الخطأ المعياري:
هو التباين المتوقع وجوده عن طريق الصدفة بين المتوسطات، ويسمى أحيانا بخطأ المعاينة، وإذا عرف متوسط مجتمع إحصائي ما يمكن حساب الخطأ المعياري بتطبيق القانون التالي:
الخطأ المعياري =عن-1![](data:image/png;base64,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)
(ع): الانحراف المعياري، (ن): عدد أفراد العينة.
فإذا كانت العينة كبيرة كانت قيمة الخطأ المعياري أقل وهذا هو المطلوب في الدراسة.
الفرض الصفري:
هو الذي يشير إلى عدم وجود فروق أو علاقات بين القيم المستخلصة من المجتمعات البارميرات)، بينما تشير الفروق أو العلاقات بين القيم المستخلصة من العينات بخطأ المعاينة.
اختبارات المعنوية:
اختبار المعنوية، هو الذي يفيد في تقرير قبول الباحث للفرض الصفري أم رفضه؛ ليتسنى له تحديد حالة الفرق في المجتمع الأصلي للدراسة حقيقية أم أنها ناتجة عن خطأ المعاينة.
مستويات الدلالة:
وهي تشير إلى حالة الفروق بين المتوسطات من حيث كونها حقيقية أم أنها راجعة إلى الصدفة، وبالتالي موقف الباحث العلمي والذي يتمثل في قبول الفرض الصفري أم رفضه. وهناك أربع احتمالات يعتمد عليها الباحث في تقرير موقفه.
- إذا كانت الفرضية الصفرية صحيحة، وجاءت نتائج البحث تشير بصحتها، فإن الباحث قد اتخذ قرارا صائبة بذلك.
- وإذا كانت الفرضية الصفرية خاطئة، وجاءت نتائج البحث تشير بخطئها، فإن الباحث قد اتخذ قرارا صائبا بذلك.
- وإذا كانت الفرضية الصفرية صحيحة، ولكن نتائج البحث تشير بخطئها، فإن القرار الذي يتخذه الباحث في هذه الحالة يكون خاطئا.
- وإذا كانت الفرضية الصفرية خاطئة، وجاءت نتائج البحث تشير بصحتها، فإن قرار الباحث يكون خاطئا في هذه الحالة.
ومستويات الدلالة الثلاثة، هي:
- - دال عند 0.05 أي مستوى الثقة 95٪ والشك 5٪.
- - دال عند 0.01 أي مستوى الثقة 99٪ والشك 1٪.
- - دال عند 0.001 أي مستوى الثقة 99.9 ٪ والشك 0 و 1٪ .
الاختبارات ذات الطرف أو الطرفين:
يقصد بالاختبار ذي الطرف الواحد أن الفرق يمكن أن يحدث في ذلك الطرف، بينما يقصد بالاختبار ذي الطرفين أن الفرق يمكن أن يحدث في أي من الطرفين. ومعظم اختبارات المعنوية ذات طرفين أو ذيلين.
درجات الحرية:
وهي عدد الدرجات التي يمكن أن تتغير حول قيمة ثابتة أو مقياس معين للمجتمع الأصلي. وتستخدم درجات الحرية في الغالب كمفتاح لاستخدام الجداول الإحصائية؛ التحديد مدى وجود دلالة إحصائية للنتيجة المستخرجة من الاختبار الإحصائي، وبالتالي يقبل الباحث الفرض الذي تبناه أو يرفضه.
اختبار (ت):
وهو الاختبار الذي يستخدم لتحديد فيما إذا كان هناك فرق جوهري بين متوسطين اثنين أو نسبتين أو معاملين ارتباط أم لا؛ بغية الحصول على مستوى الدلالة الإحصائية للفرق. وقانون اختبار (ت) لعينه واحدة، هو:
![](data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/4RD6RXhpZgAATU0AKgAAAAgABAE7AAIAAAAQAAAISodpAAQAAAABAAAIWpydAAEAAAAgAAAQ0uocAAcAAAgMAAAAPgAAAAAc6gAAAAgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAE1vc2FiIEVscmFtbGF3aQAABZADAAIAAAAUAAAQqJAEAAIAAAAUAAAQvJKRAAIAAAADNDAAAJKSAAIAAAADNDAAAOocAAcAAAgMAAAInAAAAAAc6gAAAAgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADIwMjE6MDI6MDIgMTU6NDQ6NTgAMjAyMTowMjowMiAxNTo0NDo1OAAAAE0AbwBzAGEAYgAgAEUAbAByAGEAbQBsAGEAdwBpAAAA/+ELImh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8APD94cGFja2V0IGJlZ2luPSfvu78nIGlkPSdXNU0wTXBDZWhpSHpyZVN6TlRjemtjOWQnPz4NCjx4OnhtcG1ldGEgeG1sbnM6eD0iYWRvYmU6bnM6bWV0YS8iPjxyZGY6UkRGIHhtbG5zOnJkZj0iaHR0cDovL3d3dy53My5vcmcvMTk5OS8wMi8yMi1yZGYtc3ludGF4LW5zIyI+PHJkZjpEZXNjcmlwdGlvbiByZGY6YWJvdXQ9InV1aWQ6ZmFmNWJkZDUtYmEzZC0xMWRhLWFkMzEtZDMzZDc1MTgyZjFiIiB4bWxuczpkYz0iaHR0cDovL3B1cmwub3JnL2RjL2VsZW1lbnRzLzEuMS8iLz48cmRmOkRlc2NyaXB0aW9uIHJkZjphYm91dD0idXVpZDpmYWY1YmRkNS1iYTNkLTExZGEtYWQzMS1kMzNkNzUxODJmMWIiIHhtbG5zOnhtcD0iaHR0cDovL25zLmFkb2JlLmNvbS94YXAvMS4wLyI+PHhtcDpDcmVhdGVEYXRlPjIwMjEtMDItMDJUMTU6NDQ6NTguMzk5PC94bXA6Q3JlYXRlRGF0ZT48L3JkZjpEZXNjcmlwdGlvbj48cmRmOkRlc2NyaXB0aW9uIHJkZjphYm91dD0idXVpZDpmYWY1YmRkNS1iYTNkLTExZGEtYWQzMS1kMzNkNzUxODJmMWIiIHhtbG5zOmRjPSJodHRwOi8vcHVybC5vcmcvZGMvZWxlbWVudHMvMS4xLyI+PGRjOmNyZWF0b3I+PHJkZjpTZXEgeG1sbnM6cmRmPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5LzAyLzIyLXJkZi1zeW50YXgtbnMjIj48cmRmOmxpPk1vc2FiIEVscmFtbGF3aTwvcmRmOmxpPjwvcmRmOlNlcT4NCgkJCTwvZGM6Y3JlYXRvcj48L3JkZjpEZXNjcmlwdGlvbj48L3JkZjpSREY+PC94OnhtcG1ldGE+DQogICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgCiAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAKICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIAogICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgCiAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAKICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIAogICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgCiAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAKICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIAogICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgCiAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAKICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIAogICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgCiAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAKICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIAogICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgCiAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAKICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIAogICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgCiAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAKICAgICAgICAgICAgICAgICAgICAgICAgICAgIDw/eHBhY2tldCBlbmQ9J3cnPz7/2wBDAAcFBQYFBAcGBQYIBwcIChELCgkJChUPEAwRGBUaGRgVGBcbHichGx0lHRcYIi4iJSgpKywrGiAvMy8qMicqKyr/2wBDAQcICAoJChQLCxQqHBgcKioqKioqKioqKioqKioqKioqKioqKioqKioqKioqKioqKioqKioqKioqKioqKioqKir/wAARCAGxAX4DASIAAhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEAAwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD6RooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooqC7vLewt2uLyaOCFfvSSMFUfUmgCeikVg6hlIIIyCO9LQAUUUUAFFBOKM0AFFAOaKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDP1nVoNGshc3TBYzKke5jgAscZJPQVR8S6zDZ+HLu4t4V1GRI8rbRkO0h9h3+la95Z29/ayW15Ck8Eg2vHIuVYehFYX/Cu/CH/AELemf8AgMtAFb4ea9qWuaPdf21A0VzbXJjBZAhdCqupKgnBwwBHtWn4o8Qx+G9Fkv5ESQr91HmSIMfTcxA7Vc0rRtO0S2a30iygs4WbeY4ECqW9cD6Vm6xp/wBq8U6TJLbie2WG4SQOuVUnyypx+BH40AXfD2u2fiTQrbVNNkEkFwu4YOdp6EH3B4rTqG1tLeytxDaQpDEpJCRrgD8KmoA5X4g2N1qHh9IrLRpdYkEyt9niuxbkDB+bcSPy96890zw3rUerWjy/D69gRZ0LStryOIwGGW27+cdcd69sooAzdT1e20i3ge8kWJZpkhVnbADMcDJrKa71LT31C9m1e11C3WN3t7NEVGz1Vd2eeOK372wtdStHtb+3juIJBhopVDK31BrD/wCFd+EP+hb03/wGWgDa0y+TUtKtb6JSqXESyqG6gEZq1TIYY7eFIoUVI0UKqqMAAdqfQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAMmkEMLSEMwUE4UZJ+g71yx+IemA4Nlqn/AIAyf4V1ZAIwRmsY+DPDJJJ8P6YSf+nRP8KAM3/hYel/8+Wqf+AMn+FH/Cw9L/58tU/8AZP8K0f+EL8Mf9C9pn/gIn+FH/CF+GP+he0z/wABE/woAzv+Fh6X/wA+Wqf+AMn+FH/Cw9L/AOfLVP8AwBk/wrR/4Qvwx/0L2mf+Aif4Uf8ACF+GP+he0z/wET/CgDO/4WJpf/Pnqn/gDJ/hR/wsLS/+fHVf/ACT/CoL74a+HLjxHZagukWiRQxsssKQqqOcgqSoGDjLfnWuPB3hc9NA0v8A8BE/woAz/wDhYel/8+Wq/wDgBJ/hR/wsPS/+fLVf/ACT/CtH/hDfDH/Qv6Z/4CJ/hR/whnhj/oXtM/8AARP8KAGad4usdR1CKzWC8tpZkZ4vtVs8QkA67Sw5POcVvVzniPRQ+hxNosKRXWmOLizSMbQGUHKADoGUsv8AwKtbSNSi1fSbe+tzmOZAw9j3FAC6nqdtpNhJd3j7IkxnAySScAAdyTxiraNuUH1rl70DX/GUFiPms9JK3NwOzTf8s1/D731ArqR0oAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigCC+aNLGdpiVjWNixU4IGOx7VxHhrwDHHdrrM2q6viUiWGz/tKZokXqMgsdxOcnPHtXcXdtHeWcttMMxzIUYeoIwa5PR/DPifRTHaQeJY7nTIjiKO6tQ0qIOi7wRnA4yQaAIPiDYTaoILa01e50mSKNppbuG6eJYUyBkqpAYk8DdkDmquiSeL9P0BdOt9KluZZFITU7zUxNyRw+CMkd9orc8SeF73U7631HR9UOn3sUbQyb4llinjOCVdD15HBGMZPrWrotrqVrZhNXu4LmUcAwQ+UoHpjJoAw/Amj65pEV/Hr83m+bKrxk3LTZODuILcqDxhe3NVZdUi8E6lqVtcAm0uka8sUH8UuQGhHuWK4Hua7iqOoaNYarJavf20c5tJhPAXH3HHRh780AU/C+lyaZo6m7Ia9uWM904/ikbk/gOgrao6UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAVk6rpN9fzI9nrl5pqquClukTBvc70Y/lWtRQBzf/CNax/0OOq/9+bX/wCNUf8ACNax/wBDjqv/AH5tf/jVdJRQBzR8OauOvjLVf+/Nr/8AGqP+Eb1c/wDM46t/35tf/jVRS3E2pfEg6e8jR2mm2aXIjBx5sjswBPqAF/M0aZc39r8RtX067maa0ubeG8tQ3/LI8xug9soG/wCBGgCb/hGtX/6HHVv+/Nr/APGqP+Ea1f8A6HHVv+/Nr/8AGq27m8FsyhopZM/880zimwagJ5giwTJ7umBQBjf8I1rH/Q46r/35tv8A41Sf8I5q2cf8Jlquf+uNr/8AGq172e+S6tlsYoJIjJi5MjkMiYPKgDk5xXN+IdVWBtH17SLkSxvepZzorZWZHYoRj1VsHPoD60AbmlaTfWE7vea5eakrLgJcJEoU+o2IprWqrqEtzFYymwSKS62HyUlbarNjgEimWeoJPM1rK8YvYY1eeFGzs3dPw4NAF2iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAy7vRlm1221WCQw3MSGKTC5EsZ52n6HkHtk1bFlCdQ+2lP3/l+Vu/2c5x+ZqzRQAYoNFFAHHXd54l0nXr8Wmhf2rb3TK9vMtyI/L4xscEcAEE5GfvHiptL8JFRYy6kUH2aaS6FpD/AKtZnzzk9QATjgckn0rq6KAOc8SyaxaX2n32kad/acURZZrYSiNxkcOpPBI6YPZjSeH7XUbrVrnWdW06LTZZYlhSBZfMcqDnLnAGfYZx610lFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUE4qve3YsrfzmjlkG4LtiQs3Jx0H1pl5fx2b2ySfeupfJjGcZbaW/kpP4UAVNO8SafqepT2Ns0wuYC29JIHToQDgkAHqOh71rZrh1n15PiUnm28sWmPvhBaSMxyLt3KyqDu3AqQcgDkVL4X1bW73xRrFvqttNb28YBhSYpwQSMrtJO0jB5x0NAHXzTCCF5WDEIpYhRknHoKxLjxdYW8OjymO5ZNXnWGD9wwKswyNwIyo471yZ+IWrJo9xB/Yt/eX8VyYBc2VqZYZE34MqnocDJxnqMVFoOp6jqMOm2OpWmrTXsGpeal1dWDRKIt/8R6A7MigD0DRtXh1qye6tlZUWaSH5xgkoxUn8xUN1r0Vp4kstHa3maS8jeRJVXKLt6gntUWg2M2maZfR+VhmvbmaNM9Q0jMP51wus+LdUm1LSLuz8Past7BHJHO8li5SIsoBPGd2CO3X1oA9VzRmvMNA8Z67YXd9DrVlq2pQEB7WddKeJtxzlGXkYHGD71eb4gao1na+T4a1M3Lx5nDWjqscmBhQccjOefb3oA7q8vLewtZLm8lWGGMbnkY4Cj1NM0/UrPVbX7Tp11FcwklRJE4ZcjqMiuG8VeLdR0PxVYQS6bfXlhNGFeC3tPNWUkEkhs/eGBxjoc1FD4s1ybT9Rs9J8MX9tevNmzD2wjRYiq/MWJ27vvcEjtQB6RmuNuviz4Ms7qW2udVkSaJyjr9hnOCOvITBrQ8FPq8nhmMeIUnW8WR1JuAodlzwTtJHfHB7VmXPg3XprqWWLxbJEjuWWP7BG20emc80AdBoHiTS/E9g17olw1xbq5QuYnj5Hs4BrVJ4rJ8P6VeaTYNBqGpHUZS5YSmFY8D0wKxE8ZzWEk9tqui6s88crAPb2bSRsueCrLkYxQB0ljfS3U1wk9lNa+TKUQylSJV/vrgnj64NXc15No8mt6j8UoNTZLxLcySKBLYSwgQFThXZvl4OMY710HjfXPEFvOsfhGyub+5tGV54Ylj2MDzsZncEZH90GgDuaKhtJXns4ZZYmhd0DNG+MoSOhxxU1ABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFJmloAKKKQsACTwBQAtFMEiltoIzjOKfQAUUjMEUsxAA6k9qNwoAWim71LbQRnGcU6gAooprOE+8QBnHNADsVna1oVjr9kttqKMUSQSRtG5Vo3GQGUjocEj8a0RRQBg6f4O03TDJJavdfaJF2m5knLyAegJ6Co18G2aafdWqXl+GvGzcT/AGg+bJ7FvTHFdArq+dpBwcHHY06gCvYWNvptjDaWUQighUIiL0AFWMUUUAGKMUUUAFIyhlI5Ge4paKAMi28O20Gstqck1zc3GzZH58m5Yl7hR2z3+la2BS0UAGKKKKACjFZGia2dYa6As7i2+zSGJ/OXGXHUD17c+9a9ABisyDTZIPEd3fh/3VxCilP9pc8/lWnRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABSE460tUNW01dRtdu5kljDGJgxADFSASB1HPSgDl/HFzBp15ZakbvUlZAd0Npc7E8oOm6RlJwcZAx1wxravfFVlYahp9q6vILxlAlQZWPcCULem7BArmZdA13WraysNd0HR2SzXYl5K/msvG0si4+ViBVi98Nyan4m025l8PwJHpaAJdyyK0sgGMImPujIBJPpjuaAOsTWrKTWptJEuLyGFZ2jIx8jEgEevI/DiuUiv7HWNU17TLQ6if7QsXdJ5HbyGAGw+V2HLDOOtSf8Ik3irVZNT8WWf2fygYrKCGch40J+ZmdDyWwOOgxUlv8KvCtqu22tLiIYwAl3KOOv8AeoAq+EFKa3phjlllhk0MFWlcsSVkUd+/NdJe6hd3cE6eH3tWureYRyfaSQo5G4cc5xVy10u0shCLaFU8iLyY8fwpwcfoKydS8DaHqmoSXtzbSLcS48x4Znj346E7SMmgCh4j1KebwzfaPqEYTUZ9JllZoMmPcBghSee+ayvFPiVNF/szVdJglu9RvbXbbr+8aKRfvbcLxuOeCa6bTfBWjaVNLLawzF5YzExlneT5T1A3E4qjF8MvDcESRxQXSRoAqot5KAAO2N1AC6Dc/bvF1xqMW/7PfaVbXEQbsCW4rWh8S2F1pt5eWXmXIs5ZIZYokLSb0YqV29c8flg0tzA+k2IbSNNFzLFAIooxIEyq/dXJ7Vz1j8PLO9WXUfESO2q3j+bcm2neNAeirhSM7VAXPfFADtO+JHhzxJNLo0eoS6Xqz5i+yXSmG4RiOCqt1OOeKj1S8EunwWSXE89xo+o26XEsow0oKj5j6g7/AMwa1rjwD4aubRLd9KhTYwZZYxsk3DvvHzZ/GrWmeFNK0i1lt7O3by5pBJJ5sjSFmGMcsSeMCgC7c6hFDeRWQdRdTxPJErdCF2gn82X86x01fVNJ0+S58SxWxBnjij+wlmxvcJls+5FXtb8NaZ4hWH+1LfzGgJMUiuUdM9cMORnA/KsyL4deH4p45VhumaJ1dRJdyMMg5HBbB5FAFbTNat9B0bxNe3e+SOwv53ZUGWI2qQAPU5q1pXj3S9W8I2XiKBJ0tLuaOFVdPmVnkCDI9MsOaffeAdA1DUp766tZGmuGDTBZ3VZDjHKg4PFZr/DzSbLU7N9N0sG1ikEjR/anVY2Uhk2pnbjI6YoA6g61ZDWl0ppcXjQmdUI+8gOCR+JrNbxlYf8ACWR6FGkrysSjTgfu0k27thP97ArMm8MS+LNae78T2X2e2tAY7GKOb95z95yynjI4xnoea1LHwP4d06+t7210q3W8twfLuSmZeRg5c8n8aAKet+ME0vxRb6YZ7WAGMSyLcbt8wJxtiA+83tWrqfiO00hbU3Uc5W4cLlYyfLB/if8AujnvWBqHiPR9H8eSDxLNHZMIVFhPcfLGykfOFY8bs/jiq3iLSrb4hy2UcFpFcWEchLajHdD5V7qoU5ycd+BQB1F34m06z1qDS5Gka5mIHyISqZzjc3QZwcZrE1/4k6f4Y1HydY07U4bUuI1vltWaJmPbjmi8+Fvhe9W382zkDwOGEqzuJH5yAzZywHbPTtRL8P8ASY5o4odPE0EuRPNNcu0sePu7GJyPfGKALer+O9M0vS7O8WO4uTeAvDDHGRIUGNzYPIAyCa27iZbrRZZYGkKywFkaH75BXgr7+lYS/DjwuYXjuNLjuwxBzdsZiuPQtkj8K6aGFLeBIYVCRxqFVQOAAMAUAeIHTdT3H/TPiV17SvXrHhNJI/DNmkzag7qnJ1Ik3B5P38962qKAMPX9VTwvpc9/Fp812N5klWFlXAxyxLEDtTPC/ihvEtqbg6PqGmx4BU3sWzfn09aqeONVh0aLTLzUYHk0yO7Bu3RCwiGxtrsB2D7ee3BrS0nxRoevZXRdTtb1gu4rBKGIH4UAYeofEyw03xMuhTaVqj3chIiEVsWEgH8Qx29zWz4i8U2vh2wSaaGa5mmJWG2gXdJIQMkAfQVw0mqeHbzVLjTPEN1aWE/2t3vYrx2imcjPltE+R8vTp2rqYPh74WltyX09L6KVRg3TtOAPVdxOPwoA6SxvItQ0+C8tm3Q3EayIfUEZFT1DaWsNjZw2trGsUEKBI0UYCqBgAVNQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRiiigAooooAKKKKACiiigAooooAKKKKACiiigAorLu7+/h1q1tobKN7WbO+4acKy8E4C456D9amtL+S5vru3ktJoBbsAssi/LKCOqmgC9RTDIoYKWAJ6DPWuRvvF1/Z3+qQvYIsNnd2sCTF/vrKVBOPYNQB1s1vFOu2eNJF9GXNORFjUKihVHQAdKXPGTWLqOvrb3elx2uyaK9uTA0itkKQD+uRigDbopjswRtgy2OB6msK2183tjcWry29prMEBkmthJ5vkdcE4xkcUAdADnpRWR4Xupr3w1Z3VzcLcvNHv81U2hgenFaMd1BLPJDHKjSxY3oDyuemRQBNRUS3MTzSQrIpkjALqDyoOcZ/I05Jo5SRG6sVODg5xQA5lDjDcg9RUcVtDBnyYkjz12rjNSmuMuPHOqQXUkSeD9UlVGKh0dMN7jmgDrpLWCZw0sSOw6FlBIqUDFZWg6tcaxYm4utNuNNcMV8m4ILEevFWX1O2j1SPT3kxcSxmRFweVHXmgC5RQOaKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKgvHuI7V2solmnA+SN32Bj9cHFT0UAcbrWieIW1+DXdNmgumtlHl6bOxRclWVsSc44brt7Vj6hrPjHSpru71XT9NtIb5VhjL6qQLYgHkfu+SevbpXpVQ3Fpb3cey6ginQEELIgYZ9eaAPI7rw54513UPD2vR+Sj6RtYQw6ofLvl7kkJxn3zxxXWx6Lres2uqPrVnb6fPdPCY4orjzlHl/xE7Rz7V2ccSQxrHEioijCqowAPpTqAKWpz3Vpp7SWNn9tnXAWHzAm78SDiuS0fw1dqHnntI9LiOqLfR2vniQR8Dfg4GNzbjj3ruqbJGksZSRVZT1DDIoA4fVtU1pvG7L4T8nVFhtQl7ZzXHlRxEklSrgHD8nI9AKx/CXgrXrHxZJqerW7RI6T5Z9RFwcSHPlgCNflByeSTzXpFjplnpiOlhaxW6yOZHEaBdzHqT6mrVAGVodjLpHh2CzIDvAjAKpwDySB/IVy6W+vDxDc+ILTw7Ha3TWvkyRG9BF0Q6lCcLwVXfz713tGKAPONRtvHctxqV/o2j2NtPqVqtv5cl9hoWTdtkzswc+YRjjG0c1d8Fadr+lXAj1Dw3p+nrMg+1XVtqDSmRwOuwr1JPXNd1RQAVxVx8KPDF3dS3E6aiZJWLNt1W5UZPoBJgV2tFAGToPh2x8NaebPS/PEJYvie4eZsn/AGnJNYT+NNInsdRt9R1JbK7jmmtwi8SphiFIGMk4wa7Oqx06ya7+1NZ25uP+exiXf+eM0AVfDYvB4Y00amzNefZY/PLDBL7RnP41p0UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRWXrF3NaS2Pk3NvAJLlY3E6k+YD/CpB4b0rO8TeMbfw1eWENyIdtzIBI0s4j2IWClgD94gkcccZNAHS5oryvxx8T20vXtPtvDd9pd35cqm7gkuApmVuAqN90Edck16Tp2oRalpFvqEAYQ3EKzJvGCFIyMigC3Rmsaw8Q22p6RFfQMHjuJTFH5TbsncVH0PHI7Vjarr2oeEmsdMt9Pv9fmvBMyTBkBTByA2cDADAZ68d6AOxyPWgMCSAQSOted3fiXwxPHp+uahqSRarthWSziv9uxs8hkz0BZs5Falt4l8OWmu6xJbXkHmiKOWVzdqVlbDYCAt1AUdPUUAdjVeC+trmaaKCeOSSBtsqKwJQ4zgjtxXner/F+Cx1jw5bWVlFd22r/8fEwu0H2XOMZH55ziui8MrpzeJvENxpjQy/aHhkkmhcMGO1hjI9Nv60AdCL+3OoGyWVTcBPMZByVXOMn0qzmuD0TVYNFj8RahqpIuRqojnZ/4I2KrGc9lAYn061eGrQwapPejxZYXFqUYx2JeNcHHA37s9R6d6AOmW+t3vnsxIPtCKHMZ4O09/erFcBc6odZ1PwXqlhH5V5dyM0kec4gMTbwSOozjB9cV3F7NNb2M0ttD9omSMskW7bvYDhc9s0AL9rh+2/ZPMHn+X5mzvtzjP51NketcNb+JLKTxfp2o3cqWEd9pJAS6cIVYSZKnJxkZqnr/AIt8JXzahNe6mEm0g4Rbe+CNPlFb5QG+brj8KAPQvOj87yt6+Zjdszzj1xTJbuCK6it5JFWWYMY0J5YDGfyyK871rx7a6R4kg1I6TBqNk0YhN9p94JriMHnmEDlc9wT9K2TqNpr3iHw3rGlSNLbMtzHvaNkIyF4IYAjlTQB2OaKzdSj+3sLKC9mtJ12yl4cZC56HIPBwRWTfeM4bHTtWmNvtl065FtsnkEayMUVgd/IAO7r7UAbz6jax3htHuI1uBGZTEW+bYP4selQy67pkLQia+gjM43RB5Au8ZAyM9eSB+Nc3/wAJVpGqNpE9slpcXOp5tn8uZGlgUxsxHHJGUx+Rrl7/AMR2v/CAaZ9ijtLzUA5tmYtC0toAzYfbIw6Mqd/ftQB6zLMkMLyysFjRSzMegA70kEyXEKyxMGRxuVh3Fc3oN5deIPh2kt+F+1XFq8cuwgqWwVyMcYNZmnePNJ03wJp9211DPN5SR+RHKu4MTt+bn5QD1J6UAd0WA6kD60tcNd+MPDer6Dpeo3dzAXa6gZYI7wBopC4XLYIyFzznjANaUvjjS01C5s4Luzd4bbzkc3SBZGyRtBzQB09FUtF1EavodlqIjMQuoEmCE5K7hnH61doAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAGSQxy48xFbacjcM4PrXN634am8RahaJqkdi2nW8glYGPfLIQchcnhRnr1z0rp6KAMkeFtB8ny/7HsdhOSPs69fyrUWNEjEaKFQDAUDAAp1FAGJq/huK/wBLS00+dtLeKYTxS2yD5HyTnb0OSTmqUPh7V7I/a/7UGqagPlVrweXHGh67VUHBPHXNdRRQBhweFtIkj8y+0bTzdSr+/ZIVIZjyeSMnmqus+DLK7tI00m3sLCdHB81rJZBt54xkdzn8K6aigDEsfC2lw6esF3p9jNKVAmkW1VRIfXHOK0bHTLLTY2j0+1htkY5ZYkCgn14q1SEhRk9KAKkmk2U1zLPLbRu80flybhkOuc4I6Gqn/CJ+H/8AoDWP/fhf8K1VkV/unP0p1AFODSbK1uRcQW6JIsYiUgfdQfwgdhVXWbfWbi1ki0e5t7d5BtEsqFjF6sAOp9BxWtRQBjJ4Y0v+zbW0urOG8FrHsje4QO3Tk5Pc1W03whpsUOdT0zS57jcwEkVmqDZngYOe2Aea6KigChZ6HpensTY6fbW5PUxxBatrbxLt2oo2524HSpKKAOb1nw9ql1rS6noetf2dM0AgmSS285HUElSBuGGBZuc1VuPC2oDRLjT4bq3u5L1911d30YZicAEhAMcAAAdveuuooAxtJ8KaNo8Vv9j0+3SWBQqzCIB+mCc+9PbwroLuzvo9kzMckmBeT69K1qKAIre2htbdYLaJIokGFRFwAPYVRi8NaLDv8nS7RPMUq+2FRuB6g8Vp0UAYkHg7w7aQiO30WyRAMAeSp4rDg8BSxCUTTaXON4MIOlqPLG7JH3ucrxn8a7eigBkMSQwpFEioiAKqqMAD0FPoooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigApHUMpBGQRg0tFAGN4c0OLQbSeCIYV52dSWJJUngc+lbOa5Xxn9pv0t9Bs1iD6gH+eeRkTCjJHy8k98exq94Q0/V9K8OwWOv3Ud3dQ5Xzo84Zf4ck8k4oA3KyLTxb4dv78WNhr2mXV2xIFvDeRvISOvyg5rXqpHpllDMJYbSGOQdHWMA/nQBbooooAD0rA8P6/Lqmrazp93b/Z7jTboRhc53xsisj/iG/MGt+ue1C2Gi3mreII03mS0RGjXgsULc/kwH4UAdBkGlrh/CPh/X9L8QXl/eXlo+m36CQ28Lu+2X++Cw7jGfoK7igArD8S6xqukW8MmjaFNrMjvh44po4ygx1y7AGtysnXfDWm+I4Y4tWhaVIm3KFcrg9O1AGBp3i7xRd6lBBeeBryzgkcK9w95bsIx6kByT+FdrXLWXw58N6dfQ3dpZuk0LB0YzMcEe2a6mgBCcCs2y8RaVf6lPp9pexSXVvnzYgfmXBwePrUfiK21S4sEOiPCLqKVJAlwSEkAOSpIBI+tc9eQeNL2zubeTRdDUXEbRu6XkgbBGDzsoA7iiqWj209notnbXknm3EUKJK+c7mAwT+dXaACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA5XVfGn9n6g9vbW1vcqnBc6hDHg9xtZgapf8LBm/6Blt/wCDW3/+KrppdF0mSYtLp9s8j8ktECTTG0HR/LZk0u0JA4HkrzQByN14w+13lncy6ZbeZaSGSM/2rb9SjKf4vRjVv/hYM3/QMtv/AAa2/wD8VV/QIdJ1y1ef+wI7RUkMe2aBQSQcH8K1/wDhH9H/AOgZa/8Aflf8KAOZ/wCFgz/9A22/8Gtv/wDFUf8ACwZv+gbbf+DW3/8Aiq6b/hH9H/6Blr/35X/Cj/hH9H/6Blp/35X/AAoA5n/hYE//AEDbb/wa2/8A8VR/wsCf/oG23/g1t/8A4qum/wCEf0f/AKBlp/35X/Ck/sHRt23+zLTP/XFf8KAOa/4WDN/0DbX/AMGtv/8AFVoab4ltteims74W1q8oMaRi8ilaTI5wFJqfWrHSNI0me/8A7EhuFgXc0cUKliO+B3qrd+HrLWfDvnWenR2F2yia3cRqHiccqcjp/wDXoA6Oyt1s7KG2jyUhjWNSfQDFTk4Gay/Duq/2zocF267JuY548/6uVSVdfwINVfFuoTWumpZWJ/03UJBbQAdVz95vwXJ/KgDcjlSZA8TB1PQg5FOqppdhFpml29lbjEcCBB7+p/E81boAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDi/iVo93eaTa6jpV/dWF7YzqBLbPhjE7Krrjoex5/u10+k6emmaVDaRyyzBF5kmbc7k8kk9zVqWJJoykqhlPUHvTwMDigDkvFevr4VS2itpbSye+uCTcXobyVOMkEj+I4wBXSafeLfWUU6hgHXPzIVz74POK5jxhrGnaPreky+IEYaZlyJ2UmOKcY2FvTgvgnvit7Sde0vWkZtJvYbtU+8YmzigDSooooAK5PV4Li0+I2iahBJJ5N1DLaXEe47cAb1OPXOa6yo5LeOWRHkQM0ZyhI+6aAHOiyRlWGVYYINcjqvipdH8T2mixz2ttGsSuY7hWMk68jbDjqRjnr1rsO1cPfeJdI0bx9OviVls5DEi2FxMv7tkI+YK3QNuzn2C0AW4m/sHxjuAaOx10B8MMeXcquDn03IB+KH1p+jA674outbc7rW03WdiOx5/euPqwC/8APrVvUrTTvG3hySG0vcxOcxXVu3zRuOjKex/wAa1NL06HStLt7G2GI4Iwg9T6k+5PNAFuiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAztY17TfD9qLrWbtLSAsEEj5wT6cVif8AC0PBn/Qftvyb/CuqaNX++oYehGab9nh/55J/3yKAOX/4Wh4M/wCg/bfk3+FH/C0PBn/Qftvyb/CtzVJ7fS9LuL17Xzkt4zIyRoCxA64FZfhrxVovi3e+hr58EaAvMYtqhj/DyOSMHPpQBVf4meCpEKvr1qykYIIY5/StfQNc0bW7Z30C5huIIm2sYVwFP5CrsjWUM0UMvkpJMSI0bALkDJwO/FWEjRPuKF+gxQA6iiigAqO4uIrW3ee4kWOKNSzuxwFHqakpk0MdxC0U6LJG4wyOMhh6EGgDG/4TXw1/0HLL/v8ACo5fFvhWdds2safIvo0ikVPd6JoVnZy3DaJYusSFyqWiEnAzxxVfRbHw3rui2mp2ej2HkXUSypm1TIBHQ8dR0oAevjLwyihV1uxAHAAlHFO/4TXw1/0HLL/v6Kkk0Xw7DNHFLpemJJKSI1a3jBbHpxzU3/CN6H/0BtP/APAVP8KAGWnijRL6Ux2eqWs7gbiqSAkDIGfzI/OtQHNc5rPhCzurPGlQw2E25fnt4kTIDqxBO3/ZretYTBbrG0jyFR95+p/KgCaiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooARlDKQwyCMEHvWT4b0hdD0j7DGMRxyyGMeisxb+ta9GKAMRbzTdQvriS5Fr5umTFY5Jcbom28nnpkNj86Xwpe3l/4fgm1KSOW4yytLEMLIAThh7EU3UPBugapqBvr7TY5bhgA77mG/HTcAcH8RWzDDHbwrFCixxoMKqjAA9MUAPooooAKKKKAEdQ6FWGQRgisTwjpEmhaCbGTgJc3DxrnO1GmdlH4KwrcoxQBhi+07Ub68Fx9m87Sp9iPKRuiYxq27npw1P8KXt5qHh2G41F0knMkql4xhXUSMFYfVQDTNQ8G6BqmoG+v9NjluGADvuYb8dNwBw341sQwx28KxQoscaDCqowAPTFAElFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFGaAEJANI7rGhZzhQMkntWBr0t/H4m8Pi0uvJtZJZVuU2Z8wbcgZ7c1d1LUbJp/7He5iW+u4HMUL9WAGM49KANCG4iuIVlgkWSNujKcg08EGvLNOm1+00vT/AAxrSppmrRXSPby2T/uryIMdxHocfeB9Qe9dr4Yuru4fWEvZDI0GovGn+ymxGA/8eoA36KwNKu3m8RapB/a63hgVD9nWMAQbt2ASDyflP6Vb0y9mTTS+sXVo8ySmN5IGwgO7CjnoeQMetAGoTik3CspfEek3Guz6HBqEB1OGMSPbBvnVT3xXLaBqOsbPC66hetcG6nuIrhtu3cVjkZQfptoA7/NFZPiR5j4Z1RbGcxXQtJTE6n5kbacH86o6P4l02Cx0mw1PWbZtTuoEKRyyqkkxI67c55oA6Siml1DbcjOM4zUN1f2tnaSXN1cRxQRLukkdgFUepNAFiisL+0NUbVbeWFtOfRrjb5c3nkSNuXjaMYOT056GrZ8QaWuupopvYv7ReMyC3DZbaO5HbrQBpUUVyvjrWrjRbC3lttd03Ri8hUyagm5X46D3oA6qivLNF8aX95rVpbyeOvDd4skgUwW8REknsvPWvUh0oAWiiigAormPG2paho1pp+o2UmLaC+hW9TbndC7BGP4bt34Vs32s6dpgg/tG9gtftDiOLzpAu9j0Az1NAF6igHPSigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAEYEqccGuQ1HXLnw1q9tHqyaje2jWxxdWtm8uZdx4ZYwcfLjFdhSEA0AcFoVlr+qeIpNU1TU7mXR4G8y0t57HyJC3PY/NgDAGRk06TT49Z+JNvfWZ1MJaKHmEitHbqwBAwGA3MQecdMc13mKAAKAOV/4Q+6fxkmu3Wt3E6RMTDaNEu2IEYKhuuD1PrxXQ2tjHay3Lx9bmXzX/wB7aq/yUVZooA5FvAn2G8kufDerXGlSTsxn+UTCTJyOG6YJY8f3jXO6v4a1bTlg0hdS1a+s55BOXgso2EcglVgzNnP3jux6Ka9QooA8+h+GElv4hfxDa69LFrM0Zimu/skZ3qSDjb0B4610+neHI7O10+Oa4a4lsZXmEpULvdlZSSB04c1tUUAc7rvhq+1S4kl07XJ9NE0XlTKkSyBx6jPQ8muW/wCFSTnT0tH8SSOqyLL5j2MZkLqcht3XPFel0UAcWfBeuNeNdHxfcea8Xku32OPlc5wPSs+98Or4f8K3WnvqWpXdzM0Zhmt7Qs4KKFRQACOijOfxr0SkIBoA83034c65/Zeni88XXqS2uyWKEQRlIHA+6PUDOK3NP8A29lrkWrS6le3N2HMsu9/kkcrt3bf4eABgegrraKACopraG4AFxEkoHQOucVLRQBWXTrJGDJaQqw6ERgEVZoooAKKKKAKupafDqlhJZ3IzFKMMPUVyfiLQY/FutXWg6jdXMFstqsiLbtt3gnByfrXbVF9mi+1fadg83Zs3d9uc4/OgBmn2psdOt7UzSTmGNYzLKcs+BjJPqasUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAVSXWNPfVG01LyFr1BloA43qMZ5H0Iqa6vLeyjR7qZIld1jUucZZjgD6k1xs3i+HS/F90Ndh/snTgDFHd3MWxJ3H8Qk78cAe1AHW32qWenz2sV5OkT3cnlQhjje/oPeqsviKwiVWDvIpufspMaFtsncHHQA965O8+KmjGDUfsd5ZS3FtKq2kTS5NypVTlfXkkD6VnX2ueE7XUtd0vxTPHG8V+J7aCRirPuhRsjHqxYfWgD0K41vT7XUVsZ7qNLp4WnWIt8xjXq30qzbX1vdafHewyA28kYkWTsVxnP5V57pGuaL4p1jRpdJuIJJl0i4jngV97wAiPCseueo/Cun0NpdN8A22baSeS2tiogVcs+3IAA98UAa1lrGn6javc2N5DPDG21pI3BVTwcZ/EVcVgwyvI7GvN4vG2hDwzf2Xiz7PbXLBydLuo/KaRCoKrsP5fhVuP4n+GbS30uG21GxWGQBJgsoxbYjJCn05GKAO01LUbXSdOmvtQnWC2hXdJI5wFFMtNWs728e2tplkkSJJWC84Vs7T+ODXlNl8TbfxP4d8S6b4tOn6e2Hisk83P2pCp2kA9eQORwc13uj2TW/iqa6C7YrjToFGB0KZGP/AB6gDW1fWrDQreKfU7hLeKWZIUZj1d2CqPzNX1ORkV5z458b+HorB7fUr2KG70/U7dzbNzIyxzoxYL3yASKrWHxhs38QwwalPpcGmXKt5c0d2HkhIGf3g6DOMcd6APUKOlcOfiz4VEU7jVbdjHN5aqJBlxnG/wD3e+fTmo9f+JNrpXh+x1ZfJS2u5HKtO2BJGp6qR3YcigDullRzhGDHvg06vM9L8a+AdL1+VtHurSJbmN3luFchXfeTsHYtlifxrX8F+M73xLrOo295aC2jhRZIUMbK8YJYbXz/ABfLnj1oA7WoLm9trJQ13PHArHAMjBc/nU9cr460O81ywt4rDSdH1No5CzJq0ZdFGOq+9AG5HrWmSyLHFf2zuxwFWUEk1eHNeV6L4H1mz1u0uJ/Cfg62jjkDNNa25EqD1U+tepjpQAtFFFAFO41Wytb6KzuLmOKeZS8cbsAWA6kVNaXcN7bLPayCSJ/uuvRvcVzHxB8J2XinSrNb20juTaXsMyq4yCu8Bx+KlhVfxd4si8EabbQ6ZBbMIVBNmMhvKHZAvQ46Z4oA7Wiq9heR6jp9veQbvKuI1kTcMHBGRxVigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKCcdaACigEHpzRQAUUUUAFFFFACMit94A9+ahvLUXdrJDnYXUgOACVPqM96nooAx9D0F9KtDFe38upvkES3MaBl4AwNqjjIz+NajW0DNuaFGb1KgmpKKAI0t4Y2JjiRSepVQKfgelLRQBG9vC7bniRmHQlcmsVfDky6+b/+05zbMcmxMcfldCOu3d6Hr/Ot6igCNraFyC0SMR0JUcU/aB0FLRQBG9tBI254Y2Pqyg037Hbf8+8X/fAqaigCE2lv2gj6Y+4KxdU0C81aeK3nvIk0tXDPbxw4eUDohb+79ADXQUUAQi1gAH7iPg5HyipdoHalooAKKKKACiiigAooooACM9ayIbKeLxdc3Q/49Z7VAw/6aK2P5VqySLEu6RgozjJOKI3WRdyMGHqDmgB3TpRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUyXf5TeTgvj5d3TNc4fFEdhq5sNau7OzuBZpKEeTaruSQ21j1Axj1oAsX+q6jb+NNL02CCJrG6t5pJpGJ3KyFcAf99Va14tNot7BafvLryGaOJJArMccY9Oa5bw5qOva/wCJnv8AVbbTodP04SRQ3FtM7+aXCk4LKOBjr60y2gnuvi5LdW+p21zBFbnMUERLRKwUbHfdg8qSBjIy3rQBHo/iu/1DSdBhso5LK9S+W21G0vkBlVPLkPGMDGVGCB2rq/DWqXGraObm7RY5RPLGVXsFcgfoBWHYaB4gl+IDa3rP2D7LHDJDAtuW3bSQVLAjlh83OeMnA5Oek03TDp9rcQq/E0zyKQPu7qAK2nX+pTSX63cVrugOIo4JCxPX7xI4zxV7Tbya706Ke8tWs5nGXgdgSh9MiuRs/Dnijw5POdEu7TUkusGV9QJR1YE4xtHPB7+lYFzceJtP+w+H7vUNKW+SaOWJmaYm4O/OGOMAHkdT2oA9G1rU2s9D1O5sDFNd2ltJIkRbPzBSQCByMkVlWOv3954m061WCE2N1ppuml3HcH3AYA9Oa5DTfAXivSvE+ra9BPp9xNrMRjuLaWWQRxc9V65P4DFdH4T0LxDY3lkdd+wCGxszbRtbMxaTp1yOOlAHZ5qjZa3p+o3lzbWVys0tqdswUHCn69D+Fc1rXiq1sNQ1nS7m/awvHjBs5JoWaPmMcggc4bqKh8FateR+HblvFB021ihG2Ga1R4Vljxy2H5HOaAOiu9Ulh8T6bYpsMF1DK5PUkrtIx+darypGpLsqhRkknGBXnljpGrHQdC1Dw4yN9gkuTCupO+XtnJCAkc/dC4zz61lEeIPHH9q21tfaY0d5bLbXKRtMv2fDNyuQM579OlAHd+ItYvbFtIOkxw3CXt8kEpZuAhVjkEfSpbHVbi48XanpkqKsNrbQSxkdW3mQEn/vgVw+m+DPG2i+E9P0OwvdMZNJl823uZ/Md5yGYhWGflB3EdTjiu+sNPmXU31O6VEubizhhlRDkKyF2OD3GXNAGpkEHHasGPWo7TxI2l6jqNu012d1lAkTKwAHzBmyQT3HTvVCW28ZWOoXg0r+y7q0mmMsZuWdJEyANpxkHp14rn4vAuvXfi+LWdTWzhP2hJ3MN5K4RlGMohGASPlPsTQB23hnVZtW0Rbq6VUl82RGVeg2sR/IVqvKkYBd1UE45OK5HVxZaD4Q1GzuLxlkvHlECW7YlMkh+VU98msa98LeK/Euj2un+Io9LkjRR/pKTTpIpxw+1GXLD60Ad5qN7cWgtza2bXYkmVJNrgeWpPL89QK5zUPFOraP4vWK/wBNV/DlxGnl6lC2fJc8ESf7Oe46Vk6V4S8aeGd9vYa7HrtlJFs8vVGKGI/7JUEnj1NaWoeH/ECeArHQ9LezeVYVguzcMcMm3BCnB59yKAE0nxBrIvNNt9TNtILvUbu3MkSEZjj3bCOe+0V2bSxx7RI6ruOBuOM1z2leHJbfR9BgvDGLnTFUuY8lS2zacZ559TWH4/8AC7+NNVtLG1vDZ3OmqLtZA7DcScBSFI445P5UAd8XC43EDJwMnrS7hXBXJ8S32s6ZZ60+k2ghnW6zbzSbyqnnGRg56c0k15rGoeNLu68GXFvc28MCwXaXbt5BlBJHllf4gDz25HcUAd358XneV5ieZjOzcM49cU6RisbMoyQMgZxmuF0XwVrVp41XxDqeqW08kiOJUSBgy7guIwxcgoNvHyg9T3ru3UOhVuQRg0Aeey+O/FqTOieCYnVWIDf2vGMjPXG2uu8O6lfarpKXWp6eunXDMQbdZxKFHb5gBWS/wy8ISSM76MhZiST50nJ/76re0nR7HQ7BbLS4Bb26kkIGLYJ9ySaALtYF1r09n44sNHmgUWt9bSNFPk5MqYO3/vncfwrfrM1LSE1DU9Ku2OG0+4aZeOuYnT/2egCTW9Mi1nRLvT5x8lxEUyDgqSOCD2IPOarR6hpuhtY6OziKaRQkUSKT+Z7fjWx2rjrzRTq/jm4mt9TurWGCBYryCCQDzyRlQeMrgd1IJoA7EHIopsahI1ReijA5p1ABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABVS80rT9QZGv7G2umT7hmiV9v0yOKt0E460ARrBEkQiWNRGBgIF4x9KZbWNpZ7/sltDBvbc/loF3H1OOtT54qMzxjGXX5jtHPU+lAElFQxXcE6O0MqSKjFWKsCFI6g+9PWZGcKGUsRuAz1Hr+tAD6jaCJ3DvGrMOhIyRTywFLQAUUUwyoucsBt689KAM7W9HfVrdEhvZbGRHDebCiMxHp8wNTppkMljFb36pelEAZ541O8juRjHvV0HIooAQIqrtAAHTFMjgiiJMcaoT12jGac7rGpZ2CqBkknAFKrBhkdKAFopCdoyeBTTMgQMXXax4OetAD6KKjeeON1R3VWc4UE43H2oAZJY2ks8c0ttE8sZyjsgLKfUHtU4GKb5iiQJkbiMgZ5xTqACiimtIqY3MBk4GT1oAdXOeIPB8et6lDqNtqV9pV/Cnli4s3UFkznaysCCMmt5rmJZxC0iiUru2buceuPSpEdZEDoQysMgg5BFAGfp2lGztVivLqbUJB1muQpY/98gCrdtaW9nF5dpBHBHknZGoUZPsKmooAKKKKACiiigAooppcDPPTr7UAOrmdZ8GrqWtDVrDVb/Sb0qEke0ddsoHQMrKQcevBrX1jUxpGj3GoNBLcJbp5jxwgFio6kA9cDmp7C5e8sYriSB7cyDd5chBZR74JGfxoAZptnLY2iwz3k9646zT7dx/75AH6VboooAKKKKACiiigAooooAKKKKACiiigAooooAK5zxtqOmafoO7V2Ox5AsaLMIjI/YbiQB+Jro6o/wBjWO2ZXt1kWaQyusg3Dd689KAKsOp2VjoOnyjcLedIo4RncfmA2jP9a5rUrjT7C5hsdPhktzY6xDLMHJw3mq3zAk9CSfxBqLUvh3EdWiXTdMs305gPOE91KrodxzsUAjpjHIreXwF4f/su5082bNb3LK0oaRiWK9Oc54oAz00iPTrjU9KXU5Jm1W2nnWERBQh6Ftw7/Oo/4DVbwtb/AGHX9GgjkkeJtEZQzsWJZJEB/wDQ6uR/CrwnCVMWnMjruw4nfdzjIznpwK6a30y1tfs/kRKpt4jDEe6ocZH/AI6PyoA5nX9T0dPG+j2NyWk1AsSqCfYIlIJDFcjdkrjoeprXtJIY/EuoRrfTzSCGN3t2+5COcEcdWwfyqzqmg6drMLx6haxy71ClsYYAEEYbqOQK5bVfhxpsdsJNDsI2vN67jcXMihkzzkjJOBnFAEur/FDSNJk8PiS3vJk16VYreSKHIQscDd+PYZPtWZ4hsTeWnjm2nnkSIxQ3CFHKsoEeTg9uVrS074Z+H20yAappFuLlVBKxyuyxN1/dk4I/IVaX4a+Gll8wWchY43EzudwHY880AdKssdvDCjtjdhVz3OKy7nU76fXFstJjtXjgZftjyzEMgPO1VAOTg55wKb4lsdTntLe40Ka3jvLOTzEW5yI5BjBUkZI4PWuO0XRbfxJ4pHigPpD6jbFTIumXbyeY20Bd7EADjtigDovF2qw3Gm6zoiLKt4NPMyEoQrqcj5W7kY5Faqa1bW2l6XPMTi+MUcW0ZyzrkfhxVO20/UNU1q4u9Zto7e0jjaC2g3hnYN992I4GewzXPT/Da3i1WCCy0y1bSUCZMt3KJYyM52jGOBtxz60Aadj4807xB4r1vwrBbXcV1p8WXlkj2xyAjqp+vHOM44rLtIVi+HmhfZJ2lS1v03t5m48SMpBP1PStkfDTwt5nmLpoSRhh5FkYNIP9o55rQ0jwfo2hQ3MOmWohguJRK8IYlAwxyB26CgDRm1CG31C3snP764V2QeoXGf8A0IVzfxA1iLRdOtLkWLXV55+20byJJFikKNgtsBIB+7071t614c03xBDFHqlv5vktujYMVZD04I5rIPw28ON1t5z9bl/8aAKugajJrHiTSdXdHhF5o82+Fs/I6yxAjH510UOv2VxJqEUDM82nsVniCneDjIwO+e3rTU06PSLOFNKsRILaJo4kDYYKecAn1IHU1z1p4Gi1i4n1XxZbqNSuT922lYCKMfdTIxux60AFh8VPDl9qp0m+luNH1JmCpa6hCYnfJwNp5Bz9aj1Lw/beItLm8JXOq6kt3YiO4j1AsBJnOVYEYBweDWy/gXw7Jp5s30yExnB3EfPkHIO7rmptM8I6TpEdytjC6/aU2SlpGYkemSeKAOQ0u0m1fxBOt9KLq80ixktft6HAn3H5WHvjr2BzXS+HtR+wfDPS9QuI5ZfJ0yKV0iXc7YjBIA7mrWheEdH8NiT+yLbyfNUK2XLZA7c1X8WbNL8HMsNtI9nDsSaG3UlhACAwUDk/L2FAC+EPGlh408NjWtKhuY4CWXy7iPa4KnBGOQfwNTr4r04aDa6vcM8FtcSCPMi4MbElcN6YIwa46Kw8DeJYp5PCj2VxfuNwt0uXhGf9pRyv5Vs3/h+8vdPtPDkOnxW2i4/0uQy79y5zsUdck9WOKANHxR4ysfDC26zxyXM9xkpBAV3bARufkjgZHv7VvxSLNCskZDI6hlI7g1zkXw98Mx27QtpccyMR/ryXIx0AJPAro4o1hjWOMBUUBVA7AUAeb+O1Y+IwRbeMpf3K/NossSwdT2Yg7vX8Km+H6sutT5t/F0X7g865JG0R+Yfd2knd/TNei0UAFcB4k8MXd18QNOni1a+tdO1FGhvLe3kwsrIpdc+gIDA49RXf0x4UkkjdlBaM5UnscY/kTQA14Ee2aBxujZdpB7iuW1fxSNK8UW2krLBbxLGHdJUkaSdfSIKp3EenX27111cTqPiPRdF8dzf8JK62T+Ui2V1cKREVI+YBzwp3epFAHaRtvjVsEbhnBGDTqrWOoWmpWy3Gn3MVzC3SSFwyn8RVmgAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAEIyMGo4baG3z5MSR7uu1QM1LRQAUUUUAFFFFABRRRQAUUUUAFFFFABQQGGCMiiigCKO1giYtFDGhPUqoGalxRRQAUUUUAFFFFABRRRQAVHLbwzjE0SSD0ZQakooAakaRrtjUKvoBinUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAf/9k=)