diff --git a/lessons/pydata/eda-univariate-timeseries/index.ipynb b/lessons/pydata/eda-univariate-timeseries/index.ipynb index 0de993e..96376b5 100644 --- a/lessons/pydata/eda-univariate-timeseries/index.ipynb +++ b/lessons/pydata/eda-univariate-timeseries/index.ipynb @@ -10,13 +10,13 @@ "\n", "V této lekci se podíváme na základní nástroje a postupy, které se hodí pro analýzu jedné proměnné. Nebudeme se tedy zabývat vztahy a souvislostmi mezi více proměnnými - to bude předmětem mnohých dalších lekcí. Na pomoc si pro tento účel vezmeme především časové řady s údaji o počasí (teplota, tlak apod.). V práci nám bude významě pomáhat vizualizace.\n", "\n", - "Abychom s daty mohli efektivně pracovat, budeme muset data ještě transformovat a pročistit. To je (bohužel) běžnou součástí datové analýzy, protože zdrojová data jsou typicky ne zcela vhodně uspořádána a často obsahují i chyby. Při práci s časovými řadami využijeme bohaté možnosti `pandas` pro práci s časovými údaji.\n", + "Abychom s daty mohli efektivně pracovat, budeme muset data ještě pročistit. To je (bohužel) běžnou součástí datové analýzy, protože zdrojová data často obsahují chyby. Při práci s časovými řadami využijeme bohaté možnosti `pandas` pro práci s časovými údaji.\n", "\n", "Podíváme se na základy statistiky. Dozvíme se, jak pracovat s pojmy střední hodnota, standardní odchylka, medián, kvantil či kvartil. Naučíme se pracovat s histogramy, s boxploty a s distribuční funkcí.\n", "\n", "V této lekci se naučíš:\n", "* načítat data ze souborů ve formátu Excel,\n", - "* efektivně čistit a transformat data na \"spořádaná data\",\n", + "* efektivně čistit data,\n", "* základní statistiky jedné proměnné, včetně rozdělovací funkce,\n", "* vizualizovat časové řady a jejich statistické vlastnosti." ] @@ -37,15 +37,7 @@ "outputs": [], "source": [ "import pandas as pd\n", - "import numpy as np" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ + "import numpy as np\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt" ] @@ -61,22 +53,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Načtení hrubých dat - počasí" + "### Načtení dat o počasí" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Naší základní datovou sadou budou data o počasí, konkrétně v Praze - Ruzyni. Data poskytuje Českým hydrometeorologický ústav (ČHMÚ) ve formě Excel souborů, dostupných z http://portal.chmi.cz/historicka-data/pocasi/denni-data/data-ze-stanic-site-RBCN. \n", + "Naší základní datovou sadou budou data o počasí v České republice.\n", "\n", - "Možná překvapivě není úplně snadné dobrá a podrobná data získat. Ta nejkvalitnější jsou placená, navíc [\"Česká data o počasí patří k nejdražším\"](https://www.irozhlas.cz/zpravy-domov/data-statni-spravy-otevrena-data-chmu_1809140600_hm). Jen nedávno soud nařídil poskytovat alespoň základní data zdarma, viz [článek na irozhlas](https://www.irozhlas.cz/zpravy-domov/chmu-soud-pocasi-zaznamy_1807030700_cib).\n", - "\n", - "Takto vypadají náhledy dvou listů ze souboru `P1PRUZ01.xls`, který obsahuje historická data z meteorologických měření v Praze - Ruzyni. Data jsou poměrně nepěkně uspořádána. Ani v Excelu by se s těmito soubory nepracovalo dobře ...\n", - "\n", - "![thumb_geografie.png](static/thumb_geografie.png)\n", - "\n", - "![thumb_teplota.png](static/thumb_teplota.png)" + "Data na svých stránkách poskytuje hydrometeorologický ústav (ČHMÚ): https://www.chmi.cz/historicka-data/pocasi/denni-data. Možná překvapivě není úplně snadné dobrá a podrobná data získat. Naštěstí ale existuje služba [meteostat](https://meteostat.net/en/) a stejnojmenná knihovna pro Python, kterou jsme použili pro stažení dat pro několik českých stanic. Notebook [weather_data.ipynb](weather_data.ipynb) obsahuje kód pro to použitý, ale nebudeme se jím zde zabývat." ] }, { @@ -90,59 +76,26 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# TODO update S3\n", - "RUZYNE_DATA_FILENAME = \"P1PRUZ01.xlsx\"\n", - "RUZYNE_DATA_URL = \"https://data4pydata.s3.eu-west-1.amazonaws.com/pyladies/P1PRUZ01.xlsx\"" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# stáhne data pokud ještě nejsou k dispozici\n", - "import os\n", - "import requests\n", - "\n", - "def save_file_from_url(url, target_filename):\n", - " if not os.path.isfile(target_filename):\n", - " print(\"Stahuji data - počkej chvíli ...\")\n", - " response = requests.get(url)\n", - " with open(target_filename, \"wb\") as out:\n", - " out.write(response.content)\n", - " print(f\"Data jsou v souboru {target_filename}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, + "execution_count": 2, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Data jsou v souboru P1PRUZ01.xlsx\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "save_file_from_url(RUZYNE_DATA_URL, RUZYNE_DATA_FILENAME)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ + "DATA_FILENAME = \"data-daily.xlsx\"\n", + "\n", "# otevření Excel souboru\n", - "excel_data_ruzyne = pd.ExcelFile(RUZYNE_DATA_FILENAME)" + "denni_excel = pd.ExcelFile(DATA_FILENAME)\n", + "denni_excel" ] }, { @@ -154,31 +107,22 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['geografie stanice',\n", - " 'teplota průměrná',\n", - " 'teplota maximální',\n", - " 'teplota minimální',\n", - " 'rychlost větru',\n", - " 'tlak vzduchu',\n", - " 'vlhkost vzduchu',\n", - " 'úhrn srážek',\n", - " 'celková výška sněhu',\n", - " 'sluneční svit']" + "['Praha-Ruzyne', 'Plzen-Line', 'Karlovy Vary', 'Brno-Turany', 'Holesov']" ] }, - "execution_count": 7, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "excel_data_ruzyne.sheet_names" + "denni_excel.sheet_names" ] }, { @@ -190,7 +134,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -214,46 +158,40 @@ " \n", " \n", " \n", - " Průměrná denní teplota vzduchu ve °C\n", - " Unnamed: 1\n", - " Unnamed: 2\n", - " Unnamed: 3\n", - " Unnamed: 4\n", - " Unnamed: 5\n", - " Unnamed: 6\n", - " Unnamed: 7\n", - " Unnamed: 8\n", - " Unnamed: 9\n", - " ...\n", - " Unnamed: 23\n", - " Unnamed: 24\n", - " Unnamed: 25\n", - " Unnamed: 26\n", - " Unnamed: 27\n", - " Unnamed: 28\n", - " Unnamed: 29\n", - " Unnamed: 30\n", - " Unnamed: 31\n", - " Unnamed: 32\n", + " time\n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wdir\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", " \n", " \n", " \n", " \n", " 0\n", - " stanice: P1PRUZ01\n", - " NaN\n", - " NaN\n", + " 1940-01-02\n", + " -9.4\n", " NaN\n", + " -7.2\n", " NaN\n", " NaN\n", " NaN\n", " NaN\n", " NaN\n", " NaN\n", - " ...\n", - " NaN\n", - " NaN\n", " NaN\n", + " \n", + " \n", + " 1\n", + " 1940-01-03\n", + " -9.9\n", + " -13.9\n", + " -6.1\n", " NaN\n", " NaN\n", " NaN\n", @@ -263,7 +201,11 @@ " NaN\n", " \n", " \n", - " 1\n", + " 2\n", + " 1940-01-06\n", + " -7.0\n", + " -7.8\n", + " -6.1\n", " NaN\n", " NaN\n", " NaN\n", @@ -271,13 +213,27 @@ " NaN\n", " NaN\n", " NaN\n", + " \n", + " \n", + " 3\n", + " 1940-01-07\n", + " -9.2\n", + " -11.1\n", + " -7.2\n", + " NaN\n", " NaN\n", " NaN\n", " NaN\n", - " ...\n", " NaN\n", " NaN\n", " NaN\n", + " \n", + " \n", + " 4\n", + " 1940-01-12\n", + " -15.9\n", + " -22.8\n", + " -11.1\n", " NaN\n", " NaN\n", " NaN\n", @@ -287,135 +243,196 @@ " NaN\n", " \n", " \n", - " 2\n", - " rok\n", - " měsíc\n", - " 1.0\n", - " 2.0\n", - " 3.0\n", - " 4.0\n", - " 5.0\n", - " 6.0\n", - " 7.0\n", - " 8.0\n", + " ...\n", " ...\n", - " 22.0\n", - " 23.0\n", - " 24.0\n", - " 25.0\n", - " 26.0\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " \n", + " \n", + " 23272\n", + " 2025-08-27\n", + " 18.8\n", + " 12.6\n", " 27.0\n", - " 28.0\n", - " 29.0\n", + " 0.3\n", + " NaN\n", + " NaN\n", + " 9.7\n", + " 24.1\n", + " 1012.1\n", + " 429.0\n", + " \n", + " \n", + " 23273\n", + " 2025-08-28\n", + " 21.2\n", + " 15.7\n", " 30.0\n", - " 31.0\n", + " 7.0\n", + " NaN\n", + " NaN\n", + " 12.0\n", + " 47.0\n", + " 1006.3\n", + " 374.0\n", " \n", " \n", - " 3\n", - " 1961\n", - " 01\n", - " -2.0\n", - " -1.9\n", - " 0.1\n", - " -0.3\n", - " 0.4\n", - " -0.3\n", - " 0.8\n", - " 1.0\n", - " ...\n", - " -2.4\n", - " -3.4\n", - " -3.9\n", - " -7.4\n", - " -9.8\n", - " -10.3\n", - " -9.0\n", - " 0.7\n", - " 4.7\n", - " 4.7\n", + " 23274\n", + " 2025-08-29\n", + " 18.6\n", + " 15.3\n", + " 23.7\n", + " 17.7\n", + " NaN\n", + " NaN\n", + " 10.4\n", + " 27.8\n", + " 1004.4\n", + " 231.0\n", " \n", " \n", - " 4\n", - " 1961\n", - " 02\n", - " 1.3\n", - " 1.2\n", - " 0.5\n", - " 0.7\n", - " -3.3\n", - " 0.6\n", - " 3.1\n", - " 2.3\n", - " ...\n", - " 2.8\n", - " 3.0\n", - " 3.4\n", - " 0.9\n", - " 2.6\n", - " 4.4\n", - " 5.8\n", + " 23275\n", + " 2025-08-30\n", + " 18.1\n", + " 15.2\n", + " 23.0\n", + " 13.1\n", " NaN\n", " NaN\n", + " 12.2\n", + " 33.3\n", + " 1008.3\n", + " 292.0\n", + " \n", + " \n", + " 23276\n", + " 2025-08-31\n", + " 18.0\n", + " 11.6\n", + " 23.9\n", + " 0.0\n", + " NaN\n", " NaN\n", + " 9.1\n", + " 37.0\n", + " 1013.2\n", + " 357.0\n", " \n", " \n", "\n", - "

5 rows × 33 columns

\n", + "

23277 rows × 11 columns

\n", "" ], "text/plain": [ - " Průměrná denní teplota vzduchu ve °C Unnamed: 1 Unnamed: 2 Unnamed: 3 \\\n", - "0 stanice: P1PRUZ01 NaN NaN NaN \n", - "1 NaN NaN NaN NaN \n", - "2 rok měsíc 1.0 2.0 \n", - "3 1961 01 -2.0 -1.9 \n", - "4 1961 02 1.3 1.2 \n", - "\n", - " Unnamed: 4 Unnamed: 5 Unnamed: 6 Unnamed: 7 Unnamed: 8 Unnamed: 9 \\\n", - "0 NaN NaN NaN NaN NaN NaN \n", - "1 NaN NaN NaN NaN NaN NaN \n", - "2 3.0 4.0 5.0 6.0 7.0 8.0 \n", - "3 0.1 -0.3 0.4 -0.3 0.8 1.0 \n", - "4 0.5 0.7 -3.3 0.6 3.1 2.3 \n", + " time tavg tmin tmax prcp snow wdir wspd wpgt pres \\\n", + "0 1940-01-02 -9.4 NaN -7.2 NaN NaN NaN NaN NaN NaN \n", + "1 1940-01-03 -9.9 -13.9 -6.1 NaN NaN NaN NaN NaN NaN \n", + "2 1940-01-06 -7.0 -7.8 -6.1 NaN NaN NaN NaN NaN NaN \n", + "3 1940-01-07 -9.2 -11.1 -7.2 NaN NaN NaN NaN NaN NaN \n", + "4 1940-01-12 -15.9 -22.8 -11.1 NaN NaN NaN NaN NaN NaN \n", + "... ... ... ... ... ... ... ... ... ... ... \n", + "23272 2025-08-27 18.8 12.6 27.0 0.3 NaN NaN 9.7 24.1 1012.1 \n", + "23273 2025-08-28 21.2 15.7 30.0 7.0 NaN NaN 12.0 47.0 1006.3 \n", + "23274 2025-08-29 18.6 15.3 23.7 17.7 NaN NaN 10.4 27.8 1004.4 \n", + "23275 2025-08-30 18.1 15.2 23.0 13.1 NaN NaN 12.2 33.3 1008.3 \n", + "23276 2025-08-31 18.0 11.6 23.9 0.0 NaN NaN 9.1 37.0 1013.2 \n", "\n", - " ... Unnamed: 23 Unnamed: 24 Unnamed: 25 Unnamed: 26 Unnamed: 27 \\\n", - "0 ... NaN NaN NaN NaN NaN \n", - "1 ... NaN NaN NaN NaN NaN \n", - "2 ... 22.0 23.0 24.0 25.0 26.0 \n", - "3 ... -2.4 -3.4 -3.9 -7.4 -9.8 \n", - "4 ... 2.8 3.0 3.4 0.9 2.6 \n", + " tsun \n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 NaN \n", + "4 NaN \n", + "... ... \n", + "23272 429.0 \n", + "23273 374.0 \n", + "23274 231.0 \n", + "23275 292.0 \n", + "23276 357.0 \n", "\n", - " Unnamed: 28 Unnamed: 29 Unnamed: 30 Unnamed: 31 Unnamed: 32 \n", - "0 NaN NaN NaN NaN NaN \n", - "1 NaN NaN NaN NaN NaN \n", - "2 27.0 28.0 29.0 30.0 31.0 \n", - "3 -10.3 -9.0 0.7 4.7 4.7 \n", - "4 4.4 5.8 NaN NaN NaN \n", - "\n", - "[5 rows x 33 columns]" + "[23277 rows x 11 columns]" ] }, - "execution_count": 8, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# načti data z jednoho listu\n", + "denni_ruzyne_original = denni_excel.parse(\"Praha-Ruzyne\")\n", + "denni_ruzyne_original" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "time datetime64[ns]\n", + "tavg float64\n", + "tmin float64\n", + "tmax float64\n", + "prcp float64\n", + "snow float64\n", + "wdir float64\n", + "wspd float64\n", + "wpgt float64\n", + "pres float64\n", + "tsun float64\n", + "dtype: object" + ] + }, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# načti data z jednoho listu a zobraz prvních 5\n", - "teplota_prumerna = excel_data_ruzyne.parse(\"teplota průměrná\")\n", - "teplota_prumerna.head(5)" + "denni_ruzyne_original.dtypes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pro vysvětlenou dodejme, co který sloupec znamená (viz https://dev.meteostat.net/formats.html#meteorological-parameters):\n", + "- `time`: čas (nebo spíš datum) měření\n", + "- `tavg`: průměrná denní teplota (°C)\n", + "- `tmin`: nejnižší denní teplota (°C)\n", + "- `tmax`: nejvyšší denní teplota (°C)\n", + "- `prcp`: celkový úhrn srážek (mm)\n", + "- `snow`: výška sněhové pokrývky (mm)\n", + "- `wdir`: směr větru (°)\n", + "- `wspd`: rychlost větru (km/h)\n", + "- `wpgt`: max. rychlost větru v poryvech (km/h)\n", + "- `pres`: tlak (hPa)\n", + "- `tsun`: doba slunečního svitu (min)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Výsledek není přesně to, co bychom chtěli. Náprava je ale naštěstí jednoduchá - potřebujeme jen přeskočit první tři řádky. K tomu stačí přidat `skiprows=3`." + "### Časový index\n", + "\n", + "Protože se budeme zabývat časovými řadami, je zcela přirozené, že ze sloupce \"time\" uděláme index:" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -439,389 +456,269 @@ " \n", " \n", " \n", - " rok\n", - " měsíc\n", - " 1.\n", - " 2.\n", - " 3.\n", - " 4.\n", - " 5.\n", - " 6.\n", - " 7.\n", - " 8.\n", - " ...\n", - " 22.\n", - " 23.\n", - " 24.\n", - " 25.\n", - " 26.\n", - " 27.\n", - " 28.\n", - " 29.\n", - " 30.\n", - " 31.\n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wdir\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", + " \n", + " \n", + " time\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " 0\n", - " 1961\n", - " 1\n", - " -2.0\n", - " -1.9\n", - " 0.1\n", - " -0.3\n", - " 0.4\n", - " -0.3\n", - " 0.8\n", - " 1.0\n", - " ...\n", - " -2.4\n", - " -3.4\n", - " -3.9\n", - " -7.4\n", - " -9.8\n", - " -10.3\n", - " -9.0\n", - " 0.7\n", - " 4.7\n", - " 4.7\n", + " 1940-01-02\n", + " -9.4\n", + " NaN\n", + " -7.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 1\n", - " 1961\n", - " 2\n", - " 1.3\n", - " 1.2\n", - " 0.5\n", - " 0.7\n", - " -3.3\n", - " 0.6\n", - " 3.1\n", - " 2.3\n", - " ...\n", - " 2.8\n", - " 3.0\n", - " 3.4\n", - " 0.9\n", - " 2.6\n", - " 4.4\n", - " 5.8\n", + " 1940-01-03\n", + " -9.9\n", + " -13.9\n", + " -6.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " NaN\n", " NaN\n", " NaN\n", " \n", " \n", - " 2\n", - " 1961\n", - " 3\n", - " 2.1\n", - " 3.9\n", - " 4.4\n", - " 3.1\n", - " 5.7\n", - " 4.7\n", - " 7.2\n", - " 6.8\n", - " ...\n", - " 0.5\n", - " 5.2\n", - " 7.1\n", - " 6.6\n", - " 10.1\n", - " 3.5\n", - " 1.3\n", - " 4.7\n", - " 7.4\n", - " 4.8\n", + " 1940-01-06\n", + " -7.0\n", + " -7.8\n", + " -6.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 3\n", - " 1961\n", - " 4\n", - " 8.1\n", - " 8.4\n", - " 7.8\n", - " 10.0\n", - " 13.5\n", - " 16.2\n", - " 17.0\n", - " 10.6\n", - " ...\n", - " 13.5\n", - " 10.9\n", - " 11.7\n", - " 11.0\n", - " 12.4\n", - " 10.9\n", - " 11.4\n", - " 11.4\n", - " 12.5\n", + " 1940-01-07\n", + " -9.2\n", + " -11.1\n", + " -7.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " NaN\n", " \n", " \n", - " 4\n", - " 1961\n", - " 5\n", - " 10.3\n", - " 12.4\n", - " 11.8\n", - " 12.1\n", - " 16.2\n", - " 14.3\n", - " 11.8\n", - " 8.3\n", + " 1940-01-12\n", + " -15.9\n", + " -22.8\n", + " -11.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " ...\n", " ...\n", - " 11.8\n", - " 13.6\n", - " 14.6\n", - " 16.3\n", - " 15.8\n", - " 12.3\n", - " 6.2\n", - " 6.7\n", - " 8.3\n", - " 13.2\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " \n", + " \n", + " 2025-08-27\n", + " 18.8\n", + " 12.6\n", + " 27.0\n", + " 0.3\n", + " NaN\n", + " NaN\n", + " 9.7\n", + " 24.1\n", + " 1012.1\n", + " 429.0\n", + " \n", + " \n", + " 2025-08-28\n", + " 21.2\n", + " 15.7\n", + " 30.0\n", + " 7.0\n", + " NaN\n", + " NaN\n", + " 12.0\n", + " 47.0\n", + " 1006.3\n", + " 374.0\n", + " \n", + " \n", + " 2025-08-29\n", + " 18.6\n", + " 15.3\n", + " 23.7\n", + " 17.7\n", + " NaN\n", + " NaN\n", + " 10.4\n", + " 27.8\n", + " 1004.4\n", + " 231.0\n", + " \n", + " \n", + " 2025-08-30\n", + " 18.1\n", + " 15.2\n", + " 23.0\n", + " 13.1\n", + " NaN\n", + " NaN\n", + " 12.2\n", + " 33.3\n", + " 1008.3\n", + " 292.0\n", + " \n", + " \n", + " 2025-08-31\n", + " 18.0\n", + " 11.6\n", + " 23.9\n", + " 0.0\n", + " NaN\n", + " NaN\n", + " 9.1\n", + " 37.0\n", + " 1013.2\n", + " 357.0\n", " \n", " \n", "\n", - "

5 rows × 33 columns

\n", + "

23277 rows × 10 columns

\n", "" ], "text/plain": [ - " rok měsíc 1. 2. 3. 4. 5. 6. 7. 8. ... 22. \\\n", - "0 1961 1 -2.0 -1.9 0.1 -0.3 0.4 -0.3 0.8 1.0 ... -2.4 \n", - "1 1961 2 1.3 1.2 0.5 0.7 -3.3 0.6 3.1 2.3 ... 2.8 \n", - "2 1961 3 2.1 3.9 4.4 3.1 5.7 4.7 7.2 6.8 ... 0.5 \n", - "3 1961 4 8.1 8.4 7.8 10.0 13.5 16.2 17.0 10.6 ... 13.5 \n", - "4 1961 5 10.3 12.4 11.8 12.1 16.2 14.3 11.8 8.3 ... 11.8 \n", + " tavg tmin tmax prcp snow wdir wspd wpgt pres tsun\n", + "time \n", + "1940-01-02 -9.4 NaN -7.2 NaN NaN NaN NaN NaN NaN NaN\n", + "1940-01-03 -9.9 -13.9 -6.1 NaN NaN NaN NaN NaN NaN NaN\n", + "1940-01-06 -7.0 -7.8 -6.1 NaN NaN NaN NaN NaN NaN NaN\n", + "1940-01-07 -9.2 -11.1 -7.2 NaN NaN NaN NaN NaN NaN NaN\n", + "1940-01-12 -15.9 -22.8 -11.1 NaN NaN NaN NaN NaN NaN NaN\n", + "... ... ... ... ... ... ... ... ... ... ...\n", + "2025-08-27 18.8 12.6 27.0 0.3 NaN NaN 9.7 24.1 1012.1 429.0\n", + "2025-08-28 21.2 15.7 30.0 7.0 NaN NaN 12.0 47.0 1006.3 374.0\n", + "2025-08-29 18.6 15.3 23.7 17.7 NaN NaN 10.4 27.8 1004.4 231.0\n", + "2025-08-30 18.1 15.2 23.0 13.1 NaN NaN 12.2 33.3 1008.3 292.0\n", + "2025-08-31 18.0 11.6 23.9 0.0 NaN NaN 9.1 37.0 1013.2 357.0\n", "\n", - " 23. 24. 25. 26. 27. 28. 29. 30. 31. \n", - "0 -3.4 -3.9 -7.4 -9.8 -10.3 -9.0 0.7 4.7 4.7 \n", - "1 3.0 3.4 0.9 2.6 4.4 5.8 NaN NaN NaN \n", - "2 5.2 7.1 6.6 10.1 3.5 1.3 4.7 7.4 4.8 \n", - "3 10.9 11.7 11.0 12.4 10.9 11.4 11.4 12.5 NaN \n", - "4 13.6 14.6 16.3 15.8 12.3 6.2 6.7 8.3 13.2 \n", - "\n", - "[5 rows x 33 columns]" + "[23277 rows x 10 columns]" ] }, - "execution_count": 9, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "teplota_prumerna = excel_data_ruzyne.parse(\"teplota průměrná\", skiprows=3)\n", - "teplota_prumerna.head(5)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Tohle vypadá už trochu lépe - řádky a sloupce jsou tak, jak bylo zamýšleno. Problémem ale je, že dny jsou jako sloupce. Už jen proto, že ne každý měsíc má 31 dní. Proto se v posledních třech sloupcích vyskytují nedefinované hodnoty neboli `NaN` (Not a Number).\n", - "\n", - "Chybějící hodnoty se mohou vyskytnout i z jiných důvodů než \"jen\" kvůli nevhodnosti uspořádání dat. Např. mohl mít měřící přístroj závadu, data se poškodila apod. Pro chybějící hodnoty mohou být použity různé zkratky a symboly a právě proto existuje šikovný argument `na_values`.\n", - "\n", - "Z mnoha dobrých důvodů, které samy/i uvidíte v praxi, je naším cílem dostat data do podoby tzv. [*tidy data*](https://en.wikipedia.org/wiki/Tidy_data), kdy **řádky odpovídají jednotlivým pozorováním (měřením), názvy sloupců odpovídají veličinám.** \n", - "\n", - "Tady přijde vhod metoda [`melt`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.melt.html#pandas.DataFrame.melt). Ta slouží právě pro případy, kdy hodnoty jsou zakódované jako názvy sloupců. Takto vysvětlíme `melt`, že sloupce `[\"rok\", \"měsíc\"]` jsou už správně jako \"veličiny\", že v názvech zbývajících sloupců jsou hodnoty veličiny `den` a že hodnoty patří veličině `teplota průměrná`, což se použije pro pojmenování nového sloupce. " + "denni_ruzyne_index = denni_ruzyne_original.set_index(\"time\")\n", + "denni_ruzyne_index" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
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rokměsícdenteplota průměrná
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" - ], "text/plain": [ - " rok měsíc den teplota průměrná\n", - "0 1961 1 1. -2.0\n", - "1 1961 2 1. 1.3\n", - "2 1961 3 1. 2.1\n", - "3 1961 4 1. 8.1\n", - "4 1961 5 1. 10.3" + "pandas.core.indexes.datetimes.DatetimeIndex" ] }, - "execution_count": 10, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "teplota_prumerna_tidy = teplota_prumerna.melt(\n", - " id_vars=[\"rok\", \"měsíc\"], var_name=\"den\", value_name=\"teplota průměrná\"\n", - ")\n", - "teplota_prumerna_tidy.head(5)" + "type(denni_ruzyne_index.index)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "V tomto případě bylo celkem jasné, že názvy sloupců jsou vlastně hodnoty nějaké veličiny. Někdy to může být více skryté, např. v případě kategorických proměnných. Třeba data o preferencích sportů:" + "### Čištění dat" ] }, { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " Student Football Basketball Tennis\n", - "0 Alice True False True\n", - "1 Bob False True False\n", - "2 Charlie True False True" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Vidíme, že mnoho sloupců obsahuje \"NaN\", neboli \"not a number\" - to může znamenat ledacos.\n", + "\n", + "⚠️ Poznámka: NaN je původně numerickou reprezentací **neplatné matematické operace** (jako např. 0 / 0), nicméně v pandas se tento význam směšuje s **chybějící hodnotou** (missign value, N/A). Je to podobné, ale ne totéž. Naopak některé jiné knihovny (např. polars) mezi oběma významy rigorózně rozlišují, což může být zdrojem nepěkných chyb, když mezi knihovnami člověk přechází." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ - "# Příklad datové sady preferencí sportů\n", - "sport_preferences = pd.DataFrame({\n", - " \"Student\": [\"Alice\", \"Bob\", \"Charlie\"],\n", - " \"Football\": [True, False, True],\n", - " \"Basketball\": [False, True, False],\n", - " \"Tennis\": [True, False, True]\n", - "})\n", - "sport_preferences" + "Pojďme se podívat, jak chybějící/neplatné hodnoty odhalit a co se s nimi dá dělat.\n", + "\n", + "Obecně máme tři základní možnosti.\n", + "\n", + "1. Nedělat nic, tj. nechat chybějící data chybět. To je možná překvapivě často dobrá volba, protože mnoho funkcí si s chybějícími daty poradí správně. To je rozdíl oproti `numpy`, kde funkce typicky `NaN`y nemají rády. Často existují varianty funkcí (např. `numpy.mean` -> `numpy.nanmean`), které `NaN`y berou jako chybějící data. \n", + "\n", + "2. Pozorování (tj. řádky, protože máme tidy data) s chybějícími záznamy vynechat. K tomu slouží metoda [`dropna`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html#pandas.DataFrame.dropna).\n", + "\n", + "3. Chybějící data nahradit nějakou vhodnou hodnotou. Co jsou vhodné hodnoty, záleží na povaze dat a na tom, co s daty dále děláme. Někdy je vhodné nahradit chybějící hodnoty nějakou \"typickou\" hodnotou, třeba průměrem. Pro časové řady je většinou logičtější nahradit hodnotou z okolí (předchozí nebo následující). O nahrazování typickými hodnotami (angl. imputation) se dočteš https://scikit-learn.org/stable/modules/impute.html a možná dozvíš víc i později. K nahrazování hodnotami z okolí pak slouží metoda [`fillna`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.fillna.html#pandas.DataFrame.fillna).\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Sport je kategorická veličina. Ve formátu tidy data by tabulka vypadala takto:" + "Nejprve bychom ale měli zjistit, kde přesně ty chybějící hodnoty jsou. Metoda [`isna`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.isna.html#pandas.DataFrame.isna) nám dokáže \"najít\" nedefinované hodnoty:" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -845,359 +742,300 @@ " \n", " \n", " \n", - " Student\n", - " Sport\n", - " Preference\n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wdir\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", + " \n", + " \n", + " time\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " 0\n", - " Alice\n", - " Football\n", + " 1940-01-02\n", + " False\n", " True\n", - " \n", - " \n", - " 1\n", - " Bob\n", - " Football\n", " False\n", - " \n", - " \n", - " 2\n", - " Charlie\n", - " Football\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", " True\n", " \n", " \n", - " 3\n", - " Alice\n", - " Basketball\n", + " 1940-01-03\n", " False\n", + " False\n", + " False\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", " \n", " \n", - " 4\n", - " Bob\n", - " Basketball\n", - " True\n", - " \n", - " \n", - " 5\n", - " Charlie\n", - " Basketball\n", + " 1940-01-06\n", + " False\n", + " False\n", " False\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", " \n", " \n", - " 6\n", - " Alice\n", - " Tennis\n", + " 1940-01-07\n", + " False\n", + " False\n", + " False\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", " True\n", " \n", " \n", - " 7\n", - " Bob\n", - " Tennis\n", + " 1940-01-12\n", + " False\n", + " False\n", " False\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", + " True\n", " \n", " \n", - " 8\n", - " Charlie\n", - " Tennis\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " \n", + " \n", + " 2025-08-27\n", + " False\n", + " False\n", + " False\n", + " False\n", + " True\n", " True\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", - " \n", - "\n", - "" - ], - "text/plain": [ - " Student Sport Preference\n", - "0 Alice Football True\n", - "1 Bob Football False\n", - "2 Charlie Football True\n", - "3 Alice Basketball False\n", - "4 Bob Basketball True\n", - "5 Charlie Basketball False\n", - "6 Alice Tennis True\n", - "7 Bob Tennis False\n", - "8 Charlie Tennis True" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pd.melt(sport_preferences, id_vars=[\"Student\"], var_name=\"Sport\", value_name=\"Preference\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Vytvoření \"správného\" (časového) indexu\n", - "\n", - "Téměř nikdy nechceme pracovat s oddělenými sloupci \"rok\", \"měsíc\" apod. Práci s časovými údaji a časovými řadami mají na starosti specializované třídy, především [`Timestamp`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Timestamp.html#pandas.Timestamp) a [`DatetimeIndex`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DatetimeIndex.html), pro rozdíly mezi časovými údaji pak [Timedelta](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Timedelta.html#pandas.Timedelta). Přehled najdeš v dokumentaci: [Time series / date functionality](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html). A věřte - není to jednoduchý problém. Časová algebra pracuje zároveň s desítkovou, šedesátkovou, dvanáctkovou, dvacetčtyřkovou, sedmičkovou, měsíční, kvartální, roční, ... algebrou. Do toho vstupují časové zóny, přestupné roky, letní čas, různé kalendáře a kdo ví co ještě. \n", - "\n", - "Pojďme tedy vytvořit pro naši časovou řadu ten \"správný\" časový index. K tomu se často se hodí funkce [`to_datetime`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.to_datetime.html#pandas.to_datetime). Tato funkce umí převádět numerické nebo textové údaje (jednotlivě i celé řady) do toho správného Pandas typu pro práci s časovými údaji. \n", - "\n", - "Pro nás se hodí, že umí pracovat i s daty, kde jsou v oddělených sloupcích roky, měsíce, dny atd. Ukážeme si to na na jednoduchém příkladu." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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yearmonthday
2025-08-28FalseFalseFalseFalseTrueTrueFalseFalseFalseFalse
02015242025-08-29FalseFalseFalseFalseTrueTrueFalseFalseFalseFalse
12016352025-08-30FalseFalseFalseFalseTrueTrueFalseFalseFalseFalse
2025-08-31FalseFalseFalseFalseTrueTrueFalseFalseFalseFalse
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23277 rows × 10 columns

\n", "
" ], "text/plain": [ - " year month day\n", - "0 2015 2 4\n", - "1 2016 3 5" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# příklad řady datumů v oddělených sloupcích\n", - "split_dates_example = pd.DataFrame(\n", - " {\"year\": [2015, 2016], \"month\": [2, 3], \"day\": [4, 5]}\n", - ")\n", - "split_dates_example" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Funkce `to_datetime` nám z ukázkové tabulky vytvoří řadu (`Series`) typu `datetime64[ns]`. Tento (numpy) typ podporuje mnoho užitečných metod pro práci s časovými údaji, viz. [Datetimes and Timedeltas](https://docs.scipy.org/doc/numpy/reference/arrays.datetime.html). Údaj `[ns]` ukazuje na (výchozí) nanosekundovou přesnost. " - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0 2015-02-04\n", - "1 2016-03-05\n", - "dtype: datetime64[ns]" + " tavg tmin tmax prcp snow wdir wspd wpgt pres tsun\n", + "time \n", + "1940-01-02 False True False True True True True True True True\n", + "1940-01-03 False False False True True True True True True True\n", + "1940-01-06 False False False True True True True True True True\n", + "1940-01-07 False False False True True True True True True True\n", + "1940-01-12 False False False True True True True True True True\n", + "... ... ... ... ... ... ... ... ... ... ...\n", + "2025-08-27 False False False False True True False False False False\n", + "2025-08-28 False False False False True True False False False False\n", + "2025-08-29 False False False False True True False False False False\n", + "2025-08-30 False False False False True True False False False False\n", + "2025-08-31 False False False False True True False False False False\n", + "\n", + "[23277 rows x 10 columns]" ] }, - "execution_count": 14, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.to_datetime(split_dates_example)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Aby to fungovalo na naše česká data, je potřeba jen přejmenovat sloupce \"rok\", \"měsíc\", \"den\" na \"year\", \"month\", \"day\". K tomu máme metodu `rename`, tak to pojďme vyzkoušet rovnou dohromady. Výsledek uložíme do nové proměnné `datum`." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "ename": "ValueError", - "evalue": "cannot assemble the datetimes: day is out of range for month, at position 20497. You might want to try:\n - passing `format` if your strings have a consistent format;\n - passing `format='ISO8601'` if your strings are all ISO8601 but not necessarily in exactly the same format;\n - passing `format='mixed'`, and the format will be inferred for each element individually. You might want to use `dayfirst` alongside this.", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/micromamba/envs/datalady/lib/python3.12/site-packages/pandas/core/tools/datetimes.py:1214\u001b[0m, in \u001b[0;36m_assemble_from_unit_mappings\u001b[0;34m(arg, errors, utc)\u001b[0m\n\u001b[1;32m 1213\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1214\u001b[0m values \u001b[38;5;241m=\u001b[39m \u001b[43mto_datetime\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m%\u001b[39;49m\u001b[38;5;124;43mY\u001b[39;49m\u001b[38;5;124;43m%\u001b[39;49m\u001b[38;5;124;43mm\u001b[39;49m\u001b[38;5;132;43;01m%d\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mutc\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mutc\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1215\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mTypeError\u001b[39;00m, \u001b[38;5;167;01mValueError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n", - "File \u001b[0;32m~/micromamba/envs/datalady/lib/python3.12/site-packages/pandas/core/tools/datetimes.py:1067\u001b[0m, in \u001b[0;36mto_datetime\u001b[0;34m(arg, errors, dayfirst, yearfirst, utc, format, exact, unit, infer_datetime_format, origin, cache)\u001b[0m\n\u001b[1;32m 1066\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1067\u001b[0m values \u001b[38;5;241m=\u001b[39m \u001b[43mconvert_listlike\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_values\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1068\u001b[0m result \u001b[38;5;241m=\u001b[39m arg\u001b[38;5;241m.\u001b[39m_constructor(values, index\u001b[38;5;241m=\u001b[39marg\u001b[38;5;241m.\u001b[39mindex, name\u001b[38;5;241m=\u001b[39marg\u001b[38;5;241m.\u001b[39mname)\n", - "File \u001b[0;32m~/micromamba/envs/datalady/lib/python3.12/site-packages/pandas/core/tools/datetimes.py:433\u001b[0m, in \u001b[0;36m_convert_listlike_datetimes\u001b[0;34m(arg, format, name, utc, unit, errors, dayfirst, yearfirst, exact)\u001b[0m\n\u001b[1;32m 432\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mformat\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mformat\u001b[39m \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmixed\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m--> 433\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_array_strptime_with_fallback\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mutc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexact\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 435\u001b[0m result, tz_parsed \u001b[38;5;241m=\u001b[39m objects_to_datetime64(\n\u001b[1;32m 436\u001b[0m arg,\n\u001b[1;32m 437\u001b[0m dayfirst\u001b[38;5;241m=\u001b[39mdayfirst,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 441\u001b[0m allow_object\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 442\u001b[0m )\n", - "File \u001b[0;32m~/micromamba/envs/datalady/lib/python3.12/site-packages/pandas/core/tools/datetimes.py:467\u001b[0m, in \u001b[0;36m_array_strptime_with_fallback\u001b[0;34m(arg, name, utc, fmt, exact, errors)\u001b[0m\n\u001b[1;32m 464\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 465\u001b[0m \u001b[38;5;124;03mCall array_strptime, with fallback behavior depending on 'errors'.\u001b[39;00m\n\u001b[1;32m 466\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m--> 467\u001b[0m result, tz_out \u001b[38;5;241m=\u001b[39m \u001b[43marray_strptime\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfmt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexact\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexact\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mutc\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mutc\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 468\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m tz_out \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "File \u001b[0;32mstrptime.pyx:501\u001b[0m, in \u001b[0;36mpandas._libs.tslibs.strptime.array_strptime\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mstrptime.pyx:451\u001b[0m, in \u001b[0;36mpandas._libs.tslibs.strptime.array_strptime\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mstrptime.pyx:767\u001b[0m, in \u001b[0;36mpandas._libs.tslibs.strptime._parse_with_format\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mValueError\u001b[0m: day is out of range for month, at position 20497. You might want to try:\n - passing `format` if your strings have a consistent format;\n - passing `format='ISO8601'` if your strings are all ISO8601 but not necessarily in exactly the same format;\n - passing `format='mixed'`, and the format will be inferred for each element individually. You might want to use `dayfirst` alongside this.", - "\nThe above exception was the direct cause of the following exception:\n", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m datum \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_datetime\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[43mteplota_prumerna_tidy\u001b[49m\u001b[43m[\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrok\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mměsíc\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mden\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrename\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrok\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43myear\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mměsíc\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmonth\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mden\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mday\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m}\u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/micromamba/envs/datalady/lib/python3.12/site-packages/pandas/core/tools/datetimes.py:1070\u001b[0m, in \u001b[0;36mto_datetime\u001b[0;34m(arg, errors, dayfirst, yearfirst, utc, format, exact, unit, infer_datetime_format, origin, cache)\u001b[0m\n\u001b[1;32m 1068\u001b[0m result \u001b[38;5;241m=\u001b[39m arg\u001b[38;5;241m.\u001b[39m_constructor(values, index\u001b[38;5;241m=\u001b[39marg\u001b[38;5;241m.\u001b[39mindex, name\u001b[38;5;241m=\u001b[39marg\u001b[38;5;241m.\u001b[39mname)\n\u001b[1;32m 1069\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(arg, (ABCDataFrame, abc\u001b[38;5;241m.\u001b[39mMutableMapping)):\n\u001b[0;32m-> 1070\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43m_assemble_from_unit_mappings\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mutc\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1071\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(arg, Index):\n\u001b[1;32m 1072\u001b[0m cache_array \u001b[38;5;241m=\u001b[39m _maybe_cache(arg, \u001b[38;5;28mformat\u001b[39m, cache, convert_listlike)\n", - "File \u001b[0;32m~/micromamba/envs/datalady/lib/python3.12/site-packages/pandas/core/tools/datetimes.py:1216\u001b[0m, in \u001b[0;36m_assemble_from_unit_mappings\u001b[0;34m(arg, errors, utc)\u001b[0m\n\u001b[1;32m 1214\u001b[0m values \u001b[38;5;241m=\u001b[39m to_datetime(values, \u001b[38;5;28mformat\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mY\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mm\u001b[39m\u001b[38;5;132;01m%d\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, errors\u001b[38;5;241m=\u001b[39merrors, utc\u001b[38;5;241m=\u001b[39mutc)\n\u001b[1;32m 1215\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mTypeError\u001b[39;00m, \u001b[38;5;167;01mValueError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m-> 1216\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcannot assemble the datetimes: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00merr\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 1218\u001b[0m units: \u001b[38;5;28mlist\u001b[39m[UnitChoices] \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mh\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mm\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ms\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mms\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mus\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mns\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 1219\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m u \u001b[38;5;129;01min\u001b[39;00m units:\n", - "\u001b[0;31mValueError\u001b[0m: cannot assemble the datetimes: day is out of range for month, at position 20497. You might want to try:\n - passing `format` if your strings have a consistent format;\n - passing `format='ISO8601'` if your strings are all ISO8601 but not necessarily in exactly the same format;\n - passing `format='mixed'`, and the format will be inferred for each element individually. You might want to use `dayfirst` alongside this." - ] - } - ], - "source": [ - "datum = pd.to_datetime(\n", - " teplota_prumerna_tidy[[\"rok\", \"měsíc\", \"den\"]].rename(\n", - " columns={\"rok\": \"year\", \"měsíc\": \"month\", \"den\": \"day\"}\n", - " ),\n", - " )" + "denni_ruzyne_index.isna()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Skoro - skončilo to poměrně logickou chybou (výjimkou) `ValueError: cannot assemble the datetimes: day is out of range for month`. Nepovedlo se (naštěstí) přesvědčit pandy, že všechny měsíce mají 31 dní :)\n", - "\n", - "Pomocí `errors=\"coerce\"` ale můžeme nařídit, aby se převedla všechna správná data a chybná data se označila jako `NaN`, resp. v tomto případě `NaT` - Not a Time. " - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "datum = pd.to_datetime(\n", - " teplota_prumerna_tidy[[\"rok\", \"měsíc\", \"den\"]].rename(\n", - " columns={\"rok\": \"year\", \"měsíc\": \"month\", \"den\": \"day\"}\n", - " ),\n", - " errors=\"coerce\",\n", - ")" + "Použití `sum` na `True` a `False` je užitečný trik, `True` se počítá jako 1, `False` jako 0." ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0 1961-01-01\n", - "1 1961-02-01\n", - "2 1961-03-01\n", - "3 1961-04-01\n", - "4 1961-05-01\n", - " ... \n", - "22687 2021-08-31\n", - "22688 NaT\n", - "22689 2021-10-31\n", - "22690 NaT\n", - "22691 2021-12-31\n", - "Length: 22692, dtype: datetime64[ns]" + "tavg 19\n", + "tmin 2682\n", + "tmax 508\n", + "prcp 8634\n", + "snow 22226\n", + "wdir 23277\n", + "wspd 6262\n", + "wpgt 20689\n", + "pres 12109\n", + "tsun 22159\n", + "dtype: int64" ] }, - "execution_count": 17, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "datum" + "denni_ruzyne_index.isna().sum()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Pro úplnou informaci o čase bychom měli ještě přidat údaj o časové zóně. To nám umožní správně časy porovnávat, nebo třeba zachytit letní a zimní čas, což je často dosti svízelný problém. V našem případě denních dat to sice není zcela zásadní, v některých případech se to ale projevit může.\n", + "Vidíme tedy, že ve sloupcích s průměrnou teplotou je 19 nedefinovaných hodnot, zatímco pro sloupec `wdir` jsou všechny hodnoty NaN (koncept průměrného denního směru větru patrně nedává úplně smysl).\n", "\n", - "U časových údajů, které neobsahují časovou zónu, můžeme použít [`.dt.tz_localize`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.tz_localize.html#pandas.Series.tz_localize). Pro konverzi časové zóny pak slouží [`.dt.tz_convert`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.tz_convert.html#pandas.DataFrame.tz_convert).\n", - "\n", - "[`.dt`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.html#pandas.Series.dt) je tzv. *accessor object* pro práci s časovými vlastnostmi dat." + "Opak nám ukaže metoda [`.count`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.count.html):" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0 1961-01-01 00:00:00+01:00\n", - "1 1961-02-01 00:00:00+01:00\n", - "2 1961-03-01 00:00:00+01:00\n", - "3 1961-04-01 00:00:00+01:00\n", - "4 1961-05-01 00:00:00+01:00\n", - " ... \n", - "22687 2021-08-31 00:00:00+02:00\n", - "22688 NaT\n", - "22689 2021-10-31 00:00:00+02:00\n", - "22690 NaT\n", - "22691 2021-12-31 00:00:00+01:00\n", - "Length: 22692, dtype: datetime64[ns, Europe/Prague]" + "tavg 23258\n", + "tmin 20595\n", + "tmax 22769\n", + "prcp 14643\n", + "snow 1051\n", + "wdir 0\n", + "wspd 17015\n", + "wpgt 2588\n", + "pres 11168\n", + "tsun 1118\n", + "dtype: int64" ] }, - "execution_count": 18, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "datum_localized = datum.dt.tz_localize(\"Europe/Prague\")\n", - "datum_localized" + "denni_ruzyne_index.count()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Určitě jste si všimli, že přibyl i údaj o čase, a samozřejmě o časové zóně a tím i o posunu od [UTC](https://cs.wikipedia.org/wiki/Koordinovan%C3%BD_sv%C4%9Btov%C3%BD_%C4%8Das). `+01:00` znamená +1 hodina od UTC. U datumů je totiž koncept časové zóny ne úplně přirozený a proto Pandas přidal i čas (`00:00:00`). Jelikož je ale často význam denních dat nějaký souhrn za konkrétních 24 hodin (a někdy za 23 hodin a někdy za 25 hodin díky střídaní letního a zimního času), je lepší pracovat i konkrétním časem (začátkem dne). A to je i náš případ." + "**Otázka:** Co vrátí `denni_ruzyne_index.isna().count()`?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Teď už jen pomocí `assign` přidáme sloupec \"datum\". Můžeš ověřit, že následná analýza bude fungovat i s lokalizovaným časem `datum_localized`." + "Sloupec `wdir` patrně můžeme vyhodit, protože neobsahuje žádnou užitečnou informaci. Na to stačí [`.drop`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.count.html):" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -1221,53 +1059,89 @@ " \n", " \n", " \n", - " rok\n", - " měsíc\n", - " den\n", - " teplota průměrná\n", - " datum\n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", + " \n", + " \n", + " time\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " 0\n", - " 1961\n", - " 1\n", - " 1.\n", - " -2.0\n", - " 1961-01-01\n", - " \n", - " \n", - " 1\n", - " 1961\n", - " 2\n", - " 1.\n", - " 1.3\n", - " 1961-02-01\n", + " 1940-01-02\n", + " -9.4\n", + " NaN\n", + " -7.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2\n", - " 1961\n", - " 3\n", - " 1.\n", - " 2.1\n", - " 1961-03-01\n", + " 1940-01-03\n", + " -9.9\n", + " -13.9\n", + " -6.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 3\n", - " 1961\n", - " 4\n", - " 1.\n", - " 8.1\n", - " 1961-04-01\n", + " 1940-01-06\n", + " -7.0\n", + " -7.8\n", + " -6.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 4\n", - " 1961\n", - " 5\n", - " 1.\n", - " 10.3\n", - " 1961-05-01\n", + " 1940-01-07\n", + " -9.2\n", + " -11.1\n", + " -7.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1940-01-12\n", + " -15.9\n", + " -22.8\n", + " -11.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", " ...\n", @@ -1276,139 +1150,114 @@ " ...\n", " ...\n", " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", " \n", " \n", - " 22687\n", - " 2021\n", - " 8\n", - " 31.\n", - " 13.4\n", - " 2021-08-31\n", + " 2025-08-27\n", + " 18.8\n", + " 12.6\n", + " 27.0\n", + " 0.3\n", + " NaN\n", + " 9.7\n", + " 24.1\n", + " 1012.1\n", + " 429.0\n", " \n", " \n", - " 22688\n", - " 2021\n", - " 9\n", - " 31.\n", + " 2025-08-28\n", + " 21.2\n", + " 15.7\n", + " 30.0\n", + " 7.0\n", " NaN\n", - " NaT\n", + " 12.0\n", + " 47.0\n", + " 1006.3\n", + " 374.0\n", " \n", " \n", - " 22689\n", - " 2021\n", - " 10\n", - " 31.\n", - " 7.8\n", - " 2021-10-31\n", + " 2025-08-29\n", + " 18.6\n", + " 15.3\n", + " 23.7\n", + " 17.7\n", + " NaN\n", + " 10.4\n", + " 27.8\n", + " 1004.4\n", + " 231.0\n", " \n", " \n", - " 22690\n", - " 2021\n", - " 11\n", - " 31.\n", + " 2025-08-30\n", + " 18.1\n", + " 15.2\n", + " 23.0\n", + " 13.1\n", " NaN\n", - " NaT\n", + " 12.2\n", + " 33.3\n", + " 1008.3\n", + " 292.0\n", " \n", " \n", - " 22691\n", - " 2021\n", - " 12\n", - " 31.\n", - " 11.0\n", - " 2021-12-31\n", + " 2025-08-31\n", + " 18.0\n", + " 11.6\n", + " 23.9\n", + " 0.0\n", + " NaN\n", + " 9.1\n", + " 37.0\n", + " 1013.2\n", + " 357.0\n", " \n", " \n", "\n", - "

22692 rows × 5 columns

\n", + "

23277 rows × 9 columns

\n", "" ], "text/plain": [ - " rok měsíc den teplota průměrná datum\n", - "0 1961 1 1. -2.0 1961-01-01\n", - "1 1961 2 1. 1.3 1961-02-01\n", - "2 1961 3 1. 2.1 1961-03-01\n", - "3 1961 4 1. 8.1 1961-04-01\n", - "4 1961 5 1. 10.3 1961-05-01\n", - "... ... ... ... ... ...\n", - "22687 2021 8 31. 13.4 2021-08-31\n", - "22688 2021 9 31. NaN NaT\n", - "22689 2021 10 31. 7.8 2021-10-31\n", - "22690 2021 11 31. NaN NaT\n", - "22691 2021 12 31. 11.0 2021-12-31\n", + " tavg tmin tmax prcp snow wspd wpgt pres tsun\n", + "time \n", + "1940-01-02 -9.4 NaN -7.2 NaN NaN NaN NaN NaN NaN\n", + "1940-01-03 -9.9 -13.9 -6.1 NaN NaN NaN NaN NaN NaN\n", + "1940-01-06 -7.0 -7.8 -6.1 NaN NaN NaN NaN NaN NaN\n", + "1940-01-07 -9.2 -11.1 -7.2 NaN NaN NaN NaN NaN NaN\n", + "1940-01-12 -15.9 -22.8 -11.1 NaN NaN NaN NaN NaN NaN\n", + "... ... ... ... ... ... ... ... ... ...\n", + "2025-08-27 18.8 12.6 27.0 0.3 NaN 9.7 24.1 1012.1 429.0\n", + "2025-08-28 21.2 15.7 30.0 7.0 NaN 12.0 47.0 1006.3 374.0\n", + "2025-08-29 18.6 15.3 23.7 17.7 NaN 10.4 27.8 1004.4 231.0\n", + "2025-08-30 18.1 15.2 23.0 13.1 NaN 12.2 33.3 1008.3 292.0\n", + "2025-08-31 18.0 11.6 23.9 0.0 NaN 9.1 37.0 1013.2 357.0\n", "\n", - "[22692 rows x 5 columns]" + "[23277 rows x 9 columns]" ] }, - "execution_count": 19, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "teplota_prumerna_tidy = teplota_prumerna_tidy.assign(datum=datum)\n", - "teplota_prumerna_tidy" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úkol:** `to_datetime` dokáže pracovat i s řetězci, což se často hodí. Převeďte `ladies_times` na vhodný typ pro časové údaje, přiřaďte naši časovou zónu a poté pomocí `tz_convert` převeďte na UTC. Možná budete muset pandám vysvětlit, že v Česku jsou v datumech nejdříve dny, na rozdíl třeba od Ameriky. Naštěstí na to stačí jeden jednoduchý argument pro `to_datetime`." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "ladies_times = [\"12. 9. 2020 18:00\", \"19. 9. 2020 18:00\", \"26. 9. 2020 18:00\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "# odkomentuj a doplň\n", - "# pandas_times = pd.to_datetime(___).___.___" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Čištění dat" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Co se stalo s nedefinovanými hodnotami? Zůstaly tam. Pojďme se podívat, jak to vlastně zjistit a co se s tím dá dělat.\n", - "\n", - "Obecně máme tři základní možnosti.\n", - "\n", - "1. Nedělat nic, tj. nechat chybějící data chybět. To je možná překvapivě často dobrá volba, protože mnoho funkcí si s chybějícími daty poradí správně. To je rozdíl oproti `numpy`, kde funkce typicky `NaN`y nemají rády. Často existují varianty funkcí (např. `numpy.mean` -> `numpy.nanmean`), které `NaN`y berou jako chybějící data. \n", - "\n", - "2. Pozorování (tj. řádky, protože máme tidy data) s chybějícími záznamy vynechat. K tomu slouží metoda [`dropna`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html#pandas.DataFrame.dropna).\n", - "\n", - "3. Chybějící data nahradit nějakou vhodnou hodnotou. Co jsou vhodné hodnoty, záleží na povaze dat a na tom, co s daty dále děláme. Někdy je vhodné nahradit chybějící hodnoty nějakou \"typickou\" hodnotou, třeba průměrem. Pro časové řady je většinou logičtější nahradit hodnotou z okolí (předchozí nebo následující). O nahrazování typickými hodnotami (angl. imputation) se dočteš https://scikit-learn.org/stable/modules/impute.html a možná dozvíš víc i později. K nahrazování hodnotami z okolí pak slouží metoda [`fillna`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.fillna.html#pandas.DataFrame.fillna).\n", - "\n", - "Pro naše účely se bude nejvíce hodit vynechat chybějící záznamy, které vznikly nehezkým uspořádáním Excel souboru." + "denni_ruzyne_bez_wdir = denni_ruzyne_index.drop(columns=\"wdir\")\n", + "denni_ruzyne_bez_wdir" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Nejprve bychom ale měli zjistit, kde přesně ty chybějící hodnoty jsou. Metoda [`isna`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.isna.html#pandas.DataFrame.isna) nám dokáže \"najít\" nedefinované hodnoty:" + "A co s onou teplotou?" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -1432,182 +1281,305 @@ " \n", " \n", " \n", - " rok\n", - " měsíc\n", - " den\n", - " teplota průměrná\n", - " datum\n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", + " \n", + " \n", + " time\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " 0\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " \n", - " \n", - " 1\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 1973-01-04\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 11.1\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 1975-02-13\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 5.5\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 3\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 1975-02-21\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 2.4\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 4\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 1975-10-28\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 1.7\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", + " 1975-12-15\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 5.9\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 22687\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 1976-12-20\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 7.5\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 22688\n", - " False\n", - " False\n", - " False\n", - " True\n", - " True\n", + " 1977-02-14\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 7.1\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 22689\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 1978-02-27\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 10.2\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 22690\n", - " False\n", - " False\n", - " False\n", - " True\n", - " True\n", + " 1987-12-31\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 6.7\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 22691\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 1988-01-05\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 26.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1988-01-24\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 14.8\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1988-02-08\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 19.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1988-03-05\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 8.6\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1988-03-15\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 15.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1988-04-29\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 9.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1988-05-22\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 10.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1988-06-19\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 10.4\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1988-08-12\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 10.6\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1989-01-22\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 8.7\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", "\n", - "

22692 rows × 5 columns

\n", "" ], "text/plain": [ - " rok měsíc den teplota průměrná datum\n", - "0 False False False False False\n", - "1 False False False False False\n", - "2 False False False False False\n", - "3 False False False False False\n", - "4 False False False False False\n", - "... ... ... ... ... ...\n", - "22687 False False False False False\n", - "22688 False False False True True\n", - "22689 False False False False False\n", - "22690 False False False True True\n", - "22691 False False False False False\n", - "\n", - "[22692 rows x 5 columns]" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "teplota_prumerna_tidy.isna()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Použití `sum` na `True` a `False` je užitečný trik, `True` se počítá jako 1, `False` jako 0." - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "rok 0\n", - "měsíc 0\n", - "den 0\n", - "teplota průměrná 412\n", - "datum 412\n", - "dtype: int64" + " tavg tmin tmax prcp snow wspd wpgt pres tsun\n", + "time \n", + "1973-01-04 NaN NaN NaN NaN NaN 11.1 NaN NaN NaN\n", + "1975-02-13 NaN NaN NaN NaN NaN 5.5 NaN NaN NaN\n", + "1975-02-21 NaN NaN NaN NaN NaN 2.4 NaN NaN NaN\n", + "1975-10-28 NaN NaN NaN NaN NaN 1.7 NaN NaN NaN\n", + "1975-12-15 NaN NaN NaN NaN NaN 5.9 NaN NaN NaN\n", + "1976-12-20 NaN NaN NaN NaN NaN 7.5 NaN NaN NaN\n", + "1977-02-14 NaN NaN NaN NaN NaN 7.1 NaN NaN NaN\n", + "1978-02-27 NaN NaN NaN NaN NaN 10.2 NaN NaN NaN\n", + "1987-12-31 NaN NaN NaN NaN NaN 6.7 NaN NaN NaN\n", + "1988-01-05 NaN NaN NaN NaN NaN 26.0 NaN NaN NaN\n", + "1988-01-24 NaN NaN NaN NaN NaN 14.8 NaN NaN NaN\n", + "1988-02-08 NaN NaN NaN NaN NaN 19.2 NaN NaN NaN\n", + "1988-03-05 NaN NaN NaN NaN NaN 8.6 NaN NaN NaN\n", + "1988-03-15 NaN NaN NaN NaN NaN 15.1 NaN NaN NaN\n", + "1988-04-29 NaN NaN NaN NaN NaN 9.2 NaN NaN NaN\n", + "1988-05-22 NaN NaN NaN NaN NaN 10.0 NaN NaN NaN\n", + "1988-06-19 NaN NaN NaN NaN NaN 10.4 NaN NaN NaN\n", + "1988-08-12 NaN NaN NaN NaN NaN 10.6 NaN NaN NaN\n", + "1989-01-22 NaN NaN NaN NaN NaN 8.7 NaN NaN NaN" ] }, - "execution_count": 23, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "teplota_prumerna_tidy.isna().sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Vidíme tedy, že ve sloupcích s teplotou a datumem je 412 nedefinovaných hodnot." + "denni_ruzyne_bez_wdir.loc[denni_ruzyne_bez_wdir[\"tavg\"].isna()]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Můžeme si také zobrazit výběr řádků, kde je alespoň nějaký `NaN`. Jistě si pamatuješ, že indexovat lze pomocí řady typu `bool`. Drobný problém je, že máme těch řad víc - pro každý sloupec jednu. Můžeme ale použít `.any(axis=1)`, abychom vybrali řádky, kde je alespoň nějaký `NaN`: " + "Oněch 19 řádků odpovídá patrně dnům, kdy meteostanice \"neměla\" svůj den. Tyto řádky má asi smysl úplně **odstranit**. Na to použijeme metodu `.dropna`, jen budeme muset specifikovat, který sloupec nám vadí:" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -1631,125 +1603,205 @@ " \n", " \n", " \n", - " rok\n", - " měsíc\n", - " den\n", - " teplota průměrná\n", - " datum\n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", + " \n", + " \n", + " time\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " 22441\n", - " 2001\n", - " 2\n", - " 31.\n", + " 1940-01-02\n", + " -9.4\n", + " NaN\n", + " -7.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " NaN\n", - " NaT\n", " \n", " \n", - " 22035\n", - " 1967\n", - " 4\n", - " 31.\n", + " 1940-01-03\n", + " -9.9\n", + " -13.9\n", + " -6.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " NaN\n", - " NaT\n", " \n", " \n", - " 22553\n", - " 2010\n", - " 6\n", - " 31.\n", + " 1940-01-06\n", + " -7.0\n", + " -7.8\n", + " -6.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " NaN\n", - " NaT\n", " \n", " \n", - " 21445\n", - " 1979\n", - " 2\n", - " 30.\n", + " 1940-01-07\n", + " -9.2\n", + " -11.1\n", + " -7.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " NaN\n", - " NaT\n", " \n", " \n", - " 22580\n", - " 2012\n", - " 9\n", - " 31.\n", + " 1940-01-12\n", + " -15.9\n", + " -22.8\n", + " -11.1\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " \n", + " \n", + " 2025-08-27\n", + " 18.8\n", + " 12.6\n", + " 27.0\n", + " 0.3\n", + " NaN\n", + " 9.7\n", + " 24.1\n", + " 1012.1\n", + " 429.0\n", + " \n", + " \n", + " 2025-08-28\n", + " 21.2\n", + " 15.7\n", + " 30.0\n", + " 7.0\n", + " NaN\n", + " 12.0\n", + " 47.0\n", + " 1006.3\n", + " 374.0\n", + " \n", + " \n", + " 2025-08-29\n", + " 18.6\n", + " 15.3\n", + " 23.7\n", + " 17.7\n", + " NaN\n", + " 10.4\n", + " 27.8\n", + " 1004.4\n", + " 231.0\n", + " \n", + " \n", + " 2025-08-30\n", + " 18.1\n", + " 15.2\n", + " 23.0\n", + " 13.1\n", + " NaN\n", + " 12.2\n", + " 33.3\n", + " 1008.3\n", + " 292.0\n", + " \n", + " \n", + " 2025-08-31\n", + " 18.0\n", + " 11.6\n", + " 23.9\n", + " 0.0\n", " NaN\n", - " NaT\n", + " 9.1\n", + " 37.0\n", + " 1013.2\n", + " 357.0\n", " \n", " \n", "\n", + "

23258 rows × 9 columns

\n", "" ], "text/plain": [ - " rok měsíc den teplota průměrná datum\n", - "22441 2001 2 31. NaN NaT\n", - "22035 1967 4 31. NaN NaT\n", - "22553 2010 6 31. NaN NaT\n", - "21445 1979 2 30. NaN NaT\n", - "22580 2012 9 31. NaN NaT" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "teplota_prumerna_tidy.loc[teplota_prumerna_tidy.isna().any(axis=1)].sample(5)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Způsobem, jak získat naopak počet nechybějících (platných) hodnot, je metoda `count`" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "rok 22692\n", - "měsíc 22692\n", - "den 22692\n", - "teplota průměrná 22280\n", - "datum 22280\n", - "dtype: int64" + " tavg tmin tmax prcp snow wspd wpgt pres tsun\n", + "time \n", + "1940-01-02 -9.4 NaN -7.2 NaN NaN NaN NaN NaN NaN\n", + "1940-01-03 -9.9 -13.9 -6.1 NaN NaN NaN NaN NaN NaN\n", + "1940-01-06 -7.0 -7.8 -6.1 NaN NaN NaN NaN NaN NaN\n", + "1940-01-07 -9.2 -11.1 -7.2 NaN NaN NaN NaN NaN NaN\n", + "1940-01-12 -15.9 -22.8 -11.1 NaN NaN NaN NaN NaN NaN\n", + "... ... ... ... ... ... ... ... ... ...\n", + "2025-08-27 18.8 12.6 27.0 0.3 NaN 9.7 24.1 1012.1 429.0\n", + "2025-08-28 21.2 15.7 30.0 7.0 NaN 12.0 47.0 1006.3 374.0\n", + "2025-08-29 18.6 15.3 23.7 17.7 NaN 10.4 27.8 1004.4 231.0\n", + "2025-08-30 18.1 15.2 23.0 13.1 NaN 12.2 33.3 1008.3 292.0\n", + "2025-08-31 18.0 11.6 23.9 0.0 NaN 9.1 37.0 1013.2 357.0\n", + "\n", + "[23258 rows x 9 columns]" ] }, - "execution_count": 25, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "teplota_prumerna_tidy.count()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Otázka:** Co vrátí `teplota_prumerna_tidy.isna().count()`?" + "denni_ruzyne = denni_ruzyne_bez_wdir.dropna(subset=[\"tavg\"])\n", + "denni_ruzyne" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Teď už ale ta chybějící data chceme odstranit. Podívejme se na jednoduchém příkladu, jak funguje [`dropna`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html#pandas.DataFrame.dropna)." + "Mohli bychom zkusit odstranit všechny řádky, kde něco chybí:" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -1773,268 +1825,753 @@ " \n", " \n", " \n", - " A\n", - " B\n", - " \n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", + " \n", + " \n", + " time\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " 0\n", + " 2022-12-02\n", + " -0.6\n", + " -1.3\n", + " 0.2\n", + " 0.0\n", " 1.0\n", + " 14.6\n", + " 29.6\n", + " 1023.9\n", " 1.0\n", " \n", " \n", - " 1\n", - " 2.0\n", - " 2.0\n", + " 2022-12-09\n", + " -0.8\n", + " -3.2\n", + " 0.2\n", + " 0.0\n", + " 1.0\n", + " 9.3\n", + " 20.4\n", + " 1007.4\n", + " 98.0\n", " \n", " \n", - " 2\n", - " NaN\n", - " 3.0\n", + " 2022-12-15\n", + " -6.4\n", + " -9.2\n", + " -2.3\n", + " 2.5\n", + " 7.0\n", + " 8.0\n", + " 22.2\n", + " 1010.1\n", + " 148.0\n", " \n", " \n", - " 3\n", + " 2022-12-17\n", + " -4.3\n", + " -9.1\n", + " -1.3\n", + " 0.8\n", + " 11.0\n", + " 10.2\n", + " 25.9\n", + " 1026.3\n", + " 75.0\n", + " \n", + " \n", + " 2022-12-22\n", + " 5.3\n", + " 0.6\n", + " 8.3\n", + " 4.1\n", " 4.0\n", - " NaN\n", + " 19.0\n", + " 47.0\n", + " 1009.9\n", + " 17.0\n", " \n", " \n", - " 4\n", - " 5.0\n", + " 2023-01-18\n", + " 0.5\n", + " -1.9\n", + " 2.9\n", + " 0.5\n", + " 1.0\n", + " 12.0\n", + " 24.1\n", + " 993.8\n", + " 20.0\n", + " \n", + " \n", + " 2023-01-20\n", + " -1.7\n", + " -3.4\n", + " -0.5\n", + " 0.0\n", + " 1.0\n", + " 10.2\n", + " 33.3\n", + " 1016.0\n", + " 40.0\n", + " \n", + " \n", + " 2023-01-23\n", + " -0.7\n", + " -2.7\n", + " 0.6\n", + " 1.5\n", " 5.0\n", + " 9.8\n", + " 25.9\n", + " 1034.8\n", + " 26.0\n", " \n", - " \n", - "\n", - "" - ], - "text/plain": [ - " A B\n", - "0 1.0 1.0\n", - "1 2.0 2.0\n", - "2 NaN 3.0\n", - "3 4.0 NaN\n", - "4 5.0 5.0" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# příklad dat s chybějícími hodnotami\n", - "example_with_nan = pd.DataFrame({\"A\": [1, 2, np.nan, 4, 5], \"B\": [1, 2, 3, np.nan, 5]})\n", - "example_with_nan" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Po `dropna` zbudou pouze řádky bez chybějících hodnot." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" ], "text/plain": [ - " A B\n", - "0 1.0 1.0\n", - "1 2.0 2.0\n", - "4 5.0 5.0" + " tavg tmin tmax prcp snow wspd wpgt pres tsun\n", + "time \n", + "2022-12-02 -0.6 -1.3 0.2 0.0 1.0 14.6 29.6 1023.9 1.0\n", + "2022-12-09 -0.8 -3.2 0.2 0.0 1.0 9.3 20.4 1007.4 98.0\n", + "2022-12-15 -6.4 -9.2 -2.3 2.5 7.0 8.0 22.2 1010.1 148.0\n", + "2022-12-17 -4.3 -9.1 -1.3 0.8 11.0 10.2 25.9 1026.3 75.0\n", + "2022-12-22 5.3 0.6 8.3 4.1 4.0 19.0 47.0 1009.9 17.0\n", + "2023-01-18 0.5 -1.9 2.9 0.5 1.0 12.0 24.1 993.8 20.0\n", + "2023-01-20 -1.7 -3.4 -0.5 0.0 1.0 10.2 33.3 1016.0 40.0\n", + "2023-01-23 -0.7 -2.7 0.6 1.5 5.0 9.8 25.9 1034.8 26.0\n", + "2023-01-24 0.0 -0.3 0.5 0.0 4.0 9.9 22.2 1037.6 2.0\n", + "2023-01-26 -1.0 -1.4 -0.6 0.0 3.0 6.4 22.2 1021.9 17.0\n", + "2023-01-28 -2.5 -5.0 -1.0 0.0 3.0 16.7 31.5 1027.2 19.0\n", + "2023-01-29 -3.9 -5.5 -1.9 0.0 3.0 14.8 40.0 1028.0 177.0\n", + "2023-02-26 -1.7 -3.1 0.4 1.8 3.0 18.8 40.8 1017.2 131.0\n", + "2023-02-27 -2.5 -6.2 0.7 0.0 3.0 12.2 29.6 1027.8 237.0\n", + "2023-02-28 -1.4 -5.8 2.6 0.0 1.0 13.8 31.5 1030.3 446.0\n", + "2023-03-06 0.7 -2.1 4.4 0.3 1.0 17.7 35.2 1006.5 102.0\n", + "2023-03-15 1.1 -2.3 5.3 3.8 1.0 14.0 50.0 1016.2 294.0\n", + "2023-03-16 0.8 -4.4 6.3 1.8 1.0 11.4 22.2 1023.8 539.0\n", + "2023-03-27 2.1 -0.5 5.1 7.6 1.0 23.0 54.0 1010.9 198.0\n", + "2023-03-28 1.4 -1.1 5.7 0.5 1.0 23.0 58.0 1023.1 370.0\n", + "2023-11-25 0.2 -1.1 1.4 1.3 1.0 20.7 47.0 1004.4 84.0\n", + "2023-11-27 1.3 -0.5 3.1 1.8 2.0 14.1 33.3 1006.3 18.0\n", + "2023-11-28 -1.1 -2.9 0.2 6.4 4.0 14.2 42.6 997.6 1.0\n", + "2023-11-30 -1.0 -3.2 1.6 0.0 2.0 9.8 27.8 1004.4 75.0\n", + "2023-12-03 -4.4 -6.1 -3.0 1.5 15.0 21.4 38.9 1023.0 83.0\n", + "2023-12-05 -4.1 -7.0 -1.5 0.0 13.0 8.8 20.4 1013.3 12.0\n", + "2023-12-07 0.2 -0.1 1.1 0.3 9.0 11.2 25.9 1021.2 48.0\n", + "2023-12-09 0.7 -1.3 2.2 2.3 9.0 10.0 33.3 1014.1 1.0\n", + "2023-12-10 3.1 0.2 5.3 2.0 4.0 23.6 47.0 1008.3 58.0\n", + "2024-01-18 -2.1 -2.9 -0.5 2.8 4.0 15.9 37.0 996.0 0.0\n", + "2024-01-20 -3.7 -5.5 -0.5 0.0 3.0 24.3 40.8 1030.9 382.0\n", + "2024-11-23 0.7 -2.3 3.4 0.0 1.0 21.9 61.0 1020.8 204.0\n", + "2024-12-11 -0.4 -1.3 0.5 2.5 1.0 10.6 20.4 1029.9 27.0\n", + "2024-12-13 -1.3 -1.9 -0.7 0.0 1.0 11.0 24.1 1032.5 20.0" ] }, - "execution_count": 27, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "example_with_nan.dropna()" + "denni_ruzyne.dropna()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Tohle přesně potřebujeme na naše data, která teď vyčistíme od nedefinovaných hodnot:" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [], - "source": [ - "teplota_prumerna_tidy_clean = teplota_prumerna_tidy.dropna()" + "Popravdě, zbylo by nám jen nějakých 34 řádků, v zimním období, a všechny jsou novější než rok 2022. Proč tomu tak je? Svou roli zde hraje několik faktorů dohromady, které nepůjde snadno rozklíčovat bez vizualizace. A bohužel tedy ani nevím, jak bychom správně aplikovali `fillna`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**Úkol:** Využijte toho, že teplota není definovaná v neexistující dny. Použijte vhodně `dropna` v sestrojení datumů tak, abychom nemuseli použít `errors=\"coerce\"` pro `to_datetime`." - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": { - "jupyter": { - "outputs_hidden": true - } - }, - "outputs": [], - "source": [ - "# odkomentuj a přidejte dropna na správné místo\n", - "# pd.to_datetime(\n", - "# teplota_prumerna_tidy[[\"rok\", \"měsíc\", \"den\"]].rename(\n", - "# columns={\"rok\": \"year\", \"měsíc\": \"month\", \"den\": \"day\"}\n", - "# ),\n", - "# )" + "**Úkol:** Zkuste odstranit všechny řádky, pro které není definován `tsun`. Co nám to říká?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**Úkol**: Z proměnné `teplota_prumerna_tidy_clean` vytvořte `teplota_prumerna_tidy_clean_indexed` se sloupcem `datum` jako indexem a bez sloupců `rok`, `měsíc` a `den`. Můžete použít metodu `drop` nebo indexování s názvy sloupců." + "**Úkol:** Zkuste odstranit všechny řádky, pro které není definován `snow`. Co nám to říká?" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "PeriodIndex(['1940-01-02', '1940-01-03', '1940-01-06', '1940-01-07',\n", + " '1940-01-12', '1940-01-13', '1940-01-14', '1940-01-18',\n", + " '1940-01-19', '1940-01-21',\n", + " ...\n", + " '2025-08-22', '2025-08-23', '2025-08-24', '2025-08-25',\n", + " '2025-08-26', '2025-08-27', '2025-08-28', '2025-08-29',\n", + " '2025-08-30', '2025-08-31'],\n", + " dtype='period[D]', name='time', length=23258)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "teplota_prumerna_tidy_clean_indexed = ___" + "denni_ruzyne.index.to_period(\"D\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Vše dohromady \n", + "## Indexování a výběr intervalů\n", "\n", - "Parsování celého souboru, tj. jeho načtení a převedení do požadované formy Pandas `DataFrame`, máme teď hotové. Pro další generace (a naše použití) na to definujeme funkci. V rámci této funkce také vyhodíme sloupce rok, měsíc a den, sloupec datum použijeme jako index a data podle datumu setřídíme. Přidali jsme ještě jméno listu jako vstupní parameter, což se bude hodit hned vzápětí pro načítání všech listů do jednoho `DataFrame`." - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "def extract_and_clean_chmi_excel_sheet(excel_data, sheet_name):\n", - " \"\"\"Parse ČHMÚ historical meteo excel data\"\"\"\n", - " # načti list z excel souboru a převeď na tidy data formát\n", - " data_tidy = (\n", - " excel_data.parse(sheet_name, skiprows=3)\n", - " .melt(id_vars=[\"rok\", \"měsíc\"], var_name=\"den\", value_name=sheet_name)\n", - " .dropna()\n", - " )\n", - " # vytvoř časovou řadu datumů\n", - " datum = pd.to_datetime(\n", - " data_tidy[[\"rok\", \"měsíc\", \"den\"]].rename(\n", - " columns={\"rok\": \"year\", \"měsíc\": \"month\", \"den\": \"day\"}\n", - " )\n", - " )\n", - " # přidej sloupec datum jako index a odstraň den, měsíc, rok a vrať setříděný výsledek\n", - " return (\n", - " data_tidy.assign(datum=datum)\n", - " .set_index(\"datum\")\n", - " .drop(columns=[\"rok\", \"měsíc\", \"den\"])\n", - " .sort_index()\n", - " )" + "Data, která jsme načetli a vyčistili, tvoří vlastně několik časových řad v jednotlivých sloupcích tabulky `denni_ruzyne`. Granularita (nebo frekvence či časové rozlišení) je jeden den.\n", + "\n", + "Pomocí [`to_period()`](https://pandas.pydata.org/docs/reference/api/pandas.DatetimeIndex.to_period.html) bychom mohli datový typ indexu převést i na `period[D]`. To může zrychlit některé operace, pro naše použití to ale není nezbytné." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "A teď už si můžeme načíst všechna data z Ruzyně tak, jak se nám budou hodit pro analýzu." + "Už jsme si ukazovali indexování (výběr intervalu) pomocí `.loc`. U časových řad to funguje samozřejmě také. Pozor na to, že `.loc` vrací data *včetně* horní meze, *na rozdíl* od indexování `list`ů nebo numpy polí. \n", + "\n", + "Konkrétní období můžeme vybrat třeba takto:" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " tavg tmin tmax prcp snow wspd wpgt pres tsun\n", + "time \n", + "2017-12-24 6.2 5.5 7.0 NaN NaN 28.8 NaN 1024.2 NaN\n", + "2017-12-25 3.1 -0.9 5.5 NaN NaN 18.2 NaN 1021.0 NaN\n", + "2017-12-26 0.1 -4.0 4.2 NaN NaN 11.2 NaN 1010.1 NaN\n", + "2017-12-27 -0.3 -2.7 2.1 NaN NaN 11.0 NaN 995.5 NaN\n", + "2017-12-28 0.6 -0.4 1.5 NaN NaN 14.6 NaN 994.4 NaN\n", + "2017-12-29 -1.4 -3.5 0.5 NaN NaN 19.8 NaN 1009.7 NaN\n", + "2017-12-30 0.6 -3.2 5.0 NaN NaN 17.7 NaN 1007.5 NaN\n", + "2017-12-31 8.5 5.7 11.1 NaN NaN 26.0 NaN 1007.6 NaN\n", + "2018-01-01 5.3 0.7 7.5 NaN NaN 17.1 NaN 1006.8 NaN" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# otevři Excel soubor\n", - "excel_data_ruzyne = pd.ExcelFile(RUZYNE_DATA_FILENAME)\n", - "\n", - "# načti všechny listy kromě prvního\n", - "extracted_sheets = [\n", - " extract_and_clean_chmi_excel_sheet(excel_data_ruzyne, sheet_name)\n", - " for sheet_name in excel_data_ruzyne.sheet_names[1:]\n", - "]\n", - "# pokud neznáš syntax list comprehension, koukni třeba na https://realpython.com/list-comprehension-python/\n", - "# lze samozřejmě použít for cyklus, ale list comprehension je čitelnější\n", - "\n", - "# spoj všechny listy do jednoho DataFrame\n", - "ruzyne_tidy = pd.concat(extracted_sheets, axis=1)" + "denni_ruzyne.loc[pd.Timestamp(2017, 12, 24) : pd.Timestamp(2018, 1, 1)]\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "U použití `concat` je důležité, že všecha data mají stejný index. `axis=1` říká, že se mají skládat sloupce vedle sebe. Výchozí `axis=0` by spojovala data pod sebe a nedopadlo by to úplně dobře (můžeš vyzkoušet :). Detailněji si o spojování tabulek budeme povídat příště.\n", - "\n", - "Prohlédneme si výslednou tabulku `ruzyne_tidy`." + "Anebo dokonce i takto zjednodušeně:" ] }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -2058,18 +2595,18 @@ " \n", " \n", " \n", - " teplota průměrná\n", - " teplota maximální\n", - " teplota minimální\n", - " rychlost větru\n", - " tlak vzduchu\n", - " vlhkost vzduchu\n", - " úhrn srážek\n", - " celková výška sněhu\n", - " sluneční svit\n", - " \n", - " \n", - " datum\n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", + " \n", + " \n", + " time\n", " \n", " \n", " \n", @@ -2083,64 +2620,64 @@ " \n", " \n", " \n", - " 1961-01-01\n", - " -2.0\n", - " 1.0\n", - " -3.4\n", - " 1.7\n", - " 969.9\n", - " 87.0\n", - " 0.0\n", - " 6.0\n", - " 0.4\n", + " 2017-01-01\n", + " -6.2\n", + " -8.7\n", + " -2.2\n", + " NaN\n", + " NaN\n", + " 4.8\n", + " NaN\n", + " 1024.0\n", + " NaN\n", " \n", " \n", - " 1961-01-02\n", - " -1.9\n", - " -1.2\n", - " -2.4\n", - " 3.0\n", - " 965.2\n", - " 89.0\n", - " 0.0\n", - " 4.0\n", - " 0.0\n", + " 2017-01-02\n", + " -2.7\n", + " -8.7\n", + " -0.9\n", + " NaN\n", + " NaN\n", + " 20.4\n", + " NaN\n", + " 1018.7\n", + " NaN\n", " \n", " \n", - " 1961-01-03\n", - " 0.1\n", - " 1.0\n", - " -2.6\n", - " 2.7\n", - " 952.3\n", - " 80.0\n", - " 0.0\n", - " 3.0\n", - " 0.0\n", + " 2017-01-03\n", + " -1.2\n", + " -4.7\n", + " 0.6\n", + " NaN\n", + " NaN\n", + " 29.4\n", + " NaN\n", + " 1020.7\n", + " NaN\n", " \n", " \n", - " 1961-01-04\n", - " -0.3\n", - " 2.1\n", - " -2.0\n", - " 3.3\n", - " 953.6\n", - " 87.0\n", - " 0.0\n", - " 3.0\n", - " 1.0\n", + " 2017-01-04\n", + " 0.2\n", + " -1.5\n", + " 2.0\n", + " NaN\n", + " NaN\n", + " 39.3\n", + " NaN\n", + " 1006.6\n", + " NaN\n", " \n", " \n", - " 1961-01-05\n", - " 0.4\n", - " 2.8\n", - " -4.3\n", - " 6.3\n", - " 963.9\n", - " 81.0\n", - " 0.0\n", - " 2.0\n", - " 2.2\n", + " 2017-01-05\n", + " -4.6\n", + " -9.0\n", + " -1.2\n", + " NaN\n", + " NaN\n", + " 21.9\n", + " NaN\n", + " 1023.2\n", + " NaN\n", " \n", " \n", " ...\n", @@ -2155,175 +2692,144 @@ " ...\n", " \n", " \n", - " 2021-12-27\n", - " -2.1\n", - " -0.8\n", - " -5.3\n", - " 1.8\n", - " 964.9\n", - " 87.0\n", - " 0.0\n", - " 3.0\n", + " 2019-12-27\n", + " 1.7\n", + " 1.0\n", + " 3.2\n", " 0.1\n", + " NaN\n", + " 11.2\n", + " 25.9\n", + " 1028.2\n", + " NaN\n", " \n", " \n", - " 2021-12-28\n", - " 0.2\n", - " 1.5\n", - " -2.1\n", - " 3.6\n", - " 959.3\n", - " 93.0\n", - " 2.8\n", - " 3.0\n", - " 0.0\n", + " 2019-12-28\n", + " -0.4\n", + " -1.0\n", + " 1.0\n", + " 0.3\n", + " NaN\n", + " 16.3\n", + " 33.3\n", + " 1040.1\n", + " NaN\n", " \n", " \n", - " 2021-12-29\n", - " 4.1\n", - " 6.1\n", - " 0.2\n", - " 3.1\n", - " 964.0\n", - " 95.0\n", - " 1.2\n", - " 0.0\n", + " 2019-12-29\n", + " -1.5\n", + " -3.5\n", + " 0.7\n", " 0.0\n", + " NaN\n", + " 7.7\n", + " 18.5\n", + " 1041.4\n", + " NaN\n", " \n", " \n", - " 2021-12-30\n", - " 10.2\n", - " 11.9\n", - " 4.5\n", - " 6.9\n", - " 972.8\n", - " 92.0\n", + " 2019-12-30\n", " 0.4\n", + " -4.4\n", + " 4.7\n", " 0.0\n", - " 0.0\n", + " NaN\n", + " 8.6\n", + " 31.5\n", + " 1035.4\n", + " NaN\n", " \n", " \n", - " 2021-12-31\n", - " 11.0\n", - " 12.6\n", - " 10.3\n", - " 8.1\n", - " 976.2\n", - " 83.0\n", - " 0.0\n", + " 2019-12-31\n", + " 3.2\n", + " 1.7\n", + " 5.6\n", " 0.0\n", - " 2.7\n", + " NaN\n", + " 19.7\n", + " 43.0\n", + " 1030.4\n", + " NaN\n", " \n", " \n", "\n", - "

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1095 rows × 9 columns

\n", "" ], "text/plain": [ - " teplota průměrná teplota maximální teplota minimální \\\n", - "datum \n", - "1961-01-01 -2.0 1.0 -3.4 \n", - "1961-01-02 -1.9 -1.2 -2.4 \n", - "1961-01-03 0.1 1.0 -2.6 \n", - "1961-01-04 -0.3 2.1 -2.0 \n", - "1961-01-05 0.4 2.8 -4.3 \n", - "... ... ... ... \n", - "2021-12-27 -2.1 -0.8 -5.3 \n", - "2021-12-28 0.2 1.5 -2.1 \n", - "2021-12-29 4.1 6.1 0.2 \n", - "2021-12-30 10.2 11.9 4.5 \n", - "2021-12-31 11.0 12.6 10.3 \n", - "\n", - " rychlost větru tlak vzduchu vlhkost vzduchu úhrn srážek \\\n", - "datum \n", - "1961-01-01 1.7 969.9 87.0 0.0 \n", - "1961-01-02 3.0 965.2 89.0 0.0 \n", - "1961-01-03 2.7 952.3 80.0 0.0 \n", - "1961-01-04 3.3 953.6 87.0 0.0 \n", - "1961-01-05 6.3 963.9 81.0 0.0 \n", - "... ... ... ... ... \n", - "2021-12-27 1.8 964.9 87.0 0.0 \n", - "2021-12-28 3.6 959.3 93.0 2.8 \n", - "2021-12-29 3.1 964.0 95.0 1.2 \n", - "2021-12-30 6.9 972.8 92.0 0.4 \n", - "2021-12-31 8.1 976.2 83.0 0.0 \n", + " tavg tmin tmax prcp snow wspd wpgt pres tsun\n", + "time \n", + "2017-01-01 -6.2 -8.7 -2.2 NaN NaN 4.8 NaN 1024.0 NaN\n", + "2017-01-02 -2.7 -8.7 -0.9 NaN NaN 20.4 NaN 1018.7 NaN\n", + "2017-01-03 -1.2 -4.7 0.6 NaN NaN 29.4 NaN 1020.7 NaN\n", + "2017-01-04 0.2 -1.5 2.0 NaN NaN 39.3 NaN 1006.6 NaN\n", + "2017-01-05 -4.6 -9.0 -1.2 NaN NaN 21.9 NaN 1023.2 NaN\n", + "... ... ... ... ... ... ... ... ... ...\n", + "2019-12-27 1.7 1.0 3.2 0.1 NaN 11.2 25.9 1028.2 NaN\n", + "2019-12-28 -0.4 -1.0 1.0 0.3 NaN 16.3 33.3 1040.1 NaN\n", + "2019-12-29 -1.5 -3.5 0.7 0.0 NaN 7.7 18.5 1041.4 NaN\n", + "2019-12-30 0.4 -4.4 4.7 0.0 NaN 8.6 31.5 1035.4 NaN\n", + "2019-12-31 3.2 1.7 5.6 0.0 NaN 19.7 43.0 1030.4 NaN\n", "\n", - " celková výška sněhu sluneční svit \n", - "datum \n", - "1961-01-01 6.0 0.4 \n", - "1961-01-02 4.0 0.0 \n", - "1961-01-03 3.0 0.0 \n", - "1961-01-04 3.0 1.0 \n", - "1961-01-05 2.0 2.2 \n", - "... ... ... \n", - "2021-12-27 3.0 0.1 \n", - "2021-12-28 3.0 0.0 \n", - "2021-12-29 0.0 0.0 \n", - "2021-12-30 0.0 0.0 \n", - "2021-12-31 0.0 2.7 \n", - "\n", - "[22280 rows x 9 columns]" + "[1095 rows x 9 columns]" ] }, - "execution_count": 33, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy" + "denni_ruzyne.loc[\"2017\":\"2019\"]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Indexování a výběr intervalů\n", + "### Atributy časových proměnných\n", "\n", - "Data, která jsme načetli a vyčistili, tvoří vlastně několik časových řad v jednotlivých sloupcích tabulky `ruzyne_tidy`. Granularita (nebo frekvence či časové rozlišení) je jeden den.\n", + "Časové proměnné typu [`DatetimeIndex`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DatetimeIndex.html) poskytují velice užitečnou sadu atributů vracející\n", + "* části časového údaje, např. `.year` vrátí pouze rok, `.month` měsíc apod., \n", + "* relativní informace , např. `.weekday` nebo `.weekofyear`\n", + "* kalendářní vlastnosti jako `is_quarter_start` nebo `is_year_end`, které by bylo poměrně náročné zjišťovat numericky.\n", "\n", - "Pomocí `to_period()` bychom mohli datový typ indexu převést i na `period[D]`. To může zrychlit některé operace, pro naše použití to ale není nezbytné." + "Pokud se jedná o sloupec, je potřeba před atribut vložit ještě [`.dt`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.html) accessor. " ] }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "PeriodIndex(['1961-01-01', '1961-01-02', '1961-01-03', '1961-01-04',\n", - " '1961-01-05', '1961-01-06', '1961-01-07', '1961-01-08',\n", - " '1961-01-09', '1961-01-10',\n", - " ...\n", - " '2021-12-22', '2021-12-23', '2021-12-24', '2021-12-25',\n", - " '2021-12-26', '2021-12-27', '2021-12-28', '2021-12-29',\n", - " '2021-12-30', '2021-12-31'],\n", - " dtype='period[D]', name='datum', length=22280)" + "Index([1940, 1940, 1940, 1940, 1940, 1940, 1940, 1940, 1940, 1940,\n", + " ...\n", + " 2025, 2025, 2025, 2025, 2025, 2025, 2025, 2025, 2025, 2025],\n", + " dtype='int32', name='time', length=23258)" ] }, - "execution_count": 34, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy.index.to_period()" + "denni_ruzyne.index.year" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Už jsme si ukazovali indexování (výběr intervalu) pomocí `.loc`. U časových řad to funguje samozřejmě také. Pozor na to, že `.loc` vrací data *včetně* horní meze, *na rozdíl* od indexování `list`ů nebo numpy polí. \n", - "\n", - "Konkrétní období můžeme vybrat třeba takto:" + "Můžeme tak vybrat jeden celý rok např. takto:" ] }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -2347,18 +2853,18 @@ " \n", " \n", " \n", - " teplota průměrná\n", - " teplota maximální\n", - " teplota minimální\n", - " rychlost větru\n", - " tlak vzduchu\n", - " vlhkost vzduchu\n", - " úhrn srážek\n", - " celková výška sněhu\n", - " sluneční svit\n", - " \n", - " \n", - " datum\n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", + " \n", + " \n", + " time\n", " \n", " \n", " \n", @@ -2372,174 +2878,179 @@ " \n", " \n", " \n", - " 2017-12-24\n", - " 6.1\n", - " 7.0\n", - " 5.5\n", - " 7.7\n", - " 979.5\n", - " 82.0\n", - " 0.0\n", - " 0.0\n", - " 0.3\n", + " 2018-01-01\n", + " 5.3\n", + " 0.7\n", + " 7.5\n", + " NaN\n", + " NaN\n", + " 17.1\n", + " NaN\n", + " 1006.8\n", + " NaN\n", " \n", " \n", - " 2017-12-25\n", - " 1.7\n", - " 5.7\n", - " -0.6\n", - " 4.0\n", - " 975.4\n", - " 88.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 2018-01-02\n", + " 3.8\n", + " 1.5\n", + " 5.2\n", + " NaN\n", + " NaN\n", + " 23.4\n", + " NaN\n", + " 1009.0\n", + " NaN\n", + " \n", + " \n", + " 2018-01-03\n", + " 3.4\n", + " 0.5\n", + " 7.6\n", + " 1.0\n", + " NaN\n", + " 26.0\n", + " NaN\n", + " 999.2\n", + " NaN\n", + " \n", + " \n", + " 2018-01-04\n", + " 4.9\n", + " 4.2\n", + " 5.6\n", + " NaN\n", + " NaN\n", + " 25.2\n", + " NaN\n", + " 999.6\n", + " NaN\n", + " \n", + " \n", + " 2018-01-05\n", + " 6.9\n", + " 4.7\n", + " 9.0\n", + " NaN\n", + " NaN\n", + " 19.8\n", + " NaN\n", + " 1000.7\n", + " NaN\n", " \n", " \n", - " 2017-12-26\n", - " 1.2\n", - " 4.5\n", - " -4.5\n", - " 3.7\n", - " 964.1\n", - " 85.0\n", - " 0.0\n", - " 0.0\n", - " 1.6\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", + " ...\n", " \n", " \n", - " 2017-12-27\n", - " -0.7\n", - " 3.4\n", - " -3.5\n", - " 2.7\n", - " 949.1\n", - " 91.0\n", - " 2.2\n", + " 2018-12-27\n", + " 4.0\n", + " 3.0\n", + " 6.2\n", " 0.0\n", - " 0.8\n", + " NaN\n", + " 19.5\n", + " 31.5\n", + " 1026.8\n", + " NaN\n", " \n", " \n", - " 2017-12-28\n", - " 1.0\n", - " 1.5\n", - " -0.8\n", - " 5.7\n", - " 951.8\n", - " 87.0\n", - " 7.0\n", - " 0.0\n", + " 2018-12-28\n", + " 3.5\n", + " 0.6\n", + " 5.6\n", " 0.0\n", + " NaN\n", + " 15.3\n", + " 27.8\n", + " 1026.1\n", + " NaN\n", " \n", " \n", - " 2017-12-29\n", - " -1.7\n", - " 1.2\n", - " -3.8\n", - " 6.3\n", - " 965.0\n", - " 79.0\n", - " 0.1\n", - " 1.0\n", - " 1.9\n", - " \n", - " \n", - " 2017-12-30\n", - " 2.5\n", - " 4.8\n", - " -3.8\n", - " 5.7\n", - " 962.7\n", - " 86.0\n", - " 1.8\n", + " 2018-12-29\n", + " 2.6\n", " 1.0\n", - " 0.2\n", + " 4.0\n", + " 0.1\n", + " NaN\n", + " 19.5\n", + " 40.8\n", + " 1028.9\n", + " NaN\n", " \n", " \n", - " 2017-12-31\n", - " 9.1\n", - " 11.5\n", - " 4.5\n", - " 6.7\n", - " 964.6\n", - " 81.0\n", - " 0.5\n", - " 0.0\n", - " 1.2\n", + " 2018-12-30\n", + " 3.9\n", + " 2.0\n", + " 5.5\n", + " NaN\n", + " NaN\n", + " 27.4\n", + " 61.0\n", + " 1024.4\n", + " NaN\n", " \n", " \n", - " 2018-01-01\n", - " 4.1\n", - " 9.1\n", - " 0.4\n", - " 4.7\n", - " 962.9\n", - " 77.0\n", - " 0.0\n", - " 0.0\n", - " 0.4\n", + " 2018-12-31\n", + " 3.5\n", + " 1.5\n", + " 5.5\n", + " 0.2\n", + " NaN\n", + " 11.0\n", + " 29.6\n", + " 1031.0\n", + " NaN\n", " \n", " \n", "\n", + "

365 rows × 9 columns

\n", "" ], "text/plain": [ - " teplota průměrná teplota maximální teplota minimální \\\n", - "datum \n", - "2017-12-24 6.1 7.0 5.5 \n", - "2017-12-25 1.7 5.7 -0.6 \n", - "2017-12-26 1.2 4.5 -4.5 \n", - "2017-12-27 -0.7 3.4 -3.5 \n", - "2017-12-28 1.0 1.5 -0.8 \n", - "2017-12-29 -1.7 1.2 -3.8 \n", - "2017-12-30 2.5 4.8 -3.8 \n", - "2017-12-31 9.1 11.5 4.5 \n", - "2018-01-01 4.1 9.1 0.4 \n", + " tavg tmin tmax prcp snow wspd wpgt pres tsun\n", + "time \n", + "2018-01-01 5.3 0.7 7.5 NaN NaN 17.1 NaN 1006.8 NaN\n", + "2018-01-02 3.8 1.5 5.2 NaN NaN 23.4 NaN 1009.0 NaN\n", + "2018-01-03 3.4 0.5 7.6 1.0 NaN 26.0 NaN 999.2 NaN\n", + "2018-01-04 4.9 4.2 5.6 NaN NaN 25.2 NaN 999.6 NaN\n", + "2018-01-05 6.9 4.7 9.0 NaN NaN 19.8 NaN 1000.7 NaN\n", + "... ... ... ... ... ... ... ... ... ...\n", + "2018-12-27 4.0 3.0 6.2 0.0 NaN 19.5 31.5 1026.8 NaN\n", + "2018-12-28 3.5 0.6 5.6 0.0 NaN 15.3 27.8 1026.1 NaN\n", + "2018-12-29 2.6 1.0 4.0 0.1 NaN 19.5 40.8 1028.9 NaN\n", + "2018-12-30 3.9 2.0 5.5 NaN NaN 27.4 61.0 1024.4 NaN\n", + "2018-12-31 3.5 1.5 5.5 0.2 NaN 11.0 29.6 1031.0 NaN\n", "\n", - " rychlost větru tlak vzduchu vlhkost vzduchu úhrn srážek \\\n", - "datum \n", - "2017-12-24 7.7 979.5 82.0 0.0 \n", - "2017-12-25 4.0 975.4 88.0 0.0 \n", - "2017-12-26 3.7 964.1 85.0 0.0 \n", - "2017-12-27 2.7 949.1 91.0 2.2 \n", - "2017-12-28 5.7 951.8 87.0 7.0 \n", - "2017-12-29 6.3 965.0 79.0 0.1 \n", - "2017-12-30 5.7 962.7 86.0 1.8 \n", - "2017-12-31 6.7 964.6 81.0 0.5 \n", - "2018-01-01 4.7 962.9 77.0 0.0 \n", - "\n", - " celková výška sněhu sluneční svit \n", - "datum \n", - "2017-12-24 0.0 0.3 \n", - "2017-12-25 0.0 0.0 \n", - "2017-12-26 0.0 1.6 \n", - "2017-12-27 0.0 0.8 \n", - "2017-12-28 0.0 0.0 \n", - "2017-12-29 1.0 1.9 \n", - "2017-12-30 1.0 0.2 \n", - "2017-12-31 0.0 1.2 \n", - "2018-01-01 0.0 0.4 " + "[365 rows x 9 columns]" ] }, - "execution_count": 35, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy.loc[pd.Timestamp(2017, 12, 24) : pd.Timestamp(2018, 1, 1)]\n" + "denni_ruzyne.loc[denni_ruzyne.index.year == 2018]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Anebo dokonce i takto zjednodušeně:" + "Nebo můžeme získat data pro všechny dny před rokem 1989, které jsou začátky kvartálů a zároveň to jsou pondělky." ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -2563,18 +3074,18 @@ " \n", " \n", " \n", - " teplota průměrná\n", - " teplota maximální\n", - " teplota minimální\n", - " rychlost větru\n", - " tlak vzduchu\n", - " vlhkost vzduchu\n", - " úhrn srážek\n", - " celková výška sněhu\n", - " sluneční svit\n", - " \n", - " \n", - " datum\n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", + " \n", + " \n", + " time\n", " \n", " \n", " \n", @@ -2588,244 +3099,368 @@ " \n", " \n", " \n", - " 2017-01-01\n", - " -6.5\n", - " -1.8\n", - " -9.1\n", - " 1.0\n", - " 976.2\n", - " 92.0\n", - " 0.0\n", - " 0.0\n", - " 4.7\n", + " 1940-04-01\n", + " 6.8\n", + " 1.1\n", + " 12.8\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2017-01-02\n", - " -2.0\n", - " -0.8\n", - " -9.1\n", - " 7.0\n", - " 973.0\n", - " 88.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 1957-04-01\n", + " 5.6\n", + " 3.9\n", + " 8.9\n", + " 3.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2017-01-03\n", - " -0.3\n", - " 0.6\n", - " -5.4\n", - " 8.3\n", - " 974.4\n", - " 78.0\n", - " 0.6\n", - " 1.0\n", - " 0.6\n", + " 1962-01-01\n", + " 0.3\n", + " -3.9\n", + " 2.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2017-01-04\n", - " 0.2\n", - " 2.4\n", - " -0.8\n", - " 9.3\n", - " 961.1\n", - " 78.0\n", - " 3.5\n", - " 2.0\n", - " 0.8\n", + " 1962-10-01\n", + " 14.9\n", + " 7.8\n", + " 22.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2017-01-05\n", - " -6.5\n", - " -0.3\n", - " -8.7\n", - " 6.0\n", - " 979.6\n", - " 88.0\n", - " 1.6\n", - " 5.0\n", + " 1963-04-01\n", + " 1.2\n", + " NaN\n", + " 2.2\n", " 1.5\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", + " 1963-07-01\n", + " 17.6\n", + " 15.0\n", + " 21.1\n", + " 12.7\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2019-12-27\n", - " 1.5\n", - " 3.4\n", - " 0.7\n", - " 3.3\n", - " 983.5\n", - " 78.0\n", - " 0.4\n", + " 1973-01-01\n", + " -2.6\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 12.2\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1973-10-01\n", + " 9.6\n", + " 6.0\n", + " 13.0\n", " 0.0\n", + " NaN\n", + " 3.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1974-04-01\n", + " 10.4\n", + " 5.0\n", + " 16.0\n", " 0.0\n", + " NaN\n", + " 8.6\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1974-07-01\n", + " 15.8\n", + " 13.0\n", + " 19.0\n", + " 5.1\n", + " NaN\n", + " 23.3\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1979-01-01\n", + " -17.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " 26.9\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2019-12-28\n", - " -0.8\n", - " 1.2\n", - " -1.1\n", - " 4.3\n", - " 994.5\n", - " 79.0\n", - " 0.0\n", - " 0.0\n", + " 1979-10-01\n", + " 7.7\n", + " 1.0\n", + " 14.0\n", " 0.0\n", + " NaN\n", + " 11.6\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2019-12-29\n", - " -2.1\n", - " 1.0\n", - " -3.7\n", - " 1.9\n", - " 994.5\n", - " 72.0\n", - " 0.0\n", + " 1984-10-01\n", + " 11.4\n", + " 9.0\n", + " 16.0\n", " 0.0\n", - " 5.7\n", + " NaN\n", + " 6.3\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2019-12-30\n", - " 1.8\n", - " 5.2\n", - " -4.6\n", - " 2.4\n", - " 988.4\n", - " 61.0\n", - " 0.0\n", - " 0.0\n", - " 4.6\n", + " 1985-04-01\n", + " 8.6\n", + " 4.7\n", + " 13.5\n", + " 2.8\n", + " NaN\n", + " 20.9\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 2019-12-31\n", - " 2.9\n", - " 5.9\n", - " 1.4\n", - " 6.3\n", - " 985.7\n", - " 65.0\n", - " 0.0\n", - " 0.0\n", - " 2.1\n", + " 1985-07-01\n", + " 15.1\n", + " 12.0\n", + " 21.9\n", + " NaN\n", + " NaN\n", + " 8.6\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", "\n", - "

1095 rows × 9 columns

\n", "" ], "text/plain": [ - " teplota průměrná teplota maximální teplota minimální \\\n", - "datum \n", - "2017-01-01 -6.5 -1.8 -9.1 \n", - "2017-01-02 -2.0 -0.8 -9.1 \n", - "2017-01-03 -0.3 0.6 -5.4 \n", - "2017-01-04 0.2 2.4 -0.8 \n", - "2017-01-05 -6.5 -0.3 -8.7 \n", - "... ... ... ... \n", - "2019-12-27 1.5 3.4 0.7 \n", - "2019-12-28 -0.8 1.2 -1.1 \n", - "2019-12-29 -2.1 1.0 -3.7 \n", - "2019-12-30 1.8 5.2 -4.6 \n", - "2019-12-31 2.9 5.9 1.4 \n", - "\n", - " rychlost větru tlak vzduchu vlhkost vzduchu úhrn srážek \\\n", - "datum \n", - "2017-01-01 1.0 976.2 92.0 0.0 \n", - "2017-01-02 7.0 973.0 88.0 0.0 \n", - "2017-01-03 8.3 974.4 78.0 0.6 \n", - "2017-01-04 9.3 961.1 78.0 3.5 \n", - "2017-01-05 6.0 979.6 88.0 1.6 \n", - "... ... ... ... ... \n", - "2019-12-27 3.3 983.5 78.0 0.4 \n", - "2019-12-28 4.3 994.5 79.0 0.0 \n", - "2019-12-29 1.9 994.5 72.0 0.0 \n", - "2019-12-30 2.4 988.4 61.0 0.0 \n", - "2019-12-31 6.3 985.7 65.0 0.0 \n", - "\n", - " celková výška sněhu sluneční svit \n", - "datum \n", - "2017-01-01 0.0 4.7 \n", - "2017-01-02 0.0 0.0 \n", - "2017-01-03 1.0 0.6 \n", - "2017-01-04 2.0 0.8 \n", - "2017-01-05 5.0 1.5 \n", - "... ... ... \n", - "2019-12-27 0.0 0.0 \n", - "2019-12-28 0.0 0.0 \n", - "2019-12-29 0.0 5.7 \n", - "2019-12-30 0.0 4.6 \n", - "2019-12-31 0.0 2.1 \n", - "\n", - "[1095 rows x 9 columns]" + " tavg tmin tmax prcp snow wspd wpgt pres tsun\n", + "time \n", + "1940-04-01 6.8 1.1 12.8 NaN NaN NaN NaN NaN NaN\n", + "1957-04-01 5.6 3.9 8.9 3.0 NaN NaN NaN NaN NaN\n", + "1962-01-01 0.3 -3.9 2.2 NaN NaN NaN NaN NaN NaN\n", + "1962-10-01 14.9 7.8 22.2 NaN NaN NaN NaN NaN NaN\n", + "1963-04-01 1.2 NaN 2.2 1.5 NaN NaN NaN NaN NaN\n", + "1963-07-01 17.6 15.0 21.1 12.7 NaN NaN NaN NaN NaN\n", + "1973-01-01 -2.6 NaN NaN NaN NaN 12.2 NaN NaN NaN\n", + "1973-10-01 9.6 6.0 13.0 0.0 NaN 3.0 NaN NaN NaN\n", + "1974-04-01 10.4 5.0 16.0 0.0 NaN 8.6 NaN NaN NaN\n", + "1974-07-01 15.8 13.0 19.0 5.1 NaN 23.3 NaN NaN NaN\n", + "1979-01-01 -17.0 NaN NaN NaN NaN 26.9 NaN NaN NaN\n", + "1979-10-01 7.7 1.0 14.0 0.0 NaN 11.6 NaN NaN NaN\n", + "1984-10-01 11.4 9.0 16.0 0.0 NaN 6.3 NaN NaN NaN\n", + "1985-04-01 8.6 4.7 13.5 2.8 NaN 20.9 NaN NaN NaN\n", + "1985-07-01 15.1 12.0 21.9 NaN NaN 8.6 NaN NaN NaN" ] }, - "execution_count": 36, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy.loc[\"2017\":\"2019\"]" + "denni_ruzyne.loc[\n", + " denni_ruzyne.index.is_quarter_start\n", + " & (denni_ruzyne.index.weekday == 0)\n", + " & (denni_ruzyne.index.year < 1989)\n", + "]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Atributy časových proměnných\n", + "**Úkol:** Nejstarší tag Pandas na https://github.com/pandas-dev/pandas je verze 0.3.0 z 20. února 2011. Jaké bylo v ten den v Praze - Ruzyni počasí?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol:** Jaká byla průměrná teplota první (a jedinou) neděli v roce 2010, která byla zároveň začátkem měsíce? Pokud máte řešení a čas, zkuste vymyslet aternativní způsob(y). " + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "# odkomentuj a doplň\n", + "# denni_ruzyne.loc[\n", + "# ___\n", + "# & (___)\n", + "# & (___),\n", + "# \"teplota průměrná\",\n", + "# ]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Základní vizualizace a statistika\n", "\n", - "Časové proměnné typu [`DatetimeIndex`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DatetimeIndex.html) poskytují velice užitečnou sadu atributů vracející\n", - "* části časového údaje, např. `.year` vrátí pouze rok, `.month` měsíc apod., \n", - "* relativní informace , např. `.weekday` nebo `.weekofyear`\n", - "* kalendářní vlastnosti jako `is_quarter_start` nebo `is_year_end`, které by bylo poměrně náročné zjišťovat numericky.\n", + "Vykreslíme si naše data co nejjednoduššími způsoby, jaké nám pandy nabízí. Zkusme třeba rovnou `.plot()`" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "denni_ruzyne.plot();" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Tam toho moc vidět není. Jedním z problémů je různá škála veličin. A také bychom si graf mohli trochu zvětšit." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "denni_ruzyne.plot(subplots=True, figsize=(12, 9));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Tohle už je docela užitečné, leccos na grafu vidět je. Výchozí čárový (`line`) graf je pro časové řady často vhodný.\n", "\n", - "Pokud se jedná o sloupec, je potřeba před atribut vložit ještě [`.dt`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.html) accessor. " + "Navíc už si graficky odpovídáme na to, proč máme tolik hodnot, kolik jich máme: Různé veličiny se v některých letech prostě vůbec neměřily, jiné se měřily jen občas.\n", + "\n", + "Pomocí argumentu `layout` můžeme podgrafy uspořádat do více sloupců. Pokud navíc vybereme kratší časové období, dostaneme už celkem srozumitelný výsledek." ] }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 24, "metadata": {}, "outputs": [ { "data": { + "image/png": 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", "text/plain": [ - "Index([1961, 1961, 1961, 1961, 1961, 1961, 1961, 1961, 1961, 1961,\n", - " ...\n", - " 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021],\n", - " dtype='int32', name='datum', length=22280)" + "
" ] }, - "execution_count": 37, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "ruzyne_tidy.index.year" + "denni_ruzyne.loc[\"2023\"].plot(\n", + " subplots=True, layout=(4, 3), figsize=(12, 9)\n", + ");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Můžeme tak vybrat jeden celý rok např. takto:" + "I tady je ale dat poměrně hodně a na grafech vidíme spoustu rozptylu - hodnoty skáčou rychle nahoru / dolů. V takovém případě je na čase vzít si na pomoc statistiku!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Trocha statistiky - opravdu jen základní\n", + "\n", + "Není cílem tohoto kurzu (a ani v jeho možnostech) podrobně a rigorózně učit statistiku (\"Statistika nuda je...\"). Jednoduché základy, které zvládají i 🐼🐼🐼, spolu jistě zvládneme a přesvědčíme se, že jsou i užitečné (\"...má však cenné údaje...\").\n", + "\n", + "Pokud se budeš chtít dozvědět víc, koukni třeba na https://www.poritz.net/jonathan/share/ldlos.pdf, nebo na http://greenteapress.com/thinkstats2/thinkstats2.pdf nebo třeba i na Bayesovskou statistiku http://www.greenteapress.com/thinkbayes/thinkbayes.pdf." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Metoda [`DataFrame.describe`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.describe.html#pandas.DataFrame.describe) je jednoduchou volbou pro získání základních statistik celé tabulky." ] }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -2849,232 +3484,174 @@ " \n", " \n", " \n", - " teplota průměrná\n", - " teplota maximální\n", - " teplota minimální\n", - " rychlost větru\n", - " tlak vzduchu\n", - " vlhkost vzduchu\n", - " úhrn srážek\n", - " celková výška sněhu\n", - " sluneční svit\n", - " \n", - " \n", - " datum\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", " \n", " \n", " \n", " \n", - " 2018-01-01\n", - " 4.1\n", - " 9.1\n", - " 0.4\n", - " 4.7\n", - " 962.9\n", - " 77.0\n", - " 0.0\n", - " 0.0\n", - " 0.4\n", - " \n", - " \n", - " 2018-01-02\n", - " 3.9\n", - " 5.7\n", - " 0.5\n", - " 6.9\n", - " 965.8\n", - " 81.0\n", - " 1.0\n", - " 0.0\n", - " 0.5\n", - " \n", - " \n", - " 2018-01-03\n", - " 4.6\n", - " 7.6\n", - " 0.5\n", - " 9.3\n", - " 952.9\n", - " 81.0\n", - " 7.9\n", - " 0.0\n", - " 0.8\n", - " \n", - " \n", - " 2018-01-04\n", - " 4.5\n", - " 5.7\n", - " 3.9\n", - " 5.9\n", - " 955.9\n", - " 82.0\n", - " 0.9\n", - " 0.0\n", - " 0.5\n", - " \n", - " \n", - " 2018-01-05\n", - " 7.3\n", - " 9.0\n", - " 4.1\n", - " 5.6\n", - " 958.5\n", - " 80.0\n", - " 0.3\n", - " 0.0\n", - " 0.0\n", + " count\n", + " 23258.000000\n", + " 20595.000000\n", + " 22769.000000\n", + " 14643.000000\n", + " 1051.000000\n", + " 16996.000000\n", + " 2588.000000\n", + " 11168.000000\n", + " 1118.000000\n", " \n", " \n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", + " mean\n", + " 8.633915\n", + " 4.478631\n", + " 13.237187\n", + " 1.609131\n", + " 7.550904\n", + " 14.196276\n", + " 33.702125\n", + " 1017.130632\n", + " 276.325581\n", " \n", - " \n", - " 2018-12-27\n", - " 4.0\n", - " 6.5\n", - " 2.7\n", - " 5.4\n", - " 981.4\n", - " 88.0\n", - " 0.0\n", - " 0.0\n", - " 0.5\n", + " \n", + " std\n", + " 8.105865\n", + " 7.136165\n", + " 9.424716\n", + " 5.329052\n", + " 14.504778\n", + " 6.967221\n", + " 13.409534\n", + " 8.598222\n", + " 219.449714\n", " \n", " \n", - " 2018-12-28\n", - " 3.9\n", - " 6.2\n", - " 0.3\n", - " 3.9\n", - " 981.5\n", - " 82.0\n", - " 0.0\n", - " 0.0\n", - " 3.9\n", + " min\n", + " -23.100000\n", + " -27.800000\n", + " -17.800000\n", + " 0.000000\n", + " 1.000000\n", + " 0.200000\n", + " 13.000000\n", + " 971.100000\n", + " 0.000000\n", " \n", " \n", - " 2018-12-29\n", - " 2.2\n", - " 4.8\n", - " 1.3\n", - " 5.8\n", - " 983.8\n", - " 87.0\n", - " 0.8\n", - " 0.0\n", - " 0.5\n", + " 25%\n", + " 2.400000\n", + " -0.200000\n", + " 5.700000\n", + " 0.000000\n", + " 2.000000\n", + " 9.100000\n", + " 24.100000\n", + " 1011.900000\n", + " 90.000000\n", " \n", " \n", - " 2018-12-30\n", - " 4.1\n", - " 5.8\n", - " 1.0\n", - " 7.9\n", - " 980.0\n", - " 82.0\n", - " 0.5\n", - " 0.0\n", - " 0.5\n", + " 50%\n", + " 9.100000\n", + " 5.000000\n", + " 13.800000\n", + " 0.000000\n", + " 4.000000\n", + " 12.700000\n", + " 29.600000\n", + " 1017.000000\n", + " 230.500000\n", " \n", " \n", - " 2018-12-31\n", - " 3.7\n", - " 5.4\n", - " 1.2\n", - " 3.2\n", - " 986.2\n", - " 85.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 75%\n", + " 15.200000\n", + " 10.000000\n", + " 20.900000\n", + " 1.300000\n", + " 10.000000\n", + " 17.800000\n", + " 40.800000\n", + " 1022.400000\n", + " 433.750000\n", + " \n", + " \n", + " max\n", + " 28.600000\n", + " 21.000000\n", + " 37.400000\n", + " 301.000000\n", + " 296.000000\n", + " 58.000000\n", + " 115.000000\n", + " 1046.600000\n", + " 902.000000\n", " \n", " \n", "\n", - "

365 rows × 9 columns

\n", "" ], "text/plain": [ - " teplota průměrná teplota maximální teplota minimální \\\n", - "datum \n", - "2018-01-01 4.1 9.1 0.4 \n", - "2018-01-02 3.9 5.7 0.5 \n", - "2018-01-03 4.6 7.6 0.5 \n", - "2018-01-04 4.5 5.7 3.9 \n", - "2018-01-05 7.3 9.0 4.1 \n", - "... ... ... ... \n", - "2018-12-27 4.0 6.5 2.7 \n", - "2018-12-28 3.9 6.2 0.3 \n", - "2018-12-29 2.2 4.8 1.3 \n", - "2018-12-30 4.1 5.8 1.0 \n", - "2018-12-31 3.7 5.4 1.2 \n", + " tavg tmin tmax prcp snow \\\n", + "count 23258.000000 20595.000000 22769.000000 14643.000000 1051.000000 \n", + "mean 8.633915 4.478631 13.237187 1.609131 7.550904 \n", + "std 8.105865 7.136165 9.424716 5.329052 14.504778 \n", + "min -23.100000 -27.800000 -17.800000 0.000000 1.000000 \n", + "25% 2.400000 -0.200000 5.700000 0.000000 2.000000 \n", + "50% 9.100000 5.000000 13.800000 0.000000 4.000000 \n", + "75% 15.200000 10.000000 20.900000 1.300000 10.000000 \n", + "max 28.600000 21.000000 37.400000 301.000000 296.000000 \n", "\n", - " rychlost větru tlak vzduchu vlhkost vzduchu úhrn srážek \\\n", - "datum \n", - "2018-01-01 4.7 962.9 77.0 0.0 \n", - "2018-01-02 6.9 965.8 81.0 1.0 \n", - "2018-01-03 9.3 952.9 81.0 7.9 \n", - "2018-01-04 5.9 955.9 82.0 0.9 \n", - "2018-01-05 5.6 958.5 80.0 0.3 \n", - "... ... ... ... ... \n", - "2018-12-27 5.4 981.4 88.0 0.0 \n", - "2018-12-28 3.9 981.5 82.0 0.0 \n", - "2018-12-29 5.8 983.8 87.0 0.8 \n", - "2018-12-30 7.9 980.0 82.0 0.5 \n", - "2018-12-31 3.2 986.2 85.0 0.0 \n", - "\n", - " celková výška sněhu sluneční svit \n", - "datum \n", - "2018-01-01 0.0 0.4 \n", - "2018-01-02 0.0 0.5 \n", - "2018-01-03 0.0 0.8 \n", - "2018-01-04 0.0 0.5 \n", - "2018-01-05 0.0 0.0 \n", - "... ... ... \n", - "2018-12-27 0.0 0.5 \n", - "2018-12-28 0.0 3.9 \n", - "2018-12-29 0.0 0.5 \n", - "2018-12-30 0.0 0.5 \n", - "2018-12-31 0.0 0.0 \n", - "\n", - "[365 rows x 9 columns]" + " wspd wpgt pres tsun \n", + "count 16996.000000 2588.000000 11168.000000 1118.000000 \n", + "mean 14.196276 33.702125 1017.130632 276.325581 \n", + "std 6.967221 13.409534 8.598222 219.449714 \n", + "min 0.200000 13.000000 971.100000 0.000000 \n", + "25% 9.100000 24.100000 1011.900000 90.000000 \n", + "50% 12.700000 29.600000 1017.000000 230.500000 \n", + "75% 17.800000 40.800000 1022.400000 433.750000 \n", + "max 58.000000 115.000000 1046.600000 902.000000 " ] }, - "execution_count": 38, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy.loc[ruzyne_tidy.index.year == 2018]" + "denni_ruzyne.describe()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Nebo můžeme získat data pro všechny dny před rokem 1989, které jsou začátky kvartálů a zároveň to jsou pondělky." + "Pro každý sloupec vidíme několik souhrnných (statistických údajů).\n", + "* `count` udává počet hodnot.\n", + "* `mean` je střední hodnota, vypočítaná jako aritmetický průměr. \n", + "* `std` je směrodatná odchylka, která ukazuje rozptyl dat - jak moc můžeme očekávat, že se data v souboru budou lišit od střední hodnoty.\n", + "* `min` a `max` jsou nejmenší a největší hodnoty ve sloupci.\n", + "* Procenta označují kvantily, `25%` a `75%` je hodnota prvního a třetího \"kvartilu\". Pokud bychom sloupec seřadili podle velikosti, bude čtvrtina dat menší než hodnota prvního kvartilu a čtvrtina dat bude větší než hodnota třetího kvartilu. Konkrétně čtvrtina všech dní v našich datech měla minimální teplotu menší než -0.7 °C a čtvrtina dní zase měla maximální teplotu větší než 20.5 °C. \n", + "* `50%` se označuje jako medián - polovina dat je menší než medián (a ta druhá polovina je samozřejmě zase větší než medián).\n", + "\n", + "Za chvilku si ještě ukážeme, jak tyto hodnoty souvisí s distribuční funkcí a vše ti bude hned jasnější :)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`describe` můžeme samozřejmě použít i na nějakou podmožinu dat. Takto třeba vypadá statistika počasí v Ruzyni v lednu." ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -3098,346 +3675,259 @@ " \n", " \n", " \n", - " teplota průměrná\n", - " teplota maximální\n", - " teplota minimální\n", - " rychlost větru\n", - " tlak vzduchu\n", - " vlhkost vzduchu\n", - " úhrn srážek\n", - " celková výška sněhu\n", - " sluneční svit\n", - " \n", - " \n", - " datum\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " tavg\n", + " tmin\n", + " tmax\n", + " prcp\n", + " snow\n", + " wspd\n", + " wpgt\n", + " pres\n", + " tsun\n", " \n", " \n", " \n", " \n", - " 1962-01-01\n", - " 0.2\n", - " 2.4\n", - " -4.0\n", - " 4.3\n", - " 966.5\n", - " 75.0\n", - " 0.0\n", - " 1.0\n", - " 0.0\n", - " \n", - " \n", - " 1962-10-01\n", - " 15.6\n", - " 22.4\n", - " 8.3\n", - " 1.7\n", - " 976.6\n", - " 73.0\n", - " 0.0\n", - " 0.0\n", - " 8.8\n", - " \n", - " \n", - " 1963-04-01\n", - " 1.0\n", - " 2.9\n", - " 0.6\n", - " 2.7\n", - " 971.9\n", - " 96.0\n", - " 1.3\n", - " 0.0\n", - " 0.0\n", - " \n", - " \n", - " 1963-07-01\n", - " 17.3\n", - " 21.2\n", - " 15.4\n", - " 2.0\n", - " 972.1\n", - " 79.0\n", - " 0.0\n", - " 0.0\n", - " 1.0\n", - " \n", - " \n", - " 1968-01-01\n", - " -4.1\n", - " 0.4\n", - " -6.5\n", - " 4.0\n", - " 958.0\n", - " 82.0\n", - " 0.4\n", - " 1.0\n", - " 0.0\n", - " \n", - " \n", - " 1968-04-01\n", - " 8.5\n", - " 17.6\n", - " 0.2\n", - " 4.3\n", - " 973.0\n", - " 55.0\n", - " 0.0\n", - " 0.0\n", - " 11.8\n", - " \n", - " \n", - " 1968-07-01\n", - " 20.9\n", - " 25.9\n", - " 11.3\n", - " 3.7\n", - " 980.8\n", - " 62.0\n", - " 0.0\n", - " 0.0\n", - " 14.3\n", - " \n", - " \n", - " 1973-01-01\n", - " -2.1\n", - " 3.8\n", - " -9.2\n", - " 3.3\n", - " 983.5\n", - " 57.0\n", - " 0.0\n", - " 0.0\n", - " 6.3\n", - " \n", - " \n", - " 1973-10-01\n", - " 9.7\n", - " 12.8\n", - " 6.2\n", - " 1.3\n", - " 977.7\n", - " 74.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " count\n", + " 1906.000000\n", + " 1616.000000\n", + " 1823.000000\n", + " 1027.000000\n", + " 305.000000\n", + " 1462.000000\n", + " 217.000000\n", + " 953.000000\n", + " 93.000000\n", " \n", " \n", - " 1974-04-01\n", - " 10.3\n", - " 15.5\n", - " 5.4\n", - " 2.7\n", - " 970.2\n", - " 64.0\n", - " 0.0\n", - " 0.0\n", - " 1.9\n", + " mean\n", + " -1.457922\n", + " -4.038552\n", + " 1.213275\n", + " 0.858812\n", + " 8.045902\n", + " 16.667921\n", + " 38.267281\n", + " 1019.951207\n", + " 93.913978\n", " \n", " \n", - " 1974-07-01\n", - " 15.7\n", - " 19.2\n", - " 13.4\n", - " 9.0\n", - " 967.4\n", - " 83.0\n", - " 1.2\n", - " 0.0\n", - " 0.8\n", + " std\n", + " 5.237619\n", + " 5.653606\n", + " 5.087210\n", + " 1.641651\n", + " 9.893405\n", + " 9.490501\n", + " 16.080667\n", + " 11.225654\n", + " 97.403091\n", " \n", " \n", - " 1979-01-01\n", - " -16.8\n", - " -11.8\n", - " -19.5\n", - " 3.3\n", - " 960.4\n", - " 76.0\n", - " 0.2\n", - " 9.0\n", - " 0.0\n", + " min\n", + " -22.000000\n", + " -24.000000\n", + " -17.000000\n", + " 0.000000\n", + " 1.000000\n", + " 0.800000\n", + " 13.000000\n", + " 977.600000\n", + " 0.000000\n", " \n", " \n", - " 1979-10-01\n", - " 7.8\n", - " 14.2\n", - " 0.9\n", - " 4.3\n", - " 978.8\n", - " 77.0\n", - " 0.0\n", - " 0.0\n", - " 8.3\n", + " 25%\n", + " -4.300000\n", + " -7.200000\n", + " -1.900000\n", + " 0.000000\n", + " 3.000000\n", + " 9.200000\n", + " 24.100000\n", + " 1012.400000\n", + " 19.000000\n", " \n", " \n", - " 1984-10-01\n", - " 11.3\n", - " 16.0\n", - " 9.9\n", - " 2.0\n", - " 964.4\n", - " 94.0\n", - " 0.1\n", - " 0.0\n", - " 0.5\n", + " 50%\n", + " -0.700000\n", + " -3.000000\n", + " 1.400000\n", + " 0.000000\n", + " 5.000000\n", + " 14.700000\n", + " 37.000000\n", + " 1020.600000\n", + " 61.000000\n", " \n", " \n", - " 1985-04-01\n", - " 8.8\n", - " 13.5\n", - " 4.7\n", - " 6.0\n", - " 973.4\n", - " 87.0\n", - " 0.9\n", - " 0.0\n", - " 2.7\n", + " 75%\n", + " 2.000000\n", + " 0.000000\n", + " 4.500000\n", + " 1.300000\n", + " 12.000000\n", + " 22.675000\n", + " 50.000000\n", + " 1028.000000\n", + " 130.000000\n", " \n", " \n", - " 1985-07-01\n", - " 14.8\n", - " 21.9\n", - " 12.0\n", - " 3.0\n", - " 970.7\n", - " 83.0\n", - " 7.6\n", - " 0.0\n", - " 3.7\n", + " max\n", + " 12.600000\n", + " 9.600000\n", + " 16.000000\n", + " 16.000000\n", + " 140.000000\n", + " 58.000000\n", + " 115.000000\n", + " 1046.500000\n", + " 402.000000\n", " \n", " \n", "\n", "" ], "text/plain": [ - " teplota průměrná teplota maximální teplota minimální \\\n", - "datum \n", - "1962-01-01 0.2 2.4 -4.0 \n", - "1962-10-01 15.6 22.4 8.3 \n", - "1963-04-01 1.0 2.9 0.6 \n", - "1963-07-01 17.3 21.2 15.4 \n", - "1968-01-01 -4.1 0.4 -6.5 \n", - "1968-04-01 8.5 17.6 0.2 \n", - "1968-07-01 20.9 25.9 11.3 \n", - "1973-01-01 -2.1 3.8 -9.2 \n", - "1973-10-01 9.7 12.8 6.2 \n", - "1974-04-01 10.3 15.5 5.4 \n", - "1974-07-01 15.7 19.2 13.4 \n", - "1979-01-01 -16.8 -11.8 -19.5 \n", - "1979-10-01 7.8 14.2 0.9 \n", - "1984-10-01 11.3 16.0 9.9 \n", - "1985-04-01 8.8 13.5 4.7 \n", - "1985-07-01 14.8 21.9 12.0 \n", - "\n", - " rychlost větru tlak vzduchu vlhkost vzduchu úhrn srážek \\\n", - "datum \n", - "1962-01-01 4.3 966.5 75.0 0.0 \n", - "1962-10-01 1.7 976.6 73.0 0.0 \n", - "1963-04-01 2.7 971.9 96.0 1.3 \n", - "1963-07-01 2.0 972.1 79.0 0.0 \n", - "1968-01-01 4.0 958.0 82.0 0.4 \n", - "1968-04-01 4.3 973.0 55.0 0.0 \n", - "1968-07-01 3.7 980.8 62.0 0.0 \n", - "1973-01-01 3.3 983.5 57.0 0.0 \n", - "1973-10-01 1.3 977.7 74.0 0.0 \n", - "1974-04-01 2.7 970.2 64.0 0.0 \n", - "1974-07-01 9.0 967.4 83.0 1.2 \n", - "1979-01-01 3.3 960.4 76.0 0.2 \n", - "1979-10-01 4.3 978.8 77.0 0.0 \n", - "1984-10-01 2.0 964.4 94.0 0.1 \n", - "1985-04-01 6.0 973.4 87.0 0.9 \n", - "1985-07-01 3.0 970.7 83.0 7.6 \n", + " tavg tmin tmax prcp snow \\\n", + "count 1906.000000 1616.000000 1823.000000 1027.000000 305.000000 \n", + "mean -1.457922 -4.038552 1.213275 0.858812 8.045902 \n", + "std 5.237619 5.653606 5.087210 1.641651 9.893405 \n", + "min -22.000000 -24.000000 -17.000000 0.000000 1.000000 \n", + "25% -4.300000 -7.200000 -1.900000 0.000000 3.000000 \n", + "50% -0.700000 -3.000000 1.400000 0.000000 5.000000 \n", + "75% 2.000000 0.000000 4.500000 1.300000 12.000000 \n", + "max 12.600000 9.600000 16.000000 16.000000 140.000000 \n", "\n", - " celková výška sněhu sluneční svit \n", - "datum \n", - "1962-01-01 1.0 0.0 \n", - "1962-10-01 0.0 8.8 \n", - "1963-04-01 0.0 0.0 \n", - "1963-07-01 0.0 1.0 \n", - "1968-01-01 1.0 0.0 \n", - "1968-04-01 0.0 11.8 \n", - "1968-07-01 0.0 14.3 \n", - "1973-01-01 0.0 6.3 \n", - "1973-10-01 0.0 0.0 \n", - "1974-04-01 0.0 1.9 \n", - "1974-07-01 0.0 0.8 \n", - "1979-01-01 9.0 0.0 \n", - "1979-10-01 0.0 8.3 \n", - "1984-10-01 0.0 0.5 \n", - "1985-04-01 0.0 2.7 \n", - "1985-07-01 0.0 3.7 " + " wspd wpgt pres tsun \n", + "count 1462.000000 217.000000 953.000000 93.000000 \n", + "mean 16.667921 38.267281 1019.951207 93.913978 \n", + "std 9.490501 16.080667 11.225654 97.403091 \n", + "min 0.800000 13.000000 977.600000 0.000000 \n", + "25% 9.200000 24.100000 1012.400000 19.000000 \n", + "50% 14.700000 37.000000 1020.600000 61.000000 \n", + "75% 22.675000 50.000000 1028.000000 130.000000 \n", + "max 58.000000 115.000000 1046.500000 402.000000 " ] }, - "execution_count": 39, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy.loc[\n", - " ruzyne_tidy.index.is_quarter_start\n", - " & (ruzyne_tidy.index.weekday == 0)\n", - " & (ruzyne_tidy.index.year < 1989)\n", - "]" + "denni_ruzyne[denni_ruzyne.index.month == 1].describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Statistické rozdělení\n", + "\n", + "Pojďme zkusit pojmy kolem pravděpodobnosti, jako třeba rozdělovací funkce nebo hustota pravděpodobnosti, jejichž formální definice a vlastnosti lze najít v knihách (např. v těch uvedených výše) nebo na [wikipedii](https://cs.wikipedia.org/wiki/Distribu%C4%8Dn%C3%AD_funkce), objevovat a zkoumat spíš názorně a intuitivně.\n", + "\n", + "Jedním ze základních a nesmírně užitečných nástrojů na vizualizaci souboru dat je [histogram](https://cs.wikipedia.org/wiki/Histogram). Zjednodušeně řečeno, histogram vytvoří chlívečky podle velikosti dat - do každého chlívečku patří data v nějakém intervalu od - do. Počet hodnot, které ze souboru dat spadnou do daného chlívečku, určuje velikost (výšku) chlívečku.\n", + "\n", + "Histogram zobrazíme pomocí [`.plot.hist()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.hist.html)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "denni_ruzyne[\"pres\"].plot.hist(edgecolor=\"black\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**Úkol:** Nejstarší tag Pandas na https://github.com/pandas-dev/pandas je verze 0.3.0 z 20. února 2011. Jaké bylo v ten den v Praze - Ruzyni počasi?" + "Histogram nám říká, že někde v rozmezí 1008 - 1023 je nejvíce hodnot (~7000). Okolní chlívečky mají už výrazně menší velikost, sotva poloviční. Na okrajích jsou jen nízké chlívečky, jakési ocasy.\n", + "\n", + "Přemýšlej - kdybychom si vybrali náhodně jeden den. \n", + "1. Z kterého (jednoho) z chlívečků v grafu bude nejčastěji ležet tlak? \n", + "2. Jakých 5 chlívečků bys vybrala, abys měla opravdu hodně velkou šanci, že tlak ve vybraném dni bude v jednom z těchto chlívečků?\n", + "\n", + "Pokud dokážeš na otázky odpovědět, tak už vlastně víš, že histogram udává *hustotu pravděpodobnosti* a že tahle hustota se dá sčítat, čímž se dostane *kumulovaná pravděpodobnost*, neboli také *distribuční funkce*.\n", + "\n", + "Definice je vlastně docela jednoduchá (zdroj [wikipedia](https://cs.wikipedia.org/wiki/Distribu%C4%8Dn%C3%AD_funkce)): \n", + "\n", + "> Distribuční funkce, funkce rozdělení (pravděpodobnosti) nebo (spíše lidově) (zleva) kumulovaná pravděpodobnost (anglicky Cumulative Distribution Function, CDF) je funkce, která udává pravděpodobnost, že hodnota náhodné proměnné je menší než zadaná hodnota. \n", + "\n", + "Hustota pravděpodobnosti vyjadřuje, kolik \"pravděpodobnosti\" přibude na daném intervalu, neboli o kolik se změní distrubuční funkce. Matematicky je hustota pravděpodobnosti derivací distribuční funkce." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**Úkol:** Jaká byla průměrná teplota první (a jedinou) neděli v roce 2010, která byla zároveň začátkem měsíce? Pokud máte řešení a čas, zkuste vymyslet aternativní způsob(y). " + "Poměrně důležitým parametrem u histogramu je počet chlívků. Když jich je málo, může zaniknout důležitá informace, moc chlívků může zase vnést velký šum. \n", + "\n", + "Pro naše data vypadá histogram s třiceti chlívky celkem rozumně." ] }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 28, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "# odkomentuj a doplň\n", - "# ruzyne_tidy.loc[\n", - "# ___\n", - "# & (___)\n", - "# & (___),\n", - "# \"teplota průměrná\",\n", - "# ]" + "denni_ruzyne[\"pres\"].plot.hist(bins=30, figsize=(12, 6), edgecolor=\"black\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Základní vizualizace\n", + "Argument `cumulative=True` nám pak zobrazí postupný (kumulativní) součet velikosti chlívků. Použijeme ještě `density=True`, abychom zobrazili distribuční funkci. Takto nám graf říká, jaká je pravděpodobnost (hodnota na vertikální ose), že tlak bude menší než daná hodnota (na horizontální ose). \n", "\n", - "Vykreslíme si naše data co nejjednoduššími způsoby, jaké nám pandy nabízí. Zkusme třeba rovnou `.plot()`" + "V grafu jsou ještě přidané svislé čáry pro střední hodnotu (černá), medián (červená) a 25% a 75% kvantily (červené přerušované)." ] }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 29, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" ] }, "metadata": {}, @@ -3445,24 +3935,31 @@ } ], "source": [ - "ruzyne_tidy.plot();" + "ax = denni_ruzyne[\"pres\"].plot.hist(\n", + " bins=30, figsize=(12, 6), cumulative=True, density=True, grid=True\n", + ")\n", + "ax.set_yticks(np.arange(0, 1.1, 0.25))\n", + "ax.axvline(denni_ruzyne[\"pres\"].mean(), color=\"k\")\n", + "ax.axvline(denni_ruzyne[\"pres\"].median(), color=\"r\")\n", + "ax.axvline(denni_ruzyne[\"pres\"].quantile(0.25), color=\"r\", ls=\"--\")\n", + "ax.axvline(denni_ruzyne[\"pres\"].quantile(0.75), color=\"r\", ls=\"--\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Tam toho moc vidět není. Jedním z problémů je různá škála veličin. A také bychom si graf mohli trochu zvětšit." + "Podívejme se, jak vypadají histogramy všech devíti veličin. " ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 30, "metadata": {}, "outputs": [ { "data": { - "image/png": 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sS43xvn37Ys2aNdi+fTvy5cvHfG5wcDAKFCiAy5fJhf3u7u5pPcW19haPjRcfoEnGt5a6tC+Xiad9KJlBSEv/asUpnL0tZiQmv0ThRtHUaa2eeh7xieILcHUdyjsz9gmlzUzYfBGlv99kF2F5LKh+2mHOATzRoZQqQxKH6TTvkKbXOK0QpdEy6aoXojcfP9e12BM1LpNTrLh6/xkqjQpD6KB1qD1+u+4UwDHrL+BK1DP8tIk/8QDA/L3haX97uDrhXkxcpuk4rFZkO9yNiUPhb9cLRzpIn+xnmSqMkz7BTt6iXaTlZ8HvR82oteds/tcyFhhFOd4dj3iCozfEved6BHxkFh2wzyb6XtApaBS981xsfBKmbr2MvkuPY3dqFgdp7qPhyFmu42+HNKdAA8BTDdkTT+MS0W7GPjxVOBEKDl6PgoPXC42dR2/oj/Q9fBZvE0FadfyW8Pu98VB76quahKQUO4eaXufAW9P2CpUJ0OriHfF+WKw95fiymEYTd+HDOeL1wGpiBcswSA7IgoPXa3ICy8ErQKor1iNUKPNEYI6PjU/CqLXn8MP68yj9fXq0WCTLsenkXcQsjaeCYzHJQTZI0HFM+kxF1yRGpXZoNsKsnde4+5b4bqPu49IcSiJ151rE6WiQskfDBVL7HS1KmiXGuNVqRZ8+fbBq1Sps27YNBQsW5O7z8OFDREZGIjg42OHnI5J+89OmC2gyaSfxsXEbLgh9eaTJQs9kr6TlFLH6bfV9tvWCsXQfUUi3dz1OLfKLhGTM33sdR1SLVnVNiVaM1KsmJKWg9nh+1JcWxRJdZNx4qG+S2n/1IWo4qJZriuI9iE64Ewne01o/btdlcMUnpQg5bDrPP4SGE3amOTpuPn6B33Zfw3lBL+fzhCR88edxm/ZHp289EdpXaeh8OOcgqo3ZimaTdxtaZBihz5LjuveV1ZhFIC1mRGs9U1KsuPlY++eTkmLF5rN3ERUTh2mCUQIeRwwYMcPXnMXb0/YIt19561fbMXqchiwII8YWCYujivYziK4LD2NC2CX8q7OmX4uBIEI7VWqwCGWHbxZOV1y4L5z6HfNKm6xWq41jTolIxHT2rmt2pUjvTN+H3/Zc56bLfmRAWMpqtSIpOQVLCKVnRiJ7fwlk+9GE5ur+tENIwO5eTJzmftMAfXxuPHGnISV6kXFMNBJNgrVuEZlnHzyLJ7YX/H1/uO5zErnHnzIyZFjCf9cfxOpeg8kYyVb5dIH2sjEZLcJjahKSUuyyOWW83diZkqxrRMQuovHTpovcMiURxwwLWjcEEScXqcQvp4+b7nPJEmO8d+/eWLx4MZYsWQJfX1/cvXsXd+/exYsX0k3y7NkzDBw4EPv370d4eDh27NiB1q1bI2fOnGjbtm2GnJNcS0nj1+1XmemoIhGMGoQ6hnem8yd7owa7EYwMmv+evI1BBMVSddRZzfhNFzDi33N2htwn8w4JpZnRarJEhVZY6PXcZ/QauMOcA3ZKwlqxWq0YrkotEl0cTaE4IXgtKqxWq92A+9Omi2g/m5/us5twz07ZdgXNf9kt5AFfcjAC/5y4jV4KL7izk/YhUVnPqyfdyRGIph//QynJaTaZX1v85HkCURxKtNaz68LDumpylx2JlMQjx9g7m6bvuJLpafYL9oXj5M1ovPED3/l1MvKJXTaVlrIT0uelJVKsRnQcIhmTop9zrR/1iWPFxCXqEqhTwlqEs7gS9Qyhg+xL4PReWu/O3I+TAvPNM0ZWno+HC3NftbaIkkYTyYEDJTGUz2rU2nPowcmWuflYv/DkpwsOo+5PO9K6yigRMbRo1yGvU8HzhCSm+NhAAbGqT+YdssuyMcLlqGeaFf+1QponAWDubn7Ek6WSL9L3u8roLTbzq8zdGH5tNK1mWGQcGr2O/h2x1vG8z0REDO3aff0G6F2dkd6UFKtQOjmNObuvpZWEqgn292Tuu5mx9rhhMDixaD9bK8pomQ6tXR5PLykqJg5nb9uv9Txc9ZV4AllkjM+YMQPR0dGoV68egoOD036WLVsGAHB2dsbp06fx9ttvo1ixYvjkk09QrFgx7N+/H76+vhlyTh//dtDhXnU1evv3iRjsehAZ1Ib9Q677+FNAPEmZaqgFVgS8yugtultfzdp5zXDbLL33vlaV3Kzg31N3sEAlulHvpx0ZesxBK08T+7weDn9s6LvacIYfrT1CMIpORj7R1TtWxojPxWiau0jUmaXZwBNMGUuZrAGxvuHbCUKZxwUcjSxRrPEbL2IHJ2Pmp03k8zbyPYvwODYBb/9KFrSKFihF2UJZ5Py48YKmFj1KREWISNG/fYIilHoNNSMq/YDkECdlufEcuPefxgsZrzRo86hIWyLWHLz8SCQzWsvqWMFzeAPse48VcWWJqRbN7cM97vaL96njxeV7z7jjPk3ZnzcG9eY4DUVEbWnitbxgDgsjzjVAv2jh9O3847LmBJ7z/xzBWJH59+Rtrg4PLRAgsixgpTizRkBenfLQv9np5refvMA2StapEacxT7hu5bGbWHyAvibnZVixghe3OOP5Wcb3yLuXeWsO3iemUfrFDr0BLGXZhZI4A+VvWZamTvrp3LkzAMDT0xObNm1CVFQUEhIScOPGDSxYsICpkC4Ka3L7xkDfSd4a5xKj5YdRhV69HNPQy0/NoFWnDfX5ZH0PrBv4WXwSEgy0kPlAQ89FElnVIzSjsVqt6E/oxX43Jo7b55zXxoyVhscSv0k0MNKSDG01tJofvWrEgFR/LSJeRUpBbTaZr9bN6vFa68ftuHpf/7lv55SusL6rd3Wk8wJA2+n7uO2QeLccS1vicWwCfqUsOt+atleorEDvIiqK4XxdepjvzOz2O10MTK8QlagmzkOC81AkNXmjhi4dSpJTrMzI5EMBleGmk8gdHHj1jDXH6S/v2XflgU0nCCUiNaas+WTxgQhmaVRGBw9osMRUL0c9484XLFpP24MhDIPnWXyS7nalJGego/jYQCq4UU4w1nEsI0xkHcUqd+AZ0/c4ZTytptJLLM/ejsZ0SkkSbw3Gm0MjGU5rnjHO0hqJfPQcNcdto9Z46ynZk5Fb3dIglQIo4YnAsQKFLxKTmWtyVvYk67HE5BQUHbKBeV6s7yMxOUVXlxFHcJGyZnnwLJ6YDSxClqupZyYJSSn4kLGgWGFAYZwXcfiSYOjI9DVQ7ynCvitkr61aIVMNb6E6fqP+tJiKhGioDG+NYaQ38yFOLd/j2AS8N5NuWMQJqpeS4C3qWdEuI0aWCCuP3aIOnCxjOiomjtvGLF6n4cBKkeNxWkD9nmbsy0r6ehERr6Kls8/dza5H/N9S9ljBUs7nLd61qFaruRMdpztay8ue4V0FLKdgX87nxXKSPnwWj95/HNNdx8da4IzbcIG5UObd73soYzogLVJobcluPXkhZMTRxknevqw5hTX+8XRbKo/ewnRAbDh9h7kwYy0meeOM3AOcxIdzDxoS3OT5eVgiQSI10iz0tijl0f13Y4KQSw/RnX6HDbQOMoqIQygjSEpOQalhdIeSizN97cnTPDjAcWzEM9Y7vOvHSMeellP24G+KAnkS5369x4l2spxJzpx1/BmGYDLPWckr2ePBGj95AsG8tSdvXGfNNyyDm3VcVqadjAvDGO8w+wC6MxzWop0GHM2fh/V1V3htjPGvV5xE6e83CtVx6YEXGWeJXRgVJmNxJeoZ1QFx/2k8M0LNM9ZXa1BfVcPyyvI8nw0m0FMKRdI/WUzZdplZ0/m3jr7dMrwBbwijf3MnSlqMKDylWVZU6nEs/TO9koFOgj2XH2RoPXDtorky7LX18oIjwsJzJj1nGMS8lLCrjFo3kSyYZYxoLyuKwhNh4V0DrNZfrEWE9Nr0x0atPYd1p+/ojqjxomW0OeHc7Rj05Iy9LBYfuIE2lPT4xGQrOs9njyUsw3UKY0HJy3BgRUF4C2yA3QaLp1tgJJsqQ+dnA+On3rI3QJviu1ZYdbVGx/OhOlucGuXGw1hU5vQnN5IpyGL27mvMcf2LP08Qt4uUeY0k1O0r6btUvPe7khcJyUJq2Hrg3csix6U5VpwZjg1ASkOmCaWJlIYYQUsLZjW0OvnkFCuWHIygRnplWIKOrHUFqzxzHkUwTsmqY7eoYwZPvHAxoZuIErU+kiMZvfac5syl18YYX37kpqFIGw9eWqzejDIjSpsAO/IDAL2X0AdbXvoxACzmCCywoE1eIpMI7TlJBotIeAJArN7uvJQZVn3K07hEYosF0dfmQfMGP3megIlh7H7PWy8Yq+XUq5DbY/FRjOAsFvRy/2k807BwtIq1KAZsBgDsNig8Y7xQTm/qYzXG8kW5njMilyMZokfBfh7M16UJTTkC1pUZaUCkSqSOk/Z9tJiym9u7PojxmfHuGV4mAsv4ZEV3aPoiMkkpVmqdci5fd+a+AF+gi8XzhGTdhqCrDlFHGZ6w6w4djp6JYZe4C00eo9dqF1LUAi2zw2hmfValpa46xjeEvlh6IkOOzctApGk0/CGg68MTHNUiNqnks0X0iKVRNjL0YKxWq1AEmibyy4uMA0CUgPgcjStRT3WXlxy6Tv8uaJlQMrT7ZumhCHzLCALJsNZwLBtF5LVZXLz3VEgokMTIteewhtKVIzE5xU4fSc2fhyK4au405u65jlXHtGWGvDbGuBFEjMOhfxvz2NJSPCdvYRtKPHg3PmsxIGJEGfF+0hb4ImNVBwP9NVlphzxOEvp4yzRiROwB4K1p9BqpFzpTuUWh1fsOWX2GaZQCQNXQAOpjIv2aSVGvlBQrdaBUwhsw9cK7r/S0NBKFlW5rpD0JD95C9pqBNiQ8WAIxvAifkfYoRjBSkysiunncgGbH1G1XMkxr5B5H0ZdmrIuMYW0pn4tIj+gAb/1tYyqNCsP7s/brMsinbb+iuwSjzPebHHr9Xrz7FFO2Xja83mDpP8joFQYDgIaUudCoszwruP4gVsjAo2U5iJTVDV51SqgjD405u+xVwHnCWzK0bELR1o0k9Aj3ijJn93UcDn9EnEdZdehKCuTwIm73FFDDZjmWeTSauMuupjgpOQX7rz7EXk4W11KKc8WIxo1oZivNRZGUnMLMqAOAHxjK9iKEndPfhpnW+UBEvHDQqtNUtXURtGZKmMa4AKJCUrzIE4vPKWmJ8/eGc/dliqFlsOAYLWVo2jZ99TGX7z0Vau9wkLK4TxZ4v8sZNR1GPi7eYpRZ18M5bqFc9KilEQ5e54vhsGySH9bzIyyka2TV8Vvc+mejsBbQPLGyjITlwPjzcCSaTNpJNAT1inbJsOqrMhJez2JWZsbZ29F4yKibNcoP685RjaUbD/lGFC3VnNT2RE0eTssYFrsu3UeDn3fYbLNarcJlWKy5ajAnmsEaP/Ui4vi9cPepoTTnw+GPdV9LrBR5HksEIpSiaEkvZ9Wbi/AsAzJSRB1cetPojXZLUZOYnIL6qvuMxqPYBOL1KSIau/RQJL5ZYS/8tPYU32ENkOdh0TaGtBTlcRv4Nb2LDLS+NcJ7M/ejxHcb7a5xkXEXAHzcyW0DnQQULmlq6aKotR5+3X4VHeYcEBLIJOk4nWXUsSsJHbSOqSmjlTvRL1DiO37p75zd14U6vdDgZfeyIEW2k1OsmCQY5FTbGVarldlNwgimMU5A7aUXTW+niV2Q+peqMXKTlP5+E/WxrFL//nmzvoj+AIFenyxE/CY0YRCr1YqVAqklw9ec1R01o9Uq8V7N39NV1/F4iFwerPlJxCtLiobwhGN4iBgdJYdt5Ap4ZTax8Un4jVMrdeneM/yg6i+9+/J9rio0iylbLyPyUdakePJaCgF0R0HLKWKRDhIi0dbwh89Rj7LY5oniAEDzX/j92WmQ+gtrMTbV9Xgbz9yltlJTQ3KAJKfInU3Y+9LuedJC8ZMaBYTOR3Q8NdI6hsQ1wZptVs0uj9mEqGVmUGlUGP4lZB+JOJkAMcc2C/WaJiXFKpRJBdAzKHh8Mv+Q0H0PAGXz+qFnvcI229Tzs9aMta3n7Q010QiZum98+INY9DEg7ls6Tzah55F0NVJSrEKp+d/9c9bO4BG9vgBg7Przds7axxqcSHpbEn5nMLPEkSw6EC78XFZ3BTW+HvYOh07z9GkPkUaC1cfpor9q7hlI7Q/MZl/CROvYoF6rkmw3I8KC2y9GMQUAlWhtc2sa4yp+3nQRpb/fZNMjUXRwJ6X3aVH0m7vb8ZO23mD9EQOqpVrSrdSpUKcYaeAiiEYPSXUuvLobmQX7womLHBFoIjC8dY+RNnQsRCJFRv05pDR1I/24E5NT7IxVGqTvqcv8Q7gt0F+Sdi3N3sVPcaLVTHb87SC3LACwFTexWq3UvpYkwgj9qXm6ACx4LWxkaG2taFksSsLO3UPEQ9tFqxbDdObOq3bP/+4f/QsuIymjRiC1vBPhyfMEroiZEtkR8NeRSPxz4hbiEpNRZXQYCg5ez92XFklTjyUfVsuPwS1KCp2P6KKONJ8ayRihOS/UizqesGJmoXUoJjkj6/60Q2jfN37YaijbT1nrabVa0XraHmobODUkhw8tWj7z48ppf+++/ACDVtlmdkQ+eo7Bq+yjzv/2rWXnBDp584nN/1oj7eosCCMie8cjySnEl39oTt1nzq5raDxxJ+4/jRd2cJHmI56ophK1k5cl2qVm1q5r+FqREXD1/jPhawTQn/0hMv9nJI4Upl1IKeX787Pq3H0tgisxN2d7U/F5vPi4+9Mm8U4trioRvS0EB1ejifYdfGZ1rIxtA+pxX99Ipt2uS+RSgmkfVtT9mjKvhTGuZUCdtv0K4pNSMHJtuhgNLRW7WKCPzf+LCGJmomlGADB63XkcNBgxVDIp7BJTJVtmxL/2wjvvztwvfBz1wLKB0/NQCatvMg+Sw4AW5VJTfsRmu5ZvWqIfuy7bev1p72NoS/vFqNq5s+xwBLW2RYnRFDz190SKzJEwmq1AigzcM7BImbL1MldVXMnRG+nPTU6xCqtjkwSjrkQ9wxiBlhy0mkk9ThWtX3v3348I9c8GgKtjWtj8T+pXSjLuSZy6GW1okfH1StvrjNVWR824DRew/aLtpM1qkcRDxGFCQ9R5S+KUoOND5uztaEQ+eo7Rgs4pGatVWsh+teIUvvjzBHZffkDNBHi7Qh5Nry3zQ5sywqmyomnJ8cm2Y7TVaiVmjBTI4YUvGxUTOC7ZyH6zSE6b/6cYEI8D+ErzohgtVWHRsmyw3bbxBtodKkeCmLgk4RRiu9dJHVNo31XxIF+b/9UtatvN2EcdC9TOhn4KZfKfNl1ABUYLVhLqFOZqY9gK7CxoQ6krwTACpGDOD+vP43LUM0zacknYYa0mKTlF03WmvsezESKyANCwRG68Vd5+LFGKOtKutykdjBs7PJr/spsogPpe5XwOP5YRJ40a2poi5gXfgUjKnH2zSA5D5zOqTRm7bQeuia/X1v2vNvPx05SAXdPSQfB049f8k+akTjUK4Nh3jbn70tY3dYqRO/OcufWE+5oyr4UxXngI39vPgtZ25ZOaoTb/L9gXbieGobXXnUi9NInD4Y/sPKGifQ3n7w2XarV1Gsbq1CyaRzZ8XEu7bUZEkrQ4DEioayNJ91mHN0KwsmdNu+1KY+dFQjKqj91KPIY7QRBE7X3/ZuVpuxQ1EsuPRBLFk0Q/Q/X7E6kJcwQksbRcPnz1ZBo0JVQaysWZlkgPSQ1TS+1TfJKtgrNIdwIlcpRUT6mJSDpb8zJBcFaFAHsRoqsiLUhkqv6wldnGkcWBa49s6t+OaVS0V0bWjUYernFEaVjs0xDdVkd2tAqFtZyyB7XHb9clEtZDIU7D+rx61C1MfYyFxWKBuwt5cXQl6hlCB63DxM0XMW/PdfRfLubwU6c501TnnSwWfNGoqN32dQrBUZZAGWneNnJNNZ6UHsl5Fp+EX7dfQYnv7Fu9/d37TebraMmQ0cqvH1Wym6M3qxxxWtp3Hbr+CL/tuZ5W/kDjjYJ0gdD1p++g4OD12HjmLvE7+appceTlaC9EEQyf8vn8AAC+HrblX7GK++9XhshTy7LBuDCqGdxd2EtoI/5z1r6kxb/SIRcbn0R83wBQv7j9vnL3EKvViiJDNqDmOLK47jJCtFWdzk477986V8UvH1Sw2650Am46S3b8kox4Uc6NbIompQKZz7kbHUect2oXzYmf3itvt12rUraaRMWHRPu8Pn2zIHH7NsHuNrS1TnxSMuKTkjF162WsJnTwmd/5Dbtt/ZadsNtGMmp71y+MjtULoFnpIKFzJFEs0Ndu2/UHsWljCGsMyk3oyjF2g3RfLDscgdBB64jr3gFNiiPA2w3TP6pk99id6BdpgTDSV/XpmwWRzcMVXzUtbvcYr8OIktfCGCfNAyEBnpiR+sGzGssDkqFLwt/TXt214zxbEQb1YhcABjcvgUr5/YmvSXq+GnkiUfLezP3oNI8vAHF9bAvM/Nj+gms8aReqj92KyEfPqWq6p4Y3wb99atlt33LednBg9f1VYxEMnbQqZ++1F2V2x8rwJnjM1J81yegZ+045VC6Q3W67cnJgGWilgu3rttrN2I95e64zW0Js6lcHR4Y2stk2aNVpfKKq+XnyPAGFv7V3Nk3/qJJdvSavL6NM24p5cXF0M+JjIh7dvYMaYFHX9AGdlEpGEuXIH+CFBiVy221XC2bQUtPaVwkhbldeY1qcP6TUWVK6VsMSuYmTQPkRm21qoUUEWpTIHQOMZI8AdLXcj6pJ1wdNWVaO8PLa/Sl58CwezX/ZnVbTTzs2DaUK+WlKlPjrZvaTHgBMCLuU9v3S2v2IppNpiQzN2HEV5UdsTnPQ0fa9NLo5utayXWApr+VTN59QHah96hdhngPr3v6hbRl8WC2/3XZldgnrOy4R5IuD3zZkHl9NG040/f1ZkiN1yrYrmtSJ1QvMppPt0xUBepu+79ecRbUxW3D6ZjSKD6VrMJDGGLV+AS0DYlDzEtTXBYB3pu/FT5suEuvfK4T42237XYNIVhXCXAWknyvNKB7QmJxFoBwvN529S+2AMrVDRbt11JWoZxi19hwWH7jBLD9b/nkN6mOyc7DH4qN2WW/h41qid/0icCMYxLz7t2ONUABA99q292NyihWTBEp6fv2oEjxcnTGzY2Xi40ayY0ReY26nKujyZij18VhKCvG1MS2IhvyksEs4eO0hqo0hBxUAoMMb+VGtUA58UNV2nlU7a1lzrOh6Tw9RhHVr/8bF4OXmgtmdqqBtxbzUfWdRSs9oLRdFnYd5/T0x7p2ydtuVWY609cyw1qWw86t6dts/XXAEh64/4rZJo7W/LD50I4oP3YgJlOucZoMoyzgnb7lEXOd/1VQa+5qXJRvj8jVN6/Gd04fcMaP+zzvStDe0Xl+zdl5DSooV36ykC5PK2Ryk8bPG2G1p5T6k7FnZqftxddv1tpVzrmpeC2OchJPFgmZlgjC/S1XsHdTA7nFl4f8XitQlJXmz23tk1ZMOqUfe53ULY0WPmljZ034ScuIMViPeKo3fOldFt1r2XrO9V/gRGYvFgmZl6IZt7fHbqQNyNg9XlCU4AuQL7krUM/RfdoLZQqmj+oIVjDaMeacsRrxVWui5apqUDsLZkfbGpfrQWpzYyt7HLKEbkiEPSO0xBq08RX3/xYN8kVMgekxKowsf1xItygZjWGvbz0stelaYotBeIIeXXUTrz0OSV7HqD1vSUnhJhtayz6ojr78nahdNn/BJNWQkQ2tM27KY17mq3XZRwYwf3y1HdNosORiRVrNEy3L5qmlxu9ZJUU/jceZWNNrP2p+WSvehyqDe2K82futcFVMJaXRxiSk29U4kVfG+DdhGFiBW45Q/gGxQA8Btgid5+8B6qFVUSsUd2MTeuL3+IBYVRoaleZW1ItfiDvjrBPFxWpsqZWo6zbNfMIc3UQ33aVxSmgAjbd9mpYOIkV51vfqTF+J1ZT9uvIDoF4lp2QikCTh8XEu4uTjZGdXK83xrGrl++dTwJhjYtLidc06Uj6oVwMfV2EJq4yk1fUNalITFYkFgNtuF3dX7z7D9QhTiEpMR/TzRbhzrpXifaufvlK2Xddd6imaJkFIlZe7FxKM1o83kiWGNiZoB6p7MxykaI7WL5iRul+H1kFeXNg375ywKDV7HFYI9+X0T/N7VPqoVdu4eigzZgG9Xn8ZnhFY9AxoXQ9+G9lkEgOTUGvnvOcTEJVLb/Bwe0gity+fBu5R03u/XnNUtHEWDF+lUO63VyNerr4cr2lWyPe9ftl4WFhErnNPHbtvc3ddQ+vtNNunXapZ2r47x75ZjvjZLR8HNxclOfE6JOkACAJ/XKQQnJwsxErvnygO0n32AGk0HgDFtpXuKp+vDu0drFtaWBi1HHMe3I39eR8IfYfPZu+hB6EiknBfVn7dSC4XWtUgeyxuVpF9vrPLBn94th3zZ7edm0SSbAjnIa7T3Z+1Ho4m7qOPoXz1qECPMIjg7WbCo6xuY26mKzfY2v+5Nu28mb2Fn3Xq72c/PoYPWoczwTbgT/cKuZe2yz6qjSoHs+P3TatTXHLvhAhKSUojaKD+2s3d4KOGVvMlGPM1ZJGeuqktgAOBh6vrWTyWyfP9pvCYRzP+8MU4zdqxW6YOvXzy33UIDSE/bYUHyYqudSmrxAdkAd3KywN/LfkGq3J907p/UDEVOH3d0ZnhFaagnHb0MVnn+96fWuTeauBOrCGkvSka+bWsgbjhzF53mHeL2O8zm4WpXFiDCHNWAokS9YE/W0ANVWVtE836VIzgulGw8e5ebxkbyUorWjqv3/WH9eSw7HIGUFCueJyShVTly9Io08ShFcSaGXcLuy/dRfuRmu+fl4DgQWM4X2Tg8O6Ip3qlk68UWjQ53r12IuP3X7Vdx7nYMsU1h55qh6FWvMHZ/Xd/usTa/7sXB64+oJRFypLxaIX11VgOaFMfavvbZJkpYn1n+AC+cGNaY6agi1RgWVEQO1d/3lK2XUf/nHXgWn4RZO8miknu+qY8Dgxti/2B7R6YSkvjK4OYlsOGL2qhLqbOSKZLbfqELAPmyeyGE4nyYuYOtg+Di7ISvCelkdX7abtPj/cwt+5RF2vkoiXoax5yAs6ucECK6DdlSU2lFnHM0SnGUlWlqt/UIKa2ApInQZcFhNJywE+VHbrYTy1NGppuVCUbZvOljIU9MsEXZIJwf2QwnhjVGdi/bBc7XK05h3ak73HY3RtrG+Xu5EUuTAEmNWK7/pjnOaY4m0b7wXQjpqbwhv8Mb+eHn6QoXJ/t7Xc7OWXIwgqj/QFJdVjJv73W0oQjdfV6nUFr08C2d2gIAWVuFRdVQemo7IIlGslq+Kj/OEW/bj52iehX5CVlFo9edR3xSCgZRInF5/DxQo3AO7nqMZ9Tm9iVHPqmkXq4Fc9IdtzT6NiiSZqiojQ411wglM8rsB61BFXmeeL8qOfPt3Zn78dmio8Ta6eqKeVk9D7aetgdv/7qXmQkhOzzGvEOqg36Ikt9tROXRYdQAVM0iOYnfY0xcIqZsvSzczYEGyRg/OrRR2v0xi5K5waN20VxoRHB47WB0ffJXjNW0qHxcYgrR8VGtUA6s6FmTO0/RsuVo6wGZKYxWy40V75MVC21MUe4f0IScVfTn4UhNmYH/eWOcNqi6OBtLlyHVPwN8Y6RyAfYkotSZVtdrdVKkHdParcUnJSMlxUpMnVZeND8T6mBYKL3en9ctjD+6pXuwbj5+wY1wy3ahxWLBN83SjfnZu65h16X7Numpar5tkf78HQPr2TymNIRJtTSNStqnPSvPW+b+03h8ukBbH2bZKCYZ43sHNaAu6GSsVn4aSy+C91tUeRiQUlSVfLPyNDrMOYBSwzbhOmHSXNPnTZRJXTiTyiFkaLWLNAGN2Pgk/L4/HFVGb+HWFHu7u+BblQqzXJNPW8h7pR63aCDdYHryIoE4mA9tKUX/vAnR1iTGdwwAwX76F/0yZfL6YR8hOwcAGkzYQdxeLp8f/vysOnZ9XR/+Xm7EBXVcYjISklLw4Rx2n1v1d8Yzli7/0Bz5snshyM8D2QkORRYNSuTG53ULIzCbBxZ0sc+CUKIWfGpXKR/GvlMWZfP5YcoHFYgRSNJCUA2tlyzvupz5cSUEeLsxBX3iE1OwRTVuq78bpVDWnssPsP70HYeq6yohledooagiukKK5MmL0MUHbHUcXFQLXy3zbfuq+eHp5gx/Lzf8q3JUHYt4gt5LjqHJpF3E9oglg7Ph3Mimaf+v6sUeg2nk8ffEhi/shYR2XbqPrgvlecL+OxvxVmnqmPDrtitCaYsipWpq5LldrUTMI192T3zwhn0JgxqShkLYl3Vs1PJrFmZnBJCY3L4CAKBrrYLY0r+uTUYDayErcj2V/n4TfiYIcgG2Dk5Slg2pHadWaB0Z/u4j6QI4O1ns6kyVmhGiLXVFqZUqSli/eG58RChbYTFAkT0VR9BaUDoyh6jU7Kd0qGijC+BB0NFhofyuaWUYNGhGISCtv05G0kuDAKBEkGQckhwfH8w+gBeJyXj8PBHDCK3SRqU6eaoTHPUj/z2HiWGXqGU21RSfF8v58f0a++MqbRDSsY3A0r1RlvCVyetH1XIw0uqR1uVJebuSsqJmMJz0norrkTWqXKa09FTOkd+1KmXzmEh7VJn/vDFO8zyRaj/VhA5ax1Ul/u0T28ir8svkpXgGESLyShVfpbE0p1MVjHw7/SKjLd7KDt+M9rP3E1N2lF6fGhpShQrn8saPqhQhdVosz0Acp9jf2508GNNSSz+rk26QqidhpaiL2pg+/l1j4RqlpaqWJACwdUBd5j5yqg1pgZXX35Oqeqrk29X0OhaALJ6kZaHwPqGOWm41tYbQ9qtcPv+0v9+uQK+xokGr+blw9ymG/XMWD2MTiL2Z1QM3TceBpHLt7eacllLF+syTkq3oMv+w3Xbl4pel2koaC5SGLKneXYZnbOXx9yT2c792P5YYacvl424z0aqFiACgxHcb8cm8Q8zUQ63M7VTF5jPWWgKoVBu2WCxEDQoZdU3a07hEdEg1HIoG+mJBF/uUXECqS+MtY0k12CP/PccssSmS2xdHhzbCl5T6WkBa4P19wva+UjsQf3ovfSx8GJuAXn8cwzszyM7INzgRQB6reqULgg0RbDNGQ+siWonIWAhIHUqUGROkFE+ZD2bbO5lW9awJL0WKZE5v/dkEtMikfI2Qpis5e4tULnMl6hmzM4GyRdfS7vy2RDKnhjdJy5qwWCwYSInUkJjTqYrd90rLhlBDyqZgpU6rWdu3Ftqk1vFaLBYUye2DaEXP6iuMqOE7gll+07aT9Wt45YD9KKWJJGiaG6SxJIe3m41h11s1Di0/kq767ktwEmi5LpRMbl8hrXTMYrHgh7bstF4WpFKvUsM2YcPpO4h+noinKidEa9W9QHI2PU9IogpzFVcYO2Xy0gMEWcnWC/YZYPLYRdI0kPU6aA6XaR+ml/aQnIIyPJVyXhaDGlbwCpBEf2lrGfUYH9a/jtAxSdc5jViKwKlyrFaXwvJQfj+0zlk01D3QRcX1SPznjfEJm8lRnk6pAh48SKrEyshuQ1WKp3KMp6V4ypAiccq6NGVkSB2lLEgRqElISsHh8MfENEvlJKBlDT3tw0p2A6j6xmPVER37rrGNUUgbgMqPsE97VqOOOmhJCf2CUhcH2Bv5fp6uKJwrPcq6+Uv7gWX2rmv4eO5BTOekxrLUXkk1KJ0V6fika0T+/FJSrMij8vyq1SCdDQimsFRuSRwY3JCqntyOYmzILFLVOor2vwSAU8Obomaq158lxkhz9igdNizVVp5COa0kYsjq08T+zeqWUbT0VlJ7Qg9VxNOHkmq6X7BV4uKu9FotJbVU0Wh3F2eUJ5TriBISYH9vLD8SiVo/2gtFvVCJMtG+6iJDNuCJyiP9RsEALPw0/RobSEhVP3kzmptFYLFYmAscpWCfjDpbysvNBTlU3/VxSnuaQS3YYmAsvmpa3KbtU/c65BIOUdwEo661ithHSEUjtuUVzkA9qLM8CFnbTJTp0vn82amP3RbaOvaUUZEpH1S0q3GNT0pBDEW0s1RwNjQrky56VCVUPAKYTeWI05JkQTIUPChjuMi+Iu3kZEiGlXI9xcoQ0GpkKHF3caKWaMmIip0C5KAKjRkfs9OGleNWsL/t637XqpSmIIqSNgzxMh7vqPYliUECQM8/juGrFbZz1cqeNewCIqQ5etbOaxi/0T6LQR1QIY3bGQVJPE0LJQnivSLky+5pIxxnpORGKyIt5Gjideox3otQN07if4R1+QyCqjlAbzmqpTZbjdJ4z6HReau2ZWiaRCL8541xOQoo06hkIPo3LoYOb5DrT0RQe39bKjx/tNo7GqTzsFqteBqXiH8VkUv1gGaxWJgqpGrmdKpiM7nxFOSVkGrq1RMly9hSGxkvEsjpWyJ9vtXHvfNEajsg0sf1y8bFbAxdJWrBCXVdNkkM425MHPZcecDtw6zVm82rn2s/az8exSag4qgw3FbVUrdQ9YqlpeSKoHV8Y6WE8SiUyza93IuQPdF/+QnivsprwmKxUEXzaGmDjoK2eKS1YuunWrjSsnUOh9svDNUtdXh1nzxYAnBKSOMGSS0WsI3yyKgdECTdjK9XnCKqoavbWrGyXtTj0fLPa3Br1AHgxsPnxPZiyrp6b3cXqoDURcF+0iKifIC9YfT7p+RsABIktWW9PcMBsfEZADxc7a9jUi0zCVKGh560bRleBFTNe5XT52M/L1eMJVzbcmRIKeLp6+6Cj6unGylOTha7GteYuERqtF09RxhxolbWYMiTxhzRQ5M0UUgGuhaUUXraZ0DqULKNk8Wm5MjQRkL9iEm0qZDHTqyTdM3S4Dm4lSng6oy7TjXsI340tW9Hom7P+kHVEGoLPnVpJaksk3Q//0Jps6UOqJBKCjKCTjUK2ImnDW9divJsW5Z0q4Yt/evqXg+1JgQE1Kr/NGhBOlHUBjRpviF9T4D2sVaGVJvevGwwtcMDCS0OMSWT21ewCSa4uThhtoY6e7V+lpG5KnOu7JeIuZ+Qo1c/tivLlL6XIV1vrga+gO9bl8bSQ7aL1qF/n7FbwJMOwRMIUxLgbTth5Ba8eCvl9ydG7LQY82pExa5+aFuG2q5KpvGkXQj288AdQYGv4W+VtlNytFqtdp8vSehLLySRFxbqeks1F+4+xfTtV5it0RxBqAahly39xRdDIpDSWtX9TGms7FmTqDx8/o6YodSyXLBNP2ItrOpVk6l/oMRfFd3pXqcQRvwr1uZJndqljo5pRfQaJV2btLZYX684ZbeNpNwuijobwCiFcnkTa2HLjdhk8/+3LUqkpcfLzO5Uhatu7QjUk3udYrlwangTlBvOzyIiRSa0LJj+VPUUfkjoiiCKaJo6yZj7u9ebTPVzFloWR+dHNrMz0m5RWuSp+aVDBWpWkMypm9FoV4k8r/iphOpEnaikntE1CuWAq7NFqOaY9Hnz5h8ZI2ULNJTtvEavI4+FJGeP2pnLQovxrGbyB/aRQy3CrzxWHbuJYD8PdKxewG4NSLqH1v2vFt74gd6ODKDrRni6OttlG5FopxJTtVgsRPFiUUQdcwCQnJyMxETbdU5eX/HrLi7Odl0oum+RAHe7fd+vGIQ5O8gaBEqCvJ2RJ5uLzf51C/vhCqXmWEnZvH7oWSvE7tj5/VyFzn3ex+V1v2fA/vN6I7+v8P65vJx0HTuHh8VuPwDwcEoWPnbB7G42ryG6X27COdcp7I+vGhXEEkoQRSbFCrxT0dZx0uXNgth3VSwbUc1Lb4xPnz4dP/30E+7cuYPSpUtj8uTJqF2bXkOhl/ZV8wsZ46QB8YSqxcn2C1GoT6gfVSuJA+QJjRRJIy2iRCfDdyrlRaX82oQvZDoSvLEA4CyYduhFmAh4SqgyQdk8hBYGooY4iZi4RLSeugc3VK2N9HraMoJ2lfKltWySmbvnOuXZjkPLokVEaTqriScIz5AY1qqUbmM8hFHjqkbt9e9YvYCwMd6znn3Ns7uLk5AK8PtVHNNVQSb8IV80TYanesqih8E0azWNSgZi9n37UiKlEVM+xN9GsyKzIdlkIo4Xms0teg80LhVoJ/5jpEWwaJo66XmkdpqiaHE+kKKl7Srno9Ydixxnda+aaKtwzn1P6a+rl/kE3QSLxYKzI5qh2NAN3P1JKelGggsAsPDTN7itxWgoy7LUWY0yRqPvJLJ5uNhkOmihRdlgbL9IV5mW+YnSyqxwLm9cTXUK3ouJx7B/zmLYP2LXichYQGvzN6BJMYxex29dWcWgboUakbWjBcD3DfPg0iX7MtPh9dl1zUquX7ddJ4num9c/0W5f0f2fP7qD609s3+PAmtnxNM6X2v9dJl92T9yKtF//F/dOFDp23OO7uK5KpDPyeWnZ39/L1W7/Cc3zUJ31MrcibxC3l/MXe89+nvbH/bV1PtwXcB57xT/E9etP7LZXCUhCMe6xrbh06RL8/f0RFBQEi8WCRiVzY+w7ZTF4Fd+WVPNSG+PLli1Dv379MH36dLz55puYNWsWmjdvjnPnziF/fm1qkI6C5GUsFuiLcIUx12XBYZwd0dTueaJ16iRok/2MjyoR++4pmfh+Bd3HdaZ4MV0FvZu0VOcRb5XmLkxoYkrdaxfEnN2OMUb/Pn7LzhAHpMiXmp/fK0+s3xWhcalAbjo7jR/blbUzxjMCUout6R9VQi/O9ZVRzPy4MlGIUIRzI5ui1DDbCCetl6gaUlmGKFrVjJWIRqQAckmAaDueMQbEe0hU06gtoJfc2Rybktm7fhGusqsnIQqXmagjpqK0KGMvIAZAOJumDiGlX7SLQ4MS9mmHopkXelMdaZCcwVogpX2mWIGx622NGFrJREWdTnCjiBqsJDFVI6mWAITKQWiI1MfSsiwCvN10968XMcRp11K7Svlw4Noj5hydw9sN71Gy/MK+rItC39prioggcr/QxO6UehKZiUhW5TslvfFGXg/kzp0bXl5eNvdX3pAUXH8g1hKsYJBtSYNvrng8fMYvJS0URK73TvBkd9wAgNBcPtS5/OJd+v7ZVeJ+SuISknHjEdvp7eRkQcHc9t+pyDkD0pq+ICGoIrp/sUBfu3EwJcWKy1HsjET1dyQTG59ILFdTU5yyv4XxWcuQzhkA7j+NgwdnLLEAyO3rjKgoSbwvODgYFosFHd7Ir8sYf6lrxidOnIiuXbuiW7duKFmyJCZPnoyQkBDMmDEjy87pt8727XgmprbnUCKSkpL2mpTUeSUebuSvysjahaTUrYY2cIpO2Gq1QZk3i/BT1WlK9kNaitXu0FBOqvuukFNKSDXi7SrlFVrkLOluL4altY+qEi1GmhFIgjrNFaJCWmlWWv++AGwEjbQiKh5ihMmE+95o6uYgVQ1SRqD3eqpeiGx0G/2seX3WZYoQFhpG7AY/T1eu8qrR96YWWNTCrI6VtfcShiT0RHO4CAvMELyooqnm7Qn9gEUVbtXlAEYxaozTmKVy4hi0X7OECe+VJ44Fn1B0VZTQWjGKYuS+oK09dhgQ3BJxKBbKRa7HdXKyoE4xdls31rzg5GThajnQxMSMlAuShBYzA7XeiRpPFwsaFvJBYGBu5MiRA56envDw8Ej7yebjhVIhOWFxcSP+OLm6w+LihuzZfGz28/DwgJubO3U/5Y96P/lHZF8v1fmK7p8/lz91P/9s3igSHMDc3+rkSty3UFB27jnnzeGHonkDiPvnzu4r9L7V35OHhwe8vDx1f9Y5/HzhxNjP31f6TIx8V6Rz9vDwgJcn/7y9vb2QI0cO5M6dG0+ePEFysljWGY2X1hhPSEjA0aNH0aRJE5vtTZo0wb599jWZ8fHxiImJsflxNNfGtCCme/u4u9gpJ779617h121YMhCzOKIBtHo0T85iUa3aq+TLxnR1cRmaErjIJBDs52HTokEJaWGtJqPaWMxTOFQ2nr1r93huiiiKxWLBnq/rM187fFxLYr/VAjm8hUWy9JJdZxTtjYIB2E15X6Kt4UhM/qCC0PNCNdbUK8mXPfOURtWQFGqNGuNG1vQHv23IfY6RKPasjmSnYS5fd0Pfg5H7XDBYS4WWwinTnyEiwxpbAaBhidxY0VNfn2sAVJE4Hl1rFaRG1L9vbV8qRYKUZSG68CcZS/mye6F0Hr66ME30qGVZcqRfyT8EUSmLxYKimVBC4+iIfmbQrjI5Ylomrx9+bMfOnuHddvsHs411knCjKDRhNyO6GZ/X5ZfAsL5jngozrZ2rzD+qdohq1GJiaefEuSdnfkxefwHSvSEqSkZC3S1AFIvFwhw7/T2c4OpsgZcXfV3AetdB2TxQIigbQrJobaBnKCiUkz9GeXLWFjRRQl8PV+7Ym9PXnepsZQn5yuWcOX3o138JAxkYPox7ukAOb2K3IUegLiEkIdtG8nWq1DbQs9Z/aY3xBw8eIDk5GYGBtguSwMBA3L1rb0CNHTsWfn5+aT8hIfbe+ZU92erjamU8NayBr5ZApJcF60ZTt6tSwlNR/oUgOCLDE5wBQG1bxPosXJwsCB/XEvsHN9S90K5VJCe3/YheeJ5ZmuItIAnfkVI4AX6Pxnmd+RkQRtDbVqF5mSBDtbwklVdAMkxXcoyRcvn8sF3Vh1kLrPYhNFV1JXrVWZVtjNSoW8GQIPUhBtgtAmX6NrCvFwfE0utJmT2isNoJ8foLFw/05Y6/LGiROL0Gqyis8WtDP7Z2Sa/6hXW1palTLBf6Ny5myBFGo5SAQQzYd2UAyG3o1LC0NtQq1FqgRSUBSSE+fFxL6ly1UECB3mgE3cg3ZcQgYmEkG4tnLPtwggDBfp54g1FrXDRQv4PEiIYADZG1EMsY52X6NTWYJaaHmR9XQjNKuYqMG+d9l2WMf+puAWpYYwGrzaKTRbr+WOMfa2h8GpcINxcn4v56VfS1wDpvWqYVrTWp7evSH8uX3QuFGErqtHJTEVj+nly+7ige6ItgRqaLFsE+R2LEOSfiXJU7UZC+b5GsY7tjat4jk1G/UavVSnzzgwcPRnR0dNpPZKStQvnVMS2IbRaUGBEGKcvpjzrx/fLMx1mDhD8j4lmSUi8h8roZhSPWkIu7VTNUu8ZS9+ZNvCxDC5Bae+iBlw3QvkoItd+zSJ1vhfz+xO1DWrAXZW0N9CBtWCI3hjE+L57if7l8fszJa34XtvHIukKGc6KA8zpXoUZwWJ7e2R0ro2stequRJpyFV5NSgcQUd4DeC13m5LAmGKBTkXxFjxq6nQ+8OlBeX/jP6hTijr80ln1WnWrU8iLbGQkvhbwEY2xmGSq/f/oGsfeqCCK9cXlRT9rnXb84X0xncTe64Vsolw9+EcyWUdO7PtkBBfCdkCIOEdb9LITOqSqnjzs6v2nw2BRYba9612cvFknt/WTaVswrpGXAWk+JZmioyeHtpmuhy0Pk6/uYUWrBc5z1baDvfjZCDUKGnhp1lx01LSlOYx65fd2x6cs61Mc71wxFv0ZFqRlVfBFB+uOs687H3SVDugCIwlrL82BdYwHebroNbl5wiiXka7FY4O7qrNtxwkNvticAhBps88bCw9WZGZDM46+9DOelNcZz5swJZ2dnuyh4VFSUXbQcANzd3ZEtWzabHyVGRUl48CI0tDQjGVZknJUm4unmjEND6Omp92L0K43rRaSlSkbi7uLEVPd2c2FfC28R+jwqEVWD18qP75ZDraLkCfTDavmZToJ2lfJhAsXh05ARsa+Y358bBRnYhJ6qO/H9CswaZNE6UxoiBgANWms259TMjQYlAqkTTduK9GuAFY0HgKalA6m9twEpKkT7zHgLBb2CXgBQgnPeq3rRsxh4ZTSkdkNKeOsEVk9RVm9eI2J7PFiRBhEyKoWOxvWxLbjzDCB1DqGxqldNautJnsERPq4l1+H4doW8VIcjCw9XZ7xTiew0TOA4sAC+9sWnBg1ivSVIdSjjPcB2CAKgfh4yrIjUV03ZWYA1C9MjvT+/xw4syLCMIlK7VB7j25XD0e8aZ4wxJbA8VLf4UsPKxOIFelhZR7zSItrYy3pNmUYl6evWj6rl5zqpaEGCie9XYB7fw9UZ/RoVQxXKZ8Yba1gPsw1DC9PAC8zmQexjL6OlW0pGQPpMRcZ8QOp4k52w1ivISZE3GtCzWCxYNGc6GlUphf6fdUI8oY0ZDdY1lJKSgokTJyI+Ph5WqxWTJk3Cixe2gm+siH2wH9tJK0fW/1o8H0f225Ydk7pQKNEjYvnSGuNubm6oXLkywsLCbLaHhYWhZk39dXgZBc+7xKuyYk0wyZzCyFyMSfuZznYdAL+W10gtSEZCUsC1hTfQsx+nRRy2nI/iHNcYtHRwAJjwfnlqpK5QLh+76PWFUc1wcXQzrO5lX2eppk+DophLUJd3BLT6P1FYEQfaAkjkmAOb0qPPPAeDxWLBBwwhKlYUOTZe//3KgxcVr5Q/O/ZS0sF54xsvrYuXqkZLWxzdpkyGpGuL4CKgjN9ZQOyKRE5f/TWzNBzxOVXk9A8++X0T5uMi0DoONCC0A1Wy6tgt4nbe/AiwDcgBjYsxawR5WUkzPqqEfIxF+jJVv3aZzjVDmRHi8e+yj/s+RZ1bJonS/5qWzq8kN8PJJRrYcKOMk01LswMXpNr/49815qZFG4FkpKjh3V8i5RA0GjKufV4p4vHvmuD4d411HZflSP+hbVnuXPdhtfzE70u0qwiv5p0Gcy8NsSBl2ri3mwsCOe10s3u7cZ3xLIysd0JDQ7F60Ry77bxachkvNxe7yHyZvH5cR5HRWeXevXtYs2wRpsxbAovFgnWrlwvvy7rnnJycYLVa0a9fP4wdOxaRkZHw9LQ1sHP6uNvYVsr73Iej4+Du6oS1q5Zh1ZLfUap8BeFzls/7K8YaksRLa4wDQP/+/TF37lzMmzcP58+fx5dffomIiAj06NEjq0/NDt5AzYpuA+yaNd5iw2Kx0Gs2dd5JpfNkw9xP2CnCrIhrVmKk/o80sWQGf3TjR4uMRJnVURQPV2ehOjmZbBQPJU3lXxS9qVVOFkkDglU/SFsMihzS3cWZGr3J5ikW8aQ5szq/GUrdZ+sFYw6d+QZqwgFJlOT62BZ29b1GIhUAUJsRAQTozsgog5k9jUoG6r6nRerG9Ari0a6tj6uLqYmLqpNrhfc9i0TbeNAWf7M52RdKlJoLIt+Tt7sLsYb60JCG6MspCSCpwytpzhGXo2UaDH+rNDPTpUGJQGo3kpU9a9r1gVez8Yy9tg4g9bUWoQthnPqyET2DRQ3JmeVkAaZ/xP6eSc4C0ejcakZ2T4MSubGEMs+WDM6G/o2LobyBenS9JUAAu6TAXUC4S0RwisZfPfRreQDk9ZZoxw6accq7pVnjVA4f9mfh5yk97u3uYiNQLOpkYp1b1/daoV+/fvRjG8hso0E77eHDh6NChQqcfQV6vlsshsSHU1JSkCtnDjSrUw2lixVGUpLxgIMccPvyyy9x8uRJ/P777/jhhx/snmexWGzWrvmye6JkcDYUye3DFb+OuHYV86f/gmkLl8HLy3bM5GXXAnyno5qX2hhv3749Jk+ejJEjR6JChQrYtWsX1q9fjwIFtC1EKlJqadVkZPylcC52KoiRyDhAV7rV2/pi3f9qM1O9AeDzuoXxv4ZFMfJtffVfWhZfalhKnm9XYKeTscYfkaiBo3GyAG9mcJsRo6rTVQpkR5sKeezSibUY9CT0+hfOjGjKrUGmTdgJgv24aUJ+ou2uSNG4v3u/yUw/7fAGfeFPS+lTUp8TXRTBYrGgNadUQwtnRzQVUk8m6WpM3X7F0LHnflKFe0/TWkteuMvujwrYjyV/flYdI98uzW1X+VE18hw28i2xGnia6rgoRgwH0TRlGjSnopaWe0MUhrXobt1q22ZfiLaOc0SJW79G+mqGf/+UbDyKiFOSRPgA8egcKWr/hYb3QRp/Q3N66/o8RdcxFfNnRw2Kk2Je56qoyZhn/9ewKLUX+IYv2GKNRulVj66JIPrel3+uz6g2WnZHum/L5BWLHmdE+SivjMHNxQml8/ihUE5vXfXMPH0UFk4WC8rl87cRxjMSPMqX3UvTuMkLCtIgjdm8z1lWFw8ODkbjxo1RKH9enD1zGu3af6jvJBTI5YVOTk7Yt28fLly4YBcVl8nh7QZnJwt8XKUxydXZSWgNV6V8aYTtOYwcuWzXVAHebsglMG/wyozUvNTGOAD06tUL4eHhiI+Px9GjR1GnDl0UgoborRPMEHqh9dgV4aumxbmeS1bNZU6G1zR9f/KN0bCEdrXhzxhKl0qyebiif+NiKCrQpoyEEQOUlrL2UbX8TKEVIOOcLjk5Hlkag5uLq96qxdhcnCyY+THfqSGaNkbDycmCyR9URN+GRfGFTnEpEnpTa430fxadvEhOMF4qrZL8qsj4lv51UIFjGH7fujS1/GMeR8yORVY4mWREa6dJTjQRzz3vM+XRkFE3ySf9/I591xjVC+VApxqh3NdUpzo6WaR2UKJpm0YXsUb2JrW71FJzbUQoVUZ5XTx5nsh4pi1KJ1NmKlz768woKB7kq2nMUUJrp5WVbdj0Bge0XO8iwQutiKYm670t/bxcsZkieCb6kixtDS1ULxRAFRglof5O6xbLJeykp32vGV2a5OxkgcVisTHGRQ9Je953X/bCkQN78csvv6S+tgXh4eEAgHPnzqFFixbw8fFBYGAgOnXqhMePHgKQ7sd69eqhT58+6NOnD/z9/ZEjRw4MHToUVob1/PDubXT58D34+PggW7ZseP/993Hv3j0AwIIFCzBixAicPHky7VwWLFgAiwX4ffavaNeoJqoVy4uQkBD06tULz549Y75nHw9XrFm6AL06vos3igSjec3y2LlxTdrj4eHhsFgsWL58OerVqwcPDw8sXrw4LTr//fff49GjRwgLC8OKPxaieY30YFrnzp3Rpk0bjBkzBoGBgfD398eIESOQlJSEr776CvXKFULzamWw+s/FNud069YttG/fHtmzZ0dAQABatWqFK1eu2L3uz+N/ROMqJdGgWoW081y1ahXq168PLy8vlC9fHvv370//XB8+RIcOHVAgfwhK5c+F9xq/iQ1/r0h7PF92L6HxSKvT5qU3xh2B6I3dpFQg1Wj58zP9qTwiYiUs40JkselN8a65c4SVSJQM1mZcX7lveyOLDuQiNZlaaVQqkHuj0IwDo4t6niAEIGUD9GtU1GbSzk1JRSThofiel3avjitjWqAZR5wIYCtiakWv0+FlIUCwx20KYVGn5YpV10n7uPO/Aw9XZ3Svbe8MC/bzMNSqQ6QMwgisdoCikO7b4oH8sWhRV/21mkZRTi16RKlkLoxqLjR+yBjVWjAC6XsapqE9l95ym6qh6dFgpUF58Poj4dfILeDY1gJfK0bCiHGh996i6dplUachAPrLkrR8fskGxiKjZRj7BjVEi7L6nDzFKGOdlvdev7h24ShACmIAwPh3y+HPz2qgjYYOK+o15gINTmPaWk29NLRarXiekGTzE5eYTPxRP4/18yIhfb8XCeR91QYx7dv4esRYVK9eA927d8edO3dw584dhISE4M6dO6hbty4qVKiAI0eOYOPGjbh37x6+6tlFer3U73fhwoVwcXHBwYMHMWXKFEyaNAlz5861O46bs1Qr/UXXj/Do0SPs3LkTYWFhuHr1Ktq3bw9AyioeMGAASpcunXYu7du3h4+7C5ycnPDNyB+xcss+LFy4ENu2bcPXX3/N/a4m/zgajVq8heWbd6Nl2/fRs+snOH/+vM1zvvnmG/zvf//D+fPn0bRpU+5ryunv27Ztw+3bt7Fr1y5MnDgRw4cPR6tWrZA9e3YcPHgQPXv2wOhv++Pu7ZtwdXbC8+fPUb9+ffj7+2P37t3Yu3cvAgIC0LRpU8QpBOK2bt2K8+fPIywsDGvXrk3bPmTIEAwcOBAnTpxAsWLF0KFDh7T0+RcvXqBixYpYu3YtTp8+ja7duuLbLz7HqeNHuO/HCJkr9/qSY7FY8GXjYhi/8aLN9l6cHroyrcoFY+2pO3bb9XqDtVCFkmqkZw2gdS5Tvr21fWsJ9xZ3pUzMeiczgF4nrCQjFZh5NCkdhCalg/DL1stp27QstpRiHTUYircZSQYEHpi0Lp8H/5687bDXE1FfBoAkwhvV8tbVt73ovehKWOAbsXWrFQwwlJYsQh4NhqQWvmnOVn0GJEfT9bEtUHPcNtyJzvzuEY5Aa7TYqC1uxHli9NgkhzerZlZmTNuyaDxpl6FzcITTSMmFUc2EnqceC1hq5Wr0nnIyRcAtKyPjBptrCCFahkSCpLovsqaQCfLzwPSPKiN00Drd56Dm3cr5hJ87/t3ymLL1MjowBERJjHq7DD6vU9gum0sEdamHFucB6Vp8q3weu9d4kZiMUsM2aT43R3BuZFObYBnp/RXO5QP34Gxwd3eDl5cXgoLSr6MZM2agUqVKGDNmTNq2efPmISQkBOHXrqBsKSnbMSQkBJMmTYLFYkHx4sVx+vRpTJo0Cd27d7c9Vm4f/Lt+I86dPY3r168jJETKEl20aBFKly6Nw4cPo2rVqvDx8YGLi4vNuQDAx916pv1dLl95jBo1Cj179sT06dOZn8N7772Hdzp0AgD0+WoIju7bialTp9rs169fP7zzzjvM11Eil68FBARgypQpcHJyQvHixTF+/Hg8f/4c3377LQCpdfW4ceNw9vhh1K5QAksX/w5XV1fMmjUr7bV+++03ZM+eHdu2bUOLFi0AAN7e3pg7dy7c3KTjyJkKAwcORMuWLQEAI0aMQOnSpXHlyhWUKFEC+fLls3FOfD2gP9av34iwtf+gXEVxIWOtgdDXIjKuBdLE93Uz/oIQoNfS8QQ4WIgOqmXy+mFlz5rYP7gBWpYVF7c59K3UFs3IYl0ZUdZS/0JKyTwzoilX4IWF0VZaopBafohGSQDb62zDabLQDolW5YJRIcTfUK9Vvb1DZYxmECjxFbjuvtcQdaOhFCBJNFAzbiQVUHSNQvLdeXGUP1l8yWgb5ijUIlUfOEj5WDSLwWKxUGtFM5KsM2uM0ZjTijMjIUXDNvfjl58pa/BIWSsZCa2NmLDhoXoer1WgEodHxjUYS0bLm9RkRkYHqSOFaA0zqYTp3761NJ8DVVBXIzsG1tNUzpfL1x2j2pRBqTzaFL+dnCy6DHGjkK5FXpeAlxEni4Va/nb06FFs374dPj4+aT8lSkg2xc0b19PmkOrVq9uMJzVq1MDly5eRnJxs83quzk64ef0KQkJC0gxxAChVqhT8/f3totVqDu3bjc8/bItGVUrB19cXnTp1wsOHDxEbG8vcr0YN2+zgKm9UsztWlSp8Y5U0ApQuXRpOiuBcYGAgypZN7ybh7OyMHDlywDn+KTzdXHD06FGcO3cuLQXfYrHAzc0NsbGxuHbtWtp+ZcuWTTPElZQrl54mHxwsrYejoiTx3JSUFEyaNAk1atRA/vz5ERQUhAN7d+Pu7Zvc96bEw9UZ49+la1upeS0i45kQmAZAr9vW4llVM+ItcXE0WdTly8ZFse60FKHnvfXc2TwQPq4ltp6/h64LpTQMrescR0bFjEbwRCNM71TKa9cqR8vbLkCYuHgifTSKBorv5+HqjL8NKr7zVHh5lA/xx9Lu1RESoO17r1c8F3ZcvA9AWqycuRWNTzl9TAFj18TqXjWx7UIU+jQoguJDNwIQ/54Tk+2fyeu7qkRdN+crkKYOkGseRdK1ZSqE+ONE5JO0/x29oKZRpUB2HLnxGABQSFCxmYergGqpTNl8flh1nNz+iseYtmXx7erTNttE6qCNpB/XLpoTuy8/wHsaIl8y71TKh9Hr2IsuFqPalEHl0ADk9HZDzz+O6X6dIS1Kaq69VtfS+Xm6CqlBKyMNej93vVHmie9XwNO4JISdu6drf/UaREvZkN5zpqlKaxH/2/BFHXSYcwD3n8ZrPn7FEH+7jCa9ray0MLBpcfRSXNOj3i5NFbMTobiOFq5fNy2OGTuu6j6mTCi3TeurDelyCPb3xPXHtts8XZ1xbqRt2vOZW9HE1xTNzAQkp965OzHMfUmtw4oG+iI2Pgm3n0h9ra2MVUVKSgpat26NH3/80Wb7hTsxyBmozylqtVqJYyBtu8yNGzfQp9P7eO/jLug98Fu8UaIA9uzZg65du6YJroni6uxkdyxvb9vrVW4/piQpyf44rq6246HFYiFuS0nN9klJSUGdOnWwc+dO5jmqz4d0PPk9yK89efJk/Pjjj5g1axbKli0Lb29vfPjJp0hMSGAei4SWcee1iIwbWcw7Yu4ordFLqUSf2I32k65dVF+tEWBsgv3lgwq69yUh+l2TFto964oJ1wHkBZLedXlGK6lnBDUK52D21lWypFs1tCoXjFFvpytFd6xeAIu6VhMS9zLizKqYPzsGNCluYxjrFZAqGZxNU+aFuh2PaHsekiJ6pxqhwsdVG9+ZlS1SWVHTK3pt8NDy3X9cvYCw+KSaRoQ2jSJOjJqFc8DT1Vm4Y4eS6R9VwoyPKmHk22IK6koCvN2IKbWi+Hq4omP1AjZtX3jt52SUmSWd3wzVHFFT97oVnT683FzQv3Ex9KlfRCitnQRLEImHkbWAkdRw1kKfBa3tnhaHYpHcPtg3qAHerZwPEzSq6HesYS+k2kiHWKLWj65F2WAMV2RTdawRihwalY2NYrFY0jLItDitL41unkFn9HKi/m4LUZwPFosFXm4uNj8ers7EH/XzWD/e7i7cfUnGraerM3IoHIjysOLm5mYXya5UqRLOnj2L0NBQFClSJO0nf8FC8PJKV3Q/cOCAzX4HDhxA0aJF4exsv24oVaoUIiIiEBkZmbbt3LlziI6ORsmSJanncuTIESQnJ2HAsNEoV6kqihUrhtu3xUoA1ed39PChtAg/jVy5cuHu3bs24+75M6cZe4hRqVIlnDhxAo8eieuFiLJ9+3a0bt0abdq0QeHChZErVy5cvXyRv6NBXgtjvJ+G3phKyuXzw+5vGhg+fh6GSntGUCinNyqE+KNusVzCytFKA0XrgsWIsi+vDRkLpbJ48UBftCgbJNxDVSkeN/7dctjwRW00KyPuxSJ9RloWDcqaweyCqbivKjWL5MS0DyshJMAL7SrlQ6tywQjWEJ1xVDTl62bFAbDb4ikx2sJJSQ4N4l4kobbCucUjJBXz27Y90muMa+25269hMQxuXgJbB9RFs9JB6FG3sKZ0XBJaHCeuzk7oXDNU13FI/V9FnCfe7i448X1jrOxB729Mw9fDFc3LBgs7adTM+LiyJhVzElUUDhRRh0+8whjXc22pM8i0RLn/17AoBjYtbrOtbwN6Wyg1n6ReH3ocGeohX8uwpHzq+v9pa5OlxRFnc0yLhehk4rUkUuPq7ISf3yuPdhozOFydnXBtTAtM+7Ai/u79JqZ2qCjsLDPS7gkw5gx0VIBgTqcq+KZZCazqKZ7J5ohOA1mJ0ZaYtNZyomhdSxnJbFLuKw8NoaGhOHjwIMLDw/HgwQOkpKSgd+/eePToETp06IBDhw7h2rVr2Lx5M4YN6IPk5OS0AFJkZCT69++PixcvYunSpZg6dSq++OIL4rEbNWqEcuXK4aOPPsKxY8dw6NAhdOrUCXXr1k1LFQ8NDcX169dx4sQJPHjwAPHx8ShcWOrzvXT+bNy8EY5FixZh5syZQu/3r7/+wt/LFiP82hVMnzAWhw4dQp8+fZj71KtXD/fv38f48eNx9epV/Prrr9i5LUzoeCw++ugjBAYG4q233sLOnTtx/fp17NixAz169EBERISh1y5cuDA2bdqEffv24dy5c/jss8/w+MEDw+fM4z+fpn7w24YIzuUv/HylkdW6XB5iGxetZFaafNrxnCxY3Uv74lBGa/Agq5R9u9cphDeL5ETEo1hNhjRgK6pXNTQABTWmg5E/IvHP4ZcPKuKtaXtQr3gu4bYpjqIYp398RjKB0EtaK3oXS73qFcEnNUKFW229WzkfBv51Mu1/I1e50QpXkX7IMs3KBGH2rvS6Kb3G+JxOVbD0UCQ+YPQ+V+Lp5ozPFVoGgwTE13hozYrQ6xhUK98DgLdg+zzRNj4ZwcCmxRDg7YomOtt0Kc9d9JMzaig5ij+6VcOJyCfCAqsAUCiXD86OaOqQ99BcQwqiUuFbaxeRpqWDsGNgPYzbcAEbz4rriwDAB1XzY8v5KE37OBInJwtalZMMNC1aI4u6VkO7GfsAaCvRkalTLBdqFMqhqQRM5u0KeTFl62Vcvc+uoeWRy9fdUO1409JZp+uglfBxLfEsPklzFqrSoP2jWzVUL5QDiQnaSyIssKBUnmyZvtZOP77EwIED8cknn6BUqVJ48eIFrl+/jtDQUOzduxfffPMNmjZtivj4eBQoUACNmzRBgRw+aSU6nTp1wosXL/DGG2/A2dkZffv2xWeffUY+nsWCv//+G3379kWdOnXg5OSEZs2aYerUqWnPadeuXVoLrydPnmD+/Pno3Lkzhowci9nTfsGUcSNRt24djB07Fp06deK+xxEjRmDFqtX4YchA5MyVG3/88QdKlWLr+ZQsWRLTp0/HmDFjMGrUKLRr1w59+32JeXPnGMpY9vLywq5du/DNN9/g3XffxdOnT5E3b140bNgQ/v7+ul8XAIYNG4bw8HA0bdoUXl5e+Oyzz/DW22/jdtRDw90WWPznjXHRhbeM0hB1lI2p1/s2qb1+w8WIxy9QQ9QSsE3nNJIO9j8NEQ6ZUnmyaRYrAWxbrOhxJpB622p5mVy+7tg/uKHm4xphbd9auHr/mZ3Y1qvE3E5V0MiA+JTW8UBJTge3RWIxt1MVdPtd0nAopnFBqV686k3zz53NA180clxPeT1ojRTpTQcmLeLq6WwTlJl4ubmgT4PM/Y7eKBiArrUKar4uaeidqd4sklNXiY+RMUBmcPMS6FBNXLH6nxPpqaB6rtHQnN4Y3bYMvN1d0EHQOQZIrT639K+DreejMHbDBc3HzSoqF8iODV/Uxpxd13QJULq5OGHpZ9V1H796oRyGjXGjZHZqvVGM6v3I97K2yuV0jGRo6iUwmwfiE1PSnHvFihWz6VktU7RoUaxatYr5Wq6urpg8eTJmzJhBfFxWApfJnz8//vnnH+rrubu7Y8WKFXbbhw3+Gp/26IOcPu5pZUodO3ZknhsA5MmTB1vDNuPJ80R4uDnb1NKHhoZSM2p79OiBHj16pP1vtVox5Ntv0+b2BQsW2O2zY8cOu23q9x8UFISFCxdSz5f0uqTz9Pf3t9kWEBCAv//+227fpJSUDA08/ueNca0oPdiOaAGiTKXWStuK2oV9jPDbJ1Vw7nYM6gjWDsq4ODvh3z61kGK16vIcXRrdHBfuxqBMHm1psUZQRsb1fM1/HLyR9ncuX3fcfxqPZjqjU5lFmbx+msRNXib6NSqK0zejs9RAGtNWe22vXhqVCsTavrUwc+dVfKVKy+Xh7e6SJg4GaBNBe9nQaowrF2Rj2pZlPNMWtfMy7Ms6KKojIvcqIy4MbsF3rYx3OFC+3qtAnWK5sPncPbi7ONlkgIjw8Fl6tE+v0ZDTx11XZlGR3L44TRG7epkpGZwNE9tXyJJjvwyXZGa0xM1qjJToFczpjesPJIdJVhjiQNa2ydWLm4sTCukUG7ZYLEJim7zX0Foq8zJAyp5z6Otn6Ku/ggQpbi5HDMgNCTVbNGZ+XAk9FutXtjVKw5KBaKhDYAWQlIz14ubihHL5/HXvrwdlqqCegVzZy3TLl3UR/jAW5R3Y8svEFr26D47ESB1ikmBvcyVl8vph2oeVdB1PWXee0ZNIRqI1xV7prW9VXr+C8utkiJfOkw0X7z411LbPCHn9X40FbYc38iPA2w2VVJoMIig7JGRFWVfrcnmw+9KDLPuOXzXUiv9ZQalMLl/LCj6pWQBnbkdr7sgASJobhXJ64050HPJmz1xdJhMTR2Ma4yrerZwPg1ZJan96IuNOFtvWYFo8UM3KBNtEtEwyDuWCyGgGhJ+XK8p7+Rs8I5OXkXL5/HDqpvGoUkycfe/bjETZmzizWptlBFqjQ55uzvj1w0pItlqJQngm9qzpUwuJySmZGq34qmlx/LTpIt4IDcBP74n3Ys1KnJ0sultklcqTDeEPnwMAssI35uLslGVR5leRrIyMr+5VE4euPzIsZvYq4OXmgl91OpwBwMfDFUX/A+M8KS37ZcJIFwoTMV7dkEkGoVQf15P5svOr+oaOP7RlKXi6OuPLlyAS+F9GGQ3X8z1nRr9Uk6zH6Bwkt4sa7AAxMy0ozzuzWptlBHpSmFuWC8ZbBlV9XyecnTI/bbB3/SIIH9cSy3vUQIEc/+1eygDQs266Hsqrkpb/OpOV31DF/Nnxed3CWZZ6/boRlKqRlMfPjK6bZB1mZJxAk1KB2H35QZoKqBZCAtJTWfW0Rioe5IvTw5sItyQz0YdyotNjb/3Yrhw+X3TUcSdk8lJSrWAATt+K1r0wWtS1GpKSU7L0fnaE9oWJiYl+4pLS+/16voL1kq8bpV9RbZX/EpkVjc3t64HsXm6vtNPaJOtw1HVqGuMEZnWsjMRkq+6ej7M6VsbZ2zFoV0lfD23TEM94lDVheu6lpqWDMP7dcqY39T/OgCbFEeTngUY6tRSArLmfm5cNSmuD5P6K9q51VL9frZTW0Z3BxISFcqHvn4HtcUwcw7uV8uFFQjKqhGrXBzAxhqurdH88f/4cnp6Zs74yDXETvTx/LpUfydetXkxjnIDFYoGbAQXipqWDdAlSmGQiiq/XqrML9PuvQU3X646nmzO61S6U1aehmbfK50FMXBLK5/N7JUsqvNyc8XYFfc5Mo3xcvUCWHNfk9eBVvB9fN5ycLPikZmhWn8ZribOzM/z9/REVFQVA6iltlnaYvGxYrVY8f/4cUVFR8Pf3h7OzsYwn0xg3eS3xcXeBq7MFiclW5HzF+nmamPCwWCzo+AoblVmpF2Nq1Zg4mqxQUDcxeVUJCpKCWbJBbmLysuLv7592vRrBNMZNXkucnSw4PbwpUqxWM0XJxOQlIyttl8BspnPOxLGUypMNbxQMQLDfq9HGzcQkK7FYLAgODkbu3LmRmJiY1adjYkLE1dXVcERcxjTGTV5bMltB2MTE5OVlbqcqOH0rGg1K5M7qUzH5j+HsZMHyz2tk9WmYmLxSODs7O8zYMTF5mcn0kGB4eDi6du2KggULwtPTE4ULF8b333+PhIQEm+dZLBa7n5kzZ2b26ZqYmJiYZDJZERhvVCoQXzYuZtYnmpiYmJiYmGQamR4Zv3DhAlJSUjBr1iwUKVIEZ86cQffu3REbG4uff/7Z5rnz589Hs2bN0v738zPbTZiYmJj8V/miYVH8svUyRrUpk9WnYmJiYmJiYmKS4VismdXMj8FPP/2EGTNm4Nq1a2nbLBYLVq9ejTZt2uh6zZiYGPj5+SE6OhrZspmtakxMTExeBZ48T4C/l1tWn4aJiYmJiYmJiS602KEvRc14dHQ0AgIC7Lb36dMH3bp1Q8GCBdG1a1d89tlncHIiZ9bHx8cjPj7e5jUB6cMwMTExMXk1cAIQExOX1adhYmJiYmJiYqIL2f4UiXlnuTF+9epVTJ06FRMmTLDZPmrUKDRs2BCenp7YunUrBgwYgAcPHmDo0KHE1xk7dixGjBhhtz0kxOwFbWJiYmJiYmJiYmJiYpJ5PHz4kFtm7bA09eHDhxONYSWHDx9GlSpV0v6/ffs26tati7p162Lu3LnMfSdMmICRI0emRbzVqCPjT548QYECBRAREfFa1ZpXrVoVhw8fzurTeCWIiYlBSEgIIiMjzVIGDZjXmDjmNaYd8/oSx7y+9GFeY+KY15h2zOtLHPP60od5jYmTVddYdHQ08ufPj8ePH8Pf35/5XIdFxvv06YMPPviA+ZzQ0NC0v2/fvo369eujRo0amD17Nvf1q1evjpiYGNy7dw+BgYF2j7u7u8Pd3b4/rJ+f32t1gzs7O79W79cRZMuWzfzMNGBeY9oxrzFxzOtLO+b1pQ3zGtOOeY2JY15f2jGvL22Y15h2suoao5VXK3GYMZ4zZ07kzJlT6Lm3bt1C/fr1UblyZcyfP1/oRI8fPw4PDw+ud+F1p3fv3ll9Cib/ccxrzCQjMa8vk4zGvMZMMhLz+jLJaMxr7L9Fpqupy6np+fPnx++//w5nZ+e0x4KCggAA//77L+7evYsaNWrA09MT27dvx4ABA9C5c2f88ssvQscx1dRNeJjXiElGY15jJhmJeX2ZZDTmNWaSkZjXl0lGk1XX2Eutpr5582ZcuXIFV65cQb58+Wwek/0Crq6umD59Ovr374+UlBQUKlQII0eO1OQJcnd3x/fff09MXTcxAcxrxCTjMa8xk4zEvL5MMhrzGjPJSMzryySjyaprTMtxX4o+4yYmJiYmJiYmJiYmJiYmrxP8Ym0TExMTExMTExMTExMTExOHYhrjJiYmJiYmJiYmJiYmJiaZjGmMm5iYmJiYmJiYmJiYmJhkMqYxbmJiYmJiYmJiYmJiYmKSyZjGuImJiYmJiYmJiYmJiYlJJpPprc0yi5SUFNy+fRu+vr6wWCxZfTomJiYmJiYmJiYmJiYm/3GsViuePn2KPHnywMmJHfv+zxrjt2/fRkhISFafhomJiYmJiYmJiYmJiclrRmRkJPLly8d8zn/WGPf19QUgfQjZsmXL4rMxMTExMTExMTExMTEx+a8TExODkJCQNHuUxX/WGJdT07Nly2Ya4yYmJiYmJiYmJulc2QJ4BgB5K2X1mZi8rFzfBWz+Dmg9GchTMavPxoREUjxgtQKuHll9JkRESqVNATcTExMTE21c2QKs+R+QEJvVZ2JiYk9yEvD8UVafhcnLzONwYHE7YE79rD4Tk5eZha2BOyeAxe9m9ZmI8+Ix8E9vIHxvVp9JxmO1AqNzAz8EAkkJWX02ujGNcRMTE3uSEoDkxMw95sOrwMUNmXtME30sbgccWwhsGa5tv6QEYHY9YG3/jDgrk5eNJ5HA/YuZf9zfGgPjCwKPrmvf12qVfl41bp8AlneSInkmfB7fyLpjx9yRonmZydO7wJRKwN5fMve4/xVe6HDuRd/K/HVUSgrwYyhwfDGwoEXmHjsreHA5/e8nEVl3HgYxjfGswGqVFiiZfZOamIgQ/wyYVBqY3zxzjzu1ErD0A+Dq9sw9rol+Ds3W9vzLm4Hbx4Ejv2XM+Zi8XEwuA/z6BvD0XuYe9/Yx6feFddr2s1olR9P85q+WQR5xAJhdFzj3jxTJM3l5iboATCwBzKqrfd9nUcDs+sDJP7Xvu2Mc8OgqEDZM+75ZSfgeYEYtIPJQFp+Ixq5MEQeASaWAUTkzdyxZ+WnmHYvExQ3ArWP69t02GhjuB7x4Ir5PxL70v3eM0XdcQHJiZCGmMa6XmDv6vO6AtID99Q1g+SeOPScRnkUBFzdm7oV36xhw52TmHQ8Ant0HUpKlv58/AhLjMvf4ABD/FAj7XvKO6iH2AXBhvZRymZncPgbERgE3D2fucWUiD2bNcU3EuHNK/77WZMedhx5iH2bNPZWVyAucx+Ha9kt4DhyaA0Tf1HfcuJj0vycU0/caWkmIBf54L/1/Dz/t+1/dCkTsf3WiLLEPtTvFlJxZBSxqK803WlnbH1j/FXD/ErDqM9so1ctO+O6sOe6ZldLv++e17/vvF9L8vPpz7fumZGHw5+k9YMsI7WMQACxoCdw7LWW7ZCVaWiRbrdL7lYl/qv14T+/qM+LPrta+jyN4Egns/1UKqOgt/dj1k/T7xwLi+6Qo1hRnVgJROu6rs6uBcSHA5TDt+zqI19MYT06U6j92jtf/GhNLAFMqSLUZWtnwtfT7okavPQAc+x2YWFrfBQcA06sDS9tLKaZ6uHVUMnRFiX8m3Ziz6kh/ayXxBbBpiLbal9sngJ+LAAvfkrx04wtK9SR6uLEfODJf375j8wF7J0veUT3Mqgv82QE4NEvf/vfOAss+1n6tZHkdsEYPtIk27pwEYm7r3z9Gp3PpZWBuA+me2j8tc497fi0wt7F+B25iHHB6hT6DSV7g/FJe235bhgPrBwJTq+hbFI7Lgtaip1dI2RcyZ1dp21/pLHJydsw5ZSRP7wE/FUo38PSwogtwdRuwdQT/uUrin0kZLodmA79WBU4tA/7IpLram0eAZR31GXeA5GCS74vMxohDMuJA+t9aAyqWLFzu/9UZ2DMRmN8y685BC8lJwA/BkhMzDQ3rkiXtbSO2Wgx5QJovJhQH/umjbT8SWjIhUlKAg7Ok7LWbR7XNN5PLAJu+1X5+rHMRYZ2q5E2PTfZXZyDhmTR+xT7Uvr8DeD2N8QtrgSthwPYfgKUdtKVEqJlaRdvz9aZvpCQDeyYBa/oCMTclD6kWkuKlyet56oV2aaP2c4g8DMxpAEwsKb6P8sYYm1cyrrWwb6q0cNZS+3J0gfT7xh7JS2eE+c2Atf2M1+FpTZc8tkj6ngHgxFLtx7tzCphREzj/L7CglbZ9jX5meriyNf3vrFw0aOHSZuCggYhUVvDgiuQY03IPq0nJ4ui21QrcPaMvui0v3s+scOgpMUlOApZ9BNw8BPzdS/v+d09LTrWVXYGfChs7Fy0CN1dSowRJL4C1Xxo7rh5iHwCre0jftShqJ9PVbdqOaVUsALWOQ0YE4x5elQIEN/Zr28+R9eFaz//gDPtteozjpAQpIqXFWT+3IXB+DbBCR0ruzNpSGZZRTq8ANg/V7qiyGshKVNYtp2gc/yIMZJwlPJcitSu76ysjkw3TGJ1ZNkaJuiAF30SvsbOrgMTnttu0GNSXN4k/V82JJdJ8AQAnFut/HZm9v0jrQBFGZpeChbPrSY5rR9wnoqjXFQ91ZtloXZ+o50Qtaf4ru0mflQMCWK/IqtfBKL3IF9dri5A/ug5MrZz+/3ONkQq96Run/7IVS4o8KNXSiBI2TJq8ZLQsNK7tkDyah+dK/xtJd5pcVtvzHSn+8yRS/76Prhk79roB2p6/RuERvXda+/Fm1U7/W+s1qkTzQsMqZTIcICzUWKz/Kv1vpywYli6sl5xdou83JQVY8h6w4StpIa2VxDjg797Sgm52Pekz00Nykjaj9NaR9L+H+wE39tGfS0NeKOhCsaDRMmkqxY6WdwRmvil99qIkPLd1YN7VeE9dWKft+lCyZ1L631rLdeKigZm10g1jo2z5XsOxFWnmR3VmB+nh7mnJMPypMHByqfRdi5JsUBRLabxrcRzvGCdlYO36Wd9xl3eSvuP5zTTu6MBa1Nj72u7JbaMdc9ytI6SI1OQy2ve9dVTbPZmcBNwllNks/VDbHG+1Ss6xfVOlzhKix9abegxI5YU2r6fBsfbwKvBAsZY6rsHIS0kGxgRLkdrTy4FFbcT3JXHvnPhzjQTKZJLigenVpOCb6DVLdEwZyNgTDcJF3wL+7qn/OLR1hNb1mEySYHmnnmi0mrmNVBt0ft4LW2lzOh+Ybvv/tR3i+57+S8oi0LOOUvF6GuNqL9GBX8VTr//8CHh4xXbbz8UyPlqkPiYg1dKIclCd6qzhQv/9bSnKfEqHaIh6sRB7X0oxY/H8kWSc3T7u2AiW1lrkzUPT/446L2Z0Wa3SAtoI13bq3/fFY2D3RGPHV6Jl4XD3tJRxsX8asHGQton0keKz1RqROv+vlM61aYh+UcQ/O0jOrgjByNQzhSBVQqw0gB/VUPpxeI7k9V7ZVbrOtaRNRxyUDPiFrYFROaQf0WtOHZVxhEjfhfX69lv8jtjz7pySWpdsGCT9L4/fR+aJ7Z+SIpUVyRkzevjzQ+n6uKYjKnRySfrfibHa6tJi7mg/nkzsA1WaJewXHiyMOPGiLujb7+ZRyfkwSYdhBhgXRVVGWqdq6D29Y6z0e9sofcdV1qdH3xT/3o2sO148Bn6pkP5/5EHjhpYe5LHvxWN9CuOjA8XmqZQUqWyMxMV1wLQ3xI85wj/970NzBI6dDMxrIhm0tHPgsbS97f97JkqlaDyO/W5/Lf/TW/y45/4Rf66alGT7qOGMGmLpz0kJ9rXDm7/TduxNQ6S5Q+YWZ+0JSOs8UnmLkYw90ZIIPbXlMinJ9HWEEQE5kbFcOY7IiNpUiS+AbT+ki27KrOyq/7xH5xJ/LskxL+KsUp7b+oHSPWUgxf31NMZJrOou9rwowuD37J72SIuMqEdJWQdns110YfcSKcPObch+fMM3Uh3a7HqOPa6WtK6Tf0peb5mDM8UWZ9tGA+Py64+QxD+zjaRpZW1/7bV/LERT6p7elRbRyhT3HwtIKVda0RKRSnwhpfAeXyRNRFq1ENRRZdF0LmVtZNQ5yWH17/8kw1qEp3fFnkc79u3jtimq4/KL7UtavE8oKaWui3zuJFXsPztIESqtXNshLZZ4E+72VIXUgzOAf/tpP07Yd8YdZDJPItLT5PWKQi7vJP5cIymtRlPajaA3A0ye5xJ1pv0ZaRdFWnRmdFs2q1UaI+MVWQiTSkvOIxFnJk1cT2QRe2Qe8FilYSCa9p7wnP8cEX4saPu/HmMkOV5s/XVmBdtZojfjTyQleVZdfWMki90TpFI0HrITUy8ruthvE52/ZtYGxuSx3x4mkKETG2W/bd8UcUHchW/ZG6c8UdrEF9I6jxS4SdJYYqlEVCyQpCcg6gwxMlewmF6N/5y4J/bbfi4i5iz8vQ2wi5CdfPeUtgwOvZACfiLOKqU98ThcOtfVn+k+jSwxxseOHYuqVavC19cXuXPnRps2bXDxou2k17lzZ1gsFpuf6tWrZ9xJ8SIelzYD28fSH9cq0CAjUs/7LIqe3qhXMEWPeJxWkuL1tbQhpZEB4o4L2oJMiwIp7bk8UYndqUa4etJ/KhjpWPGpvugbIJ2bVsEiNWrP3vzmYkIatEUcL+Xq2X179c/7F8Q856dXAD8E2W7TUorwJBIYXwjYODh9m6gS6T1FHavyWtGrnA9IBr3IYlS5cNcKacH59LY0voik8NFUsUVFAhNUNXv7pwnU9SoMC3W6tIjR4Uixtn+/ACaWklKnf39LbB/1uKWuRWQhEvnKCIxGmEnvkfddpSQDO8cZO+4zHfMNIAljkRadv2qIlsrEPwPO/i1msFxYSx8j1YaymvsXge2Ue3bZx/xjG4mqr9dQIkIj5g6hd7POddSs2vzrK0pDejSLy4Jp6UpopWbD/fR3KxCF5tgy0mFmQnExjQFS8Ip1TkqcXMjbRVKnE55L2ZwkWP3lede1kbp7EUgOcVHnrd6xD5CMSa0lpCKIOPciD9Af49WNPyM4bLSgNxMhJYWcraxVo0RBlhjjO3fuRO/evXHgwAGEhYUhKSkJTZo0QWys7Q3arFkz3LlzJ+1n/Xqd6ZCisGqGlrzHWSgITCKkIn/lop567Pb852QEVitdxVzkoptRE/hNXQciAG2R8GOoWOTjpI5orChaRVO0olf44+o2SXzDCCnJkjKvkpuHgDsn2PudWi6eWaJmTgNJyVLJuX/Eonoru9pv2zdVMtJFjLR9U4H4aNvU3ewF6c8XQTTNncS1HfpruwApEsAzolhCXDyj9QFh8tEKyfDgOV5Y3yVP7yMjWpg9TRUJEy17MVJPt6qb/TYtnSX0ordbB0A3QnnGn5ZaPRLJSba6KKIkPAf2TtF3zFvHpOifkrF5gb8+kQwWkf1p8MoqWFlHF9byj027fof7sdMtn913jLBUBKnOUmDcpqW/kiK4Ni/tgMjhnsnAH+3st4tmRJHITJEsJaL1wDR2GHSc8TDyfZHWBjIsA4+XyScinGwkJZyXNcqC1XKUFyzcPJTeytE3WP85GS3fpTlkZJ7rTwsHIGXh6mHrCKkzlRqL/g4cWWKMb9y4EZ07d0bp0qVRvnx5zJ8/HxERETh61DaNx93dHUFBQWk/AQEBGXtieqK4MiKR8Qkl9L22upYiszgwg65ivqgt//MieY5kWPWeLBEeozfffg01kyQy2hjXy6K2xvZ//ggYSbu/OJMLzxBnGYjRjF6+eiY1a7I0EYukdpGcYxH7jPXK3T/NWEq0OnKshes79RkjoqxjGPIi9+WeyeTt3EUX4zrYMYattq03y8RRrNKftkYtG1jQwlg6tgika3geR1zswRWp7pZmhPJaOhkdW2WBUTW89OAZNfVnii1qS8/kEoHl1OYZ40Zbr7H6qKudskrUzlMlIgv3Q3OkLjYkJXSegZicKKW/kuBlNTlC14cmgDingfHXZnH2b8e/5madoqEyvJarrHlfpGsAbX8RJ+hFVuCOsVbnzUUs4zDmTmovdZ3tK1lcEgjSsMoseGsp1nzC+0yYGRaM4ybESqWNLFifd0qK8ci4souPFmi6DymJurtqvBQ149HR0sSvNrZ37NiB3Llzo1ixYujevTuiougffHx8PGJiYmx+bF9sHDClEnD/Ev1Ezv2t9y1AKDJOSy/VovznSHiLlO0/sB//q7N+L+DaL+mePNYiwWh63KbB/OewMNIjlPdZZUQUT4Ynmsda+LFOW0jUjjKYcz8PA6myf33Cfw6tBkyr4rUaEWFFquFhsMe61taBSgIYC3CAnXIWNoxfzkBbyPJUgXnXCUuUh9XXW2TsMtKy5PENqfcyiXEF2K+dEGtfgqGEd9/RRHfcfNj7yWwk1JlG7Gc7udb0sVVsVsNTnGVlhQz3Yy/6rFZgIyXKwTOUWItnXmSGVCupBV7WERODY0VxneKNtPRfQCrH4mXQrB9IN5YmlaY7VQBjAleOLFdRk1H1ujKs+YxlkLDmg+OL+QEVIw4MlhDts7vsjM+kBPp9eZ1Tf22oXIGzL8sBtrS9JKo3pSL5cSPX7pL32Y9brQ5R9CbCS39nrh0Z98XpFXytB1akeXlH8VIxKhmgpfXnh7p2y3Jj3Gq1on///qhVqxbKlElXUG3evDn++OMPbNu2DRMmTMDhw4fRoEEDxMeTPThjx46Fn59f2k9ISIjtE3aMlRSbf61KP5mDMx3xlsiwPIFaBH30QDPE5jRgLwh5i+SIfVKtnV5m1eY/R82FtWzROpH6ZiOo24togTexsVKczxmMeP7WxH5bQqzUcu3aTv1Rlt/b8J9Det/RN/mZImv66jolYYLLk7ef/stYqpmImBBtrOEptnIFGxkLdN71V5mR5ilS/6pXr8CublQFb6FLSx28f4nd/owmiikTcUASHxrNMIppPH8E/FKO/njcE6m8gwavo8INRqr6hXV00R2vHOzXlaGVT7HmKl4t/KI2dIP60TV+FgNrfuaJXuq9nwvV07dfZqBXpyaj4RkOPFhtQLW088psLm7ImuPSjFqrle3QA4B1/dmPi7bkIsHLcrjEWEstaClpqJDgzQe8FnXKLjlqeA5plvOM58TXaaQJcWYle3y8eYi83WqVyoN43RtuMgJ3rDIs1nclsqY4voj+GK8Uh7feSUowVmdPQ2epYpYb43369MGpU6ewdOlSm+3t27dHy5YtUaZMGbRu3RobNmzApUuXsG4dOZ1s8ODBiI6OTvuJjDTQU1oPvBSpsGH0xy5tyJg0JECKoLDqUFh1eiITH+1G1JtGKaLSyhKtM+qhjjoPTGIIWdAESUTgRdVpAyaQLgznyGPvnihFIX5/Czj+B31flmAYK81chpQ+tfNHyTvO4tSfwKm/+K+vh6jz9Hvy0saMrYdjZcLwjPF/+rAfJ0U0ZWRVchou7vTHROpfWUJErPEgo9pC/taY/fiS99kLCfn60KOiKyT8xTAQeSmg6wcCMbfJj7EWfU9uACcp0XpRaA5PkdY/6weSt98+wd9Xbh9GgtdBQu+i68oWY465jOTMSmP7H8mg3vGPruoTORPBkW07tZCcxG+3t+Z/GXNsUjq/EloZIyvDUPQ5JxjrAhZJCcaUsFlrIVY69tO7Yl1vaON+uQ/I2x2BaKcCPbBq5AF6Jt65vyWnB01gUCacce6sdW3MbXo28g7OegQAoiPZZWgsZtamZyMkxWtrf6bEaOYkhSw1xvv27Ys1a9Zg+/btyJcvH/O5wcHBKFCgAC5fJtdzuru7I1u2bDY/mQrPWOLVfdPSkIxOarwo3V8c0RMepJv8WZRtb0ct7PzR2PmcNmC8PX8kiTKwDExWBGZZR/brs+rkE54DW0fSH8+IAUCZBsZKLz32u7HjkNLvRRe4JAErR7C6B/txo6rOLIwI5/AcGDTHydO7/DEqI1MttzCMpRwMsb6Ng4GrOuu6RFKIl3agPyYq0EYiVqDHKs143TRETMyM1vHByZWz32dspycvskQTyBQxxmmRDhcP/r5GylaMtMk8+af+fVd0NaZazWqRyfueWERdMNaVgQdJ5MwR8JxUGcGavsCoHJJhwMJICRsLvU4XkQgdT+9A3b1ClNG5pCBTRsAqrxRxGgPkezLxhdh3qLMmGIDkCNXbi5qWXXvPQJcA0UxP0pySkiyteVk91Nf1l7KRjbRyPaBT5ynqLD04IdKvnnSNXN0utYHlMbO21FVDA1lijFutVvTp0werVq3Ctm3bULAgX8H44cOHiIyMRHCwAWU/vYgaDqzn6RWnEZnUWOq6vAU2SyxNBJKX0sjixUBrAADA3xwjCwDCKTVvRvuA8sSzNg6i947lLYyyh+o5I8cQItBnkgUpwyIzUixpi/e/exms1TRAxAG2Iisrusxy1vAQmUAuUESsRMc/2nd6/xJw4Ff6fj6B9Mf0TsSiGFG/NwrJeLVaxWtbSYrnd06K9UtmOT1ZKYkAQznawD0t4gii1TiLGLuirSVJ/N2D3Q6JxZkVxgxIVl9sI2SUk9NRGBHTNYJ6rIuLEXdGP39IzhoRGT+NOFZoiOi5sBDJbiQZc0ZqoxNiBTQewo0Zd4C90Z0YJ3XrEQkG7dPZeQGQHKGLVWK7CbGSw4eXuTafIqBpqGWf4Nzu7Ga/7cQSccFYI9eiM8e5zIIk0JacKDYmk+bh8/+KHffuKeDQbLHnppIlxnjv3r2xePFiLFmyBL6+vrh79y7u3r2LFy+kdMBnz55h4MCB2L9/P8LDw7Fjxw60bt0aOXPmRNu2OlSjaa0wRBFNo6Qp803T0atUCzTFc0BskWNEQI4kpmHE0LrPiNA6igUtpUlWL6TF31bBRdOPBcjbeddYtrxir58ReFJapoleNyRjXEs/cDW3TwC/UOq9lcyoab8tJUV/6p2MkbTVeU3ZtdWn/gRWfW7vtLFagd0T9B9XJE03nCKMw61TT4VmzLN0OgCpl30YQdztZU0PVmKozRhhnLyiIROKFH0XcboAZB2R67slxXSecCfN6DbS9UNknqLVCE7U2aVEC0a6VYik4GvhzErgp6L850UcJM8rKcliuhZGukKQsFqB5QLCmkDWtftSt1nUmi10jlCuSHP+K5lSkbxOZYnZKSGVrHjrTMOVETE6l7a3P7aRtohH5osFRTYZVIJX3xcPL4tnrPH0KXiosxw3fC05fPRmhRrJGBKFZBBrKUNw89Z/7OAK+vclObxFtR1IAoJatJV4Girql9b0bAcxY8YMREdHo169eggODk77WbZMqmVzdnbG6dOn8fbbb6NYsWL45JNPUKxYMezfvx++vr7aD0hrhUGC5A0UiTQA9IgBKwU4oxGZTEieSJHWEwA5jclIrZBopP4YQ9hBBF5PUhbqyfVJhLGa7oiDfAVuI6rONESdTLSesrs4PZ5lSJOFkfZhyztJ3nEeDwi1SloWVyTve0qysV6gIpz6074ft9EezEa4K1giYSSte+9kexVmI7XkRqIzWmA5QnmQFgpG2mQd0CBASlpULGwlZQrwWvPQjGIjZQ6i+5IcNEb6uIumAD8yENnRK2xI4nG4VEMcK9DSZ14TskEl2obL0ffQ3dPiHWtE11xqDEfUVdeX1muaFOFe2Eps3w1f2/4feZgtZqdkYkn7bbkEU7bVUcuIg1I6rqgTSe3oNTIOiLb2NJLpAthHxnldEzISLetlUpeMPYI6CqQgkqjDm/T5RGoQbyZF1kUhzUcsDS4lMbfstwkHYwhO5wwMEGRZmjrpp3PnzgAAT09PbNq0CVFRUUhISMCNGzewYMECe4X0jIBkjNOEctQYVfp0tBL4luH8HtAAWbyBlhIjwn1KWx0Sei/uNRwhKx7ECJRgRP+PdraRBY21IXbMa8JfANPSqhNigT8E1WvVn7Xowp8mPMITLZQh3RcJBhZ6Gj2Otmi43kiqq3dPi3nu900VPw4JdesfIwrFWjznvLZEGYn6e9W7IAe0pTE6OgIoyj+9HPdarNZeJETqu2kYXQiTEK23NdpKTA1PHCsj4aWlktBqbO4lGONZVaJjxEi7dVTs86JlAInW1arnSK3nrI4KiwjSyqidNkZT10XPXSl4ZrVK65FFbfhq1dTjGjBY1JkJNB6HA6t76q+XzijR0IyG1CWDFHQgcXKJ/vft6qlvPxm93XoAYO8vtv/fOWW/jYXaCSG6XifOkf8xYzxT0Wrgzm0ITC5n6y2cWllsX1KaixbxFvWCxGh6vdF0mszASEqTw71UGl7vgsJY0ircIhLVJUESQjv8G3B5k9j+6s/LiLcSEO9pTTLGjRhARiJhWhZXpEiv6P6s9il6MOLo4wkPKZlWWX8nBKOoo31G0u+0fM8kheYIA1F+I+g1WGj9zGmo76GsLAl4Eim+uFKPOVrOWy2cpCXbSLQ/uwgPrwLjC+lLS9VaAsZrG8jiYRY65tTMaSD2edGeM6OG2HHUn5dWrZ98qpIc0Uivo7l1VDKotaLLWFNdk3r1kQCxjA9AinieXMLvmEFD7VB/FUqijLL2S2DbaNVGwfctIrDJQv35GslgOfKbtuers20LCrZUPrbQXsn9vxYZz1S0RlceXJLav9i0YBH8Akg1fOrUIxZHF9j+b6S29VUZXOwGBw2M8Dd2bCO18kpYk08xQoaBaAmAGlK7D3UElYXdQt9Abf/RBeQUIBKOrGlKTtI22auj91qMHVLbF1cv8f3VGBWd0QvJicPikqBzh4S6FlWLYa8WqBNRJJd5pMos0fI9kzoVGBHLE43ukNA7btOU1WmoIxUnl5KflxnMby7eLUJtLLCMh1yq1N2fCqUb4HfPSD3kaaj7i5M0O7Q4ku8pWmKu6i6JfekiE3uL//42XXBUBPW4oy69EUWLevWFtfbaPeqxQaZaD6CyqlxN3Z5Mq2Hp4Wf7P6v3c0ayQDA1Xo0eQ1otdGVEcEtrlqFeZ4fdePmKrJeNIprSrkZL8GQQwfmvnssnFNN3HoC9naQVLWsDdUliBgYq/vvGuF5DQGS/lipBJdKCxiuH+DFpPVj1cEOnsND9i8BwP/7zaGhVTTSSvmIUdeaAXiOElX1BWiwqFd+1LL7nN7fv2ahJDdpgCp4SliK4GqPlG0q0prf/1VmVxWB00jWw/7KPdR5S4zG1pFp+thNopm7jptpfaUjwUAvzbfpWfF/1QkxLmuSUCrY6BFo+s2vb7bcZie4Y6cqg517Rk2kjt6r5t5/UPk60NpWG1ohaYhxwbo1k7GnJ3FBnIdGyktyzAb0JNY3y9bl3Mvs4/vlt/39w0T6yLpoeCtiKSWq9PpQGsdEuFFrHEnWtvBbhzf2KUp34p/pUn6/tAMYzuu18+BfQQqXXsvgd2/9p0dPmP9pnh6lT+HnjQDtVlE6d2mpEdJNGd8J4BdgaCnpLufSMe+p2su4UXSe14wOQOjco109621gCji/zlGllIMOUVg7kKKPOaPasqKNLtKSq2zbAg9BW2kiZHZAuFM2LqNfsa79NOTclJ2rLSFJnO9P0kxzAa2CMUxY3bhwhOJFJj5Tmq764tSxk9TxfRu0N1hJVUvKrQeX3xYxWbAVq2W/LSuEM9cB/eI74vsrPl5WmzlOH12oQ85SpWagXzBnZV1rJvTP85wCAszt5uxbDn8S6/ul/G33PRoy0m4f17af1nE+vUO1PuT5LvwPkqQCU/8B2u3oBIaoNANifq6gaMCAt/JXOJq0GnrItotHv2YjRQzvv+oTSBXVNKatnK4nTK/R1oLA4AdG3JAHOA9MBP4YeSxeBXrTqtPfAMkCx5sAHhJ7kz+5LeibLO4qXgMmoP1va2FKdEoUV/V5JRuszVWZLZs1dPxbQVnvMgmWMd9kIlHrbdptaKHVyGfFjbRmuOK7O+3H7WPbjxZoAb3B0cUhroYJ1yeeVnGD7GfHGILXTxoiIpSh5KwHdCS1g/+ps/LWNzG8ytO+6Vj+gaBPbbXMbAHsEHBYVO/KfIyooK6OsyWfdF1UM6Er4U7rnkLLuRFE6HYy2Jtbr/KDpGeSjjOdanENFm9pvkzPuWDpHPfdL2S5qlNfjnsnkffPXAGr1Jz8mgtohqIP/vjFOS0V28wbyE1ofpSEwaZPqyP5VpDklJ5HrebOHkg1TgN9ypBplkbH4HbFJhLWw0lLfToMlRPbRX/bbaG2z1Hz/BBikcwAjLQgB8QVOF0IrBGXmAWsCq87pe65nkaI3uquMNCYlsPs7F1epRJ9bIwkZ6knBVZdq0KIrJVtJ37MaZVqSnveujCwZEn8DMJNy32YEsmNPq6rxqm62hiltLJCdiWonyLKP09XbtdZ2xdzSnhavRKn0THMiZKdEypTZTEaNcZHWTzLqOYYkcFawLlD3K/vtTxT9q9WRV5miTemtDVd25Ucd2v0GlH1PddwI23Gr1Fv0/Z1cgKCyttvk+/DBFSmT6qfCto/nrQR8+CdQgtAl4uciwMEZ0t/PNY4nyu/10TW6Mni9weTtRsQ21Y59Uc0MLZRqQzby5etEbyeHazsl5wurfVOBGsD7qp7acjT7cTi937Z/fqAlJ/01Ixy/+RiBA57mQ5nUoIHa+QBI5W/yPU37vD5eBfTYY19Xf2Qe+7iOIm9l4ANVJubF9cCpv4Al7en7VesJNCGUBsprIUcIm9Gct9lDgfaE0kuRUsVmHKcMAOwQeI6SZQoDn9eWUb1eF80AdXIGWk3WdFppdCM4XADJAH8cLq0Pdqiz2lIpWBeoQ5hvRPDOBRR4UxqLlCjHuykVtb8ua+3ml+rUqj0QeH8haWfpF63kBAACS4Fot8nXdEoKcInS1uzTjUCj79PHBSXPUnUMaKK8BetKDsHqvW23a3Ss//eN8acMJfQ8FeiPiUSWXQiRvGs70/9eS4noddkIBFL6aPImreaUmw+wTb+gDaoFapAN8uu7+G1Hht4nD+Ry9IuXJuRGqLe9Shlw1Fgs9vVYamiOl+ItgPcJrdCUhhnNgKg9AChAcNooU+5YxnglTl9V2vfUeJQUXSLuk3o8rYapcuE/vRpwg9L/tNVk+0lzeUepfcpPhfmpd+XaA+U70B+f8SZ5u8WJH7liLRZKv0Pervx+/ulNfg4AFGlkv81I/e+p5eILdlJWgJyeqUdVV9kXmWTUegYADb9LPTYhw+f31EXq7wwjjcSGr4FROaR+sXpQliGQauydXMhRIQDYPAR4LF/jlHuj+XjgzX7229XXtKZaxNRjJSdJDqt1BA/7J2uk361V6tbK63k/ZbL/cBnQR2dWhZsvUPZdoHhz2+0xN23vNdpY4uEvLfw/22WbZiq3tKR1tSClpGrBzUdKQVYjf15WK7t2kDaOzG0g9YZXp9YqCakO4vWTGf18318IhBIEhkTLF9rOtt92fZd0H08qJQnHkWhKMWTkseGXCsAaQgooAPQ7DVTtSnYY3ToqfVcs1es6DF0dWvukhsOAbmH0/eY1oT+mpGBt8mcWsR9Y/7VteYGSIg0lBxVpDZiSwk/nr/KpvdibGp4wrPqeBiRH7CVKwKVmX2n9mIPQo142HFhrmSGCjlmSgr+MC0c0lhaccfcFcpcSO76SWv2BPBWBbwkOUqVBTbu25Uh+O1XW5Kw6tv/Txk+LEz1tn0e+ylLEVk30LeCX8tL64DilxW/pNvSI/v5fpewkWjCq/3mg8zoguJzt9n80dDCqT+gDv7Ir+blFmwL/Oy6VX9T/lqzcLo/7GygOhs7rpN/eOe0fW59agvVTIX6JUFNCxwZ5HUIT5ZWvy6qE93dasHUmXgdjnFWbUecre5EXGZH6JpIHW1kDTeof2OJnIFswua4CACzKGmrKDd59G1CdUMOxY6zUHxKg36SAZJCr0yoWtuaLALm4SQO6etKV6w2v77TfhwevpZcWSFHL8h2khRkp8qNcsB2neP0bCvQzZBmI7hQV3vuXpAGcNuG++T9pcPLOTT/eZcZihITyXqAZeMVbAlW6AE6MoYEnbpWzKNBWJVxzdnV65kU8RQwkZ2pf1Krd6K8dxSjjeG8+8CXhcaWD6/Jm+8e/ewgMe0zOoIg4AKztL03crChxD4JjY1V34Icg6W/aODQ8Wjp2ECP902i0Qp1qCgBfXQX88kl/O1PSbXeO19amUMnafvr2U0IymIY9BLwC6PvIAjW0LJ+gckBdQgswEcG2gVeAEq2kHyVHFwCTygKTy5L7/SqRP3MZpaI3rfuFxSJlcunh09RIgM28kso+hfDSbkqa3aAb0ljg5AQUVdTe7p8u/aZlbeQqkf73W9PIz2HR96iUgqwmJRFY/okUvaQpsJO+XyW83vDWFKBgPfvtaoOYlqHxKUV7RDQq/zbh8/qrMzCGkh0h0/wn2+9IJlwxNiURnIODIoEalJrQ8N2p0TfKWkS5jiBF4uY0kMaRpRTnbHB5oMEQ7WrN8lzBg+oMVbyf8oRIspMLcGgW//VJ5722n5TOry4XUtJqEj8tluf80VxKk/p80jWyZ6IUVGEZ464e5GCMCHkUkVSa4wdgBxg6/aP9uI2+Bz7bQQ4EWVP4AY0Of0q/s6nEHmVn7e0TwK6fgenVyfvnKEp2rlmtUnkR7zuWjUwl0wRKewo3lM65H6GMZ9O3UnbSmGDyvs6u0rWljvSeWSFe604yqM+sJEe2nZylNUjeSnQNqbDv2PXt8hrPxR3oqmpbfP5f4OQyehceZdCLVOM/qzY70Fg71f4hOZIOzKDvp+K/b4wveY/ygFVa1PU+IC2I9ZCLMCHIwjg05Pqmmn2B4AqE/RUXIy1am7cyUG8Q+bGLqYuv8N3s8xBNDyfRbatUD6iGFU2i1QMDwN+9pEFNhMEMBe8HqtrJfmeAt6en/69cIAK2KWakustmikyDjn/Tj6vHWPq1KrD9B+ACYbCVcXEDCtW13y73SKdFtj9eJWUDNPgOaKDw5h2ey89eaKbwDIoueJT4BAFVCTV8f3W2LeEgIYtvsDzgcsRWjVy750KYBKzJwO9t7MXvZJxdJGODFOVY9pHUSuP3t4Hom/aP568pRfCCygIVPqKfNys91MnJXgxSff48alPEH1NSyK1AWM4Wme0/8J+jh/pD6dFtJeqFNLOsKBV5UqZFxgrUoPdM5YnZ+OQCPvjD/rw2fA1ER9CzsJSRqMKqtGpWhNYouUulp5er08wBMWNDidL5/PCytKCkLSaVRkolgXpPNbTv6Py//AyunAqlXhFnqpochaVsAvUier1AZ5TqvYAQQi9ggC+099kO6bdfPvsuHI+u8bM1ijYiG4c39tH3aT6eHhiQoaX/frDUtl6bNk7tGEN2wOapBHy+S/rbl2IY0CCVP6hZ3RO4fZz8GK1MUEZUD4CUVXQsNc126wjyPrlTsyLViv2ArcHgSOFTV+90HQUnZ3IK9LoB9HOWIQlkAaoSScKYoHyvxQg1wTKsFoI+hMAEIK2/tLQplEmOl5x6BwmZEQAQUIgtMDzjTWB2XWDbKLrTuvVkwJdQDrh+oKTPNIoQyQXShQGdnKWosRaCKwDZU2vV/RlaIDxcCWPJonfEDPLKncnbp1QAbh6x3ebJcK4rYQk5KgMuIYSMk9Wf0fcNUmQA0AT3RjLsJZ9c0m+vAPvgrobynP++MW4Eltesa5hUA6NGtK2Dhx/wOSGSfGp5+t/bGV5IWsq2qLeUJiwhQrZg+xoeq1VMLbocwQt94g9pUIthlBTIkCLNCbFkL7R/iK3RwZpgrxOcF8p6b5Lz4tpOYEol4A+KaJ1PalTUl9JCZ9dPUvSUBekafHpH8jCSIkND7kopdB2WAnUGAjUVBvDzh8AKTvqoMuvhTY7xrKbxSGDgRcDTn/w4qxfy8Oj0wb9SJ6DMu9qOLdf106K817aLl0SQiI6UPMNqPt2QHsFzpyxq42LIDptsiihpnorke3L/r+Q2NcpFywdL6fVhV7aQt6spLrC4BYCy7wOf75bEUnKXkmpM1fXIMkp1cyV1v5IcijzUi1FliiOt/ENk8rNYpGtVzUpGRoaSgnX4z1EiG1nysQMVhrEsGkmLML+jSI9sYsA5kqMwUE+Dsj0J9cL0r872DtC05+pcWmTLC7SdlT6/qTNOeP3Us+WzrXVkOchIWJykz9lisY8CRp2VovJyVlGcKtJStZs0L9Lm4KQ4qcaehjJ62EY8ogJAcsYFFJIigG+oFp4sxzwpDVau3+ShXuvQnBAihBKMY5aTW2Sdc3IJOSL/6SYgZxH2vomixh3jPGjZOV1SHfBuXvbG/AFFRhnJ+BQRMiMxKMI2uksT2qLdXx7+7NePTG27SjKKK3e2dRaT1mEvHkvZZzEEh3dzTu3tojbsNoUyNL0kWuozL71cRJhW/g4L1bfdzssiLa0oMwuglJaQaDVZsk30QioNUnJjD3COkqGgHDfcfelBzrDvbf8nrTOV718EI11ySrZW/GOwW4U6I1RDoC4LpayzGJoHRMkIf6AzpY9zCEU8xKjCKknwDZAmWHVUxdnNfsF6Yb29OrLM54pJmeQ9YqEWaFG/T1L0TYk8ebadJaW2jSN47HgpniSS4qX2PKeXc5/KhKciSooesOppu2xMz5zovBaYWknniREGmfUDyTU5ACGipBpczv3NFgRTLrDUIm4smo6lpzoqYYnLKM+h1SRb43dld/u6LRnloM/KTDkosMCt1IkuVHRgOnk7j5NLgU2E76u9Kn2cFD2ntQYr0Sp94LdYyFk0986RFzckGgwFLjKyNGRaTUxfpPRKbauXEEuO8PLUfRsMBY7+LkWVhVBcy83GSSIzao/3uTViC9Y3vwDCVFFTUWXZIg2BLd/znyejdiC+M8u2FvXnYvaRUBlllLdmH0n34RAlkqNGvUCp940UpdSLesznRaiVFG4g5gwr977t/BVUVqpV/SE1usSLLvdXlamQ0vNZtJkJeKe2I81OcI6d+1tahPc9at85RPl5e/gDcU9sH98xDqhIcQ5UUDmyWaUYat6dB5RSLF6Dy4vvSzL4CtQATgnck965bP8nZV+I0nSM5DBSKrCL9p5nof4OACA/JaVYySJBY4Cm/QMAsVH223KXsnXsd9lgK8qnLNtTG4Ol2wKtKaUZPEhO6nIfAKf+FNu/pyK7wi+//ZgdGwVEXZC0aJR0WmOf3UeKNu+eiJTLW5Dgndd+bR5UGYhLnRuLtwVuqSKr968DPpQIcJxiTg2sSH8eCZ/8tvt/ugtYrsG55+qdvn+rGcA8Sos9EgmJABQZBqLnXbg5kJRiu5bQ8p7z17F9z6R9H98hb/fOY7svbf+HN1TbPez3K/0BcEP1PbNItvDPm0Sx5kCB+un7JiSK72u1wvXdubC5mtWiyI8Fhf7wOhvjokYzqb7svQXpf3fZIPV/1vq6Mp+sBRYSIl9qGo+0N7S8ctqnRkZHALPrkV9DLcggSu0B9uIE6vfJ61MrG/MWCz8tTg2rViguWtwQp0UuAXqER0aLdxKQFjQyOQpLaXG0tHIW9YdItTZqRPvIk5xOY/PZbyOhZUFIynggQROXUaOesE8vl0RJeLAyU2IIIi5qmo6lG+N6UavJy6jfY/WetotRFiVa2EaHSAucGYSoF40chfnPAcjGjbr8Q4YUOVAal3W+kn6Gq7J8khLIQj/K9Dg3L6nWU22Mx8cA8yhpkGrlZK+c9mrezx/xo0BGjA7AfgH/7F56aqsa9fdaopW4Mf6GYKRfFCPq4a6Emk0ihMgEKV1SFFaaKYmcipICz+xA32P2jlS1graMMiW03W/2GVNPIuiZG810OknazLRXANbSfYGUZi0KqUwvsCxwT7ATgdKh7JENqPWllOa5VHAuySqUbQCzBQNFGgNXBKORclq+TL4q5OelpNhnCr411f567n8BmEgZf2VsIn8KSrQQM8aDygJ+ioy5wNL2xviyj4EAwhxCKrMjrJETji3B9TdGIcUzAHZjQIwL8DzVSVH+ayBUQ6/766oa5TcF2qjJeOVU7e+mcf8ctvs3/cO+PSIJJ1f9533nIWBRZexoOWfR45K2k8671iR+tlrUU+CBSkzOUgCoN0O8+02cn+2xRff1yQ2Eh6f/b7Vq+7zi/OF/5w6CgoJgsVik8UAnr58x/vavUkTkPcrih4fF2TaFokBNKWVSXkxpbeFRkCDuQDuumqajgRUGeiCKQqq70+J0+Pq6NsNOJt8bkiIkqbZKZhZhsKfx9jTxCLVapMkopDoqGsp6mxyFpdpFdaqh6OdvpF+yFuRokqMgXe9/fsjfj/W5iHwHNME9EUhKnizUavlaRIy8VJ+3lu+Z5DgRyRQCyMaNlkicSBrYX59IBqoaVt09j577bQ0tQKr/Vhvuc+rbK56TqNEH2K9DmEwr6uu5UF3J0KMp0yqpbHBuUHegEI1UkrRQqnSxba1IQ/Q6FEWLMf7ufElESAnNSaUWA/Lwt207Siphs6bQNTt4nUJoVCCkYdOEikiQPu+I/WL7krKQavUTuzYBqcZdjdLR5Yg2W44kT0Xgnbn2C+6CtcWM8cCy/DJG+X7/p5eUUaWElDYtsvh/Zy55u2hP8U5rbP9v/QuwPbe9A/GRaLsv2zHNCgvulPgUzgGhCMnuASf1FJGrmO38FqVhHsitqjOOdqMLyCpxyyY5INTzapQGh6R/AVvhTasVuC9wTTu5ATlV5y163FwF7e9pLees/ryi4gEI2jReOe0zbR6m8Huh5ypMXr/E+pKzS0j4hdiu3ayhwP3z/P2yFwJcVVpBgteX1Qo898mNqCjpHIODU+/F+kPZJcYUXj9jvOLHUh2Z+su3OIsJJZE8ybUHpA9Mj69LvR7L0YTjBPi7l31ze5KRUaotAMEFF2kB7hPE99SVpKRia1nkkAxxrxxSDTOLul+TlT+VsFrXqclRWGrPNlqVXkdavJAUbUlGsSjZCwKRnN6nMuoaqQ/+AMap6vho9bhqHL24zSz0lnuwjFJRR5mosVNOVQ5SvafUOuMipbRFjfoe0rIgz0uJqIig7qQAiF8nJCeJlrGA1D5ODe3zY7XL4xFIEAUkRbgfh4u1c6vWI3OMcdLnXfZd/vXpn59ct129l1i5RcuJ9h0oRJV01crDgHgdssONcQ3jiJY6xR9Dbf9vOcE2gp89VPpx802PFD+8LB41NoKW+kliT3PBshFS6nPZd4GAgvT+7zyUTkbaOEDSt+iyEZhPKfUQ4d35fD0VZzd+rTmLTn+Tt+csBjxIFReVexqrDXEj0DJLaALBatTrN99A4K0p9GweHqr5IsnND89zVUAePw94uSrm71wlJVFV9ZzuIuh49gwAPFTvPdEbSI7h7+vtC3gSRCRFju2dS7oHfQP0nXv2vPbnLfyeCRlIovu6+9kf1z9QLJoPADny2Y/fAfmAx5zWrKTPGQASXYB40XN31feZ+RLWXEHF0+9HDp45pPEqKioKuXPnhrOzs2Sz6DDGX9GVukFIC3Z1+hAN0uSlTodYZTA98MQfwF3VpE1aWImK5AQUtlUVl+kv4DlSp8ClHVs0Mks5R1JPUjWkNgiAdgElJer01ycR9gsrgCzYlsPAREzqX0hDfY4kI03ZM5xFZkXGSQwV9GqS0JpeqkRZRqKHsoLicer0PzdvSThPL7R7jYTe1N3SbcllIiJGUOm2dIE8UZTq/lohZRHpjSgC2tqFKcW1AHGV2vZ/iB+DhN77gDY+C5cjEK4HtTAYDeL4LGggOnq80mKMO/LYzi5An6P2Iq20dmyOhBQtp0H6fNT161rR0w9aRjmu7Zkofn8X0FCSQ0LoOqFcHzQxSSXu2eiZU0rBwSthZG0FLXODKDSl+YxG5WBMdvUBnFzgphxyfIOla4F0T5KcfST8BR2AJLRmudnsm0uaH/SMJ4FlyGtPdUtMR+PhR9bIICnB0yDNGUYyDYVLmyjH1oubN7mlMAUvL+k8ExNTMy8DGKrvDF5PY5wEq8+vkhq97bepU0YB4MUT+20iBqijqdod+N8x8iJaxJin3RCiixyal15kkZmbIuj2vsGa3hp90v8+t8b+cVoUR53mqgXvHPp7dL6qkFqFkajWw36bxULu+62G1GKvdFv7+uCMwNGGg4u7bTs9rYgIl9EcFSLvxaiTo0Qrcr9XERoMJY8HaiNZK7xWlF45pbSzDoTaykBCZF1Jrf5ASYPlLnoXGTThMrXolpbjitbDkVobikZrWYJYetAq4Kb7OIT7x9nFmFNRLwGFJPXs6gKCmqTza2qwpSGtLZ0e4ggpxRnhYL62g/8c2nE9/SURPRa0DiOAJMyohCQe91YGZOHoNBrS+ESg7ISEeu2Y+rnafLysNpMihpJ/fmPXiaH7VudxfYPpZQwkG8ORZMtLfs8WJ2NODSOfo7uv2PjtlYPdEk8PGs7bor7OdAYITGNcC59uklKn1ZAUSUlpDn2PkV9XJEJNg1fbzEvz5lGkIXm70QmX55ioP4Tc7gQw1iMdsPUyk8oOmhDaHgHkRSYJmlCcSJon7b2pVRq18OU59uNGRHwcAanNFCDWS5Y2aBp12IhAEy4TbRNGwsjkpW43qJVsGex9b79Y336uXvTWbUZamgB8488nt9SKzTfI/jGSyJySut/oPy8ZvddD9Z7k7SUoYk6OhOT4FSkBA+hlUXrJNGM4AwxELZEhNR5+Yv17SYtdT3/+/FyFUybxxuf8Y+slI4zxpwKpuFr1gJSwVNBFFu96nZgsjApR8vSOilDWniKBHFadscWS3jaWhKsn3XjNjLI9PddncAXyHJP2mk58EWEjjkdW4IS1PnRJtQN4Tm09WCxsJ4Sbj+QoYDhelv2zCf9s2qHj4Pbrik079mH+MqWYtGPHoZfeGJ8+fToKFiwIDw8PVK5cGbt366zZdQT5q4tP7r8RBiJaaqlo2g0JWo9fmceC6cw0aO+XN+DIfYRphhapblVJ3a8zJ8Wa1GOSJL4D8BffAPDRSqntDQl1GzrSvr0Pkx/ro6HNgxq/vMAAhlp8kx+AeoPte/oCQFeBPtVGvJJVu4tH0DOCfJQWhSLQUn5p6rUiiCwWOv5N3s7ri8qDpuwLAA15rbwE7lXa/RzE6fLANEoMGuPtKOJGMgVq0h9z5ly3rFIC1kI4VLHI1ZAuB0BamHy+WxK+JCFa2kRr3akXnkK9DO0aEak5VwpfKl+vp4AgWU1Cr1stiLTLokETDNRSRkGCJ1TV7Ef69cATXG3EGQ946a2uBt6bLyVD4+1f9b8m6dpRk8wQAOU5BYO0iFxmEqQe846E5rww2v4XYKeRs4zHjI4wA/oMftW4FxoaismTJ9s+h9UNCCB3N3AErPeTo7AUKGJljQoa6p07d0abNm1Ux2asK3IWZX6fO/cfxZDxv6J6Jdu5tnO/79Hm0/7sAJfqfj559hK6DRxl+1p+js10fqmN8WXLlqFfv34YMmQIjh8/jtq1a6N58+aIiBDtS6vCaESVRRnBOlMatRmtwdQ9vpXwItSiEQlH03WLZEDW7Et+3EALAMPwjHxfhnNErSyqpmgjcqYEwJ8IijYCfChppFrbwalhGbzuPkC9QWQDIaQq0Goy+7VZqcKdOWJmRhecLNRq5WoG35KyXbRSqD7bSVHcgJAQ79qs+DFQuL7+19cLTwX4zS/Yj7NqxbtvZ+/LMsaNRsZ5pSeNRjD2NaAhwVpYdV4LfHUN+Oqqdm2AZj9KLSz1OjJdPIFuW+klQh8S+skroYmg+eXljyMsaPMIABRtIo3LzceTHyeJ96kx6vg14lCvQOkSQSqJ08K+qfTHCjcEqhPKg2R4Ke68aC7PcFD3g9dC/W/J2ysaqHUXuc9Y1wjPADPqKGWRp5IkFEiCVF4jY7EAjYazX7veYN2nRRXcFHEI8jIzWJ83zVkDSMElVteSnMWB3GKlMvXe7Y5+w36yfyCjou+M62/47H9QoUo18oM5ixnTVmE5T5xdpbGPtb6kZRCq+OWXX7BgwQJt50bhwYMH6D3kR/y7YDICc1HW3bR1OmDj0Hn8JAYf9R2CP2eMRcmiqdkJrp5SCRsNrU50vOTG+MSJE9G1a1d069YNJUuWxOTJkxESEoIZM2Zof7Ga/5MWGSyqG5j82s5kP86L/rAiJawoBe8mM1QzZ6Tmxkla6GaVgJhSFEUN6zOpP4Tt1S9Ul29g0mB530l101phKVWz3jPvGqnShd4KMLQ2WXk+7fE32a/Ng3ffsGA533rul5wQopFCJR1XS04KGi4CJRw9KH3iH4ez92s8iv/aNHglLazJiTcW8OoPC9ajP+bswq7x9zSwkDAKS4CGlvUjAi893juHdhGh7tuB4gQNBTXqLgBKBkeyMySKNaE/1mwcuy1clS62eh1aqNqVbnC4ekrjMmtByHO6yZlcmU35D+mOrpoMB1e+N6SWoSzKvk9/7COOU4V1P4rMfzzD2EhgJCOCKqy05zQYYyCvpEokq45GKCcdvNtW4GuCYrXIeMDKaiv9Dt/JyoIlhMq7PnhOeta6khegYs1zbl7Gvisga0VzSbh5SynutM+FlwVjpDwDEP48/Pz84O/vb7uRFwSgkDNnTpw5fSrdeFbi6S8Ft1hOBkXgLLt/NpzZ9hferFoh/XEXirigjKgGmYKX1hhPSEjA0aNH0aSJ7eTfpEkT7Nu3z+758fHxiImJsfmx3XEUX0nWiGIh76JpNYn9ePQtxmM36Y/xBIyMqB+/bIOKFlhiU6xSA5EU46d3NJ8OAPpi8c1+QHMB4S5W9kXdQUDb2fTHWQOPkYVo57X0tH4hOJFNI3XQzcbRH+NFy1gZELz7wtVDMtipxy7LGKw5r82bOFnwBNhYURCemi8v7ZTlvACAtrPoj9HS8gF+uUtGYsQoaPCd485DJm8lsTH7HcZnrXPxA0CqU+dl8LDEwT5aQX/MyZluWIhEolhp5AXrOr5WXYQ8FdnjG8tR2C2MPxbQxvWiTfjldixjiOWskXH1BArrbG82jCDe1eeo1M6RWy6jk1zFpMyN/IyyFLXQmhIXd2CAWDsk8vEZ0UPed+XkRDYg81biH5fl7H5vvn5toLaz2WNRg+/YDhDeOGYo+mxgXesnddHo3O977Nx/FL/8thSWvJVgyVsJ4ZFSm91z586hRYsW8PHxQWBgIDp27IgHDx6k7V/v3e7oM2Qc+gwZB/+SdZCjdH0MHToUVkaWV0REBN5++234FH0T2YrXxvuff4N796XWwAtWbMSIESNw8uRJWCwWWCyWtAjzxIkTUbZsWXh7eyOkUmP0GvErnsU+px4HkATJZs2ahVatWsHLywsly1XE/iMnceV6BOq92x3eRWqiRutPcDU8Mm2fq1ev4u2330ZgYCB8fHxQtWpVbNmSmj1occKFK9fhVbgmlqzekLbPqvVb4VGoOk6fljpHqdPU69Wrh77fjEC/YT8he6m6CCzfCLMXr0Ts8xfoMngifH19UbhwYWzYkP6aycnJ6Nq1KwoWLAjPbAEoXucd/DJXJQRscYLyGqhXrx7+97//4euvv0ZAQACCgoIwfIRtRpwlbyX8vZGTwaek3W/iz03lpTXGHzx4gOTkZAQG2kYpAwMDcfeuvdjG2LFj4efnl/YTEqJoPRNcQeygGWl88gz9Q4wFUnZG1MnFHRh4hf64EXGuApyoJi1amtXkr8FJKWNMbiL1TEaitSREa65ZC8r6g6VoGg31+5KzQPJWEUu3NSImxIKXZkwT8ZNhGURGnASF6urfF2AvRBsPpz/GqksUgZWazzO0vALoURheWQkrKvmBQLs32qLvransCHFugRS4lhP4z9ELb4ykYbTsJCsxqlBOcwrxxEZPLydvj7qg/1wGXAQ+WcOeL3ilSd0JraiU0O6pz3awVbaNQrsnRWt2SffNB0vENT5ILbpEIBmfnv5A961A7f7sfVkiq/mqsp2kVbqwux/w+tBraQOlhiZQCWRsR4D8lNRmUT5cTl5j8q5r3yBgwAWy2KnVCiS8ABJi2T+JL8g/vP1o+8rHZuGdE/DJjV9GDkSNyuXQ/aO2uHN8M+4c34yQPIG4c+8+6tatiwoVKuDIkSPYuHEj7t27h/ffT81SSRVVXPjXWrg4O+Pgv79jypihmDRpEubOJeuXWK1WtGnTBo8ePcLOlXMQtnQ6rt6IRPuegwAA7bv0xIABA1C6dGncuXMHd+7cQfv27QEATk5OmDJlCs6cOYOFCxdi245d+Hq0SkzQw34NNWrUKHTq1AknTpxAiRIl8WGfofj8mx8wuE8XHNkgCbH2GZoeQHr27BlatGiBLVu24Pjx42jatClat24tlRRbLChRpCB+/q4fen07Fjdu3sbtu/fR/avRGDe4L8qWpWcFL/z9d+QMyI5Daxehb5cP0HPwWLz3+deoWaMGjh07hqZNm6Jjx454/lxyMKSkpCBPnjxYvnw5zp07h6Fffo7BY6dh+ZrNzK914cKF8Pb2xsGDBzF+/HiMHDkSYbsO0Hfg2VU6giYOUFLIWNSy8Var1V5KHsDgwYPRv3/6QB0TE5NukBtt4WCUsu+xlRIBSURrOaU1ETfthtGuRq8xnqMIv11H6TZAwevAqs+k/pha6XsMmErw3rJqfkTgLTZYnmYRgb5cxbSdDxfButfKXYD1A+2301RLlag/k2ZjpHox0ZSswg2krIG8lYFn94EDBsRyHEWBN9k1b0aF4bxzAbH3DeyfG4gl9FpnlROwVGRFFIp77gWGE9K6v73N3xeQVOhPr5BSDMdrGDdZ91yJFuKvoyYxTv++ADD0vvG0QxZVPgVuUEoOMpKgssDd05l/XEBKz988RP/+Il0leHy8Clj8jvT3fcFuJJ/8CyxUZT7x5mWA75jjZRZ98i8wwp9/HBIdV5NbXYlAWzeIRhWrdgPWqbRsRDpcyAQUBh5dFX8+C2EHws/AvTNABEG0r5uAGCnN8A3gZFUapUw7YCVFoV70+3p3HrCCItzIovYAYLdOh2WxpkD7P4AlKiFhkRpli4XsIE6KA37iKIdnFN/e5qfIe+eCX7YouLm5wsvDA0G5053FM35fgUqVKmHMmDFp2+bNm4eQkBBcunQJxYoVA5xcEJInEJNGDITFYkHxIqE4feMBJk2ahO7d7Z1JW7ZswalTp3D9+nWEeCcCcdFYNGU0Std/F4fPR6Jqw4rw8fGBi4sLgoJsx7N+/fql/V2wYEGMGjYEPfv2w/SxqVlwOYsTlfq7dOmS5kD45ptvUKNGDXzXryua1pMyR77o9iG69B+e9vzy5cujfPl0kcLRo0dj9erVWLNmDfr06QPkKoleXT/G+h370fF/38HN1RWVy5XEF90oehmK1x3arxsAYHDfLhj363zkzO6P7p/3ACxOGDZsGGbMmIFTp06hevXqcHV1xahR6aV8BT/uiH0Hj2L5v2F4/60mVCHRcuXK4fvvpaybokWLYtq0adh6+AIa1yEEwLwCxLob/e848FMF/vNSeWkj4zlz5oSzs7NdFDwqKsouWg4A7u7uyJYtm81PGikOEDFjeVR5FBdYjLJEmUT6k9PqkXl1ojS6bODUkKbiFWBfO/nOHLFj0HreFjMggAXwMxxYEVNR1V8SIgsGUs9GUREzUsnBx6uA9wUyFEgpj1qMFGcXqTVVrS8d7NzSKcA18DLQZT07auoI1VY17hrql3sRFoRvfMbeh6XubkQJVvQa8woAqn2m3bPriM+alHIewyjREUHkGjfS2125mHT3k2qAAWPKziIYfX2RtlfUff2NHTsuhv8cHjxxRhIF6xh/DT1YLPaONNHaedkJqgejkXGj0MoCu+mImGspnzDihKU540UMeSNYLPS1muh755US0Wg4zPb/NjOBL07qey1AEsDNxylLksnqtqp6YNw/R0+dx/bt2+Hj45P2U6KElL119WqqY8rijOqVytoEFWvUqIHLly8jOdneVjl//jxCQkKk4GJqlmypYoXg7+eL87eeME91+/btaNy4MfLmzQtfX1906tYDDx8/Qezz1EwASsu8cuXSsz9le6tsiXSx08CcAYiLi08rB46NjcXXX3+NUqVKwd/fHz4+Prhw4UK62LarBxBYGvMWL8ep81dw7MwFLJg0ghhYtTuPVDFRZ2dn5Mjuh7Ili6Q5qORzi4pKD3osXLgQdevWRcGCBRFUvDIWrdqAiKhoyYFNWfsr3y8ABAcHI+rxUyAHQeDVv4BY0E5jO+KXNjLu5uaGypUrIywsDG3bpnuGw8LC8PbbDHEREsIDOePCEKl/qtwZOLrAfrvIIprl/RSp+6b1INTTn7L+EDFDXEb5+baaBJRjCMcoIU2aXjnYyrkyvnmAp5RoH6/+j3U9GKnJFXH69DoIxMcAU6sACU+lbVoUxS3O6Qr5wx7rEyAzSvkOwJF59B70WtDb91jk+jRadkK6J/tpWKSoFxpB5aR7i0W594GTS4FrhPqkKl3Ej53Z8GrCRajazT7zIyP6l6qp3gPYqLMnuPIaaTlBWhDXGwRkL6DtdfzzA08igE/Z6XRpGDUkWYrCPEgt3ViqzWoc0fvbEa8hMs/IWJyMCRmpVft5KtaOgHbvZFbvdZLRkqcSkE+HRomWccDI90QSVgwsa2xdIMoHf5CzmgplcveMChQVdBrqsW6AYKYKQDbGXTyAQZH86/QOZS4O1tBGzmoF7p6S/nbPJliOR19XpLh6onXr1vjxR3sHb3Bwasans6vtcTh6KzbZwIo1DS1LWObGjRto0aIFevTogVGjRiEgIAB7toeha48+SExMYh7T1TX9fpOP4eriYrctJUW617766its2rQJP//8M4oUKQJPT0+8++67SEiwbed78uRJxD5/AScnC+7ef4A8QYysXvk8XDyk+e7eGVgsFuZ5rFq1Cr169cKMGTNQo0YN+Pr6YvTo0dizZw/TiaJ8v/LrpqSkSAKuJINcBI2dXl5aYxwA+vfvj44dO6JKlSqoUaMGZs+ejYiICPTooVF5WnQgL9pY/6IMABoMIxvjPDVMFrR2LWpIhkOlT/QdU6sRo7zIC3BqfJWQBuIBl8ScD30OAWMJdfhFm9B77PL4/om+/dIQuPncvKQf5Wd875z4IdrMAFanRlezwhAHpAGKFPXloUxb7LpFeh1aC6WXAtV94JVDm2iX2tn04XJ+VNFikVoaqY3xT9aKO8gCCgGPFOq6bXR0n5BOBsKZC57ZpZYwUQZaFpHGHZEoF60cIDNQjrvB5aV7UtQQz10KiDoHFKoHdPpH0gsQdRwbbZ9jxFGl/E588wAtfhJTcZfRG5kt+3563bgj2geVay/+3IFXyKmzfY6K7a/+vLVEelN0GpdZHXUkGVO8LgLU19JwzZAWwaJicgVqSnoqyjIsI1mRRqnWU+okIEr+mkCEvcCxMLRsRRZGtFlIaz2LRWoFxxVKpZRhaG2XKr+Oq6fYuJj6HDdXVyQr7013X1SqXBUrV65EaGgoXFzo1+yBowpHgpMzDhw4gKJFi8LZ2f6eKVWqFCIiIhAZGZlWenvu0jVExzxDyZLS+snNzc0uqn7kyBEkJSVhwoQJcEpdKy5f8jv//elg9+7d6Ny5c1rg9NmzZwgPD7d5zqNHj9C5c2cM6dcDd+/ewUd9huDY4YMQkggUHC+3b9+OGjVqoFOnTmnbzp41sCYB2B1VWGh0Cr60aeoA0L59e0yePBkjR45EhQoVsGvXLqxfvx4FCmiMOogqiucoTE4fY6WOKqEJaIkYTSSP3PBooJpAnSiQnh4JSEbloAjgLUabGRlSuqPWFEblRKnF604a+ES/K1rfzgJv6vf8Z5V6/PMH4s8t3UbyEpZn19owyQglZxGU2RuZbYgXqi/11gXYYjlK7BbQGtMf1Ythngha+oHtN2nJcFGXQugV35O/H1EBIeWklTtVrV6vQ1BGxKDosFSwNRGDmv/Tt1/B1HpiFw/tWhIfrZDuxXap2hxaDDSjY5XcSrGgoh669S/k56pRfidd1rFFr0iQovI99vD3q69Q+1e+/xCGsKWaN/uRX4OHdw7JaaJGtNe8EedBCjuKRYWmeq4lYsPrwMBCLUz6xmdAk9Fi+6prjrU4npWOSEDKRvuQIv5HolIn2/9ZmjxqBt+SHGuOovk4beuZjqukNHOWqC8LPeK0RgTmSON7ULmXv5NPzmIIDQnGweNnEB55Gw8ePUaKTzB69+6NR48eoUOHDjh06BCuXbuGzZs349NPP7UxliMjI9F/+ARcvBKOpSvXYOrUqfjiC3IbuUaNGqFcuXL46KOPcOzYMRyKeIFO/Uehbt26qFJFusdDQ0Nx/fp1nDhxAg8ePEB8fDwKFy6MpKQkTJ06FdeuXcOiRYswc+58/e+ZIUJdpEgRrFq1CidOnMDJkyfx4YcfpkWrZXr06IGQkBAM7d8TE4f3h9UKDBwygvKKpOOnaoAxslQKFy6MQ4cOYdOmTbh06RKGDBmCY8eOiR/DkWjsRPBSG+MA0KtXL4SHhyM+/v/snXV4FEcfx78XTwgx3N21aHHXosWdYi3FKUUKLVooUqRF2tK3uLW4Ftfi7k5IIO5ud/f+cdxl725lZvckIfN5nj4lezu7c3uzM/PzVNy6dQtNmzaVbmQKzUKo/8G5fCGzrjQA5CMUOJROPrnyADNDdYK4SkWWQAPQ1XucGWpcFktI0BWCu4mk3XRI1ZukRZ8VUwrTWtByNMKWQipLKxcnV93GtbsMa2f5DrpavXJjy+Qy5LDOCtWR4+VBY+nos015H/KU0Qltw0+Kl/DiYjoX0Fr0uO80Se1xPYVMNkQVO+ncO0kxDZeQm0Sp73ZdOb1R58jOrzsi89/9d+nmIhKFoBgktbaL1tFl5lUikH/6tbx2rp7ArDDgOxnlDr2LAE2niFdBsBYNxuq8U7hCCkluEsD4PRAKjxLDNAlY3gq6eD4pchfO/LdL7sy1hsYqL1ewBXRurHIRK08qhdw+e/jpKouYUkKkfJcpVbqTK2lMMY1F7riUIt+AkvJTJkJD/op0ii4lewFXT3OlTbuFvKfy0mFp5r9Jcg2Z4uyuczOnUSAAwMA9Oqu6WDlQIZSUz+XzWlUSRkGSkFGIVIpcFi65MGX8WDg6OKBy857IV60VAoLDUbhwYfz3339Qq9Vo164dqlatigkTJsDb29tgnQaAwYMHIzklFfU6DcaYaXMxbtw4jBrFn09GpVJh//798PX1RdOmTdG6bXuULlseu3btMpzTo0cPtG/fHi1atEC+fPmwY8cO1KxZE8uXL8fixYtRtWpVbNu2DYsWfiil6ORKNudyEbEQr1ixAr6+vmjYsCE6d+6Mdu3aoVatzD3L5s2bcfToUWzZsgVOzk7wcHfHttUL8Oeff+LoUUL5KldenfJGxLgwevRo9OjRA3369EH9+vURHR2Nr7+WubYrxdEZ+IrcSyVLu6lbBI98QNOp8tuPvqys9qpcl2k5OMuMA3Q2KWBPG0/InVBplQpd1wB3ttK14bY9MMb4WNXPydp+cQRYz3Fd67JaXh+40CgiuNYJWgWGXMVN3226sh62LqtUqonuv7TEzGM0gi1NBl9Thh7Vuba2+kG3ABUj9HIBgM//AH6pmfm3qZBMA43LEtcdfdR5oHBNwVN5yV8Z8L+Y+beppYgUv1JAT4p6mdV66X5jDz/+RIVyIHUlVqmAifeB7X344+2l4BuPpLFiSrP2y6XzKuAQvzVFEgcH8zh/Uoup0vAY080U6Xzm7AZMeqzbrDs66bLVvrkI1OhLfm9FyVxlJpsEgBv8ZYvIbmvSZ5qEbtx8NS2/BxIjdFU5aKjRX1emjM8zQAyvwkC7RcDxGeTGAQOcZ12DMoa5/y5gcUnK+3GwhFV28EFdLHKN/nTKtvqjgGMfPLeU5HWgpWxr8Sof1sJUkKdRWvOhtBIPBeVrN8WVQx+S5+YpZxBWy5Urh71794q2dXZ2xsrF32PdT9/p3hOTZF+mLt7FixfHgQPCHheurq7YvXu32fFJkyZh0qRJRscGDR5sdh4X03rnJUuWzDwWdAcA0LxhPaPzSpYsiTNnjBMzjhmTuTcfPHhwput4XBCQloja1SsjNTWzsoa+Nrqec+fOmfXN9LmY9tfV1RUbNmzAhg3GHgCLFi2ius/+/fuN7xF0z3weJsGXfB/08Qvj428D3rQLwQda/SA/xsmAggXclnBLd9C6tXI1mZRJCxTxycBMYfyTgbrY/HwVyNpyXegKVtOV6KDB1RtIjTU+ZureJkbjicCZ+ZKnWRQHR/vWN+a6edNkmjTdHHX/nbxtyUa6/+RgmjVeroUIAPU8MPigLqEXrSAO6JLAXec8IxdKTxe5qFSWTzJHm0W562pgxYc5uxdBlQE9fNaYL8+Tt7cHtYcCt7cA72/a9r5Ks3GbCfMUwo83x3rvW5I+XvWTAcC1dXSu7XpM17bxd8jbqhVY5BuOB16f0yUmbTNXl82XlBbfAU8P6+Kgm/KUxSTByUVX8lAO9UbplIs01nhT+Oqdi+HuqwsB2dZT/j2VUrqZdEk8Keyl5LMlpi7utBZ9o7YUSYctgZEiQca+N39FIDVBeXUKe5BbwbP2LKBbb2kq09gbl1x0nhMy+PiFcVotJ9ftTkksjB5LlFWzBdwMp7SuPg4KJyU9chLdtV0ABFwFOq2kjLnk/Lb9/6YfJ3zn01i4G0/OFMZtqM21K45OwKRHOrdLOVn+AV04RQ2KxEtK4SYlI3GZFoI2w6+ijZzJ2KxnXrv0o4U7F/G56Aq2M5nr58Tyn5fVaDkL2NJNeWw+DYU/0f2f6zauhDYUcYNKKVhNVxZRSWk3PTQu+o5OQPqHf/fdQXefsq2Ab57pEhXSeiUUqALMCqcrY2lJHJ2AajKE4s+W6+puN5lCn5AL0OWO8SsjT5lJbcW3ErYqQWdJitWnO5/7HXPllf9e5i0vb5xYCjnes44utsnSb0nylgdSYoFcdGW7jHBwpC77ZXeUeEcTkg3fditTrk3mvy2RsZXUUpsV6PwLkBAGFKQsm8NNVKBkgyYn3qfhOLoSNXq4mxo5vzNXa124FhB0my6pmoODLk4r2h8oQhEPnN0RSQJChK2tBbT5E4RQUm6HFlNFhz3zIdga7uaO5r22hOLVHpRpAUzzB9x8bHdP19y6RFWWyNbdYCy9V5JSbG1BA4zHJW3ZO0BZLKy9BHElVOupU0LQVK/g4uKh84qU46nn4Khz5b+lINmVJbCBAGAxhh4BLv9KXv1HD1cJmis/nVEkX8UPgmE+25XrMyVveZ1xgSKkgM8tOtvgksu+Sg97kbuwzrvJisoTJoybwp0MLCGM08T9DD4IbJaokW1Nasu0rjg46jaEWq28uPV2i4DrfwCtZsu7vxziOAmX5AhKjSdnlsEbfgJICKUXNO0Ro5VdqTMceHeDLlmTJVCS8ImLLYVx0yz1tow9tDdGczbFRjw7WqH0yBVYzKB4XnLLvZhi6/dZCVyl8/BTdG2TIjP/nZFimf587FhiXMuN/y7R0P7COE1tdXtTsrHuP1ryEFYj4MPZnTpjtShyEjTmRME0J+LoBOSRkayUgmy8A7EBcjST3FrKAN1kU7qZrgSTnARE9kbJwtnga91/tkTpZpIb2+TorNziyxCn03L73DdfBdvH5FqC4SeB/33w8slOFhZLQqMAyc7CuFIqdwNCHhiXObM2Ex8CkS/lbeDtReu5QOhjoN4I8+R3UlTtATzco/t3dvXCyElU7QlkpAJFKX9nS2Kas+RjpMrnQEyYfbxV9PiUAJKj5HmsMBgWIgfvQAgoUlv6HFNGns7M5Nn9dyA3ZWxEzf46YbwApas4gw5u4h85rmxyxgYj+9F2gS6hYU3KjL56Gk8CLq3QeX/YknwVdf93cMr6NVuFmPSIvo2bjy6Tu0ZN557PdXO0dLnFrE7vTYBGozxLOg0+xXT/ZSe8iwBfk5eqMaLOsExhnJH1cXAAag2yz70H7gFenjEuFfmx4uAA1B0GvHljlsXbZnj4Zb/YbUaWwVLjlgnjfIy9pYvlLVqHvq27LzDlJZAYJi8Te7VeOut6doo1z4n4lgRGXzEuHcP4+PDwAz5bJr99q9k6F3tbCx5uXsDUN5aJ67UHzrnkeZs4OADj7gDQ0sURchUW2aQAhkWxpSCeE+FWksiO2ZMZtsNeZcbshKOjbp5OS0uDu7sF3c4ZDBuQlJQEQFeuTglMGOcjb1ndf3LxzCe/RINKZZzZnJF1KVDZ3j1gZHVUKvtZAHOqtt+0di01OVEaZ1gVrhsubTk2BuMjxsnJCR4eHggPD4ezszMcmGKQkQ3QarVISkpCWFgYfHx8DEoluTBhnMFgm28GI2thT9f6nFTdgGEbfEsAn6+3bdZ7BiMboFKpUKhQIbx58wZv3761d3cYDCp8fHxQsKCCahcfYMI4g8FgMLIW9hRaWIIthjWo3tvePWAwsiQuLi4oV64c0tLS7N0VBoMYZ2dnxRZxPUwYZ+RMuNmTs2tcLYPxsTFgD3BqDtBtjR07wTxlGAwGw5Y4ODjAzS0HleFkMDgwYZyRM3HJBbSYCajT7FtWg8FgZFKute4/e+KdzbJ8MxgMBoPByLYwYZyRc2k21d49YDAYWYWBe3X1tnNQJmMGg8FgMBj2hQnjDAaDwWCUbaX7j8FgMBgMBsNGfLTCuL4Qe1xcnJ17wmAwGAwGg8FgMBiMnIBe/tTLo2J8tMJ4ZGQkAKBYMRb/x2AwGAwGg8FgMBgM2xEZGQlvb2/Rcz5aYdzPzw8AEBAQIPkQPibq1q2LGzdu2Lsb2YK4uDgUK1YMgYGB8PLysnd3sg1sjJHDxhg9bHyRw8aXPNgYI4eNMXrY+CKHjS95sDFGjr3GWGxsLIoXL26QR8X4aIVxBwcHAIC3t3eOesEdHR1z1Pe1BF5eXuyZUcDGGD1sjJHDxhc9bHzRwcYYPWyMkcPGFz1sfNHBxhg99hpjenlU9Bwb9INhQ8aMGWPvLjA+ctgYY1gTNr4Y1oaNMYY1YeOLYW3YGPu4UGlJIsuzIXFxcfD29kZsbCzTHjF4YWOEYW3YGGNYEza+GNaGjTGGNWHji2Ft7DXGaO770VrGXV1dMXv2bLi6utq7K4wsChsjDGvDxhjDmrDxxbA2bIwxrAkbXwxrY68xRnPfj9YyzmAwGAwGg8FgMBgMRlblo7WMMxgMBoPBYDAYDAaDkVVhwjiDwWAwGAwGg8FgMBg2hgnjDAaDwWAwGAwGg8Fg2BgmjDMYDAaDwWAwGAwGg2FjmDDOYDAYDAaDwWAwGAyGjXGydweshUajQVBQEHLnzg2VSmXv7jAYDAaDwWAwGAwG4yNHq9UiPj4ehQsXhoODuO37oxXGg4KCUKxYMXt3g8FgMBgMBoPBYDAYOYzAwEAULVpU9JyPVhjPnTs3AN1D8PLysnNvGAwGg8FgMBgMBoNhSlRyFM4GnkWnMp3g6uhq7+4oJi4uDsWKFTPIo2J8tMK43jXdy8uLCeMMBoPBYHzkaLVa7Hu5D2V9yqJ6vur27g6DYVG0Wi3i0+Ph5SJvT6vValnYZg5ArVHjwrsLqJ6vOvK457F3d4hptK8RAOB6zHWsa73Ozr2xHCTvHEvgxmAwGHZCq9Xix6s/YvuT7fbuCoOR7bkSdAWzL8/GgKMDsPfFXmi0Gnt3yWYExgciTZ1m724wrMi8q/PQaEcj3Ai5Qd02Li0O7fe0x8JrC63QM+sRlBCEv5/9jVR1quxrZGgy8Dburay2MSkx2Pl0J2JSYqjaqTVq7H2xF69jX8u6r1zS1Gmou60uxp8dj+Z/N0e6Jt2m97cEl95fojr/Xfw7RKVEWak3wux7sQ8//PcD1Bq14msxYTwb8SD8ASKSI+zdDVlcC76Gln+3xNmAsza5X7o6HVqtFgCQlJ5k+LetUbI5WnN3DaptqpZtf3MaNFoNltxYglEnRiE5I9ne3bEZt8NuY+eznVh0fZG9u8JgWJyfb/6Mqeen2mz+5W58Z1+ejS2Pt1BfQ61RI0OTYcluWZ0bITfQcW9HDDw60N5dyTYkpCWg2qZqmHtlrs3vfT/8vqx1fffz3QCAYceHUbfd92IfghKDsOPpDuq2gO69OPTqEALjAmW1B4CI5AjcDr1NNR+029MO86/Ox8CjA/Ek8oms+048OxGd9nXCsTfHqNqFJoaiya4m+PHaj/jm/DdUbfe/3I/Zl2ej6/6uVO30yN071t5a20gAH3d6HHHbWZdmodehXkhXyxPgMzQZ+On6T/jn+T/UbeWuEWFJYeiwtwOa7WqGf57/YxHBmJQfLv+AfS/3YcmNJXif8F7ROpejhXGtVovwpHCb33fr462otqkaLry7QNzmUeQj9D/aHy3+boFqm6ohLi2OWusfnhSOHU934LO9n+F9wnvidkqf0+RzkzHixAiEJ4dj/NnxVG3DksLQeV9nbHq0ibhNaGIo6m6ri+kXp+N59HPU314f1TfTuywmpSfhQfgD2S/Ycf/jqL21Nv588Cd127dxb/Hbvd8AQPZkroQDLw/gXOA5m91v7pW52PJ4C64EX8E/z+gn8uxKYnqi3e4dkRwhe2w/inyEOZfnUG8o1Ro1hhwbglmXZsm6r71Yfms5ehzsgaT0JACgXvCfRD7BnMtzEJYUJuv+6ep0HHtzjOp5Z2gysOjaIpwOOA21Ro3I5Eiqe2q1WpwJOGP4znLY+Ggjjvkfw7PoZ7KvQYOpO+Cym8uo2mu1WnQ/2B2f7f0sWwnkh14dAgA8iaIXVv71/xejToxCdEo0ddttT7bJWt+4xKfF20UBqxdo9QKurbgXfg8Djg5Ai79bKLpOtU3VqAQt7n5RP15ImXZhGmpuqYnvLn2Hjvs6UrUFdHupAy8PoMXfLTDk3yG4+P4i9TWeRj1F78O9EZQQRNUuMT0R59+dBwAq5Zx/rD9a725t+Pt6yHXitkdfH8WcK3OIzzflefRz1N5aG/OuzJN9DT3/Bf1HfO6BVwfwNOopam2thfi0eKr7ZGgy8MmWT7DtyTbMuzKPam/hH+uPX+78QnU/PXfC7hj+Pe/KPCy4tkDWdeZdmYdqm6ohIC6Auu32p9vRfk97rLsn37U+Rwvjv975FS3/aUk9MQG6zdHpt6fhH+tP3XbxjcUAgDGnxxC3uRVyy+jvRjsaYcCRAcQDfu+LvWj5T0ssvLYQAfEB+Pnmz8T3Xn13NVr+0xL/PP8Hl4MuUw3WNHUaTr49SXy+Kb/e+RX+cf5Um6rdL3ZDrVXj6JujsjTIeupvr4/+R/vjyJsj1G3T1GmYcn4KAGDV7VXU7Tvt62T4d1xaHHG7xPREbHq0Ce/i3+G/9//Jmljexb/DrP9mYdwZ8oUeAEISQ1BtUzVMOT+FeiO798Vew79jUmOo2toTrVarTBuqkjcFp6pTFQlJ+17sQ4u/W1ALKwAQmxqLvof7Ys+LPZh7mc6q9CDiAW6H3caBVweo72sp5PxeGx5uwPPo55h0bhJW31mNBjsa4HUMufth78O9sefFHtlKiBW3V2Dqhanofag3cZtDrw5h+9PtmHh2IkaeHInmfzfHw4iHxO277O+CCWcnoP72+lTKWz3VNlUz/PvIa7o59E3sG8SmxlLfUwVl8bCPIx/jTewbBCUG4Xn0c6q2tG6sliIgLsBoD0P7rL89/y2uBF/B9IvTqZRMGq0GP13/Catur8KNkBtYcHUBAuPprKZJ6UlouKMh6m2rh6dRT4nbpWSkYNOjTeiyvwsOvjpIdU+NVoOolChZigs9GZoMBMYF4tTbU8RuwBqtBs+inuGrk1/Jumffw33Njp17d47IWqzWqLH+wXrD399d+o7q3kffHKU6n4tGq0H97fUx67/Mue9MwBmitnzCM+l7maHJQEJagtEa5R/nT9QWALod6EZ8rinTLk4z+vta8DWq9j0O9gAA/PP8H7vNK/OvzieeD7RaLZbeWGp0rP2e9kRtI5Mj0Xl/ZzOl3s6nO4namxpvdj/fjeW3lhO11aPVag3W/M/2fUbVlgsTxmWg1WoNk9P8q/OJ28WlxeHCuwuotbUWJp6biM77O1PdV66LD1+8zMPIh0jKINuQ/3T9J6O/aVxg/rj/BwCd5ujLk19SDValMXv7X+43/JtmYtDDtTzSuGc9i8q05My4OIPaSmw6sZBaxB5FPsLEsxOp7sXl55s/Y9nNZeiwtwO+OvWVrImFayEhFVw0Wg3a7G4DQOcR0HZ3W+r76lFrbedmpITTAadRfXN11N9eH9uebJO1aMoVHupsrYP62+tj06NN6He4H9W974Xfww+XfwAAbH68mdq6veTGEsO/38S9oWrLVdKkZKRQtdWj1WqpFRH3w++j96HeqL2lNqpvro7/PfifrHtfDrqM3+//juSMZFlKtivBV6jnxMvvLxs2peHJ5B5K3N9VH2NKagXUaDVGG1fSjZUQGx9tJDpPq9Vi2oVp6LK/CxrvbIwam2vg8vvLiu699fFW4nP7HskUePoc7kOsSD746qDOnfXqj9T906Mf0/fD7+NNLNl7FZYUhs/2fYYMbeZ7Nf3idFn3vxx0mUp5feBlpkJt2PFh2PVsFzrupbOacsMKeh3qRdxu8LHBWHZzGd7EvsHMSzPxIPwBcdsam2ug2a5mRsdoFN4A8MmWT9BxX0dMOjcJGx5uIGoz/cJ09DzUEwnpCYZj255sI/ZIeBT5iPc4iQVzz4s9ZufJdUUGQKVs1+8fuUSlREnuLdLV6UZrjZ7Drw8T3bf7ge5osKMBjvlnuqaTWnu1Wq1F9yGPIx8Tn7v6zmqjv2kFS0tx7M0x1NxSk2itPRN4BtufGue9CUoMInreQt6yP14jm0uvhZgrOkjfSUD3W9MoAq1FjhTGA+ICjNyWaVykGu1oZGbRpnE1lePiA0DQhYN0M296nha2ieHj23iefnuaqG1wQrDR36RuXdzvxl00Fl5bSOzJYKoJprUSm7o0kcY69T/SH6cDyJ4PH3yxOrSbf+7CQar1vx9+3+jv8ORwVNtUDctuSFteTe+RXWLk9UqT5Ixk/HT9J3x74Vvqa8jxAuAm71l2cxkeRj5Ek11NiNqGJIaYxZXSukty8z68jXsrO0FN3W11qa3U0SnRBgVIm91tMPfKXEkl3d4XezHg6AA8iXqCNI1OCbny9kpZfeZyJpDMunM1+KrR38tvkm+uNFoNvjz1JVW/9Mj1ugCAE/4nZLdVwvl3543mXtrvz/ed9Z5ociBNdjXz0kwAwM5nOxGfFk89ri+9v4T62+tj6oWpGHB0ALrs70LUjmaTT8LtsNsYcGSAkeunEHqFnhzuhd/DmrtrzJTcpJZAU6v2hfdkIX9CvwuNu7fpNUhD6LhCoZ6frv+EpruaEt9bLnx7ClJDzq6nu8yO0YSdrLm7xuzY2cCzRpZyPrgKJi4vol8Q3VfICi61HwpPCkfDHQ2J7kEKqTEnMT0Rv9//3ehYSGKIRftCy+cHP5c8Z+r5qbzHSdYR072jLXkW9QzVN1dH78PkHmd6LP275EhhnM9aSOvaxeXT7Z8SWZr5No2bHm1S5G5K6hZGOvGSYiooC8E3oU48N5GoramGPzo1GpeDpK0kYhuhzvs7Ewmnfz38y+xYQloCz5nGpKpTMePiDNwKNQ4r2PSYbMEW6huJJlpIu0ebPZUbc0M6voT6t+nxJskYL9Pf6+Crgxh+fDixEuHfN//i1NtTeBTxCAFxAVh1exW1AiJdk47bobcVWQtMhS4pIpIjjMY4qRJGSTZcod+TRgEUn26s7abJaWAqPJBs+iOTIzHixAhsfrTZaOMakhiC3c9342SAuPVy9uXZvMeX31pOJDTJcZfmMvLESKO/SecCALwZYkn74+RgXrmUVPGsRFmh1qjx651fzY6TPOvgRLJ1RYjj/sdlt+ULOyBVDDqpMp91wx0N0WFvB+L7RqdEG5KIcRNMbXm8BdeDxeNUlYTIJKQlYMTxEWbH70fcx+Bjg2Vfl4SBRwfit3u/mQke867Mk8wrw+em/Nu934jCDYXG/+2w25JtAeBu2F20/Kel0TESq7qc7OeWIiwpjHffNOPiDKL2fDG4fQ/3VZwoSyq8IC6V/7k6Ojgquq+Y8KfRajDo2CAj7wVLcDvsNpEnGN8+6krwFeK8DP2P9Kfum57F1/mVliQhSnoltykaKPOMlQqzVJopvuehnrzHSfISCBnoboeSzSWm5EhhnA+5rl16XsRIa+v43OGX3VyGr09/Lfu+QoNJigvvLihayNvuaUtUKkLJhM23QH558kvJfktZ/eW6H5HETU2/MJ3XjUrpYkziEvvlSX4L0q5n5pptPtQaNeptq2d0jDRuSiwhi5TwwPd7XQ+5jm4Hukl6nbyKeYVvL3yLSecmoe+Rvvhs32f488GfZt9DiFNvT+Hk25MYfnw4hvw7BFPOTyFSrAklw3oY8ZBogXgW9czMIk0anvAy5iXvcRKLwf8e8rtnTzw7kUgRIbTxJImf1mq1WHrTOK5s38t9ku1+ufMLrgVfM2urJzZFnrC84eEG3Au/J3neN+fosuhaEj6PmsY7GxN5Y/Ft/khjP/k2YNU2VSPy8Pnm/De8rqkkCrK7YXd5j5OWurkZepPoPFOCE4LR9QC/UolEWW666SSNsQ9PCkfTXU15rSxLbizB8BPDRdsLrXUkGcK3PN7C6+JJgljcrtwSUnqkFHRCLulScdApGSlo9U8r2f0CdHl+5HhuKcldoxSh7ywniRqXtffWSp6jJExRyJrsoFBsERO0j705JvruKkm4SpKnSWhvu+r2KsnSXeFJ4XgQQR6uwSVVnYqtT8jDeUhRWkXjbKB49SWxvRppOAMfJMZZIePXkH+HyCqzluOEcbGNsjXdQTRaDfa82MP7makV1VaQLCpiQmSnfZ1E4/nUGrWgJrrB9gbEcXGmSCUhktIiylUQzL86X3JxORVwSta1pZByhbsSdEVxncVVt1fx/l4k7wWfJwEp/73nz/b5JvaNZKypkABKUpM0KT0Jk85NwuRzkw0bwDOBZ1B3W13JtkKWw35H+hFlQBWyPNHEPpry+cHPJfMiCD1rAEYJfoRotKMR7/GuB7pKvs/t9rQzO7b/5X5JNzVrJrAhsTLLFVgA4FEEf5wnKUKK2vOB5yXbrr67WvIcWiadmyR5jpCXBUnCUiFlwehToyXbiiFlNZ3530zBzzY/3ix5fb51Yd8LaUUTbT1dU4SqnJDkBtj2dJuse94Lv2dIMMWHtat/yLWM3g69rdjiaWkPQ1LEhBoh5ay178uncONy9PVRfLr9U9n3LuFdgvc4yb5VTBCbcGaC4HsjZdWU8krb92KfYO6Dnc+kE5KJ7Vuk9q1i40BKiSB1bTEPHTGZSspAIBWyJbWPE/MYJfX84ENuZnc96+9L76VMyVHCeEBcgGgiGn3cFx/Xg69j6L9DZd9biRs8bVZXU4QmHtOkbnxIaXTHnBHeYI07M453Aw7otJNCWUWT0pNELcH9j/ZXVI5EqtakmMAtN+kUCWITJp/LKZdRJ0cpundCWgI2POJPeqE0psfdyV30czHXUn15Nz4eRjwk0s4LIaQo0mg1khpdbmJBms/0CG3qtjyhr4vMRYkLu5QHhVTtUCnvDyEX5JmXZoou6Kblqmg+p03MZGm4CcG4tPqnleQYE3OVk1M/W4/cOsOAzuIrpsAQU9z9F/SfopAsKcQEbimrqdimT07JL4AsplrJbxGZHCm7jA8gP/xCKv5VrVWLGhiUKNc0Wg2+/+97WW2lPOZIrLhC5yjNc/Lf+/8E9xZqjRp9DvcRbLvo+iLZuQNMM2CbIhS3TcK0i9Nkl6zb+HCjWXiPnsiUSJzwP4H199cLzqFigliaJk0wOZhUno2Drw6KCpg/XP5BUTIwbik1U1r+01LQey0uLU7Uu/fT7Z/iu4vfCeZ3iUwRL3sZEC/sLi62FxdTQKg1asE9px4pL0N7loYVQ864z1HCeP+j/UWzWovVERx+YrgiC7aUFlEMJfFbsamxZjFOek68FU+uQGJdFNNMSblBBSXybzbX3l0rad0mccMTQqqkidjvTKLdlIvY5tvZwVnRtaXGrlgcv1SCriHHhoh+LhUWQFNuiUu/I/1ke1cAwI1QYeHRXuXVlMbhKUHKs0LK4i+2cIpZCf3j/DH6pHzLp9i78S7+nezrWpOwpDD0OCRsXQT4PQn0PIwUf2fE1jkphc2pt+LePd+cF3bb11dUEEJMWJdSOkvlKZESuOdfEa6aUr9gfcHPTLMEm6LknVVSXkvKhVMMEsFTSDgkiesXM1yQJpvkQ4lRQyrZ7agT0gptoefW4u8WuBV6iyivDB9fnfoKP/zHr7zZ/nS75DgRE9bF2Px4s1HlGFPk5lBR6s308y1xl+5vzn+DX+78ItvVXsiziMTrQkm1G6Vu20IW/6H/DpVcvw+9PiTo0SLm6QKIzxdyFUFi+y89SrwBlPI+4b3g7yW1J5aTIDtHCeNKE/GIITahAXT1DU1Rov2RchMRq+W39q58q6MSlGxQSJDSXIp5A6y4tQKf7f1MloVc6ncU2+Q4OyoTxqWs22J1MMVc5EMSQyST34gpbJbfXC6qdbUWAXEB+Pa8cPZzW2S45UMq5lWovA0XqblIDiSbTLEFW8pKKOYKLpVcTuzaSiyPSpHakIrNzUoEvNexrxXFxkq5otPWzOUy9sxY3uPhSeGSG8K2e4TLJZJscv9+/jfvb3LC/4RkiIZYeIdYXPfpt6dF+1bKu5TofflYd28ddj/fLamQnnphqmBpIZK9kJCr5quYV9KdtBIHXh0Q/VzMndY0WZwp10KuGa3Rao3aSMCRyi8x9N+h+OL4F2bHScua8mVbB8Bb3osUknunqIX3MnITZIUmhcpqRwufco/kOwtZ/EkqUCjZr1TfXF3Qg4xEQSa01pFmmBfai0lZcsVyjbg5uom2FXL9F0oYx0XKkENb5YiLaQk5U9rvac+biBQAhh8Xz+WhNzCRltIDcpAwTjoh3g+/j8XXF1NrOIUy9ipFqQJB6gUXq+WnJA5YCUrqO5Jsyu6E3RHc4JOUPguID8CKWytouyaZdf+X28riVMQQW3Clnlk+j3yCn5FMNmLCuJSbkhKCE4IFExWS1rC0NVEpUaLWCBKtfM9DPXnnOyVaeSlBCVCWrMdaSIUMSFlglDwzueFFu57uUhRrufHhRtltlUDyrISy+b+KJRPwhEKuSJ813yZczNKv56tT/CFVWq1W1Oto4rmJonlEingWkbw3l5fRL7H27loiz7Bjb45h0bVFvJ+RWG7OBPCX7pPKcGwJhNZCKUXQ8BPD8TKa31pGkjF92c3MUpxjz4xFs13N8CjiEZLSk8xKQvLBp+hXmjROCST3FvMYuPBOvGSc0P5USVlFJXNus13NFD1vR5X8TO3bnpDlYBAy9pAm2qUR8CxF3YLCeXSEcmHpGfLvEFwJumJ2nGSvLaaU1mg1knsO7udardYwtu6G3ZVUzgHCeXSkwlKeRz9HeFK44LrBR44RxgcdHUR03oCjA7D1yVZZpV2EfqBqm6pJtr0afBVHX5trn4Syy3IR016SxvwodZ+xJKSber74Q1JBfuLZibyTWuf9nYnay3WPEmsnVrtTqVJGzMtBSPunp2a+moKfkdS5l4rRtxZt97TFmNNjeDcUJJ4NSt4JJW1rba2Fn2/+zDu+SZNMdthjXlqJZC4Q8t4QCinhoiRWDhDOUG9N3sS+ERQQY1NjJZOOCf0e7xPeS2bCBvjHyYJrC0SVZ3qEFMYkGeqtUWpJKuxJDFJPAL75PV2TTlxV5GrwVUGBXgq+95Ekudvkc5MF5wPaBG60ORCEFAEkayxfVumk9CSbJDHjboL9Y/2pElt2P9hd9n25IRr632bLky2SFnkhSEL9xKCxTMt1kRdbw6VCPxrvbEx9TS47nu4wWnPuh99XFMagNImtEiUCSQ4mPdzwqdjUWPx882fifC8rb600+ltOfHJcWhxVwmovFy/e42qNmmiMjj1t7hFFsh/Z9HiToHFCKOcUlwMvM9/b0adGo+8RXUm+7U/EQ48swZbHW6j2gTlGGCfZTHLhxgSQbhSOvTkm2zo08sRITLs4zWzRIakv2POg8EaEpHRPujodvQ/3Nkp6Yc3M8lz43G5JnyGfOyWNVd10EqMJB+BbZEmy5wpZNklKQ1kLKRfNfS/3ISolCjuf7jR7RiSLl9KMwUrhq/9NknBHiTsmn+UqNDEUv9z+hejd2vhoo9FG6FXMK/Q73I/4/nx1P0kWbbGEeVIcfn0Y14KviXpCiEFTf9sUJZteIa+pxjsbSyrdhMqe8dVv5kNJzoPGOxtj6Y2lhlAjjVZDLGRbo9TSnufiFhIhnkU9w4SzE2S1vfT+EmptqUV8/oyLM4wSIdGs13wWIBLrCqBzTzVFjsKOREnDhe+dvxd+z6ysohBc4f9GyA3U3y4cW2/K3bC7WHt3reHdnHdlnqzka533d0b/o/0Rmmh912e+uevI6yOyE2P2PtRbdl+0Wi3a7xZOOGwKSbUCPob+OxShiaEITgjGtAvTDBUglCiUpZJu6ll4baHRWjnl/BQqw4OSRL5830+JZZwGrgC7+PpiyaoxXP5+/rfR32cD6HJHpKpT0WhHI7TZ3Qan356WrDQBCIdKNP+7OdE9heqQk1Bray3eMXEl2NzaborerV+r1eK/oP/wOPIxXsa8JB6fgE4pKSUDlvAyz/yfoc2gWl9yjDCuBFIBb8mNJZLJrKQwjUe5G35Xso1YMgGSuO8BRwfgadRTo+QQSt3uSSz6AP9EQroIXA4yL6tGk9DBVHsrVd+UC9/mnyR7LmC+AU/JSBGsccul2qZqmHVpFlkHeVCyuLb8uyV+vPajufsswZxGM/GRQmPd4tuQksR9nX93HhHJEfjt3m+GjaBGq8HU81Ml2+55sQe7nu4yKv037sw4rH+wnkijCxjHSnc70E0yaZcYfz38S7AsGReaTQEfI06MMFPukI67K0FXZAvVcq1CAL9ARuqKez+CPxfDuwSyxHGm1mSSOt561Fo1Nj/ebAi52PtiL5WQveCqcSbujQ83Clq6SJCriO55qKfs311uyTO9O7KU5Y8LnzeNEpdRWsEaAL48+SV1G+6zPfDyAJG7tR7u96P1Fhx0bBDW3VuHvx78hYS0BPzz/B+iShNcuK6/Qp43X1Q1j9OWi5IQOT6kEj2JkZSRhLBkc0XhyhYrec+/HXYbz6KeUZdTTNOkYcmNJZhxaQaOvjlqqABB6v3HF3rHZ3Soka8Gb3uu55zQ8x9eld/LSEl+IVMvExolstJEq9y956HX0sKwGLR5UepsrWP498RzE4nnQNMyZCtvrbRZoluaedqU2NRYo7Ccnod6isbAm9J+T3vJPCqTapl/nqZOY8K4KbQLAGD8stC8pKbCM99GdE2rNbjQhz8Wh9S9x5TRp0aLxiOLwZ3Q3sW/w+7nu3kFXSkuvb9kcLUnzR7P5/LG5x5HSt/D/KWE+IhONS5ZQ+OiJPdZAzqrGbdcDk1yP7nucoB5nGCqOlWwfIgp3EWSK2CKZSjWU9anrHlftFpFMfJy3mlaVt5eiW/OfYM1d9cY6j3fCbsjmGjHlAXXFuDLU5mbZ/17RhofC8hPoGOKnBwHgE4AobHIAzoFIDdpC4kGG9Bttk2VTdyxJkbzv5uj2qZqRmWXSN/RoIQgs+dMk8tAq9Viz/M9vHFxUphuCGk2CabQhoPserYLZwPO4oT/CTyNeoqfb/2sKByGdmO89MZS/HxTPGbfFEuFU+kzpNNk57bUu3g9+DpGnxrNGzP5Vzv+PC2B8YGyrbMrbq0wbApn/SdfmSt3b/Is+pnsZ8d1/RXKJN2/Yn/J6wgl4DNNPpWckYzTb8UTRtoKoT4Xz10clfwq8X7W81BP9D3SFw/CH/BWkiiWuxhvu8D4QLyNe2t0jC8+v5xvObNjzXc1N/o7KT2Jd09Tu0Bt3nuTMKq6cKb7Z1HPcCPkBnV5ud3Pd2PX0124F34Py28ux6fbPyUu4ypnf8xFqYFC7xGg1qiJDHaWYMOjDUbP538P/8d7XvuS0t4cYvuRDiXNQ+zuhGYaytLV6VTK98XXFyteN/SVK+LS4tD6H/Pyc+V9y5sd2/Vsl2AIHB85QhgXc41qWYy/7Be3zBRNrUVvV2+jv/ksJ14uXvB18+VtL/clvfT+EmpvNZ7s5NR07bC3g+yyYaNPjca0i9MQGBcoW6uq1qh5ax46qcTrbMth2oVpRn/zuSg5OTjxbkJMra2kyTsAICw5DE13NTW0EcsAa0lMF/f9L/bzunAvbLwQR7sLCwV6ATMpPYk3+3eLYsYukP/6/2t2zuWgy5Lu8XpM3dy1Wq3gxowEmsRa+qQ/+jY03hOW4PMDn1vt2o2LNMaUOlPMjr+LfwetVouAuADsf7lflkV+yL86D6HY1Fgqax53rLyNe2ukzCCBm12V1Mo1679Z6H7AOM6URqPd53AfzLkyB6NOjqK20JvOa0o9E2gZf3Y8vjn/jWASMncndxTPXZzoWnzxzK6OrmbHLgddRnRKNDY/3kz9fRffWAz/WH/seLpDdtkluay7t84i1xl+Yjguvb+E3ofNXZj5EiX9cf8PdNzbUdIC1qMcf5LFbU+2ocXfLbDq9irqvnKTuMkVxqNSorD4hnTmZFNM30G+dQTgf89NN8F8iZTKeJfhzWY/8dxEove4TwV55cRIEZq/HFWO6FxGPLfNmntr0GGvuVBz9POjmNfQvETlk6gnRsLs9ifbefMh7O2y1+xYfLqxd4hQXgMVVPizrXTYpSmb2m+Ch7OH4Oc9D/XEsOPDMOmssPWSL1HiytsrseDaAgw8OhAbHm1AqjpVtKoHF5qM6mNr8leQUMLcK3NxJuCMrBJaUjwYIpyf4fw7/pJwepY2XSqqOPGP9cfi64tFk0Mvbmo+V3DHWK2ttdBgRwPetnxC8aHXh6hkODG2P9nOWymgmFcx7OxkXpmK5vfJEcK4ENXyVsOKFvwaGq6boZBLSpsS5jVVTTUwfK5tYj+Q3AWPD5r4LhKO9ziORoWlXV23PeUXTA93P4yR1YwtsabuoHyLZvOizdGlbBfea3KfN18CPDdHN3xd42t0LNXR7DNTl3Y+y/ipnqcwvd503ntzoUneYdqGz9XHy8UL1/rzLwymY8zU3RQARlQzj1nVC84HXh7AnMtzBF2MvF29UcyLX4POhc/yOLP+TPzS0tzibdpnGm+A0adGG20Uvrv0HZX737uEd0a1zEkygwshZ0OrBP84f1GXOHcnd8HPpJLUaaHFkCrmYTUd9nZA9c3V8dm+zxRnnVdiiRMq9VfBt4JkW61WSxwOAIDIKiQE1yKckJ7Aq4Vf2nQpb1uNVoN9L/ZBo9Xg4KuDgvcYWEnctTgqJQrXQ+Qr9YTmrz/a/AEfVx+z45feX8KGhxuw4tYKBMYFCo7R073MrYxfnvxSdj6G0wGn0Xl/Zyy8tlA0x4CQW6tpP4Q430d802lLpBJsAro66XMazhH8PColSjT/jIcTv7BDmjCucp7Kgp/dCbsj6oHwWenPeI9z52wx+N63jns7GgRyvjrIzYs2x67Owtmrz707J3nfybUnE/WPj92dd0ta9IX2ggVyFUCXMvz7IT1ipfhIPAAXXefPwi8ENw+KUDLFvO55Ub+Q+J6UL39HLudcAKQrDwhZiCfXnowtHbaIthXj/mBzg9pP138iClFxUDnwKthI9/lFPYsKfjbh7ARRi++61pZRHnKR8nhtWKQhyvmWw4JG5nvS6puqo/P+ztj6ZKvoNYQMkgOPDpR85vUK1uM9ftz/uGi7NiXaYG2rtWhQiF/I18MXBpvXPS8AoEqeKqJtpcjRwvj2z7bDQeVgJiCaIuRSwdfO9OXgm/jErC5SlnEPJw98VeMr0U24GHcH3UXv8vKSihT2LIzf2pgneApNDDX63nxWYk9nT5TwKmEW32XqwspnqV3UZBGm1p3Ka8XjxsNNuzjN7PONHTZidM3RvNo2U/hetDzuedCpTCfJtkL83lpe+YSzvc8KaoO54ycqJYq3JMZXNb4ym/C3Pt6KF9EvMOu/WdjzYo9gpl3ShSI2zdylVT8xFcpVyOj46rvGNR35xsjQKkMF76V3HVx1e5WoVZwv6+e14Gvod6QfAuPIXYZIqZKnCmbUmyGoOJFicOXBGPeJeK1MMQvvH22EF8e62+pi6+Otwi6iH17ZSbXF46GUwHUbp0XIG0bI1ZJLUGIQUSkjIfhCZUjmXAeVA69Q3K5kO3xVw1w5sOnxJvxw+QfU2FwDMy/NFLzutHrmcxuXZruaiX7evFhz0c+FcHV0RX6P/GbHR58ajeW3luOvh3+h476O+PbCt2bnHOh2wMxTTA9fPWZTupcVz4otVlKsW9lumN1APO+JkKvp9o7b4efmR6T0kdq8yUE/h9KgF1jk0KVMF1zqe4nXSqwXst7GvRV1hxXKtkzCT01+wqme5muRlGdLj3I9sLL5SkHjht7jrP8Rc6H3kwKfwNXRFUVz8ws73GS2fPzV7i/B9fnI6yMY+u9Q0eSMFfwqYFBl8wo/Rt4eAstwLudc8Hb1xq2BwuOfD70AL/SdpRByjQeANrvbGEpNCYW69K4gb9+pt3aW9CpJ3XZ2g9n4ouoXyOeRD/u77pd1f5VKBU9nT7PjDXc0RI3NNbDtyTbBHDYb2m3gXX+3PdmG4AR+ZTMAODs448aAGzjWQzz0SGjs3x98H42LNEZul9yi7U3Re4fu6bIHfSsIh3yeD+RXVurngeJe5t5USq3498LvGVU7MOXbOt9ifK3xvJ+Jra0AsLz5cjQpKp7F/2bITV6h/pP8n4i2IyXHCuNcQVroB/zx6o9IU6fxlor5ocEPqJTHfHIiGXD6hZPPWisVY3C532WMqTkGBTwK8H7+LEq4PJafmx8cHRwx61P51io+Wu9uLenW+b92uviS3C65zTTKn+39DCffnhRs6+7kjlzOuTCkyhAzK7XUfUkTbYjF5MnZaHQu3RlbO25FwyINRc8Tsla4OLoIttG73Kg1aux6ai6Ij6g2Aq6OrmbPKk2Ths8PZro9CyW743MtNWXB1QXotM9cSaEX5A93NxaY/7j/ByKSI/Cv/79I16TzajibF2suqfEXs+4saboEX1YXtnY9i36Gf57/I/i51Oafj0/yf4L+lfqLutFptVrBsl2dy3SWtFSEJ5sv9G6Obrg76C5q5q8p2nbxjcWC78inhXTJ+MQ2WUL0LN8T339KnxlZz5Km/NlZ9UQmRwpaT4UEPC5C37l+wfqCni5SScT4lIF89+UrpadSqTCm5hjMbSgvBIj0/nyc6nkKv7aUtq7y4aBywIz64oIJALP5+692f6G0d2lZ9wR0lkupZyVWpUGlUqFnebJyZ6ZUy6crRSqlAAHMvZqGVx2ORkX4vcdI41HF3DyFcHTQbaJ/aECWRJSLu5M7nB2dsbH9RixuYqy03v9yP9bdXcc713P5ps43gm7yYujfRVplQvOizTGn4Ry0KtEKfm5+vOfMuTIH+1/u5xXq9fODXMFUbN6dfnE6boXewtQL/Ik+9dY7PsMLNyeMlFLcyYEudE9/PTmx25XzVMbG9htFz9nxdIeooly/p3F2cDb7jK+qjh79c5ITwsnd/5XxKUPdvk4BXbKzwVUG836u0Wrw0/Wf0PIf83DX+Y3mo1aBWrxjZfvT7Wi7p63gfW8Pug03JzfBz/UI5UXRP6sN7chznwCZ72F53/KC62R8WjzGnhF3vSfZQ3Kplrcavv/0e6xvKx66aJrnicvgKoNlGyn1iM0HQgpk2u8qxEcvjAtp6UbXkM7CuvPZTkGreNsS/C9SQnpmrFFgfCBvdtuKfhUBgHewc91gTa0zk2tPNiy6+muY0vNQT9wPv4+L78xjtn9srHM5tUZ2azGh+MGQB0ZubKaa/4D4AEw+N1kwTkv/nQGYbbCklB+ksZ8kZclM2f18NyadncTrHr+g8QLB7KFc5Lg9qzVqhCeFo8XfLbD2nnm2fL2iSWiTokcoMWGdgroFqHo+83I8evis8UBmjgQ+ZUKfw33w7flvsenRJl4X+Vr5a2FKnSm8m1kxK5ieDqU6iC5gGq0G866Yx8sBOmvYvEbzcKmv8AafL0EMyQb0x2s/CpYAqehXUdBFVE/7PeYJUWoVqGV4L35pIZ4Ib9BRcwvMj41/xIDKAwDImw+q562O3hV6y7bIdSjVASd78ivgVtxageZ/N8eCa+aubgB4LcxckjOSBd3M/2z3p6DC54f/fhAtO9ejXA8sbLxQdIMTkxojWnv683LycwAMqTIEuZ3pLB2Azq1VLmFJYbyWcSmUJGu60u8Kfm31q6J1qrBnYdlt9fC553PRarVmSes6le6E31r/hnzu+czOJylTCgiv7WLoFXpyBGK9V5ufmx86ljY3EPCtMVzO9j6Lin4V0at8L6r7Tq83HQMq6eYgTxdPTK0rXaVCT8U8mc9IbA6SKqXmIHMLTJLDRsiw8nsbnbcc3xjhWlilNvlKamLTMv6T8aIKZ0Dnui1kgeS6mO/qZL53WHJ9Ca/LtX7PCsj7vs6O5oI/DXpLsZ+r+F6Kj9r5dXOg2O9IUlZMDJIQFhq4Ch7uvptLt/3dJK9Tya8Sb7kvIUZWG4neFXobDARCkFSHUsKEWvQlNuVWETElywvja9euRalSpeDm5obatWvj4kWyxGB62u1px3uc9CUVim8gmRg67jVf2LgILfYX3l1Az4M9zTbhXBfv0TWFlQmX3l8yZH/mIpQ0joRtHTPdind22mkWB0NTmkZIgBZKysDFdGLL0GQgKT2JV/lAA5/r68z64q4tc6/MxamAU7zu8UoWyn1dMhUDnUqbWyS+Of8NNj7aKKgl1C+aciaJ2wNvG/pexptek8xNfGiKPh5MSJBXqVTwdfPFb63NQyGO+R8jyvQs5lHAl7kf0Ll06a1hYlZXvtq8iRnStemFvq+e7uW6U2t0uZ4FLYq3EE26wpflukuZLrwWChJKeZcyJBA63kM8FkuMgrkK4tjn5m54Qsld6hSog52ddqJgroJY33a94Ia43rZ6ZkkoK/lVwsLGOs8XIde9o2+OipamdHTQJU7ic+fV0+sQnUBCglEyRcvrUUWR4xoKGM9/e7rQ1R/3dMl0CV3VQl6OBv3YPthNOA5fCinLI5/FVb+28cVrpqpTieZkOW6PTYs2BaB77oe6Kdvg03Cm1xmDcp3WQqQXxPUMqjzIKLRAbC0xVaiJxazzoRf85K7TekVR86LNBc9JTOdfG/Tjim+tWntvrcEwIKUMUgJJHhwuUop9MZwdnLG1Y+Y+mk85mKJO4Z33uTHAchQnQvkIaJGjRCVRJvKV7KLxeNBXheBye1BmeBatazjJvfnK7ZmiUqnMvCPFIO2nkJwh5bVBConXnSk5QhjftWsXJk6ciJkzZ+LOnTto0qQJOnTogIAA8kyG1kKvMeNLrLP4unB8Mtc9U+hlHXN6DJ5FC7ubAxB1ARQaHNzJjE87KcS61uuMrKRV8lTBiubGHgMkgrQeS5WnAYDxZ8aj0c5GvMqHhoUbilp3uZgKei4OLuhbkbxMmiUp65tZCqxxEfO6v5feXxK1vulpUdxceJSCq6QS0oyKwVf6xBQx66MYJDWQxVz7hNyelVjglJS40+Pu5I7rA+iSb/Fl/pcLbdLIg90OGhZtMWuJ0O/MjVGn2SzEp8UbkqR8WuhTo02HFDs77ZTMQAzoYs3b7TZX4HIFB6XWFlq4yRT5rGm2uPcXVeTXci7vWx618teS1VZurLse09JVNPBtTPWVBgB+xYv+fajgZx5vfjnosiwPLCkaFGqAzqUzx3ZJ75JUG3q5XgQz6s1APo/M8SimCCWFq4iYflFYYDRVnkvlBzBFr/BR6iWYxz2PovZ8/HD5Bxx7cwyDjpl7NCmB+/uYKkKk4AvJJKV3hd5G3pB8SuA0dRpvHXvuOJ5cZzJ1DLRSF+Jh1XSerc6OzrwlWq2B6f7YdK8tBff50gqKgyvzu+OToKTikdJ4cu48/1MT+mTKSmhYODMUtWuZrrKvk6WF8eXLl2P48OEYMWIEKlWqhJUrV6JYsWJYt87yWQJp0U8SfHFlYtkCO5QyLzdBQs18NYnP/f0+f9Iw7sJD40LChxJhwFKaJEBXekrI3fr3Nr8TWWjUGjV+vmVc75ZrnbEnbUsKxxVJ4e7kjjuDyEtxmcYqyklOxJeURg5yNJQARN2crFE2ivse2GqxBujjBa2F2DzQZrd5tYlOpTthWNXM0B0axZzpZp9mI01jAQtKNLfIcd8NWo8CrlUI0GVSlouYVV4KkvqvQkyuIz9zNCDfykdrucztnNvgBgzQC1tci2seN3NBq8PeDlhxewW2PN5ilHPD2cEZE2pNMHLHPdLdPIP4nCtzBO8tt5LKb21+M/uepBvjCr4VMLCysUGBdK/RrqSx0qq4V3HZyWH1yLVU01jGC+YqaLB0iiWpIoHWrdU0vFEoy7dQvDlJTXUhvq5pbrAgwbRq0MU+dF6IpvmN+OZPofw13HFcyruUaBiZNeAKWrTea3LXaFPBtHWJ1rLLo9Eavkz3bzReNiQx7kKUyK1MHuEqi2i9IUyz9P/VTrjsGh9dy2YK4ErW5ywrjKelpeHWrVto29Z48mrbti0uXzbPgpqamoq4uDij/4Tgc/2lWQjdHN0kN2SWtP4CwE9NlWt7uJsLmu/L566sxA2bRgsmdwHhg68G4ZHXR1BzS02z46ZxvEo0XkqQ60qsh0ZpUjBXQaO/q+atSnWvNa3WKE6goYcvuy4JSuJj5cD1HtAnKZSLXTyrVgABAABJREFUVOkWo/ta0DJO44psalGhnQdMQ2VorGlK3wUuplUdpOC6adL2wzR3BJ/VVIg1rdYY/U27rnDHyZKmSzCksrAbPm1faCDdmJoKeLRc7n/ZaANN+55w1wgPZw9eN/kNDzdgyQ3jBIQuji5m5ST5MgqLwZ0/uJZuKfjeQVKL7eQ6k82sh6RJzfhitb9vID+pI6BsX0Fa9/tEjxOG75zPIx/+7cFfv5yP/hX740DXzCRrvm6+VF4f8xvNN/pbKgEnl0t9LxElUxRCTpZ+wHyO9nHzIfbk6lm+J/pXMlYg0LyTpt55toyTN4W033UL1kWPcj3M9lOk8Bmr/NzlhQnQKiNNn29J75Ky2wIgzjfC9QYF+OvZ096bFFMjSt2CdYnnkjYl2hjdW4mFP8sK4xEREVCr1ShQwHhzXaBAAYSEmLs/Llq0CN7e3ob/ihXjL39zZ9AdLGpiXkORxk30Sv8rkoNcLNOrHJRuRNe0WmPkUkajtSvkWcjsmBwXZj2klvHvP/2eKNEeDaZ1G4Vc4Uy1fEpippY2468xbA1M43RoJmPTbOKm5cnEcHdyR5Mi4qUhxGhRzNilXomWVSoJiBRV85ArIbhKLSVjBKBLeiV3oeejQK4CxG6etLGGpphmu6f5HnzKNLnQ1AjWx+PqsaQiRArTury0i/3OTjsN/1apVFTzwdX+xmUmlWx4SGryAvzKBiWeBLSbUVPFCamiSqmQcHPgTaM8LAub8Ff2IOWXluJJHfXw1eAmVdRbKoswF5LnKFTaUCrHix7TMUGjBO1QqgNK+xiHCNLshaSSoIkh11tMKXzjgVTpPrvBbLNxQvNO2tMDzNQKT/o7D6s6DHMazrFoX0jfya9rGBuv5CSDlAvf2kSyzvLte8r5lqO2UMuFT3Ep5G1rimnSSSVG2CwrjOsxfXG1Wi3vyzxjxgzExsYa/gsM5M9kKfRyuzm58bql0VyDC18MMx/nep8jOo9v4SO1VPzY+EezDSWpRUpIGFay+SDVvN8Lvyf7HkLs+GwH0XmmAh3XtZYWJe6htJDUYBbCdFyrVCrcH0xWjuda/2uK4u/44nxI66jmds5tlDBpZYuVZq51NPzc/Gfpkz5AmzhIjOK5yS1pfJsh0s0aX9wxSTy1EDQlpPj6SGoFlFPySQxSl8dlzZYZ/a1SqSRLsFiCb+t8azbvT649mdjl+0yvM2abManazVxMLZ9xqcLeZlIUyU0m8PDNITSeBKbQKE6aFm1qZqkkVX6YWjxpsbRgS6q44nN7Jp3Hhc7jc88nheT3EspSbo0qMSTYQjnn6yo/+S4AzGvIX0WEBLnhE2KQhlHYUvHJ5cvqX5qtVbTVAuTClyeI9Dcw9UKwhCcBbZw+F5J9mJBCvm7BurLKrgJk1bL08IVjks77pn2XU3lET9YIPOQhb968cHR0NLOCh4WFmVnLAcDV1RWursoWtJHVR+Kn6+Lu4KtbrjY7lt8jvyFTtBiezuZxyKTuZHxtSV2chMqwkTC0ylDe46STJN9GvX7B+jxnmiNU6kwJPm4+ROeZ1p73cfPB5X6X0XCHeN1we2NpNy6lGzNS+CwGLo4uqJqnKh5GPhRte6nfJaPvncs5F5Y3X46eB3tKJkLkgyahkRLNvWlN4KFVh2L1XfP5hY+Wxc3rmpLCl6SFRBjgC+8BdLWVdz+Xb70kXfiUbAr4IFFeDK7MX7tUqfcFCXy1bUt6l8T5PudRY7N02USuJ5QeUq+kRoXNywvSCPKmyHWRVQrpJrZLmS5GZZRocXe0THiOLbk3+J7s9ULMEEAyf/LtZwD6uFxbwxcTasnwGSGEwhRXtViFCWel49b5yoUubboU3174VrItX7k7pbQp0QbH/M0raXDpWb4nHOGIlJQUo+OFXMg99uS2HVhuoFnbloVaErVXZagU9Xlu3blm7Z01zkTXcNW6WvR5AcDQ8kOJ1vfKeSrztj/42UF8efJLnhY6qntX520HAF4OXoL993TxREJaAir4VTBrP6ziMOx/sl+yzzPrz0S9gvXM2nvAQ/K5aaCBWq2Go2OmLNSpdCfM+m+W5H35yLLCuIuLC2rXro2TJ0+ie/dM99mTJ0+ia1f7xO9e6nuJdwNX0a8ikTBumsiHlMVNFvO6yHi5eGFps6X49rz4hKrE5VdI2CBZxJsVbYbvPzWPIVOpVDjZ8yRvgicuSlzhlZDfIz/vpiC3S27cH3wf1TeLZ2gf/8l4s2P53PMhPDmc52xpmhRpgovvlZVuy64sabZEskSg0Fi0dnwZn0b1dK/TaPVPK6L2ppp2V0dX1MpfC7fDpLOENyhsfu96Bevh5Fv+2t1caDPp6hHaZCtVxJAo9vpX7K9oHhPiQLcD6LpfeD0Ry1lBoiiyBkrGdXQKfzlEU/jKa5G67vFBWpZIiZsfX3JUUkWPl4uXov44OPB/v2XNlmHK+SlE15CDkiz3SsaRUNkuQLdn6FGuB/a8EC5pJ5T4TEn5VSV4OnsiIV1c+V+3YF3e/Z8t9incPAhcSJWyfBa7diXbYemNpZKlqvgstYAuCfDbuLdE96elX8V++KL4F3j+/LnZZ3MqzkFyRrLkNdyc3PDmzRujY99X+J6oAkpwYDDv8WllzRM2m+IR54E3Scb3nVdpnug7wyUyKBKRiDQ6VlJTUvLeKqjMvi8ALKm6BJEpkTwtjOF7XgBQw7EGypSVLnNbwKMAb3uNViPa90JOhXjbAUC//P0AAWNzYc/CUGvVcIADb3uS3yp/an74+/ubHW+buy3qlK0j2lYLLZ4/fw4fHx8ULFgQKpVK0VyQZYVxAJg8eTIGDRqEOnXqoEGDBvjjjz8QEBCAr776Stb1pFy3pBZeoQW7UeFGuPDuguT9y/jQ120G+BOl6JGK61VSqgCQv9G+NfCWqCs8SayokFXjaPej6LjP8tpaPWLjQOp5CH3vxU0XY9hxea7uCxsvRJNd8uOx7UW1vNXwIEK4/jUJUm73YqEl/Sr2ww+XfxD8HNC58vLxRZUvsOHRBsF2Wzps4S2bZ5r4T4j9XffzHlci2M5uMJtIGJdbmksoJp7U+vi/tvwJ7sZ+MhYHXh3g/QzQlbdSkrhIDLESkYD43Lu542bU2iKvZJcYTYs2xYx61vm+R98clT4J/OOQ1AuET5FJKvjVKiDveVbNU1VRSRshjwHSd6VwLn5FVbuS7awqjCvNcs8HiQKidfHWop/PaTgHr2Je4W74Xd7P7VU2VAiS8SlUYqpX+V44F3hOsr1Q/OzK5isx8dxEyfZyaVa0Ge9xlUqFgZUHYvmt5YJtxdzj93TZgzpbxQUWIaSUZK18WiEmJgb58+eHh4eH0XxUUlsSSelJvFUv9BTzLAZXJ1ezeayktqRg5nYupXz5s2JnREsrJAvnKoxcLsbrhkarQXJ6smifpe5dPL04AhP4QzQAnaeXkJv0i+gXovcUK0mbmpGKgHjxctKOcERpX/61VKPVQBMj7JEl1A4Qf95Cz4mkrdQ1tFqt5DhxgAPyu+RHWJhOmVWokE4WI/WUNr9eFqZPnz5YuXIl5s2bh5o1a+LChQs4evQoSpSQlwafW/KED6kJQmij3KN8D95641zE4iql4iLEXAulYomEtJqAbhGQgtSiYYolao4KLZDcurvWQKo8weIm/HXk6xesL/i9ucl5aPFx81Fcis6aCJW/WN1qNXXpF1rEhHUpq4Gfmx+vKy8AjPlkjGjbGvlq8I5PkpJ4fSr0EVTMKYmRI3G7VpJkTmgOI3UtrVeoHu9xKcWcaVIaWyHlum8t99TlzZcT59WgRWjuMoVPwUJSZtHdyZ038Q6pIC+UxVYsOVet/LWwo9MO3veRNL5eaI0lnXdpM6fbAj6vNBKkvvPeLnuJlBTW8GQBrBPyQBLbKjS/Ni3alChOXqiCQ6sSrajyhZgi9Hv93vp3zKw/UzT8wrTsmCli85CSPAdie203Bze4pLkgf/78yJMnD9zd3eHm5mb4z93dHb65feHg7MD7n7OrM3xy+5i1M7T1FG6r/8+0nf4/Tw9PybYubi5m7TzcPZDHKw8K+RQSbVvUt6jgvX1y+6BsvrKy2pbJWwZeubyov6/Udy7hVwJFfIugbP6ygu093D1kPWs3NzfZ7aTaSl3D3d1d8rcql78c8uTJg/z58yMmJgZqtS6Ma+dnO4mTSXLJ0sI4AHz99dfw9/dHamoqbt26haZNm0o34mHnZzutFrfm6uhqllXPlA4lheuLb+6wGcubC2snxYTx4l7FRZNziLkWtioh7U5rr6QogDKBXk6NbD1SL5KQACdlIPyu/ncyewTs67oPS5taNiv7yuYrJRVUJAhZD/3c/MzK/fCh5Lea9alwfI6SeG6pjYbYe3F/8H3Mqi/cLzFrK8n7Jleg7lW+F/Z0EXYdlULomfi6+Zpl/TZleNXhop8LefD4uPoY1RA1RYmSSwoSa5nUvC+E2ObfGlmq9SiJ/5Tq15V+V3B9wHXekoh8Mat8CL2zPcr3EGwjtrFXqVRE2bKVlKTJqoi5fIspZYZUGYL87sKJiEhzaggpFr+tIx2nLIbY/CkXknVKDClljJRXphLF3r6u+3Ct/zWz4w2LNETfin1FlbTtS4knl+UmRuWDNOmxKWLGK28nb6hUKnh4CHuZiXljSXmnpWmk3dSFKJ67uKTCXWzdEOp3kdxFUCVvFckwDSHFd26X3KL39XD2QAmvErL2RGJ7Ei9XL/i5+Unu1b1c+b2KpbB1qVouYmPMzcnN8J314zQ9PR2ATj6Q4/mT5YVxS1ElbxWrXl9qEy2qCXRyQ5U8wv2TSpzTvVx3wc+k3EuksEYmTVJoyg9x8Xb1llxExDAtXWJKnQL8rlmvYl6JtutXsZ/sPjk7OEvW4BVyHeSLe+1WthtalWiFhoUb4kC3Azjb+6zgdaUEDqUxc3+0/UN2W7FMy0ozsQot6lICrUqlQp+KwnUqxcJVpDxRljVbJrvU07hPxhEpJPmSd81tOFe0zYCK4nHoUlZ702oPeqSqGPAl1LQUJONHTNDrWb6nUWkxLkLu8Sd7SocZCFEtbzWMrDYSgLjAI6Yo0iO2Hgkhtkmt6FcRe7rswbHPjwnOzWJJwcSEFak16o82f6BHOWFhHhBfY7uWEc9RI5TYUI+Q8szZwRkuDi640Ec6xE0OQs8lv0d+UaWMm5MbptWTjreUQkho5ktMSANfPgOlWMITRczVVyrsRIkXgbODs+ySaWIC3OImiyXn7Q3tNwieI1ZppGb+mjjf5zyvktYBDlCBrgwjF6l23i7i30lMIHZ0cJRU7pGGqnEh9eDhw8/dj7iKjumc4OjgKFn+zBIygFxlk1xljyUQU/pxFdNC441WqZ5jhHF7I6V5F/vhNJDOgCtkmVKaxEpsYuPbtFuK24Nui2aaF3OxP9f7nKiAqKT0CiD8TCKSIxRdd/wn47Gt4zbR+5pm4NbTv2J/wfI6dQuYWw+555b2Li0qpA2qPEh0o6wkA26XMl1kt5VCSkkgVf5C6HdWWvtUbPMu9b62K9lO2DNDAtLkSB7OHuhWtpvRManfSWoDJCXY1i9Un/ceUs9DSd1ePUKbaJLNoNhYmN1gtqBQKxSTTVp3PbezeWb5bR23Ydwn43CixwlRgUdMUXSg6wEsa7YMDYtYvmpEed/yKJq7KNwc+QUPKe8KIaTGSHGv4pjTcI5oOSWxeuJCc64eqSzsQmXwbg+6jVuDbgm+l1IhaGV9yop+LrTnICkXJLZ5Jt1YWzqx2bd1vsXXNb7GtLrKFQV8HO1Olk9BiFXNVwl+Vi1fNdG2Qgp+gK4OuiUh8aIp5V0KuzrtMjvevmR7/NFGXMnu5+Yne3+qxGPT180Xni6egnOtlOeHlHAq1jdrJPvzdfUlfh6m9y/vW94mCQj93PxkCeSW8Mzl7hFoymS6ObkJKs1JBG0pA4YpTBjnoCSTqxRSm1ExNw6NRloYb1Wc3+VcrlarhFcJjK05VvScn5r8hA6lOmBirYmy7rG943bBz6ReXDEXeylhyRLx7NZgZPWRvEnBuAhtKMd8MkbQMmUJF0whoWJm/ZmKhHG5i/GWDltwoscJ0XPE3rkj3Y8IxqdKQfI+AkDtArXNji1rtkz0OytVnk2vN112W70wPLzqcHxb19iyKrkBkficZMHns3iRzF9SGaWlkrTt/Izfep2cLp2xVy5870yLYi2I2w+rZu4xoFLprEmFPKVL2QgJeqV9Skt64PBBY9G3dPUD0naHPz9sZsWrXaA2RlYbyVtvW4/UeiF1f9Ka36ZIhTXVyCde3k5oP0NSTlXonPVt1xOvn3zPhSSvxZQ65gnvHgx5gMFVBmN0zdGiHhhzGswRvbbYvqKYVzEirxGx9lXzmIdoANIeTyT5GLIqfM+0c5nORL+1EKQlGPmQWjMcVA4o4VWCd4xb2y2azyqvdM2n2d+ZWntJ7q1SqVDBr4Kkx6gYLo4uKO8nbx4Uup4URT2L4u/f/4b/E3/DMScHJ/i56zyVSH5rd+fMdfrvTX/j+qXryOuel2gOpTVWMmHcRtTMV1P0c7FFgqS+q9BkL/dFP9z9ML6sIVwbENAlFlvSdIlokjgxxNyYrImY0sUW9YOVIKQpFMr0D+gmJaXkcc+D4z2O41LfS0bHO5fprOi6cpVFNfPXlBQ6xMZ+ca/isrWupPWWf272s9Hf33/6PdqWEN90KY1dlFu2DAAWNFqAK/2uoEreKmbjSWoeUWoZB/gVPiS/kdgYXN1yNTZ32CzaXmhhz9BKZ2Pljl+a8AE+RRCpqyGgPK7c0jHSpBZ9QHgsyQ0rIX2Pi3gWMXvu/2v7P4yvNV52hQFS5CjJ2pVsh/1d9wvOGXKVyiRGh+r5qvMm31S6PpLM90OqDJF9/R7lewhmD+9fsT8OdBOu2gAo93oSKnEnNUbFlPBi7u+W4NeWv6K8b3ls6bAFn5f7nLq9kmdmjZxENHMb18vMw9mDKIxLSZ9VKpXZXENizChZsiRWrlzJ/yHFVJ7PXZ5XnZODk1k/9UItH3PmzEHNmjXN7y/i1Sf6HU2QSrIMAL8s/QW3rtzCp7V0c5beQt6gSgMc33KcKofYP5v/wZ6te1D1k6rI75GfSK4SmgsEz6c6O5tCOllYK1nZry1/tfpib8m+C7kRCiE3HsQa7jFSpd4AcWHKXjHyfBmI+eCbBKQmpkKehSySqK2wZ2EzbbfSZDr2TBAoF1Jh3PS3alq0qeT3rVWglmCMvrXdFVUqlaDVSarfUu8NSZwnX6K2MwH8pee4iAmCzYo1U2ShkYL7G1fwq4DTvU4TtTN9b/pV7Icvq4srP7lYK5O7FNf6X1NUQgyAYNkXuXMvTTuuINq6eGubuGgCZBZhU1QqFcr4lOHdv5T1KUs1XriQWh2VKgb5fhelVkCi+wrMVTPqz5BUeJGEBIoh5N2i5HvLiUGmoXmx5tjTZQ9q5q8p6x3km4tIvUytsd+i2ZNwfxelY3No16H4aab03FjWp6xknDYNfMoHIWHY0cFRscJJj9hvN2XKFJw+bb4WisWA37hxA6NGjTI7zheOI/VbXbx4EYcPH8auXbvg7uKOCn4VjEKRaH7rB7cfYOsfW7F2+1p45PKw2p41RwjjFXzJ4gTEfiASIU8IpYNfiRVDzgRDW7vUVhsaEkhc5sU2I9b+Lnwa8NkNZhNnhTadAD8v9zk2tBOuh60nq1r8b4bctHcXBBFabEiTipi+e6QbDyHhUkmSF2sjtkAd6HqAKlaLy81Q6fGR2yU3DnY7KOv6SjH9TfN75Mf6tuux47MdVNf5rv53VPHvtnRt5OLh7KE42VV8WjzvcZpNDjcxntxnoSSkQ8/WjluJzlOaTNKUfV33SbpKCj0XW2WO55vv7JkQloSGhZXlShhSZQhvpnqS7007Z5jyWenPDP+WWyqNxsNFD9/Ytmd1AqlcC1y4v4utFAgOKgeL7jNpPWTEKixZCk9PT+TJYz4/OTo4Cir88+XLx5tB39XJlcgSzqVJkya4du0acuXSKWacHJxkC9G16tTCgUsHkCcfXTI52nGSI4Rx0ociFCvXoWQH/Nn2T9n3D08Kl90WIHMtERqsciYOWhdIS280lECyMRNzlSGNf5abRGZLhy1Y1cI40QvNwsWdUDZ32Iy5DecSxa9Y0iIh1yLDR0nvkha7lqURendI48pMJ3/S30DI6ilVE1YMsYSHlsA06Q03dlJJrBkppbxLoUMp4fKRVoNniHxa6FPe8l5ZCSX5UZSuZ5Ygr1umi+GdsDvE7bhzrSXiQ6XitvUosabIFWwEhXEr5sbhwudBZBNPKAVfj8/7yNXRFVs6bCFq7+zgzJv4jOR7C80ZpOvGwsYLsa/LPsxtOBebOmwiamPK0CpD0bVMV7M9ihh8wiBpNQZrjAeaa1pq7zpz7EzcvHwTW//Yasjd4e/vDwB4/PgxOnbsCE9PTxQoUACDBg1CRERmst++n/XF2LFjMXbsWPj4+CBPnjyYNWuW6Hsa/C4Y4waNQ/2S9eHn44fevXsjNDQUALBx40bMnTsX9+7dM/Rl48aNAIDly5eje9PuqFuiLlrVaIWvv/4aCQkJot9NpVLh999/R6dOnVCneB10btgZd2/cxZtXb9C8eXPkypULDRo0wKtXmdWETC3zQ4cORbdu3bBs2TLULV8Xjco3woKpCwzlwABzN3XuffN65zXcN+B1AFq2aMl731evXqFr164oUKAAPD09UbduXZw6dUry+/3555/o3r07PDw8UK5cORw8mKncv335Nqrmq4q42DjR6yglZwjjhC9nXve8vMlDljRbIllHEgA6l+aPXVSiJfR19SWyasqtt8uXuIZWgDe1/CvV8IplFrUEYgI36cIndxFxUDmgZfGWRscikyOJ21f2y4yzt0aJFxJKeJWw2LXEshhbAn0MHGkYgCUxfY9Ix4zQ+zfz05my+rGh3QbRhIeWwDRJmrXDcviwtjsnHy4OWTMZpBTWTJAkeW+ZrsBcBSjXspScQZ5oz1aCqClKNv20YWNS97SV1ZKvaoRUIrOsyM2BN1Ezf02qNvUK1rPIvf3c/DD2E/FEunocVA4o61sWn5f7nCoeloubkxsWNF5gtkcRw3T/d7LnSeKKHyRziVarRVJ6ktl/KRkpvP/xnSv0n5ODk6Fdckay2ed88wXfOj594XTUqFsDw0YMQ3BwMIKDg1GsWDEEBwejWbNmqFmzJm7evIl///0XoaGh6N27t1H7TZs2wcnJCdeuXcMvv/yCFStW4M8/+Q2AXi5eGD94PJLiknD+/HmcPHkSr169Qp8+unwYffr0wTfffIMqVaoY+qL/zMHBATMWzsC+C/uwcPVCnDlzBlOnipeuBYD58+dj8ODB2H12N0qVK4VpX03D1PFTMWPGDNy8qfNeGztWfJyePXsWr169ws7DO/Hj6h9xYNcBHNgpnsNBf9+7d+8a7jt3ylxMmz6N977x8fHo0KEDTp06hdu3b6N169bo3LkzAgLESzzPnTsXvXv3xv3799GxY0cMGDAAUVFRAGw3X1omeCCLQ7N5kLvwAcD3Db7HodeHzI4rWYh/bPwj8SY+v0d+wXg8ISbXmYy6BeviRsgNbH+qy26emJ5IdQ3uZLy943bFViEl7rjXQq6hfan2stsTC+MWdLc7F3gOX9X4iujc0j6l8UebPxSFTWQlrP095jSYg8m1J1s1blgIuQKP0Pue3yO/rOvZSjBuV7IdjvsfB2A5wVioRjMfSqwsjYs0xqX3l6RPNKFm/pqoU6CO1ZMsmUJSnkqMwZUHY+29tSjvWx7Po58rulb7knTzbX53eeO4Y+mOWHxD5wKc1d2dTVHimTTuk3F4FPmI+neyt5t6k6JNUMCjAEKTQg3HbGEZt6eLtB4lyi4u53qfy3Z5VeS4upvC9c5MzkhG/e3yyh4q5Vr/a7zhQw4qB6PfuGrRqvDx8EHuXLlRsGDm91+3bh1q1aqFhQsXGo799ddfKFasGPxf+aNkmZIAgGLFimHFihW6zOUVKuDBgwdYsWIFRo4caXbvJ1ef4Pnj53j9+jWKF9cZCbds2YIqVargxo0bqFu3Ljw9PeHk5GTUFwCYOHEiHkU8AgAULVEU8+fPx+jRo7F27VrR5/DFF1+gd+/eeBTxCMPHDceADgMwedpktGun8yaeMGECvvhCvKqJr68vVq9ejfeJ71GgZAE0bd0Udy/fBSZJ3xcAvpv+HVo3bY3J0yajQ/sOvPetWbOmkUV+0aJF2L9/Pw4ePCiqLBg6dCj69esHAFi4cCF+/fVXXL9+He3btxdNVGdJsp+aUg42msuELK6WSpggxbHPj2FgpYFGx6RiLVwdXdG6RGuM+WSM4dj1kOtU9+WW26Itc3W291mq86Uo411GUXvSsj58C6TsRHaUypoGhRsocu/mK7llTfhc/KbUmYJ+FfsRlRfj81YhRaVS2UUQBxRkh1Y4YZn+vmL1lS3J5NqZuSYs5aZdPa94qT8uSqxucpOSOTk4YUP7DZJlqPj4uubXuv/X+Jq6bbV81QSzRpMwqvoobO24FYuaLKJuy537tnTYgsVNzWNkxZDrxcWtrS43caS9BDUlCvl8Hvmwp8se6nZCwjiNoCjXwqrHNFGVLRK4ZYWwuSl15a9ZXLKbIE4L31o3rOqwLP+9y/mWIwq/unXrFs6ePQtPT0/DfxUr6t6JwDeBhvM+/fRTo+/coEEDvHjxAmq1eajH06dPUaxYMYMgDgCVK1eGj48Pnjx5Itqfs2fPYkTPEWhZrSXqlayHwYMHIzIyEomJ4ga46tUz12F97HSlKpkK4QIFCiAlJQVxccKu3FWqVIGjo6Phe+YtkBexkbHE9y1dVPe8m9RtInjf5ORkzJkzB3Xr1kXRokVRsGBBvHr1StIyzr1Prly5kDt3boSF6QybciuXeDp7UuVuYJZxE6yxWNtKGHdxdMHXNb/G1ieZSWVIszZ6OmcmVaB15eO6DNK6ICpd7E1RmoClZTEy9yy+MUVjxeNibRdiU+SWotNDu1Dyufi1KNaCKPQD0CXFWXZzGdU9LQLP16TJHSFWD1eMIrmVZU0fVGkQboXeMvxtqwSLhT0L42r/q0hTp+Hom6MWuSaNVV/JBo5WiWgJvqr+FbqW6SrbO2R1q9XodagXnkY9pW7r6OCIGvlq4G3cW+q2uV0yhWJa910AVInquDg7OuNQt0PQaDVwc8r0YKOxtNtLGDcVQte3XU99jer5quN++H3i8/mqEwCgiqne0mELOuyVn4vB9HuTCuNja47F6rurZd1zSt0pOBNoXIVBbq13uZDGTJsys/5M/HjtRwv3xvoMrDQQW59sxbyG8+ga8kzZbUu2Rei7TG8Kdyd3XOt/zey8J5H8gqfguBdAfx03Jzcz45WYgY1kX6/RaNC5c2csXmyusIx2jqbqpx6tVsu71gkd1/P27Vt07NgRvYb0wrjp4+Dt643QR6EYPny4Uew2H87Omeuw/h7uru5mxzQa4f2//hr6vbNKpRI9X+i+fMf015k2bRqOHz+O1atXo2zZsnB3d0fHjh2RlpZGfB/SvkmhUqmw47Md8AOZXJAjLOM02ljTxXpF8xWK769EGKfdSOd2yW1kTSK11nKFS1qBmquJtoR7FmlSHNM44Or5qiuyGFfNU1VRXK/cuul9K/SV1U4utsimacruzruNvDaU1km2BaYhKz6uPqhfSL67HKmF2jT+GtBt0kjxdTPOJmtLS1Eu51zwdfO1mAWMxHNCjxKPAntYYlQqFQp7FlZ0b6UlzriZzUmrjliDkz1PEp1X0rukmUWKND4VgOzkXjs77VQUwsZ9Hw53PyyvugVl3/3c/HC8x3EMqDQAbUq0MRyn8VopmrsoRlYzd5UlRe480LxYc9n3LJa7mJkQZeoxKMYPDX6QfW8ucnKr8CV/yw5MqzcND4Y8QPdy3RVdp3ju4mbKOpVKBQ9nD7P/3JzczP4rkrsI77li/+nbAjD7jGZudnFxMbNk16pVC48ePULJkiVRtmxZo/88cmV+z6tXrxq1u3r1KsqVKwdHR/O1u3LlyggICEBgYKZl/fHjx4iNjUWlSpUE+3Lz5k1kZGRgzqI5qFGnBkqWKYmgoCDi72eKl6uX7LbW4uzZsxg0aBDatGmDUqVKIVeuXEYJ3mwNjfzGhHETuFbhibUmonWJ1orvr2TDVL8g/eZ/S8ctKOpZFF3KdCG2LHEnHVp3T66ygbQGsxAz6s3AgMoDiM7lujvOazgPWztsVSQEjK45mvhcvkmaRhjQC1fjPhkn21JES98KfZHHLQ96V+gtfbIIcoSeCn4VMK3eNIyqPgpDqwy1SCZja7OwyUKjv7nWODn4uPkQn2taMonG3cl0bNrKM4cL19NGCWV8yMNOuAIHLVnBtVUOSkMauO3HfTJOaXdk4e7kLivOdFrdacjtnBuzG8wmbiM3tr9KniqKBKXXMa8N/5a7RslRdBf2LIzp9aajVv5ahmP9KvWjuoaS+cP0u5KudZZ0Z9/bZS+6le1GfH7bEm0tcl85taS9XLKegGNNlMxffIKOJeLV5VKyZElcu3YN/v7+iIiIgEajwZgxYxAVFYV+/frh+vXreP36NU6cOIFhw4YZhGUHlQMCAwMxefJkPHv2DDt27MCvv/6KCRMm8N6ndevWqF69OgYMGIDbt2/j+vXrGDx4MJo1a4Y6deoY+vLmzRvcvXsXERERSE1NRZkyZZCRkYFNv29CoH8gDv59EL/99pvs7yv3HbVmvo8yZcpg9+7duHv3Lu7evYt+/frZLWknLTlCGKdxQbSGG5uSjZ4cF1MHlQOO9TiGHxvLc3fSZ6AmhftyKX3R+lfqL0t5oS/hQMrKFisN/x5SeQjO9T6HpkWbErcnzbIpRN+KfXG+z3mMqj6KuI1SZn46E2d6n5HtTq9Hbx0mrbfNZdwn4/BNnW8U3d9WmFqvbJk0qka+GkaulTSKANN+2ipmnEv7ku3RpkQbWbHUXGj6Xq9QPdlZ8/k2FiQlJe2NJS36pNeirfkqhdzN0sDKA3Gp3yUqt9SOpTpiat2pRnXKSVHy/j+Oemz4t9z9gFJFtx7a9XVApQEo51sO4z8ZT30v7lpT0qskbw1uPsr6lDX8+4uq4omhpNqX8y1nF8+XmfVnok+FPtj5Gf1YY0hj69ADKaZMmQJHR0dUrlwZ+fLlQ0BAAAoXLoz//vsParUa7dq1Q9WqVTFhwgR4e3ujvF95FMhVAC6OLhg8eDCSk5NRr149jBkzBuPGjcOoUfx7Q5VKhf3798PX1xdNmzZF69atUbp0aezatctwTo8ePdC+fXu0aNEC+fLlw44dO1CzZk0sX74cv636Dd2bdseR3UewaBF9zhClWDNsbsWKFfDz80PDhg3RpUsXdOjQAbVq1ZJumAXIETHjNPVnfV0zXTwtNYHzuZ2SwFcaxBaYurlKYannxH32pAysNBDXQq4RJ17Tw/1N+lXqR1Srm8vV4Ktmx2g3a0qFYjlYwuKQ1z0vLvS5YDOLvim9yyuz7MvF1hmc17Zai9a7W6N+ofpUZexM677aKmaci7OjM5Y3X674OrR9t+QGrVVx2+ZykEOVPFVwL/ye7PaFPOnj1fO658X+rvtlJ1EzRYkCnHY+c3RwxKDKg2TfTy5cbzO5c3CjIo3wJOqJrGojStZob1dv7O2yV1bbsTXHwj/OH13LdEXnMvylX/lQqVS4NfAWHkQ8IA5b4/Jzs5+x5u4au/zWenzdfDHr01l2u392QMma6qByQC7nXIbqP0VzF7VUt2RRvnx5XLlyxex4uXLlsHcv//vj5qxTsjs7O2PlypVYt24d73n6muV6ihcvjgMHhMuCubq6Yvfu3WbHJ02ahO7DuhueWZW8VTBokPg7YqosLVK8CB6GP0SVvJl5EZo3b2503pw5czBnzhzD3/o654BOyZ2SkYJfV/1q5C1o+h1N71uyZEmzY6b3LVWqFM6cMc4XMWbMGKO/pe4DADExMUb3SM1IxYvoF2bnWZKPXhhf02oNmpUmzzrbrmQ7TLuoq2cqZ6Koma8m7obfNTomtyTRwsYLpU+yIEU9iyIkMQQV/OhiB5UKKbs778b/HvyPuJ4ml2n1pkmfxAPX4iYnC3NgfKD0SR8xtAobS/F5uc/tZlkfVnWY7LZySn0VyFUAD4Y8oG5nWvZKriXOtHyLPaB1kbWkgsjd2fZJ3WiZUGsCPF08ZbvWylUI0oQP8LG4yWLDOptd3AgHVR6EPS8ys5rTVO7gCsNy38evanyFYrmLKU5Sakt83Hyokl5ycXF0kV35o5BnISxovEBWW3sztMpQbHy0kSpPSHalS5kushP1AToBPC4tDl4uXnYJx8qO+Ln5ITE9UdZaWSBXAYQmhqKIp/wks44OjopyO9kDF0cXVMpTyaoGmY/eTb12gdpUmmiuJUbOg+dzkyS9v2mcqK1dqw51P4Qr/a9QZxZWam2t4FcBS5otIc6ubQmMfmcZzzmrl974WBlVfZRsgUufiIgmKRgXJbH2tijpo0elUqFrma6Gv+VaxruX1SXjkZO3wlLQutg7OzijUeFGiu9bzrcchlcdrvg61sbD2QPjPhlHrUC1N9z4a9qEofaijE8ZXOt/Df/2+BeDKg/C2tbitXm59Crfy/BvuXOBq6MrPi/3uay4WKWJ/hi245s63+D+4PvoW9G2iV3tQSHPQryZ0klxcnCCn5sfE8Qp8HL1QlmfsrISDOZ1z4uKfhWp8t98LDioHKy672cjWAQ5D54vYRrpdeS4Y1kS0nINpmRHwZRrnZCzOeJT1NjbTepj5mKfi4hNi1WkkR1Tcwxal2gt25VZyTi35zsiN2Z8er3paFSkERoUamDhHpEjR5Eg1xOJy9+d/s5xGzx7VTjILpZxIDPb8tS6U6naccvB2VIxp6dLmS7Y/3I/GhS237ucXZDjxWRpsuOeSi72CnezJEre6XPnzlmuI4S4Osmf6+0R9pYTyFm7DUrqFayn+Bq7Ou2SPolhc5R6QHBZ33Y9TvifwFc1vlLaLYYAPm4+irWxjg6O1OXnptebjp+u/6TovgCdS6ulcXCQt1Fwc3JTlKHcEsjZ5Fhis5CTBPGxNcfiVcwro+oUtiQnPGuuwsEewribkxu2f7bd5vfNjjg7OqNFsRY4G3jW3l1hZHEKexZGmjqN2puUwTDl418FZXCm1xmEJIZQZWnlo3Xx1tSb/wGVBmDbk202jxe3FIVy0ScEsgdKM0xzLev1C9aXVzeWkeXpV7EfyvuWl11Dfmenndj6eKusTMRKsESManYlp31fpXxZ40u73Hdl85X48dqPWNJ0iV3ub0u4SerY+Mz6FPYsbO8u5CjyuudFRHIEGhXJDDHKDh4z9sqdw8g6WGqcMmGch3we+ZDPQ3lZm5bFW1K3mV5vOsZ/Mj7bue4c7HYQyRnJ2WZy4gorcrL5Tqg9ASNPjDS7FuPjwkHloMhiWCVPFSxqYvvyIW6OmaXQbJ0F3t7Yw/LIoKdViVZoVSLrZ6y3BNw1ho3PrI9pEkyGddnx2Q5ceHcBnct0hrNKF+qZlJQEd3dmcWZkbZKSkgDoMuIrwebCuL+/P+bPn48zZ84gJCQEhQsXxsCBAzFz5ky4uGSW5OETcNatW4evvsr6rsBrWq3B7dDb6Fiqo/TJPGQ3QRywfO1Za2MkjMvQbH1a6FMc6HpAVjIdBsPa9CzfEzuf6erb5jRlUc/yPbHj6Q7ZYUbZKVs1I/vBYi6zPp3LdEZyRjJVSUmGfArmKmiUINXHxwdhYWEAAA8PD6uuYX5OfohIjkAetzxISUmx2n0YHxdarRZJSUkICwuDj48PHB2Vzes2F8afPn0KjUaD33//HWXLlsXDhw8xcuRIJCYmYtmyZUbnbtiwAe3btzf87e3tbevuyqJp0aZoWrSpvbvBIERundvSPvLqxzMY1oabhCi7Wsbl1rEu71seF/pcgJeLl6z22aG+OCN7wVX4Mjf1rI+DyiFHZDPPqhQsqDNy6AVya6PSqhCrikUsYm1yP8bHg4+Pj2G8KsHmwnj79u2NBOzSpUvj2bNnWLdunZkwbqkvyWCY4u6Y6f4kd9POYGRZOPJ3drWMn+0tP4FSdgmXYeQMuOMxJySsYzCUoFKpUKhQIeTPnx/p6en27g6DwYuzs7Nii7ieLLEqxMbGws/Pz+z42LFjMWLECJQqVQrDhw/HqFGjBDMDp6amIjU11fB3XFyc1frLyP44OzrjQNcDUGvV2TIsgMEQg6tgyq4xqrbOUFs9X3XcD78vK9cHgyFGfo/8+LXlr0YlzhgMhjiOjo4WE3YYjKyM3YXxV69e4ddff8XPP/9sdHz+/Plo1aoV3N3dcfr0aXzzzTeIiIjArFmzeK+zaNEizJ071xZdZnwkMDdzxseKt6s3fmnxC1wcXeDsoCyxSE5hS4ctSMlIYco5hlVoXqy5vbvAYDAYjCyISmuhvOxz5syRFIZv3LiBOnXqGP4OCgpCs2bN0KxZM/z555+ibX/++WfMmzcPsbH8MR18lvFixYohNjYWXl7MDZnBYDCyOkdeH8GsS7Pwc/OfmYWawWAwGAxGtiQuLg7e3t5EcqjFhPGIiAhERESInlOyZEm4uelK7gQFBaFFixaoX78+Nm7cKOh+rue///5D48aNERISggIFCkj2h+YhMBgMBiNrkKHJYHG1DAaDwWAwsi00cqjFdjx58+ZF3rx5ic59//49WrRogdq1a2PDhg2SgjgA3LlzB25ubvDx8SG6h17HwGLHGQwGg8FgMBgMBoNhC/TyJ4nN2+bmh6CgIDRv3hzFixfHsmXLEB4ebvhMnzn90KFDCAkJQYMGDeDu7o6zZ89i5syZGDVqFFxdXYnuExkZCQAoVqyY5b8Eg8FgMBgMBoPBYDAYAkRGRkqW5ra5MH7ixAm8fPkSL1++RNGiRY0+02sPnJ2dsXbtWkyePBkajQalS5fGvHnzMGbMGOL76LOzBwQEZJv65Jagbt26uHHjhr27kS3Q5xUIDAxkoQwUsDFGDhtj9LDxRQ4bX/JgY4wcNsboYeOLHDa+5MHGGDn2GmOxsbEoXrw4b7UwU2wujA8dOhRDhw4VPce0Frkc9K7v3t7eOeoFd3R0zFHf1xJ4eXmxZ0YBG2P0sDFGDhtf9LDxRQcbY/SwMUYOG1/0sPFFBxtj9NhrjJGEYmfPArQMQWi8BxgMObAxxrAmbHwxrA0bYwxrwsYXw9qwMfZxYbFs6lkNlk2dIQUbIwxrw8YYw5qw8cWwNmyMMawJG18Ma2OvMUZz34/WMu7q6orZs2cTJ3xj5DzYGGFYGzbGGNaEjS+GtWFjjGFN2PhiWBt7jTGa+360lnEGg8FgMBgMBoPBYDCyKh+tZZzBYDAYDAaDwWAwGIysChPGGQwGg8FgMBgMBoPBsDFMGGcwGAwGg8FgMBgMBsPGMGGcwWAwGAwGg8FgMBgMG8OEcQaDwWAwGAwGg8FgMGyMk707YC00Gg2CgoKQO3duqFQqe3eHwWAwGAwGg8FgMBgfOVqtFvHx8ShcuDAcHMRt33YRxhctWoS9e/fi6dOncHd3R8OGDbF48WJUqFDBcI5Wq8XcuXPxxx9/IDo6GvXr18eaNWtQpUoVonsEBQWhWLFi1voKDAaDwWAwGAwGg8Fg8BIYGIiiRYuKnmMXYfz8+fMYM2YM6tati4yMDMycORNt27bF48ePkStXLgDAkiVLsHz5cmzcuBHly5fHggUL0KZNGzx79gy5c+eWvIf+nMDAQHh5eVn1+zAYDAaDwWAwGAwGgxEXF4dixYoRyawqrVartUGfRAkPD0f+/Plx/vx5NG3aFFqtFoULF8bEiRMxbdo0AEBqaioKFCiAxYsX48svv5S8ZlxcHLy9vREbGytbGI87dgyhi5eg6C+r4F69uqxrMBgMBoPBYDAYDAYjZ0Ajh2aJBG6xsbEAAD8/PwDAmzdvEBISgrZt2xrOcXV1RbNmzXD58mXea6SmpiIuLs7oP6W8nzQZGSEheDd2nOJrMRg5nYzoaKgt8F4yGAwGg8FgMBgfA3YXxrVaLSZPnozGjRujatWqAICQkBAAQIECBYzOLVCggOEzUxYtWgRvb2/Df5aMF9emp1vsWgxGTkSTmooXDRrieb360Go09u4Og8FgMBgMBoNhd+wujI8dOxb379/Hjh07zD4zzYKu1WoFM6PPmDEDsbGxhv8CAwOt0l8Gg0FPRmio4d/ajAw79oTBYDAYDAaDwcga2LW02bhx43Dw4EFcuHDBKNNcwYIFAegs5IUKFTIcDwsLM7OW63F1dYWrq6tV+qmOjrbKdRkMBoPBYDAYDIZ9UKvVSGcesAxKnJ2d4ejoaJFr2UUY12q1GDduHPbt24dz586hVKlSRp+XKlUKBQsWxMmTJ/HJJ58AANLS0nD+/HksXrzYHl1mMBhKsH+eSAaDwWAwGAwAOlkkJCQEMTEx9u4KI5vi4+ODggULCnptk2IXYXzMmDHYvn07Dhw4gNy5cxviwL29veHu7g6VSoWJEydi4cKFKFeuHMqVK4eFCxfCw8MD/fv3t0eXGQyGhVA2ZTEYDAaDwWAoQy+I58+fHx4eHooFKkbOQavVIikpCWFhYQBg5MUtB7sI4+vWrQMANG/e3Oj4hg0bMHToUADA1KlTkZycjK+//hrR0dGoX78+Tpw4QVSvjcFgZF20YAI5I2uR5u8PdWIi3KtUsXdXGAwGg2Fl1Gq1QRDPkyePvbvDyIa4u7sD0IVQ58+fX5HLut3c1KVQqVSYM2cO5syZY/0OMRgMBiPH8qp9BwBA2Qvn4Zw/v517w2AwGAxroo8R9/DwsHNPGNkZ/fhJT09XJIzbPZs6g8HIYbD4cUYWJf3dO3t3gcFgMBg2grmmM5RgqfHDhHEGg2F9mADOYDAYDIbVSH//HnHHTxB5nzIYHwvHjh3DrVu3AAAnT57E9evX7dwjepgwzmAwbAvbKDAYFictIADqhAR7d4OYjOhopAcF2bsbDMZHw8tWrfF+wgTEHT5s764wshH+/v5QqVS4e/eu4DkbN26Ej4+PzfpEQ+XKlTFo0CBcvnwZkyZNQqVKlezdJWqYMM5gMBgMRjYm9fVrvGrbDi+aNLV3V4h50aAhXrZshYzoaHt3hcH4qEjKhpZBRs6iZMmSWLlypUWuVaJECYwbNw5NmzbFihUrjBJ9nzt3DiqVKsuXr2PCOIPBsC3MMs5gWJTE/y4DALTJyXbuCT1pL19St8kID0fUtm3ZyhOAwbAVzE0955CWlmbvLmQJRo8ejYyMDLRp00ZWe3s/RyaMMxgM28I2CowsijY9w95dYBDwpmcvhM5fgJAffrB3VxgMBsNmNG/eHGPHjsXkyZORN29etGnTBsOGDUOnTp2MzsvIyEDBggXx119/AQA0Gg0WL16MsmXLwtXVFcWLF8ePP/5o1Ob169do0aIFPDw8UKNGDVy5ckW0L+vWrUOZMmXg4uKCChUqYMuWLUafz5kzB8WLF4erqysKFy6M8ePHG77D27dvMWnSJKhUKsEkaP369UPfvn2NjqWnpyNv3rzYsGEDAJ3iacmSJShdujTc3d1RrVo17NixA4DO/b5FixYAAF9fX6hUKkP5bL7nyOeuHxMTA5VKhXPnzok+C6XYpbQZg8HIWTBNPT1p/v5IfvQIXh07ZouMrxmRkUi4eBFe7dvDwc3N3t2RReiC+Sh96JC9u0FPNnu/NCkpmf+WYZHICA0FAMQdPYZcTZtm6zHHYDDsj1artZtnkcrdnWqN37RpE0aPHo3//vsPWq0WUVFRaNq0KYKDg1GoUCEAwNGjR5GQkIDevXsDAGbMmIH169djxYoVaNy4MYKDg/H06VOj686cORPLli1DuXLlMHPmTPTr1w8vX76Ek5O5qLhv3z5MmDABK1euROvWrXH48GF88cUXKFq0KFq0aIHdu3djxYoV2LlzJ6pUqYKQkBDcu3cPALB3717UqFEDo0aNwsiRIwW/54ABA9C7d28kJCTA09MTAHD8+HEkJiaiR48eAIBZs2bhwIED+P3331G2bFlcvHgRw4YNQ548edCqVSvs2bMHPXr0wLNnz+Dl5WWoDc73HO0JE8YZDIZtyWaCg73Q175WOTrCq317O/dGmrcDBiLN3x8pDx/Bb/AgxB4+DL8BA+Do7W3vrhGT+oLeZToroE3PXq6K6tg4w7+VboCDp89A/PETKLZurdJuMRg5npQnT5Bw4SL8vhgKBxcXe3fHZmiTk/GsVm273LvC7VtQUdQ7L1u2LJYsWWJ8jQ+W6alTpwIANmzYgF69esHT0xPx8fFYtWoVVq9ejSFDhgAAypQpg8aNGxtdY8qUKfjss88AAHPnzkWVKlXw8uVLVKxY0awPy5Ytw9ChQ/H1118DACZPnoyrV69i2bJlaNGiBQICAlCwYEG0bt0azs7OKF68OOrVqwcA8PPzg6OjI3Lnzo2CBQsKfs927dohV65c2LdvHwYNGgQA2L59Ozp37gwvLy8kJiZi+fLlOH/+vOHapUqVwqVLl/Dnn3+ibdu28PPzAwDkz5/fLAGd6XP09/cXfuhWhrmpMxgK0aSkIO7EiWwTv5j64gWSbt60dzcYhCTfu2/vLhCR9mEhiz91Cm969ETEL78ieM4cu/aJBHtrxOWSePUqUt+8QUZEBMKWLrN3dyjhPHMLeH0knD2r+BoMBgN40/1zhK9YgagP7s2MrEedOnXMjo0YMcLguh0WFoYjR45g2LBhAIAnT54gNTUVrVq1Er1u9erVDf/WW9jDwsJ4z33y5AkaNWpkdKxRo0Z48uQJAKBXr15ITk5G6dKlMXLkSOzbtw8ZGXRhYM7OzujVqxe2bdsGAEhMTMSBAwcwYMAAAMDjx4+RkpKC+vXrG9zdVSoV1q9fj9evX0ten+852oscYRnXarWI+fsfuFWuBPdq1ezdHcZHRuiPCxHzzz/waPApSnyYDLMyrzt3AQCUOXUKLkWL2Pz+6sREOOTKZfP7ZldUTo727gI1mvh4ACBW+qjj4hCzdy+8OnSEc4H81uyaOdlQGE959hwBQ78AADjmy2vn3gAxe/bApVRpeNT6hLpt8sOHyC2xSWTYH01KCmL+/huezZvDpXhxe3eHYWVSHj+xdxdsisrdHRVu37LbvWnIxbN/Gjx4MKZPn44rV67gypUrKFmyJJo0aQIARq7ZYjg7O2f26YOSVKPRCJ5v6lqv1WoNx4oVK4Znz57h5MmTOHXqFL7++mssXboU58+fN7qPFAMGDECzZs0QFhaGkydPws3NDR06dDDq2+vXr1GqVCnia+oxfY4ODg6G76EnPT2d+rpyyBGW8YRz5xAyezb8e/W2d1cYPKS9e4+QhQuR9u6dvbsii5g9ewAASVeu2rknwiTduIEnFSsh4eIlw7G0N2/s0pfA4SMQumgRMqKi7HL/bIdj9hPG9ahAZvUMnjkTYT8tRsDgwUgPCkLIjwuRFhBg5d59IBsK46nPnxn+rQ6PoGqrSU1F6JKlSLpxwyJ9Sbx+HcEzZ+Ft//7kjTjPPDWHbfptgVarRfiaNYg7ccJi14xYvRqhCxfhVbusHzKT48mGc5q9UalUcPDwsMt/lsgJkydPHnTr1g0bNmzAhg0b8MUXXxg+K1euHNzd3XH69GnF99FTqVIlXLp0yejY5cuXjWp8u7u7o0uXLvjll19w7tw5XLlyBQ8ePAAAuLi4QK1WS96nYcOGKFasGHbt2oVt27ahV69ecPkQPlG5cmW4urqKfi/9uST3ypcvHwAgODjYcEys9rolyRGW8VQZpVMYtiNwxAik+fsj8fwFFP75Z6S/fw+vdm3t3S1yssHC93bQYABAICdZhjYtlbi9Oj4ecceOIXebNnDy9aW6d+rLl4g9ciTz7xcvkPriBdKDglD011+prpUTUTmQCeMJFy9B5eKCXPXrWblHlif+3HkAQNrbt3jZUmcljT91CuXOnrH+zbPB+2tJIv/3P0T99Rei/voLlZ4qF4TTlMbZUW5E42VmtdVqNIg9eBCuJUsi5flzeLVrl63yGdCQdPUqIn5dDQDwssBvDACJ1z8ob3LY+8JgZBdGjBiBTp06Qa1WG2LDAcDNzQ3Tpk3D1KlT4eLigkaNGiE8PByPHj3C8OHDZd3r22+/Re/evVGrVi20atUKhw4dwt69e3Hq1CkAwMaNG6FWq1G/fn14eHhgy5YtcHd3R4kSJQDo6oxfuHABffv2haurK/Lm5ffwUqlU6N+/P3777Tc8f/4cZzkhSblz58aUKVMwdepUqFQqNGvWDPHx8bhw4QJy5cqFESNGoESJElCpVDh8+DA6duwId3d3QzI4U9zd3fHpp5/ip59+QsmSJREREYFZs2bJej605AjLuK1Jun0b4WvXQksRHxF/+jSiPsRF5DT0m7m0t2/h37Mn3k+YgORHj+zbKRuS+vIlwlatgvqDa68QCRcuIHLDRovdV0vhfhM0YwZCfpiNd1+Pob7P606dEbnuN7PjKY8eU1+LhrTAQIStXInkR48QtnIl0kP5Y5+yPI7S03RGdDQCR45EwJAh0KrVUMfGImzVKqS+toP3A1e4UqDxz+Bop8VIvH4dEb/9Dq2IO50o2VK4kP9c0974W64bcuE+cwfybUh6cDDefTVa1i3jjhxB8PQZ8O/bDyE/zMbz+p8iZt9+WdfK6mSEh9u7C4qJ3LgRCefP27sbiD9zBlFbttq7G7YnW86LOZvWrVujUKFCaNeuHQoXLmz02ffff49vvvkGP/zwAypVqoQ+ffoIxoOT0K1bN6xatQpLly5FlSpV8Pvvv2PDhg1o3rw5AMDHxwfr169Ho0aNUL16dZw+fRqHDh1Cnjx5AADz5s2Dv78/ypQpY7BICzFgwAA8fvwYRYoUMYtTnz9/PubMmYOlS5eicuXKaNeuHY4dO4by5csDAIoUKYK5c+di+vTpKFCgAMaOHSt6r7/++gvp6emoU6cOJkyYgAULFsh8QnTkCMu4rcsCve2vSy7glCcvfPuQuca/G6MbIB516kCbkoLo7duRb/I3to+fzCKkvfGHe5Uq9u6GxYnashUZ4eHIP3mS4djrTp0B6DZQhUVe/MBRXwIA3KpURq56trV+JpzSuQEl37mD9NBQOBcoYNP7y8G/X3+oIyIQ+dvvAIDECxdRau8eO/eKHhWBsKKJjeX8oUHI3LmIO3oMkX/+D5Ue2DYBnJEQTTr3Ktj4BQzWWQCcixSGd+fO9Bdgm05lyFlfOc884cwZaDUaonEef/IU/b0+kHz3ntmx4BkzkLtli4/PQm7hPU/EunVIuW+7eSTp5k2E/bQYACzivaEEvQLao05tuHFccBkMeyBW7zo5ORkxMTG81m4HBwfMnDkTM2fONPusZMmSZolMfXx8jI4NHTrUUKNbz+jRozF6NL9ytFu3bujWrZtgXz/99FNDqTMpKleuLJhoVaVSYfz48YYa5nx8//33+P77742OCT3HSpUqmdVXt0WS1xxhGbdXttw0gmx+pmSER8C/T1/EHjiIYJnuEXEnTiDuuOVixayFVqNB1OYt/B9aUX+S8uQJIjdupPJc4JIeGoqI9euRER1N3Tb0xx8R+ccfSH3xwrxfDx4SXSMjJIT6vrzIfC/0bsSKbw/rvJfq2FhErF8PdYRxLG3KY+ta4q2GjI110p27un/YKPmIYiwwR6f5v0Xc0aOIP0OWWVuTnIzI//0PqXa0FKvj4xGxfj3S37+33U0tvR5a4HrxhLHNoQsXKr6XKdya59mBuGPHEH/GBuEbH8iIiED4ql9sdj8ASA+20BpnQTIi6HIzMKxH0s2biN65M9tWwlBKRnS0UfUejUaDoKAgfP/99/D29kaXLl3s2LusiTohASnPn0OdmGjvrvCSIyzjNBuduBMnkPLgATxbtFR8X3VcHELmzYd3l85wr1mTqI02NXNjICcWT5OUhPfjJwAAct24DsfcuamvIRetWo2wn5fDo05t5G4p/fzi//3XKpsrKd50/xwAoHJ2ht+HEgk0BAz9Amlv3iDp+g0UX/+HrD5o+GrryrRmRG3fDm1qGvJ8MVRWe2oIEmEQYaV1NGjmTIMlPzui1WgQvny54e+kW7el21hwUxLx229wyl8AGWGhcMpfAD6fd5d/MRt6JWVERCBizRoAQMXHjyQtreG/rtaV77FAWbDIjRvh4OoK3379qNqFzJmLuCNHELVxE8r/d0m6gZ1JDw5GxB9/wG/QILiWLg1tWhpCP1gwqTAZr/ZM5hgyfz7yfvmlTSutqBMSEb5iBbw6doBHbfLaxhlRUXg/aTIAoOKjh1BRJHdMDwpCxPr18Bs0GK6lyTMPa1PJc4tYDG1myElGRAScBOJJbUqOE/yy7vd9O1BXc9qlRAnkatDAzr2xLZqUFINM4161KgAgICAApUqVQtGiRbFx40Y4OeUI0Y4KQzjsmzdwq1LF5h7TUuSIXyxm5y7ic/WCbOT6PxXfN3bfPgBA9PbtxK5WUQpjgrUcQSnh3Hl4d+6k6Ho0xB09SpUYyN6J9SL/9z/49uqF91OnIVfDBvDtLR1SkPLkiSELeeLFi7qDhIu0kcCkZCLgXEeTlobQefMBAN6dO/FuWrKDlwQpmrQ0BH07FR716yHp2nV4NmkMn549jc5J/O+ynXpnGeKPH0fkn/8z/G0YZzTIHF4pz54jfOUqo2OKhHFSRN6hyP/9hdQXL1Bo4Y+iArY6JibzchkZUH3IoipE8i3LlLHJiIgwuNR69+gBB4n7ckn84A6njoyku6mF5g9a3o0bj5SHDxGzYyc8mzWDysUZ2qQk6uukvX0ruw+WJuHUaSScOm1Td+iI1asRvW0bordto7qvJi4u8w+1WrjSAs9v/G7sOKQ8foy4I0dR4fo18s7aYdOqVWcK4+r4eERv3w51bBwKfm+bZEq8fSLMSRF/9ixi/v4HhebPyxpKhI+YtLcBOU4Y58v1w+dmzshe5Ag39eyE0vJe3M1q0LffSp4ftXUb3k+dqkuApPBlTreU+zRsE+efERSMmH37Ef/vvwj5YTZRG71VHQD1JiXaKAmMedv09+8R9++/iNq0SfQ6Rr8TZ2LWpPBbMN5PmMDfn23bRe9jdWSMt5i//0H88eMInTcf8cePI3jW99KNshkZCpKqAEDitevICMqM2066fQdhK1ZCk5Ym2VYTHyd5DhUK3+PwX35F2NKliN2/H0nXr4ufzBlPcYcOK7ovDUZeLhRJ5LTp6VBns/J+KZzEmgnnz8uO4X43YaKFekRG9I4diD10SHb72AMHEL1zp8X6ozgDPejtlvowHSOBngR7WJA471HcoUOIWLsO0du2IS0wULCJVqNB+Oo1SLj0n0W6kPLkCcJ+/plzA7In/m7010g4e1aexwiDjixm3WQw5JLjhPF3kyYh+SF9pu7Eq1fxfvI3FnOnSzh/Hu+nfGueQVuGgBJ/7hz/tSRICwhA6IIFiDt4COErVyLxcqZFMeKP9QhbvoL4WlFbtyH85+XSJ3KwhybPVKuojstMfBX51waELllqlfumBQQYueRHb9uGyI0bEbp4ieGYJj4e7ydOQuiin3hjyvlQYmxPunkT6QoFP0XI+P3VsTHSJ2XhBTr5wQO8mzQJae9EQmd4+k/zPgaOGGH099v+/RH5+++SXjeatDQE8SR3UQTpTyEwFiLWrjX8W5PEE9ohcA1NgvFcGLpkqXklAoFxEjJvvk3mpugd5sJdWkCAbo1SUE0iPTRU/ATOdwuaOROxBw+SX9xC75aGcq1SQnpICELmzqMXQj+gzchA0LTpCJkz13JZyi0xvigUP9z4UlJSX7/Bu0mTiNciS6COi8P7Kd8i4cIFw7GItesM/9aKKBTj//0XEatXm81/tOj3em+6f27sIUn5k9k1xlzG8Erz98e7SZmJZcXmwLh//0XQtOnQ2COEIYeT3RS4DDJyhJs6l/hj/yL+2L/ULmkBQ7/Q/cPREUWWLhE/mYDAL7/SXc7PFwW/+y7zAxmLtL7Ui1PevMjLk7Zfq9Xi/cRJcC5cGAWmTTUc57p1AkDGh9JP2rQ0Q8yq74D+kpmzw35ejsj1642ORaxbh6Tbd1Bs7RqonJ1526WIKUVkbvoSLl5ExOo1KLTwR7iWKWP2ecz+/Sa3ybxP2BLd7+rzeXe4li2LjPBwvJswEb59+8CbLyEGRR/VJsneYk36YUpGVDRchT7UAumhYXg/cSK8uypM1PExejaJvEOpr17xjgtdMy2Cpk6DY25PFPzhB6t0zb+XLhQiPfAdSu3+R+As83FleB/79IZzkSKy7i2WUDJo5kzEHjgIyExqKIY6NhbvxoyFV6dO8O3bh/8kCwgnWk6cKffdTHn+XBcbDhDlVYjevh2527SW5/5I8T1S35j/Hu/GjEHqi5fSa5TI1KNJlHIbz+xj7J69iN2zl39+48PBgUoI5BJ7+Aiit21DkZU8SiUrKj80ChP2cMtraWS45FsNwt/h7eAh8KhTx+iYVquV9D57278/1DExiD/2r+wucok9eBDRO3ehyMoVcM7PXyUmfNUviDssz6slLVCZV6Eew17PFK3M0ok2gjvOY/fuReGFP0q2SXn+HMHff49848YjbMkSpD5/TnSv9xN1Qnvqy5dQubigyMqV9qn8YwHdoDotDanvg+CUN0+2qKpAa3TjQ6vVIj0gACo3t2xRGQcgm7PsganSSpOYiLR37xGxZg1SPpRxIyHHWcaVkh4UZNHrZViw9nF6aAigNt9Mpzx8iPjjxxG1YYP4BRx0A12TxrEeE2zOTQVxQLeoJl68iOeNGgu6jWlEtPXcmDEaAkeOQvK9e3g/cSLv5+ooY6E4bNnPZudoklM+fLYMybdvI2jqNFl9MYJ2sylxftiSJUi+cwchc+ZmHrTDRBX+yy+I2b1bXmMZG/CMMGWWKX3yIz7S371D3KFDiN6+w5BpPy0gAEEzZ8qq1x0wbBieVKwEdYK5MCDqpiryO3IzP6e+fImgWbOIQ1tiDxxAWkCA2fGM6GjE7tkr+K4Hz57D+x30JN+9i+Dv+ZUXKqgQ8ccfSLp5EyFz5hD1Uzbc4cS1kssQxtSx5FZUWjf19NBQBM2ahdQnT42OR27ciNQXmXk0gr//QVbFBpWD+fiJ3rEDEevW8ZxNe3H5c0zQlClIvnMHL5s1V94PGgj7HLZiJa81UF92VI82PR0hC360bUbzqCgEf/89km7ezOyHhmz+TLp+3cjDBADSCWL2TZX1SgmaOg3Jt28j/GfzNVdPOrcsIi3W9mYhGEfceTLp6lVE/PY7orZuI7p8RnQ0gr//AUl37sjqnlZGYtX348Yj5d59BI4Ywbs2SJHy6BGS79xB2FJlHoUpz54haNYsxB48+GG9IfPkUDJenJ2doY6JQdybN9AkJ4mGQFgSdVwc0oOCDXONJikJae/fy67uQ4rhPunp0CQmQh0fbzlPHyujVauR8ugRUl+9gjohEWnvg2SNd2uQ9EFB6/zB6Pi6aze86doV8SdOIHrrVrGmRnz0lvH3AoJU3MmTiNn1Nwr/tMiuSTbijx9H+K+rLXOtD1Z/U/gSPug+MF68Uh48BLp1A425VGqjq4mLQ+CIEfxWHgsvntzJNPXFS4QuWoQCM2YYn8SzUTXjw6KrjpPQQIoszpF/bUDy/fso8vMyqBwdZbm9pgcFIXjW9/D7Yig8mzTJ/ECrRQafK6qsjbJ4v8LXrEGEwPhMfvTI4EJomkTNkmi1WgTP+A7ORYsiZhd5MkY+Up8/R8CwYSgwYwZcy5Uzvk965mIYOGYMcrdogcgNG5D+NgCJFy6i3EWd62RaYCBCZs+B3/Bh8GzUiPc+6e/fI/GyLjlXxLq1KCCSv0F3vdnIM2IEcjVsKP47coQ9/779oElIQMr9ByiyaqXUVwcABIwcibLHjwtek4+YXbvg4OaGAjOm837u31c8g7hGRJC3JClPjEvXpTx+jNClS5FbTmUMCitY5J+Zrqwk77mQMBpmEmMa888/0KalofDin4yOq+PjEfTNFOEb8IyfkLnzAABen30m2T8hMqKjJUvlBX41GkVWLIeDuzvdxS0sR2VERyNo6jSdl1PFikRtIn//HZ7NmsKjVi3hk1QqxOzZg+itWxG9dauspG9Jt24ZWdvVMTFw9PERbRMyfz7ij/2LmH84ik+N8GZUmyG+UbXnRpZvXU19/RqhCxYg+ZGS8pPKB1GwQoVhxDpjpUf4ypUAdB6GUla90IWLEHfoEGL++cciyQRD5i+QTHiXwU16aVrij+JxKg07edO1GwAgdvceAIDK1cXYY1SAyHW/Ib9AThwp1IGB0Ow/gIgOHQBfH7ipVFBJlDnUqtVIDwmBg6cnnGRa0VM+KOKdHFRw8vFByodExg6pqXApXFiyfSpnvValpCAjNhaahAQ4FywoWl3BcJ+UFDj6+CD9w3WkvjMfGTEx0CQmwrlQIdGkqpq0NGSEh8PRxweOuXJR38dwv6goZGg0QGIi8PoVAMBRnSHoYaNJT4fKwcHoeXCfG1JSFFvZtVotkpKSEBYWBh8fHzh+uFe6zLxfH70wnnD6NDx5Buj7cboC8aGLl1jE7RzQ/Tjvvh5D3U5fjsfeRG/bppu8ORo6qb1l5MaN1umMVou0d+8QOOpL+A0dIprpPO7f4whfsQJ5vvzS6HjUps3IO2YMHL28ONeVvnXAsGEof/WK2aZWLF7NFL3Le3zHDvBq21aG4kGL4FnfI/HyZSRevmy0OKe9fWtkITEc9/eHc6FClLfRfvifFu++Gg2HXB4owimrJSSIA0DQNHGPgajt2xUnidOmpeFprdp07tMSk2zi5SsIGPUlyp0Vtmwlnr+AxPOZcYtcDXLQ9BlIvnXL7HfhwrWWpn9wn0znesFwxkPwzFlIun4diZev6K4n0v3Xnbsgd5vWKPLLLwbPElLXQgBIf8tj/SBYlGRbDSzqrSH+Dmk41uzYQ4cRukgnxCZduUp/JwrPnHRO/H/Uxk2I+/cYiv/1F+9GgdbamOpv7pER8dtvom3E4jg1SUm8CgNNWppkFvjwVatEPweAhHPnELV1K/KOHGk4FjJvHlKePhNtF7pgAbw+6wgnX1/JewjBFWrDV65C4sWLSLx4EY4U18wIl4jzVamkY/IleDtgoNHf4avXoOAs8VwNaS9fmR8UU6KJCOr2wCxfgwnvv5mC1CcEAqjYfGIyrtPfv0fAyFHwGzwIvn37Sl46LTBQvPKOxBoeMGIkEi8JlCfUaiXnQrEwIjlEb9uGPF+OEhRYAIt4eZsRf/Yswn5ajMJLFsO9Rg3J8/mSOaZThBxotVq8GzcOKpUKRX75hVjIUickwungQWQACGveDCpnZ4N1U7BNXJxh3XUuXBjq+Hhok5PhmDevZClNPekf9hIOKSlwjI42/I2oKDgTxOCnc/Yizs7OBm9dh8hIwVLGWo0mcw8TFQXHuDhD7LnUd+aiSUvThVx+UOY5REXB0dNT8PyM8HCDMdCZQNEghDo+3kzho4qLgxOPMVCrVn8wVqngXDhzP2z03JyczN9HrRaatDSonJ2Jf0sA8PHxQcGCBYnPF+KjF8aloE6GYDIhR/yxHhkR4Sj43XfICA9HwtmzyjrEda9MSUbQdzPhXr0a72KiSUxE0CxxzWd6aBjejRfQHPIsLsn37hlvNiQsRHKT4kijRejCRUh7/RohP8wWFcb1LunBPJrUuGP/IvHqFRT+8Uc4eHgQCcWauDhd1mCTc+PPnqP6BgAnflNGnGVGeKbwphcsAJ0Fh4+AL4bRa9Q/fMf09+8N1ppCixbBwVUwYt0A7waRg77kmhAZYWEImTcfBX8Qzogef/48lSCu1WqJSi1lmLi3pb55g/cTxou2idq0CX5DhpBlO+eZzCNW/8rfF9NEPxKbifiTp5Bw2qSOuhKjEMnmRWacsDVDJ0J/WgxHn0zrBNdLJ+XhQ0XXDpoyBdCoJWOpIzduRPLtzDrwEat1yquIX39Fofnm419JYjitWo3g739A7N69oufFHTkKt/LlZd0jbPkKqJwckW+8+btAWiJUE2/sYhq9fQdRuxcNGqLE9u3wqPUJ0fmmRP7vf8j/zTcAAHVUZqk403wdirDCeCYpXciXRE1oLEX++SfC10qEJNggQWHSnTu68qF9+iJssXhmcaUVJADz5/GyVWsAQMicuUTCuKAHISGCgriuc9IXUPibpPEoWuOOHkWeoUOFG1EoN0h5N/prAEDAyFGCJfTCVq0CNFrkGT4M8aaeWlL9MiH855+RcEq3Hqqjo+Hk50fWUAWotFo4HzgA7fHj0Pr4oMiGv+AiYtAIX7sOcR+qMpQ6dhSvOnSECoBXzx7IO3w40W1ffTDY+Q4cAL8BAwx/OxUsiBIb/iJub+jDh7+9unZFvq++5G0TvetvRH0wnDkVLoy8o0cjZMGPhmuQ8qpDR3BNm74DBsBv4ADB8/1nz4H6gxCs30H4DR4E7+7d4eDmRnzf4PnzkfTB05ALX9/jz55F2IdEzNzPuc+tyG/r4FKihFG7uBMnEL5iJRwLFECJjRIhvR9wdnY2WMSVkuOFcUA3CQd++SXcqlWXPDf59m08qVgJAFDxwX1DYiUHV1fE7BHeJJFYHkxRh0cgdu9exO7dy7uYRP7vf5LJVUJmz4aaIqunf5++KLxsGVU/5aDVasUne63W3G0KmQsuqfYzZLauZNnL6zfgXLQI+SbVpG9arRbaDJPFWqWS3lzrhRgZMePcmECpcmfmzQmTXWg0SLh4Ee85bq9BU6ag6K/8giP3+mKIvQtcordvh3PxYvAbMgSqD8/TqN+U7pTJPB4DJLwb/bVkuaHQRT8h8cYNpIuV1zH03/zZc93gjcI7ON83+e5dSSUGoKsZbFOUbBR53iXub0wuoGa2SXv71rC5sBZBU6fBKX9+5Pr0U6PjMXv2InrnThRdvdrMtdxwzv4DvMK4mBuhFG969iKzHprkDTF6vlot/5qh1SIjMhKRf/wBAMgzfDgcOG6FNEqEyD/+QN6vR1NttvS87d/fTKFIOpclXPrPIIynPLZMzXDz7y1PGI8/cwYRq9egMI8Xnr5+NW2CovSAAF5PAr48KPbgbb/+AGAQlEQh/N4R635DRkgIiv253lxhLDJGk27eRMjChSj4/ffw+MRc2RP5v7+Mwk1oIPrdNBrhmvD663A0qm+HfgH3T2oalGKm109+8BDBs39AgW+/RfLdu0j87zJSeBQ2YT8tNhPGid8nmpwIPNcTCmFUx8cjcp3Ou8fn8+7E1xMi8s//GbUj+X7q+HjD+AR0rtqqkBC4OTrCRWTeck5KgsMHRX7cb78Z/u0QHAw3wvlO38Y5OQVubm6Z11CB6BoOHEMCt71zQoJg+4zr1w3nOTo7w5VzHdJ+Z0RHG90bAJxTU0TbO4aFQWtS8jhm8RIgIACFZouXE1bHxCBq82Z4d+mClD17eROc8d07Va0x+m6xBw4AKpVR39937Wa2zoQdOgyH4GBoRH7L999ORXpQEIosW0rvhSoBS+CmUiH+3DkkXr4iaHEUIphjlY5c/6eolT3uKJn2iSaWiyT5Qvp7+viFoCmceEQraNDTQ0PxsmkzJN+7J3ySVgs+c9+7MWPxpkcP6mQX6shIpNy7bxxzJwXnu79s0dKgbeN+7t+zl8Q1MjdaNAR8MQxpr8Qtz0JkREXhZfMWCF2yVFKIf9mqNQJHjjLycIg/eUqyZIlpAqCk28ZJZ4IpSmSF/bQYr9t3wOsuXfGiQUNE//0351O6zW9agDx3atLkNWIby/izZ/Hi0wZIOH8eSVyLgP63dzLejKXrFynOV/QfNJioH5aEaGN2/rzsvAfc9yh08RK8bNHSkJgs5elTvGjIH3dvTuZ14mV6IBklWyOAL7Ny8MyZSHnwAKELFgg3TE/nf14U7m8AjKZAIkGc9xqZF8mIFFijtFqjOfVZvfpG5aVo14GYD7GfSksfBc2ahaeVKiPwq9GIlagdz00IqkmTeV/O9wwcOxYvm7cw+vhV69ZIuiZR756Hd1+PQcrjx/xeaioVtGlpeNOlK1X9df8+fZH84AF1X/T3zEqQKiHiDh1C0o0bBuukEZwhmvLMOCzi7cBBSH38xCxEQE/Y0qWyPCg0ycl41b49gr6TWO+ILOOZ/0y6ehWR635D4IiR8O/b16Cw0RM4ciRSHz9BwBfDEL7qFyTdvAlNbCykCBwzFm8+5+yfrDkOBL4zd5551a69RW+ZfPcuXjRoaFY1x5Tg72ZShR0a4DyvyN8y5YVES9S2JwiNMl1TTBWtgu24657MPX30DnMPp4hfV8tKMiqloNNqNHjeuAki1q7Dqw4dBc/jSyzLTWCqTkhA0LTpFknCnBEejrhDh5B86xZeyslDIwETxkEXC8wl9gB5fVZtejrUcXEIGDZMNPu0kED/okVLMwGUZHOsuF6uSPuYvfsQtWkz1eUyIiPxsllzSUWCVqM16nvqh+QTCWfOIPXxE6Q8eQJNWpqhRJzFMVmkMkJCzJOmfcjwKIbhOxBmvrUEUVu2ICM0FFF//WXk3k6DNj0DgSZZhLm8at/B6O93H0rqhcybj+C5c/maiJL29i1Snz+HOiYGIT9wNKaUm4VIAjcva/Fu9NdQx8Yi8MuvjLLcx588iScVK5nFwb1s3gIZERHGG1GFrpIkSHkACMGbNFAKk01k1IYNyAgJQfTWbUi4cAFvunWXtQkWskhLEXf8ONKDgvB28BAk370r6xp64k+eFP2ct1qEjPk44eIlvKVQ0kRt34GAkaMyFQ+c3yBE4N18O3CQsXJUrUbgqC8zw6Ao+61Jlh+ew0Wf0Cnh3DkEiSRBBID0wECkv9fF76sURsNmREQg4dRp3jHPDUughVfBqgKSbt9G6osXBpddrVaL999MQdiHBGBC+PfqjZTH9EnP3o2fIJl7gITUV6/wduAgJF6lz8tgBOU8z6vk4ebhEKjuoGQ88lVYiD9xAulvAyRDR4j2YTznJP73H1Lu3Ue6ibJYTSB485Fw+jRSnzzJ3LdIPHf/AQORShDLnnDuHBKv8ruky0Lm6/t+wkSoY2IQPH0G7+fxp0/j7eAhgnP324GDkPKMPAeLngwT6y8RpoI1QZ4H0/C6wFEct3SxkFLO75weGIjAESPI+vgBdVwcIn7h95aM3iKSMVxg3EuVZ4vdty8zPFHk3Xlep455Rn2OwpvPu5aWjPBwRP75JzIiI42OK5atTMjxwnjipUvimWkthMrBAdE7diLx8hUEzxKOkRUiIzgY8SdOQPNBcaDVag0bFVFMxgttKQNNaio0aWl406OnmZDFF6MtRdgKnhqzPATPmAFtaqaS5HWnzmbnxO7bb5SV1pL49+otu8SIEQYh3DbCuFartYjgH3fkiHlcsth9PyibordvR8yOnYrvb4DE0/6DO5xWrQbS6TwmLIGGUJmXdM18sxK2fAWsk0ZHmFftO+Bly1YGbwbSRSVq02bDd026cwcvW7ZC/KlTsvthtJEgIP7MmQ/9li8MBU+fobvGdXLr5pOKlaDVahF/7hxetCTXiHPLlMlGq0XgyJFIunGDvElSEhIvXkT0zl3QajRGsbBCIRYpDx/iPY/VNnb3Hl3pPNqNh34Okrlhkasgf9mqta46iUyLnzY9DVqtlihZnaVIfxtg9pyi/tqAuCNHjKxvQrwdMhRR27bhZZu2CPwQrytF2qtXCF+p/Du+Gz8BSTdvCtfmJoXSY0T7wfMkLSAAL9u01VntuM+Q0MMw+cFDvGzZiujccJ7QLdLycoo9DE1d3Gk9bEzQZmSYWdv5SL51C+/GiedS0RMwdKghhFN3k8zvrE1PJ7qfHiFPCW1GBhIuCsfmS61l78aMFZ37M8LCEPCFyFgWmVZetGyJRBleMwYILOOhJt6Z3HwTZvWu9fv2OXNE50OhZ8ZdO/ThSzSI7oskxkLif5eJ72PudSxzPyXwHAJHf42wZT/Dv79JbLxCRbMpOV4Ytx0qaFOltTTuImVVov/5B8+q10Ds4SOI3UMgiANmAyacU2+UZBP+pktXhC1bhpRHjywiZNFkEza1QKRxXKP1GlBrQuL2ZYpZn7TKNqW0BE+fjhgjN295hEjE85iiVautUi6HJGlUyMKF0Gq1eNOtm9EYoULm5j32wAHDOykHdWyshVwF6cZXelAQAjkZr0mI2rABz6rXQPjqNQj8ajTSg4Lkx67L+M6xu/cgPSgIASPo+m0JMkJC8O6r0cgIIq9rG2xaVhGQlTtCLpr4eLwdOAgvGjWWfQ0A0Kaly+i3bt0JErBQiRHxx3o8rV5D9sY2Ys0a2c8t6NupCJ4+HeoYsrk/+f59WfeRglu3WUoY0sTHI3T+AqQHBipPIEuJxeoUU84HYT8txvtJkxH640KkBwZ+KN1H5rLL5d3YsYZs1FLwei2SjjOCjbvos1Q5mPypbOv+dsBAnbcNSe10ipxDRujraKek4EXjJvDvpyuBSZKwkDfnilqNp1WrUa9btFAndf5ARlAwAoYMIT4/+aFJiAnB/kn0tzAZiwnnzun27VJ7KIEx7N+rN140aQpNaqp4mV+eMZTy+DGeVa8h6E0nqZhRMr45bup8iS9p0KanG5LBmiYGtkTSSS5MGLcVKhVS37yRPM0pj3AmSH2JnqApU8it66YvWkYGtXtF9OYtxpeUoRGS08aUKE4/0oOCqEo62YqX7dobxbGkPn+O1527II4vY6gViD1w0LLZg0lRq6mTzInxpGIlaNPTkXhZWkMau2cvtCkpsiyRrzp+ptPmy1QkBE3T1d42yrNAQcLp05YZxzLeL01iIl5//jmiNtOFmkSsXm0cgyYHBfoHkmz5lkY0v4UAmtRUs3nPlvWdtVoNkm/fhkbp89JqqIVbfbLC+BMnqG+nT4pKs7E1RYmQGHvgILSEdebDluqSnb6f/A3eTZpk9nnilSt41VF+bXdAOhxCCXx7gei//8brD3WfBdvJTUwK8M9VMuaD+H//hTY90/rG/S5irvvceHIaN1ZtaireDv3COOs64TjJIBDw1CZusFxi9hiHNtJkfn/Tuw/C165F9C5jJX3yrVtWzx3wuvvniD95CurYWKTcu4/YI0fI4nd5+mXqJsyLyXPRajQW2XvSoNVqee+p1WrxhpNjiFs6FYBkHiStRiO+dzf9iLPWiO4xBK6Z8ugR1DExSHlEFgbD/c5hK1ZKnMz/jAw4yB+XXEVV+GplZaOjTGQfLi9btNR5jUGnlH3dubOo14YUTBi3ERG//yaZ+RygcHsixDQ+NOaf3QgYNPhDNnP6672bOAkvmjQlWly4PK9bTzKphhTR27YZ/R13RJ410ppoYmPxvE4dw9/R27cj9cUL4rJA2RVtaiqRSyUNCUQadB1qGSX2wlastHhtV3vBF8ZBQurjJ4bMtjTIdSPOSWSEhOB5/U+R/CE+MyMqCi8aNKS6Bm3COS7cMB9FaLXUS0XEmjXGLqvZDcJ1OOnGDaSHhiLu6FHEH/sXqW/eGAQAdUyMLhEnwRwTtTVzbUuSWRFCDq/bdzDaFGs1GoT8MBupJgnQTHnRoOGHEJtMNGlpUCckGr67EAnnzyPOREkjP8afk6yJ0FPuDUfRQDuuk65exdNq1RE8Zw6C585F8Ezx0rJ6XrVug3QeS5o6Ph7ajAzJJFiR634zbPxpSbl/HxG//Mrr7cab18IE/TPSpKRQz0epT54Y5XogDQmNP3ECmsREI1dn2iRcSbdv42nlKnhauQrS3r2XpQjVpKYaKTNJEg2+6doNrzp0MOQ10Go0UMfGIvbAAbOSm5H/y8xxo0lMxPtvphgpWvTjI+nOHTyvV1+nQBGCGxaQlgY157cVteJKKCuEsuJzSbqt65+hIoHUY1Kr8bxuPSNjiyYxEbEHDkAdGwuVSoFoyq1OI/K83n8zBUEzvhN1p5cKD9OHcgaMHIXUFy8VeW2w0mY2Ip2nBiQvtqj/efOm7M10/L86hUL0VpGkDTxoEhMRPH0GPFuTxWcxGFqKTMwvmzWnvj5t9QSGPGL++cfsWISFFTfWJs1fXviDJj4ewd/NROkD+xG1RVjLLnhfmRUVACDqL8skM9Rq6C3j2R2ask7cued1h47I1bgxVI6OVPlMuPk5SGN0LUHa27eIO3QI3l27AhDOKWCKOjYWkX/8AQcvL8OxZ9VrAAA86tSRVCi8Hz8Bznt2w71KFd0BuRZaTjtZYXQyx7Uc5frLps1QdN1a5G6hy9CfER6OF02aErd/1boNCi9dAlfS8qwEkHoGaNVqPKtbD0hPR8UH1gnNMOVZ7Tpw9PVF+Ss6gS2JMkkgt3LBq9at4c5T0k4MrVaLl82aQx0Tgwp373wo1Sg9TvVW6MTLl5G7RQsEjhiBRJ4a2YBxOAqgMzAl37uHsqdOGsaHa7myUMcnSCtOOF4aL9u2I08qJ/EOBI4cCa/PxL173k0YD01CAsKW/QxNSiqRMK1JTETAsOEosWUzPOrWRfDsOYg7fBjudWoj+aaI0kEKQkFeb8xzq1wZfoOMqyykvX2LuGPHJBURek8FjQxjkClMGM9q2GrTo/A+XI0eDUQ1RxkMWCa0gZFFsUHWeEsSLpHVWgytOgOapCRZHghZAU1iolmJL4YwiZfkuyoCsHmYUdC06Uh+8BAFpn5rZE0jQcOTFZnUsu/foydcypSBZ7Nmhiz4tCT+J6+klCYpSReXamMl07vRX6PAzJnw7t4dcTLCD4K+nWqFXkmg1eqyr3+Ys2P2iGeOtyTq6GhE79wFr070oR6m8dXJFAl5Tb16ntWkE+QBAB88ZIQEcSHSP3hA6JV5qS9ewjFfXsl2Mf/shnfXrnAuVowqu7tWozGoGDQpKYBWCwd3d6NzxLxQI9YYu4JHrF5NfG8AeDtoMHwHD0LcYV3pSlpBPGzlKvgNG5bptUDp4h76449wLlrEyEOAtORexNp1iPrfXxaZR1RaS+dnzyLExcXB29sb18uWg6dpJsosjGezZlbLEM6lwIzpcC1fHgFfDLP6vRgMObhVrWrm1sVgMBgMBsM2OHh5wbVUKVl5M3IyRX79BZG//yFrD1Phzm1E/vUXIn6lE2zl4ODlhRIbNyDl2XND0tG848ba5N6WouTOHXCvWRMAkHDhAnWlFmuRoFaj3ssXiI2NhRfHi4gPZhnPYtBH58lDbv1pBsNWMEGcwWAwGAw7olZDk85yhFCj1sjew7xs01Z+FntKNHFxePN5D6Nj2UkQB4C09+/hXrOmLgmelZMSWgsmjGc1LJzAjcFgMBgMBoPBoEWTmIjUx0/s3Y1sR/SOHbLb2koQ/1gI+mYKwpYsRUZoqMFCnt1g2dSzGGQ1GBkMBoPBYDAYDEZWI+naNXt3IUehr2mefPeufTsiEyaMMxgMBoPBYDAYDAaDYWOYMM5gMBgMBoPBYDAYDIaNYcI4g8FgMBgMBoPBYDAYNoYJ4wwGg8FgMBgMBoPBYNgYJowzGAwGg8FgMBgMBoNhY5gwzmAwGAwGg8FgMBgMho1hwjiDwWAwGAwGg8FgMBg2hgnjDAaDwWAwGAwGg8Fg2BgmjDM+Wpzy57d3F6jJ+/Vo+Pbvb+9uMBgMBoPBYDAYDCvDhHFGlsbRz4+6jWv58qj09AnKnjlthR5ZD9/Bg5Bn5EjkmzyJuE35a1fhO3gQPJs1g9/wYVbsnX0od+kiyt+8Ye9uZCsKLZhv7y7kaAotXGjvLjAIKHXgADxbtbJ3NxhZHM8WLezdhSyDx6ef2rsLjCxMxYcPUOnpE3t3I1uS5YXxtWvXolSpUnBzc0Pt2rVx8eJFe3eJQUCJrVvgXKQI8fm5GjcGAPj06YPimzYBAAr9tAhlz52Fa+VKVPd2KV0aAKByckKRX3+hagsA5a5cttwC7OwM91q1JE/z6tIZBb/7Dg7u7nD09ISDhwfR5R29vVHwu+9Q7PffUODbb5F3/Diq7hVaMB+Vnj5BgR++BwC4lCpF1d7BwwNeHTtQteHDp1cvs2OVnj6BU968cPT0NJvg844bi/zffgsAyDNiOPJP/T975x3fRPnH8U+SZnTvTVvKaCl7771BQJaAoAgoiuDgBwiiouAARUGUqchQ9kb2hjJKSynQskpbOuneO02a3O+PkGvGJblLF+Dzfr36giT33D25PPc83/0srHYf2GLduxer44Q+PgY/sx8zBkHRj9H0ZojeZ3wbG3j//hvcFi3i3Df3r5fAfuxYg58HRT9G0xvXOZ/Xuns3zm1qCnHTJma39fnzD7Paef30o9nXdBg7Br5///1CRLhYduzAuY3t4MFouHcP57kAAHw2b4bj1Lc5t2PCde5c1sfa9OsH+zFj4DpvHus2ksAA+Kxfx/gM1hX2r4+C5w/fm9XW8/vvYN2L3VxUE7j+j9lI7PbZAtbncJgwAbaDB1erHwJn52q154rPxg0Iin6MwKjI6p9r859wmDQRbosWwapjx+qd649NnNsERT9GoxPHWR3L9PyLA5qabOf188/0/z2++5Z9557DEwpZHWdo7EvatKb/3+zhA6Pn8PrpR7h/vQQNDx3Uet9u1Eg4z/oATtOmQejnCwBw+egjvfaWHarmV5/Nm9Fw/z5Y9+gBm379IHBwYPU9uCJp0QJ+u3fRr3lWVvD84Xt4fPM1mj1+BI9vl8F77e9wmT0bdiNHwmHCBIPnEgcGAlDNJc4fzoJNnz6c+8MTCiFp3RruS74Cz8ICANDs8SM4vTOV87kM4TBhAuP51DoGz9IS3mt+rZZDym74MEhatzZ9YC3BoyiKqrerm2Dfvn14++23sWHDBvTo0QN//PEH/vrrLzx69Ai+vr5G2xYVFcHe3h63mjSFjUBQRz2uO+xGjoTt4EFI/fgTvc8aHT+G+JGj6NfuX32FzO9VC744IAB2w4cje80aVtex7NgB5bcjTB7nt2snCg4eAqCaxF3en0l/Fj92LCoeGbeWNQkOhtDdcFi5PD0dcf36Gz2H/dixAA9wmz8fFs896pRSicwff4RlmzawbNMWTwcOZGzrNG0a8rZvp/tRmZ2N+NdHQ5GXZ/SauogDAmDVsSMouQxuixZBYGMDeVYW4nobn+QCI26Db21Nv66IjUXu1m0oPHJE6zirbl1RmZkFWXw8HCZNhOfSpVqfUzIZMlasQPnde6iIjjZ4PdshQ2Dh6gr3xZ+Dp/N8lFy7huJz5yH09gJ4fFh16oSCfXvh+umniOuv7UlSK8mPg5oDGlOJ7bChKA25CWVhIf2e3YgR4AmFWt9JHBQEnz82QejmhsLjJ5D711+oePIEHt8ug6POIqK+Jy5zZkPUoIHedyo6cwZpi78AVV7O+J15IhEomQzigAA4TZ8O6YMHoORyiJs0RubyFQBUxqCCffsM3jcAaHL5Ej0WbYcOhVX7dnR7AGiwaSNKLl6C26JFiGEQuOzHj1ONUUdH1fd6+hQ5Gzeh6MQJAIDLnDlw/Vi18BccOoz0L7802h9N1L9H7tZtyFq50uDnpbduIfv33yGwsUXJlSuszpv9+++QZ2UBFAWXWbOQ/N57kCclQ9K6NYReXig+c8boOfx27UTBkSOwbNkSGUuXsf5O/ocPoeJpPKQP7iPv739YtwNUQkH2qlUQ+TdC4b//ouzWLVbtAu/egfThQyS9VaVY2o8fh7KboajMzgYlkxlsq77HFEUhe/WvUBQXQfroMaRRUQAA108/QfZvho2EdiNGwH3x58hZvx75u/eAJxSCkstZ9RsALFxdUVlQAElQEHy3/IWYTp1Zt9XsPwA8bsbeEOo0bRrcP18EiqKQtuAzFJ08CQBw/uADlN+9i7Jbt+B/+BASxo4zfp7p0+G28DPweDzkbNoEvqUlMlcwG0ccp0yBVaeOsBs6lHOfNb+nPDUViZPeRGV2Nqu2NUVA6E0IHBxQcPgI0r/4gnW7RqdOQtyokdba4rN5M6SPHyN79WqT7d0+WwDbIUORs24d5JkZcBg3HumLFzOOM9dPP4E8MxPuX3wBKBRInj4D5ffuwbpXLzRYvw58kQhF584h9ZNPTV43KPoxKIpCdFBz1t+V6RxPhw6DLDGR8fNmUZGIbt2G8TPvNb+iPDIK4sAA2Pbti8xffoHD6NGw6tgRz+b+j3EO0xwnudu2g5LJ4DDhDWT98gscxo1D0uQpqg+FQuD5/RM4OcF+1CjI09JQERMDUcOGsOrYAc7vvad1bqqyEpkrfkT+nj2AUql3bfuxY8G3sQZPKIRlmzYoCw0F38oKQh9fOE6coDfWrbp2RVloKP3aukcPlN64AatuXeG+aBEkzZoBYPeMNL1xHVmrV8Nh/HgUnT4Ny1atoSwvQ8bX3xhtFxT9GNnr1kPg4ACnt6Ygb/duZH77Hfx2/IPS8HDk/L6WPtZ55kzYDR+GvH92QBwQAHlqKtwXf468f3ZAWVqKnHXrVLfW2xvy1FQ0OnEcFfHxKAsNg/sXi8GzsAAllyOmZy9a1mj2+BFyN20C39oaTlOnovz+feTv3gOHN8aj4MBBQKlE4b//wqprV/hu2woejwdAtSYWHjsG988+g8DenvG7ad43v107IfL3R2z3Hqrr3o/SMiRU5ucja9UqOIwdWzVGdHD/egmKz5zVW5fEzYMYZWaBszMCnhvTiy9dRklwMNy//AJ8kcjob/Ls449RfP4CAu/dhfzZM+Ru2QqX2R9CxOAwKLt7FwUHD8Ju6DAUnT4NcZMmKDxxHJKAQBQePap3vM2AAfBZv47xuoXHjiFt4SIIHBygKCig329y6SIgECB+xEg4TZ0KRUEB8nftgnWPHnCZ9QEkLVviSbsqJ5bT9OlwX7QQef/8g8zlK2DZpg0a7tsLAFCWloJnZUX/jmV37iLJiCG82YP7yPr1V1h36QKRnx9yNv0B55kzIW6kMj5RSiWkjx4jcfx4xvaeP/wAu6FD8KSDSraz7tEDPn9tRsG+/cjQkceFEyei6bfLUFhYCDs7O4N9Al5wZbxLly5o3749Nm7cSL8XFBSE0aNHY8WKFUZaslPG7ceOReHhwwbPIW7aFBWxsfRrzx++h2XbtogfOQq+27fBunNnUDIZUj76CKVX9T32khYtIA5qBpG3N5zffRc8kQiZK35EWUQEfLdvQ2VGBhLGjmMU7GwGDABfLIKiqBg+G9aj5MYNpC/+Aq5zP4WisAjO770LnkCAgkOHwbe1oRdChzfGw/O77+hJw/3rJXCaPBnyrCwU7NsPhwlvQOjujvgxY1Hx2HQ4iev8eRD5+qHoxAlY9+wJx4kTaMHBwsMD4saNYTd8GBzGGRawlFIpnrRtV3Xfx4+Dbf/+yNmwEdIHD+A8cybc5hv3aFAyGb3A+vyxCdLoJ3B+711UxMUh4fXRsGzXDn47d+gplroUHDyIzJ9Wwn7MaOT/swOASnmy7duX8fjKnBxkLl8OvrU1bAcOREVsLLJ+WaV1jPeaXyFLTIR1z16wbNmC+TzZ2Yjt1RsA4DRjBmx69UT+7j2wbNsGTjNm0BOJLtLHj1F88RJAUbDp3QuWbZiFDF2UpaX0ZNHo5AnEvzZC63P/f49C8twqyoWy27eRs+kPyBIT4fHNN7DppYpoqIhPQNHpU+BZCCFp3px+v/jyZVRmZsJx0iT6HCXBwcjfsxc2fXrD8c03OfeBDUzChrHwqfx9+2Hh6gLb/v1RfPkyCg8fQfH58wAAvq0tGvz+G5Knq6yuAbfDEdOxEwAgMCoSfJGIfg7tdLw+mv3g29vD75+/Dd539bFNgq9A6O5Ov1/+8CFKr11TCStp6bAdNAgF+/erLN48IPvXNSg8cgQNNmyAbX9VRIeyrAxP2qus9iI/P8iSkgzeg+JLl1CZnQNQFChZBRRFxZDFP0XRqdOs7p0aZUUF8rZuhU3fvpA+eoSCQ4dRfucOAG0DA6AaR0lvvQ23RYuQt3WrQSXI6d0ZcH8eAQEA+fv3I+vHn6AsKwOgmqNFjRtrCdFqw5puvyvz85G/cxfsx4yGwM4OmT/8AGW5FEJvb9iPGonEKW+Ben5etWBVfu8eEie9qXcuSqFA9u9rUXLlCiqePIH710ugLCyETf/+jL+vpgLS9GYIYrt1BwA02LAez2bPoY9zW7gQzjOm67UvCw9H/p69KDp1ivE+aaI5nyorKvCkTVsAQMDt24zGIZePP0L5vUiUXrsGqy5d4Pf3dvqz4kuXIE9Ng7K0BNlrftNr2+zBfcgSElB0/jyc33lHy6BYfOECFAUFcNARaipzcxHbo6fWe43PnUXhseNwemsKo0cpa80a5G5SRTmIg4JQ8fgx+FZWCLyjbyhmo2g4Tp4Mj+fRQJpUxMUhfsRIAIDb54uQ9eNPRs9j3b0brLp0hXXXLrBs0wax/fqjMj0dAOC34x+UR0WBUiqRvYpZQVbPHwCgKCmh5xVjNL0ZQhvyAP37XHTmLNI++wyNL5xH0puTIU9Lo4+1Gz4M3gaU9YqEBBSdPAW7IYOR/s1SKMvL4TjhDdZztCw5GU8HDzH4uf+//0ISGABA+zcS+fmh8dkzoJRKRDdXrZ9WHTui7PZt+hhD46PgyFGkL15MvxY4OSEg5AZKgoMhT0uDw6RJKuNPpRz2o0cbXWsVBQVIXbQIpcFXaeUPMD33JUycCGlkFOxffx2F//4LQBWRY9O7t9F2TFAKBXI3/4XyqCg4v/cerNq3M3p8dPsO9Jzl9M5UuC9ejMQ3J6P87l3wJBI0u3eXsV36kiUqxRSA+5KvkPndc2dNYCBsBw6E/eujIGJweFEKBXL/2oLcP/6g52BNHN96Cx5fGTceq397Cw8PNDl/jrUn3BiUUom8rVth2a4drDpwjwZiS2nYLeRs2AC7YUNpmabg6FHwxWLYDTMcIahewy3btIH04UNYdeyI0rBbcH53BngWFii7cwdlERGwHTAARadPw2nqVFTm5KDo5Ck4vTMVOevWoeTadTQ6ecLg+K0Lis6chbKsDA5jx0CWkoLCf48ZnLN1yV6/Hjlr14FvZ4fAW2EAVOui+vto/h8ApDExSJn5PgSOjvDbvo2+hu5xTEijo5EwegwkbVrDccIElN2OQOGRI5C0aQ1/E84WNRXxCUhbtAj2I0fCws0N1l27QJ6VBUmAag4rPHESeTv+QYM1ayD09ARFUZA+eAihtxdtoHE/fQrOjRq93Mq4TCaDlZUVDhw4gDFjxtDvf/rpp7h37x6Cg4O1jq+oqEBFRQX9uqioCD4+PohftQrSPzcDUIU9F508hdLnoe5B0Y+1FgWb/v1RcukSAMB20EB4r1mD6BYt6c9NTcqV+flI+WAWrNq3h/P7M2nvrCnK7tyFsqwMfGsrFJ06jcqMdHivWgWeCWuXJrKkJJRH3YfdiNfA4/Ho79Vg/TrYMuTFKaVSFJ06DZtePWHh6or0pUtRsFc1SK179ID7l1+iPCoS9q+9ViOTpbo/lh07oOHOnWado+z2bVCVlbCu57wltSdT3LgRrHv0gCXL0JaKuDhUxMVpeXFqk9LQMIDPg3XnzigJDobA0RE8CwvIMzJg2994lMHLTll4OJKmvkN7611mz4YrxxD+yuxslFy/AbthQ8GXSFB05gzEjRtD3LQpSkNDwRMIYNXJuPCsHveS1q3hv9/4IlB+7x4UxcWwqYHQU03lr/HZMyiPioJl27aMlnAmlOXlKmPZw4dwnT8Pli2YjUymUH9/zx9XwGH0aOZrlZYipldvOL87AzlrqyzsDQ8cgGWrloxtKp4+RcWTJ7AdNgw8Hg/l9++j6MRJ2A4ZDMtWrVB06hSsOneG0NOTdV+ljx7RXttmjx/RC37xpUuwcHc3+x6oKYuIAFVRAevu3SF9EgNZYiLshgxGRXw8slb+DIG9HTx//NGooFERF4eK2Fik/o/ZeOm5YgXshg8DXyym3yu9dQtQUrDu2oX+jhaurrQBJCj6MRQlJSg+ew62AwcY9Aopy8tRdPoMhJ4etGFK8z5xQVdhNrW2KmUyFJ08Bevu3WDh7Iyikydh1bEjYypUTPceUOTlgWdlBe9ffobQuwFkiYmwat8Oebt3Q+TtDfuxY8HjM2fpqfvW8MB+pMx8X8ujY9WtK+xffx2WrVpB+ugxvd6qURQXo/jcedgOGgiBhvBFVVYiumUrvWvpfm9KLkfhyZOw7tIFEAj0IqqcP5wFt09Ne6DV5G7ZiqznYcOey5fDdvBgCGysTbQyn4xvv0X+7j2q6/3wA8ruRKDwkMrhofldpdHRqIh7Ckomo2UQACiPjERlbi5s+/dH2pdfMrbVRZ6aipKQEPD4Alj37Gk0wo4tFEWh6OQpSFo0h9hEukZlfj5KLl2G3dAhkGdkaM1LtQ3TeKPkctX816kThF5ejO2UZWUoOnMWNn37wMLJiR7ztsOGosGvv7K/7sABqMzORmloGJ2yxpdIjLaVPUtF+Z0I2A0fToc1E159KJkMhadOwbprVwg9PGr9epX5+RDY2dEOusr8fAhsbetkzFEyGZTl5Sjl8WBvb/9yK+NpaWnw9vbGjRs30L17d/r95cuX4++//8aTJ0+0jl+6dCmWLdMPfSwsLIR8/34IfXxhN2QwlDIZctaug03fPrDq0AGlYbdQGhIC14/mAHw+steuhVW7dnTuRP6ePcj8+Rf4/f23QcHwRaQkOBjl9x/AZc5sVouCoqQEuZs2wW74cEiamx9CZghZYiLy9+2H0/RpEL6EVc4JLydld+6g5PJluHz8sclQrtqgIj4eBQcPwfndGbCo41zHwuPHocjPh9PUmsvd4kppSAjKbt+Gy5w5JqNWAJV3rmD/AdX9cnGpgx5qk7djJwR2trB//fU6vzYXNEPxfDZvRmlICBzeGA/x83oZpqjMz0fu5r/gMGY0xE1N54HqkrdrF/hW1nAYM5pzWwAoPHkSafNVucZqj15NIUtKQv7efWavNUVnz0Gekgzn996j1y1JyxaoiImF60dzzDZOaxogXOfOhTigqUmjqKKwEDl//gmRnx/kKSlwmT0bfEtL1tekZDJkr1sPm969qp2jzAbNcPug6MeqUOONG2E7ZChn+UlRUICcPzfD/vVRZkVxEdhDR1J+8QWcaqjmA4HwX0cdof1KKOMhISHo1q2qeNAPP/yAHTt2IFonH9aQZ5zNTSAQCAQC4WWi7M4dyNPSYT/itfruilnIU1NRfPkKHMaN5aRgvqxIHz9GwpixcJn9IVw/0a/18ipAKZUoOHAQlu3a0uGchBefivgElN0Kg8P48cRbTSDUEFyU8Rf2qXNxcYFAIEBGRobW+1lZWXDXyKdUIxaLIdYIzVPbGIqKimq3owQCgUAg1DVNmoDXpMnLu8bZ2sJi1EiUyOV04atXGm9veD/PlXxpfzMWCIYNhQyA7BX+jq8cLs4QDB+OYoY8cAKBYB7qeZ6Nz/uFVcZFIhE6dOiA8+fPa+WMnz9/Hq+zCCHMzc0FAPiwzJEkEAgEAoFAIBAIBAKhJsjNzYW9gVosal5YZRwA5s2bh7fffhsdO3ZEt27d8OeffyI5ORmzZs0y2dbpefG05ORkkzfhVaJTp04IDw+v7268FKhTGVJSUkgqAwfIGGMPGWPcIeOLPWR8mQcZY+whY4w7ZHyxh4wv8yBjjD31NcYKCwvh6+tL66PGeKGV8YkTJyI3Nxfffvst0tPT0bJlS5w6dQp+fn4m2/KfV0q1t7f/Tz3gAoHgP/V9awI7OztyzzhAxhh3yBhjDxlf3CHjixtkjHGHjDH2kPHFHTK+uEHGGHfqa4zxDezcockLrYwDwOzZszF79uz67sZLw5w5c0wfRCBUAzLGCLUJGV+E2oaMMUJtQsYXobYhY+zV4oWtpl5duFSxI/w3IWOEUNuQMUaoTcj4ItQ2ZIwRahMyvgi1TX2NMS7XNe07f0kRi8X45ptvtCqsEwiakDFCqG3IGCPUJmR8EWobMsYItQkZX4Tapr7GGJfrvrKecQKBQCAQCAQCgUAgEF5UXlnPOIFAIBAIBAKBQCAQCC8qRBknEAgEAoFAIBAIBAKhjiHKOIFAIBAIBAKBQCAQCHUMUcYJBAKBQCAQCAQCgUCoY4gyTiAQCAQCgUAgEAgEQh1DlHECgUAgEAgEAoFAIBDqGAuuDa5evYqff/4ZERERSE9Px5EjRzB69Gj6c4qisGzZMvz555/Iz89Hly5dsH79erRo0YI+pqKiAgsWLMCePXtQXl6OAQMGYMOGDWjQoAF9TH5+Pj755BMcO3YMADBq1CisXbsWDg4OrPqpVCqRlpYGW1tb8Hg8rl+TQCAQCAQCgUAgEAgETlAUheLiYnh5eYHPN+H7pjhy6tQp6ssvv6QOHTpEAaCOHDmi9fmPP/5I2draUocOHaLu379PTZw4kfL09KSKioroY2bNmkV5e3tT58+fp+7cuUP169ePatOmDVVZWUkfM3ToUKply5ZUSEgIFRISQrVs2ZIaMWIE636mpKRQAMgf+SN/5I/8kT/yR/7IH/kjf+SP/JG/Ov1LSUkxqbPyKIqiYCY8Hk/LM05RFLy8vDB37lwsWrQIgMoL7u7ujp9++gkffPABCgsL4erqih07dmDixIkAgLS0NPj4+ODUqVMYMmQIHj9+jObNmyM0NBRdunQBAISGhqJbt26Ijo5GYGCgyb4VFhbCwcEBKSkpsLOzM/crEggEAoFAIBAIBALhJUNaKkdseCYatXOFtb24zq5bVFQEHx8fFBQUwN7e3uixnMPUjZGQkICMjAwMHjyYfk8sFqNPnz4ICQnBBx98gIiICMjlcq1jvLy80LJlS4SEhGDIkCG4efMm7O3taUUcALp27Qp7e3uEhIQwKuMVFRWoqKigXxcXFwMA7OzsiDJOIBAIBAKBQCAQCP8hru2MQmJUDlIiizFpSRfTDWoYNqnSNVrALSMjAwDg7u6u9b67uzv9WUZGBkQiERwdHY0e4+bmpnd+Nzc3+hhdVqxYAXt7e/rPx8en2t+HQCAQCAQCgUB41ZGWynFqYxTi72bXd1cIhBojMSoHAJCbWlrPPTFMrVRT17UCUBRl0jKgewzT8cbOs3jxYhQWFtJ/KSkpZvS8fkl/Woi/v7iB+HtkIiQQCASCYUoLK5CXXj/Cxc0jT3H/yjOz25cXy1BRJq/BHhFeJdKfFuLi9kcoK5LVd1fqlIoyOcJPJmDn1zdRXsLtu1fKFCjJrzB9oBFuHYtHQmQOTv9xv1rnIRBqg4oyOU5uiELs7UxO7V6GGt41qox7eHgAgJ73Oisri/aWe3h4QCaTIT8/3+gxmZn6Nzs7O1vP665GLBbTIen1FZqenVyMc1seoiin3Kz2J9ZFoiSvAqc3kYmQQCCoqEZZD8JLQlxEFo6vvcdJAN++6Ab2LAtDcZ4UmYlF2PfDLTyLzqvFXqrITinGnbNJuLo3xqz2Mmkltn52HX/Nu4Zti64jI76whntIeNk5/HMEokMzcHXPkxo5n7RU/sLPozePxOGveddw63gCCrPKcfdsMqf2u74Jxd+Lb6Ags8zsPvzXjB8E9lAUhYvbHyH8ZEK99eH2qUQkRuXg3F8PObWriR21anv+qFFl3N/fHx4eHjh//jz9nkwmQ3BwMLp37w4A6NChA4RCodYx6enpePDgAX1Mt27dUFhYiFu3btHHhIWFobCwkD7mRWT/8nDEhmeabVWslCvo/5cWVM/CSSAQXn7unE3CP1+EoDhPWt9dYYWiUglANX+d2/IQ6XEF9duhl4Szmx8g+WEeQo885dw2O7kYx367h5yUEvy75l7Nd04HubRqncrPKEVhNjfjs+bxZYUynFgXWWN9I7xaFGSZr1iqSX6Uiy3zr+HKrppR7GuLOzrKt1LBTfhXe8WTHuRyvnZeWike3UhDeYl50SpZSUVEka9jFAol0mLzoZAr6+R6mYlFiA7NwK3j9aeMS80Yn0olBaWyeop0pUyBPd/ewuVd0dU6jzE4K+MlJSW4d+8e7t27B0BVtO3evXtITk4Gj8fD3LlzsXz5chw5cgQPHjzAtGnTYGVlhcmTJwMA7O3t8e6772L+/Pm4ePEi7t69i7feegutWrXCwIEDAQBBQUEYOnQoZs6cidDQUISGhmLmzJkYMWIEq0rq1UGpUOLSP4/xOCTN7HPkp5u3gGhOvnu+CzP7+oRXl9LCCvy75i7iIrLquysEllTHonrzyFOU5Fcg9F/uSlpdk/okH5s+uoKIM4m4svsJYsMzcfiXO/XdLZPcv/IMJ9ZFahlD6xLN8fHoRrpZ55CVVzKer1bQcDLsXhqGnUtucrumzqGayv2rTFFOudbvZAq5TIHwkwnITS0x+5qRl1KQ/JC7cqbJ3XPJ2L88HNJS8xS1SrkCJ9ZHsk5r0LxObmopSgurGXr9XHl4dN18ma4+oHQfFLaY4QTc820YLu+IRlpsAee2WUlFOLDiNrYtvM79wgSzCTkYhyOr7uLSjsd1cj1Npb+6yq0ppKVyxN7O1F+T+dwHt7nPveaaFh+Zjfz0Ujy6VntzCGdl/Pbt22jXrh3atWsHAJg3bx7atWuHr7/+GgCwcOFCzJ07F7Nnz0bHjh2RmpqKc+fOwdbWlj7Hr7/+itGjR2PChAno0aMHrKyscPz4cQgEAvqYXbt2oVWrVhg8eDAGDx6M1q1bY8eOHdX9viZJiMrB45B0XPrHfAuI2ZOoRrOKUvaLdk3xoodxEYCQQ3F4Fp2Ps5sf1HdXXgooisLTu1koyjUvdaS6RF5KwbaF15GXxj23VzOnVllZ988mpaQQcjjOpOGHUlI48+d9HP31LgAg9Gg8inPrxpOfnVyM03/cNys0Uz3fXd0bg6QHuZwXbblMgZToPCgUVUKKOXPouS3cQu500Y3AizidyLptQmQ2Dqzgpmgx1nPhIJzpCnJsBDuZtBL5GS9u8R1TFGaXY8dXN7H5f1ex59swHP4lAmHH4o22CT+egFvHE7D3u1tGjzNEWlwBru+PxfG1qsiDSrnCrPEZcjgO2cnFuHeBW9i0mkfX05F0P5dVWkNRTjm2zL+m9d72RTfMuq45VMpeHMMQl59KU4nmGpFbXbkvNabA5DF1AUVRyM8oRXmxeR76F+m3Z0PUZZVxK+YWt/xpc9E0ih1dXbtG9mO/3cO5vx4i5LC2E8KcaPO755I4t8lNLcG2hdfpe0xpOEq5rHVc4KyM9+3bFxRF6f1t374dgGqhXrp0KdLT0yGVShEcHIyWLVtqnUMikWDt2rXIzc1FWVkZjh8/rlf93MnJCTt37kRRURGKioqwc+dOODg4cP6CpYUV2L88HI9usBO0KspqQAl+CXXa3NQSbF1wHZGX6q7wHUVRkFeoBIRn0XkoL5EhM6EIh1ZGvJJ5hNJSebXyuQBohZHJpHVvsFFTki+tVrGY2prQdIm5lYkzfzzAji9v1sn1dLm+PxblxXIEm5H7eHJDFP1/riGLAFCYXca5CFBpYQXuXUhGdnIxNn10BXfPJZs0/KTFFuDpHe2ik3yBeTlalJLiJBweWBGO+LvZ2PVNKCev460TCdi28LqWkYZLewA4v+Uhjq25h1vPlaqCzDJsW3gdd86yW/xzU0sglykQd7t6US45z7Q9p2HH2IcRntp4H1lJxXoKkDGYBKJTG+8j8X4Oq/YKMyIQ9iwLw+6lYfh3zd16S9nISipCYbZ583dabFWNnLy0UqTHFeL2qUST16sOJRr3qaxIhj8+DqYVc7ZorjGVZoTDlpfIcG0f+9oCNV28tiinHJkJ7O5j5MUU/PFJMBIiX74CukdWma8ccZ33AFUEacqjPMikleCb4a2sDY6vjcTupWHY+plxD31FeSWu7H6CRzfS6MrxR1ffwR+fBOPE+tpPmclNLcHNo0/Nuu9coSgKd84mIflhLpRKChe2P8KDq6lmnev8lkf0/9PjCiGvReNFdrJqa+o4nUJt+TVQsPTuuWQc//2e0fD+K7ueoLxYzjh3sdWRyktkuMph7quVauovEru+CUV2cjEu72Dp6a4BHUGpoFBaUIEbB2Nx5s/7daZ4VIcru6IhLZXj+v7YOrvm+a2P8OenwQg/kYB/19zDnmVhOLLqDjLiC3FoZYTBdkqlSomvL2TSSlzeFY2Ux+yLJSkVSmyZfw27vgmtlkKuueyFHIpjf/0aHIPSEjn+XhyCvxff0PIKsuXC9kfY8dVNTsaE6NB0HP45gnNe2rMn+aYPMkBeWqnWs5uVVGS2d06dS80GmbQSFWVypMdVGaS43ufSggrsXBKKrQuuo7xYJRCb8nDHRWRh+6IbuHEwDvuXh2uNGU1lQpdKhu8msOAuoFEUhSOr7+DAittQKpSsFHPNj89vZe9hDj+RgPJiOW5pKK6ZCUU4uSGK9W+cEKlSPu9dUC3ONw7FobxYjpss8r4TonKw97tb2Ptt9dORmHL4spKKam3dYfKMJz3Ixcn1UQxH61Mp0x8vpvqqNvw9i87Hsd/usbqOmriILDqP1tx5sDhPigMrbmPnklCz2huKHebqlbx9KgHrZ10yGvJ970Iydn0TqjVXxkWohNqUR9wK/J3QVN7NuHXX9nGTJ4wVWqIoCld2P0HEmUTW5+NSj+D6AVVfz299VCORVNV9/qqj4qY8zsPBn26zS3Eww90YcSYJx36/hxPrIsHT0CLMVTDT4wpwecdjs3KC1bAZ20U55fjrf1fx8GoqLu+IpivHq737SfdzzTa4sWXvd7dw50wSbaBXKpTV9sqrlVddkh7k4uaRpzi+NhLbPruOJ6EZCN7N3THA5HjZuoC9Addcyou1x0NGfJVhjW2qpu6cEnI4DsmP8vAkLMPIM0oZfHXjIDu5+/r+WETfZJ929sor41ypKW/j9s9v4N6FFDy9k40MlpZZXWp7UtBEUyZQKpR4EppudlV4tsSGqwSE8JOJAFQPHhul5fDPEfjz02Czw5HMoThPip1LbiLyUgqiLj3Do2tpnIRCdQgvAKTGmK8gJmssOA+vpbHKc02Lzcdf/7vKOjrEFFs0JmFz8j2fhGagOE/KaS/Ti9sfI/1pIW4eYW+AALS9Q1xYP+sS9nwbhg2zLwNQbcV0YMVt7F5qnvJUlFOONBbFzBLv52Dz3Kv4a572QqfkoMwD2t7SrZ+pwq2MebhLCyuMfp6VxLzYA8yyHF/AfWkpzpUiPa4Q2cnFyHlWgr/mX8Px3++xbp94n3turGZKUeL9XCRG5eDURtMFOLVD0zlfFk9CVYt0UY5549OUEndgxW3cPW9eWLFJqukIY+q6ksNN5GLMVI/rE+sicetEArbMv4bs5GJkJxcjN7UEp/+4z8oAXZBRdc3jayM5G+V4Bh6Hq3tjDAuEDPdZHfVgLOT7xsE4FGSWIezfqjB4s5Wkp1UGwWfReZyNB5y33jMytrKTi/HwaipCjxoP71cjLZUjP4PdWNGMtpBXKLDjy5u4e071/CiNGAWVCqWW4q429jy4mooNsy/j1EZ2BqqEKHZRJezg4dhv95CZUIRTbHbmMWMCUxsA0+MKtZSdS/+Yl798+Jc7eHQjHTcO1a4z6F8WMltmonF5/dGNNDy8Zp53WfNZf/pc/tn8v6v445Ng1rpHZmIRDqwI13ov5lYG47Ga6WKaqUgpj/Nw6Z/HrJwVCoUSfy/WTxVRG1XZzi0l+VItb7RMWolTG6MQE87cdzXH10Yy1r04u/kBLu+KxvltD7Wez7y0UsTezqTfMxTRU5IvxT9fhuDC9kd6n/E0oj3MSTEEwHruUUOUcQ0yE4u0rB5KM7x+TJi7EJ5Yx24iN4frB2LxxydXcHJ9JAoyy7QE6gdXU3Fh+2Ps+Kp+QntNoQ47M2cBUyopJN7P4azIhxyOQ2F2Oa7vj0WxxuK76eMruH0q0aSQounlNCfk2BC64cFMnN70APIKBfvokBokL73UYEVtc5SY8mI5yopkqGD5TD2LrlpsUs30kh/+JULL60opKSgVSk7PdXmxHEd+uWNSODUU0sm1yi2fo2faVMSBsdBgHoMEbUqg0UQmrUT8vWyt+ebAituQlVci5XE+MuILGUPKDCkxMmklTm6IohVeY6Qx5Duqlb38jFKc3/aQUfHSTHuglBQiL6UgL41doa17F5JZPbfGYON1YxsuXxvX5tqeqsE5URNNATT8RAJk5ZXYvzwc+5eHY+93txB/NxuRl1JMbn0lq6h61pMf5nKuAG/oaXwQnGpkHatqdWJdpF74tKkaB5pCaMTpqrGQEV9ocu5SKJR6OeK5qaWsoj7unk/GuS0PGaMQqpOfHMshnaO8WIZ937PLtQ87Ho9/vgjRez/kcBwUCiX2LAszaHg/ueE+dnx5E0kPchEXkYWNsy9j/axLtPdRHT2jpiinnFGuPLWBQdZjMYVTSgqXdQp4acpyRSZ2OijKLYe8gpucqxuerDl+n3IwsDPBdWcGLkhL5CbvBwDcfu4cYkIuU8lRV3Y9McuLrzn+1WuaWqlVG39McfTXu3rG8XsXUjgZX4/9dg+PQ9Lx7693TXpvjRnEn97Nwub/XTVZ/yI7pRh/Lw7Bfg0jwt3zyUiIzNEKf2ci+WGuwfSaR9fSEBOWqeW53/NtGM799ZB2XBnamSr2dhZK8ivwJNS4MeDGoVi9qCA2EVZc5zqijGugm+j/56dXWe2pV5IvNRoOZK7wohYKmbzF+RmlSI3JR0m+FE/vZulZ1SiKwpOwDIP9iryYgkqZEon31YJF1QyuqcDs/f4W62quam9RQVaZybDamiwWp1aO2PDwaipOro/Cvh/CTR+sgWYBrWKNB18hVyLsWDynKqRX98bgSZjxCUAXeYWC0QvOxkOj6ZUJOxaP6wdjzcr3oShKP5ffxM+4Z1kYDv9yhzHK4tI/j03m88mklVreGWmpHNsWXsdf/7tqsE1GfCHObXmIknxtBVIzOsEYur9NelwhUh5XPRNKBYXDv9zB5v9d5Vzp19SzZChMk6t1VmBheGpnmk9M5f1FXWIOi1UqlLiyW9/Io6k85zwrNvq8X9z+GKeNeHAOrYzAOYYQdCZvasSZREReTEFiVA4ubDftpTFU96Awuwz//noXMWGZeuNGqaT0Fvjr+2NZe7nZhLlJS+U4vjaSjh7SRcYiIsWckGw2kUnG1jOKogzWKVAqlLh5JI7Ry2FOX+UVCtormRKdRytP5rBl/jVGb7Paw3nmD+2okaIcKdKfFtLr7rMn+Ti/7SHjd6coymgoMJvUm6QHuXoRG5d3sjeuairmh1ZG4N81xufCyAspjOP07rlkOpedUlII/fepnjEh5FAcYsMzkfwwV+9rm4pqMBSuu2H2ZdwzomyUFclwfutDpMXmIzUmH1s/u866pokx5WvTnCsoyCzTkok0UY9lY5FHV3ZFIzo0HQmRKoOjbjqHoZD4h1fT8OhGGv1sxN/N1lqbFJVKXPj7kdk7MKTHFWDHlzcZvZ5q2MhpugbNq3tjsHPJTaOphHKZAhFnEpGrY8A0J/9cWiLXM7xSFAWFQqnV/8csQ4aNeTQ15z5Tnuz7V57hWbR26HzyQ8Oh9MZkSM3vUWngvnJJW9Tk4t/G18nUJ4b7dXWPas68fSrRaCStOvc7L60U+364hYKsMlRwNGZc2GZYaWdycGUbieYDjM9F2nIYT89xZGifc2mpHAd+vI3ISymc9T4LTke/5CgVSjp8kqIoPcFX97WiUolbxxPg4GaFpp3cDZ7378X6VlVNTP0kj26kGayerg6PDujsjgHvNKff1w2XbdjKGa/NaYPMxCJc+ucxfFs404vXnE39jV6/MLscVnaiqv5qdDj3WQnO/PkAU5Z1NXqOm0ficOdsMvh8HpRKCl5NHTBmfnvDDWpAFy8vloGiKOz7IRwyaSXe+rYrwk8mojhXigHTgvR+z4LMMlrg4ryPu8apmHKTuCplF7Y9gk+QE6zsRIi9nQk7Z0u4+9sxHquQK/Hnp8GMClbE6SR0fb2x8a5rLHDqokEWQr7JdmqK86RIepALCyFfb+I2tFhTFKWlRMfcyoBSCbTu20DruIM/3TY6Po+suoOclKoFOzulaoLd98MttOjljZa9vbXaqOsNmLNNC2B80gdUoc1qI0L83Wy00vhOJflSyMoVePYkH7Jy/cXGkLKd/rRQNSYNyCKGJvaQw3HITCjCa3NaQySxUOXH3s9BUE8vxuO3fnYN5cVydB/bBO0G+9Lvm1twLfxUokkldN/34bCyE2HkJ23g0sBW73M2RZuYUhqY7gnbEFZTaOYGlxVqK0vViZjSNRAZ4vbpRCQ/zEXyw1yttUdaKoe0RI5DPxuuqaGG6ReVlsoRfiIBbg3t9AquBe9+ggdXU9Gsm4fWWqNUKGlPn19LF4itDYsN4ScTEX4iAQOnN0dgFw+tzx6HpOvtpVx1De4Lwp5vw1CcK8Wkrzvj2PP91a3txWgzoKoYLFPUhiEeBKeiz5vaW6cay688/HMEXH1tMeGLTvj3ucHm2eN8TF/Zkz7m5tGniL2VCfdGzHM7oIpS82vpDFsnSdW5f4nQiqaqaQylneSmlkBaYrzuQUZ8Idz87JAQmUN73Jnm8Iz4Qq25G1ApzY4e1oznrZQpDD6/us86paTodU1toAVUBTsl1kKDfT+35SEGv9uCfs2l9oxSSRlUFo1FxTy8loaH19LgHegIoCrVLD2uAHF3sgwaOhWVSlzeEQ1lpRItennj9B8qY8z1/bHoMzkQl/55zNh/trVsTHlEc54V4/jaSHQZ2QjNNdYT3d9C14Cnrmdw83Aceus8T2runktG+IkEhB6N1xo7RTlS5GeUGhwjTBz99Q5yU7WN1XfOJiH0aDx8ghwx6lPVzk9c6pikxRXAs7E9QAHSMjksbUR6x9Bh0DIFMhOL4NnYntYvMuILaVlzzqb+oCgKeemlRlMFDdnrivOk2PttGGRSBYbMbMl8UDUpL5bB0lb7OzLpSLpoGhJ3fh2K2Rv6aX2uUCjB4/FQmFWlqOeklODyjmi4NLDh1EdjDiz1b6EpH5qTTqWQK5GRUMggW2i/fnqHOUrn7rkkZCUWIYtDZKCa/5QyrqikwBeovB6Hf7mDtgN8aYF0y/xrBrd3ObflIZp2cgdFUbi2NwY8Pg+9Jgawv66Rqn0URRkNH75/+RmUCgrRNzO0BCRd1PmSJ9ZFQloi1/KkaS5cBvtoRBhiui+6D6payFJbcU0pQjXhFw89Gg8ej0d7G4typLSy2aitKxq1cwWlpFBeIoeVnQi7vjFefEdaKsex3+7B1ccG1g5itO7vQy/sxn5DAKCMfGwoL2fbwut4Y3FH2spmSClVe0C4FAHT6hvDzc7PKEP8vWy4NLCBnYslY7vSggrw+Dzs/e6WwbBGQ4bz6Jva2wOqcx25TlK6wpxmhEJOSgmCdz/RUsY1xypngwtLDH3n8hKZScNcaUEFMhIKEROagc6jGtHj67AJ5Ur3mrlpJRBY8OnQts1zr+K1Oa1p70zaU2ZBXl0QJeRwHNoN9oVcpkB0SDrs3ZjHgC63jscj6WEeRv+vHYRigVGvkiZlRTKc3fwQwz5oBXtXSwiE1QvKopQULpmw6AOqlBa+BQ+Prqeh02v+WkZHztd8PucZe9bVKCqV4At4esKMqfGhxtCuHlyqnlNQCeaPrqeh96QAWNqKcH1/rEGhRl1lV3etiQ3PpL1vprxw4SdUz/mFbY8Q2MVDa50w5jnh6kW4dyGZzofUNNTk63o7arnQs27hJF0v950zKmXVWJqHQq7EP1+EYNqPPWDtIEbOs5JaVcR10fyN2Gyjpp5DmAzQmkWVNEPj1RiryK732xlBqaQgeC7T6BZuNJSfD6jGcr+3mkEoVm2jy6V6u2rnoOfX0Hmu2Xjh058WaL0+/Au7CuhpcYVo1t2Tfi0tlRut76EbGq9rRCjILEPMrQyTuxJc/PsxygpluLwzWksZZ6vs3w9O1VPGlUoKpzfdR6KB1IziPCl2Lw2Dm58tBr3bAg5uViavo6uIA1VGWc2INlOKpSZHfrmD/lODkBCZjYTIHIxb2AEejey1BFelgoJCrsS5LQ+REJmD5j084dPcGf5tXfTu7Y1DcYi8oF+FW9OZkRpTgNB/n6JFL28tw9y+H27RkVCmdjY5uT4SDh7W6DGuCevvCqjqyrw2pzUatnIBoJJZT2+Mgt/z12zQncPzM0qxe2kY7N0stZRxQDVPcvk9TF9c9c9+jYjXsH/jkWOgsJ1e8+dz4OFfIvQMlZUyBeuUSkPGZjb8t5RxuRJCsQAhh56irFCGkMNxEIr5CDnylFUhqvJiOe4HqwSWziP9IbYybIHV5M7ZJDTp4Ea/Tn9aiCdhGeg2uhEemthEXnNhiYvI0jqPLgdWhDPmsWguXIbQVJL0JkqNgVgpV+DxjXSEHY/HqE/aws3PsMWfbk5RyE0thaOHVZV3l8XoLi+RwdJGZNRCp2nBz0ioEmCu7Y9Bo3auuPD3I8SEZWLkJ2302ioqleDxqopNRV1KoYv7ACrhYMh7KkukuhovW8qKZIgNz0RgVw/aa8IEmxwpUyHtd88la3k5dSlnCIOMv5tNC7FMRoBKmQLbPze9v2tJvhRnNz9A634N0Lh91diMvsncZzb3MeryMzy4morXP21r8lhddAWR2iBGJ1QwN7UEIksLxrxDXR6HpNFVe+VyJQZMDWJ9XfXzX1Emx95v9YVmzf2q2eTGAarn5/5lw5WZdVEXW3wckobW/XwgFAtYe5cKMsuw53n1cPWYS2IIWWbD0V/vsop8OPjTbfr/pQUVGP5ha7Oud+bPB8jPKMWELzqxUhyDdz9ByuM8dHrNHw2aORo0eBlCc7qulCtgIRSwKtaoCY/Ho3Nd4yKy8MHvfZDDMuVIkxIzjVppsfk4svou+r3VDM17eBk1YlzZ9QQtenkh8X4uuo9rDAuhgP6MqXq2Zgi1ppEyPa4AT8Iy9LzybGFjuDbF+lmXMHV5dy2Bmg2ZiUXwb+Oit52PMa7sfoJm3Tzg4W+PmPAM3DnDXhi8cy4J5UUyxN7OwsQvO+l5xgxx+1Qi7N0s9VJn0uIKTCoLWYlFcPK0hq2TBIpKJV2ENOl+LtoO9DHaVpPUmHw8vJaGVn0b6IX+mhLyNZ9fLgZbSklh17IwFGaVo8/kQL2ILFNoGpI5QVHVMs6c3/JQy6O6f0U4K3mXadcDoHrbz53eGKVXaFPLm/mcrKRi7HruaS0tlCH8VAJa920AZ28bVMoUuLwzGv5tXI3Kw7pwfa5jb2fSUZD3LqRg6Pv2Wk6ko7/e1YqaenQjHY9upKN1vwYqxf05Z/96YHD7Sl15JeJ0EiJOJ2nJZIaiZplIvJ8L3M9FebEM/d9uxrodoApzd2lgi0q5gpZZDaVJsUEdvauriAMqWcDOmdv8aA5saxj880UIGrV1ZYwYSostgMhSX1XOTS2Bs3eVd/+OGfuZa/KfUsbVVllNa1TwHvb7wGlO4ornEyubnBpd67naC6ZUKPHYhKdBqvEgnt38AE06GA7pNRR69iQsA0oFhRY9vcwTNJ43qZQpsH3xDXpyuHEwDqP/187oOWNvZ+L2qUTkpZWiYWsXvDa7NdLiCmiPgTEKs8qRFluAS/9EY/B7LeDXwtno8ZpKktqSGBOmmkyYrPSbProCvoCHWev6gsfj6YVKxt3OwpD3THaTkZMbopCVWGRS2dC0WFfKFLAQCYwczUzI4TjE3cnC+EUdEHL4KYpzpRgyswWkpXJO4Z+lhRWQ2AghEPBRWsiuwN21fTHIiC9CWmwBxi5oD88mDgDMCxFXC8LqImY3WOZARV5M0QhNNf5975xNwpOwDIye1w4ZTwth72oFJy9VSBxFUQYFEE2u7KoKXWW7zYUaTSt+HkfF6OzmBzi7GXhtNrNCybWyfUl+BWJvmbfYque/wK4eeBDMvbJscZ4UD4JTzS4yZs74SojMQVZSEZy9uIXHAVVhafH3slk9U49DVPO6OqrFVKqQLppXyEkpgUcje84FGHV1kvPbHiH3Gbsxt37WJbg1tEODQEezUxiOrFIJdJd3RCM9rsCggQ5Q3Ve1kG/jKEb7IX4oyinHvu9vmcyP15zb89JKcWHbIzh5WcPVx5bzntF3ziWh3WA/XP7nMdwamjY0G+LKridw9mYfaguonAXXD8QaDFtm4uHVVDy8mooOQ/0QwWJN1eTm4SpD9rZFN/Duql6s217Uqccgk1biCAtP763jCbh1PAEDpwUh/GSiljG6IIu9Z/z476qCTkzpK6Zy8NV1BcpLZAg9arognZqibCmtWOhGZHGFy1ZWKY/zORWv0yUuIguD31M5NKQlctbrhGZOray8Emf/egixpQBKDgF6p/+4D2cva3QY1hCKSiXjjhf7jdTv2frZdTh6WiE9rhCPrqVh0tedse+7W6AoVUqCtb2RVMhqojnrPb2ThT8+DUZbjRQY3fQlNVGXn2mlpRhSxAFmQwRQfaPgk9AMOLhZ4pmRfG9d8jPKjNYPYMO/a+5i1CdtWfU9meM2i8aIi8hEx+H+Zrcvya9AlBGnBFMkhzqKqNfEALTu10BrPjWH/5QyrqhUTULmeM8oitKywBdmq6pisj1X+MkEuDSwgX8bV/o9NhZG3a2Z7pxL4lwyXy3EBe9+gp4TmqJNf/YWaAC0tz3nWYmWlS4ttgB/zbuKHuObMraLDk3XWrTVA5rNog2owoDUhXNOrI0Ej2fcoa5dZEt7xTAUuqZUUNj3fTgmftWpWpNfVmIRmnRwoz3/6kgDU3tfPtSoiJuTWgIPf5VFNepyCirKKtHpNXYTTFZiEU5vuk+Px60L8g2mXehCURS9f6+bny3eWNyJVTtAu8r34V/u4I3FHbW21WLLtf0xiL6ZgTc+70i/x7Zw4PUDsQjs4gGJjZDRCquJOpLi5PooOu970ted4exlgy3zrxkMD64NFGZ6Sk4yVd41g+osvCGHVLsLJHOMGFFzfG0k8jlueySTVuLYb/dYj2smDqy4bfogI1zfH8t5r3tAFS4ffsp0MVBAFZaomZ5xamMUgrp7IYaj4UR3LHPZShCA2blvTBhTxHUpfB7OfnBlBKtCdUzs/yEc01f25FxDIPRoPKIuP0NZoQzRJqrsqlGH92uizvfnQvCeJ2bPP1wVcV0oJVWtPe83zzVcUJMJpuKKhpSbmmbrgusY+XEbgxWaDbGnGvdHlz8+CWZ9bHXmOzXx97LRuJ2bXkg/W7KSi+nx7NnE3sTRGtd9HoEXzjKdSRdpqVwrKkA3IoxNqP+F7Y/Qd0ogpz2fAX1lsbJCQadBmiLVQME/XQytgRtmX0ZAF3cMmt4CfIG+o4gN6tTAuuRZdD4OroxA55HcFOPr+2NBgUKn4f5aEa5sCTuWUC/fF1A5pBw9TadTmOI/pYxnJ5fA3tW8m7bjq5tae/aZyvHURb0v47iFHej3WIWf6Lg3qmt9ub4/lvbacEFeoWAM/5JJFQaruupazwHgr3nsF+0jq7QnWi4F2Ctl2luzGKsImZtagoR7OYz5hdGh6QgwUrxPTdTlZ3gUko4OQ/3g5qtfpMoQmsq6SKx6HCklhWv7VKHMXLxSmoYhLgv44xvp9G+YlVQMhUJpcIstXXSV37Bj8UYrhjJxdW8MXfQl7HiV8MylgviWBdcwa11f1kKpZhX3vd/eQsve3nWqiANAWVEFFHIlru5nH51Tn+hGAT1kUELYwlURB1QFtkxV369tzFHEAe1weVPo1kkoL5bX2jZlLyLK53mYTOk1XFAX9eIKV6XQWJE3LtT1/KML2+rjrwJcFXEmuO41X5/kPCtB43ZuZnsjNefruqxnUBM8Cc0wuX1VTcO2wr2xLS5jwjIxcFpzs5Xx+iIrsQgnOD5fkZdU+fRcooJeJNQFRKvDf0oZNxXmbQxNRbw6XNsfy+l4rtZ1NrANVdSkKLe8RrYjq0uBg0sIcUZ8ISzE+iHiF7c/ZjQqMFFZoUDYv+ZXc6aeB6dqbs9TU9WhjaFrTAne/YRzjrwaroo4UFV9FTAe0mWKo6vZbV3GBJN3q7ZRKig8uJaKRybqRrwomLP9VE2it60e4ZWErUeaQKhPdHe0eZG5fTIR3gGOZrdn2vaPUPvsXx7OKnWO8PLzn1LGXwRqKuyvrmEqGPUqcdfIHqZ1hbomgdmFXmoIU3UMXlReNmWtoqwS1zka5+qT8qLqh0tWh7oozkcgEAivIsYKyRJeTHSjpAivLv85ZfxZdM0VDSAQahJZeSVOrIv8T4ULEl4eqlvchUAgEAgEAoGgzX9OGf+3BmL7CYTaQF19mEAgEAgEAoFAILz6GKgxTSAQCAQCgUAgEAgEAqG2IMo4gUAgEAgEAoFAIBAIdQxRxgkEAoFAIBAIBAKBQKhjiDJOIBAIBAKBQCAQCARCHUOUcQKBQCC8lDi4W9V3FwgEAoFAIBDMhijjBAKBQHgpad7Tq767QCAQCASCHjN+6Ym+UwLruxuElwCijBPqBAuxoL67QCAQXiGCenjCQkiWMAKBwJ73Vveq7y4Q/iNY2oggsRbWdzc4M2Z++3q5bueR/vVy3RcBIskQ6oSmHd3quwsEAkGH4R+2QvshfvXdDbOwdhCDx6vvXrwcjPi4TX13gUB4IRBbvRjKkYuPTX13gRO+LZzruwv1Rp/J5nu3eXW8SE1Z1rXa5/Bq6oC3v+8G3xZONdAjdgya0RydXvPHu6t6YfbGfvAJcqyza7cf4odeEwOqfZ7W/RqY3dai2lcnEFhg6ySp7y4QCAQN2g7yhX8bV7g1tMOds0mc2r75TRfs+/4WlAqqlnpnGh6Ph/+CNt57UgCu7o2p1jkEFubb3Xk8oEVvbzwITq1WH+oS7wAHpMYU1Hc3XmmCunuiKFeK1Cf5ZreX2Ahh52KJ4N1Parh3tc/b33dD1JVniLyQwrqNnYsEk5Z0gVAswKPrabi8M7oWe1izjPy4DdbPumR2e8/G9shMKIJSyX3NcPS0Rn56Kevj+09thkv/aN9bK3sRygpl6PhaQ8TfzUZeGrvzOXlZwTvIFhJ7bnNo007ukEqlUEDOua0uQjEf8golq2Ml9vxqX08qlUJkw8Ogmc2w65vQap2LDQGd3OHb2gFSqRQQABUVCti4CiFJ4/49GjRzxLNojnOSUAFYKDjfN1mZEhYCAazsxaAoCt3GNkbU5Wfcrv0coowD4PF5oMyYIOqDxu1d8fROdn13gzNtB/mCxwPCjiXUd1fM4rU5rXFyfRTndu/+0gt8Cx74Ah7++DiYW2MegJdjWGoxZ1N/zou2naslirLLa6lH3PFr5Yyk+7msju04vCE6jfBHpUyBvd/dQnGulPP1eDyA4vhbdxvTGNJSOe6eS+Z8PQAQW1k8vzZ3hdbJ0xofru9ntnA24YtO2L883Ky2agQW9aOI93urWZ0J0ZZ2IrTo5YVbxxMgLZWbdQ5XX1t4NbE3qy2PB8ze2B8xtzIYlXHnBjZoN8gXF7Y9Ymz/xuKOOLDitlnXBgD/Ni5IiMzh1Kb72CYI7OqBbQuvm31dtgz/sBVObbxf69dhg72rJRSVSpTkV7Bu07i9KzoMa4j9P3B/Fr2aOkAmrfptOg5viNunElm3b93fBy4NVN7hG4fiUFmh4NwHezdLFGbVz7ph52KJBoGOnJRx94Z2EKpT9syYvnqMbwLvQEezfq/qMPazDjVyDnmFAgVZZZz6L7aywKAZzTm1CerupaeMT1rSGVlJxfBp5ojkB+zWdq92YgT2skNa1jO0GsltDhVK5EhISEAlX8GprUDIh0KuUrwlNkLVOsfjoZTFc80X8JCQkIC2Yx3pc+iekw0JCVVyeqtR9rUuh6rvlSYuzQEbX+7rlsiSD8cAbn0WWUrBF8k5/U4UAGWlEn4BnvDw8AAPPPD45sskRBkHMGh6c5zb8pDVsRO/6oR939ftRKgJxf55qjH6vBmA4D1VnhlLWyHKi7kJhkKRAE07eXBWxruM8kfj9m7YvTSMUztNasKzZC4Sm6qQOO9AB6Q+KWDdds7G/igtrEDEmSTcN9PaZi4z1/TG5rlX6+Rank3s0XagL05vejGE2tkb+oHH52H30lDkZ5QZPfadFd2fh0vzIJJYmO2obdzBDXG3szi1ad2/AaQl5ivj6r7yaiBZyc3PFllJxayPd/W1Nes6r81ujazkYsTfy0arPg0QezuTU3tzDEW6NO/pxVoZH/BOEJ6EZXC31D/njc87gi/gY9pPPbDpoysAgLYDfXCPgwLwxucdzRYSTIXu8XjQsyK16OUFB3crNOvqibJimVnX7TslEC16eSPseDxnZdzR0wpWdiIMm9VKa04Z8VEbnFgXaVZ/DCGyrBKh/Fo6I4mlkF8bjP+8IyrKKrFzyU3WbXqMbwpbJwm6jWmMm0eecroej8+DrbMl/brLqEZIjclHelwhq/ZqRRwAYKYzhG/muPZq6oCs5GIoZArORlAnL2sEdfc067o9J1Q9T2x3gmjWzQO2ThLkPCtB6/4+4PN5GLugPQ7/codVe98WTkh+mEe/trQVQiFXQiZlb/zwbGyeMU8XoVgAVx9btOnvg8hL7Oawd3/pVS0lR43EWgg/DqH2Xu3E8GltDXd3d0jEEhRIuBl9xFYWsHGUQFYuR3GeaUVaIOTD1kkCvoAHaZkcCpmSli0AIDe1pOq72IogZZhbBUI+HNysQFEUKAp0NIFIIuD0ezt7Vz2bxXblnNqag8RWBGs7kdZ7FWVy1oZFoUQA+fM+WtqJILGyMCm7aV9fCGs7MaSlMpQWsFuzKFCQV1agsLAQPB4Pnp7mzQlqSM44VDeVLS4NqoTIbmMao8f4Jhj5Cfd8vB7jm8DZ2wYzfu7JqZ05IT7VxcZRO8S854SmZp3H3tXS9EE6OLhbw9HD2qzr9Z0SiOkre6JV3waYta4v+rwZgNf/186sc9WEZbDPm9zzjqztxeg9MQAf/N6H1fG2zjWTDiCSWIAv4L4ATvyqMwBVFVFA2xjBxJxN/TF2QQf4t3FBtzGNMWpuW87XVHkLHPTeMxf1wt99rOlz2DhKtD3LZmrj3k0dOLexEApg4yjBB7/30VIKjMEk1FQnp63NQB8IhHyMWVA3BV8cPKzQeYQ/Jn3VmfV31uXNb7pgxEdt4OZnnkGAC826eWLo+y0xcHpzzFzTm3N7dXqPwIKPfm83Q5dRjdDpNdNFbqzsRZi0pDOmLOtaLUHW0lYlIBlSWHg8HpQ6BmJLWxHaDvSFxEZotrJEKztmzLvqvjZq66r1vl9L9oL4hC86sTpO89kxZ75kosNQP9hxWCvbDvLF1OXdIbEWcp5+1H1u09+Hc/Gk0oIKiCTahVnNnUsqK830Mph5vdH/a4d3f+lJj28u9Hu7GdoO9H1+eW7Xt9JQOLyaOGDAtCCMW2Tc6+zV1BGdRzbC8A9b08+TZxMHdBvTmOVVtfs44+de6DXJvPxY70BHCGqgaKYHB+VePX8Zq3vh7m+n917bgT7a5+HwWwmEgEegBM5OLnB2doaVtRUkEgmEFiLWfyKhGBKJBGIxu3buDRxhbWMFS0tLODrbwcXTAZaWlpBIJHrXFovEzNe0UF3T0tISVlaWcHKzg8RSAkc3O059V19TIpFAZOBa6j87RxvYO9tyOr/un6OLrdY1udw39b3WvDdW1lacri8Wqe6bja01+2taiOHp7Q43NzcUFBRAoVAZA8zNdf/PK+PNunpAKOJW6Vtt0WzWzRNtB/rCtzn3whZtB/pi0pLO3BcDijJLCHXzs8XrZig6AODiUyW0jvioDZy9uBUecfKqUqY9GnGzsDZu52r6IAO06OVNL34CCz5a9mmABoHsHxRN6yDF1XwOoGFrF63XXPZEnvZTD63XFizH6NQfumu9rk4xDy5CfOP2rugzOZD2dljaiDBrbV+8s7y7iZbPr8Xjof0QP/g0c8J7q3uxLoQx4+eeaDvQF7Y6BiO1sMQG7wAHA51ifYrqNAEANO/lbWbL52OD5fhsN6jqvljaqJ4Nrspax+EN6f/3HN8Us9b2hYWQ/RxqrlccAOxdtJUUtgKWd4AD2vRXCWdOntacFDMmrOzYz9tiKyECu3hAJKleIFrzHl7oOLwhq9+rRS9vOHvbmLUPe5/Jgej3djM07+GJRs/nX7GBNUfVF+2xp2kwNtZXzQJWzbp6aH3GF6hEEy6hlTRmzNVqRn3SFjN+6QlXX1uM/7yjyfBczeGnWdlfrRw4e3MzJPea2BRdRzfG0JktWbdxcLM0uyaL1XP5QyDko9Nr/rBxFLNumxqTX2MlG9Trso0T++sD5peM4PF5sBAKMGxWK1jacivopmlgMuf50qRZV094+BuXiQwZeVr28Yarr63JuYjpHgV0ckczlt59ze/4+ty2mLm6N5p18zDSogqf5qoCYOYa5TQx5tVuEOiIoe+rnhnv52Opx/imGD67tVnXElrxIbK0gLOH6rfh8XhaciwbuKYVsV2HVQ4X5jlObK09T1vaiuDsZQOBoBqqnonp1NpBDBsH7efWycuadaFElwY21R4fFiIBLG1F4FvwYWnCAaTG2oFhrtHshpHJxcHNCq6+tpDYCGFlpXo+5HK54fOy4D+vjFMU4NfKxfSBGkz6ujPeW92Lk0CmSfuh2tWLuQxEigJGftIGzt7WnBaCrmMao0EzJwzhsMirsXEUY+JXnfDOiu7wa+kMZ28bBHZlNxkD2sWDgnpwC+WoifAkc+n0WkP6/+Y8YC109kDWVByEEmblpf/UIMxc0xvW9tyvpzsemj8PFzUXLoJOn8mBaNlbW6EUCPlm/X5iKyFsWAqXamOWsBpb5wk4KJKm4PJ9fYIcMeOXnvhwfV/w+Tw05/Bs6EYcsFE/7Fwk6DLKH4NmNEdQd08EPheouAq0ur8zV8Y/9wQ1aMbNgtx7UoD+/WXZ99Hz2psV0WPjJEbX0Y0w4+ee6DDMD8NmtQLAbuuXLqNqZ5sWNr+XuWtT4/auaNnbG817eKHf20H02uQT5MQogDPVOmjSvmrnDGsHw/0YrRGlJJRYMBpp/FoZN5qM+IhdVFobHS+ZQfhVRir3hnYmw3M1x2PX0Y1h4yhGtzGNMWxWK3Qe6Y8RH7XVOn7Up9qv1XgHOmDWur5o3e95P438xroKfrOuGvMGx2dZ93ma+FVnCCUCug6GMeycLc0u4DhuobaRY9CMFug80h+j/8ctwobr1oat+mjPXR6N7DF9JbfoRM113N7VEqP/1w5eZkQ2sb6ega8oklhgwhedMH1lT/QY3wTNe3kxH6iB+r7zBXwMmBqk9xu/xqC8aspvPB4PAiEf/acGser7gHeC0KpvA0z4il2kiSlGftxGy0lS1TGgcXs3TFnWVStSVWzJvLY3bm96dx8rOxFE4qp1lmsURFVtgJqVYfl8HuOCzxfwDc/7HLpgyPBqtD86WAgFsHe1ZLetWzXvj9jKAtZ2Itg6SeDsZU0bck1hjowNqJwJIksLejzojose482LHP7PK+PmhNIJBHw9qw+brbtmb+iHd1f1QrfR2uFFbELP1X30DnSEh789Ji3pwm0BeH6JJh3cGCdcU7g0sNUKV2/CYjJjgm2uVY/xTTB+UUe999397RDQxd2sa3OlUTtXDJwWhDe/7mKWN8+UIMmEhYjPyoM2YJr+YqhOAxg1ty0Cu3jojTOuGFp8mAwTBpVhcz0XJtr5NnfC7A396NemBEdzrmVOyKVuNIQhBBZ8jPq0HSxtRPTiIeTgOdWNMDG0sPB4qnA9gZCPkZ+0BV/AR0BnD/SfGkRby7kaTMy1/KpRf99+bzVj3cavpTOjsFldD7cpgrp7ocPQhrC0FaHr643p0GcHdyt0Hd3IaNuWvdlvc8JlWxVT4dDNe3gyGj09GumHcuoyaEYLxvcFQj4GvNNc732mZ0RzrrQQCjDj5556kT6A/rhjety8A4wbbEz9/gGd3eHW0A7d2Yb0ViMdydZZgqnLu6P9ED9Y24sZPc3GIqw0lR5dmWTwu1W/i66wpxk2zPR7uDW0w7Qf9e8/ExJrId5f0wddRjVCQGftdXb8oo5aof9NO7mjZZ8GEFtboHlP04qgJrrzl5WdSHW/WHrGu4xqhCEzW6L/1CDYOIrR7+1memkJmoxb1AFdRzdCV4ZxwHme1zncO9ARY+a3x+yN/czOJTcGn29aTG870Bf9phiYTzX6q3vfO+hsa8m0fvV5U39uYnPPxn7WQZVmNymAczSlmoHTtecc3xbOmLSks8H+OLhbaXmBPZuoIqL6TtFOEdQNYa8pNOUgu+dRXDWli1vZiiCSWBiMjBVbWZgls2i2EQj5eikyVvai5+fnviWgjZPE7HQyNg4WvoAPe1crei2p2W3kmOdqU9eQWAvpKDwu/OeU8fGfd8ScTf0x+L0WaNjaRcv7WR18WQiFPD6PlaXIwd0Kvi2ctQbxlO+6YsA7QWjdv0rA41IBXvNcDVu7YPyijgjs6gF7N+553AAYlSxDOUxeTRyqmrF8WNoO9GXMA3JpYAOe2cHA7JnwRSfweDwEdvWEk5c1eDweJy/zu6t6Gf2u1Q3LcfPVvzdqOc+nmRMGTm/OzippBEPdH/qBdnSFd6CjwTDl2tpjs8+UQC1h3tJWRHstueLgYeB3NdH1t77rpvcea28ow7kdDfWDAd3xM3CavqIEqBSEHuOb4v01veHgxnx+Poff6J0V7IR6TQzlv3KJJh7xURvGUDs2W3YZjAZi8b0tRIbPbzI9ieH0037sQdc30Mwt4xIVwRfwMfxDw2O939tBjPdq1Nx2ekKpLly2QLMQC9CbQVDXxdJWxGgs0lXGe78ZCKFEgJ5vaCubXL2fmuNq0IwWdBE8do3135pqJNXG1ddWtV43dwKPxzM932mc/7U5mkZx7Xa6kS/qcF9z6D0pwCwDmu5Xcfe3g8iqSo7g8XmwshNhxsqenAxrxq9p/P7ZOkkw+L0W6Di8IZp0cIOztw3eWdEDzXt4YcA7hr21jh7W6DC0oUFDtzrEuTp95PF46FpNAzgTNRHibQg2+d/mRtdVt+jbrLV9EdiFXQSmMYN6zwlN0UInDYz1fMARC5EALg1s4OprS8+lQrEAEmshY6ohl4g+GycJHNytzJKprly5AveG9igsLDB6nMCCT5+/b9++mDt3LoRiC7j42MLOhXsqDJ/PMyh30BgQBAQWfHy25GNMe3+ywaa6NStMsffALjRtxZDCyNSFOi7PVSsjsri4GHPnzoWfnx8sLS3RvXt3hIdXVSCfNm0avXCp/7p21c5traiowMcffwwXFxdYW1tj1KhRePasehWlOw5vCPeGKiWmaUd3vDa7tZ61x9ZZYnaBMnOxZAgtGflxGy3l1s7ZEs26eWoJWVyUcd1iRe7+dhg4rTmnHDFNmIQ9Q5bpLq9re5D6T+W+cE/8qhPaD/FVFdWqg8h1Jk+4k2dVeKAxRdeORXiOOYVjNKmJCtiAvvA9ZGZLvPl1l+fXYL7REiuhVi6W5n3RxdhPZSw80NSCY+esr+CZm9LQeYQ/Y9qAsbM17ejGWJCQbe4009fzNVHpVVNJ0RWu3f3t0GVUIz1FRo1R4YPDWOI6X4gsLfD2d93g20JfmWAKYWYS/DoaMZiyqeXQpAP7KJ6ebzTFzDW90ay7J5wb2KBVH8PebXOiZawdxBjxURu8Nqc1hs1qjYlfdcaELzuxrgmhxr+NK+fIG6FIwGjg5II6zLfvlEDM/LU3XH1sWQstupFcukYg94Z2eG91b7QZoO1VMHVv3ljcscaM6kzFXG2dJJizqT/j8QILvqogoJHiUmrc/GxpbxkANNRIj9OdD6ztxRj8Xgs0aueKfm83q5Zh1VAkhe66rA+7+bQmFRtTV5y6vDuadmSOjDPmgTN1Xs2w5fZDtIV1K3uRlkfZ2NJkZSdiLLbq4G5ltP6AMUXHrWE1C01WU6mobq0Lc5i0pDOnQnE1kc6o6ejimh9O94Oneh405Rcejwc7F0tGgxiXWitsUSvRnHjeX0O/NZ/PbGjUDIvnm+udNnI8j8+DUCzQe7adPK1h4yBmnc5oCj4tB9eMcqGbu8+qDzVyZR3ee+89nD9/Hjt27MD9+/cxePBgDBw4EKmpVfuUDh06FOnp6fTfqVOntM4xd+5cHDlyBHv37sX169dRUlKCESNG0BXruDJ1eXdW1UJtHMWcinypqc5PqBsqRJ/TxEk1w9sHvduccUJq3tMLY+a3N2rNNQdvhnxPB3crTPuph1bRsMCuHnrWv6Du3ELaAFWYfLcxTVS5GkaOazuIfeEurvSZHIjmPTwx/nP98HlN2NxRd387xrBRNr9Hm4E+BhYf7qtuv7erDCNtBvqgSQc3eiEyZDCwdZHAXyOczahCZEJwqUmcOSygM37uiYHTm6sqkUssMOqTtrBztdTxVtUe5ihybQb4YNisVmjU1pVxLus4vKGeIsPG+8zFM24uTMYTC6EAYz/rgMbt3TBmQXu0H+KnlVPb7+1mmPlrb3QZaVhp0BQeuEZGMH1td387iCQWGDA1CJO+6szac8Fn2PPc0G21EArQsJULhOLnXhQf5rEweWkXo9c051erRm0zAECvSQGYurw7WvTy5uyx0322NA2K6iJaTOd8bU5r2LlaYvjs1owCrZufHTobGSPa12TvuTaGnYuEDuM2JKgy4eBuhREft2FVrb1pR3cM+6AVmvdgv14yFbxjuqedRvij47CGrM/LhC1DSHm1p5I6MLSbpqoTvi2cMG1FD06pfRYiAQa/V5VW0H1sE0xZ1tWop9iYTKS7m40xpq/syWoXELa07O1tUCl2a1g9w54xGPPCjdCsW/XSA2au6Y1eGtvOCcXsVCNbZ4m2Q8PIAyCSqDzkmr+nWmmrjsHDyk4E/vMoFUMYm59sXVS51nYulpyKGTp6WGvNxw7uVhBZWhiONGRAYME3uY7wGLzrFiIBrOzFnNYgJqOuvaslLG1EdNE3gcY6zmRkZLtbkTlGlhpXxsvLy3Ho0CGsXLkSvXv3RpMmTbB06VL4+/tj48aN9HFisRgeHh70n5NTleeksLAQW7ZswapVqzBw4EC0a9cOO3fuxP3793HhwgWz+mXrJDFb8WRDo3ba3hcu25y07t8AE7/qhD5vBkBiLdTLkzGEpmc8oJMHY15Yv7eaGc0tN3VLDFXNNPQQWNuLtbxbhkIMNSvpcqWlEW+VMS9tdbGyE6Hf20F0dIUhnBuY/m7m5tEAQIMAR8b772JAqDdGw1bOeP/3PnhnRQ/0GKe9iDOF7rXq10AvKsLYENJ85jTvi38bbkUT2WDnYok3FnfE29/rh49r0mN8E1jaihDYxYOeoD0a2ePt77ppeauMyeVcdJpOI/y1LO3Ne3lh8Lv695bNwtKorSuGzWrF2lPGKuy4HgVgz8b2GPp+S3g936rH1kmC/lObIaCLOwK7eph8TgQWfLyzogem/diD89aJ6qq7NREG6hPEEEZcjfWmz+RA01s6mnP+airjPB5Pr3I3250mRBIL9NbYUonH42Hwey3QpKOb0d0P1M+mf2sXvLHYsCFUHWHm2cSw0sOmtgsb3vq2m8H8eoM8/738WjhXa0cBUNy2z+GSeqAJU/RV+8Gq38nGScyoJLZgKO4otrLQiswzZsw2VoOAjULMNqzZGFo7VfJ54PF5nLet0/we7QabdhBUypmdTFxzT63sRGg32JfeBQEwHc1kLNQ3+VGuwc9GsogGqSvM3U1Aja4y7N6QXYi9pY0Izt42sHYQw0IogJURZVbtIddUeAUWfLj62HJPF9WYcm0cJXBuYAOBBR/Tpk1DcHAwfvvtNzrqODExkT7W/rlSm5efhw8+noG2XYPg5GKPtu3a4Mixg0Z1pDNnzqBJKx/sP7QHgCrEXn28UqlEw0Z+2Hv4H63dqe7cuaPqQ3IC9h7YBfeG9lp/Lg1ssXTpUgCAQqHAvHnz4ODgAGdnZyxcuFBvbenYoxX+2LJB6722bdvS5wCAgoICvP/++2jRsQl8A9zQe3BXnLt4RqvN5WsXERQUBGc3R7wxZTQyMjIAqH6jMRNfw1fLPoelTVVqwTszJ+OT+R+ylruUuvt9sqDG408qKyuhUCggkWg/HJaWlrh+/Tr9+sqVK3Bzc4ODgwP69OmDH374AW5uqoUyIiICcrkcgwcPpo/38vJCy5YtERISgiFDhuhdt6KiAhUVVRvEFxUVmdV/cxV2oViAPm8GIHhPDP26oqyS/tzYNhI8Hg8uDWzh0sAWLXp7V1XpMyEkmvF7M13c6MfGrKxvft0Fe74NY/ys18SmeHQ93aDHYviHrRFxOhGpMQUoyCyDRyN79J/aDGf+fIAOw5gjBdS4+9th+sqeOLAiHCX5FVqf+bZwQv+pQZy3lKkpmnR0Q28WxZj4PB7827oiI157nBqblPtMDkR2cjH8WjqjOE+q9Vnnkf5a21axhcfjQSgSMG7v5+xtgwbNHPEsOp9+T1CNvXQHTA2Cq68tyopkprefMHIZY3nZbn6mrfVMXlpGzFRcRn3aFsd+u0e/bt2vARq1dcGx3+6h88hGBquRWzuI0byXFwQWfNy/XL2UHDVsog/YznliK/OXC2NVtXUJ6u7FKXpGLWxqKh0uPqrtUowV1Ov0WkPYOIjh19IZO766yfp6mti5WqIouxxNO7oj6b5hwZUrbCrWuze0RWJUDqfzMinOAZ3dEXMr0+xieHYu7AVJTUWZx+ehaUd3g2HHTGiO5946eyW/80N3yGUKowJT3ynNUFpYgdQnBYyfs33k62OXD7eGdijIKIVHY3s0K/VEyuN8vWMc3K3QZqAPrGxFyE0rgaxcYXZdGCYFx9HDGh+s7WNQwW/SwQ3xd7MRF5EFABi7oD1ElhagKODYb3fReWQjk8ZsNb7NnWAhFmDYB61QKVew8jYNmBaE7uOa4NDPESjKLmd1HV00f1t6btRU0GvBqePTzAkRp5P03vcytO2mCdr0b4D4u9mwEAvQdXRjVJRXalfd10Tn+wya0Rzntz4CADi4G5ajqpM6YewWvvmN8YigmuyHLm991xXJD/PQqIMTkp9p/x4URUFgwdOS6+UVKiOKSGIBkcQCikoKikrT0buWtiJQFAWlgmK1I4GFSDv0XbeF+rPffvsNMTExaNmyJb799lsAgKurK62QiyQWkFUAFRVStGnVFh/PmouGzbxw8uRJvP3222jUqBG6dNG//3v37sX777+P7dv+xoDeQ2Blp23g4fP5mDRpEnbt2oVZs2bR7+/evRvdunVDQ19/uLt5oH+fgbByEKOsoAI3Qq/ho3kfoEcPlRNx1apV2Lp1K7Zs2YLmzZtj1apVOHLkCPr3V6UIsYlSUyqVGDZsGIqLi7Hh1z/h5+ePmNgnEPAF9Pcvl5Zh87b12LFjB/h8Pt566y0sWLAAu3btou+1hUhVmV4g5KMop5y+Pttn39R2hUzUuDJua2uLbt264bvvvkNQUBDc3d2xZ88ehIWFoWlTVT7jsGHD8MYbb8DPzw8JCQlYsmQJ+vfvj4iICIjFYmRkZEAkEsHRUdv66+7uTlswdFmxYgWWLVtWI9/BwcMKNo5iPUXPFJphvb0nBeDSP9Fo1a8Buo9tzPpH1DzOZOiKjmBl1hphwqshMiKAG8urad3Pp2qbFgZsnSToy1D9U52vbAorOxGjQCSxFla7oqkxz4opek0IMJoPLrayQEVZJRq2doZXUwfYu1rCs7EDEu/nQCgSGAxZBXQEdI2v3qKXFzq9xrJwmC4mxoxeqI4Zg0xkaQFZeSUdvsRGQTS097dnY3t0HM7tu/L5PAglVcYxkYHtTnQx6vEz8pFPkKqA3oVtKoGGx1OlWUxf2dPkPKCuiFtTyviwD7iFbgd0cUdMWCbjZ9WJZmgz0BcFmeXwb1vzERFqNIteCcUCjF1gfI9oC6EArfpqR9lwDeOe8EUn5KaWwLOxPf17q6ltda11fx9QlCpaYu93t1i10f1+jh5W6DulGfzbuDLm9bOByxZ1Tl42cPe3MztFRfP50Q2TFQj5JvNMhWIBRv+vPZIe5OLEukgAKm/uw6vPU+jquGiPGjZhquMXdoBSSUFgwUfTju6olCkZawD0NLC1jl9LZyQ9UBmM2GxfxOPx4OhhhfyMMq33jSnF9H7MEarXnhrFW9nMf5p0fM2fDu1mX4vjebiurmzEwojs2cQe6XGFCOzigdSYfKTHFaLF8x0ctPrN4iuwjRZR462TGvn2D92Qm1qKhmbsyAIAXk0dMW5hB3p7qSHvGS5QN/i9FjixNhK9JqrGTUBnD1oZb9yOuQ6QmgHvBOHi34/RZ3Iggnc/MauvQ2a2xNnND+jXXKIb3fxsTc7zXLB3tUKrvlaQSqV6n1XKlNj7XThDq9rn/d/6sFJG7e3tIRKJYGVlBQ8Pw1Einh5emP3+JwBUDoyPP/4YZ86cwYEDB/SU8Q0bNuCLL77Av//+i379+hk855QpU7B69WokJSXBz88PSqUSe/fuxRdffAEAsJRYwlJiCVtnCe6nP8IX33yG5cuXY9CgQQCANWvWYPHixRg3bhwAYNOmTTh79ix9fltnCcCD0VD6Cxcu4NatW3j8+DEcxKrv39BXJS/yeCoZQS6X448//0DjxqqaXB999BFtuABUxjiRxEJPv+BSw8A70BGvzWkNgXUlPtvGrk2tVGbYsWMHZsyYAW9vbwgEArRv3x6TJ0/GnTt3AAATJ06kj23ZsiU6duwIPz8/nDx5EmPHjjV4XoqiDE7mixcvxrx58+jXRUVF8PHxgbWdCIOncqmUqSpO9vb33bBxzhWtz0yFQWpOqB6N7TFzTW+zQ8QAoFFbFzRu76q3HYUaPeuYGdZ63TWj29jG8G7qCFtnCX0vXlR0h0Lznl6s7reFWIDKCmbrZVAPT4NV4dlgaP9wNW991w2FWeW0ENX4eXoDl7xAQFs46DLKeL6kpa0Q5cVyk+dhBYOQYW+iWub0lT2gVFCM3ndDuDSwxYQvOkFaIsex3+8BUIXNmypyxojOkNAVfGoDpi2ZquNRMVcR1q3KbIgp33ZFWmwBmnX1gIUFH+UlchRmlyMvrRSTlnRG+tNCva2OWPF8vAhFAtbpNzUB17BSGo5CtNjSQmu3iLpEJLHgbITTVBLGftYBzl7WEIoFnIrc6cJlXPP5PIxb2KFWU8bY4NfSGX0mB8LORQLf5s60Ml6t8HEDqI2RvgwV0QdMC0LUpWesisby+DwINIokcV0zXpvdGod/iYC0tJJWMk3BZttVXQwZo+vyN2/YygVRzw2afSYHslp7Rs9rD1l5JSTWQrw+tx2K86R0rqqWLl5LXyOohyce30gHoIreYh3BZQBDcqMufi2cMWtdX0bZyVSh2GbdPNG0kztk0kpOyrhPcydIbIRw87VFkw5uOLuZdVMtRJYWnJQkgmps5WeV4PeNq/HviSPIzEqnI4utrbUNIYcOHUJmZiauX7+Ozp31t5TTpF27dmjWrBn27NmDzz//HMHBwcjKysKECROgLK06Tiovw9vvTcLgwUPw2WefAVClJqenp6Nbt6oUQwsLC3Ts2JFesyyEAvAFPKOGuXv37qFBgwYICAiATFqJskIZZFKVE0Ydcm5lZUUr4gDg6emJrKwsFneOGw1buXCK0K4VZbxx48YIDg5GaWkpioqK4OnpiYkTJ8Lfn1lw8PT0hJ+fH2JjYwEAHh4ekMlkyM/P1/KOZ2VloXt35m1GxGIxxGL93Jgp33aDnR37QhPqCYkped+Usqs9YfOqpYir+zD0fSOeLZ11UmItRJuBPoi8kML6Grqyp8RKWO2Ku/UF2+1VZv7aG//+ehdpsQV6n7Xo5Q1LG9NeG3d/O9rLMPLjNnTYkalFX2IthMS/+mFVmkK1qcXo7e+7o6JMjuv7Y/H0brb2hyYEC2OCx+j/tUPyo1y07Gs8pNZCKADM+MquvrbITimmX3sFOHDaCoTHU41vZy8bOtRI9X71pSlTWwVpXqK6RbMAaBUEqg0c3KxowbPf26otgpQKJSrlSogkFpwL6qhh2imiNukzORB3ziShz5vGt/AyBJeQa2PwLXgmDXP1gsZYrO7WQ5p4BzoYDP3WpbrPn1dTB5QUVFSr7gigHWk0c01vyCsURj32Ho3skBFfhKaduBmlJi3pjJTHeQjsrO+patbV03D4cA3D4/MwbqHx4qO6NGztgsgLKawLFwEqpTI7uZi5jgILmnZyR1FOebXkkG5jGsO5gQ38WjozbqvHBF9j61mBBV+raJTmFM7G6eHTTPXdHTl4eXuMawKxpQUCGMZJbWNYVjX9XQUWfM4RJSKJBab/1KNe0j3MxULEx/u/qSrlG3MM1ta1awqJjRDbfvsDf27ZgJU/rULHzu1gbW2NuXPnQiaTaR3btm1b3LlzB9u2bUOnTp1MfucpU6Zg9+7d+Pzzz7F7924MGTIELi4uyCpVKaVKSok335wEB0d7bNu+lXPf+Xy+XtSJXF7laLK0rFq/RRIL8Pk85KWrlHG1zCYUagujPB5P65xM16isZHZm1SS1umeBtbU1rK2tkZ+fj7Nnz2LlypWMx+Xm5iIlJQWenqpFqUOHDhAKhTh//jwmTJgAAEhPT8eDBw8MnqO69JkciLvnktBrkul8X4No5nTUhARuAibBoef4pijNr6BztkxTT3F5NYCtkwRFOfrhRKbg83kYM789tn9+A6UF3FIR1Ax4Jwh3ziWjeQ9P04WWagONn83UBCkUCyAUC9D3rWYQWlrAydMaIYfiVG1NXcfIAd6BjrXvZdb4nlwLbU34sjMiLySj00h/HPvtnlauF9drA6pFLKCzO4pypOg0woRHsprrdJdR/gg7lkC/ro0tUEzBF/AhqmZkjLl7v5tLy97erPKtdXnzmy6QSSvN2o9ZzaAZzVFeLEfLPt6cKmzXJTUp1GnS760gnNvykC7wVZuMntcOFFWz+y+rcz6N8drsNoiPzOYcRWDrJOHsxX5R6DqqEZy9rDlFJAkE/GrtOz743eobHi1Eghq95xYWfFjZi1BZoWBlmJDYCDFzTW+DBWyZEFsJ0cNAikF9wXYLVXMiKDQdXt4BDkiNKdDaYu5Fg8fjcXIG1BcikcjkrlM3Q2/g9dGv492Z0wCocq1jY2MRFBSkdVzjxo2xatUq9O3bFwKBAOvWrTN63smTJ+Orr75CREQEDh48qFW0GwC+/nYx7t+/j/DwcK26Yvb29vD09ERoaCh69+4NQFV/LCIiAu3bt6ePc3V1RXp6Ov26qKgICQlVclLr1q3x7NkzxMTEICBAW5djuxxrXYNSFZaLjnkMb9/aNZrWijJ+9uxZUBSFwMBAxMXF4bPPPkNgYCCmT5+OkpISLF26FOPGjYOnpycSExPxxRdfwMXFBWPGjAGg+mHeffddzJ8/H87OznBycsKCBQvQqlUrDBw4sDa6zEqIM7Xfo9ZvXQc6bpfXG6G0sEJvWwd3fzvWynjfyc2w65vQqjc4yjdTlnVFxNkkdBrekFvDGmDAtOa4ujcGNg5irT0i2VKdidXSVqRXfbwu0Qw/FjBsq8TYxlqIAVODkJlYFTpjSmFw8bbRKkxV16YbTaMWVyu6SwMbDJimCo0e9kErXN4ZbXSbLF10Cx+N+KgN6+JDvGoa5joO90dxrhSPbqSbPvgFw8pOhCYd3ODR2B7OXtXzXtYVNbELQ314tLji7G2Dlr29Yc1xv3hT2Lta4g0TWz7WFKoqwXVyKS0kNsKXVqk2FwuRwKytSF81eHwepn6vispkm7pXH/tz1zSsDYrVFAyGftAKiVE5WlXg64pB79Zd+lRd0LBhQ4SFhSExMRE2NjZaO1WpadKkCQ4dOoSQkBA4Ojpi9erVyMjI0FPGASAgIACXL19G3759YWFhgTVr1hi8tr+/P7p37453330XlZWVeP311wGoIs42//EXtv6zGUeOHAGfz6frf9nY2MDGxgaffvopfvzxRzRt2hRBQUFYvXo1CgoKtM7fv39/bN++HSNHjoSjoyOWLFkCgaBKju/Tpw969+6NcePGYfXq1Wjo64/bNyPB4/EwceoYVvevf//+mDdvHk6ePIkGHr5YtWo1CosKWbWtDrUyWxQWFmLx4sV49uwZnJycMG7cOPzwww8QCoWorKzE/fv38c8//6CgoACenp7o168f9u3bB1vbKmX3119/hYWFBSZMmIDy8nIMGDAA27dv17rxtc2kJZ2RFlsAr6YOiA3PNL1FRR0LCBJrIYZ/qL/dR6t+DcAX8FkV1tHchswcHNytMGCq/gNcF9g6STjt/6nLkJktcObPB+j6emO6gIgdh3C8+kQkscDErzqDz+cxplQYRSvmzvihHYY3BI/Pw+1TiQAAKyPF6WoDSmPHgOp4Gp29bTB+ETdlQTfigcvlNXOW68tDaudSP2OZx+ehF4sdBQh1D4/HQ5/J5oXwEwj/Zf6Luclsly5zPOOaSKyF1d4r3FxE4pffaKLJggUL8M4776B58+YoLy/X8hyrWbJkCRISEjBkyBBYWVnh/fffx+jRo1FYyKx0BgYG4tKlS7SHfNWqVQavP2XKFMyZMwdTp06lw8Yl1kJERIVBoVBg1KhRWsd/8803WLp0KebPn4/09HRMmzYNfD4fM2bMwJgxY7T6tHjxYsTHx2PEiBGwt7fHd999p/f9Dh06hAULFuDNN99EaWkpGvo1wleLlrKWw2bMmIHIyEhMnToVFgILzJz+IXp07cWqbXWolVE4YcIEOrxcF0tLS60KeYaQSCRYu3Yt1q5dW9PdY42ztw2dK2luzmR9IBDw0bofd0/xfw2XBrZ461tVwQgXn66olCmMVkJ/0XBhsZ85E5SGNm5qfhKKBOgyqhGcvKyRcC+7zseVVl/rQRZy9bVFdrIqb51L3qTEWoiOz6NFanLrFQLBGKM+aVvfXSAQCK8KLJVxzb3Ke4xvgoatam/XjJqmug6pesGI7SMgIAA3b2pv1dmwYUOtCD0nJyccPXrU6CWuXLmi9TooKAiZmcw7rWgye/ZszJ49W+/97du3Y/v27Qbbqb3uxjzvdnZ22Ldvn9Z777zzjtZrJycnbN1alY9eXiyjoyqnTZuGadOmaR0/evRorXsjFAqxYcMGbNiwAdJSOV1viM22udXh1TIJ1TMvYo4gGxq2ckbi81Bkc7ecedlxMFER/JWF5Zjluh9wjcEhN742GPxeCxxbcw+t+zdgVdhPE1NV7k3h39YVj26kE2WeYJK3vuuKvPQy+DBU7CYQCARzYLvmiq2EeG1Oa/AFPPg2N287Ni6od4ipjtI/aUlnlBXLXk5lnMCa6jjYxFYWdM2l2oYo4zXJy6mLY+D05ji7+QHsXK3g17L2J1JCPaOp4NZfL7hTD511cLPC1OXMOzjUNn4tnTFuYQezhYX6MjC9pDbJlxp7VyvYuxKhkkAg1BxcnDN16Q2ftKQLMp4WoqGZW34CzyNfa7BPhFcPHo9XZwWaiTJOgNhKiFGftqvvbhDqgRd9axGqnj3j9QmPx2O9V6wm4xZ2wP0rz9B9bN0WGBRbWaCirBJeAQ51el0CgUAg1BxD32+J/IxSeDV1qO+uMGJlJ6qXYm8vDi/vLkgEZogyXoNoqgp1sLMZgWAWVDWLrdQpFPv8doIKj0b2Zinx1WXCF50QezsTLfuQehUEAoHwsvIibzFGIKr4qwhRxmsN8rgQXkxeJkORVuF3oo2/0Ni5WKLD0Ib13Q0CgUAgEKqNOduSEv5b1NQY+e/t1VCLaIb8Wgjrbgs2AoEbL9EC8xJ1lUAgEAgEwsuNUKgqmlpWVlbPPSG86KjHiHrMmAvxjNcgAgs+ek1sikqZEtYO4vruDoHAyMs1Nok2TiAQCAQCoW4QCARwcHBAVlYWAMDKyuqFisyrVMohr5QBAKRSaT335r8JRVEoKytDVlYWHBwcIBBUzwFLlPEapnU/n/ruAoFgFHtXKwyZ2RKWNmTLLAKBQCAQCARNPDw8AIBWyF8kKIpCRVklLEQCFCVk13d3/tM4ODjQY6U6EGWcQPgP0qTDy1GghaRsEQgEAoFAqEt4PB48PT3h5uYGuVxe390hvIAIhcJqe8TVEGWcQCC8sBBlnEAgEAgEQn0gEAhqTOEiEAxBCrgRCIQXFidP6/ruAoFQp7xAqYkEAoFAIBBqGeIZJxAILyxWdiJMWdYVQjGxTBNebV6b0xrBe55g0PTm9d0VAoFAIBAIdQRRxgkEwguNg7tVfXeBQKh1GrZyQcNWLvXdDQKBQCAQCHXIK6uMqzdiLyoqqueeEAgEAoFAIBAIBALhv4Ba/6RYFD96ZZXx3NxcAICPD9lqjEAgEAgEAoFAIBAIdUdubi7s7e2NHvPKKuNOTk4AgOTkZJM34VWiU6dOCA8Pr+9uvBQUFRXBx8cHKSkpsLOzq+/uvDSQMcYeMsa4Q8YXe8j4Mg8yxthDxhh3yPhiDxlf5kHGGHvqa4wVFhbC19eX1keN8coq43y+qlC8vb39f+oBFwgE/6nvWxPY2dmRe8YBMsa4Q8YYe8j44g4ZX9wgY4w7ZIyxh4wv7pDxxQ0yxrhTX2NMrY8aPaYO+kGoQ+bMmVPfXSC84pAxRqhNyPgi1DZkjBFqEzK+CLUNGWOvFjyKTWb5S0hRURHs7e1RWFhIrEcERsgYIdQ2ZIwRahMyvgi1DRljhNqEjC9CbVNfY4zLdV9Zz7hYLMY333wDsVhc310hvKCQMUKobcgYI9QmZHwRahsyxgi1CRlfhNqmvsYYl+u+sp5xAoFAIBAIBAKBQCAQXlReWc84gUAgEAgEAoFAIBAILypEGScQCAQCgUAgEAgEAqGOIco4gUAgEAgEAoFAIBAIdQxRxgkEAoFAIBAIBAKBQKhjiDJOIBAIBAKBQCAQCARCHWNR0ye8evUqfv75Z0RERCA9PR1HjhzB6NGj6c8pisKyZcvw559/Ij8/H126dMH69evRokUL+piKigosWLAAe/bsQXl5OQYMGIANGzagQYMGrPuhVCqRlpYGW1tb8Hi8mvyKBAKBQCAQCAQCgUAg6EFRFIqLi+Hl5QU+37jvu8aV8dLSUrRp0wbTp0/HuHHj9D5fuXIlVq9eje3btyMgIADff/89Bg0ahCdPnsDW1hYAMHfuXBw/fhx79+6Fs7Mz5s+fjxEjRiAiIgICgYBVP9LS0uDj41Oj341AIBAIBAKBQCAQCARTpKSkmHQm1+o+4zweT8szTlEUvLy8MHfuXCxatAiAygvu7u6On376CR988AEKCwvh6uqKHTt2YOLEiQCqFOtTp05hyJAhrK5dWFgIBwcHpKSkwM7OjnWfFZWV4AsE9eZNV1RWAgAEFio7iVxWAaGI20b1ispKuv2rilKhAI/Pr/bvpFQqAAB8PjsjD4EdNTUGlUoFeOBBqVQCAHh81e/N5wtMXkNeIYWFSAy5tBxCsQRKpRLKykoIRELye9cCur8HRVGglErwWRhQX6Q5y5y+1Pe68TKheX/NvW8v0nghEAgEAkGXoqIi+Pj4oKCgAPb29kaPrdPVLCEhARkZGRg8eDD9nlgsRp8+fRASEoIPPvgAERERkMvlWsd4eXmhZcuWCAkJMaiMV1RUoKKign5dXFwMALCzs2OljCuVCsTcvI6zG3+Dd1AL9HtnJpy8fTgLCRVlZZCWFMPezZ3V8YpKOQoyMqBUVCLnWTJO/f4zAODDzbuwf9li5D5LRtshIzBgxixW53tw+TzObvoNr3+2BE06duHU95omPyMNNo5OEIolNXpeeYUUf338Hlx8/PDGkh+4tZVVoCQ3B6X5+bBzc8PJ1Ssgr6jA1J/XEgWthogOuYqTv63E8I8XIKhnX7PPo1Qo8Ovk1/Xed3D3RMO27RF14Qymrd4IRw8v+rOinCwAwMEfvkZ+2jOD55635xh4JsKG6oOCzAzIpeWwd3OHyNLK6LFKpQJ5qc/g3MDX6DxFURTyUlPg6OltUjFme05dcpIT8c+iT9DhtdFo0WcArB2dsH/pYpQU5GPmui0QSSwNtk2KuoeDP3wFjyYBGPrh/+DcgH1Ek/q7AYCdq5tZc01eWipsXVwgFIlV8+cfv2P0Z1+hcQd286e6/4HdemHE3EVanykVCuSl6d/PouwsiK2tIbay5tzf+qa8pBhyqRR2Lq6c28aG38SxX35Ap1Hj0HXsRGxb+BE8mgTg9QVfmWybm5oCB3cP5KWlYufncxHUsw/6vP0uLG3ZG9vNgeuarklNrIG5qSkQWAghtraGpY2t2eepS8qKChETegPNuveGxMYGALe55WV+Pgh1A0VRSI99AoVcBmcfP1jZGVd2aoKyokIoKuWwdXLRer8wKxMSG1uIrYyv2YS6Ry6VorQgHw4enpzaFWSko7SwABSlhK2TM+xc3ZGbkgSnBj6cdQU2slSdKuMZGRkAAHd37UXN3d0dSUlJ9DEikQiOjo56x6jbM7FixQosW7bM7L4d+O5LPHv0AACQFHUX2+fPRusBQ9GsR2/4tGhtsv2zRw+wb9nn9Ot3f9vM6sc/vGIpkh9E6r3/6Ool5D5LBgDcO3uCtTJ+dtNvAIB/f/4O8/edAKASCGNCr8M7qIXeJJKTkoSi7Cw0at+J1fnZkhEXg11fzgMAvP3T73Br2KjGzv3s0QOUFRYgubCAc9udn8+lhXdNirKz4eDuUQO9M42ishIhB3bB0dMb/m07IPlBJAK69oDAQmiy7bNHDyCrKEdBehosxBI079UPFiIRp+unRj8CAHg3a86573lpqchNTUbTTt0MHnPyt5UAgFNrf6mWMq4ey7oUZKbj3tmTAIBbRw9iyKxPAABRF8/g/J/rWJ1bWlaqJdjKpVLEhd+Ef7tOtPBYHZKi7kFiYwO+hQVKcnPg17qdwWdQTeT507jw13oAgMTGFnO27DF6jUvb/kTkuZPoNn4yur8xWe/zkvw8RF04g9Toh0h+EImmXbpj1LwvDJ6voqwU66aropEMndMQV3dvB6VU4vbxw7h9/LDWZ0lRd9G0c3e9NoVZGYgJvYGru7YBUM0Z2+d/iNc++QxW9g5wcPdEetwTBHTpYdBw8uDKeZzb9DsAwLmBL6at2sC6zwCQ/CAKB777gm6rHnNHV1bNn4ZQKhQ4tW4VnoRcBQA8uXkNXcdN0ppP1Z/3m/YBWvUbhLjwm3D188ffn30EACav8SKy4d03AQAzfvtTyxBmiuQHUTj2i8p4Gn7sEKJvXEVJfh7iwkNNto29FYJjq5bDQiSGb8vWUCoq8TD4Ih4GXzR4D3OfpaAgMw0ejQOQ/CASFEUhLvwmGnfogqBefVkLVJtmvY3KigrO3zctJhp7liwAj8/Ha58shJt/I2QnJaBp5+6sDV3q763mrRVr4N6oidE2FEUh7tZNuPg1pPtblJOFtJhoBHbtWSdGyI0zpwAALm7ZgKkr18LVzx+7vpiHrISn6Dz6DfR68x29NnlpqYgNuwGxtQ0ublE9x8M/+Qxufo04Geiu7fkbt44ewKRlK81a48wl/m44bJ1d4erbsM6uCajkiVO//wz/9p0gtrRCk87dzIrQKc7LQerjhwjo2pNVNFOlXI6Tv/2EjiPGwrtZczyNCMOzxw/RadS4WleMSwvysemDt7Xe+9/ufxETeh0NglrCxsnZaPt7Z0+itDAf3d+Ywuleqcd1/xmzQCkUaNq1B4qysrD3m4Xg8fmYt+eY0fZlRYV4cvMaBAIL5KWnws7FDe2HjWR17ZjQ60h+eB/9p73P6vdRIysvw9PbYWjUoQuUikok3otAk87dWBsI4++Gg88XoLykGIEsx4aa6uoXTyNuoSQvB65+jeAV0IxT20q5HLFhN3Bq7S8AgCk/rIZHkwBWbXOfJWP7/Nla7wmEQijkcrQZ/BoGvvshp76woV7ivHQHP0VRJh8IU8csXrwY8+bNo1+rwwPYolbENYm6eAZRF8/gw827jE4uWYnxWoo4ACQ/jGKljDMp4oDq+7KFoiiEHt4Lj0ZNGT+/e+YErvyzGUKJJT75+wD9fsqj+9i/bDEAYOI3P6JB85asrwkAZzb8iofBFxmF4JiwG/T/dyz6RE9gkssqEHpoL5p07ArPpoGcrlsdmBRxgJ3lSs29sycR/lzhGLt4KZy92Y+zirIyrJs+Qb9faanoMWGK0bbSkhK9cZaX9gx9335X6z2KohB+7BCcG/joeffksgrs/WYhAOCTvw9CKGGekB/fCEZ5UZHeQrHtfx8AAMZ98S0atmlvtL8AcHr9aiRG3sH7G7Yj9NAe+LZqC5/mrUy2y4yPw6Orl0we9+DyOTTv3Q9eAc1YK+JMXNy6CQ+DL8C9UVNkxscCAN768Tc8CbmKjiPG4O7ZE/Bt0dqoYU4uq0DowT1wbdiINkioad67P/19Oo0ah6CefeHq509/XlFWRiviACAtKdZqnxkfh5jQ6+gydiLtZY48pzJI3Dy4G93fmIyclCScWvsLfFq0Rt+p72Hn4rkozc+jzxEbFmL0HqgVcc1zsoV6nkbACI+HvLRnuH/pnJag9tfH7zEefvJ5dJCaPm/NQMeRYxmPjThxlP5/7rNk3Dt7Em2HvMa63xEnj9BtlQqF1mflxUUGva6Gojb+XjAHADBl+a/waNyUVtRvHd2Py9v/YDzXk5vXcGLNT3jnl/Vw8fFj1e9Ta3/B4+tXAAD93pmJ9sP1+8JEUU42Ns+ZTr+uToTI1k/fZ21MKC3Ix4HvtA1BxbnZ9P+lJSW0ESwz4Slibl5DlzET6OgQ9fNUKavQ669SqcDNg3vh07wVfFtWPZ/b5zMLTLFhIaiUVaDNoOFIfhCFlEf30W38JOQkJyE65Cp8mrdCavRDdB33JiyEQlQ+j7jb+un78AxohuEfLWBluH1y8xoA1bNxYs2P9Puj5n/BaJxi4v7Fs1qvdy6ea/Kex9+5hWOrVQr8sDnzIK+Q4sJfqvU5Py0V3ca/yeraah4GX4RCLkfrgUNZHX/v3Cmt1/8s/BitBwxFVsJTAMCtowcYlXH12qKJOlKQ7TjLfZaCW0dVMs7ebxZyNnaFHdmP63v/QZtBw9C8d394BQSxapeVGI8jPy7j1Fc1lFKJm4f2wiugGSTWNoi9FYKuYycZXJt12ffNIqTHPaFlrkEzP2L9W2ny94I5qCgtRUl+HjqOGGPy+HXTJ0AhlyMuPBSB3XvTc93dM8cxd+cRk+2f3LyOkrwcZCcnIun+Pcz4dRNrBVFXEQeA2yeO4Nru7ZBY22DO1r0G2949ewKXtm4CALj5NzbqWNBEUyZXt7+xfxdk5WWqz5+vgVmJ8Yi+EYwuYyboRXYcWv41/Ryoadyhs9Gom8jzp8EXCHDuD5XROfLcSYxe+DWePX6Azq+PNxkZdHr9asSFh6Jh2w5IvBcBAGgzaBgGvjfH5HfOTkqgxzUAZD6NQdvBIxB54TQ6vDYaNo5ORtur10M2RkRd0mKicXTlt/TrT3Yc4pSye/PgbnouAIB93y7Gp/8cYtU2/u5tvfcUcjkA1f3vOmYCIk79izaDhjOuBcE7tyLi5FFMX7+NdX/rVBn38FB1OiMjA56eVYpqVlYW7S338PCATCZDfn6+lnc8KysL3bsbXsDEYjHEYuYfSq3Is1H6mTix5idYiERo0WcAArv10jonoFI2Ga4KRaUcmz96F6X5eZi2agP4AgEubt2ELmMmwKd5K+MKNwdlPOHubYTs32Xw86SoOwAAubScfu/xjWB6oQOAfcs+57SI7Pl6IdKeqDysuc+SEX0jGA+uXIBH46bIjI+DxEQ43a2jB+i/6niHCjIzsOUTlVD/8d8HjIbDGoOtQFqUk42LWzfSr7fP+xBvrViD8pJi3D5+GINmfgSxlTVOrfsFzXv1Q7MefbTaX9u9nfG8cbdCaOVHPa4oikLY4X0oyEyHxMYWeQxh109uBOsp488e3aevo2cEkUrp/8uk5bAQixmfCfXYyE5KgKJSjmGz/6d1jzLiYmhlPC48FP/+8j0AlSCgiVoBXTNlNAAg9PA+9Jw0Fdf3/oNmPfpg+EfzGe/9zsVz9d4zxP5li/Hx9v2sjweg9Xxd+GsDHgZfAABaEQeAnZ9/CkDlxQOA0EN70bBNe7QbOhKN2ndCYVYm/vr4Xdg6u2Lm+q24dWQ/bv17kPFymoaF8GOHEH7skNZvI5OW6bUpyEiHvbsH0mKisffrzwCorL393pnJOHeoF77spATcv3gW8gqp3jH6t8H4nKj5eUFGOi5s2YDOr4+Hb8s2WsepFyomeOBhx8JPUCmXIS81BWMWfWOyX5oE79yqp4xTFAW5tJyOHlJzcetGiKys8OjqJfSf/gGcvBqgIDMDF/5aD7GVNZQKBUbMXYgb+3ZCXiFF/J1wum3khdNa58pLS0XYkdVo0WcgArv11PosSkdJ0iU7KQEejauMo6UF+YzHrZo4gv7/3wvmYP6+E7iyYwsiThyBZ9NAiCyt0OetGbThRp2Hr1bEAeDy35th7+6Jxh06A1B5BitKS7SEraKcbJz/cy0SI+9oXX/1m6Mwd9cRVlE5TKTHPsGN/TvhFRCEjLgnGDpnHqPh2tD3V3Np+x8Y/tF8UBRFP3cyaTkGzFAp1OpaKgDw9HaYVttDPyxB8oMohB7aw3otSYy8izaDhtMGgsfXLqEwKxMAEP78GRaKJXrzd3pMNLZ88h5e/2wJ7p09gaSouxg2Zx6CevVjLVscW7Uc8/YeZzy+vLgIp9dXjbmE58KzJps+eBtDPpwL/7YdGM//4PIF+v+n16/W+izkwC7WyjhFUVAqKnFmw68AgMYdu8DK3gGAYeN1SV4u7dXWJOriGa3Xh5Z/jRFzF0FsZQ2KovAw+KLRvhz8YQk6jhhDrzma85Lm/3UNMJVyOQQWFqx/m+t7/wGgUoAiz59mPZ5ykhPp/x/9+XuM+HQh64i1mLAQ3Dy4W+s9pVKJ3lOms+p3etwTrdfnN69DqwFDWDu41P9WlJYCABLuRbBSxjXnfLUirvu+MTQNVACw64t5nCObNFHLPNLSEr3PLm7dCKFYgt5TptOKNAA8vHKRvTLOYHBWK+KaqPWBirJSWh6iKApnN67RU8QBlfdYUxnXHM+lBflaRno1aiW1ICNNL8VH83cFQEceJWrMJZHnT6P/jFng8QzXXSrMysQ/Cz/Wei/i5L+IvnEVpQX5yIiLwcSlPzK21SUrKR7ujZpw0sGyk+K1Xt85dQydXx/PPqpIx/lQqZHGbIwb+3ci9JBhYw4AHPt1BdJjohF9IxgfbPxb73N1dOCG99g7NOpUGff394eHhwfOnz+Pdu3aAQBkMhmCg4Px008/AQA6dOgAoVCI8+fPY8IElQcxPT0dDx48wMqVKw2e2xAhB3Yj+U4YBs38CGc2/Ipek6fBrWEjuPr5QyGXQy6rMJmHlfIwCoBK6Q3s1gvpcU9wdOV36D1lOpr36sfY5vyf67Q8dUd+WgaRxFJlBYy6i27jJ+tNwJqoQzdNoakUG0J3QacoSksRV6NUKEBRFCrKSo1GAlSUleldU+3NSoq6y6rfOclJrI5jRONhVCviALD2nTfQou9ADP1wrl6T0oL8GgmdSo99ovfenq8/oxegvz6uUowT7t6mhbmKsjLkPktG5PlTeu0B1YS8epLKCz3286Vw8vbB3m8WoiQv12h/pGWlKC8uglKhgLWDynil2aa0IJ9+H1AJe2o2ffA2+AIBJnzzI7wDmT0ADy6fAwD4t2mPII2xfmP/Tsik5Wg//HVaEQdUgoAp1AJP9I1gtOw3CH6t2ppsY4rQI9yUcfVCVZCZYfA3YSIx8g4SI+9g3t7jOLtxDQCVhy8rMR5ZifHGGzNQVlSosp4z2N62fDpT772c5AQE79yKmNDrWu/repPZKOLxd8NxduNvGDr7f4yC/fk/1yE6JBij5n8JRw8vnFr7C9LjniAp6i7Gf/k9nBv4wNrBETw+H5WVhgUwzfGR9vz5Ofrzdyb7p0l5cRGEEktYCIXITk7Ezs8/Neg5Or1uFQBg2/9m4Y0ly3F9z99aAuuaKcyCZn5aqtbrkAO7kHz/HhLu3oZQ8g0atasKtcs28VtTlJFIASM8DL6IiBMqr5J6rjnw3ZeYtmoDnoReR9jhfRjCML8dXfktBn/wCVr2G0R7A9oPHw0nL28AYFTE1ayZMgbjvvwOLj5+qt9TY34tLcgHpVTSYZ+60QO7v5oPoGrev7b7bzptRBNTxs702GhQFIWD339Jv5edlGC0jZrkB1GsjtOkICNN67VaEdckL+2Z1nyuyb8a4/f0+tW4sX8n3lqxBpa2dqCUSpQW5OPOqX8NXj8nOVErMkbN9b3/IOHubSTcvY2mXZjblxbk4/CKb7QURUWlHLLycogsLREXftPgdQHgwZULaNq5G/h8AeMzVFqQj4qyUmz7n3ZqXFFOFu2RnPzDKng2CaSPt7Kzh7xCij8+1Pd4M5EYeQc3D+5G8oMoVr9zUtRdJEXdxfx9J3D/8jlc3LIRbyxZDpFEgoM/LEGPCW8xeoN/e0v1rHcb/ya6v2E88qxSJmPVdybCNDxwT2+H4u6Z4+g0Sn83IU3Uc3967GO9z24fP4wHl89j+uqNtAGEC6snjUTvKdMN9qGsqBA7F8+FX6t29BqvJjX6IWOb8pJiCEViVkYGU0qXunCuJrnPkrXklfLiIogsLSGwEIKiKJQW5Jv0xDKRGR9Hp7XpGtee3g5FSX6e3ryny+PrV7SUeEOoo2EAbVk49ckjgwan6BvBtCH18Y1gXPl7M0bN/xLegUGQaTjQmHgWrS2HX9iyEUlRd/D2T7/j5G8rteQ9XTa+/zaEYjHeWrGGUTY+9+daxnZqw2paTLTRvmmda9Pv8GgcgIPff4VW/Yeg5yT9yAY1FEWhND9Pzx95fc/fuL7nbzTv1Q/DPppv9HoVZWXIT081eoxSoYC0tETvu5tSxAGVURZQydpsxg8balwZLykpQVxcHP06ISEB9+7dg5OTE3x9fTF37lwsX74cTZs2RdOmTbF8+XJYWVlh8mSVBcHe3h7vvvsu5s+fD2dnZzg5OWHBggVo1aoVBg4cyLk/ESePQCIU4vAKlTdGLUADgKWtHcqLi/DhZsNeZSZO/f4LygoLcGbDr7h/6ZzpBtBf7I0p4mwpLcg3qohnxMWgokzbcpf65LFB7+yvk18HXyCAUqHA1J/XGcx9MhqSyhrDnn+KopD8IBIuPn7ITk6Eu39jrVAcY0P+4ZULaNajDxq2bke/l3gvAodWfGM0rDri5FE07dIdDZq10HpfWlqCjLgY+LZqg5K8XD1rLmDcEiyTliP6ejArJVXN4R+XolmPPiYVcUBl7VNb3177dCGsHRxRouGF2vTB25i47Cf6e22fp+05UCoUOPrzd5jy/SrkPEuGSCKhK5drcmrdKr3QnfBjh0wKfqYwtdiwJdyAR9oUSkWl6YMYOL1uldZ9LsrJ4pRLBahCKtWenKk/sx8fujnZgGpB54JSqaDDzw6v+AZjF+vX21B7sw5+r19c6+APqvfaDBqOge/NZj8nPF9hdb2bptjw3mTYOLvggw3b8c/zfGu1J8cYB777wmT+oJq7Z45rvdZMFTjy4zIt5Sf+bjiMwaZvTKi9kJqUFxdh4/tv0a/Va5ku5/74XcsbXymr8gSUaKQrMHHohyUAgO5vTKE9p/F3wnHkJ9W46DV5Gjq/Pp7RGKlJSb5qzlIqFEiMugPPJoGwtLWDstL4c0YplZCWFJulWGuSHvuEVdpTTkoSclKqYRDWoSg7Cxe3bESn18fj9vHDJp/HwuwslBcXw6dFKy0hrryoSnjev8xwfQdA9cyrlYutcz9AUXYWo6FGl7Mb19BykNpDn5uagkqZDHJpOfYt/ZyxXeT5qsiRIz8uw+y/dtO1cvzbdWRd8FBNelwsa4OLJuoaEXu//gzujZqirLAA5zevM8g1w9kAAQAASURBVBppePPgHvi1bm/Q6AwwKx9J9+/Bys6e0XCiiW7629Vd2wAeDwILC7QbOlJPUM9JTqTrRhhCWlKMfcsWo+/U9+DTojUshKrolYqyUqTHRMO3VVuja87VXdsMKuN3Tx9DcU62niIO6MszpQX5ePb4AU6s+QmWdvaYzUJePvj9l3hjiSpVorykGJlPY+HXqi1tlNs2l7kG0qYP3sbohV/D3b8x/vjwHdi5umHmuq24uHUTIs+dxLCP5ht0gDGhNjqoiTynb3j/Y9ZUk2Hb6rxjU5xY8xP9/8KsTMSFh6JJp65aEYm6RN8IxmufqCLf1E6yvV9/ho+27TcZIasrC6tT1x5fu6wV9cWEtLgI0mIg4sQR9Jo8DUCVEeVZ9ENkxccZbc+30B57lTIZUh5GoUGLVpAWF6MwS7vGl3rdDjuyD/lpz6BUKtF6wBB4Nm2mVafn6q5tuH38MNwNpN0+unbZpDL+8Mp5xvcLszJg76aK0N791Xxkxsdh2qoNcG7ga/R8xvhj1lS07DeYNkKbu0FZjSvjt2/fRr9+VQ+LOo/7nXfewfbt27Fw4UKUl5dj9uzZyM/PR5cuXXDu3Dl6j3EA+PXXX2FhYYEJEyagvLwcAwYMwPbt21nvMc4WtdXImAVbl7CjB1BSUCXYGLIi1ia5z5IRfyfcZK6IuoCaJupwV0OoPR//fPaRXohW1MWzcHD3gJt/Y449riLy/GmEHzsIR09v+r07p/6FZ9NmkFdUoCAzDUKJpZbnXj0hs+XQD0swf98JZMbHIeXR/aowHQOeIXUf7pz6F51Hv4F2Q0fSFth9Sz9HTnIiek+ZzjpaQZNjq5azjhbQpNSE8MyEbp6ymntnT+oZGbRQKhm9sLowCZj56WkMR7Ln1tEDcPb2gZNX1R6MXBVLc7h9/DCCzCh+p+bx9Staz9+xX35AQJcenM6hGVJp6rmsSSilUs/rZUjBM0Xk+VPwDgxCRlwMu2tTSpMKnSFKcnPMasc2PE0XQ4Lus+iHJg1lV3dtg7exZ66W0AwrVBtIKIrSCqM1hmYYc5hGtMm13dtRlJ0JVz/jhTgT70WgIDMDB777EkXZmWjUvhOGzZlvMu2kMCsTPJ629zw12njEFxO7v5rPutDari/010dNcp8x1xcxxJOb17Q8Y8ZQe9bHLl5mMNzclGxxbc8/8G/XCZHnT6EoW7WLBNe1Jvl+JPxat9Uz0jLx8EpV+Ltadop4Ljsl3L3NWRk3FdHHhG4akKaHlSmcV5PgnVsw+TuVUpV0/x4KszLRekDV7jyPr13Wa6M2RBqrr2KIqztVMou1gxOd5qJZpJMNeakpOLziG7QbNhJ9334Pd04fQ/COLQCAnm++A6GB1MzqEhsWguLcbDTr2VcrP7u8qBC3jx9GExM1D5IfRKG0IB8PrlzAraP7IStX7RDyzqoNEIrEKMhMN9g29NAeNH2+lhZlZyEvLZVWMk+vW4XinGyDbXVJe6IddZD04B7jcZHnT+sp47LyMtw7dwpNu7Cr78BE2JF9aNKpq1mRUuumT0DPSVONHmNI7aOU7BXCR9evwMreUVUfiMdDeuwT7Ptmkcl2uuuqOt3PxbehyfVGXd8gLvwmHD29MGPNn/RnameDZsogV5gcSoCqTo1ar8l8bmyIvhGMruPexN3Tx1CQabhIuDEeXD5HK+OaKRtcqHFlvG/fvkYtAzweD0uXLsXSpUsNHiORSLB27VqsXcscJlHThHEIcb2+Rz8/oC44seYndBk7Ea6+Dekqf46e7Cu7moM6n7HruDfx+PplFD4fqC36co9QePb4AaIunKFzHTUjBS7/vVnrWDtX7WIWakGDhmU4CJe8YzW3jh5A/J1w+LZoDQdPL3pSMUcRB7gLR2pSHt03qx0TT0KuwkIk0svnVsOUY1VXZMTFYNv/ZtETJKVU6oVc1wbqvO1B739s+mAD6IaA5WeYb5iQlbOLEKiu5xBQbT1XkGFYGOLKqedh4WxRhzabg2aONVvMHd+GDAxMxT6Z2LNkgVnXrSnU6zCbsDtdCrMykRajLchqekaNsWPRx/R4jr8TjuO/LjfRQsX6dyfpvZce9wR3z3CrKZKTnMhKGdeMHGCiOsIgW5IfRGop47G3jBdZ1KQoO1OvGKhu4UdTHPzhqxqr6M/jVy9Mkw26UX2m0kU00UyNUyvZbn7+8GgSgNDD+4y2PbLyW4xeuARPw0OR/PA+Bs2cQxvrTEUFxYReR2C3ngbzf9kQee40XHwa0oo4UD1Z1FTaiLoAoK5sBqhqeATvNO0cOfLTt1rPUGFWJkIP7jFZvFBRWan1O+sW9lOnubFCR1Ys5KBsHfj+K2TExRiMJOVyfXOjSU19V6mBMHTKSOSpLiW5Objyz2ZY2toiqFc/sx2M6ro7bA2/avLT0xB6eB/y0p4hSCeNwBDlJcWM6cXqrZ2NcfL3n9Gy3yD6dejhfchJSa52lKdSqQCfLzBbfq2XauoE7qit7poLZ3W9kmwJPaS9xZKmhZwthkLfmCjK1s/fk5aUYP93X6BZ995w9PJmaKVNJkOhDLbkJCdynlBedB5euaAVjfCi8fdnHyH3WXINpUCw57yBvChzYJNW8CJQk+G5XDE3fPtFQFZeBh6PD4WR/PgXiufKeMgBbmlYJ3//uVrRKbqGpeoYkHZ/yd1wE7xzK8L/ZVc1t765ffwwXajLXK+MJsaivwxhjoFLjaZnmk1ObX3CtLYU5WTBo0kAbuzbYbRtysMo3Dp6EGFHVEq7d2AQWvYbZHB3FE1iQq9j15fzDBrD2aBUVDIWcGVLpUwGvkAAhVyOfcsW14mhiekaaTHRBoucqqkJGWD7/NnoMnYi6+rsgMrQkxh5FwFdeyCwWy/W0V7G4IEHeYXUoKdWzd8L5qD1oGFmXePIym/Rsu9AXN9bNYa5eMbV5Dwvhmqqr5rsWfIZXHz80Pcd5p1R2KJ+/piiU5ioKC2FhVAIC5EYlRUVEEokqJTJTCrigMoTrru+VVcRB4Bf33wd763dYvpAAxBl/CXDVO7fq0rIgV3IToxnbQk/o1NFllB/UR1seBWMH8aKpbwo5KQkcfaeEVSs/T975x0eRdX24d9ueg8hnRAIvfdepCMKKE0UUMHyWXgVy6so+qoRFQQbKqKA9A6CgCIgICBFuvSeACG9Z9O2z/fHsstsnbYl5bmvi4vs7pw5Z2fPnDlPn+J4011TcEeYiCspyckWZAHzNCW5OQiPiYWWR9LFqkT2zetIPX3C9FrHkRfA09hyFWYY/jGeRkEcMMQin9vzh6lkHBfZN6+L9q67fw5x4T1atRo/PDcBgWFhSGjR2i2CuD34uGs7Q1lckJ6GP777AsOmvsG7jVFJkHs7xW7JYaFk3byG754ex3lc/t07opVZqadPmN2HBoQL48pSBS7u3yPIEyDz+hVkXr9iVS3B1ZTm55olb243aJjbx2ALewk/+UDCeDWDnSCiNmGZXIkLT1r/CKKqYix/RhBEFeGeMFhaTTxrjNjKSVOlsSl0M4LKyBq5dvQQcm8L874TG7JmREwOBcCg6NaqVVDk5eKyZcifm3G3ksxWQkw+OEsY9xgi5vSFv/7knZDa07BLewLWpROrIySMVzM8kTCOIAiCqF6c3L7ZlCiHqLoUZWWgtDBfdBJFgh86rRYnt2+GX9D9zM0MwyCFI+u0LYQK4oSB2urZ6W48mQfILUgsI1YVIWGcIAiCIGoYJIhXD7Z8nuzpIdQarFzFGcasZjxB1AT++WUd90HVmAv7dnt6CE7HcUpFgiAIgiAIgqhhiKsIXH3I4agVTRBE1YCEcYIgCIIgCKJWkXahmscGc7B6xus10qWXIGoaJIwTBEEQBEEQtYqL+6tHwiqCIGo2JIwTBEEQBEEQRA3j7O4dnh4CQRAckDBOEARBEARBEDWMSwf3enoIBEFwQMI4QRAEQRAEQRAEQbgZEsYJgqg2ePv4enoIBEHUQl5etNrTQyAIgiBqICSME7Wa9kOHe3oIhAD6TJgsqt1/N/zu5JHwp3GXHh7rmyAI5xAQEurpIRAEUUV4YNIzbu+zzYAhbu+TcA8kjBNmdHt0nKeH4FYGP/ey6Lb1W7V14kiImkqXkaM9PQSCsOKRN9/z9BDcjpTvLJPLEdWwkRNHQxCEVJ78/FuP9Nv1kbFu7W/4tLcBUJm6mgoJ4zUImUwueWGSe/s4aTRVH7/AIADA89//LKq9ty+5TLsbhtF7egiCkclomSUc03bQg27vs058Pbf3CQBDX5omuu2o6R8iqE6E6PbRSdKE6aQOnSW1JwhHjP9wlqeHUO0IjYzy9BDcQkNae9xK/VZt3erVSLtEJ/PCguUe67t+6zaISWos6RydHn5EcJvYxk0RHhMnqV9PoKooBwCERccKbhtZvwHqxCc4e0gEB/5BwZ4egmDimjbzSL9hMcLnNeEZgsLruL1PTymJ2vQX72opk8vw0k8rJbSX9p0DQ8MltScIR9Rv3Q5vrNvm9ntz6pJ16PDgCEnnkKKo+r8flqFln/6i2tYWZbdh78N4ehjoMfYJTw/BLfj4+yOhRStJ5xj0LH/P29oxi91ISN1ITw+BNyPfnGH1XkBwCNoPeVjQeYIj6uK57xY7a1geQWgsMsMw6Dl2gotGQ9ijaffego5v0rUHxs74GAAQldjQBSPiRi738ki/z38nzuMDAMa8m4zGXbo7cTSEI9zt8gjAYx6PMpn4jvU6aZ4xMpkcoVHRotu3H/KQ6LYjXn8XSR27iG5fnXCGIjCqQZLotm+s24ZWDwyUPAZPIJd7uX3sAcEhkMmlLQhSFF2hkVEozskS1dY/uPop6MXCMJ4XxiNqkREqLFaakVHIfUzCuBMRKsTaw5aQ7ArqNZem9XEmjTp3c3ufkSzhrH6rNoLb+wcHU4ZdFxNi4YIm9xK2ZD361v9M7l2j303m3c7b18/0tyeTv3mKpI5dMOrtD8i6LpBGnboKbuPl4wNf/wAXjMYxUoTidoOGOXEk/GF0OkntZXI5Jsz8QnC7xz74DIC00KTmPfsgoaXw50xVoMODwhKdOmN+jH73I9Ft5XIvPPSfNyWPwVM0bN/R7X3KJGrnGnVy/x6uuhIYFi7oeC9vb9cMRAQhEdXH4CiFpI5d0aRLD8Q3aynuBAKfrySMO5GgOs5xNWwm0PonlqDwOnji47nwCwqSdJ72gw3WAikWh97jnxTWpwQLhREpmlxGb7DQCF1UCf4EhoWj17iJ5m/KZKJDIkLqRqJuQiKvY1v1HYAxMz7Gc/esy20HDhXVp6cJqSstnk7qBq26ESwhHhkwJtkRRlyT5pL6FI/437Zl3/4SuxbXt14v1TIuQ3BEXXR6iH841jPfLERim/aS+q3uhEbFCDpeiqLHiJhN/6jpH+CZbxZK7tvTNO/1APyrWfb+toOG4tG3/ie6vRir74DJ/ye6v6bdeolua0SsR9OLP67AI2+9z/v48Nh4wx8eMoz7BgSa/g4IrT7zsk5cPSS27SCqbbvBD0Imk4n+jYWugSSMV1HECIp+9+Jpx77/Ce829Vq0wtSf12LCJ1/i1RWb7r3L746PbdIMz3+/xGR5fP77JYLGy0Yu8Pv2fuJpPPzKf+EbIN6iZH6zCLtxPO8sJJ7Yxk09PQTRyCDDhE+/FN2+zxNP8zqu+5jxSOrQGeH3LMPdRz8uuk+hxDa5H2Oe2KYdnvvWgyEgEvbUT3w8V1Q7KQLxkBdeFd0WAIJFhBm17j/Y9Dd708KXgc++BAB4dflGwW2l4AR5STwi3S31evGW8bgmzU3KU74brIHPvIgICYnuLBMAecIDQuz6wVZA+rA8hXghcnJJzcPSoF0nSb+XJ2F7AshkMjR2s7dg5xHCq350evhR099yuReadBWf8Eqn1Qpu4+0ncF7eY8gLr2DYf94Q1ZZN34lTRN1fci8vNO3ak/fxBelpACDZcCaWwf/3H9Ft2QmSffz8RZ+nQTvh3iJSDG7G8EKx4RtC13oSxqsoQq3MCS3bYMCUFwAADdt1xEsLV/FuK5d7Ib5ZC0GTp16L1hj+6tsIi76vMRerDX/4lf/CN1DYIhMQHIKWfQfglaUbRAvkUhYGVMOs3kaSOgp3pR0+7W3EN2+FehITWgglIDTM6j0vnhn/bQmDci/u+O0BU15EaKT5/RcWHeMWofiBSc+g47CRptdDX3wN4RLjlqQgJTlOaLRITxkR68hLC1fhzXXb0XbAEDTr2Vdcv4AoN+I2/QZzH2SHuGYtTLkMfAMCBbkjSvagErleWyalcYaXEl/E1voe8fo7mPDpl6ZnVHBEXV7tbM3/Ea+/y3uehMeYW5Q9USdYzPqR0KoN4pq1ML0WOm52noxGnbvxDt+QalF3hkV+4mdfIa6p+71VGol4LtvDPzhEcJvQyCi0FriWPTDpGTTq1JW3ktsRovZjIq0iTbv3FqUYS+rQGfVatMLY92YCMMw3Kc9n9v6ZDz3GPuERTyopd1VYdCwmfPIF4pu3wviPZos+j/GaC0EulzthTRDXXqgyjYRxBwiNk3ImjEB3vMeTPzdz6+IjdEjhiY/n2FyEhJadeWXZRrTsOwChkVHo99RzvNq07DvA9LdMLkfTbuI2peyNndAbVqq7pBEprv1SEPLw7DtxClr07ocJM+dizL1kaO6gcZfuaNSxi/lGTibj1FT2GPM4Rr7xrk3FAZ/M+R2H2c4qKzUTMy9kMrMEKUIf1tbnkz6e6oJMLodMLsfI198RfQ6hSevimjaHl4/4cpBWHkE8r3dIZBQGPT/VTHHjLiITG5i9dkdSoQGT/w89xjyOBiJdDuvE1RO1Katb3zqspXnPPng8+XNe7WMtNs7evr7o/fhTgsfh7pJqlht+b19fjJr+Ae/20Q3vJ19r0KY9Rr/DL/5bsjAuMQnZkBdeQVyT5qLyClQl4lmKFO5j78fECn3GeXl7Y/Q7H6H76PGC2hnp+NBITPjEcK3riBBqIxLqi+pXbAx2nbh6eOLjuWjYvpOo9pYYc1HwJSA4BI99KKxNVSC+WUtMmDlXklemmLUhqWMXyc8nsWuK0DLRVScrgIfw8vWFb1CIzR+698RncP3kcd7nkvn4QqlUIlBiggOlUolOI8bgxLZfBLVho1ZrOMdh2caI3M9fdNuA8AgwAqxpjFxuOlebwQ/h5I5tnG36PPmsWf+9Jk2BlmFw9+I53v0CgF9YuOk8Gp1e0O/mGxJmaivm92YYBqPf/h8CQ0Lw86vP82436NmXsW/pjwAMSXLO79sluO+kjp2RdoH/ter26DjT377+AfDxD4BGWSm4X6H0f/p5yORy9JkwGalnTgIwyCpci7KjzS6XFjuxTTunWFfE0qBtB0Q3bISRb7wrquSeM2Anr9NrNaLPIzreXMT1t3rgymSiXKFlkGHgsy/hr6U/8WwgQ3hcvOB+2D2y4auEnfjpVwgMDcPAZ17Ev7t+E9xrdFJj0b9PQss2SL9yUVRbI10fGYuT2zfzPr5Zz76iwxfaDR6G6IbW9cXrxCegKDPdYVshQo0tmvfsC71WixjWJlTM+vLwtLdxfu8uHFq7XFA7y9rEiW07IO3CWc52tjawjTt3R58Jk3F43QrO9vVbt8Nz3/2M9CsX0YqlPOeiTlw9k0uuGKTmuDAlnhPxGwmd02zEulsb8Q0IhLqy4v4bAsbPVrK4+9E3cMqLpr+b9+yLSwf3CWqf0KK1qH6N92C7wcNwfi//PZSzFY+invFO+pGe+Hgu1n803a19uptej03Cr3OSJZ1DrHegUCG+FgvjMiT27It67TpB7u1tWsS9/fygVakAALdu3UKnCc/wPqNfUJDgNoAh8Vt5UREAg0X71q1bCExsJOg8t27dMnvN6PWc7S3bGAlv3hadGjQR1bbliLG8N5Q+fn5W5+Eas39wMDKysq3ebzTgQUS1Faat9PUPMPWv02gE/tbBpradJz0nyJMhuG4kGL0exWotVIoyGDbk/Bb5Vv0GmoTxFn36CRbGx384C3FNmiP3VoqgdmweeuVNbP+Sv3a231PP4eAq4fkEjG5r5kuaTNKDgWsjHJkovpyOLVr07ifoeKPQ0KxHH6f0L8YVj629HvzcVGyeLTKrsYjfKaFVG5Tk5Ahux1iEjchkMlEbp+hGjRHfvCV/YRwGa8Vz3y4WtaG2nI98BLVXl28UFZvO5omP56BSoTC9fnbeQvzy2QdQ5OU6bOeskInejz8lSHCxzGL+8qLV+PEFfkk/+z9tW9n52AefYtHLUzhaS3ebdkaZKv+gYLQbNEyQMD5p1jdmFUMAQwgbH2G8ODsL3R4dhz/xnZmHUXlxIWfbhHuVScJjYk05NwCDoF2UlWG33ZSvf8Tp33/lPL9DnCQ0iFGY9JnwNJp174017wvP4i41BOqlhSuhyMvD8v8aQkiEjN/cQ9BzzrKWiiN7dBk5Bqd+24IRLA+o575djCWv8U/mZlQ4D3r2ZbcJ4/5BwVCWl4lqy3bhd0ZS1db9BwsKORRroPAWmmvCyXj7+oLRS1Og1GvRCnIvb+h1wnIaCM2DVWuF8cSefdGway/UjagDH5ZLd0R8PSjy8uAfEoKA4BDkefGfhIFh4QgKCxfUBjDUP85Luw0ACIuKMcVA53nz/zEtayjr9ToU+Dh2VbdXd7mssACVZaV22wWGhiEo3Hbm+EJfH+h4TNq6CYmQyWRWNznXtaubkGh3kusbNuTUqgfXiQADQFVWhtCoaJO7klqlQok//7I1oZFR8LsX5873OxuJSmwIhmFQUVGBnOxsJPbsi7R//ubd3oiYRTmhVVtTaz7YiscXkngEEL4oceFowyA1wYmlUCeFMe8mmzYYI15/B7/Pm2PzuAcmPYOLB/ZiqMjkY46sVSNem44Vb78i6ryAsKQpDdp1RMaVS9Bq1ADEPcC7jBiNfUv4C8JGLOeETCYHA+G/pdBEVWH3skw7S0iNTmqMrBvXHB4jVRAHDJs770g/NOnaAz5+/qgTVw+Dnn0Zv87hCEOxsa+xzK/ABy9vb7TqOwDKinKknj7BfbxFKICQKhb2YlF9fLljVD3pJWOJEEvLuPc/tekSyje86ubJf/DoW+9j2qrN8Ga5W+q13An0wuxkXh/ywivY+LH9sq1169XnHctvD0/+XnK5l1nyTSH4BYq/pwc9NxU+fv6oK8Jl2yqG14PTne9v1+/JZ9HrsYlm93VQBH+vmZcXrzH1JffywhvrtuGbCY9ytLrXj519Lx/q1EtA1vWrotr2emwi90EcxDZphgmffAGdRiNYSDYmhzbAf5IMkZD4zVkYKkFcEN3e1z8Ary7fCLm3F+95AgAQqNiqlcK4l68f6rXrhLoRdRBooXEPCg5BECv5hY+A2Gs/X1/4+/sLagPArI2fnx/8/P0F9+3vb76x0Ov1NtsbtXNePj5WbYyofXygtdN3RHw9h5vBoJAQVJYq7H5uJNDOw4frO/v7+zsU7hQc7esYY7QtYrV9vLxQIeS39vMzXT8fby/IeVq2ZTKZqV1AQAD0Oh3qteuEjNPHoFOrefdvOJmww439C8GTsXOmsbLG7Gj8bQcOxeDnORZ/jq8vVYvKxtvX1zTeRg6SeTTv2Vd0+QwAiG6QhMQ27ZFmI0zD0jLGC7MiA0IEgE/w/ZTxwD1h3EeUpViOxDbtcengXs5jh/zfK9izeD4Aa6VR/dZtcef8v5znSGzTDmkXz1u9HxoVA0Uet4XemDRTNJaX141lGmQymVkpokAbyRItCY2yLpXXefgopF08Z3P+OeKhV/4LAPjqcds5GtjYUsCNfucjXPvnEC7//ZegfgXhQeHELygIqvJylsWQ/2AatOtg832huWislVPcE9Re7peElm3Q8aGR+Hen/bCKriPHoiQ3B03dVN7VFTz+8Ryc+/MPlBcX4e4l67XFFrbmN99ndVQDa2+uuCbNkXKKO8Syvkk5L6xPR/R+/Ckc2cCdQFiMYNt5uEEYslSw8TVMvLF2m1U+JXayQb79i2HEtOk4tG4FOg8fJbgtW/nIiHxIeHl7Qy73gtxPeD6pxNbtRPXprFC7cf/7FIDB0/DqkYOC2vZ76lnodVpcOXxAdP+Wnll8EGqEqpUJ3HyDgiH39rYS/DxREiMoPNzstbeEZEB8CI2KRkjduoiIE/dduZIVhdSNlKzd9gRSkjAJWRotFRkBAQGQe3vDN4hf9lN31H1uM8BQ0qZZz752hTl/M00pNxH1xCVasUJm30I09MVpkhMXCt2sAg5cylkbGx9fP7t1RaUm8ZN7eZv1NfDZlzDhE/Hl39hzTOjmrN1gQ8xlYpv2nBbcHmMnYMgLFlZ7mUHA7TtxilnZHFv4+Plh5Jsz8Mib71m54/edOIVzrKPf/QiPfTDL5meOEvwYBf9H/vseLwHWEc17PmD2WkxiyEff5p9YyyE8fuuYxtaWP29fXwz5P/HeF1O+/pHzGLmX9ValUaeueOg/wl2CTfCY2u5Yb+0x/sPZ6DtxCh6+p7RwBgktxcXYGuGjrLSX8V4mk5nFCNvCx98fD/3nTTQRmEjRHuzkZO4ioUVrDJ/2Nh7573uIaeQ43M+I3Nv6ucU7uzrLdXrylz+g35PPiipTZkD6fO8xhl8Z0ImffiX43JH1G9r+gOdzSur+QEoFntCoaAyf9raoJGZ855FQOjzITxHKTuwnRIkiVnFgiTFxp5AcHk27G+rIB4SE4uFX30LzXg9wtHAuQpMh1nhhfIyNdPgymczqIevl7S3Z/U+MVtHo6hyZ2AB169U3Ewoj6zew14x7LHbel3t5ISg8QrTwyVVWSu7lJalOcHUkRJDywXxxMs5Fe3PHPzjE7k0tJb7LUamZQc++hLEzPsawqa/bPeaZb7hdiUMiDVa0xl16YMInX2Ds+58IHidgfl8ZrpX47821uWbX1nU0DjYDn3nRZgk2S4S69/MlpnETk2W9afde6PjgCFGJp4wPK3bCPr70emwSAEOW/rHvzcSjb/+PowXQe/yk+wmT7iGTyeEXGIhuj47jzCTPMAyade9teuiyqctD+eNos+tIGH/u28V47INZaOKE37P9YPPvLyakI8xJFRm4nl8yuRytHxhk8zMpmy4+v5UQ65VTcXBN+AodYoms3wDdHh1nEm6lhNC8+OMKPJ78uajSfWZUHa99K2y53o59z33VPyzxDwq2KgNoi/ZDHrI5v5t047e+sO+9yPoN0GXkGJcbdQBDhQMpiFFC21tnqlA0iUuom2Bd1UEo3UY9ZvXegCncv6GXjw9kMhme+eYnPDXnO/gHCzDEuKHShj0sFbWWew1XQ8K4BeES3SSECJZiaqD63LPoePv4wsfCbVyMa4QJG6tTeIy0uEax5SCciSfXXDONIGuNCQgJ5f1byb0sriHHF0po2cb+JlngEyiRVRYopG4knvlmodUxryzbAG9fXzTs0Nlh/GxgWDheWbbBYX+Tv/gBU39ei7DoGPgHBaOhgPhjc4QnubJ7JgcL5MuLVjvUQMvtzH+ZXI7/+2Gp6DFJxXhtX1q4CiNff9fqc74PheHT3sZLC1dZJdKZtoK7qoNRkPfy9kbD9p0EJY5r2ac/AMOGI7ENf3c4R8l0JK2duO9CbYvAsHCHWfftua6/tHAVXlpo7r5p+dsMeVFE3gAn7USjGiY5rGH70k8rRcWlsmk76EFJ7d2No7Wm13jHCeSs1vp78L0GllY8v8AgePuIm9fBEXUFCeJNu1kruABpBgJnw1YajnzjXUxdstbqGGfkV5AEx6350sJVdkOr+D7nxHhzAcCDL78uqp0RLs8l9yJtDZQcbmSB1L02m2mrxGXoZzPx069sKp95KTnvPWcj4hNsVqVw3NRzwrhVKIPEsofAfQMTH6qFm3pycrIpeZfxX2zsfaGZYRgkJycjPj4eAQEB6N+/Py5duiS535cXr7GrzbPnfhIcURfRSY15nd/48Iyol8A7IYezE44kJyejQ4cOptevTX8HU156Gf5BwXY1Wg0bNsS8efM4z+2s20qKUM9XsLibno64Js1w8fJl03uWIQFCadu5CxYtWw7A2q2Mjxu2X2CQlQs/l6XWumQT9zjt8di9uBsjAaHmyqMnZ88zeWrwgetYLx8fUQoqS3wDWYKdi1Tg8c1bcSaFCq4TgY4PjbRKaiaTyeDj62dWH9wTBIXXsXl/8HUHlMlkNl3QLJWENttKeNA9/OpbeHP9b5j85Q8OPW/aDBiCLiPHiO5HCPY2HXzWLnvPkqDwOpwufvaSajpCyD3rCLncCxM+/dJuiAP7/ggIsfAE4dh0Pf/9Ery5/jfRSQpdgeSa1hztJ35q5zqGhqErh/eJrXkmk8kw1oannyvwtbd/qUImSHYoSnhsvF3lsVihU4iHUH07MbVcz3cpCcGMBATzC3GzpE3/wZL7djt2lhmuezGuWQuHoTSJbdpLGZUVz367yGnnspzXYryn4praV7JyISmprQeFcSnYu5+FKBeqjWW8devWyMrKMv27cOF+tru5c+fi66+/xvz583Hy5EnExsZiyJAhKC21n+HbHpY3aaeHH0XrfualRoLC6yDERmIaI3wmP1sY8/UPQB2RMdlCMFp/bGW8loKP3fMJv7GMygA2opJKAZKvqReHVcGRNc2YTyAgNBQhdSOtLH98tih14uIFKyIYvQ4t79VptSxFIXVfZLlRcHZckrOyqIdERGLw81Px8Cv/Nd3PD097m5cLIF9GvmFtUbbFwCkv4oFJ5iXwjG7zY9+fKTgRWx2eNaodJYDjQkyMmiW2XMHZSFW62KqsYPkg7//0/6Hfk8+yPpZWZkYILy9eg66PjsNTc7/nPJZvXGKHB4cLGgMAm5br0MgoDHpuKu9zOLIWymQym/etpZW3bkJ9DJjygll5IUcoy0pdlum6KllrjTRs38nhevoAR04Du3PbTbKwvd/KmQku+WBv3Xv6C0PixpFvzkD/p593aLETGzee5CCUyxK7ZY9cqLwY8fq7GDD5/0Tvp2zD7/eNb86/LJYQRk3/EO2HPCy8IcdlfuTN90z5TFyCiBKVYvHy9sFD/3lTUp4OIei0wkp6sfGULD7+Q+tcMPaqPNhizAzb4S1CPK3rCbxHPOZ37O3tbWYNN8IwDObNm4f3338fY8YYrCArVqxATEwM1q5dixdfdJwAxBK2dkJ/b1IFhIWbit5E1m8g2qXR29cXWrX9zMFRDZOQd9t2PW5nEBoZBZ1OBz8nu2L5BwVDFhMLLx9f81JhTrqxxC5UUsp/ANzuXHXi6yH/zm2bGyHjBtbH18+2NttFa6+3nz8GPfsSGrTriKT2lnU4ZYhOaiy6ZrizlTiWCNUMOsLyAd3yXv3uhFZtcGTDKgyb+oak80vJc2D8nqGR0Xhg0jOC6ifHN+O3YD/8yluY/8x4UeNzBsNefh1Nu/XCH99bW/seT/5csHDrDKRo7J/9Tlhd38DQME4ByohlhmJ71E0QLkSOnpFs8/0OQx/GviULONuPeP0dxDd3LJyw79u6CYnoOW6iTctKp4ce4ezPiEat4n2sJcYwBns89uEs/Ph/kwSf154HQ2zjpshOuSH4fGw6Dhspqb0n3TsN2HmgcdxzfKzJ4TFxKM7JAgD0Gj8JkfUbICrROiM4YFj3Us+cMFt32g4cavIgacYj67pYuUhI8j69znbJN0d7Hb6KWHs072kncagEWvTpj3N7dnIeN3r6h07vGwAad+6G6KRGOLfnD5uf2/VA4Mojw3U/SbzfZJCZ4tlDBQh9XNj7vq0eMBgUjdVEpNC4Sw+knDpm9/M+Tzwt4ezW1zWkbhRKC/IknJMbW9ctNCoazXv2xbV/DnG2t5dzISw6FulXLjps+9y3i5GXdgtJHbsIMiB7zDJ+48YNxMfHIykpCU888QRSU1MBALdu3UJ2djaGDr2fSMnPzw/9+vXD0aNHBffjHxyC6KTGiEpsaBKi2MujlNhCdltbi66XnZgxsaxctx4de/cxZdyVyeUICA7BqNGjMXnyZLNjZTKZmXvp9z/+iLi4ONStWxf/+c9/oNFo7PazfPlyxNRLwIG/DbWvjx4/gYfGjEX95i0RFxeHd999F1qWtuyXX35B27ZtERAQgLp162Lw4MGoqKjAl99+h41bfsXuvfsQ16QZ4po0w4l/z1r1t3DhQtSrV88qk/DkF17CtLenAwC69htgFdrAvuYnTpxAx44d0bBVGzw4agwusNzTAWDD5i2Ib9DQ7L2tW7eancPLyxt/HT6CB0eNQcNWbdCqazc8O9U8nquiogLPPvssQkJCkJiYiEWLjO5IMhw9dhxxTZqhRHG/tNvFy5cR16QZ7qan277YHDuF7qMeg4+fP1r27mcIM7Ao8/Xk7HkO2ztCamZRR7BrebqSyPoN8Ohb/3Oaq64YLF20E1q1QXBEXZtWTEs3a75JoKQqoqTiGxBoVyiSnBTKDpb7IyvlkYT9k1jXTj7YSkz02qotpr+b9egD34BANO/VV/C5HY171HTurOrNe/ZFSESkw2PYlja5lxea9+yDUI5YubAYxxYDrvrtlm7bU776Ee0GD4OXjw9nbHZgaBienD1P8Hom9/LCy4vXmL035IVX4S9hbox4/R08881Chwky+cAuOWeP4LqOf0e+tB9q7aHRfbRtxZ8977JGnbrCxz+AVxwxW9kjk8nRtFsvhMfajrH1C7Red+zF4tvv0PXPIaGx6XXiE3h52bibhBat8ey3izBt5S8Ok4YJSuJlg6SOXex+prVT4jWhZRuE21lnpO41xFSxMB+AtOZGxlmEEnKtA44Szhrhmptc4Zu2Er/ZK19oiS2l4lNzvuXV1hZ87jNbpf6MSA1H4GMACI+NQ9NuvQTPSY8I4927d8fKlSuxe/duLF68GNnZ2ejVqxcKCgqQnZ0NAIiJMdcuxcTEmD6zhUqlgkKhMPsH3BNYZn2DJ+d8a3oIBISGW7VnGAYapdLuP61aZfXPP8ggHAWGhQlqx/6nUSp5a8FHPjQMhYVFOHLMoMXy9vVDUVERdu/ejUmTrC0DxhjWo8eO49bt29i/fz9WrFiB5cuXY/ny5Tb7+PLLL/HWW29h9+7dGDJkCBRKFZ58/v/QsUMHnDp5Ej/++COWLFmCTz81LBpZWVmYMGECnn32WVy5cgUHDhzAmDFjwDAMXn7+OTzy8EMY8EBfnPvnCM79cwTdulhad4HHHnsM+fn52L9/v+m94pISHDh0COPHGTZpu37dbAppSE9PR48ePdC3r2EzW15ejhEjRqB58+bYvfVXvDXtVcycPYfXNWWzY8cOPPXscxjcvx/+3L4Vm1auQPs25oLGV199hS5duuDff//F1KlT8fLLL+Pq1auc5w4TmdDDYcIMGf+HkDO1tWxsbVyfnD3PbsknPlnHqxuWv8H4D2fj/+YvtanoY7tZA7C7CeVDfPNWvF312w95SHQ/VQXL68y1bjbvKVzYdRXsuTDi9XfwnyXrBCsEuKoRNO7snHJQ7FAavnkQuBIBceUdsCxlVTehPob83yuYtuIXuxtwNjGNmuC1VVsElx6yXKfaDXpQ9Ma8YftOaNqtl+QSqT3HTUBje2EprHvAWWFAlok1ffwD7F7z1v1sZ9N/8OXX8crS9bxioNnu+yFOUig4gq+F+7EPPuN9ziEWuQ/sJWGzpwgY995MTgWVp6gTGw8fP3+nZPAGDMkwLZXQjtZme/OaSyEoBSEJR20hpcILG0ujAldYo5yjuhHAnc9FxrF229pjdhkxmtdeztYzOiAkFG+s3cbZ1gg74WWL3g+YJSK2haOyplI9jri8ax0pArjwiJv6Qw/d3xi2bdsWPXv2ROPGjbFixQr06NEDgO2NlyPBY/bs2fj4Y9t+/jK53Gw5TurYGdcuXUJo3fs3t1alwneThZf0cQbTVvzCK0lSnfBwDHjgAfy6/Xf069sHMpkMmzZtQkREBAYNsn5IGq9XWFgY5n39NULrRqJFixYYPnw49u3bh//7P/NkdjNmzMCKFStw4MABtG1rcLVcsXYdEhMTsWT5CshkMrRt1w6ZmZl455138OGHHyIrKwtarRZjxoxBgwYGt8u2bdua3PyCgkOgUqsRfS8m39eGgBIREYFhw4Zh7dq1+Ow9Q+zubzt3Ijw8HI+MGYvK0hI0S0g0hQK89tpryMrKwsmTJwEAa9asgU6nw9KlS6HIykDzZk2RmZ2Ndz/8iPvis/jss88wbuxYvP36a6b3Wrc0d+l8+OGHMXWqIT7znXfewTfffIMDBw6gRQvzUlKhkVFQ5N93xfG18/vamtFvrtuOg6uXIq6p4/JUxk3GsKlvYNeCbxweO+5/4sqKcdGoU1dc/vsv0+ue4yY6jJV84uM5WP/hdFSWKuwe4y58/APQ6oGB9je+drBc0C0fxDKZDDIXeh0AwJSvFgjaLLUd+CAv90Muuo16DCe2buJ9/EP/eRM7f/ja9DogNAyVihKerbkenByf23leWFob6rVohYyrlzkf8s6Ca354+/lBq7J26+ZTjSC6YWPk3k5BnfgEJLRohQt//SlqjBM/+woX/9qD3k88Jao9m17jJ3EK9fY2s0Ks3XIvL+dkzBUpIDoruVp0Er/cHc6K37Zc/xztsxx5EvL9rQY+8yKuHjkIgL+r9tAXp+HPhd/deyXwe/NUWAuxmkXWv7/2Dpv6Bm+LbXCdCLywYDnvEK6Jn36Ftf9zXp15I3XcmGxULpej57gJOPXbfe8gPuUMnQlX6cXw2Di0H/KwXfd4LmRyGXAvUiGpQyerz+N4lhq1Wnu45i4PSy2XMspS+dFu0DCc37fLMB4HChB760RUYkPkpd2+Nz7b113Iuh7buJnpby9vHzz2v0/x1ePc9dFtI1EYt/F9Oj38KNoNehCnd2xFjzFPiD53lShtFhQUhLZt2+LGjRumOHJLK3hubq6VtZzNjBkzUFJSYvp39+5du8fK5V7wDw6BX5DnXFvFMuaRkdixezeUSsNmbc2aNXjiiSfgZWdy+wUFo3Xr1ma1sOPi4pCbm2t23FdffYWFCxfi8OHDJkEcAK5cuYKePXua3Xi9e/dGWVkZ0tPT0b59ewwaNAht27bFY489hsWLF6OoqMju+O0lepo0aRI2b94MlcrgorRl2294dPhw+Pr7IywqxiSIL1q0CEuWLMG2bdsQdU/Av3LlCtq3b49Alitvl44d7I7BHmfPnsXQB63LzgSE3LdgtWt3PxbFWAXA8loCAuKlbSxoMrkc/Z9+3mZMmK2F1Z61wsiQF15BnVhp8Wn2GPTsSxj47Eum1w3bOxYYIuITMPTFaS4ZC1+MLnJdHxmDwc+9jKQO1t4aQrDMrO8OnGG14FMr3pK+EyZzH8TCGNtmZIg9C5IN2A8+W5tHLmHE3mbB0tvkkf++j4HPvMg7GZmrmfLlD6KTE46ZkYyBz7yIiZ9+Kek+i2vSHENeeMWuh4sQeo6dwHmMs0JanGGh6vig2I2ec+CrHGzc5f5xrfsNEuW27h8cYvWscnXJqoCQUEz87Cs8/Mp/eSdXa9zFOV4fgmDNyYmffmVW7pC9Jxdibev39POCcqlIyYLtCFsJrlyJr38A3li7Da37DUbPcRMR26QZdyM3M/j5qWgtMsN8lxGjTX/3e9Lgws0OVRnFI+wEMCSTZnvPccrifOYex3xjz8fAsHAMeYGVGM7B6Y3rpGXIwfDXppv+rltf2j5lyP+9gjYDnJf1X2oqDkuvqd7jn8SAyf+HugmJGPriNJshanzxfOFoGFzMr1y5gr59+yIpKQmxsbHYs2cPOnY0bOzVajUOHjyIOXPsux77+fnBz0YSNb54+/k5rKebc+um2euIevV5uRlZtgMMMYV6nQ4BwaGQe3nBW8C4hwwaCP177+PgkX/QPygEhw4dwtdff233eLlcDv+AALPNjkwms5pUffv2xY4dO7Bx40a8++79zNK2PBKMC4BMJoOXlxf27NmDo0eP4s8//8T333+P999/H79vXI/E+vUNViDIABkQEZdg1wNg5MiR0Ov12HtgPzq0bYfjp04h+f0ZZsccOHAAr776KtatW4f27e9rsR0tSEbhXyaXWR1nGTcfYHGdjLBvMB+LxA7sa2lM+mDsJyK+HrTnz9sdm1T4PtQTWzu3bAcb34BAdHxwBFr0egCKvFxeGdn5ZJR3ZYbkkW/OQG5qCuKaidzocFjGuej/9PM4sPJnDH3JfUqJCBv1oSPiE/DYB7Ow6RMXZ5plITap36TP7q9xxgRbTbr2EHWuIItkfYGhYZITbjmTsOhYdHhwOPYt/REA0KRrDzOFlyOCwutUqe/CtwKG05I9ipDpLRO2xTRqgic//9YtLtS24KuY6P34Uzi7ewcAg8J1yTThtZKf+9Y6kWHPcY6tO0NfmoY/f/rO4TFcxDVp7rCmvSXsGGX/YIGVG2zsD8bO+BibZ/P3nItr2hxxTZtj53xDmUjL/ZQ9LD9r4CbvGy74JCzt+shYXD92GC169zN5MvBF7uVtyjBvvLflXl4YNvV1wWOVirevH4LCpJeQc0SvxyahYYfOiG3U1OQ90ueJp5F65iSade/tsGyqTC43c39u1Lk7Dq5eavzUYb988icM5qi0wfZ2eXbeIrufWdJt9GOo37odohs1xndP3a8iUzchES/8uByq8nLO/CRGgutEoKyo0Op9PvuSRp26IvXMSV792LLIT/7yB6x4i5+RgNGbJ2rsNto6nl4sHrGMv/XWWzh48CBu3bqF48ePY9y4cVAoFJg8eTJkMhlef/11zJo1C7/++isuXryIKVOmIDAwEBMnTnTZmIwJz+z98/b1M/vn42f/WPa/sOhYePv6wTcwyNTWLzAY4TFx8AsKgo+/vyCrQIC/Px5+cCh+3bED69atQ7NmzdC5szTLHgB069YNu3btwqxZs/DFF1+Y3m/VqhWOHj1qJsgePXoUISEhqFevnuna9e7dGx9//DH+/fdf+Pr64o8/9wAwuKV7+/khpmFj+NoRdgGDIDxmzBhs2f4btv7+OxolNTSL17558ybGjh2L9957z5Rlnz3Gc+fOobKy0vTe6bPnAABe9xaTuhERKCsrQ3l5uemYs2fPmp2nXbt22Ldvn9l7YTGxvIWtJm0MHgU5uXmQyb3gGxCIOzmuzRppxJjBecBk89CDgNAwzuRKziAgJJR3abTEth0cWkT6P/1/eNqFyW18fP1Qr0UrzjhXPrTs01+wVa/z8FF4ZdkGtB3AnXzFWfj4+tn0oEhs0w6vLNtgP+bRySR17Iy4Js0Fl/ViJ7Cb8OmXeHXFJs74VEuh+7XVv+K1VVsElxf0FL3HP2nQuL/0Gu9NTVUiPCYOj77NzyLkNGFchOXDz0YlgJikxk7xChDKI2++x/tY/6BgTFvxC95Yuw1ePGJHjYx8cwbCY+Lw5Ox5NhNxca2L7ly3jLDHJHSu2HJRbtihMxqyPKKE1vv29fdH5xGjEZ3UGM0cZTW3eDZILQEppbyr0MSEsY2b4pVlG/Hwq2/hkf/yn5eAZbJNYc9H9lw2lnUFxDsY/2fJOt5u0WI9a+ReXkho0dpMeI1qkIRXlm3ECI6yqZalR7kSQ7PpMeZxs/2dt40Ei1xZ97uMHIO6CYno/fhTpufsiNffQXhMnENvMbncC/VatLJplAyJiBRkUImUEGstJA9Ryz79rPsWMM6gcPM9hTP2kEY8sitJT0/HhAkTkJ+fj6ioKPTo0QPHjh0zxRxPnz4dlZWVmDp1KoqKitC9e3f8+eefCAlxXQZcVxFSN9KkYa8oKYZWrRZdUio8Ng7F2VkY88gjmPziS7h8+TKefNJxplkh9OzZEzt37sSwYcPg7e2NN954A1OnTsW8efPw6quv4pVXXsG1a9fw0Ucf4c0334RcLsfx48exb98+DB06FNHR0Th+/Djy8vLQtEljAEBiYn38dfAgrt+4gbp16yIsLMzKumxk0qRJGDliBK7duIGxj953lausrMTIkSPRoUMHvPDCC2YhDLGxsZg4cSLef/99PPfcc3jx6aeQnpGOn35eAgCmsm+d2rdHYEAA3nvvPbz66qs4ceKEVRK7jz76CIMGDUJs3Qg88vBD8PLxxZHNv2L69OngQ9OmTZGQkIB5P/6Iz5Ma4ebNm/hm3jyHbQS7Z7KPZ/09/qPZpr/3rzBYOybN+oazxrR/SCiUbo7f9vL2xoRPvrAb9+Pj7+fUsmjOhr2hevjVt0SdwxPZ34dNfQP1WrRmxV5KH4vQDNZe3j6Y+NlXovsDDA9APgl3eo6dgNO//2p6ba9ciasJixaXPLHH2CfQY6z4GDRP85yA8nHGUldSadC+E67zKF3DJrZxU9w5/69T+pfCw9PeRtPuvQS1YXua8Y2Xb9a9N6+SYDUGC8u4sQxmvWYtcfvsaQDWifwA2y7CfSdOQXlxESITG6I/z4zSUmnUuRtST58AIDxrO5te4yfhr6XCQpOMwlnTbr0g9/KyW8LNkjrx9ZB13ZDYVugWJziiLro9Og7evn5QK+8bWMQEskya9Y2giknOTrzPpwrK8GnTcXD1EpOre2hkFLo+Og4+fn6cz9eg8Dp4/rufTXuph197G1cO7ceN4/wrTwUEh2Dylz+Y7UWb9+wrKAHq4x99jjO7tmPAZOHeOQDQZfho070oFKucPQ6OtZfgk+8+uPf4J1FRUozMa5fRXUJ8uC08IoyvX7/e4ecymQzJyclITk52z4DchCNXFT74BQYhpG4kHhk7DhEz3sO1a9ec7i3Qu3dv7NixAw8//DC8vLwwbdo0/PHHH3j77bfRvn17RERE4LnnnsP//meweISGhuLvv//GvHnzoFAo0KBBA3z11VcY1M+ggZry1FP458RJdOnSBWVlZdi/fz/69+9vs++BAweiTp06SEm9hTEj7wtqOTk5uHr1Kq5evYr4ePPYZ4ZhEBwcjN9++w0vvfQShj46Ci2aN8fcL7/EY489Zlpg6oSHY/FPP+HDmTOxaNEiDB48GMnJyXjhhfuLR//+/bFp0yZ8MnMmvv9pIUJDQ/HAAw/wvnY+Pj5Yv349Xn75ZXTo0AFdu3bFp59+iscec54rC3tjYW9hGTvjYxTn5nAK4gDQoE17XnUX3UkMzwRGniI0KhoPvvy6R2prS8XZSg6Xlq+TGODlFxiI4Ii6KCsscNKAxPF4svDKDs7i5cVrRNXgdjdFmRlOOc+wl14TLIx3H/M4fPz80UhgIkc2YhTsASGhpkSW/93wO682jpIxteo7AMe2bEB0w8aCx1KTYXv1DXnh1fseQqy1qzMr5teIrQokfOqos3HG6hiZkGgSxoUkKOz26Dic2HY/9LLdoGFQV1bySgQpleY9+rCEceHPHGNG7FtnT5slfnPEU3O+w61/TyGhZRukX72EriPHSCrfOmr6h6goKbZSXjubsOgYK4+YBxxkBHcIwyChZRtBwjgg/Tme0KoNEloJK3E68bOvcPfSBXQZORrZN29YfT5mhu2E3JYIrSoR26QZsm9eF3UO/+BgjOTwdBBL9fDXIwAYbhijO1VmZqbNYyyVGLZKmM2zsNbevn3b7PUDDzyAsrIy0+t+/frhxIkTNvtr2bIldu3aZfW+MQYvMjISf/7JL6Ovl5cXMjMzUZSTBXVFBYLuKS8aNmzImaiiR48eVm7nxjbGsYwY/jAmPGWeHdgyo/yYMWOs3OCNWF4nwNrVvXfv3jhvEScutZwCG3ayMHulPhoKSEhWFS3QfN3dPUkbkYlePI2zyiEZ4SqLAhhKBm365H3BZT8ad+2Bg6uXirYsA9ISehlj+y3L8gihdb/BHos9Bmxb/NzBM98sFHR8PM9sw1z4+Pvj4Wlv44/vvuA+2NjG189uXW0uOg4biX93/ca77i6b+OYtkXLquKA2kYn2XSp7jJ2A2CbNUK9Fa8FjkYoz3TXtUTchEQXpaZxut45o0fu+cp0tgLRiuUMbCa4TgQmffMnLumkPZzxfW/TpjxPbfkFUYkPeZdoA66SXXt7e6G6jZjR/+Pfd8aGROLDyZwCGeS6Whu3vZyZvyxE/HN2wkSk5Z70WrUT1x35eGBMpuloYdyqM9Fra7oKdN8KWMsBRYt24ps2RdeOa4e9mLUzZ3/nQrEcfkzBudHGvCvtgEsZF4lKLUC1GJpcjIq4edBoN5E6O7awJv5hc7oX/LF0PMI6Ta/ClzxNPI+3iOcExvET1pGn3Xvjnl3WiNyuWjHmXOwlSYpv2eOHH5QgMDRd07jqx8Xhp4SqbMb18GfH6O/h1zsdW9d350Hn4KDTt1stheZfqhCuTIloitNa2VK8xe3R9ZCz3QRIYMOUFdBkxWlQW3X5PPYfM61fNMjFz4RcYhJcXr7G59nt5e0uuNc+3rrwlzigpx8VTc75FZWkpr+RjbNjKcLPEa6wNuL3NuFQlkZBYfntEJTbEiz+uQEBoKDZ8PIO7wT18JCQ0tsXY92bit69nYdBz3JUe5HIvTFv5CzRKpaR7WyaT4Y2121BeXOQWpWaPcU/g5qljbkto6ixa9O6HnNSbSOrYBaUF7slT5FQELh+PJ8/BvEmjANjIw8Ahm7ErT415N9nQhHX/PzDpGWGDcRIkjAtE7uUFv8AgeHko/rC24Irr62zh3ln4BQYiICQUFYX5vI53pnt0WHQMXlq4ipRLtQQfP388++0ip/3e9Vu34z4IEJ2ATGhiJUvim7XA1J/Xiv6+UkqVVDWq8jPLh0cOADGIFS75IpPJRM+ROrHxeHnRasFz0xXeDuM/nIV/Nq/nJWjZwpneX/bw8vYRLIgDMMv8xbZ8uuOZ56zkqcH3StMKsYw37XY//8Dg5x1n1OZDYpt2mLpkHe/r5uPnbzeUTghyLy+3eReFRERa7YcCQsNQqSgRlP3f3Qyf9rap8lG4i8rYuhKhHmzsJKxWikCutYj12xpDOdn3lasVuPbwvG2+mhFSNxJh0TEkvFQj6sTFIyi8juRMpq7CLyhYdCIwZ0BzuXpgzEDfvBf/PAa2kPp7N+5iKCmW2IafIO5pPDu/XS+k8MWynGVVwl7IjVRsZdKuSlSVtbd+63YY/+Es1K1nXQLRFs9//zPaDryfVd1WFueqgrHEFmCxiXfDtZfJZKb4Z28epXC5MNZ05pPITe7lhf9u+B3/3fA72g95WHLfQNWZr67E8jtOmDkXnR56BCP/y98rwRMYxy2Tyaqdp6OUeWWpoNIzwp9zVeE5UTVNhVWZWrAYOQMvb2/otFr4Bbk/a7QlfoFBHsleLYTQqGiMfvcjBIZ4JsbTEzw5ex5Wz3jd08OoNoya/gFSTp9AM4EZl53NQ/95EzdOHEWTLuLqfNcm3GEx5AvDMxOyWNoNHobze3cJTnJlxGiBkkp8U5ZrcdW5/DWKsOhYDH1x2r3SjnKnhEy5CrbnAh/XdGfTefgoBNeJQMK98qNS6PrIGIRGRvH2SCKkUyeuHgZMEZcl3FMILWPncSSUAJRZJOmLbtCIq4XVO11HjMb+FYvNvEncDQnjAvGUZrC6aSTr1m8AvVZbpR/SVY1GHbt6eghuJaZRE9MGnuAmICS0SiSO8wsMrBLjqBZUIWHc1ZbxQc+9jHaDH0K0yJqx/kFBThHGpST8I4RRHYRCv8Ag/N/8pVZhGu7aU3l5e6PVAwOddC4fp52LqLm0GzQMxzavR7Me4pMduhPLe/G5737mbBPbpBkUebmIbXS/alB4TJwppEMIHR96BAmt2qJuQqLgts6iVgvj4jYn7hWKI+LrQZGfj9Co6pVESC6XQ06COCdV2XXUHQz5v1cwYMqL+PnV51BeVOjp4RBEjSU8Ns6l55fLvRCTJL6s1sg338PO779E7yee4j6YJ1XJM4HwHLbi+l2VNJAgPE1I3Ui8tvpXs7CMqgxbGH9t1RZeRrwJn3wBRs+A7f4UUY87R4gtHZxMJjNl4vcU1eOXcjK+vr6Qy+XIzMxEVFQUfH19ObWkmnsufmq1CpBQu1AwMjmCo6KhB6BUKt3XL+FSGIaBWq1GXl4e5HI5fGux4sLbx6dKlJYgCGcT07gp90EuZsInX+L83p2m2NWqSlRiQzz9xXznnpSEccIOzXr2Qca1y6ZcHARRk/Cuwgk7LWHLX3y9aeVyL6usZ4Fh0hK+epJaKYzL5XIkJSUhKyvLbr1uSxR5uYb/1VrI3SmMEzWawMBAJCYmOr3+c3Wjtn9/omYx+csfkHbxPDoMdU7iJCnEN2vhtDre1Q2yjBP2kMu9MOhZcdnjCYJwHsFOypbP8PE0raIhv7VSGAcM1vHExERotVroeCS2KQ0NgaqyApEejCkgahZeXl7w9vaudvkAXAFdA6ImEVm/gVvrehPmRNZvgPy7d9Coc+3Kw0EQBFHd8A8KxuQv5sNLooeoVZmzakStFcYBgwDg4+MDHx7uHP48YhEIghBHaGQ0SnJzPD0MgiBqAE/N+Q5qZSX8g4I9PRSCIAiCg8jEhqLb9p04Bef37kSvxyZxHmtZCq2qUKuFcYIgqgbD/vMG9i35EZ2Hj/b0UAiCqObIvbxIECcIgqgFdHt0nOiSmlUFEsYJgvA4oZHRGP3OR54eBkEQBEEQBFEDiWncxNNDsAkJ4wRBEARBEARBEESNJa5Jc4yd8TFCo2M9PRQzaqwwbsyiqlAoPDwSgiAIgiAIgiAIwpNENDKUHHW1fGg8P5+qHjVWGC8oKAAA1K9f38MjIQiCIAiCIAiCIGoTBQUFCAsLc3hMjRXGIyIiAABpaWmcF6Em0bVrV5w8edLTw6gWKBQK1K9fH3fv3kVoaKinh1NtoDnGH5pjwqH5xR+aX+KgOcYfmmPCofnFH5pf4qA5xh9PzbGSkhIkJiaa5FFH1FhhXC6XAwDCwsJq1Q3u5eVVq76vMwgNDaVrJgCaY8KhOcYfml/CofklDJpjwqE5xh+aX8Kh+SUMmmPC8dQcM8qjDo9xwzgIN/Kf//zH00Mgajg0xwhXQvOLcDU0xwhXQvOLcDU0x2oWMoZPZHk1RKFQICwsDCUlJaQ9ImxCc4RwNTTHCFdC84twNTTHCFdC84twNZ6aY0L6rbGWcT8/P3z00Ufw8/Pz9FCIKgrNEcLV0BwjXAnNL8LV0BwjXAnNL8LVeGqOCem3xlrGCYIgCIIgCIIgCKKqUmMt4wRBEARBEARBEARRVSFhnCAIgiAIgiAIgiDcDAnjBEEQBEEQBEEQBOFmSBgnCIIgCIIgCIIgCDdDwjhBEARBEARBEARBuBlvTw/AVej1emRmZiIkJAQymczTwyEIgiAIgiAIgiBqOAzDoLS0FPHx8ZDLHdu+a6wwnpmZifr163t6GARBEARBEARBEEQt4+7du0hISHB4TI0VxkNCQgAYLkJoaKiHR0MQBEEQBEEQBEHUdBQKBerXr2+SRx1RY4Vxo2t6aGgoCeMEQdQ4tIVKlJ/IQnCvevAK9fX0cAiCIAiCIAgWfEKla6wwThAEUZPJW3gOuhI1VKkliJ7awdPDIQiCIAiCIARC2dQJgiCqIboSNQBAnVbq4ZEQBEEQBEEQYiBhnCAIgiAIgiAIgiDcTK13U9fpdNBoNJ4eBuEhfHx84OXl5elhEARBEARBEARRy6i1wjjDMMjOzkZxcbGnh0J4mPDwcMTGxlI9eoIgCIIgCIIg3EatFcaNgnh0dDQCAwNJEKuFMAyDiooK5ObmAgDi4uI8PCKCIAiCIAiCIGoLtVIY1+l0JkG8bt26nh4O4UECAgIAALm5uYiOjiaXdYIgCIIgCIIg3EKtTOBmjBEPDAz08EiIqoBxHlDuAIIgCIIgCIIg3EWtFMaNkGs6AdA8IAiCIAiCIAjC/dRqYby6o1arMWvWLNy8edPTQxFNTk4OZs6ciaKiIrP3t23bhkuXLgEAtm/fjosXL3pieARBEARBEARBEC6BhPFqzNtvv42rV6+iSZMmZu/LZDJs3brVM4MSAMMweOqpp+Dn54c6deqYfda8eXNMnDgRBw8exMyZM9GsWTPe5z1w4ABkMhllyicIgiAIgiAIospSKxO41QS2b9+O8+fPY/fu3Z4eimhmz56NRo0a4Z133rH6rEWLFpgwYQKGDh2KI0eOwNfX1wMjJAgCAPQVGij230Vgx2j4xgd7ejgEQRAEQRA1ArKMV1MeeeQR7N+/3ylCKsMw0Gq1ThiVYywTpL333nv46aef7B7/7rvvQqVSoUuXLq4eGkEQDijecQtlhzKQ+92/nh4KQRAEQRBEjYGE8WpGw4YNMW/ePLP3OnTogOTkZLP38vPzMXr0aAQGBqJp06bYvn276TOjG/fu3bvRpUsX+Pn54dChQ+jfvz+mTZuG6dOnIyIiArGxsVbnteTAgQPo1q0bgoKCEB4ejt69e+POnTsAgOTkZHTo0AFLly5Fo0aN4OfnB4ZhsGvXLvTp0wfh4eGoW7cuRowYgZSUFNM5k5OTIZPJrP4tX74cgEF5MHfuXDRq1AgBAQFo3749fvnlF7tjrKysxPDhw9GjRw8UFhZyX2SCIMzQZJZ5eggEQRAEQRA1DhLG78EwDPRqnUf+MQzj9O/z8ccfY/z48Th//jwefvhhTJo0yUoQnT59OmbPno0rV66gXbt2AIAVK1YgKCgIx48fx9y5czFz5kzs2bPHZh9arRajRo1Cv379cP78efzzzz944YUXzLKT37x5Exs3bsTmzZtx9uxZAEBpaSneeOMNnDx5Env37gXDMBg9ejT0ej0A4K233kJWVpbp35dffonAwECThfx///sfli1bhh9//BGXLl3CG2+8gSeffBIHDx60GmNJSQmGDh0KtVqNffv2ISIiQvK1JQiCIAiCIAiCkArFjN+D0eiR+eFRj/QdP7MXZL5eTj3nlClTMGHCBADArFmz8P333+PEiRMYNmyY6ZiZM2diyJAhZu3atWuHjz76CADQtGlTzJ8/H/v27bM6DgAUCgVKSkowYsQING7cGADQsmVLs2PUajVWrVqFqKgo03uPPfaY2TFLly5FbGwsLl++jDZt2iA4OBjBwYa41GPHjuF///sfVqxYgTZt2qC8vBxff/01/vrrL/Ts2RMA0KhRIxw+fBgLFy5Ev379TOfNycnB448/jsaNG2PdunUUd04QBEEQBEEQRJWBhPEaitHSDQBBQUEICQlBbm6u2TG2YrHZ7QAgLi7Oqp2RiIgITJkyBQ8++CCGDBmCwYMHY/z48YiLizMd06BBAzNBHADS0tLwySef4Pjx48jPzzdZxNPS0tCmTRuz40aNGoW33noL48ePBwBcvnwZSqXSSjmgVqvRsWNHs/cGDx6Mrl27YuPGjfDycq6ygyAIgiAIgiAIQgokjN9D5iNH/MxeHuubL3K53Mqt3TIxGgD4+PiY9yGTmYReI0FBQaLasVm2bBmmTZuGXbt2YcOGDfjf//6HPXv2oEePHnb7GDFiBJKSkrB48WLEx8dDr9ejYcOGUKvVpmPKy8vxyCOPoGfPnpg5c6bpfeNYduzYgXr16pmd18/Pz+z18OHDsXnzZly+fBlt27a1+x0I6TAMg8L11+Ad4Y+wBxt6ejgEQRAEQRAEUeUhYfweMpnM6a7iriAqKgpZWVmm1wqFArdu3fLgiICOHTuiY8eOmDFjBnr27Im1a9eahHFLCgoKcOHCBSxYsADdu3cHAKtYb4Zh8OSTT0Kv12PVqlVmMeitWrWCn58f0tLSzFzSbfH5558jODgYgwYNwoEDB9CqVSuJ35Swh/puKSrP5QEACeMEQRAEQRAEwQMSxqsZAwcOxPLlyzFy5EjUqVMHH3zwgcdcsG/duoVFixbhkUceQXx8PK5du4br16/j6aefttsmPDwcERER+OmnnxAbG4s7d+5Y1RlPTk7G3r178eeff6KsrAxlZYZMzmFhYQgJCcFbb72FN954A3q9Hn369IFCocDRo0cRHByMyZMnm53ryy+/hE6nw8CBA3HgwAG0aNHC+ReCALT2vScIwtPoytTwCqacEQRBEARBVC1IGK9mzJgxA6mpqRgxYgTCwsLwySefeMwyHhgYiKtXr2LFihUoKChAXFwcXnnlFbz44ot223h5eWHDhg2YNm0a2rRpg+bNm+O7775D//79TcccPHgQZWVl6NXLPGxg2bJlmDJlCj755BNER0dj9uzZSE1NRXh4ODp16oT33nvPZp/ffPONmUDerFkzp3x/giCqPoq/0qD48w7CRzZCcO963A0IgiAIguCNOr0Uxb+nIuzhJPglhnp6ONUOGeOKulpVAIVCgbCwMJSUlCA01HxiKJVK3Lp1C0lJSfD39/fQCImqAs0H6ShTipG/+AIAIOHzvh4eTe0g/d1Dpr9dfc1zvj0DTVa5W/pyNu68TgRBEARR28j44AgYjcFDsjo+Z3UKNeTBPpDJZdwH88SRHGoJ1RknCKJGoFfpoFfrPD0MgiAIgiCIWoNREK+OKK8XIWvWcRSsuuyxMZCbOkEQkpE5T5koCkarR+ZHRwEA9Wb1cap2kyAIgiAIgqh5lB5KBwAorxR6bAwesYwnJycbspez/sXGxpo+ZxgGycnJiI+PR0BAAPr3749Lly55YqgEQfDA08EuOoWa9aL6amgJgiAIgriPJq+CvN6IGo3H3NRbt26NrKws078LFy6YPps7dy6+/vprzJ8/HydPnkRsbCyGDBmC0tJSTw2XIAiCIAiCIAg3ob5bipyvTiPny1OeHgpBuAyPCePe3t6IjY01/YuKigJgsIrPmzcP77//PsaMGYM2bdpgxYoVqKiowNq1az01XIIgqgmettITRG2G0eqhzihDDc0NSxCEG6m4mA/AwvuNIGoYHhPGb9y4gfj4eCQlJeGJJ55AamoqAEPt6uzsbAwdOtR0rJ+fH/r164ejR4/aPZ9KpYJCoTD7x4VeT+6sBM0DQhx6tQ6lhzOgLVJ6eigEUWUoWH0Fud//i7IjmZ4eClHD0at1KD2SAW0hrcE1ldqY/UVfoYG2oNLTwyDciEcSuHXv3h0rV65Es2bNkJOTg08//RS9evXCpUuXkJ2dDQCIiYkxaxMTE4M7d+7YPefs2bPx8ccf8+rf19cXcrkcmZmZiIqKgq+vL2SezkBFuB2GYaBWq5GXlwe5XA5fX19PD4moRpT8cQvlx7Kg2JeGeh/19PRwCKJKoLxqSIJTdiQDIX2orjvhOhR/3kHZ4QyU7LyNhE97e3o4BOEUMmceAwDETu8K7wgqt1sb8Igw/tBDD5n+btu2LXr27InGjRtjxYoV6NGjBwBYCccMwzgUmGfMmIE333zT9FqhUKB+/fo2j5XL5UhKSkJWVhYyM0l7X9sJDAxEYmIi5HKq9EfwR3WjCADAVGo9PBKCIIjahyql2PCH1j3ebaV/p0N5vQiRk1tB5uPllj6J2ov6joKE8VpClShtFhQUhLZt2+LGjRsYNWoUACA7OxtxcXGmY3Jzc62s5Wz8/Pzg5+fHu09fX18kJiZCq9VCp6MsjbUVLy8veHt7O9UzgtHqIfOu3oJ96d/pkAf5IKiz/XuOIAjH6FVaMFoGXkE+os+hLVFBJpPBK5Q8d1wJl8KfIEr+uAUAKD+Vg+Ce8R4eDUEQNYUqIYyrVCpcuXIFffv2RVJSEmJjY7Fnzx507NgRAKBWq3Hw4EHMmTPHqf3KZDL4+PjAx0f8Rokg2FReKkDBqssIf7RxtX1Ya/IqTJuO2iKMa7LLUbw9BaFDG8CvYZinh+NSnCF0MAwDbW4FvKMCqaa7AzI/+gcAEJ/cE3J/4Y9bvVqH7NknAAD1ZvWha+0iCtZegSa7HDHTOlV7RSrhehg15ZkhCMJ5eOSp89Zbb+HgwYO4desWjh8/jnHjxkGhUGDy5MmQyWR4/fXXMWvWLPz666+4ePEipkyZgsDAQEycONETwyUI3hSsuQIAKN6W4uGRiEdfC92u85dfgiq1BHk/nff0UFxKye7byP78JHSl0jLTKv68g5xvzqDk91Qnjaxmo8mpENVOX6a5/0JHAoCrqDyfD21uJZQ3iz09FEIIlLC/5kP6xxpPxYV8VFzI9/QwPIpHhPH09HRMmDABzZs3x5gxY+Dr64tjx46hQYMGAIDp06fj9ddfx9SpU9GlSxdkZGTgzz//REhIiCeGSxC1itroqqkrUXl6CG6hdP9d6EpUKD2YLvk8AFB2tHbk3CjZcwe5P5wFo6GQphqNhKWP0elReiQDmpxy542HIIhqhTq9FMXbU6Cv0HAfzEHllQInjKhqo1dpUbjmCgrXXIFeXXufrx5xU1+/fr3Dz2UyGZKTk5GcnOyeAbkJvUqL8lM5CGwTCa8w/vHtVYWKf3PhVcevxrvxErUQGWqXlYVqQAuidF8aAKD8TC6Cu8dxHE3URsqOZqFkRypKACR83tfTwyEIwgPkzj8LANArtYgY31zSuSrP5wM13CGYHfLBaPSAb+1MjEjBUTypvJSPwvVXJWluiremoOS3VOT+eM6JI3MP6owyFG64VuPdeInaAaPTo+J8HnQKae7aRC3DTVmbqwqa7HIUrLlC1l4eqNNLPT2EWggpFWs+991VdOXSrc1CYbR65C44i+LtwkIPxYYmER6gCniDkjDOk4JVV1BxNk+Se2flvfqruuLq5xKrLagU1a7ycgHUd2vRJsXz9zTBg7LDmShcexU58057eigEwQtPODPkLjyPygv5yFt8wf2dEwRBsCjeckPQ8QzDQLH3DirO5oruU3m1EOq00loTklUrqQKegiSMC0QvMfFRbUKTV4GClZeR+8NZTw9FEtpiJZgqcLO6jVqgUKi8aojF0lcYk9XVgi9NVDs8nUyRude/WSI5gqgC6JVaaLLJ+uhqyo5lIW/pRc/F87IezUK9T9RppVDsTUPh+muiu2f04vd+DCXdJHhCwrg7qUXyHABoC5Wmv3UlKpT9kwm9qnolaCj+PRXZn59Eyc5bbu1XfbcURVtuQFdGyh+hMDU8CUjR1pumrP2EcLQFlWZrU1Umb/H9sKAq4ElHEFWGwg3iBSyCP8Vbb0J1vQjl/1Q/y7AnlYiajDJkvH8EhRtpnlZ5qsDDlYRxEejVOpSdyKoV8ab6Si002ebxgpUXhZcgyF1wDsXbUgSXQvJEjBCbssMZhv//zhDcVopGNfeHsyg/kY2iX2+KPkdtpWSHexUn7oRhGJQfy0JlLS8DIha9WofsL04he+5JMDrh96cmrxIZHxxB2fEsF4zOGkZ5X7FUm5xzLFFnlKFo602XKyc9vyUj+KK8Uui5zmvhRNErq6GSuwr8ThVnxLvIE25C4MNVW6RE0a83oMlznmcOCeMiKPnjFoq33ETuj2c9PRSXkzX7BHLmnUHh2qum9wpW87TKsea3sXRU5TX+D1DFX2nI+uQYyqqhRhYAKs/lST6H8pJnS1tUR/f8in9FPPyc9NDWlagkuaZVnM+r8smy0t8/7OkhiEbPUu6J+Z3Kj2WB0ehRXMOVZIxWj6KtVec75n7/L8qPZaFoi2vHJGW1c8Z67yk8uc4zegaq1OLqVdZIwuVS3y2FjsIdOWEYBuqscvN1mjEIQu5Ar9ah9HAGdEXSczy5S3nLRnm9qNbX7nYVBasuo/x4NnIXOC8ZNwnjIlDeq/0n/CatfoKNJ11+FX/eAQAUbxOWxbKqoMkuhyanvFoKtCaq8dDdjSpNgazZJ5DLUXFAV6KyOSeUN4sNSeW+OWO/cVX4PURYlKWir9CgeEcqNNnlZn8TrqFk5y2UH3P/BpKLqvibMxp9tY4NLT2cgaxPj5murTufVwzDoPRgOvIWXUD+sotu69dTqO4okPvDWWR9dlxQu6JtNwVn867uVJzORe63Z8y8EnUKNbLnnETpYeGeikIp2XkLJb+nOiVE0RPK2/ylF1G45gopfvgg0E1dk3lvrXRiTheP1BmvtVSFjTThNkoPpqP0YDpCBtZH2NCGnh6Oyyg/mY2izfeznOrK1Cg/lYOgzjHwCvH14MjcS8WpHACAxkH1gPLTOSjadB2+DUIR/XJ7s880mWUuHZ+r0BYq4R3h79I+irbeROX5fJQdykBA+yhUnstD2aEMqudsA32FBoyegVew+Huv/HTtdK1kb8m0BZXwCveDzMu+zYLR6pHx8T+Q+1ff2rjG0LGirTcR1CUGJbtuI3JKa/gmhNg8ntEzkMmluxIxWj1y5/9rSsKmvqWQfE63IfLrq24WC26jK1Oj/B+DYix0aAPI/WvHtr3smH2PyJI/UhHSp55L+xfzW1UV2Ao1fYWm+uzDqoDhSptfCZmvHF6hfjY/lxJ+6giyjItB5G/BOCF5GaMzuHQprxdJPpcrYfQMCpZfsnpfr1DXuqRkpX/d9fQQRFPBw/WSLYgDQMHKy1Dsuo38Fda/f02G4VGDumTXbQCA+o4Cqtsl5h9Wgfg2MahulXAfJBF1xn1FRXV2B5YCH+U9wzDInHkMWZ8ed3uyTEbPIHfBWaedy5612R2W28qrhcj+4hTyfnZc0k1bqAS0+iqTbV5fqUXx9hRx5UQZoOiXG9CXaexmny49lIHMj446paa68mYxZUPnA3vzr2egK1Oj4mxu9fa4kwpfRxQJz1RtnrhyvlKouJBvtZ8S9TsLbMIwDCovF5jCSY1oC2tWJSFGp0f56Rxoi+2HOmR/eQpZs07wPmfeovPQK6VbyGuVMF4TJlX+iksGl66lF6FMKebVRnmtEHmLzpuyCJcdzQSjce1GreJMjt3Psj4V5qJVW9Ap1MiZ/y/KT2SLaq+6ozDNCb1KK16Dx9r1l4lwB1OnGTZqmvTqaekVg/JmkeBELcqrHkxAVFsReEtocivAaBzv/MqOZSJn/r8uVzLyenyx83Q42HAIOhFP1OmlpnsfMIRxid2k5Hx7BlmzTlgpuJh7CfgKN10XdV4ud3JjTLrRRb9aWWsBFO9IRdnRTOnlRO1MtpIdqWA0eqvEooxGj8rLBdWuWooUGI0eqlslohJBikYmQ9anx1G4/hqKNoq7B5Q3i1F6JKNG7IdrGoVrrqD8pPn+L3vuSeHrncCftvJcHgpWXkbW5/eF0LJ/MpE99ySKReQOyfriJP+KJYydv11A6d8ZKNp0HdlfnnbaOVWpJU4JZag1wrj6bimyPj2O8lP2hUTeiNC2Ocu1QcWyiKvvKKC+W8qZ+CR/2SWoUkuQv/Iysr86heLtKVDsTQNgcMUrO57Fy6onBC6tItfGteJ87bN+ley6BU16GYq23OA+2AJGxyDvx3PIX3wB6vRSZH70D/JteCYIP7HjeVutku44AW2xEhUX8q3u5/yfnRHvyGNhcZGLlCQkDEmTX8lrM+sJp4HKq4XI+fo0Z6LO4q0p0KSXQbEvze4x2lw3WQA9OT1s9F2w6rKoU2lzKqAv10Bjcd30ZRroCpWoOO34Oa6v0ECx/65ZsiddqRoZH/3jsCSWrkTlMjdERzAMg/JTOdBkl4PRMaKz9GpyJMwzIcKZxQ1Z/FsKClZeRuHaql1yUae4ryBSphSjaOtN0c+wwvVXkbfwPBR77vA6Xq/WiXPDtdNESKJShmGgTi+FXqVD/s8XUPJbKlQ8jTk1heqqfNAVqTjXO2uEfVfljWJTs8p7SYONXnzlx4Ubh3QFSpT8wa9ykjt/F9WNe/ITD3nHbn4SG8MtP54NvcT48VojjBesuwp9uQZFv9jXMLnyIax3QYmuijO5yP3hLPIW2U8YxS6/ps2pMCVfKj+dA0arR/YXp1D8603BCTGkZod0NHHVWeVm2dvFoMkuR9HWm4LqCavTS5G74Ky1+7AFZUczUXZUeIZ3bUGlwzkmKVme/v7iUvp3OgBzxY0g2BstjltCV03qNXPCU9rL/vwkCtdcEZexHQD7gjJaBsW/pwoKObHUmvPu1Y5111OCh+p2CUoPpSPny1MoWC1OYHM1FacM19qYrMWS0iPmayajtv+AL9p8A+nvHoJiv32B3SmwYwUlWSmdo/5QpQgLYSg/mY2Kc6x7S+T0LPr1JhS7b5tZiMtPZANaPee9m/v9v+I6lYDyUgGKfrmOnHlnULD2CnK+Oi3ZcFB+MtthCIm2UGl6VoiBXXbU6M2lvOae8DkxCbx0ZWpkzTqBzOR/AAD5iy+g/FiWqDCykj9umYSW0sPc11CdWYbMD4+ajCAAoNjvvvC1yvN5yJ1/1iyMRMjeCDB4O6a/ewjp/zvC2yuTy6vI5bC8/Kp6OVAuoZTRM6i8lM+vpLKEx7pYBarVEHh6jBSuYSnwBAjmjJ4x7KkZxiXzLGeevUS6tseolpjzp9YI42yLkrbYOgt6xblcZH78D5Q33PMwEYomu9y0+BvR5husz5r0Mrub6qxZtl3C9WUa5C28L8SrUoVtmjizQ3Ls5Rit/ZtOV2BtVWd0DMr+yTSVfWK0eoMVwc7NmzPvDMqPZSF77klociusYmHMzq3Rofx0DnLnn4U6rRR5DrJh65WGmLzi7SnQq2woFOx879K/05H9xSkUOXI3EpjR0R5Cf0sj6rul1sKeE2Q1hmEcPmgqLxWgZM8dD2uuhV171c1iaAv4b2b0Ki2Kf0+FvtR8A1t2OAP5Sy/yHoI9ba22oBLKlGLkLjxnZU1U3ihCxgdHrARB05p3U+KaJ3DaKq8XIe+n86Z68O6sF2wvKQ+j00OVWizooV7yGz/NPxvFbn5WNC7s3lOst/IWnEPxbynQOlj7qhI6hQpFm2+gcB3Lci1yTTBa/cTEcmuyBGRsd5LLBrtcqLGcZekh8YIyYFAAsZ/xluTMO4OSP1julYzNP22iSS9D1ifHoPjLucol1R3usABVmsKUdE4I9pRq2kLXxwaXHrAWvBW7b3O206u0qLzM2veJnG/GECot23NC4K2lK7knBGr1yF/sOJcCAJSfykHGB0dQfibHKTG1XOjK1ChYdRlKO+VzxSvQ76O1sTdlU3lRgsDP8egpP56FglVXkP2181ys7Q5FpTXLcWVUvlReLpAsdLLRlajMQpuEzMni7SnI/uIU8pdeNOxv7q1FHttHSjRs1B5hnEX25yestM6F666BUenub4wdYeOa65VawZseTU45r7IDjI4xaMwdaKzELDSikrw4ibIjwjTb5SeyULwtxVT2KX/FJeTMO4MKHll/c74+jazZJ6C0sxEv2XXbsZDMgr1Zd6RQsOrj3qbHGQ8ELsQmE8r94SyKNt8wi39hGEZyTFzBisvInX/WrsKoYNVllO5LE2xV0VdooLxWCL1Sa3OzU5VQ7L5jFX/vzLKBjMawQVLfUpht7AGYwh7YgiCj0d9f85ZJDGfgMT0qrxWaFD1iYuWd9Xi1FwJSsvs28hZdQKEDz6mqAsMwyF96EXk/nrO6pyw3ImVHMq3mA89eOMfgbPRKG/eDE7qxVE7xwR0CmqdxxvpjLD8qBlsJXm25TpefzEbJPVdwhmHuC4VuQnW7BCW7bzsI5eOWkCvPixPSClZdkVzatexEls1na8XpHLPEmLbQ5Iu/D4xeqEUbryMz+R8oBDyj9Wqd4JwzJTsM3grG55kypdhUhthZZH9xCgCgLVEh54ezVvs5R2tt+Rnb15vR6lF2PItT0DfOA4aPYoO1Ppfsuo2cb88ICseosJCPKk5mQ51VjoKVl5H7HU/PIR5rt2U4jpDl3pjXQ3XPxV7x5x0UbbmBjBmH7Xresh9bir13kP3NaeHu5XYGyUt2dECtFMYBQ6ITvVJrvcByzIbyE9lWk5rRM8hM/gfZs0/YFK4ZhrHqp2jLDeR8c4az3qTyRhEyPjzieFAAdDas/UKwNMoyOj0K1jjexOmVWgeWJMcPKEeWaluwFQf6Co3pBiz7h7+7eLmdYy09DgCDBdITLryeovi3+w9847UFDJr0jA8OW7lSawuVvGvrKq8WQpNRxlm6S6cwnxOq2yVmDy9NXgVK/043JR/MXXAO+csuITP5H9FJ70TD5VLGMGbzx+jRYQ9Ll2Ip7qN6y3wMNjwuzK6XiwOyGZ0eBcsuoWjzDdGxsK6m7JBBUeKOTO3FO1JFKbgYjd4w93UMVDeKoU4rtQ4TsXFaR6X2xFCw7qpBucbzOxT/liJaeOfTTq/SIW/RebuhQyb3VAFj0ObyFEKc5M1kC8aWcsIG+kotlNeLoK/QSLqV2ddayHks9wnp7x6ym3CqaNtN5C06b3fu2Hq/aPMNlO5LQ/npHGTNOmEKH3GEJrscBeuumq83Ii9O3k/nUbr/rmADgjOw9OQxutgLoXiLbS9GdVopZ0hGgYOKKJVXC5G74CzvNV2x6zYvgxXDMMiewz+btRHLPWX+4gtm8c66UrXN/bsYSn5LgeZuqcP8E5YUbbxu83qXHriL4l9vIseJFu/8FfcNd8orhdBklTtMqmwJY7m1k8kE5z0Ro3RXXS9C8W8p0ORXovRwBrK/Oe0wF4slxn1N5sfW90nhL9ehZoXtKPamQZtT4bz7+t7Spa/QIH/FJcF5r2pHwUIbMJVa08JWb1Yfu8eVHky30pKzH5K5C86aabTUGWUIaBFhdnzh6itWAh9f4aFg1WVTnDdfGD2DgjVXoOaIfXZE5YV8zhibzOR/IA/0RvyHPYV3IGETU/q3tJuHYRgUbrgG73A/hA1LsnlM+ZkcwWNktHqAh7VcW6SEdx3X1mUWgvJGEcqOOFBq6A1aP2NNZ+X1IuQvvQjfpFDUebSJ8wbCGOJuCjdcQ8gDCSZvhXqz+kAmlyHnK8PDSl+hQdiwJFOYhs1TMQxkIueYtlgJ73Bpv0/BysvQ5lci5rVOkHnLOedS5kdHzV6X/HELIQ8k8O6PbfnQVwh1CXStNJ636L5Lo75UI/h30ZWqoRMQEsAXfYUGcl9DfWiZt9xasegiQavsUAZ8YgIR1CVWULusT44BACKfbXP/Tcsh8hFeK7XIW3IBge2jENKX/xwznJ4xKSxUt0vg3zics03ZkUwEtImEX1KY4wNtXO7S/XfhN7m14/MfzoAqtQSq1BIE94q3+lyo4reqwGfc+goNMmca5oVXuB/kUuoJC3BTZ2Nrn1BxOgd1xja1qkdurJctJnmY8XmgvMZtGc/5/l9Ax0B9R4G4d7sZ3hTwpTTZ5VDdKkFQ97j779lLSqvVQ5lSbLoXGJ0eeT9fhG9iCMIfsr2/MFJ5MR8BbSL5D8zNOHrGGj0bCtdfQ8yrHXmdr3hbCiKfbgV9pRa5C84ioHUkwoY1NDumZOdt6MtFuLVzLNea9DIUpd+AJrscYQ81RMX5fPg3qyO4BrderUPlRedZ3JUC82o4ouJ8HrS5FbbDsQTIEXzDCnRlash8vUzPUUsc7aUYPQOVRbUKY1k39n5UsecOQgclml6XnRCX58HS2m8aY6HSaTHnjJ6BYm8alFcKobxSiND32vNuW2st42yKt5lrDgtWX4YqtRgAULLzlsNsguq0UvOFw8ZmyJbllQ+qNIXDpED2UF4vgvJSgbgF7R58k//Y2/jrK/i5SuvVOqhulyBv8Xn72QstKLejGdcWVKLiQh4Ue+24zt1brDUZZag8m4fSA/esj7asSVnlKDtobp0sWH3ZYZkHvq7S2XNO2r4+dh4mXIobvVqaq7GgGEkAZWLL/rCuc+XlAij2pZlZY7Q5FQYhNqfCLGzA0qtEdZu733IBCfbK/sk0y66ptLhfGY1esDuV8kohtHmVUKcpwGh0Djc1fNArtdCrtHbXIoelNTg2KVwyp/puqeA5YmqbXgo1Ow5UZtv10ZGXhTGrq7Mxu6/kNi6CC2PPuPIN2JpzRtheLNYNufsuPZQOTXqZKWZfCGJDm8Qmk1NeKeS0PrGzWavuKKw8mky/s8VEVxy4Ky3GE/ZvrUonlS1UpZagYPVlu4K5il1KTqJ3nIbtQqtjUHE2l1cYnV0c3D+Wey6nc0/wsHdNuFxTc+adQfG2FN4JM9kx1MorhVDfKrHaP9hCXAjJfWzlP3I3tpIT2/No0Vcaji07ngVtXqXNPVOZWK8w1v3tMEfN1UJTaGLuj+fMPtMWKjlz7kgJzbCN9OeMtqASin1pKFx71SxJoFhKLa3RNhY6XakaWZ8eR9Znx+1eb0cJPMtPZFv3w4PiLTd5rXWMnkHltUKzRJO2qDiTa2Yxt3s+nR6VVwsdrh2KvXdEe//VGsu4I5djyw1u5cUCVF4sMFkCPYWtmCp7KPbcgXddfwR2iJak5an4Nxd6jU7y+sDH8q9TqM0SzOUtOg/fpDCbZQfYNZxtxUTrFGpTPI89jIoDPmXc2K7aRri0oXyERCOa/Er4JfrwOrZoyw34NgiBT0yQzc/LjmSKTtoGSMuonb/McZwM+9zsBbtgpcGNiu26XnY0EzJ/6yWpZOctwRb40kMZCO5dz+y9smNZ0OSUI/yRxmbvW8bkKVNLTG01OeWmPAWRz7cVNAYAKP4tFWCkbZQZnV6Ue6IRTvsuxwFSahZbxVHJbGf5L/07HaEDEq3eBwB1mv37Sq/SmRRbtrxNuMID2OMyorxZBJ+4YF7NLF10Gb3B68a3fgiCe1tbaY04EmoZnR6Znx4zS6BjhqP7lUf4hD2rQsXZXMj8va08u8ywsXZqi5QoPXAXvgkhDvsGDNfH0lpqwo5WSEiejbwfzyF0WEPrWHqL16o0BRT3lDxcz3nF/jSEDkiEvkKDigv5CGwbCXngvbXbzlcpWH4JERNbILBdlMNzawuVyJ570v73uVcpRa/WI+rZNtAWVKL073QE902AT2SA1fHO8uXQFatQuP4avEJ9EfdedwCOFWY20QOwbTCzq4zSpEsPqbC3GS5hJUyz5cZq81wsBQWX4kZx4C4qz+bCS6JXlRBKdt1C3SdauK0/vti1XNqYQuq7pVDdUSC4V7z9tUEgXMpvY1I8XaESujI15EE+kMlkpnsx2oGl3zL3S8XZXFSczUPEE80ljlo8XHtfANBkVxi8wQL57TvNsLE2G6sOMSodsr+007+D55EQt/nKi/nwb1VX0Pwo/ycTxb+lwivCH3HTu/JuZ7P/ywWmPat3dKDd48RY7I3UHsu4k+to24U197TFSt5xdZWXC1Cy67Zp08Bo9YJjWwrXGy0IwoUr5bUiVFzIQ+GGawbNk4K/8CBGmJPJgIoL5jEV+gotlJcKBCfyYrR6u1nj2ahSS6yS+TB6xhSDLBQpApbRVVdXpkbW5yeQ/u4hhzE5jkqpOcrKyjAMcheeR/r/DttVQvCNmUl/95BVtluuZDqZ91xrAUOt5dLDGWbjsPYasZ5LRtdGI5rsCquyUpboilUoP5mNgjVXDB4mOj2Kt95E+T9ZnOWWlJcKwOgZFG27aRLEAXOhQJvNT/upySrn7fFhDzEeLoxGh7wlF1B6KIPT9M2o9Sj587ZNDTIfxZWt+HbljSJUnMu18pwps/gtTcdftb7n9WodlCnF0NpzDwXAqLTInnMS2XNOovRQBvJ+vmBaNzV5FWa/n3UHrLnGWqfzf76I3G8dtGNh6aKrvFyAynN5vLI9M3oG+SsvW3ny6ErU9gVx2F5vNXkVKP83l3MttpcUSVusROH6ayhYfslwj/KMV1anlyJ7zkmUH882uRjao2TnLWR+/A9noiKpKHbdthp/ye+pZhtDPcviyxWXbkx8WLDmCop/vYmC9fziRAvXXkXx76ko3HjNoLA4nIGKs7lgGAbKlGIoDtxF3sJz3CcCoLtXLz1/2SWUH89G/uLzVt8DsK3k0SnUyP7qlGOPCnv9ssoolR4SFh4mZl8gpTSarlSN9HcPmcKZzMai1Ztb/lnwTa7GdU8odt2GJrvCLFaWj1EiX0opKaMHQKkaxdtToLxehJI/+cVm24PRM9BXalH8RyqvraSuWIXsL09Br9RCV64xrGl2aq8bvaTYQlXuD2dR8nuqYA+o9HcPIfOTf2x6GdqaA/bI+vQ4Sn5LNXvWCREUC9dfg/JqIRQ8BTGxnrJsxOTgKD+ZjcyZx6C9t5ZocitM3i/G9cUuHDKwvTAybX4lys/kGPbZesbUd8W/ueZZ1DkoWH0FGe8dFuRhVXHvvpZafrdk122TIA5AcOw8X2qFZVyv0oqIowQK1op3IVLeKEL+Ev7Z9Yw/tk98ELxCfR2W13JExfk80TW6C9fcbycow6CegV6jh8xbBn25BvIg7hgchoHgWHhbaDLKkPEBd4I7IxVnc+HfrI7ZQMTMDcBQj7bu060Q0Kqu8Mb3FreSXbdNQr3GgYBXfjwbdUY3FdyNJqPM5IJTsO4qIp9qZfpMX6FB2dFMs3JbXOT9eA7+Ar4vw5pHRb8YNuvGLJg2j+chBDBKLa+yUkbhoPJCPgLa37dQ8clGWnY4w0oJUHH6/gNaqoDNB6NFTgzlp3KgulEM1Y1ieNuwoFlS+tddaHMqEDqsIQrXXUXIgPpQ3Sx2GKJjxPhw0inUUKYUI7BtpN21T0iCtPxlFzlDIdj5I0p2GOZE+T9ZCOmXwN32QDoqzuUhbGhDK28inUItOC5QX6Y2d8F3sLypbhYjf8kFqFJKoLxcgNDBDe4341CA6IqsN9rGzWfYiEY222R/fRoBrSLg39win8mm6wgdWN9sDXSsSLi/K+NT3siEVo/Se2672V+cQtTL7eHXIBSAIQRD7u8tOCzAEJ/Hz2W07GgmvKPu3wdsITNjxmFe5zAq8cw8OziGbLSisT27glJKeLs/G9HmVYLR6U0WP12JGqo0BacCBACKfr0BbV4lyvIqET6y8f3rLYCyY5kmTwK+ZH1+AnUntoB/0zrcB7PQlqhQtPEadGUaQXYFrmS4jijekYqwh5Mgk8nM42UlGmqLttxAYNcYh8cYw6L0Si0U+9IQ2CEaqlslgtbKol+uQ3mtyKS0r7xYgNg3O/Nqm7f4PIJ7xSOgtSF2vWDlZcHJt7T5lSg9kA59pQbKy47XTYZhbIYFlf2dbhU/zoW+XIvCDdcQ+Uwb3r8Vo9FbHVt2NBMh/e/nz3CYQ8cOfHNTFKy6jJjXO8En9p6no4htsPJqIQJaGvZhKgeeY7YoXH8N0S+3l5QwjmEYXln+jaGgRRuvG645A0Q83lxQ4js2OV9zewAYUfMok8iFJrdCUqWeMh7JJo3UeGG8ePctKE6L+1HElKOovJAPRsdAsec27zZsK7RYQdpZ7Y04skZZkvHBEcELir5c47xs5UJOY3GsPUsdXwpWXka92X2gK1bZrWFsdyganSCtXeWle6469yyd2mIl1HcdZyjPnX/W9LfyUgH0ah3kvl6GOH2RCh9La4xQxMRPS8kuDlgLgVyCmln9XQ+h2H0HMrkMgR0db+ZsoRNR3q7yUoFJa89WzPEld8FZ6IpVon5f9R0Fcr7/F3VGNYFvfYO7M5+cBLaqKZTsvIWgHrEo3sGtsNEVqURvDCxRXisys+xxxVezPTQYhgEYIOM9foKhEW1+Jbzr3hcy7QnS2twKlOZWWLmSV5zOgSqlGD7x/NzyxcYvWcbG5i+9iJjXOiFvyQXoCpSIfKY1vML9BJ1TebVQkFsg+5kmtFxU3s/migdtsRLyQB9RV0OoIG7EsjQn21rjsN2V+4JV+ruHAAC+9xQhfMiae1KUdYmp1CJ/yUUE96mH4B5xyF3E73lT9Mt1Tu8lZ1N2KANlhzIQ/3Evs5AgPspITnhMEm2REqX776L8RLapsgMfKi/kI+f7f62s/trcCqT/7wiCOBQBgGEdUqWUoM64ZvBvGSEqCzZgyJnj39JBiMs9SnbcsnL1NiHC4qu8VgTFgbuQefFz9LW7f5GYsFOI8kSbX3lfGBdB4bprqDu5FfwbhyNvAT/vGiNiSj1a3v/KK4XCS+je+2mlPG/dXdaQj7LTEXyMRkZkjMcqpPNjwYIF+OKLL5CVlYXWrVtj3rx56NuXO5ZboVAgLCwMl1/fiRA/8ZOecB3yYB/RNbHF4tsgFJqcct5umHwI6h4r+KEd/mhjUfVDwx9tjOCe8ai8VOCw7jxhnzpjmtqtN10ViZjYwmlKNlcRMqA+SvcbBCOvuv6Ssp8H96lnf7NWg5H5eTl0T7dH/MxeyPzwKPeBEoma2h7KSwUmC7cz8Y4JRMRjzcyUh1UdeZA3Qh9saLd0lMvxkjnFu6ymk/B5XzAaHTI+4L5Hwkc1cZikVQx+jcI4c7p4RwYYwjdq+c8ZO72rwxwKjvCODuBfktAGcf/rjqxPxXtXCCF8dBPIZDIEtI9E/vJLwpPh3iNsRCNeIVGWxL3fXZInidh+PUX0Kx1EPVvEPpONlKrK0WreQygpKUFoqGMFaJUWxjds2ICnnnoKCxYsQO/evbFw4UL8/PPPuHz5MhITHbtvkjBO1FQin21jnRiLIAiCIAgz/JvXQUCbSMlWLoIgCCHUGGG8e/fu6NSpE3788UfTey1btsSoUaMwe/Zsh21JGCcIgiAIgiAIgiDciRBhvMpmU1er1Th9+jSGDh1q9v7QoUNx9Ki1u5FKpYJCoTD7RxAEQRAEQRAEQRBVkSorjOfn50On0yEmxjwBRUxMDLKzreNzZ8+ejbCwMNO/+vXru2uoBEEQBEEQBEEQBCGIKp9NXWaR4ZBhGKv3AGDGjBl48803Ta8VCgXq16+Peh/34nQPIAiCIAiCIAiCIAipKBQKYB6/Y6usMB4ZGQkvLy8rK3hubq6VtRwA/Pz84Od3vzSKMRSe3NUJgiAIgiAIgiAId2CUP/mkZquywrivry86d+6MPXv2YPTo0ab39+zZg0cffZSzfUGBoV4uuasTBEEQBEEQBEEQ7qSgoABhYWEOj6mywjgAvPnmm3jqqafQpUsX9OzZE4sWLUJaWhpeeuklzrYREREAgLS0NM6LUJPo2rUrTp4UV6extmEMZbh79y6FMgiA5hh/aI4Jh+YXf2h+iYPmGH9ojgmH5hd/aH6Jg+YYfzw1x0pKSpCYmGiSRx1RpYXxxx9/HAUFBZg5cyaysrLQpk0b/PHHH2jQoAFnW7nckJsuLCysVt3gXl5eter7OoPQ0FC6ZgKgOSYcmmP8ofklHJpfwqA5JhyaY/yh+SUcml/CoDkmHE/NMaM86ogqLYwDwNSpUzF16lRPD6Pa8J///MfTQyBqODTHCFdC84twNTTHCFdC84twNTTHahYyhk9keTVEoVAgLCyMV7F1onZCc4RwNTTHCFdC84twNTTHCFdC84twNZ6aY0L6rbJ1xqXi5+eHjz76yCzDOkGwoTlCuBqaY4QroflFuBqaY4QroflFuBpPzTEh/dZYyzhBEARBEARBEARBVFVqrGWcIAiCIAiCIAiCIKoqJIwTBEEQBEEQBEEQhJshYZwgCIIgCIIgCIIg3AwJ4wRBEARBEARBEAThZkgYJwiCIAiCIAiCIAg34+3pAbgKvV6PzMxMhISEQCaTeXo4BEEQBEEQBEEQRA2HYRiUlpYiPj4ecrlj23eNFcYzMzNRv359Tw+DIAiCIAiCIAiCqGXcvXsXCQkJDo+pscJ4SEgIAMNFCA0N9fBoiKqOVquFVquFv7+/p4dCEARBEARBEEQ1RaFQoH79+iZ51BE1Vhg3uqaHhoaSME5w8vXXX0OhUOCdd95BQECAp4dDEARBEARBEEQ1hk+oNCVwIwgYNFiAwZOCIAiCIAiCIAjC1ZAwThAsGIbx9BAIgiAIgiAIgqgFkDBOECz0er2nh0AQBEEQBEEQRC3AIzHjycnJ+Pjjj83ei4mJQXZ2NgCDdfLjjz/GokWLUFRUhO7du+OHH35A69atPTFcgiAIwkPodDpoNBpPD4Mg3IqPjw+8vLw8PQyCIAjCxXgsgVvr1q2xd+9e02v2Q2fu3Ln4+uuvsXz5cjRr1gyffvophgwZgmvXrvHKSkcQYiE3dYKoGjAMg+zsbBQXF3t6KAThEcLDwxEbG8srARBBEARRPfGYMO7t7Y3Y2Fir9xmGwbx58/D+++9jzJgxAIAVK1YgJiYGa9euxYsvvujuoRK1CBLGCaJqYBTEo6OjERgYSAIJUWtgGAYVFRXIzc0FAMTFxXl4RARBEISr8JgwfuPGDcTHx8PPzw/du3fHrFmz0KhRI9y6dQvZ2dkYOnSo6Vg/Pz/069cPR48etSuMq1QqqFQq02tjdmyCEAIJ4wTheXQ6nUkQr1u3rqeHQxBux1hiMzc3F9HR0eSyThAEUUPxSAK37t27Y+XKldi9ezcWL16M7Oxs9OrVCwUFBaa48ZiYGLM27JhyW8yePRthYWGmf/Xr13fpdyAIgiBcgzFGPDAw0MMjIQjPYZz/lDOBIAii5uIRYfyhhx7C2LFj0bZtWwwePBg7duwAYHBHN2LpksgwjEM3xRkzZqCkpMT0j+pFE2IgyzhBVB3INZ2ozdD8JwiCqPlUidJmQUFBaNu2LW7cuGGKI7e0gufm5lpZy9n4+fkhNDTU7B9BCIWEcYIgajMLFy7EwYMHnXrOv//+Gz/88IPZe//++y927twJADh9+jR27drl1D5dwU8//YSCggIAwOLFi00x3QRBEAQhliohjKtUKly5cgVxcXFISkpCbGws9uzZY/pcrVbj4MGD6NWrlwdHWb04dOgQjh8/7ulhEARBEAKYMmUKRo0aZXrdv39/vP76627pe/Xq1Vi8eDG6dOnitHPeuXMHkyZNsjpnixYtMGPGDBw5cgRPP/00WrZsafrMnd9ZCFFRUXj66aexZs0a7Ny5E9HR0abPkpOT0aFDB88NjiAIgqiWeCSB21tvvYWRI0ciMTERubm5+PTTT6FQKDB58mTIZDK8/vrrmDVrFpo2bYqmTZti1qxZCAwMxMSJEz0x3GpHSUkJ9u3bBwDo0qULJX7hgG0NJ8s4QRC1kRs3bmDOnDnYu3cvgoKCnHJOjUaDiRMnYsGCBejevbvZZwEBAfjuu+/Qv39/fP/992jQoIFT+nQlY8eOxcaNG/HGG2/gwoULnh4OQRAEUQPwiDCenp6OCRMmID8/H1FRUejRoweOHTtmehhPnz4dlZWVmDp1KoqKitC9e3f8+eefVGOcJ+xkLyRcckPCOEEQtZ2mTZs6XcD08fHBkSNH7H7+wAMPVLvkZBs2bPD0EAiCIIgahEfc1NevX4/MzEyo1WpkZGRg8+bNaNWqlelzmUyG5ORkZGVlQalU4uDBg2jTpo0nhlotYSd9IeGSIAjCfej1esyZMwdNmjSBn58fEhMT8dlnn5k+z8jIwOOPP446deqgbt26ePTRR3H79m3e59+1axfCwsKwcuVKAMCFCxcwcOBABAQEoG7dunjhhRdQVlYGANi9ezf8/f1RXFxsdo5p06ahX79+AICCggJMmDABCQkJCAwMRNu2bbFu3Tq7/ZeUlCAgIMAqxnvLli0ICgpCWVkZBg4ciFdeecXs84KCAvj5+eGvv/4CACxYsABNmzaFv78/YmJiMG7cON7fefXq1ejSpQtCQkIQGxuLiRMncsZvO+qvf//+mDZtGqZPn46IiAjExsYiOTnZ6nu/8MILiI6ORmhoKPr374/Tp09b9bNq1So0bNgQYWFheOKJJ1BaWmr6rGHDhpg3b57Z8R06dLDqiyAIgqg9VImYccK5yOX3f1a9Xu/BkVQPyDJOEFUfhmGgVqs98k/IujBjxgzMmTMHH3zwAS5fvoy1a9eako9WVFRgwIABCA4Oxt9//43Dhw8jODgYw4YNg1qt5jz3+vXrMX78eKxcuRJPP/00KioqMGzYMNSpUwcnT57Epk2bsHfvXpMgPHjwYISHh2Pz5s2mc+h0OmzcuBGTJk0CAFRWVqJjx474/fffceHCBTz//PN48skn7eYcCQsLw/Dhw7FmzRqz99euXYtHH30UwcHBeP7557F27VqoVCrT52vWrEF8fDwGDBiAU6dOYdq0aZg5cyauXbuGXbt24YEHHuD1nQFDHplPPvkE586dw9atW3Hr1i1MmTLF7nXj09+KFSsQFBSE48ePY+7cuZg5c6Ypdw3DMBg+fDjy8vKwc+dOnD59Gt27d8fgwYPNlAApKSnYunUrfv/9d/z+++84ePAgPv/8c7vjIgiCIAiPuKkTroUs48IgYZwgqj4ajQazZs3ySN/vvfcefH19OY8rLS3Ft99+i/nz52Py5MkAgMaNG6NPnz4ADIKlXC7Hzz//bFqnly1bhvDwcBw4cABDhw61e+4FCxbgvffew7Zt2zBgwAAABgG3srISK1euNMV5z58/HyNHjsScOXMQExODxx9/HGvXrsVzzz0HANi3bx+Kiorw2GOPAQASEhIwffp0Uz+vvfYadu3ahU2bNlnFeRuZNGmSSRkQGBgIhUKBHTt2mIT+sWPH4tVXX8W2bdswfvx40/ecMmUKZDIZ0tLSEBQUhBEjRiAkJAQNGjRAx44deX1nAHj22WdNfzdq1AjfffcdunXrhrKyMgQHB1udh09/7dq1w0cffQTA4LI/f/587Nu3D0OGDMH+/ftx6dIl5OTkmObBnDlzsHXrVvzyyy+YOnUqAIPye/ny5aaQuqeeegr79u0z84wgCIIgCDYkjNdASBgXD10vgiDEcuXKFahUKgwaNMjm56dPn8bNmzet8p8olUqkpKTYPe/mzZuRk5ODw4cPo1u3bmb9tW/f3izhWu/evaHX63Ht2jXExMRg0qRJ6NmzJzIzMxEfH481a9bg4YcfRp06dQAYBMhvv/0WGzduREZGBtRqNUpKShzmaBk+fDi8vb2xfft2PPHEE9i8eTNCQkJMygQ/Pz88+eSTWLp0KcaPH4+zZ8+arNgAMGTIEDRo0ACNGjXCsGHDMGzYMIwePRqBgYGc3xkwlEVLTk7G2bNnUVhYaPIAS0tLMwt5M8Knv3bt2pm1iYuLM1m9T58+jeLiYvj5+VmdOzU11fR3w4YNza4b+xwEQRAEYQsSxms4JFxyQ9eIIKo+Pj4+eO+99zzWNx8CAgIcfq7X69G5c2crF2/AUDbLHh06dMCZM2ewbNkydO3a1aRwZRjGTPnKxvh+t27d0LhxY6xfvx4vv/wyfv31Vyxbtsx03Lx58zBnzhwsXLgQbdu2RVBQEF588UWHbvO+vr4YN24c1q5diyeeeAJr167F448/Dm/v+1uK559/Hh06dEB6ejqWLl2KQYMGmZK0hoSE4MyZMzhw4AD+/PNPfPjhh0hOTsbJkycRHh7u8DuXl5dj6NChGDp0KFavXo2oqCikpaXhwQcftDtmPv1Z/sYymcwk5Ov1eiQmJuLOnTt2rwnXOQBDCJnl86a6JbAjCIIgnAvFjNdA2JszihnnhtzUCaLqI5PJ4Ovr65F/9gReS5o2bYqAgABTaUlLOnXqhBs3biA6OhpNmjQx+xcWFmb3vI0bN8b+/fuxbds2vPrqq6b3W7VqhbNnz6K8vNz03pEjRyCXy9GsWTPTexMnTsSaNWvw22+/QS6XY/jw4abP9u/fj5EjR2LUqFFo3LgxoqKicPnyZc7vOmnSJOzatQuXLl3C/v37TTHoRtq2bYsuXbpg8eLFWLt2rZlrOQB4e3tj8ODBmDt3Ls6fP4/bt2+bkrs5+s5Xr15Ffn4+Pv/8c/Tt2xctWrTgZX3m6s8RnTp1Qnp6Oq5fv87reHtERUUhKyvL9FqhUODWrVuSzkkQBEFUb0gYr+GQcEkQBOEe/P398c4772D69OlYuXIlUlJScOzYMSxZsgSAQYCNjIzEo48+ikOHDuHWrVs4ePAgXnvtNaSnpzs8d7NmzbB//35s3rwZr7/+uul8/v7+mDx5Mi5evIj9+/fj1VdfxVNPPWVKGmc87syZM/jss88wbtw4+Pv7mz5r3Lgxdu/ejaNHj+Ly5ct44YUXeAm3/fr1M7nBN2zYED169LA65vnnn8fnn38OnU6H0aNHm97//fff8d133+Hs2bO4c+cOVq5cCb1ej+bNm3N+58TERPj6+uL7779Hamoqtm/fjk8++cThWPn2Z4/BgwejV69eGDNmDHbu3Ilbt27h6NGjmD59ut1Ed7YYOHAgVq1ahUOHDuHixYuYPHkyvLy8eLcnCIIgah4kjNdAyNIrDLpeBEE4iw8++AD//e9/8eGHH6Jly5Z4/PHHTcJtYGAg/v77byQmJmLMmDFo2bIlnn32WVRWViI0NJTz3M2bN8dff/2FdevW4b///S8CAwOxe/duFBYWomvXrhg3bhwGDRqE+fPnm7Vr2rQpunbtivPnz1tZsD/88EN07twZDz74IAYMGID4+HiMGjWKcywymQwTJkzAuXPnrM5pZMKECfD29sbEiRPNFADh4eHYsmULBg4ciJYtW+Knn37CunXr0Lp1a87vHBUVheXLl2PTpk1o1aoVPv/8c3z55ZcOxyqkP3vf9Y8//sDAgQPx/PPPo3nz5njiiSdMcfh8mTFjBh544AGMGDECDz/8sMkbgSAIgqi9yJgaKn0oFAqEhYWhpKSE1yanJlFSUoJvvvkGAPDGG284dH+srZSXl0MulyMgIABKpdJUfmb48OHo2rWrh0dHELUbpVKJW7duISkpyUyII6oXd+/eRcOGDXHy5El06tTJ08OpdtB9QBAEUT0RIoeSZbwGwtavUMy4NRqNBl988QXmzJlD14cgCMLJaDQapKWl4Z133kGPHj3sCuIMw0Cn07l5dARBEARRdSBhvIZTQx0fJKFQKEx/6/V6clMnCIJwIkeOHEGDBg1w+vRp/PTTT3aPKy0tRU5OjlkCOoIgCIKoTVBpMxei1Wohl8shl7tX50HCpWMs67DTNSIIgnAe/fv357WulpWVATCEVrFrpRMEQVQXNBoN7/KXBGELsoy7iMrKSnz++edYvXq1R8dBgqY1jsoU0fUiCIIgCIIguPjjjz/w2WefmZUsJAihkDDuIq5duwatVovU1FSPjoOES8eQZZzgQ22dI7X1exMEQRBVm6rwfDpx4gQA4MCBA54dCFGtIWHcRXgyMRglcHMMuakTQjhy5Ai++OIL5Ofne3oobuX8+fOYO3cu7ty547Ex0PpF1GZo/hOEba5du4a5c+fi+vXrnh4KQUiGYsZdRFUR8KrKOKoSbGF8zZo1GD9+vOk1XS/Ckj179gAwuKM9/fTTHh6N+9iyZQsAYN26dXj33Xfd2revry/kcjkyMzMRFRUFX19fh+ElRPVEq9Wa/lYqlR4cSdWCYRio1Wrk5eVBLpfD19fX00MiCJeRmpqKrVu3YuTIkWjatCmvNuvWrQMArF27FsnJyS4cHT9o70hIgYRxF3H37l2P9V0bE7jt3bsXt2/fxuTJkzkTabA39WlpaSgtLTW9ri3XixBObRUW1Gq12/uUy+VISkpCVlYWMjMz3d4/4R6Ki4tNf1NGdWsCAwORmJjo9iSwBOFOVq5cCcBgHKkKgjVBuBsSxl3E2bNnPT0EALVHuDx8+DAA4MKFC3Zr2hqxtLCxN4S15XoRwmFb8WoTnnKV9fX1RWJiIrRaLdWirqHMnz/f9Pcrr7ziwZFUPby8vODt7U0eIUSNprYquQmCDQnjNZzaFnOm0WgEt2E/DEgYJ+xBAqH7kclk8PHxcejtolQqsXHjRrRp04ZTEUdULYylzQDA39/fgyMhCKIqIKZMGMMwpLQiqjXk++QG3C0Q10Y3dSNirjU7pKC2XS+CP7XVMl7VOXLkCFJTU7F9+3ZJ57l27RrWrFljJiASruPatWueHgJB1CjKysqwdu1aXL161dND4Y1lGJSYsdc2oxNR8yBh3EUEBgaa/s7NzfXYOGqbcCnm+7IfBrXtehH88YRl/Ny5c/j1119JEeAAZ7k5rlu3Djdu3MDu3budcj7CMcYETARBOIfdu3fj+vXrWL9+vaeHwhtjaTAjlZWVgs9B+zaiukPCuIto06aN6W93u8/UZss4n+9reQxb0Klt14vgjycE4l9//RXnzp3Dv//+6/a+ayvsHBKENQcPHsSxY8c8PQyCICwoKSnx9BAEY2kZF2PlrgohZLR3JKRAMeMuwsvLy/S3u29S9mJW29x3xFxr9kJOCyphD3c+8C9fvmyWRZxcp+3jbGUneSHYp7i4GPv37wcAdOvWjbJ8E0QVojruXyzjw8XsWWvbPpeoedCT1EWw45Ddvbm7cOGC6e/quDhLQcz3FWMZV6lU2LNnD5VdqkW4817auHGjqUIA4JnNhicS4qjVauzduxcZGRm82zhbIMzKynLq+WoSYhJkElWD8vJy/Pnnn8jLy/P0UAjChDOE8apgGScIKZAw7iLS09NNf7tTGNfpdDhz5ozpNQnj3MfcunVLUHsAOHDgAI4cOYJFixYJGyBRbXHGvaRSqXDw4EHBG2JPCOOeWDv+/vtvHD58GIsXL+bdhqyztQOGYXDkyBHcvn3b00MRRW5uLg4cOACVSuWR/rdt24ajR4/SM4sHly9fdkpo0IULF8yMI4Q1oaGhZq+lejcSRHWEdjEuwFFMsqv5999/UVFRYXcsNR2pQgvf68UWpkpKSnDkyBHBiaTS09Nx4sSJWvcbVVec8Tvt2bMH+/fvxw8//CCoXXV0w0tLS8OpU6cEtcnPzxfcD1sYd1ayzKKiIlHtFAoFjhw5IioJEeGYq1evYs+ePVi+fLmnhyKKn376CQcOHMCff/7pkf6N3nrk3cDNxo0bsW3bNkn5I1QqFTZv3ozNmzeLUsDk5OTg2LFjNV7QtCxpSJZxojZCMeMu4ObNm2av3SmMW1rcSNATBt/r5efnZ/p71apVyM/PR0ZGBsaPH8+7r59//hkAEBwcjFatWgkbqAfR6/U4e/Ys6tevj6ioKE8PhzeZmZnIz89Hu3bteB2vUCjMyi85415ie8wIoToK40uXLgUAREREoFGjRrzaCK0vC5gL42VlZYiOjhZ8DkvECizLly9HYWEh7t69iyeeeELyOKoy7n62FBYWurU/Z2O8h0+fPo2RI0e6vX9P7gWKiopw8+ZNdOzYEd7eVXvbyV5rKysrER4eLuo8bI87rVZrtmfgw48//gjA8Lv17NlT1BiqA5bzsrpaxmmvTUiBLOMuwFIgdqcwzk4cB9S+BcJdlnH2g9Vozbt8+bKoPnNyckS1M1JZWYmzZ886rcQTF+fOncP27dsFW3c9zaJFi7Blyxbebq6LFi3Cjh07TK/F3Ev5+fm4dOmS5PtQyLwuLi7G+fPnJW9QnKVoESJEidmou8JNXew6Yvyu1a3O79mzZ1FeXu7poTjEEzkMahKe3Av8+OOP2LFjBw4ePMi7TUpKilnuHXfhLMWns8qL1fS8NM7wJK0Kwjjhem7evCnaoFHVIWHcBVgKxEIWivLycly5ckX04mK5YakOwnhKSgp27drllLGKiRkX2t7ZSH34b9q0CVu3bsXWrVudMyAOhCTXqorwdWV2Rgbz+fPnY9OmTbh+/bqk8wgRRH744Qds2bIFJ0+elNSn5TrmDtiKKb5rIFuAd5biszqsm85i586d2Lp1K9asWSOonbuvEfu3tSyHVN1gh5K5C0961xh/r5SUFF7Hl5eXY9WqVViyZIlHq9GIRayHYmFhIW7cuCGqbXXFGcK4uwwRjqiO3mvViZKSEqxevdrkUVrTIGHcBdStW9fstZCb9Oeff8aGDRuwevVqUQ/skJAQs9fVYSFftWoVjh07Jkhrbg+p35dve3aSPKlIXcRTU1MBuM8a56mEWXl5eU6xEki53mLn14kTJ0T3CQgTxo0u1pabOqGwhXF3bTTYv29FRQVu3rzJ2bevr6/pb2dZT6vDuuksLl68CKDqW+DYm/SqsPmWgidKFVaFOc1XwcbOueDu8AT2eiN2nll6jfFdP7/77jusWbPGzMW9pmM5L8WECP3+++/OGo5oqsL9VZMpLS31SL96vR43b97EpUuXoFAoXNYPCeMuwHLhFbKRNSYOunXrFn766SfBfVtuRquTtu7IkSOSz+EuYdyZVKffCPCMuyjDMPjhhx+waNEiSUl1AGkubUIEXPamIiUlRdJCLuaap6SkIDc3F3q9HmlpaYKTCLGVLp5wA1yyZAlWr16NY8eO8W4TEhICvV6PO3fuSLKe0sbKNux56O5rxO6vKtSCz87OFn1PeyKjelV4zvBdR9i5I77//ntXDccm7DE6SwAQeu3T0tJMf9e2tUjMPBWT+NPZ1Lbfyd2w9yPuXMtOnjyJ1atXY9OmTU4LPbEFCeMuwHKiiL1JnaGFqU4LhDOyvFZHN/XqFu/kDMu4SqUSFCvPvqdWr14tqW8pdaSFuJtv2rTJ7LXYDN2AeAXIggULcPjwYSxdulRwFmq2ZdwTc9SodOEqDcQWzBiGweHDh7Fs2TIsWbJEdN/nzp1zW/4JT1Ndxsn2gPC0YHnlyhX89NNP+Prrr3m3SUhIMP3tiWz7nr5mQsbgyfwA7DFu2bLFKecUun5armk1GcvvJ2aeNm/e3FnDEU1VuL9qMp5SBLP3H670HiNh3AVYCpXunDhi+s7Pz68SAmGbNm0kn0PItbaVuZlv+8TERN79sNHpdFZa3Oq2iDtDGJ8/fz5+/PFHMwuAI9jXyDhfxWrDpcRCCynVZSm4l5WVibboSVlD9u/fD0C4EsLTlnG+sEtFMQyDv/76C4Ah/lzsvXXixAns3LlT0riqyya6KliZ+cAO//LkmpmamooNGzYIbsfeTFb3vBti4fu7Wd477lx/XDG3hJ6TvY+rTvsDjUYjOKzAGcJ4VbhGlGDStXjKMu6u35WEcRdgma3ZnRPH0jWTa0N44cIFzJ8/36XuF45gWwgYhkF5ebkkC7nQDbClUM23fWhoqKB+jGzcuBHz58/H+fPnTe9VhQeJEJxRmsbo/sc3A73lA37dunWYP3++Kd5VCJ4SPjZt2iRageCJOPeq5hbMB7EbO1vXSGoCvOp2XwvF2coGLoGL3Z8nFR1i1hzAfMxVvbyXqxD7u7mzNnpVEMbZx1dlRaglCxcuxHfffSco47XYNTsoKMj0d03NsE3ch21E8WQCT1c9e0gYdwGetIwLdZH/559/ABhiYXU6nVvd5zQaDebMmWN6XVZWhi+++EKQ659er7cS6IXQp08fs9d824v9TY11q48ePWp6rzo9bAHnbiT5PHhPnDhhqrlq5ObNmwAgKJ7YiDs3ds7CE4Ide45XlzlqOU6+96krrm91sYyLxdlJyLjmGPs3kvp7SclmLrZvdrvqotxyBuyNs1jlmDuvl5ScP3zPyUVJSYnp7+qy9gL3Y7cvXbrEu43YOuNsS2lYWBjv/pyJJ8JNagJqtVrwPox9D7lTGHdXHi4Sxp1MWVmZmdUT8OymjKtvdgzE2rVrMWfOHLMHAV/0er3gG8Synzt37gAQtsCtXr3aTKAXGjNuuYi7Whi31b66WdCcKYzzuY5//PGH5H7Y+Req40bY04KdlA2hO8e+dOlSs9d87y1XbHg9/Zu5GmMVB2fhLsv4oUOHMHfuXEEhJ2zErtfszNzVUSEoBr1ejy+//NL0Wuzv5kk3dWck2xM6Z4xKe6DqC+NSBSNneDNJza+kVqsFzU29Xo/y8nKzvWd1QspvVl5eLqlvnU6HWbNmYfbs2bx/a61WiwULFphekzBOcGJrg8J3MZVS2kun09kUMoRMHGMN0O3btwvuf926dfjqq68E3ajOEOosr7eQBVUmk1nFP7tLGGdT1R+2ljizrrO7kmSxy75Vx41wdbaMC70nnQnf6+aMsoqW8PneOp2uWggoRti/j7P7F2IZl7L+7tu3D4D4ckiWc4rPdSguLjYLtaluCkGxv7VarXaKZdyd65/ld50zZ45V6KFQpIy/Ku8Pjh49ilmzZllZwoXcn84QxisqKjBr1izefbLJzc3FrFmzsG3bNt5tNm7ciC+++EJUf57m5MmTmDVrFs6dOyd4bn311Vf44osvrJLTCsEoIwgx4FlW0PFkzLiQvoVcXxLGnQw7Q7QxxmHv3r28BABjoiWhaLVafPLJJ/j0008Fx4zbwiiUC+HGjRtQqVSCsk27ol610O9b24RxZyxibGH8008/FTVfhIzH399f9PmNsMcsxdIRFxcneSxiqG7CuFiraWRkpNV7UsrW8L1uziirePbsWUF9azQazJs3T3CWe8CQmX/WrFnYsWMH7/4sYRhG8DrmSWG8KngT6fV6q3F+/fXXnM/3vLw8s9fuVghKeV4pFAp8/vnnopT0znL5dufvbasvIfeorWst5fpXZWHcmDxzy5YtTvtt+Z7H8jix1lLjvLZcvx31y1buVzeMz4xff/0Vs2bNQkFBAe+2xlw/ly5dcrpnlBDcuR6IzQH2999/Y+7cubz7qfHCuLsf2uxNnZ+fn+lvV6bEZyevOHHihNlnYh4C9evXF3S82MQ0rnDjzM7OFtSvWK2X1LF7wm16+/btmDlzpqhMwGwsf2Mp5V/cdX+yx5ybmyv6PFlZWR5xP/Z0n0I3hGzNuVD3P0u4kiWyE/nwOZ8rUKlU2Lp1q9l7XN87IyMDpaWlpvAcIRw8eBA6nc6UZO7gwYP44osveGcy1uv1WLx4sWBFgCsz7LvDMr5r1y5R7QDDnP7+++9x5coVs/fLy8s5E0hZfjd3W8bXrVtn+ttWFRFHnDhxAhqNBmfOnBHcr+W1Eqvsduc+7t9//5XU3tZ35DN+e+F5VVkYN6LT6TBz5kzTa76/c0VFhVUYmpQ9mJh5IqS6ytGjR+0KWHfu3LGy4FY1bFUpEOsVtnnzZmcMiReeXA8s4du3saoLX2p8Ss+7d+8iPDxcVFuNRoPPPvsMAPDII4+gU6dOdo/V6/VW8Yrx8fGmRFNiJw/DMJyum442o2I2LXXq1OF1nE6nwyeffGL2nrOEcb1eL8pynp6ejuzsbMTGxnIea8tN3V0PPilJ5wBD4r1//vkHU6ZM4d3GuJmy3CAJRejvsm/fPly4cAGDBw/Gtm3bBJdtcTT/ua5dXl4eVq5cadLoAkDjxo15jNo+c+bMQb9+/dCzZ09J5xEC3/XD6IIrlStXruDu3bum10KFB39/f9Mcl+KyyKd9gwYN7Gbld9dD21YiQa5xS3HJt1TuGr2q9u3bh8cee4yzfUlJiSgFMXvM+/btQ9++fQWfwx5cc8wZMeNiEj4ChnhvIUmpLLF8rrjLMn737l2sX79edJynQqHA4cOHRff/22+/mb12V2mztLQ0bNy4EQ899BBat24tqK3UKgpiLeP2lB3VQRi3hK9S8PTp01bvSRXGhexPysvLBSlD2WU0bXHgwAGMGjWK17muXLmCHTt2YOzYsUhKSuI9Bimw81YYETu/XOHZag9LA4onhXHKpi4SKRpooyANcMdRZ2VlWWnH2RYdsT8gn/FLEVakYKtWqrOEcT7jtndD/vrrr7zHIFYYd+Z1FXOu3bt3Q6FQYPfu3aL6tPUQdIRer8fKlSttWsG5xn/o0CEUFxfjl19+sdqEunpR/e2338wEcUCcEMQugadUKkVfd7HwvU6HDh1ySn+W3hNCH9hiQgvS09NtbuK4vjuXUs8dHDhwQFLfQsfZsmVLm+/zXUukhJZYotfrsXz5civPAKG4M5u6UCyTslrCdd2dIYzn5ubi22+/NVVA4UKj0WDJkiVWgriQ9c/WvJaCRqPhVWPd8noJ/b3XrFmDsrIySbGtlvC1etoaa3WIGf/ll1+watUqp+xtGjRoILqtFGFc6NilKl6ksGHDBpSVlWHVqlWC2qWkpODbb7+VnMfAiNjfW4hHARsx4biW8fzVwTIulBovjEvRQEu96OyHntgJzycOxtE4XTlpnZlR3BI+47anqOC6Zux+LYXxy5cv8+rb1tiDg4M52zkbdtZVIVhaLLjIy8tDamoqzp8/b/XdpcRgu9oynpaWZvUeXwUdu18/Pz/B7p1i0Ov1Nh/Oly9flhQ7LRW+G8KzZ8/ip59+Mruvdu3axSsme+3atTbf5/qNq4IwLmZjyLZML1iwQNDv68gbig9ik5fZ+k4ZGRm4ffs275hLe3AJmey+b9y4IakvIydOnMCiRYs4LcdC4tn5tE9JScHixYsFVQ75+++/UVRUxFsRyDYmsBHy3LYUnDdt2iRI2W0Ltsu8PSxzzwi9j10hwPK97s6OGXdH+Sy9Xo+LFy8iJSXFKc8ZvspYWwJdWloar9/bGUoPZycMFYPQMa9atQpFRUVYvnw5li1bJsjg6ExFka38Lnxgh4Hw9c5yRblBsdRaYXzBggVISkqCv78/OnfuLNjy46nMyfXq1XOKWx0fYVyqhdmS8+fPY+PGjdi5c6fgts7KNMg17gsXLmDx4sWCz8tGJpPZXIz5JKaw9T3Fuu24w93HmYqTX375xewzKRsfTyyqQuYHu01AQICrhmTi7t27dq2WQrK9Ohu+12zr1q3Izs622sTv2bOHs629TaeUubt48WLcunVLdHspcI2bvbnPz88X7dHz888/8+7T2ajVarN7WEo+Bi7rMzs56tGjR0X3w+aPP/5AZmYm/v77b4fHcbmoc61jxvuHvaZkZGQI+h4XL17kfSzgnOcK+5oDhutw7tw5XgrYrKwsm+/z2dPs3bvX7LXQ5wRbQElOTkZycjIWLFggKu7diKNx6/V6bNiwAXv37hUVy5yfn293jXRHGSdnVSowwlfItTdH+Vh9nREzzs7r5Azcvf7euXNHUk13QPweLCQkhPexKpUKy5cvt8pptXr1alF9kzDuZjZs2IDXX38d77//Pv7991/07dsXDz30kE1rlz1+//13zgetJceOHcPSpUsluTg1bNjQKdlfXS2M23Mrv3z5Mo4fP+5w3PZu7G3btvFKXsCOSbV1Hkds3rzZKkOtESE1J209DMRa5cW67aSkpPCyHN6+fRsrV660u8lxhK3xWm54HOEqDTLXtS4qKkJFRYVT+7x79y6vbKjsuZGamur0B7ctHIV5lJWVYe/evaKtmnyxJVDxEcZd9ZCS4qauVCqxYsUKUf1KFWaEbswyMjKskhnZg30/ssOj3L0ZtIyhXL9+vcPj09LSsHLlSuTm5gq27lvef/Pnz0dycrJTXO65nrNCE7SxUalUpnvW19fX7LNDhw45fA4ChuR8YqzR9uYvXwOF0H2TJRs3brT5vlqtRlFRkaBzLV26FDNnzsS5c+ccHnf9+nWr3D1GcnNzRWWEN+LoN7579y6uXLmCw4cP27Qsc61hjn5fvvf07du3zeYS39KKxko8Rpyxjv/222+c9wxgf47yCQlwhmAZFhZm9lqq6zfX/AQM3mNr1qwRdf4LFy5YvSfE4GhrDgupgMQWwIUouY8fP47bt2+LStZ37tw5q/2r2Dl6/PhxfPvtt1i2bBlvq7ylR+SqVaucvicFqrgw/vXXX+O5557D888/j5YtW2LevHmoX78+fvzxR0Hn+euvv7Bu3Tpei4NWq8WuXbsECfy2UKvVZpNc7CZp69atnG2FCsxsuNyJHD2AbH22YcMG/Pvvv7we5I4ejFIfCHxLT9h6GPC50Wwl/RArjAPclsNz585h+fLlSE1NFSVc2BLGDx8+zGmNMiJ2/paUlDj8nEvI4xI8xY5r/fr1nHPEUgFhuZF2heDj6JxFRUU4fPgwTp06JagcCRt7rqtsFixYYPXeli1bOH8rdjZdWziyAl67ds3ud5fips4He+2lhiU4WsPsuYKeOHECpaWl+OuvvxyuCfY2se4Wxk+dOoVly5aZXnMlblq6dClSU1OxYMECm8mEHGG5hhmv4apVq5waA28Jn32Do3uDHZdqy6K8ZMkSh+fev3+/1SY/OTmZMxGnI/dVPjlDHCnU+cwzRwK3GOWCXq/nbLd27VpJezdHShlH15N9PWxVK+FTWUEqlpURfvjhB87Qj7Nnz9rM9H/48GH8/vvvktYTtseOPeytkeySjULaCtk3Xrhwweq3ElNmUihbt24VHWZjK4P5hQsXsGnTJskhrfZgGAY7d+40VfAwEhgYyPscQtd6djtb97yY75GTk4OdO3eiqKgId+7csau0Y/exdetWK2VHUVER5s6d6/TwOBnjiZo5PFCr1QgMDMSmTZswevRo0/uvvfYazp49a5WOX6VSmT3oFAoF6tevj3fffddMo96wYUOH/TrSjDlqW1paarZBHjt2LLZv3276ISMiIjhL9Njr29/f32F2cJVKZddaWqdOHSvtH5u7d+9ybrLtfW8uLaKUa12/fn2Hwi0fDaa9/vPy8lBeXo6AgAC88cYbmDVrFu+2gOFmtCVkyuVys0RfthA7v/hqbO2dQ6fT2bXAcP1OgOF+dKRJtHcOrVbLuZmV+r2ltBfStlGjRmYhDDKZzGGiGjF9K5VKXuX5oqKibFoWpV4vrnPYa5ufn4+ysjLRfUv5nXJycjjjKh21tzd2rt+Xja3x16tXz65A7+j7RkdHm7wT7P3OCoXCruDL53621z9XW1ffz2J+Jz5t+fQvdm4Chnwh9mIoXbmGOWpXXl5u13uMqy1Xv4mJiZyeI85ce53Rzhnt7bWtrKy0culnY+8+ltovn3MI/b4xMTGm7+Ll5eWw1K3UcZeUlNhV2oiZnwkJCbyTCDvreglpb+8cfH5fPv2LXb8dtSsoKLBKggsYlNX16tVz2J+RO3fu2BVexVxvrvuJ77mk/NaO5DJjW5VKhc8//xwlJSWc8l+VFcYzMzNRr149HDlyBL169TK9P2vWLKxYscIqcVVycjI+/vhjq/NYCuPuYtq0aTh+/DiOHz/u9r4Bw6LER6Nfm4mPj8fzzz/PadEjiG7dukGn0wnOQk8QBGEkNDQUpaWlbvdgIIiqTvv27Xm5ebPx9fVFaGioR5ObEoQ9hAjjVb7OuKWrqL262zNmzMCbb75pem20jPfo0QMJCQnIzc1FXFwcL61ZdnY2/Pz8IJPJcOvWLWRkZGDYsGGcbQsKCqBUKtGgQQNERERgyJAh8PHxgU6n461B0mq1CAkJQWpqKgICAsAwDK+63yqVCmlpacjJyUG3bt3Qtm1bpKSk8Mq0qNPpUFlZCZ1Oh4iICGRlZSE1NRUxMTGc9Q/Pnz+P69evw9fXF4MHD8aFCxeQl5eHDh06ICEhwWFbhmFMNcHVajVKSkqQl5eHpKQkThcYrVaLgoICMAyDhg0b4sSJE2jTpg1u3ryJgIAAxMTEWLkVW9KgQQPI5XK88MILOHPmDCIjI5GSkoJ27dpxxkgXFhaibt26CA0NRUlJCe/6ljqdDrm5uSgtLUV4eDjq1auHjIwMBAYGOszGbvR+yM3NRZcuXaBQKHDz5k3cuXMH8fHxSEpKQnR0tMMxqNVqVFZW4vbt24iJiUFZWRnq16/PW1mlUChw/fp1BAUFISYmBl5eXsjMzESLFi0cXi+FQoGcnBycP38ecrkc8fHxqFOnDoKDgxEfH8/Zb05ODpKSklCvXj2cO3cOCoXCNGcbN27ssG+dToc7d+6guLgYQ4YMAWDIh1BZWYm4uDjO715UVAQ/Pz906NABDMOgQYMGOHLkCBo3bsw59vLycqSlpaFTp044cOAA8vLyUKdOHQQFBaFNmzZ21xOlUgm9Xo8rV64gMjIS8fHxOHPmDDp27Ig7d+4gICDA7r2lVqtx9epVNGnSBBEREdDr9VCr1cjPz4dSqURMTAyn+7VWq8WpU6fg4+ODYcOG4dKlSygsLESLFi0ctktPT0dqaipatGiBoqIiNGnSBN7e3sjMzERKSgo6d+5sNwmeSqVCfn4+AgMD0bJlSxQWFiIlJcU0X7juRy8vL+j1epSWliI7OxsdO3aEQqFARkYG4uLiOENIiouLoVQq0aNHD2RlZSEgIIB3KSMjarUaKSkpCAoKQt26dR1q7vV6PTIyMlBcXIxr166hQ4cOiI6OBsMwCAsLQ3FxMefaX1JSgsLCQoSEhCAkJASlpaW8M9xqNBqcPXsWLVu2RFFREWJjY3m75Wu1WpSVleHq1auIjY1FcHAwlEolrl69iv79+zt8Tup0Oty+fRt+fn5ISEhAQEAA5HI50tLSEBwczGstOnHiBEJCQqDX66FUKhEZGYm4uDjO9R6A6X4oLCyEXq8HwzDw8fFx6Hmm1+uRlZWF4OBgVFZWol69etBoNDh58iTu3r1r2mM4Ii8vDxqNBgMGDEB+fj6ys7Oxbds2yGQyjBo1yuH8NM5p4/MqPT0dWVlZ6NKlC+dv5uXlBT8/P1y8eBH+/v5QKpXw8vJCZGQkp2VJqVTi/PnzJqtYWFgYKisr0bp1a0RERDhsa8R4T0dERCAnJwcXLlwwPa+47mmGYeDv7w+1Wo2srCxoNBpERUU5DK3TaDTIzc1FTEwMLl++bOq7srISGRkZaN26Nef3vn37NoKCghAREYELFy4gJycHrVu3Rr169RyOubCwEHl5eWjWrBny8vIQGhqKhIQE01zj+q6nT5+GVqvFsGHDTAnhmjdvjkaNGjlsa0Sr1SI7Oxt6vR7+/v7w8fGBr6+vw+/LMAzOnz+PwMBABAQEwMvLC3Fxcf/f3p2HR1WdfwD/zmTfIUIIkVWQTXZQjKKiIi51QVu1iihqW61La/254QZqW9dardpal9aKteIGUreKspMESEggC9n3PZkkM0kmmfX8/hhnMsuduefcO8kE8n54eJ5k5p65NzNn7r3nnPe8B729vTCZTLKfs/MeTqvVIiUlxfVze3s7Zs2axTV1T6/XQ6PRID09Haeddhry8/MxY8YMrjw1qampiIqKQkVFBcLCwoRy2zivcxaLBatWrUJZWRlSU1MDnr/sdjva2towZswYlJSUYPr06Thy5AhmzZqF//3vf1i5ciVGjRoVcL9msxldXV1ISUmBzWYTmt5osVjQ3t6OlpYWtLW1Ye7cuRg9ejQ6Ozsxfvx4rtcwmUzo6elBQ0MDWltbkZ6eLvud0Ov1CAsLQ3x8vOu4RafKNTc3o7GxEe3t7UhNTUVsbKzs/RvgGFXXarXQ6XSIjIzElClThELknWw2G6qqqhAXFwer1Yq0tDTZ916n0yEmJgZ9fX2u6OPGxkYsXrxY9lpbVVUllKBz2I6Mi4ape9Pr9Rg1ahTq6upkeyQIIYQQQgghhBC1nIPCXV1dAacLA8N4ZDwyMhJLlizB9u3bPRrj27dvx1VXXSVb3tlrE2i+CyGEEEIIIYQQEmw6ne74bYwDwP3334+1a9di6dKlSE9Px1tvvYXa2lrceeedsmWd4TW1tbWyb8KJ5PTTT/fI3kr8c/ZaUfSEGKpj/KiOiaP6xY/qlzJUx/hRHRNH9Ysf1S9lqI7xC1Ud0+v1mDRpEte0nmHdGL/++uuh0+nw9NNPo6mpCXPnzsXXX3/NleHWOXc2KSlpRH3Bw8LCRtTfGwyJiYn0ngmgOiaO6hg/ql/iqH6JoTomjuoYP6pf4qh+iaE6Ji5UdYwnn9SwbowDwF133YW77ror1Idx3Lj77rtDfQjkBEd1jAwmql9ksFEdI4OJ6hcZbFTHTizDNoGbWgaDAUlJSVwp5cnIRHWEDDaqY2QwUf0ig43qGBlMVL/IYAtVHRPZr/zY+XEqKioKGzZsCMka4+T4QHWEDDaqY2QwUf0ig43qGBlMVL/IYAtVHRPZ7wk7Mk4IIYQQQgghhAxXJ+zIOCGEEEIIIYQQMlxRY5wQQgghhBBCCBli1BgnhBBCCCGEEEKGGDXGCSGEEEIIIYSQIUaNcUIIIYQQQgghZIiFh/oABovdbkdjYyMSEhKg0WhCfTiEEEIIIYQQQk5wjDF0d3cjLS0NWm3gse8TtjHe2NiIiRMnhvowCCGEEEIIIYSMMHV1dZgwYULAbU7YxnhCQgIAx5uQmJgY4qMhhBBCCCGEEHKiMxgMmDhxoqs9GsgJ2xh3hqYnJiZSY5wQQgghhJAh1N1dhIjIZERHpQqXZYzBYMhFbOxURESMFi7f21sBjSYcsbGThcuORLW178Jm78fUKXcLl21o+Ah9/XWYdsoDwlODGWPIO3IrRiUtwdSp9wrvu7l5G6Kj0zBq1FLhskOB5/2gBG6EEEIIOSFYLHpYrb2hPgxCgspq7UFfXx0sFsOQ75sxhv7+JuFyRmMVDh66Avv3n61ovx0d+5Cdcy327BVvZFmtvcg6sAqZWReAMZui/YeC2dwBm82oqKzV2o2W1m9QX/9v4bJ2uxll5X9EZeXLMJlahcrqdHtQXPIYamrehKH7qPC+m5u3oqNjLyqrXhEu29GZicKi3yHn8PVDft7POXwDjh1bH5TXosa4IIPhKDo7s4Z8vxZLF5qbt8Fm6xvyfRNCCBlZOjozkZt7M4zG6iHdr91uRUvLl+g3NQuXtVj02LN3MXbvmT8IR0ZIaDDGcODg5cjIXIE9exehoyNDwWvY0NLylaJG9bHi9difsRzNzduEyhkM+cL7crLZjMg7ss71e2fnAe6yjDE0Nn3s8VpDTck9u8XShYzMFTiUfY3w/ux2C3bvWYiCgntQUvok9Po8ofLuDXC7vV+obN6RW10/Wy16obIA0KXPFi4DAHa7Cbm5N7l+t1g6hV/DZGpFc/MXsNstQuVaWr5EV9dBNDZ9DKu1R3i/3kZsY7y7uxAWS5dwuUPZV+Nw7hqYzO3CZc3mdvT2lguXA4Dc3JtRWPQ7ZGReoKj88aq7+xiyc65DT09pqA+FDCK73Qy9Pu+46sE+Xhm6C2C1dods/909xYrOvaFks/X/WD/toT6UIWE0ViM39yZ0dO5HQcFvhnTf9Q2bUFD4W2RlXSxctrjkcdfPjLFgHhYJotq6f+JY8WMoLn4cfX11Q7rvvr569PU1DOk+1WPo7x94n3Lz1nKXtNmMMBiOor7h3ygo/A0ysy4U3ntT0ycAID5yqWIlo7q69z1+Lyz8HXfZ1tavUFb2e9fvSs8FnZ1ZKCnZKNSYZ4yhvOJF7Nm7BIVFv0NJ6VPcZWtr34HN1ove3jLhY7VYPRvB/f31QuUPHrpKeJ+O/TR6/M4wdNfIhsaPPX6vq39P+DUysy5EYdH92LlrllC5gsLfun7u71d/Pjlh54wHotfnIjvnZ4iJmYRlZ3wPi4W/R0SrTQMAtLRkIWXsSu5yjNmQdeBqAMCihZsQHS02f6bX2AmtNg1WK9DfL9ZrdTzLzvkVAOBQ9u1IP3M7dznGGIpLnkB4eAJOnf6w0D4jIiJgs+nR1PQJUlOvRlRUilB5ADCbdWhq+hSpqdcgKmqscHklGGMwm9uh1YYrml8VSlkHLkFfXw00mnBccH5JqA/nhKXT7UHekVsRHT0BZ5+1W7i8zWbC4dw1SEycj5kznhQubzAcxaHsq6HVRuP8FYXC5dWwWDoRHp4IjSZMqJzRWIXMLMe5fsaMDZg44ebBODwfzpC78PA4xa/BGIPF0oHIyJO4y1gseo8bdpO5RcF+bais+gvGjlmJxMR5QmU7OvYBAGw28dGGtrbvXD8bDEeQlLRQqHx7+06UlT+L0+a8hMRE/tF1Je+zO7vdjPr6TUhOPgfx8TMUvYZS1dV/Q2vrN1i8+N8ID5dPNOSuru5fiImZhDFjzucuY7dbPBpKDY3/waKF7yM5WSyU2WA4Cr0+FxMmrIVGwzeuZLOZkJF5HgBg+dkZiIwcy102GOobPkR9/SYsXPAPREePH5J95uT8HN09A+dau90kVL6z86Dr576+GnR0ZCA5+SzZcna7FbU1bwvty53V6/t/0pgV3GXdG0qibLY+HM5dg+Tk5aiufgMAEBYeh+nTHuQq39GxBzU1b7p+b2r6BHNmP8dVtrrmb66fjxU/itmz/sh93Fqv65rowIbV2uVWlr/zoqHhP54PCHZ86HR70dIyEHFhNuu4z6PeI+F1df/EpEm/EMpPEIyoiQMHL8OFF1Soeo0R2RjPzbsFgAZ2+1KUloqNuI5K2gAA0LUDvT1V3OXsdpOrbFVVJSIidNBqo7kvBM6yjvL8+x3YvwVWqwHh4QnQaiOFy6tht1vBYEWYNlq4rNK/2263AOwSWC1ASUk2IiJGCd2E9/X9gM6uV9Dc/AWWLfta6JgBoKDgN+jsykJL61c443Sx0C6liosfdYVmnXHGV0iIF+vpU8tgOAoGhqTEBcJl+/pqAACMWYN9WIPGOUo6lDdzajU3bwXg6DU/cvQOzJn9IiIi+BNcdnTshsGQC4MhV1FjvOrHmxvRMDibzYR23Q9obv4CyaPTMXHiOqHyPT2lOHDwUowadQaWLP6PfAE3zoY4AJSWPiXUGGeMoV23AxpoUd/wb0yb9gDX95IxOw4c/AnM5hace85hhIXFCB2zk/OccNJJ52Phgne4yvT1e45Uio4qMWbHjp2OBmV19es4K303YmICL+vi9Qqun+x2C7TaCIF9D5w/snN+KnyDdOToLwAAeUdux7nnHOIul5e3Dh2d+zBv7l8xduxFwueE3Lx16OpyhOHyHjNjDMeK16Op6ROcnHYDTOY2pI2/FmMFBgkAoKLyJQCOen7Ocr5QYKu1G1lZF7s6akTeZ6Ox0uex3LybhT+rQ9mOwY2IiNFITb2Sq4zFOnDzvm//WRg75iLMn/9mgBLBVVLyBACgrPxZzJv7F4GSyqM83BvirldjNu77ocO5N3j8npu3luuzamz6WHLfvLyPr7FxM1fjVCp6yWDIw0knncu138rKP8NgOAKD4YjrMaOR/97TrCBqVgrv3zvAMwrBJniNVcq30c/AmJ3rHNjTW+YxFQEA9u47AwsXvIeTTjpH0fFYrd0AR2PcZjOiXbfL4zGdbq/i/ao1IhvjNlsvoqKuQXzcT5CSkoLY2Fju7H89PQOj6LGxE7hvFMzmdpjNnpUzLCwaMTEny5a12y0wGt33OxFardhH19tbBsYcN91xcZOFbhYYs8Fs1iE8PEHRTaEjxDwM0FgRFzud+71mzI7e3oG/Oz5+Kvc+rVYj3AMIHO+1/A0hYwxGoxF1dXMRFXU1eno/596nu84uR16B7u6hG/1znyNVX/++4IlcnZaWr1BQ6AhnnT/vTYwdexF3We8wp+OBTrcbeUduAwCcnHYDZs36vUyJAQbDUTQ3f4FTTrkPWm0UensrEB8/SzgDqRKtbiOH7e3fo7LqFaFGtXvIXWvrt0hJuURo/+3t3wtt71Re8Rzq6993vYZoY7yp6VMAQFfXQZktPakNdW5t/cpjlEavP4zzzj0sW66/v9EVltrbWyY0SuvOeU7Q6XbyF/K6mbVYdNxF7XYrDh66wuOx/IJ7cMbpW7nKm8zt0OkGIjYslk7uyKRgzm23WDqEtu/odIzm5xfchYiIZJxx+heIjk7jKtvQ8B9XQ1xEV9cBV/hwQ6Ojg6m9/XvFIzQijYgjR+/wiJhgjHGfvw5l/1T42NwxxtDTOxA91dvLP6DiXrcAoK19u9Cxq1HqFg0gEvVht5tQXvGSon36O3+1tn2HcSmXypZXul9A/b2PBr6fCc9n1dL6lc9jeUdu5f5e1Na9K7Hf4T99LnRTqDzr2JGjv0R09Mk4c9m3CAuLDVjyyJHbJR+vrvkbV6M4NmaK79HYzbLlAKDo2CNo9aoreUfWqR7hVmpENsaBGMREn48xY0bhpJP4w8ocYcADJwKrtRoJCXO5TuRmcyciI723MyI6Wn602G7XwmodKKvV9giFuVus3YiIAJw9Z1ptD/cNjqNxWgWNphc2mx5xcWIhhzZbn8ffHRUVCa2Wr0fWYjF4lY3ivmj29es8ymq1dq73GgBiYmLQ1zcKNtv5MJnER8XVKi55Ek1Nn2P69Icw4eQ1wmG1gJJeVXWcDXEAOJp/p9AJ7ejROxXv12isgq5jH05Ou15RxIfV2o2wsHjhmzFnQxxw3AiLNMadIzodnfsRG3sK2tr+hxmnPiHcwFQiLCwadvtAQhljr9iFx+SWVCu/4G6cd26ecGirEk1NyjrF1Gpp+a+q8h0d+z1+t3rN6/Onrv5fbmXE5vd3dOxHWflzmD3rDx6PWyydXNNXmIpRuPqGTT6No+5uviROjDHs27dM8b6PHP2Vz2N2uwlabZRsWZ1ur88IjVIWSweqqt/wef/9cZ/nLkJteGVvbyU6Oz0TgdlsRtkbaAASnQd2AHzXKffzjxLt7d/jaP7ANaNdtwvTpj0gW85kakFx8aM+j7e0/Jd7ZL2jYz+s1m7hTkjAEULrJJIEuK7+fdTV/UN4fwBQVf2a5OM2zqzTNW5h06K6ujyTctXXf4DRo9MRFzeNq7xdolGl0+2SnRJRW8sXASRCbWPcZG5HVOQYBfvl7yiqqf27x+9S758Uu92KnbtmezymN+RyLwcndb3o729Aa+v/MH781QHL+p9rzXcNCpeI6rNzRld6N8RFDEbW9uMnvjKItNpR0GgjEBWlCUJv0tD3RpnNbbDZ+ENQ+rxGDHizO9ps/ejuLoDNNlDxxEMWPb8Yajqgg5EkgVdUlAYabQS0WrG51x0d+5Ff4LlOIm8dY8yOH3ZMQ0PDv2G396G09Ck0/jiiJ0evz/V5rKb2neMiiZGaULbMrJUoLd2Inbtmo6HhI6GyPT2l2L1nIXbsnI6+Pv5kJyLfvUB6e8vQ1vY/AEBNzVvc5Rhjij5Xq7XbZ45VR+c+xUklAUd4rVIiiZuUzB926urK9hjtEMma2tAoVqeCJcytAZmbd7PQdSo372b09BQhN88znL6ySvrG3JtNRWZY97nAojo69igv25kJo9G3Y6m6mq8xEayGuJOam/e6+vflN4L/60qXPoerfNaBi1BSusHjsfLyF7jKetMb8hSVU6KhcbPH7z09x7iW+yqvkP7b3CPK5OTm3Yz8grvR39+o6toqMm9b5NrkrarqVcnHyyuely2rNsmn0eh5XSkp3YCsA6u4y0tNWTOb22TLaTTKxxjNZumIGJ1uJ/eSclKN07y8WyW25MF33rfZTD6dEKWlG7nKOuq/536Kiv6Pq6xD8O8xeaYFGI1Vkve9PGoCdNjYbIG/mxZL56Cs1jHiGuOO3jqN459GA7OZLwSPMZtkONRgr2vHGENPj29CK9EwOndWK99JRSqjo9VqEGhcMlWhg949gkLLFngdo91ugt3OPx9Zo9H8GCalEbro5ubdjNZWz9H0xh9DCeV0dOz1eczAuTyF1PtcXv4sGr1uXIYbJcsX+VNc8pjQ9vUNm1w/u4/sy1GS6VQOb5IsxuzIzr4GO3fNEb5Z8tdTXt/AtyZpTc3ffR4zqLgJz8hcobisiJzD13v8XlT0ANeoImNMUfiwU0HBbyVv9OUu9oBjFM9d1gH5kFJv3vWDN5xX6mZSNOmTEj0C4cbe3Je3cecM3w7E341fW/sPio9HzftVWvoU13fbX5KqnJzrFO9bJ3EN4qEmUZcIxpjklAue98tfJ2pnZ6bwcezPOAc7dk5H0485OOTo9b5TU3g7bJwdtsHEc/9Y6achzyPQ55Gd/TPZ8iZzO8wSx+ivsexJ+YjP/gz/88r37F0kW76npwTHjvkmDO7pKVJ0PEZjDdd27vPb3fFca5r9RJ3t33+OT3SDCLNF+dx5uU4Xxhgys1aiuvp1n+f6ON6z8vJn/T7n3UHpTfdjglFvapedHnGNcWeCFifehFEWi17yZtaZeCoQNb3k/r7EvKGEZrN0A1Z0TT2nvr5ayZumL774AoWFjhHOL7/8Enl5edyNfsfx2PHSSy8hN3egp0uq0c/TEWC3myWXTlLagbFj53RVn2Fx8aNcDXqpC5jaZSJ4G6iMMdfNCmN21aO/1dV/5dpOKkS9qWmLqn3zcv9M+/pq+QsO0vxCnve811gBQ/dRMGbG7j0L0SsQZu4vT4SufRdXeX8jSzzsdjNKSp9WXN5bSyvf9BGpm7eW1i9RWiYfQnzg4GXCx+XU11eHltYvJZ+rqZWPgmhq9rxB8h5lUkLLmUCzWeL7l3N4jer9y1EToeEPzzzo0rJnJB8/KhH2zot36oahu0Dy8cO58ktXiSZBDBbp65T60bHOLvmEeWY/+Qt47uMC5clRsvY2wD+CmJ1zrc9jTU2fcZX11zApKw+coZs3TNkf7w5BEYHmmusNgUczbTYj9u1bhuZm3/NQReWLsoMqBj+vn51zrWzjVO0UimMS0yDUcE5pk+OdZM+pXSffoejv8+g3Nfp0ZEvxF7lRLlM/1UWW+D/3FRb9zm+DmUeTzOCZxk+z2T3RqxIjqjHe01PqcyHhX+9WecVRE2bkt/Ep8fi6deuwevVqj8f8rTXYKxHSx31MEg35WbNm4cYbb8TevXvx2GOP4dRTpwk1cB5//HHs3r0b8+c7wj/6+5vFGkhuvCMJfvKT2/DII/JhWU5WiTDNDo4vd6C155XOT+HuBFDZQDycuwa7dp+G2tp/uH7mjUSQGlmqqPwTV1mp+aRFxx6ATqcsZFXkBsL9vVU7XcVorFGdsIans6i1xbMRKhL252/EoN+k7EZURE3N31HvNg9arQKvqSD++EsQ08gRfu5vJLmjI0O2vgQa9W9p+SJgWX+jP4WF/ycU3eONN4mbVAezvxtcXjznsSbOKTlBNwhTeXgTpLa1So968s6zD7b+fvmpI5LX5SAkjzp8+Oey20jdewB89StQ7hW1IdlKHCter6p8bW3gaIROwWSVwdQjcy0MlLRVbspWoAZzoPOyXn8YR/PvCPjaaqmJFJOiZnoW4LhOGgxHg3Q0vozGKrS1fev3+UCdXGrmbHd45brwlpd3i9/nlA5Euvg5t5tMzdyRDFJGTGPcau3FgYO+oX6MWdFvapE9mavJ+CwyQszLYulSNVrr76Km1MyZM3HTTTfhwgsvxN/+9jdotfwh5Vu3bsWuXbuwefNmhIU5Lpg8c4N4bdr0Zzz22D2upR6mTJmCV155xe/2Uo1LnrDDQMmH+ObU+TaWmpu3cIUaqeUMxy0r/4Mr4/SxYvlRdWe4ULDlHVE2x6pZJOGW24XbatXjhx3ToNMpC9PMzLoABw9dCZOpVVF5gG8Ur6radzkc3lGdlhbpkdq0NPne70B4zkMdCkJB5fB0pBq6g38jkpu3lju0X4rcfDh/GeebW7aiuWWr4v0C4LoxG4wsE3KdCBaLdGK7ffvTUVf33iAckRsVHZlV1W8gI8M3oZTBwNmYVrhvtblA/I1CM2aTnRsr1eBp1+1AdfWbIcvozNORGTgZo/z7eTzkX3Gn+r4zwN+bLTMVQm70O1AuHH9J5wYOy/+5RC7Hh9RUwKES6Pput5u4c3qI4h1dV6JOpoM90H28mrXg1Uy/5Jm6FCiqRCrLv9ORo79UdEzACGqMBxrlM5taFYcpAbzzWIKvu/tYSPbrz4MPPgiz2YyzzjrL782VVNKm1atXIyMjA7GxjiyuwX4/k5OTkJAQh3COLLH+uC/ppATXdAg/N2beWTJF6QPMO7dau5GbK71uMs9ctUDza9rbdwQsK5QDgBv/DZPUjSNPIqdAJ2O5+eT1DR/6fe5o/l0By/pr6O/PWI7unuKAZe12i9/PSue11qYouYiAjo79iudeM2ZHc7P0SPKevUsUvWYwtLRsC8l+W1u/UVWeJ7kXY9IdtW1typalc5Dp7A4QneEvjNxJbQPQe7krEZWVL6Ov33ekmHeEjCmMdODNyu9PoJGj/RlnByzrb+pUReWLqlcfkOPv5j7n8PUB64HcPYXcfE+LpQu5edJTB9Q00tvbBZYclFBV/Ybf5/ijPsXp9TmKo9cA/4nleATq/PXX4RwsgfYtVw8KC/1PaaipfQdVVa8oPaxBJRUpCjgifuvrN0k+FwxVVb7zwZ3aVeTzqKyUr3uBOhnsfq6PACSTiPIaMY1xubAxNcuEqBnFFb2R2Lr1O6SnX4Nx407HlCnLsXLlSvT2SieRmzJlCv76V88vy/Ll1+LZZwfm82o0Grzzzju4+uqrERsbi1NPPRXbtnneaBYXV+BnP7sLaWnLMH36CvzqV4+ivX2gl89ut+P555/H9OnTERUVhUmTJuHFFx2hRjU1DUhKmo9t277H5ZffjjFjZmPBggXIzBwYKXvvvfcwatQo1+/eocZmswUPPPBHzJhxAWJiYjFlyhQ8+6wjAcMNN9yAn//cM7zNYrFg6tRz8cEHWwG4h6lrsWLFCtTU1OB3v/udI0kb58iEydTst4MBkM8MbbXwhMFJH0tPj3yniyXAzUag5GC79yxER+d+v8/LzTtrCDBCKNdLaLUq/86ZTC0oOvaIz+Mi2TWZTAPBP+UjaSUlT/h9ziQTLr5vf7rf57yTBnoLNOXD31SWYPHO6i2iuXkLCovuD+LRBMvgr0ssRafbpW6ETqaszdaHbj/zmNWEeB45KlNWRZQXb/bwoSY3J7iy6jXFHa1q59cHOq/L3QtFhI/y+5za76pcQtxAHTOB7qXkOi8qK/8c8Pnq6r/6TfQmd30OFI1y5Ogv0Ntb6fd5uetZZeXLfp8L41jSLxC5aYL+ooPULrmnjvJzY2enfIdxoM50uQZioGkDPQE605uaPg9pVIa/peKOFfvef3lTc26urAr8nVTKau2S3cagl06I191TjMLC+wKWDfR9DmTENMblMDhOIv7/98v8V1a2t7eC+4vW3NyG229/BDfddDUOHtyKr756F9dcc43qL+pTTz2F6667DkePHsVll12GNWvWoKOjw7XPyy67DfPmzcSuXR/hs8/+htZWHa67biBMaf369Xj++efxxBNPoKioCB9++CFSUjzXb3/mmddw7723YN++jzFjxgzccMMNsFp9RwXsdovPKPKbb/4b33yzC++99yKKi4/hgw8+wJQpUwAAa9aswbZt29DT4+i96+urww8/ZMBo7MOVV/qGT3/++eeYMGECnn76aTQ1NaGpiT8iIlDSCLlQ3eaWrbIdL3INqkDKyv0npFKSLdYp2AlJnEymNsH5zp6Kih6STLQhknlW6TQPqSyval9TLblOk8FYe9VJarWHYJFbj/d4Cx0NBn9h7I7n5EbaAr9fXRxJtJTwXs/am95PNmAeTKbuh2I+MAAUHXso4PNqRsLCw33X1x0qWm3EoL22XAQN7+o33uSuvR2dgXPCBD7nB45ukAsTNvb5n7aSnSOfedyfXmPgRkFm1sqAgwh9CjtpRdZQD7YuFfPkD+feKLtNZ4f/gQu5qCXG/J+nAp2jio49iHad/yhDnmXA1PC3pDDPfaWapS7VUjM1rrVN+rOsqnxFtmzWgYsU7VP5gnzHGbkTptWixy6JOeVDYcV5+QjjCKFubm6D1WrFFVdciEmT0gAAy5ZdAa02UtX+161bhxtucGRj/OMf/4jXXnsNBw8exFlnnYx33/0YCxbMxoYNA/M73njjKcyZswqlpaUYP348Xn31Vbz++uu45RZH6Nu0adMwf36Sxz7uvfcWXHyxY9mIp556CqeddhrKy8sxa9Ysj+2kegjr65txyimTkJ6+GLGxyZgyZarruYsvvhhxcXHYsmUL1q5dC4ulC5988jUuueQ8JCbGe70Sw+jRyQgLC0NCQgJSU1OF3qcjR+/A0iWfSN6MBEoO49TdXYjExHmSz1mtPf4b4yobHPX1mzBzxkZFZZubt+C0Of4zo8phjElGH1RWvaIqG7Ca5cUM3QWoqHjJ70oI/f1NiI4eL/lcX19twBDPvCO34sILlIcqBdp3ILW17+LU6fI91UoFmkd6rPgRpKX5ZgvmcTh3LRYv8h/qJpelWafbhTFjfOfs8mht/R9SUi5WVDYQtR0y7TLTBlrb/oexY6Uv+N6rhXiTez/VHLuaxDiBIkZkyUS99ZuaEc+Z3Xw4sVp7ER4eJ/2kTEQXYzaZa5IGSkcRA43iAY4OIaXfyUD102iskVm9JtDfo+4aKpXZ26ml9WvEx89SfB9WWrIRY8dcqPTQ0NLyFcaN+4nP4zU1bwYsZzRWISPzAlx4ge+1tK7uX4qnQqjJrK86uRYHf/ckfGX9nx/V5POQSzzbUP+B3zpSXPKk4v3yJEluav4cc+a8qHgfavT3NyI6Os3jMd5Eubm5N6m6F5M0SCvpACNoZDwjU9nFYTiZN28mzjtvGc4666e4+eb/w3vvfYrWVv8XJ7kOCOdomjODOQDExcUhISEBra2O+al5eUXYu/cg0tKWuf6ffvpVAICKigocO3YMJpMJF14Y+GJy2mkzXD+PH+9obDj3IefGG69Efn4Jliy5Evfeexe++WYgjD4iIgLXXnst/v1vR8hUb68RX3+9E9dd53tx6u9vRE9v4FG8QCNt3d35fns/tVwhYf5fW+0ahcOV3k+YktpleWwqliDJybkeHR17/V6IAs21a237TvF+ebRzZrz2FXjkRy5cTG5Edc/excJHxENuxNQksw49zxQOf/ILAs/RD8z/RZln6pG/PA6MsUFZV9htD36f6eurl23MB0pkWi1z8x8oeiM8QOizHH9Lzbgcp9ETgbLLG2WWNAx0PXFc4wLX0UB1WG76UVWVb5JJJ7nw+kD5ODKzLghYtjHAkkS1df8IWFaN2tq3/WYA58mu3G9qVBXhw7tyiTTpz7m0TPkylLLfxwB4ln00GPIl36+eHunVL7zxrBfuj/KpbT+W9/M5B6r3QOBRXn9rjHvuV/pzLuRcmk85dU3MUomRdTXJtNUbvMb4iBkZl6PVRuHcc3Kh1fq+JYzZZZOlJSTM9jsv3WAI3JOj1cZwHWNYWBi++OItHDiQhx07MvDWW//BM8+8hoMHczB16lSf7TUa3/sQi2Wgge4ML42I8Bzp1Wg0sFodPZR2ux2XXHIennrqdx7bREQkYurUxais5JsfEREx8L46eyXtdr758gsXzsHRo99g+/Z92LUrCzfccBNWrlyFTz913KysWbMG5513HlpbW/HVVzsRFRWFiy5aLvlajizy0vu1WLpk5ztZ/S01wbmUjX/+34tgrOE6GNo4GqY2f41ulTfIajLFynUEBMrMax/kTpPBCnOXSyxy5OgvZHqRh74OMmaTDYULVfZmtY4Vr8eZy3w79tQkwOJK2BTge1cdIBmUU0npRiyYL33DLBd23dl1ECclS5+Xeebx+eMvoZj7Fsej0rKnMWHCzT6jeL29lcgvuDtg2arq1/1GyhSXyK+S0dr6jeRoqxpGYxWyDgQ/EsWppOQJTDjZN9TYbNapyr7Mo7Lqz5g69R6fx+WWH3Oy280IC1M2xztUU6P8hlZzjh6azR2IjEz2eEwu6SvguFbNnPmMz2fNGy1ntXaDMTv38oPuLGbppLPl5S9wla+vfx8TJ3pG1nV3F3EMElkkR/T1+sOw2QLnWQCA3XsWYcV5vo12Nau/8FF3fZbumA7N+dxutw5qR3lIRsb37NmDK664AmlpadBoNNi6davH84wxbNy4EWlpaYiJicGKFStQWKhuDV85Go0GYWExCAuL9flvtfUgLCxa5r9vubCwWGi1cuWihUJmNBoNzjxzER599G7s3fsxIiMjsGWLbwgVYwxjxoxGc/NAcjmDoQc1NdLzP7w5k0ktWDAbxcUVmDw5DdOmTXL9nzRpFOLi4nDqqaciJiYGP/ygPLshj8TEePz0p5fgtdc24h//eAGfffaZa177WWedhYkTJ2Lz5s34+OOvsHr1KkRG+p/XFh6uhc3meQGz283o66uTnZPmtweTo3F5NP/XfrO6BgrPCtRr2tfXIJ8cSSWp0QyrtRtH838tX9jP+yJ/A+0ILw2F3LybUelnbpBFZRZjOeZBvzgeP3hWIGgKED6qZrRJrmyg7yTPEnX+NDV/LruNvzC9wqIHFO8XAHo5MsH6S1Jks8lHupSWSiff4vmcAs5DVTOqWBF4VHEowmYDkbpJ51mZwF8jkDHG1TCVC5tVoqtLeTInuaXxAvGXDdrbYKzHzB/ppKaB4XsuUrMcIG8Ctq6uA5JJbeVGeZ2kljDjCZsGIJnFu6DwN1xlAd+lanlXUzJ0H5UcmeVNxCgVcXDw0BVcZaXyArVxdF4AjvXKpTuuBz8RqdoVA7ypua6r6XwQ6dDLO3K78OuHpDHe29uLBQsW4PXXpVPXv/DCC3j55Zfx+uuv49ChQ0hNTcVFF12E7u6hT8RisehhNinPls6TaV0u+ZJTdvZRvPTS2zh8uBB1dU3Ytu0HtLd3YubM6ZLbn3vuMmze/CUyMnJQVFSGX//6cYSF8XzkA1/aX/7y5+js1OO22x5GTk4+qqrq8cMPGbj77idhs9kQHR2Nhx9+GA899BDef/99VFRUICsrC++/7/+mUnTd7Dfe2IRPP/0GpaVVKC+vxtat3yE1NdWVgV2j0eDGG2/Em2++iZ07s3D99YF79CdNSsOePXvQ0NDgygrPtfRYQPInCJOpGRUVvnNvTOb2gFlijQHmyRUdeyBgQqdgkBrN4A2r9xfWxTOiWcyxzvlg8bfWKU9uADWqa/4qv5EfJj+NwKFoUPhbt3iw9fVVSz7epc/B7j0LZMvLZW/2xx4gGQ/fWrbS5wutRj45Vm9vqeQ1Q8dx499v8h/ip6Zu80w7MRrLJeuiXHZaADicu8bvc3V1/5Qt74/c923nrlmqbv78NWzkVt9wskh0Dg9FQjqLikgFf3hGIv1FgfHOX5b6rPwt1efNX6I1NYmg5KbZOElNt+EOx5UYGZdbDtCjuFf5Q9nXcJeVXk+cr4HX1uo7ysizXjzgPAcqv655n6949wsAbW3bPX5Xeg0RJXWeUzPdjzE7+vv5zkNqItB4sq6L4BnI8UfNylf+VhmRomS52JA0xi+99FL8/ve/xzXX+H7pGWN45ZVX8Nhjj+Gaa67B3Llz8a9//QtGoxEffuh/WYFgkAr34e2p87fsFU9PDG8vdEJCPDIycnDttXdhyZIr8Pvfv4Y//OEBXHyx9Hzt+++/HWedtQTXX38vrr32bvzkJ+dj6tSJXPtyGj8+Bd999z5sNjuuvvpOpKdfg0ceef7H5GiOBuwTTzyB//u//8OTTz6J2bNn4/rrr0dbm/+Tm+iyLHFxMXjllX9ixYqf4/zzb0RtbSO2bv0AWu1A9V2zZg2KioqQlpaCM88MPCfoscfuQnV1NaZNm4axY8cC4O+X7vEbCsX3CiazZ31gzIZ9+5YFbFD39pbi4MErJXvuQzt/Rl55+XN+npF/v5Suf837nVVCg8FtjPvjr6HtrqBAemRAqgNIir91371HEaQcPvxzyce7urJly/obVeVtA0kllysufpwzfG++7DZSeObpKREoa667QBEBgdTXb/IbnaPRKJ+1xhsqa+j2PYe1tPKtDSzViWs01si+Z2obrzz1yJ+sLOmwbN4MyFVVvp2C5RXPc5WVHk3m+1JJTVlgjPGNMvuL9ONojPs718gljXOSvofja3D4k5d3q6ryPKTOJ5UB5t67UzvnvKRkg8fvIslRjQqXcQICTPnj5J6PRvTvb/HK/dMhk7skkIrK0CQ3A8Q6Io1e2fVFPufAiRMDM5vbPQZvrNZu1NX5X8fbm3v7iDGGggLf6SD+eJ9nee5l/BrE5G3AMJwzXlVVhebmZqxaNbDsUVRUFM477zxkZGTgjjukQ3JNJhNMpoE32mAQn1NqNrchJkasserE2/sqxWLp4trvzJmn4PPPpZLkOE5E7733nsdjiYnxeO89zxPFjTde5fG72axHRITnMimNjQUePdHTpk3Gv//tu+af0ViBhIQ50Gq1eOyxx/DYY46RTMaYqxdp8uSTodd73oCNGpUIvf6oK7P4unXrsG7dOn9/Ntat+xnWrfNc4iMqapzH73PmzAFjDAZDvk/5r77yTN5y+ukLcOSIspvp+vp/YeYM5dkrvQVae9Jdd08hDueuwYrzvP4+zh7Ljo79SE4+W/TwVJM64dtsJtk1OdXIyDwf568oHtQleAIxm9sRGTkmqK+Zk3Od7Db+wldr697l2sfefctwwfmeSXAYs2HP3jO4ykvJOXy97DZNzZ9LzvXkbTgUHXsQC+Z7hgmqTRCoRn39BxxbqbuwFxc/ipPT5N9bKXv3nY5zlh9EZKTn8pO84aUWSxciIkYp2jdTFW5sQFjYWK/H5EdMcw5fj7lzX8e4FKWrpUi/LzwNAP+RCHzvNc/UAX8qK/+E6dMf9nhMTaLQI0d/yRV94a8XjSexV0HBvUg5/xKfUfTcvJu5jtHRGPe8rZVLSsjxqlxbeX8vRBqI0iOP/OXrGz7AxAlrubd319D4H8ya9fsfj0OsUVtW/gdMmnSbov2q6eRylB+oy6L33975BfwPGkjwapSpWdpzsJclc1dY9ADOOH2r6/cGFXkUuPKTuDGZmhEbO9V1HCLRnDrdbqSlOe5/AiWHlFJ07GEsXfKx63eR6S52u2VI7yGHXTb15mZHWM+4cZ6NrXHjxrmek/Lss88iKSnJ9X/iRPFGtZpQDKXrXw6Ulx6V4uH9hbZae7izDPf11fj+3Zz3if5GQ3hDyryjCcQuBL7b8oweDhbeJGve4aUR4Ul+tvQlFfIYKOzUHe/NDD/ljYmS0g3qeig5+BsNVp/wS/5z3rtvmfBUDDlqeqZ5SX2fOzr2w8Y5gqH0vfVfF/i+U8GepsEYk014F0h3j3x+E6OxKqRrpEvO4+NMaNThtdYuY3buKBZ104F83y8b53lEajSFN4LGX3h1SekGycc5X5RrM5HwWW9Smalra99R/HpcDXE4oh9Eb9bdZWScp7gsVGa7lp47zPc9PZT9U4/fu7t9Bwb8UZulu7R048BrHaerB4hyP5fwRk4EacdeD4jdC3V2DgzAHDn6KxWHIfY5eye9Feuw9vwbDx5aLbRv9ykFotdr93N8VbVYY9x3NR/+96y62nsKk9jnbBAIaweGYWPcyTupmdzagOvXr4der3f9r6tTEpqkJuGPujnH/f31qsq7MxqrhW6MeRN2SJE6IfCGhXnfDDmTxilhs/XBxJmEAwhuFmabzSjxxZXmvZQTz/ryg8X7plpEds7P5DfyoynAEjTBwjsaLMJut3IncOMNNx7u5LI2uysr800ww4Mxq2SPteh0Fs8XFdm/541wbe3bg5r12bFPC+qCuNyS/+kz0rxvxDo7szjnugP9XufpQ9lXo+jYQ1xlvbcTOQ97Z9ZnjPmdHiFHr88TWO5U+r6joeHfXKWl5pSKjAqquT57E72ZVaqu/n2P3x2d0HxfSjVh195LT/b1id1X7c/wzfbPW0e981dYBT7jYN6P8GZw99y/8/0Wf98HI9kfn4HvpX6Qpg1xHYVgro0ut2hI79BxEa2tXwtt792hr9PtFijteQ7knWvupCZyuEZmyUwR3tNEA6mq/ovHdbWx8SOhfRUWii0bN+wa46mpqQDgMwre2trqM1ruLioqComJiR7/neTW2HVyLHmgvEHuPcJjtQbvIipG7G/wPu7Bz68oTSS6wDvcTrQzxCexisBb5j3nsrDoAe4bM1/K65u/PAW8Kip9px7wYMwW1M6jQHQ63wYCb4+j1Bx7pUuiMcaQkXked0ZNO0d26cEQ7FERkbCuuvr3FO2jvPw5ZGae73Psh7JXK3o9q7UHff38eQMaGgYusowx7jm5HR0ZqpYVKiv/o8c8/aoq6YSm/rivNnDgwCWC+37W9bPdbg2YIM1bVKRnqLhIYhvv867I3HvvzNRqEgM1t2zj3rbXWI5er7mxzc1fcJf3ntfZ01OK/Hz+Ne5371nCvW0gopFjaka3q6pedX2f7XYr9meci8Ki+wVeYaBxWlvL37Fa5LVucnBu5Ad/pLmiwnNprKamzwOuMx/wtRRc19Usqeibk0HZHaSaBnW9V+ePCN4Eyi5eg4K803ucKquU3Xd5E8ke7+TeOcWbXBDwHBxVloNBeatC5DiluN9X8CQLdaf7MYJMavqr/H7F2iTDrjE+depUpKamYvv2gYyFZrMZu3fvxllnnSX8ejabiWu+pZP7Gyh6Y+veSGPMrirUsa+vXlEFUMI3CRj/F0fNBdudeMhNN9dyOoHKex0Bd1nvv3kw1x4MRLRhaTR69owqjUQYyjC4vCPrPH7v66vFoUNXSW/spaLyZZ/HDh2Szpgrx27vE7ootLQqv7lRo1JmrefhyjEaFpys79U1fxPavrVtIJlPl14+4ZxTbt5a1NRIr7nNq8xtrqLoTVphoUjjxpP7yLjoTUNh0f1Bm2ZiF9i3d4NBaWPFgf8cdujQVcg6cJHHTbtIw9J7FLys/I/cZQGAuWXuVzOCKpWZPRDRUFRvzk4ak6lZOIuxe50Ufb/cNTT+R7iMmiU1eQd+5BQde1BFafHrs96QB0BpIrPgNCMqBTsR3KeJqBlhLi37vdj2pU8p3leo1Tc4loTzl8TTv4HPWFkkRKiG+PiTi0pxLqGnpn7xCkljvKenB3l5ecjLywPgSNqWl5eH2tpaaDQa3HffffjjH/+ILVu2oKCgAOvWrUNsbCxuvFEqyU9gog0W9zViRXtk3Bt4SsLW3Rs5/jIbDzf9/fWuym61GhV3ICi5uXMP3xNtIHoviyHyZbPblSfBCaXMrAs8flfamSE6fzmYIWR6vdRSKtKkvoMiI6aexC4mUiFgJSUbFe6bX3W15+iqVKZxESzAEl7DiXuWZ9Hztnv4s41zTWIn97Bfk7kdOYdvECqvJtNzb2+p/EZcxG/eg7V2rOioUigp7YCoqX3L43vIOx3Ac9+O7+GOnacqOgYlRENRvTnvhzRa8TzBoZz37J6Dh3eNcqfOzqxgH86Qysu7RbhMoOmjclolljfjZTI1B6XzQ3lU4/HHea8u2mHd0vJf13QbniUKfajMRK5uRQzH38y7lrw73pxMwRCSxnh2djYWLVqERYscS1Ddf//9WLRoEZ580pGl+qGHHsJ9992Hu+66C0uXLkVDQwO+++47JCQkCO9LegkYOxiY5AnfvTFuFgzrsttNqtY+VFPhQnnxct4oqIkEUIb5+Vm0rMSzjP2YlM23V809xFOJ3t5gvU/KT3BWaw+sAmvJutevrAOrAmzpK1tg3VI5IidU71GkYCdVE9HS+o2rV1qO91x+0XmP7kTmfHszmZSvyWk2t+PYsfWCpQbqWH2D2DKW7iO9Go61uv0Rnf/nPlq6b98yj/mAg83ZYat2vqnIEjdOvAkrpbhPfZBep3hwtLpFMKkJa1XC2UlWW6ssT0BzyzbhvACh56gjLS18S9d5Ct4camE/XutsNiN271kgVFRN55LzGqt0JK+7Wz5xpD8aaBTfu3pPfxAZrMgv4J+uIUUk6nU44VnyeFAwBrvdJJyvpKLyJbdlQIe+A/XIkV8qLuv8PmUJTuVSSzTXR0iWNluxYkXAxqNGo8HGjRuxceNG1fuqrn4DcXGefQ52exts1k60tcVj9OhYhId79u719ztu7Mxm8RuOvr4ehIXFwG43C5dnTI+oqEgwZhcu293d6FqqRslx9/bqERYWBQAwmaywWvlfIyzMhLAwjaL9Go0GaLWRsNlMCsqbXTfhFot4eefnDAy8Z461VIGODiNs1k7Y7b4dMt6JhERl51yH887Nce0vFHSCozM2mxHh4XGq96s22YtIr6zVazpBadnTQvsymVrcltATvwB1dh7E6NGOZcFE1sZs1+3E6NFnuc5JR1VkXPVOGCiiovIl4TJ9ffWIiZmA4uLH0da+Xb6AG/evQknJE0Jl+/ubXMvJiTao3akpq0QwRrdbWr9SXLa/vwmHssWnbqhpdPT31yM2dgoAwSWFIJ/INZD8/Ltw4QVD3WHs4OxoLytXluTQZutDWalYOK1zv+Hh4oMYTiZTK6KiUhSEtTqWFVp+9j6UK+i8Hg4ZwZUlOB2om6JRmXp9DkaNWoqWFmXf54OHrsSiRR8onu6jdNrH4cM/9/heHc3/taLXGWqM2YIUySB+PioqehCLFvGvte1kMrcjSsWyqQx2VZ02vlNa+aiNgOrSH1LckcmYDd3dhdyrwkjxTkjJwyyQLA4YhuuMDw0buntegNX6c/T1z4VGE+ZRWaKjIwAw9PeL915FRjJotZFgzKqg96sVUVF62Gz9QqOWDu2Ijh4PACqP2y48l9hZVsl+NRodoqJSYbdbxCtveD/Cw7sAOBqLoqH9js/Z8WV1flaOiAkbzKZ89PVvhtqlUqSIf7aDQfRmJzgjFXl5t6p7AYHGeE9vCfpNzYiOciSFFM2G2dNb5tYYF785NFuULXdYV/dPdHcXYcniD2GxGNDTq3wdU1G7ds9H+pk/ICpqrKKbM4MhDzExE9BrVJIJXXkdO5S92nVDqNGIX9aco0L5BfcqPgYlBka3lZ9nzCpGWZSMijuoublS3tAymZpd17njSTCmnXV07hMuU1z8OObOfRWAsggKi6ULdnu/QOb5ASZTk+JGdUHhvZg/7y3o9YcVlQ8OdQ2IkpInhbbPO3IrVpyXL5Tx2Vtu7k2KyjHYQ5gVPTR27JyhuGxb23eIj5+DmJgJisp3dO5TdM63WbuByDGSyWn5yitvkAJA1oGLsWihkqgi9aPpSjsyGbOq6iBizAbDjzkVBtMIbYwDjHXC2Pcm+vrjodHEw72ypM/ejpbWr9HcIp71cN7c1xEfPxWNjZ+ipfXvwuWTk5fDYulAd3eRULkwbQxmz3ZkiM3MEh9Jm3vaq0hImIqysufRpRdbB/Ckk87HtGmPKtovAKSfuR0NDZvR2ia2BuqkSb/EyWmOMKW2th0orxDrgU+f7Ri5y8y6yO1RBsZ6wFgPeG4alcxD8RSiEYAQjTyobVhqBGfW1Na8jVNPfVzRaFpx8eM4+6xdP/6m5P1yRluI3wR3dR0AAOQP8SiDzdaL0rJnMG+usiWQikuexLhxlysq29V1ECedpGaNYQcln3V1zZuIjh4PK+fSde6c0QBK2Wx9yMxaqahsc/M2tHOu8S1F17FHUTnn8lM9PWLXKQBoa9uOyZN/JTwf1yF0I6ZqOkxEo0R89q0whLil9UuMa/sJOrsO+mR152G393OvIS9F6dQ1nW43Wtu+QU2N+D2Uk/eKK7ycHSeK5sa63UeKTnO02Yyw2UyKIgnUqq9/X9W5t7l5G1JTr1RUtqjoIcyZ8wIsFvHoi1BxNu7URNrs3rNYuExF5Z9x2pyXFUUzAUBT8+eIj5+lqCygbNALgOo542oYDEfR39+guHx9/QdBPBr/Rmxj3IGBsW4w5jlXOyoqEgbDTtjt4iEZ2jAjoqOjUVW9QX5jCe3tHysqZ7cD0dHRP/4sftwtLf9CcvJzaG0T7/XS6T5D9LynFe0XcBx3dY1YCDEAhIebEB0dDbvdjObmt4X3r+b9chJZomY4UBrmaTZ3ICwsXlFjxblfpWWd+vubhNcPr6t/D8nJyzFmjPjITn9/Hbr0ORiVtETRCI/z5l1NlvDOrqFPCCR6E+nO+RkraWg5EwqqDVF1ZkAVUVX1CqZO/a2i/eXmrUX6mcrXlW9t/Vbx8i2FRb9TvF/Ad9ktXvX1m9DZmYn29h+Ey5ZXPI/Jk38lPB/XwXHuOlb8qIKyjmXF4uOVjYg1NX2OSZNuQ1PTZ4rKq6F0VAhQFzas0+2BVqs8B0N5xYuKyzY3b0VPzzHhcgZDPoqOPaR4CkhB4W9QUPgbTJnCP7XIyfbjfOneXiWRQUBtndiARDCJrTvtqbDod7DbTUhLu1a4bFPzZ5gz5wVV4dPHIyVh062tX2HO7BfkNwxAzeoEAHDkqPj87braf6C75xhOOeU+VftWIu/IbarKey+pOViG3dJmw8GRo79AT4+yE3lu7k3HZUbNltYvJZeCGgr19eqyWdbVvw9Dt3jYjsnUqupGxW43K9ov4D7KIjrPvQm9vRXo6uJfgsmT/ce9io3WZmZdgLLyP6CwUNnN/46d07Fnr7r1crNzrlXUaFGzhqozQYySNbSda1qqTbAlaqiWRAxEdCkjAGjXORq0Sm9IKyrE57i7q6p6VVG5vr5aVY3iomMPKC4bKn19NYoa4mo5p340Nm5WVL6z64DicNyy8j+gu7sQRcceUlS+p2foppsES0vrlzAp+C4Hg9IR+UPZq4OSi8F7ZQoezgiGktKNivbZZ6xWVG44OFb8CDq7Dikqq+a7IbLCSrBZrT2Kpo+MNI1NH6O7Ox9Hjtwe6kMZUgUCy4+O8JFxaWp6CAHgcO6aIB2JGIvFgIiIRMXluzoPKCpnt/ejQeHNEQCUlIrNrfKmdP5MScmTqsIHKyr/pLhsa9t3GJdyqXC5/RnLXT8vWiQePsOYHZ2dB1wNRRFKR9HUYswGjSZM8bro7kvVKFWpoqNKaWNc6bJkh7JX4+S0GzBhws2Kyg/FmppSmpo+xZzZzwsn9XKqrvkbJkxcF9yD4qSmwydUSsuUj7aq1dam7Lx76NBVWHbGN/Ib+lFaulFVp83BQ8pCcQHgwMHLFJcNld7eMhV5BYBQTisIhZravyMiIklxWKyaVQqGgz6j2LKnTmq+G7W1YtFywaQsuoeMFCId1jQyfkJRl2ysu0d5mFCxwrBBNcrLn8MPO6ahS2FvrJqGeH39B6itVR5S5sy0qubi26ugN7mh4UPk5q1VvM9QkF6ekF8olwSy202K1+res3eR4v02NP4HBw6Kd/YAyka1h4t9+5aF+hCOG6LL2wTT0fw7FZdVWq+d1GTVJWJCET0RauUVL6CvrzbUhxESbBAS3soK4XzkUDie5tafCIZq+gSNjJPjnmgW9mAoKVWWE8DJbuuDTrdb1aitknBL0eW9hgO1NzZ2e5+qLNlqMvru3bfMtazRSKFmDVWlcy0JIeR4pzR3xHARikGZ1tavh3yfobQ/45xQH8KIMlSdH9QYP4GUlD6NSRPVJSsgQ6O07BnVr1FT+1YQjmT4q65+A9NO4Z97I0XNBTs7RzwpjdNIa4gDwL796YrLHo/5NgghJBjUJM8khBy/qDF+Amlp2YaWlm2hPgxCgm6o138e6dRmNFdKbcQJIYQcv0ZWyDUhxIHmjBNChr2RFooWesd3IiFCCCGEkOMBNcYJIYR4GOrl2AghZKQLxpJshJDjDzXGCSGEeGhs/CjUh0AIIYQQcsKjxjghhBAP5RUvhPoQCCGEEEJOeNQYJ4QQ4sFm6w31IRBCCCGEnPCoMU4IIYQQQgghhAwxaowTQgghhBBCCCFDjBrjhBBCCCGEEELIEKPGOCGEEEIIIYQQMsSoMU4IIYQQQgghhAwxaowTQgghhBBCCCFDjBrjhBBCCCGEEELIEKPGOCGEEEIIIYQQMsSoMU4IIYQQQgghhAwxaowTQgghhBBCCCFDjBrjhBBCCCGEEELIEKPGOCGEEEIIIYQQMsSoMU4IIYQQQgghhAyxYd8Y/+tf/4qpU6ciOjoaS5Yswd69e0N9SIQQQgghZARKHbcasbHTQn0YhJATxLBujG/evBn33XcfHnvsMeTm5uKcc87BpZdeitra2lAfGiGEEEIIGWEio8YiPDw+1IdBCDlBDOvG+Msvv4zbb78dv/jFLzB79my88sormDhxIv72t7+F+tAIIYQQQgiA8eOvDfUhCEsbf53Ckgzx8bOCeiyEkJFr2DbGzWYzcnJysGrVKo/HV61ahYyMDJ/tTSYTDAaDx//BNnHirYO+D0IIIaE3ccK6UB/CcWPcuCtCtu+kpCUh2/dQW3bG16E+BJeUsavkNwqxMSddgDOX/c/1e0rKZYpeJyIiGadOX39c1rWE+NNCtu+YmCkh23cohIXFhfoQhJycdoPq19BqY4JwJOJEO9aSkpYGZb+nL90SlNcZto3x9vZ22Gw2jBs3zuPxcePGobm52Wf7Z599FklJSa7/EydOlHzd5NFnY8yYlUg/83skJIidlE4++SYAgEYThrTx12H6tIeEyjtNmvQLaLVRisq6mzL5LuEyJ598E0aPOlPR/uLiTlVUzmnqlHsBAEmJizB58q/9bpeQMBdRkQOf+8SJt2HMmJVC+5o06Zeun0866XzBI3WIj5+DRQvfV1QWAObNfQNLl3ymuLwaSUlLkDz6bKEyERHJWLzoQwCOi0hERLKifYt8Vsmjl7t+XjD/HeHPGQCiolKx/OwMhIWJhw1OcauHUVGpQmVTUn7i+nnmzGeE9z19+iMAgOjoCTgrfZdweQCIj5uJCRPWCpVJTFyE5ORzXL+HhycJlQ8Li8WihZswZsxKTJ50B8LCYoXKi140R41aBgAYPTodY8deghmnPiFU3l1S0hJotZHC5calXI4ZM57A8rMzoNHwlY+JmYzw8EQAjr/hjNO/FN7vmDErkTb+OqSlXY9x464UKHch5p72F9fvSYmLhM/74eGJSEpaDMDx3Vww/x2um8vZs5/HzBkbMHbMRZg//y2kn/kD9z6d15ioqPE4Oe0GpI2/DpGRY7nKajQRSE29GosXfYD589/C9OnrER6e4PoMeDmvU0pptZGYPOkOoTKnnvr4j2X57wsWLvgn4uNnYuaMp12PnX32fqH9ulu0cJPQ9uHhiZg//y0AQHRUGk46aYVQ+dmzn8eMGRuEygAQfm/dzZr1e8TFTceMU59A2vjrkJx8NubMfpGr7LnnZOO0OX9GSsplmDjhFoSHJ2DJ4s1C+x8//meun8eMWYnT5rzMVS4yMgUrzitA6rjVGJ/6U4wZs9Lj2uVPWFgcUsZeiqioVEyefCfmz3sTS5Z8ggkTbuE+Zq02ChpNuOt3pQ3qRQs3YdkZ/+XaVqOJcPs5HKmpq7nKhYXFQauNxuxZzynuaAHgqpczZz6D+fP+joSEeYpeJ/3M7zFx4m3C5eLjZ+G0015xtTlETZl8F2bM2CB0zp92ygOYNev3WLJ4M+LjZ7nuT3jNnfsaxoxZiaVLPsE0gbbRwgX/xLnnHMbYsRc76ufizRhz0gVYuOCf3K8xa+YfMHv2s7jg/HKkjrtKdvvIyDFYMP9tV72OjEzB2LGXcF/bAcc57/SlW5GYOF/VeddJwxhjql9lEDQ2NuLkk09GRkYG0tPTXY//4Q9/wKZNm1BcXOyxvclkgslkcv1uMBgwceJE6PV6JCaKXYwJIYQQQgghhBBRBoMBSUlJXO3Q8IDPhtCYMWMQFhbmMwre2trqM1oOAFFRUYiKGuhVdvYxDEW4OiGEEEIIIYQQ4mx/8ox5D9vGeGRkJJYsWYLt27fj6quvdj2+fft2XHWVfBiCTqcDAL/h6oQQQgghhBBCyGDQ6XRISgo8HXDYNsYB4P7778fatWuxdOlSpKen46233kJtbS3uvPNO2bLJyY75rrW1tbJvwonk9NNPx6FDh0J9GMcF51SGuro6msoggOoYP6pj4qh+8aP6pQzVMX5Ux8RR/eJH9UsZqmP8QlXH9Ho9Jk2a5GqPBjKsG+PXX389dDodnn76aTQ1NWHu3Ln4+uuvMXnyZNmyWq0jN11SUtKI+oKHhYWNqL83GBITE+k9E0B1TBzVMX5Uv8RR/RJDdUwc1TF+VL/EUf0SQ3VMXKjqmLM9GsiwbowDwF133YW77hLPGj5S3X333aE+BHKCozpGBhPVLzLYqI6RwUT1iww2qmMnlmGbTV0tkSx2ZGSiOkIGG9UxMpiofpHBRnWMDCaqX2SwhaqOiex32K4zrlZUVBQ2bNjgkWGdEHdUR8hgozpGBhPVLzLYqI6RwUT1iwy2UNUxkf2esCPjhBBCCCGEEELIcHXCjowTQgghhBBCCCHDFTXGCSGEEEIIIYSQIUaNcUIIIYQQQgghZIhRY5wQQgghhBBCCBli1Bgnx7U9e/bgiiuuQFpaGjQaDbZu3erxfEtLC9atW4e0tDTExsbikksuQVlZmev56upqaDQayf+ffPKJa7vOzk6sXbsWSUlJSEpKwtq1a9HV1TVEfyUJJbV1DACam5uxdu1apKamIi4uDosXL8ann37qsQ3VsZEpGPWroqICV199NcaOHYvExERcd911aGlp8diG6tfI9Oyzz+L0009HQkICUlJSsHr1apSUlHhswxjDxo0bkZaWhpiYGKxYsQKFhYUe25hMJtx7770YM2YM4uLicOWVV6K+vt5jG6pjI1Ow6thbb72FFStWIDExERqNRrLuUB0beYJRvzo6OnDvvfdi5syZiI2NxaRJk/Cb3/wGer3e43VCVb+oMU6Oa729vViwYAFef/11n+cYY1i9ejUqKyvxxRdfIDc3F5MnT8bKlSvR29sLAJg4cSKampo8/j/11FOIi4vDpZde6nqtG2+8EXl5efj222/x7bffIi8vD2vXrh2yv5OEjto6BgBr165FSUkJtm3bhvz8fFxzzTW4/vrrkZub69qG6tjIpLZ+9fb2YtWqVdBoNNixYwf2798Ps9mMK664Ana73fVaVL9Gpt27d+Puu+9GVlYWtm/fDqvVilWrVnmcn1544QW8/PLLeP3113Ho0CGkpqbioosuQnd3t2ub++67D1u2bMFHH32Effv2oaenB5dffjlsNptrG6pjI1Ow6pjRaMQll1yCRx991O++qI6NPMGoX42NjWhsbMRLL72E/Px8vPfee/j2229x++23e+wrZPWLEXKCAMC2bNni+r2kpIQBYAUFBa7HrFYrS05OZm+//bbf11m4cCG77bbbXL8XFRUxACwrK8v1WGZmJgPAiouLg/tHkGFNaR2Li4tj77//vsdrJScns3feeYcxRnWMOCipX//73/+YVqtler3etU1HRwcDwLZv384Yo/pFBrS2tjIAbPfu3Ywxxux2O0tNTWXPPfeca5v+/n6WlJTE3nzzTcYYY11dXSwiIoJ99NFHrm0aGhqYVqtl3377LWOM6hgZoKSOudu5cycDwDo7Oz0epzpGGFNfv5w+/vhjFhkZySwWC2MstPWLRsbJCctkMgEAoqOjXY+FhYUhMjIS+/btkyyTk5ODvLw8j96yzMxMJCUlYdmyZa7HzjzzTCQlJSEjI2OQjp4cD3jr2PLly7F582Z0dHTAbrfjo48+gslkwooVKwBQHSPSeOqXyWSCRqNBVFSUa5vo6GhotVrXNlS/iJMzLDM5ORkAUFVVhebmZqxatcq1TVRUFM477zxX3cjJyYHFYvHYJi0tDXPnznVtQ3WMOCmpYzyojhEgePVLr9cjMTER4eHhAEJbv6gxTk5Ys2bNwuTJk7F+/Xp0dnbCbDbjueeeQ3NzM5qamiTLvPvuu5g9ezbOOuss12PNzc1ISUnx2TYlJQXNzc2Ddvxk+OOtY5s3b4bVasVJJ52EqKgo3HHHHdiyZQumTZsGgOoYkcZTv84880zExcXh4YcfhtFoRG9vLx588EHY7XbXNlS/COCY9nD//fdj+fLlmDt3LgC4Pv9x48Z5bDtu3DjXc83NzYiMjMTo0aMDbkN1jCitYzyojpFg1S+dTodnnnkGd9xxh+uxUNYvaoyTE1ZERAQ+++wzlJaWIjk5GbGxsdi1axcuvfRShIWF+Wzf19eHDz/80GcOCQBoNBqfxxhjko+TkYO3jj3++OPo7OzE999/j+zsbNx///249tprkZ+f79qG6hjxxlO/xo4di08++QT//e9/ER8fj6SkJOj1eixevNijDlL9Ivfccw+OHj2K//znPz7PedcDnrrhvQ3VMRLsOib3GkpfhxyfglG/DAYDfvKTn2DOnDnYsGFDwNcI9DrBFD6or05IiC1ZsgR5eXnQ6/Uwm80YO3Ysli1bhqVLl/ps++mnn8JoNOLmm2/2eDw1NdUnMzEAtLW1+fTEkZFHro5VVFTg9ddfR0FBAU477TQAwIIFC7B371688cYbePPNN6mOEb94zmGrVq1CRUUF2tvbER4ejlGjRiE1NRVTp04FQOcwAtx7773Ytm0b9uzZgwkTJrgeT01NBeAYFRo/frzr8dbWVlfdSE1NhdlsRmdnp8foeGtrqyuKjOoYUVPHeFAdG9mCUb+6u7txySWXID4+Hlu2bEFERITH64SqftHIOBkRkpKSMHbsWJSVlSE7OxtXXXWVzzbvvvsurrzySowdO9bj8fT0dOj1ehw8eND12IEDB6DX6z3C2cnI5q+OGY1GAIBW63m6DQsLc2W7pjpG5PCcw8aMGYNRo0Zhx44daG1txZVXXgmA6tdIxhjDPffcg88//xw7duxwddA4TZ06Fampqdi+fbvrMbPZjN27d7vqxpIlSxAREeGxTVNTEwoKClzbUB0buYJRx3hQHRuZglW/DAYDVq1ahcjISGzbts0jFwsQ4vo1qOnhCBlk3d3dLDc3l+Xm5jIA7OWXX2a5ubmspqaGMebIlrhWXyK4AAAGmUlEQVRz505WUVHBtm7dyiZPnsyuueYan9cpKytjGo2GffPNN5L7ueSSS9j8+fNZZmYmy8zMZPPmzWOXX375oP5tZHhQW8fMZjObPn06O+ecc9iBAwdYeXk5e+mll5hGo2FfffWVazuqYyNTMM5h//jHP1hmZiYrLy9nmzZtYsnJyez+++/32Ibq18j061//miUlJbFdu3axpqYm13+j0eja5rnnnmNJSUns888/Z/n5+eyGG25g48ePZwaDwbXNnXfeySZMmMC+//57dvjwYXbBBRewBQsWMKvV6tqG6tjIFKw61tTUxHJzc9nbb7/NALA9e/aw3NxcptPpXNtQHRt5glG/DAYDW7ZsGZs3bx4rLy/3eJ3hcA6jxjg5rjmXwPD+f8sttzDGGHv11VfZhAkTWEREBJs0aRJ7/PHHmclk8nmd9evXswkTJjCbzSa5H51Ox9asWcMSEhJYQkICW7Nmjc+yG+TEFIw6Vlpayq655hqWkpLCYmNj2fz5832WOqM6NjIFo349/PDDbNy4cSwiIoKdeuqp7E9/+hOz2+0e21D9Gpmk6hYA9s9//tO1jd1uZxs2bGCpqaksKiqKnXvuuSw/P9/jdfr6+tg999zDkpOTWUxMDLv88stZbW2txzZUx0amYNWxDRs2yL4O1bGRJxj1y991FgCrqqpybReq+qX58Q8lhBBCCCGEEELIEKE544QQQgghhBBCyBCjxjghhBBCCCGEEDLEqDFOCCGEEEIIIYQMMWqME0IIIYQQQgghQ4wa44QQQgghhBBCyBCjxjghhBBCCCGEEDLEqDFOCCGEEEIIIYQMMWqME0IIISegFStW4L777gv1YRBCCCHED2qME0IIISPcrl27oNFo0NXVFepDIYQQQkYMaowTQgghhBBCCCFDjBrjhBBCyHGut7cXN998M+Lj4zF+/Hj86U9/8nj+gw8+wNKlS5GQkIDU1FTceOONaG1tBQBUV1fj/PPPBwCMHj0aGo0G69atAwBMmTIFr7zyisdrLVy4EBs3bnT9rtFo8Pe//x2XX345YmNjMXv2bGRmZqK8vBwrVqxAXFwc0tPTUVFRMWh/PyGEEHI8osY4IYQQcpx78MEHsXPnTmzZsgXfffcddu3ahZycHNfzZrMZzzzzDI4cOYKtW7eiqqrK1eCeOHEiPvvsMwBASUkJmpqa8Oqrrwrt/5lnnsHNN9+MvLw8zJo1CzfeeCPuuOMOrF+/HtnZ2QCAe+65Jzh/LCGEEHKCCA/1ARBCCCFEuZ6eHrz77rt4//33cdFFFwEA/vWvf2HChAmubW677TbXz6eccgr+8pe/4IwzzkBPTw/i4+ORnJwMAEhJScGoUaOEj+HWW2/FddddBwB4+OGHkZ6ejieeeAIXX3wxAOC3v/0tbr31VqV/IiGEEHJCopFxQggh5DhWUVEBs9mM9PR012PJycmYOXOm6/fc3FxcddVVmDx5MhISErBixQoAQG1tbVCOYf78+a6fx40bBwCYN2+ex2P9/f0wGAxB2R8hhBByIqDGOCGEEHIcY4wFfL63txerVq1CfHw8PvjgAxw6dAhbtmwB4AhfD0Sr1fq8vsVi8dkuIiLC9bNGo/H7mN1uD7g/QgghZCShxjghhBByHJs+fToiIiKQlZXleqyzsxOlpaUAgOLiYrS3t+O5557DOeecg1mzZrmStzlFRkYCAGw2m8fjY8eORVNTk+t3g8GAqqqqwfpTCCGEkBGFGuOEEELIcSw+Ph633347HnzwQfzwww8oKCjAunXroNU6LvGTJk1CZGQkXnvtNVRWVmLbtm145plnPF5j8uTJ0Gg0+PLLL9HW1oaenh4AwAUXXIBNmzZh7969KCgowC233IKwsLAh/xsJIYSQExE1xgkhhJDj3Isvvohzzz0XV155JVauXInly5djyZIlAByj2++99x4++eQTzJkzB8899xxeeuklj/Inn3wynnrqKTzyyCMYN26cK/P5+vXrce655+Lyyy/HZZddhtWrV2PatGlD/vcRQgghJyINk5tsRgghhBBCCCGEkKCikXFCCCGEEEIIIWSIUWOcEEIIIYQQQggZYtQYJ4QQQgghhBBChhg1xgkhhBBCCCGEkCFGjXFCCCGEEEIIIWSIUWOcEEIIIYQQQggZYtQYJ4QQQgghhBBChhg1xgkhhBBCCCGEkCFGjXFCCCGEEEIIIWSIUWOcEEIIIYQQQggZYtQYJ4QQQgghhBBChhg1xgkhhBBCCCGEkCH2/6PQETgp6WC9AAAAAElFTkSuQmCC", + "image/png": 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", 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" ] @@ -3472,26 +3969,17 @@ } ], "source": [ - "ruzyne_tidy.plot(subplots=True, figsize=(12, 9));" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Tohle už je trochu užitečné, něco málo na grafu vidět je. Výchozí čárový (`line`) graf je pro časové řady často vhodný.\n", - "\n", - "Pomocí argumentu `layout` můžeme podgrafy uspořádat do více sloupců. Pokud navíc vybereme kratší časové období, dostaneme už celkem srozumitelný výsledek." + "denni_ruzyne.hist(figsize=(12, 9), bins=30);" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 31, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -3501,39 +3989,58 @@ } ], "source": [ - "ruzyne_tidy.loc[\"2021\"].plot(\n", - " subplots=True, layout=(3, 3), figsize=(12, 9)\n", - ");" + "denni_ruzyne.hist(figsize=(12, 9), bins=30, cumulative=True, density=True);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "I tady je ale dat poměrně hodně a na grafech vidíme spoustu rozptylu - hodnoty skáčou rychle nahoru / dolů. V takovém případě je na čase vzít si na pomoc statistiku!" + "Je poměrně zajímavé a příhodné, že dostáváme poměrně hezkou paletu různých typů rozdělovací funkce. Tlak vzduchu má přibližně **[normální (Gaussovo) rozdělení](https://cs.wikipedia.org/wiki/Norm%C3%A1ln%C3%AD_rozd%C4%9Blen%C3%AD)**. O tom jste možná slyšeli, protože se vyskytuje a používá poměrně často (někdy až příliš často). U teploty je zajímavé, že má tzv. **bi-modální rozdělení** - na histogramu jsou dvě maxima. U dalších veličin se můžeme zamyslet, která z [mnoha známých distribucí](https://en.wikipedia.org/wiki/Log-normal_distribution) by se na jejich popis více či méně hodila. Logaritmicko-normální na rychlost větru? Nějaká exponenciální (nebo obecně gamma) distribuce výšky sněhu, úhrnu srážek a možná slunečního svitu? Toto ponechejme na nějaký podrobnější kurz statistiky, meteorologie či klimatologie :)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Trocha statistiky - opravdu jen základní\n", - "\n", - "Není cílem tohoto kurzu (a ani v jeho možnostech) podrobně a rigorózně učit statistiku (\"Statistika nuda je...\"). Jednoduché základy, které zvládají i 🐼🐼🐼, spolu jistě zvládneme a přesvědčíme se, že jsou i užitečné (\"...má však cenné údaje...\").\n", + "Různorodé distribuční funkce nám ale umožní ukázat některé vlastnosti střední hodnoty a mediánu. To jsou (společně s módy, tedy maximy hustoty pravděpodobnosti) ukazatele centrální tendence souboru dat. Medián a střední hodnota se poměrně často neliší a u \"hezkých\" (symetrických) distribucí, jako je normální rozdělení, jsou totožné. Lišit se budou zejména tehdy, když je distribuce sešikmená (angl. skewed) nebo pokud jsou v datech odlehlé hodnoty, spíše známé pod anglickým výrazem [outliers](https://en.wikipedia.org/wiki/Outlier).\n", "\n", - "Pokud se budeš chtít dozvědět víc, koukni třeba na https://www.poritz.net/jonathan/share/ldlos.pdf, nebo na http://greenteapress.com/thinkstats2/thinkstats2.pdf nebo třeba i na Bayesovskou statistiku http://www.greenteapress.com/thinkbayes/thinkbayes.pdf." + "Zabalíme do funkce vykreslovaní histogramu spolu se střední hodnotou a kvantily, které jsme použili již dříve. Poté použijeme velice užitečnou knihovnu [seaborn](https://seaborn.pydata.org) na vykreslení histogramů pro jednotlivé veličiny." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "def hist_plot_with_extras(data, bins=30, cumulative=False, density=False, **kwargs):\n", + " \"\"\"Plot histogram with mean and quantiles\"\"\"\n", + " ax = kwargs.pop(\"ax\", plt.gca())\n", + " ax.hist(data, bins=bins, cumulative=cumulative, density=density, **kwargs)\n", + " ax.grid(True)\n", + " if density:\n", + " ax.set_yticks(np.arange(0, 1.1, 0.25))\n", + " ax.axvline(data.mean(), color=\"k\")\n", + " ax.axvline(data.median(), color=\"r\")\n", + " ax.axvline(data.quantile(0.25), color=\"r\", ls=\"--\")\n", + " ax.axvline(data.quantile(0.75), color=\"r\", ls=\"--\")\n", + " return ax" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Metoda [`DataFrame.describe`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.describe.html#pandas.DataFrame.describe) je jednoduchou volbou pro získání základních statistik celé tabulky." + "Teď můžeme použít [`FacetGrid`](https://seaborn.pydata.org/generated/seaborn.FacetGrid.html), který vytváří sadu grafů, rozdělených do mřížky podle nějaké vlastnosti dat (kategorie).\n", + "\n", + "Jenže facetgrid očekává přesně jeden sloupec s hodnotami a jeden sloupec s kategorií, podle které má vytvořit podgrafy. Musíme pro něj vytvořit \"dlouhou\" tabulku: vždy název proměnné (\"variable\") a její hodnota (\"value\"). Datum (index) můžeme zahodit, protože pro účely histogramu ho nepotřebujeme. K tomuto převedení tabulky z široké na dlouhou slouží metoda [`.melt`](https://pandas.pydata.org/docs/reference/api/pandas.melt.html):\n", + "\n" ] }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -3557,184 +4064,62 @@ " \n", " \n", " \n", - " teplota průměrná\n", - " teplota maximální\n", - " teplota minimální\n", - " rychlost větru\n", - " tlak vzduchu\n", - " vlhkost vzduchu\n", - " úhrn srážek\n", - " celková výška sněhu\n", - " sluneční svit\n", + " A\n", + " B\n", + " C\n", " \n", " \n", " \n", " \n", - " count\n", - " 22280.000000\n", - " 22280.00000\n", - " 22280.000000\n", - " 22280.000000\n", - " 22280.000000\n", - " 22280.000000\n", - " 22280.000000\n", - " 22280.000000\n", - " 22280.000000\n", - " \n", - " \n", - " mean\n", - " 8.479102\n", - " 13.02912\n", - " 4.130215\n", - " 4.155669\n", - " 972.470844\n", - " 76.428591\n", - " 1.400274\n", - " 1.019075\n", - " 4.745193\n", - " \n", - " \n", - " std\n", - " 8.164936\n", - " 9.45250\n", - " 7.200533\n", - " 2.216812\n", - " 8.081669\n", - " 12.517161\n", - " 3.841425\n", - " 3.680072\n", - " 4.286857\n", - " \n", - " \n", - " min\n", - " -22.600000\n", - " -18.30000\n", - " -25.500000\n", - " 0.000000\n", - " 928.700000\n", - " 27.000000\n", - " 0.000000\n", - " 0.000000\n", - " 0.000000\n", - " \n", - " \n", - " 25%\n", - " 2.200000\n", - " 5.30000\n", - " -0.700000\n", - " 2.700000\n", - " 967.600000\n", - " 68.000000\n", - " 0.000000\n", - " 0.000000\n", - " 0.500000\n", - " \n", - " \n", - " 50%\n", - " 8.700000\n", - " 13.40000\n", - " 4.400000\n", - " 3.700000\n", - " 972.900000\n", - " 78.000000\n", - " 0.000000\n", - " 0.000000\n", - " 3.900000\n", + " 0\n", + " 1\n", + " 4\n", + " 7\n", " \n", " \n", - " 75%\n", - " 15.000000\n", - " 20.60000\n", - " 9.900000\n", - " 5.300000\n", - " 977.700000\n", - " 86.000000\n", - " 1.000000\n", - " 0.000000\n", - " 8.100000\n", + " 1\n", + " 2\n", + " 5\n", + " 8\n", " \n", " \n", - " max\n", - " 29.500000\n", - " 37.40000\n", - " 20.700000\n", - " 20.300000\n", - " 1000.800000\n", - " 100.000000\n", - " 93.300000\n", - " 57.000000\n", - " 15.700000\n", + " 2\n", + " 3\n", + " 6\n", + " 9\n", " \n", " \n", "\n", "" ], "text/plain": [ - " teplota průměrná teplota maximální teplota minimální rychlost větru \\\n", - "count 22280.000000 22280.00000 22280.000000 22280.000000 \n", - "mean 8.479102 13.02912 4.130215 4.155669 \n", - "std 8.164936 9.45250 7.200533 2.216812 \n", - "min -22.600000 -18.30000 -25.500000 0.000000 \n", - "25% 2.200000 5.30000 -0.700000 2.700000 \n", - "50% 8.700000 13.40000 4.400000 3.700000 \n", - "75% 15.000000 20.60000 9.900000 5.300000 \n", - "max 29.500000 37.40000 20.700000 20.300000 \n", - "\n", - " tlak vzduchu vlhkost vzduchu úhrn srážek celková výška sněhu \\\n", - "count 22280.000000 22280.000000 22280.000000 22280.000000 \n", - "mean 972.470844 76.428591 1.400274 1.019075 \n", - "std 8.081669 12.517161 3.841425 3.680072 \n", - "min 928.700000 27.000000 0.000000 0.000000 \n", - "25% 967.600000 68.000000 0.000000 0.000000 \n", - "50% 972.900000 78.000000 0.000000 0.000000 \n", - "75% 977.700000 86.000000 1.000000 0.000000 \n", - "max 1000.800000 100.000000 93.300000 57.000000 \n", - "\n", - " sluneční svit \n", - "count 22280.000000 \n", - "mean 4.745193 \n", - "std 4.286857 \n", - "min 0.000000 \n", - "25% 0.500000 \n", - "50% 3.900000 \n", - "75% 8.100000 \n", - "max 15.700000 " + " A B C\n", + "0 1 4 7\n", + "1 2 5 8\n", + "2 3 6 9" ] }, - "execution_count": 44, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy.describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Pro každý sloupec vidíme několik souhrnných (statistických údajů).\n", - "* `count` udává počet hodnot.\n", - "* `mean` je střední hodnota, vypočítaná jako aritmetický průměr. \n", - "* `std` je směrodatná odchylka, která ukazuje rozptyl dat - jak moc můžeme očekávat, že se data v souboru budou lišit od střední hodnoty.\n", - "* `min` a `max` jsou nejmenší a největší hodnoty ve sloupci.\n", - "* Procenta označují kvantily, `25%` a `75%` je hodnota prvního a třetího \"kvartilu\". Pokud bychom sloupec seřadili podle podle velikosti, bude čtvrtina dat menší než hodnota prvního kvartilu a čtvrtina dat bude větší než hodnota třetího kvartilu. Konkrétně čtvrtina všech dní v našich datech měla minimální teplotu menší než -0.7 °C a čtvrtina dní zase měla maximální teplotu větší než 20.5 °C. \n", - "* `50%` se označuje jako medián - polovina dat je menší než medián (a ta druhá polovina je samozřejmě zase větší než medián).\n", + "# Začneme s jednoduchou tabulkou\n", "\n", - "Za chvilku si ještě ukážeme, jak tyto hodnoty souvisi s distribuční funkcí a vše ti bude hned jasnější :)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "`describe` můžeme samozřejmě použít i na nějakou podmožinu dat. Takto třeba vypadá statistika počasí v Ruzyni v lednu." + "df = pd.DataFrame(\n", + " {\n", + " \"A\": [1, 2, 3],\n", + " \"B\": [4, 5, 6],\n", + " \"C\": [7, 8, 9],\n", + " }\n", + ")\n", + "df" ] }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 34, "metadata": {}, "outputs": [ { @@ -3758,230 +4143,217 @@ " \n", " \n", " \n", - " teplota průměrná\n", - " teplota maximální\n", - " teplota minimální\n", - " rychlost větru\n", - " tlak vzduchu\n", - " vlhkost vzduchu\n", - " úhrn srážek\n", - " celková výška sněhu\n", - " sluneční svit\n", + " variable\n", + " value\n", " \n", " \n", " \n", " \n", - " count\n", - " 1891.000000\n", - " 1891.000000\n", - " 1891.000000\n", - " 1891.000000\n", - " 1891.000000\n", - " 1891.000000\n", - " 1891.000000\n", - " 1891.000000\n", - " 1891.000000\n", + " 0\n", + " A\n", + " 1\n", " \n", " \n", - " mean\n", - " -1.524167\n", - " 1.164146\n", - " -4.414014\n", - " 4.688049\n", - " 973.015389\n", - " 85.116341\n", - " 0.727710\n", - " 4.396616\n", - " 1.717081\n", + " 1\n", + " A\n", + " 2\n", " \n", " \n", - " std\n", - " 5.132778\n", - " 4.979510\n", - " 5.658037\n", - " 2.951776\n", - " 10.266974\n", - " 7.385042\n", - " 1.551676\n", - " 6.183976\n", - " 2.258995\n", + " 2\n", + " A\n", + " 3\n", " \n", " \n", - " min\n", - " -22.600000\n", - " -18.300000\n", - " -25.500000\n", - " 0.000000\n", - " 933.900000\n", - " 54.000000\n", - " 0.000000\n", - " 0.000000\n", - " 0.000000\n", + " 3\n", + " B\n", + " 4\n", " \n", " \n", - " 25%\n", - " -4.500000\n", - " -1.900000\n", - " -7.800000\n", - " 2.300000\n", - " 965.900000\n", - " 80.000000\n", - " 0.000000\n", - " 0.000000\n", - " 0.000000\n", + " 4\n", + " B\n", + " 5\n", " \n", " \n", - " 50%\n", - " -0.900000\n", - " 1.300000\n", - " -3.400000\n", - " 4.000000\n", - " 973.300000\n", - " 86.000000\n", - " 0.000000\n", - " 1.000000\n", - " 0.500000\n", + " 5\n", + " B\n", + " 6\n", " \n", " \n", - " 75%\n", - " 1.900000\n", - " 4.400000\n", - " -0.300000\n", - " 6.650000\n", - " 980.400000\n", - " 90.500000\n", - " 0.700000\n", - " 7.000000\n", - " 3.000000\n", + " 6\n", + " C\n", + " 7\n", " \n", " \n", - " max\n", - " 12.500000\n", - " 15.800000\n", - " 8.500000\n", - " 19.700000\n", - " 1000.800000\n", - " 100.000000\n", - " 14.700000\n", - " 30.000000\n", - " 8.400000\n", + " 7\n", + " C\n", + " 8\n", + " \n", + " \n", + " 8\n", + " C\n", + " 9\n", " \n", " \n", "\n", "" ], "text/plain": [ - " teplota průměrná teplota maximální teplota minimální rychlost větru \\\n", - "count 1891.000000 1891.000000 1891.000000 1891.000000 \n", - "mean -1.524167 1.164146 -4.414014 4.688049 \n", - "std 5.132778 4.979510 5.658037 2.951776 \n", - "min -22.600000 -18.300000 -25.500000 0.000000 \n", - "25% -4.500000 -1.900000 -7.800000 2.300000 \n", - "50% -0.900000 1.300000 -3.400000 4.000000 \n", - "75% 1.900000 4.400000 -0.300000 6.650000 \n", - "max 12.500000 15.800000 8.500000 19.700000 \n", - "\n", - " tlak vzduchu vlhkost vzduchu úhrn srážek celková výška sněhu \\\n", - "count 1891.000000 1891.000000 1891.000000 1891.000000 \n", - "mean 973.015389 85.116341 0.727710 4.396616 \n", - "std 10.266974 7.385042 1.551676 6.183976 \n", - "min 933.900000 54.000000 0.000000 0.000000 \n", - "25% 965.900000 80.000000 0.000000 0.000000 \n", - "50% 973.300000 86.000000 0.000000 1.000000 \n", - "75% 980.400000 90.500000 0.700000 7.000000 \n", - "max 1000.800000 100.000000 14.700000 30.000000 \n", - "\n", - " sluneční svit \n", - "count 1891.000000 \n", - "mean 1.717081 \n", - "std 2.258995 \n", - "min 0.000000 \n", - "25% 0.000000 \n", - "50% 0.500000 \n", - "75% 3.000000 \n", - "max 8.400000 " + " variable value\n", + "0 A 1\n", + "1 A 2\n", + "2 A 3\n", + "3 B 4\n", + "4 B 5\n", + "5 B 6\n", + "6 C 7\n", + "7 C 8\n", + "8 C 9" ] }, - "execution_count": 45, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy[ruzyne_tidy.index.month == 1].describe()" + "# A převedeme její sloupce na řádky\n", + "df.melt()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Statistické rozdělení\n", - "\n", - "Pojďme zkusit pojmy kolem pravděpodobnosti, jako třeba rozdělovací funkce nebo hustota pravděpodobnosti, jejichž formální definice a vlastnosti lze najít v knihách (např. v těch uvedených výše) nebo na [wikipedii](https://cs.wikipedia.org/wiki/Distribu%C4%8Dn%C3%AD_funkce), objevovat a zkoumat spíš názorně a intuitivně.\n", - "\n", - "Jedním ze základních a nesmírně užitečných nástrojů na vizualizaci souboru dat je [histogram](https://cs.wikipedia.org/wiki/Histogram). Zjednodušeně řečeno, histogram vytvoří chlívečky podle velikosti dat - do každého chlívečku patří data v nějakém intervalu od - do. Počet hodnot, které ze souboru dat spadnou do daného chlívečku, určuje velikost (výšku) chlívečku.\n", - "\n", - "Histogram zobrazíme pomocí `.plot.hist()`" + "Aplikováno na naše data:" ] }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 35, "metadata": {}, "outputs": [ { "data": { - "image/png": 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2tavg-7.0
3tavg-9.2
4tavg-15.9
.........
209317tsun429.0
209318tsun374.0
209319tsun231.0
209320tsun292.0
209321tsun357.0
\n", + "

209322 rows × 2 columns

\n", + "
" + ], "text/plain": [ - "
" + " variable value\n", + "0 tavg -9.4\n", + "1 tavg -9.9\n", + "2 tavg -7.0\n", + "3 tavg -9.2\n", + "4 tavg -15.9\n", + "... ... ...\n", + "209317 tsun 429.0\n", + "209318 tsun 374.0\n", + "209319 tsun 231.0\n", + "209320 tsun 292.0\n", + "209321 tsun 357.0\n", + "\n", + "[209322 rows x 2 columns]" ] }, + "execution_count": 35, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy[\"tlak vzduchu\"].plot.hist(edgecolor=\"black\");" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Histogram nám říká, že někde v rozmezí 972 - 979 je nejvíce hodnot (skoro 8000). Okolní chlívečky mají o něco menší velikost, 964 - 971 cca 5000, 978 - 985 cca 4000. Na okrajích jsou jen nízké chlívečky, jakési ocasy.\n", - "\n", - "Přemýšlej - kdybychom si vybrali náhodně jeden den. \n", - "1. Z kterého (jednoho) z chlívečků v grafu bude nejčastěji ležet tlak? \n", - "2. Jakých 5 chlívečků bys vybrala, abys měla opravdu hodně velkou šanci, že tlak ve vybraném dni bude v jednom z těchto chlívečků?\n", - "\n", - "Pokud dokážeš na otázky odpovědět, tak už vlastně víš, že histogram udává *hustotu pravděpodobnosti* a že tahle hustota se dá sčítat, čímž se dostane *kumulovaná pravděpodobnost*, neboli také *distribuční funkce*.\n", - "\n", - "Definice je vlastně docela jednoduchá (zdroj [wikipedia](https://cs.wikipedia.org/wiki/Distribu%C4%8Dn%C3%AD_funkce)): \n", - "\n", - "> Distribuční funkce, funkce rozdělení (pravděpodobnosti) nebo (spíše lidově) (zleva) kumulovaná pravděpodobnost (anglicky Cumulative Distribution Function, CDF) je funkce, která udává pravděpodobnost, že hodnota náhodné proměnné je menší než zadaná hodnota. \n", - "\n", - "Hustota pravděpodobnosti vyjadřuje, kolik \"pravděpodobnosti\" přibude na daném intervalu, neboli o kolik se změní distrubuční funkce. Matematicky je hustota pravděpodobnosti derivací distribuční funkce." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Poměrně důležitým parametrem u histogramu je počet chlívků. Když jich je málo, může zaniknout důležitá informace, moc chlívků může zase vnést velký šum. \n", - "\n", - "Pro naše data vypadá histogram s třiceti chlívky celkem rozumně." + "denni_ruzyne.melt()" ] }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 36, "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "
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" ] }, "metadata": {}, @@ -3989,258 +4361,218 @@ } ], "source": [ - "ruzyne_tidy[\"tlak vzduchu\"].plot.hist(bins=30, figsize=(12, 6), edgecolor=\"black\");" + "grid = sns.FacetGrid(\n", + " denni_ruzyne.melt(),\n", + " col=\"variable\",\n", + " col_wrap=3,\n", + " sharey=False,\n", + " sharex=False,\n", + " aspect=2,\n", + ")\n", + "grid.map(hist_plot_with_extras, \"value\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Na vlastní nebezpečí můžete na tvoření histogramů použít [physt](https://github.com/janpipek/physt) Honzy Pipka. Přidává pár zajímavých vlastností a často usnadní práci." - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [], - "source": [ - "# physt možná nemáte nainstalovaný - stačí odkomentovat\n", - "# %pip install physt" + "Kromě histogramu se velice často používá pro zobrazení distribuce tzv. [boxplot](https://cs.wikipedia.org/wiki/Boxplot). \"Krabička\" (obdélník) uprostřed vymezuje oblast mezi prvním a třetím kvartilem (Q1 a Q3), dělicí čára odpovídá mediánu, a \"vousy\" (anglicky whiskers) značí rozsah dat. Obvykle je to poslední bod, který je blíže než 1,5násobek \"inter-quartile range\" [IQR](https://en.wikipedia.org/wiki/Interquartile_range), `IQR = Q3 - Q1` od Q1 či Q3. Tento rozsah se obvykle považuje za mez pro odlehlé hodnoty, které jsou pak v boxplotu vyznačeny jako symboly (kosočtverce v našem případě)." ] }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 37, "metadata": {}, "outputs": [ { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'physt'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[49], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mphyst\u001b[39;00m\n\u001b[1;32m 3\u001b[0m histogram \u001b[38;5;241m=\u001b[39m physt\u001b[38;5;241m.\u001b[39mh1(ruzyne_tidy[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtlak vzduchu\u001b[39m\u001b[38;5;124m\"\u001b[39m], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfixed_width\u001b[39m\u001b[38;5;124m\"\u001b[39m, bin_width\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m5\u001b[39m)\n\u001b[1;32m 4\u001b[0m histogram\u001b[38;5;241m.\u001b[39mplot(edgecolor\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mblack\u001b[39m\u001b[38;5;124m\"\u001b[39m, show_values\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, show_stats\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m);\n", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'physt'" + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/jan/code/collaboration/pyladies-kurz/.venv/lib/python3.11/site-packages/seaborn/axisgrid.py:718: UserWarning: Using the boxplot function without specifying `order` is likely to produce an incorrect plot.\n", + " warnings.warn(warning)\n" ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "import physt\n", - "\n", - "histogram = physt.h1(ruzyne_tidy[\"tlak vzduchu\"], \"fixed_width\", bin_width=5)\n", - "histogram.plot(edgecolor=\"black\", show_values=True, show_stats=True);" + "grid = sns.FacetGrid(\n", + " denni_ruzyne.melt(),\n", + " col=\"variable\",\n", + " col_wrap=2,\n", + " sharey=False,\n", + " sharex=False,\n", + " aspect=2,\n", + ")\n", + "grid.map(sns.boxplot, \"value\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Argument `cumulative=True` nám pak zobrazí postupný (kumulativní) součet velikosti chlívků. Použijeme ještě `density=True`, abychom zobrazili distribuční funkci. Takto nám graf říká, jaká je pravděpodobnost (hodnota na vertikální ose), že tlak bude menší než daná hodnota (na horizontální ose). \n", - "\n", - "V grafu jsou ještě přidané svislé čáry pro střední hodnotu (černá), medián (červená) a 25% a 75% kvantily (červené přerušované)." + "Seaborn se často dá použít velice jednoduše, pokud zobrazujeme jednu veličinu, a někdy stráví i \"wide-format\" data. U našich dat můžeme takto porovnat průměrnou, minimální a maximální teplotu. Na pomoc si vezmeme [`catplot`](https://seaborn.pydata.org/generated/seaborn.catplot.html), který vytváří graf (nebo i sadu grafů) různých typů (boxplot nebo třeba violinplot) z dat obsahujících jednu či více kategorických proměnných." ] }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 38, "metadata": {}, "outputs": [ { "data": { + "image/png": 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", "text/plain": [ - "" + "
" ] }, - "execution_count": 50, "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, "output_type": "display_data" } ], "source": [ - "ax = ruzyne_tidy[\"tlak vzduchu\"].plot.hist(\n", - " bins=30, figsize=(12, 6), cumulative=True, density=True, grid=True\n", - ")\n", - "ax.set_yticks(np.arange(0, 1.1, 0.25))\n", - "ax.axvline(ruzyne_tidy[\"tlak vzduchu\"].mean(), color=\"k\")\n", - "ax.axvline(ruzyne_tidy[\"tlak vzduchu\"].median(), color=\"r\")\n", - "ax.axvline(ruzyne_tidy[\"tlak vzduchu\"].quantile(0.25), color=\"r\", ls=\"--\")\n", - "ax.axvline(ruzyne_tidy[\"tlak vzduchu\"].quantile(0.75), color=\"r\", ls=\"--\")" + "sns.catplot(\n", + " data=denni_ruzyne[[\"tavg\", \"tmin\", \"tmax\"]],\n", + " orient=\"h\",\n", + " kind=\"box\",\n", + " aspect=2,\n", + ");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Podívejme se, jak vypadají histogramy všech devíti veličin. " + "**Úkol**: Doplňte pomocné sloupce `season` a `significant_precipitation` (jistě uhádnete jakého pandas-typu budou :). První definuje roční období (jen jednoduše podle kalendářních měsíců), druhý označuje dny, kdy byly srážky vyšší než v **90 %** všech dní v našich datech (můžete zkusit i jiný limit).\n", + "\n", + "1. Porovnejte numericky základní statistiky celého datasetu a podmnožiny, kdy výrazně pršelo nebo sněžilo. Zvyšují v průměru srážky teplotu? A co maximální nebo minimální? A jak je to se standardní odchylkou?\n", + "2. Použijte `sns.catplot` pro vizuální srovnání distribučních funkcí pro jednotlivá roční období a dny s málo / hodně srážkami." ] }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 39, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "ruzyne_tidy.hist(figsize=(12, 9), bins=30);" + "# odkomentuj a doplň\n", + "# season = denni_ruzyne.index.___.map({\n", + "# 1: \"zima\",\n", + "# 2: \"zima\",\n", + "# 3: \"jaro\",\n", + "# ...\n", + "# })\n", + "\n", + "# significant_precipitation = denni_ruzyne[\"prcp\"] > denni_ruzyne[___].quantile(___)" ] }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 40, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "ruzyne_tidy.hist(figsize=(12, 9), bins=30, cumulative=True, density=True);" + "# úkol - jednoduché srovnání statistik pomocí rozdílu\n", + "\n", + "# (denni_ruzyne.loc[___]\n", + "# .describe()\n", + "# ) - \\\n", + "# denni_ruzyne.___()" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 41, "metadata": {}, + "outputs": [], "source": [ - "Je poměrně zajímavé a příhodné, že dostáváme poměrně hezkou paletu různých typu rozdělovací funkce. Tlak vzduchu má přibližně **[normální (Gaussovo) rozdělení](https://cs.wikipedia.org/wiki/Norm%C3%A1ln%C3%AD_rozd%C4%9Blen%C3%AD)**. O tom jste možná slyšeli, protože se vyskutuje a používá poměrně často (někdy až příliš často). U teploty je zajímavé, že má tzv. **bi-modální rozdělení** - na histogramu jsou dvě maxima. U dalších veličin se můžeme zamyslet, která z [mnoha známých distribucí](https://en.wikipedia.org/wiki/Log-normal_distribution) by se na jejich popis více či méně hodila. Logaritmicko-normální na na rychlost větru? Nějaká exponenciální (nebo obecně gamma) distribuce výšky sněhu, úhrnu srážek a možná slunečního svitu? Toto ponechejme na nějaký podrobnější kurz statistiky, meteorologie či klimatologie :)" + "# úkol - vizuální srovnání statistik\n", + "\n", + "# sns.catplot(\n", + "# data=denni_ruzyne.assign(\n", + "# significant_precipitation=___,\n", + "# season=___,\n", + "# ),\n", + "# kind=\"box\",\n", + "# aspect=2,\n", + "# hue=___,\n", + "# y=___,\n", + "# x=___,\n", + "# );" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Různorodé distribuční funkce nám ale umožní ukázat některé vlastnosti střední hodnoty a mediánu. To jsou (společně s módy, tedy maximy hustoty pravděpodobnosti) ukazatele centrální tendence souboru dat. Medián a střední hodnota se poměrně často neliší a u \"hezkých\" (symetrických) distribucí, jako je normální rozdělení, jsou totožné. Lišit se budou zejména tehdy, když je distribuce sešikmená (angl. skewed) nebo pokud jsou v datech odlehlé hodnoty, spíše známé pod anglickým výrazem [outliers](https://en.wikipedia.org/wiki/Outlier).\n", + "## Práce s časovou řadou\n", "\n", - "Zabalíme do funkce vykreslovaní histogramu spolu se střední hodnotou a kvantily, které jsme použili již dříve. Poté použijeme velice užitečnou knihovnu [seaborn](https://seaborn.pydata.org) na vykreslení histogramů pro jednotlivé veličiny." + "Pojďme trochu zkombinovat statistiku a práci s časovou řadou. Zajímalo by vás, jak moc byl který rok teplý či studený? Pomocí [`resample`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.resample.html#pandas.DataFrame.resample) můžeme změnit rozlišení dat na jiné období, např. jeden rok." ] }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 42, "metadata": {}, "outputs": [], "source": [ - "def hist_plot_with_extras(data, bins=30, cumulative=False, density=False, **kwargs):\n", - " \"\"\"Plot histogram with mean and quantiles\"\"\"\n", - " ax = kwargs.pop(\"ax\", plt.gca())\n", - " ax.hist(data, bins=bins, cumulative=cumulative, density=density, **kwargs)\n", - " ax.grid(True)\n", - " if density:\n", - " ax.set_yticks(np.arange(0, 1.1, 0.25))\n", - " ax.axvline(data.mean(), color=\"k\")\n", - " ax.axvline(data.median(), color=\"r\")\n", - " ax.axvline(data.quantile(0.25), color=\"r\", ls=\"--\")\n", - " ax.axvline(data.quantile(0.75), color=\"r\", ls=\"--\")\n", - " return ax" + "rocni_ruzyne = denni_ruzyne.resample(\"1YE\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Všimněte si použití `.melt()` - seaborn totiž očekává data v jednom sloupci, jednotlivé grafy pak tvoří na základě hodnoty jiného sloupce. Vytvořili jsme vlastně kategorickou proměnnou \"value\".\n", - "\n", - "Teď můžeme použít [`FacetGrid`](https://seaborn.pydata.org/generated/seaborn.FacetGrid.html), který vytváří sadu grafů, rozdělených do mřížky podle nějaké vlastnosti dat (kategorie)." + "Co že jsme to vlastně vytvořili?" ] }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 43, "metadata": {}, "outputs": [ - { - "ename": "NameError", - "evalue": "name 'hist_plot_with_extras' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[50], line 9\u001b[0m\n\u001b[1;32m 1\u001b[0m grid \u001b[38;5;241m=\u001b[39m sns\u001b[38;5;241m.\u001b[39mFacetGrid(\n\u001b[1;32m 2\u001b[0m ruzyne_tidy\u001b[38;5;241m.\u001b[39mmelt(),\n\u001b[1;32m 3\u001b[0m col\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvariable\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 7\u001b[0m aspect\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m,\n\u001b[1;32m 8\u001b[0m )\n\u001b[0;32m----> 9\u001b[0m grid\u001b[38;5;241m.\u001b[39mmap(\u001b[43mhist_plot_with_extras\u001b[49m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvalue\u001b[39m\u001b[38;5;124m\"\u001b[39m);\n", - "\u001b[0;31mNameError\u001b[0m: name 'hist_plot_with_extras' is not defined" - ] - }, { "data": { - "image/png": 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" + "" ] }, + "execution_count": 43, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "grid = sns.FacetGrid(\n", - " ruzyne_tidy.melt(),\n", - " col=\"variable\",\n", - " col_wrap=2,\n", - " sharey=False,\n", - " sharex=False,\n", - " aspect=2,\n", - ")\n", - "grid.map(hist_plot_with_extras, \"value\");" + "rocni_ruzyne" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Kromě histogramu se velice často používá pro zobrazení distribuce tzv. [boxplot](https://cs.wikipedia.org/wiki/Boxplot). \"Krabička\" (obdélník) uprostřed vymezuje oblast mezi prvním a třetím kvartilem (Q1 a Q3), dělicí čára odpovídá mediánu, a \"vousy\" (anglicky whiskers) značí rozsah dat. Standardně je to poslední bod, který je menší / větší než 1,5násobek \"inter-quartile range\" IQR, `IQR = Q3 - Q1`. Tento rozsah se obvykle považuje za mez pro odlehlé hodnoty, které jsou pak v boxplotu vyznačeny jako symboly (kosočtverce v našem případě)." + "Dostali jsme instanci třídy `DatetimeIndexResampler`. To zní logicky, ale kde jsou data? Ta zatím nejsou, protože jsme ještě pandám neřekli, jak vlastně mají ze všech těch denních údajů v rámci jednoho roku vytvořit ta roční data. Neboli, jak data *agregovat*.\n", + "\n", + "Ze statistiky víme, že jedním z ukazatelů může být střední hodnota. Zkusíme vypočítat průměrnou \"teplotu průměrnou\" (není to překlep) a rovnou vykreslit." ] }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 44, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/kuba/micromamba/envs/datalady/lib/python3.12/site-packages/seaborn/axisgrid.py:718: UserWarning: Using the boxplot function without specifying `order` is likely to produce an incorrect plot.\n", - " warnings.warn(warning)\n" - ] - }, { "data": { - "image/png": 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", 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -4248,34 +4580,26 @@ } ], "source": [ - "grid = sns.FacetGrid(\n", - " ruzyne_tidy.melt(),\n", - " col=\"variable\",\n", - " col_wrap=2,\n", - " sharey=False,\n", - " sharex=False,\n", - " aspect=2,\n", - ")\n", - "grid.map(sns.boxplot, \"value\");" + "rocni_ruzyne[\"tavg\"].mean().plot();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Seaborn se často dá použít velice jednoduše, pokud zobrazujeme jednu veličinu, a někdy stráví i \"wide-format\" data. U našich dat můžeme takto porovnat průměrnou, minimální a maximální teplotu. Na pomoc si vezmeme [`catplot`](https://seaborn.pydata.org/generated/seaborn.catplot.html), který vytváří graf (nebo i sadu grafů) různých typů (boxplot nebo třeba violinplot) z dat obsahujících jednu či více kategorických proměnných." + "Trochu podobnou operací jako resampling je rolování. To spočívá v plynulém posouvání \"okna\", které slouží pro (vážený) výběr dat a následné aplikaci agregační funkce (jako u `resample`). Pojďme pomocí [`rolling`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rolling.html#pandas.DataFrame.rolling) vytvořit podobný pohled na roční průměrnou teplotu. Rozdíl oproti `resample` je v tom, že dostaneme pro každý den jednu hodnotu, nikoli jen jednu hodnotu pro celý rok. A také už nemůžeme použít interval \"1 rok\", protože jeden (kalendářní) rok není dobře definovaný interval díky přestupným rokům." ] }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 45, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, "metadata": {}, @@ -4283,233 +4607,1190 @@ } ], "source": [ - "sns.catplot(\n", - " data=ruzyne_tidy[[\"teplota průměrná\", \"teplota maximální\", \"teplota minimální\"]],\n", - " orient=\"h\",\n", - " kind=\"box\",\n", - " aspect=2,\n", - ");" + "denni_ruzyne[\"pres\"].rolling(\"365D\", min_periods=365).mean().plot();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**Úkol**: Doplňte pomocné sloupce `season` a `significant_precipitation` (jistě uhádnete jakého pandas-typu budou :). První definuje roční období (jen jednoduše podle kalendářních měsíců), druhý označuje dny, kdy byly srážky vyšší než v **90 %** všech dní v našich datech (můžete zkusit i jiný limit).\n", - "\n", - "1. Porovnejte numericky základní statistiky celého datasetu a podmnožiny, kdy výrazně pršelo nebo sněžilo. Zvyšují v průměru srážky teplotu? A co maximální nebo minimální? A jak je to se standardní odchylkou?\n", - "2. Použijte `sns.catplot` pro vizuální srovnání distribučních funkcí pro jednotlivá roční období a dny s málo / hodně srážkami." + "Pro podrobnější přehled práce s časovými řadami se podívej např. na https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html nebo třeba na hezký článek s podobnými daty https://www.dataquest.io/blog/tutorial-time-series-analysis-with-pandas/." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol:** Navrhněte vhodnou roční agregaci pro maximální teplotu (ne průměr) a vykreslete." ] }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "# odkomentuj a doplň\n", + "# rocni_ruzyne[___].___().___();" + ] + }, + { + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "# odkomentuj a doplň\n", - "# season = ruzyne_tidy.index.___.map({\n", - "# 1: \"zima\",\n", - "# 2: \"zima\",\n", - "# 3: \"jaro\",\n", - "# ...\n", - "# })\n", - "\n", - "# significant_precipitation = ruzyne_tidy[\"úhrn srážek\"] > ruzyne_tidy[___].quantile(___)" + "**Úkol:** Najděte, kdy v období 2000-2025 napršelo nejvíc za týden (tedy za průběžných 7 dnů). Odpovídá to nějaké vaší historické zkušenosti?" ] }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 47, "metadata": {}, "outputs": [], "source": [ - "# úkol - jednoduché srovnání statistik pomocí rozdílu\n", - "\n", - "# (ruzyne_tidy.loc[___]\n", - "# .describe()\n", - "# ) - \\\n", - "# ruzyne_tidy.___()" + "# doplňte nebo vyřešte po svém :)\n", + "# denni_ruzyne.loc[___][___].rolling(___).sum().sort_values(ascending=False).iloc[:10]" ] }, { - "cell_type": "code", - "execution_count": 55, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "# úkol - vizuální srovnání statistik\n", - "\n", - "# sns.catplot(\n", - "# data=ruzyne_tidy.assign(\n", - "# significant_precipitation=___,\n", - "# season=___,\n", - "# ),\n", - "# kind=\"box\",\n", - "# aspect=2,\n", - "# hue=___,\n", - "# y=___,\n", - "# x=___,\n", - "# );" + "**Nepovinný úkol:** Rozšiřte hledání na celé období v naší datové sadě - jsou některé hodnoty realistické?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Práce s časovou řadou\n", + "## Časová data a časová pásma (nepovinná noční můra)\n", "\n", - "Pojďme trochu zkombinovat statistiku a práci s časovou řadou. Zajímalo by vás, jak moc byl který rok teplý či studený? Pomocí [`resample`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.resample.html#pandas.DataFrame.resample) můžeme změnit rozlišení dat na jiné období, např. jeden rok." + "Zatím jsme měli data s jednodenní hustotou a příliš jsme se nezabývali hodinami, časovými zónami, přechodem mezi letním a zimním časem. Zkusme si načíst výrazně jemnější data o pražském počasí:" ] }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 48, "metadata": {}, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/dm/gbbql3p121z0tr22r2z98vy00000gn/T/ipykernel_68701/3110781995.py:1: FutureWarning: 'Y' is deprecated and will be removed in a future version, please use 'YE' instead.\n", - " ruzyne_yearly = ruzyne_tidy.resample(\"1Y\")\n" - ] + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " time temp dwpt rhum prcp snow wdir wspd wpgt \\\n", + "0 1931-01-03 12:00:00 0.0 0.0 0.0 \n", + "1 1931-01-03 18:00:00 1.1 0.0 0.0 \n", + "2 1931-01-04 06:00:00 6.1 200.0 16.6 \n", + "3 1931-01-04 12:00:00 11.1 160.0 3.6 \n", + "4 1931-01-04 18:00:00 6.1 270.0 33.5 \n", + "... ... ... ... ... ... ... ... ... ... \n", + "471611 2025-08-31 19:00:00 19.4 9.3 52.0 0.0 100.0 14.0 25.9 \n", + "471612 2025-08-31 20:00:00 17.7 9.1 57.0 0.0 120.0 14.0 29.6 \n", + "471613 2025-08-31 21:00:00 17.1 9.0 59.0 0.0 130.0 14.0 29.6 \n", + "471614 2025-08-31 22:00:00 16.9 9.3 61.0 0.0 140.0 14.0 29.6 \n", + "471615 2025-08-31 23:00:00 15.9 10.2 69.0 0.0 140.0 11.0 29.6 \n", + "\n", + " pres tsun coco \n", + "0 1004.3 \n", + "1 1002.8 \n", + "2 1000.7 \n", + "3 999.0 \n", + "4 1001.8 \n", + "... ... ... ... \n", + "471611 1012.3 0.0 1.0 \n", + "471612 1012.5 0.0 1.0 \n", + "471613 1012.3 0.0 1.0 \n", + "471614 1012.1 0.0 1.0 \n", + "471615 1012.3 0.0 1.0 \n", + "\n", + "[471616 rows x 12 columns]" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "ruzyne_yearly = ruzyne_tidy.resample(\"1Y\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Co že jsme to vlastně vytvořili?" + "hodinove_ruzyne_original = pd.read_parquet(\"praha-meteostat.parquet\")\n", + "hodinove_ruzyne_original" ] }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "time datetime64[ns]\n", + "temp Float64\n", + "dwpt Float64\n", + "rhum Float64\n", + "prcp Float64\n", + "snow Float64\n", + "wdir Float64\n", + "wspd Float64\n", + "wpgt Float64\n", + "pres Float64\n", + "tsun Float64\n", + "coco Float64\n", + "dtype: object" ] }, - "execution_count": 57, + "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ruzyne_yearly" + "hodinove_ruzyne_original.dtypes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Dostali jsme instanci třídy `DatetimeIndexResampler`. To zní logicky, ale kde jsou data? Ta zatím nejsou, protože jsme ještě pandám neřekli, jak vlastně mají ze všech těch denních údajů v rámci jednoho roku vytvořit ta roční data. Neboli, jak data *agregovat*.\n", + "U pozorování máme přirazený nějaký čas. Ale co to znamená? Možná je z kontextu patrné, **kde** bylo \"time\" hodin, ale pak se dost pravděpodobně mýlíte - důležitá je totiž definice podle zdroje data. Pokud chcete cokoliv správně vyhodnocovat s časovými daty, musí jim být přiřazeno časové pásmo. Mnohdy se na to zapomíná (\"tohle opravíme potom\") a používají se \"naivní\" časové údaje, ale bývá to často příčinou mnohých zmatků.\n", "\n", - "Ze statistiky víme, že jedním z ukazatelů může být střední hodnota. Zkusíme vypočítat průměrnou \"teplotu průměrnou\" (není to překlep) a rovnou vykreslit." + "Při čtení definice dat se dočteme, že všechna data jsou uložena v UTC (takže v Praze je v létě o 2 h více, v zimě o 1 h). Měli bychom to naší tabulce explicitně říct. Naštěstí to není tak složité - metoda [`.dt.tz_localize`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.tz_localize.html) slouží přesně k tomu:" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 1931-01-03 12:00:00+00:00\n", + "1 1931-01-03 18:00:00+00:00\n", + "2 1931-01-04 06:00:00+00:00\n", + "3 1931-01-04 12:00:00+00:00\n", + "4 1931-01-04 18:00:00+00:00\n", + " ... \n", + "471611 2025-08-31 19:00:00+00:00\n", + "471612 2025-08-31 20:00:00+00:00\n", + "471613 2025-08-31 21:00:00+00:00\n", + "471614 2025-08-31 22:00:00+00:00\n", + "471615 2025-08-31 23:00:00+00:00\n", + "Name: time, Length: 471616, dtype: datetime64[ns, UTC]" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hodinove_ruzyne_original[\"time\"].dt.tz_localize(\"UTC\")" ] }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 51, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" + " time temp dwpt rhum prcp snow wdir wspd \\\n", + "0 1931-01-03 12:00:00+00:00 0.0 0.0 0.0 \n", + "1 1931-01-03 18:00:00+00:00 1.1 0.0 0.0 \n", + "2 1931-01-04 06:00:00+00:00 6.1 200.0 16.6 \n", + "3 1931-01-04 12:00:00+00:00 11.1 160.0 3.6 \n", + "4 1931-01-04 18:00:00+00:00 6.1 270.0 33.5 \n", + "... ... ... ... ... ... ... ... ... \n", + "471611 2025-08-31 19:00:00+00:00 19.4 9.3 52.0 0.0 100.0 14.0 \n", + "471612 2025-08-31 20:00:00+00:00 17.7 9.1 57.0 0.0 120.0 14.0 \n", + "471613 2025-08-31 21:00:00+00:00 17.1 9.0 59.0 0.0 130.0 14.0 \n", + "471614 2025-08-31 22:00:00+00:00 16.9 9.3 61.0 0.0 140.0 14.0 \n", + "471615 2025-08-31 23:00:00+00:00 15.9 10.2 69.0 0.0 140.0 11.0 \n", + "\n", + " wpgt pres tsun coco \n", + "0 1004.3 \n", + "1 1002.8 \n", + "2 1000.7 \n", + "3 999.0 \n", + "4 1001.8 \n", + "... ... ... ... ... \n", + "471611 25.9 1012.3 0.0 1.0 \n", + "471612 29.6 1012.5 0.0 1.0 \n", + "471613 29.6 1012.3 0.0 1.0 \n", + "471614 29.6 1012.1 0.0 1.0 \n", + "471615 29.6 1012.3 0.0 1.0 \n", + "\n", + "[471616 rows x 12 columns]" ] }, + "execution_count": 51, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "ruzyne_yearly[\"teplota průměrná\"].mean().plot();" + "hodinove_ruzyne_utc = hodinove_ruzyne_original.assign(\n", + " time=hodinove_ruzyne_original[\"time\"].dt.tz_localize(\"UTC\")\n", + ")\n", + "hodinove_ruzyne_utc" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Trochu podobnou operací jako resampling je rolování. To spočívá v plynulém posouvání \"okna\", které slouží pro (vážený) výběr dat a následné aplikaci agregační funkce (jako u `resample`). Pojďme pomocí [`rolling`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rolling.html#pandas.DataFrame.rolling) vytvořit podobný pohled na roční průměrnou teplotu. Rozdíl oproti `resample` je v tom, že dostaneme pro každý den jednu hodnotu, nikoli jen jednu hodnotu pro celý rok. A také už nemůžeme použít interval `\"1Y\"`, protože jeden (kalendářní) rok není dobře definovaný interval díky přestupným rokům." + "Pokud si pak chceme ukázat data (a to nás zajímá?) v středovském časovém pásmu, slouží k tomu [`.dt.tz_convert`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.tz_convert.html):" ] }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 53, "metadata": {}, "outputs": [ { "data": { - "image/png": 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gCMJxmHtFZgFhK/umDLaA8DAJpueCOWtgGR69eAguHt5Zsz0QxUW1aMth9fGGA1W45bUVAGKP5ThvaMeYXmcWy2e1cOFCnHfeeejYsSNcLhfef/99zfOKomDmzJno2LEj8vPzMWHCBKxbt86u8yUIgiDSEH/IuiGzgGSHYkDMFuZKdwKhSE89F4zL5cJlo8ojLCHRYmSuG9tNfXzTK+HCZdGyYABgSOcSAMCkAe3UbVMl1g6fjSLRsgCpra3F0KFDMWfOHOnzjz76KB5//HHMmTMHy5YtQ1lZGc444wxUVzsbzEIQBEGkLmzylMUQZDczCwiLzYgW8yJeq2gWkKK8sItmz7F69bEZC8h7Pz8JP86crOkTI2uAd6javnL5loNQp0yZgilTpkifUxQFTzzxBO6//35MnToVAPDKK6+gffv2eOONN3DLLbfEd7YEQRBEWuI3EQPSlMExIDwsNiNaFkyWWyscollA9HrFmYkByc5yo1hwj7EsGp7vth6BoiiWAlf1sDUGZPv27Thw4AAmT56sbsvNzcWpp56K7777Tvoar9eLqqoqzT+CIAgis1AtIJJMDrbSt9O8n8qwnjeNUbJgRAtINMGip09ijQHJ98hdNx+sslYSXg9bBciBAwcAAO3bt9dsb9++vfqcyOzZs1FSUqL+Ky8vt/OUCIIgiBTAH2AxIJIg1OzMtoCs36ddWFc3BCu+Nka1gGgFSLQsIb/O8czEgMgYwfWFGdujtfr4rrdXxXQ8EUeyYETTjJG5ZsaMGaisrFT/7d6924lTIgiCIJKIUQyIJ7TNamGudKCyvhFnP/mNZlthqPKrXjM6Nl2K1qJoMTJ6LppY03BdLhd2PHIOdjxyDmZdODCmYxhhqwApKysDgAhrR0VFRYRVhJGbm4vi4mLNP4IgCCKzCFtAIgXI3uMNAIDP1x1M6Dklgj3H6iK2HavzAdC3aLhCibpuYeHujxIDovf8d1sPS7dboVe7IvXxFaPs8VTYKkC6d++OsrIyzJs3T93m8/mwYMECnHTSSXa+FUEQBJFGGFlA5v8UFB4bD2ZetqQsMHTroVo0+gO6Lhh2iay6YPQsIBU2Za7ccVovAPb1iLGcBVNTU4MtW7aof2/fvh2rVq1CaWkpunTpgrvuugsPP/wwevfujd69e+Phhx9GQUEBrrrqKltOmCAIgkg/jLJgmiObD9boBqGO7FYKIDJNN5qLSs8CMrhTSQxnGEluKCjV22iPq8yyAFm+fDkmTpyo/n333XcDAK677jq8/PLL+PWvf436+nr84he/wLFjxzB69Gh8/vnnKCoq0jskQRAEkeGwANNsSRDqb88dgFkfrcfwLi0TfFbOo5ca63bLBcVb/2+MGvxZFQpWZWw6WGMYU6kXxJunk81iFRZLUuNrirKnOSwLkAkTJkDRu6IIBq3MnDkTM2fOjOe8CIIgiAzCKAakZb4HgLzwVbojioyOJXnYV9kAb2MgIu34m19PRHlpgfp3dUNjxPHW7avCIB2Lhl4WTNuiXKunLYW5eD7+cT+essGpQb1gCIIgCMfxG9UBUSuhZl4aLh+3MXlAezV+wucPqC6Ym0/ujtUPTtaID0BeJ8QoENWvYxzo3Crf8nnLWLu30pbjMEiAEARBEI7TZGABUSuhZmAaLh/H4XKFAzh9TQH18+Z7slASsgLxnD24LGKbUQyNLAh16rBOuGFcd8vnLaMgJ+zKqfXG74YhAUIQBEE4jt+oF0xoW7Qsj3TiwQ/W4rY3flD7vgDB9FpWFMzb5MfXGw8BkHcIBoDe7Yvwwa3jcN+Ufuo2MTWXxy9cvw4leXj88hNsiwHp2DJsSbHDWkUChCAIgnCcJhO9YKLVuUgXFEXBK4t34qMf92PdvrDbYs/xOqwJuTGe+Xobdh0N1ghZu0/ftTG0vCUGdQzHfBhdI9ECYpfwYFzO1f+IVsXVDCRACIIgCMcJW0Aipx0WAxKtO2y6wFtyqjlXxdq94ZLs3+84qj7eeSSyWBkPXxLdyE0lipNYK6Dq0aEkn7NWkQAhCIIg0oBwDEjkc8wqsuFANTYeSP9iZLxIqPdFdpQVKcozzv7Jz8lCp5D7w6gjrihOcm22gADhGJZojfTMQAKEIAiCcByjOiB8DMSZTyxM2Dk5BS8SqrlaHnwsB0+74ryox8xn/WMMLA9iXEaezRYQgIvXIRcMQRAEkQ6wiVOahhtRcjy9XTF8k7m5K/cCAFoWeHDzyT0wTFJsrU1hTtRjsmtkmIYrumCctICQC4YgCIJIB5hVQJbxIW47WutLyDk5hVhgDABO7t0WWW4XJvWPbMx656Q+UY+5IeSaev6b7br7NIpBqA5YQNh3RS4YgiAIIuVRFMWwEqpoFTETN5Gq1Hqb8Kt/r47Y7gl9RlkacqkJCwhj4aZDus+JlVA9TrhgssgFQxAEQaQJvGtAXgdEOxXV2tRrJBnM+WoLvtt6JGJ7TshyIAqwHm0KbXtvMQZEdq3jJWwBIQFCEASR0TT6A/hxz/G0rpHBlwiXWkCEbbXe9LWA7DlWL93u0REgZlvbM6Fy3diuuvuIGTJOdB7OUavWkguGIAgio3lg7lqcP+dbPPXVlmSfSszw4smMCyadLSCSGFsAYQESq1Xi9P7tABgXF1u0+bBwLvYLkCyqA0IQBJGZbD9ci/vnrsHuUJXMt5fvBgA8Pm9TMk8rLpqiCBBxmx19RpKFXql0FgOSJbibNpise5LNXB8GJdDF4FcnLCDsmAGdxndWIAFCEASRQlzzwlL8a+ku3PDysojn0tUNE9DEgEROO21baNvF16WxC0aPz9cfBAAcrfXG9HpPDJYHJwQIE1h2ZEqTACEIgkgh9h4PxhBsrqiJeO7l73Yk+GzsgbeAyObE7Cw3BncK9zupSWMLyPH6Run27YdrAURaMPJN1uowU39DNL44IUDC9UjIBUMQBJGxeJu0loD/rNiTpDOJjwCXguvScVG89f/GYFIozqEujWNADlQ2GD7fIHynvdu3MHVcJkBkNUYYnbhutYBx59xYcbvJAkIQBJHxNPi0o7y3MT1dE2ofGIMJsTA3G11Kg5keNWnsgjljQGShMQD48yVDAADeRu13+tRVw00dlwWx+gzSX0UXnRNpuOw79FMMCEEQRObi9Wsn4m0hM366YVSEjKcwN+iOqE9jC4heY7mOIesELxKuGt0F5aUFpo6rWkAsCBBHg1ApDZcgCCJzMZps0gk2MUZbkR+sCrovXlm80/Fzcgq9+hgtcoPCZHzvNuq20gLzFVDVAmAGvg9RgLidCEI10ZPG9LHiPgJBEAThCN44BEhFdQMuf3Yx5q5MftwIm5SjTYgFOcZt6dMBvYm5VUhsTB7QHhcP74whnUtwy6k9TB8310QMiOgWcaQOiEv+XrGQ/t82QRBEhtAkTC7xWECe+Xoblm4/iqXbj+KiYZ3jPbW4MGsBOalna7z83Q4M7VxiuF8qoytACj0AAJfLhb9cNtTycXNiiAEhFwxBEARhCtH1IJtsFJMrz62HItN4k4XfpAWkRSh+Ys3eSs32/ZX1uOaFpZgXqqXhBAs2HcLUf3yLLRXmCoPpoSdAmAsmVtQgVINCZIkQIG4KQiUIgsg8PlmzX/O3zNxu1vden0IZM2YtIIdrfAAA8SP+/sP1WLTlMG5+dbkj5wcA1/3ze/yw6zhu/dfKuI4jfj+FOVk4sVupbvqxWTIxCJVcMARBECmCaLVokIiIpoCCbBO1q8xaShIBWy1HmxD76NTEOBJj9dBY2HgwbAE5WuvDMwu24rbTeqE4z2Pq9WIQ6pLfnG662JgRzALy0/4qzfbZn/yEti1ycdPJPRJjAaEgVIIgiMzjWJ22iua0F78HoJ2YJ/z5a1PHSiH9oVbNjDYhtswPBmqKlhInJlIzDJ81D88t3IYhMz83/Rq+R8rJvdugKM+j9nGJhw0HqiK2bT1Ug2cXbMMfP/4JiqIkJAi1LlSlttYXv4WNBAhBEBnLtkM1uPvtVfh++1F8v/1osk8nKlOHdZJuL+TiBw5UNZgKTk0h/YEmvzkLCMv0aAoomhW2ExU9nYJ91nxPFp68Yphtx+W/c2bd4rc1NAYiRKcTabhfbTwEAPjzZxvjPhYJEIIgMpbLn1uC91buxWXPLsZlzy7G1xsrkn1KhuTqmOpFE74Z87cd3UrtQnXBRBESLM4B0E6uidYf+yvrY34tu+43ndwdrQrN1/mIxuSBZepj5uY5XBN2TR2r80W8xolKqO2Lg40Dh9iQqUQChCCIjOVQtTZ24L+r9+vsmSrIRYNYH6PJRCMwXn8kOx7EbCXUXE6AiH1wjNh0sBoz3vsR+47HLhx4xs7+EhVV2p4usz/5yVRmEftu7LbalBXnqY+ZOOOFqcxF44TraurwYEp3QU78cS0kQAiCaDbYMWg6idgpldEi17oFhN9D77iJgq3Ys7OMJ8TsLLfaLVdjAYHx6y7+x3d48/vduO2NH2I+x0Lh3li87Yjm72cXbMP5f18U9ThmM36sIrMO3cRlBeVJrGf8a+zin4u2AwCWbIvfpUkChCCIZoOVVXUy0IvtKMgVLSDGguLD1fuwevfx8HHtaF0aB2o3XBNWgdxQig+rAqsoChZtOay7/+z//YTqUGDkD7uOx3yOhcI1llWhNRN4qVp7oogtq2S5XapFw+cPYM2eShzngpZrJQ38cmwIfhW5dKR9Re1IgBAE0WxIobAIKXrFnd5Yuku7XxQBcseb2loWye4p02TSBQOEV+1MACzbcUx336qGRjy7cJsNZxhZe0Sv83C3+z7WxF6ImOn8Gyt8NdRHPv1J89wRyTk5YQEZ1zPcy+azdQfiOhYJEIIgHKPW24Qnv9iMzQdjqy5Z52vCip3HbCl6BKRWZoiMFga9UCb2bas+jmYBEUm2AAlYECC5qgAJCoC9x+t0960U0pbjQYyT+e0H63T3nfqP73Sfs/JZrZLDXRvRLfX8N5FCzOOABSTXEz7m/XPXxnUsEiAEQTjGX+dtwuPzNuGMvy6M6fXX/fN7XPz0d3h7+W5bzifVLSB6rpKZ5w3Ai9eNUv/2G8R0HKuNzIb4dsthvLZ4R9T3r2poxJ8/24BNMQpGPWKxgDDRVFqYq7tvVUOkAKmWbDODldLiRtktVj6rVXIF6xDP1kO1EducsIDkclXwzARDG0EChCASiKIotq3m04Ef91RG38kAZn7/11J72rMrKW4D0bNUjOpeCrfbheJQrxSjgV92rX71zmr89oN1mPPlZsP3n/bi93jqq62YHKNg1CMcmBl9yhEnWY/BRF5RFel2ePIL48+oh5XfZa7BxM7ScJ1Igc0PBco2NPrRrU1B1P2diAHhP3u8gp4ECEEkiFpvE6Y+/R16/OZ/mPmhvnk3k7BrFdjYZJNwSG39IV3ZAuFBn1XUjLUM9mOfbzJ4b78mcNVOzDajA8Lpq5sPVqOyrhFfbzqkeZ53lew5Fume2X00tlRcK5dU7FqsfY5ZQOyfXlnaba3Xj5L86KXhc7KdcwMB8ad3Uy8YgkgAj3++EU9+uUX9++XvdmDm+QOTeEaJwa44PLuyV1KpOJcMPRdMTlZw4mGCzigGJNamZze+7FyjNyupqZsrgrU2fvvBOrzx/e6I3idNAQWeUIZJ26K8iNfHmn1i5d4wEoDhmicxnYYhLFPnF//6ATWhzB8j2H1jJ7wLJt5fE1lACCIB8OKjOXCo2ot6n9+2Ykx2ea3eX7UPFdUN0XdMEj4docVWndkmGoF5uAnYyFUgYpTqGi9MMFm9H0TxAQCN/gAqqhtwoLIBbYsiYzFizT6xJEAM9g033rN/emV1bMyIj+A5OBeHAiBuBUIChCAIW1m0+TBGPTQf015cmvAS2mY4+2/Ri0klC70YECZAzFhAWhWEJ+VOLfNtPLvY8dsYF9HQGMCJD32BMbO/QHVD5EQc66RrJZ6yySAI2EkLiNVCeg5oIE0WDFlACIJIKa55cSkAYPnOYzG7A5zEqIZDstF1wURYQAxiEEIT4OBOJWhZYK6FvNP4Q5/LjHukR9tCw+f5LBdZEGrMAkTHqnFy7zYR28y5YOyfXs2k1S68Z6L62EzQr1V4F0yssUgMEiAEkSSaQzaMXRbgXUfrUOczZ3bmEctrJwpFUaQBktFgFpBfndFHs51lM6gWEIMVOCug1aW0IKI8d9fW0TMnnMBKca4/XjDI8PmGxrD4apQIsVh/V3pulbMGlUVsM5p4nSxEFk2AdG9TiPLSfJzapy3G9miNHm2MxVws8C6Yhjhjs0iAEITD6A2IehkPmcTXGw9F38kkzyywXvEyWRaY7jP+h/F/+gr3z11j6XWsZ8voHq01sRzsMVvRGk2AzIqSm+2OiAGZ2Led6XOxs4GdldTU7CiTLC9EGyW/ofwYRafexx3YsQQf3zFes23b4ciaGwyzjfdiQXbMCVyBuu2Ha+FyufDKDSfizf83xlTWkVVyKA2XINIHPX99LCv65oyswFY09CbqWItVWeVfQgn1aDALSHaWS9NAjgkpvhdItGPkZLsjesjYlelhlSZLabjGz9dzJdLrGyUCRNKULR56tC1Eeal5y5FTzegAbYAxo0NJZCaQk9j5uUiAEITD6BWNqqhO3ViEWFi67Qh+Y3HF7zR6k+jgmZ8n+Eyi0+2+j7E31E7e43ajTYvICqAsANCotDovQIoEAWKlK66dHXQDFiblaO9a7+MFSKQLoDGGxntG1p7cbLelgl6JtoAkOtBYtCq+8t0OzF9/MKZjUR0QgnAYPQuIEwNUMrn8uSWOHj+WKqZWymvbxR8/Wq8+NlMsasfhWny5oUKzLTvLhccvG4pr//k9pp/UTd2uNiMzmGS9oedystwRMQNGwasijYEA8mGPNcFKefJoXxlvVWqQCBBfDMLJyNpjtZqokwJEFlTKu0R4d0yieDBUVHHzQ1Msv5YsIAThMHoBg7Umc/mJIFa1hKIohhPL9sO1GPXQfKyysfpnZV0jXli0Xf27bVEudh81Dkad8NjX+AMnWoCgqf2UPm3x48zJmoJ1S7cfBQC89b1+bxzeAtJCsIBYaWK3Mo7W9iJWJuVosSe8WJO5MRdvtV7PJFphNyuxRM4KkMhj8iLz7EEdbH9Ps8jEYDRIgBCEw+i5YC5+Wr+jZjrgbfLjaCguY8VO/ZbpdmE1JCHa/hMf+xqHqr248KlvYz8pgY/W7NP8vaWiBic/+hXW7rXWE4dNKsV5cguKUdEwFtycm50VkQVjlD0j8u6KPab3jYYlAaKzvVTSAK7OFznp7ThiPfsoFreNHuFCZA64YCQxILwFJC9BWV8vXz8qYlu95LuIBgkQgnCQ91fuxe/el/d9Sfcs3EufWYzhs+Zh3/F6U2Iq/qwKa6+Pt1NnLPA1EnjueGulpeNEywQxgreAiEGLokWooqoB76/cK52AR3UvjfkcRPwWUlP7ti+Sbpe5s2STnt7rjdCzlL1yw4kxH8uJIFTxmP07FGssIHYH4Ooh67IrE4PRoBgQIuF8sGovPli1D3+9/ARTPvJ05q63VyX7FByDdbr935r9pvbne3iYQUxftqpf7MziMIuebhBdIdHQ6wB7Sp+2WLjpEM4aGFmbgsELEFH0iaLskmcWY9fROuySuIlY5107sBIDotfqXlYFVDbptW4hf70RegG3p/axHlPBrrETKbB8DMi5Qzrg8ctOwCdrw7+/PE9ibAqyuJj6Rj9g8dKTBYRIOHe+tQpfbqjAE/P1O3MS6YPZeiZWzP9Ltx3Bsh1HNdusChAr8Q52odfrZFCnEkvH0bOAnNitFQDj4FZegIixC6IoY8Jj7sq9usexA9UqEGOjOEC+6l4Q6pR7Sp+2eOaaEQCgZhLFcn48YkCnWRHJNJ7TFpDOrQpCVi7OBZMgC4js/ozFAkIChEgae4/F1jY7nWktrO42H6xO0pnYx2frDpjaT1a1Usahai8uf25JRFaN1SyYeetiSw2MB71gRavuJ72Jmk3CRlkwLEgzNyvSAqK30t8uKaxlp4DbFOd9XpSXbVgFdOGmQ2qK8s4jddh2qMbS8UUX1OUjy/Hiddo4h9tP62XqWKoFxIEiePzEfyTUUoC3RlhpPhgPMktmysSAVFdX46677kLXrl2Rn5+Pk046CcuWLXPirYg0JgXbhNiK6EJoV5SLFb89Q7Ptjx//lMhTcgTmiomG36QF5GCVvFutlTn8qa+24FfvrI7YLgpAu9Fb9Fp1B3l0enhES8NVFEV97ni9L+KamTmPSf3bA7A3MPO7rUcAAE99tTWm1y+697So6bB5XPzNRz+acwsyRLHVoWVehLtIXPXrVThmly0ea48evAXkPz8Eg4Q9nOiQWYmcQPZdxFJY0ZGzvemmmzBv3jy89tprWLNmDSZPnoxJkyZh795IMx/RvGiycVBLdUTXBFvBvTQ9vLI6lKbFyGIJKDVrAdGLE/BYGFz//NlG6fbFM043fYxY+HbLEel2q7e9XqxMTmiS1XOP8PdcZX1jROVTPgZkxU6ti4vB4gjsLEQWD7dN7IWSfE/UyZUvwf74PGvuXbE+iszaIn4lejVm2LGc6AXD/zbuO6sfAGBrRdjaoxcEbTey6yPrTBwN2wVIfX093n33XTz66KM45ZRT0KtXL8ycORPdu3fH008/bffbEWkGn66ZhBpRCUWs0shWRBP7hftxnDs0eXn7VjhY1YC/zd+MipB1IpYAT7MxIHqmazsGdKdXiG9+Ly+9rlcCXU/I6Ykw1QVjQoB4stwRmVb893bx04ulx2CTGL9YqKxvxKTHF+DPn22QvsYsT1x+gqn9+A607GuPFsAcTwCmKLZk8Rvid6L3G7AScGsV/hqw8vAndGmpbkuUC0YWEGxV9AEOCJCmpib4/X7k5Wnr0+fn52PRokUR+3u9XlRVVWn+EemFlcmI37M2w3uheIVOkfygdv7QjgASt2KJl5teWY6/zt+Eq15YCiC2+ACzAkQvfdbtAj5Zsx+3/usH1MRQxM1qRUs7iTZZiejFkjABsmDTIamLxMuJ3hPKW0bEzbCJ1sgSySY5/vjvLN+NLRU1MbtQOob6lXQ32Z11zlXD1cetCoJusxyD30phThZc0F4zK1Y68fuRBVlGC+hlhMvO23+/Zbkj4z3aFIZL9ifKBVMoCchtVxzZOiAatp9tUVERxo4di1mzZmHfvn3w+/14/fXXsXTpUuzfH+mXmz17NkpKStR/5eXldp8S4SAbDlSh52/+ZzqjhR8TyooT28Mg0YgT7tZD4UA/Zg1JF5fUmlAhrS0hc69RfECrAnmGhlkXjJ7p3+Vy4ef/+gEfr9mPOV9uMXUsnmlju1p+jV3omeutZAYBWhHV+/5P8LEQ61DNCbMJfdvhylFd0K4oV+0XwiZNo8ylbFWAhM8t3oBKZg0026m2JN+Dhy8ajEn92+Oq0V0AGAvIV288McLisHT7Ufz89RXYcyx6YTLxfh4VyjbiEa+BnngMN96L+raW4RcxssVLMi0gp/S2nrLsyNm+9tprUBQFnTp1Qm5uLp588klcddVVyMqKPOkZM2agsrJS/bd7t36JYSL1uPfdYPOxJ+ZvNrX/i1yZajvbfaciZvpL2Bnol0g+XL1P97kfhEBbhmkLiM414d0Y0VIte7drofn7wfMG4FeT+wAAfnfuAFPnYSd6n8kom0WG+Ju59Y0fNH+LTcFaFeZgyYzTMXvq4OB5hO5Jo/vOI7k343UnsBRNK4WyrhrdBS9cN1JNLc3J1j+HEV1L0bOt1rpyxXNL8MnaA7j735HByCK8mPjXTaMxpHPLiH3ES6AXhMruUycsIHxgK8v6aVMUDqwuzElMaS+Zhc5sOj6PI2fbs2dPLFiwALW1taiqqkKHDh1w+eWXo3v37hH75ubmIjfXuumGSA2s1gqY/1N4gGxosp62lU4YVeKUrTLTifvnrtV9zuVy4ZZTe+DZBds028266vQmZf5aGYnX6oZGbK7QpmFePy489uRKYgWO1HjRWtJ91gpG1iy9wVkUAoM6FeMPFwzSPU60Dsqyeh5ut0u931iApJHwYQKEn5Tj0R/+gKJ+ftnK2SzR3JUulwvti3NxsEp7jcykujNx3KtdC4zr1Ua6TypYQHghyBYxBTnZWHTvRORkuR0pfmYW0eVsBkftNYWFhejQoQOOHTuGzz77DBdccIGTb0ckgZ/2xx6z09CYnqt/sxjFSchWmZnELyf1idhmVoDoibJ53Ore6EivfLfD8Ph5komswYaiW0ZiUq9Rl2gVOn9oRwzvEmn+Z8gGeb7Z3YYD8smWrcbZ+xktHFgMCL+PlWZsInwwtlkXjIzC3OivlbmKjtU1Rn0dWywYFQ8TJ3dZYHEgoKhuZkcsINwxeTHXuVUB2hXnyV6SMGKxgDgiQD777DN8+umn2L59O+bNm4eJEyeib9++uP766205/oYDVfj3st0Zb8LPRCYPaK8+jqVwTTph5HKQrTLTBT3TMwBcNrIzAPlArhcHIaJnSThcE17ZGqUv1wr31YlCTxOZBcRsjRIjjKwKZi0gWVEmranDO0ds220ixoGtnMMuGP3Pq4oVzoLHT+zhOBJzv19eyMQTdF3goHuBXRejYmfiLS377fL3uCPdcDkXTDxizg6Gcdk3AOCNYUHpiACprKzErbfein79+uHaa6/F+PHj8fnnn8Pjsafvx1lPfINfv/sjPl1rrgIj4Rx8ulyFTgEpHhbRDmS+C8ZoxS9bZaYKDY1+VDXorxqve+l76fZF907Eo5cMBSAffMVaC3qYsQoZxRKIfVTEM5FNglZjMWQYnbeetU9832jlu9u0yEXnVtrg7Ze+3RH13DyqCyZ6DAjLpOAF9Ofrw2Ntoz+AFTuPoe8Dn+JOE032mJBxueKblPXcN3zzuVjXpOyzGp1fRBquRMTxv3knBAh/xETFe+ghFvVLGRfMZZddhq1bt8Lr9WL//v2YM2cOSkqs9UIww7p9lLKbSvzdRGYCP/A1ZxeMbJWZKpz95DcYMvNzVOqYrr/ZLG8Fz/ehkJnszc7xPolbQmRgx2Ld1xutYgF5wzg7vgejSf2n/VV46OP1EYO0aCUzM2mJE/G4nq2jviZsAQnFgBhlwYT25cXR1xsPqY+bAgpueW05AOCDVfrByOr+fnu6w+r1YnnvFydFfW00azmzuhnVGolIw5UckxcgTvSC4S1XybaAtBFipo7U+CwfI617wVjtDZEq7K+szxj3A/8b/M+KPVH392kESGZcAz2MLCBsQpD14Eg220Lpwou3yat66hEtBdDsJP+hMKmt3nM8Yh8jf3O0iqkyndDYFP9YIh5jaGftouv5b7ZrssCASNFiZtISYwt44Tc8ZBa/4/Te0teoMSCmsmD0Kn0qOM6J02i/47AAiW+6KcrTWtCX3T8Jq383WVqTQiRasLeZ4mHiUzKL3gHOCuyEBYQXsIlKudXjV5P74tQ+bdWmfYu3HcEv345uEeNJawEiFp5JJQ7XeCP81D/sOoZz//4Nxs7+EuP+9GWSzsxe+EAssfKnDH7Fl+kCxCgr4t1QHwe90t3Jgo/vYALKbKxVtE6cZoNQ+UwpINhcTMTMCt7KeZitUWIEP6nffHJ3qRVoi5CdIwoQM1kMYo+R+95bg4WhrrAs3VVMQ1brzjAXjMH1Y98j//vkxVQgoGhW39GCD9UAzzh7oxTnaYVGUV42SoSaM3qLUlbHRg92jkbWM7ESr8zCyZcjj2aJiwX+foknMNgO2hbl4pUbTsQQrtPzvPUVlo6R3gIkRfVHoz+AkX+cj1EPzdc01pr6j++wdm/QbXS01rq5KhWxWpK7sRlZQMQBakCHsNtANqmmArKVsdn4iFgm/lgx8jdHqwYpa2VvNCGbhRdF957Vz1TqqrgyNxP/IrvO1/7ze2ypqFazYMTJj72GiWKZVYmRnxN8Lf/7HNCREyCKoploo52zmQBPM4gWECvHW6TjNgSCAvuZr4Mp41bcJrL7mb28Q4kzGSmpmDQXS/YLI60FSKrCmydHP/xF3K2oUxk+On5oecuo+/uaUQwIG6DatMjBLaf2wAvXjVSfk02CqQA/mCzbEWxWZjZQNtqKzKwAEQ8jRttHOyfxOfFdx/QohYgd2Ujs3u7UMh/ZWW7p9eCttruP1uGyZ7X9WKrqo5eYl5UJB4BJjy9UH4tFu5g7gMUtPPw//Z4u+RILCG8FE2MfogkQ9ny8Lgm+14tbJ6BVz1jHRJWMz9YdxMbQGG2UhdSPW0AA8vuZ3XtOuUdO7K6fop0sbjw5sr6XWdJagOg1eEo2Yp+KV77bYZi6mM7wv9d2RdELOfEumPpGf0anUrNJrby0ADOm9EfHluHsBVaZMtXgLQsvh+pp2JWpY3WSn35SN3x732nSyqVGqy7xfcRVrUwY2JEFY3XyOfnRryK2mZmjY4kTYX/LJs3HLh2K6Sd1wx8uGIj/3XGy6oLhXar8NRW9VdHuD/abF7OTrMJbtvSsH3pFxHoJLimeDQfCyQxGQajd2xRi7i9OUgWy7H5m18Kpniy92hXh07tOxvIHJjly/FhoVxS7tSetBchzC7dF3ykJVAspjP9augvPf5Oa5xovvAm5jmsu9/32o+h238e4790fhf21g1U85rtUx29Q3IiJkU4tU6sfjmwyibVa6+/PH4gTyluq8QhmRHhVQ6O6ij25dxt0apmPlgU5EfsZTXpi7I1spfz78wcKr7HBAiJMPrJMne2HwzEgfAq7FWQWEDHmQ9RYTI80BRTN7xQALhnRGTPPH4hrx3bDgI7FYQHCBcrzwkW0gOw4UmcY78Qmaj3LjVnMCJCZwvfK8BkEGfMdjKNZaYZ1aYWuoS60svvZ63dWgABAv7LiiAyUdCWtBUiqlrGWDY6zP4mvjXWqwg88y3ccUx8z0/Jby3aj1qvvLzZTvKY2hs6nqQAbeGUrblnH0VRAW/0ycpsVrjupG96/dRxatwgKCDMWkD9xvxPmCpAJuC826Ae7ieOCbFK5ZIS2oJcd34PPH5yw2eRzz5l9ce6QDpp9DnOpil1CExmPmRFNtkhvJYi0iO6uIQWiKMDfuL5N08Z0jThW2AUTviZaC4j22Nf983v0uv8T3fNlY0S8aal8Mzo9oaDn2jT6fvnS7WbiStxqSrOBBSSJnZfTCbpKDmCHOTdd4Ad7b1NAuhLiA27FySFa5swr3+3AwAc/w3s/RE/xTTXY+CRGzwPhASrVKqHy927/smL4A4o6scaKkflfZD1X2j8vlGlhNXtCTPft1jqyBXxhbjbO4cSBLQJEmHyK8jwR7qNogfNmPJKye0b8HYnuaX7C/okr1y47FstwYcc8XOPFDzvDi4uDOgUH9QpDhi0g9rlgrLpuZSngMmFtJk6FCSmZBcRpF0yq8vTVw2N6XdpdJf7GE1cXqYJZy8yuUCZEZX0j/vDf9fjRIDI9VREHbrEJGKAdDCNdMMaT24MfrgMAUx0tUw12r8oGNbXWQoq5oPhBef3+Kvzti82qm6xdUS7+eOEgvH7jaNw6safpY7IVoxkBwl8pVnDLbP2Iel8wpoi5U7q1LsDZg8tw9+TIvjQA8NRVw3FKn2ANAztcMF7J5CO6HXi3S6xZfDKxVN/o17h8xF1460M954LZdTSyDk2+4IIZ+cf5mu7DvxbcqozffiBvUKgKkDjrgPDXtarBmlVUrNHy1YYK9HngE4yd/YVmu5W4wsfnbYrYFhYgyS0SlmimDI5tLk47AcKPYakavyhOKmN7yCsV/vHj9Thc48VVzy/BP7/djvPnfJuI07MVMYaDDXT8QMv2afQHIgpvZXIMCBvMZBMNK5aVatYy8ft48ovN6qDqyXLjmjFdMb53G9x+Wm88eN4AUwGX2RYECD+xsIlQLzCQt7ZVVDdg0MzPMP2lZeoC4KxBHfCPq0egOE8/4yjHRlcYf50Y4qq/ZX5kPAuPGVGyene4psXz1wYzqxoa/ZrPMLKrNluCF8E13rDolzVv44NQZanyrFCdyKFqL/ZI+tKYqTJqhnjcGmKdl+tfXgYA2F+pteaYiVPadDC4yFrOWYUY7PdMLhhzpN1V4k1pqZoFIw5meoPbwaoGjPzj/JQpKS8Gp8XyGjaB8QMei/O44eVlESbfTK4Fwm5V2SCfDjEgDDah82Ijz5OF68d1R9fWkXEMIuzzm2lGxxfqUmNAdAbzOu7e+Wj1fvgDChZsOqSOETkmJjy2Km+0MQ1XEywprPqjVW82k57Nu1tYX5iGRr9qxXn+2pFoJfTp0LOAyGIe+CJj1RYtDbLS7I0m+qyYIZ7CW0aWRj57L16XqNNpuJlG2l0l3lRqZ2EjOxFXtXU6ZddX7zGuzpco9h6vx7MLtmLA7z7D+yv3WnptnVf72diEygeXMjeLrIdIc7CAyMZdtkIKKKl1H8sEiJFfmwUxGmV0ZBsE7RmhxoDoTFz8vcf3CWETnpmsC2aJsrMQmdYFY27SvHxkOc4Z3AEXS7rdivDXgw8YZat8FvTLw0/+0dIm+UZ/YkaflXNj+G3KgjHLLaf0iNhmdO/xY1C8v8XmGgMCmEshF0luO70Y0ERjp864rdLQ6MefP9uo2SbWBUklpr24VCMM7np7FS4c1sn069mPN8/jDg6CocGfj+3YfawOI7tpiz9luV3wB5SYWjinC2zBL7OA8INxoz+ALHdq+Ixlrd3F7A6eq0Z3Re/2RRjMlWMWUYtgWbT2GGXBAFrrWxFXpptNmmYmf48qjuK/D9lvIZd3wbhdaF2YgyOhQGzeCMSPX7ed1gvlkqwYGa1b5KiZG3zAaIum4DUQrS5A0HrgdgXfs4yr0jl5QPuIfbPcLuRku+FrCli2gMisHOEy54kpXT24c+S9aOTq5LPs4hYgzdgF8+19p2H0zI8svSbtrpJfI0BST4EMnzUPe47Va7bxAmThPRMTfUq6bDtUo9vZ1AyBgKL+4FrkBk3HqgWEW1X88u3IAFK2Yo2lhXO6EI4BkQgQbqBOFTfM4RovfvfBuojtstgGRpbbhTE9Whs2BAtX4bR2Puz99Ez3fJooP28wN45sItZ7DztS+mtCk3Ux50ZxuVxYPON0TB0eFPX8+MWua8+2habFB6CtppoXCnb0BxTVNePJll8v5m5i+w3sWIzLRpZL92XndkAn40UPmVgMu2ASM93kS3oSGQUZ84taqwJEzMaRBSI3FzqUWK9plHZXiQ88S5WBm4d3t7QKNUpiaah5Hje6mPCZJwozzeOM4FcVbAXqkwgQIDK4iwmQTC7HHlAtIJHP8ZP5lwY1LRLJ8lDpdRFfaPCOdVUXDkKN/l3LamPo+f55q8Wtb/ygPt4WCnQ2YwHJtjMIVacIVU62G+2Lg1aHJokAuWp0ZC0OI/jLkceVGK+sD1l+dCZ6JuRYdstZA8uiNr+7482Vls4tS3KPNNpoFWAxMv+9bbzuPrI29aJrsV9ZkfS1ZuKUNPsL41pzdsHEQtpdpWe56qepKEB4xAqOuaHVSvc2kXUJkoFV86oIL0AKc4OfjfnS64W4FzEKnZljm4MFROaC4Vf1d761KlGnZIheTBILFI51UDUq3CSy62jQBTTrAnlFSx49qwVblZqKAVEtIPGNJQ2NfrUys2yiFZvBAfZMVjlZ7giBq+fqYOfA3EEeE+9rNUZLZgGxMzBz9YOTse3hs6VuFobMAiK6YPTGYKsWkC2H5N2NneiEm4mk3VXiJyy7elQ4hdienDVTSpXy2099tSWu1/PxGwU5WguIaF1p9CsoLw1/bmZytmIBOVTtjb5TCsEmwgRZnuPm6a+3SrfPX38QQOwTpVHhJh5+8Dcy17Pz0Cv/3Wih9wibrOOtA/LMgvC103NVAYIFxB8ZM2IGflxxuVwR44weWaHP+lOo2JvRJMmst1MtxIMB2jouDLutAtGsNjILiJht94lO0TSrAuTON1dp/m7uFpCLh1u7X9LuKvHmxVSroSCWDBcVf16UugaJZpmOyd0svMmZfVa2AhCvRZM/oAbOPTdtBEpDaYLbDkUWLtPjDx+tj+t8Ew0bzOJJH0wFPmcCJMZVnVkLCG+FMHKfMPddtLgNKxaQeMeSJ7jy5rLJh72PLAbE6mT15BXD0KW0AE9dFaw+Ka749YSFaJ0wSlM+qWcwq2nP8XrdfWTI0pl9qlUgMb8D/nqwYnaiRbaFTsySVQFysFobI8MWyM01DVevF48eaXeVNMF7Bg2GkgHrHsoQz47dlL87T/4lJTpy+tYJveJ6vY+L+meDXo3XH8xuEaxTWypq1P3bF+fhox/3AwBeWLQdQNBa0PM3/8PgBz/Tfb99FgfDZGNUij0dcdoCwguQ84Z01N2PTTCiW0/EzISXbYMLpkKYhGTvK7WAxChABncuwcJfT1RLyYsWkI46FlZRmBhZQD5eE/x9fr/deJFSmJOFB88Ll5uXpTMn2irACxAmNESLbBtJqjJgXYDwVnhFUfDv5cGWEfHWPElXrC620k6A8J8v1SwgYrrt6t3HNX+zgULX/5jgrJ54BwRm1szlfvC/fX8tjtf5IvZ9MSQ0gGDsifhDX7evCv6AgmpvE3YclldaTMWsJyOM6oCkIpP6R6Zk8sQqkGWTrwzeDWJ0b7LrKtagETFT+lu13MWxmHlj6S7N37LVLxNh7/6wB1sqgr1YvDYFZzLXLgCM6yWvugwgIlMpXl187diu+HHmmbh+XHeUqUG2EgGifs7EpJrncS6Y3NC1EV0wehNlN4vxeXzSwbG6cM0UvX45hJa0EyB8Ke9UiwGJNtHkcf0BZPn3iZ5g4636x1YV+TluTUnj77Yeidh3BFcaurQwcvXBDxB6wbGpWPfFCKM6IKlItCyVWAUrswBFW10yi4bLpb+CvHZsV/Ve++v8yF4cPGYsIEwsxBMMLct6EWGfR1GASY8vBGCfZYCPeTASM1uEPk1GX8eVJ3aJ+r41DU3q5zqlT9BlI3OLsdiieJvRmYW3gHiE1GOGV5IBeNnIzrj/7P4xv+8xbuFFQajmSLurxK/SUs0C4pKGYIXJ5VYqstVmIvXHJ2v2RxRMs8rhUFDo8bpG8L+3lbuOR+zLi6sBHYsjKmcWcf069AZkqx0wk41RHZBUhA8Inn5St4jnYx1U2fcZ7ffKLCBm27bzE+qwLi0jnjeT5cGsd/FU5BXPV3adxH3mfLnZVDCoGfiFjZVjGS14JvRtG/X173FVk5krSwzm5WPBPlhlrcpyrPDXgDXRE4Pdxe97VLdWePSSoREl7K3Af8dm7+HmTtoJkEtGdFZ/HKlmAREtCuJqJJcfKHSKBSWKn//rh+g7ReHeUFfM6oYmTUbMP7/dHrFvbchcPrp7sCLq/ecEVxrsd8p/l3rfayqVLDeDUR2QVKQhZAWYNqYrZpzdL+L5WFfq7L6PNsmrJbslrpNLRnSG2wXcMK67um0Il4opKzpmxrXBLCCidcAKooVL1npBDIh97POw9cZWC4iFYxnp+U0Hqi2dQ45OLA3fG6a8VeJrIHl1ygKI96LZTCIj+HErzYaqpJF2AiQ7y40/nD8IQOrVAREnTnGFwftq9VYqZroxOo1ZSwPv84wmDljZbLbiZMFh7Dqw1SAQLv0tkipN+8xiVAckFWGrxDMGtNeIZUbMAiR030cru89+zzJT/Z8vGYK1vz8T3doUqiKEZWoA8oBUM+fL3H2b4xAgortI7Pgs24cn3owJfvI0+sxiozujVXrv9vJCXTxPXjks4lji9/CbuWvUx7LusYlCjAERm2jGKkD4gmZeISCViE7aCRAgbD1INQuI6Efu1a6F5m+Nb1JHgESL7E8EsfSuYZUeefjBsNanTU/jzfKKouAJzp9vtFIW03tTmXSrA8K6pMrqKACxT5Rm4yzUuhiS93G5XGqtGfXe4e4TWR0PM+6I/TZkVoniQua+Mprs47WAaASIwWe+4ARtZlGPti109gSGlusX+gKCZdzPHxo+nswFc6xWG4x+68Sehse0E+bifeWGEwEEq+NuPhi06nz84/4IC4WseJkej0wdrD5uCii48rkl2HaoRuNitMOi0hxIk6FRC/uRNQWUlLAYMHiLzJRBZXjmmhGam5VvH643UNjRkyJezAq7MwcG41guH1kubTPes20LtV14XUg4sMklNxQRryjB7/GUPmGfs5EAefLLzbrPpRrs1tSLATmpZzhj4bE443HsQA0q1hk8Y63jYNYFwzJRogmHsHgN/55k1lAz58vHicS6ahW/X1mhQSMLSIGO4DMLL9iMxIx4DieG3KHyc9JmzLQuzMGjFw9R/xatKTmSkvbDZs3T7PN/k/vqvp/dvHbjaGyffTY6co33zvjrQnib/Jqy/QzeOh2NK07sgttPC5Yw2FJRg8XbjuBnr6/QjJvTxlorr99cSUsBwg8aqRSIyqe5PX3NCHRrU4hBXJfQj0O1LwADC0gKWHXMBuQdrgmucMb3boMbx/eIeD7LHV75hS0gwcGWHyh9TQHNoM3/kMVxe2uFPEU3FYmWhvvXy09QH8+JsyqtHUTLyog1XZQN7tHuK5/JMtbMCvb6knD6qyyjy8z58tVSY40x4uu8vHz9KGmlTjEGgaco16P7nBl464rRteP3uyhKhVNRFA3oWIzT+rdT//7ZqVprRrieSvAaso7EjAfO6Z/wYGxZldiahibp79GqxULcf9PBcJ2jfmVFaNMi19rJNlPSUoDwA0sqCRA2ifIrDb2Vj7g6Y7ulQlyLWQHCun+WFubgjAHtcaFg4s1yu9XPH44B0bpggGAXVv5zawWIUL0xycG7VmDWOb0YkFSrlqgKEJ1JzExWiQzVAhKl+aHZtFS+pgxDJh7MuGDG9QrHkdhRh6d/h2Lp9nd/2KP7GtZHKVayTAoQvry9XjM2veNku12a70V002WrJe2D36FoRRUtKolCPE9/QJFeIysuGCBy/O7ZttDWnjfNhbS8UvwA6aTF4NO1BzD7fz+ZXhmxVdiFJ4RXF/zgwKcKioM5ews+tS1ZmK2JwLIm2ApX9Clnu11qRgPLgmE/Tv66nPrnr9WOq4AgQAQBFy3VOZUIZ8HoiVDtPZDswDW9bq6MWC0g4RgQc0GosaSlyoS7mdgK3kIZa/gVEy4l+R5pLBQAtCrQT+80UzLeCN6yYaaAGwBcz2UTmSEn2615H/GOVjse69zDVlwcdiIKiyZJlWYAqLYYWyb2KurUqgD//TGY8dNc+8DEQlpeKbfbpd7wTlpAfvb6Cjy7cBv+u3pf9J0RVv+8OuYnH770ud5g/sgnG/DuCv3VUiJgzceicTyUBcP8waIZPMvtUldGqgVEkl0BaCcQnz+AD1btxadrD0SUMY/XX55IomXBiAOVlcZ8dhMIKKr5nJ3XGzeN1uwTdxZMNBeMaoGxJjIr6xqx51hkMKkZszovhGO1gPhD965Y24bn6jHOxQTwk6HRtbthXHcU52Xj2rFdLX+XO4/Uaa6VeEu7hWJz4rVMVlCm+L56TQfFarbREIOKi3Kz1ZTjZTuSl+2TbqSlAAHkkfBOccBkWV02gPM/VP5G5c2BRqu8LzaYEwBOwdcoEFm3rxInzf4C/162G5X1QQHCVneXjuis2TfLFRaKO44E26zrmSd5AbLjcC3ufGsVfvb6iogKhp1apUYnYTNEqwMiDmK1vuRl+PBCnv22TuqlnVBjt4AE7/uf9lfhhW+26e5n1gIiVhF+4gv5/WpmkuXFYawxIEx4GwWatsyPL87DCD5t2ejalZXk4YffnoE/XDDI8ntsOFCtqc8iajV2L7NrIV7LZFlAxO9EL8uQD4I3g5gqrtfcjjAmbQWIRw16cl6AmF2PsT4I/CCQpWMeNYrQH9lVPzrdCW45pQdmXWCui+Gv/r0a+yob8OtQETIgbAEpLy1Ay4LwQJud5VI/PxOKP+ySrw7471FWR0G2X6oTTsOVf9diUF603iZOohEgejEgMQoQ/l7/48c/RT2HaMLh9tN6a/4+UhPZewgACixaQMTASbP4TQiQXAcnYM2CJ8p3FI+7h/944r2bFToui3sSLQ16ls9Eo2cBuX5cN0vHEQVYuqTapxppe9lyTPqVE4mslLTe6sRoME905czubQoxbWw3U/vKVun8oMZHf2dxMSCMJdsi+8QAgI9rBmZ0bVKt9osRbGIyG/wfS/0Vu+CvKy9AeGtDrO4vZimLBrMgRhM6LfKCq82iKKtOPeGn2YfbZfb/NkTdXwZzNxh1Pe7TrsjyKtssfBVXq+4rK/Cio1WB1qLDPnuqWUBEZM3yAOtBqGIhM6MsJ0Kf1LgrYoClz+kp2mTABlB+QuYnYH4lyK/yerVrgUlcipvTpU3EYEcrq6LdR40LN/E/5Gy3K2JVqNehlLdsyCZiVvQonQTIC6FsjWgtzRkNcTREixd2XT1ZLs3EPfP8sGWMTfxWGdq5pcVzMFcHhHWTjUew85Pqoi2HYzpGwIQFxO124dUbTlQLY9nJgo2H1Md2NkF78bqREduevHIYHjxvgDTgHAgLDzEeLFWas13/0jL1MZ8UYLV3ixivJSu/T0QnbR1XWVnGUdfx0hSDqd8fiAxC1TYokltAHr5oMDqU5GH+TxUAnJ+IxNVJrAWmgMhiRvxKx+1yRfhK9YoffcgF+i7bETlhM2GTSmnXZpE155ORTDG9IlQmWyyEx2dviO3czWK2wVejQSVUHmah8TUFq+jaVV8i1m7U7JY0Y3E51QkrCPe2dk70p3MNM1kVU776KU+WIEDEMSZVKpNXhBpoAsAdp/XG9S8HBYnVApCiK5mPVfvm1xPjOMPmRWrI0hgw2+I7VmJx7TRKmmllaTJiwvt6hO3lpQXo0aYQAHBUx6dtF7JslVgRTZd81DkfA8K4cXz09D/ZaoIF8PKumnTh5xPMlaCORfTaxe1vrpRuz8/Jwq/O6IOzB5ehp0HpbjtolGSRyeCth41+xbb05VirKptxwejxwa3jYnpPHv7zx1qrRY/XbjwR143tGhF3I8IWGmw8FmO1UrEfUiknjFsVWgsSniZkNX2zOWw965xGgfLJJn0FiDv1BAibQPhVPz8o6cWAsJXTtlDw5QuSQkt2Iq70mGC65ZTIaqbREH27vABxuyJjQEpjbHetCpA0soCM7NoKADCU69oqMqZH2CL01cYKx89Jxtq9lYbP3356b/zj6hGOn4fXpAuGt5D4/AG8v8pcmnw0Yh1KzLhgeH59VrAk+WOXDsXQ8paxvSnHCdwxPDYHkJ3cuy1+f8GgqGm0TGBsPVSDg1UN2HOsTn3upJ6tMbCjvEBbIujRtlC6PdfjxrPTRmDmeQPQr8za+Z3Wr53uc4mu+JrOpK0AYRObEwJk44FqDOf6GMjKPMtoUoPouNRbTxZKC3OQ53FrUkj5QTYvwRHikf7Z4PneeHLQOuFymS+KJVpAxIZ7om811oGIZTT4khgnYRWZRUzkXzeNUR8//42zwlOPFUnsUsrTaDILhr+ndh+tM9jTGjG7YCx2Pf7FhF7Y8cg5uERIW4+VP3E9WpI1+bHvZH9lA0Y//AVmfxIO6H3j5jGm3FNO8dL0UdLtOVlunDmwDNMtFmUDgtc51sUUESZtBQi7oc2KAyvM+mi95m+zqZ+yCcftduG7+07Dqt9NjkjPndS/PYZ1aYm+obLIM6b0i/fUTSGamtnKTWwQZwax1DFvEcl2uzQuKEA7QH50+3jT5xx2waSGBSQQUPDG0l3YcKBKdx+ZRUwkHveXXSQ6tblCp66O2Tog/DUTsxHiIVYBEraA2HYqltCrvppI1u/X/g5qk5hSLtK1daHU0pQbZ3G05P9y05+0FSBMcTvRDVcc1IwG6EZ/ANf+83s8Pm8TVu8+DiDSD5vnyZKaMF+4biTe+/lJ6oA6JJQt0Lud0752eYS6h+uzYnZSEvP7xRgQo+jylgXm/a6p5oL5YPVe/GbuGpz1xDe6+6gr+hTJANCjexu5idpObj45vMrUS8s120vD5XKp19TONPyBHY1b0OvBrLDJWuWnQoaJeI+LMRLJRuaaivd3SZ6W+En+nRsjWQ5aQEQzplGE9FcbKrBw0yE8+cVm7AqZg63klPPvxRqtOT3JirnwTCTwA5nZmhSiBYT/7I1+xTCzw8rqvyDFLCA/7jGOmwC4ujApMEEYwYvN8lJnAujuP2eA+ljPTWC2DggQtirZcT9MP6kbgNiFWDxBqHbAu3yTNSmKVXNZ4bWzB5cl43QikI01VL00+aT2yGiAk0GorMsrw2iQk71/rEV3mDVh55E6XTN1LLy9bBeueWEpqkKVHkVRwCZI3lpx99urTcWBiPEr/Ir0Pyv2YHNFte5rrQzYahpuiggQM9Z6VvbZyAWTCvDf2Ws3jDbYMz5YkTo965rPpAsGCN+r/LnrpXhHo7y0AEDsY4nVIFS74QVdstJdRavVmpBAF5u2JQvZPRVvcbRY09KJMKlxd8SAkwJEHEiMLBIlEjdCrKY93n1x4sNfxHQMGfe+uwaLthzG019vBRA5AbDBXCzKZOReYOTnaD/rt0IxJ6PutVZM1iwwcbUJy0MiMCPO1KDkKIPwQxdZ781hJ2wSn9i3Lbo56I5hVTr1rGJqMzoTqaTSSsgxDgVMH8bcjM5iEGomIn5nH6/ZD8B6gS+nEBcBJfmeuAN251w5nFJu4yR9BQirA+KA5BeD0RoNVt2yCTZWUeR0ueKnv96Kbvd9HFHFj/9x8uJp40F96wVDdDd1bBn+QV55YhdDk7BoAenaukB3351H7Mt2sAMzX7EaVJltPNBN6t/e8HmnsTLxxwOztMkE/exPfsJ/Ql2gzRTGOxyqlbPveLgyrxKjAsmKM56MfZxUCCjWSzl1Gj2hkQrXBIjMRLOjdszgziVYdO9pmm1zf3FS3MdtTqStAAkXvnHeJF/doB8PIRv0Yo3hSFTL6pteWab5mzdPDjaoWSErlCVGkvMl5TuU5GmuxdWju2j2FS0gv5jQE910RMjJvSMrSK7bV4mbXlmGTSaEkt2YmezU0vxRLCD89Xeqro0RYQHi7P2XrVpAtPfRoWovnl0Q7pJrRQg9wqV7xjqnuOO0pibbBQMA/71tPP45fST6tC9Kyvvruc1SxgIinIedvzK+um2XUv1FFBFJ2goQNQg1AeWrP113QPc52fv3ijGLxWpDpFjZV6mNL+F/nGKGQrf7PlYfy4SVeM6XjiznHnfWXJ+HLhqs2Vd0VblcLuzQsXQwHzNvJbr0mcWY/1MFrnlhqfQ1TmJmrmoyWdmTfz4Z3X6ZG8PpbB12fDFwXLyvYj2PWEcCNaMujV0wgzuX4LR+ybOk6QqQFIl/Es/DzrPi75p4U3ubG2kbRcPM97EOGkYM6VyCDQfMraplq6ZY0/kSZQER4QcPmRn6cI0XbVrkSgNAxXPO82Rh++yzAQQFhdGqUlzp6gWlDulcou7LnwMr2c73d0gUbyzdFXUftS6MyeZqQHAyTvR9oKa/OuwCVDNXBMFRL6S9x5pWGqtZnQmHWDPqkl0HJBXQE9mpEjTuZKoyP2ZGSyEntKTt1XIyDVdcybQtytXZM3LFOueqYTG/r2jCrawz18Y8XvhmYbLA0OOh85DVXJBZbVwulxrgZbSij+iUqzOIlRXnqavigJIcN0UsmO1twgepbtifeHeSzx8Uck5bQJgrSrQaVgkuTjP9TGSFpRQEO7jmedz42xUnmD6veAPaU8ECkmz0RPa/l+9J8JnIcdIVxN83qeJyShfSVoCwycqJQmTiCs3olhIHLbOtx83A0mad5KSerTX58LL034ZQp0dvo0SA5BjfQlYG9Ql95f0VsrNcGivBL99eZVsDMqfwBxQ1JiFaFgwv+h79dIPBns5gtgBYvKguGOH39frindL9jLhGiCcCgjEgp/dvj7Uzz8QFJ3QyfV5Z8bpgUiAGJNmkerG9yK7crW07Nn/fUB8Ya6T2XWNAvGZTI9gK7coTg/EMRiZ+UawU51nrqijyw2/PUB+/+X10M388DOhQjH/dpK37IK5GAcAb6r/ilfRhESuhipjNUpoyqAwl+fJrl5edpTGhfrh6H/46b5Op4yYL3vJjxQ/ekIReN96EZcHIXTBDhMBnM0JIdluxTVYLv7GxJGYLiNqCoflOPnpWPlbkLdmIgeCPXjJEZ0/rOBEG0FywfcRpamrCAw88gO7duyM/Px89evTAH/7wBwRszlbJdrAOiKyEtp41gndLvDR9lLQuiBX4Bkfvr9wb17EAYwuRJ9ttSrGztF0xfReIrIQqcv/Z/QEAN403bvjEBIZsFZnryYoY4N5ZkRqmXUAee8ALYyv+Z5mVyWkSZQHJztK6YKobGhEIKChtoXVxmhFCsiyk62Oc7MJpuDG9POml2FMBPevPZVxQejIRFwF2NpJLF5dwKmJ7EOqf/vQnPPPMM3jllVcwcOBALF++HNdffz1KSkpw55132vY+TjajY+mTfBW/ozU+qXWDDd5nDmyPiQYtmmOhf4f4W1jXGjTrkvVHyHJHBo4aWUCiBUxeOrIcp/ZpaxhHA4RXEW4XIL7Lgo0VEUKpXXEe9lfaVy3WCqLgCCjhYlYMvnaMFQGSjCyYRNUBYYXIGv0B7D5ah9MfX4CJfdvizIHact1mrpf4s89yu3DBCR1jOq9wPFls1z6Q5FLsqYDeQsbpe8os/D1VnGfvtGc2YYGIxPa7Y/HixbjgggtwzjnnoFu3brjkkkswefJkLF++3Nb3YX51Jy0gZnoseNXVo32ZC33aB9N4y0ri73JpFIUucw3IPiazfByt9UU8ZyZ1uF1xXlRLCzODy/YT04YBYFTXVurjCX0ja4Q4iSh6ZaKBlWF3uazFBjghqKPhTVDTPGYGbwwo+NfSXfA1BfDZuoMRn9nMpCX28RjUsThm/3u4qGFMLycLiAGpkhXC/wbtrvbLsvEI69h+d4wfPx5ffPEFNm0K+uhXr16NRYsW4eyzz5bu7/V6UVVVpflnBlZd0okVI1sJ8VU99dx8Tqwe2eD6r6W7sPtofBVAjSY02UpTVsOEWT7+8NH6iOfsqt7Kxgezq0i+WV6iA+D2H9cKIpkINluGXSTWVXw8MLdPIguRPbNgq7pdzIox832eO6SDpptyPJN/3JVQQy9rzhYQPVLGAsLdH+Wt7C0WNpJbDBHWsP3uuPfee3HllVeiX79+8Hg8GDZsGO666y5ceeWV0v1nz56NkpIS9V95uTmf4aYDNQCAj3/cb9u5MxqbgiMK7zbQM8864T//Yddx9fH8nw7GdSwjC4hsZf7MNSMi3CXMArLnWH3E/mIzulhhq1ez8wi/6kh0ENg5T2p75MhEXrgTrrkPdOWJwawOu66nFVhQaKKyYMRFg/jbMjNpuVwuvPfzcNnreAJAM6ESaqqSKtkxfGDyyG72Coa/XTkM00/qhgX3TLD1uM0B2++Ot99+G6+//jreeOMN/PDDD3jllVfw2GOP4ZVXXpHuP2PGDFRWVqr/du/ebep9vt9xFACwuaLGtnNnqF1M3S51MvY1yQenZaHzcMp3H++gZnReshLh3doU4qXpozTbVu06Li3DDsRvdu5XFiwdfdGwYNqk2VoKLDUYSLzbotqrjauRXZu/f7kZgHnzLBsfF287Et/JxYAvZOFKVBZMo2DxiMUCAmgtePHU4Ii1qOHCTYdwyqNfYVGoAWNzd8HIrKepYgHhFwJWs6Si0allPmaePxBdWyenD086Y3sQ6j333IP77rsPV1xxBQBg8ODB2LlzJ2bPno3rrrsuYv/c3Fzk5hoHKMo4Y0B7zFsfn3VAj3ATMbfuqo3BBp9/L9+DRy8Zavu5ROsjEg1jF4x8wBRdMxsPVuP/3lkd13no8d4vTsLOI3VqwK0sbZe1WfdkudTJq54XIAkox2+EbOVsNUvn9SXBlOvvtiZDgCQmCNXD/ZaGdi5ROxuLvy2z58Hfp/GU/I61ENm1//xe83cz1x/4+I7x2HSgBufNWaRuSxUBcoyLX2vO6dKphu13R11dHdzCpJmVlWV7Gu55Q4O+8rE94isoEwgo+HbLYU0PFN5/7+Ei99MR4yBU+dcvCpNBnYrx/qp9tp4XoyAnW5PtIxNMd5/RBwCw+aGz8bNTewLQ9qyJNXvBLswEpSaDFTuPYs6Xm3WtVwxvgtJwmWB4Yv5mVXwAWjEJWBEg4fs0LguITSn9zT0GJDc7C4M7l+DRi8M1NlJlsl+w6ZD6OFXOiXBAgJx33nl46KGH8PHHH2PHjh2YO3cuHn/8cVx00UW2vg8LKlq87UhcA/6by3bh6heW4rJnFqvbfFwWTHjVZjw4/fqsvjGfg8gvJ/VRH8c7uRpaQHR+iKIFJJFR3qxj7tmDw6mZ/MRYnB802v3ITWDJzsMXLTBLtx1N0ploufjpxXjs8014z6CeTEOjH+v2BQO/neyXAegP/PW+2AQIL6DjCQNihzFbNE8PqoIZhK8NlCrXhM9STJUGeYQDAuTvf/87LrnkEvziF79A//798X//93+45ZZbMGvWLFvfhx98/rcm9kDUf4VM3xu5lu7hAEK3xmwsg8UwDO4UWwM6GXdO6q0eTyZ8DlY1aGIgjDCMAdH5IYoTQJ1X+17TxnTFoE7FePwy+11OM6b0xzPXjMDsi8KrKN43L0t3jiYOnUYUide8aL0773u/CAdUyuqtxMP6ffqZZd9tPaw+dtwConN8sVZNtN45DD5WRFaYzCzxVkINHyeul2cMBVGKEyYD/p6K161N2Ift30RRURGeeOIJ7Ny5E/X19di6dSv++Mc/IifHvspzgHbyrPHqF9uKBp/m+tRXWwBoK6GyQVNvIvc5VEOhT/si6ftuqajG6Ie/iPA/6/HRaq3r5OTebdTHemZrcaX66boDmr/btMjFR7efjKnDO5s6ByvkZLtx1qAyTUVZfmUuWx0n0gKiKErEBGmHAOIF7AGbC6zplbgHtK0D+tlQ+M4IPYubKHDN/paybZpU4k3DZTTnZnQ843q1wYAOxao1MxXgF6zkgkkd0lYK8jdRPOPGKVwRqz9/thFAeELxZLs01RtlhFuZ26v62ST3mTD5fxiKxfh+uzkz/ytCoy/emqA3cUfrRpqowLLpJ3XD5AHtNZNzrmRySlQWzDMLtqL7jP9FCI53loczt8RJ7N6z+pk6Nn8/z/5f7A3p6n3+iO/VqHEf/4xY3Mtu9GKOPhIsmGbN9vw1iysNVy1EFqcASdvR1F7yPFn4350n46GLBif7VFT4+4PSpVOHtP3J8CueIzX6zeKiIVu1MLGR7Q67YHw6q1y1kZfNFhD2vit3HcdP+8Mm9Hh9qteN7aY+1htwo32WRAmQmecPxHPXjtR8Ztl7RwuytItHPpELg3d/CGe8iI3WupSaK3rEf8bdx2IrPlfV0Ij+v/sUPX/zPzwxP9ysz2hiZSXjWfVdJ2Ep6yJ8oPR9U8wJNkB7zeLx67PXxmtJS5V4ByISZlEmUou0FSC8GfyJ+ZtR622KaQDxS4I8NS4YFgOik03iVAojP6Bu4WqdxGs+PL1/e/WxrgUkigCxq/ppLMgsUf6AgvdX7sVtb/xgOjbGKUQBEktcRawL8cVcCu8T8zerj40sRD5ObDvNN5sPGz5/x2m91Cwnq8RT2yErhhgQ2X1ILpjU5c7Te6uPqXVc6pC2AkQccAbN/AyXPbtYZ299RHP6Z+sOaKpYRgtCdaqTKC8CAoqCyrpG3P7mSrXuCAB8taHC0jE/u+sUjflRL1sjmonSzr43Vtl7PLIaa1NAwV1vr8JHP+7H60t2Sl7lLFdxvm5RqMbSp0ZW0MkMesF/foMYFbWVfApkBmTFIYISXQm1VhJ3Rpb91KUgN/zbSHDhZMKA9BUgwq9dUYAVO4+Zfv2XGw7ioY/Xqy4Uxi2vreDScI3rgCiKotYwsNsCwg+GigI89vlG/Hf1PizlYj/+Y7HYVd8yrRnyQFVswY7JbDA1oW9kx2H+Wh2RNMxziimDgqnCLXLDgZyiBcTKyrxvyEw8oGNswaB6lisjF4zaSC0Bq/fpJ3UzfD4uN0o8QahqJVTzr5EFvpMFJHXR9mQiBZIqOBt1lgQURTHli73h5ejdefk6ILIYkOWc4LE7BoRPnWwKKNhxpDZiH7EkuAgfEHnNGPsi0vNsDri1QqFklc+Lw0SubopCbb3592/kSva3KtDPPpExvGtLbDxYrevuixWjlT0LSk5EZsAD5/THy9/t0H0+nnOI57WxFCJj/ZF4SH+kLnyZfLKApA5pawHR453l1qwCRnii1AHhJ/hcm+MieHN6nsct9Z/7otSL4FfjfDbG6FBp83/fMjamc0umBSRfIkAqqsNByFb7ecxbfxA3vbLcVCBz+2Jty4D8kBDj7w2fP/ydvG3x+vLt6mNBryS90cTK4kMS0cckmjUonjiOeKwnqgvGwr0jq9VCFpD0IMl1CwmOjLOAvLVsFy4bZa6jbjSys1zIyQ63EBfhJ8OCHHsvJT8YFuqkRxqVWQe0EyNvnn/7lrFo9AdirnyZzP4O+VGsL1ZrOdz8atAS9sT8PMy6cJDhvn3LinGwKlzSmcUs8EGeX28MP2818p5vVx8LjTpVc8VS5zxMnKRCGXGzBchkRLsvjMi2yQJCAiQ9KMxNvUJpzZW0tYDoZWLwrezjxRMlDZcFsJpNtbQC3+tEL4iwR1vjYEVeoIguomjiY/NDU/DNrydKn0vmMCuzgPDEWsvhSG10CwhvcWrTIlct4c2LnrKSvJjeH9BvV28WPdfNez/s1a0FklpBqNbPYfKA9shyu3DFibG7GGOphOqViDoKQk1t/nDBQFw+shyn9LYeGE44Q9oKkJ5tW+CknpGN6PhKn/HidhtnwbCVqhOD90pOSDUFFHSQTGz9o1SuZAIp2+2ybGL3ZLlRriOsElX4S0ZelAycWGs5mIlrYQHL43u1wfu3niS1gLDV9MiurSyfg167erMYfS9isDUjkUGoAPDYpUORm+1Gn/YtMFAItvXEEEj65JXDsGTG6TFnDgFa4WPWgia7nlQHJLW5dmw3/OmSIQlxNxLmSFsB4nK58MbNYyK2n9rHHnU7qFNwcFQtIJIBx6ky7ABwwQkd1cf+gCJdHUYbLNk5291kLJmVBKMNHrGmUpqZ/Nj1vPHk7ujcqiDcxIx7T+buiCVQl31PsTYgNLKc6IkTFjOTqO/0khGdsf4PZ+HzX56KKwRXaSznkOfJQtui3Og7GsC7n8xa0GT1ZmheIwhrpK0A0cNMEOJRE6mabHVrVIrdqRogAPCXS8ON3poCAWmUfzRLhCqQbD6/E7uV2no8qxilc1oJQuVXsQs3HzLYM4j4fbN7hH9PFhsQjwDhM2msoBeECui78dg9lEhRyd7r6tFdNduT5QbitadZAdsgCUIlCwhBWCPjBIgZ8/VzC7dFbJvUX1tfgk34OQbN6LzqhGR/UFN2llu15jT5dSwgUSZbFmBplwVkaOcS/OniwUk3Yc48f6Duc1YsILxVa7+JBnBeUYCEJpxXF+9UC6Q1qBYQ69ec3XN6waTR+N0Ha3Wf01vZB5IYhCreR8nqUsr/Psy6F+VBqLadEkE0CzJOgETLDAHkYuLqMdrVGJvw2eD07oq9uu/lVFYIH50vG5yNVrw7Dtdi++Fg7RCrqal6fHDbeFw+KjU6XP5yUh+0LozssFznM1+Kfc5Xm6PvxKF+31lBwbn3eLhnyzlPfgMgPDHFkpWhumBiiAE5XONFrcFn1xNm/iRYQPRIlgWEty6azUCSu2CSfw0JIp1IewFy0/jumr/NZBCIw4TLBUzs204zELGUwHAWTEDTFA5wXoCwSeHX7/6IjQerI55fvlO/I65doiMVJiYZd07qjeUPTIrYvnyH+Wq4ry/ZpT7u1DLfcN86X5NaOZbVfNl9NFwW/nhdMGspvhgQ487LRhyvM3Yr6gmQZLhg9IgnDTcestwutYiYWMlWDypERhDxk/YCRCwvbsaEyqe4AuHKeKO42AZZX4o/f7ZR8zcrRuRUYa5oK8JvNh+OurIF4kubzUtizY9ouFyuiMqoQzqXmHqtmJa693i9YSO7f3y1VX3Mgo5lbpZ6X5Puc9FghbiYJePtZbswYtY8rN59POprr3nhe8PndV0wCQ5CNSKeXjDx4HK5LFufyAJCEPGTurOLScT4BjMuGL3CXou3hbuJMmsIvyL6Umj+5nXcBRP9uHNX7sVv318bYTrmAyzj6Y8ysV8wNqZdnJkGTiFWzzQ7kX6+/mDEthteXqa7/3auFD6zgIjF5/wBBc9/sx0A8OOeSlPnoXmPkMts4aZgQOy9767BkVoffv2fH3Vf09Dox5aK6qh9ffSCUNltkwoCJBHl4PXwuK1Zn2RpuCRACMIaaV8JVRw4zQwgYrOv84d2jNiHHdeoL4eTabiAfEC+anQXvLE07Dr4v3dWAwBOKG+Ji0d0jji3eHnoosHoV1aE84d2suV4diN+/0ZWDJ6Pftwfse07rp29CP8u7PsWLV8HORHANw00y6drD0i3G6WG9vvtp6aOrXcMfyjgNRUqodrlNowFT7Yb8PlN12ChNFyCiJ8MsIBof/WmTKiK4Z8A+IyE8LNTh2snYW/ID2x3HxiGbFV63dhu0mJrB6u1K2CvxEcdCyX5Htx2Wm90aW1/tVc7EFedX208hP2V9Tp7h/nv6n2W3oe/r1SLl/D18PdRtxiu1yl95EX07MhiOqCT5cN0arIzmwCgVBJUnCjUPjymLSCRAoRajBCENdJegIjjhZkBRIwTkU1GbPLnYwX6l2ktJ2ELiDO9BWSfJTvLJa/CKMyGfJ2C4V1a2n5uqYJsbp7+T31XSqzwxcFY2rW4YOfdfy9df6Ll9xDrYjDscPFd+fwSbD1UE7Hdn8BuuDLumxJukjiwo7n4HScwqvcjQ2atirUKL0E0V9JegHyxQevLN+N68At1FopCMSF8MzI2IPNmYfHYzMrgVAzI+6sihZHH7Uadryliu2hBr24I75PJ46LMdSDLGIoX3jTPrG78/VCcl60RIN3bFFp+D5a6WyTEKHlsEgfySTPkgkkBC0gyyVZbLpj7sRyra4zYFkv6NEE0Z9JegIgTkJEfnyFaQF6cPgoA0LZF2ATMBqQruSZX/ARzvM6Hf34bDDhMZHv67CwX1u6titjOX4Vth2pwx5srw89l8Nyi5zqwezXKu1RYxUs+sNPbFFBXz2XFsTWky5YIG8B6cKOsbxAQmfkDcC6YJN0kSQz70GAmBXr30Tq898MeNPkD0t98rAXkCKK5kvYC5JZTe2j+NlNmnZ+c8jxunNg9mH7LZ50wC0jnVgWqCOEHpzlfblEfJ7I9fXaWK2qK51NcyiiQ2dH5eq6DaKb03habl7Hv+OrRYUHKW8e8TQE1LiDW+0G3G67Fr69lgTyWQjbZs8+QrCJg8fZxsQszabgTH/sad/97NV5fshNdJTE+ssJ4BEHok/YCpFe7IkwbI/ed68EsICd2L8W635+lbucHYd4kXZwfNInzFpBFWw6rjxNpAcnJcuPuM/pEbOc1hiKEw6VChoNTPHDOAADAhSdoM5n0smG8TX689O12bK6IjIcwgsXd8IGSgzppYxaY2ytWAcKsbgFFK5KtekfE2igMmVGITbjJEqkXntAR08Z0xdNXD0/K+zOMul4z2Ljx7dYjasE5nq6trbvdCKI5k/YCBAjGbnz+y1MAmHM3sMG9R5tCjdCQWUAA+cpUtgJKBNlZbtw0vofhPmKX3ItHpGYKrR1MGtAeqx+cjIenDtZsP+EP86Quh4c//gm//+963ePJXgMA/1sTTNut4orY/b9TeuDO03urf6sCJMasFT6ji7/XxADjaOjVuRGFKcAXIrP0FraRneXGrAsHYcrgDsk5gRBWqtAqioJ6H7lbCCJeMkKAAEDLAo/6OFqbejbIiIF3WgtI+NLkqOXYw8cd1yucMmk2cM0Ost2u6C3phdO5dES5fMcMoSTfI+298s7yPRHbXlm8M2LbgA7h7Ca9SrqHa3wRr8/zZOGuSb1V0csEiCdGCwifbstPhFYLhOrdjTIhE+4FkzFDQUxYCUL9busRHK7xOn1KBJHxZMyo0zI/aBpXFG0GiAw26IrxA/zfvBhhE8qb3+9CfahMNr9QXro9euBrLMh0hl5NCH5y4QXYr87okxI1HpxG1grdbDGw3u3D8SDRVsBizJHL5VLvhS0ht05uzBYQriurn3fBWPv++OJ5vDCXWUCaktgNN5XQjb+RwDc8ZBlLsto8BEEYkzECJCfbjYKQ7/t4vXEgapPOqk/rjol0wQDAy9/t0BwD0M86iBfZWkwvXZKfP/j4AbFUeXOiqiEyVVLGb88doD5ubJKvgAeH4j1Gdy+VPg9AzYqKNaU1y+1SRafGAmJRHLQrzsX3vzkd8+8+BR1LjJvsBQLJdcGkCtkxNgJ865YxuOO0Xnji8hMcOCuCyGwyathpmR9c7R2X5OjzsAlarKLKzOwA8D23euZN6kdCplfeynD7aeE4ADsZ07216X35SY/PzkhWh9FUoGupNk6nQtIv5aGLBmmyF/TqyLCg1rzs6EXn+J5CVmG3VS23yrYqaM4cWIZ2xXno1a5IY8mThbfoifHmhsdiHRBGz7YtcPfkvmjdIjWyeQgincioUYcJhWipuMy8LQ7s/Cpw+c5wW/dD1WF/b1ZoQGcD9yUjOqNjlFbusTLrwoGm9/39f9fjdx+sjdhuRxnvdOH9W8dp/uatVEdqvDjx4S8iXpPlcsHlcqlWriadWg5MmDhVdl/kr/M2qY+NLCBiwOvZg8swZVCZ9LWywyQ7CDVV8Ki/6wDmrT+outMY9T55VlUiM+AIItPIqF/PziN1AICf/2uF4X6s+qMYA9K7XZF0/+U7ImMJAgkoYa1Xz0GPVxfvhK8poHHdJKu+QzI4obyl5m/eFfWJTqM3Fh+jZkHouGDCojUxP5kPufYARuJAFEzjerXRxMPwosMoCDWTa8WYgQn1b7ccxs2vLsekxxdonl++M3IMuPLEcmnsEUEQ5sgoAcJoiNKITc/sXM6Z7PnGc7x5tdYbDHDVs6LYSSyBgf6AojG1NycLiAhvAdFLr2XXmFnP9FwwTTqiFQDOGNA+rvOMhp44CASUiNoe4j0T7Q7SC8hubrDfyQrO8skju32K8jyRGwmCME2znJ3UQVdiHfjg1nG4YVx3/JHrC9OXy5J4fcmu0DGc76EhZq/wwa6XjewsfU2wHDTFgADanj+lhXIfPbsHonVDZYJTJugKdAp/OY1fMiuK90y0FXo4Dbf53icA199H0ugRCKZci/y0P7IlAkEQ5mmWAqTJYNAdWt4SvztvAApywsWcbpQU/vIrCbCAcMd+/tqRWDzjdPXvR6YOwaJ7J0a8xtcUIAtIiI9/3I/th2sBAPk58uvArAvRuqGy7TLRKlohTunTNqbz1UOvr41su2jJiGoBURLrWkpV1FLsOtdaZkH7ZvNhyZ4EQZglY0cdo2ZkVs3O+cIKNxBQ1IHKSdM1b04XdYTb7ULnVgURZdnFFVxzNq3X+vyY+NjXAACfTmwHE3nMBaOXBcG+b49komZVUhl/uXRoTOerR0DHfSTbLgriaF48P6XhAghbwPQEiGw8aZcifWwIIl3J2GHHTE8HK9aLcb3CKbF3vr1K7YTqZJEv/vz04gBaCQ2wDlY1aIJQKUguiF5sB7uu0XqBMBeMzAIiTk588S87sGIB4TO2AO33/9f5m7C/sl56jOYehMr69/ACnrd6yNxdf7hgUMQ2giDM0zwFiF8/oFCPwZ1aqo//u3pf2CSfIAGi50rxCO+/62idZuBsbtPKkhmnS6tS6vn2VQtIFAHSaBCE2koQHPG4vR66KHJSkxll5q0/iNW7KyO2i24B8WxnfaTtgxNIgCsxHZA18OOtYTLLSKp08iWIdCWjBMi7Pz9JfaxnSq9uaFQLRVnxey/cdEjzd403WBfAyRLW/JygN6ntPFrn2PunI2UleThb0tiMCYtJ/dtj6rBwhhMTFEYxIHxmkayyLL9t5nkDIp63QhtJQSuxt9G2QzW4+dXluObFpZH7Cit10bLBF9sDeMtORg0FlhHdrECwczJD1l+KaoAQRHxk1C9oRNdW6qTdpLOSveK5JWqlVCvWi0uFrJOG0ODkZPAebz7XG+y+F/qd3PnWKqzbF47Ob46mddnXyirYNjT6sYsTbezysAlYFivywPtr1McyFwwvWqaP6x7TOTMOSqq1iq6WzUKRLJ4hnUs0f4tfv3i/GKUXNydkAoS3msksILLMGIIgzJNRAgQIm5JlPlsAmsnZitlZHGzY4OR0oa8rRpXj1D5t1V4kImIQKgBUcHEAzVB/SEvxP/Z5sLLooi2HNVaGRjW9Vt8C8ub3u9XHsiDUUd2C/WFaF1orHCej1htZcVO8l8XVuNsFPHrxEIzv1QY/n9BLeM74BkhEMHU6IEul9nICRGYByUtQVVyCyFQy7hfEBlyjLBjGRz/ui7oP4/yhHTV/s8HJaQvDIxcPwSs3nKgb7Nq+2LgRXnPohCuiJz4Zf7p4iPqYmdlZFoRexglDJjj/dPEQ3HFaL8z9xTjJK6zxM6HbLhA5+YlnmOV24bJR5Xj9ptFokZutec5sFkxzqpgrI19izeAtILJ7qjmnuBOEHWTcL4gNqHpBhzxlFrrYFuZmY/vss9XeG95GNnEld+CWmY55CpqhmZj/7ovyghPy6f3aAQAm9G2LEi5olO3LhFpTlGZksu+7tDAHd0/uiy6tCySvsIYsa0kURaK4Nsp0Ep/r217bbiDRJeZTFZk7hc+cEq95p5b5lIZLEHGScaMOMyk//L8NUfe9enRXS8d2uVzqSpFZQJKdPZBnEAhXmJOlugeaE9pUyuD/7UNic1h5K82+hSGLQXYU1x0jGWnNoiZinXkZRoHQYgEt0dJBMSBBDlRGxt54G/UFyLf3nUYp7gQRJxknQBjzfzoYdZ9YzM5McKzafVzzd7IwsoDMuWp4s3TBjO8VTsNlEwerj8G+83vO7IszB7ZXLSNq7JAJ153TiAHHogsmQoAYfMeinhKFBsWABBkkibHy+cPXmb8vutlg6SIIIoMFiBl0Oq8bIg7UyRYgedn6AqS5+vXH9myNxy8LViNlE8e89UFB+t9Ql9lbJ/bCs9NGqtkvzIqgVwkzkYjN7URRVC8IEKNbUBEiRsT7lWJAgvRq1yJim8wCMrp7KebdfWrCzosgMplmLUD6dyiKvpOA6CtP9srR7Xbh7MFl0ueym6lf3+VyqVYQ0aWy4UC19DVZoQnYb1DALlFsEdJsxRiQ57/ZrvnbmgVEe09QDEgQWQyI1x+ZhtuqIIeCTwnCJpr1LykWH64oOFLBxfGPq0fg07tOjtjenDvhujmXCh8HcftpvaT71zQ0AQA+WB2ZGdWvLChUn756uN2nKUUUSbwFZPmOoxHl1q0IkCbB7Ge1L1JzQpMFw9o3NOPfFEHYTbMSILKOllYRNUuqDNz9yorxwDn9Nduac3VL/nsJKEDPtoUAgHG9Isu0A8CCUKXblbuO6x6zRV627nN2IhYT4604ry/ZGbG/USq46IIRKwSrQag0sUbglRQiS5XfO0FkAs1qhtIrz24FUcMkOwaE56rRXTR/kwUkSFMggIaQP99s+ey9x+vVarqsOFmiTO9izAcfhPr+qkgLjaEAEe5XsdAaTaz6aC0gqZH1RhCZRLMSIHodUa0g+uNTaUAqyMlGeWm++ndz9lXzqamBQLjgmJny2d9uOYxxj3yJXvd/ghpvkzpJJ0rQdWtTqPk7WmqwlXtQ/A34KQZEF74XDAk1grCfZjXqNJooThYNMUki1Qak3UfD7dZT7dwSSZZgAWEZDWYEyKuLd6iP/zZ/k3rfJErQnSs004uWrWWkHUTpIhZao4lVH40FhIQaQdiO7b+mbt26weVyRfy79dZb7X4rKbK22gwnLCCp3OytOVtA+An1YFUDqr3BIFO9/h1v3DwaQLAnyDGul8yOI3Xwqf1iEnM9zxpUhpeuH4V/Th8JIHptEsOOzFFcMJSGGwm7R2TN6EioEYR92D6iLlu2DPv371f/zZs3DwBw6aWX2v1WUt64eYzuc2bKs0cjlV0wIs15UuG/l0mPL1Qf5+rUTSnOC5ZnL8jJ1nSMzXK51EDNRLlgXC4XJvZth7LioDstmgvGSiaWKEAaKbZB5eM7xuPhiwbjomGdAIhBqHSdCMJubBcgbdu2RVlZmfrvo48+Qs+ePXHqqYkp3lMa6kgqW+l6bRAgEXUVUtjK0FzrgAD6KdayrqdA2LpxuEab4up2I+EuGP69gejZW7IOvgwxC8YndHhlh27O9wpjYMcSXDW6iypSyQJCEM7i6Kjj8/nw+uuv44YbbtCdELxeL6qqqjT/4oGtBmVWa6OB2ixiWexUHpCacxaMHnrfl561yO1yqdlTiRYgWUJn57V7K9XnLjwh3J2Zj/sRKW+lLRvOZ4LxVV9pZR+GZUrxQahqDAj9pgjCNhwdUd9//30cP34c06dP191n9uzZKCkpUf+Vl5fH9Z5sHJWtGu1wwbBYgvD7pdaAxFdFbc4xIIBcgOlNtDk61yrL7VLdFIl2afHF1ADg3L8vUp/r3iaydLiM+8/pj/OHdsSfLxkCQFuIjI8tIbEaJiebYkAIIhE4OkO9+OKLmDJlCjp27Ki7z4wZM1BZWan+2717d1zvKa4aeewIQhVJtTgLfoWbaueWaGRuBT1LnJ5YU5Sw201PpDgFu5cDSmQDuiKuKNoFJ+j/vlq3yMWTVw7DqX3aAgjeH4qiIBBQNL8HsoCEYd8zf33USqjkqiII23CstOPOnTsxf/58vPfee4b75ebmIjc317b3dbn0XTD8iubWiT1teb9UG7j/eOEgtfFaoifMVCM7ywU0Rt9P3VfCip3H1McJd8FwFpA6n74AYQG0RvCxSou3HsEv/70K3bl6IxQDEiZHdcGQBYQgnMQxAfLSSy+hXbt2OOecc5x6Cyn8+KAoimbFy1Y0XVsX4J4z+9nyfqk2ILUvzsP3vzkd2VnumHrdZBJWBINehdS9x7m6KslywShKRPwSL0CKTJSI58/9qheWAgAOVoUDblPsNk4qMgFClVAJwn4cESCBQAAvvfQSrrvuOmRnJ6Z/BoMfIPwBRTPwrt59HACw80idbe8nNgZLBdoV5yX7FFICK+KwyIQVwZNgK4HqggkoEfFLLXLD55tvoriakTXMk+Vq9mKVhwmQY7U+dRtZQAjCfhwZUefPn49du3bhhhtucOLwhvADqeiGeWL+Ztvfb1Cnkug7EUnBTpdJttuV8M7HTO/4FUWTkQFoG+Pl6hRX4zG6FqkWSJ1sFm0+DAD4busRdVs4BoSuFUHYhSMCZPLkyVAUBX369HHi8IbwAwRfNOzbLYdtOf4L147U/G22uRmReGqEjKVovDR9FADg37eMjXguGQG9zAKiKNrJENDed3rF1TTHMpg47aiPk0m0bpETsY2VsCcLCEHYR8bNnvz4wAuQl7/boT6+Zoy2a6wVJg1oj0tGdFb/bu6prqlMZb3JCNQQE/u1w45HzsGJ3UsjnkvG98yLht99sE7zXA4nQHJIBNvKmQODqew92oaDdNVKqPR7JwjbyLhfE29OZmbTep9fzQwBgNeX7IrrPXhhQ4N/ZjJtTFfN38kQIHoun5nnDdDEdJAVzl5YtVx/IBj8e+FT3+KzdcHxgywgBGEfGTdyuSUxIH+dv0mzz9RQr4dY4Wuc0YCUujw3bUTMrxW/1qNcQGKi0GsyN31cd41LyIwLhjBPvicYX1Pn8+P77UexKhS8DlAMCEHYScYJkGx3pAXkyw0Vmn1OCRVlihXeAkLZA6nL5IFl2DDrLJzcu43l1yY64FR6DpJ7q00oPoGfCMkKZy/5IQtIg8+P6gatG48CdgnCPjJu5HJLBMiWihrNPnkm0haNiNIdnUghYv2uDVvcJwhZ1i8THnxKcHOveGs3zAVT7W3CEcHytWjzoWScEkFkJBknQIDwIB3Q6SJqJm3RCL3jEpmDaAEZ1Kk44ecgE0FsG98UzaxY+tsVJ9hyXpkOL1rvn7tW89yQzi0TfDYEkblkpgAx6AcDhDtbxgzpj4xHNLWbKXduN7J4AyY8eAuI2biEgpzEFgVMV5gFRMbQ8paJOxGCyHAyU4C4jQVIl9YF0u1mIQtIevHAOQPQujAHD543wPRrxDndjk7KVpHFF+0+GiwNz4sOs3EJP+45bst5ZTpGGU8UdE4Q9pGRS6JoAqR9nKXK9Y5LpCZ9y4qw/IFJlgKGRatCvdCNNlEM6FCM9fur1L/zQu5DfiI0awGJN/aJoCwYgrCTjLSAsDHCH7JUtMjV6qyS/PjM6WJQK5H6WM1WEq0KDUkSICf1bK35m63O3TFkwVwYZ/o5QQKEIOwkIwWIGoQaslTwhZr46oax0qlVftzHIFKbSAGSnHLl2YI7IMBZ364e3QWn92uHISb7EbUujCwxTliDXDAEYR8ZKkCCH4tZQHj/fVO8AagA7jy9NwBgUv92cR+LSE3EMACxGVyi8Bik2D500WC8OH2U6ZoleZ4sdI0z/qm5cO3YrtLtqVAfhiAyhQwVIMH/mdio5pqS2RG/MbJbKZbMOB3PXBN7pU0itRFdNt5kWUCEYiBTh3fW2dMcvzs3HIh77diuKMn3YNYFA+M6ZiYyqX976XaygBCEfWRmEKorXAdE9N3ff05/W96jrCS+QFYitRF9/T5/cgRInlCzJt77l8/wGNG1FX5//kCq5itBr78OxYAQhH1kpABxc1kwe4/Xq9sX3TsRnVuRCZqITqOQdtuYJAEi1qSIN5PFo2lil0XiQwe9wF7RIkUQROxk5K+Jr4TKr2RIfBBmeW7hNs3fN4zrnpTzsLt4WE4218QuzorAmYxegz/SHwRhHxlpAWECpMmvqHEgYiouQRjBxw29duOJGN29tcHezsFbQOwQQbwFJI+66OqiZwFJhR5BBJEpZKSeV0uxKwqaQkGn5LslrFDECdaTe7dNWsfZWl84hsnnjz8TR+OCIQuILnoxIB7qPEwQtpGRv6ZwHRCgKRD03RulMxKEyJmDypJ9CgCAGq4d/Mpdx+M+njYGJCN//ragd21yDMq0EwRhjYz0S7h5C0jIBUPBY4QVfnvOAJTke3BRkquHXju2G2b+dz0A4KXpo+I+Hj+BUml2ffQsXkZ9YgiCsEZGCpDsrHAl1E/W7gcAHKhqSOYpEWlGSYEHvz3XfPM6p3C7XdjxyDm2Hc/DB6GSBUQXvSBUcuUShH1k5AjELCBNAQVPfbU1yWdDEKkDbwnUm2QJ8/11CIKInYz8lUXrhksQzRU+8LQwlwSIHmTpIAjnyUgXDF8JlSCIMMV5HvztihOQk+W2vcYIQRCEFTJyBCILCEHoc8EJyQ2sJQiCAMgFQxAEQRBEEshIAeImAUIQBEEQKU1GChBWc8xPMSAEQcTIazeemOxTIIiMJjMFiDtcB4QgCCIWTu7dFlsfPhtlxXnJPhWCyEgyWoA0kQAhCCIOstwuKKBxhCCcIKMFCJ+G26tdi2SdDkEQBEEQAhkpQNReMAEFLQs8AICnrhqezFMiCIIgCIIjIwUIaxjV5Ffgawp2w82nxlsEQcSAC1QVlSCcICMFCHPBNAYCaPQHBQjfhIsgCIIgiOSSkQLEE8rDbWxS0OgPxoHkUBttgiBiYEyPUgBQ3bkEQdhDRpZiZx0/6xqb1G0e6m5JEEQM/P78QejepgUuHNYx2adCEBlFZgqQkAWk3udXt5EFhCCIWCgp8ODOSb2TfRoEkXFk5KzMglBfXbxT3UYChCAIgiBSh4yclVkMCA/rD0MQBEEQRPLJSAGSk0UptwRBEASRymSkAKGUW4IgCIJIbTJSgFC8B0EQBEGkNhk5U3tIgBAEQRBESpORM3UO1fwgCIIgiJQmI2dqsoAQBEEQRGqTkTP1waqGZJ8CQRAEQRAGZKQA6dQy3/BvgiAIgiCSS0YKkA4leZq/y0tJgBAEQRBEKpGRAiTXoy1ElpNNhckIgiAIIpXITAEiZMFIKrMTBEEQBJFEmoUAuXhE5ySdCUEQBEEQMhwRIHv37sU111yD1q1bo6CgACeccAJWrFjhxFtJ4euAXDe2K84Z3CFh700QBEEQRHSy7T7gsWPHMG7cOEycOBGffPIJ2rVrh61bt6Jly5Z2v5UuuVzMx/CureBykQ+GIAiCIFIJ2wXIn/70J5SXl+Oll15St3Xr1k13f6/XC6/Xq/5dVVUV9znkejLSs0QQBEEQGYPtM/WHH36IkSNH4tJLL0W7du0wbNgwPP/887r7z549GyUlJeq/8vLyuM9BjAEhCIIgCCK1sH2m3rZtG55++mn07t0bn332GX72s5/hjjvuwKuvvirdf8aMGaisrFT/7d69O+5z4LvhBhQl7uMRBEEQBGEvtrtgAoEARo4ciYcffhgAMGzYMKxbtw5PP/00rr322oj9c3NzkZuba+s58DEfgYCthyYIgiAIwgZst4B06NABAwYM0Gzr378/du3aZfdbmYIsIARBEASRetguQMaNG4eNGzdqtm3atAldu3a1+61MkU1VyAiCIAgi5bBdgPzyl7/EkiVL8PDDD2PLli1444038Nxzz+HWW2+1+60MuXF8dwzqVIwpg6gGCEEQBEGkGi5Fsd9H8dFHH2HGjBnYvHkzunfvjrvvvhs333yzqddWVVWhpKQElZWVKC4utvvUCIIgCIJwAKvztyMCJB5IgBAEQRBE+mF1/qaCGQRBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJBwSIARBEARBJJzsZJ+ACGvOW1VVleQzIQiCIAjCLGzeZvN4NFJOgBw5cgQAUF5enuQzIQiCIAjCKkeOHEFJSUnU/VJOgJSWlgIAdu3aZeoDOMWoUaOwbNmypL1/NKqqqlBeXo7du3ejuLg42acjha6hPaTydaRraA/pcB3pGtpDKl/HeK9hZWUlunTpos7j0Ug5AeJ2B8NSSkpKknoTZWVlpfRNzCguLk7Z86RraA/pcB3pGtpDKl9Huob2kA7XMd5ryObxqPvF/A4Zzq233prsU0h76BraA13H+KFrGD90De2BrmMYl2I2WiRBVFVVoaSkBJWVlSmvEpMJXaf4oWsYP3QN7YGuY/zQNYyfeK+h1dennAUkNzcXDz74IHJzc5N9KikNXaf4oWsYP3QN7YGuY/zQNYyfeK+h1dennAWEIAiCIIjMJ+UsIARBEARBZD4kQAiCIAiCSDgkQAiCIAiCSDgkQAiCIAiCSDgkQJLEwoULcd5556Fjx45wuVx4//33Nc8fPHgQ06dPR8eOHVFQUICzzjoLmzdvVp/fsWMHXC6X9N8777yj7nfs2DFMmzYNJSUlKCkpwbRp03D8+PEEfUrnifc6AsCBAwcwbdo0lJWVobCwEMOHD8d//vMfzT6ZfB3tuIZbt27FRRddhLZt26K4uBiXXXYZDh48qNknk6/h7NmzMWrUKBQVFaFdu3a48MILsXHjRs0+iqJg5syZ6NixI/Lz8zFhwgSsW7dOs4/X68Xtt9+ONm3aoLCwEOeffz727Nmj2SdTr6Nd1/C5557DhAkTUFxcDJfLJb02dA31r+HRo0dx++23o2/fvigoKECXLl1wxx13oLKyUnMcO64hCZAkUVtbi6FDh2LOnDkRzymKggsvvBDbtm3DBx98gJUrV6Jr166YNGkSamtrAQR75ezfv1/z7/e//z0KCwsxZcoU9VhXXXUVVq1ahU8//RSffvopVq1ahWnTpiXsczpNvNcRAKZNm4aNGzfiww8/xJo1azB16lRcfvnlWLlypbpPJl/HeK9hbW0tJk+eDJfLhS+//BLffvstfD4fzjvvPAQCAfVYmXwNFyxYgFtvvRVLlizBvHnz0NTUhMmTJ2vus0cffRSPP/445syZg2XLlqGsrAxnnHEGqqur1X3uuusuzJ07F2+99RYWLVqEmpoanHvuufD7/eo+mXod7bqGdXV1OOuss/Cb3/xG973oGupfw3379mHfvn147LHHsGbNGrz88sv49NNPceONN2rey5ZrqBBJB4Ayd+5c9e+NGzcqAJS1a9eq25qampTS0lLl+eef1z3OCSecoNxwww3q3+vXr1cAKEuWLFG3LV68WAGgbNiwwd4PkQLEeh0LCwuVV199VXOs0tJS5YUXXlAUpXldx1iu4Weffaa43W6lsrJS3efo0aMKAGXevHmKojSva6goilJRUaEAUBYsWKAoiqIEAgGlrKxMeeSRR9R9GhoalJKSEuWZZ55RFEVRjh8/rng8HuWtt95S99m7d6/idruVTz/9VFGU5nUdY7mGPF999ZUCQDl27JhmO11D89eQ8e9//1vJyclRGhsbFUWx7xqSBSQF8Xq9AIC8vDx1W1ZWFnJycrBo0SLpa1asWIFVq1ZpVOrixYtRUlKC0aNHq9vGjBmDkpISfPfddw6dfepg9jqOHz8eb7/9No4ePYpAIIC33noLXq8XEyZMANC8r6OZa+j1euFyuTTFh/Ly8uB2u9V9mts1ZOZq1pRr+/btOHDgACZPnqzuk5ubi1NPPVX9/CtWrEBjY6Nmn44dO2LQoEHqPs3pOsZyDc1A19D6NWSVTbOzg+3j7LqGJEBSkH79+qFr166YMWMGjh07Bp/Ph0ceeQQHDhzA/v37pa958cUX0b9/f5x00knqtgMHDqBdu3YR+7Zr1w4HDhxw7PxTBbPX8e2330ZTUxNat26N3Nxc3HLLLZg7dy569uwJoHlfRzPXcMyYMSgsLMS9996Luro61NbW4p577kEgEFD3aU7XUFEU3H333Rg/fjwGDRoEAOpnbN++vWbf9u3bq88dOHAAOTk5aNWqleE+zeE6xnoNzUDX0No1PHLkCGbNmoVbbrlF3WbXNSQBkoJ4PB68++672LRpE0pLS1FQUICvv/4aU6ZMQVZWVsT+9fX1eOONNyJ8dADgcrkitimKIt2eaZi9jg888ACOHTuG+fPnY/ny5bj77rtx6aWXYs2aNeo+zfU6mrmGbdu2xTvvvIP//ve/aNGihdoLYvjw4Zrr3Fyu4W233YYff/wRb775ZsRz4mc18/nFfZrDdbT7GkY7RqzHSWXsuIZVVVU455xzMGDAADz44IOGxzA6jh7ZpvckEsqIESOwatUqVFZWwufzoW3bthg9ejRGjhwZse9//vMf1NXV4dprr9VsLysri8hEAIBDhw5FKOBMJdp13Lp1K+bMmYO1a9di4MCBAIChQ4fim2++wVNPPYVnnnmm2V9HM/fi5MmTsXXrVhw+fBjZ2dlo2bIlysrK0L17dwDN5168/fbb8eGHH2LhwoXo3Lmzur2srAxAcOXYoUMHdXtFRYX6+cvKyuDz+XDs2DGNFaSiokK1bDaH6xjPNTQDXUNz17C6uhpnnXUWWrRogblz58Lj8WiOY8c1JAtIilNSUoK2bdti8+bNWL58OS644IKIfV588UWcf/75aNu2rWb72LFjUVlZie+//17dtnTpUlRWVmpcNc0BvetYV1cHAHC7tT+FrKwsNYODrmMQM/dimzZt0LJlS3z55ZeoqKjA+eefDyDzr6GiKLjtttvw3nvv4csvv1SFF6N79+4oKyvDvHnz1G0+nw8LFixQP/+IESPg8Xg0++zfvx9r165V98nk62jHNTQDXcPo17CqqgqTJ09GTk4OPvzwQ00MGGDjNTQdrkrYSnV1tbJy5Upl5cqVCgDl8ccfV1auXKns3LlTUZRg1PFXX32lbN26VXn//feVrl27KlOnTo04zubNmxWXy6V88skn0vc566yzlCFDhiiLFy9WFi9erAwePFg599xzHf1siSTe6+jz+ZRevXopJ598srJ06VJly5YtymOPPaa4XC7l448/VvfL5Otox734z3/+U1m8eLGyZcsW5bXXXlNKS0uVu+++W7NPJl/Dn//850pJSYny9ddfK/v371f/1dXVqfs88sgjSklJifLee+8pa9asUa688kqlQ4cOSlVVlbrPz372M6Vz587K/PnzlR9++EE57bTTlKFDhypNTU3qPpl6He26hvv371dWrlypPP/88woAZeHChcrKlSuVI0eOqPvQNdS/hlVVVcro0aOVwYMHK1u2bNEcx+77kARIkmApYuK/6667TlEURfnb3/6mdO7cWfF4PEqXLl2UBx54QPF6vRHHmTFjhtK5c2fF7/dL3+fIkSPK1VdfrRQVFSlFRUXK1VdfHZGWls7YcR03bdqkTJ06VWnXrp1SUFCgDBkyJCItN5Ovox3X8N5771Xat2+veDwepXfv3spf/vIXJRAIaPbJ5Gsou34AlJdeekndJxAIKA8++KBSVlam5ObmKqeccoqyZs0azXHq6+uV2267TSktLVXy8/OVc889V9m1a5dmn0y9jnZdwwcffDDqcega6l9DvfEAgLJ9+3Z1PzuuoSt00gRBEARBEAmDYkAIgiAIgkg4JEAIgiAIgkg4JEAIgiAIgkg4JEAIgiAIgkg4JEAIgiAIgkg4JEAIgiAIgkg4JEAIgiAIgkg4JEAIgiAIgkg4JEAIgrDMhAkTcNdddyX7NAiCSGNIgBAE4Shff/01XC4Xjh8/nuxTIQgihSABQhAEQRBEwiEBQhCEIbW1tbj22mvRokULdOjQAX/5y180z7/++usYOXIkioqKUFZWhquuugoVFRUAgB07dmDixIkAgFatWsHlcmH69OkAgG7duuGJJ57QHOuEE07AzJkz1b9dLheeffZZnHvuuSgoKED//v2xePFibNmyBRMmTEBhYSHGjh2LrVu3Ovb5CYJwBhIgBEEYcs899+Crr77C3Llz8fnnn+Prr7/GihUr1Od9Ph9mzZqF1atX4/3338f27dtVkVFeXo53330XALBx40bs378ff/vb3yy9/6xZs3Dttddi1apV6NevH6666irccsstmDFjBpYvXw4AuO222+z5sARBJIzsZJ8AQRCpS01NDV588UW8+uqrOOOMMwAAr7zyCjp37qzuc8MNN6iPe/TogSeffBInnngiampq0KJFC5SWlgIA2rVrh5YtW1o+h+uvvx6XXXYZAODee+/F2LFj8dvf/hZnnnkmAODOO+/E9ddfH+tHJAgiSZA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timetempdwptrhumprcpsnowwdirwspdwpgtprestsuncoco
time_prague
2024-10-27 00:00:00+02:002024-10-26 22:00:00+00:0011.28.986.00.0<NA>140.010.820.41020.30.04.0
2024-10-27 01:00:00+02:002024-10-26 23:00:00+00:0011.08.987.00.0<NA>150.07.216.71020.20.04.0
2024-10-27 02:00:00+02:002024-10-27 00:00:00+00:0010.88.988.00.0<NA>120.010.816.71020.00.04.0
2024-10-27 02:00:00+01:002024-10-27 01:00:00+00:0010.88.686.00.0<NA>130.07.214.81019.90.04.0
2024-10-27 03:00:00+01:002024-10-27 02:00:00+00:0010.78.586.00.0<NA>160.07.213.01019.40.04.0
2024-10-27 04:00:00+01:002024-10-27 03:00:00+00:0010.78.687.00.0<NA>170.03.613.01019.30.04.0
2024-10-27 05:00:00+01:002024-10-27 04:00:00+00:0010.78.687.00.0<NA>140.03.613.01018.90.04.0
2024-10-27 06:00:00+01:002024-10-27 05:00:00+00:0010.88.686.00.0<NA>180.03.613.01019.00.04.0
2024-10-27 07:00:00+01:002024-10-27 06:00:00+00:0010.98.887.00.00.0190.07.214.81019.50.04.0
2024-10-27 08:00:00+01:002024-10-27 07:00:00+00:0011.18.886.00.0<NA>220.07.214.81020.22.04.0
2024-10-27 09:00:00+01:002024-10-27 08:00:00+00:0011.59.286.00.0<NA>220.07.216.71020.35.04.0
2024-10-27 10:00:00+01:002024-10-27 09:00:00+00:0011.49.085.00.0<NA>250.014.420.41020.87.04.0
2024-10-27 11:00:00+01:002024-10-27 10:00:00+00:0011.69.084.00.0<NA>240.010.824.11021.09.04.0
2024-10-27 12:00:00+01:002024-10-27 11:00:00+00:0012.09.082.00.0<NA>250.014.422.21021.115.04.0
2024-10-27 13:00:00+01:002024-10-27 12:00:00+00:0012.39.382.00.0<NA>260.018.022.21021.316.04.0
2024-10-27 14:00:00+01:002024-10-27 13:00:00+00:0012.79.279.00.0<NA>250.014.420.41021.519.04.0
2024-10-27 15:00:00+01:002024-10-27 14:00:00+00:0013.69.677.00.0<NA>240.014.420.41021.620.02.0
2024-10-27 16:00:00+01:002024-10-27 15:00:00+00:0013.39.477.00.0<NA>260.014.418.51022.417.03.0
2024-10-27 17:00:00+01:002024-10-27 16:00:00+00:0012.49.281.00.0<NA>240.014.422.21023.111.03.0
2024-10-27 18:00:00+01:002024-10-27 17:00:00+00:0010.98.887.00.0<NA>230.014.422.21024.30.04.0
2024-10-27 19:00:00+01:002024-10-27 18:00:00+00:0012.09.685.00.00.0250.018.022.21024.80.04.0
2024-10-27 20:00:00+01:002024-10-27 19:00:00+00:0012.39.784.00.0<NA>230.018.020.41025.50.04.0
2024-10-27 21:00:00+01:002024-10-27 20:00:00+00:0012.39.885.00.0<NA>250.018.020.41026.00.04.0
2024-10-27 22:00:00+01:002024-10-27 21:00:00+00:0012.310.086.00.0<NA>220.010.818.51026.50.04.0
2024-10-27 23:00:00+01:002024-10-27 22:00:00+00:0011.69.788.00.0<NA>230.014.418.51026.70.04.0
\n", + "
" + ], "text/plain": [ - "
" + " time temp dwpt rhum prcp \\\n", + "time_prague \n", + "2024-10-27 00:00:00+02:00 2024-10-26 22:00:00+00:00 11.2 8.9 86.0 0.0 \n", + "2024-10-27 01:00:00+02:00 2024-10-26 23:00:00+00:00 11.0 8.9 87.0 0.0 \n", + "2024-10-27 02:00:00+02:00 2024-10-27 00:00:00+00:00 10.8 8.9 88.0 0.0 \n", + "2024-10-27 02:00:00+01:00 2024-10-27 01:00:00+00:00 10.8 8.6 86.0 0.0 \n", + "2024-10-27 03:00:00+01:00 2024-10-27 02:00:00+00:00 10.7 8.5 86.0 0.0 \n", + "2024-10-27 04:00:00+01:00 2024-10-27 03:00:00+00:00 10.7 8.6 87.0 0.0 \n", + "2024-10-27 05:00:00+01:00 2024-10-27 04:00:00+00:00 10.7 8.6 87.0 0.0 \n", + "2024-10-27 06:00:00+01:00 2024-10-27 05:00:00+00:00 10.8 8.6 86.0 0.0 \n", + "2024-10-27 07:00:00+01:00 2024-10-27 06:00:00+00:00 10.9 8.8 87.0 0.0 \n", + "2024-10-27 08:00:00+01:00 2024-10-27 07:00:00+00:00 11.1 8.8 86.0 0.0 \n", + "2024-10-27 09:00:00+01:00 2024-10-27 08:00:00+00:00 11.5 9.2 86.0 0.0 \n", + "2024-10-27 10:00:00+01:00 2024-10-27 09:00:00+00:00 11.4 9.0 85.0 0.0 \n", + "2024-10-27 11:00:00+01:00 2024-10-27 10:00:00+00:00 11.6 9.0 84.0 0.0 \n", + "2024-10-27 12:00:00+01:00 2024-10-27 11:00:00+00:00 12.0 9.0 82.0 0.0 \n", + "2024-10-27 13:00:00+01:00 2024-10-27 12:00:00+00:00 12.3 9.3 82.0 0.0 \n", + "2024-10-27 14:00:00+01:00 2024-10-27 13:00:00+00:00 12.7 9.2 79.0 0.0 \n", + "2024-10-27 15:00:00+01:00 2024-10-27 14:00:00+00:00 13.6 9.6 77.0 0.0 \n", + "2024-10-27 16:00:00+01:00 2024-10-27 15:00:00+00:00 13.3 9.4 77.0 0.0 \n", + "2024-10-27 17:00:00+01:00 2024-10-27 16:00:00+00:00 12.4 9.2 81.0 0.0 \n", + "2024-10-27 18:00:00+01:00 2024-10-27 17:00:00+00:00 10.9 8.8 87.0 0.0 \n", + "2024-10-27 19:00:00+01:00 2024-10-27 18:00:00+00:00 12.0 9.6 85.0 0.0 \n", + "2024-10-27 20:00:00+01:00 2024-10-27 19:00:00+00:00 12.3 9.7 84.0 0.0 \n", + "2024-10-27 21:00:00+01:00 2024-10-27 20:00:00+00:00 12.3 9.8 85.0 0.0 \n", + "2024-10-27 22:00:00+01:00 2024-10-27 21:00:00+00:00 12.3 10.0 86.0 0.0 \n", + "2024-10-27 23:00:00+01:00 2024-10-27 22:00:00+00:00 11.6 9.7 88.0 0.0 \n", + "\n", + " snow wdir wspd wpgt pres tsun coco \n", + "time_prague \n", + "2024-10-27 00:00:00+02:00 140.0 10.8 20.4 1020.3 0.0 4.0 \n", + "2024-10-27 01:00:00+02:00 150.0 7.2 16.7 1020.2 0.0 4.0 \n", + "2024-10-27 02:00:00+02:00 120.0 10.8 16.7 1020.0 0.0 4.0 \n", + "2024-10-27 02:00:00+01:00 130.0 7.2 14.8 1019.9 0.0 4.0 \n", + "2024-10-27 03:00:00+01:00 160.0 7.2 13.0 1019.4 0.0 4.0 \n", + "2024-10-27 04:00:00+01:00 170.0 3.6 13.0 1019.3 0.0 4.0 \n", + "2024-10-27 05:00:00+01:00 140.0 3.6 13.0 1018.9 0.0 4.0 \n", + "2024-10-27 06:00:00+01:00 180.0 3.6 13.0 1019.0 0.0 4.0 \n", + "2024-10-27 07:00:00+01:00 0.0 190.0 7.2 14.8 1019.5 0.0 4.0 \n", + "2024-10-27 08:00:00+01:00 220.0 7.2 14.8 1020.2 2.0 4.0 \n", + "2024-10-27 09:00:00+01:00 220.0 7.2 16.7 1020.3 5.0 4.0 \n", + "2024-10-27 10:00:00+01:00 250.0 14.4 20.4 1020.8 7.0 4.0 \n", + "2024-10-27 11:00:00+01:00 240.0 10.8 24.1 1021.0 9.0 4.0 \n", + "2024-10-27 12:00:00+01:00 250.0 14.4 22.2 1021.1 15.0 4.0 \n", + "2024-10-27 13:00:00+01:00 260.0 18.0 22.2 1021.3 16.0 4.0 \n", + "2024-10-27 14:00:00+01:00 250.0 14.4 20.4 1021.5 19.0 4.0 \n", + "2024-10-27 15:00:00+01:00 240.0 14.4 20.4 1021.6 20.0 2.0 \n", + "2024-10-27 16:00:00+01:00 260.0 14.4 18.5 1022.4 17.0 3.0 \n", + "2024-10-27 17:00:00+01:00 240.0 14.4 22.2 1023.1 11.0 3.0 \n", + "2024-10-27 18:00:00+01:00 230.0 14.4 22.2 1024.3 0.0 4.0 \n", + "2024-10-27 19:00:00+01:00 0.0 250.0 18.0 22.2 1024.8 0.0 4.0 \n", + "2024-10-27 20:00:00+01:00 230.0 18.0 20.4 1025.5 0.0 4.0 \n", + "2024-10-27 21:00:00+01:00 250.0 18.0 20.4 1026.0 0.0 4.0 \n", + "2024-10-27 22:00:00+01:00 220.0 10.8 18.5 1026.5 0.0 4.0 \n", + "2024-10-27 23:00:00+01:00 230.0 14.4 18.5 1026.7 0.0 4.0 " ] }, + "execution_count": 53, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "ruzyne_tidy[\"teplota průměrná\"].rolling(\"365.25D\", min_periods=365).mean().plot();" + "hodinove_ruzyne = hodinove_ruzyne_utc.assign(\n", + " time_prague=hodinove_ruzyne_utc[\"time\"].dt.tz_convert(\"Europe/Prague\")\n", + ").set_index(\"time_prague\")\n", + "\n", + "# Podíváme se na data v době přechodu z letního na zimní čas\n", + "hodinove_ruzyne[\"2024-10-27\":\"2024-10-27\"]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Pro podrobnější přehled práce s časovými řadami se podívejta např. na https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html nebo třeba na hezký článek s podobnými daty https://www.dataquest.io/blog/tutorial-time-series-analysis-with-pandas/." + "**Poznámka:** Uvědomme si, že i po operaci `tz_convert` řádky odkazují na tentýž okamžik v historii světa (pomiňme relativistickou fyziku ;-)), mění se jen jejich reprezentace. Naopak přiřazením různých časových pásem k naivním časům vznikají jiné okamžiky." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**Úkol:** Navrhněte vhodnou agregaci pro maximální teplotu (ne průměr) a vykreslete." + "Potom už si pěkně můžeme vykreslit průběh teploty v době slavného poklesu teplot na Silvestra 1978 (a budeme to mít správně i po hodinách):" ] }, { "cell_type": "code", - "execution_count": 60, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "# odkomentuj a doplň\n", - "# ruzyne_yearly[___].___().___();" + "hodinove_ruzyne[\"1978-12-31\":\"1979-01-01\"][\"temp\"].plot();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**Úkol:** Převzorkujte údaje za rok 2018 po měsících. Jaký měsíc měl nejvíc srážek, tj. za jaký byl součet sloupce \"úhrn srážek\" nejvyšší?" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "metadata": {}, - "outputs": [], - "source": [ - "# doplňte nebo vyřešte po svém :)\n", - "# ruzyne_tidy.loc[___ == 2018, \"úhrn srážek\"].___(\n", - "# \"1M\"\n", - "# ).___().___(ascending=False).index[___].___" + "**Úkol:** Jak silný foukal vítr (jak moc pršelo) v kterou hodinu den tvého narození?" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3.9.9 ('data')", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -4523,12 +5804,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.6" - }, - "vscode": { - "interpreter": { - "hash": "72160dfebc462fc90b093555bbb928aeea7de7923bddc35f4b44400e1d2267b1" - } + "version": "3.11.9" } }, "nbformat": 4, diff --git a/lessons/pydata/eda-univariate-timeseries/reseni.ipynb b/lessons/pydata/eda-univariate-timeseries/reseni.ipynb new file mode 100644 index 0000000..534c427 --- /dev/null +++ b/lessons/pydata/eda-univariate-timeseries/reseni.ipynb @@ -0,0 +1,319 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Načtení a zpracování denních dat\n", + "denni_excel = (\n", + " pd.ExcelFile(\"data-daily.xlsx\")\n", + " .parse(\"Praha-Ruzyne\")\n", + " .set_index(\"time\")\n", + " .drop(columns=[\"wdir\"])\n", + " .dropna(subset=[\"tavg\"])\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Otázka:** Co vrátí `denni_ruzyne_index.isna().count()`?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "denni_ruzyne_index.isna().count()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol:** Zkuste odstranit všechny řádky, pro které není definován `tsun`. Co nám to říká?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "denni_ruzyne.dropna(subset=[\"tsun\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol:** Zkuste odstranit všechny řádky, pro které není definován `snow`. Co nám to říká?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "denni_ruzyne.dropna(subset=[\"snow\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol:** Nejstarší tag Pandas na https://github.com/pandas-dev/pandas je verze 0.3.0 z 20. února 2011. Jaké bylo v ten den v Praze - Ruzyni počasí?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "denni_ruzyne.loc[\"2011-02-20\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol:** Jaká byla průměrná teplota první (a jedinou) neděli v roce 2010, která byla zároveň začátkem měsíce? Pokud máte řešení a čas, zkuste vymyslet aternativní způsob(y). " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# odkomentuj a doplň\n", + "denni_ruzyne.loc[\n", + " (denni_ruzyne.index.year == 2010)\n", + " & (denni_ruzyne.index.day == 1)\n", + " & (denni_ruzyne.index.day_name() == \"Sunday\"),\n", + " \"tavg\",\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sns.catplot(\n", + " data=denni_ruzyne[[\"tavg\", \"tmin\", \"tmax\"]],\n", + " orient=\"h\",\n", + " kind=\"box\",\n", + " aspect=2,\n", + ");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol**: Doplňte pomocné sloupce `season` a `significant_precipitation` (jistě uhádnete jakého pandas-typu budou :). První definuje roční období (jen jednoduše podle kalendářních měsíců), druhý označuje dny, kdy byly srážky vyšší než v **90 %** všech dní v našich datech (můžete zkusit i jiný limit).\n", + "\n", + "1. Porovnejte numericky základní statistiky celého datasetu a podmnožiny, kdy výrazně pršelo nebo sněžilo. Zvyšují v průměru srážky teplotu? A co maximální nebo minimální? A jak je to se standardní odchylkou?\n", + "2. Použijte `sns.catplot` pro vizuální srovnání distribučních funkcí pro jednotlivá roční období a dny s málo / hodně srážkami." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# odkomentuj a doplň\n", + "season = denni_ruzyne.index.month.map({\n", + " 1: \"zima\",\n", + " 2: \"zima\",\n", + " 3: \"jaro\",\n", + " 4: \"jaro\",\n", + " 5: \"jaro\",\n", + " 6: \"léto\",\n", + " 7: \"léto\",\n", + " 8: \"léto\",\n", + " 9: \"podzim\",\n", + " 10: \"podzim\",\n", + " 11: \"podzim\",\n", + " 12: \"zima\"\n", + "})\n", + "\n", + "significant_precipitation = denni_ruzyne[\"prcp\"] > denni_ruzyne[\"prcp\"].quantile(.9)\n", + "significant_precipitation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# úkol - jednoduché srovnání statistik pomocí rozdílu\n", + "(\n", + " denni_ruzyne.loc[significant_precipitation].describe() - \n", + " denni_ruzyne.describe()\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# úkol - vizuální srovnání statistik\n", + "sns.catplot(\n", + " data=denni_ruzyne.assign(\n", + " significant_precipitation=significant_precipitation,\n", + " season=season,\n", + " ),\n", + " kind=\"box\",\n", + " aspect=2,\n", + " hue=\"significant_precipitation\",\n", + " y=\"season\",\n", + " x=\"tavg\",\n", + ");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Co že jsme to vlastně vytvořili?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rocni_ruzyne = denni_ruzyne.resample(\"1YE\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol:** Navrhněte vhodnou roční agregaci pro maximální teplotu (ne průměr) a vykreslete." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# odkomentuj a doplň\n", + "rocni_ruzyne[\"tmax\"].max().plot();" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol:** Najděte, kdy v období 2000-2025 napršelo nejvíc za týden (tedy za průběžných 7 dnů). Odpovídá to nějaké vaší historické zkušenosti?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# doplňte nebo vyřešte po svém :)\n", + "denni_ruzyne.loc[\"2000\":\"2025\"][\"prcp\"].rolling(\"7D\").sum().sort_values(ascending=False).iloc[:10]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Nepovinný úkol:** Rozšiřte hledání na celé období v naší datové sadě - jsou některé hodnoty realistické?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "denni_ruzyne[\"prcp\"].rolling(\"7D\").sum().sort_values(ascending=False).iloc[:10]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "hodinove_ruzyne = (\n", + " pd.read_parquet(\"praha-meteostat.parquet\")\n", + " .assign(\n", + " time=hodinove_ruzyne_original[\"time\"].dt.tz_localize(\"UTC\").dt.tz_convert(\"Europe/Prague\")\n", + " )\n", + " .set_index(\"time\")\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Úkol:** Jak silný foukal vítr (jak moc pršelo) v kterou hodinu den tvého narození?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "hodinove_ruzyne.loc[\"2000-01-01\", \"wspd\"]" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/lessons/pydata/eda-univariate-timeseries/solutions.ipynb b/lessons/pydata/eda-univariate-timeseries/solutions.ipynb deleted file mode 100644 index 28df828..0000000 --- a/lessons/pydata/eda-univariate-timeseries/solutions.ipynb +++ /dev/null @@ -1,492 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import numpy as np" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import seaborn as sns\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def extract_and_clean_chmi_excel_sheet(excel_data, sheet_name):\n", - " \"\"\"Parse ČHMÚ historical meteo excel data\"\"\"\n", - " # načti list z excel souboru a převeď na tidy data formát\n", - " data_tidy = (\n", - " excel_data.parse(sheet_name, skiprows=3)\n", - " .melt(id_vars=[\"rok\", \"měsíc\"], var_name=\"den\", value_name=sheet_name)\n", - " .dropna()\n", - " )\n", - " # vytvoř časovou řadu datumů\n", - " datum = pd.to_datetime(\n", - " data_tidy[[\"rok\", \"měsíc\", \"den\"]].rename(\n", - " columns={\"rok\": \"year\", \"měsíc\": \"month\", \"den\": \"day\"}\n", - " )\n", - " )\n", - " # přidej sloupec datum jako index a odstraň den, měsíc, rok a vrať setříděný výsledek\n", - " return (\n", - " data_tidy.assign(datum=datum)\n", - " .set_index(\"datum\")\n", - " .drop(columns=[\"rok\", \"měsíc\", \"den\"])\n", - " .sort_index()\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# otevři Excel soubor\n", - "excel_data_ruzyne = pd.ExcelFile(\"P1PRUZ01.xls\")\n", - "# načti všechny listy kromě prvního\n", - "extracted_sheets = (\n", - " extract_and_clean_chmi_excel_sheet(excel_data_ruzyne, sheet_name)\n", - " for sheet_name in excel_data_ruzyne.sheet_names[1:]\n", - ")\n", - "# spoj všechny listy do jednoho DataFrame\n", - "ruzyne_tidy = pd.concat(extracted_sheets, axis=1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "leg_length = pd.DataFrame({\"left\": [81, 81.4], \"right\": [78.2, 78]})\n", - "leg_length" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úkol:** Má `leg_length` podobu tidy data? Pokud ne, dokážeš tato data uspořádat správně?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "leg_length.melt(value_name=\"leg length\", var_name=\"leg side\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úkol:** `to_datetime` dokáže pracovat i s řetězci, což se často hodí. Převeďte `ladies_times` na vohodný typ pro časové údaje, přiřaďte naši časovou zónu a poté pomocí `tz_convert` převeďte na UTC. Možná budete muset pandám vysvětlit, že v Česku jsou v datumech nejdříve dny, na rozdíl třeba od Ameriky. Naštěstí na to stačí jeden jednoduchý argument pro `to_datetime`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "ladies_times = [\"23. 1. 2020 18:00\", \"30. 1. 2020 18:00\", \"6. 2. 2020 18:00\"]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "pd.to_datetime(ladies_times, dayfirst=True).tz_localize(\"Europe/Prague\").tz_convert(\"UTC\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úkol:** Zařaďte `dropna` do sestrojení datumů tak, abychom nemuseli použít `errors=\"coerce\"` pro `to_datetime`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# řešení\n", - "pd.to_datetime(\n", - " teplota_prumerna_tidy.dropna()[[\"rok\", \"měsíc\", \"den\"]].rename(\n", - " columns={\"rok\": \"year\", \"měsíc\": \"month\", \"den\": \"day\"}\n", - " ),\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úkol**: Vytvořte `teplota_prumerna_tidy_clean_indexed` se sloupcem `datum` jako indexem a bez sloupců `rok`, `měsíc` a `den`. Můžete použít metodu `drop`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# řešení\n", - "teplota_prumerna_tidy_clean_indexed = teplota_prumerna_tidy.set_index(\"datum\").drop(\n", - " columns=[\"rok\", \"měsíc\", \"den\"]\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úkol:** Jaká byla průměrná teplota první (a jedinou) neděli v roce 2010, která byla zároveň začátkem měsíce? Pokud máte řešení a čas, zkuste vymyslet aternativní způsob(y). " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# řešení 1\n", - "ruzyne_tidy.loc[\n", - " ruzyne_tidy.index.is_month_start\n", - " & (ruzyne_tidy.index.weekday == 6)\n", - " & (ruzyne_tidy.index.year == 2010),\n", - " \"teplota průměrná\",\n", - "]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Cvičení**: Doplňte vytvoření pomocných sloupců (jistě uhádnete jakého pandas-typu bude :) `season` a `significant_precipitation`. První definuje roční období (jen jednoduše podle kalendářních měsíců), drůhá označuje dny kdy byly srážky vyšší než v **90 %** všech dní v našich datech (můžete zkusit i jiný limit).\n", - "\n", - "1. Porovnejte numericky základní statistiky celého data setu a podmnožiny, kdy výrazně pršelo nebo sněžilo? Zvyšují v průměru srážky teplotu?\n", - "2. Použijte `sns.catplot` pro vizuální srovnící distribučních funkcí pro jednotlivá roční období a dny s málo / hodně srážkami." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "season = ruzyne_tidy.index.month.map({\n", - " 1: \"zima\",\n", - " 2: \"zima\",\n", - " 3: \"jaro\",\n", - " 4: \"jaro\",\n", - " 5: \"jaro\",\n", - " 6: \"léto\",\n", - " 7: \"léto\",\n", - " 8: \"léto\",\n", - " 9: \"podzim\",\n", - " 10: \"podzim\",\n", - " 11: \"podzim\",\n", - " 12: \"zima\",\n", - "})\n", - "\n", - "significant_precipitation = ruzyne_tidy[\"úhrn srážek\"] > ruzyne_tidy[\"úhrn srážek\"].quantile(0.9)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "(ruzyne_tidy.loc[significant_precipitation]\n", - " .describe()\n", - ") - \\\n", - "ruzyne_tidy.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "(ruzyne_tidy.loc[significant_precipitation]\n", - " .agg([\"mean\", \"max\", \"min\", \"std\"])\n", - ") - \\\n", - "ruzyne_tidy.agg([\"mean\", \"max\", \"min\", \"std\"])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "sns.catplot(\n", - " data=ruzyne_tidy.assign(\n", - " significant_precipitation=significant_precipitation, \n", - " season=season,\n", - " ),\n", - " kind=\"box\",\n", - " aspect=2,\n", - " hue=\"significant_precipitation\",\n", - " y=\"teplota průměrná\",\n", - " x=\"season\",\n", - ");" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úkol:** Navrhněte vhodnou agregaci pro maximální teplotu (ne průměr) a vykreslete." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# řešení\n", - "ruzyne_yearly[\"teplota maximální\"].max().plot();" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úkol:** Převzorkujte údaje za rok 2018 po měsících. Jaký měsíc měl nejvíc srážek, tj. za jaký byl součet sloupce \"úhrn srážek\" nejvyšší?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# řešení\n", - "ruzyne_tidy.loc[ruzyne_tidy.index.year == 2018, \"úhrn srážek\"].resample(\n", - " \"1M\"\n", - ").sum().sort_values(ascending=False).index[0].month" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## TODO - skladiště nápadů" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "* Rozdělení na horké / studené dny -> cut?\n", - "* Jak vypadá rozdělovací funkce pro dny kdy pršelo? Jaká je střední hodnota, medián, Q1, Q3 a směrodatná odchylka.\n", - "* Kolik dní za sebou nejdéle pršelo?\n", - "\n", - "...\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úkol (damácí?):** Načtěte data ... *TODO připravit soubor schibami* ..., kde jsou chybějící data označena jako `#CHYBA MĚŘENÍ`. Odstraňte pouze řádky, kde je špatné datum. Pomocí `fillna` pak nahraďte chybějící měření poslední předchozí hodnotou." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# **TODO** Domácí úkoly\n", - "\n", - "* Ověřit pranostiky: Medardova kápě, ledoví muži, vyberte si pár vlastních, např. z https://www.meteocentrum.cz/zajimavosti/pranostiky/.\n", - "* Kolik dní v kuse nejdéle pršelo / sněžilo? 1) V Ruzyni, 2) ve všech meteostanicích? Kolik naopak nepršelo? A kdy to bylo?" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Možná data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Výroba elektřiny" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "GENERATION_FILENAME = \"generation_2010.csv.gz\"\n", - "GENERATION_URL = f\"https://data4pydata.s3-eu-west-1.amazonaws.com/pyladies/{GENERATION_FILENAME}\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "save_file_from_url(GENERATION_URL, GENERATION_FILENAME)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "generation_2010 = pd.read_csv(\"generation_2010.csv.gz\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "generation_2010.sample(10)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Ceny elektřiny" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import zipfile" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_ote(year: int) -> pd.DataFrame:\n", - " filename = f\"Rocni_zprava_o_trhu_{year}_V2.zip\"\n", - " url = f\"https://data4pydata.s3-eu-west-1.amazonaws.com/pyladies/{filename}\"\n", - " save_file_from_url(url, filename)\n", - " with zipfile.ZipFile(filename) as archive:\n", - " with archive.open(archive.namelist()[0]) as xls_file:\n", - " ote_data = pd.read_excel(\n", - " xls_file, sheet_name=\"DT ČR\", usecols=\"A:K\", header=5\n", - " )\n", - "\n", - " return ote_data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "ote_2018 = get_ote(2010)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "ote_2018.sample(10)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Úlohy:**\n", - "\n", - "* Převeďte na správný čas v časové zóně \"Europe/Prague\".\n", - "* Spojit soubory\n", - "* Jak se liší průměrné a maximální ceny v kalendářních dnech? Je nějaký den výrazně levnější?\n", - "\n", - "**TODO**" - ] - }, - { - "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": "3.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -}