jvezacwlCGYDU7vFZ99I5BGl/FRaPpK354PsW2uxCULZqIvnjoxCUh5hylOlRSQjzFrY3nL9I3HNBidXlZbMTxZdXYV7TqXw+AMAAFT9VHTZ21ix7Yzj9149OD23k3JD9//lk+VfFz/e0k3F2D3uzsfC11fX9VbTsP/7vVRewcpBZeUjfZNg30Ct1+rLLwo+3D3k11qhofuFr9eo8yorIooSv7t+LHLxqOYAbdc9FMknSnmotGQqL7o6DfecSuHxh6Ioiqqn6bk4cbyuhv3xTyRFUVThBRcdLacLReVeJ9/F9lA2WZojpCiKovKP2nIbB94okUek8lFZ+VAFp4eq6Xsl82T/fTzYW7nRjPpUQD9RRBRVdH2Nl6vraCt1ol4dZCstmZ8ouroM95xK4fFHpn42bkvz7mYXGlqZcgkAAGUT68b82znvyzVfE9qjzn/KmttKAUjRp+xjcdnK5t0bKcgr3BpXafmAitXW9JSV5soAAGT+rYsPGc3b69efAvqZIgLgdgoM2xmz1fdPGg1DWP0qLZmfKbo6DPecSuHxp1TtG9SzKpCCghJCRVNZNposU0VTGfh5JeVvXhBMBQ4ThLcWtGu/7D5wbbek9tOqP6cylZcPk2vYjAsA0k/Xo2aM8zlssvqKg379KaCfKaL6qtKSqedFV8+//s/A40+puveNfkT6IspGlSAIgqnjcEGirkTx8/hS2Sv8PD4oqSn+uyw47YLuSfmvkhYI5vT2/l9Bne7A8p/LhyrK3jXF8o8B28H7/L1Tvq3r/on+r+xC9Q9DsZKSqXSFuq2ef/2f8VNFVB+OP/Vnr2AauV8qoiiKkr5PGGDcsq3aq7THfAAAEDxOeaHUsq1OuZYE4d3NLqOC00sAgKGk383F1bTgenrdbn/7T+UDILi9fojNgrduZx+mRft0160XrTD/sYjqKWaDSkqm0hXqtnr+9X/GTxRRPTn+yPPGtxwVXfY25nZZnvpRkJe+sbe6/oQL+SQleZdyYM+x24UkRX487qil3ntN0otC/qd7hwPaKDX1T+HJO+gaVFn5fDo+QtNgwt85jz578iK/nnVhqaSIPiM/xHVXrl8dfCotme+uUH/gnlMpPP5QFFVve25TFMm/E+nWSV+JpdTQzDksq5ikKIp3ZaLO566Skvf/LB/eWpMJAKpNbKbtusOrTweQyspHkDGn6TfneSZLbwvlHXTNqmwXKl2rHh5kKy2Z761Qj+CeUyk8/lAUReGgngghhBDt1J97zwghhFCtgekZIYQQoh1MzwghhBDtYHpGCCGEaAfTM0IIIUQ7mJ4RQggh2sH0jFA9wU+Z0pD4irJ+24EzD9z7ajZdsjBr3xwHy0aqDIJgqBv9aesbdf3jdwbM46dMbdxoSgq/xsJHqJ6pq4OhIYS+h9Heb4N3a0UAIEve3T4bGbpmtOWjhPvxI/WYACB5c3Sq1bDwx3pWTh5LLJoqfMg6FR3qYXH69uVra6zUibKtULyc6PkxuSJXuX0PhOo+eY+LghCqGbyrk/WAO+p84ZdF0jfxQ7kAnSNeSCiKkryKteMCp+uSpI/SsjU+/c+nMUDTWTdl0+mS+YlzBnakRpJ+AAACFklEQVQwkk3epzf5an0a6hahGoWN2wjVXwztrkNaArzMeSMGED2MCTpW3C4oZk53zbIDA6OB9cylg40FVy8+EwEAECyttr0dJi9c5GWhKL+4EaoHsHEboXpM+DLrNYCanioTpG+T/r4NbdeNaMr+ahWmkevx3C+t2Cqtxwa2Bii5/j5ie25Nh4tQPYLpGaH6RMr/8Ob162IAIEve3zmz3jv0JdHJ374JG0Rvsl+BknkbXXalG0EIVT9MzwjVJyUnxpgYlF/QbGzk3qmmCgB8iUgKDBZTXpEhhL6C6Rmh+oTVZem+eWZKAAAES82odYc2jdRkRwG2dnNt4D19lC/tq/pVjibzUiNCz5B9p03qpomdVRCqKZieEapPFI27DRjSR/U7r7ANrfsYQkjMiRcekxuXOzBQ+YlBfosu9O3oO7nGokQI4bAkCCEZpfbe080hJXDChrR88vNCindjw5wTAu5Azy7q8gwOoXoHr54RQjIKJlP3hf3TxWtmZ9MjTk79zJsp59+9sGvbmWdqg3asHaRNVL4FhFCVwfSMEPqM02LSwdutw5cs25awbXGsiKFm2LLTxC37lk3qpouHCoRqFkFRVOVrIYQQQqgG4b1nhBBCiHYwPSOEEEK0g+kZIYQQoh1MzwghhBDtYHpGCCGEaAfTM0IIIUQ7mJ4RQggh2sH0jBBCCNEOpmeEEEKIdjA9I4QQQrTzf1RhtuaYecdrAAAAAElFTkSuQmCC)
В догонку к графику, обычно принято показывать, какой вклад вносят компоненты в объяснение изменчивости:
summary(prcomp(miasta.for.pca))
Importance of components:
PC1 PC2 PC3 PC4 PC5
Standard deviation 0.2278 0.2057 0.08500 0.01083 0.001372
Proportion of Variance 0.5111 0.4166 0.07116 0.00115 0.000020
Cumulative Proportion 0.5111 0.9277 0.99882 0.99998 0.999990
PC6 PC7
Standard deviation 0.0007626 3.908e-17
Proportion of Variance 0.0000100 0.000e+00
Cumulative Proportion 1.0000000 1.000e+00
Как видно из summary, уже первые две компоненты объясняют 92 процента всей изменчивости исходных данных.
Что нам говорит график биплот? Видимо, в наших данных нет четких кластеров, т. е. есть ядро и несколько переферий: с одной стороны видны Tarnowskie Góry и т. п., которые имеют максимальную долю в именительном падеже, с другой стороны Ostrów Wielkopolski, который имеет максимальную долю в родительном падеже, с третьей стороны Bydgoszcz, имеющий максимум в местном падеже. Переферия городов, имеющих много форм именительного и родительного падежа, но совсем мало местного падежа, кажется чуть больше.
Создадим переменную, отличающую города по степени переферичности.
miasta$core <- NA
miasta$core[-c(8, 42, 33, 94, 4, 13,22, 2, 46, 97, 31, 38, 39, 99, 77, 29, 56, 7, 73, 27, 64, 51, 63, 16, 20, 45, 112, 90, 3, 18, 114, 88, 72)] <- "core"
miasta$core[c(8, 42, 33, 94, 4, 13,22,2, 46, 97,31, 39, 38, 99, 77, 29, 56, 7, 73, 27, 64, 51, 63, 16, 20, 45, 112, 90, 3, 18, 114, 88, 72)] <- "periphery"
autoplot(prcomp(miasta.for.pca), data = miasta, colour = 'core', shape = FALSE, label.size = 3)+
theme_bw()
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAooAAAGRCAIAAABt7wUeAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAgAElEQVR4nOzdd0AUx/4A8O/Mlmt0pIkIIiBi7yW22EtiTbEkeXnp/Zf2nublpfpeejMxiWmmvRQTNWrUJGo0sRfsnY4iRWnHcXfc7ezM749DpagBwQP1+/kLhr2dmeV2vzuzszNECAEIIYQQak5oUxcAIYQQQjVheEYIIYSaHQzPCCGEULOD4RkhhBBqdjA8I4QQQs0OhmeEEEKo2cHwjBBCCDU7clMXoH5SUlLWrVsXFBTUwP1wzoUQkiQ1SqnqyPOKOSHEm5nquk4IodSr92FNUlPGmCRJXs6Uc04I8XKmmqYpiuLNHAGAc+7lbxE0RU2FEEIIrOkF5ObmGo3Ge++991KUClV1mYVnAOjWrVvv3r0buBNN0xhjJpOpUYpUR4wxAJBlrx5zp9MpSZKqqt7MlDFGCPHy3Y/NZrNYLF6+sGqaJkmSlzO1Wq3+/v7ezFEIwRiTZdnLNyLerynnXNf1q6emF3FPsHTp0vz8/EtRJFQDdm4jhBBCzQ6GZ4QQQqjZwfCMEEIINTsYnhFCCKFmB8MzQggh1OxgeEYIIYSaHQzPCCGEULOD4RkhhBBqdjA8I4QQQs0OhmeEEEKo2cHwjNBlS2h/ZB2K37jFvGFbx0O5u/SmLg9CqPFgeEbocuW0Hb89T361Zx9b/86Ps5zbTzjdTV0khFBjwfCM0OWKUMkMQhPAhdCAWKh3l3FACF1Kl9+KVQghD6NPq89D9/TdtkUF0HyjD7Q0enuZSYTQJYOtZ4QuV6cK06aWBP9+Tf+KQT0X+RRMTi+zNXWREEKNBcMzQpcpnlZsMwWHXqMQQg0jw/0cpdYc3tSFQgg1EgzPCF2mSIy/ubjoVDIDEO4/C8q4j29LPKERulLgs2eELlMkIjTuc0faHdu3FQraMqDlDwkB/k1dJoRQY8HwjNBli6hj2iSNadPUxUAIXQLYF4YQQgg1OxieEUIIoWbHa+FZOI9+cUfvSBMxRvS45eMDdlFzA1awZvbEpGCFEHOrvnd9sqcMx6AihBC6WnkrPJdvfnLE/TsGfbw398AXo488NuKRP6zVAjQvWHrfTW+U/X1ZlrVw93t9tzw05rEaWyCEEEJXDS+FZ/vuTxfaRr/y9NiEiLhRs16brC/9ZKe96gble75aa5z23wevifQLbjfp2dkDytasTHd5p3AIIYRQM+Odkdt6yZEDZZE3t/MhAADmhEHRjvcPnmJDfc5kb7nmg91bLVFmAABeum9dGm17e4QKAABOpzMvL8+zWWFhoSzjaHOEEEJXOO+EOl5hdRJLkFkCAADJEmQGR4mz6sNlyScy1gcA9OLk+U/c+vCShNc23RDhadqvX79+9OjRns0GDx784osvlpWVNbRAnHPONU1r4H7qmykAUOrV4XiMMUJIRUWFNzPlnBNCiHcXaHC73Z58vZlpU9W04adAfXHOvfzVhaaoqRBCCIE1vQAvXzavZt4Jz9TobxKOEocOQAF0R4kDTH7GGt8LYTvw9T//9uiPZMJza47ePyD0dNF69uy5evVqz892u91oNPr5+TWwQJqmMcZMJlMD91MvjDEA8HLr3+l0SpKkqqo3M/XcE0iS5M1MbTabxWLx8oVV0zRJkrycqdVqbfgpUC9CCMaYLMtevhHxfk0557quXz01VZR6r6JyER9BF8c7oUIKTOzol7s9wwFx/gAVGVtzTIkdQ6rlXXHoresGvxv83Kq0h3oGVLvYBQcHDx8+3PNzSkpKaWmpV8qMEEIINRkv3fVbut11g2Xlcx9sL3aV7vn0+YVkwr29fEA/tW3hN8sP2wSIkt+feSltwpz/XBdUnJWRkZGRkXXCil0oCCGErlLe6pTz6f/GqjntFk1s5dNyzJcRr65671p/Aq7Uzx649alfTjJwH9u0uzj380kd2p7WZui7aW4vFQ4hhBBqXrz2HJSYEu/4IvmOL6qmmft/fLJyfFiXlzLES94qC0IIIdS84aSeCDUHIvXEgdBdJ/MEgHD9mLo/ZvO2gA3bOhzM3ak3ddEQQk0BwzNCTc9uy5mWYS0CAIDSksyHrQGL+/Qp7t/pQe343XkVrIlLhxBqAhieEWpinJXOSrGObRMYAgAAkjFsXkJ4FwmYAAOlFurVN3wQQs0EzsCFUJMS7kUpmccik15QMz8BAABfc+BEEKk5+3umlTn8YvaEG/AsRegqhK1nhJqQSM9LnU2jPwkzKNUaySS+VSfroJ4LzHnj0srs5/s0QujKhfflCDUhfV9heWpZamIhCM5KeXHHZNt7YXyHJeaNYEWihmEhZlu2s1T4WbCHG6GrDIZnhJqQPKlzHycAANhKjiRkBu3qFiIKDj2eXfC3gFZdiWt5vj0kIDoYYzNCVx8Mzwg1K6RlaNs3y45et/WEA2hscNQP0RZjU5cJIeR9GJ4RahZ8AxPzAgEAgBhnJHSZkdDE5UEINS0cGoYQQgg1OxieEUIIoWYHwzNCCCHU7GB4RgghhJodDM8IIYRQs4PhGSGEEGp2MDwjhBBCzQ6GZ4QQQqjZwfCMEEIINTsYnhFCCKFmB8MzQggh1OxgeEaoPoTrx9T9MZu3BWzY1uFg7i797B9STxwI3XUyTzRh4RBCVw4MzwjVQ2lJ5sPWgMV9+hT37/Sgdvy+AhcDAAC7LWdahrWoiUuHELpyYHhGqB4kY9i8hPAuEjABBkotlAAAZ6WzUqxj2wSGNHXxEEJXDFxQEqF68DUHTgSRmrO/Z1qZwy8mOVSVhXtRSuaxyKQX1MxPmrp4CKErBoZnhOqLxLfqZG3pWpyyf3ym8WffvNk0ek2YQSlt6nIhhK4g2LmNUN3xgzmpjxVpOgBQw7AQc7ndua3QnlqYmrhpW+v9RfllaR2TM7bof7kfhBD6C5dZ61kIwTlnjDVwP7qu67re8P3UixACALycqa7r3s9UnObNTD1fDEov6R2n8CWu77LybvFp2YW4l+bZW/hHTovp8XcAALCVpiZlB27v3CJCXNrj3SinwEXwfJe8yfs1PXOSEkK8mW9T/U8vIlPO+aUoCartMgvPHg0/c8hpjVKeOvKc+V7OtElqeiZrL2d36WtKIkPbvF6eOiE5zwG0TVDkd63MxtM19eTshYPdJP9QIYT3M23CmjbJt9ebOV705ahJLiZXp8ssPBNCKKWSJDVwP5zzRtlPvXjOBy9nSin1fk09jQ8vZ+rJ8RK3ngEky63tut7arvI3TdM8RxgAAoLb5wVf2sw9vH9sPb1WlFLvBy0v15Rzruu6JElXT03r+0EMz16Dz54RQgihZgfDM0IIIdTsYHhGCDUWnNkUoUaD4Rkh1DhwZlOEGhGGZ4RQI8CZTRFqXBieEUINVjmzafyjZorjehFqFJfZi1UIoeZHpOel4symCDUuDM8IoQbS9xWWp5alJhaC4KyUF3dMLl/ePbafV9/jRehKg+EZIdRA8qTOfZwAAGArOZKQGbSrW2gE9nEj1DD47BkhhBBqdrD1jBBqNL6BiXmBTV0IhK4I2HpGCCGEmh0MzwghhFCzg+EZIYQQanYwPCOEEELNDoZnhBBCqNnB8IwQQgg1O/hiFULoDCbWvOpeXXA2wdJL7nOMrS0AAHdlSm9l1i1UbZLiIXQVwfCMEDpDJsOfNgz3/OwWqz9gyjBpSEs6UjDGZJnDmg+ZMhRjM0JegJ3bCKFzObGKZXWVB7askrK6ZgpC6JLB8IwQqoUX6SsOk9H9yZllLXixvrJ6CkLoUsLObYSuJtzO137NNqYKppL2o5QbBhMDwLF12qJ1vMhF4kYpU4cSI4GsVTodrERW6cXOXsPpoGopCKFLCVvPCF1NclaybWb50VcNzz0muVZpm0+Cfb/29TYy8SnD8zNl+Q9tYz6Icr4hlfTtQM5cHkQ5bEojfaqkIIQuMTzbELqaKEagHDgHXQchEVWCzE0ieJgUYwY5mN48U+nXAuwp+vEQKdZ89lP2FHEihFZNQQhdYti5jdDVJHyk3PkV7dUnAQAix6t9AsUfxUCy9U/W8EI3RA+QJw4lOTuFb3tirLJic84u8GlXLQUhdIlheEbo6iHE4e9Yajfl2euowcqXzNVWtFZUTeSX04f+IQc4+bK32bJIderdamL1zyXeReIY9mwj5E1eO+GE8+gXd/SONBFjRI9bPj5gF+fezLX/2S6930rXvFUshK4mmjiSBUm9qIWCHEh7toX0DOHnQ9r2o8EKSH60WzzkZQve1MVECHkvPJdvfnLE/TsGfbw398AXo488NuKRP6w1AjQ7tXP5/BdunTR7n9NLZULoaiOT2DA4tJM7BfAyvisVItvQuM6Qs5WXMOA2vjsVomKxlYxQc+Clzm377k8X2kbPf3psQiBJmPXa5E9u+mTnnGuH+lTZpOLYuuV/ZpBwf2L1TpkQuupQ0nmGXPANe+MpwWXSdqg8OQFMbZQRC7UPnxEaJbFD5SnxgI+YEWoGvBOe9ZIjB8oib27nQwAAzAmDoh3vHzzFhvpUyd6nx5PzvhRFPwxaPrv6h1NSUubPn+/5OSAgYMiQIbquN7BAnHPOecP3U99MAcD7mRJCmqSmXiaE0HVdiPM8Nrk0PDX1cqaeml7spy0w/B5p+OldAde5BF1vlrrefDZFs4t13/DNaYKpkDhCnjxIqMA51+1HxcebyX1/I4ZGqEVdNKymF+PMlYEQr96kNGFN6/tBL3/br2beCc+8wuokliCzZ74hyRJkBkeJs46X8IKCgh9//NHzc7du3QYMGOByuRpYIF3XOecN30+9eC7llHq165Ax5qmsNzNtqpq63W4vX1V1XaeUej/TS/vVzVkhbTfwe58T5hLywzxtY1u9n1Fs+U3s2UvKErjb5bXL8yWvaS1CCM75Ffg/rcVT04sIz16+jbiaeSc8U6O/SThKHDoABdAdJQ4w+RnrePEeOHBgenq65+eUlJTS0lKzuaHvX2qaxhgzmUwN3E+9MMYAQJa9Olre6XRKkqSqXp3siTFGCJEkr07/qOu6yWTy8j2BpmmSJHk/04afAhfi6+OWXAaDkRpUncrc4mOwmFirjtTPqP9WZjCZae3Wc0Uq+3AjfeDv1AAgnHzDd2x9KugUogfKN46klos8Ppe8prV4IpYsy14Oz01VU0VR6vtBL1/BrmbeOdBSYGJHv9ztGQ6I8weoyNiaY0rsGIL/ZISao5rvRgcDEdA2FlavBkeeNvup07OB6mLvIrZiF3dyIjOhdagMwrmr2HouP/Qf6ufgS95kS1ur05LweTZC9eWlu35Lt7tusKx87oPtxa7SPZ8+v5BMuLeXD+inti38ZvlhGz7KQKjZOP1u9MyHpLAOctgWbUUGAIP1H+gb8wSRaM/rqWuVtvkY//Ut93dbhEsioTEgUaCs8uOldtJtGA2QgPrSTtFwMh/f1ELoInirU86n/xur5rRbNLGVT8sxX0a8uuq9a/0JuFI/e+DWp345ybxUCITQX9LE4QywnNLnf6QXS6R7W0hPFYWbxaYKMEdRYxSkLuNllDi3sC3FJPpW5dmn5MhT4GMkzPNGJCEdpivj2gAAODLYqhTo0A4XuULoInitg5mYEu/4IvmOL6qmmft/fLL6fTUJvmmD/SZvlQkhVItMYkMhDeg1fcTvxWJPKkR2h6xfIGIMDflZ31YOTgBjX7kV0zMNIiyIEBBuJvLtRDjZij3K+K4E8tjbL+uFnr0R0tWrIzwajdBWZ6c+klteBFJCSMz/2gbHUCgtO3HH0dx1FXpwQNR37SN74fM5dCnhBAQIoaoo6XKb3NWtr90hnKm6c6B8fVsotgspmWdFU0snZUYikQ6wjD5ynAIgxK752gEnaR8CNJgULWY7isGdw60KaT1M+ccbhlfnqNcENXWNLsbJwrS/nbJ82rt3Qd+k25wZt+S53FrRXQdPxsV3O3VN1xdp7t9zHF4daY2uPnj7h1BTqDrUuXaKXsyXf8X2FQg3kHYjlRuHEIO3xlYJJ9+4kO04BpwSGiBdP4SquWzrSXCcFAACqMiMB3MIpGeIASY4+Iu2K5NETJCjN7AUH9rdl+3I4HSdgGjlzgnU6KUiXwI8s9ThF9y6pwwETFMiTLNyyrIMJzcYI9/zl2UiT03sOoRLuPY1uqQwPCPkXdzGNyzXdyTz0vb0fClpi1lmojLz/wgU6J+/o23vpPbTzvQYG4G6Jz6r9guEY+u0Ret4kYvEjVKmDm2cFaXOjLsmm7TXl+lfv6bTdiBMJNRXFJ8ExsXmowAArbrBoVNQaCCD4sShfL7LDrK/2HkMHO3EkZOgubXnHqncYeSN6kMDL7eJQkmUn7H4WOHWKPMA4vg2t7yEBabZXEDKn957Yp1TD/aPeDu+ZcumLiW6smF4Rsi7iEwikqSBkvi17DwpAgL7y5NbExXACaAoRJVALxRaovL8A9TEbMtfVpc871pyeoeWLpT+oW1MUgeU12yR18CqPhWmZOKzar8ggKoN9yrjrm0GoFTk5kJES2JqCeV2oBZi1kWFGyJHyteks62j5RsL9FWHwJGlc0oCFAgLA6eJjhgvharSoF5EKeKL3mPQwruvEDcK0jI0/jN76n07dpTJlgmBJn+NgOAn7dqw7l0+NbJfU/ffnGo+mBQY2NQFRVcwDM8IeRcxkYQuxOYiq/adJ4VAaBIFXWx81/1zOkRNUHsEgu2AUEKJDAAyH/iI4To/ODDPvbGL3Ha7royR+1F9/e/a3F1n29/npFtPx/jTKTUb7oR0mK50AACA0qPC5YK4WFJeCk67oKfAzQVYSL/blevixNIXRdZeLev0fqJuUh7oD5te5/ZwEhojj1RAIgChtF97WJwtePvLbvA256RnVPtDsZSASM/Zu0QzxRiUsICw8SZKQR0c5i+nlOfxwMDLrFcAXU4wPCPUPElkwP8Z+pXwRe9oy9qoPXLBnqHN+bdwyGpMH37DcJJfDNomtqkU1I/dJ/pInTpIA5WzLfJzcpw6HeNPq92UBwDhFDsWsqW7Rbupav+D2m8q6dOLtM4UP6YDLxTbvtHsw+UJLxomUQCAYwvd3zL5b/2I/QjbbKdTIkXy+9rebsptg4jBzvemQ+tel11sBgCX/Xj/Q/z97m1HQOlrOdqodn5tDcHhxwtWVPjdbNA3FFiFb1wrjM3oUsLwjFBzo4kNP+gtxsvtfUEKpJ3DxZoC0S+C9on29BiXfz+HLW2l+LtEro3OeEZpr/Nlb7ODN6njYs62yM+p7GyMJ/GD5QmDqblWU14v5gveZTkEEm9TZ3Qj6QdBjpWG99ELKmifNlKbDG2FURJr2dJwdWp7IABRY+Tu89mrM4U5lA69T2lrgZhbpBNfav/9WShmkjBMmRjnhUPW6Ey+UZ+FHb1t21aHbBodnfRxoGSAlgtiMm7Znfwgh/CAyAUJ/n5NXUh0ZcPwjFBzI4G5hK/dJtoOI7SEJ+eStteTkNAzPca8Rzz8liMsDMz95CQLUKDd4mFxtuB/9QqT4WyM54veOxtizxLi6E/MOkAKXsPSFrhfXADMAdo+7cWd5JE75GFc/LIGoqdKPV36mS5rYqEjH1ZHVtmHHCJNeVKa0vjHxauIMrRNx5w2VZNou/C4HeFNVSB01cHwjFBzQ0mXaXL2F9rLawRRSeJoZViESH73TI8xOZQNrbtDPgdRKKyM+Dv57lSImkZo6V/suEXfv3oqrImjmSJr79mJ/EIiiak7Cd8r3v63G4wkabQyKYyvuVy7rBG6jGB4Rqgp+PZWnul93hQ5mE5+Qp1c5a89z/YYy22uUcZqbF6UPMLIPnxGaJTEDpWnxIO+44JZ8jo8FVbppP8YJlVJSP3UvdpXmvSEPjafrvyG717ufmPt5dtljdBlBMMzQpeDKj3GVqvVlPeD8O1A+wyR+lXZxnbhXVDSs/5PhePvUuNBCAFyC2nyE/KUy+8dqb8m2LactDuPlxUIaOEbPicufITk+jEt9R+nHKU6RAZFfZXYsgd2FSCvw/CM0GUo8W41sVZi7RZ5Ded7KvyXH6yq9oxmckmTzXHWGCrKc249Di907zXNwFam7L0tw7Qlouhha8DKPp26gmPe/v135wVtb2XEayXyMvzKIYTOYGLNq+7VBWcTLL2Vf4wVq77i+wrcnujbNa3mjGahS2qmDGzRdFWotzKXFhsWOd5IAJRrQnxIutNqCJ2X4NtFAsbAQKmFXk53G+iKgeEZoStF7UnBernOPU3Yeclk+NOG4Z6f3WL1B0wZSo8tdme2o48/IMtF/Is52vGJ8uSOVWY0o+eY46zuJeznJ/YuYit2c81Ie90kj07y/vSfoS3if20BAMC1sreyrC2CI9pZ/LoSSM3Z3zOtzOEXsyfcgBdK5H34rUOoSXEb//1bti0bwEA6T5DHdoQ/arVfZ91C67L8Qu1JwVxHaqbU3YlVLKurfEcEFPWXJkVxFUADUBQS1I62NlWZ0SwI5KCac5zVvYTF69nSPHrvbMX/BPvgY9bqKaWzb/3L2mBC352fdX9msSEsblmk2QgAQOJbdbK2dC1O2T8uzfdggp+lCYqFrmoYnhFqQkIc/J4diJSfuIfKp/Sv57IdrZXa7VcVgNv52q/ZxlTBVDVusJg26vTzXV1seV/b3Vu5vy+pPSlY7ZQ64kX6isNkzP8RiUBoEhWMr5/rXplxJvpWm9FscmzNOc4mx557tzXLI0TGThExhIYqQFpL/YO03TnQuX39i9swwvXt4f2PuVp82K37BAPhunYwJ+0zc8wbwYpEDcNCzLZsZ6nws2APN/IunJUOoSbERHoutO9GTQSUUNqzBd+bKcTpP3rarwNbAgDkrGTbzPKjrxqee0x3/6ltPgkAAAJOrNJWplV+pCwX7KnanH+7Xnze/d067uDnSKmjrFU6HSxFnmmzS9D/QfW/zyuhf2ofzWOHbQBQOaNZbi5f/031lIKzVaihZnk0KLJDcAAhAEBJkD+UFYk6l7GxFBVlznJFbuoSM9kkEQAAEii7v8su2K8DcNfyfHtIgE8wxmbkddh6RqgJSSQ6BP7YxQdGUCmPbz8GjiTgAFLV9isAAChGoHbgHHQdBCWqDADgTGWL0ujIJL4fAM41KdiQv5wm7FxEOd+QSvqOJxQqZxgNvh7iTZXRd2lR9RnNxhHLnppznJ0vi5olDFFqPAo/X1y/hHhqse24tSh+fYbnd9k3JrVL7Ju2lOu2nnAAjQ2O+iHachkvXY0uWxieEWpClHSeIed/y95+GkxRNC4M7Gpl+MxapdPBypn2a/hIufMr2qtPAoASPlLuEwzcypcsFv3vUfwWuz3hufakYEFDL2bxKHuKfjxEutEMAJUzjK7bRqIHAxTz5DzScars+rXKjGZRhNaY4yzyvHuuWcIc0dYCOWVCACFclJaBX6DXh4bRvgm9RELlL5xzXddlSY5J6DIj4YKfQ+gSw/CMUJPiEhl8lzpGAeBiw+vcHk5ojfYrAAhx+DuW2k159jpqsJb/8C5ZkaiErWbSOKV7EKRX7qjWpGA9Yff77nNPE3auF6hmToFt37H1qeB2AYkXugAgnhlGpewv2Bu/uz3Rd0QSUTtUm9EMas1xdp6q1p62jMaZyG8beElHyfck31ZCBrVulIOK0BUAwzNCTSrvV+1bJj94I4Wj+mY7nRIFUKP9CgCaOJIFSaOohQIE8i7R8NsRXpgtjmW7DwEwB2gH3e+cUO6rMSlYPJGm0O1z3S8sBkEgoJNyf9uqQ8xI58nKDYOJQROrP2BSD1j4srbfBrKRtBspGbfqPx+RpiWBK5V9uJHc/zi9nsmyTM7bbQ0AAo6t0xat40UuEjdKmTqUqI6zebUfpdww+BzTlpnayOPz2aezdS6TLjPkTk0xbBuhZgnDM0JN6uyCjIFELxWfzNQBAID4jybGM7FQJrFh8MdOPnAcNdjI/kyI7CfddJ1nIBOkfupe3VG5vy8hADUmBTu2jds6KrOmU0ux/vU7bPcpte16zxAzT4q2ub2asINldZUHbNK2+9L+tyujzfrn7+iWGDiRrf+xl+9M5qXt63SZsO/Xvt5Gpj9liHLy79/RNiapCRtr5nVtWK1py2TS5WalS4MPI0JXHAzPCDWpMwsyuo5ob66Va7+jXJHKPtxI75sh53/FXnpcuHUVQEifa+Zb5dEh/KNX2XENYJ971rcAtV6SrjagTCKqXDNFKddXHCZjHiGGUHl6a9raAs4CoBRSs6D7SBppI2ZJ/FpWh2oIyNwkgofJMWYgZnrzTMVtgLJauSOE6gxPGISah9rvKHMb37Bc35HMS9tT6keTwmBHBZUl99SxxvXz2Z6vmRIj2Ah19ijPbJq6HEzaDq02gUmVAWUQOV7tEwxS9ZSw7dqRwUqkAWgSBV1seMe9PBOokV5zqzw0lkhAbC6yal8dSs9FfjGQbP2TNbzQDdED5IlDSe3cEUJ1huEZoeahLBfsGdqcfwuHTOIHyxMGU5NMIpKkgafbr4oReLEImcQCKFCVxlpElh9xHxcCCAfgOuQDFLzr+vP07JhQri94he0rB8VCEgdKymZtRRslfsOZIWZ8ybvaYp2MOz0ATbeK41YSfY3kc0h3W+q5nDMHTRP55fShf8gBTr7sbbaspdJ5e5W85morYtUJ55muBCFUy+UXnoUQ4ryzHtRvJw3fz8Vl7eXsrpKaQiN9N5osUzWc9mlNB/YiShFfPJctDVNubg/xnYmtgqzaL4QQYddKLday7K+NbwFrOVL2TWbHdwiSRDe/6/o1HVQzoRK5/0XV/4T+4ScscpYcsFI/VEH6PaGMcLI5H7JyAuwD9yEJtBhBHPq6BfreYuEG8d1zLiqT4GCI9wXrtfI9g0jqPPZ7PudtCAHwVE0I+It/KBX+PqRtXxIkC/AlXePhpwxdyYKkkcRMBASQHm3hpxTO2tQz6jfB+eL9TKtm7eXsmqSmqI4us/AshOCcM8YauB9d1xtlPxfBy5lyzr2fKZz+T3kzR88/lNJGem1WOMWmH8SmdKJTEdWfTB5OzJHlVZ8AACAASURBVK6aKRbqybdxahrQE65VdEkABEGvdmJpJnPHgwTAuACuM01PXSCKDdDtDucw1bLuC3ZSJpZo4RZ6rwdoxP/4d/uEmsiDiHA5hJNDcjYbaRSygez/RtuVLyoE8TELn1A4lQksjb34r7MTgAQo4CuLzOOQBwCHtKcXAQDAYe19jd7TvzJ3XScy6Lp+ofLHdBB/bmGFMeDnFLtSROQNPOYYbEjW+o4mBpvYmSIibtQ5q9fEI011kv5FTS+By+hy5OXz+mp2mYVnQgilVJYbWmxPi6fh+6kXzzkvSV5d2F3TNEmSvF9Tz3/Km5l6vhiNlumJddomkB+cTf0cfOlb+soYeWBazZSpSUxnlNLGyJSL5I/Zvq7yrYOIwc4PZoro3rJnnSSZMqBUFpB6XI8KBLuDKGFyr3jt2yOgSsRllKQK2HYMwik/5ZA2L+TJycJhIuWlUsRo2mEr25ELAEAV4dZITBKpyOalAECASGAA6DBdsi0VsdOJ8j/h9hMnSwRzQ8gw5d4xRCUAAC7KgJBdH/L9PaT7+lFSwTd8r29IBZ1C9ADphpHUcrru4UPFiEXskxeFRknstfLkJGqM4kXf6nOe5Vwmba+VJ7WnSv3mxmyUk71ePDdbkiRd8BWyxtdUNb2ITL18Xl/NLrPwDACEkIafOeS0RilSfbP2cnZXSU2hkb4bAAAghNVOug2TAmUAP6lTtL6iQJTWTAHRodEy5Q5RJsPxpezFJUI2kfajlYktxe8fsY2pQqMEgsEt09gw/XdB7BulkiCx8ygwjcTrYncJlKXw4wHUWML9w2lLXzJQEiv2AQAc/V5PUUmbm5Q724il77GMMrFlhQiNowa7sLSR4g+xraWw8yvdPxhSPoSoCep9w0jBcm2lj3zHkLNd0H69lTuK3fN+EWE9CCEkb7W+gcsP/Yf6OfiSN9myaGlaUuU0Z8RAek5Xe1a+/cxeXkXiRilT75NG6WLvIrZiNXtjw0UsGen98wUa84tU76y9nF2TXBlQHeF9EEK1EdJhujKuDQCAI4OtSoEO7Winmin1fYx6fkIc/J4dDKfdYsBsAt0JhXbI/4VtM8s3jaGBVLA89vFySJgudwShZygfvaXtZdDtNnl4f0KL9Xe+4vZc3RxEzGbhOKKv2S7cNqiwiiNZEEjBnMHmvqXtLhVlKokYJ4flcWaH0q1saylQM+k8WoolpN+dSuh6belufcVhMrp/tXp5pvUekUQIAAjPPQoNkID60k7RcDK/5goWnrefJz5leH6mLP+hbcyH4s1saR69c7Zh5u3kyP/YAVtjHTWErmwYnhE6D+EUOxZob34u2kxXhkaeO6VxMJGeC2H5/HiiMutl9cYoUbxOOyyAFOuLtpPr75PjfaiyXdvsoKMeUF94q+KpFwyzX1KvixLJBwTXhNRJef5VdepgkruSLcmlNw4nRAK2SVeC4JRdpB4kbaJpGwsxVIhyRpP8QRAIMZEB98gRTGRu4OUtID2fdAwXWeurr1IFp6f1niGFebrZznHXUv0epfLtZynGDHIwvXmm0i9YZOwUEYNpqALG1lL/ILE7p/GOG0JXssuvcxshb9CL+YJ3mbWbfP8ztIV67pRGI5HoEFhjouP7E35CT84DIZGgQVLk69ohDea/DZHj1Xv6AjdU+xCRSVgkUUqAAlSksi/TSQen2OPQFxYBNYFmF1vziUkDzarvtIKcIA0o43t2aj8VAW0t9TfpWzIhRoFkBXKOQbveYucGwinp26FKz7Mutn9bOa13WpV8hVMkL2O/HoAete9Rar/9PIica8lIr697gdDlB8MzaijBrPfszr+xe7uRZxtSIjX38KBTYXu7hUZcls+2hDj6E7MOVe4ZdLp1WDulEZ1et+rHl91CiHINlPbU5xd2TCXRfah0lOescL9XrDx4Q7VjSUykyxQlJkR7Yy37eJ6wJsrtTNB9htpro/v9Q3Rse54cRkrXCWKm4arIP6qv0gEADEbCcvWdw6XYFH2bA3QhdBlSlrG4DqSiVIo1V8nAJQ5li+yz03prc/KV+6+FxRe4R6n99nO4EqBD1gL3bKtwA4n0A66L3//rXlN9NY6qM50hhAAAwzNqEKGtPZ79av6pVa7AG6sk28tzZ2SVFVnCmqxgDaWJo5kia6/7XwsrE6Imyy1rpNykPjDgQvtgeeztl/VCzy+UTHxW7aPw379l27IBDKTzBHls17NzhFVdt+rPV7StGWw1IcGyOGWnD82Srd+6v9rFlnZSp9VarZlQkHyl/kn6GisAAAiRnQU0mPhTIAE0kvJ0ABsHky8R5RDSEqSuUvhOffdv7JgAyUg6jVYmDyEmAkc+cRe2rzLLNwCY6R2veBrsIuVTbXV7+f5+5Mjn2oXuUSQI8CFt+9FgBUCh3eJhcY6wVEBptPz0TEry2LuvcarSEU8bRni2d4vVHzBlKMZmhGrD8Iwagob5BN7ZiqRnameSOCv9V1rZ2OiAE4VNWLAGUumk/xgm1UgcItVeM/EC78fqVqElKmfn0BZi/6fsQKT8xD1UPqV/PZftaK30C6qcUnu8hX2dQsY/pMTn6lvKgREAHyi1Q0wfalvt/nq3qAA4vI47EqmlenwmKkj+JDGGrN0HQRY4WCrMBHpOoo4lul8LGqjCia7ykyPE9++wTB9wuMDPh06ZKd1Qq7SJd6uJf3lYat+13KQ+MKBKTzUlbTvDn1t5SRz1d/LdqRA1lSZaya58YddBLhI2gM5RZ/d3YhXL6irf0fIvM0boKoThGTUAkToEBbd36+9kFVemCPeilMzjLds9r2Z/2qRFa3o159BmIj0X2o+lJgIQSnu2YJsO6a7jPDmZl7ankWOkNjvZD8+7DCYiu4SdkGtuk7UftB0fuw4TaDNU8tvK96exDfnq6AjgDr7mO7YxVTAFggzEbmPvpYLbD8KuIas3cYNDpH3s3l4BLY9BvD+409gX+/hxG7glEhsE7ouqS/ydpA0jRCbnuGupLmSIMmKh9uEzQqMkdqg8JQHMbeVJC9ncmcyugV8/5fpWlVvyIn3FYTLm/y7BwwKErgQYnlEjEul5qbNp9K8hqlKXVY6ubDXn0B5IokPgj118YASV8vj2Y+CMJ+Gnp9QmvtKMf5Jl89mek8JNQQqRhiRQn3+q0n/d252Q86dOOJB2cp8WAEDy1lYu1Gj90f3xNpDj5Ac763OW6ZuClZGS9pMdJF86cDItXq6lmkmokWfkAgcQQmRlAMt2v3NCeWgK1VPZhxvpA3+nBgBgYu8itmI3187M122r2g8vjanzio9EJT2mqz2qJsmky1Sly1TQS/iid9jyDHVyLABA1iqdDlYisV8boXPD8Iwakb6vsDy1LLVjIQjOSnlJx+Ty5d1j+12dzSNDBO0TLQ3qRZQivug9tjRcvXGGnP8te/tpMEXRuDCwW0hCF2I/vSSUHEwn/0OdDGDbrr2zj6gEiAwWA2ndnjoP81KnYMUCJAAQigFoOXBdlNjB10wGTqPGdF02w6mT0JlAqx60pIz26ykZW4hPPhdDHlK7+Hr2KU0B9kdH5d4OYuN3mmchLE9RPa8m3ztb8T/BPviYtZolkwVV++H1HVHQy++ijoImNvygtxgvt/cFKZB2DhdrCoSIJVDON6SSvuNxCDdC54PhGTUieVLnPk4Axli5NbV9dvCuZjJyu6JqS7HOKQ0U1IlKC7TXfxRMJa1DwJYlKlS+/7CwAdiO6CcJRA79q+DkGQhdQR96RpY2u9/4ma/Yz6N2qn8eBZdLe3UXAEDkeKVPMBRvFhVWobpEQTEoQcSSo7/+BJPNpNctSiffmnsl1RfCAiEydoqIITRUAdJa6h+k7c4W/tX74Tdnkp51bkBXI4G5hK/dJtoOI7SEJ+eSttcTAlCeoh8PkW40//UOELpaYXhGV7SqSybXPaUxMhZr3tQ2+suPvCwFnmBvz9EtA0jBWr0kQH7yWanoR/dX20TBAvcXpcp1Pqc/oost72u7eyu3nClFlYHQNhORfUTOOpblow9pK+0Kklse0LWxsvqLNj8Njh0VQoDtD7abCEc56e4jChzgLheb5rk3AVh6Kw8lAAC0vUtNAgCAhC5VFnLWoearyaXQKQT+rNIP72hPLnIdBEq6TJOzv9BeXiOIShJHK8MiAQBydgrfGgPFEULVYHhGDUXV0M39Q2sk+gYk5AU3g07tmi3FuqU0Ako6dyJbd+tzn2KyARSVdoqFQBsxHtfn/JPphAx4xDDSny94R9s2kAAACDixSluZJsJ7V9vJmYHQtEKwcggMI5GDRO7/IOl6qY1NX35SWMpFphU4J6oCxs7UZ6eut5Kuv1MamcrmfMvlnnKnVF0dSpWceqzBJAjpNEMuqNoPr9Z8oavu5GA6+Qm1xqD3Og0UR+iqhk9+0BWNmEhCF5oUc7YbuS4pF6KLLe+6P9h6dp3cijT29ufcVWvDyIlyH5PQNHCWg+9IeUALsBWCMIEJgKhQls21QHrzTKWnL8Dpqa1HJtVcoSBkiDJCZR8+43p7uRDB9Kb7lOvieOsQOPC79muKCE3XTzAAgLi/q9NihXZABAaDbRf75Rtt7jy91AZ0M9sUIA1oCdwl3Jns5Sdc/37K/c0fwlV1WUcJgi1QUiYEAHBRWgZ+gQQkMvgu9d8vq0/cJwVxEhKOlwqEvAxbzwjVXfU2LreJDcvYrl3iHL3iQhz+jqV2U569jhqsfMlcbUWs2ieC9omiYi3Lbk3SlmkvrSGJ18qThipPJ/EFH4r+9yh+i937AXx7K8+cbkOfGQht2669s4+aCYgKqllIyS4hKORnCsYBANLmu9IAZDM/bCXt4viOPYIBgCIKbBAWRyQAaz4Y28kPTqeWYv3rd7TN7dWeZ4pKSGx38ssGXtJR8j3Jt5WQQa0h71ftWyY/eCOFo/pmO50cVZ9lmhFCjQDDM0J15mnjXhvD127krr6SUgH5J8AGoB1mr7wtPXyd+HIjvX8qbP+OrU8Bu0OArL2+i/a+Se7eFpakitHXyiNBrFolTuryxB7id1/JvIkti1Bar9YO58Ke510AAPu1LQlq/yAAOPs0+v6+xBOz9WL+3btqUZL0f6/QFipAuf7OM6yAgiqD5gTmAB5Gb7hXtgCcWuZ+808RFEk8i0YrRqB24Bx0HYRE1OonftA18vh89ulsncukywy5ky+QMXL3+ezVmcIcSofeJ7c1MZ15+WAjdJXD8IxQ3XAr/+lHHhxJtu4WLBJAiENLIC+W9DbAhgzhyNbnfijcSTR7gfZLpnzHKP3rXwgBCPIXG+a5N1LSYozY+b62v7Pk7ybaIe0HjbS4jnaL13/K4OUnwC2B0QC6AzQqtq3jvaZQpfbT6Mp5v10zuhiCPK8L+0gPP09++5JtShecErO/CBgomQC4lS/fAkInSQFwDACYKLAR5+4zg73VPsEgB59to4NMutysVBuabaEjH1ZHAoCAY+u0OR/yIpcWN1KZOqxyPFejD3RHCFWH4RmhutDF9m+ZPFruIoNfNt8MnlnARPvBUgRwtQR0hzBEEi2HLSwFiIWiPRA1UVKWsMPZoEhgTCL8T910j+T7hb7HLoRM2g2gxb9rv6sQNUMaFqB/VqA8egPJ+tS9uqNyf19Czj6N5vvPlKFyTk3Dqwsrn3QbeimzhovSQsEBhACnlZjtwEr1BW+xDAeAJIUC3/eH9vwCUcFBjZMfGye++ZhX/OZ+fhVRFIgeKN84klou+FTZs37ztFk0opwumqtt7KAO9bkEA90RQjVheEZXgapPc+ueUk3l8k3aIQDNAZywD5bKg0LI+sOiWyRIKcBKwXlSuMtBl4DY4ZQGjpUstwIAQAPQ9nO3hexx0E7+un2s0nqD9ucGnQsoaSE/GQfWHcK6z/3sBhACpFN6YU852M6XLD77NLpS5UzgVmupf/kW97xfRFg8ObmWHbACFwAghIDCX9xvVchmJ+gAoOtLDoJOwNeHKLpQTuiHTUoHma+nJHCg8ugA8fObbGlrdVrS+Udln12/WddVetM/qWYEwi7BQHeEUE14+4tQXZjpHa8YXnjF8PwrhpuiCI2UH7hB6jaDtDvBP10sKqxAKLhUaumoPDKWwEn9iA1O6bS1P+n9mOHODsSvBe3UEsoLRaEd/K16slu6+2XD39oRpUBPLoCyUiDB8sOvG55/TPYv0D9bLbZ+y6RxcvegcwfOisyzw7xbj5MiZKAyEBO5fpY6PQ4CWtOHXzc83I8QP3lUKMhRckcjhASAXSdEBkqBMoiKJbIv7RQNJ/PFhV5orly/mX/6Mn/tP9qPWwVI9RzoXh8VqWfHwLM89vojxpeecc18xDXzUfeW4r/4LGr+XMeWPTWuc0sTIZbIXre+vbGw8mU/94lfnpvYvbUvIeaWnUY/8WOa0zMQ0bHtwQjD4B+OrHy0p5+c+OIhN3Dr7o/uGtwuRCHUL3boQ5/vt13RQxax9YzQGVWGYpHzpVTBJTHgdnnAfn3OeuHOA0kGEKDZgevCaSaRE6TYVczORVYO6B3kTjYtDwAAyvaJ4GFyjBlSVQgcJfcNFpn+tM8YqaUK0EbqH8h+SdcP5YjjZxdarpwlW/FkWir/tFAvB/jVAYpBuHrR/q3Jz3lQ4Ra/zdFUN5jbAwfwiSWWctKCgzmLbSkHAPANFevfdDM3kTtI1yWAM4OtSoEOIy+4IkXl+s3kwSepj43+Mpcta6VOrbWoZcPVnhlGtwotUXt8hk+Yf2NnhpqCnvv9tC7TloTc/Nw7M2PK18/99+OjTgYcXvH3yKKf/tZ18vdk+GOzP++qpP70+ks3dTnw6aEVd0bLAADutHlTbz2oDrvj9gHBzh3PXtP7v+nd7nj2w6cDj/385uw7+hxlh1beHaM0deUuEQzPCHmcYyjWuaYKAYgdTMz7CAHI+1V84xYP3Kjcneeek08SyvnRAj73ABA/6fYR4svtPMkMx45oe8phyHAo+xL8gkgLM+wrFX7Z+iereW4RKGagFBynxIljwhlD9EPaHyUQOlK+66HKMzO1ytNoAABdbPxYypGkv8+StS/cC46wjSfVVipQGcBN/MKJO1tUsDPhUzCVWPpKQ9L1w70l/7W6epcasVQ71J0e/kH79QD0mK4MjbzgMTk7bRlnfrRrvP5TtuDtG3+NqdozwzhOCSVU4PXpSuE6+MHTPzmGffXHN7e2lACmjYpIbz1jzpLjU0f/+Mz3hZ1fObxiZqIKANPHxw6LvWv2+/tnvNYNAAByD3b/9fCno4Ioz/9u1OsHWz204c93B/gSgFsmd7spYfIzrybP+LDfFTo5LHZuIwQA55oY5HxThZwRNYZ0K9Rff8r12R6QjVAcQywdpS5GEGX6+4t4eYq+MkukrRKGQXI/jW8rId2iSWxXUlYOeTY64TYpyARhKWxZKulxi9Riuzb7cdd/PhWmPsqdfavlwgvYO2emPXGK7bmEWfWPn3J9eUQ43GLfBm7pLU0YRixJ8t03EyMQv9DT3c4cUrIgqZfUvjvJ2w3tYiFtj761CBxLtGSjdP8zythOfxVoKWnbGXK28hIG3Mb3pEJU7CVZxKJ2h3lZLthT5c9ec734vPu7ddxxkXOKombi5OZfMuRBD4yN8HzjaNgNP2ZkLr+lpX3fr4ehxwPT4ytXLpNbTXhooJS9dvupyp7v0El3DwyiAOA4tHSbO3r6nT19PecjDR1+30jfgo1b8q7YV/7w7hQhAG6tORSrdsoZZweRWciw+6WREqWML36J+YxXR0aAbbtIWSl8+ymPjiK0VJ/7km7dw+YcrHyfmA6Quq4Re9PZ57mkyy1K4m7tp2whwkiFHXyDiFYBzhR97V4ytiuRAbiN55pJ6VpeHkk9z9jsaXoZhdAukuUYP3ZKSPHyvTfQ4sXuFbngztNefgVkk3Rb0umCEogJg007+cBR8vXH2KJkwX1FQiiUd1fuGVTXFrBn/eZ5zwqNithr5SnxjdCzXXGetSy7dBEAwPLYuy/rhQAA1EnJdQ/KOV+xpeGXpFMdeYs11wp+nUPOzLJO1MBWMYGgHy+0cik40u/M15EYQyN9IafApkMwAEBgVKAnSmkleTbIfq2b6bVqO44usLErNZBdmbVCqB54qf7layydkfT3tNY+IAD0U/pnb7LjHA697o7084yLviCZxIbBHzv5wHHUkih1/oVpMYQC2DO4tY38+H3UfCawqHTQEEjLle+9hfo7+dIfIGoqpP7E8kxg6Cg/Os6zgCPb0VrpFwREIqpLOMXpTi4BmZuE0QBlLvq3WXL+R+7Fx/Wfj0o3j5F7zmfrNfAPp/4OfjAP2sVW3kPwMlL8DXvjGcFlEn+9Mvka+G22dmCh+18LK4sTdZP6wABCq4dMXm2xZ3nsdKW7YIzJskzO9CT8xUD38x3qWs+Yq65lOfcDwWI9T52Vf99FzYq1vMzf3x+y2sPiS9OpjrzF0sIHygtKtTMJWnH60Xw1OiTYj+rFuTYd/D3/XeEqzCsHnxAfz6+EytTznZP9gs3Q7vHVP05rWeV7QNTgNlfsq/cYntFVToiD3+uZLpAUwRzicBHwHPcb/sShgaQA0UVWHogf3O/knh2cdQ6UdJoi7ZijvbAKgIBPonRfHAgb/3mRsLvYWy+SzhNkT4MYTrdHP3xGaJTEDpWnxIjfvhanygBytedXAQAEh8DeTNE3iFTk6DvK6bWRfK0nFy7yS0ChoOWwj/4L0QPkGwPZygz+8wp2uFQAJS37yN2PuH+e75pZ5ZUncyL1bSc/eHr+kAkzFb9v2e+HBe2oPHMXVez897nan2lC40BaEpcAA4iD31dd7JntaC33DWycg33htSx7WvgqJzhPCSUE9r3vPtCNTuwCvja+Nx1a98LYfFkL7zuopfuzeb/lj7s5nAKIkt8f7Dlm63179t0+KhGe+uC7tNv/0U4FAHZ8yXvrWdTDvUMlqP5Aw9x+XFd5xfp03+eGx8gAAFrGF/c9tLrLG/MfCWuKGnmB18KzcB798sFbn/5uR1FA9xte+PKjuztaSP02QOhSYCK9APo/bhgdCQDit6fcm7sot3cGd2va2gLOAv3T13TndcqjQ8/7BNojf4te0EaZ9Xfq5+BL3mSrjoiOm1l+P/nZ6g1iqDKN9hmTXlRj5ml/RMn3jKNSnv6/t1lZCbDTvevKZ27wNN85aEyU+wolULnnRlg/hy3TIeoafXeB8Buq/quXWPS2tkaQ7g+oY1oBAPBiff5bem4aL06qDG3cxtcv0bcdERBYea+Qs5Jtt0iTbyMV+9nyvfq2k9KIIJFec7Fn0aexwrOJXGAty0ATgFtYc8GewTbbROky9e0lLqMvaTdMmRjXOAVATcTU7bFnh35y3/Rrb015/LpY9875z3zvGPjenUm+bcJevPH1G/45ePzJf03rLKcsfu2lP5URnzzcxQjgqLYHKXLKf+6ZPfS+QRMz/nFTZ+OJrYvfn/ub/792xFyxjWevhefyzU+OuH/HTQv3Lm2XOXfq5BGPxB/59Fp/Uo8NEGpc3M7Xfs02pgqNE3mJ3uc+yZCu77CDaxv75Cjpcj1kbdBWpENIBLH85cBQIUrtpNswGiAB+NJO0bAil9cOcn2DzhPjKek8Q86vuoCjLJK/ZdI4pXsQHDizmQQBPiRutLtNMv34deFyg4iV47L00jFy2G7t9T8FUUjciMoFlQEg909uT5JGyPqqKktntuwsDTOIX7IrB2EpRqB2EtOR8kKAfaDKABKJDoE/qi72nATeGZhlCoTw9tSHiz7R0qBeRCkq/36OqkzHp85XAqXNPT/v9Zt1/wvvPvhtoRrZa9Lbv791f5wCED7lf3uWt3vg6c//dfsbeniHQY//sOY/N8ScIzKRgGvfTV7f5uEnP3jm9tes5la9Jr625o3Helyho7YBvBae7bs/XWgbPf/psQmBJGHWa5M/uemTnXOuHepT9w0QamQ5K9k2s/zoq9SYzea8z97+l26UQfeDsBHKA+35N3P1kEcNLxG+6B0mh/5F0xkI6TBd6QAAAA7P+8TDaYtUvXaQO18PLZfI4LvUMQoAFxte5/ZgOJwtsk+/+qwT9sEi8vAU2rYz/JlMBl+vzprCl77F2DBaukinRaLQBYqRRA+QJwwgKgEA4EX6yjQy+f+kgD18zb7TxTzdeP0tuzIlfKTc+RXt1ScBAGiE3DMYAGrdK6hAAC7J/A8SBFsgp0wIIOT0Wpah8fJIBSQCEMp7xMNv+NT5CkHMCdPe/X3au7X+oEaNm/3zuNm10s193s+rfmMotRj45HfbnrxkRWxmvBOe9ZIjB8oib27nQwAAzAmDoh3vHzzFhvrIdd0AocZ2ZhEnDSDQTAc8LJ2ax05JxBIC21eLiEC+N1P07UE7h4s1BULE/lWEBhBOkbyMVb5PHEVghpz/LXvjn8ItgDNQs4RLEPN59lJjAccpcTTulcpOu32vu78X0gNTqFL53Fr/6nWXLpHYofKUWPhTE/nl9KF/yAFOvuxttiyysq2ZtUqng5VIFewXKvHZVS/df2pvrNR/y5Amx9a6VwgnFC5NA7r2WpatRPL72t5uym2DiMFODmVD62swNqOrk3fCH6+wOoklyOw5zSRLkBkcJU5etw1+++230aNHe7YbPHjwCy+8UFpa2tACcS6EcLlcDdxPfTMFAEq9+q65rusAIElevcJxzgkh5K8DWmPSNI0xVo9MjX1Iu/eNnoaj1EobRXWXwbi9iE/wc9pzjFvzwedE2algaUuO3GpImbX0nK3HszXVS+Wf5yu2ju4Zj+hBCthKgdlJu05KcpGY+nd2Yr5xZ5prbaprQOi5C+PbnyYtUF/5J5ha6NfMYMEuUVr55SS6jyG8ndNZKioAAKDtWPc9w1VVBQBwlxODydi6k02yCxuQ+GjDL0fLiiM4tUtrj0qdBjvKSsHuMAjNaS3l6um87A6D0AloTmsh7MtQYvs7tDJwEKNsgrT9ZUVBIn+FYamu/W2cDhnqdcnAtQAAIABJREFURhuM8XNYrZzzRvvqVi0S7UCGH1M/foFwWSRNdEcJIcZLmQvFf5YJxSRF96sY08LR4PO97oQQQggvn6QA4Ha7G35Zq5eLrqnb7b4U5UG1eSc8U6O/SThKHDoABdAdJQ4w+Rlp3Tbo0KHDRx995NlOkiSTyRQQENDAAnku5SaTqYH7qRfGGADIsld7BJxOpyRJlVdzb/GESS/fE9hsNovFUufLjRCHvtSO9ZCfvY6qefoHb8G8VxTfFqRtpLTqfZMpnPhL/NR647xkkjhWGZtoVM8d9TVNkySJUiIOLdKcw5UHBhnOVPrYGvf/9kHwWCXaqq/UYMqTapS/yXK+wd8BMP4xGH+uv3S7H7qBsUqC1Wr19z891WXHbu7tB3xFV+rv5KnZLKa/X1AA2DO0/DBpeoTZTEAya0Qx+AecXflRMmtEAlB8/INJYoT2R4rfiHhKiKY7RKtEv6AACJrIcz6ic2cLASAZyP7DxsTBujhB5r7ueR0ZgJKJz6qekW4XIWAIPDvk7LnX71boV/mjyXMops08R029gnOu63q1V8i8oqlqqij1nhDTyxeTq1mdQwWz5R4rVsJbhZirXXN1e+EpGw0MCzJc6MssBSZ29MvdnuGAOH+AioytOabEjiFy3TZo1arVPffc49kuJSXFy/eY6AqliSNZkDSKWihApDShh744WHngGuAGYq7s1NWOT1KnJ5zrswKOrdMWreNFLogdTqcOA2Mp//2gyNlb7X3i+0dKYVtZ5gL3qxQUM0neQ6OGNv4lv+ZrWvFAAHJ2Ct/2xHj+3Eig9M+7qAGg8wz5/9u78/gmyvwP4N+ZSdIkPdPS+27pCVgK5RBYUDxg8QAVVEBQQQQV8eLniq6Koq73hbqIouCqLIjXAouiuCpyUzlazp7Q9L6StE2bY+b5/RHAFpC2NJ0k7ef94o90mJnneTKZ+c48zzPPU/mZ/dVFTFJwqRMUk5KJIyJvPs6PQser7h3HUaX48Zv23f25QUZmS1UuvpeX9Z4WegJRFM1mM2Nd7b+gVqt71c1BB8KzVb/xmdtnvfBTFRGRbug973z62rSkU6eoreCd0SmPhX5j+N/EC975eWfeNdl7/NPv7c56OPnkh4vXcRO/GuJDYvWurzdX97v+mjTf868A0F1aDSTi1SD9nkeRg7nK76yrWzcAR59/U8cUyNMWeUU32z5/Q9yWzodtEu1jlYtPvUMlpT2ovDSQyMbH+FBFrHL+bfxZDcNOdO5rWkSUOkeVevrzhafO5P34cfeoxp21U0a6EYobYzgVUTORUsmpBGquYcoQDp1BoPPKysqqqqq6vh+NRpOent7+ej1Fu2eb5ejbN17/wqHMu1566XKd/pfPl/5z+rAqRe6amyM6VXPpM+LVzW/dc9ukqKcM/gNufGnz0sv9OTLnrbh3xo7H8sal+SrPuwJAd+G51g+OiWMVNyaTJkox6CP7S39j2hB+7Dxl4nmfE09NgayI0xKnpcmPCKKSbTnvO1R/zCdBpOQzkzxn6CuOQtJ5Etlvb1vXF1D0ROVgnXiynJqKbW/9nZkVXNIYxcQxvBYj9kOHSJKkVqvj4+O7spPKykqz2dz+ej1Ie+G5ef87r+/pM+uHH5dfGcARTbvzjstu7j/trvu+Gr1uSlhnrjOcJnXWyr2zVrZeph2xvEq60AoA3ec8D47e/NX3q66+8GanpkAWP/hRqrGy6Eu5SZfz531RWOC5xEvol51SfV/ev1nal0fRU7tlPonuwJqlravtv1ZwWm9q2Gz/KpYbGcLFV5PeyCSOK9ts/yZMNRWvI0NH8Tyv1XbpFWWZe+24g/auFtbqvGqh/3WDA06dh4qom5e+O0H65oHFW409eiJsgPM7NQUyf9P/qf72MKfdIa3P5wZMV6Tq7W88YX33WxYcSoLqVNwKvkx5lcr+zyctS160N45SXOOM+STkYGMb37T9ZFXMf0715OOKUDs7eoA4RsUif9cSr8dmc3YrKz7OMIkUQHdq735EGZQQJK7/Mcc0cbSf48oiRN78zusfpc+95b5xB1Zd2/05BHArbaqsuYy+7D8nmD3mPC8K0580DHsAnklNnDKR0/Ik2chKxBP75XvGMgRfgVQ6LoBRnbcn1NIDeLD2wrM2Y9bMxGWvjPuLYdH8m8ZeNW5knJZTxs9auXzjgJlTxrLFs9UXGvUAoMdpU2XNDuRT1JCO9inzGAI/4SGFfaXtH4sY8cTx3NDBnJjDfE/YX/g/ptRy4cGc1otJ5DF19QAeqN3afO2QJT9t9Jk/f8nTd3+26omDh58b4EWkiJ6xZg9//5S5Ty5sIqIEGTIK4C5avctEcWOEm/qSd0f6lHkURRB/w73KaMcgaFOFKyPFHwQufqrqkQQiouMfWL/zjGp6AM/VgcZ2r5gJT/2n8EmrsbzCGnjmnTN10vQP9k1ecuDX3w6cVA7w/MsRQEe1qrK22Wy8wBHXkT5lHkWsk9a8bTdmKu55ku+jYkxigd6U23ZwbDw6A3SnDveF41T+ETFnL/MKG3jV5IFOzhLARbOzH1+x/lD5xwLvocpHb6Df/mX/LY/ZVVzaOOXkMdwFx9ABIsaOfW03jlXePfp0AzPHxQ+kzb9J9QNOD4599tUAAJyrgzfA9vqjP6xavvGkzfGnrWDFrMl3PfHepgIzum+DG1FwVz7h9dLbXi+97fXSq6orE/jRY/mqUzNTeT39kGDZbNvuhOERejobO1bEitdZH19g+dsCy98WWN/9jfwvFa4Llj5cYn1thdR3umKAr6szCb2ZtWTD4+OSAnhOGTL4jg8OmRlZSzc9NSEtSMkp+6Rft/j7MhuRLf/VQYmzP31nWlpw1mv5FsOed27LilBznDbuioVfn3T/ocM78PRsK92w6IYpr+1piZi/a8Y1MUoiIl6s2Lri4y9XvPDa1A82rrgrFZXb4G5KN9uLBypmRVDV6ZmpRJGYwKl63duTnafib3jO64Y//maM2e12LuNm5UBUPICzSQZp/cf2vWWMERczRjH9Gt67nZ+ZLe/dm6auzfxoe8Uo28//mDrrlteHfRl07+Tl4W98f/LmyNI1918zeVrUoR9vJ7KXrH5iw4PP/fuxq7Sb5414qu7/vs37MaXuP49eP+1aXfaeJ9K9LpyQa7X79GzLW3rDxNf2pdz3r737Xht6Kgwr4+/+b4W5cP3joypWz7n5jSPufxsCvYtUK248wo0fwQmOKY1P2F5aaHn6H/amMYphQa7OHAC0Uvu7WJ2mfOJlr2f/LnA7xIL2hwY7+sl7R4c+v2Ryekh4xuQln32wIKVi3bvZqYtfm50VHhCeNfuVvyfueudbvZ1I4pMe/uezM67oTz+9vCH40aUP/iU6ICRjxisvX1q8esOJdhNyrfbCs+XoJ+/tES57f/1btw0OaTMWOaeJv/bZNcvHaXJWfH5M1okZAdpTvFnkxwiRqlZTGr/p9fwzyogdto2Frs4cALQSfLly2iBWnC1u2SSVmsne/ng3NfkGv+RYH46IiPfPnHr3tbpKkza+r87RVUIRlBTjZThRZyfivWOSgxRE9vqiqqbDi4eFBgYGBgYGpczZbrNVmbq3XF3WbnguyT5JqRMvCz/vEARC6Jib+pF+nx7hGdwHa5S25nHD+3E8nZ6ZagjvzZNCx2clUkEeE12dQwA4hVHxf6zvrpXK7VzKSCHJryPbBET7mApLHT2fWFPuv17/XB/oay4uMDhObXtdfonFPzpAQUS8QuCISOEfpfPJWppbXVdXV1dXV1NefOznpzO7rVDO0V545lRaFSnVyj9pCmB2i50UKgENUuA+mo6LJcFCgmOAXwWXEEqHs6VmRpJJ+j2PIuPwRhCA25BYwWGKv1px2VBeWysVm1gHnp7TZ86K/W3R018frak++t9/zJq/vCj21vsGH1288OPfK02V2SseWZI39L5JMa26mfCh4xaMLnz20VX7Kk01x75/blz6lW/l27qxWM7QXjcZTcJfkmjDl79W3T09/NyLmlj587pcirs1Tn2eTQGcys5+fOnsl6Yem85XnJp6WRl3GZs2jrRnzXZ8vpmpcDcJ4C4ELvNK/uMPLU8puPBLhEvT6Yd1Uvos3udCZ6lXv4Vff1Qz66Gs4JOW4EHTX/liUWaqcs3asrsevCJijsk/efz8davvjFVQfqtkIm7++MsT8+ZfHTW7Rogcceeb65/OdPe4xbU3RbZY+ul1yTN+G/X6ln8vGKJrXcUtGX9/55bLHtgy4N3jv9wbL0932OPHjxsMhqFDh7a/6gXZbDa73a7RyNrj3G63k+zzrjQ3NwuC0IU5zFle6aGRlSEHMvvUndjfv7j5j/9RhvwyPGl0658Es+/S588uMVUy6uMb+m5azNg/q3bpKiv74T278mblkBrbmxu5aQ8oopvNn76hiLxHdVVk96R4fjabTRAEnpf1edxoNPr7X3B+dWdz9NxWKBQcJ+utjfwllSRJFMXeU1KlUtnZDb/99tuKioq5c+d2fJMTJ06Yzea0tLTOptVaSUmJyWTq169fV3biWdoNFULkrSs+//Uvkx4eGvLOX++ecVVGcly4V8PJ4wd/Wf3PL3LMgdd/sGq2TLEZ5NfUoJ9aaKz1DiHi+8UNYnGOxWJ28eGFfMSQtj0SWhr1M0romUFDpggt3xcempbndyRdp+uObJ16aSqcjnx7ZuplceJ8L0W3pAYAIL8OBFZF+MT3c4qn/POpRc+/98ymPxbHXLXw01eeuDUjABPX9FCS3fDYceOEeJ2+7Uge5gb9fGPQqgHeZ1U+mCy2hNDI69Uc2ZUj+/hwReZaptM5/SHE8dLUXx/ghDZTLysih7Abx7W/OQCAJ+jYcy+nib3q4VVXPbzSaiwrLChr8YvpGxfqg2fmHo1ZvzxedDIy/RlV0QdtlresLDSMiu+ffE6FbkifpO/6EBFZbQ1vFBuD+0RHdUcFYfFmkR+jjFQR2U5NvTz//xQBzU1fviatj6ep6Z7QtHzedvRbuSNf2jfuk2xqfsjNivHp6MIG0Jt1LsRyKv/I1EGyNu6Ba7CC8rwlfOyPoV5KQ5v/aDDql1L4Ft8/qTNh4r6K4nlFdV6hiRtjvJ3f9eLUS1PXczydNfUy659A351gUronzEOs4K58wutKx2dHO/pYvnG77dtyfu4SpX+p/b3l9qhFykswcCZA79WB+3PWcuK7F+8cPzw9PjZt2F/nvPG/MgwS1vOJB2sa82ryUrftismprTDl999buEMkYrbNemNKpC78vE+ozPL5kX3jK4SFl1zyU5wuujse/tq8NMVziZeQfqdUbyepgcstpKgEz3vidLSj/yWcFWaz8DF8iJLUMcKIQLZP7+qcAYArtfv0bCtecX36nB+alZEDBkWKRd99+PB332R/e2jV9SEe8IwCF01xwyXDHL20G+qPJhcF/p4ZEs6RZDUuM6nvSTl/h+za2qLHLJHbMsLjJHt3VTC3eWmqzdTLQsxIfkpfT6jZbuWPdnSR1TZRUADHERHPBfqTqZZJ5Hl3GwDnYIyJolhXV9eVnVgslvbeM+pp2gvPliMfvPBDc/yCH3e/fkUfgWxl384ZNGnVwmWPj38q/aLf1QFPZWyoPqDSZZ7/VyPl1TWUGGuTfj01aqbCLzE/MyzWufEydY4qtdWfraZebmhoUGk9Kzi3bke3n/1fvetCBD2Z2Wy2WCxFRUVd3I/MbzC6XHvhueXk3hJKf37+6D4CEZEyYtyDd8StejenzEIIz72Dry61/PT7SrqgtKo/nVGCH548hCUTEdntdo7jBAEVLBd0Vjt6kDfpTYwRx0nMYCI/HR6doWfQarWMsfj4+K7spLKysqmpyVlZ8gjtVm6LVjv5hfududAq/MP9SBJxaw/QRY529CmOdnSOSxjEbdoq1fcXfKukXfXc6BgXZw/ASTiO43leq9V2ZSfyjxXjcng5CsBFzmpHDxypuL7C/uESUVJwGdMVA9BtG6BXQ3gGcJGz2tFJwWXcosxwVW4AwL10qHVr58wwgTtFmfDgQTJ/fbUfd0bAtRuN3Z1PAACAXqS9p2evvjc/cl+/lguuo+4X5+W8HF0QY0ySJMfcEl0hiqIoil3fT6c43gqQOVFRFOVPlJ0mZ6KOH4b8fTslSZKk9qfAc26KMh9QB8dvSU7yl/TMSSpzM6erjulFJCrzr703ay88q/vd8+o7suSkE7p+5px58ndKfjrIcebLnKhLSnomaZmT61XHVM4UiYgxJn+iLixpjz+mF/3T7W39s1zIw9qeHT0Au/7GjiRJTtlPpzjOB5kT5Xle/pK65MUqR4oyPz07fkgyJyr/d+uoteJ5Xv6gJXNJHdMsCoLQe0ra2Q09Nzw3/TYrdnT2kwXZD5xvkkVb/quDL932auHXV7tNp0wPC88AAAAXQZ0y74PVdf08Z8BLDHwAAACuw6xf5R2M2LrTb+vO2AMnttja38L03XVho9768P6/xGg5dXjW7csPNjAikgx73rktK0LNcdq4KxZ+fdJKZMt/dVDi7E/fmZYWnPVK9pan579fLHF/sjkRa8x9f/rAMDWnCLn0wfXl9nb3mTxhWGD0PTvMRERk3r0gNuTWzc7rKI3wDAAALmNtrv7ArPvm0uGmUYOep8oXDPaO9Ck1bnv0Le6hzSer9r176e4F1z25q0mq2TjvmqeqblmTV1+549noL6Zd+8phCxHZS1Y/sSHu8X9/NCNGeYHNiUiq/fHNwxO/zK/Tf3+Xadkjy45a2tvnureevMqyae3hZiIy53zyreXqOcP9nfbNIDwDAIDLqLSR36b3EY3VS0+c/KDB3ix16JUPwX/iK8/ekNonOO3G596c1LR62Z6i717eEPzo0gf/Eh0QkjHjlZcvLV694YSNSOKTHv7nszOuuCREdYHNs5uISD3o8cU3JfpoI0feND6ypaLBVtXePvuOun1U4/ovj7eQOedf623j7xrq57xvBuEZAABcxmgs/svvhZ80sfjAsPt1qg62DKsiMmJPTYGjjcsIaSyurCyqajq8eFhoYGBgYGBQypztNluVyU7Ee8ckB53dy+qczWutRLx3VHyAI32e5zkie317++T8h98xov7rrwvqD36yXpwwO8uZ/crQNQwAAFyFlRnqKwMSXozx48x1D5uslsAOjZdgqzpabqE0FRE16w/VaKOC+0TpfLIW5u6cEyUQkdRUoTd5R2oqfyZeIZzT2fyczXVKIuL4tt3SFf7t7pPTjbhjWNWTq7/Vb2DXrR7k09WvozU8PQMAgKtwiaGRo41HQrfuyThWnxKhqywu/Mra/ma22tWPPLepoL722DdPPbDO65Z7hiSOWzC68NlHV+2rNNUc+/65celXvpX/p93Mztl88PkCKx/a/j65wFF3ZBW/uOBTmnjHQO9OFv7C8PQMAAAuo1KHfDI05JPTf/5fbIe20ibddX3F3y8N+d0QmHnrm+v/McJX4G7++MsT8+ZfHTW7Rogcceeb65/OVFN+RzengvOsJkS0v0++z+g7hnE/5N14+yVdmpLrXAjPAADgYTht6u0rlj2zqvUyRchli77KXdRmvb4LD1YvdHxUnv5sOu/mrdYkdeYreSccHy+8TyIizss/wD/h1hn9NU4oV2uo3AYAALgYrKW2ZPdHL2wJmjazn9rZO8fTMwAAwMVo3DY/65pf0x765IF+zp8YCuH5NGb74UTegrLGWhKSg+M+TQyK485ZgroGAABX8xu/vna8yzZvzfeK1ZUXntGxCxBwTqmqyb+92vvDoUMrh6fPbC68rdxSds4SF8z3BgAAvRKenh2kIoPZLygmS0EcaW4K1zymNx70OWuJqS4yOMTVGQUA8DiSJFkslq7sQf7pxl0O4dmBi/ZT152s2RmtHcWZPy9rrLcH+Pqq60paL9EZGYV46lxqAACuwXFcS0tLbm5uF/ej0Ti7b7R768nhmdkNU3Yd/dLW6p5LEXCtSpgSo3y3sCbXZje3Hp1G2ecfoY3z9uwxKbwn6jT+NiEyJGmFOa/VEl55ThIAAHBhkZGRAQEBXd+Pl5fzu1+5sx4anpntp5ITL1VUbxYVgd7h/8mMHcEZbttxaC0zbrBo8wtsMxJCbHll+3lhbPLgzaH8vuLDj1DYLZG+f+vLc8QK9Ae+sWl0jMuKTjuc8MeSIDw6AwB0kiAIfn5OnCqit+ipXcP4UB/d7KjgSBK1gX2yFNTcZDigUClVftFkLdP6FZQ2jo/2C1Ip91c3Vjfo5xuD3g6oHZtduMnKbFbDy3prilRyyc69Udt2xuWU7Wo2vKy3DVKUX7p9d/C23Wk5JT/ZOjQqLAAAwMXpoeGZE/oFBk3u4xvGCw11NTutzR8V1ocqxWZO4U0SZ60pD0+Yr+YFTiBL44eFhlHxoZf4R68Ibbl7187Q7BO1QdrDLQFfD8vaHONtqisamV1UHxJwtIZ7YtCQ6hGZr3tVTssz1Lu6iAAA0IP10MrtUzgV7/1wYOPdu8sKJfW0cI2/gbMxqYkLeztYpagjImKi4WNF+K++AnHC2Pj++ngiogZz/ZZQnwyFUoxJerXx0Mo+/d5UnZzFIq9Xc0TKUcG+XIG5lul0qOsGAIDu0bPDMxFRckTf55tzPw3r92TL4R8sSslMYkvJkN16JtmNEnEcnxqXGt420PpqdZOI5elzsvJNZr+4/WFeEXzSd32IiCSb6bUiQ3CfqCjEZgAA6DY9tHL7NIk1P7g/73mTerqm6RW97epQbahCm6Lw/cfAzONJvr68oBN8H9YpzxdquaSoAcbRWWu05dfkm5qIiIn7ygtG7Dn2v4CkjTHeTh9eFQAA4IweHp55TnOPn/mgzTjn4ImGmPS3/XmO81qUoF6Ze2BwodkiKJk6cNDZNQjSIX3eQ7U2kYh4ryuCtQ2NzQbJ8vmRfeMrhEczB/2cEBjdw782AABwsZ5cuc2rQraPCCGip/9Y5u1YMjUoxm63/8lL7pxOYV19ovL2gKiBnGVDRVNwQCxXV/SYJXJbRnhfBGYAAOh+PTk8XywuIiTxNdOxa3eWmolPCIpeG6s5WdBQYqxN+rXQsYbCLzE/MywWzc8AANA9EJ7Ph1dPT86YntxqSfIQlvynqwMAADiXbHW1rPnYyllDIzWcOnzwbctzm/5kXA9LzlMZQ18vsMmVLQAAADckV3hu3L7wqnv2jF5+oCx35fijD1214GfjWQHaXp294aNnZtyw5GCzTHkCAABwUzKF56Z9H65rGP/iExOSw/uOe+zlG8VvP8huartKy8n/bfilkAvzR4suAAD0dvK0PYv1R3NNkbek+HBERNrk0bHmdw9V28f6tEreZ/DCZatY7drRG5a03bioqGjt2rWOz1qtdtiwYbLkGQAAwGXkCc9Si7GZ8w7UCkREJHgHaslc3yx1bOPjx48/9thjjs9jxozJyMgwmUxdzZAkSZJks8naxi1JEhHxvKzvZtntdsdkq3ImKkkSx3EcJ2tFiNVqdaQrZ6KuKmnXT4HOkiRJ5p8uuaKkjDHGGEp6ATJfNnuz7gvPov6jsWmzf20kvs9NG7eO0zBzvVkk4olEc72ZNH7qDv4uxo0bx9iphurjx48bDIauz01ms9n+/L3n7mK324lIoZC1t3xzc7MgCCqVSs5EHfcEgiDImWhDQ4O3t7fMF1abzSYIgsyJGo1GmafnY4zZ7XaFQiHzjYj8JZUkSRTF3lNSpbLTs9hfxCZwcbrvsiJEzfqlgTHGxOp146NT+/uV7S40ExFRS+FOvSa1fzBe6gIAADgvme76vTPvmuz936ff211nMez/cPE6buLcIT4kVu9a99mGIw2YPBkAAKA1uSrlfEa8uvmtlC8nRflE/HVV+Eubl17uz5Elb8W9MxZtqrLLlAkAAADPIFsFM6dJnbVy76yVrZdpRyyvats/jAu6eWvTzXLlCQAAwD1hhgcAAAC3g/AMAADgdhCeAQAA3A7CMwAAgNtBeAZwByyvNDfk96pyRkRSUVXB8B27ArbtvaygvgLvHQL0SgjPAK7X1KCfWmisJSIie3Pl1DzzLZcMqRuWMrIub3a1rYPD3wJAT4LwDOBikt3w2HHjhHhdMBERVRur833CZ3jzvMJnbqTXnqrGRhdnEABcAOEZwKWY9cvjRScjkx7U8hwRkVTdbPfWeGmJiDidWkUWy9lzowNAL4BxrwFciBWU5y3hY38M9VIa/lh61mwMiM4AvRDCM4ALiQdrGvNMeak1xCS7Qarrv7dxVaSiqcHaTKQlZrRYSeXlL+vkSQDgFhCeAVxIccMlw5qJiKih/mhyUeDvmSF9WsoTiyu+agmco2r+rMw6JNrH18WZBAAXQHgGcC9KTejqvuZpB7KfZ3xCSN/Pg5XoIQLQCyE8A7gFX11quc7xkY8PSdwR4trsAICL4b4cAADA7SA8AxAxyxd5OXHbdwVs3dXvUFm2SMRsPxQfTtu+O2R79qi82mKMDAIA8kJ4BiBDfdH9xoCvhg2rGzHgPlvJnPKWspr826u9Pxw6tHJ4+szmwtvKLXZXZxIAehWEZwAS1KHLksMyBLIz8uJ5b54VG8x+QX2yFMTxmpvCNYerTHWuziQA9CroGgZAvlrdJGJ5+pysfJPZL25/mFpXra47WbMzWjuKM39e1lhv1xkZheD9YwCQC8IzgAOXFDXAGGH56njONfm+h5KSVjTlzduzx6TwnqjT+Nt4pdMSkg4V7+9f3PzHAmXIL8OTRgtOSwAAegCEZwDpkL7gQ03cq0FKgfe6IljbcKK5TtRkRacdTuA5YgX6A9/YNEFOe3Tm+8UNYnGOz2J28eGFfMQQxGYAaAttz+CBmH1XydH+23cHb9udllPyk40Rs20tK0rZvku7dVf/w2W/i53aHadTWFefqMwRiSTLhoqm4AAfH3PJiOzCTVZmsxpe1tvGhfv6dEM5zA36+cag96O8Nd2wcwDwaHh6Bs/T0qifUULPDBoy1cu+Ke/AtDxipVbcAAAccklEQVSffVH182qFNwYNmeRlW3Uo545S3d4Yjaqj++MiQhJfMx27dmepmfiEoOi1sd46PnpF6LGZu3aaFZrxsenLdYLz251Zy8pCw6j4/sm4SQaAcyA8g+cxWWwJoZHXqzki5ahgX67AXMcJWiIbI4kxG3HePNe5aMqrpydnTE9uvUg5Nr6/Pt6p+W6rwahfSuFbfFGvDQDngfAMHsZgKp1XZNjVUpthjv6sr++mIkOgr+rxozWlNuvUPbuURHbf2NwItfN6cnUPZtusN6ZExoajNzgAnA+q1cCTSLbauw5V9U3KrB4xYJb15OV7j27xC4urM0SH+AZqAh8PUiXH9vu3T+WNBaYGV2f1wiSbcZlJPdNfiegMAOfleU/PjDHGujo/PTvNKVnqbNIyJ9eTSlpvqNiqjnjb177m2JG3uNC3MqImWfL6N4TPa9H/6B+7KD7+XlL6mf0W5hlKRN80WW4+L+7rNZiqD6gCBgoX+SXJ/yuSP9HWScucHEoK7sDDwjNjTJIku72rAyyKouiU/VwEmROVJEn+ROn0kXL6XvWmFqKGR7KL1rVQSqCir4KVVbcQNXxqsOe35A+2RCxLDGqoMIrauBDJbpdloGxJki6ipL7+fUsziMSLOTCu+umKYuc6xHcdStrdLiLRbjiv4fw8LDxzHMfzvELR1Ww7nni6vp9OcZzzgiBrVyCbzSYIgvwldRwpZ+9YkjhWZban6AS72XqopmRsTQkREae4dHDGzaXHH6gsvXJvRUqfyLVJQUGylNhut/M83w0lvRCnnAKdwhgTRVEQBK6TXe66SP6SOm62ek9JLyJRmX/tvZmHhWci4jiu62cOd5pTstTZpGVOrgeVlA/0UoYGhD2Snro4nZqM+WnHVR+F199mjJ3to6GIhCMhFf3y1evSotJlvIC45Ot11QHt8SV1JNerSipnotApuA8CD8KF64LCGio3tkiM2bZWGpmv/8DAM0vsv1WZmK9flDv8qCXz4t3buJ8d/7YPLbXYz52zEgDgz3ne0zP0ZiptxJq4wtv27b1PorCAyDXJ/n2Uvo4l94osPCByTYq/n6szSUTErDliwFej+t1w+gwz1B293xjw32EDBpJ5WU7OnPLA3VFqnH4A8GdwfQDPwqeE9d0Tdp4lDQ0N3t7eLmwXM5hKZx0r+1+LGBQQ/Wk8r+eV//19241mx39yg2L7vpusyxDIbnfMWYlKRQC4EIRnACc49UJ2WuZaP/vaIzmzSv1MtoY8kfdRKlMDI97sGz5SyVGbOSu9cO4BwAW4QzMdgMczGCu2qiMf8lcoePWtqQM3hPlODvGL8Ar9YWi/B1npTXmGeqJTc1aOzlqjLb8m39Tk6jwDgDtDeAboOlbeaCGu8YkD++J37B16rKpEHfpkqGC0Gxfsy72/TqyvK1tefPyhWptIRI45KxubDRgQAgD+HCrYALqO2SSpqsl2xaCMD9X27/Jybs6tlEg7Liz8wZjAmuKDM+oaX6nz4usqbw+IGsg55qyMdd4E0gDQAyE8A3Qdp/NShgaEXq/heVKNCfX3MvJzfRreKitaX1mSoItcl9w0o0Ax36+29ZyVaqelLh0q3t+/uPmPBcqQX4ZG/rRv3zOnO6YNSRq8PRKt3QCeBCcsQNdx4bqgsJLKjS1+t3iJWyuNzDdxkl/jUkvsz/3DMwX75vwK3i9xXkr8oyndkTrfL24Qi3N8FrOLDy/kI4bw1rfavtkFAJ4F5y6AE5zzQnZAP8Hr5Ybj47efaBEUCbrItclyvJBtbtDPNwatGuCttJbreU0k+pYAeCyEZwCnOPeFbM3MlIyZ3fK4/CdYy8pCw6j4/sk8ma3mMptp/t49BTYu4Y83uwDAYyA8A/QQDUb9Ugrf4isQESdop0T4TIsOyeRb/n0s96Y8zZF0nc7VOQSAjkPlF0CPwGyb9caUSF04R0Sk0oQ+Hx+apeQEQTMpMkDV1FiOaQABPArCM0BPINmMy0zqmf6OKmymr8iNP1C2z86I2bZVNfB+7jFTCAB0GE5ZAA/G7MY5e45tFsnYUJVNTTdtOzVHVtzxhkpTyRXbd/pv3/83W9jaROd1TGO2H4oPp23fHbI9e1RebbFExOy7So723747eNvutJySn2xnxltheaW5Ib9XlTMiIoOp9MY9e3Rbd/bNKd1jd1Zu3NGZg0JERFJRVcHwHbsCtu29rKC+gp13HYDzQNszgGditp9KTrxUUb3ZoptCpAtKrxtx5v8cr1cl/DfGW+PsZKtq8m+vUmQp/d8cGHPiSO5tZepHm45OqbCqFaoBIdF3SSen5fk42rmbGvRTC4213iF0zpjkd+p12XFaL2fnzfXaHhQisjdXTs0z3zJwyANeTU/uOzLbN3N9MP3cdh2A88LTM4CH4kN9dLOjQhLPOYkdr1e9H+X82EzM8oXeaLLWrm9hHMcrSNpRsH9SeYugDtswNH1m84n3eW/ObK5lJNkNjx03TojXBRPROWOSb45Uq5yeN7dw9kGpNlbn+4TP8OZ5hc/cSK89VY2Nf37gAFrDDwTAM3FCv8CgyX18Q856YerU61Whyd1ycgvpfmpB0EbwZKrNf9AoSQplXHTqi15VD1Ry1wUr91cYdH0Cosi67mj+equQoXZMnMnKGy1EdZf9titsx96hx6oKpOZndjvq4bdxP28fWmrpIbXdZx8UqbrZ7q3x0hIRcTq1iiwWI/3JgQNoC5XbAD1K69ernI9TXJ6Q/i/p0K1l9XOLNCMDNdsaJGNtvV7FM1PhpTVNLULIsijlukMH7jHYGpmPwhGBmHWbwVplaqnidd8NSRQLc27JZ1m9ZlCzs2+fXJML8Dx4egboQdq+XtUdJIkbHBExUKlbPSTjHX9SK6jZXPmqwXqwxpwa7O3v5RPDszqLaJGIl+pvO1RbYcrvv7ekRaP09w6I5zmOU40J9Vc0mop7xaBmfLBG0dRibSYiYkaLlVRe/nhoho7p+ecHQO/R9vWqbmFpKhl1sKqeyG41vKy3TYhP35MSEKRShIcmvepLWq0miPdaMHh4y/C+w5S6T/sFhfn1zR3Sd150aJzNriDGmG1rpVHScrU24/y9e4K27R1yRP9B8ZFzO34zu3HBkRJP79vcxz84sbHiqxZGUvNnZdYhoT6+rs4SeIpeULUE0GsYG6oPqHSZ3Xlaa3yjPwzOmVBqmpJtjA5N/UVZmnm4oUYUqTx3ABHRocCWxPzMsOi2W6m0Eauj64cWGKbs2hcdEPmvGH59Le8Y1OxfuQfuqtYuGzrkLi/7prwD0/J8jqT57HP0bbb6TO/GoshBqQld3dc87UD284xPCOn7ebASj0TQQQjPAB6MV4VsHxFy5k9dUFpVUDcnySkvj4kaXFV3f5z4UEVDeXzMp5FNk0saTLzmpsSUFRHePkRE5BijTBOQWn4qP3xKSOiAk8rFw1KvFkiUpOF+vIYjIs1lOqWyUZup4ohTjgr25QrMtcwv1Ec3O4rLKzR3c2G6RduDwseHJO4IufA6AOeB8AwAnXMqtEgtUuOxa3eVmolPCE38KCnsko52R2P6itxhVX029Q/PFOzHLVxon+AkniSb6bUiQ3CfqCheUAcGpVnF14o8MjwDOAXCMwBcFF49PTljevJFbMnFhiW1mW0zyaegvOCeojqvsKSNMd5qp2cVwAPJ1g7Cmo+tnDU0UsOpwwfftjy36Zy3C+yVPy6ZlB6k5Dht1PC7Pthvwgj+AB6LV4VsH5F6tfAnS3jNzJSMytGXGkcO2ZcWlJ+3b3yF8GjmoJ8TAqPRNgtARPKF58btC6+6Z8/o5QfKcleOP/rQVQt+NrYJ0FLlt/NuftV053+KjTX7lg7fMf+vD521BgD0RLW1RY9ZIrdlxN2oEfDOEcAZMoXnpn0frmsY/+ITE5LD+4577OUbxW8/yG5qvULj/k9+Uk99/r6RkX5BKTc8tWSU6cf/FljkyRwAuIyUV9dQYixM+vXUIGLK3ytO4MYcQK62Z7H+aK4p8pYUH46ISJs8Otb87qFq+1ifM8l7j3xv307vaC0RkWQ4+L98PvGO8B46Ki8AnMEPTx7CzteAzatCNvf38u+e0c8A3J884VlqMTZz3oFax5kmeAdqyVzf3LpxWfCJTPAhIrFu70ePzLj/m+SXt00Odzzab9269Y477nCslpmZ+cADDzQ2NnYxQ6IoSpIkirIOeSBJEhHxvKxtazabjed5q9UqZ6IuKamjjBwna/2oKIo8z8ucqM1m6/op0CmMMUmSUNLu46qSCkKnb39sNlt35AfO1X3hWdR/NDZt9q+NxPe5aePWcRpmrjeLRDyRaK43k8ZPfdbFmzXk/uvR2x/8gpv49I/H7hkVcjproaGhU6acmngtICBAqVRqNF2dicdut9vtdrVa1i6ijruBizgfuoLjOEEQlEqlnIm6pKSSJKnVapnvCex2O8/z8ifa9VOgUxhjoigKgiBz0JK/pJIkOYJWLympQtHpEHARm8DF6b4vWoia9UvDrFN/NG1d41e2u9BMff2JWgp36jWp/YPbpN1y+PVrx7wd9PTm/PlZAW0udsnJyS+++KLj8/Hjxw0GQ9ev+44bZJnjB2OMZA9ajuAhf0kdtwVyJupIUeZI6biUy5yo/N8tY4wxJn/QcsmviIh6VUkvbkOQgUyXFe/MuyZ7//fp93bXWQz7P1y8jps4d4gPidW71n224UgDI1a/5ckX8ie+9dy1gXXFhYWFhYXFpUZUoQAAQC8l112/z4hXN7+V8uWkKJ+Iv64Kf2nz0sv9ObLkrbh3xqJNVXaynty2r67s4xv6JZ4WP/btfFnbSwEAANyGbK0InCZ11sq9s1a2XqYdsbzqVP+wjBcK2Qty5QUAAMC9YYQeAAAAt4M+eAAAnk46VLy/f3HzHwuUIb8Mi7Po8xaUNdaSkBwc92liUBwexzwKwjMAgKfj+8UNYnGOz2J28eGFfERcff7wau8vhqaP4Js/yM29rdzn50gvXPE9CO6mAAB6DnODfr4x6P0oTbnB7BfUJ0tBHK+5KVxzuMpU5+q8QacgPAMA9BSsZWWhYVR8aDLPRfup62prdtqYaG/6vKyx3m7FLEOeBVUdAAA9RINRv5TCt/gKRBQRkrSiKW/enj0mhfdEncbfxss6diB0GcIzAECPwGyb9caUyNhwjohIkris6LTDCTxHrEB/4BubJgjjfXkUVG4DAPQEks24zKSe6a90RGFLU8mI7MJNVmazGl7W28aF+/q4OIPQOXh6BgDoCYwN1QdUuszTF3WNb/SK0GMzd+00KzTjY9OX6wQ8PHsWhGcAgJ5AF5RWFdTqb045Nr6/Pt5l+YEuQuU2AACA20F4BgAAcDsIzwAAAG4H4RkAAMDtIDwDAAC4HYRnAAD3wyxf5OXEbd8VsHVXv0Nl2SIRSUVVBcN37ArYtveygvoKjNDZ0yE8AwC4HUN90f3GgK+GDasbMeA+W8mc8paW5sqpeeZbLhlSNyxlZF3e7Gqb5OpMQrdCeAYAcDuCOnRZcliGQHZGXjzvzXPVxup8n/AZ3jyv8Jkb6bWnqrHR1ZmEboVhSQAA3I6vVjeJWJ4+JyvfZPaL2x+mrD9h99Z4aYmIOJ1aRRaLkZEfRgLrufD0DADgnrikqAHG0VlrtOXX5Juaic6KxWh97tkQngEA3I10SJ/3UK1NJCLe64pgbUOjRaVWNLVYm4mImNFiJZWXPx6dezSEZwAAd8PpFNbVJypzRCLJsqGiKTjAp29AcGJjxVctjKTmz8qsQ0J9fF2dS+hWaHsGAHA3XERI4mumY9fuLDUTnxAUvTbW21fQrO5rnnYg+3nGJ4T0/TxYiaerng3hGQDA/fDq6ckZ05PbLIoPSdwR4qoMgdxw+wUAAOB2EJ4BAADcjodVbjPGJEkSRbGL+5EkySn76RTGGBHJnKgkSRzHyZwoETHG5P96RVF0fMlykiRJ5kTl/24dJEnuUapc8isiIlEUOU7WXtEuLOnFbQgy8LDw7ND13wc7zSn56WzSMicnf0ld9cX2qmMqZ4pn0pU/RZf8dHtDSc+kK8MmcHE8LDxzHMfzvELR1Ww7Toau76dT7HY7EcmcqCAIgiDIX1KO4wRBkDNRxw+D52Vtr7HZbDzPy5yoU06BTmGM2e12QRBkfqaUv6SOSjWFQtF7StrZDWX+tfdm+KIBAADcDsIzAACA20F4BgAAcDsIzwAAAG4H4RkAAMDtIDwDAAC4HYRnAAAAt4PwDAAA4HY8bFgSAADoHMm8eO++Z8yOP7ghSYO3R/BbTxyfU2oqY3xCUPQnKRGDZB1DCDoE4RkAoEdj1hwx4KtR/W44fb1vNhXeWaF4ZeCgGzXSqkM5d5Tq9sZoVC7NI5wLldsAAD2Z3das5zWRrS72HC9oidkYSYzZiPPm5R3CFDoGT88AAD2Z1Wous5nm791TYOMSAiPe7Bs+0idqRfD+Edl77ySy+cbmRqiVrs4knAvhGQCgJ+ME7ZQIn2nRIZl8y7+P5d6Up9kaUjXNEPj90Mir1OybvNwbC/z2JPn5ujqfcBZUbgMA9GQqTejz8aFZSk4QNJMiA1RNDXtqGzSBwSOUHMd7XR3mZzYY9XLP5Q3tQ3gGAOjBmL4iN/5A2T47I2bbVtXA+/llBWjr6mqy7UTM+kulSfLxjUAocD+o3AYA6MG42LCklxuOj99+okVQJOgi1yYHJAvaj5ry5uz7vZbxEQERa5MD/F2dSzgXwjMAQI/Ga2amZMxMab1INT4u7VC0qFSiT5j7Qo0GAACA20F4BgAAcDsIzwAAAG4H4RkAAMDtIDwDAAC4HYRnAAAAt4PwDAAA4HYQngEAANwOwjMAAIDb8bxRw0pKSgRB6OJORFGUJEnmEXMkSSIinpf1lshms3Ecp1DIeqBdUtKWlhYvLy9O3olrRVHkeV7mRJubmzUajZwpMsYkSUJJu4+rSnoR19La2truyA+cy/PCc05OTk5OThd3sm3bNqPROGHCBKdkyZ1t2rTJz89v5MiRrs5It1uzZk16evqAAQNcnZHu1dLS8sUXX4wePTo2NtbVeelelZWVmzdvvu666wICAlydl+6Vl5e3c+fO6dOny3xHe9HS0tJcnYVegWOMuToPLnD77bcfPXp0165drs5Itxs+fHhycvInn3zi6ox0O51O98gjj/z97393dUa6V2VlZVhY2Nq1a6dMmeLqvHSvX3755bLLLjt48GCPv+Vavnz53LlzLRaLSqVydV7AjXjGzRoAAECvgvAMAADgdnpp5fahQ4eampqGDh3q6ox0uz179mi12n79+rk6I93u559/jo2NjY+Pd3VGupfVav31118HDBgQGhrq6rx0r/r6+uzs7OHDh/v4+Lg6L92rtLT0yJEjY8eO9ZS2Z5BHLw3PAAAA7gw3awAAAG6nl4Rn1nxs5ayhkRpOHT74tuW5TefUGFgK1z4wJtaH4wRdynWLN1fYXZFLZ2i3pPbKH5dMSg9Scpw2avhdH+w3Sa7IphO0W1IHS85TGUNfL7DJmzknabeMHfwS3FxvOJQOvef0BGdgvUHDb/dGq/s/suFYWd53jw/Whs36ySC1/n9b4bsjvKNnrTlSayrf8dpYv4BJX1eLrspsl7RXUrFi3SSd3+Uv/6Y31hz96oF0VdisLW3X8BTtlZQxW9Xe9SsWT0kk6v9avtU1ueyadsvY/pfgCXrDoXToPacnOEOvCM+Nv94REjBpQ53EGGOmLbcFB03d0tDq/6Wq1X/RJj97yMIYY8zwn3E+sQuzm12R065qr6TM+N31fuFztzc5/qr9cqw25hGPLGq7JWWsYe8rc2fOvHmkP+eh1/R2y9iBL8ED9IZD6dB7Tk9wit5QuS3WH801RY5M8eGIiLTJo2PNhw9Vt6q+5vpM+bEu5/E0FUnWutz1a3K1WaNiPHF8gHZLSt4j39u388UsLRGRZDj4v3w+MSPcA4vafkmJfAYvXLZq5XsLBsg6VqLztFvGjnwJ7q83HEqH3nN6gnN43qCenSe1GJs570CtY3BZwTtQS+b65tZtOpyg8hLIcvDJSzKeO04+497ddVWQJ964tF9SwScywYeIxLq9Hz0y4/5vkl/eNjncA4vafkk9X7tl7BlfQs8oRUf0ntMTnKOnHnpR/9EYX47jOCF48ha7v4aZ682i43/M9WbS+KnPLbnXJUuOieayrU+2LBp7709GD+ll0+mSsobcT+4Z2nf8+3Tvj8c2LUj3mAeSizmmnoxXt1PGdlfwCD2jFB3RoZJ67OkJztcTzwIiIiFq1i8NjDEmVq8bH53a369sd6GZiIhaCnfqNan9g1vVG1iOvnPblOf3NRMRrwkfcdvMFOPefZ5SSdipkhK1HH792jFPVt6+OX/3x/ePCvGk2pNOltTjCbp2ytjuCh6hZ5SiIzpQUg8+PaEbuLLhWzYNv90b7TP8hV21LfX73hzrH37nFoPE7FU7v/h0/WGTxKTaDbcE+Y99ZaveZK479s1D/TTxD+5scnWmL0p7Ja3bcGNgxJ1fHyo4rUhv8MyuNu2U9DSpZs0oraf2J2q3jOddweP0hkPp0HtOT3CG3hGemWQ+suL2weEahSYsc/qynEaJMda0bU7w6Y6g9uqfX7ghPVAgIt+4MfM/OdLkgVc5xlh7JW3Zv+jsMS+Tnz1scXWmL0p7x/TUWh59TW+3jOdbwfP0hkPp0HtOT3ACDOoJAADgdnpq2zMAAIAHQ3gGAABwOwjPAAAAbgfhGQAAwO0gPAMAALgdhGcAAAC3g/AM0EXmnfeEcW1ow/v/9dEvjrWZzlcy5Xy+aPLQGF+e43j/qAHjFny0t/Y8Q9OZd94XG3PPTrNs2QcAt4RR4wCcgc944I1709VEJDVXHd68YukrNw8tWHd87U2hAhHZK/5z38iJywtDR06d/cyQeFVNzqaPl84e8t3h3/a8MtKfO7MX1nTo47+vPGmd6bJyAIC7cPW4KACermnHvFDymfKj6Y9FYsXa632Ihn2otzPG7GWrr/Mhr0uf2Vornlmj7qf7Y4ni//a7Yz5fyfDror8OjHLMHhg6b4dnDioLAE6Dym0A5+P7XHptKlHpoQobkTV/5ZL1jZcsWbloVOCZE47XjX702WuiW3b874SViIhTBPUfO3neU0/PHaJ2Xb4BwG2gchugG1hKc8qJ/EJ9BRIrt359mPq/dmO8ss0qQtTMDSf/qMX2Tp+2MJ2oeW/1h++flDu7AOB2EJ4BnEE011SUlzcSkdRcfeT71+9dWsoNfnBSnJKsFbllpMnqF6JsdycAAKchPAM4Q/PGW5MjWi9ImLbis/tSVERmu1UkXiG4KmcA4JEQngGcQTH82c+fyNQQEXEKv6j0gf1i/Bxnl7JPYh9qKi4wiFf6tonRUv2uD5d+L105/+4RgegEAgBtITwDOIM6esT4a6/wPc//KCNHXxFJb6/cqJ89L7bVCccMvy554OktVw5aME+2XAKAx8BNO0A302Tc+3AW7Vx45xu7DdLphawp+41FG1t8/nrXcH9XZg4A3BSengG6myr5vs+X/Tx87qPDUr6dOvWqrASt4eiWT/75/Qm/CR+8OqEP1/4eAKDXQXgG6H5eSXd/eTh9+TPP/XPdPxevtvJ+kamD57z7+XN3jwjBKQgA58MxxtpfCwAAAGSEtmcAAAC3g/AMAADgdhCeAQAA3A7CMwAAgNtBeAYAAHA7CM8AAABuB+EZAADA7SA8AwAAuB2EZwAAALeD8AwAAOB2/h/cTzEonPouzAAAAABJRU5ErkJggg==)
Видимо, выделенная черта, не связанна с географией.
set.seed(11)
map.feature(languages = "Polish",
features = miasta$core,
popup = miasta$town.names,
latitude = miasta$lat,
longitude = miasta$long)
Видимо, выделенная черта, не связанна с количеством населения.
miasta %>%
ggplot(aes(core, ludnosc_.31.12.2014., label = town.names))+
geom_violin(fill = "lightblue")+
geom_jitter(width = 0.3)+
theme_bw()+
ylab("количество человек (31.12.2014)")
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)
---
title: "Лингвистические пакеты в R: падежные предпочтения польских городов"
author: "Г. Мороз, 21 октября 2016, [https://goo.gl/Wh0WUq](https://goo.gl/Wh0WUq)"
output:
  html_notebook: default
  github_document: default
---

### 0. Введение
[Национальный корпус польского языка](http://nkjp.pl/poliqarp/) --- вещь достаточно неудобная. Настройки в одном месте, выдача в другом, скачать можно только в html (хотя обещают, что можно и в Excel). Как было славно, если бы можно было сразу собирать в R выдачу и ее там анализировать?

### 1. API для польского корпуса
Для того, чтобы решить данную проблему я написал API (в этом мне немного помог **Даня Алексеевский**, спасибо!). Так что я написал на R достаточно неуклюжую, наверное, [функцию `pl.corpus`](https://github.com/agricolamz/lingcorpora/blob/master/pl.corpus.R).

```{r pl.corpus --- API для польского корпуса, eval=FALSE, collapse=FALSE, include=FALSE}
pl.corpus <- function(x, tag = F, n.results = 100, corpus = "nkjp300"){
  library(xml2)
  library(rvest)
  library(httr)
  
  if(length(x) != 1){
    warning('x must be of length 1. If you want a dataframe with different queries try \n do.call("rbind.data.frame", sapply(x, pl.corpus, simplify = F))')
  }
  # show tags?
  if(tag == T){
    tag.variable <- "slt"
  } else {tag.variable <- "s"}
  
  # set nkjp.pl settings
  settings <- httr::POST(url = "http://nkjp.pl/poliqarp/settings/",
                         body = list(
                           random_sample = "0",
                           random_sample_size = "50",
                           sort_column = "rm",
                           sort_type = "afronte",
                           sort_direction = "asc",
                           show_in_match = tag.variable,
                           show_in_context = tag.variable,
                           left_context_width = "10",
                           right_context_width = "10",
                           wide_context_width = "50",
                           results_per_page = as.character(n.results),
                           `next` = "/poliqarp/"))
  
  # get request data
  request <- httr::POST(url = "http://nkjp.pl/poliqarp/query/",
                        body = list(query = x, corpus = corpus),
                        set_cookies(domain = "#HttpOnly_nkjp.pl",
                                    flag = "FALSE",
                                    path = "/",
                                    secure = "FALSE",
                                    expiration = "<NA>",
                                    name = "sessionid",
                                    value = as.character(settings$cookies[7]))) # cookies from settings
  
  # get data
  my.url <- httr::GET(url = "http://nkjp.pl/poliqarp/nkjp300/query/",
                      set_cookies(domain = "#HttpOnly_nkjp.pl",
                                  flag = "FALSE",
                                  path = "/",
                                  secure = "FALSE",
                                  expiration = "<NA>",
                                  name = "sessionid",
                                  value = as.character(request$cookies[7]))) # cookies from request
  
  # check for errors
  xml2::read_html(my.url) %>% 
    html_nodes(".errorlist > li:nth-child(1)") %>%
    html_text() -> 
    errorlist
  
  if(length(errorlist) > 0){
    warning(errorlist)
  }
  
  # check for no result
  xml2::read_html(my.url) %>% 
    html_nodes(".query-results > p:nth-child(2)") %>%
    html_text() -> 
    number.results
  if(length(number.results) > 1){
    if(grepl(pattern = "Found 0 results", number.results)){
      warning(paste('No results were returned by the query "', x, '"', sep = ""))
    }}
  
  # get left part
  xml2::read_html(my.url) %>% 
    html_nodes("td:nth-child(2)") %>%
    html_text() -> 
    left.part
  left.part <- gsub("\\s+", " ", left.part) # clean data
  
  # get query word
  xml2::read_html(my.url) %>% 
    html_nodes("td:nth-child(3)") %>%
    html_text() -> 
    center.part
  center.part <- gsub("\\s+", " ", center.part) # clean data
  
  # get right part
  xml2::read_html(my.url) %>% 
    html_nodes("td:nth-child(4)") %>%
    html_text() -> 
    right.part
  right.part <- gsub("\\s+", " ", right.part) # clean data
  
  results <- data.frame(left.part, center.part, right.part, stringsAsFactors = F)
  return(results)}
```

Чтобы не заставлять читателя разбираться в коде, поясню, что в результате в вашем окружении появляется функция `pl.corpus` со следующими аргументами:

* `x` --- запрос (обязательный аргумент);
* `tag` --- логический вектор, отвечающий за то, нужны ли в выдачи морфологические теги или нет;
* `n.results` --- переменная отвечающая за максимальное количество примеров в выдаче
* `corpus` --- вектор, определяющий подкорпус, в котором следует искать (возможные значения: `"nkjp300"`, `"nkjp1800"`, `"nkjp1M"`, `"ipi250"`, `"ipi030"`, `"frequency-dictionary"`)

Приведу пример работы функции:
```{r использование pl.corpus 1, echo=TRUE, message=FALSE, warning=FALSE}
head(pl.corpus("witam"))
```

```{r использование pl.corpus 2, echo=TRUE, message=FALSE, warning=FALSE}
head(pl.corpus("An*a", tag = T))
```
```{r использование pl.corpus 3, echo=TRUE, message=FALSE, warning=FALSE}
head(pl.corpus("[base = 'witać']"))
```
Как видно из примеров, функция понимает самые разные запросы:

* простые
* регулярными выражениями
* Corpus Query Language CQL

### 2. Данные
Данные о польских городах я взял из [Википедии](https://pl.wikipedia.org/wiki/Miasta_w_Polsce_(statystyki)). Были выбраны все города с населением больше 35500.

```{r, echo=TRUE}
library(lingtypology)
miasta <- read.csv("https://goo.gl/1zZgOa")
map.feature(languages = "Polish",
            popup = miasta$town.names,
            latitude = miasta$lat,
            longitude = miasta$long,
            control = F)
```

Как видно из кода, для создания данной карты требуется написанный мной пакет [`lingtypology`](https://github.com/agricolamz/lingtypology/wiki). Данный пакет позволяет рисовать карты на основе названий языков, вставляет ссылки на данные языки в базе данных [Glottolog](http://glottolog.org/).

Для дальнейшего исследования следует построить список запросов, которые бы можно было вставить в функцию `pl.corpus`. Здесь таилось множество проблем, связанных с особенностью корпуса:

* в самом простом случае достаточно было лишь написать название города
    + `[base = 'Kraków']`
* иногда приходилось менять большую букву на маленькую
    + `[base = 'warszawa']`
* все города, содержащие дефис, следовало разделить на два отдельных слова
    + `[base = 'Bielsko'] [base = 'Biała']`
* некоторые города либо целиком, либо частично совпадали с какими-то польскими словами и так хранились в польском корпусе, в таком случае я требовал написания с большой буквы
    + `[base = 'rudy' & orth = 'Rud.*'] [base = 'Śląsk']`
* несколько городов пришлось выкинуть:
    + из-за совпадений (Chrzanów, Jarosław)
    + из-за ошибки в корпусе `Radomsko [radomsko:adv:pos]`, но `Radomska [radomski:adj:sg:nom:f:pos]` (Knurów, Radomsko)
В результате каждый запрос пришлось проверять, так что результат этой работы записан в базе:

```{r, echo=TRUE}
head(miasta$query)
```

После обработки функцией `pl.corpus` всех запросов получилась [база данных, состоящая из 99129 примеров](https://goo.gl/zu3aTC), полученных по шаблонному запросу:
```{r, echo=TRUE}
head(pl.corpus(miasta$query[42], tag = T, n.results = 1000))
```

### 3. Обработка данных
Для обработки данных я написал две функции `pl.base` и `pl.case`.
```{r, echo=TRUE}
pl.base <- function(x){
  out <- c()
  for(j in seq_along(x)) {
    if(grepl("\\[.*:", x[j])){
      out[j] <- unlist(strsplit(unlist(strsplit(x[j], "\\["))[2], "\\:"))[1]
    } else {
      warning(paste0('No tags were found in the query "', x, '"'))
    }}
  return(out)
}
```


```{r, echo=TRUE}
pl.case <- function(x){
  out <- c()
  for(j in seq_along(x)) {
    if(grepl("\\[.*:", x[j])){
      out[j] <- unlist(strsplit(x[j], "\\:"))[4]
    } else {
      warning(paste0('No tags were found in the query "', x, '"'))
    }}
  return(out)
}
```

Функция `pl.base` позволяет выделять основу:

```{r, echo=TRUE}
pl.base("Wrocławia [Wrocław:subst:sg:gen:m3]")
```

Функция `pl.сase` позволяет выделять падеж:

```{r, echo=TRUE}
pl.case("Wrocławia [Wrocław:subst:sg:gen:m3]")
```

Для дальнейшего анализа понадобиться пакет `data.table`, который позволяет работать с бальшими файлами и пакет `dtplyr`, который позволяет удобно обрабатывать данные. Необработанные данные, которые будут дальше анализироваться можно скачать [здесь](https://goo.gl/M3BT4l).
```{r, echo=TRUE, message=FALSE, warning=FALSE}
library(data.table); library(dtplyr)
df <- fread("moroz2016_polskie_miasta_row_data.csv", header = T)
```

Создадим новый датафрейм с основами и падежом:
```{r, echo=TRUE, message=FALSE, warning=FALSE}
library(tidyverse)
df %>% 
  mutate(base = pl.base(query)) %>% 
  mutate(case = pl.case(query)) %>% 
  select(base, case) %>% 
  group_by(base, case) %>% 
  summarise(number = n()) ->
  base.case
head(base.case)
```

Построим простой график:
```{r}
base.case %>% 
  ggplot(aes(case, number))+
  geom_bar(stat = "identity", position = "dodge", fill = "lightblue")+
  theme_bw()
```

Для дальнейшей работы необходмо соединить изначальную базу (в переменной `miasta`) и новые данные (в переменной `base.case`).

```{r}
base.case %>% 
  spread(case, number) ->
  base.case
head(base.case)
```

Теперь можно присоединить получившуюся таблицу к уже имеющейся, выкинув первый и последний столбец:
```{r}
miasta <- cbind.data.frame(miasta[-52,], base.case[-73,])[,-c(6, 14)]
head(miasta)
```

Надо отметить, что не по всем запросам в корпусе нашлась 1000 примеров, так что абсолютные значения количества падежных форм для каждого города сравнивать между собой несколько бессмысленно. Поэтому заменим все пропущенные значения (`NA`) на 0, посчитаем сумму абсолютных значений в каждой строчке, а потом переведем абсолютные значения количества падежей в доли.

```{r}
miasta[is.na(miasta)] <- 0

for(i in 1:nrow(miasta)){
miasta %>%
    select(6:12) %>%
    slice(i) %>% 
    sum() ->
  miasta$n[i]}

for(j in 1:nrow(miasta)){
  miasta %>%
    select(6:12) %>%
    slice(j) %>% 
    prop.table() ->
    miasta[j,6:12]}
head(miasta)
```
```{r, include=FALSE}
rm(i); rm(j)
```

В результате данных операций возникли некоторые неправильные значения `NaN`. Это связано с тем, что некоторые города в корпусе не распознаны должным образом и имеют один единственный тег `ign` (Zawiercie, Chojnice). Избавимся от данных строчек:

```{r}
miasta <- miasta[complete.cases(miasta),]
```

Теперь все данные (в итоге 116 городов) собраны воедино и можно приступать к анализу.

### 4. Анализ данных
Во-первых, конечно, хочется посмотреть, какие значения приимают получившиеся доли:
```{r}
miasta %>%
  gather(case, rate, acc:voc) ->
miasta.for.analysis
miasta.for.analysis_2 <- miasta.for.analysis[,-7]

miasta.for.analysis %>% 
  ggplot(aes(rate, fill = case))+
  geom_histogram(data = miasta.for.analysis_2, fill = "lightgrey", bins = 17)+
  geom_histogram(bins = 17)+
  facet_wrap(~case)+
  theme_bw()
```
Данный график трудно читать, так что я добавлю такое же, но с отлогарифмированными осями:

```{r}
miasta.for.analysis %>% 
  filter(rate > 0) %>% 
  ggplot(aes(rate, fill = case))+
  geom_histogram(data = miasta.for.analysis_2, fill = "lightgrey", bins = 17)+
  geom_histogram(bins = 17)+
  facet_wrap(~case)+
  theme_bw() +
  scale_y_log10()
```

Как следует читать данные графики? Серым цветом обозначена гистограмма^[Существует стандартная проблемма с гистограммой, связанная с трудностью формализовать выбор количества ячеек гистограммы. Существует несколько подходов, здесь я выбрал алгоритм из работы (Freedman, Diaconis 1981), согласно которому для исследуемых данных следует использовать 17 ячеек.] всей выборки долей, без учета падежа. Цветом же показано, какой вклад вносит каждый падеж в создание общей гистограммы. Исследуя данный график можно сделать два наблюдения:

* во-первых, падежи делятся на те, которые чаще имеют маленькую долю (acc, dat, inst, voc), и на те, которые чаще имеют долю в промежутке между 0.2 и 0.6 (gen, nom, loc);
* во-вторых, некоторые города имеют в именительном падеже очень высокую долю близкую к единице (что в свою очередь означает, что они почти не выступают в других падежах).

Первый факт достаточно легко объяснить тем, что в польском латив и элатив маркируется предлогами _do_ и _z_, управляющими родительным падежом, а эссив маркируется предлогом _w_, управляющий местным падежом. В целом есть множество разных значений, которые оказались вне данной сильно упрощенной схемы, однако в первом приближении такое объяснение принять можно.

Второй факт следует рассматреть отдельно. Вот список городов с высокой долей разных падежей:

* **gen:** Ostrów Wielkopolski, Siedlce
* **nom:** Ruda Śląska, Starogard Gdański, Zielona Góra, Kędzierzyn-Koźle, Tarnowskie Góry

Видимо, Siedlce, действительно представлены так в корпусе, а все остальные названия, видимо, неправильно обрабатывались морфологическим парсером. Избавляемся от них и строим графики заново:

```{r}
miasta %>% 
  gather(case, rate, acc:voc) %>% 
  filter(rate < 1) ->
  miasta.for.analysis
miasta.for.analysis_2 <- miasta.for.analysis[,-7]

miasta.for.analysis %>% 
  ggplot(aes(rate, fill = case))+
  geom_histogram(data = miasta.for.analysis_2, fill = "lightgrey", bins = 17)+
  geom_histogram(bins = 17)+
  facet_wrap(~case)+
  theme_bw()
```

И с отлогарифмированной осью:
```{r}
miasta.for.analysis %>% 
  filter(rate > 0) %>% 
  ggplot(aes(rate, fill = case))+
  geom_histogram(data = miasta.for.analysis_2, fill = "lightgrey", bins = 17)+
  geom_histogram(bins = 17)+
  facet_wrap(~case)+
  theme_bw() +
  scale_y_log10()
```

Может быть какой-то падеж коррелирует с количеством носителей? (Спасибо Ване Левину за этот вопрос).
```{r}
library(PerformanceAnalytics)
miasta %>% 
  select(5:12) %>%
  chart.Correlation(histogram = F, pch = ".")
```

Но все же в моих данных много размерностей, так что нужен способ их уменьшить. Так как данные числовые --- PCA. Давайте посмотрим на биплот (более крупный вариант доступен [здесь](https://goo.gl/BZCx8R)):

```{r}
library(ggfortify)
miasta.for.pca <- miasta[,6:12]
row.names(miasta.for.pca) <- miasta$town.names
autoplot(prcomp(miasta.for.pca),
         shape = F,
         label = T,
         label.size = 2,
         loadings = T,
         loadings.label = T)+
  theme_bw()
```

В догонку к графику, обычно принято показывать, какой вклад вносят компоненты в объяснение изменчивости:

```{r}
summary(prcomp(miasta.for.pca))
```
Как видно из summary, уже первые две компоненты объясняют 92 процента всей изменчивости исходных данных.

Что нам говорит график биплот? Видимо, в наших данных нет четких кластеров, т. е. есть ядро и несколько переферий: с одной стороны видны Tarnowskie Góry и т. п., которые имеют максимальную долю в именительном падеже, с другой стороны Ostrów Wielkopolski, который имеет максимальную долю в родительном падеже, с третьей стороны Bydgoszcz, имеющий максимум в местном падеже. Переферия городов, имеющих много форм именительного и родительного падежа, но совсем мало местного падежа, кажется чуть больше.

Создадим переменную, отличающую города по степени переферичности.
```{r}
miasta$core <- NA
miasta$core[-c(8, 42, 33, 94, 4, 13,22, 2, 46, 97, 31, 38, 39, 99, 77, 29, 56, 7, 73, 27, 64, 51, 63, 16, 20, 45, 112, 90, 3, 18, 114, 88, 72)] <- "core"
miasta$core[c(8, 42, 33, 94, 4, 13,22,2, 46, 97,31, 39, 38, 99, 77, 29, 56, 7, 73, 27, 64, 51, 63, 16, 20, 45, 112, 90, 3, 18, 114, 88, 72)] <- "periphery"
autoplot(prcomp(miasta.for.pca), data = miasta, colour = 'core',  shape = FALSE, label.size = 3)+
  theme_bw()
```

Видимо, выделенная черта, не связанна с географией.
```{r}
set.seed(11)
map.feature(languages = "Polish",
            features = miasta$core,
            popup = miasta$town.names,
            latitude = miasta$lat,
            longitude = miasta$long)
```

Видимо, выделенная черта, не связанна с количеством населения.

```{r}
miasta %>%
  ggplot(aes(core, ludnosc_.31.12.2014., label = town.names))+
  geom_violin(fill = "lightblue")+
  geom_jitter(width = 0.3)+
  theme_bw()+
  ylab("количество человек (31.12.2014)")
```

