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@kummerer94
Created November 26, 2018 15:49
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Analyse der Störungen der S-Bahn München."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Helpful functions\n",
"import pandas as pd\n",
"import numpy as np\n",
"import seaborn as sns\n",
"import re\n",
"\n",
"# Plotting\n",
"%matplotlib inline\n",
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib import cm as cm"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"import re"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"sns.set()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Die letzten Wochen bzw. schon das gesamte Jahr 2018 war eine Katastrophe für die S-Bahn München (https://www.sueddeutsche.de/muenchen/oeffentlicher-nahverkehr-die-muenchner-s-bahn-ist-ein-desaster-1.3890138). Allerdings hat jeder einen subjektiven Eindruck von den Störungen und es gibt einen gewissen Bias bei der Auswahl (andere Strecke, andere Fahrgewohnheiten). Ich fahre selbst häufiger gegen späten Vormittag oder frühen Nachmittag, wohingegen andere ganz früh in die Arbeit oder sehr spät von der Arbeit heimkehren können.\n",
"\n",
"Um die Störungen systematisch anzugehen ist eine Datengrundlage nötig, die alle Störungen beinhaltet und zusätzliche infos (betroffene S-Bahnen) bereitstellt. Die Bahn veröffentlicht selbst zu jeder Störung eine kurze Nachricht, die alle diese Daten beinhaltet. Allerdings gibt es keinen Weg an die Daten der Bahn direkt zu kommen.\n",
"\n",
"Es gibt allerdings Webseiten, welche diese Störungen selbst publizieren und überwachen. Meine Daten der Störungen sind netterweise bereitgestellt von der Website Störticker (https://stoerticker.de/aktuell?evu=2)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Datensatz: Störungsmelder"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wir laden den Datensatz zu den Störungen und analysieren erst einmal die Struktur der Daten, bevor wir anfangen unsere tiefergehenden Analysen durchzuführen."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"stoerungen_raw = pd.read_excel('stoerungen.xlsx')\n",
"stoerungen_raw = stoerungen_raw.drop(['id', 'meldung'], axis=1)\n",
"\n",
"stoerungen_raw.columns = ['Text', 'Date']\n",
"stoerungen_raw.index = stoerungen_raw['Date']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Es gibt in der Datenbank ein paar Einträge, die doppelt oder dreifach in die Datenbank geschrieben wurden. Diese entfernen wir und räumen auf. Außerdem schließen wir November von der Analyse aus, weil der Monat noch nicht zu Ende ist und Mittelwerte über die Anzahl der Störungen beeinlussen würde. Das gleiche gilt für den ersten Monat, für den wir Daten haben, September 2013."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"# Error in database - take out the day\n",
"stoerungen_raw.groupby('Date').count().sort_values(by='Text', ascending=False).head(10)\n",
"\n",
"# November is manipulating our plots - do not show anything for november yet\n",
"stoerungen_raw = stoerungen_raw[stoerungen_raw.index <= '2018-10-31']\n",
"\n",
"# First month: September 2013 is also manipulating our data\n",
"stoerungen_raw = stoerungen_raw[stoerungen_raw.index >= '2014-01-01']"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"stoerungen_raw = stoerungen_raw.drop_duplicates()\n",
"stoerungen_raw.index = stoerungen_raw['Date']"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"DatetimeIndex: 10379 entries, 2014-01-01 06:19:00 to 2018-10-30 19:32:00\n",
"Data columns (total 2 columns):\n",
"Text 10379 non-null object\n",
"Date 10379 non-null datetime64[ns]\n",
"dtypes: datetime64[ns](1), object(1)\n",
"memory usage: 243.3+ KB\n"
]
}
],
"source": [
"stoerungen_raw.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wir haben Daten von Januar 2014 bis Ende Oktober 2018. Es sind insgesamt 10.379 Störungsmeldungen. Um ein Gefühl für die Daten zu bekommen schauen wir uns die Häufigkeit der verwendeten Worte an und sortieren nach Häufigkeit absteigend. Um ein Gefühl für die Art der Meldungen zu bekommen kann man auch in das Archiv sehen: https://stoerticker.de/archiv?evu=2."
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"text = stoerungen_raw['Text'].str.lower() \\\n",
" .str.strip() \\\n",
" .str.replace(':', '') \\\n",
" .str.replace('#', '') \\\n",
" .str.replace('/', ' ') \\\n",
" .str.replace('\\n', '') \\\n",
" .str.replace('.', ' ') \\\n",
" .str.replace(',', ' ') \\\n",
" .str.replace('-', '') \\\n",
" .str.replace('(', ' ').str.replace(')', '') \\\n",
" .str.cat(sep=' ')\n",
"words = np.unique(text.split(' '))\n",
"word_count = dict()\n",
"for word in words:\n",
" word_count[word] = text.count(word)\n",
"word_count = pd.Series(word_count).to_frame()\n",
"word_count.columns = ['Count']\n",
"word_count['Word'] = word_count.index"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Count</th>\n",
" <th>Word</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>störung</th>\n",
" <td>4034</td>\n",
" <td>störung</td>\n",
" </tr>\n",
" <tr>\n",
" <th>strecke</th>\n",
" <td>3602</td>\n",
" <td>strecke</td>\n",
" </tr>\n",
" <tr>\n",
" <th>aktualisierung</th>\n",
" <td>3275</td>\n",
" <td>aktualisierung</td>\n",
" </tr>\n",
" <tr>\n",
" <th>verzögerung</th>\n",
" <td>3014</td>\n",
" <td>verzögerung</td>\n",
" </tr>\n",
" <tr>\n",
" <th>verzögerungen</th>\n",
" <td>2935</td>\n",
" <td>verzögerungen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>technisch</th>\n",
" <td>2462</td>\n",
" <td>technisch</td>\n",
" </tr>\n",
" <tr>\n",
" <th>technische</th>\n",
" <td>2461</td>\n",
" <td>technische</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ausfall</th>\n",
" <td>2145</td>\n",
" <td>ausfall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bahnen</th>\n",
" <td>2064</td>\n",
" <td>bahnen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sbahnen</th>\n",
" <td>2063</td>\n",
" <td>sbahnen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>minuten</th>\n",
" <td>1927</td>\n",
" <td>minuten</td>\n",
" </tr>\n",
" <tr>\n",
" <th>stammstrecke</th>\n",
" <td>1868</td>\n",
" <td>stammstrecke</td>\n",
" </tr>\n",
" <tr>\n",
" <th>münchen</th>\n",
" <td>1860</td>\n",
" <td>münchen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>minutentakt</th>\n",
" <td>1830</td>\n",
" <td>minutentakt</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10minuten</th>\n",
" <td>1791</td>\n",
" <td>10minuten</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10minutentakt</th>\n",
" <td>1787</td>\n",
" <td>10minutentakt</td>\n",
" </tr>\n",
" <tr>\n",
" <th>beeinträchtigung</th>\n",
" <td>1749</td>\n",
" <td>beeinträchtigung</td>\n",
" </tr>\n",
" <tr>\n",
" <th>beeinträchtigungen</th>\n",
" <td>1736</td>\n",
" <td>beeinträchtigungen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10minutentakts</th>\n",
" <td>1706</td>\n",
" <td>10minutentakts</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sperrung</th>\n",
" <td>1511</td>\n",
" <td>sperrung</td>\n",
" </tr>\n",
" <tr>\n",
" <th>flughafen</th>\n",
" <td>1462</td>\n",
" <td>flughafen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>verkehr</th>\n",
" <td>1338</td>\n",
" <td>verkehr</td>\n",
" </tr>\n",
" <tr>\n",
" <th>freising</th>\n",
" <td>1022</td>\n",
" <td>freising</td>\n",
" </tr>\n",
" <tr>\n",
" <th>streckensperrung</th>\n",
" <td>1009</td>\n",
" <td>streckensperrung</td>\n",
" </tr>\n",
" <tr>\n",
" <th>signal</th>\n",
" <td>834</td>\n",
" <td>signal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dachau</th>\n",
" <td>781</td>\n",
" <td>dachau</td>\n",
" </tr>\n",
" <tr>\n",
" <th>germering</th>\n",
" <td>738</td>\n",
" <td>germering</td>\n",
" </tr>\n",
" <tr>\n",
" <th>unterpfaffenhofen</th>\n",
" <td>701</td>\n",
" <td>unterpfaffenhofen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bahnübergang</th>\n",
" <td>694</td>\n",
" <td>bahnübergang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>germeringu</th>\n",
" <td>681</td>\n",
" <td>germeringu</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Count Word\n",
"störung 4034 störung\n",
"strecke 3602 strecke\n",
"aktualisierung 3275 aktualisierung\n",
"verzögerung 3014 verzögerung\n",
"verzögerungen 2935 verzögerungen\n",
"technisch 2462 technisch\n",
"technische 2461 technische\n",
"ausfall 2145 ausfall\n",
"bahnen 2064 bahnen\n",
"sbahnen 2063 sbahnen\n",
"minuten 1927 minuten\n",
"stammstrecke 1868 stammstrecke\n",
"münchen 1860 münchen\n",
"minutentakt 1830 minutentakt\n",
"10minuten 1791 10minuten\n",
"10minutentakt 1787 10minutentakt\n",
"beeinträchtigung 1749 beeinträchtigung\n",
"beeinträchtigungen 1736 beeinträchtigungen\n",
"10minutentakts 1706 10minutentakts\n",
"sperrung 1511 sperrung\n",
"flughafen 1462 flughafen\n",
"verkehr 1338 verkehr\n",
"freising 1022 freising\n",
"streckensperrung 1009 streckensperrung\n",
"signal 834 signal\n",
"dachau 781 dachau\n",
"germering 738 germering\n",
"unterpfaffenhofen 701 unterpfaffenhofen\n",
"bahnübergang 694 bahnübergang\n",
"germeringu 681 germeringu"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"word_count[word_count['Word'].apply(lambda x: len(str(x))) > 5].sort_values(by='Count', ascending=False).head(30)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Count</th>\n",
" <th>Word</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>signal</th>\n",
" <td>834</td>\n",
" <td>signal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>signalanlagen</th>\n",
" <td>20</td>\n",
" <td>signalanlagen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>signalstörung</th>\n",
" <td>384</td>\n",
" <td>signalstörung</td>\n",
" </tr>\n",
" <tr>\n",
" <th>signalstörungen</th>\n",
" <td>3</td>\n",
" <td>signalstörungen</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Count Word\n",
"signal 834 signal\n",
"signalanlagen 20 signalanlagen\n",
"signalstörung 384 signalstörung\n",
"signalstörungen 3 signalstörungen"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"word_count[word_count['Word'].str.startswith('signal')]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wir identifizieren folgende \"hot words\", d.h. Wörter, die häufig im Zusammenhang mit Störungen stehen und nach denen wir in den Meldungen suchen."
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [],
"source": [
"hot_words = [\n",
" 'störung',\n",
" 'verzögerung',\n",
" 'verzögerungen',\n",
" 'ausfall',\n",
" 'beeinträchtigung',\n",
" 'beeinträchtigungen',\n",
" 'sperrung',\n",
" 'streckensperrung',\n",
" 'signal',\n",
" 'signalstörung',\n",
" 'bahnübergang',\n",
" 'polizeieinsatz',\n",
" 'personen im gleis',\n",
" 'stellwerk',\n",
" 'polizeiliche ermittlungen',\n",
" 'notarzteinsatz',\n",
" 'geänderte linienführung',\n",
" 'weiche',\n",
" 'weichenstörung',\n",
"]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Eine interessante erste Analyse ist die Anzahl der Störungsmeldungen pro Monat. Allerdings muss man hier bedenken, dass wir noch keine Aktualisierungen oder sonstige Meldungen, die offensichtlich keine Störungen sind, herausfiltern."
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1fc83899c18>"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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AqHKYUv7dYTWixmlGIBQFY6yYSwNAAZkgCII4THAPkyEn47AYITKGEF/8tigKyARBEMRh\ngZwhpw3IViMAIBCOFGVNyVBAJgiCIA4LEnvIqUvWAGCPB2R/iAIyQRAEQRQENRmyHJADFJAJgiAI\nojBkEnUBgCPef+wvQck6Yx9yLBbDihUrsGfPHnAch1/96lcwm8248cYbwXEcpk6dittvvx06nQ4v\nvPACVq5cCYPBgKuuugqLFi0qxmsgCIIgiIy4/QIcViMM+uFz0USGHC3WshQyBuT3338fALBy5Uqs\nXbsWDzzwABhjuOaaa3Dsscfitttuw7vvvosjjzwSTz/9NF566SXwPI9ly5bhxBNPhMk0/JUIQRAE\nUXmEeMlgo8Y5fOm3HHH7edRXWdMeU8qSdcaA/LWvfQ2nnnoqAODQoUNwuVxYvXo1jjnmGADAySef\njFWrVkGn02HevHkwmUwwmUwYN24cduzYgblz5xb0BRAEQRDF5Zm3d2Hz7l7c/9MT02ab5YTi0uVM\nnyQ6LKUTdamyzjQYDLjhhhvw9ttv4/e//z1WrVoFLm7Abbfb4fP54Pf74XQ6lfvY7Xb4/f6Mj93Q\n4Mx4DJF/6LyXBjrvpYHOe37p6A/BH4rAZDWhLk3GWU7n/VC3FI+a6xxp18UMegBAlBV//aq9rO+9\n915cd911WLp0KXieV24PBAJwuVxwOBwIBAIDbk8O0MPR3e3TuGQiVxoanHTeSwCd99JA5z3/9HpC\nAIB9B9wQhdR7reV23r/a3w8AsBi5tOvi46+n1x0qyPrTBfmMtYZXX30Vjz32GADAarWC4zjMnj0b\na9euBQB8+OGHWLBgAebOnYsNGzaA53n4fD7s3r0bra2teXoJBEEQRDkgigzegNTP6w8KJV6NevpV\ntDwBgNmoh0HPlWfJ+hvf+AZuuukmXHzxxYhGo7j55psxefJk3Hrrrbj//vsxadIknHHGGdDr9Vi+\nfDmWLVsGxhiuvfZamM2VteFPEARBpMcXikC2efaVIGhli2wKUmVPH5c4joPdYiyJU1fGgGyz2fDQ\nQw8Nuf3vf//7kNuWLl2KpUuX5mdlBEEQRNnh8Se2LEuRRWaLYgqSQdQFSPaZ7qTXWSwqQx5HEARB\nlAWeQKJM7Q9WUkCW1l2ToWQNSK1PwXAUoljciU8UkAmCIAjVyKVfoLIyZDmzd9kzZ8h2iwEMQJAv\nrjkIBWSCIAhCNZ5AZZas+/0CnLb0Ll0yjhINmKCATBAEQagmOUOuJFGX289nVFjLlMqtiwIyQRAE\noZpK3EMO8VHwQiztUIlkSpUhqzYGIQiCIAhPQAAHaWKSP1QZfcjyRYTaDJlK1gRBEETZ4wlIe7FV\ndjP8JZiIlA1unzpTEBl7fARjIEyiLoIgCKJM8fh5VDnMcNiM4CMxCJFYqZeUEXdADsjlXbKmgEwQ\nBEGoghdiCAsxVNlNJQta2eD2aStZ2+MTn4rt1kUBmSAIglCFJyjbT1ZYQFbpYy1TKpU1iboIgiAI\nVcjmGlUOM0wGKZ+rhNanhKhLbclaCo2ksiYIgiDKksSABhP0eg5A8bPIbJBFXWpcugDAaNDDZNQh\nUGTRGgVkgiAIQhVyppncz+urgF5kt5+HS6VLl4zDaiRRF0EQBFGeyLaZFbeHHBBQpXL/WKYUIxgp\nIBMEMWLp8YTQ2Rcs9TJGDErJ2mFOBOQyz5Blly61gi4Zh9WIsBBDNCYWaGVDoYBMEMSI5eGXt+DO\nJ9eUehkjBqVkbTfBaZPK1r4yd+tKKKzV7R/LlEJpTXvIBEGMWHo9YRR3ou3IxhMQYDLoYDHpYagQ\nUVdyVq8FR9ytyx+Oar5vtlBAJghiRMIYQ4iPgYFBZAw6jiv1kioeyaXLBI7jYDToYTbpy77tSc6Q\nayogQ6aSNUEQIxI+EoPIGBiTHKaI3BAZgzcQQZU9kS06LMVXImvF7dfm0iWjuHVRQCYIgsiNYNJg\ngBBfGUMQyhl/KAKRMVQl9fI6bMayF3W5k8xMtFAKFTkFZIIgRiTJQZgCcu4k9mITAdlpNUKIiuDL\neMBE9qIueQ+ZAjJBEEROhPhEkAhRyTpnknuQZRy20ng+a8Htl+Y3q3XpknEoe8jFu5ijgEwQxIgk\nmJQVhylDzplUamU5aJWzW5fHz8Op0aULoJI1QRBE3gjykaR/U0DOFbkHOTnTLHe3LsYY3H5Bs6AL\nKM0IRgrIBEGMSJJL1mEqWeeMxz90YpJTzpDL1BwkLMTAR2KodmYRkON7yKSyJgiCyJFkIVey4prI\njsQeclLJOu7WVa5Ka0VhrXH/GAD0Oh2sZj38tIdMEASRG8lBOCxQQM4Vb0ASRznjQi6g/EvW2fYg\nyxR7wAQFZIIgRiQD256oZJ0rbr8AxyBxlLPsA3K85SmLkjVQ/BGMFJAJghiRUB9yfvEEhCGlX3uZ\nB2Rl3zuLkjUgvb5IVIRQpD5rCsgEQYxIkpXVISpZ54QQiSHER4cE5HJve8pHhgwU74KDAjJBECMS\n6kPOH8rYxUF7scb45KdyzZATLl3Z7iHHldZFEgVSQCYIYkQS4qOwmQ0w6HUI0h5yTiTPQR5MsfdZ\ntZBw6TJmPDYVlCETBEHkgRAfhdVsgN1qIJV1jiguXSkCstMmBWTGym/ytNvPw2k3Qa/LLtQVewQj\nBWSCIEYkwXAUNosBNrORRF05Ivcgu1IMaEgIn8RiLystkksXr3moRDKOuFtXsQZMUEAmCGLEIYoM\nYSEGq9kAm9VAbU85klArD92LLVe3rrAQgxARs94/BihDJgiCyBm5RG0zSxkyH4lBFMuvpFopJERd\nqfaQ425dZbaPnO3YxWQS9pkk6iIIgsgK2aXLajbAFlfK0j5y9njTibrizl3lZp/p9uWmsAZI1EUQ\nBJEzcsuTLSkg08Sn7HH7eRgNOljNhiF/K1e3LvcwrVpaKHZAHnp2CYIgKhxZxGW16ME4Ke8I0z5y\n1sguXRzHDfmbYg5SbgE5DyVrq9kAjiveCEbKkAmCGHEkMmSjkiGTW1d2iIzBm8I2U0bJIsuuZJ3b\nYAkA0HEc7Jbi9VlThkwQxIhDyZDNekCvH3AboY1AKIKYyOAaLiDbyrNkLbdq5RKQAcmti5y6CIIg\nskRuc0oWdVHrU3bICuvhApuzXEvWPj4nly4Zh9WIQJGMTyggEwQx4gjG9/wkYxAqWedCOttMoPi9\numpx+wW4cnDpkrFbjYjF+9oLDQVkgiBGHAMy5HjAoJJ1dnj8w7t0AYBBr4PVrC+riU+MMbgDfMq+\naa3YLcW74KCATBDEiGNA25OZSta5oJSsU7h0yUgDJsrHqSvE5+7SJaOI1oqgtKaATBDEiCMh6jLA\nFs9waARjdiiDJdJkmw6rqawGTOQ6djGZYrp1UUAmCGLEkcoYhErW2ZHOpUvGaTMiGivOPqsaPHno\nQZYppjlI2ranSCSCm2++GQcPHoQgCLjqqqvQ0tKCK6+8EhMmTAAAfPe738WSJUvwwgsvYOXKlTAY\nDLjqqquwaNGigi+eIAgiFSE+Cr2Og9GggyWeIYfKJFhUGnK2OVzbE5AIWoFQJKWbV7Fx+3PvQZaR\n95BLHpBfe+01VFdX47e//S3cbjfOPfdcXH311bj00ktx2WWXKcd1d3fj6aefxksvvQSe57Fs2TKc\neOKJMJlyvzohCILQijwLmeO4EZshewMCzEY9zCZ9QZ/HExDgsBph0A9fUE1266qvthZ0PWrIZ8la\nudgo9R7ymWeeiZ///OcAJNWaXq/H1q1b8cEHH+Diiy/GzTffDL/fj82bN2PevHkwmUxwOp0YN24c\nduzYUfDFEwRBpEKehQxIKmCTQTeiAnIkGsOKJ9bimXd2Ffy50rl0yRTb8znTe+lWse+tlrIpWdvt\ndmkhfj9+9rOf4ZprroEgCPjOd76D2bNn47//+7/xxz/+EdOnT4fT6RxwP7/fr2oBDQ3OzAcReYfO\ne2mg814cQkIMDTVW5XzbrEZEYuKIOf+HevzwhyLo6A8V9DUJkRgC4SimjK1O+zwtjdLfOIN+wHGF\nWNuGHZ341RNrcNnZs3DuKVNSHhOKSNsTk8fXoq4qt4xdjDu9xVjhv78Zi/3t7e24+uqrsWzZMpx9\n9tnwer1wuVwAgK9//eu48847sWDBAgQCAeU+gUBgQIBOR3e3L8ulE9nS0OCk814C6LwXh2hMhBCJ\nwajXobvbh4YGJ8wGHfzByIg5/1/t7wcA9LpDBX1NPZ4QAMBm0qd/npgUAA91+pTjCvV5/2x7JxgD\nnnxtGwwAjp3ZNOSYzt4AOA6IhAV052gIw8ez8Xyd63RBPW3JuqenB5dddhmuv/56XHDBBQCAyy+/\nHJs3bwYAfPzxx5g1axbmzp2LDRs2gOd5+Hw+7N69G62trTkvnCAIQivJCmsZq9kwokrW/fE9Um9A\ngFjAVqOES1f6vdhilnV7PGEAgEHP4Yl/fo7te/uGHOPxC3DZcnfpAgCLSQ+9jit9yfrRRx+F1+vF\nI488gkceeQQAcOONN+I3v/kNjEYj6uvrceedd8LhcGD58uVYtmwZGGO49tprYTbnvplOEAShleQe\nZBmr2QAhKiIaE9OKkyoFeZJRTGTwhyJw2QojoJV7kNMprIHiBuRerxSQf3reXPzhpc14+JUtuPHi\n+Rjb6AAQd+ny82ips+fl+TiOgz3uZ11o0gbkFStWYMWKFUNuX7ly5ZDbli5diqVLl+ZvZQRBEFmQ\nKiBb4krksBCDwzoCAnI8QwYS2WAhSAyWyBCQ48/vDxberavXE0aV3YS5k+vww7Nm4rHXtuGBFz7D\nLcsXoK7KIrl0RcW89CDLOKxGpbe5kFT+J5MgCCKJUHxUnqyyBpBknzkyytYDAnKgcIFCDkKZVNb2\n+LkudIYsMoZebxh1VRYA0v7x0kVT4PYLeOD/34RAOKKcm6o8tDzJ2C0GBMPRgm4PABSQCYIYYQRT\nZcgjLSD7BmbIhUJ26XJlCG4GvQ42s6HgIxg9fgExkaE+HpAB4IxjxuLrC8biUE8Af3hpiyJEy3eG\nzCC10xWS0luqEARB5JFEQE4YZsj/Lhdrx1zpT8qQ3QUspSYcrzIHN4fNCH+BJz7JwbbOlQjIHMfh\nwtOnoN/PY/2OLnT1BwEA1c58ZsgJJzJ5v7wQUIZMEMSIQp7qZDMnfjjlbDk4AjJkSbQkwKDnACT2\neQuBJyA9j02FHaY08amwAyZ64wrruqQMGQB0HIcfnTUDrWOrExcRGZThWijWxCcKyARBjCiC8R9N\nW3KGbJICykiY+BTko4hERYxpkFTFhS1Z86iym8BxXMZjHVYjYmJhB0zILU/1gwIyABgNevyf8+dg\ndL2krq6vHnpMtiQmPhU2IFPJmiCIEYWcIVstyXvI+vjfKj8g98f3j8c1ObCvw1ewDJkxBk9AwNhG\ndSZPziQ/60INmJBbnpJL1snYLUb8ctk8fHXIq1yw5AO7MjyjsJ8fypAJghhRpGp7UlTWI2APWd4z\nrnNZ4LQVrh0nEI4iGmOqxVEOW7ysW8B95OFK1sk4bSYcMaU+r8/rKNLEJwrIBEGMKFI5dVlMI0dl\nLWfI1Q4zqhxmuAuUIXtUzEFOJmEOUrgSeo8nDIfVqLyfxcKu0vikxx3CtX/4D9Zt78zqeSggEwQx\nohjOqSv5b5WMIlpymlFlN4EXYgjn6NecCo+KOcjJFNqti8k9yMOUqwuJ2hGMn37RA09AwObdvVk9\nDwVkgiBGFEE+CpNBN8Ai06rsIY+cknWNw6yMFyzEPnLCpUudWtlhld26ChOQvcEIIlExpaCr0Ki9\n2Pg87qvd2RfM6nkoIBMEMaIIhaMDBF1AIkMuRCZZbGRTkGqnWQmWhVBay4+ptmTttCVEXYVAzf5x\noZCdyAJpjEGiMRE729wAgI6+YFbtXxSQCYIYUQT56JC+WdnLemSUrHkY9DrYLQalnFyIDDnh0lUe\nJWtFYV2CgGwy6mEy6NK+tj3tXvBx0WAgHM3qwoQCMkEQIwbGGEJ8dEjbjV6ng9moHxEl634fj2qH\n1BssZ8iFcOtyxz2y1RpsFFplLbt01ZdgDxlAxolP2/dKM6qbaqwAgI5e7WVrCsgEQYwYIlERMZGl\ndJaymPUIVXjJWhSl3mDZFlIuJ3sLsYescvSiTKEHTJSyZA1IPc7pRF2f7+0DxwGnHDkaQHb7yBSQ\nCYIYMaRQ5CfkAAAgAElEQVQaLCFjNRkqvmTtDQpgTBJ0AVBEXYXIkL0BAXaLAUaDujCh10ll9EIF\n5HQuXcXAYTUgxMcQjYlD/hYWoth9yIsJzU5MGuUCIO0ja4UCMkEQI4ZULU8yVrOh4kvWyT3IQCJD\nLoSoy+3nVWfHMg6rsXCiLm8YVrMeNkvhhjukQ+5FTjXxaVebBzGRYcb4WjTX2gBQQCYI4jBHMQWx\npArIekRjIiLRoRlOpaC0PMVL1haTAWaTPu+irkhURCAcVd3yJCNPfMr3gAnGGHo8YdS5rHl9XC2k\nE61t3ye1O82cUAOnzQib2UABmSCIw5tQOH3JGkBF7yMrLU9Jyudquynv9pm+oLaWJxmn1QQxLqzL\nJ4FwFLwQK1m5GkiMYEwVkD/f2w+DXocpo6vAcRyaam3o6g8hJmq7+KOATBDEiCGVbaaM0otcwfvI\n/f6hZh1VDjN8wYjmH/90uDUKumTkqUjp9pH5SAy3PL4GL3/4lerHVQRdJVJYA8O7dXmDAtq6/Jg6\npgomo9Re11xrQ0xkyr63WiggEwQxYkjsIeuH/M0yAty6BpesASmLZQC8gfzt3XoCA/eq1eKMu3Wl\n20f+7IsetPcGsWFnl+rH7SmxwhoYXkW+Y5/U7jRzQo1yW3NdfB9ZY+sTBWSCIEYMiQx5qPDHNgL8\nrN2+oYEyYZ+Zv7K11sESMmp6kdds6wAgBSte5fQt2RSklCVrxzAjGD/fKwfkWuW2liyFXRSQCYIY\nMaTNkEfCHrKfh9UsCblkCqG09vq1uXTJZHLr8gUFbN0jCaAYgLZuv6rHlU1BSpohD1Oy3r6vDzaz\nAeObEnOjs1VaU0AmCGLEEApLGVfqticpiIUruGQtu3Qlo/hZ51FpLWekNZpL1nE/62Ey5E92dCEm\nMoxrdAAA9nf61K2nHErWSoaceG3d7hC63WFMH18DnY5Tbm+ssYKDdnMQCsgEQYwY0rc9GQYcU2lE\norGUrUiFMAfpdofAAWio1hYA5ZL1cI5Wa7Z1ggNwwamTAWgLyCaDTgn4pSBV9r89vn88Y3zNgGNN\nRj1qXRa0U0AmCOJwJaRGZV2hJWtZ+Zws6AKAKnv+M+QudwjVTjOMhqGl/3Q40mTI3e4QvjzowfTx\nNZg+vgYGvQ77OtWVrHu9YdRVWcBxXOaDC0QqUZc8bjFZ0CXTXGeDxy9o0ixQQCYIYsQgZ7/yfnEy\nSh9yhZasB7t0ySiirjztIUeiIvq9PBqrtZtwpNtDXvN5JwDguJlNMOh1GNNgx8Fuf0orymRCfBSB\ncLSk5WoAMOh1sJj0yghGkTFs39ePGqdZ2TNOJpt9ZArIBEGMGKRJT/oB+3kyVnNlj2BM1fIESEFQ\nr+PyprLu8YTAADTUaA/IdosRHAB/cODFAWMMa7Z1wKDXYf60RgDA+GYnojGGQz2BtI/Zq3hYl86l\nS8ZhNSoXGwe6/PAFI5gxviZl5i4HZC37yBSQCYIYMQTDQ0cvysi3V6rKOpVLFwDoOA4uuylvGXJX\nv6RoziZD1uk42FP4We/v9KO9N4gjptQp+/vj4qrk/RnK1j3yHGSXNoFZIUie+LQ9Rf9xMpQhEwRx\nWJNqFrKMXMauVJW1O4VLl0yV3QS3X8iLh3SXOx6Qs8iQgYFZpMyaz6Xe4+NmNiu3jWtSp7QurwzZ\nACEiIhKNKf3HM8bXpjyWAjJBEIctImMICdGUgi4g4dRVqSrr4UrWgBSQozExL+X47niG3JBFhgxI\nATkQikIUpYsDUWRY+3knbGYD5k6uU44b0+AAxwH7VAbkUu8hA4nWJ49fwK42N1rqbCnfDwCocZlh\nMug0uXVRQCYIYkTACzEwlroHGZBKuxaTvmK9rPt9PDik9peuimfN7jyUrfORIYuMIRgv7e7c3w+3\nX8CC6Q0DZiubjXq01Nmxv8sPMU1mnyhZl09A3vxVL/hIDDOHyY4B6fPWWGNDR38w7esbcJ+8rJIg\nCKLEpGt5krGaDZW7h+zn4bSbYNAP/dmuVuwzcw/I3e4Q7BaDMt1IK3Ivsje+lo8VdXXzkGPHNznA\nCzElK09FrycEg55T1OSlxBE/J59sl3y4h9s/lmmus0GIiMr+fyYoIBOECtp7A/jb/+5EJFqZ+4+H\nA0F++NGLMlazoSLbnhhj6PcPdemSSdhn5qa0FhlDtzucdbkaSLh1eQMCItEYNuzsQo3TjNZx1UOO\nlYVd6crWvZ4wal0W6ErYgywjZ8i72tzgOGBaiteUjNZ9ZArIRMWwYWc3Pt7aUZLn/nDTIXyw8SB2\n7neX5PmJzATDw7t0yVhNeoT4aF7ET8UkxMcgRMRhpy/lq2Tt9vGIxsSsy9XAwAx505e9CPExHDez\nKWVAzRSQ+UgM3mCkpEMlknHEx0syABNbXLBlqCJoHTIx/CeXIMqIYDiCx/+5DbEYw9wpdVmX07JF\n/qEbzqOXKD0hFRmyxWxATGSIxkTNLlSlJJ2gC0iYg3hzLFl35SjoAhJlXW9ASJiBzBpargaSldap\nW5/6ymj/GMCA353BdpmpaKrVNoaRMmSiIli1pQNCRERMZPjsi56iP79cCvQF82dPSOQXNQE54Wdd\nWWXrfn/6+cRyydqdozmIIujKJSDHM+RDPX5s3t2D0Q12jI0PkxiM3WJEfZUF+zt9KasW5TAHORlH\nkpd28rjF4VBK1v0UkIkRgsgY3tt4EPq4+9KGnd1FX0O/nCGnGbxOlBZVoi6TPPGpsoRdsiho2AxZ\n9rPOsWTdnaPCGgCcVuni4J11+xGNMRw3synt8eObnPAFIynL7Yke5PIKyEaDDlNGuzIeb7MY4LKb\nKEMmRg6f7+1DZ18Qx85swuh6O7bu6Sv6gAC5ZJhrSZAoHGpFXcnHVgpuf2qXLhmjQQe7xZCzyjov\nJet4hix7bx+bISDLZet9HUP3kXvLrGTttJmg13GYNq5a9ZZHc60NvZ6wKkEoBWSi7Hlvw0EAwGlH\njcH8aQ2IxkRs3t1btOcP8VHwgvRloj3k8iWosu0JqMQMeXiXLpkqhzlnlXWXOwSDXofqYTJxNSSX\ndVvHVGV02EpYaA4NyD1l5NIFSBnv9d+dh0sXz1B9n+ZaGxiAzjStXTIUkImypscTwqbdPZjQ7MSk\nUS7FmL6YZevkrMMXogy5XJHbmawZVNYAEBIqaw9ZyZDTBMoquwmBcBSRaPrpSeno7g+hoTq3FiOb\nxQD57sOJuZIZ3zy80rrXE4aO41DtLH0Pskzr2Ophtw5SoWXIBAVkoqz5YOMhMCZlxwAwpsGOxmor\nNu/uhRApzo9qclM/Zcjli+wMlS5DtsgDJiosQ+7389DruAHZ52CUMYxZCrv8oQiCfDQnQRcgOVTZ\nLUYY9BwWTG/MeHy1wwyX3ZRSad3jCaHGaYZeV7mhSksvcuW+SmLEE4nG8OGmQ7BbDDhmhvTF5jgO\n86c1gI/EsG1PX1HWkaxcpYBcvigZsnn4vT1bhQZkt59HtcOcNnOtzlHYJQu6shm7OJjzTp6EH507\nJ+0FRDLjmhzo9YYHDKWIREV4/ELZCLqypblOfesTBWSibPlkRxf8oQgWHjEKJmPiR1YuW68vUtla\n3r8DpB/yTAPVidIQ4qPQcRzMxuEDsjxgopJK1iJj8PiFjGXbqhztM3MZuziYU+eNxpITJqo+fnyK\nfeQ+XxgM5dPylC31VRbodRxlyERl896nB8EBWDRv9IDbJ7Y4UesyY9OXPUUJjnIJsKFa+mGgLLk8\nCfJRWM36lMPiZaymysuQfcEIYiJLK+gCcrfP7Ir3yjbW2LK6fy6kmo1cbi1P2WLQ61BfbaWATFQu\ne9q9+OqQF3Mn1w1pweA4Dke1NiDIR7EjPiS8kMj9kWMapPaMSjMH6XKH8I//7BnxPtzpZiHLVKLK\nWulBzhSQc7TPzHXKUy6MTzEbWRm7WCYtT7nQUmtDIBzN+NtBAZkoS9779AAA4LT5Y1L+fUERy9bu\n+Ni7RECurAz5f9ftxz/+swfvf3qw1EspKEE+mtbHGkgE5EoqWferUFgDSRlyliXr7v4QOK40GWl9\ntRVWs36A0rrcXLpyQa2wiwIyUXb4QxGs296FxhorZk1MbU83ZXQVXDYjNn7RrQxCLxTugACnzaiY\nMlRahiwbLry5bn9OLTHlTEwUwQuxtAprALDIbU+VlCH71WXIygjGbEvW7hBqnZaU4x0LjY7jMLbR\niY7eoNLzL5uCVHrJGlAv7Ep75iORCK6//nosW7YMF1xwAd59913s27cP3/3ud7Fs2TLcfvvtEEXp\nC/7CCy/gvPPOw9KlS/H+++/n6WUQhyMfbT6ESFTEonmjh1WV6nRS2doXjGBXW2EnMMkKV6dNDsiV\nkyHHRBFtXdK+nNsv4ONtpZmWVWgSCuvMAZlDhQVkX3qXLhmr2QCjQZdVhixEYnD7hZKUq2XGNTnA\nALR1S5/XHk8YHIDaEVCyboqf15wy5Ndeew3V1dV49tln8cQTT+DOO+/E3XffjWuuuQbPPvssGGN4\n99130d3djaeffhorV67Ek08+ifvvvx+CUFlZBFEeiCLD+58ehMmgw0lzW9Ieq5iE7Cpc2Vp26ap2\nmuGUx8pVUIZ8qCeISFTEnEl1MOg5vLFmX8ErCqVAzWAJQNIfWCpsJrIaUxBAem1VdlNWAVlpecqD\nwjpbBiutez1hVDvNJcnY801znR1AjgH5zDPPxM9//nMA0oBsvV6Pbdu24ZhjjgEAnHzyyVi9ejU2\nb96MefPmwWQywel0Yty4cdixY0c+XgdxmLHlq170eMI4dmZTxhGL08ZVw24x4NNd3RALNN9W/nGr\nspsqMkOWy9VHTqnDiXNa0NUfwvqdXSVeVf5RM1hCxmrWV1aG7M9smylT5TDBGxA0fx9KKeiSkQPy\nvg4fYqKIfh8/IgRdAOCyGWE1GzIG5LSfXrtdiup+vx8/+9nPcM011+Dee+9V2grsdjt8Ph/8fj+c\nTueA+/n9qedbDqahwZn5ICLvlOt5/8+rWwEA55/eqmqNx81pwbuftKE/FMX08ZnHoWmlwyNlJ6Oa\nnJgwVpp/KsTErM9fsc97l2cPAODIGc1YON+EjzYdwv9+0oYlCyenbQ+qNOT3qa7WlvIcJ9/mtJnQ\n6wmX7XdgML5QBFazHuPGZJ6/21hrx+6DXlhsZkV1rYbg59JF2pRxtXk9L1oeq6bWDqNBh0N9QeiM\nRoiMYVSjo2Lep0yMbXLgq4OetMdkvJxsb2/H1VdfjWXLluHss8/Gb3/7W+VvgUAALpcLDocDgUBg\nwO3JATod3d1D/UuJwtLQ4CzL897VH8SnO7okwZZZr2qNs8bX4N1P2vDumn2os6lzBdLC3gNSW5VJ\nxyEc5MFxQI87lNX5K8V537G3T7IyNHAwMBFHz2jC2s878d7avZg7ub6oaykk7Z1eAACLikPO8eDz\nbtTrEAxH0dXlrYiLkh53CFV2s6rPjsUoFT137+sbdgZxKvbEP+dmXf5+k7P5vI+ut2Nfuxfbd0vb\nUE6LoSx/q7KhzmnBrlh6vUvaknVPTw8uu+wyXH/99bjgggsAADNnzsTatWsBAB9++CEWLFiAuXPn\nYsOGDeB5Hj6fD7t370Zra2ueXgZxuPDvzw6BATjtqNEZj5WZNaEGZpMe63d2pRxwnitKudBugo7j\n4LQaK6ZkLYoM+7t8GFVvV5zOlhw3HgDwz4/3lXJpeUeZ9JSh7QmQ3LpExiBEyl9xHo2J8AUjGQVd\nMtVZmoOUQ8kakAZNRGNMmeY2UkrWANBcm/ncpv30Pvroo/B6vXjkkUfwyCOPAABuueUW/PrXv8b9\n99+PSZMm4YwzzoBer8fy5cuxbNkyMMZw7bXXwmzOfnwXcXgiqyuPmKI+czMa9Dhich3Wbe/C/k6/\nMjkmXwwW1DhtJmXOa7nT3huAEBExvjmRKY1tdOCIyXXYtLsXu9rcaB1bXcIV5g81oxdlFD9rIQqz\nSd1M21KhVtAlI5eptQq7uvtDcFiNGUVxhUZ27Nr4hZQhj4SWJxlZ2JWOtGd/xYoVWLFixZDb//73\nvw+5benSpVi6dKmG5RHEQPzBCIwGndIrqpYF0xqxbnsXNuzqLlxAdsgB2YiDPQFEY2LZqz9lk4UJ\nza4Bt3/z+AnYtLsX//x4L34x9sgSrCzBoZ4A/ufjffj2yRNzmnmrVmUNAJYk+0w1QqlSIldoMvUg\ny8jmIG4NGbIoMvR4wnn/7mTDuLhjV7d75JiCyMjmIOko718U4rDCF4zAaTNq3tebM6kOJoMOGwqg\nHvb4BXAAXHZpf9oRV1onT6UpV/bGFdaDf2injKnCtLHV2PpVn6LCLgUHuv2499lP8fG2Dnyw8VBO\njxXSULKWp0FVQutTogdZXUCuziJD7vOGERNZXoZK5MqYBgeSv/4joQdZpknFdgAFZKJs8IUE1ePa\nkjGb9Jg9qQ7tvUEc6glkvoMG3H4eTrtJmccq9yJXwj7yvg4fOA4pxT3fPF7aS/6fNaXZS97f6cP/\nfXYjfMEI9DoOm3b35PR4WjJka1LJutyRbTNrVJasXcoesvqA3FUGPcgyZqMeLfHSrstmTDu5q9Iw\nGfWoc6V/HykgE2UBH4lBiIhKr69W5rc2AADWbe/M57Lg9gsDBDUuW2XYZ4qMYX+nH6Pq7Cl/1GZN\nrMX4Jic27OhSNYUmn+zr8OG3z21EIBTBDxZPx+yJtTjYHUBPPDBkQzCsISCbKmfAxOAtk0y47EZw\n0CbqKhdBl4w8aGIklatlMpWtKSAfZvT7eLTnOYvMB/54xunMsnXpiCn1MBl1eG3VXjz++ufoi/vg\n5kKIj4KPxAb8GFZKhtzZFwQfiSkimcFwHIdvHj8eDMAbRcyS97R78dvnNiIYjuLSJTNw8hGjMDcu\n4tsUV9ZmQ8IYJHNGJQftYCUEZJW2mTJ6nQ5OjW5d3f3lkyEDCWFXXQ6agnKluTa9sIsC8mFEnzeM\nX/1lHW54+KOCtAjlgi8k/YBkU7IGpL3D/+/CIzGu0YGPt3Xg5j+twSsffoVwDmXJRHaS+DGUM/hy\nt8+U94YnpBHqHNXagOZaGz7e2pGXC5hM7D7kwe9WfoaQEMUPz5qpWKMeMbkOAHIqWwf5GAx6HYwG\nNQFZOiZcCXvI8dKzFpOPKrsJbg0Budwy5EmjJBGiGhFUpTG6kQJyxVEIr+FIVMQfX9kKbzCCfh+P\nrv7sy4PpiInZ9XYmMuTsStYAMHVMNW77wdG4bMkMWC0GvL56L256bA0+2nQoq3OayrLQaa2MDHk4\nQVcyOh2HxceNQ0xkeHPd/oKu58sDHty38jPwQgw/Onsmjp/drPyt1mXB2EYHduzrz/oCKshHVWXH\nAGCppD1kHw+H1QijQf1PdZXDBF6IqT6X3f0hmIw6RaFdaqaOqcbPL5iLM48ZW+ql5J0TZjWn/TsF\n5DJjf6cPV/z2A2z5KvvyXSqeeXsX9rR7FdHHnnZvXh9ffsxs1+7LsWQto9NxOGluC+6+4jh868QJ\nCPFR/OVfO/Bff/kEn+/t0/RY8j5cVYqStb8CMmQOiTaS4Th+VjNqXWZ8uOlQwfydd7W5cd8Ln0GI\niLjynFk4bubQH6UjptQhGmPYvrc/q+cI8VHVPbRKH3IllKz9vGpBl4yWuciMMXS5Q2iotpaVa9kR\nU+phy+BlX4mYMojUKCCXGV8e9EBkDF8dyl/A/PdnB/HhpkMY1+jAFWfPBAB8VYCAvHVPHxgD9mSx\ndlkk5cyyZD0Yi8mAcxdOwt1XHo8TZzfjQLcfv1v5Gf792UHVj5HIkIeWrMs5QxaZ5NDVXGdTem6H\nw6DX4eS5oyBExJyVzqnwBgQ88MImRKMirjp3Fo6e3pjyuCMmy/vI2a0hxEdVtTwByTORy7tkHeKj\nCAsxzb3SSuuTCqW1LxRBWIiVRcsTQQG57Oj1SHt5/jz94O8+5MEzb++C3WLA1efNwZTRVdDpuIJk\nyPLcXU8W2aMvlHvJOhU1TjMuP2smblk+HwCw6Uv12XsqhavDKqlYy1ll3d0fQoiPKdNzMjF/mqRQ\n37Az/2Ms93f6wEdiOPPYccq4zFRMbHHBaTNi0+5ezZOKIlERkaioOkOWj8tFX1AMUmkY1KAlQy43\nQdfhDgXkMqM3Lq6RRU654AkIeOSVrYiJDFeeMwsN1VaYjHpMaHZhf6cf0Vh+vXwPxAOyN4t5rPkq\nWQ/H5NFVcFiNmvqUUwVknY6D3WqEt4wzZDX7x8mMqrejqdaGLV/1go/kN2vsiV9gjspgG6jTcZg7\nqQ4ev6DMw1WLlh7k5ONKrbL+z+Z2PPzyFmUW8WAUly6tJev451WNW1e5CboOdygglxlyhpxrSTQa\nE/Hoq1vR7+Nx3smTMHtinfK3qeOqEYmKONidv/YnPhJDZ7/Uz5pdQI6XrPOcISczqs6Gbk8Ikai6\noOMe5NIl47QZyzpDTlhmqgvIHMdhwbQGCBERW/OsXZADspqeUtnDXEsVA9A2CxkATAYddBxXcpX1\nR5sP4dNd3bj9z+uwakv7kM4HrS5dMlUazEHkDJlK1uUBBeQyQ8mQcwzIL36wGzvb3DiqtUGZ8CPT\nOk6aq7qnI39l64PdAci/J1kF5FAEHKfO+jBbRtXbwRjQ0adOYT7YpUvGaTMhEI5mrSgvNHLL09hG\n9d7EhSpb93ikc61mSMCsibWSa9eX2vaRgxozZI7jYDXrS66y7vfxMBv14Djgyf/Zjkde3TrAklXr\nYAkZucTtCajPkBsoQy4LKCCXEdGYqFzV5lKyXrOtA2990oaWOhsu/+aMIerJqfEJP9mIr4bjQHxS\nE4Csyrn+YAQOqxG6Aio9ZUs+NWVrxhg8g1y6ZBSldaj89iAZY9jX4UNTjVXTxc34JifqqyzYtLsH\nkWj+LjR6PWHodZyqLM9qNqB1bDX2dvg0DUfQMukp+blKqbIWGUO/j8foBjt+dekxaB1ThQ07u3Hr\nk2uxdY9UIVBsMzVnyOpFXV3uEHQcN6LGHFYyFJDLiD5vGHLRyh+MZGXe0dblx1P/2gGLSY+fnjcn\nZdYwrskJk1GHPe35GyzQ1ikFZLtF+qFTWxaW8QWFgparASlDBqSxhJkIC7EhLl0y5Wyf2e0JI8hH\nNU/u4TgOR7U2IMTHsH2ftvawdPR4wqhzWaDTqbvQksvWWzS4doVk20wNFyAWk6GkKmtfMIKYyFDj\nNKO+2opfLjsK558yCf5gBPc/vwnPvr1LKSdrFXWZTXpYTHrVoq5al7nsJ5cdLtC7UEbI+8cAEBNZ\nVlfwb67dByEq4rIlM5SMcDB6vQ7jm5w42OMHL+TnR6mtSxpkIM/X9QbUZ8kxUUQgHM3apUstLXWS\n84+aDDmdwrWc7TP3aRR0JbMgroJen6eytRCJwRMQNHkSJ1y7NATkrDJkPcJ8VLOiO1/0+6TvuizY\n0uk4fPP4CVhxyQK01NnwzoYD2LS7FzqOgzMLw44quymjnzUvSO8PCbrKBwrIZURPfP9YH88mfFmM\n+OvzSl/Cea31aY+b2OICYwkBUC4wxtDWHUBTjU1pn9BiLRmIl34LpbCWqXGaYTHp0d6beZhCKpcu\nGWcZZ8iKZabKlqdkJo12ocphwmdf9ORlf1zWQ2gZMt9Ua0NTrQ3b9vSpLp1r3UOWj2VA3i5ItdIf\n/57WOgeem/HNTtz2g6Nx+lFjpL+7zFlt41Q5zPEsfPhzKKu7SdBVPlBALiPkDHlMfFxeNhmYNyiN\nMBwsRBrMxBbJLzYf/ci93jBCfBRjGx2KE5gWYVcxFNaAVJZtqbOjoy+YMeCkm7JT3hmy9H6OyyJD\n1sXL1v5QBDv3u3Nei/x51hKQASlL5iMx7GxT59qVXYYs9yKXJiD3+YYfq2g26nHxN1px0/eOwlXn\nzs7q8asdJjCkr1SRoKv8oIBcRsgZxcT4j2k2GZg3IChBMR0TR+UvIMuGIGMbHUqw0haQpR+NQpes\nAan1KSayjF7ebsU2M0XJWvGzLq8MmTGGfZ1+NFRbYM/SdnBBa/7U1lpanpLR2v6UVYYcd+sqVS9y\nf5qALDN1TLVy4awVZS5yGqV1F7U8lR0UkMsIOaOQx49pdeuKxqS9WJeK0m9DlQUOqzGvAXlMo0Pp\ngdRSsk64dBUhICvCrvRla4+qknV5Zci93jD8oYhqh65UtI6rhsNqxKe7unPeX+1RMmRtP/hTx1TB\natZj05c9qoSN2Yi6lAy5ZAFZOje1Glua1FKtmIMM/z2US9bk0lU+UEAuI3q9YVTZTcpVs9Y9ZDlA\nqMmQOY7DhBYnut3hnDM92aFrXFLJWss8Vr9Ssi58QFbb+pS2ZG0vzz3kXARdMnqdDvOm1sMTELD7\noCen9WjpQU7GoNdh9sQ69HjCOKRivz+btqdST3ySM2StPcZqqVKxddRFAbnsoICcgs++6MGT//N5\nUY0fRMbQ5+VRV2XJWjSkdS92krKPnJuwq63LD7vFgBqnWWkJyqZkXeg9ZAAYVS8prTO1Prl9fEqX\nLgBwWKUf83Kzz0w4dGVX5pSRPadzLVtr6UEezBFTJLX1ZhUmIQnrTHXjF4FEybpUrU99Ph4uu6lg\n7UbyVsvGXd3oGcaas7s/BJfNqKnUTxQWCsgp+OCzg1i1pQP7O/2ZD84THr+AmMhQ57JkLRqSg6Ca\nDBkAJsQD8t4cyta8EENXfwhjGhzgOC6rcq4SkIuwh1xfZYVBr8OhnvSZlzu+F59KHKfX6WC3GMou\nQ9bqYT0cMyfUwGrWY8PO7qx64WV6PGFJJayyBzmZOZPqwAGqXLuCfBRmoz6jkDEZax5GMPb7eDz1\nr+0Z24sGw+KmIFo9qrUwrtGJKocJm3b34oZHP8bvX9yMbXv6lPczJoro9YZJ0FVmUEBOQV9cXCXv\njRYDWdBVF9/bBTDARk8N8r6tmj1kIKG0zmUU44FuPxgkQRcAGA062MwGbRlyqDgqa0Dq92yutaG9\nLzDsHiljDG4/nzazc9pMZbWHLDt01bksOYvjDHodjphSj15vWAnyWpF7kLXuH8s4bSZMHl2FLw56\nMrzDkiYAACAASURBVH4PpFnI6rNjID97yP/4zx58uKkd67Z3abpfIBxFJCoWbP8YkC7K/++Pj8fl\n35yBCS1OfPZlD+57/jPc8vhavLO+DQe7A4iJDI3VtoKtgdAOBeQUyMFR69SZnJ5TVqS6LLCY9DDo\ndZozMLnFQW2GXGU3oc5lxt52b9aZUFt3QmEt47KbNO0hF1NlDUhlayEiKhdegwnxMQgRMaXCWsZp\nMyIQikAUS2MsMZh+Hw9fMJJzdiwzvzW3snXyBWa2HDGlDowh48CLEB/TPMw+V5W1Nyhg9dYOABh2\nWtNwyJ+7QmbIAGA06HHinBbc+v2jseKSBThhdjN6PCE8+84XuOOp9QBoylO5QQF5EMFwVNlX2l+K\nDNlliZd+jdpL1kqGrD7TnNjigjcYUZ5fK0rLU9PAgBwIpTclSMYXjMBi0sNoKM7HcZQi7EpdtpZb\nRdJlyC6b1OfpD5dHlpwPQVcysyfVwmTUYcPOrqwu1rLtQU7miMnx9qc0rl2MsewyZEtufcgffHpQ\nGV/a49H23VHT8pRvJo1y4YdnzcTvrj4R558yCdVO6TdiYkt+Pi9EfqCAPIjkrKmty180a73eQT2b\nTqtRs8pa6x4ykChb781S2NXW5QfHDZx367LHg5XKCwp/SCiKwlomk6d1Yuxd+gwZKJ/WJ60jFzNh\nNuoxd1IdOvtDOKhhhrRMTx4C8ugGO+pcZmzZ3TvsxZ0QERETmWZhktWU/R5yJBrDe58egM1sgNmk\n15whywF5sEtXMXDZTPjm8RNw74+Px91XHIc5k+oy34koGhSQB9GTFJB5Iab5y5YtyRkyIP3g80JM\n05CGbDNkILt9ZMYYDnT50Vxrg8mYyFDkPWw1ZWvGGHzBSFH2j2UyeVqns82UccjitSxGTRYCRdCV\nQw/yYHJRW2fbg5wMx3GYO6UeQT6KDzYeSnlMNi1PQFLbUxYBec22TniDEZwybxSaqq3o9oQ0VRHS\nuXQVC71Oh6Za25BJcERpoYA8CDlDHhcvwbYVSWnd6wnDajYoI/OyUSt7AwLMRj3MJvXlu/HNTnDI\nbhRjjyeMsBAbsH8MJDJ0NeYgIT6GmMiKorCWaaq1Qcdxw5qDuFWUrJUMOQu/8WzgIzGlRJqKfR0+\nqe0si0EEwzF3ch0Meg4bdmoTLQHZ9yAP5pvHjYfTZsTKd7/AlweG9kVnY5spHR9ve9JYsmaM4a1P\n2qDXcTj9qDFoqLZCiIiaWuCUwRKu0gVkojyhBrRByKXjI6fUY3+nH/u7fFgwvbGgz8kYQ483jIak\nbMKRVBKtVTmrVMo0NYpbzAa01Nuxt9MHUWSaWlSSLTOT0eJnLSusHUUsWRv0OjTWWNHeGwBjbEiW\n4PbFM2SnmpJ14TPkHncIK55Yi2iMoa7KjMYaGxprrGiqtqKxxgabxQBPQMCRU9IPFNGK1WzArAm1\n2LS7F519QTTVqlfk5tKDnEyty4IfnzMbv1u5EX98dQtu/8HRAx4zG9tMQPoM6HWcZpX1tr19ONgT\nwHEzm1DrsqC+WvpudrtDihlHJpQ95BzPDTHyoAx5EHLpeN5UydO3GL3IQT4KXogNyCYUv+SQuh98\nxhi8AUH1j0IyE1uc4IWYqjnByQwXkKsUc5DMWYO/iKYgybTU2RAIR1NeNMiiLnnQeypcGisYT/7z\nc/zqiTVZrBRYt6MLQlREY40VfETEtj19eP/Tg1j53pf4/Uubcc8znwLI3/5xMvOVkYzasuQeb/Y9\nyIOZMb4G3zl1Cjx+AY+8unVApUDJkDXYZgJSOdxqNmhWWb/1SRsA4OtHjwWQcLnSsrXV7+PhsBoH\nbPMQBEAZ8hD6vDx0HIexjQ5UO0xF6UVObnmS0VqyDvJRqfSbRWCb2OLCqi0d2NPuw+gGR+Y7xDmg\nBOSBgcCpoWSdcOkqXoYMSMKujV/04FBvEFWDMhW3jwfHpXbpktHiphYTRazb0YVIVMSBE8ZjjIZz\nDAAbdnZBx3G4efl8OKxGhPgout0hdPWH0OUOoas/CH8oiuNmN2t6XDUcObUeeh2HT3d145vHT1B1\nn0g0Bo9fwIzxNXlbxxnHjMXeDi/Wbe/C8+9+iYu/0Qog2aVL+0+Z1azXpLI+2O3H1q/60Do2MfRB\na0BmcUe+Jmo3IlJAAXkQvd4wapzSlf24Jic27+6FNyhoEkppfs54QK6tSgQGrSrebBTWMsmjGE+a\n26L6fm1dfjisxiFqZE0l63hAK1YPssyoJE/rwYHD7Zfe73TOT8pUKxXvT1d/SJntu257l6aA3OsJ\nY0+7DzMn1CjnyGo2YFyTUxlCUkgcViMmjnLhq4NeCJGYqqyuNz7rN5ce5MFwHIdLF8/AwZ4A3v30\nACa0OHHinBYEwzkEZJNB8XNWw9vrpez4jHh2DCQCco9bXetTiI+Bj8RKKugiyhcqWScRjYlw+3jl\nh0QuxRY6S+7xDs2QE25d6krWiYCsPbCNbXTAoOc0Ka1DfBRd7hDGNNiH7MFWafCz9odKU7IervWJ\nMQZ3IL1LF5D0/qjIkJM/P59s79SkyP10l6RwlkvHpWBCkxMiY4oJTCbyJegajNmkx0/PmwOr2YC/\n/e9O7OvwZS3qAiSldViIqTJ38QYErN7aicYaqzIeEoj7BkB9hpwQdBW/5YkofyggJ+H28WAA6uLq\nRzkDKbTSenAPMqC9ZC1natlk8ga9DmMbnTjQ5VfdZiX3pg4uVwPSD6fZqFeZIZemZN1cm7r1SXbp\nSteDDEjnzGY2qHp/5IBcV2VBZ39I0wXehp1d4AAcNTW/gi0tyGYj+1XaaOajB3k4mmpsuOLsmYhE\nRTz88hYlEGaTIctBXE3Z+v2NkhHI1xeMHbAvbjToUO00o9ujNiCXvuWJKF8oICchC7pkVfO4eIa8\nv6uwFpry89YP2EMuXskakIRdMZGpdicbTtAl47QZVe4hx32si1yyNpv0qHNZhrQ+yWMXB+8rp0Jy\nU1OfIV/49WkAoNr72OPn8cUBD6aMqVK1nkIhB2S1vta9eehBTscRU+pxzkkT0esN44PPpP7k7DJk\nqfwezjCCUTYCsVsMOGnO0C2dhmor+r28si2Rjj7FFIQCMjEUCshJDPbfbaixwmzUF7xk3esJw6DX\nKWIoALBbjOA4dSVRICkgZ1n61erYlSkgV9ml4QuZnM58JSpZA1LZ2hMQEEiyv/T4M7t0yTjtJvhD\n0Yyvsa3Lj2qHCactGAuzSY91KsvWn37RA4bSlqsBSZFuMugUe85MFDJDljn7xAk4YnLCZSrbPWQg\ns5/1x9s64QtGcPKRo1L2+DdUW8CAYb3Rk6EMmUgHBeQkFDFKPFOV1dbtPUFNjlla6fOGUecyQ5e0\nF6vTcbBb1NtnKplmlhnypFFxxy6VBiFtXT7oOE6ZLzwYl92EmMgU0c1w+IIRGPQcLBrMTPKF7NjV\nnuRprbh0qfjBdFqNEFn61+gPRdDv4zGm0QGzUY95U+rR41E3RUk25Jjf2pDx2EKi1+kwttGBgz0B\nVVlgjyeUlx7kdOg4Dj86eyYaa6RxmtmIAhMTn4b/bjPG8HaSEUgqZP8ANfvIyh4yBWQiBRSQk0jV\nfjS2yQGRsaz8fNUgRGLwBiMpFalaBkzINpXZ9CEDknuV1azH3o7MAVlkDAe6A2ips8FoSB1I5dJ5\nJvtMX1CA02YqiYWfLOw6lCTskkvW1Wl6kGWcKsRrgysJR8dNZj7JULb2hyLYsc+NiS3OvKqVs2V8\ns7SlcUCFsCuXOchasFmMuGX5fNyyfL4mdzoZq+LWNfwFlWwEcvSMxmENerS0PpWDbSZRvlBATqJP\n2UNOfFmUfeQCCbsGe1gn47SZVI/48wUj0HGcZoMEGR3HYUKzC+29wYxZbY87BD6FZWYyLpVez75Q\npOgtTzLJrU8yiQxZRclahVvXgUEBefakOljNenyyI33Z+rMveiAyVvJytYzskZ2pbC33IBdq/3gw\nTpsp6wlXFhUDJt5aJ7U6fSOp1WkwiYCsrmRtMxuU5yaIZCggJ9HrDcNuGfhlKbTSOm1AthpVj/jz\nBgQ47cYBZW+tTGiRxTvps2Q56xuTLiCrMAeJRGPghVjRFdYyLfFye7KwS8mQVYm6Mivh2waZpxgN\nOsyb2oBeL592e6BcytUyctDbl2FGeCF6kAuFLc2ACVFk+Ofqvdi6pw/TxlZjQrNr2MdpkO0zVSit\n+708eVgTw0IBOQ5jDL3e8JAfktH1dnBc4ZTWqVqeZLQorfNhXjIpySAkHZkEXYC6krWvRLaZMnaL\nEVV204BeZLc/7tKlYk0uFQMm2rr8MOh1aK5NZIzHzJCy3uHU1iE+im17+zCmwa7JP7qQjKq3w6DX\nZdz7LlQPciGQVdahQXvI3e4Q7nn2U7z84Veodphw0elT0z6Oy26CyaDLWLIOC1EE+SiVq4lhoYAc\nJxCOQoiIQzJVk1GPljp7wWYjp8uQ5RF/mZTWQiSGsBDLedKPrLRON38WUBmQZScrFQG5VCVrQBJ2\n9XjC4OO9qB6/AJfdpGr/M5N9ZkwUcbAngNH19gGuXzMn1MJuMWD9zq6Un6lNu3sQjZVPuRqQe9Xt\nONjtTzt1qhgK63wxeCYyYwyrtrTj9j+vw5cHPFgwrQF3XH5sxpI4x3Gor7ZmLFn3U8sTkQEKyHEU\n+8oUgXFcowNhIYaeAsxGzkeGnJiDnFtgq3GaMX1cNXYd8ODx1z8fNii3dfnhtBnTCsjU2GcmXLpK\nF5BlYVdHX1By6fJndumSUd6fYYZodPSFEI2JQy5cDHod5rU2oN/HpxwpKM8fnj+tPMrVMuObXYjG\nGA52Dy9wTCWMLFdklXVIiMIfiuC//7ENT/7PdgDA5d+cgavOna36YrGhyoIQHx3QQjeYhKCr/M8N\nURooIMdJl6mOLaCwq9cTBselVl0mJj5lCMjxgJBrhsxxHP7P+XMxdUwV1m3vwmP/2DYkGwrxUfR4\nwhjT4EirjJbXku5iQmnVKlHJGgBakoRdIT4KISqiWuV5VDLkYexN2+LbHKkqCXLZerDamo/EsOWr\nXjTV2jA6frFQLoyPzwhPt4/cU2BTkHwiq6y/OODBbU+uxfodXZgypgq/uuwYnDinRZPyX43S+v+1\nd+dBcpb1vsC/b6/T+2w9nWUyM5nsCwkhOSk0GBT0gp5DpU6UqUO8Q5VIyLWuiYlKqZgQvEmZUoQ6\nSkCRG9EKWhCMCnUKKNALBImyeUxISEgyk2WWZLaemd6m9/f+0f129yy9Tfd0v939/fwDmcxMP++b\nmf69z/P8nt9v2MEMa0qNATlqYlGQRPNsUsWuGQjIjsiMTKWc/E+RaUeh+Aw598Cm06qwq201lsyr\nxvsfD+AXE4KydOwl1XI1EEmYUSmFzPaQi7hknXj0KZszyEB8qT3ZQ0eq5LelTZFmEe9/3D8ui/5U\npx3+QBjrlliLchQsFSmxKVWmdewMcgZZ6sUmzZAvX3PC6Qngize34rtbbogF12zUZ5BpLZ1B5pI1\nJcOAHBVfsp78yyJlyHalyTDNVigcxnBCM4uJpCVRV7ol6xzLZk5UpVFh552rsay5Bv84N4An/ngq\nVhAik/1jIDLbNuk1qfeQx6QZchEDcl28pnU2GdZAJGNap1UlfWDq7pfqfU++VyqlAmuXWDHq9uPj\nrpHYxz84F82ultlyNRB5eFEqhJSJXYOjkW5pqTplyYW+SgWzXo1ZtXp8/+61+NdPtEz77HQs0zrV\nDJlnkCkN+f/WFIh9inrSEotBA4tRk/cZ8ojTj7AoTvmaQMIMLM2S9Uws/Wo1Suz40iqsaKnBPy8M\n4vE/fohAMJRxQAYiDwgOjz/peVvpQcNYxCVrs0EDvVaFq0OehDrWmY8nVfGWrn4nakzapPuQ66Ui\nIWcjQTgQDOPEhUHUmati537lRK1SoNFqRFf/1Ild8TPIpbFHqlQocGDbJ7Dv3vUpjzVlIt6GMXlA\n5h4ypZNRQD5x4gTa29sBAB999BE+9alPob29He3t7XjppZcAAEeOHMHmzZvR1taG119/feZGPEOG\nHD6olELS0pNNDSYMO30ZNRPI/DWTJ5IBmS9Z51qlKxmtOhKUV7bW4mTHEH529ENcvOqAUiHE9l5T\nMes1CATDSbvpFKvTUyJBEDCn3oD+4bHYKkk2JR9NejVcY5Nrdjs9foy4/CkfXJY01cCsV+ODj/sR\nCodx5rIdY74Q1spwuVrSPMuEYCg8qSkHED+DXAr7xxKdVpWX2bz0EJJuhqzVKGN710QTpS0X89RT\nT+HFF1+EThf5JTt9+jS+8pWv4J577ol9zsDAAA4fPoyjR4/C5/Nhy5Yt2LBhAzQa+e8jSYYcXtSa\nq5IW1miyGfFh5xC6+l1Y3lKbn9dMkWENRGYkVRpl2izrmQxsapUS2zevwuN//BAnO4YAAI1WA9Sq\n9G9iUm9mh8c/ZfF/p8cPAYCxqngBGYgcfbrQMxpbOq7JJiDr4jW7E2fCmawkKBQC1i5twOv/6MHZ\nyyOyza5O1DzLBJyIFI+ZeG2ldAY536o0keXv1HvIPtSatLJ92KLiS/uu2tTUhMceeyz251OnTuGN\nN97Al7/8ZTzwwANwuVw4efIk1qxZA41GA5PJhKamJpw9e3ZGB55PgWAIDrc/5VGNmci0HkyR2S0x\n6tSx40HJ5HsPeSK1SoH//e/XYU20J+9UPZCnku7ok3MsAINOPeM1j9ORErvOR48gZbtkDUxexZhY\nMjMZadn676ev4b/PD8Ji1GDBXEvGr19oLbOSl9AcTPOAWe6s1ToMObxTlrr1B0JwjQW4f0wppZ0h\n33bbbeju7o79edWqVbjzzjuxcuVK/PznP8fjjz+OpUuXwmSKv0kbDAa4XJkFLqu1+HtlvYORsc5p\nMCYdz/UQgBdOo9/hzduYPdGl3EUttUm/Z62lCp09DtTXJz9m5PEFYdCpMXtW5m/k07mGPfd+Ai8f\nv4h1y2ywWtPvIc9piO7LKZVTvp7bG0S1SVv0n4GlrfXA/7uAQDAMhQC0NtdBmeFDgq0+ch+UGvW4\n6+iPLt+uWmIb9/GJ11pXZ0Ttf53B305fQ1gEvvDJFtgactvPnEmWaj2UCgG9Q55J1zIWiOwrL2xO\n/vNcLIUYT6PNjI5eBwS1CtYJFdak95jZ1uTvMeWokq41H7KucP65z30OZrM59v/79u3DunXr4HbH\niwW43e5xATqVgYGZKUmZjfOX7AAAg0aZdDyqsAitWonzV4bzNubuaNa2IhRO+j2r1EoEQ2F09Ywk\n7flqd3hh0qkzHpfVapr2NXxiWQMAMaOvV4qRN+juq6MYmD3+5yEcFuF0+2Gr0RX9Z8Cgjgdfk0ED\n+1DmqyAqRGZDXb2jaEg46nPhyjDUKgXUiP/bJrvvNyyux5/fjzz0Lm+qLvr9SGdOvQGdPaO41jc6\nbv+1K1pyVSVm9vNRKLn8vGfDpIvsDZ/tHIQQqhn3dx2XhwEAOnXy95hyU6j7XmpSPaRknc3w1a9+\nFSdPngQA/O1vf8OKFSuwatUqfPDBB/D5fHA6nejo6MDixYunP+ICS1UURKJQCGhsMOS1N7Ld4YVR\np07ZOs6Upl5yOCzC5QnkXKVrJphiDSYmj93tDUBEcYuCSGrNVdCoI78K2fbwnao4SDAURu/Q5JKZ\nyaxfagMQ2Z5Y0lSd1esXQ/MsE/zByYldg6PekjmDPBNS9UVm2UzKRNYz5Iceegj79u2DWq1GfX09\n9u3bB6PRiPb2dmzZsgWiKGLXrl3QakvnBy92BjnN3ldTgwkdPQ70DLpzPiYhiiKGRr1ps5VNunim\ndcMUBQucY5HANlP7x7mwpOgXLIcMa4lCEDC71oDLfc6sErqAxPKZ8Wu8ZvcgGBIzOhoGAK1zzfjE\nilmYP9tUEud3m20m/BVXcfmaE40JWxeDo2MlcwZ5JqSq1mWPFgXhHjKlklFAbmxsxJEjRwAAK1as\nwLPPPjvpc9ra2tDW1pbf0RWIXTqukab+bqxiV58r54DsHAvAHwynTYBJV89aCgTJjmsVU6qkLikJ\nqpiNJRLNqdfjcp8zq4QuYOoWjJm0p0ykEARsvWN5Vq9bTImJXRuumw0gcoZ6xOXH0hKY4c+U2Fnk\n0cmZ1iwKQpmozEfZCaQl63S/LE1Sxa48FAjJtAi/MUkWr2Q0+nGLDJZ+JzLq1BCE+BgTFbv14kTS\nSkX2S9aTtxSkn4+mDANyqWlsMEIQxte0jhXWKaEzyPkWWR0QUi9Zl0DTDSoeBmREArJZr4ZGnfrA\n/lxrpDdyPkpoxgNy6gAgLVknO/ok5xmyQiHApFOPW86VyKHTU6KlzZEkHKkFZaamOvbUneUMudRo\n1UrMqTfgSp8rdsSnlNouzhSFQkCdpSrJkrUPapUChqqsdwmpglR8QA6LIuyO5PWkE2nVSsyq1eNK\nHnojp2pmkSjdknXsDLJMZpoTSeUzJ4qX+5RHQF4414InvrkRqxbUZfV1apVyUvGWrn4X6sxaGIpc\n8GQmtdhM8AVCuGaPJHZJRUEq9QyyxFqtg9MTgNcfHPfxYacPNSwKQmlUfEB2egIIhsIZLyU12UyR\n3shT7BNlI12VLkmywhMSKYNZqoolN2aDBmO+0KTM9HinJ/k8SFRppjd7idSzjvz7ONx+jLr945Kd\nylGTtI8cXS3iDDkiXtM6/v4QDIXhcPuZYU1pVXxAzrahurQvmOuydSZHrYD4Hmuyjk8zXaUrV9K4\nJrZhlNuSdS5Meg2cngBEUYyXzLSVd0CeWLFrqIT6IM8k6xQ1rUfYVIIyVPEB2Z5hYJTkq4TmkMML\njVqRNsu4SqOEUiEkPYecz17IM8E8RRZy5M/yyrLOhUmnRigsYswXTKhhXd4ViuY1GCEAsVaMlX4G\nWTLV0Sd7LKGLM2RKreIDcrqOSxPNs+Un03po1Is6c1XaPaVIX2F18iVrtz/WhEKOks2QnZ4AtGpl\n2kS6UiAl1Dk9gazaU5ayKo0Ks+r0uNLnRFgUK/4MsiQWkBO2tHjkiTJV2b89SFxqyywgWwwaWAwa\nXOmf/pK11x+E2xvMOAHGpNckz7L2+GHWq2WbLGJOUhzEORYoi+VqYHziXVe/CxqVYsoiLuWmZVYk\nn6J3wI2REuqDPJOs1ZOXrBmQKVMMyLEZcua/LHPqDbA7fPAl6fOb9jWlh4AMZ+VGnTqaGDW+Kbwo\nihh1B2S7fwxMXRxEFEU4PWUUkKOJacMuH64OuTHXaix6B6tCaI6uFv3jXKRtZKXvHwOAvkoNvVY1\nYck6+h7DPWRKo+IDst3hg0aVfi83ka0m8sbTn6IZeSrZLpNLgWviLNnrDyEYCsumuMZULFME5FIY\ndzakf59zXSMIhTMvmVnqmqOJXR/EAjIDDhBZth4c9UKMHo3kDJkyVfEBecjhRZ0l/V5uooaaSGu1\n/mFPms9M8ppZ9o2Nl2ccv+wr9wxrIB6sEs8iSwlq5ZDQBcT/fT6Kdg2rlIDcNCGfotLPIEus1VUI\nBMOxvIlhpw8qpRCrukeUTEUHZJ8/0jQ823J20gy5b3h6M+TBLDO7k3V8knuGNTD1krVLRo0l8kG6\nDqn7UaUEZJ1WBVtC31/OkCPqJ2RaDzt9qDZqoZBpngfJR0UH5PhZ4OyWkhqkJescZ8iZvoGZdFMX\nBymFGbJKGSkXmNiCMV6lS77jzsbEB6JyLwqSSDqPDHCGLEk8+hQKhzHi8rEoCGWkogNytmeQJQ01\nOggA+uzTmyHbHb7Imc0MGxlM1VEISKjSJfOZptmgGTdDlq6jfJas49dRb6mCvoLqFUuJXQpB4B5p\nVDzT2otRlx+iCNSwqQRloKIDcrbJVRK1SokaszanpK4akzbjTNxYUtfEgFwCM2QgfmwrFI5kiZdT\nlS4A0KiV0EbPU1fS7BiIJ3bVmnkGWRIvnznGhC7KSkX/Bg05pl9/11ajx7DTB18gu6NPwVAYI05f\nVrNyaSZZinvIQPyBQZoZl9uSNRB/uKiU/WNJs80IpUIYt5dc6erMVRAQWbK2MyBTFio7II9Ov0ep\ntI88kGVil93hhYjs9ttKOcsaiPdqlsYbbyxRHjNkoHIDsr5KjW//x/X4n/9jcbGHIhsqpQK1Zi0G\nRr0YllbhGJApAxUdkO0OLwRM7+nVFj36lG2mde9gJBFsVhYzCoNOBQFT1IN2+yEI8t+LlTpRSQG5\n3JasgfgqRbk3lZjKkqaa2O8DRVirdRh2+tAX3dZiYwnKROVkn0xhyOFFtUkLlTL755LpZlr3DEbO\nbM61GjL+GqVCAX2ValJhkFFPACadWvZVoUwT6lk7PX4oFQJ02vL58fvXT7ZgSVNNRZTMpPTqq3XA\nlRFc6B4FwCVrykz5vCNmKRwWMez0oWX29LryTPcscu+gGwAwtz7zgAxILf4m1IN2+1FTAh1kLPqJ\ne8gBGGVcf3s6Fs61YOFcS7GHQTIhtWHs7ndBIQixinVEqVTskvWo249QWMz6yJNEyqTMeoY84IZG\npYgVD8iUSa+GayyAcLQcXyAYhscXlH1CFzC5OIhzzF9W+8dEE0nvDyKAapNG9qtYJA8VG5Bj5Sun\nGZA1aiVqzdqsZsjhsIjeIQ9m1xuyrtpj0msgioDHGwQQT/CSe0IXML4FYzAUxpgvVFYZ1kQTWRMe\nuLlcTZmq3IA8zTPIiRqiiRuZHn3qHxlDMBTOerkaSDj6FA3EpXLkCUhowejxxzOsyyihi2ii8QGZ\nCV2UmYoNyNOt0pVIajIxkGGBkJ6B6e0fA+N77gKAwx2t0mWQf2DTaiKFM5xuf+yBQu6Z4US5MOnV\n0Kgjb6888kSZqtiAHGvwkEP9XVuttI+cWUDunUaGtWRi+czYGeQSmCEDkQeHUY8/4chTaYybaDoE\nQYjNkrlkTZmq2IBsH51eY4lEDdXSWeTMErt6ohnWc6YzQ45V64ofHQLiR4rkzmzQwOkOxJbauWRN\n5c5qYUCm7FRsQB5yeKHTKqGvmn5gyHaG3DPohlajnNYy+cQla+lMb6kcpzDrNQiLIq5FWxRygGPu\nFgAAEcNJREFUyZrK3ey6yAO7VLOAKJ2KPYc85PDllNAFxBM3+uzpZ8jBUBjXhjxonmWa1vnbieUz\nnSU205QyraVz2FyypnL3+Rub0TrHgpZZ5mIPhUpERc6QPd4gxnzBnBK6AECrVqLGlFnXp77hMYTC\n4rSWq4GEjk9jJbqHHB1nTywgl8aDBNF0GXVqrF1iLfYwqIRUZEDOR4a1xFajg93hgz/N0SdpZtg4\nzYAcP/YUDcieAKo0Smiibf/kTpohSz2kOUMmIhqvIgNy/Axy7skWmR596hmIZFjPmUaGNRDvuRs7\nh+z2l0RREIm01y1VGjNUVexuCRHRlMryXXHY6cP//a+P4PVPPWt1RTOV8zVDBiJL0nNTNKfvidWw\nnn43oMTymU5PYFzxAblLfHgwVKmm1dCDiKiclWVAPnaiF2cuD0OlFJImUFmMmrw0A5BmyOkyrXsH\n3dBrVag2Tn9Wa9Sp0TPohjsalEtpHzZxrEYuVxMRTVJ2AVkURbx7pg9qlQL/uf2mGW/xZ8ugDWMg\nGEaffQytc805dTgy6TUIBJ0YGIksuZfKkSdg/FjZWIKIaLKyWzfsGXTj6pAHq1rrCtJv15pBG8Zr\ndg/CojjthC6JNMuUeiqXUmKUTquCShl5GCmlmT0RUaGUXUB+90w/AOBfljUU5PViR59SzJBjCV15\nCshSxnYpJXUJghAbLwMyEdFkZRWQRVHEe2f6oFErsHpBfcFet6E6cvQpEJw6iSye0JVbQJaOPvWU\nYEAG4jP6UprZExEVSlkF5Ct9LvQNj+H6hfXQagp3PtdWq4MIoD+6tzuRNKNNlYWdCSmQSV2jzCU2\n05T2kVk2k4hosrIKyO+djS5XLy3McrUklmmdpIRmz4AbRp065xmttNQ77PQBKL0ZslnPJWsiomTK\nJiBL2dVajRLXtdYV9LVtKRK7fIEQBkbG0DjNgiCJTLrxAbjUArIleuSrVMp9EhEVUtkce7p0zYnB\nUS9uXGEreDnJ+FnkyTPka0MeiMg9oQsYP7NUKgToC5BFnk83r56DsChiaXNNsYdCRCQ7pfWOnsK7\nZ/oAAOuX2gr+2g3VyWfI3dEM61wTuoDxAdls0OR0prkY6qt1uPPTC4s9DCIiWSqLJWtRFPHe2X7o\ntCqsmF9b8NfXapSoNmqmrNaVr4QuIHKWV6ngWV4ionJUFgG5o9cBu8OHGxbVQ60qziXZavSwO7yT\njj5JR5TysWQtCEIsQ7nU9o+JiCi1sgjI0nL1vywr/HK1pKEmcvRpYMLRp54BNyxGTd6O+kgzYyZG\nERGVl5IPyGFRxPtn+2GoUmF5S/GShRpimdbxxK4xXxBDDm9e9o8l0llkzpCJiMpLyQfk810jGHH5\nccNia1Fb+tmm6PrUO5S/5WpJbMmaM2QiorKSUQQ7ceIE2tvbAQCXL1/GXXfdhS1btmDv3r0Ih8MA\ngCNHjmDz5s1oa2vD66+/PnMjnkAqBrK+iMvVQOIMOSEgRytqNeYhoUsSW7I2MKmLiKicpA3ITz31\nFHbv3g2fL1Id6sCBA9i5cyd+97vfQRRF/OUvf8HAwAAOHz6MZ599FocOHcKjjz4Kv98/44MPh0W8\n//EATHo1ljZXz/jrpWKb4ixyPhO6JLXmKgBAXfS/RERUHtIG5KamJjz22GOxP58+fRrr168HAGzc\nuBHHjx/HyZMnsWbNGmg0GphMJjQ1NeHs2bMzN+qoj68Mw+H2Y+2SBigVxV1912qUsEw4+hQLyHX5\nC8ifWTMX/2vTCiyeV9wHECIiyq+0hUFuu+02dHd3x/4simKsIIXBYIDT6YTL5YLJZIp9jsFggMvl\nymgAVqsp/Scl8dwbHQCAz93YnNP3yZfGBhPOXBxCdY0eapUS1+we1Ffr0Dwvv8lmTY25fz853K9K\nxPteHLzvxcH7np2sK3UpEmaibrcbZrMZRqMRbrd73McTA3QqAwPObIcAAAiFw3j7RC8sBg1sJu20\nv08+1Rg1CIvAmQsDsBg0GBr1YmVrrSzGlshqNcluTJWA9704eN+Lg/d9aqkeUrJe512+fDneeecd\nAMCxY8ewbt06rFq1Ch988AF8Ph+cTic6OjqwePHi6Y84A2cuD8M1FsC6JQ1QKORRQjLWZMI+Fluu\nbqzPX0IXERGVr6xnyN/5znewZ88ePProo2htbcVtt90GpVKJ9vZ2bNmyBaIoYteuXdBqtTMx3ph3\nz0RbLS4rbKvFVBITuzTuSIOLfCZ0ERFR+cooIDc2NuLIkSMAgPnz5+OZZ56Z9DltbW1oa2vL7+iS\nCIbC+O9zA6gxabGw0VKQ18xE4tEnadY+Nw9tF4mIqPyVZLenzl4H3N4gblw+CwoZdTySAnL/sAdh\nMfKxfGZYExFR+SrJgHy+ewQAsKRJXkd/qjQqWAwa9A2PwR8Iod5SBa2msL2ZiYioNJVk6cxzXaMA\ngEUyPItrq9FhcNQLhyeQ1wpdRERU3kouIIfDIi70jMBWo4NFhg0WGqKJXQATuoiIKHNFDcgebyDr\nr+kecGHMF5Ll7BgAbLW62P/ns8sTERGVt6IG5B2PvIGwlP2UofPd0eVqGWVXJ0qcITPDmoiIMlXU\ngNxn9+DiNUdWX3OuK5LQJddazlJxEEEAZtfp03w2ERFRRNH3kE912jP+XFEUca57BBaDBg3VuvRf\nUATW6LgaqnVQq5hhTUREmSlqQFYoBHzYOZTx5w+MejHq8mNRoyXW4EJudFoV7vhkC/7tky3FHgoR\nEZWQop5DXtZSi486h+D0+GHSp8+YPh9drpZrQpfk3ze2FnsIRERUYoo6Q167tAEigNMXM1u2ju0f\nN8o7IBMREWWryAHZBgAZL1uf6x5FlUaJeQ0suEFEROWlqAF5/hwzLEYNTl20IyymPv7kcPvRZ/dg\n4VyLbNotEhER5UtRA7IgCLhufh2cngAuX0vdyFqqXy33/WMiIqLpKPqxp+sW1AFIv2wt1a9eLNOC\nIERERLkoekBe0VIDhZD++NO57hGolAJa55gLNDIiIqLCKXpA1lepsWCuGZ29DrjGpq5tPeYL4kqf\nEy2zzCy2QUREZanoARkAVrbWQRSTH3/q7HVAFIFF87hcTURE5UkWAXlVa+p9ZJ4/JiKicieLgDzP\nZoTZoMGpzqEpjz+d7x6BAGAhE7qIiKhMySIgKwQB182vhcMTwJW+8cefgqEwOnsdmGs1wFClLtII\niYiIZpYsAjKQePxp/D7y5WtO+INhnj8mIqKyJpuAvLylFoIweR/5XDf3j4mIqPzJJiAbdWosmGNB\nR88o3N748afz0YIgi7h/TEREZUw2ARkArmutHXf8KSyKON89gnpLFWrNVUUeHRER0cyRV0CeUEbz\n6qAbbm8Qi7hcTUREZU5WAbnJZoJZr8apzkj3p3Pd0frVLAhCRERlTlYBWSEIWDG/DqNuP7r6XDgf\nLQjCGTIREZU7WQVkALhuQS0A4NTFIZzvHoFRp8bsOn2RR0VERDSzZBeQV86vgyAAb528iiGHD4sa\nLRAEodjDIiIimlGyC8hGnRqts83oHx4DwOVqIiKqDLILyABwXbTZBAAsZoUuIiKqAPIMyNHjTxq1\nAk02Y5FHQ0RENPNUxR7AVJpnmTC33oB5NiNUSlk+MxAREeWVLAOyQhDwf766nslcRERUMWQ7/WQw\nJiKiSiLbgExERFRJGJCJiIhkgAGZiIhIBhiQiYiIZIABmYiISAYYkImIiGSAAZmIiEgGGJCJiIhk\ngAGZiIhIBhiQiYiIZIABmYiISAYEURTFYg+CiIio0nGGTEREJAMMyERERDLAgExERCQDDMhEREQy\nwIBMREQkAwzIREREMqDK9zcMBAJ44IEH0NPTA7/fj6997WtYuHAhvvvd70IQBCxatAh79+6FQhF5\nFrDb7bjrrrvw4osvQqvVxr5PR0cH2tracPz48XEfp6nlet9FUcTGjRvR0tICALj++uvxrW99q4hX\nVBpyve+hUAgHDhzAqVOn4Pf7sX37dnzmM58p8lXJX673/Ze//CXeeustAIDD4cDg4CDefvvtYl5S\nScj1vjudTuzatQsejwcajQYPP/wwrFZrka9KRsQ8+/3vfy/u379fFEVRHB4eFm+++WZx27Zt4t//\n/ndRFEVxz5494quvviqKoigeO3ZM3LRpk7hmzRrR6/XGvofT6RS3bt0q3njjjeM+Tsnlet8vXbok\nbtu2rTiDL2G53vejR4+Ke/fuFUVRFK9duyY+/fTTBb+GUpSP9xnJfffdJ7711luFG3wJy/W+//rX\nvxZ/9KMfiaIois8995x44MCBIlyFfOV9yfr222/HN77xDSnYQ6lU4vTp01i/fj0AYOPGjTh+/DgA\nQKFQ4Omnn0Z1dXXiAwL27NmDb37zm9DpdPkeXtnK9b6fPn0afX19aG9vx9atW9HZ2Vn4iyhBud73\nv/71r7DZbLjvvvuwe/du3HLLLYW/iBKU632XvPrqqzCbzbjpppsKN/gSlut9X7x4MdxuNwDA5XJB\npcr7Im1Jy3tANhgMMBqNcLlc2LFjB3bu3AlRFCEIQuzvnU4nAGDDhg2oqakZ9/UHDx7EzTffjKVL\nl+Z7aGUt1/tutVpx33334fDhw9i2bRvuv//+gl9DKcr1vg8PD+PKlSt48sknsXXrVnzve98r+DWU\nolzvu+TJJ5/E17/+9YKNu9Tlet9ramrw9ttv4wtf+AIOHTqEL33pSwW/BjmbkaSuq1ev4u6778am\nTZtwxx13xPYTAMDtdsNsNif92hdffBFHjx5Fe3s7BgYGcM8998zEEMtSLvd95cqVuPXWWwEA69at\nQ39/P0RWVc1ILve9uroan/70pyEIAtavX49Lly4VYMTlIZf7DgAXLlyA2WxGc3PzTA+1rORy3w8e\nPIh7770XL730Eg4dOoTt27cXYsglI+8BeXBwEPfccw/uv//+2NPP8uXL8c477wAAjh07hnXr1iX9\n+tdeew2HDx/G4cOHYbVa8atf/SrfQyxLud73gwcP4je/+Q0A4OzZs5g9e3bsqZeSy/W+r127Fm++\n+SaA+H2n9HK97wBw/PhxbNy4ccbHWk5yve9msxkmkwkAUFdXF1u+poi8N5fYv38/Xn75ZbS2tsY+\n9v3vfx/79+9HIBBAa2sr9u/fD6VSGfv7W265BS+//PKkbOpkH6fJcr3vo6OjuP/+++HxeKBUKvHg\ngw9iwYIFxbiUkpLrfff7/di7dy86OjogiiIeeughrFixohiXUlLy8T7zgx/8ABs2bMBnP/vZgo+/\nVOV63/v6+rB79254PB4Eg0Hs2LEDGzZsKMalyBK7PREREckAC4MQERHJAAMyERGRDDAgExERyQAD\nMhERkQwwIBMREckA65YRlYnu7m7cfvvtseNqXq8XS5YswYMPPoj6+vqkX9fe3o7Dhw8XaphElARn\nyERlpKGhAS+88AJeeOEFvPLKK2hubsaOHTtSfs27775boNERUSqcIROVKUEQsH37dmzYsAFnz57F\nM888g/Pnz2NwcBDz58/HwYMH8ZOf/AQAcOedd+L555/HsWPH8LOf/QzBYBCNjY3Yt29f0jrQRJRf\nnCETlTGNRoPm5mb8+c9/hlqtxnPPPYfXXnsNPp8Pb775Jnbv3g0AeP7552G32/HII4/g0KFD+NOf\n/oSbbropFrCJaOZxhkxU5gRBwPLlyzFv3jz89re/RWdnJy5dugSPxzPu806cOBFrHAAA4XAYFoul\nGEMmqkgMyERlzO/34+LFi+jq6sJPf/pT3H333di8eTOGh4cndfMKhUK44YYb8Itf/AIA4PP5WPyf\nqIC4ZE1UpsLhMB577DGsXr0aXV1d+PznP48vfvGLqK+vx3vvvYdQKAQAUCqVCAaDWL16Nf75z3/i\n4sWLAIAnnngCP/7xj4t5CUQVhTNkojLS39+PTZs2AYgE5GXLluGRRx5BX18fvv3tb+OVV16BRqPB\n9ddfj+7ubgDArbfeik2bNuEPf/gDfvjDH2Lnzp0Ih8Ow2Wx4+OGHi3k5RBWF3Z6IiIhkgEvWRERE\nMsCATEREJAMMyERERDLAgExERCQDDMhEREQywIBMREQkAwzIREREMsCATEREJAP/HzMhfKFEcoLq\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1fc83bdecc0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#stoerungen_raw['Text'].groupby(pd.Grouper(freq='W')).count().plot()\n",
"stoerungen_raw['Text'].groupby(pd.Grouper(freq='M')).count().plot(title='Anzahl der Störungsmeldungen pro Monat')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Im nächsten Schritt sehen wir uns die Verwendung der \"hot words\" in Meldungen an. Wir filtern die Meldungen, welche diese Worte beinhalten."
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
"stoerungen_hotwords = stoerungen_raw[stoerungen_raw['Text'].str.contains('|'.join(hot_words))]"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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BEh127i51vvw6oxOuLLynrzczc+BwS0a8X5UNANDqUWZ8o5OtosdIYWeCIIgu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"text/plain": [
"<matplotlib.figure.Figure at 0x1fc855e8978>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"stoerungen_hotwords['Text'].groupby(pd.Grouper(freq='M')).count().plot(title='Anzahl der Störungsmeldungen, die Signalwörter beinhalten (pro Monat)')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wenn man sich die Struktur einer Meldung genauer ansieht, dann beschreibt der Text vor dem ersten Doppelpunkt meist die Art der Meldung (Aktualisierung / Störung / etc.) und nennt die betroffenen S-Bahnen und der darauffolgende Text gibt Details zur Art der Störung. Deshalb spalten wir nun alle Meldungen in genau diese Bestandteile zur genaueren Analyse."
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"No match for 139 entries\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Type</th>\n",
" <th>Text</th>\n",
" <th>Date</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2014-01-01 06:19:00</th>\n",
" <td>stammstrecke</td>\n",
" <td>notarzteinsatz / verzögerungen</td>\n",
" <td>stand 01.01.2014, 06:20 uhr)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-01 07:34:00</th>\n",
" <td>stammstrecke</td>\n",
" <td>feueralarm münchen hbf / s-bahnen verkehren oh...</td>\n",
" <td>stand 01.01.2014, 07:35 uhr)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-01 08:00:00</th>\n",
" <td>stammstrecke</td>\n",
" <td>polizeieinsatz / streckensperrung</td>\n",
" <td>stand 01.01.2014, 08:00 uhr)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-01 08:13:00</th>\n",
" <td>1. aktualisierung stammstrecke</td>\n",
" <td>streckensperrung aufgehoben / folgeverzögerungen</td>\n",
" <td>stand 01.01.2014, 8:15 uhr)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-01 12:33:00</th>\n",
" <td>s 4 ebersberg</td>\n",
" <td>personen am gleis / streckensperrung</td>\n",
" <td>stand 01.01.2104, 12:30 uhr)</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Type \\\n",
"Date \n",
"2014-01-01 06:19:00 stammstrecke \n",
"2014-01-01 07:34:00 stammstrecke \n",
"2014-01-01 08:00:00 stammstrecke \n",
"2014-01-01 08:13:00 1. aktualisierung stammstrecke \n",
"2014-01-01 12:33:00 s 4 ebersberg \n",
"\n",
" Text \\\n",
"Date \n",
"2014-01-01 06:19:00 notarzteinsatz / verzögerungen \n",
"2014-01-01 07:34:00 feueralarm münchen hbf / s-bahnen verkehren oh... \n",
"2014-01-01 08:00:00 polizeieinsatz / streckensperrung \n",
"2014-01-01 08:13:00 streckensperrung aufgehoben / folgeverzögerungen \n",
"2014-01-01 12:33:00 personen am gleis / streckensperrung \n",
"\n",
" Date \n",
"Date \n",
"2014-01-01 06:19:00 stand 01.01.2014, 06:20 uhr) \n",
"2014-01-01 07:34:00 stand 01.01.2014, 07:35 uhr) \n",
"2014-01-01 08:00:00 stand 01.01.2014, 08:00 uhr) \n",
"2014-01-01 08:13:00 stand 01.01.2014, 8:15 uhr) \n",
"2014-01-01 12:33:00 stand 01.01.2104, 12:30 uhr) "
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"text_split = stoerungen_raw['Text'].str.lower().str.strip()\n",
"#text_split = stoerungen_hotwords['Text'].str.lower().str.strip()\n",
"\n",
"regexp = r'(.+):{1} {1}(.*)\\({1}(.+)[\\)9]{0,1}'\n",
"res = text_split.str.extract(pat=regexp, expand=True)\n",
"res.columns = ['Type', 'Text', 'Date']\n",
"nantext = pd.isnull(res['Type'])\n",
"print('No match for {} entries'.format(np.sum(nantext)))\n",
"\n",
"stoerungen = res[~nantext]\n",
"stoerungen.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wir nehmen nur die Meldungen, wo diese Aufspaltung ein sinnvolles Ergebnis erzeugt und extrahieren einen Typ der Meldung (`type`), einen Text (`Text`) und ein Datum (`Date`).\n",
"\n",
"Als nächstes filtern wir Störungsmeldungen, die häufig auftreten, die aber unsere Analyse nicht verfälschen sollen heraus. Dazu gehören die häufigen Aktualisierungen zu Störungsmeldungen (wir möchten nur die erste, ursprüngliche Störungsmeldung zählen und analysieren) und nehmen auch die häufigen Meldungen zum Ausfall von S-Bahnen des 10-Minuten-Taktes hinaus, weil das meist mit einer Störung zusammenhängt und wir diese dann doppelt oder dreifach zählen würden. Insgesamt möchten wir eher eine Störung nicht zählen, als eine zu viel."
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [],
"source": [
"stoerungen_without_10mtakt = stoerungen[~stoerungen['Text'].str.contains('10-minuten-takt')]\n",
"\n",
"# types = np.unique(stoerungen['Type'])\n",
"types = np.unique(stoerungen_without_10mtakt['Type'])\n",
"types_freq = pd.DataFrame({'Words': types, 'Freq': [np.sum(stoerungen_without_10mtakt['Type'] == typ) for typ in types]})"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Hier filtern wir diejenigen Störungen hinaus, die im Typ das Wort Aktualisierung beinhalten. (Die Variable `Keep` beschreibt, ob wir die Meldung behalten möchten oder nicht.)"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"types_freq['Keep'] = ~types_freq['Words'].str.contains('aktualisierung')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wir können uns nun diejenigen Meldungstypen mit dem höchsten Auftreten ansehen. Erwartungsgemäß tritt hier die Stammstrecke am häufigsten auf."
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Freq</th>\n",
" <th>Words</th>\n",
" <th>Keep</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1022</th>\n",
" <td>1074</td>\n",
" <td>stammstrecke</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>920</th>\n",
" <td>350</td>\n",
" <td>s 7 wolfratshausen</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>763</th>\n",
" <td>296</td>\n",
" <td>s 2 erding</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>725</th>\n",
" <td>255</td>\n",
" <td>s 1 freising/flughafen</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>939</th>\n",
" <td>233</td>\n",
" <td>s 8 herrsching</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>719</th>\n",
" <td>226</td>\n",
" <td>s 1 freising / flughafen</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>867</th>\n",
" <td>219</td>\n",
" <td>s 4 geltendorf</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>913</th>\n",
" <td>196</td>\n",
" <td>s 7 kreuzstraße</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>829</th>\n",
" <td>188</td>\n",
" <td>s 3 holzkirchen</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>861</th>\n",
" <td>180</td>\n",
" <td>s 4 ebersberg</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>897</th>\n",
" <td>169</td>\n",
" <td>s 6 tutzing</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>837</th>\n",
" <td>115</td>\n",
" <td>s 3 mammendorf</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>650</th>\n",
" <td>107</td>\n",
" <td>gesamtnetz</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>910</th>\n",
" <td>97</td>\n",
" <td>s 7 kreuzstrasse</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>927</th>\n",
" <td>95</td>\n",
" <td>s 8 flughafen</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>749</th>\n",
" <td>83</td>\n",
" <td>s 2 altomünster</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>786</th>\n",
" <td>71</td>\n",
" <td>s 2 petershausen</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>807</th>\n",
" <td>62</td>\n",
" <td>s 20 höllriegelskreuth</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>790</th>\n",
" <td>58</td>\n",
" <td>s 2 petershausen / altomünster</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>863</th>\n",
" <td>51</td>\n",
" <td>s 4 ebersberg / s 6 zorneding</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Freq Words Keep\n",
"1022 1074 stammstrecke True\n",
"920 350 s 7 wolfratshausen True\n",
"763 296 s 2 erding True\n",
"725 255 s 1 freising/flughafen True\n",
"939 233 s 8 herrsching True\n",
"719 226 s 1 freising / flughafen True\n",
"867 219 s 4 geltendorf True\n",
"913 196 s 7 kreuzstraße True\n",
"829 188 s 3 holzkirchen True\n",
"861 180 s 4 ebersberg True\n",
"897 169 s 6 tutzing True\n",
"837 115 s 3 mammendorf True\n",
"650 107 gesamtnetz True\n",
"910 97 s 7 kreuzstrasse True\n",
"927 95 s 8 flughafen True\n",
"749 83 s 2 altomünster True\n",
"786 71 s 2 petershausen True\n",
"807 62 s 20 höllriegelskreuth True\n",
"790 58 s 2 petershausen / altomünster True\n",
"863 51 s 4 ebersberg / s 6 zorneding True"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"types_freq[types_freq['Keep']].sort_values(by='Freq', ascending=False).head(20)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Als nächsten sehen wir uns die Erwähnungen der S-Bahnlinien in diesen Meldungen an und zählen sie."
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>S-Bahnlinie</th>\n",
" <th>Mentions</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>S1</td>\n",
" <td>680</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>S2</td>\n",
" <td>799</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>S3</td>\n",
" <td>440</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>S4</td>\n",
" <td>602</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>S6</td>\n",
" <td>385</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>S7</td>\n",
" <td>784</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>S8</td>\n",
" <td>588</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" S-Bahnlinie Mentions\n",
"0 S1 680\n",
"1 S2 799\n",
"2 S3 440\n",
"3 S4 602\n",
"4 S6 385\n",
"5 S7 784\n",
"6 S8 588"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sbahnlinien = ['1', '2', '3', '4', '6', '7', '8']\n",
"mentions = dict()\n",
"\n",
"for sbahnlinie in sbahnlinien:\n",
" mentions['S{}'.format(sbahnlinie)] = types_freq['Freq'][(types_freq['Words'].str.contains('s {}'.format(sbahnlinie)) | types_freq['Words'].str.contains('s{}'.format(sbahnlinie))) & types_freq['Keep']].sum()\n",
"\n",
"freq = pd.Series(list(mentions.values()))\n",
"sbahnlinie = pd.Series(list(mentions.keys()))\n",
"m = pd.concat([sbahnlinie, freq], axis=1)\n",
"m.columns = ['S-Bahnlinie', 'Mentions']\n",
"m"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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AJqot8t/85jeSpLKyMm3YsEElJSWSpIqKCu3bt09/+tOfLk5CAABQrVpf7Pbw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\n1Y8//ihJ2r9/v6699lrNnz/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"text/plain": [
"<matplotlib.figure.Figure at 0x1fc8727d400>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots()\n",
"sns.barplot(x='S-Bahnlinie', y='Mentions', data=m)\n",
"plt.title('Anzahl der Erwähnungen der S-Bahnlinien in Störungsmeldungen')\n",
"ax.set_ylabel('Anzahl')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [],
"source": [
"def plot_linien_stoerungen(sbahnlinie):\n",
" \n",
" monthly_stoerungen_without_updates = stoerungen['Type'][(stoerungen['Type'].str.contains('s {}'.format(sbahnlinie)) |\n",
" stoerungen['Type'].str.contains('s{}'.format(sbahnlinie)) |\n",
" stoerungen['Type'].str.contains('stammstrecke')) &\n",
" ~stoerungen['Type'].str.contains('aktualisierung') & ~stoerungen['Text'].str.contains('10-minuten-takt')] \\\n",
" .groupby(pd.Grouper(freq='M')).count()\n",
" monthly_stoerungen = stoerungen['Type'][(stoerungen['Type'].str.contains('s {}'.format(sbahnlinie)) |\n",
" stoerungen['Type'].str.contains('s{}'.format(sbahnlinie)) |\n",
" stoerungen['Type'].str.contains('stammstrecke')) &\n",
" ~stoerungen['Text'].str.contains('10-minuten-takt')] \\\n",
" .groupby(pd.Grouper(freq='M')).count()\n",
"\n",
" monthly_stoerungen_without_updates.plot(label='Anzahl')\n",
" monthly_stoerungen_without_updates.rolling(6).mean().plot(title='Anzahl der Störungsmeldungen für die S{} (pro Monat)'.format(sbahnlinie), label='Trendlinie')\n",
" #monthly_stoerungen.plot(label='Count updates')\n",
"\n",
" #(monthly_stoerungen - monthly_stoerungen_without_updates).plot(label='Difference')\n",
"\n",
" plt.legend()\n",
" #plt.axhline(y=monthly_stoerungen_without_updates.mean(), color='red')\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Als nächstes folgen Grafiken für die S-Bahnlinien zur Anzahl der monatlichen Störungen für die jeweilige S-Bahnlinie (Störungen der Stammstrecke, die alle Linien betreffen, sind hier auch eingerechnet). Weiterhin ist die 6-Monats-Trendlinie eingezeichnet."
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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ISbfENM4vGEsc/Z2jEd89tv1hjyHEVyAQCAS9Eo/XT4PDG3e8F8BkjH2mrzNC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\nRnQ6iXNPHozb42drm8Srqno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RmcPIlYaycZOPb02fyqVTRgOwv/Yge2sPcKzxOEPTB0dz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\ngg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1fc852c01d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_linien_stoerungen(1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Für die S2 und S8 sollte man bedenken, dass wir die Meldungen zum Ausfall der S-Bahnen des 10-Minuten-Taktes entfernt haben."
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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jEGa+ACP7p5CWaODb/UWYa99jc8H3HK88xcjU4Txw3t0MThqAze5i494CkuL0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\nLwCEiS8AhIkvAIQ91Fgw0fmAutgAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1fc85460f28>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_linien_stoerungen(2)"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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PmjWLv/71r5x99tkMGDCACRMmtNmWiRMn8pvf/Ibf/va3mM1mhg8fHkq4+etf/8ojjzzC\nM888g1ar5U9/+hMDBgwI99Zx00038fjjjzNz5kz8fj+jRo1qMhd42mmnsWPHDi666CKSkpIYOXJk\naK4/1q8nnPZE4rzzzmPFihWcddZZ5OTkNJnbb0lr7ylVWloazz33HE888QRutxtFUXjiiSfo379/\no+P0ej2vv/46f//735k3bx4WiwWNRsPMmTO5+OKLAXjhhReYO3cuHo8HvV7Pgw8+SF5eXpNrnnPO\nOaxcuZKTTjop9LMNGzbw/vvvEwgE+Mc//tFoeFh18cUXU1xczCWXXEIgEGDQoEFN5vaPdNxxx+F0\nOpk6dWqTUZNozjd9+nS+/PJLpk2bhsFgYOLEiVRXV2Oz2Rg+fDg6nY6LL76YDz74AI1Gw6pVq6Je\nGibappEtBYVo3ebNm/npp5+44oorAPjXv/7Fpk2bQl8Eepre9no6k81m4ze/+Q0ffvghcXFxjBgx\ngrVr1zYZ6u7p1q1bx1tvvSVLjTqQBF8h2mCz2bj77rvZu3cvGo2GnJwcHnroIbKzs7u6aVHpba+n\nsy1dupRNmzbx//7f/+uVwdfv93PDDTcwd+5csrKyuro5vZYEXyGEEKKTScKVEEII0ckk+AohhBCd\nTIKvEEII0ck6ZamRz+fHanW0faCIqdRUi9z3LiD3vWvIfe8act9blpmZ2OJjndLz1eubVqcRHU/u\ne9eQ+9415L53Dbnv0ZFhZyGEEKKTSfAVQgghOpkEXyGEEKKTSfAVQgghOpkEXyGEEKKTSfAVQggh\nOpkEXyGEEKKTSfAF3nrrTc4//2zcbndMzvf66y+zaNGCJj8/77yzY3J+IYQQPZsEX+DLLz/njDPO\nYtmyL7u6KUIIIfqATikv2Zb3l+9m/fbSmJ5z/MgsfjN1WJvHbdjwA7m5A7jggot48ME5TJs2gz/9\n6TqGDx/B3r17cDhsPPTQ45SXl/HSSy8AUF1dhcvl4oMPFvPSSy+wfftWamqqGTbsKO6++z4AVq5c\nwddfL6O6upprr72BSZMmx/T1CSGE6Ln6fM/3k08+ZsaMC8jLG4zBYGDLll8AGDXqaJ599v8YN+5E\nvvrqv4wZM5YXXniFRx75O/HxCTz88BPY7TYSExN55pn/47XX5rFly2bKyoJfIjIzM3n22Rf5y19u\na3YIWgghRNexOb18t/UwXbWlfbfo+f5m6rCweqmxVlNTw9q1q7FaK1mw4D3sdhsLF74HwFFHjQAg\nOzubiooKABwOB3fd9VeuueZ6RowYic/nw2q1ct99d2OxWHA6nfh8PgBGjBgFQHp6Bi6Xq9NfmxBC\niJa9+fl2ftxZRnaqhfycpE6/frcIvl3lyy8/Y/r087n55v8FwOVycckl55GcnIJGo2l0rMfj4d57\nb+fCCy9h/PgTAfjuu9WUlpbw4IOPYrVaWbHi69C3qCOeLoQQops4cLiWH3eWAVBt93RJG/p08F2y\n5GNmz34w9G+z2cxpp03lk08WNTl2wYJ32blzO36/n48+Cg4j33//XP7979e5+eY/otFoyM3tT3l5\nWae1XwghROQ+XrUv9N8Ol7dL2qBROmnAu6ystjMuIxrIzEyU+94F5L53DbnvXaOn3fd9xTU89OYP\n6HVafP4Av/v1cH49bmCHXKvL9/MVQgghuoNFK4O93rMnBAOuw+3rknZI8BVCCNEn7C6sZvPeCkbm\npXD8UZkAOFwSfIUQQogOs2jlXgAuOHUI8eZgypMEXyGEEKKD7CiwsnW/laMHp3LUwBQsZgMgw85C\nCCFEh1EznC84dQgAcSYd0HXZzhJ8hRBC9GrbDljZXlDF2KHpDO2fDIBOq8Vs1Mmwc1d4/vl/8Kc/\nXcfvfncRF174P/zpT9dx7713xOTcixYt4PXXX6a4uIjrrrsSgPvuuwuvt+VvWXff/beYXFsIIUSQ\noih8VDfXe/6k/EaPWcz6Lht27tNFNv7851sB+OyzJRw4sJ8bb/xzh17vgQcebfXxRx75e4deXwgh\n+pot+yvZfaiaY4dlNCkjaTHpqayJzVaykeoWwXfh7k/4qXRzTM95XNYxXDhsesTP27DhB1588XkM\nBgPnnTeT7Ox+vPLK/6HT6cjN7c/tt9/Dl19+ztq1q3G7XRQWHuLyy//AtGkz2LRpI88++ySJiUno\ndDqOPnpMo3NffPEM3nprAU8++SgGg4HDh4upqCjn7rvvZ8SIkZx33tksXvxf9uzZzTPP/B1FUUhO\nTuauu+4jISEhVrdGCCH6BEVRQut6Lzg1v8njFpOeQredgKKg7eSawGEF35dffpnly5fj9Xq57LLL\nmDBhAnfeeScajYbhw4dz3333odX2nhFsj8fDq6++iaIoXHbZRbz44mukpqbx6qsv8tlnS9Dr9djt\nNp5++gUOHizgjjtuZdq0GTz11KM8/PAT5OUN4sknW+/l9uuXw+2338PixR+xePFC/va3u0OPPf74\nw9x11xzy84fwySeLeOutN7n++ps7+mULIUSv8vOeCvYW1XDCiEzysptWm7KYDSiAy+0LZT93ljaD\n77p16/jpp5945513cDqdvPHGGzz66KPccsstnHjiicyZM4dly5Zx5plnRt2IC4dNj6qX2lHy8gYB\nUFVlpaKinNmz7wTA7XYzfvyJDBgwkGHDjgIgKysbjydYmLuysjL03GOO+RWHDh1s8RrDh48IPX/z\n5k2NHjtwYB9PPfUYAH6/jwED8mL46oQQovdTe70ams71qiwN1vp2u+C7atUqjjrqKG6++WZsNhu3\n334777//PhMmTABg8uTJrF69ul3Bt7vRaoPDD8nJKWRlZfHYY0+TkJDAqlXfEhdnoaTkcJNdjyC4\nh+/+/fsYPDifbdu2kpjYcl3P5p6vyssbxL33Pki/fv34+eeNVFSUt/9FCSFEH7Lml8McKKllwqgs\nBmQ2P21nMdUF3y5Iumoz+FqtVoqKinjppZc4dOgQN954I4qihIJHfHw8tbVtF9VurcB0V0tMNGOx\nGMnMTCQlxYLJZAi1d86c2dx9920oikJ8fDxPPPEE335bFTre7Tai02nJzEzkkUfm8sADD5CQkEB8\nfDz9+mWQlhaPwaAjMzMxdJzZbCA5OY7MzESSk+Mwm4PX02o1ZGYm8vDDD/H44w/i8/nQaDTMnTs3\n6vvXne97byb3vWvIfe8a3e2+FxyuYf5XO7GY9fxx5lgy0+ObPU79ucFs6PTX0OauRk8++SRpaWlc\nffXVAJx33nkcOHCATZuCQ6VLly5lzZo1zJkzp9UL9aRdL3qLnrbbSG8h971ryH3vGt3tvrs8Ph56\n8weKKxzcPHMMJ4zIavHYL9cf5N1lu7h55jGcMCIz5m1p165GJ5xwAitXrkRRFEpKSnA6nUycOJF1\n69YBsGLFCsaNGxe71gohhBBRUBSFN7/YQXGFgzPHDWw18ELDYefOr3LV5rDzlClTWL9+PRdffDGK\nojBnzhwGDBjA7NmzefrppxkyZAhnn312Z7RVCCGEaNE3PxWybmsJQ/snccmUoW0eb+nCzRXCWmp0\n++23N/nZ/PnzY94YIYQQIhr7imt4Z9kuEuIM3Hj+GPS6tpe/duXORr1nca4QQog+ye7y8uKiX/D7\nFa6bMZq0JHNYz4vrwmxnCb5CCCF6rICi8NqSrZRXu5hxymDGDEkP+7ldOewswVcIIUSP9cW6Ajbt\nqWD04FTOO6X5YhotiVf39O2CbQUl+AohhOiRdhRYWfjtXlISjFw34+hQgaRwmYw6NBoZdhZCCCHC\n4nT7eOnjLQDceMEYkuKNEZ9Dq9FgMXXNtoISfIUQQvQ4+4trqLZ7mHpCf4YPSIn6PHEmvcz5CiGE\nEOEoqXICkJfVvrKQ8WaDBF8hhBAiHGXWYPDNSo1r13ksZj1urx+fPxCLZoVNgq8QQogepzRWwbeL\n1vpK8BVCCNHjlFY5MRq0JEeRaNWQutbX2clDzxJ8hRBC9CiKolBqdZKVYml1b/RwhAptSM9XCCGE\naFmNw4vb62/3kDM0GHaWnq8QQgjRslKrA2j/fC+Apa7Klb2Tq1xJ8BVCCNGjhJKtUmIRfGXYWQgh\nhGhTrDKdoX7YOdYJV6s3F7f6uARfIYQQPUpZVex7vvYYBl+7y8vrn25r9RgJvkIIIXqUEqsTnVYT\n9r69rVHnfGM57Fxc4WjzGAm+QgghepSyKicZKXER72LUnPps59glXB2W4CuEEKI3cbi82JxesmMw\n3wsNEq5iOOx8uFKCrxBCiF6ktG6+NzMG870ARr0WvU4T02FnCb5CCCF6lVhmOgNo1D19Y9zzjTPp\nWj1Ggq8QQogeoySGa3xVcWZDzHq+gYBCqdVBvzRLq8dJ8BVCCNFjxGorwYaCPV8viqK0+1zl1U58\nfkWCrxBCiN6j1OpAA2Qkxy74xpv1+PwKXl/79/RV53sl+AohhOg1SqucpCWZMehjF75iWWJSXWbU\nLz2+1eMk+AohhOgR3F4/VTZPTIecoX6tbyyqXBVLz1cIIURvEiorGevgW1flKhb1nQ9XONCgsN2x\nodXjJPgKIYToEWK9zEhVP+zc/ipXxZV2EkZsZdHeT1o9Tt/uKwkhhBCdIJZbCTZUX2KyfT1fm8uN\nM/sH9MnFDEoc2Oqx0vMVQgjRI5SGhp1bn0+NVCx2NvIH/LzxyzvoM4pJVLL483HXtnq8BF8hhBA9\nQpk1mMyUmdL+3Ywaam+2sz/g540tb7OjZiv+2lSmpFxInL713rkEXyGEED1CidVJcrwRszG2M6YW\nU/QJV76Aj9d/mc/Gss2kkINnxwkMTE9p83kSfIUQQnR7Pn+AihoXmTFOtoKGw86RJVx5Az5e3TyP\nTeVbOCp1GDk1p0NA3+YyI5DgK4QQogeoqHahKJAd42QriG7Y2ev38srmN/mlYhuj0o7ixrFXUVrh\nxWTQkZpoavP5ku0shBCi2wttJdgRPd8Is52dPievbp7HDutuRqeP4LoxV6DT6imxOshJt6DRaNo8\nhwRfIYQQ3V5HrfEF0Ou0GA3asIKv1VXF/216gyL7YcZmHM3VYy7HoNVTXuXE6wuENeQMEnyFEEL0\nACV1mc5ZKbFdZqSymPRtFtk4VFvE/216g2pPDZP7T+SSo85HqwnO3oa7oYJKgq8QQohuryO2Emwo\n3mygyuZu8fFtFTt57Zd5uPxuZg77H84YOLnR8HKopnO6BF8hhBC9RGmVk3iznoQ4Q4ecP86sp6jC\njqIoTeZs1xSt550dH6LVaLlmzO85Pmtsk+erPd+ctNZ3M1JJ8BVCCNGtBQIKZVVOBmQmdNg1LCY9\nigIuj5+4ugQsRVH4dN+XfL5/GfF6C9ePvZKhKYObfX5oK0EZdhZCCNEbWGvd+PxKhw05A8Sb6zOe\n40x6fAEfb21fwPeHN5BhTuOmY68h25LZ4vMPVzpITTRhMurCup4EXyGEEN1aaQdtJdiQWuXK4faR\nWLeGd1vlTgYn5XHD2CtJNLbc63Z7/Fhr3YwalBr29ST4CiGE6NZKOzjTGYJzvgDVDgcfFb7NDutu\nxqSP5Joxv8eoM7b63MMRJltBmMF35syZJCQEo/6AAQO44YYbuPPOO9FoNAwfPpz77rsPrVaKZQkh\nhIi9zuj5xpv1oPXx0aH3OOw5yK/q1vDqtW2HyUiXGUEYwdftdqMoCvPmzQv97IYbbuCWW27hxBNP\nZM6cOSxbtowzzzwz7IsKIYQQ4erIAhsqgzGAccSPHPZYOTbzGK4++nfotOHN39ZnOocffNvsrm7f\nvh2n08nVV1/NFVdcwcaNG9myZQsTJkwAYPLkyaxZsybsCwohhBCRKLM6MRq0JMe3PvwbLafPyUrb\nInSJVvrrh0cUeAGKK+xAjHu+ZrOZa665hksuuYT9+/fzxz/+sdE6qPj4eGpra9u8UGZmYtiNErEj\n971ryH3vGnLfu0ZH3ndFUSirdpKbkUBWVlLMz2/3OPjHt/+i1FOErzyHE4aeQ7/strcEbKi8xo1R\nr2XE0Ey02rbrOkMYwTc/P59Bgwah0WjIz88nJSWFLVu21Dfcbicpqe0bUlbWdoAWsZWZmSj3vQvI\nfe8act+7Rkff9xq7B6fbT2qCMebXsXsdvLDxVQpqCxmTPJb13+dQkeaM6DqKolBYaiMrNY6KCluj\nx1r7UtJGUDWdAAAgAElEQVTmsPOCBQt47LHHACgpKcFms3HKKaewbt06AFasWMG4cePCbqgQQggR\nLnW+Nzs1tpnONq+d5356hYLaQk7OGc+FQ2YCGpxh7myksta6cXv99EsPr7KVqs2e78UXX8xdd93F\nZZddhkaj4ZFHHiE1NZXZs2fz9NNPM2TIEM4+++yILiqEEEKEo7QqmMwU660Ev9z/NYdsRZySeyKX\njpiJ0+0HwB5h8I0m0xnCCL5Go5Gnnnqqyc/nz58f0YWEEEKISHVUpvMvFdsw6oyhnYniTBo0BIts\nRCKaTGcIY9hZCCGE6Cqh4JsSu+Bb7qygxFHGiNRhGOrW8Wo1GswmfVh7+jYUqukcQYENkOArhBCi\nGyutcqLTakhLMsXsnFsqdgBwdPqIRj8PZ0/fI0U77CzBVwghRLdVanWSkRKHLoZVFLdWbAdgdNrI\nRj+3mKPo+VY6SI43hnZCCpcEXyGEEN2Sw+XF5vTGdMjZ6/eyw7qHfvHZpMc13ggh3qzH5fHjDwTC\nOpfH66ei2hVxrxck+AohhOimOqKm866qvXgDXo5OG9HkMbX3qmY+t9k+qxOFyOd7QYKvEEKIbqoj\nkq22huZ7RzZ5zBLa0ze8ed/iKOd7QYKvEEKIbqojlhltqdyOSWdkaMrgJo/Fm+v39A3H4ShqOqsk\n+AohhOiWYj3sXOaooNRRzojU4c1uFWgxqT3fMIOvusZXhp2FEEL0FqVWJxogIzk2wXdLZTDL+cgl\nRqo4c+TBV6/TRNU+Cb5CCCG6pbIqJ2lJJgz62ISq1uZ7oUHPN4xhZ0VROFzpICvVEvZORg1J8BVC\nCNHtuD1+rLVusmK0oYLH72WndTc58dmkmpvfMjA05xtGz1fdbSma+V6Q4CuEEKIbKqpLZsqNcLeg\nlgSXGPkY3cKQM9RnO9vDyHaOtrKVSoKvEEKIbqewLBh8+2fGJviqVa3GtDDkDJENO7dnmRFI8BVC\nCNENFZYHN6bPzYhN8N1SEVxiNCR5cIvHqD3fcPb0jXZDBZUEXyGEEN1OYXnser6ljnLKnBWMbGGJ\nkSpUZCOMnq8MOwshhOh1isrtpCQYQ0lQ7dFWlrPKZNCh1WjCmvMtKreTEGcgIS669knwFUII0a04\nXD4qa9z0z0yIyfm2qLsYtZJsBaDRaMLa2ajG4aG82sXgnMSo2yTBVwghRLeiZjr3j8F8r8fvZVfV\nHnLj+7W4xKghi1nf5rDz3qIaAIbmJkfdLgm+QgghupXCsmCyVSyC766qPXgDvjaHnFUWU9s9371F\n1QAMzU2Kul0SfIUQQnQrarJVbgySrcIdclZZzHq8vgBeX8vbCu4pDPZ88yX4CiGE6C3UNb6xKLCx\npWIHZp2Joa0sMWrIEtrZqPngGwgo7CuuISfd0q5kMAm+QgghupWicjvpSebQ5vbRKnWUUe6sYGTa\ncHRaXVjPqd/ZqPmM5+IKOy6PnyE50fd6QYKvEEKIbsTm9FJt98Rkfe+WuiVG4Q45Q4O1vi3M++6p\nS7Ya0j/6ZCuQ4CuEEKIbiWWyVWi+Ny384BvfRqGNWCRbgQRfIYQQ3UiRmmzVzuDr8XvYVbWX/gk5\nYS0xUtUPO7fc8zUatO3umUvwFUII0W0cqgu+A9pZYGNrxQ58AV9EvV6AOHPLc75Ot4+iMjv5/ZLQ\nadsXPiX4CiGE6DaKyuxoiH7DAoCAEuDTfV+hQcOEfsdH9FyLSc12btrz3V9cgwIM6d++IWeQ4CuE\nEKKbUBSFwnI7malxmAzhZSc3Z/3hnyiyH2ZCv+PJTegX0XPjW0m42hODylYqCb5CCCG6hRqHF5vT\n265kK6/fy5K9/0Wv1TN9yFkRP1/NdrY3E3zVspJD2plsBRJ8hRBCdBNqpnN7kq1WFq7F6q7itP4n\nk2ZOjfj5oYSrI4adFUVhT1E16UkmUhJMUbdP1b4VzEKImPpoxV5W/FzU6jGn/SqXC04d0kktEn1Z\nqdXBy4u3cNW5oxiQFZsdhlrT3j18nT4nX+xfTpzezFmDp0R1DrXn6zwi4aqs2kWtw8v4kVlRnfdI\n0vMVohtZv72UWrsXs0HX7P/sTh/f/FSIoihd3VTRB/y4o4x9xbX8tLu8U66nLjPqnxFdoP/qwLfY\nfQ7OyptCgiG6AG7Q6zDotU16vnsLY7O+VyU9XyG6EYfLS2ZqHI9ed1Kzj7+46BfWby+lvNpFZkpc\nJ7dO9DUFpcFh4PIqZ6dcr7DMjlajoV9a5JnOVe5qlh9cSbIxidMHntKudlhM+iZzvrGqbKWSnq8Q\n3YSiKNhdvlC2ZXPURI89dVV2hOhIBSW1AJRXuzr8Wmqmc3ZaHAZ95KHps31L8Qa8/M+QMzHqjO1q\ni8XcdFvBvUU16LQaBmXHZvhdgq8Q3YTHG8AfUEJzTs1RlzjsrdvSTIiO4vb4OVzhAKC8uuN7vtZa\nN063L6pM58P2UtYWryfbksVJ/ca1uy0Wsx6n2xea3vH6/BSU1JKXnYBBH/0SqIYk+ArRTdjrEjxa\n26YsLzsBnVYTGgIToqMcLLOhZhZU1rgJBDo2z6A9ZSWX7P2CgBLg/KHnhL17UWssJgP+gILbG9xW\n8ECJDX9AYUgM1veqJPgK0U2ow1yt9XyNBh152QkUlNS2utm3EO2lDjnrdVr8AQVrrbtDr3eoTM10\njmxYd1/1ATaW/UJ+0iDGZhwdk7YcubNRrJOtQIKvEN1Gfc+39TzIIbnJ+AMKBSW2zmiW6KPU4Hv0\n4OBa2Y4eeq7PdA6/56soCh/t/gyAC4ZNQ6PRxKQtliN2Nop1shVI8BWi2wj1fE0tDztD/bdvGXoW\nHelAiQ29TssxQ9OBjk+6Kiy3odNqyEoNP4t/S8V29lTv45iMUQxLyY9ZW47c2WhvUTWJFgOZyeaY\nXUOCrxDdhLq0oc2eb923772S8Sw6iM8foLDMTv/MeLJTg8t+yjpwuVFAUSgqd5CTbkGvCy8sBZQA\nH+/5HA0azhtybkzb03DYucrmpqLGzdDc5Jj1rEGCrxDdhrqFmaWVhCuAzGQzCXEG9kjGc0hljYv5\nn2/D5w90dVN6hcMVDnz+AIOyE8hICfb2OrLnW1ntwu31R5RstaVie9SbJ7SlvsSkN1TPOT+G870g\nwVeIbiPcnq9Go2FobhIVNS6qbB2bBNNTfP1TIe8t3cn2AmtXN6VXOFA335uXnUh6khkNHRt8D5VH\nnmy1qnAdAFMHnhrz9qgrDhwuX2hNfSyTrUCCrxDdRjjZzqr6oWfp/QJU1AWGWkfTDdBF5NRkvrzs\nRPQ6LSmJpg5NuIo02crqqmJLxXYGJQ1kQGJuzNsT12DYeW9hDRogP6cLgm9FRQWnnXYae/bs4cCB\nA1x22WX87ne/47777iMQkGEeIWLB7m57na9qqFS6aqSiJhh87U4JvrFQUFKLBhhY1xPNTDZjrXV3\n2LC+uptRuBsqrClej4LCpNwTO6Q96rBzrdPLvsM15GbGE2eKbTXmNoOv1+tlzpw5mM3Bcf9HH32U\nW265hbfffhtFUVi2bFlMGyREXxVJzzc/JwkNsE96vkBwzhfAJsG33RRFoaDURr90CyZjsGBFenIc\nilJ/n2OtsNyOQa8lM7ntTOeAEmBN0feYdSaOz/pVh7RHnfrZdagKjzcQ8yFnCCP4Pv7441x66aVk\nZQW3UdqyZQsTJkwAYPLkyaxZsybmjRKiL7K7vGg1GszGtiv0xJn05GbGs6+4Fn8fH33yBwJYaz1A\n8xugi8iUVbtwun0MbLCFYGZd0lVZB8z7BgIKxRXBTGettu1s4q0VO6hyVzOu33GY9e3fV7c5atKj\nOvwey8pWqla/Yi9cuJC0tDROPfVUXnnlFSD4rUhNt46Pj6e2tjasC2VmJrazqSIact+7RjT33e0N\nkGAxkJUV3rfs0fnpfPV9AU4/5Gf33d9zmdVJoK4Gry8g7/n22lkc/EwfPSQjdC/zB6QA4PY3f3/b\nc8+Lymx4fQGGDkgJ6zzrt/8IwIyjp5KZ2jG/67QjhtfHHZ0T8/dVq8H3ww8/RKPRsHbtWrZt28Yd\nd9xBZWVl6HG73U5SUngfFGVl4QVpETuZmYly37tAtPe9xu4hzqgL+7n904PrL3/4pZgEQ9/Nndx1\nqCr03xVVDnnPt9Mvu8oASE8whu6lqa5Huu+QlbKytEbHt/dz5ucddddLNLV5nip3NT8WbSYvcQAJ\nvpQO/V2bjDrcHj9mow6zNroY1lrAbvUv9q233mL+/PnMmzePUaNG8fjjjzN58mTWrQumeK9YsYJx\n49q/g4QQfZ2iKDhc3jbX+DYk2wsGVTSYh1RLdIroFYSWGdUPO6trfSs6YNi5qLwu2SqMTOe1RR2b\naNWQOu+bn5MU1nB4pCL+unzHHXfw/PPP89vf/hav18vZZ58d80YJ0dd4fAF8fqXNNb4N5abHYzbq\n+vxyo8qa+rXOknDVfgUltaQmmki01O+Jm5poQqvRUNYBy40Kw1xmFFACrC76HpPOyAnZHZNo1ZCa\n8Ty0f+yTraCNYeeG5s2bF/rv+fPnd0hjhOirIsl0Vmm1GvJzkth2wBpxr7k3UXu+ep0Gm1MSrtqj\nxu6hyubh2GEZjX6u02pJSzJ1SKGNwnI7JqOOtDbqJm+r3InVXcUpuSdi1seuxnJL1ODbEclWIEU2\nhOgWwtnLtznqt/K9xX2391tZFxDyspNwun19Pvu7PdQh54aZzqqMZDPVNg8eb+y2svT5AxyucJCb\nHo+2jbrJq+sqWnXGkDNAerIZvU4bmt6JNQm+QnQD0fR8of5b+d4+XOe5osaF2agjuy4BTZYbRa9h\nWckjZaQE1+BWxHCtb4nViT+gtFlco8pdzeaKbQxM7E9e0oCYXb81v506nNl/GEdSg+H3WJLgK0Q3\nEG3Pd4hsL0hFjZv0JDNJ8cEPSalyFT11Xeug7KY9X3U7vVgOPYdbVvK74h8IKAFO6aReL0BSvLHZ\nEYBYkeArRDcQbc83yWIkM8XM3qJqlLq1rn2Jw+XD6faRlmQOJQjZZd43agUltcSb9aQ3M/+aUVd9\nqjyGWwuGykq2EnzVRCujzsi47GNjdu2uJsFXiG4g3B2NmjM0Nxm7y0eJteMK33dXlbXBXlh6cn3w\nlYzn6DjdPkqtTgZmJTS7b21HbC1YGMZuRtsrd1HpsjIu61jiOiHRqrNI8BWiGwh3L9/mhIaeC/ve\nel+11nB6kolES/DeyVrf6Bwqs6HQ/Hwv1Pd8Y1lisrDMTpxJT0pCy/Oqq4vqEq36d96Qc2eQ4CtE\nN9Cunq+6vWAfzHiuqFvjm5ZkJjFeer7tUT/f23zwTU4wotdpYjbs7PL4KKl0kNdCTxug2l3Dz+Vb\nGZCQS15i5yRadRYJvkJ0A/U938iD78CsBPQ6bZ/MeK7v+TaY85Web1TUTOeBzSRbAWg1GtKTzDEb\ndj5Uakdp5XrQONGqpQDdU0nwFaIbqO/5Rj7srNdpGdQvgYOlNtwxXIPZE6jLXtIaDDtLoY3oFJTU\nYtBryalbstWcjJQ4bE4vLk/773FBaTDYt9TTDiVaaQ2M79d7Eq1UEnyF6AYcLl/Y2wk2Z2huMgFF\n4cDh6AvNK4rSYZuld5TKahcaDaQkmPrssHMgoLS7sIjPH6CwzM6AzHh02pbDQiyXGxW0sqYY4Oey\nLVS4KhmXfRxx+rb3+e1pJPgK0Q3YXV4sZn3UQ2ux2GRh/fZSbnzqWw5XOqI+R2erqHGTkmBCr9OS\nENc31/k+/+HPPDp/Q7vOUVRuxx9QWgyEKnUJUnlV+4PvgRIbel3zPW1FUVha8C0AZ+RNbve1uiMJ\nvkJ0Aw6XL6r5XtXQGFS62n2oGn9ACfVIurtAQMFaGyywAWDQazEbdX0u+O4urGZvUU27hoLVZKu2\ngm9mXZWr8nZusBDsadvonxmPXtc0DO2p3s++mgKOyRhNv/isdl2ru5LgK0Q3YHf5osp0VqUlmUhO\nMLar52utDWYO95Rh2yqbm4CikJZkCv0sIc6ArQ8lXLm9/lC+QEll9AGxuW0Em5Meo2Hn4goHPr/S\nbCUtINTr/XXeae26TncmwVeILubx+vH5A+3alUij0TA0N5kqmyeUARypyrrgW+voGcFL3UpQ7flC\nMGGtL1W4qqqt306xuNIe9XkKSmrRaGBAK8UuADLVtb7tXG7U2nzvYXsJm8u3kp+Ux9Dkwe26Tncm\nwVeILtaeNb4NDa2b9412f19rXbUoWw8JvuU1wQCQ1iD4JsTpcXv9eH09K3EsWpUNgu/hiujm6gOK\nQkGpjX5pFkyG1hP+Ei0GjAYtFe3s+YY2cMhqGnyXFawA4NeDTu91y4sakuArup0t+yv56/+tptTa\ncxJ/2qM91a0aak/Slc8foNrmAaDW6WlXO5qzZX8ld728lsfe2kBxRfQ9tIaa7fnG9a0qV+oXJiDq\nRLmyKicuj7/FJT8NaTQaMpLj2l3lqqDEhgYYkNW4pnO1u4bvD28gKy6DsRmj23WN7k6Cr+h2ftpZ\nRmWNmy37Kru6KZ0iVj1ftT5uaRQ1nmvsHtRtGWI57OxwefnXZ9t46t2NlFqd7DxYxX1vrOez7w60\ne3lMwzW+KjX49pR56/ayNuz5Rhl8w022UmUkm3G6faEvjZFSFIWDpbVkp1kwGxu/5785tBqf4mdq\n3mS0mt4dntr31y5EBygsC/aMDpXHpofU3UW7o9GR4s16jAZtqEcYiYbDl7EKvht3lfOf/26nyuZh\nYFYCV08bRVmVk/lf7WTBN3tYv72Uq6eNinrbtsrq+k0VVAl1owd9JeNZ/b3pdVpKKp0oihLxUG24\nyVaqjLr7XVblYlC/yEdryqpdON1+jhnS+Houn4uVhWtJMMRzYr8TIj5vTyPBV3QriqKEdjopKusb\nwTfavXyPpKkr/xfNZucNe1DtHXaudXh4Z+kuvttagk6rYeap+Zx70qC6SlyJjByUyrvLdrHml8M8\n+O/1/M/EQUw/eXCzS05aU1HjxmzUYTHVf4zV93z7RtKVte6L1vAByWw7YMVa6240Bx6OA20UuzhS\naGvBaieD+oX3nIYKDjdf2WpN0fc4fS6m55+NUde+v4WeQIKv6FZqHN7QkGFhuT2qb/I9Tajna2r/\nn2NakpniCgdujx9TBNWyrA0Cts3hjeq+K4rC+u2lvPXVTmodXvJzkrh62sgm28UlxBm4dvpoJozK\n4s0vdrB49X5+3FnG1dNGkZ+TFPb1KmtcpCeZG7UzIS54D/vOnK8bo17L0P7B4Hu40hFx8D1YYiM9\nyURCXHgBL6Ody43UspINg70/4Gf5wVUYtQZOHXBSVOftaXr3oLrocYrqNteG4LxdTQ/JvG2P+p5v\n+4Nvet38Z2VtZB+MVluwB5VkMeAPKDjdkdeIXrhiLy99vAWXx89vpgzjnlkntLpP69ihGTx87Ymc\nfmwuhWV2Hv7PD3y/rSSsazndPhxuX5NAk9DX5nxtblITTeSkBatERTrvW21zU233MLCZrOOWhApt\nRFnlSp1jbrihwo+lm7C6q5iYO4EEQ3xLT+1VJPiKbkWd51W/XRc2CMa9Vf2cb/uH2tRgFOnQszrs\nrPZGohl6Xre1BItJz4NXT+CcE/PQatvuOceZ9Fxxzkj+eumxKAqs3FQU1rUa7uPbUHwfmvP1+QPU\n2D2kJproV1eisTjC5UYHQslW4c+7Z6SoPd/o1voeKKklNdFEUt0uVGopSQ0apg48Napz9kQSfEW3\nUlQXfCeMygYIzf/2ZrHKdob6ZTeRJl1V1rrRajTkZgR7HdGs9a1xeMhIMZOd1vKuOC0ZPTiN7DQL\ne4trCChKm8c33Me3ob7U81ULbKQmmugXZc9XTbYKZ5mRymLSE2fSRTXsXG33UG3zkNcgyW575S4K\nbcUcnzWWjLi0iM/ZU0nwFd1KYbkdrUbDCSMygfpg3JvFap0vNOj5RvjBaK1xk5JoJDkh2BuJNOPZ\n5fHh8QZIqttZKBpDc5Nwuv1hFYtouI9vQ/XrfHt/wlVlKPiaiTPpSY43Rlxoo62dhZqjrvUtr3ah\nhPFFqa3rhUpJDuq9pSSbI8FXdBuKolBYZic7LY4BmQloNZrQsqPezO72odGA2RTddoINheZ8Ixh2\nDigKVTY3qQn1STeRDjvX2IPHJ1vaF3whvCIhza3xhWCvTEPf6PlaG/R8AfqlWaisceGJYE/nghIb\n8WZ9k/vYloxkM26vn9oI7/ORwfdgbSHbrbs4KnUYeYkDIjpXT9eng6/b4+eNz7bFrOKOaJ8qmwen\n20duRjwGvZbstLhQxnNv5nD5sJj0aGOQ1Z2aGPmcb63dgz+gkJpoIrEueEY67FxjDx7fnp7vEHVn\npjDKY7bU89VqNVjM+j4x56sG3zQ1+KZbUICSMIusOFw+Squc5GUnRpzZHlpuFGbSlcfvocRRxtby\nXejSCzmgbOC9HR/x5tZ3gd69gUJL+vRSo60HKln1czHJ8UYuOm1oVzenz1OTq/rXzTv2z4inuMIR\n1drFnsTu8rZ7ja/KoNeSnGCMaM634fBlQt28c6Q9muq6nm97gu+ArHiMei17wtgWsaLGjQZISWza\nY4vvIzsbqRntqUn1PV8IzvuGU7jkUN3fWyTzvar65UYtB3pvwMei3Z/y/eENOHx1x8WDcSgsa5BX\nNzxlCKPTjoq4DT1dnw6+6lCZ+v+ia6nJVerylNyMeNhRRlG5vVcHX4fLR2pGZMN+rUlPMlNQUktA\nUcLqTYe2EjTv49ldr2MaE88W717WFlnJT84jy5LZZqm/Gkf7g69Oq2Vwv0R2FVbjdPuIa2Xdc0W1\ni5REU7OFORLiDFTWuHr9GnFrgy9NQGhT+sNhjuQdiLCyVUP1Gc/N93zLnZW8/ss8CmoLSTElMyhp\nIIn6RFb/VEV2QhqXTj6GFFMyqaZk4vRxvfr31BIJvkjw7S7U+V0141YNwofK7IwZkt5l7epIXl9w\nB55YZDqr0pLM7C2qodbuITmh7aBurXWDxs8O33do0KAx2SnX7WT+9p0AxOnNDEocSH5yHiPTjmJY\nSn6Tc9TEoOcLMKR/MjsPVbP/cC2jBqU2e0wgoGCtdZOf23yPLSHOgM+v4PEGIio00tNYa93otBoS\nLcFRk0gzntX514FR9HwzQ1WumgbfzeVbeXPrezh9Tk7KGcdvj7oAo87IzoNVfFu4gaPHD+To9OER\nX7O36ePBNzg0pX5rF12rsNyOTqshOzX4h60OP/fmjGd7DNf4qtSkq/IaV1jBt7LWhS7rIM6AjV/n\nncZnH5nJHRDgjFMT2F9TwL6aA2y37mK7dRef71/GuYN/zf/kn9motxKLhCtouC1idYvBt8rmJqAo\nTeZ7VeoXGZvT2+uDb2qiKTS6kZEch16niSD42jDqtaECHZFQ62mXN9jX1x/ws2Tvf/mq4BsMWj2X\nj7yEk3PHN7he9D3t3qhPB99qR8/t+fr8AT5Zs5/Tju0fynbsyQKKQlG5nX7pltBQYlZqHDqthsLy\n3ltoI5ZrfFVpDdb6Ds1t+/iKWjuGnL0YtUbOzDudlXE/4arWMnnARCYzEQCb186+6gMs2LmYz/cv\npdJl5XcjL0KvDbY7Zj3fuqSr1uZ9K1tY46tquLNRw00Xuqvyaierfi6OqL61PxCgyuZmWP/k0M+0\nWg1ZqRYOVzraHHL3+gIUldsZ1C+x1WIoNo+d/x5YTpo5lfzkPAYk5KLX6okz6UmIM4S2Fqx21/DG\nlrfYXbWPzLh0rh0ziwGJjd98ke6e1Nv16eCrfmBU26OrZduVtuyrZPHq/dQ6vMw6e0RXN6fdKqtd\nuL3+UG8Xgju15KRbKCp3hD1/2dPEco2vKj3Ctb4H/VvQxHs4fcAUEozxJMQZqahpnEiTYIjnmIzR\nDE7K48Wf/8W6wz9idVdz3TGziNPHUe3woNEQdn3glqQmmkhLMrG3uKbFv8mKFjKdQ20196w9fRd8\ns4fvt5UyOCeJY4dlhPWcapsHRaHJF+9+aRaKyu1U2z2ktDLqUVRuxx9Q2gyE7+xYyMayzaF/67V6\nBib0Jz85j/gcLxVFcWw+vJ1n1r9OrcfGsZnH8PtRFxOnj2tyroKSWgx6bWhuuq/r00uN1ODr8wei\nqmXbldS2b9xd3iuW4oSSrTIa13XNzYjH7fWHto/rbTqi51tf5arte+byuam2bAW/PlTkINFiwOkO\nzkUfKdGYwC3HXc+vMo5mp3U3T//4IlZXFTV2D4kWY1glJdsyJCeJGrunxS8PLS0zUjW3p6+iKASU\n9u0f3BFsTi8bdpYBRFQgo36ZUeN7EJr3beNc4SRbbSj9mY1lmxmSPJgrRv2Wyf0nkhOfzYHagyw/\nuJKajO8wjP2ah759FrvXwUXDZ3DtmN83G3h9/gCF5XYGZMaj0/bpsBMiPV/1vx2edu+n2pnUDxZr\nrZuCEltUW3t1J0dmOqv6ZybAtlIOldvJSGn6R93T1fd8YznsHOzxhLPW99tDq1H0HuKrRhNvCH5w\nqwk8Nqe32SkNo87ItcfM4sNdS/jm0Gr+/sML1ATGkmHpF5P2D8lN5ocdZewpqmn2d95SgQ1VQpwB\ntD721uylcv8v7KsuYH9NARqNhrvG30qyqfv8razbWoLPH/zyfLgy/NyGIwtsqBomXY1sYc4c2i4r\nafPaeX/HIgxaPb8fdQnZlkxOzAnusevxeyioLeTjDRvYVbmfoYMsXHTUuQxJHtzi9cLtafclffYr\niNcXwOGuL0HX0+Z9G5b/+2lXWRe2JDbUTOcje769Pemqvucbu2HnhDgDRr22zbW+Tp+LpQXfovgM\n5CpjQj9PjFNLTLb8N6HVaLnkqPO5aPgMajy1MGwthtTYvA+H9m+90pX6uhrO59o8dpbvXc1b2xbw\nScWbmE9Yykr7RyzZ+19+qdgWfD0eG0v2fhGTNsbKqp+L0Wo0aIiu59sk+KaHl/FcUGpDq9EwILP5\nHYQW7FxCrdfG/+SfRbYls9FjRp2RYSn5HJdyIp7dxzEt+7JWAy9EvmdwX9BzunoxduQHS88LvvXt\n3bZ+mm4AACAASURBVLi7nAtOHdKFrWm/wnIbBr02tF2ZSg2+vXV3o/odjWL3p6jRaEhLMrfZ8/3m\n4GocPie+4uFkNthHV+35hlNoY+rAU9H7LLy75wMOJ69gVWE6k/q3bz/WQdmJ6LSaFitdVdS4MBl1\nWEx6imyH+ebQKr4/vAFvIHgvDRoDgdo0BiUOZNrYXzE4KY8EQzyPrX+W74p/YPKAid2ilGFBSS0H\nSmo5dlgGheW2iDZFCKfn25KAonCw1EZOhgWDvmk2+C/l21hfsoG8xAGt7jKkVrkqsTo4Oi+l1fYW\nRLF7Um/XZ3u+akUe9c1b3dOCb90H49D+SRSU2CKq5dvdBAIKxRUOctItTeYMM1PiMOi1vXZ3o/q9\nfGPX84XgciOb04u7hTq/Dq+TZQdXYNLG4SsZREpifZZygjrsHGaJyf6mYXi2j0evMfLOjoXM3/YB\nHn/0yU5Gg46BWQkUlNQ2O+9cUeMkKdvKCxtfY+73T7O66HuSjUnM+tVF3D3hVu489i482yeQ5TyO\nX2WOIdmUhE6r46LhM1BQWLBzSbfIk1i1uRiASWNz6JcWT43DG5qGaEuoutURwTchzkCixdBqL7rU\n6sTt8TfaWUjl9Dl5Z8dCdBodvx91CTpty0u11CpXJWH02AtKatFoYEAr+zv3NX02+Ko9XfXN0PN6\nvl70Og0njQ7Os/20q7yLWxS9sionXl+gyZAzBJdP5KRbKK5wEAh0/QdmrHVEzxcaLjdq/kvZ8oMr\ncfqcHGU6HgL6Rok7an3n1oadG6qxewjYUpkc9xsGJvZnbfF6nvzxBUod0Q9DD81NxudXQnOTEEwO\n+2r/SvxHfY0tZ02wIH/KUK475g/cN/F2Zoz8Nf0Tcki2BF/LkZsrjEwbztiMo9lTvY+fGmTwdgWv\nL8B3W0pIshgYOzQ91GMtDrP3a611o9EQ2oWqoX5pFsqqnc1+cYHWdzL6aPenVLmrOWfwVPon5LTa\nhlDwbaPNAUWhoNRGvzQLJkPvXXcdKQm+WcEP/J5WaMPmDGaXHjc8uDRh4+6eG3xbSrZS9c9IwOsL\nUFYV3ebd3ZmjA7KdofV9fe1eB18fXEmiIYF0z0igcQ8q0j1x1b+lfgkZ/L/jb2JS/5MotBXz+Prn\n+Kk0uiA3pL9abKMGj9/DF/uXc++auSzauwSN0UmGfzh3jb+F/z3+en6VeXSj8pdmow6dVtNsfeeZ\nw6ah0+j4aPen7eqdt9em3eXYnF4mjumHXqetn6sNc97XWusmJcHUbOZwvzQLigKlLfy9tDT/ur1y\nF6uLvic3vh9nDZrSZhuMBh1J8UZKra23uayupx1NDenerO8G37pgO7AH93wT4gykJZnJy05g+wEr\nTnfP3MNUDb65zfR8AfrXJYX0xqFnu8uLBjC3Usc4GqF9fZvp+S4t+BaX381Zg06nxhYclk5tkDkc\nmvMNc9g5VN0q3ohBZ+CyERfyh9GXElACvPbLPBbsWowvENl7c0huEqCwvvQH7l/7BEv2foFWo2Vc\nyiRcG09nXPyZTYo4qDQaDfFmPXZn02tmWTI5feApVLqsLD+4MqI2xdLKn+uGnI8J9i4jKQ0ZUJRQ\ndavmtBXIm5t/dfs9vL39Q7QaLbNG/SZUPKUtmclmyqzOVkelJNmqeX02+KpzvP3SLei0mh4VfL2+\nAC6PP/QhedzwTPwBhV/2VXZxy6KjJlMNaCn4dnLS1YHDtWHPvbWXw+XDYo7NdoINtbSvb63HxjeH\nVpNsTGRS/4n1iTsNCjIkxoWfcAXNbyc4od/x3D7+L2Rbsvj64Cqe2fAyVldVWOdTFIUy/wHixq6h\nMG4tDp+DswZN4YGJd5CvOQF8ptDra0l8nKHFnvu5g88gwRDPfw8sp8rd9t7BsWatdfPLvgryc5JC\noz2RBN9ahze0BWRz6s/V9MuqogSH8jOSzY3yDJbs+YIKVyVnDJxMXlL4yWgZKXH462ptt+RgqSRb\nNafPBt/6b+smEi2GHpVwpX6oqMODalWcjT10yVFRuR2TQUdaC6UAQ8G3E3q+lTUuHnrzBz5asa/D\nrwXBnm9HrC9Xl+EcWahiacG3ePwezho8FaPOgLXWHVya1GAuLlSkIsypmOoWdjTKic/m9nF/Zlz2\nseyrOcCj65/hywNf82PJJvZW76fSZcUfaJwQdqDmIM/+9DIv/vwvMNnwlfXntrG3cP7Qc4nTx7VZ\n3UqVEGfA7vISaCaxKk4fx4whZ+Pxe1i8p/OXHq35pRhFgVPH1s+ppiQYMRl1YQVfawvJVqrWAnmV\nzUOtw9uoF7qnaj/fHFpNtiWTaflnRvRa1GpVL378S4t/n9LzbV6fXWqkBt9Ei4GkeGNEaf5dTU2E\nURNj8rITSE008fOeCnz+QNj1YbsDnz9AcYWDvOzEFnt/aclmTEZdpwTfEqszWGc6zG3Z2svh8pHT\nQo+/PdRt5hoOOx+oOci3h9aQYkrmlJwJKIpCZY2brNTGy7v0Oi3xZn1Ew84a6oerGzLrTVw5+jKG\nJufz4a7FfLzn80aPa9CQaEwgxZSMSWdkV9VeAMakjyS5ZixL99VQUa4hLy14fGWowEbrwTfebEBR\nwOX2NVu68+TcCawoXMu6wz9y2oCTGZQ0MKzX2l6KorDy52IMei0TRmWHfq7RaOiXZqGwzE4goLRa\nKez/t3fe8ZHV9d5/n+ktM+k9u9mU7Z1tsMtSpYorinoBsaCAXKVcrzyiolyvvB4erxe9KhexUBRE\nucBVUOkILOzKAgvbsj3ZTTa9ZyYzmX6ePyZnMkmmJ5mU/b3/guzMnN85M+d8f9/2+fbZo6tbKRRk\nhzTRo4Wdxw438AS8/P7wUwBcu/hT6NSpVd1/ZF0FvYNetn/YwvcfeZcrNi/g0o3zRj2DmjoGybPq\nJyw9OteYPU/pScbu8mE2aNCoVVjNOry+IG7v7MiZKuFAJTwoSRKra/Nxuv0cb858GG0idPYNEQjK\nUSudFVSSRGmemfYeF/7A1EoEKg/3ZNShJorPH8Q7yeMEFbQaFTazjl67h+6hXh6pe4L/eP/n+II+\nrqi6GK06JCHp8QWielAWozaFsLMXs1EbUzZQkiS2lp/J9zb9H25c8Tk+tXAbH5l3LuuL1lCTvQCd\nWkers51j/Q3MyyrntjU3cvOq61lVEepdr4/o9+2xe5CI7fVFrh9iF42pJBVX1V4BwNPHMtd6dKx5\ngM6+IdYtKhgX8SjJNeEPBBP+9npj9PgqaNQq8rON4QELkURWOvuDfn69/3d0uLo4t2Iz1dmVKZ+P\nUa/hjs+u45ZPrsBs1PKn7Q3c89v3w8fpH/Rgd3qpKBRe71gS3vWBQIC77rqLEydOIEkS3//+99Hr\n9dx5551IkkRtbS133303qlmm12l3esNhMmUMmt3pxaCb+cGAEc93ZCe5piaf1z9oYc/x7riycjON\nRMVWCmX5Zk602enoG4prqCeK8uDrtXumfJjDVAxViCQ7W6JN8yH//s5zBOQA87LK+Hj15SzKrQGg\nb1DxoMY/xLNMOrr67UldA7vTm9RkrTxjDnnG6L9NWZZxB9wY1IbwMIUFxVYkQuMFFXrtbmwWXcLo\njtkYuo8VBbFoLMypYVXBcvZ2HeCDzr2cUbQ64TlMlLfHFFpFEm436nGNE5uJJJbARiQluSb29Lpw\nDPmwRox5VIqtygtMPHbofzjUe5TleYu5svry1E8mgjW1BSyqyOaPfz/O2/va+MFv3+fSTfOYXxSq\nWhf53vEktJivv/46AH/84x+5/fbb+clPfsK9997L7bffzhNPPIEsy7z22mtTvtDJxB8IMjjkwzZs\nfBUjrBSOzHQU8YOsiJtq0bwcDDo1e47NrkEL4WKrGDJ3CkrF81TLTCqerz8QTDrsmi5TMVQBwBvw\n8XLj63SXPo+66CRWnZUvLr2aO9bdEja8ED93aDFqCcpywgp6RaZ1oqMEJUnCqDGOmmJkMmgoyTdz\nos1BMCgTHC7sSWZMYLLtUldWX45GUvOn489PeevRkMfPe4c7ybcZWBRlg5ysNKTyvUXbNI37rDGh\n58YOB2ajhtfaX+b9jj1U2Sr50vLPxhXTSBaTQcv1ly3h659ZRbZFz193NvLL5+qA2BrSpzMJje+F\nF17ID37wAwBaW1uxWq3U1dWxYcMGALZu3crOnTundpWTjPJQtY4xvrOl6EpZf2QORatRsbwqj87+\nIVpT0IidblLxfGHqK557Ivpikx3Jly6TLbARlIO80/Y+33/nP3i2/gVUqPA2LuZz829iXfGaUb2w\nMJI7zImSO0y23cgRo9hqsqgqteLxBWgZHpMXCMoJi60g+mSjaBSY8jiv4mz6PP282vTGZCw5Ju8f\n7sTjC7BlRUnUaEKyFc+K55sdz/hG+SyX20f3gBvbgka2t+yk1FzMzSu/gE49ud/d8gV5/PuXNnD+\n2rJwmmi2D36ZCpK66zUaDd/85jd55ZVX+NnPfsaOHTvCO1Sz2YzD4UjwCVBQMHMuvn14fGBRvoWC\ngizKi0OhEVklzah1xsI/7NjOK88etd6ta8t5/3Anx1rtrF4SUr6a6efT0TeE2aBhYVV+3HnKK4fT\nAd0Oz5SeU+QGzE/6v4dk3ndyeJhEYZ5lQuckyzJ72w/y+N4/0TTQglat5eNLLkbXW8tv3zsOKm3U\nz/cMp88XVGSP+/fCvNBmR6OL/l6F/uENRFG+eUq+l9WLCnl7Xxuddg8mc8jYlBdZYx5L+XtpYeie\nltTqhOu6NvtjvNv5Ac+feBWjScdVSy+bkjTarsOdSBJccU4NBbnjZ9pmDWsl9yb4jdtdPrItekqK\nbTFfs7gq1AFhH/KHP2v/8W7UhU30WQ5SYM7jexfcRq4xviZzskRb779cu45Lt1TRZ/ewqLogyrtO\nb5Lecv/whz/kG9/4Bp/+9KfxeEa8A6fTidVqjfPOEF1diQ10pmhsCfUbaqXhdQVDT6GWDseMWmcs\nuob793xu36j1VhaYUUkSO/a0cO7KEgoKsmb0+fj8QVq7nFSVWunuju/RyrKMUa/hRMvAlJ2TLMt0\nRngKJ5r7WFiaukFJ9rq3DRelyIFA2ufU5Gjmz8ef50jfcSQkNhWv46NVF5FjyGa3PdR6Fus8mttD\nhUxSIDju+EoQ8lRrP/mW2DnpxuYx99IkUzjs3e090knAFzL0Rq0q6rEir7vy2vau5O7pryz/Ar/a\n/zuervsbB1qP8oVlV5Olm7w8ZXuvi4MnellamYMU5/vOs+pparfH/HdZlunuH6Ikzxz3vAzDX2BD\nc3/4dS/U7UA7/yAGlYl/XnE9gUE1XYMT/87i/d7zTFryTNoZ/RyaSuJtohIa3z//+c90dHRw0003\nYTSGcjLLly9n165dbNy4ke3bt7Np08SmmGQapc0oWsHVbGAk7Dz667MYtdSW2zh6qp+Bwan1ECeD\n9l4XQVkO53PjIUkSZQVmGlrs+PxBtJrJ90wGh3x4/UFysvT0OTxTXvE8kaEK3UO9/KXhRd7v2APA\n0rxFfLz6slF6vHm2+HN94xXuJDvZaOy9NNmU5pvR69TUtw5Qkh/yFmPN8Y1EyaPHK7iKZJ61nDs3\n3MbvDj5JXc9h/t97P+VLy69NOCovWcKFVivj6yUX55qoOxlSqzNGUT1zuv3h36jC3068QkP/SSqt\nFVTa5lFpnUeW0YzZoAmHnQ/3HmP30MsQVHPtws9SaBKe6HST0PhedNFFfOtb3+Laa6/F7/fz7W9/\nm+rqar773e/y4x//mKqqKi6++OJMrHXSGPvAGCm4mh3Gd3Ao1CYVrbVjTW0+R071s7e+h5oF+dOw\nuuRpGfZ2E+V7FcryzRxvHqC910VFlIksE0XRQa4tt/Huoc6E83AnSjo530Gfk5dO/p3tzTvxywEq\nssq4MqKCOZLcOPrOECrcMerVUR/yIznf+PeEItNqmyLjq1JJVJVYOdTYR/OwUlIyOV+lHsKZZLsU\ngEVr5isrv8ArjW/wl4aX+MkHD3Jl9WWcV3E2MoBM3P7bWASCQXYcaMOk17C2Nr7RK841U3eyj44+\nF5XF4yOK4Q3T8AakZbCN50+8AsDhvmPh1+UbctHXWOjpNvNeu4EnjjyNDMgN61h9YXXK5yCYfBLe\n9SaTiZ/+9Kfj/v74449PyYIywYBz9APDYtQiSSNKPTMdh8uLxRT9Ybe6Np8//v04e45188kLF2V4\nZanRMpzzTLZ1KLLoaiqMr+Ihzi/O4sNj3RnwfFOrdg4EA/zo/fvpHuohz5DDx6ouYW3RqnGFVApZ\nRi1ajSqu5xut2AoiJxvFN14DU+z5Qqjo6lBjX3h4SCKBDUh9OISCSlJxceX5LLDN5+G63/PM8b9y\nfOAkDe9UUlWUx40fW5by+utO9DIw6OW8tWWjlMSiEVmlHN34jq50/tuw4f3ismswaYycsDdxcqCJ\nk/Ymhky9aObBowcPISHhq19NpalyStvnBMkz85tapwBlt670v6lUElkm3azwfIOyzOCQn8IoBRsA\nhTkmSvPNHDzZO+NFQ1oTTDMay1TLTEZKF+ZaDVM+IznVPt+DvUfoHuphXdFqPrvk02gTiN9LkkSu\n1RC1atvjDeB0+6ksiV6vkazxCkeRYmwGJ4PQkAUY8gTQa9VJbVZ0WjVajSoc2k+VhTnVfGv97TxS\n9wR7uw4QLGvg3eNruMpenZTxj2TsEIV4JKp4jhTYaHI0s7frAAus8zijcBWSJLE0L7ThDspBntq5\nl1cPHmD1Kg3Vtir+510nFWtFv+1MYXYpY0wSI2HnkYeedZYYX5fbT1CWw+pW0Vhdk4/XH2Tv0Zmt\n9dzS5cRi1GKNIksYjdJhI614zJNNb4TxzbPqcbh8eGMMo58MUvV8d7V/AMAFFVsTGl6FPKuewSEf\nnjHnoQhsxBJqSLbVaKpzvgBVpSNVvblWfdyq+EgscYYrJINNb+WW1TewxrYJlcGFbvG7vLTvYEqf\n4XB52XOsm/ICM5VJtNskMr6R7WFKuPnyqovGXROVpKImv4xATxlV8lkYh0LDEkS/7czhtDW+Rr0G\nrWYkBGQza3F7A1P6sJ0MoqlbjWX18IzfXXXtGVlTOnh8Abr6Q2pVyT5MrSYtFqN2yoQ2lB7f3GHP\nF0Y8janANTxOMFrOddxrfS72dx+k2FxERVZZ0scYyfuO9n777PGFGvRaNRq1Komc74hM61RhM+vC\ng9uTyfcqmA3aqGMFU0GtUlMpr8fbsBxJ42OH81l6hpKfHvZOXQeBoMyWlaVJ/c5zrHp0GlXMcYBK\nzndI3c3+7kNU2ypZnFMb9bVhQ97jijpGUDC9nLbGd+xOfbYUXY1MNIrtaVSVWrGatLx3sCPqVJeZ\nQFuPExkoTaLSWUGSJMryzXT1D43z5CaDXrsbtUrCZtGFH/JTmfd1Dle0JpOD+6BzH/6gn43Fa5Pe\nrMCIsRpbdJVIH1iSJLJMiT3HaPfSVFBdFvJ+Uwn5WowaXB4/geDE9MDbe10Eussx9S5H1g7xk/d/\nxaA38QYwNEShFbVKYtOyooSvh5COeXGuKdwJMBYl57uj600APlp1cczfQ2GOCUkKrb+pw4FaJVGW\nL4zvTOG0M77BoIxjyIdtjOcYVrma4UVXjrC0ZGzPVyVJrKrJp3/Qw4k2e8zXTSdK6DjWDN9YlBWY\nkQkZ78mmx+4m16pHJUnhdpbeKVS5Umb5JsO77R8gIbG+aE1Kx1DOY+wmon8wtrqVQpZJGzfsrMi0\nTmW+V0HJ+yaa4xuJonKVbLtRLJQQ8LWrL8PXVkmfr5cH9j6M2x//t9HY4aC5y8nqmvyUrlFxngmv\nPxgOMUfS6/BgyrVzuO8oC7OrWZgTu3JZq1FRYDPS1uPiVNcgJXnmKWnRE6THafdNOIZ8yPL4HNVs\n83zjGV+AJcPasQ0tM9P4tiYpKzmWkYrnyTW+Pn+QgUFv2FPMz4Tn6/Yl1ePb5eqhfuAki3JqyDGk\npkiUHyPsrHi+8fSBs4xaPL7YqZixMq1TycalRaxfXMiGpcl5kDDSP51Ku1E02ntd5GTpWVmdh82+\nimBPGY2OU/x6/2P4grEN+1tJ9vaOJV7et8/hQVN2HAjlehN+Vp4p1L/uCzJfhJxnFKed8Y1VIGKd\nJUIbSg4uXtgZRgZXK6O9ZhotKVY6Kyivn+yK5/CEn2FjlWuL3yM7UfyBIF5fMCnP992OUKHVhuK1\nKR9HOY+xm4hw4U4cT1JpN4oVes5EsZWC1aTj5o8vpygnepV/NEZ6fdP3fD3eAL12D8W5JlSSxNkr\nS/HUL6NUW8XhvmP87uAfCcrjw9o+f4BddR3YLDqWV+WmdMxYxnfI48er78Jn7GRxTi012QuS/iwQ\nw+xnGsL4DmObJZ5vMmFnCN10ep2axo6pHUSQLi1dTmxmXcoDthVPebKLrpTwctj4ZsVXh5ooyVY6\ny7LMu2270am0rCpYnvJxlPMYu4noc3jQaVWY4hR7Kd9NrNCzfYqHKkyUdHt9I+noCxlAxYhtXl6C\nhApOrqHaVskHnft46uiz4yaJfXC0G5fHz1nLi2POOY5FrIlEkV7vR5PweiPXDaLYaqYhjO8ws2Ws\nYNj4JjBaKpVEZYmVth4nPv/UDqBPlSGPnx67O+WQM4QeqDazbtKnG430+IaMlVajxmrWTZnxTbbH\nt2GgkW53L6sLV2DQJJ/vVIh1Hn0ONzmW+G07IxKT0TekdufUqltNlBGJyfTvacX7VIxYns3A0soc\n6lucXFnxGUrNxWxv+Ue47cftd9Pu7ODlQx+gzm9GLjzGHw4/w6N1f6DJ3pzUMRXvvr139AZzf+cR\n1NZe8qV5LLDNT+qzIo2vGGg/szjtRDbC6lam6MY3kwVXj798hDybgUs3JncjwciDMCuJAo6qMhtH\nGvto6R6MqpYzXbT2KCHn1I2v8r6DcfRv0yGyx1chz6rnVKczqYHyqZKs57urfTcAG4vPSPtYY8/D\n5w9id/kSbn4sCVSuMiGwMREmw/NVvE/FGwXYsrKUupN9vH+wj6+d+WXu2/0Az598lb+fegt3YDjC\nkAO6HHgzottvb9cBrl9+LSvyl8Y9plGvIduiGxV2lmWZnd3bAVhr3Zz0+pV1F2QbJm10pWByOP08\n3xihsiyTFonMhZ2bOhz8/YMWXv+gJaX3Dbp8aDUqdNrEX53SntE0w0LPqcpKjkXZzXf1D03amiJ7\nfBVyrQb8gWBCoYl0GPF8Yz8QfQEfH3TuI1tvi1vVmoix55FMpTOMRFcGY5x/JqQlJ8JItfPkeb4A\naxfmY9Jr2Lm/HYvWwtdWf5kF1vnkGnJYmreIctUSfM01rDdfyFdXfYnvbPg6X1r+WWTgl/t+y/bm\nfyQ8bnGuiR67J9xSd7j3GN3+VgJ9hVTnzkt6/Tazjg1LCjlvTXlqJy6Yck67rVCssLNapcJs1GbM\n+CpTTvocHoJBOWnBdofLF9ooJOGJLShVjO/MKrpKVVZyLJG9q5NVRKKEZSMn5uRFVApPdmh1xPON\nHXbe33OIIf8QW0o3xtRvToax56EINSSaDpQw7OwarxQ3kzCHPd/0C67aelxo1KpRERGtRs3GZUW8\n/kEL+xt6WV2TzzfWfRUIyb/e+eA/ULm8fOYzW8KRmVJLMbmGbH6x9xGePPonet19fKz6kpjfa3Ge\nmcNN/XQMDxH564mXAfC11JBzTvK9zpIk8ZVtqdcKCKae08/zjbNbt5kzIzHp8wf5x7D6VCAojxrg\nnojBIR9ZCSqdFSpLrKgkaeZ5vkqbUV56nm/uFLQB9drdmA0aDLqR/Wj4OFPQ65vMRKN3h0PO6VQ5\nRzL2PHqHhRpiCWwoKGHnWJ7vTM/5TjTsLMsy7X0uinKN4zbHZw+3D+0Y3kQrHGnqp3vAzfrFheNS\nIpXWedyx7msUmvJ5pekNHq37A75A9LUpnnZrzyDvtO/mpL0Ji6cC2WWN2x4mmD2clsZXr1OjjzJd\nxGrW4fL4p7xAac/xbpxuP+rhGzpZI+L1BfD4AliS1ELWadWU5Js41TlIMDhzlK5augbJterTzkFN\ntvqULMv02N3jpAuV4qupGLCQaJavwztIXc8RKrLKKLUUT+hYeWOENuLN8Y0kkb5zSKZVPUqmdSYR\nLrhK0/j2D3rxeAOURBliMr8oi/ICC3uOd4cjADAS0Tp7ZWnUz8w35vGvZ3yValsluzv38vM9v8bp\nG13VHAgGCJq60M6v48n2B3n80P+gklSouxZj0EUfASmYfZx2xnfA5R1XbKWgeMOJ9GwninKDbl0V\nukGTfbgn22YUybzCLDy+QLhlYrpxun30D3rTqnRWyJ1ko+h0+/H6guOkC0c87Mnv9U3k+b7fsYeg\nHJxQoZXC2EiB0uObmyDnazGE6iAccfp8Z2qxFYBGrcKgU6dtfNuHCwMji60UJEni7JUlBIIy7xwI\nRbFcbj+7j3RSmGOkttw27j0KFq2ZW1bfwNrCldQPnOS+3f9Nh7OTgz1H+P2hp/n2jnv4S8cf0RSd\nIiAH2Vy6ga+vvRlHrz7hhkkwezitjG9QlnE4fTELRJQHSSph4FTptbs5cKKHqlJruPk+WQ9uRNc5\neeOrqNrMlNDziKxk+j2H2ZaQBORkeb5KODbPNtbzja4ONRmMeL7Rje+77btRSSrWFa2e8LHG6jsn\n6/mqVBJmozbqZlSRaZ2pxVYKFqOWwTQLrqIVW0WyaVkRapXEW/vbQv3Yhzvw+oNsWVGSsCZDq9by\nxWXXcOG8c+hwdfHvu/6T/977EDvb3kUlqTi79Ez8RzaSe+qjXLP4KkpN5TjdfhFynkOcVvEL55CP\noCzHNr7DhSNTmffdeaAdWQ5JzoUfigPJeVYjE42Sf+BFKl1tTEGab6pIV1ZyFJJMtk2aNPWpsW1G\nbr8bvVpPlkmLRh17GP1EGPF8x2+k2pwdNDlaWJ63hCzdxIURxp5Hr8ODRi0llb6wGKPrO8eSaZ1p\nmA3amOP5EtEWNr7Rf6tZJh2ra/PZfaSLk+0OduxrQ5LgrOXJpQlUkooray4n35jHm807WJxTiW+9\nfwAAIABJREFUy+rCFVTZ5qOSVNTt2EVHrxtZlul3JFehLpg9nFbGN5Ec3lTrO8uyzNv729BpVGxY\nXBSeWpLsw92RpK5zJPPCnu/MqHgOtxml2ePbM9THQ3WPM1TbgrdhOf7AmRMeZxdZ6dzkaOYnHzxI\nta2SG1d8jjyrfoo832HjGyV/9257+nKS0ZAkadR59A96wtGDRGSZtHT0ucZV5GdSWnIiWIwaPL4A\nPn8w5aECiTxfCBVe7T7SxdNv1FPfamdFVV5Kk5cAzi7bxNllm8b9vTjXREuXk/5Bb8IpVILZx2kV\ndh4RBYhuvMISk1OU8z3WPEBn3xBnLCrEZNBgNmjQa9Wp53xTCDubDFrybQYaOwbHSeBNBy3dofB3\nOpXOB7oP8f/e+y8a7aeQAF31Pp479sqEz0vxoK0WNY/W/RFvwMuh3qM8sPdhsq0a7C7fpM95drl9\noXGCY6pog3KQd9s/wKgxJBRjSIVcqwGHy8eQx0//oCfp8GWWSYcsj++VtccQq5lpTKTXt73HhdWs\ni1sYuGxBLjaLjkONfUDqQxTiEanxrIwSjKfFLZhdnFbGV1GvitUaEVa5miLP9619rcDIDSoNj65L\n2vNNI+wModDz4FCo0Gm6ae12km8zoNclXyEbCAZ4rv5FfrHvEbxBH9cs+iTr1Z8k6DHwWutr/OHI\nMwSC6RtH5fq/O/AmHa5OtpadxeqCFRzrb6A3fzuo/OE86WThdPuj5nuP9tXT7xlgbeFKdOrJ659V\nQuon2+zIMuQk6Z3FateZLZ6vOc12I58/QM+AO67XCyF9gM3LQ/ez2aBhdU1+eguNwmjjm3gKlWB2\ncVoZX0W3OVHB1VSEnYc8ft473Em+zcCieSNj4fKsBpxuP25vYiGAdAquYCT03DjNoWe7y4vd5aM8\nBXGNAY+D+/f8hpca/06+IZd/PeOf2Vy2kfm2UjwHN5GjKWRH67s8uO/RhPNVY9Frd6PJ6WJX5y5K\nzEV8ouZyrl92DWsLVzKo7kC36H1a+wfS+uxYxJrlOxJynniVcyRKhfjxltB55FiS9XyjtxvNdHUr\nBUuaYwU7+oaQiR9yVjh7VQk6jYpz15RN6rzcyAELivHNTvJ7E8x8TjPjO3053/cPd+L1BdmysmRU\nri3XmvzounRajWDmjBds7Uqt2OpYXwP/773/4mh/Pavyl/HN9bcxLyskk5drNYDPwDr1NpblLeZg\n7xF+8sGD9HtSN5LdzgG0Cw6gkdR8cdk1aNVa1Co1X1h6NfP1i1Bn9fOn5j/g8k2OnKU/EMTjC4zr\n8fUH/eztqiPXkEO1rXJSjqWgVHIfH57vnGzuMCvGZKOZPtFIIV2Vq7CmcxLGtyjHxI+/tpkrz65K\nfYFxKInm+aaYTxbMXITxjUCjVmE2hHJ8k81b+9uQIByiUhgrgBCPQZcXifiShNGYHza+09tuNDLD\nN77xDcpBXml8g5/t+RWDPidX1lzODSs+h0lrDL9GuW52R4CbVnyeLaUbaR5s5T/f/29aB9tjffQ4\nfP4AQ4UfgMbDx6ovpcwy8v2oVWouK92Gv7uUHn97VEGEdIjV43ukrx53wM2qgmVJyYemghJ2rlc8\n3xRyvjBeYnK2hJ0txvQmG4UrnaP0+EbDZNAmLRGbLCaDFqtJS3uvk16HB61GlXAQh2D2cHoZX2W3\nHidnap0Cicm2HifHmwdYWpkzrpc0FalEx5APszH1mzzboiPLpB3l+fYM9VHXc5hTjlYc3swUY4WN\nbxzP1xfw8WjdH/hz/fNkaS3ctuYmLpx3zjhjFCmAoVap+adFn2Bb9aX0efq5b/cDHOo5mtSaXj25\nE3VOF5ZACedVbBn37wU2E76GFeT5a2lyNPOzD0MbgokQq8d3X9cBAFblT74Wr2J8XZ6Q4U+2cMcS\nI+w8awqu0gw7K55vSZLGd6oozjXRPeCmu3+InKz4IyAFs4vTahs14PSi04RUb2JhNelo63HhDwQn\n3MKi8Pb+kKLVliiSc6kIOShDFVJFkiTmFWVxsLWZv9W/Rl3vQRodp0a9RqPSkK2zkm2wka23kaPP\npjyrlNUFy9GoUvuZuP1u6noOU2YppdhcGP57S9cgkhT7geb0ufjlvkepHzhJ1XCrT6w+V6Neg0mv\nCV83SZK4aP555OqzeezQ/3D/3t+wpnAlH6u6hEJT9CKYDlcXL556EdmvZZX+/Kgi9yEPUcLScwaL\n1+Swo/VdfvrBL7ltzU1YdOm1S0Xr8Q3KQfZ1H8SiNVOdXZnW58ZjrKebSN1KQfm9jdV3tju96LXq\nlArnpoN09Z3be12oVRL5tukN8xbnmTnaPIDT7aeicOI934KZw2llfO1OL1azLu7ucURi0jcpPXWB\nYJCdB9ox6TWsXTjeCOTaFNH7+DnfYFDGOeSjNMWdeIezkw+7DtBZ8B6Ggh6ebww19y/OqaU6u5JB\nn5N+9wB9ngH6PQPU959EZsQLtuqy2Fp2JlvKNiUUfOge6uGN5h38o/V93AE3aknNJZXnc9H881BL\nalq7nRTmmKJqAXcP9fDA3ofpcHWxpnAln1/yGbQJqn1zrQa6BoaQZTn8na4rXkO+KY+njj7Hh537\n2Nt1gLPLNnFp5YWj1h8IBni07g/4ZR/eE6sp3RjdQOu0aqwmLX12D99Y9AlUkpq3Wv7Bn+r/xnVL\nPh13fbGINsv3pL0Ju9fBWSXrJzTBKBbKedhdPlSSlPQwBGWIx9iw84DLO2OnGUWSjvGVZZn2XheF\nOUbUqukNDkbmnEWP79zitDG+sizjcHkTjqCLLLqajB/7gYZeBga9nLe2LKrRyc3SI5HY8x10+5BJ\nvs2o0X6KH+7+X5oGQvOCVagI9BdwRtEKrt5wNhZtdK8tEAww4LXT6+5nX1cdO9ve5a8nXubFxr+z\nrmg155VvoTxrxIOXZZlj/Q28fupt9ncfREbGpstiS9lG3u/Yw99OvMKergNsm78Np9vPonk5Udf6\ni72P4PANcuG8c9hWfWlSBijPqqe5axCXxz8qD15pncc3zvgqH3bt57n6F3izeSe72nbzkfnncl7F\n2ejVOp4/8QpNjmZKVYuo7yseN1QhklyrgeYuJxISn164jeP9Dexq280FFVvTGnowMst3ZM17lJBz\nwdSNf8u1GrC7fNgsuqRTF5Yonq8i07qgdHLGOU4lI32+yRdc2Yf7oRdHdCVMF5E5Z6FuNbc4bYyv\ny+PHH5ATCsFbJ1loY2TKSfTme41ahc2iS5jzVR5+yUgC9gz18Yu9jzDod7IifylrClZQqK7kBw/v\nBW1xTMMLoSKjXEMOuYYcarIXcNmCj7CrfTdvnHqbd9re552291mYXc25FVtw+Yd4/dRbtAyGznF+\nVgXnVWxhTeEKNCoNl1Sez5+O/40dre/yi7pfoimvpDhv9FDvvV11PFL3BP6gn88s/Dhby89KeH4K\nI1ED97giNEmSWFu4kpX5S3m7dRcvnHiVvzS8xPbmnZxZsp6XGl8nz5BD8cB66umOa3zzrAZOtjtw\nuEJaxtuqL+XBfY/yXMOLfGXlF5Jer8JYz1eWZfZ21aFX61iUU5Py5yWLch6p9IrqtWp0WtWonG9Y\npnWG53shpCAmkZrnG2+gQqYpEZ7vnOW0Mb7JVmfaJrHdyO7ysud4N+UFlnDFcTSUh+JYCb9IRgQ2\n4htft9/DL/c/isM3yPVrP8MZ2aF+0aAso9eqaepMrd3IoNFzTvlZnF22iYM9R3j91Nsc7jvG0f56\nIBTCXlu4kvMqzmaBdd6okL5RY+SaxVextnAVD+19Ern0BLt5hrUDV1Nlq+SN5h08ffQ5tCoNN638\nfMqKTpEDA2JFNDQqDeeWb2Zj8Rm82vgGr516ixcb/46ExOeXXs2zL/UD8QfLRxbFWc06luctodq2\ngP3dBznef4Ka7AUprXvE8w3dfq3OdrqHelhTuDJhqH0iKOeR6kM8y6gdFXae6XN8I1GpJEwGTUoF\nV8nISmaK/GwDapVEICgLgY05hjC+Y5hMoY136joIBGW2rIw/5STXaqC+1c5AnFC3snNXcnDRCMpB\nfnfwj7QMtnF22ZlcXHMO3cNyjipJoqLQQkOrHa8vgC7KPON4qCQVy/OXsDx/Ca2D7bzSsAOjVs9H\nFmwhxxA/PLc4t5ZFQx/jvf63sBc38uPdv6AmewHH+hvI0lq4edUXmW+tSGk9MGIwk6kUN2oMXFF9\nCWeXn8lrTdspNRdTnV1Jj/0dzAYNBl3sWyFyru+CEiuSJPHxmsu4b/d/82z983x97T+nVIU64vmG\nDO3e4ZDz6vxlSX9GOijnkWr40mLS0dY9UuE9W9qMFMwpTjZSjG9JjIEKmUStUlGYY6StxyWkJecY\np02r0UCSu/XJlJjcdbAdtUpi07L404SSqXh2JBF2/kvDS+ztrmNRTg2fqv3YOIMwr8hCUJbDLT/p\n4Pb6eX2nnTefz+HQO0UJDa9CR7eXYPNSblv9FQpN+Rzrb6DIVMg31n0tLcML6Y38y9bb+GTtFZxZ\nuh5Zlum1e+KGnCH6XN8q23xWFSynYaCRfd0HU1r32D7fvV11qCU1y/IXp/Q5qaKEUYtyjQleOZos\noxavP4jHG5LwHJglAhsKFqMW55Av6Xa6sMDGDAg7A1QUWlCrpIS/U8HsQni+YwiPFZxgztfl9nOy\n3UFNmS1hbizSg6suiz6EO9FEo11tu3m58XUKjHl8aflnUavGe7ZKaLaxw8GCEmvS56JQd6KXR184\nHPY0GzscdPYPUZgd/2EuDxv84lwTC3Or+Nb629nfc4jFObWjhDNSJS+FHuloON1+PL5AQtUgpTd7\nrJH/WNUl7Ouq47n6F1ietzjqNY9+XKXPV0vPUC/Ng60szV2EUZP+tUiGFVV53HrVSpZV5qb0vrDE\n5JAXvc44ItM6C3K+ELrO/oCM1xdMqjWqvdeFxahNWcZ1qvjM+bVccEZ5yprugpnNaeP5jghsxL+h\nJivne/RUP7IMi6NU90Koqvipo8/yu4NPMqhtBikQV2IynPONEnZuGGjkicNPY9QY+MrKL2LWRt+x\np6t05XL7ePj5Q9z35B76HB4uP3M+V19YC8CeY90J399r9+D2BsKyklq1lrWFKydkeIFQ1a6U/lzf\nsXN8YxH2fAdGG99icyFnla6n3dXJrvbdSR/XFTFOcG93HQCrCqY25AyhIrTVNfkp6w+HVa6Goy+z\nLeysqFwlU3TlDwTp6k88UCGT5GTpqS2f/sprweQiPN8xaDVqjHr1hI2vMmJs8fzxxleWZf5w5H/5\nR9t7w3/ZjWGtmn846inq3MyyvEXo1KPXORhD17nX3cev9v2WIDJfWv7ZUaIWYynNN6NWSSlpPH94\nrIvHXjpC/6CXikIL11+2hPnFWfQ5PPzh1WPsOdbFRevjh42TUbZKB7VKRU5W4krxWITn+Nri59LG\nDqOP5LIFH+Hd9g/524lXWFe0etz3Fg2n249Rr0alktjbdQAJiZUZML7pMrZXdjYVXMHoyUZjFebG\n0tU/RFCWZ0zIWTB3yYjx7e6fHEH6iaCEypJ5YFhNE5eYPNzUh0atoqZsfHj32foX+Efbe8zLKucT\nNR/lw446Xm94n25DA7850IBOpWVZ3mJWF66g0lqBTW8Lh50jQ2Fuv4cH94Uqmz+1cBtLchfGXZNW\no6I030xz52DcymoIedp/ePUY7xzsQKOWuHJrFZdunBdW/crJ0rOgxMrRUwM43b64etPKDN9Ems7p\nkGc1cKxlIC1FMsVjTuT5qoZHP0bLLWfrbZxXsYWXG1/njeYdXDT/vITHdXl8mPRaHN5B6vtPssA2\nH6tu5vbMjkw2Ct0Ts2WogkJ4slESRVdtiqzkDPJ8BXOTjBjfL/7gZf7P1WuieoGZYsDpRaOWMOoT\nn7LVrKOzfyihgYrF4JCPU52DLJ6XPU5Y49WmN3ml6Q0KTfn886rrydJZqMlewN//ZiG7yMvGM2U+\n7NzHh137+bBrf/h9Uq4eg1nPw4caydZnk623Ud9/gpbBNraUbeKcsuT6Y+cVWjjVOUh7ryvmdCG3\n188Pn/iQ1m4nC0qsXH/ZYsqijAFcXZvPiTY7++t72LQstthEqtOMUiHXZkBuHqB/0EO+LbUwdtjz\nTaKQJc9q4FBjX9RK8Y/MO5cdLbt4ufF1NpdupID4htTp9lOUbQyLkmQi5DwRLMbRYecBpxdtApnW\nmUQqM31nUpuRYG6TsZzvkVP9mTpUVJKRllSwmnXI8kiRU6ocaYoecn6n7X3+dPxvZOttfG3VDWG5\nQ0mSyLMacfSY+Fj1JXxv0x18e8O/8NEFF7Ox+AwW5tSAX4NkcLK/+xBvtfyDvzS8yMHeIyzMqeHT\ntduSbnVJNF5QlmV+9+IRWrudnLemjO9cd0ZUwwuwZnhw+J7j8fO+zd1ONOpQy8RkE9nrmyrJ5nwj\nX6OMdovEpDVyceX5DPndvNT497if4w+EqoZNBk24xWgqBilMJmF954iws9WU3L00EzCHJxslVrma\naZXOgrlLxnK+0zlLVpZl7C5v0jnHSInJdPJahxtDG43IYqv93Qf5/eGnMWmMfHXVl8gzjjbMuVYD\nbT0uPN4Aep2aMktJeLydLMt85b43Kc03cce1y4d1mO14Ah6WpVBlC6F2IwgVXW2K4nC9saeVdw52\nUF1m5eoLa+N6/mUFZvJtBvY39MQM+wZlmbZuJyV5pinRyU1lKtRYeuxu1KrkdI4jK9KLonhFW8vO\n5PVTb/Nm804+6bwYiB6GV6YKGQxwuPcYpeZiCkx5Ka89k0SGnRWZ1orCmRsmH0sq+s7tvS5UkkRB\nggp+gWCiZMTzzc7ST6vxdXsD+PzBpHNUtgkKbRxu6kOnVVFVGsr3Hu8/wUMHHkcjqbl51fVR9YDD\nQg6O8UbE4xtev0mPSWuizFLCsrxFrC1ciT6JAp9IItuNxnKizc4fXj2Kxajl5m3LE+ZQlerZIU+A\nI03RIxvd/UN4/cEpyffCaAGMVOm1e8jJ0ieVWkjU1qRVa7mi6mL8QT//c+CvMT9HqXT2mdrxy4Ep\n1XKeLCKrnRWZ1tlSbAUjxjcZlav2XhcF2YZJm2gmEMQiI7+wqjIbPXZPymO9JotUWyOsE2g3GnB6\nael2UluejUatomWwjQf3PUJADvLlFZ+jyjY/6vtitbNAhK7zJPQdGvUaCrONNHU4RokOON0+fvHn\nAwQCMjdesTSpPCjAmtrh0HOMlqOpqnRWiCaAkQz+QJB+R2KBjfBxbInD2+uL11BqLubNk+/wQee+\nqK9Rin4GdaGRjrPB+JoMGiQplIYZuZdmRg9sMiQ703dwyMfgkE/kewUZISPGVxGOmC7vN1l1K4WJ\nqFyF873zsuke6uH+Pb9hyO/mc0s+w7K8RTHfF8+zSiSwkSrziiw43f6wIQnKMg/99RDdA26u2FzJ\n8qrkw6C1FdkY9Rr2HO+KqiDUGja+UzOLNC/OpiUe/Q4PMskVW406ThwPWyWp+PTCj6NTa3nowOM8\nffQ5/MHReUaX2w9SkF5OkWfIodwSfeDGTEIlSViMWgZdvlnX4wvJh51FvleQSTLm+ULq4g6TRfiB\nkaRCzEQmGx0e7u+trrDw4L5HsXsdXFX7MdYXr4n7vrw4HpwjRo9vuowtunppVxN7jneztDKHj21O\nbUiARq1iZXUePXYPpzrHf78tSqXzFIWdjXoNRr0m5bCzYkTzEvT4Kiii9omOU5tTxb0fuZMiUyGv\nN7/Nf33wIH3ukZC80+1DZe3Bj5dVBctnTdFSlkmHw+UNb0hni7oVgEGnRq2SEuo7t/UOTzMSnq8g\nA2TY+E6P55tqX+JEws6Hmvox6NTsdb5Nm7ODrWVncl7FloTvy40hYQiRE40m54EXNr6dgxxp6uOZ\nNxvItui48YplabVWrY5T9dzS7USnVZGfQNxgIuRZ9XTb3Ulr98JI+DhZz1enVZNl0iYV3i63lfB/\n1t3CuqLVnLA3ce97/8XBniNAyPNV53QAsyPkrGAxanG6/fQPzj7PV5IkzAYNzqH41c6izUiQSeJW\nO/t8Pr797W/T0tKC1+vl5ptvpqamhjvvvBNJkqitreXuu+9GlaCKtTjXjEGnpimKZ5QJUg2VpVtw\n1efw0NHronqxh+0tOyk2FXJlzUeTem+ORY9EdOM7MtFo8sLOAHUne3ljTwsAX9m2PO0H6oqqPNQq\niQ+PdY/ynAPBIG09TsoLLKim0MNTht0PefyjBtTHozuFNqPI47R2O5FlOaHHatDo+cLSq6m2LeCZ\nY8/xwN6HuaTyAgJD1aizOzGoTDHz/zMRJeqipBFmU8EVhHp9I2cSR2Mk7Dz904wEc5+4VvO5554j\nOzubJ554gt/85jf84Ac/4N577+X222/niSeeQJZlXnvttcQHUUnMK7TQ1uPE4wtM2uKTJVXjq9ep\n0WtTl5g83NQHGi89tl2oJTVfWHY1uiTns2o1KqyW6FKJyUw0SoVsix6rWcfx5gEGBr1cdW41CyvS\n1441GTQsmpdNY7tj1Oahs28If0CesmIrhXgh+1j0piCwEXkcnz+YdP+3JElsLT+Tr5/xz+Qasnnh\n5Kvs8DyFpPNSk7UQlTR7KmqVjZ9ifGeT5wsh4+t0+wjGiY6097ow6TUJ9d8Fgskg7t1/ySWXcNtt\ntwGhXlO1Wk1dXR0bNmwAYOvWrezcuTOpA80rykKWobkr895vqgVXEKrmHEgx53uwsRdd5QE8sosr\nqi6mIqsspffnWQ302j3jHhCTHXaGEe93TW0+F29Ib6RfJEroeW99T/hvSr43lkjHZJHKXF+FsLpV\nCgPKw8dJsbhrvrWCO9ffxpKcRTjpBWB57tKUPmO6sQz/9hSp0NlmfC0GLbIM+yJ+n5EEgkE6+4Yo\nzjPNmjy8YHYTN+xsNoc8lsHBQW699VZuv/12fvjDH4Z/nGazGYcjuTzuspp8Xt3dTJ/TR0FBZhv0\nh7wB1CqJ+eU5Sec082xGjp7qJy/PkvR7Dg7sQ13UydKCWv5p7eUJw/FjKSkIDbvXGnSjPDJvIGSM\nKytyUjbAsa71lefVYss6xdc+tXpSWpjO31jJE68e42BjH5++KDSXtv/DVgCWVOdP6XdeWR4SLPEG\nY5/vWAacPixGLfPKk5c8nV9qA5rxIyU8zth/37HXQf2ORXjNEnlFXi5fuwm9ZvZ4WCWFoQ3UkCeA\nRq1ifnnOjDRSsb6XSzYvYH9DDz97eh/nr6vgy9uWj7qXWrsGCQRlKkttGX8+zQXENUudhApXbW1t\nfPWrX+Waa67hiiuu4Ec/+lH435xOJ1ZrcnNhc4ZDOXX13awb7g3NFD0DQ6FimZ7kvW6jTk0wKHPy\nVG9SBu9IRzND+XtRB7VcXXsVPT2pD6y36ENKVUdPdFNdOjLXt6d/CJUk4Rp043YmH1otKMiiqyv6\n5mhBgZkvXbqYoUE3Q4PpTQWKRAWUF1jYe6yLUy19GHQajjWGvLwsnSrmOiYDLaHNSWNrf1LHkWWZ\nzj4XhdnGlNalH96EnWjup7Yk9sMm8roPDHp4/JWj7D7ShVaj4hPrL+Ci9RXY+9zAxK97ppACwfB/\nZ5m0dHdPT/1GPOL93heWZPHdz6/jkecP8/f3T7H7UAefvWgRZywqAKBuuFgw26Sd0t/qXCTedT/d\nibcpieuadXd3c/3113PHHXdw1VVXAbB06VJ27doFwPbt21m3bl1Si0hnnN1kYXf6Ug6TpTLXNxAM\n8Psj/4OkDrDWdD65hvQGSOTG0Cl2DPmwmLRTWrQ0GaypzccfkKk7ETK6Ld1OjHo1OSmEdtMhPwkB\njEhcHj8ebyClYiuI/H4SG01Zltl5oI27frOL3Ue6qC238f3rN3DpxvlTIrM51URuQGdbyFlhXlEW\nd33+DD55ThVOt5///tN+fvHnA9id3pFiK1HpLMgQcT3fBx98ELvdzgMPPMADDzwAwHe+8x3uuece\nfvzjH1NVVcXFF1+c3IHUKsoKzDR3OQkEgxl7AHm8ATy+QMoPjMh2o7KC+K998eRr9Pjb8XeXcOG5\nG9NdakzBiEGXl2zL1BqwyWB1bT5/2XmSD491s6omn45eF5UlWVMenrRZdKgkKemcr3J9lRxusuQl\nmVvu6hvip0/vY199D3qtmms/spDz1pbN+M1TPCJTE7Ot0jkStUrF5WdWsnZhAQ8/f4j3DndyqLEv\nfO8JgQ1BpohrfO+66y7uuuuucX9//PHH0zrYvKIsmjoGaetxUT7FRTgKStGULUroeNDr5LeH/sii\nnBrOKTsLbURlcljlKkHRVcNAIy+cfA3JZ0TXsWpCGsZ5UTwrfyCI0+2nojAz12sizC/OItuiY199\nD63dTgLBqa90htADNSdLl7TQRrJzfMeSZdahUatiHkeWZd7c28pTr9cz5PGztDKHL1yymPw5INIf\nKfAymwQ2YlGSZ+Zb157Ba7ubeWZ7PY0dDiSgaAombwkE0cjYVCOA+UVZvE0bpzoGM2Z847UZBeQA\nTfZmDvYc4Y1TO7ii6mLWF69BJanCDxi7M3Zbidvv5rd1f0BGxnN8BWvLCybk3USr2lXGoE1GUdRU\noxoetPDGnla27w0VW5VOkazkWHKtBo63DCQVVRlRt0rN+KokiVyrPmpLU2f/EI8+f4jDTf2YDRq+\ncOlizl5ZMiOLktJhlPGdxZ5vJCqVxEfWV7CqNp8/vnqMLJN23PxtgWCqyKjxVdpbGjscnLk89vD1\nySSe8bXprdy96Q5eanydN5p38LtDT/Laqe1cWX05VnPhqPcrBOUgx/tP8GHnfvZ27WfA62CxYR0f\nOnLHze9NFYtRi06rGpW7nIo2o6lkdW3I+L61rw1gyqYZjSXPauBY8wD9Dm9Co5pOj2/kcQ419uHz\nB9BqQkV5ivfk9QVZXZPP7desJehNPDt2NqHVqNHr1Hi8qadwZjqF2UZuvWrldC9DcJqRUeNbXmBB\nIrMyk4kENkxaE1fWXM7WsrP464mXeK/9Q+7f+xsWWKqQTMXYnV4CwQBH++uHDe4BBn0ena2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g2cPHkyAyueG0zkugMcP34cq9XK/Pnzp3qpc4qJXPf777+fL3/5yzz//PM89NBD3HLLLZlY8qwi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\nI4yvQCAQCAQZRhhfgUAgEAgyzP8H0E1TTmIy8S0AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1fc8729fac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_linien_stoerungen(8)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Die letzte Grafik dieser Serie zeigt die Störungen der Stammstrecke (Sxxx)."
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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rTG1/rwRfIYQQJ4PSCgdRJj3RZmNIx1miItPzVUqRdbCUuGgTvTLigjpGgq8Q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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1fc87284588>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_linien_stoerungen('xxx') # results in the disruptions for the stammstrecke"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Gesundheit des Systems"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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eYsDVjq7UUpAlEolE4hPGU1Z20ut6riBn5pTx6+EyBidGMHZ4L5/3S47XY7E5\nKa0y+31OKcgSiUQi8QmD2d7IUgwN7pmlT3aHk//3zWGUCgVzr0xrdWncU0lK0ANwvNi35lgNkYIs\nkUgkkjZxOF1YbE70wfXFOR5r2WhxdNWwOoX12/MpqTJz+QWJJMbr/do3OcGd+JVf4n8cWQqyRCKR\nSNrEI7qNXNY9MIZcUmnii215ROi1XDu+v9/7J9cJeL60kCUSiUTSGTTs0uUhtIcJcrXRxhtfHMDh\ndHHjpMEEB/nfOyssREtUWFC7Mq0D0qlLIpFIJD0b4yklT9BzLGQhBDv2F/PuN9kYLQ5GDo7loiHx\n7T5ecryePTnl1BhthIf6vgyxFGSJRCKRtEl928ymFvKZnNRVZbDyn68OsftIGVqNktmXD2bS+Yl+\nJXKdSnJCGHtyyskvqWV4/xif95OCLJFIJJI2ac5lfSaXPQkh2LqviPe+PYzJ6iA9OZJbpgwhvh0t\nL08luUGmtRRkiUQikQQUYzOCHBykQqVUeFtqnilU1Fj4z/8OkZlTTpBWxdwrU7lkZN9Gfao7QlJd\npnWen3FkKcgSiUQiaZPmLGSFQkGoTo3BfOaUPe09Ws7KtfswW50M7RfFLVelt2shiNaIi9ARHKTi\neIl/mdZSkCUSiUTSJvV9rBvLRmiwhlrTmWMhr9uSi9Xm4par07k4o3eHYsUtoVAoSIoP4/DxKqw2\nJ0FalU/7ybIniUQikbRJc3XIntdGi71dvZtPN0IIispNxEcFM+GcPp0ixh6SE/QIoKDUdytZCrJE\nIumxrFy7j6ff+qmrh9EjMJjtKKDJIgv6YA1CgNna/d3WBrMdo8VBr+iQTj9XcrynY5fvgixd1hKJ\npMey/1glnWgEnVUYzXZCdGqUysYTGtog09qXFZG6kqIKE0CnCnJudT5xwTHeTGt/GoRIQZZIJD0S\nl0tgtNhRKhQIITrVPXk20JLgNmwOkhB1ukflH0XldYIc0zmCvK/sAK9mvolKoWJEzFDUkUHkFfve\nC1u6rCUSSY/EZHUgBDhdArvD1dXDOaMRQrgFObipIJ9JKz51toX8v7yNAMSFxLK7bC+a1J0UJXzO\nupyvKDOXt7m/tJAlEkmPpNZk8/7fbHOi1fiW6SppisXmxOkSTRK64Mxqn9mZgpxTdYyj1ccYHjOE\nP2XcQn5tAf/e/jWlyhz+l7eB/+VtIDVyIE9Nvq/FY0gLWSKR9EgaCoTlDEg46s7UNwVpasPVC3L3\nn+OiChOKeMZzAAAgAElEQVTBQWrCQgIf6/4m320dX5EyEYVCQUp4EuOjr8Sy+1LGhV/F4MgBZFfl\ntHoMaSFLJJIeiaFBbazZ1v3Fojvj6cTVnMv6TLGQnS4XJZVmkhPCAp5PcNJQxN6yAwyISGFQZP2S\njSkJYeBSoa5J5u5JkygxlbV6HGkhSySSHkltA4EwW51dOJIzH6O5+RpkOP0LTAghKCg1IPysey6r\ntuB0iU5xV3+bvwmAK5InNno/ybM2cok70zo+JLbV40hBlkgkPRKjdFkHjObaZnrwvGc8Tf2sd2WX\n8tgbP7H7SOvW5qkUV3ROhnWFpZKfi3+lV2gCw2OHNPosOEhNfGQw+cW+PUBIQZZIJD2SRhaydFl3\niNYEOfQ0r/h0oswIQPbxKr/285Y8BdhC3nD8R1zCxeXJl6BUNJXUpAQ9BrOdylprm8eSgiyRSHok\njWLI0mXdIYzmlmPIGrWSII3qtAlylcGdPZ9f7N/CDZ2RYW20m9hy8icigyK4MOHcZrdJ9rqt2x6v\nFGSJRNIjMTSKIUsLuSN4LeQWOnHpg9WnLYZcVWdpHi/xL47sEeSEqMCt7PRDwVZsThuXJV2MWtl8\njnRy3VKMvnTskoIskUh6JLXmhnXIUpA7Qn2WdfOiExqsOW1lT1UGtyD76gb2UFRhIiY8KGD16Dan\nje8LthCiDmZsn1EtbucR5OM+WPRSkCUSSY+kocvaIl3WHaK1GLLnfavdeVo6onkEGXx3W5utDqoM\ntoC6q7cW/ozBbmRC4lh06qAWt4vUawkL0ZAnLWSJRHK2YjDbCQ5yW0PSQu4YRrMdtUpBUAvW5emq\nRXa5BDVGu3fBEF8Xbiiu9MSPQwMyDqfLyYb8H9Ao1UxMHNfqtgqFguR4PWXVFkxtZKJLQZZIJD0O\np8uFyeIgLsIdL5QWcsfw9LFuqaHG6apFrjXZcAnBwD4RgO9LGxYFuORpV0km5ZZKxvS+kDBt24tH\nJHnc1m2MVwqyRCLpcRgtDgQQE6EDZFJXRzGaHS26q6E+2auzLWRPhnVKrzDCQjQ+W8iekqeE6I4n\ndAkh+Cb/exQouCx5gk/71C/FKAVZIpGcZXjixxGhWoKDVNJl3QGcLhcmq6PFDGs4fc1BKuvix1Fh\nQSQnhPnkBobAljztr8jmhKGQ8+IziA2O8Wmf5Pi6TOuS1h8gpCBLJJIehzcJKURDcJBGuqw7gNHS\ncttMD57s6863kN2CHKnXeut723IDg1uQtWol0eG6Do/hmzzPIhKX+rxPr+gQtGqltJAlEsnZR63J\nkxWsJUSnlhZyB2itKYiH05XUVV3nso7QB3nLifLaEDkhBMUVZuKjQlB2cFGJfWUHOFx1lCHRqSSF\n9fF5P6VSQWK8npN1XcZa3K5Do5NIJJJuiKGuBlkfrHYLsrSQ243B3HoNsvszT1JX5z741FvIQd64\n7PE24shVBhtWu5NeHYwf25x2Psxei1KhZMagqX7vn5wQhtPVeiMTufyiRCLpcdTXzWoJCdLgcLqw\nO1xo1NIG8Ze2apAbftbpLuu6RiBRei06rRqtRtmmhVxU7rZKO5ph/U3eRsosFUxKupg++l5+7+9x\nsbeGvDolEkmPwyMMYSEagnVuu8Mi3dbtoq22mXAaBdlgQ6tWEhykRqlUkBSnp7Dc2GpDkqJKM9Cx\nhK5SUzlf539PhDac3/S/ol3HSEqQgiyRSM5CDKZ6qy6kTpDNNum2bg+trYXsIThIjUJR32Kzs6gy\nWInUB3nroZPq3MCtxWbrS57aJ8hCCNYc/hSHy8H1g6eiU7cvMSwxTk9bIWwpyBKJpMdR28DN6lke\n0GyRFnJ7MPiQ1KVUKAjVaTq1MYjT5aLGZCNSr/W+V1/f23Ic2VPy1LudgpxZlsX+8kOkRw3mvPhz\n2nUMgCCNqk0rXQqyRCLpcRjqWj3qtCrpsu4gntri1ixkz+ed6bKuMdoRwp1h7aG+vrflOHJRhZHw\nEA0hrbjcW8LqtPFh9jpUChUzU69tsVOZr6TUZYa3hBRkiUTS4zCY7OjrWj2GBNVZyDLTul34ktTl\n+dxodvi1JKI/NMyw9tA3LhSFomUL2e5wUVZtaXf8+Ktj31FpreKy5AkkhMa36xgNSZaCLJFIzjZq\nzXb0wW7XZn0MWVrI7cHoQ9kTQKhOjUuITnvw8QpyWL3LOkijondMKMdLDLiaeRAoqTIjRPvix0XG\nEr7L/4GooEiu6ndZ+wfegPEZvVv9XAqyRCLpUTicLsxWB/o6AfEIskX2s24X7lWz1KiUrcuFN9O6\nkxK7PH2sG1rI4C4nsticlFaZm+zjSejyt+RJCMGa7E9xCic3pE4jSKVteycfaMvL4JMg79mzh7lz\n5wJw4MABZs+ezdy5c5k/fz5lZWUArFmzhhkzZjBz5kw2btzYwWFLJBJJ+zB622Z6LOQ6l7XMsm4X\nBrOdUF3bLSs6e8UnTw1yE0H2rKTUTD1yUUVdDbKfFvKukj0cqjzC0Jg0zokd1p7htos2Z3nVqlWs\nW7eO4GB3l5PFixfz6KOPMmTIEN5//31WrVrFrbfeyurVq/n444+xWq3Mnj2bcePGodUG5qlCIpFI\nfMVbg1wnEMFBdS5raSH7jRACg9lBYlzb6wh3di1ytbG+j3VDPPW9ecW1XJDeOM5bXOF/DbLFYeHj\nw5+jVqqZOfi6Didy+UObFnJycjLLly/3vn7ppZcYMmQIAE6nk6CgIDIzMxk5ciRarZawsDCSk5M5\nePBg541aIpFIWuDUJKR6l7W0kP3FZnfhcLradLVC5wtyay5raH6RiaIKE0qFgrhI39tmfpH7DdW2\nGq5MnkhciG+rOQWKNi3kyZMnU1BQ4H0dH+9+Atm1axfvvPMO7777Lj/++CNhYfXZY6GhoRgMvi0c\nHRfXetaZpHOQ8941yHnvfLIL3Rm3veL1xMWF4aqrQxVKhZx/PympdM9dTGRIm3PXJyHc/R+V0rtt\nIOfbYHag06pI6hvZyGqNA2IjdBSUGpucr7jSTK+YEHr3ivDpHEcr8vi+YAsJobHMPv8atOrT6+Vt\nVy/r9evX8+qrr/L6668THR2NXq/HaKzvlGI0GhsJdGuUlvq2wLQkcMTFhcl57wLkvJ8eThbVAKBw\nuigtrSUk1G1RVVab5fz7SX6Re77Uyrbv1U67OyRQXGqgtLQ24Nd7WZWJiFAtZWVNjb2+saHsySkn\n51g54aFuETWY7dSabAzo7ds4nC4ny3e+jUu4mDl4OtWVVsAasPF7aO0hxe8s67Vr1/LOO++wevVq\nkpKSAMjIyOCXX37BarVSW1tLTk4Oqamp7R+xRCKRtJPaBmshQ30M2SKTuvzG16YgDbfpDJe1w+mi\nxmRv4q724Ensyi+pF15Phy5fS56+yd/ECUMhY3tfSHr04A6OuH34ZSE7nU4WL15M7969ueuuuwC4\n8MILWbBgAXPnzmX27NkIIbjnnnsICmp+4iQSiaQzadjHGkCtUqJVK2VSVzvwtSkI4M3ENnZCi9Ia\nY138OKwlQfa00DQwvL877utPyVORsYQvc78hQhvG9HYsrRgofBLkxMRE1qxZA8BPP/3U7DYzZ85k\n5syZgRuZRHIKX+3Ix2R1MGPCgK4eiqQbU78Wcr2I6ILUUpDbga9NQaBzLWRPQldEaPMxXa+FXNzU\nQm6rh7VLuHj34Ic4hJNZadMJ0XRs3eSOINdDlpwROJwu1m7OxWZ3MvmiJO+CARLJqRjqVicKC66/\neQdLQW4X/ljIWo0KrVrZSYLcfA2yh9gIHcEhDo6Y97L8123U2g2oa4YDbS/o8MOJbRytzmNkfAbn\nxA0P9ND9Qgqy5IzgWFEtVrs7Bph9vIqRg+O6eESS7orBbEOjVqLV1KfIBGtVVNZYunBUZyaehxtf\nH4BDgztnxafm2mYC1NoM7C7dx68lmTAsB7NCcLASFCgQoUXoeg/zJnk1R7m5krU5XxKiDmZm6rUB\nH7e/SEGWnBEczKts8H8pyJKWqW2wsISH4CA1Noe7platkh2DfcUfC9mzXXMtLDuKR5Cj9EG4hIut\nJ3/il+I9HK46isDdw1pPHJX50fxp4uXowx0s/flNFEn7WJO9lhsGX4NKqWp0TCEE7x36GJvTxo1D\nZhGu7fqSOCnIkjOCQ/luQVYpFd7/SyTNYTDbiT+lEYRO674ZW2xO9MFSkH3Fnyxrz3bHSww4nK6A\njqNhU5ANx3/kkyNfANA/PIWR8SMYGT+C/dkW/v3zAaorVCRGxmPNGk1kRiY/nNhKsamE+cNvJlRT\n777+qWgXByqyGRKdykW9zgvoeNuLFGRJt8fhdHH4RDV9Y0MJC9FwKL8Kg9nu801CcvZgd7jcohvS\n+Nrwlj5ZHfK68QOD2Y5KqfA+0LRFZ/Wz9ljIYaFqfji4Fa1Sw8Oj7iU2uL6TVnKCO6Erv8RAbGQw\nwhbCON31lIRvY2/Zfp7fuZw/ZdxCr9AEamy1fHR4HVqVlpvSrj+t7TFbQz4qSro9uYU12Owu0pOj\nSE+OQuCOI0skp9KSizVY61mCUdYi+4PBbCf0FPd/a3RWpnVVrQ2dVkVO7RHKLZVc2Ou8RmIM0Cc2\nFJVSQX5xrbfkKTEmkttH/I4rUy6l1FzO8zv/SVb5QdZkr8XkMHPtwKuJCY4K6Fg7ghRkSbfHEz9O\nT4kkPSWq0XsSSUNaEmRdkNvCk5nW/mH00xPlWfIy4IJssBKpD2JTwVYALkkc22QbtUpJ39hQCkqN\nnCyvX+VJqVBy7cCruWXoTTiEg1f3vMmvJZkMiOjHhL5jAjrOjiIFWdLtOZjvtoZTkyLp3zscjVrJ\nQRlHljSDwdS0BhkaduuSguwrLpfAZHGg92HpRQ+ebOxANgdxOF1uSz3CwoGKbAZF9qevvnez2yYn\nhGF3uNhzxL0scEJUfcz4wl4juee8PxGu1aNRqpmTfgNKRfeSQBlDlnRr7A4XR05UkxinJ6xufdtB\nfSM4kFdJrcnmfU8iATDUCcGp10Ww1mMhS5e1r5isDgT1cWFf6AyXdXVdQpct8igAlySOa3HbpAQ9\n7HUngUWFBRF0Suy7X3gyj46+D5Pd0q1c1R661+OBRHIKuYU12B0u0pMjve95/n8oX8aRJY1pyULW\nedZElhayz/hb8gSdk9RVZbCC0kGlJocIbTjnxA5rcduUhPrSpZYaggSrg7ulGIMUZEk3pz5+XP8D\n8vxfCrLkVE5dWMKDJ6lLronsOwZv28yutZCrDFZUsSdxYufivqOb1BM3JDFO7/2/Lz2suxtSkCXd\nmoP5lShwx4899O8djlYj48iSpngWlghrEkN238RNMqnLZ9pjIXeGIFfWWlEn5KFEydg+o1rdNkSn\nJi5SB7RsIXdnpCBLui12h5MjJ2pIitc3uimoVUoG943gRJnRuwqMRAKtlD01qEOW+IaxmwhyriEX\nZbCRwWFDiAhqu5uWZ6EJKcgSSQDJOVGDw+kiLblpvMfz3iFZjyxpQG2LZU8yhuwvXpe1Hwu5hASp\nURDYGHKuLROA8b1H+7T9xRm9GZISxaC+EQEbw+lCZllLui0el3R6SmSTz7z1yPmVXJgef1rHJem+\nGEx2tBolWk3jOKMny1rGkH2n3tvgu0wolQpCdGpvtntHqbBUUq06jssYztD4gT7tkzEwloyBsQE5\n/+lGWsiSbsvB/Kom8WMP/XqFEaRRyQYhkkYYzPYm8WMAnVZayP7iqSX2t9WoPlgTMJf1jye2g0Kg\nLO/v/Rv2ZKQgS7olNruToyerSU4Ia9ZlplYpGZwYQWG5ieq6PrcSibvHedPadI1aiVqllHXIftCe\npC6oX4JRCNGh89uddrae/AkcGiIc/Tp0rDMFKciSbknOiWocTtGsu9pDmqceWcaRJbgf4qz2pgtL\neAgOUslOXX5gbEfZE7gF3OkSHW5TuqskE4PdiL0kkajQMy9Bqz1IQZZ0SzztMptL6PIg+1pLGuKx\n6JpzWYO7Fln2svYdg9mOTqvye/1oj0er1tQxt/Wmgq0oUOAsSSJSH9ShY50p9HynvOSM5GB+JQoF\npCa2bCGnJIQRpFV5xftsxmSxY3O0vAatTqvq8TG4tlysuiAV1SZZJucrBrPdrwxrD575rzXaiNA1\n38TD7nChVilaXEXqWE0+ebXHGRiayj5bCJFhZ0eL3J79C5WckVjtTo6erCElIYyQVhrbq1VKUhMj\n2Xu0nMpaK1FhZ8dT9KlkHavgxfd3t7pNkEbFXdePYGi/6NM0qtNPSyVPHoK1aqw2Jy6XQKnsHuvf\ndmeMZju9Y0L93s+TlV1jshGhC27yeW5hDS+v2cOF6fHMnZzW7DE8qzoN0p3DPmqlhSyRdBVHTlTj\ndIlG7TJbIj3ZLciHjlcyemiv0zC67seGXwoAOD81DpWqeaH55VApr6/L4vE/XNRjb26eLl0tx5A9\nKz45W33Qk7jj8TaHy6+SJw8NLWSi6wXZJVxsO3qI/7d9K87kUrY7HBT8pKe5K/aEsYiEkDh0tgSg\nlqgees2eirwqJd2OQ5764+SW3dUe6uPIVWelINcYbWTmlJMUr+fOGSNa3O7rn4/z/neHeW1tFvfd\ndC4qZc9LH/HFZQ3uJRilILdOe/pYe/DsU2uyUWWt5kDFYQ6UHyKrPBuL0wy9QSVAuFSUmCwom3Fb\n61RBTOl/BbkH3CGGCL10WUskXcLBvCqUCgWDW4kfe0hO0BMcpPKK+NnG9qwinC7B+BHNrw/r4YoL\nEsk+XsWu7FLWbs5lxgTfmiycSfiS1AXIxC4faG/Jk2cfVXwenxb+TM2Jcu/7wqbDVd2XSakj6aVN\n4q3Pcrl6wgCuGduvxWP9+tN+gB7r1TmVnveYLDmjsdgc5BbWkNIrzOtibA2VUsngxEiKK81U1p5d\n9chCCDbvLUSlVDB6WEKr2yoUCv4wJZ24SB2fb81j79HyVrc/E6l3WTdvTXksZFmL3DbtbQoCcMD4\nC9p+BzC4qhgSncrFsZfjOjgBe+ZEbj3nJmaOnMB5AxJRAFm5Fa0eq9ro/k1HniUWshRkSbeiPn7c\ntnXsIT2588ufDuRV8uTbOwPaNL+j5BcbKCg1cu6gWMJaEKGGhOg03HHdCNQqBas+209FjeU0jPL0\nUWtufi1kDyGyn7XPtLcG+aeiXWwo/gZhC2KE/QaujLmBTd8E4TCE8qdrh3NBXZtbfbCGfr3DyDlR\n3arHospgI1SnRqNuecnFnoQUZEm34mCeu4QpvZX641PxiHdnLse4+3AZuYU1HCus6bRz+MvmzEIA\nxmW07q5uSEqvMG66bDAGs52Va7NwOFsulTrTaDOGLF3WPtMel/X+8kOsPrCGYJUO66ELyM2z8/Ka\nPTicLv583XDOT2vcc35Y/2icLtHq77aq1krkWVQ9IQVZ0q04lF9ZFz/2faWW5Hi3e7szBdljfXWX\n9XTtDhfb9xcRHqplxAD/SpkmjuzLRUPiOXKimv9uOtpJIzz9GEzuRhYadfO3tWBvUpd0WbeFv4J8\nrCafVftWo1Io+WPGLahsERRXmHA4Xdxx3XDOS41rss/w/jFAy25rq92Jyeo4a+LHIAVZ0o0wWx3k\nFtbSv3eYX00slEoFaUmRlFZZKK/uHDesp+tQdxHk3UfKMFocjB3Wy++MaYVCwbyr0kmIDuGrn/L5\n9XBpJ43y9FJrtrcqIDKpy3dqTK27/xtSbCzhlT3/xu608/thcxgcNYDosCDUKgV3Th/ByGbEGGBA\nn3B0WhX7WhBkT4/6yNCzI34MUpAl3YgjJ6pxCd/qj0/FUyLVWVZybd0NyhygZeU6Snvc1Q0JDlJz\nx3XD0aiVvPH5AcqqzIEcXpdgaEOQvWsiS0Fuk9JK9/UQF9m0sUdDqqzVLN/9L4x2Ezelz+CcuGEA\n3DF9OC8smMC5g1teBlGtUjIkJYqSSjMlzVx/VQb3b066rCWSLsCTlOVP/NiDp+d15wly97GQK2ut\n7Mstp3/vcPrG+t9JyUNSvJ45V6RisjpYuS4LVwdX52kOu8PFv784wOGCzm1varU7sTtcLTYFAemy\n9ofiSjOhOnWrDzgmu4l/7n6DSmsV1wy4inF9Rnk/S04IY6APZYvD+rvDLc25ras8FrJ0WUskp5/C\nchPgTjzyl6QEPTqtiqMnA590JYToVoK8LasIIWB8O63jhlyc0ZuMgTEcPVlDaSdYybmFNWzeW8ib\n6w/icgVe8D14Sp5aqkEG6bL2FafLRWmVmfiolldYsjntrMx8i5PGIi5JHMfklEvbda7WBbnOQj5L\nSp5ACrKkG2Gw2FEqFIS2o4uSUqEgKV5PUYUJqz2wFpDV7vRmI3f1zVwIwebMQtQqJaOGxLe9Qxso\nGiTQnSw1dvh4p+IprSqqMLFjf3HAj++hPgmp5Zu312XdTSxkp8vVoWvVYnN0SpZ8RY0Vp0uQEN2y\nu/rD7LXkVB/j/PhzuGHwNS0uEtEWCVEhxEXqOJBXgdPV+LtIC1ki6UKMZjshOnW7f9zJCWEIAQWl\nhoCOq+EycqYujiHnnKyhqMLEeamxhLRjJZ7m6BurB+BEWScIcoNmLeu25Da56QYKbw1yay5rbZ3L\nuptYyO99e5iFr23D7vBflO0OJw+u3Mbrn+0P+LiKK92eqvgW4sfV1lp2FP1CQkg8c4fOQqnomIwM\n6x+D2eps4t3yCPLZ0jYTpCBLuhHGNpJy2iI53i0sx4s7T5C72kL2JHMFwl3toU+cOw59shMEubLG\nfVMd2Cec4koz27M6x0r2xWWtUStRKRXdpjFIfomBKoPNG6rxh5NlJmpMdnYeLAl4mKa4wh26SIhu\n3mW99eQOnMLJxMRxaJQd7748vAW3dVXdw1xEqLSQJZLTihACo8VBaDtWl/GQnOCOPeeXBFqQ69fQ\n7coYstXu5OeDxUSFBTE0JXDLKMZG6NBqlJ1kIbtd1jdfmYZKqeCzrcc6xUpua+lFcLvndVoVlm7S\nOtPTDas9897w4Wnt5tyAjQnqLeSEZmLITpeTH09sR6fScVGv8wJyvvTkKJQKRRNBrjba0AdrWqwr\n74mcPd9U0q2x2Jw4XQJ9B9ywfWJDUSkV5BfXBnBk3cdC3pVditnqZNyIXgFdz1epUNA7JpTCclPA\nE68qaqxo1UqSE/RcfE4fSirNbNsXeCvZ28e6DQ9LcJC6WyTmQb0gt8cz4RFxfbCGvUfLyTlRHbBx\nlVR6LOSmLus9ZVlU22oY3ft8dOrAWK4hOjUD+oZztLAGo6X+t1ZlsJ5V8WOQgizpJrS3d25DNGol\nvWNCKSgxBFRYPPFJ6FpB9tYet7GyU3voGxuKw+lqth60I1TWWogKC0KhUDB1TApqlYLPtuYGPBnJ\nYGl9LWQPwUFqLN3AZe3xCAGcaEcynUfEfzc5DQislVxcYUIfrCG0mYfjTQVbAJjQd0zAzgdut7UQ\ncOCYu2zRYnNgtjqJDDt74scgBVnSTfDeUDsgyAApCXpsDhdFFf7H5VrCYyFr1ErMVmenlu+0RFm1\nmYN5laQmRjTrSuwonnrm9ohDS9gdLmpMdqLDdQBEh+u4+Jw+lFZZ2LavKGDnAd9iyOBO7LJYnZ1S\nc+0PHo8QtNdCNqAP1nBBejxDUqLYl1vBkQBYyU6Xi7JqCwlRTa3jE4ZCjlTlMiQ6lYTQjmf4N8RT\n/rQv170KWbW35ElayBLJacdodlsL7Sl5akiSN44cOLe1J4bsyTrtCgtr694iBO3vzNUWfWI9iV2B\ni79X1sWPoxt0WvrNaI+VfCygVrLBRw+LLkiNAKxdXPpkbLBqWGmV2a/yJ6vdSVmVxfsQde34/gCs\n/bHjfcnLqi04XaLZGuRNBVsBuCRxbIfPcyr9e4UTqlOTlVuBEKJByZO0kCU9mMJyI7knAxdvChS+\n3lDbIiUh8JnWHgs5vs5qON2lT666dY+1GiUXpAXWMvHgtZADmNjlWZ86KrxekKPDdVxyTl/Kqi1s\nDaCVXGuyExykRq1q/ZbmWWO7q7t1GRrESgVQ5EemdWG5EUF9dnxqUiRD+0WRdayywx3R6jOsG1vI\nJruJn4t2EaOLYlhMeofO0RxKpYIh/aIpr7FSVGFq0BREWsiSHkpplZnF//mFR1/biuhil92pGAPk\nsk6qK30KZGJXrcmOSqnwul5Pd1JQQYmBsmoL56fGewUl0ERH6AjSqAJa+lRRV/IUHaZr9P6UMSmo\nVUo+2xI4K9lgtrXprob6WuSuLl/zeIQ8FuAJPzwTnrBCw7ap140fAMCnP3YsllziqUE+xWW9vXAn\nNpedi/uO6XDdcUsM97qtK87KpiAgBfmswe5wsXLtPkxWB9UGW6PM4e6A10LuYLOLEJ2G2Agd+SWG\ngD101JpshIVo6he4P8038+N1ZVyD+oZ32jmUCgV9YkMoqlsyLxB4Sp6iwxvfVKPCgph4bh/Kayxs\n3lvY4fMIITCY7T55V+q7dXWtIHuu99Qkd79nfzwTnoemhoI8KDGCYf2jOZBXyaEO9HMv9mRYN3BZ\nu4SLTSe2oVGqGdPnwnYfuy2G9auvR5aCLOnRrNl4hNzCWrQa95/cU2sYSCprrSz/OLNdCVUei6Gj\nFjK465FrTXav26uj1JrthIVovdbp6baQPTfgPh1YSMIX+sSG4nAKb9lLR/F06Yo6xUIGt5WsUSv5\nIgCxZIvNicMpCGsjwxoaduvq4hhynUdocN0CDP60LT3RwvVwnSeW3IGM6+ZqkA9UZFNmLueChJHo\nNZ13DcZE6OgdE8LB/ErKqtwPczKG3Ax79uxh7ty5AOTl5XHTTTcxe/ZsFi1ahKuuyH/NmjXMmDGD\nmTNnsnHjxs4bscRvfj5Ywne/FNAnNpQZEwYC9bGiQLJ5byG/Hi7j12z/19ett5A77pJNDqDb2u5w\nYrU53RZy3dhOdwzZcwPuG6fv1PN4WmgGym3t6dJ1qoUMbstn4rl9Ka+x8mNmx6xkQytNQVzChc1Z\n7w3qLkswesbcKzqE8FCt3xZyeIiGsJDGYjWwbwTDB0RzML/Ku3Kav5RUmBtd6wDfe0qdEgNb6tQc\nw9c9gncAACAASURBVPpHY7O72JtbjgIIP4vWQgZo8+63atUq1q1bR3CwO6bwzDPPcPfddzNq1Cge\ne+wxvvvuO84991xWr17Nxx9/jNVqZfbs2YwbNw6t9uyazO5IcaWJN9cfQKtRcsd1w6k22rzvB5qs\no+6Shfa4wz0WQ0eTuqBBx67iWs4Z1PJ6rL7g+S5hIdouc1mfLDMSHqoNiPegNfo0SOy6oMH7VdZq\nhBBE6dpeTq8hFTUWgjQq77ydypTRyWzafYLPtx5j/Ije7e7I1JIgCyFYumslOdXH0GtCiQyKwGUN\nQpPiYGdVDc7CJCKDIhgY2Q91AFpA+oO3qiBYTd/YUA7kVWK1OQmqs+BbwmJzUFZtYUgLa4ZfN34A\n+45W8OnmXB5IjvSrL7zD6S55GtCnPjRSYipjf/khBkSkkByW6POx2svw/tF8u7MAm91FeIimzSS9\nnkabV2FycjLLly/n/vvvByArK4uLLroIgAkTJrBlyxaUSiUjR45Eq9Wi1WpJTk7m4MGDZGRkdO7o\nJa1iszt59ZN9WGxObps6lD6xoejqfvCBckt6MFsd5NT11G3YatJXjBZ34pSujRuSLyTXZVoHooWm\n9+EiuJJN1dtB1fe0uqzbugEHEk9M8nhZNVnlhzhYkc3+imyKjO7OWgkhcQyJTmVIdCqDowYSpGr5\ngbvKWk25Ihddvxr+uecwaVGD3L2PVfWiGaEPYuLIvnz983G2ZRUx4Zw+7Rq3R5BPdVnn1uSRU32M\nmOAo1Ao1JaZSbC476gTYazrO3gPu7dKjBvOXc29t96ImHRmzXqehT50gnyw30r9363kCnr7XLYUv\nBvQJJ2NgDJk55RzMq2RIP99brJZVW3AJ0agG+ccT2wC4pG/gS52aIy0pCrVKgcMpzrr4MfggyJMn\nT6agoMD7WgjhvXBDQ0Opra3FYDAQFla/hm1oaCgGg283w7g4/9e+lfjGig93k19iYPLoFKZdOhiA\nmBg9Wo2K8lprQOd+x75Cb6MDq1P4fWyLzUlYqJb4+I4nLsXG6gkL0XKyzNTh73i8zrVfGLSLUmMB\n6jhAOaTdx/V3v+y6BJ2BSZGd9lsRQnC8+iTZ9iyCh+zkgL6CA3vcoSitSsO5vYaiVCjJKj3M9wVb\n+L5gC2qlmrTYAZzTayjn9BqK3WknuzyX7PKjHC7PpdxUCSlgAw5UuOOQmwu3c9OIaxmXcoE3U/fG\nyUP4Zudxdhwo4frL09o1fkW+u9Snd3xYozl6L2cnAHeO+h3DE9IRQrDjQD5P/78fmTQmjhHpoWw6\ntp2DZYc5aj3C6KTA9Gb2BXvdbyUlKYq0MhPf/VJArdXZ5t94T677ekjrH9PitvOmDuOvy37gix35\nXHxBss8PGsfq4tj96641i8PK9qKdROjCuWLoWNQq/70I7blmh/aPIfNIGfExoWedPvg9w0plvQvB\naDQSHh6OXq/HaDQ2er+hQLdGaWlg+w5L3GzLKuJ/2/NIitczfVy/RvPcJzaUE6UGSkpqAmYVbNlz\nwvv/8iqT33/XaoM7kzlQ10NinNvqyDte2Sge5i8FhdUodAZKHe6HUlVcAWWVxnaNMy4uzO/9sg67\n4/HRodpO+618emQ93+R/734RBi5TGJenjmRYbBoDI/p5rVp7moPc6mMcqDjMgfJDZJVkk1WSzf/L\n/LTR8cI0etLC09iXJRgWP4DfXXoeGws2s+n4FpbveJNP93/NjEG/ITVqEABDU6LIOlZB5sEiesf4\nnzR0si5XQDhc3jmqtRnYnv8LCSFxDItP876vsKsR5jDUhjgywgfTa1Afnip/ibd3fUyytn9AVi/y\nhcoaMyqlAkONmfAgt1foYG45Gf1a94QcqutkFR6kavF6iApWc87AGPbklLNpZ743e7ktso+5F3fQ\na93H3nxiOya7mav7jqOyHTkn7bneAVITI8g8UkaIVtkj9aG1hwy/r76hQ4eyY8cORo0axQ8//MDo\n0aPJyMhg6dKlWK1WbDYbOTk5pKamdmjQkvZTWG7kP18dQqdVccd1w9FqGruBe8eGcqywhhqjjYgA\nuYWycivQaVVoNSq/Y8guITBa7PSKCVxLyOQEPQfyKikoNXhLS9pDrcmOOj4fgHBNODXUUGEoAoYG\naKSt09kZ1haHhU0FW4gMimDagKvY/Svs2FfN6FEX0Te6cRKZRqkmNWoQqVGDuHbg1dTaDByoyCa7\nMgetSkP/8BT6R6QQo4viYF4luwt3kzKgH1G6SGYMmsolfcey7uhX7CzezbJfX2d4TDrXDpzCuIze\nZB2rZMveIm6YONDv72Co6zXe0GW9rfBnHMLJxX3HNHroDA7y1CG7s6zjQ+K4JHEsG47/yPfHN3NF\nykS/z98eDGYHoXVrf/f1Y/nL+gS/1q+HqWP7sSennO1ZRT4LckmDDGshBJsKtqJUKBnfd5RP+weK\n81PjWLc5lwF9Ik7rebsDfkfMH3jgAZYvX86sWbOw2+1MnjyZuLg45s6dy+zZs5k3bx733HMP/5+9\n9w6M6zzvdJ8zvWEADHolABJsokSxkxIpWd2y5CJLsSSmuOxNcZzcKGtH0b13I99NdqNks/HKdort\nZB3HlmW5yUWSrepIskSximoUwU6Q6H0wvZ79Y3BmBsCUcwYDYAB8zz8SgcE5H84Mvvd72+81m1de\n/L8UCEVi/NNP3iMUifHpD23IONNU2dwHi5RHHpoIMDQeYMOqSirsJs0GORiKIsvMadLTTJTCru45\nVlqP+3zoq/uw6x3cu/YuAEb0Z+e8PrWo3YAL5c2hdwjHI+xt3MWuhm20VddMu28uykwOdtZv5bc2\n/AafWPsxdtRvodrqQpKktJan1D5QZXXx6Sv28+D2P6azooP3Rrv468P/izP8GqtV5sB7/QXphCs6\n1kpBYFyO81rvIUw6I7vqt017bUqpK1UHcHvbTdiNNp69+BKecHFHd2bDl9Y3bbcYKXeYVOmI9414\nKXeY8vbrtzc4sZoNnO1Rr8qn7Ae1lVbOTlygzzfA1TWbqDAvrGGsc9n46gPXsW+eZGJLGVUGubm5\nmR/84AcAtLe389hjj/H973+fRx55BL0+ceL8xCc+wY9//GOefPJJbrvttvlb8QLw/OFL/H//cpCw\nBn3ZUuHpAxfpHfFx09ZmdqzPLLPYMNXeMlikAQzKHNNN7S7KbEZCkZimZ5eSzSxeuFBpfZqrhGZ3\nqAvJEGVr9Tauqt2AHLbgNXdPa6WZT9RuwIXyRv9RJCR2NSQMV1O1em8tF4pBVtTN0lnlbOFPtvw+\nn73q09TZazk4cAT7FceYCPg4cXFs1uvzocxCVpS63h89xWhwjO11W7AZpytOWU1KpXzq82kz2rij\n/VaCsRBPn39O8/21okSE0jsKmqrtjE4Gc+qkB0JRRidD0wRBsqHTSaxucjI4Hkh2VuRjcMyP057o\nt3+1N6Fbfd0CFXPNxGjQLWiRXamwsLX+S4SuSxP0j/oZnQwWlNNaTHqmKos/dl171tcoGrjF8pAV\ng3xFu4szUydyjz9CVbm6imllDN1c2nricpyfnfsllyYTuV4ZGfMGN+9IOr785qtAYkD9La0fYEOV\nunSKLMsMSCeRZYl9TbvQSTr07hbiNWd4Z/g9ttdvKXi9alA24I158oqFMuQf5rz7Iusq1+CyJO7R\nWCRN6/HJ2YMl0pEkiU3VG9jgWsvjp37Mwf6jmNcf4ZV3qrmyo0rTvXwzDnRKZfC+5t2zXmsy6pCk\n2Updext38WrPAV7vO8x1zdfQ5Jg/7yxTRKix2s77F8fpG/FPaztKp29UW/qis7mC986PcbbHzbZ1\nNTlfG43FGZ0MsqapHHdokreG36PRXs+aiuz7iKD4rKwmL5Uowu9Kr+BSIhCKIkFOzeNUyHruHnI0\nFudk9xi1FVZqK23JebTpM4TzUQzZzOe7X+bFS69weuIcpyfOcWbiPLqyUSKW4eTXTo2f5Tsnv08g\nGlR1zQuTlwgZxomP19JQnjASNn8bkPAs5xutG7BWDvYfA2B3Q6rruLLMjNU8d03rXCpd6eh1en5z\n/T3sadiBzj7J+/pfMjSpbfiJJxDBbjGg1+kYDYxxYvQUbc7WjH2zkiRhNRkIzmhd0+v0fLzzTmRk\nnjzz9LxqvWeKCKWGe2SP6PRl0LDOxdrmRKhZzcCJ4YkAspzIHx/oO0Jcjs/KvwvmH2GQM6CcuNMn\nsiwV/KEoVrMBXY4/JJczMUigGL3IF/onCYRiyXmminqQljyyL4fSkhrOu7t55sLzVJjL+du9X+Sr\nN/wNX73hb9ge+jSBw7fx4Mb/wldv+BvuaL8Fd9jDMxeeV3VdxdMyutuTz9OhqyTureTU+FnGgoVr\nBqtB6washbgc59DAMSx6C1fXbEp+XZIkGqvtDI4FiEQLl7QcmwxhMelVVbjrJB37199Nq2Ejkn2S\nR9/8Ot6I+gOB1x9JfnZe6zuEjMx1TdlVpaxm/bSQtcIVVevZ4FpL1/gZ3hs9qfr+WlEiQukHUDUq\nacl6gmp1im1tDU70OknVnGRFua+m0sxrfQcx603snOcIkGA2wiBnQPmDSZ9ZulQITBnkXEiSRG2l\nlaHxwJw9gffOp8LVkMrjaREHSW5QBRhkfyTAv514HFmW+dTG+3CY7OgkHTpJR1tdGSBxeciHTtJx\nS+sHqLZW8UrPAXq9ueUavWEfbw6+DUE7TjklWGGzGIgONSEjc6j/Tc3r1YLWDVgLXWNnmAi52Va3\nGdMMgY+majtxWZ5TjcG4J5gxf5wNnaTj97bcS2yoBXd8hK8c/wbecH6jrAyWcNiMROJRDvQdxm6w\nsbU2uyiRxWzImqv9+Jo70Uk6fnL2GWLx+akhyaQs1lidKL7MlSpIVdyr60YwG/Wsqi+je8CTd96y\nEi0LWweYCLnZWb8Ni0H9+ycoDsIgz0CW5aQh9i2wZnEx8IeiqrySukoroUhszgMYTlwcQydJSSUp\npfVEi4dcqI61LMs8cepJxoLjfLDtRjorp7fMtCgSmkOJSmuj3sgn1n6MuBzniVM/IS5n9wCVtpnw\nYAtOa8pgWc0GYmP1GHVGDg4cndfQptYNWAsHp0Luexq2z/pe49QBoNA8cigcwxeMTquwVkNlmZX1\n+n1EB1vo9fbzlbfyG+VAKEYsLlNmNfHW0Lt4Iz52N26fpgg2E6vJQCAUy/jeNTrq2du4i0H/MK9O\nRUiKjS/D7G+bxUhlmTmvh1xZZsamIbWzpqmcWFzmwpSKXjaUepLz4XcA2Nc0O/8umH+EQZ5BKBJL\nKk4tNQ85LssEQzFVM3OVdqihOeSRvYEIF/onWd3kTN5TCVl7NTy7QkPWB/uPcmzobTrKV3F7282z\nvt9S40BieqX1FVXruLpmE+fdFzk8kNnDjctxft17EKPOSGykaVp/q81sgLiB9eUbGAmMcs59UdOa\ntVDIBqwGf8TP2yMnqLPV0uZsnfX9pjkWdiXHLmo0yAB7r2wk0r2RBnkjvd5+vnz86zlbkZQeZLvV\nkDSg+xpzD0GwmPXEZZlwlpD8He23YjVY+MWFF/BFiq/5ngpZT/87bay2MzYZyqiV7g9GGfeENNcT\nKNOkzuQJWw+O+ZHMPi76zrO6vG1ei9oE2REGeQbphVy+JZZDDoaiyJBVzD+d2opEO8hcKq1Pdo8j\ny6lwNaR7yBqKuoLai7oGfUP84PRPsRosfGrjfvS62RXdZpOeOpdt1mzkezo/gkln5Cdnn8GfYcM9\nOXaa0eAYG8s3QWz6VB3l2a5zXAkkPOn5oNANWA1HB98mGo+yu2FbxqKdxjm2PuVqecrH1Z3VOKwm\nhk90cF3TNfT5Bvjy8a8zEhjN+Hql5UmyejjvvshG1zpqbLmrtJXWp5mFXQoOk50Ptt2EPxrgFxde\n0Pw75CPbMIxcB6FMM5DVsEZlYdfQeABbcx9Azvy7YH4RBnkG6UZ4qYWslaEHWjzkueQJT0zJ+G1q\nT22AhRV1aWt7isSjfPPE44TjEfavv4cqa/a2oNY6B4FQYkCDQqWlgtvbb8Yb8fFUhr7TV3sSntY6\n22ZgugKUdcqrqdY3UWWp5M2hdwhGQ6rWrQWlwno+CroOTvUe76zPrN1c4UhMtirUQ1bGLmoNWQMY\n9Dp2b6zD44/SyTXc2LKPft8gjxx+lEP9x2aFmRVRkGFDF6Au1JpU6wpnz6te33wt1dYqXu19gz7v\ngObfIxe+LF0FuQ5CSvW11gNaud1EXaWVc72TWUVXItEYYx4fVF6mzOhgc+2Vmu4hKB7CIM8gPUy9\n1ELWypxeNR6yMtGlUA9ZlmXeuzCG3WKgrT6lzWqzJCq8teaQDXoJk1Hdx/Fn535Bj7ePaxp25ize\ngemjGNO5sWUfdbZaft17MNm7DEy1zXSxytmCNZ44aGTykAOhGLsathOOhTk+/K6qdWthviQz+7wD\ndHsus7FqXVYFJkmSaKyxMzTuJxLVXtiUDFlnmIOshr1TCk2vvzfA3Z0f5pMb7wPg2ye/z7fe/x6B\naOoz6w1EQBelL3qaSnMFm6o35L2+JSkOkv3AbdQZ+PiaO4jLcf7u2D/w4qVXilbkpUSEsnrIGRS7\negv0kCERtg6EolkPWEMTQXRVA8R1YfY07lgwPW/BbIRBnkG6V7zUQtbKBmNVURzltJswm/QF55AH\nxvyMTYbY2OZCp0uFPXWShMNq0FhlnVAtUtPz+N7ISf7j8mvU2Wq5Z+1H8r5eUey6NEOxy6AzcO/a\njyEj88TpVIFXettMahbyjBwyiWetyDIemoee5N55anlSirl2ZyjmSqe52o4sp8b9aWFsykN25elB\nzkZrXRmttQ7eOTfKpC/Mzvqt/D87H6Dd2crRwbf468OPcm7iIpAwyPrqPqJE2Nu0OzlFKhdWlXOt\nN9ds4rc2fAKjzsBPzj7DI0ce5cz4+YJ+p3TSZyGnk/KQZ+fM53JAU8LWZ7OErYfG/Em99r2Nophr\nMREGeQbpvcdLTRhECVmr8ZAlSaJuqvUpXkCl8HsXprc7pVNm06Zn7QtEVOlYu0OTfOfkDzBIej5z\nxf6c83gVWrJ4yADrXGvYVruZ7snLHOg7TCQe5Y2+I9gMVrbWbk4eKsrSPBllM/eHolRbXaytWM2Z\nifNZc5yF0ldgiDIXsXiMw4NvYjfYuLI693CMueSRxzPoWGvl2qsaiMVlDp5IhIurrVX86dbPcnvb\nzYwHJ/hfb/4zz5x/nkl/CEPtJXTouKZxh6prW82z5TOzsadhOw/v/jP2Nu5iwDfEo8e/xrdOPIE7\nVLhGuhIRMs8Y+mI1G3A5zRk92d4RHy6nWVU6aiadyTxy5sKuUyPd6BxuWiyrc6Z/BPOPMMgzmBay\nXqIestpxg3WVNsLROBMe7TnQdP3qmZTZjPhDUaKx/MIS8biMPxjN2/Lkj/j51/e+gzfi4641d9Jc\npm6YfbndRLnDxKWhzJW6H++8E4vezM/PPcvrvYfwRLzsadiBSW9MaSSnh6wt070rxdM8WGQveS4b\ncDbeHzuFJ+xle/2WvGHJuVRaj3mCWM2GOa1998Y69DqJ197tT+aN9To9d3bcygNb/4AKczm/uPgi\nB6M/QGfzsr5iI06TupGvVlPCEObSjU7HYbRz//q7+cL2z9FS1sSRwTf5y4N/x8s9r+dsncuGLxjB\nbskcEWqstjPhDeMPTt+H3N5wwYezepcNh9WYtbCry/cWAHvqdhZ0fUHxEAZ5BkrI2qDX4Q9GC5o+\ns1goOWS1G2Gdq7A8ciQap+vSOA1VtoyVtA4NrU/+qcrwXKIgY8Fx/v7Nf+a8u5vtdVdzfbM2wftV\ndWWMe0IZw+gV5nLuaL8FX9TPj878HIC9U4VBmULWSQ956llvqb0Si97Mwf5jBW3OmfAHI0zMYQPO\nxhvJcPW2PK+Expr8ylHZGJsMFZw/Viizmbh6TTU9w75ZE7vanau4p/5TVMU7COoSXp+WymC1IeuZ\ntDlbeXD7H3Pv2o8hSRI/PP0z/seRrzAezC9NmY4vEMlawJjpIDTX9IUkSXQ2lzM6GWJscrpsrD/i\nZ0R3jnjQys6WTVmuIFgohEGegeIh11ZakUmFgZcCAQ0ha0h4yKBd0/psr5twJJ4xXA3axEEyiSSk\nc9nTx/88+g8M+Aa5oWUvn9x4n2Z93RYlj5zFS76++Voa7fXIyGxwraXWVg2A16/0uGbOIQOY9Ca2\n1m5mPDTB6fFzmtaVjbkU8GTDE/by7sj7NDkaaHE05X2902bEYTVq9pADoSiBkHZRkExcO1Xc9do7\n/cTicU5cHOPfn+3iP//D63zlh130HO1EurSV1dIuNtWuUX1di4oq62zoJB3XNV/DF3f/GTvrt3LZ\n28d3u36kWiAmX0Qo03CPYhT4JfuRZ4StDw28iSzFMLnbsZrmZ6KYQD2inG4GiodcW2Glb8SHL5j9\nNFtqaGl7gsShA2BoTJuH/F6Gdqd0tMhnZqs4hUQ/8L+++x1CsTB3r7mTG1uv07ROBaXS+vKgN+Ow\ndr1Oz/719/CtE49z26obk1/3+BNDCwz61Ll1pocMibD1gf7DHOw/ynpXZ0FrTKd3HiqsjwweJy7H\n2d2wXdWBRtG0PnN5gnAkhsmobnKXkj8utKArnSs7XJTbTbz+7gCHTw4lIy5Om5EbtjSxfV0Na1sr\n0Ou0+RX5+pDVUGZy8Dsb7sUT9nJy7DTHht5me93VeX8uX0QoqWmdVmldDAnVVGGXm10b64BEp8Qr\nPQeQ4zrqWVfwtQXFQ3jIM1A8tpop4YylVNhVSA4ZtHvIJy6MYdBLrGupyPh9Lb3IviyymQf7j/JP\nb3+TqBzjM5t+s2BjDIleZMhc2KXQXt7Kf73mITorO5Jf8/jDyfC7gsWsR2J6uLOjfBW1tmreGn63\nKAPuU0MliqdhfbD/KDpJx4469QMDmqrtyGirtJ5ry1M6ep2OfZsbCUVi6HUSN25t4sH7t/ClP9rL\nb9+2jg1tLs3GGBJa1lCYh5yOJEnct+4ujDoDPzrz84wiMzPJFxHKpGldDAnVVXVlGA26aXnkU+Nn\nGQ6MEBurp6FCFHOVAsJDnoEvGMFqNuC0G5P/XipozSGX2YxYzXpNOWS3L8ylQS8bVlViNmX2mrSo\ndc0UBZFlmWcvvsTTF57HZrDy+1d9as4zWWsqrFhM+qwh60zEZRlvIEpt5fRNUCdJWMyGaakMSZK4\nvvlafnj6Z7zQ/TIf77xzTuvtLZKGdSgWZiI4Qbenh15vP5trNlFmUm/k0yutV9WrK5iaa8vTTD5y\nbRu7NtbR4LJNa6+bC8miriKko6qtVXyo7RZ+dv6X/PTcL9m//u6cr09GhLJ0FVhMBqqclmm5+94R\nH1VOS7J/Wg2esJfvdv0Ik85Ig72Oensdzc0yFy9NJgfQ/Lr3IACxoRbqVllVX1swfwiDPAPfVH5H\nUdFZSuIgqRyyuvBiYuqTjd5hH3FZzjmyUeH9i9mrqxW0eMjps5Bj8RhPnPoJB/oP47JU8rnNn6He\nXqfmV8mJTpJoqXVM5b7VhV/9wShxWZ5W0KVgMxtmFQRd27iLF7tf4dXeA9zYui+r6IYa+jRuwOFY\nmJd7XmckMMp4yM1E0M1EyI0/Ov2glWmQRC4KqbROtjwVwUOGRHFlsXuxCy3qysZNrddxZPA4r/cd\nYlf9NlZXtGV9bcpDzv7eNtXYeefcaPJvY9IX5qrVueVA04nLcb598vu8P3pq+jdqwVwt8d8Pv0lb\nRQPvjJzAKVUz6K1IRssEi4sIWc/AF0iIVCghpaUkn+kPRTHodRgN6gwyJBS7orF4Uu4wHydy9B8r\nJD1kFYcZXzACUozuyPs8cuRRDvQfpqWsiS9s+6OiGGOF1toyZBl6MqggZSLZg5zBIFtneMiQUHb6\nUPvNROJRnrv4q4LX6Q1EcPvCNNWoN0IvXnqFn537Ja/3Heb90VOMBSdwmp1scK1lT8MOPtR2M5++\nYj+bqvKrWKXTWKO9F1mp4i1ksMRCoUR25hqyVtDr9Ny//uMAfO/Uj4nGs+8ZKVGQ7HUp6ZGJ3mHt\n/egv97zO+6On2OBay1/ueYg/3PwZ7lpzB2vtVyL7nUxG3Bwffpe4HMcVXg9ISeU+weIiPOQ0wpEY\n4Wgch8WQzGkutIcsyzIXBzy01jk058f8oZjq/LFCeh65qjx3mFGWZU5cGMNpM9Jcmz30qRR1efOE\nrCfDHk6GDmG5+gS/Gg6jk3Tsqt/GJ9Z+tOizWFuUPPKQh45GZ97Xp1qeZouP2CwGeodjs6IKu+q3\n8UL3y7zed5ibW6+nypr90JINrUMEwrEwr/QcwGaw8sDWP8BlqcRapGfntJkosxmTOspqGCtiUdd8\noZMkLCZ9UULWCh3lbext2s1rvQd56dKr3NZ2Y8bXJQdLWIy4Qx4CUf+sg+e0yMRU9bbaz8MlTw8/\nPfsLyowOfmfjvThNZVRZXVxRtZ49tRH++NFf076qgt+9q4PJsIfvPTWEhDtZ4ClYXISHnEZyLJrV\nmAxZexc4h9zVPc5f/ftRDp4Y1Pyzgan8txa09CJfGvTi9oW5ot2VM7xtt+Zue+rx9PGd93/AX7z+\n1/TojoMks69+L3+55yF+Z+O98zIYfVVapbUaMql0KdjMBmRm5yD1Oj13tN9CTI7xiwsvFrROrRXW\nB/qP4I34uK75GpocDUUzxgpN1XZGJoJ5B9wrjHtC2C2GrPUFpYLVbCCgUhhELR/tuJ0yk4NfXnyR\nYX9m5bZETYrMhfB7/NeDf8sjhx+d1cec9JCHfakKaxURk2A0xL+deJyYHEsa43TsFiNNNXbO901S\nZnSyytnC0HgAl9OsKaommD+EQU7DlzYGUMnxLHSVdd9URevwhPahD/5QTHUPskLSQ1Yx9elI1xAA\nW9fW5HydQa/DbjHMClkn5tt+g0eOPMrBgaO4rJVUe7YTfOt6Pt55B5WWzFXbxaC+yoYE9I+qDVln\n95DT5TNnsrVuM432eg4NHGPAN6R5nckKaxUbcCwe46VLr2LUGfhA87Wa76WGxmSltbrnNjYZPgux\ncwAAIABJREFUpLKEvWMFi0mvSjpTCzajld/o/AiReJQnTj2ZsTd5JDCGad0RXh55lkg8SlSOcWDG\nCM/GKsVD9tI34kMCGqryfx5+eOZnDPlHuKnlOjZWZW5j6mwqJxyJc3nISygcY8IbnlW4KFg8hEFO\nI73gIlnUtcAestuXCPmpUblKJxKNEY3FVRd0KSR7kfN4yLIsc6RrELNRz5Ud+QtMHDbTtCrrrrEz\nfOnYP3F6/CzrKtfw2as+zV/s+gL68XaMOpPqPtdCMRv1VJVbkgeefOTKIdsy9CIr6CQdd3bciozM\nMxee17zO3hGv6g342NDbjAXH2dOwU1P1tBZyTSCaiT8YJRiOFaXlab6xThXmqRX0yITbG+Jfn34f\ntzdVf7G1djMbXevoGj/D0cG3kl+Py3Fe6TnA2/on0ZePsa58Lf9l1+ex6M0c6Ds8bZKU2aSnujxR\nad074qO6wjJL93omRweOc7D/KK1lTXxk9Qezvi5dIERpd1RGsQoWH2GQ00iGrC1GLCY9ep204AZ5\nwhuetha1+KdO+1YVQxrScViN2MyGvL3IFwc8DE8EubqzWpXxLLMZ8QYixGWZQ/3H+Me3/zfReJTP\nXLGf/3vL77GpegM6Sbegwiv1VTYmfWFV72lOD9mSu0r3quorWFXWwptD79Dj6dO0xj6VG7Asy7x4\n6RV0ko6b5tCjnQ8tQybGPaVf0KVgNRuIxWVVeuvZeP29AQ68N8DhrlQkRJIk7l13F0adkR+feQpf\nxM+wf5SvHP8GPzj9U5B1hM9dxe9d+SnqbDXsqN/KRMjNidGuadduqrYz6Y/g8Ufy9qOPBEb53qmf\nYNKb+PQV+zHk0Clfkxw0MZE8hNdWiPxxqSAMchrpg8MlScJuMSx4yNo9ZZC1eshaW54UJEmizmVl\neCKQU7dbCVfvWF+r6rplViOyLPP02Rf49snvY9ab+aOrf5dtM9SMvIH8gyWKhRIKVCN04U0Olsjh\nIWcxyJIk8eGO2wB4+sJzqtc36Q8zqWIDhsSgiF5vP1trr6K6gOIxtTRNaVqraX0aS7Y8lX7IWulF\nnkvY+uJAQmhmZodCtdXFHe234Il4+ee3v8l/P/wlzkycZ3PNJlx9t6FzNydb2vY27gISYz/TaUxL\nWeSqJ4jFY/zbie8RjAW5b+1d1Npyp5Oqyy1UOEycneYhC4NcKgiDnEaqqMsw9V/jwoesp8JfWqu7\nlfCpzazd26yrtBGNybOE5xVkWebIySEsJj1Xdqjb/B02A8a293nu8otUmiv4/LY/nKaCBRCLxwmE\nogvmITdUJUJz/SqMS86QdR4PGWC9q5PV5e28O3KSC+5uVetT8sdqCrpe6H4ZgJtbP6Dq2oXisBpx\n2k1cHvLmDe8uhZYnhZRaV+EH7ov9kwCMZvi7ubFlH432ei5MXsKsN/GZK/bzu5t+m6BfP+0A2lzW\nSJuzlfdHTzEaGE9+Pb2qOleF9dMXnufi5CV21G1hZ/3WvGtODJqowO0LJ1sYRQ9y6SAMchrpRV3K\nf32BueWZtDLhm5uHbNXoIUMqj5yt0vpCv4fRySBbOqtVVWOGYmEumH+FofYy1aY6vrD9czRk6ClO\nTxEsBA0aPGSPP4LZpM/4+2bSs56JJEnJXN5T59V5yWqHSlxwX+LMxHk2uNbSonIM5VzYuKqScU8o\n6RFmI6VjXfoGOaVnXZiH7A1EGHEnDHGmg6xep+d3r/xtPtR+C/9l1+fZVnc1kiThDcw+gO5t2o2M\nzIE0Lzk9SpLtgNY1doYXul+m2uLi3nV3qR66ooStuy5NIEkpmWDB4iMMchozdWbtFgNxWSZYJAGB\nfMTicTy+QnPIio51AR6yK7em9ZGuRAvWjvX5hTomwx4effNrjHKJmLuKD7ruzapapUa1qJgoG5ua\nimFPIJKx5QlmT3zKxpqKdja41nJq/Cynx8/mvafaqT4vXHoZgFtXfSDvNYuBkqY4cjJ31XhSNnMp\nhKyViU8F9iJ3px1OMnnIALW2Gu5ovyVZcKdEhGYeQLfVXoXVYOFA/5FkcZfSFSBJqchOOv6In2+/\n/wSSJPHpTfs1tbutbU51M1Q5LRgNwgyUCuKdSMM7ZQQdllTIGhZOHGTSF0HxxQOhKLG4+oKTuXjI\nqdan2R5yorp6CKtZn1OdC+C8u5u/P/qPXPL0sNpyBeHT2wiGsp/a1agWFROHNTFSMJ+HLMsyHn84\nY0EX5G57momSS37q/HN5Iy29I76sG7DCgG+Id4ZPsMrZQmfF6rz3LwabOlxYTHqOdA3m/B2UwRLF\nGL043yg53EJD1hcHEuFqSUrUfagpDlMO2TM9ZJPexM76bUyGPbw78j6Q6AroaHLS0ejMWET55Nln\ncIc93NF+C23OVk1rb661J4sGhUJXaSEMchqK4bWlhaxh4eQzlZan5Ho03HdOOeSkOMhsQ3W+b5Kx\nyRBbOmuynqS9YR+Pnfwhf3/sHxkJjnF7283cUn8HyLqcAybyCe3PB41VNobdASLR7FGPYDhGNJZZ\nxxrU5ZAVVjlb2FyzifPubo73n8j6OlmW6RvxUVNhzVnF/uKlV5CRubX1A5rnQheK0aBnS2c1o5Mh\nzk/lTTMx7gnhsBrnvYWtGCgH10JD1kr4fm1zBTIw4ckvPZsrIpSpuOsL927hC/fOns7VNXaGN/qP\n0Oxo5JYCagj0Oh2rmxJqdbWi5amkEAY5DV8wgtmoTxoe5Q9nodS6lJan5Ho0eOb+OXjIdosRu8WQ\nMYecq7o6Lsd5rfcgf3nw73ij/wiN9nr+dOtnubPjVpy2hJeUa8BEvlF080FDtR1ZhoEcM6BzqXSB\nuhxyOne234qExHff+QnhWOYDyqQ/gjcQyZk/ngi5OTzwJrW2aq6quULVvYuFkq7IFraWZZmxydCS\nyB9D2oCJQj3kfg9OmzGZj80Wtk4nXQlwJo2OelaXt3Fy7HRS5cts0s9SPAvFwjze9SN0ko7f3HAP\nel1hh581TYl1i4Ku0kIY5DR8gei00+tCT3xSKqzLHabketQSCBaeQ4ZEHnlkIjAtTB5PhqsNs8LV\nlyZ7+J/H/pHvnXqSqBzl7jV38tCOP0mOSlQzgjG9zWyhSBV2Zc8j5+pBhlRrmdr8Y6Ojnr1Nu7ns\n7uOxkz/MGPbtUzFE4FeXf01MjnFz6/XopIX9072i3YXVbODoqSHiGdbvD0UJRWJLIn8MaSHrAnLI\nHn+Y0ckgq+qdyd93TMVwlnQd60zsbdoNwOszWqDSeer8s4wGx7m59Xpay5q1Lj3JdZsb2b6uRnUb\no2BhEAY5DV8wMs04JOUzFypkPeUhK16SFs98Lh4yJHJJsbjMaNrGcr53knFPiK1rqzHoEx8Vf8TP\n90/9hP9x9Kt0T15mW+1mHt79Z9zYet2007pizHJViydz9gtU1AVprU858sgpg5x54zQa9Bj0OlU5\nZIV7Oj/M+urVHBt6m2czTIPKV2HtjwR4vfcQ5aYydtZvU33fYmE06NjaWc3YZIjzfbPD1kov7lLI\nH0NayLqAgk2loKutvoyqKVUyVR5ynojQlporsRtsHOw/mnFi1AV3Ny9ffp1aWzW3t92sed3puJwW\n/vCuK5fM+7VSEAZ5imgsTjAcm9Yj6FhgD1lpeVJaHrTcNyUMUqCHPBW6GkrTtD48o7p6IuTmvx36\ne17tfYNaWw1/fPXv8plNv5mxitpo0GEx6UsvZJ00yLk85MT74MhikCGRR/ZryD8adAY+f+3v4bJU\n8vSF53hr+L1p389XYf3r3jcIxkLc0LIPYw4lpvlkx4bs1dZKQddSkM2EVNuTlkOVwgXFIDeUpTxk\nLTnkLB6yUW9kV8M2PBEvbw9PrzeIxKM81vUjZGR+c/1vYNIv3N+MYOEQBnkKf4b8Tmom8sKGrJXB\nAlpzyBJgKdBDrp0x9SkuyxztGsJuMbCxrRKAn579Je6wh1taP8D/u/MB1rs6c16zzGbMHbJWiroW\n0CC7nBZMRh19Izk85EDukDVMaSFr/FyUW5z8wVWfwqQ38e/vPzFNVjNXhfV4cIL/6HkNq8GSDGsu\nBhvbXNiyhK2TLU9LYLAEpP5OChnBqAiCtNU7qUqGrPN7yGoiQsnirt6D077+3MVfMeAb5LqmPcm0\nkGD5IQzyFDNFQRL/v7ATnya8YfS61LBwTSHrYBSL2ZBzLGIuZk59OtvjZsIbZsvaGgx6HecmLnJk\n8M2keH0uvVwFh9WExx/J2irjTXoMC+fx6SSJBpedwXF/VqnQXCpdCjazNg9ZocnRwCc33kc4FuZr\n73yLPvcYr7zVy6UhL7WVtmlCJLIsc6DvMP/t0JfwhL3c0LKv6OMVtWDQ69i6toZxT4hzve5p30vO\nQV4iHnKql7yAkPWgh3K7iQqHCavZgNVsKErIGqDOXktnRQenJ84x6B8GElPSnuv+FZXmCj6y+nbN\n6xUsHYRBniLVE5tW1LXQHrIvRLnDlPQYNRV1haKadazTSRrkKQ9Zqa7eub6WuBznh2d+BsBvrP2o\n6oKiMpuRWFzOuun5AlFMRt2Cz2JtqLYRicYZybKJ5ivqgkRhVzQWz9k+lY0O21qusOxhPDTBX738\ndf79uZOEwjG2r0vpEI8Fx/nHt/833+36ESCzf/3dfGiOecNikC1sPT65dHqQIVXUFdRYZT3pCzM2\nGaKtvizZduZymlV5yJkO/ZnYpxR39R4iLsf57skfEZfj3LfurkU9kAnmn8VJRpUgmXpirWYDEguT\nQ5ZlGbc3TGtdWUEHAX8omiwwKQSbxUCZzZj0HI+eSoSr16+q5I2+I1z29LKzfisd5W2qr5mstA6E\nk7276XgDCzfpKZ0GV0rTOtOkm6RBzrE2ZaqWPxSjXMWBwhuIcPj1C7x89BKnLk8gy06Mq+sxVA2w\nds9l/tOV91JTaUOWZV7rO8RPzz5DMBZio2sd+9ffPa+zorWwYVUldouBI6eGuO/mzmREJjlYYomE\nrHU6CbNR+0xkpf94VX1Z8mtVTgu9wz78wWjGz7lCsso6TxHj5ppNOIx2DvYfxWa00e25zI66rWyq\n3qBprYKlh/CQp8gUTtJJEjaLYUGqrL2BCLG4TIXDlDxBq9WzjssywVA0GYYrlNpKKyMTQboujeP2\nhtm2roZwPMjPzz+LWW/ioxrDZYqHma2wa2ZV+0KRT9PaGwhj0CeK0rKhRCP8Kg9NX/7h23ztyXfo\nujRBR6OT+27s5P+/+f+itayJy9GTvOs9xmhgjK++9S88cepJJEnitzZ8gj/c/JmSMcaQClu7vWHO\n9qTC1mOTQZw245KSYbSY9Zr7kBWFrrYGZ/JrqcKu3F6y2oiQQWdgT8MOfFE/T51/FofRzj2dH9a0\nTsHSRHjIU6QGHUx/JHarcUGEQZSWp3KHGaNBh9moVx2yDoZiyKTEDgqlrtLGud5Jnj10CUhUVz9z\n4QW8ER8fW/2hrJrU2cjVi6xUtS+Kh5xH09rjj1BmM+ZUwlKq2dV4WLIs0zPso6HKzufv3TytV/f3\nr/oUf3vkKzx55mmeOv8c4ViYTVUbuH/9xzU/74Vix4Zafv1OP0dODrG2pQJZlhn3hJIHnaWC1WRQ\nfaBSuNifanlSUCJTY5NBmmuyj87UMvv72sZdSc3yT6z9KA7T0nq2gsJYOsfZecYXyFzxu1ATnyam\nZDMr7Amv0m41qPaQky1PcyyOUorJ3rswlhi7VxVMtDhZq/lAy17N1yuzZveQsx2AFoK6Sis6Scrq\nISsGORdKH6s/lP898gUTohktdWWzhDMqzOX83pWfRK/TY5D0fHLjffzBVZ8qWWMMsL61EofVmKi2\njsv4glHC0fiSKehSsJr1BDT2IXcPeqhwmKhwpH5X5T0dzSMO4g2ojwjV2Kq4pfUD3NCyl621mzWt\nUbB0ER7yFNkKLuxWA9FYnHA0nhRknw9SHnLCiDksRoYmsss7ppMSBZmjQU7Ttd22rponzz1NXI5z\nd+eHC+p9zeUhZzsALQQGvY6aSiv9oz5kWZ7mCYcjMUKRWM6CLkgpoqnxkEenxvTVZhHyby9v5eFd\nf4bVYMZmLH0pQyVs/erbfZy+PJE8CC6VlicFi8lAJBonGosnhW9yMeENMe4JcfW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"text/plain": [
"<matplotlib.figure.Figure at 0x1fc873ca240>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"monthly_stoerungen_without_updates = stoerungen['Type'][~stoerungen['Type'].str.contains('aktualisierung') & ~stoerungen['Text'].str.contains('10-minuten-takt')].groupby(pd.Grouper(freq='M')).count()\n",
"monthly_stoerungen_without_updates.plot(label='Anzahl')\n",
"monthly_stoerungen_without_updates.rolling(6).mean().plot(title='Anzahl der Störungen im gesamten S-Bahnnetz (pro Monat)', label='Trendlinie')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Störungen nach Jahreszeit"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Von der Bahn so kommuniziert und eine weitverbreitete Ansicht ist, dass die Zahl der Störungen im Winter nach oben geht und im Sommer eher niedrig ist (Weichen frieren ein, Oberleitungen haben Probleme wegen der Kälte, etc.). Dies können wir an den Daten nun direkt überprüfen. Wir sehen uns dafür die Anzahl der monatlichen Störungen an und teilen die Monate in Kategorien ein.\n",
"\n",
"Wir richten uns nach dem metereologischen Beginn der Jahreszeiten. Das ist damit folgende Einteilung.\n",
"\n",
"| Frühling | Sommer | Herbst | Winter |\n",
"|-------------------|----------------------|------------------------------|-------------------------------|\n",
"| 1. März - 31. Mai | 1. Juni - 31. August | 1. September - 30. November | 1. Dezember - 28./29. Februar |\n",
"| März, April, Mai | Juni, Juli, August | September, Oktober, November | Dezember, Januar, Februar |"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {},
"outputs": [],
"source": [
"seasons = {\n",
" 'Frühling': [3, 4, 5],\n",
" 'Sommer': [6, 7, 8],\n",
" 'Herbst': [9, 10, 11],\n",
" 'Winter': [12, 1, 2],\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 112,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Durchschnittliche Anzahl</th>\n",
" <th>Monat</th>\n",
" <th>Jahreszeit</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Jahreszeit</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Frühling</th>\n",
" <td>86.933333</td>\n",
" <td>4</td>\n",
" <td>Frühling</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Herbst</th>\n",
" <td>93.650000</td>\n",
" <td>10</td>\n",
" <td>Herbst</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Sommer</th>\n",
" <td>100.733333</td>\n",
" <td>7</td>\n",
" <td>Sommer</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Winter</th>\n",
" <td>91.416667</td>\n",
" <td>5</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Durchschnittliche Anzahl Monat Jahreszeit\n",
"Jahreszeit \n",
"Frühling 86.933333 4 Frühling\n",
"Herbst 93.650000 10 Herbst\n",
"Sommer 100.733333 7 Sommer\n",
"Winter 91.416667 5 Winter"
]
},
"execution_count": 112,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"stoerungen_for_month = monthly_stoerungen_without_updates.groupby(by=[monthly_stoerungen_without_updates.index.month]).mean().to_frame()\n",
"stoerungen_for_month.columns = ['Durchschnittliche Anzahl']\n",
"stoerungen_for_month['Monat'] = stoerungen_for_month.index\n",
"stoerungen_for_month['Jahreszeit'] = stoerungen_for_month.index\n",
"\n",
"for season, months in seasons.items():\n",
" stoerungen_for_month.loc[stoerungen_for_month['Monat'].isin(months), 'Jahreszeit'] = season\n",
"\n",
"stoerungen_for_season = stoerungen_for_month.groupby(by='Jahreszeit').mean()\n",
"stoerungen_for_season['Jahreszeit'] = stoerungen_for_season.index\n",
"stoerungen_for_season"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {},
"outputs": [
{
"data": {
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ttxo+fLji4+M1Z84cFp4BAKASTIv84MGDGjNmjLKyslzbLl68WKXBsrOztX//fm3cuFHp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\nPxoMIjjpVMYsAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1fc835ae2e8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots()\n",
"sns.barplot(x='Monat', y='Durchschnittliche Anzahl', data=stoerungen_for_month)\n",
"ax.set_ylabel('Durchschnittliche Anzahl an Störungen')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 113,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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DFgAASgnLRk5LS9PMmTPVsWNHdenSRXFxcTp+/Lg7sgEAAAuWRX7PPfdIkmrWrKmjR48q\nICBAubm5Lg8GAACsWR4jb9GihUaOHKmoqCg999xzOnTokHx9fd2RDQAAWLAs8sjISJ06dUpVq1bV\nvHnzlJycrOHDh7sjGwAAsGC5a/2FF15w3EK1UaNGGjx4sF555RWXBwMAANYsi/zAgQMaMmSIdu3a\n5Zh26dIll4YCAAAFY1nklStX1rvvvqvZs2dr6dKlknTbD08BAADFw7LIDcNQtWrVtGbNGu3bt0+j\nRo3K9zhTAABQciyLvHz58pIkf39/vfXWW6pRo4bLbt8KAAAKx7LIV6xYke/9mDFjlJiY6LJAAACg\n4CwvP9u1a5fmz5+vn3/+Od8u9YSEBJcGAwAA1iyLfNq0aYqOjladOnU4yQ0AgFLGssiDgoLUoUMH\nd2QBAACFZFnkTZs2VWxsrNq2bZvv1qzNmzd3aTAAAGDNssgPHjwoSTp8+LBjmmEYWrVqletSAQCA\nArEs8ri4uN9M2717t0vCAACAwrEs8psuXryoDRs26MMPP9S1a9e4BA0AgFLAssiTkpL0wQcfaNu2\nbfLw8NDf/vY39ezZ0x3ZAACABac3hFm5cqW6d++u1157TfXq1dPHH3+sihUr6oknnpC3t7c7MwIA\nACecjsjnzZunjh07auDAgWrWrJkMw+A6cgAAShmnRZ6YmKiPP/5YsbGxunDhgrp3767s7Gx3ZgMA\nABac7lovX768wsPDFR8fr2XLlkmScnNz1bNnT73//vtuCwgAAJyzfGiKJNWvX1/jx4/Xrl27NHLk\nSO3atcvVuQAAQAEU+PIzSfLy8lKXLl3UpUsXV+UBAACFUKAROQAAKJ0ocgAAbKxARb5lyxbNnz9f\nV65c0UcffeTqTAAAoIAsi3zOnDnauXOnPvvsM12/fl0bN27UjBkz3JENAABYsCzy3bt3a/bs2fL1\n9ZW/v79WrFjBfdYBACglLIvcw+PGj9y8q1t2drZjGgAAKFmWl59169ZNo0eP1qVLl7Ry5Upt3ryZ\nh6YAAFBKWBb5sGHDtGvXLlWpUkXnzp3TiBEj1KFDB3dkAwAAFgp0Q5gqVaqoU6dOMk1TkpScnKzm\nzZu7NBgAALBmWeQTJ05UYmKiqlev7phmGIZWrVrl0mAAAMCaZZF/+eWX+vzzz+Xj4+OOPAAAoBAs\nTz9/4IEHdO3aNXdkAQAAheR0RP7qq69Kkq5fv67evXurWbNm8vT0dMyPjY11fToAAHBLTos8JCQk\n3/8BAEDp47TIn3jiCUlSRkaG/v73v2vgwIH64YcftHbtWg0bNsxtAQEAgHOWx8hffvllnT9/XpLk\n5+envLw8jRs3zuXBAACANcsiT01NVWRkpCTJ399fkZGROnXqlMuDAQAAa5ZFbhiGUlJSHO9PnDgh\nL68C3UcGAAC4mGUjR0VF6bnnnlPlypUlSWlpaZo1a5bLgwEAAGuWRd6qVSvt2LFDx44dk5eXl4KD\ng7k5DAAApYTTIl+0aJFGjBjhuJ7817iOHACAkue0yBs1aiSJ68gBACjNnBZ5/fr1lZqaqtDQUHfm\nAQAAheC0yMPDw2UYhuPRpb9kGIYSEhKKvNKffvpJffv21fLly+Xl5aXo6GgZhqE6depo0qRJ8vCw\nPJkeAADoFkW+fft2SVJ6errKly+fb96ZM2eKvMKcnBzFxMSoTJkykm4cax89erRCQ0MVExOjhIQE\nde7cucjLBwDgbuJ06Hvu3DmlpqYqPDzc8To1NVWnT5/W0KFDi7zCmTNn6s9//rPuu+8+SdKhQ4cc\nx+HDwsK0Z8+eIi8bAIC7jdMR+cKFC5WUlKTz589r4MCB//kFLy+1b9++SCuLj4/Xvffeq7Zt22rp\n0qWSJNM0ZRiGpBu3gL18+bLlcoKCysnLy9Py5+A+lSoFlHQEFBHbzt7YfvZVXNvOaZHfvLxs6dKl\nv3lISnZ2dpFWtnHjRhmGoS+//FJHjhxRVFSULl686JifmZmpwMBAy+WkpWUVaf1wnQsXrL+AoXRi\n29kb28++CrvtnBW/5Vllvz6pLS8vT3/6058KtfKb3n//fa1evVpxcXFq0KCBZs6cqbCwMCUlJUmS\nEhMT1axZsyItGwCAu5HTEfmgQYP09ddfS7pxKZrjF7y81LFjx2ILEBUVpYkTJ2revHkKDg5W165d\ni23ZAADc6ZwW+apVqyRJ06ZN04QJE4p9xXFxcY7Xq1evLvblAwBwN3Ba5Dt27FCHDh3UqFEjffTR\nR7+Z36dPH5cGAwAA1pwW+bfffqsOHTo4dq//GkUOAEDJc1rkI0eOlMTDUQAAKM0sH2O6a9cuLViw\nQJcuXcp3u9bbuUUrAAAoHpZFPm3aNEVHR6tOnTqOG7cAAIDSwbLIg4KC1KFDB3dkAQAAhWRZ5E2b\nNlVsbKzatm0rX19fx/TmzZu7NBgAALBmWeQHDx6UJB0+fNgxzTAMx3XmAACg5FgW+S9v3AIAAEqX\nAo3Ily9frrS0tHxnrTMiBwCg5FkWeVRUlMLDw1W7dm3OWgcAoJSxLPIyZcrkex45AAAoPZwWeWpq\nqiSpQYMGWrlypTp16iRPT0/H/CpVqrg+HQAAuCWnRR4eHi7DMGSapr766qt8x8QNw+DObgAAlAJO\ni3z79u2O1zk5OfL29lZOTo6ys7Pl5+fnlnAAAODWPKx+YOvWrerbt68k6dy5c3r88ce1bds2lwcD\nAADWLIt88eLFWrFihSSpevXqio+P16JFi1weDAAAWLMs8pycHFWsWNHxvkKFCvmuJwcAACWnQPda\nHzNmjHr16iVJ+uSTT9SkSROXBwMAANYsi3zSpEmKi4vTunXr5OXlpebNm6t///7uyAYAACxYFrmP\nj4969eqlIUOGKDk5WceOHVNubq58fHzckQ8AANyC5THySZMm6a233tJ3332nV155RYcOHVJUVJQ7\nsgEAAAuWRf7tt98qJiZGW7du1Z/+9CdNnz7dcdc3AABQsiyL/Pr168rLy1NCQoLCwsJ05coVXbly\nxR3ZAACABcsi79Onj9q0aaOqVavqkUceUd++ffX000+7IxsAALBgebLbs88+q0GDBjkemPL+++/r\n3nvvdXkwAABgzbLIDx48qOXLlystLS3fjWB++RAVAABQMiyLPCoqSuHh4apdu7YMw3BHJgAAUECW\nRV6mTBkNHDjQHVkAAEAhOS3ym5eYNWjQQCtXrlSnTp0cx8klqUqVKq5PBwAAbslpkYeHh8swDJmm\nqa+++irfMXHDMJSQkOCWgAAAwDmnRb59+3bH65ycHHl7eysnJ0fZ2dny8/NzSzgAAHBrlteRb926\nVX379pUknTt3To8//ri2bdvm8mAAAMCaZZEvXrxYK1askCRVr15d8fHxWrRokcuDAQAAa5ZFnpOT\no4oVKzreV6hQId/15AAAoORYXn722GOPacyYMerVq5ekG7vamzRp4vJgAADAmmWRT548WXFxcVq3\nbp28vLzUrFkzDRgwwB3ZAACABcsif+GFF7R8+XINGTLEHXkAAEAhWB4jv3r1qs6dO+eOLAAAoJAs\nR+QXL15Ux44dVaFCBfn6+so0TW4IAwBAKWFZ5O+++647cgAAgCKwLPLk5OTfnV61atViDwMAAArH\nssiTkpIcr3NycrR37141a9ZMffr0cWkwAABgzbLIY2Nj871PT09XZGSkywIBAICCszxr/dfKlSun\ns2fPuiILAAAoJMsReUREhAzDkCSZpqkzZ86oXbt2Lg8GAACsWRb5iBEjHK8Nw1BQUJBq167t0lAA\nAKBgLHetly9fXhcvXlRWVpbuv/9+ShwAgFLE6Yj8p59+0siRI3X8+HHVqFFDhmHof//3f9WkSRPN\nnTtXgYGBhV5ZTk6Oxo8fr7Nnzyo7O1svvviiateurejoaBmGoTp16mjSpEny8Cj0oXsAAO5KTot8\n6tSpatq0qVauXClvb29JUnZ2thYtWqTp06drxowZhV7Z5s2bVb58ec2ePVvp6enq06eP6tevr9Gj\nRys0NFQxMTFKSEhQ586di/6JAAC4izgd+qakpGjMmDGOEpckHx8fjRkzRocPHy7Syrp166ZRo0ZJ\nunHinKenpw4dOqSQkBBJUlhYmPbs2VOkZQMAcDdyOiL39fX93emGYRR517efn58kKSMjQyNHjtTo\n0aM1c+ZMx1nxfn5+unz5suVygoLKycvLs0gZ4BqVKgWUdAQUEdvO3th+9lVc285pkd8s18LOs3Lu\n3Dm99NJLGjBggHr16qXZs2c75mVmZhbo2HtaWlaR1w/XuHDB+gsYSie2nb2x/eyrsNvOWfE7LfLj\nx4+rU6dOv5lumqYuXLhQqJXf9OOPP+q5555TTEyMWrZsKUlq2LChkpKSFBoaqsTERLVo0aJIywYA\n4G7ktMj/+7//u9hX9vbbb+vnn3/W4sWLtXjxYknSX//6V02bNk3z5s1TcHCwunbtWuzrBQDgTuW0\nyF3xdLMJEyZowoQJv5m+evXqYl8XAAB3Ay7YBgDAxihyAABsjCIHAMDGKHIAAGyMIgcAwMYocgAA\nbIwiBwDAxihyAABsjCIHAMDGKHIAAGyMIgcAwMYocgAAbIwiBwDAxihyAABsjCIHAMDGKHIAAGyM\nIgcAwMYocgAAbIwiBwDAxihyAABsjCIHAMDGKHIAAGyMIgcAwMYocgAAbIwiBwDAxihyAABsjCIH\nAMDGKHIAAGyMIgcAwMYocgAAbIwiBwDAxihyAABsjCIHAMDGKHIAAGyMIgcAwMYocgAAbIwiBwDA\nxihyAABsjCIHAMDGKHIAAGyMIgcAwMYocgAAbIwiBwDAxihyAABsjCIHAMDGKHIAAGyMIgcAwMYo\ncgAAbIwiBwDAxrxKOoAk5eXlafLkyUpJSZGPj4+mTZumGjVqlHQsAABKvVIxIt+2bZuys7O1bt06\njR07VjNmzCjpSAAA2EKpKPK9e/eqbdu2kqQmTZro3//+dwknAgDAHgzTNM2SDvHXv/5VXbp0Ubt2\n7SRJ7du317Zt2+TlVSr2/AMAUGqVihG5v7+/MjMzHe/z8vIocQAACqBUFPljjz2mxMRESdL+/ftV\nt27dEk4EAIA9lIpd6zfPWj927JhM09T06dNVq1atko4FAECpVyqKHAAAFE2p2LUOAACKhiIHAMDG\nKPJidubMGT322GOKiIhw/PfGG2/k+5kLFy4oJiZG+/bt09KlSyVJSUlJioyM/M3yIiIidOLECcXH\nxyshIcEtnwE3/N42mTNnjuLj4y1/Nz4+XnPmzCnQelJSUpScnFykjPiPpUuXavDgwQoPD1dERAT3\no7CpZ555RgcPHpQkZWdnq2nTpnrnnXcc8yMiIjRkyBBlZ2c7Xcbnn3+uH374weVZSwuu8XKB2rVr\nKy4uzun8SpUqacqUKZKkRx99tEDL7Nu3b7FkQ+nz2WefqWLFimrevHlJR7Gt7777Ttu3b9cHH3wg\nwzB05MgRRUVFafPmzSUdDYXUunVrffPNN2rcuLH27t2rNm3aaOfOnRo6dKiuXbums2fPKiEhQYZh\nOF3GqlWrNHnyZFWuXNmNyUsORe4GSUlJmjNnjry9vdWvXz8tXLhQW7dula+vr+bMmaPg4GBVrVpV\nJ0+e1NChQ3Xx4kV16NBBI0aMcCxj0aJFqlixooKDg7Vs2TJ5e3vrzJkzevzxx/Xiiy/q5MmTio6O\nlpeXl6pWraqzZ8/e8ssEbs/cuXP1zTffKC8vT4MHD1b37t0VERGhe++9V5cuXVKPHj20f/9+PfPM\nM8rIyNCIESPUvn17zZ8/X0lJScrNzVWXLl3Uu3dvbdq0Sd7e3mrUqJEaN25c0h/NlgICApSamqoN\nGzYoLCxMDRo00IYNG3T48GFNnTpVnp6e8vX11dSpU5WXl6fIyEg98MADOnPmjHr06KHjx4/r8OHD\nat++vcaMGaOIiAjVq1dPx48fV7ly5dSsWTPt3r1bP//8s5YvX65y5cpp0qRJOnnypPLy8jR69GiF\nhoaqZ8+eeuihh+Tt7a358+eX9J/Fllq1aqXFixfrueee086dO/XUU09pzpw5unz5sg4dOqSQkBB1\n6tRJW7du1aRJk+Tj46OzZ8/q/PnzmjFjhi5cuOD4IrdmzRqtW7dOH3/8sQzD0OOPP65BgwYpOjpa\n6enpSk/c54pcAAAIbklEQVRP15IlS3TPPfeU9Me+LRS5C3z33XeKiIhwvH/qqad07do1ffjhh5Kk\nhQsX/u7vXbt2TYsXL9b169fVvn37fEX+S6mpqdq8ebOys7PVtm1bvfjii5o1a5ZeeOEFtWvXTuvX\nr9fZs2eL/4Pdhb766qt82/L06dMaNmyYzpw5ow8++EDXrl1Tv3791Lp1a0lSz5491blzZ8XHx6ts\n2bJaunSpLl68qKeeekphYWHasmWLVq1apfvuu0/x8fGqXLmynnjiCVWsWJESvw2VK1fWW2+9pdWr\nV+vNN99UmTJlFBkZqSVLlui1115TgwYNtG3bNs2YMUPjxo3T6dOntXz5cl29elWdOnVSYmKiypYt\nqw4dOmjMmDGSpMaNG2vChAkaMmSIypQpoxUrVigqKkrJyck6f/68goKCNH36dKWlpSk8PFz/+Mc/\nlJWVpb/85S9q2LBhCf9F7Kthw4b6n//5H5mmqeTkZI0ZM0YtW7bUnj17lJKSorZt2+rrr792/HyV\nKlU0ZcoUrV+/XuvWrdOUKVPUoEEDTZ48WadOndInn3yiNWvWSJKeffZZtWnTRpLUokULDR48uCQ+\nYrGjyF3g17vWk5KSVLNmzd/92V9e/VenTh35+PhI0i3vbFe3bl15eXnJy8tLZcqUkSSdOHHCsZu+\nadOm2rJly21/Dtz4x/7LkdWcOXOUmZmpQ4cOOQo+NzfX8cXpl9u5adOmMgxDFSpUUEBAgNLT0zV7\n9mzNnTtXP/74o+P5Arh9J0+elL+/v2JjYyVJ3377rf7rv/5LV65cUYMGDSRJzZs319y5cyVJ1apV\nU0BAgHx8fFSxYkWVL19ekvLtrm3UqJEkKTAwULVr13a8vnbtmo4dO6a9e/c6juXm5ubq4sWLkuT0\n3zoKxsPDQ/Xr11diYqIqVaokHx8fhYWF6Z///KeOHj2qQYMGObajJMf2vf/++/Wvf/0r37KOHTum\n1NRUR2FfunRJJ0+elHRnbSdOdnMTD4///Kl9fHx0/vx5maapo0ePOqbf6pjPL/3ez9WtW1f79u2T\nJB04cOA20+JWfH19FRoaqri4OL333nvq3r27qlWrJin/tvn2228l3Ti5MSsrS/7+/vr00081b948\nrVq1Sps2bdLZs2dlGIby8vJK5LPcKVJSUjRlyhTHCVA1a9ZUYGCgatas6fg3lpycrIceekhSwf+t\nORMcHKwePXooLi5Oy5YtU7du3RxfBn75bx1F07p1ay1ZssTxZbdp06Y6fPiw8vLyHH/nm35vWxqG\nIdM0FRwcrNq1a2vVqlWKi4tT3759Va9ePae/Z1eMyEvA0KFDNWzYMFWtWlWBgYHFssyXX35Z48eP\n1/LlyxUQEMC96l3Iz89P5cqV04ABA5SVlaU//OEP8vf3/83PXb16VYMGDVJWVpamTJkiHx8f3XPP\nPerXr5/KlCmj1q1bq0qVKnr44Yc1a9Ys1apVSy1atCiBT2R/Xbp00YkTJ/Tkk0+qXLlyMk1T48aN\nU5UqVTR16lSZpilPT09Nnz69WNb35z//WRMmTFB4eLgyMjI0YMAACrwYtWrVShMmTNCsWbMk3Rj8\nBAQEOEbfVh599FGNGzdOy5cvV8uWLdW/f39lZ2ercePGd+QJcNzZ7Q6xefNmPfLII6pRo4Y+/PBD\n/etf/3LsZgQA3LkYtt0hHnjgAUVGRqps2bLy8PAotpEHAKB0Y0QOAICNcVAHAAAbo8gBALAxihwA\nABujyIE7UHx8vKKjo53Oj46OLtDDX1zp9ddfdzwI6Jd3zwNQOJy1DqBEjBo1yvH6l7fcBFA4FDlw\nB/v66681f/58Xb16VZcuXdIrr7yi7t27S5L++c9/as2aNfrpp5/0wgsv6Omnn9aiRYu0f/9+nTt3\nTgMHDlSbNm00efJkpaenq0yZMpo4caIaNmyoLVu26J133pGnp6cefPBBzZ49W+vWrdPGjRsl3bgZ\nzunTp7Vz505lZWX97jKio6MVEhKiw4cPS7rxTIKbzyMAUAgmgDvOxo0bzaioKHPEiBHmd999Z5qm\nae7Zs8fs2bOnaZqmGRUVZT7//PNmXl6emZKSYoaGhpqmaZoLFy40w8PDHct5+umnzUOHDpmmaZrH\njx83u3TpYpqmaXbs2NH88ccfTdM0zXnz5pmHDx92/E5eXp75l7/8xVy2bNktlxEVFWVu3LjRNE3T\nrFu3rmv+EMBdgBE5cAebPXu2duzYoU8//VQHDhxQZmamY16nTp1kGIbq1KmjtLQ0x/SbT2HLzMzU\nv//9b7366quOeVlZWUpLS1OHDh3Uv39/derUSV27ds1368zXX39dPj4+Gjp06C2XAaB4UOTAHeKb\nb75RtWrVVLlyZce9xQcMGKDQ0FCFhoaqZcuWevnllx0/7+npKem3D4+4+US9vLw8+fj46O9//7tj\n3vfff6/y5ctrwoQJOnr0qHbu3KlXXnlFw4cPV+/evbV161bt2LFDa9eutVwGgOLBWevAHWLjxo3a\ntm2bpBtPA6tWrZr+7//+T6NGjVK7du30xRdf6Pr16wVeXkBAgB566CFHCX/xxRcaOHCgcnNz1aVL\nFwUFBen5559X7969deTIER05ckSzZs3SG2+8obJly95yGb/m6emp3Nzc2/0TAHclRuTAHWLYsGEa\nN26cVq9erfvvv18LFixQenq6evToIX9/fzVp0kRXr15VVlZWgZc5e/ZsTZ48We+88468vb01f/58\neXt7a+TIkXr22WdVpkwZBQYGaubMmXr11VeVm5urUaNGOb4wTJw48XeX8eu9AJ06dVLv3r0VHx8v\nX1/fYv27AHc67rUOAICNsWsdAAAbo8gBALAxihwAABujyAEAsDGKHAAAG6PIAQCwMYocAAAbo8gB\nALCx/wfx4vg6WPycLQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1fc8516ed30>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots()\n",
"sns.barplot(x='Jahreszeit', y='Durchschnittliche Anzahl', data=stoerungen_for_season)\n",
"ax.set_ylabel('Durchschnittliche Anzahl an Störungen')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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