{ "cells": [ { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "# Tutorial 1 - Intro Python\n", "\n", "Python ist eine Programmiersprache, die zugleich einfach und mächtig ist und welche die Spass macht. Die ersten beiden scheinen sich zu wiedersprechen und der dritte Punkt trifft in der Regel nicht auf Programmiersprachen zu. Nach einigen Jahren programmieren kann ich alle Puntke voll und ganz bestätigen. Dieses Tutorial soll Python als wirkungsvolles Tool vermitteln und nicht eine Programmiersprache. \n", "\n", "Falls du einen allgemeinen Einstieg in Python lesen möchtest, empfiehlt sich [A Byte of Python](https://python.swaroopch.com/) von Swaroop. Dieses Buch gibt es auch [online](https://cito.github.io/byte_of_python) in deutscher Version. Zitat daraus ist\n", "\n", "***\"Erfolg im Leben ist eine Sache, die weniger mit Talent und Gelegenheit zu tun hat, als mit Konzentration und Beharrlichkeit.\"***\n", "\n", "Viel Spass!\n", "\n", "Markus Markstaler.\n", "\n", "# Installation \n", "\n", "Der schnellste Weg um Python zu installieren ist über die Anaconda-Plattform, welches Python mit den wichtigsten Paketen (Libaries) enthält, sowie die Entwicklungsumgebung \"Spyder\" als Editor um Script-Files zu erstellen. (Internetsuche \"anaconda python\")\n", "Bei der Installation beachten das \"Add Anaconda to my PATH enviroment variable\" angekreuzt wird. Somit kann über das Command-Window python.exe in jedem Verzeichnis gestartet werden. \n", "Die Systemumgebungsvariabel (enviroment variable) kann auch nachträglich erweitert werden um den VERZEICHNISNAMEN, wo python.exe abgelegt ist (z.B. C:\\Anaconda3) durch folgenden Befehlt im Command-Window:\n", "\n", " path=%path%;VERZEICHNISNAMEN\n", "\n", "Bei Python gibt es grundsätzlich zwei Version: die 2.x und die 3.x. Natürlich verwenden wir die Neue Version! Die 2.x ist aber nach wie vor sehr verbreitet.\n", "\n", "**Pakete:** Zusätzliche Pakete können über das Kommando-Window (cmd) mit dem Befehl `conda install ` installieren, wobei `` durch den Namen des Pakets. Anconda enthält jedoch alle, für uns notwendigen Pakete. \n", "\n", "Wichtig! Aktualisiere das System mit dem Pakte Manager `conda`. Dieser organisiert das System und installiert die aktuellsten im System kompatiblen Pakete.\n", "\n", "`conda update --all`\n", "\n", "\n", "# Lets start\n", "Nun starten wir die Entwicklungsumgebung \"Spyder\" für Python (windowstaste dann Spyder eingeben oder bei Mac nach \"Spyder\" suchen). Das müsste dann so aussehen:" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "![Starten von Spyder und Befehl in Konsole eingeben](Folie1.PNG)" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Wie bei allem was mit Computer zu tun hat, geben wir nach dem Starten von \"Spyder\" in die Konsole (IPython console) ein Befehl ein. Die Konsole ist auch unser Python-Interpreter. Gib folgendes ein:" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Hello World!\n" ] } ], "source": [ "print('Hello World!')" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Es wird der String ausgegeben. Ein String ist gekennzeichnet durch \"doppeltes Hochkomma\" oder 'einfaches Hochkomma', was gleichbedeutend ist. Bei drei Hochkommas kann der Text über mehrere Zeilen geschrieben werden und im Text können Hochkommas verwendet werden." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [], "source": [ "a = 12" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "36.2\n" ] } ], "source": [ "print(a * 3 + abs(-0.2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "String und der Veriabelinhalt können als Text ausgegeben werden. Hierzu eignet sich der f-String (Formated string literals). Dabei wird vor den Kommas ein f geschrieben: " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Der Inhalt der Variabel ist 12 und ist im Text eingebettet\n" ] } ], "source": [ "print(f'Der Inhalt der Variabel ist {a} und ist im Text eingebettet')" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Die Variablen können auch in einem eigenen Fenster dargestellt werden, dem \"Variable explorer\". Dieser wird wie folgt geöffnet:" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "![Variablen über Variable Explorer anzeigen](Folie2.PNG)" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "# Tutorial 1 - Übung 1: Mathematische Funktionen in Python\n", "Nun werden einige mathematische Funktionen vorgestellt. Zuerst die Division:" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "8.75" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "35/4" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "So wird eine Ganzzahl-Division ausgeführt:" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "8" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "35//4" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Hier die Modulo-Funktion oder auch \"Rest\" genannt:" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "2" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "35 % 3" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Potenziert wird in Python mit **" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "8" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "2**3" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Im gleichen Stil kann auch so die Kubik-Wurzel geschrieben werden:" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "3.0" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "27**(1/3)" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Im Folgenden werden zwei Variablen definiert und geprüft ob sie gleich sind. Jede Zeile wird einzel eingegeben und mit Enter abgeschlossen:" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a = 5\n", "b = 6\n", "a == b" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a != b" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Logik-Operatoren sind \n", "\n", "\"&\" für bitweises UND, \n", "\n", "\"|\" für bitweises ODER und \n", "\n", "\"~\" für bitweises NICHT." ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Energierechnungen basieren in der Regel auf Zeitreihen, z.B. Strahlungswerte über einen Tag im Intervall von 15 min.\n", "Python bietet hier \"Liste\". Eine Liste beginnt und endet mit eckigen Klammern []." ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [], "source": [ "H = [0, 10, 120, 230, 430, 500, 510,]" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "# Tutorial 1 - Übung 2: Bibliotheken importieren\n", "Mit Anaconda sind bereits die wichtigsten Bibliotheken installiert. Wir verwenden zum Rechnen die \"numpy\" Bibliothek. Um sie anwenden zu können, müssen wir zuerst die Bibliothek importieren. Dies erfolgt mit 'import numpy'. Numpy ist eine Bibliothek mit vielen numerischen Funktionen, wie z.B. die Absolut-Funktion abs(). Wenn die Funktion aufgerufen wird, so muss zuerst der Bibliotheksname dann Punkt und dann der Funktionsnamen angeben werden wie z.B. \"numpy.abs(-3)\". Da dies etwas lang ist, importieren wir wie folgt \"import numpy as np\", dann müssen wir später nur \"np.abs(-3)\" angeben. " ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [], "source": [ "import numpy as np" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Nach Eingabe sieht man nichts auf der Konsole. Mit **dir(Bibliotheksname)** können alle Funktionen (aber auch Klassen und Variablen) der importierten Bibliothek aufgelistet werden. Die importierten Bibliotheken sind nun aktive bis Spyder wieder geschlossen wird." ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Liste ermöglicht auch unterschiedliche Typen wie String, Zahlen, usw.. Wir werden aber vektoriell rechnen, was ebenfalls durch numpy unterstützt wird, jeodoch müssen wir die Liste (nur mit Zahlen) in ein \"numpy-Array\" umwandeln. Dies geht so:" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [], "source": [ "Hn = np.array(H)" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "(7,)" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Hn.shape" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "\"shape\" gibt die Form der Matrix an, d.h. Anzahl Zeilen und Anzahl Spalten. Hier haben wir einen eindimensionalen Array." ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "### Indexierung\n", "Wie wir gelernt haben, wird eine Liste mit eckigen Klammern erzeugt. Werden eckige Klammern nach dem Variablennamen einer Liste oder eines Numpy-Array gesetzt, kann man auf die Elemente zugriefen. Man nennt dies \"Indexierung\", welches ein sehr mächtiges Werkzeug in Python ist.\n", "Die Indexierung beginnt bei 0 nicht bei 1, d.h. das erste Element ist Hn[0] ! Im Folgeden werden Befehle eingegeben und anschliessen mit Kommentar erklärt. Der Kommentar wir mit Doppelkreuz # angegeben. Eingabe des Kommentar ist nicht erforderlich, sondern hier nur als Erklärung." ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "230" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Hn[3] # das ist das vierte Element" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "510" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Hn[-1] # Das ist das letzte Element" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "array([230, 430])" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Hn[3:5] # Hier von Index 3 (viertes Element) bis und mit Index 4, ohne Index Fünf." ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "array([230, 430])" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Hn[3:-2] # auch hier wird zweitletzter Index nicht mit genommen" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "array([230, 430, 500])" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Hn[3:-1] # hier wird bis zum zweitletzten Element übernommen, ohne den letzten Index" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "array([230, 430, 500, 510])" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Hn[3:] # Hier wird bis und mit letztem Element übernommen" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true, "hideCode": false, "hidePrompt": false }, "source": [ "# Tutorial 1 - Übung 3: Ausführbare Programme, bzw. Skript-Files\n", "Die Befehle können wir in ein File schreiben und als Skript laufen lassen. Das File wird mit der Endung *.py gespeichert. Den Inhalt des Files schreiben wir im linken Fenster bei \"Spyder\", genannt \"Editor\". Im Folgenden importieren wir Numpy und die Bibliothek zum Erstellen von Diagrammen \"Matplotlib\" oder genauer gesagt aus der Hauptbibliothek \"Matplotlib\" importieren wir die Bibliothek \"pyplot\", worin die Diagramm Befehle sind. Wir definieren wieder einen Array und stellen diesen als Diagramm dar. Nachdem wir das Script-File erstellt und gespeichert haben, können wir dies mit der grünen Dreiecks-Taste oben links \"laufen\" lassen, oder wir drücken die F5-Taste." ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "### importieren von Bibliotheken\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "H = [0, 10, 120, 230, 430, 500, 510, 460, 310, 190, 80, 1,]\n", "Hn = np.array(H)\n", "\n", "### Ausgabe\n", "plt.plot(Hn, 'r--', label='Strahlung')\n", "plt.ylabel('Strahlung [W/m2]')\n", "plt.title('Tagesverlauf Globalstrahlung')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Das Diagramm wird mit \"plot\" generiert. Mit 'r--' wird die Linienfarbe und Linienart angegeben. Mit \"label\" wird der Name der Kennlinie angegeben, welcher nachfolgend über \"legend\" dargestellt wird. Der Befehl \"grid\" zeichnet die Hilfslinien ins Diagramm.\n", "\n", "Nun erzeugen wir einen Zeit-Array von 6 bis 19 Uhr. Der Zeitarray sollte gleich viele Elemente haben wie der Strahlungs-Array Hn. Die Länge des Strahlungs-Arry finden wir mit Hn.size heraus. Um einen Numpy-Array zu erzeugen verwenden wir die Funktion linspace(start,stop, AnzahlElemente). \n", "\n", "Du kannst das bestehende Skript-File mit den folgenden Aufgaben abändern und ausprobieren. Es ist nicht notwendig für jede Übung ein eigenes Skript-File zu erstellen und speichern." ] }, { "cell_type": "code", "execution_count": 62, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "### importieren von Bibliotheken\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "H = [0, 10, 120, 230, 430, 500, 510, 460, 310, 190, 80, 1,]\n", "Hn = np.array(H)\n", "tn = np.linspace(6, 19, Hn.size)\n", "\n", "### Ausgabe\n", "plt.plot(tn, Hn, color='#aa5500', linewidth=3, label = 'Strahlung')\n", "plt.xlabel('Zeit')\n", "plt.ylabel('Strahlung [W/m2]')\n", "plt.grid()\n", "plt.legend(loc='upper left')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Die Linienfarbe kann auch als RGB-Wert in Hex angegeben werden, durch \"color = #aabbcc\". Ebenso die Stärke der Linie über \"linewidth\"." ] }, { "cell_type": "markdown", "metadata": { "collapsed": true, "hideCode": false, "hidePrompt": false }, "source": [ "# Tutorial 1 - Übung 4: Wichtige Details..." ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# -*- coding: utf-8 -*-\n", "\"\"\"\n", "Es empfiehlt sich am Anfang kurz zu beschreiben was das Skript macht...\n", "24.2.2017, Markstaler\n", "\"\"\"\n", "\n", "### importieren von Bibliotheken\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "\n", "### Berechnung\n", "grad = np.linspace(0,360,200) # [°]\n", "amp = np.sin(grad/180*3.1415) # [1]\n", "\n", "### Ausgabe\n", "fig = plt.figure(1, figsize=(5,3))\n", "plt.plot(grad,amp, 'b-')\n", "plt.xlabel('Grad')\n", "plt.ylabel('Sinus')\n", "plt.title('Sinusfuntion über Grad äöüß')\n", "plt.grid(which='both', linestyle='--')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "hideCode": true, "hidePrompt": true }, "source": [ "Nun sind da einige neue Funktionalitäten. In der ersten Zeile steht \" # -*- coding: utf-8 -*- \". Bei Python können \"magische\" Kommandozeilen angegeben werden, sodass der Python-Interpreter den richtigen Zeichensatz verwendet. Standardmässig ist der ASCII-Satz vorgesehe, bei welchem die Umlaute und ß nicht enthalten sind. Dies führt zu einer Fehlermeldung (es lohnt sich dies auszuprobieren). Um die Kodierungsproblematik zu lösen, geben wir in der ersten Zeile an, dass der UTF-8-Code verwendet werden soll.\n", "\n", "Anschliessend kommt ein Kommentar über mehrere Zeilen durch drei Hochkommas zur Dokumentation, was das Skript macht. Anschliessend werden Bibliotheken importiert und eine Sinuskurve berechnet. Die Sinus-Funktion bei Numpy erfordert die Eingabe im Bogenmass (Radiant), wir verwenden jedoch das Gradmass. Deshalb die Umrechnung. \n", "\n", "Mit \"fig = plt.figure(1, figsize=(5,3))\" erzeugen wir ein Figure-Objekt mit Angabe der Grösse des Diagramms. \n", "\n", "Wenn wir das Script-File unter \"sinus.py\" abspeichern, so können wir das Programm wie folgt startet. Wir öffnen das Kommando-Window (Windowstaste+cmd) und wechseln in das Verzeichnis, wo \"sinus.py\" abgelegt ist. Wir geben in das Kommando-Window \"python sinus.py\" ein.\n", "\n", "Das Programm bleibt so lange offen, bis das Fenster wieder geschlossen wird." ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "# Tutorial 1 - Übung 5: Einrücken !\n", "Weitere wichtige Elemente beim Programmieren sind Möglichkeiten zur Steuerung des Programmflusses. Dies sind \"for/if/elif/else\" oder \"while\" mit \"break\" oder \"continue\". Sind diese Funktionen bekannt, einfach anwenden, Python ist hier intuitiv.\n", "\n", "Wen **for/if/elif/else** nicht bekannt sind, dann unbedingt in einem Python-Buch oder online-Kurs nachlesen oder ein online-video ansehen. Im Buch [A Byte of Python](https://python.swaroopch.com/) ist dies im folgendem Kapitel [Control Flow](https://python.swaroopch.com/control_flow.html).\n", "\n", "Wichtig bei Python ist, das Einrücken. Dies wird am Beispiel einer for-Schleife erklärt, da sie für Energierechnungen notwendig ist, um einzelne Teilschritte zu berechnen. Die Folgenden Zeilen können im Skript-File eingegeben werden." ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2\n", "3\n", "4\n", "nun ist die for-Schleife zu Ende...\n", "...und es wird im Code fortgefahren\n" ] } ], "source": [ "liste = [2,3,4]\n", "for i in liste:\n", " print(i)\n", "print('nun ist die for-Schleife zu Ende...')\n", "print('...und es wird im Code fortgefahren')" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Alles innerhalb der for-Schleife wird bei jedem Durchlauf bearbeitet. Was zu for-Schleife gehört und was nach der for-Schleife kommt, erkennt python durch das Einrücken. Eingerückter Code gehört zur for-Schleife. Ist der Code nichtmehr eingerückt so weiss Python dass die Schleife Zuende ist. Die for-Schleife führt Code-Sequenzen aus, wie hier \"print(i)\". i repräsentiert die einzelnen Elemente der \"liste\"." ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wahnsinn\n", "was\n", "mit\n", "Python\n", "alles\n", "geht!\n" ] } ], "source": [ "for s in ['Wahnsinn', 'was', 'mit', 'Python', 'alles', 'geht!']:\n", " print(s)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Kopieren in Python\n", "Stellt man sich einen Array als Kasten mit Schubladen vor, so lägen die Zahlenwerte in den einzelnen Schubladen. Als Beispiel ein Kasten mit Namen k und den Zahlen 1, 2, 3, 4, 5." ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": [ "k = np.array((1, 2, 3, 4, 5))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nun ist \"k\" nicht der Kasten, sondern das \"Schildchen\" wo auf den Standort des Kasten zeigt. Wir machen nun eine Kopie \"a\" von \"k\" und weisen dem letzen Element/Schublade den Wert 99 zu und sehen was passiert:" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a: [1 2 3 4 9]\n", "k: [1 2 3 4 9]\n" ] } ], "source": [ "a = k\n", "a[-1] = 9\n", "print('a: ' + str(a))\n", "print('k: ' + str(k))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nun geben wir \"k\" aus und sehen dass auch dort das letzte Element geändert wurde! Dies liegt daran das wir nicht den \"Kasten\" kopiert haben, sondern das \"Schildchen\". Die Änderung haben wir aber beim Kasten gemacht, d.h. beide Schildchen zeigen auf den selben Kansten.\n", "\n", "Um eine richtige Kopie zu machen, führen wir folgendes aus:" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a: [1 2 3 4 6]\n", "k: [1 2 3 4 9]\n" ] } ], "source": [ "a = k.copy()\n", "a[-1] = 6\n", "print('a: ' + str(a))\n", "print('k: ' + str(k))" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "# Hilfe\n", "Zu den einzelnen Funktionen ist ein Hilfetext hinterlegt, welcher durch \"help()\" aufgerufen werden kann. **Probiere mal \"help(np.sqrt)\"**." ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Für allgemeine Hilfe zu Python verwendet man am Besten die Internetsuchmaschine und stellt die Frage. Es finden sich Reference-Manuals, Lernvideos, Forumseinträge, usw.\n", "\n", "Beim Programmieren unterstütz der Editor die Fehlersuche durch Fehlermeldungen:" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "ename": "ValueError", "evalue": "operands could not be broadcast together with shapes (5,) (10,) ", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlinspace\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m10\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[0mb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlinspace\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m10\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m10\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mb\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;31mValueError\u001b[0m: operands could not be broadcast together with shapes (5,) (10,) " ] } ], "source": [ "a = np.linspace(1,10,5)\n", "b = np.linspace(1,10,10)\n", "c = a + b" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Unklar sind die Fehlermeldung wenn ungleichviel Klammern geöffnet und geschlossen werden. Hier wird der Fehler bei der nachfolgenden Zeile angezeigt, welches verwirrend ist." ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "ename": "SyntaxError", "evalue": "invalid syntax (, line 2)", "output_type": "error", "traceback": [ "\u001b[1;36m File \u001b[1;32m\"\"\u001b[1;36m, line \u001b[1;32m2\u001b[0m\n\u001b[1;33m c = a + b\u001b[0m\n\u001b[1;37m ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n" ] } ], "source": [ "b = (a + (2*a + 1)+ (3*a + 2)\n", "c = a + b" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Der zeite Fall von unklarer Fehlermeldung tritt bei Umlauten auf, kann aber durch die \"magischen Kommandozeilen\" gelöst werden (siehe weiter oben im Text)." ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [], "source": [ "a = 10 # [m] Breite\n", "b = 2 # [m] Höhe\n", "c = 2*a + 2*b # [m] Umfang" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Tutorial 1 - Übung 6: 3D Plot \n", "Variieren wir nicht einen Parameter, sondern einen zweiten Parameter, so lässt sich das Ergebnis als 3D-Plot darstellen. Dies wird über die Funktion \"plot_surface\" realisiert. Für die Farbdarstellung importieren wir cm (colormap). Im folgendem Beispiel wird \"cm.Blues\" verwendet. Es wird \"LinearLocator, FormatStrFormatter\" für die Achsenformatierung importiert.\n", "Beim untenstehenden Code wird eine Beispiel-Funktion gewählt, welche ein Eintdruck vermitteln soll was mit 3D-Plot möglich ist." ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [ { "data": { "image/png": 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/ztLSEmfOnOGZZ5657Zdot8VumH0PSq/Ly1e+8hXGx8d3TK4ZRVG5MYb/5V/9Md+cXsVxLFrdBJVl+I5NpeTT7AjGSg6NbkqlUqLd6tBJFAhDqg14IZ1uDJZFGPpEnYj6xBhrzS6VSl4onCpDmmqcVPETv3yBP/oXP9BfnI0xpGnaH1uzvLxMHMd88YtfBCAMw1vKJlzXHUjEHhQ35n6z7Ar2D8X//BZsF49rt9tMTU0RxzGTk5NorTl16tRA+xxW7O6lG7NXPrCwsIAxhqeffvq2sY5RNIL+xx9+kVfm2niBB1pTKQckMiDLMmSqqdbKNLoJWDYxLmMT48RRQq1aptnqUBurYJSP0oYoycALWWsneL5PKzVARqXkU/ZcDBavLbT48Z//Y375p/4ikAu27/v4vs/ExASQj6x5xzvegTGGKIr6ZRPz8/P9bFHLsm4SwF43jo0L614VqN0oYxjVee6GZbed52U7Cjfm/qEQuw1srI/rLQKWZbGyssL09DS2bXPq1CnGxsZI05TV1dWB930/uDGTJGFmZobl5WWOHj3KW97yFi5evDhQUP9u3Zj/+7/7El++vEaiTJ50goVjWwS+jdQamSREcUI59Oh0IlSWYfyQRIPMwLIErW6K0YZS6GGMYXyiwlqjje06WEZRqwREcUKiJdgOpcDlU1+5xn/8k0v84Hc9etvz64nY5OTkTa8ppfoNijudDjdu3Oi3puq1o+rFbDudDmEY3pXAjFo492pd3KgtuyzLBm7BV7D/KMSO/EvVbrdptVpUKpV+N4/5+Xnm5uao1Wo89thjlEql/nt2U7yG3X7Yha/ncuwtuL3ygVarxcmTJ3nooYfuaJjnnYrdv/vMt/j3n7lEogXKWOA4CCVJkowszaiVfTqAhUEAjuch05RWlHdOUVpTrY/TarYZr1dYa8eE5RKrzQgcH2HZBCWXtVZEEPoEnoclLCzbAiH45x95nrc/cZhTk9sX+e+EbdtUq9UtF9I0Tel2uywuLpKmKa+88gpRFAE7d5PZiVG7Cveq9XIvY3b7tSH5g8wDK3ab43GNRoPFxUXOnDnD7OwsS0tLHDp0iDe/+c1bWja7LXbD9Lsclp4l2Ol0biofeOyxx25Z+IwxA9fJ3Yl1+eVXlnj/R1/AdhxCAcoxCAxRoin7ZYyBRqqo16qstrokEurVCo12hIdCChsyiTKCcrVCM8owBizXw8oUYxWfONMkSUZ9rAK2QzdKkEojLBvPc8k0/J1f+AJ/+M++e+jPfzt67aggF77z588D3+4Z2osPbu4ms7Ex8eZuMqMcyfMgWXbDlh4UQ1/3Fw+c2G0Xj1NKsby8TKvV4vjx4zz77LM7LijDfgnuRByHKVUYlJ7Iv/jii9i2fVP5wFb0LLbbne+dWHYrrZif+JUv0Oxm2JagHSlsofF9D7/koZUmjhOMzksGxiohjVZEO5FUKyWanYTQt4mlJEoktm1huR6OBZ0oo1Iu0U4N0li4tkMmHDqtGNuCWiXEcfLWYkobvjXb4J9/5Kv8k7/x5qHOYVA2X8ON3WQ2o7Xuu0W73W6/m8xGy8R13Zvmt92p+I3SShy1NSSlHGkT5iJBZWfs2mljZDTSfZpo8T8ZY0b/FHkHPDD/871Mu83xuNXVVaanpzHG4Hkeb3nLW3blaW63xfF2bCwfSNOUs2fPMj4+ftv3DZp4crt5dlv97n/+13/CYiOmFHpkUlEteUSZoR3nolf2LUqBS7ujMEoRpRaea5NmEquUL4KZtrDCCmQZlXLAWjvF8UoQx2DZ+L5F1okpjZVZa8V4rk2tEtLNoNmVIAS+a+O7Nh/50yv8tbed4vyZidue77AME2ezLItKpUKlcuuooizLeO2110jTlEajwdzcHFEUYYzB9/1brEHf93c87l7OnrzX2ZgPmlVnVIz/xA+PdJ/xcz+3N8aO8ACIndaaJEn6VlLPNdHryF+tVnn00UfxfZ8XXnhhV2/wYZ58R5V0orXun+vY2Bjnz5/n1VdfHfiJedAencNmY/79/+fPePV6B2FZxJlGadBYhIHAsS263RhlLALfw3YdtM5ni9nCJc06JKmkFHp0E8VEvUQ7ckhkfnzXsSlVAjpS4DoWQeDRiDUICEoBy908TlUp+diWwBICDcTS8JO/eYFP/9N3jfw+GJXV47ouQRBQLpc5ceLETfvvJcD0YoRXr17t3/dbuUVd193TYjdqS2wvN6neGwiw9u/12ZditzkeZ4zBtm2yLGN2dpYbN25w6NAhnnrqqX48pfeeOznWbgjknVh2Gz/LxvKBycnJm2KPwwjToO7JYdyY//6PX+UzL9xAGk2UKBzbQhmDDXRTTSlwGQ9cGp0UlUHguXSTFK0FjutQqddJ0hTfsSFRdGJFKjW1crBedqCILYFjCeJEcnC8RLwWU6uW6GYa17FzKzKRWMIiVvnvhBDMLXf5J7/9Vd73Q08PdC7DMMo42+bYkxCCIAgIgqDfW3Tj9r2yiW63y+zsLJ1OJy/pWHcVaq3vupvMXrfsYHBrbZRx0fsGQSF29wsb43EzMzMIITh27Bjdbpfp6emb4nFbdeQflp4gDfr0OWj8a+O+B6VngSmlmJ6evql8YKtzHfWUhEHF7uWpVT748ZfBAtuyqNdckkQitUZhYdsGqQ3GgO/aJGkuhmHg0umm+I5FojQKG+G6jNUEjVbC+FiJtU7GeK3MymqHsbKPsSxa7YRGV2LZFrESYASVssdaO8H3HYTtUPLXZ+kBtm3xqefm+MF3nOKp0wduez6DMso6yGEX4o11gJt57bXX0FoThiHtdpsbN27Q6XRu6SazcYr3dvfvXrfshuVBc2OCAHtfScJN7Isz2yoeZ9s2a2trLC0tYYzh5MmTW2Yb3g2O4wz1hRxG7IZ1Yxpj+Na3vkWn0+HEiRM7lg/sxkigQc4pzhQ/+ZvPIbVAmdwlp5TG8xyCwKUbZ3SjDGM0ge+QZACSbpxRq/jYtqAbZxwYC1luRsSpolryGRtz6GZ6/ToIglKAAjrdjMmJMotrEWPVgChRhCWfRiehWvHxXAelDFIZpM6HjrqOTaINP/vhF/jkP/oLA12jQRllbdwo7+NyuczRo0dv+l3vO9VLlFlZWWFmZqZfNrFVN5m9bNkVpQQDIAo35p5lcXGx74LpPe1alsXCwgLXrl1DCMH58+e3DPRvxzBuyTstPxjkqXzQffemD3S7XY4dO8bjjz8+0jKBUfS87PG3f+lL3GimWLZFFGdIpfFdh0RqAlfgORbKt0liiRAwVvboOBYlzybOFPVqwEojpptKAj9v/JzIvP3XeNVnZU3R7KZ4rgUIBPRF0HFsSDWZ1BwYC7Edm3aUkiYKx7EIfAfHFkipcRyLhUbC+37vJf67wyM59ZG3C9vtDiobu8lsTmTa2E2m2+32u8lEUYSUEqXUTdbg5m4ygzJKy+5OhPOBtOys+1oSduS+PrOf/umf5u/+3b/Lk08+iZSSqampfozq7NmzLC8vDyV0wwxMhW9bdoMyzIy6ncTOGMPa2hrXrl3Dsqx+y7J6vT7QF3Q33Ji3432/9xIvzbaIpQYDBoHjusSZREmNlIrAy2NpruuRZgrbgXLo02jHWELgB7nb0nUsMIYklfiOhVIWjW7G2FiJRivuJ7TUKgGdRHLkQJlGV+L5DkZqMgTtbobMFOO1AGyBbeUCmWmN7znEUvGJi/OceavDO+767Eff9eReth7b2E1mI4uLiywvL3P8+PF+N5mlpaW+W9RxnC3dotsdf5TJM8XEgwEQwD4uzbivz6xer/Pyyy/3Y3UbJ2T36pKGoSdeg4rd690CbPP0gbNnz/bFfG5ubtemld+t2P3+hWl+/7k5lALXtdFK5ynxxpCsuyZLgUsqNYmC0M/LC+JEUi3bhIFLFGdobXKLLJZUSi4H6yHLjZiJsZBGJ7cYSyUfx4ZOJPEDBxJJJ9VoYzDrReZKQ6QyDo2XELZNJ5ZEMsOxLSxbkCqD77mkyvAbz8X88F/dv1MPRukq7D3I3a6bTKfTYW1tjbm5ObrdLgC+79/SX3SU1+xex//uDwo35p7DGMPnPvc5Pv3pT/PZz36WX/iFX+DZZ5+96YsxrNUFuRgNU8j6erUA26p8YPP0gWH2PUzM7m7dmN+aa/DBT72K0iBsC8cYYmVIpUIYsByLibGQVpSRSY3nCKJMUQ492t2UbN3ii+KMNJV4fm4VJ5nCcWyOTFbp5sG93GI0+QMq5NetHLr4nkO15LHaTlAI2lGK7zskRpB0UiwBrufgWHnNXaYMmdTYjsVaKvjAJ77Fz37fG+74GsCDMfXgdsLZ6yZTr9dv+n2vm0xPCHvdZDqdDl/84hd37CYzKIVlNwBFzG7v8fnPf55f+7Vf493vfjdnz57l6advTRO/E7FzHGco8boTN+Yw2xtjmJqa4vr167eUD2xm2Djc62HZNaOU9/zON0glJMpgtEYbUMrgOmBEvshKbQg9J++YkirGyh6JNNgWRInE92xC3yFOFTXXJkkkmdSEocdaJ6Ve9VDS0I4yxio+2hjGyoJOavB9m1aUIYTgQC2gHSssSzAxFrLcTPI6PN/BFuA5NlgCSxlsy6K5ME/7+iwf/OKf8su/kLtPfc/h8ESNv/Lnn+DHfuAd1Gul21yFnL0qUHvBStzYTWZj2cQXvvAF3va2t23ZTaZ3rM1u0e26yWRZVlh2t0WAvX8nud+X//vvfOc7eec738lv/uZvMjs7u+U2dzLj7U5jcMNsP4hwpGnK9PQ03W4XIcSW5QOb2S3X5J3OqdNa85Mf/jqLrRTbsQgtAeQuTBE4tGNJmim00niOReDl7spa2SWSUK86RL5LnEgs12Ei8MkySSfOqFd8VloxriWwbcFaO6VS8VHNGC0EUaKolT1IE2oln5awkJnCWDaZzDg0kZcpOLZFteyipQHLYi1W2LZANtdYu3wJnUQYrUBJmtLFswVRqpm/Mc0r00v82se+yJ9/+hF+7j1/jWp559Ex91uCyp2glBpZe6+eN2GnbjJSyr4F2Gw2uX79en8I72a3aBRFRUH57Sjq7Ibn3/ybf8Ov/uqvYozhx37sx/ipn/opfuZnfoY/+IM/wPM8HnnkEX7jN37jFnfGsNTrdV566aUtX7uThWVYsXMcpx9zGITbWXZRFDE1NUWz2eTEiROUSiVOnjw58L6HiQcOep53OqfuZ//fb/DaUoTrOGAM0hi0NiAspDKUfQffsWh1U0qhCwg82ybNFFIp4szgezZxqujGCq+6Xl5g21iejefaNDopYxWPtXaaW4aVAM+CCEiVoVJyiTOdD38NHdpR3j8zMaANTNR8OnGGxsKzYazscv3lbxCtLGK0xvSupxfkk+oti6SbUKmUEULQ7qZ85suv8h1/8+f453/v3fyPf+mpba/HfkpQ2Wlfo4z/3c4ScxyHsbGxW3q79rrJ9CzCXuJMlmXcuHHjFrdoqVTqN5fYyAPnxixidsPx9a9/nV/91V/ly1/+Mp7n8d3f/d187/d+L+9617t4//vfj+M4vPe97+X9738/H/jAB+7qWOPj4zQajRF98tfHsttq+175QG/6wLlz5xBCMDMzsyt1ebudoPJzf3SZ56+1UBowkig1sK6XmVK4dt6eywhBvRbQ7EoEUA1tXMciSRVxKgl9n8C3iRNFkinKobveNNomLPsEtqCd5NczkxqpDK5r43s2mTSUAodunE9BOBiGKC2ZHA9ZaiaMVT06scT1HHwnt7inLl4ka7eBvPhcBCEmyxCWjRECJSVYLtKATCWp1IgkxrJtfvbnP8WXXpjig//g+7a8JnvZshulQI0ye/JOP9fGbjK9IbxXrlzB932OHDlCFEV9Iex1k5FS9ovvS6USBw4cuCUuvu8RhRtzKL7xjW/w9re/vZ+W/F3f9V187GMf4z3veU9/m7e//e189KMfvetjjY+Ps7a2tu3rvYV60C/gsDG1OxG73v63Kh/YbOkOUwqxV8Tut/9shk98dYFMGWzLYIxNtWQhLEGSKHSSEfouUabwHQtLaFzHIss0nVjiuzblILfCkkxRDhziRJFlGrz8OnQTSbXkstbOODQWMJvKfryuFUlqZY+1VrqenJLH+LqpRoi83s628v6b41WHVIE2kpfjr7EAACAASURBVKsXv4pJYgCEBQg7FzrHwUi1npbtgVFkmcL1faSOqY9Vaba6WLbNb/3RC7x4ZYHf/+CPEPg3Lxp71bIbpUCNMrNzN2bZlcvlm7rJbB7CK6Xsi+ButQHc64h93CJt5Gf2xje+kc9+9rMsLy/T7Xb55Cc/yfT09E3b/Pqv/zrf8z3fc9fHmpiY2FHs7sQtuZvb9/pzLi4ucvHiRebn5zl79ixPPvnkli7dYTMsd2Oy+aDZmMYYvjwn+Y3PT4El8H0Hx3EJfQfLzl2hws4tOS0spIY40xgsaiUXzxFk0mALg3AsyoGN1nlSi+cKMqkJnDxJJJMavZ5zudaVHJ3MB+6GvrNeDO3gOvmo1yjVlEoumdRM1EOWWwkH6iFJpomkxrXh2vMvYtIULAtsN0+cETYiKOVFto6bp3naNsJ2yYxNtxtTqpRZaUYYyyYMfVzP4+WrK7zrJ3+DZju+5frsVctuL4rdvWg95jgOtVqNI0eO3HWI5X5ECBCWGOnPXmLklt3jjz/Oe9/7Xt71rndRqVR46qmnbrrJ3ve+9+E4Dj/8w3c/SmJQsdvKH7/T9oMyjMBorVlbW2NhYYHDhw/zxBNPbDnL7E73f68su17t3yefu8onr4BwHBygHUtKvkOjI9Emj9E5jsGxbYTQZNIiTiSuDb7nMTlephmlSA3VkkuWadqxxAtd6r7BwqC1ohzY+T6VwnctUmVACA7UQ1KZf852rKhVXNpRhlSG0PdYa+dZna2uXG8a7WPZgm9++QV0kubfdK0RtsAoC6MkYOfBPQC/jEBjtAYMQbVKpxsTBD6l0Mu7saQpnu8zs9jh+97zH/jUv/6blIJvNxrfi5bdXhW7ezml/MFF7Osknl2xWX/0R3+Uixcv8tnPfpaJiQkeffRRAD70oQ/xiU98gg9/+MMj+bKGYUiaptu+/npYarfbvtfZ5cKFCyilOHjwIOfOnbut0MHecE1uZ9kZY1hYWODChQt87ptz/H/TDhIL28mttrGyjzKCwLMZr3p0EkmcalKpUMYQ+DaTEyWMZZNqwBYIy0JpMNoQePmt2Y4lrmvTiDXtVFAfK3FoPCTJDNVST0igHWsC36bs5/E6hMVY2aUc2Cw1E0q+TZwZDtbzOIwGLr/0KjKOEY6N5fng+hjhIDwfvBDhBuD1sgtzKxMvf3+c5n93PI+1bp5ZOj4+RqY0qTJcvd7if/jffqd/7fZq6QGMLhHjfrfsNvIgujDZ55bdrojdjRs3AJiamuJ3f/d3+aEf+iH+8A//kA984AN8/OMfv6XN0N2ynZtttxNOdqrLS9OUy5cvc/HixX75wIkTJ4bKbNwLbszN22qtmZ+f58KFCzSbTaLqST7yiiLRYNsCEPi+jTYG37Uol3LXYjl00MagTL6d5zsY8ukGSapIZB67A2jFEqnBc/PMTaU1lcDBAFKDEhYTYwH+egwvzjRjZZfVrmZyPL+3Qt8mVlArexgEY2WXbqJIMknJt2ksLhE1m2BZGCHQUuZxOWFhZIawrDwbUxsIyli2A44PMkOUKmA0GE0kQStFdazKWifB9YO8KN3AN6fX+OH3fRzYu27MUbKXLbssywZq09fjQRQ7sW7ZjfJnL7Erdv0P/MAPsLy8jOu6/OIv/iLj4+P8xE/8BEmS8K53vQvIk1R+6Zd+6a6O07sht1tIdtuy2yotf3P5wMbpA693e7FRbtsTudnZWQ4cOMBTTz3FZ19b49e+NJeP2xF5v0ulNUlmqIVOnhQCaGOwbYsDNZ9WnBGnBt8V2HZe0N2NJVmmCTwLzxEkWd7eK/Rs0kyTZjpPWokhThWVwGGxmXJkPODUZImZ5ZjDYwHNWOG5FicmAjKpSaXhcD1ksZlRrwYYkdJNFEJL5qfm80wUy4C2wfn2OWBZgM5jdTIDYaGNAteDRGKUxvICsAQqzSiPjdFqd6hWSnSiFNd3UYBMMz73wgz/67/9r/z4Xz61J92Yo2SvukRhuOzOB3ZCwrplt1/ZFbH73Oc+d8vvXn311d04FGEYEsfxltai4zhkWTbwvu6k60qPVqvF1NQUSZLcVD6wef93MqPuXm5rjKHRaHDhwgUmJyd5+umncV2XD39llk++vIxSuUAIYXAcC2Og5Nu04jybEqASOOSpKFD2HZrdjCRTTHgupbJDmubbHqu5jDuGG12LwLY4fSDk6zNN4lTxxLEqcaLoJIrzx6osNlO6ieShAyHH6iFSG6ZXYlJpMMJCG0k1cLh8o8Mjh8q0IsmpAyUcC/7Ln3wNEAhjEI6LVuvjgbQErRCej8lShO1gLBuyNBc+rXAqY8ioC0KgTS6MUSqxg5BWLCmVS0TdiHLoo1wPYwk++tlLTASav/3uNw50zQdhL4rdqC27URWo9xhGiPfi9d1tBGJPegxGxX0fsa3X66yurm4rdkmSDLyvYQuojTFIKfna174GwOnTp3fM4tpNy27UVqCUkrm5OWZmZvB9n2eeeaYv1v/i06/xwnyHVOUWm20gwSC0hbBZT0ixGS85SAUr3Yyqb3Os5uPagvm1mNnVmBP1kPGyy6OHylxdiTBGMx66JI6g0c0ohQ5vPTtBkmmMNhyrB1y60SHKNEfGfG60UgLX5uJ0k2dP1ThY9bjRSnnDkRJxoqmWSnx9rs2BmsfUVJPVbobVatCJJcKyQdhoJUHlw121ZYPW+b9dF51l4PpYtoXtOGRRhFQa4Qd52aDMcEplZBKD1liuTzdKCMKAdmawhcRxXRzP5lc+fYU3PnyY7z88oplBe5S9GP8rGBABlv36i50Q4irQgtwhYox5VggxAXwEOANcBX7QGLN6N8e572W8Xq9vm5Hpuu4dW2o70ctAvHjxIlmW8fDDD/PUU0/dNl152Jq1e+HGlFJy9epVLl68CMC5c+eoVqs4jsOVxRbv/cQlvn69izK5y0NjaCeS8SCPyXmW4GQ94NHJEifGQ46O+Rwou6x1JQvNhJJn89ixKmcOl3llOWI5kqQamrFkuauQ2nC46oMQLLYzFIKXFjrMtlNOHAx55vQYi62EQ9X8qT/KNBXf5vmZJm8+lXfSKPs2s23DeDlPYHEdmydP1jhSsZmZX8ldlcaAMDiBD0EJbbkIxwW/jO2HCDvv6oJSgCBLJU6pAlphCYERFpaTD591wxLuesKRZdvEUoDIJye4jkAJgRYW//S3XmCpOXjHnQeZQTqo7CYPomUH9GeCjupnCP5bY8ybjTHPrv/7Z4HPGGMeBT6z/u+7Yt9YdltxN27Jrdg8feCJJ57g5ZdfHjjhZtgJAq+nGzPLMqanp1laWuLYsWP9fpyNRgOtNR/68jW+eKWNNIaK72CMYSx082nhkw7LnYyam3Kk7vOtpRjXtjhQcii7NkdqHqcnApa6koVOxoGKRyVwWGhlLDQTzhwIOTIWcG05opUajldtbAHzjYSDFY+x0KGxLorznZR61We8kicbzDdiToyHXFrskBrDM6fHaMa563qmGXOs7nOjnVv3r7w6jzICyxJguWgpkZnEcR2kMRglEY6HVCoXw7CEi0EZAVmK0uCEJYQwqCTDK5eJuxFSKhw/QKddhBeAzAiCAA1kxkInGmE08zLie//x7/ELf+vRfr/HXoGz53mv+wK7V2N/cHcdVDZzJ+e5V6/LbiLYUxmU3w/8hfW/fwj4Y+C9d7PD+17sduqicqditznhpefSu379OgcPHuSpp57q1+71rK9Bv5jDfIls296xtGIjwzS+3ih2aZoyNTXFysoKJ06c4Nlnn+0/kTVjyZ9eXeaLrykIUiZrAY4QIASdNO+AkkhDK5FMlBxcYyMNHKr6XG/ENCKYrHgoYxErw0onI1Wa0LOpBg5jgcNqN6OTKsZCB0vASmQ4BhwZC5hdi+mmikNVn0YkaSeSI7WAVxe71Esuf/6xCS5ebVAJ8mvfiCQ3WgmTJYcDoWC+kfLGoxVemG3SWG7Q6aYIIRCOh9EK1/fIkqQ/Xy+JDUYrLMdBZxmu7ZClKcKxsd3chauwwHZASJJUIRwfSxiyNMPyQ7SUBKUQYwwKC5VJwOAFPrZtc6Mr+K2vZvzjv36oP86m3W6TpulNXfw39m3crTjKqEsYRskoLbuixm5ABLvhOj4ohLiw4d+/Yoz5lU3bGOA/CyEM8Mvrrx82xswDGGPmhRCH7vaD3Pd3wE79Me90pl3vi5amKTMzMywtLXH06NF+3Grz9sMUru9m6cGwkwwuXbrE2toaJ06c4OGHH84bRCvNi3MtvrnUZbEZ040NxobQ84gyRUcZWt2U8bLL5ZU8VnWk5nFlLcUzUA0MkxWX42Meryx2+fpCl2M1j1rgcKwe8NpSl+uN3Jo7XPNY7ebW3cMHSxyuesw1UtqxZLzkMrsWs9ROOTmRuwivNxPOHSoDsNRJmax4nDlUwgCuLZhZjThzsMxSO+Vo1aaxYvBci/NHSnz6yhzKgDKAzGN0EoEblsnSjFSDHZbzGJ4QOJYgS1Msx82vqxdiyQzbsclSiV+ukEQxwspr9FQUYYSF47pIpZHGAq1wXQfXd4liia012lh85AvTHD8xzt/6bx7h1Klv3zcb21U1m03m5+eJoghjDEEQ9AVQSjl0Kv1WjFLsRp3BOErL7k6u1YNo2cGuZGMubXBNbsefM8bMrQvaHwkhvjnqDwH7QOwmJib6dX2budOZdu12m4WFhX75wEZrZ6vthx0ltBvNnQd1kfZKI6IoolarcfbsWYQQdFLJV6YbvLbSJc4MUhmkEmRGkGkIDVgIar6Fb1toZTg3GRJlmrVIIpVGaTjgWkhAGMHBis/VlS5zjQTXtqj6NgdKLmtRhmMLDo8F1Ev5RPCyb1P2LSqeZrzqUfZtnnZqTC1HQG4hLnVSDFD1bZbaGafGQ7650OGhgyFPnxzjuekm1cDhteWIkxUL29IkUvOlr88is7zQPAjy4axGKYyUKAOu5+aWmSNQCIwG3ADX8cBodJJiDGgsxHqY2yDwy2W0Vnk8LywjswzhuvkTss4L123fpxulOG4+My9TBtuFX/z4yxjf48h4mTcdrnD+SLnfrqpWq91yv8RxTLvdptPpkGUZzz//fH9GW08Ee27RMAwHur/26lw8KCy7e4EQ9yYb0xgzt/7nDSHEx4C3AgtCiKPrVt1RYOtFfgju+zugXq9z6dKlLV8bdqZdu92m3W5z6dIlzpw5s2X5wGbudKbdIE+tdzrZfCu63S7Xrl2j0+lw+vRpGo0Ghw8fJpaKL1xtcnmlS6ry7iVKQ2YECoNtCSIFJWNoZYq1RsaJmk8zVYgMfNtisuxxbMzn6lKLV5ZTQtfiSNWj4lscrQXMNWI8O+9oUglcXphvcmUt5ZGDNok2XFrqcqDscrTqsZZZzN3o8viRMlIIEiEIA5vzxyt8Y75NM5IcGfO5vBSRSE0tcJhaTXjziRqPHioTy/x6TXcMz5yu8dxry6w24jx7UkAqDZAXZQvXxbFAGYHne2Rphuu7ZEkGBjINCJugXCKOUjzfI800YbVM1E0RlsEPfLK0i0bgBz5C5HE6lSVUqiXa3QzHdTFGo4RFEDho8knrH/mjb/Ej3/cmvjS1xnNzLQ5XXN5xqs546eav5cbhppOTk8zNzfHWt74VyK2W3ky31dVVZmZmiKL8ASEMw5vigpsnfI964sG9qosbZF/FlPLBeL2zMYUQZcAyxrTW//6Xgf8D+DjwI8D/tf7n79/tse57sdupP+YgN2xv+sDU1BQA1WqVkydPDtwIdthJCT0BHrXYbUen0+Hq1askScLp06eZmJhACMHVq1e5MNPkxetduqlCINDG5B1KtCFTGtuyyBBU1/sgHyg5TJZdljsZsdJ4FniezWoiqRibqmdhWYL5ZsYiGecOhVQDB8+zea2RcNxAPXSYKPsstFJasWQscAgdwXIn42DZZcyDrszjbxOl3PV0ZSXmkckSXWM4XfPwLYvLSxFLnZSjYz6vLkUoY1iKMo7XfI7WPG50MhKpWVlYywPvtg1aoIzCdRy0yQPyaSbzJ1rXxuh8npfjC2Qq85hemiFx8Eph3npaZhjh4ni5yydOJE4YIjOFFHl2qtGKUiWkE+XJL7lnKO9OkSQKxxVg21xf7vCfvniV7/7Oh0AZLi3HXFm9zuGKx5uPVnj04K2JT5utd9d1qdfrt9yvWmuiKOoLYW/Cd8/l3hO+LMuIooggCO5qgR+12I2yS0xh2Q2GEOTJW68vh4GPrd97DvAfjDF/KIT4CvAfhRA/CkwB/9PdHui+vwNuN+ZnO4wxLC0tMTU1RRAEPPLII1QqFS5fvjyylmF3u/2dzJLr0W63uXr1KlmWcfr0acbHx/uL2Vok+VIjxNNdlNYgLDKtyKTBsQXNRFL28mGpS+2UijBIqUkSTWBbTJZdJssujUSx0M5YiyRV36Zqw6GyzYl6yKWVmKlGypGqR9mzsYTheiuh7FmMlxwWmgk3Wim1wOZwzefqSkwzkgQ2WAJutFIOlj3GQ4e1WKK1YbLi883FiDcerfDsQ2NcXuhQWm8ZttxJGS97LHQzHp3wudHJWFnt0Iklji2Q2uC5DtK2UFKhVV4Ebzt2/m9tcFwbKTW+72E7Tj5sFtA6b3PmuDaWbZGkEmPAc/JOK8Ky8P18jJHSBplJ9HrWpzEGLIFt2SSpJAg8tDGAQCrD1y8v8oaHJjh7vE7gCKSG5W7Gf31tjU9dWuFtJ2o8fbSyfqzhXOA9a24zaZr2h5omScLLL79MkiQIIW4aalqpVCiVSgOJ2F6uixtG7B7Y7ikAiNdd7IwxrwG3TD02xiwDf3GUx7rvxe52kw82z7TTWrOwsMDMzEy/fGBjU+Z7NcB1FPsGaDabXL16FWPMlkXuX5vv8OWZFm1pU1UayxIopTEIHDu/0cu+iyUMY4FN6AYsrWbYwMGSw0pXcmlZMhbYVHybI1WPA2UHz7ZZaHYIjMAyuXtzNZKEbm69Han6zKwlrEYZk2WPg1WPxVZKJ1FUfAcB3GhnnCjDoarH9WZKLBUHKh5rsaQZSw6UXZY6Ga1E4VgCP3Ap+TYlz+Z6I+FNx6vcaKdgCeo+vPDKItoIBAZjDJlUCCFwXAecvC+nZ1ukArTS+YMIOhc3nb+nXCvRaSeEJZ8kySiVS3S7CWHo5eIVeqSZQjgWShu00tRqJdqdBD9wcxF1bKIoxQ+8/n4d18KzbJQ2fPLzV/gb736CyYqHbVksdTOOVjxSafjaXJuvzXc4XvV426kq44F91y42z/P6CVVSSp544gkg/250u91+bHBxcZFOp4PWebbq5tjgxnKJvSx2vdjmMDyIbsx83uPezM4dBfe92N1uWnlPvCzL2rZ8YKvtB6WXtTkouyV2a2trdLtdrl69ypkzZ25JclDa8IlvrrDQyZDryRNCQKo0thCgDe1EEXgWloC5VkqSak7WfRwbSr6DEFDxHOIsAwy+baEsg4fFcjejmVkoozjmuUxWXNqJZKGdEbo2Y4HLgpVbcxOhx5Gqh73uNin5NucOlVhopqQqo151ud5MWe5kHF+fUnCjlfLY4TJCwEIr5dyhEldWFNc7kqdP1nhuqtFfoOZbktW1NkmmsS2BwcYRudVlCbEeiBckcQZoXNclMxmWbVEqB0TdBNd31y00iyD0+1aeMhrPdzHra6GwHZx1q89oQWZSklThuE6exOI7dLspYeiRyXyAbOC7WELkrmLbIsk0/+VLV/med57lQGhT8x0SZRjz8+bXsVRcb6d86LkFjlZdStJH6TyeejdsTiqxLKtf/7cRYwxJkvRdogsLC3Q6HZIkwbbtvvWXJAntdntXyyXuBKXUUFPHH0Sh63EP3JivG/e92JXL5X5Afissy+LKlSs0Go1tywc24jgOcRxv+/pm7mVzZ2MMq6urXLt2Ddd1CYKAN77xjbcsNJ1U8dGXlvMGy+TN/S0haCUS17awHUEnUzRTBUJQ9S0eqgckytBMFKuZw/Jawplxn3roUPFtVmPJt5YiAsficMVlPHSIk4zVxLDalUyEDmcm8jhQybUIXJs3n6gx20xJjOFgyWU1VSzGilrZo1LymO8qsOFgzeNpP491+ZbgaNVjvpUitWGy4rHYzovGQ9disZ1ypOZzerJELDUHyi6L7YQbSxGOZSGNxhiD6zrYOrfulFQ4jo3vuyRJhu2A7dhopbEdFz/0cF0LtV50btsWCHLrLs6wbQvHsvNSDSlxndz9iYFKNaTbSfuB/jiReL6LWo9BeW4+VFYDvueQZhopDLOLHV69uszYGw6TKU3Vc7jRkRwuu6xKQ8UHI6CbaeaTMr/4pTnOHyrx5mMVDpTurARh0AQVIQRBEBAEAQcOHLjpNaUUnU6H69ev02q1ePXVV7csl9hYPD/I5xql4IyiTONBQIi8Oft+5b4Xu+0mH0RRxPT0NI1Gg+PHj+9YPrCRYRNO7mT7uxU7YwwrKytcu3YN3/c5d+4c5XKZixcv3vK0vtzN+L2XV3P3GQIwGCAyNjJRHCjZWEJQD11qnkMjUUw1UqJEcaLuM1lycZI2VljlWiMBBIfKznqvS4/ZRsJc0/DIgYDjVZvDFUGGA5ag6rnMrCXMNDPOjPt4tkWcKTqpoh46HCi5NGPFWiQ5XPEIHUFH2mQaEm2YbSScGQ84OhFyqB7gCsHBMiy2M5qx5EjN59pqjNSG5a6k4lk8crDEN68sk0mD1LnIxUlGlils2yIMXKRUKA2ul48ikpnC813SJOs3hU4SRVgJSKMMP3CJohTPy+N4tmORJhIv8MiS3CL0HIcsycgyjeM52JbAcWw6nRhhW5ApgsBFG4NrCeJUkUlJpeQhtcGyLf70xXkeO1mnVPJZaKccGwuYaSQcr3m0EkXZyyczpMai6lpcWY15fr7FqXrAwxMh5w+VCN3BXYlKqbu2wGzbplarEUURlmVx9uzZ/j0axzGdTod2u83c3Fy/bOJ25RL3enBrYdntT/aN2PVot9tcu3aNOI45dSofq1Kv1wf+Uu9mwgncXTnBxqSaUqnEG97whptalW0siAeYbiT84Str62n3BkyeVRllCiEsDpRcLMtiNcpT7au+w1hoUw8dkkyz0EmZaqSUhMMhW3ByzGe+mRJJTT1wOFa1OVh2uLqWstCVjLs2Uhvm2xmBa3G85nGw7NJOE5Y6GSfrAQcrHnPNlHaiGAttPFuw0s0zMQ+WPaYbCe1EUfXXE0+6GafGA76x0MGxBG+YLPH0SZuryxEnx3PX1Eo342jNZ2ot5lBJkXQThGXh2AKtDa5ro01+/bQB23NRUUaaaoLAIzIptmMRWB5Jsl5ikGQILFzXQa0nLaTriSm9BcG2IKwF+cDWRFEbC2m3ExzHQgiI44xSKSDNJGHoYgkLozVJpvE8G9u2kNqgelMXbIuP/Mlr/J2/+ji10CHKFEeruRgKDJ5jESV5wk1gC1ZjSdV3iFLNV+dafObVVd50pMyJMZ9zB0KC2wjfbo7k2VgucfDgwZu2lVL2RXCrcgnf98n+f/beLNay87rv/H3Tns5056piVZGUSEoiKVmWxLaMtjsW3EGnk8CdtIFWO4GBBmIgeekG8tAPBgykH4O2gQR20gjQNhowYLj94sB2yw7ioK2kZSdOpMi0RFMTp5rrVt35DHv6hn5Y+15RFEVWkUVLlLiAg4t7zrlnn7PvPt/61lr/oe85Pj7+NrrEW4n3kt29xXcJjfmXFu/6ZAcCv/53/+7fsb6+Doj7wGw2E7L0ALe+1/heAqicxqnw9NWrV5lMJt8GqjmNV1eCL+zXfPalE1AKjXDnhrET48xCK8/bW/UUVjMtNF1I3Jn3dD6xXVkuTnPOxcjJSY81mtzBY1slN046vr7fyvwo01TOsLfqcSjGDjZHlr2lZ94GprlhkmtOmkDdB6aF5dZJy91lx7Ss2BpJdbjspHIB2Fv2zArLONPM20BMia2R4+6yp4uJeRcpcyvVaG64u+g4d0HmTH/6lV1ilAUrBFnMjTOkBMFHvA8YIC8sbSNkeJcZ+qHySmQYIxQK3wec03R9YDwpWC07isLR9YFqlNO1AYhSuRHo+oDLLdZotFLE2BMBawxKK7o+kJKAAPLMsqx7rJWEao2IS9dNz2f+41X+ux99FJXiYHibMFqTYqKPMNKRZRfRQOUMTR84bDyXZzl3Fj17i47/5ysHfPhcxeVZziPrxeu2Or9b/nPWWmazGbPZ7NveT13X7O3tcXR0xLVr176NLvHq273SJe4XjfmDmuzg1ID5+zPe1ckuxsjv/d7vce3aNX7lV36FX/u1X2NjY+NbnuOce0c97d5KcrxXQEuMkb7v+cIXvsDa2hof+chH3tDj6zTZPX+n5k+uzkUHEmiDZLnMKHEG90JwnljFdC2jD8Kvy63i/esFtU9cPWpY+cjWyJG04trQwrwwcZwbOzrfcWvecWmWs1EaFq3noEnkWrh0hyvP3WXPKNNslJaTJrC/6rk4LdgcZdxddtTdNyu4vWXPdMNSmcjKQx8Tm6OMRdectT3vLntOmsBaKajMg9rz+M6IZSduCQTPncMGbTQhRsrCUbce30VJ1rkRv9ZB3zMvLF3ryQuH95Eg5Du8j4ynJU3do41BeZltTSaFAFX6gDaGPFcorWnbnum0YLHsMEaSUuMDWZnRt56isPR9EGpDH8gzx6rpyTJBVoYoZP7MKvqQePH6CS/eOOLSuQm5UXQ+MXaaeReZ5ZpVrWn7wIVpxkkT6GLioaECTClxa+V5fLPgqPHsr3r+w7U5CvjgdslmKVJuW5V74Mnu7c7FTukSp0T5U5QofJMusVwu2d/f58qVK/dMl3iPZ3dv8V5l9z0cv/qrv8pzzz3HM888wz/6R//o2xIdvDXAyXe7sjt1V7h+/Toxxu+IHH1taK358p2aL+9HMdtOsGgFiZob2F95DurAzljsa24sPCEFzo0dKcHNE1k8zo8dl2Y5N09arh93TBRcnGZcO+q4PSS4h9cyjpuAUlBlhg9sH90tRwAAIABJREFUlSyaFhUjs9IyeWhE4xMqBZxveXScQCdUbLk0MWyPKnJrKDPNJy5OaEKksJqNLFLXmuNGQC4gifD9GyVGKe4O5HOthKrwxHbJiwcNT+1UHB6sACUQ6syctTBVZoheqtssczRNj9aIhFcEZTTVKKdedRSlo228VMFKVOC1UrStaGZWhaXpPH0nwJVTMEVEZnTWGqFzJE/wgTy3WGNIStCf41FO3XjK3OKTeP8Vg4uEDwFnDQrFv/r8DX7urz3GMlmmmaENiUmuSTGwiJbHNnOuHrWsV5ax0cQEJ638Px5bzzlsPIU17DUdW1VGYTWvHDbcPG74o5c8hTOs60jhNPtmwdZIQEan1fX9xv0iHt8oXk895ZQucdq9OY1TusRpW/T16BJN05y1RL8b7hLvnvjL59n9Zca7Otn9g3/wD85+Pijng3dyBvdmzw8hcOvWLW7evMnW1hYf+9jHePbZZ+95x/xSnXH1pCN3Fh8TB6uewgkA5cpxxzS3vG/Dclh7+mS4MLEobZm3ntIaPrBVUfeRVR+YDAnscNWzaCylMzy2WXLlqGW/DpyfOKoEtxeePsJGZVkFxbw3qC6RqciNk56YEpcnJaPCcP2kIwbNVCcOVp42BbZsT0Kx1xvWcsU4t+y4jI3CsTGyfOTCiKsDCGV77Nid9/QhsTN27C5E23Kcab549ZD5oj/jDZ7y2wzSlkox0vciAJ3lUtEBGKvxfaQoHUWRkWWargt0nafIBS25tlZxfNJQllKRVaOcZtVjnQBWcmdou0CWW5nJdYHxKGO5EvBK08usr6qEk2etImmNCokiNzRdoCwM1somJCnR3vydP73Bz/7Xj6GAUabRJHbrxLnc8/Jhy8NrOTFJNbe76Lk4zSAlbi86ZoXjpPM8slay7DyHdc8os8NmJUMrmC+hR/G5K0f4CFuV46DuWSss58ayuaqcZlZYMqMorKF0msJqMqvI9TfRew9aeuxeK7FX0yXOvcoYN6VE13VnOrevpkucVpCvllJ7NV3iBzUZKsV7aMy3EyEEnnnmGS5evMhnPvMZAP7ZP/tn/PN//s+x1vI3/+bf5Bd/8Rff1jHW19cfmKfdO+179XrJLoTAjRs3uH37Njs7O99Cj3gt6OQ7xX+8vuClpaPIoQuJWwvP+XHGsg90PvLYRkFMkZgU5ycZB8c9+3VknAVKZ7h+3FE5zc5IhJlfPupkJpdb9laBGyeymJ6bOG7Ne46bwFphGGeRwyYwyjSzTDPvAnfmLRvOs1Fk3K0jbdJMc4PTcNxGtsYlWzpw46RDZSXTXLN/0HLSJTZNIiNwewmhb8QE0hhynXhkPUehOKp7NipJdseNZ2eS8exXdwnDgmuGdm3XBcIge2asAmWxWoHSkBJd66WSC36Y7ymaJlKNCmIYKAd9xEcoquxMXUMrzXRa0PlI9JFynNOdSPvUZpYQO+pWQCnWaDJnWNWSHLu+w1mpOovC0jQ9k3FG24tKjdYDBFwp7hw3fPbPb/LXP3GJ1keWPrBTam7XjkfWc+ERGsV+7Xl8s+TWScMoszircEZxbuS4etxybuzARxKCml12gYQiJLhVw/mxkPr7ELkwkc95sOpxRnFnGam7wCiztD6wv/LMSjmPdxbd2dx079iS7zVs797FR2mLTwuD1SJ+XTlJlAkRHCidxmoorKGwmsIqSmfIrX4guphKKfI8J89zsizjySef/Jbv22lLdD6ff4u7xHg85uMf//jbOva7Od6r7N5G/PIv/zJPPvkkJycnAHz2s5/ld3/3d/nSl75Enuff0bHgfuKN3MoftIHr241XJzvvPdevX2d3d/cNLYTeTDLsj6/M+epejdOw7BNzH7g8zVj1gfVCFqbDuh9mVfDyUceaE/j63TpyfmL40E5J00eMgodnOas+UPtEZhQbtmfPZ+ytPFuVAE72V57SarYqy6JtubvsmemekU7Mo0PnFSOr2asb9leCGtyoHLfn4l83zg2KxEHtWSuLM3WUqAzb0xGLgwZvMtZzjWo9t5aBnb6jT4aR8hjvGVu4u+jwKtL5JHY7StH7hCGRD0T4tgsYbbBW0TQ9xkBRZig1aFdqTVP3lJXD14J2XHUJl2mMkb/JnMFYI2LSXSA5jTGaoCOLVU9RZqQYWdU9RZXJvG+gGMSYGI9zVrVnOs7pfCTLNG3jGY0k0YUQyZwkxhDTAGzRfOXaCVtrezzz/k26AAuf2LSRRRvoQ2LNGs6PHC8fNFyaZviUmOYZN0+kgrk4yQgpcW6csWg914bkt7voydE8MtFgJLkqBfPG46zGKMWN4xZnNWuF5e6qIyXFhWnOvAssG8+FSY5WIj+nVaSwisPaE1OidJr9lbhOFFZz1AT6EDBaoRH5Nq2VCG6HhDMyr+xCwARpM7u9W6xXjpHTWKNZy4XjOc4Ns0E5583i9eS/TukS38ld4gc23pvZvfW4fv06v//7v88v/MIv8E/+yT8B4F/8i3/Bz//8z58BLXZ23rYn3wP3tLvfuF+Pur7vefnll7l79y4XLlzgmWee+Y472Tdzbvijl054+bChsJrbQex1Lk8dfYisD0CRky5yYeK4edKxNbI8vZ1zMK8xGi5NHVdPejZKwyQzvHJW4Vnmq46DBtac4fLIUQdZgN+/nlP7JLMxFblURRadyG3NdGRRy3zw8ixjs7LsrTx1HxhnBug5WPVMCsN6JaLSrY9MMsPesqcOmk2tsBqO6sD2OGejhIPaU4zGbGeR3YVillvOa49KkX/75X0RadaK4AcYv9YoBgkkI4jKsrDkuaVtBwqB0XRtoKpkZmmMwZrAauDWtW1kPM6pVwIyWax6ysqikiiktK1nMsmZLwRwlBcOHzq8j1LVaUFYeh9o+4A1ioAISPc+Mhk76i4RQqIsHSkpOh9x9pvttJAUn//6PhuTnA+dn7BsewiKLsFDU8eVo5ZpYaWlGSMKuHrccnmWiy3RQLd45bDl/NixWSpigkfXcg6OF7TBUFnFnWVHTLA9chw1ntYndiYZjY8c1D1bVYbVYtpbWsVmmdH4RBsS66VlHhJtAGdlhtv2iS5GKivV3KoLOKMwKNpTeToUPkW0GqpZnaiMpV52dFFhM9hf9twIgUwbjAYfE0YpuhAprBEUa4ysVxkPTXM+cfFb1V/uB5xyWg3+wLYxUdjv4zbmO/rJ/uE//If84i/+4rcgvr7+9a/zuc99jk9+8pP8xE/8BJ///Off9nE2NjYeaLI7NTe9n+ffS8Lruo5r165xdHRElmU888wzXL58+Q1bNt9pxpdS4l9944iXDhtKZ9ivPWjFZiFyWIXVvHTYYozm/ETUSN63kXO48txaeIxW3GmEjvDUVs5WaSms4n1rGcs+ctQEzo0zYoJ5tFSZcOiunvS0UdH4xNUTz915R1EW9LZkgaPILY+s52yNHFVmuLyW8+ROxVplmZWWxzdLqszQ+ch0QGIeN4HMaDKjWEVpQW5UbpDKikwHJ/KTV/HvTrrEbFzy/G5D04OzBqMVWW7JBqpB10d6H0WHMjMkoMgNeWZoWk+eyyLY+4jSirYLlOOcqnJn/5OYwDgtWRPwPqGdEQFtoPeJvLBYq1nVnrLKSEmuidZH+j4wGWXECMYZIZ0bQ5EZfBIe4LhyhDgkZjfMwOTCQutE6xP//i922V10KMBoxUZpuHrc8eh6QWE1icR+7dEaHl0vOFj1oIRa4mPisY2CzGrGuSHFyJWjVjYHCW4vOrZHGdsjR+MTW2XGwzORcxtnhkvTnEyLxuissIydISSRi1sb/jchKUaZtCrrPhJSYjxcM/PWkxmN1ZrjNtAG6RjUXgQGtFaEGGl8JCWRPbBGIVhiKIxGa2j6eIYwTkkSX90H2ghGKT587tvpOO8hMe89TtGYD/L2vRTvWLL7zGc+w87ODp/4xCe+5X7vPYeHh/zpn/4pv/RLv8SnP/3pt600/kbOB/fj4H0aD5pr17Yt3/jGN3j22WfPBuIXL168Z0WX177/ECO//fwh14Yq7O6qwxnFWiZJ0MfIy8c9j2/kjDOFQrPoIq8cdVxay9ishMx9oYC7K8+iTzQhceVYwCKPrWWsl4ZRpnn/ekafFMs+sj0SrcY785bUrbAKlsmSOcdmafERugjj3DDvE7eXnojipItcO/G0EfLMELUmac3mOOOp8yMeWsuZlIYntipGJrHy8SypHdWyUBol5HGtYOQ0J62c7zt7C5KSaiWiRLZLSdIbjTKZz6EpCocP0HSJvMzIMofSmvE4x/tAOSS+lMAHyJ14z9WNxzpD5xOjSU4I4n7urGE6HvQuUWc6lQpNkUsFWRUZZW5ZNZE8F3mxUZXJbM5quj4yGhJd5iQZxwjaKIrMkFIihEEWbhX44+fuYjXMg6AvL02lHXm6+D+ylrO/8tR9pHDy94+u56QUORjaizfmImV2cSaoxLVC8/BajgIKq5nlmrr3UqVpUbyZt+FsDlr3gaQgtwZUoh80Oh2isdqHRGE1o0zT+ETj45nQ98GywWnFODMse6GLTAtLHwQUJST4SO0ZEl2iD4EgxhEibTf8r61RGAVGaf7q42v8jQ9tyHt6TbznZXd/YbR6oLfvpXjHtjx/8id/wu/93u/xB3/wBzRNw8nJCT/7sz/LpUuX+Omf/mmUUvzIj/wIWmv29vbY3t5+y8d6qzY/3ylOk929wP1f/fzXfqmapuHq1ascHx9z+fLlMymlmzdv3vN7eW0bc9UHfuerhxw1gfWBe1Y6S+UUdRNYhYQm8cGNnL3GM8kMu8uey1PHZmG4tezZqhw3W8XMKZ7YzAZ1EZhkmtuLnkdmGXurnl3veXiWsZFBrhOmr9k2gaOUk1djdoCbc3EhmGSGvRrmXrOmxNH8pI30MTHNhSM2bwMblROgyvD++wR3l57zY0fhDK4s0VazOcqGahKsVmyPZd7X+MhG5Vget3zp5YMzdRFjDX3vyTJD1wd0lDZl5uR3a4Q2sBrsgqzVUsmVliyzaKNxTtO2gap0rBr5iVJkp69tNW4sCMi2k8dNF4Sg3gUm45y6CVTD7yEkZpOM43mHtQbvE00XGJWOZRuEFqHF+zyEiDWKzBmaNtBFeR2lxWfQasWNwxX/7/N3+RtPb3C38VwYZ2yUYJXiqPUs+sDDa9K+BEG8HreB7SrjpPUUVjRPl51s5BSJW8vItAhUznB73pFZQV8eN579PrJZyQbn1kkrc7PCsuwCqy6wVjlyo+lDFH9AraiM8AbrPqAVogTTxQFUlOE0ND5RGE1mNT6KWPfEWvEXjIpMJ5zV9BGslrlp75OcB6NJKRLRXJjl/ORja+RvoNT/XmV376GQ79r3a7xjld0//sf/mOvXr/PKK6/wW7/1W/zkT/4kv/Ebv8Hf/tt/mz/6oz8CpKXZdd23yQndb7yZzc/9xtulE9R1zVe/+lWee+451tbWeOaZZzh//ry0YO6x5fl6r7237PmXXznksBHgyXEjlIGRU8QIi15RGdgoDDfmPaXR9CHxgY2MGyc9XRJiuVFwqVKceNmJHzeB24ueS1PHo2uORR/YGqq4/bqnoOewSyzI2d6YUVpNbhRbpeHRmbS+ULCWK3xStCExzb7ZepQWliS4lBJr5aDm30eqQdLquA1nFcK8jbQx0SfFraWnS7AzyXl8q2JWOrZGjkInXt6dY7QZWo7CV1NaYY2h60UAuiwMo9IOSiqaqtD0XSAb3l8Moku5aoQuMB1nqOEL74PoiVqrMEaxrD1tHwbBXMV81YvIc0ii2mIEtOKcJs8tWaZZ1J7xSCgFRWEHfl1CaxiVlt6Lt502GmsNq0be22SU0fpIMxjrdjERUbx4e8V/ulZzeQAROaO5W3suTDImmWbRBlofhw1ExrmRHG+SG24tOo5aSdrS9tZcmloKI3XU5TVRWlEIDeHhtRw78AwvzQo2Sstx3ZMSbI1EjOD6UYNPoFU8O2cxSXVXOsOqi8ybnnOTHGfkc+QWcqtlbopcj0oBKiGYlYhWIvemtDpr3WZWy3nWmv/q0Sl//YMbb5jo4P5EoH+wvewY2ubvtTEfWPy9v/f3eOmll/jwhz/Mz/zMz/Drv/7rb7tt8GbJ7n5ncG+1jblarXj++ed5/vnn2dra4hOf+AQ7Oztv6/OdqqJ85W7NH754wrINzHIz7JwVI6dISDtyuxIbm5UXL7rKKXyMXDnueXQ9E2TlkAhXQXGhiORGs1FIC2136dFKseoimYKLuafpA0lp1nNNE8BHcSzfrwONT2RG44yiMPDQyHI+94Qo6LrcwEkru/6NIcHVr0pwR4MvXeUUdR/xMVFqSeyrXlB8AEeNxxrNvA9cOe6ISrF/3JydG2ektdt0kjDz3DCdSHuw90mqPR/p+4jLHcbJQro2yfAhUg0tzBih6RNWa9Ym0qIcl45lE5lOckBRFo7OJ2ZT+d1ZqR6L3AxVoWXVeuHaVdIZSEr+R3XjZVYXEqPKsWo8VWHJrBZ0ZhcYlQZtFKs2MCosuRMqRWG16Jsq+OJLB7x8Z46PidwoJpnm5rxj5AyVM8wKy8gpbi46tNbMG08fE4+u5cxyQ240l6c5KSVqL4lp3vbcmneEGOlDYHfR0ni5PqyS85tbzcVpzkblpCJTcGGaQ0osyQgJnBHag9KKZqjuticZPsr8NDcGO4CHSIn+dFiZYNkJmV8naY/2Xq6PmKDzkvQnueF/+PAWT5/7dlPa14u3oov5g9rGPN1UvNfGfBvxqU99ik996lOAKCH8xm/8xgN9/fF4zHK5/I6Pv9W25L1GjJEXXngBgEcfffRbXMFfL+7ny5SU4d/fDqxYkRDZK42ijbBWaFJS3F30vG8t48ZJR2WgzKQ1dmPheWjsmOXS0nJGkHEf3Mx58bCjNJIkq0zxgY2c6/OeEBOFTtxYes4VjolSFCkxKgzzLrBfey6MLId14KAOXJg4rILdZeChsUVpRxelJfqBzYJmaD+NM8OdpeeoCVycSiJeDQluVjhWfceqj7ihQjhqPNM8Z5Jr5q08b71w3Fp07M1bdg9rgecPc5oiFx++Ze3RWuGsoswNdRswPlEO87cUE7mzrJrAdOREB9NoRpWjbjzTccZ82TMZOWaT7EykOcbEZCzzNpAkOhtnxJhYtYHZxHF80mGtpjKOtg1S1VWCjHVOU+WGRePJnLzXyUjapeVALJ+O3LCwR/JBSsxaMFqfVUx9ktzwr760y9/55CVuLxGpsDAgYo3i1qLjwjhjLYnDxfmx4+aiJ8bEKDPcXnSUTlOqSBcShyGwOcqo+8hhHcQ9fmI5qnuOG8+scFgNB6uOzGgmuWWaW2JKrPpIHxKlkuTX+IgdZtGlMyQSR6uezGnxREwQSPQ+sep6xoMTROMT5QAyWkRpYxqtB8AKlJnl0tC21Pfx/XmvjXnvcYpc/n6N74tPprUmDUoSrxfvlN7lfD7ny1/+MsfHx2xsbPDxj3+cjY2Ne0pm99IyuXHS8rk9y+1adCvvriJrheGg8cwyg0ZxZyn2OdfnPVuVxmiwCu6sAk9s5OzVIhdWZoatylD7yN06sF1K++jCxLLoBBSSqYhvlmwUAIo6GTYqx4KMPsHDa46LEwcKNkoju++B4pAQMnuhJRnMu4hWioMmsOjlfT+5lfO+9ZyR0zw0zTFKIOmFlfN11HgUMM3NwLmKTIeqa94GCicVwRdf3Ccm2TmGKBSIoTigzKVqs1pTlYb1SUaWGarCMhlZcSfPBq+5QVB61XhGhWU2yUCKJ9ou0HtZdCeVk6SpZKY2G2cyk0uJPDM4q1msetZnOV0fqZvA2kQ2Vs4oCmcIXhIeyPH7IHO/Ijf0IZJnGqXl/jI3ZFbEqGOSKs85RZ4ZcqdFVDrAb3/xNjmBu6v+rG20VlhmubidKyWE86VPXJ7lTHIhbV+e5QMNBM6NM6a5JNNpJrZNhVU4rTg3zrg0zbBaKu1p4Sgzw8Gq46jpQQnYZGtk5Vgr4XKeVXdKWteFM4wzQQSjoPOJNgSmxbD5TOJNKElMroU+nH6fBaH5Y4/M+KuPr99XooP3kt39hlbqgd6+l0IDqNdZnZVS029/+vdmvFlyedDoyuPjY/78z/+cl156iYcffpiLFy++oUDza+PNTFnrPvBvXjzmc1eXdEExspEbJx0PzxwHjWe9sGRWsbvyvH8958ZJx6WpQ6AaUAe4NLVcOe64MLZAonKa63N5vlYyiD4Ohhhh23n26sA0g5UpwWY8vpahEfCDUYmjNpEPs55FJ8jMy1PHvJN2owKOu4gm4TScdJGEVHg+irCz1rIINwPtYGdkWS8tG6Xlqe2ShyaZJLsBzr7oIrlVQlxuPIqEb1tOao82IlVlnSYkIAkq0FhDmYvax7IR5GDbBxZ1T+YsEWnV7KwXMlsbFv2mD/gQ8TGwvV7gw1ANdpGqkNfURtN0QagMTlNkUqlNh5mcVopRacmc5mTVsz7JBv1LmI0zlk1gNpFqcFRYityg1FAF5U4kxwYCtbNCXVAqUZWWEEWgOgEqyWxr0Xj+5RfvUCmprpyC24ueSWbZLC1WKc6PHLWPLAfY/u6yZ97JrK+3BYeNKOig4Paypx4qs0XruXEi1XZpNWuFzGlTSkxLx6SwrDpP7YOgI1Xk/FSurS6IW0PnI5UTV4x0ai/lAzFJ4lRKKAMohQ/y//Mx4hODL5/CasNPP73FE1vfTiu4l3jP3ufeQyklG8UHePteitPK7reUUj/zmgT3T+9Vnf97Iay139Hd4EFVdoeHh/zZn/0ZV69e5f3vfz8f/ehHmc1mD0xPsw+R/3Rjwe9+7YhrJx2ZAa8gRNGC7APMckvhpKJ7ZJpxa9BE7MJgBQNolThqIpcmjrpPHNaB3AjM/Paip7Qap2FMx34j4sPnRwbjMtYKw3ErvDOfEpmBdetJQOsT64WljxCG9lLhFONMcWmW4SMEYDYkqzYkRkMVtewi+XDxn7R+0Hs0HLcCQbdG0fhIWRbsjCxPbOScG4lSxlPbJe9bL3BGc/XuAmsGwjgKZzS502SZpfeRthP3gjK3hJDoepm7paE9OCotdReIyBxKKdhey+l9pCpkzpcUTMdusHuRpIIW/zprFMtaFFXi8HjTezam0kpcNp7paBAbVmLnE4dyUSlJtEVuafuAsxYfIpuTglUbyHMj8HqjWDQBZzXOGXofyYwiH85lUoo+CifquOn4rc/fkuRaOUZWcdTI7PLuqqcLcGHsqKymtIZLk4xqaKNWoWaWyQZplhsuTx2TTCqsWem4NJPranfZ0/Sy6y+tpjCazourvRs4cAYhxx/XHqeFIlBlBqsV3XCeuxCxSjHOLIlvnruU4oDMTGilZEaY4MIk43/8oW023qITO7yX7O4nvt9ndqfJ7ing54FfUEo9M9z30e+kN/m9GA9SMuzVzz91Bf/iF7/IzZs3eeKJJ/jIRz7CZDI5e/7bdUqo+8B/uDbnt79yyNf2GqyGkTMc1J7NQtEkI/JJRgi3jY+cGzsOm8D5kRtafmIDs0yWyhqmuSEhQIGLQ1Kc5YaN0qBCz34ryMztynASNEYrjpvAdmlxWnHSBjZKx+4qkBnDQyW0IVI6uYCP28B4qNqOO0lqD00shU5nLbKTNuC0LF7zThbHWW4IAyH4VO5p1UeyAYLfIar/Wiv2ayEgG604aT3PXtlnOXC+QkpYK0okvZeWV1VYZmNH5iQBbkwzSSBWsznLKTJp4ykFTes5P5MkkznDqHQ4K7vRRd2LFFhMbM1yQoRJ6ai7wOZaAQiNIaGYjDLxCgScM1ijWTQ9s5Hw+nxIzEaOVRuZVBmrxr+qagysjRzLzjMqxd08c4pVE8izwVPPJ8aFBS3cOmcF8WmUcM8ybVi2kd959jYv311Q6MQk0zit2SwNi05c2VOCO8uexosCycHKE2xB5qwktEXP0gv6tO4DeytBXe6MHZemGUbD3kpMd5VKTAvHNBcR8ZNG5qSZVWyNHbINEr7nqhdZuQS44TmJBAM9IbcGZwwkWWh9kGr2ye2Sv/aBDdzbnCF57+8LjfmDnOzgu9PGVEr9t0qprymlXlBK/fw79tmGn0fAXwVuA/+bUuqnAL1YLN6p4z7weCOu3VvxtOv7nr29Pb74xS9y+/ZtPvShD/H0008zHo9f9/lvpbK7ftzxhy8e8TtfPeLFwxanZTZ3sPLkVpEZRR8VlY44pTmoA8WwCIcI64VUF32IrBeGO3VkTXfUg9agNVAYxe1lzyMzx+1Fz3JV44xiu9SsdEHlNOfHDqc1SikO2sDOyDDJzdksrUajBwSdSEUZoRsMv6/6iEYSUJ9VlE7x2HrG+cE6aDYQxFsfzxLcspNqRSPzuARMCknQXRBtRYbHjFboFLiyV4uTgRYEpEJR5pZymPElpEXc+ciikeSaEsxrD4hOZR8Sn3xsnY9ennFpLRcljzZwbpJxsvJDUhQUZEzgk2J9mg9VoDx3fZqLB+CQiEelGLY2XWBzmnFqlZJlkpR8lIoQBevTnMxq0tD21INR7KlMWN1FilySJgmqXGajKIHcpyQtaWeNkOgT+AStD/zBX+xx67imbVoOak+9WlHREroWmzwbhZxvoxQ7I4dOYoy7VlgujDPGQzt6mhu2Kse8D9yed9S9kPwvTvNB87KXTYeC9dIxdnLtOKOovXArlVJ0fWS9HM7H6cWfBF3ZhjAAWE5nKZIcy8zwfrvkRx/+VmPXtxp93783s7vHOAWoPMjbmx9TGeD/AP46UnT9HaXUU2/8V28tTt/NAng8pfRPgV8Cfgp47FSC693AP3lQlV1KiePjY+7evcve3h5PPfUUTz31FFVVfce/uR9e3u6i4+t1xe++sOSPr56cJbbEKSdNUTpNG6TycUYeW3RSxe0uxIKFoQ3UBqEZ3F55Hp46apUxzqR6OWwCuQGnIweLmo08Ma1yjoMhM5qKnnkfWfQyC7o4Fc5cZjXHXSDTivMjQ59k0UYp9pvAWqG5PM1oQjpTOmmC6Fs0PsBgAAAgAElEQVQCdEHIwCsfcRbOTSyPDnY0Vovo8KIT1+7JQHvoQqKyp7M6AYOUVlqbISa+cuPkrB3YhwCD7mNCEJlFJtw6H6RtmTt1NhsDaLrAkxfGtD4ybwKvHNQ8f3vJJx9b58IsZ2MkYAmthMRttKA5l7VskrTRzMYZnRf9yTwzjCsn4BFrBm1NxbzxrI1lVteHxPpE3Alm4wwfEvOVJxtak+sTx6IRAFHhRBzZGIU2ihCENxiBIpPnV5kk+XkX6YOopGTDfUpruhD5N187YtEnCqsItmRUlgQsJ17RNS11XXPQBOarBpsCi8azNzjAJxSrPoh8m1Zsl44Lkxwf41lVWGWWc+Ocwhn6GLFaUftE1OLkYJW0pxWKcWHRwyQ5DK1qH+VaK6xQMJzWwxwSxs7w3zw2ZSe/943jm8V7AJV7j1MloL/kNuaPAC+klF5KKXXAbwF/6534fKfJ7t8Ct5RSnwaupJT+PvC/npK93w2l/du1+Ukpcfv2bb7whS+wWCwYj8d86EMfoizffDD+Rm3MEBNXjlo++9Ix//eX9/ijl044CgZRM1Q0g/daaWV37KO0ATNxoWHZJzIlraNFH7g4dWcggjjs8u+uAg9PM/brQE5AAwd1YMN49prImoVRUVDmOQHDxbHlsEsUGtYLy1puBT0JnB8ZTtogiL4mMMoMGy5QB1gbWpBKaVZ9wGiYZmLdc9KK0C8pMe8Cg0EAi07mMN1QGc1yzRNbBQ9NRY3/NMEth7/RRFan2ooDEvPrt084WHqs0igUuTPY4XzpYRZWZIbJ0NL1MVEVYlXU+chD6znv2yrZHDk+/NCYF++ueP9WRR/hYOXZnbckEp94ZMbBoueRrYrjVc9sZBmXwoNrukhmDdPKobRi2Xhyp2WuZgVFuTaWlqdQH4R/uOqEW9eHxLRyTEeOug9MS0vTR9bHGWVmyJzMHPNM9DOrQgxdjdEsm8DGJKMNUsVXuaHMrAgqR2lnhqSkBekTv/vcHi/uLtgZOZy1bIwyKqsJtmA2GTHJNME4ktJUypPHltVyzmJ+gulqXOo5XPXsLntCjKyX4k6vVGLedIC4E8SYRD/TKTIlG5lqMM1FyblXSip1cWGX61alREK6DyHKdTcrLX/rqS0mTj/Q5BRCuC+7oAfl3P6uDPWOaGNuKaW+8Krb33/NUS8C1171+/XhvgceFiCl9L8DKKV+CZgBv5pS+lXg/3wnDvpOxBu1Md8o2cUY2d3d5dq1a2xsbPBDP/RDWGt59tln7/nYr21jLlrPK8cdrxy2HNQ9mTHoAZzQ+Uhk0PdTop4RUiIbYONxIPoaLRqQnVc0wbBTyOIWkgzvZxkctyL5dGFiOWw8k9xQB2n9jf2SQzXm4tiyV4NNUA0Q8twaNgvNotEcNp7tUpTv9+vARmlYL+yQqDwrH0lKHq8yqfjmnXCxDpuAT+KHxmDbkuHxSQjGk0xz0gm6bpQZjoYZXGY17eBMvlYYRlkuTt8aZqqndyVdEPSn73uev7UAJcaSTR/QyOzHaNF/bDrRTywzQ5UbVm1AoRmXlkXtWa8KTurAf7xywkcvTtgcZxSZ5kPnRnz9zpKPXJzw5ZsLfujimB++PKX14m23aAIMyMciMxyvOkYDfD9khpNVz6R0tJ0HJYjO6ZBwex9YG2UcLjrGpaXvA6tOHMpTgjyzhM6z6gKjXHO88mxNc45WMu9LAFqxajwbk4x547Fa4awZEp6GoAkpQZLzcTojiQn+/ZVjdhcdn3zfJrnVTHLHSeNZdZFpYXEmcpwqotVMKz0INgcCMDEJH3r6EDleaXoUZexQxmC0bOwmmaELUr1qBR4LCpatZ5zJHLK0In6QOyH1O6MJQRK4D2EA8Sie2K74xEWZgS+bt+9l99p4N2zWvxdCIXPVBxx7KaVn3uDx1zvgO9JKtABKKZdS6oHPAQfDfUUI4V2z07nfZBdj5NatW9y4cYPNzU1++Id/+Ix0nlK6L8UVYwxHrRioXjluqQdot9IMBNs0vK4ios6U250RXlxCwB9WK3KjUVZaeVZJNXXYS8KIKLQWObDdhWdnJJD02suMK/meoC1T45nrMedKQx0Sm6VDETloIg/PHDcXns1SU6hIWVr2msD5kWFvJYoV+01gozBslZaDxrNmE/NoKElcnjhuzj1rhXyGeRfYLC37TWCaa0aqY6GyQQpMkt2qD8yGKm3RRbadHjQSIzGZoYXrWSusQNqVoAXXCsP1/eUZJDrGxCi39DHR9KI9WeXSTkyJwTVcwClxAMA8sVly3AQurOXcXXRcPWrYGDn+87U5P3xxwpMPTXCDcPE37qw4P83YX/X8+GNr/PGLR2xNMw4WPTuznP2TliK3HC17dqYZu8fCjwtJUKP7i54ik9mcQmgJVWFltmc1pVXM68DmNOd42eGcocgUyzayPnacND2TymG0bIaWtRz3YOmpMjl/IQnStOkFrZkpmVHaqEhaAEy51YQQeXm/5rDe5UcfmXJhbcS0MJw0gaPGM8k01jcoWwFKzFOtZtUnFm0PKmNtbJkpqb7q3pJiIobASRuxqxU9Bp0CoNAp0raGchAur4bWa5mdJrrBZ/CUG4nGasUnL0+5vFacfZfutxJ7Lx5cnKKF/5LjOnD5Vb9fAu5dPPg+4rRf8EGl1Hng/wP2AVJKDUhSeDdI6GxsbHDjxo3XfezVyS6EwM2bN7l16xbb29t87GMf+za01r1+1jvLnhf2W145rNlfVqzvN2ftGT0sWCEGUd4fHKidBrQiJkmmVkul1qfTWVcaVCpkvhGQBOk0gwlmxOrEpanj7tKzVhh85+n7lmByitTQmTGzgZQ81moAOCgKC4dt4NzIsuojnS3YsGqo4iIjp0W4OdMcd5Ht0rCjLU0nZqgnbWSrsuyMLXGo3Ba9zNEyLUTywjmKzAw6hjLDqX1irVBUTg8tSrGOOWwCXRAZKlqxe8lUosoUyy7x3PVjjpsoTgCDl1lCUKQuF+WNReNxRpE5ESRetdIubHvP/rLnwjTn1smK2kc++b6ZgGkGnuErBw1rleWFvRU/+siU64ct08py9ahld9HzxE7BwUoqqsNlRzVU3s4oDpY9m5OcZdvjQ6INilklm4+2j2xNHHdPesrB5sb7eDaTC1FangKqGe5LisJZGCgdi2H2d7jyMtccwDY6CrWkKgyrNlI4zSg3Z8a7mTUi6DvMEeeN59++eMjT2z0/9vgGW5WjS4l2sBqaFXItHNWB3GrGmaZyons5bzw+wnrlsNqgDLg8o0qJmL7Jqeualrpt8b3Hh5reRwLimoC2olKjDcbYYdunWK8sf+XR2bcZsD7IGdv9Yg3eDevcOx3fBQGVzwNPKKXeB9wAfgb4u+/EgU6vqkeBXwbuAP9ZKfUscPTCCy/w2GOPAd/7sNw3M3Dt+54rV65w+/Ztzp8//7qu4PcS8zbw3J0V14470Y1EiLZC9BVwA8iCllJCadEWPBUXli+gJiUBaEgVIAkuxURKsnvXSjQLrZZ250kXKa1iqzLMW1ElKXVkuViRZxmdqzhXWe4uFCOrKQfV+LmPbOSa3TpyYWS5uxJNzUluiN2Ku3XFpYljd+nZLA3HrZDWl97TD1VjoRWawArZFDRenBXWcsuyF+DCKNMctdLyLKwkwY3CcHmmOag9fUhUzrDqv+leDYFlFykqQX42PmHRlEazW6947vaCBOSZxodIkQkJvu4EXZlZxbRyhCBo0EkhvDVIbJdw0GpeOWj44Pkxf3FrwcbIsTtvaXtJfPtLTzaIIF85all2nvVxxtMXxnxld8mTOxV13/HQRs71g5YiMxytenbWCm4dNig9KKpUmv1Fz1rlMFaUQw6WPRuTjFUreo9rlWV/0bM1yThaSYtwVFiOV4H1keOk9mcItmXrmZSWZeOZFE6AOQgPc5RrugC+i6xVMv8LSVHl0io/lRSzQ/cgpAQBvrS74KWjFX/lfRs8vDEikYgmpxtARuNc0/SJo1pk5UaZHjQwRe0kNzIP7IKnMIa691SZw4fhGreOsipQqRo2JQnfBzof6LuOpq/xQebJF4rE46OMk4OOMFhenXaQHmRld7+v9W4A4r2T8Q61Md8wUkpeKfU/A/8aMMD/lVL6i3fiWKczu88An1FK/V3gV5DN5eQ3f/M3Wa1WfOxjH+PTn/70O3H8BxbfCY3pvef69essFgvOnTv3hq7gr43TBB9i4qt7DS8cNBzV/RmQRC4Mac0oBT5IS0cNXp/ivizPiYmhNZoGEVwBFij4pjDuAE/3A0EcRB3eJTEwnbeBuo/oFOhWDXnmqCYTFm3kwthytw44ekYupw2R2kc2C7n/oZHlzkqAJ42PksRSxANtEKFmUb5QLPvAucFhfKO0nLSKkQpErVh2kXFmWHSCjNipDG08bddGvLZkRkEvs8dxprHaMHIC2Fi0gsSsnD5LcCEmRs7QeI9XGmLguZtzfIAQxf3aRzkfhdM4K+Tv1cD5cs6wqD3GCGH5aNWTDHxgp+KgDoxzw8cvTfjG3or3b5Z86eaC3UXPwVIS1Cfft8YXrp7w4QtjvnRzzkcvTvjY5RlHy5aYFG2f2JmKC4FRiqNlx84sZ9F40b00hlnl8CkJjWGWcftIrGumlehrnjTCqVu0gSq3GJU4aQLnZjl7c5nrGZKgWgvhvo0KJ23uqGj7wLR0rLqAIrFWOeaNzMPUcA2GJJVWlWkya4iD5BpJobVm2UX+8Gv7XFhb8F8+MiWPns6X+GE+mhnFZiUV83HjRXi5tOgIKKgyhY+Cph0rmStWznDSe4wGgwgRKI0c0xhya8iyjCLBtLD8FxfHuNixXC5ZLBbs7u6yWq1IKVEU0s7UWnN8fMxoNHpbVd57Xnb3F99cr/5yI6X0B8AfvNPHOZ3Z6ZRSROZ1n00p/S9KqQ9//vOf/58+85nP8HM/93Pf88nutc4Hfd9z7do19vb2eOihh6iqisuXL7/BK3xrGGPYX7b8+W7LjbnAz2XBHbhKWpQjQoCI2K8k1NDChBAkUQ4UKb6ZFIUz5n1A0qA8dmpWqZK0NhUioeRTIg673kJF2tWKLMuYTCbMu8jYKKohkW2UlkUvPKc2wFZpOWqFgzdvI1ulHZRHEiMHR3rChcpwdxmYZHpY8ETqy2rhYp3udr12TDONT9/c/dV9oLCSPAujGDvFqhfYudNi9TNO4DQs+siWc2xWYsOTaY2pFLfmHc0Aq9dAj+E/vHws5GejMQORfpQ7+phYdR6lFLk15FZatFYn1keW40Z81p7Yqfj6nRVHjVQk//n6nI88NB5UXxQ/8siUL91c8sFzI758c0GZGc5NM5zVbI0sz+8ueXi9xAMfXFd87dhzeb1g1XecW8u5ddSKG3xm2Mgydk86NgZQidWRu/OerUl+ZoezPcmYt4HMikKKj4mQFLkVIeXZSGTStILYe3SmscQBrZhEZWWccVz35FbcwFfDPMxpuRYXbSCzmulAVg8xnulyRqTLoI0ZvOk6fue5fXYqzTMPK7YnFUqJI4XMkSXpCX8vUljFsg3kTjQ0tZHWu9OimJPpROelqlQIipiUSERiVOTG8MHtkse3Tp0KMsbjMefOnTv7vqWUqOuaK1euUNc1V69eZblcEkIgz3NGoxHj8ZjxeMxoNLonUff3aAf3F7Lx/v5N9qeV3SkaYw48o5T674Efe/rpp/mpn/opfvzHf/y79gbvNU7bmG3bcu3aNQ4ODrh06RLPPPMMWmtu3bp1z681bwNfXE35s68dyw45xoGgnMgG3psi0nvO9P1USmdgk+7MvRqUSmcJRq4jdeaGnUAqPAZQg5JEqrTCAgNFjD4lFvMF1jlcOZKF1on802HjKZ1muxTek9FmqOgM806qT6cVYQAGOCMk8I3KQvKEaNiuZBZ13Ea2Ss2yFyL0qk/MMkWhEx5Dbgx1ExgXkJshmWWCqKs9rOeW0Mzp4kjcxLtIFyIqdKAzjuZLNJHelgQlsmUbuSW3ijKzlGuaP/nGHW7Pe4zWBC8q/qs2nn3mvBJtyc5LW7NAuG0JxXrlOFyJQPET00g1ySit8M++cbfmiZ0Rz99e8uS5EdUgtvzkTsVX7654+sKYP7+54JnLE45qj1bwykFPqjQ/fGnE3rLDJ6nGLqzlHNeezovY9ebY0frIqotcmGVSfWnF+ihDkdhb9myOMw5XHUZrZqXlYNmzMyTEnsg41+wv/VlLc5xbQpTztzlyHNaewg1I0KFFnhmZ5y47sQNq2kAy4rJulKjniGccmEE5JqFIURRO7qwCf/iNIybZMZdnJU9sjxhlOfMmoLVilMl1o5CkqQfVFgHQJPogdIMQIwqRGetTJAa5ZqvM8uhawQe3R29aMSmlqKqKsiyZTqdcvCjo85QSbdv+/+y9eYxl2X3f9znn3O3ttfdWvU71wtkXDocELUC2E0uhtVgwDTFxElGKExkZQ9QCxKBjGlEUEbRgixZoIZAJWIriCFIsRJBA0BIsyYrhiNaQkkVxFvb0Ur1Vd+2vqt5+7z3n5I/ffW+qeq3uLs70DOcHNLqq3qv7bt133/md3+/3XUaV4I0bN2i32yOfupuTYBzHo9e6n2T37d7CBETe7r2e7ACUUieBvwTkwCeBP3j55ZeZnZ19h07t/qLdbtNsNvnkJz/J5z//eU6cOLEDSTr0tNsNurQWGz7UGFCemWbTBlzZFBWJrKjDrBNzSaXkf5DE5byo/mqti0GvAFG00sVut2hxFkoYzjnMCK35FkpTeSkH80FGv98D7xir1wRqr8StvDWwkixKwsdKnSc2ho6JmE40W5mQeetxwEZ/KKisaGeemXLAat+R2D7tNCA0UA2kYmv2PeOJYWsgJPF25qlHiuZAWqtaK1qpZ6pkWO7mOAexFi5VLTTESZVyIDNJECh6LQrILKgophYZNvqWzCuCLEV76NuIvN3h6kaPSxvSjvQFwVXElUNy6+imMm9MwiGHTSrLemLY7Ekr7eRUiXOrPfYnmnY7Y62T8uT+KnEk1IxTMyXeXJGE9/XrbZ7YX+Hx/RWMUlQizWtLHSbKAdU44OkDZV5d6jEDZE7xgX0V3ljqorUorEyUQxZbUtVVk4AkcCy1BEG5UbgONEoBoZHkMFW4nG/1LftqMWudlDg0hAFs9CwztYi1Tka94Ng5pPW3NRC1EVP0vftWrHr6mfDXSlFAnjsqsSEviPu582jnCQMjGysnPn1GgdfiJm6UXOdWBmfXepxv9sXFoBRweCzBu5BaEtFOLaWw0C4NpTI1ygv53Tts7sitwusukY6YqEYcHy+zv57c/NG6Z1hrR+3M4ec2SRKSJGFycnLHc7Mso91u0263WVlZYX5+nsFggDGGSkUSbJZldLtdSqXSrhLut3UbE+kqvVdj2MYcR2gHvwH8l977rxWP/8K7AY350z/903z5y18mTVN+9Vd/9bZaePfraRdHAdMJzDUqvHBQ2i+d1LLQSrnUFDX4Vio7wtxKElDF5lCp4c+KUk9L8vJFmxKKlo/ShYqgAFMoRIjzLGcw6BKagFq9TqvdLmgLYt/TiGUxzJ0f8dFs7kA7yn7ARhqQGKiE0sasRhpdtFoTI0T1cqjIbUCjFEBR1U2WDStdIf7W40I1BY/1hpJK6eda9DczSc6NOBCJp1CTFXw6ZVO6eYLJ+kwEIT0fYAKIPaSusOEJtbTM4hKxUmz0c250HX++OJDr5IeVsCpaa4rEKErlEOulfRpqTb0kxqRlo5iuymPVJOClI3WW1jeYHo9p9zMuN/vsq0X82YIkt6MTCZU4YHYs5uxyh7lpqe5ePFJjYWNANQ745nKH4+MJj9VFJ7TVl2rvyHjCejdjkAsIY189FGf1zLGvHtHNxKy2HAdUIs1yK2O6FtNLc0kSGpJAHLtn6jHOCYl+qhKy2cuYqkY45wR0YgRhWilshLz3tAc5k+WQZjdnrBxIwjMKpw1KeYwXuYI4FIRmDIKM9aJgYq0XubVI5qECNwcK1G8787TTlKubqbSLQ0G/lotkGxgoF6Ae7x3WKeK+5cSU4am5A9RLu3f/uF3cTzUWhiHj4+OMj4/fcoxOp8PCwgJpmvLNb36Tfr8/qh6HVWC1WqVcLr9r6FXf6hC5sEd3nX/YGLYxm0qpI8AB4KNKqb8E9IY7okc9fuiHfojPfOYzd0VY7oWBayUynJoscWpSrknuPAtbKZc2Bsz3t4rKx4wSmUJaSQ6H8gXht9g4+KE6b9Ha1AqyQUY/7RDokEatThBI1aeUwitJFKKUAXjZveOlZTqWaPo5pKZEIxDoeTv1VEItu3AlaMmpkmGtZxkLNVs6FJ+yQty5n8FEohnkntRCIxZbl571REoV1YUky7SYSWo0iVFsAd00B5tBmBCXKgRKYTNPOYBQe1b7YhYaG0Uvg34miXh5s8t/utbGepHrSnNPGIgBa2iEON1NxUomCYt5YO4oh4qxkpDVg9gwXY14bbHD3FSJzUyzvNTl8f1VupljrBQwsJ5zq10emyzx59fbPHWgwmQlKhRsFG8sdanF8jc+c6DKNxY7HK1K1frBI3VeubLFvlqZzYHlUDXg2saAsZJhrGTQZc9SK2OiEkpCUbDVz5mqhGz1pLU6UTYstTL21yPaA0taaJgWgElq5ZBAK7w2DAY5SaAJC7sf76Hdt4yVI5q9nKlihleKZLMSaFGrmSzQus5DIwnEUaKo5AIFaMitdBuMEgFrvChnqAIwpbRc9yQyBEr0WkOtMMphjB6994044KNH63RWF5maGnvoRAd7g8YMgoBGo0Gr1aJSqXD06FFAAGKdTmfUEl1cXKTb7QKQJAmPPfbYjqry2y2+LWZ2RXwH8AXgzxGgymM/93M/x2c+85lHfudz7NgxQFBc1trbJry99rQDuTGOjsUcHYuZ7l7j4KESmz7i2lbGWjdjo5+jlSwiWhfoTgClcIVSvnKQZin9XpfAGOqjdqXHO5kJGQUa4axp5dEIjy9QGovQA5yXxFbyA/q2TKIhChShkgTc7Ftmyoa1npOEZiHAUQ0VWynMlA3Nvsz4kkARGWhnnkakafYt2jv6FhpGUwl9wZ3TtC1kmSXJOuRRReY5CMIziRXk0M8VtVgzoxxe+dHinDrP/GqLv7jRxRXSX6BIIgqAQwHq8QWtwIk6TTkyNEqw2RND16mK8OryXpu5qsKmA6ajnMXUcLnZZ6oqVd3j+8rEgaIWBxyoR7yx1OXEZMKF1R4fnK1zozWgFBrOrghq88n9JVa3evRyy7nVLk8dqLI1yMF71roZs+PCg8ssVBPDVDWin1kGuWNfLebG1gBtFBPVCGc9q52c/fWIlVZKEhpKkWKtm3OgFrFeuHkbrVjrZIxXxE29HAtPr5taZuoRK+2M6WpIq59TigxGebwSgv50VSq+aiLITougM5MwZGBzsIKeTJWTFqSTrkBBw6QcaqarYZFkzVudiIIe473M78JAcWY65oUjIif4+tLCnq0RewkqybJsh8+k1pparbbDsQTkc9npdO7Lk/K9GYK0fa/G9jv0s8APeu//K+/93/Pe/xe/9Vu/xfr6+p6+4O/+7u9y+vRp5ubm+NznPrenx240Gt8Sm5/dPh/vODqW8NEjNb7vzASfeGqKD83WONyIibTGezWyW7HekqYpzWaTfn9ArValVq+OWsbKD0kKkixFdWJUCBYLlCIymnpsGIvFZ86ZiFIgaLnEgNHiTzdTNmz0hTCulPDw0IagwIpap6jHomrRyzxx4XjglaIWaZwyo+qhEgiVIEtT8AJeGW+M0YgDgiBA5X080O8PCJSQyF1Rxaa5IjEBM+WIlc0ef3qjiys4ikqpglcolZvzUtE478mcIw7FQibQApKYrgTgpJ17aKzMQj/ExxVauWZhEDNbhZrJ0YM2+2LHm8tdjM/58xttpishZ2bKlAr1lNeWOzJ3xfPBwzUuN6Xt1baK52br9DKhEqx1M546WHtLBcRoDo0JqCMONGOlkH21iKV2yqGxhF4qCFGlkLlX5pipRVRjxUbPcqgRs9zOiAJDYjRrnYypakirZ6kmYVHVumKeJ5ViNxX371KosQUKuBoHItQcGwyy2dCFvmgvs9QiaUOmzmG0HyFqvYej4zEfmClzYqLEWCkaVZNaIQa3oThwJIFhsqL52KmJUaKDd5Ybd7fYbeJUSu0a4fleDqUYuczv1b9HKbbfCQ7oAiilSt77nveetbU1hoLQDxvWWl5++WX+7b/9t8zOzvLiiy/yfd/3fTz++N44Ogwlw253vg+SvO7HvPZ2lWBkNKcmE05NSmtko5dzaWPAlbUWq97R6fWp1eqEgUEVCQwvMz8NOG8FAOMY+ZepAhVKQWB3BdBAK1FY6eYCcCmHYv/SyxzTZc1m31MOBPSR5QXx2Ka085jpsmaj7xEDA6mm0kyQlr1UZkKR8iShppPK++gt4CxJGJI7QfrlXpHEZcYjxUrXinqGdzhlaHf74HKIKnT7KV+7tsGlVibnH2hs7slzjw6F0lFNApwTME4plCS8VVTK1diIW7kWUnmzm5E7z/OHKgysZ6JkmF9usTIIOdQoc261x+npEkE3IzGeQ2XFN5e7HEgsi4OAkw1F6jXWO640U2aqER+YKZNbS6ThG9fbnJgo4fBMlkO+fr3NkfES3Uzk1ZZbKYfHYtY6QjWoJgHjZam+jBIY//WtlP21SNRsgNQqJsqCymyUAhReZM0aESttQWVa6+lnnkNjETe2JAn20hxjxCVhq5jHZk6sWbwVg9zNnmVyWOVpESdQWoF1lKOAzX5OI1ScmioxVQnJ0URaqsDQQFyIcwdKuJNBgezcXwt46cj4LQnknUhQe32sR1004+0IxTsiF/a2xfY74Q2gBuC97wF86lOfYv/+/Xv2Yq+88gpzc3OcOHECgE984hP89m//9p4lu7tVdg/iaTfs5+8mdmPg6vst3I155pKEqWiLA2ee40Y7Y7WTMrAOVcysXG4xBrQF7cRzzFDTF/QAACAASURBVFuPNa4gbxdtTaOLSlAsUvAQKkmE7dSThIqpkmFzIDMprRXWysIYKc/AJ4VlDtQiNXInqAWKTgZlI4tArMFFZYzNwSsy5wiDEE+FcuDZGMjMKQkUmVUEWjOZaHIv1dBW30EQU49LLLb6/MdLG2ylwlRWSmD01nsxJt32WYtCRRyGOC+gj8lKiPMC6JmqhuROJLKe2FfhtaUOAxuCzVnuOR4bS9jKxC7pyX1lLq73OTqe8M2VHnNTJZKSp54Y2EqZb2XsL3s2U89jVcvlTkrsBlzrGY6XHW0ilIJzKz2ePlgVmyItldnhsZil1kASjtZMVgKubabM1ELKhSffYjtjdixmqZUSF1y41sCiQ81UNcI6TyezHGjELG0NmCw4e73csa8WsdjKmKqE9Ap3cJFay5ksBWz1LdXEoAGvBdDSKAd0U5lToiikwRTGiBzcmeky1cTQiEMy76locT6PAz3aOEEBEkKjUZyYTHjiwO095t7tld37IaGAR6wY29PYfif890BSIDMDwCwtLbG8vMzZs2c5c+YM9Xr9oV5sYWFhB7F7dnaWP/mTP3moY26Pe9n89Pv9XR/rfjzqhse/0/ObzSaXLl0iiiJOnz5NpVLhlVde4fh4zPFxmRNs9HMubwxY6WS0UkvuwOCwzpENPFnkiGMhBZsRkkCG7uKjKggWpwzKOyZLQsLeHBRcOAR9F4fSpqxFir4JqQaeTi7am6H25E40LFUmbcRQizKM95oBmkakaFtDHMDAKozWTCSezdRRi9XIYkdrhc8NiQFiIap/9fIyF9YsVotpqbVCvdBAGEvS7adi1hoa6KYix5YECmcdzYFIW+XOszGwTJTFCeJic8Bj4wHr7QETlYCZeoX1nmW6GvD6cpcjYzGlyOCA5w6WeXO1x5GxhFcXu5yZLjNZEVmszSxlKYs5NBZSjTRHwgGXWiGHypa0n3K0ZHm1AK0YDMcbEZc2BxyoRXgFBs2NVsbhsZj1bioGrsYwXhbCeyUy1JKAG1spB+sRvQK5aVFUIsNmP2eqFoEXIfCpashyO2OmEtK3Du8V46WA5XbGvmrI1kBmlrHRbPZzypEmQxJWJS5MUjNLuVC8mamGHBkvUU8MynsGzolDQZZTHZLPGS56cj8FCp7YV+bwxK2mxcPYywS1W3rQbuL9ZHd/oRSjzfR7MbbfCX8NeBHIgAQ49ulPf3oksPwTP/ETvPjiiw/1Yrcjbu5l6+BBbX724vnGmFsqx42NDebn5wnDkFOnTlGpVEaPDduRw79/LAkY2y9vR24dlzdSVroCdMno0xlYtHHEoUEHAUqLTJRTigAlJplagQVLQLeApFcjWbisEwh5J3OMx5qtFMK8S6ZLNOICKeoVFe3pZYLEbKUO5XK0tyhrUXGVIPA0jCqWRbF4CY1mPJE2oEK0M2uRZoAnt4ql9S2+utSl1Rf1f+WEmiFixQ7vKYjOikoifmjdVKyIgsIQNQ40EyXFZt9SjTXVqqAQpxJPq5fSHoTMjFV4c23AkTGRyWr2cp6frdIaWA7FEWdXekyWQ+pxiFeKZw5UeH25y8nJEhebfZ45UCnEjz3n1vrsrwYcq1hckNAsBKef3Bey0k7pdi1K5czWQzb6OdZBrRQwUaZAQypmKhELmwPGyyGlUIQHlooqb6WdSXvWaNq9jEpsRvy6gfWMlwxrnZz9VfEvzKxnphpyfStjXy2kk4oORDU2rHQyJsoh7UFOJTIYBd1cDFyDwKCU5vSMeAiWAkMrs5QDaRfjHbXQCA/VyoYn0PL+BiiePVhlqnZ3RPZeOxXs1Zpwv8nuUQfivR3xHu5i7kh2EVBHxKCXgGBlZYWTJ0/y8Y9/nCNHjjz0i83OznL16ls+fdeuXePgwYMPfdxh3EsM+lsNUBlWjpubm8zPz2OM4eTJk1Srt+6KtdZCKr/NIhEYzWOTCY8Vs75Xz7fYdJ48jGn1Bugsp14zBEkiVZGR6sh7sNqjyEnChOF9a7Qk1n7uGU807VTUWXIrqhgDK2CW1EI9Fqj9oNdDO0eSJOTE2PYaeI+1jpyAaiQ+fLmDkoZuBpXQoGNHO5VEuLjV4Y3VDps9gcKbgrFqncz/QKgUKHECj5F2plNKWnneYz1MV6V9CTBT1fRT8dELbMr5XsBMbOhlnu5mn7max7mMgxXNYtdycb3PeGK43Ex59mC1qKY88+t96knAoUZMYBSnp0t8Y7HLyamEzU7G6YbiwlbG0bGEK1u5tEKbPVIn6NUn91c5t9olDAN06tlXC7myMWCmGhIZGCsFLGylHGokIhjuhbKxrxay2s2oRJpSKIlquiqCylpJO7Eaapq9nJmauA+kFmlnbqXsK9RanPM0SqJfeqAW0xrko9nmes+yryqqK/VSwOMzFSaKueDAwmQppDXIKQcCbkEJPSUqkK9DVaBnD5QZq96bevSozrver+zuL9R7HI05uhO8978N/Pb2B3/pl37pHzSbTV566aU9ebEXX3yRc+fOMT8/z6FDh/j1X/91fu3Xfm1Pjg2ij3n27NnbPvZ2VHbdbpevf/3raK2Zm5u7bZLb/vzd7ojHEsOE9hw8OI7znoVml1dvtJhf7dCowmyjgtWmcO7WI51FhYgDd1JPOYRGIIkuDkTP0AYJpkBg5U6RGEd3oFCDDjquEKAIjSe3UK1P4GxG5gJwKX0dY3tbEFUZpBlKhfQyiI3n/PIGlzcGQokoWq5Ga6yTqjUKxIY998JH01oXqEsKqkUhbRZotPd0BzlhILqMndQxXgropDnexDy9P6aXOQ4VoJXVTspYrHizaTmQCJdNpZ59seG1pS6ztYArWzlP7a/Qyx3Wei4Wie/kVAmbDfBZynwacmyyTGQ0c5MBf7HU5WSx+Tg9nfAXi11OTyZ4BcoHXNtKOTKWkFqxt1ntZMzWY9a7GcYoapHwL/uZpxEZklBanrONmNZAkJzeCwexnVqmKiLI3EktMxVBd05XpTWdWs94JWSzl7OvJgLVgVZEgTjIz1TEpX1fLeK5YsaYOklmcSD3RC3UOOR9SIzG4UX7QEOk4OlDZarJ7qH4j2Ky896/X63dTxSf0/dqbJcLixHjvDIwBox9//d/Px/96EeBvdklBUHAP//n/5zv+q7vwlrLj/zIj/DEE0881DG3x162Me9nZtdqtUZSRU899dQtPJ6HPf6wCgRJBocnKhyeqHC9uckfX+rz2o0OkYFqoomVpxaHOBcJdFwryrEmdZ5OBqVQJIH6mcK4AVqHBFp4d2m3RVhuUKvVRt5x1hsqocznkjihJOw3+jk06g2y3LLeybm0scVyDzb7GdYBupj/KDBKF9ZHYqjq8WQWSoUwcuZEWiU0ikHmGBT8r27qGFhLPQ5oD3KMVszUAtLcc2KiBEpAHKFRfGOxy+FGTBgYMIbnDsqcbCxQvLnSZ6pimDLSlp1Ncl5b7LAvsaykASfqmlZq2drqsW5DDo9VmQ0N3dRyozVAK83jMyV6maM1sHQzz1P7y2z0cga5p5c7jowlNLspzkMlCpgqh2wOZP44VQq53koZL4WUQ0WgPddbUjWu9zJKoUEr8S8cOKkKvYfWwDFTE9PZmWpht5M5xsoBvcwxXg6xTjiLGSJAHhlR5Tk+kTA3WZG2snU0ooBWmlONNAPrCbTBO482urB20SgvvoRPHihRSd5+GP5QremdikcxYb+dMZrVvkdje/b6CPC/IS6xOVA6c+YMP/iDPyhP3KN2wMc+9jE+9rGP7cmxbo7deNrtNnShX3m3GCY57z2zs7Osrq7uKtHB/SW7280DAQ6ON/ieUsz/d7XDRtfRzjxbFm50UpIwI9CaJDREOqAaaWpJQKQDBrmiEkHHBdhsQF9ViFwfVxknMSJVBYrYQK8ArwylrlZbKRuDlKV2Ti/N6eSWfl4gSY2hmkgCC40hUG6kJjNciENjMAwl6PRIKDsv3COCQslDK1WgAaW92sss7YGllwsCc6WTCeEcWOhmPLm/Qj+zjJdimv2c82s99lUjLqwPeOpAhX5uCZTi8kafyCQcHjfCscsGnN907IsyegQcSVKabYeNNIs9xdx4yMB6OgPLcifj2ESJ3DrWOhkbfcvxiRK9NGerUC2ZqUastFMqcUAlNJQjzbXNAQdqMdaLCe5y1zLbiFntZJQjmUsOcodDuI7Ow+YgZ18tZKWTMlURNqS1QmvwTuaxtlBHafYdkyVDp3AtePZgjYlSUPgiKsqFM8VYEtJJLdXC6NYbLQarXq5zbDSn9kXvSKKD913KH4X4dpnZ/SnwMtBD3A/WPve5zw1gbxFS38q4W2VnjBlVRw8b7Xab+fl5nHMcO3aMRqNBv99naWlp18e432R3p+cmScJfmYv506sbXG85CCHLPcZIgupkjjYDVnse25QkMhR79bklDCOU3iTUCu9TqSK9FVSndXQyi8ORO01mc7F2MYowMERRQBwq0AbnLJExhYAzuEIEO3eOciAOA5l19HNLhlSXUSDixBpxK1dKF/ZJBfzdezyaxHsapRCjFJGCZw4m1BNxF1jYGnBlY8ClZp/IKL6x2GFfNaJRCgmM5ol9ZRZbGeMlw9m1PienEiHse8dCs0eO4uhYRCkqM6Xgmyt9TkzEtPo5p8Yd85spk6FjK1ccjC0LTZHkGuRwZirh/HqPA/WYxHnGywlXNvrsr0Zi96PgWivl6FiJvnUoBZsDx/5qOEp0pUDTycQHsRpJomv2M2brhSxYJUShyKzQDsRtQtrBjdiw3MmYrkTiYxdqPnp0nHKo6VvxEuxmbiQAnRdi3a4QKohMca0B4xUn90fU7qN1udexlzO2B6kS36/sVMGtfG/GzXfWJPBHCFjlf/jsZz/LX/7Lf5mPfOQjb/uJPUjc7Gm319HpdJifnyfPc44fP06j8Rbv6EHapLt9/vY25u1CKcUHj4zz+vUNLrc8JhRfl9BrMifEdOscShvyXLzOjFa4IKBfVAed1BYfdtHa1FiZqWkFBEQGAhMWrUmFtZZQeQHmWC8KIIGmnVlCLYhAnKYUakDRz8WxYDwJ5PcLp4aBk4orcB6ti7/RKqwSjhdF5RdrhVGaeqKoF5VHOTKcnCpzcqo8uhab/ZwLaz0WtlLOrfa52BwwUwlZ7eY8c6DCZi8nG/S50YMDtYhaEoKHZi9jc+CYm0owSuyCzq31OTlZxgLTgea1pS7HGwGD3DEZZby64jgQZfS6gm68vGmZbSRYJxXcQltald3UoTUyR6uErHQzaklAKRRXcqOFD6iVcPION2LaA0s1lnamVqJcM10OSJ0nzS0T5YitfsZMNcI6mK5EPHugKjxNB5VAF61iWbxCo0idJLkQj0FoI0ZBgObYdPBAiW4vW4/vc+ze2fh2amPuB/6J9/55pdSLwI/nec7P/uzP8qUvfeldUd2NjY3dsY35oOGco9frcenSJdI05fjx44yNjd3yvPvl5d1PpbnbYz9+cAx/aYuraU5QHD80gXC5tCLLHKGGOJT5T1AQ2FHiGq5QOJFwkRvfiwA1VmgAuQeXZ2gTopQjDqRVlmiZ+QycGH2WQ83mIKc89EDzEISGQAup2VlHYjTl2EAhguy9zPh8MegzShUcPNEEVQq8zehev8Jr68EdPcwaScDzh2o8L3ZotAeWN1d7XFzv8qfXtkh8ykoW8cS+EqkVTdGFzZSxUsCJCUF9tgaWZi/nzEy5oEU4zq72+MBMSWTYIsXZNc8TMwm5A7zlfDNjNs5wLgTvWOmLdFwnFdUX68WtYr2XU44CKqEufO9Eui3UioVWyqFaQmZdYYorvMLFVspUJQQF1jpqcYh1jlJoSK3niekKc5NlBkV70xUJUg+VeIrrGmKxXqgIoRb3g0ApDo8pGuUHq+geVV7c+152DxCFhu97NbbfDRsIxw7grwD/6z/6R//o/zh9+jTw7ijxgyC4awIZVki7/XAqpXj99ddHSe5mK5Gbn3s/H5r7qezuJ5EendJsXtkgN1P4QBZDUySwsNBaVEOUpXMQh+iCVeWdiAp7a/HakOU5gTKghcenvScIA8ATBwHt1FKLAzIrZp9lrdAqoJPlxcxIkeaWJCrOQ4ExClUk4DR3BYHcoJyVBdoYERxWikB5tJKdvlZQjQPOHH9ypFq/trbG5cuXGQwGBMHOBFitVomiiEqkOWjaDNrzvHBmP8nECS5uDPj6jQ7aw3xzwNExQaVa71lppwTG8NhEidw7epljtZtzZrpMZsWD8NLmgCdm5HvvLZc2M2bjlCApk1lYG3hm6zGd1I3AObXIsNHLiAOpdnMrYgCVUBzXl1op+6sx3ntCrVnrZsxUw8L7LiruLcXAeWqBLuydLN9xdJypSkxqHaXC2BUornXhvFG8/9ZqokJyztkMnKW7do3Xr2ztMEEdWt/s5jP/qKqnDM1ddxuPuo3Z2xEKvm3amJtAVyn1w8B3Ar+2trbGM888A7w7kt0w7sT72a3NT6/XY35+nl6vx+zsLPv27dvzv/9B0Zi7OW7NdiiVJrnak8U2DAKsF/MyVyitUDQrPUMjWsAUi6WWx8QCxhN78dkraUXfQ1jodNYjjUOADVorvDfkToAQA+sweMaSkFaaE2mNKUA/RonAc6DlvMSoVKTP8CJbNhRFA3mtQCmOTAQYY6jX67eo+WRZNkqCy8vLo/cvyzKSJOHAgQOMjY1RrQQcaCR89GiDzHourvf4xlKXpVbKjc2URhJSj4y4ww8sncwzN5GQOU/uLIutnDPTJdLc0+33Wep6TjQMmAbOO1Z7OYdqMd1MgDSZg3oivLYkFPCO9p527imHhihQtAeWWhKgtXwgF9sp+2oRuXVUY0M3czSSgLVuymRF5MUqseGvnZwSqoaGspHWcd+LNFyWe0IDzlFU+TLHVYXzuHOK8XLM7JEn8N7T7XZpt9tsbW1x/fp1er0ewD2T4F4nu3eisns/3gr9Llrn7ze28+xSpdRPAv8T8H95788BfOYzn3mnzu2+Y7g7uyNZ+x7Jbtiu7Ha7I9ugoePxXocxZtdC0/eTGHu9HhsbG3jvOTp9nKWBLvhGwvPSMIJcaeVxXhdzISX6lqEis4C3JIERYMSIw+epoejllsCI5FTqpB3mvMMgbZDMOqqhIXOeXmYZjwNyDwMrYBUYujhIK1UqbfWWnVHRRhVpNDAoypGidheUYBiGjI2NMTY2RqfT4dy5c9RqNY4ePYpzjna7zfXr1+l0OuR5TpIkVKtVapUKf+1IlUplnGbf8tpyj8vNAde3BqQWjjQicifu9Csdy9xkQref0u32aLqIMzNlssIU7vpmztxEzNbAE2hPK/VMl8NijinT0CQwbPUFnBJqSe4OTzkwBFo4dhPlCIUiCgNW2gOp3HJLPQnpZ45TkxWeOVAlszJTNQo5R+9JjCK3olOaOwgDMWzVeriBUDiX4wZN9h04MOouJElCqVRiZmZmdL8PrW9uToJDl4BqtYoxRlrQe0Asz/P8/ZndOxjiOvJtkOwAvPf/SSn1PwIvKKU++Su/8iv80A/90Dt0ag8W9Xqdra2t27YcwzC8beuw3+9z6dIlOp0Ox44dY2JiAqUUa2tr9wU6uVkC7G6x123Mbrc74vrFccwTTzwhIJKWY7nnpWILDNY5hNYm7uhxIHOz3HsC5QXJqQrDWKAShVjvyB0ohHxci0P6WU4UGMpm6JkWkFtPpGXWZz1EeMIwoJc7kgBqYUA3EyeB2MjsyDlHoIuZ3FCYEcnHYUFPADhQu/c1TdOUixcv0mq1mJub23EPTExMjL723jMYDGi327Tbba5evUqn08E5x1ipxKF6hXh/heU05GoHljoZlzdzjtUDmlstgfv7mFPTJbKC53Z+bcDp6XKBioSLbcvhesKgmL+t93PRuMxc4VQOUWDopDmVKIDiejsvfnFGKXq5oxwZUOI83hrkfMfRcfZVE3A5YZHArNdERqpjjcIYcM4TB6I3GhV2PdZ5vM2JAs/cY7OjazGMm7sHSilKpRLlcnlHd2N7ElxdXaXVavGVr3xlRxIc/iuVSrtOgu/UzA7eXZ2rb1U8agAVpdT/gmg2rxQ/+gfe+y8Xj30a+O+Qkf+Pee9/717H23E3KKVOAr8IhMB3/O7v/i5LS0v86I/+6A7k4aMcQzHo2yW7m7l2/X6fy5cv02q1OHbsGKdPn95x099N3Pl2MUxKu/mQ7VUbczAYMD8/T6fT4fjx49RqNV555RVu3LhBvV5ndqKG2kxZaUvC01pjcWht6Gd54Zsn5HPnNUY7WcALCbLUWqLAEGlJiApZhOuxaDYGRpFog7VeqAfeUzKqEKfWhAoiI4LNRkE9DsmsFePQsJjXIU1VFG8Z0+oi+QGVSNEo37mqs9Zy5coVlpaWbvs+3hxKKZIkIUmSHXZQ3nt6vR7tdptOp0PUXuVAt8uMtRwpwXI/oVIb5+wmzE1KIiuHmovrfeYmSwxymZtdWO9xbCymlzviQHFtc8Chekxu5fvrWzmHGjFZ8fzNgWWiLDJg1UicwONIyOFDRGY5DPjPH5sSUIkGCPB+qGFJ8TWgZBNjtPghRkZ+JrNqRSlMODSmdlyL23292yQYhiFBEHDmzJmRE3i73WZjY4Nr167R6/XQWlOpVKjVaqMkmCTJLe+RtXbPDFTfT3YPFo/gZfi89/6fbP+BUupx4BPAE8BB4PeVUqe893ddUG++G34W+E3v/b9QSv0/P//zP/8DP/ZjP8Zf/at/lRdeeOGR1cDbHrtRURkMBly+fJmtrS2OHj3KqVOn7jrj223cT7K7F5hme9yO4J6mKZcvX2ZjY4Njx44xNzc3Ot4HPvAB2u02CwsLdDodvPcEE7OouFEAFmQ+loTmLb1LbwBPbDSxEbNU7xW1OKSbWbxSop1Y/N/JPaVAwCpKKXK81H1Kjh1rMV31BTG8EmjS4lYsR4EkzaxwONCCAx0mOrA4J0orkVHMVG5/z3nvuXHjBpcvX+bgwYN86EMfeihkoFKKcrlMuSxUBmstly9fZnl5mSdOHOS5KKLT6fBs0mahvU7ThtzolRmPDO3BgFocspVm7K9FRUtR007FnidzUp1t9VKmK2GR7DVrXZkTOi/CzevdXJRRvKcWajYGOS8cbHBmpoJ30uLVypN7SXoiCedxXlEyMiMMlWiWmiLxeZvL/Z2n5J0brLtbUay3uxa3+3r7fbiyssKFCxc4fvw4eZ6Prl+lUmH//v2j39ueBJvNJlevXqXfF3Pc7VVgv98fXfuHjTzPd5043w3r2tsVj1Jld5f4fuDXvfcDYF4pdR74EPCVu/3SzatyAgzFJcO1tTWiKGJtbW3Pz/ZbFWNjY3fl2l2/fp0rV65w9OhRTp48edeb/EH1NHfzIbufNub2yPOcq1evsrKywpEjRzhx4gTOCcgjCATAMT09zfT09Oh3hvSJy82MrtPowqfOoPBaoY0hLHqIQwf0IDCFaoenHomtTuoEjJLmIuHVTXNxJtAKgyfzmrCA2RstljfOCrzeO08tVgysaG2WQk09FiHo3DpxTtNS44FQFowCN+jw6p+fxRizA22Z5zmXL1+m0WjwwQ9+8L6Qd/cK7z2Li4tcunSJQ4cO3TaJPockw263S3OrxcWVDvObXTqpou0NgTGiXhNEIyUT7z1J+NYGwXuoRkGhGCPaoJU4QOaXolP4vafHqSeRVHNGwEXWDo02IXcyszNa3OnDAKxVBNqNZrU6iDFArAbkLrwFxbq99Th07L5bEuz1erz55psopXj22WdJkuSeleCdkuCwlby+vs7y8jIrKyvMz8/vOKdarXbXxHy7yPN8T++Jb4dQfEsq3Cml1Ne2ff8vvPf/4j5+/+8ppf5b4GvAT3nvm8Ah4D9ue8614md3jZuT3RpwDPh/gY1Pf/rTPPvss5w8eRJ4d5T6tyOWD6uglZUVGo0Gzz777K7nag/rVn6n0FrfV4vUe8+VK1dYXFzk4MGDPP/88zjnRmAcY8wdq5phG+lMyXFhOaeT5yL8qzReCaBE1lGpsFCGzDpQ4sDgnKA665EqIO6maLkFI34cSlEOFP1c0IAyqzJQgFeU1ljrqQaG1MlrRloRG01iNOBHSLAh0Mh7OLKvTvXoR8jznE6nw+rqKq+//rrM+oKAVqvFhQsXdlQIDzP3aTabnDt3bldJ1BhDrVajVqtx5JBAmAG6g5Q3F7e4sNalmXmutCzTlYjciZP4ajdjqhxjvbQx13sZ42V5vBxqNvo5T87UeOZAXagIhaWS9cXO2yDzVS++f8MWMF48C4XHL6Aiipb0VAJR1ICxneOIPM9HbdthoknTlDAMb0mCQRBw+fJllpaWOHnyJJOTk6Pj3KsSHIJYtsf2yk4pRZZlzM7OUq1WR5Xg+vo6V65cod/v79jwDP/dKQlmWfY+QOV+Q31L5MJWvfcfvONLKvX7CMf75vifgf8d+Blk0vIzwD8FfoTRZH9H3JP3dfPd8H8CQ6n+3zx8+PB//bf+1t/i+PHj9zrOIxPbK7s0Tbly5QrNZpPDhw+PtDN3m7QfZGa322ptt8d2znHjxg263S7ee5577jmgqMyMIQiCXbXuhi251aUlakefwuhITFaN+OGhBRWYWVHyCANBaQ4Kg1WjYFB41ynvKYXSZnRekRjNIHdSsWnIvaIeh3QzAWeAER3HQOSwSoEAMZwXCavADGkQjIAxeIiNaEEOz39hYYFut8vTTz89miGnaTparG+Htty+WN/tOnW7Xc6fP49zjieeeGKH9+D9RjmOePboFM8eFej/ctezuJWy1OlzbXOAUhGZcxilyJynGgeiuqIFkfrdJ6c5UI9ReHKnMQaynKLaLcj3SmGQGYvzClMkk0AjlfSQWG404zHciW0TBMEIxbo9siwbXdelpSWazSbdbpc4jpmcnByhfiuVyl03BGrbBmZ7DBPfsCuxvLxMs9kcoaC3J8Hh71pr6XQ6tFotVldXuXTp0m2r02q1et/J7lEXzHh7YjhGePvCnpwPnQAAIABJREFUe/+f7eZ5SqkvAl8qvr0GHN728Cyi6XzXuBmN+Yfbvv7tW5/+6Mf4+DhvvPEGr7zyCgBHjhzhscceQynF5ubmt9zTbi/0LoHRAnD58mWmpqYolUrs3y8bIK31rpOcc46FhQWuXbvGoUOHeOmll8gyx+UNT8HXRhdK+dpDFEo7zXlpu5VNiFIeNyQz5w4nDUqc0sSBJ3OKUHm0EUPVUAvPqxYZepkjCfVoFqCVGMka7QmHEMyiipPHZdumNeyviSzZpUuXWFlZ4cSJE0xPT+9YOKMoYmJi4q5oy7W1tdHsslQq7VgUoyhifn6ejY0N5ubmdhxnLyLPU1orN5ieOMT+WoOnD8i593LL4lafpXbK1iBnsTXgiakqT++rSdLTYruklcc70bAMjHqrcgPwDocmwIIyI/EAAahIK7QWeB5E7jIMQ8bHx0mShLW1NSqVCs899xxa61ESvHHjBu12e9S6v10leKcYvofdbpezZ8+SJMmOSvp28+ybK8HtSXD4Xg+TYLPZpN/vU6/Xb3m/3w0dqncipI35Tp/FW6GUOuC9v1F8+wPAq8XXvwP8mlLq5xGAyknglXsd75a7USmlfLHtGurevVtujmazyZe+9CW+8pWv8OSTT/LX//pf35EQ3g5Pu90+f8gHvDm896ytrXHp0iXq9TpPP/00xhharRavvfYa9Xp9hGqrVCp35CUN506XL19menqaF198cbT4xLHm6Ljl6oZ4rw3nRaOzUYz4Nrn14BSRESFnpYu2o9c4Z8m9Jgk1zgbilC5OPoRG/OeSQJFbsexxyItEgczqhouyKrh1+OIDpyWJri7f4OrVq3ecm93t2t4JbTkkT7daLS5evEi32yWKIsbGxtja2sI5d9f22G7DOce1a9dYWFjg+PHjJJEh8+Ly4ArllLmpCicmpZGii597L4neOT+a5SkUzsuGA0A5h9daroezqEKLVCA+8jseqIee0gOCG51zXLp0ieXlZU6dOrVjE3C7zcX2CnthYYF2u421dlRhDxPh8J4dbmLW1tY4derULZXl3SrBm0MpNWonD9erP/mTP+HZZ58doWuXl5e5ePEiaZruUNvZPqd8Px45UvnPKaWeRW7nS8CPAnjvX1NK/d/A64hDz8v3QmLCbZKd39ZYfzeV9v1+n4997GN853d+J0mS8L3f+723POdOPLs7xYPoXe72+bdbSDc2Nrh48SKlUonHH3+cMAxHBpTPPPMM1lpardYt3LBhtVKr1ahUKiPOXaPR4Pnnn7/tBzmODPtqsNIWzp3SHuOVyEq5t0jCUaGZ6Z0fma5mzktvX2tKStwVlB5aASlUUVVIZSKu6EKAFjFqXyAFtdYo/VZVpwrLHkXO1bN/wcTY3oJPhjywXq/H2toa09PTHDt2DKXUKAluRwveSYLsXrG6usr58+eZnp7mQx/6UEG8ho0+WKRC887hvBrtphWjIhflBZwSeFdgXBWRFp6cbEwM3mZoZTAmAIV40w23K8oT65Qkirn9eGN3579///5dbTKUUsRxPGpxDuNOfMbBYECe50KNmZ0d6cTe7XV20w4dxtraGmma7lDb2X7s4ZxymASVUjz11FO7v0Dv1VCPVrLz3v83d3nsZxH2wK7jPTPBTZKEP/7jP+aNN97gH/7Df3jb59zJF+5O8SCVYL/f3/Xzhx/cYZVhjOHkyZOUSqVRsgnDcFS9GWOYnJy8ZUEZLtQrKyu8/vrro3ZdnucsLi7uaOFsj1rJkGWW5kCNACrOD2doMjuzTtQ5TKGPmTlFqB3GaHIrLVCN8O0yC6GR5GndW2osWkNiNJlVMgt0b4EW8L5wR1bgrVQJnQ2efvIJSqXSrq/lbqLdbvPmm28SRRHPPPMMSZK8dS2KymB73LwoXrx4kSzLiKLoFqCEMYZOp8Obb75JEAQjlOIwlIJq4GhZeS+V1gQI8AQvVV0cFG05J7+gtVxjoxBvv6Ltq/GYMBwJPisFrqAk4Bybq4tcX1+m3++PwEl3Es7eHr1ej7Nnz6K1vuX8HyRurrD7/f6oZXnkyJHRXHB9ff2WNvPwnMvl8q6T4GAw4OxZAZO/8MILO7on25OhUmpHEux2uw/1d75XYtgVeK/GO5LsvvrVr/LhD3+Y3/iN3+DjH/84IFXN3/k7f4dXX30VpRT/8l/+y/u2FlJKMTExcUfng6G00W7jQSq7+0mO1lpeffVVrLUcO3aMarU6er3tSe5uMVRtuXFDWtsf/OAHR8cZLtTbUXZRFO0g9zYqFZxSbA2KlqIHpSXBAQRGNBZtbvFoWZBVQO48UbE4RwayYrG23hMo4YDlzhMXslVGQRJq0WwMCi3OIRLFg/diMaS8pbVxg6/fuHgLD+tBZy5pmnLhwgU6nQ4nT57ctUDCncAbaZrSarVGLbtWq0Wv18N7z/T0NFNTU+R5fku1EoZQ9pYUAwpBqXpdJCppZQ7bmEoJuCU0RZsZ0dQUvVChiQTK4wskpinanUngmThyEI4cBN4CddxNOLtUKtFsNllfX+fkyZN7Prd0znH16lVu3LhxC4pzO0VmO6l/eN8OgVnlcvmWJLhd0eXatWtcu3aNubm5Hce8WyXonONf/at/xRe/+EX+w3/4Dw8FSnqvxLtlZPUg8bYnO2stf//v/32+67u+a8fPP/WpT/Hd3/3d/OZv/iZpmj7wbutubuX3G/f7xu8WoNLv90fSXqdPn6Zer2OtFUueMEQP5zH3iF6vx8WLF+n1eszNze1YlI0xNBqNWxb2O8lkTczOEVXqKAxaiUv5EG2ZW4fSwcj01XlIAlHuV0rEpYfO2SJMXIBRtMJZT2RkRicJT5Fa8dCTlolkVR0YQNMIA44W4uN3WqjDMLwlCd4ODGGt5erVqywuLnL8+HHOnDmzJx/mKIqYnJxkYmKCa9eusbm5ycmTJxkfHx+d7+0W6tG5RhUsBqMKYWy25f0icflRS8kX7U65tk4VGxJVbHScbE7Ak+CIbur43ks4e3FxkQsXLowAT/Pz86ysrOyoBh8Gwr+xscHZs2eZmprixRdfvOsGbjupf2ZmZvTzIU90eN8uLS3R7XZHnY9Op0OtVuPJJ5+kWq3e8fjD1wB48803+cmf/Ek+8IEP8O/+3b97P9EV8S6aXN13vO3J7gtf+AJ/82/+Tb761a+Ofra1tcW///f/nl/5lV8BZDF50IFxFEUPRNbei7hXJZimKZcuXWJra4tjx47R6XRIkmTEGbsbV+7m4wwRhCdOnGBqamrXi/idZivdbpf1gSileF/QCpDWRhwGKCDLHWhFaBR57lFKExiP97qYJalCfUVmcgrQxZxve8IrhYVOo1coZUazuthAbVvn8k4L9b3oBpVKhSzLuH79OgcOHLjnIvsgsb6+zrlz55icnNwB/imXy7cQ+rc7Cty4cYNer8f+Q0eZmD4g801jCi8/kWhDUVj1FLQPQHnZVARKkp8uKmNtQClPjCO4jz8xz3MuXbqEMYYPf/jDo5bl8NreSTj7ZqDJnSJNU86dO8dgMOCpp556KGWUYSu2Uqmwb98+QDYyFy5cYH19ndnZWay1o43fdo3O4f9DebLBYMDnP/95/s2/+Tf8s3/2z/joRz/6wOf1XosRUOw9Gm9rsltYWOC3fuu3+MM//MMdye7ixYtMT0/zwz/8w3z961/nhRde4Bd+4Rceard1JwmgYR//fsA3DyvunOc5V65cYXV1laNHj/LYY49hrWVycpJvfOMbaK13qEXcCQgxPM7y8vJdZc7uN4aLQxw7brQGxaBai7dVgdJ03mE0gMU7LXM9hehpGlFaSUKw7i06gnDFpQxRUFjOyCxQ5oJvEchRUA9212K+E92g3++ztLTEhQsXUEphjGFxcZFWq7WjsrqdLuNuo9vtjtRDnn766XvOFbe/t9vDWks/y1BGQCTe5TKPC0LyLCMIQvBattreg/IYDygt7cvi9JVyxNhdz1qGfMuVlZXbtix3Q+W4GRy1vQoslUosLi5y5coVTpw4scNFYa9iCKAZUmlup7E53GAMNTr/9b/+1/ze7/0enU6HJ598kp/+6Z9m6NX5fgxDvZ/s9ip+/Md/nH/8j//xLTvCPM/5sz/7M77whS/w0ksv8alPfYrPfe5z/MzP/Mx9v8b2Pv7d9C53WzkORZh3Uxnc3Ma01nLt2jWWlpY4dOgQzz//vHi3FZXciRMnmJub20GW3T5fi+N4NJ/o9Xqsrq4yOzv70BqQN4f3npWVFS5evMjU1BT1/Y/hvBoB+RQQCouL3JkCFKHIckmAvhAZdm4bF6y4XG9R6aTlFmjRzywY5LJIK0VJuTsSn3cT/X6f8+fPk+c5zz333Ci5bK+sNjc3WVhYGAE3bjcPvFPkec78/DzNZnNP+HjGGCrGkBbXARMWajSKKIoEranFnV1paTF6Z0XbtLhuHkuidqevCm9pWQ6r3b2gcmwXzr5+/TobGxtorUdWSysrK/ftfnCn2A5AuRuAZruyDUgrtdPpcPDgQf7u3/27dLtd/uiP/ojBYMAP/MAPPNQ5vZfifYDKQ8Yv/uIv8sUvfhGAzc1NPvGJTwCyO/vyl79MEAR8+MMfZnZ2lpdeegmAj3/843zuc5974NesVqu0Wq3bAhHuN9kNn7+bZDdsYzrnuH79OtevX2f//v07VE9uRwi/XbtuuJu+cuUKFy5cGAEzFhYW2NjYeCjdwO2xsbHBuXPnRqThOI7JMtjKxLlgOFaTc5c2pVjRCIfOeXAmKPhgArBAK5QXLpjyjuEwyhg1Ij+rgj2uCx3I6gPywYbtuLW1NR577LEdizHcubIayo+1Wq2R2esQwLOdxlGpVFhaWuLKlSscPnyYubm5Pa1UIuVoNpdwKqLaaBTke4XTWriOetji9Cij8daytbHB/Plv7qCdbK+sbk5iQ5SlMWZPUJbDGM7Yoiii2WxireXFF18c0V+G13fYut3eXryX3Nf28N6zsLDA1atXbwGg3Ov3fud3fofPfvaz/MRP/AS/9Eu/9K6iU70T8T5A5SHi5Zdf5uWXX77l55/85Cf5nu/5Hv7G3/gbABw+fJizZ89y+vRp/uAP/oDHH3/8gV9zbGyMZrN522T3reTaKaXo9/t87WtfY3p6mmeffXb02P2onnjvWV1d5eLFi4yPj/ORj3xklJy3VyrDFs2QE7YdZXkvYEG73eb8+fMAPP744ztaxmEINe9p2ULCq1DX98jcDUQBZcgLi7XA5bXSQl1QntwbAjxWGQLlR78/SoiFGwLeofI2Pqow9K7bTXjvR6Lehw8fvq9KBWQTcy8Az4ULF0aVSqPRYDAYsLy8fFvH7geJfr/PuXPnsNZy6tQpIpXjdCg7bMS2By1UA1G4cSjjmJ6oM/2hD92CXtwO3KhUKpRKpdG9cvr06T1HWQ5Vfi5evMjhw4d3tNWH9+BwxgY724tDPuNgMJAq96YkOLzf2+02b7zxBo1GY8RZ3E0sLCzwUz/1U9RqNX7/939/x3m8H3cIRTGqeG/GI8Oz+8IXvsDf/tt/mzRNOXHiBL/8y7/8wMe6l83PXnPthsnp0qVLOOdGqifACDG224V4Y2OD8+fPUyqVbjsT2l6pDOXD4C0tw+3AgqGCxfYkaIzh4sWLIxj+zbD6YUQRNHJHK9cCWgFwnnAIi/dCAvfOY71Ca0TdsgCqhAq8MkRKHje6IE67t2Z0Hkfv/2/vzMOjqs/2/5nJTPaNkIWEBJKQlSxQloqtRMQNg0VccamUF6uoqCAWQbBUfbWib7W0VUuVolgrUlHhJ0VcsOjLC4oiBIIkmexk35OZZJLZzu+PcI5nJjPJTDIBEue+rlyQzMmc75nMnOf7PM/93HdHI62N9dKclchcFNdsr7/W0tJCcXExY8aMcbvjgY+PjySxplQqueiii6QysqOg4mqmIvffS0pKsspGvSw2781+2pj9sRerqqqoqKjAz88PHx8fKbNzpXTbH0SZL29vb6ZPn+7U89iWF0WIWbZ8TKanp0eqkowfP57w8HCn2glms5ktW7bwxhtv8Oyzz3LNNdeM6mzFnRB76KMV5y3YicxLEVOnTuXbb7+1f7CL6M/mx92SYS0tLZIlSUZGBidPnpSMI0WGpTPQarUUFxejVCpJS0sbkEJtC1HLUG5aK5I2tFotHR0dFBcX093dja+vLyEhIVbyWPZuVioVBCss6MxKBBQIZ4kmlrMyXwCCF73UeeGsa4LFjOqs4r5S0ZsJ+iglFTFUZxVZUPRS7sOiIhgf1VuWctRfE3f+YrlMrVaTlZXl9qFzUcKqqamJpKQkK8aqvaAiZiparZbW1lYqKyvtjkaIYsnipqikpMRpdRJXIQYhlUrFT3/6Uyu7KXtBRV66FQ1W+9O1FGXEGhsbSU1NdbhZcgW2WbZIQImJiSE4OFjS4ezs7MRoNEq9bDnT0sfHh/z8fB5++GFmzZrFoUOHPOMEg4CnZzfC4IyBq7NwxLDs6OiQemmpqamSp9e4cePQaDRWH0p5D8heP6WkpISenh6SkpLc6ggvyjg1NjbS2NjIxIkTiYmJQRAEuwPn4nqttTeVBGJBLygRhF5LIK+z7uaWs5YzggBmwYJKAYJKJelcCkLvwHnvceKaevt9Kiz427AvHfXXRP+0lpYWgoKCMBqNHD9+HB8fH6usdSBnA0ew9a9ztiTqKFORZ9miWLLBYJDUV2JjY602Je6APFA7Ggx3VLqVjxuIhr/2nCN6enokGTFXy8bOQCSgCIJg1VscSIfz8ccf5/Tp02i1WhYuXMj06dPp6enxBLtBwMPGHGEYKNi5IullGxx1Oh2lpaUATJo0iYCAAMzmXpkrtVpNfHw8iYmJwA/9H61WS0VFhVSqE/spOp2O7u5uKYtwZwlBLgQdGRnZp99he9OT30S0Wq2VU4C4gx4TMQ61X1Bvr06p6BUkFnrLlwplbyBU9/IrELnxFgFUP5AvQQHeWPB2gkUoKm/U1NQQHx9Pdna2FdvWkbOBv7+/VRDsb9Sgvb2doqIigoKCnC7HDQR5lm0ymSgtLaWtrY3k5GTJNUD+frAdOneVuThYlqWI/kY5xCxbZLr6+PjQ0dFBeXn5oNdrC1cIKHIdzrCwML788kvq6+t58MEHuf766ykoKODUqVNotVq39yhHOzxzdiMQYWFhnDlzxu5jgy1j6vV6qZeQmJgoSXL1p3pib4DbYDBQXFxMbW0tQUFBqNVqNBoNFRUVdrKqwQ1CNzc3U1JSQnBwsEMhaFs4EvMVS4tarZbG2ipQqoiMjkNxtkQrWETB8LNBiF5yhTgdreTs+MHZBxWY8VX2T/iRj0LYC9Tieu3R4W1LoXICjzygqNVqysvLMRgMpKenu1w2HgiihFtFRQUTJkwgOTlZCgj21tvZ2UlHRwc1NTVOj0aIJUu1Wi0xad0FeVWgqamJ9PR0qW8m9i9tmZby0qKz/cvBElCam5tZv349TU1NfPDBB8THxwO9G9D58+cP9fJ/tBjFsW50BrsxY8Zw8uRJu4+5GuzEDKm+vp6EhARCQkKsZuWcVT2RW77ExsaSlpZm9Xui3qI4tKvT6ayyKmfGDLRaLRqNBpVKRWZm5pBUK0TIb7qi/NbpE9+SnjUNlcoP4Wx90mI2ofBSIZhN4KU+63iukDQwlQoBhcLIQFSSjo4ONBoNfn5+g7qB9zdqIKqYaDQadDqd5MZdW1s75FKoHGK2GBwcPCCBRr5eW+aiI21Tf39/uru70ev1pKSk9Bm3cAfa29spLCwkLCzMSoHGnpqJuF6xHyjvX9puMsSNhqh40tbWRlpaWp9SsCNYLBb+9a9/8cc//pHHHnuMW2+91TNO4CYo+EHqbzRi1Aa7ofbsjEajpDTh7+9PZmamVK708vJyOsjJd/giKcHe7lXUW7SXVdmOGYgECDEL9PLyklyb3d33E69B7GnJ5bdMmAFVr8qHqtfGRlCqgF4pMYvFjKnHiK6jndbmeqtynW2W0t3dTUlJCd3d3aSkpDh983MWXl5e9PT0UF1dTXR0NDNmzJDko+yVQm1Zls6orohZu16vH3K2aE/bVHwvlZaWEhQUREhICKWlpRQXF/fprw3kFuAIRqMRjUZDd3e3S47tA2lwiizWkpIS9Ho9RqORkJAQYmJisFgsmM3mAbO68vJyVq5cSWxsLAcOHLD6rHjgHngyuxGG/tiYA83ZmUwmqqqqaGhoIC4ujvDwcEmA2NfX16UgJ+7Iw8LCBkWR72/MQKvV0t7ezqlTp+ju7pbcDEQvr6HKYokQaf7BwcF9elq9bx4TFgv02p4rEM7O5CFY8FIIePso8Q0LxtdbKWUpolWO6G7d3d1NZ2cnkyZNGhZ5Ka1WS1FREX5+fn2uYaBSqO0so70sRczaa2pqSEhIGJZrkJcsZ86caZXxylm3oh2Rq6MR8k1ZQkICUVFRbrkGtVotOUf09PRQVFSEWq0mISFBIvJUVVVJ8mPyoO3r6ysNyb/88su8++67vPDCC1x22WWjmiJ/3uDp2Y08hIWFOQx2jjztxNmq2tpaoqOjJWkvcVatoKBAYqiJDDxHw8Wtra0UFxcTEBDQxzfNHVAqlXR0dFBXV0d8fDzR0dEADntV4lrlmeBA6OzsRKPRoFAoBtzh9w6Hn+3D2ZkLs5eliOSTyspK6fUsLy+nvLy8D8FksAox8kzLlWyxv02GqApSV1cnEYxMJhOBgYHExcUREBDgtJaqMzCbzZSVlUmO3vZYnAqFAj8/P/z8/PrM28lLi/ZMaQMDA1EoFBQXFxMYGOj2uUXon4BiK0guBu3Ozk6OHDnCb3/7W7RaLeHh4SxatAiz2TzsgW716tV8+OGHeHt7M2nSJF5//XW7Ixb79u1jxYoVmM1mfv3rX7N27dphXddwo1cubPQGO8UA/m7Om79dQNDr9eTk5PD555/bffybb75h5syZQO8Noa6ujqqqKiIjI4mJiZE+TLaqJ3KGmriL7urqkm6OarWa1tZWvL29SU5Odjv1Wb77jo6OJi4ubsDAJafBi2u2dTeXM+pE7zedTtfv0PlQ0NraikajISQkhMTERKubq5wQI65bXrp1JmhbLBYqKyupra0dNjFicRwCYOLEiVavc2dnJ4BL/VZbiJWBkpISxo8fT2xsrNt6U2LQFgkxXV1dUi9woFEZV6HT6SgoKCA4OJjExESn7YJ0Oh3//d//TV5eHps2bcLX15f8/Hza29u5++67h7SmgfDJJ58wd+5cVCoVa9asAeC5556zOkZUvfn000+JjY1l5syZbN++fUjKT05i2KLRtOkzhIOHvxn4QBcQ4KM8KgjCDLc+6SAxKjM7X19fDAZDv8eIN5OKigrCwsKYMmWK9MF2JO0l30HLd6eiA3ZbWxsBAQEYDAZOnDiBn5+fVVY1WIq2XD7M1ZKoo2FzvV6PVqtFq9VSU1ODXq/HZDJhNpuJiIggKSnJ7QzFrq4uNBoNgiA4zBYdEUzE0q04C2YvaAcEBNDZ2UlpaSlRUVEusfucRX/zbPasfbRarcNSqPjesA0A8pLltGnT3MqyhN6+tcFgoLq6mri4OMaPHw9YS6UNdTRisAQUQRD4+OOPefLJJ1m2bBmbNm2S/obnIJAAcNVVV0n/nzVrFjt37uxzzJEjR0hKSpLGjG699VZ27959ztY4HDj23dGPA3yU7mY7Nbn5+QaNURnsRNgrJwmCgMlk4ujRo5Lho0qlko51RfWkp6eHsrIyOjo6mDRpksOSjFj20uv1VpJNjm52cogzTr6+vm4ridrKTInZYmxsLCEhIZKppzhbJQ/ajkq3/cFoNEr+e4N1DFCr1XZnwUQafHNzM6dPn5YCoF6vp7q6Wnqdh1qak+tAOjN43l/Qth04F8vjoiyZXq8fFi1L6M1ICwoKUKvVTvUvRa9D21EDkZVp2w8EawUUkQjkDOrq6lizZg1ms5m9e/dKQfh8YuvWrSxatKjPz8WNgojY2Fi+/vrrc7k0t0MQhHnnew3DiVEZ7BzZ/LS3t1NaWorJZJKo+WIPQK1WOx3kRKZmU1MTCQkJpKam9vlAO+qjiBR48cah0+kwm81WGUpQUBAWi4WSkhKpXOJudiL8MI8XGhpqlS3aGy4WsyoxaNvz4LMNKGIftKqqiokTJ1rNmrkD4uakpaUFnU7H1KlTCQkJkWj7oqOBSIiRkx+CgoKcZizqdDoKCwvtElxchb1MW3TJKCsrk8YfRM+8wWhv2oPFYqGiooKGhgaHCiv2IK6hv1ED0UVeZFmqVCrGjx8v/S0GKl1aLBbefPNN/vrXv/Lkk09y/fXXD3tf7oorrqCurq7Pz5955hmuu+466f8qlYo77rijz3H22j8e0syFjVEZ7ACppBUUFIRWq6W0tBSlUklycjIajQaLxdLvQLg9iP50NTU1xMXFDUrbUKVSSew0EfKyYltbG4WFhRgMBvz8/AgLC6O9vV3SsHRHWU4suzqjMekoaMsDSn19vZQFigFFLL1GRkZaOXm7C/K5xfj4eKsNhyPavrxM19TURFdXF4DDgGI0GiktLaWjo4OUlBS3j3SAdcnSVsvSEcHEVntzoOpAS0sLRUVFREVFuU3mSz5qICegpKSk4Ovr20d6zJ4VkZeXF4WFhTz88MNkZGRw8ODBYXmN7eGzzz7r9/Ft27axZ88e9u/fbzeIxcbGWglXVFVVERMT4/Z1euA+jEqCCkBubi4rV64kODgYg8FgJe3V1NREfX29RH+X99Xs7fYtFgu1tbVUVlY6TQxxFSaTSZrri4+PJyoqSsoCbcklzjgD2ENPTw8lJSV0dXWRnJw8LPN4zc3NknWQj48PPT09UslLXgodSnYklskiIiKIj48f0t9CHlDE17m7uxtBEDAajURERDB+/HiCgoLc+jcXWZYtLS2kpKS4RASSl0LFLzlTWHyNvby8KC4uxmw2k5qa6nbhbLBWQHFEQJETu8SvRx99lDNnztDe3s4tt9zCtddey+zZs/s8a1zXAAAgAElEQVTM6bkb7777Lk888QSnT5/myJEjzJjRlzuxb98+FixYQFJSEt7e3qhUqj4i9SaTiZSUFPbv3y+Vtd9++20yMjKGdf0MI0FltGNUBruqqiquuuoqFAoFO3fuJDo6GoulV4tRPhAu3+2LvTU5u1IMjvX19YSHhxMfH+92Wra81BcbG8v48eP73Xnb9lDEm7PtoLk8C5QH0sTERCIiItxecukvkMqd2MV1O7vRkKOzs5OioiK8vLxITk4elpt3W1ubpJUZHh5uZe3TH4vVWQwXy9KWKdzQ0EBnZyc+Pj6Ehoa6pRQqhzxYp6WlOR2kBEHg8OHDrF27ll/84hcsWLCAgoICTp48yZIlS0hJSRnSugbC6dOnUSqVLFu2jD/84Q92g11SUhLl5eWkpaVJ5tKbN2+mpqaGX//61+zduxeAvXv3snLlSsxmM0uXLmX9+vXDuvaz8AS7QWLUBbsvvviC1atXM3bsWO6//35+9rOfoVAoXFI9MZvN1NTUUFFRgVKpxMvLS7rRiT21oKCgIQ1ti4SHsrIyIiIimDhx4pBKfXK2ojinJPYje3p6iIyMZOLEiUMW7bWF3JvNlYFq242GSNkXe0TyIKhQKCgtLaW9vZ3k5GS3OwZAb7AW3SpSUlLsMkXl5WYxAMr7l/KNhr1NUWdnJ4WFhfj4+JCcnOwW0WlbiDJfY8aMITExEYVC0SdztWdDNFApVI7m5mY0Gg0xMTHExcU5/X5qa2tjw4YNlJWV8corr5CamjqUSx0S5syZ4zDYAcTHx/Ptt98OixTbEOEJdoPEqAt2RqMRpVLJrbfeil6vZ+HChUyZMoWUlBSnsjLR902lUkmlT+h7o9Nqtej1emlo215G5Qji0HlgYCCJiYlup5bLfdOCg4MJCQmRaPDijc52za5mF4IgUF9fT1lZGdHR0UyYMMEtGYpYVhQ9+Jqbm+nu7sbPz4+xY8cSHBzsNg1L8XyVlZXU1dUxadIkwsPDXd4MiD5x8iAoJ8T4+/vT3t6OVqt1mwecLYxGIyUlJXR2dpKamjrg2Ijt/KWj3po82xYVUCwWi2Rr5QwEQWD37t08++yzPPzwwyxZsuS861kOFOwSEhIYM2YMCoWCZcuWcc8995zjFTqEJ9gNEucl2LW2trJ06VJKSkrw9fVl69atZGZmcubMGRYvXkxdXR1KpZJ77rmHFStWDOocp0+fJj8/n6KiIo4fP05xcTFqtZrJkyeTlZVFdnY2WVlZUuZQW1tLY2MjJpOJpKQkp8sy4k1DLCmKske22YmPjw86nY7i4mIUCgVJSUnD4rclCh37+PiQlJRk94Ykt/IR1yzqQdqu2R7a2trQaDQEBQWRmJg4LBmK3I08ISHBihBjb3BbXLe3t7fTwUrs/UVFRTFhwgS39uTEsmJ1dTXV1dX4+PggCIIVZX8wa7Z3HlG3ND4+nnHjxg3pueTMW1E0AXpHKfR6PbGxscTGxjq95urqalatWkVwcDAvvviiFaNzuOAM03KgYFdTU0NMTAwNDQ1ceeWV/OUvfyEnJ2dY1+0kPMFukDgvwW716tUEBgbyu9/9joKCApYvX87+/fupra2ltraWadOmodVqmT59Ort27XLLoKYgCHR2dnLy5EmOHTvGiRMnOHHiBG1tbdKHdsOGDUydOnXAvtlAkA8UixqWOp0O6LV3CQ8Pd4n67gy6u7spLi6mp6eH5ORklxv9tmvW6XT09PRImpviTbmmpgaz2UxycrLbh87BWpkkOTm5X+cGObnEds22ZUX569zV1WXV+3O3nBs4LlkOtGb510DBt7Ozk4KCAvz9/UlKSnJ7Pxl+IKD4+fkREhIi9TBtS6G2Ducmk4ktW7awbds2Nm7cyLx58y4oav5AwU6OJ554gsDAQH7zm9+cg5UNiAvnRRxhOC/Bbv78+Tz22GNccsklQK8H1aFDh/rs+q677joeeOABrrzyyuFYBh9++CFPPvkkixcvJiIighMnTpCXl0dVVRVjxowhKyuLzMxMpkyZQlpamss7cKPRSHl5Oc3NzSQmJhIcHGy3RyWfr3PU73EEk8kkEQXEwXZ33lQMBgNtbW1UVlZKtjgqlcoqOwkKChpydie/DlfmwBytWZ6diHZJfn5+GI1GyR1iOGTEROWQ1tZWl1iWcrdweYXAVsLL19cXi8UivVapqanDQtd3hoAiX7P49dZbb/H999/T1NREamoqTz31FNnZ2W5nL9uDM0xL6GVb3nDDDYwdO5bly5f30bQUX/ugoCA6Ozu58sor2bBhA/PmXRAz155gN0icl2C3bt06uru7efHFFzly5Ag/+9nP+Prrr5k+fbp0THl5OTk5OeTn5w8bHVmn0+Hr69unMS/2vI4fP86xY8fIy8ujoKAAgLS0NKsyaFhYWJ8bptxhOy4ujpiYGIcZnNy3TMyqbFVL7EmNyVmcA51jsJDPT8nPIe+riUHFYDC4zK4UzyEquIjSVe4OQOI5ysrKCA0NRa1W09nZKbFY5RngYGcZ5QorYqlvqNchZ97KN0miq8W4ceMGtUEaCIMloOj1ep599lm++eYbFixYgF6v5+TJk8ydO5dly5a5bX2O4AzTcufOnZIHXmhoKHq9nq+//prQ0FCJaVlaWsr1118P9G7Cbr/99nPFtHQGnmA3SJyXYNfR0cGKFSs4duwYWVlZFBQUsGXLFqZMmQL0BqFLL72U9evXc8MNNwzHElyG2M84deoUx48f5/jx41IZNDY2VsoCS0pKMBgM3HHHHYPuA9lKjYnjBaLUGPT2tKKiooiPj3f7wDYgzcuFhYWRkJAw4DkEQZAyKnuZq22PCn6g+dsThHYXtFothYWFBAQE2C31DZRROTPLeC5Ylnq9nsLCQry8vEhMTOxDMLE3Z+dqmdxgMFBYWDgoAsoXX3zBunXruPPOO1mxYsWwvCedRX8lysOHD/PEE0/w8ccfA/Dss88C8Nhjj53TNQ4BnmA3SJyzd+TLL7/Ma6+9BvTOp7z++utA7wclISGBhIQEoLf0d+ONN3LHHXdcMIEOflASmTFjhtWHyGKxUF5ezrZt23jssceIiIjAy8uLL774gszMTCkLnDx5stO0f0eqJeKOW6lUEhwcTEtLC01NTZIljrykONisQj7Llp2d7fQsm0KhwMfHBx8fHyu6tnzGTvSy6+npwWw2o1QqiYuLY+zYsW6/OYruDSI70ZHcmre3t13NTWfskvz8/KioqHC5ZOkK5GzRlJQUq3XaqvD09PRIG43GxkarUQ554LYlHskzeNFT0Fk0NTWxfv16mpub2bVrF/Hx8UO+5uHEaNS09MA5nLNgt3z5cpYvXw707ugNBgPe3t5s2bKFnJwcSXborrvuIj09nVWrVp2rpQ0JSqWSxMREQkJC+PLLL0lMTEQQBNra2sjLy+PYsWNs3bqVU6dOYTKZSE5OlgJgdna2U30jvV6PRqPBbDaTmZlpRQyRE0taW1uprKy0IpaIN7iBqPoGg4HS0lK0Wq1brX3kslKiY0BjYyMJCQmo1Wp0Oh2lpaXSML8tI9TVbE8QBKqqqqiqqiIhIYG0tDSXA78jPUg587a4uJi2tjbUajXBwcGSae5Q5y/laG1tpaioiMjIyAGl6RQKhSTkbOu+IG42RA1LOSFGrVbT0NBAaGioS7JuFouFHTt2sGnTJtatW8eiRYvOyTiBM0zL/uDRtPzx4ryUMQ8fPszixYvx8vJi8uTJ/P3vf2fMmDEcPHiQ2bNnk5WVJX1wfv/735ObmzscyzjnMBqNnD59mmPHjkll0IaGBqKjo6UyaHZ2NsnJyahUKhobGyXhZVtXhYFgqwxjS4YR//Xy8pL6i+50qJZDPpPXn2qIbf9SPq82kGEu/OCTJ5Zeh4MUYVuyVKvVfeYv5SVnZ90t5DAYDBQVFWE0GklLSxsWpRi9Xi8F7MDAQIxGo0NCjO1rXVZWxsMPP0xcXBzPP/+8S+/LcwFPGdMDexh1Q+UjDaLivZwMU1RUJPVhli5dyiWXXEJ2djaBgYFDCkTykmJHRwetra3o9XopGwgJCRmS7549tLe3o9FoCAgIYNKkSS73s2xlsMRhfrlqibe3N3V1dQiCQEpKSr/jCoOFyBZ1tmQpd7eQ61f2RzyyLScOh6wbOCag2ErRica5Xl5e5OfnU19fT2NjI4cOHWLTpk3MmTPnnGRFLS0tLFq0SJol/Ne//mVXRSc+Pp6goCDKysqYMGEC33//fZ9jzqOmpbvgCXaDhCfYXWDo7OwkJyeHa6+9lksuuYSioiLy8vI4efIkXV1dJCYmSkzQ7OzsQbEwOzo6KCoqwt/fXyq7yoklct89eUblSqbU09Mjzf2lpKS4fSbPbDbT0dFBRUUFbW1teHt7o1QqrUga7gjc7mRZ2hKP5HJj3t7e6HQ6goODh033c7AEFJPJxAcffMCWLVswGAxS+Xnx4sXnpN3w6KOPEhYWxtq1a9m4cSOtra19nMMBIiMj8fLyoqWlhdDQUKZOncrHH398oWhaugueYDdIeILdBQitVmuXUGEymdBoNFIGmJeXR01NDWPHjpXIMFOmTCE1NdVuBiUOnhsMBpKTk/v1yJNnJraOC7YqK/Kbv1wrc7hEp+VyaOPGjZOkyhwFk8GWFMWhbT8/P0kB390Q/6bt7e2Eh4djMpn6sCsHKt8OhKEQULRaLU8//TR5eXm88sorZGZmSs/Z1dU1LCpAtkhNTeXAgQNER0dTW1vLnDlzKCws7HPcBaxn6U54gt0g4Ql2Ixxi5iGWQU+cOEFBQQFKpZL09HQyMzNJSUnho48+Iicnh9mzZw9K/1E8l1xlRdTa9Pb2lm56zc3NxMTEMHHixGEhLMh7ZklJSU7pijoK3LaGuWJ/Sl6yHK6hbXkfc+LEiURHR1v9TWzLt6J0l6skHp1OR0FBAUFBQUyaNMnpvqEgCHz88cc88cQT3HvvvSxbtuycDIbbQ2hoKG1tbdL3Y8aMobW1tc9xF7CepTvhCXaDhCfYjUKIotUnT55k8+bNfPjhh6Snp9PR0UFcXBxZWVlSGTQ+Pn7IQUk0BxUZgd3d3QDSTdl2vm4wMJlMlJaW0tbW5haav1zYW54FWiwWjEYjY8eOJS4uzu0+dvBDwPb19ZVILs5CTuKR2yWJotPy8YKKigqXLXgA6urqePTRRxEEgT//+c+MHz9+MJfpEvpjWf7qV79yKthdwHqW7oQn2A0So9ap/McMhUKBv78/6enpxMTEoNFoGDNmDBaLhdLSUmkkYvv27VRUVBAcHCwFwKysLCZPnuwUfd5gMFBcXExXVxeTJ0+2uqHKKe/ifJ0rzEoRcoWVCRMmkJyc7JayqPga+fv7ExUVhU6nkzLGyMhIuru7qampsWuYa6986wyGYtgqYiAXdq1WS1VVFe3t7ajVasLCwmhtbcVoNA4o62axWNi2bRubN2/mqaeeYuHCheeMlt+fc3hUVBS1tbVSGdNRGVZ0Co+MjOT666/nyJEjozHYeTBIeDK7HzkEQaClpYW8vDxJGeb06dOS2LM4D5iVlSX137q7u6msrKS5udmlcQX54LMts1JelhN7au3t7RQVFREcHDxsCivyjNFRyVJevpWPF8gNc0UhZEdZoOiwEBMT4zbDVlvYElBE0out1JiPj4+07u7ubqKjo6moqODhhx8mMzOTZ555ZlhKtyL27dvHihUrMJvN/PrXv+6jTSkIAitWrGDv3r34+/szdepUJk+eLBFUWlpaeP75561+5wLXs3QnPJndIDFqg93q1av58MMP8fb2ZtKkSbz++ut2d9IDffB+rDAYDHz//fdWZJjGxka8vb1paWlhyZIl/OIXv5BmAocC255aR0eHVAodN24cY8eOHXQ25QjyntlgNTntGebKSTxiP628vByFQkFKSsqwOCy4QkARZd3ENb/66qt8+OGHNDc3M2vWLC6//HLmzZtHVlaW29cJvdltSkoKn376KbGxscycOZPt27dbOZvs3buXv/zlL+zdu5evv/6a5cuXExoaSmVlJRMmTODdd98lLCzMimXpip5lYWEh3t7ekmrTCIMn2A0SozbYffLJJ8ydOxeVSsWaNWsA+tCVnfngedALi8XCwoULUalUXHvttZw5c4a8vDzJk1A+FJ+ZmUlAQIDLwcNisVBVVSUNuAcEBFgJTsuFm+XZlKtZkliyHA6Wpaho09HRQU1NDR0dHajV6j5lUHeZzw6FgHL48GHWrFnDDTfcwIoVKygtLeXEiRNMmDBh2Mp/zgx1L1u2jDlz5nDbbbcB1mxMVyEIgtX7sLq6mrVr17J+/XrS0tKGcinnC55gN0iM2p7dVVddJf1/1qxZ7Ny5s88xR44cISkpicTERABuvfVWdu/e7Ql2dqBUKnn55ZetdAWh92bS0dEhZX9vv/02+fn5dHd3M2nSJKkPOGXKFMaNG+fwBi8KT4eHhzNz5kypHBgYGGgl2SXPSioqKuyauDrqTTlTshwqlEolJpOJM2fOEB4ezk9+8hO8vLysbIfEdcsNcx3pVjqCMxY8jtDW1saGDRsoLy9n+/btpKSkAEgl6+GEM9qU9o6prq4eVLATA53Y8xs/fjwNDQ385z//IS0trU8w9GD0YtQGOzm2bt3KokWL+vzcmQ+esx5ZonqDl5cXKpWKb7/91r0XcQHANtBB780kJCSEnJwcq2zAZDJRWFjIsWPH+Oqrr/jb3/5GbW0tERERVmxQhULB559/Tk5OjlPC0/aEm+VkmKamJsrLyzEYDBJDMTAwEIPBIFkuuYvkYguDwYBGo6Gnp4esrCwrJRdvb2/Gjh1rJa0lN3K11a3sT9dUroAyc+ZMp69FEAR27drFxo0bWbVqFa+++uo50bO0XYMtbNc/VP1Ks9ls1TvdsWMHH330EVlZWTzyyCPcc889fPfddxiNxmHpA3twYWJEBztnRGGfeeYZVCoVd9xxR5/jnPlQZWZm8v777zvlx/Wf//xntA+0Og2VSkVGRgYZGRn88pe/BHpf77q6Oo4fP86RI0fYtGkT9fX1TJ48mVOnTln5BIaEhDh9gxMJLvIheZEM09DQQElJCdDLZBRLi/JgMtSeoyAI1NTUUFlZSWJiotOmsPJ1y7MWObOyublZyl59fX0lQk9GRka/ogC2qKqq4pFHHiEkJIT9+/e7NFjuTsTGxnLmzBmrdYksSleOcQRBEKRA99lnn5Gdnc2iRYuYPHkyS5YsITY2loKCAtRqNWq1GovFcs4DvgfnByM62PVHVwbYtm0be/bsYf/+/XZvPs58qNLT092zWA9QKBRER0cTHR3NyZMnueeee7j33nsxGo3k5+dz7Ngxdu3axVNPPYVWqyU+Pl7qA2ZnZ0tKKc5AVHJpb2+Xgqf4c7GcWFtbi06nw2w299GsdNa5QKvVUlBQQHBwsEuuAf1BtEoSs0CRgFJRUSE50RcVFTllmGsymXjttdd48803ee6557j66quHrWw3ENnrwIEDXHfddXR3dzN58mRuvvlmdu3axdtvv2113IIFC3jppZe49dZb+frrrwkJCRmwhCkGLYVCwaFDh1i7di2TJk1i/fr1PPbYYyxcuJBNmzaRn5/Pzp07aWtr45577nE6iHow8jGig11/2LdvH8899xxffPGFQ2HgmTNnotFoJDX+d955p88Hz1koFAquuuqq0a7e4DY8+uij0v+9vb256KKLuOiii6Sfmc1mSktLJYeIf/zjH5w5c4aQkBCrMmh6eroVS1PMHsvLy+2WLL28vAgNDe3jBScOmHd0dFBdXd3HxVz8VwwkJpOJkpISOjo6SEtLcynLcgVyAspFF11kFUxt5+uampokd4tXX32VsLAwDhw4wJw5czh06NCwSnuZzWaWL19uRfZasGBBn/737Nmzuf/++1m5ciVvvfUWS5cuJSMjg82bNwNw7733kpuby969e0lKSsLf31/yvrQHseemVCoxGAwIgsD27dt5/PHHueqqq/jJT37CunXruOiii5g9ezazZ89GEAT27dvnUsbowcjHqGVjJiUl0dPTI+2OZ82axebNm+2Kwt50002YTCbGjBlj5QUmL4f2ZxsCzqk3ONv/84xD2IcgCDQ3N0vzgHl5eZw+fVqaK4uOjubzzz/nt7/9LZdffvmQWZbiaIHcucBisaBSqejq6mLcuHHEx8c7TSpxBUMhoOh0On77299y6tQpJkyYQG1tLa2trWzdupVp06a5fa3gHMvywIED/OEPf2DPnj1uOaecXHLw4EF+85vfsGHDBubOncvRo0dZvnw5jzzyCHv27MHX15dt27ZJvzt//nweeOABrrnmmpFGUhkxC73QMGozu+LiYrs/j4mJkQIdQG5uLl1dXUM+nzPqDc70/5zdIf8YoVAoCA8P54orruCKK64Aem947e3tPPjgg+zZs4ef//zn/PnPf+aJJ55g/PjxEhM0MzOTSZMmuST9JSqQiGSYrq4uSXc0MTERvV5Pfn6+VTlRTioZ7A1UTkCZMWOG06VbQRA4cOAA69evZ/Hixbz88stSJigIgt0etbvgrAP44cOHmTJlCjExMfzhD38YlLWOvGTZ3t7O0aNHefzxx9m4cSNz5swB4KuvvmLhwoXceeedBAUFccMNN7BkyRIuu+wyAMniCjzmrT8WjNpgdy5hq97wySefsGHDhj7HOdP/84xDuAbRkPbaa69l27ZtUmCwWCxUVlZKAtnvvfceJSUlBAQESA4R2dnZZGRkDChZZrFYKCsro6mpidTU1D7iBLblxIaGBkm02dYst7+enmjaajKZmDp1qksD6E1NTaxbt47W1lZ27dpFfHx8n9dpOG/qzpC9pk2bRkVFBYGBgezdu5eFCxei0WhcPpf4N96+fTtbtmxh8eLFtLa2UlFRAfS6eyiVSmpra9m1axeffvopq1evlsYqSktLmT17tjTH58GPA55gNwA++OADHnzwQRobG5k/f75dj6z6+vo+6g2DlSlydofswQ9QqVR9RkuUSiXx8fHEx8ezcOFC4IcsUJRGe/PNNzl16hQ9PT0kJSVJAXDKlCmSBNqJEyekkuXMmTPtZlmiALavr68VG1cUbdZqtdTV1VFcXCyRYWx1Nmtra6msrHTZgsdisfDOO+/wpz/9ifXr13PLLbecF3ahM2QveSk2NzeX+++/n6ampgEZzCaTCZVKJZUbtVotW7Zs4bPPPuOdd94hIiKC1tZWjh49yrx584iKiiInJweLxcKTTz7JmjVruPXWW6XnS0xM5Pe//72brtyDkQJPsBsA119/vRTI5JCXQxMTE8nLywN6xyG2b9/O9u3brY6X9//6g7MzRq66N4/m+T9noVAoCA0N5dJLL+XSSy+Vfm40GikoKOD48eMcPHiQl19+maqqKoxGI5GRkdx9990EBwdjNptdCiSORJvlbguVlZV0dHSgUqkIDw/HaDTS0dHRr86miLKyMlauXMnEiRP54osvrGYPzzWcIXvV1dVJm4gjR45gsVis5g7t4fvvv+fyyy/ntdde42c/+xlhYWG0tLRQXV1NcXGx9Nr+/Oc/p7q6mu3bt7Ny5UqmT5/O9OnTefDBB6XerWfM4McNT7BzMwYahxgIzs4Ybdy4kcsvv1wSx924caNd92bwzP8NBLVaLTE877zzTg4dOsTy5ctZt24dY8eO5fjx43z00UdoNBrUajUZGRlWLhHBwcFOlwhFtwUfHx+0Wi0Wi4UZM2bg5+cnEWHOnDmDTqfro7Di5+eHv78/RqORl156iffee48XXniBOXPmDGuJcunSpezZs4fIyEjy8/P7PC4IAqtWraK7u5u0tDQiIiK47777+rAsd+7cyV//+ldUKhV+fn688847A667rq6Onp4ePv/8cz744ANee+01Jk6cyC9/+UtaW1slRue0adMoKyvj3XffZfbs2UyfPh3oZfqKQ+aeQPfjxqhlY17I6I/ZaTKZSElJYf/+/YwfP56ZM2fy9ttv92nke9ybhw96vR6gj5qLIAh0dnZy8uRJySj3xIkT6HQ6EhISpIH47Ozsfp0N5ASU/o4TdTbFLPDf//43W7ZswWAwMHHiRO6++24uvvjiYdd4/PLLLwkMDGTx4sV2g52tcPOKFSuGVHoX70kKhYLOzk5mzpzJiy++yI4dO1AoFKxevZr09HT+8Y9/cPDgQZYvX052djaVlZWUl5ePdlsfD5tmkPBsdc4hPvjgA2JjYzl8+DDz58/n6quvBnrHFnJzc4He/tNLL73E1VdfTXp6Orfccotdxlp9fb00aBsdHU1DQ4Pdc4rzf9OnT+fVV1+1emzfvn2kpqaSlJTExo0b+/yuIAg89NBDJCUlkZ2dzXfffTek6x8p8PPzsytbJpJhLr74Yu6//342b97MoUOHOHbsGM8//zwZGRl89913rFq1iosvvphrrrmG1atX8+abb5KXl0dpaSkvvPACZ86cYerUqQMOyYsEF3EQv7a2lgkTJvDWW2+xYcMGGhoa2LFjx3C+FADk5OT0WyLdvXs3ixcvRqFQMGvWLNra2qitrR30+UQyTX5+PgEBAVx33XW0tbXx+uuvExkZyfLlyzlw4AALFy4kMjJSel/LBayHk3nqwQiFSEl28OXBecTll18uZGRk9PnatWuXEBISYnVsaGio3eeorq4WBEEQ6uvrhezsbOGLL74QBEEQTCaTkJiYKJSUlAg9PT1Cdna2cOrUKavf/fe//y3MmzdPsFgswuHDh4Wf/vSnw3CVoxMWi0VoaGgQPvnkE+HZZ58VLrroIiE0NFSYPXu2cPvttwu///3vhX//+99CZWWloNPphM7OTrtfOp1O2Llzp5CVlSW88sorgslkOi/XU1ZWJmRkZNh9bP78+cL//u//St/PnTtX+Oabb4Z0vm+++UbIysoSdDqdsH79emHbtm3Cvn37hIkTJwo333yzMGnSJGHr1q3C9u3bhYMHDw7pXCMMA92zPV8Ovjw9uwsYw/F5ofMAAAl3SURBVOne7MyIg6Md+2DU539sUCgUREREcOWVV9Le3s6sWbP45JNPUKvVnDp1iuPHj7N37142btxIa2srcXFxVtqgCQkJNDY2snr1ahQKBR999BHjx48/35dlF8IQhZvleOutt5g/fz5ms5krr7ySgIAApk2bxk033cT06dN54403mDNnDv/85z/R6/X84he/GFZlGA9GDzzBboRiwYIFbNu2jbVr17Jt2za7TM/+5v/OtdXKjxk33XQTN910k/T9jBkzrPq1FouF8vJySRnmX//6FxqNhqamJv72t7+xcOHCC3rweSjCzXJ0dHTw0Ucf8Z///IfKykppJjE3N5c777yT+++/X5KUu+222zyEEw9cgifYjVCsXbuWW265hb///e+SezPg9PyfM7txV3bszooAi+7QN9xwg93B+x8jREWWxMREbrjhBuAHMkxgYOB5Xt3AGIxwsz0EBwfzz3/+k8bGRtauXcvrr7/O2rVrGTduHE1NTVbvPTHQCSNL6suD8whPsBuhGDt2LPv37+/zc0fzf7Zwp9WKKyLA7tJFHO0QyTDDiYFGCsQNilKplHRBY2NjefLJJzEajYDrws0DQRAEIiIiuOuuu/Dx8SEjI4OPPvqI0tJSuyQZT6DzwFl4gt2PFM4MATu7Y/dInI1MLFmyhAceeIDFixc7PMaZDYpCoeDll192y5rE4PXVV18REBDAnXfeyaJFi4Ys6u2BB56i9wiEyC4aChyNOGzevFkaBM7NzSUxMZGkpCTuvvtuXnnlFbvP5ai3ZwtRBPiaa67h1KlTQ1q/B0PHQCMF5xMhISEEBARYlSlNJtN5XpUHIxmezG4EwlHpxmKxkJ+fj8ViYerUqQM+T25urjTfJ+Lee++1Oo8zO3ZnenuuiAA7o9ixYsUK9u7di7+/P2+88cawWdf82OEOl4LBYNGiRVIZV61WA7jFGNeDHy88md0IQ2NjI6+88gp1dXVAb4ATodFouP322yXmn/iYOzLB/uCsCLB488rNzcVoNNLU1GT3+ZYsWcK+ffscnk+U7tJoNLz66qvcd999brgKD2whblDy8vJ48MEHJUHtcwHxvSJ/f3vgwVDgCXYjDKGhoRw8eJCjR48C8N5777FmzRrKy8vZvXs3AQEBXHvttZw8eVJirNnauwiCgMVicVsAlPf/DAYD77zzDgsWLLA6pq6uTjrfQCLA51qxwwP7cGWDMlzwjBd44C543kkjDGq1mtbWVskd+y9/+QuzZs2iqqqK7777jmeeeQa9Xk9paSnQa2L7f//3f5w6dcrKrFI0vxRhsVgwm82D2kk70//buXMnmZmZTJkyhYceesgpEWBHcLZHKGLp0qVERkaSmZlp9/EDBw4QEhLC1KlTmTp1Kk899dSg1nUh4MyZM1x22WWkp6eTkZHBn/70pz7HCDIZuHnz5klaoLZwZYPigQcXOjxF8BGInJwc6uvrefvtt4mJiWHhwoXcfPPN3HXXXVxxxRU8//zz0o68tLSURx99lKSkJBobG7n55psJCgrCYDAQFhZGbm4ufn5+Q95BD9T/e+CBB3jggQeGdA4Rrip2uIt1OBKgUql44YUXmDZtGlqtlunTp3PllVdaMWPFMvCMGTP49NNPaWlpsTtSMBiXAg88uFDhCXYjEPPnz2fp0qWMGzeOxx9/nBMnTvD+++8TExNDe3s7iYmJaDQaLr/8ctra2vDy8uLNN9/E39+fDz74gIceeoj/+q//4uDBg1xyySX85je/4fvvv2fChAmsW7eO1NTUC9r7y1XFjpycHMrLy8/Bys4/RNFogKCgINLT06murrYrAyc6dcsdNORw5wbFAw/ONy7Mu5kH/UIQBBoaGkhNTSUzM5M33niDe++9l3HjxrFjxw4+//xzSfqrpqaGq6++WvJBa2hoYPr06Tz11FNs27aNqKgonn76af7xj3+Qm5srlR3/53/+h9deew2DwQD0uix0dnaet2uWY8GCBbz55psIgsBXX301aMUOOUbjWER5eTnHjh2TJLZEuFoG9sCD0QBPZjeCIM4cFRYWMnfuXFauXMmOHTs4ffo0e/bskajZu3fv5vXXX8dgMNDc3My4ceOAXu3B5uZmLr74YqBX+aSqqoqnn34arVZLZGQkO3bs4I9//CPXXHMNK1as4O677wbgoYceYvbs2edkp3/bbbdx4MABmpqahl2xA1wbi4DevtjixYupq6tDqVRyzz33sGLFCqtjzvd4hE6n48Ybb2TTpk0EBwf3WZstPOVJD0Y7PMFuBKGnp4eHHnqIo0eP8sQTTxAXF8ddd93FjTfeiEqlwmg0olar8fX1JTo6mvfff5/GxkaphNXa2kpbWxtTpkwBoKysjD/96U9ERETwyCOP8MILL5Ceng6A0WjE19cXgE8++YSysrJz4p0GsH379n4fd6diB2AVDHJzc7n//vtpampyaHjrSl9Mo9Hw9ddfc9999w3J0NQVGI1GbrzxRu644w5Ja1MOdwk3e+DBSIIn2I0g+Pj48Ktf/YrbbrvNyo05NDQU+GH49uqrryYnJ4eOjg6ioqKIj48Heh2ya2pqJDHo7u5uuru7Wbx4MWlpaQQGBjJhwgQAxowZwyWXXMJLL71EbW0ty5YtA7ige3mDRV1dHVFRUSgUCqdYh670xc61PZIgCNx1112kp6ezatUqu8e4S7jZAw9GEhTDOWzswYUHhUIRA7QKgqA/+/1LwFxgD/AA8DtBEP7n7GPPAcuBR4GtgiB0n59VDw0KhWI7MAcIB+qB3wFqAEEQNisUigeA+wAToAdWCYJwyMnnjge+BDIFQeiQ/XwPsFEQhINnv98PrBEE4Vv3XJXD9VwC/C9wEhDnSNYBE0C6XgXwEjAP6AL+a7jX5YEH5xuezG6UQ6FQKATZjkYQhBr544IgPKBQKMYD44By4HPZwz1AIbBPEIRu2+caKRAE4bYBHn+J3pu/S1AoFIHAe8BKeaATH7Z3KlfP4SrOBtd+G3Bn/4bLh3stHnhwIcET7EY5nAlOgiBUA9XAUQCFQqEUBMEC5ABP0RsEnXquHwsUCoWa3kD3T0EQ3rdzSBUQJ/s+Fqixc5wHHnhwDjC6mi8eDBqKXojvh2sUCkUlkC8Iwu6zgc+DszhbBvw7cFoQhBcdHPb/gMVnX9dZQLsgCB5NMw88OE/w9Ow8sAuFQjEWMAqC0DFSy5fDBU9fzAMPRh48wc4DDzzwwINRD08Z0wMPPPDAg1GP/w/EEAet1HIzAAAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# -*- coding: utf-8 -*-\n", "\"\"\"\n", "Beispiel für ein 3D-Plot. Speichere das Skript ab als 3dplot.py und rufe dieses \n", "über die Windows-Konsole (Windostaste>cmd) auf mit \"python 3dplot.py\". Es öffnet sich ein Fenster\n", "mit dem 3D-Plot.\n", "\"\"\"\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from mpl_toolkits.mplot3d import Axes3D\n", "from matplotlib import cm\n", "from matplotlib.ticker import LinearLocator, FormatStrFormatter\n", "\n", "xArray=np.linspace(-2, 2, 90)\n", "yArray=np.linspace(-2, 2, 110)\n", "\n", "### Initialisierung, d.h. es werden Array mit Nullen (zeros) erzeugt\n", "zMatrix = np.zeros((yArray.size, xArray.size))\n", "\n", "for x in range(xArray.size):\n", " a = xArray[x]\n", " for y in range(yArray.size):\n", " b = yArray[y]\n", "#…Berechnungscode….Anfang\n", " berechneteDaten = 500*a*b*np.exp(-a**2-b**2)\n", "#…Berechnungscode….Ende\n", "\n", " zMatrix[y,x]= berechneteDaten \n", " \n", "fig = plt.figure(2, figsize=(8,4))\n", "ax = fig.gca(projection='3d')\n", "X, Y = np.meshgrid(xArray, yArray)\n", "surf = ax.plot_surface(X, Y, zMatrix, \\\n", " rstride=1, cstride=1,\\\n", " cmap=cm.Blues, linewidth=0.2)\n", "ax.set_xlabel('xArray')\n", "ax.set_ylabel('yArray')\n", "ax.set_zlabel('z-Achse')\n", "ax.zaxis.set_major_locator(LinearLocator(5)) # Definiert Anzahl Teilstriche\n", "ax.zaxis.set_major_formatter(FormatStrFormatter('%.f')) # Formatierung Zahl\n", "fig.colorbar(surf, shrink=0.5, aspect=5)\n", "ax.view_init(azim=29, elev=29)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Alternativ kann auch \"Contour\" als Plot verwendet werden:" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(3, figsize=(8,6))\n", "X, Y = np.meshgrid(xArray, yArray)\n", "CS = plt.contour(X, Y, zMatrix, 15) # 15 Linien\n", "plt.clabel(CS, inline=1, fontsize=10, fmt='%.f')\n", "plt.title('Fantasiebeispiel einer Funktion')\n", "plt.xlabel('x Achse')\n", "plt.ylabel('y Achse')\n", "plt.grid(which='both', linestyle='--')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "# Funktionen in Python\n", "Für die Sonnenstandsberechnung benötigen wir trigonometrische Funktionen (Sinus, Kosinus,...). Diese Funktionen sind in der numpy Bibliothek enthalten, jedoch rechnen diese mit Radiant und wir werden mit Grad rechnen. Um nicht jedesmal umrechnen zu müssen, bauen wir uns unsere eigene Funktionen mit Grad:" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [], "source": [ "def sin(arg):\n", " y = np.sin(np.deg2rad(arg))\n", " return y" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "\"def\" zeigt an, dass wir eine Funktion definieren mit dem frei wählbarem Namen \"sin(arg)\". Mit den Variablennamen in Klammer definieren wir wieviel Variablen der Funktion übergeben werden. Anschliessend folgt der Code, welcher die Funktion ausführt. Am Ende definieren wir den Wert welcher zurück gegeben wird mit \"return\". Versuche dies im Editor und gib die Funktion ein. Teste anschliessend \"sin(45)\".\n", "\n", "### Lambda-Operator\n", "Die \"def\" zur Funktionsdefinition ist uns geholfen, jedoch benötigen wir 3 Zeilen Code um dies zu definieren. Dies geht in einer Zeile mit dem Lambda-Operator. Der Aufbau ist wie folgt am Beispiel $y = {b}^{e}$ als Funktion y = hoch(b,e) beschrieben." ] }, { "cell_type": "code", "execution_count": 75, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [], "source": [ "hoch = lambda b, e : b ** e" ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [ { "data": { "text/plain": [ "8" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hoch(2,3)" ] }, { "cell_type": "markdown", "metadata": { "hideCode": false, "hidePrompt": false }, "source": [ "Zuerst kommt der Funktionsname \"hoch\", ist gleich lambda. Nun weiss Python das hoch = keine Variabel ist, sondern dass eine Funktion definiert wird. Es folgen die Argumente getrennt duch Komma, anschliessend ein Doppelpunkt und der Ausdruck für die Berechnung. Vorteil des Lambda-Operator ist eine kompakte Schreibweise. \n", "\n", "Für die Sonnenstandsberechnung benötigen wir angesprochen Trigonometrische Funktionen (Sinus, Kosinus,...), welche mit dem Lambda-Operator wie folgt aussehen:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "hideCode": false, "hidePrompt": false }, "outputs": [], "source": [ "cos = lambda arg : np.cos(np.deg2rad(arg))\n", "sin = lambda arg : np.sin(np.deg2rad(arg))\n", "acos = lambda arg : np.rad2deg(np.arccos(arg))\n", "asin = lambda arg : np.rad2deg(np.arcsin(arg))" ] } ], "metadata": { "anaconda-cloud": {}, "celltoolbar": "Hide code", "hide_code_all_hidden": true, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.7" } }, "nbformat": 4, "nbformat_minor": 1 }