{
"cells": [
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"cell_type": "markdown",
"metadata": {},
"source": [
"# 800100715151 Astronomide Veritabanları #\n",
"\n",
"## Ders - 06 Veri Görselleştirmenin Temelleri ##"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Doç. Dr. Özgür Baştürk \n",
"Ankara Üniversitesi, Astronomi ve Uzay Bilimleri Bölümü \n",
"obasturk at ankara.edu.tr \n",
"http://ozgur.astrotux.org"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Veri Görselleştirmenin Temelleri #\n",
"\n",
"* [Veri Görselleştirme Neden Önemlidir?](#Veri-Görselleştirme-Neden-Önemlidir?)\n",
"* [Veri Görselleştirme Paketleri](#Veri-Görselleştirme-Paketleri)\n",
" * [Matplotlib Kütüphanesi](#Matplotlib-Kütüphanesi)\n",
" * [Arkayüz (Backend) Katmanı](#Arkayüz-(Backend)-Katmanı)\n",
" * [Grafik Nesneleri (Artist) Katmanı](#Grafik-Nesneleri-(Artist)-Katmanı)\n",
" * [Kodlama (Scripting) Katmanı](#Kodlama-(Scripting)-Katmanı)\n",
" * [Matplotlib ve Jupyter Defterleri](#Matplotlib-ve-Jupyter-Defterleri)\n",
"* [Veri Görselleştirme Türleri](#Veri-Görselleştirme-Türleri)\n",
" * [Eğri Grafikleri](#Eğri-Grafikleri)\n",
" * [Örnek: Keşif Tekniklerinin Performanslarının Zamanla Değişimi](#Örnek:-Keşif-Tekniklerinin-Performanslarının-Zamanla-Değişimi)\n",
" * [Alan Grafikleri](#Alan-Grafikleri)\n",
" * [Histogramlar](#Histogramlar)\n",
" * [Çubuk (Sütun) Grafikleri](#Çubuk-(Sütun)-Grafikleri)\n",
" * [Örnek: Keşif Yöntemlerinin Birbirleri İle Karşılaştırılması](#Örnek:-Keşif-Yöntemlerinin-Birbirleri-İle-Karşılaştırılması)\n",
" * [Pasta Grafikleri](#Pasta-Grafikleri)\n",
" * [Kutu Diyagramları](#Kutu-Diyagramları)\n",
" * [Keman Diyagramları](#Keman-Diyagramları)\n",
" * [Saçılma Grafikleri](#Saçılma-Grafikleri)\n",
" * [Balon Diyagramları](#Balon-Diyagramları)\n",
" * [Zamana Bağlı Değişimlerin Görselleştirilmesi](#Zamana-Bağlı-Değişimlerin-Görselleştirilmesi)\n",
" * [Örnek: Bir Geçiş Işık Eğrisi ve Modelinin Grafiği](#Örnek:-Bir-Geçiş-Işık-Eğrisi-ve-Modelinin-Grafiği)\n",
" * [Örnek: Tayfsal Verinin Grafiği](#Örnek:-Tayfsal-Verinin-Grafiği)\n",
"* [Kaynaklar](#Kaynaklar)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Veri Görselleştirme Neden Önemlidir? #\n",
"\n",
"Bir veri setini görselleştirme, özellikle büyük veri setlerinde i) bir bakışta farkedilemeyen detayların farkedilmesine, ii) parametreler arası ilişkilerin kurulabilmesine, iii) konuya ilişkin sorulara çabuk cevap verilebilmesine, iv) bazı konuların daha derin ve iyi anlaşılabilmesine ve v) neden-sonuç ilişkilerinin kurulabilmesine olanak sağlar.\n",
"\n",
"Tablolara bakarken, araştırıcının her şeyden önce en çok ilgisini çeken öne çıkan rakamlardır. Ancak bazen insan, ilgisini çekenlere odaklanırken önemli bazı detayları gözden kaçırabilir (algıda seçicilik). İyi bir örnek için [bkz.](https://www.youtube.com/watch?v=vJG698U2Mvo)\n",
"\n",
"Altı ülkenin (İspanya, Portekiz, Güney Kore, Çin, Türkiye ve Brezilya) kişi başına düşen gayrisafi milli hasılarının 1980'den bu yana 10 yıllık dönemler için değerleri örneği üzerinden görselleştirmenin nasıl faydalar sağladığı ve ne tür çıkarımlara yol açtığı aşağıda örneklenmeye çalışılmıştır."
]
},
{
"cell_type": "code",
"execution_count": 1,
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"source": [
"%matplotlib inline\n",
"from matplotlib import pyplot as plt\n",
"renkler = ['purple','green','blue','orange','red','yellow']\n",
"# yillara karsilik GSMH degisimini dogrudan cizdirebilmek icin\n",
"# oncelikle vericercevesinin transpozu alinmalidir.\n",
"gsmh.transpose().plot(kind=\"line\",\n",
" color=renkler,\n",
" marker=\"o\")\n",
"plt.grid(True)\n",
"plt.xlabel('Zaman (yıl)')\n",
"plt.ylabel('GSMH (US\\$)')\n",
"plt.legend(loc='upper left')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sosyal bilimci olmamakla birlikte ele alınan tüm ulkelerin 2000 ile 2010 arasında kişi başına düşen milli gelirlerini arttırdıkları, 1980'lerde Türkiye'nin gerisindeki Çin ve Güney Kore'nin Türkiye'yi geçtiği, İspanya ve Portekiz'in Avrupa Birliği üyesi ülke oluşlarını takiben ulusal gelirlerini hızla arttırdıkları ancak 2010'lar sonrası bu artışın yavaşladığı, Brezilaya ile Türkiye'nin benzer bir çizgi izlediği, Güney Kore'nin ise bilime yaptığı yatırımın sürekli bir artışla gelirlerini tüm bu ülkeleri geçecek duruma getirdiği görülmektedir. \n",
"\n",
"Yukarıdaki gibi bir tablodansa bu grafiklere bakarak zamanla değişimi görmek ve başka ülkelerinki ile karşılaştırmak çok daha kolaydır. Bir grafik, bir tablodan veya yukarıdaki gibi bir paragraf yazadan çok daha fazlasını çok kısa daha kısa sürede, özellikle grafik yorumlamak konusunda eğitimli insanların kolayca anlayacağı şekilde anlatır. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Veri görselleştirmenin çok güzel bir örneğini alanın devlerinden Hans Rosling'in [4 dakikada 200 ülkenin 200 yıldaki gelişimi](https://www.youtube.com/watch?v=jbkSRLYSojo) videosunda bulabilirsiniz."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Veri Görselleştirme Paketleri\n",
"\n",
"İstatistiksel Bilgi Veren Görselleştirme Uygulamaları: Dağılım grafikleri (ing. scatter plots) ya da eğri uyumlama gibi uygulamaları destekleyen paketlerdir.\n",
"\n",
"* `matplotlib`: Python'da statik, hareketli ya da interaktif görselleştirmeler oluşturmak için kapsamlı bir kütüphanedir. John D. Hunter tarafından 2003 yılında EKG diyagramlarını görselleştirmek ve Matlab ortamındakine benzer grafikler oluşturmak için yazılmış, pek çok gönüllü programcının katkılarıyla geliştirilerek bugünkü yaygınlığını sağlayan başarımına erişmiştir.\n",
"\n",
"* `seaborn`: `matplotlib` üzerine inşa edilmiştir. Renk paletleri ve çizim estetiği veri setlerindeki özellikle istatistiksel bilgileri sunabilmek üzere geliştirilmiştir.\n",
"\n",
"Grafikle Görselleştirmenin Gramerine Yönelik Uygulamalar: `matplotlib` arayüzünün çok ayrıntılı bulunması durumunda `R` programlama dilinin `ggplot2` görselleştirme paketini temel alan paketler gibi uygulamalar kullanılabilir.\n",
"\n",
"* `ggplot`: `matplotlib` 'a dayanır ve ona benzer bir işlevsellik sağlar ancak farklı ve daha kolay bir arayüz sağlar.\n",
"\n",
"* `altair`: `ggplot` ile karşılaştırıldığında daha da basit bir arayüze sahiptir ve`jupyter` not defterlerine kolayca yerleştirilebilen veya PNG olarak dışa aktarılabilen Javascript tabanlı grafikler oluşturur.\n",
"\n",
"İnteraktif Görselleştirme Uygulamaları:: zoom, pan, veri noktalarını interaktif etiketleme gibi özellikler sağlayan, aynı zamanda bir web sayfasında bağımsız çalışmak için Javascript olarak dışa aktarılabilen grafik uygulamalar sunan paketlerdir.\n",
"\n",
"* `bokeh`: Anaconda paketinin üreticisi Continuum Analytics şirketinin görselleştirme paketidir ve özellikle internette sunmak üzere interaktif görselleştirme ve infografik uygulamaları geliştirmenizi sağlar. Kullanıcı arayüzünden veya seri veri güncellemelerinden ve stream'lerden gelen olaylara yanıt vermeyi sağlayan ayrı bir Python süreci başlatmak için bir da grafik sunucu (bokeh plot server) desteği bulunmaktadır. Bir örnek uygulama için [bkz.](https://ozgur.astrotux.org/ttv/basturk2022a/)\n",
"\n",
"* `plotly`: görselleştirmelerinizi depolayabileceğiniz ve paylaşabileceğiniz bir kütüphane ve bulut hizmetidir (ücretsiz / ücretli hesapları vardır)\n",
"\n",
"İnteraktif Harita Uygulamaları: renkli ve interaktif özelliklerde haritalar yaratmanıza olanak sağlarlar.\n",
"\n",
"* `folium`: Verileri haritaların üstünde görüntülemek için $Leaflet.js$ javascript çizim kütüphanesine bağlı HTML sayfaları oluşturur. \n",
"\n",
"* `plotly`: jupyter not defterlerine gömülü renk kodlu ülke / dünya haritalarını da destekler.\n",
"\n",
"Üç Boyutlu (3D) Görselleştirme Uygulamaları: \n",
"\n",
"* `mplot3d`: `matplotlib` 'in 3-boyutlu görselleştirme uygulamalarına platform sağlayan paketidir."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Matplotlib Kütüphanesi ##\n",
"\n",
"Bu derste `matplotlib` altyapısını kullanan ve `pandas` veriçerçeveleri üzerinde tanımlı `plot` fonksiyonu sıklıkla kullanılacaktır. Ancak grafik parametrelerini tanımlamak ve özellikleri üzerinde daha geniş kontrole sahip olabilmek için kütüphanenin diğer fonksiyonlarından da yararlanılacaktır. Bu nedenle `matplotlib` kütüphanesinin yapısından ve mimarisinden kısaca bahsetmekte fayda vardır. Daha geniş bilgi için `matplotlib` [dokümantasyonun](https://matplotlib.org/stable/index.html) incelenmesi ve gerektiğnde [dış kaynaklara](https://matplotlib.org/stable/users/resources/index.html) başvurulması önerilir. \n",
"\n",
"`matplotlib`, kodlama katmanı (scripting layer), grafik nesnneleri katmanı (artist layer) ve arkayüz katmanı (backend layer) adı verilen üç katmandan oluşmaktadır. \n",
"\n",
"
\n",
" \n",
"
\n",
"\n",
"### Arkayüz (Backend) Katmanı\n",
"\n",
"Arkayüz, bilgisayarda grafik çizimi amaçlı daha düşük düzey, `wxPython` gibi araçlar veya `PostScript` gibi çizim dilleriyle iletişim kurarak arka plandaki işleri yerine getirir. Kütüphanenin temeli olup, en komplike işlerin yapıldığı katmandır. Üç ana bileşenden oluşur\n",
"\n",
"* FigureCanvas — `matplotlib.backend_bases.FigureCanvasBase` Şeklin tuvale (ing. canvas) aktarıldığı nesne ve metotlardan oluşan arabirimidir.\n",
"\n",
"* Renderer —` matplotlib.backend_bases.RendererBase` Çizim ve aktarım (rendering) işlemlerinin yapıldığı nesne ve metotlardan oluşan arabirimdir. `FigureCanvas` 'a şeklin aktarılmasından sorumludur.\n",
"\n",
"* Event — `matplotlib.backend_bases.Event` Klavye ve fare gibi çevre birim elemanlarından gelen girdileri alan ve yorumlayan nesne ve metotlardan oluşan arabirimdir.\n",
"\n",
"Çoğu grafik çiziminde (ve bu ders boyunca) kullanıcının arkayüzle ilgilenmesine hiç gerek olmamaktadır. Ancak `matplotlib` altyapısına dayalı bir grafik çizim uygulaması programlanmak istendiğinde arkayüz hakimiyeti gerekecektir."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Grafik Nesneleri (Artist) Katmanı\n",
"\n",
"Tıpkı bir sanatçının tuval üzerine yaptığı ince ayarlar gibi, kullanıcının şekillerin mümkün olduğunca çok özelliğini kontrol etmesine ve ince ayar yapmasına olanak sağlayan nesne ve metotlardan oluşan katmandır. Bu katman, \"tuval\" (ing. canvas) üzerine çizim yapmak için `Renderer` arabirimini kullanan `Artist` adlı bir ana nesneden oluşur. Birden fazla şekil ya da eksen kullanılırken, her bir alt grafik (subplot) bir `Artist` nesnesine atandığından hangisinin aktif olduğu konusunda bir karışıklık oluşulmasının önüne geçilmiş olunur. Bu ana nesne ve altındaki grafik nesnelerinin yönetimine dayalı olduğu için nesne yönelimli grafik çizimi olarak da adlandırılır. Bir `matplotlib` figürünün üzerindeki başlık (title, sembol, çizgi ve eksen gibi her bir özellik bir nesne ile tanımlanır. \n",
"\n",
"İki tür `Artist` nesnesi vardır. \n",
"\n",
"* Primitive: Line2D, Rectangle, Circle ve Text gibi temel tür nesneler, \n",
"\n",
"* Composite: Axis, Ticks, Figure gibi kompozit nesneler. Bu nesneler temel nesneler ya da diğer kompozit nesnelerin bileşiminden oluşurlar.\n",
"\n",
"Bir üst katman olan kodlama katmanına kıyasla daha fazla özelleştirme yapma olanağı sağlar ve gelişmiş grafikler üretmek üzere grafik nesneleri üzerinde tam kontrole ihtiyaç duyulan durumlar için daha uygundur. Grafiklerin üretileceği bir web uygulaması ya da kullanıcı arayüzü geliştirmek için de sıklıkla başvurulur.\n",
"\n",
"Grafik nesneleri katmanı hakkında daha fazla bilgi için `maplotlib` Artist Tutorial [dokümantasyonunu](https://matplotlib.org/stable/tutorials/intermediate/artists.html) incelemeniz önerilir.\n",
"\n",
"Örnek: $\\mu = 0$, $\\sigma = 1$ ile tanımlanan standart normal dağılımdan rastgele seçilmiş 10000 örnekten oluşan normal dağılım örnekleminin grafik nesneleri katmanı düzeyinde histogramının çizimine bir örnek aşağıdaki kodla verilmiştir."
]
},
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"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Arkayuz (backend) nesnesi tuvale (canvas) sekil cizdirmek uzere \n",
"# Grafik nesneleri katmani nesnesi FigureCanvas import edilir\n",
"# Arkayuzden import edilen FigureCanvasAgg \"anti grain geometry\" adli kutuphanenin\n",
"# tuval nesnesi olup, estetik olarak etkileyici sekiller icin gerekli ayarlara sahiptir\n",
"from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas\n",
"\n",
"# Figure nesnnesi import edilir\n",
"from matplotlib.figure import Figure\n",
"\n",
"# rastgele dagilimi olusturmak ve sayi dizilerinin kontrolu icin numpy\n",
"import numpy as np\n",
"\n",
"fig = Figure()\n",
"canvas = FigureCanvas(fig)\n",
"\n",
"# mu = 0, sigma = 1 standart normal dagilimdan 10000 buyukugundeki orneklem\n",
"x = np.random.randn(10000)\n",
"\n",
"# figure nesnesine otomatik olarak eklenen axes artist nesnesinin olusturulmasi\n",
"# 1 satir 1 sutunda 1. seklin eksen nesnesi\n",
"ax = fig.add_subplot(111)\n",
"\n",
"# 50 kutucuktan olusan histogramin cizdirilmesi\n",
"ax.hist(x, bins=50)\n",
"\n",
"# Baslik ve eksen etiketleri\n",
"ax.set_title('Standart Normal Dagilimdan Rastgele Secilmis 10000 Sayinin Dagilimi')\n",
"ax.set_xlabel('x')\n",
"ax.set_ylabel('N')\n",
"fig.savefig('normal_daigilim.png')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Kodlama (Scripting) Katmanı\n",
"\n",
"Verisini çok fazla teknik detayla ilgilenmeden analiz etmek isteyenler için geliştirilmiş olan kodlama katmanı `matplotlib.pyplot` nesneleri aracılığı ile sağlanır. \n",
"\n",
"`matplotlib` mimarisinin en üst katmanıdır ve `MATLAB` betikleri şeklinde çalışmasını sağlamak için tasarlanmıştır. Kullanımı en kolay ve dolayısı ile en yaygın katmandır. Grafik Nesneleri Katmanı (Artist layer) nesne yönelimli grafik çizimi katmanı olarak adlandırıldığından, programcılıktaki yapıya benzer şekilde yapısal çizim katmanı (ing. procedural plotting) olarak da adlandırılır. Bir `FigureCanvas` nesnesinin oluşturulup `Figure` grafik nesnesiyle bağlanmasını otomatik olarak üstlenen `matplotlib.pyplot` paketi fonksiyon ve nesneleri üzerine kurulu olduğu için bu katman da özünde nesne yönelimlidir ancak kullanıcının bunun farkında olması gerekmez! \n",
"\n",
"Örnek: Grafik nesneleri katmanına örnek olarak verilen standart normal dağılımdan rastgele seçilen 10000 sayıdan oluşan örneklemin histogramının kodlama katmanında çizimi aşağıdaki kodla verilmiştir."
]
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"execution_count": 4,
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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"# FigureCanvas nesnesinin otomatik olarak import edilisi\n",
"import matplotlib.pyplot as plt\n",
"# standart normal dagilim ve dizi islemleri icin numpy\n",
"import numpy as np\n",
"\n",
"# standart normal dagilimin olusturulmasi\n",
"np.random.seed(123)\n",
"x = np.random.randn(10000)\n",
"\n",
"# Histogramin cizimi\n",
"plt.hist(x, 50)\n",
"# Baslik ve eksen etiketleri\n",
"plt.title('Standart Normal Dagilimdan Rastgele Secilmis 10000 Sayinin Dagilimi')\n",
"plt.xlabel('x')\n",
"plt.ylabel('N')\n",
"#fig.savefig('normal_daigilim.png')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`matplotib` hakkında daha fazla bilgi, örnek ve tutorial formatındaki dokümanlar için [dokümantasyon sayfasını](https://matplotlib.org/), özellikle mimari hakkında daha detaylı bilgi için ise kütüphaneyi geliştiren John Hunter ve Michael Droettboom'ın [yazısını](https://www.aosabook.org/en/matplotlib.html) okumakta fayda vardır."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Matplotlib ve Jupyter Defterleri\n",
"\n",
"`jupyter notebook` defterlerinde `matplotlib` grafiklerini görüntülemek için farklı modlar bulunmaktadır. Bu modlar jupyter sihirli kelimeleri (magic words) kullanılarak aktif hale getirilebilir.\n",
"\n",
"* `%matplotlib inline` interaktif kullanım araçları olmaksızın grafiğin ekrana getirilmesini sağlar.\n",
"\n",
"* `%matplotlib notebook` grafikler üzerinde zoom, pan gibi interaktif işlevlerin uygulanabilmesine olanak sağlayan moddur. Uyarı: Oluşturulan grafiğin sağ üstünde yer alan ve etkileşimi sonlandıran butonun tıklanmaması durumunda bir sonraki grafik interaktif olarak çalışmayabilir ve hata verebilir. Bu tür hataları önlemek için `matplotlib.pyplot` paketinin modun jupyter sihirli kelimesi ile (iki kez) aktif hale getirilmesi sonrası (daha önce edilmemişse) import edilmesi gerekebilmektedir.\n",
"\n",
"Aslında bu `jupyter` \"sihirli kelimeleri\" `matplotlib` arkayüzünü (backend) değiştirmektedir. Arkayüzler hakkında daha fazla bilgi için [bkz.](https://matplotlib.org/3.5.0/users/explain/backends.html). `%matplotlib widget`, `%matplotlib ipympl` ile aktif hale getirilebilecek diğer arkayüzler ve `mpld3` gibi interaktif kullanım sağlayan başka kütüphaneler de bulunmaktadır. Ancak en sık kullanılan arkayüzler (ya da modlar) `inline` ve `notebook` burada örneklenmiştir."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"/* global mpl */\n",
"window.mpl = {};\n",
"\n",
"mpl.get_websocket_type = function () {\n",
" if (typeof WebSocket !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof MozWebSocket !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert(\n",
" 'Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.'\n",
" );\n",
" }\n",
"};\n",
"\n",
"mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = this.ws.binaryType !== undefined;\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById('mpl-warnings');\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent =\n",
" 'This browser does not support binary websocket messages. ' +\n",
" 'Performance may be slow.';\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = document.createElement('div');\n",
" this.root.setAttribute('style', 'display: inline-block');\n",
" this._root_extra_style(this.root);\n",
"\n",
" parent_element.appendChild(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message('supports_binary', { value: fig.supports_binary });\n",
" fig.send_message('send_image_mode', {});\n",
" if (fig.ratio !== 1) {\n",
" fig.send_message('set_device_pixel_ratio', {\n",
" device_pixel_ratio: fig.ratio,\n",
" });\n",
" }\n",
" fig.send_message('refresh', {});\n",
" };\n",
"\n",
" this.imageObj.onload = function () {\n",
" if (fig.image_mode === 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function () {\n",
" fig.ws.close();\n",
" };\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"};\n",
"\n",
"mpl.figure.prototype._init_header = function () {\n",
" var titlebar = document.createElement('div');\n",
" titlebar.classList =\n",
" 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
" var titletext = document.createElement('div');\n",
" titletext.classList = 'ui-dialog-title';\n",
" titletext.setAttribute(\n",
" 'style',\n",
" 'width: 100%; text-align: center; padding: 3px;'\n",
" );\n",
" titlebar.appendChild(titletext);\n",
" this.root.appendChild(titlebar);\n",
" this.header = titletext;\n",
"};\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
"\n",
"mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
"\n",
"mpl.figure.prototype._init_canvas = function () {\n",
" var fig = this;\n",
"\n",
" var canvas_div = (this.canvas_div = document.createElement('div'));\n",
" canvas_div.setAttribute(\n",
" 'style',\n",
" 'border: 1px solid #ddd;' +\n",
" 'box-sizing: content-box;' +\n",
" 'clear: both;' +\n",
" 'min-height: 1px;' +\n",
" 'min-width: 1px;' +\n",
" 'outline: 0;' +\n",
" 'overflow: hidden;' +\n",
" 'position: relative;' +\n",
" 'resize: both;'\n",
" );\n",
"\n",
" function on_keyboard_event_closure(name) {\n",
" return function (event) {\n",
" return fig.key_event(event, name);\n",
" };\n",
" }\n",
"\n",
" canvas_div.addEventListener(\n",
" 'keydown',\n",
" on_keyboard_event_closure('key_press')\n",
" );\n",
" canvas_div.addEventListener(\n",
" 'keyup',\n",
" on_keyboard_event_closure('key_release')\n",
" );\n",
"\n",
" this._canvas_extra_style(canvas_div);\n",
" this.root.appendChild(canvas_div);\n",
"\n",
" var canvas = (this.canvas = document.createElement('canvas'));\n",
" canvas.classList.add('mpl-canvas');\n",
" canvas.setAttribute('style', 'box-sizing: content-box;');\n",
"\n",
" this.context = canvas.getContext('2d');\n",
"\n",
" var backingStore =\n",
" this.context.backingStorePixelRatio ||\n",
" this.context.webkitBackingStorePixelRatio ||\n",
" this.context.mozBackingStorePixelRatio ||\n",
" this.context.msBackingStorePixelRatio ||\n",
" this.context.oBackingStorePixelRatio ||\n",
" this.context.backingStorePixelRatio ||\n",
" 1;\n",
"\n",
" this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
" 'canvas'\n",
" ));\n",
" rubberband_canvas.setAttribute(\n",
" 'style',\n",
" 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
" );\n",
"\n",
" // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
" if (this.ResizeObserver === undefined) {\n",
" if (window.ResizeObserver !== undefined) {\n",
" this.ResizeObserver = window.ResizeObserver;\n",
" } else {\n",
" var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
" this.ResizeObserver = obs.ResizeObserver;\n",
" }\n",
" }\n",
"\n",
" this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
" var nentries = entries.length;\n",
" for (var i = 0; i < nentries; i++) {\n",
" var entry = entries[i];\n",
" var width, height;\n",
" if (entry.contentBoxSize) {\n",
" if (entry.contentBoxSize instanceof Array) {\n",
" // Chrome 84 implements new version of spec.\n",
" width = entry.contentBoxSize[0].inlineSize;\n",
" height = entry.contentBoxSize[0].blockSize;\n",
" } else {\n",
" // Firefox implements old version of spec.\n",
" width = entry.contentBoxSize.inlineSize;\n",
" height = entry.contentBoxSize.blockSize;\n",
" }\n",
" } else {\n",
" // Chrome <84 implements even older version of spec.\n",
" width = entry.contentRect.width;\n",
" height = entry.contentRect.height;\n",
" }\n",
"\n",
" // Keep the size of the canvas and rubber band canvas in sync with\n",
" // the canvas container.\n",
" if (entry.devicePixelContentBoxSize) {\n",
" // Chrome 84 implements new version of spec.\n",
" canvas.setAttribute(\n",
" 'width',\n",
" entry.devicePixelContentBoxSize[0].inlineSize\n",
" );\n",
" canvas.setAttribute(\n",
" 'height',\n",
" entry.devicePixelContentBoxSize[0].blockSize\n",
" );\n",
" } else {\n",
" canvas.setAttribute('width', width * fig.ratio);\n",
" canvas.setAttribute('height', height * fig.ratio);\n",
" }\n",
" canvas.setAttribute(\n",
" 'style',\n",
" 'width: ' + width + 'px; height: ' + height + 'px;'\n",
" );\n",
"\n",
" rubberband_canvas.setAttribute('width', width);\n",
" rubberband_canvas.setAttribute('height', height);\n",
"\n",
" // And update the size in Python. We ignore the initial 0/0 size\n",
" // that occurs as the element is placed into the DOM, which should\n",
" // otherwise not happen due to the minimum size styling.\n",
" if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
" fig.request_resize(width, height);\n",
" }\n",
" }\n",
" });\n",
" this.resizeObserverInstance.observe(canvas_div);\n",
"\n",
" function on_mouse_event_closure(name) {\n",
" return function (event) {\n",
" return fig.mouse_event(event, name);\n",
" };\n",
" }\n",
"\n",
" rubberband_canvas.addEventListener(\n",
" 'mousedown',\n",
" on_mouse_event_closure('button_press')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseup',\n",
" on_mouse_event_closure('button_release')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'dblclick',\n",
" on_mouse_event_closure('dblclick')\n",
" );\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband_canvas.addEventListener(\n",
" 'mousemove',\n",
" on_mouse_event_closure('motion_notify')\n",
" );\n",
"\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseenter',\n",
" on_mouse_event_closure('figure_enter')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseleave',\n",
" on_mouse_event_closure('figure_leave')\n",
" );\n",
"\n",
" canvas_div.addEventListener('wheel', function (event) {\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" on_mouse_event_closure('scroll')(event);\n",
" });\n",
"\n",
" canvas_div.appendChild(canvas);\n",
" canvas_div.appendChild(rubberband_canvas);\n",
"\n",
" this.rubberband_context = rubberband_canvas.getContext('2d');\n",
" this.rubberband_context.strokeStyle = '#000000';\n",
"\n",
" this._resize_canvas = function (width, height, forward) {\n",
" if (forward) {\n",
" canvas_div.style.width = width + 'px';\n",
" canvas_div.style.height = height + 'px';\n",
" }\n",
" };\n",
"\n",
" // Disable right mouse context menu.\n",
" this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
" event.preventDefault();\n",
" return false;\n",
" });\n",
"\n",
" function set_focus() {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"};\n",
"\n",
"mpl.figure.prototype._init_toolbar = function () {\n",
" var fig = this;\n",
"\n",
" var toolbar = document.createElement('div');\n",
" toolbar.classList = 'mpl-toolbar';\n",
" this.root.appendChild(toolbar);\n",
"\n",
" function on_click_closure(name) {\n",
" return function (_event) {\n",
" return fig.toolbar_button_onclick(name);\n",
" };\n",
" }\n",
"\n",
" function on_mouseover_closure(tooltip) {\n",
" return function (event) {\n",
" if (!event.currentTarget.disabled) {\n",
" return fig.toolbar_button_onmouseover(tooltip);\n",
" }\n",
" };\n",
" }\n",
"\n",
" fig.buttons = {};\n",
" var buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'mpl-button-group';\n",
" for (var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" /* Instead of a spacer, we start a new button group. */\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
" buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'mpl-button-group';\n",
" continue;\n",
" }\n",
"\n",
" var button = (fig.buttons[name] = document.createElement('button'));\n",
" button.classList = 'mpl-widget';\n",
" button.setAttribute('role', 'button');\n",
" button.setAttribute('aria-disabled', 'false');\n",
" button.addEventListener('click', on_click_closure(method_name));\n",
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
"\n",
" var icon_img = document.createElement('img');\n",
" icon_img.src = '_images/' + image + '.png';\n",
" icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
" icon_img.alt = tooltip;\n",
" button.appendChild(icon_img);\n",
"\n",
" buttonGroup.appendChild(button);\n",
" }\n",
"\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
"\n",
" var fmt_picker = document.createElement('select');\n",
" fmt_picker.classList = 'mpl-widget';\n",
" toolbar.appendChild(fmt_picker);\n",
" this.format_dropdown = fmt_picker;\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = document.createElement('option');\n",
" option.selected = fmt === mpl.default_extension;\n",
" option.innerHTML = fmt;\n",
" fmt_picker.appendChild(option);\n",
" }\n",
"\n",
" var status_bar = document.createElement('span');\n",
" status_bar.classList = 'mpl-message';\n",
" toolbar.appendChild(status_bar);\n",
" this.message = status_bar;\n",
"};\n",
"\n",
"mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
"};\n",
"\n",
"mpl.figure.prototype.send_message = function (type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"};\n",
"\n",
"mpl.figure.prototype.send_draw_message = function () {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1], msg['forward']);\n",
" fig.send_message('refresh', {});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
" var x0 = msg['x0'] / fig.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
" var x1 = msg['x1'] / fig.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0,\n",
" 0,\n",
" fig.canvas.width / fig.ratio,\n",
" fig.canvas.height / fig.ratio\n",
" );\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
" fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_message = function (fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
" for (var key in msg) {\n",
" if (!(key in fig.buttons)) {\n",
" continue;\n",
" }\n",
" fig.buttons[key].disabled = !msg[key];\n",
" fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
" if (msg['mode'] === 'PAN') {\n",
" fig.buttons['Pan'].classList.add('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" } else if (msg['mode'] === 'ZOOM') {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.add('active');\n",
" } else {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function () {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message('ack', {});\n",
"};\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" var img = evt.data;\n",
" if (img.type !== 'image/png') {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" img.type = 'image/png';\n",
" }\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src\n",
" );\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" img\n",
" );\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" } else if (\n",
" typeof evt.data === 'string' &&\n",
" evt.data.slice(0, 21) === 'data:image/png;base64'\n",
" ) {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig['handle_' + msg_type];\n",
" } catch (e) {\n",
" console.log(\n",
" \"No handler for the '\" + msg_type + \"' message type: \",\n",
" msg\n",
" );\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\n",
" \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
" e,\n",
" e.stack,\n",
" msg\n",
" );\n",
" }\n",
" }\n",
" };\n",
"};\n",
"\n",
"// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function (e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e) {\n",
" e = window.event;\n",
" }\n",
" if (e.target) {\n",
" targ = e.target;\n",
" } else if (e.srcElement) {\n",
" targ = e.srcElement;\n",
" }\n",
" if (targ.nodeType === 3) {\n",
" // defeat Safari bug\n",
" targ = targ.parentNode;\n",
" }\n",
"\n",
" // pageX,Y are the mouse positions relative to the document\n",
" var boundingRect = targ.getBoundingClientRect();\n",
" var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
" var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
"\n",
" return { x: x, y: y };\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * https://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys(original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object') {\n",
" obj[key] = original[key];\n",
" }\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function (event, name) {\n",
" var canvas_pos = mpl.findpos(event);\n",
"\n",
" if (name === 'button_press') {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * this.ratio;\n",
" var y = canvas_pos.y * this.ratio;\n",
"\n",
" this.send_message(name, {\n",
" x: x,\n",
" y: y,\n",
" button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event),\n",
" });\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"};\n",
"\n",
"mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"};\n",
"\n",
"mpl.figure.prototype.key_event = function (event, name) {\n",
" // Prevent repeat events\n",
" if (name === 'key_press') {\n",
" if (event.key === this._key) {\n",
" return;\n",
" } else {\n",
" this._key = event.key;\n",
" }\n",
" }\n",
" if (name === 'key_release') {\n",
" this._key = null;\n",
" }\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.key !== 'Control') {\n",
" value += 'ctrl+';\n",
" }\n",
" else if (event.altKey && event.key !== 'Alt') {\n",
" value += 'alt+';\n",
" }\n",
" else if (event.shiftKey && event.key !== 'Shift') {\n",
" value += 'shift+';\n",
" }\n",
"\n",
" value += 'k' + event.key;\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
" return false;\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
" if (name === 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message('toolbar_button', { name: name });\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"\n",
"///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
"// prettier-ignore\n",
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";/* global mpl */\n",
"\n",
"var comm_websocket_adapter = function (comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.binaryType = comm.kernel.ws.binaryType;\n",
" ws.readyState = comm.kernel.ws.readyState;\n",
" function updateReadyState(_event) {\n",
" if (comm.kernel.ws) {\n",
" ws.readyState = comm.kernel.ws.readyState;\n",
" } else {\n",
" ws.readyState = 3; // Closed state.\n",
" }\n",
" }\n",
" comm.kernel.ws.addEventListener('open', updateReadyState);\n",
" comm.kernel.ws.addEventListener('close', updateReadyState);\n",
" comm.kernel.ws.addEventListener('error', updateReadyState);\n",
"\n",
" ws.close = function () {\n",
" comm.close();\n",
" };\n",
" ws.send = function (m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function (msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" var data = msg['content']['data'];\n",
" if (data['blob'] !== undefined) {\n",
" data = {\n",
" data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
" };\n",
" }\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(data);\n",
" });\n",
" return ws;\n",
"};\n",
"\n",
"mpl.mpl_figure_comm = function (comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = document.getElementById(id);\n",
" var ws_proxy = comm_websocket_adapter(comm);\n",
"\n",
" function ondownload(figure, _format) {\n",
" window.open(figure.canvas.toDataURL());\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element;\n",
" fig.cell_info = mpl.find_output_cell(\"\");\n",
" if (!fig.cell_info) {\n",
" console.error('Failed to find cell for figure', id, fig);\n",
" return;\n",
" }\n",
" fig.cell_info[0].output_area.element.on(\n",
" 'cleared',\n",
" { fig: fig },\n",
" fig._remove_fig_handler\n",
" );\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function (fig, msg) {\n",
" var width = fig.canvas.width / fig.ratio;\n",
" fig.cell_info[0].output_area.element.off(\n",
" 'cleared',\n",
" fig._remove_fig_handler\n",
" );\n",
" fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable();\n",
" fig.parent_element.innerHTML =\n",
" '';\n",
" fig.close_ws(fig, msg);\n",
"};\n",
"\n",
"mpl.figure.prototype.close_ws = function (fig, msg) {\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"};\n",
"\n",
"mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width / this.ratio;\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] =\n",
" '';\n",
"};\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function () {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message('ack', {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () {\n",
" fig.push_to_output();\n",
" }, 1000);\n",
"};\n",
"\n",
"mpl.figure.prototype._init_toolbar = function () {\n",
" var fig = this;\n",
"\n",
" var toolbar = document.createElement('div');\n",
" toolbar.classList = 'btn-toolbar';\n",
" this.root.appendChild(toolbar);\n",
"\n",
" function on_click_closure(name) {\n",
" return function (_event) {\n",
" return fig.toolbar_button_onclick(name);\n",
" };\n",
" }\n",
"\n",
" function on_mouseover_closure(tooltip) {\n",
" return function (event) {\n",
" if (!event.currentTarget.disabled) {\n",
" return fig.toolbar_button_onmouseover(tooltip);\n",
" }\n",
" };\n",
" }\n",
"\n",
" fig.buttons = {};\n",
" var buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'btn-group';\n",
" var button;\n",
" for (var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" /* Instead of a spacer, we start a new button group. */\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
" buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'btn-group';\n",
" continue;\n",
" }\n",
"\n",
" button = fig.buttons[name] = document.createElement('button');\n",
" button.classList = 'btn btn-default';\n",
" button.href = '#';\n",
" button.title = name;\n",
" button.innerHTML = '';\n",
" button.addEventListener('click', on_click_closure(method_name));\n",
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
" buttonGroup.appendChild(button);\n",
" }\n",
"\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = document.createElement('span');\n",
" status_bar.classList = 'mpl-message pull-right';\n",
" toolbar.appendChild(status_bar);\n",
" this.message = status_bar;\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = document.createElement('div');\n",
" buttongrp.classList = 'btn-group inline pull-right';\n",
" button = document.createElement('button');\n",
" button.classList = 'btn btn-mini btn-primary';\n",
" button.href = '#';\n",
" button.title = 'Stop Interaction';\n",
" button.innerHTML = '';\n",
" button.addEventListener('click', function (_evt) {\n",
" fig.handle_close(fig, {});\n",
" });\n",
" button.addEventListener(\n",
" 'mouseover',\n",
" on_mouseover_closure('Stop Interaction')\n",
" );\n",
" buttongrp.appendChild(button);\n",
" var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
" titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
"};\n",
"\n",
"mpl.figure.prototype._remove_fig_handler = function (event) {\n",
" var fig = event.data.fig;\n",
" if (event.target !== this) {\n",
" // Ignore bubbled events from children.\n",
" return;\n",
" }\n",
" fig.close_ws(fig, {});\n",
"};\n",
"\n",
"mpl.figure.prototype._root_extra_style = function (el) {\n",
" el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
"};\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function (el) {\n",
" // this is important to make the div 'focusable\n",
" el.setAttribute('tabindex', 0);\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" } else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which === 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
" fig.ondownload(fig, null);\n",
"};\n",
"\n",
"mpl.find_output_cell = function (html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i = 0; i < ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code') {\n",
" for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] === html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"};\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel !== null) {\n",
" IPython.notebook.kernel.comm_manager.register_target(\n",
" 'matplotlib',\n",
" mpl.mpl_figure_comm\n",
" );\n",
"}\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib notebook\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt\n",
"# Histogramin cizimi\n",
"plt.hist(x, 25)\n",
"# Baslik ve eksen etiketleri\n",
"plt.title('Standart Normal Dagilim')\n",
"plt.xlabel('x')\n",
"plt.ylabel('N')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sistemde yüklü `matplotlib` versiyonunu ve hazır grafik stillerini görmek için"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'3.5.3'"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import matplotlib as mpl\n",
"mpl.__version__"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Solarize_Light2', '_classic_test_patch', '_mpl-gallery', '_mpl-gallery-nogrid', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn', 'seaborn-bright', 'seaborn-colorblind', 'seaborn-dark', 'seaborn-dark-palette', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted', 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk', 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'tableau-colorblind10']\n"
]
}
],
"source": [
"print(plt.style.available)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Veri Görselleştirme Türleri #\n",
"\n",
"## Eğri Grafikleri ##\n",
"\n",
"Eğri grafiği veya çizgi grafiği (ing. line plot), veri noktalarının doğru parçalarıyla birbirine bağlandıkları temel bir grafik türüdür. Verinin içinde yer alan belirli bir zaman aralığındaki trendlerin görselleştirme sonucu belirlenebilmesi ve farklı gruplardaki trendlerin karşılaştırılması için uygun bir grafik türüdür. \n",
"\n",
"### Örnek: Keşif Tekniklerinin Performanslarının Zamanla Değişimi\n",
"\n",
"Örnek olarak [exoplanet.eu](http://exoplanet.eu/catalog/) kataloğundaki verileri keşif tekniklerine göre grupladıktan her bir teknikle yapılan keşif sayılarıının zamanla değişimi incelenmek ve karşılaştırılmak isteniyor olsun.\n",
"\n",
"Bu amaçla öncelikle verinin görselleştirme için hazırlanması gerekir."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['# name', 'planet_status', 'mass', 'mass_error_min', 'mass_error_max',\n",
" 'mass_sini', 'mass_sini_error_min', 'mass_sini_error_max', 'radius',\n",
" 'radius_error_min', 'radius_error_max', 'orbital_period',\n",
" 'orbital_period_error_min', 'orbital_period_error_max',\n",
" 'semi_major_axis', 'semi_major_axis_error_min',\n",
" 'semi_major_axis_error_max', 'eccentricity', 'eccentricity_error_min',\n",
" 'eccentricity_error_max', 'inclination', 'inclination_error_min',\n",
" 'inclination_error_max', 'angular_distance', 'discovered', 'updated',\n",
" 'omega', 'omega_error_min', 'omega_error_max', 'tperi',\n",
" 'tperi_error_min', 'tperi_error_max', 'tconj', 'tconj_error_min',\n",
" 'tconj_error_max', 'tzero_tr', 'tzero_tr_error_min',\n",
" 'tzero_tr_error_max', 'tzero_tr_sec', 'tzero_tr_sec_error_min',\n",
" 'tzero_tr_sec_error_max', 'lambda_angle', 'lambda_angle_error_min',\n",
" 'lambda_angle_error_max', 'impact_parameter',\n",
" 'impact_parameter_error_min', 'impact_parameter_error_max', 'tzero_vr',\n",
" 'tzero_vr_error_min', 'tzero_vr_error_max', 'k', 'k_error_min',\n",
" 'k_error_max', 'temp_calculated', 'temp_calculated_error_min',\n",
" 'temp_calculated_error_max', 'temp_measured', 'hot_point_lon',\n",
" 'geometric_albedo', 'geometric_albedo_error_min',\n",
" 'geometric_albedo_error_max', 'log_g', 'publication', 'detection_type',\n",
" 'mass_detection_type', 'radius_detection_type', 'alternate_names',\n",
" 'molecules', 'star_name', 'ra', 'dec', 'mag_v', 'mag_i', 'mag_j',\n",
" 'mag_h', 'mag_k', 'star_distance', 'star_distance_error_min',\n",
" 'star_distance_error_max', 'star_metallicity',\n",
" 'star_metallicity_error_min', 'star_metallicity_error_max', 'star_mass',\n",
" 'star_mass_error_min', 'star_mass_error_max', 'star_radius',\n",
" 'star_radius_error_min', 'star_radius_error_max', 'star_sp_type',\n",
" 'star_age', 'star_age_error_min', 'star_age_error_max', 'star_teff',\n",
" 'star_teff_error_min', 'star_teff_error_max', 'star_detected_disc',\n",
" 'star_magnetic_field', 'star_alternate_names'],\n",
" dtype='object')"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"exoeu = pd.read_csv(\"veri/exoplanet.eu_catalog_20230502.csv\")\n",
"exoeu.columns"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ötegezegenlerin keşif yöntemleri `detection_type`, tarihleri ise `discovered` anahtarında bulunmaktadır. Sadece bu bilgilerle ilgilenildği için onları kullanarak gruplamalar ve veriçerçeveleri oluşturmak iyi bir fikir olacaktır."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"transits = exoeu[exoeu['detection_type'] == 'Primary Transit']\n",
"transits.groupby('discovered').count()['# name'].plot(kind=\"line\",\n",
" label=\"Gecis\")\n",
"radvel = exoeu[exoeu['detection_type'] == 'Radial Velocity']\n",
"radvel.groupby('discovered').count()['# name'].plot(kind=\"line\",\n",
" label=\"Dikine Hiz\")\n",
"\n",
"# Kepler'in gozlemlere basladigi yili isaretlemek iyi bir fikir olacaktir\n",
"plt.annotate(\"Kepler\",\n",
" xy=(2009, 70), xycoords='data',\n",
" xytext=(2009, 150), textcoords='data',\n",
" arrowprops=dict(arrowstyle=\"->\",\n",
" connectionstyle=\"arc3\"),\n",
" )\n",
"\n",
"plt.yscale(\"log\")\n",
"plt.xlabel(\"Yil\")\n",
"plt.ylabel(\"Kesif Sayisi\")\n",
"plt.legend(loc=\"best\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"y-ekseninin logaritmik ölçekte çizdirilmesinin nedeni, geçişle keşiflerin bazı yıllarda çok yüksek sayılara ulaşmalarıdır. Bu yıllar Kepler verisinden en çok gezegenin keşfedildiği yıllardır.\n",
"\n",
"Benzer bir grafik keşif sayıları yakın Kütleçekim Mercekleme ve Doğrudan Görüntüleme teknikleri için de yapılabilir. Bu kez y-eksenini logaritmik çizdirmeye de ihtiyaç duyulmayacaktır."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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jS0vCYfr378/58+c5ffo0q1evpmfPnjz77LMMHDiQ/Hz7/jIaDIbST3Kw3Nxc+vTpw7Rp03jggQfYvHkz0dHRzJo1i4sXL/LJJ59U+NqKotj9HgshhD1Zkn31dfQSyAjH8PDwoHbt2tStW5cOHTrw0ksv8fPPP7N69WoWLFignhcbG8vgwYPx9fXF39+fESNGkJiYaHWtt956i5CQEPz8/HjkkUf4v//7P9q1a6cef+CBBxgyZAhvv/02derUoWnTpkDRMwmBgYFWr//PP//Qvn17PD096dSpE/v27bM632g08vDDD9OgQQO8vLxo2rQpH3/8sdU5ltd///33CQsLIzg4mHHjxpGXl1fs/Zk5cyZbtmxh/fr1jB8/no4dOxIREcGtt97K559/zrRp09Rzc3NzGT9+PCEhIXh6enLzzTeza9cu9fjGjRvRaDSsXr2ajh074uHhwZYtW9RxFTRhwgR69Oih/tyjRw/Gjx/P5MmTqVGjBrVr1+b1119Xj9evXx+AoUOHotFo1J/Lcu1r5ebmMmnSJOrWrYuPjw9dunRh48aN6vEFCxYQGBjIr7/+StOmTfH29uauu+4iKyuLhQsXUr9+fYKCghg/frxV9+3SriuEcD1qsm9dD5fPkXFz9ACciaIoZOVlOeS1vd290Wg0lbpGr169aNu2LStWrOCRRx7BZDKpQcymTZvIz89n3Lhx3HPPPeoH0bfffsvbb7/NZ599Rrdu3Vi6dCkffPBBoa7G69atw9/fn7Vr15Z5PBkZGQwcOJA+ffqwePFiYmJiePbZZ63OMZlM1KtXj2XLlhEcHMy2bdt47LHHCAsLY8SIEep5GzZsICwsjA0bNnDixAnuuece2rVrx6OPPlrka3/33Xf06dOH9u3bF3m84L2ePHkyP/74IwsXLiQyMpIZM2bQr18/Tpw4QY0aNdTz/u///o/333+fhg0bEhQUVOb7sHDhQiZOnMjOnTvZvn07DzzwAN26daNPnz7s2rWLkJAQ5s+fT//+/dHpdGW+7rWefvppDh8+zNKlS6lTpw4rV66kf//+REdH07hxYwCysrKYNWsWS5cuJT09nWHDhjF06FACAwP5/fffOXXqFMOHD6dbt27cc889Zb6uEMJ1mAwm8i6Y/yFoNSPjotuvJZApICsvC9/pvg557YwpGfjofSp9nWbNmnHw4EHAHHxER0cTExNDeHg4AN988w0tW7Zk165ddO7cmU8++YSHH36YBx98EICpU6fy559/kpGRYXVdHx8fvv76a/R6fZnHsmTJEkwmE3PnzsXT05OWLVty9uxZnnzySfUcd3d3/ve//6k/N2jQgO3bt/PDDz9YBTJBQUF8+umn6HQ6mjVrxh133MG6deuKDWSOHTtWaPZi6NChaiDWpk0btm3bRmZmJnPmzGHBggUMGDAAgK+++oq1a9cyd+5cXnjhBfX5b7zxBn369Cnz+7do06YNr732GgCNGzfm008/Zd26dfTp04datWoB5pms2rVrl/vaFrGxscyfP5/Y2Fjq1KkDwKRJk1izZg3z589XZ6Dy8vKYM2cON9xwAwB33XUXixYtIjExEV9fX1q0aEHPnj3ZsGED99xzT5mvK4RwHZbWBBq9Bvdgd9wCXXtpSQKZakZRFHW24ciRI4SHh6tBDECLFi0IDAzkyJEjdO7cmaNHj/LUU09ZXePGG29k/fr1Vo+1bt26XEGM5fXbtGmDp6en+lhUVFSh82bPns28efOIjY0lOzsbg8FgtbQF0LJlS6vZirCwMKKjo8s1ns8++4zMzExmzZrF5s2bATh58iR5eXl069ZNPc/d3Z0bb7yRI0eOWD2/U6eKtbhv06aN1c9hYWEkJSVV6FrFiY6Oxmg00qRJE6vHc3NzCQ4OVn/29vZWgxiA0NBQ6tevj6+vr9VjlvGV9bpCCNdRMNFXo9G4fI6MBDIFeLt7kzElo/QT7fTatnDkyJFCy0K24ONTeLZIo9EUajJWUt5KUZYuXcqkSZP44IMPiIqKws/Pj/fee4+dO3danefu7l7otUvaodW4cWOOHj1q9VhYWBiA1XJReVx7D7RabZnef3nHXp5rW2RkZKDT6dizZ0+h5amCQUpRYylpfGW9rhDCdVjyY/R1zP84lUCmGtFoNDZZ3nGU9evXEx0dzXPPPQdA8+bNiYuLIy4uTp2VOXz4MCkpKbRo0QKApk2bsmvXLsaOHatep2Cia0lq1arF+fPn1Z+PHz9OVtbVHKPmzZuzaNEicnJy1FmZHTt2WF1j69at3HTTTVazQidPnizP2y7SyJEjeeWVV9i3b1+xeTIAN9xwA3q9nq1btxIZGQmYA4Zdu3aVWqOlVq1aHDp0yOqx/fv3FwoMSuPu7m6VXFuRa7dv3x6j0UhSUhLdu3cv1+uXxF7XFUI4jtqeoI4HgMsn+8quJReVm5tLQkIC586dY+/evUybNo3BgwczcOBANSjp3bs3rVu3ZtSoUezdu5d//vmHsWPHcuutt6rLJM888wxz585l4cKFHD9+nLfeeouDBw+WKfG4V69efPrpp+zbt4/du3fzxBNPWH3Q3nfffWg0Gh599FEOHz7M77//zvvvv291jcaNG7N7927++OMPjh07xquvvlrmQKokzz33HFFRUdx22218/PHH7N27l5iYGP744w9Wr16tzi74+Pjw5JNP8sILL7BmzRoOHz7Mo48+SlZWFg8//HCp73/37t188803HD9+nNdee61Q8FEW9evXZ926dSQkJJCcnFyhazdp0oRRo0YxduxYVqxYQUxMDP/88w/Tp0/nt99+K/eY7H1dIYTjqFV961aPGRkJZFzUmjVrCAsLo379+vTv358NGzYwa9Ysfv75Z/VDWqPR8PPPPxMUFMQtt9xC7969adiwId9//716nVGjRjFlyhQmTZpEhw4diImJ4YEHHrDKaynOBx98QHh4ON27d+e+++5j0qRJeHtfXSLz9fVl1apVREdH0759e15++WXeffddq2s8/vjjDBs2jHvuuYcuXbpw6dKlQjk7FeHp6cm6det48cUXmT9/PjfffDPNmzdnwoQJdOvWzWrb+DvvvMPw4cMZM2YMHTp04MSJE/zxxx+l7kzq168fr776KpMnT6Zz586kp6dbzWyV1QcffMDatWsJDw9XZ48qcu358+czduxYnn/+eZo2bcqQIUPYtWsXERER5R5TVVxXCOEYBfssgesHMhrl2oX4aiYtLY2AgABSU1Px9/e3OpaTk0NMTAwNGjQo0wf39aJPnz7Url2bRYsWOXoowkXJ/1tCOK/9t+0nZX0KzRc3J3RUKLnnctlebzvo4Na8WytdCsRWSvr8LkhyZK5zWVlZfP755/Tr1w+dTsd3333HX3/9Va56MUIIIVxHoWTfK9uvMYIx04ibr2uFBq41WmFzGo2G33//nbfffpucnByaNm3Kjz/+SO/evR09NCGEEHZwbbKv1lsLOsyBTKoEMsLFeHl58ddffzl6GEIIIapAfno+xnTz7iTLjIyllkz+5XzyU/PxqOvhyCGWmyT7CiGEENcJS1VfnZ8ON7+rcxmunPArgQwUKjwmhKgc+X9KCOdUsOt1QRLIuChLzZOCRdyEEJVnMFz5V18lmmAKIWyvYNfrgly5KN51nSOj0+kIDAxU+8p4e1e+A7UQ1zuTycSFCxfw9vbGze26/hMjhNMp2GepIFfugH3d/5WxdBy2dRM/Ia5nWq2WiIgI+YeBEE6m2KUlF+6Afd0HMhqNhrCwMEJCQsrd8FAIUTS9Xo9We12vXAvhlIpbWnLlHJnrPpCx0Ol0sp4vhBCiWlP7LEmyrxBCCCFcjeGcdZ8lC1dO9pVARgghhLgOKIpyNdm3Gi0tSSAjhBBCXAfyLuWhGMw1nvRhsrQkhBBCCBdiSfR1r+WOVm/98e/K268lkBFCCCGuA8Ul+oJrb7+WQEYIIYS4DhSX6AuS7CuEEEIIJ1dcoi8UWFpKy3e5XmkSyAghhBDXAUuOTJFLS1cCGUxgzHCtWRkJZIQQQojrgKU9QVFLS1ovLRo3c0sRV8uTcWgg8/rrr6PRaKy+mjVrph7Pyclh3LhxBAcH4+vry/Dhw0lMTHTgiIUQQgjXpCb71i08I6PRaFw2T8bhMzItW7bk/Pnz6teWLVvUY8899xyrVq1i2bJlbNq0ifj4eIYNG+bA0QohhBCuSe2zVMSMDLhuLRmH91pyc3NTO1AXlJqayty5c1myZAm9evUCYP78+TRv3pwdO3bQtWvXqh6qEEII4ZJM+SYMicXnyECBLdguVkvG4TMyx48fp06dOjRs2JBRo0YRGxsLwJ49e8jLy6N3797quc2aNSMiIoLt27cXe73c3FzS0tKsvoQQQojrWV5iHpgAHehDiglkXHRGxqGBTJcuXViwYAFr1qxhzpw5xMTE0L17d9LT00lISECv1xMYGGj1nNDQUBISEoq95vTp0wkICFC/wsPD7fwuhBBCCOemJvqGeaDRaoo8x1UDGYcuLQ0YMED9vk2bNnTp0oXIyEh++OEHvLy8KnTNKVOmMHHiRPXntLQ0CWaEEEJc10qq6mshyb42EBgYSJMmTThx4gS1a9fGYDCQkpJidU5iYmKROTUWHh4e+Pv7W30JIYQQ1zM10beIYngWrjoj41SBTEZGBidPniQsLIyOHTvi7u7OunXr1ONHjx4lNjaWqKgoB45SCCGEcC2WpaWSZmRcNZBx6NLSpEmTGDRoEJGRkcTHx/Paa6+h0+kYOXIkAQEBPPzww0ycOJEaNWrg7+/PM888Q1RUlOxYEkIIIcqhtK3XIIFMhZw9e5aRI0dy6dIlatWqxc0338yOHTuoVasWADNnzkSr1TJ8+HByc3Pp168fn332mSOHLIQQQrickvosWbjq9muHBjJLly4t8binpyezZ89m9uzZVTQiIYQQovopy9KSJPsKIYQQwilJsq8QQgghXJIx20h+sjk4qY7JvhLICCGEENWYZTZG66VVg5WiSCAjhBBCCKdTMNFXoym6qi8UyJFJM6KYlCoZmy1IICOEEEJUY5YZmZKWleDqjAwKGDNcJ+FXAhkhhBCiGlP7LJVQQwZA66lFozfP2LjSFmwJZIQQQohqTO2zVLfkGRmNRuOSeTISyAghhBDVmOFc6VV9LSSQEUIIIYRTKUvnawtXLIongYwQQghRjZVUDG/n2Z28vflt8k3mGRhXnJFxaIsCIYQQQtiPoiglJvtO/HMi2+K20bluZ/re0NclAxmZkRFCCCGqqfzUfEzZJqDopaX49HgAEjMSAdeckZFARgghhKimLMtKbkFu6Lx0hY5fyroEQHJOsvk8F+yALYGMEEIIUU2V1PXaYDSQbkgHIDnbHMhIsq8QQgghnIaa6FtEfowleAFIyUkBZGlJCCGEEE6kYJ+la13KvqR+ry4tSSAjhBBCCGdR0tKSJT8GZEZGCCGEEE6opBoyRc3ISI6MEEIIIZxGSTMyl7Mvq9/LjIwQQgghnE5Jyb4Fl5Ysib+y/VoIIYQQTkExKeSeL1uy77UzMsZ0I4pRsf8gbUACGSGEEKIaMiQZwAhowD3UvdDxgktL6YZ08k35aiADkJ/uGrMyEsgIIYQQ1ZBlWUkfqkfrVvjjvuCMDJhnZbQeWjQeGsB1En4lkBFCCCGqIUsNGX3dwom+YJ0jA66b8CuBjBBCCFENGc4Vn+gLhWdk1IRfCWSEEEII4WjqjEwRW6/hao6MBvNSkszICCGEEMJplFQMT1EUdWkpIiACcN0O2BLICCGEENWQpRheUUtLWXlZ5BrNx2+ocQNwdUbG1ar7SiAjhBBCVEMlLS1Z8mP0Oj31/OsBkiMjhBBCCCeiJvsWsbRkyY+p4VWDIM8gQHJkhBBCCOEkTLkm8i7mASV3vg72CibQMxAokCMjgYwQQgghHMmQYJ6N0eg1uAcXruprWVoK9g4uNCMjOTJCCCGEcKiCib4ajabQcaulJS9zICMzMkIIIYRwCqXVkClyaclFO2BLICOEEEJUMyXVkIECS0tehZeWZEZGCCGEEA5lWVoqdkamQI6MJPsKIYQQwqmoMzLF9FkqKkcmJScFRVEk2VcIIYQQjmXJkSl2aamIHJl8Uz6ZeZnqjIwxw4hiVOw/2EqSQEYIIYSoZsqztOTj7oOb1hy8pOSkqIEMQH6a8y8vSSAjhBBCVDOlLS0VnJHRaDRWO5e0ei1aT3N44Ap5MhLICCGEENVIfno+xnRzfktRMzImxaQm9tbwqgFQeOfSlS3YrpAnI4GMEEIIUY1YZmN0fjrc/NwKHU/NScWkmADz0hJQqCieJeHXFWrJSCAjhBBCVCOlFsO7kh/jq/dFrzOfU6gongttwZZARgghhKhG1PYEpexYsiwrQRFLSxLICCGEEMIRylpDJtgrWH3MlYviSSAjhBBCVCNlXVqy5MdA4RkZVyqKJ4GMEEIIUY0YzpXSZ6nA1msLmZGxgXfeeQeNRsOECRPUx3Jychg3bhzBwcH4+voyfPhwEhMTHTdIIYQQwsmVNiNTsD2BRcE2BSCBTLnt2rWLL774gjZt2lg9/txzz7Fq1SqWLVvGpk2biI+PZ9iwYQ4apRBCCOH8ytP52qLQrqUrdWRk+3UZZGRkMGrUKL766iuCgoLUx1NTU5k7dy4ffvghvXr1omPHjsyfP59t27axY8cOB45YCCGEcE6Kolzts1RcVd8y5MjIjEw5jBs3jjvuuIPevXtbPb5nzx7y8vKsHm/WrBkRERFs37692Ovl5uaSlpZm9SWEEEJcD/Iu5aEYzI0e9WHFJPsWkSNTXEE8V0j2LVzyrwotXbqUvXv3smvXrkLHEhIS0Ov1BAYGWj0eGhpKQkJCsdecPn06//vf/2w9VCGEEMLpWZaV3Gu5o9UXPVdRVI6MZWlJZmTKIS4ujmeffZZvv/0WT09Pm113ypQppKamql9xcXE2u7YQQgjhzErreg0lLy1lGDLIM+ZJIFMWe/bsISkpiQ4dOuDm5oabmxubNm1i1qxZuLm5ERoaisFgICUlxep5iYmJ1K5du9jrenh44O/vb/UlhBBCXA9KK4YHRS8tBXgGqN+n5KRIIFMWt912G9HR0ezfv1/96tSpE6NGjVK/d3d3Z926depzjh49SmxsLFFRUY4athBCCOG0SmtPYDAaSDekA9ZLS25aN/z0foA5kLHkyJgyTZjyTfYccqU5LEfGz8+PVq1aWT3m4+NDcHCw+vjDDz/MxIkTqVGjBv7+/jzzzDNERUXRtWtXRwxZCCGEcGql1ZCxbK/WoFHzYiwCPQNJN6STnJPMDSE3qI8bU41ogx2+N6hYDk32Lc3MmTPRarUMHz6c3Nxc+vXrx2effeboYQkhhBBOqbSlJUt+TJBXEDqtzupYkFcQcWlxpOSkoHXXovXWYsoykZ+aj3uwu30HXglOFchs3LjR6mdPT09mz57N7NmzHTMgIYQQwoWoyb51y7712qJQUbwANwxZBqfPk3HeuSIhhBBClEtZO18XzI+xcNWieBLICCGEENWAKd+EIdEcyJSn87XFtY0jXaUongQyQgghRDVgSDCAAuhAH1L+pSWZkRFCCCGEw6jLSmEeaLSaIs8pqmGkhdqmoECODEggI4QQQogqUNrWayg5R+bapSVX6YAtgYwQQghRDRjOXZmRKaYYHpScIyNLS0IIIYRwmLLMyJRp+7Uk+wohhBCiqpXWngCuzsgUuf3aS2ZkhBBCCOEgZWkYacmRKXH7tST7CiGEEKKqlba0pChKmbdfK4oigYwQQgghqk5pyb5ZeVnkGs3BTkkzMkbFSIYhQ3JkhBBCCFE1jFlGdZt0cTMylmUld607Pu4+hY57u3vjrjU3h0zJSZHt10IIIYSoGobz5tkYrZdWXRK6VsGt1xpN4YJ5Go3malG8nGRZWhJCCCFE1Si4Y6moIAVK3nptYVleSslJUQMZU7YJU57JhqO1LQlkhBBCCBdXphoyJRTDs7Ak/CZnJ6Pz16mPO/OsTNHzT9f45ZdfGDBgAO7u7vzyyy8lnnvnnXfaZGBCCCGEKJvybL0uqoaMRcGieFo3LVofLaZMkznht6btxmtLZQpkhgwZQkJCAiEhIQwZMqTY8zQaDUajc2c3CyGEENWNZWlJX7diVX0tiiqKZ8g0uP6MjMlkKvJ7IYQQQjheWWZkSup8bRHoEQhYF8UzxDt3IGOTHJmUlBRbXEYIIYQQFaDOyJQhR6akpaVCMzIusAW73IHMu+++y/fff6/+fPfdd1OjRg3q1q3LgQMHbDo4IYQQQpTOkuxbUp+lktoTWFzbONIVtmCXO5D5/PPPCQ8PB2Dt2rX89ddfrFmzhgEDBvDCCy/YfIBCCCGEKJ6iKGVbWipLjoyn9YyMK1T3LVOOTEEJCQlqIPPrr78yYsQI+vbtS/369enSpYvNByiEEEKI4uWn5GPKNuevVnr7dYGCeFBNZ2SCgoKIi4sDYM2aNfTu3RswR4SyY0kIIYSoWpbZGLcgN3ReumLPK8/264K7lsC5A5lyz8gMGzaM++67j8aNG3Pp0iUGDBgAwL59+2jUqJHNByiEEEKI4pWlGJ5JMV3NkSnD0lLBXUtQzQKZmTNnUr9+feLi4pgxYwa+vr4AnD9/nqeeesrmAxRCCCFE8Qq2JyhOak4qJsW8/FSeZN9qmSPj7u7OpEmTCj3+3HPP2WRAQgghhCi78tSQ8dX7otcVP3NjyZHJysvCYDS4xPZraVEghBBCuLCyLC2VJT8GIMAjQP2+YONIl19akhYFQgghhHMynLsyI1PC0lJZtl4D6LQ6/D38SctNIyUnhZCAEKAaBDLSokAIIYRwTrbqfG0R6BlIWm4aydnJ1AmoAzh3IFPu7denTp2yxziEEEIIUQFqsm8ZiuGVtrQE1kXxXCHZt9yBTKNGjejZsyeLFy8mJyfHHmMSQgghRBkoRgVDQulLS2XZem1RsCieJUfGlGPCZHDOFZlyBzJ79+6lTZs2TJw4kdq1a/P444/zzz//2GNsQgghhCiB4YIBjIAG3EPdiz2vLJ2vLQoWxXPzv5qB4qzLS+UOZNq1a8fHH39MfHw88+bN4/z589x88820atWKDz/8kAsXLthjnEIIIYS4hiXRVx+qR+tW/Ed6eXJkChbF0+g06PzMy0vVJpCxcHNzY9iwYSxbtox3332XEydOMGnSJMLDwxk7diznz5+35TiFEEIIcQ010bdu8Ym+UL4cmWLbFDhpLZkKBzK7d+/mqaeeIiwsjA8//JBJkyZx8uRJ1q5dS3x8PIMHD7blOIUQQghxjbIUw4Ny5sh4WjeOdPaE33JX9v3www+ZP38+R48e5fbbb+ebb77h9ttvR6s1x0QNGjRgwYIF1K9f39ZjFUIIIUQBlh1LJW29hvJvvwbX6YBd7kBmzpw5PPTQQzzwwAOEhYUVeU5ISAhz586t9OCEEEIIUTzL0lJJO5agnNuvva5uv4ZqGMgcP3681HP0ej33339/hQYkhBBCiLIpy9JSnjGPdEM6UL5dS67SAbvcgYxFVlYWsbGxGAwGq8fbtGlT6UEJIYQQonTq0lIJyb6W/BgNGjVIKUnBgnhQDXNkLly4wAMPPMCaNWuKPC69loQQQgj7U0wKOTHmwrSe4Z7FnmfJjwnyCkKn1ZV63YIF8YCrHbCddEam3LuWJkyYQGpqKjt37sTLy4s1a9awcOFCGjduXGpnbCGEEELYRvaJbIzpRrSeWryaehV7XnnyY8B6+7WiKE6//brcMzLr16/n559/plOnTmi1WiIjI+nTpw/+/v5Mnz6dO+64wx7jFEIIIUQB6XvMeS8+bX1KLIZXnq3XcHVpyaSYSDekO32OTLlnZDIzMwkJMbf1DgoKUiv5tm7dmr1799p2dEIIIYQokiWQ8evoV+J55dl6DeDp5oleZ865SclJqX6BTNOmTTl69CgAbdu25YsvvuDcuXN8/vnnxW7HFkIIIYRtZezJAMCvQymBTFbZ+ywBaDQaqzYF1S7Z99lnn1XbD7z22mv079+fb7/9Fr1ez4IFC2w9PiGEEEJcQzEppO81z8j4dvQt8VzLjExZc2TAnCeTmJlIck4ykQGRgPPOyJQ7kBk9erT6fceOHTlz5gz//fcfERER1KxZ06aDE0IIIURh2aeyMaYZ0Xho8GnpU+K55c2RAeuieM6+tFThOjIWer2eJk2a4OtbckQohBBCCNuwLCv5tvFF615ylkh5c2TAuiieW7BzBzJlzpFZtWpVoaWjt99+G19fXwIDA+nbty/JycnlevE5c+bQpk0b/P398ff3JyoqitWrV6vHc3JyGDduHMHBwfj6+jJ8+HASExPL9RpCCCFEdVPWRF8o//ZrsC6KZ5mRUXIVjDnOlydT5kDmww8/JDMzU/1527ZtTJ06lVdffZUffviBuLg43nzzzXK9eL169XjnnXfYs2cPu3fvplevXgwePJh///0XgOeee45Vq1axbNkyNm3aRHx8PMOGDSvXawghhBDVjSWQKS0/Biq4tFSgA7bOTwca8+POmPBb5qWlf//9lw8//FD9efny5fTp04eXX34ZAE9PT5599lmrc0ozaNAgq5/ffvtt5syZw44dO6hXrx5z585lyZIl9OrVC4D58+fTvHlzduzYQdeuXcv8OkIIIUR1oSgKGXvLtmMJKre0lJKTgkarQeenw5hmJD81H31oyZ22q1qZZ2TS09MJDr56E7Zs2cJtt92m/tyyZUvi4+MrPBCj0cjSpUvJzMwkKiqKPXv2kJeXR+/evdVzmjVrRkREBNu3by/2Orm5uaSlpVl9CSGEENVFTkwO+Sn5aPQafFqVnOirKEq5t19DEW0KnDjht8yBTN26dTly5AgAGRkZHDhwgJtuukk9funSJby9vcs9gOjoaHx9ffHw8OCJJ55g5cqVtGjRgoSEBPR6PYGBgVbnh4aGkpCQUOz1pk+fTkBAgPoVHh5e7jEJIYQQzkqt6NvaB62+5I/xrLwsco3mxpLl3X4NVxtHVotA5u6772bChAksWrSIRx99lNq1a1st7+zevZumTZuWewBNmzZl//797Ny5kyeffJL777+fw4cPl/s6FlOmTCE1NVX9iouLq/C1hBBCCGdTnkRfS36Mu9YdX33ZdxcXLIgHzt0Bu8w5MlOnTuXcuXOMHz+e2rVrs3jxYnS6q100v/vuu0I5L2Wh1+tp1KgRYK5Ls2vXLj7++GPuueceDAYDKSkpVrMyiYmJ1K5du9jreXh44OHhUe5xCCGEEK5Arehblh1LBfJjNBpNmV9D3X7tAh2wyxzIeHl58c033xR7fMOGDTYZkMlkIjc3l44dO+Lu7s66desYPnw4AEePHiU2NpaoqCibvJYQQgjhShRFqdDW6/Lkx4B1QTzAqTtgV7ogXmVMmTKFAQMGEBERQXp6OkuWLGHjxo388ccfBAQE8PDDDzNx4kRq1KiBv78/zzzzDFFRUbJjSQghxHUp53QO+cn5aNxLT/SFirUnAOuCeODcOTIODWSSkpIYO3Ys58+fJyAggDZt2vDHH3/Qp08fAGbOnIlWq2X48OHk5ubSr18/PvvsM0cOWQghhHAYy7Zrn1Y+aD1KT3NVa8iUY+s1XM2Ryc7PJjc/VwKZ4sydO7fE456ensyePZvZs2dX0YiEEEII51WeZSWo+NKSv4e/+n1KTopTJ/uWedeSEEIIIRyrPBV9oeJLSzqtjgCPAMD5G0eWKZCpUaMGFy9eBOChhx4iPT3droMSQgghhLXyJvpCxdoTWBQsiufygYzBYFAr5C5cuJCcnBy7DkoIIYQQ1nJjc8m/lI/GTYNP69ITfaFi7QksChbFc/nt11FRUQwZMoSOHTuiKArjx4/Hy8uryHPnzZtn0wEKIYQQ9pK4NBGvRl74d/Iv/WQHS997paJvKx90nrpSzjaraI4MWBfFc/nt14sXL2bmzJmcPHkSjUZDamqqzMoIIYRwaWm70jgy8gjuoe7cdO4mNLqyF4xzBDU/pkPZK/RWNEcGrGdknDnZt0yBTGhoKO+88w4ADRo0YNGiRVYNJIUQQghXk7olFYC8xDxSt6cSeHOgYwdUivJU9LWo6PZrKDAjk5OMW+2rS0uKopSrSrC9lXvXUkxMjAQxQgghXF7azjT1+0s/X3LgSEpXkURfk2KqVLJvwaJ4lqUlJU/BlGMq97XsqUwzMrNmzeKxxx7D09OTWbNmlXju+PHjbTIwIYQQwp7Sd17dgXvx54s0nNHQqWYaCso9m0vehTzQgU+bsiX6puakYlLMQUdFlpYKtinQ+epAAyjmWRmdV9lydKpCmQKZmTNnMmrUKDw9PZk5c2ax52k0GglkhBBCOD1DkoGc0zmgAY2bhuzj2WT9l4VP87IFCVXNMhvj09KnzEGEJT/Gx90HD7fyN1Mu2DhSo9Wg89dhTDWa82SK791c5coUyMTExBT5vRBCCOGK0v4xLyt5N/fGM8KTy2suc/Hni04byFhaE1RVfgxczZFRG0cGumFMNTrdFuxKV/Y1Go3s37+f5ORkW4xHCCGEsDvLspL/jf4EDzZ/0DtznkyFdixVYus1WBfEA+ftgF3uQGbChAlqjySj0cgtt9xChw4dCA8PZ+PGjbYenxBCCGFzlkRfvy5+1LyzpvpYbkKuI4dVpIok+kLltl6D9fZrcN4O2OUOZJYvX07btm0BWLVqFadPn+a///7jueee4+WXX7b5AIUQQghbUkwK6buuzMh08cejjgd+nf1AgUurnG9WxhBvIC8xD7Tg27YCMzKVXFpKzr5mRsbVA5mLFy9Su7Y5y+f333/n7rvvpkmTJjz00ENER0fbfIBCCCGELWUfzyY/JR+tlxafVuacmJqDzbMyF3++6MihFUlN9G3hg8677LuFKrP1Gq7OyKTmmnc/OWtRvHIHMqGhoRw+fBij0ciaNWvo06cPAFlZWeh0zrMdSwghhCiKZVnJt4MvWnfzx6AlTyb5r2TyM5xrxqG8Ha8t1D5LlcyRMSkm0nPTq8+MzIMPPsiIESNo1aoVGo2G3r17A7Bz506aNWtm8wEKIYQQtmQJZPy7XO2v5NPSB8+Gnii5Csl/ONfmlYrsWILK58h4unnioTNv23bmDtjlDmRef/11vv76ax577DG2bt2Kh4f5Tep0Ov7v//7P5gMUQgghbCn9n6v5MRYajcZpl5fURN8O5QtkKrv9GqyL4jlrB+wy1ZG51l133QVg1Tjy/vvvt82IhBBCCDsx5hjJOHBlhuNG68Cg5uCanJ15lku/XcKUb0LrVukKJZWWez4Xw3mDOdG3XTmXliq5/RrMeTIJGQkkZycTEhACVIPt10ajkTfffJO6devi6+vLqVOnAHj11VfVbdlCCCGEM8rYl4GSp+Ae4o5npKfVMf9u/rjVcCP/cr7aUNLRLLMx3s280fmULw9VzZGpzIxMgaJ41SbZ9+2332bBggXMmDEDvV6vPt6qVSu+/vprmw5OCCGEsKWC+THX9lXSumkJHuhcxfEq0vHawjIjU9EcGbAuildtcmS++eYbvvzyS0aNGmW1S6lt27b8999/Nh2cEEIIYUtF5ccUVDBPRlGUKhtXcSpSCA8gz5hHusH83MouLcGVHJnqEsicO3eORo0aFXrcZDKRl5dnk0EJIYQQ9qBW9L2x6MCgRr8aaD215MTkkHkosyqHVqT0vRXbem1J9NWgUYORiihYFK/aBDItWrTg77//LvT48uXLadeunS3GJIQQQtic4YKBnFPmTSp+nYsOZHQ+OoJ6mz+8Hb17yZBowHDOAJoKJPpeyY8J9AxEp614jbeCMzIFc2ScYbbKoty7lqZOncr999/PuXPnMJlMrFixgqNHj/LNN9/w66+/2mOMQgghRKVZlpW8m3njHuhe7HnBg4O59OslLv18ifqv1K+i0RWmJvo29cbNt3wf15VtT2ChzsgUyJFR8hVM2aZyVRm2p3LPyAwePJhVq1bx119/4ePjw9SpUzly5AirVq0iKirKHmMUQgghKi3tn6uNIktSc1BN0ED67nRyzzmuiWRFK/pC5dsTWFjNyPjq1KjBmZaXyhzIzJw5U/2+e/furF27lqSkJLKystiyZQtRUVH069fPLoMUQgghKkvdsXRj0Ym+FvpQPf5dzedc/MVxy0sVTfQF22y9ButdSxqN5mqejBPVkilzIPPSSy/xzTffFHksMzOT/v37c+mSc2xXE0IIIQpSFKXUHUsFOUOVX0dvvYarMzLO3AG7zIHMokWLePzxx/nll1+sHs/IyKBfv35cuHCBDRs22HyAQgghRGVlH88mPzkfracWnzY+pZ5vaSKZsj7FIR/ahiQDuWfNy1q+7R23tFSwIB7glEXxyhzI3HXXXXzyySeMHDmSjRs3AuaZmAEDBpCYmMjGjRsJCwuz1ziFEEKICrPkxxTseF0Sn2Y+eDXxQslTuLzmsr2HV4hl27VXEy/c/MrfTaiyna8tCi4tgYvPyAA88sgjvPbaawwePJiNGzcyYMAA4uPj2bBhA3Xq1LHXGIUQQohKSd95ZVmplPyYghy5vFSZZSWwXY6MZWkpJz+HnPwcpwxkyh3mTZ48mcuXL3PbbbdRv359Nm7cSL169ewxNiGEEMIm1EJ4pexYKqjm4JrEvRfHpd8vYcozlWkmx1Yqk+gLtsuR8ffwR4MGBcVpq/uWOZAZNmyY1c/u7u7UrFmTZ5991urxFStW2GZkQgghhA0Yc4xk7DfPcJQl0dfCv6s/7rXcybuQR8qmFGr0rlxQUB6V2XoNtsuR0Wq0BHgGkJKTYg5kAs1hgzPlyJQ5kAkICLD6eeTIkTYfjBBCCGFrmQcyzR2va7rjWd+z9CdcodFpCB4UTMK8BC79fKnKAhnDRQO5seZEX7/2jl1aAnPCb0pOCsnZyYQGhALOtf26zIHM/Pnz7TkOIYQQwi4KLitd2/G6NDUH1yRhXgIXf75Io1mNyv38isjYa5498mrspS7llIeiKDZbWgLronh1A+oCzrW0VHULfkIIIYQDqIXwyrGsZBHUJwitt5bcuFx1ecre1GWlDhVbVsrKyyLXaJ7RqezSEljvXHLGHBkJZIQQQlRrlQlkdF46avQ1z2pU1e6lyib6WvJj3LXu+OorFgwVVLAongQyQgghRBXKu5RHzsmSO16XxlIc79LPVVO93pZbr22xFFawKJ5LF8QTQgghXI2lEJ5XEy/cg4rveF2S4IHBoIWM/RnknMmx5fAKybuUR85p82tUdGnJlvkxUHQHbJmREUIIIapAZZaVLPQ19QR0M+/ctXcTSUtFX88bPHEPrFjgZaut1xYFk30t268lkBFCCCGqgFrRtxKBDBSo8vuTfQMZy46lii4rgW23XkPxyb6Kotjk+pUlgYwQQohqSVEUdWnJ78aKBwZQoInkphTykvMqPbbiVDbRF64uLdllRsayHdwIxkznyJORQEYIIUS1lH0ym/zL+Wg8NPi2rdzuHe9G3ni38AYjXP7dfk0kK7v1Gq7OyNg8RyY7Ga23Fsz5vk6T8CuBjBBCiGrJsqzk194Prb7yH3f2biKZl5xHzqkrO6w6VHxGxp45MhqNxukSfiWQEUIIUS2pFX0ruaxkYQlkLq++jCnXZJNrFmTJj/Fs4Il7jYol+oJ9c2QACWSEEELYxux/ZtPkkybEJMc4eihOyZIfU9lEXwu/zn7ow/QYM4wkb0i2yTULskV+DNh++7VlRiY1JxWTYpJARgghhG28v/19jl8+zrLDyxw9FKdjyjWRsa/8Ha9LotGam0iCfYrjWbZeV7TjtYU6I2OjpSVLjoyCQlpumtN1wJZARgghXNDplNOcTjkNwIHEA44djBPKOJCBYlBwC3bDs2HZO16XRs2T+eUiism2248rW9HXQs2RsdHSkoebB15uXoA54ddS3ddZOmA7NJCZPn06nTt3xs/Pj5CQEIYMGcLRo0etzsnJyWHcuHEEBwfj6+vL8OHDSUxMdNCIhRDCOWw8vVH9/kCCBDLXUgvh3ehv047Vgb0C0fnqMMQb1KUgW8hPzSf7RDZQuURfk2KyebIvFL0FW5aWgE2bNjFu3Dh27NjB2rVrycvLo2/fvmRmZqrnPPfcc6xatYply5axadMm4uPjGTZsmANHLYQQjrfh9Ab1+/8u/kdOvn1L57ua9H9sUwjvWjpPHTX6276JpGVZySPSA/fgiif6WvJYwHY5MuDcHbAdGsisWbOGBx54gJYtW9K2bVsWLFhAbGwse/bsASA1NZW5c+fy4Ycf0qtXLzp27Mj8+fPZtm0bO3bscOTQhRDCYRRFYUPM1UDGqBj5N+lfB47I+ag7lrrYZsdSQfZoImmzRN8r+TE+7j54uHlUelwWMiNTRqmpqQDUqGGOIvfs2UNeXh69e/dWz2nWrBkRERFs3769yGvk5uaSlpZm9SWEENVJTEoMcWlxuGvd6VqvKwD7E/Y7dlBOJO9yHtnHzcs0/jfadkYGIPj2YNBB5qFMsk9l2+SazpofY1GwKJ6zdcB2mkDGZDIxYcIEunXrRqtWrQBISEhAr9cTGBhodW5oaCgJCQlFXmf69OkEBASoX+Hh4fYeuhBCVCnLbEyXel24qd5NgCT8FqR2vG7kVal6LMVxr+FO4C2BgO2WlyxLS7baem3L/BiQGZkyGTduHIcOHWLp0qWVus6UKVNITU1Vv+Li4mw0QiGEcA6W/JgekT1oW7stIDMyBVnyY+yxrGRhyyaS+Wn5ZB8zz+xUpjUB2L49gYU6I5OT7HQdsJ0ikHn66af59ddf2bBhA/Xq1VMfr127NgaDgZSUFKvzExMTqV27dpHX8vDwwN/f3+pLCCGqC0VR1B1LPRv0pF3tdoB5RsZZuhE7mrpjycaJvgVZ8mRSt6RiuGio1LUs9W48wj3Q19JX6lr2WloqckZGtl+b/4d8+umnWblyJevXr6dBgwZWxzt27Ii7uzvr1q1THzt69CixsbFERUVV9XCFEMLhTlw+wbn0c+h1eqLqRdGsZjPcte6k5aapdWWuZ4qiVEkg41XfC582PmCCy79VromkrRJ9wX5LS7JrqRjjxo1j8eLFLFmyBD8/PxISEkhISCA72zzFFhAQwMMPP8zEiRPZsGEDe/bs4cEHHyQqKoquXbs6cuhCCOEQlmWlqHpReLl7odfpaRnSEpA8GYCcUznkX8pHo698x+vSWJaXkpYloRgrPhumdryuZEVfsN/SkmVGRpJ9rzFnzhxSU1Pp0aMHYWFh6tf333+vnjNz5kwGDhzI8OHDueWWW6hduzYrVqxw4KiFEMJx1PyY+j3Ux9qGmvNkpDDe1URf33a+aD3s+xFXc8iVJpK/XWZ75HZOTj5JxsGMcl/HpjMyNm5PYGHJkbFaWkrLd4rlTDdHvnhZboCnpyezZ89m9uzZVTAiIYRwXlb5MfV7qo9bApn9ifsdMCrnUhXLSha+7X1p8HYD4t6Pw3DOQNx7ccS9F4dPax9CR4cScl8InvVKbo+Qn3410dcWgYzdtl8XsbSECYwZRtz8HBpKOEeyrxBCiNIdvXSUhIwEPN086VKvi/q4mvArMzKk77wyu3Gj/XYsWWg0GiJfiuSm8zfRcmVLag6viUavITM6k1MvnmJHxA7299rP+Xnni80nydifAQp41PNAH1K5RF+omu3XWi8tGjdz2wdnyJORQEYIIVyEpX5MVL0oPN2u/kvfsgU7JiWG1JxUh4zNGZgMJtL32ac1QUm0HlpqDalFq+WtuCnxJpp81YSAWwNAgZQNKRx9+ChbQ7fy74h/ubjqIiaDSX2umh9TyW3XFnbffp2djEajcaoO2BLICCGEi9h4ZiNgvawE5g+tcH9z8c+DiQerelhOI+NgBkquglsNN7waeTlkDO6B7tR5pA7tN7an6+muNJjeAO8W3ii5CheWXeDQnYfYVmcbx8YdI3V7Kum7bZcfAwVmZOy0/TrXmEtOfo5TdcCWQEYIIVzAtfVjriWF8a4uK9m643VFeUZ6Evl/kXQ+1JmO+zpS7/l66MP05F/KJ/6zePbdtI+kb5MA2wQyecY80g3me2DrpSU/Dz+0GnPIkJztXFuwJZARQggXcPjCYZIyk/By86Jznc6FjrcLbQdc31uw1UaRVZAfUx4ajQa/dn40er8RUXFRtPmzDaFjQ9H6mD+CNe4a/DrbLtFXg0adQbEVrUZLgEcA4HxtChybaiyEEKJMLLMx3SK6FdnVWGZkqnbHUkVpdBpq9KlBjT41aPJZEy6tvoR7TXfbJPpeyY8J9AxEp9VV+nrXCvIKIjknmeScZPwDzPdYAhkhhBBlYqkfc21+jIVl59KhpEPkm/Jx015ff97zkvOubmN2shmZ4uh8dITcFWKz69lr67VFwZ1LQQHm5F9J9hVCCFEqk2JSZ2QKFsIrqGFQQ3z1vuQaczl26VjVDc5JpO8y54Z43uCJvmblZzdckb22XlsU3LnkTEtLEsgIIYSTO5R0iEvZl/Bx9ykyPwbMOQytQ1oD1+fykrqsdKPzLivZm722XltYFcVzog7YEsgIIYSTs8zG3BxxM+4692LPu54L47lCfoy92WvrtUWgRyDgfMm+EsgIIYSTKy0/xuJ6bVWgKArp/1ypx9LFNfJj7EHNkbHX0pJXEUtLUkdGCCFESUyKiU2nNwHF58dYXK8zMjmnc8i7kIfGXYNvO/t2vHZm9moYaVEw2deZOmBLICOEEE7sYOJBknOS8dP70bFOxxLPbRXSCg0aEjMTSchIqKIROp5lWcm3rS86T9tvO3YVds+R8SzcOFKWloQQQpTI0l+pe2T3UrdU++h9aBLcBLi+ZmXURpHX8bISVEGOTIEZGQlkhBBClIklP6ZHZI8ynX89FsZL+0cSfaEKc2RkRkYIIURZGE1GNp/ZDBTdX6ko11urAlOeiYy9GcD1vfUaCuTIVMWMjKX7dZoRxaTY5fXKSgIZIYRwUvsT9pOam4q/hz/ta7cv03MsMzLXSyCTeTATU44Jt0A3vBo7puO1M1AURV1asnuOTHaymuyLAsYMxyb8SiAjhBBOyrKsdEvkLWXunWPZgv3fxf/Izsu229icRcFGkRqt4zteO0p2fja5xlzA/ktLqbmpoAeN3ny/Hb0FWwIZIYRwUpZCeKXVjymojl8danrXxKSY+PfCv3YamfOQ/Bgzy2yMu9YdX719tqAX7KidlpvmNHkyEsgIIYQTyjflX82PKUcgo9ForhbGuw4SftUdSy7SKNJeCm691mjsMzOl1+nxdvcGnCvhVwIZIYRwQnvP7yXdkE6gZyBtQtuU67nXS2G8vJQ8sv7LAmRGxt5bry2csSieBDJCCOGELPVjbo28tcz5MRbXS6uClPUpAHg28ERf6/rseG1h763XFs7YAVsCGSGEcEIbz2wEyresZGGZkTmYeBBFcezWWHsx5ZuIeTUGgFp31XLwaBzP3luvLYragi2BjBBCCCt5xjz+PvM3UPb6MQU1q9kMvU5PWm4ap1NO23h0ziFhXgJZh7Nwq+FGxJQIRw/H4dSt15722Xpt4YxF8SSQEUIIJ7M7fjeZeZkEewXTKqRVuZ/vrnOnZa2WQPVM+M1Pzydmqnk2pv7U+rgHuTt4RI7nkBkZJ+mALYGMEEI4Gcu261vr34pWU7E/09W5MF7ce3HkJebh1ciLOk/WcfRwnIIjcmQk2VcIIUSRLIXwKpIfY1Fdt2Dnnssl7v04ABq+2xCtXj7GwP6dry0sgYwzNY6U3wAhhHAiBqOBrXFbAehRv0eFr6Nuwa5mMzIxr8Rgyjbh382fmkNrOno4TqOqt19LjowQQogi7Tq3i6y8LGp511LzXCrCMiNzOuU0KTkpNhqdY6XvTydhYQIAjT5oZLfCb65IzZGx99KSJPsKIYQoiWVZqUf9HpX6oA7yCiIiwLyb52DiQZuMzZEUReHkpJOgQMi9Idd9AbxrqTkyDth+LTkyQgghVAUDmcqqTnkyl1dfJmVdChq9hgbTGjh6OE7FpJjUQKaqcmQKJvvKjIwQQggAcvNz2Ra3Dahcoq9FdWlVYMo3cfKFkwDUG18PrwZeDh6Rc0nNScWkmAD7Ly3J9mshhBDF2nluJzn5OYT6hNKsZrNKX88yI+PqCb9Wxe9edq7id3N2zeG76O8cOgbLbIyPuw8ebh52fa2COTI6/yvbr9ONKEbHVZB2c9grCyGEsGLpr1TZ/BgLy4zMoaRD5JvycdO63p/8/PR8tRVB/dfq4x7oPMXv9p7fy1O/P4UGDZ3qdKJxcGOHjKOqiuHB1RkZg9FAvs/VmZj89HyH/beRGRkhhHAStqgfU1CDoAb46n3JNeZy9OJRm1yzqsXNiCMv6Urxuyecq/jdkuglACgofLD9A4eNQ21PYOf8GAA/vR86jXkmJlVJReNhDrgdmfArgYwQQjiBnPwcdpzdAVSsv1JRtBotbULbAK6Z8JtzNoe4D64Uv5vhXMXvTIqJ7//9Xv15wf4FJGQkOGQsVbX1GkCj0RSdJ+PAhF/n+a0QQojr2Pa47eQac6njV4fGNWy3RNEutB3gmnkyluJ3Ad0DqDnEuYrfbYndwtm0s/h7+NOpTidyjbnM2jnLIWOpqq3XFmpRvOxkp+iALYGMEEI4AVvVj7mWpeeSq83IpO9LJ/GbRABueP8Gpyt+Z0nwHdZ8GC93fxmAz3Z9RnpuepWPpao6X1s4W1E8CWSEEMIJWBpF2io/xsKS8Ls/YT+KYtudJbvjd3PzvJtZH7Pepte1Kn43MgT/G52r+F2eMY9lh5cBMLLVSO5seidNg5uSmpvKl3u+rPLxVGWyLzjfFmwJZIQQwsGy8rKu5sfYOJBpFdIKrUbLhawLNs/heO6P59gat5V7lt9DYkaiza57efVlUtanoPFwzuJ3f536i0vZlwjxCaFXg15oNVpeuOkFAGbumInBaKjS8VRljgw4XwdsCWSEEMLBtsVtI8+URz3/ejQMamjTa3u7e9MkuAlg2zyZbXHb2BK7BYCLWRd5ZNUjNpnxMeWbzLMxQL1n6+FV3/mK3313yLysdHeLu9Ut7aPbjCbMN4xz6efU3UxVxVE5Mik5KdSfWp92f7ej1t21quS1iyKBjBBCOJilfkzP+j3tkguiFsazYYXfd7e+C8BtDW5Dr9Pz67Ff+Xrv15W+bsLcBLKOZOEW7EbEFOcqfgeQnZfNyv9WAuZlJQsPNw8mdJ0AwIytM9RKu1WhKrdfQ4EZmZxkfNv4EnhzIPoQfZW8dlEkkBFCCAfbeGYjYPtlJQs1TyZxv02ud+TCEX45+gsaNMy+fTbTek0DzEtNJy+frPB189PziZnqnMXvLH4//jsZhgwiAiKICo+yOvZ4x8fx9/DnyMUj/HbstyobU1UvLRWckXEGEsgIIa5biqLYPAG2vDIMGfxz7h/ANo0ii2LrGZn3tr0HwJBmQ2hasynPRT3HrZG3kpmXyZiVY8g3VSzxM/bdWHPxu8ZlL35XlTMfcHVZ6d6W96LVWH+EBngG8GSnJ4GrM1ZVoaqXlgruWnIGEsgIIa5L8enxtP+iPe2+aMe5tHMOG8fW2K3km/KJDIikQZB9ElstMzJHLx0lOy+7Utc6l3aOxQcXAzC522TAXHhv4ZCF+On92H52OzO2zij3dXPO5nD2g7PAleJ37qV/PP116i+CZwQzfvX4cr9eRaTlpvHrsV8BGNl6ZJHnPNvlWfQ6PVvjtrI1dqvdx5RnzCMtNw2o+mRfmZERQggHuZx9mX6L+3Eg8QAHEw/Sb3E/9V+1VU3ddm2jar5Fqe1bm1retTApJg4lHarUtT7a8RF5pjxuibyFrvW6qo9HBkby6e2fAvDaxtfYe35vua4b80oMppwrxe8Gl178bufZnQxZOoSUnBRm75rNqeRT5XsjFfDTfz+Ra8ylWc1m6izXtcL8whjbZiwAM7aVP6ArL8vvrYarFXftrWBBPGcggYwQ4rqSachk4JKBHEo6RJhvGHX86vDvhX+5/dvbyTBkVPl4bN1fqSgajcYmhfFSclL4Ys8XALzY7cVCx8e0GcPw5sPJN+UzesXoMs/+WBW/+6D04nf/Jv3L7UtuJzMvE51Gh0kx8cE2+/c6siwrjWw1ssQxTrppEho0/HL0Fw5fOGzXMVnyYwI9A9FpdXZ9LQvL0pLMyACbN29m0KBB1KlTB41Gw08//WR1XFEUpk6dSlhYGF5eXvTu3Zvjx487ZrBCCJeXm5/LsB+Gsf3sdoI8g/hzzJ+sHbOWGl412HluJ8O+H0Zufm6VjSc9N53d8bsB++XHWNiiVcHnuz8n3ZBOq5BWDGg0oNBxjUbD5wM/p7ZvbY5cPMKUdVNKvaaiKJx8/krxu/tC8O9ccvG70ymn6bu4L5ezL9OlbhdW3LMCgHn753Eh80LF3lgZXMi8wNqTawHr3UpFaVqzKUOaDQHg/W3v221MUPX5MVBgRkZyZCAzM5O2bdsye/bsIo/PmDGDWbNm8fnnn7Nz5058fHzo168fOTk5VTxSIYSrM5qMjFk5hj9P/om3uze/3fcbrUJa0aJWC1aPWo2Puw9rT61l9MrRGE1VU9xrS+wWjIqRhkENiQiw71Zjy4xMRQOZnPwcPtrxEQCTb5pc7IxETe+azLtzHgAf7/yYv079VeJ1L/9+mZQN5uJ3DaeVXEMnMSORPov6EJ8eT4taLfjtvt8Y1GQQnep0Iic/h0/++aT8b6yMlh9ejlEx0jGsI42DS++FZZmxWnxwMWfTztptXFW99Rqu5sik5aZV2f8rJXFoIDNgwADeeusthg4dWuiYoih89NFHvPLKKwwePJg2bdrwzTffEB8fX2jmRgghSqIoCk/99hTLDi/DXevOyntWWm2dvbHujfx070/odXqWH17OE78+USW7mapiWcnCkvB7IOFAhXb6LDqwiMTMRML9w7m31b0lnjug8QB1984DPz1QbC6FKd/EyReuFL+bUA/PSM9ir5mSk0K/xf04cfkE9QPr8+foPwn2Dkaj0ahBw6f/fGq35cGCy0pl0aVeF26JvIU8U54aANpDVW+9BqxycVJzU6vsdYvjtDkyMTExJCQk0Lt3b/WxgIAAunTpwvbt24t9Xm5uLmlpaVZfQojr28vrX+bLvV+iQcPiYYvpe0PfQuf0btibJcOWoNVo+Xrf12VaFqmMP078wbx95pkLey8rATQNbopepyfdkM7plNPleq7RZFS3XE+Mmoi7rvT6Lu/1eY/GNRpzLv0c434fV+Q5MS/HqMXvIqdEFnutrLwsBn03iAOJBwjxCeHP0X9S17+uenxos6E0qtGI5Jxk5u6dW673VhZxqXH8Hfs3GjTc0+qeMj/PEmB9secLu+WTWGZkqnJpyV3njo+7D+AcCb9OG8gkJJh7goSGhlo9Hhoaqh4ryvTp0wkICFC/wsPD7TpOIYRze3/b+0zfMh2Azwd+zoiWI4o9d3iL4Xw50Nz0792t7/Le1vdsPp7c/Fye/+N5+n/bn0vZl2gT2kbNp7And507rUJaAeVP+P3pv584fvk4QZ5BPNLhkTI9x0fvw6Khi9BpdHx36Du1W7RF7HuxxM2IA6DRR43U5oPXyjPmMWLZCLbEbiHAI4A/Rv9RaGlHp9UxKWoSAB/u+JA8Y1653l9pvv/3ewC6R3annn+9Mj9vQKMBtAppRYYhgzm75th0TBZqjkwVzsiAcxXFc9pApqKmTJlCamqq+hUXF+foIQkhHGTevnm8sNbczG/6bdN5rONjpT7n4Q4PM6O3edvs5L8m26TsvsV/F/+j69yufLjjQwDGdR7Hjod34Kv3tdlrlKQihfEURVGLu43rPK5cY+1Srwuv3PIKAE/9/pSaK3J+7nlOTTZvl274bkNqj65d5PNNiokHfn6A347/hpebF7/e96u6RHat+9vdT4hPCLGpsWrgYSvlXVay0Gg0TL7JXGvn450fk5Nv+/xOy9JSVebIgHMVxXPaQKZ2bfMvdmKidUfVxMRE9VhRPDw88Pf3t/oSQlx/VhxZwaOrHgVgUtSkIrcLF+eFbi+o5z/+6+P8ePjHSo1FURS+3vs1Hb/syP6E/QR7BfPzvT/z6e2f4uVedU0RK9KqYNOZTeyK34WnmyfPdHmm3K/5cveX6VynMyk5KTz484MkLk/k6GNHAQifHE7E5KKTnBVFYfzq8SyJXoKb1o3lI5Zzc8TNxb6Op5snz3Z5FjD3OrJVjtOxS8fYe34vblo37mpxV7mff2+rewn3DycxM5FvDnxjkzEV5IgcGZAZmTJp0KABtWvXZt26depjaWlp7Ny5k6ioqBKeKYS43q07tY6RP47EpJh4qN1DzOgzo9zNGKffNp1HOzyKSTFx34r7St19U5zL2Ze5e9ndPLrqUbLysritwW0cfPIgdza9s0LXq4yKzMhYZmMeavcQIT4h5X5Nd507i4YuwsvNi79O/cW0mdPABGGPhNHwneJ3Kb2+8XVm75qNBg0Lhyzk9sa3l/paT3Z6El+9L9FJ0aw5sabcYy2KZUmsT8M+1PQuvVDftdx17kyMmgiYWzvYepePI7ZfQ4HGkdd7jkxGRgb79+9n//79gDnBd//+/cTGxqLRaJgwYQJvvfUWv/zyC9HR0YwdO5Y6deowZMgQRw5bCGEDiqKw4sgK/jz5Z4V78xRl17ldDPl+CAajgaHNhvLFoC8q1FFao9Ew54453NXiLgxGA0OWDmHn2Z3lusam05to+3lbfjzyI25aN2b0nsGfY/6kjl/Z+giVJut4FucXnMeYXbYPxzahbQA4k3qmTB9ABxMPsubEGrQaLc/f9HyFx9m0ZlPebPwmAJ/3/Jy0UWk0+bxJsf9dZu2cxRub3wDgkwGfcF/r+8r0OkFeQTze8XHANr2OFEWp8LJSQY90eIQgzyBOXD7BT//9VOlxFaQm+1bxjIwzFcVzaCCze/du2rdvT/v27QGYOHEi7du3Z+rUqQBMnjyZZ555hscee4zOnTuTkZHBmjVr8PQsfoueEMI1LIlewvAfhtNvcT/qfViP59Y8x574PZVaEjh84TADvh1AhiGD2xrcxpLh5mWJitJpdSweupg+DfuQmZfJ7Utu59+kf0t9Xp4xj1fXv0rPhT05m3aWxjUas/3h7bzQ7YVCjQYrQlEU4r+IZ3fb3Rx98Ch7b9xLxqHStx0HeQURGWDeHXQw8WCp51t6Jt3d4m4aBpVc46Ukmf9mcuOTN9L5RGcM7gb+d/P/yKPohNxFBxbx7BrzEtEbPd5g3I1F73gqzoSuE3DXurPpzKZyB57X2p+wn6OXjuLp5lmphGxfvS9P3/g0YA6wbLHslWfM46V1L6ktJ8L8wip9zfII9AgEJEeGHj16qN1nC34tWLAAMP+L6I033iAhIYGcnBz++usvmjRp4sghCyFsIDsvm5fWvwSAh86DxMxEPtr5EZ2+6kSLz1rw9ua3y71F+EzKGfou6sul7Et0rtOZlfesxNOt8v/o8XDzYMU9K+haryuXsy/Td3HfEsd2KvkUtyy4hbf+fgsFhYfaPcTex/fSqU6nSo8FIO9SHv8O/5djTxzDlG1Co9eQeSiTPZ32cG72uVI/JMtaGO9MyhmWHloKXG0OWRHZp7M50PcAxstG3oh9gyDPIPYm7uXNTW8WOnfV0VU8+PODgLn5oiVRuDzq+ddjVJtRQOV7HVlmYwY2GYifh1+lrvX0jU/j6ebJrvhdan+tijp5+STd5nVj+pbpKCiM6zxO3ZFWVdRk3+t9aUkIcX2atXMWsamx1POvR9ILSfw68lfubXUvnm6e/HfxP17Z8AoNPm5A9/nd+WL3F6U2dLRUfD2Xfo7mNZuzetTqSn/wFOSr9+W3+36jZa2WxKfH02dRHxIzEgudtyR6Ce0+b8eOszsI8Ajg+7u+Z+7guTbblZS8IZldbXdxceVFNO4abvjgBqJio6hxew2UXIXjTx/n0J2HMFwwFHsNS6uC0rZgf7j9Q4yKkd4Ne9MhrEOFxmtINHCwz0EM8Qa8W3pz24rb+GKguVfTtC3T2B53tSbYptObGLF8BEbFyJg2Y/iw34cVWhIEeOEm8061lUdWcvTi0Qpdw6SY1ECuMstKFiE+ITzU7iGg4gGWoigsOrCIdl+0Y1f8LgI9A1l29zK1WWdVUpN9c1Oq/LWvJYGMEKJKXci8wLQt0wCY1msa/h7+3NHkDr4b/h2JkxKZP3g+tzW4DQ0atsRu4YnfnqD2+7UZ+v1QVhxZUWgLa2pOKv2/7c/xy8eJCIjgzzF/2iXxsYZXDf4c8yf1A+tz4vIJ+i3up+YHpOWmMXblWEatGEW6IZ1u4d048MSBEmvWlIcpz8Spl05x4LYDGM4Z8GriRYcdHQifGI4+VE/rX1vT6ONGaPQaLv16id1tdnN5bdHBX1lmZC5lXeLrfeZt5+XZ7VVQXkoeB/odIPtENp71PWn7Z1vcg925u+XdjG4zGpNiYszKMWQYMth7fi+DvhtETn4Og5oMYu6dcyu1BNeiVgsGNRmEgsIH2yvWTHJb3Dbi0uLw0/sV2VeqIp6/6Xm0Gi1rTqwpV8I1mH/PR68czdifxpJhyOCWyFs4+MTBCu2ksgVJ9hVCXLf+t+l/pOWm0SGsg7oEYOHv4c8D7R7gr7F/EfdcHO/1eY+2oW3JM+Xx038/MfyH4YR9EMZjqx5j85nNZBoyGfTdIPYn7CfEJ4S1Y9aWq2BZedXxq8PaMWsJ9QnlQOIBBn03iI2nN9L+i/YsOrgIrUbL/3r8j40PbCQysPhKteWRdSKLfd32ETs9FhTzbp9Oezvh1+HqjJNGo6He+Hp03NUR7xbeGBIMHOx7kJMvnMRksG5HYNmCfSjpULGF42bvmk1WXhbta7fntga3lXvMxiwjhwYdIvNAJu6h7rRZ2waPOh7q8U8GfEK4fzgnk08yduVY+i/uT7ohnVsjb+X7u74vU+Xg0lgCsIUHFnI+/Xy5n2/ZrTS0+VCbbZFvGNSQu1vcDaBWSi6L7XHbafdFO5ZEL0Gn0fFWz7dYP3Y94QGOK/jqTNuvNUpVNBRxoLS0NAICAkhNTZWaMkI42NGLR2n5WUuMipH1Y9fTs0HZegxFJ0bzbfS3fBv9rVUDPm93b7LysvD38Gfj/RtpH9beXkO3cjDxILfMv8Wqz0xkQCTfDvuWbhHdbPIaiqKQuCiR4+OOY8ww4hboRpOvmhByV8lboI1ZRk5OOkn8nHgAfDv60mJJC7ybeAPmJZPAdwJJN6QT/WR0odyKrLwsIj+K5GLWRZYOX1qukvxgnj06NOQQl3+/jC5AR/tN7fFtW3hpbUPMBnp900v9uUNYBzbcvwF/D9v9ne42rxvb4rbxYrcXeaf3O2V+Xr4pnzof1OFC1gVWj1pN/0b9bTamvef30vHLjug0Ok6MN/eNKo7RZGTa39P436b/YVSMNAhswJLhS+har6vNxlNRm89s5tYFt9IkuAlHn67Y8l1pyvr5LTMyQogqM/mvyRgVI4OaDCpzEAPQOrQ17/R+hzMTzrB+7HoeavcQ/h7+ZOVl4enmya8jf62yIAbM25h/u89cbRbMRc/2P7HfZkFMfmo+R0Yd4b/7/8OYYSTglgA6HexUahADoPPW0eSzJrT6qRVuNdzI2JPB7va7OT/vPIqioNVo1eWlovJk5u+bz8WsizQIbMDwFsPLNW7FpPDfA/9x+ffLaL20tP61dZFBDEDPBj2Z2NVcX6VJcBNWj1pt0yAGrs7KzNk9h7TcsvfdW3dqHReyLlDTu2aFZqRK0iGsA70b9saoGPlw+4fFnhebGkvPhT2ZunEqRsXIqNaj2P/EfqcIYsC5ZmQkkBFCVImNpzfyy9Ff0Gl0zOhTsWRHrUZLzwY9mTt4LgnPJ/DzvT+z85GddI/sbuPRlq5bRDf2PLaHdWPXsWTYEquOwJWRuj2V3e12k/RdEuigwVsNaLe+HZ7h5duBVXNwTTof7Exgz0BMWSaOPnyUw/ceJi85r9jCePmmfN7f/j4Ak26aVK6t64qicHz8cZKWJKFx09Dyx5YE3hxY4nNm9JnB7/f9zo6Hd1So2F5pBjYZSPOazUnLTeOL3V+U+XmW3Up3t7jbJstc17IEWF/v/ZqLWRcLHV9+eDltP2/L37F/46v3ZdHQRSwettjmgV5lFMyRcfTCjgQyQgi7MykmJv1pbur3eMfHaVazWaWv6eXuxZ1N71SLvDlC81rN6dWgV4V31xSkGBVOv3mafd33kXM6B88GnrTf0p7IlyPR6Cp2fY+6HrRd25aG7zRE46bhwg8X2N1uN43TzE0Xr21VsOzfZZxOOU0t71o82O7Bcr3W6ddPEz87HjTQ7JtmBA8oPeFap9UxoPEAdSuvrWk1WnUH00c7PyI3P7fU5+Tk57Dyv5WAbXYrFeW2BrfRIawD2fnZzP5ntvp4piGTR355hLuX3U1KTgo31r2R/Y/vZ3Sb0XYZR2VY/pvlmfLIzs926FgkkBFC2N2S6CXsOb8HP70fr/V4zdHDcTo5sTns77mf01NPgxFCRoXQaX8nAroGVPraGp2GiBcjaL+tPZ43eJIbm4vHC+bE2wMJB9R/TSuKom4LfubGZ8qV4Hr247OceeMMAI0/bUzoyNBKj9tWRrUZRR2/OsSnx/Nt9Lelnr/6+GrSctOo51/PZkuF1yrYTPKTfz4hKy+Lvef30uHLDszdNxcNGl66+SW2PLiFG2rcYJcxVJaPuw86jQ5w/M4lCWSEEHaVnZfNS+vMxe+m3DzFLksIrixpWRK72+4m9e9UdH46mi1qRovFLXDzr3hF4qL4d/an075OhN4fSoOEBmhNWi5kXSDmSAwAa0+tZX/CfrzdvctVTTfhmwROTDgBQP0361P3qbo2HXdl6XV6nuv6HGCuVGxSTCWeb1lWurflvTapwlyc4S2G0zCoIZeyLzH8h+F0/borxy4do65fXdbfv563b3vbLstatqLRaJymA7Zt/08RQohrfLzzY+LS4gj3D2dC1wmOHo5TiZkaw5k3zTMZfl38aPFtC7xusF83bDc/N5ovaE6NfjUI3x7OmeAzLB+xnO7p3Xm5/8tQBwbuH8jRZmXfhZJ71rxcU29CPSJfts2Wc1t7rONjvLX5LY5eOsqqo6sY3Gxwkeel56az6tgqAEa2ts+ykoWb1o1JUZN46ven1AaXw5oP46tBX1HDq4ZdX9tWAj0DuZh10eEJvzIjI4Swm6TMJKb9faX43W3TbFaPozrIic0x14YBIl6KoP3f7e0axBQUOjKUGzveCMCJoBMczDvI7jq70Rl1DPtzGLmxuWX+wgS1H6zNDR/cYJNcIXvw9/Dnqc5PASX3Ovr56M/k5OfQJLgJ7WvbfxfcA+0eoFGNRni5efHlwC9ZfvdylwliwHmK4smMjBDCbv638X+kG9LpGNaxzB2MrxdnPzqLkq8Q2CuQhm9XvCFjRXW8oSPLTi/j8v2XWWNcAwlwd8TdDFhbviq2Ol8dPs197DRK2xnfZTwfbv+Q7We3szVuKzdH3FzonIKdrqsiKPNy92LvY3vRaDQ2a2NRlZxlC7YEMkIIu/jv4n98sce85fX9vu/bNd/A1eRdziP+S3PBuojJEQ4Zg6WWzObkzVzKvgTAS4Newj/Uebb42lJt39rc3/Z+vtz7Je9ufbdQIHMp6xJ/nvwTsN9upaLYsidYVXOWHBn5yyKEsIvJa83F7+5seic96vdw9HCcSvyceEyZJnza+hDU1z5bj0tjaVVwIesCJsXE7Y1vp3Voa4eMpapMumkSGjT8euxXDiUdsjq2/PBy8k35tK/dnqY1mzpohK4l0CMQcPyMjAQyQgib2xCzgVXHVqHT6Hi397uOHo5TMWYbOfuxuc1CxOQIh+WV1PatbbWDzLIduDprHNyYYc2HAfD+tvetjhVcVhJlo87IyPZrIUR1YlJMTFpr2+J31UnCggTyLuThWd+TWiNqOXQslgq/Xep24ZbIWxw6lqpiqar7bfS3xKXGAXAu7Rybz2wGKHdvqeuZJdk3JTfFoeOQQEYIYVPfHvyWvef34qf34/Uerzt6OE5FMSrEvW/+8Kz3fD20bo79E/xQ+4eo51+PGX1mOO2OI1vrXLczPer3IN+Uz8wdMwH4/t/vUVC4OeJmIgIck7PkiizJvjIjI4SoNrLzsnlpvbn43UvdX6KWj2NnHJzNhR8vkHMqB7dgN8IeDHP0cLi31b3EPRd33czGWFhmZb7c8yXJ2cmyrFRBlqUlyZERQlQbH+34iLNpZ4kIiODZLs86ejhORVEUYmeY68bUe6YeOh+dg0d0/ep3Qz/ahLYhMy+TiX9OZHf8bnQaHXe3uNvRQ3Mp6oyM7FoSQlQHSZlJTN8yHYBpvaT43bVS1qeQsScDrZeWOuPqOHo417WCvY4W7F8AQO+GvWUGsZycpSCeBDJCCJt4fePravG7spR3N2YZSd2eSk5cThWMzvFi3zXPxoQ9Eoa+pt7BoxH3tLqHyICrLRVkWan8pCCeEKLaOHLhCF/u+RKAD/p+UGTxu7yUPNK2ppHydwqpm1NJ352OkmcuFR/YI5DQ0aHUHF4T90DnbZRXUen70klemww6qDexnqOHIzD3Ono+6nnGrxmPh86Doc2HOnpILseSI5NuSCfflI+b1jEhhQQyQohKm/yXufjd4KaDubX+rQDkJuSS+ncqqZtTSfk7hcyDmXBNixv3Wu7kXcgjZWMKKRtTODbuGDUH1SR0dCg1BtRAq68ek8ZxM8w7lULuCcGrviy5OYtHOjzCvoR9dK7TGX+P6lnR2J4CPALU71NzUgn2DnbIOCSQEUJUyvqY9fx67Fd0Gh3Ppz/Pfw//R+rmVLJPZBc616uxFwG3BBDYPZCA7gF4NvAkNy6XxCWJJC5KJOtwFheWX+DC8gu41XAjZEQIoaND8b/J32W3B2efyibphyTAce0IRNG83L2YN3ieo4fhstx17vjqfckwZJCckyyBjBDCdSgmhcx/M0nenMzTZ58GTxi0cxDG340kkGA+SQO+bX0J6B6gfnnU9ih0Lc8ITyL/L5KIFyPIOJBB4uJEkpYkYThvIP7zeOI/j8ezgSeho0MJHRWKd1PvKn63lRP3YRyYIKhfEL5tXa8xoBAlCfIMIsOQ4dA8GQlkhBClMuWZyNibQcrmFPNy0ZZU8pPz+aPtHxwZegSfHB8e2PoA/jf5E9A9gMBbAvG/yb9c+S4ajQa/dn74tfPjhndvIHlDMomLErm44iI5MTmcefMMZ948g19nP0JHhxJyTwj6UOdOmjVcMJAwzxzYRbwoszGi+gn0DCQuLc6hO5ckkBEOkZydzM9HfybMN4x+jfo5ejgOcfzScX499iv9GvWjRa0Wjh6OFWOWkbQdaaT+bc5vSduehinLZHVOfN145t8+H4BJzScx8PxAdF62qY2i0Wmo0bsGNXrXwPiZkYu/XCRxcSKX/7hM+q500nelc2LiCWr0rWFOEh5c0ynrspz79BymbBN+nf0I7BHo6OEIYXPOUBRPAhlRZXLzc/nt+G8sPriY347/hsFoAGDx0MWMajPKwaOrOoqiMHffXJ5d8yxZeVnwJ7Sv3Z7RbUYzstVIwvyqvuJrXnIeqVtT1eTc9D1XdxRZuNVww9jTyN8d/+YX71/YlbILgIiACF4c+SI6d/sEEjofHaEjQwkdGYohyUDS90kkLk4k/Z90Lq++zOXVl9H6aKk1rBaho0MJui0Ijc7x+TTGTCPnPj0HQPjkcJfN8RGiJM5QFE+jKIpS+mmuKy0tjYCAAFJTU/H3l6z0qmZSTGyJ3cLig4tZdniZVdRe168u59LPodPo+Pnen7mjyR2OG2gVSc5O5rFfH2P54eUANA1uyqnkU+SZ8gDQarTc1uA2RrcZzdBmQ/Hz8LPLOHLPm3cUWZaKMqML7yjyqOdBQPcA9N31bG2wleWXl7Pm5BryTfnqWPs07MM7vd+hXe12dhlnSbKOZZH4bSKJixPJOXW1Fo2+tp6Q+8xJwr7tfB0WQJz9+CwnJpzAq5EXN/53o1MEV0LY2pd7viQ6MZoRLUfQPbK7Ta9d1s9vCWSEXRy5cITFBxfzbfS3nEk9oz5e168uo1qPYlSbUbQKacX9P93P4oOL8XTz5M/Rf9r8fwRnsvnMZkavGE1cWhxuWjem9ZrG8zc9T3J2Mj/8+wOLoxezLW6ber6XmxdDmw9ldOvR9LmhT4VrNCiKQvbJbPNsy5XgJedk4SJ0Xk28CLzFvJvI92Zfdig7+PbQt/x4+EfSDenqeR3DOjK6zWjubXUvtX1rV2hMtqQoCmk70sxJwkuTyL+crx7zbuFtThK+LxTPSM8qG5Mpz8TORjvJjc2lyedNqPO4VPIVorwkkLlCApmqcz79PEsPLWVx9GL2nt+rPu7v4c9dze9idJvR3BJ5Czrt1SWIPGMew34Yxq/HfsXfw5+N92+kfVh7RwzfbvKMebyx6Q2mbZmGSTHRqEYjvhv+HZ3qdCp07snLJ1kSvYTF0Ys5dumY+niITwj3tryX0W1G06lOpxJnGRSTQuahTKsZF8N5g/VJGvBt56sm5gbcHIA+VM/BxIMsPriYJdFLOJd+Tj09MiCS0W1GM6r1KJrXal75m2InJoOJy2suk7g4kYu/XETJvfrnLeCWAEJHh1Lrrlq4B9m36F7C4gT+G/Mf7qHudD3dFZ2n8+XvCOHsJJC5QgIZ+8owZLDyyEoWRy/mr1N/YVLMCaFuWjcGNBrAmDZjGNhkYIl9d7Lzsun/bX82n9lMiE8IWx7cQuPgxlX1FuzqVPIpRq0YxY6zOwB4sN2DzBowC199ydtwFUVhd/xuFh9czHeHvuNC1gX1WJPgJoxuPZpRbUbRMKghJoOJ9L3ppG5OvbqjKCXf6noavcaccHplxiXgpgDcAswzPGfTzpqDp4OLiU6KVp8T6BnIiBYjGNN2DDeF31RktV5nlp+az4UfL5C4OJGUjSnq0plGryF4YDCho0MJvj0YrYdt35eiKOxuu5vM6EwaTGtA5JTI0p8khChEApkrJJCxj4tZF3lx7Yss/XepOWH1iqh6UYxuM5oRLUdQ07tmma+XmpNKz4U92Zewj8iASLY8tIV6/q5dyn1J9BKe+PUJ0g3pBHgE8MXAL7in1T3lvk6eMY+1p9ay+OBifvrvJ7Lzrxaaa5neEr8kPxSj9f/GGp0GtxpuuAe541bDDbdAtyJzNJKzk9lxdgfKlU95vU7PwCYDGd16NLc3vh0Pt8J1X1xRTlwOSd8lkbgokcxDmerjboFu1H64Ng3eaIDO2zazJpdWXyL69mh0vjq6xna1++yPENWVBDJXSCBje+tj1jNm5Rji0+MBaFyjsbrscEONGyp83aTMJG6edzPHLx+nRa0WbH5gs8MqRVZGWm4aT//+NIsOLgKgW3g3vh32LZGBlf+XeXpuOj/++yNzf57LNrZh0ppKf1IZ3BJ5C6Nbj+auFnep2ymrq4yD5qJ7id8mYog3L7l5N/emxXctbFKwbl+PfaRuSqXe8/Vo9H6jSl9PiOuVBDJXSCBjOwajgakbpjJj6wwUFJrVbMaXA7/k5oibbbYz5EzKGbrN68a59HPcWPdG/hrzl9127tjDP+f+YeSPIzmVfAqtRsvUW6by8i0v26yZWvbJbA7fd5j0f9K56HeRU/efwr+/P/owfYX+G+i0Om6NvNUmQZarUYwKl367xLEnjmE4b0Cj13DDjBuoO75uhX+f03amsbfrXjTuGrqc6oJnvapLMBaiupFA5goJZGzj+KXj3LfiPnbH7wbgsQ6P8WG/D/HR+9j8tY5cOEL3+d25lH2J2xrcxm/3/eb0SxxGk5EZW2cwdeNU8k35RAZE8u2wb+kW0c1mr5GwKIHjTx3HmGHELdCNJl82IeTuEJtd/3pluGjg6MNHufTLJQBqDKhBswXN0IeUv2rwoeGHuLjiIrUfqE2z+c1sPVQhritl/fx2rew9UeUURWHh/oW0/6I9u+N3E+QZxI8jfuSLQV/YJYgBaF6rOatHrcZX78u6mHXct+I+tXaJMzqbdpbei3rz0vqXyDflc0/Le9j/xH6bBTH5qfkcHn2Y/8b+hzHDSED3ADod6CRBjI3oa+pp9VMrGs9ujNZTy+XVl9nVZheX1lwq13WyjmZxceVFAMJfCLfHUIUQRZBApoKq+UQWYC45fd+K+3jg5wfIzMvk1shbOfDEAYY1H2b31+5ctzM/3fMTep2eFUdW8Piqx53ynq84soI2c9qw8fRGfNx9mD94Pt8N/06tdllZqdtT2d1+N0nfJoEO6r9Zn3Yb2uEZIUsWtqTRaKj7VF067OqATysf8hLziB4QzYmJJzDlli0PKe6DOFAgeFAwPi3sE+QLIQqTpaUKemndS3y992siAiKIDIwkMiDS/H1ApPpzDa8aLluWfFvcNu778T7OpJ5Bp9HxRs83eLHbi1Y1YKrCyiMruWvZXZgUE5OiJjGjzwyH39OsvCxWHV3FNwe/4ffjvwPQqU4nlgxbYrNt44pR4cz0M5x+/TQYwbO+J82XNCcgKsAm1xfFM2YbOfXiKc59Yq6j49PWhxbftcCnefHBSe75XHbU34FiUGi/pT0B3eS/kxCVVdbPb+m1VEGnU05zIesCF7IusOf8niLP8XH3UQOdCP9rAp7ASOr41bFZEqit5Jvymfb3NP636X+YFBMNgxqyZNgSutTr4pDxDG0+lK8Hfc1DvzzE+9vfJ9g7mP+7+f+qfBxGk5GNpzeyOHqxVaVbDRpeuOkF3uz1JnqdbTox58TmcGT0EVL/TgUg5L4QmnzWRK37IuxL56Wj8azGBPUN4uiDR8k8kMmejnto9FEjwh4NKzKQPjfrHIpBMXf/liBGiColMzIVlJqTyumU05xJPUNsaixnUs5wJvWM+nNCRkKp19BpdNT1r6vO4hQMdiIDzQGPt7u3zcZcmjMpZxi9cjRbYrcAMKbNGD69/VP8PRyfJP3Btg+YtHYSAF8M/ILHOj5m99dUFOVqpdtDS9Tt5nC10u2YNmNoWrOpzV4zaXkSxx49Rn5KPjpfHY3nNKb2aMe3Abhe5Z7P5b/7/yN5rbkhXs2hNWn6VVPcg6/WhslPy2d7xHaMqUZa/dyKmneWvX6SEKJ4smvpCkftWsrJzyEuNc4c5KSeUQMdy89xqXFqo8CS1PSuWWjZquD3wV7BNllq+eHfH3hs1WOk5qbip/djzh1znK4j9UvrXmL6lulo0LD0rqWMaDnCLq8Tlxqntgk4lHRIfTzIM4gRLUcwus1om1e6NWYaOTHhBOe/Pg+A341+tFjSAq8biq+ILKqGYlI4O/Msp6acQslT0NfV03xRc4J6muvtxL4Xy6nJp/Bu7k3nQ53RaF1zOVkIZyOBzBXOuv3apJhIyEiwDnAKzOqcSTlj1aivON7u3lcDmwLLVpbv6/rXLXH5KsOQwfjV45m/fz4AXep2YcnwJTQMamiz92oriqLw5G9P8sWeL3DXurNq5Cr6Nepnk2un5KTw4+EfWRy9mE2nN1lVuh3UZBCj24xmQKMBdtkGnr43ncMjD5N9LBs0EDElgvqv10frLrn4zqTQf6f/iyDy5Uh2NtmJId5A03lNCXswzNHDFKLakEDmCmcNZMoiJSeFMylnrGZ1YtOuBjzlWb4qKtjRarQ8/fvTHL98HA0aXu7+MlNvnYq7znlLqhtNRkatGMX3/36Pt7s3K+9ZSdPgii3tKJiXjhYdXMSqo6vINeaqx26NvJXRbUYzvPlwu1W6LfJf+oubE9SjelfWdWX5GfmcmHCChLnm//f0dfQY4g3o6+jpGtMVrV6CTyFsRQKZK1w5kClNbn4ucWlxhZatLMFPbGpsmZav6vnXY/HQxdxa/9YqGHXlGYwG7vzuTv44+YdNr9u8ZnPGtBnDfa3vs3ulW8WkED0omsu/XwaKzr0QzitpWRLHHjumNuds+F5DIiZFOHhUQlQvEshcUZ0DmdJYlq+slq0KzOqczzhP3xv68smAT6jhVcPRwy2XTEMmo1eOZs2JNZW6Tk3vmoxoYc57aVe7XZVu7T791mlip8WWuBtGOK+c2ByOPXUMY7qR1r+2xs1PdpUJYUsSyFxxPQcywrkpRoXsmGy8G1XdzjQhhHAV1apFwezZs6lfvz6enp506dKFf/75x9FDEqLSNDqNBDFCCFFJTh/IfP/990ycOJHXXnuNvXv30rZtW/r160dSUpKjhyaEEEIIB3P6QObDDz/k0Ucf5cEHH6RFixZ8/vnneHt7M2/ePEcPTQghhBAO5tSBjMFgYM+ePfTu3Vt9TKvV0rt3b7Zv317kc3Jzc0lLS7P6EkIIIUT15NSBzMWLFzEajYSGhlo9HhoaSkJC0TVUpk+fTkBAgPoVHh5eFUMVQgghhAM4dSBTEVOmTCE1NVX9iouLc/SQhBBCCGEnTl34oGbNmuh0OhITE60eT0xMpHbtohvpeXh44OFh+zLyQgghhHA+Tj0jo9fr6dixI+vWrVMfM5lMrFu3jqioKAeOTAghhBDOwKlnZAAmTpzI/fffT6dOnbjxxhv56KOPyMzM5MEHH3T00IQQQgjhYE4fyNxzzz1cuHCBqVOnkpCQQLt27VizZk2hBGAhhBBCXH+kRYEQQgghnE61alEghBBCCFEUCWSEEEII4bIkkBFCCCGEy3L6ZN/KsqQASasCIYQQwnVYPrdLS+Wt9oFMeno6gLQqEEIIIVxQeno6AQEBxR6v9ruWTCYT8fHx+Pn5odFobHbdtLQ0wsPDiYuLk91QFST3sHLk/lWe3MPKk3tYOXL/iqcoCunp6dSpUwettvhMmGo/I6PVaqlXr57dru/v7y+/fJUk97By5P5VntzDypN7WDly/4pW0kyMhST7CiGEEMJlSSAjhBBCCJclgUwFeXh48Nprr0mn7UqQe1g5cv8qT+5h5ck9rBy5f5VX7ZN9hRBCCFF9yYyMEEIIIVyWBDJCCCGEcFkSyAghhBDCZUkgI4QQQgiXdV0HMps3b2bQoEHUqVMHjUbDTz/9ZHU8MTGRBx54gDp16uDt7U3//v05fvy41TknT55k6NCh1KpVC39/f0aMGEFiYqLVOfXr10ej0Vh9vfPOO/Z+e3Y3ffp0OnfujJ+fHyEhIQwZMoSjR49anZOTk8O4ceMIDg7G19eX4cOHF7o/sbGx3HHHHXh7exMSEsILL7xAfn6+1TkbN26kQ4cOeHh40KhRIxYsWGDvt1clquoebty4sdDvoEajISEhoUrep73Y6v6NHz+ejh074uHhQbt27Yp8rYMHD9K9e3c8PT0JDw9nxowZ9npbVaqq7uHp06eL/B3csWOHPd9elbDFPTxw4AAjR44kPDwcLy8vmjdvzscff1zotarr38LKuK4DmczMTNq2bcvs2bMLHVMUhSFDhnDq1Cl+/vln9u3bR2RkJL179yYzM1N9ft++fdFoNKxfv56tW7diMBgYNGgQJpPJ6npvvPEG58+fV7+eeeaZKnmP9rRp0ybGjRvHjh07WLt2LXl5efTt21e9PwDPPfccq1atYtmyZWzatIn4+HiGDRumHjcajdxxxx0YDAa2bdvGwoULWbBgAVOnTlXPiYmJ4Y477qBnz57s37+fCRMm8Mgjj/DHH39U6fu1h6q6hxZHjx61+j0MCQmpkvdpL7a4fxYPPfQQ99xzT5Gvk5aWRt++fYmMjGTPnj289957vP7663z55Zd2e29VparuocVff/1l9TvYsWNHm7+nqmaLe7hnzx5CQkJYvHgx//77Ly+//DJTpkzh008/Vc+pzn8LK0URiqIoCqCsXLlS/fno0aMKoBw6dEh9zGg0KrVq1VK++uorRVEU5Y8//lC0Wq2SmpqqnpOSkqJoNBpl7dq16mORkZHKzJkz7f4eHC0pKUkBlE2bNimKYr4X7u7uyrJly9Rzjhw5ogDK9u3bFUVRlN9//13RarVKQkKCes6cOXMUf39/JTc3V1EURZk8ebLSsmVLq9e65557lH79+tn7LVU5e93DDRs2KICSnJxcdW/GASpy/wp67bXXlLZt2xZ6/LPPPlOCgoLU+6koivLiiy8qTZs2tf2bcDB73cOYmBgFUPbt22evoTuNyt5Di6eeekrp2bOn+vP19LewPK7rGZmS5ObmAuDp6ak+ptVq8fDwYMuWLeo5Go3GqpCRp6cnWq1WPcfinXfeITg4mPbt2/Pee+8VWjqpDlJTUwGoUaMGYP4XRl5eHr1791bPadasGREREWzfvh2A7du307p1a0JDQ9Vz+vXrR1paGv/++696TsFrWM6xXKM6sdc9tGjXrh1hYWH06dOHrVu32vvtVLmK3L+y2L59O7fccgt6vV59rF+/fhw9epTk5GQbjd452OseWtx5552EhIRw880388svv9hm0E7GVvcwNTVVvQZcX38Ly0MCmWJYfsmmTJlCcnIyBoOBd999l7Nnz3L+/HkAunbtio+PDy+++CJZWVlkZmYyadIkjEajeg6Y146XLl3Khg0bePzxx5k2bRqTJ0921FuzC5PJxIQJE+jWrRutWrUCICEhAb1eT2BgoNW5oaGham5GQkKC1Qew5bjlWEnnpKWlkZ2dbY+34xD2vIdhYWF8/vnn/Pjjj/z444+Eh4fTo0cP9u7da+d3VXUqev/Koiz3uDqw5z309fXlgw8+YNmyZfz222/cfPPNDBkypNoFM7a6h9u2beP777/nscceUx+7Xv4Wlle1735dUe7u7qxYsYKHH36YGjVqoNPp6N27NwMGDEC5Ugy5Vq1aLFu2jCeffJJZs2ah1WoZOXIkHTp0sGo5PnHiRPX7Nm3aoNfrefzxx5k+fXq1KUs9btw4Dh06VGgmSpSdPe9h06ZNadq0qfrzTTfdxMmTJ5k5cyaLFi2y+es5gvwOVp4972HNmjWt/hZ27tyZ+Ph43nvvPe68806bv56j2OIeHjp0iMGDB/Paa6/Rt29fG46uepIZmRJ07NiR/fv3k5KSwvnz51mzZg2XLl2iYcOG6jl9+/bl5MmTJCUlcfHiRRYtWsS5c+eszrlWly5dyM/P5/Tp01XwLuzv6aef5tdff2XDhg3Uq1dPfbx27doYDAZSUlKszk9MTKR27drqOdfufrD8XNo5/v7+eHl52frtOIS972FRbrzxRk6cOGGjd+BYlbl/ZVHRe+xK7H0Pi9KlS5dq8zsItrmHhw8f5rbbbuOxxx7jlVdesTp2PfwtrAgJZMogICCAWrVqcfz4cXbv3s3gwYMLnVOzZk0CAwNZv349SUlJJf4LY//+/Wi1WpffMaIoCk8//TQrV65k/fr1NGjQwOp4x44dcXd3Z926depjR48eJTY2lqioKACioqKIjo4mKSlJPWft2rX4+/vTokUL9ZyC17CcY7mGK6uqe1iU/fv3ExYWZuN3VLVscf/KIioqis2bN5OXl6c+tnbtWpo2bUpQUFDl34gDVdU9LEp1+B0E293Df//9l549e3L//ffz9ttvF3qd6vy3sFIcmWnsaOnp6cq+ffuUffv2KYDy4YcfKvv27VPOnDmjKIqi/PDDD8qGDRuUkydPKj/99JMSGRmpDBs2zOoa8+bNU7Zv366cOHFCWbRokVKjRg1l4sSJ6vFt27YpM2fOVPbv36+cPHlSWbx4sVKrVi1l7NixVfpe7eHJJ59UAgIClI0bNyrnz59Xv7KystRznnjiCSUiIkJZv369snv3biUqKkqJiopSj+fn5yutWrVS+vbtq+zfv19Zs2aNUqtWLWXKlCnqOadOnVK8vb2VF154QTly5Igye/ZsRafTKWvWrKnS92sPVXUPZ86cqfz000/K8ePHlejoaOXZZ59VtFqt8tdff1Xp+7U1W9w/RVGU48ePK/v27VMef/xxpUmTJurfBcsupZSUFCU0NFQZM2aMcujQIWXp0qWKt7e38sUXX1Tp+7WHqrqHCxYsUJYsWaIcOXJEOXLkiPL2228rWq1WmTdvXpW+X3uwxT2Mjo5WatWqpYwePdrqGklJSeo51flvYWVc14GMZUvqtV/333+/oiiK8vHHHyv16tVT3N3dlYiICOWVV16x2n6pKOYtmKGhoYq7u7vSuHFj5YMPPlBMJpN6fM+ePUqXLl2UgIAAxdPTU2nevLkybdo0JScnpyrfql0Ude8AZf78+eo52dnZylNPPaUEBQUp3t7eytChQ5Xz589bXef06dPKgAEDFC8vL6VmzZrK888/r+Tl5Vmds2HDBqVdu3aKXq9XGjZsaPUarqyq7uG7776r3HDDDYqnp6dSo0YNpUePHsr69eur6m3aja3u36233lrkdWJiYtRzDhw4oNx8882Kh4eHUrduXeWdd96pondpX1V1DxcsWKA0b95c8fb2Vvz9/ZUbb7zRajuyK7PFPXzttdeKvEZkZKTVa1XXv4WVoVGUK5mrQgghhBAuRnJkhBBCCOGyJJARQgghhMuSQEYIIYQQLksCGSGEEEK4LAlkhBBCCOGyJJARQgghhMuSQEYIIYQQLksCGSGEEEK4LAlkhBAur379+nz00UfqzxqNhp9++slh4xFCVB0JZIQQTk1RFHr37k2/fv0KHfvss88IDAzk77//5rHHHnPA6IQQjiaBjBDCqWk0GubPn8/OnTv54osv1MdjYmKYPHkyn3zyCeHh4Xh7eztwlEIIR5FARgjh9MLDw/n444+ZNGkSMTExKIrCww8/TN++fRkzZkyhpSUhxPXDzdEDEEKIsrj//vtZuXIlDz30EMOGDePQoUP8+++/jh6WEMLBJJARQriML7/8kpYtW7J582Z+/PFHatWq5eghCSEcTJaWhBAuIyQkhMcff5zmzZszZMgQRw9HCOEEJJARQrgUNzc33NxkMlkIYSaBjBBCCCFclgQyQgghhHBZEsgIIYQQwmVpFEVRHD0IIYQQQoiKkBkZIYQQQrgsCWSEEEII4bIkkBFCCCGEy5JARgghhBAuSwIZIYQQQrgsCWSEEEII4bIkkBFCCCGEy5JARgghhBAuSwIZIYQQQrgsCWSEEEII4bIkkBFCCCGEy/p/MqnkjGUk8zoAAAAASUVORK5CYII=\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"microlensing = exoeu[exoeu['detection_type'] == 'Microlensing']\n",
"microlensing.groupby('discovered').count()['# name'].plot(kind=\"line\",\n",
" color=\"m\",\n",
" label=\"Kutlecekim Mercekleme\")\n",
"imaging = exoeu[exoeu['detection_type'] == 'Imaging']\n",
"imaging.groupby('discovered').count()['# name'].plot(kind=\"line\",\n",
" color=\"g\",\n",
" label=\"Dogrudan Goruntuleme\")\n",
"plt.xlabel(\"Yil\")\n",
"plt.ylabel(\"Kesif Sayisi\")\n",
"plt.legend(loc=\"best\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Doğrudan görüntülemeyle keşiflerin 2020 sonrası büyük bir ivmeyle arttığı görülmektedir. 2023 yılı sonunda bu grafiğin ne şekilde değiştiğini incelemek ilginç olacaktır. 2027 Mayıs'ında uzaya gönderilmesi planlanan [Nancy Grace Roman Teleskobu'yla](https://en.wikipedia.org/wiki/Nancy_Grace_Roman_Space_Telescope) alınan verilerin inclenmesi sonrası bu grafiğin y-eksenini de logaritmik ölçekte çizdirmek gerekebilecektir. \n",
"\n",
"Son olarak toplam keşif sayılarının zamanla değişimine bakmak istenebilir."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"exoeu.groupby('discovered').count()['# name'].plot(kind=\"line\", label=\"Tum Yontemler\", color=\"r\")\n",
"plt.yscale(\"log\")\n",
"# Kepler'in gozlemlere basladigi yil\n",
"plt.annotate(\"Kepler\",\n",
" xy=(2009, 100), xycoords='data',\n",
" xytext=(2007, 250), textcoords='data',\n",
" arrowprops=dict(arrowstyle=\"->\",\n",
" connectionstyle=\"arc3\"),\n",
" )\n",
"# TESS'in gozlemlere basladigi yil\n",
"plt.annotate(\"TESS\",\n",
" xy=(2018, 350), xycoords='data',\n",
" xytext=(2018, 600), textcoords='data',\n",
" arrowprops=dict(arrowstyle=\"->\",\n",
" connectionstyle=\"arc3\"),\n",
" )\n",
"plt.xlabel(\"Zaman\")\n",
"plt.ylabel(\"Kesif Sayisi\")\n",
"plt.legend(loc=\"best\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"2023 yılında gezegen keşiflerinin yapılmış olduğu, ancak henüz 4 aydan kısa bir süre geçmiş olduğu değerlendirilmelidir."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Alan Grafikleri ##\n",
"\n",
"Alan grafikleri, özelikle aralarında ast-üst ilişkisi bulunan değişkenlerin çoğu durumda zamanla değişimlerinin kümülatif olarak gösterildiği grafiklerdir. \n",
"\n",
"Örnek olarak geçişle keşiflerin tüm keşiflerin ne kadarını oluşturduğu ve göreli bu durumun zamanla nasıl değiştiği eğri grafiklerinin altındaki alanlar doldurularak alan grafiğiyle anlatılabilir. "
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(12,6))\n",
"exoeu.groupby('discovered').count()['# name'].plot(kind=\"area\", \n",
" stacked=False,\n",
" alpha=0.5,\n",
" label=\"Tum Yontemler\")\n",
"transits.groupby('discovered').count()['# name'].plot(kind=\"area\", \n",
" stacked=False,\n",
" alpha=0.5,\n",
" label=\"Gecis Yontemi\")\n",
"radvel.groupby('discovered').count()['# name'].plot(kind=\"area\", \n",
" stacked=True,\n",
" alpha=0.5,\n",
" label=\"Dikine Hiz\")\n",
"#plt.yscale(\"log\")\n",
"# Kepler'in gozlemlere basladigi yil\n",
"plt.annotate(\"Kepler\",\n",
" xy=(2009, 100), xycoords='data',\n",
" xytext=(2007, 250), textcoords='data',\n",
" arrowprops=dict(arrowstyle=\"->\",\n",
" connectionstyle=\"arc3\"),\n",
" )\n",
"# TESS'in gozlemlere basladigi yil\n",
"plt.annotate(\"TESS\",\n",
" xy=(2018, 350), xycoords='data',\n",
" xytext=(2018, 600), textcoords='data',\n",
" arrowprops=dict(arrowstyle=\"->\",\n",
" connectionstyle=\"arc3\"),\n",
" )\n",
"plt.legend(loc=\"upper left\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Bu grafiğe bakarak toplam keşiflerde 2013 ve 2016 yıllarında yaşanan artışların geçiş yöntemi, 2002 civarındaki artışın ise dikine hız yöntemi kaynaklı olduğunu söylemek mümkündür. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Histogramlar ##\n",
"\n",
"Histogramlar, sayısal verilerin *frekans* dağılımlarını temsil etmek için kullanılır. *x* ekseni sınırları belli kutucuklara (bin) bölünerek, her veri noktası değeri itibarı ile uç noktaları arasında bulundğu kutucuğa atanır. Her kutunun y-ekseni değeri o kutudaki verilerin sayısı (frekans) ya da olasılık kütle / yoğunluk fonksiyonu değeridir. Kutu boyutları görselleştirmenin etksini artırmak ve bir aralığı ön plana çıkarmak üzere değiştirilebilir. \n",
"\n",
"### Örnek: Geçiş Yapan Ötegezegenlerin Yarıçap Dağılımı\n",
"\n",
"Daha önce koşullu indeksleme yöntemiyle oluşturulan `transits` veriçerçevesinde gezegen yarıçapını gösteren `radius` parametresinin dağılımı örnek olarak incelenebilir. Geçiş yöntemi, yıldız yarıçapının düşük ve yüksek çözünürlüklü tayflar, tayfsal enerji dağılımı ve yıldız evrim modellerinden belirlenebilmesi durumunda gezegen yarıçapını doğrudan verir. Bu nedenle veriçerçevesinin sadece geçiş yapan gezegenlere sınırlanması durumunda bu gezegenlerin hepsinin yarıçap değerinin belirlenmiş olması gerekir. Ancak bundan emin olunamayacağı için öncelikle bir kontrol etmekte fayda vardır."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"11 1SWASP J1407 b\n",
"84 38 Vir b\n",
"452 HAT-P-44 c\n",
"455 HAT-P-46 c\n",
"586 HD 10442 b\n",
"1197 HD 75784 b\n",
"1198 HD 75784 c\n",
"1390 J1433 b\n",
"1834 KIC 9413313 b\n",
"1883 KMT-2019-BLG-1806/OGLE-2019-BLG-1250 b\n",
"1922 KOI-142 c\n",
"2672 Kepler-1520 b\n",
"2854 Kepler-1661 (AB) b\n",
"4701 SDSS J1411+2009 b\n",
"4707 SOI-3 b\n",
"4708 SOI-4 b\n",
"4709 SOI-5 b\n",
"4710 SOI-6 b\n",
"4712 SOI-8 b\n",
"4721 TIC 156514476.01\n",
"4840 TOI-203 b\n",
"4995 TOI-717 b\n",
"5111 WASP-138 b\n",
"5238 WASP-81 c\n",
"5260 WD 1032+011 b\n",
"5261 WD 1145+017 b\n",
"Name: # name, dtype: object"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"transits[pd.isna(transits['radius'])]['# name']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Görüldüğü üzere 26 gezegenin yarıçapları `exoplanet.eu` veritabanında yer almamaktadır. Bu gezegenlerin yarıçapları [NASA Exoplanet Archive](https://exoplanetarchive.ipac.caltech.edu/cgi-bin/TblView/nph-tblView?app=ExoTbls&config=PS) gibi diğer veritabanlarında araştırılabileceği gibi literatürde bu gezegenlere ilişkin yayınlarda bulunup eklenebilir de. Ancak yeterli sayıda örnek olduğu için bu gezegenler ilgili verçeçevesiden çıkarılarak devam edilebilir."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"transits_rad = transits.dropna(subset=['radius'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`numpy.histogram` fonksiyonu `matplotlib.pyplot.histogram` gibi veriyi aksi söylenmedikçe 10 kutucuğa ayırarak bu kutucukların sınırlarını ve sayılarını döndürür. Öncelikle histogramın bu parametrelerini listeledikten sonra dağılımın grafiğine bakmakta fayda vardır."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"35 1.57000\n",
"36 1.57000\n",
"95 0.17370\n",
"111 1.02000\n",
"116 0.45710\n",
" ... \n",
"5313 0.54000\n",
"5314 0.44000\n",
"5315 0.68000\n",
"5316 0.49000\n",
"5351 0.16719\n",
"Name: radius, Length: 3725, dtype: float64"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"transits_rad['radius']"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[3122 578 19 3 0 1 0 0 1 1]\n",
"[0.02543 0.943847 1.862264 2.780681 3.699098 4.617515 5.535932 6.454349\n",
" 7.372766 8.291183 9.2096 ]\n"
]
}
],
"source": [
"# np.histogram returns 2 values\n",
"sayi,kutu_sinirlari = np.histogram(transits_rad['radius'])\n",
"\n",
"print(sayi) # herbir kutuya dusen gezegen sayisi\n",
"print(kutu_sinirlari) # kutularin (binlerin) sinirlari"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
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3w4cgu3btqsKFC2fad/fu3R2uofTHe5R+nNTUVJ07d04FChRQxYoVM72u3bp1c5jzXL9+fRlj1LNnT4d29evX18mTJ3Xz5s0sXgFYEVMggFsULFhQ0h9TFW73/vvv69KlS0pISHD41fvRo0dljNHIkSMdwuWtTp8+rccee0zHjh1Tx44ds1STh4eHJk2apMGDB8vX11cNGjRQmzZt1K1bN/n5+d1XH6VLl5aPj4+qVKni8I/RiRMnNGrUKK1cuTJDuE5MTHR47urqqnLlyjlse/zxxyXJYVmlVatW6d///rdiYmKUnJxs355ZwC9dunSGbYULF75n0C9YsKDOnTuXYfurr76qNm3aSMo4PeLIkSPau3evihcvnmmfp0+fdnh+8+ZNde7cWampqVq2bJnDh2nut69ffvlFJUqUyPAhrvLlyzs8z8o9lO72a5ceQO527Y4cOaKffvrpvq9B2bJl79hXZu5Wk5eX1z1fX69ePUlSnTp1HO6XAwcO6I033tCGDRsyhOnb79PHHnvsvj7wduzYMVWsWPGeq1lk5X6uUKFChm2PP/64rl69qjNnztzz57VChQoKCQnJsH3Lli13fZ30x72/ZMkStW7dWo899phatmypzp07q1WrVvd8bfr/NFWsWNFhu81mU7ly5ez70/97+/2bJ0+eO06PyeweSktL07Rp0zR79mzFxcU5/M9BZlOfbr+vvL29JUn+/v4ZtqelpSkxMfGuU6gAiQAMOPD29laJEiW0f//+DPvS5wTfvoZm+lJEr732mkJDQzPt9/Z/MLJq4MCBatu2rVasWKF169Zp5MiRmjBhgjZs2KBatWr9qT5TU1P1t7/9TefPn9ewYcNUqVIl5c+fX7/99pt69OiR5SWWJOn777/XM888oyZNmthXmXB3d9e8efO0cOHCDO3d3Nwy7cdksibsrSpVqqSYmBj99ttvDqHw8ccft4fy21cqSEtL09/+9jcNHTo00z7TX5duyJAhio6O1rfffpthbmNW+7qXP3MP/Zlrl5aWpmrVqundd9/NdP/tgeL2kbt7+bPv591cvHhRTZs2lZeXl8aNG6fAwEDlzZtXe/bs0bBhwzLcp1mt+W6yej87k4+Pj2JiYrRu3TqtWbNGa9as0bx589StWzctWLDAaXVl9n689dZbGjlypHr27Knx48erSJEicnV11cCBAzP9e+dO91VO3G+wDgIwcJuwsDB99NFH2rFjh5544ol7tk8fFXV3d8909OZWgYGBmYbr+xEYGKjBgwdr8ODBOnLkiGrWrKl33nlHn3766Z/qb9++fTp8+LAWLFigbt262bff6VeoaWlp+vnnnx3C3eHDhyXJPvrz5ZdfKm/evFq3bp3DiOm8efP+VI130qZNGy1atEifffbZHUPo7QIDA3X58uV7vkeStGjRIk2dOlVTp05V06ZN/3RfAQEB+u677+xLcaU7evSoQ7us3EMPIjAwUD/++KNatGhxxyk3uc3GjRt17tw5LVu2TE2aNLFvj4uLe6B+AwMDtX37dt24ceOOS4pl9X4+cuRIhm2HDx9Wvnz57jjqnp1sNpvatm2rtm3bKi0tTa+++qref/99jRw5UuXLl7/je56+nnlsbKzDb3lSUlIUFxdnvyfT2x09elRPPfWUvd3Nmzd1/PhxVa9e/b7q/OKLL/TUU0/p448/dth+8eLFO34QGMhuzAEGbjN06FDly5dPPXv2VEJCQob9t48u+Pj4qFmzZnr//fd16tSpDO3PnDlj/3PHjh31448/avny5ffsN93Vq1d1/fp1h22BgYEqWLCgw69ksyp99OTW4xpjNG3atDu+ZubMmQ5tZ86cKXd3d7Vo0cLep4uLi8OvNI8fP55hdYEH1blzZwUFBWn8+PHatm1bpm1uv56dO3dWdHS01q1bl6HtxYsX7fMG9+/fr1deeUUvvfSSBgwYcMfj309foaGhunHjhj788EP7/rS0NPv88XRZuYceROfOnfXbb7851JPu2rVrunLlSrYcJztldp+mpKQ4zMn+Mzp27KizZ8863NPp0o+V1fs5OjraYQ7ryZMn9dVXX6lly5Z3HK3MLrdPCXJ1dbUH0vS/J/Lnzy/pj3v0ViEhIfYvxrn1On/88cdKTEy0r3ZRt25dFS1aVB9++KHDPNvPPvssS59PcHNzy/DzuXTp0gzz3IGcxAgwcJsKFSpo4cKFeuGFF1SxYkX7N8EZYxQXF6eFCxfK1dXV4dfis2bN0pNPPqlq1aqpd+/eKleunBISEhQdHa1ff/1VP/74o6Q/fq3+xRdfqFOnTurZs6fq1Kmj8+fPa+XKlZo7d65q1KiRoZ7Dhw+rRYsW9tCXJ08eLV++XAkJCerSpcufPs9KlSopMDBQr732mn777Td5eXnpyy+/vOM/ZHnz5tXatWvVvXt31a9fX2vWrNHq1av1r3/9yz66FRYWpnfffVetWrXSiy++qNOnT2vWrFkqX758tn59tLu7u5YvX67Q0FA9+eSTevbZZ9W4cWP7FI6VK1fqxIkTDstUDRkyRCtXrlSbNm3Uo0cP1alTR1euXNG+ffv0xRdf6Pjx4ypWrJj9A1RNmjTJMLresGFDlStX7r77at++vZ544gkNHjxYR48eVaVKlbRy5UqdP39ekuM80vu9hx7Eyy+/rCVLlqhv37767rvv1KhRI6WmpurQoUNasmSJ1q1bp7p16z7wcbJTw4YNVbhwYXXv3l3//Oc/5eLiov/7v/974F9zd+vWTZ988okiIyO1Y8cONW7cWFeuXNG3336rV199Ve3atcvy/Vy1alWFhoY6LIMmKVu+ye5eXnnlFZ0/f17NmzdXqVKl9Msvv2jGjBmqWbOmfamzmjVrys3NTZMmTVJiYqI8PDzUvHlz+fj4aMSIERo7dqxatWqlZ555RrGxsZo9e7bq1atnn09vs9k0ZswY9e/fX82bN1fnzp11/PhxzZ8/X4GBgff9W4U2bdpo3Lhx+vvf/66GDRtq3759+uyzzzJ8xgDIUQ930Qngr+Po0aOmX79+pnz58iZv3rzG09PTVKpUyfTt2zfDgu3GGHPs2DHTrVs34+fnZ9zd3c1jjz1m2rRpY7744guHdufOnTMRERH2L7UoVaqU6d69uzl79qwxJuMyaGfPnjXh4eGmUqVKJn/+/Mbb29vUr1/fLFmyJEvnExAQYMLCwhy2HTx40ISEhJgCBQqYYsWKmd69e9uXIrt1ia7MvgjD19fXjB49OsNyRh9//LH9iwUqVapk5s2bZ18m61b6/784ILM673fZoosXL5px48aZWrVqmQIFChibzWb8/f3Nc889Z77++usM7S9dumRGjBhhypcvb2w2mylWrJhp2LChefvtt+3LLAUEBNzXF2HcT1/GGHPmzBnz4osv2r8Io0ePHmbr1q1Gklm0aJFDffdzD6Uvg7Zz506H16YvGXXrEleZfflDSkqKmTRpkqlSpYrx8PAwhQsXNnXq1DFjx451WDbuTu9P+r7MlkG7dZmuW2u91xe23N737cfdunWradCggfH09DQlS5Y0Q4cONevWrcv0fKtUqZJpv5ldi6tXr5rXX3/dlC1b1ri7uxs/Pz/z3HPPmWPHjtnbZPV+/vTTT+3ta9WqlWHJscxkxxdhfPHFF6Zly5bGx8fH2Gw2U7p0afOPf/zDnDp1yqGvDz/80JQrV864ublluH4zZ840lSpVMu7u7sbX19f069cv0y/CmD59ugkICDAeHh7miSeeMFu3bjV16tQxrVq1srdJvx8z+9KQ69evm8GDB5sSJUoYT09P06hRIxMdHX3HL9O4vY87/Qxkdp1YBg134mIMs8UB3F2PHj30xRdfZLo6BrJuxYoV6tChg7Zs2ZLha5zx1+Ti4qLw8PBMp1Q86tLS0lS8eHE9++yzmU6vAXIj5gADQA66du2aw/PU1FTNmDFDXl5eql27tpOqAv6c69evZ5h+8sknn+j8+fNq1qyZc4oC/gTmAANADurfv7+uXbum4OBgJScna9myZfrhhx/01ltvZeuSXcDDsG3bNg0aNEidOnVS0aJFtWfPHn388ceqWrWqOnXq5OzygPtGAAaAHNS8eXO98847WrVqla5fv67y5ctrxowZDt+qB/xVlClTRv7+/po+fbrOnz+vIkWKqFu3bpo4ceJ9fQEJkFswBxgAAACWwhxgAAAAWApTIO5DWlqafv/9dxUsWPAv8+1JAAAAVmKM0aVLl1SyZEm5ut59jJcAfB9+//13+fv7O7sMAAAA3MPJkycdvqwqMwTg+1CwYEFJf1xQLy8vJ1cDAACA2yUlJcnf39+e2+6GAHwf0qc9eHl5EYABAABysfuZrsqH4AAAAGApBGAAAABYCgEYAAAAlkIABgAAgKUQgAEAAGApBGAAAABYCgEYAAAAlkIABgAAgKUQgAEAAGApBGAAAABYCgEYAAAAlkIABgAAgKUQgAEAAGApBGAAAABYCgEYAAAAlkIABgAAgKXkcXYBuLMyw1c7u4QcdXximLNLAAAAFsQIMAAAACyFAAwAAABLIQADAADAUgjAAAAAsBQCMAAAACyFAAwAAABLIQADAADAUgjAAAAAsBQCMAAAACzFqQF4zpw5ql69ury8vOTl5aXg4GCtWbPGvv/69esKDw9X0aJFVaBAAXXs2FEJCQkOfZw4cUJhYWHKly+ffHx8NGTIEN28edOhzcaNG1W7dm15eHiofPnymj9//sM4PQAAAORCTg3ApUqV0sSJE7V7927t2rVLzZs3V7t27XTgwAFJ0qBBg/T1119r6dKl2rRpk37//Xc9++yz9tenpqYqLCxMKSkp+uGHH7RgwQLNnz9fo0aNsreJi4tTWFiYnnrqKcXExGjgwIF65ZVXtG7duod+vgAAAHA+F2OMcXYRtypSpIimTJmi5557TsWLF9fChQv13HPPSZIOHTqkypUrKzo6Wg0aNNCaNWvUpk0b/f777/L19ZUkzZ07V8OGDdOZM2dks9k0bNgwrV69Wvv377cfo0uXLrp48aLWrl17XzUlJSXJ29tbiYmJ8vLyyv6TvoMyw1c/tGM5w/GJYc4uAQAAPCKyktdyzRzg1NRULVq0SFeuXFFwcLB2796tGzduKCQkxN6mUqVKKl26tKKjoyVJ0dHRqlatmj38SlJoaKiSkpLso8jR0dEOfaS3Se8jM8nJyUpKSnJ4AAAA4NHg9AC8b98+FShQQB4eHurbt6+WL1+uoKAgxcfHy2azqVChQg7tfX19FR8fL0mKj493CL/p+9P33a1NUlKSrl27lmlNEyZMkLe3t/3h7++fHacKAACAXMDpAbhixYqKiYnR9u3b1a9fP3Xv3l0HDx50ak0jRoxQYmKi/XHy5Emn1gMAAIDsk8fZBdhsNpUvX16SVKdOHe3cuVPTpk3T888/r5SUFF28eNFhFDghIUF+fn6SJD8/P+3YscOhv/RVIm5tc/vKEQkJCfLy8pKnp2emNXl4eMjDwyNbzg8AAAC5i9NHgG+Xlpam5ORk1alTR+7u7lq/fr19X2xsrE6cOKHg4GBJUnBwsPbt26fTp0/b20RFRcnLy0tBQUH2Nrf2kd4mvQ8AAABYi1NHgEeMGKHWrVurdOnSunTpkhYuXKiNGzdq3bp18vb2Vq9evRQZGakiRYrIy8tL/fv3V3BwsBo0aCBJatmypYKCgvTyyy9r8uTJio+P1xtvvKHw8HD7CG7fvn01c+ZMDR06VD179tSGDRu0ZMkSrV79aK+wAAAAgMw5NQCfPn1a3bp106lTp+Tt7a3q1atr3bp1+tvf/iZJeu+99+Tq6qqOHTsqOTlZoaGhmj17tv31bm5uWrVqlfr166fg4GDlz59f3bt317hx4+xtypYtq9WrV2vQoEGaNm2aSpUqpY8++kihoaEP/XwBAADgfLluHeDciHWAcwbrAAMAgOzyl1wHGAAAAHgYCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEtxagCeMGGC6tWrp4IFC8rHx0ft27dXbGysQ5tmzZrJxcXF4dG3b1+HNidOnFBYWJjy5csnHx8fDRkyRDdv3nRos3HjRtWuXVseHh4qX7685s+fn9OnBwAAgFzIqQF406ZNCg8P17Zt2xQVFaUbN26oZcuWunLlikO73r1769SpU/bH5MmT7ftSU1MVFhamlJQU/fDDD1qwYIHmz5+vUaNG2dvExcUpLCxMTz31lGJiYjRw4EC98sorWrdu3UM7VwAAAOQOeZx58LVr1zo8nz9/vnx8fLR79241adLEvj1fvnzy8/PLtI9vvvlGBw8e1LfffitfX1/VrFlT48eP17BhwzRmzBjZbDbNnTtXZcuW1TvvvCNJqly5srZs2aL33ntPoaGhOXeCAAAAyHVy1RzgxMRESVKRIkUctn/22WcqVqyYqlatqhEjRujq1av2fdHR0apWrZp8fX3t20JDQ5WUlKQDBw7Y24SEhDj0GRoaqujo6EzrSE5OVlJSksMDAAAAjwanjgDfKi0tTQMHDlSjRo1UtWpV+/YXX3xRAQEBKlmypPbu3athw4YpNjZWy5YtkyTFx8c7hF9J9ufx8fF3bZOUlKRr167J09PTYd+ECRM0duzYbD9HAAAAOF+uCcDh4eHav3+/tmzZ4rC9T58+9j9Xq1ZNJUqUUIsWLXTs2DEFBgbmSC0jRoxQZGSk/XlSUpL8/f1z5FgAAAB4uHLFFIiIiAitWrVK3333nUqVKnXXtvXr15ckHT16VJLk5+enhIQEhzbpz9PnDd+pjZeXV4bRX0ny8PCQl5eXwwMAAACPBqcGYGOMIiIitHz5cm3YsEFly5a952tiYmIkSSVKlJAkBQcHa9++fTp9+rS9TVRUlLy8vBQUFGRvs379eod+oqKiFBwcnE1nAgAAgL8Kpwbg8PBwffrpp1q4cKEKFiyo+Ph4xcfH69q1a5KkY8eOafz48dq9e7eOHz+ulStXqlu3bmrSpImqV68uSWrZsqWCgoL08ssv68cff9S6dev0xhtvKDw8XB4eHpKkvn376ueff9bQoUN16NAhzZ49W0uWLNGgQYOcdu4AAABwDqcG4Dlz5igxMVHNmjVTiRIl7I/FixdLkmw2m7799lu1bNlSlSpV0uDBg9WxY0d9/fXX9j7c3Ny0atUqubm5KTg4WC+99JK6deumcePG2duULVtWq1evVlRUlGrUqKF33nlHH330EUugAQAAWJCLMcY4u4jcLikpSd7e3kpMTHyo84HLDF/90I7lDMcnhjm7BAAA8IjISl7LFR+CAwAAAB4WAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFIIwAAAALAUAjAAAAAshQAMAAAASyEAAwAAwFKcGoAnTJigevXqqWDBgvLx8VH79u0VGxvr0Ob69esKDw9X0aJFVaBAAXXs2FEJCQkObU6cOKGwsDDly5dPPj4+GjJkiG7evOnQZuPGjapdu7Y8PDxUvnx5zZ8/P6dPDwAAALmQUwPwpk2bFB4erm3btikqKko3btxQy5YtdeXKFXubQYMG6euvv9bSpUu1adMm/f7773r22Wft+1NTUxUWFqaUlBT98MMPWrBggebPn69Ro0bZ28TFxSksLExPPfWUYmJiNHDgQL3yyitat27dQz1fAAAAOJ+LMcY4u4h0Z86ckY+PjzZt2qQmTZooMTFRxYsX18KFC/Xcc89Jkg4dOqTKlSsrOjpaDRo00Jo1a9SmTRv9/vvv8vX1lSTNnTtXw4YN05kzZ2Sz2TRs2DCtXr1a+/fvtx+rS5cuunjxotauXXvPupKSkuTt7a3ExER5eXnlzMlnoszw1Q/tWM5wfGKYs0sAAACPiKzktVw1BzgxMVGSVKRIEUnS7t27dePGDYWEhNjbVKpUSaVLl1Z0dLQkKTo6WtWqVbOHX0kKDQ1VUlKSDhw4YG9zax/pbdL7uF1ycrKSkpIcHgAAAHg05JoAnJaWpoEDB6pRo0aqWrWqJCk+Pl42m02FChVyaOvr66v4+Hh7m1vDb/r+9H13a5OUlKRr165lqGXChAny9va2P/z9/bPlHAEAAOB8uSYAh4eHa//+/Vq0aJGzS9GIESOUmJhof5w8edLZJQEAACCb5HF2AZIUERGhVatWafPmzSpVqpR9u5+fn1JSUnTx4kWHUeCEhAT5+fnZ2+zYscOhv/RVIm5tc/vKEQkJCfLy8pKnp2eGejw8POTh4ZEt5wYAAIDcxakjwMYYRUREaPny5dqwYYPKli3rsL9OnTpyd3fX+vXr7dtiY2N14sQJBQcHS5KCg4O1b98+nT592t4mKipKXl5eCgoKsre5tY/0Nul9AAAAwDqcOgIcHh6uhQsX6quvvlLBggXtc3a9vb3l6ekpb29v9erVS5GRkSpSpIi8vLzUv39/BQcHq0GDBpKkli1bKigoSC+//LImT56s+Ph4vfHGGwoPD7eP4vbt21czZ87U0KFD1bNnT23YsEFLlizR6tWP9ioLAAAAyMipI8Bz5sxRYmKimjVrphIlStgfixcvtrd577331KZNG3Xs2FFNmjSRn5+fli1bZt/v5uamVatWyc3NTcHBwXrppZfUrVs3jRs3zt6mbNmyWr16taKiolSjRg298847+uijjxQaGvpQzxcAAADOl6vWAc6tWAc4Z7AOMAAAyC5/2XWAAQAAgJxGAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAICl5MlKY1dXV7m4uNy1jYuLi27evPlARQEAAAA5JUsBePny5XfcFx0drenTpystLe2BiwIAAABySpYCcLt27TJsi42N1fDhw/X111+ra9euGjduXLYVBwAAAGS3Pz0H+Pfff1fv3r1VrVo13bx5UzExMVqwYIECAgKysz4AAAAgW2U5ACcmJmrYsGEqX768Dhw4oPXr1+vrr79W1apVc6I+AAAAIFtlaQrE5MmTNWnSJPn5+enzzz/PdEoEAAAAkJu5GGPM/TZ2dXWVp6enQkJC5Obmdsd2y5Yty5bicoukpCR5e3srMTFRXl5eD+24ZYavfmjHcobjE8OcXQIAAHhEZCWvZWkEuFu3bvdcBg0AAADIzbIUgOfPn59DZQAAAAAPB98EBwAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEtxagDevHmz2rZtq5IlS8rFxUUrVqxw2N+jRw+5uLg4PFq1auXQ5vz58+ratau8vLxUqFAh9erVS5cvX3Zos3fvXjVu3Fh58+aVv7+/Jk+enNOnBgAAgFzKqQH4ypUrqlGjhmbNmnXHNq1atdKpU6fsj88//9xhf9euXXXgwAFFRUVp1apV2rx5s/r06WPfn5SUpJYtWyogIEC7d+/WlClTNGbMGH3wwQc5dl4AAADIvbK0DnB2a926tVq3bn3XNh4eHvLz88t0308//aS1a9dq586dqlu3riRpxowZevrpp/X222+rZMmS+uyzz5SSkqL//Oc/stlsqlKlimJiYvTuu+86BOVbJScnKzk52f48KSnpT54hAAAAcptcPwd448aN8vHxUcWKFdWvXz+dO3fOvi86OlqFChWyh19JCgkJkaurq7Zv325v06RJE9lsNnub0NBQxcbG6sKFC5kec8KECfL29rY//P39c+jsAAAA8LDl6gDcqlUrffLJJ1q/fr0mTZqkTZs2qXXr1kpNTZUkxcfHy8fHx+E1efLkUZEiRRQfH29v4+vr69Am/Xl6m9uNGDFCiYmJ9sfJkyez+9QAAADgJE6dAnEvXbp0sf+5WrVqql69ugIDA7Vx40a1aNEix47r4eEhDw+PHOsfAAAAzpOrR4BvV65cORUrVkxHjx6VJPn5+en06dMObW7evKnz58/b5w37+fkpISHBoU368zvNLQYAAMCj6y8VgH/99VedO3dOJUqUkCQFBwfr4sWL2r17t73Nhg0blJaWpvr169vbbN68WTdu3LC3iYqKUsWKFVW4cOGHewIAAABwOqcG4MuXLysmJkYxMTGSpLi4OMXExOjEiRO6fPmyhgwZom3btun48eNav3692rVrp/Llyys0NFSSVLlyZbVq1Uq9e/fWjh07tHXrVkVERKhLly4qWbKkJOnFF1+UzWZTr169dODAAS1evFjTpk1TZGSks04bAAAATuTUALxr1y7VqlVLtWrVkiRFRkaqVq1aGjVqlNzc3LR3714988wzevzxx9WrVy/VqVNH33//vcP83M8++0yVKlVSixYt9PTTT+vJJ590WOPX29tb33zzjeLi4lSnTh0NHjxYo0aNuuMSaAAAAHi0uRhjjLOLyO2SkpLk7e2txMREeXl5PbTjlhm++qEdyxmOTwxzdgkAAOARkZW89peaAwwAAAA8KAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEtxagDevHmz2rZtq5IlS8rFxUUrVqxw2G+M0ahRo1SiRAl5enoqJCRER44ccWhz/vx5de3aVV5eXipUqJB69eqly5cvO7TZu3evGjdurLx588rf31+TJ0/O6VMDAABALuXUAHzlyhXVqFFDs2bNynT/5MmTNX36dM2dO1fbt29X/vz5FRoaquvXr9vbdO3aVQcOHFBUVJRWrVqlzZs3q0+fPvb9SUlJatmypQICArR7925NmTJFY8aM0QcffJDj5wcAAIDcx8UYY5xdhCS5uLho+fLlat++vaQ/Rn9LliypwYMH67XXXpMkJSYmytfXV/Pnz1eXLl30008/KSgoSDt37lTdunUlSWvXrtXTTz+tX3/9VSVLltScOXP0+uuvKz4+XjabTZI0fPhwrVixQocOHbqv2pKSkuTt7a3ExER5eXll/8nfQZnhqx/asZzh+MQwZ5cAAAAeEVnJa7l2DnBcXJzi4+MVEhJi3+bt7a369esrOjpakhQdHa1ChQrZw68khYSEyNXVVdu3b7e3adKkiT38SlJoaKhiY2N14cKFTI+dnJyspKQkhwcAAAAeDbk2AMfHx0uSfH19Hbb7+vra98XHx8vHx8dhf548eVSkSBGHNpn1cesxbjdhwgR5e3vbH/7+/g9+QgAAAMgVcm0AdqYRI0YoMTHR/jh58qSzSwIAAEA2ybUB2M/PT5KUkJDgsD0hIcG+z8/PT6dPn3bYf/PmTZ0/f96hTWZ93HqM23l4eMjLy8vhAQAAgEdDrg3AZcuWlZ+fn9avX2/flpSUpO3btys4OFiSFBwcrIsXL2r37t32Nhs2bFBaWprq169vb7N582bduHHD3iYqKkoVK1ZU4cKFH9LZAAAAILdwagC+fPmyYmJiFBMTI+mPD77FxMToxIkTcnFx0cCBA/Xvf/9bK1eu1L59+9StWzeVLFnSvlJE5cqV1apVK/Xu3Vs7duzQ1q1bFRERoS5duqhkyZKSpBdffFE2m029evXSgQMHtHjxYk2bNk2RkZFOOmsAAAA4Ux5nHnzXrl166qmn7M/TQ2n37t01f/58DR06VFeuXFGfPn108eJFPfnkk1q7dq3y5s1rf81nn32miIgItWjRQq6ururYsaOmT59u3+/t7a1vvvlG4eHhqlOnjooVK6ZRo0Y5rBUMAAAA68g16wDnZqwDnDNYBxgAAGSXR2IdYAAAACAnEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWAoBGAAAAJZCAAYAAIClEIABAABgKQRgAAAAWEoeZxcA6yozfLWzS8hRxyeGObsEAACQCUaAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApeTqADxmzBi5uLg4PCpVqmTff/36dYWHh6to0aIqUKCAOnbsqISEBIc+Tpw4obCwMOXLl08+Pj4aMmSIbt68+bBPBQAAALlErl8FokqVKvr222/tz/Pk+X8lDxo0SKtXr9bSpUvl7e2tiIgIPfvss9q6daskKTU1VWFhYfLz89MPP/ygU6dOqVu3bnJ3d9dbb7310M8FAAAAzpfrA3CePHnk5+eXYXtiYqI+/vhjLVy4UM2bN5ckzZs3T5UrV9a2bdvUoEEDffPNNzp48KC+/fZb+fr6qmbNmho/fryGDRumMWPGyGazPezTAQAAgJPl6ikQknTkyBGVLFlS5cqVU9euXXXixAlJ0u7du3Xjxg2FhITY21aqVEmlS5dWdHS0JCk6OlrVqlWTr6+vvU1oaKiSkpJ04MCBOx4zOTlZSUlJDg8AAAA8GnJ1AK5fv77mz5+vtWvXas6cOYqLi1Pjxo116dIlxcfHy2azqVChQg6v8fX1VXx8vCQpPj7eIfym70/fdycTJkyQt7e3/eHv75+9JwYAAACnydVTIFq3bm3/c/Xq1VW/fn0FBARoyZIl8vT0zLHjjhgxQpGRkfbnSUlJhGAAAIBHRK4eAb5doUKF9Pjjj+vo0aPy8/NTSkqKLl686NAmISHBPmfYz88vw6oQ6c8zm1eczsPDQ15eXg4PAAAAPBr+UgH48uXLOnbsmEqUKKE6derI3d1d69evt++PjY3ViRMnFBwcLEkKDg7Wvn37dPr0aXubqKgoeXl5KSgo6KHXDwAAAOfL1VMgXnvtNbVt21YBAQH6/fffNXr0aLm5uemFF16Qt7e3evXqpcjISBUpUkReXl7q37+/goOD1aBBA0lSy5YtFRQUpJdfflmTJ09WfHy83njjDYWHh8vDw8PJZwcAAABnyNUB+Ndff9ULL7ygc+fOqXjx4nryySe1bds2FS9eXJL03nvvydXVVR07dlRycrJCQ0M1e/Zs++vd3Ny0atUq9evXT8HBwcqfP7+6d++ucePGOeuUAAAA4GQuxhjj7CJyu6SkJHl7eysxMfGhzgcuM3z1QzsWst/xiWHOLgEAAMvISl77S80BBgAAAB4UARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCkEYAAAAFgKARgAAACWQgAGAACApRCAAQAAYCmWCsCzZs1SmTJllDdvXtWvX187duxwdkkAAAB4yPI4u4CHZfHixYqMjNTcuXNVv359TZ06VaGhoYqNjZWPj4+zy8MjqMzw1c4uIccdnxjm7BIAAMgyywTgd999V71799bf//53SdLcuXO1evVq/ec//9Hw4cMd2iYnJys5Odn+PDExUZKUlJT08AqWlJZ89aEeD8iqh/0zAQDAnaT/m2SMuWdbSwTglJQU7d69WyNGjLBvc3V1VUhIiKKjozO0nzBhgsaOHZthu7+/f47WCfzVeE91dgUAADi6dOmSvL2979rGEgH47NmzSk1Nla+vr8N2X19fHTp0KEP7ESNGKDIy0v48LS1N58+fV9GiReXi4pKjtSYlJcnf318nT56Ul5dXjh4LzsV7bR2819bA+2wdvNe5kzFGly5dUsmSJe/Z1hIBOKs8PDzk4eHhsK1QoUIPtQYvLy9+qCyC99o6eK+tgffZOnivc597jfyms8QqEMWKFZObm5sSEhIctickJMjPz89JVQEAAMAZLBGAbTab6tSpo/Xr19u3paWlaf369QoODnZiZQAAAHjYLDMFIjIyUt27d1fdunX1xBNPaOrUqbpy5Yp9VYjcwsPDQ6NHj84wBQOPHt5r6+C9tgbeZ+vgvf7rczH3s1bEI2LmzJmaMmWK4uPjVbNmTU2fPl3169d3dlkAAAB4iCwVgAEAAABLzAEGAAAA0hGAAQAAYCkEYAAAAFgKARgAAACWQgDOZWbNmqUyZcoob968ql+/vnbs2OHskpCNJkyYoHr16qlgwYLy8fFR+/btFRsb6+yy8BBMnDhRLi4uGjhwoLNLQQ747bff9NJLL6lo0aLy9PRUtWrVtGvXLmeXhWyWmpqqkSNHqmzZsvL09FRgYKDGjx8v1hP46yEA5yKLFy9WZGSkRo8erT179qhGjRoKDQ3V6dOnnV0assmmTZsUHh6ubdu2KSoqSjdu3FDLli115coVZ5eGHLRz5069//77ql69urNLQQ64cOGCGjVqJHd3d61Zs0YHDx7UO++8o8KFCzu7NGSzSZMmac6cOZo5c6Z++uknTZo0SZMnT9aMGTOcXRqyiGXQcpH69eurXr16mjlzpqQ/vq3O399f/fv31/Dhw51cHXLCmTNn5OPjo02bNqlJkybOLgc54PLly6pdu7Zmz56tf//736pZs6amTp3q7LKQjYYPH66tW7fq+++/d3YpyGFt2rSRr6+vPv74Y/u2jh07ytPTU59++qkTK0NWMQKcS6SkpGj37t0KCQmxb3N1dVVISIiio6OdWBlyUmJioiSpSJEiTq4EOSU8PFxhYWEOP9t4tKxcuVJ169ZVp06d5OPjo1q1aunDDz90dlnIAQ0bNtT69et1+PBhSdKPP/6oLVu2qHXr1k6uDFllma9Czu3Onj2r1NRU+fr6Omz39fXVoUOHnFQVclJaWpoGDhyoRo0aqWrVqs4uBzlg0aJF2rNnj3bu3OnsUpCDfv75Z82ZM0eRkZH617/+pZ07d+qf//ynbDabunfv7uzykI2GDx+upKQkVapUSW5ubkpNTdWbb76prl27Ors0ZBEBGHCS8PBw7d+/X1u2bHF2KcgBJ0+e1IABAxQVFaW8efM6uxzkoLS0NNWtW1dvvfWWJKlWrVrav3+/5s6dSwB+xCxZskSfffaZFi5cqCpVqigmJkYDBw5UyZIlea//YgjAuUSxYsXk5uamhIQEh+0JCQny8/NzUlXIKREREVq1apU2b96sUqVKObsc5IDdu3fr9OnTql27tn1bamqqNm/erJkzZyo5OVlubm5OrBDZpUSJEgoKCnLYVrlyZX355ZdOqgg5ZciQIRo+fLi6dOkiSapWrZp++eUXTZgwgQD8F8Mc4FzCZrOpTp06Wr9+vX1bWlqa1q9fr+DgYCdWhuxkjFFERISWL1+uDRs2qGzZss4uCTmkRYsW2rdvn2JiYuyPunXrqmvXroqJiSH8PkIaNWqUYTnDw4cPKyAgwEkVIadcvXpVrq6O0cnNzU1paWlOqgh/FiPAuUhkZKS6d++uunXr6oknntDUqVN15coV/f3vf3d2acgm4eHhWrhwob766isVLFhQ8fHxkiRvb295eno6uTpkp4IFC2aY250/f34VLVqUOd+PmEGDBqlhw4Z666231LlzZ+3YsUMffPCBPvjgA2eXhmzWtm1bvfnmmypdurSqVKmi//3vf3r33XfVs2dPZ5eGLGIZtFxm5syZmjJliuLj41WzZk1Nnz5d9evXd3ZZyCYuLi6Zbp83b5569OjxcIvBQ9esWTOWQXtErVq1SiNGjNCRI0dUtmxZRUZGqnfv3s4uC9ns0qVLGjlypJYvX67Tp0+rZMmSeuGFFzRq1CjZbDZnl4csIAADAADAUpgDDAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAANALtesWTMNHDjQ2WXo3Llz8vHx0fHjxx/qcbt06aJ33nnnoR4TwKONAAwAD8gYo5CQEIWGhmbYN3v2bBUqVEi//vrrn+5/2bJlGj9+/IOUmC3efPNNtWvXTmXKlHHY3rRpU7m4uMjFxUU2m02VK1fWwoULs+24b7zxht58800lJiZmW58ArI0ADAAPyMXFRfPmzdP27dv1/vvv27fHxcVp6NChmjFjhkqVKvWn+k5JSVGRIkVUsGDB7Cr3T7l69ao+/vhj9erVy2G7MUb/+9//9Pbbb+vUqVOKjY1Vq1at1K1bN8XFxWXLsatWrarAwEB9+umn2dIfABCAASAb+Pv7a9q0aXrttdcUFxcnY4x69eqlli1b6uWXX5YkrV27Vk8++aQKFSqkokWLqk2bNjp27JhDP82aNVNERIQGDhyoYsWKKTQ0NMMUiLS0NE2ePFnly5eXh4eHSpcurTfffNO+/17HST9GRESEvL29VaxYMY0cOVLGmDue33//+195eHioQYMGDtuPHDmiS5cuqVWrVvLz81PZsmXVq1cvpaamKjY29kEuqYO2bdtq0aJF2dYfAGsjAANANunevbtatGihnj17aubMmdq/f7/DiPCVK1cUGRmpXbt2af369XJ1dVWHDh2Ulpbm0M+CBQtks9m0detWzZ07N8NxRowYoYkTJ2rkyJE6ePCgFi5cKF9f3ywdZ8GCBcqTJ4927NihadOm6d1339VHH310x3P7/vvvVadOnQzbd+/ercKFCysoKEiS9Ouvv+r111+Xh4eHqlevfv8X7x6eeOIJ7dixQ8nJydnWJwALMwCAbJOQkGCKFStmXF1dzfLly+/a9syZM0aS2bdvn31b06ZNTa1atRzaNW3a1AwYMMAYY0xSUpLx8PAwH3744X3XdPtxmjZtaipXrmzS0tLsbYYNG2YqV658xz7atWtnevbsmWH7a6+9ZlxdXU3+/PlN3rx5jSTj6elp5s2b59Bu69at5t///vd913y7H3/80Ugyx48f/9N9AEA6RoABIBv5+PjoH//4hypXrqz27ds77Dty5IheeOEFlStXTl5eXvYPk504ccKhXWYjrel++uknJScnq0WLFndscz/HadCggVxcXOzPg4ODdeTIEaWmpmba57Vr15Q3b94M2/fs2aPw8HDFxMTo+++/V9OmTTVo0CD16NHDoV3Dhg31+uuv37Hme/H09JT0x1xkAHhQBGAAyGZ58uRRnjx5Mmxv27atzp8/rw8//FDbt2/X9u3bJf3xQbdb5c+f/459pwfBu7nf42RFsWLFdOHChQzb9+zZo4YNG6p8+fKqW7euZs+erUmTJmVYKq1Tp07atWuXateube/nhx9+0PPPPy9J6tChg7p06aJ69eopMDBQu3btcnj9+fPnJUnFixf/0+cAAOkIwADwEJw7d06xsbF644031KJFC1WuXDnTQHkvFSpUkKenp9avX/9Ax0kPxem2bdumChUqyM3NLdN+a9WqpYMHDzps+/nnn3Xx4kVVrVrVvi0oKEiBgYEZlkE7cOCAKlasqMTERBUuXFiStG/fPlWrVk2StHfvXtWuXVs7d+7UuHHjMqz7u3//fpUqVUrFihXLtD4AyAoCMAA8BIULF1bRokX1wQcf6OjRo9qwYYMiIyOz3E/evHk1bNgwDR06VJ988omOHTumbdu26eOPP87ScU6cOKHIyEjFxsbq888/14wZMzRgwIA7Hjc0NFQHDhxwCNO7d++Wu7u7Hn/8cYe2LVq00PLly+3Pr169KhcXF508eVIVKlSwb9+/f7+qVq2qy5cv6/r16xo8eLAkZRrav//+e7Vs2TILVwoA7owADAAPgaurqxYtWqTdu3eratWqGjRokKZMmfKn+ho5cqQGDx6sUaNGqXLlynr++ed1+vTpLB2nW7duunbtmp544gmFh4drwIAB6tOnzx2PWa1aNdWuXVtLliyxb9uzZ48qVKggm83m0DYkJES7d++2f/nH/v37VaVKFXvgTbdr1y5Vq1ZN+/btU5UqVeyjz3v27LGPDEvS9evXtWLFCvXu3ftPXC0AyMjFmLss/AgAeOQ0a9ZMNWvW1NSpU7P0utWrV2vIkCHav3+/XF3vf/zko48+Unx8vIoVK6azZ8/qjTfe0NatW9W6dWslJibqgw8+0Lvvvqv9+/crKSlJzZs317JlyxQYGChJmjNnjpYvX65vvvkmS/UCwJ1k/JQGAACZCAsL05EjR/Tbb7/J39//vl+3d+9ehYSEqEaNGmrXrp0OHz6sgIAAVa5cWS4uLtq7d6+efvpp1alTR8YYTZ482R5+Jcnd3V0zZszIiVMCYFGMAAOAxfzZEeA/q3bt2lq9erVKlCiR6f7GjRtr4cKFWQrVAPAgGAEGAIvZuHHjQzlOSkqKGjRooFatWt0x/ErK8ogyADwoRoABAABgKawCAQAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwFAIwAAAALIUADAAAAEshAAMAAMBSCMAAAACwlP8P6LBFbL3++8cAAAAASUVORK5CYII=\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"transits_rad['radius'].plot(kind='hist', figsize=(8, 5))\n",
"\n",
"plt.title('Gecis Yapan Gezegenlerin Yaricap Histogrami')\n",
"plt.ylabel('N')\n",
"plt.xlabel(\"Yaricap ($R_{jup}$)\")\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Özellikle $[0.0-0.1]$ aralığındaki yığılma bu histogramın yorumlanmasını güçleştirmektedir. Bu nedenle bu veriyi ikiye bölmekte fayda var: $R \\le 0.4 R_{jup}$ ve $R > 0.4 R_{jup}$ gibi küçük ve büyük gezegenleri birbirinden ayıran bir gruplama faydalı olabilir. Ayrıca küçük gezegenler için Jüpiter yarıçapı yerine Dünya yarıçapını kullanmak daha faydalı olacaktır. Bu amaçla `astropy.constants` öznitelikleri arasında yer alan `R_earth` ve `R_jup` değerlerinden faydalanılabilir."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_6896/2249128842.py:3: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" transits_rad['Rearth'] = transits['radius']*R_earth_jup\n"
]
}
],
"source": [
"from astropy import constants as const\n",
"R_earth_jup = const.R_jup / const.R_earth\n",
"transits_rad['Rearth'] = transits['radius']*R_earth_jup"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"kucukgez = transits_rad[transits_rad['radius'] <= 0.4]\n",
"buyukgez = transits_rad[transits_rad['radius'] > 0.4]"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"kucukgez['Rearth'].plot(kind='hist', figsize=(8, 5))\n",
"\n",
"plt.title('Gecis Yapan Kucuk Gezegenlerin Yaricap Histogrami')\n",
"plt.ylabel('N')\n",
"plt.xlabel(\"Yaricap ($R_{\\oplus}$)\")\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Bu histogram biraz daha sınırlanıp ($0.5 - 4.0 R_{\\oplus}$), kutucuk sayısı arttırıldığında (25) küçük gezegenlerin birbiriyle kesişen biri $1.3 R_{\\oplus}$, diğeri $2.2 R_{\\oplus}$ civarında maksimuma ulaşan iki ayrı popülasyondan oluştukları görülmektedir. Gezegen sayısının görece az olduğu ve en \"dip\" noktası $1.8 R_{\\oplus}$ civarında olan bu aralık literatürde Yarıçap Vadisi (ing. radius valley, [Radius gap](https://sites.astro.caltech.edu/~fdai/radius_gap.html), [Fulton gap](https://ui.adsabs.harvard.edu/abs/2017AJ....154..109F/abstract)) olarak bilinmektedir. Bu \"vadinin\" sol tarafında karasal gezegenler (süper-Dünyalar ve daha küçük gezegenler), sağ tarafında ise bir gaz zarfa sahip gezegenlerin (mini-Neptünler ve daha büyük gezegenler) bulunmaktadır. Bu ayrımın başlangıçta ince atmosfere sahip gezegenlerin genç-yıldızlarının ilk 100 milyon içinde enerjik X-ışın ve morötesi ışınlarıyla atmosferlerini tamamen kaybedip karasal birer çekirdek olarak kalırken, daha kalın atmosfere sahip olanların atmosferlerinin bir kısmını koruyabildikleri düşünülmektedir ([Owen ve Wu 2017](http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:1705.10810)). Alternatif bir açıklama çekirdeğin çok sıcak olduğu ilk zamanlarda da atmosferi kaçırabileceği üzerine kurulmuştur ([Ginzburg vd. 2017](http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:1708.01621)). [Hirano ve Dai (2017)](http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:1710.03239) tarafından bu iki açıklama üzerine yapılan bir araştırma için [bkz.](https://sites.astro.caltech.edu/~fdai/radius_gap.html). Her ne kadar ilk bulunduğunda bu aralık bir \"boşluk\" olarak isimlendirilmişse de sonradan bu aralıkta bulunan gezegenlerle birlikte giderek bir \"vadiye\" dönüştüğü görülmüştür. Ancak yine de bu aralık iki ayrı gezegen popülasyonunu birbirinden ayırıyor gibi görünmektedir."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"buyukgez['radius'].plot(kind='hist', bins=50, figsize=(8, 5))\n",
"\n",
"plt.title('Gecis Yapan Buyuk Gezegenlerin Yaricap Histogrami')\n",
"plt.ylabel('N')\n",
"plt.xlabel(\"Yaricap ($R_{\\oplus}$)\")\n",
"plt.xlim(0,2.0)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Bu dağılımda da $0.75 R_{jup}$ civarında bir başka vadi görmek mümkündür. Ancak bu vadi kısa yörünge dönemli ($P < 2.2$ gün) gezegenlerin yörünge dönemlerine karşılık kütleleri çizdirildiğinde kendisini çok daha iyi ortaya koyan Jüpiter-altı cisim çölü (ing. sub-Jovian desert) ya da sıcak-Neptün çölü olarak bilinen parametre uzayından kaynaklanmaktadır.. Bu grafik saçılma grafikleri konusunda örnek olarak verilecektir."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Çubuk (Sütun) Grafikleri ##\n",
"\n",
"Çubuk (sütün) grafikleri, özellikle kategorik veride her bir kategorinin ya da özelliğin gözlenme sıklığını karşılaştırmak için kullanılır. `maptlotlib` de bir çubuk grafiği yatay (`barh`) ya da daha sıklıkla dikey (`bar`) çubuklar (sütunlar) kullanılarak iki farklı yapıda oluşturulabilir.\n",
"\n",
"### Örnek: Keşif Yöntemlerinin Birbirleri İle Karşılaştırılması ###\n",
"\n",
"`exoplanet.eu` veritabanındaki ötegezegenlerin her bir keşif yöntemiyle ne kadarının keşfedildiğni karşılaştırarak performanslarını görselleştirmek için çubuk grafiklerinden yararlanılabilir. "
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"detection_type\n",
"Astrometry 20\n",
"Default 32\n",
"Imaging 218\n",
"Microlensing 238\n",
"Primary Transit 3751\n",
"Radial Velocity 1033\n",
"TTV 26\n",
"Timing 48\n",
"Name: detection_type, dtype: int64"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"yontemler = exoeu.groupby(\"detection_type\")['detection_type'].count()\n",
"yontemler"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(10,5))\n",
"renkler = [\"purple\",\"violet\",\"blue\",\"green\",\"yellow\",\"orange\",\"red\",\"brown\"]\n",
"yontemler.plot(kind=\"bar\", color=renkler)\n",
"plt.title(\"Kesif Yontemlerinin Performansi\")\n",
"plt.xlabel(\"Yontem\")\n",
"plt.ylabel(\"Kesif Sayisi\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Bir `matplotlib` stili de kullanarak bu grafiği yatay bir çubuk grafiği ile keşifleri performanslarına göre sıralayarak ve yüzde kaçının o yöntemle yapıldığını da çubukların üzerine yazarak görselleştirmek daha bilgi verici olabilir. "
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib as mpl\n",
"mpl.style.use('ggplot') # ggplot-stili\n",
"plt.figure(figsize=(10,5))\n",
"yontemler.sort_values().plot(kind=\"barh\", color=\"red\")\n",
"for i,sayi in enumerate(yontemler.sort_values()): \n",
" label = \"%{:.2f}\".format(sayi/exoeu.shape[0]*100)\n",
" # place text at the end of bar (subtracting 47000 from x, and 0.1 from y to make it fit within the bar)\n",
" plt.annotate(label, xy=(sayi, i-0.1), color='black')\n",
"plt.title(\"Kesif Yontemlerinin Performansi\")\n",
"plt.xlabel(\"Kesif Sayisi\")\n",
"plt.ylabel(\"Yontem\")\n",
"plt.xlim((0,4000))\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Pasta Grafikleri ##\n",
"\n",
"Bir \"pasta grafiği\", bir daireyi (veya pastayı) orantılı dilimlere bölerek kategoriler arası sayısal oranları karşılaştırmalı olarak görselleştiren dairesel bir grafiktir. Medyada yaygın olarak kullanıldığı iyi bilinen bir tür olan pasta grafikleri `matplotlib` de `kind=pie` parametresi çizdirilir.\n",
"\n",
"Bir önceki örnekte verilen ötegezegen keşif yöntemleri arası performans karşılaştırmasını bir de pasta grafiği ile görselleştirerek yapmak faydalı olacaktır."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# yine yontemleri basarisina gore siralamak iyi bir fikirdir\n",
"yontemler.sort_values().plot(kind='pie',\n",
" figsize=(12, 8),\n",
" autopct='%%%1.2f', # yuzde isaretini kullan\n",
" startangle=90, # 90 dereceden baslayip terse git\n",
" shadow=True, # add shadow \n",
" )\n",
"# y-ekseni gosterme\n",
"plt.ylabel(None)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Görüldüğü gibi bazı yöntemlerde az sayıda keşif olduğu için birbirleriyle karışabilmektedir. Bunu önlemek için bir miktar görselleştirme iyileştirmesine ihtiyaç duyulur."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"rengler = ['gold', 'yellowgreen', 'lightcoral', 'lightskyblue', 'lightgreen', 'pink', 'turquoise', 'cyan']\n",
"kenarlik = [0.25, 0.3, 0.1, 0.1, 0.1, 0.1, 0.15, 0.2] # ortadan uzaklastirma miktarlari\n",
"\n",
"yontemler.plot(kind='pie',\n",
" figsize=(15, 9),\n",
" startangle=90, \n",
" shadow=True, \n",
" labels=None,\n",
" colors=renkler, # renklendir\n",
" explode=kenarlik # 'ortadan verilen miktar kadar uzaklastir\n",
" )\n",
"\n",
"# basligi biraz yukari al\n",
"plt.title('Kesif Yontemlerinin Performansi', y=1.05) \n",
"\n",
"plt.ylabel(None)\n",
"\n",
"#plt.axis('equal') \n",
"\n",
"# legend ekle\n",
"plt.legend(labels=yontemler.index, loc='lower left') \n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Kutu Diyagramları ##\n",
"\n",
"[Kutu diyagramları (ing. box plots)](http://ozgur.astrotux.org/ast416/Ders_01/Ders01_Hata_Analizi.html#Kutu-Grafikleri) Bütün veriyi dört çeyreğe ayırarak ve ortaya ortanca değeri (medyan) getirerek bir dağılımın hem görselleştirilmesine hem de veri setindeki aykırı noktaların görülebilmesine (ve gerektiğinde ayıklanabilmesine) olanak veren grafiklerdir. İlk çeyreğin sonunu gösteren Q1 değeri ile son çeyreğin başını gösteren Q3 arasındaki uzaklık, çeyrekler arası uzaklık (ing. Inter-Quartile Range, IQR) olarak tanımlanır. Kutu diyagramının her iki taraftan sınırı Q1 ve Q3'e, 1.5 x IQR kadar uzaklıktadır ve buralar bir çizgi ile (whisker) gösterilir. \n",
"\n",
"
\n",
" \n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Örnek: Dışmerkezlilik Aralıkları ###\n",
"\n",
"Farklı keşif yöntemleri farklı dış merkezlilikteki gezegenlerin keşfedilmesine daha duyarlıdır. Örneğin geçiş yöntemi yıldızına yakın ve büyük gezegenleri keşfetmeye daha duyarl olduğundan aynı zamanda bu özellikleri nedeniyle yıldızıyla aralarındaki kuvvetli tedirginlik etkileşmeleri sonucu daha çembersel yörüngelere zorlanmış gezegenleri keşfetmek konusunda daha başarılıdır. Doğrudan görüntüleme yönteminde ise yöntemin teknik sınırları nedeniyle yıldızına uzak ve genç gezegenlerin keşfedilmesi daha kolaydır. Bu gezegenlerin yörünge dış merkezlilikleri de bu nedenle daha büyük olabilmektedir. Keşif yöntemlerine göre bu aralıklara bakmak ve karşılaştırmak çok iyi bir fikir olacaktır.\n",
"\n",
"Öncelikle verileri analiz için tekrar hazırlamak gerekecektir."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"# Daha once bu veri islendigi icin tekrar orjinal halini elde etmek gerekebilir\n",
"# Istatistiksel olarak anlamli sayida ornek barindiran 4 kesif yontemi\n",
"exoeu_ecc = exoeu.dropna(subset=['eccentricity'])\n",
"transits_ecc = exoeu_ecc[exoeu_ecc['detection_type'] == \"Primary Transit\"]\n",
"radvel_ecc = exoeu_ecc[exoeu_ecc['detection_type'] == \"Radial Velocity\"]\n",
"imaging_ecc = exoeu_ecc[(exoeu_ecc['detection_type'] == \"Imaging\") & exoeu_ecc['eccentricity'] < 1]\n",
"lensing_ecc = exoeu_ecc[exoeu_ecc['detection_type'] == \"Microlensing\"]"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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TBal8jRw5EvHx8e2KI7IVHDNiRXZ2dnj55Zdx/Phxo3EhJSUlOH78OF566aUuvRQ8tW7YsGEAAHt7e6Pbx/v7+8Pe3l4UR/IzfPhw4bFCoRAdM9w2jCOSOxYjElAoFCYHKDY/MZH8/Pe//wUANDQ0oLi4WHSsqKgIDQ0NojiSH8PPtvl5wHCbOUC2hMWIFWm1WqxatQqDBw82WgTGy8sLgwcPxurVq0W3lSd5MVzmXaPRiI4ZbnM5ePn65ZdfzBpHJAcsRqxIf6O8kydPYuDAgdizZw8qKyuxZ88eDBw4ECdPnsTly5e5voCMGQ5KdHBwwMyZM/Hmm29i5syZcHBwMBlH8mLY+6FQKDB27Fi89tprGDt2rKh3lNO7yZawGLEi/WJm48ePx3vvvYe6ujrs2bMHdXV1eO+99zBu3DhRHMmP4QyanJwcJCQk4JlnnkFCQgJycnJMxpG8ODo6Co9Pnz6NuLg4BAUFIS4uDqdPnzYZRyR3NzWbJjk5GXv27EF5eTmCgoKwYMEC4X4bpuzduxf79u1DSUkJ3N3dERUVhblz53bp+6/cDP2gVT8/P4wePdrorr36YqQrLHqWlpaG1NRUVFZWwtfXF7NmzWr15m7MgSYffPCB8HjEiBF4/vnnMW/ePHz88cd4/fXXRXGTJk2SookdwjzouJSUFOHxHXfcYXSjPMO4V155xaptuxnMATKHDveMZGRkYNu2bZg9ezbWrVuHoKAgrF27Fjdu3DAZn56eju3bt2POnDn4v//7PyxZsgRHjx7Fjh07brnxXY1+EaOPPvoIYWFhoss0YWFh+Oijj0RxnVV2djZ27dqFadOm4bnnnoOfnx82bdqEyspKk/HMgd+Vl5cDAKZMmYKysjI8//zz8PPzw/PPP4+ysjJMnjxZFNeZMQ9ujuHN3QwLkebbXeEmcMwBMpcO94x8/fXXmDhxIsaPHw8AWLhwIbKzs3Hw4EHcf//9RvHnzp1DWFgYRo0aBaBpMaeRI0ciNzf31lreBTVfyKqxsVH4r7W4zubQoUMYMWKEsB7KnDlzkJOTg8zMTJN/zTMHfjd06FCcOHEC58+fx/nz5/HRRx+hpKQEXl5e+MMf/oAJEyYIcZ1da3kwffp0o3jmQZOwsDChV3TChAno168f7OzsoNVq8csvvwh3bg4LC5Oyme3CHCBz6VAx0tDQgIsXL4qKDqVSicGDB+P8+fMmnxMWFoa0tDTk5eUhJCQEv/32G3766SeMHj26xZ9TX18v+qtAoVAIt1OXw/TXkJAQnD17VrToWUBAAEJCQpCXlweg877PhoYG5OfnY/LkyUIb7ezs0L9/f1y6dMlku5kDv1u5ciU++ugjXLp0CYsWLcLTTz+NsWPH4vDhw1i0aJEwi2blypWd+n22lQemMA+azJ8/X7hUc+TIEaH4AIBu3bqJ4jrze2QOmJf+vcjpPXVEh4qRiooK6HQ6eHh4iPZ7eHjg2rVrJp8zatQoVFRU4KWXXgLQNL118uTJeOCBB1r8OV9++SV27twpbPfr1w/r1q0zmg7b1ein7F64cAH33HMPXnjhBTg5OaG2thbJycnYu3evEOfj4yNlU1tUWloKnU6Hfv36idro4+ODnJwck+1mDojdd999+Oqrr3DgwAEcOHDA5PHg4GAJWtZ+beWBqc+JedDEcFHDuro60THDbTs7u057HgCYA5Ziq6svW3w5+NOnT+PLL7/En//8Z4SGhqKwsBBbtmzBzp07MXv2bJPPmTlzJmJjY4VtfaVYXFwsLArVFekHaL3wwgv473//i6+//lo4FhgYiL/97W/417/+BZVKhYKCAqma2Sr92KCSkhK4ubkJ+6uqqlBfX4+CggLY29uLThTMAbF3330XarUa3377rdGxqVOn4t133+20n79eW3lQXFxs9GXBPGiiPw+EhoaavDyh39+ZzwMAc8DcFAoFvL29UVhYKKtp3c2/D1qM68iLuru7Q6lUGg2uKy8vN+ot0fv0008xZswYTJw4EUDTl65arUZiYiIeeOAB0ehxPQcHB9GaC4a68ocUGRmJgIAAZGVlIS0tDVlZWdBoNFCpVBg+fDgWLlyIwMBAREZGdtr36ezsDKVSiYqKClEbKysr4ebmZrLdzAFjmzdvRm1tLVavXo2CggL4+PjgpZdegpOTU5d4f23lgSnMgyb680Dfvn2xe/duPP3007h27Rp8fX3x1ltv4cknn0RdXV2nPg8AzAFLMTWO0BZ0aDaNvb09goODcerUKWGfTqfDqVOn0L9/f5PPqaurM7oGZirhbIH+3jQpKSlYuHAhVCoVYmNjoVKpsHDhQqSkpHT6e9PY29vD399f9BedTqfD+fPn0bdvX5PPYQ6YplKpcO+99+Kxxx7Dvffe26WmNjIPbp7heSAuLg5jxozB008/jTFjxiAuLq5LnAcA5gCZV4cv08TGxiIhIQHBwcEICQlBUlIS6urqhDUyNm7cCE9PT8ydOxcAEBERgb1796Jfv35Ct9ynn36KiIgIm0zCmJgYJCYmYtWqVaIBrIGBgUhMTERMTIyErWufcePGYfv27QgICEBgYCAOHz4MjUYjjKjfunUrfH19mQOtSEpKwqpVq4zWmnn55Ze7RA4AbecBzwUti4mJwZIlS5CYmChad8TOzg5LlixhDpDN6XAxEh0djYqKCnz22WcoLy9H3759sWLFCuEyTUlJiajynTVrFhQKBT755BOUlpbC3d0dEREReOSRR8z2JrqamJgYTJ06FceOHRMu00RGRnb6v4T0wsPDUV1djW+++QYVFRXw8/PD4sWLha7ZsrIyYbQ7wBxoLikpCYsWLcKkSZPwzjvvYNy4cTh06BDefvttLFq0qMsUpW3lAc8FLUtKSsKmTZswceJETJgwQRgrkJqaik2bNiE8PJw5QDZF0diFLk4VFxd3iYWA2kOr1XbZYqQtDg4OFhvp3tVzQKvVYuTIkRgwYAA2b94szJgoKCiAVqvFggULcO7cOaSnp3fpfLBkDgBdOw8Mc+C9994zOXaMOdC2rpwDpigUCuFc0IW+ltvU3jyw+GwaMiaHLnq6OfqbJSYkJKCxsREZGRmignTZsmW47777kJmZiejoaKmbSxagz4F58+aZvC3EvHnzsH//fuYA2RRepLMyfRf9gAEDRMvBDxgwAIsWLUJSUpLUTSQLKioqAgD8+uuvGDlyJGbPno25c+di9uzZGDlyJC5fviyKI/nRf7br1q1DcXGx6FhxcTHWrVsniiOyBSxGrEir1WLVqlWYNGkSNm/ejIiICLi6uiIiIgKbN2/GpEmTsHr1amFxNJIf/VL/cXFxJgvSuLg4URzJj/7eU42NjRg1apQoB0aNGiV00Xf2e1QRmROLESvSd8/GxcUZjRxXKpVYtmwZLl++jMzMTIlaSJY2fPhw2NnZwcvLC/Hx8di5cydmzZqFnTt3Ij4+Hl5eXrCzs8Pw4cOlbipZiL7Y6N69OzZs2ICNGzciOjoaGzduxIYNG9C9e3dRHJEt4JgRK9J3uw4YMMDkcf1+ds/KV1ZWFrRaLUpKSozyYOvWraI4jheQp++//x5A0wqmt99+u7D/5MmTou3vv/8eY8aMsXr7iKTAnhEr0ne9nz171uRx/X520ctXewtNFqREZEvYM2JFUVFRCAgIQHx8vDCtU0+n02Hjxo0IDAwUFgwi+dF3wQPA+PHjMXnyZGGNif379+PgwYNGcSQv4eHhwuOxY8di6tSpQg58++23OHz4sFEckdyxZ8SKDJeBXrBgAbKyslBZWYmsrCwsWLCgyywDTTdPf3M8R0dHJCYmQqPRIDs7GxqNBomJiXB0dBTFkfx89NFHwmM7OztcuHAB33//PS5cuCD63TeMI5I79oxYmX45+H/+85+i5eADAgK6zMqbdPOOHz8OAFCr1QgNDRUdW7lypVEcyc+5c+eEx6mpqe2KI5I79oxIpPnNosg2GN7d2tSMKlNxJC89evQwaxyRHLAYsTIuembbHn/8ceFx84HKhtuGcSQvTz/9tPC4+Z2aDbcN44jkjsWIFXHRM7pw4YLw+LfffsOsWbOQnZ2NWbNm4bfffjMZR/Jy8eJF4bFGo8G4ceOQlpaGcePGQaPRmIwjkjsWI1bERc/o119/FR43Njbiiy++QHh4OL744gvRIleGcSQvP/zwg2j70KFDGD16NA4dOtRqHJGcsRixIi56Rnp9+/bt0H6Sj5qaGgBAYGCgyeP6/fo4IlvA2TRWZLjoWUREhNFxLnomf+Hh4di6dSsuXbqEnj17YuTIkejZsyeuX7+OI0eO4NKlS0IcydPQoUORlpaGy5cvm8wB/c0Shw4dKnFLiayHxYgVcdEz6tWrl/C4tLQUu3fvFrYNZ1gZxpG83H333di4cSMA4Pr166IcaB5HZCt4mcaKuOgZGd4KoPmN0Ay3W7plAHV958+fN2sckRywZ8TK9IuerVq1SrToWWBgIBc9swGGA1MVCoWoADHc5gBW+WrvZ8scIFvCYkQCMTExmDp1Ko4dOwaNRgOVSoXIyEj2iNiY1ooRsg3MAaImLEYkYmdnh+joaPj4+KCgoIAnIBsxZMgQ4XHv3r1RWFhoctswjuTF8LPt06ePKAcMt5kDZEs4ZoTIik6cOCE8Li0txdKlS3H+/HksXboUpaWlJuNIXpgDRMbYM0JkRfoesG7duqG+vh4JCQlISEgA0LTwXbdu3VBXV8eeMhljDhAZYzFCZEX66bt1dXVGx3Q6nbCfN1KUL+YAkTFepiGyovYuZsZFz+SLOUBkjMUIkRW1dzEzLnomX8wBImMsRois6MyZM2aNo66HOUBkjMWIRDQaDRITExEXF4fExETRrcNJvo4dO2bWOOp6mANExjiAVQJr1qxBYmIitFqtsG/16tVYtGgRXnzxRQlbRpZWW1tr1jjqepgDRMbYM2Jla9aswbvvvosePXpg/fr1KCgowPr169GjRw+8++67WLNmjdRNJAvq37+/8Njb21t0zHDbMI7kxfCzbT5jxnCbOUC2hMWIFekvzXh5eeHHH3/EvHnz4O3tjXnz5uHHH3+El5cXL9nI3E8//SQ8vn79OkaOHIl58+Zh5MiRuH79usk4kpfs7GzhsVKpFOWAUqk0GUckdyxGrGjr1q3QarV4/vnnYW8vvkJmb2+P5cuXQ6vVYuvWrRK1kCytqqpKeFxfX48jR47g448/xpEjR1BfX28yjuTlypUrwmOtVivKAcNLt4ZxRHLHYsSK9HfhnDx5ssnjkyZNEsWR/Li7u5s1johIDliMWFFQUBAAYP/+/dBqtcjIyMCOHTuQkZEBrVaLlJQUURzJz+zZs4XHpnrHTMWRvERFRQmPm9+p23DbMI5I7jibxormz5+P1atXY82aNdiwYQOuXr0qHPPz80NlZSXs7Owwf/58CVtJlnTq1CnhsVarxejRozF16lR8++23SE9PNxlH8mLY62V4Wab5NnvHyJawGLEilUqFSZMm4dtvv0VFRYXomL4wmTp1KlQqlRTNIysoKioCADg5OaG2thZpaWlIS0sTjuv36+NIfgwHKpsjjkgOWIxYkVarRVZWVqsxP/74I7RarVH3LcmDq6srgKY1JMaPH4+amhpUVlbCzc0Nzs7OOHjwoCiO5Ke9f2zwjxKyJSxGrOjo0aPCXzsTJkyAo6Mj1Gq18P/U1FSUlJTg6NGjGDVqlMStJUu499578cUXX8DR0RGnT58W9YD06dNHyIV7771XwlaSJRnOklGpVKKp/IbbnE1DtoTFiBXpxwQEBwfj/PnzyM/PF475+/sjODgYFy9eRHp6OosRmdLf/EytVkOtVouO/fbbb0ZxJD8XL14UHjdfU8hw2zCOSO44m8aKrl27BqDpJDNw4EDs2bMHlZWV2LNnDwYOHCicfPRxJD9hYWFtLvn/4osvIiwszEotImtrbGw0axyRHLAYsSIfHx8AQPfu3fH+++8jIiICrq6uiIiIwPvvv4/u3buL4kh+nJyc8MQTT+C9996Dv7+/6Ji/vz/ee+89PPHEE3BycpKohWRpt99+u/C4T58+omOGtwQwjCOSOxYjVuTp6QkAuHHjBh5//HFkZWWhsrISWVlZePzxx3Hjxg1RHMlXTEwMMjIysG7dOgDAunXrkJGRgZiYGIlbRpZmODjZ8NIcABQWFpqMI5I7jhmxIsNxAGlpacIiZwDg6OhoMo7ky87ODkOHDgUADB06lDOobER77z3Fe1SRLWHPiBUZdsE2v1tnS3FEJC99+/Y1axyRHLAYsaKoqCgEBARgyJAh8PLyEh3r1asXhgwZgsDAQC4DTSRjEyZMEB77+vqKjvn5+ZmMI5I7FiNWZGdnh5dffhknTpxAcXGx6FhRURFOnDiBl156id31RDK2Z88e4XHzmXOGt4gwjCOSOxYjElAoFEaXaZRKZauXbohIHqqrq80aRyQHLEasSKvVYtWqVZg0aRLOnj2LnTt3Yvv27di5cyfOnDmDSZMmYfXq1UY3zyIi+QgPDwfQ9EeJqbv26v8o0ccR2QLOprGizMxMXLlyBQkJCXBwcEB0dDR8fHxQUFCAxsZGLFu2DPfddx8yMzMRHR0tdXOJyAL0BUhjYyOUSiVGjBiBvn374tKlS8jMzBT+GOHlWrIlLEasSH8fkgEDBpg8rt/PO7YSydelS5eEx/X19UhPTxduFdFSHJHc8TKNFfXu3RsAcPbsWZPH9fv1cUQkP+39Y4N/lJAtYTFiRfqpvfHx8dDpdKJjOp0OGzdu5NReIpkznNbv6emJGTNm4E9/+hNmzJghWn25+fR/IjljMWJF+qm9KSkpWLBggWg5+AULFiAlJYVTe4lkznAJeKVSCZ1Oh8bGRuh0OiiVSpNxRHLHMSNWFhMTg8TERKxatQozZswQ9gcGBiIxMZH3JiGSufLycgBNhUhJSQm+/vpr0XF9gaKPI7IFLEYkEBMTg6lTp+LYsWPQaDRQqVSIjIxkjwiRDdD3fuh0OigUCtxxxx0YNGgQcnJycOrUKeESrmEvCZHcsRiRiJ2dndHUXiKSv0mTJuHYsWMAmgqOkydP4uTJkwCazgv6qb2TJk2SrI1E1sbSm4jIigxXWm6+wKHhNldkJlvCnhGJaLVaXqYhskHN70dzq3FEcsBiRAJJSUlYtWoVrly5IuwLCAjAyy+/zAGsRDIXEBAAAHB1dUVVVZXRcf1+fRyRLeBlGitLSkrCokWLMGDAAOzZsweVlZXYs2cPBgwYgEWLFiEpKUnqJhKRBelXWq6qqsLYsWMxcOBA+Pn5YeDAgRg7dqxQoLS0UjORHLFnxIoMb5S3efNm2NnZwdXVFREREdi8eTMWLFiA1atXY+rUqbxkQyRT169fFx4fPnxYeHz16lWcOXPGZByR3LFnxIr0N8qLi4szmranVCqxbNkyXL58GZmZmRK1kIgsrb1FBosRsiUsRqzI8EZ5tbW1+Pvf/46pU6fi73//O2pra3mjPCIb4ObmJjz28PAQHTPcNowjkrubukyTnJyMPXv2oLy8HEFBQViwYAFCQkJajK+ursaOHTtw7NgxVFVVoVevXpg/fz7Cw8NvuuFdkf4GeI8++qiwzoDe1q1bERkZKYrrzNLS0pCamorKykr4+vpi1qxZCAoKajGeOSBPzIOO27dvn/C4+Sqrhtv79u3Dww8/bKVW3TzmAJlDh4uRjIwMbNu2DQsXLkRoaCj27t2LtWvX4q233kL37t2N4hsaGrBmzRq4u7vj2WefhaenJ0pKSuDs7GyWN9CVREVFwdHREceOHYNKpcKiRYvw9NNP46233kJiYiKOHTsGR0fHTn+jvOzsbOzatQsPPvgggoKCcPjwYWzatAkrVqww+dccc0CeWssDwxu+6TEPmlRXV5s1TkrMATKXDhcjX3/9NSZOnIjx48cDABYuXIjs7GwcPHgQ999/v1F8amoqqqqqsHr1atjbN/24rvCXvyVoNBqo1WoAwKhRozBlyhT07t0bU6ZMQU5ODlJTU6FWq6HRaODk5CRxa1t26NAhjBgxQiia5syZg5ycHGRmZppcNZI5IE+t5cH06dON4pkHTdo7OL0rDGJnDpC5dKgYaWhowMWLF0VFh1KpxODBg3H+/HmTz/nxxx8RGhqKDz74AFlZWXB3d8fIkSNx//33t3jvhfr6etTX1wvbCoVC+HLuyqsSrl69GgAwffp0nDx5UnSjvICAAEybNg3JyclYvXo1XnvtNama2aqGhgbk5+dj8uTJwmdhZ2eH/v3749KlSyY/H+ZAy/TvRaFQdKn31VYemMI8aPLjjz8Kj1UqFTQajcntH3/8sVO/R+aAeRmeC2xRh4qRiooK6HQ6k4OuWlot8LfffkNxcTFGjRqFv//97ygsLMT7778PrVaLOXPmmHzOl19+iZ07dwrb/fr1w7p169CrV6+ONLfTKSgoAADExsaKpvABTb/E99xzD5KTk1FQUAAfHx8pmtim0tJS6HQ69OvXT9RGHx8f5OTkmGw3c6Bl+pzw8vLqtJ+5KW3lganPiXnQpLa2VnhsWIg0366tre3UOcEcsAxvb2+pmyAJi68z0tjYCHd3dyxevBhKpRLBwcEoLS3F7t27W0y+mTNnIjY2VtjWV4rFxcVoaGiwdJMtRv8Lu3TpUkyePBkbN27E2LFjcfjwYWzYsAFxcXFCnP5LqrO5ceMGAKCkpEQ0PqSqqgr19fUoKCiAvb296ETBHGhZSUmJ8P/O+pmb0lYeFBcXG31ZMA+aODg4GN2TpqW4zpwTzAHzUigU8Pb2RmFhoaxunNr8+6DFuI68qLu7O5RKpckR4M17S/Q8PDxgb28v6oLz8/NDeXk5GhoahOuGhhwcHODg4GDy9bryh7RixQps3boVCoUCmzZtgpOTE1xdXREeHo5NmzYhJCQEjY2NWLFiRad9n87OzlAqlaioqBC1sbKyEm5ubibbzRxomf69NDY2dqn31VYemMI8aBIbGyv8pe/g4IDhw4cLl2eysrKESxKxsbGd+j0yByyjq50LzKVD64zY29sjODgYp06dEvbpdDqcOnUK/fv3N/mcsLAwFBYWQqfTCfsKCgrQo0cPk4knZydOnADQlGwDBw7E2rVrcf78eaxduxYDBw4UElAf1xnZ29vD398fubm5wj6dTofz58+jb9++Jp/DHJAf5sHNO3TokPC4vr4eR48exeHDh3H06FHR2AjDuM6IOUDm1OFFz2JjY3HgwAEcOnQI+fn5eP/991FXV4dx48YBADZu3Ijt27cL8VOmTEFVVRU+/PBDXLt2DdnZ2fjyyy8xdepUs72JrkK/mNnEiROh0WiQkJCAsLAwJCQkQKPRYOLEiaK4zmrcuHE4evQojh07hsLCQnz++efQaDTCiPqtW7cyB2xAW3nAc4FplZWVZo2TEnOAzKXDpWh0dDQqKirw2Wefoby8HH379sWKFSuEyzQlJSWi0cBeXl74xz/+ga1bt2L58uXw9PTE9OnTTU4Dljv9FLannnoK77zzDp588klcu3YNvr6+ePvtt3H27FkcOHCg0091Cw8PR3V1Nb755htUVFTAz88PixcvFrpmy8rKRFOTmQPy1FYe8FxgmouLC+rq6toV19kxB8hcFI1d6OJUcXGxqBuzq9FqtRg5ciQ8PT1RXFwsmoHk6+uLXr16oaysDOnp6V1ijYGWODg4WGyke1fPgeZOnjwpTOkePHiw1M0xG0vmANC18yA5ORmPP/54m3EffPABpk2bZoUWWQZzoGMUCoUweaELfS23qb15wHvTWJGdnR1iY2Nx/Phxo6nQ165dw/Hjx3HPPfd06UKEiFo3YcIE0XavXr2wdOlSoxN28zgiOWMxYkVarRZbtmxpNWbLli3tmvZHRF1T87tyFxcXIyEhAcXFxa3GEckZixErSktLg1qthr29Pc6dO4eVK1di2bJlWLlyJc6dOwd7e3uo1WqkpaVJ3VQispCjR48CAJ599ln06dNHdMzb2xvPPvusKI7IFnAulRX95z//AdA0An3ixInIz88Xjr3//vsYN24cUlJS8J///EeYnURE8qIf59C7d29s3rwZ2dnZwqrL4eHhOH78uCiOyBawGLEi/WJxKSkp6Natm+hYcXGxUJw0X1SOiOQjICAAAPDCCy+0K47IFvAyjRUNGTJEeNx8ap/htmEcEcnLAw88gO7duwMAIiMjhcsyzz77LCIjIwE0rVT6wAMPSNZGImtjMWJFU6ZMER47ODhg2bJlyM3NxbJly0TLHRvGEZG8uLq64o033oBCocCJEyfw5ptvAgDefPNNnDx5EgqFAuvXr4erq6vELSWyHhYjVnTs2DHhcX19PTZu3IjQ0FBs3LhRdH3YMI6I5CcmJgaJiYlG03m9vLyQmJiImJgYiVpGJA0WI1akv+dMSwvAeHl5ieKISL5iYmJw5MgRrFu3DgCwbt06HDlyhIUI2SQOYLUi/RLpxcXFmDBhAhwdHaFWq4X/p6amiuKISN7s7OwwdOhQAMDQoUO54CHZLPaMWNFdd90l2h45ciTmzZuHkSNHthpHREQkZ+wZsaLbb79deJyamir0hLQWR0REJHfsGbGi0tJSs8YRERHJAYsRK+rZsyeApiWfm18btrOzg7e3tyiOiIjIFrAYsSKFQgGgaWXFM2fOYP78+ZgyZQrmz5+PM2fOCCsu6uOIiIhsAceMWFFJSQkA4IcffsCQIUOgVquFY59++qmwrY8jIiKyBewZsaLevXu3eMywN6S1OCIiIrlhz4gVDR8+HHZ2dujRoweOHj2Kjz/+GCUlJfDy8sK8efMwYsQIlJWVYfjw4VI3lYiIyGpYjFhRVlYWtFotSkpKMHjwYNFlmn/961/CdlZWFqKjo6VqJhERkVXxMo0VFRUVCY9bu2uvYRwREZHcsRixIsMpu42NjaJjhtuc2ktERLaExYgVGRYczafvGm43L1SIiIjkjMWIFR05ckR43FoxYhhHREQkdyxGrOj48ePCY5VKJTpmuG0YR0REJHecTWNFNTU1AAAXFxecPHkS2dnZ0Gg0UKlUCA8Px+DBg1FdXS3EERER2QIWI1bk7OwMAKiursbjjz+OmpoaVFZWws3NDc7OzqiurhbFERER2QIWI1Y0dOhQpKWlAQAOHjzYahwREZGt4JgRKxo9erRZ44iIiOSAxYgVDR482KxxREREcsBixIqeeeYZs8YRERHJAYsRK/rll18ANM2m8ff3Fx0LCAgQBq7q44iIiGwBB7BakX5hs/79++Orr77CsWPHhKm9kZGRmDFjBn7++WejBdGIiIjkjMWIFQ0fPhznzp3DTz/9hPr6ekRHR8PHxwcFBQWora3Fzz//LMQRERHZChYjVhQaGio8DgkJwahRozBt2jQkJycjPT3dZBwREZHcsRixovnz52P16tVobGyETqdDWlqasO4IACiVSigUCsyfP1/CVhIREVkXB7BakUqlwqRJk6DT6eDg4ICgoCCEhoYiKCgIDg4O0Ol0mDRpktF9a4iIiOSMPSNWpNVqkZOTg6CgIOTn5+PXX38VjtnZ2SEoKAhnzpyBVquFnZ2dhC0lIiKyHvaMWFFmZiauXLmCPn36QKvVio5ptVr06dMHly9fRmZmpkQtJCIisj4WI1ZUVFQEADh27BhUKhWWLVuGvLw8LFu2DCqVCseOHRPFERER2QJeprEiDw8PAIC9vT3OnTuHbt26wcfHBytWrMBf//pXhIaGoqGhQYgjIiKyBewZsaLk5GQAgL+/PxQKBTIyMrBjxw5kZGRAoVDAz89PFEdERGQL2DNiRZcvXwYAXLp0CQMGDIBarRaOOTo6Ctv6OCIiIlvAnhEr6tu3b4vHDJeAby2OiIhIbliMWNGKFSsANBUeWVlZmD9/PqZMmYL58+fjhx9+EAoSfRwREZEt4GUaKzpx4gQAoLGxEXfccYfo2NatW0Vx0dHRVm0bERGRVNgzYkXtnbLLqb1ERGRLWIxYUY8ePQA0TfE9e/as6DLN2bNnhSm9+jgiIiJbwGLEis6ePQsA8PHxgVIp/qdXKpXw8fERxREREdkCjhmxoitXrgAAzpw5g/79+4uOGY4Z0ccRERHZAvaMWFFQUJBZ44iIiOSAxYgVPfjgg8Lj5nflNdw2jCMiIpI7FiNWtG7dOuGxqbv2moojIiKSOxYjVnTx4kWzxhEREckBB7BaUW1trfDYwcEBYWFh8PDwQHl5Oc6dO4f6+nqjOCIiIrljMWJF7u7uwuPevXvj1KlTwrafnx+uXr1qFEdERCR3vExjRZcuXRIeX7t2DbNmzUJ2djZmzZqFa9eumYwjIiKSO/aMWJGzs7PwuLGxEV988QW++OKLVuOIiIjkjsWIFfn6+gqXZry8vBASEgKVSgWNRoO8vDyUlJQIcURERLaCxYgVTZ8+Hfv27QMAlJSUCMWHqTgiIpKv2tpa5OXlCdtqtRpVVVVwdXWFo6OjsD8kJAROTk5SNNGqWIxYkb+/v1njiIioa8rLy8O0adPajEtOTsbgwYOt0CJpsRixoqioKPTs2RPXr19vMcbLywtRUVFWbBUREVlbSEgIkpOThe3c3FzExcUhPj4eoaGhojhbwGLEyjQaDQCgR48ecHd3h0ajgUqlQkVFBcrKylBXVydxC4mIyNKcnJxM9niEhobaRE9IcyxGrOjo0aOorKyEh4cHysrKUFZWJjquXwDt6NGjGDVqlEStJCIisq6bKkaSk5OxZ88elJeXIygoCAsWLGhXV9KRI0ewYcMGDB8+HM8///zN/OguLSMjAwBQXl4OhUKBxsZG4ZhCoUB5ebkQ19mLkbS0NKSmpqKyshK+vr6YNWtWu+42bOs5IDfMA2IOkDl0eNGzjIwMbNu2DbNnz8a6desQFBSEtWvX4saNG60+r6ioCB999BEGDhx4043t6gxvhjdhwgS8+uqr2Lx5M1599VVMmDDBZFxnlJ2djV27dmHatGl47rnn4Ofnh02bNqGysrLV5zEH5IV5QMwBMpcOFyNff/01Jk6ciPHjx8Pf3x8LFy6ESqXCwYMHW3yOTqdDfHw8HnzwQfTu3fuWGtyV6Xs+VCoVTp8+jRUrVmDBggVYsWIFTp8+DZVKJYrrrA4dOoQRI0YgKioK3t7emDNnDlQqFTIzM1t8DnNAfpgHxBwgc+nQZZqGhgZcvHgR999/v7BPqVRi8ODBOH/+fIvP27lzJ9zd3TFhwgScOXOmzZ9TX18v3DQOaLqEoZ9nrVAoOtLkTqW4uBhA0yDWwsJC0THD7eLi4k77PhsaGpCfn4/JkycLbbSzs0P//v1x6dKlFtvNHDBN/14UCkWXel9t5UFLmAfGmAOts4UcALpuHphLh4qRiooK6HQ6eHh4iPZ7eHiI7q1i6OzZs0hNTcXrr7/e7p/z5ZdfYufOncJ2v379sG7dOvTq1asjze10vLy82h3n4+Nj4dbcnNLSUuh0OvTr10/URh8fH+Tk5JhsN3OgZQUFBQA692duSlt5YOpzYh6YxhxonS3kANB188BcLDqbpra2FvHx8Vi8eHGH7kQ7c+ZMxMbGCtv6KrG4uBgNDQ1mb6e1BAQECI8N79ILNC10lp+fL8TpE7Oz0Y8NKikpgZubm7C/qqoK9fX1KCgogL29vXCiYA60Tr8Kb0lJSaf9zE1pKw+Ki4tFXxbMg5YxB1pnCzkAdN08aIvh90GrcR15UXd3dyiVSqMxDeXl5Ua9JQDw22+/obi4GOvWrRP26WeQPPzww3jrrbfg7e1t9DwHBwc4ODiYbIPhDJSu5siRI8Lj6upq9OnTB3V1dejWrRuqqqpEcXFxcVI0sU3Ozs5QKpWoqKgQfRaVlZVwc3Mz+nyYA63Tv5fGxsYu9b7ayoPmmActYw4wB4Cumwfm0qFixN7eHsHBwTh16hQiIyMBNA1GOnXqlMllbX19ffHGG2+I9n3yySdQq9V47LHH2n3ZQi4MZxy1Nki1rZlJUrK3t4e/vz9yc3MxZMgQAE05cP78eYwePdoonjkgT8wDYg6QOXX4Mk1sbCwSEhIQHByMkJAQJCUloa6uDuPGjQMAbNy4EZ6enpg7dy5UKhUCAwNFz3dxcQEAo/224M4778SJEyfaFdeZjRs3Dtu3b0dAQAACAwNx+PBhaDQaYRn7rVu3wtfXlzkgc23lAc8F8sccIHPpcDESHR2NiooKfPbZZygvL0ffvn2xYsUK4TJNSUmJTY4Ebo+nnnoK27ZtAwB4enpizpw5GDJkCE6cOIHPP/8cpaWlQlxnFh4ejurqanzzzTeoqKiAn58fFi9eLHTNlpWV2cRdJm1dW3nAc4H8MQfIXBSNXejiVHFxsWiKV1dz3333ISsrq8244cOH46uvvrJCiyzDwcHBYiPdu3oONHfy5ElMmzZNdnfmtGQOAPLKA+bAzZFTDgDMgw4vekY375dffgHQNHPGFD8/P1EcERGRLeCN8qyoe/fuuH79OvLz8zF+/HjU1NQII8+dnZ2FVWy7d+8ucUuJiIish8WIFb344otYsGABAODMmTOiVVcNp7S9+OKLVm8bERGRVHiZxoqcnZ2Fx60tB28YR0REJHcsRqxIf28ac8URERHJAYsRK9IXGX5+fsJgVT1/f39hH4sRIiKyJRwzYkVlZWUAmsaHfPHFF8jKyoJGo4FKpcLw4cPxwAMP4OrVq0IcERGRLWDPiBUplU3/3NnZ2Vi4cCFUKhViY2OhUqmwcOFC/PTTT6I4IiIiW8BvPSsaMWIEAOC2227D2bNnMWPGDLi7u2PGjBk4d+4cgoODRXFERES2gJdprCg6Oho9e/ZEXl4eJk6ciCVLlsDb2xuFhYVITU3FgQMH4OXlhejoaKmbSkREZnbx4kVUV1ebPJabmyv6vykuLi7CH61yw2LEijQaDZ544gmsWbMG6enpOHDggHCsW7duAIAlS5ZAo9Hw3i5ERDJy8eJFk3czbi4uLq7V42lpabIsSFiMWFFeXh7WrFkDAKirqxMd02+vWbMGo0aNktW9CYiIbJ2+RyQ+Ph6hoaFGx9VqNaqqquDq6gpHR0ej47m5uYiLi2uxZ6WrYzFiRSEhIUhOTgYAaLVafPvtt3j77bfx5JNPYurUqbCzsxPiiIhIfkJDQ03+salQKODj44OCggJ0ofvXmg2LEStycnISJaGdnR3efvttxMTEsCeEiIhsFmfTEBERkaRYjBAREZGkWIwQERGRpFiMEBERkaRYjBAREZGkWIwQERGRpDi1l8jCuAQ0EVHrWIwQWRCXgCYiahuLESIL4hLQRERtYzFCZAVcApqIqGUcwEpERESSYjFCREREkmIxQkRERJJiMUJERESSYjFCREREkmIxQkRERJJiMUJERESSYjFCREREkmIxQkRERJJiMUJERESS4nLwREREFqbRAc5+obhWAziXqo2OKwDcUFai5HotTN0Y4lpN0/M1Oos3VRIsRoiIiCysRA0MemoT3skDkHephaiW9gOAAwY9tQkl6nqzt60zYDFCRERkYV6OQM6GJdgYH48QE3fwVgDw6tULJcXFJntG8nJzsSwuDl7vxVu8rVJgMUJERGRhKiVQczUXvs7AbZ6ORscVCgV8+rihQFdl8g7eNc5Nz1fJdKSnTN8WERERdRUsRoiIiEhSLEaIiIhIUixGiIiISFIsRoiIiEhSLEaIiIhIUixGiIiISFIsRoiIiEhSLEaIiIhIUixGiIiISFIsRoiIiEhSLEaIiIhIUrxRHhGRhV28eBHV1dUmj+Xm5or+3xIXFxcEBwebvW1EnQGLESIiC7p48SJGjx7dZlxcXFybMWlpaSxISJZYjBARWZC+RyQ+Ph6hoaFGx9VqNaqqquDq6gpHR+NbywNNvSZxcXEt9q4QdXUsRoiIrCA0NBSDBw822q9QKODj44OCggI0NjZK0DIi6XEAKxEREUmKxQgRERFJisUIERERSYrFCBEREUmKA1iJiIgsrLa2FgBw8uRJk8fbmlXV1jo0XR2LESIiIgvLy8sDACxfvvyWXsfFxcUczel0WIwQERFZ2LRp0wAAISEhcHJyMjquX0umpfVoAHmvwstihIiIyMI8PT0xd+7cNuNaWo9G7m6qGElOTsaePXtQXl6OoKAgLFiwACEhISZjU1JS8N133+HKlSsAgODgYDzyyCMtxlPXkJaWhtTUVFRWVsLX1xezZs1CUFCQyVjmgHwxD4g5QObQ4dk0GRkZ2LZtG2bPno1169YhKCgIa9euxY0bN0zG5+TkYOTIkXjllVewZs0a9OzZE2vWrEFpaektN56kkZ2djV27dmHatGl47rnn4Ofnh02bNqGystJkPHNAnpgHxBwgc+lwMfL1119j4sSJGD9+PPz9/bFw4UKoVCocPHjQZPyTTz6JqVOnom/fvvDz88OSJUvQ2NjY4ohi6vwOHTqEESNGICoqCt7e3pgzZw5UKhUyMzNNxjMH5Il5QMwBMpcOXaZpaGjAxYsXcf/99wv7lEolBg8ejPPnz7frNerq6tDQ0ABXV9cWY+rr61FfXy9sKxQKYcCPQqHoSJM7Nf17USgUXeZ9NTQ0ID8/H5MnTxbabGdnh/79++PSpUvteh+2mgOm2m2YAzfzfKm0lQftYYt5cKs50JE4S2MOmFdX/D4wpw4VIxUVFdDpdPDw8BDt9/DwwLVr19r1Gh9//DE8PT1bHaDz5ZdfYufOncJ2v379sG7dOvTq1asjze30CgoKAABeXl7w8fGRuDXtU1paCp1Oh379+ona7OPjg5ycnHa9D1vKAf1n3KtXr1b/bby9vW/p+dbWVh6053OylTy41RzoyGtYE3PAvLri94E5WXU2za5du3DkyBGsXLkSKpWqxbiZM2ciNjZW2NZXicXFxWhoaLB4O62lpKRE+L8+ETs7/digkpISuLm5CfurqqpQX1+PgoIC2Nvbt3iisLUcKC4uFv5v6jNWKBTw9vZGYWGhyTu2tvV8qbSVB8XFxa1+WdhSHtxqDrTnNaTAHDCvrvh90B6tfR+I4jryou7u7lAqlSgvLxftLy8vN+otaW737t3YtWsXXnrppRZHWus5ODjAwcHB5DE53WJb/14aGxu7zPtydnaGUqlERUWFqM2VlZVwc3Nr9X3Yeg601u725EBnet9t5UFrbDkPbjUH2noNa2IOmFdX/D4wpw4NYLW3t0dwcDBOnTol7NPpdDh16hT69+/f4vO++uorfPHFF1ixYgVuu+22m28tSc7e3h7+/v6ipYl1Oh3Onz+Pvn37tvg85oC8MA+IOUDm1OHZNLGxsThw4AAOHTqE/Px8vP/++6irq8O4ceMAABs3bsT27duF+F27duHTTz/FE088gd69e6O8vBzl5eVQq9VmexNkXePGjcPRo0dx7NgxFBYW4vPPP4dGo0FUVBQAYOvWrcwBG9BWHvBcIH/MATKXDo8ZiY6ORkVFBT777DOUl5ejb9++WLFihXCZpqSkRDQSeP/+/WhoaMCbb74pep3Zs2fjwQcfvLXWkyTCw8NRXV2Nb775BhUVFfDz88PixYuFrtmysjLRcsfMAXlqKw94LpA/5gCZy00NYJ02bZqwzn5zK1euFG0nJCTczI+gTm706NEYPXq0yWNPP/20aMASc0C+WssDngtsA3OAzKHDl2mIiIiIzInFCBEREUmKxQgRERFJyqqLnhHZGo0OcPYLxbUawLnUeMaAAsANZSVKrtfC1MoC12qanq/RWbypRESSYTFCZEElamDQU5vwTh6AvEstRLW0HwAcMOipTShR17cSQ0TUtbEYIbIgL0cgZ8MSbIyPR0hoqNFxBQCvXr1QUlxssmckLzcXy+Li4PVevMXbSkQkFRYjRBakUgI1V3Ph6wzc5ulodFyhUMCnjxsKdFUml4CucW56voqju4hIxniKIyIiIkmxGCEiIiJJsRghIiIiSXHMCBERkZXV1tYiLy9P2Nbf/djwLsgAEBISIrrXl1yxGCEiIrKyvLw8k/d4i4uLE20nJydj8ODB1mqWZFiMEBERWVlISAiSk5OFbbVajaqqKri6usLR0VEUZwtYjBAREVmZk5OTqMdDoVDAx8cHBQUFJqf5yx2LEQu7ePEiqqurTR5r6RqhIRcXFwQHB1ukbURERJ0BixELunjxIkaPHt1mXPNrhM2lpaWxICEiItliMWJB+h6R+Ph4hJpYCryla4R6ubm5iIuLa7FnhYiISA5YjFhBaGioydHQtn6NkIiICOCiZ0RERCQxFiNEREQkKRYjREREJCkWI0RERCQpFiNEREQkKRYjREREJCkWI0RERCQpFiNEREQkKRYjREREJCkWI0RERCQpFiNEREQkKd6bhojIgjQ6wNkvFNdqAOdStdFxBYAbykqUXK9FS3eoulbT9BoanUWbSiQZFiNERBZUogYGPbUJ7+QByLvUQlRL+/UcMOipTShR15u1bUSdBYsRIiIL8nIEcjYswcb4eISEhhodVwDw6tULJcXFLfaM5OXmYllcHLzei7doW4mkwmKEiMiCVEqg5moufJ2B2zwdjY4rFAr49HFDga4KjY2my5Ea56bXUHGUH8kUU5uIiIgkxWKEiIiIJMVihIiIiCTFMSNEFlRbWwsAOHnypMnjarUaVVVVcHV1haOj8XiC3Nxci7aPiKgzYDFCZEF5eXkAgOXLl9/S67i4uJijOUREnRKLESILmjZtGgAgJCQETk5ORsdzc3MRFxeH+Ph4hJqY9gk0FSLBwcEWbScRkZRYjBBZkKenJ+bOndtmXGhoKAYPHmyFFhERdT4cwEpERESSYjFCREREkmIxQkRERJJiMUJERESSYjFCREREkmIxQkRERJJiMUJERESSYjFCREREkmIxQkRERJJiMUJERESS4nLwFqTRAc5+obhWAziXqo2OKwDcUFai5HotGk08/1pN0/M1Oos3lYiISDIsRiyoRA0MemoT3skDkHephaiW9gOAAwY9tQkl6nqzt42IiKizYDFiQV6OQM6GJdgYH48QE3dkVQDw6tULJcXFJntG8nJzsSwuDl7vxVu8rURERFJhMWJBKiVQczUXvs7AbZ6ORscVCgV8+rihQFeFxkbjcqTGuen5Ko7sISIiGePXHBEREUmKxQgRERFJisUIERERSYrFCBEREUmKA1iJiCyotrYWAHDy5EmTx9VqNaqqquDq6gpHR+OB7gCQm5trsfYRdQYsRoiILCgvLw8AsHz58lt+LRcXl1t+DaLOiMUIEZEFTZs2DQAQEhICJycno+O5ubmIi4tDfHw8Qk2sR6Tn4uKC4OBgi7WTSEosRoiILMjT0xNz585tMy40NBSDBw+2QouIOp+bKkaSk5OxZ88elJeXIygoCAsWLEBISEiL8UePHsWnn36K4uJieHt7Y968eQgPD7/pRpP00tLSkJqaisrKSvj6+mLWrFkICgpqMZ45IE/MA2IOkDl0eDZNRkYGtm3bhtmzZ2PdunUICgrC2rVrcePGDZPx586dw4YNGzBhwgSsW7cOd911F9avX4/Lly/fcuNJGtnZ2di1axemTZuG5557Dn5+fti0aRMqKytNxjMH5Il5QMwBMpcOFyNff/01Jk6ciPHjx8Pf3x8LFy6ESqXCwYMHTcYnJSXhzjvvxIwZM+Dv74+HH34YwcHBSE5OvuXGkzQOHTqEESNGICoqCt7e3pgzZw5UKhUyMzNNxjMH5Il5QMwBMpcOXaZpaGjAxYsXcf/99wv7lEolBg8ejPPnz5t8zvnz5xEbGyvaN3ToUPzwww8t/pz6+nrU1/9+p1qFQiEM/FIoFB1psqSaT+lTq9W4cuWKcFyhUMDDwwPl5eWie9MEBATA0dFRGIWvj+0MGhoakJ+fj8mTJwttsrOzQ//+/XHp0iWT7bTlHGiupqZG9LnqHxvuA5oGOzo7O1u1bR3RVh6YwjxowhxgDpiify9yek8d0aFipKKiAjqdDh4eHqL9Hh4euHbtmsnnlJeXo3v37qJ93bt3R3l5eYs/58svv8TOnTuF7X79+mHdunXo1atXR5oruZKSEgC3PqUvODgYPj4+5mjSLSstLYVOp0O/fv1EbfLx8UFOTo7JdtpyDjSXnZ0tzK4wtGzZMtH2jz/+iNtuu81azeqwtvLA1OfEPGjCHGAOtMbb21vqJkiiU86mmTlzpqh61leKxcXFaGhokKpZHXb33Xdj/fr1wpS+jvaMAICrqytcXV1RUFBg9faboh8bVFJSAjc3N2F/VVUV6uvrUVBQAHt7+1s+UcglB5rr3r27qEu6rq4OlZWVcHNzQ7du3URxneUzN6WtPCguLjbLl4Uc84A50DFyzAFTFAoFvL29UVhYaPIu7l1Ve78POlSMuLu7Q6lUGlWx5eXlRr0leh4eHkaDW2/cuNFiPAA4ODjAwcHB5LGu9CGZmtJ31113CY8VCgV8fHxQUFDQ6vvqTO/Z2dkZSqUSFRUVonbpT6am2mrLOdCck5OTaPpmaznQmd9nW3lgCvOgCXOAOdCaxsZGWb6vtnSoGLG3t0dwcDBOnTqFyMhIAIBOp8OpU6dMdjsCQP/+/XHy5Encc889wr4TJ060urhPaz9fjrrS+3JwcEBAQAAuXLiAiIgIAE05kJubi7Fjx8LBwcHo/TAH2tbV3ldbeWDq/TAPWtfV3hNzwDLk9r7a+346/K5jY2ORkJCA4OBghISEICkpCXV1dRg3bhwAYOPGjaIegZiYGKxcuRJ79uxBeHg4jhw5ggsXLmDRokUd/dHo0aNHh5/TFXS1a58zZ85EQkICbr/9diEH6uvrcc8998DDw4M5cBO6Wg4AzANzYw50jBxzAOiaeWAOHS5GoqOjUVFRgc8++wzl5eXo27cvVqxYIXSzlZSUiEYDh4WF4cknn8Qnn3yCHTt2wMfHB8uXL0dgYKDZ3kRXVVtbi5UrV2LlypUml4nurJgD5tNVcwBgHpgLc4A5AHTtPDAHRaMtXpzqJGpqavDYY4/hww8/7NRT+MhymAPEHCCAedDhRc+IiIiIzInFCBEREUmKxYiEHBwcMHv27BanrZH8MQeIOUAA84BjRoiIiEhS7BkhIiIiSbEYISIiIkmxGCEiIiJJsRghIiIiSclrEfwuIicnB7t378Yvv/yCsrIyPPfcc8K9fsg2MAcIYB4Qc0CPPSMSqKurQ9++ffH4449L3RSSCHOAAOYBMQf02DMigWHDhmHYsGFSN4MkxBwggHlAzAE99owQERGRpFiMEBERkaRYjBAREZGkWIwQERGRpFiMEBERkaQ4m0YCarUahYWFwnZRUREuXboEV1dXeHl5SdgyshbmAAHMA2IO6PGuvRI4ffo0/vnPfxrtHzt2LJYuXSpBi8jamAMEMA+IOaDHYoSIiIgkxTEjREREJCkWI0RERCQpFiNEREQkKRYjREREJCkWI0RERCQpFiNEREQkKRYjREREJCkWI13QoUOH8OCDD6KoqEjqplA7FBUV4cEHH8ShQ4ekbgoAICEhwaYWU5ILfm62benSpUhISJC6GRZj88vBP/jgg+2Ke+WVV3D77bdbuDU379tvv0W3bt0wbtw4qZvSJRw6dAjvvPOOsK1UKtG9e3cMGTIEjzzyCDw9PSVsXZPMzEz8+9//xuLFizFx4kSTMSdOnMCaNWvw2GOPISYmxsotlA99Prz22mu47bbbpG4OSYi5IA2bL0aWLVsm2v7uu+9w4sQJo/1+fn7WbFarxowZg+joaDg4OAj79u3bBzc3NxYjHfTggw+id+/eqK+vR25uLg4dOoSzZ8/i3//+N1QqlaRtCw8Ph7OzM9LT01ssRtLT06FUKjFy5Egrt46sbfHixeCC2bbrrbfegkKhkLoZFmPzxciYMWNE27m5uThx4oTR/ubq6urQrVs3SzatRUqlUvIvSrkYNmyY8NfPxIkT4ebmhq+++gpZWVmIjo6WtG0ODg64++67cfDgQZSWlhr11mg0Ghw7dgxDhgxB9+7dJWolWYu9vc2frm2a4R+fcsTsboeVK1eisrISS5cuxdatW3HhwgVMmjQJjz32GH744QekpKTg0qVLqKysRM+ePTF27Fg88MADUCqVRq/xzDPP4IMPPkBubi5cXFwQExOD++67T/TzvvnmG+zfvx9FRUVwcHBAnz59EBsbi1GjRgH4vRtx48aN6N27N5YuXYri4mIAv192GjRoEFauXImGhgZ8+eWXSEtLw/Xr19GtWzf4+flhzpw5GDJkiJX+BbuOgQMH4quvvsJvv/0m7GtoaMAXX3yB7OxsFBYWQqfToV+/fnjwwQdxxx13iJ5fXV2NDz/8EMeOHYNCocDw4cMRGxt70+0ZPXo0UlNTkZGRYfQ62dnZqKmpEfICaOrZ27t3L/Lz86FSqTB06FA8+uijNnX3T3NISEjA999/j//7v//D+++/j9OnT8PZ2RkzZ87EtGnTcPnyZWzZsgV5eXlwc3PD3LlzRZ9DVVUV/ve//+H48eMoKiqCUqlEWFgY5s6di759+4p+VnFxMTZv3oxTp06hW7duGDVqFO688068+uqrosvDCQkJyMnJEcYNFBUVYdmyZXj00Ufh7OyMr776CtevX0dQUBAef/xxhISEiH7O0aNH8dlnn6GoqAje3t546KGH8MMPP4hek9qntLQUn3zyCX766SdUV1fD29sbsbGxmDBhghCjvwHe008/jcLCQuzbtw+VlZUICwvDokWL4O3tLcQWFBTg448/xrlz51BTUwM3NzcMGDAAixYtgrOzM4CmMSODBg0Sxg3pvwdWrVqFzMxMfPfdd9BoNBgyZAgWL14Md3d34fV1Oh127tyJAwcOoLq6GqGhoXj88cfx2muviV5TSixG2qmyshKvvvoqoqOjMXr0aOEv0UOHDsHR0RH33HMPHB0dcerUKXz22Weora3FH/7wB9FrVFVVYe3atYiKisKIESPw/fff4+OPP0ZgYCCGDRsGAEhJScGWLVtw9913IyYmBhqNBpcvX0Zubq7oZGdo/vz52LJlCxwdHTFz5kwAgIeHBwDg888/x65duzBhwgSEhISgtrYWFy5cwMWLF1mMmKAfFOzi4iLsq6mpQWpqKkaOHImJEydCrVYjNTUVa9euxWuvvSZ8uTQ2NuL111/H2bNnMXnyZPj7++PYsWO3dKIfOHAgevbsifT0dKNiJD09Hd26dUNkZCQA4H//+x8+/fRTjBgxAhMnTkRFRQW++eYbvPLKK3j99ddF74naptPp8Oqrr2LgwIF49NFHkZ6ejs2bN8PR0RE7duzA6NGjERUVhf3792Pjxo3o378/evfuDQD47bff8MMPP2DEiBHo3bs3ysvLkZKSgpUrV+LNN98UernUajVWrVqFsrIyxMTEwMPDA+np6Th9+nS723nkyBHU1tZi0qRJUCgU+Oqrr/Dvf/8b8fHxQm9KdnY23nrrLQQGBuKRRx5BdXU13n333U4xNqqrKS8vxz/+8Q8AwNSpU+Hu7o6ff/4ZmzZtQm1tLe655x5R/FdffQWFQoF7770XNTU12L17N95++228+uqrAJr+2Fm7di3q6+sxffp0eHh4oLS0FD/++COqq6uFYqQlW7ZsgYuLC+bMmYOioiIkJSXhgw8+wDPPPCPEbN++Hbt370ZERASGDh2KX3/9FWvXroVGozHzv87NYzHSTuXl5Vi4cCEmT54s2v/UU0+JLplMmTIFiYmJ2LdvHx5++GFR11pZWRmWLVsmXAKaMGEC/vKXvyA1NVUoRrKzsxEQEIBnn3223W2LjIzEp59+Cjc3N6PLS9nZ2Rg2bBgWL17c4fdsC2pqalBRUSGMGdm5cyccHBwQEREhxLi6uiIhIUHUTT5x4kQ8/fTT+Oabb/DEE08AALKysnDmzBk8+uijmDFjBoCmfDB1e/D20o8H2b17N65duwZfX1+h3T/99BMiIyPh6OiI4uJifPbZZ3jooYfwwAMPCM+PjIzE3/72N3z77bei/dS2+vp6jB49WijwR40ahcWLF+Pdd9/FU089JVzGGzJkCJ5++mlhlhsABAYGYsOGDaLe0TFjxuCZZ55BamoqZs+eDaDpj4/ffvsNy5cvx1133QUAmDRpEv72t7+1u50lJSXYsGEDXF1dAQC+vr54/fXXcfz4cSGPt2/fDk9PT6xevRqOjo4AgMGDB2PlypXo1avXrfwz2ZxPPvkEOp0Ob7zxBtzc3AA0/Z6/9dZb+PzzzzF58mTRd4JGo8H69euF84eLiws+/PBDXL58GYGBgcjPz0dRURGeffZZ3H333cLz9DnSFldXV7z44ovCeJLGxkZ88803qKmpgbOzM8rLy7F3717cddddWL58ufC8zz//HJ9//vkt/3uYC6f2tpODgwPGjx9vtN8w6Wpra1FRUYGBAweirq4OV69eFcU6Ojpi9OjRwra9vT1CQkJEU3RdXFxw/fp15OXlmaXdLi4uuHLlCgoKCszyenKzevVq/PnPf8YTTzyBN998E926dcPzzz+Pnj17CjFKpVI4keh0OlRVVUGr1eK2227DL7/8IsT99NNPsLOzw5QpU0TPnTZt2i21UZ8z6enpwr7MzEzhy1K/3djYiOjoaFRUVAj/eXh4wNvbu0N/adPvDAcOu7i4wNfXF926dcOIESOE/b6+vnBxcRH9Hjs4OAiFiE6nQ2VlJRwdHeHr6yvKmZ9//hmenp4YPny4sE+lUrU4YNmUESNGCIUIAAwYMAAAhEuNpaWluHz5MsaMGSMUIkDTpdzAwMB2/xxq+qLPzMxEREQEGhsbRb9rd955J2pqanDx4kXRc8aPHy/6Q2bgwIEAfu+F1fd8/Pzzz6irq+twm/Q9Yoavr9PphEv3p06dglarxdSpU0XPmz59eod/liWxZ6SdPD09TQ4gu3LlCj755BOcOnUKtbW1omM1NTWi7Z49exqNhnZxccGvv/4qbN933304efIkVqxYAW9vbwwZMgSjRo0STjAd9eCDD2L9+vV46qmnEBAQgDvvvBNjxoxBUFDQTb2e3Dz++OPw8fFBTU0NDh48iDNnzpgcKHbo0CF8/fXXuHr1KrRarbBf3y0PNF379/DwEJ3wAQi9GTcrKCgIAQEBOHLkiPCXd3p6Otzc3DB06FAAQGFhIRobG/Hkk0+afA0Ofuw4BwcH0XV3oOmLw9TvsbOzM6qqqoRtnU6HpKQk7Nu3D0VFRdDpdMIxw8KhuLgYffr0MXo9w/EEbWk+Hkj/+tXV1QCaek5aek1vb29RcUStq6ioQHV1NVJSUpCSktJijKHmn4/+cqk+X3r37o3Y2Fh8/fXXSE9Px8CBAxEREYExY8a0eYmmtdfXf/76oqT55+/q6tqpLt3yDNVOpmavVFdXY+XKlXBycsJDDz2EPn36wMHBAb/88gs+/vhjo2l4hl22LfH398dbb72F7Oxs/Pzzz8jMzMS+ffswe/bsdq+JYmjQoEGIj4/HDz/8gOPHjyM1NRV79+7FwoULO/TXl1yFhIQIs2kiIyPx0ksvYcOGDdiwYYNQVHz33Xd45513cNddd2HGjBlwd3eHUqnErl27RANdLWn06NHYvn07Lly4gJ49e+L06dOYNGkS7OzsADR9+SkUCvz97383mWfNCyRqW0u/r+35Pf7yyy/x6aefYvz48XjooYfg6uoKhUKBrVu3mn16bkvt4TRg89P/m44ePRpjx441GdP8D7325Msf//hHjBs3Dj/88ANOnDiBLVu2YNeuXVi7dq2ol9YUuXz+LEZuwenTp1FZWYm//vWvGDRokLD/VldGdXR0RHR0NKKjo9HQ0IA33ngD//vf/3D//fff1JReV1dXjB8/HuPHj4darcYrr7yCzz//nMVIM0qlEnPnzsU///lPJCcn4/777wcAfP/99+jTpw+ee+450V+wza+39urVC6dOnYJarRZ9+V+7du2W2zZq1Cjs2LED6enp6NWrF3Q6neiSn7e3NxobG9G7d+9b7omhW/f999/j9ttvF8YT6VVXVwvjDICmnMnPz0djY6MotwoLC83WFv1fzqZe05w/xxa4u7vDyckJOp3O7BMAAgMDERgYiFmzZuHcuXN46aWXsH//fjz88MO39Lr6MUGFhYWintzKykqh96Qz4JiRW2CqIm1oaMC+fftu+jUrKytF2/b29vD390djY6Po8kBzjo6OJhOr+es5OjqiT58+qK+vv+k2ytntt9+OkJAQ7N27Vxhprv+cDf/SyM3Nxfnz50XPHTZsGLRarejz1+l0SE5ONvo5NTU1uHr1qtGlvJZ4eXlhwIAByMjIQFpaGnr37o2wsDDheGRkJJRKJXbu3Gn0F1FjY6NRHjRXWFjILyYzMnVuOHr0KEpLS0X7hg4ditLSUmRlZQn7NBoNDhw4YLa2eHp6IiAgAN999x3UarWwPycnB5cvXzbbz7EFSqUSUVFRyMzMNPlv1/wSTXvU1NQYndsDAwOhUCjMcp6+4447YGdnZ/S9ZOq8JCX2jNyCsLAwuLi4ICEhQRgMlJaWdkvdY2vWrIGHhwfCwsLg4eGB/Px8fPvttwgPD4eTk1OLz+vXrx/279+PL774At7e3ujevTvuuOMOPPvssxg0aBCCg4Ph6uqKCxcuIDMz02gwE/1uxowZePPNN3Ho0CFMmTIFEREROHbsGN544w2Eh4ejqKgI+/fvh7+/v+jkHhERgbCwMHz88ccoKioSpvaaKjiOHTuGd955B3/5y1/avWru6NGjkZiYiLKyMqOZMd7e3nj44Yexfft2FBcX46677oKjoyOKiorwww8/YOLEicIMH1NWr14NAFxvwkwiIiKwc+dOvPPOO+jfvz8uX76M9PR09OnTRxQ3efJkJCcnY8OGDaKpvfpxS+ZacfORRx7B+vXr8dJLL2HcuHGorq5GcnIyAgICRDlMvzt48CB+/vlno/1z5szB6dOn8Y9//AMTJ06Ev78/qqqqcPHiRZw8eRJbtmzp0M85deoUNm/ejLvvvhu+vr7QarX47rvvhMLnVnl4eGD69On4+uuvsW7dOtx555349ddf8dNPP8HNza3TrOrKYuQWuLm54YUXXsC2bdvwySefwMXFBaNHj8bgwYOxdu3am3rNyZMnIy0tDXv37oVarYanpyemT5/e5rTM2bNno6SkBLt370ZtbS0GDRqEO+64A9OnT0dWVhZOnDiB+vp69OrVCw899FCrX0y2LjIyEn369MGePXswadIkjBs3Tlgn4vjx4/D390dcXByOHj2KnJwc4XlKpRJ/+9vf8OGHHyItLU1Y9OyPf/wjnn/++Vtu1913340tW7agvr7e5Joz999/P3x8fLB3717hEpKXlxeGDBkimq1Bljdz5kyo1WocOXIEGRkZ6NevH1544QVs375dFOfo6IhXXnkFmzdvRlJSEhwdHTFmzBiEhYXh3//+t9lW3Rw+fDieeuopfP7559i+fTu8vb3xl7/8BYcPH0Z+fr5ZfobctNTDPW7cOLz66qvYuXMnMjMz8e2338LNzQ0BAQGYN29eh39O3759MXToUPz444/Yv38/unXrhqCgIKxYsQL9+/e/1bcBAHj00UfRrVs3HDhwACdPnkT//v3x4osv4uWXX+40K7sqGrvaKBciIpnbu3cvtm7dik2bNll0YbLly5fD3d0dL730ksV+BnVO1dXV+NOf/oSHH364U6xBxDEjREQSar4KpkajQUpKCnx8fMxWiDQ0NBiNSzh9+jR+/fXXTn03cjIPUyut7t27FwBEky+kxMs0REQSeuONN+Dl5YW+ffuipqYGaWlpuHr1aotrxtyM0tJSrF69GqNHj4anpyeuXr2K/fv3w8PDw2hVaZKfjIwMHDp0CMOGDYOjoyPOnj2LI0eOYOjQoTe9hpW5sRghIpLQ0KFDkZqairS0NOh0Ovj7++Ppp582612jXV1dERwcjNTUVFRUVKBbt24IDw/H3LlzRVONSZ4CAwNhZ2eH3bt3o6amBh4eHoiJibnlacPmxDEjREREJCmOGSEiIiJJsRghIiIiSbEYISIiIkmxGCEiIiJJsRghIiIiSbEYISIiIkmxGCEiIiJJsRghIiIiSbEYISIiIkn9PwHAAKBEapiGAAAAAElFTkSuQmCC\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(1, 4)\n",
"ax[0].boxplot(transits_ecc['eccentricity'])\n",
"ax[0].set_xlabel(\"Transits\")\n",
"ax[0].set_ylim((-0.01,1.0))\n",
"ax[1].boxplot(radvel_ecc['eccentricity'])\n",
"ax[1].set_xlabel(\"Rad. Vel.\")\n",
"ax[1].set_ylim((-0.01,1.0))\n",
"ax[2].boxplot(imaging_ecc['eccentricity'])\n",
"ax[2].set_xlabel(\"Imaging\")\n",
"ax[2].set_ylim((-0.01,1.0))\n",
"ax[3].boxplot(lensing_ecc['eccentricity'])\n",
"ax[3].set_xlabel(\"Lensing\")\n",
"ax[3].set_ylim((-0.01,1.0))\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Tüm kutu diyagramlarını tek bir grafik üzerinde göstermek için veriyi bir liste içine almak gerekir. Zira `numpy` dizilerinin ve `pandas` serilerinin bu şekilde birleştirilebilmesi için aynı uzunlukta olmaları gereklidir. Oysa listeler için böyle bir zorunluluk bulunmamaktadır."
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"eccdist = [transits_ecc['eccentricity'],radvel_ecc['eccentricity'],\n",
" imaging_ecc['eccentricity'],lensing_ecc['eccentricity']]\n",
"etiketler=[\"Transits\",\"Rad.Vel.\",\"Imaging\",\"Lensing\"]\n",
"plt.boxplot(eccdist)\n",
"plt.xticks([1,2,3,4], etiketler, rotation='vertical')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Grafik hemen hangi yöntemin ortancısının hangi yörünge dışmerkezliliğinde olduğunu göstermekte, sırasıyla kütleçekimsel mercek, dikine hız ve doğrudan görüntüleme yöntemlerinin dışmerkezliliği yüksek gezegenleri bulmak konusundaki başarısı öne çıkmaktdır. Geçiş yönteminde de pek çok yüksek dışmerkezlilikli gezegen bulunduğu halde ortanca 0'a yakındır."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Keman Diyagramları ##\n",
"\n",
"Keman diyagramları da kategorik verinin içerisindeki istatistiksel dağılımları görselleştirmek için başvurulan bir yöntemdir.\n",
"\n",
"### Örnek: Kütle Dağılımları ###\n",
"\n",
"Farklı keşif yöntemleri farklı kütle aralıklarındaki gezegenleri keşfetmeye daha duyarlıdır. Örneğin Doğrudan Görüntüleme uzak ve büyük gezegenleri keşfederken; zamanlama, kütleçekimsel mercek ve geçiş yöntemi daha küçük kütleli gezegenleri keşfetmeye daha duyarlıdır. Dikine hız yönteminde ise gezegen kütlesi yerine ($m_g$) onun yörünge eğim açısının sinüsüyle çarpımı elde edilebilir ($m_g~sin~i$). Bu nedenle dikine hız yöntemi göz ardı edilerek yine sadece istatistiksel olarak anlamlı sayıda gezegenin keşfedildiği ve kütlelerinin de bilindiği yöntemlere konsantre olunacaktır."
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"# Daha once bu veri islendigi icin tekrar orjinal halini elde etmek gerekebilir\n",
"# Istatistiksel olarak anlamli sayida ornek barindiran 4 kesif yontemi\n",
"exoeu_mass = exoeu.dropna(subset=['mass'])\n",
"massdist = [exoeu_mass[exoeu_mass['detection_type'] == \"Primary Transit\"]['mass'],\n",
" exoeu_mass[(exoeu_mass['detection_type'] == \"Imaging\")]['mass'],\n",
" exoeu_mass[exoeu_mass['detection_type'] == \"Microlensing\"]['mass'],\n",
" exoeu_mass[exoeu_mass['detection_type'] == \"Timing\"]['mass']]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Basit bir keman grafiği doğrudan görüntüleme (ing. imaging) yönteminin daha büyük gezegenleri bulmaya daha yanlı olduğu ve dağılımının $12 M_{jup}$ civarında ortalaması olan bir normal dağılıma benzediğini göstermektedir."
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"etiketler=[\"Transits\",\"Rad.Vel.\",\"Imaging\",\"Lensing\"]\n",
"plt.violinplot(massdist)\n",
"plt.xticks([1,2,3,4], etiketler, rotation='vertical')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Saçılma Grafikleri ##\n",
"\n",
"Özellikle parametreler arası ilişkileri (korelasyonları) araştırmak ve görselleştirmek için kullanılmasının yanı sıra astronomide zaman serisi verinin (ışık, dikine hız eğrileri vs.) yanı sıra başka tanım kümelerindeki verileri (tayflar, tayfsal enerji dağılımları vs.) grafik etmek için sıklıkla başvurulur.\n",
"\n",
"### Örnek: Karasal Gezegenler İçin Kütle Yarıçap Diyagramı ###\n",
"\n",
"Ötegezegenlerin tüm çeşitliliğine karşın fizik kurallar gereği karasal gezegenler için bir kütle-yarıçap ilişkisi beklenir. Dev gaz gezegenleri çok sayıda bulunan yıldızına yakın sıcak-Jüpiterler domine ettiği ve yakınlık etkileri nedeniyle bu cisimlerin büyük bir kısmının genişlemiş atmosferlere sahip olduğu için bu ilişki ancak uzun dönemli yeterli sayıda gaz gezegen keşfedildiği vakit çalışılabilecek bir konu olarak durmaktadır ve bu parametre uzayında çeşitlilik de daha fazladır. \n",
"\n",
"Bu ilişkiyi görselleştirmek üzere yine öncelikle verinin ona göre düzenlenmesi gerekecektir. Hassas yarıçap ölçümleri ancak geçiş yöntemiyle yapılabileceği için örneklemi öncelikle geçiş yapan gezegenlerle sınırlamak; bunlar arasından da dikine hızla doğası kesinleştirilen, dolayısıyla kütlesi bilinenleri almak gerekecektir. Daha detaylı bir çalışma için yalnızca bu değerler üzerindeki belirsizliği büyük olmayan (örn. <%5), güvenilir kaynaklardan gelen veriler seçilebilir. Ancak örnek olarak `exoplanet.eu` veritabanında yarıçap ve kütlesi bulunan tüm gezegenler kullanılacaktır."
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Solarize_Light2', '_classic_test_patch', '_mpl-gallery', '_mpl-gallery-nogrid', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn', 'seaborn-bright', 'seaborn-colorblind', 'seaborn-dark', 'seaborn-dark-palette', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted', 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk', 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'tableau-colorblind10']\n"
]
}
],
"source": [
"print(plt.style.available)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(9,4))\n",
"trkarasal_massrad.plot(x=\"mass\",y=\"radius\",kind=\"scatter\")\n",
"plt.xscale(\"log\")\n",
"plt.yscale(\"log\")\n",
"plt.grid(which=\"minor\")\n",
"plt.xlabel(\"Kutle ($M_{\\oplus}$)\")\n",
"plt.ylabel(\"Yaricap ($R_{\\oplus}$)\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Her ne kadar özellikle küçük kütleliler tarafında doğrusal bir ilişki görünse de kütle büyüdükçe ilişkiden ayrılan küçük yarıçaplı gezegen sayısı artmaktadır. Bu da bu gezegenlerin atmosferlerinden uçucuların ayrılmış olacağı şeklinde yorumlanabilir. Ancak böyle bir açıklamanın mutlaka fiziksel yaklaşımlarla desteklenmesi gerekir.\n",
"\n",
"`seaborn` paketi saçılma grafiklerinin görselleştirilmesinde `regplot` aracılığıyla sadece bir saçılma grafiği değil aynı zamanda bir de model opsiyonu sağlar. Aynı ilişki `seaborn.replot` fonksiyonu ile görselleştirildiğinde aşağıdaki grafik elde edilebilir."
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import seaborn as sns\n",
"sns.regplot(x='mass', y='radius', data=trkarasal_massrad)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Balon Diyagramları\n",
"\n",
"Balon diyagramları (bubble diagrams) saçılma (scatter) grafiklerinin özel bir türüdür. Veri noktasını çizdirmek üzere kullanılacak çember (balon) büyüklüğünün bir değişken üzerinden belirlenmesiyle grafik üç boyutlu hale gelmiş olur. `pyplot.plot()` ya da `pyplot.scatter()` fonksiyonlarının sırasıyla `ms` (marker size) ve `s` (size) parametrelerine bu üçüncü boyutu belirleyecek dizi değişken geçirilerek grafiğin üçüncü boyutu belirlenir."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Örnek: Sıcak Jüpiterler Metalce Zengin Yıldızları Sever ###\n",
"\n",
"Yıldızına yakın (yörünge dönemi küçük), dolayısıyla sıcak, dev gaz gezegenlerin (sıcak-Jüpiterler) diğer gezegenlere göre metalce zengin yıldızlar etrafında daha sık bulunduğuna ilişkin bulgulara rastlanmıştır ([Osborn & Bayliss 2019](https://academic.oup.com/mnras/article/491/3/4481/5628339)). Geçiş yöntemiyle keşfedilen gezegenlerin yarıçapları hassas olarak belirlenebildiğinden kütle yerine 3. boyut olarak yarıçap kulllanılmak suretiyle grafik sadece kısa yörünge dönemli gezegenler için çizdirildiğinde bu durum açıkça görülebilir."
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"/* global mpl */\n",
"window.mpl = {};\n",
"\n",
"mpl.get_websocket_type = function () {\n",
" if (typeof WebSocket !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof MozWebSocket !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert(\n",
" 'Your browser does not have WebSocket support. ' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.'\n",
" );\n",
" }\n",
"};\n",
"\n",
"mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = this.ws.binaryType !== undefined;\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById('mpl-warnings');\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent =\n",
" 'This browser does not support binary websocket messages. ' +\n",
" 'Performance may be slow.';\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = document.createElement('div');\n",
" this.root.setAttribute('style', 'display: inline-block');\n",
" this._root_extra_style(this.root);\n",
"\n",
" parent_element.appendChild(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message('supports_binary', { value: fig.supports_binary });\n",
" fig.send_message('send_image_mode', {});\n",
" if (fig.ratio !== 1) {\n",
" fig.send_message('set_device_pixel_ratio', {\n",
" device_pixel_ratio: fig.ratio,\n",
" });\n",
" }\n",
" fig.send_message('refresh', {});\n",
" };\n",
"\n",
" this.imageObj.onload = function () {\n",
" if (fig.image_mode === 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function () {\n",
" fig.ws.close();\n",
" };\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"};\n",
"\n",
"mpl.figure.prototype._init_header = function () {\n",
" var titlebar = document.createElement('div');\n",
" titlebar.classList =\n",
" 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
" var titletext = document.createElement('div');\n",
" titletext.classList = 'ui-dialog-title';\n",
" titletext.setAttribute(\n",
" 'style',\n",
" 'width: 100%; text-align: center; padding: 3px;'\n",
" );\n",
" titlebar.appendChild(titletext);\n",
" this.root.appendChild(titlebar);\n",
" this.header = titletext;\n",
"};\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
"\n",
"mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
"\n",
"mpl.figure.prototype._init_canvas = function () {\n",
" var fig = this;\n",
"\n",
" var canvas_div = (this.canvas_div = document.createElement('div'));\n",
" canvas_div.setAttribute(\n",
" 'style',\n",
" 'border: 1px solid #ddd;' +\n",
" 'box-sizing: content-box;' +\n",
" 'clear: both;' +\n",
" 'min-height: 1px;' +\n",
" 'min-width: 1px;' +\n",
" 'outline: 0;' +\n",
" 'overflow: hidden;' +\n",
" 'position: relative;' +\n",
" 'resize: both;'\n",
" );\n",
"\n",
" function on_keyboard_event_closure(name) {\n",
" return function (event) {\n",
" return fig.key_event(event, name);\n",
" };\n",
" }\n",
"\n",
" canvas_div.addEventListener(\n",
" 'keydown',\n",
" on_keyboard_event_closure('key_press')\n",
" );\n",
" canvas_div.addEventListener(\n",
" 'keyup',\n",
" on_keyboard_event_closure('key_release')\n",
" );\n",
"\n",
" this._canvas_extra_style(canvas_div);\n",
" this.root.appendChild(canvas_div);\n",
"\n",
" var canvas = (this.canvas = document.createElement('canvas'));\n",
" canvas.classList.add('mpl-canvas');\n",
" canvas.setAttribute('style', 'box-sizing: content-box;');\n",
"\n",
" this.context = canvas.getContext('2d');\n",
"\n",
" var backingStore =\n",
" this.context.backingStorePixelRatio ||\n",
" this.context.webkitBackingStorePixelRatio ||\n",
" this.context.mozBackingStorePixelRatio ||\n",
" this.context.msBackingStorePixelRatio ||\n",
" this.context.oBackingStorePixelRatio ||\n",
" this.context.backingStorePixelRatio ||\n",
" 1;\n",
"\n",
" this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
" 'canvas'\n",
" ));\n",
" rubberband_canvas.setAttribute(\n",
" 'style',\n",
" 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
" );\n",
"\n",
" // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
" if (this.ResizeObserver === undefined) {\n",
" if (window.ResizeObserver !== undefined) {\n",
" this.ResizeObserver = window.ResizeObserver;\n",
" } else {\n",
" var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
" this.ResizeObserver = obs.ResizeObserver;\n",
" }\n",
" }\n",
"\n",
" this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
" var nentries = entries.length;\n",
" for (var i = 0; i < nentries; i++) {\n",
" var entry = entries[i];\n",
" var width, height;\n",
" if (entry.contentBoxSize) {\n",
" if (entry.contentBoxSize instanceof Array) {\n",
" // Chrome 84 implements new version of spec.\n",
" width = entry.contentBoxSize[0].inlineSize;\n",
" height = entry.contentBoxSize[0].blockSize;\n",
" } else {\n",
" // Firefox implements old version of spec.\n",
" width = entry.contentBoxSize.inlineSize;\n",
" height = entry.contentBoxSize.blockSize;\n",
" }\n",
" } else {\n",
" // Chrome <84 implements even older version of spec.\n",
" width = entry.contentRect.width;\n",
" height = entry.contentRect.height;\n",
" }\n",
"\n",
" // Keep the size of the canvas and rubber band canvas in sync with\n",
" // the canvas container.\n",
" if (entry.devicePixelContentBoxSize) {\n",
" // Chrome 84 implements new version of spec.\n",
" canvas.setAttribute(\n",
" 'width',\n",
" entry.devicePixelContentBoxSize[0].inlineSize\n",
" );\n",
" canvas.setAttribute(\n",
" 'height',\n",
" entry.devicePixelContentBoxSize[0].blockSize\n",
" );\n",
" } else {\n",
" canvas.setAttribute('width', width * fig.ratio);\n",
" canvas.setAttribute('height', height * fig.ratio);\n",
" }\n",
" canvas.setAttribute(\n",
" 'style',\n",
" 'width: ' + width + 'px; height: ' + height + 'px;'\n",
" );\n",
"\n",
" rubberband_canvas.setAttribute('width', width);\n",
" rubberband_canvas.setAttribute('height', height);\n",
"\n",
" // And update the size in Python. We ignore the initial 0/0 size\n",
" // that occurs as the element is placed into the DOM, which should\n",
" // otherwise not happen due to the minimum size styling.\n",
" if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
" fig.request_resize(width, height);\n",
" }\n",
" }\n",
" });\n",
" this.resizeObserverInstance.observe(canvas_div);\n",
"\n",
" function on_mouse_event_closure(name) {\n",
" return function (event) {\n",
" return fig.mouse_event(event, name);\n",
" };\n",
" }\n",
"\n",
" rubberband_canvas.addEventListener(\n",
" 'mousedown',\n",
" on_mouse_event_closure('button_press')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseup',\n",
" on_mouse_event_closure('button_release')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'dblclick',\n",
" on_mouse_event_closure('dblclick')\n",
" );\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband_canvas.addEventListener(\n",
" 'mousemove',\n",
" on_mouse_event_closure('motion_notify')\n",
" );\n",
"\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseenter',\n",
" on_mouse_event_closure('figure_enter')\n",
" );\n",
" rubberband_canvas.addEventListener(\n",
" 'mouseleave',\n",
" on_mouse_event_closure('figure_leave')\n",
" );\n",
"\n",
" canvas_div.addEventListener('wheel', function (event) {\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" on_mouse_event_closure('scroll')(event);\n",
" });\n",
"\n",
" canvas_div.appendChild(canvas);\n",
" canvas_div.appendChild(rubberband_canvas);\n",
"\n",
" this.rubberband_context = rubberband_canvas.getContext('2d');\n",
" this.rubberband_context.strokeStyle = '#000000';\n",
"\n",
" this._resize_canvas = function (width, height, forward) {\n",
" if (forward) {\n",
" canvas_div.style.width = width + 'px';\n",
" canvas_div.style.height = height + 'px';\n",
" }\n",
" };\n",
"\n",
" // Disable right mouse context menu.\n",
" this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
" event.preventDefault();\n",
" return false;\n",
" });\n",
"\n",
" function set_focus() {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"};\n",
"\n",
"mpl.figure.prototype._init_toolbar = function () {\n",
" var fig = this;\n",
"\n",
" var toolbar = document.createElement('div');\n",
" toolbar.classList = 'mpl-toolbar';\n",
" this.root.appendChild(toolbar);\n",
"\n",
" function on_click_closure(name) {\n",
" return function (_event) {\n",
" return fig.toolbar_button_onclick(name);\n",
" };\n",
" }\n",
"\n",
" function on_mouseover_closure(tooltip) {\n",
" return function (event) {\n",
" if (!event.currentTarget.disabled) {\n",
" return fig.toolbar_button_onmouseover(tooltip);\n",
" }\n",
" };\n",
" }\n",
"\n",
" fig.buttons = {};\n",
" var buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'mpl-button-group';\n",
" for (var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" /* Instead of a spacer, we start a new button group. */\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
" buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'mpl-button-group';\n",
" continue;\n",
" }\n",
"\n",
" var button = (fig.buttons[name] = document.createElement('button'));\n",
" button.classList = 'mpl-widget';\n",
" button.setAttribute('role', 'button');\n",
" button.setAttribute('aria-disabled', 'false');\n",
" button.addEventListener('click', on_click_closure(method_name));\n",
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
"\n",
" var icon_img = document.createElement('img');\n",
" icon_img.src = '_images/' + image + '.png';\n",
" icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
" icon_img.alt = tooltip;\n",
" button.appendChild(icon_img);\n",
"\n",
" buttonGroup.appendChild(button);\n",
" }\n",
"\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
"\n",
" var fmt_picker = document.createElement('select');\n",
" fmt_picker.classList = 'mpl-widget';\n",
" toolbar.appendChild(fmt_picker);\n",
" this.format_dropdown = fmt_picker;\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = document.createElement('option');\n",
" option.selected = fmt === mpl.default_extension;\n",
" option.innerHTML = fmt;\n",
" fmt_picker.appendChild(option);\n",
" }\n",
"\n",
" var status_bar = document.createElement('span');\n",
" status_bar.classList = 'mpl-message';\n",
" toolbar.appendChild(status_bar);\n",
" this.message = status_bar;\n",
"};\n",
"\n",
"mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
"};\n",
"\n",
"mpl.figure.prototype.send_message = function (type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"};\n",
"\n",
"mpl.figure.prototype.send_draw_message = function () {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1], msg['forward']);\n",
" fig.send_message('refresh', {});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
" var x0 = msg['x0'] / fig.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
" var x1 = msg['x1'] / fig.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0,\n",
" 0,\n",
" fig.canvas.width / fig.ratio,\n",
" fig.canvas.height / fig.ratio\n",
" );\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
" fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_message = function (fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
" for (var key in msg) {\n",
" if (!(key in fig.buttons)) {\n",
" continue;\n",
" }\n",
" fig.buttons[key].disabled = !msg[key];\n",
" fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
" if (msg['mode'] === 'PAN') {\n",
" fig.buttons['Pan'].classList.add('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" } else if (msg['mode'] === 'ZOOM') {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.add('active');\n",
" } else {\n",
" fig.buttons['Pan'].classList.remove('active');\n",
" fig.buttons['Zoom'].classList.remove('active');\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function () {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message('ack', {});\n",
"};\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" var img = evt.data;\n",
" if (img.type !== 'image/png') {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" img.type = 'image/png';\n",
" }\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src\n",
" );\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" img\n",
" );\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" } else if (\n",
" typeof evt.data === 'string' &&\n",
" evt.data.slice(0, 21) === 'data:image/png;base64'\n",
" ) {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig['handle_' + msg_type];\n",
" } catch (e) {\n",
" console.log(\n",
" \"No handler for the '\" + msg_type + \"' message type: \",\n",
" msg\n",
" );\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\n",
" \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
" e,\n",
" e.stack,\n",
" msg\n",
" );\n",
" }\n",
" }\n",
" };\n",
"};\n",
"\n",
"// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function (e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e) {\n",
" e = window.event;\n",
" }\n",
" if (e.target) {\n",
" targ = e.target;\n",
" } else if (e.srcElement) {\n",
" targ = e.srcElement;\n",
" }\n",
" if (targ.nodeType === 3) {\n",
" // defeat Safari bug\n",
" targ = targ.parentNode;\n",
" }\n",
"\n",
" // pageX,Y are the mouse positions relative to the document\n",
" var boundingRect = targ.getBoundingClientRect();\n",
" var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
" var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
"\n",
" return { x: x, y: y };\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * https://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys(original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object') {\n",
" obj[key] = original[key];\n",
" }\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function (event, name) {\n",
" var canvas_pos = mpl.findpos(event);\n",
"\n",
" if (name === 'button_press') {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * this.ratio;\n",
" var y = canvas_pos.y * this.ratio;\n",
"\n",
" this.send_message(name, {\n",
" x: x,\n",
" y: y,\n",
" button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event),\n",
" });\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"};\n",
"\n",
"mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"};\n",
"\n",
"mpl.figure.prototype.key_event = function (event, name) {\n",
" // Prevent repeat events\n",
" if (name === 'key_press') {\n",
" if (event.key === this._key) {\n",
" return;\n",
" } else {\n",
" this._key = event.key;\n",
" }\n",
" }\n",
" if (name === 'key_release') {\n",
" this._key = null;\n",
" }\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.key !== 'Control') {\n",
" value += 'ctrl+';\n",
" }\n",
" else if (event.altKey && event.key !== 'Alt') {\n",
" value += 'alt+';\n",
" }\n",
" else if (event.shiftKey && event.key !== 'Shift') {\n",
" value += 'shift+';\n",
" }\n",
"\n",
" value += 'k' + event.key;\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
" return false;\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
" if (name === 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message('toolbar_button', { name: name });\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"\n",
"///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
"// prettier-ignore\n",
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";/* global mpl */\n",
"\n",
"var comm_websocket_adapter = function (comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.binaryType = comm.kernel.ws.binaryType;\n",
" ws.readyState = comm.kernel.ws.readyState;\n",
" function updateReadyState(_event) {\n",
" if (comm.kernel.ws) {\n",
" ws.readyState = comm.kernel.ws.readyState;\n",
" } else {\n",
" ws.readyState = 3; // Closed state.\n",
" }\n",
" }\n",
" comm.kernel.ws.addEventListener('open', updateReadyState);\n",
" comm.kernel.ws.addEventListener('close', updateReadyState);\n",
" comm.kernel.ws.addEventListener('error', updateReadyState);\n",
"\n",
" ws.close = function () {\n",
" comm.close();\n",
" };\n",
" ws.send = function (m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function (msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" var data = msg['content']['data'];\n",
" if (data['blob'] !== undefined) {\n",
" data = {\n",
" data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
" };\n",
" }\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(data);\n",
" });\n",
" return ws;\n",
"};\n",
"\n",
"mpl.mpl_figure_comm = function (comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = document.getElementById(id);\n",
" var ws_proxy = comm_websocket_adapter(comm);\n",
"\n",
" function ondownload(figure, _format) {\n",
" window.open(figure.canvas.toDataURL());\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element;\n",
" fig.cell_info = mpl.find_output_cell(\"\");\n",
" if (!fig.cell_info) {\n",
" console.error('Failed to find cell for figure', id, fig);\n",
" return;\n",
" }\n",
" fig.cell_info[0].output_area.element.on(\n",
" 'cleared',\n",
" { fig: fig },\n",
" fig._remove_fig_handler\n",
" );\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function (fig, msg) {\n",
" var width = fig.canvas.width / fig.ratio;\n",
" fig.cell_info[0].output_area.element.off(\n",
" 'cleared',\n",
" fig._remove_fig_handler\n",
" );\n",
" fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable();\n",
" fig.parent_element.innerHTML =\n",
" '';\n",
" fig.close_ws(fig, msg);\n",
"};\n",
"\n",
"mpl.figure.prototype.close_ws = function (fig, msg) {\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"};\n",
"\n",
"mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width / this.ratio;\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] =\n",
" '';\n",
"};\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function () {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message('ack', {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () {\n",
" fig.push_to_output();\n",
" }, 1000);\n",
"};\n",
"\n",
"mpl.figure.prototype._init_toolbar = function () {\n",
" var fig = this;\n",
"\n",
" var toolbar = document.createElement('div');\n",
" toolbar.classList = 'btn-toolbar';\n",
" this.root.appendChild(toolbar);\n",
"\n",
" function on_click_closure(name) {\n",
" return function (_event) {\n",
" return fig.toolbar_button_onclick(name);\n",
" };\n",
" }\n",
"\n",
" function on_mouseover_closure(tooltip) {\n",
" return function (event) {\n",
" if (!event.currentTarget.disabled) {\n",
" return fig.toolbar_button_onmouseover(tooltip);\n",
" }\n",
" };\n",
" }\n",
"\n",
" fig.buttons = {};\n",
" var buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'btn-group';\n",
" var button;\n",
" for (var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" /* Instead of a spacer, we start a new button group. */\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
" buttonGroup = document.createElement('div');\n",
" buttonGroup.classList = 'btn-group';\n",
" continue;\n",
" }\n",
"\n",
" button = fig.buttons[name] = document.createElement('button');\n",
" button.classList = 'btn btn-default';\n",
" button.href = '#';\n",
" button.title = name;\n",
" button.innerHTML = '';\n",
" button.addEventListener('click', on_click_closure(method_name));\n",
" button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
" buttonGroup.appendChild(button);\n",
" }\n",
"\n",
" if (buttonGroup.hasChildNodes()) {\n",
" toolbar.appendChild(buttonGroup);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = document.createElement('span');\n",
" status_bar.classList = 'mpl-message pull-right';\n",
" toolbar.appendChild(status_bar);\n",
" this.message = status_bar;\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = document.createElement('div');\n",
" buttongrp.classList = 'btn-group inline pull-right';\n",
" button = document.createElement('button');\n",
" button.classList = 'btn btn-mini btn-primary';\n",
" button.href = '#';\n",
" button.title = 'Stop Interaction';\n",
" button.innerHTML = '';\n",
" button.addEventListener('click', function (_evt) {\n",
" fig.handle_close(fig, {});\n",
" });\n",
" button.addEventListener(\n",
" 'mouseover',\n",
" on_mouseover_closure('Stop Interaction')\n",
" );\n",
" buttongrp.appendChild(button);\n",
" var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
" titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
"};\n",
"\n",
"mpl.figure.prototype._remove_fig_handler = function (event) {\n",
" var fig = event.data.fig;\n",
" if (event.target !== this) {\n",
" // Ignore bubbled events from children.\n",
" return;\n",
" }\n",
" fig.close_ws(fig, {});\n",
"};\n",
"\n",
"mpl.figure.prototype._root_extra_style = function (el) {\n",
" el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
"};\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function (el) {\n",
" // this is important to make the div 'focusable\n",
" el.setAttribute('tabindex', 0);\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" } else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which === 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
" fig.ondownload(fig, null);\n",
"};\n",
"\n",
"mpl.find_output_cell = function (html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i = 0; i < ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code') {\n",
" for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] === html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"};\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel !== null) {\n",
" IPython.notebook.kernel.comm_manager.register_target(\n",
" 'matplotlib',\n",
" mpl.mpl_figure_comm\n",
" );\n",
"}\n"
],
"text/plain": [
""
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"source": [
"%matplotlib notebook\n",
"%matplotlib notebook\n",
"from matplotlib import pyplot as plt\n",
"mpl.style.use(\"default\")\n",
"hotpl = exoeu[(exoeu[\"orbital_period\"] < 5) & (exoeu[\"mass\"] < 13.)]\n",
"# Yaricapa gore sembol buyuklugu olceklendirmesi icin\n",
"# keyfi secilmis 100 carpani kullanilmistir\n",
"radii = hotpl[\"radius\"]*100\n",
"hotpl.plot(x=\"orbital_period\",y=\"star_metallicity\",s=radii,kind=\"scatter\")\n",
"plt.axhline(y=0.0,ls=\"--\",c=\"red\")\n",
"plt.axvline(x=0.7,ls=\"--\",c=\"orange\")\n",
"plt.xlabel(\"Yorunge Donemi (gun)\")\n",
"plt.ylabel(\"[Fe / H] (dex)\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"En kısa yörünge dönemli gezegenler ($P < 0.7$ gün, turuncu dik doğrunun sol tarafı) dışarıda bırakılacak olursa Güneş bolluğundan metalce daha fakir ($[Fe / H] > 0.0$, kırmızı yatay doğrunun altı) barınak yıldızlar etrafında da büyük gezegenler varsa da daha küçük gezegenlerin buradaki ağırlığı daha fazladır. Metalce zengin yıldızlar etrafında (kırmızı yatay doğrunun üstü) hem daha fazla sayıda gezegen olması, hem de bunların büyük bölümünün dev gaz gezegenler olması, geçiş yöntemiyle daha kolay keşfedilen sıcak-Jüpiter türü gezegenlerin metalce zengin yıldızları tercih ettiğini göstermektedir.\n",
"\n",
"Grafiğe bir dördüncü boyut olarak barınak yıldız sıcaklığı da sembollerin gösteriminde bir renk skalası kullanılarak eklenebilir. Bu durumda sıcak gaz devlerinin metalce zengin yıldızların yanı sıra aynı zamanda sıcak yıldızları da tercih edip etmediği de denetlenmiş olur. Bunun için renk haritası (color map) parametresi `cmap` amaca uygun olarak seçilen bir [desene](https://matplotlib.org/3.5.0/tutorials/colors/colormaps.html) atanır. Gezegen barınağı yıldızlar genelde soğuk yıldızlar olduğu için `YlOrRd` yıldız renkleriyle uyumlu olması bakımından da iyi bir seçim olacaktır. Ancak, bu desende sıcaklık arttıkça renk daha kırmızı olacağı için desenin ters çevrilmesi gerekecektir. `matplotlib` renk haritalarının hepsi için terslerine karşılık gelen birer harita daha bulunmaktadır. Bu desenlere erişmek için desen isminin sonuna `_r` eklenmesi yeterli olacaktır. Örnekte bu `YlOrRd_r` 'ye karşılık gelmektedir. Örnekte yıldız renklerini daha da gerçekçi hale getirmek için (örneğin 9000 K yerine barınak yıldızlarda daha düşük bir üst limitle kısıtlamak gibi) farklı ek seçeneklere başvurulabileceği gibi renk skalalarının farklı anahtar parametre değerleriyle denemeler de yapılabilir. Yıldızların renkleri ve bu renklerin sayısallaştırılması üzerine [Harre & Heller, 2021, \"Digital color codes of stars\"](https://ui.adsabs.harvard.edu/abs/2021AN....342..578H/abstract) makalesi önerilebilir. Bu bilgilere uygun bir renk skalası hazırlamak da mümkündür."
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
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Go9FouhKepDjKdrB//Ip3IH8esS/SBeY8hFTmOaFVRKihk2M3lAEs05al0Wi6FNpY1mg0Go1Go+lK9BiJ7ap0GDFR2cOcEVW6Hpa94YgswPamz30U6ejCJMMOhMSMGIUoyBoM/eJTOE3TBakt8NXRD03EaGNZo9FoNBqNpguheo0BFQdjGaDnaGfkrHgXRw16MaFgARSvcE5mGCiXB8adZIdiR42gxp+GitdnptFo4oY2ljXdAqWgT7aLPtmuuK0fNBqNRqPZIRh2qDOhwY1Q0GMEKmNAzJLEVwqbf3S+YrdywZrPnJUZzrS7n1qfuxzxyS7IHAhjjnJcL41GE390gS9NtyDRa/DmP/p3thoajUaj0cQdlZ6D9N8bts510GgW1K6nOiMqf358WluJCVtnIiId6qVVyVlw8r+R966GgC/816ZckJSBOvlhVDzzzDVdECH25t3RzKmJFO1Z1mg0Go1Go+liqH2uwLEwZ2XYedDDD3dGXvEq21CMB8EqqMqPj+w2UD2Goc54ClKya59pY3BoeZ05AHXW/1BpveOun0ajiQ/as6zRaDSanRbZvhnyNiBVZSi3F1LSYchYlFd7gTQ7NiprMOz1R2TOs7FKAuVCHXQLynDIwC3fHB/PckP5KX3iJ78VVPYQOO8VWPktsuB9KFpvG8a1xrFY9qP3KNT402HEwSiXt8P11HQBaq+Vjp5TEzHaWNZ0C3x+i+sftneaH72hNwleHTSh0WhaRswgLPoRa9rbsPLX+udr/5GQjJp8MurA01F9BneKjhpNWIw9E8q2wYpo83gVKAN1+F228e0Upt85WS1hBeIrvw2UNxnGngi7nQDbFsPWBYivHDBQiWkwaC9Ur1Gdpp9Go3EWbSxrugWWwIqN/rp/azQaTUvIsplYr9wOZYVgtLKp5qtCpr2NfP8GjD0Q48J7UMlpHauoRhMGSimY/CdI7oH89opd7TJc75EyIDEDdcj/ofpNcFYxdyJ2mHKcfpBdCfGRGwFKKcgZBznj4tHES9Pd6YxWTrp1VFRo95tGo9Fodgqs2V9gPXktlBeFnmjDqLBCIaRLZ2A9dCFSUhB/BTWaKFBKofY4H3Xif6HHiNCTbYRTKzvsmpHHoE590XlDGSB9UIytlsKQr9FoNB2A9ixrNBqNptsji6cjr9we+c66ZUHBZqwnrsa48UVUYkp8FNRoYkT1HIk68b/I9hXIqm8gbxEUb6jPHfYkQ8/RqJw9YNSxqKSs+CmTNTJ+OcvedFRSj/jI1mg0miZoY1mj0Wg03RqpKsN67q/RC7BMyFuH9f4juM67zTnFNI2QgA+qSsFfDYmpkJyBcullSqSonqNRPUcDIJYJwRrby+tO7Lh2S733AJfX+dxlZcCAA52VqdF0Clbo0dFzaiJF/wppNBqNplsjMz+FoC+2fC3LglmfIadch0pOd065nRwRgbW/IT+/C4u+b5xv601C9jkRtd9pqN5DOk3HrowyXODt+GgI5UlGBh8J6750tgKvWDD8d87J02g0mnbQxrJGo9Foui1iWcgPbzlTZ8gKIjM/RR12ngPCGiM1JVC4EopXQ02pnVeakAnZI6DHKFRC9zPQZeUs5MMHYftGMFzNjSp/Nfz8HjL9bWT4nqjTbkX10rmqXYZRp8P6KSAOeZeVAf0PQKXrCvWaboAu8NVl0MayptuQkarr1Wk0miasmA2FW52RJYJ8/zpy6LmOhLOKCOTOgxUfw5bZgLTcs1UZyIDJMPQocGeCFQRPEvQYiHJ5YtajM5A5nyLv3kvdLobVSn5r7fPr5iOP/wEu+Q9q0NgO0VETGyqlD7L7pTD/SSekgScFJlzpgCyNRqMJH20sa7oFSQkGHz4woLPV0Gg0nYiI2MaVMlChtlCyfpHttWzNGIuUojxk3XMw4GSUt1f0ulYXwaz/wJaZIeM4ZDTWGsiNBlvIxumoTdOR8gAU1tipZ4YL6T0CtfsxsPuxqKSu4X2Whd8h79wT2UmWCTWVyDPXwnUv6rDsrsKw46BoBWz8NgYhyv4O73sbKiHDMdU0Go0mHLSxrNFoNJouixRtQ2Z+BKt+hS0rIOCzn8/sC0PGIdVVdkizk5RtgNwXkYwDIX3fiL3MUrgCvvsbBKpCT7Sf01k3RaobklJgWzUETMhdgeSuhO+egoMvgX3PsfNUd1CkbDvy5t+JqgevWBCoQV66CW56p+OKVWmiRimF7PUnu9jXui+I+HNXht1TefKdqF7j4qWmRtMJCHHrQ97mnJpI0cayRqPRaLocUlWGfPQw/BpagDc1OEtyYWEB+ANxKAAqgAWl0yBYgmQfE7bhJkWr4dub7SrBURQ+UkohLiAnGbZWQiC04Ar6kan/haXfw9kPoFKja60jvkpY+DWyfq4d7t1rGGriiajMflHJa8asj8E0iXrRZplQsAHW/Aoj9nZGJ01cUcoFE69B+kyEef8Bf0XoSBvXgHLZrad6T4Q9/6RbRWk0mk5DG8uaboHPb3HLkwUA/OvqXiR4df6yRtNdkY1LkGf/DJWloYIlrSy6LTPkknV4Nz3RW//vygXgSoLMQ9o9TYI1MO2uqA3lWpRSiCHQJwk2VzU+mLsSefFy+MMzqNTsiOTK8mnIB3dBoNp+30RgxXTkp5eRyeeijrgKpaK/t4oZtKtex1od2XAhM95FaWO5S6H6T0Z6j4cNU2HNJ1BRW0tAha630HWhDMjZF4b9DnrtriMINN2TllJuOmJOTcRoY1nTLbAEFqzy1f1bo9F0T2TTMuSJKyAYpsHp9Do7PRmSvI2fK5uJJA5HJQ5s+9z5L0JVAU4Y70opxGNAlheKG1QbFhNK85B3b4ELnwo7JFvWzUXe+Vv9eyoNcqgBfn4dcXlQh10evdLLZkBFUfTn12KZsORHpGw7Kr1n7PI0HYbypMCIE5HhJ0BNoV39vTLXvm7dyZAxFDKGoNyJna2qRqPRAKDdbxqNRqPpEoivGnnx5vANZXDcWFYTR7Tg6VJQ+BkirRcRk6pCu+q1g15upRRkeJu/RjFh82KY817YsmTqf9sfNONVpKokIh0bsW2VXajJCcSCvLXOyNJ0OEopVFJPVM6+qJEno0adhhp2LKrHGG0oazSaHQptLGs0Go2mSyBfPQ0l+RGFkimlwOWQxWwo2H1IS5qBWQrVq1s/d82XOO/mDolMa7l9lHz/DOKvbleEFKyDLUvbf1/FggVfRqFk6PTqcmeLrVVXtD9Go9Fodkikkx6aSNHGskaj0Wh2eKS6Aqa/H13OlRO/dErBboNRSQmtDYDyua2fv2Eacag0ZpPSSkZVoBoWf9P++UWbw5tHuZDiLeHr1RS3wz2hnZan0Wg0Gk0TtLGs0Wg0mh2f+VPs8OsoUEqBOwaPplKQlYo6fEIbgwR8mxAr0PxI0Aelm6Kfv03VFCS0FtqskCVh9Ld1t7YB0BQBt7f9Ya1pk5wJloMbBsm6565Go+miCHZtiA59dPaL7ppoY1mj0Wg0OzyyfiEY0f9kKUPBYeMjj4RWCjKSUWcdhEpoz5MpECho/nTZZuK5SlFGa5sBAluXIdLO3APHgieMPFHLRI3YLyodAdj1QOeqsaZkwsBdnZGl0Wg0Gk0raGNZ021I9CoSvbrFhEbTLdm03K6CHC0eN8beo1CnHVBfzbqt20Vtbu3g3qgLjkClJ4c3T2B78+fMmohUjYrWcoH9VVDegk4NT/Umw8ST7JY9rQ5yQfZAGLpX9Cr2HgzD92x7nrAEGbDf6SiXbuih0Wi6KLWtozr6oYkY/Uuj6RYkJRh88Wg7bVs0Gk3XpaYytvPddqiyGt4Prj4BVm5B5q6CLYUtjx03BLXHcFSvCEN9Jdj8OaMDfmrb8h4H2jfW1WGXI5sXwdblzRdUhgu8yaiz/hVzz1u1/5nImjZyu8OVM+mkmGVoNBqNRtMe2ljWaDQazY6PN9y82lZokCurXAbsMhC1y0CksAyKyqEmAC4DEr3Qv0cYIdetoFrIH07tF6XS4SEiEGzDWA7DA6u8SXDhk8j0V+HXD6C2RZTLDWOPQh38R1RW/9iV3fVA6D8atq2OMlJAwX6nojL7xK6LRqPRaDTtoI1ljUaj0ez45IyC/I3Rh5H5AkiNH5XYuECV6pEOPdIdUDCEO7PZUyohHUnuCVVth0NHjb+N98TlhfTeYYlRnkTUoZciB10E2zfYxmxWDioxzRk9wQ6dvvhR5LGLoGx7ZAazUjByEurEGxzTR6PRaDqHzmjlpCt8RYPOWdZ0C/wB4dYn87n1yXz8AX0z0Gi6G2rQrsT8Q59X3H6xq1jxtuLxzNmnZa9zjIgI5PsQs5XX1XckyohsXuXyoPqMQPUb7aihXCc/rQfqmheg9xDsxPF2Qrtrc5x3Pxz1h4d0rnInICJU/fgzW/9wJWsnHsCasfuw4dDjKXryWcyi4s5WT6PRaOKG/sXRdAtMS5i1pKbu35GXvNVoNDs0exwFnzxGTAbzpnwY2Dt+twdPb5TRSlXpkb+D1V/EZVrZXAWWIH0TGucUK4UafWBc5owVldELrn0BZn+CTH8bCjfbudENPc21fw/ZHbX/mTDuMFQMFdE10eFfu56t51+Kf8UqcLnAtD8jMzcf3+KlbL/3AXr+7Sayrr405px2jWbnQdquNRGvOTURo41ljUaj0ezwqIxeyB5Hwvxvo6+KvWQDTN6NuFnLaXu2ekhlD0f6ToC8RSAxVPVugFgC231QEwrDrjQhtcHPujJgwgmOzBUPlDcJDjgL9j8T1sxFfvvaDs32VUJyOvQYgNrnRFSfYZ2tardALIvgtjzMklKU242rZzbuHtltnuNfv5GNR5+MVVZuP2E2uXZFwB9g+53/xKqooOctOkReo9F0L7SxrNFoNJougTrpemTJdNuYioYqHyzfhIwZ6KiHUkRQRhIk79L2wEl/hs8ua25wRDknpiAry+ufLAvWG8tKwT5nolKyYp4r3iilYMReqBHRt6XStI5ZUkrJG+9R9MzLBDZsanQsad+9yL7sQtKPPwrlbZzPLyJs++NVtqEcxjVb9NBjJB+wH8kHxNCLW6PRaHYwdDyTRqPRaLoEKr0n6vd3hXoKR+EdNgyYuRwCpqO5y0opyD4aZXjbHpfaFyb9Keb5anWXZWXQsEZDQBCfZXuUM/qhDrks5rk0XRcRYfsjT7Fy9D7k3XYvgY2bm42pnjOPLX+8lpW7Tabiux8bHauZNx/fwsXhb+64XBQ/86ITqms0OwFWJz00kaI9yxqNRrMTIIEaWPMDsnUB5C+DykJAIDEdeu+C6jcWRh6BSnC+oJOTqLEHw/n3Iq/93X4ikpDsQWMhsA1+mY86ZG9H9BFLILcENXBM2+OKNsHSKci2pVDphuQAoIg0xbPOUF5aBoX+5gOqLUhPQp15P8oTY7stTZdFRMi98XaKX3it7YGmvXg2C4vYeMYf6P+/R8g4/UQASl96w+45HgzzO2aaVH71LcHcfNx9w6vArtFoNDs62ljWaDSabowE/ci812Dh+xCosisyN8yZ9VdCeR6y+nuY8RQy5hjUpEtQiQ62U3IYtceR0G848vodsHl588JQjQYbdqGrYy+HQ89H/nc+bNiAzFmC2ns3O4Q6yqJEYgnkF8LyctS+LcuQgrXI1MdhwxxbFwm1C6lyQbYXMVTY84sI1Fi2R7k00PIgw4O64L+IlYC15DeoqUalpKJ690Nl94rqdWrij+RvRJb8DBuWIkW5gNhF0AaNQY3Zp93NmKZs//cT7RvKjRSwiw1tueLPuPv0IuXA/fAtXRa+oVyLZeFfu04byxpNe0gnFPjq8IJi3QNtLGs0Gk03RQpWIVPugtKt1FXBbKm4VG3vYisAyz5H1v4Eh9+KGrRPh+kaKarvMPjzy7ByFvLzB7DqV6ipaDBAQa9BqD2PhUknoTJ6AiD9d4XizbB0DeL3w6TdbYM1ghzmOgN73WaYuQT2OLHFMcx+A/nxmfoFSsMe0T4TcqshzYOkelCGqvMa1xrPIgKCfcxvIVuqYGNVq5F0ImAlDCNw963IisVN3zGMfQ7EffLvMfY+QFeV3kGQNQuwPvkvrPzVvmaVUbfxI4YBc6cgYsHAMRi/uxy1+0HtygzmFVDwr/9EqZCQ+9c7GTbjKyQQjE5GMMrzNBqNZgekyxnLTz75JA8++CC5ubmMHz+exx9/nH32aX9B99Zbb3HOOedw0kkn8dFHH8VfUU2HkpRg8N1/B3W2GhrNDoNsW4R8dhOYASJqFyEW1JQiX9wCh9+GGnlY3HSMFWUYMGY/1Jj9bMOyJA+qSm1Pc3Z/VEJS83MGjUcWfmn/sXoT5BXC5AnQtydiWW0akXXHa/zILwtgU25I5oTG40SQb/4N8z9q+wUIUBaAsgCS5AKvAR4X4godqzShLIBVGoAif5sfo1kexCwKwPo5dm52C5NZc2fgn/0j9O6H99YHcO3uTCi6JnLEDCAfPYF8+1p9H2mRxptZVoNdkc0rsJ76M+x9DMa5f0MlprQqu/jVt6L3IFmCb9lKqmfPw53TF//ylY31CANXH+1V1mjaRXuWuwxdamv57bff5oYbbuCOO+5g3rx5jB8/nqOPPpr8/Pw2z1u/fj033ngjBx64Y/ab1Gg03QcJ+pBtS5FVPyKrpiGbfkN8Fc3H+SqRiiKkptzRYlMAUrYV+exm21CWaAp62D/iMvUfyNaFjuoWL5RSqKy+qP6jUf1GtGgoA7Dr4eBukMtbXgVf/4x89iOs3Yz4Ww5vFtOC/GJk2q/w3jd1hjJJ6TDqgMaDZ77avqHclGrTDq3eXgN5NUheNVJUg6yttHOT2zKUiwOY2wP1HufWjJvaQk0Fefhv/APmtK8i01HjCBIMYD19EzL19dATYXxHa+8Rc7/BevgypLq85WHBIEXPvhqxgdsIl4ui514l/YxTIpNjKLy7jsE7akT0c2s0Gs0ORpfyLD/88MNceuml/OEPfwDg6aef5vPPP+eFF17glltuafEc0zQ577zzuOuuu/jpp58oKSnpQI01Gs3OgAR9sPJ7ZP6HkLu8xcWvZA2A3rtAeSlsXQEVhfUHk9KR/ruhdjkExh2F8iRGr4tYyNR/gemP0lBuiEKm/hPOfhHlacX47GKohBRknzPgl9cb77IXlsCM+TBjPpKSBJlpdnEjS6CiCkrKW9iVV6h9z0W566tgS/4q5KfnYtdTKcRrQLYHilrJTwbMsiBmSYRhr2KBKfjv/Qve9Exce+wbo7aaSLDeeQiWTI/Oy2NZsGUl1jN/xbjuyWb57r6VazDzC2JT0DSpmPI9OU/cj5GViVVcEqZuQuYlFzbTSSwLti6DLcuQ7RsgGABvEqrPcBiwG6r30Nj01Wg0mjjSZYxlv9/P3LlzufXWW+ueMwyDI444gl9++aXV8+6++2569+7NxRdfzE8//dTuPD6fD5/PV/d3WVlZbIprOgR/QPjnS9sB+NtFPfF6oivYo+kalK/ZyMr/vUXudzOx/AGyxo9h1BVn02vyxKiLNUWLrJuJfHUfVBXZOYetLYCLNkNRqMepv4kRW10Ga2Yiq3+Br/8Dh1wCk85EGa7IFVr9A+Quivy8lhALKvNhwTuw14XOyNwBUAddjCz9DkpzW95QqKy2H21huKDnENjv3EZPyzePOKenUki2x+6fHGx+XUnAwixs3ZBuGwFL8N/1JxLf+RHl1ZWzOwJZNhN+ei82IZYFy2ch0z9EHXhqo0NmcXFssmunKK9Aeb30efg+tv3xqvYNe5eLxD33IP2sen0kUAOz3kdmvgOleYCyvze1xy17k0f6jUbtf469Uahz6TU7DZ3Rykm3joqGLnNX2r59O6Zp0qdPn0bP9+nTh9zc3BbPmT59Os8//zzPPvts2PPcd999ZGRk1D0GDhwYk96ajsG0hB9/q+bH36oxLZ2T0Z1Z8tDzfDTyKJY9/BJFc5dQsmgl69/6nK8POJdpp12LWeNrX4gDiGViTX0U+eAmqA4tUNtaUCqo6xOU4ILEJrff2nP9Vcg3jyEvXo6Ub49cr0Xv1+dAOoEIsvADrOVzkUU/I6sWINu3OSe/E1CeBNSZ/wJPYnTvlTIgIQV1+r0oV/2esxSshS0LY/PoK+xfZhfgViiPASOSYUgS9PJCg41AsyzCSsVNEQvKSzGnfR2bHE1YiAjWuw8Tcb+w1uR99BgSaHK/c+q7H9Ix7YRj6fP4g+By2Y+mhIzbxL0n0v/N5zES7E0X2bQYeeI85OsnQoYy2Bs0wfpHLbkrkffuRF68Gine6oz+Go0mZkzT5O9//ztDhw4lKSmJ4cOHc8899zRKHRMRbr/9dvr160dSUhJHHHEEq1ataiSnqKiI8847j/T0dDIzM7n44oupqGicnrZw4UIOPPBAEhMTGThwIA888ECHvMZw6DLGcqSUl5dz/vnn8+yzz9KzZ8+wz7v11lspLS2te2zatCmOWmo0mkhY/cJ7zLvpAduAM+sNBQm1N9n08VR+ueS2uOthF3B6AOa/X/tE+CfXLpRdCpLa8BxvXY48f2lEBrOUbYW8pQ6EXzfBV4Y8cTnW/Vdi3XUB1vXHYN7zB2TWN0iwdc+miOBftZrqmXOonvsbwby260t0JKrPCNQFT0JyZmQGhjIgrSfqoqdRPRoXFZQlXzXynEVErYFs0HhjhVA+dpILenhQI1IgJwFRglXuQNVhwyD44auxy2mCiOV4Ln6XZ+1C2LbGuSI7VeXIvKmNnnL3yHZEtCsjvS5KJ+Ps0xky/Wsy/3g+Kjm50bjEiRPo+7//MPDDN3BlZAAgS75HnrscircRVnHB2vdj40LkqYuQbavaHq/RdAdqC3x19CMC7r//fp566imeeOIJli1bxv33388DDzzA448/XjfmgQce4LHHHuPpp59m1qxZpKSkcPTRR1NTU1M35rzzzmPJkiVMmTKFzz77jB9//JHLLrus7nhZWRlHHXUUgwcPZu7cuTz44IPceeedPPPMM7G/zw7QZcKwe/bsicvlIi8vr9HzeXl59O3bt9n4NWvWsH79ek444YS656xQoQq3282KFSsYPnx4s/MSEhJISNDhaBrNjoYVDDL/tkfbGWSx7vVPGPf3K8kYPazVYeKvhJL1EKgGlxvSB0BSj/BDuOd/AEu+CFv3FlEKDIEEA3wtGLeWCWUFyJs3wiXPoYwwbtd5y2PTqRVEBFJdUNLAMF45H2vFPEjLQp3/V4zJx9YdMsvLKX/nQ4qfeZHAmnX15yhFyhGHknnJBSQfelCnh1yqfqPhqjeRbx6DBZ+H+iC3stFQ2yN5z5NRh1+F8iY3H7NlSev9ntui1r5u5/qruz7T3Vil7oiKnLeKZSErFmGtXYExbHRUIkQE8pchq7+zN2sK14LpAxSSnA19dkXljIdRR6ES0hxQumsiC35ouyd4pCgDmf8dTDqu7invyGF4hgwksGFz9Ea5AWkjgljvXYHa9Xcw8nC8I0fQ+7476fn3vxLYvAXx+XD17IGnX+P1l6z/DXnntlBhsAjnt0yoqUBevBqufg2VoatqazSdyc8//8xJJ53E8ccfD8CQIUN48803mT17NmDf+x999FFuu+02TjrpJABeeeUV+vTpw0cffcTZZ5/NsmXL+Oqrr5gzZw577bUXAI8//jjHHXccDz30EDk5Obz++uv4/X5eeOEFvF4vu+22G/Pnz+fhhx9uZFR3Fl3Gs+z1etlzzz2ZOrV+F9WyLKZOncp+++3XbPyYMWNYtGgR8+fPr3uceOKJHHroocyfP1+HV2s0XYxt3/5M9bb2C9cot4s1L37Q7HmpKkQWvIZ8cAG8dQp89WeY+jf45mZ471x45wzkl0eQojVtypeSrci0/0b9Ohorq8Bj2F7mFiczYdsK+PmNsMRJ4ZroPZvtkdLEWK81KsuLkf/egvXJ8wD4lixj/T6Hkn/LHQTWrm9yjlD53TS2nHURW867GKuyKj66AuKvQjYvQlbPRNbPRRoWVGuASkzDOPH/UNe8Z+cf9xnR+D003NB3FBxwIeq6DzCOvbFlQxkgPwqPWJiGciOdlUKqTNsD7RDWxrVRnSebZiPvXoJ8eDUs/gjyl4UMZQCBqkJYPwOZ8STy8mlYPz6M1OyctUBkfZSbKa0KtGBd437ayjDIvuyi2ORakLlPKuSvQH54CHnpNGTJJ4gIRnISCaNGkDhut+aGsq8KefeOkJEepaEuFvgqkQ//oSMTNJo4UVZW1ujRsFZTQyZPnszUqVNZuXIlAAsWLGD69Okce6y9Ob5u3Tpyc3M54ogj6s7JyMhg0qRJdfWkfvnlFzIzM+sMZYAjjjgCwzCYNWtW3ZiDDjoIr7e+WObRRx/NihUrKHaoDkMsdBnPMsANN9zAhRdeyF577cU+++zDo48+SmVlZV117AsuuID+/ftz3333kZiYyNixYxudn5mZCdDsec3Oi1SVghmElKxO93Jp2qZy/RbbOGhn/SSWULFuc4O/g7DoTVj4hn1ya55DXxms/gZWfYkMOgAmXYtKymouf9arDi94xe6vW926TJn2POx1CiqxHa+cvxJHLagQSinE3bZceecxakpq2HzHU1hV1a17tULh81VTp7HlvIsZ8M7LqAY/kLEgvkpY9DUy90PIX0vTi0VSsmH8cag9T0Fl9mt0TGXloA6/Cg6/CjEDdr9mpSApo1Fecpv42ykK1pQoDOU6Wij4FRPlpRENl0A1MuNxWP5lgz7BrVzDtd85KwDLPkfW/gSH/hU1eCerwp2/0XmZpQWIZTYqBph5zmnk33U/4vNHLk9B4gAvif281H1/AlXItIft4oFH34FKzGjxVPnpFSjfHnsaiGXCmtmw7EfY9eDYZGk0OywxbCrFNCfNHIZ33HEHd955Z7PRt9xyC2VlZYwZMwaXy4Vpmtx7772cd955AHU1o9qqJ5Wbm0vv3o2jRNxuN9nZ2Y3GDB06tJmM2mNZWc3XYh1JlzKWzzrrLAoKCrj99tvJzc1lwoQJfPXVV3Vv6MaNGzG0waMJA1n2I/LDC7A1FLaa0Qf2PxcmnaGN5h0UV1JiWL8rylD2WECqi+Dbv0FxmF6z2sX+pp8hdz5y6N2oPvWba1JTDsu+bt0oiAal6nNVW1tjBgOw4EuYdGbbsuLlVYZ2QzpFhNzb/41VDZhhLJYti+oZMyl68ll6/Pnq2NVbNQP59J9QWUyruyqVRfDLG8jMN+Ggi2Hy71s0hJXLA2nh17qowzDC30iptY+jLPakDIc3RRLCb1cmvgrks5tg+8rQExEYR2JBTSny5d/gkJtQY45t/5zugpObbI3kWo2++67MDPrefyfbrv9bZHIUKLei74k9Wj6+dT7ywTVwyuOopMxGhyToh9nvO1cvQRnIL2+htLGs0TjOpk2bSE9Pr/u7tfTTd955h9dff5033nijLjT6+uuvJycnhwsv7D4dMtqjSxnLANdccw3XXHNNi8d++OGHNs996aWXnFdI0+WQXz9CPv5X40VqaR7yxSOQuxpO/luHtx/StE+/IyaHjJG2F2MSNOl/3EFIdTF8dQNUtFwtv20hFgSqYMpfkSPvrzeY188GM9pWPW3NJ+A2mreUqh+ALPoG1Y6xrNL6IXFYkIslUNP2+15TYuKviHChLELJsy+Rfe3lKHd0P0ciYnvef3qhwXe6DcNeLDvA4IdnYO0sOPshVEJKVHM3I70vlGwJb6xBbFWRvcpRp4TKCG/nXiwT+er/bEM5asPIVlx+eAASM1BDJkcpp4uRkgHlRc7K9CTYdReakHXhOZiFxeTf82B4chQol2LA73uRmNNKpIdYULoF+fwWOPWJxnUU1syB6vIoXkAriAXrf0PKClDpvZyTq9HsKIjlfDHOcOYE0tPTGxnLrXHTTTdxyy23cPbZZwMwbtw4NmzYwH333ceFF15YVzMqLy+Pfv3qo7Xy8vKYMGECAH379iU/v3Fxz2AwSFFRUd35ffv2bbEmVe2xzka70DTdgkSv4vNHBvD5IwNI9La+AJXqcuTzh0N/tLDSnPcpbFgQJy01sZDcvw+DTjsK1VL7kloMg8TePRh40uEw/X7bUI72x0gsu73JD3fW5VhK3vL4eW/buxvnrWrfEO41iriEdSmgou3Ky2UbfVFFgJv5BVR+M7X9ga3xy+u2oQyRFzTatAh5++a6fq8xk7NbeJW1m1S7jgajr4OFKJNTMMbv0+phqSxDNq9GNq1CfnkJtsXYHqsOhXx/P1IdWQh4V0UN2c35+8fA0a1u7va84Spynn4YV3ooaqClYaHLNaG3h8GX9SFlRFLb84kF+cth/juNn968ND73xi3LnJep0WjCoqqqqlnErsvlqiuYPHToUPr27duonlRZWRmzZs2qqye13377UVJSwty5c+vGfPfdd1iWxaRJk+rG/PjjjwQC9c6IKVOmMHr06E4PwQZtLGu6CUopkhIMkhKMtr3Ci7+1Q1pbw3Ah8z51XkGNI0x68g5ShvRv0WBWLheuBA8Hf/gExsbvYds8Bxb0Av4KmP2E/Wfh+viEUirVepGvWoJ+KG3HS957DHgd8pI2paRtg7K6yIzOTve4qZ49LyqVZNty5LunozrXFmDBht/glzejl9EANWxSWNecqJC3PgaMVDcqyxOTDFuQC/dxZ6ASGxtJsmE51gv3YP7paKzLD8S65TSsW09HnnoMmVWMrKhASgMxFmGyv1/yi0MF83Z0Ruzh7P3DMFCj9mpzSMZ+OYy4sTc55/QkaXBCI4NZuSB9XDKDL+/LkGv7kdg//A0Ymf08UtHAW5S/xnkvmeEK1R7QdDZSUYTkrkE2Lkby1yE1Fe2fpGmbLtA66oQTTuDee+/l888/Z/369Xz44Yc8/PDDnHLKKYC99r7++uv5xz/+wSeffMKiRYu44IILyMnJ4eSTTwZgl1124ZhjjuHSSy9l9uzZzJgxg2uuuYazzz6bnJwcAM4991y8Xi8XX3wxS5Ys4e233+Y///kPN9xwg6NvebR0uTBsjSYWpDQ/1LqjlYW/ZUJJFGG7mg4hsVc2x816h/m3P8aaFz/ArA718VOKnGMPZMI//kzWuJHwwe+dm1QsWP8DMv58u9VUZxJouWJlLcrtRXb5HSx817GFq1gCxYE2QsRD48xoq9+CVR5d+KZ8/gBOFDSTH56B3Y9BpcUY7jn6EJjyCPjaWUiagvLEvlftGpJEsDjGtADLxHXC2XV/SlEe1vN3w4Lprbc5CggU+O1HqgsZlYpKjtKrKBasmorsezkq2ZkewTsqas+jkHceirwQXGtYgtr/5DaHyIL3UG4X6WNTSB+bgliC5ROUAcqrok85EkGWfoba54/23/6ayCM72kUhgZo4lCzUhIOYQVg6Dfn5XVj/W+ODykB2OwS13xkwdA+dutZNefzxx/n73//OVVddRX5+Pjk5OVx++eXcfvvtdWNuvvlmKisrueyyyygpKeGAAw7gq6++IjGxvg7G66+/zjXXXMPhhx+OYRicdtppPPbYY3XHMzIy+Oabb7j66qvZc8896dmzJ7fffvsO0TYKtLGs6Sb4A8Ijb9q5YH8+Jxuvp+Ubt0rv2XYoq+Gyi31pdlgSemQx6ck7mPivv1D02zKsQJCMMcNI7m9/brJ5pt2uxkmUASs/A3f4RZDigrv9qtFq99OQJR9BsG3DOmwUsLn9xb1yqegqNCswUlMjPk22LIVtDvWVFoF5n8DBF8ckRrkTYL8LkB/a8ZQ6tK40+nhRGW6kLBidV18pXEefijFgCACyYAbW4zeCP3TthOMFrTDht1JkeAoq6tBwC5Z/ARMd3OTaAVGJyahDz0a+eSl2w9JwwYRDUD37tzpEynNh05zGOhgKV5IDF6BYsPhjZO+LUMoAbyJhtSuIbBL7O6XpcGT2h8g3T0NlScupJWLZhvTi76DnIDjxRtTISR2upya+pKWl8eijj/Loo4+2OkYpxd13383dd9/d6pjs7GzeeKPtFpi77747P/30U7SqxhUdhq3pFpiW8PXMSr6eWYnZVnjj2CNaLIZSh2WiJh7vvIIax/GkpdLnoL3pd/h+dYYyAJtn2/GFTiIWbPwZegyx++46jUjrlbBrcXkgs/1CFyq1F2r/losgRq6WwJYa2yBqh8QsV3RGYCBI4l57RK7bkinO5UiKhSz80hlZe58JfUa3fQ06ZE8oQ+HZKwMSjcjfe2Vg7L43nuvvsFVaMAPr39eCrzryUGEBVlci22oiVKL2fEE2RxeK39VQx10CPfvbxQqjFqIgIQnjrL+2PW7boujnCIeaUigJtenrNTS219QSlgm9hzkrs4sjQT+yZhay8Ctk8bfIthVRpUKIZbZ4nohgff4f5MN/2YayPbhlIbX3icJNyIvXI79+ErEeOzfSSQ9NpGjPsmanQiVnwDHXIZ//mxZ3wXc/GoZM7AzVNE6xfRmOtnaqpTIPNWqoc8WgmtJeGHOfEY2rz7bFLsdD7mJY8Q3R/jiKCJQFYWN4IaMZgxKozI38vXH17EHqMUdEfB6bFzub/1myFampQCVG7uVuiDLccPLdyKuX29WBW7gWJSAoB9KNAVSCgXdyFoHZpUh50Dak2lo8hyrKGwccjvfWB1EeL1KYh/XYjfaiOBaP55oqJNWNSotiaVFgL/q7ezin8iZiXPYQ1kN/hEBNu9X9mwtQ9kbHJf9CpbfS4imEFKxsPZTeKQpWQtYgVP9d4lKJn/67OC+zCyLl25FZ78Dcj6CmSdpKnxGwzxl2D/kWnAEiAmt/RZZ8B5sWQf56OxVNGUhWDgwcixq1P+x6CPLd8zC9bQ9gCxMAgrx/LySkoMYdHu3L1Gh2SLSxrNnpUPueAanZyPfP1xcPSe2Bmnw27H9ut1+sdXvKt8VPdo/+tmfZaYNZKQi2tdBUqLFHRiBOwSE3IYYbln1OJOGRdQZLSQCWV4RtaydmufCkGAQqI1j8GwaZF1+A8kRhORZujPyc9ijaBDmxL85VZn8477/IW3+CisLmnhnDzgV3qleySjDw/G4C0ud3BD94Fdm4BlyuUL9rsa8vwwDTxBg7EffJv8c48Ki6nvLW83fZ+fBO5JyurED2yIj8tQWqwF8JCbFtVnQF1ICRGDc8g/X4tVBVGr7BbLjA7cG49AHUrvu1P748L76GsnJBeajGx4hJkJgKThV+UgYMHIfK6O2MvC6MbFuBvPon20huycubvwb59D5YMhXOug/lTa4/d+k05OvHoGhL840TsaBoM5RsQxZ8Bd5kqK6MQVOFvH079N8FlZ0Tg5ydBBHHaotENKcmYrSxrNkpUWMPh90Og/ICMIOQ3rvFHVlNFySei0NvIuxyJCz9xjnvtYhtkLb1m+lyw4TjIhKrDBfqkBuRgXsj0/7doOhUyz+WdSF5ArK2EnIjy3lWStFnQjJbZlYiqJCh1gYug8Q9J5J13RURzVOHGQcPv4MyVfYguPg15PsnYcEntmERumYMjwEOGcr2ZAZq1P64Djob1+/Owlo8D/O7z5DCAqiqgNR0jH4DcB1zGsbg4Y1OlXVLYeEM53SptqAoAD3bz69vRjwiQnZQ1KBdMO58H+udB2H2l217gGuPjd4b4/d/R2WH2Xc0XlEwtaj6OZQnAdn7FJj+ujMGgFio/druK78zIEWbkFeuAV9V6+9r7b173a/IO/8H5z4EAR/y8X2waEp9m7rWrq/a5/1VofuSQFRfRQFLkFnvo469NhoBGs0OibYONDstSilI17vWXRmxTChaAiUroXQN1BSCxHGB6ElGTTofWTbFudQfpaCmHa/ygReikjKiEz/8YBiwJ6ycgiz+EEo2tTIwATaWQW61Xe04ChIyvPS/4Xdsff5rrOKSlnexXS4wTZL234+cl5/GSIiygE9CivPVyRPTHBWnElJQx9yMTDwF+e0jWPw1BGvsDQlLQOFMJItYqPEn2XMqhWvcnrjG7RnWqdbUd5wP1d1aE52xHCqgJyJQUWB7LS0TPImQNbiRx6w7oFIycP3hH8ixlyA/vY8snAbbt9Lo5pLZG3bdD+Og01GDd41sAk+S7aGNl/dKBDz1n4k66EJk/pdQURTbnIYLBo+3N7R3cmTKk3YdgXDeT7FgzUxkwZcw633YuiL0fAT389ogJBfRGcxiwqwPkSMuRXk6uSCmRuMQ2ljWaDRdDvGXw4YvYcPn4CuhvlahBa4wimVFg+GBtP4owwUHXYH88ETsMkXsCtKt5SsrF/QaAgdcGNM0KiEVxp2CGncKUl0KBSvsiuEikJgBvUZBYRFy29kxhGkpUIqkP1zD0MtuofSNdyl57iWCm7Y0GpU0eRJZl15IytFHtNgvO2xyxsCqGc6Flbk80GOAM7KaoHqPRB19E3LkDXaod8EaWP0TrJzqgHADdj0alRFl2OOC6c5HY5QFEVPsCunhktoHtszHWvwpbF0AvubtxCQ9B4YdgBp7IiozPp9VZ6D6DkGd8Rc44y9ITSWUFAACadmolOg2yQBU9lCE751TtCliQfbQ+vkSU+G0O5CX/xS9TGWAJxF1ym07fUqUlOXDip8i3HhQ8MWjbXui2xURqnsQrcHsq4RF38HEyKKhdjqi6HvsyJyaiNHGskaj6VJI7kxY+AQEKqj3wDRYFLgNCDhtLSvIHmEbygATz4Dc5bB8KkTrYq6tgO1rRVfDBSnZqHP/7WiKgErKgEH7NH8+tRfWxX9HnrsrSsmCcfW/UL0H4AKyr76UrCsvxr90OcHCIpTHg2fQADwDWm91Ewlq8B7IKofCh5UBA8aFX0At6mlc0HMI9ByCpGfA2u+QoMTWScrtRR0SXcijlJdAcUEss7dOlQnhFvoSBRUlyKd/bdsTWrYVFryHzH8HGToZdfCfUakx9sbewVCJKdA3xRlhvUZFbTCJCJSbdtSLKXZ4rkdBhqfxJkivkY3OU8P3htPvQt67IyQokhoGLttQ/sMTqCyd88qCKCr0W5YzeeO1BrNB5JvPhgtZOxeljWVNN0Eby5puQaJX8cH9/ev+rel+iJiw+FnY+CVtFqxKcEG106HYAiOOrvtLKQOO/T/EkwiLPmtbnxbFhQzl6ja27XsPR539AKoD+34bh5yKVVONvPYAYb8mpQCFuuQO1D6Ni5ApwyBh7K7EpVPq7sfC1KecCbsXC7XXqbHLiQDlK0PSvKhSP7TV7q4NBFBj9kVFGz5elBfdeeHgs6A9tWq/ByJAKEe+PeOq9vj6WcjmC+DQG1GjdPXdFskZb4dJB6rCPkWCoZzzwkB93/SGt4KtPiTTDT0TUYPHopIym8lQux8JaT2Q9++CsoIwDObQBDm7oE6/A9VjYNj6dmekeGvIaA33BIejqpQK5aVHeH+yTLsTgKYdOqOVk/YsR4Pus6zpFiilyExzkZnm2ulDt7ojIhYseCJkKEObN3yXAR6Hb23uJBh6aKOnlOHGOOqvqBPvhcT02mdblyHUh135rRYMZdvoxJ2AOuxy1KXPd6ihXItxzHkYf34Ueoc8wK31Mq59vt9QjJv/i3HwyR2hXh0qORP2PNn2RMYkyICsATD6ICfUChsrb6vtrcvwgjuKe5YBpHqQqih7GwOdunCSUBGhOhUi1EVMCFQj39yDLPjAYeW6B8qdALv+LuzviFQGYUUl5PnrDWVo/NEIUByEVRVQndlqj181dCLq2jdRh10CqaEWV8qw7xuGq3G/+l5DUCfdirr0f9pQbkikUQHx+DrXepcjJZ6FNjWaDkZ7ljUazY7P2o9gy3fhj0/xQElk1ZzbZO8rUZ6kFg+pkQfB4L1g+bfIbx/A9rW0uGpJ6w19doGyEti2EgINdt69ydBvNGrXw2D8sagEh8Iwo0TteSjGxENgyWysKW/CvGmNF26GC/Y5EuPIs2DUHp22QaUOuwJZ8SOUb48+P08EdcodHV4NPzh7Dp4MbIM53WuHu1YHw1vwJrog2Q0WmGs2EHXmd1pWtGe2j6etjaNoq+22Iu6nxyApwxEPs1gmbJoPW5ch+avt/Eu3B7IHovqOgaH7dPr3MxLU7qcjSz6GYNv3Q6kMwtrICubJjK8gtR/q5GtanjshGQ75Ixx4AWxabL+nBeshGABvEqrvCBiwG/QdqTe5WyKtZ2Tj41GrQ0UYNQX270NSevvjdnbE6oTWUR08XzdBG8uaboE/IDz1fjEAV56WhbethZqmSyHlG2HFa5Gd5DIg2QNVgdgmVwbk7NkoBLvFYd5k2P1E1O4nIr5KyF9p99fFgqQM6D0KlVxvmIgIVJVAoAbcXjs3eQdbLCqlYOwkXGMnITVVUFYENVWQlAJpWajEzq9MrLzJcNaDyMtX2u9lFAsBdexfUP13i4N2rSNVlfg++wH3WT1RbsNekCa5bSPYb4HfhKBVv/hV2Ln4HsNOMwi1nVIuCMxcgbsgD6NX+1EIEqyx3yeXGzwpkNUbUtKhssz5F5nShgkfBw+YfP8Q5IxHpTY2MEQEirdAWb7t7UpKh97DUK7Gvb3FDMCv7yFz3rZbCtZ6Y8UC7D7VYpng9iLjjkPtfxEqbcfPl1ZpvWHyVciPj7Q6RvwWrI+usrx8/SJWv2EYk1rPT1UuNwyZAEMmxJaf33Bey4L8jZC7FvH7UJ4E6DsE+gyury3RxVFjj0R+eim8wfEs3BSpwWxZqJxRcVNHo+lotLGs6RaYlvDxj3ZRi8tOyaTNcFhN12LxU0S1uk502blWNVHmtCoDeo6GgyKryqoSUmDgHm2PUQpS4ujVcxiVmAw7gHHcEqrvSKxj78R87v+gohJcYPT0YiS3sWA2XKBcqONvRo13vgiNiEBpAWzfYocLp2ZB78F13mtrw1ooqyK4shL3mFRUbc9lpWxjOKH9xb6IIOVBzI1VmCuWtGgsi2XC5jnIqimQtwQq8usPJqRBr11gwEBYtdzZsMlkl70J0LLi8fGABX3ItEdRx//DTttYOweZ8z6s+xX8TQxBw4X0HYmaeBKMOwqKtyCf3AnbN1B3r2m08SL170/QD/M/RRZ/DUffiBp3TBxejMPsdiJsngtrf6LFe2lhIKbPRD7/H7LPsR2y4SfrF2P98A789l2jz7XuVXkSYPzBGAefCcMn7HCbkJGgeg9DBu4Omxd3rkdQJLKyHC437Hl8PDXSaDoUbSxrNJodFinfAEVLoztZKTtU1VARephDq4LhR8E+V6HculfkjoqVt4XAI3dizZneoBiNhbm2GpXpwT0qud5oDhUiQywYurftUc5ypjJ3LbJ1NTL9fWTeFKgsaXzQ7YHhe2AceCZSZS/gA4vL8ewafW/nwGI7lF/KmnuGZcMvyPRHobKg5QrTvnLYPAe8PufzC/u1UdItXg4wsWDddKxV0+HbpyF/Tev9oy0Ttq5Att4PX/8HlEmo0liYc5kQqEE+uwcp2YJx4MVOvhLHUUrBkbchX98F6xtXkBdLoMgf2wQFm2HFHBjTvMq+U0jpdqw3/gkLp7XdFzzgg3lTsX79BnbZF+P821FZHV/7wSnUEVchL19tV4xv6/rcUeo2GS6YcAxKh2GHgS7w1VXQxrJGo9lx2fC1HWsqUS7ma8NbvQZUBhq1lBJL7FDXgBXqcxxajKT3gnGno3Y7QRvKOzDW1k34rj2LQFEJhdstgkHweqBHNrhcCikNEvitHM9+AzAyU+zq4v13hbFHobKd7dEr1RVYH/0Hfv6w9YV8MAArf8VaMRsy+2EkG1iFfgKLy3DvlhaRB0wswSoKEFhiG8sN+1WL6Ud+egRWfk1dhE2rXimBTI8dMl3pkMHsVtCrFWPZalD9Oh4evxoL3ri5PoS6zU2A0KIxECqQprB1D1uv0PnTX0BSslETT4lC4Y5DubxwzF3w29vInBdC63QTSoOxe/oNF9a0d3DFyViWVfOwnvoz+EKe5PY2d2qPr5iDdedpGJc/gNp1clx0izdq0Hg4/R/Ie7eFCkS28mGpaHo8xQHLRO13emdrodE4ijaWNRrNjkvBvOgN5Ya4DEhPQIImlPuh1Gf3ga0j5JVUBuTnwrePI989hYw5HLXHqaicjs1p1bRPxW3XsWJWEVu3SqPOJi4XDOovjBgquJSb4DoXCS9+ELdwTNm+BevxK6A41IaprYV8aKGrSvNI3C0V39pqfNOLIMmFe1hyWDqKZYdf13yeV1exWGVk2sfMAPL132Hzr7Wj25WnlEJGp8K80nbHhsXIFJSLxjmUtT1bA5b9XYzHZ1EdrP9OR3PPEOz3003E+sm3/4Ehezu+CeM0ynDDnufB0MnI7Bdh3XSodsDAskxYuyh2OS0gq3/DeuwqMM3IQ5EtOwLAevJ6jKsf7boG8y6HwB//h/zwPKz+xf6dqtsQCoI3ya7m/9tXcVIg/BhsdfSVqP5j4qNHN0NEWq0mH885NZGjjWWNRrNDIsFqqNrmnLyABdsqoaKlkGyp97TUYgVh2bfI0q+R4QegjroJVdsCxTGdAtT8Og/f/IUE1q5HggGMtDQSxu5G4t574hk62NH5ugvVM2fwy1tLqa5uvoQzTVi3EUpKYa8JQVyb1mHNn4Vrj30d10PKtmM9eimUF0a2kA8VjUoYloTPEnxTCpC9M/FMyKhr09LUcBZLUIbC3FhNzXfb7T7GAIlJuHafaI+Z9b+QoRzZgkilupERKbC6MqLzmtHDg0pQdmXvWv1rIziCYhcpS4rEexsmfqvJ5leUCHaUSaStvCwLmfoY6owHYtehA1DZQ1HH3I1UbkeevRGKFsdeIKomxmunBaSiGOvpv0RnKNcJEcDCeuavGHe+j8rs7aSKHYbqvxvqvIft3svLvkcqi8HlsTdodj0MXB5k0Xd2Tn08COfyOOBcOPjC+Myv0XQi2ljWaDQ7JpVbHRMl5X7YUkEjF2RYJ4YW4KunI2tmIL0noiacAGMPianVkFVRScnTz1H2wsuY2wvBMOwH2B7ugF2ULHG/SWRedyUphx/aurCdkN8uv5PqmrbXb8WlsHodjB7twpz6mePGsohgvXmvbSgHg7bXNCj115ih7OrVnpaNw1pna8KwZKoXluOfXYJ/fhmeMal4xqahMuqrNYvPIrCsnMCScqSsQcE6lwvviaejklOQrQtgcfT9hlVOou11WFMVnYAsN/Ty1BvxLeGKg0dZpJUNsCixsD9DIwJdxYTVM5CSbajMfq0PE0HytmFt2QCmicrIwhg6EuX1xq53FKiUnqheI5HVy8CMshBiLW5P+2MixHrrfqguj724lQgEfFiv3oNxzWNdu+hXVg5MPq/FEqYyaDysm+t8MbBWN1JCWrg9qGOuQe1/lrPzajQ7CNpY1mg0OyamM32SpdRnG8qxoLAXIHm/Iu/Ogg/T4chLYL/TUUYrVX9bofrnmeRddT1mbh5YoUWNZdX/uwE1s+aQe84sUk85kZ73/wNXZkZsr6MbULVhC3kLN4Y1duMWGDE0iFG83XlFFk6D+dNsj2arBmJosyXRsIvNNTEWlVKIIXgHJeJbUw1+i8DCMgILy8ClUF4DCVoQaGWxapp4TjkHAJn1dMuFvCJA9U9CUt2wosLO/w1Hngvol4BK66TlRI3pfM0aM0JjGez3atlU2O/3zQ5Z61YT+OgNAlM+hbIm4e4uF8bYPfCcci7uQ45GxcHobJOMns60HUp3OOpmy2qYO8U5gZYJS3+GdYth2Djn5O5AqH1ORdbOcVoquBLArGl+qMcA1OSzYOKxqMRUh+fdCdB9lrsM2ljWdEnEMmHTUjtUdsCuJHi8vHFPDgAJusdy90DF3itTKgKxG8q11LoC011QUop89BDMnwLn34dK79n++UDFR5+Sd8V19h8tGMfNCI2p+ORzfIuXkPPRO7h7hTdXd2XLe1+H3cbENGF7sUFOYpKjOohlYb32ABSH6dGssaDGD2mhXsoNUErhyvagNtYgDY1iU5DqNkKLDQP34cfiGjYS2b4SClZE8UqaozI8yF6ZUOCHsnTYto0W32yvgiwPZLhR8fAYh4OIbSw7LpeoipDJtqWNPH5SU43/2UcIvP2ynatttqCraWItmodvwa/4hwwn8e8P4RrdcTUS1F5HIZ8/E6MQhdr3d84oFEJ+er/tqtfRUFuIrJsay4w5EDL7Qmm+c0aRyw3XvYEq3mZH0QRqICEFMvvAwLFd2kuv0YSLNpY1XQ5Z/Svy9p1QVmA/kZSGOulG+u7RBfpdasInKTajUEwLtpY7pEyIOoPZDUUB2LgYeeJiuPo5VEavNk+t/nmmbSiHYyQ3xTQJrF3PtjPPZ8DXH3da2OaOgK+gCOVy2cXawsDvszAm7ufY/GKZWI/cAJs2RX5yedD2Wia7mhli7h4eArlh5hsaBq5ddyfptn/ZOq37Kbaq8U1QhoI+CTBuGOqY92HDcqwfX4dVM8AQSDRsAzmyoIrI0yDaw4xTz2aw5UayXycW5K2qP724kJrrLsBavwaQlg3lusH2i5BN66m+9DQSbnsQz1EnRKV2pKi+Q2HknrD6t+gNLGWgJp/kqF4y71vnW5pZJiz4HhHpUCNPCvOxvnoXa8FsqCiFxGTU8DEYx56JMcy5YljK5YZTb0deuMo5mUdfg8ruD9nOttnTgG4d1XWI9KdOo+lUpDgXefHPUN4grLK6HHnrDmT9ws5TTOM4KrEHeKLvQUteVV21YEdRISMhJeT1KM1HXrwBaSPnz6qoJO/q62Ob1zTxL11G8aNPxiani+NJT40obNSdnIDrMOe8XvL6wzDnu+gFVJm2p7khSmGkuu1S3m0RCvl3TTqA5MdfQiWGWpvlL49PeF3hGvAmoEZPxNj/eFSagUpxRe9JNh1uGRWP73ct0Rj2vkpk8XdYP79P9WWnYG1YE9nnYppgWfjuuZHg9BiusQgxDj07+uvHcMGeR6HSshzTR8oKobzIMXmN8FXbfaE7ACneTuCf1xM4/1DMN/6LLJqNrFuBLPsN68t3CF59CoE/n421crFjc6qhE+EgB4psKQOG7wOTzohdlkbTxdHGsqZLIXM+tguRNFksB5SXp1/fwNMfFBOI5wJK07Fk71rfIiMCJGhBiTM5zy2iFCQZdjiwZcKWFfDDq60OL33mecxtedF5lRsiQvEjjxPMy4tNThem34mH2VEDYWAo6HvrX1FJyY7MLct+RT5/JXZBFSEPcwgFuAb2xTVxkv2Ey1Vf8M0w6oxo1667k3T3wyQ/9D9Uckq9vOL1xMVjYPqhMhTBM2QiGE2C0SJ1jJjiTH5sQ3nxIhrRlSXI67fif/ROZFtuTN/3mnv/ihTHyWBsyoRDYe9jI9/IMFyQ0RPj9D87q0/eBmflNZO/ru6f4itHVn+BzHoY+fpq5PNLkK+uRmb9G1n1GeKLrqWa5G0h8KczkBnf2hsRTa+FUKSBrFxE8MbzsObOiPrlNEUdcQVMiqXXsYIhE1Dn3h9xTQ5NBIh0zkMTMToMW9O1KGq5QnLQUry7ZTxsKefC4zPwRNr6YwdFzACUboDS9RCssRczCemQNRxS+nX/fKGBR0DerMjPK26hGEk8SDKgKhRC+e0LsP8ZzQqdSDBI6QuvxG4o1wkUyl57i+y//MkZeV2M9LGjyD5gT4p/mY+0EdqqFPQ/YiLJZ5znyLwigvXCP23j1YnPsiIAGfXh9MptkPLEy5gb1xP4/AOsrZuQygpUcgpGr754jjsZ18hWQjbNOLWLaSBbJWciux0OSxqExwq0WJa3LQKWXSW8u927RMAUrEqT4NYYN+pEoLIC37OPkHjzPc7o1wZKKYwL7sDyVdmF68LBcEF6D4w/PYVyuLgXgThudAIEAoivDBa8COun2NezMhqnMZSuh3XfwrynkSGHwfg/ohIzwxIvlRUE/vZHKCpoP5TcskACBO++Gvejb2MMHR31y6pFKQXH/wX6jkS+eATMQHgh7cplG/YjJkDfHOTXV2GXY1FZA2PWSaPpymhjWdOlUH2Gtrzhb8ReDGpHQawgbPkFVn0K25c2+AFvUtXInYT0nwwjjoceY7qn4dx7T0jIBl+EHpbSOC+2akmsN5YJ+mHuF7D/mY2G+ObNx8wvcG5Oy6Lig092WmMZYM8X/skPk84kWFbRosGsDEXy4BzGvflf5yZdvRA2rWp/XLj4beOqrkJ2gu39dg0aguvKGyKT5U4An8P5+XWyE+v+qSb/HlncoEKxQdjF1urwWeB16H69o93yTCG4zaF7j2US/PJD5MqbUGnpzshsA+X2YFz+IPL5s8jU1+xw5doaDQ0xDPu5sQdgnPs3VEYcCg56E9sfEwu+zfD5/yBQUR9+3jTfv/ZvCcL6b2HLz8i+N6FyJrUr3vrmPdi2KXwvnggEg5ivPo5x+xMRvJDWUUrBXifBiEnItJdg/hf2b1TTommG2y6UqgzIGQFV66FsOZTZBQPl19dhv0tQe5/viF4aTVdEx1douhZ7n2gvKhuG5nYTI1FEkI3T4JPz4ed/wvYlTX7Am/zwBqth4w8w9QaY8iekZB3dDaVcsMsfIjpHLAF/B7RHUKpZKyBZ0twrU7NgUeRtaNohsGYtVnUHec93QFJHDuGQWe+Qte94AJTLhfK47YrDStHn+EM4eNZ7JPRwMI9y9tT2c4ojpfY6NQzUwBgK/WQPJy6WozsRUuqNIdV7OOqgP9bPleKGhAiXEZaA33QmHDCeVbgjFa0UErAI5jvo5Q/4Cc7ouNxlZbgwTrgC4/4pqN//HfqPrA+9VwrSe6COugjjnk9xXflwfAxlgH7D4iMXoKcXNrwN/gj6N4sF/kr48U5kww/tDLUwP34t8jB+y0Rmfo8U5EZ4YtuozL4YJ92C+usXqDPuhv3OsnORB4yFoRNhrxNRJ/8NLnwQ/OttF5pY9tojtP6QX55D1v3sqF4a6ltHdfRDEzHas6zpUqjUbLj8KeS9e2HLcvvJ7P6o42+GLlz3SHxlMOc/sOVn6lZp4dzUao3pkjXwzTXIbr+HXc5EdSNPOzkHwrafIP/X8N6TmtYLbTmOUuBWoUJDApuWNau0Gli7zjayLAf1siyCGzfiHT3KOZldjNSRQzh4+puULlpB7iffESgtx9srm/5nHEPKkAGOzyerF7Zd0TgagqGSyyIwJPp2Nqr3LsjmOQ7noynoOQrVtGbA/hfAxgWwZZ59q/K47MrRkWxQVZvgNoAYC37FM90mkg2uUAi2VFvO5lG73VgrlsAxJ9dPVVMGhavBVxEKhe4PmQMdveerhCTU/ifD/icjIrZH0uXpsPxVlZIBWX2g2OHaDMku1C7pRJ5sDyB21sEv9yOpOageLd97ZclcyNsSnX4KrG8/wnXOFdGd35boxFTY/SjU7kc1OybVlcgb17f+dVQGMu9t1NDJjuul0XQFtLGs6XKonFGo615GinNtAyS7P8ovQMdUuHQaqS6E726Gytod5SgWW7VG5OJXoHSDHS7WTQxmpRQy7hr4+SaoLmjfYA528M5pw/VjTQXUVEJSg7zlQDCqj7Q9JNCBmwI7MBnjRpMxLvY8v3bZFoeiQ7XFCA0Xaq8YWt8NPwTmvuSERg0Q1Mgjmj2rXG44637khXOhJtSVwBv6EkRiMFcGIdVNNP2M6zCU/XC6JRVEHndXY9nGspMEg1gb1yI1pbD8S2Tpp1DWQt0OlxcZsj9q7MnQd5yjKTlKKfAkOCYv7Hn3OhqZ+rqj7aPULumhay2660UBIhZMuR72+gtqxOHNxsi2KFrK1U2gkNwYzo+C4MdvEPjfg3gOSLYr8reEWFDgYAqKJoRuHdVV0GHYmi6LyuqL6jGgxYWBiCAr52E+dxvmPy/CfOIGZO7UNtv7dAbiKw8ZynnOhcds+hFmP2J7BLoJKiED9v0nJPVpvzp2R7/sppdfEw+ykZkRl2njJVfTCk73fK1FGbDP71CpmdGLyBwE/cZHVTm+VdxJ0IIxAKA8ibDLYfXzKQUJLkhyhR++bAEVQcRU0TnEa43shDh4lxWRGfA+y3498dgUK8tDXj8HmflMy4Yy2EXY1v6IfPwn5Mu/IZXbWx7XhVAHnuZcUUSAnl5UqjvmrC2lFAoLmfEvrKl3Iv6KxgMCMYThi4A/jsX6mhB48xkCj91t56cHpO01gyfOeeQazQ6MNpY13Q6xLKwX78T61x9h5pewej789gOVd1xL7qSJbBy7B1uPPZGKd9/vfINy7hO2R7lpcZGYENgw1S5K0o1QST3hgIfssGz7mZYHOpwf3C4NLyFlQEJKo8MJY3eFoLObNCo1FXf/HEdlatohJQ6bE4aClAyMk68L+xSxTKSyACnPRapL6u5har+rHFVNTboU5Ulq/fjoI2hmHboNO4/Z22BpUec8UY2N+az+lObvwuaH11Exv8weGk4Ic8P2JwHLfg+d/spHkgvts+xibeB8WLhSqKpNEKimXUu89jdk02zk7YuQvKXO6tLBqF4D4MDTHNsAUv2THctSEBH7Wt/4M/LFXxBfA4M5NYZibMqADijmBmAtnU/wuYfr/97ceg0MsQRR/TpCLY1mh0SHYWu6BQkexfO39QXA+/1rMP1j+0DIG1S+voqSJVV14/1FRWy/9s/4Fy8l+66/d7i+ALJ5hu0Fjhfz/ov02QOVHKciLJ2A8qTChBuQfgfA8lehYmOo3UWDzYaEDg4/b9jXu9cglNvT6HDi3ns6O5/LRdK+e3fP6uc7MGr4WCRvk7MeZo+B8Yf7UMltL5CldAuy/HPY8hsUrgUrUH8wIRXpNQY1eDKMPwvmvxmbTsqAvuNg1xPbHtZnDDLmaFj+dfPzkxJg18PA8Iby9U07v9aTgOo5FPqNoXr+WkrvvgiA4s+3U/FrGWl7pZMyLhXlNuxCfYqWr3NT6nODlYJEl50H7QQuFdmGW6De+2mkOH3vEYxsT/vDGp1iQaAa+fQvcPJjqJ4jHdap4zBOvQ5r0Y9Qtj02L7PbgIzYvcq1KKVCpQZMKF6HfHs7HPcQShkY4/fFdLkhmig2M4ix98HOKNkOgY9es7+boToM5oZqjMFJkOpCNbj+xRLwWfh/WELiRZbuu+wkndH3uLMdRF0UbSxrugWGoRia40XMINY3rzY6ZgWE0mVVjU8I5biV/e9Z0i78PZ5hQztKVcD2DjHvaSLvuxIBZgAWvwb7XB8f+Z2I6rMP0ntvKFkJW76H4hVQvsE2mj2GHTPTEanLltTPY7hg2MRmQ9z9c0g6+ECqp//sTIEo0yT9Amd6BwNI0SZY/h2ybRnkr4JADbi90HMY9NsFNfpgVO+us+AWy4Q1M5GVP8LmxVC82Q6NdydAr2HQfyxqtyMhZ9fINhx22ROmf+aorurU61Cj9mr1uJRuQWY8AZtmhfrAtnBR+ypg81xk86/gSoDMIVC8PjpvqzIgczDqqLubF/ZqafgRf4Wew5Df3oHKQnvjasTBqP0uQWX2b/11+cope+C8uu9p4rAkEocl4e7pxaqxwCVgCSLgzvDY41wGmBZUms1vmS5lV+X2xfilV4Qfb1f7/qa4odw2jJRLYaS5sModMtwFjD5R5AuLBaYf+eZOOPMFlDs+OccS9ENlib1hkZJl57M7iEpMwbjmMax/XwK+qugMZmVAemJ8NhcNZeuUtxCWfQy7noLKzEYdfBwy7fPI7/e9+qH2PMB5PZsgFeVYP3zVWD9TCEwvwr1bGsaARJRLIZZgbfURXFIONRbW/Fm4Ju4Xd/00mh0NbSxruhd5G6GssNFTNYWB1tOBDYOqr6eQceVl8detIbm/QnWc88rEhA3fIRMuQXlT2x/fxVBKQdZo+wF2f+pAJUpMxH8/rJ3pcHh7E6RJiyrLRE06qcWhmddeQfW0n2Kf0+XCM3gQyUceFrMoKViDTH0cNvwaCnVssstdvh3W/4r8/BKSsyvq0GtQA3aPed54ISKw5Bvku/9CeUHzfqKBGti6FHJXIHPegd4j4OgbUIMmhCVfTT4Weflf4Heoj252b9SxF7Z4SERg6SfIL0/Vv4Y2axqEPjfTB8UbwJtit7oxWjGwm80XStHtOx511F2ohPDuF8pwwcSzYY8zbaPdnYhye9ueK3c+/HgvNUs3kzI2lYyDsnBneuwQbKOxJ1mskAfZBLDsqJEEN5T6mxfy8xi2AVsTpcHsIlShu3byll5w7X8bGF6GNDLU3f0S8JdXNT83ClSmG6NHhJ7lWsSCsm3IvNdQ+1zsiD4AUrgFmf0RLJsO+evrry+XG+kzDLXrwTDpJFR6L0fmU/1HYvzleawnr4OSMAo8NjrZgLQsjNP+ACtfdkSfxvLr/ylznoXhR6AS0nCd+HuC330asTjXKRd2iOdW8re27PkOCMH5ZbCo3L6m/VajyCnZsgG0sewc2rPcZdDxFJpuQSAovPRZCS9PUwQi3QPqjJvH6s+dLcbTGlYQ1k+N/zw7AMpwoxIyUInZqImnx9dQBnvBXFv91nDB4HGoAbu0ODT5oANIO+dM2zsWC5ZF7ycfQcXQ71dEsH55BXnxD7BxbuhJq4XvgdS/h9uWI69fhfXd4ztckTwAqSlH3v0r8vFdtqEMrYdL1z5fsBZ59Sqsbx+zN1raQSWloI45z7G+7urUK1pcGIsIMutZZPp/7MJNEV/HYue4Gm67rRC1a7Lm9zmprSIdsJAN1ciX05DPnsOqLkNKNiDbVyHF65FAdduvRRmoxPT2DeUts+HbW5HqUnqd0YceJ/bGlWHfr5VLNfP+NQwHJSB2BW3TgiyvbRw3xW1Asss2fMH+XraHwpblcdmfbe3DaOFRe6zxi2/Ua9rVy4tKdObe7hmfHqNHVGDR+0gg9p7sUl2B9d69yAOnwrTXIG9tY8PVDMLWlcjU55F/noj1+WOOzAug+o/AuP09OOi00GfTzvtruAAF+/4O4873oddAR/RoEzMAq7+xpx89DtelN4d/rlKoyUdgnHR+nJSLEFOgymycYqTR7MRoz7KmWxA0hVe+KANcnJ6Sjacyv+5YYg9362G5lkXSEbF76SJBxIL8hc5Vv24TBQWLYFTLHs9uy+A9IXMAlG6Nz/sc6qtKoD5vUp3Zdu57z3/cjm/BQvwrVkUdjt3jjr+RuOceUZ0LYNVUwHs3wpbFkZ1Y+x7OeQcp3gIn/8PxkMtokeoy5LWroWBdhCeGXtOst5GSXDj1bpTR9mtSp1+JzJoCBVujz102XDB6Auqw01o+vuAt+xELtZsfpVuRDTWQZECygSS57HuhYHtCK02kNABlQXvMgERk20fw+qfNwrglPcf2PI86FnpHGMIOSNFq+OFOxDSh0k/iULt4WERyBDs3WYBMLxT5mvc1NhQkJ8AuR4N4YM0sKNpCI1exMkBZ9uaVQewbIIYCj4KAoAyFd3QKvgXl0ctT4BqchHtg6wXWwiZQDet+hFHN++uGi+SuQZ67DiqKQk+0cU+tPfbTG8jSH+GSx1FZsReHUonJuM6+BTnyQmT6B8icr6GwhX7G2f1QE49AHXQaKmQkS1J2zPO3iDT+Q1Z8idrN/l67Tr0IXG7M//3Tvt5aul+EcobVoSfgvv6ejutj3auvveEQYVi76ud8//qdG4uOyRdrOqcmUnaM1Y5G4yDqsLPh08ep/SUzPAYZo5IoXd7AO6IUiJB64e/xjqrPx5SCdbBpEZK7EqpKAAWpPVD9RsPAcahsB34sKrba4ZIdggWFyztorh0HpQw46ibknT/Fa4K6PEUAdcrNqN5D2jzFSEsj54O32HbuRfjmzQ9/LpcLLIsed/yNzKvsdAERgepC8JUCAp4USOnTZp6prJkBn94Bvli8PQKrZyDfPoo6+sYY5DiDiIW89zfbUI56U0RgxTRk6pOoI9u+XpQ3EeMvj2LdcYHdbiXSHErDBZk9Ma69v8WFsbX8K5j1bGQyW0Vsj3lvD6yoaL00QrILRqei0tyISOvGa9lWKM9DVn4JWUNh36tQOc1z9FvUxAzA9PvtfPJKP1hNvMaRUmPaRb36JEOJz/67Ya9lMaE8F+PM/9h/+qugvBDERCwLXryAevezA4jYlbBDm2eudDfekcn4V0URjq3A6OHBu2+mM7opF7JtESpKY1kKNiBPXw6+ysi+YyJQtBX576Vw7YvOhWX36Ic66Wo46WqkugLy1tupEW4v9B2CSk5rflLmMOJSH6Rpf++SDUiwBuW22yy5Tvo9xt4HYn7+NtZX70BVJaR5MEZkovqloob3hfQ0VJIbVj2LpA2BrHGo1EHO6tkElZaBceDRWNO/CX/jtkdvjD10CLZm50Qby5puhzr695C7HOZ8U5e3mD48BXeSi/ItEKgU3AP6k37xRaT+/lzb07vwa2TW27BthS3EcIfCH+12J7VhmjJ4D9S+Z8PoA6MPjyvd4MwLDZfqwkY/4DsLavCeyPiTYeEnznqXRezw66C9+FIn/QU16eSwTnVlZ9H/s/cp+e8zFN3/sB262HTBVTfY9jp4hgyi9xOPkDBhN2T9t7DhByhaAYEm/T1dCUjmcOi/Hww9CpVgV1gWM4B8+yAs/gIciaAWmP8RMupg1NC9nRAYPXM/hI3zHBAkMPttZPTB7eYwq0GjMO58Geu+K+36COEazEpBzhCMW55GZfdpPHvQh8x4Dpa+F3mP3zanVEiCAX0SILfJBp0C+iVCv4RG49ukNiS8eD3y5U3I6N+hJl3RZospAJa9D6UboSbQtmPDrRqnKgSt5p7jWsoDMCANlWHf16Q6CEXVUO63baL8VfWvy5sMPZLtP9bOjE9JxSbtptx9E8Ct8K+sDOVct0NoA9c1KAnvfpkot0NeRjEhP7oNUzGDyGt/i764lmVCRRHy9l22h9nhIlsqKRWGjG1/nDsR6bmLvXHswG+BiLRyHYtdXK/XmPq5cwbjvvRm5LSTkVVvgW8NICgMIAhWMVQWQ+UW2D4b1r2NpA2DQSeieoS3GRUN7lN+j3/al+ENVgr3KefHlP6j0XRltLGs6XYolxvjivvhwJOxpr0P+ZsgLZuUS04gda8jUZ76vDop2oR8eA9sXtR4gVqXwyiNf1w3LkA2/AajDoATbkGl9ohcwWBHeZUbzlkDO5mxDKAOvRbZvga2LnHGYJZQ6HWFCVn9UOfchRo6ITKd3G6yrruK9HPPouzNd6n44CM7NLtBL2YjI4PEffcm/YJzST7kAFj9EXzyDwhU0aqHxPRB4VIoXAaLXkaGHgW7/R758h+wYU54C/awX4SBfPMQXPZW3FtYVS9YQtELr1H54y+YpWVgWRgZ6STvPZ6s5Hkk9W7DGxoJykC+fhguebldeWrwaIyHP8F6/d/w3fuAavv6Ugr2OxZ1xd0ob+PKxFJThrx/A2xfZXtLHUYphfRKgDxf/WWjgBEpkO6O8r0LCVr5BbJ9BRz7QN3mTLORVhCWvm97dFuqVu1WkGj3Zq7VpaGHW0TAZ9re44aGsylQ6oPskKGe6EL1T0P8JmytsA28lqgpi+L1toNqudezu6cXV7ob/7pqzIKQEd/06xsKhzWGjMBz7IG4yr5uLihWfFG+5p/ehFzbuIsay4TVc+C3L2HicdHLiZWRJ8J2Z3pPK6WQYCs3VH/jTUyxgrDxI9j4KarRh9/0u9Dg7/J1sORRpOc+MPJClKcFb3mMuMbtifv3VxF87b9tD1QGxh6TcJ9xkeM67PQInVDgq2On6y5oY1nTLVFKwdjJuMZObnWMrJ+HvH5DvWEczk2rdkG86hfkv+fBhU+g+oyIULlOqKunds4dYeVJgNP/jbx/M2xeQEy/FLWGcuJg1BnnwB5HoTzRb0C4evYg69oryLr2CsTvJ7B5C/gDGJkZuPr0thdkpRvguz9DacN83PZeg4AEYd1XyLopUFAeymGNWtUWprCgZAtsmAtDWm99FLV4Eco++pztjz1L9W8Lwe2CBotTs6SU0s1bKDUtEnq4yd4rhcxxSbEZzWJB/mrYugz679rucJWcinHJ7Vi9+8O7TzavzlyLoewogdlfIbnrkCvvRQ20Uz/EV4G8ex0UrrNzXuvKUjuMAWR5oCjUn3l4LIZyA8SCojXIlzfD8Y808jCLCGz6DVn8MeTl2xEUtUWyaklxoxKbh383/bckuOxK2DUmVDUIjyjzI1l2W6C6czwGDE6H7a1sSnbwvVB5DRJGpyDDkjALA1gVJlYo71pl98J11Lm49piEsdt4WPEV8kMcjOUofnPEDCI/vo4zNw6FfP8K7HFs5/WHH3gALBkEZZuI5TWJiH16axEPDXZNxPTDkkegZGloznDnDY3b/iuUr0XG/w2V2DNqnVvDfdG1kJJC8PlH7Sinhmsgw07/MQ7/Hd6/3INyR1mVXaPpBmhjWbNTIpuXIK//2a5gGc3OnphQU468dBVc8jyqRwTVNhMyIp8vFpQL2guT7MYobzKc+SjMehX5+UX7yYi8zCGv0Zhj4OArMNKdX7Qorxdvk17fUrAYfvw7WP7ohIplX6c9EmCbieOFPZQLWfoNymFjWUyTbbfcTdGzr9RXvW3Ji2Par8dXGGTb16VUbvCRc2wmhjuGxbjhQpZ8gwrDWBa/D+vJv8Lc7+0n3Ebze0mtYVB7vW1ejfV/Z6Gu+Adqv2ORr++1DWWxwOWOj6FcS5rbNpb7JECGA4ZyLbUG86/Po/a7Bgn6YOEnyLz37AJ7KuRN8xj1r08B6d660OV2Pfm1XuZEly2nLOSltQSqg5DsaTaWXonI2g9Rw05pLCwj9mJTzRBpPZ2iVi+PYYdm15KQjLrhnUa5vJIWB91QkNF6z+tWWTnTDg92BIH8dbBlObTSMSDeKMON7HsTfHNd27n5bVBXUd7fRphOap/QWAuWPtbAUI4GC3xFsOCfyMS7HPcwK6XwnHkx7mNOw/zmI4LTvoayYkhKxrXHfrhOOBsjpwMqie+0RLKB4uScmkjRxrJmp0P8Vci7/9d8JzViQRb4qpD3/w6XPNduJd06soZHP2c0ZAwOX7duinK5YfIfYMQByPRnYc0vdTmC7f54DN0XdfAVqF4d97lJ8Wr48TawAjGFjyul7AVePIwwMSOvqt2eSBG2XHsLJW++bz8RQZ5k2YoaTF8xg07Nir54lGXCliXt62lZWI/dCAumNz7Q3vscqogr//0bFK+ANaHzHcxTbgmlFJLihkQD+ic6790TC5Z+iJU2EGa/DcWb7dfkCm00KaPx6wsZypHqoZRCXKHzS0ObSD6zkbHciOUvIxkjwciAovUQ9CPKsPVxukp+2G127PdEnXln86JXvUa2fEosKKNRDm24yIZFzXuVx6SHgo2LWzSWxTJh/ULYtBTZtgpqKuy6IVn9UAN3gWETUQ5sUqrskcg+18OshyM2mOsNZav1fUd3IqTn2P/eOgWKF8akr03IYF79CuxytQPymqPSM3GffhHu0y+Ki3yNpquzc6+gNd0Gr0fx35v71P27LWTq01Ce70yuiJh2UbCZ78Dkc8M6RSWkI0k9oXp77PO3O5kLekS+UOquqN4jUac+gFWwBr55ALYta/06MEIL6i3zkIWfwOQ/opLiHxUgQR/8fG/MhnItSik7jzMeFG1CrKBjmzHbH/sfJW+8F93JApXrfOT9UEbfw2L4nArWtD/Vt2/B/B+jn8MAWfY+yhXq4xRLZegwUV4DyUlsMbfWoRlgxqNQadmFpo1WwsqT3VEZynWz1BrMSW7bq9zGtS0A0/8G60sa74l5ATFsb7ApsTtblGo9DL8hob7P6qy7Ubse3FyMNwXpOw7yHKqxACAmanAUVYy3rYquqFdrKAPZuqrR5Sf+GpjxDjLjHSjNr99UsULFNQ2XnfOrDGTswahDL0QNbD/qo001hh2NLHgLaraGbTA3MpRbC79WBvTbA6UMpGY7rH07Jj0bY0HBLKT3ZFSP6FsHajSa6OiE5EmNxnlchmLMkATGDEnAZSi7pYwZaDZOqkrh1w8dL6og019pcb5WGXhQx+Quiwn9W8/b3hmR9bPhvRsgbzkoCXm+mjyMUOioUhD0w4KPkBfOs9svxZslr0JlnrOer7hFXgkEI7ju28CqqqbgwSdillP0WxXByhg2B4Jth71LaSHy5iPRyweo7f3e0SFxmZ445oyGjH6X1BvkTedyKbsQV4w6KKUgyWUbymV+JNDyd0WBXUAszdvyQQPwGvaYaBGxvcptXXK19/reQ1HXvoLa/YjWh449xbnvvlKQNQT6RGFg1lTg6PUpYrefqv1z/ULk32cjXz5pG8pgv+46T7Y0qCdiwZIfkcf/gPXZY0gglvZ3oHb/vd2v2xRE6h+N1W3wvCnNC8zVjgtYSHkQKfFB78l2IbutU5yPXEDBxk8dlqnpVMTqnIcmYrRnWdOtkKJ1yK+vwNqfQEwkeyhqwlkw6ijENMl/5AEK3i3BCgpZQz30HZ+AO8GBxWN1KSybBmNbXwQ1YsRxsPKD2Odtj+Q+0FfvRNcii79Avv5XqCJtaOETzsJdLKgpQz66BQ6/ATXhlPbPiUa/6iJY+SGOG1FxaDFah8uZwi+l73+KVVHZ/sD2EChZVE3PfVOjO99ouwCU/PBBo8rlUdG7BeOtqyMhg6Kt75PT1b4T3VDog4XbkawE6JUEqS1sCGQm2nnOTakdZwBeZRfwi/R7ohQMmQTL59R3OqhL8QgxaCxq8lmw2yF2SkhbDDsIegyHonWxL2xFUPtdUZ/zbZlQvA4KVyLF6yFYbRvySVmo7JHQcxQqpRdiBqE8L7a5m6IUeOycbZn7BfL23XU6hkWtEf3j68jaeXDp46ikKHN4hxwIvz4HlYWAaW+WGAppuH9tSauRByIChX5YX9WoJZv8dBPS91HUWTko5bRRIlC+GqnchErRecQaTUeijWVNtyAQFN7/dC2y5BNOzf4Zjwr9sBatR777F2buWhbePZPi72bWeT0KlgXYOKOGiX9MJzEjRi+v4ULWzESFaSyrtP5Iv70hdx51vUvjwZjTUJ1RfXsHRFZPR76+L/RHVBLs/5/6MCSmocaEuTESCeu+DnvxKJZAwKrvRWs1MP7dyi445THs/F2P0XLbHicI+uziVDEgImz/34t1bXRiEwZFv1XSY5+UFnOXa0pMyjYFqcwzMQOCy6NI6e0ifaCbxCwXZLe9EJVpH8VmxCQaqKZGYwc4mMWSZr2AHcUXRsV1b+xe5VqUUkiaxzaWAYp99qNHIjI4rW4epezWVOJSbYTQhoxbT6QGs4I9TsE46gbbwMxfC9tWQ02lXQG95yDIGR2RUacMFxz+f8h7l4LEsMulDBh1FGrQJKRyO7LyC1jxCdSU2scNd6N7jYR+h6T3bnZ4e1VBdPO2hgiq91Bk0ffIW3fGJIfNy5Hn/gRXPo1yR77xpFxeOOivyJc32k8Ewy+0JD4T5pRASaDllAZVilJ9WjjgBAqKF4M2lrsHIo5HOYY1pyZitLGs6RYETeGZKR7gNE7M+or6tGX7xrDp389T/ENFw6cA8JVZrPi8kvHnxlhl0jJhc4TFjva8Br68DMw4GMvKgMwRMDz2vpayfSOsnoVsXQZFm+0K4olp0G+UXTV45GSUN/IWSpK/ClnxLWxbAgWr7V7QygVpfaDfbqjBe8PIg1HuhPaFtTdXVTHy9T9xxsWqkG8egP7jUWm92h8eCeu+pj39xBSoCdr5cy0OEPBL3XHxGHbbnXgYywrIXwkDY4teCGzYjG/xcmd0AoIVFtW5AZJz6hfShSv8bPqpmtINtle44R5Sre2bMdjDgAvS6d2KXKkqh/zNsSmX3IJ31ZKW83sdwi7y1n7V6agxpY1WOiEU0Rdea02k22huBBfWQNBChmc0fr2JbqhsI2Wg1mB2hwzmdidXMGRv1OHX2n+63NBvlP2IEZU9FI64HZlyV+h2EOE9SxnQdxzsfy2y5D1k7vPNQzCtVqIj8kPVm/snweYqqHEqd9pCsnPg7bsckcXGJci3L6COuSIqEarfBGT8ebDg9fCn9ZkwvciOoICWP5beSVFX2w5DAyhfHwe5Go2mLbSxrOkWSPm2No9vmV7VYmsPEShcGcBfYeFNjdEDW7w1ouEqpTeyx+Xw62Oxzdtcsr1Y2vdG20sRJbJuLvLDC7B+ni3TMBpXRl3/m118JSEZ2fMk1IEXopLbL6wkWxcj0x6H3KW2cdzIs25CySYo3Yos+wq+fwT2Ogf2PLf98MW25pz2ZChfzoldVbGr6n7/KOrEex2QF5LqK7NzlVs7LiEDuCrCEOCAZeeSJsTBu2wAFflhD5eqUijZZl9HiWmQ3R9luAhud77YnVllv9ZAlcWqTyopWOJv5AlqyTlcujFA6T1TyVtyLaOfvgtvz+zGA7aui12xZAOxpLnhaIn9fsbLoI1nEbFWcoYbES+vtsdovuFY6ocNZXa/5dqK8J4w7u+1ba5ctJ6DXFtJe/cTUEf+GeVQGkKzaYYdBMf+E5l6L/grw4xmCOk//DDY91KYcgtSsCzCmUP3SLeCISlQ4LNDjmMlvSfM+woCrfS/jhiB715Cxh+B6jciKglq4kWIFYBF79DeRqqI2B7lGrPNnxGVmWB/l+N1vcfBWPZtL8KsqiGhdw9cibFvTms03Q1tLGu6B9WlQOs5iv7ytr23/koHjOXWdurbYtgxULbZwfxlZS/49v87Kj26UC3xVSHfPGEXQqtzv0nzFiK1r9dXBb+8jcz/Ek7+P9ToA1qWawWR6c/A3LfqDYLWQtBrn/dVIDOeg+VT4fg7UT2GRv56Kgth2bfOFrYQE1b9iJRuQznVt7V4devTiUBlMDyjpDUSXXZodmWM+bYNMWj3upeC9civH8LSH6CsiWHtTkAGjsVUo53TKYTlF/zlFr89V0pNceh9a2+vJHR8+8dTqVywnD1+fJ2Efg38zAEHjAaP0XL4ZtCChPj9JMctG6O2AFJn0ZpNUuhDUqpQaV7wusLfhFDKNnTMJt+12jZK2YNQh1+HGrpPTGqHpcqgSXD2K8gvT8Gqb+sPNL2X1W46pvVFTb4K+u6GfHE9VOTGMHno/eqdaG+0FMRg5CoFE46BH16NXkYrcuWnt1Bn3hbl6Qq192VIz9HIjEcgUNX670RRwA69bo94pjpgR0k5MYOIsOXdL1n50AsUz1kEgCspkcEXncLoWy4jeVCOA7No2ib88H9n59REijaWNd2D1L5ARauHU/q6qdgSbPE+YbghMdOBwjNRhAsrpZAJl9hFkpa9TUxhwsqwF03734bKiW4hJ9VlyMvXQe6q0BNhGmdiQXUp8sZNcNxfUJNOb3zYDCKf3QZrfwYizdMRKNqAvHUFnP4Yqk+EhtXiL4nLD4QykMWfo/a/xBl51YUtPi0itjc5FkMZQrnMQIrbGYPZFZLpavm6l+py5KvHYP5nrfdrDfpg/W8YuTNj16cpHlj4Shk1JWHk0jbFNKnZsIUFR/+RveZ8gJEQCudOSoldr9ZWumaD74WD3mURwV8YwNvH2+LU9kaMaVcHtrAX+6mu5nnVrdFCxE7LioSrcYS09bUoC9gbRD4zsnuOAlKzbIPZcEH2IOi3C2rkgdB/XBwriregSlIm6rBbkX0vh5XfILlLoGAF+Cvs+31Gf+izK2rI/tB/IoiJfHaNbSg7tUHYM8HezCmOovK9MqDnQFsXJ/s2gy1r3pfICdejkqIs6AeooQdD3/HIso9g2SfgK6MuQqu2K8L6qvB+nmO9T7dHVRkSqEF5Ik99asjiW//NyvuftSPGQpjVNax79h02v/0lB09/g/RdhseqrUbTLdDGsqZboJIzactYHnRUBktfaMEYUZCzp0MVsXsNi+o0pRTsfhHSc1eY/Qj4yyJc5IR+wbNHw6S/oNL6R6WHmEHktRtsQzmaRVZoMSpf/BuS01Hjjqo/9N2/6w3l6JSDQA3y/vVw/suotNaySls4ddO8+BS1EAs2zgWnjOXWvOx+q/X85EipNZhjDcmubbsDkNU8gkHyViOvXA+VxfYTbS2QxcKT5rzbs2B5kMrc6BfmEjSpXLKa9fc8ybB//Nl+sv/w2Bf8bb3tPtPOrXWK0HW/ZlolI45x4c2wZYslkO+DDdVQ7G8x5Fi8CnonwOBkVGYbocbhXkbh9CGOEDs1oY3PosyPZHlRFnZus6HCM+6VAUMmYhzvQH6tQ6jkbJhwdrteRVnwJhS13ys8YnonQoUZmTGoDHB7UOf+A3nnHmcN5VrMAGxaAqMmxSRGJWXaYdnjz4OC5XbF8JJNYPrtW/Onr4b18yWF1Y7n5tfJtgQqayBvBQwYH7WcbV9Msw1laFZQUYImgdJyZp56DUcu/aJDN4Z2PjqjlZNuHRUNukyuphtS2ywXe+dduej7t/sYesc1Dfp/2v/pNcbD8COSY5/ScEH/KHpZNkDl7APHPQtjTgdPaJdcteHdqT2W1h/2ug4OfyhqQxmA6a/B5iUO3LwV8sm/kFDIraz9GRZ/RsyuJbHAX41Mub9ZT8xWTxGB3OWxz90a+avsdixO0IKHViyJPEe5PZTd6zamu787JEe5oElovBSsR1640jaUw7yW3MkuUod4W/e6RoICTw83W391IGRahI0PPIs/z86pVh4vDNkltphmXxvXiyUQMO0xlUHbM1rmh/KAXaE4aEXoIVUov0npliC5S32IJUheDXy3HeaWwvaWDWXALhK3pQZmFCEzCpHyVq7DcPURENMK+7vbrrjaHP62xFnUF2NSQEaYlZPFsgsPdjGkZCOy4LX4CFdATgTeTGXYFcEPPh2p2Q75cTDga+fZ7FxxQOXyoPqOQ+12Gsb+12McdDPG6DPDv87zquJnYCqgyg+5K2ISs/qRl1Cu1tcWYpqUL19LwQ+zYppHo+kuaM+yptuhJl8FG6ZCoMauqrzbyaisQQy/82By9u/N9v/8C8uErKFuUvs49BWwTNRuh8UsRnlTYfc/ILudB5tnQP5CKFwOZZvqPY+uBMgaYXuS+0+CXrGHBUrRFuSH52LWPyTNLoD1xSNwxj3Itw8STXi55bfwrakikOsnuN2PBCyUx8DdMx/v1gwSL/wzRlo7VczNAPjKo34l7RL0gb/KLlYVK+mDmj9XEwdPTC2JLtsgi+TaUdQbyijoPapR6xYJBpC3bgF/dcSbLtnjU6hY74SBC1aaFxFnNhnEErY+9y5D/u9KANThpyPP3hm9wCqr5e+rJXYV5op2PnOXsitqJ7aRh1tbWdtvgikUbwqSmFnDwMQAbI0g97T2K1sahJ8KkTGpMDS5if4RfLdrTEh2cNnRUu/kpoQ8yUopxEX4aQiVzhedizey7EOc2XFqAaXszy7RAB/tf7+9QA83rPgQVnwAOV7wuaA8aIf9O6aXgZTkxutV2wQiCD8vrEFKfZDujY/RXFqDlOVF/XrFssj/bma7LfqU203+lJ/pfei+Uc6kaRfdOqrLoI1lTbfA61E8fL0dmpsw4gSMPU5scVzioafQf97zUOOkAaWgx0AYNME5iS4vDD7UfhDyolgBUK6YKly3hsz5wNmbqGXCsmnIos8iXnRafovK2aVUL6mw+18aNIocCm73U7P0ecqeeo3kc35P6vU3YKS2kq/WESFOTnmWMwaDckPIyBORtr2QsaBCvZeFkK0TRtsiF02qNQtq/EmNx0x/BbZvJBpPfspgL+40g2B5bJ+Z4VVUFkalQstYFts//rbeWN73GOS9J6GkMLrrq9Js3lomYIEvTIVNsQ2OahPSPXZObkNqv8e+IJhCdYmJWW0xyBtAtgajW2TXqrasAmosZJfUev0jcbJXByHZHXNrHft+iO1xb3dw/T+VUkiS247WaLfYW9daVIq/ElZ/03o6hxMoF+x9AOTWwJq5Ld/7Eg1Ic9upHgoavdFew85/Trdguy+8Fl3hEO/7fGp6RMNlfgHqoBiivFqSaQkUV4bC4KN/vWJZ4fWyV2D5HNi81Gi6AToMW9MtcBmKCaMSmTAqEVcb+ULK7UUdepnDswvqyGvimtujlEK5vPExlC0T5n3i/IJDKfj1zYhCVgN5Pore3Eb1wnLbUIbm64Lav30+ql55ke1HH45//m8tC3R7wYhPaxcbBV4HwvgBZbih19j69yvehWLAzlsu8tu9VFuqaKywjWQPtkez4TXuSYZRh9f9KYEa5Oc3iNZKVUrR79D2W4+1R9/7/k5lgbOGTsWilVjBUH/mhCSMy+6J/vsSFCgzbVtMxP4MwjWUm8op9tdfJ7XGnSV2H25TEEtYP7OKSZNcZGY45HNcVwVrqur/jkSoABWBmO+VSikoqA7PZmjp9yCcvPAEB4q5dSS5C8CMs3EjJpStRl38GOqeaXDFUzBimG0A90mAAYnQK6H1qIfa5zwK+iVCkkO/Z0mRGbMRk90bcoaEH4WzZDtUBW0D1ykUsKUEEFRCeJFMIoL4q5CaciRoR5QYbjcpwwe2+1okECR9t+hacmk03Q1tLGt2PvY+NeQFNuwFZ+0jGk+CMmDc0ajRBzqtZcexfSPUtF4cLWrEgvLwK7IGcn0Uf5SPVdl2H8tGWBZWQT5F552Ff+6cZoeVMqIuvBYWWQMbhSHHzMgT6t+vjmjHk+iyDeXiAOT5YFsNlPjtmCOvshe1TY3kEGryJY0rsi793m4jFgNpQxPod1j0C9/e/3cDqSedhNVW0acoEJ+fYFFp3d9q3H6o06+OTphhQKmy39KAxOZdE+zPK2CHW1MdCFV+bjBki59evQ0MJ4sOrahASkNe3UjF1phITTDq3GURQUr9UBFmmL23+TInWG1R+H0xRdNKKF9ciRVsQZfeo6LSr7OQwpVt17hwCn8FVBUAFsz5H/jzIMmw3+dI2nMB9PLanuhYsIKo/vH9rJRSqOPPC/93yW8h36x3rNCXiMDmYqj22978Pq2/XikvQGa+gvXeDciTxyGPH23/9z9HYP3vFKxPbmOPq/bC1c7Pljs1mQFnHeeI/prWkE56aCJFh2FrugVBU/hsum3w/e6AVNxt9TrM3wCJvaCihRA+T8hACOdHThnQZwTq+Jui1HoHYVtsxUJaxYBww8WsapOSzwpC7XMinMeyIBCg+NKL6TnlO1w9ejY+njMWClY7X4lVuaD/OGdl9psEST3tNlJxqB7cCKWae3YEqLKgyoTUVn4elAG9RiBpPWHxJ3bvtYz+yJrZjrSGyRqXjJGg2PJ1abu/7coFiT28JKRAxmm/I+WAYQS2rI1p/lZpYtwZJ1+G5U1E3noEO2YxzNftBoakgbLAX+mAXkBpwDZYGhgrliVsnlXNqOEqrCj7iFDAgjLkwGwUEVSZrqU2fDox/JDsunFlASioCW+eFDeqSZi6Ugoj1U3JzDL7CQuMrxTp/8/eecfLUZVv/PvObL393vSeAElIIKH3DoEISO8ooIAIgqL8FBURsICIgqiAKCqgUpUuRXonJKGEFNJ7Lze3363z/v44u7duv7Oh7fNhyd2ZM+ecnTkzc57zvu/z7l5J7YHVWD7LjPGhk3P/PZ8GbFm87ZR1tyxGV8+BjQspePItYu6p/n5Ym6OXQDqM2KkPB+cGOeQ49B+3QCSU28L6imZ02jpk3yF9aldVobEN1jV0bhy8Y+9yjWvR1+6AxW8kD6TXtWnZDIvfoL86HPuzASx7u52P/9dCLIVnyy6//wmecne8pkoo4bOOElku4XOBaEz5w0NbAZi6b3lasqzz3kD/8aP0k4qkpSdoGYtaJgzfGTn7t8hnzV2vJ1q3msmh627YuRdtfn0rmk3ZNhMcB21toenan1J725+6d2PiVPSDRwqsOAM0jkyc6mqVYtnoXt+F16/eNgvA6cZ4QwzKU7hSWpZZBKlfDM9d17uLFQIhMUrKfUD1uCDBQV62zm5n6wLFaWkDj8cQUoXyIT7qxngoH+zpJForXkH/9jK2o64PZ/F68NT1dhG3jjkX3WlvnL/9ApbOybxYIMDgRComO2JcqN2Cg/GO8ZpzoQhxApTXjsTaPAdx+95WTNz0pgj08xpX/eQNnytpbo6ae77Ci9IpwtWrqSRJjiu6qT2/HOFVqUMw7OQiUeK0OGGlYVoTbUvbGfqVQdhBkIlfyr2dIkA3rUFffQSd9y60NEA8DuVVMHoi1uGnIWN6EMRwM9vKaqT1y+H9B/renghYCjVeqC8wh/OoSUjd0L71I5emyiqwLv8Vzk3fy/kYnbYOAhay66C84/Q7yje0waKNCX0JC0btiVT071aOWY+jr91mxki2e10dE13jge0PCjJsso+ZDzazZVkMjTv4+tcy+ZYfMeqcE3PuawkFItf4cbfbLCFvlMhyCV8Y6PKP0HuvTDwssrzk253UhFkssGzk8Ith3zOKEkO8zfEJ51GMNUQJL+6b+y4A8Tjh554htnQJnu2279gsgyegA8cZ67IbpEEAnwcqq2HVi+jyZ4x1taw/1I2FfuOQisGFVz94D3TMl2DWk33va6GIqXHPTpIKwRDlbEPFK+DzmpQ+LbE+WYt81R4GHVjJwBt/QtOSCG3TZqINm6ixFhO0GlAE6eZvnCBcllBeK7RscY84lO88FsubmnjJqB2xf34fumwezvP3wkevQGvEkEaPGAt9lRcG+hBvl3h0t93sIwoeY0IWAe9JP6fu2iuKZ20UYEUb9K81M4muswlNhrdkaTucSJMVMOre6rG6EQp1FMJxtClqPIHyOWU+y9SbKxQiG6Osf3gTQ689Gau6+AQsZTfmvUv8v/fAvHegp0dA/Xp01SKcNx6HkTsiU7+C7HcsYuXhAu0GVs1MLLC64K0jiXukIZr/80Id5MAz+t6HHCH7TkG+cz36x6sxOXKzHFDjRZ12WLoRRtShHjMes5FmTagk6/LNsLGLGKk6yB6ndSnnoC/9DmY9XtjvEQjUeDjw4ho2ciDO9kcw5NhD0j7rSijhi4oSWS7hCwP97+9TuyalQ8SBoKezfHkdsufJsMfxSOWAYnVz26Oyf3Em1DlWGZrXUkhmqdSwbdoeeoCqH1/dbbMcfjn6YIExpkl4rUTqFDsx2QnB8pfp9HGVjsmj9p8A40+AEQcidgETj90vgQWvQmtj1qJ9QibC1ho3ZNnKMSwBugv41HihKdYp1FYgrICf2jO/TM0BO+H89pvQ3gIO3YlyD9SNsGmpz0HxOBfYFv2OOTR7OW87wvswqTL7/VQMlXMFHBNjLlN/Au1etLWIadMU2BRBHe0dmymSINC2IczZxkAo3pEmTZOxr6qwJVzYgostMDiYlpTE0y3kKITWhAnFx1K27C2Ix8BXDv23R8pqC+hI7lBVnMf+BE/+BXXM2lSqxSlB0Zii8+ci86+CR+9BzvoO4q/CvQdpFqyd7Q5R7opyj/FWyBWWDWN2g8lHZC/rImS3PdC96mBZk/GsgO7XSTFx2COCMCxg7o2WECxYB7UV0L8C/Oad0E0ATBJq7bE4bGyCDU0m9VvHfgu22w/GdKZy0tfuKJgodzZr+jCIN5GJRyElolxCCb1QIsslfCGgaxfBitn5HRQXOPQiZOBoGDIeqgcXVfH6E8OQ8UWqWExQaZZJVWR1yL35XTxO5O23evdk2GR0jzPhvYfIuzELkzOzV3xlF1G4njFsWxbAWzdC5TD0gB8i/fI7x2L70HHHwgf359fXfKBq0g+lm1+HHUOSCxnzkqi02mNcuvtiRa0eiG5ajfObb0CoLafY4CHjPayc5U6eZRxl6DfPzFhEm9ejz16d6FsOv9WtlDm9OmIhx16HjDsM56l/FCe8olt7GA+CVO7OyXHjSbju5yK65pEE6Xc6yayjuS/WJOsYUtYrVrmjy44SWtE75tk/3E/1XlWUTyjDWvdP9Okex1UMQHY6DiYei5T3y70/OSLyl5/jeecxwKQ/I2h33puhuHFZjyjaHu8YPwow/2P02kuQvYYio63i5htOIlaAy3Q2+C3IdW1HLPD6kTN+uk3fyaoO+uKvkEobJlWh4TisDxsvHEfNgmqtF+q8vfvlKGxphi3NqN8LQR8EvGZsq0IoijaGoC3c+xEiFvgrkKOu7KhXl76deJ+5BUGfuwEGT0SqBrlYbwlpUcqz/JlBiSyX8IWAfvRS/uJDAmIHkQmHFq1fnwrUDoOyGmhrcL/u6uHQuDotYVZHiW1xd+IVW7QQjcUQT/fHmxz8TbRhNSx5i5wJs9+Can+H5SDniVmSoLSsg+cuRyd/FXb+Sl4TOxm8c+60XtV4QkQTnyTRsMVM4HyW+bcnQomCqQiz38qPpPRE0jpYaRvCXGAdOnAH9NbLcibKAP5yi2ETPayZ20fCbFkMv/QrBIand6tXVfTlmyAeJadxpVo8pfMxByLjDjN/r1xkrl8R0+4C6clyEsm4VL+d3qJu0XthJhbvXGgZU25EwTKdNwEqvVDrQ+wMCssCbR93qv/b5Rb9v9yfih3L0bgi6eL4Wzah0++Bmf+E/b8Jk082avsuIPTQn/G+94RJvVTnQ3ooeKsqOrvJ5CZOA121BWt0/7T7XYMnAOoyWRZJqVqeuqwFHh9y4R+Q2r6JZ+WNhS/DujmdXfHbMKoAEaxw1Hy6QhNhC72Isg2+IHL675EKs0ij4Rb0fzd2PmNdgUIsij7/azjl5s+nYaCEEgpEKXVUCV8MtG4l7xwnYqOtDcXozacKYlkmnZZLE78uFcO+52W2LMe1byqoqRCLoe29Y6DF8iDH/QImH5fYkGU8+G2o8Xe4xxUETcTHf/RPmHF7fulyhu0B/ixplFShLWbcVRujRsU6miBj8QSBbo0ZMan6cHeyohgCIimsx4LJl9pXO5UYt+CC0sOIBcMnwXsvweIP81bZHr2Hl0ClFPwTxGMTGDWU7W64InPBVTNg7Qe5u6UWc2G/6zlqb8tPobpQ5OJmL4nr0HXBRjAE2SNgd4m5Ve1w8TYp/TDx2CPKYFDQWFw9YmYvHjGLOv39MKoC6R/ITJQBjSpNM4wStn+ojxGXDqd8rCE8aYlyx8EOxKPoG7ehT16JRtuz//YsiNdvwv7oHuO+P8jfiygD6MctsCY9UQaMS3yRc7Oro+jGVvr8XEiFnDJQCNQNRS69Cxm97dXKddZ/3H9PdkWvsSvQfwzylT8jg8Z2bv7oKbO47baVUOOwYgasn+duvSWkRtKyvK0/JeSNElku4YsBj7+Ag9TdHLqfYsieJxp5TNcqtGDyVGTHI6BmWPoJhpu5X7s270kjxmR7sI78AXLyb6G8f2dfe8JrQY259q6tsC96CuY+kHNxsb2w0/Hpz13cMSQ4VyGtmBpC3RQxbq5NXQR1VLvPfys8ibeDSy/WnimqcoE6sM+p6PP/LMgV3PYIk77kxxfM/3Dx2HgH1LHrC/dgZ0mfonMeJ6/8tsUy2IgYobkkbE/x2urZbq7lPJaJZ/ck/k6Vw1vELP60dRnUG9rNUCyzkSFlyMgKZHSl+XdYOVLlyymnraqy9fktaNjBN9DL0POGYPmt7CQ5FVa/j/73KjReuJVVt64ifu/ZWIN9JpdvKjXw+gi6IgdSHld0aWv3OFiXIZbA+hZ0W6WoMo2af71+OPRc5P/uR4YVJ3RIVdGWDejyN9FZ9+O8dzf6wT/RRf/DWfYmbJxfvLAGSWhD2IlnSaASOfgi5Jy/Iv1Gdemjk8juUKTrLDb64WPFqbuEEj6jKLlhl/C5gM8j3HDJgI6/e0KGjUOdPF0ynTgU6aX8aYNUDYCjvo0+c3MBB9NJeuMJsatAJTL1O8ZN8air0IdTi2uJLVhlFk6bexMQq19/JBjM3OUx+8A3HoYlb6MfPWkEayJtnb/HbaKcxKx/oEP3QurGZi8LyKRT0blP9k4LE0sQ5ULmSyHHxBxu7TLJ7+nOV+XBNaYlYlILeSR3sS+xoN9IqBkJaxYX3HSw0mK34wLMfz1C47ocxljiPFQfsAcT/vmbjO7XABoNwcp385tAJ62sbs91xYLaLgrO/QYliEaRiU0+XgOqRrkqE6FriMDWHs/qqMKKNmS7isL6CGhcCa8Ns/XlLYgtDDp9EOKRnEh26godWPMhvHcf7P21/A9vXIPzn0ux7UjG54yzoj31eBGMVV3EPA+iii5uRXYo/Bxl7K8qrA/B1igysgj5d4P9YHgFNC6DAAkxxSBU9Ef67wA7HQcDd0Js9xewtX0rLHwOnfc4tG02G8Xk2zbK1PG0yu7qKJvnh1n/Xohwo/Hs8FfbDN4jQP8d/fmPr0HbI7ufBWMPSb1Yv34+NG/Ir858oHFY8DI69UeIVaIIRYU6xdWUSNdmCXmjdCeU8LmAbQv7TspAkHaZAo/fDOHW3CutHgTj9ul75z4r2OtkWPQOLJ6W/YEasIxSuK9Heq1kypgxu0P7ZiirNuJae30FZtyXsirPID+R5e3ukAfLwrvrrjkVFcsDYw9Gxh5sJkRN66BtKyx4FNbkEdecD0TgrZvQY+/MKe2YBKrg0B+g//tp50ZHDaHoS/eiaq5dtKvaahfC7M8hTVQ+UDUWxTyUseWU69ClH/e5aX+5xeQv+dmwOM7q2VHaGsyCjnjsDsE2jcVBlbIdt2PkDy5k8Hkn5bZQsqXAdGQecV/ky4kjQ3bs/L7dBKPmXGxU56GeK2lWCZKK8m0x2Jwm/3R9BPW3IcPK8s9ZG1eiW6Osu2sVOFBzWDXeWk/hRLmzZnTGP2CHQ5G60Xn0J4Y+fTWEmjP2oUNAKolyGxkVRPr7oap7/zUch61RdEUbsl15IT8mQ4cTYR2zGotj0LRtGD0GiW+GUCL0pMNbowGap8O0d8EOoKOPgjHHIpXD+9ysOnGY/TD6/j29xfl6Epket7mqsuaddpY810xoq9NNS08sWDu9nUCdxfZfqmT4frkuLghU1CETjkxfZMMCiq56Ho/ClhUwYPvsZUso4QuAElku4QsB8QbQA06DV+7NOWZDDjn785FHOUeIZcEZ16MP/BCWzCDlyzhoGzEfWzonuN0qEUOK1sxA/zMNHTwJOfj/kAMuQtsbYc5/e1UZGFdOZFnfY/8AcBwCx52QU1ENt8OS2eiKj2HrJtP36mpk69sUbSKiDjSthDXvwoj9czpERh+A7nomfPig2dBSQD7SXpViCHHUKOx2g0fcdY+Pq0kLFMm903LCVcjQ8egbTxl34j6SPhFh8FgPg3awadmitOx6Fq0b2nHaQ1jBABWTxlG1zy5U7L5Tft4E9SsK65DPhqjLRNb2wOg9Or7KuF2Kn0QoaKWMsc0IERATi9yxWNEcg7Xt0BQ3Cu1xjDdCwDb57v2J/MvrQmhUYWQZSnbCnKy/fVErG/61jnhLHPEINXtXu0CUO34QOusR5LD/y/2Q9+6D+uWIZLlCjYkxErSwJlUhgwOpU3VhxKZ0oIVlCRpzTAoxtzxjROCDhg5BQG2OQoXHnfqDRhtCWhfQnaym0ACIh2Dpf2HJU+j4M2D8mYWl5gO0ZSP64jWwZVFuB3TxhlBV5j/axMpXO7UxuvLq5N+heoe59zfSsi7G+JMqczhfmvWZohsWJLwziqzct3FhiSyXUEICJbJcwucCsbjy4nRjNZ6ydzmeFDFocuQ30JVzYcnMLIRZYJcj4IAzXO2jqtIy8yOim+oJjBlB2YQdXK3fDYg3AF+5Gd64F33172aS5MQ7XZODdue5y/TiT050NsxD/3Mhss9FcMQPkLpR6Jt/TghNJFzWxgSRoIW295EBimDV1hE46ksZi+nWjejT96CvPQbhNmMGsBIT/pF+GFtRXCVQsWDBEzmTZQDZ+xtmGjnz/k4F675CFcpsiPQgbW4pWcTUiIvlakEVC2wvcuJPkEkJy0q4d4qfvkBEqOwvVJ9yIDLpwL5XGA9TkJXHb0EeTi5ZYdmw01FIWXXntgFDYNQ4WLHQxYZ6YEQB7riJRTZ1HNgSQRe2dpLCnkiGZ3gFrfMiFR6jCN0UheFBtDbhpqp0EMikiJ6IQNhB++9H09pNxFvXAFA+sRzxu3h/axzm/w898FuIN3P4B4BG2tD37yeXMaNxRYYHkMlVHQtYmUi+CEbLIAoStM293JdnWfJaLWuBNV0WNFeFYIIL7t61PqTMm3il5HgPJZnogodg3TvoAb9EAnV5NavN69CnLodQQ17HJbHs+dZuRDkbVrzSiq/CYrujcjhnTpYY+FBz8YmyWBBqKm4bJXwyglslga+CUBL4KuFzgWhMuemf9dz0z3qiaVw9xeNFLvgd7H1CRzxS9wJirDOHfAU5+xfG0uoStv7vdd6fOIXZB57K/JMu4sNdj+ajg06jbV6Oq9rbEGJ7kEMvQC65F3aeYlzk+vs7YxPzmXxpHJwY+s4dMOOvsPsZyDn3wnYHJK6BcYetOjS/yU7qtpSqX1yP+NLHtDlvPoVz5Qnoiw8aogxm8hWPQTyGDAn0vR9Z++nAhg/RPCZqIoK1z0VQllusc46Vmgm4t+f17KM3RTJ/c0M0P1djseDLP+gkygC+QoT5coDXpets+yjIC8ESs1DhFsRCDjyv46s6Ds5tP4VlC9xro1ebwPDs5LAnFNBQzLj0zmhMT5S7IqqwIYKuD6NJlfelrTCrAVa0weYw2hQ1Fs+GKKxtRxc2w+Y65NhrGHznH6n6qsmVHRwddD+MOx6BTTk+yxe+ALEsytYJSJUHa/caYyXOZAlPph2KKTiJCIr2eGeqrUImyKrmWm1qh1k9iNO6ELTF+yYmVuc3oTwUyucVmlfBaz9Aww25HxVuQZ++whDlXBXsuyDSHGfxM7kmhO7E4qebibTkMPCsbJbybUR2SqSqhBI6ULIsl/CFgnh8yKlXoUddBO8+ji6aDqFWKKtCdtwf9joOKa9xtc2Gl97i4xO/0evl0/LeR8w+5Ax2efdxAtuNdLVNNyCDdoCTr0GtTUYFtK8v6Q8fhPIByM4nIcdfj7ZsgoUvoxsW4K+ZT2CNEvpoS4GdFQInn0pg6tFpiziP3I4+8RfSWgIt3HMtzAVbFsGwvfI8ZrW7fdCescsCnmAiJ3mBKr9tcSjES8CJwxM3oL4gstPhZtvQ7YsTdztsO3fqqenDfRu0Iey4knNZDr8E6Tei47s+fje8lFC0zcUTpBDsUI74C1hQVIXZzbAxTWxyJrTGIRpChwaMgnVMU+ceFgt8AeTiX3Uo4w+65UZqL74Anv4uYrtp1sec200LYWj3dEaqCg1rTJqfeAT8FeiSN8jJG0FAchEadDT9GArFweOYNHi5joOkNTnmQGME3mtMUQaY0wx71+QdPw6YfNgBu+/PWnWgfSO8ewN60I055b3Wd+8wIl75ag1YAnFl9bT2QtceWDOtjTFTsliXa7LEYgeqEs/nIlqX1UHrP4I5jSAeCA6AmrFQNQbxbIMF5S8KHN026f16tllC3iiR5RK+kJCq/nDkhciRFxa9reU//jWJAL3uO+IO8dY21vz2L2x/xy+L3o+CMPtR2Nh3kaUk9J07YcReSPVwpGKAsTQn9lV/NQY//D6hJ/JPWxH48vFUX39j2v3Oyw8niDKknaRWercdURYL6vMjy9qyBdpTTFz71A/pfAsk3VfPvAZd8DBs+Ji8F0hCBRJl0wHz33+ugX4jkcE7IGN2ct+OUjMAqXTBkwFgwFgKFtsRMfH/jZG+WTonHwP7nN7xVWNRQ5Y7NiS7mEJjoBAIJrVYoSJSC1oKI8pJRBQ2hNEh/tT3q2WDvwy5+DZkSPeYS9+4sThv+qHNbbJso+0NHc8yjbTBvOfRmf+BLcu7ly3LMaVXOl2IrojnMNmOKcRiibRdVqfjSM/3UVLgL+qg7TFzL3/UnD7sozlmCPPOlfkRZq/l7rNWHdgyF5Y9A9t9OXPR1TNh0f8Ka8cC4rDqjdbC1o0VVr6RhSxbNgyakLEaGTgOnfNMAR3IE00fQSSRb1kdTKyDBx1+CIz+MlLz6QsjK6GEYqHkhl1CCUVEaMkK2mZ9nH5CE4+z6YEnO+LsPk3Q9q3ou3e5XKmDvvmHlLvE46H6t7+j6vobIRjsjCNOB8uCQICqX/6K6lt+j3hSr/3phlXofb/J3rd8UuD0GQLteVrR61cVpysWnUT51CuRXQ5DJh5N3jNCR43lr08wbeqj16HxGAwfB4NH45o0t2UhB+YmAJcLxBuE4Xv0DunIFbZAta+7onxODSfa2+dM5PirulvUFn4ETVu7l09eyr4+ZwTjtr97TUECWbo1Aotzj/VMi3YHmtOMtbF7ID96GBk5MfX+Qq9VRmhHvfr+I+gfj0f/91ujKNyr/RyqS46HbBblfKxEMQfaY9AaNf9GHCPwF3WMh0NLBK0Pmf0bQjCzMfv9vCFsXLRjmvs7rKowQa6smHM3GsssFKmz7iv8+luCE1dCWwtf2QrVZ3Fdd+LI0EmZKxk8nqK7Ygvgw7ipaxeVcI3B6lfgje+h7/0GjZTimkv4YqBElksooYiINWaPbXLa2sH5FOa+m/8s5JubOhs0Dqtnoo2p3YlFhLIzzmLAq29S8b3vYw1L7ZJmDR1GxXevYMCrb1J25tmZ85Q+cjvEcyBx28qqnES+57ZYaYBEzOeoC5GDEhbKcVPAV0ZeJLU97s4czonDhiXw8auICHLkV3FvcijIwae4VFeixkkn5e/S2RW2QI03txjm5ES/ejByzh+xjvpOb9fTUBoy6gZh9luwbx1SaLz1xy2Ft90TWyLdCZpPoNqGU680nkPpUDnIvT4k4cShYiDOK7ejL/wOYklhugLPtZBFQDGD63U2KObYqGMIc8SBmGOGxdYo+n4jzGvNXW9gcwTmNSMx7RQs6jnGkts8ggQKC3VRVTQSR9tiaFMEbQybf1ujaDiORtth1avpj29YAes/KvxeTZDlviKe6byW9YORWbyNBk8ozhjuiooMlv/k+Vv3Jrx8MbplTnH78nmGKh0pyrbZ59NnmPksoOSGXUIJRURgzAjE40FjaYiOCP4xIxD705eiSuc9SVFWsMVG5z+L7PONtEXsfv2puORSKi65FKe+nujCBWh7GxIswzt2HFa/fjk1pU1bYPrzucV3uTARyh0CnjzFq/wu505NQhVGT0aO/mbHJvGVwcGXoy/+Kvc63FLpBhALnfZvZOcpyEEnoq8/CqsW9DlOT064BKkb7FInExi1LwzaycT1FyAYZDomxj03YEM4DhWjoX4tRLtYyioHwIjJyC7HwvZ7p4/PHJQh5jHpkg25u2UnvcyHB2DHSsRb2Bq7tsRgSx/cr3vCwdyz/b3GtTjxWySQJSZ00ERzrdyO+Vy/GGb+J3u5bOc9l9NbjGeVAuVeaM5zQUOAEQG0PWa8DTyWWQCy6Rg7GnWIN8WQGj92mtRXabulmgjviKUIV0ieB3MtdfrfYdA+SFmKMItlr9MtGXIBsMusgqMuICH470vz28VCJp+IWJmn5SIW7HYK+vqfCu9INtTk8G5SB6It8M5P0X2uQwbsUpy+lFDCpwAlslxCCUWEp7aafqcfy+aH/tvLuikWBCqE4Wcfji6bD4NHIsECUrEUAdq6BVo2FqnyOKz7KOfiVl0d/n33K6yp2W/nPiluLZLlNhU0DlUjspfrigHb9Xmy17sfCnFBzvllb0vCjlNh2Tuw5DWyTspi6u68TR1YNRsNtyL+cqwLf4lz/VdNKqlCfr9lwZhJyJfOy142T4hYcMSP0Ye+btL29OVE2Dbs/mWsQ7+PqpMQhoqBvxzJcbFEho2B8bvAwtmpz5Um/uezOq2HPQlA1+8D/TCqDOmXXmU+J2zMTQE6L7TEYXCXcRuohPLM8egyci901r9zb8MWE2frtYzIk2BIW6yLG3PMyY0oQ/cFi5QdzEGAqxhrmJZApQet8RpF8VxR6+1cQFES5wTUUaJrwoQWtBJdZ6599TdG5eWsojEHmqO5Lw401aP//hoc9H/Idod0r2vTgj5b1cRjUTfOR/3CSN7XQCyoG+tLbbEVCyoGwC6n5lbZ5ONg5gPQ3uC+pTC5aJcT1LzLpv8cPfhWpDLPd9oXHaXUUZ8ZlMhyCZ8L+DzCNRf27/j704QxN/2YlhkfEVqyAo/HYeBIm35DLYLliXQgHzyA88EDgMDgEch+RyJHnYZkshAVG5uLnNJq8yKc5fNgzjvosrmwYaVZTKioQUZPgO0nI7sfivj6qLy5bJ5JB5aLC3NbHI05iGdbRKco1OWXBkq8fnTgdsZF2c3Z8sRDkbohvdsTgak/QR/dCOvnZa4jTbq2vkFh/SIYtSsyZAzWFXfi3HIJREL5WQVFYNRErMv/iNjFeeVJ9TA46jr0uZ92ktG8K7Fg8M7Igd82X8XKSvzSwfra93Gu/rqJaU0l5GSDHDbA7N8cQbdGoSVmvnsEqr1IjdcQ5aDtjot9PgQsV7R0GQdiwdCdsrv4jtzTuLE2b8hczm9BmRfxG+LQOybXqDlr3IGGCISTObezIK6Z3ayzuWAXUc1WHYURgfyu1QBfL4EvJxSn6eV64lui3U6JZ2gwZxdsjSbUuPNFpBV96efQdimy88md2ze7kNFBhFFHVFC/oD7vQ9WBkYekWfBSBznyJznl6QYQfwVM/RH62A/z7kfmioFBZXm6yauJZf7gd+hBv0Hk0+clV0IJfUWJLJfwuYBtC4fu/umwygJGDdWJgcePd0A/Jr96P63XXUH5mvc7yvR+HymsX4k+cTf62N/hsBOwzr8SKa/apn0HoK3AFE45QLdGYFUjvHm2sfgp3SxgunQ2vHA/GihHDj8dOf4bSKCwa6ub1+UX67s1gvbzFyRelBfEhtr80xfJ7iegz97iYj8EOeKb6XfbPnSXE81EM5bBolssF/aG9TAq0ZftJmFd+xDO3dfAwvezW9kt20xCjzoXOfESxFuknM0JyOj94egb0Bd+bvLo5uuS3X8ijDgWPnoLLa+CEeORssrC+jJhd6yf/gnn1h9BwxazYISaBamAhRzYD0kKLdX4slI8DSQIc4FQVaOe7DYiXa6/OsikqVkPEbFgnwvQF29IXcACqnxIwNONIKclEJaYnMHVPtjYnv08xdRYqQtFEeUtxBK0Lk8Pggq7F1FufHYzTlIcLHkKvYL4cvvdGldo6pvLvr5zO5T3R8YcbDaE88+NnAr9dwnir7UINzi5c28Bf7XFgJ1SP4PkoG8jPdKOZa1yu/3R3U+D9/PwksiGwWWFhVmoA42LYPkzMOY49/rzeUfJsvyZQYksl1CCC9BIG8x/AV36Fqz/GEKdKX4cqw55fz0Vza25uaAlxb5eexLn/dexfvQHZPyuRek3kCbth/sPVI0rLGuFTV0mQamEzZLkNtSKPnsv+s4zWBffgIzfo4BG8/sduqoda8A2yCOZTNOSLyZ9CV6+E8Jt9N1KYsGYPZH+ozIXEwv1JFxQ4+7kBc4d3duSAcOwvn8XvP8SzksPwKIPEjusxDlNCJjYXtj3aKwjzkZGjt9mvZVR+8BZ/0BfvwWWv20WRdKR5uQYEA+6sh3efxN4s/MXe7yw75exDj0NGZU5nUzK6nfdH+uvL8GMV3E+eBmWvQkVcaj1QLmdV7ofsQQN2iZ2NI/L39FGYwxcDFfuDYFABex4WG7Fxx8Ji16GldO7L7h4BOoCHc/pXM5PsozaIEPL0S0hY2lOh6SKdTYLcipsg4mueC3UbxmF7GzwSDdPHHWUppfrDVEuVH9MFVqiLryCBH39Zhg8GQnWuHbuLFvY7dL+TL9xo3FwyVatgOWB3b5R130RNrHYJwd9B9nl5PTHZ6r60MvQWAQ+eqKg47thUBCp7GOoxeJH0dHHlKzLJXzuUCLLJXwuEI8rb8wyYjgH7RLEzjcVS4HQeAzeux+d/q+EAmr34D9ti8OHSwpzU3UcaGrAueZ8rGvvQiYWQBZT9VkV5r2P88z9MPNVEwdaVoEceDRy9JnImB3B7641W2MOzGvOP7WQOtCwCefXF2Fd+htkj8PzOlyq+6G2nZsaNsCmMBqKg98qbs5ljcH692D4/nkdJv5yOPoH6OPX9b0Ptgc55gfZy/kT1k1LjLXWk4iZ7OoO6rXcFfhKory21yaxLNjzSOw9j0Sb6mHFPHTdcohHIVCOjBhnrLL+3Fwa3YaU90OOvh7dssyI5C1/B1p6uPzaPjTqgZWboTGeenzGovD2kzhvPgY77IZ1yW+QqtyE7Tr64vGiw2qR96fDSJsO9ajWKNT4CyPMESfn55lYXhh2OHLsqWj0DzD9ZXeV/ztCbhQ58nLEk9tkX0TgyKvQR74NDavMc8buJMqF3PvJY6RfwPCyTC7EYce4t39aUW7nRpZ7eOBE14SN63UqxBSNKZItTCoZB95nKERa0FeugYN/CN4gRNxRY68e7WPP7w/g/d9vJhbKEEMu4AkIe1xSR/VIb/cdlYOQI69ChmRJFZUBIhZM+T/ovx362u0mPCVfjxZbYEgZUuZCSq/QZtj4AQzas+91lVDCpwiin8YEr58iNDU1UV1dTWNjI1VVn4A7bAk5oT3scOz3TDqip383nKC/+HGn2rgWfepq2Jw6hlTjanJV5jLpyATLAn8Q649PIXUD+1SVxmM4t18LLz9uiE/X2M/EdznjEjjmJHjwnL71O9mmKsxt7psbpgiIhXXV3cgOuburOS//G73nevIyUwzyY+3am6S5CsuCml1gxBTYfh8kmLu7raqiT/wCZv+Pvphf5PirkV2Oyd5e6yb0/jMzFwrFYbP7Ak5y5bNIeY3r9W5raLgFmteDxtFIFL3zati4KnfiaNlQ3R/rB39FBuSuZaANq9H7v24WEnqOFa8FlWaCnC85VEcNoYmnIApiQe0YZPzRMO5IxGfUqZ2H/4Lef5u7KtS1HmR8JWy3N3LGzfn/jvZG9Mn/g02LoX8AbHFlkUxVYU2bUTZPB59lyH7P9mxJb3VWLZI+QI9mPmw0KaGywWshu3fOi5pe2EJ0QzjtY6nm0jF4hmZexNLGiEtkOQHBXFurDLY2ZA4nyRPhxjirX29h5cutRJq71+urtBh5cBnD9y/DX+VJWJLjUD4AmXwSTD4Z8brnxaQNa9HXboPFb3Z62WSCANV+6BdA3DIuiA2jpiKTLnGnviz4rM7Pk/1uePV8qir6aM3Pt+2WCDWH/v0zd84+aZQsyyWUUAC0YTX60KUQaiLtzGBpW9+JMpgJdTiEc8e1WD+5o0+TOecv18MrCZetnpPWxHd96E/GKuercGclfn247/GKqoDi/PkqrOv/k7Pwl+y0D5ovodwQRte3w8BAcWKXBaN0vHoGTHsNPD50l6ORvU5GhozLfrgIHHcV6sRg7ot5tp1w/Tv6+zkRZQDK+kOgBkIN6cvkGIuYF/qN/FwQZTCCPOrdDl21GOeOq2DTarCc3O9lJw6Nm3FuuQTrJ/9EKmqyHqLqoC/8irS+otGE0nClNy8LMySUkwNeUEUnnYsM3BWcKHjLoGZUSguvTN4H/dfvc24jJ1R7YeD2yEm/yJ8oR5phzl1gr4F+7hHlDgwMwOrW9OtZESeRS4juxDjXlF7FRK4iYvseDXwIkVbizTGi6zMvmEVXtmMPSk/OVNVdogzm/Ecc8IeQGj/aHjOeFS7AX22z/XHVjDmmioZFYcINcfBW4B8xhpohrVgaNXoBNSNg0I7Gijx8d8Ry36tAaoYiJ9yANm2Auc+iqz+EDfMh3NpZyBajdF3uNXH5br/fNA5bF7pbZwklfApQIssllJAnNBpCH/u+IcppXJ60PQ7rXLS0OXF4/w2YMwMm7V1QFbp6Kfzv4dzKPnAbXHoesvC/2VeoM9UTdWBFW8HHd6/Mgc1r0P/9CznuwpwOkUEjYeLeMH9mXu6fOq8JqfSiQdvdCUXCYiSAJieMsQh88F/0vSfQnY5ATvppVjEqsT1w0nUwclf0hT+YOO+M1ykRHlA1EDnhp8io3XLvsgg6/kvw0cPp27AEymxoc8tqKMg+p7lU1ycHjcfQd1/BefZhmPc+hNu77/cIBC0I2tmtO04c6tfhPPIH7POuyd744tdg/ZzMZaIONITN5NmXaxxzYixVDIH9rsTqv2P2vgCMnwwjd4BVS9yJHxVgrwOR06/PKa2WOjFY8g666gNY9R7UL+90vx5a7ipRFhFzPiu8ZkEiHcJOIi2V4XQiYgS8toUgfyZkCpexLPD4kAt+iBx1Gvrg92DFTGIbs1uiwx81Etw3g8J7sazmUQfxJ+oO2OacN6a3gOcLyxbqdgyAWMiu5yC7n+tOxVmgThzmvYMu/hDaEwJmZVXIDrshp5xrFl0SYqM64xdI44Lid6p5RfHb+LygJPD1mcEn/UjOG7fffjujR48mEAiwzz77MH369LRl77rrLg466CBqa2upra1lypQpGcuX4A50zQrib/wP56PpaK6xop8h6Nt3QdO6zLFBbhLlJCwb57kHCj5cn3vIuHPmglgU2eTpE1EGYJN7ExLAWLJefNDEiucI65TL8o+TjCo6ox7a48bl1A1kEvRJWvnnvYLecxkaaU9drmt1YiF7noxc+jAccA4Eu7hUJQWvkug/yliTL7k/L6LcUd2OX87+kq10IeYNTL/La2HXo92p7xOCLphF/JLjcG64HGa904soA4YcNMdhYwRtjaVIT9QDThym/Rdtbcre/qxHzDjIBgdojqJNxv012QdV7fbpQOVw2Pf7cMydSK5EGUMErbMvc2WypkB8l72xvvq7rERZnRg640H0Tyejj/8Y3n8ENi6BWNy4kQeKYzNQVajKwcUy6pgwhnjX807q87QNLM4ap9MjSixDjpOoqEZOuRDrT89gTT0dEUF2OgpUcSLZn7GxFe3ENobTP1OLJR7YpV4RMQsk1f7cBDfzxfgcPXb6AG3ZivP8vThXH4dz++XoC/9E33rcfJ6/F+e2b+NcfRz64j8hGkWC1YgTKnq/AHCiaL5x0yWU8CnHZ8qy/NBDD3HFFVdw5513ss8++3DrrbcydepUFixYwMCBvWM5X331Vc466yz2339/AoEAv/71rznqqKOYO3cuw4YN+wR+wecb2tZK9KYfou+81Llx4BC8V92CNWHXT6xfbkIb18IHOaRq2FAEsuzE4d2X0HB7QeJF+tG0vOIFdcki5KCTYO7jhU9wNxbhPDRuNpbinfbNqbiM3QU5+lz0uX/m9zvCDjptCzKhCoYG++Yd2YMoG3fDFH1RB9bMQx/+CZz9m5zc9aRqIHLYN9FDLoQtq2D9AmhrMBPd6sEwZEeo7N8ny5lUDUF3PhnmPEra1Q+vBVVeaOqji6MqctLVOVkLP61wnroP5y83dF7zXBZrmuIQctBab2ZvhngMfecpZMpX0hbRlk2wbnZ+nU4KKwlG/dwjnQJOCk7UQdsU6b8T1qjDETt/V1LZ/0jY/yiY9mLBQl+qEG5XVr3Vwo5ZxrTWr0Sfug42dnEN7TmRLy9S7m0xLq9qS3YS6GAW5ja2Q6UHKjxolSc1l7MoXvoosZHxByNnfQOWzEU3rTPPpOp+yPYTYOiY3td9whHw0h8QqzV1nT3Q9r8NVJ0zMs3eYlm9eqjqi6A2UOGDZpdk2sWC7Q5Dyvu7U18a6MKZOHd8DyLtne8zJ8Xi8db16GN/QJ/5K9a3fk9xVgbS4TNnhyuhhIz4TJHlW265hW984xt8/etfB+DOO+/k6aef5u9//zs/+tGPepW/7777un3/61//yiOPPMJLL73EueduGzeZLxKiv/kR+u4r3Tdu3kD0xxfg+9uzSL++iVN9GqAfPZE1v6uGndREyA04DixfAIWkkorkQVxVIRJG9r4QXfEOtGzKW2VT4wrtRZjVWRa6dA6SI1kGkNO+g65fAR++nh9hjik6uxEtq0IGWRDO4xxaXcZJqkl9KM35VAcWvQPzXoGdp+TcnFg2DBhtPkWA7HU+uuJto+ycbvxXeiAS75Mythx6ITJ2v4KP/6ThPPcwzp+vN1/yXWSKKGyNonXe9IsbCvrqw9CFLKsqrJ0Da2aj6+cb0cFw3MyPrYSIlEVuqz1KgjiDxpTo8jYiH7fi1CcXQW4H6048Bx+O//Rz8Oy1X14LMda3f46zbgWsWJy32Jc6SjwGSz6MEm77gPZ5CwlOTB3nrxsWoA9+B6JZLGo+291Y5Z7w29CW2RNGVY3rc8iBUMSk1xvoR4f4e/fNktxjivOFxpHJJyEDh8LAoTnRK/H64cjvIQt+nFMTkfkthD5swD+5uveiULGuQ4p6RQT8Nhq2zTOrbw2AtwzZp7jCVs6M59B7fwooWF3GgHb5dIVZWcK59ZtYJ+1Hz2wdRYG3orj30+cJJTfszww+M8s/kUiE9957jylTOiePlmUxZcoU3nnnnZzqaGtrIxqNUleXIWamhIKga1eib6ewFiTEqeLP/eeT6VgX6Mp5OI/8FufuH+L861p0+n/RaJ6Wz/kvZHdNzjc9Ul4QdMWiwg7tNyj3yYhtI/0GIt4gcsyvwVdulC7zgWvxqz2gwKr8zoF4vFjfvhk58uzEhhzOgyRUaQ+diByzL7Ln3rDTJOjX3+TATQXLgqpqGDsOJk1O1JFmohbKMIEWC303Bw+GbQjxBJAv/coIv6Vz7xWBfn4Tv5xX5ZaJ9zvyUjj0/L539hOCrlqC86df9q2SiEJLpntHYdNq467rxNEPH0f/djZ6/yXo63fCwldhywpznzgYV++oY1xrY05OkyVVJTy7meaH1xF6q6ELUU7AiRN742Vav3UuzScdQfSd13P+eVJeiXX9PXlrL6gq4XZlwcwo4TYF26b+0WdTl23agD70XYi2Z17k80hxRPyS/VDNKn6nSYXrrT3O8cYw1Ed7u+Ynn0tuQyzovwMUkspop6PwHjzFuDfngNYn1xPfEEKbouimELqhHd0cMqS1GJN5T+proKpQ4Ub4iCIHXoEEi5NFQVfOw7njUvSfVyN2gihbdH5sEK8Y81fPn6oOqIPOnUPxrcsCNWOL3EYJJWx7fGbI8ubNm4nH4wwaNKjb9kGDBrF+/fqc6vjhD3/I0KFDuxHungiHwzQ1NXX7lJAdztL56Xeqoksy7HcBXo9w5Tl1XHlOHd4eeRy1fj3OLeehN58Lb/4bZr0M7z2H3ncd+tOp6IxncmpD2xqgdXP2gsVa9QdjVWjPzd2tJ+TwE3OfiMTjyKHHm+NqRiAn/hEqB5HXy7Zo1g8HDeWv0i0eL9ZXr8S66u8wMhGGkbS8JWF1mYiOGYB8cwrWETubCbUI1NbChImw736w9z6w82SYuDPsPAl23xP2OwAm7wKDBoM39SRMVdGIk3kxQR1Y+RG6cWnev7OYkJoRyPF/gPKBJE+UNsfQ5W3oohbzWdGO+mzo58v+hkm6mQ8YjXzjr8iBX/1MWyXif7zWncl+SxzNJHbkOOiGReh9F6Mv/Ba2rjLbExPjtIipUQbOcG+qo7S/uZXw+02ZPWQSehTOmlW0Xn4h4SdzXxCViiqsn9+FXHodVNaYdlNFJSTipZ24smF5nI+nJYgyRpE7tmVr6mOeu9EIG2VNn7MNxloGMq6qxkV7QyS1a/WqdmNlTpZNwq1UPz0gU35ccI5p+/Rf4N91VNZXhF3toWxiOdaKFpjfCMtaYEUrLG2Bj5tgeStsCplx6ha8qR9EIonFkj6q+cteFyFjDulTHamgkRDOY79Dbz4XXfBux3AVkV4fswOjrt7TZ1QV3RqmeP77JDsGNdkzOpSQQNKyvK0/eWD06NEpx9ull14KQCgU4tJLL6Vfv35UVFRwyimnsGHDhm51rFy5kmOPPZaysjIGDhzID37wA2Kx7saCV199ld133x2/388OO+zAPffc06dT6zY+U27YfcGNN97Igw8+yKuvvkogkD7tzK9+9St+9rOfbcOefT4gNf3S77QsqC6uNd9jC1/ar6LXdm3chN76dWiuNxuSbn9Ja0N7C/qvayAeQ/Y9PnMjW3IkLsWcf6mCp7DbVg78Enr3b6C1OfMk0rJh2BiYuEfnsTUj4LS/oTPuho/+nT2PY7GsH0nYhVsDZMc9sL5zPrrsXVi8Hl2zFZraTJ+ry5BhtTBuCNIvS+5jn9980iHTYkFDDh4Nlo1+8DQy9dvZy25DSM0I9KQ70QeuhddehqTVMXm9Ez9b+/lgdBBqvUgobiybHedEoHYojNoV2e1Y8+9nmCQD6JJ5RvHaLbTFoSrNvR6w4MFvQayA+HDFEBGv1Yt0qSqh6Y3ElmYXmOtyEKjS/osfY1VV4z30yJwOExFk6mno4Seg016i6Ve/xBeuxxcwz45YBFobHZq3OtSvc1J6bFvBFO/yha/Aihm597/YSLMIYLxLHEOGM3GYtcYCy8gy8EnnsTauCmLJvhcg/bcv/HiPn+BVfyR8ynGpC9hQNqGCwHZBUNJb9BWTarA5BjVeqPX1bVHDFhN/nwaqCZG3SJ6xywnvGtn3UmTiiYX3L12/WhvQOy6FNSbePieX+MR5UhS8QIzO8bepHY1WI2kWDlyBOjDM/UWDEj45zJgxg3gXod45c+Zw5JFHctppJlvF9773PZ5++mn+/e9/U11dzWWXXcbJJ5/MW2+9BUA8HufYY49l8ODBvP3226xbt45zzz0Xr9fLDTfcAMCyZcs49thjufjii7nvvvt46aWXuPDCCxkyZAhTp07d9j86BT4zZLl///7Ytt1rxWLDhg0MHjw447G//e1vufHGG3nxxReZPHlyxrI//vGPueKKKzq+NzU1MWLEiMI7/gWBTNwNBg+HjWt7u2LH49hHnfiJ9Esfv9UQ5SyxcfrwDbDzwZnzl2aLfUsi4H4OxQ6oIoPTiaNkhviDWD/+A861F5rJWSqBHcuGYDnWj27tRV7E40f2uxiddDL68X9hwXOpLe1iQf+xyO6Ho3OvL6ivGWF7TEqovsBTjQyqhUHVxeH0qhDqTThUE5a9rTlMzNSBxg3Zy21j6Ka16LUXwepl3ZVye87b6yOwJWJUZy+4ANnrDPBWQDwC3kDKXLyfZTgvPwW23WFx7TPa4mhlinhanwXDg4ZN9kWtPprI89uFtMTXR4guKMxzBaD1mv+j+n/TkGBZzseI14ccdDStL33M4pvvhHhuv0mjMSr226P39pkPZdWV6EDMyTvHdN6Ide+HOsbNXptjuWtbtMRhXjNa7YH+fqjygxVPuNq7QJh3ORV2P7vP1Xgn7Ezwwotp/+ud3baLV6javwa72mPOda6nuyFqtB0GBzNa6DOizJPx+ooI6rVMmFEuuhzJsVUzCjn0x0hd4QsM6aDhdvT2S2Hd4oI8VUTMogoeOgmzA6xqR8eUF8mhwoK6CUhlab6cO7J4AhWrzTwwYMCAbt9vvPFGtt9+ew455BAaGxv529/+xv3338/hhx8OwN13382ECROYNm0a++67L88//zzz5s3jxRdfZNCgQey666784he/4Ic//CHXXXcdPp+PO++8kzFjxnDzzTcDMGHCBN58801+97vffWrI8mfGDdvn87HHHnvw0kudSsuO4/DSSy+x337pxWBuuukmfvGLX/Dcc8+x5557Zm3H7/dTVVXV7VNCdohl4b3qFgiUdaatSahm2udcVnQ17HhcmTa7nWmz24knU3A018OHL+YmIuPE4d0nM5fJ1ZpZZhX3ztp+YsGHyk57Yt3wDxiViCuybGOpTrrDTtwD67cPIsPGpK+jYiDWXudjffVh5NzHkGN/ixx5LXLUz5CT7kDOfwY5/g9IYBT48lftzop4DEYXfg4A8A2huC5pCi3dXcU73CjXteemsaIKoWb3u9YH6PpVOFecAWtXmg2ZFI2Tv7E5ht7zH2iLIL4AEqz63BFlAP34ffeIMpjz17M6AYb6jVHLjUlWpHsMc2R+S+EeIarQ1kbkuSzP0TQYcMGZeRE/75CB1BxzePcu1K+EtXNzPzdJMbMiQUTQFW3o2hC6LoyuCcGqkPHGKEQEsjEG6z1wwTPIqXchx/wSdjkFbF9uacK6dc4Gy0b2vxg58FLXFgzKv/sD/Kec3qUdqNqvBrsqM2lNi5ADG0KFhTd4JKfFaxGBEXt0nkOx6XYjdM1K0H88csiPkRPvLApRBtD/3g5rF+UtgNcVHee6i0lMlzUXLz0XDoxPr9BfwmcfkUiEf/3rX5x//vmICO+99x7RaLRbaOuOO+7IyJEjO7Sk3nnnHSZNmtQthHbq1Kk0NTUxd+7cjjI9w2OnTp2asx7VtsBnxrIMcMUVV3Deeeex5557svfee3PrrbfS2traoY597rnnMmzYMH71q18B8Otf/5prrrmG+++/n9GjR3fENldUVFBR0dtlt4S+wRo/Cd/fnyX+3CPoko+huhb7yBOxdtyl6G1HYspVf9oEwNO/G07QFvj47dxfNqrorJeRIzKopNflZs0UEbTG2+me6hZEYMQOSE3fUlPIuMnYv3sUXTQbnfk6tLdAZQ2y35HI8O3yqytYDcN37/iu7a3oI39Fn3sQGuvNRMWLu7GBthfZOXcl7JTwD3enL+kgFjQ1dnztRpTTqWD3qkPgU5Q+SVuacK65EJob85vEOXFo2IJzzUVYNz+ElH16fpOrWLHY/TpjDni6TNRrveB12SwUdcBn47TGia3sYy5WEcIP/gPfiWfkRIw0HoX6lRBqwqdxhl50NOvvfQ4nBzX1YT/5Tu80Rmvn5t/n9hjqtYpiXVbHhtZEXLIbKsSWjew+Bcv2Qr/tod/2yOgD0F3PQF+9BVZMy24hTe4ftCNy+A+QutF5d0PbW2DlfHTzarNAFKxARoyDgaMQy6Ly5zfiGT2G1j/9keAIsGsKJMpJtMeNW3ZVHuE3AlT7cm5XJp0MB14JG+ehmxdCw0qIh8HyQMUgpN84GDgBqS7uu0OXfQSvP+hKXR0WZhuz8BZ20LkNyC5uC5EJjDoa6V+AOFwJnwh66jH5/X78/gxhZcDjjz9OQ0MDX/va1wBYv349Pp+PmpqabuW6akmtX78+pdZUcl+mMk1NTbS3txMMFsHokic+U2T5jDPOYNOmTVxzzTWsX7+eXXfdleeee67jJK9cuRKri1vgn/70JyKRCKeeemq3eq699lquu+66bdn1Lwyktj+es775SXfDINSSiK3NcZLSnsWKVzEQ/JUQzsHaNzTgPllWRY51b+VWxk5Cxrr3ctOPpuH84SrYurnTshOJg8/Fx4wI7HJAZnf5XKrxVKOB7SC0DFcmsV2hCuFQB1lWVdPEunZozmNMiAVVA7KX20bQZx6EDWsLs2g6cVi7HH3+38iJX3O9b5801InlHqaRV8Vd/hZM/LfbpM4BVIkua+t7ZhlVnCULcZYsxN5hfPpizRvQ2U/BR09AqHNRacgoGHT1EOrfb2Hju220r+lxv1gWOA5Df3QZA84/s3e9GxcacpMq72w6NEeR6syTxIIgFjLoADTuoqq9E0cOPq13U5UDkeNuRLeuROc8Ccvfgca19LqYFQNh5F7IzicgA/MTYtJ4FP3gFfSVh2DxB733AwTKkQNOQA45jbILLiZw7NHo789A3HjGbglDhSc3d2wBav2InYe13YkaNetRByCjDii4m9mgjoNY6fulL95jLNl9sCp3hYiglnZ6qaxph6OOgQ3TcOXdJxZUDIeJX+t7XV80OFpcQdh0bUKv8NJceNHf/vY3jj76aIYOHVqs3n1q8ZkiywCXXXYZl112Wcp9r776arfvy5cvL36HSvj0oqwmP9et8pqMu0UE3eFgmPdc9timWg+U266lkVIRpHYActAxrtTnNpxXnkBvu7q38JeDsVx5UqdQyhuqsPptnAevRk69pm/uvFV7QahIatNr13bGQrbHDVHO193TiSO7HF2c/uUJjcfQp+/vm+uvKvrUfejx52acLALomvnoa/fAonfNZGziocih5yH9+xirXgRoLIK+cp0JvXDbo7frLVPhQYqkgkxc0bZ438lyAs6G9SnJskba0Bd/AwtfTisSaFlKvz0r6L9nOa2rIix7eCvhLeY5WrH3Lgz+7kXUHp9GRKy9Kf8xGnXQtigE+2j97AmxYc8L4MOVsHBm38mPZcEeRyHD06fmkdqRyEGXwUGXoZE2aFhtNAIsD9QMQ/xZRAvTQFcvxPn71bBmcWZ371Ar+spD6MsPIl/6GgQTMfduKMQr0JKDddlvQaUv/5RgdvFCQ7Spgei//kT8uUehtRkZOhL7uNOwDz8a6TesU5irYSPMfcOd89UTHc8ngd3/D97/DWyYTp9ueLGgfBjs90vE88lb/0rIHatWreoWZprNqrxixQpefPFFHn300Y5tgwcPJhKJ0NDQ0M263FVLavDgwUyfPr1bXUntqa5lUulRVVVVfSqsyvAZJMsllJAzJu5v8uHmpBgryO5HZS+1y4no3KezlxNBd6yA9xvdWbxVxfrODUggd+GcrtBwM2xeDK1bAIVAtRHhKuu7O5bOfM0Q5XRpCUKOWThA+06Yqz1GzXPOS6jXj5zy08LrCmwPwXHQvohCL5LTGCL8wkJCLyxE69uQMh++/UfgHx7C9ohJ11FIvmkRGDwOGbpjQf1yHTNeh62b+l7PprXw4duw+4Fpi+iSmeg93wW0k2DMeg6d+zJ88y/I4E9PHk9VRd+4EdbMhGqvETRzEx3KtZLIXV0MRg44alJVuTRH11Tidq1b0EevgPoVQOYUJklLZNmIABO/P5LWgafj2/VQghNyufYFPGO2hGBYBYqLYl+TzkfKB2Cdcw3Oz0+DSHvhJEgsKKvCOuPK3A/xlUGe1uNUcKY/h/7zGjO+tytHgh4zDOOKtsagKQYNkc6xk7hn9bm7oS6AuClg1BJNT5b9lhHz8hYosFkxrPB+ZYC2NBP+zlnompWd52btSmJ/vhnnsT/i3XMcnHI1MnpXWPxecYgydD46qvohHj+6549hwX2w+D+Yeyaf65RYVRu8H0y+DPGVwhoLQgGpnFxpE/LWZLr77rsZOHAgxx57bMe2PfbYA6/Xy0svvcQpp5wCwIIFC1i5cmWHltR+++3H9ddfz8aNGxk4cCAAL7zwAlVVVUycOLGjzDPPdE/h+sILL2TUo9rWKJHlEj63kLIqdM9jYPp/s6/qe/2w17GZywAycDzxiu2RpsVZV66l3EZ3KINFbfl0OyWidjWByfnF6WqoGRY8h859EhpWpS5TMQCZcCxM/DJSnn8stDY34vzxJ1kKYayrZbZ5UBc6GQ1aCdKNqeeDZ9AjLkJqBmU+Lg1EBO13tBGrcsLkyxRiizbRdPVzaGvnRFHbooT+u5CQOlTsXY1vePo0dRmhiuzb293yk4K+84I7roG2jb79PJKGLKsq+viNxnOj6yTCiUM0jD59K3LB7X3rg5tY8iKseMP83d9nFMDdmvtYyY9lYlWHDIa2HPK8FwIHswjlkmVZpBmdeR8aaUMClejwPeDZn5vnUB7kSXAQolRufQQZlH0xk8oBhf2GmMKWEDLABSuGWNB/EuxgUihJ3WCsb/0O54+XmfjefMmjZYE3gPWd25Hy6r73Lw/oO/fDjLuQg/ohlhglb+g4xyKJ52jUgdVt6Ko2kyIOzP3rRN3Vq4g4UOczLsWqpiMeAVv6tsjhCUJZ5qwqqaCxMMTCJkODN/VCduyhv6Crl6ckRc7GCM7KFVj3XA5XPIKunJd/GEEOEBGTTkoEOfAks82yYcK56JD94KPboXFJdhX55P5AHez0DWRo8dzVS/j0wHEc7r77bs477zw8XVKXVldXc8EFF3DFFVdQV1dHVVUV3/72t9lvv/3Yd18zXz3qqKOYOHEi55xzDjfddBPr16/n6quv5tJLL+2wZl988cXcdtttXHnllZx//vm8/PLLPPzwwzz9dHbD1LZCiSyX8LmGHP8ddMkHsGVNmom+cQ+Wc3+JBHNbHY3798ATW4R6MuSKTNY+JGDekYvzJ8xJN95IU4yoN06utEtVYd5T6Ft3mBd5ppljyyZ05j9g5j9hz3Ng968idm6PBXXiOLd/H1oask9O4xgLa7BAC3O5bazKXY9TYP4bsO+paQ/LBrEr0IFnwYZ/gXZNSpkZztZ2Q5Tbor0PSShEt0xvpKrMxlOXZ05osWD4zrBzDuRgG0G3bnYnhi4eRxu3pt+/bhHUr07TCQeWvoe2bkXK3RaoyR8abkHf/WPHdxlVhi5oyXBEniizEa8XDjoZ66jz0H9lEB90AVaNp89Ga3ugD/+e1dhzbkPFArFQJw5OH1I0qWMWSp78MZz3LySDG7AMGm/aKwQtUdQWpC5QcF8VkJqxsP9Pu/VTxu2J9d0/49x1JTTV506YRaBuCNY3b87ofu02NBaC9/6Ern4eBgc63nPd3ndd//Ra6OhyZGQZuqDZxMXaFCe+3hHEb86txh2TDmlNGxpVCNjIyDIYEsi9bbGgbqfcBOmcGKyYhi56GTbMg+b1nfsC1TBwR2T0/jDuSGhvQl+9k/jj/05vPRRwtkSwKmz0pTtha6PrRLmjKTH+Gkmy3LG9ZiwcfCvasBCWPwubPoDQlt4VeCuhbiKMOgoG7oFIEVNklvCpwosvvsjKlSs5//zze+373e9+h2VZnHLKKYTDYaZOncodd9zRsd+2bf773/9yySWXsN9++1FeXs55553Hz3/+844yY8aM4emnn+Z73/sev//97xk+fDh//etfPzVpo6BElkv4nEPKq+F7f0cf+AXMft1MPizLzGqcGNQORk7/ETIxjxVS9dH+RgPBQ2tRR7MT5qEBtNyGBa3GJTlb9YkXqzoQ2hohHnKQ2hxzj0Za0eeugdXv5VS+oyFAZ9wLS9+AL/86q5VZt6zAeew6mDkjdytOHJMvNGAZhWxIT5oTQj7YQI0XSZX+w7JcEVUS/1B08Lmw8WGIt5DLDwo9N98Q5UziHGLRvqCVyv1q8uiMBf1GImffhHjyJNnFRCS8beoK50A2Q63wKSDLLHm+2/iTKi86yA8bw323zgowPGDcWNe9AqEvZ07T5QK8owKEpouxshYAz/AAwUPrOu9pTeQQTTzP+kScNG7ib1fMhNF7py83bHJ261gmNEbQmAP9g3m5ZHeQ62gcjdiI1XtqJdvvgnXtIziP3wZvPda5+NSTSIlltnl9yGFnIsdehPgK9FApANpeD6//GG1alVdOZCMkBdbEarTOh37cmP2ggjqYeD9uCqFvbemuBSEY63aFBw7sj1Tm8AxVB8Zk1gJRVVj8slmAbtuSeoyFGmHldHTlu/DmHyEch/a4GU9pKwZNpnKa9TTYddn7m6mPMe28f20Bbw+L+077IbWpPbGkZhzsatz2NdIMrWs6492DAyHQr7j5yL+ISD4jt3WbeeKoo47qzOjRA4FAgNtvv53bb0/v8TVq1KhebtY9ceihh/LBB72FAz8tKJHlEj4X8HqE75xR2/F3V0h5DXLhzeiWNfDec2jTZvAGkHF7wfh9s4oN9UIgQHxjmPaXtxA8uA715mBhrvaie1TDhjCsCUF7gqD2eACJCBqHaEuMaGu8c9Lty67WqtE29IkrYPOi/H5PZw1Qvxx95FI45fa0hFlXzUIf/j/Y0FKYJSrkQBjwWeYJZNGdNJdVwthdTRyoz0n/gnbiMDC/VFfpIL7B6NBvwtaXoOUDsvlyhv+3ILuKpeMQXRfBiQmWN7WYUQeSLs6jd0POvBEJfMpiwKpqcMVH17KQigxxUoO2z+yGGKyCmvzdJYsBnf8UPc+H7F6DPr+xz7lMZXQQ6ecDHIi2ow9cDn4vOImY6CKEuYnXwrdDGZEFrXnXL+U2wUPqko46xYFY6KxHkQxkWSr6oTscCIvfIqsIYzq0xkwmhTo/Wt5JtlI9hzpIsqNoOGau+/pZ6My/Ivt8q3f/ghXYZ/0IPe5idNp/0YUzYflcaG0EBCprYcwkZMe9kL2PRoKFCXIVCg03wqtXQuv6gq5jxzkaFEDiCut7x673GR4LrY+gr2/q/f5JjtvWGPrKRjhyMBLMZAEVCPSDQXukLaGRVvTFG2D5W102pnuWJzrgxMCjUC7IIB+6Ov0CmpUMLbIFWgsLs9C4mlCnrm3EFMKgQRvxJKzKJ30vp/rEVwm+T4leRgklfApQIsslfC7gsYUTD8k8sZB+w+CoCwqRf+kGe/T2oEp8U4TW/27Ev0cV3tFlGa3MqmpI4SA/kfVhohvC2B7B6hIn6MQUJ+Lg9LTsiGRMw9LRxiu/MUS5T4rFcWjdjD7zEzjlDhPX1HX3xsXow1dAPArNkcL5k2Ji25JGRqEzDu6cK7COOAnnsV/B+2nizcWCyn4wdp8CGk8NsfzQ7xi0ah9ofh9aZoF27WCy48YNOyeowpm/RzZ/hM54BFq3GmKcrC/528YdgOx9CozZM//Fm20AGT0enf5K39NcKDA6/ViWsmp0z+NhxuMpx7EceHbOYQLFhIaboam3u7iUe2CvWnRafeGVDw3AEL8ZIn67y6JSDIKJRTNVQ8yijknP1lfyXNEfOexb+A72E/nmNyGenyuob3x5gij3eP4l06a5AXVg2Tto03qkKv2Ciex1Frro9b61FVfYFIL6MFR4odxrcjEnnu+qiZQvcTXxut3uC4V5j6KjD0IGpU7NJxU1yJSvwpSv9q2fLkJVYcYt0Laevvrjiwg6JICub+/z+7Yb/BZiC85HDZm7qEDEQRc2ZckprLDLpWldijXcgj7xXdhSQNYEEbAU7x41RBu3oE0p7imPYPX3GQ8qm4Jm5KopiHJXtMfRctvEzg91Z3G5BJfwCQp8lZAfPvlZRwklfMZgjd+p428NO4TebiAypwXv2DI8I4JYZT0IpipOY4zo0jaiS9sgYh5Wsah2WJgzN2hhT8icD1mXvA6LX8n/x6SsLA6bFsCsf8NuZ3bZHEWfvM4QZXVMDLJrE+HEx/bASmMZl6nfQpe9D/VruhMnyzaCR2f8oheZT1t9Hq6g4u0HdUeitVMgthUi6yHemmg7AL7BSNl/0Kbc3Axl0Ehk0l5w8Hmw8C3YvAINtYDHh5TVwI4HIdWFiZTlCm3aDGsXGVfeASOQAfmlYJKjTkEfurPvHRFBppyUucgxl6PtTTD7RbopCe1zKhxc3LjdnFG/OO0uGR6EfWrRGVs7x3WuGBFE9qxB2uOGJHdU2mPciiQm2DYEbEOa22P5tWWLOdZrgbcVnXErtidA5eUHEHn9QyILW1NP8HtCwDe2vPdCYZLQ55vCJw00rhBzYPG7sNvxae9lGTYJ3fVkmPV4310c42oUmD0CkTyyBYuFvn83cvQtfWt/W2Lly7B+hmvViWVBlRdtjLjnvlvlRZujsCmHsBAFlraiO1enybdswYhDkcF7pT5cFf3ftYYoFzqORBBL8R5WR+TZTebdn1xg9gneiRVIuW3uZZGE+n2eHhG5qNjHgHEZwhdKKKGEjCiR5RI+F4g7yuzF5gU6aQc/tksTtFSwqmuwho/EWb2yY5vTFCP8XhPh95rAJ1iVHqMeGnNwmmJ5v/+6IR7HnrRb2t3qxNG3bsM1KdtkvdP/blSy/cYlWJ+7Fd2yvNNS4E4K6d5IpJ2Rsmq4+K/o6/+AGU8Y10jLhp0OQw79GjJ4h/R9j0dh/qvogtdgzRxo3gSqqL8Chk5AxuwNk4/JKBQlIuCtM58e8B11NOHH/m3UbdPBsrB3nIg90BBhsT0w4RDzdw6nwQ3omoXo83+F2a91m/DpmF2RI7+OTNg/p3qk/2DY+1CY8VrhQl+WDQcchdRmjocXrx8585foERfC4hnmuHH7IbVDCmu3GGjPIFIGyIgyqPEawlwfzX5regXZrQaGBRAHQ5SzEYyu+70WeH3QFsuez9tjSIz47B6LSDGItSDajH//fvj3ryO2MkTo9c049enT70nQ2yG41IGYA6HEOCkrbJqhqiYt0doQbI116D3oW1ehweth7M7IIV9GDj4a8XdXsZZDLkZXfQD1Kwt3xwZzzUKOIWc1vu4LGBmPc2D9R2jDCqRmVOHtbyOoxmH2Pe5X3N+PNOWSujFHDKmGzXmIZcYUWuNQ1eO6iQXV28HkS9IfO++/+Wl/pIMIYoPvyP44S9rQiIOU21gDUuSC9kr+2eFy0RiIxpG9Msdll/AJwNG+e2sV0mYJeaNElkv4XCASVa64dSMAT/9uOEF/cemI76SzCN12U2qXlojibHFvgiD9B+LZO4MA2crp0LLRtfY6EI/CgufRHY9B/30ruvxJY41KTtKLJYbp83X8KWXVyJe+jR51KYRbTax5BuErVYW5L6Av3AptDb2FWMItsGwmunwmvHonutfpyCEXId7sMeFdETzrHMKPPJS5kOMQPLe3euS2gi6cjt71PUNue1pGln+E/uVyOOn7yMFn5FSfdcK5OO++XHiHHAeZeir69mPoppVIZT/Y40tIdWryLANGw4DRhbdXTOTgyiaVXjhsAGyJoMtajfBXV08Sj0CtFxlVBsODZuKcjHXO1xInYvpU7jUW5nAagljhhXJPl8N6t9O5TfCMDFJx9nBC0xqIzNzatZD51+fDe/RxwDvmu6ohyckJfIGPYW2Lw8ct0BhLvdDQ3gqzp6MfvYv+7dfIRVchh3Vam8VXBmf8AX3oOyavc76WQU1YABsSiw9RNaS91gsjynKzlosFq6bBZ4Ass25magXkvqLGBwEbbY/1zbps2bDdHsgxV6D3X+ZCv8bDftchntSpwjTahr59R8p9BUEECdjYo4KZ9QxETIrFFpdXor1+GLunu3WWUMIXCCWyXEIJBcB73CmE/nQzxIqT5qEDloXv9HMQOz0z1YUvgNh9s6CkrhlnztPw9JOwfi4ytAehDNrQ7HKb8TgM377XZrEsyCJ2o7Ew+sTPYf4rdMzSU06SE25rGofpD6ILX4czb0HqRuTcTc/4CZT/9Be0/vzqTuXujs4a4uI/8xz8x56Qc51uQhs3oX/7v4TLfIrJWVIB/bHfwpDtkRwmUrLzXsi530X/cWtBfZLjzoB/XYmG28D2oI4DT/4BTroCOeTM7BV8mhCsyamYiBjrWn9z72jUMeTLEhN/mSQQifjXPiFZV9Bjrnmkx9ivNsQlH9IiAthC8IBaPKMGEpoRBo8Xq64f3sOn4jvmRCgLon8+DiKtJnayj79DN4RhXhdV9HTVJcd1Wyt661Xo9FexrrgRSYghSnktfPXP6Kt3GJfsbM9ICwh4wGdc08USGJRsKhEX2hKDte0wLJjTgoZuXrhNvEg0HkdXLcNZuwricaSmFmv7HZGy8twqWP16aoXnPkJE0DHl8HFT4anDELC9yCk/QaoHo1N/CW99LbdD7QT5BPP7AMafBWNPS6lY3oGFL0HUZXEyVeOZ0J7lnVluJ+6jHOv15KBgv/sRJSXrEkroA0pkuYQSCoBVU4fvzK8Tue+vxRNMEEEqq/GddFbmcuvnFIEoJyaIMz+CZgdq7d6TnQobXDdoK7JDl5jweAw2zIWNC9D6ZWYCY3mgehgyYBwMmYwEKk089cM/hOUzOurJrTmFhvXovd+Er92F1A7LuafB08/GHj6C9rv+RHTGtI7t9vY7EPzaN/CfcMonNkHRdx6DaCT72LRs9JV/5USWAeSUCyEaRR+4vdOamfEAU0ZOPR9m/adzcamLgJQ++lsYODJnl3AwoQcsmYYumwFr55nczE4MvAEYtAMMmYjseAgyqEi5aevShwBkgnitRFxiF6gLRLlnfUEPxCKd7pyV3ryJck94h0fxfvl8ZNLZvZvc6Vh454Hev0MxCwFCbuRyYxjm5purOtHmOy/i/Oq7yA9/i6Dg8SO+MuSo76MTj0SnPwBL3jLlLTsxdhMx1eUeE7+dQM/zJCJQ5jHKwhLInA6oo1sONCzP87fkh/hHM4k+eh/xN1/snZJNBGuHCXhO+gqeKV9GAqmtqABsnuc6Ue5AwGPSqjVGjCJzvseLIF/5FZJQwbe22434DpNhyezMzx8BxlQgHtsQ5aEHwrjTkKrRWZvU+c/idliTiUkGsnFwEaj2mvCNXOCRzF21LKxTLs+9nyVsO6gW777L1GYJeaNElksooUAELrqc6CvPoevWFCcHqirBn9yAVV2Tvki0rTgu2ACbIyZmEEzamp6o8YK0uzifEBg0DMZMQEPNMPsRdM7j0N6QmGgnLB9ipLNV42B50HFTIOqBZTMoqDMah/Zm9NGr4et3ZbY49IBv/4Pw7X8Q8Q3r0S2bkYpKrBEjP/lV/Hcey+0l7MTh47eNAJjGYPUcdP0i465u2UjdcBgyAYZNQCwPIoKc9S105PY4998Oq5Z0pr3qCts2XgIjx2J95dvohtmJeyTF9RELfemfOZFldWIw8xH0nfugZXPvNFPhFmjZAstmoG/+HR06ETnkG8h27qmmA0igGq0YDJHNUOYDvwe8nk4mEHMgHIVQFNoimStzkyhD5yJG0AutUfBZSHn60IW8MOsf6LB9kLoe3h+Vw9Nbt2JO7wWCFND2eHeLcq4QoMoD1R5ofQ9+cUTHKNPaoTByEjL5KOTE64lvXE39E/djbV6Mx24jOMDG690MGs9N/K8jBMXkr1Uni5pt3MV43S7QrVsI33wt8def77zXehVSnMUfE7npJ0TvuQ3/T27C3q33faCxELRtyL8Pyby+0bi5xk7CY8cSsC1D4vy20e4YFIQ17VCZ55TTAgYGYUh3FWfrzO/h3HAh4KQ+/wJ4Pchhx8DIXWHo/oi/Jrff5cQS6ReLQCpEjLU72z3vs8x4bszuuSYiaNA2gpu9dlrIt29F6joFJFUVNiyANR+hGxdDqMl4XVQPQQbvCKP3RoIZ0vuVUMIXECWyXEIJBUICAcp+fgut3zwL11MAiOA95iS8hx6ZuVy41b02u0BjCqtDnRsSk8OuEK+F9vPCZpcmhAJyzFdg5TT05Zsg3NRJ+FTp8Evrep6dGCx43pC1gECowGugcVi/AGb8B/bJ3yXYHjQYBn1K8v86cWjKI1+nB2OVX/ex+d4ltZU6cUChvA72PAX2OR3xlyMHTMXa/yiY/yHO0/fDrGnQ2pyIuauA3Q7AOvZsGDfJTOZuvS+9MJg6sHx29t+1eTn6xM/MdUoiZT5m7Wxr3Xz0ge+hux6HTPkO4s/RLTVbX+rnIAOCEK9OrbTutVGPhVQE0LgDTe3QHEpRUQ5KtoVAJCEWJFDl64MLbArMuAOm3tzxVdWBN+9NXz6mxqKWDQXkd6bGA0P8iMdK/Ru3roXGDeis/xHVIB881ci6ua2Ix8PEU6oYe3RlxpR/6dDRTtJink40x5vBmlsgnCXzaf/uedDcZDZkEhlMjE3dvIHQ5efg+9YP8Z55QfcysfzdjTUSN2JyqX53XE2fIkBbDPXbZqYZVRjgN+riuWSBKLOh1mfyKr/1R+To6zt2yY67Y33vVpzbfmAs6gqgna7kNQOwrvwTMqIAz5KGNUVb5CCZQjIXR7CgbcZXq2XOZwZhRbEFrbDNOY4lPCZGT0S+eTNW/yGJphU+fgF991+weSkgiRCieMff6iQWoCdMQfY/H6kZ2vffXEJ6lFJHfWZQIssllNAHeCbtRtmNt9H2w0uN5cyNB5EInv0OJviT67OXdSMnr9cy+Vw9CRdREcRRqA1AQwRtjIKV5neNCBp3sT4a1hWQQcNhYBR95irycoFLWpsDid/QUngcub7zL9jr1Lysy586iJVb/KFgJqR+qwcBTTEpa61HX/8bvP84nPBTZMyehjBM2A17Qnql9g74g5ndtn2ZBdZ09Wz0/u8a1+J8kDwHs55G182Hs/9gVNYLhEZb4OO/wObpJBcU0qYwSopN2RZaU2Ys0JtbIN7luhTTA08VgjbicTFvtzqwcTbauBKpTqQfW/IuNGWwTCqGQCXT46Qq0hrL3e0UDOEYEUSqPNnTwiXGs0fb2Pt4HytHK+GAj7FHGw2EfIlyV4iIad9KQZjFhn7uhgE4a1bS/p1zoLUlP1X6hOdT5I5fQyCI98QurvSS+/hQVeOt0DMePhOSYnMDfUjQNiQw5hiV6nDcEDxVMzZ8xhpNucdYYMEsZC5/B23egFR2Wkhlt4Ox/vAC+uZT6IyXoLUJagYgBx2H7DUF8fpSdCYHRArwbsgHkse7LWDDl/8PZr1lMhqk8uJJVmt7QOIwaDBy+o+RiZ2ioNqyGX32Blje+dzqtqjY9W8nBvNeQBe8DIdeBrue9Ml7SpVQwieMz/CMsIQSPh3wHjyFslv+QtuPvwPhUOaV/kxIkAnv0ScS/Mn1GVWfO+Cv7u2KmiuCHij3dlhlTBcSL0VLzIp+0EaGJqwjbTFoiJh/k132WeiYMliSRzqPHki2Ha8K43nvH8mt+VckYp5oFZ7CCXNrPSydDjvkHj/7aYOIoKN2ghVz0xPmpOtqcp6ci8u2OtCyBf3X5XD81cguR+fep12noPOnpd5p2bD7Uemb3bw8QZTDhcd3qQMbl6IPfg/OvRPx5D6R1raNsOxZWPsWOPXgsfOb8JK4Jj4PDK6GDY2GLEBx03hI4h5206oMhgQuexl2/RoAOu+F7IszYceQpGTO7J5YG859fcwCxpRB0AzeXH9bkhSPmORDyj0FWZRT1pskzD0Xg9RB+o/vc/2d1TmEf/l9aMuTKPdA5A+/xN51b6zRibh7XwVYXnAyL1aYVF6RwsMGhgc7F4c8FlRb5OZygDm3i16E3b/SfXN5FTL1KzD1K2kOLABSrDQPhUGGjEP2OhnduNJoUcyfBuuXdh8D1QNgzC7I3l+GCfshVudv0Ia16AOXmneb2ZK9UY1DLI6+eAtsXQOHXVYizCV8oVEiyyV8LuCxhYtOqun4e1vDu98hVP7nBdqvv4rYW69mXAFOCctCKqoI/uR6vIdNzfkwsT1o3XaweWHubXkso4zbxeKU1jrWZTKpZR6k3Is2RWBTe8fER/r70IgDq0J5T8w7iLLfwjMi4Q7WFyQJc8DuzPOaDywbXT0b+QyTZQA56Ax0+dXpC1QmiHK+E6CkivaTv4TyWmSHfXM7bo8vwesPwvpl3e8Ly4ZABXL4eWmai6GPX2ssyn0VQtE4rFuAvvF35LCLsxcP1cOsO2Ht2wnPBV8iLrmwMSoiqAUMrIJ1jcXROejdqPt1qgOb53d+XzU7t2sTiidEtFIQ5oZo7msPwwMQtAqevIsI2hZHNoZgsDtu0iJGZEm7EkmxYNSBrtQPEHvmEZy5H/a9IlXCv/kpwdsfAEDERqvHwNb07xBVNe7TfYivF8g/h3BnD9ANH28bZfFg4Z4nWZHJZT9lecsIFgIycCRywuVwwuVoLALN9eYZEqxEylJnitBIG/rQ5YYoFyoC+t5DUNEP9u4t7FdCH1Fyw/7MoESWS/hcwOsRzjzykxWlsPoPpOyWu4i9+TLhB+8lPiMxybas3tbmLtulrj++076K75SvYNXU5t/w8N1hy5LeL0NVY9EJO3TIkPbzQ79AogsFxulVeqHMA2taO9zxtMpDrDWGpyyFanYaqCo4EG2L492vlsKkUlN2FAKWSdGT7+TOcWDDIhc68Qlj8uEwaidYNb/3ok3QyugSmxsU/feV6AV/wRq4Y9bS4gvAt/+CPnYLvPdcQg1bYNzeyCnfR+rSxHtPf9jl66Hwzj/RiVOQQekVrXX16/DBHyEeMsfYNvj6LpIlIqhtoUE/rG1CyrfBK9it+6prhfVLzF/xKDSszb0f7XHj9u+RTtdbMC65uaDag1S7cB0AGqNolRcpc+cadHPHFhvGHIIEez/PddNaWDgbXbEQQu3g98Pw7ZFxk5Aho9LWHX3o75lDGXJFPI4z+z3iiz/G3mGC2dZ/Z3TLwvQe2ZFEyrO+INn3QgizakJ0q3jQ9gb0vX/C/GeL2k7O7ySxYOhExBvovcvjg9rsGhn66h3QvKHPC436xp9hu32R/ttlL1xCCZ9DlMhyCSW4CBHBe9AReA86gvjK5cTefpX4x3OIz52FNmxFnTjiD2BtPw7PxMnYk3fHs+9BiKfwW1EmHot++GD3jWGntytyrQ/pH+yzW6aZ8AMjKmBVC0Qcoh+3oFEl0hjDE7SwfFane2LymK5/O0o87BAPOVgjAlgVRXgU+a3UCqEZoRBqdr8v2xji8cI3fo/+9QpY/lGnp4OFWUhww+IYi8FDl6Bf+j4y9tjsfSqrQr5yHXry92HreqioRar6pS2v8ZhRvXYbYqHTH0KO+0nqdhc9AnP+Tje/4KC/O7krAKoKK5vRxQ3QEDbjc8I2WOArhiEhnkhTFA3n30DYMeTLaxlxOcidPA3xu+tWvjEEoytcqSrZJ0XB9iB7dBfS0pmv4zx+N8yZbjbYXZ558Zg5D2N3Rk74GnLAl7r9Rmfxx+iKJa7007RtE/vfEx1kOVpfm1awXFWhzS0Rx6QwWgHCdtEUAnkuQZe+hr52s8kVXqxUPkkxv1x/tzrInqcV3tzmpSa/uBtQ0Jf/iJz+O3fqK8FAneKNt0xtlpA3SmS5hM8F4o6yaKUR/xk70oftQixaX2GPHI098mtFb0dqRqAj94FVM411ORVRLvfAkDJT3oWJpoiYSeGwcpyPG9EtnZOpWJsDbQ6WVxCPILYgqJkrxBWNK060c8bg2aHctfjBLh006Tfa4/lPyjy9V/I/i5Dyavj2X0xqqDf/DSvngh0xIjBuoTGMTvs9RFqQnc7IrV/BCgjmkKd40VvQtrWPHUwBJw5z/4dO+XavFCm67NkEUYaOgeP1dBfSUzUiXR2psBKq07adlkxrUwSdsd6Q5I6Nrv2ibY+kAJ5doJVXMYQ5kgh3zuWYStvkqXYTYQcNxZGAO3Gqydhl2ecypMKIUWlTA86dP4O3n+8+juIpdBUWz0N/+330hUewvv1LpL+xHjoff+RK/zrbjuPM/aDja+jfT8PoNjyjgkjPMKaI4+5YVc1Lv7EDdnGmq/r+fej0v9KtU4X0LxeEcyQqYkHVIBh/SMFN6QePGQ+HQt2vu1UWhxUz0K2rkdrhfa+vhBI+Y3D5zVNCCZ8MIlHlWzdt4Fs3bSAS/SzPQguDHPxdM4FVhdYekzALGOZOypxubSZyRkq/1OTSiSrxdodYS5xoS5xYa5x4yOlGlPEI0s/rLlHu7KBx98wHlgcGfn5czcSykZ0OwvrmH7Cufwnq6txtQDHj7cO/o8tfcbfqZdMTaayKgHgMVndPV6XNq0yMck94vYYYR6LQ0gbNrdDWDqEwhCLm37aQ2d7SCuFIN1dZ3dSOvrwSGsPd6406Hd4WRUUx3vJVIwAQrx/K03sH5AQH4+2QtU1vcc5Xs3tpgkQE/BXIOCN+p/Ubca48E6a9ZApki1NPWn1mT8f5/unomuXmsGWLoQ/eR6ngLDUxyvE1q4m++Rqtz6xP7eIdcXFxDcxzOduCrccy8e1lHvMJ2FA9GI3nqYafBTrnsQRRhm7s2O1Y/6RVOVcVcXWQ469BuixGabgJXf8huvINdNVb6OaPTY7slM2ZNFGuEOUkxIIF7j7jv/Bw9JP5lJA3SpblEkr4HECqhsDB30Wfu6H3ivjAoCGlRRD7ERFkaBBrZBnOyvwVsaXGUzyVTVUz6Yrmk2IlhgydUJz+fMLQtgZo3uRunaqwuBn120jrTXDOZCTYR/KUxJq5fVL9zQjLRtd9jIw16VVUHZh5Myn9gR0H2nN0AXXUkOVwBPw+NOygb61JHaeYjOF1KWY2JZICMm6rYffvEqc+bCIsfJM+meIqbQhlIRJlhYt6ZUQhQoAZINFWNNIKeHCuuQA2rs1/HDtxaGrA+enXsf7wOERC7ls6Q63oM98gPDsAIjhbIrS9tInyqYO6l4ttI7dNj2UU0/12t7CdJCS2DJ44DR15KGz/ZaS2b2m5dOsK9O070hdw07os0i2LRNbih3wTGT4ZbdsMi5+Fpc9D28aUndTa7WDsl2HUYUgyr3fTBgi7nwJL18/fJiJrJZTwaUPJslxCCZ8TyISjobqHe6slUOsvatoHdRTP7jUFHVuUWOVuDeSr9qzokg/QSHtx+vNJYsvK4tTrtWBjGJ2xHueWr6PNLrlOb13tTj2poNq9/g3vQ8Oi3vFcIob4FoJwBJrbwZthDDbHimddVoWYIm7kYu9WbxxGduZwlfGH0GdW0T+HVF7+Ik1X8skZnCvaNqEP3g5rlhW+4OPEoWEzzt9uTOQpd7eLeASaV+MsfJvkIlF42lZC79Z3FNGkRdRtJF2xIZHGzofU+juIMiQWYrt8AJPeasXL8NLl6Ixb0AJzIqsq+sqvM4ulJRTO+wxVM8ZiWU5kQl1NDroQ9j4D/fDv8MQ5MPf+NEQZQGHrUpj+e3j8bHTpC+aa1a9woeM9m3Jgk4tx8yWU8BlCiSyX8IlCG9ej0/+Dvn0fumzmtnFL/DyjoodCZo3P/UlWD4gl2CPKkJoC4het3hYE15B3WiQ1c8b3n0TvOAdtWF+Ubn1iiLnrwgidKXM6sHwVztUnosvm9L3yYlmVAdDuMaNLnyK9FHAfUO5B9uqfSJmUAlsixVvIEjGKzzE33b0FqobDwEmdmyYcAf4+hnlU2h15k9O2XDQPlCLUuWUd+tjdfVeudhx45UmsigojqOcirH5+80cXlWt/fy/e5S04cxsT2QqK/D72WFAXMPoS5HiNk67FK1+G/12ENizNv92NH5tPNjdlNwhzFONBkrkhk4rvzN/BLlPh2Utg3sM5CkAlrlG0Dab9Fl7/WcKzoQhw2Q3+C4+k58+2/pSQN0pu2CX0Gbr0A/SFv8HS943gyy5HIFMuQPoNS39MPIo+81t4/ymzQcS8FPqNhDN+jQwYvW06/3lDeU33HM9VfU+zkgvUUeztyom935DfcTEXlW17Va7kPBNOvkDiAA40rkf/djF84y6kakBx+ret4StzvcqUE+r2ZpzffgPr+39FxuxUeOUeH8TC2csVArEgkZJFI82wYWaRmhHUZyF71KHTNvd2x444aFMUKl0ORxAL/NUQWQP1YWSgO/mEQWGPi7r1Vbx+OPhC9IXfF1yriKBjgjAv/STfdRHAJIqwRqLvvOyeG69tw9rFBR4rWP19WAP8HQs2Goqjm8JYQxIpBP0W4hHKh/uxAwlX94+b0PXtyB4uaxx0hSVmMZcCF0LUgUgTvPoD9NDfIjVjcj907pO5i19J4kLmcy3FAtsHO34Z1q+AJe+YOiSRiUDpbLt2uFG9nnQ0RBrg+e9CpIWCB8/ad2FLkbxy+rooVkIJn1GUyHIJfYLOeQ2958rEFwdiUZj5DDrnNbj8XqR/auVEfebmBFFOvBCSZKV+NXrPJXDpA0hZTdH7XwgMQXAQu0jiQ32A7DQFff+Jzg3BIsYE92x7oD/vY7TJPXGdlMglp2Vy7HU13DhxaNmM/vun8PU73Hdl/SQwYAxFkXntKainCrEIzh8uw/rl40aVuxAM2A5Wzep7/1JBFRmQEHJrSONa6NJ9I5agQRsZV4V+3Ni7wOp22LESxcWFI3XgyJ/Bi3+FpdPRthgE7b7VLxaMPgwZvm/vfXueCvNehLUf52AJS1N9pQettKE5DYEJOVBWhGeu3+U6xUJnvw5BATcMfPE4Mmcasv14dGmKUIEUsIYH8exSjb1duRl/Sa8ZAKtLKj8Fz/AAvvqAyVzQdXxsjaIvboAD6hDXz5FAuTfxZx/GpDomjdmbP0Wn/gXx5rgguOa9/MSvpMtzM9vj0/bD5JORSScjFWahVUMtsGEBbFwC4Vaj7F07HAbvCNWDzfWIheCVn0CkueB7yDTmQOuqwo9PB7Fh0Hj36/0io5Q66jODz8EMsIRPCurE0Udu7H3DO3EjHvLcn1Mf17QRPuhClLtXCu1N8N4Tvfd9QnBamml/4J80fudithyyD5t32o7Nk3Zg0+4T2XrWybTcdD2xhfM/6W4ajNrdWOfFAp9VHEtMCoglWIPyT7mkjTG0WK5+ItnjxLoS5Z5FnTisnAUzHilG77Y5xBcElz02RCR1OhTHgbYmnAdvKrzyoROLp4atDgxOTPwaFvd2wXZ5gUlEkOFlUJsiNjfiwJp2dxe1djkTa/BOyCk/g/6jYVPYWLELdsGzoP8E2PfylHvFspFTboCK/gV3WbdGoCUDgWmLFydkw6W0UUmoE0cmxpGjByOnDUNOH24+Jw5FDuoPEyuNkFUekFAb3mNOyTrRlRov/tOHEzhlGPaY8o7nv0gihZ/dSYhFBBXw7VyNfdRgpDKNF9KWSHGe0V6XRCfVQUP1Jm43l+KhRmjdnH87SRVvofPTbT/meTX2cKz9vtlBlAEkUIGM2gPZ63TkwK8j+52D7HgYUjOk8xzMuhda1rtCZsQGeqYA6ys0XrIsl/CFRYksl1A4Vs6FpjQvHScOH72IpkqVsfCtzC8EddCPX8mrKx5bOPeYKs49pgqPSy8JDYVoueXXbDl4b1p+eS2Rl1/A2dRFaCPUTmzWB7T/8262nng0W796GrH581xpu1CICHLK9cbF1LNtLd+S5wQQAAVnbag4kzFH05Nl7WIliJLRWqAv/RmN5qiG/CmH7Ha8a3WpKhpz0ucOdRyY9gy64uOC6pfxhxQvbjlQCcMTcbfhBrbFq1AdRUanmWxuiaDrXRpj2x+B7HUBABKsQr7+Jxi5O6xr64idzJV0dpQauT9M+RWSIQe5VA6ASUcV1GWNObA8lCAcpI4TbYgWx0vGxVAVRQ1J8dkmrZ5tFizFEpPLeWgA2bkaOX4IckC/vCzl9tjxWLvta9yyU+3fuYrAV0diDTIePr3yJadAx/ms8yFHDYYxKcbn+rD7i65ey1VvHQFY9wbxe67ILs7Y0seMAB2kOZFfPfkRARxoTV+/ahzdOBP9+G502tXoa5ehr38XnfZzWPAornr9lBUhBGv+4ziv3YI67sbPl1DCpx0lN+wSCkcky+QuHkuQ4h4vxVg4EbeT4cWQJznxeoSvfbkmr2MyITpvDk3f/RbOmtVdiFWa/sbNBDQ26wO2nnocZd++grKLvrXN3J97QgZtD1//C/rstUB91vLuNVzYYfHFbdjD3YqpTEDVpIRJlTYn6ZLo5BiHFm6FOS/Bbsei7a3oR2/Asrno8nnQtMXUX1mHjJ4IY3ZCJh+EBPu2Au+Ew2x57HlaPpyH0x7GU1tF3TGHUbn3Ln2ql12OgRf/4J5wT3OWSZNl47z6MPZ51+Zf9/BJxiq6eQWuTiLFgolTYOkbOBsXwup3oLkFLIW6YNHuW7EE+gfQoJ1a8Gd9CI0rDE3EkubTD7HMs3by6cheFyJdLOUSrIJz/gDvP4G+eDvaGoI6P9iGNKdqJ3nbSKAG9rwERh+atT8aj8Ks/3Y+BxwwcZoZjks+UzdHuy9sdT0kubndQdvjEHAxhVS5B/G6SdpM7vl0v7mrIJ4OCyJDAujMrbA8e9o9QfFf9WvaLzoFGrd2W0jy7F6D76DCrfodFug963C8Fixs7tzZEEVbE278bpFmt926SSxGbX0f57bvYH37dsSbRmG92G6oKepXVVj1Aix8AML1veOl2xe5349yG5qzF8sZyXE99ym0dQtM/RlilyhEn/BJCG6VBL4KQmmkl1A4hu9oBL3iKeJORWDY+NQP06ETMt+wlg3Dd3avn3ki+sF7NFzwVYhE8nuwJEhz2+9/i7N+HRXX/OKTI8wDt4Pjr4VXEm6THg8Eg+aTvCbxOITaob0doi7EDmdzeU4DZ1OE+IYw1gCfO5OxZLqT1niXCXtyXwH1ieBMewyZMwt96wmIhM057KqmvG4ZumQWxGOoL4AceAJyzNeRusHp600BJxRm1Q23s+7O+4ltbUS8nsRPUlZdfzvlu0xg5E+/Tb8Tjizgh4AEKtHhQ2HlmoKOT0JVTaxyuvjSJJw4vPsM+pWrEE9+lg4RgUMuQh+5qg89TQWF+U+iC59KiOE5Zlt58cXwVBUGBmBFmmDWTWFojsLIMijzpCWzHUiS5MrByCFXIoMnpS4mAnucCLscDXNfRuc8j9bPA28UDdiI3YUweiqQIZNhzOEwYn/EynGasOhNaG/sJIqWdsaz2/QmkIKxyNkWbE6hsitd/k3et2tDsJ1LQnWCuRYuQUn8xByf+WIZN2hr3344fhsWZGE2VbVYg4YQvO0+Qpefi9ZvAsfBHlfRJ6LcE9YuNThtMRNLn8T8ZigwPWA3iAUeQXzuk2WxBB0SgNc/QJ+/Bzn2otQF/ZWut92lE8ZrpQs00gTv/wa2fNRlY5fnpipE3LfUim2h1X5odEkksSN1m8Lyt9E3fo8c+n/u1F1CCZ9ylMhyCQVDyqrQA06F1x+kFwtRRaZckPrAEZNh4PaweXlqN0snjux1al59cRxlxXpD+EYN9mIVSLria9fQeNF5hiinciHPEaGH7sMeNpyyCy8uuI4+o2IIVFVDv35QnrB0dl3JlC4WkPZ22LIFGhsKX3msGg2yIj8V6gSiMxvxT+2PivQ9XFQEmqKdgjbk3Z3Ow1ShJQarZqLyQed4jaeY3CS3RULoq/9B33wCOesHyMEn57RoEmtuYe4x59M8fVbH2NNo93ZaZ8/n41O/xehf/YDh308zGcyGsXvDlv9Ca2ELJB25V1MRnFSIRmDtUhiZvziM7HgoOuEwmP+aexYhv9WZf7vr86cI1q5eUJAqb+bhGHJgYQtabkM/P1rt6U5mk/D4YciuyE4nwPC9ulmT00E8ftjlaGSXo013Qi0JxXEHPF6w/Yi3MC8PXTULLA8kXTRFTA7u5hhE1BDmaq9RQPZ0XgMNO9Ce5domb5+QA5sjaH9f3xciBwQQn8uuwJ78+pT8DdZuCYK6Ko0Lse2BEdubsiPGELz3acK33YDz+hP4jhiYfVElD6iqUW/ftK4zxKIxBiva0VF98LwQG/wVECheSIt4LDRgoa8+jH7p64idYgGscjB4ghDL4q6dC5LPwg4BNQdWz8Z59jpk0Hh00Hhk0V3QliENYTHTc5XbEPFDex8Js9/qsQikMO8pdLuDkJF7963uLzK2RXq2VG2WkDdKMcsl9Any5e/AAad1F+IJlCOn/QSZdGjqY0SQ038FZTXdH8CJOuTo/0OG7phXP8JR5YJfrueCX64n3FOdN0eoKs1XX4mGQn0iykm0/uFmYosW9LmeQqDhtbDmLzByJJR1scSIgGWZT9dzHwjAsGEwdhyUFeBCLDYyem9819xiLEX5CjO1xYm3j0vEsfVx0tcWM5PqPkJVoT4CW6NmQpRP/KwTN6T53l/g3PUTNJaZmKoq88/8Ds0zZmUee4kX6/If/4aN9xUmgif9xhuLWnnCap3HsR1EeUM4L08CXVW4AJ4c/UOoHZZQrekjPGJIWyr4XHTvTQOxJPcY2dY4rGyD2U3ovCaYfAEy5WfI1OuR0+5BvvZf8iSZRAABAABJREFUrC/dgIzYJyeinLI/gQqkoh9SMQAJ1BRMlAFY93EnUe5oQKDSAz4xadnqo0bQrOtpzlcRf2MEGmJ9E/vqF+hIW+QaMrhfZ4OqInvVQSDFdbQsGL9LN7diqawi8OMbCVx2qLHUujhuRcTUuVtt9x1LW41ln9xj3jsrtSFYA7udXPzMApUeaNkKc99J3RURGLhjb1G/fKBq8lPH1GRc6PrIbt0Ci19F3/ozPPo9dMECtDmU/pwVkSyJCNTYfZvp+y2zuNW7cvTlG9FipfcroYRPEUpkuYQ+QWwP1sk/QK55Gvnab5Bv/B657jlk3xMzH9dvBPKt+5Epl8GwnYyleZdjkIvuQfbOz6rsFiIvPU902tsd7tR9hiotN/zcnbryaXbr27DijxBJCI3kMpFKWpm9XthuOxg4KM9G49B/Mp5Djybwp/8gI8ck6s3yiLEs8Afwfu9neK+8Czn6euPany8xSk5EWmPZXYNzqk5hSwTaXLBmvvsszt9+mlrsLoGmt2bS8PwbEM+9veVX/QYtYKzqiP1pXR5h5fMtrH2nFY1r1slvx/6QA+tCvdNFZYJlQ0tj3v1MQoJVyFdvh7rhfZvgeiSFhaQLtpFyfMqJZ0YI1IxA9j4LGXMgMnJfpGZEwQS5aGjZknp7kjBX2IYkr2k3CwHJMZVOIC4dBgaQAwYgo/J0p7Vs8PiRE36InOJyiExSmKzQw5MEdVKKNGuOgxxzVq/N2roBCa0oSsYDsQSGB3urdi9oQRc0g0NuoozJMTpsd+SkP5l0i0Uct6oKPnOP6+b0uYZlxy8V5qmiCjEnh4XCLt5VkThsbIP1rUbIrieKbFkUS8zCaL6x+YJRik/3vFKFtnpY8lqf+1hCCZ92lNywS3AFUtkP0liS0x4TrIL9z0b2P7s4ncoT7f+6x5A3F6zKAMTjRN99m9jypXhGb+dOnVmg9a/B5meT3/KvIDmBHDjQWIjXrcvtuGB/GLQ7ANbYiQT+8hjxl54m+ti/0IVzutefnCRX1eA54Sw8x5+F1T9BzkfvB2fdi778a1j7YW8hlN4dxkhqA00R4+7pBlri2V1Dc4UqvPscusOuyBFnpiyy7o5/IR4bjeVOfiNrN7D1udeoO/bwnI9pn7+YZd/8Ea0zVpnJvQM0xRi8dxAqvUgKN1JVNeJKzbH8iY2poc/OAlLZH87/G/rKnTDzPzmMix7wm1hJt1NCbRso1nGXbDP9A22oJ/bif9EtG5Fho/AcfgySk7dJpthqMRNvv2XG0Pp245Ld35+fW+ButcgedWZI1fjRWh+saIGGNCEBXeOdB9XBab9FErli9ZCfwOu/MvvyGUsJaKJ6BFfGlliCji6HDxs6F6MsGwYPR/Y5ovcBy56l+w90GQqyXTk6t6n79jUhs5A4qgwdHEBs6STO0kOYrv9YZPIZsN0hJlVVcXraq98dnUmH7Q6FN/8IkZY86tWCdTkAaI/B6mZ0aEVRYrYzQ8wigkc6LeIZiuLN8XkpFvrRI8j4wlTwv/Ao5Vn+zKBElksoAYhv3EB0+jT3K7Ztwk8+huc7xRfC0OY5XYiyC+jXH8IRqE9jMeqAwPbHd1fg9frwfOkkPF86CW2ox1k4B2f9Gog7SHUN1tiJyLBRKV3ypGoInPA7WP0eOvsxWPFO5wNerO4x0XVjYNJJ8MhvjDucC9CoAw0uCJ71rPfhW9BJByADR3TfHoux5bH/5UWUAbBtNj38TM5kedM//sOKb1/dObFNnNJIowNNxiKvthiXWUvMKY46+VmRU8FxoKI2e7ksEF8ZMvUKdKcj0XcfhAWJOOauIl3JMZgcL95E3Gwu1re4oh73Yj/TIprHZEUERo+CfnG0YRFUb19Ui3L02UeJ/OZq411j2xCLEbntBgLX3469x/6ZD64aAI1rM5dJkuaAbe7jLeGcLbKyZx2yW13iS+Kfci9MrEVDcagPGX2BtoReQdKiVuGFfn7E74H5f0TrbkS8Fciog9Evj4A3b4KtS3LrRAIdMcK2JFJduTRmLGBEmXF5BlAH67s3plZ2XjuNohFlEuR9aBB6kmUwHiYLWmBJK1rjNZ4DwcRiyJDByF5fg0E7IXVjuh8XqCloYSLnPouY57cqMmhU+nIeHxz4bfTlX+VWcV+JchKOwtoWdFgF4rFyz8jQVyQXpCwx2gw+7Z4RQugU3MtDpA51YNMCNNSMBPL09CihhM8QSmS5hBKA2OxZxanYcYh+9GFx6u4CjbfChkfdr3jwYGhpNoJnqSAWlA2C7b+ctgqpqcPe++C0oaIpjxGBEXsiI/Y0OY63LIH6ZRBtNyJC1UNhwHgkWAOA89bjsMalHNf5xlDmingc54k7sb9xfbfNsYam/Ilyor7I+txyhm66998sv+THKfe11cc7CWJcod392ZuMmuBeXcMnIcMnoS1bYOUH6LoF0LDGCKx5A1A7FD56BJxwfhbtSLzoIl/qKDTmKIwGxto/Hph3F6AQGICOPgaGT0G8fUtP1hPxebOI/OrHdMzeY4n44/Y2Qj/8JsEHXsAakEHdfchEWDMn99j+5JjL5ZSPKe8kyqmqCtgwNMv5UAda18AHv0P3utpoZ9SOQY+9DRY+jc66HwnXd4Qc9Fw0SRLkjpAEbxE8FRSknw9NkGW55Fpk3OTexeJhaEnvZuwaqrydHiipEFMj9JcU+xtTDgcdgUzo/j7QeBSWvoEuf6uvTibZ0RSDmgEwYZ/M5cYeCUtehZXvZre2pVuI7eoVkUuKtEiinaWNaJUPgiaeP3lkeHOUDa820bwwRDzk4CmzqJ5UxsCDKvFWFTZd11SEXBLaDTnk4s4JmxfC8D3cqeuLhFLqqM8MSmS5hBKA2IL5xpLiVrxyEqrE5s7JXq6v2PQ/cFxQ9+wJERgyFFYsT71fFfb8P8T2u992sgveAAzeyXzSYeRkWLcALKfT2tPRRzpX0bNYBzSu7sQpp4ITh+n/Q8/8PlLZaWkVb+Epiyx/dpGitrkLWX7Z1Wn3hxodnJhi5ankmzP8QRg82vVqpaIfTJyCTJzSbbtOuxslmr/rdyiOVBV5Ki+gzTkuxgwKIrv2RzxdxmxoE8z/Byx9HJ10GTLQvQlq9OF7TOhFz2egKsSixJ56GN/530l7vIzcDZ3+QN7tisdCg1b6sIeAhRzokuKzOrBpJqx5DYYfajYtnYfefx+sXIDWeJFaH1R60ApPp0dCQndQk5Nbr9Xphu0ixBK0zg++AHLpz7AOSbMI2bxmm7hTiiVohTf3BcQaDzK4M+2jxmMw62H0wwch3Axio/28RfPe0KgDIQc55mwki8ikiMCUn6JPXmHIXrrz6TidZDNJNFK9RjqyTHQ00LUxs9+TCEOIJ7wqCIPXIu63WXJfPVvfb+21ONG8KMSax+oZcFAlo84egOXN/dypYmKsiwqBLUtLZLmEzzVKZLmEEgBtbkq4cLrvIqZtaXKqulV/vA2a3qMo/lwiUFkJPl9q6/KkC5B+7lkNC4GGmqB1Hfi7TF+7TVQAUUOivWIIczrX4rbiuQgC4MTRmS8gh53escmuqsDTr5bYlq351eWxCY4dnbGIqrLsoiszl3GgflmUftt73RcLsmxk/+NT51svAjQeQz96PH8ioQrNUXRAsd2wBTaGEs+aHlaFZPhpmQcZXwNDy9L0RSHSBO9dj44+DnY8zxXXbOfjWekXCx2H+IK5mSvYfh+o6Jde6CsTBvthWerFPtm5xn2l8vn3ovUenCfugsUfJhoSaIiiqUIwBNip0hDp5PdioSKIdds/kYFD05dxI+1Rrsh1Ea3CRgb0g1H7AqD1y9AXfmk8gpLvJo1DyDK5vV2+z1TViMdNPhg54is5HSPeIBx/i3HHXvZG6kIOmUlyr450+aMnYU5ac7tYqjXqYEUdBu7so2VRO9HmHs+uxGNi4+vNtK+PsuMVQ3MmzCKgkSK/08QyHl8l5I+SZfkzg0+ZnGYJn0e0L17Bpv88S8Nr0zMqAvcFHls4fUolp0+pxFOIa5GniJN5u8hiHk3vUwyS3wFVqOvqApk4vzt/HRl7UvHazQG68n30rrNhydudit6pJmFd93nEpGhJNUwiRV6FFwuWdvc0EBGGXHSmserlg1icwRecnrFIyzvv0fbBnKweE5sWRYuiqosTRw49zf16U0C3rkffuBcaCyBrSc+DpkjfUhJlgljIkH2wfvgocuDBMCQI1T7j6jogADtUI/sOQg4bigwrz0ImEn1c/hTM+6srfZaKqgxK4TZSkTkmUSwPsu9XC2u8n8/EyvdqF5hQ7f7YDNfj3Pd9WJIIv8lG3BSY22xio4sMqR2YmShD/qn5+oJcx9aYcmTSyYjtRdfPRR/5FmxdTi+GGYoVz7I8cgrWRb/OalXuCvEGkaN+hkz5qUlvBZ3aB47TGdeb7y2mJI7tcqBqr8WH5Leq0T52uqgfvpo0fVdoXhhixUObc2tfLNQRd2Kts8Eq2d1K+HyjNMJLyAnR+gbaFyzFP2ww/pFZXuQJxNvaWfD1K9n8yP86tvlHD2en/9xGxa4TXe2f1yNcfHLhIkL2sBEm5rEIsIcOK0q9HWhbQlFVUUWgvCLxtwXectj9cmTofsVpL0fo0nfRR65MKErm8dslca4ClhGq6XposcmyE0eXzu61edCFZ7Lq13/OvR7bpmq/3SibODZjsc33/gc8NmSJiW7f6rB5cYR+27loXRaB3faB2Ep0SxRqxhTFXV8jIfShn8OHL9JxMX0C/X25p2lKip41hKHK5fy7SagD406DyBqkehmy+wB36l35HFSMhFFf6lM1nqOOJ7L449Q7nTieKcdmr2SPU2Du87B+YV5CTv/P3nnHyVWVffx77p22vWfTe08gCUkIvXdEuhSRIuCrgkhRFJUiIAgqAoIidpQmvXcIBAiQhJAKKaTXzWZ7mXbv8/5xZmZnd6fvTAI4v89nk907555z7p1zz33q71GmQkYVwac92In7F+h85CxDbEENKUK2e1PPO7ZFE29NLI2fw9tnKChJ4f3qqc7VBHqjM4Xvsb8bNWwYTDsTadyAPP9jsPyxIzyCgnQGIYveZQHUiK9hzLgk9ue2BfUboGETBAPg8kDNcCgfoHPXlYLRh8GIg2D9e8iKV2H7ch0l0dfXqoT+CRtrTWK+rpWpcBQZTDi/giV/3Ikdq7KDwI63Wxh8UiXO4iTPhdjg6Ads7OMFJIFYULQL12MeeewG5JXlPJKi8ZV3+Owbl2B3egEY+ssrGHLN95Oet/qHN1L/1Gvdjvk2bmHx0Rcw6/M3MYuzS1DTFzgmTc5NeIpp4thzWvb7jYZ3Izmn1PR4tDdj8CGwx0Uod2lux0sCadyMPHVNFwtyugjnkLlDCnMYWWLUToiWhl6HPEMHMuL2n7L2R7ckP980MAsLGP2nm5M2bX3vo6SKchibPvZROtCB00PfFWaFJq6pWAsf/SZyUKomaDK4wfujjMxztaMhT/waFr1Bt3XgF6jzwwB3aspQ+FS/DTu9SJUnq94vAdSok6B4ILxzC1k3bn32T6RmL1Rhv9TnFPDCtlXQtAVsC3PCUNSwkciGtd3L5ymFuc8hmLMOTtqnMkw48QbknxeDry2tcHhV6kCGemCDt+tgtVsrtln2LCtDIVUuvQek+j0rBfV+pDmAqnDlxjuqDKgcl7xdQRU4iyGQRumjDCBeq/v+GAtlDhhTijryF2A4kDdugWAcRTmM9gC4TMTIQtqDMlCFtTDtou5zt234/EPkwyfg84/0nHrCU4yMPwg161QYNFGni4w8GDVSr3X7/hOgs7lv84MuxukwDBXzXWOYCleZyZAjS1j/QgwWcvRtrX+3lQHHlCcYUMGY46EjGHm+c4qasbnt/6uKfBj2lwZ5ZTmPhLA6vXx21g+wvb7IsQ3X/57yw/ejZO+pcc8LNDRR9++ne9cstmyCDY3U/fdFBnw7e+GZti3UNeoXQr8KEyNN4coxbgKqtAxpycKLMRqWhWv/A7PbZxTEDoCVW4EJ0ILi4XeiSnZNvehEELGRF24OhRb3YeMPe5hdKnv1mVNBHCFy0A8vQIJB1v309vg1lw2Fo6KMyS/8g8LxoxIOY/t8+Nam7lWwA7D6rU7GHVmI4eiDgqIAU+lSP44eTGsNn8HO5bC4Epl5JSpUmztTSGsDLHgprgcLn63LFCXspMd33+iDImfW8ipFRJPslE2G1f+FYAdZN25JEFb8C6b9OHEzKwgr3kHmPQ4bFvWah3u4TdBRSnBTJ3h9qKp+OE49B+eZF8Ys8xYLqmIwnHMv8tBlWtFIR2EeWIQYRkhhVl05wrlAiTN9Nmul4NNWZO8KyAbhWE+IBf2TPxNKKaRqIrLto5ylT4sdJqFKgFo3jC3FOO5GVO1EZPETsGNFCp0DzT4odyP04T4qA1wlcODN3aJWZNNy5IlfQv36UGm5OMqitw0Wv4J88iKM2AtO/gWqQnv25fM52VGUI5OSLiNtAnoUZShq9y6k7qMOOnfEiHYTaF7ekUBZVjBwJkz/HmrlG8iyZ7J0AXHgLIDyIcnb5ZHHlxj5nOU8EsK/eTt2W0cvgbJj2aqE53nXbY5bDkc5HHSuWJu1OQL4AsLZ127h7Gu34MugLqxyufCc8c2s54KpsnLcRx6d1T67QXJU5igWXAW7bqxEWPMBbF6SVphnXCilQ3XDslou8nZ7ojC+V37wVRczdd4z9DvvVFQPpmvX4AEMv+XHTF/6CsV7JWAGD8Hu9KVtRfY22ax4rYOAV7rqMacLt4GaVYUqjuE5DitO3kaY8wtk4Z+QvnyPDUlYgTOtEV3XAQG7z7nAEq7P2uBD5v0bNr6RGxZjsWHbh4i3d9RCpMm2lchfzkee+AVsXEwshV05DZwjHHgOLMVzZD8KrrwI59kXoRzpRQGompGoi/8D4w/RB5Ltq2FlqXIwxk/+jXHH4zB8bPZK28QcUmVG1OWzYYs3K+ujx4ygdChUp5iiZNbklGdMGQpZ24OcMjxgoQmTS1F7Dcc4+feoEQcgtoUsejT1ASzRaQ82Gd5HBYX94dA7UMUDAN2PzP47cv9FsDNkKEzmVQ1/vn4RcvdZyOJXdT9z/pjBnBIgjUsUS+g3M/77Ntgeaw8JfTmjjoYDr0MZDhh5IDhyV6kCZcL449LKEc8jCrbsnp880kbes5xHQrgG1KA8bsTb3cLsScLC6x7cHwyjt2cZkKCFZ8TgbE4zKyg4+1t0/vsf4M0es2PhRf+HcuXyZbULH+FdOVYCyILH9Us6G8oydJGuWAa4wiVscvRCMQwYkVjRLZ46kTH3/YoRt/8U76r1WJ2dOMrLKJw4OmXvHoDhyWzdeZtslj/XzqBpbmrGulILgw1HFQ8tRI0p6eFRjoXQ/f38OfC3Inv/KDNG54oBXd6aWMi0HJZDwc5OKHNDoTO1skVh5Ut0CKhSCrwWNHn15W5fhjhKUa5cPUcCm2fDqFN6f/LJ88jzv446kFhhVyFGI5l9P6x6D876HaogvdQLVViOOukmZK9T9TO74u3QuCpEoBTFNdBvLGrm6boUmKkVc+N3j8E71yGti9MaN1XoMlAZnry5ExnsQTmN7JS00jOCyd9MqS9p34nMexb6KR3FkQtm6YAN7cEuMkSPqb3xFQ6oKEJN/jpq72+jXIX6pE0LoC21uu8RWAKNXihyQoEjxefM0Otm7Ckw6ZyIR1lEkJfvhvfTL18GaKXZtpDHroN37gYrdhh0n5CiUUCZiqo9C1j/YmvMz83Crr0yvD+Lz0JNugC199ld/bgKkfHHwrLnsve+jIZYqElfz36/eeTxBcMXQ/rN4wsLs6iQsf/4DSvPvRIJ6JCggVdcSNkBMxOe5+pXRc1px7LjiZe7M/EaBmZRAf3OjFM/cjfCrO1P8c+uo+26a7LQmYk5djwF512UvG0foAwXYhaBlePyVLagtu+AIVkiJcp0HgEvrJufXe9cmCF7+qmoNkFe+U/urK8CanhqpbYcpSUUT5+cvGEcGB43rqGD8G/YnPa5dhA2zvOxY0WA6jFOqkY5McPlSsLCbFjwMxUMLkQNKUQVZfBK2Thb5/JOSp9JWZVWI5MPhaWze68JM8R6nrSTHvnDRuiYAE0+xBvUSrOpugvzhqHJ0wyjd0SCCBKwQNma5Txc67TTgpwpy0Bjb4IuWfQi8lwKufDxsOVT5O/fRvY/Xt8q0wWlQ6BiNBQPSKrcqKFTUUOnIv5OqFsFdZ+Dv0Mz6FYOgQHjUUWVvc9TChk0BbViKTlh1GoLppezDF1r3mtDmwUOA+XOwvepDBg4C4YclNo0Fj4JAS80Gqia7Ef8KKUQz2DU3k4IdOj5FVZC/0mogVNh7BEoV3fOEdn0cWZGTAHaAiHSL4dOfwg9T2GPc2SNOYthxDEw8tiINzmCeU9mrij3xPZ6KHVo42m2oVRK7xdHgYGr1MDf0mPtKygdq79zCdrQGMDe2AH1AeTDP2FMOQnlLuxqPv1bmrAs0JHVy0AZMP4YVOWw7PabRx5fQOSV5TySovrUYymZOYX2pStwDx5A0Z7jUzpvzJ9uJLBjJ01vfRA55qwsY+KTf8JRvnsJouLBc+oZBD76AN8Lz2ZOhGDqMiulv/sDKpclqcLwDIb2leSU5KuhHfuvP8C44QlUcXnuxkmGutW5CWNVoA6+AFpbkJceyH7/YYigph+Ru/57oHi/GTRs2ZYyyVdPeFtsNi3wsWmBD3eFg37HzaTfaYfDZ4+A8muBsjB+bq/YAn5LK4vRhDahvGYcBjhN1GePIAP3RVUkzsMW24LNC5Btn8COz6BtO3gsGF8NTa3QGYSWgFZea1xpkDfR9fgYqrsS5bXA24F4zFAusxPldmolOY6ypZQClwOpMKGiANr8UN8OPj+Qq0gTgabu6TFSv667Rzmjbm1o2AJv/wv6F+txwgpRUX9k7Ikw4qheylNPKFcBDN5T/6SKslHkQlFOKR+310k99tfWIBQ7ENPum3dXGVBYCzN/mJpX2QrAoqf199JuI0VBKMgis7SAGjgLte916fVZ92nfvJeWaOKv9gAS3hvCdjkUjDgCdfDVMeckDZuRl+7KfOxYaAtCRQZ57YkQJvpK0RjrqXbgb+lNTFZdHMR+Zwd09LjfHS3IBy+jDu6KLlFFVXDQ5Zp4LVtQBhRUoPaPzT6eR4oQciq2xR0zj7SRV5bzSAnuoQNTLhkVhqOshD1fe4DW+UtoW7gMZ201lccchOHKIWlLH6GUouSW34JS+J57Ov0OTBNVXk753x/CMXxE1ucXEwUjQ8pybiCWDRt2Qnsz9sO/xry4j8J3X9CYwzIYjZtQgybDxFnw2byYKQR9gmHAxFmofruODKXmW6fS8Eh2CF58jUEKz/k+qmI5tDpA4ntdxBLwBuLX+BT0Z0ELvBbiMmHB3agjYgu8Ylvw2fPIkkegfUdvD5YBVBXoYwNDIaS+NAT3aHbaeCHnPgtKPKgCt/YwQ1JBOizYS7FLh5o2ZNm70xOBFsQOogwd0irP3Jw99tMWP1LiRRVGiQ3t22Dh/bDsIWTvy1GD98/OWGFUTgRHAQSzlxoDOh/X3hz6LlLxLofvYfhWKjTTMOh14TLBqTIIyVZQMggO/TXKU57aKVuWgjcqRLjeCwMKEQd9VpgjOfaTL0q/r5YtfRq7GyzpXRu+oym+Ue6lu7LP+GyjldFMomUSwUo9/F/1zNlXUDXMxBlvb1MKWfAWRCnLAIw9ErYuheXPpj/fXmMYYDhQx96U1ECWRx5fFeQJvvLIOUpm7MGAi8+k+utHfKEV5TCUw0HJr++g5ObbobBQKznJYGqCC9eRx1D57Ks4xuzCUgql08mMqSY1KNNAFm/SyuP8V5ENcWqx7gr0FKCyCVsLv8aJ382+ogxg2xhf/7/s95sAJYfsi2f86Mj6zBimiWfscIprg/D5Cwm9++KztCc1nqIcC34LNizFXvFC7/5atiAvXI588AetKENsD1b4mFLgNLRymipBVLJHXAEDy6DUExoivedNhWqsquriXD6qGuH7sH4hbFme3VzFhljeWAF/G7x7EzLvLm3YyBKU6YYhR4dynLMDEdElkTZ3dCktiQwKPRXlyPGoz/wW4gt29Z/MQKFCz+O4k+Goe1AFValfwPYV3e+HLbCtQ9cv7oNhJMLavq0DGrem30GuyxNZMZihAWnaBp/Nyc34Xjt7xqYw0tgXbX90CTcoLDcYtleCyBQR8PY2yCmlUAf9ECaekM5Me0OZYLpQJ/wWVZsiEV0e8REuHbWrf/JIG3ll+UsA3+Zt1D/+Es3vztO1A/PIOZRSeE45naqXZlP4vctQlVHCjMOhf8JKtGHgOvxwyv5yL6XX/xTlspBchArHm6ujGEqmkIvHWSwb2dQIO0M50YaJPfuxrI/Ta9x4AmdULlbWEbKSqzHTUEecnVUBHaVQR52DGj01e32mNKxi5F9+0/cXpG0xfEYTPPdzsLxxm4k3CN7YQm1SCPDu75G1b3cdalyLPHcJ1KcZOREm2ypwaMU5lfaJFOsBpeBx9Mlz1y3XOWcKs4JQ/WqZ/0TW2f3ptBB/rL0tTNj2Mnx4R3b3v5FfByN7RlalFLK0MUpRjvowWpiMfmZiKspoxSfcLmBrb3PA7tZeRLqfbrph1LFwzH2oad9BpclWLPVr6LWALIEt7dAWiIyZcn/htm0B2NKhPar1a9KaEwBOT/rnpAwFrjh7/8IXsxsqHQ0hu2UFhZj1leOhY3sw8lqvGGQy/hAPZiLSQsNE1cSOAFSGiTr4StRhP9HlnlQGe0PtBNQZf0MNTCOVIo88vgLIh2F/gSEibLjhTjb++r6Ip6tg/CgmvfB3PGmGRH/VYRqKEw8qjvyeLRg1NRRd8kMKv3sp1prVBJctxdqyGSwLo0RwVjRhBDdDyzpYcQcSLjHp8CBVY1BD94Exx6A8ZVmbU0zUHAtty0HSzMNLAfJ6lCfZtuCT2XDuddkdo2UTrH8L6j+FhlXaUwWIqxgqR0PVBBh+KNSMzuq4ESgTqrqIStSpP0BWfgybVvXdY2GYMGQs6uTdk99VNH0Phvz6GjZe/auM+xh8cDFFtQ4ocsRlxxaflV7oc0wI8tavoLAaSgYgL/4I/O2Z5amHWbLdpva+JRNSQwTN2NLdUFJeAAXO7DIOJ2Lw7gsKB6CUZmhmzbzceNs6gxA3Qkhg/RtQOQrG9WblzgTKU4VM+g4svrvPfYktOmz58x616cNe4vBXHP5uEuWWFpmhVALRofv9RkFJDfhaAYUUlqMKSvTeX1Sl6wFXjILSYRHG74zg74j9PAiw04e0B6HcpcmyehJkRS4v6rjPQpr8OjcftDEnkEHYe/UYaN2e2bOaDEqhqkbG/Eg2LM6ttyxogztLhtMUc5VFBF+zjavaSfmUIvodUYZrZTPs7J2/3L1/C3XQyXE/VkrB+GNh8HRk/r9hxStgBUIM4zH2inC6S9lg1LQzYcJxmVUtyCM28jnLXxrkleUvMBqef5ONt3Sv9de5ah0rz7uKPd/KEuvjVwQup+KHZ/ZmVM0WlGniGDMOx5hxSNMG5P27Ydsn0BCH/TPohe1LkO1LYcE/kDHHoGZehHIV52Z+jlKk9kTY9t+s9SkiyPufw84egmV7E9K0A1Xed2ZsaVgFn/wVti/qKgkSvZv7W/V93r5I50XW7KE9GIH43s30oaBmJMrRpQAodwHGj+7D/u3/wcZVmQuAyoDBYzCuug/l3n11qvtfegHYNhuv+bUWhlMJZzdNsC0GH1xM7bSQ16jIEdMrqnOUM/Qo90TQQp75OZSUga+FPr3dw0qpx6HJg5K1ddA9TNJpQFVh1kvzAFrByibrujKgIpT+0bwNfG2J22eKkEFELDukLEaFqhpKs38v/BsMnIUqGZSdMQcfpsnLNryUcRdiC3QGkbn1CRql0WGRgwgz3ISvoQ6+fNfUmzXMxMYWrwXbOhGnoefoMhF3FGO7LbpWtN/SinWgx94mZOR1VDXjkLXvpn1eShAbauKkNm1eTk41gExrtfeEpGCwC0EphWdUIXveVtF1ulGKvJdg7RomjJ0KY6cl77+4H+qQq5B9/w8+n41sWw7bl0Nbnb7XDjdUjYJ+41FDZ8LAqbnZA/PI40uCvLL8BUbdf57SgocV9TKzLFrenY9v01bcgwfEPzmPrENEYOnjyIK/RYXqJVM6ROfCrnwR2fA+HPQT1KDpOZmfKt0L8ddBw+w+9yUisHwrfLQ2doOdW6APyrLYQVj6H1j2aFQpongKaVeoo6pfhngsCGbXM6em9M7lUsXlGD/9B/ajv4O3nwgp8ykqzeG2B5+C8Y0rUZ4cho+niP6XXUjxvjNYe/GP8a5co8sexWLJDh33jB7O8P39FJVFeZmccVh/vUkU0VTQFoR6ny7JU9IBw7Ok7IVLQ7nN5J7vsMJsifY0l+fIwBG5h9kM8bShei/9e2ua9W7Tgc9CWnwJci8tzWj87JVw1M2omjF9HlIphUz+ji5btfYZutOXJ4cAtAaQt7d3eVD7gjInymVAQRnq0KtQIw/se5+porQ/kdJmiRCwoSmJJzIWxNJjpIuRB8KHf0n/vFTgLISBvZVAsS3ozEE95Ghk06CVqs1VAaXdow9UtRtmVCALGoGod5GhjZqM3hPjh3empdQqdzFM/Bpq4hevlGceeXyRkFeWv8Cwvb64G7Xdmf1w2y8zRITmNv3yKCs2sm4FFRFk7t3w2XMZdmBDZyPy6jVw8DWokYdmdX4RVB0Nygk7XyNdgRLoCrFdtAl5MwGRV1+IZCw/zLkRti7A2xBALMFT5YgZ2htjglDshNYsKGdhOD0w6eiYHylPIeZ51yIzjsR+8g+wdlmXcBIL4c9GTMQ45QeoibOyN88soHjmFCZ//DItb7zLjgcep+39+QS21kU+dw6spWS/GVSfexqlh+2P3HIMdEaHZMYIv7YlPTKvngjasMULLVGe6WoXadfATYQw6VcqYeJhr51haPbrnOVDSnbDsZ0l0D+03nLJmWCl+H03b0ce+w4y/ZuoGef1LfQYdPjnxG8j1VN1SLavkeR7nKE/H3g48tKjmrApG5g6DXXgmTDqoJSuS7asRD54AjYuBZcHNfkwmHECqiD9EoqqdnxWSdRiojZ9gkpVPgQZNA22LEq8/sIeViuU222gnQKGiv28K0OH/+Y0JzrHEIF0vrJqD8rsHe6sBhfDhH2hfTjyyTvg64T+wzAOPQ0m74tKhYw0jy8OdgfhVp7gKyPkleUvMCqPO5TGl2Z3P2gYeIYPxjN6WMxz/lfh9Qun/GQzAC/8fjAF7iwrywv+kbmi3NULiCCzbwF3CWrQjKzMLRpKKag6HCkYqUOyA426nEkSRTRC8uINYL+6DD5P4pkqySzkXUTgvVtpfOtdVj2wk9Z12vPh6edg9JkV1O6TPExdOQ2k1Knr6WYB6sgrUO4kNWIn7YM5aR9k/WfIhy8ha5bA+k+1sALgLoBhE1EjJ6P2ORY1NLVa5LsDyjAoO/Igyo48CACrtQ27w4tR6MEs6X7/ZcRe3ZlmLZteRHL+PgjuPgvWdvQIfVbaIJILOI3eYaexIOg85SzyH/RC2OOdFdlFwYgTUCFyLwrLs9FpbKR1TwQWPIhs/xSOuyVtMqtYUP32Qg79M2yZA+tegJY4ZFSOIvD0g8YNqM9fgoku5IM+3mwFTJ2Ace4dKGdJSqfIe48iz9/RzcgmG5fB2/+G7/wJ1S/NEoMDJ5OJITRlFJRBxeCMTlV7fxt56gfxG4jo/SJ66jaak8UIGbR6KswON2rKN2KPZ5hI1tNyeg7Sxz0g/G5N1aBY5OjlVe7qy0btdR6qajyctGsrK+SRx/8y8sryFxi1F5xG/VOv0vzGeyiHA7FtDLeLMX+7LZ8/sgsh25bA4oey2+fbv4ZT/4FypyZwpQtVOAIZfgXseB8+fxyqtRIklt1dSDdCYbUtXmThBli6GXxJck9dBVCTmTDF5y/SMmc2C3+1tZvzwVsXZOndO0ApamelULuxzAWdVmqKTzwoA0bvD5OPTf2UYeNRw7oUYbGCmnxmV+Qq5ghmSXEvJTkMdeA3kU+72KlpDyIes/v+E8zwOwjYvRVlgMJcvZZC+bSBFFlVXI4M6uamO6UsKD3KgKJBMOLErmOVQ8DhgmAGYbjJkGo5rggENn+MvHYTHHNTVu6nLil1BAw5Agl2QPNa6Kwjsq9teAe2fgRtLREvp+rnQcaWwsoMw3YVUFmI2rcCVtyGjLkc5a5OeIqsX6IVZegejSICnc3IAz+CKx9LyyOoSmqQkfvA2g+zH0GgDJhycsYkTqr/ZGTK6bDocWKu656KcjTCJHw92J7VAT9AFSdI+RkwFjYszmi+KcHZh/UaYUpP8RkvNKG2IM4zomD0iVpRzuOrgTzB15cGeWX5CwzD5WLyC3+j4cXZtLw7D2dtNf3OPhFX/74TK+WRGsQKIO/8Or181eS9gq8F+ejPqAN/lKU+e0MZLqg9BPtP9yL+xVBbiqotgYIQkZUvgNS1IttboK41tU4NE8bPzCjcSzp2wMf3s+7ppl48XmF8/mgDNXt5UOHPFSHSoO65skoppF8B1HVmqDArGDYd9fUb+lYOyPxqb6Fq6B5w+i+Rp34FAR90xvjS0iiFEoGIDr2O5W3xGFpwzrZXVwHFFeByQEuojmyikPqiXVQTvk/6stJkTFMu7/IqE/K4DZoMGz7JvkKVifIgAmvfhRUvazbeRE1bt8GOFUj9as2KrwxUQaUmeKoZh/J0D11WjkKomgRMQrZ8CPN+B8FQrdnoazcN1JETkNJNMH9z+ve9pgh1ymSU24BAM6y6Exl9BbQ2QP1qzVJtOqF8CPQbi3IVIe8/Gn+N2Tbs3ASrP4Kx+6QxEVB7fQNZMzetc1Lr2EDt2bdavGrvi5Dtn8H2Zd3vv51CFIVla2NMeE8efyyMOybxOUMmw6Zluavz7OpjaHNAUstVrnJDuSv2+0gZUDoMJp3bt7nkkUceGeGrLel9BaBMk6oTDqfqhMN391T+N7H+XWjbnv1+xYbVryLTv40qzB2LN4A69AzkoVtgZxuyvI+d2RbGIbFD4pJi5bNgB2hY0hlXeOjcFsS/zY+7vLenVkwFLhPl0MKLMhVSWwCNfs10HC5zkQjKBAT2PQ+137l9zqP8X4CachSM2x+WvglNm6DpBVJnqomD1qD+iQVHbvPu1PkPQ90qqPsMqVsJbTugaQXYneB2auZsf7Ar6iKX6JOVP6Qo73UNqrR3KK+afhKy/uO+DNAbJhl4lrsgc+6GkQehXN2jR8QKwprZyNInoe4zfdAwCefIi9h6z1QGMvwA1OSTUQOndO9j/Rsw747wX70Hr6lBOR2oA0cgQ8qRV1eG9o3YzSEyPGrWUNh7cFQeqY34G+H9q2D5ulCj6PxzhQydCZ8vSqzEGSayYQkqXWV52Axk3GGwcnZWjSFq/4tQJf361ofDBcf/Gnnp57Dlk64PUiHKEojc9AnHow66IukzqKYcg7yX3civbghHuqQTQaMMKKyEcUfDkmehtTl2OwModUGZCxWnHryIQNCBOvAWlONLnLedRx5fYuSV5TzySABZ/nSWvcrdeoeVL8LUc3LQdxfUPscjL/0Nmnb07ToME4aMgwnpCXYQIvVa/aLOuXIo8MUXnIx4u5IVKv3iUOBxoJTSOaVVbqS0CNxjYd1HXZ2IjVYo0AKrYcK4w1D7nI3q13eG3v8lKE8RzNAeJ/moDTa+kwITfALUJwgPziUBiVI6xLR2HNSO6yqru+rfsPlVxOeDLU1aWS7cBYYUBUgmrmUD3OUw7SpUxYTYTcYfDMXV0Jag3Ey6KDD7lsMZ8MLK12DySZFDsnMN8uYt0LCGbvWtYymZYsO695C17yCjDkHt/0NUQRmy5YOQohznPhYXQ1EXI70aXgHfngmr6pEl22Bba+8IiXIPanw/2KMWVdw711opoKIIqSmDHc091q3Axvng7Uh8P0Qyjk5Rh1+JbFwInc19fz+Fn4kZZ/Stn3B3rkI44bew6L/IR38LRQmlOEdXIergK2H0YSkZq9SAscigibDls+y/pwvMrggXp6HXSFylP/Qce0phz5NR089CuQqR6Wcj930dqh2hKCgdKYXbAGd8MtJICsg2L7KyHnV4K7jLsnt9eexe2GSXbT3VMfNIG3llOY884kD8bVC3LIcDCLL+PVSulWV3Acb5v8T+/Xf70gsohfHtmzJj3Kz/FALtANTuW8SWN1t7yTWOYoOaaR6cJSGvcrx3SFB0aZrCLgIm5QzCwefAsT+BTYuR7SuhI8SWW1KNqh0PQ/ZEFVbE6TSPlDHxHNj0bpeynK6u57ehI4GiHZRYpNvZQVGcFJayMcia52DDzi7hxbJzn7MM0G8m1C0ICfrJbmSI3XnIETD+PJQjfmkr6WwFO4teeofqe0gqIMtfQIWUZVn5KjL7N0SuOxVlJ7zu1ryDbF6IHPEL1PzfkfDeVVbQk11dOQyY0A81oZ9mdG/q1IRzpiaYU2EPuiM+H4GIwLB+Wlnu9aGtUwraE6x1sWHcfgkuNj5UQRmcfifyyCXg78zceKVMKB+EOvl2VFxLZQbdGiZMOwtGHoQseRKWPQ+BJMaD0v6os+5Pf5+edTo8+cvMJxsLCiiJuh9K6WdAQuHk4X1CRBsbBk9F7XU2DJ7WLWJJPn4N+bwFtjtQo4tRlS693hQx95ZIRYr2IPbnbbDTD4aBvPsk6qTLsnuNeeSRR0rIK8t55BEPO1fnfozGtYht5ZwgSo3fG/WNHyH//W0mZ2tF+aJbUf3TZG4No2EVWtC3GX5iOTvmdeBvtSgd7mLgIcVUTvbgqeixHUULJT2trwJ0BJAipxY4lAENq1H994KJR6ImHpnZPLMJEQhsB+9q/X9wJ0gAMMAoAld/cA0CzxgwdlF+bBagigcge14In9ynD5gqvdJRiRRl0MRtuVBQlQk1sclxpHQCbGrsvs58u8i7POHbMOl7sOkN2PwWtG8hpuJXUAuDDoYhR6I8VTG7kpZN8PmLyJZ5sORTHeruUDp8ui/3VAHFjix8LwI71+hIk89nI2/9ug9d2eBrhRd/ipQ6dYZFLBQWgDOxqKMU4LChow3avNDQ05Jn6n7KSqHQE7kPSilwu5DyYmiKURe82BFfWVYGjJqOGjgu8XUmmnf1SDjrPuSZn0HjRjKK6x88FXXCL7XynQOoskGoA36AzLoIef7aUPRP7Hmqw65KW1G23/4v8tjtmhzLFVsBzQilztgpIUp1cWlEH556GmrY3r2ayzv/1ee0BZFPmpBCE9XfA2VOpMQZSSsSW/Tz2hLA3u7tXu3BtpF3n0BO+F7C1CGxg9C0HnaugratYAV0bfKywVA5FkoHfanJKL9yyBN8fWmQV5bz+ErANBRH71MU+T0raFxPH9l3ksMOQutW/TLLMYzDz8Z2FyIP36rJZVIhRDFMcBdgfPtm1J4HZT548/rIrXRXmux9fT8sCwqqndiWYMTKgwwLJQqtkIXZUsMQwGtBQWgba1qb+fyyDd8GaH1fK8i91pANdit428C7ClrehcLJUDzzy6M0j/oaNK6C9W9ogTKYhlfLm6Rth9XLC5gViIXqPyX2Z/P/1Tsn0R/MvVfZUQSeGj3OqFNg1ClI0Aut68HfAgg4i6FkOMpZGLcb6diBzP0tbFmol1qzvysnPBhiynOQ2X1VaMWhD7nK3SdrIWvfhdm3Z6GvUK3eFgspd8f+voqL41+3CLS0QV19qCxaHAQt3a6lDVxO6F+jlWdCSk5NWWxl2WHomuE7/aFQ5JBhz7Zg2J6os29J73J9bdC6TV93QTkU1aCqhsG5/0Dm/gPmPxy6J4neWaH9yFmAOuRS2OOEXVJdQzkL4IRfIS9cD2ve0+8WgfDeqA69AjUivRQf+82HkCd+p/9oD4IyEWcWFOYypybcCtipExjW9DZ6iAhsXdv9++iwkDXtXW3C77hkQRWdbdDSABW1vcdp2Qwrn4dVL3V575XZlUcfjjpwlyHjToCxx6EKEzO555FHHl3IK8t5fCXgcip+cm5sb0vGCHp7kLbkCIHO3PYfBeOAk5Cxe2E/fBssnxsSWHoIV9F5g9OPwPjGj1Clfby3wU4ddi4CARtXedfWE1NRjkZY8DHQ1vyg3aV7Bm3EsrVXyfL1bY7ZgB2A1jnQ+WnUwXjrJ3IR0LFIe6DLjwTXwBxPsu9QykBmXA7KAWteTq4ARyNZjpYl0BSAcmd2FWZ3CQzbv9dhadkCy57u3b4zGFpbOSIcUwYMPKSXYK8cHqhIzdso7TuQuffCmjldz7AI1PWoOxsUfTwcRprsvobbOJX2jmabmfyjv5LVWHsbTdZVHMPY5HHHvl7Lgi110J4kNLgn/AHYsAUqyqBfFcpQSGl8QwZuE/p7ukrdDd8XdcC3YNiUlJQ6aatDlj8PK1/XhtVouIqRoTNRk05EHfAdmP4NWPICsvxlaNhAr73HMDVT9x4nwIQjtAK7C6Ecbvj6rbD9U+Sz18HXhqoYAhOPRRWnp7zJmsVdinIYjQEoNqGoD2Xfyl1Q4w7N14EELPAl0GSVATVjY5e3Cvq1QTwR0vEudrZ1U5Yl6EM++DOy4ElwOzAKo/YqiVGmy9cMSx6CJQ8jU8+DSafnPc27EyK5ly9jjZlH2sgry3nkEQ+76iWyi19Wqt9QzB/ei2zfgHz0IrJ2KWxeBQE/uAtg6HjUyD1Rex+HqugbM2oEhkO/ty3p8rCkPfGQoO8wuhRmy4YGL2IJ1L2JtCvUjHNQ1RmGi/cFth8an4VAXQYnC9jt0PA0lB8DnpHZnl3WoZQJM34I/fdCZt8KvhSNFal89/U+rSxnDQo16bSYIYyy/Ln4JH4tXqQ8Xt3TPkJsGHJUZqdafmT+A/DJw/SSiDut2F4qi646tqbENgSGr9NGSwfFZvYVZYX2jmYbPhsp6GHcUAqcMdZR0IINm7XimykamyEQgEH9UR4XYhp6P3IZ4Iq6b7bo+sJGyKvs7kANn5q0e7ECyIL/wMf/CR2I8aX62+Dzd5DVb8GgvVCHXo2adQ5q1jlIoBN2rNGh6igorIDqEbu9AoBSCvpPRPWf2Kd+7Lce7F2Wy2dDm4WU2lDlREhDYTYV1HpQxT3uj8PQ311nHIOg2Kg9TonTp5M+Rac5FXiMCFO2PHkdHPYd1MSDsTcuwX/L97A+2xF53o1+bpx7l2PWJmDNDq+jhX+H9XOQw25EFWbZ0ZBHHl8x5JXlPL4SEBG8fv1C8riyVPKluDb77Joxx8mSQpomVO1Q1Al9If1KA0W1WlDPpCZvNKIV5s5Ad4u/bcFnbyArZ8Npd6IG7tG3sdKB2ND4QkhRzvQaQ+c1vQyVJ2XdwyyBTmhYC/52QGnW1srhKLNvod9q8IHIiaPhqYtTi5JIhSTKa2vG7GpX373LyoCyobBHnJJnq9+M/5y3+KDUgxhZzIUEwIABB6KKBqV9pjRtQF6+Fpo3xm6QiFAKtJc5CCjR0RrR12XbXYq2oSATMr9kUOG40xx4OLwWFEXN2YxhiBSBTVv6piiH0dYBW+ugqhyGlkDImyk9jBCRYx1BaF6FNG1ClcdPvRFfK/L81VC3gqT3KRxiu2UR8ugFcNyvUQP31F7jgZP6dn1fUEhzPSzs8dyK6JrGAC1BHZY9wAOFRuL3jlNBuRtKo0jdoqCUQgzAY/aOoFEGFFXDyINjdq0MA4rLoa0xvQsEcBuoIrP7Wqpbizz8E2S/s/D+6a9Ii7/b8rB3+PC9sB33MbWYA1MoM9W4Bl76IXLsXXmFOY88EiCvLOfxlYDXLxx/xSYAXvj9YArcWRBsq8f2vY9kKK5FuYpzP85uhrgr0strTYSwwuxygK9HCSKxwBbklVvg/IcyUnBk81pk6TxY8ymyc5sWgEvKYMQE1LgpMG5q7347FkNgSx8uqgeaXoPqs8HomxdImjcjy56Dde9CcwziKGUiFcNQow+FCcdlXPPbKBmAHP5L5JWfJjcwFaQYSbHdC0VmH8sVGWC6UIf8LLZX2dsM7Tvin24L1LejaksyHD/etDww8Gtph4pKw1rk2ctDBo848Ie8m25D/x/WSwO2Ni6FDUyC9jbHU8b8OTIUqhzyQPgsKEryzOxsAm+C0mXpwFAQ9MHOHTqoPJr4qweUUkihA1XkhHnXIXv/AlXWO4JEgn7kuR9D/SrSuk9iQdCHPP9jOPkPqJpd8P7aTZDFb/feZ3oqxKZCjSvVUm5AtKIbCEUkKXR4vNsEZ3LjugoxYYtTQuWfwhOxUYddo2tLxzt31vHIWw+nxhESOQmt5NNjLYWuWd57GOkM9F4eob/97+/Ec+rA5HuLWNCxE16/Bjn+3t0edfA/hzzB15cGeWU5jzzioagfFFRCZ0Nu+lcmDJiWm76/aFgzO7v9qRDDr8vUIY7REBuaNsG25TAgdc+KLHgH+8m/wacLAKW9UpbONxPDhDkvIWJD/6GoE85FHXWarpFqtULr3OxdWzgku30elGRWVkZatyFz7oL1H8QPMQYtLDWsQeathXn/RMYdhdrveyh3+sqhGjQdDr0WeetmfQ3xxiwwdChwMgZtAdZ1wPDCjBRmEYVyuVFH34aqjBPW3hTHOxuNjgDS7IXSOARSac0plIbw8Tp440woLEOmHo2adSqq3/DE53Y2I8//SCvK8e6tEhjo0TVhY+WmKaWVipYANAe6hWvbnRbWDj9WSxDpCIVyuw2MKidmjQtzaAGqr6WjVA481dEQukrvgPaUR8MfgPos7edOAzzpiVDh9SP+BtS7VyHjzoZRp3VbVzL/n7BjJRlJtWKDHUReuwm+8beEStyXGm0NvUOwezp9x5WCQ+m14EYrxn2AiGjjUzRnxp6noQZNTXieOuA05I3/pDdY0udMMGtcWJtjp75IcxDZ6UdV964P3ruxpRm0lzwEU89Lb5555PE/ghy/ufLI48sLpRRqwtdzJ+CJhRp3XG76/gJBGtflrl61J4EA1JbAYxgFaW3C+t2PsX/1fVixMHw0oigDWigLKyjbNyJ/uRn7J2chGz+HjmVk31wr0LFUE4alc5YIsvx55JHzYcO80MFUateGGFNXvII8dC6y/oP0pwyoEQehjv+9TmGIR+CkFFSmKMRbAmvaQ2zCqZGhSIhAzO+vQJ34Z1S/BLmRwRQ9jA0dOiQbeoXYpoyworx4BzSHhNyOZvjgCeT3Z2A/8xvEF59sSt67C7zN8b9PE+3pdITuu1K9f0DnZpY7YUghFJrY7RbexS14P2omsLYTe2cA6bQRn420BLHWdeL/qJnOp7bhX9CMBPricRbi13jKEqJZzW0bglHPcVNLdsZwm1Dg7H5f04DSNfFgxX9g3u1IaB1K4wZY+Ah92k/EhubNsPixzPv4MiL6uXQZMNDTZTTJAiIGjXA5qdGHofZNnsak+g2B8bMSpjTYfhvba0X2rqSSuZDUcCXJSvT17HDxQ0jzhjTOyaPPCL/TdvVPHmkjryznkUcijD02N8qyMqByFNRMyH7fuxkd8z9h/bmXsHzsLD7b6zDaH74VSeMedrZZLHirlTnPNbN2uTe+cqIUmEb8kjalA5KOJfVbsa8+E+a+qg/09ETFPCk0n3UrsX98BvLJy+QktkkCurRUqs1FkLl/Rt7+nQ4NlQzC3sUGbzPy4jXIsmfTPx9QtZNQp/wNNf0C8JSHDpp0U56rPV1KXdI5AVu98Hm79oZGsz6HGNbtoETWSdsGPyv/vpMmx8mo0iR5344UPC9hNHQgO9q09zIdgSMsoFg2LN0BjT28QWHv2IdPInedjTRs7t3Fhg/h89mxFWWFVpQhdeVNKUQJgZ0BvAuasRsTMPaGL9WC4Mp2Op+vw9qRQRizMiBBnm7W0POr8fq6voNsKMtOA9xZDMrb8T7ywNewn/gZMvcvWWKAF2TJk0g6ob/p9G7bmRuNsoGSqt57dfR9G1yQVbL1bnAasMepqMN/ljKTtHH6j8Hp6SVLBFuCtC9ppW1BC20LW2ld0IJvoxfpWcauJxSIN3EbVZTmGlUKPnsuvXPyyON/BPkw7Dz+5yC+dtiyEjZ/hnQ0gwiqqBwGjYeBY1HuokhbVVgFe52PzP9rlichqP2v2CX1LXclmp99mfXnXQqmwjBs7IZ6jKYAqjAFshFg9eJOHrunnmBQdGqyDUPHujnrihpcnhgKt4gWXqwooVAZUDkM+iXO2ZP2FuxrL4AdW9PLJwvD1jlw9j1PYfzoZNSQGKVD+gQF/i1QmBprrMz7Byx6NAvjaiFY3vk9ODyocekzNiuHG6Z+E/Y8AzYvQHZ8CvUrobNJC2VF/WCIB155PPVOOy3Y2KkV58JQLrPToG2HReumIO0b/bSu8dG5NYhyORn17LHJ+6wYlt6Ftfk1sVxFIRJVpijWcxzJRxbR53gDmnQoHsSG5jrkTxfDJX9Hlffv+mjRf2OH0yu6TN5p7iWBT1oJLkpTeRSg08b3Rj3uQ6swa1M0NihD1wXuPxnatu3avLn2digu0kpzKsawRDBU2qHXKaGfBz6fCw7JHvt4RwNsWwIDp2anP6Bl0zZe+sFNrHjuLRxuF9MuOo0jfv0jnAVd+7uIQNt6aP0c2jZAsB0wwF0BJSOgdAzK051MKt3cfTXlEOTRX3fft6P0VlWVm/BzpZR+5vY8Oa2SS6r/CIzv341976WhclI2weYgHct71OYOCr5NXiyvReHeZQnvS1yDlQJV4URVppl/LDasfhnZ69u7vKRYHnl80ZFXlvP4n4GsX4zMfQyWvKFfskpFQgJFLC3UGiYy+TDUvqejhk/RJ04+Hda+Aw2fZ+at6wUFe56Bqhmfhb52DeydOwi++RLWp0uwVyxF2tvA6cIYNhJz/B449j0Y5fERfPx6Rn+7EnelIxICJ8qGnd5Q6KIjrifY22Hz2L31BEOMpmHHxcbVPt56spmjz66IPTnTIJKwpkxwulHHXKsJdWxLh67aQXB6UO7Srmv6++2wY0vfBOiQx9D+++sYP/sGypnNEFOBQGoldmTTx7Dg31kcO9Tv7N9C/0mosvRZmwGU4YAhs1BDZsXuv3wc8uiv0us0KJrttiXIlk98rJ3To6awgkE/PB9nZXny+bmLkZL+6ZUysjTpFw0duq6v24G4HV3hmQIELE1oZ9n6d0JKhC/J/mFb0NGEPPwL+L/7UYaBNG+CLQtjt89QUQ5+3p6+otxtnuB7uwHP8f0wipKseWVoo8vXfoOsnZN7RbmnTa2tHaotrSz3FblQlMMYXAh1adZ8TgRlQN3KrCnLdjDIvw47l6a1mxDLItDRybx7HsTb2MLJD9yOWF7Y8hZsegW8ofJ5yuzayJWKvD+lcAhIAbRsgfZtIBZiOKFkCFSOh0H7Q03sOtRiB2H7chg4BDat6/og+r1S5sytIbphFZSmtyeq0dMwfvRP7PuvgvrNeNfHrxwQrA9gNRg4qtDh2z2MuarGgyptRxp7kHwpwFC4DqjK7PotH9R/9r/DpbK7kSf4+tIgryzn0Qu210fngk+wvV5cI4fjHpGm9+ULBmlvQp75DSx5vTspiAhID0+PbcHSN5HFryF7HIE68cfa63zkzcjzl0F7XWo5oHGhYPgBqL0u6EMfuw721k34/vgbgm+9HDImdPfiWls2IqvmYq55EFXioHys2av8hhI0s67fhtaA9giWunp5UD6b30HQ33snFxs+eaeNo84q7y0AKAUuF0ixZo4eczCMPgBZPxv58E5oWNMt71fcpVAzHvz94K2n+3p7NGyBuibktYWo42Zkp88wrLakTSTQibz568REXplCbOTNW+Gku1E5SEdQ+5wEhaXIwzeBvzM1D79hIgIbPxE2zvGGhEkbHCYELQb839kMv/nK1Ccx5khY+GD6986WUB5zHCWsxNldifXZqQkqtgUblsCHT8C+p8OmEOFcz5MzVJSlw8I/tzGtc2LCEvwfNuE+tDKBYK6gpD/q2JtRVSOhbZs2TOYSZox12tgE0kflyVRdBpEsQyntsZYCB3QmiD5Ir1OkeWPWopHXvDGXhlXrux0T22bJg89x9A2nUrDtP+BroNs6jf6uo5dv+4aQ8hwgwjJnB6B5DbSsh7UvQtEAZI8LUQP3DY1lwcKnkLn/hvadvQi9dE1tTWAXrkucEygD2rZnduqgMRjXP431zrPYc6+K39AwCI46HuepX0Pm/Bs+/0jvCwUGVLhQhQ48x/cn8Ekzwc9aIyWzjCEFuPYqx8jUs64M2LkqryznkUcP5JXlPCKw/X523H43O+9/ALulNXK8cP9Z9L/xpxROn7r7JpcEpqE4aFpB5PcwZPNnyN8vg87Q9aQijIfbLH0T+XwectQPUGW1cNiv4L1bYefqDGYYEnbHHoPa7/K0Qrh2B0SEwDOP4LvzV5roKux97RbuDK5JRThHFEby12LVqeyFTgt8nbq2ZRRDaUe7HakK1RN+nyB2HG6g4n4Y5z+g689+eA+8dnV8xdHXApvmIR/uzG6pVwF5azFy1DSUI8ve5WRY9iy016fWNu3hLdi2TLNqD8+MmTsZ1J6HwfA9kefuQea/BGJh22BGrSU7RHxjGArGzMQ48XKGVgym4PGXaHj+LayOTgrHDKf2wm9QNHF0euNP+Bqy8MGsXhNOozvDsQg0pZfnK2/9E2adguxYGVrPPel+ySi/NbCsNTkTeUoTBHubD3uHH7NfdDh2mEjMCXueipp5vg7LB+iXY44GQ8UmdWpugcKiSNWgjOAKeUlz5LEUER2pkC1lWdARNVlCe93O2MPYNp3v30bBoEJS3oPC99DpgNJiXa86/G4Jr/P2bfDBzcjgg2HkqciLt8HW5V1dOEEqnNAYRYLoMaAjRyXPukbuU4SZMgwYOC5ZI6SjAzV8Kmr4VADk5SuhbmlXE5eBa+8KHOOKoc6r134/N6qkL+WfFDSt68P5eaQFEW103dVj5pE28spyHgBIIMCGs75D21vv9Hp4Oz6Yx9pjv8GwJx6g+MB9dtMME8PlVNxwcfecUdmyErn/uxDwZeZxExtpb4anbkLaLMAJB5yEmrofLHoQEpXHiSCkkblLUQdehRqaG4UjmxAR/H/6Lf7/3B+/kQL3zDLMftqCnXbIlw00+KDCHWG0HjLaHbfaTf9hLox4inhBBbL0MWTB36LIn+J/L9IZhLos1VmNRrsPFq+DvUZlr0+VeIsWsZElT5LT2CplIEufRmVBWZagD1p2aGHTU4oq0qH1qrQa9c0baJh8MnPP/SYD+5v072fidiqCllC3U2h31bD3/X9HVWuSKAXUnnMSteec1Kc5qeIaZMo34JNHydp9jFWmpiHNMODWelgxN3b6R4aOM7GE4Iq27C0XQxFc7etSlgsqoHY8avBMGHdk7xJk7iLoPxG2fUpO1mwCdnxpTVCbOhU4jJwpyhDaQwsc2gGejVujAHdZFjrSGH7w3joaKFo+UIrSagfl/d10q0OWKsL3s6QIWtt02kIEoXE2vYOseRu2946yUSWh+9UQUpgdBph22jnQaUFscBYlb5cA5uCh4PaAzxu7gRXEMWFy92OB7mHbErCRxc26UkD42OftSJULtWdZZt51sSEYZ0555PE/jLyynAcADQ88Stub78S2Olk2IrDpossYt+x9lOOLv2zE1448cFXminIIEU9nkalrk77zONJxNMY3/o2seEGzR/pCuX/KDOnGUUp0+VDUxJNh1OFfGtKMwH//mVhRBlyTizH7ufoukDT6NDOy02DwaBej9vCwZqm3e5obcOipcYQ+ZYK/DZn35zTGzIGiDGAayOqtqGwqy84kpGFbFkNbXfbGiwWxYeM8pG0Hqjh9EjNp3oZ88gysnAM713d7HqWgHIZMQU09AUbOonLKFILTT+DZfz4V2YuUaYDAOa/+MqIoZxtq+vnI2vd0DmVfw4Q9ZjfvpohAvS99b67hQD6fD4EYwmuGj51d74+EbGYFtmDtAL77hi61FyNUX+wgbJkLa56H+mXgD5Iz406cWroStKEziMo059jIrERURnCZyXPbU4FtoWrG9L2fEMqGDuSIW6/i9Z/8FmWaIDaGASf8aHh8Q2YqCL9ki4ogKqKtCwJOgf5u2NI7p1sVOxCPAW0WtAZ1mk97EIr74mFNBIGKEX3qQRUW4T71LHyP/Ks3Z4ZhQGERrmO/3uN497XdU1GOYKcf+aQJNbMyg4kpML748t1XBvmc5S8N0noqPv30Ux555BHmzJnD+vXr6ejooKamhmnTpnH00Udz6qmn4nanUYojjy8ERISd9/0jcSPbJrh9B60vv0np19Jnx93VkJfugZb6rORwKqUQROcLddow72U47mKM6Rcge50HLZs102/rVsQOokw3VAyH6jGowuq+X8wuhLVuNb57b0/Yxqh24hxemL1Bm7TCrJTi9EurmfNsCx+/3Ya33WbQSBcHn1zGyElxDA1iQdP62J/FHS+Y3RDsMCwbWZdZLltsKHDWJm6yfVlucpVjoe5TSENZFl878ua98MmzRKjNe6KzCVa9i6x8GyoGw9d+zgn330T1hFHM/+NDtNftZNCsKRx8/aXas5UjKIcLjr8deeYH0NGYucLsNlGuLqFWRCBgw7b4ZD5xYQdh0zKoivOazkB5s2MJ131Fexv2XRdhKK8uEVcxEDV4AoyZBe4ALLgTOneg3eEh9nqXoTkMsolCR8wQbBGBjkDfnndT5TQEOwwJs/tnQ1kGxCzKagWl/a++mFFHH8hnT72Ma+ebTDrQQ2lNFpQrpfTyKPBAZ2/jkFIKipxIqVMbrXt+7jCg3EDKHJobICCILVmtsxw1GlSml+oRCwWX/ghr7WqCc+eA6dD7owgUFFJy919RRcXdTygeAA2rdcRbSyC2ohxGYwBpDqDK0jUYhCoV5JFHHt2Q0i738ccfc/XVV/Puu++y//77M2vWLE4++WQKCgpoaGhg6dKl/PznP+cHP/gBV199NZdffnleaf4SwW5tw79qTfKGTgcdH87/QirLnT6b46/YBMDz1yo8Hz6Z1f6VUuBWiM8GUciy91H9h2tPStkQ/UPuSjvuKvh+c33SnBb3niXZFUSCovOYCx04XQaHnVbOYaeVpxZKl0n+TZYE0ZhoziKbLQKexEKZ7FiRxfESQJnIjpWokQel1Fy2r0T++2NoDxH+JPqewopp0xbk39+D/c9nvx9dxP4/vqjv804DqqQWTroXef2Xmm03XXhiKMo2sK49c0WtuQ5GToXGdd2NDRkqbdJuaaUkhewRs9qJWeXCKDVRIY+t+GzsliDWzgBWvT9yXbJqMZSFxInta5DP3oUV/0HVFtC1K9qhqStddqvRm6VwY1PXbzbCERY9OvVbXfO0bJ3b+UUt2SfEJihLux/REQQPXok99WuoIy9DeYqTnxevO28zNKwHfxu1FSa1Z1TCthKyanFUCtyurrrYPecgAjUFmiQyzrCaKM0E286NoqwMGDgD5ey7sVh5PBTf8w+CH72P/7UXobMTc9IeuL52CkZpjEiqqjGwYY7+vT6J0Uuho1nSVZbF0uPkkUce3ZCSsnzqqafy4x//mMcff5zy8vK47ebOnctdd93F7373O372s59la4555BppEAzIl4AcQOY9mxNvm4hoj4iPvodqfgFhrVmFtfCjhG3MGhdGUQ7CtNpDLNlRQmxKAm08RrDdhazNRYGjJnkYdtOmXeNVRqBla2ott69C/nOJDh9OZ27htu/9E/F3wuE/2OVKjSquga/fBcueRhb8uyvFIhFMzWQcTW4nIrrE1Jo28PZtr1A145B172V2sog2RtmS8rNi1rpwjS5EuYxeRjHlMFEFBo4BbsRv4/+8A2ubn27ai9gwqgQqwoy8vcdUpkLKXGmTnsXoCEpqUSfcAQ2fwge3htaRHrNXua6gjXKnuX/t6v1FJDte7I4QudeiF5HVc+Gcu1E1qYcPiwhsX44sfQpWv9WdHHNUP3CauXk+wwpzD0QivEpd0Jxk3fhsHXpvZtkwIjaM+3rydilCKYVz1v44Z+2fvHHNxKj9VHITHQVQ/eUpafmlR/hZ39Vj5pE2UnprrFy5EqczuYVq3333Zd999yUQ6B0mk8cXF0ZZCc6hgwls2JS4YSBI4V5Tds2k+oJFr+ZEgVBKIS7Aa6HGfzGJzvqCwItPgGl2Z7zuAcdgT27C24Ihod6ZRr+ZbvquHJYVKS1EggEIhvZAp1vn96UNgZIUCLWsLIfVhm9Nz1wqscFKvq+LvwN57Or0FeWemPcoDBgPk3Z9FIsyTNjjVJj4dWTNO/DpM9rTHJ1b6DCgthYqq1BlFeDyaOE1EIC2Zti6Axat61KUC0I1xkORyBhOKC6F4kKdDxuwoKEZ6pt0feYwiqug/+Te9zKZMhWwoTmgQ1ajHdKdVnyvsgGuicU4alxd7PYxnvPIMafCPaEYq58fFf1MDSnS5W2SKCnKaSLlbmj2ZS70KwWeMmTRI6h+E5H9b0DNvxO8jYCtDRbRfVs6PBeVojEuQhiY4fzShaJrzWSqMEsoUiecIy82tDci//wuXPBnVPXw5F20bEVevl6nFymzu3HY7UC5cpTXGi4FmKgmdirKMkBLAFWZvQhHEUGVDIaBicsDiljQsgGaV0HrBl27WJlQ0A/KR0HZaJSzSJOHtjfp76u4XJeoTIR+E6G4P7Rt04YoSUBYJ0QZq1KEMqB2D1RxktSfPPL4H0RKO14qijJAR0cHhYWFKbfP44sBpRRV3zmPbdfeEl8BUQqzvIySL2AIdi+0N+YsHloZCpk4CzU49VAlCRN+KeOLG/4HWIsXJFSUAYwqZ3cBWqKE0QxL2UQQsHW+XsrI0LRe5syN8GsABX744NVuh6WgCEorof8QLRQluUciQAvI6qdQnhKoHgP9xqMKYxC2mBnW04zMWWnjgUP1Ck+NeEcDoRrZdcuQde+AxwOdoTIyrlItABbWamPSW3+CtmxwBSjkld/C8BmoogyIajKE1dJC5/yFeD9ZSmDjJggGMUqqcI/7Fp6qFlwsQNVUwKDhKJcbsW1QXfdNRKC8GmPYGGTmLNiyEalfh/K3g8MJ1QOgeiDK5elqL0SUN7EFNm1HFq+GjXUwZBL03wNKB4Y8+9Ee3BjKlAjs8EFL7JJBRnEcw40B7iklGKFQ6lT2qXAbozL0PNlAiRPVP3UiQ+U0kEoPtAXST49QgASh/jNoWIUseRycRcjYo8DwoTa92bsWL4AvqGsaJ0vziH4XWvYuIfhSSiEdQX0vCjMoVSWin9WOHhcuNvg6kEd/Av/3QFcpr1hd7FyDPHMF+ELs0z2jqApcuWWbNo24W7tSCnHH/zwCAwjaiDeoeQT6ONew8UhKRmDEqTcvvkZY/yqsewF8jaEJRz1voh8SEZCdNqxp6JZ/LaXVMGJP1MzjYdIBMcpLKhh1GCx6GMqdOu2hJdj7PiigxAEV6YZg2zD+xPgfexth56fQuBq8DfqgqwQqRkPleFRRXslOF3nH8pcHaZsHDz/8cB544AEGDRrU7fhHH33EOeecw8qVK7M2uTx2HSovPIfmZ16kc8Gi3uyMSjOBDvrjbzBcfRTOvwJQh5zW65h01sOGt6FhBTSuAn+rDlsT0YzcQQtEISUDoHqCtk4POxDVV2Uni7BXfZa4gUNhFJhagfKHvDY9dSJDt8NlaEUsHQRSVbDikEWFICL4Giy8dUHEEhxFBoUDnZjukJBTmSNjng2qMsaW2tkOnR2wfSMUlSKjJ6NKKmLP3bahYScydy7YdkiZ0sKqDJmJ2uMUGDqrS/grHwqN6xPej5gwgAIHymHEFXyVUoiJjjbwmGC2wce/ji28u0qRgQfBkmeyFNUh4O9E5j+OOvg7WegvMXyfrqDhT3+j5bGnEb9fX7MKSeRKQSBIydHj6H/z8ajCLoORMroLzkopHZYNKNNEBg1FDR4KTXVQWNTr3imluhn2lKGQwf0whvZHGlrAMU63mXwK8v69XQ1DCnY3iMAWr/YqxoFR7IiZs+wcWYhR5shIqVDh+2QAI4rTVqSUoaDUpcNmvUHtWU0k0IW7jh4jHCIcaMea/yTebYK/YDqyZQmG1YJ7gAv3ABeGUzOr47dQ7hQU5kj/WQqNTgWdQb23tgsUOoiswUQIS8BeC9rjfP9iQeMm5O2/ow7/XuwmbXXIs1eBrzX+c5xuGHsmMM3uERZR0BFehiby6gmHApOulIOOADgMxEwxkiAGJPreNmyI/fmGV2HZX0LRN1HzipGupRRIpUJVVyNbO2BFi44CaKmHxbORRW9CWQ2cfBVq2hGI5Yetb8P6F6FtA5igLAVTK5CFjVphDl+aAMUO1LTkRtnukzK0XDKkdzST7FgCq56CLR/qAVQPJT78fqqeBKNPhEH7f6GdAnnkkQnS3vU8Hg977rknf/zjHznjjDOwbZsbb7yRW265he9///u5mGMeuwBGgYcRT/+Hrb/4FU0PPq4FxhDc48cw4JZfUHzogbtxhl8cqKhwVOmog0V/hc3ROYU9vD8m4HCEBKAtOoxq7Rsw715k4ukw6XTUbi7XIMFA/JqPIRgloZIciRxANuAXTarjUOBJQ2lONXe+eizs6K3Yt2/2s212Gzs+6iDY0dPgA0VDnQw4pISavQsxqlzQ4E8slKcLh4Ih8bxqoYHaW2HR+8igkTB8XKTUTkRo31GHfDg3tod/0wJk4zwYOgsO+RGqqBrVbxyydk5683QZ3erRJhJsunmabbTHy2X2/k79LdqjMrIY6r2wM82awrEgNix8GjngApSZGwOH+P3U/+4edt5xj76msIAeff8NRe11R1Fx1l5ppyCElWkpr0WJDVbyGqYRBby8GIyV0PohTPgaLH8WmkM56jZ6vUWjzpdQUQadK+zo7ya4pev7MUodOAa7+ybghpX+gB0hA0u7C4cBxS6kKJRjHcm1Rv9YEvf6RIT2zzpofK+ZjlUh5nG1Vp9nh/tXlE4vpuKAMtz93YgvCC4ztsIcy/0StHNaa1mzdocUZdDX3xrQz6rL6J5z3vP3QOjcZOXJROCDh5B9z0IVlvf+eM7d4G1JbPAyYntWs4pk97jnM2jQlcKjevzf6ocSV0YKczdF2RLwNnf/POiFBb+GugVp9RvZQ/oXQJUbFjaGiMtC9725HvnnT5Fl+6OGBpCGLVhLmrBXNuvIg4CNcilUqRNzZFHkOVGVbqh0pnmdSivAB/y4W+k38bfBovth/etame5iyYvdTf2nujRczRRkxuV5T3MeXymkLaG/8MIL3HvvvXz729/mmWeeYd26daxfv57nn3+eo476EoTo5hEXRlEhg37/K/pffzXtcz7A9npxjRpOwbQ985bCaITCo2T9G/DxPWAHiKt1Rd83A61oBAWCgL8NPvkHrJuNHHgNqnx4jieeAL1CvrrD0d+Na0xhYkW5J4Kia18WGlrI7AuUqcPYZ1yM+NuhflXkpW35bNY92cTWN9viM/0KtG8IsPpfDWx4tpmJZ5RSJFnO9x1bogX+hAitk81rwNuBjJ8GKLBt7CWLYG0CVvqwILVxPvLIBXDCb2LnsyaCx8xcmQlPP6ww96qtqpUOqfboGqcb29MiD4yJzmbYvgoGTuxbPzFgNTez8Rvn413wiVYi4tzG/r88hrJT9wRi5/CmAr1/GuDwQDC5wqzHCgmoLe+ibC8ceg3y9CVdDSKKpNKRHq2xQ697wjHITXCbL3K9jqGe2J7qTLCtE0b3zbAR8c73dGCJxPQ6B1uCbH18Bx0rOrpy7oGeefcSFJrntdL8USuVh5VTdUQlhqAV5lDDhO85vwXOzJ6dVKCUQup7lBgTtIGgM6jDk0PpEpHPgrpMUkTBTgViwyfPw37ndD/cVgdr3yM3OSo5hIlO34nn+RegxQ8eEylILc0gYkCxe6y5aGXS8sEH10Fj5hUJlFKIw4AZlbAgOixbYGgJtr0K6/GdyGfNvddzB0hzEHtDJ5Q4cIwvQZWnqyiHcOBPUCUDu/pu3wZv/6Qr3aYbE3+PcyNzCrWpXwKvfR854CZUdfb37a8U8nHYXxpk5M665JJL2LRpE7fddhsOh4PZs2ez334pkNHk8aWAWV5G6QlH7+5ppAXTUMya5IHOVsz6HLMDl9YgK5+ExX9N77zwS8yBts6H64w2r4eXfogc8WtUzYSsTjXlqRkGqqIKadzZ6zPHIDfu0UWZd95hQwHJ85Ed0YKo0oKJWGC6YcxRqEmno0oGIPP/GvKsgK8pyNLf1tFZF1IUEn31oXeEv8nik/sa2etEDwXY2ZENC03U5NL0ztm5DVYsQmwXrFub1LMfgVgQ6ECevRJOvCt2PmssuIyMFeVe8FvgjuFhJiQAekwYWgwb2vqoMCvYtiLryrLd6WXjaefiXbQ0ofBQfvZelJ82JTuDKgVi6PVspel5b5uPKj8CDrkaeevX+piNVhREYtaejQfDY+IcWUhgdQc4FWZ1hgJ2LLQGkICNSot7IDVEFIuodA3fNh8b79+C1Rk6lmzrD33e8GYTnWu8DL5wAIYt2pjn0Lmw0RUfut2VoK1zlw2Vde9ypB53SwwDXjivPWjrSgx9HwxZ9jqqp7K8/PnuHut4iBMeHX840ed4g+APdhl5nCZ4nOCKEf7fMxWsJ8JrIKwoQ/LvxGvpd67bRNymTnnoca2ReViCBKzeRojSLoWSxfeGFOW+yRt6HsDUSpi7Q1/bkGJs0yT4n5DxNN4Q4em1BgnOa0St78B5WE13wr34A+v/D/gpDD0A2bQA2bIIti8F7wq08bPnObH6ofurR2xtEJzzc+SQ21EV+VJUeXz5kbay3NjYyEUXXcQbb7zBn//8Z95++22OOuoobr/99nwYdh67DS6n4tZL+iH+UuSGGKQX2YJSCA2odBXlHn3o3F5DC0BiQ9AHr/8UOf5eVOngrE03HRgTp2C9/1Y3YcmocPRNUQ6jU5fxSBiSPWxvnaNnBcFZABXDUVVjYcDU7nUtQ17wYIfNkt/U4a1P8/sOtV3ykpfpx7oxlfRtvShQ+1en4FWOgfotmg3Yn6bAFV4zr/0SJp0Ic+9L3N5Q3UKvs4Kwwhwv39ltQG0BbO1D7WnDRJq3Zp2vb8evfoP3kyUJhXLnkHL6XX1YdsmMlALlADsYP5wxHppmo0aeD/wUmf0bfcy2tLDanF4FCkd/F3Z7EPw5IGpqD0B59liIwxAR7VkNXWqgKcj25+opGl+IMg1sv41vmx9/nT+5/iLQuc7L5n9uY/DFA1BBWxNCKSIe3Jj3pSMAxdnnmVBKIVvb9R7ZM5RaqfQ8x6mgbg1iBbqnNyx9NrUoFW8gpTUjlg0tndDUodne48FQSFkhlBegnA79/rEScFJYoRB9Re9UhGSwRXvpO4OIqfR3HY6QkVB8QbyhlQn9dFkl2fYRbHorvbETQBuCgPGlsK4dyzCxnk9SnSQGZIePwCvbcR5Tm8RgpaB0MLLfVaity5D/nA1t2/U1lprgjCIjTeUWR7eR0D+2H+beghz1J5TDk/a1/E+gR7TALhszj7SRtrI8efJkRowYwcKFCxkxYgQXX3wxjz76KN///vd54YUXeOGFF3IxzzzySAnK5UEGjIEtq0h1V7B9NlZLELtNE0IpU2EUOzDLHBjdLLQK+o1ALb6P5HScySaq9NNnh36wtbfp3duQY+6MwYSZezj23l8ry2GY4B6XPmFPXHSGGF5j9aUM1OE/SYn5WBXWIHaQNY82akU5Q8N+wA+L3vQx7Ug3qmeJmVQQliUOrEbVZKYciAiUuGBnil7lbifb0LwFOuqhtD+0bo8v7BbmYD0JWoiPI7AqpaDMhbT6oS21EOHY42Q3UqRz3gIa7/t7Ug9azY8OQZk5YLAX0Szmwc7kbbvBguY3UWNPhuoxyJu3wM7PdRhummtXKYVrVCFWSzD7peA6LSjPXnfdEJqnKHBUOBj63d6GRTtg07qojab3m/FuSOCKFehY3UnTe81UHFgeOaZzk+M8L7aE2LSzl0MvItDo1UqcQufehskTJYN9KRXYQWjYDDXD9RyCPvA2pXZupz/pO0FavbC9ObWoElugsR0a25GqIijxxNXPRELKLqRXZjAWLOnNDWGo+ClDYqGG7YPYFiy+hz7LAD2gDAW1BVhiYv13fWadCEhTgMA79drDHP0dhUuAFdbAkP2RoMBzVyNh1nMAFyhX1NrP5BaHb4sIdGyHZf+BKRdldj155PEFQdqukO9+97u88847jBgxInLsjDPOYNGiRfj9Wc4BzCOPDKBmnUoqL7HgTj/tC5ppnd1Ax8cteFd24FvTiXdlBx0ft9D6VgPtC5oJ7gyva4GhgyDQnlL/KSE6B05s2LkCVu0eg5PzmJM0C2n474EeTSKSLWXBIjYBjTJh7EGplwiqHkPzKi9177f3NQKOznb4bLlAVQbeoiIH6sha1ODC5G3jQCmlhaSMw6MFlj4DB14eX6k0VW6UPghFRsR/FkQEqlMvJdS7AxvlSTO8PQnq77g3KUmRo18xJYePzSxaIBlUKMWgJ6tsUgh410CwGVU5AnXKfahDrobiQUnPjD0NhaPCmZ1c5Whk2wsahi06msFUoSyN2BM3nAal00oYdtkQBpxTi1mY+Dvc8WIDwXgM0rHgs7TCnAWIiA69rguTkoVTdYyu7yVXWUWBKGONP0HN3p4I2tDq1WXOekBEkK1NsLUps/SLne2wuTFm3xAywDX59L3JQTh8hPW898hQPgQG7AnbPwyVhsr+OhcRlJ1mxEmvTkA2e5Gdga77VDYYJp4KE05HbDfyyWOw+PGu8mBhFDsi+ft92heiz139NOJv7UNnX2GEc5Z39U8eaSNtSeDaa6/FCAkaXm+XN2Tw4MG89tpr2ZtZHNx7770MHz4cj8fDrFmz+OijjxK2f+yxxxg/fjwej4c99tiDF198MedzzGPXo9Nnc9zlGznu8o10TjgKPMXE2+0lYNOxuIX2+S0E63uEL/bYR4I7A7TPb6FjSStieEDWZM/TpUJhyT2nuey/SJa9aSlNp6QU58zBkfk4BuUgdCpWuLFYqFlnpd5HxQi2vNmRwe4VAzY0fOanY3ARTC2DeHVooet7chuoPcpQx/VHVfc93FREoCB9ZTnos2nZ4Mdb70U1bUTtE6fEksvolZuXNQgJhXmlFMpjZh4CLjbUjs3s3BgIbNpM+2tvJa0nXnbyHlkbMyZEICMGfAXti/Vvhokadwzq6F/2aSpZN6LkwL4gAVuzBYeZrZPMWYVCa0v2KGb41UNxD4xvDBNLaPm4R6pAssfFGwRvIGPhM/I8Nnphaw9FNZw37FC5DZmMDsFON0x2Z3s3Y4XYNtLcDmvqoDWDKJloBGxo9PVSmEUE8Vk6csHRO984a4ipqAtqn+/odbfuJXKyyAntlwM8Gb0PusEAa30n1JZCvxIodyE7ViMLH4bGdbH3bJehuUuIIZNkgnAfYsOqZ7PQYR557D6k/cTbts1NN93EoEGDKC4uZs0aTUBw7bXX8re//S3rE4zGo48+ypVXXsn111/Pxx9/zJQpUzj66KOpq6uL2f7999/nrLPO4sILL2ThwoWcdNJJnHTSSSxdujSn88xj98DrF7x+Qbk8qK//mFiShu2zafugicDWFKMgQl0EtvhoW9CBtLYlbp8uRHTeVDTa62Drx9kdJ5WpBL24phqoYgdGiYnhzoE30qK7cKkMmH4aatDklLuwvUF2ftx3r3L0FOo+7EANKYADq2BqCQz3QJVTK89Fpv59Yinq4BrUyYO0spwlr6NSCUL/YkBEWPtqK2//ZDsf/Lqed36+jQXfvpPA0GNQMy/ofYIjR17lMJKQ8YiIZsfOBMqAAdkjvWt/852UlJuCGUOy77WKhlIZeJYBBHw9ar2W1yZls4+JQVWw54jk7dKFJ7tl8CRg6zzoDKBMhVlgMuT7g3DVxlGYBZpXuFD7nggFJfqYLcmVMZ8F7f4u5SqFdRXpM2gj61u6PMq9Jh5ae6kQNWUEBRVRZFXOAnAkMfyJ6Gu1BNq9SF0bYtlIayds2gn1bdmLKrC1x73Xd7AtZNQwcmDkiR47GsqA0YehRhyAiAUNy8mdu19flzGgj4ZqG+xPm5FwyLqvHrYu7PoOY6HYqb3K2byt4b7WPJfFTvPIY9cj7bfazTffzL/+9S9uv/12Lr744sjxyZMnc+edd3LhhRdmdYLRuOOOO7j44ou54AItEN5333288MIL/P3vf+enP/1pr/Z33XUXxxxzDD/+8Y8BuOmmm3jttde45557uO++JIQ4PdDe7sc0eytYpmngiRIO2tvjK2GGoSgocGbUtqMjEPflrZSisDCztp2dAewE4VJFRa6M2nq9QawEJB3ptC0s7GJr9fmCBIO923p7eiynHo1v4VsEl78X8QSLJbTNa8VuN0AMCoxghG/KbxsEJL5gUmAEob6JtkfacZ8zjGDPuiZR8DjtSDSzP6AIWPHfPh6nFdGVA0GF3zIAA9YuRJXt2a2t2+3AEVKqAgELvz++dyy6bTBo40sQNuhymTidJjStwTIMrMMHEpi7E8vXW8lymTZOU68BywZvMP59cJo2rlhtO03tNVEmVA1FzbwQl9/CFcqVsm2hszO+cNwxb1nkhW8L+BJsYyY2LhX6/gW8sdpaULfaZqBf4fIGodQJJU46/FHXVuqC4hBrq1/bNzyurjXX7o2/dlJtK5YTw7IoiG7r631/t87rYPnTnSgM3KFaXjsX1vHBKZez1wt/QVo+huWfRrynym+iFBS6u/rt8BlxZfuebTv9RkJ9uKgwqq3P6CWLiQgoF/gDFLm61qw3YGBJ/GejyIMOzy8sy8oeAdAwfwliOlCWfh78YhCMYTO2R/WnoxMKCgQjtEn4/UIggc7mMf0Y2zYjDQ346xsJdAb1zSwuQZVXQL9aKK9AKYXHA6apAIXfbxNIENXrcYfbQiAg+DvqoNAXpcy7sMccAcvewm0EcBj6CwhY4f2kB9xOmDUGz7j+mO3tsHQdQVvhC8Zfw9HPfdK2Lifh3d2y9PccD05TcDklbluxBdpsEFPvJ47Qc29DZyDJ3hNqK0rRaTspO2sQG+7e2ItXzYENqzZjD9sLNWov2t96BjYsBtPoZS9xmII7NF8R6GhXuva8w9Dl1JxdddNNJXhcWvlQStHuNZCOADT5de1fIFwfyzQEjzPWcy9gG93SVwwlFES39ce/Dz3bdvhNbf8tH4QRcGjihvBIQ4+kcO1LhG9Qh9/QvwZtrQRH2zhRFHY26HBrp0GncmInWBNF7q6b3uk3sBM99+G2ARtvi2CHUlSk3gttofdGiMm5yG0RLvvm9RtRvGAhEk1F5DkpdFmR79MXNAgmeC8XOkKnKQNfxXismT9EtfuR1s26nnXUnlHgsiNZHcne96m0FUuwyotwSocmnyS5fOIxrEjbgK3wiwkW+JZ1YE4u1/3aJnSauB02DjNqjwiGCO2CDl3SMgpup0TaBi2FLxD/2lwOwemI09bXBps+Q1WM1G3DMgdgWTZeb/wN0Ok0I7JBz7aJZOgvBSKcNbt4zDzSRtrK8gMPPMD999/P4Ycfzne/+93I8SlTpvDZZ59ldXLR8Pv9LFiwgGuuuSZyzDAMjjjiCObOnRvznLlz53LllVd2O3b00Ufz9NNPxx3H5/Ph83WRgrS0tAAwcOB9QG9r33HHjeCFF06N/N2v3x/p6Ij94B988GBmzz4z8vfw4X+hvmddxRBmzKhl3rxvRf6eOPEfrF/fErPtxIlVLFvW5VGaOfM/LF/euwQQwLBhpaxb1xWuedBBjzB//vaYbaurC9ixo6uu57HHPsHbb8dmaCwsdNDefnnk71NPfYYXX1wbsy2AyI8iv3/rWy/y+OMr47Zta7ssolz/3/+9xr/+taxXG8NhcvDFXd+DUoqrPjqMP/25Jm6/n0z8D0PdOpfm5q2zuKduaty2741/hAkFjdh1Pm66uz+3zJsUt+2Ht85j5mjd710vDuEn/xkdt+2bN3zMIRMbAbh/9mB+8EDYi9YM3N2t7fPPn8zxx48C4MEHP+WCC16O2+9//3sCp58+DoCnnlrFN74R37L7j38cw/nnT4bWLbyyqJITfjMtbts/HPkx35/+OQBzNtZw+MOHxG1726GL+NEs/b1+vL2Cff51ROyGl97P9dfvyw037A/Ap5/uZPLkf8bt97tHlxAO2t5OMWfaZ8dte5JaxhXqPQCa8XCifW7shivh3H9s5O9nLkShBdDSnx4ft9/T9qnjv1d1RaiUfOuQuG2Pm1bP8z9bHPm79qID6YihBAMcPGYnb17xQeTvkdceSn1bbI/PGHZwN08D2h50+jvDqSu5Gxgc+unCxEFtLL29a5/c+9pZLN9cHLPfYdWdrL3r3a453TSD+WvKYratLvFT9+e3u6715j15e1lFzLaFziCtv+xah6c9NIuXVvSP2RbAuuUp1Ey9X2Zjj9Co5L1yB5WG3qN/3XEAD/v27N1sqg20s3ZeIcOHaqHv57f6+e0f42vLi6+bw6T+LaAUtz43mhtfjBU+rj1jH77kYe+9HKAM7vqbzdW/itstb/0XDglVZrz/Qbj0Fxbwhx6tSoETefa0ORw/ehsADy4byoUv7h2330fvbuf0Y4uQ6lKemlPCmU/sG7ft306Yx/lTNOnQK5/X8vVHD4jb9g8XreSSYzcDMOfTcg67Pv5+ctu3VvPjkzYC8PHaEmb9ZEbcttd9fTXXn7gagE+3FrPndfHncNXRa7n9G7r+7YaGAkb95OC4bc9yL+bawncIrK+jpbqW2mNrgSNjtj3vwC3847t6bXX4DEouPDxuv6fO2MZ/L12svdTeICXfj7+fHDt+G89f9GHk7/43HENHILZ4dvDwHbz57TmRv0fecQz1HbH3iBkDG/nwu29F/p58zxGsbwpVN/hR9/fLxHElLLnchhIPOAxmXTmT5VtLYvY7rKKDNde8qkOmAzaH3HMA8zeUx2xbXexj+2/fiPx9/B9m8vaqqphtC11BWu9+NfL3aXfswUtL+8VsC2Dd/nRE+D/3ob14Ykn8/P2W216IKOLffXRPHpg3NG7bbb9+jZpSP4w4gKue3pc/nXl/1KcHdmu75i8fMLxWy4w//88IfvfUkLj9LrlnHpOG6j3glseGcuMjw+O2nTPzaWaU1gNwz8ZJ/Hz1rLhtX9nrBQ6q2ArA3zaP54qV+l3K7N5tn/3ePI7fQ0djPvjRIC7895S4/T565RJO328HAE99WM0Zd8RPT/n7Jcs5/1C997zySSUn3Nqz3+cjv91zz+FcconeF+bM2cShh/43br+3334QP/6x3sc+/ng7e+/9YNSnfQz5zyOPFJF2jM/mzZsZPbq38G/bNoFEZvc+or6+HsuyqK2t7Xa8traWbdu2xTxn27ZtabUHuPXWWykrK4v8DBkSf+PL44sL8fsILl2cvGEGCG7sQymcLzLs7JDW5BoStHITImtL1rmO/ieQq7zKaSehBqcenr/bEXa/pxKOu3QR4stG0dweyCQce9Kw3ObGfkkg3gBKpS0SxYffgvpOaPCGvJFfcFheGFoBbgdsaU2doCsW78auQjpesmAa+eWFlagjr8M4+peojLgF8sgjBXxJCL42b97MOeecQ1VVFQUFBeyxxx7Mnz8/6jKE6667jgEDBlBQUMARRxzBqlWruvXR0NDAN7/5TUpLSykvL+fCCy+kra17WuPixYs58MAD8Xg8DBkyhNtvvz2z+5oDKEmTJWH69OlcccUVnHPOOZSUlLBo0SJGjhzJjTfeyGuvvcacOXOSd5IBtmzZwqBBg3j//ffZd98uC/jVV1/N22+/zYcfftjrHJfLxb/+9S/OOquLPOiPf/wjv/zlL9m+PbY3NZZneciQIWzZsoPS0t6srPkw7Nhtd0cY9uk/19bS535Ziv/S82lfvJRgKNzLUWqCr/vc0w3DjrQVA2Ofagr2j20dTy8M29bhUz4rKgwbcJehTnmgW9tch2HL+rcIvns7voBCtnbCTl8vITorYdiHfAvjsO7pGtGhVsnCsBv++zxrL9ZpF1kJwwaGHlPEsEOKIqGQInQPw65wQ4EZWYc5CcNuDWD4g0nDsD++dyeNq/0oJBKGDfraDlzxAu7Av7oat7bB8qW5DcMusCN5qrHCsAHEb8G6ttTCsJUJlYMpvvg+lFt7wbIVhr3xrIuQd9+J2FpihWErp8nYDy4HoKCAuGHYsuJT5LPlkb8LnFZXiGVQEYgVAh2Cx2VjFhfCvvsSCAQJtHdAwBcKgVWa/MvlAXcBnpICHI6oMOwAUHsxmN1ZxqWtEdffvoOjfQfYVvcwbAUcNwMqi1GhSbpd4HBoQSf4yif4NjXHFaSShmGHz5tcjsutcIVeMZmGYYslmtALiRjGMg3Djm4rItQ9XU/zvK4oLUdojxhx/3dwHTydjoJyXfe2YSvy2n3d9MBeYdi+rmsTQecgh25F/NDq3kja1m9H8oH7HIbtMfR+FsaEE1Hlpah1z1AQ9ML6JpCokO0YUOiwZgDcJp04sBP4XjIKwwa8foXlB+pDMpkBuI3ImkgnraPQaWmaAKfCZ5kJwrAVhVe+gunQizh6P5G6RTD/5m6tsx6GbQv26jYcb27tWxi2AvOAWhwzqrQ8uL4JbOkdho2JqogdmZC1MOwwDr0TVTY0a2HYLS0tDBxYQ3Nzc0z5/IuKlpYWysrKaLzzQEoLdq0xpqUzSMXlc1K+Z42NjUybNo1DDz2U733ve9TU1LBq1SpGjRrFqFE60vG2227j1ltv5V//+hcjRozg2muvZcmSJSxfvhyPR0fkHnvssWzdupU///nPBAIBLrjgAmbOnMlDDz2k59XSwtixYzniiCO45pprWLJkCd/+9re58847+c534pCX7kKk/S1dd911nHfeeWzevBnbtnnyySdZsWIFDzzwAM8//3zyDjJEdXU1pmn2UnK3b99O//6xQ/n69++fVnsAt9uN29174ygqcnVT8OIhlTaZtI1WcPvSVkTY+sd/s/P5NzALCxjw/W9Rfth+KfUbrbwngycNkpd02rrdDmJ8PRiOLoGg5fsX4fhsKW5l4Q7t16bfijCkxoLLsHGlaKZ2KRtjVSNFh8cON+3W1tklDMZEFOGG0yE4HaGXf5ELlWB9OJ1dL5tkcDgMHI4U1lrpUBymfjlKOdCSmDHYNLoLK6m2VTOOSHhthqESPhsybTzhAH9DQUHPRKs4UPHaKhg61dlNWFWqu9CGEQBP/DJaRZ7UXRzx2kpnSDmIbuvufX8nfa2A+XeFohvCzRWMvuhkqsYORzYUgxWy2Lo8EGO8aGU4GaKV95iIuicFMfoVEQgEoMdaib7fXX0ZUDUQdfZdEUUZsrNHAFRMGUvjh+9DUK8Dl4rx3AeDuNracNZ2D0F1uRSu0LKUNauRtUsgzjguh+ByJHk2Ojpgzts4R9fi6lnKygI6Qz9tTqS0Gkoq9XPvckFJae/oiqJa5Ad/R/7xQ9i6CqdD4TRDc9hjGAwpibl+lVI4DpqI4/kPuxieE8BhCI6o71IkFJFhATvaUCO67ptpQpGZ2loLtxVboNkPbokbQWIYsZ+NZG3FFmomugjM774PKAWORx5C/vswBQMHoI47EnXIATDjEFj6Zsx+ler+LIstvdZ4NFKdb6+2IqAkdtk9Ut+DAQrdFtQ4wYw6Z/3TKG8JooIRRRmilOFkMBUFDgFSa590P4mCxyXgFGi19Lw8BqjYkUUx95OesIGA4HZauOPUh6dyOIajS9aJ3k+kdljM/TSMpO/7FNqKLVhtnViq67N05BOnIThD7zlHtYHpCT1Tzt7vPqcpOD0CbispYVpYNkgFcdv616KKukemmqaRsizcs61lZVDyMY+0cNtttzFkyBD+8Y9/RI5Flw4WEe68805+8YtfcOKJJwI6Xbe2tpann36aM888k08//ZSXX36ZefPmMWOGTrX5wx/+wHHHHcdvf/tbBg4cyIMPPojf7+fvf/87LpeLSZMm8cknn3DHHXd8IZTltGOOTjzxRJ577jlef/11ioqKuO666/j000957rnnOPLI2Hk+2YDL5WL69Om88UZX7ott27zxxhvdPM3R2Hfffbu1B3jttdfitv9fwIZr72DN5TfS/Pp7NDz/JsuOPZ/G13ITDbArYSiYMsbNZPc27M+W9S4Nk+UwMbshgMQqg5RRZz1eKsqAylHZ6TsdlA0DFVJKcmXtNEzo1zcG3sJJYzCK+lC7tweUAZ6qJIaHgJ1TRmmR+MJwT1SOdTP90kpKh2qBzlViMOqbk5n4xxt0A/cguup/OYirOWYLcerddoM3iSAdZobe6xTUeX9NveZ2miiYukdEUU6Ezk82I3E82dLaiixa2PfJiIAvANuaErcLBqBhK2z8DOloAVf/uEqkKqlCff8fqLNuhqGhEHaHCdNGJly/qtANx86AQndae6Umb1NdelK9D2mOwWKcDtoDmdXoTQHKUHiG9uYecZcaXaWQtmxF/voA9o9+Aa6hITb2r0iCRoVL16mORpELsW3Y1JJZOH4CI3RWEK4W4FLdCLsyhk18vV6Z0H9i/HMLasBRFP/zLEAZCrsuCykaLgNjVMhw5U+w56Wyf2cDygzVp84jAtlNP2ng2WefZcaMGZx++un069ePadOm8Ze//CXy+dq1a9m2bRtHHNHFSVNWVsasWbMifFJz586lvLw8oigDHHHEERiGEYkKnjt3LgcddBAuV5cB5Oijj2bFihU0Nu7+dZORRHzggQfukprKPXHllVdy3nnnMWPGDPbee2/uvPNO2tvbI+zY5557LoMGDeLWW28F4Ic//CEHH3wwv/vd7zj++ON55JFHmD9/Pvfff3+iYb6ykGCQzXd0LXJsG5Ri82//QsWRB8Y/8UsAt8vg9qPqaPrGmb09Iyo3ZSbslgBmFursxiy3UZW92rKpQhkOpP802LZAe3XcBviyTJ04fhbK7Jsibjid9D//VLb8+WEIpu5ViQdnidGtZmhM+CzEluTtMoCIxK4/nQBVEzxUTfBor55SqCMuQTnCho4x0LGiq3FlJWzdmsUZ90ASYVkphdilgCaK0Xm1Socci+i/JxyBmnk6KotlomKh6IhDUC4X4k/MotrxwXpKjhwX8zNZOD+jvK+42NmGlBdphTURbAu2r0OCJVBlx82vVQ4n7Hkkas8jke1rYMc74FiddBqqpBA5cR+YvwpWbu6q9xsD4Wch6Cgk6FUYm+pxVLowi0z4vBUmlCEeM+19VwJW17OQI+OUo6y3YaxsUAwPVV099vW3oi69CGQ1SgUiz1tM5FLnMOnFVJw2Klyx6527HNDsg84MBsiG8poKHCq74wRF39OefYqFGnVQ3NOUUki/6bD1XcJVNrIBaQ/Ctk5tgHcoZEcflWUF5pRKlNPQ75cEaVi71A5k9/19nUd2ECYvDiNeVO2aNWv405/+xJVXXsnPfvYz5s2bx2WXXYbL5eK8886LcEAl4ofatm0b/fp1J+pzOBxUVlZ2axPtsY7uc9u2bVRUJI/kzCW+VMwFZ5xxBjt27OC6665j27ZtTJ06lZdffjlyQzds2IARFc6233778dBDD/GLX/yCn/3sZ4wZM4ann36ayZO/RKQxWYTtD2hypGiIEGxp3T0TyjI6//k3HXPX06ucK/T1XRkOwe4pj4oNQ1ILjc86xnwdts6DtmDaClxKOOTi5G1SwMBLvqWV5b5CQdXwFLfB9gBS7My64UUp1VUPM4NzcZfCyChjV/Ee0PAKSCjBtrZ/7pRlRWLPhDKgek/USTdBw0bY+hk0bUFsC1VQCrVjoHZst5DrXMIsK6P09JNofuSJhPtEy3PL6Hf1YageqSfS0gw76rI/sZ2t2qubUtslsPIvyNiLkxJSqdqRiP81SFH2Vk4H7DsBmTQMVmyCDTugrXvFBssn+Dd04F3Tid0euoehPcxZ68IzvAAnoMaWIkWO9J6Xztzv3UqFPJTh3GKnoqQ2xh4QStSXe/6KOuNoZMd8XYs2jsKslEJMlb1aw10d6/m6gYCk/95xKK0oO+OsFQXsjFPv+YsC0wx9H1m8txa9JeDiGhgen3UagOHHwZZ3sjIFCdjI4kbY4YsorSLgGOxGWi2sbb15Q1LrGMypWrlQSumSZfGwq0oJiQ2O7EWEfSWQIeFWn8eEXuTF119/PTfccEOv5rZtM2PGDG655RYApk2bxtKlS7nvvvs477zzcj7dLwpSkhIrKipSfuE1NDT0aULJcOmll3LppZfG/Gz27Nm9jp1++umcfvrpOZ3TlwVmYQHFe0+h7eOlXR45pag85pDdOq9swG5uxvfKC7EF4BztRaowA+bZMMIbZKDHm0oZUDMRVT4s8777ggHTEbsS1n6e/fs2ZirGkAQhbmmgcOwIhl93Geuu/33m81QKh0sYsmeKufhtgYTCciYQES1c91wHiaCUrpVrKM1/NONbKLPrGpThQkpnQfN7gGiWqopKaMzB3hxPAI/G5Au0Ulc1TP+we4Naq676AS1PPIMkUJbtdj9Njy+i4uy9UGbXNcq6NQk9rhmjqQMZaHcbKyF2vA8F/WDoyQmbiVjgT99QokoLYeZYmDkWCQSxVtTRdu9HWNs7tEMtTph0oM5PYLsfoyxA6bhjMTveQwq1mJHsmZF0n4MMYfvsbntG7UQPRpLoCHnhXZhgonw2FJhIgQNlqN7h5i4j+wp/eAyldCiyHQp9Txb1YyoodkChmdgr2xGABARLieeW2WlpwZLceCSDog0JUVD7XoRKxihfORFKR0Lruj55l8WykY/qtWEaIvdSgf6+SkxMhwdrY/rlkcy9q1EV7hBfhKW5COLBym2KURcESneTXJNHL2zcuLEbwVcsrzLAgAEDmDixu9w2YcIEnnjiCYAIB9T27dsZMGBApM327duZOnVqpE1dXXcjczAYpKGhIXJ+PI6p6DF2J1J6M9955538/ve/5/e//z2/+MUvAB1LfsMNN3DDDTdw9NFHA3DttdfmbqZ5ZAXjH72Hoj3GR/7u962TGfyz7+/GGWUHbR8v4qK9n+Ci/Z7Ba/TOSetTDl0MqEITozh1wrPeHSgtGMbyKu/5rZin7BK0NcKKLdkXgtwuOPM3We1yyNUXU3H0QdCTHCkVGAplmoy75BCcHhNJRUi3BJr82RcsWhKHBAPgdMCASpgwFKaNQk0ahpowFDVxKHS8iiy8Gvn870jrar3Wyw8CRzkRtXTkSCIU7dmCoTRzW1woGHcGqjx+nfHdAdewIfT75c+Ttqv/wxysxo7uucs7duTOE9CZwjqIxoZnkbb1idsEdoL0LX438Gk9TTe8Q3BrBxKUxPnEoY/sVi/Ndz5CcEO7Xt8+K7IHi0ivHz1Q76inbENE8G7ucrOXD3FSXJPEZyAC7R2w1dLX3h6Eei/S6NOKjtcCn6X/z/beEOseuJ1Q5YZ+bih3QpEDCkwdYl1oQpkTqkOfFzmSz6mlj7VqY9LfCwRtfV/CP0E7s+80DrN9VhAxRJgwbG+YcEzSU5RSMPWHfX9HbuyA1mDcfpRSqAIDVZpeAKgxoQzz4NquW72jPfEJu8BAFUHFF+tdsNuxG3OWS0tLu/3EU5b3339/VqxY0e3YypUrGTZMGz5GjBhB//79u/FDtbS08OGHH0b4ofbdd1+amppYsGBBpM2bb76JbdvMmjUr0uadd97pVoL4tddeY9y4cbs9BBtSVJbPO++8yM97773HjTfeyMMPP8xll13GZZddxsMPP8yNN97I22+/nev55tFHuAf1Z8oHTzFz0wfMqv+YMX+9DcPZB6XvC4LAp8tpdZXT6iqP+bnYWVSYTRPHjFm6vEu6PrJowbBnuJ4yYMzxqAHTsjLNdCEiyJO3QjBNoT0ZDAUX3IVRmN3SDsrhYNLj91J9UohYMFVB1WFiFBYw6dn7qbz1XtjjAOiwUlsf7QGkM5i9tdQeSBy2aRowrBb2GA4DKlGF7tjKeqAJdn4En94OS2+Ejo3Q71QiW7zLBaPHZGfOoJe9K4miPHA/GH9Wgja7D+UXfovSs05L2MZu9bH1Zy9GvL1i29DclLtJpassA6z6W+K1aPWtJnxwXSMtN83W+1U6pFu2jXi9tDyxDavBr/Nhm3xIayg31h/KTfZrJVPa/L1rEQvZV5ht6FyrQ47LBzupGZti6Lttw5YO7f0OI2Dra2kNQEtA/x/x0GZJaVaqtzJVXqPfFQ4DCh1aOa5wQaULyl1aQXYZqe+HmXqVw7DsrnDSgK0jcJoD2pDQaXX9tAVDxwP6u0/1u1XO0Ls2B7DRinJJP9SRP0vZEKrKRsL4b2Y8rIgg65MosSEYFSlce7jqx/QqHMcP7ko12Nmpn10VikiIdc8lFA6e03BgBeWjUK6S5E3z+ELhiiuu4IMPPuCWW25h9erVPPTQQ9x///1ccsklgDbqXH755dx88808++yzLFmyhHPPPZeBAwdy0kknAdoTfcwxx3DxxRfz0Ucf8d5773HppZdy5plnMnDgQADOPvtsXC4XF154IcuWLePRRx/lrrvu4sorr9xdl94NabtkXnnlFY45prf17ZhjjuH111/PyqTyyC2UUrj6VeEo/epsXLKzPvHnVvZCZ7Es3N/6ARz6OygeGBoghRdNuI3f6s18rAyoGAnTdyNF/sal8Nmc7Ie8FZajhkzNbp8hGB43Ex69m3H/vB2ztDh0MM625tCe1YojD2DmspepOHJ/mPc01C2AQBokcDu9WsDPWLjQ40jBiFDIZpxxSwth0jCo0iV/ks8v5CHo3ArLb4O6D6HfNwgx2Wiir2wozApwxw7tlLBCNeIYmPkTlMqyN7vneA1rsT/8C/azV2D/80Tsvx6r/3/2cuwP70ca1sY8TynFgLtuo/zb5+gDcfKu2+esYdtNr+qxAsnLKvUJCepIx4YN7euh9fMEbfo239bfz40dAZMKBMRn0/7ajq5jQdFexo6gDv/tCGplLWaUDVn31CpT0fpJKwP39NBvvCe9d4JlQ2OCcFbQ8zUgK6E5YQU0PEeHG3Xw92H8Yfp9kS30daoBW289bUHtdU/G6h8U/b23BpKveWVCQXX8d5KpdCi1M/R/JgSM5QNRp9+TPgP/6NNh2LHpjwdacU0hXF8phfKY2ggCem2p0I/R9b8xsQznOSNxHD4AZZqgHKjhZ0BbKGqgIwhNgfjPU4acGalDYNTXczxGHrnAzJkzeeqpp3j44YeZPHkyN910E3feeSff/GaXsejqq6/mBz/4Ad/5zneYOXMmbW1tvPzyy5EaywAPPvgg48eP5/DDD+e4447jgAMO6Ea2XFZWxquvvsratWuZPn06V111Fdddd90XomwUZEDwVVVVxTPPPMNVV13V7fgzzzxDVVVV1iaWx1cT0txA8OmHCL79ClhBzH0OwXHKtzBqB/at42T5cHZIkO8rM7ZpYu4xFcdeMzVxxpF/hBWPwaeP6HDHWMJ0OMcxbk6egopRcMStKOfuI8CQuY9rZuJsK8ttjbD6Ixi7T3b7DUEpRe05J1F96jHseOxFdjz6Aq0fLSbY2KwbmAaF40ZSfug+DLjoDIr2GKct+y/eAR89rlVVU1vXcaSilKIV5lIXUuKMzCG1yRrgKITpl2EMPgBZ8w4y+3fga6Eb61BFMYzon17fEYTW2NaXwVcPg86F+qcg2Aw1NdrLvHoVJGGEjglDxfRaRZjCOyyCi4I4vv695Ll/fYA0rkfm3AlbF2mBWqLWrOWDrYth2zLkk0eQ/nugDrwcVdmdaVOZJv1/czNFhx/CtsuuJlivc7p73u6mhz5GvEFqf35Yzq4ncxiw9XUojRPeaBRm3HNg1U6stY0Znw+AQGCDF6sxgFmRQQRTdL5uHyGWENzqY8h4d9Ic5ZhQSiuE1Ulqu6qQ0mb3Ibw1/BrxlMPASaiR+8LEo1CuQuSjP2feby4QEPAnMSLEgo0OQy4wtfEtFsSCsoGwc3PXMYXmSggzZEe/c8Me1ICdWim+oTNRJ96CcvZO3UoGpRSyx/fAXQErHw5NLNXvPPX1p5TCedFo2OTFXt2MdIZC2j0mqtKNOakcVejQ7xaxoWwMTP4BqrA/snIurPuky8gTtLWBoefz5LU0HwdZdCp0XQG4imFIfJbx/1nsRoKvdPC1r32Nr33ta3E/V0px4403cuONN8ZtU1lZyUMPPZRwnD333JM5c76YpWzTVpZ/+ctfctFFFzF79uxIrPmHH37Iyy+/3K32Vh559IRdvx3fJWcg9dsjgkRw03qCLz6G5+6HMUZk7vUyqmtgS+I2VkAwXSpzgialwHRQ9MvfRM5XphMmno2MPQXm3QPrXkfC76Jwfohtxw5hVKZ+uU36Bkz5FspMIoTlEGIFYckbuSFSMUxk0auoHCnLYZgFHvqfewr9zz0FEcFqbUcCAcySIgxX93srb94PHz3e7ZjqsKDUkfr6aAmFl5a6kKiSLL3ODStzhguGHwmTzkG5y/RHIw+CITNh1RvI0qdh5+dQXNAHRbkHGuaDoxiGfh+aZkPLR1BWBlOnwaaNsH17XFZoCf2j5VHRCoDD6DUn8VnIdi/WZ63I+g7tUVz8IWpa9hndRWxk/n2w8Mmul77EWbPh49uXI49/B/b9LmqPU3s1KznmCIo+nsOS/U7E2PA5TrPrWQ079pqfXEzHwk0Mv6gClcWSMd3gyMRbaEPj4vhr1lXd25iQIrwvrAwpfX0U5hR4F7VQdEgGxnSbDOLf4sOxpi3zusAS5Q10GeA0u+YWFB0xFAnTtnWEi23TzQiWCpQBFYPg9LswSmp6f1xQgWRzDfZli4nKgcwY4XvaS2FWYPaH7fVE7qHL0IpytMe9136LbudCk6AlSHNR007PSFGOnK8UjDsLqZ0BC++Atk1dSmsc6L0UKDKhPclzqQwYNhFjv+th4ysYI94HKwZzueGC6mkw9FiomNS1F+x7GXx8dle75oAO14+F1gCqLBcyiMBel6HMLJTZzCOP3YS0leXzzz+fCRMmcPfdd/Pkk08COh793XffjSjPeeQRC4G/3oHU13W3uNsWdHTgv/MGPHc9mHHfjokTYXGSRgJ2QDCcGSjMSoFhUHTbHzCHDOv9scMD+/4IGX8KvHYz4t2oLc8hgb7rd6Xf7cqAoQfCpNNQu6Gmci/UrQErA+9AKrAt2LAkN33HgVIKRzgsuwdk/SJ455+9P7CBDgtVlMa2GLC1l9lUOn/QaUJpOaiQlO+pgKrxUDUBBh+Ecvb29ClnAUz8Gmri15DOBlh2E9gdZCWUE6BuNlRMQVUeiZQfBG2LoWMljCiCwUOgYSe0tCAtreDzhqzdhIw82mssXgtZ3Y69JpRnF75HXqu3wGeYyPKFkEVlWSwfbH0dWfggbNmW7sn6v/fvBX87avq5vZoYxUUM+tXPWPz176GU4DIFM6Q0a0JZA3t5gOHlI6Exec3ijFCQoaAabAd/I7h7h5EqZSKuAeDblFaXdkcA3zvr+q4oAwj4lrRQeGAlKpGiGk+njLba9AWftUJHEuUkHNYrAv4ek+nvQU0ogX6ebns7dBm1xArl7LaFuAgOuBjmPwK+9oQKlO4kZNQYNAXGHIza9AlSORSqR3Zju6dqTPK+0oHDSM6sHQvZUJTD6LRC9z7EDxAmCJv7KRSbqCFucBtdho5EayH8mYgmPfPFSHsKo//42MfThCofgxxyL+xYCGufhx2fEI9YTxmlSGshmO1AS8w2EYiNOvgMVOlImPQ9ZOJ3obMO2jeC5de53IUDoWhA7JSXBc/rEllhBEQ/A7EY0n0W4g2CO/366PFhwOADUYP2z1J/XzHY7LrSXdFj5pE2MmJNmDVrFg8+mLlik8f/HiQYwHrjhdieS9vCXjwfe8c2jJrMKOLNSXsAzcnnYWegMBsmqriYolvvwrnvgQmbqoqRcOr9yLO3Iite0S9rt6llCqcHNf5wGLQX9J+KKtj9DH8RbM2RAhDGzo1IMIBy7F4yObGCyJM3xrf++wWwoDDkMkpVaAja0BpEHXEFanL8cKWkqHstu4oyoa5W/xWZdjvKcEPpTCidqb3vD/0e+6WXwWWj3IIqd2qhVAEBQZoDSGMAGvzdp+RNEMItNvbnn5GtIGxpXgGr7kd2bIItO5KfkKiv+f+EyhGoEb2f4+oTDmPEDT9g7Q1/wI8D8YX2KtPEcJrs8dQfUWWfQtOa7CoroO93psoyQMemmMoyAKXTYEeaynJdW1ZZiMUvSKeFKs5A5Aivu0zk95AHUj5vg41xaglXu6C/B8odqCjvplgSIu4KooYVoao9Ot0gHFUUq9ayaSClLih1QUtA1w+/4CHkkyfhk6egs0k3DBNWiXR5/cNratNC2LSw63EzTGTEvqipp8CwGVA9Tp9vZynP1JHBjc2mohxGRxBKnBHbCMtadMkjOwiugtjhw4kQbusOGSG6eZiVzlUuyt47WCkD+k2HftMR24K2DdC6AYJe/X0V9IOykShnkbYLnebHvvu7sHZJ7P1EKRi/D2r6UVGHFBTW6p8kEG8bfPgYvb6o1qCOGPHEIIFrCUCFQmJEEKUNZUDleJj+w771k0ceXwCk9OZqb2+nqKgo5U7TbZ/H/wD8Pggm8Vy2tUCGyrKjpITR5krspkaMJKYzscHyaYUZo7d3AOjyCBsmruNOpOCKazAqUiMAUaYDdfK1SOOF8OkcCHhh0HgYORMVRT4VDqVT2SRryRS+9t75X9mEiL4Pu1lZ5rO3oSlJvL4/FLpXZGpurOiQv54If2YDA/bqk6IswQ6oe5usS6EKsNph4W+QKVfqKAhC6725HZo6wQpmT/4VgdambPSEbHkV1j6kFZfNO7PQo0Le/h0MmILy9GZnH3H9pVQetT+b7vkPzXM/wXC7qP76YQz63lkUDB+MNI1AFj6chXn0QHlRt70hbVi++J+VTIH6l0FSjxyR9uxHmdg+GyN2sIdGLM+yYUBpFbg8+vOgH5rrUzNWiOjuGvywKgbzcKUTJpSgPGZMw6kyFVLuRFW4dF/tAR09kgQRL3OpEzY8BmP2x9jv28isc2HHKti+AmneCr422LQIGtaj43LjXJNtwZq5yOfvwuApqGN+BqMOh9WvZxRe3wtmyGObiJV/V8AG8ds6zHpZS1eebYEjtXru8SCiDYA9ogrUXr1TMrIFZZhQOkL/xGvjdGFccg/2o7fCvJfR0RMhxV4ZsO+JGKf/CGVmyAT+yUvxZa7mANihGtzQ/f3W5NfGHnfs5yJl9NsL9vlZ5H2TRx5fZqT0FI4ePZof/vCHnHfeed2KTkdDRHj99de54447OOigg7jmmmuyOtE8vuQoKEINGIxs3UxMkbygEDVgSMbdu10Gf7yslMaTz0yZWMUOhBRiE01OpCQisIkAnkLKnngRc/DQjOakKgbCfmf0Oi5bPtEC96b5WgjrPxk17SzUsH0zGicrMMzcE030RRnIEuSDx5LmlAFacGwJapZVt6F3yp5Cg0gXu29AoG0e0taAKu5uVBHLoun192hfugJXbQ1VJx2JWRzDmFj/QdzQvT5DRIdev3MNcuDNKGdofMPsW85iPDj6XupFtrwGa0OEIA2tGbBFx+wV/G3w/+yddZxc5dWAn3NH1y27G3f3hCCBAMElOBTXUkopUEEKpdDS0n5IaakX2lKoUdwCFHeHhCTE3ZPdZN1H7vn+uLPZ3ezs7sidlXCf32+SnSvnPTNz58573mPLn4eZF0Y9Imf2DHJmz4i6T3IHo0MPgi2f2WOoNNMvyc4EnVQdF8OP5s2F8tdil5eMcdKRHrHkCguQloWMmQ5DRkNuv3aF4tQ0oboMdmxAV38BNRVtF/qa/1brlq6ratqPMTYTGZzWJk0mqjqtt9eHrFDVHO+edmKdvhQRCNXC29ejh9+LZA6A/hOsx7Yv0Wd+AIFmb3cX13bztbZtKfrwRXD4VfZef2keqI2j4F8KfioUrHDsJdVWIbVmBvqSM9qarwe3RMKxBXwZMKXrnsqpRvzpuC65Az31O+iiN6GuCrLykBlHIVlxVufeC/3iBTr9oGoiPcJzPC2pB82tyqoCVh2OLE98770YYHhg2pUw/LgUFAvbx+gjBb4cYjSW3377bW655RZuv/12pk2bxqxZsxg4cCB+v5+KigqWL1/ORx99hNvt5oc//CFXXnllqvV26GOICJ7zryTwq9ui7cR9xsWIP7lK0O4x40i/8mrq7/9DXDcEDdO2f2aE7N/9LmFDucOx1ryBvvGLyI9SZIJUsgz93y0w+9vItK/ZOl7M5Cbm0Y8ZXzp4E6/MawcaaIAtS+L7sQiq1acSIh2YWuXD7T1XNcOwcSFMPnrPpsbN21l24mU0rFpveXDCJq7vZDD+v78j77i9qoNWLSPuYkCxIgJeD+xaC+/dhs69GzE81gJVBwW+EsblRga2z+uPB61aBRusVB9VhbKaLs6IR7iJLnsWpp+XUMVuOey76KOXQMim960wG/EnWVjHm9P5/rw5ULsUAiXEkrRmZNtfjEf8XRiYGTnIfkfCkLGg2qGnXQwDcgvR7AKMCQegOzain78e8TjTknOPoFsboGqvBahJWVBkvb64J/NhhYomNM8Xk8FsLc5Uw/s/Qo/+E+L2ozuWoU9+D8Kh+MP5NVIJ+c3fw4RDYfvH2HK/8LpgwETYuaprIzxFc+3mT0IbW43vNSDfa4/R5TYi31lFjrsxamRJZ6gqVK2H8hVW3YKGUuue70mH7OGQOxqKprcsRMaB5BYic9svrMeumwlNWyCwHQI70aYyKFnT9YlBhd0B631Od1n/N7ffagxbRev8bjTdjRjSbnGpzXPDD2NPg5HzkDSnM45Dz3DnnXemxFkbk7E8btw4nnrqKTZv3swTTzzBe++9x4cffkhDQwP9+vVjxowZ/PWvf+WEE07A5UptX02Hvotr3tfwlJUS/NefrYkCgAiuk87Gc9m1toyRfuU1BD//lOCCz5Jq3ZF26TfwHW5vqxgN1KPv3EuL67p5h6Wnfnw/jDocySyyddyYGGRPoZOO5U/o+VXmnauTW1UNQ6czRcOFbluBRIxlVWXFGd+iYd2myPnW5xyurWf5mVcxa9Ub+Aa1WqSo29C5/GQRsQqQla+EFY9ZVblHT+r4PfEIUuRD8r1WrqkhaMBEKwJoWaDjnrPhEDJ6YsJqargJ1vyVPaGpgZB9hmkz9eVQtQXyhsepXAjxbIMD56IfvJq8Hn4PFHVh6HaJQHrnUTkiLnTAubDlATAb6Oo6M4ozcQ3MIrzdhkUKAfcgP4a/k7nBmBmWoWxEigvFcK/YY0wXD0XmfR1d/B4s/TjiIbMMasxcWPVBy2/BiHQo8iV3L2r2vOXFKEdNqC+F5f9Ex52PPndLYoZyawUUWPMpFA+Eup1Je5nlwG/BkEPQhy+20mVSVfE9FtJdVlQPQJFN1ZlFWhY7p5xk9aqOETXDsPkNWPc8VG8AJBKd1PyeC5QssJ4bHnTokTD6dCQr8Ui52HVrgtpFULsAwjXsWXLYXRHfb13AtB5g3Xab88NNhbDVq1nT3VabrzQX2rxQFDahIYw2AROOxJjUvniiQxc4jl5befLJJ/nhD3/InDlzeP/9922TG1es3NChQ7n++uvb9Vh2cIgFEcFzyTW4Tz2f8GfvQTiMMeOg5HssA40Bk8t+tgOAv//mb3DdNwl+8lG8CoIqaRd/nYwbUpBGsP5tq9hHZ6x6Bfa7yP6xu0Ay89GCIVC2FftzZg1k1Cx7ZSbC7s2plW+GYfemPU9rPllE3eIV7Y9TRYMhSh56gqG3WotEGm60QjZTiaqVM94UgJWPooMPRcZOtqp3V1e2HJftxjUhGxmZYeVttqqILAoYkeruVUHMlTWYa2vbXDIK1D3+ODw7H9eQobgmTMZ76BEYRTFGL+x4A5rK2CO0IYF+0LGwa3V8xrIGoeEDMKuQkRMg0IR+9k7i4/s8MKLISgFJhvRBMbWdE08BOvgbsO3vVg57J99zEcF/8jjqHvg8Od2whvEfMR6kpv0EXgQ58ARk9NSEQ233GM3TD4PCwei7z0JWATLvm0hYMD9fDNU1kGHAiHR7Fu3CaoVlZ8Rag0Fh7XPo5s1QX2mDMapW/raRD9kC1dsTlznjYmRyJH/3rF+hj3/fqrTcAwazqlqFp5qLRPtc1mVq1zrriFnIcTfEfA1o9WZY8CuoXNtKCd1rcaLVczMIm16HTa+jEy6AMWelrN+8Nm6C8hf2+i5H/q+OkqMfKyaRKvh7fVfrQtajIyrj7FLg4JACZs2axQknnMDmzZt5+umnmTx5MmPGjEn6vp98YpmDQ5xIbj7uY061VaYqlJRHfrDS08n5279oePhv1P323kjIbCcr783VTbNzyLrjLnxHH2erbnt0rCnpooqpoDU7U5JCGgsy+yz0hd+kRvisk1MjNx6CTaQszHnPGC2LIY1rN3V8nAgNa1rtN1NkEEYZdw9rnkVmfRdj3rmYj/0F1MSYmI0xzfJ0NhtxHRpz2W6MA/IwxmYS+qAMKoNWhe0mJbToCwBCCz+Fpx+jXgTP4UeRfu2NuEaM6lA9VRN2vEabz8hurzJYOb71cRQMUxMaPgKzimbdZPx0yMxGP3wdAo3xeXLyMmBAXoyhvJ0hUHx47Ed7i9Ah18Cu56FuOZ19H3xHjKTuoS+sUMxkNEx34bv4h7D4UdjZNg1CDjoBRk6x/k5yMiMi6MARyLzLIHcI4rVCrY3vX415xz0wMsNew6s+hKa5Y17s0DCwKsriiiGQ5bOKh6V5rJBoI5I7GgxDfRAaglDd1LYIl4Zh8wI4+3ew9iVY/yYx39/EBW4fcvB3kdEtaSMyaAqc/0f0uVuhemcP5FPS9h7lEntrKkw9MWbjVbd/CJ/eTUvaQozvRbPhvPyfUPI5OvunUVsGJopZsh7e+yOsX2wtfAL4vDCoECaNQApybKrvECehTooMOjh0Ew888ABLlizhxBNP5KOPPuIvf/kLa9asIS8vj8mTJ/Pwww8nJNcxlh32ScTlIv3yK/EdP4+Gx/5D4+OPoNWR5WrDaFNYwRg4iLQLLsF/+tcwcpINiexEp/QCK6SrQxQyejDXZ+Y8eO0v0GRj6yLDBVOORrIL7ZGXDG4vKY95crd4+HxDoxdDtFD8w1pFVEh33Yojr19N2PwmOu0buE6/BPN/j+Ka4UEG+mM2WvbkreV4cJ/Qn/C7u9CtDQRqW13jocjCkCrBd9+k6r23SPvOD/Bf+PXo41StsHoGR1HZduIKU1wFZnm7zTJ4JJx6Mbr0M1izFIKBzgvIZfisHOWs5OoztCjgguL4epiKOxMGnI/WrYCK96FxE9F6GRtpbtJOGU/Dk8uSUjH96AFI8VQ4djr67l2w4R1AYNxMZNTUpGTvjRgGmpOPGC3XoEwch1x/Jfr54/angjSGID1G73L1XlFFXhf0S4e8tKj5oAC4DdTnhvw0GARUNcLuemhoTmMyYPkrGMf9CB11JPrFv2D3Kms7tL0ODZcV/eLywOhjkZmXIOntf2+keBxc9i/0gwdh4ZORlKluMpqFtt/LsNq6wCEx1s3Q7R/BJ//X/CzxActXwgc/QufcmXRVaF31IfrOP2HDF20L2gHUN0FlLSxdj/bPh4E9MI+IIbrFYS+cAl+205yz/NprrzFhwoQ928vKyvjyyy8TlusYyw77NK5Bg8m87iYyvncj4Y0bCC1fillRjohg9B+Ie9JkjP4DuiefdtRc+OD3HXuW1UTGpsarHQuSlgWn3og+frtdEsGbhsz7rk3ykqRgcGrlG24oaCkIlz1nf/yjh9O4YUvUyIbiS89qeeJKA1c6hOtTp58IBFtde2YQylZA8UzcZ8+A2rUJhsFaE33X4YUE5+/ALOkol9l6Dxp+/X+YO7aTfuOt7cerXku7NjqeFIQxahiiGApRCVdCcFWHu8XnR/Y7FJ02G7ZtQMtKoHyX1S7PMEAbwQNk+hG/na3TBAbPQ9yJtWmUjAmQMQFtKoHqxbD5efD5LJ1NhUAj6ccVEV61jcDSyoRsBt/++fgvOL/FUDjiNhh+KLroQWTmEclVOe7odRFJa8CFuCOFvNLDMeVBx03AhFidhq1DWAszoNj63Drr2wxtIzs0x4/kpqG766Gk1srFXv02HHczMnQ2MnQ2WrYWti1Ad6+Cqq2RPsWZ0G8M0m8cDDsY8XbWwwvE40fmXo0edBEs/R+69n3YuRKCHfSqtgkRQRtbffcDpr2e5Yx+XR6idTvgs3uwZYFATasY2JK/oNOvgV1bYPMqtM5auJfcIhg2HsnruE6JqsLbD6Ov3t9qESSKbs3bSsqtRwoq2neI4U59kVAHhxhozlm+4oor2uQsFxQUMHfu3ITlOsayw1cCMQzcI0fhHtlxCGjKdfBnw8FXo+//lqjhcjMvRHIG9YRqLUw/Hpa/C8vesmEFUpEzb0WyekllzP7jUivfDCEDWwqliWEw8ek/8+VxFxPcsQvxuNGwibgMxv79HvwjWwxrEUEzhkP18tTqGGgV7i2GNZGr2obUr2upgpoAIpbB7Du6iMZNmyFgIl5BPAZqqjUBbnU5Nf33YVyDh+A//9K2gmqjFDlLS5HHonBsbMcFOg9Xbkbcbhg2Bhk2ps12baqFlW/YnANqQFp/GHJK0pLEVwyFx6JbFsPmD9voKUDW+YOpeVQJLK6KUSCg4Dson8zThiDDW3qPiwiMPAIGZYBWpm6R0jQhUIGmFYDLjZZu6dzjnyhBMyaDX1UhaFoVmYfngt+d2MJU8zkFaZDtg42V0FSHWbIeo3ikdUzBaCgYbYuNKf5smHUOMusc6zXUlaMNVfD3FBZyat0PeVcTMsymEOacwV1+51VNWHAfdrbw05om9MXH4K+PQFPb6II9d5S8ImTu15DDzkBy9vq9fPNB9PW/Rk6Ipb948/+amgWiaJghZECKf1/3RaKkhnfLmPswTs6yg8M+gEw+DdLz0QX/grK11sacwciM82DcCT2qG0QmY2ffjv6zDtZ9mqDBbM2W5fSbkclH2K1iwog/Ax04AXasTFEoksDwmW22pE8YzaxVb7L7yf9Rv3QVnv6FFJ13Ct7+UcLScyZA9QpS8mumCsHgXq9boHIDbPzAliHEEEhzkX1Wf6gIYPhaPBsaVsJVIYLbGglsbkSDSv1v7sZzyOG4ho1oEdK4i3av3+uOtH2x0dDxpkFuDG3hzDoIlyY1lPgy0SEzrPxSWxCrl+n4byOGjT/hE78BuxZCqG10g7gNss4fSuOochre3YW5O9DO+Q/s2eYq9pN2eCG+/fKQsWe3rwqs9QhVKZ3Ii2GA14v5+sOQUwA7N6SuYFUsYcIh0/L0jcwHj2FPfrbHgFF5sL4CXrgPLv99UjJjGZPMAiSzAHPwNNj2pa3vqapCgxnphRyh0aq+T44n6UJ4Mu2Mrt/3nZ9BWXJpB81o0ESXV8Hm+q7X2ipK0Wf/jM7/C3LGNcixFyKGC136VouhHLcCkX+6y2AeNKHrYxwcUkyP5iw///zzcQs+5phjSEuzKS/LISE0HMbcshEMA2PwsA77Vjp0LzLyMGTkYWhjtTXZ8Of0fFulVojHB5f8Cn35j/DBf+PzyIgB/kzkrNuQiYd1fXw3IweehT5zh/2CDReMPQTJaR9O50rzU3zR6V3L6HcwbH0mdTlFNXtX21ao2EiybWdaI4ZgDEizenS2rqLtElx5blx5mfgnZtK4oo6mDU003P9bMu/8TSuV2usiImh+FpTG6NmMhaFTYiv0E9yEHUXhJH8oaoZg6+Kk5IBh5QZOuhHJsLc1jfjz0KnfgYV3td9nCGmzC/AflE9wXR2NH+4muLF+T09c8bvwjM4k7eAC3MPSrfc2awSMjtI3PrzVVr07Qs0wMnIifPwC2mifp7D9QDFYywqMyLPFUG5GRFAjIvfTBWjFTiSve0JhZb8z0aSv5SjsilIkakcjkpdkdInLC+OO7fq49fNtiUDQ6iD6yW5oDimP5fahJoRM9PH70AVvIN/5Lbzxt/b5ybFiqlUgLeWIleJUPLobxtrHcHKWU8LUqVN7Jmf5tNNOi0uoiLBmzRpGjhyZiE4ONhB47nGa/vo7dFcJADJgEP6rrsNzXPJhe70RERg2wLPn776A+LN7WoUOEbcHOel76OS56Iu/ha3LWwrEtDvYwFrBdsHME5Hjr0Yycrtb5diYdBS89ieoK7f3R8MMIwefl5QI8WShBbNh90e0d9slgaoVllq/V76hAlXbUuNxy/ZAZdsK33uMBBf4J2XgGeij7u2XMct3Y+RHcgldvujy8jOhrMaeKq+GwPAYW5mFW7WwShLpNxL1pMHmhRAOJiY3YwiM+xaSnny7vWjIgNnolG/Dl38i2iKBiOAdnYl3dGc5rwZkDoEDb0eMKDnaSXrqY0UMFzooknaTyiL4sfzgZPjA67I/P1sEdQHj89GPn0FOuMpW+R0y5jAoGA7lm+25f4iBeDPQyppIznwrmeVBtDwAeZ6E3z+Z823E13metjaWQ+kXCclvI6c6iH6wq62HPF42LEPvuABkd+IedROrt3Q3IAee3asW/B0cCgsL+b//+z+8Xi833HBD0jnLMbsad+7ciWmaMT3S0+0rk+8QP02P/YPG//vRHkMZQHdso+HH1xN44ake1Cx1+L0GD902gIduG4Df63jQ7UKGT8e4+iHk2n/BnPNg+HRorigqAln9YOJhyInfRW55CePMH/VeQxnLay6n/cheQ1kM2O80ZNj05GUNOcMq9mVnVRsRKK9s/5pN0yrylQrSOp+liQiuXDeZB2cRfP+Nlh0ZQ1qK2LQ+3u2Cgfn26DYwH8mLwQuiCmalPWNGkJwBMOEYyB9KLJ+xNrcKcqXB8LNh+k9SZijv0XHocTDrFvBkRv0sOjnT+m/gITD7TsQbZTFQQ0Bqi0S10cjthczcpPLxO8Wga2PGZSC+xA29rhARJN8PJe93fbBdY7rcyMk/tk+gmshZd2H88C8wfj9rm+ECl8v6f0091IYSu23vdwEy5bSuj6tYk4DwtmjQRD/enZyhDNaidNkOqArtqZKemBxS7EkUSMuCaT2fQubg0JqzzjqLgoICHnroIQC+/PJLbr755oTlxeRZvuSSS+IKqb7wwgvJzu69XrN9GW1soOn++zrc3/SHX+I5/hTEbWdVVod9HRk4FhnYUhwlFVVsuwsZMxuddQZ8/gxJu5sMF+QUI8ddY49unix05CWw5k+2yEPV8ig3RDFQ1LS17WwzIoL6unZpiCEYmS50yWNwyjnWxoxhUBo9h1py0tHGbNhVnbhy/bKR3AzIHN71sdoE2N/jWdxeGDoTHTAJyjdC1Q5oqGrnoQvVhKhdWcOut8oZ/pcn8fa3J8RWTRM2L4XNS9EdayFQDy4PUjgMBo+HUbOQ4gPRuRNgxT9g21utdIvyfTHc1rK7Jx28WdC4Bb64A80aCdmjoOhAxBPx6uneqQDdQF4xVJWTEteyO4bFBK875cWWVBX61aOhpj0VwFONFI+FY65DX703eVlzv40MmQZDwDXlIHTbevT9F6Fil2U4ZufD/nNhzVOw8UMriqmz9BGx2kPKnG8j06OkAkSjcl3XcrtAl1dBk02ROqoQUCuUu4vFxw4Ja0vP7pRcfoqc+kPEn1hF/q88JrYGkcU85leAuro6rrzySu6//34ApkyZwiuvvMJdd7VPM4qFmIzlZss8Vv785z8npIxD8oS/+Azq6zrcrxVlhFcsxT1lRjdq5bCv0VcN5WZk3nVWzvjS1xMXYrggqx9y6R8Rn32TBcmbjg47HzY9kpwgVWhsgrK2/YG1JohurAOPCxmWlhKvm7iNmEwTMQR3eAe66j1k3KGQO5lOjZqiHCtMs6QyfqWKc6BfNqQNQLy5MZxgv6HcGvH4oHgcFI+zjJ2mWvjgOaqWlLPpkd3UrW9Z4Mh/fyH9zjoxqfE0FIQPn0DffxQqdlrG2578TEFFLMPEl44ecAoy92Jk2rXohEtg61tQthQqV0EgkjtueMCXBgSxZuIhCLS61uq2wI43YfVDaP85MPIcxJ3C3OFor1kVvP7UeZb9XUyhDLG8oylGRKy+zdveh2FHpXy8PePOOA1Q9NVfR3Jr45iJR649mXsVcuD5bXcNGomcc227U3TsTNjxJbrkGVj3jnWPMwwgkterYfBmwORTkMmnINmd9brfi6aKro/pBK0JWsW87KYmhPqTyHUPaWSmb/N3QAyYfDQyYa69ch0cbKC4uJjt27e3+d40NjZ2ckbnONWw9zE0GENYZSDQ9TF9jMaAyVV3W2Hnf76puNtDsXXXRnTxS1BbBrkDkOnzkNw4fqgduhUxXHDm7Wj+YHjvn9bGeHPvhs9AzvgJktV178649Suei7rTYcM/I6HScXjFmr1YdfVQ3jIB1KCJLq2ELQ3WvGlE7/AGqALvPoSMOxRJH4Bmj4PqNURbAhcRKMxGM/2wvRwaYriX+T0wqABpbkE14JgYNeu+e4iIgD8LDYbIHuZm4vXFrPr9TqpXWj/uMd3XO0G3rUIfuQ1KN7HnWmo2LqwnLZdYUz188AT62Xw442ZkxnEw8lTrAWi4Cdb+B7a9SsuCQrS+r5F9GoId70LpJ+jYc5D8bkqkbEYsQ0Pdknx4bGsMoKvfGU/qvcrNqKnIjre61VgGkBmnWws+L/wMKrbGXpAqqwg56VZkyPTYxxKBgVORgVPRujJY/z40VFgedW8G5AyEEYck5l1PMlxZN9alJjdeSc67rFgeZredqT0GDJmCnPpD+2R+FTG1TSHMbhvzK8BvfvMbLr30UkpLS3nsscd4+eWXGT9+fNcndkDMxvIZZ5wR03FPP/10wso4JI9r0jRrJTvcgVfE58M1bmL3KtUNqMKmHcE9f3ffuIq+/if48N+WpzGigL77dzj2O8hB53afMg5xIYYLOepKdMLh6Au/hG2dFDGzTrAM6ow85KhvwcyTU+phl4ID0MzRsP5hqFnZ9aS7eX84bOUot1pF1eog+tHulhBBxer7miL1NY4fZBFg+wp05xqk/xgYdAJUr+r8nDQvjOqP1jdBZR3UN0FTqOU98Lkh3Qe5GZDmbVVcLB0KZ8eomI/UVoZqi5phCDRZlcN9MOG6Aaz8zU6qljeQMWNy4nJXfYw+dH3EeI3xtZhhaKxHH7kN3bUJ49hvWrLCAVh8D1Q29wOPdYHJhHAjrHgYHX4AMmhKvC8jIUQEM9hkXeZuA0I2Rgtkebv+/ruMbqs4KYZA7TpUw4h074KEDJwIX/8nrHgDXfAElKxuVipiPNOyeNJvBLLf12DSsYjHn/iYGQUwxVrAseUd9iS+eKiqsKU+dbeKxnDixjJYn8Oc6fDBIvZ44ZNh5P7IuXcm9fk5ONjBz372M2644YZ2tbJGjx7NCy+8wLPPPsuXX37JrFmzuOyyyxIeJ2ZjOScnp83zRx55hJNPPpmsrKyEB3ewH6OgH55Tvkbw2cfbe8pE8J59MZLpfGa28cV8y1CGdkaWvvJbKBiGjIlxcu7QI8jA8cg3H0R3rEIXzodNi2DXxrafZ3YRDJmMTDkGxs5BXN0TlCO+fJhwHbrpFVj7D0hPix7WaZrQFIDaWmhoG2qktR1UZ60OpcTYt0KK4zRKRGDTF9B/DJI/Hc3fD8q/oCtjTNJ9llEcK6MuQdwx1t8QA4xsMG1sWdUZ1eV77tlW0Shl3DXFrJ3fj/TxoxISqVtXWIayGUpgghw5/rW/oek5cMjZsPwPEUM5kcl25JyNn6LedKQwsdcUL1K12/pfBPUaELAhac/vQrwxGC/dna5iBqFuu1WNvJsRtxemnIBMOQGt2Q0lK2H3xkgetRfyh0H/cZZHuTem8eSMSDxfuS5keW9TRVATrxMiQGEeMn44WpADby+AqgRqBxguK0rj2GvggLOcVqQOvYKf/vSnfOtb34paWNrr9XL22Wdz9tlnJz1OzDO+vfOWn3zySe655x6nPVQvxH/drWggQOjFVgWMDAPPaefi+9Z1ParbvoSqoh/8u+MDxEA//I9jLPcRZMA4ZN44ADQUgPpI0SVfZo8XMJFhx1lhh8v/beXoeTyRibha3rJQ9FxQNRX9vMIylPeey9UErdDNVORzNsRrLBvojpUtHqLRl8DC1RCqw56KJAIFs6DfAfGdZuSDWU2qvctqmlC+s802MQTDA6O/MSChibIGm9D/3GYt+iQbYvrCb5FCL+z6NCk5e1j3AZrd39Zc/2hoOIyWlYJhvX/iMlAPVlRFongNyIyhQKYhPdPHsHZLjxjLrZGsfpA1B0bPSVXwiv3kjUn83KoUdRVoRkm8FZQCU62FKSnMQ884Apauh2XroL6x87D51m0hpxyNHP51pKBnr619CqfAV9IkVS0+Dpyc5X0Q8fpI//HdmN+4ltDnHwHgPuhQjCJ7qqk6RGisgfItHe9XE7Ys6T59HGxD3F7ILuxpNdoy4Tyr8vDShyEQjC3Hen0tVHcwkTOB7Q3owDRbDWYRsYrdxIMZhtqW4lDiyUYn/wC+/D8IN5HcL7xA9hgYc0X8nhnPYAhtSGLs2BDDQLe2b10jLsFVtQxKl0DxtPiEvvcolG2xJy9FFN38OOKyKSw9HIJNn8PYw5OX1QFqmlCyBeqaIMu7Z8FB3AYqJOZhTndDujvG66iHzMRQ97Xm2qfIGAhZw6BmM3Ff48ksvsSKqeBK4Jrye2FES7s5cblg2hh0ymjYshO2lEBpOVTUtL1XuAWKhyNTToZpJyDpOVGEOzj0PN0RqeIYy/swxsDBeE+JsW2CQ/wYMSzzxnKMwz6NqkLDJqhfb7XVadwBGgAMcGdD2hDwD4bMiYi7Y0+biMD4s9F+k+DTe6G+hM5yatVUdF3n4Xa6uR5jcPvwpURRVagPJTZ53Kunr2QMQafeCst/A027SdhIK5hlGcoub/znGvkgWaA1iY0dA6om1FRARUn0A8QFq+fHZSxrOGRVvbZr1b0oDXHZuYKvsHs9OuLAlOU9imFgLltgrbM0hJD0Fm+wuAzULxAyYyv65TUgw4PE0irKGjwxpe2gN4Y49wFEBB11Ciz6fSJn266PbUwdhbii9K43BIYNsB6qaHUlLFtk3WYNsfb7QWY7dVdShlPgyxbGjh3bpcFcXl7e6f6ucIxlB4cEEV8GOmQqbF0a3ctnuGDcod2vmEOvQDUElZ9C+fsQKKVlQtXqxypUCY1baY6x0+zpUHAY4h/UoVzpNwk97gHY+h6sfQ4q1jbvadUKSGFXU9c9P2tC6KY6GJpuz+qsArsTaM9guCGnuN1mSR+Ezvg5bH4atr+CVYK4K0M8soDgSofRlyLxhl63ESXgHQdNnycuo8shDHTVgo4P0DBs+RANB2I3+NctgJoyexQEGJxlf291NWH3ehhgf8FJNU1oaoCNkUJxAROVEJLmbvEwi4DHhbq1ZdJqtkpXMGTPQ3yuVl69TrzrzX1688bB2NNh6X22v7Yuae5p7RA/Q+bCqkehoYy4oln83bA4Em/0jwgMLoKZ42I6VnbttArStaaxAm0oR9Ly4xvbwaEb+elPf9qurpbdxGwsP//8822em6bJG2+8wdKlS9tsP+WUU+zRzMEhDkSgONKSpDsX1uXwy9F/fzfaHkCQQy7sPmX2MTQcgO0fwe7lUL4aGiLeRW8W5I+zHoPnIN7eV7BOG7bC9kciRvKerR0c3TwpC0P1F1C9EC2YC/2ORYzouZHi8lotYoYdhTZVQcUaqNkK4QC4vJA1BH37LXA90nFl/Gat1tQi/Xxomiv5cOzdjRBMYOXaDCEDJ0TdJS4fjDgP7X8UlLwFO9+BcKSfqTT3WI0sEACkDYCBx0DhbMRlg9fSPQhCW9HQTqiptvLD3W7IykraeLRChTfB9nVdHBiGyg1QEMPEF2DzUiu33bQpPDTHZ3+omwjU7rZXZrNow8D88LW2r78pbEU+tDKYLTXEMoQ7CwIKmtBvOow6HEq/gIpVkftR84BuyBkGBZNh+DFIzgjUDMEyt9U6q1vxomoiKfZua+1O2L0CKtZBUxUgkJYP+aOh3wQkrSCl46cCcfvRWdfDezfHd2JODDnsyeDxRFIg4mBQPzj+wK4LcakJdXVQVhp9f8UaSDswvrEdYsPxLNvCueeeS1FRUUrHiNlYPu2009ptu/LKK9s8FxHCXUzMHBxSgd9r8N+fd+yNSxUy6gA446foi/dAU11LsYyMXOT0nyD9x3a7Tn0dDTXCysdh3QsQrG3x1jTTWG4ZhhtfhUX3o0OPgEkX9ZrJmZa/DyXPEXdonmlCYz3UN8COR8F4Di04GPInQP6YDlf3xZcD/WdZj9ZsfRDCMRhLYUU/L0cOyEd98RvMzYaHljd1nB8dCyP373S3pBXB8HPQYV+DhhKo2whNZVa+s8sL6YMgYzjizU5ch73QpjpY/Aq6+GXYvgJCrV6fx4MWFyOTJsHESYg3vjBvNU0INsHid2I7oSJ2Y1l3rLWvJlmaO/bw43hQhZpd9os1w7B5Haxd2n5nwIRQANLcllc50mos6hXfHKWRlgczLodRx1iG9cgTrHGC9VZ+sBjgzUIM916nu9HMoVCz3vbX2CGmwms3gcuHDjscxp6CFCRRuGovVBW2fQyrnobSL62Ne7ep0jAg6MADYPwZSLy59j2M9JuCjj8fVj4S+0l+F/iMriN5EsFwwZRDYUg+fPZi1/d0twumjIIDJkYNv26DRiIp1q3saHCo3ZaI1g4O3UJ3VdaP2Vg27VqhdnDYx5Apx8L4w2D1B1BbBrkDYPTsbmsvtC+hu5fBp7+E+l3sme1Ha+fRvM0MwqbXYet76IyrkWFHdpuu0dCyt6D0xeZnsZ1U3wC7dkNFVUuOaXOk5/ZNLbJzR8C402DYXMQdg8e0Lo4qzo0m+nE5MjkbCv0xh9xqZLKlpQ0Qb1GvZsSA0QchuQNiO1wMSB9gPVKEmiZ8+iT66p8h2EDU0NtgELZuRbduhTffhMPnwsyZsb1vpmkZ3h88b4ULd4kRX+GmhprYCsDFQioM5WbC9npd1QxDbQ367osdH2QCdSHUCEHRcCQ9Eyo3WveSZjKKoHAiDJ8Lgw9EotSeEE86eLrI9+83A2o20i0laFUhEHk/w02w4Q1Y/yo6bC7sfzXiS24RSRvK4NPfwvZP2+ZkR223pLDjc9j+CTriGJh5JeLtQ+Hh48+3onTWPBnT4SICwzPQVSmobWCGMeaeBUXpaNMH4CmAdSVQVt32uPxsq+r1mCGIJ4a5R3NP+nUrrUXaaIhY74ODQy/FqYbt8JVCG2ph1WfWDXzc/kh67wut7Qzx+GHSUT2tRq9Dy0oxX34cXbkY0jMxDjsROehIqyLn3sdufR8+uStik8RxA1TTMiQ+uxet3Y5M6pnQd61e3MpQjoFgCLZug8rq9vuivfzKjfDJfbDoIfSg65FBXeTiuuMsaBUw0YWV6AA/MioTMtyoqVYqdCsDUFt/PjVBKG+KrUhSJ8jcK5I63060vgp95Car33bL1s5PCgbR11+DVSvhjDMRf8eLGaomNNTCxy9CbWWsWrX34HWGy8aw0FRORox0kEzQBPq+7oWaJtTXov/7NzR2kDffHKWSVYwcciWMOdKKijDDEKi19rnTEE+Mvbi7YvDRsOEpe2R1hQg0tjL4m43Yze/Czi/QI/8PyR+dkGitWA9v3gTBusiGGIz/5vE3vgGlS9Cj7kEy2tcl6I2ICEy+DM0eBov/DOHGrl/z0AxYXWNvlzkxoN9AmHgQlC2zon7MCjhmGpqVB00Bazy/NzYDuZnm7/S6lR2HXzfjFClNHU7rqKTpLkeuYyw79Djm+8+gj//SCkkEcHuRM76LcUTsVRibAibf+7V10//NdUX4vD1YjdQBAHP5QsK3XQGBJivE2DAIv/8Kst+huG77PeJpMea05IuIoZzkjW/FI6gnAxl7epLax4eGamDHE3Ra/Kc1NbWwYXOX+cR7jWL911QF79yGjjoB9r82qtcLQAaOQNcujt97t6MR3dGI5nmRfl7I9qDpLqvATFitliJh06p6XZlsf1GBORcjA8cnKccetKEGffDbsCvBdlFbt6KP/AfOv6CdwaymaRk067+EFZ/G+bkoZMXhSS8cAqvdYNrgua0P2V/cCwCBjEHg2R9CK8Dc2fUpUdij246N6McvQagesnwg2VBdat1TDBfkDYX+E5FRh8Ow/dvk9IrhAr/9BWIkrRDttx+UfWGfpz8aqtZ3MhgtCseEQA28dgN67H1I3ojYxZphqNkGb/zAel8TeQ1qWpFCr9+IHvtbJC0vfhk2oI3V0FBlPUnLRfxdL8jL0CPRoumw/F+w5U0r5UMk6vsgaV4Yn42uiLL4mbDSJsalP7Fay/kj75sqrFmO9B8EQ0ZGyqPEMd9RhaZGy1Cu7UJXDYOvZz4vB4fehGMsO/QouuYL9D8/b7sxFEAf/yVaNBSZdHBMckyFVZsDe/526Fk0FCT8i+9CU1PLxCKyAqgL38d87l+4zrrceh6otUKv7fJgffkgWjQdyY19Upg0O58FM0BMhnJ1DazbmMRgzV6Bl6GpCp1za3SDecQkeCu2MMKoVATQir1C8Aq8yKhIeyuXAZluqE3UIBMYfxgy9/LEdbQRVUWfvsMylBM1bFRh9270fy/BaadZDmHDQMMh2LwKNi6F6gRbWOTHnnsqgyZYBabswFSoC0JmAq23OkMEskZaxbE8UyBcbBnNxBb2qaZpFS8KNmEueAPWt8pR1jBIDXLOH6FwfMqLXXXKuIvhw0WpHUMEaps63q+mFZr97k/ReQ8gbl/7Q9SEkoWw81MoXwXVm6wQ3KCZvLdUTasg2qe/QQ+7vdvyDNUMwdoP0IVPwpYv2u4btj8y80wYObvDBUcA8efDzO+ik78OW9+BshVQvsKqnaEmuHyQM9yqgD57Fvzll7BppWVYJ4XAUecgEyK1HDIHWmOFI5/zzm1QWQ6DhkFBIXtqZER7byOL1QQDULIdtm+J/R6Xl1g0gkMMOAW++gyOsezQo5hvP2qt+u/9wyIG5puP4IrRWHboXeiC96Gyg9Y1qpgv/nePsczShyEQR35tLHz+a/So33XLpEwD5VCzOLaDGxph/aauj4ttZNj6ESx8AGZ9u91emXk4+nCU71Yy5O8V3utzWXO02lDsH19z4aT9z0CO+167wkg9xpevw8p3k5ejCqtXox+/h+Slo5W7oGyHVVgqIQRyhiL+3K6HNsNQuRH1tCo2aAcldWiGx/7WUf1mtjx3FYHRD8xdEN4CWmEdptoysRfDCptWhYoSzFULYfPK9l56NcEMoa/egpz2AGT2XPivZAxCR58Pa/6VmgFUrfDraF7lNseZULsTlvwLZn6j1elhWP8SrH4KGna1LagYVvtuy2rC9k9gy3sw9DCbhHYy3K516FM/gJqS6J7XzQvQTZ9BzkA4614kf2in8sSbBSNPsh4dHQPod3+PeedlsGtrEvdegRmHY5x7Q8sWMdDcUVC2vOWwxgbLQ7xpHfQrgsxs6+H1Wq/ZDENDg+VBrq6AirL47gmGB7KGJPgaHBz2HWKepaxfv56RI0emUheHryIlm6L/oKgJpZu7Xx8HW9BdOzqfrEfypLSpGja8am+IoppQuQ52L4PCyfbJ7YjKj4kp/FoVNm2xOQdUYfVz6JCDkeLpbfZIdgEceBx88oo9BrNHIDdKLqzXBbkG1IWsasMd0bwolj8YOfEGpIvq192Jmib6+p/tFfrRJ+jITBsMTIVxp3Z+RN0uWPMSrJoPTdXW1ZjjgUqbivNsroGRufbIAkAgaziSPWqvzQa4iq2HhjE/ugvCleDxWveTYACtKIWK0q4XH9SEYAO69AnkoGts1D0Bhp8E5Yuh7EtsXRRsDr+u68Sr3PYEdPmTNC5uwD1hJq6RRciyP0HF6laHhFvJttsLJbD0EXTIoSldyNSS1eh/v91SvT7a70vztuoS9F9XwAV/RvolP8eV7HyMWx7GvP8mK90irpMjC4lHno1x7g3ti4QOnG15tve+hkJBy9OMjZWrxQUDDujU6+7g8FUh5tikqVOnMnnyZG655RY++eSTVOrk8FViwMjoBSQMF/R3Fmf6KtJ/cCdGoUDRQOvPTa8TvZpqsgq4YH0cxbaSoWohMU2Ad5VZnmXbMeDjX1lexb33fO074N7LwPUI5HlgkB+GpVmPgX7Idlv9ZjtieHrHE1xDIMsDuV5Ic1ljNB8qgMcN009ELv0TcvWjvcpQBmDD51Cx3V6ZQRPqbQjF9OXC8OhV3tUMo0sfh2cugS//C02tchCLfHF3L+uQxhBUNti40KMw8pzOj6jZCSvfgjVfwPJPYNnHsHqh5bGL1UuvYVj9MhqMo5J4ChBxwfSbIG8Ctn0ozYZyZUOc9reJ+eE/qLnqYipPOoH6/75HOFrtgZSkWCtUbYSyVakQbo3QUI0+cZ11jcTy26Jha1Hl8e+jgQ6qQseJZOVh3PAActGN0Fy7oLOPvfm+WlCMceNfcF34Q2Tv+zbA8GO6r+CWhmFUx150BxtQWop8ddfDicJOiJiN5d27d3PnnXdSWlrKqaeeyoABA7jiiiuYP38+jR1VnnRw6ALjyPOir/qaYYyjzu9+hRxsQWYcDP36W3lS7VCMky+w/iyNMXw5XjQMJV90fVzSw9RDqDKGAxVKd6dICxPqSq0Qx72QfgOQS26x7vSFXpiajeyfh0zIgqFpMMBvPYalWW2jDsiFCZmWMd2afl4kL4acVZdAuhuyvZDvgwKf9X+OB/oVIsNmdFu+Yjzoqg9SMwmtTbYAmsLs66JWZ9aGcvjfd2Hh36xCXnvdR8Xngv4xtBiLhWyPZXyYaoPBbMCAuUjB9E6P0pUvxFe4qCNCjbDujeTlJIm4fDDzVhg4t3lLYoKa3/9AGCrrE/o8PMMj11NQaVpQQfWf19O0oKJtG5ZU5TaKkdp785cvWIW84olWUhPqymHZy7aooGYT7J6PDF2FfOco5OTpMKQAPFHuMWleGFuMnHsQ8s1ZULADNaPPqcWXDUOPtOd70SkGZA2GwqmAlfutmz5Blz6PrnwVrU+w7oKDQx8l5jBsv9/PySefzMknn4yq8tFHH/H8889z0003cd5553H00UdzyimncPLJJ1NYWJhKnR32IWTEFOSyX6D/vdPqDQrgz0C+dgMyvovWOA69FnG5cd/6e0I/+jrUR9rCGAaEw8ic4zBOOs/aVr6KlC11BqrRhjIkrSA18gEaYwx7q6m1+vJ2gpoKjWFojEzy3ALpLiSWPrdiwKrnYXD7HH8ZPhAOHgRmQ5vJsIi0m6+LCJrjQfK8aF0I1tSB14DhXfST7Qo1Yenz6AGXIC6bC0XZwdZl9uZ2N9OYpMyxpyKDDmy3WevL4H/fi/Qj74QCn6VDRRJGu98FIzMRBKrrICcTq3JZIsaeAdkjYeylXR+6/i2b0jME3fAOMr7nvWTi8sLkq9Hi2bDsjxCoIuYK+s3fXQVqGqApsQJuIoKrf6sCXyZgKvUvlRAqaSL9hGLr3rCXEa6NYShrstIt6kLWeQL4DMj0WAtiOTHktatC2erOj0kQVdMq5pXgb4oueBKmn57Ugp42rIeSJyFcCyjiMWDqEGTqEOv+W1kPDUHrvcv0I1l7LWjVLID6VWjRmUj6qPYDTL4Etn0AwXpS5yY0Yb/vWr8HS59HP3kIWhvI4kLHHIEc/r2Yqoo7dIBT4KvPkFBlFRHh4IMP5uCDD+auu+5izZo1PP/88zz88MNcddVV/PrXv+bqq6+2W1eHfRRj/+PQ6XNh3WJrcjRqGuKNv89lTqbTLqo3IWMm4f7bK5ivP4OuWhLps3wCMn12pLdpMFLYK4XUl0IqjeVQTWzHVUfvI6uqUB2Ekibr/yi/Y+ozrJDafr6ODWc1rV6m4SAS6bGrZhj94Pew7Lk9nohYJoFiRI5Jc8G0bDAVURu8wU01sG0xDO1lIdgA5VtTI7ezHO6uGHUCzPpWu80aDsDrN0P97i6NSRFBB6WDuxF2xZrX2opsj2UoN193IROqaiE7w4pWiNeoyJ8Mk7+PuGLweDdVxa1udBQaKmySZQ9SOBM99E+w8wPY9BLUbozsaFVcC1oMVhFrktsQsIp5JTnfNfwu8AoE2goKLKjESHORdkThnjG0PgSb6637UzRCYagLQ0kjeA10UJp1r+rw2lCotTnloZmti6Gmi77BHaJQsRl2roQBExKTUPsllDzRIm8vRATyMqDTbkxqGdo7/mEZzFnT2srw56Ezr4FP7k5Ix64RGH0q0m8S+tk/0Y8fjKJiGNa8ie5eC2f9EfFlpkgXB4fegS1lSMeMGcP111/P9ddfT1lZGeXlToiGQ3yIxwdJeJLTfAbP3DPYRo0c7ECyc3GdcVn0nanw5LUbw6b2OR0Rq+ervn0unDaGYUNd162XmkzY0gDbGtDhGZDvjT4R1TBUbYL80Zah/NrPYMO78enZij1Gs0vsqYorBpSu6p3Gclz9ruPAiHjRmwv3dIUYVgXaWd+CUSdE/5wX/xsqNxPrByIi0D8NzfLAtnrreupsfDWtz3xwenSjJ2RCRQ1kpIHf0zxIVHHa/I8aaNrhGFOvsNo9xYKd94dwAgsFKUZcPhh0JAw6Eq3bBlXroHodNJSAGbTC3ncutt7vYNjKT7ZzfEPQKNdQ4/tleMZk4urngR2N1jUT63c/YFr3tLKAVdzO28Fnnar7cnWJPTISMJa1bmXEULbDcxeRUfokaniQjIltdw8+DHYvh3XzbRirFWJA/niYcglavjG6obxHRRMqNqOf/QuZc5W9enxVaM4j7u4xHeLG9p4dBQUFFBSk0JPj4OCwb+Dytvek2I0nyfDhrjCiFGGJxl51HbQqAGtq45tXmcD6OqgKoiMyohtSVZstY/nDP8GG9+IQ3gU2Gcxats62mlO24s+ExhijBOIhswCO/Tksewy2fYIVvrzXNd/83OWDkcfCpLORjKKo4rRiPSx9jEQ+CMlwo2OyrKJjFQGoD7U1nN0Chf1h8mFQ9mrLYklURYDaBqhvhDQf+NxWmkWra1JNMLfVEvyinNCXldDwGTL8GdJ/+ReMQZ236bH08UdCTW3A27tDRSVjEGQMgoEtLZW0rhTWXpSS8VQVDXYwaxaoe3En2YfnJxaNAJYXenkVOiHbyp3fG2+KPJHhZGsEYPWWjhMNVdtoKO9FyZPo0O8i7pw9m0QEnX6ltaC04SWbBhLIHwdzfoa4fJhfPtf177OasGw+etDXo/budnDYV+glDS4dHBy+aogYaNYQqN6YogEMyIphUp4Mvhj7t7bKE9LqYPyGcmvKrMlcVIM53Ihu+wKWPp2g8A5QtcJuk1nXUBMCPVuVuEMGjoeqEptyZCOIAYMmIoUTYe5PLeNn5yIoXwPVWy3vodsPuSOhYAwM2A/panFn+TMR729iH4SIQIbbehBJA1BAmkP0G2DGcfDma7EJNBXqGqHOktFsMDd9UE7ws7J23lDdspH6ay8m478vI74uQrHzRsCuFcl/JuKC/D7YWSG9ENzpELJpwaAVZnmw4++ygjfdSNxQbiZgwspqdHIu0rrKvrggb0xysjvCZ8OiSJw5uKoKu54FtcFQjzpAGEqfQQdc0uZ+L2KgM6+G7MHw5UPWcQl9VwzAhJEnwNRvIO7I93LLgtjuM4E6KNsAxeMTGNvBoW/gGMsOfY5waQlmRSVGVhbGgAGICE0Bk5v/aBW7uevqQnwdhX859C4KJkDNltR4l7OH7snfTRneIhA3aBdhhZGCORoyYV0ShnIzZQErn7Rf29V8ReCtu2IP+42V5oI/kXlVgkIg1Z9HgsjQKeiKt2M/wcCq+u01wGNYhqKJZSA0haHBup5lSEufb8koglHHWo8E0KYa2PCmrd+VdkXeRGDbAiieYVWqj6uiMBA2MWvDBD/ZFf0aD4fRndsIvfESnhPP6Fy3CaegpctiH79DvcLIhJOTl9PNmNu3Ydb5cXnqOvfyx4mGldD2jjuYuLJc+IbZVEW9yYSt9TAso7UCUDDWHvl7M2RaSz/3RHB5YdCU+M5pWA/1axIbLyZMaFgHDWshve0ig4jAmNPQ/vvD5/dB2fL4Uj7UhPR+MOt7SNH0vYaNI1Q+1elO+yqR4nrdPqZD3DgWhUOfQFVpeGE+u884jdKDDmD3CcdSOmc2u+edQP3jjxEOhVm8ponFa5qcYn99iSGHpSgMW2DoUSmQu9coYkDacLpsA+ONGIlb6iFk0wW6qa59KGV1CdSW2msoNyNi9VNOFMOAnEH26WMnU4+LrR2LW6wFiqEZUOi3FizSXJDmhnQX5Hqgf5q1P9eDTjysa5mxsvMLyxudStSEzR/AmFMSvobCm+s6XwwyDEIfvdu1oOGH2hA+LVAwGuk3Lkk53Udo1Qoqv3U5ZUcfRv1Ly201lAHEJQSWdVxYMW1sRof7EqKk0SoS1ozhiVq13w4kPQ/GH2V5r+M+2QWTjo+/WFXVx6R+Km1ExomOZA1CjrgXjvyN1VqqdXqQuKwFXXHT8jslUDQdDv4JnPBge0MZoN+o2N5HcUGuUy/GYd8mIc9yZWUlTz75JOvWrePGG28kPz+fhQsXUlxczKBBvXQy5NBnUdOk6kc/pOGxR9v17Q2tXkXVzT9A33wXjJt6SEOHhCmcCpkDoXYHtuZ7iQuGHY2qpr6vb95sqF/b+TEZ6WhNA+yOPx+uQ0xgdxMMaFU5ftPn9nuVW5OMd9kMI0Up8igliWQVoJOPhqWvd+yVyvJAvteabzZfU62vrdZ/u8QynF+9ET3sZqR/nN6qaOxek/ocf7Dy3oumWY9dX8Z5LQn0mwq83vEhSkwyxeVFJ5wCix8h8XuDIpPOTPDc7qfpvXeouvZbVps5VZpW1GAe2w9Jd9lyH1NTMSuChLZG9yy7sly4s1IQcFjaCMMzrXvT8KOQVOUsAzLjDHT5q/GfqGFkRufRDu1OCVVDfQrbH+7BhPrVaKiqTe7y3kj+WMi/Dt3vO1C9CSrWQO1OMAOWAe3Ps0Lgc0ci7s47jsjkU9F1XSxqiQtGH4ak5SbwmhycAl99h7iXw5YsWcLYsWO5++67uffee6msrATg6aef5oc//KHd+jk4UPeXByxDGcDc65seed705hvdrJWDHYgITPsmdk42FNixOJNXsmbzincSC06/mtqV62yT346syeDqYvKXkW4ZtnZT2iJTMwZCybLUGcpgGYSJztnFBYNm2KqOHagZRis3wMRp7Rbj9pDvtTzKrQ3lWKjbhf7vBnSjDcXWytem3lAGa4ya7TDnNsgdQVzThEEH4Tr1xi7km7hmtu8dHQ2ZfgEUTYzN69/+bBh1FIw6OoFzu5/Apx9TddU3oKmppTp7WKl5bZd9C34Cda923FrJ299n9Xu3m91NllyXD6akpmhZMzJwMhwY/xgy5xtI0ej4TmrcROoN5VY0bIrpMDHcSO4oZMTxyJRLkWnfRKZchow5Dek3qUtDGYAhM2HoAR1/98QAlwc54NLY9Xdw6KPE/Qt03XXXcemll7JmzRr8/pa8lhNPPJF3340htMrBIQ60qYnav9wfw4FO7HVfRQYcYIWOJTQhbotiULctxJd3L0JDYTQUZtf8t/ho9jnUb0xNL10RFxSf0vlBuTldt4hKhIAZCcUWKJ5pv/xoJDJxFxeMPtwKk+wlaM12dNFf4Zmz4ZVvI0v/CgOj5GrmeiCnuQVUnK9dTdAw+tbP0ZKlySkcSEG17g7HqkM8GXDkvTD0UGtbh99PsT7fcWfCwT/CNXQkrsOOjr7wYBiQm4fnuFNjUkNcXuSYn0O/sfG/98MOQebckPrIEhsIl5RYhrJptvst803IprE8lLQRq6o0fV5JeFvH+cruHLftYd+A5c1qDMOsq5H01HdLkUOvgFnnRp508rvSvG/2JXDQJfEP1LSd7stmNCLjdQ8iBnLiHTByTmSDiz3fdYC0POSM3yD5w7tNJweHniLueJvPPvuMBx54oN32QYMGsXPnTluUcnBopvGtN9FI9ILDPszMa6BmK1SuTdwzKgbhJhcL796JGWjxwGk4TLi2ng33/p1Jf/ixTQrvRfYMqF4EtSuJGufkckF9ijy+dSHI94G/CMv12RsXjkxk5nk9rQQAGg7A0n/ByqcihctaPhfJdqMD02F7pAKx14Bcrx2jou/cCWc82FJtNm660eiLGJji9sPsm9Epl8K6l2Dd/yBY23JcWoGV3zziWMSf27L51ntouOlbhL/4FFyRaUY4hOTmk3bf35GM2MNwxZcFJ/wK/eRPsPrlyOcV7RqPXPtuP0z+GjLjIqumQB+g4bFH0IaGdpFT3vGZeGfk8uW1axl+cSHZE9ISMmZVlcDyGhreLev4IAEjI4Fc31jJOwAZ0T1efhEDOeIadPBU9LNHYduSSO5u5L1T03oMnobsfx4yKsEc6kAJ3RfXakKge+fY4vEjJ96Blm1AV/wPakrA40eGHwwjDkFcTo3gpDC1Bwp89cb5Qe8n7ivd5/NRXd2+OMTq1aspLCy0RSkHh2bCWzZbhka4G8IPHXoMcfvRw/4PPvo5lC5KRAKkF7Hwl9uo39E+3FlDYXa/+n7SenY4ugg64Guw8XcQrCLqBCqUoklVSGHapUhjAE2irVBcxGWTC8w8HylMUbuYONDa7fDObS058lEiUiTfh3oM2FbXrtp44gObUFcKXz4BMxIMQ03Lw87FEFUluLWR2k8qCG5rxGw0EQOMDDf+Hc+S+fX+uCK/6ZLZH6Z9HZ16KQTrINRo9TB3p0f13EpmFml/+DfhRZ8Reu8NCAZwTZ6O+4jjEW/876m4fcgh30dnXgZrXkGXPwv1u9oelDsUmXg6jDoK8cQQZtpL0GCQhkf/3T7FCMiY15/GbU0Ey0Os/cMOBp9ZQPHRuWhY27Zj6kh2ZGLc+FE5jR9VdHqsuCR1XngRpGBy18fZPeyYw5Axh6G718Pqd9D6CkCsCJdxRyAFw5IbwExBak1vGi+CFIxA5ny7R8Z2cOgNxG0sn3LKKfzsZz/j8ccfB6xJ4ubNm7nppps488y+U0jDoW8gbk+7CW0gKFRUu6hrMFAg3W+Snif4wg3g7p2taRy6Rjzp6KE/h/UvweK/RSr/dmEYNBezGnMaTLqI0K0dey/dWTZXed1bFXcWOuwq2PTn6AazpMjrmzUAxp0OS56wX3ayiAHFE5ADEghxtBmt3Q6vXxcJZ+78c5AsDzoqGwI2Ljyooiueg2nnIUYCHpmCMbDts6QXQ9RU6hdWUftBOcEdTe0LtpUFCfz+b1T/4UHS5p1I1re+iW/6dCBS/d2bFVOVahHBPeMA3DMOSErfNjLTcmHqOTDla9BQaX2WzTr5c/pEyPXeNL3xGlpe3m67e3g67v5+wqWRvuoh2PJYGRUL6xh8ZgGZo/xo2Cq41/p1NxvIYgihzQ00vLOb8K6uCwtqqlOZetDLL/1GQr+RKYjN6ObX1EciJRxixPEs9xni/ub96le/ora2lqKiIhoaGjj88MMZPXo0WVlZ/OIXv0iFjg5fYTwz92uz4l7fKGza7qGq1iAUFsJhoabOoGRrmN8+dzzPnLGBNJ/zg9JXETGQUSfBvH/A5Eshvajjgz2ZMPo0OP5vyLQrELefgRedGj23UcTal2LEkw/DvwMZUVrVZNrkpdybg76FGC7L89gdXmWI0eYX6D8ROeUexGVHKHPiaKgR3r7FMq5iDfNPxaSisRK2f5HYuQVjk/58zYBJ2b+2UvHkDoI7I16qaG+HaUI4TMOLL1F60qnU/vfRpMa1GxEDSc9HcochOUOQtNw+aSgDBN57x4qe2gvflGw0rPiKvGSM9u+ZrdWuaWTlXdtY9tMtlLxRBW4DFTDrQoQrgwTX1tH4fjlVf9tE7ZPbYzKUAQiD2tXWbm9UIa9/amT3JK5Mui89QsBI7YKvg4NDdOJe3s7JyeG1117jgw8+YPHixdTW1jJz5kyOPrpvVJx06Ft4pk7FPWEioVUr0bDJjl2eyDy99Q+U5bHbWeZhxIz9ekRPB3sRXw6M/xqM/xraWA4V66CxzJp0ebMgdxRk9G83QR561fnsmv8WZW9+DK7I7DJsUnDEgQy96vzu0d2dhQ75OlQvhJLnIFyP1dcyG6ob7HUuiyCjIpWFC7upLVNXHihxAQqzLkJmXYi47I320MYaqN5hGb2+TMgZ2HVu6pKHrTDoeN78KGGxSSMG7F4Fg/eP/9z+063Q52B9QkNryGT3Q1sIbIycH8tbEUl/qbj+RggEyLzk4oTGdugYs7Ii6rXmGZq+x0Ae/u2BrPrpJkJVYat7mAlNu4JkTM5EMqzvV3BTA3WPb0tKl1BNCHeuOzULD4PH2y+zp/ENgLpl3Teef2D3jeWQepzWUX2GmI3liy++mD/+8Y9kZVnhV5mZmVxxxRV4PE7Yq0PqEBGyf/wTyi88n9oGg7DZ0Y+4oAq7HnuJgd1kFDl0D+LPhwH5MR3r8nmZ9cqDlDz1KiXPWe3Eik89iuIzjsHoxnuViEDOfmj2NKhZCuUfwNBdsKbExkEMGDkd8UYKRuUOtVqzhLspr81wRQznSHi5muDywNijkelfQwpG2jaUlm9Ev3wO1n9gFZlpjduH9p+ETD4JRh3WzjjXyg2w5rn4B03FpEIVLV+fkC9K3D50zImw4umEiuBVPLPTMpQTXKypuOVW3MOG4Z97eGICHKIT6am8N67+vj1Ga9ogH1N+M4qy96tp3NqEt9BDweE5eLJbpnDeyTkEVtYQ/LI64c84VBHEnZeC+2T+AMgttl9uT+MbRPcVVNTIeA4ODt1NzMbyf/7zH+699949xvKhhx7KokWLGDnSvgmRg0M0fAceRN4Df6X8/G9jzWDbTzVDLg+PH/dTfMsGcW9Q8Xr6ZkieQ/IYbjcDzjmRAeec2NOqIOKG7OmQPR0d1AgfzYP69gUSE0JN5NBzWsYyXOiYo2DVK6kNx55+HpI1AC1bD4E6MNxI9gDLsz1gklW92Ca0vhJ95zew5i3LYx3tdYWaYNsidOtCSM+Ho29Chh/Usn/tCx2f29G4Kcvf1IQ9wwCMPw1WPQ/hGENrIwR3B6hfUJX4uBEq77qH/o6xbCuSnWO11NrLuyyettESrnQXRcd23not47RB1AWU4MoE24wNTEtNUPGgcRAO7Xs1RfxDwfB1T+Et8YI/yYJkDg4OCRGzsbz35CHlxSAcug1VhTWL0e0bkMJBMGEWEq1HZg/iP/Io8n5yG7uv+VnU/aa4WDPkADAhbDZ7uxwceg+Gx4+e+G30ybtsEOaCAaNg8mFtNsukU9GVLyUvvyNcXmS/CxFvRsq/Ybp9CTr/Fssgh86N3WZPa30F+vxN6JRTkcO/axWJ2/h63IsHIpI6f1ES+duSWYTu90349A9xnVf3cUX7Ql7xokpwyRICS5bgnTo1CUG9EzXDULYSyldD5QarRZYYkNYP8sdAv0lWVXCbcY8ZS1RTy1SIoeJ1a8QtZJwzmKYPymh4szQip6uTAI9B+vHFeKdmw5oatKTR3u/30rfRX10AF9yBDI5Sz6GPIoYHzZoFVR+SWg+zAdmzEKNnaz842IxT4KvP4DRJ+4qj1eWY91wDa7+0ngMMHIFx85+QosE9qtveFJ13Cmuvvwttis+r4uDQa5h9Oix6DdYvAjNR72+kB+4FP23X51IKx6LDZsPmTxLvV93ZuNPPQ7ypLzKj279En7nOeo/ieh2RicCXz6OBephxChKnF3YPqSheLi7IGZKcjHEnwdaPYcfCmN4bM2BS91mlPWHlLhc1//gXBb/6pQ3CegcabLCiD9bMh4ZdgLTqvy2RivvWd1WLpsP4M5ABCeScd4D/jK9R97tft9se3h3APSD+ntziEvyH9cMzIYvGj8oILKqy2ssJ1oKJtjzEZ+CdmYf/wFyMLMvrqyMykfImNGDak7sskceuTejvLoOv34uMT7CvcW8k5wCo+ojUGssK2fZVlXdwcIiPuIzl5cuXs3On1RRdVVm5ciW1tbVtjpm6D64478uYf/ghrF/eduPOzZi/vBbjnqd7VYVRd242o+75AWu/+/PIZMZZIXPoW4hhwCV3or+9HMq3J2YwiyAX/RwZMDr67sOuRx+9OLlw33ZCDauP7cwL7JPZAdpQhb5wSwKGchspsOo1kCAJW70usYwMO9EwUpBcv2kRAz38NnjjR7BreZfvUdOaOrTJpoWTcJiGZ55F772nW34b1AzB7uWWt7d6s5WP7/JC1pAWb28SnnotXQKf3Av1u2m5Rlr339a2UQm7lkDpInTwobDftxF/bsJjN+MqLMR37Ak0vfq/PQXVAIKb63EV+WLqpxxdro+MUwaSflwxoW2NhLc3YNaGQARj8Gjcx1+Pa2gB8uWfoKylSJV4DHR8DnxZiaom/zk3n64mhBX9+w3wnb8j+0jBL/Hko/lHQPkbqRsk7wjEW5A6+Q49gmoK1rRjGNMhfuIylo866qg24dcnnXQSEAlZi9xUw+Fual3ikDRaug2WfNh+hxmGLWthzWIYO73b9eqMQddcjKdfPpt+/kfqV6wDwDdsEENuvAq+7GHlHDDLdhN682XM8t1IZhaew4/GGOzkWbVGMvPguw+iD90E6+NoI2S4wOtHLvgZslf4dRv5GQVw5A/RV36Mfd4OhcOus72yddSR3vktNNXaM4tY9S5akGYV6I4XlwEhm3/PXB4YPCtpMeJJQ4++Ez7+Dax/g84WBMK1oaTHa402NqINjUh6mq1y24wRqIXVz8C6F6GpikgzYeuakIh7VE3wZKKjToRxZ1gV9OMZY/Vz8MX9tLhbYzkpck1u+wB2L0WPuAvJHhrXuNFIu/Bimv73QpttgVW1pB0YW2HDzhCfC8/IDDwjW0WETLkIGW51jtDD7oJNr8Hqp6B2G4gLyfXCpBxYXoVqEklN7U60Pjf9z21w/X8Q9z4SVpx7KNQug0Ap9lYGNMBbCHkd3+8dHBxST8zG8oYNG1Kph0NPUN55ZV4t29krM3+Lzj2JwnPmEdhegpqKb1AxjUHg+1ttHUcD9WC4EHeK+uPuQ2hjA433/ozgS89YhWpcLjBNmn53F66DDyft1rswCvr1tJq9BsnMg6vvhw+fRF96ABqqI+GeUSZazcbBlLnIGTcg2V2/jzJiDjrtHFhsV39cgfd+g576W8SXaZPM9mjFFlhto4dGFeoCkJ2Ake8Se0OxxYBRxyBee94/cftgzk3osMPgo99AYwXREpM1YNoeUq71dZAiY1l3fAaf/hoC1a2+D2Yrx2+rBYxgLax6Eta9hO7/XWTwnNjGWPtCxFCOyI5bSdMy4t+8ET36N0jmgPhltMK73/6kX/5N6h/8y55tgWXVmLUhjEybs+VcPhg8d89TEQOGH4cOOxZ2L4Wdn0LFasS9HvW7kZVVUBfngovs9X9rzDCUboKPn4U5Zyf4InoXIi50wEWw9QEI12KPwWyAKwMGXIQktNrn4OBgFzHfhYcNc7xD+xwDhkWtwtmMDEkuXDCViAi+Qa2Lrdi3mqur3kE/fAhK1wKCjtgfOfSbyIB9I2zMbjQYoP57lxNevKDlWgq1TK7Cn7xP3RVnk/H3JzFyk/eU7CuIYViTxYNOg0Wvo8s/gE1fQkWJZeT502HwBBg1AzngZCQ/9gm5Vm6BZc9gn5WkULkJfe2nMC91Ibj65XMdLxokJhEagmimGzHiLJYkgnpd0GSTd9nlRaZfaI+sVsiQ2ejAWbD5A1j1HJQup+UzFwy/y/Z0SiPLvornrdHVz8CivxDXdasmBOvgw1+gky5EJnWeKqCVG2Dhn5PWFTUhUAsf3YUe9WvESM6gybj+JsyKChqffsLaYEL9G7vIOKV9P/nEERh5GuJuv9AhIlA4xXq0HI2GQ7Dgf+jrD8OuzTEN0fUqu6LvPwaHfK1XpXolg7iz0UFXwPa/Q6iS5L50Au5sGPh1xB1fxIRDH8Ip8NVniMlYXrJkCZMnT8aIsULysmXLGDduHG63Uz+sNyM5BTD3dHjr6baJDIYBUw9GBo/qOeV6CF30PPrKPVbIn7UFNn6Obv4Czvs9Mmhyj+rXGwk++xjhRZ93nAwTDqM7t9P0tz+QdsOPu1e5PoC4vTDrRGRWS6urZHIF1Qyjb91leXDssJWb9VATti2AlS/ChJOSFNoBGz5MTRJX0ARfAsaMS6xHOPkJhhx0NZJZlLScqLJdHhgxF0bMRUNNULEeKjdCqBGXaw089XvbxjJycxGf/dE2uv6ViKEM8V+0keOX/Rt1pyHjzoh+lBmGj+9JWMcoAq186jXPw7jTEzg9DGWrLBlVG8mal0va2CMIfL6M4I5GmhZX4puRg3tQWsK5y3sQA9IHwJhzuj629WkuNxxwMlq6Ed7+t7Ug2vrjkQ7+7opdm6F0IxSPiEuf3ox4ctEhV8PuV6DmM+K/AUeOz9oP+h2HGPEXeHNwcLCfmKzZGTNmsHPnTgoLC2MSOnv2bKcHcx/BuOwWTJcb3nzK6oMoBsw+HuPy23patbhI8xm8+afkcsc00IC+GZlUtjb81LSiAN/6A3Lh/dFP/oqiqjQ99s+u5wPhMMH5T+K/6jokI3VhvPsKSXlbVr4IpStaC7P+j7eyRwc66Id/hOFzkLTcxPTrAA3UQ9V2W2XuIUFjWURQnwsaQ8kFr0w5B8Ycn4SA2BG3DwonWA/APzaMce/jmCWdp93EhMtFxgXnJy9nL7RmOyz8oz3CljyIFk9HcqPMP3Z8BlUb7RmnNcsfRUefFHNOvzbVWBW4V8+HxnJaqm6buH2Ca04/0jWMmkpgQz2a74E0dxIGs2H1A551c+J1BzYvi+SMY19nxq0r9iljGUAMHxSdgmZNhvK3oHEjXfdti+z3D7WKeaV/9RwVX0lM7E1xj3VMh7iJyVhWVW677TbS09NjEhoIOK19+gri8eK6/Fb0nGth13YoKEayv6KhspsWQLAh+j41YdtStLYMyXSqUjaj5WXolo2xHdzYQHjVMtwzD0ypTl9lVBVd/Hj0na2N344M51iM9FAAVr0M08+NX8HOqC0lZe1XOkg1iQURQf1uKxw7Hg9zJM9QZn0DJp/VY+Gm4nKRddklVN1zb1LvAwCmSeZFKaiI/vlvibcXdqd8+iv0mD+0f8/XzLc5zD9CoNoq+jV0bpeH6taP4JP7IFBD2wrc4T1/S2SzGIJ3VBaCiQZA/bF9RdsgBrj8MPsOJHt4nCe3YncMIdjxYLhg9zZ7ZfYiJG0kDBqJBkqhZjE0boGmbaCt5sfiBd9A8A+BrOmINzWRJw4ODskRk7F82GGHsWrVqpiFzp49m7S01FXKdLAfycyBzK94bkxHhnKbYxpTr0dfIhSM7/hgnMc7xMf2L6A6Bu9sUoabokufgalfSzpPs63YFC15S/KuMBEBvxsNmRAId27Ti8syfIomIgd/B8nrec9ZxnnnUvXLXyUnxOXCf/hhuIcmX/25NVq5wWrJZJtAEyrXw+5lUNiSNqOhRij5gpQsyIgB2z7p1FhWVVj0IKx8knjCcyXiChLThEY3+CIFFLv8vkS8lf2mwbTvIGlJFlhMdqGlHYJquFcWEbUT8RZBwTFA5BowG0FDIG4w/PtMzrZDAjg5y32GmIzlt99+O8VqODgkRyCo/N/DuwG45dJ+eD0J/AANmNj5/vRcyC6OX+4+jOTlg88PTbEtIhiD7Z1oO7RFN33UYqylkrpdULEJCmxMtfFl2yerNWJYdRjsEOU20OYc5rCC+CwjwgyB2wf5o6FoAjL6GCRvuC1j2oGrsJCcH9xA1Z13JybAEMTnI+fWW+xVDGD9y/Zfs+KC9f9rYyxTuYGURS6oCWUrOj9m0d9g5VPNJyQ2hhmCYJp1nVUut7aLq5U8aXkf8yfAyFOg/2x7DLKMXKgpS15OMxpGMnLtk9cHEBFwOY4kB4e+hlOBy2GfIGwq735heYZvulhJxJMkeYPQsYfBmvejrtrLAedbxU4c9iBeH56TziT47KPQWY91w8A1fX+MQY6xnFJKV6beUG5m92p7jeWMAvBlQVONfTLBKnQ28hgofdcWcSICbgGvB064H8kcaIvcVJN1zdWEtm2n7p//iu9EwwCXQcEvb8ST14Q2VCBpefYpVrrY/mtWw1C6l7e62uYw4r2pK0HNcNRoC93yQStDOQnUhFAD1NfDUQ9C5WqoWgtNlVZqhS8HckZB3jgkvX+X4uJi6CSrIJdp02elCoOcDhMODg69H3uW2x0c9hHkxFthxAHNzyL/GbD/OXCAzTma+wi+8y8Dr69j713Eq+G74tpu1OorStm67hnHcKO719oqUkRg4JRIX2mbmXGh1RLHTtkzvtVnDGWw3t+8O39B9nXftza4YgihFyutsvDKwfgbnoA3fgDPnIs+fS76+Z/RquQMUA0HoGZLUjI6pGG3VUirmXAA+ypTdYDZPs1Em6rh09/aN7aaUL4GNr0D+ZMhbzr0Owj6z4URpyODDrffUAZk1H72GcoAHj8Mdoxlh68wzWHY3f1wiBvHTebg0ArxpSNfuxctXQObF4HLA6MORrKdwhsdYQweRvrvHqL++9+Autr2bcgMg7Sf/sop7JViVE0IdVNOvSoE6mwXK5NOQjd8aKNAAwZMxsgdgs75Cbx9kxWOm2x+9KTzkdEndn1cL0NEyLnhOtKOPYbaf/6TuieftuoIuFxWOLkAWCHmrlwPmYfkkX5ALq6MvaYKjRVWu6TVz6LDj4T9rkISCaMP1KYuVx0sj6sv0hPa5SVlYdjNGFGmVKuft15ntLEFMCI59RrnRHbRg/DZX9tt1rR8GH0cjJ2HZNj4uzXtSHjmHmi04XtvuGD/kxCv0xrJwcGh9+MYyw4OUZCiMVA0pqfV6DO4p84k6+k3Cbz0DMEXnkLLdiOZWbiPmYf3tHMwigf0tIoOfYHhB0H2AKgpsceIUhOZYfWVFW8GesTd8PG9sP1j4u6BKob1mH4FMuaU5HXrQbxTp5B/7y/JvfVH1D31DMHVqzFLNiMVyzH8im9sOv5xmYjRiTe0+fPZ9DbsWIAe/jOkX2o9hQ2lQUL1JukDPbi8sUQJtNI/a1DK9AIgrRDZy1hWMwRrXqBNvxaPy3q4o+TSNxvMIRMCIQh38h1QjX4JN5TD0sdg6ePo9Ith0tm2FOITjx+OvBR9yYYWX2Igh6egqrqDQ19CSfn6XdQxHeLGMZYdHBxsQXJy8Z13Gb7zLutpVb6SiBioO83KaUz9YOCzv1+2GC44+mb06e/aIQyGz4aRh7Rs8mSgc34MW96BBX+KtO/pwmhuLj6VPxYOuB7JHpy8br0EIzeXrMsvQ3ctgzduArM/cTfiVNPKM3/jRvSoe5B+E2I/15sVU3Gv2k1NrHxgFzXrrLY7rjRh2Ol5DD05G9GIV7ZVjSsMsf7357YIyU1l71oDCsa137x7ueXdBvC5weexdFONXpFeBFxiHeNzW8ZyYxCCHbw/hkRvZ9a8kPHFQ7Dtc/SoOxBPbK0/O2XuhbD4NdixLqmQbDnpWqTfvvM9cnBw2LdxcpYdHBzaoaEAum0puvApzDd/j/nGbzDf+wu68g20MobWRA49Q7/R3TOOGUL6pSbyQgZPh/2S9DqJC9LykCOvb1cJWESQoXPhlH/DgTdCvwlWG5doeDJg6OFw9H1w1K/3KUO5GW2shHd+EjF+EvXmmxAOwTs/tnJ0Y0RcHsge0ukxTeUhvrh9BzUbLEPZ8ApFB2ZQMMmHBBSCJoS0pUJ5SCFgQpPCon/syasWTxr0m0Rqpj0mDNi//eayNeAyIMsP/oihDF23bmvebwhk+CDD2z7lWSS2NOhdy+CNWy0vd5KIy41c9ivIzLNCqRNh1jyYc07Sujg4ODh0F45n2cHBYQ9avRNd+DQseR6aagFpNSlSNOJN0P4TkJlnwYSj2oUeOvQgReOhZHn3VMROkbEMIAdfgQbrYckzJBQunZaLnPU7JKOg48NcXhh+JAw/0jIkqjZBfWmkDZQfsodBeuG+3wf1s99DsI7EDeVmTCs397M/wJw4WkwVTbcqVXcQdr/ttWpCjSaYkD/Vz/jL++HNMWK4JBRWzYeVz6ETTocZl8GYU6z+y3bjTrcWVfam9FPI9Fl/J3IdNZ/jdkFWGtQ2ts1rlhi+G2pC6VL48lGYdmH8OuytUl5/uPbv6EM3wPbVMZ5kWHrMvQiZdw1iUys3B4c+jdNnuc/g3LEc9gn8XuHF+wbz4n2D8Xv38cltClA10YVPoQ+eD58/GjGUAdQyHsxQ27C7klXoS3eg/74SLdvYEyo7REGGHdw9hnJmf8gbljLxIoIc/l3k6JutqrmxVLFuPmbkIcj5DyK5sXuBxXAjeaOQQbORIYciA/ZHMor2eUNZy9fAluit8hITaMLmd9CK9bGfM/L4TsevWtUICmMuzGPa9cV4sw3r+ugsn7q1PgArnoXnvwlZQyFzgM0V1wXGn4G4fW2H3v4+1K+JHJLkddTsRc7yt3in42XJv9Hqbcnp0axO/gDke/9ATvw2+DOsjdE8zc3b+o9Crv4LxsnfcQxlBweHPofjEnLYJxAR0nz79sQ2VWgogM6/HdbG0Ye2eRJauhZ9+DI49Q5k9JyU6OcQBwOmQs4QqNpK6ip5CDLldCQVLZ5ajyICE0+AobPQRU/C0vlWBW4RK8wasBZzIosDg6YjM86G4Qft80aubax5Iaac4bgQlyX3gO/EdnjOMLR4JpQuimo0uzMMJnyzgOLZllEWk5HcDoW6Unj1BjjwWvjkrgRkREEMyBoM489uO1r1Bljym8gxNl2LEsl1zvRBdYJV71c9D/tfZY86LjccdRkcdh4sfhNdtwA2L4XaSqtwWeFQGDIJmXokDJ3kfCdtQHdtQD9/ErYsAV86MvFomDYP8dqQj+7Q/ZgkH9CTyJgOcSOq6vjkO6G6upqcnByqqqrIzk6gNYaDQy9G1USfvRXWvde25VNciFXd9Mx7kBFOe6ieRlf+D33nl6kbwJOGnP9fxN+990MNNUHJSihdhVbvsIxkXxZSOBr6T0SyirtVn76OqsITp6emIJwnA856KmYDSetK4OUrIdzUbl/dxkbSi932GFtiQHo/GHssLP9v8rJcXjjqPiR3+J7Naobggxugbmtq2mKpWpWyG4LW36E47tuedDj36ZQvdDnYj658G336NivCYE+Ul0DBUOTiPyPpuT2oXc/QV+fnzXqXnzeZbG/ylerjGjsQJv+/S/vce9bTOJ5lh32CQFC577/lAHz/vHy8HmcVOyYWPBmfRzkqCmqi838Cl/8XycizRTWHBBl3HKx6OWW5yzLnu91uKANWmOugaTBoWkx1jRy6oHZH6iqnB+us/O+M2BYwJKMYnfUd+GSvRR5TSe/vgbCJNoSgybQCJgzA7wK/Kz5Ps5pQtwvqa2DieRGDOc6ceIgYyn6Y+39tDGUANs6H2s3xyYtrbLGqagfCEIrz+x2sh5rtsA8WqrMLrS+HNW+jpSusxbmmmkgEQX8onmAVIBw22/Ksd5dODdXoc7db12+bRW2F8q3o679DTvlxt+njYBNOznKfwTGWHfYJwqbyysd1AHznnDxiKxP61UYrt6Hv/tkuaRCoR1//NXLqHTbJdEgEEQOOuBl94nKrOrBd3i0xYMgBMOYYe+Q59CxVm1Irv3JTzMYygAw7Eg01woLfA4ZVTHBXI+xugvoOjEIBzfFAgQ9Jj3U6o7DqOTj5fsgdAZ/9DkL1MX5PIoZ1v4lWG7HM/m0lm2HY8HyMeiSBqtVaKpDAYljFesdYjoJW70A/+husfdu6FsRou9hYXw67VqNLnoK0XJhxDkz7WvcYzUtfhVCQqIs6GoZlr6PHXof47W/n5+Dg4BT4cnD4yqILngDTxjBBNWH1W2jFFvtkOiSEZA9ATrjTyh+1I+RSDCgYjRx1q5N7uK8Qah/ybCtRQqq7QkadCHPvRs0MWFYFm+s7NpTBsh0qg7CuFt1Sh4ZjvJ+JC1bNR4YcCif+FcaeZoUoN+9rvdgqRsvznGFwwHVwxN3tDGUASj+DQFVsOiSDCHgSDN8MJZjvvI+iqujS+egjl0YM5TBWtFSU6665/VZDJfrhX9DHrkB3x1HMLlEdK7d13qrLDEHt7pTr4eDwVcXxLDs4fAXRQAN8+YL9YbpioIueQ464xl65DnEjA6fBSb9EX/4RBBuS8zAPmIYcd4dTSGZfwuVNrXzDk9h5W7bCwo5bSXVIZRBqQ+iITMTfhSGpYVj3GjrrSsSfC9OvQCdfDDsXQPlqqFgHgRrLcM4ogvwxUDgZ8sZ0vlhU8jGWD6Kbquh4XdAYZ/9kl6/rY74iqCr64f3wxWOJnA0Vm9Anvw2n3IMMnGq7fs1IViHa2fdBDMjIT9n4DilC6f6CW04UdkI4xrKDw1eR7UshmAIPg5qw7gNwjOVegQyYCuf8A333Ptj0QUu/05hONsBwIQddCZNOc4oC7WukOhQ3Z0jcp+gXr6CP3p74mCGF9bXo6Eykq8I54QCUr4OiSUAkJ37wwdYjUSpW0a2zX7cLiNNYzhmaElX6JAseSdBQjqAmhAPo8z+As+9H8ofbplobJh8Hb/05uqEjLhg7B0lzijU5OKQKZ/bj4PBVpGSVzb1GW1Gx1fJcO/QKJD0fOe5nyIl3w+D9W3a0C+tr1ZLJkwFTzkLO+Qcy+QzHUN4XyR6cOi+j249mDEDDQas1XQyV9nX3VvRxG+odhBU218cwpkDZmuTHi6ChBmgosU1el4iAJ87vpcvnGMsRtHQ1+snfbBBkQjiIvvpzqxJ6CpDMAuS4660nre/bYkBGLnLMd1MyrkOKaS7w1d0Ph7hxPMsODl9BtHJbpG9nSqRD1Q4oHJkK4Q4JICIwZH9kyP5ozU7YvgjdtQp2r7Mq5BouSMuHonFI4TgYNNPytDnss4gY6KCDYMv7tqVjaFihIQwI/OFEtKnW2uHNQPuPQ4YfAFPmIeltK+arqmUomzalhTSEoawJ+vk7PsZwQZ2Nxm1ThX2yYsWIw1gWF4w8Euks9/Urgqqib9xFQpXQowoMw+618OWzMO2s5OVFQWaeBgVD0U8eha1fgscPk49F9j8HyXRCsB0cUoljLDs4fBUJh1Kbu5KiFXaH5JGs/jDueGTc8T2tSo+hoQDUlYE/C/F9hSvIjj0FNr+TtBhVheog1AYjW/Yq7hWog80L0S1fwPt/RWechRx6BeKJGLNblsGGL5LWow2lTWiBr/McYzvvU3YZ+qlCwzD+1J7WonewfQmU2V+YS794HKamLhJHhs1Ehs1MiWwHB4eO6TOxdeXl5VxwwQVkZ2eTm5vL5ZdfTm1tbafHX3vttYwbN460tDSGDh3Kd77zHaqquqFSpUO34/cKT989iKfvHoTf233VekNrV1P323upvfNnNL35Ghru5ROmZrzplmc5lfIdHFKANlSgu1a2eC3jOTcUwHz/fvSBk9G/n43+eR7m87egldtToGkfoHASFE9PKiVDQyaUNrQylDs7WC2jcuHj6EMXoWUbrc0fPtV5td9ECEcM+M50cXfieY6XVBdMi0qsK54CE05H8pxoHwBdNr8l5cROakthywL75Trsmzhh2H2GPuNZvuCCC9ixYwevvfYawWCQyy67jG9+85s88sgjUY/fvn0727dv595772XixIls2rSJb33rW2zfvp0nn3yym7V3SDUiQm5W94aXNfzr79Td/XNwuUCExv88jHvWgeTc/xDit3ESlgKkcGTK8qtweyFnQGpkO3xlUTOMfvx7WPWSlSdoeGD6BTDtgpjaWakq+uKPYf2H7DEy1IT1H6Lbv4QL/45kFqb2RfQyRAQ96Hp44RtWwYc17MMAAHl2SURBVKs4w000ZMKuhvhrWqlCdQn6n6vggj/Dqo9S45mtDUFOB0ashiF3mH1j+fuBuEG7KapG1Spo1hViQPYQmHFZ6nXqK2xdaH8nCABxoduXIEP37/pYBweHPkOf8CyvWLGCl19+mb/97W8ceOCBzJkzh9///vc8+uijbN8e3SMwefJknnrqKU4++WRGjRrFkUceyS9+8Qvmz59PKOSEiDokR3jjeuru+UXkSRgi11Rowac0/OvvPahZjPQfnyLBAkVjnLw4B/tZ+gSsfLGlmrcZRBc+DBvfi+387V/C+g9oZxBqGBqr0QVJVMXtw0hGEcy5JRJpEnu0iapCWWPixZ/VhEAd+uz3obY8QSFd0NCFQZQ/1rahxHBBlo3GdyyEujL4xDKUj70HsdOL3ofRhkqoT9H1piaUrkyNbId9D7OHHg5x0yeM5Y8++ojc3FxmzZq1Z9vRRx+NYRh88sknMcupqqoiOzsbt7tjh3pTUxPV1dVtHg69n0BQ+e2j5fz20XICwdSHmTS98lL00EVVmuY/k/Lxk6ZoDOQMJJ7JcazIxONsl+ngoKtepL3n00DX/C+289e+23Gor5qw+s2k9OvLyKCD4NCfgMsTe3hqTTA2z2ZHuAT6+8FXn7iMrgh2MjNML4Qcm9tn5U9IXZeBvRGBYAfGcvNnOP4UOPF3SFpe9OO+itTuSqFwhZpurIju4ODQLfQJY3nnzp0UFRW12eZ2u8nPz2fnzp0xydi9ezd33HEH3/zmNzs97s477yQnJ2fPY8iQ+HtFOnQ/YVN57t1annu3lnA35GRoY2OHdqY2pqB/sc2IGMjMFFTtdHvBMZYdUkGoKcpGM/Z+4eEucmrDgbhV2peQwQfBvL9aeczQqdGspsaWo9wRHgOGZkGGJ3EZsdDhT4HA+FPtL8Q06IjY+5gni6kQiGIsGx4YeRTM+xNywNWIJ6179OkrxNDGrFfLd3DoRm6//XZEpM1j/PiWyMTGxkauvvpqCgoKyMzM5Mwzz6SkpO2C0ebNm5k3bx7p6ekUFRVx4403tovwffvtt5k5cyY+n4/Ro0fz8MMPd8fLi5keNZZvvvnmdh/C3o+VK5MPaamurmbevHlMnDiR22+/vdNjf/jDH1JVVbXnsWXLlqTHd9j38B5ymBV+vTcuF965R3W/Qokw7RTI6W+rJ0QOuRzxZdgmz8FhD8MOiXKtCjL04JhOl0HTOs6LFRcM2S85/fYBJLM/HHUPHHk3DDqwY4O5SROvpu82YHAmuKzfeNwpnIa4o61oCnjSYbT91eAlewTkjCUVETttBzJg5Klw0p9hzk1w0HfhkB/AvD/Bec8ih9yAFIxOrQ59FX9WauWn5aRWvsO+Qx8p8DVp0iR27Nix5/H+++/v2ff973+f+fPn88QTT/DOO++wfft2zjjjjD37w+Ew8+bNIxAI8OGHH/KPf/yDhx9+mB//+Md7jtmwYQPz5s3jiCOOYNGiRXzve9/jG9/4Bq+88kpy76+N9GiBr+uvv55LL72002NGjhxJ//79KS0tbbM9FApRXl5O//79Oz2/pqaG448/nqysLJ555hk8ns5Xsn0+Hz6f01/UoXPc++2P95jjCbz2SqRVo4LLheTmkfb1K3tavZgQjx9OvA3979U2CHNB8ViYdU7yshwcoiAzL0V3LoHKTZaxoCYMmA4TYmyHM/pQyB0EVTv3Ku5jGTay33m269wXERHoPx36T0fDQajaBNWbLc+8ywM5w+DDR6Di9cSKJPVPbzGUAXyGFZIdToFHLi2asa9w4LWIP9v+8QDGnAuf/yw1spsxvDDiZMRfAPmjUjvWvkZWf2uxJJiC8H/DDUXj7Jfr4NCDuN3uqLZWVVUVDz74II888ghHHnkkAA899BATJkzg448/5qCDDuLVV19l+fLlvP766xQXFzN9+nTuuOMObrrpJm6//Xa8Xi/3338/I0aM4Fe/+hUAEyZM4P333+e+++7juON6R6RijxrLhYWFFBZ2XX109uzZVFZWsmDBAvbbz1r9f/PNNzFNkwMPPLDD86qrqznuuOPw+Xw8//zz+Ht5hWKHvoOIkPXL39H45KM0Pf80WleL55DDSLv0ClxFxT2tXszI4Klw3A/QV+5OQogLsgqR0+90Cns5pAzx58BpD8CWT6B6K+SPhoEzYg6lFZcHzvotOv82KFnRssOfjRx7M2Jz0Ts1w7BjJWxfiZZvtXqb+zOR4tEweDKS0/vvE+LyWO9zflsvpe5YnpihnOsFv6tN9XIRQbM8UJmCMPiMvac4AsMOgxFH2D9W8wiF09FBR8K2t0lZNZ2Jl1uGskPciAjafwJs/cL+kHkzhBRPtFemw75LTxTcSmC8NWvWMHDgQPx+P7Nnz+bOO+9k6NChLFiwgGAwyNFHH73n2PHjxzN06FA++ugjDjroID766COmTJlCcXHL791xxx3HVVddxbJly5gxYwYfffRRGxnNx3zve99L9FXaTp9oHTVhwgSOP/54rrjiCu6//36CwSDXXHMN5557LgMHDgRg27ZtHHXUUfzzn//kgAMOoLq6mmOPPZb6+nr+/e9/tynWVVhYiMvlTOodkkPcbtLOvZC0cy/saVWSQqaeDC4P+so9VphqvJPgolHIGfcgmf1So6CDQwQx3FY4dqLnZxUj5/8FLVkFu9dbIZPD9reMQpvQQD188gT62ZNQsxuQVoXF1DKiAR25P3LwBciojhd8ey31lYmdl++P3uarf5r9xrKwV9sogYGzYM6NMbUaS4oJl0HZEmgqt9kgEyjcDwYdaaPMrx4y4UQ0Ff2QPWkwIvH7k4NDd7F38eKOomoPPPBAHn74YcaNG8eOHTv46U9/yqGHHsrSpUvZuXMnXq+X3NzcNucUFxfvqSe1c+fONoZy8/7mfZ0dU11dTUNDA2lpPV93oU8YywD/+c9/uOaaazjqqKMwDIMzzzyT3/3ud3v2B4NBVq1aRX29FVqzcOHCPZWyR49uuyq+YcMGhg8f3m26Ozj0dmTS8TBwCvry/8HWxZa3uFOjWcDlRg75Oux/nmXEODj0EaR4HBTbHy6pGxeiz/wMana1MpIUovU037AAXf8ZOvlY5MTrkL6U65iIrZnpQVwdRAHke8FrQMBGwzLfi7ikJWR/wmmw3xXdcq8STwZ64M/go1sgWG2TwSyQNx5mXJ96Y39fZ9Rh4M+BxmoST77fCzFg4klWepODQywkmEOc9JjQrnjxT37yk6g1nU444YQ9f0+dOpUDDzyQYcOG8fjjj/cKI7a76DMz3Pz8fB555JEO9w8fPtzq+xhh7ty5bZ47ODh0juQNgnP/ADtXoF88Des/hobKvQ4yoN8IZNIJMPlEJC1FeX8ODn0MXfwS+uzPrZY+sRhHzccsex3dvhwu+SOSXdT5Ob2F7GJorInvnEwPqhrV0BMRdEw2LKu0Rz+3QP8MQCF7MBz0HaR4qj2yY0TS+6MH3wWf3QF120naKCvaH6Z/H3E5NVWSRVweOPy76Ct25ZYL+LKQ/S+ySZ6DQ2rZsmUL2dkt87dYazXl5uYyduxY1q5dyzHHHEMgEKCysrKNd7mkpGRPjnP//v359NNP28horpbd+pi9K2iXlJSQnZ3dawzyPmMsOzh0hs8jPHLHwD1/OySGiMCAicgAK+9Ka8ugarsVnu3NgIKhiNuZrDk4tEZXf2AZymj8rWPUhIod6D+vhW8+jHh7x+SgUwZMgt0bOq4uHg2/u1OPqOR60QFpsKMhef1GD0RGHwRjToSiyT3miZW0IvSQX8O6x2Hd07EvpOzBAJcPJl0BAw93PMp2MvoIWPs2rH/fBs+/IkfdlLqicQ4ONpOdnd3GWI6V2tpa1q1bx0UXXcR+++2Hx+PhjTfe4MwzzwRg1apVbN68mdmzZwNWzalf/OIXlJaW7mkB/Nprr5Gdnc3EiRP3HPPSSy+1Gee1117bI6M34BjLDvsEhiH0L3AuZ7uRzALIdArJODh0hNZXoc/ekaSQMJRvQd+8Hzn++/YolkJkxEHo4ufiOAHEE0MhthGZVphgSYK96sWAc2/DmDkvsfNTgLg8MPYCdMAc2PSSVfjLDHaQ6tIcNh4GTzYMOx6GHof48npC9X0aEYGjb0GfvwF2Lk/KYJZDr0VGxNbCzsFhD32gwNcNN9zAySefzLBhw9i+fTs/+clPcLlcnHfeeeTk5HD55Zdz3XXXkZ+fT3Z2Ntdeey2zZ8/moIMOAuDYY49l4sSJXHTRRdxzzz3s3LmTW2+9lauvvnqPN/tb3/oWf/jDH/jBD37A17/+dd58800ef/xxXnzxRbtffcI41oWDg4ODg0OC6Nt/jYQkJxlmqwqfPI7OPAUp6uXtgEbNhowCqCsnptdtxOYRFRF0VJZVxXpjbXwTuzQPcvn9yLApcZzUfUjWMJh8FTruYti1AKrWQeVqaCyzctpdHsgYBDljIHcM9Jvu1IJIMeLxwyn3om/eA2veJNIHMsaTXVbdjrnXIeN7R3sbBwe72bp1K+eddx5lZWUUFhYyZ84cPv744z2djO677749daSampo47rjj+NOf/rTnfJfLxQsvvMBVV13F7NmzycjI4JJLLuFnP2tJgRgxYgQvvvgi3//+9/ntb3/L4MGD+dvf/tZr2kYBiDqJvZ1SXV1NTk4OVVVVCYUsOHQPwZDy4POVAFx+Si4etxOu5tB7UVWCi74gvHUL7pGj8Eya3NMqOSSANtWh986DUJM9Ag0XzDwVY96N9shLIbr0f+j/ftHlcYEdTTSsqCX3yvgWALQxDNvqobShc6PZa8CANBgxGGPev+Iaw8GhGV33Lvrub6GurKUoXDSa9w09AJn7fSR7QLfq6dBCX52fN+tdduxYsj3d25mnOhim4NXVfe4962mcZUuHfYJQWHn8davgzCXzchxj2aHXEt6+jcorv0FoZUuvX89+s8j94wMYBU7Ie0eoKoQqIbgbNATiAU8/cOf0XC7nqvftM5TBygFe8j/0xOtj7h/dY0w6Hla+ARs/7dCwaFxbT82b5WCA2RTG8MU+MRS/C0ZkooPToTEMIRPC2vJwCaS7Idtjff7Zg+x6ZQ5fQWTUYTDiYNj0CbriZdi5DOrLWx1gQN4wGLIfMulkJH9Yzynr4ODQrTjGsoODg0M3oapUfvNyQmvXtNkeXPQFld+7lvx/dVzx/6uIqkLjJqj6FOpXg0YxTA0/mj4ecg4E36BuNZx1+3Iw3NFbQyVKoAHKt0LBUPtkpgARgZNvR/97jdWzei+D2QyY1LxbEXkCoa0NeEZmdP35aMQYDppgqtWlyi3gjmJoCxBS8Lggb6wdL8uhFRpqgg3voDsWwa4VULfLyqd2p0O/0VA4ARl5JJLbu6/VWBHDDSMOQSK9krWxGppqLUM5Pc8pbung8BXFMZYdHBwcuonggs8JrVrZfkc4TPDjDwmtX4d7ZC/PV+0mNLALSp+Gpq2AQYexuGYj1C6B2kXgH4EWnY54uqkgUul6ew3l1nJ7ubEMIL5MOO8P6Is/h3Xvt9kX2NBgGbLNz9fV4RmR0XmPZlOhKRR7rrICgTAEw9Bdn/lXAA0F0CX/hWVPQ7CufTGycBVsWwjbv0AX/RvtPxU58CqkYEzPKZ0CxJ8NToVrhxShCTRPsGNMh/jp5XFeDg4ODvsO4c2buti/uZs06d1o1Wew5Q/QtD2ypSvrKbK/cRNs+R1asziV6rUQtKHNUTTsDO1OMeLLRE6/EznpdsiJ5G8aLsJ14TaGceOnFZ0LCpnQEIeh3BoFPn8AXRVHhW6HqOjuNeizV8Cif1uGMkSp2g1Wm7TIh1WyFH3+asyF/0DjaSfm4ODg0AdwPMsODg4O3YRrxIjO9w8f3j2K9GK08gMoeznBs01rAl/6JKoBJHt/W3Vrhzc9NXI9/tTITREiAhOOhvFHwqYF6MbPcJW+Cp8v2nOMWRWi6csqfJNzENde7uWQCU3JGlkKn/8J1TAy/owkZfUsu9//nPV/fZz6LTvJmTyWUd8+j+zxqY840R2L0FdviURLxOGCajaaF/0LrdoCh/8QMbq3cJGDQ19DVVGze129Tk3nxHA8yw4ODr0aVcXcXUp4/RrCG9eiNdU9rVLCeKbPxD1xErj2mki6XHgPPQz38M6N6X0drVuehKG8F7ueR+vX2yOrI4pGWTnLtssdab/MbkDEQIbvjzH326T95BEkPQNa5SjXPr8TDZptJ4im2mAot2LBA2jJEvvkdTMr/u9+3jr0AjY/8gK73vqEdX9+hFennMy2Z19P6bhasQl99UcQDibVc5gN76Cf/Knr4xwcHBz6CI6x7ODg0OvQUIjgO69S/4MrqT3hAOpOOYT6C0+k/vwTqD1uP2pPP5yGX9xMeOkXfWqlVETI/cvfcU+Z2ma796DZ5Pz6dz2kVe9Aw/VQ+qyNEgVKn0LN1IU0y6CJ9ucs+9Ihb7C9MnsASU8n++57LWM5sjhkVoeoeWYn0tx3WW02lAEw4MNfoqFGm+Wmnqqlq1n6o/sA0FB4z/8aNvn04h8QqqtPybhqhtF37ozdo6xqLXKEozxME5Y/i7n185To6uCwr6Bmzzwc4scJw3bYJ/B5hAdv7b/nb4e+S/Dd12n65Y/Rsl1W39koOXBasp3Qy88SevEpjPGT8f/oLlyjxvWAtvHjKi6m4IlnCK5YbvVZHjEK9+jRPa1Wz1PxllWsyzYUwjVQ+R7kH22j3FaMPcQKmQ7apLfhgmnzeq4Vls34jz8B12NPUfe3Bwi8/x4gUDybcMEkXGX/ixhXdi92mVC/C1Y9B5POsVl2atn8n/mI27XHUN6DKqGaOna8+DZDzj7R/oFXzofytV0fp9p1TrlGHi/fgnnkjzBGHm6Dgg4ODg49h2MsO+wTGIYwYqC3p9VwSAJtaqLxrh8ReuW5ltDNzorFhK195poV1F96Kr6rbsBz3uV9xtDwTJiIZ8LEnlajV6BmE1QvIK48ydgkQ9WnaN5cROz/uRNvOjrzVPj0CXuW7E0TmdW38233xjN9Brl/uL/ddt08Hj68N0WjKqx+Hp1wVp/KnQ1UVNFZufBAhf0pKKomuvSJrg5qMYJjFhyGN36Guf5w5NDrrMrpDg4ODn0QJwzbwcGhx9GmJhpu+AahV+dHNsQxKwuHIRym6Q93E3jg16lR0CG11C4DDaZGttkAdatTIxuQuZdDem6b3NzEBAkcfD5SONwGrfoAhdMhnMKYwPrdsGtp6uSngPz9p6ChjsP68/efYv+gO5dAbUnH+5u9yYmuY218D53/PbSxKkEBDg77KNpDD4e4cYxlh32CYEh5+IVKHn6hkmDIuRv0NRrvuY3wwk+T9s4F/nk/gfldeEkceh9NW0jdz5ERkZ8axJ+FnP4TOm8g3AWGCwpHIHO/YZdavZ/dq1IrXwzYHaWneS9myLnzSBtUjOxVAFBcLoqOmk3ezEn2D1qy1HqvOiLZn1M1oXIT+vIPnbZSDg4OfRLHWHbYJwiFlX++VM0/X6omFHaM5b5E6P03CP3vGdsqTzTddwfmzu1dH+jQe2jcSmINdmPBhMZtKZJtIaMOQM74qWV0dGZ4RD3ZgPwhyEW/R/pYy6ikqFgLksIQaSW2PNxehDsjnbnv/Jvcma3SM0QYeOqRHPzU71Mypu5e08lOtccTpSbsWgWLH7VBmIPDvoGa2iMPh/hxcpYdHBx6DA2Habz3p1YIql1VrYMBmu6/l7TbnZDsPkO4NsXya1IrH5DJR0NOMfrM7VC5I2JkdHJNNxevm3EScux3EF9GynXsVaQ8LNeExooUj2E/maOGcvSnT1K9fC0N20rIGjeC9KEDUzdg/e7oC5WxFPOKE13wDxhzLJJZaK/gbsJsaiJcVo6RmYErO7un1XFwcOgmHM+yg4NDjxH+5D20dId9hjJAOEzojf9hlpfZJ9MhpQQ2VVD3/laaVpWlqBVY96ymy5ApyFX/QY79DuQOaNlhuK3HHk+qwJhDkEv/hHHyD796hjLQLZ9JH+6Tkj1xNMXHHJJaQxnsvfd2PRi66sVuHM8eQqW7KL35x6wfM42N0w5i/agpbD3zAuo/+LinVXNwcOgGHM+yg4NDjxF86WmrB2vY5lw2M0zojRfxfu1ie+U62EpoZwk7r/oeDe9/uGebd1QuxT87FN+oPPsGcnWfMSoePxx0Lhx4NpSuhx2r0LItYIasisD9x8CgiUiGja+vL+LNSvEAAr6cFI+xD5CeB2VCu8WLVKwzqAkrXoT9Lk2B8NQQ2lnCluNPJbSztM3vVMMHH7HtvQ/o/8DvyDr9lB7U0KGvotrNa1V0/3j7Co6x7ODg0GOElyyw31AGMAzCy5fYL9fBNjQUYuuZ5xNct6HN9sCGKrZd9QrDHjsNV54dObwG+AbZICc+RAwoHg3Fo5Mp/bXvkj/aai+UKkSsMRw6p2AsbP08tZ9FaxrK0brdSEa/7hkvSXbdcns7QxmwnotQcu0NpB9xOK5cZ2HGwWFfxQnDdnBw6BG0phrdXZoa4eGwYyz3cupeeZ3g6rXtJ6GmYtYEqJ7fSeGhuDDBN9gmWQ62kT82tfLVtAxBh06RwgntDeVUu5/K+kbhtVBJKbUvvtzxgq4qGghQ/dhT3auYwz6BU+Cr7+AYyw4ODj2C1landoAap69nb6bh40/B3UFwk0LDwk56v8aDeCFjvD2yHGxDMouhYFz81cNjxZcNxdNTI3tfYtB+kNbNKQFNqS+4ZweBlavB7CIe3TBoWrq8exRycHDoEZwwbId9Aq9H+NMPivf87dAHSNUkuRnDWQvszUhaWsceLEOQNDt+ngSy90MMrw2yHGxn3Gnw4d32yxUDRs9DXB77Ze9jiOGCCaehCx+muwrhIX3jN1q8Mdw3RBCvc505xI+a3V+DsA/XPOxRnNmkwz6ByxDGD/cxfrgPl9E3foi/6kheQUoNWilOcRVZh6TIOvnEjsMbTSXzyGHJD2L4Ie/w5OU4pIZhh0HuCJsXzgS8mTDhDBtl7uNMPguyBqR+AbOZjKLuGSdJfDOmYmR1UYguFCLj6CO6RyEHB4cewTGWHRwcegTx+TCGjUyNcJcb16RpqZHtYAu+KZPIvvh860lrT5NA2sxiMo+wwVguPAXpxkrYDvEhhhsO/oHNUhVmfRvxOX1wY0XcPuTwm6G5FF2qPb/9xqRWvk0Yfj+537q84/fD5cIzfBgZxxzZvYo5ODh0K46x7LBPEAwpj75WzaOvVRMMOQUMUoXWVWO+9TTm0/djvvAwumllUvJc+x9itY6ym3AI1/T97ZfrYCtFv/wFhff8HM+oEeBy4epfTP41JzPgvqMRd5I/T3lHIJmT7VHUIW40HEbr67rsmy15I+HA79k4rqJv34n53DfRlfPRYL1tsvdlpGgiMvdHEcNQSE0Jd4F+YxFPWiqEp4T8664l68xTrSfuyG9VxHh2Fxcx8LF/Ih3VXnBw6Izm3lHd/XCIG9Gufsm+4lRXV5OTk0NVVRXZ2c5KdW+loclk3ve3AvDifYNJ8znrQHaiwQDmf38Nbz4JoZBl4KppFT8ZNQXjGz9BhsTvLQhvWEP9BSfar3BOLpnPf4B4nFzVvoaqQsUbUPEO1ow9np+oyPH5xyJ5h6ZGQYcOCa9bTfCZRwi+Oh+aC/iJIIXFeE49B8/JZ2P0ix6C+//t3Xd4VGXax/HvM5NOCj2hdykqXTGKoIKCgivqro1VVNR1BRTUXXVtuOqiri72sqtiecG6YkNEFMEFURBFEQGlGVoINSGkz3nePyaJJKRnSmb4fa5rLpJT7nNPEpJzn6fZ9XPh68e8hUgtB9ZZazHGYD0WSmd7Lf5ZiGqEOeEG6HQKJkTGygaT3bocu+gByM8Cj+8HOJqhf8UcNcLncf3JWkvukqVkvjyTgvUbcSclkXDu2SScPwZXvHquBEuo3p+X5L09tTOJEX5oLKjq2kUeWi/dGHJfs2BTsVyNUP3PeKQJdrGct2EzGTPeouDXbUR3bk+Ly/9ATKd2Ac2hMtbjIfedd8iZ+SqetC2427Yh7pKxxP7hAkwNWnVtUSHOw5Ng9VcVP5V0uSEyCtddL2E61H7W4ZwbxuH59mvfrbdsDFFX3UD0FRN8E0+CwuZuhoz/QtF+qi+ai/dHNoOWv8fEaKmoQCr69mvyn/sXzqpvvQ/SKvq/XDw/QcTQM4j+88242h7ezd7uXgtfPgQHtpdsqfbapbcwHlvJ4cU/G52HYwbf5O367SdFGzaQ99mnYC3Rw4YR2TU0uhuXZ/OzsMueg3XzfNcSZVwQ2wRz4auYiGjfxJQjWqjen5fkvW1QcIrlNl+rWK4tFcvVCNX/jEeaYBbLu2bOZuPVtxS3iFjvvwa6vvIozc47M2B5VMQ6DvtvmETeBx94b1Ydx3vTYh2iR46kyVPPVFswOx/PxM78Z9U3TS4XJLfH9dC7tW69cbalcXDsWVCQX6vzKs7DjWnXkUYvv4eJ0g1ZqLO2CA6ugcyvIC+tkqMMxHSEpBOgUXeMCezNx5Gu8MO3yHvgDu8n1S2zA95iOjaOuEdewH1sv8N2W08B/PIRrHsXsnfg7RL8W2tzyS2LMcb7sWOhRg2gBjoMxgy93TsDtA9Za8m67+/kvPDCb5MWOg5xl40j8Z6/+6xF2xYW4KRthohIXO06YPw847+zZwO8NwE8hT6JZ858ENN2oE9iiYTq/bmK5dCjgRYi9ZCftp2N19x6+E2iMWy4/EYSTz6eyBbNgpMckPfJPG+hDL/lWHzTmf/xx+R9+CGx55xT6fnWcbDzZlbfwOM4sGMzrF0BPWt3M+Rq056Ym6eS94/banXeYYyBiAhipz6iQjlMGBMB8cdC/LFYJx/y06FwF1gPmAiIagFRKVoaKkgKP36PvH/8rXYneTyQc5Cc6y8j7rk3cB/Vq8xu446CHmOw3c+BPWth91rY/g122/LfDrLWWyjX6lG/hV//Bz+9A8f8oXY5VyP3nf96C2Uo87cg55WXiezVi7iLLq5XfOvxkD/jGfJnzcBmedePd7VuS8y1k4k6a0y9YlfF1awLdtjd2Pl31r+Fuc9FKpRFJCRpYKdIPeyeOZsK79isxRYWsfv19wOe06Fy33jd2026Ii4XOW+8XnWAHZth1zZqdFfqdmNXfF7bFAGIHP17oicVF8t1aYUp7goe+/B/cHc/uk45SMNmXNGY2A6YxIGYpEGYxAGYmPYqlIPEs241efffUreTHQcKC8mdciX24IEKDzHGYJr3hG6jsPu2gmO8Xa09xS3Jdazd7LcvYrO21u3kSuS8+krFy+AZw8FXXgYgd8Ov7HrjQ3a9/gE5a9bXLv59t5P37KOlhTKAs30rOXfdTP5b/1ev3KtjOqRiTrsTjLsOS0sV/y4/5nzMcVf5PDeRUOZdZ9kG+BXsdx2aVCyL1EPB9p2VrhVsItwUbt8Z4IzK8qSng1PZWrYOnvQdVQfIza75xSyQe7Dmx5cTdfGVxPzjSYhPrLzAr4gxuDp0Ju4/bxExMLXO1xeRmit47YX6BXA82P17Kfz4vaqP2/w/7xhmX93lWQf749u+iVXMs21bxV3QrSV301Z+PPNyvu05nJ8vncLPl93Id33O5IdTL+LAilXVxi5au5rCDyrPN/fxB7E5df+9WxOm81DMmKcgqWQejho80DQu7+Rqp92JK/U6Ta4mIiFLxbJIPcR27wxFFRejtrCImO5dApxRWRFdu1W+NJPb7d1flcSmtbtgYpPaHV9O5CkjaPTGJ0SeezFEx3g3VrQsh9u7zTRtTtS1NxH30ru4u/Ws17VFpGacvXso+myuTyblK3jz5SqXl7Jr3q1Di2YVrAMb5mMLfFdgRnTvUeHv2QKPi22/FpK58KvD9h346jtWnXIRWV+uqDJ24bwPq15eLzeXwsULa5tyrZnm3TDnPYc5+UZocsjkbC43uCK8r5IiOiYJ+v0Rc8HLmC6n+D03kVCklaNCh8YsS1iIijT8a3LL0o8DpfklY9gy9V84OXllWxbcLtyJCTT7w6iA5VKRuD9eSt4HlXQF93hodOmlVZ5vWraFTr1g89rqW3YcDya1/hOauRo3Jeamu4m+9iaKFn2CZ/X3eNaswu7fCy4XrpYpuI7uQ0SfgbhPGKo1LkUCrPDDtyvvsVIb1mK3bMazchkR/QYdvrvgoHfMsq95CiBjNbQ93ifh4q/5E3sX/6/MNmshY4/b+2ehoq+Vx8HaItZdcj0DN3xR6USLNmt/tdc/tHu2Pxl3JPQYBd3Pgv1psGsNdtcqyN+FLczF5BRgcz2w6yB8+B72oznQoh2mQy9Mt/7Qpa9amEUk5KhlWcKC22Xoe1QMfY+Kwe0K3B/jiKaN6fHei7gT44s3eG94Ipo0pscHM3A3igtYLhWJHjSI+Jtu9n5ScjNW/G/8pOuJPnlItTHMmZdVXyi73NC9P6b9UfVJt5TNzYRf5uK23xLVbBWxAzKJG+Yi7sxEYs7qQHRqe9z9+6lQFgmCoiULfNdE4Y7A8+Wiivftrd3Y3hozLtjzi8/CRQ8ZQtIDD2Lifltzt8AVS0GRq+oZwh2Hgu0Z7J1T+VwPrk5dDlk7umLuTgHuwZSdBls/gg0vYPYvhpx1mIJfIWIHJjEDV9ccTP8iTIu98OtS7IfP4jxyFc7U83C+eBvriwctIqHO4p1/IZAvtSzXie40Reop4aSB9N/0JXvfnUf+r9uI6dKBJr8bjiu6YczInDDpeqKHDCX39dco2pKGu21b4i64iKj+/Wt0vkkdiV3/PXzyGhWud+tyQ5OWuCY+WO9cbd4B7JfPwZq53taYQ5aMASBnH2xeit38FXz5H+xRwzCDr8PE1a/7t4jUnN2/17fxKmsZzc7w6XV+Y7DZ6TUZeVtjcRddTMzvzqFg2TKwlp0Lv4OH/l1tV3UTGUHm51/S7HfDK9wfNfo88p7+FxQWHv6AwuXG1bYd7v6+aSGvji3Kg3WvwOY5pUsQQvGcjOVajI3LYNvE4WrXCLv1IHb1fshIw742Dfvle7gu/zsmpVNA8hYRqQ8VyxIWijyWDxd7J6MaPTieCHdgu3q5YmNofnHlSzAFW1SfPkT16VOnc40xuC69BdvuKOwHL0DGITPJRkZjTj4bc/51mKT6LZFl05ZjP7kP8rJ+K5Arar2yltKC/edPsZu/hOG3YToPrtf1RaSGCn2z7q6XxRYWVLLLjy2QfpgW1hUXR8wpp3g/+fw7b8FYg7fg5Ffy/vEOS4m7bzo5t13v3VBSfLtcmEaNaPTgkwHp2mxz0uGruyC3+AFGDb5+pqSXV+s4TIsY7Ne7IasQtqzDuf8SXNc9iul5ePd7EZGGRMWyhIXCIsvjb+wDYMQJjQJeLIc7Ywzm1POwp5wLG1bB3gzvBFzd+mDiEuod365fiP34nrKFcI1OdLD52TDndhh2C6bXWfXORSRcWWvZ9d5nbPv3G+Rv20nioD50mHI5jXrWrhuvSUjEpm/zTVLGYBISK94XVf/fLZVd02+xi8V27YgtLKr2OOtxiO3ascpjok4bgXvWB+S/8SpF3yyFyEgiTx1B9O8vwdW8pY8yriLHnJ2w5BYozKIu/TiNy2AjXZjUFtgvd8EBbyu589QNuCY/g+naz/dJizRwtmS9+ABfU2pPxbKI1JgxBrr29mlMu+NH7Md/r32hXJJTyVmfPQTxLTDtj/NpfiLhYuNdj7HpvmfA7QKPw8Gf1pP+6rv0//QlGp80oMZxXN164mz82SezYePx4OrUteJ9Tf00FtcpwjTz7zjfZuePZMPke3Cyc6o+0GVo8cdzq43n7nIUcX+710fZ1Zx1PLDiAW+hXI/WeOMyWMAc1wy7aCd4HHDA+c8tuKb+FxPr34cXIiJ1pQm+RCRobFE+9pP78Za7dX/iaQCMwc6f5tMlYUTCRc7GLWy6/1nvJx5v0WOLPDgFRaybdF+tYkWNucg3hTJAVDSRp59d8b74ZIhO8s11ymvh36Xm3I3iaH/n9dUe12bKVUS1rN8QFr/a+A5kbfRJt3XjMhDrxvQo/p5aBw7sw3l7er1ji4Qa6wTnJbWnYllEgmfl25C1wze/wa0Dufuwy/+v/rFEwszuOQsr3uE4HPjuJ/J31HwyLdfRfXF1OeqwSZ1qze0m8qzzMI3iK9xtjIGjzvTtOsvGBS16YhLb+i5mJVpPvpJ2d17v/Tq5D3kPxSsStJp4GR3uvdHvedSVLTwIv7zh05jGGOjYCGKLV2ewDix9H7tnh0+vIyLiKyqWRSQorOPB/vBffLqWgXXgx/exRfm+iykSBqqdBKoWha8xhsgLLq//8lEeD5HnXVL1tbqPBl/OW20dzNHn+y5eFYwxtL9zEgPWfkabG68mcfBAEk4aQKsJl9Lvh4/p/K87Ma4GfBu29XNwqh93XWsWTPtGh2ww2MXv+P46IiI+0IB/S4tIWNv2PRzc4/u4Bdnw69e+jysSwpqffWrFO1wuEgYeQ3RKi1rFizzzXNwnngL1KPairp6Mu0v3Ko8x8cmYfuPqfI2ywdzQegB0qH59eV+K6dSOjvffzLELXqP356/T+eHbiesR4LWR62LbQvyxMKtxGWgb99sG62CXf+zz64g0ZNaxQXlJ7alYFpHg2PmTb7tXlnC5selrfB9XjhiFu/aQu3odees34RRUvqxPKInt0IbOUyd6PynuBmwi3Liio+jx5F21jmciIoi99zFcx/SrU3fsyN9fStTl19Xs4GMugBa96vf7wrggqhHmpBsDstRSqLOOBw5s9lt8ExsBkYd8P/dsx+Ye8Nv1RETqSrNhS1iIijD8488tSj+Whs/u3uCfwI4Hdv3sn9gStqy1ZH70GRnPvkLWgiWl291JCbS48mJaXPNHotu3CWKG9df5rokkHncs2/79ZunSUe1vuIy4rh3qFM/ExhH3+MvkTbudonnveYvwqib+Mi5wGaKvvYnIS66qcdFqXG4Yfj/2k1tg7/raz3Fg3BAVhxn5MKaR/5daCgsHt4Pjy/W0K5AYCXsOGTKzfQN06evfa4o0ENbWfyRLXa4ptadiWcKC22044djYYKchtZF3wH9TM+arhUJqzikoYPM1f2XvWx+UtrqW8GQeIP3xF9j57Ct0feM5koYNDlKWvtH8zKE0P3Ooz+KZqGhi734Yz7g/Uzh7FoUfvAV5ud6dLhc43v/jpnlLIn9/KZGj/4Crae1nfzbR8TDyYew3z8O6972Fd7W/P4oXlks+GjP4r5j45Fpf94hVVM2SV74QWe5hSa5WMhCRhkfFsogEhz8ntjHu6o8RKfbr9Xey9+0PvZ9U1DLq8WDzHdb//mp6fPYGjfr7dq3xcODu2AX3lDuJvvYmir7+H3bfHsjNhfgEXCmtcQ9Ixbjr9//SRMZiUidhOw3F/vAabP+meIcbrOeQjx3AQuMOmGMugC7D1fW6tvwxRKa88s866vnzIRJSHAsmwE29GrNcJyqWJSwUeSyfLvM+lR5+fCMi3LoxavASW4HL7e027UvGDY1Du7usBE7OD2vY8+rb1R/oWKyniK13PEj3j2b6P7EQZWLjiDxlhH+vkdIbk9IbeyAd0ldi9/wMB3d7i+ToREyzbtDyaGjWTUVyXcXWbsK3Oskt97u/sVr+RaThUbEsYaGwyPLQq3sBGNo/TsVyCDAtu2NXvev7wNYBE4vN3oeJb+L7+BJWdj0/EyLcUFSDhzYehwOLviLvl03EdOvk/+SkSiYhBRJGYrqNDHYqYcdEN8ZGNYaC/X6Jbx0L2YeMiY6MhuT2frmWiEh9aDZsEQmOtv39FNjCF29h7x+J88DvsJ+9gM3a7adrSajb9968mhXKJVwu9s9d4L+ERBqK5r390h3bOhb25v+2KpVxQefe3oncRI4UjvfZfiBfhw19kBpRsSwiQWESU6DDIN/ejFkLBQ4UFd+FZe7EfvY89qFzsF+86l0OReQQngPZtTreuF149mf6KRuRBqTDSL9MwmhcBvvrIZN5WQfXyef7/DoiIr6gbtgiEjRmwFjsr1/7MKCBA+WWO7EOeBzs3Cfhp//B5f/CxMT77pohzhbmwp71sOcXbPZOcIogIhqT1A6aHQVNOoZ1i48rLhZPfs3XUraOgyu+kR8zEmkgmvSChI6Qneazotk6Fgo8kF48Y7oxEN8E+p7ik/gioUJLR4UOFctSZ3u/+4nV9z7N/u/X0vS4Yznmrgkk9eoa7LSkAtZxWDv9JX554v8o2J9F67OG0ufBm2nUrlVQ8zJt+mCPHQM/vlf/3+LWQq4D+VXc1KWtwj4/Ea55BhPl36XGPAUFbHzxv2Rv3EJSzy50vGwMrgY026vN+Am75n3YtNBbIGO8E66V7HeKvB9EJWB7jMJ0H+0dIxpmkk4fwt53Pqp5V2yPQ+KpJ/k3KZEGwBiD7XM9LL7JdzFdBmflvt+6YFuLa+ztGHekz64hIuJLKpalTjLXbGD+iRdhC4uwHg8Hf93O9o8WcdaqD2jUQTMRNzSrpj7B6nufLv087c257FryLaPWziUiNiaImYE56Vps+k+we33dWy+s9Xa9ziys5jgHtq/DfvQ4ZswtdbtWDThFRSwceRUZC5dhItzYwiK2ffA5g//7RNBn57W5+7BfPga/Li675A62uGgup+AArHoTu+pNbJ9LMH3GhtWNbYtr/sjeNz+o2cEuF3F9j6ZRv2P8m5RIA2GSumCPugR+rv8M8NZa+PUg7M4vDu6C40Zg+pxS79giIv6iMctSJz8//gq2yFsoA1iPB09OHr8881qQM5PyPAUFrH1kRplt1uMhJ207W2fPD1JWvzGRsZgx/4KWRwF1KCRLCuU9Bb+1VlR5vANfv4PduKL216qhbe8vIOPzr8FabKG3AN06ez4Zi5b57Zo1Ybcux/73ckj7snhDDVtTS2YHWTkT+9612AM7/JZjoMWfMIDEM4aCuwZ/Dq2lzdSb/Z+USEPS9Q/QcXS9QlhrYXsu9sf93g3GBV374frjnfXPTyQEWccG5SW1p2JZ6uTg5m3Yct0WrbUc/HV7UPKJijDcdVVz7rqqOVERWjbqUIWZ2Xhycg/bbtxuctIaRtFjYhIw5z8Jx13mvYkyNeiuXDLg56AHdhXUbpZH48IumFH9cXWUu2OXdyxeRduDxP66BDv/dijIqcf4QwuZW7AfTMJmbfNpfsFijKHLK48Tf8IA7/esopb/CDe4XXT69z9JGjY48EmKBJExBnpdBb3Gg4mo1aSM1rHeQvmXA9jv9lL6QLTfabgmPo6JjPZP0iIiPqJiWeqkxckDwVXux8daWpzkr+WAquZ2G07pH8cp/eNwa43lMqKbN6FRxzaHFQHW46H5if2ClNXhjDsS1wlXYi6ZAcecDRElN1HG+zp0NgxrIae4SM6qoOtwdawDG5Zjd2/xVfplNB14zOFjsF0umvbr6ZfrVcfuXodd8PfiIrm+Y8MdyM/Czr0ZW1C7maQbKndCPEd9+ArtH76L6M4dyu100+SckfT8/L80u+Tc4CQYRIX7Mtn8z+f5fsx1rL7iNvZ+/lWwU5IgMMZgOv0OhjwGzfoUb3VVONWEtYe0YO0vwP4vA/tL8e+KuARcVz2A++oHMVHBHQIkEkyBXjaqdPkoqTVjreZGq0pWVhZJSUlkZmaSmJgY7HQajMKsbOafdBGZP/6CiYzAFhbRbFBvTvv81aCPgZXDbZuzkP+Nua70c1vkof0FZ3Li69ODPoa2MrYo3zuOeec67GfPQt5BcCwUOlBo613zAZgxt2AGnVf/QBVY88iLrPzLQ2AtJsLNcc/eQ5fxf/DLtapiPQXY2dfAge2+/UtpXNBtBK7Bvpv8pyGw1pKzcjWFO3fhio4i9ujuRLZsXmY/O9dC+mrsrl/g4B7vjtjGmBbdILkHtD4W44f1aQMt99dtLD/xIgrSd4H1Lptlizx0vPUauk4Lr++71I49uAO2fAp718D+X8B6Z5S3Hsc7d8S+AuzWg3CgyPugtl0PzNALMANP9/vkinJkCNX785K813dtT0JNhv/40AGPQ9f1aSH3NQs2FcvVCNX/jIHgycsn7a25ZK5eT5O+PWl73um4o6KCk4vH8r/vvV2NT+4Tq9blCmT+tJ6NL/6Xgn2ZtBoxmLbnj2hQszNXxuZlY+8Z5vvALjcMGI3rvL/5PnaxnK3pHNy8lfiuHYhNaeG361TFfvcK9rtX8cnThQqYMx/GtOrrl9gNifUUwuo52JVvw/4tgPE+MCgZ911SHFsH4lti+pwHvcdgIkO3MPj+vIns/mDBYUNuAI5f8Q6J/Y8OQlbS0FhbPDmg44E96bBjIzY/B9wRmKatoN1RKpDF50L1/ry0WO7SLjjF8oYtIfc1CzbNhi115o6JptOlY4KdBgAFRZa/P78bgDnT2xKrYvkwSb260u9h/80A7TeZGf6J63hg/07/xC4W1zaFuLbBW27JFhVgV/8XfxXKGDd21ZthXyzbXb9g590PezcfurXsBGmHttpnZ2CXPAc/zIYzbse06UOo8eTls+u9z8A5vDeCiXCz842PVCwLUDym2R3pfaV0hJSOdZmqUUSkQQr9fmIiEt78OcjGqeFs0KFq8yIoOOi/+NYDW5dhD6T77xpBZn9ZiH39T7AvDe9Dh5o+eLCQvQv73+uxP8z2Y4b+YYuKKiyUATAGT05eYBMSEREJAhXLItKwxSX5J65xQXwT/8RuIGzal7WaubZuDGz52s/XCA67cQn246nFM6PU4cFK8YMeu/BR7I81XMu5gYiIb0RC/6MPn8gRsIVFNB2eGoSsRETCg7VBmOBLA2/rRN2wRcRvrFMEu3+F9J8hN8tbuCW0gFbdISmlZpOLJTT3Fsw5mT7Pz7Tu7vOYDUrGGv9Pf2lc2D0/h123S3sgA/vx3312d2E/nw4pvTDNu/gkXiB0++df+PaMK71rUHuKf45cLpJO7EeL0acGNzkREZEAULEsIj5nd23CfvMOfD8HCou7axoX3nGexcVHQgsYeD70G41p1LTSWMYYbMe+sHaxb7tNWwc69PZdvAbGFhyEnN0BuJAHdv/s/+sEkLUW+9mD4Cn0bdxP7oeL/o1xhcaf3qanpTJw4atsvOcp9i/5lojGCbS+4nw63X4tJgQmBxQRaaisLV6DPMDXlNoLjb/YIhISbEEu9vNnYdlbYNyVT4AEcGAXduFzsPglOOMG6Pe7SluazfFjsD8t8m2yzdtD+2N9G7Mh8edY5cOuFR7rLZfauQbSvvFtTOuB3Rtg01LocrJvY/tR48ED6T9/RrDTEBERCQqNWRYRn7D7d2D/fRksf7t4Qw1aga2FwjzsnAexb96CLcyv+LhuJ0Czdj4df2tOHttg15j2iYC+t/D6OtofZnsf9viacWG/f8f3cUVERMQvVCxLWIiMMPz10qb89dKmREaE1417KLCZO7Ev/Qky0+s+xvOXL70FcwVdX43LhfnDXb4Zf+tye1uUB/6u/rEasuiEwF0rxk+TsAWBtQ6s/6JuE3pVG9yBrd9i88OsJV5ERGol4JN7Of6fwiRcqViWsBDhNoxMjWdkajwRWmM5oKx1sO/cCdn76jem2DqwcTn2ixcr3G069IZhV9U9PnhbpqPiMBfeg6lglt9wYiJiIKF1AC7khhY9/H+dQNm/FYr8vCzSrl/8G19ERER8IrzvFkXE/5a9BVt/9FFLnIUlr2J3rK1wrxl2FZx8SclntQvtckNMPOaapzFN29QvzVDRspf/l46yHkzzo/x7jUDavdHPFzDescsiInLkcmxwXlJrKpYlLHg8lq9W5fLVqlw8Hv0yCBRbVFBpS3C94lbWumwM5szrMRf+HaLjalYIlhzTeSDm+v/DtAqjwq4apvMp/u935YqA9if69xqBVJjr3/gul/+vISIiIj6h2bAlLBQUWf72zC4A5kxvS6y6YgfGms8h74BvY1oHfl6CzUzHJKUcttsYA31HQJeB2C/fgK/fgdwD3gmtDp2UySny/tv+WMzgi+DoU8N7Qq+KtDkO4pr7bwkp44ZOp2DCaMwyLj8viWSt9wGDiIiINHj6iy0idWbX/c/bcuuP1stfvoSB51W62yQ0w4y4DjvsKtj6E2xbi927DTweiGmEadUN2h2DaRqAcbsNlHG5oe8fsV8+6qcrWMyxF/gpdpAkHv6AxqesAwnJ/r2GiIg0aNbWfT7U+lxTak/FsojU3bYf/VMou1zYHetqNCrZRERBx77QsW+YLWDkI93Pgg0LIGO1z2d4Nn3/iGna2acxg655V7zj4f14V5EcRhOiiYiIhDEVyyJSJ7aoALIy/BPc8UCGJkHyBWNcMOQv2Pf+DIU5vnm4YVzQrBv0uaT6Y0OMiYrDtuhWPGO1HwrmuGaQ2Mr3cetp77er2fPVSnAsScd0o8XQ44+8YQsiIgFiHb8+kq30mlJ7KpZFpG4qWA/Zp4ry/Rv/CGISWsHIf2Ln3gxFufX7i2lc0LgDZsQ0TJiOvTW9x2A/e8gPgQ2mz7kNqgjd/dVKvp3wd/Z9u7p4gnkD1tKoS3v6PXILbc4ZHuwURUREgkazYYtI3URE+Tl+tH/jH2FM826Y0Y9DYltqveyWN4L3n/apmFHTMdGJvkyvYTlqGMQkUrevUxVckdDrLN/GrIeML5bz+dA/sm/lGu8GS+mgtoMbt7D43IlsfvXdoOUnIhKurGOD8pLaU7EsInVi3JGQ6KeJilxuSO7in9hHMNOkA2bMc97u08ZNzYrB4mOi4jGn3I45bSomKt5vOTYEJjIGc9rN+LqTnBn8Z0yjZj6NWVdOURFLL5yMU+QBp4KeBsWzzywbfwd5u/YGPkEREZEGIDz70MkRJzLCcP2FTUo/lgBpezSs2eX7gTCOg2mlSZD8wbgjMQOuwPY6F375GLv2Q8hOr+RgFzQ7CtPrHOg41DuZ2hHCdB2K7X46rPuUehfNxgVt+kLvMT7IzDe2v7+AvPTqlxSzniI2vfg2PW+5JgBZNSzWWsjeBTvXQc5e7wOERs0g+SiIb9mgutMfqazjgfSfYOda7J7NUJQH7ihM0/bQsge0Psb7YFdEpI5ULEtYiHAbxgxNCHYaRxzTfQj2pwX+Cd71RP/EFQBMbGPofRGm90XYvEzYsx6yd3rXp46IhqR20LQL5gjuDm+G/RWblwW/LqPOBbNxQcujMKPv90621kDsmLcYE+HGFlUzQ7pj2TFn0RFVLNu8A7B6Dvb72ZC1o+KD4uKxXbpCpy6Y2CYQ3RqiWkFcV4zryP0/Eyi2MBdW/he78h04uBsw4HJ5H2gY433QYR2ITcL2HoPpdwEmRvcI0nBo6ajQoWJZROquxykQmwi5Wb6LadzQ7URMktaiDRQTkwRtBgQ7jQbHRETB6Puxi5+B7/9byzXFi5efOuo0zKk3YaLi/JlqrXly82pc/xfl5Po3mQbErl+E/fSfkHeAKr9AOdmwaiWs/RHbpxemTSvAAROJje8DSamYyMaBSfoIY7d9j/34PsjOOOTu33pXUSj+sFRuJix7FfvD+3DGrZhOqYFOV0RCXMN5zC1SDx7HsvLnPFb+nIdHExgEjImIwgy9ysdRLWbIlT6OKVI3xh2Ja+j1mPMeg8btSjZWdYL334SWmNH/wDXizgZXKAM0al+z5auM202jTm39nE3wWWtxvngS++Gd1RfKhyosgm9+wP7wU3FrZiEc+Ba2PYPN+sa7TXzG/vQx9q3rvd3ja/q1tQ7k7se+dwv22zf9m6BIDVlMUF5Se2pZlrBQUGi58VHvmr9zprclNlq/EAJm4Hmw+lPYuhpsNV06q2Vg8OWYVt19ktqhrPXA/o2wfz1kpXnHtrkiIL4VNO4KTY7CRMT4/LoSHkzbvvDHl2H7D9g1c2HbD5C5nTJFVUIytDoG02MEdDiuQXW7Lq/juHP56f5nqz3Oejx0Hv/7AGQUXHbJc1BaSNWhwN20BVwGjukOON4Cbc9cyN2IbXkexuh2q77shsXYT6YBdem/6j3efvEkRDfCHD3K5/mJSHjSb28RqRdjXHD+vdgXr4bsPb91hat9IOg8CHPy5T7NzxZkw6a5sPFDyC2e0OjQlkFrAQfcMdiOp0OX32HiW/s0BwkPxhho0wfTpg8AtiAH8rK8P0MxiZjoRkHOsOYSunWk3QVnsvW/87CeiruWmwg3ScccRcoZgwOcXWDZX5fBN7PqH2hDGrZFM0xy89+25fwMO9/GJv8BU1WPBKmSzdmH/eQfvom1YDq07YdJ0u95Ealew33sLSIhwyS0wFz+HDRu7S16a3e295/up2AueADj9t0zPLtjGcz/E6x++bdCGbwt4CUvigsFTx5snAPzr8Wue8s7y6pIFUxUHCYxBZPUKqQK5RLHz5hGi1MHeT9xH3I7YAwYSDiqE0Pm/gfjCt9bBVtUgP3kAe94dF/4bjXWc+jvDgu5v8D+xb6Jf4SyXzwFBbn4ZDk3pwj72cP1jyNSDyUTfAX6JbUXvn8Bxe/s7q3YtV9jM9KCnYo0ACYpGXPNK3DCxYCpelxn6UkGomIwv7sd8/v7fLY0kbUW++PLsPQeyM+kxjdY1vEW0KtfgsW3YwtzfJKPSEMUERfL0LnPk/r6dJqn9sMVFYmJjCDpmG4MfPbvnL78bWJTWgQ7Tf9av9A7m7Kvlr/LL4BtOw/fvv9/2PxKlmiTKtmDe2HdZz4Y5lMS0IG0b7B7f/VNPBEJayFTLO/du5exY8eSmJhI48aNGT9+PNnZ2TU611rLmWeeiTGGd99917+JHgHs/l14Hv8zzt3n4DxxHc495+KZfjV2TyVLbMgRw0RG4xo+EfPnWXD876FMa1u5FuekFMywCZhJ72D6jPLtmqWrX4Gf6zH+EGDPavjybqwn32dpiTQ0rogI2l94FsP+N4s/5P/IBQWrGfnDB3S55kIi4mKDnZ7f2R/e812rconNWyrevne+b69zpFj7CaU9gHzFuLGrP/JtTJFaUMty6AiZMctjx45lx44dzJ8/n8LCQq644gquueYaZs2qfpzRo48+6tsb8SOYLSrEeewa2L2t7I6N3+M8ejWuO9/CRIX/DZZUzTTvgDnjBuzpk2DPFkj/2Tu207ggoQW06o5J8E+Lld3x9SGFcn0CObBnjbfw7n11/eOJSINiPUWQvsZ3rcol9h/AehzMoV3bsZC3GVu4BxPZzLfXC3N2+ypKl2LzWVAPbPved/FEJGyFRLG8Zs0aPv74Y5YvX87AgQMBeOKJJzjrrLN4+OGHad268kkaVq5cySOPPMI333xDq1Y1WypDKmdXLoCKul07Hti7A/vNJ5gTzwl8YtIgGeOC5h28rwCwBdmw4jF8d2NlYf272DYnYZr18kE8EWkw9v0KTpHv41oLB7KhcWK5HS448D00Pc331wxnO/3wQANg13qstWpMkaBwrPcV6GtK7YVEN+ylS5fSuHHj0kIZYPjw4bhcLr7++utKz8vJyeGSSy7hqaeeIiUlpUbXys/PJysrq8xLDrHhO3BVMhbV5Yb13wY2n2IRbsM15zbmmnMbE+HWH74j1qa5UJCFT1sgcMFP/+fDeCLSIOT68e97QWEFGx3Iq6SLtlQur2ZD7mrNU+B9iYhUISSK5fT0dFq2bFlmW0REBE2bNiU9vfIJM6ZMmcKJJ57IOefUvKVz2rRpJCUllb7atWtX57zDUmR0/fb7SWSE4aLTE7no9EQiI1QsH4ms9XiXh/JpoQzgwK7vsdnbqj9UREKHP1sUKwtdsAOrgYO149fvk5bzEqmpBx54AGMMkydPLt2Wl5fHhAkTaNasGfHx8Zx//vns3Fl2ksO0tDRGjRpFXFwcLVu25C9/+QtFRWV79SxcuJD+/fsTHR1N165deemllwLwjmomqMXyrbfeijGmytfatWvrFPv9999nwYIFPProo7U677bbbiMzM7P0tWWLngIfyvQbXvk6uo4H0394YBMSKbF/Y9nloXzKBduX+im2iARFQrL/YsdWMneHLfS+pOYSWlZ/TF3EJPl0qUKR2rDWBOVVV8uXL+e5556jd+/eZbZPmTKFDz74gLfeeotFixaxfft2zjvvvNL9Ho+HUaNGUVBQwJdffsnLL7/MSy+9xF133VV6zKZNmxg1ahSnnnoqK1euZPLkyVx11VXMmzevzvn6UlB/S9x0001cfvnlVR7TuXNnUlJSyMjIKLO9qKiIvXv3Vtq9esGCBWzYsIHGjRuX2X7++edz8skns3DhwgrPi46OJjo6OK2jIaHjMXD8KFg2h7LjQg30PQ2OOi4oaXkcyy9p3u5U3dpH4XapdfmIs299aMcXkcBKTIGoRlBw0Ldx3W5oVMVEl/4YfxvOUo6GfVt9t3QUAAZSevownkj4ys7OZuzYsfznP//hvvvuK92emZnJCy+8wKxZszjtNO9cDDNmzKBnz5589dVXnHDCCXzyySf89NNPfPrppyQnJ9O3b1/uvfdebrnlFqZOnUpUVBTPPvssnTp14pFHHgGgZ8+eLF68mOnTpzNixIigvOdDBbVluUWLFvTo0aPKV1RUFKmpqezfv58VK1aUnrtgwQIcx2HQoEEVxr711lv54YcfWLlyZekLYPr06cyYMSMQby8sGWNwXXo35oJboGV7cEdCi7aY86fguvIfQZsoo6DQct1DO7nuoZ0UFKqL2xHpwK9+7FLnwP4NfootIsFgjIFOqb79vWEMJDev+m+hK9J31zsCmPYDfVwoHxJXJEhCaemoCRMmMGrUKIYPL9t7dMWKFRQWFpbZ3qNHD9q3b8/Spd7eeEuXLuXYY48lOfm3njwjRowgKyuL1atXlx5TPvaIESNKYwRbSPQ/6dmzJyNHjuTqq6/m2WefpbCwkIkTJ3LRRReVzoS9bds2hg0bxiuvvMLxxx9PSkpKha3O7du3p1OnToF+C2HFuNyYoRfA0AuCnYrIb4ry/Bvf4+f4IhJwps+52HWf+i6gtdCpbeX7I5pgNE62droOgegEyD/gu5juCOh1pu/iiYSQ8pMXV9Wr9vXXX+fbb79l+fLlh+1LT08nKirqsF68ycnJpXNKpaenlymUS/aX7KvqmKysLHJzc4mtbFhLgITEBF8AM2fOpEePHgwbNoyzzjqLwYMH8+9//7t0f2FhIevWrSMnJyeIWYpI0Lj8/OzP3/FFJPBaHQPt+vumddkYaNoYmjWp7ACIblP/6xxhTEQU5rixvowIfc7DxCT4MKZI6GjXrl2ZyYynTZtW4XFbtmzhhhtuYObMmcTExAQ4y4YjZO7+mjZtyqxZsyrd37Fjx2pnmNQMlCJhrFErP44FNBBfRWuRiIQkYwycfiv2lUuhyKFes+kbA/2PqaILtoW4bnWPfyTrfwGsWwC719fv97xxQUIyJnW873ITqaNgVSVbtmwhMfG3deAra1VesWIFGRkZ9O/fv3Sbx+Phiy++4Mknn2TevHkUFBSwf//+Mq3LO3fuLO3dm5KSwrJly8rELZkt+9Bjys+gvXPnThITE4Peqgwh1LIsIlKlxl3x258e44ImuskVCUcmMQUz6l7v//M6BwGO642pamIvVyw00qRSdWFcEZjRf4eYhLp/n4wLIqIxZ9+PiTxyW8lEEhMTy7wqK5aHDRvGqlWrysz/NHDgQMaOHVv6cWRkJJ999lnpOevWrSMtLY3U1FQAUlNTWbVqVZmJmufPn09iYiK9evUqPebQGCXHlMQItpBpWRYRqVLT7uCOBk++72NbD7Ts6/u4ItIgmE4nwDkPYufcAUX5NZ8Jxxhwu2DgsZjkFlUfm5Sq8cr1YJJawwVPY/87GQ7uqV0Ls3FBdDzm3EcwLbr6LUeRmqrvUk51vWZtJCQkcMwxx5TZ1qhRI5o1a1a6ffz48dx44400bdqUxMREJk2aRGpqKieccAIAZ5xxBr169eLSSy/loYceIj09nTvuuIMJEyaUFunXXnstTz75JH/961+58sorWbBgAW+++SZz5szxwbuuP7Usi0hYMBEx0OH0+rUOVaZRa2h+rO/jikiDYToeD+NmQuviIRdVzWhdsq9lcxh2UjWFsoHIlpB0gs9yPVKZJu0wl74CR48q3lDNw4eS/V2HYsb9Hya5u38TFDnCTJ8+ndGjR3P++eczZMgQUlJSeOedd0r3u91uPvzwQ9xuN6mpqfzxj3/ksssu4+9//3vpMZ06dWLOnDnMnz+fPn368Mgjj/D88883iGWjAIzVQN4qZWVlkZSURGZmZpn+/dKwFBZZZn6cCcDYkUlERmid5SORPbANPv2z75cZ6X8DpuMZvo0pYS1vzc/sef7/yFv7C5Ht2tDsyktodHz/6k+UoLMFu7DrHoPNv0LGbsg+WHaER0IjaNEMOrbBJMRXE814C7bWV2Kikqs5VmrD7t6I/eFdWDu/4rWyI2Og26mY3mMwWlM57ITq/XlJ3subtCPeHw/3q5BtHY7btyXkvmbBpmK5GqH6n1HkSGXXvgE/veKbYMYFzY6Gk6cFbQ1xCT2ZH8zj13ETAAMeD0S4ochD6wfvovm1lwc7PakBm/sr7JwF1oP1FEFBoXdHVCTGXdOu1Mb7OyT5Ykyslqz0F2stZO2APZugMA/cUdCsIzRugwlwMSKBE6r35yqWQ4/GLItIeDnq97BzBexdU/9ZUyPjYeCNKpSlxpycXLZcezM49refvyJvT4ftt91H4ugziGrbOogZSk2Y2A7YVuMg420MWRBb27HGBtwJ0PL3mBgtF+VPxhhIau19iYj4mB65SVhwHMum7QVs2l6A46izxJHMuNxw4lRochTeKWrrEsTtLZRPnoaJa+nL9CTMHZi/ECf7YKUTRGXO/ijAGUldmejW0ObPkHg83tulmvw+Md5jE4+Dtn9WoSwiFbI2OC+pPbUsS1jIL7SMvy8dgDnT2xIbrZbAI5mJjMMOvh9Wvwwb3ve2EtemlblZL2+LsgplqSVPdgVjJ0u4XHgOHAhcMlJvxhUJzc7ANj4JDnwH2augcHfFB0c2g/hjIaEfxl3dWGYREQkFKpZFJCyZiBjo8ydsm5Pgp/+D3auKi2aAQwvn4nGF1gONWkH3C6DD6ep6LXXSaFAVk3gVFdFo0MDAJSM+Y9yNoPFgaDwY6xRCQQY4uYD1rp8c1RLjigp2miISIqw12Lr2fqvHNaX2VCyLSFgzzY+BIQ9gD2yB7Uth33rI3OBdS9UVAQltoUk37zrKzXurSJZ6ie7amaTzR3u7WzuHPJRxu4ntewzxp54UvOTEJ4wrEtS9WkTkiKBiWUSOCCahHXRvF+w05AjQ7pl/EtmyOXtmvIbNywe3m8bnj6b1Q1MxLk0VIiIiEipULIuIiPiQKzqa1g/cRfIdN1G4PZ2IFs2JaJIU7LRERKSBsJRdvj1Q15TaU7EsIiLiB+74RriP6hLsNERERKSOVCyLiIiIiIgEiLVBaFlW03KdqFiWsBDhNlwwPKH0YxERERERkfpQsSxhITLCcO15TYKdhoiIiIhIlRxrcAK8dJSjpaPqRNNyioiIiIiIiJSjlmUJC45jydjnAaBlEzcul56eiYiIiIhI3alYlrCQX2i55M7tAMyZ3pbYaBXLIiIiItLwaIKv0KFu2CIiIiIiIiLlqGVZREREREQkQNSyHDrUsiwiIiIiIiJSjoplERERERERkXLUDVtERERERCRALAYb4HWWA329cKGWZREREREREZFy1LIsYcHtMpwzJL70YxERERGRhkgTfIUOFcsSFqIiDTdc1DTYaYiIiIiISJhQsSwiIiI+Yw/uhN0/wb71cHAHeIrAHQUJbaFpV2jWCxOrh5sicuRyLDhBuKbUnoplCQvWWjKzvb92kuJdGKOu2CIigWKtA9uWwvoPION770bjBuspPsKAcRV/brBtToBu52Ba9glWyiIiItVSsSxhIa/Act4t2wCYM70tsdEqlkVEAsFm74Bl/4LdP3oL4tIdnkOPOuRzC9u/hm1LsW0HQ/8JmJjGAcxYRESkZlQsi4iISJ3YrUvgq4fAFhVvqGHHwpLjtn0JGSuxg+/BNO/l+/wKC3C+XIDnmyU4a1Zi9+4GDCalDa6evXGfOAxXvxMwLi0OIiKBY20Qlo6yakiqCxXLIiIiUmt2y/9g6bSSz+oYxIGCHFh4K/aUaZjmR/smN8fBM+dNCmc8Bpn7wO0Gz28t3TZzL571a/C8OxPTqh2RE/6GO/VUn1xbRETChx6lioiISK3YfevhqwfwFsn1nTXGAccDX9yJzdld/9yy9lPwlysofHSqt1CGMoVyKY+3Ndymb6Xgjj9T8NDfsIUF9b6+iEh1rA3OS2pPxbKIiIjUmPUUerte+5QDnnz45lFsPe7o7IFM8m+8FOeHb2pxkvd6nk9mUzD1emxRYZ2vLyIi4UXFsoiIiNTcL+/Cga01H59cU9aB9BWwdXHdTreWgofvwP660dtSXfsAOF8vouj/nqnT9UVEJPyoWBYREZEasY4Hfn6X+ne9roRxwc+z63Sq88U8nMXz61Yol7CWopnP4mxYV/cYIiLVCUYXbHXDrhMVyxIW3C7DiBMaMeKERrhdmu1PRMQvdiyHvL3+i28d2LMGm7m5dqdZS+GrT4Pxwe9/Yyh84/n6xymWv3UH6S+8yY5/v0buhl99FldERPxPs2FLWIiKNNxyWbNgpyFyRMjbvJUdz80ib2Ma8f2OJuXqi4hs1iTYaUkg7PwWjLvcGsq+ZmDnd5DUscZn2J9/xG762TeX93hwFs7FTroDk5BU5zDWWjbf+iDbHp0Bzm9d1luOO5+uz9yLKzLSF9mKSAgKRkOvGpbrRsWyiIjUWPa3q/nh1Itx8gvAcdjz7nx2PDuTvkvfIapVy2CnJ/62d52fC2W8rcP71tfqFM8P33i7cPtqHLWnCGfdKtwDB9c5xPbHXmLbv144bHvGK+8QldycjvffXJ8MRUQkANQNW8KCtZbcfIfcfKdeM6mKSNU23fYQTn6+dykea8FxKEjfzdZHfNdtVRqwzDT/X8M6sG9D7U7ZsNY3XbBLuNw4v6yp8+nWcdj6yH8q2WnZ/tQreHJy6xxfREKbY01QXlJ7KpYlLOQVWEZN2cqoKVvJK1CxLOIvWYuXg6dc653Hw/4FS4OTkASWJ0DrEBfVrpC0BzLrN7FXeS4XZGfV+fTC3fsoTN9V6X7nYC55GwLw4EFEROpFxbKIiNRYZIsK5gZwu4hurS7YRwQToNsGVy1HiUVE+rZl2VqIqPtINXd8HLir/lpFNEmsc3wREQkMFcsiIlJjbW644vCNHofWk8YFPhkJvNgATeQWV7uHL662HcHl9t31PUWYtp3qfLo7Lpbm540EdwU5ud0kDh5IdNtW9UhQREJZoJeNKl0+SmpNxbKIiNRY6xsup/1d1+OKjwMgMrk53Z5/gCYjhgQ5MwmIpj3837ps3NC0e61OcXU/BjxFPk3D1f2Yep3f8YFbiGzZtGwLs9uNOz6OLk/cU8/sREQkEDQbtoiI1JhxuWh/5yTa/vUaivZmEtmyGaai1jMJT816wNbF/r2G9UCzWhbLx50MMbGQ54NJs4zBdOiKaVf3lmWAmPat6bf8fXY8/Sq735mH9XhoOuo0Wk8aR0z71vXPU0RClrVBWDpKLct1omJZRERqzRUdraWijkTtT4EfXvDvXVdkPKQMqNUpJjYO96gL8Mx+tcyaxnViLRHnXYbxwRjoqOTmdLhnCh3umVLvWCIiEnjqhi0iIiI1YmKbQpuT/NcV27igy1kYd1StT4289DpIbFK/ib7cbkz3Y3GPPK/uMUREJGyoWJaw4HYZhvSLZUi/WNwurSMnIuI3x/wR/9w+GIiIg6POrdvZCUlE3fZQcbFch78DLhdExRB124MaWiAifuWdcMsE+BXsdx2aVCxLWIiKNEy9ugVTr25BVKSKZRERfzGJ7eHYy/wQ2cJxN2BiGtc5gnvgSUTdOd07qVZtZsd2uyE2juiHX8LVrnOdry8iIuFFxbKIiIjUzlHnQcpA6tSCW5kuozBtB9c7jHvICKKffhvTvrjodVVxq1NcULv6DiL6+Q9w9Ti23tcXEamODdJLak/FsoiIiNSKcbnhxDsguT8+KZg7jYD+19U/TjFX155EP/cOkbc/jOnRu+JxzG43ruMGE/XAf4h68AVcLbXusYiIlKXZsCUs5OY7jJqyFYA509sSG63nQCIi/mQiorGD74afXoM1r3sLUluLmaiN2zuhV5+roOvZPpl9umx+kUScNpqI00Zjc3NwNqyFvbu8S0Mlt8F06oaJrP1EYiIicuRQsSwiIiJ1YtyRcOxl2LYnwsrnYNeP3iLYeqo4yeWd3abVcdD3aky8/9ccNrFxuI/p7/friIjUhNZZDh0qlkVERKReTJOucOo/sVlpsHEe7FoFmZvAKfrtIHc0NOkKLftA55GYuBbBS1hERKQGVCyLiIiIT5jE9tD3agCs44G8fd6C2R0FMY0x/lqfWUQkhDjW4PhygsQaXlNqT8WyiIiI+JxxuSGuebDTEBERqTMVyyIiIiIiIgFiCfwYYg1Zrhv1hxIREREREREpRy3LEhbcLsOgo2NKPxYREREREakPFcsSFqIiDdMmtAx2GiIiIiIiVXKKX4G+ptSeumGLiIiIiIiIlKOWZRERERERkQBRy3LoUMuyhIXcfIezJm/hrMlbyM3XrwMREREREakftSxL2Mgr0KT4IiIiIiLiGyqWRUREREREAkTdsEOHumGLiIiIiIiIlKOWZRERERERkQDS4MHQoJZlERERERERkXLUsiwiIiIiIhIgGrMcOlQsS1hwGejTLbr0YxERERERkfpQsSxhITrKxfQpycFOQ0REREREwoSKZRERERERkQBRN+zQoQm+RERERERERMpRy7KEhdx8h0vu3A7ArHtbExut50AiIiIi0vCoZTl0qFiWsJGZrV8DIiIiIiLiG2p+ExERERERESlHLcsiIiIiIiIBom7YoUPFsoiISIiy1sL+HbB9HWTvA2MgKRnadMfENwt2eiIiIiFNxbKIiEiIsTmZ8M372K/ehsydFR+T3AWT+gfoOxITGRPgDEVEpDJqWQ4dKpZFRERCiF39OXb2NMg7ANZWfmDGRuy7D8AXr8IfpmLaHxu4JEVERMKAimUJCy4D3dtHlX4sIhJurLXYT572Fr8YoIpC2XuC9999O7D/vgbG/A0z8Gx/pykiItVQy3LoULEsYSE6ysUzt6YEOw0REf/5/MXiQhmqLZQPZb23SHb2/RAdizl2uO9zExERCUNaOkpERKSBs2mrsJ89X/8479yPzczwQUYiIiLhT8WyiIhIA2atxb5zn3em6/oqKsDOmV7/OCIiUmdOkF5SeyFTLO/du5exY8eSmJhI48aNGT9+PNnZ2dWet3TpUk477TQaNWpEYmIiQ4YMITc3NwAZSyDlFThcfMc2Lr5jG3kF+nUgImFk4zew69fS7tT14njgp4XY/RXPoC0iIiK/CZlieezYsaxevZr58+fz4Ycf8sUXX3DNNddUec7SpUsZOXIkZ5xxBsuWLWP58uVMnDgRlytk3rbUkLWwc6+HnXs9VU4OKyISauy3H4HL7cOIBr6f58N4IiJSG2pZDh0hMcHXmjVr+Pjjj1m+fDkDBw4E4IknnuCss87i4YcfpnXr1hWeN2XKFK6//npuvfXW0m3du3cPSM4iIiI+8ev33hZhH7JbfkQLB4iIiFQtJJpYly5dSuPGjUsLZYDhw4fjcrn4+uuvKzwnIyODr7/+mpYtW3LiiSeSnJzM0KFDWbx4caDSFhERqRdbmA/7tvs4qAPb1/k2poiISBgKiWI5PT2dli1bltkWERFB06ZNSU9Pr/CcjRs3AjB16lSuvvpqPv74Y/r378+wYcP45ZdfKr1Wfn4+WVlZZV4iIiJBUZjnn7gFmrtDRCRY1A07dAS1WL711lsxxlT5Wrt2bZ1iO473R+JPf/oTV1xxBf369WP69Ol0796dF198sdLzpk2bRlJSUumrXbt2dbq+iIhIvUVE+ylulH/iiohIWHjmmWfo3bs3iYmJJCYmkpqayty5c0v35+XlMWHCBJo1a0Z8fDznn38+O3eWnTwyLS2NUaNGERcXR8uWLfnLX/5CUVFRmWMWLlxI//79iY6OpmvXrrz00kuBeHs1FtQxyzfddBOXX355lcd07tyZlJQUMjLKrgtZVFTE3r17SUlJqfC8Vq1aAdCrV68y23v27ElaWlql17vtttu48cYbSz/PyspSwSwiIkFhomKwCc3hwG5fRoXkLj6MJyIitWEJfEtvbee/bdu2LQ888ADdunXDWsvLL7/MOeecw3fffcfRRx/NlClTmDNnDm+99RZJSUlMnDiR8847jyVLlgDg8XgYNWoUKSkpfPnll+zYsYPLLruMyMhI/vGPfwCwadMmRo0axbXXXsvMmTP57LPPuOqqq2jVqhUjRozw8VegboJaLLdo0YIWLVpUe1xqair79+9nxYoVDBgwAIAFCxbgOA6DBg2q8JyOHTvSunVr1q0rOy7r559/5swzz6z0WtHR0URH++lJvviNMdChVWTpxyIiYaPdMbDmC98sHQXgckHbXtUfJyIiR6yzzz67zOf3338/zzzzDF999RVt27blhRdeYNasWZx22mkAzJgxg549e/LVV19xwgkn8Mknn/DTTz/x6aefkpycTN++fbn33nu55ZZbmDp1KlFRUTz77LN06tSJRx55BPA2ai5evJjp06c3mGI5JMYs9+zZk5EjR3L11VezbNkylixZwsSJE7noootKZ8Letm0bPXr0YNmyZQAYY/jLX/7C448/zttvv8369eu58847Wbt2LePHjw/m2xE/iIlyMePOVsy4sxUxUSHxYy0iUiOmzxm+K5QBHI83poiIBIUN0quuPB4Pr7/+OgcPHiQ1NZUVK1ZQWFjI8OHDS4/p0aMH7du3Z+nSpYB3guZjjz2W5OTk0mNGjBhBVlYWq1evLj3m0Bglx5TEaAhCYukogJkzZzJx4kSGDRuGy+Xi/PPP5/HHHy/dX1hYyLp168jJySndNnnyZPLy8pgyZQp79+6lT58+zJ8/ny5d1P1MRERCRM8hEN8MDu6l3gvJu9zQ/lhMy06+yU1EREJK+cmLq+pVu2rVKlJTU8nLyyM+Pp7Zs2fTq1cvVq5cSVRUFI0bNy5zfHJycunky+np6WUK5ZL9JfuqOiYrK4vc3FxiY2Pr/D59JWSK5aZNmzJr1qxK93fs2BFbwU3ErbfeWmadZRERkVBi3BFwzi3YmX/1Tbzf/cUncUREJPSUn4vp7rvvZurUqRUe2717d1auXElmZiZvv/0248aNY9GiRQHIsuEImWJZpCp5BQ5/ftA7A98ztySrK7aIhBXTawi2/yj49iPq05nOnHEdRpN7iYgEVTCWciq53pYtW0hMTCzdXtVcTVFRUXTt2hWAAQMGsHz5ch577DEuvPBCCgoK2L9/f5nW5Z07d5ZOvpySklI6PPbQ/SX7Sv4tP4P2zp07SUxMbBCtyhAiY5ZFqmMt/LqjkF93FNa7l6KISENkxtwGvYbU5UzvPz2HYHP34rz5N5w3bsF57z7s129it/1UYc8sEREJPyVLQZW8ajOxseM45OfnM2DAACIjI/nss89K961bt460tDRSU1MB7wTNq1atKrOi0fz580lMTCxdrSg1NbVMjJJjSmI0BGpZFhERCQHGHQEX3Q+LZ2I//bd3o+Op5iSXd4kAt4UN/4NNEcXnWHC5sd9/5H3a2LwDpF4C/UZjjJ6ji4j4UzBblmvqtttu48wzz6R9+/YcOHCAWbNmsXDhQubNm0dSUhLjx4/nxhtvpGnTpiQmJjJp0iRSU1M54YQTADjjjDPo1asXl156KQ899BDp6enccccdTJgwobRAv/baa3nyySf561//ypVXXsmCBQt48803mTNnjo/ffd2pWBYREQkRxh0BQ8d5W4kXz4KVH4On0FsUu4qLXMfjLYAjosAWQoT5bWIwp+i3YIcW2rvTsB9Mg+8+gHPvwjQtO6ZNRESOLBkZGVx22WXs2LGDpKQkevfuzbx58zj99NMBmD59eumky/n5+YwYMYKnn3669Hy3282HH37In//8Z1JTU2nUqBHjxo3j73//e+kxnTp1Ys6cOUyZMoXHHnuMtm3b8vzzzzeYZaMAjFXfqyplZWWRlJREZmZmmf790rDk5juMmrIVgDnT2xIbrZYREQl/Ni8btqyG7euw2Xu9Pa4TWsL6xfDrt7VfeN7lhsgYzGVPYFr39EvOIiL1Far35yV5P0kXYnEH9Nq5eJjIhpD7mgWbWpZFRERClImJh26DoNugkpHJOO//A9JW1r5QBm9rc0Eu9pVJ8KeXMU3a+DJdEREhNLphi5ea30RERMKEXfc/b1fqesyYjXWgMA/77r1Yq9srERE5cqlYlrBgDCQ3dZPc1F2nxhQRkVBnPYXeccf44Jeg44G07+GHefWPJSIiZThBekntqRu2hIWYKBev3afugiJyBFuzEA7u8108Y7BfvY7pc6bvYoqIiIQQtSyLiIiEAfvdB95ZsX0W0EL6z9iMjb6LKSIialkOISqWRUREQpy1Frau9o439rVtq30fU0REJASoG7aEhfwCh8n/ygDg0RtbEh2l50AicgTJTIeCHN/HdUVg03/xxShoERGRkKNiWcKCY2FdWkHpxyIiR5T8g/6Jay3kZ/sntojIEUpLR4UONb+JiIiEOpfbP3EN4NJzdREROTLpL6CIiEioa9zKu4ae9XHXGmsxTbTSgIiIL6llOXSoZVlERCTEmcgYaNrO94GtA617+D6uiIhICFCxLCIiEg56DPXt0lEAUbHQrrdvY4qIiIQIFcsiIiJhwAw817dLR7nc0O93mKhY38UUEREsgV9jWfPf1o2KZQkbSfEukuL1Iy0iRybTuBX0P8d3rcvuSMyJl/gmloiISAjSBF8SFmKjXcx+qG2w0xARCSpzxiTsL0sge2+9W5nNmTdiElv6KDMRESmhCb5Ch5rhREREwoSJboS55F8QGVO/FubjL4C+o32XmIiISAhSsSwiIhJGTEo3zBXPQkLz2hXMJccOuQIzcjLGGP8kKCJyhAv0eOVgtGSHCxXLEhbyCxymTN/JlOk7yS/QrwMRObKZlG6YCa/BwHO9RXBVRbPL7f23aVvMlc/hOvUaFcoiIiJozLKECcfC97/kl34sInKkM1FxmLNuxp48Dr59H7tuMWRsAE/hbwcltIAOfTH9RkOngRhfLz0lIiISwlQsi4iIhDGT0AKGjscMHY/1FMHBveB4ICYeE5MQ7PRERI44muArdKhYFhEROUIYdwRohmsREZEaUbEsIiIiIiISILb4FehrSu1pcJKIiIiIiIhIOSqWRURERERERMpRN2wJGzFRWupERERERBo2TfAVOlQsS1iIjXbx0aPtgp2GiIiIiIiECRXLIiIiIiIiAaKW5dChMcsiIiIiIiIi5ahYlrBQUGi57akMbnsqg4JCTY4vIiIiIiL1o27YEhY8juXr1XmlH4Mm+xIRERGRhkfdsEOHWpZFREREREREylHLsoiIiIiISICoZTl0qGVZREREREREpBy1LIuIiIiIiASIWpZDh1qWRURERERERMpRy3I1rPUuQ5SVlRXkTKQqufkORQUHAO/3qjBaz4FEREREwlHJfXnJfXqoyQ9CO28wrhkOVCxX48ABbwHWrl27IGciNZXyQrAzEBERERF/O3DgAElJScFOo8aioqJISUlhevqmoFw/JSWFqKiooFw7VBkbqo9kAsRxHLZv305CQgLGHL52b1ZWFu3atWPLli0kJiYGIUMJRfq5kbrQz43Uln5mpC70cyN1EcifG2stBw4coHXr1rhcodWbMC8vj4KCgqBcOyoqipiYmKBcO1SpZbkaLpeLtm3bVntcYmKi/qBIrennRupCPzdSW/qZkbrQz43URaB+bkKpRflQMTExKlhDSGg9ihEREREREREJABXLIiIiIiIiIuWoWK6n6Oho7r77bqKjo4OdioQQ/dxIXejnRmpLPzNSF/q5kbrQz42EI03wJSIiIiIiIlKOWpZFREREREREylGxLCIiIiIiIlKOimURERERERGRclQsi4iIiIiIiJSjYrmennrqKTp27EhMTAyDBg1i2bJlwU5JGrAvvviCs88+m9atW2OM4d133w12StLATZs2jeOOO46EhARatmzJmDFjWLduXbDTkgbumWeeoXfv3iQmJpKYmEhqaipz584NdloSQh544AGMMUyePDnYqUgDNnXqVIwxZV49evQIdloiPqNiuR7eeOMNbrzxRu6++26+/fZb+vTpw4gRI8jIyAh2atJAHTx4kD59+vDUU08FOxUJEYsWLWLChAl89dVXzJ8/n8LCQs444wwOHjwY7NSkAWvbti0PPPAAK1as4JtvvuG0007jnHPOYfXq1cFOTULA8uXLee655+jdu3ewU5EQcPTRR7Njx47S1+LFi4OdkojPaOmoehg0aBDHHXccTz75JACO49CuXTsmTZrErbfeGuTspKEzxjB79mzGjBkT7FQkhOzatYuWLVuyaNEihgwZEux0JIQ0bdqUf/7zn4wfPz7YqUgDlp2dTf/+/Xn66ae577776Nu3L48++miw05IGaurUqbz77rusXLky2KmI+IValuuooKCAFStWMHz48NJtLpeL4cOHs3Tp0iBmJiLhLDMzE/AWPiI14fF4eP311zl48CCpqanBTkcauAkTJjBq1Kgy9zciVfnll19o3bo1nTt3ZuzYsaSlpQU7JRGfiQh2AqFq9+7deDwekpOTy2xPTk5m7dq1QcpKRMKZ4zhMnjyZk046iWOOOSbY6UgDt2rVKlJTU8nLyyM+Pp7Zs2fTq1evYKclDdjrr7/Ot99+y/Lly4OdioSIQYMG8dJLL9G9e3d27NjBPffcw8knn8yPP/5IQkJCsNMTqTcVyyIiIWLChAn8+OOPGg8mNdK9e3dWrlxJZmYmb7/9NuPGjWPRokUqmKVCW7Zs4YYbbmD+/PnExMQEOx0JEWeeeWbpx71792bQoEF06NCBN998U0M+JCyoWK6j5s2b43a72blzZ5ntO3fuJCUlJUhZiUi4mjhxIh9++CFffPEFbdu2DXY6EgKioqLo2rUrAAMGDGD58uU89thjPPfcc0HOTBqiFStWkJGRQf/+/Uu3eTwevvjiC5588kny8/Nxu91BzFBCQePGjTnqqKNYv359sFMR8QmNWa6jqKgoBgwYwGeffVa6zXEcPvvsM40JExGfsdYyceJEZs+ezYIFC+jUqVOwU5IQ5TgO+fn5wU5DGqhhw4axatUqVq5cWfoaOHAgY8eOZeXKlSqUpUays7PZsGEDrVq1CnYqIj6hluV6uPHGGxk3bhwDBw7k+OOP59FHH+XgwYNcccUVwU5NGqjs7OwyT1s3bdrEypUradq0Ke3btw9iZtJQTZgwgVmzZvHee++RkJBAeno6AElJScTGxgY5O2mobrvtNs4880zat2/PgQMHmDVrFgsXLmTevHnBTk0aqISEhMPmQmjUqBHNmjXTHAlSqZtvvpmzzz6bDh06sH37du6++27cbjcXX3xxsFMT8QkVy/Vw4YUXsmvXLu666y7S09Pp27cvH3/88WGTfomU+Oabbzj11FNLP7/xxhsBGDduHC+99FKQspKG7JlnngHglFNOKbN9xowZXH755YFPSEJCRkYGl112GTt27CApKYnevXszb948Tj/99GCnJiJhZOvWrVx88cXs2bOHFi1aMHjwYL766itatGgR7NREfELrLIuIiIiIiIiUozHLIiIiIiIiIuWoWBYREREREREpR8WyiIiIiIiISDkqlkVERERERETKUbEsIiIiIiIiUo6KZREREREREZFyVCyLiIiIiIiIlKNiWUREJIBOOeUUJk+eXO1xQ4YMYdasWf5PqJxbb72VSZMmBfy6IiIiDY2KZRGREGStZfjw4YwYMeKwfU8//TSNGzdm69atQcjMfy6//HKMMRhjiIyMJDk5mdNPP50XX3wRx3GCnV6NvfPOO9x7771VHvP++++zc+dOLrroogBl9Zubb76Zl19+mY0bNwb82iIiIg2JimURkRBkjGHGjBl8/fXXPPfcc6XbN23axF//+leeeOIJ2rZtW+N4BQUF/kjT50aOHMmOHTvYvHkzc+fO5dRTT+WGG25g9OjRFBUVBTu9GmnatCkJCQlVHvP4449zxRVX4HIF/s908+bNGTFiBM8880zAry0iItKQqFgWEQlR7dq147HHHuPmm29m06ZNWGsZP348Z5xxBu3bt+f4448nOjqaVq1aceutt5YpJk855RQmTpzI5MmTS4ujzZs3Y4xh5cqVpcft378fYwwLFy4EYOHChRhj+Oyzzxg4cCBxcXGceOKJrFu3rkxu9913Hy1btiQhIYGrrrqKW2+9lb59+5Y55vnnn6dnz57ExMTQo0cPnn766Wrfc3R0NCkpKbRp04b+/fvzt7/9jffee4+5c+fy0ksvlR6XlpbGOeecQ3x8PImJiVxwwQXs3LmzdP/UqVPp27cvr776Kh07diQpKYmLLrqIAwcOlB7jOA7Tpk2jU6dOxMbG0qdPH95+++3S/SVfi3nz5tGvXz9iY2M57bTTyMjIYO7cufTs2ZPExEQuueQScnJyynztq+qGvWvXLhYsWMDZZ59dZvvatWsZPHgwMTEx9OrVi08//RRjDO+++26ZfPbv3196zsqVKzHGsHnzZgBeeuklGjduzLx58+jZsyfx8fGlDyAOdfbZZ/P6669X9+0QEREJayqWRURC2Lhx4xg2bBhXXnklTz75JD/++CPTp0/nrLPO4rjjjuP777/nmWee4YUXXuC+++4rc+7LL79MVFQUS5Ys4dlnn63VdW+//XYeeeQRvvnmGyIiIrjyyitL982cOZP777+fBx98kBUrVtC+ffvDWilnzpzJXXfdxf3338+aNWv4xz/+wZ133snLL79c66/BaaedRp8+fXjnnXcAb5F7zjnnsHfvXhYtWsT8+fPZuHEjF154YZnzNmzYwLvvvsuHH37Ihx9+yKJFi3jggQdK90+bNo1XXnmFZ599ltWrVzNlyhT++Mc/smjRojJxpk6dypNPPsmXX37Jli1buOCCC3j00UeZNWsWc+bM4ZNPPuGJJ56o8ftZvHgxcXFx9OzZs3Sbx+NhzJgxxMXF8fXXX/Pvf/+b22+/vdZfK4CcnBwefvhhXn31Vb744gvS0tK4+eabyxxz/PHHs3Xr1tIiW0RE5IhkRUQkpO3cudM2b97culwuO3v2bPu3v/3Ndu/e3TqOU3rMU089ZePj463H47HWWjt06FDbr1+/MnE2bdpkAfvdd9+Vbtu3b58F7Oeff26ttfbzzz+3gP30009Lj5kzZ44FbG5urrXW2kGDBtkJEyaUiX3SSSfZPn36lH7epUsXO2vWrDLH3HvvvTY1NbXS9zlu3Dh7zjnnVLjvwgsvtD179rTWWvvJJ59Yt9tt09LSSvevXr3aAnbZsmXWWmvvvvtuGxcXZ7OyskqP+ctf/mIHDRpkrbU2Ly/PxsXF2S+//LLMdcaPH28vvvjiSr8W06ZNs4DdsGFD6bY//elPdsSIEaWfDx061N5www2Vvs/p06fbzp07l9k2d+5cGxERYXfs2FG6bf78+Raws2fPLpPPvn37So/57rvvLGA3bdpkrbV2xowZFrDr168vPeapp56yycnJZa6XmZlpAbtw4cJK8xQREQl3alkWEQlxLVu25E9/+hM9e/ZkzJgxrFmzhtTUVIwxpcecdNJJZGdnl5n0a8CAAXW+Zu/evUs/btWqFQAZGRkArFu3juOPP77M8Yd+fvDgQTZs2MD48eOJj48vfd13331s2LChTvlYa0vf75o1a2jXrh3t2rUr3d+rVy8aN27MmjVrSrd17NixzNjhVq1alb6H9evXk5OTw+mnn14mx1deeeWwHA/9WiQnJxMXF0fnzp3LbCuJWxO5ubnExMSU2bZu3TratWtHSkpK6bbyX+OaiouLo0uXLqWfH/q+S8TGxgKU6T4uIiJypIkIdgIiIlJ/ERERRETU7ld6o0aNynxeMpmUtbZ0W2FhYYXnRkZGln5cUqTWdEbq7OxsAP7zn/8waNCgMvvcbneNYpS3Zs0aOnXqVKtzDn0P4H0fJe+hJMc5c+bQpk2bMsdFR0dXGqdkpu7K4tZE8+bN2bdvX42PL1HT719F+R16DsDevXsBaNGiRa3zEBERCRdqWRYRCTM9e/Zk6dKlZQqgJUuWkJCQUOUM2SWF0aGTPR062VdNde/eneXLl5fZdujnycnJtG7dmo0bN9K1a9cyr9oWvAALFixg1apVnH/++YD3/W/ZsoUtW7aUHvPTTz+xf/9+evXqVaOYvXr1Ijo6mrS0tMNyPLTF2h/69etHenp6mYK5e/fubNmypcwkZeW/xr76/gH8+OOPREZGcvTRR9fpfBERkXCglmURkTBz3XXX8eijjzJp0iQmTpzIunXruPvuu7nxxhurXIooNjaWE044gQceeIBOnTqRkZHBHXfcUevrT5o0iauvvpqBAwdy4okn8sYbb/DDDz+U6Zp8zz33cP3115OUlMTIkSPJz8/nm2++Yd++fdx4442Vxs7Pzyc9PR2Px8POnTv5+OOPmTZtGqNHj+ayyy4DYPjw4Rx77LGMHTuWRx99lKKiIq677jqGDh3KwIEDa/QeEhISuPnmm5kyZQqO4zB48GAyMzNZsmQJiYmJjBs3rtZfl5rq168fzZs3Z8mSJYwePRqA008/nS5dujBu3DgeeughDhw4UPq9KWnZLynkp06dyv3338/PP//MI488Uqcc/ve//3HyySeXdscWERE5EqllWUQkzLRp04aPPvqIZcuW0adPH6699lrGjx9fo8L3xRdfpKioiAEDBjB58uTDZtCuibFjx3Lbbbdx8803079/fzZt2sTll19eZhzuVVddxfPPP8+MGTM49thjGTp0KC+99FK1Lcsff/wxrVq1omPHjowcOZLPP/+cxx9/nPfee6+0C7cxhvfee48mTZowZMgQhg8fTufOnXnjjTdq9T7uvfde7rzzTqZNm0bPnj0ZOXIkc+bMqVPrd2243W6uuOIKZs6cWWbbu+++S3Z2NscddxxXXXVV6WzYJV/XyMhIXnvtNdauXUvv3r158MEH6/T9A3j99de5+uqr6/9mREREQpix5QcqiYiI+Njpp59OSkoKr776arBTCQnp6ekcffTRfPvtt3To0KHCY5YsWcLgwYNZv359mQm76mvu3LncdNNN/PDDD7UeBy8iIhJO9FdQRER8Kicnh2effZYRI0bgdrt57bXX+PTTT5k/f36wUwsZKSkpvPDCC6SlpZUWy7NnzyY+Pp5u3bqxfv16brjhBk466SSfFsrgna18xowZKpRFROSIp5ZlERHxqdzcXM4++2y+++478vLy6N69O3fccQfnnXdesFMLaa+88gr33XcfaWlpNG/enOHDh/PII4/QrFmzYKcmIiISllQsi4iIiIiIiJSjCb5EREREREREylGxLCIiIiIiIlKOimURERERERGRclQsi4iIiIiIiJSjYllERERERESkHBXLIiIiIiIiIuWoWBYREREREREpR8WyiIiIiIiISDkqlkVERERERETK+X8RbFnpH+EXUQAAAABJRU5ErkJggg==\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"from matplotlib import pyplot as plt\n",
"plt.figure(figsize=(12,8))\n",
"# Grafigin buyuklugune gore olceklendirme carpanini\n",
"# degistirmek gerekebilir\n",
"radii = hotpl[\"radius\"]*200\n",
"plt.scatter(x=hotpl[\"orbital_period\"],y=hotpl[\"star_metallicity\"],s=radii, \n",
" c=hotpl[\"star_teff\"], cmap=\"YlOrRd_r\")\n",
"plt.axhline(y=0.0,ls=\"--\",c=\"darkblue\")\n",
"plt.axvline(x=0.7,ls=\"--\",c=\"royalblue\")\n",
"plt.xlabel(\"Yorunge Donemi (gun)\")\n",
"plt.ylabel(\"[Fe / H] (dex)\")\n",
"plt.colorbar(label=\"T$_{eff}$\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Bu grafiğe bakarak böyle bir çıkarımda bulanmak kolay görünmemektedir. Grafiğin dayalı olduğu veri setinde tüm gezegenlerin değil; belirlenen koşulları (geçiş yapan P < 5 gün yörünge dönemli gezegenler) sağlayan yörünge dönemi, yarıçapı, barınak yıldız metalisitesi ve etkin sıcaklığı veritabanında bulunan gezegenlerin bulunduğu unutulmamalıdır. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Başa Dön](#Veri-Görselleştirmenin-Temelleri)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Zamana Bağlı Değişimlerin Görselleştirilmesi ##\n",
"\n",
"Dikine hız, ışık eğrileri ya da gözlemsel tayflar gibi gibi astronomların sıklıkla başvurduğu zamana ya da dalgaboyuna bağlı değişimleri gösteren verilerin görselleştirlmesi için de saçılma grafikleri kullaınılabliir. Ancak genellikle gözlemsel hataların da grafik üzerine aktarılmasının beklendiği bu türden veri görselleştirmelerinde `matplotlib.errorbar()` fonksiyonu gibi buna olanak sağlayan fonksiyonlar daha sık tercih edilmektedirler.\n",
"\n",
"### Örnek: Bir Geçiş Işık Eğrisi ve Modelinin Grafiği ###\n",
"\n",
"HAT-P-23b ötegezegenin [Exoplanet Transit Database](http://var2.astro.cz/ETD/) açık veritabanından alınmış 123 numaralı geçiş ışık eğrisi ve bu ışık eğrisine sistemin temel parametreleri dikkate alınarak `EXOFAST` (Eastman vd. 2013, 2017) yapılmış bir geçiş ışık eğrisi modeli `veri` klasörü altında sunulmuştur. Bu ışık eğrisi ve modeli `matplotlib.errorbar` fonksiyonu kullanılarak aşağıdaki şekilde çizdirilmiştir. Gözlemsel hatalar sadece normalize göreli akıların üzerinde olduğundan hata değerleri dizisinin `yerr` parametresinden sağlanması yeterli olacaktır."
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"mpl.style.use(\"Solarize_Light2\")\n",
"isik_egrisi = pd.read_csv(\"veri/hatp23_etd123_converted_datasubset.dat\", delimiter=\"\\t\", \n",
" index_col=\"#\", skipinitialspace=True)\n",
"model = pd.read_csv(\"veri/hatp23_etd123_converted_model.dat\", delimiter=\"\\t\",\n",
" skipinitialspace=True)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
![](\"images/matplotlib_architecture.png\",)
\n",
"![](\"')
';\n",
" fig.close_ws(fig, msg);\n",
"};\n",
"\n",
"mpl.figure.prototype.close_ws = function (fig, msg) {\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"};\n",
"\n",
"mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width / this.ratio;\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] =\n",
" 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CBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIECAAAECmYAAyagNESBAgAABAgQIECAgQPwAAQIECBAgQIAAAQKZgADJqA0RIECAAAECBAgQICBA/AABAgQIECBAgAABApmAAMmoDREgQIAAAQIECBAgIED8AAECBAgQIEC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"
],
"text/plain": [
"![](\"images/boxplot_scaled.png\",)
\n",
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\")
"
],
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