From 7f2a0d39f9da322b69d65e61d99bdf82805e0cf1 Mon Sep 17 00:00:00 2001 From: Malte Woidt <m.woidt@tu-braunschweig.de> Date: Tue, 22 Nov 2022 19:49:04 +0100 Subject: [PATCH] Uebung 04 --- Uebung04/Grundlagen_Matplotlib.ipynb | 390 +++++++++++++++++++++++++++ Uebung04/Uebung04.ipynb | 275 +++++++++++++++++++ Uebung04/anatomy.webp | Bin 0 -> 65490 bytes 3 files changed, 665 insertions(+) create mode 100644 Uebung04/Grundlagen_Matplotlib.ipynb create mode 100644 Uebung04/Uebung04.ipynb create mode 100644 Uebung04/anatomy.webp diff --git a/Uebung04/Grundlagen_Matplotlib.ipynb b/Uebung04/Grundlagen_Matplotlib.ipynb new file mode 100644 index 0000000..28d6858 --- /dev/null +++ b/Uebung04/Grundlagen_Matplotlib.ipynb @@ -0,0 +1,390 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "ebd6b03b-7ef5-40a3-a47d-637b11ac1795", + "metadata": {}, + "source": [ + "### **Einleitendes Thema - Zeichnen mit Matplotlib**\n", + "Diagramme erstellen ist eine Aufgabe, die bei wissenschaftlicher Datenauswertung häufig vorkommt. Du hast bestimmt schon einmal Diagramme z.B. in Excel aus Tabellen erstellt. Auch in Python gibt es Module zum erstellen von Diagrammen. *Matplotlib* ist sicherlich das verbreitetste Werkzeug für diesen Zweck. Das erstellen von Diagrammen mit Python bietet dir mehrere Vorteile gegenüber anderen Ansätzen. Durch den Programmier-Ansatz kannst du Diagramme mit etwas Übung sehr schnell formatieren und die Erstellung von Diagrammen automatisieren. Dadurch kannst du z.B. ein einheitliches Aussehen erreichen. Falls du Dinge wie die Farbgebung verändern möchtest, kannst du einfach alle deine Diagramme automatisch erneut erstellen und hast mit Matplotlib generell eine riesige Auswahl an gestaltungsmöglichkeiten. Wenn du wissenschaftliche Artikel im Bereich Maschinenbau ließt, ist die Wahrscheinlichkeit sehr hoch, dass die Diagramme in diesen Artikeln mit Matplotlib erstellt wurden.\\\n", + "In diesem Grundlagen-Dokument ist eine kurze Einleitung in Matplotlib und seine Programmierschnittstellen beschrieben. Daneben gibt es noch viel mehr zu entdecken. Falls du ein Diagramm aus Daten generieren möchtest und eine Idee hast wie es aussehen soll, allerdings keine Idee wie du es umsetzen sollst, ist es immer eine gute Idee die Beispiele von Matplotlib anzuschauen *https://matplotlib.org/stable/gallery/index.html*. Hier findest du viele Beispieldiagramme und Quelltext, der diese Diagramme erstellt. \n" + ] + }, + { + "cell_type": "markdown", + "id": "0d218d73-2216-4e34-840d-b87dbecc7b2c", + "metadata": {}, + "source": [ + "### **Kompaktes Fallbeispiel - Eine Kurve zeichnen**" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "adecfb0a-1ecd-4fec-a107-6ab85d29a581", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt #pyplot ist ein Modul innerhalb von matplotlib, dass die meißtgenutzten Funktionalitäten zusammenfasst. Wir Importieren es unter dem Namen plt, da der name sonst matplotlib.pyplot wäre, was etwas lang ist\n", + "%matplotlib inline\n", + "#Diese Zeile weißt matplotlib an, die Grafiken direkt in Jupyter-Notebook auszugeben. Wird bei manchen älteren Versionen von Jupyter-Notebooks zwingend benötigt.\n", + "x=[0,1,2,3,4,5]\n", + "y=[10,2,4,5,1,2] #X und Y Daten für eine einfache Kurve.\n", + "plt.plot(x,y,\"rx-\")#Zeichnet ein X-Y-Diagramm. Das \"rx-\" bedeutet: Die Kurve ist rot. Die Punkte werden mit einem \"X\"-markiert. Die Punkte werden mit einer Line verbunden\n", + "plt.xlabel(\"X\")\n", + "plt.ylabel(\"Werte\")\n", + "plt.title(\"Ein Titel\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "8d7ad515-6341-453c-8fd3-51e5eb2808a6", + "metadata": {}, + "source": [ + "### **Übersicht Matplotlib**\n", + "Matplotlib ist ein sehr umfangreiches Modul, das fast endlose Möglichkeiten bietet Daten zu visualisieren. Der Schwerpunkt liegt auf 2-Dimensionalen Darstellungen wie Kurvendiagrammen, Balkendiagrammen, Tortendiagrammen, Konturdiagrammen und vielem mehr. Es ist auch möglich einfache 3D-Diagramme zu erstellen. Darüber hinaus können statische Diagramme in diversen Dateiformaten abgespeichert werden, um sie z.B. in Artikel oder Berichte einzufügen. Es ist auch möglich interaktive Diagramme zu erstellen, was in diesem Notebook allerdings nicht gezeigt wird.\\\n", + "Prinzipiell bietet Matplotlib zwei Programmierschnitstellen. Eine sogenannte implizite Schnittstelle, die sich stark an das Programm *matlab* anlehnt. Diese Schnittstelle ist einfacher zu bedienen, bietet allerdings auch einen kleineren Funktionsumfang. Sie wird vor allem für einfache Diagramme verwendet um schnell etwas darzustellen.\\\n", + "Die zweite Schnittstelle ist eine objektorientierte Schnittstelle, die bei einfachen Diagrammen etwas mehr Schreibarbeit erfordert, allerdings mehr Kontrolle über die Darstellung bietet und für kompliziertere Diagramme oft die bessere Wahl darstellt.\\\n", + "Beide Schnittstellen bauen auf der selben Logik auf, die im folgenden kurz beschrieben wird:\n", + "#### Grundlegende Begriffe\n", + "Die Grafik beschreibt die grundlegenden Komponenten einer Grafik in Matplotlib.\n", + "<img src='anatomy.webp' width=\"400\" height=\"400\">\n", + "##### Figure\n", + "Die *Figure* ist eine komplette Grafik. Man kann eine komplette Grafik anzeigen oder als Datei speichern, Sie kann aus einem oder mehreren Diagrammen bestehen. Die Diagramme heißen bei Matplotlib *Axes*. Die Diagramme sind dabei innerhalb der *Figure* in einem Raster angeordnet. Die *Figue* bietet sozusagen die Leinwand, auf der die Diagramme gezeichnet werden.\n", + "##### Axes\n", + "Ist ein Diagramm. Ein Diagramm besteht standardmäßig aus zwei (oder im Falle einer 3D-Grafik drei) *Axis* Objekten. Also den Koordinatenaxen. Es ist auch möglich ein Diagramm mit zwei Y-Achsen etc. zu zeichnen. Das Diagramm verfügt weiterhin optional über einen Titel bzw. eine Überschrift, Achsbeschriftungen für jede Achse, ein Hintergrundgitter und eine Legende. In einem Diagramm bzw. *Axes*-Objekt können mehrere Datenkurven eingezeichnet werden. Bei mehreren Kurven ist eine Legende dann sinnvoll. \n", + "##### Axis\n", + "Eine Koordinatenachse. Jedes Diagramm kann mehrere Axen enthalten. Die *Axis*-Objekte legen fest, wie die Achsen unterteilt sind. Z.b. logarithmisch oder linear. Sie legen auch fest, an wie vielen Stellen ein zugehöriger Zahlenwert eingetragen wird (sogenannte major_ticks) und ob zwischen zwei dieser Markierung ggf. weitere kleinere Unterteilungen bestehen (minor_ticks genannt). Mit den *Axis*-Objekten wird auch gesteuert was unter den *ticks* steht. Standardmäßig sind das die zugehörigen Zahlenwerte. Es ist allerdings auch möglich die Zahlen durch Text zu ersetzen\n", + "#### Artists\n", + "Alles was in der Grafik sichtbar ist (sogar die oben genannten Objekte). Alledings sind hier meistens die sichtbaren Objekte in einem Diagramm gemeint. Z.B. eine Linie, eine Markierung, Text, die Torte eines Tortendiagramms etc." + ] + }, + { + "cell_type": "markdown", + "id": "8aaeafc3-560f-4f8f-89a2-c9591b23b179", + "metadata": {}, + "source": [ + "### **Das Objektorientierte Interface**\n", + "Das Objektorientierte Interface wird zu erst beschrieben, da das implizite Interface auf diesem Aufbaut.\n", + "Eine Einschränkung von Jupyter Notebooks ist, dass die Diagramme allerdings nur über das implizite Interface darstellbar sind. Das ist allerdings kein Problem.\\\n", + "In einem ersten Schritt wird ein *Figure*-Objekt erstellt. Es bildet den Rahmen für die Diagramme. Die erstellte *Figure* hat eine Größe von 3x2 Inches. Die Auf dem Bildschirm dargestellte Größe kann abweichen. Die Größe beeinflusst das Seitenverhältnis und die Größe der Schrift. Als nächstes müssen der Grafik Diagramme hinzugefügt werden. Die Diagramme werden als *Axes* bezeichnet und sind erst eimal generisch, soll heißen es ist zunächst egal, welche Art von Diagramm sie konkret werden. Im einfachsten Fall fügen wir ein Diagramm ein. Dazu wird die Objektmethode *subplots* ohne Parameter erwendet. Das Ergebnis ist ein Objekt der Klasse *Axes*. In dieses kann jetzt inhalt gezeichnet werden. Im Einfachsten Fall X-Y Daten. Das geht mit der Methode *plot* des *Axes* Objekts. Die erste Liste enthält die X-Werte, die zweite Liste die Y-Werte. Zum Schluss wird das Ergebnis angezeigt\n" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "id": "0a141e67-98ef-4d4f-95b4-4fbe479098cc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x2521a643ca0>]" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 300x200 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "fig=plt.figure(figsize=(3,2))\n", + "ax=fig.subplots()\n", + "ax.plot([1,2,3],[3,2,1])\n" + ] + }, + { + "cell_type": "markdown", + "id": "615d4499-5989-4774-b3e1-c707815d800f", + "metadata": {}, + "source": [ + "Man kann auch mehrere Diagramme in einer Figure darstellen. Dafür sollte eine neue *Figure* erstellt werden, die als zweiten Parameter den Layout-Typen (\"constrained\") erhält. Dadurch wird verhindert, dass die Einzeldiagramme sich überlappen. Um mehrere Diagramme zu erstellen muss die Methode *subplots* mit zwei Parametern aufgerufen werden, die die menge an Grafiken untereinander und nebeneinander angeben. Das Ergebnis ist jetzt eine Matrix von Diagrammen (Das ist praktisch eine Liste mit zwei Indizes). Das ist im folgenden Beispiel für insgesamt 6 Grafiken in einem 3x2 Raster gezeigt. Es werden verschiedene Diagrammtypen gezeigt. Im ersten Diagramm das bekannte X-Y-Diagramm. Im zweiten Beispiel ein sogenannter Scatter-Plot, also einzelne Punkte im X-Y-Raum. Der Parameter s ist dabei optional und gibt die Fläche der dargestellten Punkte an. Das dritte Diagramm ist ein Balkendiagramm. Die erste Liste enthält die Namen der Balken, die zweite die zugehörigen Höhen. Das vierte Diagramm enthält ein Tortendiagramm. Dabei stellt der erste Parameter die relativen Anteile der Tortenstücke dar. Der Parameter *labels* gibt den Tortenstücken Namen. In den letzten beiden Diagrammen ist gezeigt, wie mehrere Linien in ein Diagramm gezeichnet werden können und wie mehrere Diagrammtypen gemischt werden." + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "id": "0382bc33-5c6b-4cc8-9c8a-59903904b06f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x2521a7f6b30>]" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 900x600 with 6 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "fig=plt.figure(figsize=(9,6),layout='constrained')\n", + "diagramme=fig.subplots(3,2)\n", + "diagramme[0,0].plot([1,2,3],[3,2,1])\n", + "diagramme[0,1].scatter([1,2,3,0.5],[3,2,1,4],s=[90,30,10,30])\n", + "diagramme[1,0].bar([\"Äpfel\",\"Birnen\",\"Pflaumen\"],[20,10,5])\n", + "diagramme[1,1].pie([20,10,80],labels=[\"A\",\"B\",\"C\"])\n", + "diagramme[2,0].plot([1,2,3],[3,2,1])\n", + "diagramme[2,0].plot([1,2,3],[1,2,3])\n", + "diagramme[2,1].bar([\"Äpfel\",\"Birnen\",\"Pflaumen\"],[20,10,5])\n", + "diagramme[2,1].plot([-1,1,2],[1,10,20],\"r\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "c603cfb6-9efa-4653-9f3d-8f21030509d9", + "metadata": {}, + "source": [ + "Soll ein Diagramm erneut gezeichnet werden (z.B. weil es nachträglich verändert wurde), reicht es einfach den Diagrammnamen an das Zellenende zu schreiben. Hier wird einem Diagramm ein Titel hinzugefügt und alles erneut gezeichnet" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "f1025510-9a62-4561-8db2-d09c597437e0", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 900x600 with 6 Axes>" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "diagramme[0,0].set_title(\"erstes Diagramm\")\n", + "fig" + ] + }, + { + "cell_type": "markdown", + "id": "93737992-91ab-49d9-86e6-5a058560ac10", + "metadata": {}, + "source": [ + "Nach diesem Beispiel sollen die Möglichkeiten der Diagramme genauer beleuchtet werden. Das Beispiel erstellt ein Diagramm, mit mehreren, benannten Linien und stellt verschiedene Möglichkeiten zur Formatierung dar. Den Linien können Farben, eine Linienart, die Liniendicke, Punktmarkierungen und die Markierungsgröße zugewiesen werden. Alle Parameter sind optional." + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "id": "43fff7bf-d044-4c42-a8e0-a1eee4c01fef", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(1.5, 15, 'Eine Anmerkung')" + ] + }, + "execution_count": 132, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 500x270 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig=plt.figure(figsize=(5, 2.7), layout='constrained')\n", + "ax = fig.subplots()\n", + "ax.plot([1,2,3], [1,2,3], label='linear',color=\"blue\",linestyle=\"-\") \n", + "ax.plot([1,2,3], [1,3,9], label='quadratisch',color=\"red\",linestyle=\"--\",marker=\"x\",markersize=20) \n", + "ax.plot([1,2,3], [1,8,27], label='kubisch',color=\"green\",linestyle=\":\",linewidth=4) \n", + "ax.set_xlabel('X-Werte') # eine X-Beschriftung\n", + "ax.set_ylabel('Y-Werte') # eine Y-Beschriftung\n", + "ax.set_title(\"Ein Titel\") # ein Titel\n", + "ax.legend(); # Eine Farblegende hinzufügen\n", + "ax.grid(True)# aktivirt ein Hintergrundgitter\n", + "ax.set_xlim(0,4)#setzt manuell den Bereich der X-Achse\n", + "ax.set_ylim(0,30)\n", + "ax.minorticks_on()#aktiviert die minorticks\n", + "ax.annotate('Eine Anmerkung', xy=(1.5, 5), xytext=(1.5, 15),arrowprops=dict(facecolor='black'))# So kann man einen Punkt mit einem Pfeil und Text markieren" + ] + }, + { + "cell_type": "markdown", + "id": "a685d605-7a95-4686-978a-de96c629f716", + "metadata": {}, + "source": [ + "Man kann Grafiken auch speichern. Das funktioniert mit der Methode *imsave*. Viele Dateiformte sind möglich. Hier ist das Speichern als Bild (png Format) gezeigt. Dabei kann in einem Parameter angegeben werden, wie viele pixel pro inch Grafik verwendet werden sollen, also die Auflösung. Es ist auch möglich Diagramme als Vektorgrafik, z.B. pdf zu speichern. Die Auflösung ist hier irrelevant, da die Dateien verlustfrei skalierbar sind." + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "id": "ede243fb-4d84-442f-8821-5b546f463e9d", + "metadata": {}, + "outputs": [], + "source": [ + "fig.savefig(\"diagramm.png\",dpi=400)\n", + "fig.savefig(\"diagramm.pdf\")" + ] + }, + { + "cell_type": "markdown", + "id": "2597c9d2-d024-4a88-829d-8b72f4ae3795", + "metadata": {}, + "source": [ + "Das sind die wichtigsten Funktionen von Matplotlib. Für weitere Möglichkeiten an Farben, Linestyles etc. ist der offizielle Quick-Start-Guide von Matplotlib eine gute Quelle\n", + "https://matplotlib.org/stable/tutorials/introductory/quick_start.html" + ] + }, + { + "cell_type": "markdown", + "id": "0acab7f1-2b94-4779-aa3c-45d102ab6beb", + "metadata": {}, + "source": [ + "### **Das implizite Interface**\n", + "Das implizite Interface verwendet im Endeffekt das Objektorientierte Interface. Das implizite Interface wird über Funktionen aus dem Paket *matplotlib.pyplot* gesteuert. Es wird also nicht angegeben, welches *Axes* Objekt verwendet werden soll. Viel mehr wird erst ausgewählt, welches Diagramm bearbeitet werden soll, anschließend kann das Diagramm bearbeitet werden. Die meißten Funktionen haben den selben Namen wie im objektorientierten Interface. Als Beispiel das letzte Diagramm im impliziten Interface" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "id": "aa9e7e45-3c5a-4696-bf88-3f8c9c4555f6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 500x270 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(5, 2.7), layout='constrained')#Erstellt eine figure mit standardmäßig einem Diagramm, das im folgenden das aktuelle Diagramm darstellt\n", + "plt.plot([1,2,3], [1,2,3], label='linear',color=\"blue\",linestyle=\"-\") \n", + "plt.plot([1,2,3], [1,3,9], label='quadratisch',color=\"red\",linestyle=\"--\",marker=\"x\",markersize=20) \n", + "plt.plot([1,2,3], [1,8,27], label='kubisch',color=\"green\",linestyle=\":\",linewidth=4) \n", + "plt.xlabel('X-Werte') # eine X-Beschriftung Die Funktion heißt xlabel und nicht set_xlabel\n", + "plt.ylabel('Y-Werte') # eine Y-Beschriftung\n", + "plt.title(\"Ein Titel\") # ein Titel. Die Funtion heißt hier nur title und nicht set_title\n", + "plt.legend(); # Eine Farblegende hinzufügen\n", + "plt.grid(True)# aktivirt ein Hintergrundgitter\n", + "plt.xlim(0,4)#setzt manuell den Bereich der X-Achse. Die Funktion heißt nur xlim und nicht set_xlim\n", + "plt.ylim(0,30)\n", + "plt.minorticks_on()#aktiviert die minorticks\n", + "plt.show()#Zeigt die aktuelle *Figure* an. Nach dem Anzeigen wird eine neue *Figure* angefangen!, das erstellte Datenobjekt ist verloren" + ] + }, + { + "cell_type": "markdown", + "id": "4701dd39-6b33-42f9-969d-9ce4711127d7", + "metadata": {}, + "source": [ + "So lange nur eine *Figure* erstellt wird bzw. eine *Figure* nach der anderen, funktioniert das ganze bis auf kleine Unterschiede in der Namensgebung identisch. Es ist auch möglich mehrere Diagramme in einer *Figure* zu erstellen. Das ist hier gezeigt:" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "id": "65b70027-b716-42e2-a2aa-e395d5065e8f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 640x480 with 2 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.subplot(1,2,1)#Erstellt ein Raster von 1x2 Diagrammen. Wählt das erste Diagramm aus\n", + "plt.plot([1,2,3],[3,2,1])#Zeichnet eine gerade in das gewählte Diagramm\n", + "plt.title(\"Diagramm 1\")#Gibt dem gewählten Diagramm einen Titel\n", + "plt.subplot(1,2,2)#Wählt das zweite Diagramm im 1x2 Raster aus\n", + "plt.title(\"Diagramm 2\")#Gibt dem Diagramm einen Titel\n", + "plt.scatter([1,2,3,0.5],[3,2,1,4],s=[90,30,10,30])#Erzeugt einen Scatterplot\n", + "plt.subplot(1,2,1)#Wählt wieder das erste Diagramm als das aktive Diagramm\n", + "plt.plot([1,2,3],[1,2,3])#Fügt eine zweite Linie hinzu\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "5a006675-3008-4cc2-b9df-10e9ca3cde0a", + "metadata": {}, + "source": [ + "Die Logik dabei ist, dass immer ein Diagramm als das aktuell zu bearbeitende Diagramm ausgewählt wird. Die Diagramme im Raster sind dazu durchnummeriert, beginnend mit 1. Anschließend kann das ausgewählte Diagramm bearbeitet werden." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/Uebung04/Uebung04.ipynb b/Uebung04/Uebung04.ipynb new file mode 100644 index 0000000..06dec38 --- /dev/null +++ b/Uebung04/Uebung04.ipynb @@ -0,0 +1,275 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "e990c2fb-c4c7-470f-8090-86de9651ec50", + "metadata": {}, + "source": [ + "# <font color='blue'>**Übung 4 - Module und Zeichnen mit Matplotlib**</font>" + ] + }, + { + "cell_type": "markdown", + "id": "9caa439c-ae2c-4871-9b81-950a32f458a2", + "metadata": {}, + "source": [ + "## <font color='blue'>**Einleitung**</font>\n", + "\n", + "In den vorherigen Übungen haben wir uns mit den Grundlagen der Programmiersprache Python befasst. Inhalt dieser Übung ist die Verwendung von Modulen. In der letzten Übung haben wir Klassen und die Objektorientierte Programmierung kennen gelernt. Als Beispiel diente eine einfache Klasse um grundlegende Vektorrechnung zu ermöglichen. Vektorrechnung ist etwas, das in vielen Programmen benötigt wird und sicherlich bereits von vielen Programmierern implementiert wurde. Um das Rad nicht bei jedem Programm neu zu erfinden bietet Python ein sogenanntes Modul-System an, durch das Programmcode wiederverwendet werden kann. Ein Modul bietet Klassen oder auch Funktionen an, die von anderen Programmierern wiederverwendet werden können Dabei beschränkt sich ein Modul meistens auf ein spezielles Themengebiet. Ein solches Modul kann selbst in Python geschrieben sein, es gibt allerdings auch viele Module, die in anderen Programmiersprachen programmiert sind, sich allerdings trotzdem mit Python verwenden lassen.\\\n", + "Module können in Paketen zusammengefasst sein, die sich über einen zentralen Paketmanager namens *pip* automatisch installieren lassen. Viele davon sind im Internet bereitgestellt und lassen sich darüber hinaus sogar automatisch herunterladen. In dieser Übung geht es darum, wie solche Module genutzt werden können. Außerdem geht es um die Verwendung eines konkreten Moduls namens Matplotlib, das im wissenschaftlichen Kontext oft zur Erstellung von Grafiken genutzt wird\n", + "\n", + "### **Weitere Notebooks, die dir helfen könnten**\n", + "* Python Grundlagen Teil 1\n", + "* Python Grundlagen Teil 2\n", + "* OOP Grundlagen\n", + "\n", + "### **Vorkenntnisse**\n", + "* Übung 1\n", + "* Übung 2\n", + "* Übung 3\n", + "\n", + "### **Lernziele**\n", + "* Module\n", + "* Grundlegende Verwendung von Matplotlib" + ] + }, + { + "cell_type": "markdown", + "id": "fdde8bab-000b-452f-aa39-98cbcd11b8f4", + "metadata": {}, + "source": [ + "# <font color='blue'>**Abschnitt 1 - Importieren von Modulen**</font>" + ] + }, + { + "cell_type": "markdown", + "id": "e082132f-33ef-4956-955f-d7b462d20a14", + "metadata": {}, + "source": [ + "Ein Modul kann man sich prinzipiell als eine Sammlung von Klassen, Funktionen und ggf. Variablen vorstellen. Am einfachsten ist es, diese Module mit *import* zu importieren, was immer das komplette Modul lädt. Python selbst bringt automatisch einige Module mit. Diese werden als die Standardbibliothek bezeichnet. Eine vollständige Liste findet sich unter *https://docs.python.org/3/library/*. Ein Beispiel ist die Bibliothek *time*, die verschiedene Funktionen rund um das Thema Zeit beinhaltet" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "eee8bebd-4394-4149-b66c-3bad8de9658e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "time.struct_time(tm_year=2022, tm_mon=11, tm_mday=21, tm_hour=16, tm_min=50, tm_sec=41, tm_wday=0, tm_yday=325, tm_isdst=0)\n" + ] + } + ], + "source": [ + "import time\n", + "print(time.localtime())" + ] + }, + { + "cell_type": "markdown", + "id": "9765a216-c831-4f97-8f51-de6a908a0cff", + "metadata": {}, + "source": [ + "Das Beispiel importiert ein Modul mit dem Namen *time*. Das ist möglich, da dieses Modul automatisch mit Python installiert wird. Um Funktionalität im Module *time* (z.B. die Funktion *localtime*, aber auch Klassen oder Variablen) zu nutzen, muss dem Funktionsnamen ein *time.* vorangestellt werden. Ähnlich wie bei der Objektorientierten Programmierung. Der Sinn ist, dass verschiedene Module unter Umständen Funktionen oder Klassen mit identischen Namen beinhalten könnten, was ohne diese Regel zu Problemen führen würde. Jedes Modul kann nur einmal geladen werden. Mehrmaliges Importieren eines Moduls führt zwar nicht zu Fehlern, das Modul wird aber nicht neu geladen. Das kann allerdings nur dann zum Problem werden, wenn man selber Module programmieren möchte. Falls der Modulname zu lang ist, kann man dem Modul in einem Programm auch einen Ersatznamen geben. Es sind auch mehrere Ersatznamen möglich" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "4f2c174a-09e9-4044-b7eb-96ce07c6481b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "time.struct_time(tm_year=2022, tm_mon=11, tm_mday=21, tm_hour=17, tm_min=0, tm_sec=25, tm_wday=0, tm_yday=325, tm_isdst=0)\n" + ] + } + ], + "source": [ + "import time as ti\n", + "print (ti.localtime())" + ] + }, + { + "cell_type": "markdown", + "id": "7d565fc0-2a58-48bf-9c01-1464b9ecf522", + "metadata": {}, + "source": [ + "Das Beispiel macht das selbe, wie die erste Zelle. Das Modul *time* wird lediglich unter dem Alias *ti* in das Programm geladen. Es ist weiterhin möglich, nur einzelne Funktionen aus einem Modul zu laden. Diesen kann optional ein neuer Name gegeben werden" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "d142c8f4-5fd4-4299-b914-abbc9b5913fd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "time.struct_time(tm_year=2022, tm_mon=11, tm_mday=21, tm_hour=17, tm_min=2, tm_sec=16, tm_wday=0, tm_yday=325, tm_isdst=0)\n" + ] + } + ], + "source": [ + "from time import localtime as Lokalzeit\n", + "print (Lokalzeit())" + ] + }, + { + "cell_type": "markdown", + "id": "482c83c0-cbcd-4d05-a9d9-e1d05e4a4d53", + "metadata": {}, + "source": [ + "Das Beispiel importiert nur die Funktion *localtime* aus dem Modul *time*. Im Programm ist sie unter dem Namen *Lokalzeit* verfügbar. Alle drei Beispiele machen das selbe. Welche Methode ein Modul zu importieren die beste ist, hängt von der jeweiligen Situation ab. Mit der möglichkeit *import as* funktioniert es meistens am Einfachsten.\\\n", + "Module können in Python verschachtelt sein. Das bedeutet ein Modul kann aus mehreren Modulen bestehen, die ihrerseits dann Klassen, Funktionen und Variablen anbieten. Ein Beispiel dafür ist das Modul matplotlib, das ein Modul pyplot enthält. Schaue dir das Grundlagen-Notebook an" + ] + }, + { + "cell_type": "markdown", + "id": "33039b46-4f2b-4eea-8254-79061a7504ca", + "metadata": {}, + "source": [ + "# <font color='blue'>**Abschnitt 2 - Zeichne eine Sinus und eine Kosinusfunktion**</font>" + ] + }, + { + "cell_type": "markdown", + "id": "25e7cf2e-5eea-4cd2-a0b7-85959683097a", + "metadata": {}, + "source": [ + "## <font color='blue'>*Aufgabe*</font>\n", + "Erstelle eine Grafik, die eine Sinus- und eine Kosinuskurve zeigt. Die Grafik soll auf der x-Achse von -Pi bis Pi gehen. Die entsprechenden Sinus- und Kosinuswerte sind selbst zu berechnen. Die Grafik soll aus 100 Stützstellen bestehen, die gleichmäßig über die x-Achse verteilt sind. Alle Achsen sollen sinnvoll beschriftet sein und die Grafik soll über eine Legende verfügen. Um an diesem Punkt die Aufgabe etwas besser zu gliedern, besteht sie aus mehreren Teilaufgaben, in denen du auch einige Techniken der vorangegangenen Übungen wiederholen kannst." + ] + }, + { + "cell_type": "markdown", + "id": "348e7767-baf7-42b4-935c-d7496bb4a34c", + "metadata": {}, + "source": [ + "## <font color='blue'>*Hinweise*</font>\n", + "Der Sinus und der Kosinus können über die Funktionen *sin(x)* bzw. *cos(x)* aus dem Modul *math* berechnet werden. Weiterhin enthält das Modul eine Variable namens *pi*" + ] + }, + { + "cell_type": "markdown", + "id": "79aa95c6-adc0-40ee-9566-49439896681f", + "metadata": {}, + "source": [ + "### <font color='blue'>*Teilaufgabe 1*</font>\n", + "Um etwas zeichnen zu können, brauchen wir zunächst die Werte der Sinus und der Kosinus Funktion an 100 gleichmäßig verteilten Stellen zwischen -Pi und Pi. Dazu sollen 3 Listen erstellt werden. Eine mit den x-Werten, eine mit den Sinus-Werten und eine mit den Kosinus-Werten. Dafür benötigst du eine Schleife, bei der in jedem Durchgang ein weiterer Wert angehängt wird\n", + "### <font color='blue'>*Lösung Teilaufgabe-1*</font>" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f361c08d-ade7-446a-a519-d953c4ea267f", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "e45669c5-f500-494a-bac4-eb49846204ba", + "metadata": {}, + "source": [ + "### <font color='blue'>*Teilaufgabe 2*</font>\n", + "Um etwas mit Matplotlib warm zu werden, solltest du zu erst versuchen die Sinusfunktion zu zeichnen. Da du nur eine einfache Grafik zeichnen möchtest, kannst du hierfür das *pyplot* interface verwenden. Versuche die Grafik zu beschriften. Die Kurve soll im rot und gestrichelt sein\n", + "### <font color='blue'>*Lösung Teilaufgabe-2*</font>" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3b77a06d-a486-45f4-a0e3-ad2fd087ddfd", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "704cd96d-5767-4be4-9761-9bec88e62cfd", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "a9d7fe62-9ffd-418d-819e-ee72a8617bd3", + "metadata": {}, + "source": [ + "### <font color='blue'>*Teilaufgabe 3*</font>\n", + "Für diese Teilaufgabe soll das Objektorientierte Interface von Matplotlib genutzt werden. Erstelle zunächst ein *Figure*-Objekt für die Zeichnung. Es soll die Größe 5 zu 2.5 besitzen. Die Zeichnung soll einen Graphen enthalten, der sowohl die Sinus und die Kosinus Funktion enthält. Die Sinus-Funktion soll in blau, die Kosinusfunktion in rot dargestellt sein. Außerdem soll die Grafik einen sinnvollen Titel und eine Farblegende besitzen. Die X-Achse soll mit \"X\", die Y-Achse mit \"Y\" beschriftet sein" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fb035a92-6fb1-4306-bf47-b585bfa5a43d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "3c798465-575f-4d0a-b803-aeb93d023fc0", + "metadata": {}, + "source": [ + "# <font color='blue'>**Aufgabe zum selbst probieren**</font>" + ] + }, + { + "cell_type": "markdown", + "id": "91ebfd38-aabb-4538-a547-f0fdae15c22d", + "metadata": {}, + "source": [ + "Probiere ein neue Grafik zu erstellen, in der zwei Graphen untereinander positioniert sind. Einer soll die Sinus-Funktion enthalten, einer die Kosinus-Funktion. Probiere die beschriebenen Möglichkeiten im Grundlagen-Notebook selbst aus. Markiere z.B. das Maximum der Sinus-Funktion mit einem Pfeil. Hinterlege die Grafiken mit einem Hintergrundraster, damit du Werte besser ablesen kannst. Die x- und y-Achse sind momentan noch recht grob in Einerschritten beschriftet. Füge kleinere Markierungen für 0.1-er Schritte in der Beschriftung hinzu" + ] + }, + { + "cell_type": "markdown", + "id": "cc3b1290-6063-4985-9ef4-1c035c96582c", + "metadata": {}, + "source": [ + "# <font color='blue'>**Lösung**</font>" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f2845551-20ea-4d56-be1c-e6dfce2ddadb", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/Uebung04/anatomy.webp b/Uebung04/anatomy.webp new file mode 100644 index 0000000000000000000000000000000000000000..cb6521ea0a57bf807eee321f001e3d8c479e3a62 GIT binary patch literal 65490 zcmV)HK)t_GNk&G>{{R42MM6+kP&iD!{{R3l+r@SP{|7meBuUC__5N0jU4f9FCx!wy zbX7(srw(u=+g7dYf4+YlA~NPb98z-2^y%3GA(Cv@$~}h+0&swK5QCPV^O@QCSDUs0 zGp6T`18WktY}pYn0qiAFqPW>%D|oPF%T^KyNg&v=WeXvRBz^{de<WcG!In7w9Qv0- z_(ir55D*ZONMiay90=k-n0`Q*e)x04RuV}hVat{!3<Lymh-3Oe9O6K*^#_T=7J@k5 zmjm!HxDw79XTnwEtZ_6r8(eH0d|+c^Z{uiVuW_<*&^Q{LZJacYge!3O^7i5B^~=qF zF2`qA-ytDcLa+l#1cWGCaU@{}k{w7#B8g;40tv}d5=kUW5=q#RM6%dQmRNQmAweNb z!;*+;XdRM7n35n0LWC%YX-p3qk|3b4L_B=|q6LFhTBTJinpHE69`N};W<pPx88e|r z^f>l_nb8w^Ko4V&V<yZZR?SQEQ}bQ%RXMJUZcA><xeD8}yXSAUZEIVq+S<0NQrot+ zPpZmkvsAUJQrlM5*0!x}scoxjRi&y_wY6=>rc{-xcHXP1-G5#9@bB^chjS#ijU-5t zB>%n6tg7DKyMIJX0D%8u_Fuzq6a2PoidZ{-MZ{?92?(e_R@KwxL9Uz1jOrs5q+$_l z$LCF+i-LIQ5^x3816Kqm1z6mHsv9{vktu9y6#LK?V0gHccnPW?c5yDC-U;A(c=a)$ z+Ef>3jmt#@C=gDdT0XLd`&Q%nLZyO(^Mmtn`2Nv4fB_uz3)kWbRGc4?;=TYL@x#Io z0lp&SiPcXj_(D(t9$Mcb0FmntI8~rLy2t$>Liu<R5U*MN5_Gu-WRLY!r7{<$E(+d2 zRD>r!^d7*8>~5|d?{+UMk3Z0f=0RdSj{SmHccutfz5=?fs;yWNSzA$b@C;bRv9oe} zF$*WH%#QvfaNz<)k5}b2XTMJB=0B<d|9{6$8x769mn(y8j4Vow3l7*$v6DbdoIrvL zhBWW{*pAD_N!FF#I~Z>Pfsl|XVhuRPm?FJ(d+$r{y>HJO2?UrXfhEzlUCrrd&Y5%W z-ObFLDG~jrMcY=@SX$WCsdEXzM<r1a;Q;4@VgR;rBdLk&=X$vQ>$nE?5e1O|MC(q; z%<OJN|EbZ|8?=$0XLh$*mk}yMS^@@JmVWpj0NRz(Y}<wzWKa<-h#C}B1VyodC?%mt z74?b;(iExZ53#o^J!-Bbn#&e@>~#ENN{n7fj3vebKh0ii?R^d-4CwtlGix(vBKl8@ zw(YoWbCA?EL&*=cNDw12JmBM71?}z^{&W53fuX3-++F{<{&W53`p@;B>p$0juK!&B zx&Cwg=lTz6(k0j1T0+mn=>l`oR~r|;Ut0$_6NHVvR~Sy}Jk)O#LA{<&3cZQvuC60+ ztAn_J8>?v%;`vxl_d}~No8<JWIx22ukSf5Yb$J~%7q=E#lhoscv#Mt4d!ZjCIKkAX zgvhxlU0HdmISWQAioME}XrTx>6s3zVWO3paU5Jsw0%@{7^uuE9{5JgfdC59x1pRD5 zG@YQ{R-Va_MKOq=uM~GGfTjfYF;P30!U3KnsD*t1#RbpAu;e%Ix6p}b7{C(nbS`kF zcm;-(s&GYdK{J_UknjG0l#&p#kFhK$WTq10jq+ig5aKH?VCEv^dq4Grlo4b<BPm#> z(?<X`4ARI)HDG?jL7_4+cq*33=R&X&6p4#NP_~9q`uNxfMZ)3`l$~c4?+_vq6=$HV zirF2Uq68EbAaf0r1q^pMK+(0rW9GwUtVKz|F`2b+8Ea7(6dH3D$i3zU+sH>ijy6ew zG1hWBi&#hB2eOd23X8c~XQzoZArO7Pu$W39*GcAI^rOVi!h&Mb8|<87KLef}KV3-7 zRp6t5gL`@;KJaTHF^wEu$y#Nnv5=S$@;f)bhK0nuZ>O0DV&HyJ1;k`(?PPf%0<OJE z7Y^eC1)Jex9wNY_fH**F8WRH^3x}Bx@yU_Lq;Qy!tGn<ez!M9HiGfUP_~0^d)2G5= zsvu!;6jV|;Of^?&YOdI+E^Pl%*e)(?e_COCy86QQ>tX+U?0js}T;@Mn(4KF6Vf+1_ z3fu3~TG(E`g2MK4(G;|oXRNTj9Fk}I^8+94&;5S3_t)cS?`PB5-ao#hy<e+mdw;b5 zn=_6CXP{^$WBqTO?c+9cw2!ya(LPRMXZ!f({a^REL>kkXu|83c_Hh6{+Q;wuydHP= zbu{(verEg2U<qz}8F<L{GC0@$+)?xI3GSbo#W8mK)STpgWkO2}vfG1fC8hQtYfK8Y z+i|aoydC$F(E2Y$?Js#4F8Ts~yQyAC{;N@Y2cL^oJKNhSyK_?5-oEg^@Sp$o6}sp@ zKK}j5Q$PI>I(GQpUz0x+$N5~8=qfk=3EX??`rsS)ugA<~Isc%Wm-|myP*l_h+PMDr zrA4ZD;2t~T*<Fvh@_vk$-=4L~eE(#OhLd+`^OfjS0s+4dBeYAg<Zi9_KL^KVHvS^v zp@(yV2O|)DDU}rcH)(=1EEsbC^LX!<r^kXe_R#cC(pn!m=`oW>AevKp^udb>a>@RA z^!ZrN#=q}+=sStb*YD4EiTZ|q{lVu>YpNdfePDQS43`(zHnlrErq0_K$SiMYHiU)N zdq@@nRQr1D65M+K_OjRCoh9(!n{2YmaAc6tsi(sLX*(Ulcp=VD+JJ?8OO6UINxE=D zNOA`9<lLRUuFH@0k3yEcTI<O|fSZ8JLWCz&dY(Vd-0Af{2c1&z#V;Lwy|+)<W2>aW z>)Dcb<UM}0wB9Ms|D7PDJpJc8PmY7V6z8YRJ}8$3$7#M090K0H<0$lh?-ju_55Eb{ z13H96;U4w~j)8PO-A<1;_f$WQHTY~yl}{lXyqNh*KEi*0vRXMwCLgAppg-PmQrK(B zbNHlm3ii`n5Ih$AjH7mYyTyJ^5x*+{PQ_#*5b3z!j$d$9>sPnQIN<|hs7y5=dW!c_ z-8d2b>j{O*Vp+NI%wO*|HQ-lMvMPCj$HaTpE7}Fk`DsbQLb1LgQFp;NXwUls;U@IE zJ$w#ix^-4;^>CeVW*&l0g&=$mNG|)_&$o{2s16}R=f$%(1zqm3Q?eb%to342P)Ax2 zulNR47R%y|r=Gvd%m#mxywO6L4iAknSQ1~6hmutFdqkvBzqtF?TL054_yT02B7**J z3P2xm92R^|csY9ag5s9+B@i$qZiCJX3GR=b(m=#adM{ZTFo7tL?B8r{K=@uP?oV&t zVb%!BwKu|ofc7=bXA=JL@Q2^SMGq(Z9)1R&=Pn%d@9Gnt0WCNu_*LBh;7}jJ7jYp> z<KX|#$4prW?u5agxn7GKvIn~jhg??2a_%DP^Xz<gDfZq=e}iC_&&hcL>{uK`MIMB@ z1+Y0bH*nDZQ&7YWCCeM^<+$a9T=L7z*JGxX2r8;z45D|N=VynoyB6+YksrRh*n(8A zq($KNIk}|})B0Z&g!4O<%2MCLLI3-R)I2T`Qq)CwIlhDfhI*tN8Y?BTO|W#epe5X^ znQ$CEM@6ZhbK-rY@G1<78CAqev+!GZezCp6bkpwIy-m8Gi>1^w&qLHc?k(B}%_ z<#>$lhVDxFZLE}ZkUYc%-)^~g_m0lcHWJi%;GN%8?Y*#1%Aa>Z;&^$vHr?18a29YM z1pO09ah?jk6MRQ`CLoUmcTQ4f(pV|g=)Fq?Tg(x?WNq%c)eBw9{*Hu|nK^pR@_8=h zZ6@ycXQi#p%^6=7YudM=uqiw-Jv%2O#qUi_39QM^&03Y<8d}0<r+K8$T)D{YZOmR3 z$X&N$wpS35lpgpvYqjKH_5RA&2R;7fz8xjOL4}eIUZUjj`ViqEaNQt6dpZPB9$xie zpF=oI&x7*M3a$~BaA`e8%1nn~9!l}Y(@b3QmQ_2TX)TRa__yUnL?Rz<t6b)!{Uh^a zZo;q9D`inL7Pzrsx{O#MO%d*8W2u`oqqqgxvvexO5+KP$1=b098cY(fYZ;mLiWEtv zCb`Ko;jKx|uQ9N6x@Ik@;6;oX@~gkm;Kz;lx05^I0Z0)m`31$8pMol4EZ&Tc40VnC z@^iz%CGLGm3Y-D~J__a9{OI9V;Fb7G>+qlN5~(PAQ20*dRUpe#?2KH*=T)B&_8$Bt zJ^ud2m??RJdT}{y6yzu~wUQ}gWJ;K^p<Q}u3?)%4mGsDH@C&Ep2E9ZguaO_2fGrP8 zItW=$iQBe}x~T6^O-Iup$TCNI3)5!X?4iK9zDX+J>yPomvSw1arj#KiW(zaR_~MTd z^Zs&gL8B0;FDa4WTbw`E4cw33i|0E1fLBBk`mP^-g0l3vJTQ8c2>r4f=TGzXUcdkH zm?(rxl0{rP8&sLKlO-lsRtkWEF)|3^P>+nNZHsS|3tT%*h1pu-<2XGD@DXjzrLqiQ zwQ`co=l2aSmmh)lv?0LdP%+PVT#zmOt*#tGVjEdXI>gv$9u@x|QxB27RpKas{M5(% z$lUJ7NpbWAEK7h$y>mivj|j+=yzuB)DT^I~so>%dL`YI&8u;5*UtNoDsu!u?Z>Xta z;?^@w7AX2uZQC4di^gp=*wNY^BWHg5BH1RC8PRVvRM(*U=<#SGGQt31TT;qQ=Xi4c z3t79R&i3PQk>x{%vAwoxTRoQkX&zXEow<-*Hx6vJaL8D;9Ud6Z?-|h%+<$oMhcRU3 z_ZK&Ga+)Zb4(t!mp(~J^kEqa|XT1>KOJu0J3X|Vs^LqzH_itmRY!FnUi?pCb4I$BZ zk~k%u<9<LxP(o8l+Ds_P#HH}^+&V+8M@GM;w?)*$i&+i`-k((fufmm5ns@Mcq@)|w zzk|Zh7!=20K@E_$MCN=H%b3y*+(9$sGGIfJu#$iE4tPM~Ak!CkOr0Pz0FB=SZ5z|$ zT_{$x7#_$k67ZS!c>n~E8B}8yl)q+aggDR(%Z1C^JXF++?JI!orshz2!GhsK?oUBi z{@XnT&u&4dq%qoLYWmQ@>%IEMk&qVHP?o0`yZbwX_x0z3BZ6*_o`*8-1D88``+M$O z5e;w}BV~#qSP97h7t%;2m|Ka9ld}v6vY4bQRT6l=q*dXv9wqCMQ97i)cDgiVXe|wN zz>sg?CHnG2<yOCakO=lsI(lnO@0|#*q{P)f1dnZv%j%bf8rDc6ZD#>T^HsV}Q^E;d z@m%6}o7&FILjm^dNIoNv+Sfhotb9+~%Kzn*46i5Y5I=76SoSkPGJ$&$0T~Q{Z~!#| zWGM*a+ob_3PKBa`4I%0PojgLRM@HkIdohK)1~<dhHBxpG!9!oF4Y*niaKfmFg?d5^ znJDYb0I%9h$wOHI!$d54BQw8&=pWlYep$1W1^Kk2J*3F4LAPw{>?Qb_^HST<rbp$) z<1gR9@FEb;`yV})O|2vx1;k@kt075{lL4<_rc9yqg6u*M0@<tbHGvjo1+=7;6zYP2 zzQ~g17YWK_?qsdCd(Tw~kRNOY(hq%}sV}xOj5S*X^^zO-;vu9qBr815cC_sdoIAw4 zBrm?a+kfNdQ$I6&iF+)YxiH#Rb{{%Zg`JWs(EyMo+Pr;=DgIFEkx_Rmh*nU#ac_`O z6Gjkz0<v2|3P?UmFtJTu+*&DgbR;NTqU`~#;BfN%At&`l`$2ieOhbMdnrLH4P?A6N zE5H{9oV}|a(&7S{&gRa`u(52`3wBVKm?n_;M1_2rxZ{F_<_l-3r`U_M2~pw7$@68b z0>aE7Kp)mA2NLI_eg)nEssEu!{?v^=Bs3~T`?}i%-$dqhz$*Kj+u5=bmPH{GcH@xI z<WjNWTOE;n!*(!DT2PN|>OVVKk7X0yA`SU10M{m`0!w66TJTiYo#G$JXJjh%=xC1G zb<o`o;*=%yfN~v3osT-84up*$hzGa-krwVfjS2Tc?#XzbJ>PEUezvSv3r<QOGB#)l zA7kFa(UxRrsI++c&6V5T{r)?bK6|b8m^Nu-*bkWxX|Vz`loD*NlrcS{sCq}U;UEoh zZ|Xb+iK5x8cs;8DA?`H8;nA{ys^+#K0Acb|r6Ecg7Vez}h?KGhxJ)dVxT0W7LsJ`* z<{`FhQ+pEE+#w@dMiu5&!gty)JCmRr<7SIOY+bEF-XgW@ZK)(3kED<rnrO@`RM~4M zO`T%V3dMqrl63WW>GRLQL779PAxgEfXP(>+fm$9n^TDyZMV)wD?gP!EY}u~nDuoXj ztF($^{EY{YuCMI~VZN7XL@>H6*u)r6C?3%)Q@1cH5i3nrb6CY8NLS3fR4u(!;w0jn zPe^z(*x9nZb)MpLQK!RWM;TY4!K^}mwt!=pAeXj%s7RHUSx?~J%=eN5GaIQS{K&ML zY1<uU*$cTRp^YdJLBUb0Gs7joBO$r~>}=WIx=64|&LH4kx`c0J_CgHB)G|#&R{o?c z*oui<zLy5@{Q`*r-)f6-q9S=){*|A(Z1Ex>eltM2=M$BC)g^K=KsbaMN<fc<%mjD5 zZYr7m4=LQtaD!^0G=1n&$bj~3p>@lbB!geTa~#kvm@TK-JDC0+n{hT_KC+fIK(zX0 zP7}AYYI|zcY?oQUO_PD=@fsnTyp;bkg;IeODn1Qm3ZNHN<`}?f&7@;RzQYj7uW-H` z!#kKdVh}rYC95sBTP5-~a_LwxC1xnJmU?grj5HGr?Lq||I8_qoXDEibZ#8wPTx{o4 zQkH_uRzy^+e-jSoxrJ@27pksQDFRW>vInNH{2}qxEtN8nt)RvNBAMvM;!<QCGmlXd z*=C03a7&=WT?|?3OgGa^KyBXBS|KS=zG6D`4W?LR=L#uK8{g~?CG<^&7B$I90c5Gt zsFWo26%MEb<@C$_dNQV~9k~Vz&@Juslfm^Np-^bC9Gh(`&b)@@^WsATW6-3tDU)U; z%LP^DE_stsU!y6x9$PRH&&MYcaNCTX6rGE9zJ=`@=gQm|wOpaGp-Hq-=F;@r9FV6L z!@N$$fKrMYXPXslvwvR6!Nm>*$;?Z~syEx9kapz?r*5_c`fj^OTGd{NEZ+5~TG5x` zS}Ejtu_+b;=YxrvYJi<_ePbS2SuSM@$YMa1kCd$VK)?a1DygWnu94wX%Kb2xt)Rg6 zeL&u<a`3D%YT{TD4j|2NWK6Y?T$L~#=XME`6^DyDz)EkG1sJg6KbMKo8^E!l;#+Gd z+$Ob(w|<QftevD9X<Q0RWJRuJN{DwLOhxqOTEZgRHr7Sj1es&UsL2Pnp%axtKSA(C zwuNL0LehG~OK_vdG-)M=$CePW1A1a4;P%l5EL1McH3YtK-hPc)D!&(_l>U!K3DbNY z(8cg!g_3ga<!n(1)QM<TMkPArDKQ_%jGbH2+}@BEsYta2&s_{EWP7M%`3aO>)7H8z zO$7eSEC%dCh?2B%rxE%W^y0dLTbqsMEz8FGaPE}V^j)4@u)#vo6v{P>Zjuo~MI9() zk5Y*9`~)T#k%8N{GH_7LHDLe1BPPZ`;bQXV=T#I@WeUqvz&isSSR(aURYlP59Yzuv zup?ZOSV$d}{Lh|{$$)uzw@>vxq|Y_uEVHa-O5W*p$R+{T*d9w19w91yzR-N@h+%0F zV1wIOh7(oW-4&+vtf969xj&=9X^!P~S}3rVvH2{uWT^S1E8_=}BoTsn{&^!^l@8_u zT@3%=Bv6s-S%G+#ep$;Fk+v=0H~XOJIzW81w`R>xDPyiyV`h9PRLeRfOpGD}p-?E7 zd2uL&Ultb%g_=mRnd??2tf)8I%~9lN%t}h|ZxIY`cNj&B6IX0<aQ@gH8(<8onG%PK zElgKmBQS!PggS*w-f`>>s1*|5g7<N*HINfviWJx!_{5+eMCKc352q*+F%SMN)|API z!sB1&)Cz~UFbJPt+g6l3Ej%Xi6CuSG`Jsk+lCxdN%EFOsS3~s)wZRj&!w(~U{yW28 z6=2%31;|%qd)4Mfih(w65FbOkk<DS$4nh&&L4a>vz{b?EJf?t4Nr}0~AGysVeQIdc z%Gij=xK-dnTGlAx5ac&_g<KGb!=X+{;&eOGKYML0_Pd*-1x&|D0bOEAOBJNY&dy7S zj+n8u+<+dJNUMo%gW|6JC=@<paZ#I);k#U*6Xj)EHckc1P^iC1!zarYEzPVDa+XzF zgXst4&oC_N)g_(1v*#BFJ=?y(1V{xwe>Qk4892pOrb#%CuEawTir6w7Ysc~!XH%ER zMKI}(g=LhLvDDNJ%D4~N5AQ||;>3;I#tLSG%Oq!j_JX0pJO{(QX<ZtrV4C8z)#wa` zLLBcN#s_*~i|p^Lu$}VfNXcuiR2^XzCc?>tQj7#~Y<8o!QpN_ntD0ewtziVqsb6b7 zmyP972QHdUbMd=X7BXHXqb4SdfUfY;SNMc0)%ec_IfX85k_w>MOH|Oc0(w_Cu5On* zjIm+Xqw}TNiW7@?K~LXIQW1kn@1%c6p)v`ZBDH0h2Y!sj55>oP!c!RGrPLCS*EP90 zPx(VvIflnvHkszG0EiW99oki3$m$X)B~r3uK7E;AA-SN{C2Oq!p3f#aqyrwHccH;1 z$(?>qc-T;&SGLgC{%M*Yw4PtG6Yf!*fD6ZLlidkqHj~w#42D^V>G<{6ki7KOTjFCD zaf(d!QnnK%<ps=<sqAB`9>XIkPncOIF0VkW1WPS4y`UadnKuWV;^}KWW>72cI74y^ z?^;^ch=L!A71ID>`=sKsEWh!conLF9Qj%4!sZTzibN5h)d*r%mD0}_-co6>Hz5;rZ zQ7Md7ku&j$b5OumNbQkKgR9FMS{!W+<*Tf(;dScs&wyp?d;O&$kF?j5P^3(Iw+Tu} zh{tB;yYx+qm5IUexih4pOVS;8tBX84VSJWF*TD;5mN;|(iEIYYeshhTmlz*C<Rxa! zV2<-^FE<(9*bdp0f6x8B${_m*BK;-OTff0hwzFM|TY}`9>F;KK*tRRu9Zz^cR+1%D zd;3um+FMR;E2!$WcbBgxP%ljyN42i;x?Qki1(}NPPi85zf_eFvJa5iI^S>ddEwXcg z4&@_R6)@&7cu<IUBhY|sqM$k1<+YM)hy0CJz@%)5a04Z+99JgV;Hois^uJLPn}(eE zK&}ZXD#XG{V#|r}T9|}pBnP{wMO2>d9gaE)CEOmVkRl-2LIwidFp<tPrR%s!gp|bu zWJvxY2RU##Gsn_-f^PI*4l$W^cIFx?l#L|SX`CC7;D#wyGe>yZTeA|A%b2&3Mfn64 zk&&mX99%hn%EUmpRm_S9WgToHibu#{u3zOT>!7U_k;~kWk&@Y1r_R6*=B=v}=Z}}R zar{_1&hJpRsUhYJkcP8_+E+^Ehb6%{Z(bHo<=w4=$(h_EJZn%HWz&e1QT4J!kKs6f zwN*6Ai#2niJRcc0VqybKz!a~Jo>ogFK#m(rN8dy3sChHAUsqA`J!e56C1Wc}-7F25 zTQ`5aa&gkq^y2O4s+ABn!V{agxy5M6n@HZSuWyum)CTkF+J+RZgSBn`ZA-(Na1jPE z#R0<}pAlvP?Oai@)6hHYHPK;X>P$X^n^5Kj{~k4AqExV~F<Txe7-Ln~h|fFZ)otgG zhqq^fw4%#-e;q=aftatf=#io2Mf0LC-<f$1UiRLD7er&>hkRRf#?YcIU5^;dDsPj} zk~0|Q1LL2LTW-?oe(!;qU&mUMKq?zgh2h~#gYJ||YRjbT@|vBkhHh@C%1em|)4njh zhCe@`&%KZM?S(GRXMj}N%qhmQ_19fNxlep#0>BNm@(aukBth*ZHdn%~fhhMxo00AR zombx+{@V9HUu5zepj7g+p_u_UehN{_Pd;CN*XTRU4^tD-x+@Gu1`$kF7{CJ^Y^aGS zTHi!pO`Q-~VF2kLstBeb0-tb>Zn8~?_6jSl0s+1m1g|Lw(L9*emg%XiC>7R5FeO|S z2GC=8hqwDH2*#>_OdnmKrHJVju%=$m6y^0n=v86hgDQfF7S=(9bfoZBye|-7K!@Om zX*I!E<#jOOnGETpi!f<a9TXJ^(DlvsG9)Sr#;T{)^$twu`k%tJs-H520(`%{42jBu zF&EaLy50far-jvASqqKah6bysP=H5*;Pu;82Ggmk4(`@e&%1cTf<~*UzUl)+%$DW$ zDhdU-nS0fKMrkmXO^Eb5f8N}N`Y-|fBBg}`4DAs7z(7$JA(6w777oz2{T8?k=y-oz zR_cP?9TrTuk`il9!KAlJb(JfN<4}<ZUk!q98f?D)8oqlyaLMkKyAeZ~n4G21fe78@ zdx6e!_bU=l1i`Cmd<HAPAMfyiDQaEsAX>km6;(9f{6D>hx0jHC(T}h7jpO@DyT$F! z^Ln?3G~54?c&9{vERaU~6U95l`&qox0>9rDo9<rN9@0HtkM@xIlzL(N3-l=UW7~{$ z2WI2}`-~)5GZNWnq&F}l-Rv{c3v)*15f)hpq(K%z$7=>WUUU58&>{h3kwnrWnmAqz zTV7vzIR<Ahi8)^ZcNQat4)=TOFxjxI5q|w^`ZK(*fUms#6`bXj#5%Xc_~kFdwnPc9 zfJZw7WlDtgiv4qhfw(jXVk33e<3-Q8o67a`<xAEf{4O}#l5*f;m;Y8Lb5|M!o)YnR zdlf+49S-(-@!Z+QQ>V|Iy8!qtKp^{85cD_9xL@vc9UQCvV%MPD46xi#irbamce<8@ z8r|ehx{Ig!i(PlqS22$C=25(eEg0fo_|Jb`<}SHor6bi}?AjK^Nmt)sYhz>tkY<Eg z;HuNr>u!3>ox7fP!tT<9zPoaB0XiQ0RR<&a>AQ8<<!^NghePGgSIm9x_ek&Ky9ykE zgS_)hGU&W`7^nJN??*PfRNOEBR^fMj?4;H|IEkSQm_!an@(ukVHG5A21Gor8I6-Ey zpVTi#l|(}x3eJ5Xjlxhk`d=%^^N=1`!OsMThkep_ly&PNNOy0)z>}eijGxx?-26i9 zoazgM0TI-QLui0A@AxTm5RFLeBUE7Y-V3+8`#LY}b`G<Ly|`OXfx5fzivn4?Zi#&8 z#qu>6!cxo`sMREs?vnh81|yjP`#P~aSBF;x_9?c%hxJej7uZ~q*ZOf$@B`*L3>bPu zYdcA}_S+shKyIF&NQr)Ndi7z?_`BO3;>@u(6(>fD&hw-8NujaY&dp!C@`E+&J^zDf zX>zX3a=qd^bVB+d8uRbpPo4!qMA~D%L?aS=iO@}({wrrL+d#tuhS9^Gd-J+Wq+4)D zFO=rHj2{Hu6q%BoUyQDf<mJ4^ZWgy>e88U*0Ym?z2blK&9-#YO;OG8>qj-bEC+XZ< zmt|B06LkxMv|KQ3+F_a`v|KB{OU4I$H!)Iz2L<0CPNETsbqUW!H*6H2@LAj%KDnc3 z;2Sl;_(9++FWJ*8DfC_^m&!rGEtTSGP78L?nk4j6q~(#Bj^UHCo<UkwNC!cgTrg$U zX;E-q5ITrWTSbtQiL=@VT&1|0Yl6Q$&?6FiM#}Z!^RRd883^``*7uA&T@XY{OJ;r@ zHJ1dAVgKJ9+GZr^2)E;NEh(-Bk1cf|C>`nhYf^q5M!jD>J%zbCFz{5C=2e)7_Aw9o zC$UrhfAa6b+ygo093FsbIwdcz<^`>K0lNeza9W<zCkgYbS08rmL{X$}m?QmgQT?Sj zNLf)5#D4vv5JTvY|A(RNfwRSq%IV+@;y0qWntQ<YKzxIfXWkT0Et7Y7_hHvgM=w-2 zjFGNeaH$0OO(}}~1?wCq+<3xH7#`j(J$6Y-IygcUR}&DNqDT7v2_C`N^Ux{z`|$N& zKWxC72miEqAHVL6L9_xMztG~IeSa5*um{e?aXB3jMa4fN=)d^W$pAId_xNR97f+wN zB4PxhK4`#Ni0XA(WL+*1UO&4E-lt6N|L_OfoQflJI=CsAEYUEYbCQw1zao3r4;e^R zL95(IK}#gpJy<Lg-n04Ga_}VL!J)0r#ECf_xcUf}!uboOQZSFGq&V)2WcfBHKV%?P z4NEfLNM#QoYV_)yqn?H>2T%_VCQdAgq7!pEcuH#DSMb>FKEeM`xX=+|&{c2s^!IjN zJG1Ytw;y)#pO%g^FHt3#w98AL!4o=2tt6XK4+0ap?pv(rq*Qg_|2d(W+4eqyAQ-GY zuqvQZdgXqP8aF_n;J63-H@fVCuZy9q1H`rM+?qefH0iFM-ld@qVC@yU<rzytFuo0r zxOB=#JUFp8<En2|DhHI?I9-C$X01yrnB3;07TRUi3)g@NdRmJd_~7_%OBcaAXO3Z$ zS`OBMw~c-|B-_BLCTU+njtl1KPHh9^-F<L=K|3?oI8DQk8-t@Bya2X^MHy4WbrHG| z#ko(3iArX_RrjE^p4TS&seH7G5i-+UL;#5%<l|b1$SKZ0gi5Nj$qC%vFOfTczWyiz zRafWrrbyk9s2fJe<{Aiew=1weu*DAg%iDegaWZ#L;)Vm##zJP^WcH2J4IgChr^q0A z7f9ZRh@9iBok!shjwKfF+}6jJJMXWzHvAs8n){ER;Lzof0l90JPc`=>6`-|UX>-+2 z=Yh2G?9~a%kLFkz$ntkZ&VH{iJsy3%f0)uKblLzM%V}X(r-QH-(tn+t^kDaKRPHve zSFG<JWeOy75O|;%`Q{xx3O4LR&0=L%P`c8!B}M6FQ}I|QuB7e6VED_DYoNrx)E)K# z)c=3H1-8c7Q+MhUPJuEC_4S}2a#-K5&Fnpac#Vx3hdd8!t>q4Q^C=b){s9vM$5*Vv z{8mbEIXR5Y8~1=bjZhkYA6<gA3Y1ZRf@qb~^846$;3O)Qy=$Np234CI%HCL?g7`M( z_83c<zQZGgQMEqLU#;GH&^*vpD<%1P{!NW)%n^T$Ert0T+L$wCq%+$U1^FA>g>NE) zqNTbx_(>sn+t!(5BwPl*>tA78&!z;3yz~0J=GMdTCmq?QW0;tj-wp<b!b)7?{|jLi zGvb5{K?U6H%sb}cqx^|qj!Og-Re?+OU@03i3@)4q;tA@>1Cmpa;KYN5XfRifkx&g> z@?;V7S;C!;8gO*5I?wGq27kcslgfq}$1=D>Kn!!93R2Of!<6j7`oo@?6DN6eFZA`W zJJP~TGE>4jdg$rHJ%1Wqa#Ez~Rv>4kh#`m|#`uYZ9(CuLhU(ZqtzhQaV<OzB14ra4 zF&?$i!RkDh+5<nCdxGQa55$HAqI<(2mt^K-$fNrJvt@3WDdZP#m+jy(*~r2z)k*^q z9bpQaR_Bg^78!L;QXM4QL#kuGoi!%HJUbs}Sd&?cXhcY-y~h5Nh$m?nm^a2)$zqQL ziLwiPp_=AfEi}VKSse0u85xp+H;z*sNAHTU5Ue$J%GuXzH3Bliv4356_G_HnpW%@1 z&&6`*_v<%ZfMR#-@=9iIoMGYSd<VBXNh+AD)D&W8M}i5GWy%P&RK_fcK$P@Jg~7&F z1E={M3!x3{3t;TI2FyU4Q$HGa!Jm}ubf}k^*;{rR?K?{5<G|RpM4)e>GE2k=c{Ns~ z4`2f2jYezDI4q}pFoh=KWzr;5Y4pHm717n1Rn*WP@E63G+eH(!{<_pSt)tSRVCqzd zw=$T&ctDX1S@_Wm8Ic}TyevuevZ2x*3*j8l@3eTRkM?4)k0UwNW%j|}n+|PuA~T8e zJs(}2+JUeGJGm}gl_DW28EfY+!xyQk?-c6{l!!ZNghlECEVqtY6>J3tYVaqhaDfWh zvMAn28Cs3yhSaKK8H^{w5D(0C{&4Hvau|`fjpaPz9Cdli675yhXz(8gcR>AKE93S# zT9H)dV0uzQ+WKb12IhaIB`hs8c$+wEU3w+SGeJPq{KrBf=5Zhyyv>~Ikzf--E;@~@ zH@7nqle1cQe3}^qeVQ#zPP5TEwp)XCWfJn$Cd<i{MHPgsAQlvWye?@vD0ZQAjDzt+ z7-9rTA4d|xla6e498=I8psNO*@Cyuax-T~~&YPuJ&DkR2072$F?AWAv<r^t7qn)e5 zQMYavjjZ`$rHb3K(>m%L+-%jLf3Dlm1pg;P%34|U@DwX3mS}}U#n=XcIR!?8?l_S2 zaU|zH37%3X*q3I=;+DhL;F16Sn0fxx7KwVHnjCcAS|ZuqHm-OlAk?b?%hzJ&u!|#{ znGG{I$AfwzL6t{Fr-iZKSq;KYGi9ulWwe@S1v@1NYMT#*12sRi(9qhha662dv)wj$ zuEWP1SopDs8FS)89ulz6VSA;cIYymgZl5W;Yt17f0PJ^%dg5ZW++2rg3H(Q^oJ2`P z>nwsItJUw=St2Bs;rCEP#vz*o#{^^(xZ1}y2+S!k8r(}BH=oF3t#&C-aCv>~osWk! z2)FBCL>m!sHnR;}m()pSZY^FOtEhFN#ydke(`LSj!!C{hGdIYIV;qVXKJM2U1j{^F zd#xH|=1nr3%@XC$vn^nnhcyJt9AhJt0~x;ap|_d2U<!T5yG;iX$uONHu9K&g(K^fQ z80O~yH>kN}Hq!S#+PpJNm5@AAZ!Y&xOhMh1Z@@ue&N_m~W}s*@R+?t!N@;%B^>na( z3R}RShkT5)#;7e`g}A@Z!}sY5fYQ)h;DZRiL6%FlZG#XxhB60lN}1x+I+-A%p1IXr z_M{ovn_HN<Jq3{&PndU!63ViXBQzPz%t<uZ2{2|Na^Q8JNIAJ}B1w`$EXeGDOt;62 zrNkM`I)%_ROp7)*y0J5oAgx@RJ|H@Gh3Ftudm)n9j}SV9L1Lip(+G+jMl;vA%m!Y~ zD{=4+C%kW5O^NmHd?V|b$`KgXv}Kze(r1E@MRnHA5F`|`K@naff{s#g9Ko6z$AH48 zrFH#6CrTbGc1$747M5sn)Ock0?2p?WH6|fE7?sqsf_*3~$nz(35UZU(G27wy`a8JM z5hM^JzxxR$l{tH{C4s^PF!fUmD<yvPc)%}bHJzWnf$K+P<fbZugdQ}t_KN(1jcv^7 zWPtiqkYv88ydZCVd4op;B|O5kR2Ajt6@wgBo5JL{Nc|aU5r-kyEYsVVTl1%mtx!#r zXZ+Vu`n$e|oGW1V!h&$Ay(hU6b{SyEnUB@rz_lGQwVAg$#SRNilZGNsYq@1m&cGlj zCdJ?a6-<i0ln&4@WKOc=u#2ND#}%f6j&CL;%LyaV1Dj+$YCfm}ZT=Oh^1LTk&_LAB ziuAD7EIPF&-L3W53X7nS{#^v6qQ#i4M>xw+o}6f$rLuq#mE1N{Yj*=TQr8@tzPn#O zk%%FPM*px02H`qaE~QGTeUOyxj%sDpMW0R=tP^YS4nJgpDP6PCh0$DJmhN$K)zGmU zA+;%C60}~l#lV7BXQ?>2(?eD5n40BUtDyCq!ur<0j!#!cfO2fo&7fq)R5mwJ`O$-% zP&@<S+1hggn#O(yTe5f4__DTzxngNTS|!&()}nlni3XRc5^M{Iq7F8C1Sax1HmqHk zu&i*WV=Z+?|LF5wZ}YPR6nk8V*@J<A3y2vH$~tHQWgD0feVfC`O$>!%a9IZ}c`5T2 z2kRUaW)6EoSeB_Pv$9vm2bJ=jL?owY<*r+mp#B?i&0W4WHzzYyDf~vUB;p~Mw0gUC z&#wrQaIWz^Z9sI6m+>L?K}!fB61N2|+@IlGtY<W$Amb%~c!NJB!r51;LX>ne1zjmh z8Jl!zIc6^sFte3RHyNVKBr_p;d>fN#LNX03X{njbT6y>CGgjtc!#yN(5fC*V0rdk5 zfJSNOgUF6=j1iV_8|Ucg!W~9yO{Oc^gZNo3Q;COi+OcZPSi7;I)o9+D;UbmuW_z2_ zv^9saruEeq-ylTCmFzGSF(dlyig7Y*V@5$;t1(_vxG2m=C*H79gL_<me5Tw504BbW zXadG_9ElnD9brgV!jt<_Zl~-VJ~e5?{XL7?8Z5Jjs9oQioM=e(u@+!F$C3D8IlgVp zq0;!l(XINBroj5t>EXfXlp^8RtF)%^L(dLbFk(3-i7oXfFvpQ-(1&VA7!sOrx5b9; z&&G1+_xrbaY_CM}@TRHS0-hf|YmqUD`sW)zo-k%K@NgjOQ(&SA5}L;T&?Z$VW2*eJ zouq8gt2%cfipm3BKoww9G8lo|r@+MIwjPDw#Z?ayv9z$dvE9*TSLMc8vQ?pT7mgjg z|LEL>$V=kNl^Ail;wG@5B9&k0`4p5(?K{af6=t{ZL~`fX$1m|81jpZTdr#OSaWZ}s zb5dG9DFze7Ym^6CfF`j23bFT+d<6OwmfL;|`eNI}>}Ak!q+8@e@A8iG;+XmX&mo$Z z%SQ;Wx&|Dm7=`Q!BhaU~T;>4u#r9Yt=JxJL=N={V*J--fE=)CwC5CJ7Vnd(<$}_eY zxOFyre6SE6LUTKhLtkv86apF@^E;K`^3(&<cM*}d9_A}lb|RCWy_Ges5R2I$Hn-_8 z^u=~)QXZY5-sg=KVqW)QQ?mc0fGg}4kkf-srU_vJUCQE1g}INWuj1atl0RbDyIAg| zic=1L43nOw^k))eYGbJWWy7uqHrXr!>f2Sc9;>EJ0!)Q@WV1#I$gy0iMN8=lYcDH5 zCBSAomzZ8u?!R3t#6D)9hTiAz#4c*w(chOle&kF3ho3l=E0EC2EjFFYz)zIFo=sI? z70OtO!&>wOQ{sHF{VA;}&a8?6Xty(Z&?b7iD^Pu!AyuDbNAiAzwy$CWeX*lkbS4WJ zc6yhGSYluGv1;l75j*BaV0~`Hxv2M^g!<B#G(#RU)#pgF;$vECK@lrLqRPf|ygGJ& zN>h^g0OJ{SpFnI<d`vw=M8thms-rDbxA7odUtI^qawm>rxs#4PN6Qv7+6xcbc$4ar zT8=UN&uDH}QG!(Ni8y`jhWgs6I|6dHY#p;|$pug0O^T0ct%az>ihyne3NM7ngzL7_ z^p!46%N?)Oh3mjA!RTOb>;gzqlE(;9G~c2vj*>cvOu#M!^>t*EZWLcc$QX+*NggLe z(ZYl-Nf^OoLUvGJ$9HH(-h<0ni$aA5J-jWeGBn97iU8IKdu*(1gZVnS*V2jj@b28j zUgWDg7{gNZgC=@}A3(IC2aHu7(fc~IQ6n;+k3L_UfR)x&e#{kEzI7EC!tg;4<37Pb zMT9+cIR*Z*$F`|9?nN2dx$Bn4y_;Cuyz{Qi$|D(Knqetei6{3N)3iP!5#mX4MuM&k zeC<-|fKop-aN8yG-$jl8x3*gr`nJQ?d}1j!@d4z7ycls+$h;61$Bz@?FYt|r;F*>w zGjY`p(zLI04o{1o7rY$7jLn{x`eRz*eQ{;+#S~Ft2%!;N-715ueD)G2!n|vUFL(UF zmk%ke4i7CA>+?%$!2j6cX1*y4oknNiPx>+(wo2IvH2|gr{#g<Iv_8a)T!bhL;bKX& zAl438e#6OjB^D>Oi)IQh4@VQb5j3j9IgD(+1gbBJA7x7UIsjvxK{Rwk?edB<Ezn?- zFbd*YL~}`;v1GBtHy?qQXHR_@*eSX+Z;%S|H<&qV7@;1hw?9w11keH)bHgS?d0kjO zw>}EWL%Uyu^oC3>8-v~l>R?8BDHrYNh?F*~z=(f$u&#-?JXKs*>ewM9a%ibk+%8xm z%%htXmyn85CzptQh7By>U@I3V&|<K{>6!pzZdBFM!6aBx;U~hx58~Ftp4{;s_9R1z zhXSPu+c-n!lsx>^fseN@pwz7dqVG+-wX!TTCu3ZG)gDjJ;bjAA9@7P@v$BH=T^8)Q z-hx1Hp0tiwvL+{x6q0uoLuYM(F*oLZL{1_nTfVUIFf<624ajXcRLWB=r5Z2-B$!eR z8m#j;iM}_>K$Cf<l(fUN`70#tR<mIP%gSP;7w>7st;hxiQ)sAC1pYLFc_I&%yAax{ zndowmWpIz)7u6f=Vhs}aIxSfp2-^p(QeOgB>uW4`;zwe+kSv{2HAMG^Ra4B{>0po{ zD1C1tm=_`>%2n%e&Yg25q_;C+n(ia^i2`q)q{P+}GL@+9=m$g7N)1`D23O&d__55E z_RbT~6!yw0&h=0zXV62t3scnS;QD6<4|&A~Qs0|Ua+{cI*5?(2Tli$jr1jY05xdUw zPU}f>fIwvh`2jFD`g#!-#rYfx%z2Vf==mEg%7e25H(j!01*mt9r!@h_nBt~}Dumah zvLTdS$-cHigV?63Yyk75PHuJ(z5NKocHl+4{rmMdhkh2J?@cHM*Tw_!3P?Z5GHME} zEN*6lVhJ-hq@ey-^2p<*32Uv0f_R?5LD&I2GtPBjat^ArTCqzI1ifX9H&xG{Z9L_f zB&6n7COIFR+@+{gd03=CwTC2vmRQNlQ2O44)_k}QpNm_mxPu0=QDpJ$4ubJ!kDLQ^ z=jDBsu(r7<Fy~1E@0?0{Dq>Yyn``}Y5PVm;VVL?<f<btZ3+A0UJi3^WIuCOd*d(sj z1Z&ja=!Ze@btv=b*(tS(Z~-<@0Z$YGW}YSSw!A`EOLP=?^CV>%-4ULPlv;`YXb`+< z>3xjZ1q<R(#`bshlqYw*#N(Mc@ABw8LUwqFQ_M%T8q*dj8xvcUzBd7gs9;&w$`nXa z)5I7AH4fgQWfMy17ELhcNy1JiJ;%tFE72neg3o9WBpSrgEiNG-;lln$6%-0v-<vS< zDbZSR_kC=W_3&&hCemQek>=d$L#CAx6qxfQp<E)+3i_KW*x+q?So>o(9!A{2HC3FF zIkv?vT-b|?B!Po{k^0_*kx4;JRfwIkFrHG(d{!}EB-5r2N;f~4^CWv2#Wwt(OK@?i zZJbf*e~h&sdij(q5X*%M#g}cTUzShv6|}xLq1Q|)(Jq;IKe`Z;szgK-(0LSu^Muw< z$BSS>oDd#RciXIL2O?7!kH7;o1HH%Jfu8Ec`t$1ZAb9%Tq<|p{&d<lJQiJFgd?5<V zc_QL=ta&KY61ZbV<b%EaIPCJNA1K$;R$LF80`kL3!PEC91zMQ5kra6#;%qZ5Z6DEl zC@|-VgkM3_qw4~2YC*#EMcE9k+s9c|Ojl1trgE%WIW~&?3gUg-qd)^o`b20mCds-f z6nGufg*O7sc_QIi`ytJb5jvcHD35^2z%HLUv0Ww6ArJX7rnCunMvY=r7Bz2EV1s1- zA3B>b(agNb8Y19^$u|&S&JzK^qPmV6<&*=JneV()Ek7;-6&jL5t>Og3aP}#eQ1pV- z%|tTHRVg>VnAQ3zA5Y(#6j<wFT+{9W6KOu%Oc&COI)H-!bDjtQ;u)c;B>IX{0ySHx zAD0?E2`WiUH{cqW3+!HlL`xCE)wm^y9Nr%kvd?mt>FVni;<kI6n`9|?-jf1Y`ragj z$jQ_+Q8Hi3sSb_IlSAea0p2{3@G9OMe7=KHf`+&HKH>yYkQidkYv}YIyZw!-)S;>} z6vXOiF+4vg<T&)&SZP!GgeM!Oh(MIei3CgFb6OR^(D&vO0U=Z=GFu|>?BAn^Y?jVH z$D8+K0RNU>gUH7QZ=Oha9H@&6e9t5Mnp)BWIR<&s4><`!08e_%A#cFhL(UiZXTmaj zOf29E7l-|~H=9&Zto0&8xD9D8c-2JpD^LNc@6DTG5WG!;XyJA=te)zevTU0J^e87i z0m}<fIDIhb>9?LH9Z60ta4_cypXYBP#+Lkb;6T#bD#_n>Ne_Z{UiZ$$Jmjeri)aqD zI$8|>Z-0E7GNKo^$?HWE5vELOdlbFzKJn!D-wuKozfA+Z(9eV^q%YoCLK0(JQC@y= zm3T7K)5HT(2%c{|<~-r^4ZJbo|7?fHRFYkYUKhNqBc6B{<G@3rh|20{F#;4wd19wB zqW#+>^%=_wYIV#b!y)l|`SxK{(1{J09A^PN=~S254%$SdRUliRh2F~#f1WVujxb)f zz~B3i`<1CAN5Lw2fKtr7?Y`>|P%3kC0SrYxwaT`<IB~mIU)x1se;w-V>$yebxPAat zLF3{1j=p|3#zpIg+ykr^Nm!fl&)(|lvu~c=6~Zybue8?wTfm-^^zdq+uee(o(R%3? z1F=)|!mJrOJ_3CH{A6Idh!WZ#+_KYXt}B=&?Zr+#klRQUnK1Mr3xivTc5^&sAbAu# zNIXw?=Z8-r+Rm};-Xf*svOwIae}*)F;uO>c2g#~_vIi_k7RON>z(G9v1^tA^txO<S z?-t+^jZ<}D^OHnjy+{J=xkGBblXmtXiJo?Vn1*4u$gkTM!*UzmA4!<xOSel2ts|4y z<m6_pFn<tIx2L-I|Ayc1envA_Co6hJ>)7R)xq&rHW>~a*+0vLNveJwZS0#Gy07)&M zL(M^W<oEk;P^+PWn@BHn93;mimO=%W*3z}M<styQ7P=GX2=<e7gz4wh(r57#CD2VA z<8akudtt%;gL)V?TaL;86*)v_iE|9igz3Bj)}w~)Jo#V~4Js*7z!}g1ai{LO<@fjh z@g1QH4nf(H!r|{dckCt+2@rV)EprpMsid38mAQWA{2j_kxPKBlH6X1I_IePyGvx2S z6u8(0+^}7O@Ad9JA<e_E;g?$v-r9JWqgUi?cDa+fm9S32zhEe$mfi=>zGhj@Qv{p| z{!L3gp_GQ|oY?(y5lRo;kKc$0-7g7G#dt{TNU(blFViYFUg0GX;v!sNM6h$<r0<va zVyyrnydHZsa$M}M88pRdFOG58cNln5o)6an-Km4Hx*u$nuvn6KPkqMb5{K29KV&O^ z%UQ5~6)fiotaC+Tl$6h)j%e){uj}>fJ~_-LG_vFr_6WT76YA-71F1FAvwjafuQgtT zIPPHog`d3Br=5}gQoTqD?;w`?6Ivp$-_@w$`l5;`LH3Cqnu82SRc6AVGji6NI){g( zA#Jfo)WmL{n!sZDXVjGQP)D?0ihFmUXjE@dcs!k6<{^xg#Xbjn0&;JT>1dpIrwjWp zE^7sVhvJD;FOv2uWQ*<aBXia@Y+qDS86O0`?tnJyv>u`_porBxMIPk;YRWCNDyww* zQ4Hz>!eMasNLJaFZ#DKg+{PNZ@<eZpL3##u8>frkD}i!{!linVbV2@gGNHm$!}vuN zot6AvOJ}f}emK-JJw!y+ponaqXvnH91qBDqcjF(^_Y9?<JW42~(^bM#@rVfbx!{r4 zFK|&gqAn5s3lh>9xg}AjM;zb#h~zgvHv5KY%7z+@S3HoCC}l&96!EI|dc>{UP}gGU z=K7KqL-^?|0Y&H7%##P!T(QKcDSu*j;~-uXXD$#y`V6982~Wjj!sqZgDrl?^h0o)( z_RxP}R-GRIjrAglhzyo!OwtA6#`QiM_8-m-tNX#>jJpfSp>me#5YX~#Au<&OJ0&Mj zV10)h-^afc97R#Dq%IBW^C*@!5-KSbp}VHtldvv<A>@w57jnHw>LR3(NCYf<bJ)KU zrw>B2EYn<A)eMJ#R_sG$s>&%M=}c!|@E*=5)lIMJCxk8y5<Z70y!k&usByt(M7nqt zexP;C>?T&H$7_O~{|R1w=OQEufua!349^$A7d&XLHWGf_9xu2&eJgpvrVZ2|`Ws*} zB?VvE=`N1@gDQ)%L$b=Ye50|?p_5P?F#q+lS3p{NcH-5$WuFQ^3VP3<)B##Ak`AL{ zFVCL4-hW$D61@QB=<FH(BQbZMgx%p!bLl1W9HjmfpU@?M)X5?!QdOJ*xq{ywBnpk6 zEL&w;c4_Q$xGadIOFFpXrdID36%JtWzS5cruSfVzTDN?$MA!xEc|QDKRCk_$y{_ic zIcEct&aoCGkjS1g%F1(CoEXVzqR{w9N;G|AbR}KaZJdscj_u?`9ot4H9oy;Hwr$(C zZL4G3wsp_*j_>}dF;3O4J(u<#bylr4tHN@^`|oU^o2c1|_O&X5{iC&FpBJt^X<rZI zUgvAj4qRBt0m+7`T6gK*HpJhUt^V|pT!+dbNeEONCu1!^tG8;D*9=73s(O0<__KtQ zg9!Yt_Wkj=<@m)8(Xme6)!7(W^e;cmkG|J+Ugu?cKI9_vFp7ZG04361QKx$*Gw(zV zY1PJAf3DKldR8eqRe_MiT1|<&c4(#FS{L>su%v<yajkz2v;|pU(M0&e93WX`B?<k> zYqv|a!RkA~IrXcL=;A_%)Dfc$0*vp-H(sM+E78lv*(Gi3q`T!cg0lx|vizTsr<x8| zaGq`pkhct3(UQI9?ub+6Cp`3EE?RyFbyhh@KD?nSlmC<dWvVDr7g8?v7Jn}D9)E)7 z%gZk{i{7cXeB?{p<!u#GKDkj=oV;{Sftb-b4zW2UjZ5F`)%!@@d%;1R>W`Jm?c$IH zX#Dr`sBmt5W$3%=u0^LRpT>P04oRdeW_%udu4UITf5-$Lh9U^|-es?Ok@=Kl*04ux zJQuL9f_&FdlSex{rNl;nB2mWm<QVNR5?9rU^kwXfXm$#ckmJdH<rNm~K>1AJ7+&wf zNM1L@@Y)^bEq`#*mP`eCv%X2W02A4h)VOS4Dak%7e&Kty09vv|F?h}?3P8+TB4#CP zh7B;lg`Iy`n$41%O@S2jftm86_WU@obyFOgko+1IJKe8e9nj_3@OjzR^~8XWBs8hf z0N2m?5xI)6xDa1X!o`jW=CH**<5=3nq+<ut^;RzA`M97mH6a$-X2ii*G=RF<jn!u$ z20VFtiAwUOL*|mtG0uK>m1Z@P7lf~*kTL?TZIqtSao0qaNuk`3%3r*Mogm9RR#)JS zR$9uTBVRx=>P1!4JT+T>f2`CrQDgNBM_N%_O)Zz0b}=($bD>#ZZ!P)hNDte}gKKiT zsk(YfHz^RtSfvG97B@v=;eDXZT~qo!dQROWE`mY(8+`2?)}&u|seZ3rrNB)yS@RS` zXo+ur)>pO`mh*CY{wv-tU15=<SqXtrCP6A1&56U6Hwrd`b4rbQBfJumOuX315_$@y z9HU0FXfmCqc$p=Ix@pkTuq1TdS4(8RG=dL7+F%7$78{t41~a;}yWX4aW_7mlUXmU* z7itPV>8M25KxIh5V>!drOZKjH$HCxhvV2L21dLbCNwh@4i#y28`9HWH4Z)_16~P{p zd5v3EN>(3B^*=E;<G$`wi;7%_C^Ol}$*O73WJ)U@l)_LjjKZghi#mQt?^IQwVworp z90{ki+@_1($Mc&zu(o3$5*b`B3mng_e5&vzN6rWS?X^V*rD*03M<=5Ubyr91%oYoh zrbF2a)GBhf&JLzitwH9g9%tK0qDI44pOsnBfhx%xCK)FEmZ!Fb!dXcb((5g_NVg{V zGaCU@qL0C08vz9aGY^C@x^%ewvtt~<uXm^qF2yNZ%4XXDw+Qdt9ez++T99jQ!i*{L zh;I%v>$+xi<XS;ByJl|7aH5rID;j%wOsr3{657Xvkp{8;nS7Z~<=&XrO{c_a7Y62F zkz-gR<Q&i=Y|b0%9+e|5b0&{gPHuLZ0b?5we-K&<+!I)7go>GB=Fw3!Hc>9)wrOB} zr}2!zE@8tJ$qAp!h1fdBmyz+U6~$sJ=!F#@F#bwyqOs8Op_lK=W29=lcSbp02ATXN z{p1;+WPX>dbrtA_6Y2X~`$AC&49aQ>h7j4o8O3-!6eqG3U^KilddWTs?QO)ep0SM3 z+zE6{un5do6<5TE(ci#$cA(}j&;EspuL1&j23<*Ks0JGrRG_D7zIPh4^C;nF?FrD= zb$epD{xI<fh^gm1X3eA7c@oU^VVqAQ3lYO7O#!V0dIafAY$;s^`(r~O!IV5I+ELHA zN-DOwm$h8Bx#@y3)e0XrzrZI<*``ON2~5c%=d~ESL#}^Zo9NTSU(NW50ARJyU>}v! z6eBckF7yjmE7Ah*&)@igg6L^MsG1T*6g)p24Tz0$`W<=jkUbc*`)HJN<4HC=`t#m~ zrDk=hr!n;Qdx**n$TyJ>b}cOCE=;#yQ$F{K5?r#Se|g`hjdZFgI7!Y%H~JVoa4=T8 zW!^aAo5kvlQryU4^BB=}o@7B$AhiL4>JKETmy~*($>wOzFzt^Wy$FJdF+$_!LXbMY z=u_577Rkg#vUrY1D97Hpw-(qKgxxChyYSR6$^s_n3j@Iwen8GHI=`Z~d@=UN=F+(f zjoM6QS<aK=K|Zpj+%C_aXL<3m_q>k;to>e<ilq8z-Q0ehKw&5QVfwjzZn)3ewGYi? z{jQ;UT{WX+<`45iMV3XOtOP&(cjve0n4%)(5elqfW_2{JqQSk^FWG`SW}4c!$10=g z##kXXEs(U61>8kFvaoa&7S(xZg+C8TwG#_RgNU;I#(navHN7NJAt`FVn~Lf&Zr+{p z1yAI2iHP!M;&iAc?GAW0#eVUAPh9Wb{gB!<7ZTNdPES)pCl?pP2ep<j@OS29rs449 zt202Vgl7MVAmRtX0xR*K0Lh%K@W(3Q&9RHElnj4F0Ti9G6U9O?Gdz8hCP=W*wtp{g zkt{|O)>$ZBq<SjdDbl)>woV!3J4RnuZz@!DXfz*nGEi&Ie<^l+TMHQxO(YP|LBD*J z)(DlG3k4}3DkUf>+E<pAc&s}7#5U^4CfuAaWt7}+k5L*)XvnYyv_<1qN+(ZiCbkXD z=I5F#Clj@F;k4r<GS`;tpbwZ3gIjHMx?6h!pFbY_@F)KO_nSghFx-{NDGMx$!{!$k z+opcdOwIQP<9)@hczojp?Y<mzfN#Y=yWI_Z{!}%)acSdo>l=34D<0%~*2T&1FF0`@ zVhvLK#jrO-kY9ilFANoVG#XE>DMSY4Bs|(P<517mSm2Vw4SG~&4%0Yf#9)mYM?Gj( zCBq?%`CU?^dQVi}rR;dfJkIAQ)Cj03PF*dhdy}WWv0X?b4O~?mZ*r*RFnS8<#rI9S z2sQSe=R0_i0Lct4DF+H7{m*hpT;qJXIkq><;(7bMhY`Os3U|#3ibL$%bvo$Wx5o?P zw;UP`LICSgxl}ZY6YJ=ITjk5%<F6<&4`Gy~Y#!!{_EobAfMi6h8BUT*-T+HW6ZTX_ za<I8Y%~9F<THs}p=<+lMt_#lPV-QvITF)Q!xDUlt=rK@bbl#X$_h@5}hmaSR6I!Ab z`Jh=J;+3j)<>oILS@UdKGr>ToCuEpoKz`v{jbMSWZm|Aw>By-eKU!h>xwyL1ac+*` zs?KGfo4F)3`zLdQu3edB)LBaSGt%EEM^y=1{3-qHnX;GNcUyX-$EviU%wIS|YS6iE z2o{LeV^UnMmnruD-Lko#vR9m;cW@!f)TL_stdmQi^HLKd3xms4z+sk@dL&TzEA=0M z_H;*;6M&I2zO>KE*u}%SFOXx{BS@KEE1@<A&c}My>h?PDipsU~&bsDOg9lrG+(qP} zvy;PLM2>#}nH`W2_$ugBX2}bOI;OOT-w*Tfje0RWm2?iS12e9BSAsMZz($|Bsh_xb z>1RxqGl#8@pP1}eE8SdKPLWz%kHJx8p|m%qLG2DNy-4dS$iec7=4qkx?W~&Q)w6=| zhbFLlC$X_G;MiZM<1c8yd{a-5DUD`dO#ZqJsG<jh7p-<pM&0%f8{&q~27T+H$8wf1 z2fTPY7T(-;Su3J7Oh#vLj8S3DI-2gJHv$JDW!!3r?vuy2#lZJ#K+m)nfnLV=5_^|G z@`UNMPWvVjs@d6gslhIH?e<P%;Wfy|vG}K>c>C{=2NxRk>%GfBS=?ViSd>k7@A-P! z;$DqJaJRC?=UDZjI{9j@tL~d0k+l#P_i(y+O&&Nmf=|)bb7(w0w7aS(^6R1~lrP2g ze|%N}=cHm@h!}8yG;ZbhT*s%D+IO9;kX{<nSHp}(hz?^JsFru}>W@|3?<w7nTbsqq z1_>GC3U9j)4OJiA<texjeY?a+h?FV(a(;m0qs!U0;&WH0O}`~KVj5e8db>MQS-sOF zxJ$01tg{QuDv4K?gFPE}f%58Ex><ewA$FtDP4&{4Oi~pNTuSl5!Bnkz#)DJm<jRG? zZ(tWm>eR|H9ABMm*P!Qb;|lBi0$fkk)gKwnv{;V7-#UBKs@u*X&G>rzC@WcQzozFS zXUSV_I(TC_;X7Dd1W}%)z1#SAF(kccy!sQqRF*eghsoO)h(&3g1<!?wVjNO1ex|If zSd9sy$V+BQ_*7VEmp;fobYI;{)Horl6eA8{%%7LE6*i;%{T}#ZPzhcuNf?jiw&stx zexayw_t?jeH1amWuu`E2hLa2!!ah+(7D=1jZMb}S4sYaC*%X|Abz#qrpjR64o+vHW z#OG5!5=0`Tk(oP6etNS^5$7>C1xr1F@vYD6Vdil=ns$EpdaRXqyUW&6S8Y=JZ+IUb zpR$Ij5EGkQtP6#&y*vn6mvO|f1^7LPK{uR?L+@{y+q0WIW~8H=yg9fu%_Rzkt--2| z(tl|n;k=;8o2c-F9|GIN_*>J^z3+v|bclpBaJ|5J*IPeH3uW=5V6$LySI|I$B%=KU zy<r>9$t-_om0;k+fF#7i6P9y`Wz90K2S}NMQ9VNVHvAlm^X4T4xt<r4wku^J05u{0 z$)|iO!qR2g{D%uopo|jaBk*K^6~tu%Tl|5zG^>`Hymg2H$Z#<23Xuxs@}e+H`%+eY zAeJ-@p>PJ{tDJ8x0e%k(ddp4y`__LVQrwq(2a&Mcz(CNMA%ykc0d-TN8Act)5nnOr z3AKwg?}enxo%MKr6+9u0MK2K9UYQH6m+lpWsmB`H@wX_`{H}1&M=l}V@0*O%L3Wxf z7+<JI>8$`d`CNCZDk?R6r9^!$&r(LOn-Oe2W!sdYIc<*g*ehhf_OwUr5sWgDDMWCE zy=4dzMj_G{_CQFucY!Ok5w!yY@sfpGkS`uf8Eo{TIEV@U2U7^rAB5j1aZ{7cLZ)DP zx%ky-XY?)~#NBak2S~R?->f5Nq#zB5U#SBjG+}MVSybn}_fh|i1UYiLsoF{>ssW#A z)oi&8yg9QV^}?%&0h#1_F$AjB9$8<Hybkn<Z`i5DOu>aJ)L+ntuLCtN2)(5~LXQ^( z`nSfSF1`u%t5Vey84&m#H#nEmntU~@<8fM=igK(WI4o9Hj1ED&Y#l<p)lx)*^WmYk zHvTD5Z&YXpfSCW}cF&w5FWGYfjpRbGp|h^apTo{}_eqr#GLnOf7I%cT@-IlqFmf&} z`sn^y_Qo|qquZgxh(7&<bINrIy&f%<^vc{+aP{+@paPf5iAASD!_SGPoyyY_vD+P* zi<AhgK%x91Hg@B!JrZae7~HD)GW|dJS#@8Ba<&@>TasS&k>QWD@Tj1E9*0!!iE_Vt z@}lD_%#-S}{*t1=foS6KyduMbVyVu*&1+@-2wBK)Hz_FMnkQuADgiQr@v3U(*b{?F zdd8oBIU3`OVnK^3SS!nwcVmuRbZfP4c#@m9I~M0d;g=m&oz%GyyR;*Q<10t;5zF4@ zswMw+OgYqUDg4OXUid0G6_qw{d_L?d6*5a^s1{G(Oi`X#4PTVVTSw-$TO&iSi!7oY zpV1ZmFc<R%62(z3_^Tn@eEP*q)Xbko_Ds~YIZT?I98|Y`DB>f$AEJ`m(Q9Fw2~@(m zU#@JngQQ<rB9KL?tE&16Q?gHSo|q0nKZ-O(z>^}qtvblP$N66!bo&gEbZZ$|Tj2-q z5=r(PLfM`jWOE{X(l{}Qez;t`)~Z3J#}wi`J(^ex9mdB!+lkrs`66~5Oyhrg?f;`* zBa0kj=o2&q%PU8-68@)N^H__T+8DGHf-KWY;Q0cMg&ey<nZ~E%u$BKXg4ZADH$0#b zN?b&%1=ne<j?|{K(V-@lfI?jAj7T%2eGw=mzs-acFV>nCr@x`D4aOsC`{83C{vz;9 zadO~2ltSDwQbLy=!OI1Sdv4YqZK7s?`zGlgTW}!e_!0T<uy;0Ly$J24yvfuY@C5Ne zr-6UM$z0Kk-fQ&`Lp%jt!eR|7E}x;zkhJ52bpm+0-%&0*mLLL;3O<DKcVgG#GMQIg zIr!W5!`p>x!k~^)FB5Rak-mz^ny!o?Lgv%%Mald-ryVj5-ne9i&KZg1HwM`_j(QAO z0}C^eaNIkYsCv>6hrUDQcIwOqrXjnaNdMr7E&tvY;OF=f<9k2hORhxAY`-7<Fcf$V zDmh=)5Bi8a!#4RkLg@(f)Z;TZ=LlX1(J+$&Fg~+V?1;b85OVo6B&k|uDe@<yoht<- zun#y_kGAL7(;BSHU50Ezl<ecoT+D!{($M6yU*4k6Z#Kayt~*71Qf(lEjBWB7y&JGA z3{MUM2f|sw_o)WspvRR9zkt;UDl-V`ovE>zE}%aQ?6Z_XUI!^HC3|%qD&}3w3qi|g zA%6`9(wS@fU~T$g)4A2Vm_{v>Tx_b3;nP=@)UKE#M5sqWg=@YoNybxYnjpU^$!0Fm zxI<jCwJ%{=9T-!M2MZ)aN4-UsvT*byBp#LTeRSsI-0;UJ;)nLxmrQ_=K9>OxZ3RUa zSRU}`hBI>}JYuU^6#pjIn=zr)hplgKnt8ievv@cE++o2P*~jhSF1%IMV0kpwqf^hC zT>SFMxL(77=$mJC;i;b!Crj`+AW@J&jNnC4D2x^n{Fjxcj%wfeH!{yO7P>G-fnphg z7mlibz#zuALLMDrH!bb3is)u7kL~TeC`OH<MdDX%Wh%5#?r|{9kA4=G2@Am+XYPec zHs6J|`&)&p8V6H6sj1;_t$qEv_uQm!MI=X46U^ruq8DNe4Um}MKSqbTN*6q<_xA#b z!a-xs{I1Aa8qzgp-sJoUjO9iM@-|AMb*NZ!q+ir7q(Ok!FVYErLHFTmhnKo1cB%0s zz@hHPOTrfo$xRhd?59f3lsOQYcbTqhdYv9AIqN+AFtb;RMGRqD$_*Y!rP${lg(zYf z^qX?%<%Vnm2%8$mgi<VvlQY8moeIpPhMO_V324zw4x=Z{ZJAr6KXiR?2uUQY7r=51 zN<xN<A&Vw}0(*7s()~mDlPH?)4!thg@Oy0pbT<a>Bikk>+5~xtw#?g|r%)*hOCns- z^PzzqYQg42vVqw&ThvfLE^^A86h3@oqfxF|2{1te=eaO7jKbqZEzROU>LpsUDYmGA zPsT1Y_oLT+S<RxW^?;fTisl)K*yd4mUKIQqj<MTu_w46?_e`ywS7u0M6=PGOhN`_o zhOuQZrjV}cgOP*1ksBsCan-@Iu&yVsA-)(pLr|uW3M;6yx*%|-qmDr$w7KsNNPWpz z?vRCc!7?d_Cm6AI(iatsr8BiR3%>&bcH9P8Tfx_OLkGYC!*xu;dzqSe$rM{<jC6CD zCIZJ1E*dDwbX#R2=T&>qlkgLm*NtK`XxGYlP4wO%=f18bmiXw`jlX14LJ4=4iErgz z^}%~d;@TBDl{8iiZskPvaU@u@kHcN0mhabv-=djjhV4FB4BA)nGa205c?$v9HN1r- zP8_im6m;^P^MA9*w#t;x>48vl=WD_^dRNv+r|O2?^Iu?Hvfod!P-$}<&Nr~Wj~xD3 zj4A@2EkFMe%<UJ8dq~XuWU2gwd`tDdBt~HKtOh~UBzb}RhY~_?p&~$yh@aI3hH4!K zsF(y$Om1Xdg2sKdA|0n_#(xr*){NEq@OVdmA$6;Q%-SR<ar8JEwSdiW^b{K13mbQ) zG7%mUbZ03%lHA+RCL*xd_qdkRG1))=PR4fEanuty5Yk+V`72NlsK{<D<`Ea@M|1qs zgD0=pWg_)tJb<~9xZP?Z<!Z3$&hf)P@Av3=FSSiMNk*pM!W~yGcvmOlgFb=r+bo{^ z@2LWrryo}K5cU%Vk+2VURP&*3aQr9`eal91Ewy(3Rfvgi2hX>M*)2C#dGY`oeJ@ve z<Y#&Nhg^4g<TMWL*hSl4Q;jgNF7n8E7^FvY)zPkpwDzqjIl`8P1*Ijx@)AfmTC6{+ zL%<^4HM-&m?K6S|#yn>Lf0YZ;6=<~@PIPKdlmnUabsxP~-3`SC=+6j4y2y1pRSzWV zPZeiGn90ju<d8Y&)+>JPT`_-GISXU-N*02KL_S-Vhmx~|dy?EF{RcarAcdPIrSHUD z=Rx6^@K(m&wVA!hRFBAU6lm|`muM@pEu7rY1UJ_-gRRvc4`OzT(K?XX#zW<N%8H{d z#>>S)H`P>lKb03txarAB-}fsc6G5w@P9{>{rmI%V!7>!4X16tz#K){k<@J@8$~Pub zaiHtwl9>KH$hS|92Un2++%4g>D&!tE?Atqh?`Uz^lu|y>sc@aQ^5mdpOiS8Upd9Z_ z!2YBzE-7c4t3v&`KZN5L?qB(b=B~}twtPyoIaHur0-mLbg?kz?)NC3`tF3L<OdiCF zIs6zAC#0&5g?p(HQcqWiX#5xC74muF6dwA?;*fA42q8J5QaEk6>b(#arP@yiPm~RB zg~fEY#Eq6tN}~2Eq3~bXdtrA~LoKYGF}-qy+#t1R<$+ge{MB#ASpBRZn7rSn`kNZd zFLagFx3D7fP^BtaR22)<<#L75Wr3li{~Vp7#I*x2S>{j%Nv40X8=A0jcGqWjt7HkK z){f`v%fuX3lm4K^pZ$j-;w{xe$!6q^+DJ1=1xHJ_Y7y@{%zH$A@<diskU$8<S*>N6 zSZQMPw;+RfEhbA`zivX2lK)r|le<mM+p&V73fPNmTuvH|Ine#WB0V>M@#bh=<mI$e z%$(Wx6H<Y@<=^<&9%*P9xV;;f?R--^?FaUPwmxCd?l6~c5ay%+H2${KJ4BzS0a<y6 zkd}m#YN?gev>V0(r>U+}p9Z`e)WVM7Y(}*uh-l%c_Hm}mLr<2%aVCzMYGY0ukku3! zPT@%qYApxdOfCu;W!J#vS9|_qAD0e8(uW0%BCwz+!Mi=7DKL7p^(Q{yTyHayb`t3( z;~Y$_C%=eS8@i<tv!3uuh<%?w=-fnW`AoTI*!V<QSL?ebXtcK2%25=9LAd0tHFy>f zj>5I5i+?iK9Ge<3i-~GV!za`d6bNMVpcu$34PP?7udyN)v`=YSj5rcnV>E8-`|C|a zPV$Jd<?=bHKR)lISHLYBNNYZjxS0QUAd%pfH}<yx>GGWgln0l7PHEDoKSa@AkKE|n zpDH%1f|bNr?iB0MmySUkR-fAP?^lIWwT)mK2A>fx4}Z*|u?UfWC0L2GT9w?+&{AzI zNtauFHYY-P$6|Z^I92=ZXVMZ>+bE)V9R`4~B@fnSPseUWFH4Ct6h<Kii3PkYDa8#| zgffiDC}lDCzK%Imms#<Oii^JtHqTu)hE<u-AU<CINDx{5>49$4Pw|(V;GP_*Jd>Er z%7B*Kc`;=wLQ6@LEuy&J=UZwd(X3c+9`P@xaVk2eN0pk|>Q~86fsb-b3iQQ%2>m9K zGRL(}`~|x4TF1Q4Y$c+Am`1h~M+yy0V-9(F_O^tpJ(%Ea0rfCBDc(C9N@<p%#H+o- z1UvH6Gf41p)AG=z!6hE?<F>Z{^*cuhqx@3ilkCtWb~HF<BEZAS58oyZ>NZSNGCYy( zpmNnZl^dMiSz)VQsC=3IVQRj(Im;zrJPx)xb8ZS?NSgf-C6IPe=A0<uPYtPssmuYd zz?cHX=iX<mY$30f!+-E>wO`%mm;7*;`nLAh_gC^aUKr<Wn!QJl$OX0qza`1g&&S!N zJ1kzqhA1#t@IK`?p}Yq>=R|U^xJpOVzqzNccBzAzCq`Igjk={Sc5?l?WIk-?f;$?f zHa;_16C>VE>dyJPjZw#hL4JBPUW!L`Rtw3T<MG`Rs$4K=Uy<S}oF)v#z*a-7bgVP& zOa~-zK+EH8(aVX%vG%y*b;F5B3zADT#{ZD>r$;zl))bQ;MBC>iQ*TUV@);@HkzU2% z+c`?OVNTi{-P<l2_C!Kf#X$cD_LEIz4r@$`QeXWhk#p9IjbvGd>0~dHY3!HM-BFA+ zHloL8zq!`{6br*R82JBJk9niA5Rj9X>j@N2n(RpAdG$w=Q*SPo)>XsJJy$Fnpl|yN zjnUtE&hNZSj@I{oSVlBnZgwY=P2AdEg6}CcTSS)YxjFXX<X(#K<J(RT@td>rgsom* ze3wRE70)`CS6yC~%zY66@6(fWge-T8FoYW*h~jW@goDAcB87#Pt#OE}#1?+sd1vf- zZ_@OaMLe3<ohf@ecu&ti@A3<mKTz>y4~LyOjJ!ytoa6WJa&?7(aKTrfgyvQrzdO^5 z4*$lrFG7h0YER{hnUfV?{iJ$*F`~dVOp^sThO#4iEw;(gXyFq!X_K4D&o&st^(_U; zHyf(<XCJne;N{fuUO-ZJ?gZoOF+G!#)!!@=N!`#PL}C451-z2q-^kNS3bc4h;EgBM z^i<CB$YN+myn;rb<@iK<l5W#t&bb_$(1UcdZhF$iT`NLKeugw&cI!`5w8yvTd>m9S zuo640(r+Z{7mU&GmlaqunO#P3mdt*N&p|o6p9_X|tbNp+-nSRBMA;c?047fkA&gZS zX!=f%SIKmb9Xhw_UQK>RFI73+3va0VNW8n7PUtLcAH<bpg8w0fx$jVTRc$M!sb?8U z>Yn6&)Ii3F)bj2YxAArcZUs_RQG%x&Xm&EI;5qE>RK5cfI<%WP5uyV(1RIs@9H!x0 zysi7k24i;d>5|$ZwmTHRyi%;c=%<ZJx_xaDs(YPAA-4gavKq!asZzR)h(4Y-8Q1b> z6FU?+ss3#0&}ws7L-$C3mi7*-0nu3;WgU!kwLq3u*w<>pJWq<1)3;32O_z1@-*sDz z>4-&I!mFIt3i{Q8gNl8}J3Q{BW2Dh?XVa26+nz(BG~gr3Z+CC-yirz&`_yLlBTxpC zx{-!-rxO4Xp}kG^QQ=w9Oaonot?-;7)wI`i<js+NUe6<Pldc`+0EYYc%2P7yg$JiW zhCQj9G@h6j^S&PH?V)cKoR^|GEY{r^WDZxVP@BPTh>y&jx%lo>DT#}AB2M(49}J3p zMdCY^^mdODoFavy1kSs<N`1D&=D-p|M~)!6itNhM0_%zBoCVwZ0u)vM<vX6ema;ve z<kjK(n7LlYr0&kR&qw)TtV{CfhC;xBL5}?-U>AaExim8|$34gUD&-DW2cR6R`?Ac) zw$X+bF@Jv-jRxd0Etbk4xJzP`v~Q6zmxERyu)~sI0yVDls`;yoa{`pv^AqvH?Q$+b zzh3m>F4H-e+-o%mFLqQXcI72(#O<9xoIvIYZOO?=Xl4dTdl$-_P<t{!hwl;i0j}!s zVYw3dHkaR$rm|Yg{q%!;#7a;c`Og35i!Uzm=m9M}%Uw20+k8F8GHgx&82UTCBimuF zThf92kHO&drxWa>pl$MG<1XNB-*?EU4;=y^RQ0cDt2~_!iup)AVbnpwx$@AK#hWKw z_!8?`ZPMAW9if&A&}3-oS6JxE@54x7%3&3~IX{d1^l7|Kd)pqb0+7dSYWaV$A_7e$ zqVR?0*sbmIm-naZ?>DWLu{$3*yqxXEXmqfLZQ-f#_b({&H^vEImta5fKP+6R%_?M) zhUEC=p`&SzM7$W#uJ<gF@p^EP)%a%&l2-Sy`SqveN6o+B1IlmqaGnQ%Oko&<EB!q0 z3G?KKpzLmo4*mFjmX!7|t;RP~BR>{FeprqnK!@EItM2t99@XD2g`eK+a3K<e<Jb@9 zZH5`zBKYG9?t#(wC9Zgx-SSj~V7^ZQ1Nl6|Gg=Me&P8kgx%@)_UF07m-;r8rQgnSG zU~Y)-(27w1PyZ)27V_N(vmkPO=M7bpPHCj?&Q_wfXyJ7NJXfrmfAxFeq@8XDEz>7j zBM<&6FETf|^xlo><)jiWcJW+FDR*o|jo=M3@d8hX`W)8k!8ccAWjo;@G(;_b!9CHQ zCt0}hMefO0R4Tt7Dcdzn&{9^pn;||+oZwjgtJu-W&G&;M1i+W0$%m}YSXW6ARF~wI z#>(eLbrCAK>_Jrg)3&7N{EY9|Vb9PT-!l^*xXl$Ne4l?UW_NQ_eg}V@h`+dzraX34 zY<l5i5&lM8^_#%o+f7l8=5<uOhn|Ec7S-LKRj9G(+?aivI^KCWX?3?(CA$>v)gm)2 zA<(%xJLh<wOopFsc~E+Vr5NDdY&d7`y^#-Q@>dJwaS_rKM}{$f?>}A~pSHuRh7zn^ zyOocx<MkUzvX+lzdSwwZ?QQ;&W=IF7NxsIIDfk!6HH9T9`Bys{URe|pfrJ!7X9 zN9N98Ukzq*W+4+K+tCy540n>*52B9$WTjk%m`C}VABwsJaYv3}B{Mm3=P@2-a(`Ld z2oh}OM2Uu&Ys~mno3V`CKyOKZSY|FCEnQx*6G0hvdd5ydupYGewCetdoO<#8Cq;v? zF?-1!2g0=c*X&f;hrU?u@fig{!q-|bQCFWU_W93X{lBhlk1k<kGKMkfVPdDZ(mi-F zO^Hcuf8~D&N4Ch$x;i-cMdAI8Y+WJHewx9B2ucPLxW$v&jp+&%aviy(!R$4X$ncop z{6DsEY<+496AAyF%@N_Fx~0WRj7n9=apygK3X%@w8i~NW*&#u<_qKBf$FL2o*?}$5 zcwW(Jf2MM4b3?>P1_1k@_5uVodlZ|lk%qb=?qd`<Mi0q01d!+t@}m%2P*$Fyts<Vt z-u+o^07Oidk&kuEHUQ&)ZSqv2S)5IURh%<v$`-720rb|BRL{_n#j><FnOc-lTAxHZ zBGur7y3Q@c{L}P{pq1RkHD(?vMrR}y&5s*kP4H|&*C{>b&g2>v&y)ya_rq-qpD3|J z)Q$5$J}sE)@JRkmhp==NPtDMZ!G+4#10?RB{J}BqpM(&LN?CaDUaclAeT_Dv)NZQc zRD5-y72ZH{Vk;+9iTGO0(blI%^k{;R{ad{~BW25=4WLw{)gt7meraJSl*Wj|{5PHJ z(dAHTcI_?8=y+#WVIJE<UZU6nXw?MPwVt&MLUZ3@L?N|8qkSJw2ZU^Uo<s}=Pd?Ob z;`uC-WIPWVM6;{ofEqM%_w(AiJfGwBan5Vp0g=^&Nsfson~ne4Gc<|<Ki@D-8asoe z*7}^3(*Jk?)!HDDu?S&*5&z4QlU;i`yF@f}^nC$Zmdyqb>RX!Dg2l|#R0?<JNA*)9 zML?WvvFJ8ZFYH&(Pg8sW?5|<diwHqibm~U>fGGmI1XI;`Fgf`uwAA5J{6w#Kt8lXb zi-92|v%T3qhO>kVxVg?QqFj?LozYxuCuD{s2+a2(yy`fy+)8H1FD?+@EQ#b_k(ciS zI?@ZEhpS16yT76g!4dY~dC8e?9kn#Lr3Ad<y#&)+upkbOE`wkX6e-og5C<*obl8Y8 z=S@aJjyO3c&|l6$4yvLv9aBB8JQ5%=WX^~h3B3HT0B>&2<WVn{k|nD+Cc*Y0D4>V9 z<hguf-9%ICa9{>N7eeoq&KLTEGbx?J6F?VQS(%~}o1ktu0gLXjjw-?XTTo$vabdk@ znI@lL8m^HUJMa@5-%=&VNH_NA5)yO+qTa}Eavct1l>PutmYEM(P|wgb6y`q6t#%1i z;)Dx|3c{%h4R88~TOD9KN#v_}GJlM9$eDz(#oW>N4QOvh8vxnHGS*0E*Ns3WHFN5@ zs*HpArO|W)$c0lcvs1%I#OJdBeLz$w7Pq&mKLtm+(El03Usvis-~nAK#r<0S&}DRs zUUg_|qz2q{!!%#@T3S#aWIS1~g8x(n4nvgzs){>Vs+1qKOd2wXz6}Pt?AHO#&pmEv zIyB+04U-%0l(?&Ha(4pqDES1bzoiqa2ekN_o>&$tlw7DXkR&##3>6AWunxf%zxCH> z)Nv+2>+V8o+zw|7_FOH%FmO2vRRL&~9iUYZirqZ&5KI=R6=&F9$mxv3&F?fjYJ9no zvCn<^jm#AyZ>t6ky3EEJXw@TmTEY-T#f0687bsV;0^L0Nzy><I{z0*vC61Z^TX|D| z8$pb1UpkAgr>CKTgWiFE7tFXke$oN|ijzR8(!2c>L<p}doRU+?*B(=uS*<5yYG_i- zQoqfu43H&S?KLZ`1phyMY6UV{u+DZwvoLoxXJ;cx)uYF$5>if|NPtrj8}A!Kuuu)- zts3s~8j#Ocli?IQT1zX9BvU>+Sp^CmtQ7?CDE$}88=YM{e!w-d&=<i)-)Nz&?U76D z6HX?@<z|>5Xz2AgREr<!1R{(KK3S!4$GiuOcpDxPGnO`BE(UcBLCj%D+zwI48q#RB ze?lB?2BMC9tlP6>ASQ||lW5Q>J_V&EZEduNLk2Fmw87B@L^J+kBBGDB8g*}Mg39S1 zKDN^q9W+wpv@P&9$Daf|`!r?AoslQl==&BC-tY3?;~!(+odSYIalhGhlvqeW1EQj< z^b1%fCF%h?o9ukwQpgWZN$Ao#V#@I0cFse(ZoZmP9K*tYw~5)MQ<|)dE6^?@p^kzI zSm7n>0R*=5y!!%T^<gm@bZ$Rq8L5V|e2^5^)xzg*tLB2@#{L!f080;+N!0ZgY8+@X zZ<+J;6e0&|z>g0}ER~$L`BkcARJIVu<{od4y+4`>5kDjAlbD=H<1Zqb1;81Aa#I22 zM$1LmwccnV3Zdt?;Es{rmZ74;O{Q4I5+57_TBA*n$(y)8teP{-8js6(NPio);X2j> z7U|qTiPr6>B2XmC4`zqy@Bze@Nay#;59XG)!lV#>|073%zFh2(LQm5v{SchilYp{L z=Ayp!=MLV#<N#9p00TU4)p73#L=PH&jj}(72fJb4pBiHmp&Pl_J(!MJg_F{>h}>&Z zRo2sh{j$VcW)gO);RHc{{HDCeI#$2W=1yi~d&)nVsAWK<^%Wwy%eJH(fuAsmUXLG$ zRxFD_<A(jQ4qpKb01`H;Vg5J2)MNQuKz89%OC|3GckYo|t8MIGAlwQN?y|7xV|8z! z`_FLkY5V?W3kHV*FskEl(f5zpsokG7yjIu=lWNS{pA2epL)@silz>WC^I}~;Je@~Z ze77ApztxhWu6PLgVOIm+P(kO_&`RGi%da;>3>#bqbXSvDJ9XsjD@jE>_^%^)Y-YL5 zm!$nuc4XHB*lCRz$m`W~h=*%tZGGi|4jKjFuM=W~d-Qp33a5eD+3G%<DceR%;`??R zc&F%O)<uL>j<4bN>nPf5W_?X-s<CiHeozhY#?3)4NV=ID(xQp4JnjF}vNCF3#E=NX z)&K0QDu%CLfziDk6$=Z4Ta^$zGZ20YA8E#X*~8La(<9K_O3oP>#q>A>VSVY}_QeVD z&Dbp4?0!7R{-8q|&8p86yTjfCi@D|@ZrPb2Nw`Lo=vK38#!t{rGr!9^!H1_&tBTE! zz=_HtucJtf*IhQb=;cjOpg&E42)CX`8H3E(#_ZV%Q~0U8a?nf0X%&$uDPRT5Iwvc* zPqA<sfC|?=0_SD}AW??;lL~@GuW=K$YZj(rB*lVzjx{xdV=4zWt@0nwF3uAtB-_DH z!azGRT!5PmL@9hZM`qNTux73V@!tu<&b}rSw(Y{iTTr@}fVBQ{-@y|2a+vgf#StTj z1zR=;-dU3MRh6E|3qE3Tb}VIL9%F?m1u33%CY3ObBhUO92xb|DaiW*~_4_hM(@0&I zGN-;5>#11ThvGq0PP4XiVm?jCvqI#Etfi(pN*8J4ih0XHqw2rtFJdpZo9PA!yRMaq zr0T`NBxw<2j*r47mAsUP${S2mVge_f@$ad7YG9*7G1r)(e}qSu%NU;UYj<KS<406V zFn&T>>o9g}rXu|gxykV3rLus4#1Zip!$afBLEohgfK?)oJ}IlWFW*NC)lN=bD{6$k z?DGXh$Y(q=-&2CZFc6#)6ro?2vQeJo84;;z-V)^w_40v6$VY~qr3s*Mo>I;;5LXFI zWjSyw_TL~dr_knooG6L5oDQ&$**LvRMX6#g4YtCc{9dtb9M=1tYN50*Onf5eSC5D) zst!Gt`UkN(lixT$C%88kb6hh|@FLbvy?xr}h`-E+v9$kytuK2{s(27kWcY?=$G=;h z_xpNTL-mWSNb@5rQE(Q{k)8KI?zSroIY|(M+)LwDj#QaB0Wm~ZRo+=bg@}K_gf-by zgc4%B!XiPBUrnC>hq;l3lBZ4nb85q1tE-XjE0etT-CR}opgJsq0ApnFmLsb{rMq<M z9<RA!g*FHHa39J!8qOjjxr_1n*ttm=6kzk8BYgNa(Hs<i75dZemoi`QP%s^qC7;9U z3YvNT65q|~Ce^{{(FfeTM%p^ukt{2tLs~{>JfD5Z`ZLMc{WYDYoxw4T8HtRajZ=HH z!BMiCh6UK=E89s#cihI<3#-OSKqaFG^S_tKV$#kmx3=WkAkIbZ^Xa@BhR^dzO<i&a zqCm__(i$P=duRHB(Z00q6LvZca?vrHrz-T8cQRJ-anEtU&&eT(!RXcQ69#w<G>IQQ zavSZTjS+*6_BBcTxA6m+B|_6HU;_iAiq<?3&q?h1_zr%F21maPW3Vld7M7zuVStRU z3`NOqtJq}2mhwB@cchcXTVZ+Ourary6I2d<sj?w?-E4>AcT^SzatR9KTKpS6)h`}x zDh!Seh3GCOckR(&Gb!d|7OVF<e5WjeC(UvV^w<si96Y)iJfpmVP#USY2~2fGla?VN zulX69h?buCoAJ<N1(soblaHeL-T%mQ>owg4SFkCD*E~?uw`~c?Y<3qfWionUc~zhz zQV@`=Cw(^1jI8k`z48gBYV-Rb+IMPlxSDy9es}v19dd(K;qLx8eJONWl<xOO<9My# zc`MViDZB^1oOvMgUxhoC8#ykKe-o4QvtFj)sTU0eJ?xkWzQkO43YNcUhEQX(^a`zM zU&T%4_Y`zBD|i_UN=}^;&s80{nzUd{t$*4F^WfPb{8QWB2jQ2x!1qJnl_;Tw$cpw> z$9<K`|B&0#54+(Ln+L<h+du7(Ova8(PNI);+_`xAqmNoEe^y9ogRLjaL?q&Cu?-n4 zl#S?xzYe~KqvjTIuGx)?=F?uA9cb1iv`=y5YhCqXJ&^Xp4N5AtEqc6?i@@jzHK)-= z-qT=eu})!ksng$D9tvSb<;{+jcxL!14CwS>gUO`=h21S>g1!l6Xx#daG_?SrFKH=O z;jpYH2y2ru-jI7|c&;M&0&qRH!tu7QRlg{hTku68(f~vmZ32g<-k`dT-_?2B;>SYA za=)4YfpGWG#>b;6@iU!k?{Ax%2q&2hbW+gT4)08*wmuYqT!(2l#OhcBmYI9ek%?Re zAPXbEGWO*t9E9?WRlU(ep0o9h<hyGdoiY?>TRJ08D-%-g{vk#-K<;!oNhcHvc^O3r z?F?@l<J5~ugRqHRX$A*(d+=hJj~dRpjwY0*AE?eQ{TqKwz0AO@N;)Px6LxBuu($OL zJg&N4w<;4t!WuLNln1I}E{2l_bFg@~!-a4IFH$he8bRn<gGuL?camtsy;nRhCB%Jt zk-Td=?o673o7r}ID1#<qNPe4mi^={k^-f?FhX@R}O-+><qhNExI*F_I-EN$fTTrw2 z{q$5mSzYVS41fDjEz=~D*AzHz76Sw8P%8cnZE5s%GwcM@X%{65wbNbb0yl#-0R3z7 zX6NVwV^4afz684g?JJ$~srX(wF$|TadtV-y?qZcus5j5JSz(yS<AoMDXEK%)dm1Uc zopyYri9^)Bieb=1k>}b|*krQcQCaB3ebqmdJ5|cg7*Xqp=KT02g(knwWLF@?$;NkT zq8h`L=5<2}xh1B};OsqaxQpHJimc`8DK8b1Fg^J#70Q@8Kw?^5%GfLQixV@7i97lW z|IDZwu_W6~DfVx@ZKrtjg(9FnV<F6$Fod6@on>xI#`H+7z3dh|n?Is6zC#q|loR4` zzDyqXIm^-Hch*as+I-xw7U}s{l*myP-zjbx=&&W<4{~@UtHpItW3E<g6hU*P2W6YW zl8v^<+7ejcV)(Hq80gx2t5Wj%P_=NhL%kr}mh#`)hvu2CM?$imUEZS;LHpy7#sh5{ zZEh$7>%{zg;78w{?zo`()HF$3_BA!}bALE>atmz~+C81@D5}&Px+qbD+BDkDa8gWU z$yndkwj$ajwhi=D+xndjuVO-SOTwnjVHsJMlhNcJbTHuNADefZMQF`_b(+vM@1k&_ z=}7V7Y;`Nx0I7gk<XO~9B0Y2*QuFzduOq?P>853|OfdoJNNN@IZs2ZQR<e$XbA>j{ zaSDiFnavv=zi3}-Rfqyo^rf7|={s**y{3MH%5wC-nVl`?$kkv^ThD7TdM`lFP2yx` z)7Y-Q;U#th#;ZLgqUG%J^A16W|C*IHnvq7<&5c||FRK02q>UIqM>A!DcwWYaWJ+-o zv?1Fix1amY<#zw9N=e6UCQOpwq$*M5*ahd4%V@4kkt>XZi$l&vipR2G9jd-e{W;ZL zpB+Qzh+^gH3q>C8*!sEtS=UFXL1fduZRox>V0p--65=HSVrISFn%5TWa?_I5HSpB@ z1(yl&B}Dw$k_LSQ+k#T;A0^V|cxbxWyY=Q_QOZVJLC^J8Y3Ir3Nv`nq&UB({3zx<E zm*MVM)EX_(DmUan>SQ%3aqvzrB9yu^m$m^rI7xa0fqhA<OC5R|_4Zbow)Eq(1Jm@$ zFg264(^9in>^w$@6BsaPPXW$*vgyXo_=v)l0YZK!&0H2EUxqgc=ozqROv9F29`Mq( zX3JuBakoeW;ta)`>4DT^KUX;|lHntZ3?rNH&y)IZMz^fud{^q<|4CMg77G5LsHvfR z!~gXsMesnr-=hLChVX$sJaBRvd_;)O#qk;wp&zk$%EhLw^eN>-j_h-Y0W^{c*M)Ex zEl~V9f#5Nw8;z61g4aUxB8x1}3|RwmeFFAg+65Ly=Ys0nx6`URUTL-Q_y_z8=N##K za|vEnwbOdGFy&XYNWQe$WLC6EO5X14ed3jW64A5ch0j`#LjmdQvCqeQf=>v&Ie@T^ zEsrm&om%RVv2%g`bMA9h4M>Pgfo;gvOn5)yG=g}wmAn&~Yh?YJ;`0{LGok}RiFCbc z897VcT8Oqqjh#!}rR?7F;EH&G51nv7zN&I;_%`&d2PeNWLuY~6=o!s|F#o(FpH9H} z6V;X1-F9Yr3Nz(ng8!S;2mtz=SbyoRJvDHFH*?N3ijTqNN=F7{<-uENxQEB;&Gv}5 z<wLq^e#{2@6gG&~ol8OQkf3&Xq%M;N4(YHMNk(tLPmo>zg8311vyFJYY5mji0r@9q zaBC6IIIvW#sAr`pm}z*t$gA-a?X?0g3h83K!NRnbQ+8KGsL?8<$K%>hSUjdBM0|hy z!koVeWs#G>NfDIVHep9Y)A^V|tms58J2aYr)AK~nvG?Nnc{MY~fg&6UT091yU(yNj z>x=MvRRtd6vQMvZh(+;uYF$eyV+E0MPWOVxj5PYt?mO!pk?@-vx-CKcYd7a>s5$-t zx_U$GsF}HfCYP{nbAUaH4}~S@1_?34g|q)WjP%{bO16oRWB%tsGjy{7eWWqRj|7+{ zg<-tTHI%+(-2s;x=swj!tJ%?>hUK@7#;<&6mdgWX9Z;mMP{WKRYJqP!+ivggK2l1K zO-T-C+wD$=URaQS7;M#@*=9WIh@|tZW{Mqet{is*rnb-|&-H3_aqfMIl>{F7%wuOo z4)bp_p;@7TUO1nd_nv!~5jU;}v=<*eWLgk4$@G4<DkNrHG|)KuNik8uDAD%q#{S*B z9wv?Rka&Ra^WI0>I}!n({RLUaKA-sa7vUF^i@^7{u&OWSYuuogbY!Mq9N6NkehDPa zm7(iso@eE?4ylvN@qXR|R>y{P;Ll-VGQW@MO%De`fOt$+Zmbj^a|jZ_N(*<2+&qb7 zX*uU$MVO)yjX0?(W8IX0aNo=`8f`AeqVFBT^tk0(z17IH_LsHcQ=rE_$0VnrC;uvn z<z^>}-EBfMaYUOy@du21!mHe3jE(*gDxrmprAOeKah(ORy&c$inuxED-)S9mxP{3P zf}C##ti&T$M=>exx9KmGo$tEUvI(B9xU`nQbEG`=flg3`el4S^R%TK5-jEkB<S7!? z8D;IMN!lOeaAS;pdh{&kVfut(Xsd{XYlGQ7VZjSbC8hgY!;?-*jWeRp#|A)7@pQy4 zzf~$7mg=-`NXRrZMtP;-rl2%j1vkxW)h&r-l#s<bSxO<5boF77%)QylC&$lSRxX6k zvEpFedgU~=<P1Wkg9iH&I;QfT6}M?4U58xLAj^Uxd#2ZiMOL`5du5$e<H1V7t7ldw z6^rGNKr_HM0w3?ew3U}95FIB8+ENe>XZ0HDYMhhGH~m&{WUyH`AGqoV7S&f|_Jg*C zt-c_`9%lZ#=!PWPy>3!*Rz2kXLU&?25!VdFY$73yv_Yh<I}5PG!J<;0EeY&G+ttGF zhWodQz5bJ}zR*+v9|@_@X3-p1uYrk;but6`WOEIVFxHUKVc*l9-K6?S>MEXFg)5%B zN2jL|t%y{6glDz{cbLo3RB49bE@11m4Hd~6EBWEx?J+<vig1nWNrT?mLg%6=r((<g zxVprv?cTeq$zgfEdstdEhx%zPF4P(AwLT<hDlCW1fMt+}ZMYiKqUv#w(?NJF;&E-x zeV`#@nI!f%*d?SR+whTf!DP`R^u@_{L7(Zt^b}z5KX%v_=RLsS8n=zUU*fm}0JG4+ z@WY168$$Q{Yv-$)w{P?LBStrvPhdl)>neNZn^rw%u6yJ8r05*nwvskUp(kGZ`?KVH zz`8z)_AGS6=Sud=He(6${48`cEnp^7M>RT1fUyf7*W1yKn{63uS<zlRCu<qb{>%NW z(#ga-xW;ooOwYaJ_5(;cvcK(_SF1IOzxuheTM+wn&GnGgf98XA+%-rm#xrCcD*Y+$ z{P~*Pos{<Q@Rf%)7xhZ=(q<91{V$o|eX&Xn?C=_NY?u~uuJa>K#>e3#ZC?2ee@?S* z*FcbU#)l-pHD9Kr!$;s#{<00sEIT`Y>$vTgG#~vTSk_S?UcBSgVGA769@SVB)8^2; zR$yt52Zb4=0V?K*<h}>t@A&M+<3rlqr}E{WogZThOFsz%>Lks}Xw*=uTI-&`unxUT z0ydGltFt&l+gi&j0ItHF>%^~1qYr-{#a7fDh?SJKN_Y&p;Eq#FlTvCn59Zi5nkX@( zn}o<8<pOTCH_L3(pvxnct+jMWXA>GMpc+;BGK18P7W|EMa#S?houOHpQL+FDl&CXQ z1~`4E`IrD)XK?{#=g_Zj=f<KYGD!<7FeN0ELzlCHsv1{cpIGUH-ri4oT9W=o$x0f9 zM4NKqpWbi{U#+>?zQq@l5saK-(}RpwIP>NRR0eB4L+?Hx?AV$1C#c;-OArQ-sp}I; zSrh_mf_E{@gECS59^cOmVWj`)QEUK!Fe_%ZUGFIiog4wfzw_$JpQ7J_V4kzjU-i0n z8B1L5+W1T(HT5NEscVfJ1}}}m7|+zou2BY*5m;<!q(F{R6a(w|MIl3P(V`yOl1xYX zs$TxGu8q9trf{Oz5hE=UY7?;~8jcwC9UPglN+)EK_OXKuT&}|;u>P-;6ZCA2Mhb%& z1~U@xxiblJRH9E4VFF||=|K;8DUJK8*Old+c!bLnpEao@_iJ}z+hvtr2Ldsl<;;7; zszt<oE`--9)SuAH3#q5%3-W%S(aD`rSoA}#$T!<C$(t(&>@?3sNq@jMUdw=A#HPud z9Ou|htal#DS<y2U)QP+a<NoaJCJuAYO6`^nqu`!+z#W=Ona<&MSnAkmQLhJc9+nlp zAwMX4gz-zd8wB$!COS!WHr7bt@L{Svswu_lXz!~%BD+?j7rJctS3Ut&UriUdCafR0 zJg;u&YYmW@B~rWRu8|sY!<4Fdu|twMntXR6v-T2=!1nFIDaHAJRJ~(xrcKuc8r!yQ zPHfw@ZQQYK+xCPL+nCtaM3YQxo%{LTI#uWV?|p4{UtQIEuZ3Xe1N|5zMM&kCt5iIN zIz3zdAoS>Y@w(rfFYy+ulqv4Mo%1HH`O#5zhFY#@OyoR@LF{LHDzGELmRKTiYPdkA zpVC9X0d{|tcND5QP?vAVBsf~Nspp{ZC*;oCM77D9Q!;HRZMAY}7E&=r915r3nZp0j z$csu<EtI9`Omni_r)&+g7^fT0ptM=v3KFBCNaYXAUs;QK^ziBD>)yvfYQOo2ce%ou zQ)s%AP8aZ=DO3drY$*@hpfzYa7s)L(B#f(^T8_7-KD5HnD`@*HDP5qvDk2B2WmAJy zL%y2dJi~O*{2bK*MJ0Jutxc(mWRVFtL)7dL1b{D*>3~Do+E~yU!f|Da&wei5GliYS zMojd4-W<`M4vV5gp-aIU>fh4{G-=~?aW!}1e?tx#$+Yp#%>4|`k_=)aCzP5^KoDcT zw+YzFlWer}w$(Ng_oc1Yh7gF16q<Zz<bUZLQ|!arS!Oadr}Fjr48uXkVe#HXSgI;T zYOP1zXm=`Qf2v!Tq+wc`NH_Skf|q9{rA#zhYHRhVS)w*;c?;Ay_)C7RbJXEC+A4W} zq#SeCsNFZkUqb#Ro6sVDLw|9$kPRv#H*6HMu24CSkIt^*O}Q$EucP_#mFALxZTk+} zU!$DN*~k;uI)z)3b2`NVv%$;Db)RdriNv*Buc9=DwFV~0iJ{5a?Blf1zw}A8^9vMX zGDXwt$0eSw7B6C5trVsqU4dN##M>jTKRDz@r0_-1veWz*+%^bmbYhBy8xOo+ZkI^u zJ#`v>RkhzaDqNW$MC@#F;TgmflUSV-A}vJQL{9DAWEcl>sHBxs<o8muVE}9g%*W2J z=Ca7VBq1ebwX9yEG**6he?*k}-`0Q`zak>e)~7UVt)iXUr96&U(rl$>1ZmY5Ei@A5 z$wEt=f((AhitXiV{aEY0d)hY4H3_zz=)N^I_X39<>OWy0-mkfXmzgANIs360dOmsc z?QeExY4KEKy&0=-mE8l(9-K+}NS_n|$TU>=M{>A10~cjy047m72Km{`M`vWS;YBd+ z&V5F8w5ZN8|Db}bzD?4d+|RHRJ$4-rRRY+P(Z(ief0TvJQll5T<%gGw#7a2UMSPxl z#H3)EOgVj+{R~uwVuJN-1?zw-syfA(r6327{P0d?DKQRoAC#=CKQ9lSPFbNT68CXr z%J-YO2q=|ArEtJ+Kk!wgXk&~_JBaEn*z?XCm73G5*1gB}*(%SN0+BY&`|N;iEBbvX z9U?sul}l3Q-ogrVVh;8-bL#deZ<xxfLw?<=e9e1yuE{2Il>>W{vQi>y82RI1&l8ER z=R?4Oc=@9B_UQV}<R8MMHNozKt)zD!)d?Y$RZnP43STx;XzlgEQ`=EEo)J)ii!t?y zm#quoH_U(IhCvGR+ni7^R}2SAe8OR$ODq%!#ZMFmY|h~*g~tF`YRc55bYU6%)%7fy zB;l~Uu@x`mc3ssiyEN2|h3+YCurnf|&^e%qx<pGj!H%G#b$NM}B!I@BjmzkHqj$o` zEqU<GMN*83eM%p%|FSiDzR=KCWNV|GxC4o=u*C(14$M%4h#vW8cdRDkv7F+uMEb)! zBYd5wDPNa_S{E#v4<X6vDm&+Aea$0dg*<XjFxxm|)Fis#NU#$aEGmdyjN}HN&_f1) z5=G|L4xgf`j=;rc-ab}%nj^BbCtjA(q;}cS_2L^jeV1-kc$m)NKX!2~)hhyzGfWpz zqe<fuuYAH-<e=Vzr6DvsmIu9!`Q?xIgL_yu{cnC=FJ0A^ui7zdhSjb9HVhTZCxUP_ zJmRYlh0VGVb}3|jzpuBeV;Pm;%)}>uZ{2cAv4kM6?zpF0RxP0uuu;oJl_bm@4lH{Q zTn}F7MC2=T8ulH3SVBm>V%jnXoWqy`*}3{ifs)pn{Fe?60O+tSG^g8krD7LxbD2Vi z@2=O*sqC$^ZU(r|?jgBc{-`IDO?A+j=F8tGwC1vGL+-hd^n%>P5plpB_ixBmT|O@B zr4<*f56fp*4@F|HXgkv4)Dd$F)sv9F1BMNh3{B39M3+pu-30>NUh=bm$bX-IR&^7T zT_9=X1hMm=?S_~c#N7f@KE*q?1?L(H17CkP9qnDr3A_(MFDEL9XhNq2F{KvrD2b7_ zHZI>bR}9pF@GlC)vFhBH;2^asALC9c{O$04y`^>lxnw@BoWMW#2vQR1HOZtZ`1hr9 zAszLh@XJ_4oJdROk_Y+?W9@{J;Ei^Vssl9ayDXJX5%nUhFB;!qj*$)xL&imxz_-Cb z!l?6TN}waYEpO0j@YrsNk`)C5{y1(4`2OXgs@;Mj&25i~m8vr>l{3kpjUY2lZ0$W@ z{Io1~NZJdzmxCZcMNGW@>a;$Gz1)z4ifl8uH=V5t7N&2*A%y;R{q_k+>pXeR3ampj z7*R6I9n?B&^-bBh+;>1|U>Wg2j_c}>-jQ#`3EX~kR(ajNyq$N*KC{2WTE+NBrhN<@ zQPP6C?g%34JG^R2fI$OL*@f?qtj&o2*Y#HR=kIkUqh)(W2-!(<)nrucA~iqb8110I zpG_&4fL3{TE~=-|%eA%8NLTG?y10cCQ>w_jMA#=isxHN$JSd5LX<_S65zW%!W92W4 zLG)?yH8y3G6>}Zu1|+hj3wOuwDDId$csSgKC6U))F{_51^9%URe!oYkh4bRM$Ggge zBLD1~5OKEWz^?_PkKcvgPeU9Z_CW=~5!Ny}f|<6YY`qDur39J9-Of@sSx8et*VOWJ z;5gV+<{h2%AmOiQR#LBKEIuai5B5RyEk_!wS)c9@iaMM6RpApOl6U1>ZRl-0ye63o zhsP;W(M2D60e8qW634|wrNr>y-vC$+pTIoM#;RCqk|(SBY35b5iQYY0p#z4O!lr3= zAK~|rm2XBM@fjHOpIEB*Zin}i^!v(yK2Ux5q~x2u0ON+j-V5pw--H*){=D9G`hbB` zldv-}Q6)b=hrI~fLl}C)!Llrk1K$f_z!*#d5Vvhnu?K^Hz(~m&nUI9W2;zfZxZqSQ z<Qh^4{_WW~vy6HBXa!2gXta0Tt1uEj?M$pir(DOSsGGg4Ot9^bjcyOO<c9;xmGx7l zN6d}SLmMBQ)ZblkfL<bU!2PF;zs^nmJ{4*Y@rBqVefV54u}_PW?^(GxvG0)ncOw#2 z8HIow7W<s5P#o^h0)3R?_p`rNMPi1KLZKzavkyt6FOj1%o6Pz|SqD90H*A;8{WI%f zXJ#r{e`_y_L~9nScG;LBlhLhu_~Zn57~s%DjrfKjr66?6B>!b_W07S&MDGnl(y$~= z)%PbYN<;}#g`Xp=biGGDQewy*d3H^7VDsxWtO_{+V!WA!F6HH+fbYU&G~daqPUeB1 zM?_h&F0Y%&a#=kjf3QU#4!i`OQ+Y4Qd(d-?ZWnpg3%82ZVrCIf<6vm<Z6B5dIt<8q zP7esP3}RrW3gcusJ6cXXq!XXv=faZC!}d`yfBI_vr4PBMhHZ&N^Is1n7rd_ORIXF2 zx)9F`I8TwodOR)?|7EcT(Spmld5<~3y^hb)jS-hCfi&SUcwMyY*dHmUE%~hi>}-j~ zLsK?%z@~iDM$r7xj$T^MN5#F+*L^&k)qIdP`cD<g5b&)V@1#sJD}nd|&qo3z7(V$F z9OM#T50FY5|LKoQT`PnH;XK^(Ij{l_Olhmmd3M{1)1&0E)%fK1Au4Q&gT-sbMXRrK z|Go_kk?5PD@DqIBXts$jb6)qs^HE5MQHk~Dy*+qw!GRZ8pwihx=QNq{xsvEZ6Hd)% zhT{l;PH$A^lBMK!DX?Ln;~kXRSq&YsoBu;NO<^e<9<C3XfS4?uk^%dRqZeSrP5QQu zHOAYY21hNCO0Ew_PW{`5>xF0NQ(j>@!e4BjFuVgUb=uBhFIeAyClMa*3$LtN{LZ~t zbF5P_S-(X5SwN)ShaAGK>r}$<PZX@~J55}{-E21vm+zf*=s{Z2Qb?ekIG4(y?=mvr zt-Il$n;^ApT_+4&eB#@=qSM@O=4w2cPme=M01#E-u@JeBLgHCq(gREIC-m7P)s7v% z|Gtw|){_bj*Oft8uAm^Bq(b&Q>7sUoZ^A(1P3J{}XAxs6Icb}&773y$Jt5YX^tH6u z@UxWdhTk@?>5#nqHxshw_ilY;{9L*!I)m7c!@=<YjBD46k!R!9Q2(r|^yE}aa^l}v zEJHXFe|9I`NN{J<8xMjHrAoIna>8Iq)^H#CjN05Ujs8_lP7J@_F0)FE(a>WnyI<Be z9t>BpQgJls&0m^T%!&x)aN3wBtLQj_bOo-Jk{L%<Ri_@@S>W;^5_-OS>sdfnmYsKc zT(%Jr4&I<V-f8v1)cb3VDM-njD8uQYPG|A*MjRq-0W3Zc++*@o#xRx--}}bTIi0b1 zoBq^AcVh5_JNp4)N}S1aUFjrtQ`@O#hIo67=7+lhGb7R&-#LN}6InyfCC*s0(Ru>l z>X{j;sVU(MXgl%S({t3u!E)r7xL<a%Omd<8-~>-}wmh)Y^#yTR%QpQFp-9~#kN%Q$ z8O*2oPZT_O!TivAd9DnC7`AMQlqGf`0iEzO{v)st<^Wy-^vip?k;e9ks9W~rL`l3- ze4G%%8MEj!ydWZJl)EzGJ61v__yVNDqW04AZ_aK3rO+XguRb|nl)Sair0_853r4{^ zc1Nh$Qc+S*QXhlHPR%Ge^{Bg0Tjzv_xcme^jv<^jGs~xpe989&wDpB%`l!j{d{fKL zYi(5^b7nl|Ie3<^cj<yIJ5j^@0o6*3$lVMv`H-GhDjED;J12g<2jmj%kQ?6SxR3(y z4c`_9qNgf$!q`=!Og;h5N4Z{M*Ha9)r(fo1m4(dl`@yA;*Ry3yt@lr4h+7Exr)Yse z$T$#^L@4(A@YzoG#?&_EXzy*Q|1DSO`)JR=Aiw}AE<560`ZjBF{dic1Hh#6NB{*Ln zyFnH;g9Dof!9qHrs~W4=j$o_04VGLX-krhA7q7y;)?V<sfqmYZ_$m0vkgl#cWjf?L zhS#OUrzyWVT??x{0(H$nD*g$&C~-)#?T`DH6wEwr56)ZziUy7SNX&UP&JX$(Hsgn7 z9-PFqMDB)Zy$tK0HIlKu<NHWb_3(9(P*-lPWYsf+4`pGkkH4c3fv<0J+Pc;Q3xu)J z$l)>BVnZ|Pg(JK7O%sd<w&u<nno~XD*?a_J`r>?A6;zfStd$^ag!+Xh)PbMzB$qX) zXBhmEN^XG^L!M6|Z&NkDSPns}Dv*)*c#-W)Fu{<;I+)-zKI7}i9j?_NWeOkOY4J$) ze_PBmm;*OwXfl-)Xm*HWy8)+k{45qu9(F}$uFklKEMfgkFZusV@}tx0Js^Ca;%C}j zDqVZ4!tmDE>Iy@h`@Kxt!{wk4{YKxFUmIk%{P^2AN{|F@)scPw8DO)<IOhvQOzp_l zvN3_!P)?h@w+ifx*v^}f(Gn4`-YID>dH*1~ycYtGyod=Y%M8-~w)^~k9o~+VgAEJ( z%%(P#l=p!?N^VB|rV79-IJ&;C{B?s>FHgB9t5y7qmpaWDUrW1f8p_eLI2uxDuP#*i z-#XG@FOm*S<(M=mzFHIJ-aIsa7^fW{wI}x4_flg)Zhti}HemaFE>>t^k68WpaLd8> zRowAZ9xz71USKZA4oQe|Og7XDICaKf-#<{k3`Vrkt<3aE%ag=sve1d|l7jq^w&)3e zvtD4h@ez)o|IU*V2jS2iMLSVH<L9(SN0|Mf5mX;?fXR*0ot@WRLsx-Ggc9Kb2m{+s zK3?T-IIB=|cm8hpvqiZ-Ce{LN!7}Lope7LoX~nQ$)_@%jU3NS9PLkUs56M&CjJUxE zv;2@(Z-DBQx{!Y9;uWi~s$}2F@~-ZLge-0I@@Ak4mod{0uZ^CThzmNHP@$?wnqM&$ zr!>dQlK(i6&)u!NIhJYe1RuV*4wglI3Z1EU5+3NWg(s(47wuV#0vC6`y1tod{A9bA zW;*A@VS3PuP4=n6MCVA=Qw%@WDvdbgrIKfBi^8*Kp|nME4$YA>P94>hwfv~E0Nw&S z{82`R6}2df!*yhNx)`D0pAOVvk-NaV_${M^_d;{;Yl->_zo9=_zBMq;eRSHwQ3GXb zpj^O0FE*au4QS_%Q+BDv-|{VKgwPpED@$CFXaBHPr=_v}|M-V6Z>`Lou+~1FFvKnS zO&H96g)WWG)i1_`T^pCOn3OaI!OGH1V|7C{!N@q^x(n^a2g>iUBj$#>ssr^wpZ!|7 zFk)%n4hmI$GjNr8?B&z0>JQ3b0aM)<B4tC<AV|PHic^t;LL|7(kyJir$>|)k__1qc z7##}WKH#d2Bonf)x7y2|IjUhGRfVqSx>bO+!8I5t>~P-?4LRao^vDDTGhiq@TZNON zNAx&%(I|xC0Z0K^9#W>uM@(q(9=YNKcRhiduh!l&hK;*I5v*N?_nD=BaydGKwcZAz ziNq}FfT?(!3)y3<%hWEhXs4yjBa#sc9UZ<eZj$NVn1sG+hN7b7i*%U7AcX!e0-v*U z{#zC3T0e{-sUg_u86wO!bT<KMEbo$TH;qg=w&m8$ml7#ElFNnX)5t^>_5CfI&HiRW z*5=Gsh-qYag^XBoW!p9z4Rs{XqWwe2pbnxw-K~iFlIb`KyOO~{yyYN3R`o8dr|Kz> zY?F0&1G^`Zo@v*iCLGlO&qe8m9HILfHMzMz1V%UOgNn`Tt4@D$ZS6U%>Y<<(VkYYx z2lgB@&H5z%>>shpqyu}KCztaPNicAiH2RUDilM}RnW%C1c<XjzG|7tB<#1qb&*X`! z4oM=M>(^s;)Cx%7$&dbWVbrCZ2FOS9-*9>@kAkIFrh^ON|8QuS++zKLrioothbM0^ z?Gu?@u(=VVw*EcvcRuiOJ3F@h?epuuntFbJchrZ;Lv$ckJq??lpmm#{WK75C{r@lz zX(W&??6YZvIDo1w4@xEujL_NbG<up0H4o({v@J7x`(Ct0gSJm<I95)|qzvij#+U|^ z=WfuzP*`$Am5O9|B%y3h_P{_>wH=qw_<GGV173)DFX-I%HnxBI%o2H@50K=YlvQI% zenfSK<&ks22=Lao?UKvQlV?82>DGK}Q1HVTnd>sCB-F5hmmB@m1&iW(Q6sAgNT)+G zx2+T&lKUUg&<d3^=k#>D_~I}jqPk<wsl_7O)T&Ag4N5iyp$89|AFuUf_vxZ%Txs_= zc!e%blM#u{?pG>_<M?T?VNAlLtIS-g3_wse8o31f7Ts(alhB}J*t&kwozfRYs1_2E zw!?NKLBnipGaj*C@?Nv~F!EmRS39nPo?BItrIn;dtc-iIe&A-v-wVVcktk*-ww(5| z2$i&m(;q-EH*A$B<|;eRq0GXISX2+pl`VuD$yy<L2qXd4wIP@hiYcBqgv)y{j`8!% zhQ6<Vde}mNXcZ*qVMd7tol8r5&sP2SUmAmk;VeFQZ_D*yMOEr<y-&JFzgTW2vX$pz z;_~>R{Vz1-SYvtq3J{>9Ftd52vF5<?GXD1E8YB5Pm=njyrV9ty?(su?ys*0qnFXQl zwcsAaQIKHsotd@1^2O^N9NCz_UeMvlRDe&t>9gbE#EJD<ZCx0%CUZrs);X><)B?gZ ziwHLQ*0u=2=cgFrvr;PBZbO(2bvvi^itpAV9qFVploD{OcLiKke5iDlT}Mv}z~}F( zj;rGJ__v=xzw4YmWOQW|IT3}xwj`f3axw}0nXQL*swU)V?_ym-<$+0LSnTrRW%4eY zcN}H|OSbwQr;jv*hgw*dm}x+}a!00~ec#hM1OwaNb=z`NkUoytZQ0Y{gD*2$T0vT< zA)LT@PI%k`H-XEC9+12&ZuY?3-uGD(Bm9#Y%_rDPc_YC%#Z-*!OolX*+K5jmrTlkx zP=<E@%*FE}zSFmtHgYAKE8HC!EnyrhRXK?R@<=T++8s1PAgoR@4BbR7J80=UAUGFm ziE=@ci>M$i;6&RDBkC7p&l{PDCPK;FXJP=~S)x{Qlw)s7S%!x+&dmoNDTo_u9dWU! z8x;w{`Hd@v5X*if5||6Vrg;G;9xkNKUoJ=g<azq+_Vwv9=j+h37;$BkS`I6)p&QaC z%0r%*V@p#ZK<tdDHgze9VaKC{=$h-_G_p{=WEi$Ipg{*xHjzFeyLC=aFJx-_U~PTU zXE@qQI@>YgNyXcFurQ%<Vv`2nF|x8hy(fPZ>NYmIs(5JVvwqvl$;ue7V8hBxD>>7n ziA31~?ejwVvu8<~x@f20{8RuI%pS9%0dD)BamC<aHPR3QX*ukm#g*jek9HGo?Qa=p zcVr)=PmPWNxw^u@IB|GkMi+(1x=|UQU*u0fjC5|Pj9KgP=966k80DDCj^$Mu%0_<! z7anu{w=xtM5uDqvCWEQA_7{8sLhpZ?Yo-PU9mNUT{@m>&RUt<}>s+yWfbjs85e(yf z%^?_*cFyJl)FLNgj$E|;!G--c5cm@f^I!Pdwy_M%|MMfscxeEBlhAQC>>igL-21b( zVboS%sRf+gKn0xjXP@-G@tf>Br<%Y!866sEdDs>?r9EIBCHzF58$&&0I`1EJE8|*b z(KFnx(Yjalx$L6ftEkutG|o^foEPaDHmn2tH;oo<v{VGrb)rf#jP|G+-KkPG4$L?P zJN7IQ0)#%??`&tZbshypVu!etgDCeaQ8!GFo=P<}F%L%BDv<e$*f3dKi>es$ft$4w zwkZ~NJr!Jw|AffMD@pEAR)3|DlugfBI-79;I7O{Hzw9ckA0<MV^j@wGgoswLOUY0h z!-Ty(95{Fz%=J42CV`?w!}RXd{Z*nUV}n0a-r5W$-ZK8y?lZ19rysYFd4PT$sHLaS za1lqxrVTaiv3kw1yV4yB)+KH)x3`J{z)t{ViN~teMun+=r)xNmtV+@KZS`~oBQ{?_ zH=ihtbu<gKPz5e&nJC)V3pi(2t>)Yr9qi8VUxWX$9Hg|0UoX{^%};C^&mN;b)hjN! z9#y)R85H;}4`DFL+8EH7JFu{4E|txe<NTmfXfE5*Al_C3hiA;!`Ef}sgg+(T;htjg zz?9y|{FOF6>q6*?xdLgR9ofwJTQx=2D(;8mwJYpurgHT&<wA-Eh#l|bEm;X^Uy5i3 zu?_+0TS`?zxfiFfN6eUK_}<07Mstr;2pGF1l*%g9MFe<rxee8p#ulD(nUjdjX;JeJ zWeJ3&`tzBpIv;EjvPaBJ#QS3i(HIXUYDx@zlJ_tj9twI=vOlA-7E&DENHtY!cv=3& zXIPX`T`OLx|14(Y)i=mISpKOM#TmW^!-}u?WTL{HdzrPeAm9Fou^6U8-I?!<laQ9e z6NtOV=~`>gN`MSf6#lZjFO%xxU<C9mw&o2aquG0OrCXh83RSclBqP-!3g9bur|D7+ zb)|=%W&2?rH33|D6;nQudj1w^|NHoQ)I*0kuX8ci%crt9EWr($JgcsapZRMF?w*-w zu_>3=y5;AknomDlV?~rE4^qb<A^o%4b|DR=tFW}}EmL7;i;|vW7;KmTej=(_<eJSw zJejJ3fESWR#h-rb?RF5rU*pcyGKPiAI1{m1l6a<5)U|n7B)G{quu}pNuf|GR4y!B+ zY?!ZA@{PmjNsGLqgG36ETtSpZ$5AyPm^b7|m+Zg^wV4ht$ONv=s`!HyDAeBVNtIaC zwsNjY;cIwUBDjeeB=rY#nueUpEFC5*LOYXeqa_S}76jZyE|tv_tHzk13wNVH|Auy7 z#Y2U1Wr=^-0?bVWuH#MCV}W92<s*E^2`3IwwS-jL1Qxf_G*mq)?Mbsz;}u<D)=cpi z{l4M0Y%XLucXa^L89;pzR0CgY7kj)lbuWT5&q9{c;%KUOou$#`Pwp+`84sqR<8mPS zJluZ9(NsI)>MxsKWGp4==^ym~0O~KB{Cn(u-+s8C#h{;<^E-hB-<Si8T=h;{&~*+= zZw}i1X>^Sax>g^M!qQd=R;IbD#3}EIgbj<CA=sn-ITaRILC_qga4IY6@Q^>VQ#^DP z`$&F<5*>RJRy8<4qmWv3uAKklpW?scpL%f6ed`h49eU>Gb2@-6-R@_!py9)Nt1gRc z=iTvFO6p7Kqn_x<Q<YFxLAYjn(naI1e!@cDX!&^KeKiaqx7tW6E<G_%v2~3&vT{}e zU8bl%K2ElEi#X_ViwjL}Gs<N_V_Z2JVZ#^GJT3Rl*E=akZTuN<E$@8$L$I8Ir_2vn zgcyoMHC-3pvy8R7Rp&IAW!15Aym)W4WqI5VQ*XsJX10LwG**u;@=lktRR>#zjfP69 zB-a+83(Y3a9_|~BQp4f5)&Qo8$%*Qj@|-?JXn)$}^8p#r_`#PA0)3F&pH;C6jK#de z>Ql<4Es5g9Q!%jAwCqUfg0B9B1mTPOAzME@RUvRW5lR0z)-LUMU_C|sWzbgv&T9m{ zu!1uEF-g6A>KpSlt+M;5vVkG=u4Pf&CGz!;BN2?PSSjWW$qM4l`dbnYrlSMVM68p6 zvs1s7+L!nD$$aN_yGeIo+B#tF+uA+<;{h{DF<`7T>;kcq%KwFoxKgfGMGbWdQr(fD zLWY>}CwMzn<=H@dfhr4T0ct8?kqq%?L-&vxeqKqpsLzxi;dMm31_|xhthl+t)T3tQ z91y5R0fqOJfD3-1$WxYR9;S@SU%$5d)f|I9ufck4eiieo8nI*^^D2rKMu4E(@MvBe z%g2bWBHpz{FP~LX?%XT;*W%w5b%v<WU;)F2vP8VUmLDIgmFJduceFh+vcF$8XcXQ$ z3?I@IA8n|6<q){?5B5@goilqgi8&GVx{cD>87VF#R<O`kDbl*ic{=a!pZJXi#l?L= zB*qX+3mmeVOL`I2a<;Zu$_+^zvP8v>7R_D<Qu6Aj!WKT-p_8!n47!eiK=x<Z-1Wo2 z7VfF%@nnAYT6Q@sb*#fD5LvP#Q-hb-vGD7)q1@W>=d_OBjUz1%@i`IFb%UT8$I^Ou zarx(A@?nhY7yA9f{w|y3=YA!>96mLfD}Dvw3*jeE=<1A;S3+oWg}VSu(W5!#vsOgv z>KxoVwDld_xn1clt|ByQP^e|xDlitXBNxUx)IyYy3t0&b_aig(H&>U!9Bk|NH&@*V zYIaO@%1@rs#ED3x48JcGT|RxbOQQNn$~!klGKS6tMn`fUkm&ZvGN*)$3fpEz>No2d zbH`_dAHZeH%`fGT>%q2Z8+_?VA!}_j`mo<rLeS;?W#jD425t7<Rc6+M^KuEjuCbE$ z7o%ehW*5!UD|1?+%wVjG1xe3)__M5=y6*2C({5Yx4Sm3P<b>YEs_i$<MB^}~5_dMh zn+8V-v}S#=1fq5?wv8sx?6lh^u-<eqBd3zVg*5qZVP;Bwnbi5Cx3AWnsHPE+$<F9U z^B?qx;eq$kWO=1?94>V4Imvd}WmeZ@u%>;uREV}l<RWdzcgbnyJ?6W$JVD(J98S#6 z(^K8(l9WBa_r;v-U<{~62>$%h7c;K!ne!?NLfbKM_wgH-dT}Dkb~?e(T=|X?Z2)MN zr%}ro>&XeWY4y<1rI{7?({}xCJyQ$9-A;eF<ttp@*9XJn);ULsTddWlbq;9tgyfOq z^qey6?P|8;22WprD!nFdk}O3(t|}8)zO3dEf4Oe&@Brf}O!^zE%MVGVP|u%2OhdAA zBHj8N{Uq<W(Q=eBXF2jgZ*l@<aiKDpRbZN!AAlDtG9=77f=c;AR`#2QK#xe%k{F$3 z^Yct^+L~bP2M2&`$~>nx!b#l4y!Mq-TC(VbGZ4|Zl^7|-3u1}?59nD|@x&?{1}Ixv z{n<zfzgfO!2-*K+{1(m1+-g@2JFh<x<ONjGZIJ_R^O@an9w{D8$h!W%MuWmmt)?~7 z)*4=hl4;4-%yTy7R2rME>F|?ZMaD9uw~WC@H<yx$MK`f0$(&0BLs*>Zq>HhIMQziZ z&2!2?EP}q8Vci%NDP9f>lfBzirSUdTj8onAj+t2k=9BqIEu>C_uBMeVEt<$=g_H3i ziMpuVn(RVCJo=D4o*uW!{t*)i_bvx`^_BkIi+6c^rM(9!zxIyDMw@GC?|Qq;wGw%X zwbRaD|8$0e?(1&HJUURyxo5xgeKq0X5&1`VvVk5C@3}^T*<!2}u&-EjmIDt-*hRIl z&grc%Iv@%84%-V_2=W3pbGrl2hPn1Nt%O#d-<!7BcnvDMotV#Jg`9F`107}UjEIdK zYRXclSnp1uF_q)LJtM4M&yMAte5rncnO~{=!#;?{rMO6JjRLQm>KW1s;-_P(r~yRK znke9qU@#yBscd^+YhbmICfM;1CbE`j8UQbKvd{NTMwb*-4uN}nhSFjd(WUQV$*8Tt z1P3B+GUgwGWRPlond28u8HEru5gdE!s7A|`Oz-wN^U4Pe`>!xe@wZGOPuOzQC!a0W zpr;X>{w0{=Ium!asOK}RP1Pgp8DT)O56Cs~_JmcZLey_K=q+ACap8m?(eDtz5G1d2 z7PGg2iF|Sy+FXITLYZ`VT@r9-KZ(Ny2#XR#vU`E>Fg>k_3a<tCau1p8nIv@(EeG4< zNLQ2V9bQ}Am<-vQ*AP6zR`Z~k7#JZFbNuygKzBdO5jR^ChZu}~*|0iX+yg%}4R|cA zQw)^0f=#FZay2b(=wt4R$Pd`)mQ3$U3`@K&mR3xm$omSI<M4qCd~t8HX^CinDqAqs zpLQw^6x*T27@+gF?K|1kE2&J<7Q%Kpcm1B$MS2M0Po6!g>4n=c<!gjw{Oj_`c8!sO zXkxVYY`{uE=n@dZ`Y&5{{^M686_{&@{uwW5WP=Qcr$R_aStwr`-z}fBm2=liFP(cx zYaY-f4<Hj$GqH>Ry3B!8e-z_6Q^B?j;5P4$%n%K~E9;pcg-DrYRE^_8IbsT$%%&Zd z+g+ig$<7s`{u~@Vh=PeuYMGMEfFJfeZhH~L_J`I^hP=7QrT%Muj-Ep}zO1*DVE%Bl zE&kN%$VSK|@wV%`zZk188u81D0~j#H%9lCDnWtLn^V-C4h2t`w#$8@;o47oQFI-3( zU`VS@IG6ecXOZZP?*>1P$&JibA?PTDGV#l2W)GsYod0$1;Rn;}cvrnspg5OqK@j|3 zX?KRNK88sP(FhdKBsKe{xQEzJ5XLe?JoL0&|HrrFj`6!P-efGUP=aI1e7o6e#(f6$ z=YGmaXEQfFavs>%phF1a|Jk*lRO%AX^(~dA#l!RxCymVvIaeM(hsp(+>O7z__YLv0 z&kYqVykS^g=Q<}i(qyHT)e%~-rB0->-F*k-+0M2CjKOK3OQ8{%$9RKOp{SP~r+LwL zXUMX0tIC&k+Q@}(m}8+pRp>Kst3aG|AMdB_$FHrNlrsrr{X(#aO^o&0c-P9LxLM+d z*bapvoxF5tvi;54)@ca*|8tW^x~wDaf7D79&Cw}bXtB?j0@s(rPO7d(Fyxe*i4~1A z-HufV+_-CToGw4Q$Y<e^vtRWmr3{Y92TFtHasO`<Br6tNYOO`l&ON2m&uqug9`wa` zFlPgvoB}}i3!4hFTDY;R{Uh27S$z*-Lhxj!Q^+id=T6T)Zp(x=)9SeCiARE@K#SS` zR}uz61aJEd|1Y`HgZd8@hMq$TeK0Pt3FKyYF7dCAE28edSj16_t>UR7GoUypX(ne@ zGm?}mE`y-)xun|*ujJi5)JiH~8mubucbM`KzDTiDj~aX!DHlLsvrL+e--1vA?xPdq z?5{BzwQCK?r6cO23Zsgn*GJQr+1RfnpaoTU1d%pYl9FOB!r}2AO@|9hXNU%@wYW|M zL)02BEr0Mv(}Q+#&x7vO(p4Lu5!P3QR2#(2IG{zhT3MOWRn$&Mly*`!V6FU4M}y_c z;O4>ED3xPn)4(wP_{hG4S@tCIOCIp<AEVZ*wJ)U0F4B3uxtMl})C6;I`Xzz*Q%KUD zg-lXJUaQ>B_zUjmRhJq-`B9WfSrCbvzt7ur?8{T_-5&iPs?6>mP!m)4aE31lb&KJ+ zZCW`5=)@|@DH}r#scFilP#Szobxr%B=cQqD)qMBvJ{2a`qU6-1Zc~U_c6Q?SjGn9} z89_S62~Gipm8>89NRJXJp$qHC$L`Giq8no%**`%AY#bCuH!|!u>0)~9vmiLztW6^G zwEE-2OOJ!Ok-LPj<vxhEpGIdNP<c)0InSFV<2IM6Ope&3;JSUAh76FmkSq|!z_pb7 zz%mlg{v2#WWj6e@9!xOAu@8dZ!XPKkWgPOLXbH5M5?}%mB>GK3-~V1|r~C^!e?-Dr zK=Xz1UwmuKv5*cH#OJ6uEf-S#{1wwlAT1Mu+8Iy(lM_>%O6p$m>jcNo&{yl$s*6M# zN6i?&qg?Q0fh^ul3szgWi-kH^tb=Z}OOUygzpWbmf5zcl`YRbpVW9X577b<Y7?2?b zjSGk&mc}M3?bivo>K4yv-OdErwARd|ZQuk7eTRsO6}y#clWyRoqVYQdSp4(!cwq(8 zpU9WsyvI~?+IqYGi4~yGi@n0(A<Pm}95K?mogR@|)DnrjC!ar%lDk3YjG%lvLVhrN zwyQJcK!pxNlW|xg$s@Vzp(oYaP=!m4sk5;Iic~<V{Y(33=Cq@6*hC=0-=yywFSvql z!9utY6mFttYaQHLFFszgg10v{OPkysv&L{DsJztO3_aDhB7$x7HgiL7SQzOW>^O7U zEjn3$@x!gA>+G0vIOwBQ{76-p5y9}d(m&uCyYhf!FaI^J8>D_h^p409fm-6s7?;HX z|7y*@GsVSJ)X$9dnzYGf8|x~a5k-nFu3Ux8nOKDc?SzwK%wDO(+YN=)M#95ZZ`Peu zU6O%I+u=!@(c+T9re>RLPN`U)ZEuQHQl&JUg7a(niCa0__dzVlRNEExb!coqeg;RW zwnmDfe#{O-?83W@ehOKiG(w(4q*!p3zp876UWRBkm=ox2wZ(A1xu1$<dc+Jn!EYWJ z_{G23*k%Y~==$8$=W3Q_3a$cLa8p}eze~I)3tM^cc9J$0k2y7Fa@Ei^*WfD^O{j9S zAlNTnG6(duD4AxeJV&M+5}QD(X9RqH-U*aNk`SHp;_!JOo#YhL)LN#FdZ;4CxJz{I z!H*=tQqU}e=O|SfW`F}d-ba%Q<0jRrF37DUonA2`AR4#8znMyd6)<sv5=;;o%1v!J zqj<>{8^E<THj9~(|G^3^v-}@()Cx!E6)Jqv=Jt`mj3C};0gqY_^oJVX`i?06T!QhY z_FKA>`D47$jR@*#tijI3-(;Z(c@~jkq6NP)UbMR1<-}>QbAE4a(HZ;<^Ap3?|Ita! zqXx=UX`*M+s18aZBvenRXHQa{kVN^k9;{1F(zgkKX}ZmwXpdixFs4N>PZRD+85xh2 z-NlE^-nKcZxBL9~lSqm#ty~q!L0pvp!HS>&lRd_-sCLY<9X9m*TqzN}+Lg^d7&e(8 zGBOi`9DeblCXv$tMcKhgU~w$}qX{CU>Sxjnm~HhHD$3kv7w%4w4T0H-{1K(Kj|f3t zFP|L2k70!D>5X<p^)z7xHKOtV92?IR{GVfsenq@!mnPOB{#kugz9tlwxuG23w4h;| zv}uDvNd8?X=?7l>bev?_9ie-JZOcG?P$5;Pa+3Pmw!RP}ZvAi4*HO{drJhGhc(iGo z@~eFF0wn_VlxpyUNrvD~`7~o>dq=u;j*q&(iNvUiij<LUzSLG&?|29BBB)+QR>k5+ zCf&jCtf7|5RJ4C&h&<RpbutiCvBq}>MTtDAv2Tpvv6Lo!QKpFgPo3jWFr}F2WL>Gv zxPmydV<+ptYa!_N`J)+$f{dy}&o>;lV2E%Z`TN4!gjpanE=~@LUkNiKnBxi-H3f!J z7E@f71NYckaEib$9r-#f(k20mFWq)6(w1P3!MJGha_EBZ^Xo-E7r7fL74X(9m?X!< zrq`z0CigHR*t_v0STdSrvm9h~sS}k59t4GnCyT}L<W|lE7gYvH43y;lM}3ELt|r6B z_~j>#fJu-$_kZ@S&$MO~)7EvAbBA$HmCJ}k6fWP8&VaW)ZCct-r(<B|fjfB|n0dv5 z@8i_tr%-EK{LEs0%>}X9O8v+WHYly!-O<56SZo|O@q=+)Q%q=E<O2zBu3bX-rTvUb z;>7z%DKg~c63<p<1mAvHPWj<^I4v`0;5Vke3Baj?bB79HgzOpUa3AIS<ckr0(Lqa? zH5W=*`-0kmn|+y>q{(Q_7B)<KdCC*qgm8XL1SQM^@qC|BJh<ws19%j!3wlz8tdL~= z@stCDwsA%OQv)omq+5sY5i^ohhJyF~;;wVOYJG%k@eomgs#j$Xi1p!lh`TY|0i;Os zO3Mt;$KZjD0ZF!kuJw5nYteMFvMprx+!dXZeYQM3+D*~7wrl2O@!qVPAB?#*<-a1C zg}1Ay!Kkg{TAxzr5yz`!*!M<Za}8$yY~%1xfV|k-E~EIM(PN8IB?BwTmPl1#XS!f* zkYwxe;|y5BGI(qLdAtRAJ7JhwmfOY#&F;G;GmHsXaX{74;wL9<@TsnPo1QeKwIa0O zwHFes_E@e<@P^j_rJrRuTo>ScS+$y!OwvCe)`e|-;~=GN{<+OeaMA<RAx_gJqvJ*` ziFr)k2;$0T9-8;*_64E~+efpGMjIU8e*b4uaFKE%(4=03WMpht;1LxXmmEwXV@n11 zJOunBw1T}s$Zqu2>E>Je@rx?T{X9Wsd7h}MO;@R~e|K~`loHUu#Is@#<yoSRb0&hU z(LQoX03B7s{d;GEDFlVg2FiOD8!<0u-igBo3#@SU`=AT!Bw(yFZ$|&x;l)2exvuCY z&eS;m*u0QiBtsdV52Nxq*Hq!Yl`^54KgizFjXP108*XjWx}WQR(0t!ElQQ7bvfs98 zUBey=w*j6V@F>g|u!G#?(f5vgvnlXqmBxOqQ0&>2+>Dkc)-98Ks|j+$?ipEvDh3E} zkFMhhsJ$R#3))VdCW<8RUsr2G0G-#$)B|n<4ZCDO6!~Wnv@v$5Xm5_4l=~)fx_oXZ zEsBs?<%|#Zu!_+7XtD`C_4S16n@Hdq6;!xS+~6p=uC(>FsjZDxBgByu41pa%!H9Dz zRCP=x!uT8r(d*8Ic`e}C18t$ZI}msr;}XM_ud=;ExzXWYJA2*CwnmeO%ku}&?TY42 zsbu8VX6cW~ZijjqnET=~3_37_D|K91>>DXpy)U5OKR6?;6l}=-Nk0UD=V9=rO2TKT zpdW1?9#I{jLgt1u@g@Quo_A#U0L#h`Zc>j$%38rH{j<0~h8!y1CHQ72g~oZq*epI^ zL`>szw*!=8zu}=|2SgL@4uYP$*VBI~{XW#j+^V$XUUcx6qMGP(E_R;?lnes4(m~Sm zONM*B^NFye4#WHZykCirx4qN{v|LSvk?$~dksDNtK~3-~aHB%BR4CqrjZWOEu?!;y zq$@3DF2fP1oYeN4jWRU~OeE-V5Sb&3nG93nD_ajGlVtH&d`KU#m~J2Ax`Az<e&bg< z)fC=YJm-p$_?oOmuFh6Q&LkcgO2-}T;;;dy6By>gX9vG4VN1Eg4g$cQ`XMLF7Ct<) zKCp@)Q@Kf@_C0I2xWDCoY2oq|3xMNX9*LrlYb#nkgjGKs31!(xzA|;{;2RxUAa$a* z&P#k33p&=AHi#zdq;QH7OUC7fe2)>1uvf_ATq#S&7xMc*bwdyX3`gEU!aG3qRVQHw zCdcu&9X%3W_`KwO*;AQMQb}l6ni_KQ3*>QrL#lr&g8y_M?SV6nLq~E4K=Jib6H8TU zZNa``*){NfovaA)+7d9Dn40a}pfW5J439LCcTy(|(f;a%C~@98C4}9}-%YLLcq<rX zhDu}gorgB2lFwg3nrsj|RKh!T@n-H<k@?p-a?kH@XuZv)LGA9NB<MKYyL_zI$ZN#E zqf9(Hn0*}a2W|hLael<6Ws7tRkj3LaRd#D8>Fk31&-&p-My=xa3}F=67uP!|iT=yK zhXQ>TY#J5=BFNf~N7Z38uhhGr)kv;}2C(#VvBkG^YSc;uLY@yW7viO3amcCFxAG&E z*eblFi(DG0K<&JLQlIW9wYBJ)>i4>csWV)n9o3lx-uZr<`2kVr{d+#*vS3q7Ce<p& z*bzoIvQv{Pt^uOT#JU8p4+!lIHYVjJ$@}tS5<eDhvZB?jW{aO;Z`@*rg~O1(mSxP& zF`aXr68T?esD-JI0;>}%&8XuWf1#QUSF`WBV7R#kjK{lwnHo(gC37i)3-S;dxcJX- z+J3%~K9w`idYuVnuKOd=mL(vyR47dvgiRYaxm~%Gk17}m%E$F#ldJL5D6sF-+Ia1G z;INyx`kLYq8C*tALZHK1G#M3d0H|nJ4(VNrm5+?s=#Dqp;z|YOPEJLU4ry*#5>RlB zO1Q5d{;k7yj&Qb|I0tk2N-{+&amb3t?&uE2B2}Ojg)wEkn-2Bew|Bq$c0207+!gc5 z=jsLJMB3#gzsUiKd0L7V?uK2Rz*T7s2wv!ps5exV`-b;ZM+yZUWI0SOY2?gfdr>DS z!rM+eus8zy8)E$*LTuZ#2pcH^1n?VN#AHQ=$y6FuyF^vuK9*2R#}nGA>+^p2kI4sS zWPc*fgpa)hq{zcp$SamSnZJ-jcCNP!5S{4@GG)cE^8;~%#wb#cJEOnzmfxUHs}gJN zlySe8E^6@Y8nDg@+Jj<|^srxyiP1gv9FYmIYho({`!@a8_5`MO%54NL7yJ%;@415o zZgR?nW<%=Ped$LNu%t_Cq#PRTYQg2w?wF|cIqPQ)h<03Uz%5cmE~Oetm}HFX^EWb` zl@}^d7$#%?ZeA2jy@hO2dV!=KUiK}n08T5{jzQG@W#XUrkC}f0o_D^6B*IRwdY!lS z*1T=n-7v(^kNY=W<K#>D0$4lpCkP1M74RbEP~BAa!S!7Yw$*S5)i~B!3k@E?mmvAJ zzYy@upt(b2)}Gu;6WYd$z4J%VsIfS052k$BY-}Qnn6sVzOPpBJQBdu4?Des`i^ZJx zDJLO852UwU!fjlgIf-GaK>xj>e{2SpU<;U@(uA*~)bL{aWO0<$Ae+<%kmyCWo~!pQ zq<?||1Oa=|L1L8izUSM7c?78h`oHIjvoaIkK&7HUQLp=5Pnr=U_{`iz;Z$qhU$Oce zbg4BOCSuYa#=rYqEc;<LPR+Y>eHY>#Jk};3z1~qf_y6s_N&STdC4dK!G77qpf4Cl^ zz3Lw|BXBz+Hob(AqMixeP_fy3tcoFFEvW7Lxeu~1Ue5q<qu<G9s^^_dpL^CCBwl92 z?Lp?F?7ppfJkuL-&St@pq3fyB9_B5BbqW`tJ6O_PH}jinOl+ar&)&m2-`axkw*-V( zbAHk$kfb}gTj?1rR~y>Cn2CAun<?7GUw;P{XVgjefXz#w3Pu`9a5T=i$4LSavUriH z`*3{WNXgnT`O2Q+?Hbs+$CzCl^mf9a_Y9=S^FH{9l53!elH6R94V%ftmaBg4iI&29 zO3E7J48iCq#4LD8M++zS4bDWC-FL~S4}|9BxdQZd{;~%dcr}`VEqAFuVfLC!5CxU~ z7DHxV=cE-v7JDJtn%5kGTDk}&Lj-#jw8GGspN^xd3L4>T)!)^`hB&7sE<vrn>#l~` z9e+r{d_^a)U;(my$4Mn!J;)4w@V*UzU2m=#Yn$K=@O|iPLZ#|L*o`6SuI+^r^?b{B zv4M$mc2Pf*It{@KH7(QZjfWn-<Fkq$^n(;r_>eoRY5vNVOBA#YnV2XhflJ4NmRBY< zusNn4OGmx<D*)++(%&UYF-j`gdyKpvzMd#`bj#9)M2jvMx$|OGfIO%iIq+yCMam#L z0p!LMX_bC^${poxi9~{`j!zV`w0H=_rf3wq9;;Mb!BjKIoZHYEWO^#}QXl;M!ndY? z9?xIiw?z|cl6fI8wEk#rh^?G!ib9IQ^G5;yHk{KOcR@YgMZz2Bd0tpy-*BjCt{S`r zp*;{Rte1rZ-LR$YkUA>k=8E=HSIN=VA8vYg5j86mLw@l$O78u87TQ_la~RcG=)6bJ z(;oT&#P$YQ0=_KeFq*EJD>3PHqCaz&tlpOi&nP<|`B-g3dw=rIlL+`6f<_Ilq}74A zGgpge{fjN@c6WUcxkF`m#jDOzyy#q^Wh5(jmDy+4`3nlxT_7&PCFV_u`F&Z>{9K)T z^S3?I$>SNa+c7WTtV|N~qbq@TVPVbNA~O|^t&2hr^z7e4SI6DUWqrZd?yQ~FQ!gUE zzcW!!F__(^us?v7(Iafp;Q3!4K!}@26yChkzLxp5dRWF~7U|Ccet08B9SS@o%}V&F zmhKdc0&aMHABDJT-U3DbK<wy-8)#OrBAp!W0RZdZ+5VA{H03ak$_6avHQUr_yjGPo zsnzh!vu8@ArMuu`3v3LW)aYJKigFZJVG(3Iry%l4`KE0#>7P&UY1w2OvcSGCoiJ%O zhE<wyGigVWh>~tsP(w=J4noVqB|4FRfGq0wDe04lkcYZz-gK#~AV@9vl%c)o{!49F z3_R9p?YM7$5#TX2U48rXb2*-yTiH!41{#g{rmA(h?rr=?3Yqw9{)lArSpZJKxXs0T zU>Ss{Jh9D^ICU^2C#~qD$r*<vb~OwR8Aq20TY9hH{i<d|FC$!7rSZi&RD#$(m_Xp_ z3ETHWhXAZRYa(=MqP&zG3)DmVKr9dB88W$VCv;n*rJZ3#zofF)p5@|GYA@69eE}Ou zsD5$QLa+lN3O)h6YXBOx=yh$#WGZ;8R<)R~4Zkl#ZjY#4*V0oJ0M3l4SIE19yU#R1 zz}H^V*-OfdrUK2!XMlFnUspq^oM~bzGwxYmjmNe5Nm+f+_oEQx^E4zesAjNOyV8K5 z9KG;5Y%>`z9rPayE>x1)yE^(YsZ4sN`(-reI@3|#4+l@d=Bo8_#JlaXAT$O2)IK0< z-|tJUd9gQY1g%2eUflfzlKC7?q4Ky+ybVg=tV2p;=rlI9MH^q-d5s*eC+K}e>&R>E z^p=!0P22z^@*&#(*hEGJ&-^ESF?!+fN~NL)REM0^3CNvPnW_^-aO`|hN}YzmViSIo z8wUE-QW}1tFL!B`uu`sy4-~b^Qi=b6GR{yP!|MCN4;w{sp!%d%^pUNHDG3hF2i?7~ zkeJoNzbh+Dh^vIL+qy7>t|NaV4CM3x7NS>M%5x1q4f+XO%qp$dUiEf9zxdYXi2P2j zXnunLR6~?Q9JZ_E5sAJU8BJp3c%M9_Xb$tof@9>o2cZ2faEJItd|AA*2wv;HKRaM? z*M!f$uf>Oxc#FQDD68!ZGkXY|fWfd7B>DhNP__Us%W<ghC^I|d>0k|XX;o6h*Uq%U zGc(FrMF0lT;Mb4emxY5Bcb;m<!2z^=+pZUTZ_#+H|E`|VE9Cro$oW1nq<TNqD!IV7 zQD;IhSd=s<#fyQTlTru4#k+&{b7Ck;)4tz;P7}t6sy5p;zYXyJ`G8m=16q~M+-(RG z%`0-B3*;eRo6El*ix=U=K+e!OoZD$X{?!YySR$cI~E5cZZCSDa|y%Jv@TD6A7S z(;1r$8PitF^dVJC^+ngsvV6K$UU8pG&AI!mQChap;y9~1W!?`4$?<xTw)@<~LgQ}h z6AnY`Br5pc+7j}JVIRmJ;!4gyY2dd<LY1>WNm7!`V0AKKOdts#US&ND47*==$I?)F z4ss9v{O2nT`5{!4vfm%Bk=^&%eNXthOgjq#ux3`+1Zz~_{gEKJdmg%m*bP@Fg~;Q6 z;g*WSI6T*3!|Zz|LG-4;yraRd@)?l*3Ju_spIb3Y%)bT!>L=tS*&-_->$vm~z!&6J z7?@nM{KXNP-n78>0jcie)V%r@UABf70OD5;>ieO(t=oS=l|$?de67z1{kP~smP-cB z+yWw>nsD|1v~|wWl|)^ekBuAKwv&!++qODR$9BiIZQD*dwr$&(yze)&X3bjj-(6L; zckO!4sdMXM{~kSHypK_c>gT?2HIQ<Di8@mF;mtW_9pLKzpWhcjiA`^Pxq!Y^&#*}| zBagB2;{89LyS|huet~WX-g8OF&>L?-_=5fyact0-cxaIBd;z@G<|De-|G;%5qu-e& zTjGEHc3Ak3Hz#pX64jWhX*k>7xSO_0FzyYKu={x^`@rxGG!?-5Oabi#^{UL@0hN_q zq4!;ek_mhzu$0R@UQ9$ql|TVGUucX7a75?!cBnu1zpqhW1$Qn&$K5#4D)x}&IN(8V z4MWGxDl&3Lq;9Uijloyon2Q@)c)%vDA0r@gho$)ao9V+HWuOvhxzL!xtJ6iiW44uO zNZhXBri@EL1PWZ!dHe+PX)DPoHe$JpI>24eB9rdvNgFfg=O4~3TGo~RQFa|e(~I53 zyY=wy-p-Y#xnVaLF!iQtaUri{ouJlTq_Y79%D*(e15gsB+_R;s3K()YJx^WvM~M!b zKfh**8cKwBE_)u{<aM`=s%?QpQdZsCbgW107^2#IZXHGPA5*6lVn2!a#}QnFz1$%@ z-6Pl;n!X6=Mr>P_ea~DG2t>|nY6&$F<4!Tj12aB7MQ*(LPu2@`1t_`;?BoCat)0hy zBU(Y?lAvii)8-BFN6K%adw^aRGSLdzuZ6^hLIINH1xc?&_-&V2_$Al#%crWMr{?@9 zcwpL3!q>-jR=KwJvgd1iL@UPBAc*qqh1#~dGK!FSb-!zM+sQyqm|Ao;C`TNtES*bU znm?g>nEl-XP=Tv7b`Np#ckAqX;-6oXJk=0UIME{?Lkl6QMKVF_RPD(^?r(tOyD(^| z_cdn?Twrr4LWQyX*jqN?yY<u2kccYd=JZhzst)oyW7Ubq9REyLpV_sZ40Yl9UKNuJ zc5pbA+pxwxlPZnS&nJ;^RTZG9aKI&M*O>|h*FK=3xsRGUY&cb3J@@UWsdqV+05gst zmrM2<2F_T5e6#+{rFFH*H3osH%)RLZU4{yAO)7##5ZN<FM1ZE4kjqu%YdyH8G>xxw zKO}ZWF?PJkX64=Hsq3FKPBT>adcNoHd<+C<e(auABB(bfbsQ4dD#HOSY0t}&>L{io zkJk}a#>3^mk!m})giv?+m<gQP!W)OM@x7Q`0=L?DdfpFPdSkNULOl5GV?2vCF-LXe z+0nE6in<&(glemzT?o=ap85ey#V>msR*}WZkFv3-*5Oj`K1ISil99e1Sf$LEPI}gk zpLP6FGO|;4l?-=j7u!UX2^cv!IXENt%K1P?#1^t07PD4sS}jFXx(}*aiWKu&#XOM4 zADr<1xAF;8XfF};R;;ecgXsoRK3N(j|I7<~3(mcXmIvpa#2=Hi>oLu-P^qP%gVh$w zl$+6DlB34z{Bi%oCblp$h;&9fnC#2gK1;{z+Br0<A;m%kL!{uu*k8=2&uII7_!8k! zpbKqDb0!1W8DAKTBtJqG;r{=Ti<LA~{~e}laOoe~8~eXdFhZ=g5-EN7iKz)~MR2*i zC{x(T%HRbwDC+)!MWqtSPH_vgCd*i4t$WxZ4Rq(M^ee@_Q(H*eA-PbQ@MjG!Sn>q_ zFUc5bk0nD)7Df6#Q-sWxPCY%LqH1{_MhHvIU=Ax{=O+RjHoiX-n2L<_uPSjgCqaEG zXP{Vqc#*q&B~CLekOHswp!Zp(6J1jf1Psk@a&1NPXep^>Mxs@bh%Yj!LgpG``Ur4V zM_JmUhQ-5EN=rZeW$<T@RZ~5X+T=@-ROtll`k#~JX3hwW8I5B1-)d0#+gmA7NuD}C zTBU2G$H0wR4WDobmg1<jN#Ze-h^<Am6B#BAm0B86y{eU*hJ(Q)daLIM%|ku?A+Lw~ zlPI9`SJh@((%ZNg&4n4J@|ApX&kmKXPG#V)u6-CCVus!Cq3P=*PxZ<YR*27OZL1wJ zW*KQ>y{1#O1vDoXB^i?<-GDpYJ*Z#>x)PPdm=)7-XADtU+Ql1OG1+2;ko3X$>%I3( zZEf*M)f7rW0U97{$%*FtE0iNDg*u9)EsNxbsPwF$kwUH0sED-VR2kb>3BbeBwanR_ zK|2%byS&H5_Vvz^Rc3TwosEObB5?!Q@ypDbQ}VibZWa#t9*;7N^mvjH%~^6@ZnjSH zQCfuUzLtA-nUH7_3LKO94v%uYYLkv4iu5D*$Q2ANrrMjK!8w=qvI^nZt;=629fNhy zzTPTPT?D63YI#ja+bSu_=6w44#lA07og*lzaW2g1m9fq++H-@ik&ps5h=iZEn6o-s z8&hP;b3(;Lm)Oes@?>eYx<s#v`RPvLknGV50k)oV?PWTPzBRnj{NEanx19e}As<kj ze;Z7}D}=#mLocc=m=ZFnj8kf3gpAsPI5xght)~dh<^sa$M(M2^$IG?o7YCItac4~G z*J%+-qdZPH^I3H9W9PCkWT0~6B7DTySeBm_+IkpP-0$ZwdfGZO<abX`)LG3eH*2XI zH}tf7=)}$qY%_e<m8Nmf#uV*DH}BG)*!AeBw12hqS!{KNQER*XZyfYjZB+#ar7CsQ z6k-!r6j}BQaMF)p#o<M$&0L>v!p^<@rp$O###qw=<>OuUZ=gzhkKa*{$JhLZ2hKk5 zS+!%u;T~+0Gx@73aR?VxawU90!%Sq}4h{_{b`Q6;Y+VA44KHxBZ^xf^zz5`FF2AQy zxNHyk7OIH#fnx#_vZrdk^B|qCbZ2FP5gC-jOkIgKq$VhV?r}RWx-c4HZ_(dD-}FY^ zz_2S0o#*L@9Ji1`y0^g7nU0CEBfj7scZFhq{I@oC4?&3>+t6K|DWp$XpvZMHTmL}p zijHaSTDbHu?2|$DkNj{8u$C479dd<-GewE3Jt)=K+Zu3!WLZ3!@aK|u@7~uSxHp+m z=N35!t5Pk?bt<N%u`<vR-qm&^2HFF<2T247f^&6a&NU!`zLKAXbw_Ac&@C=9fb_xw z<F>A0s)N0FOv>>2U=01+TyY0w(%j@BBEq}Ex_yetTCZ|<^Ons?=@8-b6Q8CF=U*Q= zFGBumA3w?6nbi~2TG7oX#}KmdI-T2&T+1=oS+J$E7l)kgrl~kc4LE8zPtiE@arGxj zalQmwFg>IM32*?#oJ>i>3OqxnZSA9Uc8jMMg!!oBwL$n`R`uu=T4#oU7j~s}>PrUF z6L$!(UP?wCDc-vio3$X;;`9Z9vg~pbhc1F&U-A+rC*5`+uumK*NxykF^|LovYv|;w zi{Ni5j?=qLFtBjkns(v9$5tyVkL&vh`MO=7;xO8NO51I#8Db@8dF(YlfX*2`J!54k zeq6v8T`1LfT9&>FzLlfE)?=9Ar7$c&EB5}m9kp($!$Sd^1SksPx`iy2o2GD`r{Dn0 zxnI#StFL|wk?CdcWaEB5uWo0l?94b_Z#742`WW96<qL7*6L0sz7AYZkIE(;3!a$z} zYWkV?Vg~3T3MnqnhdREhEBJG`5T&}HEo(?Y$EWK5{?fQ@7#8B(`1C`$Q$ir^#}z>c zMZwU!FUFuaf!=XWd!XIA{9f!(uj{n>>wT>M&Pevj2X>gY+GMlUZ%}eYi4`M=EQN_L zXGJ6HcOr2*@3s}EFUr)6@<zo);AYKm(PvsIiUG3+(qBE$(-dj_u(2iXwEE62Bjmd& z>)h*b45s8wqIb>jZQHqg)#enpX}BfHqBE@1DDu|TJi*d%u0ie`cCvC~cm+jN)kREk zd7%G7PJS$QZ!dAI#pls#45Omvx{LEHmmT;oevr{UmM|jbplDzdtx*u2Xa3PjgY;2Z zBBSzdP7wljs}&eF{zKOjZ!1f`JPF6tlp)E-4#Z{RqCLsgy6IM&rY5{;EGy;iez%b* zNgUB4PzsITJ9-Y}>S9?dRZPF{Sq~)p?Z{p*{nuiN#zj|(UqKMxJ#18`8>1(*+YU1$ zEchVn%>wmjR-Z1Su9Sna@xX@rp&=lnSY*BTwkvLkg<K2nL@`ilBM6`LS@Ip~WO=&M zFLD|znny3z$L?kuzu`~y2to3pq<3kWWGnUv?Y-bSpn@f9QAe`)mJ)?Sn@h8EO)jG1 z3&>6Ft)Rxpd?MSnFt3z#K6P=VvdI{0KvAKjspuD5O0vt6HU?>XD*ThTLHFES=3G)^ zC&8?fU};b(G}@LkmFgdgr5JjAmSv>uF8c!So(#Rr_ikKICC3hfC!-h4(|%0SXZVuo zZ0Uej;{Grc8I6f&qqZJl1#<gJd-k^!Tt*c)JJ`~8btI$rJ$HJ8qpJ}lU(T6;E9sTF z?Mi{PuU1kX9JiHzhTConqqO{q)sq%(gVLMglRK2b`HSs}kop4DW6RGbLZqLj8SAph zxOc`IfY8mxvO4Fn<#R;3!fw;aRfwx-VMULXJ{&&Evxk9^$TeB3MGj>7?bD5pd)IP? zE$oC3>_@d~FlM``=A2gQKC0>VzFS>V7k=lFURNz5nx5S6-bulw{u*$;{VnMm?BSfG z{r#>jn|H&f3C|hoM3j<@n7zXrYzR)nx(>~gP#6aJ$t{&WOp|M}nJAN#z7YwGL&4=H z)(U4zsGklB7}17IrqM0wTr5cjGS))R7@t=sk-%zeNv%Tw5_M-M+#q{%t_Op^8EF}L z(wo2h4}uF70V}Wn-#AgWTN2f_unQPcSD30M<c%V%PbaiBCaU&XNWa4FCvB_|(Z>#K zX*6Lz1}6@%mwl9DXN|i-5Q>YiSm}-9u0z`pfFJxj#U)v-&;&2l)*kxNZ3Mb>H&$ac z7MZ&9;;)N$5>X&h4+H&NxJGVC&Xxh-`lKWlIiUiZStvLq^&(A>kX}^t$qpV;sJS>w zva^dVS7NcV^yi}Fl$PvH1|$6?{(V*L3XG;>4si#Cp~7?K^`Fo9H)b~LJ44l7Y-1z% zRR*kjsSAi$xlSfVDC`DvZ$b95?TuXFaK*{@&NNJf_4ZCzV37yGT&vP!PjJ2yS-hI# zN~q~soE%Oyu4x;(!p?E`V$rt%a)*hvF5Uy6^ZIcXZ)Pg{bBTY^H@r2(hpodj=m(Ed z{(>Q97G1c6rT<B#iI6V*j-2YXIu{<)Yi+uE1p&%{Mve8e%g&07(uguJs1k_^f^GnU zg2a|rk;w)MZ41NvrZ{h_d2}wE=O(_b8Q(8QhB^c>ufGG*&Jq3+*YBmZP@+cgpT-}z z>9yTF^+7F9%n)`w{CNIJ975(v2s-1<U0&<Z&=5n7Ro0-t%HsdH!enUb5gC^7^cq~< zUbry2JWn9R-p{ZVmf9p}0`Pa9M?H~i=;ql_S<Mg;GeXKs?$VdV0cm=HdWg<X#Sm2% z*shMf#KmT)>WMY-e`A@uDJx#)%O^!oMcmoHtomn+%#&5WD%^^6F33vfc<s6=@Z}`M zhSHPQxjKN0^_ePH<pvXjvA{EIxy6IS|2j!EtJrGw7!fPFgZHlyCApQX2c?NG*pjN; zWnz#qMOie+rawAbQy8gv7!ECs*Jrv_AbN_})vl6Qsk3>SNEP?!;BKgbs%1LG7(C)$ zy1BHaD2UTZtOWo4R@G$Rk;6utO_w5gguipDhKAA*okPb-tv^NHqrMGwla7F~GLl{e zQ0aSFe!Y*D^#?>mndVeVVX9mq9l`uS)BJcBQhU(W9rk(96mE-0G69MEp1er2#RAF8 zc@G&A&@E53BM-yryoIi^4HN*iRo3kQr)mtf7>4h}_;rxt6rv0-bj@>UBbX8A)F0np zHQ&To+jY}8*4t*?MyrjSR8>{H%owWd@JMi@b23-<I*T)nP4%~>RTr1ibxorQS9*5T z^1793Y7IU+wYiZ+S5sVa0?l`NmCoBf@iF-DRTK59wh>?2h#tGqg3IjiNssmD6m4$A zL)W3TgH<QBmBpu#CH$w<ErSN}g=)*EAb8Gy7?aRs$EvD!Q7pbwrVd;fE?{&mnIg`K zvA#5O_Z-~21&h<dOUAq#1;M{|L~tKBthhyerkY^RFUw;DKJjh2b^9smMuiR559NZk z3s>&usRNW&P#g=IHh<}*Q3vchw64r!$U$e6i%Fs1HI}S46C@N+bMPriI@;nS-kcup zg-5gdXS6QTtJk{X!+g+VN+_$@PB$IY%AZBCc}iTyn;}}tW@@<?Pq+E|$#V@ACM0V| zJG<?(*m#oF&LQrVP%SY}sVa7n3HeOfvj1JL&4~J3n^JmLUVJI+wDLqBuKcM<%2t&A z`|debvuQwI9n#R>)S|W<ntvX{Mb}0hKDDEK)>tY@*RQ(h77^K_p=+XfUN*iEd?2{F zYbkz!uZ&~mB5twT)>YTcZq97FttQ{AeAG612EAhe8c_oGPu{UZ_lpFwhR=$NfPl3P z&Z4?Yk}ZW4(Qm8-CbJ=S2d%EW48n)~YD&{gU#VhPK?5w-#;lZB%k_q?K+_d{yN_Q8 zCyFNP`>0#i8_l`~V}>~kI5tnCR?F-i^vyI)t4`Gfo#i3hRAaWugI1ns5tm{641_$c z<V4HO$MCzHC7>F1kUFt3Hr%>#Xw6+v#%eY!B}ty&tGOZ-v>VjgdfN#y_mDNv$Rwc+ zOU>r)kZsLTzZ0%UMH8{-Z9ThuFfbc0y`&M|3;#1I)H<41%~e*1)-E`oO<!aKdz9kW zX|V>o)X!dDpsfbDxS18Y`Z$XR$UB0#>h4j;S}rvPhxh2TY3@>56Ni%PyYsEQBKil3 z`-i|2Xd?aYn<A{Jdr`eyVwgr(>BYiz(ZVSi${q&n9_vaKTO|ws;gDWYg?n^)ID|o) zT_`stYjK<Yd8)W%Q^S8M{hxY%ZtLQj6^r%10~6U!G5wxz2N+h46`9T%e_4!58H>UP z8SXm5oFHt$3f0z$f}N_Bp(wm}lU(Dl9aQoE2qyzovM#~YrQ`-V&i`23`2-m2`<`OC z9DjrOtF)w#NWl-=q!{J3rX&@8;midik9wtpt!l`kzGV(>mjpL#R7WnrEKP~mt~8r# zdaML`{P_84UUHeK%aXPYmrZ6n>5IS>xRJG~Zd=gMfT8nZjT{V6W^>IZPPK^{0+D)> zOnI=Wm#j1=0D@_d_m1cps+u|ER8h5s+>i2CGviyB<PvaXF(0dzmP0WES=NIwHw@JC z&UH0?);e2r^{*yvS8P=%$23lI8VYBI$DXM#jhHo3(Vc9$)veL2ON@hUk2Sqkggpu- z@ilB~SMPz(HY}eq-$62cE5@o^=iE)S$p47-pp85s=EkO$HCMS!Jwh|>RTg=zOPMIA z@Ho?VINESegVce_IS;gjOQ{`qKX<WlLDrRGA<vu4{MBdGXwVH+@V71bccJ^Cf{U0d z=oisZ3B(z|6Mi)cR?#@xeEF(1wzisz(a0fJ_fi}BAeO;fyJk9xpNfT=@^u$%_%n@` zk@z~9dlVA1Zwo8xY5IsvsY{j#?aLU*zD%2{Jf_&@_=jyfR_J=>5?5U#>;DK#-j%b_ zOC9j@D-R4lD0|!uVf?1)&$whZS#|A}_Q88AdU<7?ya!ut?s6Ob+W&5BCoWv9%=(-5 zUEea*^id1>5R&0t>B`$ca{$mrHhaqyc2i8!R()^?{^k+?w?Ua$mg8hgs%N%t3JNn< zS=p>y`Ime~*@jy?-qGh;-t1*B0hM|6%OH?*T~)(){an@gasL)$Uyn7-c70X2nNxEE zhenHA{o047ydu7m|H8QI){LNBcllz$rQ1>AF>`<o1@JRHbDV==GK6VafDPqq#Ln%i zfm7>gStvFm2H`SfyJ;0n?ZOlzSF|ntS5&a^+r*9f_dmC@6+J%VbQx5u337(AE{QAa zFXJT^2bWArNwEp)Q^0LKi_4o>kaT~qONZ>#B0lOFJjJb@PF!UswUcxI**t5bKbI(L z23^W@!rHMQqZzZ^D^zw{1q#ZthU*ovK>a>y&e6m%WZ_NcgC>}Bew0*o4c1yW$8b}S zPPPNNr-|%^R$Ww)_?-K@EpIsKiZy4`;Y?_A5`M#|a(X6A>@o^Kx-&O9uGC~U0C%-) z%0g!c3-vC225E>{m@<755R~lzO<Q_osU)sj)2niwLc#=MBWsh*jjirROx9I;$L;EA zgD_xo&~nhd033zNu4r{>)=3m5HFvG_Uo?V_a`On2sq`IYe>^>AluDvxj??c8+;d*6 zW}EEgU%)6z^LvJA+N>Y$xgQCCP13GU;g^5Z{<GyS4JBk8OzZ5%_dO|BnjA4q_KQpx zwqFVLU|@WgxYRL|cb+Mx+aykQ(_t@iiY{b*mvYSbb&7g7u;p(IGN7a{lAvO1jxfd< zTA6dj2yP1PIq|gj0l#;71{qq3oAEM!M%U1YT&=Votw;kgV#2ES5;Bn|!7j$Qu58jL zeKylD>NEg_n8<O#ta7-L=tpc)88f)i*SKnMr;MQp)^G^dXGn0?)q6qGgpul<eq`X_ zqo)Xu3*fV+ENwn6%XAV^+mn&}-9Uk-89fP$6n)Bdj-ET#aQW-d31JWv4>hT*3co&+ z(3X@%T1iDq!S8^_EBx<!V>`260%IBw?RMwN{!64z>tc0~xnPLt?mUNK?8Fml2Cncp zGHzi~Ym-L-DXAgf-L*+h#D0xp*z?3`m}zs@Y?Z<n>8g#f*_vy2dsB%8I0vd}-p5>) zP{0`!OOP?QhVROV$NnUr&X0aMEw;G62gah@qwD(<8y>;R(C`0ri>Enx&Zo%Z)*mE8 z`|Yp31V4V|AGJ)f<Aa&wu>8D_EAk&R7W$T!qjH8JkcC+os3wIcqkZt1>m^gZWSPB* zt?TijVA=boD5rHe|JLCdZDpG5T(QBZ(%X5aI9_ee5<|<%LL)#iOx}`*8w56P25z*q zZV7oI>&qSa0W^9<25~02s*cOFUtB+CG^7L>RA<?3=L4?ERDaf3^GS%bkoeJnc~3GQ zRDSE){3t>4T?iTt&*WhpH_<=9pA2-Y!g@_z_yp@%|9uY9Xb4?^$iP$6(UxVO@W5Rm zYpg6?+e$b1%51R1&>V}VD%@DgbiO|dbKJKxOoN;1fQx5c*UR&o@_#W4-C-jm8#dVT zw=-4JXac#8K(xu%G)f@H69`j8w)S6<fzoV~nUColTOfahGjoKGT+KEXwpDx+pQ;tJ z9wkDo4kGkkNg2g&+jk*~YPnc$=A@E&>n$K1{L7AQF8bKhPXx1+UBH(GlOX+QAj9E* zkmit#|CGC>&@i$voQ|h~%)^@MUn?z|4}QD>2pTE5DfVI^YGI?mW1I#y9}rSumiw_% zT}1tvO~Ns|cw1LBg_VXLUQ5`ixD0wIh*F=8ZmL1-vKM#qQXFdF<NR{2nnbP#doDvb zAle+&`m)*BSE@tc^s2<V8duka4g%Bcg>FO*YKJMd<sMh-pq|<)d%R?9o}KxQ6}q*V zA4P~JiElpdQBtR|VFe0}$y%Ooav1fh^C6t`u$VP}0Hv$O0+R@Iwg^ud2E!4Z@lmSU z<M+uLj#KdUJNSr}Zke$g$yv@h5yy?hmqUp3^R^uZ64RXLMF@SpkV%R1yc49O=0}Z4 z$2TNcuain<2vIlFJo~N;y3PF|KCIEkK6L7sg@3+F78BKuju<8Fd*2j!8hBNr4_e`m zJkIl$nR-JT+M2f>ClLe*3JPTsbj6C9oeWUr^Ft>|I4cBW4mIp7qCiAzu&9CfUVQ*O z#tVrii2Ek7Iei<yG8uS5s$<{~MM-`UuyMDN4X?W$k`<gG-|{Xk5kLnl+o`LldA?}4 z+OmZZWe?2Oz5WYaEfVj2RJ=5Ng^F?_wCw8JXdbmTUwccDt5Mj|s0ow)-Tl*q6PeGP zD-7U4I1Cj8IHMw_l)8xbUd)l~%=^>RRH29;JV6;2q~~#uwY-_PS~!%!dNH#?`534q z*%2nJcg61`?B2Z4AEYj={U>H0sZI9<Py8U&T4vU{N-SRZ;rurvsTLx8Fh<J5B>?Wa zy3&h9+?SH!kP;1H8Ia<=sXLz9Mr0%s8r5&l(733x^Y6>(Zx(I!zB?*HP))OMl)@T8 zO!(DEbw?OCAHC*;4Qb?td`DWcmQ`4zrQQog0}Lut3K?(;&n%G}TT7`+@(WMi5YhC| zOTy!q{82{t<qveqzaP0Z>2Odw28avN&h`1(dE*y>$DVc_i0iMzu-`{ljXP23?_LiO z#+s-&_@`{RGY?_?e73RsIZq%KqD{)@W4*7fC1ki@Bt`HL{O9tjoTo+NglE*8Q!RXG zR1kHzvrz|jri?9~1xo6)2G)6<0j5aPs*kmLmfyIF8u-Y<?Qc%@wOP9Ai3_zu@Ws+E z|40aJi}Euc=12hTS0%r$rI~u7(qJ3q0rPcQp0~wksG#vy-KH^r{G8L6qFi_{{_)xW z@f9LNLP)Ph`wn)`|0<xQsC$6gnT@;dc6-azcp&1#Nt4jE`+SgcnwuL=NwN+9uXjt| zy-sPDo3e`J58aKp+H|!gSNxk*jgP&g_p&S9=%e%0zu?b1NTgQge`~SdxPJa41M%ZG zCdZHOAkmbmTWbSaKhSz3sKdfy2lWO-`=piP0^Gni7E2q^nw*vaoQzYR$aB2#K{4=q zz8hJ|$+mmoK2B9p&f^s6Me+mFs7)JNv9`MRQ%s@ezPirbgM`HndYKRCUl+RoEod3v z(w^UM=Y1#x(;dPPD)a7J(B0Qz#6M=r5g$NpyJ|FtxfC#ntv94>oZ&^{elx<aTh`m( zXV@@<wi1S09jQjr&Y)glISc~bp-o$sdB_rNu<Bmpg*C$-4spf1au1)`-FCQR>wJPG zLbg@(Ad6W<A=|HY>HkrEr&~C3{KlV1;2;F`DDZ6x4y)4CjF)Kwqj&SfFuBDejA(JB zJS!!CThZ9tym5Im(8?=k$unyV!@hJvU-A_%?EYRdrVV=T2V*Mvb5Fi4lI<mhiov8O zE1X3%CD~4FNwhFIZKCoDp)jdir}@w?dDt-r$DA7ot>INZ@7GFf&pgtJ{Pf75UocJk zXc@NACZ{EoJBrPoZQk9@xVL(aj0!Xd<l_ZfN-z<T?zv+d^@~|Sv>I9dlJjYg;tlGY zj+nuQ=nFbHR^hR@KGVg+u*99f*g4F1e@rHE4-;?gye<mz^r2EuIv`EP2j=nsl3}RW z#jOW%^pxJ#RykzQ3z-K#wbFpf`f<#Onty~saPpLu?4t<AasAcFCw${_Lf%-s0eGs^ zBWO=cBd!WOjiH=QMRA`a=|6m??o2sv&ZGzDG`*+&_*iBrMHBYiARgx;+zcd6@QJln zE|)8f1`R{iV$`5>*<zX_W|Gyb?rkIslVeczhW>*S{$b_zkUS)s4mrQCnTs1An3V=} zO{S2M$uG#1@Hs7sAQb$TN3r3W7?64Qh}N}#x2lX`%V@Y33TG&(o;}PZZ>^gX3ZS(% zmfs(Zuy%1rap7-rojJE%tp&b?2gW6Q4ij{|&WpLWB#3M)==$jO#?zw9q13>Hhk0!y zq&w{Om1kz1jzK*rJl1^qv4J6G+%R4wv8om@kT6urp$+bV)is)i!ktcvkNb2`6C3aC zh?^@frtilD{;X=NcNs25!+ifZv4f%ytD-^?D7z7_jiz~wLGdEXh{q8ZOvgdv9Q#n| ziP!OE`j~EmaKj-<ioJ4B?Uj4QT3!a2UH6N%Qyk(QJEKfVFKj5TQKS(&*?G>Who5Pc zjlCwuKCkZHb9B7Db&O2If786kfx#EF2RY`D+R-ZEEJtjLmoZI`c938<YXEolKQ_LR zwlT{t6<Kk8^3AkF+%1Y6(sKRTU3AS;ioBU#O`r+4jxmjh9McAcu1YSy#g;e{Hu9A8 zX0Lo`GX=wBP&K(*(J?d86p!RYqf(WRXoo<E^*kVK>oJQQGf(&g!0p3)GDign($=Y* zrs}V^y<XG(_*HI*_&`N_fAMg@YOdv`v(y5iP9F9^_ZB<?CrEGzh^%E+CuNzMHVP8v z2biD>y{#kPXQQfyO_)kp-`gt;=YyCe1845%QizfTk2Df`2w)h`uH`C3F*~G`)qy15 z&MsE-v692;5NS?}r-Zx=zxp#p3B<omb!xb<=OkQrI<+OVLmg4nVCVM#jyarR16Ddz ze>MI)8UB?UPM5o*oz%%X?{}HtfLxxiX);(Sr?i_{<DRC+G55#^t-ha3s1#91E>P}8 zuV1V=@e?x(=QDd;;?CwptWsg^sLzfS6qxHbt#@nk=ellvyO4QMS3UACq$(lDF><g9 zCxa@#ctSqE1?|Cb<aireio3oM>!&eYVA}meKZ4nL#tsH-G`?g;b@oF7+MT=b1ltPH z^VDN(dC8}YhFJ`@FExFH##}m3+KstPJ|k88SSs@=VgLEfj67FGn@b2rCCbr*M&Fgv zlI(=d3QY8TE8_6>A4$XjSG{N9;jVwb<z+4B(mOqn^vmvMR206z+VCyYQFQsY%(4Af zHGpp$Qq`>(6u6*_a#?=~<yZ)><?&3%jtoE=W8^P`)1T}8vV1K=OB)0Eg6%IXlu%_^ z3gX{K4(FV00Z&R3BScYCdnaKO$`$UBOP$|`;eKCij|OK0(v0bQ(ZfZ1$VFwb>&S!q z`m)b|BL9XZdH8xC3SaMfTcaN*`sP|#U3NOZxDJD?<qAfe{`2tI!Box1Z;HP&bOgt5 z^L$ZN&G&w^s!N1x{2^t18A|QMA<0DPyF4rHDlYH4^Yr@OnDAJ&<=NEn{8Tpv#?bvz zR8Yg=e3nMaZlJA@W(oFC5`9#*M{$X{u$Ai!xUeuusVt86Pb*sZw2Bx`*<~*64h)@E z&@Go!q-zF2yK_MC`1Zyf0>&NWRh2k-I+#W&jhMl2C$zp>)c1*}>|DtNe)1b<Fy@$8 z4J7qg12)3ei4c7CO=xcA@xL>__%U`&d_mMR?YdE{<1a7<)j?nX87OBN7GG*BlWs;C z#G*OD*edsQSvxiKj5}3`$BkzY(k3qiP-XmZ3Au8qpx?w@6Aoh@Q%je~o%u9sZb(3S zI5+?L=bw!Y3_hHQC$=9GDj)593nKpTA){YVT(K0EV|A>{r|+wr5%jymSOph2`Yl{( zq}&?M3C;*|+Mk9#K@<fVXx_tk!-%4W^lhA|ocOTi{H3(#T>^F}xoSUre*QuE))_T` zLob7D{e8~nc1;Ka3+n_GX|vcaj{lv1{_@Cje61kY|CumT25jjqv8caXk_YNSWnTx| zYS;m`eZJ`}gnio8hw_7rZ{6<pxSd#)Ztf*l#&pqtX}hPNaz+F1#NEf3-U8cegPye= zj*)~U3J(AuSiXjrg3K#7D_y;Jv4>?Tp}aU@AyTcFb256K7Nq<{>$4LHx=INuG2$t7 zAzk4O%dm0VPg<&`SvgIcxgMGFPl&c#m9}`ND0({|b*SqxW7Ma8-op&_4)v!H^+{o( zf6=;u0$&%0xLG*!h3<k@)RKpwA8TnPL62^;Kl$<&a?ZFlofEXcn}s{x4&<Q31LM~E z0U4YDLcNPZnS=4N%+gvdWL<w#ZsOO1aZ{1RX0&;=V?$SfTBpE|J8Z3A-};XQTE^XB zb<SO3)SN%QcaVp!2ElCR^r!5%_!y0IYzw$c<@mFMc9BbAw+4P<_%O3ZyNW$YvlNB= z0Zhi`lC@X1<L+mXR=hnqE@O<yWiIGqLg<0m7j_HvDa4dw`&=P;$%S3v(wkuecfqi) zO>-wA1mLP8Rk3CIU@7J_xrc=J)mH*_7lo-EJ%tA`ma2);YgxVi+hfO!l<}_CG&^2I zCNAbKs<iOiWK_V;#iF!m7Js-jml_&#w=V*J-uTQ-OyTgs#FZ;aahDhxcg;uZ*h5Xq zyu(6B;w)WzhMs}E6G^9XsS#>kLEvXrT1=0xvN!Co8?BJ@Q2}~~d-vNhpY<hXzGow9 zpTuN2B{W*cjhZMk)XR4UH2EK|CUk7o`YP?A7Tb`P(fk2ca7;liMtu6?+^R&Hs3n!& zmpE%yhgZ1DOlinVq;RjpoP$kurX9!F7EInKTtYCE%O`*UD#sw~M%|6pIiy7`GX-|A zT}S(^dK!a1jt7%sCe;PhJx*a6V8scQXf@nUFR>A!50*k%B*6!g5p{AF=NJaqG{a4E z28h7fDnGFQj=n`M3fvhsC8T{}%3iatEMO&HaN$F7FF|)NP3~DFCEoNFkWQofVvoY` zLZ+=^qcwalesq5w+OY*?#rJHngF{z?v2FzPtSpYI1%|F!_20%q^$Ff@zKlHZ3ZGKM z!07ow6pShren)_4lD~k{pOJqe@AeQ9WyNXV$&|GmmTman8#l=Nr@R1g@1=kFe`0yx zY@O1gzPIU*+quQT-DByK<B4PkV*J%uqx-Ljnz1pC*(OKC{hKR$Dn;n0&`Py&QwT1J zSO2b=iJCH%cJW(d|Cp#IX;QNkBk^uuA(@kf_u&-y3$XPo3NK|?yM5WU(IL;KY{3OA zUjs;d_h>E!GZSw?kP4?o7S8F2Prg}Dt-fG>37Wio2qwxEOLL~b@a%2>Ql^fCBj*Ik zq{)4rnm)J?LXa?FkZ|}Obb{+1iGxh|406%Unt8s*B!|kMAf;`eUin$$;&)8h2KubK zgii@uzXl4e6pq!%!VKQ1%-Zpa{abrcj#nJs_;G?399@}H;3ofN=5V!!1ho)`S{mV@ zu^<&@Tsv>C3o>d%;)1Dbp=xaJ4nN;Agx}nM)}x*tE7IB)5>z$0VC(gEP^7hy@COX+ zn$pP<{a{zXXg!s)D_(J&p{`KE?*esO8`^{dd{TA*^{*(aiRKP*`Rh7ENs^FE7TnF^ z{YtHoF`YuEgryNtO!K_&jYFsYcs9erssgNBoKpj>%FS4M(d?duYP|+ixcMAX52Glu zvwTtLr4c6_C#Yj}?wiQOC1EtS=K44IQxuC;KlSyLqMim#6T#Sh#Q>~yZm{C$^@0iP zVX*RxsQzD`i}br|G#8lsjR`ao9+BfKJw4@17{U6v58zdh_`UQungj3G7X(@RbnB0n z;|?#fGAzsDZvJzE3ZJZ_o=%%DV(ct~-__)ZrM^kQ&qi@;|C-H$%Vzp@ctk|pB*^?Y zKof@`XGV$y*~u6J^n?!5J1Y*q{4}M)Z=5iSp0`(yXCzO<UtJo%8tUc;TE=6P-xOy& zzX}m%=uY?}jSQ!=JGOkam65wn;&_dv9HCqXCK}A?T~OLA9;Zh^%maRr(EF@L-Iu(2 z)NK2v@kFrevzU$-25QLubhjS8Dhk&)14ySU^n<IvJi5%^dlrIq`xjI_qC%0IoFBop z!llggaDEe^sHZHkH|>)0S_A6wXa5av1(BzDx@ZHyK1ISB#C?i*B~Y>X(^{=^`~<&O zj_ox8k||{NL$a?72e}zuDmIKLdNDT{i5nRGwIVCv=k9VW&;$W3-a)F+&!D67qxb*7 z1SRhJ3kpw=*SJpR;``h2*&E@TZEPaAaCl4<);5N0>E9Hq^a}uNY{|WmCKcvd!jv78 zf*H6Gn$D0`y(g)dYD_VIV~=6f*XBjq7-GWiY^sq3zu(KoNbk?Ei=SyQ+?8tr-r4u~ zka1l%Uo!Nex?|m>=%t?G@B#)#%ijgP1c2UIxDbh_3MhcTwghKCafseL*(Mxm@w#NJ zpA1S1X^6Apo&>p`6ZK79sQy^7IkU^b_ZX@cTI!%7B;P;}5f15)&f=1FQwh1!=vdYu z_3efly0gclp7O^_Bl{;XxIUaAv_|8mc9Qsd))x?<QGS5Zy#(I3cwSU%dl5>_Bg;ZC zL6!jOg>$d<FHbw1?(7!aM69AV+y69m)a>sGJ6`$gTmi6Qd=6KHe{56U*{EyVeFY++ zMz(j=%;D#UcxavMGh~#9C-RQ%h=$!rMoi;vVmDnDH!NCE#)NnC!;D`hsz}Kogs%=u z0H()oF+xkY-dB}IhEfY<ar*5QNopx~CMeTj;hLI3My)L&8T~)Z)8bW;(yrbE-=i`Y zKbbrNbq5}wiHS?I_G@eOf0{qvV(F6YA7wwYwtA7cP32K3;X3mL|H5h>KRWHl!euGY zrEwKnKyK%oYLI`o5xqNX><7H}ka{kGn`L+>>qqo$SVYJmGJ(;6lj|Q@nO48g0PZtJ zeN$odJ2W~~3<-2P{Y`EZm}h%tJjF2a%O?3snuJKhIE1SqsVglCB9%1l8rNF8AzAoY zO@LRnnRBz%NbCf|;fN!L)v&8G#ui>+c4Dy_P@xe0v6ki}Y4<h7-dR0zf0c*fU(mkq zMB3cb?c=O4*{_zrCx+krfn{ynf-X#EkqDvZw8q`QXKhN0OvqAV2<G4>ic{famm}KH zijVe&`400-eEdsz{Y}IX*WPWLoZ07k)GLCfvyCJ*CoDxrmfTW_D{_Ys2pp^w<hF-y z4pKr=w>3*YuoGcn5NB)hnh+lHqJKkh?Y{SD4%;Ac_JI83hd1p{q3`hN)$|z#tH|MC zIg4C&$cW=o1fB!N(ZbZguZFd!y``6^u0m744Rdff3|VwIT*E3bCOFMw81izNBN6Op zvP8_qpst=vR$BYnnYeGroS;dWpoL(Yjxw3-q9BIhL@10w#dl3*Sz?2^3j@S-e_LJ@ zaaod4HBc1y&{8BnQ<n_r?zEvOrt<Ce!ZJ;pEZvwsVC3{j+H=w(S$ZSNVcUK+DhI?` z!-eppKnzt-xk|O1{vC?Vt9~2BmJXpXJ#t)QRn0?IJFb+*Q2`uJiR0r~1TZ*bnBWnb zRDE`BTYs}N(lUf;PWWT(l!6)2qXzOFoSpLWK;4Dv_^Y62cV)d?UOX92;o!dr-YogO zdy*A>5SBH<9QYY@gDE2*F(tHd41E-u{9-)a^=lrx4>D0(V!EXFL#Na>u>@&%g~Ct3 z-=sFuB(t^VlPNC!0naGuAt_HOk*Php<W5{JZBlU6G*8Z!-ya)8I9h8*4J#$q^al7; zR~~g<6gR_z&Nnx5Kn_@}&qw=P>*{9oP(!1PSN>*7XQz*oIhC*2mbUBs+&AQ9{Dwb5 zmQpmAqqDT0aw1>EhW}?UhK}{KUe7jKf-l{(&Gq)v8(fJVa0x_yt)z)^M;_Ux=}9g} zu<MxQ7R!ZA94>8|%dvD<6aQcG4#)z6Z4$Hf&b<K~zljtblR1E@-529UgfvuX0SiC+ zgWYg5End^0oox<g<{U^0xw6e*e}(@@ijD-_QS1Jkkhw+sPmUJ*hx9OpshVXzOwIpL zb`-x3++qyrL(VaisWTHEs2b|X+p=k(*Z-~jK8PtnMQQ?+8Es{z*S2SKrWi?trWCvr zV8-smg`fjU6U7#QtNvkJ8~m1mZ|)nZ<N%LQqfa$Y$%UJY!>4f*fe#>o!N*J{9b*wR z_$$s4=^~&oyPy}#%+Tca?g=!p$~7}7t4OL1%`!auyXA_nPDFljy06HVU0yi3LVcxj zoP8&W3Z=>TH@S^`;J-VanDWF1)XfJ(_FAT3gBQTN5*-<aas=0n3b<e}o>VSL{24J! zPBdE&mN^~(lg??!(2c;46Z}$ZdZ88WG>*7Qw)*EJu!VGC8vU7KI(GY2`CxDliu9$L z=B>n|PxrBmXf}g8sSz>(1nvu+3K3jTDN-QPrUD4d5(L<7<ESs^K!T#AJs7<c!GFSS z*FXy!p90>iI;L5V9MXwHcSA%x4_crU;Cxxk13XNIOZ`d6i4_-PGHyiqOn!|+L10<M zie{NW{{l3KrfPxqbK1IkjqcZ*rh)k48LSa+(HKlt1;Ug`<bAj8w!f>eESoTp3f;6w zT7jCPx#uR=VC{q-&8v<LqQ8K3>q6(1z&3#)&IKwh^eMaA-e3;HEr8xzYOgyCxyl4| zATat|E<Rj+M_OStYnbHlr{tv{>TVxIoL`}6BVH&bK=UKOv%0Izok&2cEtP{=!pan6 zx2pd03CMmRjNp=G<^u=<==NyIDmYE?D_#7se7F5Lwf`y*+O&s769vD%L`YY6#5hq^ z%1@!+l=utZ28FwiQ11I{D4Q@Y*Q6fJt&L@x1HYW-#z}7z_;DYgEG33gWs<&3!gAye zU$taZcT6WfIFQ;#8E2yYqfvw!#e!kXmkY-Z#S4I3#kODSdxyFSwHgXBg`H|H7U)sO z!KfA(I^TCn{`V8Pz)mlW1Usu2O$)NrcPI=jwm>x-!mBq{{DKbEihwJA52L8(B(<;G z>~#p))Qp)|c-3*m=b{rnS8+^jVDFFNk1Q9xPc3eW0FJ3x64W;oiyRRfs7wY27hr_5 z!)1@#MMG+DQC3maA<xBvGLaqgs1CX%$Bh#P0&Rw>aK0eelu|d*XZmYE`9Z-C$wg|R zfftGWILat}qvZ+B9umYDuk*S$b!i;l89yndb)o&8GJe>Fpd^~YoWsyo8H+<Bg*K~& z(&=vjxblR~FHd`;UQ=kt^@_X-K|$~zYz*~i9uUb{;;31*c2cU63E0^7rK|XQdKwBS zu#6?(<K$k~oBwYe!j`XrOi2jh86~C?W{cJz0+(1O=30he%En407L=y*MZ2GzG{{jg z;$=<}0^(WdyV|p}ktCYY<K_t|r%%MgT$pUN{N1yJO%(7~O;>#7K@58O^A?R9sEU$v zBn{;mQO$42N=W?s0o-ucLZRlrt(np}=-}stLAcHuXR2LXF8xD3sNyM4529otq8=A9 z23#3`Mh$S`;$m6)2J|;6DJm<XvGm?-traZg9HXzZ8tfh3K=7A=$J<`~xh)5m=_Q)_ z1mw)ZA;#DJi-E+XT8#<7<LC{2d=Bqas_nq_VZs!4-S<^=F_V2;dj1bB%I8h6>j0!e zm$p^fi8+&s3avNb0kX_ApI~@Kq3(fdhM+Jx+~-N?U4f4?oBZeHo6y`0*3q!k0P}2& zUae;rn##~z3_rhbK|x1P%l=&-bSy^g{w2Qt#l`tAjC`(&hu%YO-o9wq9+)t_bUu&1 z>qoV7!qB@hdKuUcS(nr0G2_o##07k#D5o>>x6$7LkhE{J@4!AaEpNIr@rRv{^ARw> zzo@ZL{jUh!ppHe;9CeWL3A%QkJ!nSrJ|OWgsoTA-9>7mRct|`lmbZOhFRD63)VKA8 zXlzbY3CFJ!PsHueCiLvU)k&|FS=Zq+F~S^NPXNw*kE0+w&^<eP0bR(!^BcbMVLnd* ztLIe;)XC8v_6H|16p!!|Cj3l3fiYlsh8{{BS1BedNG~Z=v(sDPyAK{TLH(tVIVtaB zfRB<^^`##O-*y;@<K`EU2)|d~>7yEy=pBCX_q1K;zI{$0keD#Nz38}TK7$9MKBLEv zW^tX3?9&pSmTyc34Ah48%Hu5}46+2>2LF?|#@{|C)Go{LIs9eQLCQspA$NBH;1jhY zIsPH}!1=ffD_7GJP_D5C&vm>mO4`aJ1P8HYH)te>Yj3?tr)@GQ{F5xFd*>(FjY7AW zLt~dBzWSavKP6=<CS2z~`ocq<FT2_nkVlJyhG{!q3K4#vzVk=5Z`c*GFp#T}mo`{D zpI%Zc#+%>kDet|AsR9pu9wWiZ{Q8%7FNB#vCnF4)U0X0~r&SN|W4Tby0KD!kaX7R^ z>D4gU-dj(?|D^j-V1|6=r3=FmxjK(=Fc$to>~6yi*woi4DgXMOQHTIDM&JHNh{k#C zQ*(^=H||FgBl`qHFWZ>=vJ!*c>WcS)reblO+?M;4?<;h9H=+ET%jqeH&*Qi0$DDKi zZ|GeL*Uc!vFs(`4$v1=9#FG^lX~%o~kAoY*RDCW8XY!BH`seYza`is`QRfwa(vDTj zdU#+!MJye7_Z?CO{lLzeUF#gCIMnhK<W@TP0)q_<<jY_plxoyvV<2)F@8iE7Xw-yW z-+tm;=sdCL<obj@Nat{r;?i@Wlqdgl5If^H4V|H7Uf+7=U7VS~%NKA0T=lqAS_`97 z=s;>kt-uGelRM3T+?3VsttCM=;fezyiryb6=3~PVa@lsQpF(u_guGFHbtMT$zz$wV zx>m!8CwNqx1SU*I;5{?$x`b*~JMC4M)x`SWeuADt3bh$`?19{B_YSMr3?(DV#$L3B zwl3r4r`?A^0ck%m2VE0{VZ!;K5>W554}tHsWQPf9O!3?gAhU8`5nZ{20woN`b|UpZ zBZ3X0=3m9D>PFfOq_N-gQ?AmkIUo|%a8p(li?9N=`F9d#`r#CHMchip8%@83kyU=; zk6a)(@Xl_7;(%^GLHTyMS14stDQOJ?kjLxe2x1A>9S|LAxC<p9!t^0}pAlF7k2Ta7 zB>t=6=BO9T&)&gOS?R9jXTKj&O*g$8pva)g)bt2_a9Z(6kUj^XH-3)#(WmqfooQt` zf@IR~=c1Eco+tZ+mC*i;!w%YoaY7RzeFh>F{*-g#0{MWL(QgPeJ6?1k!6Fj&`UN~M z6;?>(zp+S;9;P4o<CR3KA<e)_OdxY%Bzcqp?XlTs_FJQa(NJ?&Zba)<f(33%2kPw$ zc)I;vjJ-h-ATeQ~phM{6pb1ImPIZrdyu?X;@G~k%{$y!(<R>nn_EsNVbB838jD%<J zkUZyC9fJag#Z>fwo|_m!xU5Pq{}*0{>NLkb2Smdf?g@s~Ei+cz$uu%7%Mc*NZGHo- zKie;NezToqsxJO7LnP43%T|pGsPsx2gg(<x=EtpHPM;+slzZ19#wo;KzkjXs|7Xkp bp6<)O)!#bbZU4UwCE~x<{ypa4pfUU}Q+s^p literal 0 HcmV?d00001 -- GitLab