python 一篇搞定所有的异常处理
一:什么是异常?
异常即是一个事件,该事件会在程序执行过程中发生,影响了程序的正常执行。
一般情况下,在python无法正常处理程序时就会发生一个异常(异常是python对象,表示一个错误)
异常就是程序运行时候发生错误的信号(在程序出现错误的时候,则会产生一个异常,若程序没有处理他,则会抛出该异常,程序的运行也随之终止),在python中,错误触发的异常如下:
aaarticlea/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsKCwsNDhIQDQ4RDgsLEBYQERMUFRUVDA8XGBYUGBIUFRT/2wBDAQMEBAUEBQkFBQkUDQsNFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBT/wAARCAHaA1wDASIAAhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEAAwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD5m8UNF/wkurZRyftc3Rx/fPtWZuh/uP8A99j/AArQ8U/8jPq//X5N/wChmsutTIk3Q/3H/wC+x/hVrTrOHULnyvnj4JzuB/pVGtTw5/yEh/uGgC//AMIvD/z2f8hR/wAIvD/z2f8AIVtV22heGrRU0l2imu7yW8jaZHtpBEkODkEsuDzjP6etNK5DlY8v/wCEXh/57P8AkKP+EXh/57P+Qr3Px3Z6Hb+Gr8WsGnxXi7MCFEEg+dc9Oema8stLSe/uY7e2hkuJ5DhIokLMx9AByabVhKVzn/8AhF4f+ez/AJCj/hF4f+ez/kK2+lJUlXZi/wDCLw/89n/IUf8ACLw/89n/ACFdBJZzxW0Vw8EiW8pZY5WQhHK43AHocZGcdM1DQF2Yv/CLw/8APZ/yFH/CLw/89n/IVtUUBcxf+EXh/wCez/kKP+EXh/57P+QreeB0iSRlIR87W7HFE0EluVEilCyhgD1waAucpqmkw6bGj7nk3HGMgY/Ss3dD/cf/AL7H+Fb/AIo/494f98/yrnKCiTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigCTdD/cf/vsf4Ubof7j/APfY/wAKjooAk3Q/3H/77H+FG6H+4/8A32P8KjooAk3Q/wBx/wDvsf4Ubof7j/8AfY/wqOigCTdD/cf/AL7H+FG6H+4//fY/wqOigDU8U/8AIz6v/wBfk3/oZq14R8D6145vJ7fR7Ge7aCF5pGihd1QKjMFJVThm2lVB6sQKq+Kf+Rn1f/r8m/8AQzVvwLc2Nt4lgOozfZ7SSKeFpTJIiqXidF3mMhtm5huA6rkdDTWwiTV/h7r/AIe0R9T1fTbnSIxcJbpDqFvJBJKWVm3IGUBgNnODkbl45qh4c/5CQ/3DWvrHhu18PeFWW+n06bW5bxTb/wBnahHdkQBG8zzDE7Io3GPb0Y/P2xWZ4Vt5LrV0iiXc7I2BnHalu7L+tF/X4Dk1FXeh0te4317cRadpVnausMl1FgzMu7YoTJwMjnpXj39gX/8Azw/8fX/GuzvfE+o3tjbQHSfKltwPKniuQGU7cZ6dCO1dlGLjNOpFtdTzK9WM6bVKolKzs7rfoddp3w2uNZ06LTorCXybnaiXv2JtiA4HmbjwcDnqM/jXO+GdBl+H3xwtdF8+G8aG4WHznt1O4OgYEK27a3IGQc9Rmuvf4zXVv4E03TNPsb201i0tEtjNvjMZKx7Q4O7rkBsFT0I75Hj15Fruoas+p3EksmoPJ5xufNAff2IIPBGBjHTFfKYHF5/meNnWx9BUaEE4xgk22+bSTeunLpo7a7HZGhl2X0PZ0a/tJyak22rLTVJep1+jz6fbeFZfEN+scd5c6k1vLJDodrdxRqsalU8p2RI92WOVXJ2nkc5k02PR9Qvr3TNIso9Lvb7UHW1XW9OEscyfKBbbvnaBlLNyvPIy64Fctb6h4stL64vYNU1GG8ucedcR3zLJLjpuYNk496is5/E2n29zBa319bQXJJnihuyiykjB3ANhsj1r6L2U/wCV/wBW/wAhfWaP86+9ef8AmdBrd1f3vw58L6ZFawTSyXd1biOCyiMpZTFtVWVd2455wctxnNTM0+geD/CE1loNjPeXc1xDNLdaek7TMs2FiIdTz24w3YEVy9ifEemWxt7O7u7S3MqzeVBdFE8wY2vgNjcMDB68Ct248Qa7B4d0ex0y61GwubdJ1u5IbryxNvkLjlXy3BPXuTT9nUX2X9wvrFFq3OvvRrav4OsPEF5e6RpEUEE2kas0MksYHFpI3Lu3VhEwILHOAw9K4DxPf2mpa7eT2FulrY7tkESKFxGoCqTj+IgAk9ySa39G83w/oOpLaR3L6tqMBs5C2xIoYSwLbSHJcsFA5VcZPXiuc/sC/wD+eH/j6/40lSqLSz+7+v8Ah2xvE0Xrzr71/X/DIk066isLfdMROJGyIBg7cH7x9D6Cqd8uLlm84XAf5hIDyfr6H2qx/YF//wA8P/H1/wAaP7Av/wDnh/4+v+NV7Of8r+4j29H+dfejlfFH/HvD/vn+Vc5XV+M7Cext7bz49m5zjkHOB7fWuUrNpp2Z0xkpJOLugooopFBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAanin/kZ9X/6/Jv/AEM1Y8E6raaL4mtLy93LCgkUTIm9oHZGVJQvcoxVwP8AZqv4p/5GfV/+vyb/ANDNbXw6m1PUfEmmafb6xqenxQGe5iGnzMJUIiZnEIBGJHVNgx1JGc9KaEdB8TfE+lalp9xHb63/AMJFf30tlNJcIkwWIwWvlSEmZFZnkds5A6ICTk4Hmf2qaygnmt5pIJlQbZImKsMsAcEe1etT/EXV30D/AISKw1jxHLZ2t7HZ3GleIdWe+tb0OjsVJURBlAQhkKnh1OecV5DdndZ3RwBlRwP99ajZv+uit+Fi3ZpFf/hKNZ/6C9//AOBL/wCNH/CUaz/0F7//AMCX/wAao2sKT3CRySeUjHl9u7H0Hr/nIou4Pst3NBu3eW7JuxjODjNVzS7mfs4fyovf8JRrP/QXv/8AwJf/ABo/4SjWf+gvf/8AgS/+NZlFHNLuHs4fyo0/+Eo1n/oL3/8A4Ev/AI0f8JRrP/QXv/8AwJf/ABrMoo5pdw9nD+VGn/wlGs/9Be//APAl/wDGj/hKNZ/6C9//AOBL/wCNZlFHNLuHs4fyo1NR8UaymmWjrq98rNNKCwuXBICx47+5/Osv/hLtd/6DWo/+BUn+NGp/8gmz/wCu83/oMdUbDT7rVLpLaztpbu4fO2KBC7nHJwBzS5pN2TK9nD+VF7/hLtd/6DWo/wDgVJ/jR/wl2u/9BrUf/AqT/GtbxN4Fu/D9ld3T2OoRQR3rwJLPCyp5Yxhydo+8SMHocHrXJ1PPLuP2UP5UaNx4i1W72+fqd5Nt6eZcO2PzNQ/2tff8/tx/39b/ABrbuvBy23hxNUN7C0LM+2ZGYrJwAqKm0Op3CQFmAX5eD68zSb11LSSWhb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aXTtIv9XaRbGyuL1o13OLeJpCo9TgHApNN0i+1mZobCyuL6VV3GO2iaRgPUgA8Uhh/a19/z+3H/AH9b/Gj+1r7/AJ/bj/v63+NNtNMvL+8FpbWs9zdEkeRDGWfjr8oGeMVo+J9LtNJ1C2S2S4WCW2inaO4cGRSwyy5Cgdfajt5gUP7Wvv8An9uP+/rf40f2tff8/tx/39b/ABps1q0moSW9vbToxkKpbv8APKOeFOAMn8B9KLrTruxigkubWa3jnXfC8sZUSL6qT1HuKAHf2tff8/tx/wB/W/xo/ta+/wCf24/7+t/jS3ukX+nQ2813ZXFrFcLuhkmiZFkHHKkjkcjp6iqdAFv+1r7/AJ/bj/v63+NH9rX3/P7cf9/W/wAa29P8HLe+H5tTN7CIUZd8wZsQjB3qybdzNkxDKZUbuT6czR1sHmW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAFv+1r7/n9uP8Av63+NH9rX3/P7cf9/W/xqpRQBb/ta+/5/bj/AL+t/jR/a19/z+3H/f1v8aqUUAW/7Wvv+f24/wC/rf40f2tff8/tx/39b/GqlFAHo/in/kZ9X/6/Jv8A0M1P4L/s7/hJbT+1biOzsSHDXMnm4gbY2yTEQLkq21gB1IAJAJNQeKf+Rn1f/r8m/wDQzXYeDNdXTPCCQ6d4vt/Ceqm/kkujIt0rXMPlxiJS0MThlDed8jHHzdDWyMd9DJ8a3N3qVvb3F/48i8WzRNsjhMt9JJEp5JBniUAcDODnpx6cdc/8eNz/ALg/9DWux+IOm6EmsahqGh67pl7Z3F0zQ2FnBcxvCjEkcSQogUdMBj1Fcdc/8eNz/uD/ANDWoWxb3MyxgkuLyGOKNpZCwwiKST36Cp9cgkt9YvFljaNjKzAOpBIJODVGijsAUUUUAFFFFABRRRQAan/yCbP/AK7zf+gx0/whFaz+JLCK7hlmieZRiKURkHcOSSrZA5yMc+opmp/8gmz/AOu83/oMdQaNrE+hXZu7VYxdBSIpnXcYW/vp2DDnBOcZyMEAiW2tUVa6szd8V32nXOjad9ms7uCa4kmvN012so+Z9jZAiXOTGMc8e9cnXX2nxN1C0uI5BYaWyRHzIoRa7FilP3pU2EFXbnJBwPlwBsTbZm+K941uI4NE0WydHeWGW2t3VoJGzmSPLkK3zdcfwp/cXGS5ktF+P/AKbuzmp/EeoXFsYpLmVnbcJJzIxklRlQbHbPKgRrgf/WrMrqv+Fjamv+qt9Pt9nzw+TaKv2eU/emj/ALrtzk9B8uANibdGL4tXUCwhNA0NDDI00ZS3kQxyNnLrtkG1jnqMfdTH3Fw7y7fj/wAACjaaRqmo+GtLn0aKa5FvcO1wlsNxhlyCkjgdBtxhjwNp5qR9PvfEPhx49Pjk1LUE1KaW8jskLmQMq7JNqj7oIkAOMDd2zUUnxJ1IyM0Fpp1moJkgS3tVUWsp+9LF1KueeSTj5cAbE2t/4WNqa/6q30+32fPD5Noq/Z5T96aP+67c5PQfLgDYm1Xm+n4+n+QLT+vX/M2dVsZ9dtNUi06OS71pVsvtsFupaVwIiJflHLYk2bsfxYJ6Zqj4rtNct9f0N1jvl1R7KAROm8zM4XBCkclh0OOR0qp/wsbU1/1Vvp9vs+eHybRV+zyn700f9125yeg+XAGxNp/wsbU1/wBVb6fb7Pnh8m0Vfs8p+9NH/dducnoPlwBsTa+ad07db7+QeXlY3raz1S0+NMyxW93FNJfSSFVjYF4SxySMcoR+BFZN3aa0PDdpd31ldyGPVZGZrqJgu4hAQSRxllIPuCO1V/8AhY2pr/qrfT7fZ88Pk2ir9nlP3po/7rtzk9B8uANibXR/ErVIJFeG206AxkSQBLJMQTfxTIMYDtznqPu4A2JtUXNWVv6uJ2f9eVjV8XWeraBp+sr5GpxW2p3YluGlt5EijwW+Qv8AdfLNwRwQqnqcL59Xef8AC39RjtzFb6Ro9o28yCWC3cMjltzMvzkKxIHIAPC4xsTag+Ld0ixiLw/ocBikaaIxW8imKRs5dMSfK3PUf3U/uLgXMun4j3OXi8R6hDaiFbmXcmwRT+Y3mQoocbEOflUiRsj/AOvWZXVf8LG1Nf8AVW+n2+z54fJtFX7PKfvTR/3XbnJ6D5cAbE237b4sXdtDbouhaJut3Mscgt5EZZCDukXbIArHPVQMbUxjYuC8+34/8ADhqKu6zqf9s6pcXv2S2sjM24wWiFIlOOdqknGeuM9+MVSrQQUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB6P4p/5GfV/+vyb/wBDNU7B7WO6Vr2Ga4t8NujgmETk4OMMVYDBwTxyARxnIueKf+Rn1f8A6/Jv/QzV/QviF4h8MaLPpekatd6ZbzXC3LPZ3EkL7gpUjKMMggjIOfujGOc69DETw74Um8S6VfyW1uwltN8sl3JcKsSIlvPOU8vYWLssD4YHAIwRyCOauf8Ajxuf9wf+hrXoWjfGDXPs99Za9qmoa1ZXFvcqhu7h55IpXs7iBNu98KpNwC3fCjHTB89uf+PG5/3B/wChrSe7K7GLRUttdy2chkhdopcYEiHDL9D29PxNXNbnknktfPkMt0kAErscsTkkAn1ClR+FIZnUUUUAFFFFABRRRQAan/yCbP8A67zf+gx1k1ran/yCbP8A67zf+gx1k1LLCu50z4JeNtX01L610C5e2ddyscKSPoTx+NYHgl7WLxloT3xRbJb+AzmQ4UJ5i7s+2M1+o3hbVdOi+Hvi1JLRHuUFmLWYW5byR5h3YcDCZHHJGenNeFmONrYaUYUktU3d+Svb5n12S5RRzClOrWbdnGNo2T952u7p6L9GflPfWNxpl5La3cL29zE214pBhlNV69l/aumspvikDaeWJRZRfaAmOJCznn32lT+IrxqvTw1V16MaklZtHg5hhlg8VUw8XdRdrhRRRXSeeFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB6P4p/wCRn1f/AK/Jv/QzX0Jqf7IcB8NzXWlazcXOp+R5sFvNGipI+M7C2eM9M/nXz34p/wCRn1f/AK/Jv/QzX3Pp3xe8Ex6fao3inSlZYlBBulyDge9aGSPj7xL8EPGvhDRLnV9X0X7Jp9vt82b7VA+3cwUcK5J5YDgd64K5/wCPG5/3B/6GtfYvx8+JPhbX/hLrthpviDT769l8jy4ILhWdsTxscAegBP4V8c3X/Hjdf7g/9DWjoPqZ+n3EFrcCSeB51A+VUcLhux5U5x6YpLya3lYfZ4ZIupZpZfMZifcAD9O55qpmjNTcqw+imZozRcdh9FMzRmi4WH0UzNGaLhYfqf8AyCbP/rvN/wCgx1k1vTqG0i13AH9/L1/3Y6peUn9xfyqRmdX1f8PdY8Zv4C0yOx8ZvHp89rEskEcETIQg+VH4+YoePmycg96+YfKT+4v5U9WKIyKSqN1UcA1nOnCp8cU/U6aOJr4Zt0JuN+za/IPFFzLeeJNVmnvBqEz3UrNdrjEx3H5xjjB6jHHpWXWj5Sf3F/Kjyk/uL+VWkkrI55Scm5Sd2zOorR8pP7i/lR5Sf3F/KmIzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoAzqK0fKT+4v5UeUn9xfyoA7bxT/AMjPq/8A1+Tf+hmsutTxT/yM+r/9fk3/AKGay61MQqO6/wCPC6/3B/6GtSVHdf8AHhdf7g/9DWk9iluZFtHFJJ+/laKIDJZF3N+AJGfzqXULSO1ki8qVpY5IxIpdNjDJIwRk+nr6U2xt7i4uFFrA9xKvzbEj8zp6rg5H1q5r0ryyWxuIRBeiLE6CMJyCduVHQ7cfpWfQvqZdFFFAwooooAKKKKALkv8AyCLb/rvL/wCgx1Tq5L/yCLb/AK7y/wDoMdbvwuMH/CwNFFwYlBmxG07FYxKVIiLEEEAPs5BGPWqiuaSRMnypsx9a8N6v4bkhj1bS73S3mTzIlvbd4S6/3lDAZHuKZ/YWpfYZL3+z7r7FEqO9x5DeWiuSEJbGAGKsAe5Bx0rsfH0PiCx0WG01TwzF4QsxdtNHZNHcLJcTFcPKv2h3cgBVDFSFOVzk4xqfGG78X2+meGYdZbV4LS40mFZBeLIizyhiW3lsb2GI/vZIAX0FDSUebzS/Bv8AT+tgT1S8n+DR51a6FqV7bPcW+n3VxBHG8zyxQMyrGmA7kgYCruXJ6DIz1qW28L6ze6PPq1vpF9PpUBKzX0Vs7QRnjIZwNo6jqe4r0DxVd+L7L4ReEXmbV4NKkW4iaZ1kWN42IEUZc9UKFtq5xgtgcmtW00fUn8aeDvEmmWlzN4Tt7OxWe9WNntLSJY1W7jlYZVBnziykjO8nHzc3ya29F+er8v6uRz6X9X62toeQ2Gl3uqyeXZWc95JuVNsETOdzMFUYA6liAPUkCobi3ltLiWCeJ4Z4mKSRSKVZGBwQQeQQe1eo+BZPEi/D/wAdyeHo9VOmK8TRtaxyMkfz/OwxkK4jxuYHIXqcV5dcXEt3cSzzyvNPKxeSWRizOxOSSTyST3rN7I06tEdFFFIYUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAdp4p/5GfV/+vyb/ANDNZdanin/kZ9X/AOvyb/0M1l1qYhTLrmxuf9wf+hrT6Zc/8eNz/uD/ANDWhjRh7aNtOoqLF3G7aNtOoosFxu2jbTqKLBcbto206iiwXJrqUQ6Ra7gTmeXp/ux1VtdW+xy+ZGv7wDCsRkqfUe9San/yCbP/AK7zf+gx1k1LSejNIycWpR3N3/hKJR92OJMcptiA2N3ZfQn/AAxjAwf8JRKPuxxJjlNsQGxu7L6E/wCGMYGMKis/Zw7HR9ar/wA7/r+vy7I3f+EolH3Y4kxym2IDY3dl9Cf8MYwMH/CUSj7scSY5TbEBsbuy+hP+GMYGMKij2cOwfWq/87/r+vy7I3f+EolH3Y4kxym2IDY3dl9Cf8MYwMUrjUkuJmkMYQt1Ea4GfXHbPWs+iqUYx1SM51qlRWnK6Ln2xPRqPtiejVToqjEufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigC59sT0aj7Yno1U6KALn2xPRqPtiejVTooAufbE9Go+2J6NVOigD0fxT/wAjPq//AF+Tf+hmsutTxT/yM+r/APX5N/6Gay61MQplz/x43P8AuD/0NafTLn/jxuf9wf8Aoa0MaMWiiipKCiiigAooooAKKKKADU/+QTZ/9d5v/QY6ya1tT/5BNn/13m/9BjrJqWWFFFFIAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA9G8UHPibVz63k3/oZrMrS8SnPiPVT/ANPcv/oZrNrYyCmXP/Hjc/7g/wDQ1p9Muf8Ajxuf9wf+hrSYIxaKKKkoKKKKACiiigAooooANT/5BNn/ANd5v/QY6ya1tT/5BNn/ANd5v/QY6yallhRRRSAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPRvE67PEmrL6Xco/8fNZlanir/kaNY/6/Jv/AEM1l1qZBTLn/jxuf9wf+hrT6Zc/8eNz/uD/ANDWhgjFoooqSgooooAKKKKACiiigA1P/kE2f/Xeb/0GOsmtbU/+QTZ/9d5v/QY6yallhRRRSAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPR/FX/I0ax/1+Tf8AoZrLrU8Vf8jRrH/X5N/6Gay61Mgptxj7Fc55GwdP95adTLn/AI8bn/cH/oa0MEY+U/ut/wB9f/Woyn91v++v/rU2ipKHZT+63/fX/wBajKf3W/76/wDrU2igB2U/ut/31/8AWoyn91v++v8A61NooAdlP7rf99f/AFqMp/db/vr/AOtTaKAHTlLi3ihZWCxuzghucsFB7f7Iqv8AY4PST/vof4VNRSGQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAEP2OD0k/76H+FH2OD0k/76H+FTUUAQ/Y4PST/vof4UfY4PST/vof4VNRQBD9jg9JP++h/hR9jg9JP++h/hU1FAHY+Kv+Ro1j/r8m/wDQzWXWp4q/5GjWP+vyb/0M1l1ZAUy5/wCPG5/3B/6GtPplz/x43P8AuD/0NaGCMWikzRmpLFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAFopM0ZoAWikzRmgBaKTNGaAOy8Vf8jRrH/X5N/6Gay61PFX/I0ax/1+Tf8AoZrLqiAqSL/Vzf7n/swqOpIv9XN/uf8AswoAjoq5o9mmoavY2shZY550iYr1AZgDj35rv9c8FeG3uPGVlpcGrWM/h3zHN5e3kdxDOEmEWwqsMZjZi2VO5uRjHcD0V/X8N/zBau3p+Ox5pRW1B4N1i51jTtKis91/qEUc1tF5qDzEddyHOcDI9SKvaN8M/EWvWVnd2llF9mvZGhtpbi8ggE0gbaY08x13Pnoo5PYUAcvUV1/qG/D+da974c1LTdOS+urR7e2a5kswZCAwmjCl0K53AjcvUd/rWRdf6hvw/nQBn0UUVJQ6KJ5pFjRSzscBR1Jq/L4d1GGBpmtz5ajcWDqePXg1ueG9At5bK3v3kkWYMWBBAC4OO49q6ZdNmltWtIo5WLqUXMW0AEY7AACuv2VOnDnry5dL7o82eJm6nJRjezs9GeWUV13xC8J2fheWyNm8rJOHyspBxtx3wP736VJqXwyvbDwPoniNLu0uRqckkYs4rqFpVwUC7VEhd2O/lQuUx82M15eGxEMXSjWp7P8AzsetODpycJbnG0V02qfDbxFpCQmawWZpbhbPy7K5iupEnb7sMiRMzRyHBwjgEkEY4Na3hv4PatrPjLTdAu7mwsftjMpuo7+2uEQrjcuUlwZBlcx7t2DnGK6TM4OirWqabLpGoTWc7wSSxHDNbXEc8Z4zw8bMrfgTRp1kNQnMPnLFIVPl7+A7f3c9s8/jj1pLXYb00ZVoq/PpElnZNNdH7PIW2xwOvzvzycdgPWqFMRasf4/wq3VSx/j/AAq3VIlhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAGp4q/5GjWP+vyb/0M1l1qeKv+Ro1j/r8m/wDQzWXQAVJF/q5v9z/2YVHT0YJFMWIUbByf94UAW9CuY7PW9PuJm2QxXEcjtgnChgSeK9I174jQeONb8T6Tr2t3FzoF1dT3Wk3115sv2KUMxiIXBdYmU7GUDjKnGVryX7RF/wA9U/76FH2iL/nqn/fQoeqs/P8AG35W0Baary/C/wDmezeGfEPhYeKfB3iS+8QJZLpllDa3VgbWd5xJErIGUqmwoRtYnduGSNpIrj77xFZy6D4Mto7k+dps9xJcKFYeVumDKc45yBnjPSuJ+0Rf89U/76FH2iL/AJ6p/wB9Cmnyz513v+NxNXjy+Vv0Ou8fz6Tq2uavrFhqf2mW91W6cWv2d02wFt0cu49d24jbgEbeetchdf6hvw/nS/aIv+eqf99CormeNoWAkUnjgMPWoilFWRbbk7sp0U3ev94fnRvX+8PzoGdR4R8Qy219p1i/lrb/AGhMyNwVG8HrXrWuX82mWj3MbxiNEYkPHkAhWblt4wDgL0PJHrXz7vX+8Pzo3r/eH514eY5Z/aNWFSU7cqta19PvOnD1lh4yjGO7ub3ijxbdeKpLdriOKJYAQqxA98ZJyfYV2PhrxlpGmeHvBN1Ncobzw3rEt3NprRv5lzE7wsGiYKUyNjZDsvQYzmvMN6/3h+dG9f7w/OvXoU4YeChSVktvvuc826jblrf/ACseua943a0u1XTPGekfY59SiuFfSvDqWs8KoxZJZyLePLKSPlRnBy3P96e38X+FtH8beENakn06fU4L0yarf6Dazw2rxEKquYpETEgO9mEaKpBGBnNeOb1/vD86N6/3h+daJJW/r+thO8r36/1+pd1a1hstRnht72DUYUb5bq2WRY5B1yBIqt7cqOlN06W2gnMlzG0yoMrEOjN2DH0+lVN6/wB4fnRvX+8PzoWgPV3NfUdZXWbcvdoftyHCSxgBWXP3WHbHYj6H1rKpu9f7w/Ojev8AeH50xWLlj/H+FW6pWUyJv3Oo6dTVn7RF/wA9U/76FNCZJRUf2iL/AJ6p/wB9Cj7RF/z1T/voUxElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBJRUf2iL/nqn/fQo+0Rf89U/76FAElFR/aIv+eqf99Cj7RF/z1T/AL6FAElFR/aIv+eqf99Cj7RF/wA9U/76FAElFR/aIv8Anqn/AH0KPtEX/PVP++hQBseKv+Ro1j/r8m/9DNZdanir/kaNY/6/Jv8A0M1l0AFSRf6ub/c/9mFR1JF/q5v9z/2YUAR0UVs6f4R1LVdFk1Ozh+0xRSmJ44+XGADnHcfN2qZTjBXk7Gc6kaavN2MailIKkgjBHY0lUaEkv+rh/wBz/wBmNR1JL/q4f9z/ANmNR0AFFev+C/2bdd8XeBbvXvM+xXTKH0+xlXBul65JJ+UHouevXgYNeS3dpPYXUttcxPBcQuUkikUqyMDggg9DQBWuP+PeX/dP8q5CuvuP+PeX/dP8q5CokXEKKK6vwXr2kaPaXsepWNvdvNc2bo01sspSOOXdKAT0DKMEDqOOlJK7SHJ2TZylFeiwva6XoGs+NLayspJ7vWGstOtrm0ilgt0KmWRvIcFCQrRooKkKCx6hSMPX/E48aWujwTWWlafqMMskUlzZWUFjHKjlNhkESKuVO8bsdMe5Mq7sra6fir/qU7K76a/hoctRW5qFkfBPi9oDcaZrn9nXKt51q63Nnc7SDwSMOh6HI9QRW5qttF4U+Kg/s6G3ksZLiO4tIry1jniNvOqvGDHIrK3ySAcjgjI5ANXBc7il1Ik+RNvocPRXteqBfEmvfEGz1PRtLtvDmi/bfJvrDS7eyNnOjMLZPNijQuXYBNjltwJOMrkcQnwp1NfCsPiG51DR7LTri3lntzNfoWmaMAmFQu796QfuHBGMNtLKGzUrrm6Wv/XnoaNWdvO39fecXRXYaX8NLzVILaNdT02HWLuITWmiyvL9quUK7lKlYzGpYZKq7qxGMD5l3M8NfDm88SWtrINR0/TZb+ZrfTre+eRXvpVwCiFUZV5ZV3Ssi5brw2LtrYi+lzkqK6zQPhlrfiXVdX06zNgbvS43kuEa/hwQud2whiHAwcsuVUcsQOaWL4eSS63qtmNc0hrDTIUnudZiklls1RtgUgpG0jZaRVwEyDnOACaW/wCfyH/w3zOSortLD4V397qWsWz6ppFlbaXHDPPf3d0Y4milK+XIi7fMYEOrYCZGQCAxCmv4z+G+o+BoQ19d2M8q3UlncQWkxke2lQBtrnaF5VgRtLdwcMCAPTV/1/VwWrsjk6K3fA10bTxjoziG2uA11HG0V3bR3ETKzBWBSRWU8E9RweRyAa9J+INr4x0V/Er6n4NstM8ORzTW8M8vhe1sshmZIvKmFurFhwwKtyF680S0Sfe/4W/O4LVtdrfjf/I8ZorotW0HUtP8HaLqFwdPOm3c862xtmgefcqxlxKyZccMmEkORkkKN2TpWLxXXwi1kPZ2gmtNWshFdC3Tz8SR3RcGXG4qfLT5c7flzjJJI9E32/zS/UFrZnF0V03hnwLL4jhhkfVdN0j7TN9ns01B5AbuXj5U2IwUZZRvk2Jk/e4OG6N4Hn1CXURqF/aeHodPnW1uLjU1mKJOxcLERFHIwY+XJ1AA2HJHGXbW39f1t967h0uc3RVjULJ9Nv7m0kZHkt5WiZozlSVJBIPccVpeDPDE3jLxTpuiwSCBruUI0zDIiQcu5HcKoY/hSj71rA9NzForo4rDTfFfi1bKxmsvDWnyuIYJr95mjAHCtIyrIwZuCSAFBJ4VemhrPgODwXqdimt6vZXC/b3t7qxs1nFwkUczRySfPEq4OxtvO7kcDnDWtulxPS/kcZRXr/xL0O90jw/M2rWWimzvp1/4Ru70WztovtMQPzvviUOyhCikTEtuYd1fE3i34fax4HsNS0jSNO0O7Wxs9+r3U01jd37NtHmMkLs0sEaFsBkRWI+diQV2zfS/9fPtbr2Ktql/Xy7+R41RXV+HtCtfE/hbWo4LYRaxpEJ1FZkZibm3DKsqMpJUFAwcFQOA4O75cLpNtb6v8PdciFvENQ0qeK/SdYx5jQORDIrMBkgO0JAJwMtjqab0/r+vP7mJa/1/Xl95ydFeleH/ABLc6T8KJ5rbTtFnu4NXhtYprvQ7O6l8t4pnZS0kTM2WVcZJIxgYHFX/ABh8NIb8T3kdxpvh7WLHRY9T1nRZlmWRJWcqRHGkbCMkGFjGSoQy9FUfKS91vy/yv+W4R963n/nb8zyaiuotfBCSat4bsrjXLCD+2VjkLhJ2NorthRIPL5J7BNw6HIBzXSeG9AsvDXxustDtptP8S2bX/wBiIktWmQqzlChSaNcyAcZC4BOVPQ0dl3v+Ar9fT8TzOiut1f4a6npdlptxFc2Opve3ZsDbWExklguQFPkuCAC3zjlCy9RnIov/AIdz22nz3VnrGk6w1o6JfQ2M0mbMs2wF3kRY2Xf8u+NnUHHOCCT+v6+9feh/1/X9dDkqK7zXvg5q/huy1OW71DSWu9Pt4rySwt7rzZmt5NgEqlVKFQZFH3sn7wBXDHY8CwajrHhnVnj8L2d34XsNNnN1P/ZsT3Tz+X99J9hlykjxsQjBUQDcACdx0b7f1/wPXQFq0u/9f15HldFd/wCAvElxPqGg+HbCx0aGOacJdXl/o9peSHc+XkLTROVVE7A4+UnqTXJeJdTh1rxDqV/b20Nlb3NzJLFbW8axxxIWJVVVQAABgcCh7gjNorpPA9zfR6mYNI0q21TWLjCQC7s47qONQC0jeXKGToOWYEKoY8dR0PjqaPwd8Q9S+06HbWmrWtvChtJLJPsgu/LQSyiFgEMZO9lXaUOVIG3ih6WDe551RXofjTUYEg8DeIW0zTbfVZ7Y3F3aW9nFFbXAjuHWN2gUBBvCEEBQCFzjk1jeMfDUcPj6607TDFFaXcqT2RuJUgjWGZVki3O5CqAjqMkgcU0m3Zd2vu/zDTc5Wiu91/4P6j4fi1kSaxo93eaNKF1CxtJ3eaCMvsExBQKyZK5Ckuu9dyrziHU/hdJpeuf2dJ4i0eRP7MGq/boxdeR5RUOq5MAbcykY+XGSASGyBN1a/wDW1x26f12/VfecRRXYWngixn+G9x4lk8QWdvdpeC1TTpI597fIzYysRXc3BGWCgA5OTgdDpvguXx74J8JiJ9G0V/tt1p6310gg+0SHyDFGzIhaRyWf5mBCg8soxVW1a66fj/w6JurX6f5f0zy6iuk0vwRLdJczalqmn+HrSCdrU3OomVleZeWjRYY5HYgEEsF2jIyQWUHUtPhBrtzNrayS6dZx6OI5LuW4vEAETldsqgZZoyrhtwGCCAMsVUq/UZw9FbHivwzP4R1ltPnuLa8/dRTxXVmzNDNHIgdHUsAcFWHUAjkEcVQ03TrjV7+3srSPzbmdxHGpYKCT6k4AHqScDqaFqGxWorq9R8A/YLeyvE1/Sr3Sbi5+xy6nbC4MNrLgNtkBhEn3TkFEYHBwTg4seL/hpJ4MtrqS71/SbiSKVI4YLb7QWulaKOXzIi0KqUCyryxHtnjIBxlFdZ/wrm8OkXF0mo6fLqFtbC9n0dGkN3FBwfMPyeXwGViocuASSow2Lum+KdCtfDEFnNplrLfJp17A0zWaM5mlkUxtuPJKqDhv4c8daHpfy/r/AIHqC1t5v+v8/Q4aiivXvA8fiLUPhZI3hzwvaa7f2uqiFpI/DVtqE6wtGznezQOxG7oW6cAHHFPo32/zt+ouqXf/ACv+h5DRXZ65o+oa94+t9H1RNJ8N6oxjtrqSaOOwtIHxndIqIqx4BAbC9QfWuTvLU2d5Pb+ZHMYpGj8yFt6Pg4yp7g9jSWoyCivX9GtbPS/jX4W8OrpenXUVp9l0u8iuLOOUTTPg3BcMCGcO7oGOSAowRgVx2ufDe/0vSl1KC80/VYPtYsblNOmMjWdwRlY5MqAc4bDoWQlWAbIo9P61/XT77Cv3/r/htTkaK6nxX8P7nwpaySvqVhqD21z9ivYbTzt9ncYY+W/mRoGPyOMxl1+Q88jMq/De8bSp7g6jpy6lBaG/fRi8n2sW4AYyH5PLGFO7YXD4520r6N/13/LX012H5f1/XT1ORor0zWvDUfi+30bUGn0fwxbRaHHNdXL2skVuW+0zRICIInJkIUckZYISScE1z1l4B+3LoUia/pa2+rXM1mk7Lc7YJY9nyyAQ7vm8yPBUMPm5xg4qz5nFd2vudhXVr/1tc5Siu2s/hTfz2WrX1zq2j6dYaXffYLq4ubsko/z/ADeUitLtJTA+TJzwCFcrm6n4D1LS/GcHhpzDc3lxNDHbzWj+ZDcLLtMUkbcZVgykdDzyAcilH3mkuv6jfu3b6HN0V6BeeEz8Q/iHrdj4a/sy0s7RZfs/mzxWySQwIQGGcb3ZY9xIB5YsxADMGW/wiubzU9At7fxFodxZ61M9rbanHLObdblSAYJP3W9H+ZMEptIdSGxyBe9ZrqD929+n9f15anBUV0N14Oe107ULsanZzG1v/wCz0t0ScS3L8/NGGiA28chirDI+XJFW9W+HV1pWkXt4NT028uNPZF1DT7WR2ns9zbRvJQRt82FPlu+CQDjmle/9f13HbWxydFdhP8NLyG0u9up6bPq9nC1zdaJE8puoI1GXLHy/KJUcsqyFl5yAVYDpfhN4PEOtQy6hNocr3dhcSf2PqSCS4MBhZkmQOhRWyFKjeJMfMF2nJb0v/X9f8B9hLX+v6/prueVUV03hnwLL4jhhkfVdN0j7TN9ns01B5AbuXj5U2IwUZZRvk2Jk/e4OF8GeGft/j6x0jVImgiguWN+jjBiiiy8+fTCo+fpT62YujaOYorsvCGhWvxM+Iotbq7tfD9tfzyTEJCwjQct5caxoQvHA4AAH0Bxrbw2b/X302y1Czu4U3M2oqZI7cRqNzSHzEVwoGeq7jjABJAMrValPRmNRXUaj8P7611DRbexurXW4NZfyrC8sDIIp5N+wpiREdWDEAhlHUEZBBNPxJ4Zi0BLWS31rT9bgnLr5unidRG643KyzRxsD8wPQg560xGHRXYeOfBFj4SsNCntfEFnq02oWaXUkEEc6sm4tgjfEq7cAD7xbIJwBiuPo6tdtA6J9wor0Gw+C2qXsWj7tZ0G2utZtzNptq99ve6bc6iJWjVkVyUwN7Ku5gudwZVym+Hk6+HNJ1catp7jUL86d9jVbgz28oxu8weVtGAyn5WYndwDhsOzvb+t7fmK/X+u/9fM5Oir+u6WNE1i808XlvqH2aQxG5tN/lSEcErvVWxn1AqhUppq6Kas7MKKKKYgooooAKKKKACiiigAooooA9H8Vf8jRrH/X5N/6Gay60/E7bvEurEd7uY/+PmsytTIKki/1c3+5/wCzCo6ki/1c3+5/7MKAI69m+DP/ACK91/1+N/6AleM1s6f4u1LStFk0yzm+zRSymV5I+HOQBjPYfL2rjxdGVenyR7nm4/DSxVH2UO6O8+KH/CM4k3/8hnt9lxnP/TTt/WvKqUksSSck9zSVpQo+wgoXubYXD/VaSp8zfr+nkSS/6uH/AHP/AGY0+xu2sL23uUSOR4ZFkCTIHRiDnDKeCPUGmS/6uH/c/wDZjUddB2H0L4e+Imu+Lvhn8TfEF5eNFfxtZG3NuSi2wWQlVjGflA/PucmvGfG3jW/8fa0NV1NLdbwwpC728Qj8zaMb2x1Y9z9AMAAUmkeNdT0Tw3rGhWrxiw1by/tKsmWOw5XB7c1g0AR3H/HvL/un+VchXX3H/HvL/un+VchUSLiFFFFSUdt4X1PStW8GX/hfVtRi0ZheJqNhqFxFLJCsm0pLHJ5au4DLtIKoeUweDkYusaJpemXFpBbeIrXVjI37+5tLedYIVyAOZUR2b7xICYAxgsSQMOin1v8A12/IOljR8Q2Nhpmt3lrpmprrOnxSFYL9YHhE69m2P8y/Q11S6lpfiBfBL3Wr2+nXlijWl7LdRTMqRxSGSFyY42Jyr+WAoJHljOBzXCUURbjZ9tfmKSUk130O7+Mfiq58UeM76X/hLJvFWlm4mnsXeW5KW0buSIwk6qUIAXIUbeBgnFM8SvpUvw48LwW2vWV3qNm07XFhHFcCVPNZWHzNEIzt24OHPJGM9a4eiojHljyotvmd2esr4g8P6l4k8M+MpNet7G50qCx+1aQ8Nx9pmktVRMQssbRYdY1wWdcEnI4yb2gyWdt4T0fUtY1TS9M1CS8udR0hNTjvV+zfOqiRDBFL5iF0c7H2kNGhBKl1fxit3QfHfiXwrbSW2i+IdV0e3kfzHhsL2WBGbGMkIwBOABn2q+7/AK139CFpZen4KyOo8HWVpoHiHxdY+INestIuhZ3Wm+ZdR3EglmYlcjyonOAVySwB5HB5xQ+HJ0G2k1mXUdR0yy1OOFRpk+r2ctzZ7/MG9mjSOTJ2Z2h0ZeTkZxjiiSxJJyTySaSkuj8rfn/mN6383f8AL/I9l8Waz4f16+8UXS+MNPmk1PStPt43ltbtGaaNoPM3AQEDHkseDjDLjuBm/ErWtBvtG19NM1+11OW88RtqEUUMFwjGFom+Y+ZGoGGbbjOeOmOa8sopPVcv9bp/oPrf+trG14M+yr4r0mS9v4NMtIrlJZLq4WRkQKd3IjRmJOMDCnkjOBk1a8eXFt/wmGuvperR6np95dSTrPbLLGkis5cBlkVWyMjIIxkcE9a5uim9beV/xt/kJaX87fhf/M7fU20o/CjR7SLX7GfVYNRubuTTkiuRKqSxwIBuMQjJBhYnD9CMEnIBo7aUvws121m1+xt9Uub61uodOkiuTK6wpOrDcsRjBJmXGX7HOOM8RRQ9U13/AEt/kC0SXb/g/wCZ6r4c8YvL4A0zSrPx/ceC7iyknjurUy3ixXkLtvVlFujAsC0ikPt4289cZvw91aw0i61oweIbHS7GaSOJtO8Q2009vqNrliVkWCKTDqVjII2lSxKsCM155RTvrf8Ar+v82K2ljS8SvpsniLU20aN4tIa5kNpHISWWHcdgJPJ4x15rb+FHiC28M+P9Kvb1xFZMZLaeVs4jjmjaJnOOcAOTxzxXJUVMVZWeo3qdFY+F4LXxa2keItQi0KG3kIuLiVJJBgc/J5aOTuH3Tjacg5xXY634l8PeJNS8MeL9Vvbe71CG4hi1fQvLmeSaCGQLGVZk8s5hVVYF8kqD1Y48xnuZrkoZpXlKII13sTtUdFGegHpUVUm1byBpO/mesah4rt9M0HxPDc+LrPxbFqzrPbWMMd2HtrpXQpcfv4VRNsatGdjMSCq8ryEn8QaJB4r1rxtF4gtJ5dSgvG/sPybkXQluYXRkZjF5WxWkJyJCSqjucDyiiptpbyt+g763+Z3fw7vl8N6F4u1i4AEVxpcuk2wbH76eYoCFB67U3McdPlz94Zyvh7q9npPiLZqU32fS762nsLuQqWCJLGyhyqgk7GKPgDPyDFc89zNJDHC8rtDFkpGzEqmeuB2zgVFTer17W+Wv+bFsred/np/kj1Dwr4kHhn4WapDpXjtdC1y5vo7o2Vm17DNLFHHKhjZ44tmWLKQC+3HUqRiud+GJu4vF1jcJZzXenvKtnf7VOzyJ8xurN0XKl8E9xntXI1e0/W9R0mC8hsdQurKG8iMNzHbzNGs8Z6o4B+ZfY8U/tOT/AK0sK3u8q/q7ubF74gtZfH8Wpxh1023vIvJXGWW3iKrGPqERfxrprCbQrP41Qas/ijTm0c6g2otfJBdlUUylvLKmAPvx6Lt5+9XmdFLtfpf8bf5De7t1/S/+Z6l4X1zR/A2k6Tex6/Y6pfaX4ijv/sFvDch5oUwpZWeJVGdu4AsDg8gHiqhk0DwtB4lbTvElnqya3bmxt4I4LqN7aNp45PMn3xKvyrHjEbP8xGMgZPnFFD1d3/WiX5IFpt/Wra/FnsOs3fhu88ReJrmLxjpRgvNCt7OBzbXw3zKkKsuPs+RjyCcnAw6c/e2814LOneDL7T/E48U6ZPdWqmX+yIIbv7S5KkGEs0Ai5zhjvIwTjccA8HRQ9f69f8wWmn9dF+h03gvVrTQY9cv5bhY78afJb2MexizySkRuQQMLtiaU5J64xntnaB4lu/DU0stpDp8zSrtYahp1veKBnPCzRuFPuADWVRR1v/X9ah0sbekaZa+JLu8lv9e0vQGLeZm7gnCSFiSQi28LhQPTCgZGPbqpbjQvFfibSbTV/ENtb6Vo2mpZnUJYrjbfGMsVVAkLOiksEDMgIRd2M/JXnVFPsv66r9fQO7/r+tDq/HgtZrlLtfENhr11MdgTS4riOC0hRQqRgTxRnGOABkALySTTfEWq2mu6D4WZJt+rWkD6fcw7G3FEkLQvnGDlZNgAOR5XPUVy1WNP1C60m9gvLG5ms7uBxJFcW8hSSNh0KsOQfcU4Plab6O4PyPV/HwtPBniv4gXQ1ex1C61aS6sYbKBZDLCXuA0hlDIAm0Ky9TlipXcuWrE1nU5LD4YWlhqFlPaa6LiTTledSjGyVln2FTyCJXGD0xx2NcXrfiDVPEt99t1jUrzVbzaE+0X07zSbR0G5iTgelM1XW9R16aKbU7+61GaKJYY5LuZpWSNfuoCxOFHYdBWSVopPy/D+n97Hs9P6/rT7kdLpd1pt98NNQ0qfVrbTtQh1Bb+KG5jmP2lRCy7EMcbANnH3yo569a19IbQl0HwSs3inTre5s9VmuruB7e7LW8b+UQWKwEMf3JBCluWXtuK+bUVqpWlzrfT8LL9CHFOPK9tfx/4c9S1i98P+JtIvdBbxLYWLWWtXWoWepXFvdfZ7qGdUDABImkVwY14ZAME88DM954j0PWdH8VQnXbSzcaRYaXZLcQ3Je9NsYizrtiYKG8pgocqeVyByR5NRWaiklHtb8Fb8jRu7v6/i7/mdp4+XSbrVdDWy8QWWpW62FtaTz2sNwBA0aKjEiWJCR1I2g8Dsad4Z1LR/AnxTtri31eXU9DtbhoxqtrC8EjQupQyojfMrAMSB6jr3riaKpaO/q/vItpbyS+5WPQPFsyeILuyj1f4kHxPO0vlx39w19LBZw87i/nRCTJO3Cxqw4OT0q14x1LQvFPhWJV163j1Dw9I2nadDLHcFr7TxyjA+VtV95c4crw+MDaoPmtFK2lv6/rf72VfW/wDX9bfcj1vx94xh8WWU903j+9n0eeCOVfCrS3ZeG42AbArJ5ARZMtkPnb0GeK8koop9WxdEgr0PRrXQ9R+GK6Zc+LtJ0nUZNT+2G3vIL1iiCNo8Ford1yTgjBPB5IPFeeUUbprv+jv+gdU+3+Vv1OrvNG0J/E2k2UviyO5s5lQX+tR21xJFAdxHyRuiSOFQJ2GTwOOar+EG0nTfHFhNqN2kmk2dz57zCJyJ1jJZVC4JG8qFGRxu5wAa5yimm07r+v8Ahv8Ah7iaTTT/AK/4c6zwX4mitvifpGv6vOY4v7US7upyrPtBk3O2BknqTxk/Wtb7Tofhvw/e6J/b1rrkWsX9rLc3Glw3Ci2giMm7/XxRkufMGMAjCnPUV57RSjaKSS2/4H+Q3d3be/8Awf8AM9j8da14duPA+s6NpfiXRJLaPU4bvTdP07T7qAeQqyphneBS82HQlpGPC/fOAK53xtH4W126uPEdrr6Bru3WRtDW2mW6iuSoVl3lPKMYYbtwfO0gbQenn1FK2/8AXSw77Htd7qvhnW/Aej+E7/xhpCwWVg01teRWd7m2vfNdikmLcF45EcLn5ipjyOOH5rw1PoI0fSYL3xJaWT6LrU96wNtcObuJltwpg2x4yfJbiQx9V98ec0Vak1NzW7d/x/pehFvd5en/AALf8H1PW7rR7HxJpvj5rPX9PSxl1+1nt9QuVmigmDLdsFyY8q2G6MAPlIBPy7s6Lxjpdt4vTURdq0ehaKLLTpFhcfa7hIfKRxxlRvdpAW2nagBw3FcbaeMNe0/RJ9Gtdb1G20ifJl0+G7kS3kzjO6MHac4GcjtWPWfKkuVbWX4R5bmjld8z3/4NzsvhPaLfeLpIXmW2jfTNRDzujMkS/YpsuwUFsDqcAn0B6VNqm7T/AA9p/hXSruLW9QF9LqUsulK8iofKVVVG2gkgI7NgEAFecggc3oHinWvClxJcaJq9/o88ieW8thcvAzrnOCUIJGQDioLXWdQsdVXU7a+ubfUlkMy3kUzLMHJyWDg5z75zVt3a9Pydyf6/Cx3vjzxdbp4s8P3kdn5bweRq2oWxxh72URyTEegYKnB6cg1meL9P8MWN/faro/iNNXW4nE1lZJbTRTQAsHIuC6BPlGV/ds2TzkDrxtzczXtzLcXErz3ErmSSWVizOxOSxJ5JJ5yaipLSzWlv+B/kH/A/D/h2euan4k8PxeNtY8d2euW07ahHdSLoXk3K3STXELoyu3l+VsV5CSRKSVHAycC1pGq+Er3xlpXiqbxTZ6Sp01La502ezumnhnW1NvkFImQxkhXyG3ANjbkYPjNFKySsv63/AMw8z1jRPFpHgew0aw+IcvhKWwmuIbmFJL5IL+F23JIghjOW5dSJAvG33xymhavpWh2Hiye2nkFxc2/2DT4ZkPmmOSQeZIxUbQRGpUjPPm8ZANclRRv91v6/rqG333/U6f4aaxZ6D460i+1Cb7NZxSkSzFWYRhlK7iFBJAzk4BPoDWv4A1ez8E+MNQhHiQW8FzYy2kWv6X9oRbeRlDJIMosu0Oqq2FzjdgHjPA0VX9feK39eh3GuXkN94q0efUvHFzr14Z0+1a8j3Mi2sQYbShmRZiyfM3C4+7tyc1P8UdZ03W4dMuPt+maz4kZ5m1HVNJgngjulO3y2kWWKP97nzNzKuGBUklsmuAoqeliutzsvG11pusaF4avLTVraW6ttPisJ9N8uZZ42RnJckx+WVORjDk89OuMO403TI/DVnfRaws2rSzvHNpX2Z1MMYA2yeYflbccjaORgevGTRTerb7u/3u4loku2n4WPWLXTrKw0z4da/f6xaWUOnWn2mSxkWT7TMqX9ww8oBCrbsFR8wwRltowTU8G+IZ7W08TanqlhILOdDq9jKEKxpfJLsiZCeCAZXUgen+zXFat4w17X7C1sdT1vUdSsrXAt7a7u5JY4cDA2KxIXjjjtVWTW9Rl0iLSn1C6fS4pTNHZNMxhSQjBcJnaGI4zjNEvebfr+Lv8A5fcC6fK/y/p/eUicnJ5NJRRQAUUUUAFFFFABRRRQAUUUUAFFFFAHfas5k1W8c9Wmc/8AjxqpVrVF26ndg9pnH/jxqrWpEviYVJF/q5v9z/2YVHUkX+rm/wBz/wBmFBJHRRThGxGQpI9hQA2inGNgMlSB7im0ASS/6uH/AHP/AGY1HUkv+rh/3P8A2Y1HQAUVvaR4K1PW/Desa7apGbDSfL+0sz4YbzhcDvzWDQBHcf8AHvL/ALp/lXIV19x/x7y/7p/lXIVEi4hXU6F4E/ty3tXOvaXYz3MUs6W1yLgyeXHv3MdkTKOI2OM5OOlctXS/D5ifEgBJIFlege3+jS1hVbUG4vZN/gehgo054iFOpG6k0uvVrt5GdruhrozWpi1G01SC4jMiT2fmBeGKlSJERgcr6dCD3rLrp/hqlpP410yC+sIdRtppNjRT7sDvuGCASMfxAj1BqxpOpLr/AImtJIdC06NLW1kVIVAjhQIrss0xYMJNmQTuB3hACDnlc7i2nrZXvp5/5Giw8KyjUi1HmlyqKu9fdu+umt7avpqchRXomq+H7TVvFHhZEe1vhqFr5k7afb/ZYrh1llXCIFXbkIq/dUnrjJrCfVh4qjtbKfTLO0YXkaJe2VskAhibKmNgqjf2IZyW+U8nJojU5tl6/fb+v89Aq4P2V+aXp1vopdG0tGtrq/W2pzSLvdVyFycZY4ArR8RaDJ4c1M2UlzBd/uo5lntixjdHQOpG5VPRh1ArrPGd7oqWuoaRZ2cktzaTbIx/ZcNo1mEYq+6VHd5geh8zBzg5HIOzJdWmqeI7XQLrTbNrS50WAy3TRj7Qki2SyLKsp5XbsA2g7SM5BzmsfbtrnS01fy0f9eflqdyy2HNKg5rmvFJ9E22raednfdLpf3TyeivSfDunQXXh1LS6h06xSbTbu4SKSBZry7kRZWWZZNm6FBsUbd4zsJAIZqwrK7PhXw/peoQ2FldyX8svmS3tslwNkZUeUquCF65LAbvmGCO+vtbycUtf+H/yf/D6HG8DywjVlL3WrvTVfD0v/eW9r7rSzeMdCf8A4R06uLq3aNblbZrYM3nKWVmViMbcHY3fPHTBBOZXpfgzTLXVLTW8QLaNDqkE9npE/wA5ncJcFLbLrgnHHzD5sYxlgK4HV9Um1i9a4nitoZCNuy1tY7dBj/YjVR+OM0Qm5TlHtb8Uv+CLEYaNKhTqp/FdabO0mm9dVpbS33FKrWpaZcaTdG3ukWOcAFow6sUyOjYJ2sO6nkHggGug+F1rDeePdISdQ6JI0wRujOiM6KfYsoH41H4LuYptevbi+srfVGNleT7bwMy+YsLuGwrDJyO/r64Icp8rfkr/AJ/5MilhlUhBt2c5cq7K1rt9ftK1vM5mivXY9O07xZMlhLp9hpscsel3Es9rbpG/mTNGkpBAG1SJPuDCggEAHOecMya/beJLC70+xs/7Mt2ntGtLWOF4SkqJsZwN0gKsR87McgHOc5zVe/Tb/gf5nXPLHC1p3vtpu9dH22+99rtcLTxE5iaQIxjUhS+OATnAz6nB/I13N9FHe+CGbS4rGWG2toTe20tpFHe2sm5QZhLt3yxuT2Y7fMAIACk17LWbi2+Fd5bJHaGNtTSMtJZwu+GikJw5UsDxwQcjsRmr9o7NpbNL72v8zD6nFTUZS0cXK6V9k3bfyt3T0aTRxdFFdZ8PDYG71UahpcGpxpp1xMomZ1KMkZI24OOfUgkdsHmtJy5IuXY4sPS9vVjSvbmaV35+hydFd14furHV7zW/EGoW1vYraQw7YbDTY54YmYrHv8h3VD05ySNz5x0phXTtd8Q3F/aabvtrbT5LkxyQC3ju5I15fyoyVRc4JRWI+VuQDgZ+1tutlr91ztWB5oxcZr3nZeava9tWtfL53snxFFdnpMkXjjXdCgvdMhgYzPHNPY2yQLcqAGWPy4wihhyMggkOvoDUuta5o2omwNrp66i0FyGklk0yPT4/KPAhdIJDv5GQ5YN1GWzw1NuSjbX+v66EPCR9nKqp+70vpfRN6b6X6Jr5anD08xOIlkKMI2JUPjgkYyAfbI/MV6H40lsZ08X2VvpFlYw6ZqgFq8EKrKo8yRXBfGWU8HaeF2gAAVm63rNw/wANvDloY7TymmulLCzhEnymPGJAu4Hnk5575xUQrOaTS3/yubVsDGhKpGU78qb0XVT5LataX1v26dDi6KK6yyuz4V8P6XqENhZXcl/LL5kt7bJcDZGVHlKrgheuSwG75hgjvvJ226nn0qaqNuTskrvr1S/No5OtLw7oj+I9ZtdNjube0kuXEaS3RYJuJwo+VWPJIHA784GTXUeGhHA+r3SWNjpFt9rRBc6tEt2tshLn7OsTxuXc4HzYBGzkqGNR22nw6V8ZoLO2XZbwa6kcaj+FROAB+ArF1NXHZ2/y/wA1/wANa/dHBqMYVW7pySa26teTs+V62Xa900uSgsvN1BbWSeK3HmbGmlJ2JzyxwCcD2BPoDU2u6RLoGs3umzvHLNaytC7xElGIOMjIBx9QKgv/APj/ALj/AK6t/Otz4kf8j7r/AP1+y/8AoRq1J80V3T/T/MxnSgqVRpaxkl8nzf5I5utXWvD8mi2+mztdW11HfQeejW5Y7cMyFW3KOQykcZHoTWVXSeJf+Ra8Jf8AXlN/6VTU5Npxt1f6N/oZ0YRnTqtrVJNf+BRX5M5uivSb3ToJfCGpwzw6dYzWen29zBYRQK93GxeINLLOEB+cOxEZdiu8AgbVqlocUd94Pe306Kxlv0t7iS7sry0i8+ZAGInt52Ut8gHMasD+7JAbLYz9to3bZ/8AB/rp5nb/AGc1OMObdX21ve1rXvfy0bXS+hwyRPIrsqMyoNzkDIUZAyfTkgfiKsWGl3Opi4+yxiVoIjM6b1DbB94qpOWwOSBkgAnoCa6nwbrNxpnhHxYIY7Rx5MDf6RZwzdZlX+NTxg9Ox5681ieDbiW18W6LLD/rFvIcDGc/OBjHfPTFaKUpOSXT/I5fY04+ycm3zavy95rR6327IxqK6LV2g8LePr821rbXttYajKIre6TzIZFSQhVdeNwwBkd6w7u4+13c04ijgErs/lQjCJk5wo7AdqIT50pJaNXMq1H2MpQk/ei2vu6kNFFFaHMFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB3+sHOr3x/6bv8A+hGqdX9fj8rXdST+7cyD/wAeNUK2e5juFSRf6ub/AHP/AGYVHUkX+rm/3P8A2YUhkddxoP8AyCLb6H+Zrh63tP8AEy2NnFAbcuUGNwbGefpSauNG1r3/ACCLn6D+Yrh63tQ8TLfWcsAtyhcY3Fs45+lYNCBu5JL/AKuH/c/9mNPsbRr+9t7ZHjjeaRYw8zhEUk4yzHgD1Jpkv+rh/wBz/wBmNR0xH0L4e+Heu+Efhn8TfD95ZtLfyNZC3FuC63IaQhWjOPmB/PscGvGfG3gq/wDAOtDStTe3a8EKTOlvKJPL3DOxsdGHcfQjIINegeC/2ktd8I+BbvQfL+23SqE0++lbJtV6YII+YDquenTkYFeS3d3Pf3UtzcyvPcTOXklkYszsTkkk9TQBWuP+PeX/AHT/ACrkK6+4/wCPeX/dP8q5CokXEK1fD3ifUPC129zpzW6TuhQvPaRTkAgggeYrYyCQcYyDisqioaUlZmsKk6UlOm2mtmtGauk+Jb/Q9ZOqWRt4r0lmDNaROiEnJ2oylV9sAY7YpbDxRqGl6vNqVq8ENzMrxyKtrF5LI4wymLbs2kHptxWTRU8kX08vl2NFiK0bWm9HdavR9/Xz3N3UvG2sao9g808MUlg261e1tYrdoedwCmNVIAOSB0BJwKi13xbqfiNgb2SD/WGUi2tYrcO56uwjVQze5yeT61j0UKEFay2Kliq801Ko3e19Xrba/e3Q3dY8a6vr1u8V5NA/mYMssVpDFLNjp5kiIHk5APzE8gHqM0tz421a708WckltsEK2/nJZQJcGNVChTMEEhG0BTluRwcisGil7OFrWQ3i8Q25OpK703ex01j8Rte061toIZ7UpbQm3jeawt5ZBEd2Yy7Rlih3N8pJHPSqul+NNW0ezmtLeWA2sk32jyLi0hnRJMY3oHQhGwcZXHQegrDoo9nDX3VqP65iVy/vJe7tq9NLadtNPTQ3bLxtq1hYtaRSWxjacXLPLZQSSmUEkOZGQvkEnv3I7mqeva9eeJNRe+vzA11J994LaOAOSSSzCNVBYknLEZPrWdRTUIp3S1Ilia04ezlNuPa7t93zf3lnTdRn0jULa+tX8u5tpFljfGcMpyOO/StQeJP7M1m5v9Ghjs1uYnR4J4I50jDjDogcMNvUA4zg4yeScKim4qW4oVqlNWg7a3Xk11T6f12R0Nz491q7tJbZ57dYpYYrdvKsoI22RHMYDKgIwccggnAznAqLVvGeq63bPDdy25EhDSyQ2cMUsxHP7yREDSc4J3E5IBPIzWHRU+zhvZGjxeIkuV1JNbbvbXT8X97Nu58Y6pd6Z9gke1EHlJAXjsoI5njQAKrSqgdgNq8Fj0HpVfT/EV7pmnXdhC0DWl0QZI57aKbDAEBlLqSjYY/MuD71mUU+SNmrEfWKzkp87utE7vbsFaugeJ7/wzJcPYG2DTxmKT7RaQ3GUPVcSK2Ac84696yqKppSVnsZQqTpSU6baa6rRmnpHiK/0K8mubOSJHnRo5Y5II5IpEJyVaNlKEZAOCOMDHSpo/F+rQ65Bq8N0tvfQcRGCFI4415+VY1UIFOTlduDuOQcmsaip5IvVo0jiK0Uoxm0k77vfv6+ZrXfinUry/tLwzR289oweD7HBHbpEwOdypGqqDkDJxk4GasXvjbVdQuYJpTZBoZfPCQ6fbxRu/wDekRYwsh5P3wcZPqawaKOSOmmxX1mvr77131etu50V5491i/j1NJ2sXGpNvumGm2ytI394MI8qe+VI5JPUk1QXxFeroh0ktA9jvMirJbRPIhOM7JCpdM7RkKQDWZRSVOCVkkOWKrzfNKo29Vu9nq/v6hW3o/jHVdDsJLG1mha0eUTeTc2sVwqSAY3oJFbY2O64PA9BWJRVuKkrNXMadSdKXPTk0+6djc0vxnq2j29zBBPDLFcTC4kW7tYrn96AQJB5ittb5j8wwaX/AITXVj4kGvGS2bVd2/zmsoCu/wDv7Cm3dnndjOec5rCoqfZwveyNvrWIUVD2jsndK70e9153bfzL8utXM2rnU3S2NyXEhX7JEISf+uW3Zj224NO17X7zxLqUl/ftC91J994beOEMfUhFUE89cZNZ1FPlirabGbrVZKUXJ2bu9d33fd+YVr6t4p1DWtPs7G6+y/Z7NdsAhsoYWUc8bkQMQSSTknJJPXmsiim0nuiY1JwTjGTSej8/U6iX4k6/PbywyT2kizQLbTM+nWxeaNQAod/L3ORtXBYkggEHNUrbxjqlppSafE9qsKRvEkhsoDOiMWLKsxTzADubo38R9axKKj2cNuVHQ8ZiW7urK/qzS0XxDe6A1wbRoStwnlyx3NtHcRuoIYZSRWXIIBBxkU/w9q0eiakuomMy3dviS1XA2CUEbWb2XqAOpAzxmsqiqcU7+ZlGtUhy2fw6rsvkXNN1e70nVoNStpdt9BKJo5XUSYcHIYhgQeeeRUF1cyXlzNcSkNLK5kchQoJJyeBwPoKiop2V7mbnNx5W9N/n3CiiimQFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB6P4q/5GjWP+vyb/wBDNZdanir/AJGjWP8Ar8m/9DNZdamQVJF/q5v9z/2YVHUkX+rm/wBz/wBmFAEdFFFABRRRQBJL/q4f9z/2Y1HUkv8Aq4f9z/2Y060s7i/mEVtBJcSkZ2RIWbH0FAENFaf/AAi+s/8AQJvv/AZ/8Kr3mk32nKrXdlcWqscKZomQE+2RQBQuP+PeX/dP8q5CuvuP+PeX/dP8q5CokXEKKKKkoK7P4YfaJ9T1K1tdPt9SuJLCeSGCawiu2MqISmxXRjnPYde+a4yup8BPp8Vxqjahq1tpayWE9tGbiOZ97yIVGPLRsAHGc468ZrKtrTl6M78vfLi6TbsuZX1S0vrq9NibxYuvRWNrb67ottpU0826DOlw2EuFGGztjQlSXHJ4yprI8U6Xe6RqaW9/9k88W8LD7EYzGUKAqd0fyscYywzk85J5rNYlmWAzgwq52sS2wZwCwGM84HbPFdD49ewmvtPew1W21REsbe3c28cybGjiVDnzI04JBIxnjrioScHFW3v0/q36m1SUa8KlRyd1y2vJN+fZy12tsg8WtHPovhe4W2treSWycP8AZ4Vj37Z5EBbaPmO1QNxyTjkmoV8F3L6bLOl7ZveRW/2uTTVZzcLDgHefl2cKQxXfuA5I4OLHig6e3hzw5Ha6va31xa27xTwQxzKyFpZJOrxqpADgHBPOeo5rb8VeJI9fsTM3i+6fTZII2Ph4yXBZJggG0Ar5O3eN2d2Qp6Z4qOaSVorq+nnp/X4o65U6FScpVJJtRh1X8qvrdK6fq/7rPO66rwrr2laVbWyX1jb3Lpfid2ltlkLReUy7ST1G4g7emRntXK0V0TipxcWePQrSw9RVIbrudZpC6jceGUbTtMivZo7lo2ZdNjncJtBGSUJ6k8msq6s5tQ18Wlx9k065JEcrOFghRgOSQAAvTnA61s6Z4cj1XwpAn9taRaSvcNN5V1dbHUY24IxweM/QioZPBivqlvC+t6a0Lgefei+iZVPOcKWDHAwOnWvqquGr1Y0rQco+59pWen/kvm27dz5mFejTqVLySfvdHf7+vocu6FJGTIYg4ypyD9K6uyihg8aWWnrbW8qRBLSRHiVg74+ckEctuLDPUYHpUOi+HHtNZgmuLrTTBA/m5/tG3IfbyFxv/iIA59eafoWkXMHiK0vLq609UE4eSQ6lbnGTyeHzXPhMNWpuneD1mr6bJfo7/gbYivTqKSU1pF9d2/1VvxMm68O3FvaxTxzQXaNKIH+zvu8uTHCNkDrzgjKnBwTTdT0N9MjLG5gudkhhlEO/MTj+E7lGeh5XI469K6JPDa6fY/YG1TSryK5uYpJpbbUIgI403A/fKkk7/Tt71e1zRFl0S4tbfVtCdUuVlgt7a7jQeXhlxkkZbkZLEnA+8elbyyxulOSg00tr317Lvf566dDH6/acVz3V+3TTftbXttc5I+HphaySfaLf7RHH5z2m5vNVOOTxt7g43Z9qvX2nLqot7kyWmmxLaRvJIYmWMsXZQMIp+Y49MnBPY1o634WgvJ59Qh1TTSZxv+xi+hEiSHqCS23aDnkEkjAx6ad1oMN/o1ppk2u6IFt4N0MyXqfJLu+ZW7kMCOecFPwO0cumvaU1T2tbXSVuazvdW07dbfCnpnPGxahPn1vrpqtNfX+t7WONt9BNy1htvrZVvHaNXYSYRxj5W+TPO5emRz1FPg8MzS2s9zJdWltbwzeQ8ksuSDzztUFsfL6ZPXGASOg0rw6qwaf5+raVAbK8eZlN9ExlU+XgphsfwH7xXtRP4Te4stVVdT0sRNfRvHO17H5bjEnGQTg/NnBA4BxnFZLLXyKXsru17X62i9etr83b1NJY5Jte0/D+9bTztbv6bnMy6FcQ62mmNsaZ5ERHjbcrhsbWU9wQQR9atPph8Ra3fLp32aGCMO0YeRYwY0BxjOMkhck+5JwMmtsae66pLci707FrZC3tz/aFuPMcRiMN9/jqWGccAd6p+HPC901/Kr3Onxo1tOpk+3wuEzEwyQrk4GeTjgVmsDL2ipKm3Fyl9y0jrbTrfysy3i1yOo5pNR/F6vS/kvyKMXhSSe7sYo7+ykivSUhuVZ/LMgIBQ/JuDcjqMcjmqDaURavMtxFIROYEjVX3yH1UFenI64PI4rfl8PXi6baWFndafdTJLJdM8GoQ/Kdq8DLg8BCScY6c8Va1SymGtWNxGLBFhdLieFtRt1zMSGkwC/AyAPwpywCa/hNapXtJ7pXt/h9771v1I4v3kvaJ79ls3a/rp+Zzl3oMlraSzC5t52hZVnhhZi0RPAycbTyMfKTTpfDssUM2Lm3kuoFLzWiFjJGo6knbtOOMgMSO44ONjUfCEVlO9xZ6tpl7mQNDGt9CrIM5/ebmA9sKT9fXRudHSLVr/WINT0uT7UsxWz/tCISq0qsCGO7bgFj0Y5x78JZdJ83NTs+ut7b6rv0utfldWl45WTjO+/S2umj7LfXT101x/Dek+VO7TvZO0lpK5tJxukCeUzK4yMA5CkYO7HOMc1ladob6iiH7Tb2zStsgSdmBmb0GAQOSBlsDPfg47ODQbafV01Nta0m1ElsY3tnvYy8chhMf8JIK55yDnB6VBa6beNoltaReJbLS/I8yOWIaogSZCxYMoRiCfmIw2OgrreXOyhKF1HmtqtdY26q102/W+j1Rh9d95yjLV2v5fFfo79F+vU5PRLBZ9bhhuUKxRMXnVh0RAWcH8FNSaPYR+IdbMc08VikpeU4QhRgFtqhQcflgAfQVqWehvZ2mqNHc2AlmUQQo2o2+7YWyzEh8dFA/4FTfDuhTWesQSz3WnRRYZWc6jbkLlSMkBycc9q8+lhKilRhKm2m7vR9Xaz22Sv8AM7amJg41JRmk0rLVb2vp96XyMKLT/tF60EVxC8a5LXHzLGFHVuQDj8MnoASQKnm0GdLqzhhkiu1vCBBNDu2Od20j5gCCDxggfkRXQ6Fok+j6ndxjV9OhWWBokv7bUogEbhg33g+MqAeM8mmXXh65m1a0kn8QWd3MXBlvxqcZEYyNpBZg5I5PT0xTjl8vZxbpu7evS2u2r2t1tbrzaNCeNj7SymrW+/T038r/AC105vUNPSyETR3kF7HIDh4N4AI6gh1U56du9Wtc0aDSUtDFfxXbTQrIyxq4K5Gc/MoGPxz7CtzxLob3ht5FvNGur9i5ubm0v4USTptJDMvzfeyQMHg8nNRa34dku7awnh1DSnkW3jhe3/tCEOhUYJJLbcfQnrSq4GcFVUad9Y2321vbXXpde9bo3uEMXGXs3Kdt77fK+m3bbz7HJVvReDrqUWqm7skmuo/Mt4fP3NKckbQVBUHjHJAycZyCA6Xwg6afBMmo6bJcuzCS2+3QAxgdDu8zBzz06Vtw+HHtX0C9mv8ATYvs0IkaBr6IO+2Z2G07tpDZwDnGQc4xTwuXTbft6T+z8k9/VpdOj3W6HiMbBRXsqi6/gn+F1v16Pqcz/YDmysblbu3YXcxgEaiTdGwxnd8uONy9CTzxnmr2j32n6INTtruK2v2aSARzeT5i4SUM+0sAQCoIPHI4rS0rSb60tL2W6FlskH2i2cX9uFE4JVSDvxjlvxUelchdWr2Vw0MhjZ1xkxSrIvTPDKSD+BrjxmG9lThJ03G9nqn09e7TfpY68Him6suWadrro91+l7epPrVzDe6xf3FtGsNvLPJJHGiBFVSxIAUcAAdu1UquaPaW19qtpb3l5/Z9pLIqS3XlNL5Sk8tsXlseg607XNNGjazfWCzrdLbTvCJkGA4Ukbsds+navJVo2h/Wh6k1OqpV3azeu27u9t7b+RTRtjqxUMAc7W6H2ro/H/ltrNrKkEFsZ9PtJnS2hWJN7QIzEKoAGSSeBXOIod1UsEBOCzZwPfiul8evYTX2nvYarbaoiWNvbubeOZNjRxKhz5kacEgkYzx1xUy+OPzN6Vvq9XVfZ6q+/Rbv5bFPXNGvtOttHF0bLZc2++3a2eI5QyMP3jpwWzn7xJAGDjGBpar8NdR0e2vXuLzTzcWtvHdtaRXHmSPC+z94pUFSAXA+9zgkZXmm+JRp0vh/w1DbazaXc9tA0M8UUc6mItLJJklowCAHAOCTnOARzW7fTaJPrWqzJ4m08wzaPDaRv5F180qxRoRjyc9YicnjDL7gYOc0tPPo+j0+89KOGw8pNSafwWvOOl4u/ryvp02ZzGk+C7nWLaEx3tnFeXKs9rp8rP59yFznbhSoyVYAOykkcZyM89Xob+JE1LwzptuPGFzpNnDafZr7RQ9z++2k8xqqmI7l2jDsvIOeOa89bBY7QQueATk1tCUnKXN/W5wYqlRpwp+yd20ru66pPZN2s7727W0bfT+B11K7vlsdF020vdQncb5L20iuEjjyAOJVZUG48tjP3QDyQc7xfHDD4p1VILRrCFbmQLbOhQx/MeNp5H0PTpTdI0a01KF3uNd0/SmVsCO8S4ZmGOo8qJxj6kGr+q31r4t8ZpJd3zWdnM0MEt80LSMFRFjMpReSTt3bRzzjPelb97ddv8vv/ruVdSwag3rzK2q2s76bx13b307HN05EMjqowCxwNxAH5npVzXNNGjazfWCzrdLbTvCJkGA4Ukbsds+naqaKHdVLBATgs2cD34raLUkmup504SpzcJbp2Zu614f1GHX7bTbo2C3ksUOxoJYUg2sgKEyLiM8EZbPJ5JJOaseIfh/feG7W+luLuymmsbkW11bQSs0sJO7Yx+UDa2w9CSMjIBNWvFI0y71/Rjba7ZXNutrbW8twkVwEhaONEYsGiDEEgkbQTjsKv+ILjR7t/Gs8HiCxlN/e/abWMQ3IaVd7PgZiAB+fHzEcg9sE8nPO0bfPR91/wT3nhsO3WTabWz54/wAsn89VFdtbWuef1uaT4QvdSshqE7w6XpO4r/aF8xSJiM5CAAtIeMERqxHfA5rDrsbvxbY+MzEPE8c0V8kawpq9iAWCKMKskBIVgBgAoYyOSd54roqOSXu/1/X9Jnl4WFGbftXr0Wyb83rb7rd5R3HD4Z3E9r9rg1XTRaNB9tTz5wsotvMKGV0TcFwcZTJbnADEECg3gia1vL2O+1Ow062tpfJ+2ztI0Uz43ARhEZ2BUhs7cAEZwSAd9pdFi0s248R2Mrpoj2Y8uC5w0v2oyhRmEdVPU8Zqz4q1XQ/E9vLpaa7aW32a4juIL6WG48mZTbRRyL8sZcMGiBGUAIzz68qqVOZrW2vTzt+X+Z7ksLg3TUo8qlppzppvlba30V9N+yvd3OS/4Q27h1O6tby4ttPhtVV5b2dmMAVxmMgorM28EEBVJxk4ABI6Hxf4bGp63awxTaVZTjRku2Fqm2G4KIzNs8pCu4qpPzbenJB4p13rmj+ItNvNGm1GLT/JjsltdRuIpWimMEbxuCEVnUN5hK/L0UAgE0XWo6LB4g0RotagubVNKfT5rhIJgIZDDJHuYFASuXByoJwOgPFKUqj73Xl/d/z0sEKOFhFxUk4yte8lde/a262Wt15u9tuT1DQm0rTdK1L7Va3sF7vKpF5mY2TbuRwyrz8w+6SPQ1oePVSTWrSSK3ggafT7SZo7WFYkLtAhYhFAAySTwKseIhpa+FtFsLTW7a/ubS5nEwjhmRdsgQh1LoMqNpByA2eikc07xXf2Frr+i31hqdtq6WttaxuLdJkw8KIpB8yNOCVOMZ464raLcpRb8+hwVKcKdOpGLVrQejT1trbXWzve2xSu/BcljZy3L6ha3K2jol/BZ7nmswx25YMqo3PHyORnAJGRUWqeELqzs5L+ymh1jSkxuvbElhHk4HmoQHiJPA3qASDtLDmug8aarDrss7SeNbjV7CSffZWM73TG13HrKHTaAikg+WWJOMDByKdh4q0/wLcCbw0JbvV1Vk/ti8XYseQyt5MAJGCDjdIWyP4ENRGdRxvbXtb+vv8AzNqtDBxquF0oL7Skm93qkm73XTS7W8EzjaKUnJJ9fSkrsPnwooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigD0fxV/wAjRrH/AF+Tf+hmsutPxQd3ibVyOhvJj/4+azK1MgqSL/Vzf7n/ALMKjqSL/Vzf7n/swoAjrodJjRvDd8xUFgXwSOR8ornq29Nv4INBvIHkCzOW2rg8/KKTGibVo0Xw3YsFAYlMkDk/Ka56tvUr+CfQbOBJA0yFdy4PHymsShAySX/Vw/7n/sxrr/hKniuTxhGPBsixa35Mm1n8vGzHzf6wFa5CX/Vw/wC5/wCzGt3wLpFhrmvpa6lr6+GrUxsxv3jLgEdFwGXr9aYj6C+yftE/8/sH/fNj/wDE15h8ZJfiY1jpy+OS01iXL2sqxQCPeV6bogOcdm9DxVj4aeDtF8Q+Ntc0++8VNc2enxSvZlWaP7ftDYcc8AABiuckewJq3428SeHvDnwlHg7TfEUni2+ur1byS5aNkjtVAHyrknnI6Anqx47oDxS4/wCPeX/dP8q5CuvuP+PeX/dP8q5CpkXEKKKKkoKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAq3Hq19FZNZpeXCWjfet1lYRn6rnFVKKuM5Qvyu19CZRjL4lcKtWOqXmluz2d3PaOwwzQSMhI9Dg1VoojOUHzQdmEoqStJXRNDeT21yLiGeSK4B3CVHIcH1yOajd2ldndi7sclmOST6mm0UuZ2tfQdknewUUUVIwooooAKKKKACiiigAooooAKt3erX2oRRxXV5cXMcX3EmlZwn0BPFVKKtTkk4p6Pclxi2m1qiZ724ktUtmnla3RiywlyUUnqQOgNQ0UUnJy1bGklsSW9xLaTxzQSPDNGwZJI2KspHQgjoajooqSru1gooooEFFFFABRRRQAVJb3EtpPHNBI8M0bBkkjYqykdCCOhqOigabTugooooEFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAHoniMbfEOqA9rqX/wBDNZ1anioY8T6v/wBfk3/oZrLrYyCpIv8AVzf7n/swqOpIv9XN/uf+zCkBHRT441fO6RY8f3gefyBp/kJ/z8xfk3/xNAENFTeQn/PzF+Tf/E1HIgRsB1kHquf6gUAOl/1cP+5/7Majq7Z2T6leafaRkLJcMsSk9AWcgfzrsZfCPh+3kaItqNwUO0yLLGgYjqQNhwPxoA4OKV4JFkjdo3U5VlOCD7Gm13n/AAi/h7+5qf8A4Ex//G6P+EX8Pf3NT/8AAiP/AON0wPP7j/j3l/3T/KuQr0jxnoUWg3Pl28zT209v58TOMMFORhvcFSK83rORcQoooqSgooooAKs6Zarf6laWzP5azSpGX/ugkDP61WpQSDkcEUAd94zvdFS11DSLOzklubSbZGP7LhtGswjFX3So7vMD0PmYOcHI5BhuNVsNL8BaRJDoGmte3gu7WW6lRpG2gIN4DMcSZOQw4GOAMtnD1jxrq+vW7xXk0D+ZgyyxWkMUs2OnmSIgeTkA/MTyAeozUN54q1C+0S20mb7KbG2OYlSyhSRT3PmBA5zgZyecDOcVxxpSUUpd9dfK39fme/Vx1GVSpOnpeNo+6tPeTW7fTS99NkkkdF4f1Ww0XwM+oHQNNv8AUINSjiWa8RpFdWjkJDoWwRgYAG31OSARCbkeEvD2gXNtZWF5/acck1y15aRzltsrJ5QLg7AFUHKbWy554XGHF4q1CHQJNFX7L/Z7v5jK1lC0m7+95hTeDyQDu4Bx0p+l+L9T0ey+xwvbTWwcyJFeWcNyI2OMlPNRthOBnbjOBnoKt03zOXdrrurWt9+pnHGUlCELtWi1dJJqTle61V7r3btpnWWWlaRonjfxVp8ulw6lZW1tdSQLcSNvi2oWUAg4zyASQSMcbTzXD61qh1rUpbw2lrZGQKPIsovKiXChchR0zjJ9yataN4t1PQrq7ubaWCSe7Vlnku7WK5Lhs7s+ardcnPr3rJdzI7OcAscnaAB+AHApwpyjK8nfRL/MwxOKp1aXs6at70pWslo7WV1q7a+l9BtFFFdB5YUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAej+Kv+Ro1j/r8m/8AQzWXWp4q/wCRo1j/AK/Jv/QzWXWpkFSRf6ub/c/9mFR1JF/q5v8Ac/8AZhQBHRRXqNp+zX4+vrSG5h0uBopkWRCbyIZUjI/i96APLqK9DtfgJ4zvLLULuLTomgsJZYZ2N1GNrR/fGM84x2rzygDa8L/8jPoH/X1D/wCja9I8MxaPNr7LriXj2GHyLEAybu3XtXm/hf8A5GfQP+vqH/0bXrfw4l1CHxhu0zVLPSLrZJi5viPLA7jkHk0AWbfwzb6140gTwpZX9xYQNDJIl2F81RuG4kf3a0fjp4avrLxvqepmzMOmTNCkM3ARyIUBAH1B/KujuvC2u3nieLxA/jvw8uqRBQs0dwFGB2IAwRjgjvXN/GSPU7y7t9T1HXtL1TzGMUVrpkxdYABnp2z696APF/iT103/ALB3/tWWvJq9Z+JPXTf+wd/7VlryapkXEKKK7nQ9LtfE/gj+z1t4l1yGWeaxljjVXuERY2khYgZdsMzLnJ+UqOoFYTnyK7OzD4d4mThF6208329XsvOyOGorsL3T5vFd1A7Np2l29pp0c1zdLaiGJFJA3OsMZLEs6rkKTyM8AkVbbwHd3F7qMJv9Ot4LCKOeW7nnKRmKTbsdVI3sCHU4C5GcEbiAUqi2ZrLB1NHTV09unS+1/XXbRnM0V1GtfDzUtEmit3mtLq7e6Nk9vbTbmil4KhiQFwwOQQTjnOCCKktPD8ug32manb3mm6zZm7W2keKIzRRyEfcdJowDlckEAqcHByKaqRlble4pYKvTk1Ui1bfv56dbdV062OTor07xva+JNOm1/wC2eGbax0OOWSKKZtCgtflL7Y/LlEQYnoeG5ANcxF8P78+H49ZmvNNtbKWKWSIy3a7pGRQfLAXP7wg8KcHjnGVzlCvGUeZ7ev4ep0V8uq06rpQTbV73VtE7X3el+pzFFdPoPw/v9e0pdTF5ptjp/niBri8u1RY2IYjeBkqCVwMgZzkZAJFXSvCjajaRXFxqdhpS3DFLZb1pAbgg4O3YjbRnjc+1c55+Vsa+0jdq+qORYSvaMnGylqm9FZddenS/V7GFRXQaR4F1bWtT1HToYoYr2wWRp4bidI2BTO4AE5Y8HOOB1JA5qB/De3xNFo41XTHEjxp/aC3H+iLuAO4yEDAGcHjggihVIt2T6X+Qnha8Y88oNK/Lrpr2/wA+xjUVNd2/2S7mgMkcxidk8yFtyNg4yp7g9jV3w34euvFOtWul2TQrc3DhEM8qxrn6nqfYZJ6AE1XMrc3QyjTnKoqUVeTdreZmUVu6z4QudGsLS6a5tLtZ5Xt3S1kLtBMoUmN+AM4YcqWHXng1Pq/ge60nCfbrK5uEuVs7mGN3Q2s7ZwkjSKqfwuNysyjacnGCZVSLtZ7/ANf16rubPCV43Tjtv89f0em+j7M5uiu3ufhPqNq0itqekuySzW22O4ZibiMbjCMLyxXkH7vOCwbisnSfBdzrFtCY72zivLlWe10+Vn8+5C5ztwpUZKsAHZSSOM5GZVam1zJ6f1/XpqaywGKhJQlBpv8A4H6tL1dtznqKK1vC+pWuk6uLm9toruAQTr5U0YdS7RMEODxwxU/hWsnZNo46cVOcYydk2te3n8jJorQ0fSG1eeRftEFnBEnmTXVyWEcS5AydoLHJIGFBPPTrVy68I3lvrVppqTWs5vEWS1uRMI4JkbOGDSbcDIIw2CCCMZ4pcyTsWqFSUOeMbr+um/lfvpuYdFdB4i8F3Xhm7gtLq8sJLySaSB7eK4G+BlYAGTdgIG3Agk9M5wQQLGvfD3UfDoiS5uLGS9lliijsbe4Ek7iRNyuoAwU/hyD1xjIIJhVYNJp77G0sFiIOalB+7v5aX1OXoroNQ8HS2dhc3MGo2GovZ4+2QWbuz22TtyxKBWG4hd0bMMkc4IJni+H9+fD8eszXmm2tlLFLJEZbtd0jIoPlgLn94QeFODxzjK5Pawte4fUsQ5cqg72v8r2/PR9nozmKK1rLUrWDw1qdnJbRSXlxPA0U7RgvGiiTeFbtklM464rJrRPVo5pRUVFp3uvu1at+F/mFFbPhfSb7Vry4Fj9j8yK2lkcXjRYKBGLbVfO5sAkbQWHUYxkV9E0Z9auJU+0Q2cEEZmmubgOY4kyFyQis33mUcKevpk0nJJtdi40ZyUWk/ebS7aW6/PXsZ1FXNW07+yr+S2+0w3aqFZZ7csY3VlDAjcAehHUA+1T+G/D114p1q10uyaFbm4cIhnlWNc/U9T7DJPQAmjmXLzdCVSm6nskryva3nsZlFb+qeC7zTbWymSe1vmup2tTFZuXeKcBSYm4ALfOMFSwPPPFLqHg6WzsLm5g1Gw1F7PH2yCzd2e2yduWJQKw3ELujZhkjnBBM+0hvc2eErptOO2v6/lfTdWfZnP0V0eoeFrSy8H6brC6xbS3N3JKpsgkocBSgwD5e3I3EnLY5GM81zlVGSlsZVaMqLSn1Se6ejV1t+W4UV1/gPQHk1fSr2afTIUluVWC11QbhdjdtcBSpTAyRlyoJ4BJBxUufDqX2u6yzXlnpFhb3bx+fchxGpLNtRVjRmJwp6LgAc44qHUSly/1/Wp0rB1JUlUXV2t8r38tFfW2muxzdFdj4T8IqvxI0/RdYltoFW6jDiXe8c6kqQqlFbIdSCCcAg8kVna5NPrWuw2yXej3bDCR3FjaxWFu2efm3RxDg8EuB9cUKopSSXa4pYWUKTnPR3cbaXurXur369E/kc/RXSnwlqmseOZtBJso9Ve5aFtrxwQB88hQAFxnoqjnoAar614RudFsLW7a5tLtJpXt3S1kLtBMoUmN+AM4YcqWB554pqpF2V9WTLCVoqU+V8sW029Nt16q+q6GFRXQaj4NuLDTrm6W+s7x7NlW9trZnMlqWOBvJUKw3fKSjMASAeoroPDvhv+ztJ8Qrdy6VcXH9mvJJZSKGurRhgoQWXAbnkIxYdGAxgTKrFRclqa0sBWnVVOStf/g/qmmt1Z6aM8/ooorY84KKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA9H8Vf8jRrH/X5N/wChmsutTxV/yNGsf9fk3/oZrLrUyCpIv9XN/uf+zCo6ki/1c3+5/wCzCgCOvvLw7rXjRfD+mLF4W0uSIWsQV21tlLDYMEj7OcfTNfBteo2n7Snj6xtIbaHVIFihRY0Bs4jhQMD+H2oA+iUg8aaB4b8Sxy+HtLkivZbu8Z11hsxiQEkAeR82PqM+1fEteo3f7Snj6+tJrabVIGimRo3As4hlSMH+H3ry6gDS0i9TTdX0m7kBMdvNHKwHXCyZP8q76eK0lld4NV06SFzuVmu0Q4PqrEEH2rzOX/Vw/wC5/wCzGo6APTfs0P8A0EtM/wDA6L/4qj7ND/0E9MH/AG/Rf/FV5lRTA6D4h31reXcMVrOtylrZiBpU+6zbnY7T3HzYz7V5ZXX3H/HvL/un+VchWci4hXRQ3celaBpF7ZatEmr219JOLVEkEsPEex9xXYeYycBs8j3xztFZtXsb06jp3st1brpqndW66Hog1zw7rmv6jqRay0idrOI2ceoW0k1pFcZXzRsRHyB8+wMpXGMjpU/iLU9I1e51uceJLKWS80u0t1Zre4UtLG0O8YEWB/qmI7cr7geaUVgqEU003oeq81qyhKEoRfNvur6NX0aWz7HrL+KtC0vVbi8i1lLyOTXUuttrFMkogMLqzqWRQCDJwM5yvTHNYGo3cd/q+nNqnjj+3mjnBjupzdyR28YOW3+ZHvy2FACBh1yRgZ4WiiNBQfMm7/LordhVc0qVouEoK127e91d39rX53tbSzu322v6fo1zq+t6iniyxmt7mSedLW2iuxLLklo0O+AIPm25ycDrziqesNp8ngbQ4YdXtZ762kmeWzSOYSKJNmOTGEONpzhu4xmuVoqo0uVJXenp6djCpjfaOb9nFc97/F1afWXdem+h1Vu2nn4d3Fs2r2seoNfJcrZNHN5hVUdMbhGUydwI+bp6Hipml0vxN4b0W3n1i20e80tJLd1u4p2E0bSNIrIY0fkF2BDbe3J5xx9FU6et79b/AIW/IiOMaio8ity8r31XNza6737WO/sNe03XPF3iXU7rUYNHgvba4hg+1pM7MZEKrny0fB6FvrxmuM020tbnVoLe7vlsrN5Qkt55bSCNM8vtA3HjnHX6VToojTUNn0S+4mripVkueK+Jye+rla99dtOliW6jjhuZo4phcRI5VJQpUOAeGweRnrg1ufD+6s7DxnpF5f3kVhaW1wk8k0qOwwpzgBFY5OOOMepFc9RVuPNFxZjTqulVjVilo721to723vb538zrXg0mDwolo+u2lzImpGV4baKfe0WAhZS8Sr0BYAkHGOM8V0mvajoU+hahpVl4h0mKz/tCGeygt7K5jCwr5inzGMO55MOpJYtwDhugry6isnSu73e9+nl5eX4s74ZhKnFxjTjquX7W3vX+115vTRO10es2+s+H4/EUV43iKz8ka9dXxP2e5/1LoCrf6rrlcY9T6c1lS+I01Hw3p1svjG40uzgtfs17o6vc/v8Aax5jVVMZ3rt4cryDnivO6KzWGila76dul/LzNpZvVlf3Er325lu0/wCby/O9xWwWO0ELngE5NJRRXWeHudd4C18aTFq9qNZm8PXF3CnkajE0qiN0cHaxiBfaylhwDzjtVeeS2uPFtnLc6/8Ab3MiyXerXPnPGzA54ynmkAADJXOe2Bk8zRWaglPnW52/W5OjGhJJpeve/e3fW19bXN3xaLS78X6hLa6jb3VpdXTzLdIkqoqu5PIZA3APOFPtmtvXtcsdL+Iem65YX9vq9vA9rMRAkqYMSopU+YiHnYcYzwR9K4eipjSUVFX2VipYyUnN8qTlJS66NX2183vc7We40jQE165sNXg1NdTge2gtY4pkliV5FfMu9FXgLjCs3zY6jJqprDafJ4G0OGHV7We+tpJnls0jmEiiTZjkxhDjac4buMZrlaKSpJW1ehc8dKakuRJSTVtdLtO613ul5eQUUUVueadN8P5bG21159Q1O30yFbW4jD3CSvuaSF4wAI0Y9WBOccA9+KZ4QuRpWt3MkWvW+lSRxOkV1NDJJbz5YKyOgjYlGQscMmOACBXOUVm4Xbd91b8/8zshipU4wior3W2nre7t2a7K1rPzNrxjNplxr88mkpDHasqEi2DiHzNg8wxhwGCFtxAYAgGp/h/dWdh4z0i8v7yKwtLa4SeSaVHYYU5wAiscnHHGPUiueoo5Fycl+lhfWZfWPrHKr3vbpvf7vmd3o+o6d4Y03TrmPWLK/u7DWFvfskMdwGljUqMgtEq87c8kHB9eKhnuNI0BNeubDV4NTXU4HtoLWOKZJYleRXzLvRV4C4wrN82Ooya4qio9im7tvU6VmE1FRjBK22+j1138+t1otDpbqeyv/A+nQjUYIb6wnnLWciS+ZKJDHgoQhTjac7mB471zVFFaxjynDVquq02rNJL1srL8Du9MudD1K38LXVzrMGlXGk/ubm3mgmdpUWdpVeMojKSQ5GGK8r1wc1fs/E0Vv/b9npvi5tCml1H7Zb6jA11HFcRsCGRvLTeCPlIyuOG9q81orGVFS3fft1d+x6NPMqlNLlgrqyv713aLitpdn0tqdh4WutNs/iHYX1zrCrZ2tylxNf3SSt57KwLlQqM3zHONwBI64JxXOtp8C6sLQanavb7wv28LL5OP72Cm/A/3M+1UaK1jDld0zjniOeCg4rdvr1tpvtovPzPRDqWjr8Y49YGt2raUb4XxuxFPtC7t2wr5e7dx/dxz1rNim0/RvDlv5Ws2V9eWuqC6FrFHcBpEGFBBaJV5255IOD0zxXG0VnGiopJN6W7dPkdMswlJyfIrycn105kk7a+Wl7ne+Ntcj1SSe4bxhc69Zed5tjpkr3DPBk5AkEihBtXK/IWycY4JIvy3PhyfXPEmrR+I7WCPWLafybSS2ufNhklwxSTEZUAHcuVZs8dATjzOip9guXlTfVdOtvLyNXmlR1XVlCLbaevNur2+1fq9L28gooorpPGCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPR/FX/I0ax/1+Tf8AoZrLq/rzmTXNRc9WuZCf++jVCtTEKki/1c3+5/7MKjqSL/Vzf7n/ALMKBkdFPjmaLO0Kc/3kDfzFP+1v/di/79L/AIUAQ0VN9rf+7F/36X/Co5JDK2SFB6fKoX+VADpf9XD/ALn/ALMajqSX/Vw/7n/sxr0P4AX2i6b8Rre41+WzhsEt5fnvtvlh8YH3uM9aAPRf+GdvAX/RQoP/AAIt/wD4qvFviH4dsPCfjHUNK0vUF1Wxt/L8u7VlYSbo1Y8rxwWI49K+zr/xT8OtLvZrS7vdAtrqFykkMnlBkYdQRjg14h+0/J4c+y6cuk3lnPfNcCZ4IBGDBE0KFcbVB2tw/wAxPLccYAlMpo+ebj/j3l/3T/KuQrr7j/j3l/3T/KuQpSHEKKKKkoKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPRvEyhPEmrKOALuUD/vs1mVqeKf8AkZ9X/wCvyb/0M1l1qYhUkX+rm/3P/ZhUdSRf6ub/AHP/AGYUDI6KK9H+EXwltvipdyW66/Bp9zAwaWzkiJleLIy8Zzg+ntxnrQB57LaT28UMssMkcc6l4ndSBIoJUlT3GQRx3BqKvuj4peAPBs/w4TTtYlg0TTtOiCWV6cBrZgMDb3fOOV6t9cEfDU6JFPIkcgmRWIWRQQGGeDg88+9ACy/6uH/c/wDZjUdSS/6uH/c/9mNR0Adtf/Fe91S9mu7vQ/D9zdTuXkmk0xCzsepJ7muc8SeIbrxTrEupXixJPIkabYE2IqoiooCjoAqgVmUUAR3H/HvL/un+VchXX3H/AB7y/wC6f5VyFRIuIUUUVJQUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAej+Kf+Rn1f8A6/Jv/QzWXWp4p/5GfV/+vyb/ANDNZdamIVJF/q5v9z/2YVHUkX+rm/3P/ZhQMaiNI6oil3Y4CqMkn0r3HRPFGnfs9eHZobaOHUfiDfxgXGfmi01OojYjq/QlR36/dGfELe4ltJ454JHhmjYOkkbFWVgcggjoQe9MZi7FmJZicknqTQB33xX+Ks/xTOh3FzCbe6s7Uw3CKf3Tybid6jtkY47YxzXAUUUASS/6uH/c/wDZjVvQdEufEmtWWl2QVru8lWGIO20FmOBk9qqS/wCrh/3P/ZjUdAHv2l/sga/daW019q9rY3o3YtVj80HHT5wwHP04ryjx78OtZ+G2pW9jrSQpPPF5yCGQONuSOv1Br7c/4U94I/6FXSv/AAFX/Cvj34+aPY6B8WtdsNNtIrGyi8jy4IECouYI2OAPUkn8aSGedXH/AB7y/wC6f5VyFdfcf8e8v+6f5VyFTIqIV6V4e8SXOk/Ciea207RZ7uDV4bWKe70OzupfLeKZ2UtJEzNllXGSSMADA4rzWvT/AAn4l/4Rr4VanFpXjpdA1y5vY7o2No17FNJEkcqGNnji2ZYspAL7cdSpGKl/BL5fmv0H9qPz/J/qSeI/htceI/GeiaNplnaaV4ivdNS51LTZZVgWC5LNlVjPKuyeW/koCQXIVQBgcvP8O7qDWI7D+1dJlC2gvLu7huvMgsU3bXWZlB+dTgFUDFiyhdxYZm+E17p2m+O7C+1bVINJs7bfI89xHNIGJUqFAiR2yd2eRjg89My+DNS0vRrrxNod9qUH9n6tYtYpqsUUrQo6yxyxyFdok2FowD8m4A52nGKNvxf56D7X8l+V2Z+peAb61utKSwubXXbbVHMdneaeXEUrqQHT96iMpUkZ3KOCD0INGueBZtJ0yG/tNU07XLZ7j7HK2mNK3kTldwjbeibsgNhk3Kdpw1dVpHifQvCA8O6NNqEWv6fBqFzeXt7p0cyokc8KQlY1mSNi6hWY5UDO0A8GsCe20PwTrOnX2n6/B4nmt76O4Q2UE0MaxI2cP50aHe2BwuQMH5jkU1a9ntf/AC/4P59xO9rre3+dv0/Ig1j4e3WlaPdX8ep6dqTWLpFqFrZPI0lizEhQ5ZAjDcCu6NnUHAJ5GY9Q8DSaZoX2+bVtPF4sENy+k/vhdJDLtMb5MYjIIdDhXJAYZHBx03xN12HXVvJX+IV74qsTOZNM0uaS7Z7UM2R5omQRrtTK/u2bJx25p2r6zo9x8OvsN9run+ILmC0t10lBb3Cahp0hZWlhaRoljeEZmAXe+DtKgZaoTbi2/L+v6v6l2XNZbf1r/X3HL2vgaSbw+upzatp9nNNbyXVtp1x5wnuYo2ZWdCIzH1SQYZwfkPHTPM16doGs6PF8Pm0/V9d0/UrI2tzJFotxb3H22xvWLCN7aVYtiqdsTMpk2sC2VLAV5jVP4mv66/1+PWylbf1/X9fM7/4OaJYarrupXF7qGmWbWGnXVzAmqW0lxG0iwuQ5jEUisqEBiGHPGAx4qnpNnqvjX4j29vps2g3GovcLHBL9ltrOxmIIVSIXjRGB4Owx7m/uk8U/4Wy6Xb32svqmuWeipLplzZxG7iuH8x5YmRceTE+ACQTnHB4zVf4aTadpHxJ0O81HV7Wx07Tr+K6kvJI5nR0jkDHaqRs+WA4yo98VT1nH0/G7/SxGqhLvf8LL9blTwl4E1TxxqF9aaa1p59pBJcyLcXMcOVQEnaGIz07DAHLFQCQ3xN4Mn8N3GmINQsNTt9ShE1teWUreSw3tGQTIqFSrIwOQB3zg5roPBA0bTPE3iFLzxNp1vayadd2kF60N20U7yxMi7QsBcAFudyr0OM1R8TJpc3hTwjBbeILG7ureKSK5gjiuVa3LytJli0QUgBgDsLcg4yOaj+X0X5v/AIBrK15ert+Gvn1Mvxvouo6Fr/2PVPsP2wW1u/8AxLvKMJRoUZCDENjHaVyy53HJy2cm14h8FyeEEE0mqabf3dtci3u9PiWbzbWUAnZIJI1VuVYEozDIPPIzc+KUul3Wt6dNpet2mswrptnayPaRTp5bw28cTZEsSEglCRjPHXB4rc+IeraNrGiQwTeIdN8R6zHeRxWus29vdRXAslRl23ZeFBIRiLaw3uMMMkBRT6XW9/1X9fjfTWdNE+36f1+VuzviB8PbrUrzU9bt30jT9mm2mpHSYAIJXiaGESTRxIgjVd7k7cqTyVUjmuY0T4c3mu2ULRajp8OpXUbzWekytJ9qu0UEkptQoudrYDupbHyg5XPY3k/hqTxHrs6eMtLa3uPD8VnFKLW9w84gjjKAG3yPmizkgDDr3yA258YRa34R0e3/AOE/vdG02DT0tNR8NrJd5nMZIzEqoYDvQJ99lw2c8UpafD/Xxf5L7/uI3+1/W3+b+7uZHwo8KPL4m8PahdXOiwx3F4iW+n60u8X6b9km1WRowB8wBkKgsCFJZSBxviSJIPEWqxRIscaXcqqiDAUBzgAdhXoWh6h4Y1ZvA2p3fiG20KfQdkF7ZXNrcSSTJHcNMskJjjZGJWQqQ7Jgp6HNcD4tNu/ifVXtLyLULWS5kkjuYFdUkVmJBAdVYde4FOfxRt/e/S33hHZ/L9b/AHGz4Q+HM3jCzt54dZ0ywM+pRaWsV55+4SyKTGxKRMoU7SM5zkHjHNVJvBs9rLp32fU9Mupbq6mt41eUwKpiYDfI06oio2eNx7EMAeKueAfFNp4etdcjvCQ0lutxYnyy+y9icGFsZwMBpOT61N441vTfGnjSCS1vI9O06RVYz3SSeXBJITNMCqKzYWWR1G1TwB1q0lzx7f1+qf3oXR3/AK/q6+5mJ4n0q607xjqem6pJaW15DeyQXMkEYS3jcOQxVY1wEBzwi9Og7V0PinwxafDbx5Y2tjqun+IfKaF2R7Z3RWKISJEmiVWBLEgDcMYDc5FUPivd6fqfxD17UdL1ODVbG/vJbuKe3jlQBXcsFIkRG3AHnjHoTWn41l0fXvHNlqlr4isPsl95DSl4bkGy2RxqRKPJ5OQf9Xv6UqL1g5aaoVTaVib4l/Da50bUPE+qxT6bHb2mqvFLpVvJiezjkkk8ksm0KFIXG1WJXjIWvOa9S8Q3Hh64T4jS2/irT7g6jerc2ES212GuV80yEDdCApw+35iPmU9sMfLaxp3UUn2X5Gkt7nWaJ8ObzXbKFotR0+HUrqN5rPSZWk+1XaKCSU2oUXO1sB3Utj5Qcrm1oXwwfX9AttXi8R6NBbPcG3uFmF1vsmEUkuZtsBAUrE2CpbJ+jY6W58YRa34R0e3/AOE/vdG02DT0tNR8NrJd5nMZIzEqoYDvQJ99lw2c8VQ8C6j4f0XTTpV/r8C2HiWKSHVikdwTp8aDfASBF87+aAx2bhhduQGJrV7yt8v681/S2IWyv8/68vx/Fcz4V8OahquparFpM+mXP2S0uZJJbpotskKRuXaKOYbmbapI2rvXg/LjIPhx4TtvG3i+x0i71OLSoJyS08iO2cDJVdit8xAPJGB+h1vh3Ho+jeLtQN/4m061s47G8tYr1obto7hpraSFSgWAuAGcE71XgHqeKzfh5qlj4b+IGmXd7dothBOyvdojsgUqy78bd23nP3c47Z4pdV6fqxvZnP6naRWF/NbwXsGoxRthbq2WQRyD1USKrY+qik03TbnWNQt7KziM91cOI44wQNzHpyeB9TwKfq1lDp2oS29vqFtqkKY23dosixycZ4EiI/HTlR0rU8BaxY6F4u0681NJH05WaO58oZcRujIzKD1IDEj3FEdbBLS5b1P4eXVraWlxp2paf4gSe7WwYaW0jGK5YZWI70TcW5wyblO04ak1X4fzWGk3d9aaxpms/YSov4NOeVns9zbQWLRqjru+XdEzrkjnDAnT02bQvht4t0XWLHXYPFEllqUVyPsME0KCFGyQ4mRD5jcYC5UYOWOauxX+g+Bx4hvNM12019dVh+y21jDDcxyQoZ45d0/mRqnCx7cIz/MR1AzTVnbX+tPz1/pam34frf7tC34W8HjR/DfjGO+n0O8vE0hpZtPkQPfWEgdNhDOgCthiGETsV6OFIxXLaJ8ObzXbKFotR0+HUrqN5rPSZWk+1XaKCSU2oUXO1sB3Utj5QcrnuJ7nwjNrvjTWYPGFlDF4gs7j7LZTWd351vJK6SmOYiEoNpDLuRnBODwCSK1z4wi1vwjo9v8A8J/e6NpsGnpaaj4bWS7zOYyRmJVQwHegT77Lhs54qJNvXrZfL4v+B3/ya008389I/wDB7bHkldx8KXsZdV1SyvNHsdSM+lX7x3F2rs9s0dnM4aMBgmcheWVsYBXaea4g4yccDtmu0+FMml2mu3d1quuWeiwiwu7ZDdxXEhkea2liXHkxPwGdSc446ZPFXvGS8n+QtmjiqKmu4UtrqaKO4juo0cqs8IYJIAeGUMA2D15APqBUNIAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigD0fxT/AMjPq/8A1+Tf+hmsutTxT/yM+r/9fk3/AKGay61MQqSL/Vzf7n/swqOpIv8AVzf7n/swoGR0UUUAFFFFAEkv+rh/3P8A2Y1HUkv+rh/3P/ZjUdAH1TD+2TpRhTzfDl4Jdo3hJ0K574yOlfP3xO8Zr8QfHOqa+lsbNLtk2ws24qEjVBk+p25/GuXooAjuP+PeX/dP8q5CuvuP+PeX/dP8q5CokXEKKKKkoKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPR/FP/ACM+r/8AX5N/6Gay61PFP/Iz6v8A9fk3/oZrLrUxCpIv9XN/uf8AswqOpIv9XN/uf+zCgZHRRRQAUUUUASS/6uH/AHP/AGY1HUkv+rh/3P8A2Y1HQAUUUUAR3H/HvL/un+VchXX3H/HvL/un+VchUSLiFFFFSUFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAHo/in/kZ9X/6/Jv8A0M1l1qeKf+Rn1f8A6/Jv/QzWXWpiFSRf6ub/AHP/AGYVHUkX+rm/3P8A2YUDI6KKKACiiigCSX/Vw/7n/sxqOpJf9XD/ALn/ALMajoAKKKKAI7j/AI95f90/yrkK6+4/495f90/yrkKiRcQoooqSgooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA//2Q==" alt="" width="699" height="385" />
而错误分为两种(语法错误和逻辑错误):
1,语法错误(这种错误,根本过不了python解释器的语法检测,必须在程序执行前就改正)
#语法错误示范一
if
#语法错误示范二
def test:
pass
#语法错误示范三
class Foo
pass
#语法错误示范四
print(haha
2,逻辑错误
#TypeError:int类型不可迭代
for i in 3:
pass
#ValueError
num=input(">>: ") #输入hello
int(num) #NameError
aaa #IndexError
l=['egon','aa']
l[3] #KeyError
dic={'name':'egon'}
dic['age'] #AttributeError
class Foo:pass
Foo.x #ZeroDivisionError:无法完成计算
res1=1/0
res2=1+'str'
二:异常的种类有哪些?
在python中不同的异常可以用不同的类型(python中统一了类与类别,类型即类)取标识,一个异常标识一种错误。
1,常见语法错误
AttributeError 试图访问一个对象没有的属性,比如foo.x,但是foo没有属性x IOError 输入/输出异常;基本上是无法打开文件 ImportError 无法引入模块或包;基本上是路径问题或名称错误 IndentationError 语法错误(的子类) ;代码没有正确对齐 IndexError 下标索引超出序列边界,比如当x只有三个元素,却试图访问x[5] KeyError 试图访问字典里不存在的键 KeyboardInterrupt Ctrl+C被按下 NameError 使用一个还未被赋予对象的变量 SyntaxError Python代码非法,代码不能编译(个人认为这是语法错误,写错了) TypeError 传入对象类型与要求的不符合 UnboundLocalError 试图访问一个还未被设置的局部变量,基本上是由于另有一
个同名的全局变量,导致你以为正在访问它 ValueError 传入一个调用者不期望的值,即使值的类型是正确的
2,更多错误
ArithmeticError
AssertionError
AttributeError
BaseException
BufferError
BytesWarning
DeprecationWarning
EnvironmentError
EOFError
Exception
FloatingPointError
FutureWarning
GeneratorExit
ImportError
ImportWarning
IndentationError
IndexError
IOError
KeyboardInterrupt
KeyError
LookupError
MemoryError
NameError
NotImplementedError
OSError
OverflowError
PendingDeprecationWarning
ReferenceError
RuntimeError
RuntimeWarning
StandardError
StopIteration
SyntaxError
SyntaxWarning
SystemError
SystemExit
TabError
TypeError
UnboundLocalError
UnicodeDecodeError
UnicodeEncodeError
UnicodeError
UnicodeTranslateError
UnicodeWarning
UserWarning
ValueError
Warning
ZeroDivisionError
3,python所有标准异常类
异常名称 | 描述 |
---|---|
BaseException | 所有异常的基类 |
SystemExit | 解释器请求退出 |
KeyboardInterrupt | 用户中断执行(通常是输入^C) |
Exception | 常规错误的基类 |
StopIteration | 迭代器没有更多的值 |
GeneratorExit | 生成器(generator)发生异常来通知退出 |
SystemExit | Python 解释器请求退出 |
StandardError | 所有的内建标准异常的基类 |
ArithmeticError | 所有数值计算错误的基类 |
FloatingPointError | 浮点计算错误 |
OverflowError | 数值运算超出最大限制 |
ZeroDivisionError | 除(或取模)零 (所有数据类型) |
AssertionError | 断言语句失败 |
AttributeError | 对象没有这个属性 |
EOFError | 没有内建输入,到达EOF 标记 |
EnvironmentError | 操作系统错误的基类 |
IOError | 输入/输出操作失败 |
OSError | 操作系统错误 |
WindowsError | 系统调用失败 |
ImportError | 导入模块/对象失败 |
KeyboardInterrupt | 用户中断执行(通常是输入^C) |
LookupError | 无效数据查询的基类 |
IndexError | 序列中没有没有此索引(index) |
KeyError | 映射中没有这个键 |
MemoryError | 内存溢出错误(对于Python 解释器不是致命的) |
NameError | 未声明/初始化对象 (没有属性) |
UnboundLocalError | 访问未初始化的本地变量 |
ReferenceError | 弱引用(Weak reference)试图访问已经垃圾回收了的对象 |
RuntimeError | 一般的运行时错误 |
NotImplementedError | 尚未实现的方法 |
SyntaxError | Python 语法错误 |
IndentationError | 缩进错误 |
TabError | Tab 和空格混用 |
SystemError | 一般的解释器系统错误 |
TypeError | 对类型无效的操作 |
ValueError | 传入无效的参数 |
UnicodeError | Unicode 相关的错误 |
UnicodeDecodeError | Unicode 解码时的错误 |
UnicodeEncodeError | Unicode 编码时错误 |
UnicodeTranslateError | Unicode 转换时错误 |
Warning | 警告的基类 |
DeprecationWarning | 关于被弃用的特征的警告 |
FutureWarning | 关于构造将来语义会有改变的警告 |
OverflowWarning | 旧的关于自动提升为长整型(long)的警告 |
PendingDeprecationWarning | 关于特性将会被废弃的警告 |
RuntimeWarning | 可疑的运行时行为(runtime behavior)的警告 |
SyntaxWarning | 可疑的语法的警告 |
UserWarning | 用户代码生成的警告 |
三:异常处理的定义
python解释器检测到错误,触发异常(也允许程序员自己触发异常)
程序员编写特定的代码,专门用来捕捉这个异常(这段代码与程序逻辑无关,与异常处理有关)
如果捕捉成功则进入另外一个处理分支,执行你为其定制的逻辑,使程序不会崩溃,这就是异常处理
四:异常处理的用法
为了保证程序的健壮性与容错性,即在遇到错误时候程序不会崩溃,我们需要对异常进行处理,
1,如果错误发生的条件是可预知的,我们需要用if进行处理,在错误发生之前进行预防
AGE=10
while True:
age=input('>>: ').strip()
if age.isdigit(): #只有在age为字符串形式的整数时,下列代码才不会出错,该条件是可预知的
age=int(age)
if age == AGE:
print('you got it')
break
2,如果错误发生的条件是不可预知的,则需要用到try..except:在错误发生之后进行处理
#基本语法为
try:
被检测的代码块
except 异常类型:
try中一旦检测到异常,就执行这个位置的逻辑
#举例
try:
f=open('a.txt')
g=(line.strip() for line in f)
print(next(g))
print(next(g))
print(next(g))
print(next(g))
print(next(g))
except StopIteration:
f.close()
五,try...except...的详细用法
我们把可能发生错误的语句放在try模块里,用except来处理异常。except可以处理一个专门的异常,也可以处理一组圆括号中的异常,如果except后没有指定异常,则默认处理所有的异常。每一个try,都必须至少有一个except
1,异常类只能来处理指定的异常情况,如果非指定异常则无法处理
s1 = 'hello'
try:
int(s1)
except IndexError as e: # 未捕获到异常,程序直接报错
print e
2,多分支
s1 = 'hello'
try:
int(s1)
except IndexError as e:
print(e)
except KeyError as e:
print(e)
except ValueError as e:
print(e)
3,万能异常Exception
s1 = 'hello'
try:
int(s1)
except Exception as e:
print(e)
4,多分支+Exception
s1 = 'hello'
try:
int(s1)
except IndexError as e:
print(e)
except KeyError as e:
print(e)
except ValueError as e:
print(e)
except Exception as e:
print(e)
5,异常的其他机构(try...finally语法)
try...finally语句无论是否发生异常都将会执行最后的代码。语法如下:
try:
<语句>
finally:
<语句> #退出try时总会执行
raise
示例:
s1 = 'hello'
try:
int(s1)
except IndexError as e:
print(e)
except KeyError as e:
print(e)
except ValueError as e:
print(e)
#except Exception as e:
# print(e)
else:
print('try内代码块没有异常则执行我')
finally:
print('无论异常与否,都会执行该模块,通常是进行清理工作')
6,主动触发异常(raise语句)
我们可以使用raise语句自己触发异常,raise语法格式如下:
raise [Exception [, args [, traceback]]]
语句中Exception是异常的类型(例如,NameError)参数是一个异常参数值。该参数是可选的,如果不提供,异常的参数是"None"。
最后一个参数是可选的(在实践中很少使用),如果存在,是跟踪异常对象。
示例:
一个异常可以是一个字符串,类或对象。 Python的内核提供的异常,大多数都是实例化的类,这是一个类的实例的参数。
定义一个异常非常简单,如下所示:
def functionName( level ):
if level < 1:
raise Exception("Invalid level!", level)
# 触发异常后,后面的代码就不会再执行
try:
raise TypeError('类型错误')
except Exception as e:
print(e)
7,自定义异常
通过创建一个新的异常类,程序可以命名它们自己的异常。异常应该是典型的继承自Exception类,通过直接或间接的方式。
以下为与BaseException相关的实例,实例中创建了一个类,基类为BaseException,用于在异常触发时输出更多的信息。
在try语句块中,用户自定义的异常后执行except块语句,变量 e 是用于创建Networkerror类的实例。
class Networkerror(BaseException):
def __init__(self,msg):
self.msg=msg
def __str__(self):
return self.msg try:
raise Networkerror('类型错误')
except Networkerror as e:
print(e)
8,断言:assert条件
assert 1 == 1
assert 1 == 2
9,总结try...except
1,把错误处理和真正的工作分开来 2,代码更易组织,更清晰,复杂的工作任务更容易实现 3,毫无疑问,更安全了,不至于由于一些小的疏忽而使程序意外崩溃了
六:什么时候用异常处理?
有的同学会这么想,学完了异常处理后,好强大,我要为我的每一段程序都加上try...except,干毛线去思考它会不会有逻辑错误啊,这样就很好啊,多省脑细胞,这样其实并不好,为什么呢?
首先try...except是你附加给你的程序的一种异常处理的逻辑,与你的主要的工作是没有关系的,这种东西加的多了,会导致你的代码可读性变差
然后异常处理本就不是你的擦屁股纸,只有在错误发生的条件无法预知的情况下,才应该加上try...except
七,异常问题的解决方法
7.1 TabError的解决方法
问题:Python文件运行时报错如下:
TabError: inconsistent use of tabs and spaces in indentation
原因:说明Python文件中混有Tab和Space用作格式缩进。这通常是使用外部编辑器编辑Python文件时,自动采用Tab进行格式缩进。
解决:将Tab转换成4个Space(通常)或者用Python编辑器(如pyDev)格式化。
7.2 EOFError的解决方法
使用pickle.load(f) 加载 pickle 文件时,报错:
EOFError: Ran out of input
可能原因:文件为空
解决方法:加载非空文件,或者加载前判断文件是否为空。
此文参考:https://www.luffycity.com/python-book/di-5-zhang-mian-xiang-dui-xiang-bian-cheng-she-ji-yu-kai-fa/514-yi-chang-chu-li.html
主要是自己复习和巩固知识点。
python 一篇搞定所有的异常处理的更多相关文章
- 一篇搞定RSA加密与SHA签名|与Java完全同步
基础知识 什么是RSA?答:RSA是一种非对称加密算法,常用来对传输数据进行加密,配合上数字摘要算法,也可以进行文字签名. RSA加密中padding?答:padding即填充方式,由于RSA加密算法 ...
- 2021升级版微服务教程6—Ribbon使用+原理+整合Nacos权重+实战优化 一篇搞定
2021升级版SpringCloud教程从入门到实战精通「H版&alibaba&链路追踪&日志&事务&锁」 教程全目录「含视频」:https://gitee.c ...
- 忘带U盘了??别急!一行python代码即可搞定文件传输
近日发现了python一个很有趣的功能,今天在这里给大伙儿做一下分享 需求前提 1.想要拷贝电脑的文件到另一台电脑但是又没有U盘2.手机上想获取到存储在电脑的文件3.忘带U盘- 您也太丢三落四了吧,但 ...
- 【python3】Python十行代码搞定文字转语音
前言本文的文字及图片来源于网络,仅供学习.交流使用,不具有任何商业用途,版权归原作者所有,如有问题请及时联系我们以作处理.作者:万能搜吧 都是copy的百度SDK文档,简单说说怎么用. 1.没安装Py ...
- 文字转语音?我只用十行Python代码就搞定了!
详细使用教程 1.没安装Python的小伙伴需要先安装一下 2.win+r输入cmd打开命令行,输入:pip install baidu-aip,如下安装百度AI的模块. 3.新建文本文档,copy如 ...
- 一篇搞定Python正则表达式
1. 正则表达式语法 1.1 字符与字符类 1 特殊字符:\.^$?+*{}[]()| 以上特殊字符要想使用字面值,必须使用\进行转义 2 字符类 1. 包含在[]中的一个或者多个字符被称为字符 ...
- Python入门系列(十一)一篇搞定python操作MySQL数据库
开始 安装MySQL驱动 $ python -m pip install mysql-connector-python 测试MySQL连接器 import mysql.connector 测试MySQ ...
- 一篇搞定微信分享和line分享
前言 在h5的页面开发中,分享是不可或缺的一部分,对于一些传播性比较强的页面,活动页之类的,分享功能极为重要.例如,京东等电商年末时会有一系列的总结h5在微信中传播,就不得不提到微信的分享机制. 微信 ...
- 一篇搞定MongoDB
MongoDB最基础的东西,我这边就不多说了,这提供罗兄三篇给大家热身 MongoDB初始 MongoDB逻辑与物理存储结构 MongoDB的基础操作 最后对上述内容和关系型数据做个对比 非关系型数据 ...
随机推荐
- 11.python线程
基本概念 1.进程 定义: 进程就是一个程序在一个数据集上的一次动态执行过程. 组成: 进程一般由程序.数据集.进程控制块三部分组成. 程序: 我们编写的程序用来描述进程要完成哪些功能 ...
- 你真的了解interface和内部类么
java 访问控制符 private : 只能被当前类访问 protected : 可以被同包的类和任何子类访问(包内,包外) default : 可以被包内的任何内访问 public ...
- 解决Win10下_findnext()异常
在win10中,使用文件遍历函数_findnext会报0xC0000005错误 ,发生访问冲突错误 错误定位到ntdll.dll 原因: _findnext()第一个参数"路径句柄" ...
- 开启第一个Node.js的Express项目
手动创建一个Express.js的应用可大致分为以下步骤: 1.创建文件夹 a. 创建一个项目根文件夹,如helloWord b.在项目的根目录下创建项目的目录结构,依次创建{public,publi ...
- JS获取当前周
var now = new Date() var weekFirstDay = new Date(now- (now.getDay() - 1) * 86400000) var firstMonth ...
- 关于虚拟机打开ubuntu黑屏的问题
取消勾选“加速3D图形“后重启即可.
- RouterPassView——路由器密码查看工具
大多数现代路由器都可以让您备份一个文件路由器的配置文件,然后在需要的时候从文件中恢复配置.路由器的备份文件通常包含了像您的ISP的用户名重要数据/密码,路由器的登录密码,无线网络的KEY. 如果你忘记 ...
- 【Unity与23种设计模式】责任链模式(Chain of Responsibility)
GoF中定义: "让一群对象都有机会来处理一项请求,以减少请求发送者与接收者之间的耦合度.将所有的接受对象串联起来,让请求沿着串接传递,直到有一个对象可以处理为止." 举个现实中的 ...
- 解决python本地离线安装requests问题
使用python36进行本地requests安装的时候,由于安装requests需要联网,导致安装失败,现象如下: 一开始以为,需要安装什么证书,其实只是需要一个python的证书库,(⊙﹏⊙)b 执 ...
- 使用openssl演练数字签名
以下代码摘自网上,设置一个server和client,client代码如下: package main import ( "fmt" "io/ioutil&q ...