ANN-route-predition/experiments/Experiments.ipynb

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{
"cells": [
{
"cell_type": "markdown",
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"source": [
"# Initialschätzung von Kurswechselpositionen eines Segelboots auf einer Karte anhang con Wind, Start und Zielpunkt\n",
"\n",
"## Motivation\n",
"\n",
"Ziel dieser Semester abschließenden schriftlichen Ausarbeitung im Fach \"Maschine Learning\" an der Fachhochschule Südwestfalen ist das Generieren einer Heatmap von Kurswechselpositionen eines Segelbootes zu einer Karte abhängig von Wind und der Zielpostion. Dies soll das Finden einer guten Route vereinfachen, indem die Qualität einer ersten Route, die danach über ein Quotientenabstiegsverfahren optimiert werden soll verbessern. Da ein solches Quotientenabstiegsverfahren sehr gerne in einem Lokalen minimum festhängt, müssen mehrere routen gefunden und optimiert werden. Hier soll untersucht werden, ob dies durch eine Ersteinschätzung der Lage durch KI verbessert werden kann.\n",
"\n",
"Eingesetzt werden soll die so erstellte KI in dem Segelroboter des [Sailing Team Darmstadt e.V.](https://www.st-darmstadt.de/) Einer Hochschulgruppe an der TU-Darmstadt welche den [\"roBOOTer\"](https://www.st-darmstadt.de/ueber-uns/boote/prototyp-ii/) ein vollautonomes Segelboot welches eines Tages den Atlantik überqueren soll. [Eine technische Herausforderung welche zuerst von einem norwegischen Team erfolgreich abgeschlossen wurde](https://www.microtransat.org/)."
]
},
{
"cell_type": "markdown",
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"name": "#%% md\n"
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"source": [
"## Inhaltsverzeichnis\n",
"\n",
"1. Einleitung\n",
"\n",
" 1.1. Situation\n",
" \n",
" 1.2. Vorgehen zur unterstützenden KI\n",
" 1.2.1. Eingaben und Ausgeben\n",
"2. Vorbereitungen\n",
"\n",
" 2.1. Imports\n",
" \n",
" 2.2. Parameter und Settings\n",
" \n",
"3. Szenarien und Routen Generieren\n",
"\n",
"4. Daten betrachten und Filtern\n",
"\n",
"5. KI Modell erstellen\n",
"\n",
"6. Training\n",
"\n",
"7. Analyse der KI\n",
"\n",
"8. Ausblick\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## Einleitung\n",
"\n",
"### Situation\n",
"\n",
"Eine Routenplanung für ein Segelboot hat ein Problem, welches man sonst so eher nicht kennt. Eine relativ freie Fläche auf der Sich das Schiff bewegen kann. Dies verändert die Wegfindung wie man sie von der Straße kennt fundamental.\n",
"\n",
"Navigiert man auf Straßen, hat man zumindest nach einer ersten abstraction relativ wenige Freiheitsgrade für den Weg.\n",
"Die Richtung kann nur an Kreuzungen gewechselt werden und dort nur in Richtungen in die es Straßen gibt. Beim Segeln auf dem freien Meer ist jeder Ort ein potenzieller Wendepunkt von dem aus Potenziell in jede Richtung gesegelt werden kann.\n",
"\n",
"Dennoch ist es oft auch ohne Hindernisse zwischen Boot und Ziel oft nicht möglich das Ziel direkt anzufahren das sich die Maximalgeschwindigkeiten relativ zur Windrichtung verändern.\n",
"Das folgende Diagramm zeigt die Segelgeschwindigkeiten an einem Katamaran.\n",
"\n",
"<img src=\"https://www.researchgate.net/profile/Hoyun-Jang-2/publication/320062151/figure/fig2/AS:667648312483865@1536191170832/Polar-diagram-of-yacht-speed-according-to-diverse-wind-direction-and-speed.ppm\" alt=\"Ship speeds relativ to the wind\" style=\"width: 400px;\"/>\n",
"\n",
"Da der roBOOTer anders als an Katamaran nicht auf Geschwindigkeit, sondern auf mechanische Belastbarkeit ausgelegt wurde hat der Fahrtwind einen geringeren einfluss auf das Fahrtverhalten des Segelboots dies und eine andere Maximalgeschwindigkeit sorgen für ein etwas anderes Fahrverhalten. Die ungefähre Form der Kurven trifft aber auch auf den roBOOTer zu. Man kann deutlich erkennen das auch, wenn man nicht direkt gegen den Wind fahren kann man schräg gegen den wind immer noch erstaunlich schnell ist.\n",
"\n",
"Das aktuelle Verfahren zum Finden einer Route läuft folgendermaßen ab:\n",
"\n",
"Eine direkte Route wird berechnet. Die Route wird an jedem Hindernisse geteilt und rechts und links um jedes hindernis herum gelegt. Bei folgenden hindernissen werden die Routen wieder geteilt somit erhält man $2^n$ Vorschläge für Routen wobei $n$ die Anzahl der Hindernisse auf der Route ist. Jeder Abschnitt der Route wird noch einmal zerteilt, um der Route mehr Flexibilität zu geben.\n",
"\n",
"Die Routen werden dann simuliert, um die Kosten der Route zu berechnen. Die so simulierte Route wird danach über die Kosten in einem Gradientenabstiegsverfahren optimiert.\n",
"\n",
"Das ganze oben beschriebene Verfahren ist relativ schnell sehr rechenaufwendig und findet nicht immer ein Ergebnis. Wird kein Ergebnis gefunden wird eine mehr oder weniger zufällige Route optimiert.\n",
"\n",
"Diese Ausarbeitung soll wenigstens bei der alternativen Routenfindung helfen. Im idealfall kann es aber auch genutzt werden, um die auswahl der Routen um Hindernisse frühzeitig zu reduzieren und den Rechenaufwand unter $2^n$ zu senken wobei $n$ die Anzahl von Hindernissen auf der Route ist.\n",
"\n",
"### Vorgehen zur unterstützenden KI\n",
"\n",
"#### Eingaben und Ausgeben\n",
"\n",
"Die Algorithm zur Wegfindung vom Sailing Team Darmstadt e.V. arbeiten intern mit Polygonen als Hindernissen. Diese werden durch die Shapely Bibliothek implementiert. Da eine variable Anzahl an Polygonen mit einer variablen Form und Position eine Relative komplexer Input muss dieser in eine normierte Form gebracht werden. Ein binärfärbens Bild ist dafür die einfachste Form.\n",
"\n",
"Für den Computer spielen sowohl Zentrierung, Skalierung und Ausrichtung der Karte keine Rolle.\n",
"Wir rotieren also die Karte immer so das der Wind von *Norden* kommt und das Boot / die Startposition in der *Mitte* der Karte liegt. Da distanz Liner ist, wird davon ausgegangen das Scenario einfach skaliert passend skaliert werden kann.\n",
"\n",
"Die nächste eingabe ist die Zielposition relativ zum Startpunkt. Diese kann entweder durch ein einzelnes Pixel in einem zweiten Farbkanal oder aber in abstrakterer Form an die KI übergeben werden.\n",
"\n",
"Als ausgabe wird eine Heatmap erwartet. Zwei alternative Heatmaps sind relative einfach denkbar.\n",
"\n",
"1. Eine Headmap der Kurswechselpositionen\n",
"2. Eine Headmap des Kursverlaufes\n",
"\n",
"Headmaps sind in gewisser Weise Bilder. Das Problem wird daher wie ein Bild zu Bild KI Problem betrachtet. Diese werden normalerweise durch ANNs gelöst.\n",
"\n",
"Um eine ANN zu trenntieren gibt es immer die Wahl zwischen drei Primären prinzipien. Dem unüberwachten Lernen, dem reinforcement Learning und dem überwachten Lernen. Letzteres ist dabei meist am einfachsten wenn auch nicht immer möglich.\n",
"\n",
"Der Wegfindealgorithmus des Sailing Team Darmstadt e.V. ist zwar noch in der Entwicklung, funktioniert aber hinreichend gut, um auf einem normalen PC Scenarios mit Routen zu paaren oder auch diese zu *labeln*, um beim KI lingo zu bleiben. Um anpassungsfähig an andere Scenarios zu sein wird eine große Menge unterschiedlicher Scenarios und Routen benötigt.\n",
"Da das Haupteinsatzgebiet das Meer ist gehen wir von einer Insellandschaft oder Küstenlandschaft aus.\n",
"\n",
"Zum Finden von Scenarios gibt es zwei Möglichkeiten.\n",
"\n",
"1. Das Auswählen von umgebungen von der Weltkarte und das Bestimmen eines Zielpunktes.\n",
"2. Das Generieren von künstlichen Scenarios.\n",
" \n",
"Hier wird die Annahme getroffen das sich ANNs von einem Datensatz auf dem anderen Übertragen lassen.\n",
"Der Aufwand für künstliche Scenarios wird hierbei als geringer eingestuft und daher gewählt."
]
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"name": "#%% md\n"
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"source": [
"## Vorbereitungen\n",
"\n",
"Folgende Python Bibliotheken werden verwendet:\n",
"\n",
"1. `tensorflow`\\\n",
" Die `tensorflow` Bibliothek ist das Werkzeug welches verwendet wurde, um neuronale Netz zu modellieren, zu trainieren, zu analysieren und auszuführen. Tensorflow wird mit den kürzel `tf` abgekürzt.\n",
"\n",
"2. `pyrate`\\\n",
" Die `Pyrate` Bibliothek ist Teil des ROS Operating Systems, welches den roBOOTer betreibt. Kann Routen zu Scenarios finden.\n",
"\n",
"3. `Shapley`\\\n",
" Die `shapley` Bibliothek wird genutzt, um geometrische Körper zu generieren, zu mergen und an den Roboter zum Labeln weiterzugeben.\n",
"\n",
"4. `pandas`\\\n",
" Die `pandas` Bibliothek verwaltet, speichert und analysiert daten. `pandas` wird üblicherweise mit `pd` abgekürzt.\n",
"\n",
"5. `numpy`\\\n",
" Eine Bibliothek um Mathematische operations an multidimensionalen Arrays auszuführen. `numpy`wir üblicherweise mit `np` abgekürzt.\n",
"\n",
"6. `matplotlib`\\\n",
" Wird genutzt um Diagramme zu plotted. Das modul `pyplot` wird hier vermehr genutzt und mit dem kürzel `plt` abekürzt.\n",
"\n",
"6. `PIL`\\\n",
" Eine Library um Bilder manuell zu zeichnen.\n",
"\n",
"7. `humanize`\\\n",
" Konvertiert Zahlen, Daten und Zeitabstände in ein für menschen einfach leserliches Format.\n",
"\n",
"8. `tqdm`\\\n",
" Fügt einen Fortschrittsbalken zu vielen Problemen hinzu."
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
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},
"source": [
"#### Imports\n",
"Importiert die Imports the necessary packages from python and pypi."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:59:16.416888Z",
"start_time": "2022-07-15T18:59:12.921020Z"
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"pycharm": {
"name": "#%%\n"
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"outputs": [],
"source": [
"import sys\n",
"\n",
"# Pins the python version executing the Jupyter Notebook\n",
"assert sys.version_info.major == 3\n",
"assert sys.version_info.minor == 10\n",
"\n",
"import os\n",
"from typing import Optional, Final, Literal\n",
"import glob\n",
"import pickle\n",
"\n",
"from tqdm.notebook import tqdm\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"from PIL import ImageDraw, Image\n",
"from shapely.geometry import Polygon, Point, LineString\n",
"from shapely.ops import unary_union\n",
"import tensorflow as tf\n",
"import humanize"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Definiert den Pfad an dem das Jupyter Notebook ausgeführt werden soll.\n",
"Importiert die pyrate module. Wird nur ausgeführt, wenn innerhalb des Pyrate Containers ausgeführt."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"C:\\Users\\phhor\\PycharmProjects\\ml-projekt\n"
]
}
],
"source": [
"# Import route generation if started in the docker container\n",
"if os.getenv(\"PYRATE\"):\n",
" %cd /pyrate/\n",
" import experiments\n",
" from pyrate.plan.nearplanner.timing_frame import TimingFrame\n",
"\n",
"# Protection against multi exection\n",
"if not os.path.exists(\"experiments\"):\n",
" %cd ../"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"if os.getenv(\"PYRATE\"):\n",
" # Sets the maximum number of optimization steps that can be performed to find a route.\n",
" # Significantly lowered for more speed.\n",
" experiments.optimization_param.n_iter_grad = 50\n",
"\n",
" # Disables verbose outputs from the pyrate library.\n",
" experiments.optimization_param.verbose = False"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Activate pandas for tqdm\n",
"tqdm.pandas()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
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"outputs": [],
"source": [
"# The scale the route should lie in. Only a mathematical limit.\n",
"SIZE_ROUTE: Final[int] = 100\n",
"\n",
"# The outer limit in with the goal need to be palced.\n",
"# Should be smaller than \n",
"SIZE_INNER: Final[int] = 75\n",
"assert SIZE_ROUTE > SIZE_INNER, \"The goal should be well inside the limit placed \"\n",
" \n",
"# The minimum destance from the start that should \n",
"MIN_DESTINATION_DISTANCE: Final[int] = 25\n",
"assert SIZE_INNER > MIN_DESTINATION_DISTANCE, \"The goal should be well closer to the outer limit the\"\n",
"\n",
"# The size the ANN input has. Equal to the image size. Should be an on of $n^2$ to be easier compatible with ANNs.\n",
"IMG_SIZE: Final[int] = 128\n",
"\n",
"# The size an image should be in to be easily visible by eye.\n",
"IMG_SHOW_SIZE: Final[int] = 400\n",
" \n",
"# The number of Files that should be read to train the ANNs\n",
"NUMBER_OF_FILES_LIMIT: Final[int] = 1000\n",
"\n",
"# \n",
"NO_SHOW = False\n",
"GENERATE_NEW = True"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## Szenarien und Routen Generieren\n",
"\n",
"Um das neuronale Netz zu trainieren werden Datensätze benötigt. Für die Abschätzung der Routen wird eine Karte mit Hindernissen und eine zugehörige Route benötigt. Hier wurde die Designentscheidung getroffen die Karten nicht auszuwählen, sondern zu generieren.\n",
"\n",
"### Generieren von Karten\n",
"\n",
"Eine Karte ist für das Sailing Team Darstadt eine Mange von statischen und dynamischen Hindernissen. Statische Hindernisse sind Inseln, Landmassen und Untiefen und Fahrferbotszonen. Dynamische Hindernisse sind andere Teilnehmer am Schiffsverkehr und Wetterereignisse.\n",
"In dieser KI wird sich auf statische Hindernisse beschränkt. Daher ist eine Scenario eine Maenge an Hindernispoligonen.\n",
"Um das generieren der Poligone einfacher zu regeln und größere statistische Kontrolle über die den Generationsvorgang zu haben sind alle generierten Basispolinome als Abschnitte auf einem Umkreis definiert die Zufällig über die Karte verteilt werden.\n",
"\n",
"Ein einzelnes Polygon wird hier Folgendermaßen generiert:\n",
"1. Die Anuzahl der Kanten/Ecken wird festgelegt.\n",
"2. Ein lognormal verteilter Radius wird zufällig ausgewählt.\n",
"3. Auf dem Radius werden n winkel abgetragen.\n",
"4. Die Winkel werden sortiert damit sich das Polygon nicht selbstschneidet.\n",
"5. Die durch Radius und Winkel entstehenden Punkte werden in das kartesische Koordinatesnsystem Umgewandelt.\n",
"6. Der zufällige Offset / Polygonmittelpunkt wird aufaddiert.\n",
"7. Aus den so generierten `np.ndarray` wird ein `shapely.geometry.Polygon` erstellt.\n",
"8. Polygonen die den Mittelpunkt berühren oder einschließen werden ersatzlos gelöscht.\n",
"\n",
"So wird eine Festgelegte Anzahl von Polygonen generiert.\n",
"Setzt man vor dem generieren des ersten Polygons eines Scenarios eine random seed über `np.random.seed` so erhält man zu jedem seed ein eindeutiges mänge an Polygonen wenn auch alle anderen Parameter übereinstimmen. Diese Polygonmänge hat nun mit hoher Warscheinlichkeit überlappende Polygone. Dies ist für den Algorithmus des Sailing Teams Darmstadt e.V. ein Problem. Die Shaeply libraray besitzt eine Union function die vereinigungsmängen von Polygonen bildet wenn möglich. So erhält man eine reduzierte mänge an Polygonen. Diese kann später an einen Solver übergeben werden."
]
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"execution_count": 6,
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"source": [
"# https://stackoverflow.com/questions/16444719/python-numpy-complex-numbers-is-there-a-function-for-polar-to-rectangular-co\n",
"def polar_to_cartesian(\n",
" radii: np.ndarray,\n",
" perigons: np.ndarray,\n",
"):\n",
" \"\"\"Transforms polar coordinates into cartesian coordinates.\n",
"\n",
" Args:\n",
" radii: A array of radii.\n",
" perigons: A array of angles in perigons [0, 1[.\n",
"\n",
" Returns:\n",
" An array of cartesian coordinates.\n",
" \"\"\"\n",
" return radii * np.exp(2j * perigons * np.pi)\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
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"outputs": [
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"data": {
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"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"-16.37816427364242 53.572469871489815 6.660645097041407 6.473724419318636\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,113.61866416229827)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"0.13321290194082813\" opacity=\"0.6\" d=\"M -9.964209735750694,58.12346496725632 L -10.380908764033304,58.90225055101728 L -10.981914756343256,59.53091446131591 L -14.62510766338472,59.79950373165877 L -16.051330505870038,58.08054532765174 L -16.13147371449274,57.81979780226843 L -15.655931768323725,55.1495345171628 L -14.888014501362616,54.37062796397931 L -12.399620374135152,53.8191604306395 L -9.964209735750694,58.12346496725632 z\" /></g></svg>"
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"text/plain": [
"<shapely.geometry.polygon.Polygon at 0x26a826e36d0>"
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"source": [
"def random_polygon(\n",
" radius_mean: float = 2,\n",
" radius_sigma: float = 1.5,\n",
"):\n",
" \"\"\"Generates the simplest of polygons, a triangle with a size described by a random polygon.\n",
"\n",
" Args:\n",
" radius_mean: The average radius defining a circumcircle of a triangle.\n",
" radius_sigma: The variance of a radius defining a circumcircle of a triangle.\n",
"\n",
" Returns:\n",
" A single triangle.\n",
" \"\"\"\n",
" # define the number of corners\n",
" number_of_corners = np.random.randint(3, 10)\n",
" \n",
" # generate carthesion coordinates from a radius and a sorted list of perigons.\n",
" array = polar_to_cartesian(\n",
" np.random.lognormal(radius_mean, radius_sigma),\n",
" np.sort(np.random.rand(number_of_corners)),\n",
" )\n",
" \n",
" # add an offset\n",
" offset = np.random.randint(low=-SIZE_ROUTE, high=SIZE_ROUTE, size=(2,))\n",
" return_values = np.zeros((number_of_corners, 2), dtype=float)\n",
" \n",
" return_values[:] = offset\n",
" return_values[:, :] += np.array((np.real(array), np.imag(array))).T\n",
" return Polygon(return_values)\n",
"\n",
"\n",
"np.random.seed(42)\n",
"random_polygon()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Parameter zum generieren der Karte\n",
"\n",
"Die Folgenden Paramter wurden für das Generieren von Karten genutzt:\n",
"* `radius_mean = 2` \n",
"* `radius_sigma = 1`\n",
"* `number_of_polygons = 40`"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"pycharm": {
"name": "#%%\n"
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"outputs": [],
"source": [
"def generate_obstacles(\n",
" seed: Optional[int] = None,\n",
" number_of_polygons: int = 40,\n",
" radius_mean: float = 2,\n",
" radius_sigma: float = 1,\n",
") -> dict[str, Polygon]:\n",
" \"\"\"Generates a set of obstacles from a union of triangles.\n",
"\n",
" The union of triangles meas that if polygons overlap o polygon containing the union of those polygons is returned.\n",
" Args:\n",
" seed: A seed to generate a set of obstacles from.\n",
" number_of_polygons: The number of polygons that should be drawn.\n",
" radius_mean: The average radius defining a circumcircle of an obstacle triangle.\n",
" radius_sigma: The variance of a radius defining a circumcircle of an obstacle triangle.\n",
"\n",
" Returns:\n",
" A list of unified obstacles.\n",
" \"\"\"\n",
" # sets a seed\n",
" if seed is not None:\n",
" np.random.seed(seed)\n",
" \n",
" # generate a list of poligons\n",
" polygons = []\n",
" for _ in range(number_of_polygons):\n",
" poly = random_polygon(radius_mean, radius_sigma)\n",
" # skip polygons that are to close to the startint point P(0, 0)\n",
" if poly.contains(Point(0, 0)):\n",
" continue\n",
" if poly.exterior.distance(Point(0, 0)) < 1:\n",
" continue\n",
" # append to polygon list\n",
" polygons.append(poly)\n",
" \n",
" # build unions of all polygons\n",
" polygon_list = list(unary_union(polygons).geoms)\n",
" return {str(i): p for i, p in enumerate(polygon_list)}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Generieren des Zieles\n",
"\n",
"Zu jedem Scenario gehört neben einer Situation auch ein Ziel. Auch zum generieren eine Ziels wurde zu erste der gleiche seed gesetzt wie für den Karten Generator. Danch wird eine zufällige Position mit Abstand zum Kartenrand ausgewählt.\n",
"Die so generierte Zielposition wird danach auf Plausibilität überprüft. Folgende Prüfungen finden Statt:\n",
"1. Es wird sichergestellt dass, das Ziel nicht in oder an einem Hinderniss liegt.\n",
"1. Eine Minimaldistanz in x und y wird sichergestellt. Leider ist hier ein Fehler passiert. Anstelle die Summe der Absoluten Distanz zu Prüfen wurden die Distanzen einzelned geprüft was verhindert das Ziele über, unter und neben dem Startpunkt gefunden werden können. Zielpunkte werden nur auf den Diagonallen gefunden. Lieder ist dies erst aufgefallen als schon zu viel Zeit vergangen war und die Daten nicht neu generiert werden konnten. Dies sollte aber zumindes das Konzept dieser KI nicht beinflussen. Wohl aber ihre direkte anwendbarkeit."
]
},
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"cell_type": "code",
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"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"POINT (-61 31)\n"
]
}
],
"source": [
"def generate_destination(\n",
" obstacles: dict[str, Polygon],\n",
" seed: Optional[int] = None,\n",
") -> Point:\n",
" \"\"\"Generates for a map.\n",
"\n",
" Can be used to generate a valid destination for list of obstacles.\n",
" Args:\n",
" obstacles: A list of obstacles.\n",
" seed: The seed determining the point.\n",
"\n",
" Returns:\n",
" A goal that should be reached by the ship.\n",
" \"\"\"\n",
" # sets the seed\n",
" if seed is not None:\n",
" np.random.seed(seed)\n",
"\n",
" # generates the point\n",
" point: Optional[Point] = None\n",
" while (\n",
" point is None\n",
" or abs(point.x) < MIN_DESTINATION_DISTANCE\n",
" or abs(point.y) < MIN_DESTINATION_DISTANCE\n",
" or any(obstacle.contains(point) for obstacle in obstacles.values())\n",
" ):\n",
" point = Point(np.random.randint(-SIZE_INNER, SIZE_INNER, size=(2,), dtype=int))\n",
" return point\n",
"\n",
"\n",
"print(generate_destination(generate_obstacles(42), 42))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Ploten der Situation\n",
"\n",
"All die Scenarien die Oben generiert wurden sind rein Matematische Constructe und daher für den Menschenen schwer nachzufolziehen. Die Folgende Funktion übernimmt das Ploten der mit der oberen Funktion erstellten Situationen. Eine Route kann optional mit eingetragen werden."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def plot_situation(\n",
" obstacles: dict[str, Polygon],\n",
" destination: Point,\n",
" obstacle_color: str | None = \"RED\",\n",
" route = None,\n",
" legend: bool = True,\n",
" title: str | None = None,\n",
") -> None:\n",
" \"\"\"PLots the obstacles into a matplotlib plot.\n",
"\n",
" Args:\n",
" obstacles: A list of obstacles.\n",
" destination: The destination that should be reached by the boat.\n",
" obstacle_color: The color the obstacles should have. Can be None.\n",
" If none all obstacles will have different colors.\n",
" route: The route that should be plotted.\n",
" legend: If true plots a legend.\n",
" title: The title of the plot.\n",
" Returns:\n",
" None\n",
" \"\"\"\n",
" # Create an plot in the definined size\n",
" plt.axis([-SIZE_ROUTE, SIZE_ROUTE, -SIZE_ROUTE, SIZE_ROUTE])\n",
"\n",
" # Sets a title if one is demanded\n",
" if title:\n",
" plt.title(title)\n",
"\n",
" # Plots the obstacles.\n",
" if obstacles:\n",
" for polygon in obstacles.values():\n",
" if obstacle_color is not None:\n",
" plt.fill(*polygon.exterior.xy, color=obstacle_color, label=\"Obstacle\")\n",
" else:\n",
" plt.fill(*polygon.exterior.xy)\n",
"\n",
" # Plots the wind direction\n",
" # The following code for an arrow was taken modeled after:\n",
" # https://www.geeksforgeeks.org/matplotlib-pyplot-arrow-in-python/\n",
" plt.arrow(\n",
" 0,\n",
" +int(SIZE_ROUTE * 0.9),\n",
" 0,\n",
" -int(SIZE_ROUTE * 0.1),\n",
" head_width=10,\n",
" width=4,\n",
" label=\"Wind (3Bft)\",\n",
" )\n",
"\n",
" if route is not None:\n",
" if isinstance(route, np.ndarray):\n",
" plt.plot(route[:, 0], route[:, 1], color=\"BLUE\", marker=\".\")\n",
" else:\n",
" if isinstance(route, TimingFrame):\n",
" plt.plot(route.points[:, 0], route.points[:, 1], color=\"BLUE\", marker=\".\")\n",
" else:\n",
" raise TypeError()\n",
"\n",
" # Plots the estimation\n",
" if destination:\n",
" plt.scatter(*destination.xy, marker=\"X\", color=\"green\", label=\"Destination\")\n",
" plt.scatter(0, 0, marker=\"o\", color=\"green\", label=\"Start\")\n",
"\n",
" if legend:\n",
" # https://stackoverflow.com/questions/13588920/stop-matplotlib-repeating-labels-in-legend\n",
" handles, labels = plt.gca().get_legend_handles_labels()\n",
" by_label = dict(zip(labels, handles))\n",
" plt.legend(by_label.values(), by_label.keys())\n",
" return None"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Die aus den Seeds 0 - 11 generierten Karten werden unten Angezeigt um Beispiele der von der KI zu Lösenden Scenarien zu zeigen.\n",
"Wird dieses Notebook im Pyrate Docker Container ausgeführt werden auch die Routen eingezeichnet."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d1fda510fdb54f56941f42f61f7c24a3",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/12 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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CzUZZ21FR2jxfgOB3Aj1Vqwb8+Sfw3XecxuSJUAMXI/RFeDgwdizvo2KMMea7cePoY9u2/h3HZqM06wYN/B4SY4Z39SowaxYFBqpVozagR45QFf/U1IK/3+mkzJuXX7bOVlilBAUBDz4InDhBH202dTNnIyOBV16hIAVTlAWXaE1GCOD++/UehTmEhdHWA6sQAnj8cb1HwRhjzKx27wZmzAAefpjqH/kjKgp44w1lxsWYETmdtOr8ySfUqjwkxL+i2E4nFfI7cAD4+ms6T2WZChemoqhjxgDDhlEmtdJFyENDgbg42p7MFMcZBcw8rDQBBwVRFwwuFsUYY8wXiYm0FxgA3n8/98fcdx+t5hW0X9hup729Rmtzxpi/0tKAFSuAvn1pH/2IEVRIPDlZmYtWh4NqjbVvT13NWE716gFbtgCffUZ1BJTMpI2MBObO5VpfKuFAATMPI7RdUUp4OPD883qPgjHGmFkNH04fFyzIO5A+ejRw6RJlHdSpQwGB4ODsjwkJoYucu+9Wd7yMaUVKaqGd0bGgb1/qPOZ0Un0BpTmdwD//AC1aWKvgtpIyMqhPnKAuCTab/7VQbDZg3jygRAllxshy4EABMw8r7eWvV49a7DDGmFns3g389BPvxzWC1atpFa1OHaBXr/wfGxlJQYU9e4BNm2jPsN2eWfQrPBz49FPVh8yY6rJ2LOjaNXvHArWlpFBRxMmT1X8uM4uKAqZNo8BKq1Y0F/nCbqeAQ5cuyo6PZcOBAmYeVgkUREUBL72k9ygYY8xzmzdTS7AhQ4B9e/UeDZswgT5+8413KbcNGlBQ4NIlqkrepAnw3ntAuXLqjJMxtWV0LKhaNXvHgoSEnB0L1OZwUACPFaxmTSro/u23QPHilB3gqaAgoHJl4K231BsfA8DFDJmZWCVQEB0N9Oih9ygYY8xzH3xAe3qlBM6fB7gwvn5276b2Y/fe63uVb7udiosNG6bgwBjTyNWrtJXg44+BvXspWJaUpPeo6GKXs3M8JwTNY926Aa+/DkyfTpkZLlf+32ezUV0Iq3VDMyAOFDDzyCM9KQnA8Sz/Pp3PIS4A2J/l3+UAaNpx1W4HnnuOe1QzZlYZPesDyMWLF3F1z57/thwk5HMSd/DgQRQpUgQAEBQUhBo1amgxxMDyyCP0ceZMfcfBmF5atQJOnaLaAEZhs9G2no4dvf7Ww4cPIy0tDQCQkk+NA0diIvbvzzyLLVKkCEqVKuX9WI3GbqeOKyNGUF2JTZvy7nJmt1PXiipVtB1jgOJAATOPPNKS3hZBeD04FPaIzGrNERVzLncFl62ND45uxQfp/05KcWKg24XP0zQsPCMEvZEwxswjLY1Wr156CTh5EqhVC+jQAWjTBmjeHKhY0dLBg1ZtO+Di5asIKVoSgIAMCoY9tnyOx0VXaYLuvTPb/cZfOot1a/9A69atNRytxZ07R23dRo/2vx0iM6bUVOC774CXX6bV1bg4WmmtWlXvkRlH8eLAwYN6jyK7EiWAd9/1+tv+/fdfNGkah0IlMl/PRarH5XhcSNEyOLHxMlp1ugMA4EpNgT08BOdOnYCwyvtPlSrAypXAsmUUNLhxI3vAICKCOoYNGqTfGAMMBwqYeeTRtqmZdCO6SClEPfRBrl/PYGvQFbYGXf/7d8jcl9D62HZFh5ivsDDqdR2laQ4DY8xXUgKzZwOTJlEbrYQEuv/ff4GdO4EvvqAgQpMmwKpV1urMkkWjxo3xx7XCiG5yV76Ps3fP7GPtTnbAOetB1K1bV+3hBZb70wMxb7+t7ziYOtaupQr9TmfmfLNsGQUlJ07Ud2xGcvvtwF9/0fxrBDYbsHChT1tka9SogbCICET1eQPB9sJ5Pi60aGkUHvzef/9O2LUSDXHEOkGCrHr0AI4do9oT//d/FDxLSwOKFeOtHRrj/GdmHnkECjoBcF47i7T4Kx4fyp2ahISTu9BLmZF5JigIePJJLZ+RMeaP5GRa1cgojJWVlFRJ2+kEtm8HHnjAst0AHhjQD0En/vbqe5xHtqBFqzYoXDjvE1/mpYQEYN064MUX83w/ZCYmJfDQQ1RoMut843bTRRPL1Lq179XylWa3A88+CzRu7NO322w2dO7SFY5Dm736PnH8LwwZ2N+n5zSF8HCa6w4coBoGoaFUl4AX2zTFgQIrWrcOOHpU71Hk7quvqDXgoEHUZuv6dc+/N48TozAA3UUQnIc2eXyopGPb0SA4FLGeP7t/hKBWPeVzpusyxgwqIgLYupVet/lVZHY6gaVLaY+lBXXr1g0JZw7C5bjh+Tcd/wtDBvRTb1CB6A5KOeb2axb1++8UlMzN8eOaDsXwmjc3Rn2CoCCgWjXKOvPDAwP6I+i458FYd7ID8cd34q678s/ysoTy5YElSyirz8dgDPOdqoECIURNIcSOLLebQohxQojJQogzWe7nEvBKWbGC9s42aECpsUYhJe23e/RR6uX8/fe0V79kSRrrq68C+/fnf4x69fKMID+QloygnSs9H87u1RiakkehFDXYbMALL2j3fMzyeH7VSNOmNDcNHJh/sMDhoHnsiueZTWbh7YqXOzUJ8Ue2o1evXuoOLNDUrg28/z4Xw9WI5nPszZt51zo5nV+Z5gBUqBBQpozeo6Bg8k8/ASH+7eTu0aMH4k/uhjspoeAHI0AztrjDgS5UfbeRUh6QUjaSUjYC0BSAA8DC9C9Py/ialHKZmuMIGIcOAX360OeJica6MB07lvYZZS1KEh9PhXp27aK2KHFxVCgsLwMG5Nky5XYAiZdPeLTiJdNSkXDsH/T28kfwS5UqFAFnTCE8v2rIbgc++4xOCIsWpXojuQkNpeJLFuTNilfS0e1o1LgpYmM1y9kKDJ9+CowZo/coAobmc+ydd+bdFi6vTINA1r69vs8fGUm1QqpV8/tQ0dHRaNuuAxyHPcwq4IwtphEtw9KdARyRUp7Q8DkDx82bQJcuFCDI8NtvwOXL+o0pq6tXqUJzTAydZAcF0epcdDRQuDB9npwMjB+f9zGKFqV9SrmwAegUFOzRilfSiR2oGRQMzRrKREXRPivG1MPzqxa6d6dK25065b4VKigo75ZOJufNipc89heGDOSTWGYp6s+xNhv1lM8tq+D6dcvWQPFZx4761eoICaHFrdGjFTvkkIH9IY7/VeDjOGOLaUnLQMH9AOZk+fdYIcROIcRsIURRDcdhPW430Ls3RZyzvpEEBQFffqnbsLKZM4eK8Vy5QgEBh4PqKGzeTHuPvvmGVuyeey7/4zz2GAUXcjEkNQlBuwrefuDaswZDUjTc2xYRQf8/jKmH51etFCtGVchnzKCT1Kxp4BYOFHi64iXTUpFweAt685zHrEWbOXbUqNy3WAYFWXJbk19atdLvue12Oq9VsOPA3XffjfhjO+Au4PyUM7aYljQJFAghwgDcA2Be+l0fAagKoBGAcwByNB4VQowUQmwVQmy9dOmSFsM0r2efBTZtogvwrJxOOpk1YhQ6PBwoVQqoUwdo25b6og4dShHa/HTqlGcLsh4AEs4fhiufFS/pdsFx+G/0gUa/E5sNePppv/evMZYXX+bX9O/jOdZXQgDDh9O2qQYNsq9qWTRQAHi24uU8sQM1a9dBqVKa5WwxpipN59g2bYDOnelCtFAhWmiw24FGjbja+61q1NDn/DZjK1rp0ooetmjRoohr1hLOI1vzfRxnbDEtaZVR0B3AdinlBQCQUl6QUrqklG4AnwLIsXlbSjlLShknpYwrXry4RsM0oR9+AD74IO+T07NnjVEZVilBQcDIkbnuEY4C0CYoBM7DeZ/IJp3chUpCoIKKQ8xh1Cgtn40FHq/n1/TH8Rzrr8qVqSvCs89SUNDhsHSgwJMVL/fRzRjKJ7HMWrSbY4OCgEWLgA0bgM8/B959l7oh/P03BQ1YpqAgCqBoKTycuo/07avK4YcM7AfkE4zljC2mNa0CBQOQJWVLCJE1DHcvgN0ajcNaduygnrv5BQKqVDFOr1mlPPxwnlWfh6Y6IXatyvNbXXv/wODUJLVGll1ICPVWD6SqtEwPPL/qKTiYapCsXw80aQKUK6f3iHL67jtg9mzq3uDHClxBK17SlQbHob9w3333+fwcjBmQ9nNso0ZUnPrRR4HWrRU/vGV07aptxmZUFAVwVHLvvfci4cg2uFOTc/06Z2wxrakeKBBCRALoCmBBlrv/J4TYJYTYCaAjgHwq2LFcXbwI3H57/qtXQgBW7LFaqRKl++bibgDxZ/bBnZzz9yKlG0kHN6KfVqlqISHAM89o81wsIPH8aiBNmlDNlTzmJt0sW0bB1ccfp61d0dHUQveNN4B167zOgMhvxSvp1G5UqlwZFSpomrPFmGp4jjW4Nm20Wwyz2YC5c4EiRTz/nlWrqMOXh4oXL4669Rsi6fg/uX6dM7aY1lQPFEgpE6WUsVLKG1nue0BKWV9K2UBKeY+U8pza47CU1FSqvn39ev6Pi4gABg3SZEiae/zxXPfrFQEQFxwC59GcK17JZ/ahpJTwv5GNh9q0AapW1erZWADi+ZXl68IFYOBAyjpLTMy8rVsHTJ4M3H03nfTWqkVt9+bPp+1q+chvxct1ZBMG388nscw6NJ1jFy3igoXeatFCm+21NhvV0erUyfPvuXEDuO8+6vbVqRMV7S7ovB3A0IH94D6as4MXZ2wxPWjZ9YApJS2NOgbkkX6P4GAqrvXSS0DTptqOTSu9ewMVKuTaGmdoihPYvTrH/al712JQHulciouM5JaIjDH9uN2Uupy1ZW5WqanUVjc1FThwAPjwQyrQWLUqULw40LMn8P77tMUtLe2/b8trxUu6XXAe2ox+ffuo+EMxZkFuN/DLL3RR2agRcPy43iMyj0KFFC8qmKvixYGpU737nsKFgY0bKYtrzRraRlKyJBXw/vzzPINCvXv3RuLhvyFdqdnuTzq1G5UqccYW0xYHCszIZqNWgw88QJ8DNBGFhQHVqwPjxwNLl1KBLauy2aji+MyZQNGimb8HAL0AxJ/4N9uKl5QSqfv/RH/p1mZ8pUsD7dtr81yMMXar6dOB7duzXeQXKD4eSEoCLl8GFi+mrVPt21P2VrNmwKRJwIoVGHrv3TlWvJLP7EOpUiVRrZpmOVuMmdeVK8D339OiR+HClP3pdlNGT5MmFKBjnlH7XMtmAxYuzHae6bE6dWgeLl2a5taUFCpU+cQTQJkylBHx8ce0nThd2bJlUa16TSSd2JntUK4jmzB4AGdsMW1xoMCsihQBPv2UCmiNGUOfnzkDHDwIvP027UFVsL+rIQUFAQ8+CJw6BTz5JE3iISEoDqBecAiSjm3/76Ep5w+hUFoq6mgxrqgoyiaw+u+fMWZcK1b434HB6aTgQXIydXd46y2gXz/0njQJiXvWZ1vxSjuyGQP7B2A2gZQUUKlZE/j2W71Hw8xg+XK6SBw1ii5AExLodSYlBQuuXaNV55Ur9R6pOXTsmGt2qSLsdmpx3aSJ78eoVImCBRUrZnbsSkykoMHff9P5a7Nm2b7lgQF94coSjM3I2Orbh7cdMG1xoMDsmjSh9ND+/YFixfQejT4iI4HXXwcOHaLovM2GoSlOuPdkbj9I2bcOA1yp0OTSPTgYuP9+LZ6JMcZyV7Gi8sd0uYCbN1E2LQ1VhfhvxUtKieSdq9H/t9+Ad94BNm2i4ILVJSdTuvh77wFHjlDtHMYKsnIlXSQmJOT9mMRE4J57qGMJy1+rVuocNyiItmIpsY20VClgyxaqBxMenv1rTicFjrLo26cPnIc2Q7pdANJrbJUsgerVq/s/Fsa8wIECZh1lywI//gisX4/e9esj8dh2SFcqpJRI27sW96dPuKqKiADGjcuMGjPGmB4qVaKgpUqGpCTBtWcNACDl3EEUTktB3c2bgRdeoD7j0dEUyM6SUmsp164B7drRirDbDYweDRw+rPeomBlszb29aA5OJ3UsefNNdcdjdjVr+tX2NU8REcBPPynXfrFoUapZ0KxZ9m0MoaHAnXdme2jlypVRtlw5JJ/aA4Aytgbd31eZcTDmBQ4UMOtp0gRl//0X1SpWQtLxf5F66TgiUpzwI3HMO2PHavVMjDGWuzJl6ERXJX0h4Tz8F6TbRRlbaekZW8nJmUUSDx4E1q5VbQy6OXGCgiBbtlBGweHDVC8nJkbvkTEzOHDA88c6ncBrr9EWU7dGNZbMJigIaNhQ2WPa7bTVSukV/MhIyijp1CmzraPNBtx2W46HDr6/H1KPbKKMrcOb0b8vBwqY9jhQwKxJCAwZNQKuo5uRfGAD+gUB4tZ0L6UFB1OV8UDdAsIYM44yZZRbCctFZQBlASSf2oO0fWtxv8wlY8vpBHbvVm0Muhk4EChfngrOzZ+vzjYPZk1Op/ctEB0O4MsvgV69AmNLjy+6dFEugyokhDqGjRmjzPFuFR5OrTB796ZgQVJSjhoFANCvbx8kH96ElLMHUDjajrp166ozHsbywYECZll97rsPjsN/wXX8LwxYuAAYNoxW2PJqK+mvsDDguefUOTZjzHRSXCno/m13dP+2OxJSEv77PMWVov6Tly6t+grk4NRkJPz5Td4ZW243FeuymmXLgHXrlF/FZNZ34IBv1fMdDlqJbt8euHFD+XGZXdu2yhU0tNloG6s3BaldLmD/fsqiOnoUOHmSOlhcvAhcvUrFKrMKDga+/hoYOZKyknJZyKpVqxaKxcTgxrovMaBfXwijFcjesYO2uFkxa4z9hwMFzLIqV66M8uXLIyjVgZbdulELmn//pQq5GSlfSmrcmFrhMMYYgJ5zemLtibVYe2Ityk0t99/nPef0VP/JS5emgmkq6ifdSDyzD/1crrwLxVoxo6BwYb1HwMxq717PHmez5ax15HTSxVnt2nTxyTK1aEG/H3/Z7cBnn9H86akLF4DWrSkLIS6OAoh16tC2hYoVKburaFFgxozs3ycEMG0atcnMw8D+feE8uRv39zPgtoMFC4DTp4Hu3YGvvtJ7NEwl6uUlMmYALzz3DC5cvIKgjCyCGjUoKr9mDUVyz52j6sL+ymiJyBhjt3CmOeFMo5NYW4gPq4m+iI0F0tJUfYpaAIYHh+KhLG0Sczh/ngIWXODVO+++SxctDz3Evzsr2bUr/24HAAUJGjakhY2sgoJo5TnjvIVrYmQqXJg6C5w65fsxwsOBbt2Afv08/56NG4G776a6LAXNt88/T9uWvNieOuSBwTh5+gya+NOeUS0LFlAmhdMJPPooZVS88Qa3BrcYziiwkoQESol87DF6k/niC3UqwZrIA4MG4anxubSs6tiRJrUZM4AiRXxLBcyqaFF6g2GMsXTz+s1DWHD2i7yw4DDM7zdf/ScXguY2lX3uSkWj/B4QEUGta5l3/vc/6q9erhzw+eeqB32YRrZuzf+8zG6nQndr11IHpfBwSqmPiaEOCEuW0N9C+fKaDdk02rXz7/ujooDZsz17rJSUDdClC2V3ePL6TE0Fnn3WqyHVqlUL3371hfG2HVy7ln1edzjofLpPH66jYTEcKDCzlBTgzz+BSZOA+vXpjWTAAODDD4GdOylg0LkzRZ9ZTsHBwPDhFIEeN46CBb4U/4qMpEix0SZyxpiu+s7tm6MeQYorBX3m9tFmAMWLa/M8+QkOVn0LhCXFx1ORs0uXgCeeACpUAL75hlbwmHkdOZL31+x2Kli4aBFlkUyZQh02tm2jv4OPP6YaBSq2PTW1Tp18r1OQUZfAk+BqQgJw773UCtab7Q4pKcCcOdbYjrVqVc66Cg4HsHw5bcPwtmAnMywOFJiJ2w388w+tNLRpAxQqBNx1F/17926KVt68mVnAKjGRCi6pVbnVKqKiKF3q4EF6k/Y2u0AIYOhQVYbGGDM/W4gNhcMLa7ftIIM3+2zVkpbGKdLecrkoSJAhMZEC/qNHA5Ur0wUNt8ozp5kz6Zzj1qLKdjstXHz7bWYgQAigZEmgZk31ijBbSatWvn2fzQY88AAtrBVk/36gXj1gxQq6MPZWUhIwapT5s31//jlngUaAAie7dlFW8+HDmg+LKY9nHrP46isKDLRvD7z0Eu2LyuhXnV/Kk81G1f5ZwcqVA+bNo+BKkyaeRabDw4FHHvF/6wJjzHIWDViEDhU7oEPFDjj95On/Pl80YJE2AzBC276UFA4UeOv69dzrEiQmUgbcgw9SobTUfGpDMGO6804qSFi1Km3LAShI8PTTlLrNmYm+q1XLtwBasWLA9OkFP27uXCpWePJk9kCeN6Sk2hNLl/r2/UYgJWUO5CU1lTo+NG0KrF+v3biYKjhQYBY//EAnCQkJ3u3/KV2aCq0wz8XF0T7Cr7+m4jj5dUgQAhg/XruxMcZMIyw4DMsHL8fywcsRFRb13+e31i1QTZUq+q9EVqoEREfrOwazuXIFCA3N/WsZ70edOnEKullVrUoXi7160TnElCnA5MkcJPBXUBAtqpUs6fkWBJuNivLlt9iTmkpbeR98kM7D/c0GSEykBSazBvr27y84UCIlLWTefjvw3XfajIupggMFZnH8uPffExUFvPMOv/n4Qgigd2/aHzh5Mr3p3LofSwigRw9qfcMYY0ZTpkzmqqUewsPp5Jp55+rVnEGAqCgK/L/2Gm1D+PRT/YNAzHc2G7XFu3CBaiQxZfTtS1k3779Pr5eoqLwfa7cDTz1Fi0N5OXcOaNmSCor6stUgL9eu5WyXaBa//up55obTSUU4X37Z/NstAhS/y5iFLwUJOZvAf2FhlBJ44gTVIbDZMk/ObDYqJMkYY0ZUunTeK9NaEMK7VmOMZFRRDwmh95nWrakuwenT1AmhcGG9R8iUIIQxCo5aTWgobbk9eZKKe5crlzNgIARlXL30Ut7H+fNPoG5dKg7uTdFCTzgcdPF8+bKyx9XCvHnebb1wOmnR8v77ubCtCXGgwAySkwvuu3uryEjOJlBSbCzwySdUTPK22+iNqGZNqmXAGGNGVKaMvqs45cpRmjXzjt1O/2/DhtF7zoYNlL0WFAQcOECrpUqubjJmRSEhVKTw+HE6fytfPjNgEBEB/PRT7p2upKQi4d260cq/Wq1J09KAiRPVObZanE7qwuEthwP45RdqYXntmvLjYqrhQIEZnDnjffpomTKcTaCGmjWpLczq1cDChXqPJjAdPEjpzHv36j0SxoytdGn9VnDCw7kbjK9uu4329376Kb3nJCZSf/eGDYHGjSldmmvjMOaZ4GBg4EAKGHz2GVCnDqX916iR87Hx8XTu/MorymcR3Co5mbaf7Nmj7vMo6c8/fd/O5nRSIc+GDYGjRxUdFlMPBwrM4MSJ3KOeeeFsAvW1bWuMiuKBZuNGoFkzKjQZF0epe2YtCMSY2ooX1+/1ERREqabMNxk1CqSkE+vHH89MgU5OBr75hoLWjDHPBAUB/fvThfmIETm/vncvbTVYuVK7jJ2kJGDkSPPs3//lF+8znLNKSaHFzyZNgE2blBsXUw0HCszg5EnvUp84m4BZ0YIFQJcutNLmdmfue6td27dUOMasLihI244DGc9XuDDw6KNAtWraPbdVnT1L5wCJidnvdzrpouf6dV2GxZilzJlDixCnTnnXWcxfGe0Sly3T7jn9sXixby0os3K7gRs3gM6dqaMbMzQOFJjB8eOep0BFRQFvv83ZBMxapk0DBg/O+TpwOIAjR2jf27hx6qcKMmY2ahdLCw6m953YWGDUKDrhvXqVgnjMf2XLAhUq5P61hARKpWaM+e6NNyjDQK+6H4mJNHcaPTvy9Gng4kXljud0AsOHUycXs2RUBCAOFJjBgQOeR/BKlQLuuUfd8TCmFbeb+he/8EL+QQCnE5g1i1Yw163TbnyMGV3p0sofMzSUtriVLEmvz1WrgEuXqMJ427bctk9pY8fm3uc9JIS2JTDGfPfll/oXB71+HZg5U98xFGTFipxtW/3ldAJvvklFJ40eKAlQ/G5uBsePe/a4qCiuTcCsZehQKuLlyZu400lpunfcQVHqmzfVHx9jRvfEE7lfZHorLIyq8ZctS4X01q+ntr3TpgHNm/P7jpoGD865WBAaSnVyunTRZ0yMWYHbTXXA9JaYSK0ajdwu8aefcm6BUoLDQVtLO3SgLQnMUDhQYAbPP08naAXhbAJmNRs3eh/pdzppv2GVKsDSpeqMizGz6N2bKlUXL04Xl94ID6cgQ6VKwLPPAlu2UPrpW28BjRpxcEArxYoBY8ZQ/aHwcMrYaNmSuu/w/wFjvjt1yrti4WoycrtElwtYu1a942e0XWzY0PPFUaYJDhSYwV130epNbGzeExpnEzArKlnSt+9LSgKuXAH69aMLJSNH6RlTW9OmVOm7adOCg84REXSrXh148UUqtHXsGPDqq9RWjOnj3XepWnhSEmVLrV3r+/zIGCN793ofQFVLbu0Sjx0DPv6Y2kLruY9/yxbltx3cKiWFAjeNGwN//63uczGPcaDALBo3ptZI1avn3sOUswmYFZUt69/3OxyUVVC1KlXX5YI5LFAVL06ZBSNG5AwW2Gy0Ul23LhWW2rePTkwnTaL3HGYskZG8KMCYEvbsMVYR5FvbJU6bRnVgGjemxcLevYEvvtB+u8SyZdr8ntxuqtfQsSNtR2C640CBmZQpA2zdSnsSs57ocTYBs6pKlfw/RkoKrcANGADEx/t/PMbMKiQEeO894PPP6T0kPJxOQN98k7qH7N4NPPWUMq87xhgzuq1b6RzBKG5tl3j1Km1JcDiAa9eAhQuBxx8HatWijKJBg2ir5fnz6o7rp5+8a9PuL4eDarO8+SYv8OhM9UCBEOK4EGKXEGKHEGJr+n0xQojfhRCH0j8WVXsclmG3Ux/TrAWqzJJNkJoK/PgjpTAx5oly5aiImj9sNjrOn38ChQopMy6DMMT8evIkVbsfNQq4cEHVp2IKuf9+yhg4cQLYvp1OPP3N3gkEUlKNhsWLgalTaeWLWZoh5limnp079R5BTlnbJV69mvPrCQmUeXDxIm1VGDWKgrsVKgAPP0zBhNy+z1fXrgGHDyt3PE85nZThNny4tkEKlo1WGQUdpZSNpJRx6f+eCGCVlLI6gFXp/2aeEoL6vn72GW1DePddY2cTuFzAN9/QJDZiBKUUNWxIaUUul96jY0ZWsiStevrKZgMefRQ4dIjatlmT9vPr9evA008DlSsDNWvS57NnA0uWKP5UTCVly/Ie9/xISVkW8+cDzzwDtGoFFC5MWzEeeICKDLdsyfVPAgOfw1qRlFQDwIgy2iV6EoyMj6f6BqdO0XXBsGHUFrd6dVpUXL7cv2zKVav8Ow/zh8MBzJ0LdOrEnax0olepz54Abkv//CsAfwB4VqexmNfAgbQyZNSe1W43nWQ99RRFJBMSMr+2cye1vouNpaJMFSvqN05mXKVK+fb3ndHG7YcfgCZNlB+Xsak/v/7wAzBjRvaUzXLlKA2SMTM6fBj46y9g82ZgwwZg/36ae4KC6L0ra/prUhJ9PHoUaNYM2LSJ5ioWKPgc1grOnDHuIltGu8Rixbz/3owL6sOHgfffB778klbna9akc/KaNb073sKF+m7bdDiouGHjxsAffwDly+s3lixSXCnoOacnAGBev3noO7cvAGDRgEUIC/YzE9ZAtLjClAB+E0JsE0KMTL+vpJTyXPrn5wHwsoavPLmIun4daN0aWLNG9eEAoBOqxYspmvnQQxTlzBokyJCQQF+Li6M0WMZuVapUzv7h+RGCsgiefZaKFFk/SKDP/HrzZvb/F7udUiBzK7TKmNGdOgXUqweMHk0n1v/8QyfWiYl0gpzXHtnUVNqKEBdHx7iV00kn6Y0b09wUFsZZdObD57BWtXev/1sb1ZSW5n/RQreb3q9TU+nnff99775fSuDXX/0bgxKSk6ltYsOGtF3OAHrO6Ym1J9Zi7Ym1KDe13H+fZwQPrEKLjIK2UsozQogSAH4XQuzP+kUppRRC5HgXTp+QRwJAhQoVNBimhRUuDBQtSqk7Dz9MVVQjI5V/HimB334Dxo/POzhwK7eb2ti1aEGZBQ0aKD8uZl4lS9IbhCciI6m7wY8/UqGfwODT/Ar4OcfeuJG5ZzAigtpQtmvn/egZM4KdOym11pfU1rQ0KiQWF0dFIufNA77+OufjGjcGXnhB/RZjTGn6zLFMfXv2ZGYHGVFyMs1Lnp4DFcTtpjT+GTM8z6TYt884vyO3m7KT27WjrWAREbQwlPHRbs9+X4MGQLduqmddO9OccKZRRwhbiE3V59KD6oECKeWZ9I8XhRALATQHcEEIUVpKeU4IURrAxVy+bxaAWQAQFxfHJS/9IQSlCtetS/uXliyhyULJPdt//AGMG0epTomJ3n2vlJT10LYtpXzWr6/cuJi5FSlS8ApccDC9mU6ZQm2EjLoVRwW+zq/p3+P7HNuvH1XPT0ykN+Xp0/35MRjT1969/rX+crmAS5eAu++mf4eE0N7gRx8FqlRRZoxMF7rNsUx9O3YodxGuFqXHd+0abbkoV86zx//6q/GyoBwOqpuQn5AQChZUrUpdIWrXVnwY8/rNQ7mp5f4LEgBAWHAY5vebr/hz6UnVM2ohRKQQIjrjcwC3A9gNYDGAoekPGwpgkZrjYACio4EVK+ik/tw54PbbgTFj/O+LunEjZQPcdRe1dPE2SJBVfDxfcLDshKBgQV4iI6mg2J49dGIeQEECXefXhg1pPilUiFZRCxdW/CkY08TVq8Cnn1Jqrj+kpNfD+vV0rHfe4SCByfE5rMUNHpzZPSxQlCnjXYeb+fONH0zJTVoaZTXv3Ak0bUrZXAr/HH3n9kWKK3trzRRXCvrM7aPo8+hN7bPqkgDWCyH+BfA3gKVSyl8BvAmgqxDiEIAu6f9maqtdO7N/ttMJfPEF1RHYvNn7Y23bBrRvD3TtSkVG/AkQZPXLL9wzlWV3220538xDQoCoKEqh+/PPQO37ru/82qYNbUG4915VDs+Y6i5cAJo3p72vSkhJofdGZhV8DmtlXbtShq3drvdItGG3A08+6fm2g+Rk889nUtL1zrRpVMRx40bFn8IWYkPh8MKW3HYAAEKa4KIsLi5Obt26Ve9hWMejj2ZWQQXoImzkSODNNwsuRpaaCtxzD9UTSEpS/qLebqdCUjVqKHtcZl7JyfSGvmUL/c3Z7bRH7csvNak0LoTYlqUtliXxHMsCzsmTVOT3wgVle3T3709b/ZhHAmF+BXiONbSNG2kvuyd1tcwsIoLqqXiaAZiSQgsy/mZbGYnNRh3jpk6lDDA/mKXrgb9zbODk6bJM771Hxd5C0ktUOJ3ArFkUbduyJf/vPX+e6hE4neqs/LvdwLJlyh+XmVd4OKW5d+8OxMQAX31F++a4HRljzBeHDlHxwXPnlA0SAJRhxxgzj9atafHLzwtHQwsKAnr39m6bYFiY9RbtnE7gu++AypWBRf7tGAoLDsPywcuxfPByRIVF/fe5kYIESuBAQSAKDQWWLqVIYQank1ZYOnQAnnkm77084eHqji0piQotMpaVzQYsWEAdMvpYa/8XY0xDO3fSdoPLl71rveqp06fNuaeXsUDWpAkV0y5a1PPUfDOx2agjmbc6dbLe7yMpiWrTDBxI9dXOn9d7RIbGgYJAVbo0RdNu3fvtdAIffADUqUNbAG4VFqbOyVVW27ZRFwTGGGNMKX/9Rd11rl9XrxZOWBgwfDhwMddC+Iwxo6pXj+aI2FjrFUYuW5ayqLzVvn32RUUrcTiopXv16lTQ1gRb8fVgsVcC80r79sDLL+cs5OJwAEePUrGySZOy708KD1e/VUpoKFC8OHVqqFaNIpqPPEJVpOfNo/YujDHGmKdWrwY6d6buOmpKTKRK4ZUrU90fzi5gzDyqVwe2bgVKlszcnmt2UVHA00/79r2tWlmrRsGtUlOpNsW4cfQewXLgQEGge+YZqiqf25YCp5PaFdatm7k6okWgIDExs7XJkSPAmjXAJ58Azz8PPPggFbYzWl9XxhhjxvTLL8DddyvXnacgKSkUcH/tNerIsmABr1YxZhYVK1Jma9mytHBldm43MGCAb99btmxgtJBMSwN27NB7FIbEgYJAJwRVaC5ePPevOxzAiROZgYKgIP1SslJT6URv3z5aqWGMMcbyM2cOdSJwOLR/boeD9r8OGUJ1EfhElDFzKF2aintXrkzbicwqOJj24kdG+n6MFi2UG49RpaQA27frPQpD4kABoxT/FSvy7iXbogXt3cqgdzqWwwFMmcInXYwxxvL2ySfAQw9ltgLWS2IipTO3bg0MHszFsxgzg+LFqWZBrVrqF/JWS1gY8MQT/h2jSxfz/vzeWLiQusJZeauFDzhQwEidOsBnn+UMFtjtwP/9X/b79A4UAHTid++9VL2UMcYYy+rtt6nKt95BgqycTurqU7Uq8Prr/P7FmNEVKULdEBo2BCIitH1uJboN1KiRfaHPF23aWGMLRkGcTqrLVq0ateBmADhQwLIaMAB44IHswYJatWiSyMooE8aFC8CECXqPgjHGmFFISfVsJk82VpAgQ2oqZcX93//RXuh587h+AWNGFhUF/PEHZddqtV8/PJzmhdKl6TmDg2n7QOHCQKFCngUtoqN9L2KYVfPm1u18cKvERGoVf999VPB97169R6Q7DhSw7GbOpAhkSAhNSrnVAjBKoMDpBL74Ali1Su+RMMaYMi5dotVwbhHrPSmBsWMpfVSPmgTecDio9s+DDwJNm1LxNMaYflJSgN9/zz3Tx2ajVnq33Zb3Nl2lBAcD5coBN28CZ8/SXBEfD+zaBSxbBsyeTV3AJk6k+iutWwNVqlAAISiIxlqoEGUk9Onj/3iCgqgrQCAUNczgcADr19Pc/PDDwJUreo9INxwoYNmFhgJLl9JEWL487U26lT/pV0pPNE4nTZTcMpExZgWLFtGKeKVKFAh1u/UekTm4XJQR9+WXxg8SZJWYCPzzD9CuHb2XnT2r94gYM47y5SlwqrakJOCOO4CePak2wYQJVMg7q7AwYPFioHt3dYMFhQpRt6/o6Mz7bDYqrNi6Na12jxlDWUk//EBbI44cAW7coGDHkSOUAbFzp3K1BUaMCLz3Iinp7+Kbbyj769136fcbYDhQwHIqU4ZWN377Lfc9Uv/3f95PkpGRQGwsvdiUFh8PDBum/HEZY0xrW7dSq6YbN4DHHgMaN+bCrQVJSaGaNQsXmitIkJXTSeOvVg14+WVjbptgTGunTwMbN6r7HImJQMeOwKZN9LpLSADef5+23nbpAqxcmbk9KCSE6oz07atOsMBup3Pv8uV9+/7gYNqu0LixsufbsbHAXXcpUzfBbJKT6W/k5ZcpWLN4cUBtF+NAActdtWp5T1SDBwOjRnk2SUZFUXT2nXeAM2eAO+9UdpwAnSSuXAl8+63yx2aMMS1t2ZL5eWIirQq1bk0rOpw5lZPTSSuBK1eaN0iQITWVfp533gEqVKDWjgF0QspYrtS8OI2PB9q2payerFsOUlLo36tWURCyfHna0nTzJqXif/EFLVApGSyw2Wj1Oi5OuWMqacoU2rdftiwFTGw2qpngT+tFM0lMpIyvgQPpPXnXLr1HpAkOFDDfvP02FXbJK60pKoqimtOnU4DgkUfosSVKqNM1weEARo+mIiSMMWZWBw/mvM/ppEBopUrA558HXgpoXuLjgQ4dMlcCrcLhAC5fpr2xjRoBf/+t94gY04+agYIHHwT27aNV47wkJNB57PPPA6VKAcOHU5G799+nrC8lggV2O/DCC0Dv3v4fSy01a9KWhtOn6fd18CBtlZsxA3j2WaBHD6pxZrfTNo1ChWj7RHCw3iNXVmIitc1s3hwYOpRqzVgYBwqYb4KDgZ9/BkqWzD6JR0VREZaPPqKL9oceyl78MCaGJhA1OJ2UDsYn0YwxM7pwIe8ezsnJtJr1xBPUqmv7dm3HZjRXrwKtWlHGhVXbDGZklNx2GxUlO31a7xExpj21AgXz5gHLl+cfJMjK4aDzzK+/Bpo1owvF5s2BZ57xL1hgs1GA4LnnfD+G1oKC6Fy/QwcKnLz5JtU3O3CA5q0LF4DVqymwfc899D1W6pyQUb/g++/VyZQ2EA4UMN8VKkRpWVFRlHpUqRLw2WfA8eO0PSG3zIGYGHUyCgAqZrV7tzaFbxhjTGm7dxdcLDYxkR7Xti0FYgNxO8L583SifvCg5yf5ZuZ00spdjRq06mj2LRaMeUONQMG1azR/+vJacrnoNbl1K60oz5gBFCvmW7HusDCgQQPqZGCl/f9FilDHgL59gQULqObOxx9TLYiwMOsEDcLDgZEj9R6FqjhQwPxTrRqwdi1F1Y4coarN+aUZxcSoOxk6HMArrwTM3iHGmIV4szrudALffUcB2k8/DZxMqhMn6AT05Mm8sy+sKC2N/s+nTqX90t9+Gzj/5yywqXHOuHy5MvU/EhIou+niRZqPPM2YjYqiLISxY4EVK4zTdlwthQoBgwZRlsHFi8AHH1C9g7Aw89Y4EAKoXp0CThbGgQLmv8aNKbUoyIM/p5gY9YszOZ1Ar16BsdLEGLOOv//2bt7K2I4wfjytSl2+rN7YjODgQSr0df48XTgHIqeTLkweeYT+zzdt0ntEjKln506qBaC0hQvpIl8pSUk0J93aPi8iggr+2e2UTVu2LNC1KwV3r1yhlnuFCys3DjMoXBgYMoQWGc+fB2bOBNq0odV5MwUNIiIoYOvJtY+JWfunY8YTE6PNCd65c8DTT6v/PIwxppR//vHt+xITgcOHad6zqn//pf3AV67wSjpA/+d79gCdO1NgnAv5MiuqX5+KYCtJSuD335U9Zm6ioiiYW7kysGQJBRNOn6b2h/ffX/A2s0BQtCgVlFy/njoKvPce0LKl8TMNbDZgzBigbl29R6I6DhQEmpQUYP9+/VouxcTkjLiqwemkegl//KH+czHGmL/cbuDYMd+/v2RJoF495cZjJJs3U02GGze4XeCtnE4qIlarFjBxorKrpIxZ0a5d2ixYJSTQfLVnD3UEuP12ChJwoDN3MTGUxr9pE3WZmDqVgsPh4cq2oVRC4cLAq6/qPQpNcKAgUDidVHClbFnaKlC9OhUW0bookpYv9owuCNeva/ecjDHmi+PHfd+nGh4OjBhhrWJYGVatArp04Qvg/GTUL5gxA6hQgXq888UIY7n79Vdtty6lplI2werVwH33UY2RadMo8MlyV6wYFQn86y/Klnr3Xdp2Fh7uW9FIJdntwJdf6j8OjXCgwOri44E33gBKl6YesJcv04R15AgwYQJF67RuLaVltdP4eGrdwhhjRrZrl+/9poWgTjNWs3gx1b9JTNR7JObgdFI198ceA+rUoXRexlh28+frV8MqIYFS7F94AShVChg2jLrYsLyVKEE1WbZsoWK2b79NC556BA1CQylw3a2bts+rIw4UWFl8PPU5ff11ilzeerLlcABHj2rf2qNQIe2eKzmZKsrOmaPdczLGmLd27vT9grhaNdoHayXffUf7eLkVoPcSE6mfebduwF13UTs3xhjNJ//+q/coaBxJSVQMr3594M8/9R6ROZQsSbUBtm+nrXpvvQU0bKhd0CAsDPjkE/Wfx0A4UGBldjv9UTudeT/G6QTmzaOAgVaKFNHuuQCakEeOpCIyjDFmRJs3+3ZBZ7fTaouVfPQR8PDD+b93sYI5HJRmffOm3iNhzBjWrTNWEcGwMGD0aEqrZ94pXZqyp3bsoCzpKVOoTk94uDr/x5GRFJgoVUr5YxsYBwqsLDgYeOqpgqNswcHAmjXajAkAYmO1e64MSUlUr4D3bTLGjGjnTt++z+UC+vdXdix6evNNet/iIIEyGjSgyuKMMdrOFB+v9yjoYrZ4cSpE+uGHAbPfXTVly1Kb4F27gEOHKJO6Th0KGCgRNBACqFKFgjoBhgMFVjdyZMFVoqXUtrCL0q1uPJGWRifi06Zp/9yMMZaf5GTqJ+2L5s2p8JPZSQk89xzw2mu83UApERHAoEF6j4Ix4zh2TP/OKXY70LMnXdB27KjvWKyofHmqwbZnD3V5e/VV6goTEUEBGl9ERNA2kaDAu2wOvJ840BQtSqtNeRXJCgsDWrSgNE+t6JW243AAL75IkwdjjBnFgQO+rShFRVlj24GUtO90xgwOEijt3nv1HgFjxvHKK/q12gsNpRpd334L/Pgjtdhj6qpYEXj6aWDfPmDvXuDll6nrmzdBA5uNrpEaNFB3rAbFgQIju3RJmeM88wwFBHJTrBiwYIG2UbISJfSLyiUl0YlTSoo+z88YY7favdu3Va60NFqZMjOXizo2fPUVBwmUVqoUpcsy/f3zD1C7NhWXnDgR+Pxzapd3/Li2GZ2BrnlzoF077c9B7XagQwfKIuDgnT4qV6astYMH6T33xReBqlUpEHDrNZLdTkGdiAggOpq6xwUo1V4pQojyQog1Qoi9Qog9Qogn0u+fLIQ4I4TYkX7rodYYTO2bb+iCWokUqTp1co+E2e3Ab79pX1wwNtb39B9/SUlFDZ99Vp/nZ0whPMdayD//+NbxoFs3KrBkVikpQK9ewM8/c5BAaSEh1qpdoQNF51i3m9Kgly6lgmiPPw707g3UrUsXIyVLAs2aAQ88QHU65s4Ftm4Frl7VP1XeaqZN0+4cNDiY5uiZM+l8W4+ttyynqlWBSZOAw4epGOKkSRRIyAgauN3AQw/R38qGDeZ+n/VTiIrHTgMwQUq5XQgRDWCbEOL39K9Nk1K+o+Jzm9+QIfRRCGWO98ILwMCBmUVcbDZg9mx6k9JaTAydxOjF6aT2JvfeC7Rvr984GPMPz7FWsXmz9xcD0dHat7ZVktMJdO8O/P03Fy5UQ3g40KeP3qMwO/Xm2FsDYxcv0m3rVjo/stno/C8piVa/S5emi5s6dYCaNSlTpHJloFIl/RZezKp2bQpQzpunbjaH3U7/X/PnUwo8M6YaNYCXXqLb/v3UTn3OHPob4WsE9QIFUspzAM6lfx4vhNgHoKxaz2cpFy7QxxUrlDtmjx4UEYuPpzegUaP0W22IidG/IIjTSV0QDh7kfWLMlHiOtZD9+337vq5dlR2HVm7eBDp3pvTPpCS9R2NNYWFA06Z6j8LUdJtj09JyVuY/doxuK1dm7q92uehcplAhoFw5uuCpWxeoVi0zkFCqlP7nW0b05puUyaRGoEAI+j965RXgySf5928mtWrR/9srr+g9EsPQZFlXCFEJQGMAfwFoA2CsEGIIgK2gaO01LcZhGsOH00clTwKDgqiAynff0RvHa68pd2xvxcQYI5Xuxg0qUDJ3rt4jYcwvPMea2M2bNBd5IyiIAp2hoeqMSU1XrtAqzZEj1O2BKU8IyphTKiORGWuOTUrKHmC7do1uu3ZRzanISEp5T0mhC+ESJShoUKsWraZXrUr/rlyZMpMCUYUKdK792WfKzkN2OwVtFi6kbALGTE5IlS/YhBBRANYCmCKlXCCEKAngMgAJ4DUApaWUw3P5vpEARgJAhQoVmp44cULVcRpGaiqtBPTqRRONFZ04QVFvX/bkKs1uB778kk66GcuFEGKblDJO73HkhedYk9u0CbjjDgoYeCoqijLOWrdWb1xqOHcOaNOG6sSkpuo9GuuKjqZ059tv13skBTL6/AooNMcCTQ0xw4aF0Wq3lJSNEBFBPeirVaPzsurVKRuhShW64NVzm6jaLl+mLQFK1Uex2aj2xGuvmTOIyyzJ3zlW1UCBECIUwBIAK6SUU3P5eiUAS6SU9fI7TlxcnNy6das6gzSaGzeouODBgzRhW1F8PBU0NMqJYnQ0pf6WKaP3SJgBGflEludYC5g1Cxg71rv5sHhx2qJmphXjEycosHHxIld5V5vNBly/nne3IwMx8vwKKDjHCiFNMcPa7XSRm5ZGWQuxsdSXvlYtCiRkBBGqVKHsUDPNQbl56SXgnXf8q5MSEUG/p59+onbjjBmIv3OsaqFCIYQA8DmAfVknVyFE6fR9XwBwL4Ddao3BlAoXNkZavpqiomhvnVE4HFSvYd0687/psYDBc6xFtGpFGQV5zT253T9okPnmqj59gPPnqZo0U1fnzqYIEhhdQM6xeRVZ3LYtZ5FFITKLLNauTcGEjCBCxYp0AW10zzwDzJjhe6DAbqf5ePp0+pwxi1Ezp6gNgAcA7BJC7Ei/73kAA4QQjUApW8cBjFJxDMyIhMgsrGgELhewfTu9WTzxhN6jYcxTPMdaQf36wOLFeo9CXW437Z/mIIH6oqPpwoUpgefYrHIrsnj8ON1Wrcq7yGL16kC9erS9oXJlCiQYpchiVBQVrps0ybvtsGFh9Fr74QegSxf1xseYzlSvUaAETou1oLJlgbNn9R5FdnY7tSaqXVvvkTADMXpqrBJ4jmWqSk2lCwgTnG+YXlgYrQCbpJtPIMyvgIm2HqglY4Eoo8hiamreRRarVNG2yGJKCm2vuHjRs8fb7ZQF9vnntFWYMQMz7NaDgHf9OqUidelCqaXBwXqPyFiKFjVeoMDppErRe/caI9LNGGNWEBpKF7Dc5UB9TZqYJkjAAoiUQEJC9vvOnqXbhg25F1ksUyb3IovlyytbZDEsjOoUjB6df1ZBxtaLzz/nAtgsYHCgQC07dwJTpgBT07e1de8ODBhALQ8jI/UdmxHExOg9gpykBI4epSCPEcfHGGNmFR3NgQK12e3A4MF6j4Ix76Wk0C1DQgIV9T54EFi2LGeRxZgYanFYsyYFErJmI8TGel/DZeBA4OWXgWPHcv96ZCTQrBnw/fdUl4GxAMGBArU0aEATVcZ+rrlzgeXLaSJs1YompXvuAUqW1HeceilRQu8R5M7tpogxY4wx5RQpQu3ImHpcLqBnT71HwXITFMQ1Ovxxa5HFS5fotm0bZeza7XTOnRGMLF2aAgd161IwISMboVKl3IssBgdTnar778+eVRAURI9/911g5EjzFZFlzE8cKFBLkSKU/pf1xCgjaPDHH8CWLcCYMZTC9MADeoxQX6VK6T2C3Llc5qjUyxhjZlK0qN4jsL6KFal4HDOe2Fi6AL31gpf5z+XKu8jimjWZRRbdbvr9R0fnXmSxUSMKJuzaRcew24EaNajtYZUqGv9QjBkDBwrU1KgRsHJl7l9LTKSV60aNtByRcZQsSZFZoxW3CgnhiDFjjCnNqFlkVhEWRpmKzJgqVACGDweeesr3VnzMN0lJdMtw/Trddu8Gfv45e5FFp5OCCsnJ1Anh2We5xhgLaFyxTU3TpgEdO9Kkc2t/VbsdGDeOWmMFothY+r0YDfeeZowx5QXqNjuthIQA992n9yiyc7tpTP36AUuX6j0a/T36KF2YRkXpPRKWIaPI4o0bmQEcKWmbwfPPc5BAa243ZYIsXQps3Kj3aBg4o0Bd9eoBq1fT9oMffgA+/BA4dIhSmD75BLjtNr1HqJ+YGCpMkzXKawR8MmtMu3bR6+i22zjjgzEz4gJg6oqKov3YRvLxx8CKFZRBuWgRzeM1aug9Kn3dfjvw11+0iHT1KhXnY8Zhs1Eh8vHj9R5JYHC5gJkzgU2bgB07gBMnKDgTEkItNK9dM+aiYgDhjAItFCsGjB1LbfdOngT27QvsIAFAgQIjtiCsVEnvEbDc3HsvdQ65+26K/DPGzKV4cc7YUktQELVrM1IQ9fx54JlnMgvDhYYq29LOzOrUoaBJ7dpcE8lIbDYKbnGQQDs7d9L2jrlzqcNFcjLVkbh5k+aMvLZvM80Y8ErN4kqXNuYFstZiYoxXnyAykvd4GpHbTQG25GR606hZk4qBMsbMIzaWAwVqiYyk9H4jmTs3e+E+l4uKyDFSogRlFtx+e86tqUx7djswZw4wZIjeIwksFSvm/bWbN4Fvv9VuLCxXfMXK9BETQycORlK8OPDgg3qPgt3q9GmKLAMULLhwAejQAXjrLW43xZhZxMTwfl+1SAm0bq33KLIbPRpYsAC44w5KHU5K4kDBrWw2YOFC4LHHOFigp8hIYMkSbi2qh6JF8188XbKEt+fojAMFTB8xMbT/yCgiI4EPPuATWSPavz8zUJDB6QRefRXo3Jl7szNmBrGxeo/Aurp3N15af2go0KsXsHw5cPEisGcPp9nnJigIePNNOv+w2fQeTeApVIhalnfsqPdIApMQQNmy+X/9zz+1Gw/LgQMFTB+FChkrSlinDp1sMePZty/3opcOB1XFrVkTWLdO+3ExxjwXG2u8LDIriI42/pa5QoXoPZblbdgw4Ndf6XdlpFoTVhUURAtWmzYBcXF6jyawVa2a99cSEoDvv9duLCwHDhQwfQQFGSd6brMBH33Eb85GtWMHbTnITUoKVY6+4w7gxRf5QoQxozJaFplVpKQAXbvqPQqmhPbtga1baYWV63moJyQEKFUK2LaNA1hGkF+beCmBn37ibaY6Mkeg4MIFvUfA1GCE/YrBwUC3bkDTpnqPhOXl338LfozTCUydCrRpQyfOjDFjKVKEX5tqaNWKts4xa6hend7zGjY0zmKKlYSFUQG9bdu4y5VR1KiRf42O1FTg77+1Gw/LxhyBgjNngK++0nsUTGmFC+s9AtpHOW2a3qPw3fHjwKRJlLLodOo9GnUcOeLZ4xwOYPduqlzMGDOWoCAu2Ka0yEhg8GC9R8GUFhMDrF8P3HMPv2aUFB5OLSm3bKGMAmYMVavmrEOVldMJ/PCDduNh2ZgjUCAlVdBdvFjvkTAlxcTo+/wREcCIEeaNKu/bR5kQb70F9O8PFCsGzJ+v96iUdf26dwGQxEQqcmi01puMMWNkkVlJWhpw9916j4KpISyMgt4TJ3JmgRJsNqBZM2DDBqq0z4yjSpX8a5a5XBQo4PM6XZgjUADQxcKAAcDatXqPhCmleHF9nz84GHjlFX3H4Kvt24GWLWl/vstF/WYdDuoBPHGidfZzHTjg/UnSxYvAypXqjIcx5rsiRfQegbXUqAGUKKH3KJhahKDaO198wZkF/rDbgU6dgFWreJuOEZUvn3vB6qwSEoBdu7QZD8vGYP10CuBwAHfeSRXOmzTRezTMX3qmfkVGAi+8oH9Wgy/+/JM6NCQm5vya0wnMnEn77376iSoom9n+/d4XKExIACZP5gJfjBlNsWJ6j8A6IiI833bw2mvAzz9T0NVmowsnux2IiqL3woxbRATdbLacn+d2X8bnISFcDFhN/ftT5uMdd9CigFUWArRgtwO9ewNffsntr40qJIS64ly8mPdjUlKAuXOBBg20GxcDYLZAAUAXR506AX/9RW3RmHnpGSiw24Fx4/R7fl8tXw706UNBs7w4HBRMqF+fVtarV9dufErbvTv3gEhBtm6lbAszBoIYsyoOFChHCODeewt+3LFjwBtvFLxiFxREF1IZt6Ageo6sAQAp6eZ2UwA34yYlneyHhdFe4/DwzFtGQKF0aUof5jR637RoQR2AOnYEzp7NuxMQy2S30/bS6dM5kGV0FSvmHyhITQW++w54/XXtxsQAmDFQAFBEtW1bSr8uX17v0TBfFStGJxJav+FFRlKF/IgIbZ/XXz/+CDz4oGd79pOTgVOnKKjgSdcAo9q2zbfvCwmhNLUOHZQdD2PMd6VL6z0C64iN9SwI/MIL+e//zeB2083XFpapqfl/b3AwfZ0DBb6rWJGCBXfdRe+N+S0YBDq7nbZhvvii3iNhnqhTh4pM5ufCBeDQIXMvfpmQeWoUZCUlcO0a0Lo1cOmS3qNhvoqJyb/SqVrKlgUGDtT+ef3x6aeeBwkySEkFD8288nDggPffExpK2RRt2ig/HsaY70qX5pU9JYSEAPffX/DjjhwBFizwLFCgtmbNzL8VzggKFQJWr6b/f65bkDubDfjf/zhIYCZ16tC8lh+323oFu03AnIECgNLdLlwA2rWjDANmPjEx2u8Zs9uBjz6itEqzeOcd4IknfGt/aLPRCoQZpabmn4qWl6JFgSVLCn7TYYxpKzaWssiYfyIiKFusIM8/73uGgJLsdm7jqKSQEOCzz6jDD2doZGez0e9mzBi9R8K8Ua1awYGvtDQuVK0DE10t5SI1lfbfde5s3R7yVqb1/nEhgLg4qnFhBlLSid7LL/v+952cDGzcqOy4tHL0qPfbQ+x2YMUK3gvNmBHFxuqTRWY1wcG0Qp+fQ4eopbS3xWDV4HIBPXvqPQprEQKYMIHqPnBmAbHbgXnzzJcxyqhFYl6CguhcsHdvYPZs7cbEAJg9UABQJczdu4F77jFGeh3zXEyMticxERHABx9o93z+kJIi4u+9598+xORk80Zg9+3zLvPDbqeVhEaNVBsSY8wPsbG89cBfQtBFd0Fz43PPGSObAAAqVADKldN7FNZ0zz3Ahg302grkLLrISODXX6kzGjOfKlWoY9Wt7HbqYLVtG3U9qFhR+7EFOPMHCgCq5rthA0URuW2MecTEaHciExoK9OoF1KunzfP5w+UCBg0CvvpKmWJFf//t/zH0sG+f5z+/3Q6MHAkMGKDumBhjvmvQgAK2nFXgu+jogusTHDgALF1qjGyCsDBe4VVbo0bAzp1A1armK9Lsr4zA4/DhVOScmVOhQlRbKmM7shBAy5bAH39QAKhOHV2HF8isESgAKDV76VLg0UdpNZYZX5EilBGihZAQ4O23tXkuf6Sk0ArBokXKVTSOjwfOnVPmWFrats2zLKGwMKBJE6rlwBgzrhIlKADYsiWnS/sqJaXg7XPPPqvde2tBQkMpZZipq0wZes9s3z5wXlsZLTxDQyklvXNn3+oaMWPYsYPO+dxuWgDetKngLVZMddYJFAB0YfXNN8BLL+k9EuaJ4GBtot8REcDYsdTtwOgOHwaWL1e27VF4OLB5s3LH08qePZ49LjaW9uJqXRiTMea9mBhaJRo3jgux+aJjx/wLQu7dS3VajJJdabfTSiFTX2QknT889JD1gwUhIRQc+eIL+lkTE4H164EaNYBfftF7dMwfQtACEDMEawUKALrAmjoVmD5d75EwT0RHq/8cYWHUS9oM6tShrQJ169KbvhJSUoDjx5U5llak9GzMdjvw++/U6YAxZg5BQcCUKcBPP9F7gJm60OgpKoq2peXnmWeMk00QFATcdx/XpdBSUBAwYwZl2Fk1EBcWRnvat20DunWj1WeAtrLeuEE1PIYPN06NDsZMTLfKJ0KIOwC8ByAYwGdSyjcVO7jDQdXiY2OBBx5Q7LBMBYULq5sqFhlJLYTM1L85Lo72G37xBVU1TkqiooS+CgkBhg5VbnxauHCh4MfYbJRBVLeu+uMxGVXnV8aU0r07zXXduwMnTnD3ooKkpAA9euT99V27gNWrjZNNEBkJ9Oun9yhUYfg5dvRoajnXu3fuReLMKiICqF0bWLOGzh+lpNabBw9S2npaGtXmOHKEswyZeblc9Lq9eZO2D2fcsv775k3g2jXg6lXg+nX6POPrCQl0LZwRRPODLoECIUQwgA8AdAVwGsAWIcRiKeVexZ7E6QRGjaKVxrvuUuywTGEqrgR/Vx+YdHsSTl4fjwrTp2FK5ykYVL+A1RijCAqi9MH77qP9pt98Qy94b+tv2O20FUfrVpT+2r+f0mvzmuTsduDxx3nvay40mV8ZA/Ddru8wadUknLxxEhUKV/Btjq1UCfjnH2DECGDhQmW3XVlNw4b5v2c+84wiJ4aKcbksWWDONHNs166UodixI11MmH2F3WYDmjcHli3L3FohBHU7siBF5lemndTUnBfyt36ecXF/5Qpd3N+4QbeEBNo+43DQ9WtaGtXeCAmhgFdG1p2UNK+mpdHzaRAU1iujoDmAw1LKowAghPgBQE8Ayk6yTidFs1esANq1U/TQTCEq9bv/rmkYRt6RAkcoVX0+ceMERv4yEgDMNdEWKQJ88gm1SnzwQapmnZjo+fdHR9MFtdns3593+mx4ONC6NaUus9xoM7+ygPbdru8w8peRcKTShb1fc2xEBPDtt8CnnwJPPMGZBbmx2WjlNC///gusXWusYs63327VDhfmmWNr16asna5dgUOHzPvaymiTN3duQOxfV3R+Zeo7coS6+rhcmRf3GVuu3O7Mi3tvtoWlpBhiG5leGwPLAjiV5d+n0+9TntNJb1Z7jTd/MwAlSyp7vMhIoFgxTOoZBcct5yeOVAcmrZqk7PNppUEDYOtWYNYsWlHypAhkZCTw3nv5F74yqn//zf2ERgiqnP7TT7yvOW/aza8sYE1aNem/k9gMfs+xDz9MBclKlgyIiwGvSEl7r/Py9NPGyiaIjrZyW0RzzbElSgB//UXnwmYscmi306LfTz9Ze1545RXabgqV5lemnscfpy3Cycm0mHfzZma2QHw8ZQoY4KLfF4Y90xZCjBRCbBVCbL3kywGiouiWsZ8pRLdyDCw/pUsrc5zISKB4ceDdd4EzZ3DSfS3Xh528cVKZ59ODEHTideIEbauJiMj/YrlSJfPuD92xI/f7IyOBlSvNVXPCoLLNsZd8mmVZAMtrLvV7jm3ShAL7rVqZ86JGLWXLAhUr5v617dspwGKkbILkZOCOO/Qeha4MNcdGRNDWnscfN9frym6neguzZ1u75oCUwOTJVIz96lX15lemvM2bqWaGy6X3SFShV6DgDIDyWf5dLv2+/0gpZ0kp46SUccWFoOh0XiujkZEUFAgLo8JmjzwCfPQRrcAmJtKbaI0aqv0wzA/FivkXIY6KotWn6dOBM2foAjosDBUKV8j14XndbyrR0fTz/vMP9SPPrTuC3U5bFsxabfrQoZz32WzAnDn8Wi5YgfMrcMscW7y4ZoNj1qDqHBsTQ0X5JkywbuV2b4SGAgMG5P31p54yVjYBQEV5tehqpA9zzrFCAP/3f3R+bIbXld0OTJpEHRzMei7jqbQ0WtAMCwM+/9za57BWIiUFssy6pccDegUKtgCoLoSoLIQIA3A/gMV5PrpxYzppePNNaoVSuDC9oKpXp33bM2YAGzZQUGD3bpoEBw8Gatbk9GSji4nxbQ9jVBRQqhSl1p86RYWwshxnSucpsIdmj5rbQ+2Y0tlC+9pr1aJVpK+/pmwKm43eTG022r/fpo3eI/RNYiKla2Vlt1NRRy5M6gnv5lfGfKD6HBsURB1rFiygDKJAfi8PC6PCtrnZupVWtIyUTWC3519PwfzMPccOGUK1uwoVMu4FuM1Gq+vPP6/3SLQRGkoBkZQUYPbswDiHtYKff859YctCdHnnlVKmARgLYAWAfQDmSin35PkNQlB0etw44NdfqWKk00ntUGbPpn6pDRrw9gIzio31Lp0sKopSMD/4gAIEw4fnGmgYVH8QZt09CxULV4SAQMXCFTHr7lnWKwIjBFX+P36cioC1b09p++PG6TwwPxw8mD01MjwcuO026t7ACuT1/MqYDzSbY++4g4qx1axpjlVQNdhs1PEgNxMmGG81SwgKYFy9qvdIVGGJObZdO2DbNjqfMtq+f5sN+PJLyhA1qqlTgQoVaEtHgwZUjNWfNtYAncNdvQr89VfgnMOaWWoq8Nhj3hUYNyEhjRSFzkNcXJzcunWr3sNgati4kfpC37qCfKuoKOoA8H//RymYVt6rFujmzKEThPh4WkWsVImKG0ZF6TIcIcQ2KWWcLk+uEZ5jmeElJQEjR1JBs0BqoRgUREUeP/4459f++gvo1MmYv4+ICHqffu454Mkn8wzyBML8Chh4jr12jYJxu3YZI+Bkt9Nr3Oj1LWrUyL6SHBVFr9WRI+nisYLOWwTmzwemTQPKlaOPZcroOx4rmjmT5jeDBwoE4NccG8C5fMwQYmLy7wMaFUUT7qxZtGo+eDAHCaxuzx7qKQtQ/YXff9ctSMAYM4iICNpmNXNmYGUWREbmXZR2wgRjBgkACuwkJgJvvEEXK7Nm0T5sZixFiwJ//gn06qV/kcOoKHq/N3qQAKCaWFklJFCl+xkzKPupSxcK5Oll5kxaiFuwgDIejDpPmFV8PPDCC4YPEiiBAwVMXzExFMWOiqLaE4UK0UlgWBhQvz7w2WfAsWOcRRBIMvYiBwVRVLxKFX3HwxgzjuHD6QS4VCnjpUyrweWiNPFbbdxIBW2NzuGgdOonn6S5fMECY9VTYPQ6+u47Wh3VIwgnBGWMbtgAtG6t/fN769q1vINeKSkUJFu1CujeXb+/9QsX6GNaGl3Unjihzzis6vXXaetBAOBN/UxfxYvTG1RKCvX6zbiVKhXYxasC2auvUj2ClBT9VzgYY8bTqBG1ULzvPlq1s/JqWbduuRf8NXI2QW4SE+k2ZAhQuTLw/vtAhw56j4plEIJWSGvWBIYN0/ZvK6M1YIMG2j2nP44epQynlJT8H5eSQtsmGzXSZFjZXLlCH+12qllVu7b2Y7CqM2coY8MIW3U0wFdiTF9CUFrl4MHA7bfThFqmDAcJAl1ICAcJGGN5K1oUWLkSePpp625FiI4GBg7Mef+ff1KBRzPK6E7VowcVqWXG0rcv9YQvUkTb87Dnnwf69weuX9fuOX115IhnmQIpKcBinZphOBwUYGzTBnjtNX3GYFVPPx1Q26j4aowxxhhj5hMURCuRP/9M29astj0tJYUyCm5ltmyC3DgcwLp1eo+C5aZ5c1oJr1SJug5pweEAFi0CqlYFli7V5jl9dfiwZ6+/1FTghx/UH09uli+n7T7z5/PCm5J27aL3mwDZdgBwoIAxxhizloQEKvw3cWL+xWKt4vbb6QTOai0UmzWjrIKs/viDtl1YAdcqMK4KFagGRsuW2mX3JSdTPYt+/YydXbB7N9UO8cSRI8ClS+qOJzft2wNvvkkBVKacMWOoBkUA4UABY4wxZnapqcCyZUDPnlT7ZcwY4K23AudirEIFYPt2usCwwrYlu5225GUlJWUTBEClbWYAhQrR9p6BA7V9TRk9u2D/fs8fGxYG/PqremNh2lm1Cti2LXDeU9NxoIAxxhgzIymBzZuBESOog8z999Oe2KQkyioICTFXOr7T6d9JWHg48MUXwAcfmD9Y4HJR0Cer1auBAwf0GQ8LTCEhwKefUpV3LbN1smYX3H+/sbILTp70/LEJCcCPP6o3FqYNtxsYPdr8W758wIECxhhjzEwOHqTiX6VLA1270sVxQgK1wcpKq/3FSli1CoiNpa43Eyb4d0E8bBi1Dyxd2rwtFKtWpe4/GaSkPcecTcD0MH48MHcuEBmp7fM6HMBPP1FrzeXLtX3u3CQnex+0WLMmoIrfWdJ33wFnz+o9Cl1woIAxxhgzugsXgGnTgFq1qDvMO+/QfQkJedchiIjQdIg++/Zb4O67KaPg8mVgxgwgLs6/vfgNG9L3t2tnvuyC8HBg0KDs9/3+O+13Zkwvd90FbNhAAb0QL7qr22w0FxUqRLfChamrQpEi1L0kJoaOGRtL26Yy2mSXLEnBsuLF6RgLF6r1k3nu+HHvMyuCgmhbFDOnpKSADtJ68UpnjDHGmGYSEoAFC4CPP6YTzaAg73o3Gz2jQEpgyhTgjTey/1xpafSzd+5MRQqLFfPt+EWKAL/9Ru3B3nrLPH2vg4OBe+/N/DdnEzCjaNiQXpOdOtFFc0GF3Ww2ev1NmKDJ8FR35Ij3XQRcLgrwMnOaOjUgtxxk4IwCxhhjzGhOnaIVtTFjgE2bKOXV2wtdI6+ku1zAww8D//d/ef9cV64A48b59zxBQcDLL1NxNLO0UCxSJPuFxa+/0kUZY0ZQujSwdSvQoUP+c4zNBsycaZ0gAUCBgpQUzx8fHAwMGMDdB8zqyhUKZHOggDHGGGOGcfkypfcmJPh+DKMGCpKSgDvvBObMyf8ELKOTgxJVprt2pbZmtWoZu4VicDDQty8gBP2bOx0wI4qMpNfmww/nPs/YbLSv+6GHtB+bmvbv9649XliYtQIlgWb69ICvL8GBArN4/32gaVPg558979/KGGPMnJQowqd14TFPrV4NrF3r2SqNN3uhC1K+PLW3GjDAuEEUu50CBRmWLvWuyjpjWgkKogupqVOzB98iI6n7StbtM1axe7fnjw0LA9q3B+rUUW88TF3Fi2cGbQMUBwrMoksX2hfWty9QrhxNzrdWuGaMMWYNYWF5Fyn0VFSUMmNRWqtWnv1skZHUlk3JE7XwcODzz4EPPzRusKBlS/rI2QTMDEaNosCA3U6v2VWr6JzVio4eLfgxNhvNMx06AD/8oP6YmHo6dzbHdjUVcaDALGrVAmbNopPH8+eBSZOoGuxjjwEnTug9OsYYY0oKC/M/5T46WpmxKK1oUercUJDISODBB9UZw9ChVPuhTBljFH0MC6Oft2/fzBPTxYsDtiUXM5kuXSgtf+9eoEULvUejDimp00xuQkIoUFKtGhVoPXWKCqkWKaLpEJnC6tTxvnilxQT2T282w4ZRC6mICErZdDiATz6hIMKdd1JKJWOMsfx5U4xKL8WK0UmmPxf7Ri6gNWRI/rUCIiOpiFRoqHpjaNAA2LOH0oO1zi4ID6f/24gIoE0b4JVXgJUr6T0doIyLCRP8q1HBmJbKlwcqVNB7FOoRAvjgA6BmTXrdZryGCxcGRo8GNm8GDh0Cxo+nlHVmfkIAbdvqPQpdcaDAbD7/nPrLZkhNpROKZcuo9zRjjLGczp2jvbS1atFFYbdu1JteiUJ5aoiMpGyx776jE5WICO8vmgsXVmdsSrj/fqqeHhpKAY1b6ylER9Oqv9qKFKGuAhMnqlvkMCKCtoLY7UDHjhQEWbOGAgHr19Pzt2yZWZMhMZGzBRkzmocfpsyJ3btpW9QPP1Dh2RkzgPr19R4dU8Pddxu7AK7KFKwSxDQRGUnFjVq0oKKGVaoAgwcDvXtzn1bGGMvq+nXgp59olXbnTkohzGjF99tvwIYNlDL7ww90IWc0wcF0knL33cCxY9Rq7LPPKLjhyUqzkTMKYmOp1Vh8PLBvH63s79hBbdeOHKECvkoWMsxPUBDw4otA69bAfffR79bfosE2Gx03KIiO26MHcNttQL16nqWyRkcD/fvT3yYXMGbMWKpWBZ56Su9RMC107hzQBQ05UGBG9eoB27fTiUSZMnqPhjHGjCMpiYKpn3wCrFtHF5t5FYNLTKSAQatW9NHI6aKVK1NGxP/9HzB/PvD225Tmmpyc+4VkSIhxixlmFR0NNG9ON7117kwrhT16AIcPZwaVPBEZSQGcsDCgXTs6RocOFMD39SRz8mQKdHGggDHG9FG9Os3rnnTpsSDeemBWNWtykIAxxgDqc/z777QCGxNDBfB+/50uoguqGO900mp2gwaUUmp04eHAoEG0+r55c+Ze/1tT90NCPGuPePMm8PTTwI0bqgzXdMqVo6yGQYPyr1sQFUVZKMWKURbCjBnAv/8CV69SEcJHHgFq1/ZvJapaNdoiE+DFtBhjTDdCUNA3QPG7D2OMMXNr3py2X82dSxf+3raOTU2latadOtHnZlG/PjB7No397bcp6yAyMvPi1JNAwaefUqZCv37GrdegtbAw+r18/HFmsCCj8GCpUsCAAVTUbP9+4NIlyvAYPpwu7JVOUa1bV9njMcYY887dd3v2fmpBHChgjDFmXufPU0suf6vDS0mr659/rsy4tBQdTVW3jxyhLRS9etFJTVxc/t/ncgH/+x8VxF2/ntp6sUwPPEBZG489RltZDh+mopjff0+ZHBUrqj+G1avp/4cxxpi6XC7giy+o/luNGsDttwOPPw4cPBiw8zDXKGCMMWZeq1dT5fzkZP+PlZgIPP88Vds3Y5VjIahw3oIFnj1+8eLMfZcOB1Xib9mSCjwyUr++fh2FpKQinIyxwDF/PlCpUsGBXqYct5vqwUyYQNvHMrYsHjpE2xjDw6m4cADijALGGGM5mSUFf/FiZXvNJyQAs2Ypdzwje+217L87p5P22588qd+YWKYjR/QeAWNMS5s3UyZT+/bU+YW3g6lLSmqPW7s21TY6dSr3ukbJyQFbzJAzChhjjGW3bBlw552U0l6qFFChAlX+rV6dPs+4lSihb6E1KSna7w8h6OdMSaF0/RYt6CTN6rZvBw4cyHl/YiLQvTt9PTxc+3GxTLGxAd2Wi7GAkpwM3H8/de4BgGefBdasAb7+OmD3x6vuwQcpg6OgoscBjAMFjDHGsluxgi5Q4uPpdugQsGoVFXmLiKDHpKRQt4FKlYBt24BChbQf56FDmSdVngoPp5vTSYGPTp2oonGrVkDZsuqM04jeeCP3353LBRw7Bjz8MJ2gMv0ULQq88AJlfgToahZjAWPyZCqOmsHhoKB9/fq06l2jhm5Ds6SrV4EfflBm26KFcaCAMcZYdqtX557ymJJCt6zOngWuX9cnUPD77wWnZkZH0zaKiAjKFujalfbxN2kSuCvm584BS5fmXZzJ6aT9mu3aUcCA6WfcOGDaNA4UMGZlO3cC771Hc29WSUnA8eP0fvXll0CfPnqMzpq+/z5g6w54Q5WcUSHE20KI/UKInUKIhUKIIun3VxJCOIUQO9JvH6vx/IwxZmWqzrGpqVTh1xshOsWcf/45+4lVWBgFLEJDafVl1Chqc3fgAK0e/PorFStq1SpwgwQAMH16wQEWhwN44gnKFmH6iYigCwhOPdYUn8cyzaSl0ZaDW4MEGaSk1PihQ6kDi1nqBxndjBkcgPWAWptLfwdQT0rZAMBBAM9l+doRKWWj9NsjKj0/s5oXXwQ+/JALuzBG1Jtj09K8awPkdusXKNi2jYID0dG0heCVV4AlS4AbNyg48PHHQP/+VE+B93oTp5PmUk/SLZ1OoEcP4MoV9cfF8ta/P23xYVri81imjXfeAU6cKPhxDgcwezZlxp09q/64rOzff4EzZ/QehSmocnYnpfwtyz83A+BcGea7/fuBd9+lE32bjYqPMBbAVJ1jbTagUSNg69aCHxsaSq9LvVY7166l565cmQMBnvrmG+8CrteuAb16AX/8wWmaehGCgl7duvEKmEb4PJZp4tAh4NVX884muJXDAezaBdStSxl1HTqoOjzL+ugjrk3gIS3KVQ8HsDzLvysLIf4RQqwVQrTL65uEECOFEFuFEFsvZS3uwQLP66/TvmiHg9KuXC69R8SYkSg/x06YANjteT9jRlHDBx4A9u3TL1BQvz5QpQoHCTwlJRUx9KbCc2oqdUB4/nn1xsUK1rYt1YzgYI0e+DyWKc/tBgYM8P6CNS2N6gJ17w5MmcKZtt5KTga++46vJTzkc6BACLFSCLE7l1vPLI+ZBCANwHfpd50DUEFK2RjAkwC+F0LkWgFLSjlLShknpYwrXry4r8NkZnfuHBXVynhBCwHs3avvmBjTgK5zbP/+wODBOYMFERGUcTBqFHD0KPD550DFikr9yExtK1f6to3A4QBmzgQWL1Z+TMxz779PWTxMEXwey3T18ceUMevNVr+snE4K/HbrRoED5plffuHFBS/4vPVAStklv68LIYYBuAtAZykp3CWlTAaQnP75NiHEEQA1AHiQ48oC0rvvZo+WpqRQX3fGLE7XOTYj1TklBZg3j05kgoKouN2TT1J/d2Y+r70GJCT49r1OJzBoEPDPP0C1asqOi3mmWjUqaPbll5w2qwA+j2W6OXUKeOYZ77K7cuNw0Ba8OnWA5cuBhg2VGZ+VvfcetX1mHlGr68EdAJ4BcI+U0pHl/uJCiOD0z6sAqA7gqBpjYBYQH08XK1lPiIoUATgyzwKcJnOsEFQ4ae5c4P/+j7J7pkzhIIFZ7d8PbNni3zESE2n1yt+TW+a7KVP0Kx4aQPg8lqlGSmDIEOWCfSkp9P7cujW9Z7O8nT7t//tggFGrRsH7AKIB/H5L+5j2AHYKIXYAmA/gESnlVZXGwMzuk0+yt4Gx2agAiRquXuX9SsxMtJljhaCq9088QZ0FmHm9+ab/bbWkpGrbgwfzvli9xMYCL7yQfw0RpgQ+j2Xq+PZbulhNS1P2uBl1vIYMAZKSlD22VXzxhd4jMB0hTfBmHxcXJ7d6UoGbWcu8ecDkyXRiWrMmrWp27Kjsc6SkANOm0fM88QSdTDOWhRBim5QyTu9xqInnWIu7ehUoW1a5k0e7nYrMjh+vzPGYd5KSqDbIxYt6j8RvArD8/ArwHMvSXbxIW4jUTH232agl8PLl1BGIESmBMmWA8+f1Homm/J1jteh6wJhv+vYF9uyh9lybNysfJPj1V6qY/uqrdOJlsyl7fMYYMwKlM7EcDmDSJGDDBmWPyzwTEUH7bPXqNsIY883DD6u/2u90UtvFBg2AJUvUfS4z+fNP32v0BDAOFFiVlMCJE5wemheXC7jrLuDMGTrpDQ8HihbVe1SMMaY8h0P59wKnE7j77oBbnTGM/v2BSpX0HgVjzFOLFlHnGX+3gHnC7aaL4n79gGef5a21AHWN4fo6XuNAgVV98w2tlleoALz9NsA9fLMLDgZKlMj8d0gIFUpkjDGrefJJZQvghYdTzYpr14DVq5U7LvNcRmcSrlXAjGzMGJorypcHGjUCbr+dOne88AK1XJ0zhy6e//3X2p08rl8HHnyQgrZacjrpArldu8C+Drh5k9oi8uKp17h0rhXdvEn77d1uqvD58svAiy8CXboA48YBnTpRq7NA16QJsHQpfR4czBkFjDFrio2l7QePPJLzRDU0FAgLywwkpKXRe0daGt1frBh9f4kStL+zbFn6vFgxoGRJoH177X8eRtq2pQuAlSt5xZAZ09GjtLKdkEDno1mFh9P8ExxM89K0aRRYsKKxY7UPEmRwOICtW4HateliuVUrfcahpx9/pL8z5jUOFFjRpEnZ90A5nfRx6VLqt2q3A48+SnulypTRZ4xG0L498PvvVNBQCM4oYIxZ1+DBVFNg/XpqMVu6NF30lypFF/3Fi9PHYsWAQYOAv/6iPa6bN3M7PiN7/32gfn0OFDBjyq+dbnJyZhZBRAR12LGiVauAhQv1zZhITQWuXAE6d6YWq+PG0XlvoNi3j+dIH/G7v9Xs3Qt8/nnexVIyIrtvvkldBFq3psrV3bsH3slgXBy9OaWkUDoSBwoYY1aVkaruidGjgV276OTquedo+xozpmrVKJX7yy+tnbrNzKl48YIfExxM9U6sWKE/MZECr3plE9zK6aRtH3/8AXz3HRAVpfeItPG//9HP/vXXxvm/MAnOP7cSKYHhwz2rqJqURCcVa9bQJFa8OBU8OXZM/XEaRePGmdkWaWm89YAxxgDg3ntpTnQ4gA8+oA4xzLimTAm8QD8zh9jYgleuQ0OB117TZjxae+cdak9rJA4HsGIFULcuBYMDQUgIbb/78EPucOYlDhRYyfz5wO7d3hfriI+nQivTpwN16tD+pblzrb86UbRoZhZBaipnFDDGGEApqhnb0pxOqrB/6/5iZhyxsbRKyIUNmdEUKUK1CPISFETp8DVrajYkTfXsSVk/RmtlmpwMnDxJmbVz5ug9Gu0MHQqsW0db7Di46hEOFFiFw0F1B/xp/ZGSQpkGmzcDI0ZQlsFjjwH79ys3TqNp3Jg+ulzGm8gZY0wraWm0j7ZNGyp6deZM5tcSE4F77qHHMGMqWzaw9hwzcyhcOP8LsvBw4I03tBuP1ho1AvbsoU5kFSsa7zzT4aDz/VGj6BogEMTF0f9Jw4bKZRcIYdn5lwMFVvHKK8r2B42Pp9vHH1N3gEaNgK++st7ennbtaH+c3W7ZFzljjBVo9mzahrZxIwWMs540ulzAgQPAM8/oNz6Wt127qKMF9whnRlO4cN5dtoQAWrakoqlWJgRt5zpyhNLfS5Y0VsDA4aBARrNmgZM5VqIEsGkTvecpkYkVEQEsWEDZXRbrKmetnyZQHT5M/Wgz9tsrKS2Njvvvv9TepXhx4KGHgB07lH8uPcTFUaBAy0k7Pp6KyMycSQGeRx8F7rsP6NCBfseMMaa1w4fzfw9xOChwnNFSlhnDtWtAt27WC+IzayhSJO9FGJuNimoHiuBg4IEHKOX/f/+j341Rtgs5nbTKXq8eXUAHgtBQ4NNPgffe8+//wW6nFvS9egHbtlFHIQtta+BAgRWMHKlNPYGEBDoZ+eorSk+1Qv/sxo1p5Sw6Wrvn/PBDCrY8/TQweTJFmBcsoH1Ts2YBN25oNxbGGAOAU6cKfozTCQwc6NljmTaGDaOaElkZabWSBbbChfOum9WwIdCihbbjMYKwMFogOnuWLjCjomhFWm8uF2WT/fGH3iPR1ogRwOrVQEyM9xf4QgCVKtH5PEDbS7ZvB6pWzb82h4lwoMDsfvmF+l273do9p8tFAYMNG8xf8LBkSfqo5WpMQkL2/sFZCUGFFRljTEvnznn2uMREamXG85S2Ll6kYsNFi1Jxye+/p/tatMh+cmu3U2G44GD9xspYhsKFc+9fHxkZWNkEubHZgIkTqR7Mk0/Sa1fvi0u7HXj8cX3HoIcWLTIzKrypWxARQcXfs87BJUoAW7YAffrQ7zMsTPnxaogDBWaWlETZBHqlHNpsFBE1uz/+oBV9rXTrlvdEVLcuVWNlyklN1TaQxpgZXbjg2eNcLuDQIeCpp9QdD8t07hztHz50iDoUzZ1LNQnKl6faEi1a0MmozQYsWgT8+COl1TKmt8KFcw8qVqtmjaxUJRQqRC1OT5wAHn6YXsd6vH4jI4F33w3cjKRSpWjhtX9/z7Yi2O2USVC3bs6vRUcD334LrFxJAbFhw2gOL1aMgrhRUfT/boIgAgcKzOytt4CbN/V7/pAQa6Sgduigbfpb27bAyy9nTkR2O92KFAFefVW7cVjV1avAkiV0IdOwIb3pValCWzsYY7nzpte3w0F7O3/5Rb3xMHL6NJ1gnj2bvetEfDxtmztyBFi7lk4+U1OpkFa1atQGTO/VScYKFcoZKIiMBN58kwtI36pYMapddfAgMGAArVZrmRlUtizNG4EsLAz44gsKmBSUWVC2LLWlzU+rVpQt8sUXwN9/A5cuUVbeli1Uq8wEQQTrVFsINBnFUPQsYORyWSNQoIdnngGOHaOVojvvBDp2pJM7fuP03Zkz9Cb355/0Bhsfn7k38sQJoHt3+l2//z6lhjHGMnlbG8XppIrRu3bRvkymvBMn6ETz4sXc07czuN30/yEEBUQ7daIVym+/Nf/2QGZuwcF0wZP177BcOcqsZLkrV45qgb34Ip0r/vorZRDnVetBCXY71ciyWMV+nz3yCHXjuOsuOpe8tTWwzUaZXb5kfoSHA7Vq0e1Wycl0bXD4MAWMdu+m27Zt9HUdsmM5UGBWo0fr3/M0Kcl4gYKUFEqhPX8+83b2LHD8OI313Dm6UOzYUd9xCkEVxJn/pKT023Hj6GTZ5cr9teFwAD//DCxfTqsZjzzC+3gZA2guv/VEyBMOB51IbdtmmNUPyzh6lIIEly97fnIoJbWxBKhN1wsvAK+9xh0RmL7s9sxAQVQUZxN4qlo12ha7axcwfjx1I1DjtRwURJmuHToof2wza92aLtLvuCN7VyC7HXjsMWobr7TcggjTp1P9BJ3mcQ4UmNGqVbSv3pcTOyWlpdGLR09PPUW/i4sXqfJzUhKtJoeG0klTRnvHjEhsRAQ9llnDqVNUhf2ffzzrIZ6aSrdnn6XuE998AzRpov44Wf6k5BNHPV26RCco3p6IuFyU+v7kkxSAZco4ehRo3py2g3i7injkSObn48cD06ZxoIDpKyqK2ngCFMC65x59x2M29evTXvfNm4EnnqCLRk/OdzwVFsbzd17KlKFtAg89BCxcSHNpiRLU2lwL8+cDzz+ff+tilXGOidmkpgLDhxvnjT/rSYke5s2j1axTp+h34nbTxxs3qH6Dw5H9REtKLqBjBVICn3wC1K5NUXZv3zQTE4G9eymK/vDD3JJSD0eOUO2IkBA6UeH6HPq5eNH3vs9OJ+2//PlnRYcU0M6epTnKlyyN06czPw8Ppx7hgVqcjBlDRvvpqCjgjTc4vd1XLVtSsb1Fi6gDihKv6/BwuqaoXt3/Y1lVeDgtKv3vf1Q7YO5cbeq/rF9P22l1DBIAHCgwn2nTKBXRKPTeevDQQ969YIsWBUqXVm88TH3HjwNt2gATJtDJdH57dwvidNIbQKVKVFhGzT2ALJPTScV7jh+n/7+0NDqBNNLcFkguXfIvo8PhAB54gP4/mf/atqX6BKNG0V5Yb97jLl3KPo/170/zG2N6KVKEPhYqRH+PzD+dO1NK/Lff0mvbn4BBaCjw+uuKDc2yhADGjKFFpWbN1H++vXuBHj0MsSjMgQIzOX+eVt0M8IfzH09baqll4EDvTnA7dVJvLExdbjelx9WtS9VjlUq9S06mlmOjRtGe4P37lTkuy9vZs5QdlfWCJjiYMoSY9goqlueJjHoFetfOsYoSJSgb4PhxqknkacAgODh7wE0Iyr7ypN0XY2ooWpT+Dl95hesCKUUIoFcv2v778cdAyZLeBwwiI6mGSdGiqgyR+ejsWeC226iIogFwoMBMHnvMeCdhDgfVBdBLtWqeV9yOiqKiJMx8jh6ltLuJE+lvzt+LmtwkJlIAokkT6o1rpICc1Vy5krNAm8MBLFumz3gC3aVL/lfHd7vpdfr448qMiZESJSiT8MQJ4NFHCw4YhIfTY7Nq04a23PFFGtNDbCzdhgzR5vlOn9Y9XVszwcHA4MGU3fv223TR72lQsEgRWiVnxnHjBs3V3rQrVhkHCsxiwwZg6dKc/Wj1ZrNRWzo9jRhBRQoLkpbGVV3Nxu2miq/161MtCiUL+ORGSjrB+OADoHJl7hOvlrp1Kb3aZsvcrxoVBbz1lr7jClSXLilTHDdjK89PP/l/LJZd8eLA1KnUGnnMGLoYyCtgcPJkzvtmzvStlRdj/ho1irb2qd0Z5fRpyjKtWpV63M+cGTjtQUNDKfPozBngpZfo/dRmy/vxkZFU0JnnBGP53/8o0KvGYpiPOFBgFp98YswIaUhI9uJJehgwwLO95VFRQIUK6o+HKePQISAujlp8ZRSq1IrTSenY99+v3XMGkshIYMUKyuC480664Fm4kAo0Me09+ij1Nc/vxBKgrxf0GIcDGDaMsguY8ooVA959l04mx47NGTBISsqZUQBQ9t3QodoU4WIsq9atgdtvV+/4165R55UaNWj7WkoK3ffcc0C5cnT+bLRFNrXYbNTV6cwZ+p3kFlAUAqhXD7j7bn3GyPL2+ON0TWOzGaYTFAcKzKJLF7rQNRqXS/+ChmXLUvX7gnA2gTm43ZRC17Ah8O+/6mcR5Ie3H6irXj1g8WL6PXfpovdoAleFCsDy5cC6dXRSf2vqamQkpam++KJn1bETE2llz2pu3KDMpp9/BhIS9B1LsWLAO+9Q9sBjj2VeEKSkUJA1N1Om+N7dgjGjSUoC3nyT5q+PPqIAf9bMqMREqtcxYQJQvjwV/wsUhQpRkcITJ4CRIzPbhgP0+SefGOZClGVRsiTw9de0iNK2rSE61nCgwCx69DBefQKAJma9AwUATYT57cuKjAS6d9duPMx3GzYAkyfT35aWWQRMP9wuyxji4jK3uTVtSsHpihWBGTOomO5zz9Eqdn4nL8HBtBry0EPajVttmzZRQLp4cSqIO3AgMH683qMisbEUWD11inqsh4fnXWQ4NpaCPVzYkJmZy0UtWcuXp2J8CQn518pKTKTXxKhRwKefajdOIyhWjObvw4eBQYNofr73XlqIYcZVrx4F7hcupG2wOgYMhDRBO7C4uDi5detWvYehv4YNgZ079R4FCQ2llYmyZSn61aqVvuO5fJlSzPLaj2a30+p0tWrajot5b+1aoGdPWr0zAAFsk1LG6T0ONfEcyzx27Rq1mM1tro2MpHoi339PJzdmJyVdhGcELrOKiAB27ABq1tRjZHm7epWCBXmdWCYn0wrsxYvajisPgTC/AjzHKkJKynwaO5b+fn3JNrTZ6AIszvJ/crm7cAGIieHaBGbicgGzZwPPPEPzt5fb0P2dY3kZx0wGDtR3f2FwMK0wlSxJe5+2baMUR72DBABFTfOb+ENDqcANMz61Cx4xxnxXtGjOOT8khC5M33kH2LjRGkECAPjhB2rpltuJWUoKpfwbTUxM/qtP4eHUdtEAKa2MeWz3bqB5c6BfP+DYMd+3JDqdVKvDBIukqihZkoMEZhMcDDz8MGWNjR9PwS4N/w9VCxQIISYLIc4IIXak33pk+dpzQojDQogDQohuao3Bcnr10idFNzqa9js99BCwciVw7hztC/OkLoCWHn447zoO7drxfiyz4EBBgXh+ZboaOTJzro2MpLoG+/YBjzxinXnW6aTCUnnVKXG7aZvGunXajksJ/fsDlSrpPQpD4znWYB56CNi6VZmaRcePGyc7lzFPRUVRnZlDh4D77tOs4KHaV53TpJSN0m/LAEAIUQfA/QDqArgDwIdCCG7u64maNWk1RwvR0fRH2LcvMH8+9T3/5BOgRQvjngjee2/ulW1tNq5PYCZhYYEb7fcOz69MH/fcQ0XDoqKA998H/viD9gtbycaNBdcFcjgoOGK2WipC0Ps51yooCM+xRiAlsGuXcsdLS+MMU2ZeZcsCc+ZQ7ZwWLVTPDtNj60FPAD9IKZOllMcAHAbQXIdxmNOgQQW3p/JVZCSlJXbtSvthrlwB5s6ltjZmqJRcqFDunQ2CgoDbbtN8OMxHHCjwB8+vTH2RkcD69cDBg9QK0ajBY3+cPetZAODkSdqiYDZt2gDt21NaK/MGz7FaO3xY2WzaOnWM2UWMMW80bEgB7blzqe6MSgEDtQMFY4UQO4UQs4UQGUvhZQFkLZN/Ov2+bIQQI4UQW4UQWy9duqTyME3k1VepIJ9SF+42GwUH4uKA6dOpsvVvvwF9+qgXkFDTiBGUDZGVEMbbJsHyFh7OgQLP+Dy/AjzHauqHH4DGjbO37jK7pk2pqKFVnT2bfyX1DImJwLhxnj3WaGbO5P3K+eM51gi2bFEuGBkWRue3jFmBENQV78gRKrxbuDAV2lWQX4ECIcRKIcTuXG49AXwEoCqARgDOAXjXm2NLKWdJKeOklHHFixf3Z5jWEhEBrFhBq+e+CgujIECNGtRa5uhRmohHjKBe2WZ21105T8ZbtbLmipdVhYWZL5VXBWrOrwDPsZqREnj+eSrGNXeu3qNhngoN9fwiOjERmDZN3fGooVo1KuymZ5FkHfEcaxLr11MLRCWEhfFWVGY9ISHA6NGU4TZ2LF3jKbSg7FegQErZRUpZL5fbIinlBSmlS0rpBvApMlOzzgDIupmxXPp9zFOlS1OwwJsV/+BgSkspXZpabOzYARw4AEyYAJQpo9pQNWezAXfckfnviAjgzjv1Gw/zHgcKAPD8ahm//QZcukQBzBdf5GwZs3j0UaoQ7gmHg4LuZswqmDLFHFsLVcBzrEko2SpZCKBRI+WOx5iRFCpEmQUHDlCbcQUyw9XsepA1J/FeALvTP18M4H4hRLgQojKA6gD+VmscekpxpaD7t93R/dvuSEhJ+O/zFFcBBZI8ERcHfPpp/n8EQlAafpEiwKhRVHDqzBk6oalRw/8xGNVDD2VuPwgJyb1uATMuDhQUiOdXE3n55czVsIsXgWXL9B0P80xEBBXy9eREKyQEqFvXnB1bYmMpgMWFDbPhOdZA+vfPuaXUVx076tM9jDEtlS9P719//un3odQMI/9PCNEIgARwHMAoAJBS7hFCzAWwF0AagDFSSpeK49BNzzk9sfbEWgBAuanl/gsQ9JzTE8sHL/f/CQYNAv75B/joo+wtnKKjAZeLokkjRtCFciAVLOraNfNC0+UC6tfXdzzMO2Fh9P/G8hPw86sp/PNP9mrdCQm0DYGznIzF7QZ+/RXo3Dl7Gn7TptS3evr0vNskArQvdOlS816AjBsHTJ2a/88YeHiONYrbb8+9o5W3oqKorRxjgaJpU78Podq7mpTyASllfSllAynlPVLKc1m+NkVKWVVKWVNKqcAVs7E505y4kXwDzjSn8gf/3/9oD35GUcI77gC++gq4ehX4/nugU6fAChIAdKF57730ebNmgffzmx0HCgrE86tJvPpqznT0I0doz61VJCbSvkgze/99avnYvDkV9M1q8mRanbHZKK2zcGG6RUfTKnxEBGWJlCihy9AVER4OvPee6m22somMpN+3QfEcayARERTE81dqKi0kMeYvlytgthEG5sY0jczrNw/lppbLFiAICw7D/H7zlXuSoCBg4UJg9WpKqfKnyKGVDB8OfPstFTc0odTUVJw+fRpJZtzzqoTlGp97ud2IOHwY5SZPRui1a9o+N7OmEydolfrWbTSJicCkScDatfqMSylSAvPm0V7+q1eB/fvNuaXt4EFg4kQ68du7lzLQfvuNulQAVNBw1Sq6RUfTrVChzI9Fi1ojbb9/f+D114E9e9R9nshIoFQp4IMPaKXYrFkYTFtDhgDr1gHx8b4fIzaWXuenT2e/yMv4PLf7PPncio+tWZMCooy4XMCsWZTKv20bcOwY8PjjwDvv6D0y1XGgQEV95/bNUY8gxZWCPnP7KLP1IEN0NG0zYJnatwduuw3o1k3vkfjk9OnTiI6ORqVKlSACsWODw6FptFYCuBITg9OTJ6PyE09o9rzMwt56K+/MmC1bgH//pT7IZrR3L/Dgg3RRmZhI9XD69gW2bzdXBldaGrVKS07O/Pfly0DbtsAXXwD9+tH9ZcvShYqVCQF88gldvKuxBcFup9u77wKDB3OAgHmnRw8gxc/6Xteu0QUwkNkJS0rPumIJkXlO4s05ma/nb74+n6eczry3c5QsSS19b7tN+ec1q9Wrgaeeyj43LlzIgQKmDFuIDWHBYcoUMWSeCQ4G1qzRexQ+S0pKCtwgAZD9TVKLpwMQGxKCS9WqafaczMJu3ABmz877RCw5mQrILV6s7bj8deMG1ViYPZt+hqwrVEeO0Op87dr6jtEbb7xB474168PhoEDIjh20yh4oF7Vt2lCQ/fffldv+FRFBxR5feAF44gnFe3yzABEVBXzzDV3Abt9OWQE2G712ExM9O4ZThe2/ZpHRFt3tpvmtcGGgYkWgTh3KoqpendqlVqlCv2uW3W+/5dxGeOoUZbgoVWjToDhQoKJFAxah5xxa6Z/Xbx76zu373/2MFSRggwQ6EUDgXBAwdUmZ/8q6200XY4cP08mZWTz1FNXAyS0AEhxMK3Zm8e+/wJtv5n3x4HDQvv0dO2iLRWoqbT/o3VudFT6jmDkTaNDA/4uqkBDatjFyJHX+KFpUmfGxwNW3L90AClTu20ev47//BjZvpu1PUtLfncNBGUKBJDycAnEuF71+Y2KAypWpI0vdupnBgMqVFWmbF1CWLMkZULbZ6G9PifoZBsaBAhWFBYdl22Kg6HYDxqwsKIhbJDLzKlIEmDMHuP9+WoXILTsmLY1WtGfP1nx4PhszBvjuu9wDBW43te01g+RkuuAv6GLY4aDMtMaNadXy0iX6/7RyoKBaNdpm8eWXmVsyvCEEXaz07EnFlsuXV3yIjCE8HGjUiG5Dh9J9UlKmwY4dtG3IioECm42yA9LS6PVZrBhlAdStC9SrR6/fatWASpXM2a7ViG7eBI4ezXm/w0E1CyweKODlM8bMoFQpOgFT6laqlEdPe/r0afTs2RPVq1dH1apV8cQTTyAlJQVffvklxo4d6/Hwp0+fDoeP+17/2LYNd40f79P3Mqabe+6hi8xeveikNusKjt1Oq14tW+o2PJ80akTp41mL9xUqRD/Lo4+a58T0+eeBc+cKfhxAgYGjR4GzZ4EyZQIj62jKFMoI8JbdTlsX/v6bAmUcJGBaEoL+5u6+G+jSRe/R+M5up60Bdju9DsuWpdfVmDG0J37uXGDnTgp0njsHbNhAhfYef5xqOdSoYZ652Az+/DP3LVNpabQlweI4o4AxM7hwQfPjSSnRu3dvjB49GosWLYLL5cLIkSMxadIk1K1b16unmz59OgYPHgy7p9XBrbxixwJHixbAggW0Ev3pp8Bnn9Fqz3330QmdGS+kXnmF2gFevkzteO+8k4pexcToPTLPbN4MfPSRd6n1Gfv1L16kDJDhw9UZm1HExlINjVdf9aywYWQkUKEC/V47dFB/fIwV5KGHqLOMP10S1BQZSUGAlBS64CxTht4b6tenOi8ZmQFly5qrQKwV7dmTd3bVjh2UTWfhADIHChhjuVq9ejUiIiLw4IMPAgCCg4Mxbdo0VK5cGa+99hpOnTqF2267DWfOnMHgwYPx8ssvIzExEf369cPp06fhcrnw4osv4sKFCzh79iw6duyIYsWKYc2aNRg9ejS2bNkCp9OJPn364JVXXgEAbNmyBU888QQSr1xBeEgIVn34YbYxJTqdeOztt7H7yBGkpqVh8siR6MknpszoihenVeznn9d7JP4LC6N9wWb122++pdQDFFx47DHgn3+A6dOtfQI/bhwwdWr+gYLISMoomT6d9o5zgJcZxR136Lv1QAh6fQQHZxZ+LVuWVvvr1wdq1coMBpQuza8dIxszhgpo/vJL7vPhvn209cOiOFDAGMvVnj170LRp02z3FSpUCBUqVEBaWhr+/vtv7N69G3a7Hc2aNcOdd96JEydOoEyZMli6dCkA4MaNGyhcuDCmTp2KNWvWoFixYgCAKVOmICYmBi6XC507d8bOnTtRq1Yt9O/fHz/++COa2Wy4efkybOHh2Z5/yuzZ6BQXh9kvvYTr8fFoPmwYujRvjkguzMMY80SlSpTSm5Dg2/c7HJRV8O+/dOJo1V7j4eFUzHHEiJxV5W022m7y2mvA6NH0OWNGEhEBdO9OGV1qCQqiYEBQEAURg4MpS6xGDSoIWrNmZjCgeHEOBphVZCR12/jiC2Ds2MxgQWQkZYKULavv+FTGgQLGmE+6du2K2NhYAEDv3r2xfv169OjRAxMmTMCzzz6Lu+66C+3atcv1e+fOnYtZs2YhLS0N586dw969eyGEQOnSpdGsWTNgzx4UyqVFz29//YXF69bhnW+/BQAkJSfj5PnzqF25sno/KGPMOipX9j8TwOEA/vqLVgZXraJq4lbUvz+1h9yzh/4dFka/u/HjgYkTLd8WjJnc8OHUXcaf7QfBwRRYFIKCAeHhtM2mZk0KBtSokRkMMMv2K+abBx+k7YT/+x8VLG7WjIpmWjxQas5AgZT0gk1MzPvmdNIe0BIl9B4tY6ZUp04dzJ8/P9t9N2/exMmTJxESEpKjfaMQAjVq1MD27duxbNkyvPDCC+jcuTNeeumlbI87duwY3nnnHWzZsgVFixbFsGHDkJTRn1ZKSuO6tV8tMr4s8dNbb6FmpUqK/ZyMsQBSuTLtC/ZXSgpVWG/ShFYtu3b1/5hGIwTwySeZheEGDKBOHR4Ww2VMV127ZtYXyU9ICAUDMq4tIiOBihVpe0CDBpltBatWtW4GEfNMnTrUESaAmCNQsGsXXfAnJdFen5QUemGHhFC0Lygos5CElHRLTQUaNgQ2beJ0H8Z80LlzZ0ycOBFff/01hgwZApfLhQkTJmDYsGGw2+34/fffcfXqVdhsNvz888+YPXs2zp49i5iYGAwePBhFihTBZ599BgCIjo5GfHw8ihUrhps3byIyMhKFCxfGhQsXsHz5ctx2222oWbMmzp07hy1bt6JZ7dqIT0zMsfWgW8uWmDl3LmY+/TSEEPjnwAE0rllTj18PY8yMSpdWJlAA0LlGQgK1Apwyhfb1W+18o00b4JtvKHuC51pmJmFh1H3mhx/o84gIes06HHTBX6kSFQ6sXz97MCAyUu+RM2YY5ggUpKRQ1eis0tIKLlSyezdV4X30UfXGxpgWSpZUtvNByZIFPkQIgYULF+LRRx/Fa6+9BrfbjR49euCNN97AnDlz0Lx5c9x33304ffo0Bg8ejLi4OKxYsQJPP/00goKCEBoaio8++ggAMHLkSNxxxx0oU6YM1qxZg8aNG6NWrVooX7482rRpAwAICwvDj999h8dGjYIzORm28HCs/OCDbGN68aGHMG7qVDQYMAButxuVy5bFkmnTlPu9MMasLTiYeo8rOZ86ncALL1CRw88+s15rsj599B4BY76ZPJm2yNSsmRkMqFw5e7taxliehJRS7zEUKE4IudXXb7bbgb17KY2IMZPYt28fateurfcwtOd2U3VZney7fBm1u3fPdp8Atkkp43Qakibi4uLk1q0+z7KMmUvz5sCWLcof12aj1NTly6l4GSuQEMLy8yvAcyxjTB/+zrHWbfyYITmZ9tWZICDCWECTkoJ6jDGmpogIdY7rdAI7dwL16tFHxhhjxuF08vWgl6wfKHC56A171iy9R8IYy4/TqdzeYcYYy0udOv53PshLaipw8SLQqhVw8qQ6z8EC2z//AIMH59ySyxjL2/z5QKFC1KWgaFHahtK6NdC3L/DUU8C0acD331Mnm9276fXldus9at2Zo0aBvxITgQkTqKdqhQrKHvuLL4Dz52nPd8atRAn6eEshNsZYPq5d40gvY0x9HTvSCaE/bdMKEhTEFdKZstLSgFdfBd55hwJSbjf9HTPG8rdyJTBkSGZtu+vX6XbkSOZjwsIyW8C63bRwlZoKREVR68ty5ag1YqtWevwEugmMQAFAHROGDQNWr1bumMePU6HE1FRKZQxJ/3WmptLzhYVRr81ixajS8vjxFKxgjGV39SoVF+NAAWNMbQ0a0ElgdLQ6wQKbDXj2WQ4UMOXs20dFJY8fp+w7AFi0CNiwgTpTMMZyt2UL0KtX5usmLykpuWe13rxJt+PHgc6dgUmTgOeey+y2Z3Hm+CmLFaML7qgo3/9jXC5g/Xr6z1bKxx9T1MnloqyFGzfo5nDQ/UlJlG2wezfw++9Av370h8YYI2lpwOHD9LrgFC9mFqmpnvXnZsZUuzZw4gRlBI4aRS3RQkMpLVWJ9obh4dQqMRC53dTSmudzZbjdtIrZtCkFCxyOzK85HMADD9B8xBjLad8+oEsXukZTgtMJvPEG0KEDbTELAOYIFFSsCFy5AqxYQSv4xYpRn9MQLxMi7HblKqqnpQGffOLdnmqHg/otF9TWkbFAcOMGBdFu3OCTSmYe169T6mHdunqPhPmjZEngvvso4H/4MJ30zZlDmX9162YGDrw9z7DZgAULaGEjEM2fDzRqRDcdO9hYwtGj1KHjlVfyLsJ24QLtrWZMa0eOUKC1bVugXTugfXu6gL7tNtre1bkz8PzzVCdOj2zRkydpXEouEAN0LffXX0CtWsCaNcoe24DMESgAKJOgdWtg5kx6Q1+7liL2pUtTACA0tOBjSKncH8ySJd6vKLnddELy4ovKjIEFjNLlKkAIoditdLn8a3WMHz8e06dP/+/f3bp1w4gRI/7794QJEzB16lQsXrwYb775plc/y7ChQzH/gw/oTSYtLdsbyLh338W69JPLh157DQ0HDkSDAQPQ59lnkZC+kjJ51iyU7dEDjQYORK0+fTD6zTfhTg807D9+HI0GDkTjQYNw5PRpfP/rr/8de9fhwxg2ebJXY2Ush5UraZXi5Eng4EG9R8OUUqQI0KMH8O67FMC8fh34+WdKMY2Lo62EhQrRx7zY7bSHvGNHjQZtMG438MwzmVkFbdsCQ4fSQg/znJTAhx8C9etT4cKsWQS3cjgokHD6tHbjYwwAJk6kQvEbNlDG9p9/AuvW0fXZH3/QVu933qHAeqVK9LeslUuXaEvOtWvqHD81lY59553A+++r8xwGYc4aBUJQGlbTppSStXs38OOPwLffUhDB7aa2iLdyu5Xbj/juu74dy+EA3nuPTkjatVNmLMzyzp85hYrPLlHseCfeuivfr7dp0wZz587FuHHj4Ha7cfnyZdzMEmTbuHEjpk2bhpYtW+Kee+7x/Inj42lyTUjIkUVw5fp1bN69G9MnTAAATBs/HoXSV+WenDYN78+di4nDhgEAxg8YgKceeAButxvtR47E2u3b0TEuDj//8Qf6dO6MFx56CH9s24bvV6zAwDvuAADUr1YNpy9exMnz51GhVCnPx8xYVmXLUrGj5GRg7lzghRf0HhFTg91OF/wdO9LFf0oKrZD/8QewfDntew0OpmBnUhJlEsyYATz0kN4j18/8+dmDAk4n8MMPwMKFlK47erR63Sas4swZ4P77Cw4QZJWSAowcCSxbpu7YGMtq3bqCH5OaSreTJylw+M03QO/e6o7r5k3KbrhwQf1sVacTeP11YOxYdZ9HR+bJKMiLEBR1ff112ue8YweduFWvTgUGs/ZLdrnoAsVfJ04AW7f6/v1OJ71Q1Ip0Mean1q1bY9OmTQCAPXv2oF69eoiOjsa1a9eQnJyMffv2oUmTJvjyyy8xNn2CHDZsGB5//HG0bt0aVapUwfz58wEAUkqMHTMGNatWRZcuXXAxj9Wln1avxh1ZqslmBAmklHAmJ0Pksnc4JTUVSSkpKBodjWUbNmD6nDn46Kef0PGRRzDx/ffx5z//oNHAgZiWXhn67nbt8MNvvyn3i2KBp2FD2tPudmu7QuIJKYE9e7goqBrCwoCWLWkVbe1aCnquXw+89RZw771UWC6QgwQZ2QS3nmOlpNDvauJEqg2xYYM+4zM6KekiqlYtYPNm7/ZUp6XR32SWDDrGVHX2LG0b9YbDQW09X31VvfeopCSga1fg2DHtaneULq3N8+jE/IGCW9WoQYGCgweBvXvpD7JuXSoulJqqTKAgo4ihP27eBAYN4hM6ZkhlypRBSEgITp48iY0bN6JVq1Zo0aIFNm3ahK1bt6J+/foIyyUF99y5c1i/fj2WLFmCiRMnAgAWzpmDA9u3Y+8PP+DryZOxcefOXJ9zw86daFqrVrb7HnzlFZS64w7sP34cj/Xv/9/90+bMQaOBA1G6e3fUqFABjWrWRI82bfDIffdh/IABWPPxx3hz7Fi0a9wYO77/HuMHDgQAxNWpgz+NdnHHzMVuB7ZtAw4cAL77Tu/RZNq7l7LsGjYERozgYotqCw6m3/Xjj1NNgq5d9R6Rvm7NJrhVYiJw6BD9nvr0Ac6d025sRnfpEmWZPvIInaP6UsfK4QAefLDgyu6MKWHDhvy3YeXF6aTgat++dFGvpLQ0qgO3c2fuWeVqqV5du+fSgfUCBVlVrgw8/TRtTThyhFL+Bwzw75hpaRQo8KaIYW5SUihtZ9Ys/47DmEpat26NjRs3/hcoaNWq1X//bpNHO6ZevXohKCgIderUwYULF4AzZ7BuyRIM6NoVwUKgTPHi6BQXl+v3nrt8GcWLFs123xcvv4yzy5ahdqVK+DFLJsD4AQOw4/vvcfG335DodHqcJVCiaFGcvXzZw98AY3kICgKqVMmesaYXp5Pe5+LiKKPO5aJ077vuUv5EjLHc5JVNkBunE1i8GKhWjS4YAt3ChXShsWqV51sN8nLzJvDaa8qMi7H8rFrl+1ZuhwNYuhRo0YK2ByhBSmDIEMry0vJ9TwjKlLIwawcKsipbljomlCnj33GWLlVupSYxEXjySWD/fmWOx5iC2rRpg40bN2LXrl2oV68eWrZsiU2bNmHjxo1o3bp1rt8THh5OnzidkC4XvQl4mDVjCw9HUi4BuODgYNx/++34KZfqsqEhIbijVav/CiAWJCklBbaMMTJmBY0bAx98kL0qusNBe+m7dNF1aCxAFJRNcKvUVPobffVV9cZkdNevU2bF4MGUwq1EmrTDAUyfTpkbjKlp1Sr/vj8pibLg6tenwqf+GjeOtn/5G2zzVmQkbUW0sMAJFCjF1yKGeXE6gXvu0TZNhjEPtG7dGkuWLEFMTAyCg4MRExOD69evY9OmTXkGCiAlcP48VYUHALcb7Rs3xo+//w6Xy4Vzly9jzbZtuX5r7UqVcPjUqfTDyGyfL163DrUqVszl6SQ2/PsvqpYrl+Nr0XY74m/Z53nw5EnUs/ikzgKIw0GddHJLN05KohZOjKnJm2yCW2l9Um8UK1ZQRsWSJcr/DpKTgeHDeVsrU098PNVq81daGm27ad2aAme+mjIF+OwzfeaT4GDq6GBh5ux6oJeTJ6nSsZKkpLY248YBH32U92NyKeTGAkepsuUL7FTg7fEKUr9+fVy+fBkD0/f3Z9yXkJCAYsWK5f5NiYlUtTnLScq9HTti9datqNOvHyqUKoVW9evn+q13tm2LTxYswIhevSClxNDJk3EzMRFSSjSsXh0fpdc8AKhGwbfLlyM1LQ0NqlfHo3365Dheg+rVERwcjIYDB2LYXXdh/MCBWLN1K+7MY9sEY6YjJbUGzivLTUp+/2DqmjeP2x96KiEBeOwx6pai1kVNRpHVefOAfv3UeQ4W2DZvpi4vShYL/PlnIL2rlVc++YQ6qugVdExNtXygQEgVoo5CiB8B1Ez/ZxEA16WUjYQQlQDsA3Ag/WubpZSPFHS8uLg4udWfLgNKee45YOpU/+sT5MZup4m9R4/s92/eDHTvDpQvT0Uae/cGQji+Y3X79u1DbTPue0pNpUIyPs4rbUeMwJJp01AkOlrhgQHJKSnoMGoU1n/6KULyeA3tu3wZtbt3z3afALZJKXMvrKATy86xzHuDBlFNglsL7NpsVANn8GB9xsWsz+2mWlAnT/p8CCPOr4AKc2ytWnLrjRu0cqrFHuqiRWnVV4X3UhbgJk2i+iJKFsxt186zdotZzZsHDB2qbwHPjFbJBm77KoTwa45V5YpTSvlfeXIhxLsAsvbQOCKlbKTG86pKqSKGeXE4gIEDqZJ2yZJ0348/ZlaxvX6dWi+NGQNMmEDVcYsUUWcsjPkqNBSIivJ5e86748bh5PnzqgQKTp4/jzfHjs0zSGAmlpxjmW8mTqTVmKwrKjYbrbRwkICpad484OpVvUehCsXn2IMHtd0O4HTS4tb772v3nCww/Pqr8l11/vqLWsbfUtA6TytX6h8kAIDYWEMHCZSgao0CQY3P+wGYo+bzaGLZMvXbTSUmUlqalFTk59ZWNwkJwOXL9LXSpakFFhetYUZTogRVhfdBi3r10EClVjPVK1TAbU2bqnJsvVhqjmW+qV8f+PNPoFMnel8IC6NtbA88oPfImJX5U5vARBSbY7WuGZCUBMyeTRl+jCklNZU6ySktNJQC3p64cgXo1Uv/IAEA5FIfy2rULmbYDsAFKWXWq9nKQoh/hBBrhRDt8vpGIcRIIcRWIcTWS5cuqTxMDyhdxDA3YWFAo0aUSvrWW3m/CJxOehP46it6fB7F4RjTReHCeo8gkFhnjmW+a9KEqlCfPUvvDUOH6j0iZnUWzia4hTJzbHAwbTHVUlISBQxv3ZZkFlyQ0Xj++UedtsCJicAXX3j22MuXfV6MUpxKC1tG4vNvWgixUgixO5dbzywPG4DsUdhzACpIKRsDeBLA90KIQrkdX0o5S0oZJ6WMK168uK/DVMbJk8Dff6v/PGlp9OZ7axppfo93OIDbb6cTRBY4MmoBXLyo90hyCgqidCzml4CaY5lyuHAhU5tFsgk0nWMbNqQ6U3Y7rZ5qQUrgyBHKLDCbhQvpXOLcOb1HwrL680/1urRlbD8oiFECSEFBQN26eo9CdT5v1pVS5tugWQgRAqA3gP9yfaWUyQCS0z/fJoQ4AqAGAGNX0fr4Y/UjsnY7XfTv3et9HYSbN6lf9tat2kesmfbcbtrvmJICXLjw/+zdd3iT1RcH8O9NZ9KWPWRv2bIFQdmyRBHZQ8SFiuDe4AYX+gPFCYqgIogoMgQRkCl7T9l777ZJ2qTJ/f1xGrrSNmneleR8nicPbVKS2zS5ed9zzz2HUv2NpmRJSg8L1pUMAwirOZYxFjx++y0ksgk0nWOFoJoBQ4cCTz0F/PmnNqnTVivw3HNAz57BEcC/dg24+25gzRr6/qabdB0Oy2bRIvUCBVFRFCB66KG8f84ox5UWCxVzDXFq5m50BPCflPKU5wohREkhRET611UB1ABwRMUxBE7tIoYeKSkUnSrI46SlAUePAv37GyfSxtThWSHwVE12Oo3Zi1rLVZPwZfw5NikJGDcO+PFHYN066pnMcxRjwc1iUb9mkzEoP8eWKUOZo8uWATVrAnFxSo85p9RU4Omn1X+cQJ0/T8Xs1qyhDl9Hj3KGlJFIqW52td1OgQhfxmGE10VERMi3RgTUDRT0R87iL60B7BRCbAcwG8DjUkpjh6UXLaITcbW53YFFyVJS6IPn9deVGxMznlOn6OQr88mWSq2WIiIi0LBhQ9StWxcNGjTAJ598Arc/r9FMRQ3fy7b3rGV+EeM8TJ0/H2cy7al/ZMwY7D1i7HijSow9xyYnA23aULrt8OEZbV4tFtrXd9ddwKef0muaMRY87rqLOi+FfgajenPsbbdRBun48VTXJyYm4MHmyuEAfv+dgrVGVro08MUXdML4229hcRIWVA4eVGc1PyqK6h4MHAh8/HH+P2+UjAKHIyxeo0IGweqOrj2+27Txv7ennsxm2o/Wv7/eI2EB2LdvH2rXrp31yosXgZMns06SJhNQq5YqB2zx8fFITt+DeuHCBQwcOBCtWrXC22+/7dsdeOooSIn41q2RrND7qO1jj+Hjp59G0zp1FLm/zPZduoTaXbtmuc6ofb6VlOcca7fTay8hgS6+tJe0Wmnu3L077zRFs5lez3ffTatsjLHg4HIB7drRvuIAMi7DYX4F8pljr10DXnsNmDqVAv9qHZdXqwb8959vczhj2U2ZQttmrFZl7i8mhjIDhgyhBYUKFXz7fzt3AnfcQduu9RQZScc3RimsmAshREBzrLF/O71pVcRQSXY78PDDwKZNeo+EKSkxMWeQAACkhCPKhK4/dUXXn7oi2ZF842uHS7ntMqVKlcKkSZPw+eefQ0oJl8uFF198Ec2aNcMtt9yCb775BgBw9uxZtG7dGg0bNkS9Ro2wev9+vDJxIuypqWg4cCAGjR4NAIhv3RoAsGLLFrR97DH0fvll1OrdG4NGj4YnePnO5MloNmQI6vXrh2Fjx0JKidnLlmHzvn0Y9PrraDhwIOwpKWj72GPYvHcvAGDG4sWo378/6vXrh5cnTrwx/vjWrTHqyy/RYOBAtHjwQZy/fFmx5yaknTlD6bG1a9Ne0ehouhQqBPTp4z0IYLPRCcSePfnvZbTb6Wc4q4Cx4BIRAcydGxz73o2uSBHgyy+pzlTz5uptRzh7lrK4GCuIxYuVCRLExtLi1vDhwLFjwDff+B4kAIyzfbF4ccMHCZQQ+r9hIL75xjgpLv6w2YDOnYHTp/UeCVOC3Q4cOpQzk0AIoGhR9PilJ1YeX4mVx1ei/P/K3/i6x4weud9nAVStWhUulwsXLlzAd999h8KFC2PTpk3YtGkTJk+ejKNHj+Lnn39G586dsX37duzYsQMN77gDHzz9NMwxMdj+88+YPmZMjvvdtn8/Jjz3HPbOmoUjZ87g3x07AAAj+vbFph9+wO5ffoE9NRULVq9G7w4d0LR2bUx/911s//lnmDO16Tlz8SJenjgR/3z1FbZPn45Ne/fijxUrAABWux0t6tXDjp9/RutGjTDZ13694ezUKaBZMwoW2Gy0aiglZYokJVExrnbtsraNtduBDh2AXbt83xITFUWpzIyx4FK0KPD33+GwBUEbdeoAa9dSTZdSpZR/Xm024I03KEOMMX8FmhVqNlMQ7PnnaeHrf/+j7Sb+Msp5mT/BjSDGgYLcaFXEUC2JiXTAbsRCd8x3Tid1OHC7M4IDCQlApUpAgwZA1ao3ftSeZsf11Ouwp6lfSfnvv//GDz/8gIYNG6J58+a4fPkyDh48iGbNmuH777/HW2+9hV27diGhXLl8i87cWrcuypcuDZPJhIY334xj6a0+l2/ZguZDh6J+//74Z/Nm7MmnDsGmvXvRtkkTlCxaFJGRkRjUpQtWbdsGAIiOikL3O6jddZNatXCMWy7l7fhxChKcP5970TK7Hdi6FWjRgg487XbqvrJ9u391M8xmCjgwxoJPvXrAtGn0PmaBE4I6FBw7BrzwAj2vvFWA6e3cOd9aF3oTF0dZiKNHU1bLmDFAsWIFH4tRMgpuvlnvEWiCAwW5UbMFiBZcLjrY79PHONE35r/TpylYkDk4ULMmpTylHzz82vdXREdEZ/lv0RHRmN13tqJDOXLkCCIiIlCqVClIKTFx4kRs374d27dvx9GjR9GpUye0bt0aq1atQrly5TB06FD88NNP1CoxDzHRGWOPMJmQ5nIhJTUVwz/8ELM/+AC7Zs7Eo/fei5QAgnZRkZEQ6QGLiIgIpGlRoDRYHT0K3HorcOFC/pXNU1OpwNEttwCtW1PgwN/imikpQNOQ36LMWOjq3Rt48knOLFCS2Qy8/Tawfz8VglXiubVYgFGj8v1MZiyHf/+lbYf+iIujgMCYMRQgeO01OpYNVOHCdOwRERH4fRVURARlAIUBDhTkxtPeLS5O3Wq0akpJAVasoA8GFpzKlQMaNswRHMisz6w+OeoROFwO9J7VW7FhXLx4EY8//jhGjBgBIQQ6d+6Mr776Ck6nEwBw4MABWK1WHD9+HKVLl8ajjz6KRx55BFu3bgXKlUNUdDScERE+7+fyBAVKFCmCZJsNs5ctu3FbgsWCJC+ZMrfWrYuVW7fi0rVrcLlcmLF4Mdo0bqzAbx9Gzp2jIMGlS74HGJ1O4Pp1KjBUkA4c9eoF7xzLGCMffEBZSP6eTLC8VagAzJsHLFxIGYSB1C8oUoTSvhnz17JlWbcZ5iU+nrYU/O9/FCB45hllg4jVqgFbtgCDB1O9Az2ymcxmoEoV7R9XB5zPlJsOHYArV6hq98KFwOzZdCAcG5uzPZ2R2WxUvKZePWDQIL1Hw/wVFeXzj5ojzYiOiFasiKHdbkfDhg3hdDoRGRmJ+++/H8899xwA4JFHHsGxY8fQuHFjSClRsmRJ/PHHH1ixYgXGjRuHqKgoxMfH44cffgCEwLDHHsMtffuicfXqmP7uu/k+dpGEBDx6772o178/bipeHM0yRW6H3n03Hn//fZhjYrBuypQb15cpUQIfjBiBdo8/Dikl7rr9dvRo00aR5yJsbNhAkXp/s5DsBdzuEhnJ9QkYCwUREcAff9CxBtdHUl6bNpRd8NVXtDLrdPqX9RoXB0yezEFZVjBLl+b/M/HxVLfkvfeo85qaW2bq1qUuIRMmAN9+C3zyCbVkTu/UpTqTKSxaIwLcHtE/ycm0Qj93LrBgAa2iAQU/SNaS2QwsX04VdZnheW2PmAuHy3GjcOGvfX9Fn1l9AABzB8zNsSVBV3v3Gr5mRti3R5w+nfqja/VhW6gQnVxwjQLGQsO+fZSVZDJRhfTs25dMJjqhSE0FmjeHWLUq5OdXQOHj2MuXgRdfBGbO9O3402SidnLpxX0Z80tyMm0hSM8gzSE+HihTBnj/faqvoUcnALcb+OsvClJs3UpjVXOLqdlMRcbLllXvMRTC7RG1FB8PdO9OUdmzZ6my97hxFOmNjaW9N0ZtlWG30z63kyf1Hom+9u2jN/bDD1MNhxAQHRGNRYMXYdHgRYiPjr/xtaGCBGlpwRFQC3fJyfnXJVCS3U7FEFl4SE6mlanXXwdatQLWrNF7RExptWtTIb6ffqK/c4cOtCdeCKqzM3IkMGcOLbSsXKn3aINT8eLU037dOqBx4/y3I8TEAJMmaTM2Fno2bPCe3h8XB9SvD/zyC2W79Oql3zmQyQR060afKdu3Aw89RGNWq26K00kto8OAQc9qg0S1alTAZ8UK+tCbO5eiaUbl6YSgRB/UYJScDHTpQvuwf/wRqFWL0qMOHNB7ZKHv+vV8ux8wA0hOVjcKn13NmlwtPZRduAD8/jswYgRViC5WjA4m33+f2sBxT/fQVLw4cPfdwJtvUmDowgWqX3LsGKUKt2/PKfBKaNAA2LyZUq+LFfM+l5rNwLBhYVOhnalgxYqs5w0WC2UnL1gA7NhBJ+hGOr67+WZqb3/+PNVOKV+eFnqVVLKkcReGFRYev6UWoqPpsmSJsd4wmblcwIkTdKBm1E4IK1ZQEZQpU5StAyElFT65cCGjF3xKCtWeaNCADmp27lTu8VhWV64Y9zXHMsTF0b5CLaoJm0yU5cRCg5TA4cO0b3TgQMrcqlABePBB4MsvqTuG00kBa0/WytKlwVPvhwWGixyqQwha8DhxgrI1zOas83dMDOBDXSDGcvXXXzRnm81A27ZU2HD9evraqOc7AGV5jxxJ7405cyhAGRvrV+2vXFWsGPh9BAkOFChl+nTgzjvpIMjIBz6pqcDq1cDLL+s9kpxcLuCRR+hkfuRIWv2/cEGZ+/70UwriZK/K7nLRdQsXUgp0+/bAnj3KPCYjbje9L5jxPfYY1TJ54glaFYyPVy9oEB8PdOyozn0zZaWkAJ060Z5oD5cL2LYN+OwzCvgULUppqCNHAjNm0PY8hyPvz0SnE/jvP21+B8ZCWVwc8OGHVIC7fXta9TWbgfHjlWlJx8Jbt26UBbZ8efBtFxSCjjWWLaNaWY8/Tu+XQDqI1Kyp3PgMjgMFgZKS0usefTR49mDbbMAXX1D6vZF89x1w6hR9bbPRiX316pTaFIj166lKcF6F9Nxu+vstX04Hukw5SUlhk6IV9ISglMKJE4GLF+mD9ckngRIllN/rZ7cDt92m7H0ydXz0EbBqFe37fOQR+rvFx1N9npdfphWn69fpb+pPIUyXi+Z5xpgyqlYF/v6bVlBHjgSGDNF7RCzYbdwI/PknteoOdlWqUHD7wgVq31iliv8Bg4gI2rocJrg9YiAcDuD++2mfTrAECTzsdoqqVa9unIP1kydp20GhQrTfrlgxoFQpWqkqqIsXaVuBP3+fgvSCZ7m7elXbAnlMGUJQ9fKmTWmv3/z5yt5/1aq80mVkV64A//5LwdOvvspoxZZ5W1igc2VKCtUweOqpwO6HMZZVp050YSxQRt5eUFAWC9XuePRRyrJ+/336rJOSzu3y+79VqmgzTgPgQEFBXblCqfG7dwdfkMDDZqN0ou3bqRqx3t59V9m9dC4XcO+9GW0sfaVlMTeDGzt2LH7++WdERETAZDLhm2++wbp16zBs2DBYfFlhlhK4dg0AMHX+fHRq0QJlS5ZUd9DeCGHsLUFG5XZTMHT+fGVbWwoBdO6s3P2xwJ04QQdMS5YA//xDwaHYWMoQyFxfROn30YYNtAVBiX2jjDHGmK+EAFq3psvJk5Rt8M039JmXW+F3IYDKlTUdpp44H7ggDh+mAng7dgRvkMDD0wlBq77pWho9moIgufV+zQ2vfgMA1q1bhwULFmDr1q3YuXMnli5digoVKmDChAmw+XrSaLMBbjdcLhemLliAMxcvqjvo3EgZmlFxNbndVIjujz+UDRIAlElw553K3ifzndtNQe4vvwR69KB6FDVrUpbZtGl0wOSpL6B2EdKoKEptZYwxxvRSoQK1vL9wgbZn16xJ2xKyHzs6HGGVUcCBAn/9+y/1rT19Ov/0lGDgdlNdgJ49Q68q/fTpBVv9CsJAwfRd01F5QmWY3jah8oTKmL5resD3efbsWZQoUQIx6W2sSpQogdmzZ+PMmTNo164d2rVrBwB44okn0LRpU9StWxdvvvnmjf9fuXJlvPzii2g8cCBmLF6Mzfv2YdDrr6PhwIGwa729w2QqWLBArR68Ricl7UWfPVv5IAFAAdbbb1f+flnujh+n9Mo2bShQc9ttwAsvAPPmUYZcSoo+AeO0NNpyxhhjjOktNhZ44AFg3z7qzHPPPdQ9xNPS1eWibdFhggMF/giWzgb+Sk2laqYvvKD3SJS1Zw8V4SpXzr8eqkG29WD6rukYNn8Yjl8/DgmJ49ePY9j8YQEHCzp16oSTJ0/i5ptvxvDhw7Fy5Uo89dRTKFu2LJYvX47ly5cDoO0Jmzdvxs6dO7Fy5UrszNRmsnhMDLb+9BMGd+uGprVrY/q772L7zz/DHBsb0Nj85nZT27+YGN+CBXFxQLNmVMwv3EhJe/d++UWdIAFAkfsiRdS5b+bdrFlU1HXVKvq7JifrnxFnsVCf6+rV9R0HY4wxlpkQ1OHhjz+AY8foHKlwYdp2EEYZqhwo8IWUwBtvBFdnA19FRVHxwLS00Gthl5AAjBhBe29/+432IMXG0gljXoIso2DUslGwObOe0NmcNoxaNiqg+42Pj8eWLVswadIklCxZEv369cPUqVNz/NysWbPQuHFjNGrUCHv27MHevXtv3NavQ4eAxqAotxsoUybvYIEQVM12zhzaOx1sbYACJSUwfDjw88/qBQkALrKlh+efp0CB2az3SEhUFBXL5C4zjDHGjOymm4AxY2hbwtateo9GU1zMMD8OBzB4MLUGCYUgQVQUnSw7HNTqpHt36rnbtCkQHa336NRhMmVUAD54EPjkk4zWkN5OhoKsqNaJ6yf8ut4fERERaNu2Ldq2bYv69etj2rRpWW4/evQoPv74Y2zatAlFixbF0KFDkeLZVuB2I84oJyUABQrOn6dAwL599B7wZAaZTBRAKlGC+uyGUbT4Bimp+vwPP6gbJEhI4ECBHkwmYOxYqq/z4IPq/o19YbFQ1ko4vtcYYywcOBx0TB0q83x0dOieK+WCMwrycuUK0KoVtT/U+6CqoKKj6cA8Job2pL71FvXYTUoC1q+ngn8tW4bPC79GDeDrr4Fz52i/bpkyWbclmM3Axx/rN74CqFi4ol/X+2r//v04ePDgje+3b9+OSpUqISEhAUlJSQCAxMRExMXFoXDhwjh//jwWLVqUcQcuV5YtOgkWC5L0fh+lpNBWm1q16MPLEyCoUAGoX59OXkLlA81fzz5Lre/U/hulpgJ33KHuY7Dc9e1LtXZKlMg/u0otZjMwY0ZY7fNkjDFdfPABMGQIZdZevard427eTOceFgtw9Kh2j8sUxRkFuTl0CGjXjtJMgqloYXQ0vTGdTqBJE8oYaNeOCjAG2Uq5qhISaPV0xAhg8WJaaVu7llJzg2y1c2yHsRg2f1iW7QeWKAvGdhgb0P0mJydj5MiRuHbtGiIjI1G9enVMmjQJM2bMQJcuXW7UKmjUqBFq1aqFChUqoFWrVvSfswUJAGDo3Xfj8fffhzkmBuumTNG+TgFAWQVXrwLlywO1a9N2m6JFKWAQzk6dAiZP1iYgWro0naQy/TRsSF0POncGDhzQNlvObKaWm127aveYjDEWrmbOpC5tf/xBgfqqVal1eLdutL1SrXOD6tWpKPK331Lr8ylT1Hkcpiohg6AoX9OmTeXmzZu1e8A1a4C77qJVd6M/PzExFBxwOqn4micw0KiRfqtFweraNSpUYoAV5X379qF27do+//z0XdMxatkonLh+AhULV8TYDmMxqP4gFUeYjytXqPiL0TppmEz04VWokNebvT3vQogtUsqmWgxPL00jIuRmrf5WDz7IBwxGkZoKDB1KnQ+0yvapUoW29+gRKGSGEw7zK6DDcSxjHhMmUPaw1ZpxXWQkrfQ7HEDz5sB999EiWc2ayh8DX7hAxYsLkrk8aRJQty5ld7MCCXSO5TPJ7H76iSp+G7UeQUwMRf9cLioE5QkMNGwIREToPbrgFsRV2AfVH6RvYCC7K1eMFSQwmWiLSdmy/nXACBda/a0SEmgVmxlDTAwVrvz4Y+DNN9X/3DObKSjBQQLGGNPG008DixYBK1ZkZEhnLmC+ciWwcSPw6qs0N3fqRBkHHTook/1X0C1mLhfw2GN04UCBbjhQ4OHpbPDJJ8YKEniq9LvdFBi4+24KDNxyCwcGmDG53cbooOGJihctSrUojFRYMVw5HNR9hBmHEMCLL1KNjj59aNVJjUy6uDhKP61XT/n7Zowx5p0QtP2gVi1a3ffGc95js9HP/vknZZxVqgTccw9lWbdsScFlrezeTf/ec492j8ly4EABQG+GwYOBhQv1DxJ4AgNSUjrQ3XcDbdvSQRwHBsKKlBLCANsg/JacrO/2DU+9gRIlqKWNj+luwbANK+gVK0ZBG2Y8XbpQ8akOHYCLF5WvzRMdDTz+uLL3yRhjLH9Fi1I2V7t2vp3npBesxsGDwPjxVMMoNZU6pHm2KdStq+6x3sqV9G+4tak2GA4UXLlCL/i9e/UJEngCAwB1JejenQID9eqFR4G1ixeBI0coKMJuiI2NxeXLl1G8ePHgCxZcvUopY1ozmehDq3RpSnXzo0aHlBKXL19GLKdEq6tdO71HwPJSsyawaxcFqLdtU7Zugd1O3S6WLg3qbV6MMRaUmjenLWbvvpu1XkF+MmeJ/vsvsGULZWBHRgJ33knbFDp2pGMvJXkCBcWKKXu/zC/hXczw0CE6Kb9wgYoBasFsphMak4nSeDyBgTp1wiMwkF3PnhTlnD4d6N9f79EYhtPpxKlTp5CSkqL3UPx38qS29QmEoPdO4cJUf6CAgZXY2FiUL18eUdkqAIdDsa2mQkjVy2zFxwNffkkV75mxpaUBI0cCP/wQeLDAbKYDSqeT7rdiRWD1aqoXwsJeOMyvABczZAYhJWWN/fuvclljCQl0X2XLUpC5e3fg9tsD3+555Qq1tObPioAEOseGb6BAq84Gnr7sJhO9ce66i1bVatc2RHV9Xe3bR20bU1JoQvnlF5pkWPDavZvSxPyJVhdUXBxQoQJFx3v2VG1rTjgcyGoSKIiNBfbvpxNFFhwmT6ZCWAXNtjObgUGDqPbPO+9QoMhup4yf1auBm29Wdrws6ITD/ApwoIAZyOXLVK/g0iXl79tTODolhYqs33cfFTC+5ZbwXAw1AF27Hggh+gB4C0BtALdKmXGsKYR4FcDDAFwAnpJSLk6/vguATwFEAPhWSvlBIGMokB9/pCqaamw1sFjo36iorIEBNVqOBLu3386IaNrtlFEwfz7Qvr2+41Latm3A4cP0uzqd9K/n4vk+NZUmVs/lqaeoLkWwmTNH3ewck4mK6TRuDIwZA7RpE9Lvq6CdY71JSOAgQbB59FEKanfvTkF1fzOFSpcGPvuMAgYffwyMGEFz2/z5QJMmwPLltOeVMZ2E1BzLmC+KFwfmzqXtAkqfB2XeprBxI7BjBx2rCUHH9j170nYFzhIIGoHWKNgN4D4A32S+UghRB0B/AHUBlAWwVAjhWTr4AsCdAE4B2CSEmCel3BvgOHwjJfUSHT9euTdH5sBA69YUGGjbllZKQvgERhEVK1JKqidY4HbTnqRQChS43bQvLDaWXn9S0nWef12ujO8zs1iATz/VZ8yBmDFD+SJoAL2/IiIoMv3220CDBso/hjFpM8eaTOpvF+FuB8Hp9tuBnTspXfXkSQpq+sJspoPRzOmnlSvTVrN16ygIcccdwF9/UcCPMX0E13EsY0po2RJ47TXggw/UzQBNTc34zJg7F1i2jBaTSpWiAHT37jT/x8WpNwYWkIACBVLKfQC8FVvrAWCmlDIVwFEhxCEAt6bfdkhKeST9/81M/1n1J9jUVEqBXLQosCBBXByd1MXEZA0MVK/OgQF/vfEGFTOcPh0oWRL45huaNELJ+fMUDPFUkPXVyZPqjEdN585RYUolxcbS+2rwYPpQq1xZ2fs3OM3mWIuFPrx9PQn0V1wc0K2bOvfN1FexIrB9O7VPXLky/7oFcXHAW29Ruqk3t91GwYcZM6gzCWM6CarjWMaU9NprwJIlFLjVqk5bcjL9e/Ik8PXXdPyfkkIdFHr1osWgRo24y5uBqNX1oByA9Zm+P5V+HQCczHa913L3QohhAIalf5sqhNit9CALhCJvJWCzXcLcuRQh018JACpsNiow/8dz5oya9QmC7/mZM0fLwJNxnx9PMcfJk+mij5p6PXAelJ9jaWVNHVYr8PDDdPGNcV+TxmDs8VitwIsv0sUI49GfkcZjpLEAxpxfgVA+jiVGex0YaTxGGgsQquORMmObwrZtdBk9Wr/xKMdo4wlojs03UCCEWArAW8h/lJRStbNkKeUkAJPSx7DZSMVueDx54/HkjceTNyOOR+X75zk2Gx5P3ng8eePx5M5IYwHUn1/TH4Pn2Gx4PLkz0lgAHk9+eDx5C3SOzTdQIKXsWID7PQ2gQqbvy6dfhzyuZ4yxsMNzLGOMqYfnWMYYKxi1elXMA9BfCBEjhKgCoAaAjQA2AaghhKgihIgGFYqZp9IYGGMsVPEcyxhj6uE5ljEW9gJtj9gTwEQAJQH8KYTYLqXsLKXcI4SYBSrukgbgSSmlK/3/jACwGNRWZoqUco8PDzUpkHGqgMeTNx5P3ng8eePxpOM51jB4PHnj8eTNSOMx0lgAncfDc6xhGGk8RhoLwOPJD48nbwGNR8jsbdkYY4wxxhhjjDEWttTaesAYY4wxxhhjjLEgxIECxhhjjDHGGGOM3WC4QIEQoo8QYo8Qwi2EaJrttleFEIeEEPuFEJ0zXd8l/bpDQohXVBzbL0KI7emXY0KI7enXVxZC2DPd9rVaY8g2nreEEKczPW63TLd5fa5UHs84IcR/QoidQog5Qogi6dfr8vykP7Ymr41cHruCEGK5EGJv+mv66fTrc/27aTCmY0KIXemPuzn9umJCiCVCiIPp/xbVaCw1Mz0H24UQiUKIZ7R8foQQU4QQF0Sm/ta5PR+CfJb+WtophGis1rjUxHOsX+MxzBzL86vXx+c5Nu+x8ByrMZ5f/RqPYebX9MfkOTbn4/Mcm/s4dJ9f08eh7hwrpTTUBUBtADUBrADQNNP1dQDsABADoAqAw6BCMhHpX1cFEJ3+M3U0GOcnAN5I/7oygN06PFdvAXjBy/VenysNxtMJQGT61x8C+FDn50eX10amxy8DoHH61wkADqT/bbz+3TQa0zEAJbJd9xGAV9K/fsXzd9Phb3UOQCUtnx8ArQE0zvz6zO35ANANwCIAAkALABv0+Bsq8DvzHOv7GAwzx/L86nUMPMf69/fiOVb935fnV9/HYJj5Nf1xeY7NOQaeY33/W2k+v6Y/tqpzrOEyCqSU+6SU+73c1APATCllqpTyKIBDAG5NvxySUh6RUjoAzEz/WdUIIQSAvgBmqPk4AcjtuVKVlPJvKWVa+rfrQf2F9aT5ayMzKeVZKeXW9K+TAOwDUE6rx/dDDwDT0r+eBuBeHcbQAcBhKeVxLR9USrkKwJVsV+f2fPQA8IMk6wEUEUKU0WSgCuI5VhGaz7E8v+bEc6xfeI7VAM+viuBjWMJzrO/0nmN1mV8B9edYwwUK8lAOwMlM359Kvy6369V0B4DzUsqDma6rIoTYJoRYKYS4Q+XHz2xEevrIlEypNno8J9k9BIpaeejx/BjheQBAqWsAGgHYkH6Vt7+bFiSAv4UQW4QQw9KvKy2lPJv+9TkApTUcj0d/ZD1o0ev5AXJ/PgzzelIJz7HeGXGO5fk1G55j88VzrL54fvXOiPMrwHNsDjzH5slI8yug4ByrS6BACLFUCLHby0XTSFkAYxuArC+IswAqSikbAXgOwM9CiEIajOcrANUANEwfwydKPGYA4/H8zChQ3+Hp6Vep9vwEAyFEPIDfADwjpUyEDn+3TG6XUjYG0BXAk0KI1plvlJSbpGnPVCFENIB7APyafpWez08WejwfSuA5VrHxaPpa5Pm1YHiOzRvPscri+VWx8fAxbJDgOTZ3Rp5fgcCfj0gFx+IzKWXHAvy30wAqZPq+fPp1yON6v+U3NiFEJID7ADTJ9H9SAaSmf71FCHEYwM0ANhd0HL6OJ9O4JgNYkP5tXs+VquMRQgwF0B1Ah/QXp6rPTz5Uex58JYSIAk2u06WUvwOAlPJ8ptsz/91UJ6U8nf7vBSHEHFBq23khRBkp5VlBKUgXtBpPuq4AtnqeFz2fn3S5PR+6v558xXOscuPJNC7V51ieX/3Hc6xPeI5VEM+vyo0n07j4GDYnQ7wfeI7Nl9HmV0DBOTaYth7MA9BfCBEjhKgCoAaAjQA2AaghhKiSHtXpn/6zaukI4D8p5SnPFUKIkkKIiPSvq6aP7YiKY/A8buZ9JT0BeCpe5vZcqT2eLgBeAnCPlNKW6Xpdnh9o/9rIQgghAHwHYJ+U8n+Zrs/t76b2eOKEEAmer0GFe3aDnpMH0n/sAQBztRhPJllWN/R6fjLJ7fmYB2CIIC0AXM+U2hUKeI7NxkhzLM+vOfEc6zOeY/XH82s2Rppf08fDc2w2PMf6xGjzK6DkHCt1qFiZ1wX0pJ4CRe/OA1ic6bZRoAqg+wF0zXR9N1AlzsMARqk8vqkAHs92XS8AewBsB7AVwN0aPVc/AtgFYGf6H79Mfs+VyuM5BNr7sj398rWez4/Wrw0vj307KN1nZ6bnpFtefzeVx1MVVDV3R/rfY1T69cUBLANwEMBSAMU0fI7iAFwGUDjTdZo9P6DJ/SwAZ/q883BuzweoSuwX6a+lXchU0TqYLjzH+jUWw8yxPL96fXyeY/MfE8+x2r4meX71fSyGmV/TH5Pn2JyPz3Ns3uPRdX5NfzxV51iR/h8ZY4wxxhhjjDHGgmrrAWOMMcYYY4wxxlTGgQLGGGOMMcYYY4zdwIECxhhjjDHGGGOM3cCBAsYYY4wxxhhjjN3AgQLGGGOMMcYYY4zdwIECxhhjjDHGGGOM3cCBAsYYY4wxxhhjjN3AgQLGGGOMMcYYY4zdwIECxhhjjDHGGGOM3cCBAsYYY4wxxhhjjN3AgQLGGGOMMcYYY4zdwIECxhhjjDHGGGOM3cCBAsYYY4wxxhhjjN3AgQLGGGOMMcYYY4zdwIECxhhjjDHGGGOM3cCBAsYYY4wxxhhjjN3AgQLGGGOMMcYYY4zdwIECxhhjjDHGGGOM3cCBAsYYY4wxxhhjjN3AgQLGGGOMMcYYY4zdwIECxhhjjDHGGGOM3cCBAsYYY4wxxhhjjN3AgQLGGGOMMcYYY4zdwIECxhhjjDHGGGOM3cCBAsYYY4wxxhhjjN3AgQLGGGOMMcYYY4zdwIECxhhjjDHGGGOM3cCBAhZ2hBBDhRBr9B4HY4yFIp5jGWNMPTzHMq1woIAZhhDidiHEWiHEdSHEFSHEv0KIZjqPqUT6OC4LIa4JIdYJIVrpOSbGGCsII86xmQkhhgghpBDiEb3Hwhhj/jLqHJs+r1qFEMnpl2/1HhMLDpF6D4AxABBCFAKwAMATAGYBiAZwB4BUPccFIBnAQwAOApAAegCYL4QoJaVM03VkjDHmIwPPsQAAIURRAK8B2KP3WBhjzF9Gn2MBNJBSHtJ7ECy4cEYBM4qbAUBKOUNK6ZJS2qWUf0spd3p+QAjxkBBinxDiqhBisRCiUqbbagkhlqRHcPcLIfpmuq24EGKeECJRCLERQDVfByWlTJFS7pdSugEIAC4ARQEUU+B3ZowxrRhyjs3kfQCfAbhU8F+RMcZ0Y/Q5ljG/caCAGcUBAC4hxDQhRNf01aUbhBA9QKtN9wEoCWA1gBnpt8UBWALgZwClAPQH8KUQok76f/8CQAqAMqDsgIey3fcCIcQreQ1OCLEz/T7mAfhWSnkhgN+VMca0Ztg5VghxK4CmAL4O9JdkjDGdGHaOTbdKCHFOCPG7EKJywX9NFk6ElFLvMTAGABBC1AbwMoCOAG4CsBDAo1LK80KIRQBmSym/S/9ZE2hbQG0ALQCMkFLekem+vgFwBsAY0ORaX0r5X/pt7wFoLaW83c/xxQLoCSBaSjktoF+WMcY0ZsQ5VggRAWBD+v2vF0KsAPCTlJL30DLGgooR59j0n28NYD0AS/r9tQXQkLfQsvxwRgEzDCnlPinlUClleQD1AJQFMCH95koAPk0vKHgNwBXQVoBy6bc199yWfvsg0CRdElSL42SmhzpewPGlSClnAHhFCNGgIPfBGGN6MegcOxzATinl+gL/YowxZgAGnWMhpVwlpXRIKa8BeBpAFVCAgrE8cTFDZkhSyv+EEFMBPJZ+1UkAY6WU07P/bPoer5VSyju93BYBIA1ABQD/pV9dMcDhRQGoCmBHgPfDGGO6MNAc2wFAGyFEt/TviwFoJIRoKKUc4cf9MMaYYRhojvU6PFCQgrE8cUYBM4T0Ii7PCyHKp39fAcAAUKoUQHtXXxVC1E2/vbAQok/6bQsA3CyEuF8IEZV+aSaEqC2ldAH4HcBbQghL+n6vB/wYVwtB7W6ihRBmIcTLAEqDUmUZYywoGHWOBTAUtLLVMP2yGcDbAEYF8OsyxpimjDrHCiHqCiEaCiEihBDxAD4BcBrAPiV+bxbaOFDAjCIJQHMAG4QQVtDEuhvA8wAgpZwD4EMAM4UQiem3dU2/LQlAJ1DxlzMAzqX/bEz6fY8AEJ9+/VQA32d+YCHEIiHEa7mMKwZUROYyaGLtBuAuKeWZgH9jxhjTjiHnWCnlNSnlOc8FgANAopTyukK/N2OMacGQcyxocesXAIkAjgCoDKC7lNIZ6C/MQh8XM2SMMcYYY4wxxtgNnFHAGGOMMcYYY4yxGxQJFAghpgghLgghdme6rpgQYokQ4mD6v0XTrxdCiM+EEIeEEDuFEI2VGANjjIUinl8ZY0w9PMcyxph3SmUUTAXQJdt1rwBYJqWsAWBZ+vcA7cepkX4ZBuArhcbAGGOhaCp4fmWMMbVMBc+xjDGWgyKBAinlKlA/0Mx6AJiW/vU0APdmuv4HSdYDKCKEKKPEOBhjLNTw/MoYY+rhOZYxxryLVPG+S0spz6Z/fQ5UdRMAyoF6iXqcSr/ubKbrIIQYBorWIi4urkmtWrVUHCpjjHm3ZcuWS1LKknqPI5uA5lcgBObYnTsBp8GLNptMQK1agNms90gYMySDzq8Az7HMKNxu4MABwGYDtCpAHxEBVK0KFCqkzeMx1QQ6x6oZKLhBSimFEH69uqWUkwBMAoCmTZvKzZs3qzI2xhjLixDiuN5jyEtB5tf0/5cxx5YvLzevWQPExio+PtWULAlcuqT3KPLmdgMXLgDbtwPlyuk9GsYMx+jzK6DQHMvHsawgLl8G2rYF0tK0CxIAgMUCvPMO0L+/do/JVBHoHKtm14PznnSs9H8vpF9/GkCFTD9XPv06xhhjvlF2fj17FqhQAfj+e8DlUnqs6nA49B6Bb65eBVq3Bq5f13skjDHf8TEs09epU0CTJsD+/UBqqraP7XRSkIKFPTUDBfMAPJD+9QMA5ma6fkh65dgWAK5nSu9ijDGWP2XnV7ebVudHjgRq1AAWLtR29aIggiVQ4HLRAV+nTtof7DHGCoqPYZm+3noLOHlSny12KSnGz9hjmlCqPeIMAOsA1BRCnBJCPAzgAwB3CiEOAuiY/j0ALARwBMAhAJMBDFdiDIwxFoo0nV+tVuDoUaBvX+DWW4FNm5T6NZRn9PoEmTkcwK5dQL9+FJRhjBkGH8MyQ7Ja9f28OHNGv8dmhqFIjQIp5YBcburg5WclgCeVeFzGGAt1usyvViuweTPQpg3Qvj0wYQJQvXrAd6sYlyt4tkh42O3AkiXAM88An32m92gYY+n4GJYZkt5ZfefO6fv4zBDU3HrAGGMsmNntwF9/AfXrA48+SoX5jCA1FYjUpBavsmw24LvvgE8+0XskjDHGjOy554D4eP0e3yif90xXHChgjDGWO5eL9iv+8ANQpQrwxhuUcaAnu53aNwUjmw14/XXgl1/0HgljjDGjuvVW4N9/gaJFASG0f/zkZO0fkxkOBwoYY4zlz+Ggk9yPP6ZWf199pV+dgGAOFAA0/gcfBFat0nskjDHGjOqWW6hWUKlS2n7mxcfzFjkGgAMFjDHG/GG3U6u/F18EypcHhg4Fpk8Hjh/Xbk9lSgpgCvKPL7sduOsuYM8evUfCmLZcLmD9espOYozlrVo1YOtWoGJFIDpa3ceKiACKFaNMhnbt1H0sFhSCcJMnY4wx3VmtdJk2DfjtNzr4j40FbrsN6NIFeOwx9Q5q7PbgDxQAlNrZti2wbRsFXRgLVadPA4sX01yxYgWdkKSk6D0qxoJD2bJUYLhdO2D/fnVa7UZHA2XKUKZbxYrK3z8LShwoYIwxFhjPXka7HVi4EFi+nLYn3HefOo9nt6tzv3q4epW6S2zdChQurPdoGFNGSgqwZg0wbx5dzp+n4IDe9U0YC1bFigFr11IgfssWZT8HzWagTh3qzFO0qHL3y4IeBwoYY4wpSwjg8mX17j8lRZ/iTmpwuYBTp4BOnWglJyZG7xEx5h+7nWqYnDtHXVJ+/ZVWP2NiKIioZy94xkJJXBywbBnQqxfwzz9UNyhQFgtlKsyeTVmBjGUSArmbjDHGDMVuB55+GnjhBapnoMb9hxKHA9i1C+jbNzhOqj78EChdmla4Zs/WezRML4mJwJw5dKJRpAjQuDHwyiu0vzk1lW4PhtczY8EkOhr44w+gTx967wXCYgEeeICyfjhIwLzgjAJmXIcOATNn0kH0HXcALVoACQn5/rfU1FT8+OOPSEtLy3HbgAEDUDgU03tdLmDYMKB7dyqQpnbBG8byIiWdzH/xBTBpEvDmm8CIEcqtltvt2hVO1IrdDixdSgGWiRP1Hk2e9u/cieWeHtsDBwL/+x/Qvz9KV6iAnj176js4ph63m+pp/Pkn1Rr477+sJxdKrG4yxrBgwQKcOnUqx/W333476tWrR9t4vv8eKFkS+PLLgr33zGb6bH7pJQVGzEIVBwpCidsN7N0L1K4d3K3DAJq4Pv+cfqe0NEq3cruB1auBhg3z/K8LFy7EM6+8AXPVxlmut5/Yg7S0NIwYMULFgeskLQ1ISqI94XFxwKBBwOOPA40a6T0yFs5SUujyxhvARx/RCeWAAYEXIkxJCb1AAUAHe1OmAJUqUTaGQT1z5AT+rVAPMYVK0RWJACbPw9X/VuHihfMoyntcQ8f588Dff1Ng4J9/6H3ncNAFyPiXMaYIh8OBe3r0QPEmXbNef+0C6v/yG9YsX0JXCAGMGwcULw68845/mXZmM/DttxToZSwPHCgIFZ6TxNWraTX5nntoAujQITj3vJ4/n3XSS0ykf9u3B7Zvz7Miq5QScWWrw9z+iazXL58EGYonFwD9jX/5BWjVCnjuOWDyZOCnn4CbbgKefBIYPJj68DKmB5uNLo89Brz9NmUa3Hlnwe/Pbg/dlGabjQIr5csD/fvrPRqv3EWKIKb07YirdXuW65P3r4H84QfgqadCp4ZEuHE4qGDaggWU3nzyJB1TeAqWMsZUZzJFIC7bMazpyBa4L6zM+cOvvAKUKEHzri/Bgvh4YP586rjD9CWl4T8ruUZBKDh2jFbZV6+mfYFJSdTXfMAA2jfYvTudRCYl6TxQP1Sp4v3Nc/06cPfd2o8nGAhBacurVtHf3eEAjhwBRo+mwErHjnTgxytATC9WK3DwIHDvvUDLlpTGXBB2O223CVV2O/DQQ8DK9IPC48dpD6lRAp25ZaxJAK++CmzYoOlwwtK2bdRhRImA2ZEjlL7crh113ujRA5gwATh8mD4vOEjAmLE98ggtDpnNuf9MRARlH6xdy0ECvR09SvNsQgJw4IDeo8kTBwqC3erVQIMGFCzI3lc1MZFSdP/8E3j0UYo4tm5N6UYXL+oyXJ+VK+d9wnO7+aAlP61aAbt3A3Xr0nNot9NrY9kyYMgQeh088QRlZjCmB5sNWL+eXqv33Ufzlz9SUkI7UADQ+7Z7d3ovjxlDBxVvvaX3qPLndgObNuk9itB2/Tpl1/XtC1StCkydWvAA8IQJ9FnxwgvAihX03kpMDP33F2Oh5r77KKDsrcBhdDQtGG3fDtSvr/nQWDqbjbJ869alczO7nYpSGni+5UBBMJs0Cejc2bfKwklJdCCxejXwzDNAhQq0f338eFqt8sWFC9pVGy9bFoiK8n5bpUrajCGYlS0LbNxI208yf2gkJdFl8mQ6SatWjfaNGz1wxEKPp+DhvHlUV+XJJ31vqRgTA0RGBl7rwOiSk2nlp2NH+n7RIl2H45PUVGDnTr1HEdpeeoneO1YrfX6PHEnbzD76KGObnq927aLgQKh1EmEsHHXsSAG/QoUyrjObgVtuAbZupS1tTD+vvgp8911GVqTbTYXbP/pI75HlKsSPskJUWhowfDjw7LMF+3C3Wulgbvt2YNQooFYtoEYN2ju8Z0/O9FaXCxg7lk7QPS2Q3n6b+iSrpWzZ3NNsa9ZU73FDSXQ0ZY98/nnO7AyXiyKbnq0JFSrQnvG5cwGnU5/xsvDkctGJynff0YrHu+/mX8F52DB6rY4YAVSuTIGD+HhNhqu5a9doDypAB3tGJwTXQ1HTtm3Ajz9mzSBMTgauXqXP5bJlgeef970K+rVrqgyTMaaTZs0oY694cfps7NABWLOGjt+ZfvbsoUW67NnfNhsd9+zdq8+48sGBgmDjSTmcNk2ZVkR2Ox2kHzoEvPcecOutlPb/3HO0z/TAAQoMvPce/ZzDQQcqY8dSy8LduwMfgzdlynhPpYyO5kCBvx58kD4kSpXynqXh2ZqwdClw//304TJ8OLBjh/ZjZeErNZXmtA8+oFWPyZMpKOpNVBQFtj79lPb6HTsGfPUVpV4WKkSdP4KxiKs3Lhdw5gxlgE2YoPdo8hcTQ11XmPLcbto+ltsCgc1GCwFffQXMmePbfV6/rtz4GGPGULs2sGUL1R6ZOzd0Pg+DlZTAAw/QeZQ3KSlA7965H/PoiAMFweTgQdpbtGGDOv2KHQ6637Nngc8+oxSmunUpGJD98TyrzkuXKj8OgHrDegsUREYCTZqo85ihrHFjilY2a+Z9/5qHZ2vCpElUbK56ddqeYsStCU4nrV5yQCO02Gy0Ovrss7Q1Zv78/Iv43XQTdfb47TdaIV23jiL0LVpQcLFQoeDepuBwUM/6gQON3+3h7ruBOnX0HkVo+vZbCozlJzWVjhd84e9WBcZYcKhUiYriBvNnX6iYPp0+w3M7lpGStpG9+6624/IBv3qCSbt2wKlT2lStd7konTEtLfcD05QU2l+shogIoGhRqghaqBAQG0uriN98Q5kMzH/Fi1NHhMceyztYAGRsTTh8mLanGHFrQmR6d9eGDen3YqHFagVOnKDuLU2aUCqlL4SggOqLL1LA4Pp1CiCMHEndVKKjg3Obgt1OBUmfekrvkeQtGAouBqNLl6jgoNWa/8+63VR7wBdcHJgxxtRz/Todf+Q3d9tswLhxhis0zoGCYJGYSMUEjdIey2PDBvWqdS5bBsyaRS3Cjh2jA+XBg9V5rHAREUHFC6dNo/RsX/q3etua8OST+hcsEyJjr1ebNsCvv+o7HqYOq5W2O3XoAHTpAuzf79//j42l7KgJE6gmx4kTwNdfA716USu4YNqmYLMB33+v9yhyFx1F2R1Mec88k3Nva158fZ/4EnhgjDFWMC+/nPuWg+zsdtqCYKA25hwoCBZ79uTdH1UvJpN6qd8NGtCJQcOGQOnSuffuZv7r3ZtamJUr599JkmdrwjffALfdRkUwJ0yg1S49REcD58/T1xs36jMGpg2bDViyhOaDBx8Ezp0r2P2ULk176GfPpi0O69ZRzZXbbjP+NgWzmbJ6jMqoz1uwW7cO+P13/w4eT5707ec4UMAYY+rYsQP44QffAwUA1SQaPVq9MfmJP9WDxe7dhixyAacT+OcfvUfBCqJ2bQpAtWmT/1aE7DxbEw4doq0J5csDnTrRVhSttyaUKkWZNuPGafu4THtuN33g/vwz9Y9/7TUKXBWUZ5vC888Da9dSiuDvv1N6f9WqxtqmYDZTkTpPq0QWHtLSKJPL3w5HNptv2wr8OYBljDHmG7ebChj6O3fb7dStbNMmdcblJw4UBIstW9QpYBioiAgqwMGCU6FC1Jv95ZcLnrFis1FK7JIltDXEKFsTWOhyOOjDdMIEClJ9+qkyqXqxsbTFYfx4qs9x4gRlz/Ture82BYuF3qMPPKD9YzN9ffYZFRj2l9lMW23yw4ECxhhT3rJltJhWEJ4tCAaYnzlQECw2b9Z7BFnFx9OK23ffBUfLLkYSE6m9Vv36NIkBlC78xhu0kpqQEFj6cPatCTffDCxcqMzYGcvObqfX9KhRVOH5l1+UreNSujR1Gvj1V9qmsGEDtYpt2VK7bQoWCx0wvPGGuo/DjOfsWfq7F2SRQAgKduXF4TBe3SPGGAsFxYoFdnxw8SLw0kvKjaeAIvUeQMiTEnj0UWrxZbHQCXahQlR9+8sv6WtfHDig7jh9FRdHAYL33we6dfOtGJ7KVq5ajU8///LG96dPnYSEt3oGAt9OmYrlq9feuGbwwP64794eGozSAP75B+jfn06sUlOBe+4Bmjen12GtWlQPYscOoHNn2t8aSCTTszXh4EFKl+7WTbnfg7HsrFa6PPww8Pbb9Jpu21bZxxCC2sXWrQs89xy9P9auBf78k+oGnDxJ2QaBbIXILjaW3qPffafrXPvu2A+wLVMtmu1bN0M0r5vzB4UJQx56BNHRlHURERGBLz8bj5IlS2o11NDyxBMFz5Sx2/NfzUpOpm5C/hRJZIwp6tq1a3jsyZFwOml7scvl8j7fC4H9e/fgvr4DblxVp3YtjHn7Ta2GyvxRt67/2w4ys9upJW6/fkCrVsqNy09CBkE0uWnTpnKz0VbUfTVxIvDKKzlXBKKjqaf98uX0QZ2XCxeAihX1/zAvVoxWnVu3NkSAwGPcxx/jrQnfwtzwrhvXxZSvg6giWatvu5Kvwn5s243v7ftW4qHud2Dip+M1G6surFbg6aeBGTNyvg5NJnotDhwIfPABULIk/cz99wN//RX4dhchgFdfpWJxQUoIsUVK2VTvcaipqRAySGdY7ywWaqn4xReUPaOFCxeoM8gff9A2HKeTAmYFDbhFRlKx0E2bKECro5vr3oJz5iqIvqk6AECYTLDUvB0iIutaQ+rpfXBe9aTJSyQum4R1a1aiSZMmGo84BCxbRsHcQObgBx4Apk7N/fbjx+lgVseChgII+fkVCPLjWKaq//77D/VuaYAidz5549g6snApxFaol+XnpNsF2/5/IV0UUHBeOoGE81tx8sghCAMdk7NMKlWiLYyBKFOGFt0KeBwQ6DEsbz1Q09q1tK/U2we9wwFs3QoMHZqR+ud2UzGtY8eoj+by5cCcORRsiI3VcOC5KFGCCt8ZbELq3asXkHwRcXXaIL5ee8TXa58jSAAAEfFFb9weX689olOvYUC/PjqMWENr1gDVqwPTp3t/HXqKw/30E1C5MqVVm0xUEX7s2MA7bcTFATVrBnYfjPnLZqPXfvPmFI0P9IPaF6VKUcBt1izgypWMbQqtWlGmgT/bFISg+Xb5ct2DBAAwuH9fRJtwY+6Mq9M2R5AAAGLK1c6YX0tVRdFixdC4cWMdRhzkHA46Ngg0ULt3b963JydzNyHGdFarVi2Ur1gZUcXK3pg/swcJAECYIhBXu/WNn4mMEBjQtw8HCYxMiSD51avUHlcnHChQy9mzQPfueaed2O20+lSiBB0MRkXRwWa9enRC3rMnHSyMH0/p4nozYjFFAFWqVEH58uWRemqPz//HeeU0hCMZLVq0UHFkOrLbgREjqBPBuXP5r2o6HPT3HTuWsldmzqQshL//BooUodXNgoiIoEAFY1qTkt4Hv/9OW2uefpo+cLXg2abw7LMUsLh+nYK+zz5L74foaKoH4k1sLAXt1qyhGgkG0LdPb6QcWgcp3T7/n9SD69C3dy8+iC2IDz+kYFOgjh3L+/akJMMF/hkLRwP79YHj0Dqff15KibTD69G/b4gvdgW7Vq3o8z4QKSm02KdThzkOFKjB4aA92b7sVbXZ6IDAZqPVXYeD0gATE+ngMjGRvjfCFpFA9tqobHD/vkg7tN7nn7cfWItePXvCFIp9vzdsoCKCU6YUrKXWxYtUV6N+fVoB3bOHTnoKkl2QmsqBAqavtDR6H3zzDVChAm2x0bqScEwM0L498PHHlEJ46hQwaRJlOxQtSoHi2FjaMtGlC7BrF1CtmrZjzEOtWrVQolhROM7s9/n/uI+uD/2MLTUcO0Y1gJQIzF+5kne7Wl/aJzLGVNevbx84D6+Hr9vBnRePITYCnLFldI0aKZMRbrdn1BjTmKpnSUKImkKI7ZkuiUKIZ4QQbwkhTme6PrQqnY0YQcUH09L0HomyDNCmIzf+rniJYxswsH9flUelsdRU6gffrh2diAQS2LFaKUDQsSMFDjZuBAYMoBMZf3EhM1WE7fxaUKmp9Lp+910KGEydSjUE9FCyJH3oz5wJXL5M76/33qNWeL//bojtBtn5s+LlvHwKwmEN3YwtNT3yiDKtPgE6QM2rfXFSkjEWIQyK51imlVtuuQXxsdFwnM+nU0k6ztgKEg0bKnfulJRE55caUzVQIKXcL6VsKKVsCKAJABuAOek3j/fcJqUMnf5p06blvh882OldTDEPNWvWRInixXxa8Uq7fh7OxIu44447NBiZRrZuBWrXBr7+WtnMj9RUWt2KjqbK6xMn+pdZUK4cp7aqJCznVyXYbMClS/SBe/PNwKJF+p4sCQHUqUPbEh5+2LDvF39WvOwH16LXfSGasaWmefOAdeuUC2BFRubdIjE5mTIZmVc8xzKtCCHQv29vOA76FozljK0gUaxY7tsM/ZWSAvz2Gx2zaEjLT/EOAA5LKfMIbwe5bduA4cNDM0gA0MGLgbMkBvm44mU7sBb33HMPIgu6795o0tJoH9SJE8qtRHm43dT67cIF+v6hh4DVq2lFNL9uHQBVbWdaCP35VWlWK3DkCNCnDxU95IrkefJnxUsc3YCB/UIsY0ttNhtt+VLy+CE1Ne9AQVKSoT/TDYbnWOafCxeoNs6uXT79eP++feA6mn8wljO2goySnZdsNmDwYODaNeXuMx9aBgr6A5iR6fsRQoidQogpQoii2X9YCDFMCLFZCLH54sWL2o2yoK5cAbp2Dd0gAUAnhjq2UcqPrytepmMbMTiUth1ERlJGwa+/AmPGUOX1hg0zihAmJNCloIERKYHPP8/4vkkTqqbdtGn+WxFuuaVgj8n85df8CmSbY7UZozFZrdSCsHVrakeX14lVGPN1xct57RycSZdCK2NLC2+95VtdI3+kpAD79uV+OwcK/BHYHBsMx7FMGVIC339P9Zm+/JJO7HzIxGrWrBmi3E44L+Xdpcd+MIRrbIWi998v2Lbd3FitFFTWiCavMiFENIB7APyaftVXAKoBaAjgLIBPsv8fKeUkKWVTKWXTkkbf4+xyAT16KFOl2MgiIw0dKKhfvz7izTF5rnilJV2G/eIJtG/fXsORaaB2beqS8fLLtPVl2zaq8H7tGlVP//574J13aF/0LbcAhQtnDSLk1SIrNRX49tus15UoQZkFw4blvhUhLo6qzTNVFWR+BbLNsVoM1OjsdmDhQuo6M2wY1eZgWfiy4mUPtYwtLezfT8FYNQoG796d+22JiRwo8IEic6zRj2OZMg4fBlq2BEaOzAjEHT4M/PJLvv9VCIHevXsh9eDavH/uaAjW2AplLVpQ7aFA242bzXTsbjJRBwSN5m6twlFdAWyVUp4HACnleSmlS1LluckAbtVoHOp45RVa0c2runAoMJkMXSVZCIH+fXrlueJlP7gOXbp2Q3Sg7UqCRVwcBQZ69QJefRWYMQPYsYMCCFevAqtWUe2Bt98G+valk6RChSiIUKhQRhDh7Nmcf/uICGrdOW2a92hpZCR3PNBGaM+vWnK5aBV22jRqUfjGG4YOjmqtadOmiHQ78lzxMh3fiEG8d9Z3UlIbZLVqAOWVIRPqixvK4TmW5c3ppIzO+vWpOG3mzw2rFXjqKZ8CgQP69oY8uiH3h7l2LvRqbIWDzp3puCK/YIEnGGCx0DF0uXKU7fjkk8AnnwCzZ1OW2IULBc8S9pNWIf8ByJSyJYQoI6U8m/5tTwB5hLwNzm6nk6VwWD0xmQx/0Ny/bx9M+bkv5O2DvVaDNR3biPuHv67DyAwoPp62KDRsmPO2xETg0CG6HDhAQYWYGO/306cPtU/s1ImKxHkOeLk1olZCd37Vi8NBl48/pgKe771HqX7hMM/nwWQyoXevXvh111pEl6yU4/a0pEuwXzyJDh066DC6IPXLL7SHWa2igufOUTDCW5FMDfe5BjmeY1nuNm+mrlBnzuQeDLBagXHjKPich1atWsFtuw7n1TOIKlo2x+32A2txN2dsBac+fajt/dNP01butDQ6Ti5Vitoh169Px9I1atClQoW8s301ovorTQgRB+BOAI9luvojIURDABLAsWy3BRezmdrI/fMPMH8+pXm73XQpaBphZCS9OIzWZUAIQ2cUAOl7vCTt8cp+IOuyXUfymQPo3LmzTqMLIoUKAY0b08UXderQ+6BPH+Dff6lWh9sN3HSTuuMMcyE/v+rNbqfLiy9SsODTT2mLj0E7E2hhYL8+mDXvYaDlgBy32Q6EWcaWEr7/Xr3P+oQE6ljjdNK/2XGgIF88x7JcJSfTds/vv8//eN9mAz74gALOZcrk+mMRERG4994emHdgLaKa985xu+n4Rgx+8aNAR8708sgjtIDmcNC/FSsafgFC9a0HUkqrlLK4lPJ6puvul1LWl1LeIqW8J1NkNjjVrAk88QTtb71+ndKOxo0DunShD+q4OOpn7KuoKKB8eVrBNxqDZxQIIdC7l/c9XraD69G+w50wB7pPiHlXuDDw1190UhUVBZQtG9YnVFoIi/nVCKxW4NQpYMgQysD591+9R6SbzCte2ZmOb8T9A3jvrF+mT6euG0oVu0pIoAWMnj2Bn3+mVc7cAjeJico8ZgjjOZZ5ZbPRQsqUKb4vCqalAc89l++PDerfF+JYzu0HnLEVItq2pQzcqlUNHyQAtO16EB48PbGffJJ6XV6/DmzYAHz0Eb0w4uIo5TuvwEHlysCSJfSzRpKWpnz7PRUM7NfH6x4v07ENGDKwnw4jCiMmE1Xvnj+ftuQwFkqsVmDnTprLO3bMu6J8iPKseNkPZA3GumzXYT1zkDO2/FWiBLByJfDMMwUvdpWQQFvD7rqL9sFevkzFs7p3zz1IACjfZYGxcCAlcP/9wMmTVNPGV04ntZvesiXPH2vbti1Sr5xFWuKFLNdzxhbTAwcK1CYE7TkZORJYvJgi+GvXAh9+SAea3gIHtWsDVaooUyVTKTExVBQvCA4CW7ZsmWPFy52SjKQTe9CtWzcdRxZGOncG7r1X71Ewpg6bjbabde2q90h0QSteG7NcZzu4Hh06csZWgUREAGPH0md+oUK+7UuNj6fP5U6dqCvN5cvAggWUSeDr38DgWwkZM6RPP6XsSX+CBB52O20/yKNzTFRUFLrffTdsB7IW5o44sYkztpjmOFCgNZOJClY89RRlDSQmUl2D998H2renlO1+6aveHTtSSzsl+28WRGQkBS4WL869oJ2BREREoGfPe5GSacXLdngTWt3RBgkJCTqOjDEWMiIjgXvu0XsUumjbti0cV88iLTGjhaTp2EbcP4AztgLSpQu1M6xTx/vJflwcZQi0bQt8/TW18Fy8mDrWFCQD0WYLeMiMhZX9+4HXXgvsvXPgAPDbb3n+yOD+fWE6nhGMddmuI/k019hi2uNAgd5MJqBBA0o7XLaMUvv7ZooYPv88pRP6U+NASUJQRc6VKym9MUgM6t8XyLTHSxzbgCEciWWMKSUmxqf9pqEoKioKd3XvDlt6MJYytnZzxpYSKlSgKupDhtAiQVwcvdZatgQ++4y6GCxfDgwaFPhnckELLjMWrj79NPBW6FYrMGJEnhkJd955J+znjsKVfBVAABlbRiuKzoIOBwqMTgjac1ilij5tMgoXBlavpmBBEGnTpg0cV88hLfEC3A47ko9sxz1huvrHGFNYXByt5FaurPdIdJN5xct2aCNu54wt5URHU8bAjBnA//5HhTT//Rd46CGgaFHlHqcgqdOMhSu7HfjhB6rXFaikJOCTT3K9OSYmBnd27gzbQdp+4FPGlsNBNdHGjwe6dQOKF6ctSrt2BT5eFrY4UBAMzGbg77+1X9GPi6OVi6pVtX1cBWTe42U/sgVNmjVHUSUPsBhj4Sk+nuoTtGyp90h0lXnFS3ChWHXccw8wbBgVPFSa2x34yihj4WT2bOU6Odls1HL33Llcf+T+Af1gOr4x94ytc+eAOXOAp5+mLc0JCVSz5NVXqZj6lSuAy0U10hgrIA4UBIvy5alQkVaFosxmqlzfsKE2j6eCwf37wnRsA3B0PYYM5G0HjLEAJSTQNqxbb9V7JLrzrHgl71mOpKPbcffdd+s9JOaP5OSgaM3FmGF88omyBUCdTuCFF3K9uUuXLkg+9R+Sdy/LmbE1eTJQqRIwdCgwcSLVNnE4qO5Z5u0GUgKbNtHnFmMFwJ8SwaRVK+Djj6lPvaeQihB0Uj9kCEUObTZKj7LZKK3QbqdJIyWFJpHUVJqcHA761+mkNCq3mw4aIiLo66lTgXbtdP11A9WxY0fYzw+Ey3UYPXvO0ns4jLFgVqgQsGoV1ZRhAGjFa8Gg+9GiRUvO2Ao2yclUPJmzChjL3969VIRQSU4ndTrZvt3rolxcXBzatG2PpUt/wpBJX2e9cf9+Oo73pWW5zUYt23ftUi4jgoUNDhQEm+HDaQ/Sr79SpLBUKWrTUrt2YPfrcmUEFEwmoEgRRYarp5iYGHTq0gUnT51ByZIl9R4OYyxYFS5M3Wnq1dN7JIbSpUsXRAjJGVvBKClJn7pHTDlOJ9CkCXD9OtC8OdCmDdCsGbWy1qsAdqiaOFGdoFpKCrVL3LjR60n8kIH9sHTxwpwZW1arf49z7Bh1Wujdu+BjDRVuN53zREXpPZKgwIGCYDR5MnDiBBUqmTqV9swGKiKCKizr3YpRYZO+/BxOXjFhjBWEEBQ0/fffwIOxISguLg67duxA+fLl9R4K81dyMi0KsOD19dfAkSN00njiBG1PjYqiFeSKFYHbbgNatwaaNqUgZ3S03iMOTnY78OOPyhQxzE5KYN8+4I8/gJ49c9x83333oXHjxjkztvwNFFit1F2tR4/wPkE+c4bay166RO3nH300KNq+64kDBcEoOpqKDLJ8cSYBY6xAhKAK82vXAjVr6j0aw7r55pv1HgIriKQkvUfAApGUBLz+etYTRrs9o+XlkSN0mTOHtpXa7VSYumVL4I47qM5K3br6jD3YzJ+vblDNaqVs4W7dcpy0xsbGolatWjn/j2f7sT+uXKGM5NtvL+BAg9y+fZR14yny+MorwFtvAe++Czz8MAfScsHhZMYYYywzk4kytjZs4CABC01KFmVj2hs71vf96YmJlDa/fz/w/fdUBb9pU6q5wvK3c6f6gbXERGpr6CtPQMgfRYoALVr4//9CwZo1tD3n4kUKEgAUoLl8meq+lS9P2dqcgZwDBwoYY4wxD5OJ2tFt3AhUr673aBhTR1IS7dVlwefMGeCzzwp2sgjQCZLTCSxcqOy4QpXFon49D5sNGDOGTmR94e/fPi4O+PDD8Ox08uuvQOfOuQd7rFZ63p99FqhQgbZ0q7HNJEhxoIAxxhgD6GCwdGlqJ1Wlit6jYUaQmAgcOpSRrhoqSpemkxNOtw0+L78c+ImMy8WBAl+VLq3NPnank1a3feFvoKBYMWDgQP/HFOw++QR44AHftmpYrcD588CIEdR6cu1a9ccXBDhQwBhjjEVEADfdRJkEFSvqPRpmBPPn0wFjo0ZA2bJUBCwujk4catakNN6776b9rYsW6T1a/7RvDzz4IJ2cxMXR/vWRI2mfdM2aVCQ5MhJISKDWoFzwyxj27qXq9UqkSO/fX7C97uGmZEltVuIdDmDWLGpjmJ9Bg6g1ui/tDuPigHHjwq/LyUsvAW+84X9QxWqlrJ0RI9QZV5AJwxwUxhhjLJPISKBMGWD9ejohZOzXX4GhQ3OeSNlsdLlwIev1M2dSTYtgaqFZsSKtMj79NO1Zz37SkZxMbdWOHqXLf/9RQbBjx4CzZ6lie2ws/Wu3c7quFpYsoedbCbGxNOe1b6/M/YUqLYtie9olrluXdxBgxAigXTugf396b+bVBaF0aaBPH+XHanRLlwYWCNu7lwIGYX5MwIECxhhj4SsykgoZrV9PB1TMuyNH6KTyySeBAQNCe6/ryZPAQw/5d5Bps9Fq/N69yrQs1sLrr+d9e3w8BT68BT+kpO0YniDCkSMURNi/Hzh+nPb8RkXRxeWi50epE9xwNmIEpUdPmFDwGgUeViuwejUHCvJTsqR29TykBHbvpmyme+7J+2fr1gW2b6d6FaNHA6mpWbdHxcRQsOGzz8KzFer48TQnFzRYEB1NcxsHChhjjIU1kyk8C5tFRdGq6rp12q4aBaOkJGDrVuDxx+nkYtIkvUekDpeL+pkX5CTs4kVK5581y7eU4GAmBHUGKV6cshGyc7sp68ATSDh0CNizBzh4EDh1Crh2jVKn/e0HH+4iIoD33qMWh/37U9ZHQefumBjKpGJ5K1mSTsK14mmX2KVL/jVEIiKoCN999wH33w9s3kzvzYQECuo+/HD4nui2aQM0a0bdPQoSpJSS2oiGOQ4UMMZYuKtWjQ44r10LfJUqWERHA5UrU8Gi4sX1Ho3xVa9OB042G7VYmzgxNPetf/EFrYwXpHBhSgoViJs6lQIG4cxkAsqVo4u3vu0OB3DiBFCjhvZjCwVdu1Lbvm7dKBBTkHnbZAJatVJ+bKGmUCHtA+lXr9Ic+/zzvv18pUrAypUUiIuIoGK84ZhFkN3nn9PJvr/vDyEo+BIVpc64ggi/ihgzCIfLga4/dUXXn7oi2ZF842uHy4deyYwFolAhSh1+6infCyQFs+hoOvFdv56DBL6Ki8tIqXe7Q7da/p49ge1rlZJO3FjePO9BVnCVKlGWz4AB1MLPXy4XULu28uMKNZ4Vei3ZbMCbbwKXLvn+f4QAbr6ZAv8cJCD16lHBWX+3ysXH0/YzxoECxoyix4weWHl8JVYeX4ny/yt/4+seM3roPTQWDmJjgQ8+ALZsoSrvcXF6j0gd0dFU1X3tWqBoUb1HE1wqV6Z/ixYN3WBSICuHUVHALbdQpW3GtBATA3z3HfDNN/4HC1q04BNKX+nxWeF0Aq+8ov3jhppx4/zPDIiI8J4JFYZ4hmDMYOxpdlxPvQ57WpikgDNjqV2b9jl+9hmtooTSynFMDFCnDrBmDVC4sN6jCT516lBAad48vUeinkAq9xcpAixYENqFHpkxDR5MrV3Ll/dtS5DZDPzvf+qPK1SUKKH9YzocwM8/U4FUVnAVK1InCV+3ykVEUOHecGsnmQsOFDBmEL/2/RXREVlPyqIjojG772ydRsTClhCUdnf4MNCjR8HSWo0mNhaoX58K8RUqpPdogtMXX1CP75Yt9R6JegoQKHBEAF2HmND1repILhTL28aYPurWpZPKO+/Me86OjaXAQsOGmg0t6D3wgD5ZdikpwGOPaf+4oebNN30P4MbGUmtcBoADBYwZRp9ZfXIcWDpcDvSe1VunEbGwV7IkVXBfsICKkgVrwCA2lg6KV64MntZ1RlSkSOjvKy9AEcMeg0xYWTUCK69u521jTF8JCZTx8847lDWQncVCNQ0++0z7sQWzJ56gvf9ab7mSEti2DVi0SNvHDTXFigGjRvl2DBMf772TS5jiQAFjBmOONKNwTGGYI718yDOmh3btKLvguefo4DOY9rWazfSh/88/wRvoYNrxN6PAbAbKlgMiI3nbGDMGIaha/tKldIIUFUXXWSzA5MnAlCkUPA0GP/xAxeiWLdO3ha/JRNsA9HjerFbKKnA6tX/sUPLMM96DZx6erZZPPx26NXgKIIiO9hgLbXMHzEWbSm3QplIbnHru1I2v5w6Yq/fQGKP9fe++C2zfTifewVDs0Gymgl1LluR9gMCYhz9BsMhIoG5d/Dp6B28bY8bTsiW1+mzWjDKBtm6lvdfBZPZsymi7916gbFlgzBjg3Dl9xlK3LnUG0iPgfOUKbf1iBWc2Ax99lHHsEh9PxzVly1I72ylTgFOngFdf1XecBiOklHqPIV9NmzaVmzdv1nsYjLEwJITYIqUM6Tw0v+dYKWml56mnaA+lw4B7sc1mqlq8YEFoFWRk6lq6lOpy+NIisUQJYM8edP37Aaw8vjJLJoE50ow2ldpg0WBOGc5LOMyvAB/HFlibNsCqVRnfx8bS50/r1sCzzwKdOmlbdC4lBahRg04otRYfDxw/TlkirGBcLuC++yjY0707ZUuWLav3qFQV6BzLGQWMMcb8IwQVdzpyBOjd23gp/WYz0LYt8OefHCRg/unYEVixgupz5NVSy2IBFi4ESpW6cRVvG2NMYYmJWb9PSQFSUylLrF8/oHRp4PXXgZMntRlPbCzw00/6fOY5nbzaHaiICGDuXGDGDGDQoJAPEihB9UCBEOKYEGKXEGK7EGJz+nXFhBBLhBAH0/9VrkGpEHSAyBhjIU7z+TW74sWB6dOBv/6iFkRGCBhYLLTKNG+e/72TGQMoVXvfPtq24u01bbEAEyfSz4G3jYUy3efY7I4eBZKSNHs43eX1uyYlAZcvA+PG0Sp/69bAH3+ov5e/TRugZ0/f2+0pJTUV+PFH4L//tH1cFta0yihoJ6VsmCn14RUAy6SUNQAsS/9eGV9/DXTrptjdMcaYwWk3v+bmjjuAgweBl17St9ihxQJ07Ur7WrmXPQtE8eKUWfD881nrW5jNVDX+oYduXBUdEY1Fgxdh0eBFiI+Ov/F19roFLGjpO8devAiMH08nw3Xq0GuzcmWq4h4E24cDYrXm/zOpqXRZvRoYMoSygV56ibIP1DJxoj51b1JTgccf1/5xmfKkpK0kBei0oyW9th70ADAt/etpAO5V7J4fe4wmCMYYC0/qza95iY6mXsU7d+a+Eqsmi4WqY//yCwcJmDJMJmoz98cfQKFC9LqqVQv48ku9R8b0pc0cO3cu0L49UKECBQUOHaKTX6eTTjAmTAj9411faoVklpQEXL8OfPop8Pvv6owJAIoWpYVJrYv6ut3Apk209YIFr82bKaBVvTrQv7++HT3yoUWgQAL4WwixRQgxLP260lLKs+lfnwNQOvt/EkIME0JsFkJsvnjxogbDZIyxoFOg+RVQcY6tXh1YswaYNAkoXFib9EyLBejVi9pXaVnYioWHTp2A3buBYcOoLgHXvQgn+syxmzdT5sry5bSKbPfSctNmo6DV//7n330HE2+/ty8iI4HOnZUdS3Z9+9LcEBlJnzsWCwUUCxemVnuxseq02ZMyuDJJvv+eujawDG++Sdtm0tLoM2X4cMP+TVXveiCEKCelPC2ECzNRqAABAABJREFUKAVgCYCRAOZJKYtk+pmrUspc93hxtVjGmF6MXJVbifkVUHGOvXqVehf/+mvBD/jyY7FQRH7yZP22PDDGCsTI8yug4xz79tvA2LG+7bc3mykwO3iw7/cfDNLSKCjn73lKTAzw5JPAJ5+oMy5vbDY68ct8uXSJLmfP0uXCBbr+2jUq0piaSmONiqLPLinpd05N9Z6ObjJRAGLePKrHEAykpHFPngw88ojeozGGs2epiGJUFL13XS56/Zw7l6U4rlICnWNVz8+UUp5O//eCEGIOgFsBnBdClJFSnhVClAFwQcEHpIPSuXOB116jvqeMMRaCNJ9f/VW0KDBtGm0JGzSIDpT8TSXNi8UC3H8/8NVX6qzcMMbCmm5z7O+/+16Uz26nbJcSJYAuXRQfim6Sk+lkyt/2uyaT9t0BLBa6VKjg+/9xOmmlPXtw4fJlOmk8exY4f55qVFy9Sh0e5swBKlVS7/dQmhCGXSnXjdkMvPACUKYM/S09l5Il9R6ZV6oGCoQQcQBMUsqk9K87AXgHwDwADwD4IP1f5UoDb91KB44OB7BtG7BrF6eiMsZCji7za0G1bAkcOAB8+CHw3ns0PwdawMdiAR5+mPaicpCAMaYw3ebYxET/K9vb7cC991Lxv1A55k1M9D9QEBNDxf5KlFBvXEqJiqKT/9Jed66wUFWkCHXqCBJq52mWBrBGCLEDwEYAf0op/wJNrncKIQ4C6Jj+vTKqVcuIXh0/TqtZjDEWerSfXwMRFQWMHg3s2UOBg0CKQFkswBNPcJCAMaYmfebYf/6h/e3+atIkdIIEABUm9Hc7mR7ZBIyFMFUzCqSURwA08HL9ZQAdVHnQIkUoknj2LAUMDJrKwRhjgdBlflVClSrAypXArFm08mO3055MX1kswNNP0/5dDhIwxlSi2xw7dy6tpvvDYtF2T74W/A0UxMTQFgw+7jeea9eoI9Ltt3MtoSATmn+t4cMps+DFF6ldFmOMMeMQAujXDzh2DBg40Pd+1BYL7e177z0OEjDGQo+UwJ9/+v//mjShtrShxN9giclEbSSZMUgJ/Psv0KcP7cfv1g24+WbaEs6CRmgGCkaPpn6zb7+t90gYY4zlpnBhYMoUagFWrRoFAnJjsVBKKc/rjLFQdegQ1RnwRyhmEwCUUeBrIbyYGKqqz9kE+rt8mV6PlSpRi8rffgNSUuh1ffgwLQ5wgcOgEZqBAsYYY8GjeXMq3vXGG3TQm32frcVCt40erc/4GGNMC1Yr4Hb7XmtACODWW4FmzdQdlx4SE30vemsy8eeDnqSkLYX33guUKwe8/jpw8iS9nrMHBY4epe4NLChwoIAxxpj+IiOBl18G9u6lHtGe7AKzGRgzhm5jjLFQ1rAhzYHduvm2JSs2Fvj4Y9WHpYukJCAtLf+fi46mDjgq9KBnPli+HChfHujeneprpKZS7aHcWK1UZ8iXvy3THQcKGGOMGUelSsCyZcAPP9DX48YBzz6r96gYY0wbVaoA8+ZR94P69XPvECMEdZBp0kTb8Wnl+nXfWiNGRHA2gZ6eeQY4cwZITvb9/1y9CkyerNqQmHI4UMAYY8xYhAB69aJih08+qfdojOnRR4Hq1am2Q9WqdKlSBahcmS6cgcFYcGvRAtixA/juO1otz17DJZSzCQCqlJ/fXvboaODBB4HSpTUZEsvG5QIOHqSMQH9YrcBrr/lfj4NpjgMFjDHGWDBZtgz4+WcqDHXkCO35PHqUAivHj9Nl7169R8kYC5SnQ8yJE7TvOy6OCvcJQVu0GjbUe4TquXIl/58xmeh5YfqIiAD27AF696bAla+1NQDaovDRR+qNjSmCAwWMMcZYMImKyvv2yEigVSttxsIYU19MDPDKKxQMHDKEVtpD/SQrv0CBJ5vgppu0GQ/zrkoVYMYMYOdO4J57KGBg8uH00m4HfvlF/fGxgHCggDHGGAsmrVvTJbd0T4sFaNRI2zExxtRx7RqdUN13H9C+PW03cDiAW24Bzp6l9nPXr+s9SuXl9ztxNoGx1KgB/P47sGUL0KULFeMUIu//U6yYNmNjBcaBAl9duwbcfTfw2WfUuoYxxhjTy9df555Z4HAADRpoOx7GmDKkBPbvp0KujRvT/vtHH6WWcocPZ2w7qliRVnMHDQLee0/vUSsvr0BBdDTwwANAmTLajYf5pk4d4M8/gXXrKLCVvbaGR0wM0LatpkNj/uNAgS8uX6aiMosXU/GN5s2BU6f0HhVjjLFwVakS8Pzz3luoRUdzOi5jwcThoNojw4cDZctSgOD114Ft2+i2pCT6OZsNGD8eSEykY9PUVLrMmKHscFwOdP2pK7r+1BXJjuQbXztcPnQhUEpeVfRNJuCNN7QbC/NfgwbA0qXAypXAHXfkDBgIQW0SmaH5WaYyDF24QO1nTpwAnE66bN1KaZ+7duXetoYxxhhT02uvAd98k7Nnde3a+oyHMea7CxeARYvoJH/lSgrwJSfnn7V66hSdKHu2HpnNtA1BQT1m9MDK4ysBAOX/V/5GgKDHjB5YNHiRoo+Vq9wCBVFRwP33U0CFGV/TpsCqVcDatcBzzwG7d9NnVq9e3K0iCHBGQV7OngVuvZUqSDudGde73cClS8CKFboNjTHGWJgzm2kLQuaAtae3OmPMWKSkdofvvEPp2RUrAiNGULZqSgplCfiytTU1Ffj8c2DWLNoL/txzwOzZqgzZnmbH9dTrsKfZ8/9hpdls3q+PiADefFPbsbDAtWwJrF9P2xLuvRd46y29R8R8wBkFuTl9mrYYnD8PpKXlvD0lhdpP3XWX9mNjjDHGAKBnT1pN3LKFqk3b7UC3bnqPijGW3bRpVKU/MjLjuDI11f/7cbkoSPDFF0DnzsqOMd2vfX9F+f+VzxIgiI6Ixuy+6gQkvMqeKQVQNsHgwUC5ctqNgymrTRu6sKDAGQXeHD8ONGsGnDvnPUgAUIbBli3ajosxxhjLTAg6aZgwAfj7b9rL3LEj3SYlHWxfvcpFeBnTW58+wDPP0MluftXg8+N204KVSvrM6pOjHoHD5UDvWb1Ve8wsXK6smbwenE3AwtH77wPVqtHCwPjxgNWq2UNzoCC7w4cpSHD+PE1Uedm5U5sxMcYYY7kpXx544gnKgouOpho60dG0jzkhgfaB1qhBbdQ4YMCYPuLi6CB/40Yq9BZIjas776Tih+fPKzc+L8yRZhSOKQxzpJeiqWoymYCRI4H69YFChSgLIzYWGDiQ5jvGwsXUqcC77wJHjgB//EG1iapWpS1LGuBAQWb791NNgkuXfDuYOnaMVmwYY4wxI/jnHyq461mN86zMHTlC7cRq1gTmzuXPLsb0Uq8eZaROmECBvOho//5/XByweTPQrx/VPFDB3AFz0aZSG7Sp1Aannjt14+u5A+aq8ng5CEHtyHfupDaJly9TMbyvvtLm8RkzgiVLqBNK5m04KSlUCPW++6gg5KVLqg6BAwUee/cCt91GKZq+HkBJSdsTGGOMMSMYNSr3tESrFTh0iPb41qoFzJ/PAQPG9GAyAY88QgG8Xr1y7zXvTWoqZRL06QN06qTK8KIjorFo8CIsGrwI8dHxN76OjvAzqKGUQoWARo38D6owFqx27qStBt5qdQBU7HPBAtqSMGeOasPgQIFHv35UcTYhgS7x8RS1tVgo3SkmhvaVRURk7C2TkvrbMsYYY3rbvJna9uYnORk4cAAYMICqry9cyAEDxvRQogTw88+URly5sm8Bg7Q0OnH++mvVh8cY08GpU0D79vnXInA46Nx14EDVhsJdDzzmzQOuXaN9UFFR3v/N/nWgxWgYY4wxpYwenfvqgzdWK/Dff0CPHsDrrwNvvKHe2Bhjubv9dgrejRsHjB1LWQO51cmyWIBvvwWKFdN2jIwx9V2/Tl0hrl3TeyQAOFCQoUoVvUfAGGOMFcz+/cDKlf5nBpjNQNmyQP/+6oyLMeabqCgqVDZoEPDww9RzPvuKYlQUFSvtrVH3ASPbtIkyogIpCsmYkTgcQJcuwOnT+RfUzywqSrUh8dYDxhhjLNi99Zb3dmJ5sViAvn1pu8LNN6syLMaYn4oVo6rm3opqx8YC33+v/ZiMxmYDWrQAHnyQt02x0CAl1Q/asYMyivyhYu0ODhQwxhhjwezUKWqb5OsKhBC0Cjd5MrVeMmvc+owx5t3ChRQk+PHHnNuI4uKoE8BNN+kzNiPZupUCnX/+CUyapPdoGAvcq6/S69mf7YMeMTHKjycdBwoYY4yxYPbBB7619AUoKFCtGrBtm6oFkBhjfrh4kSqc9+lD7c5SUrLeHhEBNG5MLU4ZbctwOCiz4Nlnge3b9R5R+LLbqWbGmTN6jyR4ffMNMHEivZ4LIjZW2fFkwoECFp6uXKG+vIwxFswuXwamTPGtA4/FQrUIdu0CatRQf2yMsbxJCfzwA1C9Oq0m5naiEBsL/PQTF9H2+OefjDnPbge6daMicExbSUlUM2PECGq5q2KbvpC1cCEFuwoaJAA4UMCY4u6/n/a2McZYMJswIf89uiYTpS1/9x0FFVQ8qGCM+aFPH+CJJ6jFWW41RuLiKGuoYkVtx2ZkmzZl/f7KFQqCcr0C7Vy9CrRsSYHn1FQKGgweDAwdGthJbzjZupXmgIJsN8iMAwWMKax6dWD+fGDNGr1HwhhjBWO1UqAge5pyZmYzZQ9s386dDRgzGrs97/evyUQrtcOHazcmozt/nk5KM0tNBVatAj75RJ8xhZsLF4Bbb6WWnpkL79lswC+/ALVr83YQX3TrpkxQxWIJ/D5ywYECFp6qV6cUvkce8X1vL2OMGck33+Q9f1ks1Gptxw6a8xgzApcL+PRT4PhxvUeiv48+yrsQWUwMMGMGBQwY2bjR+3NmswFvvAGsW6f9mMLJqVNAkybAsWPet7ylpAAnTlC2wccfa3OM/e67lHEzfDjV3wkWTzyhTDHhYAwUCCEqCCGWCyH2CiH2CCGeTr/+LSHEaSHE9vRLN7XGwFiuKlYEEhJowuNWQywI8Rwb5hwO4L33vK9GmExAfDx1NJg8WdWKyIz57bPPgJdfBurW1XskedJkjq1bF7jzTu+BAIuFTny5nkhWa9cCycneb7PbgbvvpoKQTHmHDwNNmwJnzwJpaXn/rN0OvPkm0LYtZYGoaf9+4PRp4KuvgEcfVfexlPTmmxQIjIsLrP6IioGCSNXuGUgD8LyUcqsQIgHAFiHEkvTbxkspP1bxsRnLW6VK9K/VCjz/PO0RKlRI3zEx5h+eY8PZzz97T1k2m4HKlYEFC6jNGmNGcuwYMHo0pSv72ytce9rMsR9+CPz9d9b3sxD0Pn7hBUUeIqT880/eq9SJidRBYuVKzsRQ0r59wO23U20CX2tB2GyU4VGzJjB9OnDXXeqM7YMPKCCRmEjFFYNJjx5Uc+POO6n7iS+FibOLi1N+XOlUewdJKc9KKbemf50EYB+Acmo9HmN+qVQp40M5NRV46y1dh8OYv3iODWNuN600Wq1ZrzebqVDrtm0cJGDGIyUVOzN+gACAhnNsrVq0VzkiIuO62Fja6x2p5npeEHK7qXheXpxOKhL39tvajCkcbNsG3HYbFY30t2BkWhp1pLjnHgoyqKF8edpK/NxzlPEQbGrXBnbvpue4INkBwRgoyEwIURlAIwAb0q8aIYTYKYSYIoQomsv/GSaE2CyE2Hzx4kUthsnCSZEiGWk+KSmUrnT4sK5DYqygeI4NM/PmZT3g8mw1+OknqlvAWw2YEU2bRgXOXC69R+I31efYDz4AoqLoa4uFTnjq1VNq+KHj4EHfsgRsNmDcOMo+YIFZt45W6QNtP1mmDB17M++KFAGWLQMef9z/ugUJCaoMCdAgUCCEiAfwG4BnpJSJAL4CUA1AQwBnAXgtUSqlnCSlbCqlbFqyZEm1h8nCjRBAqVIZ3zudXFWYBSWeY8OMlMBrr2Xs0bVYaEVy507gvvv0HRtjuTl/HnjqqZxZMEFAkzm2Rg1acTWZgJtuoowhltOGDb7v5bbbaU48c0bdMYWyZcsoJT63mhC+io6mFf9A9uGHg4gI6twxZYrvmQVmM1C2rGpDUjVQIISIAk2u06WUvwOAlPK8lNIlpXQDmAzgVjXHwFiuMvckdrmoVSJHn1kQ4Tk2DK1YQRWlATpAGDqU0kKrVNFzVIzl7ZFH8m4DaFCazrHvvw+ULg3MnEknViynVav8O2m1WikAk1/hPZbTggX03CkR3DOZgCFDAr+fcNG/PxXtLFUqI9Mou/h4oEIF4NtvgaefVm0oanY9EAC+A7BPSvm/TNeXyfRjPQHsVmsMjOUpe7swm42qpfIHSnBzuYDOnUO+9RbPsWFq9GiaqxISqKDhF18oc1Ihpf97Txnzxdy5FIR3OvUeiV80n2OrVqXV72bNFLm7kLRqlX8/n5ZGRfheekmd8YSqmTOBvn29d9UpiKpVuW6Ovxo0APbsARo1yppdEBdHhU6/+46Kww4cmLW+icLUzChoBeB+AO2ztZD5SAixSwixE0A7AM+qOAbGclezZs431/nzwKRJ+oyHKUNKqiAd+gcGPMeGm61baZWhbl0q6HXvvcrcr8sFNGxIWxhmzOBgKVPO9evAQw8pd8KhLZ5jjSQlhU6M/GWzAV9/Dcyfr/iQQtK339J71m5X5v4sFtp3z/xXogRlOw8eTOcr1apRrZfDhymQo0FXD9XKqUop1wDwthlloVqPyZhfKlem1N3MaWxWK/DKKxSh46IrwW3ePGDvXqBOHb1HogqeY8NQ4cLA669TVoGSqck//kgHHlYrMGwY7SV/+WXgscdULZLEwkCQ1iUAeI41nO3b6ZitIJkpdjswaBDVcqlcWemRhY4JE6gGjlJBAoAC0f36KXd/4SYqiooUv/wybTHUuM4DNxhl4atiRe/pOg4HMGqU9uNhyjGZ6O/4LC/0qMLppCDM7NlUdKtrV+pZzdRVrRrwzjvKBgnsdurV7jmZS04GLl0C3nyTiqo98wxw6pRyj8fCx8qVwK+/Bk07RGZwGzYUrMe8h9UK3HUXvx5z8+67dOyrZJAAoHaFmYuHs4KpWlWXYpDcoJWFr0qVvEemU1Op4uhTT9H2BBac3G5g9Wpg40bgVq7nVyBOJ60079lDqe4bN1Kv37Nnqc+3EHTw5XbTvrk2bfQeMfPX+PHeDww9qeJffUWrGd26UTZDw4aaDo8FKbsdGDBA+ZMOFr42bQqsIKbbDRw9CowYAUyerNy4gp2UtFXzyy+V3yIUH0+ZaSxocaCAha8yZXKPLDscNLmtWKHpkJjC7HY6KPCnpVI4khLYvz9nQODMmZwBAY/slac3bdJ2zCxwly8D772X98GhZwXvjz+Av/4C6tcH3nqLCobye4rl5rXXgGvX9B4FCyUPPQTMmRPYyazdTkVg27enQFa4kxJ44gnafqZGHZG0NKBnT+Xvl2mGtx6w8BURARQt6v02t5tOfP76S9sxscBlr9y+dy+wdKk+YwkWW7cCTZoADz5I6YcLF1ILvrQ0CggkJWUNEnhz5kywFiwLX2++6XvhQreb/r4bNgB9+lAa5JQpnMbLctq6lbJQOJuAKal9ewpQ5tYuzlc2G7Xr3L9fmXEFK5eLiuSpFSQAgE6dKKuABS0OFLDwVq5c7rfZbFTYK8haOrFsrFZg5Ehu/ZYfqxVITKSDh4KwWCgbgQWHo0cLfqKfnEzVx59+muoYvPMOcOWK4kNkQWr0aN+CBBpU7GYh5quvlKnRYrdTbZ1wDW47ncB991GmmFrPQUICtRxnQY1naRbe8uvreuUK8Pnn2oyFqefUKSq8x9TjdNJKIgsOzz0XWGEwgAIG164B778PlC9PB4VHjigyPBbE3ngja9/v3BQurP5YWGgpXZrmG19eX3mRkmrtPPSQMuMKNp9/Tm2k1QyUSEkZICyocaCAhbdatfK+3Wqlg55Ll7QZT7C6csXYK/ZWK50YcX949djt1O+XGd+WLcDixQXPHskuJYX+/lOnAnXrUuHD9euVuW8WfFq0oPa0eZ3MxcUBy5ZpNyYWOoYPpxpSLVpQRlNkJL3WChem15WvUlKA+fPDs7Dhrbd67/qlFJOJtqgFuk2E6Y4DBSy8Va2af2Ta6aT+pSyrAweADz8EGjQASpQAvv5a7xHl7epV4Pvv9R5FaNuwQe8RsPx4ilepsX88LY0Ovv/6C+jQgeaGOXOUC0iw4NGhAzBzJvW9z85sBn7/HWjUSPtxseAXEQH873/AunWUFZCSAvz3HzB3LjBxIhXSvOceoE4doFAhCiQkJNDXMTFZ78tmoy1UO3bo87vopWVLoHhx9e7fYgEefli9+2ea4a4HLLxVrJh/xDM1FZgxA3j2WaBePW3GZUQuF30wz55NvbGvXqUCZ6mpVKymdGm9R0hyy2ywWoFXXgHuv58q+TPlnThB6exK7CFl6vjrLyrwqSYp6QB8505gyBA6SB81ioplBpoyzILH3XdT5sr77wP//EMneFJSULlTJ71Hx0JFRARQoQJdvLXotVqppsrRo7Q1at8+uhw9SoEGux149VUq4hsuhKBj2lGj1Nl+EBsL3Hab8vfLNMeBAhbeKlXybbUrJYX2365dG14twZKTgSVLKFCyaJH3NnkAfd+ggT5j9EdKCvDZZ9QzmCkvNpZaLPJKoTG5XJS2a7Vq95jJyXR5+WU6GF+6lNJeWXi44w66XLlCnyMJCRQ8YkwrcXG0Japu3Zy3SQlcvBiehTUfeIDmZKVFRQFDh4bncxqC+K/IwlvFir6l4EpJFd3nzVN/THo7c4ZWfO64g7YUPPAAZRDk1SbP5QKqVNF+rP6y2YAxY6i6P1Oey8UFDY1s6lQ6KNaD1UpbE7Zv1+fxmb6KFQOefJKDBMxYhABKlaJjnXBTtCjQvbvyi1+eQAELCRwoYOHNbPa+h9Ibq5X29ubWTuyJJ2i1OiVFufFpQUpKEX77baBmTarb8PzzVJguNZWCA/mpXj14osdOJ6XCMuXZbMC//+o9CuaN3U6ZNFpmE3jjLdDIGGNMe888o/x2sJtu8p69wYJSkBzZM6aiMmV8/9nr16mIjjeNG9OkW7as8QMGDgelAD/2GEXTW7YE3nuPChSmpvq/Zy2YUolTUoBPPwUuXNB7JKGJq90b0yef6D8nScmBAsYYM4qWLenEXqmsgthY4JFHlLkvZggcKGCscmXff9aTun7+fM7bHn0UmDWL0tqffZYCBp9+qv/Buce1a7RH9O67gSJFgF69qC3QpUu0yljQnuoWC9C8uZIjDVx+H3ouF/D669qMJdwcOqRsG8pPPwVOn1bu/sLRpUuURaNmz2xfGbmNKmPMWNasAe67D+jbl/bTf/UVbQHdsoW7qShBCCo4WqyYMsECKYHBgwO/H2YYHChg7Oab/fv5tDTg22+939a7NxX9i42lrgCvvaZvwODoUWDCBKBZM+pK8NhjwIIFlIacmKjMQXtkpLEKGfryOzkcwA8/UCVkpqyYGGD/fuXu76WXgM6djRNwC0ajRxvjoJozChhjvpAS6NmT5v45c6hO0gcfAM89R52L2rShAALPJ4GrVo0yAYsWDTxYUKcOdZ9gIYMDBYzVqJGzt25eIiKA/v1zv/3OO6kVVEICreBdvUotaMqWpZN2NU943G5g40aqMF65Mk3ar74KbN5MJ8e+1Bvwl80G1K+v/P2qLS2Nux+oRemChocO0cEhr0b77/BhCorlVltFSxwoYIz54uOPgb//zpkFlZJCixxWK22ffO45fcYXaqpXp2BBkSIFDxZYLLQYxUIKBwoYq1TJ90CB2Uyrc9Wq5f1zzZtTK0VPhNZqpYDB6NFUE0HJgIHdTlkC999P6WMdO1IdhePH6THUXoktUYLaDwWbtDRg/nxq58eUk5wMrFun3P0JQSe5CxcC48Ypd7/h4tlnC76tSA0cKGCM5WX9euDNN/PfKmWz0fbJCRM0GVbIq1GDPruLFQMKFfI/YOByAX36qDM2phsOFDBWsaJvP2c2U8sXX1eh69WjlfzSpSk9H6CAwbVrlGFQpgwwfrxv7Rmzu3ABmDKFggJFiwKDBgE//UTFFpOSlN0jnh8jbTvwl8NBJ1JMWWvXKn+fNhvw1lvAX38pf9+hatMmWnUzwrYDIHQzCi5dMkbGBmPB7vJlqqPk63GRzUZdmlasUHVYYaNmTaoJ9MsvdLxbtCgQH59xDJuXVq0oyMBCCgcKGKtUKe9V99hYqgq7eDHw5Ze+TZgeVatSGnaFCtRb1sNmo4DB66/TloT8AgZSAvv2UUGy+vUpuPHUU8CyZXSAmpjo+5iUFBlJVXODldtN7fy4Ur+y9u9X54TQbqcVi4MHlb/vUCMltWwtSCBSLaEWKDh9Ghg+nObwAQP0Hg1jwe+jj2jBIz/R0XQCa7EAnToB5curP7ZwERMDdOlCi1GXLwPLl1MwpnJlOh6Ojc35fywW4PHHNR8qU58fZzyMhahixXLf+2yxAAMHUmpbQdPry5ShzIK2bTPaD3p4epq//jrwzjv07xNPUPZCWhqtzM6eTZfr12ll0PP/jbCCZbEAjRrpPYrA2GzAyJFU20GpFkHhLiKC9sbXqBH4fWX/m1itlEmzaxelRzLvFi4E/vtP71FkFSqBgqNHKbtl1iz6fZxO4z3XjAWj//6j91N2QlDdp5QU4JZbMgodNmoEmHjNUzVCAE2b0uWDD2jumzuXMlivXKHP+FtuoQWsnj31Hi1TAQcKlHL+PLVtSUyk/eH+OnYMmDmTKrneeisdaDNtCAGUKpW1BVtMDJ2EzJwJtG8f+GMUK0Yn/Z07A9u25VzlyxwwePddSuFasYJeB1arcVKHs3M6jbf1oCAF7/btA5YsoZUJFjiTidpXKREoyE5K4Nw5YMgQ4I8/lL//UJCWRivdnnnFSIK5IOV//9EcvWABPceZt3hxC0/GApf5fZSQQAsi5cvTdoRu3YDbb6cFCqaPKlWAZ56hCwsLHCgIhJTAhg2UKrVoEZ3MVazof6Bg82aqlG+1UkqP200np3360IllqVLqjJ9lqFgx4wPKYgF69QI+/1zZFcv4eOqG0LMnsHKl90I9Nhtd/vxTucdVkxCh0QrHaqWtHHv38uqEEpKSaG7MqztIQQlBAbTWrZW/71Axfz5w6pTeo8gpWDMKduygVrf//EPBUW+BW6uVAsBms/bjYyxUJCTQwkqnTkCPHkCHDkDJknqPirGwxYGCgkhJAWbMoDSc06fpxM6zSpJfNfzsFiwA+vXLOGn0pFzNn0/7gpxO2hfUuzdFVJs25WwDNVSrRqnnRYpQSlWXLuo8TkwMMG8eBYK2baMK8cGsZs3QSdc/dYq2ePTtq/dIQsOaNcrcT+bXl8VCbZxmzKDWn8y7du2Azz6jz6djx+i1fe4cFd1LTKTaIjEx9Nx6tjN5S/dVWjAGCrZvpyy/tLS8syHMZuo0U6uWZkNjLOQsWULHuKFyXMFYkONAgT+OH6eDr0mT6HtvJ3n+HLx+9RUVCMmt2JTn/vfvp6yFzz6jA5WOHSlw0LkztaZjgXvgASqO88knFCxQWmoqbSWYNYvSpbU6MFdb8+Z6j0A5Viv1ZL7vPv8KVjLv9u6l+UqJA76ICDqxfe89qifBWR95K1IEePJJ77e53dSq9dy5rJcTJ+gz7vRp6qpy5QoFsGNjMwqxOp30eVXQ7QPBGChwOikIkF/B2IgICspwoICxguPPXsYMhd+R+ZGS0g0/+IBWyNzu3HtSm83AzTf7dp8vvUQV9H2tSO10ZpxY/vFHRrX7atVoi0L37kCTJnwAXVAdO9JFSVeuUEGxn3+m7JDoaErJDuY9upnFxdFKWyi5do0q/Q4bpvdIQsPx45QRFYhixWie+/FH31uZstyZTEDx4nSpWzfvn3U6KWiQOaBw9iz9XU+cAM6cAS5epPeNy0VBhYgImuMcDu/dZDKn7aemUibXmTOUWWdEpUv71m7W4aBAAWOMMRYiOFCQm6QkYOpUYNw4Wn3xJUU8KooKfeTF4aAq+osWed+j7s/4gIyWef/7H63c3XknBQ46deJ+poE4c4aCQv623ElJodoGP/8M7NlDwQHPayevFozByGQyXiFDj4IGY6xW4NVXgfvv573GgYqMpNaggQYKDh3KSJNn2oqKAsqVo0t+kpOpqG/moEL2rQ8XL9Lf8a23aNvdrl00zxYpQpk8mVvIGkWpUr7N3XY7t+1kjDEWUjhQkN3+/ZR+/tNPdCLkT9VotxuoWjX3269fp+0CO3cq29s6c7bB77/THq/UVKo43qcP1TZo2JCzDfJz/Djw66/AtGl0wGex0AGuPxV2N28GXnklY9Ust+yTUGC3G3OfeHQ0cMcdwLp1dILpCar5KiWFtvm8/LI64wsXViuwezedAAbCW89mZjzx8XTJXqfH7aatc7Nn0xw7fjwFyT2r9BYLzblaBQlcLgqs33orzRP5fS7GxtKc4kuwYO9eZcbIGGOMGYBuZ45CiC5CiP1CiENCiFf0GgcAOnCYNw+47TY6of7+ezoJ8re1lN0OVKrk/ba0NCqQ5601ntKSkugEdc8eYOxYarlYtCilds6aRRkSjBw8SM9RzZq0t/T11+nkJjWVLp995t/9tWwJ3HSTOmM1mjJljHkSZzJRPYizZ4FvvqHKyRYLVVP2pRCozQaMGUOBvSBliPk1JobaWbHwdugQZRBs2UKfS4mJGUGC6GjaNqfl68Rmo6yhbt2oxs/IkTS2vLKQfK1bc/SoIkNkxmeIOZYxxlSmS6BACBEB4AsAXQHUATBACKH90qTLRbUHypQBBg8G1q+nVQNf9iN6U6gQHRx7M3o0ZRJovcLsdFJKaGIiBQkeeYROZG+5hU6Gtm8PnT3z2UzfNR2VJ1SG6W0TKk+ojOm7pmfcOGYMZX80aAC8+y5w4AD97TOvGtlsVDzNnxVpkwl4803avx/qGjXSewR5K1YMGDCAanpcv07bfZ55hoJ5sbF5by1IS6O/fRAyxPwqBNCiBXVpYSErzznWw+WigIA3FgsV9dVSQgJ9/tlsFDT/6isKpjdtmnvWQJkyvhVZy9wDnoUsQ8yxLOT5NL8ypjK9MgpuBXBISnlESukAMBNAD81HsX078PbbtG/S3/Rkb/Lazz5lSmA1CZTiyTbYtYtOkO+4I+OE6rffgnoVNbPpu6Zj2PxhOH79OCQkjl8/jmHzh9FE63AAH39Mqz92O2UO5CYtjepU+GPIEGPutVVSVBRlTwSLyEigVSv6ux87Bvz3H31dt6731OOUFGDiRNpzHXz0n19jY+n5ZSErzzk2s8zFCzOzWCh7T49aOn36ZAQvXC7KHty3D3jwQe+B819+oWD/rbfSYkBCgvfgR0qK/5mILBjpP8eykObz/MqYyvQKFJQDcDLT96fSr9NWmTLKFsiqUcP79adPKxOIUJrDQdkG164BM2fSQVKpUrRS/P77lAERpNkGo5aNgs2ZNTBjc9owatkoOsD791/KAMmP3U41K65c8f3BY2KAF18M7WJ4ZjNt0wlWlSoBtWsDJ096vz0ujoJEwVnFXN/5VQgKQBo944QFJM85NjOXK+fnbFQUdZm59151B5mbbt1ynujb7bQF8csvc/58jRqUKbZhA32WL1kCvPMOvc7NZqrNEBtLQcfjx7X5HZiejHEMy0KWz/MrYyozbHU7IcQwIcRmIcTmixcvqvMgN92kXC97IXJvNbV6dXCsMHuyDbZvpz2lLVtSC63Bg4E5c/LvI20gJ66fyPv6unWBlStpZSg/Lpf/aejDh4d2lfbUVON2PMiPlLTafddd9Jr21tc9JYXqGXz0kfbj00iWOVapO42IoP3c/tb2YEEn3znWw1tGgdkMfPedCqPy0S23eK9XYrNRkHfdutz/b1QU0Lw5FTtdtYo+N1evpuB67960AMEYNDqOZSHJ5/mVMZXpFSg4DaBCpu/Lp193g5RykpSyqZSyacmSJdUZhcmkXNqjxZKz2rPHkiXGzCjIi8NBKZRXrwLTpwMPPACULAk0aQJ8+CEVSjRwtkHFwt77rWe5vmFDYNmy/OsJpKbSKpM/aehFigAPPZT73txgFx0dnEUb7XY6mH/zzbyLirpcFCyYO1e7sSkn3/kVyDbHKvGosbHAzTfTtqaaNZW4R2ZgPs2xQM5AgcUCTJpEhQT1IgR1IPLGbqcg4rlzvt1XRAR9ljzzDH1WFi2q1CiZcfk/x6p1HMtCks/zK2Mq0ytQsAlADSFEFSFENID+AObpMpIKFfL/GV9ERgJVqni/belSZR5DT55sg61b6SSreXMKHLz5pt4j82psh7GwRGVta2iJsmBsh7FZf7BZM+Dvv/MPFrhc/v+uL78cui0pa9fWewT+O36cDugXLvS9Xkhu+6uNTfv51WIB7ryT2oOW4wzccODzHJt560FUFKXr9+2r0SjzcN99uWeUJSXR9oRQbm/LAmGcY1gWknyeXxlTmS5nMVLKNAAjACwGsA/ALCnlHj3GgurVlbkfh4Oq6Gd35YrvKxPBIjWVsg2Sk6kFnQENqj8Ik+6ehEqFK0FAoFLhSph09yQMqj8o5w+3bAn8+WfeNQUcDur1nduedm/Kl6c9uKGYVXDbbXqPwD///EPpxocO+dYPPYhpPr+azcALL1D2hcWS/8+zkODzHJs52BYbC0ydaoxtWR075l7INi2NCp6OGKHtmFhQMNQxLAtJfh3DMqYiIQ2cPu7RtGlTuXnzZnXu/K23qChRoM9DZCQddGRfQZ4/n/b4B9H+fp+YzcDYsZRuaYSDPiXUqUOVr3MTFQX07w/88IPv93n9Op2gnjxp6K0afomPp5ZigwfrPZL8eeoR5LfVIA8C2CKlDOk+f02FkAWaYS0Wej/06qX0kFioWLUKuPtuChh8+SV1hTGK2rUpIJAbs5m2DrZqFfhjpaQAP/5IAfa0NLrPYOocoxIhRMjPr4DKx7GMMZaLQOdYHxoDh7gqVehgN9CWRiVKeE8zX7o0+OoT5MVkohPF338HOnTQezTKio/P+3anE/j1VzrpzK0eRXaFC9NqduPGoRMskhK4/Xa9R5E/mw24/37gr78KHCRguYiMpL3Yf/8dWPeL48epYGp+7z0WvFwumvvatqX3o5H06kU1d9LScv8ZpWqxPPwwFQV2uaiAamwscPBgcNZ6YYwxFhZCdAO1HypVooPeQFWu7P36v/8OnZXkmBigYkVg27bQCxIAwD335N/S0OkEXnrJv/utVo3SskOhXWJcHLB4ce6vd6M4fpza8/lTj4D5xmymriG7dgUWJNi1i4oftm7Nf6NQFhNDAdOffjJe9ln37nnPywkJvgeF87N1KwUsHQ4KTKSmAsOGKXPfjDHGmAo4UFC5sjItEr1V+bZagcOHA79vI7BYgDZtgJ07vddiCAUvvQQ0bUoHtnFx3g8gXS46+dy717/7btsW+OST4N7DnZAArFihTBqumsKoHoHmLBZKI9+wAShdOrD7+v57Omnat4/uU6lWtcxYWrYELl40ZpHLZs3yLljapYtyj5W9PZ7TSe8jxhhjzKA4UFChAq1qxcQU/D4iI71Xgd+wITRWkc1m4KmngEWLcq8SHQqioykDZPx4YPdu4PPPvf/9HA7g+ef9v/8nnqB9/cEYLChcGFizhgIpRiUl8NFHtEqYmEjpvcw3kZHU5i0ujv7W3l6jZjMwejQwc2Zg86WHJ9MqJYX61g8axH+zUBUVpfcIvIuIANq1835bQgLQo4dyj5WcnPN56N5duftnjDHGFMY1CiIiqNhS27bAnj25V0HOi9nsfZV9+fLAax/ozWKhav+9e+s9Em3ExtIJPQA89BC9Hl54IWtqtNsNrFxJqaSNG/t3/198QdkIGzcGR+stIWgv+r//ArVq6T2a3NlsFIRZvJjrERREgwbA+vXAqVPAkSN0OXCA5sTDh6ko5+TJyp7YZN7yZbdT55GnngImTjReijoLXb16UaZU9s/q1FSgfXvlHmfpUnqP/fcfZdGcOwc89phy988YAy5fBooV488QxhTCgQKAVg5WraKDgp07/U9XFsJ7oGDRomDtw04rH0WLUsXnW27RezT6eeIJej2MHp01WJCSQh0fVq3y7/4iI+mEaMIEYMECYMcOCk7Y7cZLvTaZqEjn2rXK7dNVg5RAixZUGIy3GhRcZCRtxapcWdkTpNwUL05B1pQU+hvabLQdoXRp4PXX1X98xgCgc2fvxQyrVQOKFFHucW6/PTiKwDIWrKZOpQWeOXOUzQZiLIzx1gOPuDjKAGjc2P/tAikp1D0hM4eDinUFI4uFipTt2RPeQQKPZ5+lQEHmdGwpgS1baKXdX4UKAW+8QVkFSUlU82D0aNovGx1Nt+udqhsZCZQpA2zebOwgAUCrc0eOcJAg2Dz/PB3QPfooUKoUvb+cTnpv5FWFnjEllS1Lc11mkZFAz576jIcx5r+vvgKGD6djs59+0ns0jIUMDhRkZrEAy5bRCZs/wQKTiVbfM9u6VZl9vFqzWIABA+gEuEQJvUdjHK++SlsQMgcLbDbKKgikq0V0NBUHzBw4WLSIVlRvvVWfwEFUFBUe27SJanj4Yu9eYNIkfTJo/v47eDN3wllUFK3mfvMNpWFv3gy8/z6lgSvRiYYxX917b9b2xhYL0K2bbsNhjPlh/HgKPHu2HS5caLwMTcaCFAcKsouNpROP227zPVhw000590OtWlWwegd6MpupMv+33+q/om1Eb79NEevMwYJ9+yi4pJToaKoS/vrrVAxTy8BBZCS9/jt2pCBB9lW2vHz0ET03derQ/9XSnDmcTRDshKCCsM8/T91VGNPSPfcA8fEZ3zscNN8yxoztvfcoIzNzbaLISAo4M8YCxoECb2Ji6ORs6FA6eTabaWtCQgKdpBUunHExm4Hq1XPex8KFwVGsDqCCjoULU4Dk8cf1Ho2xffQR7YHzBAus1sCzCvKSW+DgjTeUCxzExtLl/vtpu8zChUDJkv7dx65dtKp/4ACd6D38MHDtWsHH5CunkzIxGGO5S0sDfvlF71EYV6tWWT+vb7uNg+WMGd0bbwBjx2atHwXQcdKMGfqMibEQI6RaJzgKatq0qdy8ebM+D56SQic8KSkUsUxJyfq13Q40bw6UL5/xf9xuCipkn7yMKDYWqFiRihZWrKj3aIKDlLSvesYM+hvHxdHXd9+t/VgcDkrZ/ucfYP58YPt234sjWiyUbjtyJNVh8Dc4kFmxYsDVqxnfx8TQOCZOpG4EalUgXrMGuOsuaoeoEgFskVIauC9k4HSdY9Vy5Qpl+1y/Tu8FzyUtjYo1Nmum9wi1s3AhvU9atKDipFwRPKd27WgV0mwGxo0DnnxS7xGFBSFEyM+vQIjOsXqREnjpJeDLL3M/zi5cmD4DTLweqojr14FDh+iyfz8Vfj94kD5T3nmHihAzQwp0juWNoPmJjaWtBf7Ysyc4JieLBejQgfqie+ubzrwTgvbjp6YCv/+ekVVw113a/909GQctW1L6nS+Bg/h4+nuPGkUr/3FxgY3BaqUIfmapqRQwGzoU6NOHxqCG/fu58B3LcO0aFbL64Qc6kImOpkwXt5sOLl0u+jc6mlriTpgA3HyzzoPWQLdutEWnZ0+ao65eVbaifyjo3ZuytgCgUyd9x8KYUSUn0zGDXsFGKWlx4/vv816Mc7upHWnLltqNLZS43cCHH9Ln6YkTdExnNtPzb7XS7QC1e/3xR9o2+PLLWbdwsZAQBGezQWjVKuMXVzOb6U09dy4HCQrCZKJWPN260fN37hwwa5beo8oIHIwe7X2rQv36VIPi9GnqWR9okACgqLKnnofJRPdZsSKlBJ4+rV6QAKAWSJ4PLMaGDgVefJHqZKSm0uvfZqPsr9RUCiq5XBQ4W7yYurs88ABw9qzeI1ffvfdSTRWAiu9u26brcAwhc9ZV1670uoiL876dkLFwlZxMwdeWLWml/r779KnB5XYDjzySf5AAoJPZmTO1GVeouXSJAuljxlCh6uRkmisTE+kzNfMxl8NB8+Ynn1Dx6z/+0GvUTCUcKFDDX39lLaxiJELQgdAvv9DJI6egFlxEBG05aN+e/t4vvmi81e3sgYOdO4F+/ZStKn/oEH0ox8XRSdfy5cCxY/R8+JuN468SJagQWTBk8DB1XbtGJ/++FrZ0u+l9O2MGtQB96SVKrwxltWoB58/T140bU+puuJo+neYsz/NRtSr9W706fy4y5nTSlqUePWhb4pNPAuvW0by5eDHVItJyvnS5gCFD6OTfl229bjcd5wbB9mrD6dWL/tb+bJ+22+k4cMEC9cbFdMFH10qTkvZNG1F0NPWM3rRJn/30oSgykrYf3HkncOoURd3DzT33APPmURR6yhTa+63lgfZLL6mbtcCCw88/Fyxg5HTSQc7EibQi8vHHwdexxh+lStGqULlydPDfo0dw1NNR0rZtwLBhFOzNvG983TparWQsHElJCwqPPgoULw7070+f7SkptKrsYbfTtsYmTYAzZ9QfV1oaLXDMmePfXGW10uII8090dMEWvRIS6POThRQOFCjt6FFjHmRaLHQCt2sXtSFjyomKog/TNm0y6gSEk+hoqs+g18l6kyZA5cr6PDYzjokTAzvhTUmhE+g336SAwW+/KTc2o4mPp8+qu+6iuatatZx1RkLVxYtA5870WnE6M+oSAFSYq1Yt/cbGmB6Sk+nYpUwZao88ZQrNB3nNCamplDnYsCGlp6vF6aRtUwsX+j+/u930fmf+qVnT//9jsVA9A659E3I4UKC01atplcJILBZq6bdiBe1NZcqLiaEtJ88+y6luenjlFS6iE8727gWOH1fmvmw2Orh8+GFl7s+ooqKo4Onzz9PXRts2pQank+rKeFq3uly0VYqxcCUlFfIcN4624SQn+173x+WiubJFC3UyaVNTKZj5zz/+b+c1myl43LGj8uMKdTffTMe0voqNpe0KXbuqNyamGw4UKG3x4qwpWnozm4EvvqAJU8l96Syn2Fjal+/PBMuU0bcv1ykIZ998k387UH+FQ2aQEJQqeuJEeASRhw+nrkSe14rZHB5dLxjLzZgxtMAVyHyXlESdQmbPVm5cdjtt6Vyzxv8ggcVCxaVDPdirlsqV/TuOTUig8wwWkvjIWmmHDuk9AhIZSQd+K1ZQJXDGQllMDPDYY7QNgoUXpxOYNk35FXGlAw9MX9evU8cXz9/VYqFOMF9/re+4GNPLkiXA++8rU6PEbqdigxMmBH5fVivQrh3V0/I3SFCoELBsGdC9e+DjCFeVKvmeGWuxUIHJhAR1x8R0w0vMSmveHNiyRd+WbWYz7TldvJiKFzIWDkaOBD77TO9RMK399Zc6821aGh0scQX80FC4MPVVX7WKUqxr1KAuLVFReo+MMe2dPElbDpTs0GW3A6NG0TawTz4pWJZfYiK15tu71796XxERQLFiwMqVXIcrUJUq+dY9KDYWGDCAOn+xkMWBAqX17UurW3oVhrJYKJI6bRpXgmfhpUIFKij59996j4RpaeJEdebbiAg6UOV5NHQ0b04XxsLdO+/Qyr3SbDZg0iTazjRjhn9ZflevAnfcQZm5/gQJPB29Vq8Gypf3f8wsqyJFKCs5v6y6IkWATz/VYkRMR7z1QGmtWulfC2DUKD64ZeGJixqGl4sXaYVYDRERvq2qMMZYMLHbqZ2sy6XO/dtswKJFlBmQmOjb/7l0iYoiHjzoX5AgNhaoWxfYupWDBEq66aa8bzebqQ5EXJw242G64UCB0kwmSsXRq/OB00kfAIyFo7ZtKf2QhYcff1SviCUHChhjoWj2bPWL/9rttA23aVPg7Nm8f/b8eaoXcvSof0UVLRagdWvg33/DoxirlipVyv02sxl48EHK/mAhjwMFaqheXb99j04nHTxziz4WjoSgzhMc5Q59UgKff67sHtvMIiLUu2/GGNPL119r053L4aCT/4YNgf/+8/4zp09TMOHkSf8KyFos1JLvzz/pxJUpq1at3G8rXpy65bCwwIECNSxYoO9K1PXrwM6d+j0+Y3p64AF9i4mGouRkKgS3Y4feI8mwbRutRKlFCM4oYIyFnsuXtXustDTgwgWqH5Td8eNAs2aUceBP1xqLBXjqKarFpfdW31BVs6b3+hJmM/DrrxycCSMcKFCay0UH1HpKTQV++knfMTCml4QEYPBgPoAoCKeT+szPnEn1Htq1A0qVouf0ttuM1VXiq6/828vqLw4UhKbjx4EjR/QeBWP60WNrbJEiWb8/fJi2G5w/71+tBLMZ+PBDauvIHWnUU6lSzlpnZjPw+ONUS4KFDT6SVtqOHerv/cpPWhptP/joI55IWXh67jl6D/izShHODh0CqlQBTp2igwMhKItASjqotFiouvHDD+s9UpKaShW11SrGBdBzwFsPQsP+/bQK9sMPlOIMAFWrAsOHA/36ASVK6Ds+xrSkdaBACKBTp4zv9+8HWrakLgf+bJO1WICpU4E+fRQfIsumcuWc15UuTQEaFlY4o0Bp//zj3z4rtSQnU2ouY+GoVi2gQQO9RxE8rl8Hjh2jwEpyMrUblJIOzNq1o0rUjzxinMDjvHnaBGQ5oyA4SUlB+1GjaGWsUSNgzBh6Haek0GXvXuCll6hSevv2FEjgwBALB1oHChISgA4d6Ovdu2lF2t8gQXw8sHAhBwm0Urly1s8/s5mKYMbE6DYkpg9VjrSEEOOEEP8JIXYKIeYIIYqkX19ZCGEXQmxPv3ytxuPrav58ddNhfcXbD1i4e/XVkG2VqPocGxUFFCoEfPcd8Pff1KPaSD77jIIZauNAQfCQEtiwAXj2WaBMGWpVPG4c9XO3271/LttsdP3y5ZQtU6IEMGgQsGIF1zkJcyF9HKt11mtKCnD77bR41aoVcO2a70ECk4k6GqxZ473OAVNHkSIZCwMWC/D000CTJroOielDrdliCYB6UspbABwA8Gqm2w5LKRumXx5X6fH1kZYGbNyo9yhIWhowfTp3P2Dhq3v3nHvsQod6c6zFAnTrRtsR+vc3ThaBx+nTwKZN6j+OlLzCbHQuF7BqFfDYY3SS37EjMHEi7Xu2Wv3L7ktKosDBjBnAPfdQbY4XXqCaHSwche5xrNYZBaVKUV2Q1q2BxETf/19UFAWpt27lDEGtCQHcdBN9Xa4c8Pbb+o6H6UaVQIGU8m8ppWdz8HoA5dV4HMVcuUL91wsXDqxlzLZt+rVF9MZmoz62jIWjiAg6gQjB6ryqzLExMbRy8/PPwB9/ACVLBnyXqpg6VZvHcbs5o8CInE7KchkyhF6v3bsD335Ln+PJyYHXrZCSggaXL1PmSrNmQI0a1A4sv37wLGQE3XGsP7QOFBQuTNt7/Dm+jo0Fbr6ZggTe9ssz9VWqRBkds2d774DAwoIW+UcPAViU6fsqQohtQoiVQog7NHj8/H3yCfDvv3RguHJlwe9n2TJjbDvwsNt5+wELT1Yr8PLLwP/+Z4yaIeoKfI41magn9ZEjQI8eqgxSEVICX36pzTzLgQJjWbaM9icXKQL07k2fbUlJdFFrm4DTSZ+jhw4Bb7xBBT9btqSiiFr0oWdGYfzjWH9omWkXHw8cOECfyb4ymylAt369cQPW4eDhh6mI8S236D0SpqMCdz0QQiwFcJOXm0ZJKeem/8woAGkApqffdhZARSnlZSFEEwB/CCHqSilz5CIJIYYBGAYAFStWLOgwfVOyJGUC2GzAn38Cd91VsPuZPx9wOJQdWyBcLtp+MH688dKHGVODlNTab+RIej8Hceq4pnNsqVI0Vxjd2rVUeFELHCgwBikp7XXcOHpP68Uzl6xbB+zaRdlKXbvSvx06cDvWIBRSx7H+ePpp2iarxfvJ4fAvWG+x0PtqxgxjZegGO6cT+O8/YPt2+rsPG5b/ecGQIZoMjRlbgT/ZpJQd87pdCDEUQHcAHaSkjfJSylQAqelfbxFCHAZwM4DNXu5/EoBJANC0aVN1N9o/+SSlOO3cWfBiKU6nMdP8U1JoP++tt+o9EsbUtX078NBD/q9eGFRIzbFK+fJL7U4W09KMH2jasgUYO5b26TdoQC3IbrsNaNqUDriDndMJPPggMGeOvkGC7DzZBHPmAEuX0gH3oEHUGaRRIw7MB4mwnWN79KBjwtWr1W0xC/i3eGax0Cr2hAn6txkPZomJdD6zbRsFNjdupKKusbEUeHW5gOLFKTOLsXyoEgIXQnQB8BKANlJKW6brSwK4IqV0CSGqAqgB4IgaY/BLVBQV7+rWreD3sXkz7fE10tYDgA6ufvyRAwUsdF26BDz/fFi1Nwu6OVYpcXF0MKlFIMjlMmZGgctF2Wtvv01BMbudDv7++Ycqg8fG0nUVK1LtnbZtKXhQtWpwncAmJlJ235Ytxn5fe7pvTJpEWxKKFaPVuvvvpz2+LCiF9BwrBHW0qVfPOO8tsxl4801qWcoKbuhQqjNkNlOQJvNnWObMjieeoHOeUAgoM1WpFbL7HEACgCXZ2se0BrBTCLEdwGwAj0spr6g0Bm0tW2acCTczt5tSuLjVEws1aWm08lC5Mm03MOL7Tz3hN8cCwDffAJMnU+tGtdNSpTTWKnZSEr3ey5Wjk1BPCmnmzjYOB51gO53A4cN0MvDEE7THtHBhChqMHUvtAI28x/70aWrFtWlT8LyvXS4KYJ08CYwZA9SqRdkFkydTOzgWbEJ7jq1alQLsRij2azbT3M5BgsDMm0cLJk4nfQ7kFei2WrmTAfOJkEHQPq9p06Zy8+YcWV3G0ry5cVojZhcfT1Wib7tN75EwpoxlyyjN9+JF1VeXBbBFStlU1QfRWVDMsZldvEgpqsuWqXsyP2IEtdvT0/HjVHF/yhT6PtDfNyqKDsztdqB8eWpZ1q4dfT7UqKF/1sGuXVQh/epV9dOitRAXR0HNtm0paNO1K1cQz0QIEfLzK2DQOTYlhQIGenbzsFiA334DunTRbwyh4OpVoFo1+tdXZjNtUaheXb1xMd0FOsfyJiAlpKbS6o5R2e20/YCxYHf0KB1Q3HMPcOxYSNQiYAVQsiStnvz4I1XBV+vES8/X1/r11PqvVi1abbPZlAmKeFabnE56P02bRgGRxo2BhATg9tuBd96hvff+9DxXwpIlFLC4dCk0ggQAvYZSU4HFiykTpFgxqqWydm3WbBDGtBYbSwHIQNPPY2Jo7vCHEJTltGIFBwmU8Oij/n9epabSNinG8sCBAiVs3Khtuxl/uVyUms3bD1iw8rQ7rFuXTmCMlBLO9HPffZRif++9yu61NJtpe0PPnsrdpy/S0oBZs2jvcIcOwMKFtOqndovP5GR6j1mt1Cr43XepXWaJErTP/v77qR6CmqZMoSJroRz8S0qi32/aNKBzZ6BMGWDUKODgQb1HxsJVly4UHMyva0d0NM2J8fFARARQqhTQogVl9tWoQXOXryIjKUjWqxd9nr/3Hm2JGjOG5p61awP7nYxizRoqkO7PKn9BzJ0LLFrkf9c1txvYsIFq3jCWC+7no4RgOHFJS6Pqp61a6T2S0DJ/Pq0UHT4MlC5NVdm5OIxyQqjdIVNJsWLAL7/QSfWQIXTSW9CismYzHcS++irw1FOUNq6F69cpa2DcOAoM6F0/IC0tI5vgxAkqjlWzJjB6tPKPJSXd74QJ4fP+drvpb5ycTNtKxo+nWitPPAH078+945lvpkyhOh5uN9CnD9AxzyYOuZs+nTqm7N+fcRJvs1G2VuXKFLisX5+6g9WoQdsVPFlcb78NHDni33vX5aJgw7RpGVk1mf/98EMKWDZoULDfxwjWrqUgjM0GzJ5NK/5quHKFChgW9BzE0yrx6FFjL3gy/UgpDX9p0qSJ1MWaNVL26SPlyZN5/1yjRlLS9Gbci8kk5bBh2jxv4cDtlvKdd6Q0mzOe49hYKevUkfLsWb1HFxq2baP3Vlycru8dAJulAeZBNS+6zbFKu35dyiFDsr4vfbmYzVImJEg5ZoyUSUnajffwYZqXzWb/x6zlpVAhKX//XfnfPzVVyn79pLRY9P8djXCxWKSMiZGyTRspZ86U0mZT/jk3mHCYX6VUaY599VU6tgPodfPee3RsUhApKVJ+952Uc+ZIuXu3lHZ73j/vdkv5yivqvXdLlJDyzJmC/S56W78+63HLrbeq91g9e0oZHR34vPPmm+qNkekq0DlW98nTl4vmB7FHj0rZrRu9eSIjpXzqqdx/1m4P/E2q1aVwYSldLq2exdDlctHBvbcPyMhIKUuVog9aVjAXLxbsZE+lSzgcyIZMoMBj2TIpS5em4F1ef1+zWcr4eCnffVe7AIHbLeWqVVLeeSeNLypK99d4vpf4eCn/+0/Z5+HaNSlvu80w73PDXRIS6Lnp10/Kf/4J2c/ucJhfpVRxjt27V8o77sgIGNx7r5RWqzqP5eF2S/n00+oG+CIjaeFF7d9FaRs30nyZ+XepVEmdx5ozR7m/gcUi5fHj6oyT6SrQOZZrFHjz9NOUxmqzUQrmjBm5/+y6dcGTruN2054pVnCpqbQv+qefvKd6paUBFy5QF4wlS7QfXzDztDusUiUc2x0yJbVvDxw6RFsRvLX/Mptpr+0rrwBnzlDqe3y8umNyOmneqFWLKt8vWaJN/QElpKRQRW2lnDxJxRO3bOH3eW6Skui5mTWLajeULAk8+yywe7feI2NGUrs2sGoVbYMsVw744w9qy3n8uDqPJyXw+OPU9lPNLbdpabSloU+f4KqvNXRo1q1jFgswfLjyj3P5MvDgg8r9DRwO2vrEWDYcKPBm+nQ6cLRYqJrrCy/k/rNLlhi/PoGH1Qr88IPeowheSUnURuzvv/P/m1utdHA3aZI2Ywt2y5bR3sfRo+lD1t+iPIxlFx9P+/7//psOoM1musTFUb/u06eBN97wv1q3v65coUJdpUvTgdiBA8FXsK9cufyLnflq+3agYUM6keH3ef6kpM+eK1eAL76gIHS1asBHH1GQizEA6NaNTqw/+ogCcfXrAytXKvsYbjednOa2UKK0lBTqivDyy+o/llJmzqTgTUwMFYKdO5c+b5T2yCPK/g3S0ui5XrZMuftkIUFQVoKx/Z+9+w5vqnrjAP493Ulb9l6CDJEhqyKgIIooqIjIEFDBiQOcuPf8qbgXCu69cYKiOHAyRdl77z3apDPn98e3paVN24x7c+9N3s/z5KGkaXKaJif3vuc972tZ/9mdO3mQOWIEC6/406ED+5A6RZUqPOAo7/cR/u3Yweq169cHVyjN7ebJwYQJQJzE5cpYt47Pz++/2zbgpoCo7/Ntyx7fRvJ62fIvKQm46Sa25TLbypXAY48xI00pZ6+cn3kmMHVq+Pfz/ffAkCHOC5TYkcvFE7eOHTmHnneeMUGvnTv5eo1QQcVwe3w7RUTn2F27uMD10UcspDdgQPj3WVAAjBwJfPtt5D+r3W7grbeYXeAEPh+DNUYGWEuaMoWdaMz4OzRpwmy8xETj71tYItw5Vs5cKlKnDnDhheWfVHs8wPLlkR1TuLTmSZmTaA3s3w8sXcoMjrffZjudK64A+vZl9LZmTX4YHjhg/OOvWcNUvjVrgq+m7vEAL7/M7AInnygYTdodikhyuYBHH2WFbjODBFoDP//MzKMOHZjBlZ3t7Pd+fDxw/PHh38/kyTyZlSCBMbxefh7Nng2MG8csg82bg7+f7GyuIt50E++jcWNWtZ8yxfgxi8ioXZvHSXPnAt27h39/eXlsZWhFkADgY775ZuQfN1RxccwmMCNIsHs3cOml5v0d9uxhFxYhCkl7xHCsXu28lfnMTB689u5t9Uj8Kyjgwfw//zAiu2MHMyCUYipXXBxv4/Xy35J+/JFBg2nTuMpihH/+YT/zAwd4EhAKj4cnw9268d9Ybn2ltbQ7FNEnJ4ctBB9+mHNWNJ0Mp6YyjTlUWrMWxIsvyvvdLJmZfG5Hj648dVhrYMkStvX9/HN+xiUn8z6K9oLn5nLFsn59Y040hTWOOy78+8jNBc45h3UQrHz/zp9v3WPbyWWXmft3yMriMXjR+1/EPAkUhKN9exZkmjWr7EmrXWnNVLTJk82JdoZrzhzgqaf8R0sr28+akwNs2wb06MGI6JgxDDCEasYM4NxzjTnoz84Gli3jKuMvv7Aneaz5919Gwp24R1sIf3bt4gnwc8/xM6BkEato4fMBbdqE9rO5uUxX/u47yRoyW6Cvv3PP5Webz8fPJcB/plxeHvcsS6AgdmVns/Dq7NnWB/n27+eiUY0akX/sTZtYVHTPHqBXLy76VKsW+XF8/jnfu2bXdsnL42LOZ5+Z+zjCEWTrQTiUYlGX5GSrRxK8336zegT+ffll+JOg18s0yvPPD/2E9MMPGUU38oQ2Lw/Yvp1pvEYXGbKz3bu50tWjB7BggQQJhPMtXcoVlyZNWH/kwIHoDBIAPFlo0SL4n9u/H+jZs7iDkDBfINtqtm3j36MoSFCevDxuoxGxyeNh9xg7BAkAbh+LdFZBdjbnsKJCyxMm8LiyTh1uLRg9mhm6a9aEnnEajAkTIjOX5uUxuCtd0gQkUBCerCzuk/d4nFWoLjOT+9fs6LPPWH01XB4P2wW1awesWBHczz7zjHnpXUUVrPv3t+/fwCjS7lBEm3/+AU48EcjIYDAxO7vyEy6nq18/+MJWGzZw+9e//8r7PpKqVKn8NsGsyP7zT+hjEc516BBXzhcssM/7NyuLGaeRdPPNDE7k5HCeLygADh7kifTGjQwSjB3L7OLRo83PLI7koqTHww4XTsmWtsoff3CrxrJlVo/ENA46u7URn6+47/aMGXyRtGkTXpp7JGnNQkVGnJAbacsWXoySnc0D1q5dA1vt05ofDHffbf6Ho9fL3rp33hmZSHSkSbtDEW20BoYNA/76y3+NlGjVtm1wt//nHxZ/3bRJ3veRVr165bcJpjNCVhYzEETsOHAAOOkkYPFiewVBi9r3RcrPPwNvvFH5sWBRfZDPP2dXBjM/F1JTzbtvf7ZtAyZOjOxjOsXevaz1dsYZbH/cpQsXJidPZjApikigIFhffMECho88wir7Xi97cX/0EZCSYvXoApeTw1Z/djJ1qvHFIbXmB0xlFXPz84ELLmCHgkilyXo83Ns8dGjw3RTsat06oF8/bttYv162GYjo8c8/sXfSFBcXfMeDfv2AffuKC+OJyCmdLVBQwPbNL7/MqvX16gW37zg5mZXzRWzYu5f775cvt+cxyeLFkXmc/fu5xSCYBSOPhwVCH3nEtGEhLc28+/YnK4uLWbt3R/Zx7W7nThYK/ftv/t3z8vhaWbKE257r1uWiwm+/RcVCoAQKArVkCTMGzjuPVet37QK+/ro4ONC2LV8gbre146yMUoxKvvVWaPtOzfTxx+acpHs8wOOPl3/g6vEwKvjVV5HfS+vxcA/viSfyQ9qppN2hiHYvvmivFbZICLbjQUEBC36JyIuL4+XHH4F77gFOOIEnFieeyEy5KVPYkSMYmZnMoBHRb+dOZl+uWRN4JlCku35lhNwKPjiXX87tF8HyeBgoCOVnA9GgQeS3Oefl8dxGFJs4kcETf++TrCweJ3z2GXDWWfybPfSQfbbwhEACBZXZtw+oVYspJQCwaBEn1Fq1yt723ntZ5MSuXC6gVSvuGx050urRHCknB/jzT/Pu/8AB4Icfyl6/dy+rOv/1l3Unt14vV32OO44tN51Ea+7VPuoo4IUXYislW8SOrCwGMmNtlVzr4Doe7N4NJCWZNx5Rvrg44MkngSFDgEcf5X7u7Gye7If62ebzMci+dauxYxX2sm0bM4c2bOCJYWVcLi6aRTIVvkoVdrIy2yefsJBfqBkVTZua97xcfHHkM5dzcnjSO29eZB/Xrnw+4KWXKn99aM25d/t2tk3+++/IjM8EEigoT34+06dr1OAKyZdf8g9fFDDwJymJJ00uV8SGGTC3m1W6//vPfpkEALsAmFmoJTMT+N//jrxu0ybupV22zPqVwrw8Hox16WJuwMRI//7L8V5xBd8jDo6YClGhTz+N/OqZHWRns9ZIoHbuDL7woTBGfj4vBw8aG6xNTgaaN2dbxUgXkxPm27SJQYKtWwOrW+Vyce/+W2/xhDhStbkKCpj5aaZt25hNEGpgLTWV23zMWvXv1InvxUjzehmkiLVAuT8//hh8ECkpiXU/HEoCBf489hgPdr75BrjvPr45Bg4M7Ge7dWP1U7vUK4iPZ/rhe+8BkybZt5Xj55+bl65VZO5cYOVKfr1kCSfdLVsCi6BHgtY8yOvblwEnu5J2hyLWPPNM9LY/rEjdusFlCOzc6awOQKJyRRXfv/4aOOUUbi/74AMpVBkN1q1jOv/27YEFCVJTeVw8fDiLYs6cGVxxzFAVbfs1O1vpiitCX/BQCujcmS0lzXT77ZGvVQCw5tQ770T+ce3m6aeDO1eJi2O9Cwdn2skneknff883+x13MHKZlwfcf3/wEdMnnwysTZHZ3G6mjS5eDAwaZPVoyqd1ccaGmfLzgSee4NdXXslVcDumyXu9bM/4wAP2KoQi7Q5FLFq2DFi1yupRWCOYbQcA98DLqlN00porrUuX8vOzbl0eH+3aZfXIRChWrmQmwe7dlR8HKQVUqwb8/jvQp0/x9Q0bskCm2dlWaWk8JjLbUUcBCQmh/WxKClPSzTZkiDXZbVo7+mTXEHv2AL/8EtzPuFyR2TJjIgkUANwXrhR726en88Xw/fehTxipqVzBt7KwocvF6Oj8+Zz87GzFisis1uXn8+8KsDhLpFvNBMPrBSZMYCcGO2Q8SLtDEasmTrTHezDSlAq+48HOnfasli6MlZnJyvCPPw40acLuPcI5li5l9uvevZUH9hISgPr1eSzZqVPx9Vozs2DjRvMXXBISgJ49zX0MgNtTQ8kGTkzk1pxgCr+GKikJuPrqyGYHu908n7BbbbNIS00NPphUvXrwn6M2I4GCrKziPZiLFjH1u3SLoVD07Qu8/nrkgwUJCcxm+Owzrv46Yb/oN99EZmXf5eIECzDDon37yO2vC4XHw0yLXr14UGYFaXcoYlluLvD224Gl5UabtDQWWA3G1q0SRIwl2dm83Hknu97YKQNO+Pfff9w2uG9f5X+v5GTWtFqwADj66CO/d999XEAwu75TfDxw4YWR2dJUtSrw/PPBLyIlJBRnq0bCuHGRO3ZNSeEx6NNPR+bx7CwlhS0Pa9YM7PlPTmb2lZ3PMwIggYLUVJ4AVVaoMBTDh3NffKNGkTlhd7uBDh0YLT7zTPMfzygffRSZVai4OE6wAN+4b7xhn1oS5fF62b+9Y0d2bogUaXcoBFumxrJgtx5s3GjOOIS9eTxsHzpqVGwG1Zzkww8D2zbocrFY8Zw5Zbt5ffopt9j6Oy4w+qQoORm45BJj77MiF14ItG4d+O+RksLjyoYNzR1XSQ0bAr17h571HKiEBG41/fxzqT1TpH594I8/GFSqjFKs5+Vw8pcHzE3Nb9OGaSdmf3i6XMB11wGzZkV2wgrXgQOsoWC25GTgqquOrB1x7LH8ALJ7sCA3l8WG9u0z/7Gk3aEQxZ55xvwiq3bl8bCdbjCkjV7s8niAKVO4hVPq19jXo48CU6cCJ57I40Z/+93dbmYS/vJL2WKFCxawAn55f2Olwu/8pRQfNz2dj9WxY3j3F+xjv/VW4MeFSUnckhlpr7/OOlZ9+jC9PSWFx7dGBmqqVWPWiJXbqO2oRQs+L5VlnrRvDzRuHJkxmUgCBWbbuZM9Wc1MyXO7eVL36KPmRxiN9uOPkdlrpRRwyy1lr//f/+zbCaKkatXYn9dM0u5QiGLr1/OgOFbVrRv83LhjhzljEc7g8XC17cQTIxPYFsFTCjjtNP6d5swBhg7lSWbRe93t5sn5Z5+VLV63fTtw+unlZximpLBnfIcOwc8dcXEMDFSpwsf/8kvWUHjppcinbrdrB1x6aeXBgtRU4KGHrCle3qABt/zMmMHnafVqbpMbP56dLFJSOL5QOySkpvJkuH59Y8cdLTp3ZsZheUGxtDRg7NjIjskkEigw2yuvmHv/bjdTWyJRERYArrmGaWdG+fRT81fsEhKAESN44Fta1arAU0/Zu7AhwFUas0i7QyHKmjw5tiv4H3ts8D+zZ4/x4xDOkp3NLMFHH7V6JKIy7doxg3DdOmakVq8O3HUXt5GUTjXPzmaQoLJ6SRdcwKLRjRpVXp0/Lo4nVNWqAZdfDnz7LU9633iDbQatXPj63/8qz4yoWrW47pXVGjZkQcUnnuCW56wsYN48Blouu4zZYYmJDGpUFgBxuYCPPw6+Rk2s6dOH2Sf+Xif5+cDgwREfkhkkUGCm/HwWRjGr2EtSElOynn/enPv35/vvedI9bFj4e+Z9vuIuBGZKSKg4NeySS+zdGaJKFWDAAOPvV9odCuFfQQEwaVLsFuYLpeOB1iwGLEReHvDDD1aPQgSqXj12Wdq7l6vUpVfwtQYuuoir1hVto23alF0wqlYFZs5k4KG0+HgGB2rUYKG3779ngHHSJBbNs6L1nz9VqjBgUt4iUmoqu33YtWB4XBxrLYwaBbz2GruLHTrELN7HH2dB7/r1Of6qVYuDMm43gyRnnWXt+J1i2DAGZ0pvzzj77NCzOWxGAgVm+vZbcw80a9Vix4BIRl07dOBB9JdfslvEzJmh39f8+eav2MXFMQpeumJv6du8+Wb4++rMkp3N6LqRpN2hEOWbPj02WyIWCaXjQVaWVL0XxZYtk8+VaPHII8C0aRUvJqSkcMtAkYYNgV9/5VxSFByoVYvp2DNmALt2sfXsiSfat1DeiBHMrPK39eHoo523YpycDHTtyuyRKVNYU2bHDmb23nsvcPLJ/PvccIPVI3WWsWPZcj0uju+DFi0YcIsSpr07lVL3K6W2KKX+LbycWeJ7dyilViulViilzjBrDJZ77DHz0upTUxkZNKKVYzAmTGA3h4QEpqz37s1JJ5SuBV99ZX5rneRk4MEHK79d167AwIH2jA43b87UPCNIu8OoIPOryZ59NnaLGBYJtuPBjh3OqPciIiMlxdE1PmSOLfTVV1xhDqTz0dChR/6/bVsep958Mwsj7tzJVfgTTrBvcKCk8gobut3cVuzwtncAmPXRty9wzz0M7EyYYPWInOmhh5hl7fEAq1YBnTpZPSLDmL0U/YzW+smSVyil2gAYDqAtgAYAZiilWmmto6u0+ooVwMKF5ty3ywV88EHwB3JGaNmSe9qys1k5d9Ik4OWX2Vv0n3+Cm/w3bTJvnEUyMpgFEYhnn2WGhp1WEhMSuO8sXFlZDJi88AJXeaSTQTSI3fnVTNu3cz6LZR4PcMwxwf3Mzp3OK6YrzJOTw4J5J5xg9UjCEdtz7KJFrDkQyLbERo38Z25268aLU7Vty2DJL7/wmH7lStZz6tHD6pEJu4mSrQalWRHSGwjgI611jtZ6HYDVALpaMA5zPf20OSecbjf7259zjvH3HYyUFKZd/fADDxCffz74CPETT5hbRDA1lRV4A1W3LnDfffZqBeN2h1fIUNodxprYmF/N9Oab0bFSFI7atYNvG7tzp2w9EMVyciJTgyjyYmOO3bWL3RECyTpMTo6KfvHl6tuXWRXffstAwVtvWT0iISLG7EDBOKXUQqXUG0qpoqomDQGUXEreXHhd9MjMBN57r+KiL6FISWGVzXvvNfZ+w1W9OovQBKtOHZ7EmlUboFkzoGfP4H7mhhu4j84ucnNDj8ZLu8NoF5vzq5m0ZkDN7C1RdhdKx4MdO4z/zBPONmeO04NHsTnH5uZyi2KgLS7j4ljUTQgRdcIKFCilZiilFvu5DATwMoDmADoC2AbgqSDve4xSap5Sat6uXbvCGWbkvfOO8StS8fGsJvvRR9G12tW/P6vpGh0sSEtjAZ5gn6vERFaItUtWQdeuwddNkHaHUcHM+bXw/p07x5rlt9+kNoFS3LIVrB07JBgpjpSfD6xZY/UoyiVzrB9asyjhsmWBZ8XWq8f2e0KIqBPWhkKt9WmB3E4p9SqAbwv/uwVA4xLfblR4Xen7ngxgMgBkZGQ4JyStNVPqjT45S0tjURi7nMAa6bnn+LutW2fcfdaowfYkoejbFzjpJHYGsDJNPyUFOO+84H5m9mymC+bmSsVphzNzfi28f2fOsWZ67jkJrKWmBl7XpaSNG52+eiyMFhcH/Pknq4DbkMyxfjz1FPfkBxr0S0riYo8QIiqZ2fWgfon/DgKwuPDrrwEMV0olK6WaAWgJYI5Z44i433/niq6RkpOBjz9mRkE0SknhB5PbbUy2RFoaK5CGU1X3lVf4AWiluDjgjCALKq9fz+dQggRRLWbnVzPt2wd8952c7MbFhVYod/Nm48cinC0zk63wHCgm59hp07i1NZAOB0USEtgJSwgRlcwsUTxBKdURgAawHsCVAKC1XqKU+gTAUgD5AMZGVbXYJ57gh6OREhO5Op6SwhSvpk1ZkbplSxapK7pUr+7cbQnt2wN//80aAbNnB/dBVVpKCvvfhqNZM+D667nCaFU6bUpK8JXHO3UCfD5zxiPsJDbnVzO9+64zWnaZLZSOBwC7RQhR2syZVo8gVLE1xy5bxjoDwR7v1KwZWk0TIYQjmBYo0FqXm4uktX4EwCNmPbal9uwx/j6LAg+ZmcDq1bzMmMFMg6K+1dnZDBLUrcvMg5YtebDXtCmDCB06mFc00CjHHQf8/DMDBtddxw+uQNOA4+OZMpuXx36wwe7r9+eee1ivwKpAQd++wQd+WrSQgmIxIGbnV7Nozfao4QQoo0XNmqFtcXPKHmwRWTt2AHv3cjugg8TUHLtnDwtlB7vtKjFRth0IZ9i9G/j0U+DVV4ElS4DmzVl0vnNnq0dme9L02GgDBgDz50cm9Tsnh5eSNm7k5Y8/mBLmcnGf/dChzmnp0r07qyX/9BMDBhs38gNMKQYD4uJ48p6czCBImzZAx44sptOqFbMTjOB2Ay+9BFx6aeT3LaenAwMHBv9zcXEMFixZYvyYhIhW8+ezvZ8ILZsAAPbvN3QYIkqkpDD4f9ZZVo9E+JOXx79NKFtmExNl24Gwr4MHgS++YHBg3jwuKBYtBixbxlpkDzwAjB8v2YQVkECB0fr0AR591B57xPPziyt4G1koMBKUYlG+JUuAL78E3n8faN2aKW6tWjFjolo188cxdCjw5JOcZCK5dzknh6+lUHTrJoECIYLxwgtSsR/gvHv88cH/XH6+PH/Cv8xM4NdfJVBgV1deCSxaFHiHg5KqVQPatTN8SEKEZc0a4JpruO0pMbH87eBeLwMF337LbIM6dSI7ToeQQIHROncObcI1W6D9cO1GKWDQIF6sevw33mCbwkgeCDdqFPqk1b0722jGevV2IQKRmcmDBKntEXrHg127mOElwQJRms/HrkbCfp5/noWyQ9lylZAAXHCBc+tiiehUUMBuYYsWcXGvdNZ1aVlZzHg65hgeNwdbQDwGSK6F0RISQutBbbYDB6wegXO1a8d9eEX1IMzmdgPnnx/6z3fqxBQrIUTlPvlE3i9FQu14sHOnMXVhRHRatsweWZai2I8/ArffHnpdluTk8ItGC2G0F15gRkEwGcB5edw6N2gQi5jLXHUECRSY4ZxzIndSGaiiLQgiNI89Fpm/qdsNXH012zuGqm3byqOoQgh65hnjO9U4lcfDLV7B2rlTVhZF+VJSgH/+sXoUosiqVcDgweFlAKWmsjaUEHaxYQNw112hZ9N6vaxncOaZxo7L4SRQYIZTTwWSkqwexZGkmnd4qlcHJkzgh6NZ3G7gzTdZEyGcFc7kZO7N6tOHB2iyWiqEf0uXcvVBUPXqoc1xO3Yw5VMIf3JyWGBZWG//fh6jhhMcjY9nNoEEB4VdaM3M33AXybxe4K+/uHVBAJBAgTk6drRfi7rcXPuNyWkuv5y1A4yWlATUrw/Mns0+xkY44QS20FywgFWJU1LsF7wSwmoTJ9qzpoxVQu14sHOnZDGJ8uXkANOnWz0KkZ/Pzlw7d4ZXnNnlAkaONG5cQoRr3Trgzz+NCVhrHVqL4CglgQIzxMfzRM1OkpKkTkG44uO54m/kBOJ2s1Di4sXmVA9u3Zq9YteuBcaN42qhTIBC8OTl7bclgFpSqPV1/vhDAi6iYrNnR7ZzkChr3DhuAQl3D3ZycmjdUYQwy9FHs4OBEce3XboAzZuHfz9RQgIFZhkwgKu4dpGY6NzOB3bSvTv3LxlRuMvtZmuiX38FatQI//4qUr8+8NRTwLZtrKEh2QUi1n31laTOlpSWFtqe40WLgO+/N3w4IsoUFMg2Hyu98grw7rvhb0ONi2OxZZk7hd3cfTfw4IPMeAlVWhpwxx3GjSkKSKDALKeeyg4IdhEXx71pInzPPx9+oMDtBl5/HXj66cjWEJgxA/j6a6nqKsTTT0uR15JC7Xhw3XVAdrbx4xHRJS6OqcEi8mbOBG66yZhaVampbIsohB2NH886X6EGC9xuoF8/Y8fkcBIoMMtxx9mrL3d+vhzMGaV+fUYug0lxSkoC0tOZste9O/u2Dh9u3hj9mTSJH/BS2FLEunXrgP/+s3oU9uLxAMceG9zP/P47MGeOpJSLymVmsiWfiKy1a5lFGE6Hg5Li44Fu3Yy5LyHMcM01wEsvBR8scLmAG2+UAuCl2GjJO8rExQGjRnEPrFETdKhcLuDWW3mCGi0KCoBZs4C5c1mpu3NnHuRGKotj/HhORHFxHEt29pEHy0lJDArk5gKdOnEryimncA9wpPuNa810rAkTrH8tCmEHkybZK5BrB9WqMe0yUFoDY8dK4FEEbuZMq0cQW7QGTjvNuPavcXEsuBwna4zC5i65hNu/L7ss8ONerYErrjB3XA4kgQIzPf008N137O1pBZcLqF0b+OILnkhHk9GjgS+/ZAGtpCTul8vOBpo1YyHJyy4DTj7ZvMdPSmKg4u+/gT17gF27gK1befF42JrwlFP4vEc6MFCSz8foqhF7E4WIBvn5wOTJsv2mtFatgrv9l19ytVKIQO3cCezda35NHkFaG1tkVLYdCCcZMYILdhdeWHmwIC4OGDgQqFkzMmNzEAkUmMnl4n7wbt0iv5LrcvFk+umnwyvsYUdffMFL0YlvyQP+lSt5+eMP8w9iGzUChg419zHCkZvL7Q3Tp0uQQIgi06dLpwN/unQJ/Lb5+cD11wNZWeaNR0SflBT2KD/7bKtHEhvi4lgsuXdvYMeO8IMGSgEnnmjEyISIjPPOAz77jMfqFR0Hp6QAt9wSuXE5iOQPme2444CHHmIkNhKSkhgR++Yb4OWXoy9IsG0bcPHFlZ/4bt4c2yuGWVnMavj+ewkSCFHSs89KEcPSUlO5RSpQb7zBlWEhgpGZyRNXETnNmwP//sv2y+EcDyoFDB4s+7eF85x5JhdtKzoPa9YsuGB5DJFAQSTccENk9sO63XxDrFrFk8RoozVXyAM58U1JAZYvN39MdrRnD7NY5s6VmgRClLRtGwvwiSPFxwfe8cDjAW6/XbIJRPB8PiloaIWaNZnJcdppofeZT09nCrcQTlS0cOYvWJCWBtx2W+TH5BASKIiE+HgWsTNLQgJf6K++ypT86tXNeywrvfgiMG9eYGnDWsdmVfONG7kyuGIFkJNj9WiEsJe//rJX21q7CKbjwTPPyNwiQrd8eWxn+1klJYV1RcaMCS1YoDXQq5fhwxIiYk46Cfj557JFe5VikU7hlwQKIuXMM7ktwGhuN9C1K7BsGTBypPH3bxfLlnEVK9A0+sxMrqjHkqVLWTxxyxZjCxgJES0GDADq1LF6FPZTpQovldm7F3j0UdnOJEKXkgL884/Vo4hNcXEM9D3xRHDbEJRioTcJsjqP1swy3rdP2tgCPF/67bfiz7ukJODKK1n0UPglgYJI6d2bH5BGUYoT/cMPM5W2USPj7ttucnOBQYOCT6OfNcuc8djR339zu8GePdL2TYjyJCUBn3wSfbVbwhVox4MHHpBCkCI82dmy/cdq11wDfPpp4JkF6enARReZOya70BqYP5/FH6PB448D7dsD9erxZLhuXaBDBxYUve46Fjz/6CO+J9esiY3tqp06MbuwWjX+va+91uoR2ZqEByOlSxd+QBrB7QYaN+Y2g0DTRZ3szjuBTZuCj4YuW8afUcqccdnFtGmVV3QVQlBGBnD11Sz2GgsHRYEIpIjTpk3c3ibbDkQ4cnO5V1gqjFvrrLN4cnjaacCBAxUvMBQUsN1ztNMauOkmYNIkPh/JyTzG7taNnxsdOgCtW1vb8joYu3axmHrJOXvnTl4WLuT/ExO5iJmfX/x5OHAgt6lEs7ZtgdmzuUW5SROrR2NrEiiIlMRE4OSTGcUKpwiUywWMG8c3vxlbGezm99+BiRNDO6DPywO2bwfq1zd+XHbxzjvAVVfJCY8QwXjkEWYWbN5s9Uisl5oKdOxY+e1uvVW2NAljyPvOHjp3ZkeEk08Gtm4tv3bE2Wc75+Q4HHffDUyeXHw8lZPDk8nZs7mvXSku+DVqxOBq9+6cO487DqhVy9Kh+3XbbYFngCkF9O3LdoL9+pk7Lrto1SrwbLoYJoGCSJo6FXjtNeCuuzgBBbMCnJLCIoWff87JKVZcfHHoJ8HJyYwWRmug4IkngPvukyCBEMFKSQE+/pirabH+/omP5+pKRZYs4QqTbDsQ4UpNBe691+pRiCJNmgALFvDkcOHCsvNhlSrAqFHWjC2Spk5l69zyjsszM4u/XreOl2++4XFmdjYzfdu0AXr0YBAhIwNo0SIiQ/dr6VJuKSgd/FGKW0mys5kdMWgQ0L8/xyw1KIQfUqMgkhITmfK6ZQtw//18swayV9blYmr5ypWxFSQA2NYnVF4vo+XRRmvgxhv5Gor1kxwhQtWjBwORRtaOcSKvt/ItbNdfL1sOhDHq1wdGjLB6FKKkatVY4O3ss8vWLcjPj85226U980zw2zdzcoCDB3kyvn8/M4afeoqdJdq14zG7VR59tHi7c2oqP+caNAAuvxx47z1g924upN1/P3DCCRIkEOWSQIEVXC7uz9u8GRg/nhOzv4qbiYlA1apc+XrnnbItPWJBv35c8QpFXh6L/EWT/HzggguYHic1CUQ0CGcrVriefJIHybEsNbXi5+CPPziPSsVsEa7UVOCFF1h9X9hLUhKPNa+//shgQb9+0V8RftcuznNG0Bo4dIiv8RkzjLnPUOzfz7/jWWcBzz3HltlbtvDYccAALlQKEQCZra1UpQprDWzcyH3mLlfxPjC3m8VjVq3imzpWnXwyDy5CtWCBcWOxmtfLFLGvvpIggYgOmZkMgM6ebc3ju93Ahx/GdheEivZoag2MHSvzjTDGsccCZ5xh9ShEeZQC/vc/BnNcLq5Cjx5t9ajM9957xgevvF5uTbDK558z2+Hbb4HLLpOCfSJkEiiwg5o1uTdqzRruBatWDXj+eVYGrl3b6tFZ64QTmNZVpUpoxRu3bTOu24SV9u8HTjqJUW85aBfRoihLqls368bQuzcwfHjsbkHo3Ln87339NT+XhAiX280T0GjvQhQNLr2U7/0TTwROP93q0ZjvpZfM2cb555/WZWIlJUnmjjCEvIrspH59Fjvct48RQPlA5YnEsmXAu++yH+yYMTxhbtiQe6pcLm7PKKpIW5rLxaIuTrZ1KwvNLF4cHUEPIUqaNg1o1szaMTz3XGymYrrd7CntT34++2xbuTVERIe4OH5uWxkQFME57TSmzkd7APW//7igZAafj8evQjiYVK8Q9te0KS+l+Xxsf7h2LS+rV/NkeuVK1n/IzOTq+5YtFa+a2dnKlUDPnsCePexlLES06d+f718rpacz/XTQoNjK2ElIKL/jwVtvcd4RIlzJycyaFMJu3nvPvEKtPh/w88/shiCEQ5kSKFBKfQzgmML/VgOwX2vdUSnVFMAyACsKvzdLa32VGWMQMSAujlVcGzTgakVpHg+waZNz+6TOn89qwwcPSiExcQSZY01w+unAwIHAlCmxU+G/vI4HXi97cEs2gQhXYiIDcJV11rAZmWNjxLBhwOuvswCh0e1fvV7WCBg3ztj7FSKCTAkUaK3PL/paKfUUgAMlvr1Ga93RjMcV4ghuN3DMMZXfzo5mzADOPVcO1IVfMseaZOJE1oaJlUCB2w3UqFH2+meflW1OwhgJCdw26DAyx8aI44/n9tQBA/iv0RllCxcae39CRJipNQqUUgrAMAAfmvk4QkSVjz8GzjlHggSiUjLHGqxaNeDNN8v2Eo9WLVuWvW7fPuCRR2JrC4YwR3Iy+7Y3amT1SEImc2wMqFePLWCvuMLYDjhuNzubCeFgZhcz7Algh9Z6VYnrmimlFiilZiqlepr8+EI4ywsvAJdcYk4FXhGNZI412sCB3IYQSpcVp/FXu+WBB4xPwRWxKSEBuP9+q0cRLpljY0FCAjOp3n+fLbnDLSaelMSOOpdeasTohLBMyFsPlFIzANTz8627tNZfFX49AkdGYbcBaKK13qOU6gLgS6VUW631QT/3PwbAGABoIv0/Y9MPP7A14tlnWz0S82kN3HUXP6gkSCAgc6ylXnsNaN6c80+08tfxYPNmYPLk2Nl6IczjdrPOhb+tLTYhc6woY9AgYMECFtndsiX0LVhpaezWJd3LhMMpbVKRNKVUAoAtALporTeXc5tfAdystZ5X0X1lZGToefMqvImINrt28UDd5wPWrQNq17Z6ROYpKGDK28cfS7qvDSlgvtY6w+pxlCZzrMk+/ZTZPdG6BahqVeCbb9hVpcgFF/D3zsuzblzCWeLiuHqamMivtebntssFrF9f6TYepZQt51dA5tiY5vEAF18MTJ0a/HGZy8WfO+WUym/7/vs83r3ySuO2PezZw0WnpUu5ne7UUzm3x6LffgPuvRd4+GH/Rc9jQLhzrJntEU8DsLzk5KqUqg1gr9a6QCl1NICWACzuiyVsady44lWtm28G3n7b2vGY6fzzge++kyCBCJbMsWYaOpT1CmbMiM4TZ6/3yLZdS5cCX3wRnb+rqFxycvHJvlI82c/LY1ZNfDxXSNPTeeJRsyaD93XrAnXqMGugRg2gevXif+vXj4ZaHzLHxiq3m4s3r7wCjB8feKan2826HIEECQDgqKOAO+7glq9bbgGuvZbvs1Bs2QL873/83NK6OBvigw+4pS4tLbT7daL//uNzOX8+j61feSVmAwXhMjNQMBxli7/0AvCgUioPgA/AVVrrvSaOQTjR77+zpUxR2u+nnwI33gh07GjpsEyzYoUECUQoZI4125tvsuBfNJ48JyfzhK/I9dfLlgOnS0jg6n5CAk/2tWa9idxcfu128ySkalWe0NeqxZP9unX5Wih5ol/0b/XqfK3EJuPm2JwcrvSWfM8Je1MKuPpqdkY480zgwIHKt6Pl5jKwEKiTTgKWLQNuuonbTx95hMe748fzvReInTv5859/zgBf6TEmJDB7bMSIwMflVGvWcHFx+nQGSoqy5qdP59eyFSRopm09MJKkbMWYO+8EHn30yOu6dAHmzo3ON/ns2Yw+S20CW7Lr1gMjyRxbgXff5cFitG1B6NyZqy0A8NdfQN++ErB0oqZNgV69WLm9du3ik/vSJ/xGFGgzgZ23HhgpIy5Oz0tM5ElbkyZA69Zc/GjdmsHIli1DX0muSEEB8OefwCef8HFvucWWrwPb27MHOO88YN68iufJhARm3Uyf7r9YbEV++w0YPhzYto3BubFjWeejTp2Kf+7uu4HHHuPfujynngr89FNw43GS7dsZaPngAwb2Sz8XLhezDPx1+olydt56IERoNvvZCrh8OfDZZ0wHjjYnnMAevpL2K4T9XHghMwt+/z26ugEUFTLUmgekEiRwppEjuQop7E0prvTm5vJ4Zvly4OuviwM4Hg+/btoUaNsW6NABaNWKl+bNg8vq8HiAH3/kSdO0abz/rCwgJQVYuJDzWWKiab9qVKpZE/jlF3bxePLJ8hd28vOB3btZ++X113niH6hevYDVq5lN8MorwDPPAC+/DIwezWBAw4b+f27u3IqDBACDRfv3M4gRTfbv5/z30kt8DirK+Jg+PSYDBeEyuz2iEMGrVq3s3sasLB7MRuuq+3PPxUY7NrtIS+MBWWqq1SMRdqcUswqiKf3a5Spe7Zo1C1iyxNrxiNAkJHAbgbA/f9m7Ph9w6BBw8CBPMA8c4KrnBx/wxHD0aKBbN35O1a7Nr6+4Anj+eeD774G1a4tPEPfsAd56CzjtNGaRXHQRswgyM/kYPh8DCFOmAH368DoRnLg44MEHuahTpQr/Xx6PB7jsMmYE+HyBP4bbzeDA778zS6iggF14WrTg62HdurI/s3Rp5febmAh8+WXg47A7r5eZx40bAy++yP9XFCTwevl3E0GTQIGwn2efBSZM4IdjQomkl6ws4PHHLRuWqerVA+65JxqKPzmDUtzL9t137HXscrFglxD+NGzI1Z1oCSwlJXHVEuC/3bvL3ONECQnmpKsL6+XlMYBw6BBPFnfv5jbF114Dbr2VK9XHHccsgbp1gQYNWLztp59YD6G8QIDXC8yZA2RkMMVdBO+MMxioqaxLgcfDk9h+/YIPzJx0ErMLLr+cJ/nZ2QwgtWnDzNrly3m7/Hym3VcmMxN49dXgxmBH+fls4duoETsZZGYG3sLyr78kazcEEigQ9hMXx+yBlSsZHS86gPV4GEDYssXa8Znlxhtt3XM6qvTrx9dZz55MJ5w3DxgyhAddktkh/Ln8cqYDR0NAKTu7uONBlSp8D9x8s3HtuURkJCTEViVzJzOyHlhODrMPsrJ44rRzJ1dTMzMD//m1azmf+dvqKSrXrVtgQTqPh7UHOnTwnw1QEbebKfU//MBAUFHA4IsvuHXsrLP4dUpKYPc3fz4DTk6kNQubN2vGwo179wa/XS4xkUEyERQJFAj7atCAK74ffMD9YSkpjAZed53VIzNHUhIjvrKyZ6709LK1Ltq0AT76iBH8q67i30BOmkRJSnEuioYtCImJTGUuEhfH9lxffcVU9mgIhsSCuDjJKBChyc/nidb55/O9//HHwIIFgQcbYp1SwCWXBLawkJMDbNjA4pW//hr8Y510ErBqFXDppTwuKShgwOC777gdIVDx8eyM4DQzZvAY7ZJLGNgKtbCw18vnTARFAgXC/gYOZCR21ChOzlOmAH//bfWozNGvH9OA5UDdPDk5wOmn+/9ew4asF7F1K7eCRFvhHxGeo45idWmnb0Fo0cL/9X37AosXA+3aSaDMCZSSQIEIXVYW07EffJC1D3r3ZoeMatV4UnvBBczi/Oor7oOX9qlHGjUq8GM1n49bSc48kzUIguV2cxvDjBk8TnG5uMru9QYe3PF4uHXFKebN4/Hwuedyq0W4nYfy81nkUwRFAgXCGdLTgUmTgD/+YAXgp5+2ekTmmTRJ0t/N1K5d5QXAqlYF7rgjsL1/IraMHcuWZhUVsrK7oo4H/jRqxCrao0dLdpMTSKBAhKuyooqjRrE7U2oqW/UVFVV84YWyRRVjSevW5XciKI/XC9x3X+iP2aMHswsuuyy0YO6iRfY/rlmxggGVXr1YbNfI1sT16hl3XzFC2iMKZ+naFVi2LHq7HwAMhIwbV1zJVRgnORkYNiy42wtRUlwct6kcd5wz358pKZX3905M5KrXKacw3dXjMXaPtTCGzyeBAmGuvLwjC8Dt2sXL7Nn8fExJYXAhJ4dFFVu0YDZCmzbF7R3r12f2SzQaMwa4997AC+olJrIjRThcLgZpRoxgB4tAHxvg59enn7Lwpd1s3gzcfju3R+TmBtctIhBKsVaECIqDl0REzEpMZAGuaHbffZL6a4b4eGDAAKtHIZyuRQvu63XiintycnHHg8oMG8YCWE2bBl4wS0ROQYEECoR1ShdV3LIFmDmT2/duvJEp4y1acO44+migf39m6r3zDleK9+yx+jcI38iRgQVRi+oejR4N3HWXMY/dvXvwJ9Ner/22H+zdC1x/PYNKn3zCwIfRQQKAGTGtWhl/v1FOMgqEsKPUVGYUXHGFsWlXsS41FTj2WKtHIaLBTTcB777LPf1OWm0v2fEgEMccw3TViy8Gpk0LvtK0ME9+vgQKhD2VnifWreNl+nR+DsfFcS5KSGDtl9atmYnQujXQsiUvTujo0bAhtzPOn+//+2lp3Mp4662cQ41c5CpaIV+wgHNBoFasADZtAho3Nm4socjKAp56inUwirJSzOTz8TUmgiKBAiHsavhw4IkngH//ddaJiF0pBZxzTvSmQIrIio9npfAuXZy1BSE+nvuMg5GaypWeV14Bxo931u8bzfLynF9YU8QWrY8svpeby+2ky5axaGJqKj+jPR6eZB91FE/EO3Qo3spw9NH22hZ45ZXMoCha1ElM5DzbowdT6U87zbzjji+/ZOD3wIHAfyY+nnUnvvvOukyxDz4Arr6awYFIFcns0oWvJREU2XoghF0pBbzxhqT8GiU9HRg82OpRiGhy7LFMpXXSFoQWLUI7aFWKB3a//869yFJw1XoJCbwIEQ1KF1Xcv59FFd9/n+n6o0axTlVRUcXu3Vkj4IUXmKmwbp01RRWHDOF4U1MZ3Lj6anaJ+OkndpIxc3GiQQMGcV0uBigC4fGwYG39+lyMsiJrdedOFhZUikGfqlXN/Rx1u4HHHzfv/qOY0g5YqczIyNDz5s2zehhCWOPSSxl9ldZE4UlOBvbtC7r2g1JqvtY6w6RR2YLMsWHIz+cqxYoVVo8kMKNGAW+/Hd597N3Lg+PZs2UrgpXS03lS5WCxML8CQIZSWmZYk/grqtiyJbMQ2rZlFkLLluYWVXzpJY5j5MjwTni15on7nj3A7t3F/9aty8KF5dm0idkLU6YUFwJUisGLitonut3cBnLzzcANN1TeEcpoWjNosHIlP0MXL2ZwaOVKXp+czGCo18vfK1Tdu7MVaAwKd46VQIFwrt69GUlu397qkZhrzx6gWTNG2kXoevVioaUgxcKBrMyxYVq4kC3D7J6Sn5zMVZXrrw//vnw+4OGHgcces//vHa3q1AF27LB6FGGJhfkVkECBZdxurrQXnTw3bMjAQadOrIdQtJ2hRg3jH7tom0XRyX7JE/9du1j8cds2fr1nD7cPFJ3UJydzi4BSzJLw+YCBA4FXX614u9GyZayHsG8fT45bteI8vWtXxfO0y8WAwdixwC23ALVqGftchCI/n1kiK1cCy5fzc3bRIl6XlcUxFwVWKip+6HYDP/wAnHhi5MZuIxIoELGrKDLsgNdw2F58kdFiKWwYGrebKXbXXBP0j8bCgazMsQa4805W+7bzCnvVqmw9VdHKVLB++QUYNKi48rmInGbN2MPewWJhfgUkUGA7Ravt8fE8gS4qqnjsscxEKAoitGgRelHFBx7gSXrRqjjAk/68vNAyRFNSeAL/9dcMdAQqO5ufT6+8UnlQNyWFz81ll/Fn6tcPfpyRcOgQsGoVsxCWLwf++Yf/btpUvJ0hL4+fx127MvstRkmgQMSuDz8E3nqLe9OiXUEBq4+vWWP1SJwpJYUfKE2aBP2jsXAgK3OsAXJzeZBp5xO3lBSOz+iDv61bgbPP5nvMzoGSaNO+PVfZHCwW5ldAAgWOEhdXtqhi06bcxtChA4/FOnWqvGtA587sSGA0t5u1Yjp3Du7n5sxhy9udOysPGCQl8Xm44ALg3ntDOnayhNbA9u38LFq5khkWV1wRXKefKCOBAiFixW+/sQ+xHIgH76ijgPXrQ/rRWDiQlTnWIPPnAz172jcV3+Xiyr8Z+3Tz8tgy8vXX7fv7R5so2HcbC/MrIIGCqJGYyNXqtDRuGyiPz8dgQ3a2OePo2hWYNSv4uTw7G7j7bmDixMDm6aIODoMGMUOiZcvQxissE+4cK10PhHCKXr3YZkeqXAcnPl66HYjI6NKFFa+DLJgZMc2bm1fMKzGRNWPefbd4NU6YK9KFx4SIdXl5rCNQWcHC1at57GGWJUtCy6ZNSQGefJL1mpo2rfyzKi+PwYVPPgGOO451EhYvDmnIwpkkUCCEk7z4YuAtcAS53cC551o9ChErHnkEqFnT6lH416GD+Y8xeDDTbY8+Wlq7mq1aNatHIERsat684u/Pn8/UfbNkZbHmUqjtII8/nnv6x44NLLBdUMCAwbffMpvh9NMByUKMCRIoEMJJGjcGbrvNWX3brVZQwBRdISIhJQX4+GP7ZRUkJzPjIRJatmR16nPPNW+uUgqoUoWB04qqgEez6tWtHoEQsalt24q///ff5neq2rkTeOed0H8+OZlFnn/7jYVRA/nM8vm4ZWHGDGa59uzp+DopomISKBDCaW67jf2zRWBOOUW2a4jI6tEDuPhiewULUlKAdu0i93guFwvOPvOMMc9DYmJxYKB9e9ZD+OADYMMG4Kmn2PYs1OrkTmVGSzchRMVcLhY0rMgff5g/jqwstjIMtyZMRgaL/l17beBztVLcWjF3LrMnRNSSQIEQTpOSAkyaFLuraMFISwPOP9/qUYhY9OST9tpDnptrTeXnMWOAP/8E6tVjJe1AuVx8/7pcXLV64AFg2jTg4EGuYD35JHDWWezgcOWVwMaNwPvvc3uF2x39NRISEuz1+hIiViQlcWtVeXw+nnhHgtcLPP10+PeTnAw8/ji7KRx9tP9MsLQ03u7oo4EbbwS++Ybz8SWXhP/4wrYkUCCEGTIzmRK2cqU593/OOWzPY+YeuGiQmwv062f1KEQscru5om6XrAKtgQYNrHnsTp144NyrV/lbEdLTi/uEDxzILIG//+Zc+ttvwB13ACeeWH7dg7g4zov//gv89BP30KakRG82UUJC7GVQCGEHBQVM1S+P2YUMS/J4gEcfBfbsMeb+unQ5MrsgPZ2LUgMGsEbWunVs0/3kk0Dv3sEFf4UjyVmGEEbauRO4+Waunl1zDVe37rzT+MdRCnj1VUZ3RflatABq17Z6FCJW9e4NDB9uj6J+Rx9t7Sp7tWrADz9wPnS5ircRNG0KXHYZMHkyA6u7dgFffsnuEe3ahRYM7dYN+P571kkYNYrPvx3+BkZJSmKgoGtXq0ciROzxetlyuTxmFzIsLT8fuPde4+4vKQl47DEWK5wxAzhwAPj6a2D0aGZwiZgigQIhjDRgAPD889w7lpXFKrHPPMN9tEZr3ZoH2NF0AGykxERg2DCrRyFi3XPP2aOmSCQ6HlRGKeCuu5gh8OGHDKyuWwe89hoDKo0bG/t4LVoAr78ObNrEvbxFq2NO5nJxXluzJnLFKYUQxapVq3glPRKFDEvKyQHeeINzqZHatGEwMlLZEcKWJFAghJEyMvxHkr/6ypzHe+QRySooT1ISU5GFsFJ6OvDee9Z2KklKstdJZUYGcOaZkWvvV6sW8OCDwI4drPLdoIHz0vZTUxns+eMP4N13gTp1rB6RELGpsoBmJAoZlpaXxy0IQhhMAgVCGOn++8tGX+PjzTsgrlKFGQtOXyUzQ0IC0LGj1aMQgvvlBw60LqjnckW244FduVzc0rBpE/DWW8Bxx9m/1azLxe4GkyYBCxYAnTtbPSIhYltFHQ8iWciwpIICYMuWyD+uiHoSKBDCSLVrs21XyQJmNWsCI0aY95ijR3OfrzjSWWdFf+Vz4RwTJ1p3UmpVxwO7iosDBg8G/vuPe3DtWPgwPp6fI+PGcevaBRfIfCaE1eLigLZty/9+JAsZlhZum0Qh/AgrUKCUGqqUWqKU8imlMkp97w6l1Gql1Aql1Bklru9XeN1qpdTt4Ty+ELZ066086ExOBk44Afj8c+6XN0tcHPDmm/aprm4H6enAkCFWjyJsMsdGkWrV+D61Iljg8wGNGkX+cZ2ge3dg+nQWPrzoInsUPnS7gVNPBRYvBiZMcN42CQeROVYEJTUVaN68/O9HupBhSdnZ1jyuiGrhvpoXAzgPwG8lr1RKtQEwHEBbAP0ATFRKxSul4gG8BKA/gDYARhTeVojokZ7Ont6HDgGzZnE/rtmOPx4491xpVVMkJwc47TSrR2EEmWOjycCBXL02M3DoT7NmshpdmRYtWBBs40Zg/HhrCh+mpgJNmrCmzQ8/VNyrXRhF5lgRuLi4it+XkS5kWFJOjjWPK6JaWIECrfUyrfUKP98aCOAjrXWO1nodgNUAuhZeVmut12qtcwF8VHhbIaJLWlrkTwaeeSbyj2k3KSk82H78cXtUmg+TzLFR6LXXmGlUvTpT3atU4WvVzFWo444z776jTe3awMMPs/DhhAlsB2b2in5SEuetBx9k6nJ0BDkdQeZYEZScnIoDBVYUMiwiGQXCBGYdmTQEsKnE/zcXXlfe9UKIcNWtC9x3X2wWNkxOZrruTTexoM8NN1g9IrPJHOtUNWsCv/8O7N0L7NsH/Por8Oqr7IN9zjlAq1bF6e9Vq4a/VSExMTJZTdHG5QKuuYaFD995B2jf3py51eUCzj+frc1uukmCvfYhc6woy+djMLG871lRyBBgsPGkk6x5bBHVKq3co5SaAaCen2/dpbU2qecboJQaA2BM4X9zlFKLzXqsENQCsNvqQZQg46mYjKdizh9PUcrd//7Hi7EqKHEcPplj/XL+a9II5a8QBT6evDzWTbn1VqNGFd54IsM54/F62e7w3XetH4s1TJ1fARvNsdzmYBd2ex3YaTzljyU314oaBJU/N7m5wOTJvNhhPJEl46lYWHNspYECrXUoOXBbAJRsNNqo8DpUcH3px50MYDIAKKXmaa1tsyQi46mYjKdiMp6K2XE8Zt6/zLFlyXgqJuOpmIynfHYaC2D+/ArIHOuPjKd8dhoLIOOpjIynYuHOsWaFxb4GMFwplayUagagJYA5AOYCaKmUaqaUSgILxXxt0hiEECJayRwrhBDmkTlWCBHzwmoarJQaBOAFALUBTFVK/au1PkNrvUQp9QmApQDyAYzVWhcU/sw4ANMBxAN4Q2u9JKzfQAghopTMsUIIYR6ZY4UQonxhBQq01l8A+KKc7z0C4BE/108DMC3Ih4rIppsgyHgqJuOpmIynYjKeQjLH2oaMp2IynorZaTx2Ggtg8XhkjrUNO43HTmMBZDyVkfFULKzxKK21UQMRQgghhBBCCCGEw0W8dKcQQgghhBBCCCHsy3aBAqXUUKXUEqWUTymVUep7dyilViulViilzihxfb/C61YrpW43cWwfK6X+LbysV0r9W3h9U6WUt8T3XjFrDKXGc79SakuJxz2zxPf8Plcmj+cJpdRypdRCpdQXSqlqhddb8vwUPnZEXhvlPHZjpdQvSqmlha/p6wuvL/fvFoExrVdKLSp83HmF19VQSv2olFpV+G/1CI3lmBLPwb9KqYNKqRsi+fwopd5QSu1UJVoDlvd8KHq+8LW0UCnV2axxmUnm2KDGY5s5VuZXv48vc2zFY5E5NsJkfg1qPLaZXwsfU+bYso8vc2z547B8fi0ch7lzrNbaVhcAx4I9H38FkFHi+jYA/gOQDKAZgDVgIZn4wq+PBpBUeJs2ERjnUwDuLfy6KYDFFjxX9wO42c/1fp+rCIzndAAJhV8/DuBxi58fS14bJR6/PoDOhV+nA1hZ+Lfx+3eL0JjWA6hV6roJAG4v/Pr2or+bBX+r7QCOiuTzA6AXgM4lX5/lPR8AzgTwHQAFoBuA2Vb8DQ34nWWODXwMtpljZX71OwaZY4P7e8kca/7vK/Nr4GOwzfxa+Lgyx5Ydg8yxgf+tIj6/Fj62qXOs7TIKtNbLtNYr/HxrIICPtNY5Wut1AFYD6Fp4Wa21Xqu1zgXwUeFtTaOUUgCGAfjQzMcJQ3nPlam01j9orfML/zsL7C9spYi/NkrSWm/TWv9T+PUhAMsANIzU4wdhIIC3C79+G8C5FoyhD4A1WusNkXxQrfVvAPaWurq852MggHc0zQJQTSlVPyIDNZDMsYaI+Bwr82tZMscGRebYCJD51RByDEsyxwbO6jnWkvkVMH+OtV2goAINAWwq8f/NhdeVd72ZegLYobVeVeK6ZkqpBUqpmUqpniY/fknjCtNH3iiRamPFc1LapWDUqogVz48dngcATF0D0AnA7MKr/P3dIkED+EEpNV8pNabwurpa622FX28HUDeC4ykyHEcetFj1/ADlPx+2eT2ZROZY/+w4x8r8WorMsZWSOdZaMr/6Z8f5FZA5tgyZYytkp/kVMHCOtSRQoJSaoZRa7OcS0UhZGGMbgSNfENsANNFadwJwE4APlFJVIjCelwE0B9CxcAxPGfGYYYyn6DZ3gX2H3y+8yrTnxwmUUmkAPgdwg9b6ICz4u5Vwkta6M4D+AMYqpXqV/KZmblJEW6EopZIAnAPg08KrrHx+jmDF82EEmWMNG09EX4syv4ZG5tiKyRxrLJlfDRuPHMM6hMyx5bPz/AqE/3wkGDiWgGmtTwvhx7YAaFzi/40Kr0MF1wetsrEppRIAnAegS4mfyQGQU/j1fKXUGgCtAMwLdRyBjqfEuF4F8G3hfyt6rkwdj1LqYgBnA+hT+OI09fmphGnPQ6CUUong5Pq+1noKAGitd5T4fsm/m+m01lsK/92plPoCTG3boZSqr7XeppiCtDNS4ynUH8A/Rc+Llc9PofKeD8tfT4GSOda48ZQYl+lzrMyvwZM5NiAyxxpI5lfjxlNiXHIMW5Yt3g8yx1bKbvMrYOAc66StB18DGK6USlZKNQPQEsAcAHMBtFRKNSuM6gwvvK1ZTgOwXGu9uegKpVRtpVR84ddHF45trYljKHrckvtKBgEoqnhZ3nNl9nj6AbgVwDlaa0+J6y15fhD518YRlFIKwOsAlmmtny5xfXl/N7PHk6qUSi/6Gizcsxh8TkYX3mw0gK8iMZ4SjljdsOr5KaG85+NrAKMUdQNwoERqVzSQObYUO82xMr+WJXNswGSOtZ7Mr6XYaX4tHI/MsaXIHBsQu82vgJFzrLagYmVFF/BJ3QxG73YAmF7ie3eBFUBXAOhf4vozwUqcawDcZfL43gJwVanrBgNYAuBfAP8AGBCh5+pdAIsALCz849ev7LkyeTyrwb0v/xZeXrHy+Yn0a8PPY58EpvssLPGcnFnR383k8RwNVs39r/DvcVfh9TUB/ARgFYAZAGpE8DlKBbAHQNUS10Xs+QEn920A8grnncvKez7AKrEvFb6WFqFERWsnXWSODWostpljZX71+/gyx1Y+JpljI/ualPk18LHYZn4tfEyZY8s+vsyxFY/H0vm18PFMnWNV4Q8KIYQQQgghhBBCOGrrgRBCCCGEEEIIIUwmgQIhhBBCCCGEEEIcJoECIYQQQgghhBBCHCaBAiGEEEIIIYQQQhwmgQIhhBBCCCGEEEIcJoECIYQQQgghhBBCHCaBAiGEEEIIIYQQQhwmgQIhhBBCCCGEEEIcJoECIYQQQgghhBBCHCaBAiGEEEIIIYQQQhwmgQIhhBBCCCGEEEIcJoECIYQQQgghhBBCHCaBAiGEEEIIIYQQQhwmgQIhhBBCCCGEEEIcJoECIYQQQgghhBBCHCaBAiGEEEIIIYQQQhwmgQIhhBBCCCGEEEIcJoECIYQQQgghhBBCHCaBAiGEEEIIIYQQQhwmgQIhhBBCCCGEEEIcJoECIYQQQgghhBBCHCaBAiGEEEIIIYQQQhwmgQIhhBBCCCGEEEIcJoECIYQQQgghhBBCHCaBAiGEEEIIIYQQQhwmgQIhhBBCCCGEEEIcJoECIYQQQgghhBBCHCaBAhFzlFIXK6X+sHocQggRjWSOFUII88gcKyJFAgXCNpRSJyml/lJKHVBK7VVK/amUOt4G44pXSj2slNqqlDqklFqglKpm9biEECIYdpxjlVI9lVKZpS5aKTXYynEJIUSw7DjHFo7rVKXUP0qpg0qptUqpMVaPSThDgtUDEAIAlFJVAHwL4GoAnwBIAtATQI6V4yr0AIAeALoD2AigLYBsS0ckhBBBsOscq7X+HUBa0f+VUr0BfAPge4uGJIQQQbPrHKuUSgTwBYBbAUwGkAHgF6XUbK31f1aOTdifZBQIu2gFAFrrD7XWBVprr9b6B631wqIbKKUuVUotU0rtU0pNV0odVeJ7rZVSPxZGcFcopYaV+F5NpdTXhZHUOQCaBzoopVR1ADcAuEJrvUHTYq21BAqEEE5iyznWj9EAPtNaZ4VxH0IIEWl2nWNrAKgC4N3CY9i5AJYBaBPuLyyinwQKhF2sBFCglHpbKdW/8AT9MKXUQAB3AjgPQG0AvwP4sPB7qQB+BPABgDoAhgOYqJQqmgRfAjMA6gO4tPBS8r6/VUrdXs642gPIBzBEKbVdKbVSKTU27N9WCCEiy65zbMnbpQIYAuDtUH9JIYSwiC3nWK31jsLHuaRwK213AEcBkBoHolJKa231GIQAACiljgVwG4DTANQDMA1cyd+hlPoOXGV6vfC2cQAyARwLoBuAcVrrniXuaxKArQAeBifX9lrr5YXf+x+AXlrrkwIY00gA7wN4A8A4AC0B/ARgpNb6R0N+cSGEiAA7zrGlxncRgAcBHK3l4EQI4TB2nWOVUgMAvAagZuFVV2utXw339xXRTzIKhG1orZdprS/WWjcC0A5AAwDPFn77KADPKaX2K6X2A9gLQAFoWPi9E4q+V/j9C8BJujZYi2NTiYfaEMSwvIX/PliYRrYQwEcAzgzhVxRCCMvYdI4taTSAdyRIIIRwIjvOsUqp1uBx6yiwbkJbALcqpc4K9fcUsUOKGQpb0lovV0q9BeDKwqs2AXhEa/1+6dsW7vGaqbXu6+d78eDWgcYAlhde3SSIoRTtLSt54CoHsUIIR7PRHFt0P40B9C4xHiGEcCwbzbHtAKzUWk8v/P8KpdRUAP0BTA3ifkQMkowCYQuFRVzGK6UaFf6/MYARAGYV3uQVAHcopdoWfr+qUmpo4fe+BdBKKXWRUiqx8HK8UupYrXUBgCkA7ldKuQv3e40OdFxa6zXgPrK7lFLJhWllwwsfUwghHMGuc2wJFwH4q3DOFUIIR7HxHLsAQEvFFolKKdUcwNkoXggTolwSKBB2cQjACQBmK6WywIl1MYDxAKC1/gLA4wA+UkodLPxe/8LvHQJwOngCvxXA9sLbJhfe9ziw/dZ2AG8BeLPkAyulvlNK3VnB2EaAaWF7wOjrPVrrn8L7dYUQIqLsPMcCTIuVIoZCCKey5RxbGHy9FMDzAA4CmAngc7BmgRAVkmKGQgghhBBCCCGEOEwyCoQQQgghhBBCCHGYIYECpdQbSqmdSqnFJa6roZT6USm1qvDf6oXXK6XU80qp1UqphUqpzkaMQQghopHMr0IIYR6ZY4UQwj+jMgreAtCv1HW3A/hJa13Ud/72wuv7g73oWwIYA+Blg8YghBDR6C3I/CqEEGZ5CzLHCiFEGYYECrTWv4H9QEsaiOLCRG8DOLfE9e9omgWgmlKqvhHjEEKIaCPzqxBCmEfmWCGE8M/MGgV1tdbbCr/eDqBu4dcNwV6iRTYXXieEECIwMr8KIYR5ZI4VQsS8hEg8iNZaK6WCaq+glBoDpnUhNTW1S+vWrU0ZmyglLw9YtAgo2Q0jLg5o3RpwuawblxAWmT9//m6tdW2rx1GeUOZXoII5dutWYPv2I+eAWBMXB8THA02bAlWqWD0ac23fzr95NPy9U1KAtm2tHkVkLFoE5OaW/32lgLQ0oFWryI0pBHafXwGD5ligS+u4wrW5GjWAunX5ehVCiFCsXQvs31/pZ/d8IKw51sxAwQ6lVH2t9bbCtKydhddvAdC4xO0aFV53BK31ZACTASAjI0PPmzfPxKGKIxx7LLB8efH/U1KA6dOBRo2sG5MQFlFKbbB6DH6ENb8C5cyxPh9Qr150nDSGw+fjZcsWoFkzYNIkBg2i0U8/AYMHAwcOWD2S8MXFAYMGAXfdZfVIzPXZZ8All1QcKNAaKCgARo4EbropcmMLkk3nV8DoOdbl0vMmTgTOPx9wu80ctxAiFuTlAaeeCsydC+TklHszBYQ1x5q59eBrAKMLvx4N4KsS148qrBzbDcCBEuldwg4uuABISir+f14eULWqdeMRQpRmzvw6cybg9Ro6UEfzeHgi3aYNcM890fncdO7M3zMaeDzAI48AS5daPRLz+HzAbbcBmZmV39bjAe6+G/jnH/PHFX2MnWPbtmVwR4IEQggjJCYC333HxYwE89b9jWqP+CGAvwEco5TarJS6DMBjAPoqpVYBOK3w/wAwDcBaAKsBvArgGiPGIAx03nlHvugKCpjCWJENG3iSkZ1t7thE9CkoAEaP5uqtKCOi8+tLLwV2AhJLCgoYIHjqKeD0060ejfGqV2cqdLTIzgaGDgXy860eiTm+/BLYubPSmx3m9QIDBgCHDpk2JKeTY1ghhCOlpQG//grUrs3tZiYwJAShtR5Rzrf6+LmtBjDWiMcVJjn2WO7LLVplSk4u/wW4ahXQuzewdy+zEHJygOOPB4YNA4YP54tXiIps3Qq88w5w8CDwxRdWj8Z2Ija/HjwITJ0a0o/GhLw8ZhZEoy5dgGnTrB6FMbQG1q8HHn2UWSDRROvAswlK2rOHwdjPPzftYNLJ5BhWCOFYdesCv//Oz3ETthCaufVAOJVSwJAh3O8JAKmp5d/2q6+A3bu5inPwIAMFf/wB3HILcM45kRmvcLYNGxgVnT6dk52wxkcfsYCf8C8hARg/3upRmKN37yO3mzmdx8NAweLFVo/EWF9/zeKTwcrJ4fz65pvGj0kIIYS1mjcHZswwZWuTBAqEf0OHFgcIKtp28OOP/gsq5eQA//0HLFxozvhE9NhQWGfF6+UezoICa8cTq55/HsjKsnoU9tW5s+0ryIfs+OOjr6uN18vPsbw8q0diDK0ZgA91a5DHA1x7LbBsmbHjEoHZsgXYtcvqUQgholVGBrPGDP4sl0CB8K9Hj+LK5+W1B9MamDOn/PvIyQEeftj4sYnosn59cZG47duBiRMtHU5Mys5mqx3hX3o6cMcdVo/CPJ06RU9Bw5I2bmRxw2iwezd/n3AU1SuIxqKcdrd9O1ODN2+2eiRCiGjVrx/w8suGBgskUCD8S0gA+vfn19Wq+b/Npk0VFy/0+YBvvuEedCHKs3x5cRZBVhZw5508KBaRs2tX9BZ/M4LLVTwfRqOqVYFatawehfE8HmDChOjIbMvODn9rkNb8PB43zpgxieBs3cpgwerVVo9ECBGtRo9mi2CDtiFIoECUb0RhfZ/yKmL//Tfbc1REa+CZZ4wdl4gupQ+acnOjdy+4Xe3ZEz0p2kZzudiHPtrrNxx/vNUjMIfXy5o7Tn995+QU1w0Kh9fLeiSffRb+fYngFBQwKNu1a/TVzxBC2MeddwIXXmhIsEACBaJ8ffsys6C8laZff6285VJODvDWW0aPTEST0um0ubnAp59K7+9IKtpmJMrSGrjiCqtHYb6TT2aHm2i0ZQvw4INWjyI8OTnGdSzweFgPZv16Y+5PBE5rYN8+bu+saOumEEKESiluQTj11LDvSgIFoSgoAK65hj3Ho1laGj/MygsU/PKL/+vj47mnt2pV4KKLWFxDCH+09l/gqaiwoZzARobPZ/UI7CkuDjjvvPKzqqJJRgaQkmL1KMzh8QBPPQX8+6/VIwldbq6xrQ09HnYmcnqmhVMdOsSD+F9/tXokQohoFBdnSOaYBAqCdegQV9pfeSV6UzVLmjIFuPfesteXLn6WnMwUl4YNgeuuA374Adi7F3jnHaBXr8iNVzjL7t3lp9OuWcPXjxBWSUkBbr7Z6lFERrQWNCxS1AXBX5ceJzAyowBgcHDNGuC224y7TxGcrCzgrLNYy0kIIYxmQJagBAqCsWkTD6Z++YWpqF27Wj0i89Ws6b965r//MrMiORlo0wa47z5g/nxW9H36aaBbN2P2U4rotmFD+RNZVhZwww3AwYMRHZIQh7VowTk/FqSnA3XrWj0Kc23dys8qJ8rJMf4+PR4uekyfbvx9i8B4PMD55wMffGD1SIQQogw5kwvU3LlAhw5cRa9ZE3jySatHZK2MDODDD4F164AlS9g6rHVrq0cFAFi0aBHqNWqCmnUbHHGpVa8Bfv75Z6uHJ0rasKHi72dnA3ffHZmxCFFSWhpw++1WjyKyAgx+35uQhJqJyWUubRJTUEEfHOt5PMBzzzmz/okZgQKAmRbnn8/2fcIaXi9w+eXcUyxiXkFBATpmdC1zDFuzbgPcdGuMfSYJyyVYPQBH+PRTfpBqzfT611/n6kssS0gAhg2zehR+rVq1Cvnp9eE65eojrvf8/QGWLFmCUw0o7iEMsmFDxS02s7OB115jTRCbBKJEjEhIAAYPtnoUkdWzJzBtWsXvSQCz4xKA3hfD1fzI7XdrJ4+BB4CtKx0UbUFYtgxISrJ6NIE7+mjztk1kZbEWxx9/SCagVbxebnNyuYCLL7Z6NMJCBQUFWPTvAtQf8+oR12dvXIRZc+ZaNCoRq+QTIRDDhjFI0KABMGoUMHCg1SMSlYhPTEZCldpHXOKS/GyhENZaubLyg9+cHOCyy6SwoYic5GRg7FhnnUga4fjjA/6d41xVysyxSjnkkGLbNuCee6weRXBatGCAo7KWxKHIzwf++w94+GHj71sELjeXHTpEzFNKlZlf491VrR6WiEEO+VS3WEEBT1K2bJHUMCGMtGJF5bfx+XgQ++WXpg9HiMPGjrV6BJHXsWN0FzQs4vUCL7wAzJtn9UiC8/jjzHQxg8cDPPYY8Ndf5ty/qJzbHRu1r4QQjiGBgkBIKp4Q5qisRkGRrCzgqqt4gC+EmZQCTj8dqF/f6pFEXmoqM+diQdEWBLP2/puhXj3gllv8Fxg2gtcLnHsuOxaJyPN6gS5drB6FEEIcJmfAQgjr7NgR+G0PHQL+9z/zxiIEwFW9WG4ZF0srmjt2AHfdZfUognPbbWzbaZYDB4CRI2WrlxWqVwdq1Kj4NuvWMZC5c2dkxiSEiGkSKBBCWOPQoeCKc3m9wFNPAevXh/6Y27cDX3wBXH+9rJoJ/+rVA3r0sHoU1unVy9wTUTvxeoGJE4E5c6weSeDcbnZdSk015/5zc1nU8IUXzLl/4Z/LFVjdjLlzgR9/ZM0KIYQwmQQKhBDW2LAh+BTa3FxuQQhUTg7w0ktMp61bl+nk550HPP88sGdPcI8tol9qKlsiKmX1SKwTREHDqFC0BaGSTg+2Mno0A1pmycri++Dff817DFHM5QImTwbGjav8tsOGATNmAA88YP64hBAxTwIFQghrbNgQ/AlZQQHw++88UArEpk3MHvjqK6ZqpqQAV14JHDwItGwZ/JhF9Bs50uoRWKtDh9goaFjSrl08MXaK+HjglVeYXWAWrxcYMADIzDTvMQT/hl98AVx4YeA/06cPcOON5o1JCBG4bduAtWutHoVpJFAghLDGhg2h9QX3eNguMS+v8tu2aMHAQvXqQKtW/PqVV4D09OAfV0S3xES+rsw8+XIClwto1MjqUUSW18sV3VmzrB5J4E47jYXvzMx+2b2b7wkRvtJ/J6WAqlWBmTOBM86wZkxCiPAUFAAnnAAceyz//fhjZxXIDYAECoQQ1li9OvR03927gWeeCey23bszm2DZMiAjI7THE9EvIYHbUX7+Oeo+6IPWrZvVI4i8oi0ITuqsMnEikJxs3v1nZwPffgu8/bZ5jxEr6tRhEC4piX+zunVZb0A+k4Rwrp9/Bvbv56LXnDnA5ZcDtWoBX39t9cgMI4ECIYQ1li0L/Wc9Hu7R3L49sNsnJEibU1Exrxf48ENg0CCu9PXsCTz3HLB8eexVgO/Vy7wWfHa2Z4+zOl60awcMGcJsGLN4PMA11wArV5r3GLGgUSNm0Y0fDzz8MPDff7L9Ldbk5QGvvw6sWWP1SIRRUlOPPD7IzGSAdelS68ZkMDlyFkJYI5zuBQA/dK+/3pChCAEA8PlYvyInh5Xfb7+d6d21awMXXQR89hmwb585j22nYERGhrknn3bl9QKvvQb89ZfVIwncE09wu4yZBSgLChhEE+GpXZstfm++mRkGIrb89RcwdiwDfKeeCvz0k73mfRG8bt2AatW4GJWWxkyhm29mLawoIYECIYQ1tm4N7+fz8oBvvgH+/tuY8QhRWnY2V1T37AHeew+49FJWm2/TBrj7bh745eeH9xgHD3J/Y/v29jlBbd/eWSn4RiraguCUgo716gErVgAXXMBirUZnTrlcDJjddZex9ytErJk6lZ8X2dnAL78A55wDfPqp1aMS4YiL46LCbbexyPa2bcCjj7IuVpSQQIGwp82bAz4Az8vLw6ZNmw5fdu/eXe5t9+3bd8Rts53UEitQf//NQlcjRgAPPQT8+qv9otbZ2WzBFS6vF7jkEq54CWG2Q4e4F3HZMuDxx4F+/bhN4YwzgEmTmFocjLw84KyzWDF5yRKgb1/g7LPDz7YJV0oK0KTJ4f/uB7CpxCVb+8r90S0lbrfFzDGaad8+rgo5Rd26wBtvAAsWcKXSiIKcbjdT42fNAu6/nytmQojQffXVkccqHg+z1ABs3br1iGPT8uRkZx9xu31mZbiJwB11FLcTnXBCVLZWlplf2IfPB0yfzjfcrFksCjJpUqU/NuHJJ/HAAw8hJa3K4evcx/Urc7v4Ws3w5PMT8eTzEwEAOZ4sjL54NCZPfNG438FKublc9XnppeLVwLg4HvA1b86DSLtMYps2caXKiNZbmzczXTiKUr2EA+TnM3AAAD/8wFWFG27gSsKAAbz07s10RH+0ZobC/PnF3T88Hs6BbdoAV10F3HcfAxFW6Nbt8F7a4xOTsVXFIT4unkOPi0d6jQZlfiS1fkucuGv94f9n5WThT63huNKIXi/w1lsMtvbsafVoAte6NfDjj8BvvwFXX83Alb+AbHIytyrExfFzNy+Pr8HUVL5+a9cGzjyTWTNmbmkQIlbs3u0/APzTT1i0cCE6du6M1Gq1Dl9dtWm7MjdNqFYPq37dgLadjgcAFOTnoWp6OrZsXAdll2M7EXUkUCDs4cMPuYJz8GDxyeM77wA33QQcc0yFP9qhfXtUadQKaUMeqfB2rvZ94Wrf9/D/s757El06tA976LawZAmLsG3ZcmTKsM/H53PVKn5INWtm2RCPsGEDe4EbISsLuPVWYNiwqEr3Eg5TlKq+bRvw6qvARx8xc6ZdO2DwYKB/f6BDh+LU8IcfBqZMKZvin5/Py8svs/DVo48CY8ZEfkW3Vy/2d/d40AbA3t6XIL3TmRX+SNrIxw5/7cv1Ivf5kTimIIA2pnbk9QLnn8+5MzXV6tEEp1cvYPFituq67z7OtXXqsKBe48ZA/fr8f506zEaoUweoUcO4OVkIcaSffmKArnRL6OxsHK01kpJTUPWCZxDvquL/5wEk1miIGpcWL55lLv4ZrfOWSZBAmEq2Hgh7uOUW7lkvucKcm8tVkUr07dsX3h3rUJAZeAqWzs9F5pr5GDRoUCijtQ+fD5gwATj+eB7QlrevNi7OPvufAQYK8gw8gcjJYbBACDvQmkHP3Fzgn3/YoaNXLxY9uuEG4IMPGACoaB98djbv49ZbgVatzCuiWJ4uXQ4HJy7Ky0HcohlB/bh3zTx0iU+Ao0N3+/czWO1ESgHDh7N+wdKl3IL23nt83V13Hb936qlA27bMIJAggRDm+fLL4gy0krRG6l9/oVfvU+FdNTuou1TrZ2PUiGHGjE+IckigQNhD06Zlr/P5gNmzGYmtQHJyMvqecQY8qwIvauddtwBt2h2HOk6uPLxhA9ODH3ig8sJjmZksnmMXa9caWywsJ4cHwQsXGnefQhglN5fvwdxctvS84orAiwVmZbGY4pw55o6xtHbtDo+xP4DMnWtR4D0Y8I/rxT9hVK7DCyJ6vcC77wIzZ1o9EiHsr6CA9Vs2b7Z6JPaiNbenleZycWtP+/YYNfJ8qA2BBwp8uV4cWvcvBg4caOBAhSjL1ECBUuoYpdS/JS4HlVI3KKXuV0ptKXF9xfmMIvq1L2cLgMfDtNtKitVdNOJ8xG0I/EDat24WRo90eCT2lVe4WhnoCfevv5o6nKAsX278febksLCh3Qo3mkTmVwdxuZj2/fbbwHffBR8ky8nhAXgkJScfDuCmAugVlxDwipcvLweZG/6Dw/O1qGgLghHFV4WjyBwboAULmJnidjO7sWVLtgHcs8fqkdnD8uWcw4skJvIz4dprWa/ppJNw9tln49D6RfDlBPbZ4F0zD12OPwHVZbulMJmpgQKt9QqtdUetdUcAXQB4AHxR+O1nir6ntZ5m5jiEA7Rty0rb/uzYwYrOFejXrx8yNy8PaMVLF+TBs3oOBg8eHMpI7eOhh7jtIDU1sJ7nGzcaUzzQCIVF0gylNdNsP/rI+Pu2IZlfHcLlYrDzr7+Yxu4v/bQyOTnAf/8ZP7bK9Ohx+MtRedlQiyvO7iqSvX4B2sYnwMH5Wkc6cIBbRkRMkTk2QHFxzBLMzWVALTub9VWKqsHHaqvVItOns+6MUvw8GDQIWLmSnXPS0wEAVatWxQndT4R3TWALXlq2HYgIieTWgz4A1mitg+wfJWJCy5ZcwfInK4s1DCo4wE5NTcXJAe7xyt6wEEc3b4mGDRuGOlp7SEjgiceqVaxQXVlLLJcLmDs3MmOrzBaTGqdlZQHjxtknIBI5Mr/ajcvFFfmZM4FnnwW+/hrYuzf0jBcrAgUnnXS4kN/ZAA5tXR7Qipdv8c8Y7fRtByVlZwPvv2+vrCwRaTLHAuzuUrqtdIcO3CJasuhnTg4/jx99lEWUjdxq6DRdu7JY6AknMGD88cfMMCtl1IhhwLrKj2F9eTnIXD3P+TW2hCNEMlAwHMCHJf4/Tim1UCn1hlJKcmdiXYsWjLiWJyeHK+gVCHSPV8HaWdEVia1fn4VyvvmGHz7lBQw8Hn7IW62gwNzCbB4P+37HFplf7aQorXT5cqbiAnyfhtpqLinJmmJzGRmHuzRUBXBCfGKlK166IA9Za+fD4flaR0pN5fNQumK5iCUyxwJsFzplStnre/QApk4te/zh8fDirzVgrOjRg8W6//4b6Nix3Jude+65OLR2AXy52eXeBijM2Grfwdk1toRjRCRQoJRKAnAOgE8Lr3oZQHMAHQFsA/CUn58Zo5Sap5Sat2vXrkgMU1jpqKPKRqlLys4GXnyR6fPlCGSPl/YVwLtqFoYOHRLOaO3p1FOZ0n/77TxRKX1ikZ/vv6BOpG3dWn72iBGys4GJE5lpEQNCmV8Lf654jo3EQGOB282g559/Mq205Ou8a9fQsglSU4E+fYAZwXUdMETbtkfMy6NyvcCiircfZG9YiOZxcXB4vhbThFNT+fd87jlg507g9NOtHpWwgCFzbKDHsbt2AZMmAV99Zd/AVHnFPU8+mYsWpYMFcXHciy8qVLNmTXTs1AXedfMrvJ1vbRTU2BKOEamMgv4A/tFa7wAArfUOrXWB1toH4FUAXUv/gNZ6stY6Q2udUbt27QgNU1gmIYEtmiqSmwtcf325365SpQq69TipwhWvnM1L0bBRIzRr1izUkdpbUhJwzz1sh3XKKWU/sP/5h90krLRhQ2A1FcKRk8PK8rEh6Pm18HbFc2wEB2s5t/vIFFmjuFzA+PF873XqVPb7jRoxo6daNZ6EBnqfDz3ElbqqVQ0dbkASE4HmzQ//91wAhzYthi+v/KBuwZJfMaqSFTFbS0nh5ZxzgB9/5F7iyy6rfGuXiGbhz7EVHd9kZnJrS8+enCduugm46CKgZk3g8svZ/clORXor2oLTty/w6aecu4rk5UmgIECjRg4D1pV/DKsL8pAVDTW2hGNEKlAwAiVStpRS9Ut8bxCAxREah7CzEgekfhUUsCjM7PK3F1S2xytvzd+4cHgMRGKbNuVB7kcfAXXqFH9oK8UDXytt2FBpF4uw+XzAvHncjhH9ZH4NRoMGgZ+oB8LtBo49lvPSgw9WHAQ77jhg1izuV42r4OM3KQmoW5crdzfeaOx4g1WioGFNAB3jE5C99h+/N9W+AnhXz8JQ2OikJlDp6UD16sCttwLr1nFltHt3a597YRfGz7G5ufx8GjCAiyRXX81AYm4uU/UPHWIA4a23mFHUqBG31Fmdwl+rVuXHEGeeCXz4YfFxh8fDz31RqfPOOw+Zq+dC5+f5/X72hoVo3qKV82tsCccwPVCglEoF0BdAyU1NE5RSi5RSCwGcAuBGs8chHKBdu8pv4/Vypbic6PrAgQPL3eOltQ+5q2dhWDRuOyjPgAE86L32Wn5oZ2dzn5yV1q+PTBXkrCxWm69oS4vDyfwapLQ0ZtyMH88T/IpO1itTVMH6jjuAhQvLb/Fa2jHHMIhVp47/ugOpqUzhXbasuL6BlUoUNAS4/UAv/tnvTXM2L0FDAI7J14qP59+wc2d21tmxA3jgAaBePatHJmzC0DlWa+C334BRoxgsvPBC4Ntv+RlVXrHmggJ+lm3dCjz2GIOSHTsCr74K7N8fzq8WmlNOCex2AwcyyFEULLB6gcIh6tWrh2OObQPvhn/9fr9g7SxmHQgRIaYHCrTWWVrrmlrrAyWuu0hr3V5rfZzW+hyt9TazxyEcoKIWiSWtXcuqsX7UrFkTHTtn+N3jlbt1JWpUr4bWrVuHO1Jncbu5X/rff7k6aGZ9gEAsX25+RkGRgwfZQjJKyfwaJKWAYcO4Mvfnn8AFF3DOCTat3O1mYHP+fODuu7l1KhhNmzJY0LDhkT/rcgH33svMKbv0xy5R0BAAzgOQuf4fvyte+Utn4sK8nDLX25LLxW47c+bw7zhkiPlbooTjGDbH5uYyAHjmmcB77/Hk/2Dl7ZyPkJPDoMJ//zHTqF494KyzmJmQ538F2nC9ewd+22HDgMmTOe+uW2fakKLN6JHD4Fs7q8z1h2tsDYmhxS5huUh2PRCiYhW1SCwpKwu47rpyV4pHj/S//SB3zd+44Pyh4Y7SuVq14mrGyJHWjmP16sg9lsfDIInsjxRJScCVVxYHIzt2BN55B9i+nS28GjdmxkFF4uJ4gnn//cCCBVzdC1XDhmxX2qwZx1arFluM3XqrvdLdjz2WJyiF6gE4Ji6+zIqX1j5kL/8Dw7TFNVAC5fWyOO7nn9tr/7eITkuWsDVeVpYxr7esLL4vp01jwLNmTc5vc+ea+3oeMiS44PuFFwKvv87WgCIggwcPhmfVbOiCIzuB5WxeEt01toQtSaBA2EdlLRJLysoCnnjC77cGDRqEzNXzjljx0lojf/UsnD8shgMFdlFB5wpT5OYCY8dG9jGF/cTFMcBYWtWqvH7DBq7MnXkmA5alg5apqewX/t9/wC23GNOusE4d1ja4/35m2nTvHv59Gm3ZsjLV10fneuErtf0gd+sK1NI+OCpfy+PhSc/VV1tf5FVEN5/PvEy6Q4d4ef11bg1o0oRFUM2oC1CnDue/YFxyCfDCC8aPJUo1adIETZs1Q/amI0tf5K+eFRs1toStSKBA2EfTpoHvJ/d4uF9vx44y36pXrx5at2kL7/oFh6/L27kWqSmJOO644wwarAiJ1mz/FEn5+VyprahSs4h+J5/MrIHyKMW02qlTmSZ7223cR5yWxq0GjzzC7QItWxo7rurVWeegZk1j7zdcPh9/5xNOKJOSPxiAZ83cI1a8cpfOxEinbDsoyeMB3n2XK6V2bUcnRCCK6hls3sz3buvWrL/x+uvBb3MQlrpo+DAUrCmuJ6W1D9mr/46tGlvCFiRQIOwjIYHpt4HKyys3sl16j1fOqr8wfNgQKDul9Mai3bvDKyAXKo8HuPTSwDNWRHRJSwNuvz3w29evz6J2O3aw1deSJWzNasVr1ypvvsmTDa+3zP7nJgCaKnV4xUtrjbzlv+N8p2w7KM3jAb7/ntXls7KsHo0Q4SuqZ7BgAeeuunVZ3HjaNPkcdIChQ4fAu2oWtI9ZKLlbV6BWjeqxV2NLWC6GjnqEobKyWJBn+nRj77eyFokl5eUBn30GLFpU5luDBw+GZ/WcwyteBWtnY7hsO7Dehg3WFVPcsQN48UVrHltYq2ZNZhQEKyEB6NeP2U6xpnnzCos0XpSbjYIlvwAAcnesQVpeDhydr+X1MmOkWzdgzx6rRyOEcbKyGDT49ltg+HDOh1dfzSKeUp/Dllq0aIF69eoiZ8syAEDu6r8xMpZrbAnLSKBABM7nA375BTj//OK+v+edx7Y9RgmkRWJJ2dlsgVfqw65x48Zo2uxoZG9chNzdG5Hoy8Xxdmg1Fuus7KXs8bBCfaS3Pghrpabar0CgE/TsWeG3h0LDu/JvaF8Bcpf9huEFeXD8M5ydDaxYwXTtSNdSESISDh3iNoRXX2Xw1O1mtsExx7Ar0qBBrOnzyCN+t3aKyLlg+FDkr5nFjK01UmNLWEMCBaJyy5czxb9OHfbG/fRTrr5kZnJV//rrjXusdu2CW3HWmhkFU6eW+daoEcNQsPZv5Kz6C0OGDJZtB3awYUPgdSjMkJfHtlIidmjNvuUiOPHxPGkoZ95sAaAeNHK2LEPB0pkY7otQy1Oz5eUBW7YwWLB0qdWjEcIcRfUMsrOBnTuBlSuBv/8GvvwSmDiRbVonTbJ6lDHt/KFDkbN6FjO2UpKkxpawhAQKhH+7d7NKbVExnOeeYzrmoUNHrt7n5fEkfXbZdoQhadGiuH1ZZZQCqlThGHbuLPNt7vGaDd/aWZKyZRcrV1pbMCw3F5gyhSnGIvolJAAXXVR520PhXyXP3QV5Ocj84wMkZmciqvK1Cgr4ede9OzCrbD9zIaKez8f6BsIybdq0QbX0VBz87W2psSUsI4ECUSwnhz2l+/QBGjVi8a8VK/wWszqC18tCcUa0l2rZsuJCOy4XL/XqccvBxx8D+/fz8Utp3rw56tevB+05gB49eoQ/NhG+FSusHgFfrxdfLO3QYkFiIjB+vNWjcK6TT65wD/P52oesjQsxRBc4f9uBPwcP8vPwu++sHokQkSdBMksppTDi/KHwrFsgNbaEZcqvVCRig9b8MJg8GfjkE6abHjoU/P1s2AC88w5PwMJx1FFHpqYrBaSn87qMDGDYMPY5D7BF2W3jb8T2XbsRb0TPcxE+K2sUlLR+PfDWW34DTCKK+HzMNjK6pWG4Vq/mvy1aWDuOyiQmAmefDXz0kd9vtwFwfkISLsuP4raCHg8weDDTsC+6yOrRCBE5OQ5sdxplRl14AVatXoOMjAyrhyJilNIOqHiakZGh50mqsLHWrWP7q1dfZa0Bjyf8FdZq1VgAKj09vPtp2BDYu5fbCs45h/tke/dm0R3hLPv2sdhljRqstFy9Ol9rdlC1KgMXVatWeDOl1HytdVR/SmcopaN2hk1NBX79lYFGuxgwgK+9//6zf5HF775jpfRY78PucgEPPSQZKgaLhfkVcOgcGx/Pz+ukJKtHIoQIUbhzrGw9iCUHDjAw0LEj0KYNMGECsH07AwVGpGHn5AD33x/+/cycyQPo7ds53jPPlCCBE33xBdvKde/OVmsul73S/XNygDvusHoUwmxZWcCppwILF1o9kmK7dwOLFwM//GD1SCrXp4/0XQe4Zenee4Gbb5aWciI2uFz2yQIUQlhCAgXRLj8fmDaNK1h167Li+3//MZXf6LQyr5fVctesCe9+WrQAWrWy/0qb8O/QIWDkSODCC7kKeegQXxs+n7UdD0rLzub2gyVLrB6JMNuhQ0CvXuzgYgf79vFk86ab7H/SmZTEYK3RUlJ4OfZY5wSCPR7g5Ze5BcGM4ImVhV6FKC0+ntmnQjhcbkEu+r/XH/3f64/M3MzDX+cWyJxbGQkURCOtWa32mmuY7j18OPDttwwMZGWZ+9h5ecDVV5v7GMK+/vyT+8GnTLHPFoOKZGcDl11m/5M1Eb4DB4ATTww/kGnUWACu1k2bZu1YAjFqVPhbyoqkp/Nz6a67uFVt4UKgUyfnpDd7PMyWOussBkCDtX8/u658+CHwwAPAeecBbdvyealSBdi82fAhCxGS3Fxg7VqrRyFE2AZ+OBAzN8zEzA0z0ejpRoe/HvjhQKuHZntSzDCabN3KgoKvvALs2sXAQEGEe1sXFPBkccYM4LTTIvvYwjq5ucCddzKjJJSDZ6tozRTwzz4DhkpV4ai3bx+3wsybBzRpYt04MjP5b1YW97yfeaa9M6j69g1vBT0+noGA9u253efss9m6ssi33wIdOgCbNjkjaOfxAL/9BvTsCfz0U9k6J/v3A6tWsWjlihUMhixfzt8vJ4cp3Vrz719yO1Z6utSCEPbh9bKlsRBRwpvvhTefx6iuBJfFo3EGCRQ4XVYWV28nTmQWgVLWp3d7PMAVV/BAKUFeYlFvyRIWnNyyxVlBgiJZWcy+Oess56RAi9BoDezZw2DB3LlAgwbWjKFkts2qVby0ahX5sQQqJQU4/XTgq6+C+7nUVJ4IX3ABt1kce6z/21WrBvz8M9C5s3NOlLOzgUWLWCTzggu4pW/FCmZJ5OaWHwwAKm43LISdyNY8EQU+HfYpGj3d6HCQAACS4pPw2bDPLByVM8jWAyfy+XhQNWwYULs2T3JmzeJKhdVBgiK7dgEvvWT1KISZfD7gqaeA44/nypkTthqUJysLePBBq0chIsHnA3bsYLBg587IP/6hQ1xhB3gy+fzz9mvf6M/o0YFvP0hNBRo3Bh57jM/1q6+WHyQo0rw58M03fE6coig1+6GHgC+/BJYt41ySl1dcnyXYAq5OyKgQscMOW7WECNPQT4aWqUeQW5CLIZ8MsWhEziGBAidZtgy45RagTh3g3HOBTz/lCm5RGqudZGUBd9/N1TsRfTZv5n7v++7ja9DpB7deL0/YZD9mbCgo4FatE09kK9ZI2rePJ5L163Ob1tix9t52UOSMMwIvtufzsQjauHHB1Tbo1Qt48UVnZfb4fMZ1c3HC60DElm3brB6BEIZxJbhQNbmqbDsIggQK7G7PHuC554BjjgG6dOHXe/ZwpcLu8vKAW2+1ehRiwwYGmH780Ziq2u+/z9XBuXPNL44ZSbm5wJVXWj0KESn5+Xxv9OwZ2XT3evWYbbVsGYv4OYXbzTaT5VEKSEtjd52PPy7OmgjWpZdy65qTggVG0dr5QVcRXfLyWHNDCAf7asRXOPmok3HyUSdj802bD3/91Yggt9PFIKUd8KGUkZGh582bZ/UwIi83Fzj6aK54OXHvN8A00tmzWcRKWGPIEFbpTkvjh/6pp3JPbf/+3BscqH37gEsuYcDBydsMKuJ2s+bHGWccvkopNV9rnWHhqEyXoZSOwRmWkpOBNm2A339nyrwo3yefAJdffmSgOj2dGRqDBzPQ1qNH+CvjPh/Qrx8LBhrdxtfO0tOBv/4C2rWzeiQREwvzK+DgObZKFeDXX50V1BRCHBbuHCsZBXb20kuM5Do1SABI+zmrrV0LTJ3KA++DB/lamjqVB/R16wInnMCU+40bK76fn37iPurvvoveIAHA3+2yy6SfeSzJyQGWLgX69HH2XBsJZ55ZXKgvORk4+WTg9deZ5fbOO9zKYUT6fFwcA3aNG4eemeBEsvVA2JFsyRMiZkmgwCS5Bbno/15/9H+vPzJzMw9/XbqYRrn27QPuvdf5qd1a8yB8yhSrRxKbHnjAf1uzQ4d4wD9nDnD77dza0rw560osWFAc2PF6gauvBs45hycDsXACvW8fizSK2JGTw6r1/fvHxms8VGlpwJNPAg8/zG0bv/7KtqIpKeY81s8/c0UzlkhQXdiJxxN8QcPXXmMLWiGE48nWA5P0f68/Zm6YCYAtOIoCBCcfdTK+u/C7yu/guuuAyZOjJ+2yTh0eWJpxQCn827IFaNEiuE4YCQlcKUxOZsHMn35iZfhYW2l1u9myrkGDmEiNdWxarNFcLq6Sf/ONtHa1izlzgN69Y2MOqlIF+OOPmNqqFwvzK+DwOfbii4E33wzstjNmAAMGMDtm5EgG3atWNXV4QojyydYDm/Pme3Eg58ARvTsrtW4d20lFS5AAYGeGCROsHkVsefTR4Ktx5+czi2XvXh4YbNgQGwfopeXlAddea/UoRKR5vcDMmVwlLygw9r537wY+/1xWjIPVtSvwxhuxWdxQCDtYvjyw2+Xmso5Rdjbn0vffB5o2BT74QOY9IRxKAgUm+XTYp0iKTzriuqT4JHw27LPKf/iGG3iiEk08HvbU3rLF6pHEht27eXAdThp1LH+w5+UB33/P9nUitni9wA8/AKNGGdf2DgAmTWJhUdnWErzhw4Ebb4yNYEEsz7vCntavD+x2Tz55ZLvZ7GzW2RozhkVOV60yY3RCxA6t2Z586lRuARw61PQt6hIoMMnQT4aWqUeQW5CLIZ8MqfgHZ89mVXmjV7PsID+fWyqE+Z54wtiTnFjk8TDlUsQejwf48kse4Bp14vbuu/z33nvZhUQE56GHgL59ZfuaEJG2e3flx6QeD09c/BU7zsriFqIOHYC77gpuO6QQotiJJwJHHcVtPffey1ogJmefS6DAZK4EF6omV4UrwVX5jbUGrroqelO98/JYNf/vv60eifmWL+c+vQMHIv/YBw6wY0Y0bV2xyrZtVo9AWMXjAT78ELj++vCDBRs3chsPwPn9wguBuXPDH2MsUYp/jxYtort+hGQUCLtJSgK2bq34NgkJFR9z+Hyc+559lm2/f/jB0CEKERPq1WNXoKwsoEEDnk/VqGHqQ0qgwCRfjfgKJx91Mk4+6mRsvmnz4a+/GvFV+T80ZUr0p2Z5vWw/F+2r3enpwLffMvoX6WDBCy9E//MbKU7vOiLC4/Gw/d9dd4V3P198cWTrO48HOP30wFN6BblczLirVs3qkQgROxITWTurIklJQGpq5ffl8TAAP2gQMHCgBOOFCMbzzzM7u0YNYNYsBg5MZnqgQCm1Xim1SCn1r1JqXuF1NZRSPyqlVhX+W93scURaUnwSvrvwO3x34XdIS0o7/HXpugWH5eayeFosnJhs3Ai89ZbVozBXw4ZA69ZsDXnSSZELFng83HYQrVkp4gixOr9GlMcDPPcc02pD9fbbZd+TBw+yw8L+/WENL+bUq8duLLFQr0BYTuZY8MRk7drKb1e7duD36fEww7RlS86v0bjdVgijNWoELFoELFzIryMgUhkFp2itO5Zoz3A7gJ+01i0B/FT4/9j20ks8cIwFWVnA+PHR//u+9Rb30y5fDvTsGZnfd9Ik+cCNPTK/ms3jAf73P+Dpp4P/2Z07GTAszecDtm8H+vULr+hoLDruOG5DcAWwpc9pZOuBHcX2HJuVFVi2a8OGwd1vXh7v+667gLZtud9aCFGxdu0ikklQxKqtBwMBvF349dsAzrVoHPawfz+LUsRCNkGR7Gz+ztHshBOAV15h2t6iRcwsMDNYkJvLVc9Yeh0Jf2R+NYPXC9x9N9/Twfjqq/L31OfmcmVg1Cg5QQzWOecA990nmQXCCrE3x/oLdpbWrFlo952VBaxYAfTqBVx+uTW1nYQQfkUiUKAB/KCUmq+UGlN4XV2tddHGpO0A6kZgHPZ1333R1w6xMtnZwOTJ0V+TYdQodrK47DJg9WrgppvMe6y335YChrFH5tdI8nr5Hn7nncB/5u23Kw7eeb3AN98A998f9vBizq23AueeG52ZBcIuZI4FgJUrK79N8+YstBYqrxd47z2gaVPggw8keCqEDUQiUHCS1rozgP4AxiqlepX8ptZagxPxEZRSY5RS85RS83bt2hWBYVpk/XqeMMfiCV5ODnD11VaPwnzt2wOvvQbs2sX0ZbPcf79kE8SekOZXoNQcG4GBRg2vl91pPv648tseOBBYd4Oi2iLvvRf++GKJUsCbbzJtOTHR6tGET2tWshZ2InMswN7tlWnUKPygXU4Os2zHjAF69Ij+xSQhbM70QIHWekvhvzsBfAGgK4AdSqn6AFD4704/PzdZa52htc6oHUyBFKe5/noWiolFPh9be8RKm5zUVKBOHfPuP9ayUkTI82vhzxTPsZEacLTweoFLLmEmQEWmTgWSkwO/zzFjgN9/D398sSQpCfj+exZSK9lZwkkSE7mFYupUcz8jRNBkji2UlcWAZkUaNjSudWlWFjBnDtChA2sYZGcbc79FWQtduwI332zMfQoRxUwNFCilUpVS6UVfAzgdwGIAXwMYXXiz0QAq6BkYxWbPZqunWA0UAPzgueIKOck1wtCh4aX9CUeR+dViXi9w/vkVBzrfeQc4dCi4+zzrrMDSfEWxmjXZCSGQ9mxmSElhwCJYaWkc85gxwH//seitsA2ZY0twuytv59qwobGtmX0+zonPPgscfXR4i0r//MMtoLVqMZN17lzg5ZeBzz83bLhCRCOzzyrqAvhDKfUfgDkApmqtvwfwGIC+SqlVAE4r/H9s0Zrpq9LGDtizB3jxRatH4XzDh1t3oCysIPOr1bxe9gP/7Tf/369sBc6fzEygd29uVRKBa90amDIlsvUKlOLJ/uuvA1WqBPYz8fE86WrbFnjhBf6dX3wRaNHC3LGKUMgcWyQuDli3ruLbNGxozjZajwfYto1z7cCB/DpQL7/M91bPnqwX4/Fwji2634svrvz3EiKGKe2AYiEZGRl6XrS1TZkyhYXuZE85paVxsq5Vy+qROFdBAVC9enArmKJSCphfoi1WVMpQSkfZDBtZqalc0T7hhCOvnzOHJ/3BBoQTE4E2bYBZs7haLQL30ksschhKkCYYSUnc7vDTT8Axx/Bv1acPT5T8tah1u7lCOnQocOONQKdO5o7PIZRSUT+/AlEwxyYns47KtdeWfxuteTszM0QTE/nee+QRYNw4Bt7KE8gxUVwccOyxzDgIJStICJsLd46VPGUr5OZygpMgQbHcXNkvFq74eLYME0JEVlYWcOqpQJMmLK5XpGtXtoF1uwOvVQDwgHvxYmDTJuPHGu3GjgUuvNDctoluN/+2ixYxSAAA3bpxK+E99wD9+hXv105JAY46Cnj8cWD7dm5HkSCBcJqcHGD58opvoxRQo4a548jL43x7113MyqloETE+ngG8GjXK35bp8wFr1wLjx5szXiEcTgIFVpg4UfrElpabC3zyCfdpitCNHBl4CqwQwjgeD0/sS/cbv/12YONGnsC6XBWvWsXH88Ry2DBgzRqgZUtzxxytXnoJ6NIluOBMoNxuFrL85ReuVpbUowfbHX/3HavEHzrEgM+6dVwcqFrV+PEIESml5zZ/6tUzfxwAgwUrVgC9erHOVXnH1G3aAPPnA3Xrll9o0evl9qHKitMKEYMkUBBp+/dzhcnstEgnys4GLr9ceueG49RTpTCkEFZ6/fWyxQhr1gSeeoonjJdeymBAyXZ+cXEMIgwcyFXq99/nKrQITUICD/rr1TO2wKvLBTz/PGsKBFLdPSWFveWd2o1BiJIC2cvfpIn54yjJ6wXefRdo2hT48EP/x49Nm3JrwVFHlR+o9XqZiRRIG0ghYogECiLtvvvkRK48WgPLlgGffWb1SJwrJQV44AFz026FEOXbvx848UT/FcLr1mVxrZUrgREj+H51uYAzzmAV7s8/l6J2Rqlalav+aWnh31d8PFCtGjBjBiunCxGLtm+vfCGnefPIjKWknBzOu1dcwbl31aqyt6lXj3Ns69blZxplZXH7Zix3IhOiFAkURNL69cDkycb1g41GWVlM0ZVuEKG76Sbg5JMjW/1bCEFaA3v3At27l7861bgxK3AvXcqD12nTuN9WGKtZM2Dq1PDmwpQUBm8WLuTWAiFi2e7dFX+/aVPrigJmZbHteIcOwN13lz3Wrl4d+Osv4Pjj/c8JBQXcznDHHZEZrxAOIIGCSLr+eolUBiIrC3gs+rsNmSY+Hvj6a2DAAMksEMIKPh/b3nXvDuzYUf7tmjWTAIHZTjqJdYFCCRa43cBppzFtuXFj48cmhJMkJ7PwX0UaNjSnNkigfD4uND3zDHD00SwwWlJqKjODTj3V//GRx8MaJz/8EJnxCmFzEiiIlDlzOGFJoKByHg/w5JOyVywcCQncrzdypAQLhLBCQQFTdbt3B/bssXo0se3ii4FrrgluLnS5gFtuYdBV5lAhmC1VWZ2Chg3tUZPD4wG2bQPOPZe1X7ZtK/5ecjLw1VfAeef5f297vRW3gRQihgRQjSfG7dnD1FClwrtcdZWk0wcjN5cT9RdfWD0S54qL41aXatVYgCs+ntF2gHv6hBDmys9nwPPEE9mmq1o1q0cUuyZMAJYsAX79tfLtf2438N57wKBBERmaEI6QlcUaK8OHl3+bhg3ttSDm8bALScuWwCOPsPtIfDwv77zD1omvvXZkgfGUlIp/RyFiiNIOqDCfkZGh51XUK9VMkybxJD81NbAqx+XJy5NOB8Fyu5n+deKJVo/E+Xbu5GpAQgLw8cfArbfyQ19USgHztdYZVo/DTBlKaYtm2NiQlAQccwzw559AerrVo4ldWVlsm7h6NTM+SktM5InDjz8C7dtHfnwxSCkV9fMrEEVzrMvFdq+1avn/fl4eT7SLFiXsxO3mFqL33gMyCl9yWgMPPQQ8/njxMbrLxVa3NWtaN1YhDBLuHCtbDypzxRWMQGrNPq2hXiRIEDyPhxWm7fiB4zR16rDies2awOjR0oJSiEjKzWWngz595LPASqmpwE8/AVWqlP2eywUcdxzbU0qQQAj/fD6eVJcnMdGYTiNm8HhYrLBXLx7bHzjAjN9772XGkcvFTINRoyRIIEQhCRRUJi6Oadt33CH7FK2weTPwxhtWjyK6pKYCF1zAD0QhRGTk5PAk9IwzZOuPlRo2ZKZayc9ztxsYNowV0WvXtm5sQthdTg6Lg+7bV/5t7P4e8nqBd99lh4YPP+TCydix3IJQuzZw551Wj1AI25BAQSCUYquVZ56RlnORlpUF3HwzcPCg1SOJLtdfb10LIyFiVXY2MH8+O5Lk5Vk9mtiVkQG8+SY/z10urpC+9ZbMiUIEwudjwenyNGwYubGEKicH2L+fmQUnnQSsWsXiz9u2AU2aWD06IWxDAgXBGDMGeP99ySyItJwcBmqEcdq2BVq1snoUQsQerxf44w9W3Pa3T15ExrBhDBZ8/z23FwohApOdDTz3XPkLOE2bRnQ4YcnKYqHZDh14nFlZoVMhYowECoI1aBAwdSrTt0VkZGczJWzlSqtHEl1uucW+ewmFiGZeL/Dzz1zBirYaLGvXOidb4vzzuV9ZCBEcnw949ln/32vRgtt2ncLn45z8zDNA8+bAjBlWj0gI23DQO9lGevcGfv8dqFrVHv1iY0FODrtPCOMMGWL1CISIXR4P8O23LNgaLcVFvV6gdWu2gRw+HJg2jYUchRDRxesFnngCyMws+71GjZy5TdfjAbZuBQYOBM49F9i+3eoRCWE5CRSEqlMn4OKLeYDnpMipU/l8wJw5TBMVxkhOBi69lFWKhRCR5/EAn3zCQlrRECxwuZh27PGwDeuIEUD16syccEqWgRAiMAUFwAsvlL2+YcPw2olbzeNhkLNFCxYzly1iIobJGW44OnXivz6fnGxFQlYWC89s2MCCMyJ8114r3Q+EsJLHA7z9NnDrrVaPxBiDBhXPKQcP8vf77DNgzx5rxyWEMJbXCzz2WNmWrw0bOn9LVV4ejznvvBNo145FaIWIQRIoCEdRP/qdO1kcLiXF6hFFv717gZYtgTZtgOXLrR6N87VoAXTsaPUohIhtHg9bjt1/v9UjCd+AAWVr+BQUSF9yIaJRfj7w8stHXtewYfS0gM3K4rFmz55cqDpwwOoRCRFREigwQu3awJ9/At27S0cEs3k8jPQeOAD06MGWNiI8t9wCpKdbPQohYpvHwz2/EyZYPZLwdOt25DaD1FQG0iXrTojooBRQpw4zh3JzgddfP/L7VatGx1aqkrxe4N13ubXqo4+i7/cTohwSKDCK2w1Mnw6cdZYECyJBa/bA7d4dWLfO6tE424ABUmdDCDvweJhV8OKLVo8kdAkJXH1LSGBXlf/9D/jnH6tHJYQwSnw8sHo1O1KtXs1j35KUis4MopwcHndefjlw0kmyUCVigpwdGCkxkZHGSy6RYEEkaA3s28cVrA0brB6NcyUmAldfDSQlWT0SIYTXy3oFb7xh9UhCd//9wLhxnJevu87Zhc2EEEdyubhAk5AAHHUU0Lhx2dvUqxf5cUVKVhYwaxZrF0hXFxHlJFBgtLg4VoG9/XYJFkSCzwfs3s1gwZYtVo/Gua6+WrIKhLALr5cn2h9+aPVIQtO9O3uS16hh9UiEEEZTCli7tuLbNGkSmbFYJTEROPtsWWAR1vjmG55nRoCcGZhBKeCee4Cnn3ZmL1mn8fmYDvb111aPxLmaNGGwRQhhD14vcNllwBdfWD0SIYQolp0NrFlT8W1atIjMWKxSrZqzs74CtXEj8PDDQKtWzJZev97qEQmA2xQffxyYPNn0h5JAQWVyctgWJZQe0FdeyeInEiyIjP79rR6Bs0lRQyHsxesFLrgA+O47q0cihBCUm1t516mjjgKSkyMznkhzuYApU1i0MRodOAC89hrQpQsDBA8/zHoM770HHHssMHQosGyZ1aOMbaedxn+vvRb44w9TH0oCBZW59FJW169Zkyf+c+YEV+108GBg2rSy7aKEsY46itVoRejOOCN6P9iFcCqvFxgyBPjlF6tHIoQQVNmJYsOG0ZmW73YDN9zA84JokpfHdPazzgLq1uXv+M8/XCwtanWZn89ski++YBChXz8pVGuVmjWBY45h0O7ss02t0yaBgoosXcqoYW4ucOgQW8CceionwHvvrTz1qkjv3sBvvxVHH5UybcgxKSUFuPhifn3wIPDss/xXBCc+nvuiU1KsHokQoiSPh91J/vrL6pEIIUTl3aYaNoy+Y924OKBlS+DBB60eiTG0BmbPBq64gvVkLriAC5s5OSzYWJ6CAgawf/iB3R969jR9VVv4MWgQj9sPHQL69AEyM015GAkUVOS6646saFpQwDfPtm3cG9KuHYs25edXfl+dOwNz5wIXXgicfLKs3BopPx/4+29+/dZbTKE/9ljg33+tHJUzjRkj/YGFsKOsLOD007kVTgghrLRzJ+tDladhw8COjZ3E5eJqutO7uKxdC9x3H9CoEU8w33yTJ5mHDgV3P1ozYPDHH8xI7dyZrTLlGDIyzjqLGS4+H4u5Dx5c8XsyRBIoKM9ff/Hks7wnPTeXKTjz5gVeLb5lS9Ys+OILWbU1Un4+MGMG8PvvzCbIzwe2bmVq2EsvyaQVjPr1gVNOsXoUQgh/srL4/ly0yOqRCCGCEW2r64mJwPbt5X+/Xj0eezn9pLqI2w1MnAg0a2b1SEL3wQfAcccBbdtysXPrVn6mFBSEf98eD7BgAU9WW7cGPv/clJNWUcIJJxTXz8vOZsDmjjsMfxjTAgVKqcZKqV+UUkuVUkuUUtcXXn+/UmqLUurfwsuZZo0hZFoDY8fyhV+ZunWDbytXrRpbKErdAuN4PJygdu4svq6oH/nAgbIVIRg33wykpVk9ClEJR8+xInSHDjHVs7JiYkKIsBg6x7ZqBVSvHj0nzklJFbdITEwE/vuPWYqpqc4+3k1OZjbXqFFWjyR0n37KLQaLFvGksqjugNGysoCVK7kduGlT4J13oi+zxC4SE4ETTyz+v8fDc0uD2yqbmVGQD2C81roNgG4Axiql2hR+7xmtdcfCyzQTxxCab75hhc9AhNoC5sILGdWLtiizlbxeXkryeLiPqnVrRjtF5U45RbofOINz51gRngMHuIVNCGEm4+bYtDQWAOzcmavTTldQUHmdgpYtmdW5cyezPVu0YMDAace9VatyW6tTrVzJ1oaBLH4aJTMT2LSJi64NGwIvv8wAhTDW4MFHdtbzeoHLL2e2u0FMCxRorbdprf8p/PoQgGUAGpr1eIYpKGBtgooKeZTUvn1oj6MUI22yBcE4mZn+U51yclhX4sQTgRdflK0IlYmLY8Vbaetpa46dY4UxKtsjLIQIi+FzbN26wJ9/Aldf7fzP16wsYPXqwG7rdvPkZeVK4KefeHKTkmL/5yAtjdsxv/nGua0Qs7LYnSCSQYKSMjP5WXXLLXwun3jCtKJ7Malfv7LXeTysGbFtmyEPEZEaBUqppgA6AZhdeNU4pdRCpdQbSqnqkRhDwN5+G9i9O7DbulxAmzaV3648xxzDoEQ0RJedwOsFbruN1cMPHLB6NPZ26aVyEuIgjppjhTHatAl+25sQIiSGzbEJCcCTTwIff8wTUae+h7UGFi8O7meU4r7qTz/lavO99wJ16tgvgzEtDTj6aODVVznOrl2tHlFotOYWgG3brF8gy8oC9u8H7r+fAYP77gP27bN2TNGgWTP/QayDB4G+fQ3J4jB9hlJKpQH4HMANWuuDAF4G0BxARwDbADxVzs+NUUrNU0rN27Vrl9nDpKI97YFmEyQlMbUqHPfdZ79JMpp5PCx8eOyx0v+1IrVqAWee6bwUwRhkyBwbqcEKY6SmMutHCGE6U45jBwwAFi7kMaTdV9bLE+gWXX9q1QJuv50nsR9/zK1UKSncd22V1FR2M/voI2ZLDB/O9nNO9fLLbHdop5R/j4cZBRMmsOvCTTcBO3ZYPSpnO+usstfl5wNr1rDlZZhMDRQopRLByfV9rfUUANBa79BaF2itfQBeBeA3VKe1nqy1ztBaZ9SuXdvMYRZ77rmye9wrkpcXeo2CIi4X9z5JVkHkFG1FOOkk4PnnrY+02tX48fK6tDnD5tjIDVkYwefjQaw4UmYmkJEBTJ1q9Uii2/79wGOPsfDt+++zQFrJVtJRxNTj2GbN2MZ5yBBnftZu3hz+fcTFAf37A7/+CixdClx7LRfPIlVQWSk+9927c95YuJAnXk5fJJk3j+9Pq7YcVCY7m2ObOJFFD6+4Ati40epROdPAgUCVKmWvz84Gvv8+7Ls3s+uBAvA6gGVa66dLXF+/xM0GAQgyd8kk+/cDjzwS3JsqNxdo3Dj8x+7XjwXkoqUarlN4vWwlcvbZshXBnx49GPUXtuS4OVYYQyng3HMlE82fL74AliwBhg7lqqAw1qZNwLhxQIMGwIMPAk8/DVx1Fev/pKbygH/gQAYRpk3j7R0ciI/IHJuSwnpVL77ovGDBwYPGrlY3awY89RSwaxdXw9u143NixvaMuDgu1PXtC8ycyZboJ5/s/AABAOzZw4zQYBY+rZKTw9fQ229zO/bIkaxlIQLXu3f570MDAkVKmzSJK6VOAvA7gEUAijY73wlgBJiupQGsB3Cl1rrCigsZGRl6noEVHP0aP56RrWAmvQYNgC1bjHn8LVv4Jgl024MwTnIy2xZ9+y3QpYvVo7GXF15geqBdo9IRoID5WusMq8dRmqFzrFLa5BlWGCUtjZ1cune3eiT2c9JJLBYH8CTg88+5WinC4/VyIeXpp5nSWtS7uzwJCTzBK7pdy5bA8cfz0r49TwALV8CUUracXwELjmMXLuTrdc8e89rXGSktjSfZu3ZxYcGM4OWCBXzdffYZT+7DPRZJSODlrLMY7Aqnzpgd+XxceJw1y5lZPvHx3H5y2mmcc447zuoROUOnTsxO8iPsY1itte0vXbp00aarX1/ruDitGf8O7NKzp7FjePpprVNTgxuDXIy7uFxaP/OM1j6fsX9XJ9u/X+uUFOv/NhZeAMzT2vp50MxLFxs8z3IJ8NK4scxR/uzYoXVy8pHP1aWXWj0q5/v6a63r1tXa7Q7/tetyaV2litaJiVrXqqV1794xMb9qHcRx7P79WvfrZ8zzbfalalX+TdPStE5K0nrQIK3//Tew3zNY+/bx+KxhQz5esGNNSuKxzCWXaL12rTljtIN77nHGa6eyS1wcX1u9e2v9999WP6v299BDfI37eS7DnWMdWm7VBDNnMgoXTOqX0ZGua69lloKwhtcL3HUXU7b277d6NPZQtSpbGTm1MrMQ0cTl4udENKTHGu3jj8sWHpOCteG59lrWwtixw5isMq+X6ep5eewu9euv4d9ntKlalds27rvP/kUODxzg3zQzk6vXX33FTKeePctd3QxZtWos4LppEx/njDO4bSM5ueKfS0nhcf1VVwFr1wJvvMEtDtHohx/YUSMaMkB9Pr62fv0V6NOH2Ug//cRTX1FW//4ssG8COfov0rIlq+F/9RX32aWmVnz7lBTjU5YSEoD33rP/h0M083iAn38GWrdmMRgB3HijvCaFsAOfj+2uRFmTJh15gOx2s5aDCM3PP/OkKhpOOpxGKXbg+uEHbot0Sv2qopO7P/7gvmmD+rgfQSng1FNZpG31am4brlat7LYHt5tbI26+mcGF555jW75otWkTa7M4oS5BsDweHo8PHAi0bQt8/bW07y6tUyfTFhAkUFDaaaex5cujj3LiKS9amZwcfmtEf7p2ZQS/siipME9uLldQevViYZ1Yj2B26cI2NkIIa51yChCpLkBOsnYtW0GV5HLxZEsE7+BBHodIkMBaJ50ELFsGdO7svEKHWVnAOeewpoVZGjbkPvadOxnU6tKFx87VqgH3389AxUMPATVqmDcGO8jNZc2FaK9xlpXF98MFF7Dj3AcfAAUFVo/KHuLieHxgxl2bcq9Ol5DAlLsNG7h643KVTb3OyQm/NWJ5nn6aGQvCWl4vcO+97Eqxb5/Vo7HWzTdXnmUjhDBPejpTb0VZ77575AqT2w0884xkQoXqmmsYLBDWq1uXBTqvvtpZr+f8fLY7vOMO8x8rMZEtJufNA1asALZvB265JXItFq02bhyzK2LlpDkzE1i3DrjySnaemzzZmYUbjXbeeaa85iVQUJHq1YFXXgHmzy9u/5OaCtSrx0rwTZua87jVqrFVjpyYWc/j4R6p1q2BOXOsHo11RoyQzAohrJSUxIw3Udby5QzmN27MPdJjxnDVSQRv2jS2mXRC1f1YkZDAvecffcQTAafUDPJ4gJdeAr77LnKPedRRsZWR+8EHwPvvR+eWg8pkZjJr5KabuK3kmWdiOwvq9NMr70gTAtPaIxopIu0RAzFzJifpzp3NLyalNQ945s6VvTh24XKxnc748bFZTOyKK4A334ydqHUhu7ZHNJK0R7S55GRm9Tz8sNUjsSetY3NONtq+fcyU3Ls3Yg8ZC/MrYOBx7Nq1LLi8caNzTg6rVAGWLJEtjEZbtgzIyIjtk+OS3G4G1W6+GbjuOhYGjTXNmgHr1x9xVbhzrEPCkjZx8sncAxWJAxKlgLffjq3IqN15vaxEfMYZsbkVYfx4TsTp6cYVV0pM5H2lpvJgompVBuNMqt4qhCMpxUCd02jNvcOffmpugFGCBMa44oro3+fsdEcfzY4CgwebV7fA6OKJWVnAgAGmrHbGrMxMbot1SrAoEjwebpl69FHWr7j1VnZXiSUDBxqecSSBAjs75hjg+uudtS8t2nk8zCw55hhg9myrRxNZrVtzpWn6dE7ArVvzhL50teFAuVzAN98w6LJ4MVvffPQRt/tMmMC9jaNGMZ2qUyegSRMGEuLjGWCQ4IKIFZ06MaXWSXJyuGXp2muBSy9l69/nn5cTUbv68kumiMuWA/tLSWFdjhdfNC5YoFRxPS6js1gLCoCVK1k3QIRPa26t2rlTtoT64/Xyc+aFF3jceM01wJYtVo/qSFqzAO/ixcYG0M4+2/A6BbL1wO6ys5lKsn271SMRpblcrKx7yy2xu6K1Zw/w44/A55/z34ICFpWprLCMywW8/jpPJIKlNXDoEB979+4jLzt2AFu38v2ycycDGwcOMPqekMBgQnw876NorJVM0rGQGitbD2wsPR147TVg2DCrRxK4Xbu42rVs2ZErXm43T0Suvpr7SuvVs26Motju3dxycOBAxB86FuZXwMTj2IUL2UN9z57QgjyJiTx+yc3l+9PMNHaXC/j4Y2YXiNA9+yxw112y5SBQSUn83Bk6lFnBzZtbNxafD/j2W/791qzhcWlODhfeTjuNmevdu4fe3Sg7m3XuSswF4c6xEihwgunTWc1SJgX7cbuBHj344RftLXgqozUPWqZNY6rxkiVc+ShdPdvtBv73P2bLRHJsBw8eGVQoCjRs387gwrZt/H9RcCErC0hIgMrNjfoDWQkU2FhaGl+XTtmGtmQJ0KcP30flBeGSk3lycu65wD33AG3aRHSIopQBA3icYUFquAQKDHDgAHD++cDvvwd+nOh2FwfLExP5t4/E+UB6OrBokfMypOxi1izg1FNly0EoEhL4ubN1K1CrVmQfOzeXhSfvu4+fjZmZZW8TF8fP++xsnk+88gq3EgTrpJPYKaVQuHOswRuRhCnOOIMTw/ffm9uTVgTP4wF++43RwK+/Brp1s3pE1lEK6NCBlzvu4Kr/L78wpfXbb3nirTUDBJEMEhSNrWpVXgKNJvt8PACL9QCQsE5CAnDRRc4JEkybxsyHyrYXFK12fPop54e//uL2ChF5H30E/Pyz7B93sqpVuW1kwgTggQeOPIl0uRgI0Lr4fVe/Po9VZs5kAD2Si1BZWUyPnj9ftgsGa9cuPncSJAhNfj4/S6tVi9xjZmbyhP/RRxks8BcgKOLzFS+sbd8OfPZZaIGCwYP5/srODm3MpUiNAqeYNMk5B4uxJjeXE/ippwKPPy57xoqkpwPnnMNiZjt2AAsWcOJ75BGrRxaYuDi2SBXCKomJ3F9pd1qzfduQIcHVICgqcFhi9UNE0PbtbCUp2YrOpxRw223MDOnRg9k6t9wCPPUU2+f9/jv/3vv3A4MGcWFj+/bI/+19PnZuuOGGyD6u0xUU8G9aOkNTBKdjR+OLdfqzaxcXzOrXrziLoCLbtoX22P36GVrQUDIKnKJBA7bGuvtuKQZlV14v2ydOn86Vspo1rR6RfSgFtGrFixAiMM2aAe3aWT2KiuXmApdfzjoloax0ZWczo2DcOOPHJsqnNbNVDFp1EjbRs2f5gbfff2ddoL17rV2V9njY1eu007itVlTu7rvZ7UIyf0KXkMDWoma79VYWUiyZxROKnTtD+7nWrbnt16AgoGQUOMm117Llh7Avj4cf0q1bA3//bfVohBBOlZpq/1W3vXu5H/Kzz8I7KJk717gxicC8/TYDNHLiEf0OHWIw74wzWP3dDqnrHg8wejSzC6JZQQG3eLz/fujZptOmAc89J5k/4XK7WSzQTF9/Dbz0EgOw4XaQ2bMntJ9TilkFBpFAgZPExwPvvSftEu0uN5fFx/r0YdE+o1sNCSGin88HDB9u9SgqNnEitxSFe+KxYYOcsEbS5s1ceJATj+g3fTrr8rz/vj0CBCVlZQHPPGP1KIyXkwNMnQqMHMn98AMGcIvPiBHBz3MbNvBzwG5/OyfyeoGuXc27/0OH2ArYqHk1nC40554beuvyUiRQ4DTHH8/JRuoV2J/XC9x7L4vPCCFEoIo6Ahj0QW+arVuNKbCbkgIsXx7+/YjKac1jCNlyEP2uuoqp/bt22fPvrTUXVaLBoUPsfnX22QwOjBwJfPgh96UfOsSTx2++4QJSoHvVc3LY+lK2GxujVStzF1pvucXYv5XHU1zHJ1h9+kgxw5j21FM8sBL2k5wMVKnCf9PTgc6dmZorhBCBcru54mt3oe6hLE1rZiYI802axOdaOihFv08+sX/WSDirpnZx/vlst3fFFcwkyM72X3TQ4wHmzOGqdiBz59VXA+vXS1aqEeLiuPXGLHPnAu+8Y2xALimJ2/tCUaMG0KKFIcOQQIETVavGPTCpqVaPxBmU4om72238fRe1HmrZkm3BHn0UmDIF2LiRHxRz5gB33mn84woholeNGs5otRrqHsrSMjM5VwpzrV8P3HyzrFAK+zh0yOoRhO/XX7nlNJDfJScHWLWK1ffXrCn/du+8wwwF2XJgjLQ0diYzQ14eM0iM/lslJTEbKFSDBhnS4UECBU41ciTQvr2hLTCiUmoqqwDPnw+ccorxmRg+Hyf7lSs5qd94I1N+6tQx9nGEELHB5WI2gVJWj6Ryl13GAKwRn0N//RX+fYjy+Xxc+bRjCrowhxPmkGgIFHTvHtzt8/PZmrJLF+Cff8p+f/FiZhPYPRvESbxe4MQTzbnv994LvZVhReLiwgsUnHWWIVst5CzTqZRi1WKpVeBfairQtClX92fOBNq2ZcvCVq2YAeBPYmJogYRXXw1rqEIIcZjPB1x8sdWjCMyFFwILF/KAN9wMt1WrjBmT8O+FF4AlS0Lf8yqEGYLtLW9HffoEf+yoNbddPPvskdcfPMiK9RIkMFbDhszGNsOUKeZkaWkdXqCga1dDtphJoMDJWrUCrr/enJR6p0pJAapWZR2HVauA008v/p7LBcyYAdSsyYPatDQGB5o1Y4rOI48AbdoEF4XPyeE2ENnvKYQwwimnALVrWz2KwDVvDsyaBTz+OOfV+Pjg7yMpCTjnHOPHJmjVKuCOO2TLQaxxQkZBNJwQd+9e/gJURVJSgIyMI68bPTp6CjzaSZ8+5tyv1lyMNENeXnivhYQE4Lbbwh6GBAqc7r77WDwv1sXHMxAwbhzrA1x5pf+9ObVrcy/sG28As2fzwGntWkYEb7mFWRrBRobz8tjnVgghwpGeDtxwg9WjCF5cHDB2LLB0KWsrBJtdkJICPP+8OWOLdQUFwNCh4ff0FsIM0bAHv0OH0N5fSUkseF3Srl3SKtZo6elA377m3PeGDebNrdnZ4RcMvu++sIchgQKnS0nhyW0sZxW43WxJs2wZ8MQTlQdOGjdm4cE2bcpGgdu1C7795KFDfFwhhAhHUhJw2mlWjyJ0TZoAv/8OPPccM7YCKaSUmsr025o1TR9eTHrmGWYUSOV0YUfRUDMjMRE45pjgf87jYZChpNdfly3FRsvNZa0yMzRpwqwQA4oGlqE1sGWL8fcbJAkURIPTT2dajRkvVDtLTWVBx59+Ar78EjjqqNDv6623gEaN2KHg2muDfy7nzQPWrQv98YUQsS05mX3PQ0ndtxOlWORw+XIenFWUXaAUcOyxzqnJ4ERvvRUd6d0ieFWqcDXVzN7x4UpLs3oExujTJ/itHnXq8O9T0jHHADfdFNuLf0arVg1o0MCc+46LYxtSs95jEigQhnnlldiJQrrd3ELw2mvAf/+F30Zs6lTgmmv4hnz6ad5fXFzw6bMzZoQ3DiFEbLviCqtHYJyGDRnEffllHgyXzt4qKjj74YfO2EvtRFpLADuW/f038NlnzCoZP55F8lq25HsvIYHvyypVmMlkBaWipzZJz55lT/or06WL/+vvuYctcoUxTj7Z3Ptv2BCYNMmc4M727cbfZ5BibAk6ijVowGJ8d90VvQWLkpL44XbnnfzQM6LV4ezZ3IZQtE+uaK9RTk7g9+9ycQVt1KjwxyOEiE2dO4eXFWVHSgEXXcSst4svBn77jftvk5KABx9k9lYoRcBEYHbvli4Hsaxu3SMLOpd08CCwfj0DSWvXMgNo2TJeV3RyUnQM5PGY8zpKTweGDDH+fq3QrVtwe9WTkspPh09OZsu9M8+UbKBwpaYCZ5xh/uOMGMEW6d99x60ORtmzx7j7CpEECqLJuHFcvVmxwuqRGEspfmANGwZMmMB0rWBt2sQIbcksgRUr+CFa3kRc2d65xETe34cfMlIvhBChcGoRw0DVrcsDqE8/BX75Bbj3XqBePatHFf2WLeNnpxQyFKVVqQIcdxwvpV15Jds+163LgN7atSxUumIFi0Xv3cuT2cREdnwKdXEqJ4ddXqJBgwbcRhHoe83lKj+jAOAq+DnnsNC2kSeesUZr8+oTlPbmm8zYMfLkfv9+4+4rRBIoiCbx8YxC9uoVHZVkAZ6Id+zIrRXt2oV+P6NGsYVJgwacnE88kS0UDx0KfVxt2wLffBNa4EIIIYpoDQwcaPUozDd0KC8iMpYvlwrqIjj79gHvvss5ac8erpSWlp8PbN7MbIR161gsc8kSYM0aXp+VxRPhuDie5Ja36HLiicZkhtpF164MiAbC4wE6dar4Ni++yI5aEigIXUIC0KJFZB6renXgo48Y4DHqHOzQIb4XLdyeZ1mNAqVUP6XUCqXUaqXU7VaNI+pkZAAjRzp/8k1NZTXRzz4D/vgjvCABwMn2gQeYivnNN8Ddd/NDUOvQ7s/nAxYu5JaDX34J/X6EMIHMrw6SkMD0/FipMSMix85F7BwuaufYl18u/jozEzhwoOxtEhJYX+SUU4BLLwUefRT4+msGCw4c4LaG2bOBDz5gR6hx41jsr1kzHpsmJfEycmTEfq2I6Ns38Hm8WjWeWFakZk22jQ22XpYo1r17ZE+yTzuNn+dGzb1xcXw/WciSQIFSKh7ASwD6A2gDYIRSqo0VY4lKTz3l3EBBSgpT4h5/nNHpMFL631/0Ppo+2xRxD8Sh6aRj8f65RwMrV7LgSF5eeHvuvF5Gyb/9ltHDRo34gWiD/UQitsn86jCJiSym6kBHzLHPNsX7i963ekiipAsvZKaKBAwMFbVzrNbAk08Wr4a6XNy+Eiy3m+2nzzqLQYIXXmCx57VruZK+bRs7RV16qbHjt1r37uUHCtxubjFLSuLC1yOPVHp37y96H0333Yu4m7PQ9Abg/fbGDjfqpaQA/ftH/nGffRaoVcuY+0pO5gKnhazKKOgKYLXWeq3WOhfARwBiIO8yQqpWBSZOdFYUMj6eH0pXXcU9cGPHhtXu8f1F72PMN2Ow4cAGaGhsOLABY74Zg/fvGmB8P+nMTGDrVuC++xgwOO889hKXLANhDZlfnaRZs/AzpixQ7hwrwQL7UIrtEdu2laKRxoreObZq1eKvCwpCCxRURCnWi2rfPvq6nXTqxG0XSUlc8EpMZObFyJHsPPHbbzxeXLSo0g43xfPrRmgFbKgGjBkgwYKgJCZyK3akuVzAF18YE6CNjwd27Qr/fsJgVaCgIYBNJf6/ufA6YZThwzkRxzmgA6bbzcyBJUs4mZb8oArRXT/dhf+zd9dxUlZdHMB/d3tmgy5pFFEURVpBEAUUBMGgFbEwsLvrNV7FehULC1uxAzFQREAFQRTBoKW7dndmc+77x2+HDTYmnpw5389nPyyzs/PcnZ298zznnnuOr7B8kUJfoQ+3NfjDvPoNwSyDjz9mtdpWrRhZ3L3bnOMJUTmZX90iPd21RQyrnGO/vc2mEYlKpaQAX37JlsKxdmFmn9icY5XiFs2MDP4/N5ctqEVoUlMZmLvvPmab7t7NGg5vvglMmMB6WyEG7CqdX1OA204yftgxq7Cw8mKdVujcGbjxxuhbJmodt4GCGimlJiilFiqlFm63+UlyJaWA115z9r7X9HSmp33zDSfV1q0Ne+h1e9dVfnuWBav8WjNqvG4d21UedBA7Nvz8s2QZCMcoN8faPZh4FQgwqOtCVc6xVdwubFSvHvDdd6UXgMISrjyPHT26/NbVhQvtG4sbnX02cMMNrLQfRVZvlfNr9Oto8aNTJ67I2+X224GDD45uwba4OG4DBRsBNC/z/2Ylt+2ntZ6ite6ite7SoEEDSwcXM9q2Ba65JvqIltG8Xu7fmTKFKVjHHWf4IVrUalH57ZXU5TGVz8csg/ffZ5GTgw8Gnn7a9uIkIqbVOL8CFeZYy4Ym9lMKGDaM+1ZdqMo5torbhc3atWO2m9QrMEL4c6xbzmOTk4Fbbik9b4y1dtsuUeX8uk+ygkKSnGxPfYKykpLY3jKamnH5+XEbKPgFQFulVGulVAqAUQA+tWksse2OOwxJ5TdEcjLffG66iavtY8aYtjXi/pPuhze5fIDEWwDc/60ph6uZ1kzjW7OGP3+jRow8S7ReGE/mVzfweoErrrB7FBGrdI5N9uL+k2ou0iVscuKJ3N7ntMUD9wl/jt2zB1i82BF90Wt08cWl52Z79vDcRViqyvnV18PZmcJO4fEAffrYPQq2ZnzkkcizS4qKWPzTRrYECrTWRQAuB/AVgL8ATNNaL7NjLDEvLQ149VV7TwyU4h/tyJHsZHDnnaavaoztMBZT2t2AlnsVlAZa7gGmfAaM/cPUw4YmN5dZBm+/zYmsXTtmV+Tk2D0yEQNkfnWJunWBHj3sHkXExnYYiylDpqBlrZZQUGhZqyWmDJmCsR3G2j00UZ2LL2a1eQkWRCyiOXbNGuCEE4CGDfncH3wwswyvuAKYPNn2i4Fy0tM5rtRUjlWyCixX5fz6wOfu7Wpmpbw8oGtXu0dBl1zCsURaoH3DBmPHEyalXbBnukuXLnqhrLxGZ+hQYMYMFvewUno6iyo+/7y1RUX+/JMn4dnZ1h0zGunppfuVr7oKOPpou0ckSiilFmmtu9g9DjN1UUrLDGshj4dFw264we6RiHhUXAycfDIwdy5TW22kgJifX4Ea5tiUFGZ7zJhh5ZCqt2MH0KIk/X3KFGZACmd4/XXg0ksl06M6Rx3lrEKcW7ZwUTCSbcc9e3KujlC057COLWYoDPbcc3wzskp6OtC8OTBtGvDjj9YGCTZs4Eq9W4IEACd8v58FKI87ju2sXn6ZNQ6EELElEADGj7d7FCJeJSayXkHz5vYW+xJUUADMmgVs3Wr3SErVrw+MHcvzkj8MSsUsKmIb6cMOA3r1YpbprbcCO3ca8/jx4uyzuZjkhq5mdkhIYCc1J2ncmOf0oWZyJSezxWZCgu3tk+VVFi+aNAHuvz+qKqwhSUtjca4HHuA2g0GDrG3JtHs3q826tSVhcTGDA3/+ycyCBg2YKrpMMseFiBl9+/JvWwi7ZGSwE0JWlt0jEQDPk15+2e5RlHfbbRzXL78Y83iXXQZMmsStDPPmcSFp0iQGD0To3NDVzE4ZGXyPdZozzwQGDz7w96YUr5s8HtaUO/FEZhx+8gmwdy8Xem0kWw/iSXExV6rN2G+WmMiMhQsvBO69F6hd2/hj1MTvZ4rOsmWM0MeK4HPbti3w8MNMGRWWka0HwlCZmUwdHTrU7pEIwYvAE06wLXtNth6U0bgxsGmTtYsrNTn9dGDBAmDjAU0dwvPss8D111f+OvN4gPXr2cZThO6ee3hOKJmn5SUnc+uME4Oge/fyXN7v53VKu3acf3v3Brp3B5o1M/zvX7YeiNAlJgJvvml8IUGvF+jfn+lpTz5pT5CguJitxv76K7aCBAB/Nr8fWLJEIu9CuF0gwJTe667jRYEQduralSvZ0jbRfjk5wPff2z2K8u6+G9i1K/r6Vi+8UPUFrdbAo49G9/jx6JZbJDOtMi1aODNIADBjYPFiYPZs/r0vWcLrprPO4lYwJwUJS0igIN507syTVCNSltLTudfsyy9ZhOfgg6N/zEht3gzMnMlKp7HK6wXOOcfuUQghopGby4/JkzlnjhwJLF1q96hEPBs5ErjxRumEYLecHLavdJKjj+bqbHJydI/TsWPVX8vL48VSJIXe4llKCvDGGxLkq6hfP7tHUL2mTYFOnaL/m7KIBAri0SOPRDexeDxs7fXMM0zzP/5448YWqWbNeBEdy3u2iosZdRRCuF9BAU+QP/gA6NaN8+i333J1zQjFxSwU9vTTxjyeiG133cWaQnLRYa+vv+aFuZMYUduqa9eaX1uffRb9ceJNr148L4zlc99wZGY6P1DgMhIoiEe1anG/WLiTf3IyVxxuuIH7ycaNc1bV1SeeiO2TnA4dgEaN7B6FEMJIwa1Fc+eybkHbtqxhEE2q77ZtPIH873+5HUuImijF1cl27Vyz0hWTEhKAV16xexTG69Ch+tdVIMAtrCJ8//sfC4kLBuCdsHgZQxx0lScsNXIkU8HS02veE6MUL8CHDwdWrmQBFSemKNauHVkAxA28XhaKFELErtxcdou57DIWNoukd/LcudwStnAh540uMV8nThglNZUr2lJUzj5+P9PwXVBoPCxHHsn5rTLJycAllwANG1o7plhRpw4zfGPx3DdcdevKgprBkuwegLCJUsD06TwpWLAA+PFHbiPIy+PJgs/Hnrfp6UD79sCUKdXvMXOKkSM5Yf74I1fqYkVREVurCCFiX04O/33iCWYGhEJr4MEHgfvu48UGwEDB0UebMkQRoxo04BaY7t1LX4fCWnv2MOAXSyujtWuzDsbvvzNrouxHZiZw++12j9DdRo/mue9PPzE7I1716WP3CGKOBAriWa1azBIYPrz0tq1bgd9+Y1XOhQu5vWDIEEdW4qyUUsCrr7INZPBkORZ06gTUr2/3KIQQVvrjj9Dut3s3MGIEA6Rl5z2fDzj8cHPGJmJX+/bAe+8BZ5wRW++jbpGby3TyWAoUAMADD9g9gtilFPDaa8zciNe/2YwMaR9uAtl6IMpr1Ih/aDffDLz/PnDaae4JEvh8wJ9/8qNLF04asSA9XbYdCBGP9uyp+T6LFjEY8MMPB7Yfa9JE9q6KyJxyCvDQQ87cZhjrtGbG5+7ddo9EuEmbNmyZGK9/s8XFQO/edo8i5khGgXCfoiJGTpcv53aJVauAjRsZhfd6GdjIz+dHLCgq4sqOECK+HHpo1V/Tmh0Nbryx6hUkN2wXE851xRVs3fnGGwcGoYS5EhJ4nnPVVXaPRLjJzTezGOaaNXaPxHqpqUDr1naPIuZIoEC4zw8/sNhXZYGA7Gzrx2O2bt1YrEYIEV+6d6/89pwctoP9+uuqgwTJycBxx5k3NhEfnn4a+PtvYP782Am+u4HPB7z0kgQKRHiSkxnY69cv/rYg9OzpngxoF5GtB8J92rVzVltGM2VkABdcYPcohBBWy8gAjjnmwNv//JM1WL78svpV3rQ0ySgQ0UtKYn/7Jk3i533XCTweppELEa7jjmNh79RUu0diHY+H26WE4WTWF+5z0EHxc8JSWAgMG2b3KIQQkVCKF+yRtK0KBFjEtKzXXgO6dgXWrWOHmspkZgIpKcAhhwA9eoR/XCEqysoCZs3ia0uYz+MBpk5lJXshIvH443wdxYvERKlPYJI4udoSMUUp4O67Qy/Ykpjo3sKGPXuyO4UQwn28XmDmTOCee3jSFmqAMzER6Nu3tGNBXh470Fx66YFZBGlpPE69esCYMcDLLwObNwO//sqWZEIYoVUrYMaM+C2UZhWPh6njI0bYPRLhZrVrA88+G1mQ2o2Ki9nxQRjOHYECrYGPPwZOPZUv/hEjgJ9/5u0iPl13HV8HNUVMExLYF/qII3jy7SaZmbLtQAg3q1uXaaDXXQcsWQIcfXRoF1qpqeyJDbBY69FHs12dz8c5LSuL9+nVC/jvf9n5YPt24M03gbPO4nGFMNqxxwJTpsTXSqVRQgkSejzA229L8WJhjJEjgc6d3XfuG4kuXeIn09hi7nhWV6xgCtYXXwB797JtX79+wJln2j0y58vNZcGrWKMUT1g6dWKabVVq1wbmzQPeecd9+7UKCoAhQ+wehRAiEh4Pq8YHiysdcgiwcCFw330MFlR2UpOQwAyimTOBFi2Ajz7iKsny5dyKcPDBwNVX8/a9e4E5c1js7LDDpIiTsMbYsXwNGpFZ4Lb35Gi0bFn9c+bxANOmAUOHWjcmEduU4haW6s6RY0FKCjBwoN2jiFnuCBQ0blz+JEhrXgB/9RXw7rv2jcvpFi5k4b+zz2aLvViTnMxew337Mv02M5OFlxIT+Xnt2jyRbtOGaZN33umutMkTTpA9oUK4VSAAjB9f/raEBOCaa4Dff2ehwrJpoSkpQPPmwOLFXLkFuLo4aBBTkdetA1auBB59FDjxxPi6yBLOcv/9QP/+klkQjrp1gQULgGbNDvzb9XqBDz8EBg+2Z2widrVuDdx+u7vOfcOVlgb06WP3KGKW0i5I3+/SpYteeM01wEUXHdjuIysL2LZNTprKKi7mqtVDD7Gd0WOPxX6LncJCtm+aOZMn3EccAZx8MieQoKIi7vldudK+cYYqM5OtkYYPj+5xNmzgPrUXXuBzVKcOt2IcdBBPWJo2BRo1Aho2LP23QQM5ASxDKbVIa93F7nGYqYtSeqHdg4g1p5zCPd1VCQSAJ58Ebr2VgfCxY4FJk24VSEAAAQAASURBVKQmiRFWrWLNBqnRYB6/n+07//or8oWIfv2gZs6M+fkVKDmPXbgQ2LcPGDUKmD2bW4m8Xm6t7d/f7iGKWFVYyHPfVavsHok5UlLYGj3WMyciFO05rHsCBQsXciXlzjvLF3NKTQU2buRJgQD+/Rc4/XTgn3/4PNWuzcJWZS+Y49mCBVypd3p/2dRUYOfOyArRFBezddqjjwI//sjbqup/nZTEYyUlMVOnqIj3TUri8/TllxH/CLFCAgUibJmZrClw8sk133f7dl4sxEvRKbP99BPnro4d+bnsWzXP1q1Ahw58DYcrIwP44AOok0+O+fkVKHMeC/C9dtIk1hd57z3gpJPsHZyIfT//zEw0p5/7RqJjR2biiUpFew7rrnfQ664DLrkktlNoovH661xJX7KkNFJ9220SJCirWzeu3Dn9OenXL/wLh337gLvuYmbA6NFsZ5WfX3WQAGBgIDeX+5337ePrJjWVaZKXXRbdzyBEvEpJ4d9wKBo0kCCBUZYtY3CmoABYuhR45BG7RxTbGjUCvv02stdvRkbofyOxRingxhuBXbskSCCs0aMHzwudfu4brsREZu8J07gjUFC2X/Qjj7DYSzBYEAhwr3o827MHGDaMQZTcXK4oA1wVlou9Az36qLODTZF2Ozj7bG432bmTaVjhSknhCd/ddwNr1wKnnRb+YwgRzzIzGWR78sn4qDRdE61L34+sMHRo6dzn83EuW7LEuuPHow4dWCw4nO1qHg8LIkq2hxDWeeyx2NtWmp7Ogr+TJnER0Mr3mzjhjll63brSz5UCXnuN0bHERO7hzsqyb2x2mz0baNuWKeJlt2R4vcDNNzv7gtguWVnsmODU56awMPwI6TvvcGWnuuyBqijFN4+xYxkguOEG2eslRKjS0piF078//w63bQPGjLF7VPbx+9mm8cwzWRPF62WLru+/N//YFWsS5OVxu6Iw1+DBwH/+E/p7aiAAXHihuWMSQpRXqxbw3HOxlcHm8wHnncds2o8/5hYLYSh3BApyc3kRFJSUBHz2GXDTTfGbWlhQAFx7LVuC7Nhx4AViQgJbc4nKnXFGabDJaU45Jbyo75YtwIQJ5QNFoUpPZ4X1X34BXn4ZqF8//McQIh5lZLAjzx13MMD29dfsUODEOcVKL7wAnHsuq7jv3cv3ql9/5XNz333MMjDL1KnM6lCKwc5mzYCHHzbveKLUtdcCI0bUHCxQioEFqSslhPWGDwe6do2d96miIi6u+f28Dnr/fbtHFHPcESgIBICLLy6fUuL1skVPkyb2jcsuf/8NHHUUI4OVFSbxeLj/LSPD+rG5hVLAK684r1tGZiZw/vmh319rbjkouz0nVA0bsm/z3LmsbSGEqJ7XywyCYcMYrN60iV0LGje2e2TOcdJJlWck+f3Agw+WFlg1w5FH8vGvvpqrTH/8ARx6qHnHE6WUYqZex47VZ6R5vaw3JYSwnlPPfY1QXCyBAhO4I1AAcNX0lVfsHoW9tAaefpppnMuXV129NDEx9tshGqFFC+5hddIWhOJiYMCA0O8/dSpTrQoLwztOejrrGQwaxDcOIUTlEhL499KqFfDAA+yy89FHrKwvfzsHOuII9u6uTFJSZBXyw3HkkdyL+9xz0mrSasnJwPTpLHJY1d9Go0bM5hNC2KNVK2bCxdIWhKCdO93RAt1F3BMoyM3l3umcHLtHYo9t27hSc9NNTDGvKn0zLQ245pr4rtsQjmuuAZo2tXsUpU49NfRI7/r13F6Smxv+cYqKeCwhROXS05mdNXo08N13wOrVDMDWrWv3yJzv6qsrPwktLmbxXRG7atdmx53MzAO/lp4OXH+9BNiEsNv118dmRrbWwCef2D2KmGJKoEApNUkp9bdSaolS6iOlVO2S21sppfxKqd9KPp4L64Hz81kwJ95Mn870yblza74oTEzkXkERmqQk4K23nFEJNiuL6bKh0BoYNSqyLQcAX08NGkT2vcJ2ps2x8S4xkRlGhx8OPP44+8S/8QbbqsrFTehGjaq8+nRhoQQK4sHBBwOff37g+2ogAJxzjj1jCpPMsSKmJSWx6KwTzn2NlJfHc3phGLMyCr4BcKTW+igAywHcUuZrq7TWHUs+LgnrUf1+4KmnuJIaD3w+tskbMYJFoWpKL09LA6688sDKz6J6Xbrw5MXu/rLFxaH3lX7mGeD33yNrBZOayg4Hws2MnWPjvU1ZRgZXOy+4gFt5/vwTuOiiyldFRc0yM4HTTz8wuFJQIIGCeHH88XyfCm7tS0xkdo57aieZcx4rhFN068ZzQbvPfY22dCmwe7fdo4gZppwdaq2/1loXlfz3ZwDNDHvwwkKmNca6xYu5qvX226FXs09IYDqRCN+kSfbWKlCKBdKSk2u+76pVLFZZVXZJWlr1E39iIo8lXMvwOTYry1m1Oqzk8XA/+44dwPPPsy+8iN7ll1f+mtq2zfqxCHuMHw9cdhlfBykp3OrnEqaexwrhFI8+GntZBampbBkfz3JyeB357rtRP5QVy0jnA5hR5v+tlVKLlVKzlVLHV/VNSqkJSqmFSqmF5UofFRUBM2awnVusmjcP6NULWLeu6oKFFaWmApdeKvtnI5WVBbz4on0XSxkZbClWk0CAGSaVbTlISOCEP3IkT9CCFdorqlULaNcu6iELx4h+js3KAk4+OT6DBVoDY8bE3qqK3Y49FqhTp/xtXi/Qtq094xH2eOghFv7s2JGFJt0p+jnW7CKeZlq5kluxunXjucrtt0fWjlk4T1YWW9rG0nt/djYXWWNdQQHwzz/swPTII8C4cUCnTnzfrVOH8+5FF0V9GKUj7GmslJoJoLKeULdprT8puc9tALoAOENrrZVSqQAytNY7lVKdAXwM4Ait9b7qjtVFKb2w4o0dO7I3cyzuGz3jDFbVDofHw8BC/frmjCle9O8PfP89A1JWyswEdu3ivrHqTJrETg0V36S9XqBnT6Z6HnIIb9u1iz3En3qKAYa8PAYTJk4EnnzSlB8jFimlFmmtu9hwXOvm2C5d9MKffwbOOgv45pv4OQn0eoGbb2YFaGG8hx8G7rqLc096OoNR778fm+/b8czn4zlIVb9Xrav8ml3za8mxrZ1jFx5wJutMRUVsM/rBB/zYtYu/w+AChcfDufOJJxhkjfeta26nNbe9/vCD9ee+ZvF6uc0tlCxdJwsEgA0b2Olu+XJuq/j9d2YW79jBv8WEBP5tFhRU+hAKiG6O1Vqb8gFgPICfAHiruc/3ALrU9Fid+TIu/5GervV77+mYk52tdVragT9vdR+pqVpfeaXdI48N69Zp7fWG9/xH+6GU1uPH1zy2P//U2uM58O/g4IO1/u67qr9v1y6tb7uN901O1nr2bOOerzgAYKE2aZ6M5sPQObZzZ/6whYVaDx5s/d+AXR8NG2rt8xn4ahHlbN2qda1aWvfrp/WcOVoHAnaPSJhh6FCtmzbV+oEHtN60Kaxvder8qs2aY50qEND63Xe1Pu00zv9ZWVonJFQ/f6ana33EEVr/9JPdoxfR+vff2Hrfz8qq/rzYSQIBrbdv13rePK1feUXrG27Qun9/rVu25Dm718v30Yrn/yF+RDvHmjW5ngLgTwANKtzeAEBiyedtAGwEULemx6s0UABo3aiR1nl5Bv/GbPbGG1pnZIT3QvB4tN6yxe6Rx45Jk6ydMDMztZ41q/oxFRZq3b49gwoAg0m1amn9/PNaFxWF9nPt2aP19Omh319orbUjT2QNn2PLnsQWFmo9aFBsnTRU/FBK6zp1GHwT5pLgQOz7809eNCYmcuGib1+tP/pI64KCGr/VifOrNnuOdZpAQOtLL+XvMJL51OvVetgwLrQI93roodh5309I0Pqyy+x+RsvLztb611+1fucdre++m38z7drxOU9J4Tl9enrpeb5BH9HOsWblC00GkAngmwrtY3oDWKKU+g3A+wAu0Vrvivgo2dlMfYoln3zCIhShSklhS71GjcwbU7y55hqgeXPrjpeQwArR1bn/fmDNmtI6BJddxq0mEyawOGEoatUCBg0K/f7CycybY5OSgI8/Bnr3jr0iRwD/hurVAxYsYMFYYS7ZZhD7Dj8c+PZb1krKzwdmzeJ+2Xr1gCuuYBcR97HmPNYJbrwRePXVmttvV8XnYzvMdu2A226L/HGEva69Fmja1O5RGCM1lTU1zHTllTUXTZw+vfK6Affey/Osf/7h309BAbvb5eby8t5BIq5RYKVKaxQEpafzAipWesJfeCHw0kuh3z8tDVi9GmjSxLwxxaNFi3jxHmoxyUglJLAl25QpVd/n99850QDAKacAkycDrVubOy6xn517aK1S6f7ZwkJgyBDuWzT778AqiYms4/Lzz0CrVnaPRojYMmMGcOaZ5eeLpCTuE27dGrjqKmDUKBZQKxEP8yvg4BoFd9/N2kdG1aXxePjx+OPA2WdL/QK3WbiQiwRufs/3eoE33mCLXjO1aQP8+y+7zT3wwIGLcH//zfbrNgfOoq1R4P6/4MJC4JZbar6fWxx0UOj3TU4GzjlHggRm6NyZhd3MroTu9XLlpTqPPw4ceiiLLE6fLkECYY3kZODTT9mBxUmZBQkJDBA3b86/hcxM3ub18gIkK6vyv9ukJKBxY3bMkSCBEMYbOJAtRsvOF0VFvOj480+uWDZqBAwfDsye7biVs7jzyCPGBgkA/q537WLWY4cOwE8/GffYwnxduvC6wo1dgJTiucG4cWwNeP31hrQHrFKPHiw2OHkyu/xs3lz6tZwcFu+NgcLQ7s8oAPiC/vXX2Egjfeop4IYbmL5Xk+RkYP584JhjzB9XPMjN5cnLZ58xjW77dkYIzfxDr1OHlUuri7rn5XGLiUTmbREPK17VrnYVFHDLyo8/2rvKkJ5e2h70iisYzAsqLAS2bgU2beLH5s3A+vXMtlq3jv+vXRv44gsJrAphtqq68wQFT+gzMqC2bIn5+RUAuiQl6YWHHcYA5yGHcDWyaVOgWTN+NGlibYX2Z57hhZTZc7rXy25STz4JtGhh7rGEMfbtYxB+l4t21AQ7hiUl8XyguJj/93iAuXNLs3KNVPZvKCmJrUM/+ADo2xcYOpQdpCprZW6xaDMKaujF5hIFBcCll3LF1e3q1+ebRSiBAqWYHn/vvTxxdmsbEK0ZwTz5ZP5rlUCAAaYvvwQ+/BBYtoxBp+xsa1Y6EhKYhllTAMCNkV0RO1JSmMkycCBXh6x84wumLR9yCGuHjBjBC4yKkpNLT7iFEPa64QYG7KZMqTxYoDVX3EI5z4kVxcU8x1i2jP9PSeE+6oQEXtjk5fFCo1EjBhDatAEOPpiBhWbNeFvTppXPf+F69VVrggQAf//TpwNff8093bffzp9TOFdWFvDii9w64oYV8dRUzinFxQeen/j93A7199+8n5E6d+a5h9/PzKk9e4DBg5mFOW+eI4IERoiNjAKAUcuPP2bk0s2+/ponw3v3hv496ekMMLzwgjU/f3Ex8Oyz/HjgAUbOonHPPVx9mDsX6NnTkCHW6NJLgddf55t0fn6V/UdNlZHBiGOPHtYfW4Qs7jMKgvLzGcybP9/8N8DMTL7xn3suU1jbtzf3eEIIY2kNjBnDAs2VXZB6vUDfvlDTp8f8/AqEeB5bUWIiV0QTE3ne5ffzYqd+fW5TbdUK6NiRQdSUlNAe8913WQDbjuwwj4cLH489xvRwyZJ0tv79uQBbVGT3SKrm9XJBIS+v6vP4YAHwRx4x9th+P4MqFZ+flBR7rimqEG1GQewECgCmyqxY4ayq7loDu3czLbbsx6ZNTInduJH/D1YK3rWLaSv79oV/LK+XF9rPPcdotBnmzuWbzObNTNX3ehl1fPLJyKJ1773HwEizZnw+rKqQnZXFzAE71a8PbNsmVcEdTgIFZeTlAQMGcJ+/0cGC4Paao4/mXuahQ0vnlLw8pvk1aAAcdhira5cpiCaEcKCiImYizZ1bfr4Injc8+yxUYmLMz69AhIGCUKSlAd27s5BkTbVkPvsMGDnS/kJ1wRozL75o3eKQCN/69dzS7dQuFl4vg2WrVtWcneTxMOhhdCeE1q2BtWuNfUyDydaDsrZtY8eACRPMPU4gAOzcWfnF/7//ll7879rFC/7ExNIUs0CAkaaKL+qMDGDDBk6eNUXvqopW+XzAd98BRx4JTJwI3HWXcSlemzYBl18OfPVV+VQkn48r899/zzehQw8N/TEXLQLGj2c08Morrb1gTk21N1CQnMzVFgkSCDdJS2PWU79+/Ps1IliQmck58uKL+VFZsc6HHgIefJB/NwkJnHe8XgZEjzqKwYXDDuNHy5bOChYLEa+SklgQtWdPptwXFPCE/ZZb2EZP3v+il5fHLK8TTmCLyqrO+b75hlsd7Q4SALzw/PtvBp1POom1uVq2tHtUoqLmzbm1+c47nRcs8Hq5jWXjxtDar/r9LFC+fLmx23m7d3d8oCBasZVRALBX/Pr1PPkMR1ERi9dVvPjfsKF05X/7dl785+TwhDW4AhYIRJ++XqsW98p36MCiW1UFC4JBh+Li6iNowRY1Tz4Z3QVpQQHTde6/n/voCgsrv59SPN7TT/PivyYbN/IEf9cu/jzr11vb4vLgg1nozCqZmfydpqRwYhkwADj/fBYzFI4mGQWV8Pt5grd4cWTBgmCmQK9ewNVXs+1nUhVx640bGYCsbq9kSgrf/IuKOGe1b88WiE7q1iBEvNq9m/t5N25kV4Qy5wjxML8CJmYUBKWmAl27sp1txfO9uXOdW4E9WIfm8st5QSr1C5yluBg44gjgn3/MP1ZGBq8xQskOeOklYPRoboG+7rrQAmAeD3DRRcD//ld6m8/HGmUzZnBuCvf1N3kya7I4uB6BZBRUlJ8P/Oc/wMMP8wI+uLq/dSszDrZsKb3437SJF/+7d/PFkprKCUup0qIYVV2w5+cbW4hHawYBvN7q75eczNX7k0+u/vh5efz62WcDU6cymhyuL78ELryw9Pmpjta8z8SJjBT/979V3zc3lxcZwToMJ55obZAA4Mrl3XeHNrlkZvLio0uX0FZRk5L4e/T7WeX3hBP4Mx53HKPmsooi3M7jAWbO5Ov6999Df5PMyGDa6eWXM1AWSjvYK6+sOQhbUFD+PmvWAEuWMCgnhLBXnTrAggU8DzviCLtHE5vy8xm4feYZnocF/fILA7FODBIAPMcuKuIF1wsvAI8+ykCS1C9whsRE4M03WTjdrGyUjAxeA9x0Excm166t+torM5NdyXr35v8POYQLBaGMze/na2zECF4fPvcc8NFHvH5RisVXw9WlC4/v4EBBtGIvUJCXxwnn8ssZRT33XF60KcUXXl5eaduMivx+e9Ky0tM5rtq1Oc6MDFbPrCgxkfv9unZlC47HHmNwIy2N/wYLxQQ/UlL4EW69gm3bmIXw00/hv7n4/ZWPPSgQYPrPv//y95CZyRVFq118MYsoVibYp724mG+wY8cyAyAjg6+rl14qPymkp5cGlzp14n179eJeKImOi1jl9XKrU9++DBZUFbj0ePh3P2AA/9ZPOCH0k8CffmKkP9xiSkVFPGmO90BBUVHVmRpCWKl+fX4I8+TmAjfeyPPENm0YLD3pJOeljVcmeP595ZVc6HvxRZ5HCft17szgzSuvRHZBXFmHj/R0Bgfat2dNohNO4Hn0sGE8j96yhecNQUlJDDh+/3354saHHBLe+YHfz84E+fkch9ZcgL344sg6ing8MR0kAGJx6wHAF9TgwdwHd9JJ3CrgFMELeL+fBfzatweGD2fl+3bteJ9WrXghXdn3/vori4uY6fnngauuiixjIisLeOcdvlFV5oYbGPEOBiDq1+cqgx3R4yuuYASxoKB0K4nHw1YqI0fyTapiy8mcHG5b2LOHk1yvXtyvfdxx3B8tUfCYEw+psWFvPSgrN5dv8n/8UTpnKMVAQr16PPEbP56fhyMQYL2Vv/6KbFxjxwJvvBHZ97rZtm3AW29xHl+zhnvDDz7Y7lEJUal4mF8BC7YeBCUksBPC66/zvCScDlpOUtIVA5Mn85xY2CsnB2jblu/3CQk8b87L4zlzMBidn88Fs7p12eazRQu+97RqVb7FZ5Mm1XfpWLuWwYldu/j/1FRm437/Pb+3rKIijiHUYIHXy59jxYrS65C0NGDp0vDfJ3NyeI6ybp01LdUjFB9bD4J1AEK5X0YGL8IDAaaE2FnUKimJESq/nyfJ3btz4uvencW3nnmGe2U+/7z899Wrd2CgICGBF6RmBwkAPofJyZEFCvLygD59Kv/aq6+WDxKkprJNoV0X1zfeyOyANm241+mss/h7qW5rQEYGt1YUF8vqiBAA57hZs/h3/9dffMMcNowBgh49It9qM3Uq34AjNX9+5N/rZpdeysKyhYV8/7v1VrZEE0LEvkCA+8mPOcZRLdrC5vNx+2v79txKceed4dceE8bJyGB3gVWr+L68bh2wYwfQuHFpAKBpU16/RLu9tlUrYM4c4NhjeR3SrRvwxReVZ+gmJXHRbvPmmh/X6wVOP52tOc84o/T27t3DDxJoza3dW7Y4OkhgBHcECoK9Yr/8kic+wTTvwkJGgvx+pp8MGsS+n8cdVzqhDBlizaqSUjxmYSEvsjt14v7dHj0YsKisaN1337FeQvB7girbr5+ayqrfVqhVK/KL906dKq+zMG8eT2DLbu1QioVF7NK8ObtShJuaKwUIhSgvIwOYPbu0I4IRrQuffDK6lNl//z1wbo0Hd9zB7RqFhXyf/PRTYOVKvkcKIWKfG7YahKK4mOeMkydzK8Ijj7A9t2Ru2sPrZcH1Dh3MP1b79uzi8eWXrF1Q3ft4mzY1Bwq8XuCCC7g4W1jI68Xp0/m1W24Jf3xPPMHab0bWqnModwQK6tThnvzCQmDhQqaq79nDlKrDD2dgoKq94CNH8kRp3z5jxxTcl15YyBf0CSewBVC3bkyxCSWitmAB77dqFdPWgyqm1ijF1bojjzT0R6hSVlZkEcG0NG6jqGjtWuDUUw+s/9ClCy/W7ST7d0XQ+vVciX37bW5duukmu0fkLhkZ5aP00Tr/fL6BR1qEKy2NbZOOPtq4MblBx47sUnP77XzuCgv5PL73nt0jE0KI8OXl8ePKK3nOdu65do9IWKFLF37UpEcPbsuuqsac18vzuTvu4LVNSgowbRoXkT/9lAvM4fjxR7Z3dUKrUQu46yopOZmpKOE46aToIz6pqfwIVrHv1YsX7t268QI/ku0N27cz0OH1Ml23bKCgYiXwtDTrsgkAZhREkkqTkHBgbYJ9+7jdIju7/O2ZmcA110Q+RiGiFQgw8PjRR3zT2LSJbyJ+P2tpCHtdeCHf2CMVCHBr0WOPxV9A8Oqrmar5ww/cu/nHH3aPSAgholNUVLpvXYigBx7gVuD//IfbbcrWK/B4gIceYiHyis4+mx/h2LqVmepxEiQAgNjP3/F4mHEQqsRErqinpHDvzWmnsdXfl1/ywn7lSu6dPe88tvmJtAbCggUMAPh8XPUqq1Gj0j7jSnH8HTtGdpzVq8NPQ8vKqrozRHU8nvIBj6Ii/kFt3lx5jYnBg8M/hhDRyM0FPv6Yhe7q1mUg8ZFH+HcSbId62mn8EPbyetkf2eOJ7PtzczlXN2zIFfXKCsTGKqVYVDYjg6/zr76ye0RCCBGd4mJ3110Q5khJAW6+GVi+nFsKkpO5GOnxsGB5ZUGCSF1xhfEZ6g4XH8ssY8bwwrziBXOwFWGwhdQxx7CuwLHHMt2lbl3zxrRxY+ke0kWLyn9t2LDStOe0NEbDwrF2Latev/QSayC0bctUmVD3DdeqxbGFa+DA8lsWLr+cK7YVMzqSk5lWXF3VUyGMsm5d6ZaChQsZhKtqok9LY59d4QxXXhn+/FdWMJPpsce4p7BzZ7ZiGjIk9msX1KvH9mgJCQduZxNCCLeRQIGoTtOmwCefMOtk61ZeYxjd8WfWrPDbNbtcfAQKBg9m1dSydQUOP5zbB4L97ps3j75SZzjGj2cHgD/+YFuOslq04B6sF17g2Dp3rvnxdu9mj9MXX2RLLK1LL9BXrGD6/5w5lRcarKhWLT4v8+YxYyKUPcJZWawmGvTMM2zPU9n3JiYCl11W82MKEYlAAPjlF+DDD7kve/NmXiwFX4tVbUXyeoGnnuIKtHCG2rWBCRM4n0Rzghj83nnzSi+eL7iA81Astw5s2tTuEQghhHHioHiciFLduuYs9G7bduA26jgQH4GCxo15oqkUL7wPP9zetokAI10zZnD7QrAHZ9lAxb33sqLmww+H9niPPsr7VpYJUFDAXtqXXcZU3JokJrLa6Pbt3L/98svA4sVcgatqG0NeHtO4AWDmTOD666vew3P44cChh4b0YwkRkpwc/r1Mm8a92Vrz9Rdq5DcxkQG5cePMHacI3403As89Z9zjBd/on3qK7wtHHcUsg2HDSrd8CSGEcJ68PLtHIOLV/Pk8R4izYFXs1ygIuuACprsfeaT9QYKgJk0YLKhX78BU6IYN2Q2hW7fQHqtx4+p/rqSk8Go1AGzTOGEC8PPPLPT2v/+xs0NqKrMzyjr8cGYi/PMPMwuqChJkZLDQlhDRWreObZN69mQhm3PP5b7sfft4MRhOelhqKjNgrMwqEqFp0gQYMcL4goSFhTzpXLCAbVrr1+f+w3/+MfY4QgghjCGBAmGXuXO5KBVn4idQ4FTdu7OOQK1a0T1O69bV7/mvX5/BkkjVq8fvnzuXqdyTJwO9e/OYKSnAmWdyX9CJJ1ZfPDEQAM46K/JxiPgVCDBodeONfL23a8fPf/yREd5IU8K8XlbNbdnS2PEK49x1F+eZqtrgRis7mycAzz3HWjXHHMPCSEIIIZwjjqrNC4f57rvKC7PHuPjYeuB0Rqxitm5ddUvD9HSm2BqVSVGnDmssjB/PThCzZjFoMHAgtytUNY7ERGDUqNDqJAgB8OLt66+Bd99l9g0Q3paCmigFHHIIV5KFc7VpwwDlxx+zSOv8+bzd6BTAoiJ+/P47cN99wGuvGfv4QgghIhdnad/CIYqLD6wnFyckoyBWtGpVddHB9u15EW+GWrWAoUO5neCPP6rvlpCaamybEhGb/v2X+8ePO46ZLOPHs/ZAdnb4WwpqkpbG7QoJMhU6XlYWa0jMns3Xh5knjFoDH3wgJ6VCCOEksvVA2OHvv43f/ugS8flTxyKvl5kDFWsdeDzAs8+au/f6kUd4Ul1TSljTpkzpFaKs4mLuE//wQ+D994EtW/h6Db6ezGqH5PWy6Obhh5vz+MIc69ax+KDZEhOZxTJsmPnHEkIIUTNpjyjsMH9+1dnSMU6W0WLJnXdyhTQzk/9PTAROOSW09oqR+uwz7h+uqYWi1wtcdZV544hFxcXsIDFqFFfWv/zS7hEZJzubwaURI7iV5eST2ed+7VquGFixD7FxY+C228w/jjBOUREv3K14fWRnG9ttQQghRHQky0vY4fvvq6+/FsMkoyCWXHcdWyB+8w0ruP/+O/DYY+Ydb8kSYPTo0E7aAwHg7LPNG0us0BpYtIgtKd96i89bTg5vP/tsdsKItvClXdauBT79lD/X4sXcimJXT1qPh1sOqisAKpznjjvYlaC42Jrjff89sGcPULu2NccTzrZwIQPyXi9rm/z3v3aPSIj4IoECYYc5c+wegW0kUBBrPB7gtNP4YaatW4F+/UKLsCkFDBni3gtcK6xYwcJpL7/MApF5eQdeDOXkABMnAm+8Yc8Yw1VczHSt4JaCrVut2VJQE4+HHTy6drXn+CIys2ezRauVVa+TkvjavfBC644pnOm339jVJxjcbNYMuPdeCTYKYSUJFAir5eQAGzfaPQrbSKBAhC8vDxgwANi9O7T7p6cDV15p7pjcaMsW4O23geef577r4uLqL57z84GPPuIWhFNOsW6c4di3r7RLwZdfMjDg81m3AhyKWrWAhx6yexQiHDt3sgWr1a2xcnO5/UACBfFt2TKgT5/SIEFWFrv9SJBACGtJjQJhtUWLuMBUXbH2GCaBAhEerYExY9hjPNTq87VqAT17mjsut9i3j3vzn3+eK1QJCeFd/Ph8ztuCsGYNtxS8/bb9Wwpq4vUCb74pLTrdJDjn2PWaWroU2LCBK8gi/ixfDvTqVVoo2OMBPv+cWw+EENaSQIGw2o8/Wr9I4SCmFTNUSt2tlNqolPqt5GNQma/dopRaqZT6Ryl1slljECa4+27gq69Cb1Hj8TCbwMyuC27w3XfAoEFAw4Z8PubPZ4ZAJJNPTo4z2kzm5ACHHcb2m7fcwp+poMC5QYLUVBbCO/FEu0cStbiaX59+Gpg3z74TRKUYXBLxZ/Vqtmndu5f/93qZYXL88faOS5guruZYN4nTVV1ho2+/jevXndkZBY9rrR8pe4NSqj2AUQCOAHAQgJlKqUO11g7KTRaVevddYNKk8C5uAwFg/HjThuQK06YB551X2hki2j12+fnc93/OOdwCYpf167lvyy19jb1eXnTGjtifX//4A7jxRnuj+Xl5zAC66Sb7xiCst24dcOyxwK5dzGrxeoErrgDGjbN7ZMI6sT/Huk0cX7AJG2jNIrZxzI72iEMBvKO1ztdarwGwEkA3G8YhwvHLL8D554d/wn7CCVxFj1dffMFASU3tI8Pl8wFjx5amw9ohO5stON3A6wVefDEeqtfHzvzq87EIqhNS/rZsYVDus88Y/BSxbdMmBgl27OCJYloai/c++KDdIxP2i5051o0kUCCstGFD3BfQNDtQcLlSaolS6mWlVJ2S25oCWF/mPhtKbitHKTVBKbVQKbVw+/btJg9TVGvDBva5D/diNzMTuPpqU4bkCrNnA8OHm3ehk51t7xaEnBz7jh2O5GQGrM44w+6RGC3i+RVwwRx72WXslOEEBQVsOztmDPemv/VW6DVanGzjRs5TcvJdats2oEcPvvYCAXa+OPRQZtQ5aAtdQXEBBr4xEAPfGIicgpz9nxcUyx5uAxk3x5o90nghc5Ww0vz5PIeMY1EFCpRSM5VSSyv5GArgWQAHA+gIYDOAR8N5bK31FK11F611lwYNGkQzTBGN3FzgpJMiW7lOTQX69zd+TG6wYAFw6qnGZxKUlZ/P1m0zZ5p3jOrk5HC1zelSU4GXXip/28aNjh+7mfMr4PA59v33gffec862lmDXjpwcFu+8+GKgeXNuSXDrasPWrUDnzpynatUCBg9mLYadO+0emX127mQmwebNpb/zevUYJEpLs3dsFQx9eyhm/zsbs/+djWaPNdv/+dC3h9o9NNewdI41dujxSwIFwkpz5rhnUcwkUdUo0Fr3C+V+SqkXAHxe8t+NAJqX+XKzktuE0wQCXIUNtu4LR2oqcMkl7klNN9IffzBNNTfX/GP5/VzlXLWKGRxWyslxfhp2ejrwxBNA48Zs5/nuu6xTsHQpL/ImTLB7hFWK2/l13bryNT2cKCeHH9ddx0Ket9wCXHopkJFh98hC4/MxALxzZ2lmxPTpzC4oKGCR0jFjgNNO4+cOWkk31ejRrL0SfE7S01mI1sHb5/xFfviLmLXmSfLYPBp3ids51s1iIZNLuMesWY5fVDKbmV0PmpT57+kAlpZ8/imAUUqpVKVUawBtASwwaxwiCtdfD8ydG9mqnlLARRcZPyanW7EC6N3b2sr/dm1B6N7d2YGCxER2ZGjQABg4EGjShK/ppSVT0YoV9o4vCjE7vxYVsTOFE+oShCI3lwGou+/m6+vOO1n8zsmKixkAXrXqwJPunBwGCpYsAe66C+jShT/XpZey8nOstybbsqV0xdLjYdHY9u3tHVMV3hvxHlISU8rdlpKYgvdHvG/TiGKLq+fYjAymSyfFYAd0CRQIqxQVAf/8Y/cobGdmjYKHlVJ/KKWWAOgL4BoA0FovAzANwJ8AvgQwUarFOtArr3DFNdJVvc6dgRYtjB2TGwweXNpKyyp5efZsQTj4YODZZ1ko0KkWLQLOPhv48kumiJfN8li1yr5xRS8259c77uAbc7gZTHbz+XiRPWkS0KwZcNVVTF93oiuvZDplTQHg/Hz+XFu3AlOmMLhQuzbw9deWDNMWnpIVea8XePRRe7vK1GD4tOEH1CMoKC7AWdPOsmlEMcd9c2xGBtCuHc/fXnzRcdtlDOG29wbhXkoBWVl2j8J2pgUKtNbnaK07aK2P0lqfprXeXOZr92utD9Zat9NazzBrDCJCc+cCEydGHiTIzASuucbYMbnF4Yfbk6bk8zFV2MpMBoCtwoYMceYJSSDAj6qek3XrrB2PgWJyfp09G/jf/5y95aAmeXnMhnjuOaBNG3aKWbPG7lGVeuIJYOrU8J/jQIB1aoqLgWXLzBiZM3TuzJPD889nFoULeJI8qJVaS7YdGMw1c6xSDGx17w58/DHw11/AWWcBLVvG5tZPySgQVklMBG67zdmLYRawoz2icLLVq1ncKtrU3yFDjBmP21xxhX37lLOzuVpotZdecuYe3poCNlu2WDMOUbOdO4Ezz3TPloOaFBQwaPD660xdP/98u0cEfPopcOut0QVilIrNdOag88/nHP7EE3aPpEafjP4EfVr2QZ+WfbDh2g37P/9k9Cd2D01YITGRAfqBA4EffgB+/pl1R4L1RJo1i72L6qQkoFUru0ch4slFF8VmwC0MEigQpfbuBfr2ja7CZ3o6K4KnpNR831jUt29p+qrV8vJYrO/bb609bno68Pnn7ou6xnN1d7NEUpFaa3uyYaxQVMS/y9des3ccS5bwOY42EJOQENuBgi5dmNXighPDlMQUzDh7BmacPQMZKRn7P69Yt0DEmJQUBgjGjOHf9fTpzISpqGlT53SNMUJyMrMk5s2zeyQinqSncwHOiVmzFpFAgaCiIu6v37Il/AJ1SUn8I+rbl6lvDz9syhBdISGB3R5SU+05frALgtUXXR06cE+vm4IFRUXWdKaIZRs3Am+8wWrxDRuytVy4nn6aJ3+xXCivuNjeysnffGPM8xvrGQVCOJXHw/fXiROZ+fnaa0DbtlXfPy3NvkULo6WkAIccwrbTTsxeFLHt6qvjp/NPJeQdX9BNN/FkPTWVNQYSSmJIxcVcJSwo4GSdkcHiHrVrs790gwZA69ZM2Tz4YFt/BMe48EJ7gyX79rGY2ssvW3vciy8GZswAvvrKHb3l09KATZuqP9kS5W3dCnz/PfDFF7z43LWLKz05OZwzTj89vMf74w/gxhtjZ8tBVRISOIfaFUA0ilL8fQshrJGezuDcDTewu1GtWqF/b8OG7u8Bn5rKFq2zZ4f3swthlPr1WRR76tTIsiZdTgIFggYNKr34r1On9KNuXf5bu7asJIWqRQvgmGO4Z9AOwS0IZ58NnHiidcdVinuyDzvMuRXfy0pMlEBBTXbu5AnaF1+w2v22bQwYls1YCQaFUlMZoAqVz8daJrEeJAD4WouVQIG8DwhhvowMftx5J3DeeZGlPjdvzuwDt0pLA446itsp7ar9JATA+j6vvy6BAhHHTjqJH8IYV1/NIih27bsOdkFYudLaN9isLOCzz4Djj3f+BWAgwECBKK+4mKv8H33ErQWpqZUHBio67LDwes5fdhkzFOJBQgKft8xMu0cSHQkUCGGu9HSgSRPgvvvYvSCaehlt2jDQ60YeD2uGfPVV7GyhEO7VqhULh37ySfjbs11OahQIYYahQ+2fTPbuZcDCap078yTH6fUK8vIkUFCZqVPZ3m/NGq6ChxLsysgArr8+9GO8/z7w3nuxVWyrOomJ7tiOUxMJFAhhvGCLw65dGaBdvhwYOTL6opqHHOKKwpwH8HiAXr24vU2CBMIp7r7b/VmBEZBAgRBmCFYltvNNOi8PeOst7im32jXXAD17Orv7RWEhsHat3aNwlrw81isJt4WeUmxvGIp165hKG02bPrcJBOwNFGRkGFdbQAIFQhgj2OJwwAC+Ty9YAPTvb1zhtCOOcF+1dq+X2a3Tp8flRZlwsKOOYpZLnJFAgRBmuewy+9/o/H5g1CjrCxopBbzzjvOLD7l5/6YZnnwy/C0jycks4BnKa72oCBg2zPnbUoyiFFfEBgzgfmG7nHOOMX+LklEgRPSCLQ5HjQJ++w348ktmExjttNOYmeD07L4gr5f1sj76SIqmCmf6z3+4PSiOSKBACLN07AgcdJDdo+AWhGuusf64desC999vf7CkOuvX2z0C59i7l1tGwl3pT0xkNe5Q3HEH8M8/rIMQ67xeZtXMm8d9jXae+Hq9DNwZkcYrJ/BCRCbYsvDii1k/6I03gHbtzDueUsALLzBLwekp/F4vs9LefVeCkcK5evcGWra0exSWkkCBEGa66ir7o/l5ecCbb1pX1GjLFmDSJLbLvPpqriI7VbwU0wvF/fdHVtG3UycWzarJ7NnA//4X+1sO0tOBI49k6uycOeyA4gS9ewOjR0eXihwIyEm8EJFISABuuYUFYp98Emja1LrjTpvGlGmnBu29XnZpevXV0tbcQjiRUlxQiaMuHPIXKYSZxoxxxuqp388UxNxc8x7/nXfY7aBVK+Cuu5jW7/M54+evyu7dgNZ2j8J+hYXA5MnhFxfMzGR/75rs3MnVoljecpCezpWGN94AliwBTjjB7hEd6IknIu+8kJ7Oi5ujjjJ0SELEhaOPZqvDOnWsP3ZKCrc3HHaY8+oGeb3AhAksoGtUbQYhzHTaac7fVmsgCRQIYaa6dbk/2QmM3oIQCAA//ACMHQvUq8d2kHPnsmibWy4IleLzEu82bowsoJOUBAweXP19tGbAzK5WoWZLTwcaNGCgZdUq1mBw6glvZiYDGeFkOQUDIK+/Dvz5J39WIUR47F4p93qBWbPYwjY5ma2M7Q4aeL3MOnzsMefOmUJUlJjIoF+c1CqQQIEQZrvySmf0T8/L40VCtFsQVq5kCmXjxsCppwJvv83AgNUFE42QmsqL5Hi3axdbIYYjNRW49NKaU9F37QJmzgz/8d3A6wWuu461LsaPd0crsgEDgIcf5nYRj6fqdOT0dKBRI+DZZxkAOf10OZkXws3q1AEWLwZ27AA+/RR44AGujh50UGnwwKrtCV4vzyPuv1/mFeE+554bN/V6JFAghNlOPNE5ewODXRCi2YJw+umsQbB9O4MDbk7dT0gANm2yexT2i3S169JLa75PvXq82HR6Ma1web0MDtxzj3P+vkM1cSIv/n//HbjttvJBA6+XFxSTJjEAcs457giACCFCk5UF9OnDIOcnnzBYvnMn8PnnwIMPMiuqaVPzggceD6vH3367sY8rhFVSU7ntMtbOayohgQIhzJaQwD14dqf5Be3ZwxOESL3+euwUcikqkkABEFmwp1cvoFmz0O47YQJw4432F/Y0Smoq0L07i5K5Wdu27EQRDBrcfjtP4DduZBAoTlZMhIh7mZmsMXTNNWxPuGEDs8GmTwceegg44wy2eE1KYvAg0qKoHg/w6KPAtdcaO34hrDZxYlxkw0igQAgrTJhg/x7FoLw84LXXWJE9Eh07Aj//zPoLbp8k8/Jk60EkMjKA668P73vuuotV990eLEhI4GrbJ5/E1kp727YMFFx7bVyskgghapCRwYDwVVcBH3wArFvHhYYZMxg8GD6c9UtCDR54PMAzz4SWiSaE09WqxVanTlkENIlDrlyEiHEtW7LqsVP4/cCIEZG3qjvsMOCXX4CGDd19sVRcDKxZY/co7NeoUXgXh15v+EU6lQKef57dAKJp0We3rCzgu++cUXdECCGslJ4OHHccay9NmwasXcuCwF99xe1KI0aw81EweBB8X/F4gJdf5nYtIWLFDTc4ZxHQJLH90wnhJFdd5ayU/Wi3ILRpAyxaxEJIbu6tLoECFqYMNc08LY2v5UjeHBMTgQ8/ZIs9N0bhPR6uprVsafdIhBDCGbxeoEcP4PLLgXff5XtqdjbwzTfcZjB2LPDee6yPJEQsadIEOOssdy+Y1UACBUJY5fTTnVX4Ly8PePXVyLcgAEzBXrgQaN3anRd+gGw9AHjRf889obX70Rq48MLIj5WaCnz9NdCihbsCTB4P8MILPCEWQghRtbQ0oFs3bjN44w12SBIiFt1xR0zX85FAgRBWSUtjRN1JkUe/Hxg5MvItCAC3HyxYALRr577q7wCwbZvdI3CGyy4LLVAwYAB/59GoVQv44Qd2RHBDnYtgv++xY+0eiRBCCCGc4tBD2UXEDecyEZBAgRBWmjjRefuz9+wJvzBdRbVrAz/+yDoMTvv5arJ3LxAI2D0K+6WkAI88Un2wICMjuu0qZTVpwmBBVpYxj2eWtDSgXz/2+xZCCCGEKOvee2O2CLAECoSw0jHHcD+4k/j9wNSpwLx50T1ORgbw/fdMzXbThJmcDOzYYfconGHsWBY2rErt2kDv3sYd79BDuY81lEwGOyQlAQcfDLzzTsyuFgghhBAiCt26AYcfbvcoTCGBAiGsdsUVzmsRF20XhCCPh9WPTzzReT9jVVJSgE2b7B6FMyQkAE8+WfmFu9fL1nlGXzB37crWW04MLtWuDcyc6cyxCSGEEMIZ7rvPuYseUZBAgRBWO+cctuVzmt27gRtvjP5xUlLYY/6009wRLFBKChqWNWgQV/orCgTMa2118slsneikC3KvF/j2W+dlAAkhhBDCWU4+ufqMTJeSQIEQVqtbl3uencbvB156iYUJo5WYCLz5JlPZnR4sKCyUjIKylAImTy7/e1OKgZ86dcw77jnnAHfe6YzXi8cDvP022zgKIYQQQlRHKdYqcFIbdANIoEAIO1x5JZCZafcoyvN6mTZl1IVaQgJXiS+91BkXf1Xx+4ENG+wehbMcdxxw7LH8HQK8cL72WvOPe/PNwPnn2/t68XqBu+5iYEQIIYQQIhQjRzorM9IAEigQwg4nncQUfSdITWWA4I47eMF85JHGPbZSrKR/443ODRZoDaxebfconOd//yt9jR50EIv1WHXcU06x583W6wXOOMOYLThCCCGEiB9JScDtt8dUrQJTAgVKqXeVUr+VfKxVSv1WcnsrpZS/zNeeM+P4QjheYiIwYYK9wYKkJF6MTZgArFvH1VyzWhvedRcLvTg10vrvv3aPICyWzLFHHAEMGcJgz3XXWVf1PyGBXQY6d2YQyyopKQySvfSSdDgQIs7JeawQIiIXXliajRkDksx4UK31yODnSqlHAewt8+VVWuuOZhxXCFe56CLg8cetP65SvAAbPBh49FGgRQtrjnvNNdy7ddVVTPd3EpcVM7Rsjp00CcjJYa0JKyUnAzNmAN27A8uXA0VF5h5PKaBBAx7TKZk+QgjbyHmsECIiXi/Pcx95BMjLs3s0UTM15KGUUgBGAHjbzOMI4UqtWwMdOlh7TK8X6NkT+Pln4L33rAsSBF10EfDyy87LLNixw+4RRMT0ObZlS+CLL+ypp5GRAXz/PasImx2dz8gAvvuOhUaFEKKEnMcKIcJ29dUxk5lodm7E8QC2aq1XlLmttVJqsVJqtlLq+Kq+USk1QSm1UCm1cPv27SYPUwibXHWVNRVS09OBdu2Azz4D5swBjj7a/GNWZdQo4N13nVWzICeH3Q/cJ7bn2AYN+HqtVcu8Y3g8wMcfV94SUohQzJwJPPWUM9veimjF9hwrhDBevXrs5JScbPdIohZxoEApNVMptbSSj6Fl7jYa5aOwmwG00FofA+BaAG8ppbIqe3yt9RStdRetdZcGDRpEOkwhnO2MM9if3ixeL1dkX3gB+PNP4MQTzTsWwIr148bxxLm6dPEhQ4BPPnFOwZe0NGDrVrtHUY7MsSVatwZmzTLnteL1Ao89Zv7fhYhdX3/NDhk33wwccwzw9992j0iESOZYIYRpbruttJuYi0Vco0BrXW0jeKVUEoAzAHQu8z35APJLPl+klFoF4FAACyMdhxCu5vGwncqrrxobMEhLYyTznnuAiROt23d9+unAiBHA668zU2LoUAYO+vY9MLLarx/wzTfAgAFc0bdTcjKwaRPQrJm94yhD5tgyjj4a+Pxz4NRT+XeSkMC0vuC/wIFpflrzA+D3aM1/gx/FxcAFFwCXXGLtzyJixw8/cM4L1lxZuhTo1IkdZG68kUVrhWPJHCuEME2LFjyvfOUV4IEHgH377D/XjYApxQxL9APwt9Z6f4NypVQDALu01sVKqTYA2gKQvmQivk2cCEybBuTmRv9YycnsZjBxIlu0mJmyXZkhQ4DFi4H+/blC/+abwKef8sJsyBDg3HO5ehsMXBx7LE+2TziBk6hdtOaE7i7xNceecAJXb3//na+f5GT+G+nnwQ8hIrFgATBoEODzld6mNYMG990HvPUW5/XDD7dvjCJa8TXHCiGM5fXyfPzSS7nYcffdwD//8H0iuJDhcGYGCkbhwOIvvQHcq5QqBBAAcInWepeJYxDC+Tp14vaA1VGcayQk8ALozDOBhx4CmjY1bnzhOuwwrqydfjowfz6Qnc3b33kHmD6dK7mDBzPlu2lTpuv+/DPQqxewe7c9k2dhoes6HyAe59iePfkhhJ1+/50ZUVUFd30+YNkytvi8/Xbgppsku8Cd4m+OFUIYLyGBW9ROOw1YuBD4z3+48FFc7Pj6WKYVM9Raj9daP1fhtg+01kdorTtqrTtprT8z6/hCuIZSwBVXRF7cz+tlav+iRcAbb9gbJAiqVYt1CiZOLN/hIDubJ9Hvv8+T56DDDwd++QVo2NCeE2q/H1i/3vrjRkHmWCFs8NdfQJ8+pQHQqgSzC+6/n1tn/vrLmvEJw8gcK4QwXJcurNH1zz/AxRfzHN6sTmAGdIwyu+uBECIU55wTfsXs9HTgyCOBr77iRXn79uaMLVIJCcDDDwNTpx4YBAkEgA8+AMpWgm7ThpHWJk24fcJq0WR0CBHPCgpqvnCOBatWMfNp797Qv8fnYyHZzp25JaG6Iq9CCCHiQ4sW7JazeTNw771A/frGd0FLS4v6ISRQIIQT1KsHnHRSaPdNT2fWwKuvAkuW8MTVyUaM4NaCxo0P3BM+eXL5/zdrxsyIVq2sK8AYtG6dtccTIhZs3gz06OH8eSha69YBxx3H7VHhCmYXPPgg0LEjAwdCCCFEVhZw/fV8L33hBW7fNaJTQno6F+uiJIECIZziyiuBzMyqv+7xMKX/4YeBNWtYj6BipXen6tCBe3a7dCnNLsjLA/73PyA/v/x9GzZkobBDDwVSU60b4+bN1h1LiFjw44/AEUdwz76Vf6tW27KFQYKdO6OroRLMLujShXtUJbtACCEEwEzaUaP4HvHll6yDk5YWWYZtUhLrn112WdTDkkCBEE7Rr1/lq+gpKQwSXHstsGED//DdWK29bl12ODj//NJgQVERq4NXVKcOL0KOOsqQ1KmQ7NhhzXGEcDutgSef5Jy1eze3EjVvzq+tXcsL6lixYwe7s2zdGv72sMoEswv++1/WLli2LPrHFEIIERuUYobeN98wa/icc3geHM65sMfDAuIGLCZKoEAIp0hMBC66qDRYkJjIieHss5lBcN99xu9fslpSEvdkPfssJ7LcXP5cla3SZWYCs2cD3bubV+ilrPz80n7oQojK+f3AyJHALbeU/3tp3Zr/HnYYtxDFgj17eMK2caPxq/8+Hwscdu0q2QVCCCEO1LYt8PLLXCS85RZmFde0LcHrBZ5/HjjoIEOGIIECIZzkoosYAfR4gAEDGE186SW2T4wl48YBc+awNsPq1cCsWZXfz+NhC5m+fSPvChGqtDTZfiBEddau5R77zz/nhW5QSkppcOCll/jhdjk57G6wZo157avKZhccdZRkFwghhButWsXAslnq1QPuvJOZbU89xcC8UjxvzchgAKFWLZ4n9+sHjB5t2KFtKC0uhKhSmzbAM89w32/37naPxlydO3Mv1sCBwPTpwIknVn6/lBS2khk79sALFCMlJQGbNvF3IIQo76uvWJg0J4dbDcpKTWW3EoB/p27n97O47D//sKOD2Xw+4O+/mV1w003AbbfZ0/lFCCFE6BYvBm64AZg3j++LrVoBgwcDJ58M9OxpTFHCslJTgfPO40dBATvw7NnDLYB79nDbX8eOHNfOnYZsqZV3IiGc5vzz7R6BdRo2ZEeExMTq75eUBLz9NjBhAv81I1gQCDBQIIQopTVT4//736q35iQksKtJLMjPB045hdlcFQutmimYXfDww9xb+t57bH8rhBDCWZYsYYBgzhwW5g5un12+HHjiCeDFFzmfH344MGQI0L8/uwMZUfR3+3bg1lt5vrptG7BrF4ME2dk8j01N5TmzUgcG9SMggQIhhL1CLcyYkMDWMZmZwJQpxgcL8vMlUCBEWfv2MYtgzpzq63cUF5dmFLhZUREwdCjwyy88+bODz8dMhm7dJLtACCGcZOlSBghmzy4fICgrEOB7J8CAwp9/crtAXh5w+eUMukdTkPynn4DXX686kG3wubHUKBBCuIdSwOOPAzfeaHzNgoIC7sEWQrDQ3hFHAN9/X/OJR36++wMFxcUMivzwg/1FTctmF3TowJNTIYQQ9vjzT24p6NaNdbP8/tBb5RYVMXBQUAA89xyzxaLRtWt03x8mCRQIIdznrruAe+81vhvC6tXGPp4QbvTBBzwZ2bgx9PR7N3dk0RoYP551GOwOEpQVrF3QrRtw993mFVUUQghxoL//BoYNA7p0AWbM4PtDNOn8Ph/w6afRjalJE/OLe5chgQIhhDtddx3wv/8ZGyxYv964xxLCbYqL+Xc1bhxbl4a6YlKnjiH9mm2hNXDJJcCHH5pXKDVafj8waRKzC/74w+7RCCFE7Lv8cuCYY1hEO9oAQVnffBP6e2tVOnc2ZiwhkECBEMK9LrqIRWOMChZs3WrM4wjhNjt2AL17MzUy3Avmhg3NGZMVrr8eeOMN5wYJgoK1C7p3Z0aVZBcIIYQ5Zs0CXnmFdQWKi4197Lw8YOXK6B6jb9/o6hyEQQIFQgh3GzOGVcKNCBbs2hX9Y4j4UVTE1p4DB/ICLtpVArv8+ivQvj2L+EVywXzQQcaPyQp33x1ZYMROfj/wyCPsiLBkid2jEUKI2FJUBFxwgXnvC1oDM2dG9xjduxu/9bYKEigQQrjfaadx31e0+7bKVqsVoip//QVccw1Qvz4wejTw5Ze8aHPj1pVXXgF69WLLpUhXqVu2NHZMVpg0iR9uChIE+Xxsw9WjB3DnnZJdIIQQRpk8mW0HzeL3A598Et1jdOliWT0dCRQIIWJDv37c+xVNUbW0NGmRKCq3dy/w7LNcee/cGXj6ad6Wnc2vJycDP/9s7xjDUVDAVZPLL4/uhCMhwX2BgmeeYTaBG4MEZfn9wKOPsjuFZBeIeKQ1sGqVe7O5hLNs3w7cfjtr9Jhp7tzoah7UqgU0aGDceKohgQIhROw47jj2t83Kiuz7ExIkUCDK8/mAM88EGjdm/+S//uIFWsVV3OxsvvbcYNMmdjV4++3oL5Y9HndtPXj1VdYlcHuQIMjnA1asYHbBHXdIdoGIL1OnAoccwg4tQkTr6aetmUOVAn77LbrH6NHDkKHURAIFldEa+Phj4KmngC++sHs0QohwdOoE/PRTZJXYi4slUCDKe/FFtkXKy6t5lWHWLGvGFI05c7i//c8/jUldTEpiuyY3ePdd4NJLndUC0SjB7IKJE+0eiRDWOfNM4LvvgGbN7B6JiAXbtzPbzmwFBcyAjUafPsyCrU5iYnTHgAQKDlRcDJx/PnD22Vw9Gj4cuPpq46teCiHMEyzM1qBBeBNlXp6sTIhSRUXA/feHfmG5ciWQn2/umCKlNfD448DJJwO7d/NnM+pxGzc25rHM9NlnwHnnxWaQIMjvB3Jy7B6FENbJymIFeCGi9f77wOuvW3OsggLgo4+ie4zjj+e/lZ3jer0MIowZE90xIIGC8goLGZ2cNo0rR/n5TOt74QXgpJO4H1UI4Q4HHwwsXMjVzqSk0L6nqAhYu9bUYQkX+eCD8FLUPZ7o0wnN4PMx6H3HHcZfKBcUOD+j4JtvgJEjYztIEOTmVpVCCGG1PXt47XfuuaU1h6zw22/RLSwccwzw44/AxRezZkFmJmt0NW4M3HMPs2Nfey3qYUqgoKxRo4Cvvz7wxNDnY5Gqo46SaL0QbtK8OYMFLVuG3nN29WpzxyTcQWv2qw9nzs/P57YXpzn9dLZxNKNAU2Ehuz84ld8PDB4cH0ECpZz9uxBCCCeZOZM1LqZPt75uTWpq9AWQjzmGdRV27ADee49ZERs3sg5PnTqGDFMCBWXVrl311/LzGXVyU1VrIQTQqBGwYAFw6KGcmGuyYYP5YxLO98MP4b8W8vOj33dohr17ua3GDBkZhuyDNE1aGos+hZpV5GapqdWfxwghhGBQYMIEttbeudOeLYO5uWytbISkJG4rPPlkFuU2kAQKynrmGaB166pPeoqKmFoqhHCXunW50tuhQ83FX8zsnyvc4667IluBX7DA+LFE65BDzHtsp69gKwW89VbNf/exIClJAgVCCFGd33/nwtEbb9ibaVZcDHz6qX3HD5EECspKTWV0Jz39wK95vcB11wE9e1o/LiFE9DIz2b6uW7fqA3579khP5nj355+RX/BnZwObNxs7nmgNGsSVfzO4oZBh06bsYuT12j0ScyUmSqBACCGqM2cOF4ScsB1t5Upg3z67R1EtCRRU1Lw5K1GWvZBITQV69wbuvtu2YQkhDOD1MjX8hBOqvmhITAR27bJ0WMJhPvww8hZJqanA/PnGjidap55qXsun5s3NeVyjnXsucOyxsb8FQQIFQghRtcsvZ9tjr/fAFtpWb6NLS+MCloNJoKAyJ54I3HZb6YuoSRN2QjB434cQwgYpKUz3OvXUyoMFqanSIjHe5eVF3hI3O5srFk5SqxbQubM5j926tTmPazSlmGoay9sHtZZAgRBC1GTcOODXX4HRo4GBA7l41L175O/7kcrOBr74wtpjhkmufKty663MIvB4uAKZmWn3iIQQRklKAt55h51OKgYLlGJbGRG/hg+P/IJSa+Dbb40djxHGjTM+9T4tjWn9btG4MfDcc7G7BaGoiEEhIYQQ1WvXDnjzTV6oz5rFYvUdOlg7Bq0lUOBaSgEff8yq12YWghJC2CMhgelnF11U/sKhqEgCBfHu6KOBs85i9kkk/vqLryMnGTbM+DGlpDDjzk1Gj+bqUajtUt2ksFAyCoQQIlKhdMYy2tatwJYt1h83RFEFCpRSw5VSy5RSAaVUlwpfu0UptVIp9Y9S6uQyt59ScttKpdTN0RzfdKmphvWhFEI4kFLA44+z52wwWOD3O2brQczPsU72yCORX0ympgJ//GHseKLVuDEweLCx1f+DW/PcRClg6tTYzCooLjavaGWMkjlWCLHfa68BDRpYW6sgOZkZDQ4VbUbBUgBnAPih7I1KqfYARgE4AsApAJ5RSiUqpRIBPA1gIID2AEaX3FcIIeyhFHDPPfzweIBAAFi92u5RBckca5eGDYE77qi8C05NiorYjtNpXn8daNXKuJOgoiJ3dD2oqEED4KWXYi9YkJZ2YHEuUROZY4UQdPjhwOLFQIsWkWcUhktr4LDDrDlWBKIKFGit/9Ja/1PJl4YCeEdrna+1XgNgJYBuJR8rtdartdYFAN4pua8QQtjr+uuZXaAUsGaN3aMBIHOs7a65JrI9336/M+sUBLt+ZGUZ83h5ee4MFADAmWcCAwZYdzJohUiCWnFO5lghRDlNm7LQYYcO5he/TU8Hvv4aOOYYc48TBbP6BDUF8HOZ/28ouQ0A1le4vXtlD6CUmgBgQsl/85VSS40eZBTqA9hh9yDKkPFUT8ZTPRlPRbNnl12Za2fnUKogc6y1wh/Phx+aubrrjOenuDi4Ku+M8ZSKz/Fs3x7Ka85pz40T51dA5lirOWk8ThoLIOOpiXvHk5sL9Oxp7miinGNrDBQopWYCqGzJ4Dat9SfRHLw6WuspAKaUjGGh1rpLDd9iGRlP9WQ81ZPxVM+J4zH58WWOrUDGUz0ZT/VkPFVz0lgA8+fXkmPIHFuBjKdqThoLIOOpiYynetHOsTUGCrTW/SJ43I0Ampf5f7OS21DN7UIIEXdkjhVCCPPIHCuEEJExqz3ipwBGKaVSlVKtAbQFsADALwDaKqVaK6VSwEIxn5o0BiGEiFUyxwohhHlkjhVCxL2oahQopU4H8BSABgCmK6V+01qfrLVeppSaBuBPAEUAJmqti0u+53IAXwFIBPCy1npZCIeaEs04TSDjqZ6Mp3oynurJeErIHOsYMp7qyXiq56TxOGksgM3jkTnWMZw0HieNBZDx1ETGU72oxqO01kYNRAghhBBCCCGEEC5n1tYDIYQQQgghhBBCuJAECoQQQgghhBBCCLGf4wIFSqnhSqllSqmAUqpLha/dopRaqZT6Ryl1cpnbTym5baVS6mYTx/auUuq3ko+1SqnfSm5vpZTyl/nac2aNocJ47lZKbSxz3EFlvlbpc2XyeCYppf5WSi1RSn2klKpdcrstz0/JsS15bVRx7OZKqVlKqT9LXtNXldxe5e/NgjGtVUr9UXLchSW31VVKfaOUWlHybx2LxtKuzHPwm1Jqn1LqaiufH6XUy0qpbapMf+uqng9FT5a8lpYopTqZNS4zyRwb1ngcM8fK/Frp8WWOrX4sMsdaTObXsMbjmPm15Jgyxx54fJljqx6H7fNryTjMnWO11o76AHA4gHYAvgfQpczt7QH8DiAVQGsAq8BCMokln7cBkFJyn/YWjPNRAHeWfN4KwFIbnqu7AVxfye2VPlcWjGcAgKSSzx8C8JDNz48tr40yx28CoFPJ55kAlpf8bir9vVk0prUA6le47WEAN5d8fnPw92bD72oLgJZWPj8AegPoVPb1WdXzAWAQgBkAFIAeAObb8Ts04GeWOTb0MThmjpX5tdIxyBwb3u9L5ljzf16ZX0Mfg2Pm15Ljyhx74Bhkjg39d2X5/FpybFPnWMdlFGit/9Ja/1PJl4YCeEdrna+1XgNgJYBuJR8rtdartdYFAN4pua9plFIKwAgAb5t5nChU9VyZSmv9tda6qOS/P4P9he1k+WujLK31Zq31ryWfZwP4C0BTq44fhqEAXi35/FUAw2wYw0kAVmmt/7XyoFrrHwDsqnBzVc/HUACvafoZQG2lVBNLBmogmWMNYfkcK/PrgWSODYvMsRaQ+dUQcg5LMseGzu451pb5FTB/jnVcoKAaTQGsL/P/DSW3VXW7mY4HsFVrvaLMba2VUouVUrOVUsebfPyyLi9JH3m5TKqNHc9JReeDUasgO54fJzwPAJi6BuAYAPNLbqrs92YFDeBrpdQipdSEktsaaa03l3y+BUAjC8cTNArlT1rsen6Aqp8Px7yeTCJzbOWcOMfK/FqBzLE1kjnWXjK/Vs6J8ysgc+wBZI6tlpPmV8DAOdaWQIFSaqZSamklH5ZGyqIY22iUf0FsBtBCa30MgGsBvKWUyrJgPM8COBhAx5IxPGrEMaMYT/A+t4F9h98sucm058cNlFIZAD4AcLXWeh9s+L2V0Utr3QnAQAATlVK9y35RMzfJ0p6pSqkUAKcBeK/kJjufn3LseD6MIHOsYeOx9LUo82tkZI6tnsyxxpL51bDxyDmsS8gcWzUnz69A9M9HkoFjCZnWul8E37YRQPMy/29WchuquT1sNY1NKZUE4AwAnct8Tz6A/JLPFymlVgE4FMDCSMcR6njKjOsFAJ+X/Le658rU8SilxgMYDOCkkhenqc9PDUx7HkKllEoGJ9c3tdYfAoDWemuZr5f9vZlOa72x5N9tSqmPwNS2rUqpJlrrzYopSNusGk+JgQB+DT4vdj4/Jap6Pmx/PYVK5ljjxlNmXKbPsTK/hk/m2JDIHGsgmV+NG0+Zcck57IEc8fcgc2yNnDa/AgbOsW7aevApgFFKqVSlVGsAbQEsAPALgLZKqdYlUZ1RJfc1Sz8Af2utNwRvUEo1UEollnzepmRsq00cQ/C4ZfeVnA4gWPGyqufK7PGcAuBGAKdprX1lbrfl+YH1r41ylFIKwEsA/tJaP1bm9qp+b2aPJ10plRn8HCzcsxR8Ts4tudu5AD6xYjxllFvdsOv5KaOq5+NTAOMU9QCwt0xqVyyQObYCJ82xMr8eSObYkMkcaz+ZXytw0vxaMh6ZYyuQOTYkTptfASPnWG1DxcrqPsAndQMYvdsK4KsyX7sNrAD6D4CBZW4fBFbiXAXgNpPHNxXAJRVuOxPAMgC/AfgVwBCLnqvXAfwBYEnJL79JTc+VyeNZCe59+a3k4zk7nx+rXxuVHLsXmO6zpMxzMqi635vJ42kDVs39veT3cVvJ7fUAfAtgBYCZAOpa+BylA9gJoFaZ2yx7fsDJfTOAwpJ554Kqng+wSuzTJa+lP1CmorWbPmSODWssjpljZX6t9Pgyx9Y8JpljrX1Nyvwa+lgcM7+WHFPm2AOPL3Ns9eOxdX4tOZ6pc6wq+UYhhBBCCCGEEEIIV209EEIIIYQQQgghhMkkUCCEEEIIIYQQQoj9JFAghBBCCCGEEEKI/SRQIIQQQgghhBBCiP0kUCCEEEIIIYQQQoj9JFAghBBCCCGEEEKI/SRQIIQQQgghhBBCiP0kUCCEEEIIIYQQQoj9JFAghBBCCCGEEEKI/SRQIIQQQgghhBBCiP0kUCCEEEIIIYQQQoj9JFAghBBCCCGEEEKI/SRQIIQQQgghhBBCiP0kUCCEEEIIIYQQQoj9JFAghBBCCCGEEEKI/SRQIIQQQgghhBBCiP0kUCCEEEIIIYQQQoj9JFAghBBCCCGEEEKI/SRQIIQQQgghhBBCiP0kUCCEEEIIIYQQQoj9JFAghBBCCCGEEEKI/SRQIIQQQgghhBBCiP0kUCCEEEIIIYQQQoj9JFAghBBCCCGEEEKI/SRQIIQQQgghhBBCiP0kUCCEEEIIIYQQQoj9JFAghBBCCCGEEEKI/SRQIOKOUmq8Umqu3eMQQohYIHOqEEKYR+ZYYRcJFAjHUEr1Ukr9qJTaq5TapZSap5Tq6oBxDVFKLVVK5ZSMr73dYxJCiJo4eE6dopT6RykVUEqNr+Tr1yiltiil9imlXlZKpdowTCGEqJYb51il1JFKqa+UUjuUUtqmIQqXkECBcASlVBaAzwE8BaAugKYA7gGQb/O42gJ4E8AlAGoD+AzAp0qpJDvHJYQQ1XHqnFridwCXAfi14heUUicDuBnASQBaAmgDjlsIIRzDrXMsgEIA0wBcYOmIhCtJoEA4xaEAoLV+W2tdrLX2a62/1lovCd5BKXW+UuovpdTukmhoyzJfO0wp9U1JRPcfpdSIMl+rp5T6tGR1agGAg8MY18kA5mit52qtiwA8BL4Z9In2BxZCCBM5dU6F1vpprfW3APIq+fK5AF7SWi/TWu8G8B8A48P6yYUQwnyunGO11v9orV8CsCyCn1nEGQkUCKdYDqBYKfWqUmqgUqpO2S8qpYYCuBXAGQAaAJgD4O2Sr6UD+AbAWwAaAhgF4JkyWwSeBifLJgDOL/ko+9ifK6VurmZsqsLnCsCRkfyQQghhESfPqdU5AlwNC/odQCOlVL0IH08IIczg1jlWiJBJoEA4gtZ6H4BeADSAFwBsL4mmNiq5yyUAHtRa/1Wysv8AgI4l0dnBANZqrV/RWhdprRcD+ADAcKVUIoAzAdyptc7VWi8F8GqFYw/WWv+3iqHNBNBHKXWCUioFnPRTAHiN/PmFEMJIDp5Ta5IBYG+Z/wc/z4zw8YQQwnAunmOFCJkECoRjlEym47XWzcAV+4MAPFHy5ZYA/qeU2qOU2gNgF7iy37Tka92DXyv5+lgAjcEobhKA9WUO9W8YY/obTIWdDGAzgPoA/gSwIcIfUwghLOHEOTUEOQCyyvw/+Hm2gccQQoiouXSOFSJkUpBNOJLW+m+l1FQAF5fctB7A/VrrNyvetyQ6O1tr3b+SryUCKALQHMDfJTe3CHMs7wN4v+TxaoMFYH4J5zGEEMJOTppTa7AMwNFgsS2UfL5Va73TwGMIIYShXDTHChEyySgQjlBS1OU6pVSzkv83BzAawM8ld3kOwC1KqSNKvl5LKTW85GufAzhUKXWOUiq55KOrUupwrXUxgA8B3K2U8pbs/zo3zLF1VkolKqUaAJgC4NOSTAMhhHAkh8+pKUqpNHB1LVkplaaUCp6PvAbgAqVU+5LA7O0Apkb4NAghhCncOscqSgO30aLka9KCVlRKAgXCKbIBdAcwXymVC060SwFcBwBa64/AjgPvKKX2lXxtYMnXsgEMAIvBbAKwpeS+wYnvcnDf6xbwhPOVsgdWSs1QSt1azdj+B2APgH8A7AZwUVQ/qRBCmM/Jc+rXAPwAjgODr34AvUuO/SWAhwHMArAOTLm9K7KnQAghTOPKORbc9uBHadcDP3h+K8QBlNba7jEIIYQQQgghhBDCISSjQAghhBBCCCGEEPsZEihQSr2slNqmlFpa5ra6SqlvlFIrSv6tU3K7Uko9qZRaqZRaopTqZMQYhBAiFsn8KoQQ5pE5VgghKmdURsFUAKdUuO1mAN9qrdsC+Lbk/wD357Qt+ZgA4FmDxiCEELFoKmR+FUIIs0yFzLFCCHEAQwIFWusfwP6gZQ0F8GrJ568CGFbm9tc0/QygtlKqiRHjEEKIWCPzqxBCmEfmWCGEqFySiY/dSGu9ueTzLQAalXzeFOwtGrSh5LbNZW6DUmoCGK1Fenp658MOO8zEoYq4oDXw229AIGD3SMyXmQkceqjdo4gJixYt2qG1bmD3OCqIan4F4myO1RpYuRLIzubnoUhMBA45BMjIMHdsQsQxh86vgMyxQrhTfj6wbFno7/UxbhEQ1RxrZqBgP621VkqF9RvTWk8BW3qgS5cueuHChaaMTcSZceOAN96I/QnknHOAp5+2exQxQSn1r91jqE4k82vJ98XHHFtQAJx2GvDXX+H93SclAXPmAA2ceA0jRGxw+vwKyBwrhKvcfjuwfDnf+wUUWwxHzMyuB1uD6Vgl/24ruX0jgOZl7tes5DYhzHfOOVxtj2UpKUDbtnaPQphL5tdQBIMEP/wA+P3hfW9iIlC/vjnjEkI4ncyxQrhNIABMmSJBAgOZGSj4FMC5JZ+fC+CTMrePK6kc2wPA3jLpXUKY64QTgOJiu0dhrrQ0oGVLu0chzCXza00KCoAhQyILEgBA69aAUsaPSwjhBjLHChGpnBzgwQeByZOBDz4A5s0DVq8GfD5zj/vDD0BenrnHiDOGbD1QSr0N4AQA9ZVSGwDcBeC/AKYppS4A0x5GlNz9CwCDAKwE4ANwnhFjECIkycm8eHjnHbtHYq4WLewegTCIzK8RKCgABg8G5s6NLEgAAEceaeyYhBCOJHOsEAZ7803g7ruBhARmuSoFFBXxIj45GahTB2jYEGjalAtbLVoABx0ENG7MjzZtIqsP9MwzDFIIwxgSKNBaj67iSydVcl8NYKIRxxUiIuPGAV98AezbZ/dIzJGfLxkFMUTm1zAZESRITgY6SXt0IeKBzLFCGOyFF0rT/yuu8BcXA5s38+P333lbUhKQmsp/g7WEPv0U6NMn9GPm5ACffRb7NcgsZubWAyGc6aSTGNmMVYEAUK+e3aMQwnpGBAkAwOsF2rc3blxCCCFEPNi8GVi6NLzvKSoCcnOBvXu5iLdvHzBwIPDcc6E/xvvvM9AgDCWBAhF/UlKAQYPsHoV5GjSQvdUi/hQUAKeeGn2QAOBJi7QyE0IIIcIzbRq3HETL7weuuw64+OLQFveeekq2HZhAAgUiPo0bB2Rl2T0Kc0h9AhFvgkGCefOiDxIA3L7TqlX0jyOEEELEkxdeMOZ9GGDxwzfe4BaE3burvt+aNcCffxpzTFGO5GiI+NS/P1BYaPcozHHIIXaPwHpvvAE88QRXgY8+GmjXDjj0UBbESUmxe3TCTPn5DBL8+KNxJydNmkgKoxBCCBGOf/8FVq0y9jF9PmDhQqBDB+C773huV9HLL3PbrTCcnAmJ+JSWBgwYAHzySc33dZOEhPhKmS4qAq65hm8SPh+waBHT3jwevmn4/azX0LYtcNRRfKM59FAWqqtTx+7Ri2iZESQA4utvSAghhDCCWR3FCgqATZuALl2A337jIlBQIABMmVJaPFEYSgIFIn6dey4wa1ZsdT/weuOn48GuXWx1+dtv5XvzFhaWzxbZto0f8+YxQJSczDoOK1YYs49O2CM/n8WOfv7Z2CCBUkDnzsY9nhBCCBEPXnzxwC4HRtGaHRNmzgQmTCi9fc6c8ueAwlBylhyPAgHgtdeAf/6xeyT2OuWU2ItAJibGR6BgzRr2uV+4MLw3iLw8IDsb2LoV+PBD88YnzGVWkABg7+YjjzT2MYUQQohYtnw5sHGjucfw+ViwuKxnn2XHBGEKCRTEm+3bgb59WUX02GOB1avtHpF9PB7gxBPtHoWxCgvjI1DwwAO82I800JObC9x4o+xpc6P8fAb5zAgSAMwokK0HQgghROjefJMr/mb76afSz3NygE8/ZbaBMIVsPYgns2cDZ5zBFdXCQp5wH3cc93U3bWr36AxTWFiI999/H0WVtFM544wzkJ6eXnrD+PFMW8rOtm6AZsrLAw46yO5RmKuoiHUIor3I37YN+Ogj4MwzjRmXMF9BAYME8+ebEyQAuGLRrp05jx0j1qxZg7kVV3UANGrUCAMGDLBhREIIETu+++47bKxkdb579+44tLJifnbTGnjlFWuydP/9l8dJSQE++ICZtMI0EiiIB8XFwD33AI88Uv7kWmtgx47SYEH9+vaN0UDTp0/HhROvRkaro8rdnrvxH+zbtw8TJ04svXHgwNjYfpCRweDP+PGxX6191ixjosfBrILTT5daBW4xaxbwyy/mBQkAIDOTf0+iSpdffR3m/rESabUblbt959LZ2L51K+pIoVAhhIhIQUEB+vXvjwZHl894zd+3Ax1aNMCc7762aWTVWLoU2LnTmmOlpfF4nToBTz3FrAJhmhi/ohDYsoUXQkuWVH5yXVwMbN4MHH88V+mysqwfo8ECgQAymrWDZ8DV5W4vnjUFgYqr0BkZ7M/6tQMn3ppkZjLIcfzxwPnnA4MH87ZY99JLxmWAbN0qWQVukpNj/upBPLYXDVNRcQApR50Kz2G9yt2evGIBtKSACiFEVBISEg84h8XqRSjeNtuW8dTo9detazleXMzFzbp1gWXLrDlmHJNltFj2zTfA4YfXXPCtsJDF4U48MT4rh553nnsusDMygNRU4KSTgOefZ82Jb74BRo92z88Qjbw84LPPjHu83FzgppukVoFb+P3m/66OOcbcxxdCCCFihdYskG5VoCBY0PCVV6Q2gQUkUBCLioqYUj10KLBnD/9fk/x8RuYGDYqNVPxwnHqqs3/myoIDM2fGT3CgrBkzjF9R3roV+PZbYx9TmMPnMzdQ4PEARx9t3uMLIYQQsWTRIuvT/3/8kefD+fnWHjcOSaAgFt12GzB5cvj7ePPygAULWPDQisqlTpGZCfTsafcoysvMLB8c2LaNwYExY+IvOFBWZiZfm16vsY9r9OMJc/j95s5NKSnS8UAIIYQI1auv8vrBSqtXS0tEi0igIBZ9/nnkxb78fhYMGzcuvlJ6zjvP/gJmwcyBE08EnnuufHAgBmpHGKJfP2YA/Pe/QJMmxvzOvF4W9BTO5/eHliEVqfx8CRQIIYQQoQgEgLfesn5xMTVVAgUWkUBBrMnLA1asiO4xfD7g44+Byy+Pn2DBkCHW7a8qq7LgwLffSnCgOhkZwBVXABs2AG+/DXTrxpTxSDoXpKQAF10EKGX8OIXxfD5zT0i0ZgAqVCtWAHfcwSysL74wb1zCXeIpI08IEb9+/NGec2e/P36uT2wmgYJY8+uvvGiKls8HTJ3Kk+B4UKsWLzitUFVwYOxYCQ6EIyGBnR7mz+fHqFFsm5OWFt5jnHeeeWMUxjKq20VVWrYMPWi0bx87ptx/PztnXHeduWMTzrdjB3D22UByMuf4+vXZRaNbN85Vb71l9wiFEE4xbRq7Vj32WPQLfHaZOlVW9mOcBApizbx5xu0V8vmAxx8HHn3UmMczkxHpyOedB6SnR/84lQkGB/r2leCAGTp0AN58E1i3jl0MatUKbVtC27bAwQebPz5hDLMLJh15ZGj305p/u7t2la5qrF3LDxF/AgHO623aAO+9x9dEQQH7iq9aBfzyCzB9OrOXHn/c7tEKIZzA4+GK/K23sojuww+7a5W8qIjznXSNimkSKIg1X39tbAV/n49ZBS+8YNxjGiEQ4MnXrbfyQi85GVi8OLrHHDrU2P3PZYMDzz7LvfXffSfBATM1aADcfTcDMU8/zdW8qoI/6encXiPcw8xAQVIS0LlzaPd99ln+LVesuPzuu8aPSzjbwoUMMF1/PTNeqnv/9fmA228H7r3XuvEJIZxp8GDg0EP5PuL3c14YMIABaDeYPdtdgQ0REQkUxBKt2bXAaH4/cNVVTJNygokTgbp1mbo/aRKrn2ZlsRVkNOrWBTp1iu4xqgoOnH02V7mFNVJSWJBz+XK2VBwwgFsSkpNL71NUBIwYYd8YRfjMTHH0eoHDD6/5fr//zotCn6/87Xl5wMsvmzM24Ty7djELrXdv4K+/Qn9t+nzAQw8BN9wgJ9lCxDOlgEceKV3MyM0FfviBGZJumBteftn6tojCchIoiCVr15pXEdzvB8aP50WXnQIB4MMPgb17OUEFf97iYqBVq+gfP5LtB8HgwAknSHDAaZTiHsCvvgL+/BOYMIEXhCkpbD1Zu7bdIxThMDNQEAjU3PEgOxs49dSqu8qsW8fApYhdgQDw4otA69YsphpJhyGfD3jmGeDSS91xQSCEMMegQUCLFqX/LyhgrROnp/MXFLDoucxfMU8CBbHkxx8jq/weKr8fOOssYM4c845Rk4QE4PnnD+x7n5cHNG8e/eOffnpoFVzLBgeefprBgVmzJDjgZK1bA5MnA1u2AE8+yQ/hLhVX8Y3k91dfr0JrBkt37qz+Pu+8Y/jQhEP89hvQsSNw9dUsZllx60k4fD7g9deZ+SRdEoSITxWzCtzim2+4XU/EPAkUxJJvvzU/DcjnAwYOZHcFuwwZwi0CZYMideoYM2nVr8+iMpWpKjgwbpwEB9wkMxO4+GIpYuhGkazehqphQ2aaVOXFF5mZUl2x2Px84JVXjB+bsFduLrORjjsO+OMP4zJbfD5myA0fbl42oBDC2QYOZMcdN3npJQZLRcyTcFAsmT3bmuPk5nIP/s8/h7an12hKsbjiMccAeXmYn5CIZ5NSgQsnAAD+XbMGVSVDvfHW21j0+x/7/z9y+FkYePKA8nc67zxg6VJelGRkMMOgRw/g/PNZ8FCCAkLYw8xAQXXbDpYt4ypyKBkNGzey0n0MBaKeePIp/LakdN5cuuQ3oHP7Su6pMPHKq5Fa0qI0MSEBjzz0IOrUqWPNQM2Snc3q3gBrnRjVWQjga+rLL1nY7JNPGIwWQsSN7JwcXNf6YBSsXgsUFSGgAQQqDxyu/OdvjC851wWAw9sdiptuuN6agQb5/fZvQxaWkUBBrNi3D1i/3trj9erFis+tW1t33KDDDgMeeAD48EN8V1CIaet3wbO+pFBd0qFI69bhgG9J6zwMK1ctxMqSp8m/fB7SUlIPDBSccQYr53ftWhockL3sQtjPyAu0iqoqZJqby32koW57CAS4/eC224wbm82eeuY5bPO0RErDkrm+/RBkHNz1gPtlnXoDvt6+af//s394FRMuOA/du3e3aqjmaNyYxQv/+ouZe59+yq1+iYncqxvNFgSAJ94//AD068eslYpb64QQMWvdunV4+euvUOuEC7gQBqBerUYH3C+t5dHIyT4Ln61nEKFw5wakf/U1brz+OqiS77PEjBksDG3m+7FwDAkUuNny5cB117Et4NatXIkIZX+9UfbsAXr2BBYtApo0se64QddcA1xzDYavXIn7ux6LjI6nQKmqd9MkZTVE5jGD9v9f/zUTY0YNP/COjRrx+RRCOItZJybp6WxxV5kLL2S7zVAFtx/EUKBgzMiz8OxXfyCjzPxZGU+rjkCrjgCAgh3roGploWvXAwMKrqQU0L49P664gnUFliwBZs5kJsCiRdy64vdH9j7s9zPw3rs3t7RlZhr/MwghHKd9+/Zo3LQZipu0RWqTQ6u8n0pMQubRpQtb2XNfx6gRZ1kbJAC4DS8729pjCttIjQI3Ki5mW8COHYHp05nqWlRkbkXwygQCwPbt3LdZXYEvkx1yyCFo1Kgh8jf+FfL3FO7ZgkDubvTs2dPEkQkhDFVdj/poJCZWvvXg1Ve5ehxugGLTJmDFCmPG5gAjhw9HwaqfoMOocJ2/4kecdeaZSDCzwK6dEhO5/e2GG4C5c5ll9+WXwO23A507M2iQlcX7hSovj9vejj0W2L3bvLELIRxDKYXRI4ajYOVPYX1f8er5GDWiksUuM2Vns6uXiBsx+g4ew1as4EnI3XdzBcLu1iRFRQxU9O5ta4Rx7KjhKFr5c8j39y+fh2HDhiIxnJM4IYS9zAoU+P0HBgr+/hu47LLIOi0Etx/EiCOOOAJZGV4UbAk9+KHXzMeYkRafxNopOZkX+HfeycyAvXvZPuyGG4AjjuDXs7Jq7kyUn89swbPPtmTYQgj7jRoxHEWrfg45GFuwYx2SAvnWZ2x99hnnMhE3TN16oJRqB+DdMje1AXAngNoALgKwveT2W7XWX5g5FtcLBIDHHuNJSH6+s3qsFhayeNeJJ3Kfpcdj+RBGDh+OJ55+HrrP+SGlYam1CzD2lsctGJkQ5ojL+dWsQIHHU74Oid8PnHpq5MUT8/OBqVOBO+6o+b7Z2ayL8ttvTDevVYtdXOrXBxo0YDeGOnU4vso+MjP372s1S3DF6+W5P1WbGhtUuHszArl74jtjKy2NRX/79gUefJAdiebOZdbBF18A//7L+1RWObywkKt2hYVyUm6juJxjhS06deqEtESgcPva0low1chf8SOG25Gx9cIL5ndXE45iaqBAa/0PgI4AoJRKBLARwEcAzgPwuNb6ETOPHzNWrgRGjAD++cfcqt/RyM9nyuSpp7IYk8UnN+3bt0etjHQUbFlR44ls0b4dKNi1CSeccII1gxPCBHE3v2ptXgu5ih0KLr4Y2Lw5uoytzZs5Z7drV/V9tm4F+vQB1q7lHLpjR+X3S03lnJqQwKBA8LkoLORWtLQ01llo2ZL75Q86KPJxV2HUiOGY8urp0L3G1RiMlYytSmRkAKecwo8nnuDWgtmzWRhsxgzWwUhJKc3MS0ri66eq2hnCdHE3xwrbKKUw4qwz8davP4UUKNBr5mPMf160YGRlBIOdIq5YGYo6CcAqrfW/Fh7T3YJZBEcdBfz+e2QpsFbKy2PLxOHDefJqIaUURo8MbY+Xb/mPOPXUwUiWlRoRO2J/fs3LC2+/dziOOqr087feAj74IPqgbHFx9dsPVqxgnZlVq2qump+fz5O0ffuY0r5vH98PCgv5PuHzsV7M4sWsGbN9e/WPF4GyK141UWsXYOyoEYaPIabUqQMMGwY8/zywbh2DRVOmcMtBo0b8fUtRXSeJ/TlW2Gr0yOEIrKl5C61tGVseD1uiSwA4rlgZKBgF4O0y/79cKbVEKfWyUuqAJstKqQlKqYVKqYXbTTjpcbxVq4Bu3bjVwO931laD6vj9wDffAOedZ3n9hFD3eCX8uwBnj5aTWBFTwppfARfOsX4/V1mNlprKC3aAF+8TJhgTlC0o4PaDyuzaxfl961ZjsySKi1lIsVcvw2vGBFe88ldUH4wt2rcdBbs3S8ZWuBo3BkaNAl5/Hdiyha+Nk06ye1SiVOzPscJWPXr0gCrIReHODdXez7aMrcREbpvKyLD2uMJWlgQKlFIpAE4D8F7JTc8COBhM6doM4NGK36O1nqK17qK17tKgQQMrhukMgQDTEo86iqtDVncyMILPxxW5q66yNFhwzDHH1LjiVZy7G/4tq9G/f3/LxiWEmSKZXwEXzrF+vzkrGWlpXCXJy+PWKSMzt7ZuBf6qpBvLY4/xeGbMj4WFDBZ89ZXhDx3Kipdv+Y84dbBkbEWtYUO7RyBKxM0cK2yVkJCAM884HXkrfqz2frZmbDVrxoKGtWpxq5SIeVZlFAwE8KvWeisAaK23aq2LtdYBAC8A6GbROJxt9Wqge3f23/b53JNFUBmfD3jpJeCeeyw7pFIKI4efVe2Kl2/Fz+h/8slITU21bFxCmCw+5le/v+aK8ZEoLGTHg8svBzZsMPbivbgYePvt8rdlZzMYHG7LxXDk5gK//GL4w4ay4pXw7wKcLdsORGyJjzlW2G7MyBHAmvlVft0RGVvHH8/aaYMGAV6vfeMQlrAqUDAaZVK2lFJNynztdABLLRqHMwUCwJNPAh06AL/+6vxaBKHy+YBJk4DHresuUNOKV8La+Thn9EjLxiOEBeJjfjUzUDB/Pi/ojS4WW1AAvPpq+dueesr8ILDWwJw5hj9scMXLX8WKV3HObvi3rJGMLRFr4mOOFbY7/vjjUZS9A4V7tlT6dcdkbNWvD3z0EWv6pKXZOxZhKtMDBUqpdAD9AXxY5uaHlVJ/KKWWAOgL4Bqzx+FYa9YAPXoAt9zi/iyCyvh8zJB45RVLDte9e/eSFa/1B3yt2J+NnA1/45RTTrFkLEKYLa7mV7/fnDaAXi9wwQXmBWh37ACWLePnfj/w8MPWdK9ZutSUrQ1jRo6AqmLFy7fiJ8nYEjElruZYYbukpCQMOe00+JdXHoxNWOuwjK1168wJ4AvHMP23q7XO1VrX01rvLXPbOVrrDlrro7TWp2mtN5s9DsfRGnj6abY+WrQodrIIKuP3AxMnAu+/b/qhEhIScNaZZyCvkknWv3I+ep9wItLT000fhxBWiKv51ayL6717zZ1/i4pKtx88/zwzGKxQWMgWjQY7/vjjUVjFilfCvwvsz9gys42miDtxNccKRzh71Agk/LvggNuLc3bDv9VBGVtvvgncdFNsX78IS7seiLIWLQJuvDE2swgq4/cD48aZUmCrojEjR0CvPXDFS62dj3PHyLYDUQO/3/KOHSIEZgUKvF5z5+CCAuC11/jvffdZd1KVksKtbAZLSkrCaZWseBX799mXsZWXx/eWSy4BmjQBDj7Y+jEIIYQBTjzxRPi3r0dR9o5ytzsqY+vzz4GLLrImO07YSgIFdvn66/hb9fD7gTPOAObNM/Uwxx9/PIqzd5Zb8Qrk+5Cz9g8MHjzY1GMLl9Aa2LgR+PZbZvZMmMB2dfXqsfVPp04s1iOco0EDc1bjrbhw37mTtQoKCsw/VpBJBQ2Byle8/Cvmo4+VGVsbNjBDo29foHZtYMQIYMoUdprYtMnw9pBCCGHFvJKSkoKBg06Fb3n5wtyOyNgCgNmzgZEjJUgQJ0xoSh3jAgGeWObk1PyRnQ3s3g3s2cP01n37Sr+2caO1J41O4fMBp5wC/PADcMwxphwiMTERQ4cOxefLf0RytzMAAP5Vv6D7sT2RlZVlyjGFixQVAQcdxL/P1FQgP//ACvRLlvCNcNEie8YoDtS5M3D00cBPVXc1cazCQuC996zbdgCw44IJBQ2B0hWvtOwdSMqsDwBQ/87HuNuuMOV4APh3O38+8PHH3Ma2ZQv3xgYDPfn5pff1eNhF6OijzRuPECK2FRYCf/zB95zvvuO/mzdzDho61NRDnzN6BL6/4R6g8xAANmdslbVokfFthIWjxV+gICcH+P57XiTk5HDVJTubF/K7d5de0Acv6nNz+QeRl8ePggIgORlISmJP74SE0gJbWvPkrKiIH8XFtv6ojpWTw1Wgn39mWzITjB01AtMvvQ4oCRRg7XyMu/pcU44lXCYxka+/Tz/l33tlAgHJKHCixx8HTjzRfScphYVc3TejGGN1liwx5WGDK17fLf8JWZ2HIJDvQ7YZGVs7dwJffglMmwbMnMm/XZ+v5vdWpYBVqyRQIIQI3YYNDEb+8AMwaxbwzz9cTCgqKl09z8gwt7VtiQEDBsA39hx4fHuR6K1lfcZWVSZM4HWRiBvxFShYswY46SRWoQZKL+oLC8Pbk1xYaO3KUCzatw/o1YvRyZYtDX/4vn37In/nRnj27UCCJwPZq37F0KEf1vyNIvYpxS4cRx/NVceq9qf7fHydCufo3h3o2pUncm6rI1FQwEDHnXfydWXBySays/l+V7++4Q9ddsXLv2oBehzXy7iMrY8/Bm6/HVixgrUWcnLC+36/n4ECIYQoS2vOvXv3MhAwfz63IP7yC+eNlBTOm8H3l4qZvwkJQK1apg/T4/HgxH798dPyn5DZ8RTzM7ZC9eKLwIABzJSOt+3TcSp+AgWzZwOnncYTjngoHuh0WjOD47jjGCxo3NjQh09JScGgQadi5oqfkJRRDx07dUG9evUMPYZwMa+XK5UdO1Z9EeL1SlaBEz36KHD88e7bH1lYyGD1qlXADTewZoHZP0NaGrB4MWBClewBAwYgd+zZ8Pj2AmvmY9w144178L172XYrKSn8IAHA5zrYklIIERu0ZgB/797Sj337yv9/925g+3ZmI+3axQvafft48e/zlc65yckMCgQzhYNqCuAqZUmgAADGjRmJ+Xc9isDhvc3J2IrEMcdwO0b//jw/siLgLWwVH4GCZ54Brr/efSeWsS4QALZtA3r2ZDS3bl1DH37sqOH47vq7odPrYtyE4YY+togBBx8MvPVW1UV5tI7PQMHixcA11wDHHgs8+KDdozlQ587MRpo5011ZBYWFwOuv8zl99llg/Hhg9GgW3zNrK4Xfz84HJgQKPB4PTurXHz/++T18qxdj6NCPjHvwc8/l3+UbbwD338+siHADBn//bdx4hBDWy8sDTjiBmX+5ufx/QkLp9l+l+BEIMEM4nGzf4uLILnIDAcsCBQMHDkT2eecjsGyWs2psNW7Mc/YxY9htxm1bAUVYYrvrQWEhcMEFXL2RIIEzFRUB69cDffoYXk12wIAByN28EtkrFuCMM84w9LFFjBgyBLjiCmYPVOTzAcuXWz8mu2zYwMrxPXsyA+v55+0eUdUeeYSr5W6zd29p3YDu3Xkxe911LL5nRv2CwkJu0zDJOaNHInve2+h4TGfjM7bS0oALL+RFwscf8z3C42GdglCsXWvseIQQ1tqxA/j9d2YIBFuJB+sFZGeXZhMEswWs2BJcXGxZoCAzMxO9ju+DvXNew7jRIyw5ZsjS0oAPPmCbd4/H7tEIE8VuoGDnTq46vfOORLucrrCQe1H79zc0jcnj8aBfv5NxWPsj0djgrQ0ihjzwANPpkpPL315czJOUeLBhA3DoocBHH5UGVRs0sHdM1TnqKBY1THDZW1h+PvDmm6X/T0kB7r2X26+OOgowo1CVSQUNAWDQoEFQgUKMG2PiSaxSrC30/ffAb78B48bxJLWmk9MdO2QPrRBulpt74PtytJRigcJIFRSwHatFxo0ZCV2Yh2HDhll2zJApBdx1FzPlKltsETHBZWdZIVq2DDjySKbQSpDAHfLzeVE2eLChUeHnn3kSH017y7DHEzEoMZErlpWtEvz1l+XDscW2bQwQlL2wcnpwbdIkXmi7SVERT6oqbpk4/HBuEXjgAZ5wJRm0KzAtDTj9dGMeqxKZmZn4ZcF8jBs3zrRjlHPoocDLL7O98O23c7taRkbl901LY7aaEMKdcnKMzbTyeDj3lm2lGq5AwNKL4rPOOgu/LFjg7BpbZ54JzJ0L1Ktn3HuXcIzYCxR8+ilTOrdskc4EbpOXB/z4I/emGlRw8qCDDkLr1q0NeSwRw+rXB7744sBVynXr7BmP1Srb69+0qfXjCMfhhwMDB4aeiu4U2dlcGa8oIQG48kpuR+jVy5jsAq+Xe/xNdPTRRyOjqot1s9StC9x6K9/nX3gBaN+ez1fZi4qkJG5bEEK4U26ucYECrxeoUyf6eTU52dICfl6vF506dbLseBELFjk87DDZihBjYidQoDXwn/8Ao0ZJj0838/tZHOWCC9xVqEy4X9eu3PtedrUgnqPjrVrZPYKaPfRQdKmpdpzQVNx+UFHz5sB337FGRFZW5FkT6eks5JuZGdn3u0FyMt/zly1jcctBg5hJEDyZl0CBEO5lxLm8UpwL//c/zr3RPmZSErPt7r6bXRVEqSZNgAUL2D5RtiLEjNgIFPj9wBlnAP/9rxQtjAU+HzBtGnDttXaPRMSbSy9lgcOUFF5gzZpl94jskZoKHHSQ3aOoWdu2wLBhkQV0hg0rLSRo5RaGoiJW868uEKoUMHYsWykOGRL+SVdCAtChA4tTxosePYDPP2dv9Esv5XMg5wNCuFdubnTZpR4P0KYNt3WtWGHMVuTcXBZRfPhhoFkzFkOWluulPB7WOrrhBsksiBHuDxRs3Ah06cKe6FKPIHb4fMCUKSz0JYRVlAJeeYVt62bOBI4+2u4RWaNiUcCUFKBRI3vGEq4HHgg/UJCczAvL//wHWLOGv++0NOuKI+bksIZOTerXB95/nx8NGoTe6SE1FZg61ZxOCk7XogVXD3fu5Em8EMKdcnIivwj3erl3/o8/ON8/9ZSxgUO/nx9TpgCbNxv3uLFAKWZcvPaaZBbEAHcHChYs4KrJP/9YumdIWMTnY2rxk0/aPRIRTzweXmR162b3SKxTpw4vQmvVYppmXh73GjpRTg73p0+dyv+3bg0MHx7eFoTEROC22/izduvGgn+LF7OTghUnNvn5zCoI1cCBTKM/99yaV2k8HuCyy4B27aIbo9uZ1XJSCGGN3Fx2HwqHUpzDn3uOhWM9HuCSS9itwAxJSbJNtipnnQXMmSNFDl3OvYGC114DTjgB2L07/IlEuIfPB9x8M3/fQghztGrFInqffcZ2env3MgjrJIEAK963acMKy717l37t/vvDK2qYl8f3DZ+vtPDtYYcB33wDzJhRWhzPLEVFrFMQzglmRgZPfr/7jr+vqgIa6enAPfcYMkwhhLBNbm54LU7T0oCWLdlu9pxzeNvMmXy/MPM6QQIFVevUiVkd7dqFnhEnHMV9gYLiYuDqq7kHUfYfxge/nxHhjz6yeyRCxK6WLYHjj+eFuNP2Fv7wA3DEEcDll7Nv8/ffc5xBzZsDZ58delZBejrT8/v358r+mWeWfq13b2DpUuCll7j9wqwMA5+PJ7Th6tGDWXTXXlt+1Ty4kvbmm+YGOYQQwgo5OaEHCrxe1p1Ztqw0G66wkIWxzdyWrLUECmrSpAnwyy/AySfLVgQXclegYN8+nti98ILUI4g3fj+Le33zjd0jEUJYZfVqpt336cOWeH/9BUycWHktgXvvDT2roFYtYPt24OuvuW2hYoq6UmzT+u+/rGOQkWH8aojfH972g7JSUjiuhQuZ+ZGWxi0Yv/7KitNCCOF2u3eHdj+vF5g8GXj77fIXok89BezYYc7YgjIynN9K2AmCRQ6vv955CxGiWu4JFKxcyROiefMkSBCv/H5GjH/6ye6RCCHMtG8fM8cOPZTZA1OmMH20Zcuqv6dJE2YehXISctRRobUNTE3lyv369cDFF/OxjdprWVwc/vaDitq3Z3Dg449L0zuFECIW7NtX/dfT0li8dMEC4Lzzyn9t+3bgzjvNuV7IzOR7Q9++wAcfhLftLZ4pxW1xr74qmQUu4o5Awb593Oeyfr15BUmEO/h8XDH7/Xe7RyKEMFpxMffhN2vGyvW9erGt1UUXhVaYbtIk4NRTqz8JUYrvJ+GoXRt44gnWcRg61LhCeXl5TMmMRmKipHQKIWLP3r1Vf83rBQYP5laDI4448OvXXsutB0ZKSwO6dmVW8/btrBdz/PHGHiMeDB/OdvahBOuF7dwRKFi5EsjOln1AgnJyWMhy+XK7RyKEMMq33wJt27L+TFER21TOmsWgQaiSkoB33uHFfFUXzhkZlZ9YhqJFC7YqnDeP3RKirQXg97MytxBCiPKysyu/3esFHn8cmDaN83lFixZxpd/ohcXkZOC667gtTS5yozNtWtW/X+Eo7ggUSIBAVOT3A59+avcohBDRWr4cOOkkoF8/YM0a/rtqFTB+fGSr9omJ3Ps/YkTlwQKlom/9eMwx3AL1/vvsQBBpwKC4mPtq5T1OCCHKy8kp///UVNYD+OknYMKEyt8ftOY2BDOKnScksL6NiM6mTdFn0gnLuCNQIERZXi9wyincwyyEcKfdu4HLLgOOPJIpnOnpvMD/+mvWG4hGQgJbKZ599oHBAp/PmL38SnEeWrmS2xLq1ImsSFN+PjB/fvTjEUKIWFI2UBA87/vrL9aYqcrrr7MIrlkkUBC9114zZuuesIQECoS7eL3AiSdyJa+6omLXXMMiaEIIZyksZP2Bli1ZpFBrYNAgZhGMHWvcCYRSrHdw/vnlgwW1ahnbPjAxEbjwQmDDBuCmm3islJTQv9/ni7z7gYhtmzZxL7TPJ1knIv4ECxF6PKw/89FH1af8Z2dzASk315zxBAKsVyMipzXwzDOszyNcQQIFwj08HtYm+PDDmiuPf/ghMGQIsHatMcfeu5fVxd97D3jwQWDqVGMeV4h4MmMGcMghwC238CQwIwN46y1g+nSgUSPjj6cU8OSTzFwIBgsOOcT44wB8/Lvu4vaJc85h4avK2jhWFAhw+0EgYM64hDt9+im3tbRoweBWQgJTr2vVYmtMIWJdYSFw0EGsCXPZZTUHke++25wtB0FFRZJREK2FC4Fdu+wehQiDQX2ehDCZx8Ne6h9/zIIyNaldm10y+vUDfvut8oI3ZQUCXL1ZvZorm8uXs93YihVcKSws5BgKC/lGdPHF3EMthKjZn3/yb2bxYq72BCtWv/giUL++ucdWCnj4Ya7yP/gg6wuYqWFD/lw33ghceSUwZ07NLboKCoCffwaOO87csQn3ePFFvt+UrdxeUMCP//6Xf0PXXWff+IQw2w8/8P0hK6vm+65cCTz7rLkr1YWFEiiI1nPPmRvMEYaTQIFwPo8H6N2bKyyhBAkAoG5dpjht2MCiZtOn8wRrzRoGAlav5sXLsmX8fOtWPnZKCqPGlaV6BoMF//kPcNttxv+cwjzB36Xsi7PWjh3AzTcDb77JvfjJyQzivfIKMGxY+I+3di3w/POsaN2yJXDaaUz7r6k2gFLA/fcDbdoAPXpE8INE4NBDgS+/5GrYpZdynqkqJdbv5/YDCRQIgH8rM2dW/XWfjz3is7LYOlSIWNSmTej3vfhi/t2YKRBwRxvaXbuA669n8HnuXJ4PO0FeHrsSSfacq0igQDibx8Ne6uEECQCgQQP+m58PzJ4NdO/OrQMeD/cU5+Ud+KZSVFR9pNPrZf/cMWPC/zmEPbKzWThn0iSm7v78M1d8hbkKCliH4J57GGArKODfz6mnckUhnBOX/Hzgk0/YDuu333iSUVDAbJ9584CHHmKrpVAusi+4IOIfKWI9ewK//87gxpVXAvv2HRgwKC7mCdTkyaFtVxCxbeZMvt9V937k8wFXXcU926NGWTc2IZxmxgy+t5t9AZqW5uzFhkCAQfhrr+X7ptYstHvvvXaPjD77jOffwlVMPyNRSq1VSv2hlPpNKbWw5La6SqlvlFIrSv6tY/Y4hAt5PDz5//zz8IqDAeUvBn0+BgmKi1lFd+/e8CLPSvFk7MsvJUjgFv/8w5XmRo1YYO7ff5ld0rMnq+3HCMfNr1pze1Dr1twvmpvLv5+6dYF33+UFfahBgmXLgIkTmXp64YU8EczLK98b2+8HNm7kFqPLL685xd8uSgFnncWMiPvu43ySllb+PgUFwI8/2jI84TBvvMGAUk38fhbrnD7d/DHFKcfNsaK8ggJm1Vgx9xtZBNdov/0GdOzI4OG+fTzHLShgoMCs4o7hmjyZizfCVaxauuirte6ote5S8v+bAXyrtW4L4NuS/wtRKi2NKcLTp4cfJAAYKCgb+S0ujmwcyclA48bs+Xr88ZE9hrDeeecxsu73l75JFhYC69ZxG0tsvVk5Y35dsoR/s2efzXofPh+zCM48k9t9Bg+u+TFycoCXXmLLxK5d2RUhJ6fm35ffz3aIbdsy1dKpUlJYlXv9egZBPB4WZk1LY6G6YCaUiF9FRQyOh8rvB4YPB7ZtM29MwhlzrDjQ449bF/yvqdaVHfbsASZM4KLaH39Unq02ZYotQytn82ZpA+xSduU4DgXwasnnrwIYZtM4hBOlpXGrwIwZPHmORN26kX9v2XEcdhjTho3ouy6sc/fdB67YAqUp6yee6NzV5+hZP79ecQWDBL/8whOVtDRmAnz0EesThNJSyu9nhferrmI2gd/Pi6ZQ+f0MUPTuzcrKTlarFvDII8x8GTUKuOQSZhvIPCPmzAk/vbmw0JkXMbFLzmGdYMsWptVb9V4eSlFFK338MTujvPZa1duUfD7ggQfKF0W1w+uvO3vbhqiSFYECDeBrpdQipdSEktsaaa03l3y+BcABfbGUUhOUUguVUgu3WzBI4RBpaVxJ/PLL6C7069atuYVidbxeoG9fRkBllc99BgzgR2V1LfLzgaVLgVNOMb/4kfkiml+BCnPs9ihn2Y8/5omK1vzbGTWKWQQDBoT+GLNmcfUjmjRJrxc4/XQG+NygeXOeQD3+ePX9wYVlCooLMPCNgRj4xkDkFOTs/7yguKDmbzbCm28yiyYcjRu7o8iaOzljjhUHuuoqay+AQwl4W+mOO0LbSpuXx/oAdtEaePppcztSCNNYESjopbXuBGAggIlKqd5lv6i11uBEjAq3T9Fad9Fad2kgUaj4kJYGdO4MfP115avB4Qj2nY6E18uiZ59/XnM1deFczz9f9esoL4+rzqedZn+kPToRza8lXyudY6MNhp11FgNzjRrxhOSVV8Jfffngg8i3hCjFv9vJk4H335fVVRGxoW8Pxex/Z2P2v7PR7LFm+z8f+vZQ8w8eCPDvoGLHnZp07mzOeATglDlWlLdgAd9rrHz/rlfPumOF4qijQrtfURHQoYO5Y6nOokXAzp32HV9ExfRAgdZ6Y8m/2wB8BKAbgK1KqSYAUPJv9ZvrJFAQ+9LS2N/8m2+iDxIALF4YSfTS42Gv9SeflOrjbtewIfDYY1UXIPL7meY7cmTkNSxsZsj8aoSrr2YK6MqV3NYRLq3Z2STcCySAf7Nt2vBk5Lzz5P1CGMJf5Mfe/L3wF1nY83vBgvC22wCseyH1c0zjmDlWlAoEONdX1xXEDE4LFIwfz7//rKyqM2gTEoD+/Vm/xy779sn7souZeiWklEpXSmUGPwcwAMBSAJ8COLfkbucC+MTMcQiHS0tjtdaZM41bwX/zzfLV0UPh9bIy+5VXGjMGYb8LLgAOP7zqoI/fD3z1Fd9wI7lItZGj5teWLYFbbol8Jf/PPyPbZ+r1AqNHcyuJW7YbCEd7b8R7SEksX0A3JTEF74943/yDv/NO+Bc/aWlAp07mjCfOOWqOFaWmTmUnI6s5LSukf38WaJ42jYH6U08FDjqIQYOsLLYiTElhpx07nXCC8+o7iJCZvWTaCMBcpdTvABYAmK61/hLAfwH0V0qtANCv5P9Vk72bsSs1lelT335r3B7LDRtYGCxUCQlAnTrADz8AQ4YYMwbhDEqx1Vh19S58PuDDD4HLLnNbsMCY+dUJPvssvJXUhAQGJV57jV0SjMhCEgLA8GnDD6hHUFBcgLOmnWXugbVmoCDc7Ca/n9l4wgyxM8fGin37gGuvtb7lX1ISzxOdplEj4OSTGaj//HO2C96zB2jalHPJ5Mmhb1EwS0ICcMMNUkfFpaKo9lYzrfVqAEdXcvtOACeF/EC1a/Mk0im9QEV0lGLwx+8HTjqJ0VAjJ5BPPmEkNVRaAz/9JBXHY1W7dsD11wOPPlr1qrXPx5oGd9/NN14XMGx+dYJ33gk9A8jrBQ45hH/nrVqZOixH0ZqvU7N7eW/axOJ4cb71ypPkQUpiinVFDJcsCb+IIcCLF6cVWYsRMTXHxorbb7enCHFKCmtfucGSJcBff7Fg8wUX2D0aOu884NZb7R6FiIA7zgSysly7h1iAJ5xZWaxA37YtcPnlXOXduhWYPt34E9/XXw8vjTk1FbjpJretJotw3H472/VVJSEB6NfPNUGCmLJ7N09qQuHxAJdeykKUsR4k2LuX27Huu491Hxo0MCfjSWvgt994EteyJT+6dwfWrDH+WC7wyehP0KdlH/Rp2Qcbrt2w//NPRpucXf7JJ5FdAHXsaPhQhHCk7dsZ0Lejen5iojsCBcXF3EoJcBXfKWrV4jbBcBbxhCOYmlFgmJQURs03b675vsJ+iYm8+Pf7GRg45RRehPXsaf4+pT17gMWLw/uevDwWUbz/fl5QitiTksK6FQMGVL4HODWVhQ+F9b76is9/dRkFSUncavDuu+G1XHSLggKuAs2fzzaRP//MFFKAGVjHHcf2UkMNqrwfCPBY77zDj9xcjiFYQfzXX4EjjwReeAEYM8aYY7pESmIKZpw9Y///y35uqpNPBh56KLwtOGlpQJ8+5o1JCCepXZuv+XDrTxkhIcEdgYLnnmNR4fr1WRvASa67Dnj7beuLUIqouCNQAAADBwIvv2z3KER1MjLYF3zoUG4pOPZY89NkK/rii5ovOirj8wH/+Q9wzjlcUROxp1cvtvGbNq38yl1iIueXI4+0b2zxbNq06tsier1cNf3gA6bEx6LTTwdmz+aFenDuatqU2RPjx/PzaBUWsg7LW2/xuQwEOO9Vlq0X/NpFF7FgltOKeMWi7t2Bjz7ia8HvPzDDLSmJfwt+P9C6NYPvffuygJkQ8SA5mSnszzxjT1tjpwcKdu4Ebr6ZweULLnDe9rH27Xme9csvdo9EhME9gYLBg9kfe98+u0ciqpKYyMJixx5r3xjeeCPyXuwJCbF7ISLof/9jG76ygYLkZGDSJPvGFO8WLar6ax4PT3xuu815Jz0V+XxMH//oIxaX69OH/e2rK6QZtGMHV5KTktiu87LLeOFoREup5cuBO+7gNq/ERM6PoW6zKi5mltXzz0c/DlGzAQPYIvHCC4E//uDvv7iYr6dTTmEbxG7dpCiYiF+XXAJMmWJ9oCAQcH4tkGuvZaA5OZlziBPdeiswblzk5+nCcu4JFPTta8++JBGe3bvtO3ZeHtN2I3XccaGd1Av3qlOHFz0XXMB06+Rk7ptr08bukcWvHj3Y4qmsYOGojz/m36VTBQLMBHj+eQagEhNZkO6TT5gim5/P7RI1bRmYNIlbDYYNM65FbND99zNrIxL5+az5ctNN8jdilSOOAH78EZg3jxcm7ds7P0gmhFUOO4xbWpcssfa4RUXOzihYtAh47z0GCo46igV/nWjwYJ5nS6DANdzz7lO7tpyoOF1xsb2Bgu++4wVGJLxeYMQIY8cjnGnECKBLF75WmjcHHnjA7hHFt1NP5balIK+XgeF//nF2kGDpUmYgDR3KC3G/v7RqfUEBs9/y84GxY2s+qe3dmwEro4MEAPDnn9F9f0EBcM01xoxFhEYpbpU68kgJEghR0VVXlX/PsEJhoXMDBYEAt6j5/dzue/nldo+oaklJwNVXm/NeJ0zhrnegYcOkYqaTFRbaGyh4553It6YEAsCgQcaORziTUiyo89xzrLYv203MpTX3Tv72G1fdJ09mUaPBg3khdMklpRfYHg/w3/8CM2Y4s2d1UEEBcMYZrMJdUyp/bi73k2/bZt34ylq7NrrvLy5msdeFCw0ZjhBCRGXECOs7oQUCzr24nTq1tEtNUZHzF70uvli6jLmIe7YeACw49swzUqfAqQoKgF277Dl2IMB037IyMrhvOBCo+fsbN+bqsogPTZqwKJKIns8HrF/Pj3XrgH//ZTbA6tVMp9++nauiwW09BQWVbyNLT+fexSuusHb8kbjrrtKuBKHYvZtV7X/+2drtTfn5xgVvFy1iJo4QQtgpI4OB2rffDu38zggejzE1Y4y2Zw9rE+Tm8v+nnOLczIeg+vWB005j3Tmrfn8iYu4KFPToEVmfYWENre1bNZs/v3yE0uvlxeCGDTW3YklM5JuOEKK8oiK2pV23joGAf/9l66UVK/j/rVt50e/x8O+oqIiBg8pWC2qau3NzuTIyZAiDwk61aBGLYobT4qmoiMGTceOY+WTVCefatfzdBDM2otG/f+W3P/gg0KIFt1gIIYQVLr+cNWyCF8hms7qDV6hefLH0vTUzk4Vw3eDGG4HPP+f5gnA0dwUKUlKArl2BuXPtHomoypYt0X2/1owwhrvFZNq00gnH4wHuuYctxS6+uObvTU83rj+5EG60Zw+3BKxezSr5a9bwb3nPHhblS07m36XfX3mfdyMuRAE+/siR3Kbg1Jo0d90VWR9ov58nRq+8wroMjRoZP7aKVq40Zrte3bqV/z727WNHivR01liQ/fRCCCt07855yapAgdU1EUL1/vulGXpJSWxN7gadO/M9ZelSu0ciauC+d/XTT+eJq3CmHTui+/6TT2aP6O+/D/17tGZl8eJiZhK88QZw/fV8EwnlxLWoyNlF00RkPv+cKW4XXyxR65qsWQPccAPw+ONso/fnn9xGFAjwudu7l3vxKwsSGC03l/OAU39n69dH9/0XXGBdxsSqVdF3C0pI4PtuZf7+m/PvHXdIkEAIYR2luE3NqroBWVnWHCccfj+weDE/T04Gzj/fXXXcbr7ZuQEYsZ/73tkHDHDXH0K8iaZGwS+/MFtk/XquuA0fHtpWhr//Znp0rVrsfBDcRhBqMbQTTmAkVsSGwkJW1R0xgkX0Xn8dOPRQ7g8XlQsEnNN+NhDglqELLrDn+FozUHLffaw8X7EWwYknRr51wOdjjYLRo6MfZyh27Yo+uJORUXXG1apVQLNmrEIuSm3YADzxhHP+poSIRePHW7fH3YnFdefMKV04TUoCLrzQ3vGEa/hwuZ5zAfcFCo44Qi7qnGzv3si/9+abS0+sfD5WSD/4YPYor+7NYPVq3u/XX5mOFlSnTs2VcaUtYmxZv57bk154oTQ93O/nxd6JJzLTROqcOF9eHvef/vWXNccrLmbf+quv5palrl2B//yH/ewrrpT37cu9oJFKSAAuuiiq4YZs5MjIW8YGFRQAxx9f+ddGjQJ+/93aAo1OVlzMrJx27bgHd/Jku0ckROxq0IALPVaoW9ea44Tjs89Kt/21bg0cdpi94wlXSgprKsj7h6O5L1CgFE/4hTNlZ0f2fYsXAz/9VL4IWkEBJ8HrruN+pqq6XZx6KvdVV9xDW6cOV5erEgwSWLW6J8z1+edst7d0aeVp634/u6YccQQvboSzFRYCd95p7jHy89mesU4dbgeYPJnZST4f55+DD2ZR1LKOOy7yleKkJBb9q1076qGH5PDDedEaTfHE446r+kROKWeeQNvlySeBW2/l68fj4XwkhDDPVVdFF7gNVb165h8jXJ9+ykW09HRg4kS7RxOZyy93ZjcJsZ/7AgUAMGyY7GtxqkiLmt1yS9Un37m5XFm87rqqv7+y/bG1a/NkvzIeD/DUUywsFu2Km7BXYSFPFkaMYDCpuiwSv5/p0sceC9x9tzV77kVkiosZ/An2hzZadjbQpw/w2mv8PDu7/GsnKQk466wDvy8rK/L9qklJrAVhpWnTGCzwesP/Xsm4Ck/XrjzpTU/n+1afPnaPSIjYNmAA9+ebrUED848Rjk2b2HUI4HmMWxe8DjrIPQUY45Q7AwUnnVT9SrGwT3Fx1RfnZWkNfPIJ8PXX3Gf1ww+Vt1QLys8H3nyTWQehSko6MAiQnAw0bMhaCOefH/pjCWdav5693V98MbxK9H4/MGkScPTRrHEhnKmoCHjgAXMee/Bgdleo6nXj8ZTuzc/O5gX3aacxABlpRkHXrqyXYaW2bYElS4Arrwy/8FcgAAwaZM64YlGvXsD27cxcevFF6wqtCRGvEhO5lcvMBZ/kZOfVKPj669IASb9+zhtfOG6+2bntJ4VLAwVNm/JiTzhPSgqwe3f19ykuBiZMAMaMYTGTfv1C2zfu9/N7QglEBJXNPPF6gW7dWKisU6fQH0M402efcRvBsmWRVcj3+Zip0qUL61wI50lKMi/lc8eO6uedvDxuUendm90zLryQrzm/P7LMqYwM4PbbIx9vNJKTgQcfBGbN4gpOTZ2D0tOBDh1YHLZ5c2vGGCvS04Fx41hoTQhhvgkTzO26kpzMYtlO8uGHfB/KzOQ+fzfr2dOadsEiIu4MFABc5ZB9Lc6TnFx9oCAvj6tyb73FC7V9+3jhH2rl2m3bWI08VMEUYY+He6Fmz3bmXjMnW72ae+Gqy/iwUnCrwciRB6aLh0trvibHjXPOzydKJSZytcEMNRV+UorbnebM4RwVaf2VoDp1gP79o3uMaHXvznouo0dXvhUhPZ01GaZOZZDk2GMtH6IQQoSlTRtz64EkJjorUBAIMOgLMEAyYIC944mWUsBNN0lWgUO5N1AweLA1BUxEeBISqg4U7N7N1Mzvvou8R7rPBzzySOjp4nXqcPXs7beBhx6SViyRGD6cH716AStX2juWdesi22pQneJipqBPm2bM4wljeL2sXWJW4b+OHaufDwoKuM/cCOnp/FmcENxOTwdefhn44ANmF2RlcZ486CAGYdeuZW0GJ4xVCCFCcfXV5tUuS0hwVqBg8WL+m5QEnHtubHSCO/tsec9xKPcGCvr0Me5CQRirskDBhg1M9//jj+h7S+flcUUslCyEd9/lMavqAx7vli7lxUHfvsCr/2/vvMOjqp43/p5s2m4KRVARUKogWFCCIioWUEB/CCoo9go27H5t2BULKvZesSsqIAo2UCyodKkiRXrvJLspmz2/P96sSUjbcuvufJ7nPkm23Du5u3fuOXNm3hlV9flffgEWL+ak6Y8/gEMPpRK9HS0Gx4/nqkGspQa1UVBAtXLBORQWmtNGMBhkZtHvv1vXlkkpDuicRO/ebBu6cyewbRt/v/FGEXcVBMF9nHmmeVmBWjsrUDBxIsdg6enWtdo1G58PuPRSa4Qphahwb6AgJ8d9PUOTgdLSqoGCBQu4erd6dXT6AjWhNbBkCfDKK3W/tk0bbkJVAgG2PnvgAeCnn1iasXNn5dfccUf5qmooxPc89RQF0qZMscZOI0sNamPVKuMDEELspKdzMltTW9RoCAQYaBo0iKvnffsC335rzeednk59g1i6DgiCIAh14/VyEcMMPxsKWdfSNhI+/5zjombNEqsF6403StavA3FvoAAAzjhDok9Oo6SkcqDgl1+Arl2BrVuNneAVFAC33cYWMUJsfPghb4DhFoF7KsxPm8aU/D3x+xn06dOHE68tW8yz0YxSg5rweu0vrRDKKSyk8OixxwI7dkT//u3bgfffZ7ChQQPg/POZYZSfz4BTpLoo8ZKSAtx0kzXHEgRBSFb+9z8KGxodLCgtdU5Gwe7dXHzLzOTiTiLRqpXo4jgQdwcKevWqW71ZsJbiYqaxAsDo0Rykx6IQHglFRdLiMB7eeqtyDXZhIfD882zvBVBcprYV10AAGDOGzv3NN41P+zOz1KA6lKLQm+AciopY+nL00eV+pTbWrgVefJGiffvuC1x9NTMHioriFyOMlZNOAvbf355jC4IgJAtKAU8/zc3I1qTFxc4JFEyZwgVSrdkFLNG44w7ztCaEmHB3oODII7mCLTgHrdmZ4JlnWJNr5gQvGGTGwhdfmHcMIygp4cr7EUcA33zjHHX9665j6UHr1kyr83g4+Q8GKZbz55917yOsBn/DDewRv2hR/HaVlLDnu9mlBntSUMBJqeAsiouBZcs4+a8ue+Xvv4Hhw4GDDuJ3+bbbmA1TXGxekDJSsrLco32Rnw9MmMBVqhYtGIgXHSBBENzGkCGs48/NNU4gzymLkuPGcVx9/PGJ2cGrZ8/ybmWCI1DaKZOWWsjLy9MzZsyo/smTTipvEyI4gwYNuIJnVb13gwbAv/86J+JbkeJi1kP/8gsH3VlZXCV/+WXg8MPttq4yoRDtzcxkWcG330YX1FCqPB3ugQdii+ivWsXztWSJPZOUAQOYCVMBpdRMrXWe9cZYR55SugYP6xzS0oCmTSlCuGoVu1R8/DEzDUIhewQ26+LAAxnIcKKaczAIzJjB4OXYsSzz8HoZnNOa1/IhhwCTJkmHIcE0ksG/AnWMYwVzWLqUc4SNG+PTx8rOti8jbU/224//z5gxbDWeiDzzDDBsmGhGGYQC4vKx7s4oAKhTYGSKkRA/hYXWXuB+P1e0nUZREXDqqeVBAoCr1tOmAcccw0npypX22liRlBRODhYsYHpbtEFErfl/vvACyxG++y6692/ZUl5qYNdK5sKF9hxXqJuSEnZPadoU6NEDePZZlhoEAs4MEmRnA3ff7ZwggdbMmHnhBZ6/3Fz2337kEeCvv3h+d+0qv+4LC4G5c5l1VFPLW0EQBKfSpg19WF5efPMEpwjRrlgBrF/PBac+fey2xjwuu8w5mbdCAgQKTjnFOQMxgVg9ySsq4urir79ae9zaKCxk6u7UqVXPR3hCPW4c06VvuCH+lpFGctdd8U28AgFgwwYG8fr14++RkJXFVWOrSg2qw0mBG6EqwSCzB/Lzy0U4nYrHw/IZOykuBj76iKVPjRqx/Om224DJk3md7t5de/leWCOif3/LTBYEQTCM+vW58HHuubFP+J2SUfXtt/x5wQWJLeSem8vPKzXVbksEJEKg4MADnVM7JNhHIADccovdVpBAgAGsadNqD5oEg3z+tdcouuYE/vmHmQBGKML7/awTbNOGq5h17dPrBR59lAEDuygpYYcOQYiHjAzqbKSn22vHJ58Al1/On9u28ZqMNpBbUsLyCUEQBDeSmkrB5Uce4Tgj2om/U2rmw3pcV15prx1WMGIE2yU2asTPSxaEbcO0QIFSqrlS6kel1EKl1AKl1A1lj9+vlFqrlJpTtp0a54GAk082xGbB5fz1l72r0QAH4j17AtOnRz4gLyzkQH7JEnNti4R77jFWILSkhOUWd9wBHHYY0wBr47LLgIYNjTt+tGRmUjjPBVjmY4XoUQq49lq7rSApBtzmnVKfKwgWIj42wbjhBgZM330XOO00BnQjCRo0aGC+bXURFu9u1YpjqURnr72AJ56gHsNXX7G9sc/nnOyOJMLMjIIggFu01h0AdAVwrVKqQ9lzT2utO5VtE+I+0umnJ/aXxyn1UXWRkcEVNLtEBVNSjBkUx0pBAYVzZs2KvpQgLc3+wfi//wJffmlOsKWgAJg/H+jalSutFdsyViQ1lUI2dmUVFBYyA8IdWOdjhchJSeE9aZ997LaEgS8jfGJhofNLPQTBeMTHJhqZmSyl+uor6iK9+ipw4okcv9Y07rBz8SJMePHJKQFoq0hJAbp3B957j9me77zDxeHaPi/BUEybVWmt12utZ5X9vhvAIgBNTTlYz57OFLMyigYN2ArSqReFz8d0rvPPB374wT4RkjZt7EtPys/nzeavv2LXG7A7G+L++82fDAQCwBtvAC1bMihRHWecweftoH17ZwwKIsBSHytETmYmcOeddltBvF5jfGJ6OrBjR/z7EQQXIT42wcnOZi385MkUCXzuOS5mZGRUXqBzQhvCCRM4ab7gArstsY/MTODMM1keu24d8NRTzK7IzORnJpiCJcuvSqkWAA4HEG7MPlQpNVcp9ZZSqtqcHqXUEKXUDKXUjM2bN9d+gL33phJ2opKWxp72Y8dyImNVwCAtjZka9erxmB4Pfx5wAHD00XSw99zDFeDff2cNWLNm9q085dnUYWn3bva0nTs39iCBUvYGCtasoSCkFZ9dIABs3szvT69ePHZFlAJefNH6TJqMDIq+uZC4faxVhiYD7doBnTrZbQUxMlAg2h1CEmP6OFawlwYNWPoYbr87YkR5iv/++9trG0B9guOP53xH4ILOlVcCc+YAixaxnWKzZuVzFcEwlDZ59VcplQ1gCoDhWusvlFL7ANgCQAN4CEATrfVlte0jov6z11/PyYURImxOo3798vZUWgOffw7cdBMfqymFuy683nLV1KIiThDr12e6bPPmQOvWXNVt1oxBmKZN2b+1LuHIkhL23l661NqJr9fL6KLVooC7djEt6u+/48tqqVcP+Pprtk20gyFDmNJlpD5BJKSmchLy4IOsH6yocnvCCcDPP1uXoeLzUYCyY8dKDzu9z7chPlYpLR2+DSA7Gxg1iqseTuC331iLu3NnfPupV4/CpEcfbYxdglCG0/0rYOE4VnAe69dzXGxnWeuOHcxq+OwzZlwK1aM1S3/ffBP44AP+bXdJrwNQQFw+1tTeE0qpNACfA/hAa/0FAGitN1Z4/nUAXxlysNNO4wBt1y5Dduco8vP5hVeK24ABrLF65x2muPr93ABOtDIzGVErLeXqbUYGlUObNAFatGCKfvPm5QGApk35vBGOMC0N+P574NBDrU1VTUvjMa1k507guOPYPqy4OP792ZVRsGED67+sDhIADFAFg8C997L7wwcflGeGPP88cNRR1rXbzMoCOnSo+3UOwlIfK9SN18uWoE7B6zUu0CYZBUISIj42yWnSxG4LWBqRk8N5jlAzSgGdO3N77jlg0iRqUEycyLlRfr7dFroS0wIFSikF4E0Ai7TWIys83kRrvb7szzMAzDfkgMcd56xe9Ebj91cuOUhNBa64gvVKL77IyXnLltVnAVidwt28OeupevSwbpIXCAAHH2zNscLcfTczCYyaYNsVKHjkEfszcfx+tmbs3p3f6SefZGbKqacC48aZWxKRnc1Az3XXuaoFj+U+Vqgdrxe49VZnpT0aFSgIBiVQICQd4mMFRzB+PHDOOfa323UTqaksbe3ViwGCsWOBV14BZszgoqhVc5MEwMyMgmMAXAhgnlJqTtljdwE4VynVCUzZWgHAmIagPh8nirNmGbI7RxGuD61OmyAzE7jlFm5O4uijgaefpl2xlkdEQ26u9d0WGjTgpMDNgYItWyguaERGhBEEAsxu+OwzRoKffJIlGUYHCnJy+D+fcAJw4YWM1Nevb+wxzMdaHyvUzZAhdltQmcxMY4KAJSVsKyYIyYX4WMF+srOpnyDERnY2F6D69wd+/RV46y1gzBhmIgeD9mTTugjTAgVa618BVLc8Z14bmTPOYAs2p0x6jCI1lYECJwiqRMPmzdatVB90kDXHqcgdd/C4H37IFKe0NEYuY/2f7QgUPP64/dkEe1JYyO2SS4AuXZiZ8sMP8WlApKQw0BYKMShw/vlsseP1Gma21djiY4XqSU2lOKfTgk1erzHXd3Ex/bkgJBHiYwVH8PzzdluQGIwfD5x3Hn8Pix4qJYGCOrBRncMEevVKzBYZSnHl100UFFA11or0HqXsEdny+Tg5GD+eegxffMEVxcaN6YSiTROzOlCwfTvw0kvObS3q9zP6++23sTny1FRGkvfai2U6X37Jz+mTT9jn3sVBAsFhpKUBt91mtxVV8XqN8Ss+n/sC1YIgCIIQ5txzgenTqfNWWsoAeFjfTagRU8UMLeeII+zvRW8GoVD89aFaA1OnUg30m284mW3XjuJtbdoArVpx22cfY+q0X3jBus8iOxs4/HBrjlUT6elc+e7Rg5PvBQuY2vTRR8Dy5Zy01laCobX1392RI52XTbAn4XPi9UYWdMrIYPZAo0a8KZx9Nv2Ci7QHBBeSl0d/6jTC7RGVik2rIDOTZTrvvw+ccorx9gmCIAiCVeTlAaNHA5s2AS+/DDz7LBeiROiwRhIrUODxAMceC3z3nd2WGEtJSXyBgq1bgb59gblzOdkKhdjyZe5cTqp8Pv4sLubEbJ99KIrYoQMnWiedFN3x/H7g0Ueti9RpTeE7p6AU9TIOPhi45x52FfjqK5YoTJ3Kyeye3TlCobpbTxrJrl3AM8+4RwC0tiCBz8fvbevW1Bs480zgwAOts01IbrKz2cPZiaSnA3/+Cdx4I1t/RuOTvV5g0CAOpHJyTDNREARBECxl772B++4D7rqLQoePPMIOZkVFzl9As5jEKj0AqFNgtcq/2RQWxl4fOns2J/wzZnBFe88LIBRiJG3XLh6npARYswb45ReKyfXtC8ybF90xX3nF2pqfwkJnruaF2Xdfpr5PnkxBsPffZ51UvXqcZIRbO/boYZ1Nzz/v7uyb1FRuRx0FPPEEszYWLKBuhAQJBCupX9/Zq+2HHQb8+CM743TuXL0obkUyM+mzJkyg6JMECQRBEIREJC0NGDiQc6Xff2dwPDOz9oW7jAxndTcymcQLFJx8snF9o53EunXRv+e995hhsWlT7BN3vx/o06fqCnhNFBYCDz9sbd1P06a82N2Az8fgywcfMGgwaRLP1+efM6vDCqzUjzCLYJDOWile8/vtZ7dFQjKSlQXceac7Slu6dWN95pgxQPv21QcMvF7g0kuBpUvZEUQQBHeTiONhQTCDww7j2HzNGmYDN2rExbw9CZcKK5UUgfTECxS0bl39B+t2NmyI/LUlJcA11wBXXWXMhH3LFkbZIrnh2NFqr1Mna49nFCkpwJFHUgRt332tO+7LLxvfbtAOCgqYTn3YYcC99zpXlFEwj5QU3qjt9PkXX2zfsaMlHFhbuBB4910KFGZlMUDQrBm7i7z0Ut1ZB0Jy8McfvF98+y2wZEnidZRKdL75hm2cW7QA/vc/rpi6OZNQEKxgr71YkrBhAxdc8/J4jwxnERQX817q83GeNWAAMxASce6JRAwUAEDv3nZbYDybNkX+2gEDgLffNm5Vv6gImDKFPe1ro7gYuP/+2kX7jCY1Feja1brjuZ3CQmD48MRReg2FmBnx1FMU5fzpJ7stciduWBHfk4wMaqFMmQK8+CJw3XUsRcnNZW1+bq65XXDS01lS5KRJdTDIessVK2p/nVLU8li+nIGBO+7gRLBbNyusFNzC448D118PnHMORWF9Pq6yde7M8rlHHmEXmenTqYUkq9fOIBgEbr2V1/jOncDKlcDTT7MzWIMG/Dy/+EIE3AShNjweoH9/+rdp09hWOzOTQQOtOdd54QVm323ZArz2GnDccRx3JFBXrcQSMwzTty8HS7t3222JcUQjZti3L1eGPB7josd+P4U/unUDjjmm+te8/bb14ng+H+v7hch4443E7Bnr93M77TTg//6PE8dGjey2yj2kpzPQ56aBfloaS04OP5zbRReVP7d5M7VV5s7lqujs2cC///L/TEmpXq8lWpQCbropvn0Yydy5HNRs3Mj/rVMnihj2719zwMTjqXzeBKEi553H8ridO8sf27qV26xZ/P74fLwWCgt5be23HzM7Dz6YejGtW7Oj0v77u6dE0M2sWcP2v4sXVy4vLC0tHxN/+ikwcSIXgcJBn9NPlxaoglATBx8MjBpFEfA33uDiVEEBg2233srxxosvstvWpk3sePbKKwzShVsxuhSlXTAwzMvL0zNmzIj8DVu38mbl4g+mCo0aRSdouHIlB4AzZxq7wt+wIbBoERVDK1JSQq2AWEUXYyUzE/jnH6B5c2uPW5HFi5n63rAh207Wq8ft1FOdVTtfXMzPaMsWuy0xl/R0ToxGjgQuvzzu1XKl1EytdZ5B1jmSvEMO0TP+/dfabKB4qVeP9YSnnRbZ60tLuYI+dy4wZw4DCPPm8X7h83EVLppMm969Odh2ClOmMMNhxQp+//1+Bn6ystgN5JprnNUdJllZtoylZk7KRKmJ/HyOPWIt6/J66Y+DQQYSwmnw7doBHTsCrVtDnXNOwvtXIIZxbCxMmMCJSkFBdItE4RXSffdlp6szzwS6dLFON0kQ3EZpKe//jzzCbIPSUuD444Evv2Q2Y5h//gHeeYfCwAUFvC9b3FVBAfH5WK2147fOnTvrqGnbVmu6vsTYMjKiPwehkNbvv691bq7W6enG2JGaqvVRR2kdDFY+1htvaJ2VZf158Xr5f9rJK69onZZWblNaGu1q3dp+2yry6qv2fEZ2bVlZWh9+uNYLFsR12gDM0Np+P2jm1rlzZ62/+ILfW7s/t0i3evW0njo1rs9Wa611fr7Wf/5JH3bllVofcQS/O5mZ9J0Vr+2K361ffon/2GYQCPD/ef55rQcM0LpZM62Vot0HH8zPWbCeUEjrRx7hvTwjQ+sePbQeNUrrbdvstqx2unc35/pNTdU6Jycp/KvWMY5jI6W4WOsbbzTGf5d9Ljo3V+tBg7QeM4Y+UhCE6lm0SOsrrqBf79ix6vxIa/r/qVO1vvRSrbOzeY1ZNFaK18cmZkYBwFSQp59OnH6YKSlMI0tPj/69W7ZQcGPiRGNq030+rk498QT/DgaZsrZ+ffz7jpZDDwX++sv641Zk3Dhmb+zZGcLn48pl27a2mFWFNm24mpVMKMWsk2uvBR58MKa6saTIKAj72BtuYFqdGzQscnJYO2hGa1StKWQ0bx79S7h8Yc0apk83awb8/bd7tB1272aq+LRpzL4aNMhui5KLoiKKXo4fX/nays5mplenTnz+jDOAJk1sM7NafvqJ46niYv4fJSX8vaSEWzBY/jO8iu3xcMzi8fAaSUnhz/AWRmuoXbsS3r8CJmYUaA2cdBKvbTP8dm4uP/cuXVii0Lcv/Z8gAMwi7tqV9+NOnVjK0qEDcNBB9GVuuUcawa5dvM/W1TGouJhCo6+8wrbpqammZnPGm1GQuIGCSZOYPhVpWz+n4/VykhfPIOKbbzgY2bUrfi0Br5d1bv/3f1QFveYaa4VxMjM5Ef/0U6BHD+uOWx3TprGPesU6ToCppc89B1x2mT127cmQIayxSqSSnEjxejngGTWKgk5RkFSBgmCQN/2//nJ+Z4zMTGDVKpb7WEVJCUX/9t5bNDCEyNi0iT5nz5rxPfH5ONFu04alImedxd/dRjBYHlSo62dREVTfvgnvXwETAwWffsoxhhVlYz4fF9+aNqUg4hlnUORSShSSl+nTGagKj/8zMnhvLipikKBlS5a85eWx3Oigg7iwKN8ZsnMn8Nln7C6zYAEfM1jrTQIFNVFYyBrWRJkU5eQAv/0Wf41pfj7b5IwaVfugJRI6duSE4oADgLVr49tXNIR7fT/2mDN6mK5aRee3ZzTf66XA4znn2GPXnnz3HdCnT+Jk2cSCzwf07Am8+mrELSmTKlAAcCW9Qwdg+3Z7jaoLpTgYEYE0wals386Ml+3bowu8ZWRwpXjSJODYY82zzwEkg38FTAoU+P0cf9mhO5SWxu+px8Msg7PP5qKNz2e9LYJ9fP89MHBg1YWyPUlPZwAhGCzPQj74YGaqhAMIrVpxdT1ZWb0aeP99jk83b+b81YAFm3gDBYkb0snMpBJ2opCSEl3ng5rIzmbk6scfGemLx6lv2gSMHl23gzCKrCxOYH77jeqiTggSAMA++1SOAHq9dIKTJ9sfJCgqouM55BBG/5Mdv58lOG3bsq1NMgdNamLffVlO4/T2PunpEiQQnE045T7awV5RESdgEQYzhSTloYfsE6AtKeHC086dHGNccAEFnY8/nhOddevssUuwlu3bIxtHFRczm9nv5+9Ll7I73X33sXS3c2eOOVq0oBD4ffdxfjF/fuxiqm6jeXPgzjspSPz77yyZrV+fcx0bSzgSN1AAcGJkZh9tK9HamEBBmKOOYo3t//7HizOWL+GOHey/bXbJQVoagwSPPkrFcqcFgDIyyr9nXi8v7n/+YQq3XaxeDdx+O1Okr76aztYGtVVHEh7g3HGHMzQunMhxx/FG7eTVoexsuy0QhNqpV48B41i+q5mZbC0oCNXx77/As8/GnxlqFLt2cUL388/AzTdzdfjAA4F77qG+iwuyl4UYyMqKbxIbDPK7k5/P31eu5GLOww+zi0+3bvSfTZsyY+X229ntaNYsd2gpxcqhh7IV45YtDKicfTbnFzYskCZ2oKBXr8RZcSopMT69LD0duP9+XnCHHRZ9uyatrUl5Ky1lW6Xly6mzsGOH+ceMlhNOYIbGr79S5NGOAJXWHJT26sUV82eeKXfAQlUKClgTdvTRwHXXyXmqSCjElGev17m1hBVbEAmCU+nYkQO9aDN0undPLiEwITquusq5pbV+P4MGS5YAjz/O73KjRsAll7CFo8E12IKNtGhhThAoFOL4dfduBhDWreP49oknuPh14okMxDZuDAwfbvzxnYLHQw2Ijz/mfOv115m1k5Fh2UKOQ0eABnHooYlzoy0qMm9S3r49MHMmHXpWVuQ1Qmlp1qS9hUJUG3/uOaru7r03RZ6uvhoYM8YZtdQTJjCQccQR1h97927g+edZq9ivH7UIwoJRQt0EAlT6b9mSPXAF4O67KdC5Y4dzs1AaNLDbAkGIjB49WC4X6cAuK4tCwYJQHd9/z0WJcJcJJxPO4Nu2jdpY557LdOoePXjf3bDBbguFeGjRwtqsFq055t21qzwboWlT645vJz4fy5l/+olZw48/znLszMzYOuJFSGIHClJSGHlJBEIhc9sPpqQwZf7vv3nOIskusDrlLRxhLClhB4hXX2WEunVrKkonGwsXMjVrn32YRr96tayKx0phIQNx557LjIw1a+y2yD7Wr2c2it/v7IGodB0Q3MSll7L9aCTBAq3rbrElJCclJbzvuzXtOlyiMHkycOONnGgedBDwwAMsA5QSBXeRlcXsw8xM648d7r52ySXWH9tuGjcGhg5lVuy8ecBtt1HTJjvb8CzQxA4UANQpiDal3qmYGSgI06wZo9VvvcW0HhOjVHGjNW8627eznjoZCAaBL76gUmxeHvDOOwzYuHXQ4DT8fg5g2rUDnnzS+S0CzeD++93xf1vZFlEQjGD4cAp11VWGkJEh+gRC9Tz7rD1dDsygoIBBg7//Bh55BDjmGPr1yy9nmWmyiNi5na++YrDHyvlCdjbw7bfMok122rShsOm6dcAPP7Bdak6OYeWZiR8o6NnT2ati0bBpkzXHUYrCGcuXs5dzTSsg8YqYGEmiZxRs3MgJ3D77ABdfDMyYwQBBony3nUQwyIDBffcxrSvZ2L6dq1ZORxThBbehFIW4Djmk9kG16BMI1REeByTiwkBxMQMHW7eWt5WuX58lcO+8Y934V4ierKzyTmpm68KlpLDs8LffKLoslKMUhepff53X0YcfAqedFvduEz9QsP/+iVPLanUUuWFDftG+/JKD8oqrICkpFBO58UaKNaWlMXpll3jk6tX2HNdMtGaLlP79mZ73+OOs85PyAmvw+ynGlGx060YBndRUphNmZ/ParlePzztB3DA1lVolguA20tO5WrrvvtVfSz4fsw4EYU9uuik5tIfC2aKFhcxwve46juUPPphq+PPnS4mC06hXj7oZ++3H8YMZpKbSb86cSQ06oWbS0hgk+OqruHcVoWqdy+nTh6n0bscu0b4ePagJcOedjFQFAowg3nQT1TgBPjZjBlvjfPMNL2SPhyveVmgZ7NjBVdBE6HLh9zNA8/jjLDfx++WmKFjHOecwIJWVxQBBOIUtJ4ffw/79KSZkJ+npDGQKghtp0ACYMgXo1Il96PfkxBMtNylmgkEqcnfs6LzWxYnEtGnsnuGGbC+jCS+OLFjAFOvHHmNA7YwzgAEDqKvl5DJZpzJ3Lttsrl7Nn//8w/aErVoBn38e/YS/USNg6lSgc2dmgBgphJyRQcHun39mZq1gHVprx2+dO3fWcTFmjNa5uVpzmOvezeeL7zwYwcyZWrdtq7XXq3VRUc2vKy3Vet48rQ84wJpzk5Wl9dKllp0GU9i4UeuhQ/m/ZGXZ/32TTWtAA5ihtf1+0MwtKh87YQKvfzs/l9xcrT/7LHKbBXsoLtZ6+nS7rXAu06bxvl7xu12/vtahkN2W1U1RkdavvKL13ntrnZGhddeuMe0mGfyrjtbHbt+u9Yknat2undY33MCxTceO9vpcJ25K8V6Qmal1795ajxql9ebNkZ/nZGbRIq1TUsrPX8Xz6vNpfccdse97+XKtGzbk52PE5+z1an3kkVrv3Gnc/59ExOtjHZBDagEnnJAYfVsDAftFxo44glHdVatqj+CmpFCUxqrWN6mpjIi6mSuuAF55hXV6VrSdFIRY6NOHJUcW9fCtFqUko8DpaE1Rsi5dgDlz7LbGmXTpArz/fuWyPqfrExQWAi+8wJZkt9zClcOiImDWrMQYZ9nNihXMNPntN2ovPfccNS1WrLDZMAeidXmJwjffsHNX06ZMS58+3W7rnE3r1ryHh89fRfx+imb+8ENs+27Zkt9fI8T0fD5mjEyZYpg4nxAdyREoqF8/MRSE09PtKz+oSFpaZK3JPvjAunrmkhKKL7qV5ctZi2d3IEgQIuGhh5hmbFepj9YSKHA6Tz/N9FWlqPYvVM8ZZ/B68vkYMDBAfMoU/H5g5EigSRO2492ypXJAOzOTkwMhdqZPp19dvbpci0BrLhLJ4kHd5OfzvM2bx2tKqJm0NIqV1xSUDASAgQNjX+xr3x746SdqHMWKz8fSkq++sqf9ogAgWQIFAOtqzRLYsIq0NCpZmkEwyCiskTf6V16xRp8AcL/w3PDhEiQQ3IPHw3rZsMCh1ZSWJo5IbSIycSJw993l+ipffcXWTUL13HILcMEFvF86TZ8gPx949FGKlN1zD/WAqpu05ucDX39tuXkJw9ixzH7dscPY2u5kZdIkGVPVxaWX1j6Rz89n+8FYu2t16gR8911s2Yc+HzB0KDteuH3u5nKSJ1DQuzfFudyMx2Ne54M//qCS7F13GbO/RYuANWuM2VekLFhg7fGMYtMmihfKTU1wE40acWJQV094MygqkowCp1JSwva6FYPEWjPDQKiZl14C/vyTPbGdwM6dwAMPMIPg4Yf5d21t+UIhdkgSouepp4DzzkvMtod2kZpKYT2hZo47juepJoJBzgvuvTf2Yxx9NDBuXHTBAq+XPufxx51dhpUk2BYoUEr1VkotVkotVUrdYfoBu3bl4NLNaF17RsHs2VQD/d//op90fvUVywSmTzemnvStt6yf+C5bZu3xjOLJJ/nZCoJBWOZfjzySN3Or9Qq0dn/gN1FZurTq4K6oiBlmMhGqGY+H15PdA+Pt24Fhw1jr/fjjXFWM9HNbvTpp+t0b5mPXrWMph1XZl8lCfj7wxRd2W+Es8vOBl18GLr6YWQIpKcD559e+Yu/3M8g7eXLsx+3ZE/joo8gWFbxedle76abYjycYii2BAqWUB8CLAPoA6ADgXKVUB1MPmp5O4SA3EwzWHCj46y+mrW3axJWJI4/kTTtSMjI4QCksZMpoPIRCwNtvW9/GZ4/U1g/mfYAWz7RAygMpaPFMC3ww7wNr7YmE3bv5ebk9iCU4Bsv969ChzNiysoYwK8v+CZVQvY+dP7/6z0ZrppEKzmTLFi4yNGtGLYKCgugnrxkZTPlOcAz1sfvumxhtnZ1GKESNFBdj6Bh25cryhcTRozlnABg0qOveHQhQz2DjxtiPf/rpDADUFizIymJw5/zzYz+OYDh2ZRQcCWCp1nq51roYwMcA+pl+1DPPdLcgRnFx9aUH8+ZRKXnXLv7t97M/aseOkacCnngiVwW15o3+n39it/PXX8uFeKyksPC//u4fzPsAQ8YPwcqdK6GhsXLnSgwZP8R5wYJXXpFsAsForPWvSgHvvssBr1WT93gEkgRDqNHHzv3gPz9ciYICarFI/bWz2LgRuP56YP/9geef5/gh1u4Fu3cDY8YYa58zMc7HpqRQwFAwnq1bXZtpavgYtmFD6voUFNAHhwN6nTsDOTl1vz8/n8KrseoVAAwAjBzJwFhODjWOfD5eA7m5tKl379j3L5iCXYGCpgAqLnevKXvMXE4+2d2iGMFg1YjeggWsMwoHCcKUlvKmfe65wDXX1D1xP+qo8sFBSQlw//2x2/naa3QqVuP1/tcicdikYfCXVE6X9Jf4MWzSMOvtqoniYuCxx5yZjiurtW7Gev+alcX2VFaVINSvb81xhBqp0ccGv605+LlrFzBhggXWCXWydi1w5ZVAixbAq69y1dCIzLYffkiG4LexPvaUU2qvFRdi56uv7LYgJgwfw+bk8Fx4vbzOw4uISjGroK6slmCQWQgPPBDb8cNcdRXLm6ZNY2bDc88B991HfZajjopv34IpOFbMUCk1RCk1Qyk1Y/PmzcbstGNH9zvjiun1ixYBxx5LkaGa8PuZ7nnYYf9NoqvF62UdktfLaOMXXwCrVkVvX2EhVxTsGCgo9d//uGpn9bbX9LgtfPihs0oOlOKEr23byNpfCq7GcB/brh1LjqwIFuy1l/nHEGqlRh+bUctqdH5+/ANNIX6efZaiiW+/zXu2kRmAxcUcmwiR+9jTT2d5bEaGdcYlA4EAa+NdiClj2E6dgCee4Hdt+vTy8uCLLoqs/MXvZ1ZYvP4iK4vtE08+Gbj8cooltm8f3z4F07ArULAWQPMKfzcre+w/tNavaa3ztNZ5jRs3NuaoSgE9ehizL6tJTeWFHC49WLwYOOYYttKpi0CApQQnnlh7zeE11wCzZgEdOnACG0vv66++si9ro7Dwv0DB/vX2r/YlNT1uCxMmOKM3cmYmt/79uRq0eDFTUEUszq3U6V8Bk3zswIHAJZeY3wlBAlm2U6OPrSVuDQBYuJDCu4J9aM10XzN0hEpL2RItsTHWxx5+ODBlCidxDRtKRp+RzJ5dfSmUwzFtDHvNNcxgKSoCZs7kYx06UL8gErKzGWgQkga7AgXTAbRVSrVUSqUDGATAmr46/foZU9+amsror8/H/eXmst4mvOXm8nGvlxdVePKclsYJWIMGrOk94ACuxHXqBHTrRnXQfv1YyzNkCPsr33cfJ+1PPQU88wywZAlbjkQSJAgTClHocOjQ2l/Xvj27Htx3H7B8efTn5eWX7XPKFVYyhvcYDl9a5ZVNX5oPw3vEEPwwi2g+PzPIzubK7J13Uujmiy/YHUQpTviaNbPXPiFW7POvAH1Uu3bmZm9FOqgRTKNaH+vJxPDf6tABKiyMLQgtGMcNN3DhwIwV7MJC14vIRYDxPjYvD+jbl4sHiV+6YR2ZmcD339ttRdSYNoZVCvjgA3Y1+fnn8scvvzwyf3DggfEdX3AdtuTha62DSqmhAL4F4AHwltZ6gSUHP/lkRrw9Hk6eU1M5kQ+nfYVXV71eBgHCW3Y2J/jhAIDPx9dUt9X0XLizQDwsW8aOBjt2RH8zCQSAjz9mIOL002t+XWpqbBoFW7cCv/0W/fuMpCxQcP4hVE0dNmkYVu1chf3r7Y/hPYb/97gjqK1kxCw8Hn7XDzmELZn69q1+QpeSArzwAr8rTtRQEGrEVv8KMBj69ddcpTDrO77vvubsV4iYan1sWm+cv6gOsa1QiN+PtWs5WBWsRymmZHfoAKxZY/z+p0/nimWCptKb5mP32UfEPo1m1y7g008pZu4iTB3D5uZSI6Bilst55wEPP1z7+7xedk0QkgqlXRC5zMvL0zNmzDBuh4EAJ0Lp6e5K8Vq+nGIfW7fGF3HOzQX+/hto0sQ42wDgxReB226zd2LZvHls2gp2cNBB/BysINzR4vzzgZtv5rEjoWtXiswkMQqYqbXOs9sOMzHcxwLATz8Bp55qfH/wjAym6F53nbH7FeLnppuYUVIX6en8/J580nSThFpYsIALD0bfs3NzgXHj2LK5DpRSCe9fgSh8rJXjgmQhJ4eLaymOlWVzBh07sjSsOrxeapqcc461NlUkGOQ8IzeXmQ3t2jEr1k3zOBuI18cm51Vj1Oq+laxYwUnbtm3xp6X5/UwtNzpyPXq0/avPGza4J23Pis4Q2dksbxkxgh0zXn898iABwKwCs+vNhcTkhBOAu+4yXtwwLY11vILzmDYtstcVF1Np3wkaLclMx45s0Wv0NVpQwKwRIXp69HDX2NQtGB0IT0SGDKl+vOf1MgPJziABQA20O+9kkPm001gem53NMe1ZZzEj4rPP2B7e6AWKJCY5AwVuY9UqBgm2bjVmch8MUofgqafi31dFnn0W6N7duhZp1eHxUIvBDZg1SA6X0PTuDYwfT4HHa6+NrFfunuTlsZbVzW1FBfsYNozaK0aKH3k8EihwKtGo3WvNFSrBXi68EBg0yNiAcGkpMwqE6DnhhNju1ULNBALsxiXUzjnnVJ1j+HzUr+rXzx6bKvL44/wsCwpY1lhUxMXJv/+mjfffD1x2GbvB5eZS9PjII4ErrmAbxm+/5Xi4tNTu/8RVSKDA6axezXKDzZuNzQAoKKBg4Zw5xu3zsMOo3Dt5MnDccfYEDNLTa28D6SSMjnhmZ1NI8+abgaVLgYkTOeiId3Xi6acja50jCHuiFDONjGxnGAxSDFZwFjt2RJclVVAAPPKI1GQ7gZdeAlq1MjYgvHIlFzeE6OjWzVltkxOBYJATSaF29t0XOPTQ8r+zsriK37u3fTaF+eefuucrpaUUU9+9m5/51q3US3nzTZZFn3MO9bkyM4H996d4/P/+x4D11KnsKueWjGQLkUCBk1m7lpkERgcJwgQC5ojVHXUU1VQnTWILRysDBqWl7ggUhELGDAY8Hp7fww5jWcGmTRx8GykSduCBwNlnS7BAiI369dkK1Ag/4PPRpxxxRPz7EoxlwYLoP+PduzkQFewlI4PXqJEtcTMyOAYQomO//SSjwEiys6nHFYtAdzIyeDAX3LKyuAJ/4ol2W0RGjuTkP1aKipiFUFDA/axeTf/05JMsZTj11PJShg4dWMowfDhLGebNS+pSBgkUOJX16znh3rjR3DSZSFomxkrXrsCvv7I1zdFHmx8wSE3lRX7sseYexwgKCuJrH+fzMSp63nmMhM6Zw/RRs/rbPvqoue3uhMSmUyem/sXjA7xe4O67gW++kT7OTmT+fKCkJLr35OcDDzxgjj1msm2b3RYYz/77A598YlwJwu7dwNixxuwr2ejWzW4L3I1SvNd06gS8/z4nheeea7dV7mDAAI7dJ09mUN4JFBQA770XX6Cgrv1XLGVYtIgZKPfdx1KGY46pWsrw/PNJU8ogI38nsmGDNUECgD2PP/mEmQVm1SB168bJ7G+/Abfcwuic0VkMGRlAixZUWndD67Rdu7hCH+3AOjubqw233MK+t/Xrm2JeFfbbD7jmGirOFhZac0whsbj8cuDHH3kDjiY6Hw4Ajh0LHH+8aeYJcbJtW2wDub//BmbNck+WiN9PgdjffwcOPthua4yld2/gxhupN2TEPfq775jKK+J80XHyyVxgSeJVzJhIS2OWZc+ewD33cFInREeDBiwhdhLvvWePDwmXMoTZurW8nCGsBRYMMsDQpAm7MHTqRJHYAw/kPS0z03q7DUYyCpzGpk2M5q1fb170bE/8fuCii3hMMznmGOCPP7gieOSRxmUYeL0U3Zs+3R1BAoCBgkjrQdPS6GxOPBH4/HP2vb7lFuuCBGHuvluyCoT4eOMNrlxG2qbK52PN5MKFEiRwOpdfHluNe2Fh3f27nYTPx6w1szLx7OahhzjANSJrJxBgbbEQHcccI/faaPB6eV0OHszV4PHjJUiQKGjNrl1O65BTXSnDDz+wlGHoUAZdjz6aHX5cjvsDBVoD118PXHop06M//JDp7itXRr9aazebNzNIsHatdUGCMH4/U46sEJY67jjgzz9ZE5mXF1/AwOdjm5TJk91V17drV92TpexsbkOH8uY3eTJwyin29QKuX58q9nZ2tRDcTWYmRTYj+Q55vZx8/vEHo/WCs9l7b+Dqq6NfQQmF+J1Yu9Ycu8zgqqvKhXsTDY+HCvG5ufHvS2tmFQjRccghCTHBMJ3sbArl3ncfsG4dMx5btLDbKsFIpk51TyezMAUFzERYvDghAsruDxQsWcJVqnfeYarRVVcB//d/FKPIzGQbrY4dOZm86Sb2hf/qK+sn4nWxZQujT2vW2GNbMAj89RejYVZx/PHMAvj6a65gRCuk5PPx8/70U/fVLO/aVf3j4dq69u1ZA7V5M0VcnHLzu/FGY9toCclHy5YM6Nb0PVKKvuC996hrICKa7uGuu2ILZIZC9HNuoU8ffkevuSYxuzY0asT7cry+PhBgFpwQHampDBYI1ZOVBbRtC7zyCjNhb7+dHZ+ExGPECONLla0iEACWLbPbirhxf6Bg4sTydhbhepKdO/nFCoWA7duZtjphAvDMM8Ctt7JFhpMUULdtYx3/qlX2ZkEUFPC8GNkyMRJOOAGYMQP48kuq90cSMPB6qUj61FPurH/ctatyG5bMTNY8DRhAnYVFi4BLLom9vqm4mJHYCROMbfeSmQk89pix6thC8tG3L3DttVUzCzIzGRSbNYuqw4K72GsvZvhF67eKi4FXX42uvaKdpKdTPHbxYuCjj+y2xhyOPJJ9y+PNIPvzT/dldzqBk082tl2l2/F4OEbad1/qai1eDJx/vgSSE5mNGykY6NaWhVlZwL332m1F3Lg/UPDpp9GJq4VVLUeOZK95u9m+nUGCFSuccTMNBIDTT7c+gqcUcNJJwOzZwLhxrEuuaTLq8wHvvsvVbbeycyeDBdnZXL255x5mk3z6KdClS/T78/uZBnvPPUDnzizD6NOHbQ1PPJFpeUZxySXM1BGEeHjsMV7n4YFeuIxo3jwKAQnu5PbbY5vgaM1+1m5h8GD+vOmmxO17P3Qoy93iEeRKT2f5kBAd3btLQB7gdy8zkzXfaWkUk3v1VbutEqzg5ZfttiA+mjfndexy3B0oCASAmTNje29REXUN7IxU7dhB0Zp//3VGkCDM5s1MqbQDpYAePZjVMGYMVaUr3ixzchhhHDDAHvuMokMHdrb48EN2ubjrLgYMImXnTmYL3HILS2vq1wfOOIM6HbNmcYVu1y5mifz2G9VY33/fmO97aipVsWUQI8SDx8OgYE4OB4IjRgCjR8v3yu3Ur8/MvWjT1v1++i+3tJo68kj23d68mdmKiYhSvG/su2/smXsFBcz8FKKja9fk7nqQlUWdjFtvBT7+mJmW+fkcK0+a5P5JpFA7wSDLb90ahM3OZoa2GzOe98DdgYIpU5iKFAuhECdUn31mrE2RsmsXRf2WLXOeaE1hIQfsdvZAVoqpd3Pnsp1ax44Uy/rjDypOu52uXfm/9O0b2erb5s08D1dfDbRpAzRuzL7ATz/N0pqSEn6nqhtkB4O8wV55JXDqqdxXvPTvz1pzQYiHvfemTsmMGSxFSICbqgAGMGPJKti9mxpCbkAp6mgAwB13sIQwEcnKYqeiWPUKSksZ9Beio3795BRxzc7mSuzIkUw979KFY52Kqvd+PwMIf/1ln52CuYwf76wF1Gjx+RKmfNLdgYKxYyv3uIwWv59iePHsIxZ272aQYMkS5wUJwvj9TK20W6hJKaY+zpvHlfcOHey1xyrWrGG2wcUX86bZrBkzYF55hcGlcGAgmgwBv5+R+LZt4xeYUorCoNIBQYiXVq0YCBQSh5wcZklFO7nMzwceeMAcm8zghBO42gkAvXrZaoqptGsHvPVW7P5++XKWWQrRkSwtYVNS+N3q0oX6AytWAEOGsBRz0KDqMysCAZaqWT1+t5NQiBmi8+ezBMOttfuR8Nhj7v1sfT7e/xKkxam7AwVffhn/heL3czXAKvLzWbOyeLHzU2oKC53T/kmpxF1t1Jp6GW+9BQwcyFXWtm0ZxHr3XQYNwqUE8VJSwrKFiy4CzjwzvsHb8cdTDyFRPxdBEGLnttvY3jLayeXixcwwcQvnnAOMGkUB2kTmnHN434glsyAjwzljCTfRowdX2BOV9HSWnfXvz7bm06Yx6zElhdmSV11Ve/nFli1cTEnkCXOYYJDX4CmnUNesaVOev0aNgIMOAnr2pL99+GGOJSdOZAnvpk32L/hFQ1ERP/u5c+22JHZSUoArrrDbCsNQ2gUXWF5enp6x58Bh+XLWrxtRw+X1Ar//TsV9Myko4ORq/nznBwnC9O3LgIxgHKEQywWmTKEz//VXTuCVqpxeZzbp6eVt6E47LbZ9/PUX23omcC2lAmZqrfPstsNMqvWxgmAE77xDzZtIfYRSFNS1s/RNqJ6SEq76zp8fvZbERRcxoLIHSqmE969AjD52yRKgUyf3toerCZ+P1/ngwSxTatas8vPvvMNStEj+b5+PE8shQ0wx1REUFzOYMmVK3eckJYXBl/BqdnExr9ucHJasNmkCHHAAS0ebNuXfTZoA++3HRSq7VsFLS7kwdvvt/B+tHAsbSUYGhdYfe8xuS/4jXh/r3rwII8VxAgHgwgsZfYulB3Qk+P1Un3dTkAAAfviBE1uzzksyEAzyuzVlCntTT5vGm2Rpqb0T7OJibmeeybKOBg2i38dhh1GNePx4/p+CIAgVueQSrnj16cNU0rr8hNYUrF29mmVXgnNIS+M9rGNHZqZFQ7iVtWSgRU6bNonVIjE7mxP7O+5gkKCmbIlPPok8OOL3s/PI0UcDhxxinK1OIRCg75w2LbLxYihU/bnbsYPbkiX8WykGFMJdh0pKODfJzmab2yZN6H9btWIgJxxQaNKE4qax6sPtidbU37rpJuq8uDVAEEYp/i8JhHsDBZ9+auwka+lStma6/HLj9hkmEGAK2bx57goSAAwQLF0q7cqioaiIAm0//cRB1Zw5dMbFxc78/NPTWe8WS6AAAJ56ioNACRQIglAdRx3FIHmvXswG9HhYhldTRmMoRDGzp5+21k6hbpo2pcZN377RjcHy86mv06aNebYlGkoBeXnAjz/abUl8ZGUBLVoA993H7kx1rVpHm3bu9zMrcuHCxCrVyM/n3GHu3OjawEeC1rx+97yGd+3i9u+/5Y9lZnKcqBQDCoWFzMTeay9gn33KAwrNm1fOUGjSpOZSJa25EHn99QwKuz1AAPC+NmAAz0kC4c5AQWEh8Oefxu0vO5sT4mja00VKYSFrh+bMMf5CtwKlGMmUQEHNFBSwdGXyZE6YFy6kYw0EylVbnfzZezyMNMdKy5bMyBk1yrninIIg2Mt++7FUaflyahD8/jvLrhYupA9KSSkXryouBl5/HXjoocQa+CcKPXowRXjEiOjS4r/7TgIF0dKrFwXs3HZvTU3l1r07AwTdukX+3g0boj/e5s3AZZdxETER2LGDpcpO0DMrLKw6hi0o4LZqFRfGAGYZpKfTlweDfE9aGtCwISfPzZqVBxQ++YS+PxECBGHS0oC777bbCsNxZ6Dg11/5hYzn4lGKKVAtWjANauBA41JpwhQWUnhk1ixnTxRrIz+fKfMXXGC3Jc5hxw5+BydNYtuoZcsYNS0oKK/bdNtNPdo00j15+GH22xYEQaiJlBROFNu0oZo5wOyBZcuAmTOBqVPpWxctoj+dMiV2/RTBXO65h59PpJPYQIApxtdcY75ticQxx3DhwS1jisxMjq/PP59j69ato99HWlr04/vCQmZwvvUWAwZuZvNmfu4rV7rncwf4me35uZWWAuvWcZs9m4+lpbm79WFNdOvGDjEJhjsDBePGcQIbC5mZ/Nm3L1WZ80zS0CkqYl3RjBnuDRKE+eUXuy2wl40beQ6+/57bmjUMDOTnl6vJutnpaR1fRgFAEZybbmKqcAILGwqCYDApKezy0rZt5eDB8uWxTTIEa0hJYQnCQQfxHhkJv/3GlcYEaRtmCXl57rinZmfzc735ZgoRNmwY+76aNWPwMFr8fuC664CuXd3bSnvdOk44161z97iyNhLx/8rKcldr3yhwp7ceOzb6dh/Z2cwYuOEGtlxp3NgU0wAwAnjaaSyPcIODr4vlyxn4MDrjwqmsWgX8/DMFtSZPZguejIzKPV0TydGVlsYfKAC4evDCC4nxnRcEwT7CmQeCs2nQAJgwATj22Mj8floaSxmjSUNPdjIzeS04tf1mdjbH0/feC5x3HlPP4+Wkk4AVK6LvrAGU6xUsWBB9a1a7WbmSooybNsX2vwv20aIFs0ASEPdJ2a9cyYlbJHg8XPnNy2PbjQ0bmC5nZpCgpITZClOnJs6EyetlbWkiEwoBV17J70a7dsDVVzOVft06Bn4qBgkSjeJiYwIFOTnA/fczsioIgiAkPkccwUyySCZlgYCxHauShR49nNctwuvlxGjMGK7+X3KJMUECgOOIeCb5GzYwq8FN/PMP5yobN0qQwG1kZzObwGnXqEG4L1AwcWLdrfp8PjqxCy+kyMb06ZEprcZLSQnQrx/T1BMlSABwIvnHH3ZbYS4vvsjAwJYtLBWJtbTFjZSUANu3G7Ova65xXxRfEARBiJ0hQ7hAEi7trIlgkBNLITpOOIGBeKfg9VKj6ddfKdZt9ARpv/2AN9+MbSwRVufv2NFYm8xk/nx2htm6NfpsacF+cnKA/v3ttsI03Bco+OyzmlV2s7PZjuOhh7gS/Pbb1jmLYJDBiJ9+SqwgAcCJs9vb89TGypVMm49GvTnR2LTJmP1kZLBdomQVCIIgJAdKUUSuadO6J41LlsQvnptsdOtmv/J9GJ8PePxxpsibycCBDD5FWvKalsZA1eWXs1z21lvNtc8oZsxgZsaOHTW3ixWcS1YWMGwYM9gTFHcFCoqLKYZTkbBzOP54YPRoCs3dfDNQv751dgWD7J3544+JFyQIY2Q7SiehNTNPnHITtotIy3ki4fzzE66PrCAIglALPh+7ANW1CpyZmdgLD2bQpAmQm2u3FVytP/ZYYOhQa4732mt1j+XDc4CLLgKWLgVeegnYd19LzIubX39ltsiuXXZbIsSKUsCll9ptham4K1Dw2290CgCjOFlZTHmbN48r+b17112WYDSlpcA551ANP5FXpLduNS493UmMGsX2lcleE7Z1q3H7SkkBnntOsgoEQRCSiTZtgPfeY2p6TezaBYwfb51NiYITBCBzc4GPPrKuFjs3l9+V5s2ZMVwRj4cBgkGDgMWLgTfeYEaLW/j+e6BXL7aBFdxJRgZw/fUJX27rrkDBxIkUlWvRAnjySYp+vPCCferIpaXAuecyip7IQQKATnnGDLutMJZQiK10xFEbI2ZYkVNPBQ480Nh9CoIgCM7mjDOAwYNrHzxPmGCdPYnCySfXHoAxG6+X+hLxtD2MhS5dWB76xRfAccfRjsxMliYsXEih8v33t9amePnyS+qZJfq8IdFRCrjxRrutMB1TAgVKqSeUUn8rpeYqpcYopeqXPd5CKRVQSs0p216Jase33MLMgeXL2eLQzhXLUAi44ALg668T+2JPS2PUrEcPoHNnu60xluLixC0ViRaja0aVokBkgkda7cI0HysIghAvTz0FHHRQzQLSO3cC//5rrU1R4jgfe+yx5gty14TPx5r/Y4+15/hKMVDy88/A3LkMEHz0EdCypT32xMNHHzELQsae7iY1lZ+jmV30HIJZGQXfAzhYa30ogH8A3FnhuWVa605l21VR7XWffahFYHcLilAIuPhiRgUTNUjg9XIbPJhpXePHWx9JNptg0P7vklMwo8vD0UczXdLqcqDkwBwfKwiCEC+pqcBXX9Ws1K8U8N131toUPc7ysQcfzA5FVpOaSlHw++6z/tjV0aaNOwMEAMsjLr9cggSJQGoqcNdddlthCaaM4LXW32mtg2V//gGgmRnHsQWteaF/8UViBgmys4G99uJNYf16rgofcIDdVplDaalMYsOYVX7x7LORqxYLEWOaj129WgYxgiDEz777AmPHVp8u7/c7vk2i48axHg9wyCHWH9fn42eVwKrulvDMM6xnl/trYtC9O9C2rd1WWIIVs6TLAEys8HdLpdRspdQUpdRxFhzfOLQGrrgC+PTTxAsSZGXxS//KKwwQ3H47UK+e3VaZi2QUlFNUZE7/3g4dWItnV8pkcmCMj/3uO67U5OTQHxxwAHs7n302cOedVJMeNw6YPh1Yu5bXjyAIQk107w7cc0/1JWi//OImEWFnjGNPOcXaCbvPB7z/vrtEAp3Iww+zhZ4ECRIDnw+4/367rbCMmEfvSqkfAFTXg2SY1npc2WuGAQgC+KDsufUA9tdab1VKdQYwVinVUWtdpTeIUmoIgCEAsL8ThEq0pi7Cxx8nTpDA42G7m6OOYgaBE8o6rEQCBeWkpVGN2oy2oiNGcIIpE8uosNzHKsWMop076eNWreI2bRrfkJlJfwEwBbaoiEGFvfcG9tuPIrOtW3NQ2bQp0K4dHxMEIXm54w5gyhTqS1VsQ+zxADNn2mYW4MJxbPfuwPPPW9NOz+tly8G+fc0/VqKiNb//L7yQOPMGgeUvRx9ttxWWEXOgQGvds7bnlVKXAPg/AD201rrsPUUAisp+n6mUWgbgQABV5PS11q8BeA0A8vLy9H9PTJ0KFBYyohOuo99zMzqdXGv2jX3//cS42DMz+XPgQNbYtG9vrz12EQxK6UGYtDR2PjAjUNC8Oct1Xn+98kBRqBXLfWzjxvR1NVFYyK0iO3dyW7KEk4GUlPJU49xcYN26iP5XQRASFKWATz5hdllFf1BYyE5WNmLbODZWjjrKmlVppXjffuYZ84+VqITnDe+8kxjzBoFkZwMPPmi3FZZiSj6wUqo3gNsAHK+19ld4vDGAbVrrUqVUKwBtASyPeMdLlgAnnFCexqY106VDIaawlZZy8hdeKU9PZ310RgYnx5mZHMQefXTkDlBr4IYbEuNiz8riQP766/k/JYFaZ624J+3RfDwe4zsfVOT++4G33jJv/0mGKT62ceP4sz5CIepdpKcDAwbEty9BEBKDevUYFDj66PJxVEkJtZ4cimnj2HioV4/ZWytXmnscr5cC1qIvFBulpcCllwKff+7+eYNQmdzcpMuyMatw+AUAGQC+V0zt/qNMGbY7gAeVUiUAQgCu0lpvi3ivHg9rneua0JSWMupaXeTV44l81VRrtoR58013X+zZ2fyf776bqWR29uJ1ElJ6UI5SzCgwi732ou7FY49JnZ4xGO9jGzWqmjEQKykpTLkUBEEAgEMPZQr20KHl46lFi+y1qXbMGcfGy/HHA+++W/53Skr5gpgR93Cfj3o0Bx4Y/76SkWAQOOcc4Jtv3D1vEKqSlUXNlSTLRDYlUKC1blPD458D+DzmHbdsyQlvPBONevWADz6o+3VaA7fdRnE/N17s4ZtHx45cze3TJ+m+3HUigYJytDY3UAAAt9wCPP20BAoMwBQfm5HBEpR4y0M8HuCss7jy5WaKimRFTRCM5NJLgR9/BD77jPcBr9eeln8RYNo4Nl569ABGjy7v2nTaaVwE+vZbCubFkymZmcmx4sUXG2dvMlFURPHmX35x57xBqB2PB7jkErutsBx3zRyVAs49N3bVV6+XN6hGjep+7bBhjKq67WJPT6ez79cP+PVXKpSfdpoECapDAgXlhELmBwqysoDhw/lTcCZGdDpJSwPuvTf+/ViB1qybnjSJrWAHDwa6dAEaNmSK4ZYtdlsoCInFa68B++/PMcnu3XZb4z5OPBFo0oSZGUuXckzbqRP9brzjvIYNgbffNsTMpMPvB04+Gfj5Z/fNG4S6ycwEbryxXOMtiXBfz7Kzz+aNJj8/uvf5fMDVV9PJ1sW997L/u5su9rBuw+DBLJdoZm/LX1dQWiqBgjAlJeZqFIQZPJjBgoIC848lRE+DBsCmTbG/XynqyDgtbbWkBFi2jKnOixZRbX3+fNb6pqQwwFpUVF56kZ7OoHQkQWVBECInM5N6BYcdJoGCWGjenL5sT9LT4wsUhHUJcnJi30eMFJcWo99H/QAAo88ejYGfDgQAjDt3HNI96ZbbEzW7dwMnncR7ilHle4KzUIr6bkmI+wIFXbowchoNKSlAq1bAo4/W/doHHgCeeso9QYLsbDr4228Hhgyxxcm7FmnXV05REbB9u/nHSUsDRo5kFwQJFjiPxo2BxYtjf7/Xa68i8M6dtH/RIg7aZs7k35s2cYKSkkLfvue1X7EcJjWVJVuvvWat7YKQLLRsCXz4IRd+pBTNGOLJKPD5OPY94ghjbYqQfh/1w5SVUwAAzUY2Q3Fp8X+PT7zA3s4YdbJ9O9tWLlkiXZ0SldRU4PzzqbWVhLgvUJCSAnz6KXDhhewlG8mE3utlH/e6AgzDh7PnuxuCBFlZTN+77z7WA6e676O0HQkUVGbzZmuOM3Ags3b++cea4wmRM2QIV6vCZSjRDuIPOYTBXDPRGli7Fvj7b26zZwNz5tBuv5/+PhSqmnUWaRZa/fpc8Ux3wUqWILiV//s/ps8/8YTdliQGsWYUpKWx7eIttxhvU5QEggEEgrzneFNdILq9aRNwzDHAqlVAcbHd1ghmkZoK3Hmn3VbYhjtnlz17AitWcOV/+HCmldYkiBNWcG3VqvZ9PvYY8Mgjzg4SpKZyO/ZYBgiOOUZS5+NBSg8qE0+g4J9/gOefB377jW3xzjoLaNeu+tempFD9un9/Z19vyciFF3JbvpyqzaNHA3/8wUFofj4n4DWRlQU8/LBxthQXswb377+ZITBjBrBgAQdl1ZULhIlHHM3noyjYPvvEZ7sgCHXz6KMSKDCKtLTYxjM5OVx8s3EsNPrs0Wg2stl/QQIASPek47OzP7PNpjpZuxbo1o0aN7LolLgoxbKSuuaQCYw7AwUA1ajvuosqujfeyNqqPVe/MjKA3r3ZErA2nnwSeOgh505awuIZ553HlmNt29prT6Igzr0yW7dG/54FC4DLLgPmzeP5LCkBFi7khLFhQ9Z533BDVc2Mk0/m6vOffxpju2AsrVoB11zDrbiYAaCvvgLGjOHAKC2t6gp9s2ZU5I6WHTvKswP2LBfw+XijLiioquZtdMqyz8dyA5vSb6NmwQJ+BunptW9GiJwJghnEKkwtVCU9PfrJfjQC3yYy8NOB/5UbhCkuLcaATwc4s/Tg338ZJNi8Ob4uE4Lz8XrZOS6JcW+gIEyTJsAnnwDTpnHCsnIlbz7BIIW56lJwfeYZpkE7sU4uK4sZBDfdxBS9JK2PMQ0JFFQmWo0CrYFBgzi5q0i4Tm/tWuoRKMWSnj154QXW9jnx2hPKSU+nCOyJJzKLa9064LvvOMD88cdyf/vQQzUPVLUG1qxhZsDff7NUIFwuEG6TVlpaVbfCKrEzn49lF+efb83x4iUUYj/1/HwGkrXmFgqV/ywtLf+ZksLPKZyVlprKAEJqankwIS2Nv2dklP8Mb5mZ/On18vfwVleQItotNVWyvAQhFqINFPh8wHXXRSbwbRHeVC/SPelVggaOYvFiZvNu3157hp2QGLRrZ345pcNxf6AgzJFHAnPncuCalgbsuy8Fc2rTJXjhBWYlOG2ikp3NCO8993DgKr28zUECBZWJtuvBF18wsl4bPh9w8MHVP5eXx5Sub76RqLyb2G8/9hK+5BJ+bjNmcPJ/5pkMEi1dyoDAwoXArFkMJK1eXT45LSysKvpkZy/19HQOBJ580j4boiUlBXj3XZb5RHLdhkLcjDzPSjH4kJJSeVOqfNuTcECjYmAjvIUDG+GARvhnOKBRMZhRU1AjHNAIBzLCgY3w6+raWrUCWrc27hwJglVEI/Lt8XACZGSpWByMO3dcjV0PHMXcuQzQ7txJ/yUkNtnZ9oozO4TECRQAHKREmvr68svsFOCUIEFKCgczhx3GNJdTTpGVFbORyWllolm9LSlhq5i6OhcoxR7PNTFyJDB5snOuQyEytm8vLxeYO5cBgTvuYCpmTeUCThR7UgrYe29g7Fj3pUGfeiqDG//7nz1lc1qbE2wtLTXeN1cMang8/Dsc1CgsLA+g3Hwzs2YEwW1Ek1Hg89HnOUQEO92TXqnEwJHlBtOnc34hLT2ThwYNeJ9NcpzhJazmtdeo8OqEyUlYqbZvX+Duu4FDD7XbouQhGJSocEWiaVf42muRrWQGAkD79jU/f+CBbJH14Yf2rioLkfHxx9QtCJeppKZWnSy6aSCVlQX88AM7HbiRa65hKuwbbzhXY8cJVBfUSElhxsFee7Fs8ZJLRP9HcC+RZhT4fMCoUeyaJUTGzz9zwigtnZOHrCxmdYu+TxIGCt58k+KHdgcJwqtuV13FVYz99rPXnmRESg8qEwhwQB3JqsRjj0V202zevO42c488QtVlCRQ4n+OOY3eLRYuAv/7iJHX1an5vMjK4Euz3uyMA5/Uy8FFTdw638PTTLPeYPLlqBwihKjk5/DloEHD55SxblOw9we1E0s7V6+X3/owzzLcnUfj2W5bVSSA2uUhNrVsIP0lIrkDBqFEUb7EzSJCdzUjVXXdxFSM72z5bkh0JFFQmJYWT/0i+k5deyhTdum6enTvXva/99uPK6IsvykTH6TRtWlXwT2tgyxZgyRJu4SDCP/9Q0FIpDmKDQecMtnw+9kU+7TS7LYmflBQKSx51FM+9+LWqZGfzvPTuTdHKnj2jq+kWBKdTV6BAKd5rX3zRGnsSgbFj2W3M7oVFwVq8Xmadiz4cgGQKFLz/PnD11fZc8Erxi9e6NfUH+vVzXz1sIlJa6o6VT6tIT2erukgCBcOGMfC2alXNr8nIYAuhSLj7buDVVyN7reAslAIaN+a25+etNbBhQ9UgwpIl7J4QVt0vKbEuiJCZyfacw4ZZczwr8HpZQnHYYcDGjeLXAJ6TUIiiqVddBfTvL4F5IXFJS6v9uvd62UY83G5bqJ0PPgAGD5YgQbIydKjdFjiG5AgUfPQRVxGsvuDT0hgQOPFEtmDs2tXa4wu1IxoFlfF4qDvQrFndr83IYPCtV6+ar6uMDODwwyM7dv36nLg99JC1q85hJfWKbdlKSzlxLS7mc04U4XMLSrGFbZMmbIVZkVCIwYJwEGHhwvIgwsaN5e3yiouNyzTxeFib++GHiZduvvfewE8/sYODm3QijCSs+dOyJXDllcC55/K8CEKik55e83jG52Mr8IMOstQk1/L++/bMGQT7SUtjyUGDBnZb4hgSP1DwySesQ7Tygvd6+fPCC9lZoVUr644tRI4ECiqTksKMgkg57jjW7n32WdV2dwAnd4cdFvn+bryRKu7RBArqmuinp3OQlJMD5ObS+TdsWL4CvtdeDFJUt+Xmct+JNqF0CikpDEo1a1a1l3dpKbUPwkGEBQvYXWHZMnZWyMjgZ15dq8XayM4Gvv+e34lEpF07rhr26ZM8g1yPh6ukOTnAFVdwkCeihEKyUVNGQUYGS22uuMJ6m9zKM88kj/8UKuPxsIOT8B+JHSj4/HPWUlt1wWdn01nfeivLHCQi5WwkUFCVaAIFAPDcc8BXX1U/WcvJie4ayMwERozgtaNU3RP9vffm73VN9AX34fEALVpwO/nkys8Fg8DKldRAWLIEmD8fmDcPWL4c2LqVgdqUFAYRKmaDhFNvE13t+/jjWcZz5ZWJPdgNixKeey4XA7p0kaCekLykpzNLa08aNADefVeujWioraRSSFyU4nijRQu7LXEUiRsoGDuWK/pWDJSysoB99gHuu4+KspGozwr2Y3SvbrdTWhpZy8OKNGwIvPACa4D37IJw8MHR23DZZXTUPp9M9IXqSU2l3kvr1lw5r0hxMfDvvwwg/PMPAwjz53Pg99BDzIJJBi68kP//yJHOEZA0grAoYZ8+5aKEDukFLwi2Ul1GgdcLjBsH1Ktnj01upKQE2LbNbisEO/B6qSMnVCIx77Djx5uvVOrxMCCQl8cAwUknScTWbQSD1Ufgk5VgMPqMAoAq+G++yV7DSnELhWJXlG/ePLb3CUJ6OtPv3d7y0AgefJABky+/dHdmgc/HIGaXLsw26tePwXlBEMrZM6Mg3F3ryCPts8mNrFrF7MZI2j8LiUVpaWwLXAlO4gUKtAbOOsu8nuwZGZwInXkmnXDHjuYcRzAfKT2oTHExsH179O9Tij3ci4p4PsNbotaBC4IbUIopx927A7Nnu0uUs6Io4dVXA+ecE5koodb0RbNn8++LL2aZkiAkOhUDBWlpFBJO1lrrQICZRrFkJC5fLllKyUpGBu8fvXvbbYmjSLyrQSngkkuoWmrkKkpWFvc9dChF1/bZx7h9C/YggYLKhEKs8Y4FpaTtkiA4jfR04JtvgE6dKA7p5AyqlBSmfubmlosStmkT+ftnzGBQYdEiBi2Vopjx1KlSwiQkPmlp5dd3VhZFhlNS7LXJCIqLOS7ZsqXytnkzsHYtsH49u+Rs3cqMyF27uDJ85JHA779Hf7zly90VVBWMY9cuzh0lUFCJxAsUAMCzz1LZesWK+PeVnc2By7BhDEDIKmniUFrq7IGzHWzebLcFgiAYSf36bJt4+OGxlRaZTU4OJ/VhUcK8vOjL+DZsAI49tqqo6oIFwPXXAy+/bJy9guBE0tI4pvF6GSBz+2LWlClA//6cvGVklHcgCoWYMRzOYKyJOXOoV9OyZXTH/ftvd5dqCfHx5ZdcRJSskv9IgHBjNXi9FDMMtymMFqUYEDj8cOCDD7gSc801EiRwAhs38jMxQohQMgqqsmWL3RYIgmA0LVoA333nnHtYdjYzkM48Exg9mquBr7wSe+eCTZs4mdiTQIDlF++/H7/NguBkPB5eO1ddBZxyit3WxMfXXwOnnsrAZijE63jXLoot797NjjZ1jd20Bt55J/pjL1gQi8VCIvHLL3Zb4CgSM1AAsH/7/fdHNzBKS+Pg5f/+j9HMWbOA009PjPQtt7NzJ3DbbYwOX3EFBfTizQYQMcOqxKJRIAiC8+nShRPmWAPo8eL1cjLfvTvw2msMSn7+OdCrV/yrN7t21Rxg8PvZKnLOnPiOIQhOZ/Zs4PHH7bYiPj75BBg4MP5uLUVFwBtvRL8YtGxZfMcV3E1BARcjAWbYShlKAgcKAODWWxkwqGsQ4vVyGzKEaUdffsn0R8F+/H7gkUeAZs2A559nZLmkhDeT1avj23dJiWQU7IkTU5MFQTCGM85gNwSrMgvS03lv7dABGDGCPnvKFJYZGNm5YNeu2p/3+1l3Km3PhESktJRZOV4v28FaMa7ZsMH4UsU33gAuvdS41P+dO4Hp0yN/vdbAunXGHFtwJ6EQA9j9+1NAd8QIuy2yncQuwkhJoaBL+/ZMV9qT7GyucNx2G1ccpNescygp4U1j2DBGhv1+ZntkZgIDBgB33gkccEB8xwgGjbE1kajuOhEEIXG45RZg8WLgww/jX7WrjrAoYb165aKErVsbf5yK7N5dd3bYtm3AoEEswRAo2rZ8OdCjh7R2dgpa85rcupXbtm3lv2/Zwsn5+vWcoG/ZUi7eFwgwKJeWxrHT6NFA377m2VlUxEW4ggJg+HDg2mvjzwp6+mmO94zUBwgEgNdfj7xF5LZtsngkMPA2bhzvY8ccY7c1tpPYgQIA2G8/4O23OVgJD4qysoCmTYH77mOKkygiO4dQCPj4Y2aD7NrFG1FWFgUlb7gBuO4649pdSUpRVfLz7bZAEAQzUYp6AMuWsSPAngKAsRIWJTzvPIoSdu5s3QQ0rHReF9XpGCQjs2YBJ5zAe+AJJwCjRrlf/M7p7NjBsejWrdRaCqv1b9nCCequXeX334yMcs2BSMX7ioq4eTzAX3+ZGyh49VWOzQoKOLl//nl+h2KZVGnNLKcRI4wXEQyFmH360kuRjfOXL+e5N8onCu6koIA/PR6WyiU5iR8oAICzzgK++IIT0OOPZ4Cge3eJojsJrYGJE6lQvX49gzrZ2RThuuceDj6Nbr9XUmLs/hIBM1YYBUFwFh4PS+w6d2bAIFZx2OxsvvfUU1m6d9JJ9qhF795dtz/PzGSWWrIzdy5w4onl2WOTJwNt2wIvvghccIGMi8zi33+50FFUVHc2YzzZjqWlwMyZsb+/Lvx+4N57yydTBQX0ISefzODE888zZTsStAZuvpmaJWaOPb75JrLAyfLlklEglGenDRzIe2WSk9gaBRUZNYr1kZMnM1ggN0Pn8OuvwBFHsCYo7KiPOYbBneXLgcsuMz5IAEhGQXVoTUVhQRASm+xs4McfgQYNonufz1cuSvj661wR/ewzKq3b1VJq587aAwVZWVxVTPZV8wULgOOOq6zpUFLCoMHVVwM9e0qNtlmEQpxUW1HyOH++eft+5pnqr7VAABgzBmjVii3K6/o/QyFmHpkdJNi9mxlUkbBsmSyWCMTn45xEMC9QoJS6Xym1Vik1p2w7tcJzdyqlliqlFiulepllQyVSU1mGIDiHv/5i0Oa446hInZLCzIHp0xk8OPlkcwM6olFQlfR0DroFR+M4/yq4k/32Y/C8LmHB9HQGazt2rCxKOGiQM1outmxJG3Nyqj6Xmgp07cpOOcnODTfULPxYUAD8/DPQrh1T5JN8ZdXVPnbVKnM6Ou3cCTz6aM2T6ZKS8nKEgw5iaVN1BIPAOeewLMCKifmkSZEJNS9YYEzrbcH9FBdLm8QyzM4oeFpr3alsmwAASqkOAAYB6AigN4CXlFKS25FMLF0K9OsHdOrEgUlODm8sq1axfVfHjtbYIaUHVUlNlc4H7kH8qxA/hxxClec92yZ6POV6PnfeyUH0/PkULjNKJ8YoLrmEAo0vv8wMtJYtWZOcm8tAxnvvSRYhwEB8dnbNzweDrJO/7jpqF6xZY5lpDsWdPjY1FVi71vj9PvZYZAssBQUc5/XsyQ4nmzaVP1dUxBbkEyZYt3qfmkqBx5oIBoG33mI5liAA/E58+GHSB0wBe0oP+gH4WGtdpLX+F8BSABFKkgquZt064OKLuWLx5ZfA/vsz7WzTJuDhhyOvazMKCRRUJSVFAgXuRvyrED29elF13Otl4LZePWoOTJnC7IH772dKsZNp0YJZA2++yZK1LVuAsWPZ8rhJE7utcwbnnRdZwKSggKvB7duzvEQGyxVxvo9NSwMWLTJ2n1u2AM89F11pYiDAEtJWrfje3bvZZePnn61N8S8oYBBxT7Rm2VTLltTHEjFnoSI7djBAnuSYHSgYqpSaq5R6SykVLoRsCmB1hdesKXtMSFS2bQNuvJHtDN99FzjqKIrLrFgBDB5sjv5AJIhGQfVIoMAtiH8VjOPKK4F33mF2wZYtrOm3snOB0eTmUrRPggTlZGYyIySS7g/BICdYN91EUa/kxJ0+trAQWLjQ2H0+8EBsafnFxfwe3XUXM5FmzjS+u0EkLFoErFzJ37Vmm9SDDmI20po15eKMghAmGGR5TJITV6BAKfWDUmp+NVs/AC8DaA2gE4D1AJ6Kct9DlFIzlFIzNm/eHI+Zgl3k5/Pm0rw58MILwIABVFyeOpUrWHYPQKUWrSqhkGgUOAQz/WvZ/sXHCpU5+2xqw9glSiiYz/XXR/f64uKEVf621Mcaa3rtFBUBs2cbt7+1a5mpE0/bwIICvt8usWStuVD1++9Aly7AmWeyXEkCBEJNFBezHDrJiWs0oLXuGcnrlFKvA/iq7M+1AJpXeLpZ2WN77vs1AK8BQF5enuS9uYniYqZ5hSPQN9zAzWmK03YHKpxIaalkFDgEM/1r2f7FxwpCstGkCdtZjh0bWUlBWhrLUhIQS32sUtb62L/+Mm5fw4a5X/y5qAh48EHqLEhnAyFSNm4ElixhC9kkxcyuBxXz/c4AEO7X8iWAQUqpDKVUSwBtAUwzyw7BYn75hRfU889THXfDBuCRR5wXJADYDsoJit1OorhYAgUuQPyrycybx9WnJ57gCuwZZ7Bkqls3puULgpu5666q4pXV4fMB//tfUnaMcr2PXb7cuP188kliaDoFgxIkEKIjFAI+/dRuK2zFzPzCEUqpTgA0gBUArgQArfUCpdSnABYCCAK4VmstOeCJQtOm7FnbqxeF8ZxMjx7AkUcyuCFlCCQYpKaE4HTEv5rF99+zf7JSXIXacyVt+3agUSNbTBMEQ8jLA9q0YSlgbWRlAbffbo1NzsPdPraoiPfyhg3j289ttyVGkEAQYqGoiIsGw4bZbYltmBYo0FpfWMtzwwEMN+vYgo20auV8deyKvPEGcOihEmWuSMVWRoIjEf9qEvn57O9dnT/w+YCvv07qFEQhgRg2DLj88pqV3rOyqFQfSeZBAuJ6H5uZSQG/Y46JfR8LFrCNoSykCMnMqlXc9t/fbktsweFLvoJgMq1bA+PHM7VSyhCIpFYLycrUqdUPin0+DphPOMFykwTBFM48s/buB23aMGgmuJNgMP4WibfcEp+AoSAkCp99ZrcFtiGBAkE46STW4f3vf1w9SVCF54iR0gMhWcnNrSpyGg4SHH+8PTYJghmkpnIiGA4WpKXx+5+by8def10Ef92M3193aUltzJgB/Pwza7QFIZkpLARGjbLbCtuQHkiCAHBgdP/9wMUXA1dcAfzxR/KWI4iYoZCsNGxYOaPA5wMmTgS6d7fPJkEwi6uuAqZP5/e+fXuWDbZsyZ/16tltnRAvs2bF/t4bbwQCAcNMEQRXs3gxxdn33dduSyxHAgWCvRQVAaedBqxZwy4JZ5xhrz0tWwKTJgHjxgGDB7N+M9lulrt22W2BINjDXnuVC3f5fMA33wDHHWevTYJgFg0aAF98YbcVgln8809s7/v5Z2D2bGNtEQQ34/HQV15zjd2WWI6UHiQKWkfWE9lJlJYCffuyLnjxYtZDLl1qt1WkXz9gxQrg2mtZjuD0Dg5GUpO4lSAkOvXrM3jp9UqQQBAEd7N9e/QLHVqzJWyyZlQKQnX4/cA779hthS0k0ewnwZk4kSrFbduytdeDD1J8Y9481tc4ka1b2YosfCPzeoHGje21qSI+H/uoz57NNopZWXZbZC6pqVRKllpsIVnxeJhy+913EiQQBMHdeL3RZxV8+61zFmwEwUn89RfnLUmGlB4kCj17UpjokUfo5L/6ihNbrRkJ22svBhE6dWI7wPbtuTVubJ9g0d57A716Ab/+yuyCESOcWRfZrh2zHj75hGlHgYBzgy+xEA6AXHwxcMMNwIEH2muPINjJ00/bbYEgCIIxLFoEHHZYZK/VmmOAggJzbRIEN5KWBowdy7aySYQEChKF9HTgoYeAs89mCv/KlZVrzTdt4vbbb1wpT0vjZDclBWjRAjj4YOCII8oDCK1b8zVmM2YM8PnnTPO/4grzjxcrSgGDBgGnngrceSfw9ts8f24r9wijFFcbmjYFbr8dOPdcaQ8pCIIgCIlCfj4wf37kr//8c2DtWvPsEQQ3U1DA7gdJFihQ2gUTnby8PD1jxgy7zXAPwSDw+OPA8OHRTWZTUzlZDIX4vr335uryEUcwkNC+PVfXGzY01343MHcucOGFwLJl7oq+e738fE8/Hbj1VqBLF2mBVQdKqZla6zy77TAT8bGCINhBMvhXAMhTStviYXv3ZmlqXZSWUsx59WrzbRIEt5KezkVXJ2Y/10C8PlYyChKR1FRg2DDgrLOYXRDpZDYYrJyFsG4dt59+Ynp6airT7tPT2T7pkENYynDQQQwitGjBGt9k4NBDqV3w9tvAzTdTAK2oyG6raiY7m5/hTTcxc2Ovvey2SBAEQRAEM1m0KLLXvfcesG2bubYIgttJT2dp9/nn222JZUhGQaJTWgo88wxw773MEgiFjN1/ejoF8EpLOVFu0oRBg86dgY4dmYHQrh2Qm2vscZ3Etm2cgI8e7axWiunpLC3p2pXlBaecklzdGwwiGVa8xMcKgmAHyeBfARszClJTOfarbRGnuBho1gzYvNk6uwTBrZx8MgWPXYJkFAi14/FQ5LB/f9ahL1xobKp8cTG3MKtXc/vhB65gp6RQTDE7m7oHhx7KLISwFkKzZu6fvDZsyLqla69lOcLatfaWI2RnA0qhePBl6Nd+DuDNxOiTjsXAD08DAIw7dxzSPen22ScIgiAIgvlkZAD//gu0aVPza15/XdohCkKk/Pwzx/iJ3gmtDAkUJAutWwN//AG8/DJw221c/S8tNe94WlNIJ8yOHcDMmdwyMpiFUFLCrVkzoEMHZiGEyxgOPNB94npHHslAzEsvUfCwuJj/nxV4PDyvrVvz8x04EP1G98eUldMAAM1GNkNxKQM6/T7qh4kXRFCzKAiCIAiCe/F4WH5QU6CCz5u3AAAoZklEQVTA7wfuvttdWkuCYCfp6dT9GDDAbkssweVLuUJUpKRw1XvePODoo+2LhhUVATt38gZVUsJo99dfAw8/DAwZAnTvTqGQRo2YNn/VVcCkSfbYGi0eD3DdddSF6NeP4oFm4vMx6HLeeexoMXcucMEFDBqUEQgGsLNoJwJBB5VFCIIgCIJgLoFA7ToFzz1XOStUEITa2b2bWcRJggQKkpELLgAOOAAYOZJp6qkOSSwJhXgB7t5NYcWtW4E//wRefRW45x67rYuOffahZsE331Dk0ejsiOxsZmI88giwYQPw7rss6ajA6LNHVykxSPek47OzPzPWFkEQBEEQnEdJCTM5q2PXLnbHkrIDQYiOH36g9kcSIIGCZKRlS+DDD4FXXuEqdPfuzk7zz8mhzoJT2bKF7Shff71qK8ru3YF//mGgw+eLLygTLtno3Rv48ktg1SrghhtqbNMy8NOB/5UbhCkuLcaAT5MjXUoQEoKdO4FffgGef56ZQwceyI4zTz/NNk2CIAi1MW9e9Y+PGMFFGYEZtmlpdlshuIX0dAYLkgAJFCQjZ57JFel584AePYAnnwRee40Tcic6yvR0pvE7Ca2BqVN5Lps1A+6/n50Peveu2mIoLQ244w5g8WKqpUYblMnJAerXB269FVi6lLVRJ54IKBXR272pXtTLqAdvqsllEIIgGMPu3RRGbdyYW9++1B756CNgyRJg/ny2wG3bFvjxR7utFWpj4ULWso4YISnegj2sWFF1EWPrVgYbk2RVtE5KSoCrr+aYrnVrjtuystixK1nafguRs2sXW4omARIoSEZ69qROQDDI1fBjj+VK99KlbKHnpOwCrxe4+WbnlEfs3k2xwtatea7GjuW5LCykGNBPP7Ed5C+/VH1vs2bAhAnAF1+wjWRt59nj4f+elwe89RZXDh9+GGjaNGJTx507DscfcDyOP+B4rLl5zX+/jzt3XNT/tiAIFtKtG0uXtmzhAHbnzqoD+kCAg5XTTmMLXBe0Ok4qVqwABg6kSO+YMcADD/C+MVGEZAWL0RrYuLHyYw8+aK6gtdtISQH22w/4/HOOhQMBYM4clnXedx/97AEHcCyanc0FHLd37BLi4+uvrRMstxGlXTC4kB7fJnDYYRS+C+P1Atdfz5r3L74ArriCjtLuFZDMTGDNGmCvvey1Y948Rt8//pg3h7oUgr1elkvcf3/10ejCQp7rJ5/kOQ7fsLOyeFM//3xmKBx0kOH/ihAdydDnW3ysw+jalfoskeLzcTXsySfNs0mIjA0bWGr2/vscRO45GcvKYgD41VcZVE5yksG/AkCeUto2D1uvHoNVJ57Iv9etYxeEgAgcV6JxY+pKHXFEza8pKWEgYf584K+/gGnTgAULuJjj9XL8VlAggdtkIDcX+OwzZgo7mHh9rITDkpWzz2ZKf5hAgDWwffoAvXpRtb9vX3uzCzwe4Kyz7AsSFBUBH3xAkcCjjmJkORCIrI1QIECRoNNPr/75zExG9OfPB447jlHqli050N+4kaUgEiQQhOTkyiu5ahUpfj+zmQT72L6d5WGtWvFeUVhY/YptQQEzzjp1AoYOZbaIIJhJcXHlzgd33y3aBNWxeTMzbK+4gtdzdaSlcWw2cCCzPL/7Dli7ltmmv/xC7a9bb6U+1d57c2yXm2tflzHBPHbvZkA4wZGMgmRl9mw6svz8yo9nZDD9atIkTlzHjwcuuYSDm6Iia230ermqdsgh1h73338ZNHnjDUaF9zxH1eHz8QYSCPActm4NHH44AwX9+9f+Xq2ZNdGsWcS6A4J1JMOKl/hYh7FzJzunRONzjz6auimCtRQUsIPQ448zMBBNzXdmJu8XI0YAl1+elLXQyeBfAZszCgBg8GAuQPz7L9Chg2gT1EZGBreRI4FLL42vxCA/n0GaBQuAWbOAGTOAv//m414vAzbSdcK97LsvsH693VbUSrw+1iGF34LldOpU/aCkqAhYuZLPjx3LrIJly7jyMWaMtQ6tY0frggSlpawdHTECmD6df1dXe5SdzZtGIMAatbZtWYN62GG8+R50UPQZEEoBzZsb838IguB+6tUDjj+eq1WRkp5e92sE4yguBl5+mfXLxcWxpXEXFnK7+WZmk735JjPMBMFoZs/mz9tvT4q66rgoKuJ2ww3As88Co0Zx4ScWsrOBLl24XXJJ+eM7dlDodP788gDCP//wuJmZ9CkSzHE+SVA+JoGCZEUp1tV89lnV50KhcpGsxx8HrruO6TXffw9ccAGfM9uBZWdT1dtswmn+zz3HbgWhEM9NdjaddSDAiX+7dnT0hxzCgED79gwUCIIgmMHgwcDvvzO9MRIyMsy1RyClpSwtuP12Bs4jKUWri4ICdrPo3ZudiF54Adh///j3Kwhhli3jyvb48SJiGCkFBdSnOuYY6kY98QQ7UBlB/foUre3WrfLjmzcz+2D+fAYPZs2iJoLW9PFO0A4TSHo650kJjgQKkpkBA4Bvv615IBoIsK3fzJmcTJ98Mm82N94IfPihuUI4mZnMZjALranTMGYMb5oeDzsKHHQQAwIHH8yAwIEH0hZBEAQrOe206OqIJVBgPjt2UOhs0yZjAgR74vczs619e2YZ3HWXs7oQCe5l925qn8gkM3oCAbbCGz2a5QiXXGJex4PGjYETTuAWRmumt8+fz23aNAop/vsvx66pqfQdojthLRkZzPxLcCRQkMyE2yTWht8PfPopndPEiXRib7wBXHQRMGgQB05GBwy8XorBmFmvqRRFG887jwGBVq2oMSAIguAEvF7g//6Pg9NIkNID83n5ZXY1MDNIHgxyGzmSnRGefx445xzRrxHiw+fjCnUoZLcl7iRcjnD99eXlCJ06WXNspagdtt9+bMsdJhQCVq1iBsK8eeUBhNWreT/weBjQlAwScygurr1DRoIgXQ+Smb32ouheXQQCbKV48MF0QgCFEJcuBS67jANaI9EaGDLE2H1WxxVXAGecwbICCRIIguA0Lr888hInyXwyl5IS6ghY1VIuEAC2bOF9qnPn8hpzQYiFkhJph2gEBQUcD3frxnHqjh322ZKSArRoweyzO+5ga/Nly/g5z54NvPMOcO+9wKmnspQpNZVltTk5Eng0gk6deE4THAkUJDsDB0b2RS8pYbplt27lugY+H2spJ0+mEzIiYODxsCSgQYP49yUIguBmevSI/LVSemAuo0fbk7ZdUMBB/zHHABdeyPuwIESLBAmMJRCgVkmLFpyQO6mDnMdDoe0zzmCg4OuvKVJeUAD88Qezgu+8k1nFTZrw9Tk5DCJIACEyMjNZvp0ESKAg2TnttOgm+H4/yw7uuqs8ha1rV2DxYuDaa+MPFqSnA7fdFt8+hOTj99+pGCwIiURqKgOnkdTDGp3ZJZSjNfDAA5G1yjWLQIBlgK1asTuPW2rNtaYY8jnn0O5vvmE7YCdNrAQhFoqK2Mp26FCmoIczbp1Kejq7iZ19NjB8OAXK162jX/v5Z5ZW3XILO680asT7T24ukJVlt+XOI7x4mgQobYKzVkp9AiDcM6I+gB1a605KqRYAFgFYXPbcH1rrq+ran/T4NpFQiK24oh0A+XwsP3jmGTqTcAnDrFl0QuvXx9ZK8aijGPEUhEj4/Xfe2GbMoPDk/PmGH8KJfb7FxyYRU6dST6UuH33zzcBTT1ljU7Lx889M3zVDwDAWsrKYdffaa0CfPnZbUzMzZrA8cflynru0NI4diou5ctmmDdTcuY7zr4AJPlYpLR42wcnM5ELaiBEcV7ud/Hy2cFywgGP76dO5IJOfz8B0Mpez+HzAr7/G3jbTQuIdw5pSXKG1Pif8u1LqKQA7Kzy9TGvdyYzjCjGQksL01nHjonuf3w/89BPVmVNTqb7arBmjqgsXAg89xEFrNE7EqpaIgvv5/XcKXs6ZUx6QWrKELS4bNrTVNCsQH5tEHH00B2V1BQpEo8A8HnzQOUECgLYUFDD1tUsXih46qZ/3pk3ATTexq1DFMUBJCVdgw8yda71tESI+VoiawkKKHH7yCQUPL7rI3an82dnAkUdyu/TS8se3b+c4f/58dkWbOZMBhJISlsAVF5vfQt1uWrRwRZDACEwtPVBKKQBnA/jIzOMIcTJgAB1CtFR0BBddVJ5KmJ7OQMGff7LdYKTtnbKyuGojCDXxxx/Asceytm7q1MpZKxkZwHff2WebDYiPTQKUon+tTUvG62VKumA8S5YAv/1mtxXV4/cDv/xCUa2hQytPwu2guJirqa1aUcsoAVYbxccKUREuR7j2Wi6cOTgYFjMNGlAz5cormdU0cybbb65aBYwdSx9w0UUUQPd6GcSuVy9xOvNkZ3OhKkkwW6PgOAAbtdZLKjzWUik1Wyk1RSl1nMnHFyLhlFPiq3cMBtmWZcSIyo8fcgid5J130lnUFlm1oiWi4F7+/JN1cz16cNBeXVlLaSlvVsmF+Nhk4OKLqw6yUlLoN088EZg0iR0SBON57DFn9ycPhRi0f/NN4IADOHC3ox3axIksQQxnX7hFQ6FuxMcK0VNQQM2Crl2Bq66yP4hnBXvvzfvRddcxs2LePJ6HpUuZZfHIIyxNPvBA3s98PmoguK1zQChEzZUkIWaNAqXUDwD2reapYVrrcWWveRnAUq31U2V/ZwDI1lpvVUp1BjAWQEet9a5q9j8EwBAA2H///TuvXLkyJjuFCGnXLn4xOJ+PF8+rr1ZtN/j333xu2bLqUzgzM6lrUL9+fDYIicW0aQwgzZxZt+ZFRgaVfffZx1AT7NIoEB8rVKJFC36/PR7611NOYebWoYfabVnism0b0LSpu9Jos7LYb/3NNxlcNZslS9gmbtq0mHSJFGCbRoGlPhboLB42ScnM5PgkEcoRjCIU4v1swQIGFP78kwuLa9bwXKWkcK5gR9CzNjweYPBgCj+6hLjHsFprUzZQ/2AjgGa1vOYnAHl17atz585aMJk77tA6NVVrFhDEvnm9WnfpovXmzVWPEQxq/eSTWvt8WqeklL/H49H60kut/58F5/Lnn1p3787vSqTfvcMPN8UUADO0SX4ynk18bJIxciS/5+efr/U//9htTXLw4IO8p8V7X7Rj8/m07ttX65UrzTk3O3dqff31PD8V7+dRbk71r9poH2v390E2+7esLI5T5s419lpMJEpKtF68WOvPP9f6vvu07tNH62bNOD/JztY6J0drpez7DOvV03rdOrvPUlTE62PNLD3oCeBvrfWa8ANKqcZKKU/Z760AtAWw3EQbhEjp29eY9lqBAAXmDj6YUcKKeDxUqJ87F+jcubzlirREFMLMmgWccALT137+OfIVKq8XuOQSMy1zIuJjk4mbbqJY1Pvvs0e2YC7FxcDIke6ts/f7WQ7Qvj1w992xdSGqjlAIePvt8jKHQKC8VXLiIT5WMI6CAo6PjzoKuOaa5ChHiJbUVJYmnHkmcP/9wIQJwOrVPHe//06fc8cdwEknAfvuW97CMRadtWjJyABuvBFo0sT8YzkIMwMFg1BV/KU7gLlKqTkAPgNwldZ6m4k2CJFy5JHGpfiUlAAbN7I2a8yYqs+3bk1Ruscf54V3+OEczAjCxRcDU6bwOxQNoRBw1lnm2ORcxMcmG26r5XQzH33kbG2CSAgGOZEfOZIT+48/5rpYrPz5J7WHrrsO2LHDXSUZsSE+VjAWrXlNvv02y8neey++azJZSE/nAuSgQdQ6mDSJ5co7dwI//gi89BKD6cceCzRqVB5ACC9IGoFSybggFbtGgZVIj2+LOO00Ru+MJCxS+MAD1ddlbdjASKAV0UDB+YRCzCr4+mvg88+BxYsZTKpLpLC6DBaDsEujwErExwpCBbQG2rQBlifYQnFWFlfr3nwzutZeGzYAN9wAjB9veIaFnRoFVpKnlBYPK1QhK4saYaNGcRwjGMPu3eUtHGfPBqZP53gyEOC8JBBgMKG4OPKAcKdO3JfLiHcMK8sTQjkDBnA118h+0YEA8NRTnPx98knV6N6+1ekICUlLSgqQl8ftvvu4ajVpEjNTJk5k66FgkD/D+HwU0xIEQTCCH38ENm2y2wrjKSjgQPeYY5iB9dRTVCqvDa3ZbWbJkugzvQRBqJ3wNXnkkcCllwKPPsqVcCE+cnJY4nHUUZUf37aNAorz5/M8L1kCTJ7MkpBgkMGD6hamsrLY8jIJkYwCoZz164GWLStPwowiMxNo3hz4/numQApCtGgNLFrEgMHo0by5KsX+4U88YZqSsGQUCEKScfzx1EhJZNLT2T3j3ntZd1tTj/PJk4HTTzd2AaECklEgCGVkZnJ74QXgvPOkO4KVaM0uDH/+Cfz6K/DTT+wEl5HBsuxQiJlV9erZbWnUxDuGlUCBUJlWrYB//zVn3ykpjPJ99RXriAQhHvx+flc7djT1MBIoEIQaKCmhKNfHH1Nz5qqr6OfdzKJFwBFHJEP9PcnKYlvi114DTj216vPdulFEzCQkUCAIe5CVRd2uUaNMH98ItVBSwuyDP/+kjzznHLstiol4x7Auv6MLhnPmmexOYAahEIVHTjkFeOUVc44hJA8+n9xEBcEuwoK1H3wA5Oezc02nTuxq42YefTS5UuwLCoC1a4GBA9lxZvHi8udmzWJKriAI1lFQwGuvSxdmTO7aZbdFyUlaGu9pV17p2iCBEUigQKhM376cgJlJIMA2iYMHJ9eATBAEIRFYuBDo0IFBgbC4XUEBBUW7dgWuv960VHVT2byZZU1GdQByE34/8MsvHBgPHcqg/ldfub/zQyKSmsrszHr1yoWg3Z7JI1Qm3B3hzTdZrvvhh9IdQbAF8SxCZbp1s2by7vfT8R13HLB1q/nHEwRBMAOtgVWrgC++AL77LvEHc/n5QO/eFIWqbhIZCACvv87WX+PGWW5eXDz/vN0W2EsoxJKLN98E9t+ff5uVYShER3o60KsXS30efZRZmePGUavn3HPlc0pUCgsp6jxkCAUPFyyw2yIhyZCuB0Jl0tKoH/DDD+Yfy+9netXBB/N4kkYuCIKT0RpYswaYORP44w8K3s2bxxXotDT+bN4cePJJ1nsnohjVRx/VHdwtLOR23nkMPr/1Fs+LkyksBJ59Nnm0CWoj/Pk9+SR/+ny8Xwv20aoV8M03VR9fsYJdgSQ7M7EpKOB9p0sX4IorgOHDmVUiCCYjGQVCVQYONL/8IExJCZVEjzrKfatPgiAkLlqzdvvLL4FhwxhArVePPa8vvpidNn7/nSvsgQDrSAsKgL//Zj3jaaclZnbB1q2Rd8bx+6ke3b49MGKEs9PYP/ggOUsOaiNcPpKI32O3sd9+1T9+++3Ovq4E4wiXI7z+OssRPvpIrk3BdCRQIFSlTx+mHFpJQQHT5x54QByfIAjWs349MH48cM89LImqXx9o0wa48ELgsceA335jf+VwUKA2H1lQAEyZAowcaZn5lrFjR3QT6mCQAYMHH2TA4I8/TDMtZrQGHnrInboKVhDWoRDso7q20osW0WdJoCC5KCwEtm+nztdRR1EzRhBMQkoPhKo0bw40bgysXm3tcQMBrjrNnMl2W1ZlNQiCkFxs2EA/8+efnND/9RdXydPTmSFQMQgQayq638+gwwknAJ07G2K2I4hVU6agAFi2DDjpJGZcjBwJNGhgrG2x8t13opUjOJeUFJYe7Mmtt0ae3SMkHgUFwIwZQF4egwYPPyzlCILhSEaBUD39+9ujouv3A99/zz7WVgcqBEFIPDZtAiZOZLbSSScBDRtSaO+884BHHqHOwM6dDAjUlSkQLYEAO8ns3m3cPu1m27b43h8IMGW2ZUvg/fedkUH2wAMMEAmCE8nMrFp6MHs28OOP1md/Cs4iXI7w2mu8r338sTN8qpAwSKBAqJ7TTy9vu2M1hYXA0qXAoYcCU6faY4MgCO5lxQqgRw9gr72o3j5oEFPLf/yRKZtFRQwKWFGTvm0bcNFFiTN42749/n0UFTE4c9VVFDtcsiT+fcbK/PnAnDn2HV8Q6iItDWjSpPJjN94owptCOYWFvNdccQVw9NEsSxEEA5BAgVA9xx1nb0pbaSlrYXv2pHCLIAhCpCxeTE2BbdusDQpUR1ERU9vfesue4xvNzp3G7auggOUfXbsat89oefhhSd8WnI3WlTMKfvuNKeeJEnwUjKOgAJg2jeVuN9wgmVJC3EigQKiejAyKpNhNIMDI+VVXuUew57ff2BZt7Vq7LRGE5KRnT8DrtduKcvx+4PrrE2OVx+gyCq8XuPlmY/cZKRs2sNuOpG8LTqa4uDyjQGtOAKVdpVATFcsRDjgA+OQTCSoJMSOBAqFmzj7bGYNtvx947z2ge/f462Ot4Nhj+XPXLnvtEIRkxeMBLr2UKbtOIRAA/u//3K8gb2RngPR04JhjgLvuMm6f0fDsszKAFpxPSQnQqBF//+EHtmAVhLoIlyNcfjlLvOR7I8SABAqEmunTx24LyvH7qVJ+yCHOX5V74QVg+XLgoIPstkQQkpfBg4FUBzX20RpYtw649lq7LYkPIwMFe+0FfPopM7CsJhCgr5ayA8Hp5OZSXFprZiZJG08hGsIlXkccAdx0k5QjCFEhgQKhZlq1Yi9xp1BczIF2ly7sHexUrr2Wit6CINjHQQdRBdpJFBYyDfSzz+y2JHaMyojweoEJE+y7x7zzjmQTCO6gcWP+/OEHYM0ae20R3Em4HOHVV1mO8Omn4v+EiJBAgVA7p59uz2pPbRQUsA/3ww+LoxMEoWaGDgWysuy2ojJ+P8siVqyw25Lo0doYrRifj2n/nTrFv69YCIWA4cNlZVZwB2F9gvXr7bVDcD+BAMsRLrtMyhGEiJBAgVA7/fsDOTl2W1GVQAB49FHgrLPcX/MrCII5nHeeM0VQ/X4GYUtK7LYkOpQCHn+cE/1YycwE+vVjaYhdTJxobPcGQTCTAw6w2wIh0Qh3RzjiCOCWWyRoKtSIBAqE2jn+eOfWcPr9HPB17izpeIIgVKV+feCUU+y2oiqhELBsGXDbbXZbEj233spgQSxCt0oBzZsDb75pvF3RcP/9UqcruAOlWAYa/l0QjCIU4kLbyy8zGDV6tGTpClWQQIFQO14vJ+JOpbAQ+Ocf4NBDgT/+sNsaQRCcxrXXOjMryu9nveg339htSfQMHcrSgWiDBVlZDO7a2U1n9mxg4UL7jp9oeL3OK+9JJLxeYL/97LZCSGQCAWDrVpbEHXsssHix3RYJDkICBULdDBzIdFGnUloKbN8O9OgBvP223dYIguAkevZku0QnEggAgwa5s/Z48GD26Y500u/zsc1t69bm2lUXw4czwCzEj8/HtOWGDe22JHFJTS3XKBAEMyko4ILb4Yczc0zKEQRIoECIhFNPZWsep+P3c6Vr6FBn1iULgmA9Hg/7SKel2W1J9RQUAGeeyYCn27jgAmDUqLqDBT4fAwv9+1tiVo2sXQt8/TVTboX4CH+mDz7IzJh4dCuE2glnFEjpgWA24XKEl15i16DPP5dyhCTHBbM/wXbatnVPaqHfz6yCE09kloEgCMIVV3BlzokEg8Dcuezi4kYGDuRgMi+PmWfZ2dwAID2d944OHYAnn7TXTgAYOVKCBEbg8wEDBgBPP83Ja58+/PzdsKDgNkpKyjMKMjMlWCBYQyAAbNkCXHwx0L07S3yFpES8ulA3SgF9+9ptReT4/VRzPeQQqbUSBAFo3x5o2dJuK2rG76dA4G+/2W1JbPTpA0yfzuyI6dOBF18sFz189132f7c7UJOfz5Xv4mJ77XA7Xi9w8snAW29VnrS++iqQkWGfXYlKURGw9978vWdP+f4K1lJQAEydyla2//uflCMkIRIoECKjf38gN9duKyKnuBhYt46rHBMm2G2NIAh2M3SoszOjgkGmxbuZlBQGZS66CHjiCeDGG1lWUa+e3ZYx00xSaOMjMxPo2pXq6HvqfoQ/dwkWGEtOTvm5rl+fWkyCYCXhcoQXX2Q5whdfiC9NIiRQIETGiSe6TwBKa64iDRgAPPqoODZBSGbOPdfZOgAeD3DNNXZbkZiUlgKPPMLMDSE2MjKAjh0ZzKpJ7+PRR1luIhhHo0aV/776amd2cRESn3A5wkUXsXX6kiV2WyRYgAQKhMjIzmYLQjcSCLD+d+BA9wU7BEEwhvr1mTLtRDwerrw3a2a3JYnJ+PEMGguxkZbG0p3Jk2sXrmzQgF0lnJy54zb27HjQq5c9dghCmIIClskddhhw220SgE1w4goUKKUGKqUWKKVCSqm8PZ67Uym1VCm1WCnVq8LjvcseW6qUuiOe4wsWc/bZ7k0r9PtZgpCXx5IEQXAB4mMN5tprnbkal5YG3H+/3VYkLg88IIGCWPF4qLr/yy+RlR9efTXQuLH5dhmE433sAQdU/jstjdlRTm35KiQH4XKEF15gOcKYMZK1m6DEm1EwH8CZAH6u+KBSqgOAQQA6AugN4CWllEcp5QHwIoA+ADoAOLfstYIbOPVU+wWp4iEQoLjhwQdT7FAQnI/4WCPp2dN5A2ylWHfctq3dliQmS5cCf/9ttxXuRCmmvv/2W9UU+JpITQVef91N7RKd7WOrE2EdPJh6EYJgN4EAsHkzg1czZthtjWACcQUKtNaLtNbVycr3A/Cx1rpIa/0vgKUAjizblmqtl2utiwF8XPZawQ106ODejIIwwSDbJp5wAtW4BcHBiI81GI8HuPzymmus7SAz072tEd3APvs4W5vCydSvzyBB06bRva9nT+Doo6tv5efxUMfA63VEdo+jfazXW/2579yZZR6C4BS0lmB3gmLW8nBTAH9U+HtN2WMAsHqPx48yyQbBaJRiVsH779ttSfwEAkyRnDmTvbWdtsooCLUjPjZWBg8GXnqJ/cmdQF4eW08J5pCTw/TtpUvttsRd5OQAP/8MtG4d2/vffBO46y7eW7Oyyjevl8GxzEx+LqeeaqzdxmG/j01Lq6pRAHAsduWV1IMQ3SXBCbRvz8CikHDUGShQSv0AYN9qnhqmtR5nvEn/HXcIgCFlfxYppeabdawYaARgi91GVEDsqZ3q7fH7geee4+YEe+xD7KmddmbuXHxstTjtO2CePb/8Uv3Ka+0kz/mJDbGnZiKzZfdu4JBDzLfGZP8KOMjHsswhcnbtYmtqc3DSdxJwlj1OsgVwgz1z58ZyHzMK558fe4nLx9YZKNBa94xhv2sBNK/wd7Oyx1DL43se9zUArwGAUmqG1jqvutfZgdhTO2JP7Yg9teNEe8zcv/jYqog9tSP21I7YUzNOsgUw378C4mOrQ+ypGSfZAog9dSH21E68Ptas9ohfAhiklMpQSrUE0BbANADTAbRVSrVUSqWDQjFfmmSDIAhCoiI+VhAEwTzExwqCkPTEpVGglDoDwPMAGgP4Wik1R2vdS2u9QCn1KYCFAIIArtVal5a9ZyiAbwF4ALyltV4Q138gCIKQoIiPFQRBMA/xsYIgCDUTV6BAaz0GwJganhsOYHg1j08AMCHKQ70WvXWmIvbUjthTO2JP7Yg9ZYiPdQxiT+2IPbXjJHucZAtgsz3iYx2Dk+xxki2A2FMXYk/txGWP0lobZYggCIIgCIIgCIIgCC7HLI0CQRAEQRAEQRAEQRBciOMCBUqpgUqpBUqpkFIqb4/n7lRKLVVKLVZK9arweO+yx5Yqpe4w0bZPlFJzyrYVSqk5ZY+3UEoFKjz3ilk27GHP/UqptRWOe2qF56o9Vybb84RS6m+l1Fyl1BilVP2yx205P2XHtuS7UcOxmyulflRKLSz7Tt9Q9niNn5sFNq1QSs0rO+6MsscaKqW+V0otKfvZwCJb2lU4B3OUUruUUjdaeX6UUm8ppTapCq0BazofijxX9l2aq5Q6wiy7zER8bFT2OMbHin+t9vjiY2u3RXysxYh/jcoex/jXsmOKj616fPGxNdthu38ts8NcH6u1dtQG4CCw5+NPAPIqPN4BwF8AMgC0BLAMFJLxlP3eCkB62Ws6WGDnUwDuLfu9BYD5Npyr+wHcWs3j1Z4rC+w5BUBq2e+PA3jc5vNjy3ejwvGbADii7PccAP+UfTbVfm4W2bQCQKM9HhsB4I6y3+8If242fFYbABxg5fkB0B3AERW/nzWdDwCnApgIQAHoCuBPOz5DA/5n8bGR2+AYHyv+tVobxMdG93mJjzX//xX/GrkNjvGvZccVH1vVBvGxkX9WlvvXsmOb6mMdl1GgtV6ktV5czVP9AHystS7SWv8LYCmAI8u2pVrr5VrrYgAfl73WNJRSCsDZAD4y8zhxUNO5MhWt9Xda62DZn3+A/YXtxPLvRkW01uu11rPKft8NYBGAplYdPwr6ARhV9vsoAP1tsKEHgGVa65VWHlRr/TOAbXs8XNP56AfgXU3+AFBfKdXEEkMNRHysIVjuY8W/VkV8bFSIj7UA8a+GIGNYIj42cuz2sbb4V8B8H+u4QEEtNAWwusLfa8oeq+lxMzkOwEat9ZIKj7VUSs1WSk1RSh1n8vErMrQsfeStCqk2dpyTPbkMjFqFseP8OOE8AGDqGoDDAfxZ9lB1n5sVaADfKaVmKqWGlD22j9Z6fdnvGwDsY6E9YQah8qDFrvMD1Hw+HPN9MgnxsdXjRB8r/nUPxMfWifhYexH/Wj1O9K+A+NgqiI+tFSf5V8BAH2tLoEAp9YNSan41m6WRsjhsOxeVvxDrAeyvtT4cwM0APlRK5Vpgz8sAWgPoVGbDU0YcMw57wq8ZBvYd/qDsIdPOjxtQSmUD+BzAjVrrXbDhc6vAsVrrIwD0AXCtUqp7xSc1c5MsbYWilEoHcDqA0WUP2Xl+KmHH+TAC8bGG2WPpd1H8a2yIj60d8bHGIv7VMHtkDOsSxMfWjJP9KxD/+Ug10JaI0Vr3jOFtawE0r/B3s7LHUMvjUVOXbUqpVABnAuhc4T1FAIrKfp+plFoG4EAAM2K1I1J7Ktj1OoCvyv6s7VyZao9S6hIA/wegR9mX09TzUwemnYdIUUqlgc71A631FwCgtd5Y4fmKn5vpaK3Xlv3cpJQaA6a2bVRKNdFar1dMQdpklT1l9AEwK3xe7Dw/ZdR0Pmz/PkWK+Fjj7Klgl+k+Vvxr9IiPjQjxsQYi/tU4eyrYJWPYqjjiehAfWydO86+AgT7WTaUHXwIYpJTKUEq1BNAWwDQA0wG0VUq1LIvqDCp7rVn0BPC31npN+AGlVGOllKfs91Zlti030YbwcSvWlZwBIKx4WdO5Mtue3gBuA3C61tpf4XFbzg+s/25UQimlALwJYJHWemSFx2v63My2J0splRP+HRTumQ+ek4vLXnYxgHFW2FOBSqsbdp2fCtR0Pr4EcJEiXQHsrJDalQiIj90DJ/lY8a9VER8bMeJj7Uf86x44yb+W2SM+dg/Ex0aE0/wrYKSP1TYoVta2gSd1DRi92wjg2wrPDQMVQBcD6FPh8VNBJc5lAIaZbN87AK7a47GzACwAMAfALAB9LTpX7wGYB2Bu2YffpK5zZbI9S8Halzll2yt2nh+rvxvVHPtYMN1nboVzcmptn5vJ9rQCVXP/Kvs8hpU9vheASQCWAPgBQEMLz1EWgK0A6lV4zLLzAzr39QBKyvzO5TWdD1Al9sWy79I8VFC0dtMmPjYqWxzjY8W/Vnt88bF12yQ+1trvpPjXyG1xjH8tO6b42KrHFx9buz22+tey45nqY1XZGwVBEARBEARBEARBEFxVeiAIgiAIgiAIgiAIgslIoEAQBEEQBEEQBEEQhP+QQIEgCIIgCIIgCIIgCP8hgQJBEARBEARBEARBEP5DAgWCIAiCIAiCIAiCIPyHBAoEQRAEQRAEQRAEQfgPCRQIgiAIgiAIgiAIgvAfEigQBEEQBEEQBEEQBOE//h/fQBQMIo5YCwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 1260x1800 with 12 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"if not NO_SHOW:\n",
" # create a subplot with 12 routes.\n",
" plt.figure(figsize=(17.5, 25))\n",
" for seed in tqdm(range(12)):\n",
" plt.subplot(4, 3, seed + 1)\n",
" generated_obstacles = generate_obstacles(seed)\n",
" generated_destination = generate_destination(generated_obstacles, seed)\n",
" route_generated = None\n",
"\n",
" # try to generate a route\n",
" try:\n",
" route_generated, _ = experiments.generate_route(\n",
" position=Point(0, 0),\n",
" goal=generated_destination,\n",
" obstacles=generated_obstacles,\n",
" wind=(18, 180),\n",
" )\n",
" except Exception:\n",
" route_generated = None\n",
" \n",
" # plot the situation\n",
" plot_situation(\n",
" obstacles=generated_obstacles,\n",
" destination=generated_destination,\n",
" obstacle_color=\"RED\",\n",
" route=route_generated,\n",
" title=f\"Seed: {seed}, Cost: {route_generated.cost:.3f}\" if route_generated else f\"Seed: {seed}\",\n",
" legend=seed == 0,\n",
" )\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Das Normieren der Scenarios\n",
"\n",
"Um für eine Neuronales netzt Verständlich zu sein ist es immer einfacher wenn ein Input normeirt ist. Hier wurde sich entschieden die Scenarien als Bilddaten zu normieren. 128 x 128 Pixel sind wesentlich gleichförmiger als eine Mänge von maximal 40 Polygonen mit unterschiedlichen Formen. Daher verwandelt die folgende Funktion die mit den Oben definierten Funktionen genierten Scenarien Datensätze in eine Bildform. Rot ist dabei das Hinderniss. Grün das Ziel und Blau die Route. Entwender als Linie oder als Punkt wenn die Route sich ändert.\n",
"Für diesen code wurde sich am folgenden Beispiel orientiert. https://programtalk.com/python-examples/PIL.ImageDraw.Draw.polygon/"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def generate_image_from_map(\n",
" obstacles: dict[str, Polygon],\n",
" destination: Point,\n",
" route = None,\n",
" route_type: Literal[\"line\", \"dot\"] = \"dot\",\n",
") -> Image:\n",
" \"\"\"Generate an image from the map.\n",
"\n",
" Can be used to feed an ANN.\n",
" - Obstacles are marked as reed.\n",
" - The destination is marked as green.\n",
" - The points where the route will likely change are blue.\n",
"\n",
" Args:\n",
" obstacles: A dict of obstacles as shapely Polygons. Keyed as a string.\n",
" destination: A destination that should be navigated to.\n",
" route: The calculated route that should be followed.\n",
" route_type: How the route is drawn. If 'line' is selected the complete route is selected.\n",
" If 'dot' is selected the turning points a drawn in.\n",
" \"\"\"\n",
" # generate an empty image (All black)\n",
" img = Image.new(\n",
" \"RGB\",\n",
" (IMG_SIZE, IMG_SIZE),\n",
" \"#000000\",\n",
" )\n",
" draw = ImageDraw.Draw(img)\n",
" \n",
" # draw in all obsticles in red\n",
" for polygon in obstacles.values():\n",
" draw.polygon(\n",
" list(\n",
" (np.dstack(polygon.exterior.xy).reshape((-1)) + SIZE_ROUTE)\n",
" / (2 * SIZE_ROUTE)\n",
" * IMG_SIZE\n",
" ),\n",
" fill=\"#FF0000\",\n",
" outline=\"#FF0000\",\n",
" )\n",
" \n",
" # draw in a route if possible. Does so in blue\n",
" if os.getenv(\"PYRATE\"):\n",
" if isinstance(route, TimingFrame):\n",
" route = route.points\n",
" if route is not None:\n",
" route = ((route + SIZE_ROUTE) / (2 * SIZE_ROUTE) * IMG_SIZE).astype(int)\n",
" # draws the route as collection of lines\n",
" if route_type == \"line\":\n",
" draw.line([tuple(point) for point in route], fill=(0, 0, 0xFF))\n",
" # draw the route as a collection of points. The starting point is seen as redundent ad left out\n",
" elif route_type == \"dot\":\n",
" for point in route[1:]:\n",
" img.putpixel(point, (0, 0, 0xFF))\n",
" else:\n",
" raise ValueError(\"Route type unknown.\")\n",
" # draws in the destination in green\n",
" img.putpixel(\n",
" (\n",
" int((destination.x + SIZE_ROUTE) / (2 * SIZE_ROUTE) * IMG_SIZE),\n",
" int((destination.y + SIZE_ROUTE) / (2 * SIZE_ROUTE) * IMG_SIZE),\n",
" ),\n",
" (0, 0xFF, 0),\n",
" )\n",
" return img"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def generate_example_image(route_type: Literal[\"line\", \"dot\"]):\n",
" \"\"\"\n",
" Generates an example image with the seed 42.\n",
"\n",
" Args:\n",
" route_type: How the route is drawn. If 'line' is selected the complete route is selected.\n",
" If 'dot' is selected the turning points a drawn in.\n",
"\n",
" Returns:\n",
" The example image.\n",
" \"\"\"\n",
" # generate obstacles and a destination\n",
" obstacles = generate_obstacles(42)\n",
" destination = generate_destination(obstacles, 42)\n",
" # try to generate a route\n",
" try:\n",
" route, _ = experiments.generate_route(\n",
" position=Point(0, 0),\n",
" goal=destination,\n",
" obstacles=obstacles,\n",
" wind=(18, 180),\n",
" )\n",
" except Exception:\n",
" route = None\n",
" \n",
" # draw the scenario\n",
" return generate_image_from_map(\n",
" obstacles=obstacles,\n",
" destination=destination,\n",
" route=route,\n",
" route_type=route_type,\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nachfolgend werden zwei solcher Scenarien Bilder gezeigt. Zerst aber wird zum Vergleich das Scenario mit dem Seed 42 als Karte Dargestellt um den Unterschied zu zeigen."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"if not NO_SHOW:\n",
" # set the default seed of 42\n",
" seed: int = 42\n",
" # create a figure\n",
" plt.figure(figsize=(8, 8))\n",
" wind_dir = 180\n",
" # generate obstacles and a destination\n",
" generated_obstacles = generate_obstacles(seed)\n",
" generated_destination = generate_destination(generated_obstacles, seed)\n",
" route_generated = None\n",
" # try generating a route\n",
" try:\n",
" route_generated, _ = experiments.generate_route(\n",
" position=Point(0, 0),\n",
" goal=generated_destination,\n",
" obstacles=generated_obstacles,\n",
" wind=(18, wind_dir),\n",
" )\n",
" except Exception as e:\n",
" route_generated = None\n",
" # ploting the situation\n",
" plot_situation(\n",
" obstacles=generated_obstacles,\n",
" destination=generated_destination,\n",
" obstacle_color=\"RED\",\n",
" route=route_generated,\n",
" title=f\"Seed: {seed}, Cost: {route_generated.cost:.3f}\" if route_generated else f\"Seed: {seed}\",\n",
" legend=seed == 0,\n",
" )\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Zeigt das Scenario mit dem Seed 42 mit eingezeichneten Wendepunkten wenn dieses Notebook im Pyrate Docker Container ausgeführt wurde. Wichtig zu beachten ist in dieser Darstellung die Drehung des Vorzeichens der Y Achse was zu einer Horizontalen Spiegelung der Darstellung führt."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<PIL.Image.Image image mode=RGB size=400x400>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"generate_example_image(route_type=\"dot\").resize(\n",
" (IMG_SHOW_SIZE, IMG_SHOW_SIZE), Image.Resampling.BICUBIC\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Zeigt dads Scenario mit dem Seed 42 mit eingezichneten Wendepunkten wenn dieses Notebook im Pyrate Docker Container ausgeführt wurde."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<PIL.Image.Image image mode=RGB size=400x400>"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"generate_example_image(route_type=\"line\").resize(\n",
" (IMG_SHOW_SIZE, IMG_SHOW_SIZE), Image.Resampling.BICUBIC\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Massengenerierung von Daten\n",
"\n",
"Die oben definierten Funktionen generieren immer einen Datensatze.\n",
"Die folgenden Funktionen definieren einen einzu einen einzelnen Datensatz als `pd.Series` eriner einzelnen Zeile in einem `pd.DataFrame`. Die so erzeugten Datensatze wereden in `pd.DataFrames` zusammengefasst. Hier wurde eine Anzahl von 50 Datensaätzen auf einmal gewählt. Diese werden dann gespeichert um danach mehr Daten zu Generieren. Da der Wegfindealgorihmus immernoch experimentel ist werden Wege die nicht gefunden werden oder bei deren finden ein Fehler auftritt werden mit `NaN` gefüllt."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.257373Z",
"start_time": "2022-07-15T18:58:57.257373Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def generate_all_to_series(\n",
" seed: Optional[int] = None, image: bool = False\n",
") -> pd.Series:\n",
" \"\"\"Generates everything and aggregates all data into a `pd:Series`.\n",
"\n",
" Args:\n",
" seed:The seed that should be used to generate map and destination.\n",
" image: If an image should be generated or if that should be postponed to save memory.\n",
" Returns:\n",
" Contains a `pd.Series`containing the following.\n",
" - The seed tha generated the map.\n",
" - The destination in x\n",
" - The destination in y\n",
" - A list of Obstacle polygons.\n",
" - The route generated for this map by the roBOOTer navigation system.\n",
" - Optionally the image containing all the information.\n",
" Can be generated at a later date without the fear for a loss of accuracy.\n",
" \"\"\"\n",
" # generate obstacles\n",
" obstacles = generate_obstacles(seed)\n",
" # find a destination\n",
" destination = generate_destination(obstacles, seed)\n",
" \n",
" # find a possible route\n",
" try:\n",
" route, _ = experiments.generate_route(\n",
" position=Point(0, 0),\n",
" goal=destination,\n",
" obstacles=obstacles,\n",
" wind=(18, wind_dir),\n",
" )\n",
" except Exception:\n",
" route = None\n",
" \n",
" # collect all generated data in a `pd.Series`\n",
" return pd.Series(\n",
" data={\n",
" \"seed\": str(seed),\n",
" \"obstacles\": obstacles,\n",
" \"destination_x\": destination.x,\n",
" \"destination_y\": destination.y,\n",
" \"image\": generate_image_from_map(obstacles, destination, route)\n",
" if image\n",
" else pd.NA,\n",
" \"route\": route.points if route else pd.NA,\n",
" \"cost\": route.cost if route else pd.NA,\n",
" },\n",
" name=str(seed),\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nachfolgend wird ein kurzes Beispiel eines solchen `pd.DataFrame` angezeigt."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.259380Z",
"start_time": "2022-07-15T18:58:57.259380Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "a7f747777045479eb050b609c1af7890",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/12 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>obstacles</th>\n",
" <th>destination_x</th>\n",
" <th>destination_y</th>\n",
" <th>image</th>\n",
" <th>route</th>\n",
" <th>cost</th>\n",
" </tr>\n",
" <tr>\n",
" <th>seed</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>{'0': POLYGON ((-17.62168766659423 -98.3692662...</td>\n",
" <td>-66.0</td>\n",
" <td>-54.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>{'0': POLYGON ((-97.82715137072381 -82.2211677...</td>\n",
" <td>-38.0</td>\n",
" <td>65.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>{'0': POLYGON ((-46.23706006792075 -76.7569948...</td>\n",
" <td>73.0</td>\n",
" <td>49.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>{'0': POLYGON ((-7.4210414351932155 -83.111096...</td>\n",
" <td>31.0</td>\n",
" <td>56.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>{'0': POLYGON ((-77.97638439917915 -70.2390972...</td>\n",
" <td>47.0</td>\n",
" <td>54.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>{'0': POLYGON ((-71.45682729091783 -138.627922...</td>\n",
" <td>-67.0</td>\n",
" <td>37.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>{'0': POLYGON ((-76.20025009472265 -92.9434076...</td>\n",
" <td>-67.0</td>\n",
" <td>55.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>{'0': POLYGON ((10.806865516434499 -102.670968...</td>\n",
" <td>67.0</td>\n",
" <td>-52.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>{'0': POLYGON ((-38.740101054728726 -89.986420...</td>\n",
" <td>58.0</td>\n",
" <td>61.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>{'0': POLYGON ((-28.332925461055822 -73.516031...</td>\n",
" <td>45.0</td>\n",
" <td>-63.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>{'0': POLYGON ((-42.90670292182745 -82.5864109...</td>\n",
" <td>38.0</td>\n",
" <td>48.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>{'0': POLYGON ((-124.01583316741481 -73.449792...</td>\n",
" <td>-48.0</td>\n",
" <td>-31.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>&lt;NA&gt;</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" obstacles destination_x \\\n",
"seed \n",
"0 {'0': POLYGON ((-17.62168766659423 -98.3692662... -66.0 \n",
"1 {'0': POLYGON ((-97.82715137072381 -82.2211677... -38.0 \n",
"2 {'0': POLYGON ((-46.23706006792075 -76.7569948... 73.0 \n",
"3 {'0': POLYGON ((-7.4210414351932155 -83.111096... 31.0 \n",
"4 {'0': POLYGON ((-77.97638439917915 -70.2390972... 47.0 \n",
"5 {'0': POLYGON ((-71.45682729091783 -138.627922... -67.0 \n",
"6 {'0': POLYGON ((-76.20025009472265 -92.9434076... -67.0 \n",
"7 {'0': POLYGON ((10.806865516434499 -102.670968... 67.0 \n",
"8 {'0': POLYGON ((-38.740101054728726 -89.986420... 58.0 \n",
"9 {'0': POLYGON ((-28.332925461055822 -73.516031... 45.0 \n",
"10 {'0': POLYGON ((-42.90670292182745 -82.5864109... 38.0 \n",
"11 {'0': POLYGON ((-124.01583316741481 -73.449792... -48.0 \n",
"\n",
" destination_y image route cost \n",
"seed \n",
"0 -54.0 <NA> <NA> <NA> \n",
"1 65.0 <NA> <NA> <NA> \n",
"2 49.0 <NA> <NA> <NA> \n",
"3 56.0 <NA> <NA> <NA> \n",
"4 54.0 <NA> <NA> <NA> \n",
"5 37.0 <NA> <NA> <NA> \n",
"6 55.0 <NA> <NA> <NA> \n",
"7 -52.0 <NA> <NA> <NA> \n",
"8 61.0 <NA> <NA> <NA> \n",
"9 -63.0 <NA> <NA> <NA> \n",
"10 48.0 <NA> <NA> <NA> \n",
"11 -31.0 <NA> <NA> <NA> "
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = None\n",
"if not NO_SHOW:\n",
" df = pd.DataFrame(\n",
" [generate_all_to_series(i, image=False) for i in tqdm(range(12))]\n",
" ).set_index(\"seed\")\n",
" df.to_pickle(\"test.pickle\")\n",
"if os.path.exists(\"test.pickle\"):\n",
" df = pd.read_pickle(\"test.pickle\")\n",
"else: \n",
" print(\"No data generated or chached!\")\n",
"df"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Die Folgende Zelle ist Verantwortlich für das massenweise Generieren von Trainingsdaten. Sie kann entwender so eingestellt werden das nur eine einzige Batch aus 50 neuen Datensätzen generiert werden soll oder eine ganze Reihe von Batches. Sind nicht alle anforderungen zun Ausführen der Zelle erfüllt wird sie automatische übersprunngen."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.260370Z",
"start_time": "2022-07-15T18:58:57.260370Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# Skipps the following cell if the code can't be executed.\n",
"if os.getenv(\"PYRATE\"):\n",
" save_frequency = int(os.getenv(\"save_frequency\", \"50\"))\n",
" start_seed = int(os.getenv(\"seed_start\", \"0\"))\n",
" continues = bool(os.getenv(\"continues\", \"false\"))\n",
" \n",
" # try finding a block of seeds that is not used\n",
" files = glob.glob(\"data/*.pickle\")\n",
" seed_groups = {int(file[9:-7]) for file in files}\n",
" for next_seeds in range(start_seed, 1_000_000, save_frequency):\n",
" # skip if the seed block already exists or is generated by another instance if this notebook\n",
" if next_seeds in seed_groups:\n",
" continue\n",
" \n",
" # start generating routes for the seed block\n",
" print(f\"Start generating routes for seed: {next_seeds}\")\n",
" \n",
" # reserving the seed block by looking down the seed block with an empty file\n",
" tmp_pickle_str: str = f\"data/tmp_{next_seeds:010}.pickle\"\n",
" pd.DataFrame().to_pickle(tmp_pickle_str)\n",
" \n",
" # generate the data\n",
" df = pd.DataFrame(\n",
" [\n",
" generate_all_to_series(i, image=False)\n",
" for i in tqdm(range(next_seeds, next_seeds + save_frequency, 1))\n",
" ]\n",
" ).set_index(\"seed\")\n",
" \n",
" # saves the data and delete the temporary file\n",
" pickle_to_file = f\"data/raw_{next_seeds:010}.pickle\"\n",
" df.to_pickle(pickle_to_file)\n",
" os.remove(tmp_pickle_str)\n",
" \n",
" # break the loop if only a single block of data should be generated.\n",
" if not continues:\n",
" break"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Daten Zusammenfassen\n",
"\n",
"Nachdem man den Generierenden Teil des Codes für eine Weile hat laufen lassen erhällt man eine vielzahl einzelner Dateine. Diese werden Nachfolgend Zusammengefasst. Diese so zusammengefasste Tabelle wird nachfolgend bereinigt.\n",
"Direkt nach dem Zusammenfassen der Daten werden alle einträge für die keine Routen gefunden wurde weggelassen.\n",
"\n",
"Dies kann folgende Gründe haben:\n",
"* Startpunkt $P(0, 0)$ ist von Hindernissen eingeschlossen\n",
"* Der Zielpunkt ist von Hindernissen eingeschlossen\n",
"* Fehler im Algorithmus der die Routen generiert"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.262368Z",
"start_time": "2022-07-15T18:58:57.262368Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "88137743b4d9467d9a419895ca479506",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/1000 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" 50000 maps collected\n",
" 43400 routes collected\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>obstacles</th>\n",
" <th>destination_x</th>\n",
" <th>destination_y</th>\n",
" <th>image</th>\n",
" <th>route</th>\n",
" <th>cost</th>\n",
" </tr>\n",
" <tr>\n",
" <th>seed</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>{'0': POLYGON ((-17.62168766659423 -98.3692662...</td>\n",
" <td>-66.0</td>\n",
" <td>-54.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-6.514627334268863, -5.502693040...</td>\n",
" <td>100.151629</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>{'0': POLYGON ((-97.82715137072381 -82.2211677...</td>\n",
" <td>-38.0</td>\n",
" <td>65.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-38.0, 65.0]]</td>\n",
" <td>75292.761936</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>{'0': POLYGON ((-46.23706006792075 -76.7569948...</td>\n",
" <td>73.0</td>\n",
" <td>49.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [43.20648551245758, 31.2114102262...</td>\n",
" <td>18967.522925</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>{'0': POLYGON ((-7.4210414351932155 -83.111096...</td>\n",
" <td>31.0</td>\n",
" <td>56.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [5.303962239032221, 10.6856391688...</td>\n",
" <td>63200.630758</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>{'0': POLYGON ((-77.97638439917915 -70.2390972...</td>\n",
" <td>47.0</td>\n",
" <td>54.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [4.691900284503645, -5.4114328014...</td>\n",
" <td>28914.654143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50045</th>\n",
" <td>{'0': POLYGON ((-86.63193290264695 -93.5319244...</td>\n",
" <td>69.0</td>\n",
" <td>-61.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-9.17985022292322, 0.74185570341...</td>\n",
" <td>695.38234</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50046</th>\n",
" <td>{'0': POLYGON ((2.518895755683328 -96.87282498...</td>\n",
" <td>-71.0</td>\n",
" <td>-58.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-54.61671323674942, -33.84002165...</td>\n",
" <td>67.928607</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50047</th>\n",
" <td>{'0': POLYGON ((-4.460598846031621 -99.2649725...</td>\n",
" <td>-36.0</td>\n",
" <td>-47.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-36.0, -47.0]]</td>\n",
" <td>36.544878</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50048</th>\n",
" <td>{'0': POLYGON ((-90.6998307775452 -75.58510795...</td>\n",
" <td>-48.0</td>\n",
" <td>-42.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-48.0, -42.0]]</td>\n",
" <td>37.990761</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50049</th>\n",
" <td>{'0': POLYGON ((-73.30908588454162 -74.1477834...</td>\n",
" <td>-48.0</td>\n",
" <td>72.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-8.34785332097252, 2.56320973960...</td>\n",
" <td>34269.035908</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>43400 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" obstacles destination_x \\\n",
"seed \n",
"0 {'0': POLYGON ((-17.62168766659423 -98.3692662... -66.0 \n",
"1 {'0': POLYGON ((-97.82715137072381 -82.2211677... -38.0 \n",
"2 {'0': POLYGON ((-46.23706006792075 -76.7569948... 73.0 \n",
"3 {'0': POLYGON ((-7.4210414351932155 -83.111096... 31.0 \n",
"4 {'0': POLYGON ((-77.97638439917915 -70.2390972... 47.0 \n",
"... ... ... \n",
"50045 {'0': POLYGON ((-86.63193290264695 -93.5319244... 69.0 \n",
"50046 {'0': POLYGON ((2.518895755683328 -96.87282498... -71.0 \n",
"50047 {'0': POLYGON ((-4.460598846031621 -99.2649725... -36.0 \n",
"50048 {'0': POLYGON ((-90.6998307775452 -75.58510795... -48.0 \n",
"50049 {'0': POLYGON ((-73.30908588454162 -74.1477834... -48.0 \n",
"\n",
" destination_y image route \\\n",
"seed \n",
"0 -54.0 <NA> [[0.0, 0.0], [-6.514627334268863, -5.502693040... \n",
"1 65.0 <NA> [[0.0, 0.0], [-38.0, 65.0]] \n",
"2 49.0 <NA> [[0.0, 0.0], [43.20648551245758, 31.2114102262... \n",
"3 56.0 <NA> [[0.0, 0.0], [5.303962239032221, 10.6856391688... \n",
"4 54.0 <NA> [[0.0, 0.0], [4.691900284503645, -5.4114328014... \n",
"... ... ... ... \n",
"50045 -61.0 <NA> [[0.0, 0.0], [-9.17985022292322, 0.74185570341... \n",
"50046 -58.0 <NA> [[0.0, 0.0], [-54.61671323674942, -33.84002165... \n",
"50047 -47.0 <NA> [[0.0, 0.0], [-36.0, -47.0]] \n",
"50048 -42.0 <NA> [[0.0, 0.0], [-48.0, -42.0]] \n",
"50049 72.0 <NA> [[0.0, 0.0], [-8.34785332097252, 2.56320973960... \n",
"\n",
" cost \n",
"seed \n",
"0 100.151629 \n",
"1 75292.761936 \n",
"2 18967.522925 \n",
"3 63200.630758 \n",
"4 28914.654143 \n",
"... ... \n",
"50045 695.38234 \n",
"50046 67.928607 \n",
"50047 36.544878 \n",
"50048 37.990761 \n",
"50049 34269.035908 \n",
"\n",
"[43400 rows x 6 columns]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"DATA_COLLECTION_PATH: Final[str] = \"data/collected.pickle\"\n",
"\n",
"# Load a cached result should it not be demanded to generate all data new.\n",
"if os.path.exists(DATA_COLLECTION_PATH) and not GENERATE_NEW:\n",
" collected_data = pd.read_pickle(DATA_COLLECTION_PATH)\n",
"else:\n",
" # Read the first n files\n",
" # The number of files read can be defined with the constant: NUMBER_OF_FILES_LIMIT\n",
" # The dataframes read are concatinated direclty after\n",
" collected_data = pd.concat(\n",
" [\n",
" pd.read_pickle(filename)\n",
" for filename in tqdm(glob.glob(\"data/raw_*.pickle\")[:NUMBER_OF_FILES_LIMIT])\n",
" ]\n",
" )\n",
"# Prints a short summary of the data.\n",
"number_of_maps = len(collected_data.index)\n",
"print(f\"{number_of_maps: 8} maps collected\")\n",
"collected_data.dropna(subset=[\"route\"], inplace=True)\n",
"number_of_routes = len(collected_data.index)\n",
"print(f\"{number_of_routes: 8} routes collected\")\n",
"collected_data.to_pickle(DATA_COLLECTION_PATH)\n",
"collected_data"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"### Daten Filtern\n",
"\n",
"Die so erzeugten Daten sind ungefiltert. Sie müssen nun überprüft werden. Dazu wurden einige hundert Datensätze Geplottet. Einige Musster sind dabei Aufgefallen. Die Nachfolgenden Filter resultieren aus diesen Mustern.\n",
"\n",
"#### Die Route Verlässt die Karte\n",
"\n",
"Das Generieren von Heatmaps von Segelrouten erfordert das sich das mögliche Ergebniss sinvoll darstellen lässt. Dazu muss die Route vollständig im definierten Bereich liegen. Alle Routen die die Karte verlassen werden weggelassen."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.263369Z",
"start_time": "2022-07-15T18:58:57.263369Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"43400 - 188 = 43212 sets of data remaining.\n"
]
}
],
"source": [
"def check_route_in_bounds(route):\n",
" \"\"\"\n",
" Check if a route exists and is in bounds.\n",
" \n",
" Args:\n",
" route: An `np.ndarray` of points the builds the route.\n",
" \n",
" Returns:\n",
" A non existing route or a route that leaves the area routes should stick to return `False`.\n",
" Otherwise `True` is returned.\n",
" \"\"\"\n",
"\n",
"\n",
" # CHecks if the route exists\n",
" if route is None:\n",
" return False\n",
" if route is pd.NA:\n",
" return False\n",
" # Checks if the route is of the right dtype.\n",
" if not isinstance(route, np.ndarray):\n",
" return False\n",
" # Checks if a possition is out of bounds.\n",
" if np.array(\n",
" abs(route) > SIZE_ROUTE,\n",
" ).any():\n",
" return False\n",
" return True\n",
"\n",
"# Count the number of datapoints there are before this filter is used.\n",
"data_before = len(collected_data.index)\n",
"\n",
"# Filtering\n",
"df_filter = collected_data[\"route\"].apply(check_route_in_bounds)\n",
"filtered = collected_data[~df_filter]\n",
"collected_data = collected_data[df_filter]\n",
"\n",
"# Count the number of datapoints there are after this filter is used.\n",
"data_after = len(collected_data.index)\n",
"\n",
"# Print a short report over the changes to the dataset.\n",
"print(\n",
" f\"{data_before} - {data_before-data_after} = {data_after} sets of data remaining.\"\n",
")\n",
"\n",
"# delete variables that where only used inside this cell\n",
"del data_before, data_after, filtered, df_filter"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"#### Routen auf Fehler überprüfen\n",
"\n",
"Ein bug in der Routenfindung hat zu selbstschneidung der Routen gefürt dieser wurde beim Sailing Team Darmstadt e.V. behoben. In den ersten ca. 27000 datensätzen gibt es denoch Selbstschneidungen der Routen. Diese werden hier erkannt und da nicht Representativ und nicht Richtig aus diesem Datensatz herausgenommen."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.264374Z",
"start_time": "2022-07-15T18:58:57.264374Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"43212 - 2759 = 40453 sets of data remaining.\n"
]
}
],
"source": [
"def check_route_self_crossing(route):\n",
" \"\"\"\n",
" Check if a route has self intersections.\n",
" \n",
" Args:\n",
" route: An `np.ndarray` of points the builds the route.\n",
" \n",
" Returns:\n",
" `True` if the route is self ingtersecting.\n",
" \"\"\"\n",
" if isinstance(route, float):\n",
" print(float)\n",
" return not LineString(route).is_simple\n",
"\n",
"# count the number of datapoints before this filter was applied.\n",
"data_before = len(collected_data.index)\n",
"\n",
"# filter the data\n",
"collected_data = collected_data[\n",
" ~collected_data[\"route\"].apply(check_route_self_crossing)\n",
"]\n",
"\n",
"# count the number of datapoints after this fitler was applied.\n",
"data_after = len(collected_data.index)\n",
"\n",
"# print a short report over the changes to the dataset.\n",
"print(\n",
" f\"{data_before} - {data_before-data_after} = {data_after} sets of data remaining.\"\n",
")\n",
"\n",
"# delete variables that where only used inside this cell\n",
"del data_before, data_after"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"#### Filter der Routen nach Kosten\n",
"\n",
"Einige der Routen haben trotz einer Erfolgreichen wegfindung enorm Hohe kosten. Kosten werden beim Generieren der route mitberechnet und sind was bei dem Routengenerierenden Grandientenabstigsverfahren optimiert werden. Sie setzen sich zusammen aus Segelzeit und Risiken. Auserordentlich Hohe Kosten legen daher entwender nahe das keine gute Route gefunden werden konnte oder das die gefundene Route zu einem Schlechten Lokalen Minimum convergiert hat. Daher werden die teuersten $5\\%$ der Routen weggelassen.\n",
"\n",
"Die folgende Route berechnet das $95\\%$ Quantil und errechnet wie viele Einträge über $95\\%$ liegen."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.267367Z",
"start_time": "2022-07-15T18:58:57.267367Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2022 entries over the 0.95 quantile at 39839.307\n"
]
}
],
"source": [
"QUANTILE_LIMIT: Final[float] = 0.95\n",
"if \"DATA_UPPER_LIMIT_QUANTIL\" not in locals():\n",
" DATA_UPPER_LIMIT_QUANTIL: Final[float] = collected_data[\"cost\"].quantile(\n",
" QUANTILE_LIMIT\n",
" )\n",
" OVER_QUANTILE: Final[int] = int(len(collected_data.index) * (1 - QUANTILE_LIMIT))\n",
"print(\n",
" f\"{OVER_QUANTILE} entries over the {QUANTILE_LIMIT} quantile at {DATA_UPPER_LIMIT_QUANTIL:.3f}\"\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Der folgende Codeshnippsel berechnet das Histogramm der Kosten. Wie wenig die höchsten $5\\%$ der Kosten representativ sind ist direkt ersichtlich."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.269369Z",
"start_time": "2022-07-15T18:58:57.269369Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"collected_data[\"cost\"].plot.hist(bins=15, log=True)\n",
"plt.axvline(x=DATA_UPPER_LIMIT_QUANTIL, color=\"RED\", label=\"95% Quantil\")\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nochfolgend werden einige der Route mit sehr hohenn Kosten gezeigt. Die Meisten kommen dem Land sehr nahe oder Segeln sehr stark gegen den Wind."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.270369Z",
"start_time": "2022-07-15T18:58:57.270369Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "07e9b38a3e3444419be141489932469e",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/12 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x1800 with 12 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15, 25))\n",
"for count, (seed, row) in tqdm(\n",
" enumerate(\n",
" collected_data[collected_data[\"cost\"] > DATA_UPPER_LIMIT_QUANTIL]\n",
" .sort_values(\"cost\")\n",
" .iloc[0 :: int(OVER_QUANTILE / 12)]\n",
" .iloc[:12]\n",
" .iterrows()\n",
" ),\n",
" total=12,\n",
"):\n",
" plt.subplot(5, 3, count + 1)\n",
" plot_situation(\n",
" destination=Point(row.destination_x, row.destination_y),\n",
" obstacles=row.obstacles,\n",
" obstacle_color=\"RED\",\n",
" route=row.route,\n",
" title=f\"Cost: {row.cost}\",\n",
" )\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Die Daten werden nun beim $95\\%$ Quantil der Kosten gefiltert."
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.271368Z",
"start_time": "2022-07-15T18:58:57.271368Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>obstacles</th>\n",
" <th>destination_x</th>\n",
" <th>destination_y</th>\n",
" <th>image</th>\n",
" <th>route</th>\n",
" <th>cost</th>\n",
" </tr>\n",
" <tr>\n",
" <th>seed</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>{'0': POLYGON ((-17.62168766659423 -98.3692662...</td>\n",
" <td>-66.0</td>\n",
" <td>-54.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-6.514627334268863, -5.502693040...</td>\n",
" <td>100.151629</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>{'0': POLYGON ((-46.23706006792075 -76.7569948...</td>\n",
" <td>73.0</td>\n",
" <td>49.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [43.20648551245758, 31.2114102262...</td>\n",
" <td>18967.522925</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>{'0': POLYGON ((-77.97638439917915 -70.2390972...</td>\n",
" <td>47.0</td>\n",
" <td>54.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [4.691900284503645, -5.4114328014...</td>\n",
" <td>28914.654143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>{'0': POLYGON ((-71.45682729091783 -138.627922...</td>\n",
" <td>-67.0</td>\n",
" <td>37.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-42.539218405821984, 15.14880405...</td>\n",
" <td>186.095369</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>{'0': POLYGON ((-76.20025009472265 -92.9434076...</td>\n",
" <td>-67.0</td>\n",
" <td>55.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-7.80975254664349, 3.41866699781...</td>\n",
" <td>23898.229531</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50045</th>\n",
" <td>{'0': POLYGON ((-86.63193290264695 -93.5319244...</td>\n",
" <td>69.0</td>\n",
" <td>-61.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-9.17985022292322, 0.74185570341...</td>\n",
" <td>695.38234</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50046</th>\n",
" <td>{'0': POLYGON ((2.518895755683328 -96.87282498...</td>\n",
" <td>-71.0</td>\n",
" <td>-58.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-54.61671323674942, -33.84002165...</td>\n",
" <td>67.928607</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50047</th>\n",
" <td>{'0': POLYGON ((-4.460598846031621 -99.2649725...</td>\n",
" <td>-36.0</td>\n",
" <td>-47.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-36.0, -47.0]]</td>\n",
" <td>36.544878</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50048</th>\n",
" <td>{'0': POLYGON ((-90.6998307775452 -75.58510795...</td>\n",
" <td>-48.0</td>\n",
" <td>-42.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-48.0, -42.0]]</td>\n",
" <td>37.990761</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50049</th>\n",
" <td>{'0': POLYGON ((-73.30908588454162 -74.1477834...</td>\n",
" <td>-48.0</td>\n",
" <td>72.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-8.34785332097252, 2.56320973960...</td>\n",
" <td>34269.035908</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>38430 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" obstacles destination_x \\\n",
"seed \n",
"0 {'0': POLYGON ((-17.62168766659423 -98.3692662... -66.0 \n",
"2 {'0': POLYGON ((-46.23706006792075 -76.7569948... 73.0 \n",
"4 {'0': POLYGON ((-77.97638439917915 -70.2390972... 47.0 \n",
"5 {'0': POLYGON ((-71.45682729091783 -138.627922... -67.0 \n",
"6 {'0': POLYGON ((-76.20025009472265 -92.9434076... -67.0 \n",
"... ... ... \n",
"50045 {'0': POLYGON ((-86.63193290264695 -93.5319244... 69.0 \n",
"50046 {'0': POLYGON ((2.518895755683328 -96.87282498... -71.0 \n",
"50047 {'0': POLYGON ((-4.460598846031621 -99.2649725... -36.0 \n",
"50048 {'0': POLYGON ((-90.6998307775452 -75.58510795... -48.0 \n",
"50049 {'0': POLYGON ((-73.30908588454162 -74.1477834... -48.0 \n",
"\n",
" destination_y image route \\\n",
"seed \n",
"0 -54.0 <NA> [[0.0, 0.0], [-6.514627334268863, -5.502693040... \n",
"2 49.0 <NA> [[0.0, 0.0], [43.20648551245758, 31.2114102262... \n",
"4 54.0 <NA> [[0.0, 0.0], [4.691900284503645, -5.4114328014... \n",
"5 37.0 <NA> [[0.0, 0.0], [-42.539218405821984, 15.14880405... \n",
"6 55.0 <NA> [[0.0, 0.0], [-7.80975254664349, 3.41866699781... \n",
"... ... ... ... \n",
"50045 -61.0 <NA> [[0.0, 0.0], [-9.17985022292322, 0.74185570341... \n",
"50046 -58.0 <NA> [[0.0, 0.0], [-54.61671323674942, -33.84002165... \n",
"50047 -47.0 <NA> [[0.0, 0.0], [-36.0, -47.0]] \n",
"50048 -42.0 <NA> [[0.0, 0.0], [-48.0, -42.0]] \n",
"50049 72.0 <NA> [[0.0, 0.0], [-8.34785332097252, 2.56320973960... \n",
"\n",
" cost \n",
"seed \n",
"0 100.151629 \n",
"2 18967.522925 \n",
"4 28914.654143 \n",
"5 186.095369 \n",
"6 23898.229531 \n",
"... ... \n",
"50045 695.38234 \n",
"50046 67.928607 \n",
"50047 36.544878 \n",
"50048 37.990761 \n",
"50049 34269.035908 \n",
"\n",
"[38430 rows x 6 columns]"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"collected_data = collected_data.loc[collected_data[\"cost\"] < DATA_UPPER_LIMIT_QUANTIL]\n",
"collected_data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ein neues Histogramm der Kostenfunktion wird geplottet."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.272368Z",
"start_time": "2022-07-15T18:58:57.272368Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"collected_data[\"cost\"].plot.hist(log=True)\n",
"plt.title(\"Route costs cut at the 95% quantile\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"#### Filter der Routen nach Kompläxität"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Gegenüber den Routen mit zu Hohen Kosten stehen die Routen mit zu geringen Kosten. Daher werden als nächsten Routen mit zu niedrigen Kosten Betrachtet.\n",
"Nachfolgend ist eine Auswahl solcher niedrigkostiger Routen angezeigt. Es fällt auf das all diese Routen direkt sind.\n",
"Eine betrachtung der Verteilung der Routenpunkte ist daher notwendig."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.274377Z",
"start_time": "2022-07-15T18:58:57.274377Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1260x1800 with 12 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(17.5, 25))\n",
"for count, (seed, row) in enumerate(\n",
" collected_data[collected_data[\"cost\"] < DATA_UPPER_LIMIT_QUANTIL]\n",
" .sort_values(\"cost\")\n",
" .iloc[1:600:51]\n",
" .iterrows()\n",
"):\n",
" plt.subplot(4, 3, count + 1)\n",
" plot_situation(\n",
" destination=Point(row.destination_x, row.destination_y),\n",
" obstacles=row.obstacles,\n",
" obstacle_color=\"RED\",\n",
" route=row.route,\n",
" title=f\"Cost: {row.cost:.3f}\",\n",
" legend=count == 0,\n",
" )\n",
"plt.show()\n",
"del seed"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.340281Z",
"start_time": "2022-07-15T18:58:57.321167Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def get_route_points(data):\n",
" \"\"\"\n",
" Counts how many stops are made inbetween.\n",
" \n",
" Args: \n",
" data: a `pd.DataFrame` collecting all the data.\n",
" Returns:\n",
" \n",
" \"\"\"\n",
" complexity = data[\"route\"].apply(lambda r: r.shape[0] - 2)\n",
" complexity.name = \"route complexity\"\n",
" return complexity\n",
"\n",
"route_points = get_route_points(collected_data)\n",
"route_points.plot.hist()\n",
"plt.title(\"Route complexity in intermediate points\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Bei der oben angezeigten Complexität wird deutlich das diese teilweise etwas noch ist. Hier wird ein Limit von 15 eingeführt."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.344287Z",
"start_time": "2022-07-15T18:58:57.344287Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"38430 - 1797 = 36633 if only routes with less then 15 course changes remain.\n"
]
}
],
"source": [
"routes_before = len(collected_data.index)\n",
"collected_data = collected_data[route_points <= 15]\n",
"routes_after = len(collected_data.index)\n",
"print(\n",
" f\"{routes_before} - {routes_before - routes_after} = {routes_after} \"\n",
" f\"if only routes with less then 15 course changes remain.\"\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.346282Z",
"start_time": "2022-07-15T18:58:57.346282Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"get_route_points(collected_data).plot.hist(bins=15)\n",
"plt.title(\"Route complexity in intermediate points\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Die nun reduzierte Anzahl der Routen enthällt eine zwar Representative mänge an sehr einfachen Routen. Da das ergebniss dieser Routen aber eine lehre Heat Map für Kursänderungen ist muss hier deutlich Reduziert werden sodas sie nur einen angegebenen anteil am Gesamtvolumen ausmachen. Dieser Anteil wurde hier auf $5\\%$ gesetzt."
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.404332Z",
"start_time": "2022-07-15T18:58:57.386321Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Limiting simple cases to 5.0% of the total routes. Reducing simple routes to 11.5% of their volume.\n"
]
}
],
"source": [
"# Define the upper limit the route cann reach\n",
"LIMIT_SIMPLE_CASES = 0.05\n",
"values = get_route_points(collected_data).value_counts().sort_index()\n",
"chance_limit = (\n",
" (len(collected_data.index) * LIMIT_SIMPLE_CASES * (1 - LIMIT_SIMPLE_CASES))\n",
" / values.get(0, 1)\n",
" if 0 in values.index\n",
" else 0\n",
")\n",
"print(\n",
" f\"Limiting simple cases to {LIMIT_SIMPLE_CASES * 100:.1f}% of the total routes. Reducing simple routes to {(chance_limit * 100):.1f}% of their volume.\"\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Der folgende abschnitte setzt das oben aufgestllte limit um."
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"np.random.seed = 0\n",
"collected_data = collected_data[\n",
" (\n",
" (get_route_points(collected_data) > 1)\n",
" | (np.random.random(len(collected_data.index)) < chance_limit)\n",
" )\n",
"]\n",
"del chance_limit"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Die so veränderte distribution der Routencomplexität sieht dann so aus."
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.406316Z",
"start_time": "2022-07-15T18:58:57.406316Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"get_route_points(collected_data).plot.hist(bins=15)\n",
"plt.title(\"Complexity Distribution after an enforced minimum complexity.\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Das `pd.DataFrame` welches die Gefilterten Daten sammelt sieht dann wie folgt aus:"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.409316Z",
"start_time": "2022-07-15T18:58:57.409316Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>obstacles</th>\n",
" <th>destination_x</th>\n",
" <th>destination_y</th>\n",
" <th>image</th>\n",
" <th>route</th>\n",
" <th>cost</th>\n",
" </tr>\n",
" <tr>\n",
" <th>seed</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>{'0': POLYGON ((-17.62168766659423 -98.3692662...</td>\n",
" <td>-66.0</td>\n",
" <td>-54.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-6.514627334268863, -5.502693040...</td>\n",
" <td>100.151629</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>{'0': POLYGON ((-46.23706006792075 -76.7569948...</td>\n",
" <td>73.0</td>\n",
" <td>49.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [43.20648551245758, 31.2114102262...</td>\n",
" <td>18967.522925</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>{'0': POLYGON ((-77.97638439917915 -70.2390972...</td>\n",
" <td>47.0</td>\n",
" <td>54.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [4.691900284503645, -5.4114328014...</td>\n",
" <td>28914.654143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>{'0': POLYGON ((-38.740101054728726 -89.986420...</td>\n",
" <td>58.0</td>\n",
" <td>61.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-8.211437427025228, -1.293253961...</td>\n",
" <td>16899.906926</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>{'0': POLYGON ((-78.64598261951151 -82.5905995...</td>\n",
" <td>55.0</td>\n",
" <td>-72.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [7.15433954975134, 5.559264844101...</td>\n",
" <td>177.415475</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50034</th>\n",
" <td>{'0': POLYGON ((-28.196683384837495 -99.951510...</td>\n",
" <td>-60.0</td>\n",
" <td>-67.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-4.393689188661578, -7.847642659...</td>\n",
" <td>149.322187</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50039</th>\n",
" <td>{'0': POLYGON ((-80.21298069840438 -87.2502584...</td>\n",
" <td>74.0</td>\n",
" <td>31.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [5.67318252835214, -5.67318252835...</td>\n",
" <td>5162.824624</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50043</th>\n",
" <td>{'0': POLYGON ((-55.5210778390028 -66.95232495...</td>\n",
" <td>47.0</td>\n",
" <td>28.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [3.868462226776941, 3.86846222677...</td>\n",
" <td>284.832436</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50044</th>\n",
" <td>{'0': POLYGON ((-73.9722160089151 -90.72439219...</td>\n",
" <td>-66.0</td>\n",
" <td>49.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-66.0, 49.0]]</td>\n",
" <td>199.213594</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50049</th>\n",
" <td>{'0': POLYGON ((-73.30908588454162 -74.1477834...</td>\n",
" <td>-48.0</td>\n",
" <td>72.0</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td>[[0.0, 0.0], [-8.34785332097252, 2.56320973960...</td>\n",
" <td>34269.035908</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>22264 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" obstacles destination_x \\\n",
"seed \n",
"0 {'0': POLYGON ((-17.62168766659423 -98.3692662... -66.0 \n",
"2 {'0': POLYGON ((-46.23706006792075 -76.7569948... 73.0 \n",
"4 {'0': POLYGON ((-77.97638439917915 -70.2390972... 47.0 \n",
"8 {'0': POLYGON ((-38.740101054728726 -89.986420... 58.0 \n",
"12 {'0': POLYGON ((-78.64598261951151 -82.5905995... 55.0 \n",
"... ... ... \n",
"50034 {'0': POLYGON ((-28.196683384837495 -99.951510... -60.0 \n",
"50039 {'0': POLYGON ((-80.21298069840438 -87.2502584... 74.0 \n",
"50043 {'0': POLYGON ((-55.5210778390028 -66.95232495... 47.0 \n",
"50044 {'0': POLYGON ((-73.9722160089151 -90.72439219... -66.0 \n",
"50049 {'0': POLYGON ((-73.30908588454162 -74.1477834... -48.0 \n",
"\n",
" destination_y image route \\\n",
"seed \n",
"0 -54.0 <NA> [[0.0, 0.0], [-6.514627334268863, -5.502693040... \n",
"2 49.0 <NA> [[0.0, 0.0], [43.20648551245758, 31.2114102262... \n",
"4 54.0 <NA> [[0.0, 0.0], [4.691900284503645, -5.4114328014... \n",
"8 61.0 <NA> [[0.0, 0.0], [-8.211437427025228, -1.293253961... \n",
"12 -72.0 <NA> [[0.0, 0.0], [7.15433954975134, 5.559264844101... \n",
"... ... ... ... \n",
"50034 -67.0 <NA> [[0.0, 0.0], [-4.393689188661578, -7.847642659... \n",
"50039 31.0 <NA> [[0.0, 0.0], [5.67318252835214, -5.67318252835... \n",
"50043 28.0 <NA> [[0.0, 0.0], [3.868462226776941, 3.86846222677... \n",
"50044 49.0 <NA> [[0.0, 0.0], [-66.0, 49.0]] \n",
"50049 72.0 <NA> [[0.0, 0.0], [-8.34785332097252, 2.56320973960... \n",
"\n",
" cost \n",
"seed \n",
"0 100.151629 \n",
"2 18967.522925 \n",
"4 28914.654143 \n",
"8 16899.906926 \n",
"12 177.415475 \n",
"... ... \n",
"50034 149.322187 \n",
"50039 5162.824624 \n",
"50043 284.832436 \n",
"50044 199.213594 \n",
"50049 34269.035908 \n",
"\n",
"[22264 rows x 6 columns]"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"collected_data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Das convertieren in trainierbare Daten\n",
"\n",
"Die bisher erstellten und gefilterten Daten müssen nun mit der oben definierten methode zum generieren von Bildern `generate_image_from_map` transformiert werden. Die so transformierten daten werden dann zusammengefasst und in ein `tf.Dataset` convertiert werden welches von Pandas genau für solche Fälle vorgeshen wird. Es gibt dort auch andere Methoden wie zum Beispiel die methode `tf.keras.utils.image_dataset_from_directory`. Bei diesem Problem besteht aber die Hoffnung das auch ohne Solche Methoden der RAM ausreicht und die Daten nicht immer wieder neu von der Festplatte gelesen werden müssen."
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.470318Z",
"start_time": "2022-07-15T18:58:57.470318Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def generate_image_maps(row, route_type: Literal[\"dot\", \"line\"]):\n",
" \"\"\"Generates the image version of the route.\n",
" \n",
" Adds another dimention to prepare vor concatination in a later step.\n",
" Divides by 0xFF to contain only 0 and 1 and valus.\n",
" Color channel zero contains obstacles.\n",
" Color channel one contains the destination.\n",
" Color channel two contains the route either as course change poiunts or as continues lines.\n",
" \n",
" Args:\n",
" row: The row of the pd.DataFrame that shoul be used to generate an image.\n",
" route_type: Defines if the route should be drawn as a collection of course change points or continues lines.\n",
" Returns:\n",
" The image modeified for concatination and sacled to be easily used for pandas.\n",
" Cast as uint8 for a minimal memory consumption.\n",
" \"\"\"\n",
" # expands the dimesion by one\n",
" img = np.expand_dims(\n",
" # converts the image into a numpy array\n",
" np.asarray(\n",
" # generate the situation image form a map\n",
" generate_image_from_map(\n",
" obstacles=row.obstacles,\n",
" destination=Point(row.destination_x, row.destination_y),\n",
" route=row.route,\n",
" route_type=route_type,\n",
" )\n",
" ),\n",
" axis=0,\n",
" )\n",
" # integer divide to ensure all values are between 0 and 1\n",
" img = img // 0xFF\n",
" return img"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.472315Z",
"start_time": "2022-07-15T18:58:57.472315Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# drop the image column to save some space in the dataset\n",
"if \"image\" in collected_data.columns:\n",
" del collected_data[\"image\"]"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.473311Z",
"start_time": "2022-07-15T18:58:57.473311Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# save the collected and filtered data into a pickle file to load again later and flush the ram a bit.\n",
"DATA_WITH_IMG_PATH: Final[str] = \"data/collected_and_filtered.pickle\"\n",
"collected_data.to_pickle(DATA_WITH_IMG_PATH)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.475316Z",
"start_time": "2022-07-15T18:58:57.475316Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "6647186a3e1c481da542b6bbd91911f2",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/22264 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# collecting map images with routes as lines.\n",
"collected_routes = np.concatenate(collected_data.progress_apply(\n",
" generate_image_maps, axis=1, args=(\"line\",)\n",
"))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Die gesammtlen Daten sind relativ groß die Nachfoglede Operation zeigt an wie viel RAM dafür gerade belegt ist."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.498310Z",
"start_time": "2022-07-15T18:58:57.479312Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"humanize.naturalsize(sys.getsizeof(collected_routes))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Stellt sicher das ein Datentype verwendet der ein Minimum an Speicher verwendet."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.501315Z",
"start_time": "2022-07-15T18:58:57.501315Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"assert str(collected_routes.dtype) == \"uint8\", \"Dtype needs to be unit8 to fit in the ram.\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.504314Z",
"start_time": "2022-07-15T18:58:57.504314Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"COLLECTED_ROUTES_LINE_DUMP = \"data/collected_routes_np_line.pickle\"\n",
"with open(COLLECTED_ROUTES_LINE_DUMP, \"wb\") as f:\n",
" pickle.dump(collected_routes, f)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Generieret die Daten für das Line format"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# collecting map images with routes as dots.\n",
"collected_routes_dots = np.concatenate(collected_data.progress_apply(\n",
" generate_image_maps, axis=1, args=(\"dot\",)\n",
"))\n",
"assert str(collected_routes_dots.dtype) == \"uint8\", \"Dtype needs to be unit8 to fit in the ram.\"\n",
"COLLECTED_ROUTES_DOT_DUMP = \"data/collected_routes_np_dot.pickle\"\n",
"with open(COLLECTED_ROUTES_DOT_DUMP, \"wb\") as f:\n",
" pickle.dump(collected_routes, f)\n",
"# löscht das collection oject. Wenn die daten neu benötigt werden können sie vom der Festplatte neu geladen werden.\n",
"del collected_routes_dots"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Das Model\n",
"\n",
"\n",
"Jedes neueronalle netz hat eine Bestimmte *Form* diese wird im Modell definiert. Die Form bestimmt die Anzahl der Versteckten Schichten, ob beim Training spezielle Filter wie `Dropout` oder `BatchNormalization` ferwendet werden sollen. Auch die art der Aktivierungsfunktionen wird hier Definiert.\n",
"\n",
"Oft gibt es für Bestimmte Probleme schon die Eine oder adere Art von Netzwerkstrucktur/Modelstrucktur die sich als geeignet erwiesen hat. Für diese Art von Problem wo aus einem Bild eine anderes Generiert werden soll haben sich GAN netzwerke als besonder Schalgfertig erwiesen [2], [3], [4].\n",
"\n",
"GAN netzwerke bestehen immer aus zwei Kompenenten einem `Generator` und einem `Discriminator` der `Generator` generiert ein Bild von einem anderen Bild. Der `Discriminator` versucht die Builder zu Unterscheide und weist so den Gernerator auf Fehler hin die durch eine Normale Lernfunktion mit einer $l_1$ oder $l_2$ norm nicht herforgehoben werden weill es für diese oft reicht wenn das Ziel ungefähr erreicht wird. Der `Discriminator` sorg also führ Klare Kontrasste und einen Saubere Farbverläufer.\n",
"\n",
"Das hier betrachtete Problem erwartet nun eine Heat map. Da nicht davon auszugehen ist das die Perfekte Route driekt gefunden wurde ist ein etwas verwaschenes ergebniss eine Funktion nicht ein Problem. Daher wird hier versucht den Routenschätzer ohen `Discriminator` aufzubauen."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Der Generator\n",
"\n",
"Der `Generator` besteht ist eine Art von Autoencoder. Er nimmt das Bild Abstraiert es in einbe Sammlung von Features und generiert aus diesem Abstracten Format wieder ein Bild.\n",
"Der `Generator` besteht daher aus einer Reihe von *Downsamplern* gefolg von eben so vielen *Upsamplern*. Der Downsampler fasst jeden zweiten Pixel 3 Pixel über ein `tf.keras.layers.Conv2D` layer zusammen. Der Upsampler macht genau dies wieder Rückgänig. So wird die Bildgröße mit jedem Downsampler Layer halbiert und mit jedem Upsampler Layer wieder Verdoppelt. Dafür erhält jeder Downsampler mehr features während der Upsampler jedes mal Features verliert. Up und Downsmapler sind meist Symetrisch aufgebaut.\n",
"Wie in, sowohl dem Tensorflows Tutorial [4], als auch in dem Paxisteinstige Maschine Learning in der Sektion über GANs [2] zu lesen ist benögitgt der Downsampler eine BatchNormaliszation leaky Relu als AktivierungsFunktion im Downsampler. Relu wird für den Upsampler Verwendet.\n",
"* Relu `y = x if x >= 0 else 0`\n",
"* LeakyRelu `y = x if x >= 0 else b * x` wobei bei eine Zahl viel kleiner als 1 ist.\n",
"\n",
"BetchNormalization normaliesert die Output Werte über eine Trainig Batch indem der Mean jedes Layer Ausgangs auf 0 geschoben wird und auf die Varianz 1 skaliert wird[5]. Beim Ausführen des Models wird die in der letzten Epoche festgelegte Gesamtberschiebung und Skalierung genutzt. Dies sorg zusammen mit dem DropOut Filter im Upsampler für ein Konstitenteres Lernen und Verhindert das Overfitting.\n",
"Interesannterweise erhält jedes UPsampling Layer sowohl das Vorangangene Layer als auch das Symetrische Downsampling Layer als Input."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.578312Z",
"start_time": "2022-07-15T18:58:57.552321Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# Source: https://www.tensorflow.org/tutorials/generative/pix2pix\n",
"def downsample(filters, size, apply_batchnorm=True):\n",
" \"\"\"Create a downsample layer.\n",
" \n",
" A downsample layer contains:\n",
" * tf.keras.layers.Conv2D\n",
" * An aktivation Function\n",
" * Optional a batchnorm\n",
" * A activation function (LeakyRelu)\n",
" Args:\n",
" filters:\n",
" size: The number of \n",
" apply_batchnorm: If True the Batchnor is applied. Batch norms are used by default.\n",
" Returns:\n",
" A sequentail model contain the keras generated layers.\n",
" \"\"\"\n",
" \n",
" initializer = tf.random_normal_initializer(mean=0.0, stddev=0.02)\n",
"\n",
" result = tf.keras.Sequential()\n",
" result.add(\n",
" tf.keras.layers.Conv2D(\n",
" filters,\n",
" size,\n",
" strides=2,\n",
" padding=\"same\",\n",
" kernel_initializer=initializer,\n",
" use_bias=False,\n",
" )\n",
" )\n",
"\n",
" if apply_batchnorm:\n",
" result.add(tf.keras.layers.BatchNormalization())\n",
"\n",
" result.add(tf.keras.layers.LeakyReLU())\n",
"\n",
" return result"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.583314Z",
"start_time": "2022-07-15T18:58:57.583314Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# Source: https://www.tensorflow.org/tutorials/generative/pix2pix\n",
"def upsample(filters, size, apply_dropout=False):\n",
" initializer = tf.random_normal_initializer(0.0, 0.02)\n",
"\n",
" result = tf.keras.Sequential()\n",
" result.add(\n",
" tf.keras.layers.Conv2DTranspose(\n",
" filters,\n",
" size,\n",
" strides=2,\n",
" padding=\"same\",\n",
" kernel_initializer=initializer,\n",
" use_bias=False,\n",
" )\n",
" )\n",
"\n",
" result.add(tf.keras.layers.BatchNormalization())\n",
"\n",
" if apply_dropout:\n",
" result.add(tf.keras.layers.Dropout(0.5))\n",
"\n",
" result.add(tf.keras.layers.ReLU())\n",
"\n",
" return result"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.586314Z",
"start_time": "2022-07-15T18:58:57.586314Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def model_generator():\n",
"\n",
" inputs = tf.keras.layers.Input(shape=[IMG_SIZE, IMG_SIZE, 2])\n",
"\n",
" # down_stack = [\n",
" # downsample(64, 4, apply_batchnorm=False), # (batch_size, 64, 64, 128)\n",
" # downsample(128, 4), # (batch_size, 8, 8, 512)\n",
" # downsample(512, 4), # (batch_size, 4, 4, 512)\n",
" # downsample(512, 4), # (batch_size, 2, 2, 512)\n",
" # downsample(512, 4), # (batch_size, 1, 1, 512)\n",
" # downsample(512, 4), # (batch_size, 1, 1, 512)\n",
" # downsample(512, 4), # (batch_size, 1, 1, 512)\n",
" # ]\n",
" #\n",
" # up_stack = [\n",
" # upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n",
" # upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n",
" # upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n",
" # upsample(512, 4), # (batch_size, 16, 16, 1024)\n",
" # upsample(128, 4), # (batch_size, 32, 32, 512)\n",
" # upsample(64, 4), # (batch_size, 64, 64, 256)\n",
" # ]\n",
"\n",
" down_stack = [\n",
" downsample(64, 4, apply_batchnorm=False), # (batch_size, 64, 64, 128)\n",
" downsample(128, 4), # (batch_size, 8, 8, 512)\n",
" downsample(256, 4), # (batch_size, 4, 4, 512)\n",
" downsample(256, 4), # (batch_size, 2, 2, 512)\n",
" downsample(256, 4), # (batch_size, 1, 1, 512)\n",
" downsample(512, 4), # (batch_size, 1, 1, 512)\n",
" downsample(512, 4), # (batch_size, 1, 1, 512)\n",
" ]\n",
"\n",
" up_stack = [\n",
" upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n",
" upsample(256, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n",
" upsample(256, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n",
" upsample(256, 4), # (batch_size, 16, 16, 1024)\n",
" upsample(128, 4), # (batch_size, 32, 32, 512)\n",
" upsample(64, 4), # (batch_size, 64, 64, 256)\n",
" ]\n",
"\n",
" initializer = tf.random_normal_initializer(0.0, 0.02)\n",
" last = tf.keras.layers.Conv2DTranspose(\n",
" 1,\n",
" 4,\n",
" strides=2,\n",
" padding=\"same\",\n",
" kernel_initializer=initializer,\n",
" activation=\"tanh\",\n",
" ) # (batch_size, 256, 256, 3)\n",
"\n",
" x = inputs\n",
"\n",
" # Down sampling through the model\n",
" skips = []\n",
" for down in down_stack:\n",
" x = down(x)\n",
" skips.append(x)\n",
"\n",
" skips = reversed(skips[:-1])\n",
"\n",
" # Up sampling and establishing the skip connections\n",
" for up, skip in zip(up_stack, skips):\n",
" x = up(x)\n",
" x = tf.keras.layers.Concatenate()([x, skip])\n",
"\n",
" x = last(x)\n",
"\n",
" return tf.keras.Model(inputs=inputs, outputs=x)\n",
"\n",
"\n",
"generator = model_generator()\n",
"tf.keras.utils.plot_model(generator, show_shapes=True, dpi=64)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.587312Z",
"start_time": "2022-07-15T18:58:57.587312Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"!pip install pydot"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.588314Z",
"start_time": "2022-07-15T18:58:57.588314Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"!pip install pydotplus"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.589313Z",
"start_time": "2022-07-15T18:58:57.589313Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"generator.compile(\n",
" optimizer=tf.keras.optimizers.RMSprop(), # Optimizer\n",
" # Loss function to minimize\n",
" loss=\"mean_squared_error\",\n",
" # tf.keras.losses.SparseCategoricalCrossentropy(),\n",
" # List of metrics to monitor\n",
" metrics=[\n",
" \"binary_crossentropy\",\n",
" \"mean_squared_error\",\n",
" \"mean_absolute_error\",\n",
" ], # root_mean_squared_error\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.592314Z",
"start_time": "2022-07-15T18:58:57.592314Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"early_stop = tf.keras.callbacks.EarlyStopping(\n",
" monitor=\"mean_squared_error\",\n",
" min_delta=0.0005,\n",
" patience=2,\n",
" verbose=0,\n",
" mode=\"auto\",\n",
" restore_best_weights=True,\n",
")\n",
"\n",
"tf_board = tf.keras.callbacks.TensorBoard(\n",
" log_dir=\"./log_dir\",\n",
" histogram_freq=100,\n",
" write_graph=False,\n",
" write_images=False,\n",
" write_steps_per_second=True,\n",
" update_freq=\"epoch\",\n",
" profile_batch=(20, 40),\n",
" embeddings_freq=0,\n",
" embeddings_metadata=None,\n",
")\n",
"\n",
"reduce_learning_rate = tf.keras.callbacks.ReduceLROnPlateau(\n",
" monitor=\"some metric\", factor=0.2, patience=5, min_lr=000.1, verbose=1\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.594314Z",
"start_time": "2022-07-15T18:58:57.594314Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"plt.figure(figsize=(17.5, 25))\n",
"np_array = np.flip(collected_routes[1, :, :, :], axis=0)\n",
"\n",
"for chanel in tqdm(range(3)):\n",
" plt.subplot(1, 4, chanel + 1)\n",
" plt.imshow(np_array[:, :, chanel], interpolation=\"nearest\")\n",
"plt.subplot(1, 4, 4)\n",
"plt.imshow(0x88 * np_array[:, :, 0] + 0xFF * np_array[:, :, 2], interpolation=\"nearest\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.596313Z",
"start_time": "2022-07-15T18:58:57.596313Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"collected_routes[:, :, :, :2].shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.624444Z",
"start_time": "2022-07-15T18:58:57.598317Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"train_dataset = tf.data.Dataset.from_tensor_slices(\n",
" (collected_routes[:, :, :, :2], collected_routes[:, :, :, 2])\n",
")\n",
"# test_dataset = tf.data.Dataset.from_tensor_slices((test_examples, test_labels))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.626439Z",
"start_time": "2022-07-15T18:58:57.626439Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"train_dataset"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.628442Z",
"start_time": "2022-07-15T18:58:57.628442Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"BATCH_SIZE = 64\n",
"SHUFFLE_BUFFER_SIZE = 100\n",
"# train_dataset = train_dataset.shuffle(SHUFFLE_BUFFER_SIZE).batch(BATCH_SIZE)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.629441Z",
"start_time": "2022-07-15T18:58:57.629441Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"train_dataset = train_dataset.batch(BATCH_SIZE)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.630444Z",
"start_time": "2022-07-15T18:58:57.630444Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"history = generator.fit(\n",
" train_dataset,\n",
" epochs=20,\n",
" batch_size=512,\n",
" use_multiprocessing=True,\n",
" workers=5,\n",
" callbacks=[early_stop, tf_board],\n",
" # tqdm_callback,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.632443Z",
"start_time": "2022-07-15T18:58:57.632443Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"plt.plot(history.history[\"loss\"])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.633443Z",
"start_time": "2022-07-15T18:58:57.633443Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"collected_routes[0:1, :, :, :2].shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.634439Z",
"start_time": "2022-07-15T18:58:57.634439Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"predicted = generator.predict(\n",
" collected_routes[:100, :, :, :2],\n",
" batch_size=None,\n",
" verbose=\"auto\",\n",
" steps=None,\n",
" callbacks=None,\n",
" max_queue_size=10,\n",
" workers=3,\n",
" use_multiprocessing=True,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.635444Z",
"start_time": "2022-07-15T18:58:57.635444Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"predicted.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.637443Z",
"start_time": "2022-07-15T18:58:57.637443Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"plt.imshow(predicted[1, :, :, 0], interpolation=\"nearest\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.639225Z",
"start_time": "2022-07-15T18:58:57.639225Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"for pos in range(5):\n",
" plt.imshow(\n",
" predicted[pos, :, :, 0] * 0xFF + collected_routes[pos, :, :, 0] * 20,\n",
" interpolation=\"nearest\",\n",
" )\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.641233Z",
"start_time": "2022-07-15T18:58:57.640226Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"# tf.keras.utils.plot_model(generator)"
]
},
{
"cell_type": "raw",
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-11T16:47:19.020872Z",
"start_time": "2022-07-11T16:47:17.607427Z"
},
"pycharm": {
"name": "#%% raw\n"
}
},
"source": [
"!pip install pydot pydotplus graphviz"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2022-07-15T18:58:57.502313Z",
"start_time": "2022-07-15T18:58:57.502313Z"
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"memory = sorted(\n",
" [\n",
" (x, sys.getsizeof(globals().get(x)))\n",
" for x in dir()\n",
" if not x.startswith(\"_\") and x not in sys.modules\n",
" ],\n",
" key=lambda x: x[1],\n",
" reverse=True,\n",
")\n",
"memory = {name: humanize.naturalsize(mem) for name, mem in memory[:10]}\n",
"memory"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Ausblick\n",
"Minimaldistanz ist or verknüpft nicht and verknüpft."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Literaturverzeichnis\n",
"\n",
"[1] Jang, Hoyun and Lee, Inwon and Seo, Hyoungseock: *Effectiveness of CFRP rudder aspect ratio for scale model catamaran racing yacht test*, 2017\n",
"\n",
"[2] Aurélien Géron: *Praxiseinstig Machinen Learning mit Scikit-Learn, Keras uind TensorFlow*, 2020, O.Reilly Verlag\n",
"\n",
"[3] Jun-Yan Zhu: *Image-to-Image Translation with Conditional Adversarial Networks*, 2018, Available: https://arxiv.org/abs/1611.07004\n",
"\n",
"[4] Tensorflow: *pix2pix: Image-to-image translation with a conditional GAN* Available: https://github.com/tensorflow/docs/blob/master/site/en/tutorials/generative/pix2pix.ipynb Commit: df4485e052523e0f852e83cea30ad319808bd97b\n",
"\n",
"[5] Keras: *Keras* Available: https://keras.io/"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"@article{article,\n",
"author = {Jang, Hoyun and Lee, Inwon and Seo, Hyoungseock},\n",
"year = {2017},\n",
"month = {09},\n",
"pages = {4109-4117},\n",
"title = {Effectiveness of CFRP rudder aspect ratio for scale model catamaran racing yacht test},\n",
"volume = {31},\n",
"journal = {Journal of Mechanical Science and Technology},\n",
"doi = {10.1007/s12206-017-0807-8}\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Ich würde auch zu 1. tendieren, stimme Ihnen aber zu, dass das Thema sehr umfangreich ist. Könnte man sich nicht einen Teilbereich herauspicken? Ich verstehe nicht viel vom Segeln, daher lassen Sie mich kurz zusammenfassen, was Sie vorhaben: - Sie generieren Trainingsdaten mit dem existierenden aber langsamen GD Algorithmus. Ich nehme an, es handelt sich um lokale Routen in einem relativ kleinen Kartenausschnitt. Lässt es die Laufzeit zu, dass Sie eine große Menge an Routen berechnen. - Sie haben dann eine Karte und als Ausgabe eine Liste der Wendepunkte - Warum wollen Sie daraus eine Heatmap berechnen? Diesen Schritt habe ich noch nicht verstanden - Wenn Sie aus einer Karte eine Heatmap trainieren wollen und dafür genügend Beispiele haben, könnnten GANs hilfreich sein: https://arxiv.org/abs/1611.07004 Ich würde Ihnen raten, das Problem möglichst so zu reduzieren, dass es im Rahmen des Moduls noch handhabbar bleibt. Alles Weitere kann man sich auch für spätere Arbeiten aufbewahren. Das 2. Thema ist auch ok. Aber vielleicht nicht ganz so spannend. Ich überlasse Ihnen die Entscheidung. Freundliche Grüße Heiner Giefers"
]
}
],
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