Jerasure库简介及使用范例

时间:2021-12-22 15:24:04

刚刚写这篇文章之前看了下上一篇博客的时间:2013年7月19日。居然已经过了3个月了!好快!感叹时间的同时不由的又感叹了下自己的懒惰,其实仔细想想,这段时间自己也做了很多事情:

  • 完成了一篇副本同步相关的专利撰写
  • 参与朋友创业项目的初期开发
  • 实现了一个比较粗糙的Swift监控平台
  • Erasure Code相关内容的学习、论文阅读,主要是用在分布式存储领域

只不过事情多了就有些嘈杂,没有静下心来深入的思考、整理。

好啦,反思到此,接下来有时间好好整理。进入正题,也就是最近的工作内容:Erasure Code在存储系统中数据备份的应用。

===================================进入Erasure Code===================================

目前,采用副本机制(一般为3个副本)对数据进行备份是很多流行的分布式存储系统惯用的、保证数据可靠性的方法。副本机制不仅可以提高数据的可靠性,用于某一份数据丢失时的恢复,而且有很好的负载均衡的作用。然而,这种方法带来的代价也很明显:成本高。一个拥有10P数据的云存储系统,在采用3副本机制保证数据可靠性的情况下,将会真正存储30P的数据,考虑存储硬件、机房消耗、电费等一系列问题,将会带来比原本数据高出至少2倍的存储成本。且随着数据存储量的不断增大,这个问题也愈加突出。

Erasure Code(纠删码)就是在不降低存储可靠性的前提下降低存储副本数目的一种方法。由于本文的重点不在于介绍Erasure Code在存储系统中的应用,故在此不再继续赘述,相关内容可Google关键字“Erasure Code”,会冒出一大堆资料,当前该方向也很热,Facebook的HDSF-RAID/HDFS-XORing、Google的GFS II、微软的Windows Azure Stroage都采用了Erasure Code机制来改进副本机制。此外,SwiftStack也在博客中宣布将在下个版本中为Swift加入Erasure Code副本机制。

====================================进入Jerasure库====================================

Jerasure 是多种Erasure Coding算法的一个开源库,采用C/C++实现,活跃很高,且使用广泛。Jerasure库提供了RS coding, Cauchy RS coding, general Generator matrix 和 bit-matrix coding, 以及Minimal Density RAID-6 coding的实现。

主页:http://web.eecs.utk.edu/~plank/plank/papers/CS-08-627.html

Github:https://github.com/tsuraan/Jerasure

以下为我个人使用中的一些记录,可以方便初次接触Jerasure库的盆友们更快上手。

运行环境:Ubuntu 11.04 desktop

代码版本:Jerasure 1.2

使用过程

1. 解包

代码下载下来后,使用 tar xvf Jerasure-1.2.tar 命令对代码解包,产生一个Jerasure-1.2文件夹,其中包含源码和Examples。

2. 编译

分别进入Jerasure-1.2和Jerausre-1.2/Examples文件夹,执行make命令,makefile文件已经写好了,所以直接执行make命令即可,系统会默认查找到Makefile文件的。

3. 运行

为了有个快速的体验,我们可以直接进入Examples文件夹,执行make后的可执行文件,并附加相应的参数:./filename [args]

Encode范例

在这里,我们使用Jerasure库中RS算法范得蒙德实现来进行演示。

1. encoder使用方法

./encoder 'inputfile' k m 'coding_technique' w (packetsize) (buffersize)

inputfile:需要被编码的文件。在这个例子中,我们在Examples文件夹下创建了一个data文件夹,其中有一个图片文件“40kb-image.jpg”,可爱的樱桃小丸子哈!~

k:将文件划分的数据块的数量

m:根据数据块生成的校验块的数量

coding_technique:使用的编码算法。可选的有"reed_sol_van", "reed_sol_r6_op", "cauchy_orig", "cauchy_good", "liberation", "blaum_roth", "liber8tion", "no_coding",在这里我们使用"reed_sol_van"

w:bit-word size。范得蒙德算法的w只能从{8, 16, 32}中选取,这里我们选择8

packet size:就是packet size -。-,这里我们选择8

buffer size:每次处理的数据大小,这里我们选择1024

2. 执行

root@fs-:~/Jerasure-1.2/Examples# ./encoder 'data/40kb-image.jpg'   'reed_sol_van'   

按照上述说明执行命令后,我们会发现在Examples文件夹中创建了一个Coding文件夹,顾名思义,这里存放着编码好的数据块和编码块,以及一个meta文件,存放文件的编码信息。每个数据块文件都会被命名为"_k#"(数据块)和"_m#"(校验块)然后跟着源文件的扩展名。例如 40kb-image.jpg 就会生成一个 40kb-image_k1.jpg。

执行结果如下图所示,40kb-image_meta.txt是这次encoding的相关参数,这些参数将会用于decoding过程。

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xsISE8UoLFJW/ZuDE+PtbVUc6azSZYniUrKys3N2f+/Pn7DxyAWzXEEVwaV1o+lVRCbdy4MSUlmbeTYWFZablckZaWmpmZ3tfXf+jQYbvDqZCREukUWwIcYzOaTU6OoJRxcUq+VcuxNljizc63zymZTKNVKSnWQqdsefzOJVLjJwe2HTIQY04Lx5gd2c88/xX+0E8OVZklclmANjRLD9NZD/zHt26La37jZ7/5ZEg5Z1waeKxsHJYlpCVITP0WbgouzZQSBhMZHuPbMu7839/ckmKc/7++/fpVShVIDZDZYXLmf/l3P1qhshz97y+/2KLSSWiz0WDjCKkqIXYit3SiayPyxzjWYRsy2mlSHhuv9qk+dF7ZLVa7g+avSEoqV2tUHozGM/ntxWHvNpJEF69VujpQZ2+Dhr4z9XPPPMxfYqd2njBO+MhgIrO8FVdqSQe8Z8sBdz0XDYlErlCoVcF27LEOq7PkoR8/W0z0flR1oG6QKHho+lc3ZzPJln3v379aStYqf/SzQxadTy/wRDUL7dhEFTGQTtt0Lu3QLMLUkxDgR4Yz/I81/GS7hjjw2yRp8DASQAJIQGwEpubPCLdC3kVx3RbhDumq70Q3Rw58FyedoZD83/ULVOBrGEy+iFLkyj9sKP3qvos9DA3zFGHoGcsSMMxXIVds2nSzREpC7wq8hg0cI1daBwljzggSnIctmzfv3r0HBr7BCi4wggzu0nDnhp4XSCVXyIaH+VT8P/72PZJKF6PdtGnTxx/vdsIDUwo6CYIe+gHeiFmz5ju/fHqxChol33luh1Ettdu11z30lYc2FCfJnQO1R958+Z0TJu8BZh719QIVkBs4ZUxM8ZIsGUEUX5+r3HWW5Xgqot84zmFkKn7y6pMlRPfbz/1kh1mpCa6rY0oJg4vMWq2xN39xSwpBdH66p4GR6ciAchDg+sjm3VyhIojh0/uaGSU4M7bkR3/z8k0xRPOrT/3bCTZGHvRpFCUi8tPgLGaHqvyeF76zOd925Mdffa1T4+nRQecVrVt02xOfW3tdrl5KOAeaznz0xpufdrAaYbSUJ5OD9jv+31/uSfKqWvP/PPMfZwjw8GfzzA32EptEhvGK0zLObEtafufWW1aVFiSp4E4z3N10/sjud3ZdssplU+5mhNtbSFc3p1AMn/notLl0RclDDy45/odqTqmIzO1hXEW2n1/wv6Z+aU8iBB4OmcDIUG3XIG+3P4MuTchcMQMkgASii8DU/BnBdsGrEe6MEDLxnRHG69JOx09WFEqHB+ClNf5rP2yUKdX/VpHx5JFmeNEXHwdm2jgc625YAyPOrBZ4Pjy2CYPE4BOWI5DJ5KtWLdu7d7+UhFQUmOSw2zfcuB7ysFqsAVLR0J+zZs0KSCUhYR5NkI0tzm4i53/he7wzM7JxDgu14MkfPrtGx0MgZPEl67/6bxrrc386NVZJ/hfEYhgepuFBvkKv8+wOYq1DRisJT70VWo3Mu1VPyRWD+37/V+Ua/ZVPztqVMonVZLU5YYwfNNdImHKklFMw8cPJwDA7SqZUxowMluKcwxaT3RWLIGGCkQreDS0oDA/irXboR6JdOcC6CFKFcvSxLuuw2C02GijDAYVaqYGHzgGpsFZzMJaAAX6yFZZyGKUAZIwWiSKe798IbLkLJsfy9fZNyFqHDRaGoOT6WKWM5GxGk9lJUAqFVOUnsqfL8f/Zuw4AKYqs3Wl68uZMZslJkKByiAlzwlPR01PvN9155jMHzDnnrBhQTBg4zIqASBAQJGfYhWVzmBx6uvv/qnt2dnZ34jJ4oFWuw0x1hVdfVXe/Vy8U+FW592mn9GaY0LqPvq0GhgmWsRKQxCGHjzQyjOvX77dKRjPfnmvWFlqs8RIYoSry+n3EcUKfFTE726h6Y04T8UtwewMSdgmIk5hgyzIbGMnR7AsxnCXbCh2d5HYTmzfRmmfn2RgtQ2cYA/ZOs4m7SpGs/Y+/4OwpBxe3oqqPIrx2gU+o/Lx7rtYWNwP0DXnlB59/s6n+6hfXKEZwz+0w2eI/IFwv6h+/P6SymKB6X6cJMllzLVwoNggpLjAU8/sl7DqjRwKWyWKyEGVJ9MzoDwBCf5wVHgNwXTBtP+MBxTzyX/dccVhBZHSstbjfXw5e/fHnqxWDwDGK5At4fHCLI4obo9lka7VyA9ABD+47kMna2rDhDU3t726ndk9pu+a4B0W0YGy9B2PeuSYhtG72V9UHn1k68owJucvneEQIWSmmmA2GNTzxgMJDPtlAlns5IclNlyKBtFhmESBvan3/kSpnMossbY0iQBHYlxDoujwTYRYS6K41hUno+BJrkeqVWlow8DpvsMEnDcm36iBsavbaDDyM0GSfq8SWc3yp7buGIBxpJFmGwwzOM/Z6IQKRrlo3lrRIZVpIAHzCLBhnhJV1K6urqRN5Htx6SUmJzWrVajE//jgPvXdA++ijj4JBWrhWbZ2gpoSA7PObJ1z1nyPywiHW0Ch4ofy/nEv4veav75v6xvbu//fozcfnjT3rsE+Wf9fWZ8ifdczUJ88fKKgVs2+/979bwley/nLVo4cXZBlCzRvnffLS9KUOE8zfoihVZZ9aftrfj4XZDLdi+Rs7C4//53lHDelemmMC8+Sq+PX7xS29Dx0/qszC+GtXfPnu87O2sBZB9jK9z7718om98y1gbvx1GxbPnPbxohbezMpev3nIiedPOXpUeY7AqAFH7e6N89956es6wcT43eLAky/4+/EH9rJxwcbNP33y7jsL60UwxjFEGsUfyDsqOSXYwJd9sZo1QCQIp+KzHnv1LHyvnHH5bfM8vNg3JuURXrsNm6iKt841nXLna1N6MI3fT73hw22SffwNr1w+wlD31QM3fK5XaNdL0B4xDAN3xvWcODqHYaQrGTo0AAAgAElEQVQ1c1Z6BKKdaS+jtHUI/k+yjJg0BKaQjl/mb5dFSLQQJKMTlB3eWOMVjVxQso89+6LjRvfvXWjFaHy7fnhg6qeGGIPlxFBIHHrqzecccUCJiVECLZVLXn30nV/lg+59/+L+mjprVi1Xfsmzr0+0+n959JJnt/NiTseW73h/u2QffEqy2VRVnz/7+Duv/ltZh1FESQOCkdn82StfhQpXfPHN6kal23EPPTall3HA2FL+1ypG5Nthsi3A6PJM9Ye3XfvJ7vAtxwoWk1B4/O1vxZqg69+r7ndu57WKXYpUFhgfxDr813mTBncvzjHxjOKp3jD/vx9+8HM95qbDNGJqYi5F0YQxdAb83XWKSYT8Ez3jwaxxV12iCTO186e989nyyuaQqbD3wHJuY7NBNGpT3//E8849bkzfbA5qrJ//+8HbP+zibZCvJV+o21GX/v20Q3plc4HGpsijRgkwvSJ39+s7C0/49wVHD+5Wkm3EPSc1bV84651p8+tEiDRoPM6da+Bq532388zze/Q6bFTet3P9ampeNErcBhM8CkBUSgOpS3zTtVts9MfviYD+so58/p5d074oAhQBisDvg0DKu3qJyAELEfsPLvqIEHlYoTnkccLsDH+1fvnR5TvX1DnwfUOD8+FllbXYvNQuoczhKAkbNhXGZkppWSlOuYHsAaFFi82imQGT829IiuSjTFlZqe7JAxO1srISeMvo10Hy0UcfOWnSEfofvsOYTWsKnhO+7t3KUD4e5dH5asjvy5v0n4uHmQJr3npzvW5jh8Yt5aN64J+mpT9uDlpC2+ctJQJbjwP7WiKSAGcfccF/IMyAEX7q4c8rOWzlhpOlIIsJKIyQO/Coi+76R3/VJyntMGwHt8xkDxvXrxuEGcRsYzh7rzGnnTUJwgwh31Q86q9XXDbS4A0q2CaWLQW5hoDL4ZEYU9Ggwy+78ZRSv8/vF4ZeNPWWM8eW5/CO2trGkDG7pM+4EYUwapM8TN/zbrvtzDG9bIrbGRDz+x91yS1XjTF6grGQAWevpkKJHIzbLNlO15Pkamlqbqlp8CrYiY5JecAfioVJW0WBqfny1RkVDJM/6fLJPXPHnnvhCANT/dVTH24Pxuolak4VSckZNIicm1S5dJuf7OvLAY+nqcnZ5CDeUIAygAASLkTJIiJ50DzkmGGw/WtZ9ONOxQRBryPPHIo7XjmgFhwyaWQ5EWakQIgxcy1OrOJY0+Q1j73qmuMhzMiOuupGyZpn9PniyVggXI3VsrHf+SnMJssaDY0LPvxi1ttP3fTYUn/bWou+ixmjJbDmg/e+3+63ZEFLpEtwrmpXiCOiXztMpFhPEagYzWauNuYEfVQBwSUWCIFAKgssIJN1OLZfGYQZOADJnLV0yPGX3jH1+Fyvv22BacOC3i/OCg8EYwGukNiI7UcXzB15yigiiO9458kXftzqDKlw5m/cumzhZp/RAJGF7XfB7VPPGgdhBusCaqzDL7j17tOKg17J77GOv+rGf/wFwgwj+YX8vNjeegru7jF9SyHMYCwKWuhz2D+uu7AfdoBCwfh3Li9yzWtXEwmi24g+Rt2pJ/ZDuG3ZYwsmfoNxgQpKgdQGEllH0bd2Kg9YWmZvIkAWNE0UAYoAReAPj0BK2onEKCR4XEKVAuPdHiZW8XihYUE7w4pybjj5sEf/O/f03jmf7nBcfcKhw1mn4mrGJbjud7eaUZ7UUmSoWRA1H/mEpWxN+K65/us5Mr5DwrFaLNDegJlALSupFYxUgbSjt4CSehsojy+QZHCymKbzibQd54uq+AK5k244sx/n+fn5V3+ULvl7uCCbVawdJOpqcCkca1Cc1U6GyWGy8u2c7iMk9j75qiNG5zOB9dPufWOpZLLxSqvzkHvuPTc8t04uPeb6py4ckD3h+KHTn/zN6YNdUTgZjAbwzx2T87u7bni1dviNz1wxxshsefk/t87nj7nn0YvLxSEHd+d+3c5b+e2vXnv2ywZrtt2aN/ba+6aU5w8dmvtRJXvIOYeCVM/CJ257+hdfj7/d/9ipmukMtBRZfznv6HyGqXr/pntmVshFk25+9uJ+B540OnvxgqCoW/5FEdGGVUJKlm/250yM2WzOonnNJOIDUu0nd0/9uEpmDWKWFWNVYlCe8/H3XobXmEBMU2vn0RWNVrlm9nMzD3rk9L6n3PCAYjQz1TOfm1Wh1+nUCxdpBFGY+Jxe0M4wnqrdPpxL5PdaDjj/psuO6qFWrfz2089m/eI68MpbTlHnPfvivCZGto07fAhY9sYlP1YqRitZfu1WjSoHsifEHG/2ovmt40UEiBte2SRxJrPdyjfHmqZd1u6FRDDYPu2OB76uk2ERaLe0WwRxlmpry0aRz55wVezZ/MkbCLjbVpc51yYG1sz6QJLZ/odo00FSFMh6BmswmwQIp3KfKf85qzfDuBd99F09b7LA2CxkGxvBRI5YS5ZOuf/9KeHWmr6+56oZdRZjzAkSrUY1xoznfrQD9xBJiRfYVjkMDCn2yhZx6Lm333Vicfnk0wZ//+KqaIkGOxdZ8aZmrrO0E+BWaHsgy0aPThL79ikiJNUtW91sgKEneZIglAiHkgh04rdPOPeoPCjelr14x+PzHSXH3/DY+f17nPTX4V89/avtqFOGg1DnnIdvf2mF2z7h1tev6Edaij2RZCwvb8s98Z6H/q+vdfTEnuz6rf6CibHvXLTBcmpjRQPDFHF5PbK5lS7VEDadVSWX29VurlvnRw4Fcg+N3WCCR8GiuY6ig9MZSLtbu+2m0yeWflIEKAIUAYoARWAvIJABeSbe+5lQS/ZyVQtiqGqSCZLSUj/QLp0xbvibC1b+ffyIoUpTyNkUHhfLmhRJYxa1D5bYquESRJGFC5eEy0T9M378QaScqhpNvF4en5oRGjkVRxdgSL6WIl/008SQgwDRWmZs5iLSjyIFzGP+eU5/1rf87WnLnErEUSBJPTRg6j8a+hvpt1de+aZByIKVUhsbrMDWHhGTGpYt2nHhgHK+qF+eJfi3J24dGd7BlZY/fuFzERKiv7Ccp2J1DTOmF2NEnFa2ZfMmhErKNWdbMJigzzT83Gv+dVw/zedBT6JVZIX8wcSwyL/uu9UeHMkR1ZwidBvWk/zudvbDL58duZDTLVeQq1Whk29R9JjjU6IobLxmDWrrZKMz1mS3mAk5OK4nNuWql/jNRBGsf41UVBleNNV/++yMMU+e0yuLY3Z/8tKnO1mzhfG01Ykq3JaJhWKwkj13yR1UoCoQRp1/xVE9iKjVbeTkK0ZO1koGVzS3yDAtyzpoUn8IGvULF+5Crc4LRo0Po0FpjKLEaIcPjBpnsJxcvXxZ49HH5ve5+OmnJ/0yZ9bMrxc3SGwMsVZvsd1coGWz6g/Eg53nul/zWrvV9dQWk02EtWKUQ1useyEU9AhDzr/r6uPKGGnjzHtfXaWYjQIxx8o6JAqTKPUMNJ+6/jLU7FWw8xBzgizWuCBEjSr+AoMzRzSq5uDGr3+oOPGcXqZeg/L5VfVt12BsFneFG5iWzoA3ItoBHiBRo4Ow29qethDb3faQi8Pt+9d8uaTFmCVU/zxny/n9Bxp6DivifrMPKEEN7/r5G3wWKycTnWfixIps8wYEP+uba8238orMlsS7c7V2ENICjzoDhENWdeBhS2iTXHL/6zvPtR6LMSTEbTD+GhYUV3HaA2m9tZM/JRMjQq9SBCgCFAGKAEUgFQQyIM9ERIXO/eENC7nC5QsY4aNOfLpJ2lC5+5MNjnMOGfHZsnW9B2YPzg7v2MMnBq7mKA/ffnz4vH6wIyiP34cfPlF3m9FbIEKMykD3Aj9HMBkoSaQXlggzfn+AcFHwqg2ftNnxCGToZKCVAV8SCKBkRNXTmfZwV1LQPOqY4YT1HX3Za+9dFi5XeNLjL+U9PgPqlmLGXmBnZU+Is5do6hpno6t1h9jnZsw2wwH/d95fNr/0i180tY+gRfDAUaJai8TGLtUU5ot0hVPrDwiOEjvivKuP6yfKlT+8/8P6QPdT/u/onmFZQC+rq7DadYNTYDR2rXHJ10trW5lE1b3ZyRHX6vZqiGh5TG8kDiUANV6zZG7DrWKfm3hFqSA8wI24JCblCuJW+0IqbzAZMY8dK4IIEAm7pe59w57ahYP7535W4wYjzcUs3Dp2TVjWeEEBYQQUhcvJDe6u+nXWAy+vzB59yhknH3tgKbdr/gtv/BaCpZVl5NH9gWPdvJ9qWAMbCKoID451FzYe1FZg/PG203EBUASsiDdYAbHSbnugYvIpp0wa1nvcSVeNG9PrtrvfbdDUmgwPObQ9K93hF8YbF3ZIZWF/tcjkh4P+RX5rX8h8yOCRAbjZxMO40W0Ycdl9l0/MY9wrpt/x9LwmBA1EIVkK5hwUhQnHtJr3VX94V6v/DCuYTHYTpiHWBAWleCC0JyjuAosuRoCQg/rixd0UjUsCTJwcYkZs7wz4hzWKEj06kQ017YQQbmeKRg3N+eh7h8HM49GCh0hI5gxEhAh3iIVMlnab9E3sEsk17ZwlfImSy9vNXbshQ+Gsiz0siQdAHp/kcuc7l9ybCos9GVwN+RFBnsEDlpSN0XTrXKNA/AbjrmGHfj5xSgNJeNO1Gyf9QRGgCFAEKAIUgUwikBF5Ji5BeLlyHL/Z5R/Kg1MiapMtrtCTm1xXTho3zBgceNwhj3618OoBtkEw0Ce6HMNWdwAHOxBbCo7DuZl2uxUsFr57vV7N/58kTZgh4QH0BNbV5XJptVCQczicWi3yAy93lNG+kERYALC/5IxkMLyIAe3kImxv3BGgIOOr3Vmba9KLsObCIqL+CDbubGjcWl3F9OuWN/aI8s/fqOg+cSwxYNq1crtX0dlr58LnX/Od/5+TSg+8/Jpjd9zzdZMoRHEbasBvGHLaUb1Qx1+xodG7/rGLz4hsOwuiIA6MS1TMCyqX1a2IiIaVcz/6Yn6jOGT0OUf31KgO1W2uZYaXmYYff1DBM4sDBXkRr3xOrtm4mxneg7FZahfP/KYS6hAhqyBHcfvBhLWZeLX21zknJiVMomYRFc4DKZXP61tmDO5yBgWTlYtLuWoZcdbFf8nfNWf67A0+rmNFxGdDFDzTwZf8+2Ar07R2FTt0xOBzrz1hw9Qv61UhRmHwe2GeEgtMdu7ClrbF1q3QxFQGm+a8eNM3DGJk8XW/fvTkknfhzcQJFquRl/35Yw8rxzCrf/65WmHzh44pa1j+226fbcj4oSRgVbCl2afy8WHkNJG8DUA5FHewCm+2h3Z899bj37/f54wH75hSWnLw6IL3Zzma4eBiyh8yMFupCBtj6c2141zJnRafDDO3qd3qMmXDnUdjv6MTTD1ly/ApF+qAb/TI2RNvvhTCjG/V27c+MbcGAwl6WQQiZOX8CRFMVIOJJTd2x0SczlwcNDGxJui/9QVx1mrHZmL+bluHnMCzQY9SPP6Q3igp121pkllF1YKemQvzjcoOmYm3wmEvxomdAf/wk+r8w6JGZxbY5lXzKs45vxf8cK66JDh91vKdzZIhu7TP4KL6Zb/WSVVrKpmR5aZhJ47NffwnR+nxRxGTstDOtXUw1NtQzYzoYRxx6viCh+bUhLdttBHFkDr0kba7wMlx71wGsQ653G755NnWUuWQ8fDUZ1OwxplrdIpVH7fB+PcsJ0g1KQ0EwdE63Nq4Q9tuOn2A9JMiQBGgCFAEKAJ7AYEMyDMJ3s4QKESD4adGz9BCIkmAfovZctWkQYODdVJ9Y7k95/pjDzbWbVdDXjI0XvyxISQaLBAz4Ljf0FBvtZrBYsFbnOMUHBQTLc8gYICeULKurs4Ae/b2tSD/4AW/eHFU8GQNPgQDgFJAryUQJ5W4rIWOtmCWN75615W6O7SqmkZeN+2mYXz9tw/cP6uasb3/ywnXjcs97s7njwE/iQreZR/8WKewYXWB4tk848mZwx45vXff068+cdWt/61hwnhnHX3n04eqejBldfvnn60LGcxWY1hmQjuq0ubtoNOR9JOVm7dsdzOltj7nP/bYoVVec69WEUyt+/njFSdcNcoy7rIHp7dqmEh7CA3buOCDhcddP942/IK73rpAkhSDgQv+8uA1T25RrV1eGomaZQVp1y9b1VEDDKOvfeotb0j0zb/9uveqYlMu9Dj+b6cenMswJbsWT/28pnPFGTtMYy67CCG0m7965vkZzF+fvGtS37MvPX7Z/bNjFP6gJnJUCMsIavOGLV6m1NLzwO7C4i2cxWgnUh4WA2+28K0xuWW/XHDEEcQib+fcX2oUQ7+TL7zyKE0LF06eJd9tC5kEIR6Mm6PKkq8qJyhxpkllSyY/fO8RVmdDg1coIoZKct1uNxNq+XGF7+BDzP0vfOTdc/ysqW2NtG8aZ7zyccnAbFotRNpuSzGWvRpUSk+PAH77Z/KYk4aSjQbzgL/e+5xugqc0/vTsne97DmrFpBZSHxRsrc1G+89Ab7r6mZvvXTf8hhgTdN+3sWe8/ZiS/7Idcefzh/hxIxE9Rcv8L1YHcFpV45Z6Zmw3w8ir77/m4ZufWhN7hT+xMSD0OOfJToDLTEH70bGcsen7F2cect/p/YVuR11y01GXtJLlX/7AFS+tdyx5b85JU4/MGfPvR2f8S38KICbFp78FBNG/8N0Fx988wT7i4gffO8/nJ4Hx0km4j+rj3LlES6bY+w0jy6Rm3XY/okS3TagQZ65x2JYQr8EE9+xmXmxMaSBcsPMdGnXTpTN0WpYiQBGgCFAEKAJpIRBl+p5WvajCEBvi/SHsjkE0/OjkKwPEbEyVQ2WiPNC7O9RUi+9yS0O5q7K7iA3VEDQyy93qPDdiNRuwiy4IYlNTs9vjhdACf5ggHHDI/+Sf8BfkScTZBjGyWpqbO9cKSqGRIw8YN27MwQePPfjgcfjE9zFjDkQ+2vR4vY0NjQYoTOITH7nEm012mxl/Ns3bI5xYBHDyr3jpgRe+39KI80GYUNOmeS/ePe3XYPRZMqqy+9tnP6pClZ6nn39EHs7jcKz5dXutS4IBEU6G8ddu+O61e+/5ss4Iy5X2lKQ/GwKz6f2H3l2y3SHbyvoM7FdiCjh3b1hb6WcMRu+SZ+567OOFv22u2Lph9YqdhP9EQDniRGIMrHj57gc/Xra1mVhfGTjFXbu9RhGgSIJRXmdwUqIKUZ7iNgszJOdPz7345fomiYGjC+9zojNeiUm5L1T/63IQ69u6dHUTfNM7VeTNQ/7297Em+GK/N3OrrG6d9doS+IP0PPuig/PYlk69RI8Ip/YEd8xfDTcb88jDBxtxOEyMwZJz6IrGHgkfKGbnnCWNnCgEti5dtdutmxP66zd+89JDr26QcXRH/PG2A4zsoHMiG3OwfkbgPLvqfHxWQWlJDuPctXTmM88t84lmae0bj09bsKMlxMCCi0es7eqty9c5mfbmZ9pMJSIj5mwSeqITzzREAG9UeWtB2BHLZMvOztL+coqyDEJxFCYwvYshGemNwtXGekDsCTrEumFGrLUat62OC6+1oLfRTUzx5JaNP7x219tbGKNg5Bu+eW76/B0uGUpUp8SLsVe4gYG1WCfAl7rZzqPjDELdN3df//SMnzZVhydf8TXsWD5vnccg8AZ541v3PjhzxU5cQpxyR8XP7z0y9aNdvJE3iP41r97z0CfLdzhCDE6lwWE8LbvXraz04hzfjuMJ/243fnIfxbtzmaCUd9Ax/dBO7aLldSo50rPz3dopByskXoPxFw+CH6Q2EE7sdIfC1yrWY6QTYakQT8t0BYE4C41mUwQoAhSBPxoCrNNBogynksKiRTDo8XjcONfP4WhpaXn88UdwPGWC6tgTRMVcyXV3sSdLJXGZOxfmBIOTNdxUY/cZEeuKtAYVCmQXVCwv763bmOnKmYi9GSQZiEA4gm7r1i1EBjIYoZDRa+FS3759iKOGZlemJ61NEs2M8BIqu23bNnyFykczQksjqaGgC+cDwi/cClMXokiBYBUgKh+yP240CSTKEM7Q9CDULyviOEvwWgG/J0g6NlmMIgffd5yDqbnwIHGcKCKWWSz+JroRLrpBWGwRp2vOCI9uVg4EPIjUzIt2CyEHBzL6SOta4yyaF4xmA4Q2wW4PNTS4CE3dTrrzngvKucav7rl6xm4ckIKXZAhDQBBhrRZQFY1GUZD9HnKuY4fEG0W4nbcOLRElcZolFl/YWw74pSA5fZAEijKDQsRLjkm5ggNCQyoH5ZVAXCM6VhSYQMArqawgQtQkvjQ4MxTE8Qb43ePsjs69RA1H8QdLpjx21+RCdcubN0/90WkWOzCZOK5SyT31nidPL2a2v/vvqfN8ZgGydSCIU450oMCwwv2mdUcgNozw6mq3GHQC4g3W58csaCuSHLRKgmkRo0mssQAmKHwBC5iclIo4W7FaTgB7x7nUfreuZ95iFTEL8I2JAM7Lkhtotq8GKb776e0wIagBKg9CLXfsATK7UY4zQWYBd3jntYpId1H3TpwFZmZ98oAbX/0PTmfSosaRu4tgYiSeLYQcOYTDPGEzKFpNOLApHiaMLLUHXBBVJr/9jLetCZzVi/0UbIZow8Rtwgu4G/SHAI4MlvxB/bRbMnFkdnQwEDEgCP8W/YhbsqcD1TOsGtvNXbu7G4+Ltjsa0kDsO/e9Srb3lKfuPSZf2fzK1Q/P94r6MaAdJ6DTbzVeg4keBZqVZioDgYyd5KbrRBDN2MsIYNfv5JNPKyjIz8vLy8nJyc7OttkQOtQq4sWD/atOMSz3Mjm0eYoARYAisLcQ6LJRUTRBnRiZqIuyLBlEsYmxXF/DXZLlHG2UYfpNpAgiW5AEOWCpT3jVaQ+IZvAHhPsg3i8I2yMEAsFNm7biSBnEVgZXF5E9dBHF63ZVV9fADg1PZi0GQLhWMBDYvHkLapnNZtRCfis5pJ4sybt2VUG2MRgEzZitAxebBGhWMGTZdflN52uwrwmJpD0aLGux6XZBpAxvNGaFC+AnazSL7YqTqrEAbNdIuwYhJrXa4qtgqaIah1xjsIkdxEucamE75PZHLu2j+D0+xmrVKKv89ofdDClIPJgFowF/UWOQfXK/Sx+5cHhH4yb/qpfuf3WbKYuoqQjNCSiJ1Wx4mODqTOYo4zqtqViUIzqWYLPrS5SU6VQRjiXGrDCRpIBgNrZag2kCZKdeosbIGrmqWW8uPuqGg/udceqgBdO2qRpvGkmQIpiSQycWI2PrDyubBQ5HNSJ8gyUcwaGtXPhbDBi18bZfDHrheIO1dDTy00fNiiYx2vtCa4TcPtHLLAkZ4csd/+mwniFetgHOg5du/3yA3BLsiAlpEQfa2EydVrXWlyH+BMVYqxhvCku9NbKI1gFr0HYNtNS6wHjebNWNBvUp6LzCtXweLlJRA4w3Or1tLs4sEBIYyDDt77swJUAGd5at3c2l0Rn/7o66oxE8IvadKzNZh55LInNXz5oxvwXhMlq700mN+4nQG7EbjP8oSGsgne/QFAmLSzG9QBGgCFAEKAIUgVQQyIA8k1TDEQwEjUajxPKPt/DjDO7DzL5yQbJzCo5t2RoyYN/7F8lmMZvIkSth9oOoTeAuQ2rBKHtXFbaUbHbsteIsQ9hlKX6/3+0iWiKjaII9mxaAhwhHei3RaIKF2s6du2AhY7VZ0QgUMtgnh6Wax+1BwADRSPamJO3gzj9BgnbGoO7e3lDUo8CKMFeBxi0rvnr/gy/rGWM8YyEYmzHGou75YTegNozUQmCpiaJ/hARH5zUzHn23odv6bzfLgoHsLkcNCxvx3Q45rBDM55Zvf23iefEPMuo9mbl9E5NMLch9bnQJ7lzPwmcetx2bv3LWTg4BtIFAStOaoMEEdoMpNU0LUQQoAhQBigBF4H+IQAbszRAKK5UBQB8CYwsJlhnwe0F0HgXqFIgnsBPBFShYOupJdG0M4Z7hQhOScBYNQqQhEyWJrQdszFCLNEE6j1RvqwXTGVKJeMtABCKVNBMRSDKw6cF/4F47d5rKQPbDMtiXDRFzGML1AAmWyHOJJw2niHpj2ZuZjNE+RPshFB1Jhr4OsSYiVmPtLpNo0QgEwZosxBaLJoLAvoKJ4iP2kAi3JmoxizOU9pXRRYYT/86F/VtIFUQ93nrqw4/fYOpt0JL7DwKwQaD2ZvvPdFFKKQIUga4jkAH9TIqdQ7qAtRfcaSxms3Y4TBIOMaxvgZsAEUSgUtEtbsCSk4q4CklGLxMtlkRqKQrsvFDNoO9cElaeSFGMftqm3kKKlO//xWAUl9DJqfMIWQ7x1jpn//FyeEN8cZwT4CX1xxvyHo1oX8Fk76zPfWV0kSmKf+cS17suzGT8BrvQGK1CEaAIUAQoAhSBfQOBDLBrEbeWpCNCSewqSjEiAiStmvkCqVloZL5f2iJFgCJAEaAIUAQoAhQBigBFgCKQKQR+V3kmU0TTdigCFAGKAEWAIkARoAhQBCgCFAGKABDIwPkzFEeKAEWAIkARoAhQBCgCFAGKAEWAIvA/QYDqZ/4nsNNOKQIUAYoARYAiQBGgCFAEKAIUgQwgkAF5BuHJMkAIbYIiQBGgCFAEKAIUgcwhgDA8mWuMtkQRoAhQBPZdBDIgivh8gX13fJQyigBFgCJAEaAI/CkREIQMhjP/UyJIB00RoAjsJwhkQJ5BOOX9ZLCUTIoARYAiQBGgCFAEKAIUAYoAReAPhUAG5JlOJ2H+oQCig6EIUAQoAhQBigBFgCJAEaAIUAT2WQQyIc8kOxlznx08JYwiQBGgCFAEKAIUAYoARYAiQBHYrxHIgDzDUAXNfr0EKPEUAYoARYAi8MdEgB4c/cecVzoqigBFoAMCGZBnqDhDVxVFgCJAEaAIUAT2NQRUKs7sa1NC6aEIUAT2DgIZkWfYvUMbbZUiQBGgCFAEKAIUgS4ioFKBpovI0WoUAYrAfoZABuSZpCO+976HRFFMXKympnrGe9PxmbgYvZpxBPLy8k+d/NeCgkKWZe+IgCgAACAASURBVOWEKbprh6Pl5wXznE5nxunJYIN4l+NwpFBIzmCbe9LUvkbPnoxlf6m79zDH/UKZxcgy2Hs47y8rjdJJEaAIUAQoAv9DBDIgz+C9nngAgiCMHj06XplQKNTY2FhYWFhw1bWffzZz6dJf4pVMPf/2qXej05jlwbEv/Pmn+fPnSpIUs8CfLXPKWeeUl5fn5eUpWvJ4PM8tuMjtd3TAwWbKvmLC68g0GAwoVlVVBRl11uef7MtwybJiMho9si8tIq+97rp4iye6Hb/f/+zTT6fVctfoSasLWrgDAl3GnOf5nr167a7aHQj4O6Oal59vt9srKyq6LNIcOHo0x2lng+gPUO0pqj1JWe2/cL6iyL8sWdKZgD3J6d69J6sF2VcVZdeuyj1pKlK3yzhLlt4hWzlj6x00FGDYhmAD664Q3FsN3u0ZISy6kd+zr4wTTxukCFAEKAIUgQQIxGb6E1TofCmZOMPglQ8OGPxfh7p4jxMG2uutqant378fvp86+fTc3Lzvvvu6cy+Jc6648trCwqJIGQgtY8eO7Vxlzpw5EyZMsNls4w46ZPo703bt2tm5zJ8qx2g0gi0rKCgIBoNr1qzp27dvVlaWL+h+6l+3hJmrMBzqda88gjKYRMifxcXF3bp1q6yshEgjScF9FjGdQ0y6PjvQD4HtsIlHJh3UvPlz0m25a/QkpYQWSIBAlzHPL8g3W8wlpcUQWjq0D1EHVwVesGfZXV1VUeKp2K+8XwLK9Uvbtm1Nd5klbhOykmAQiouKUayuro7jOTydE1dJ5WoXcFY5k7f4eEP2gLGlZd1ysvJtRpz9GGKZBq934bbK2t3rLDVfcGluRsQj9ffsKx4NNJ8iQBGgCFAE9h4CGZBn2jO+MUjVtzA7b2Tq8owcksETm83mnJwc6EyOOHKSxWr9/LP0Nv5zcnLHjRsX2VafO/fHzt2BMpfLiV6GDh26bdu2f/zfJa+//nL17t0xKP7TZGVl5WCXFhOxefPmUaNGQT7RN4tVNeQO/BaBwWY8AN8Bnc/nq64O2wRyHIuZcrTs+2oubde7qwlDjlTFKm3fTNda7lothmcZ+U/p3cty0CR0df7C9dLGPCs7p7xv+eYtW8xmS/QaQHtFRcUFRD+T5Q/4XU5X1yjDngueUbW1tQmqY+MAxZI+YBO0oF8aU56FxaMnSeVbFBYt42d9fd2BfXIENmyQidW1bOseWpCmirNkLHMVnzS8qNvQwoIlK+fO37rM6azhBbE4v3TMQUdcftTRa3Z2e29hiaV6lujf012ndPuC1my8P2BSmZ9Moj+z0mTSqaIFKAIUAYoARaBLCGRAnkn6wIfiBW/uzgJGa44qSSFeEKAoCAQCUAKMG3dQVdWu5cvSMDyDBojjOPeyJxVvHXAIyUei086AQJ5BptVq7dGjB3iUiy/+F2jwer1PPflIZ/I6Vw/nKMGmBo8hL8cupPryjtvU//pCdnY2hEDIMPn5+SaTCaoJaGw0Y5cOPifhnxB4oN3CZVRBSSDpdLSkOghZCsicKEY4q+T1FL/Hq5qs5jSqtGtUs9tJuj4T09HU1BQpAK1UdOG0W+4qPQaOGWoPFRqZoKysdwl1QWIslIGkSo5Gj5CbYwUHBwnW4ePsdguxgVIlt9PD23PMbR2pcsDlVTAZIqQLOeANChYzz8j+psaArSDbyIY8Hkm0mg0ZvSdEq2ovUXkD43cxrhpO7YInVJcwx/LmYPtkMPTu1SsY8O/Y3mb7JBpFW5a9pKRUZYh3VtproHXaZEXG6iwuIXJFgiSrcpe7iDTLc4wtH0uXzM3aiuaystxAMIDv2TnZu2t8Q3rlaiVVd2NV1/tKB2eFNbYUHDupVz9XfdW0+W+azLLZ6rGZsLESkNjauYs+nfPTFzdffdstJx96/6fBnN3TeSU9k9FoPNPtS1T913qDI3hRyMk5c3fV5Tm2UILpoZcoAhQBigBFYN9AICPyTBIWRhdmOgsMeg6MyM1m07fffgu/bY5lYeORZbefcMLJvy5fmjpEkF5gB2U58Gq9ivzdtzHlGaPR9Nprr4BNEUVw40Zw58cee9zcuXORk4Y7jWXUfR9O2XT/vV/UyErAUdvc2eCKsxXkEWlHlZrrWvyJ9tSF7MIcS1fZ9dTxiVcS8oy+/QzJBFY0mBFiFghOrT3nGPkJoRFV9NZQ0Wa16/qceO1H5auKqefAAk/VrpqqBm9HWZMz5hVmGck6UkNSSGlFzDLstBPtS7/8pb6DDojleIOQnKcHi6WnFMgLF5E6cczNzc2R6h3kGVlhhHTmrgv0oGv0MCpb6jVkkGC3Kj6PYe36uY18JzJTH2JUSeOga14/s+KRR76t9sli39OvO6JhxrSfm1TOYOl11q3H1894a2lzZKb4wkMuPMo4d/p3OwV7dsnoicU7vl/psuRNfPz58V/c/NQKd/GkMwZU//RLRae57RJlpBJ46+we6phBvY2iyeHyrRQqHbtgHJVee13DHH14vZ6G+vqiohKL1YKtFrfbrXcMSaastIxluPq6Gq/Xl/L670i2gtWT6MkQLo9iXe4i0iWRNVQ24CW7OT6Pd9PGzfjTr+I+CniICGu0ZOlYdSQ0td9p4ezMPbRfdr6rsWb+6i/yrc05os8gGnv16HvoYUfKodAXX8zeVu24+/E7Ljvv+lMOGDLbe1he8zepURGjVFp9fe0/7KyBrnXZ2Y0e37isXPuMGT1lZTvM4GiiCFAEKAIUgX0bgUzIM8lGCNFCV9F0KAhTCvDQkCUKCgttdjsYWWyKQsYQeB5MZBIhqX1b8EZF0mwzSArJoZjyzCmnnBpd76cF8/WAXgbBEEolPICqSJKs8GCpVMhPkqRkjb7tv1cN6fS6a/z63ns+3ikx5gOmfnTFqESh3SrevOGRBY4U+JpkIHftOuz0oJYB5pDuoBlDMID6+nqyPQ8bwFDbvqTEtwkUKKnLflDU2Oy2VKdJZYpOuPym/l/e9eGRD7xxbH4Hcr0LH7hx+jYiGIp5RYWa3otl+LwjL5o8dnnl8kqhA/sOvYLDJaWIWqoUaiRB0Rchbfv27Tt3trN1mT9/PjR7ffr00ctA7ajtSqeX0qoALcFIu9Rz8ACDzRpy1PMmO2RxM6945OTiXGKysIKlYAgYKopYNmRggTG32+Dxh5+40b/GHaivMZf3ya/2YRFgzxz3I1hqg2iwj/j7I88Pe/2Rd1bnDT/pyrNL7r/7Y4c2foWxH3rheeM3PDRHSWt0iSmEWsYsCoKB90vNdlvOAUN6rFQrXVV8uiINeukCVQ119Vjg8Mrr06s86A943B6sDguEG4slPy8fD5w63Cq1tV1oWR91PHsz3RIsggyKdbmLaHi1TSWytof1tHaAXc/Xd5f2sK9UqvuFYlko6WO1f7X4w0JjY4FVNop2jmcHDhp82MSJRcUlY8aMffbZp37bWPP6By9ef8ndubl9/O5uZqkq8WqJeTW9vi66/e8jnKHskssu+ufbb762rKLyKL+v1qpts9BEEaAIUAQoAvs2AhmQZ5Ia9MTTzwAZXILNhlk1YeMfjjSEbTJAz5+zdevWpM1GA6uLTJEcbPLpr+fE4KMY2AXIQbB2S6U7lrcWFmYZzMU2wZRf2r1MdTo2TbvhRt3EhrUNv+T2I3976NklLYrsd4VIg8HN0267dTrL5Yy77OYxC+574Td9j9c44B93T6548vEfa+WQD+b3XTfySDy+5FcRrBnyJMAPSoE7Pj0pECJ2HdlWK/H8DxCLFD0ZWD8YyztmnYCfRsFy/aTp2O6FYJOdnZMi8Qrb84SJ4oo3V7WokxTfqidve2NTq1qLLz76tivzSDv4zzrkvJvOG2gk3QpWixH2TBMumTohQkj4S2DT9Hte/s2dVKABJ0Ka7SJDArkFMt769esj3Q8ZMiQizIQz02o8TXqIMGML9hrUV8zKkltqWNEo+dxN7qBH0W0CO8KS1m/OUlhaWJZttBT2HH7ssccMKu1eamneNfCoMwYzTUu/2V0ku2RbTq5BVYI+XxCMcLBu6dsP1tVefEbPHH7Ruo+fmdX7iiPLZ3+M4y1U1TRgyinZi974rlIiZlqZSrLEuBwhl8dnNoveYJPdljd0UNlatdq1G4rElDtJE/NIu3g0OB3O3dVV3bv3wG5LVm6Os8VRVFrSo2dPDLlq9y6X00E2UNJaAFFUd7Y3W/nbCrjm19RV435E4rX/jCbjqNFj9Bw9DwNa+POClMevFSQgkJmK1Kr1W4hNHc+39SVxXFb5qNHhnLT7Shlnn6Gohz1rw64NZoMTwgyU87hFgeSCBT8VFhXjFkOUAqvNmm8NeUOBub/MHVbaZ0FNsTnUFUfH1Pvyh/yWZZeWdC9yG4xvvP6C0x1Qrdb7crJ8sNWjiSJAEaAIUAT2eQQyIM8kNYdIIM/ASAz+G+CM8alrVKCx0V+xSZuNxlZXs0RkGPAiMfUzHaaDSDPEKxeG8sSHJOlkcXkHnn/NST1FMYc3d7/wipENS198/LPtTt22m1N8ISXkRbwjJ9kG1duTfS5c5rjWS7rvsNED9VGAlCR6h1R6TkpaFwuAUYM8o3HtG84Yc8PXa58/94iJWRaLX/L7g212dNgiv+6vZzi83ulz5h1ZfkltTR12kTVfmpTszVRZMh88ZYKw/rGtPrYApIaad1dVeMM0G7gADMyAApkB7+oXb71RDbqahXE3Pnlp4ex7bvtgg6OdATtrzCnIt4BtTo6bLsokLxcfvIEDB0Jn9dtvJDTCmDFjBgwY0KFsWo2nRQ/QGGwO9uzX05ibH2quZg1GJSA3b96xxW9Iq9M4g+OyDzjzujMGFlrNQ8495MNHn1p73l3HLH364+JT+817/Rvv0OtOzepz/o2PZtnYyq8ffGx2ZUD2NLf4eP/sZ5+AMw9rMDkXvf60oNgKe1sES4G9+cvnXlZdookPSWmIGnFIi8r2NvDrt9UMLi8xiUaPvzEvK3/gAHWDUuep5VLsJy3MOxAE1yl7dnZZabdePXsjDCMYW2hnbBa7FAri3sXVPZmIzvZmAX/gL+M7ye6dQKrcWZluv2SrAPdYxI6TYaB5y2xfqeMscXlZBtOmhopc7GOZjBzLwWkSFq3Qfc+Y8Q5+Cogcx8ORz5Br5bbtXDexdKjEZqc7ZB22lPsSrildPLIop3zCMG/1qlcrx5pEtnLN+o3GzLqDdZpLmkERoAhQBCgCGUIgE/JMMlJ05Uk8AQPMNIQZsh+p+W+gMQg5KJxcvIjqt6N+Jo69WQdKZa0Y0c/wKbn2q42Lnpu6iDEOvuqRMzc9cv/XtZo40tqo/oVsU4ZzVEhV2oC0gKj4IMITuYb4CJrFGtneBVsOCS6twXYYxZ78hLEZwN+4cWP37t3z8kaElOD0OS9PmTieY5sluU0/I4W2q2reR/MWHd7/H0NKx7tcLtjawKkAdmrJKccOPzfk0nP78kotxg3PF9584D3vf9SObN8ykfBc4cT3Ouuh60/o7/z6vl/sF77ywdEF0Vuk0vrX73xqqTOtDfo9gejAAw+E7wTYqeHDh3duJ/nwO9VJpQrKDDJJ/fqUmguLpOZqOBXBVsixuRIBzkcZsWjCW+1YTkGVbZT5aln0qGltJCvOpa/d/luf8+46o+KR5xcXTLm3X8svvw47qHzw+IIBC78e3ovf8d5D7xZecbH49jc7gxBgSk+6/bYDqma9OnO1h+ONfc9+6D8DWnYTeVypZQ6/8NLDGTG7zLT0kTvf39HFeHe8yBizFINN5XhIt22oYc1s2F4zoBfOew05PfWFuYVSP2mr2uStS0NLkwrmnSaKwQ3raG5CVPdevfrkZGdjhfbq2QvPqIqKHU2N9bihu9as3hGeO2iqQ3yzzjkdqMI+Auxcu9AvUaO1FwH3Rl+pEOaRRei4oUC3GhQ8+qAkB9B4OGqAMCoHFylV4VXEXbCa5Kr6epE1eBX98ZD6TR+GLZW+VEE5y77qgD45fY+c6K+u8Dj4IsfqFVWBNXXp2Tx3Xj80hyJAEaAIUAR+NwQyIM8ktbggL1ItxRtVB198yDakcAoKk0iDRCjR4p82fXQHTDTGKIrri+XxuouYXYxR5cZPlg8KSXdMLGTkXI+j5bb5DXFrRS6Ql7YKzUttXcBekNvRm58YOGlFyduZR6hZeHSbsknUKIWFHwK5whpFnsdhCzxL+FKFxEuONJ7Cl6Kiwjtuu0UUDXrZYFC65/4H6+rg95JeggAJkxNAV1NTM3jwYHwZ2eMon+T6eMH7kw8aJav+kEx0KAJvUWTrrCWLD+pz5vCyw1EMwQPgW4LAAEQKFQRNLEuQzMP+ceGogFMmbkaKd8dnt131BXzcDT0m3/lP42t3fwAGGLKd36fAUQOCHeybDL1H9LdUzHzi20qf2vTkffOxSQrPJU/APvGfN58kVjSAh08NMJQi05Fa4fgjmDhxYtyLaTWeMj2lhlCfshxzWanUUqMEvODwOCOXPaCHdiI9YU017hRrR1GkUK7L36PJvTMobFUQYzb1RI6FIgKmOdtqFpqrA2X9C7evWrR7zMgDxgy0MtYBeTbe4t/uUwiAcsOimV9mnzXlP2d6H/2sAr0Et310y/Vf10W8jYRuZz85tTsxGewK2pZC2ZbHlhRYs+1Q1ZJlEB6iZpKKESPMV0AK4QdEmtLCgoAU3BHwBhwpiHApYx4TuOZmR26uAwoZWJ253OtwDKU/4PP5/U6Eae7SSNt6IYS1i29WsXNHh5yYJME5MO2uCZ5kuSTofU/7ShlnRYZrXghmq5xgYMgJZGS3BwsxRDZ78AeMQSpJeDrhqBxoiok8Tx6raS+tpH3h9J0zLCtH9M7rewQRZlxOfteSuT/Xlm8L2NMGOSaCNJMiQBGgCFAEfhcEMiDPJH2t44WlcV+p8looiSpJm43GB+V1eQZxhkvGHYFXEalO/te6xRtT+yM/NIcZcpCH9snhl7tFaalXm+vqs/NZNpE8A6ba6/Z4ELaWtw89+bInB9rmPvHiklZVgf6yRZ865VzhYbfcNaVPG8AXPfNKNMn9737hGPLbsejRO9/b0jlGWvzph27k81n/PfaYo2tq60qKi7759jvkpAWX3jYULIACAc3gsKQBTkZwUO9TvAHn54u/OH7MECmk24RZvl7264E9Jo/peaI+j/hELQCOI2hwJIvHEw79FJNkLn/c6YMrP3y/4bi/iZxgtJg1MQw2S4LI8aKBCHzEkN9sFUKhoAo7t4IT77igO1P/1Zp6sg/taa6HIzbDGIoO+9d1Jxh+fPHZzysCKQ5W4xhTYkvGj584aPBQHYFpb7751tvvtI2lbdmSb+FfWEeKfPm/r9SLbVi/dtGin2IOPzozdXrKBMlSkCO31KpeNyxx4JWi+jxYy9oOtvZHSCFfQLPJKpisuXyNQ/B4N6qWpGToBRS/u9mSl5fVY+I1JzW8sGXdFtkuItqesm11jb3nsKZ6pe/o4SrfvARyJlkXarB+9efPLHvPz1stAvybjP0uevOzi9r35fqxS+IMhJmCEr5vjxyMkuzS695vrUsNnK7+Ff+EALrsVZR6BAWsyXYHncnlmdQxj4Ob0tTUiLAQPXv0LCosxneEKmmoR1D4VGXqOM1qvHn7R2LnnJh1EYgkxfXfVp101LpstNyM95U6zibF2ehuyTIXs0ILy1ZFhBSW1R77HB4N+A/yCxNQxRxLfl1zk0F1dE2FnbgvPL7OtK8dWZ5bDs1MTYXLwe9e+tP9NUf7pK48TmNOFs2kCFAEKAIUgd8HgUzIM8m2zXT5RBMsUkq6/JPWbhyq6LXA7+CIE6lpM1xp4bdCXuKKrCI8APnDF0lFyCY5RD4R0CwYZOElEiCf+MORDIk75ay9JxwzYcL4scMEY2OOY/bbn/+KXdrw8PUXbkScYdSmBQ9ftYAMWIWB2n1/XfvwQ3MadEWGcdC/Hj172333flsXVmykzZ/M+XHeuHFju3crrW9oxPfEZMcDHd4v0K/AeQkuNNgxhbpGL3lY/3M8ftd3KxYcOqQ3cr5fvWFA4WEH9Z4cmUe9MJQzCD6FiE9ejyZxxElq8/I3n1npEI49DsHL+p5+63kj7ZrOymonh5tc/chAt1uzwvNveuvhN9fnHnb9LSeKW1rkLNgdemurnEF91Rh6HXlo8bKHrn3qFxfZZOYtxSU48yROl23ZBNhUwOnXf+Bpp50G0zuM8f2P3j/koIPhNqMnGJvFjOXt9nlOPvlkdIWFgwKLF2lznSSlSg+QgTsBIwfB4GtyeFhhERZmdMGK8KhkfUNZiKVuL8gqC7Y4glItkyigXiuBrO3AK5+8YrSNqZn55EfbCi69ZMCGp95YH8wefclFfd+9494Hys+7+/IjzVWfNUcxz6rYZ8IA96otxAssuGPmwy8ubYlo5vj8w6+6KIsIj8lnJRokMUvJKeQgzJARE/vMsPAS+YYhRr7jOloPMQhtRx5cqfWVKubxpg5RAXxuF6T3vJy8zb8sCRoEhDxOret4Ter5xEMfvu9RhUhO5xM2O0Q8QxCTdHsnBnxYJlH+MwAv032lirNJaWj2NBbY+oYkJ6tWwWGG57DIOQZeM5yKn+QPkfsZ1i+bbebiWke1SW6GbjsxmjGvJuhL4JQpWesO7Jfb78jDdWGmasm8t4L/3O6vLu1SXzEJoJkUAYoARYAi8PsgkAF5JikD08qjJJZn1Hd/PsoXdOjDFnmwRu3OLkwMB7gNJLK/jlBMrcoZstVHuCFWN+jC9q4KBjEkKcGASv4gyQTC8kyASDWSW0oyFiFv+CBr9eIFuacM/+XTLxZp/jMdq+gblVHkykzxQT19W79wtAVe1V/NnUomHmP0VbCxr09786br/4NPfO9IQ2oNWW02+PSjrH4MedjMT6t77NCLP13hWLxxHeas2D78iIEX6OKiLpTiKNKysjKiGTCZYHvWkEinhcb8dTWMoTtpNrD1w3tu/VANen09//7M1MPBwyIAwAv/eXENrx/jCPOTXUs/fnab45g7zmb4bic//ezkXtHBsG9/Y7ZGHpRaj9w1Q4vvnDDpCKfACOkSWksLORsU9i07tBSz6YhYLsECqjUEHKqnNAUp07NLNuRU1dp6FDPk3EPiLM3BVYmYYZF9dqJsRIIkAw4VZpZSkMG5Obxiz7eU17gcjOCH/itJUv3bv3zi3sVHXn5SgETEYMTuJ1xx7SSGN9r4VRCQPNuXbAgc2H/bNge60gFUZePQMy8+c+ej935aTcSrQGNNfX2bvZmAc5ZwgklKOLTSxgmqtUDuWZatq001bLGsMOWEr9WhRh6+Yfn5JQIFbmqDaNpd7wq6+JT6ShnzzoDBkccIXw6WEWrqdkCJuGGrEb9gDgUDSMK9J36gdW6vfY5GWFFxUSS3clcFcpKesAn9TEoDj+qNrJr28c1IC5ntK2WcrZyrqqWqV+6gEDdSUhyCuonoHRFgksiqoJSIMzAz8zAWj2zqkzNg0fZFuWxLukPWRx+vL05l/2pZOyYizDh5CDOz2Bt/qHV3ua9k802vUwQoAhQBisBeRCAD8oxupZOAxojyJEEZMOUur/umc54LhPz+kPfFmXclbTa6Nb0LVFFxGCP4s0BQYTVvXShn4GkqQy2Dv6AmyQSVgE/xe1UIMzg70h/g8AkVTUDytYRYtjQBkYxn7fQX1jLGgaUnwDVcF5vaihMOB6lDtuwXRpw0Krj6md1oXC8RfjWTguGMRH3Gu1Zf33D/g480t8Bmo4utQD8DazFAB8MzqGiysrJgRQZZRecjTxlx9axVT0BUOnHolZGdXRy+gSrQSECSQTEIM2aLNRUCdBpBKPyOXDmT7rz+wMpvV7Dj+bkre15133mP3/bmqoA9xyKwwepflzLG/mTQStPiV+5bEw7UwBdMvHSK8ZNXvqvVgp3J/uY2OOMhpOGcGspQsGBQ5CxRom+REC4cyhm93YgA06EbXhT18shH9ZRASJmeWlm0tvj7MnXW0jzF4yLSicw4dtThYCDCRLcy0ji1w5xlMllEFbx+SBYwiXbjgBbPGiErOa8daKhutpFi2jr0rXvh0tsWewomPfbYKDIitwMhx1u213phGKitL0XOOujEcveqWbXaWI19znnmrXPIhbbk+rHj6m9/vcMvlrEUy6XFFtHAQecAnMHIQsHU0AJPmShPD3hwcUz3EhvskPCUMImWmnpPY7UcdIa90RL2kcYa6NBOYUjpw/EmI+/2S5zXK1fX+VWlwCI2+UJDJcXGcwGV2c4wzpQiicSgkYBK5Le21DknRjUtXEoqi61dXSLQdM3eLNW+Ur/X7Ly7WW7eVLeqX/4Eu/FwL8uK7CaJBMbTFyP0NJCN7fWBvO72YVvrtvs9O+02Z9pD1sYfuy9JOtW4YnS/nLBmBj4zi+e+779kudfm96zvcl8xJ4tmUgQoAhQBisDvg0Am5JlklOJFpe/uJyiIl20AsobsdvqXCPwgfE+LSUf7un5GcrSofpfUUssoiKADhYzEQCGDlyX+ggFFCmiCjcTg7M4g7FZCLAzPguQ7vsCMJVmnSiCAQz/DB3tHCkNekmROO5yQbIxH8tWQr0Udce0F5TtnfViJIFGt49e/4DNZdwkAI5egT9iTFnKyc2BhhXaAHrh5SDI4QBBe/vgOngl4/u3gOzB3eug5CDxIyCRHnUJu1PJhq4YTOVOhQS+j+NxK/7Mevv4I6Ytnpm0ce9PBxo2fP7frxH/f+NxdXz//wscbAlYjYd3DDcq+5notFjbo4xlnMGRprK+vawvenGK/qRSDQAJli65vQaDqxnZWQO1mISLeWLJzIvoZIs8kmavwZRRLseQOxSQ2e3uojdbibMXtZAVDVml+y67GVbLFqVlbIRllZUijq0Rl4IcEeYaRA2aTUCgqJSF/DWdKRhGGEuanQZJ5yL9fefsihjPZhFWK32c/8rzDce7iCYflzZ/tNBng2KKWHndy96ZF03cjfhlcoAJb37376V+I/R4/oQAAIABJREFU9kZza2H5giNvuhK6hhRHB9pEm5KbT2L3YrFplLCw7Kva7ffUCEooPEDBpGZ1k8uKzbjpcD6V2Wipb/I21smBxjRMglLHPIJYbkgdJBqMPIftkTyL2OgJeJta6kWO8QYtPJdrCZs62kPKOklqhrzVpRTBP1IbOZ3tzSJXdcMz8qBLszsiyhDfq3ZSYsb7Sh3n7mLFBqcl37Qh21xuEA/3c6UKv51T6qFy9CtGf8jukgwFpv7BEF/rqxxkr22sa8gvKkxz0OHiHfoKcKUnG18Z3Sun3xGHEjMzl7Br8Y/veC/crgyt9a3dw766RiGtRRGgCFAEKAJ7jkAm5Jlk+gFdmOn88tapf/7Lozx+YueTY8v2BZt8kltUndiC7HvcamQqklAxZ0jScUbszVyb10qNu/2Va7WD/bT3PnmVw2pEIZY5iMQF63P8EUlGhpWO9kX7HpQVCFGJx8JaS4rZ5mCWhSfcPMvq/AEr2vOtctBekiUgRJe22631KweFwf839d8jKmc+tLgp7G6vXdEKkHKJe9PK7sVks2dBnsF5kf3798dwEIUZviJE5WI2Q7DRg2hr4CngOL1eb2NjI8rgJ2jCZ1VVVV5enjVF/QyZDK7gsBuuPato1YwnZiypVcvGEhgU97pPnnpo5+R/XH5H0asPvLMJVkthnrgVH5AQdHpV7OKTwNbpQKYVTgllCCQYoK5v8Xh8qkE70bMtEZu+dnvpCFTgRZgros9BSnHLPHV69GY3M1au2dOTc5pzLYrHLYimnJLsfrscK7hsvUCQ4TdydkuTI78IAfTgT41lLNmshuLGQK3RHEV/jK9qyFPb6MFtooPqX//Wva9t9tgm3HpD7/zR/3fJlJwV019tPu4flx+/8rEf62Sh6IgLJtq3z1xYTTbsw5Ogf0GIO8nnDPFWM76lhLZOjTFLLcw162F6NXabqWnw++pFeANFJtlcGCopMnIckbfNJkuLM9RQK/vqNOeZ1Jj6dDFHy4LKlHOsSeBrEEFNUQfZTDgSq8rMemEHpcrwOUPnmz2+PF7INxv6y8pKRk3fQ5+syxUrf42eGA1YtqSkJMZsRWXpxRKX6XS1I1gZ7ystnAVG6WXcsbqOKbXV984dIsnFMmv1Kc6A5IBtpZG1dTeVVblrqtzrRxU3TD7i2GnTP3C0OHJyiYFquim6rz65g0/gPhvbW+h3xHh/baXLKVQtmfuh97Jlrvwq98o97ytd2mh5igBFgCJAEcgUAhmQZ5JyFmBWIG/ofHBnuptdjn+ffb5oMIBp8ASbEFxLkV3nnXI2DlnDTvmM2Z8mbR9t6voZ4lEQkBWfV3G7SS386TvQ4JUQOQfOxNhIxu4mrFnCUk2bbKMpahBCoOOLvx3BhuJJ1157RD6sTJZ+6dbi2JLEGsvPuOOfB9gZ/46vKlxaYFGS+PxDL7p4XP3nT721qB62b1ENczimjTcaSHDids3/zj9wegxSz5490W9kdnBQIJLO7ugeNTq2eoGIUIrgAdgtxk+T2ZzKBLFGbHYbvL+999DaQIMT/tw47B45RpEALtUs/eiR32bz0J5pkHI4zU7Q8NF+5U685fm/9Wadq970RDBPGSq0kALnC4EEBma6vmXaKy+l2DrK/9Dz8aMqryMBA1LohTSbGj06AZCgNrE2odFZxqhmq0n1eBB+IUtkzSHFR5xMSPKxQoVqERu8OblGFsZoOLoDQecUInV0EMA6DEroduozL5zc3bXsOT+CQRtY0ZR9wAW3nzswtOYL+wFj6ma/Mn3pTs6x6KJh+Sa+3ita+OZtPy38tUlb3gi5wYkmCC9kOGLvc+++6i+5DNO8/NWmKFmkQ3+dfnKiipgd0AOSm5Tlaht8nkZehqKr9U7hDIzZymAdIDqzUTQ7XVJdneRrQJDfTm0lzkgHc7SUKynZFtEjyVsEjshbJIIw69XOiW80Cn2h9EVceINQzbIj/VIWjn30BetwPkqaqbamukON4pLSeJs+HdtOcbG1ViO2ZopitkXJA06yz9Ox2Zi/U+8rHZztvHeQeeNOr2ept77IXGw32m1Cvo3P94Q8Lr97W9NKybO7d77sC/ILFi0+56y/vvTyW4JowD5LTBoTZ0b6Gj945ZEju5V2G0SEGReEmXkvNEyZ65Akz6+Z6isxJfQqRYAiQBGgCOwlBDIgzyR9k+t7/PFen1KQ9foRwXMbzmPBIGEV0RxaGpAkf1AyG/r6o8y0EkCgy0sqvGI4A+fxci5fG3+JtzZM8/HyhkiDaFEypBpY5ihES6P9ES0N0djISpBnExvpSJUz7/7Pp4LAysSPoXXgqm/tm7dc1UZdOF9xLH397uXkGPCODJh/9QvXEuVTx/wEA9wblyCiEIHGaIw3NUk7hYJCi7aUPEnbP7zt1nYQRXL06mrQB0sy/bt/7UvXr43gozoWPX3lonDdVPqKpoawWMmpIw4wDkc4FgVgiUh3Sav+ZdPl8MHaG/ZmetdYvBtYO1/vLA4pFrtZ9gdD+K/9AazVvDkvEDA4gzZEjFNZjyfo4ElQ7MQDV+rmPHT1nPAAf3vuht/w9ddblukZc+fr/2789LmN2rdA1fxpz+l5aDa4cdotj5JfpIvg9hl3XjtDv5as09ZS5F/ZxzY6AnlZ5BHU7AgijkGwpb0VWQiKL7LPYBaNLZ5QfV3QVyNiCyDxuKK70L+nuAYiFWHYBNnFEZKDBi4HApq2KRLpFDFAcPov4gR4DGxdSMEpm0Usk/bZT52p1HJwJ7aPeNZWrqioLXJAughAAPN5nO37zM14X+nibGDlvqYKh9zo9Nc2eq1emShFTVzQzDgL1BZVrtzxW11hj75+d46wYsX5f5/y8mtvcmVlFqtZ0wWll/S+jh3ds+jQf2IuXVse3rloziNVEzb63QXqrsz2lR5ltDRFgCJAEaAIZAKBTMgzyd4uOoMYj2n2BRSXr0UQChUZXITq9leaDN05NiRwIbfPgbPUUnl76ToE1evhOYHxePhoeQaGQpqVPzm4UjuFRpNqIM8QXQ2DT3DkGnFwtmbNyd+UJNwzpKXkBdFi2mdlZmJOU23jrbfeWb58eVNT07x586BsKSwshP0YzqLBJiisziDnIPpZREUTcarRRUcdcNhorVu3Li8n1TNPUqUsQ+WIlonMVPKpCgT8X3/9dbxu4y3dSHl4b6XSS+r0RFMCBn49ny01O3MaPQijto23w3G+w5A2G7M5X4vfSyK+uRh+uzk7FXrijff3yQ80iU2i5CE0qwEf56szdKbZWyvskgMIdRbyczBFI4e+JJ/MduR3AXPoDJFwrBT+LYJyhmVxDFOk42ZVyWOZHizrYFgXTsxhES9B62SPk9YM2yE6c+dW9WKd8xPkbKrpGAqwqCTDfWkQaB/pJNxZ2bzbzjrJ8wRH+8LsMPJ8EY0FhYV1O7e5rfaAu5DnDeecfcb09z7s0asHDGLT7QhE5VuUDbtc3YJ+V+Vib8g/bXf3Rl9TrtJAXk+Z7isdDGhZigBFgCJAEcgAAhmQZ5Lul+KlhVdGXKZQNb8w/QcMxWo2nXXyAfC8DQjNH/73N8RPRiarpmReorPX8DFgOZF1ezT9TCs6RFKJUtGQELeaSKNZoEUgJAdURxQEGQB2P2gC+jCHw6m7++NTFzsjn/qsYRjIgTAD2ypoIXQ/pcgndBrwaUm6AP6XWGAZJGOxMNIFC+b4/KG83ALg8MILL5x00klJaZ49e/a///1vLO2m5kZEwYLBZEo8Vgr0dO4a1mMbuGyoLyPHvXQoE2S5NZY8M06OhwUaDweQ/SBhb8FTbfAbCLHEzCxaCdJKvuTjpJ0izlwNu7Inm8rYw04Tc4SFRsLZutDc5psMCLxVGxXlo0bgSpBvFgd5A9jYwBUCetcI60Ru3Idkh5KZ6C7zfaWJsz4mkEGs4UiwAvLsQTxK8qmJNUDVare5nc6Az7PQ65hwyLgB/curauvKzKaU7rX2oDU11lzy4JJPbfzWnc6fNrk2+7L2Xl+dJpZmUAQoAhQBisDeRSAD8kw715BY1EY441gXmfsuIEYvKHPNiwe3eBr9QViqN7k9IWHzGJKfGqsAVhve6oaNa6yIxbxqCdHPIOlvfcIvhVU0xOosToJZSwCb7JliTOL0sk9lgyeAQGK32y688EKEbNZ94sFHIB/TAQFG93cHewH3EnyHVKN/JwyHjFPcQy0tDng97eOgJSUP4+VZDof54eR3rA8MDbJK0plCscYmYmcE4y9Ux6kZSavoBZLSE6+dzoaLHUr6NDMzpEywu/GoyGg+7ssgITYJwenbmHWgMi3Md8OETFGLLKJu4FXtDTqMbYZwAZ6tlEL9eK7UQuyjYHeKEzHTaj8BginKGBnpbm/01TXC4JAVjt6Cf3AHancSmsLeFAmiKIo40rShvvGb7+b4fYHe5X1wr3WhI4s9/6CDS+/7rJ4ITAoa1t4ue6evBFNML1EEKAIUAYrA3kAgE/JMQmYEb00cALdixYrE1KOY3682OpogcYRCzYjXLKRjXLJxwxrLzi29v3oXgdJ+rUjcVdyrlfa8NM0l4ja1X1wwGngEX25qaq6o2Nk1ggFXbg5sP7pWe6/X0ixgUnLUF0UDjvALSSFfIPS3c85KkTIex79oFclp5imk1OlJoTFaJCUEuoC5R+Q3S1J3zdKsWVF3QJhpP701oiAFUYARWK5OkZuNXT2Dpv0I0MuKlcuTjirFJZ24nYz31QWcQaG2dUKkGXg4QsbgoadReEgbeB1o21Da9hNivhUXIlwHpJqystKsbHsXlDNoxqeYoO6H8+Pv0Fdi8OlVigBFgCJAEcg4AhmQZ5IyjG+//RrZCUuW/N3Ujz8PO9byjIBjGpO2HGly166KXdgr7TUK7ul4JSbrqt117PYJiEWgRSP4UyWL1SgaeRwfCQaiCwPHDicRA7QTbPbNZDQZNauVlIQNMK8itoKNIsYCbkrbxCVsVTQ4GDJ4KaKL0b6kO+q06Em3cVo+JgJdw7xOFMiTCIZQcSYZgc4aw/2lqpeLSV50Zn1dbdIy4QLpr70OLWe8r67hDKr0+wgww0uKZ3hdjmlPLSliMpsKCgtSxSdOud+zrzgk0GyKAEWAIkAR2CsIZIAZjfPGD5OLV4jREDaDSTyCwvpx7QokbjdWW5BK9CBpsS7SvBgIQBzBX4wLf4gsgwD2KB5HmmiERGiBfJtpCbfL9CSilV5LiMAeYd4Fq6aExPyBL+4Rzhou4Q0C8thP/9GfJrK/Z19pkkaLUwQoAhQBikBXEMgAL9uFjequUErrUAQoAhQBigBFgCJAEaAIUAQoAhSB9ghkRJ6hoFIEKAIUAYoARYAiQBGgCFAEKAIUgf8BAhmQZ34H84D/ATC0S4oARYAiQBGgCFAEKAIUAYoARWCfR2BP5Rm40VN7s31+limBFAGKAEWAIvCnQ+BPGOfmTzfHdMAUAYqAhkBG5BmKJUWAIkARoAhQBCgC+xYCVJ7Zt+aDUkMRoAjsNQQyIM9Qe7O9Nju0YYoARYAiQBGgCHQRASrPdBE4Wo0iQBHY3xDYU3kG8ZGbW5z726gpvRQBigBFgCJAEfiDI4Ajxv7gI6TDowhQBCgCGgJ7Ks9g++ezz2ZTMCkCFAGKAEWAIkAR2KcQOOdvU/YpeigxFAGKAEVgLyGwx/KMdhojTi1sbKh3OR2hUGgvEUqb/bMhIAiCPSs7v6CQBpz4s009HS9FgCKQEQT4P+5xyRnBhzZCEaAI/GEQ2GN5BseoMwyEGUkKDhwyTKTa7T/M0vhfD8Tr8WzfuglUFBQW/a9pof1TBCgCFIH9DwHqP7P/zRmlmCJAEegSAlyXarVVgv8MfrgcLb1696XCzB6CSatHI2CxWsu69cDSorBQBCgCFAGKQBcQ0F/QXahIq1AEKAIUgf0LgczoZ6RQSDSaYHW2fw2eUruPI2DPzsbS2seJpORRBCgCFIF9EwGqn9k354VSRRGgCGQcgczIM/CgiUfZokWLYvo/SJIkimJJSUmPHj04bk/VRPF6p/n7NQKCYEiwtPbroVHiKQIUAYrA3kaAyjN7G2HaPkWAIrCPIJAZeSaBYiYYDI4bN67zaOfMmTNhwoTNmzdXV1cPGTIkKyurc5n0cuSGBS8/+1PZRddP7gkuuC0pjjVffvZb9nFnHVq8p6NNjyBaOowAZFeDod2c4ILf7zeZTEkxSrC0ktalBSgCFAGKwJ8ZASrP/Jlnn46dIvCnQmBPFSMR81wYm8VMshyKme9yOXNyciDJ2Gy2VatWud3umMXSyJTdO1au3FQfUDrUCTWvnPXJ9xuccuK2/Btf/dcZFz+/2pO42P5yVfHuXrNkeYW7IxqJ6U+9Vsolm5qarr322hkzZkT3/Pbbb990001OpzMxObj6p7ob6WApAhQBikAGEaD+MxkEkzZFEaAI7MsI7Kk8Ew4HGZ/vDMmyEitBngEuVqsV9mZGo3Ht2rXxYQrVzX30gsmTr5xZFfalCDX88s6d/5wyefLksy+/74NVDiV+3ZSvcJaCbt27FVr/IDqcwNYZDzwwbWmLnDIApGDqtVIrWVdXd8ONN5gtpu+++w4ijU7Lu+++O2/eXNEoXn/99ZB2khAYf2klqUgvUwQoAhSBPzcCNF7zn3v+6egpAn8iBPaUe9fV2WQXHXxnLNZTDoUgznRG1Gg0vfbaKzBDQlQ0LYkxqzOM0rLspakvrJT0JkgXwYqP73lgpm/CP66/JK/qq9dm3POg9dl7TywlBMQiI15+B5qEbpNve2KyPpDO5O53OZG5iDUpcUeTeq0USsKiDEqY/IK84uLiwqKi77//XlUULJgffvh+8JDBcJoKBgJ3TJ367LPPxvSwCk94XFrpBYoARYAiQBFIhAC1N0uEDr1GEaAI/IEQyIw8o4kRsWMChOTY8swpp5waDeNPC+bHNC2Sdn/16FOrRlx9jeGNB1ZpXai+jZ/Orsw77sHLTx1kYtQB5op/3f/p7B1HX9wrTADKKO41026649u8ix6bemJ3luS3LH/1xoVbdzTLYtHwY/5+2XmHloodZlGqePeKa+aMffTFi/uJcv1PLz3x3tJtNY4gw/B5g4+ePN6w6vv5KyscIVPJgaddfvUZw7KIZiu0e/YDd76zogGljEXDj7voqr+PK9ARlZt/++z1t/67aDt0R7y1qOfQo6+87ow+IiPVL37/pbe/+rXax2X1+csZ/7r0pAE2NuZ6SpUGJkGbO9+5/Ix3SOtDb3znvkNMcaltT0BUrbeuU1668rHNE+976pKhVja4c+bN136Sf+XTNx9WoFVp376twziMJtOUKVOglpFCEhRxffv1/X7OD3JIHjCwf4ujxeFwNjU0QUXDsGzMqW9tLeHFDl3SnxQBigBFgCLQigCVZ+haoAhQBP4kCOypPBM2z43Pc0I/k4oXBIrFQDy449NH33OfeO+Fo9V33whflxrWbnAbB4zrqfmSs7YBh/RhF67d2CL3ChdQg7u+eOT+L7hT7rnphO6QWjTNjiJlHTjlmnMLlIq5705/4vZAzjOXDbfGFiRIaW/lqg0tvc698a8DTa4Ns19+7403uh15wUU39TI1L3n3xRmPvTP8pcsHo38+e9gJF950er5NrV/5yUszHn9p4Cu3HZLNqv5N02+767PA2LOuOGdwnlI7/9UX561r/P/27gOsqev9A/jJIIwQRoAoS1RURFEcqHXgqtviXrX9q9TR1lU71KLYqqi4al3gQi2O0uJCReu27p8LRXHUhTgQWSYEyM793wRERhIixAF879PHyr1nvOdzeSQv59xzFaSm4tammYtOCQZ8E9LKMSvu77BNc9c5r/nBj6crECNjoHJ0t6l9/F7QO2haV3oXBIalkxVtpTvafLY3/ytUy9reYsy3n0xeujLK//cRvCMr/nrZdOKMdo70O4e0qkXbL9EQIT169KBn5zQpjYJOapQ1PNwpNZUlzhKLxcJM0ddff920aVMd1Qqf0v+tVUpFXIYABCBQtQXw/EzVvv8YPQSqkEB585nX6820i810LW3Ke36mVFG6WInq8qSYFTFUn9ABtSzIw4K1ZCpRag6xduKx8sozzOwEXHLzJf24v3YsipenV0RsTm4zddGXDblvlp/xPxkytHsdOrvx862lSpy8Y9f1Lxq2sZblSOlsi67FYFuY5X1wfjMQK3ff5o3pKvUFL07F7XLz79quiSUhddnXT829FZ+qrO9O98f1aN5am0fVq8l7cnLKkfgU+Sc2HFHcXwdeCAYs/WlobbpHdWZqNDlFR0sJ4/469spnQuiX/nw6g/H8NuN/324/dj/XrymdbJQ4tHGVGgNLeFV3m96a6hx7V48aLvn3mNIdrXnhnrWdFqlF7FuP/brl5GXLVoi5cS+aTPy5nQOz4F4XbV935tGrZ086WY3esYO+g0qlkl5mlpubKxJmDf/88/b+/iVuenEH7SJCHBCAAAQg8NYCmJ95azJUgAAEKqaAafIZA5856f3NdD4/U4yLLlb8TPqZiL05nYP7eNA5Ab2gy7gj8+jScMqp75Kxn/DpSQRdB9vRpz4vKv6/dEWTR7+Pnns5r2mfoM2jdZWmz7FtXGyITCiSU8SSQdi21azJ3SyJ9pEgecr5vzbuOH37eaaEyeXIiVl9Bf3pW/EyIUlh29zPtdiSNnnqnedK5asVYwaseNOVWaaMIla6JmgKh6M3BpXeNkuORne0JcsVO8O0bzNu9InxK09neH0zo62DHlZDzdDTMWw229bWVigU0uXofe0kudL0jAxDdQquIZ0xigmFIAABCBQXQD5TXARfQwAClVSg3PkMW/P5Nm9qRucnT/pX8sbkM3SxotUp4fVDCblpCTOGHyig3zbxi9sz1o1w4pLsVLEqrzwl18zXcAU8JpHQBa0adPB8emrfyqhm80Y2KrSOiy6c9x9dRq2pST+zYeH5xazZvbT9smxqmZP7r8vkt/z6S4YZm0FkKrU2a2OwOSxCb3BA5zPypF0hS/cyu379w7d1+eT5P0uWXdBWUVP0ZBOLzcx/LCSvNY2SZuGdVavv5nzhWTApwjC317x4p6BMwVjz/pIXM/2nvhg0jepu83nhUdCtKfREW6zrYrU0YVDiR/GJcsIgj/69lNq5t3PBfI/2ov7g84YQHR1Nb27m7FKdXmNGv4yIXm9G/6V69WonT54wM2N//vnwYkMu9iXmZwz74CoEIAABfQIs7Q9oHBCAAAQqvUB585kiz8/oWm+m0u7XXKojXazY0iPbT6au8qLnLrSH/Mmueb/d9p8xs09DGytzL+vom5eSpL5e9H4AOffPP6b4HevZsqhcuqC5R89p4xuunB4+f4nTsuBeLpr3y2vboP/M+4v0yZWbYk5NbwGbwXNv0Nj9dWiKpDfFilXJH5f2o/Wbv1PSZ7eSSd1Jw7o0s2MQlaWb5nl4TS9mDp4CcuT2nXRlXe1n/9dVOE71XBiHE58QQfuiUze63IqHrScGvW3K2FZsIhVL6ffP5I1QX7Svx5/3/+K16OxMdHnj6rO2Q0NnmkUERa74p2nIZ9oVbCVLFm1J+9Wu3bv/+ecfe749PTMjk8rog07N6JDo9JXvwD9y5Ci9u93AAQN01Mw7xdBu5oADAhCAAATeXgDPz7y9GWpAAAIVUqDc759h5WVEej915u1vpusNNEXO0cWK+bG4Tq5uBUc1Hothbufs4mDBsKzXr7d75qEV6w5euva/mNVh56Ve/XvXLFjbxTCr3vm7oP6ChI0LdzyQvo5L8vRG3I2E+MtHIxfO35vu1mdoY50P4b/VPTSvXteJPNi342jc3QcPHyamaPIpzcHktxzwCTdp65INhy7fTLhybO+JZ9rzDDu/wV34qXsWLPnz+OUbN6/97/j+I/ey9crlt2b4f3rb5FTzdmenn4iK/V983IXjJ++KOXqiVQsvLAkcMjb8hiaSErVU4vgt4ees+07sV88zYPLn7ve3hh17qblVJUqWHAedvRw/fpzBZGRniyW5EplMPvqr0ePGjqUTm9xcCT1LQ2crdAFtkmPgKNmwgcK4BAEIQAAC+QKs/B/QAIEABCBQyQXKOz/z5v0zetYd6Xv/TDFXzTZoBqnzrtJ/UoRTY8Csn2WrNm5ddEpu4dx8aPCE7vQeXpQi/1f5FL2dV/0hPw6/9v2fK3Z9snS4h7V74/p2F/9ePIf+HG5mX7f1yLmjPvO0KNldoS4KmnqznkrbtebI+wv9J6fWoKmjX63dETHvkOatlRxeNS8XzebLFMOmxYTZYy0jYrYtPCrhONWqzqD3JKZ3JWZwG49e8LPtxqgj60J30UvSbDzaBX7yaT2unhUB+uIpHAPFsNbTpl2rr8d1XBq5bclVwnbw/cKrbYCeaDUBa6aeNONiFKtV0+VKxEnSeXY/zcYGxK3nuN6HgrZvudr6p5a2Jdqvz9PuqfbmoF8sFBoaOmPGDHpDM7r14cOHd+zUib4skUq3bt1Kb9xsY8NbsCCULlbyXuS1osEs2ia+ggAEIAABIwXw/IyRUCgGAQhUdAFGlkjziLYxBz2fQu+6Sz8CkZOTk52dLRKJ6EVEd27dmDj5+1s3rvu1aqNzXdmGTet79wwotf0D/+wf+9W4UotVxAKKJ39P+eFok9CwsXWL7CVWEcdShpjpzQBmzpzZoX37QYMGFVTfu3fvkaNHQxcssLHRPD6k76A3Q7ty8XzDxk30FcB5CEAAAhDQJ7B65e8sM0tHRwc+n09vxEJvymJtbU2/DYzD4dAvs6b/gdVXEechAAEIVCyB8s7PvF6eq/fX6GXe36xiORaNVv789KGbDGcXRx4zO+nCzpgUhy7+7nqSGWV28tOXedulvWmEwbZxruFEb6dW8Q8bHm/J4sUWFtrXBb0++vbt271792In9YxV77eWnvI4DQEIQAACGgH6BzT+AcW3AgQgUBUEypvP5K83y1utpAuMxWTF7Nul60qRc+YcvYuOSq370RU1S1pWAAAgAElEQVRQS5LvnN99LjEjV0WYPFffHlO++7wevXeBrkDVWReXT13zsPgl81a/RExtTL/vpjIc5hY6VvfpPFlstJolcDrVKoMKxgABCEDg3QrQP6BLWcn9bvtH6xCAAATek0C585n87SC1u4fp+uw5xvhVZLqqvycG03bDsPEbF+pXbPWcntEx7Tsv2tFZd/96quguXCnPagSQ0FTKW4tBQQAC71yA3q9ZqXjnvaADCEAAAh9coLzLZwvvB/DBB4MAKp8AspnKd08xIghA4P0IYD+A9+OMXiAAgQ8uUO75mbztIDVvdaSnZ/Dh84Pf0EoVgOb7Cd9UleqWYjAQgMD7E9Du16zZfhMHBCAAgcotUN75Gbyuq3J/f2B0EIAABCBQQQXwA7qC3jiEDQEIvK1A+edn8l+eolbhl0Bvi4/ypQjkfVPdvH61lHK4DAEIQAAChQSsuNaedb2w3gzfFBCAQBURME0+Q680s7CsJJtxVZEbX1GG2aa9ns0SKsoAECcEIACB9y5w7tRxuk/kM+8dHh1CAAIfRqC8683wz+WHuW/oFQIQgAAEIGBQAD+gDfLgIgQgUHkEypvPsPP3a648IhgJBCAAAQhAoBII4Ad0JbiJGAIEIGCMQHnzmVJ+/aNIPrl1XVScUG1MLB+8jFp0ef3Maatv5JaMhMq5f3DT2l0PZCUv4QwEIAABCEDg4xMo5Qf0xxcwIoIABCBQNoHy5zMGn8CRPz0aHXvuicSYfIaSpty+ePE/kTFldQxW+STq64DB8y9nl33TaEqSfPPGnec5OlpQi2//s+fAlTSljp4Nn6Ky49eM6z/wu20P5YYLfuCr0v82TxzQ/9sNt3N1DP8Dx4buIQABCEDgrQW0+zXjgAAEIFD5Bcqbz5hQSPFk76J54f++fPuUQROE4tmZk8kWzbo34DKKxERJE2NmDg4IGPfnk4LXJFPiO3sWTRreJyCgz/BJi3bfFpcxhTJq8JQ09XGKUp6clPlRv6aZkmUkJSuUKUnpmIIy6r6iEAQgAAEIQAACEIDAxyBQWX55o3h2+uQLK7+vvYumM/KnB+YHRSYWkValHg6duel+3f6TgxuSW7vXbQ5eyF07t7sgf+NpU98VpuOnv66tmcx29+SaumlTtsewbf3zmt+fql3r2BdNCE3ZCdqCAAQgAAEIQAACEICAaQVMn89Q0ifHN67eduxOhpLNr+kmIUTwOmR15tnfglafS86hX1XDcfBqP+TbsT09reiPz9Jby7/6+bhYUy72x4Gx2vIWbUK2BDWhN4HWW6uQhPzpv6decv0m1i+cM1DiaxFzIsUBs6e8XBhy93VpeVJs9E1G82lBgf52DNKyHidpzJLog0mdRtXmFGqQfi+9OCFyRvAe0m9+6Egf67xLD6NmBC59lC5nO3h/+sX4MV1qWhj87K/OOPLTqFX38+r6zPgrtHVBePJHf4XM33U9Vcpx9G7dxPLe2bgUs7q9vwse04pP51WGhqxMvxy9bkvsxcdiijAsHWt4tQv86avmtppAVKKEfRs3x5y5l6lk2dZq3W/sNwMa2ZY2A0eJTk3/cumd12Nn+M6KmtdSEycluhqxcMOpe89F9EI5tp3nJwGjxg5ows//jjEQRhFGfAEBCEAAAhCAAAQgAIF3KGDqfEYtvLB8+orztp0Cp/m7KJ/FHfzz8Zvomdaenb78vqujnaU66/7RiHVr5nJqr/+2vjkxrztyaXjAg79mLbnWdGrIsFqazILJFVhoq+qt9aZh+ZMTp1O5LSbXK5TOqDJOr1h63nPS8mFeKSvfFFUL78anEc//886JnfHNFvmgJVPb1yLL4+9lqWs7vimlenV186x5B9n9Q0JG+FgXJC2Uef2+E4e7spPPbN+88ucc67XTWtM5kd6Dadf25zXeMmXGvwtnRRctpXx171aq09BfJ9W8uHjRIctBwfNdzixeufqvDk3G0x56h0zl3Ngwbe5B6pMvvh9R355kXNqwfP+1p7mq5rZsSnIncnrQfrOuX/0cWNdKeH332shfQrlr5/esZnjiicFrOXVNuJR+aEaVdnzBr7sL4lRLnt1IeM7t99MPfraKl/GxW7bOmvoqdOU4Hy7DQBh6MXABAhCAAAQgAAEIQAACphcwcT6jSj3z97nsml/9Nrm/C910Cx+rywfnZRWEzXH283fO+8qrJnXlVMjNhHRlfVc2g2Pv4s7NtjEjZjbV3d3di86U6KtV0Kz88Ykz6byWXetZFZxSpZ1cueZ+8x9X+juyZCmF3JTiFDGxdOGbSR6m5EjlKRJOHQdz8uClWEkc8z/4S5MOLV4UfrPWmKXTA2pbFs5X6gwY0U87x9K0turhN5HR5wJb9s5bp6aW50rkas2T9Awmx9KKkzcrwuIK3LhEZc4313XnGDa1vLybMT05h7NqeTdqYd5w/enEFxKqvjmD6BkyM+Pc1n/Sqg9ZMXWYdjYpR7aH7M/jVWec3bw31XdKxMROfE3nXh7k1shFBy+md+tTSkLDtHRyc9fEpzKzLxknv4FfM196yE2aejImTNm55fzAhV35mXrD0DVOnIMABCAAAQhAAAIQgMC7EjBxPiNPSUgm9p0bOOpsVyW8EbNp26ErD19mU1a2VlIlEciUpe6mVWotWeLxc5m8lt3q0YvT8g5KeDFi038+49fkrcPShWdeJ3DVpj5qewE7Iabo9YRV0xOUdQLDZvZxN9NVU3OO7dSoEZ+cuJWiyMtnpLfDRgedyNYW53VZtOm7BnlzS/rqFzrPZNIZE0WvHWOyGITSpkRE35DlydeTKNsOfq5FEz5NFXnytcdqhWTZyL7LCjVu/1yoIqXkM0bEqCnCcWvVzH7Hv9eT5V2t9YdhZGMoBgEIQAACEIAABCAAAZMI6Mw7ytEyg54boOhDRxPKF7Fzg/9IaTps3C8tavCoV3Eb50UKdZQreqr0WtJHx85l2n7StU5BCkFl3dh7XpxDFo3ou6igtagJg+MmbFjcjVedRyQZmVKKZedEP9lDZWZkyAivGo+WyIvatVN3638Pb1m6zTNkpK+NnsdPKG0KUjB3Y15r8C/zO8k0+6QxzZ08ik5zvC6lC0VTgcnSpDRvDv1DptRKNWGx6cSnxKFFt+00fc5gj0LJDptXTW9OVqKJUk4wNOPV3lkDYZTSBi5DAAIQgAAEIAABCEDApAImzmfMXXw9yNlrl57J63sWn0OQP7+WSDkPDBzSsabmM7Y0R2BOiuQzZhZsIhVJ6M0CCh2l1pI+PHpBZNu6q+ebGREGz+/HNeGy1/mD7N4fQcsfdQ7+daAPn8lUefk6kQOnE7I6tqMfoqdEt88kEkFAPU3iktezvd+oOQO9V8xcPmu6YvbCMc10PVEvf3Hl+itGDV+X/EEyuG7ejd303BmGmSU9YImQfguPdYn0yLLJz9F7NBWlBbX1D9nMqZ6AXLhFb7VQz7nYnTN3beLBOHvrnnJ8W089uxTQsz4H98apm/T9zNfe8DM1ugaiTLt5M5O4NqxOLwrUH4aumjgHAQhAAAIQgAAEIACBdyVg4nyG6eg/ouffM3fMmqsa0btxNY44IYOQ/BkCjrOPG7l6NGpf7c98BBaU6F6xN52YOXp5cHb+b8ufx4Y2tVdlPM+t3+NTd05ptST3j/5PZO/fpXbhBV5MK4Hbm2dppCJrNjGzdXYVcOmP8SyP3kMaxYatXLhFNqABub173VWq0YRehSc1CIPj8un3SziMHxfP/dV60YLPvTR7sGmOjFuXrlrZyV9cP7htd7JTrwltHUrkJzpuFINbw9uRxOzeftC2tV1OqqJ+907a51X0HfqHzK7ecWDTqOWbF6xhDv1EoEq5efghIU7adpgO7UYF7AzaMzNIPOyzVrXsWbLM5DRem96tnF7fYtn97YvXHxKRo9n1Nk70LvmkjO5w7u/eskfa1JVFb4EQ+YTbNqitE4sw9IehuxGchQAEIAABCEAAAhCAwLsRMHE+QxjcxuOWzuav3xK7dsFuer6DzaveoIOrleZjP9u1D/1he+22PUtn/EG/WpLB4TrUbuFiWZAR0LMqX3/X67eNB1aExBCWbd0eP3Tq7M4ppVbu/aMXxfyOnWsa+/mcjqNat6B5ueHh0cvn7iRcj7ajQiZ0K/nyGbaj/+Q5L5MnR4asrRP2fUsbS9dGDar/e2DZ7L10SmRXu/X/zRkzoHGxd3fqu0Wc2oO+G/Joxe51occZvNo9f+zQ0d2Qu4Ehsxw7T1uQvTZ8x4ZFRyg238OZXuHGYGrXvTG4PqOXLhT8sXV/9PJj9C7ZTGuXpgN9e7bKS3foAmbVmvtVO3qSatbM4Bq0YmvZmJJbe1YcfKVi8+t3nxw0Jm8/NwNh6DPAeQhAAAIQgAAEIAABCLwDAUaWqPRnWPL6VavVCoVCLpfn5ORkZ2eLRCKhUKhWSLv26H3j2pW2HT59B+GV1mTO9SWjZ936dNn6sXWLL28rrWoluK56sXfKuM22QVtD2vB0PFLztiNUJG2fMDGmVv5rf4gqZe+UsRHWRV6bo7NJE4ehsw+chAAEIAABowXOnTreuKnf0UMHHiQ+dXR04PP5dnZ2tra21tbWXC6Xw+GYmZkxmcYsMDC6SxSEAAQg8OEEDM0TfLiojO055+7hKzmO3ToVWS1mbOUKWU766PDBu1Y13Owt1OInl/Zse2zRfLq3kdNEOgesTD2zbX+Ki1cNG8nd/ftfmNX/ooYRU10mD0NnbDgJAQhAAAIQgAAEIACBUgQqcj5DZd85ciXXqVenGlVmbkYlTko4uf3s4yylZoGZc8OO40NHtbUvz+/YlOKXz67t2x8jlBMLQeMBP09pp319jeHD9GEY7g9XIQABCEAAAhCAAAQgoFuggq830z0onIUABCAAAQhUXQGsN6u69x4jh0CVFCj9d/FVkgWDhgAEIAABCEAAAhCAAAQqgADymQpwkxAiBCAAAQhAAAIQgAAEIKBTAPmMThachAAEIAABCEAAAhCAAAQqgADymQpwkxAiBCAAAQhAAAIQgAAEIKBT4N3tb0ZJE/eGTNt4w/7zsLDhNcy0vVPiOzHh4TvOPRYTXs22g74d368Br1BGRcmenVgZvDy+2eKIyd4WReKlJE8vHdj7z5mrtxJF7t+sXdJL8wZMtfi/w1u3xJxJSM5Ws2w8/Hp/NX5oMz59AQcEIAABCEAAAhCAAAQgUBUE3lU+I396YH5QZGIRQlXq4dCZm+7X7T85uCG5tXvd5uCF3LVzu2syE6IU3T+9Z/u2XVfTCLEpBk/Jnvzz2y8b/3Pu0LPnmL41qjm65O1QrHxxbMO2Gw49AoMa8hVJZ7ZvjgqRVI8I6eyASaeq8K2LMUIAAhCAAAQgAAEIQIC8k3yGEl+LmBMpDpg95eXCkLuvleVJsdE3Gc2nBQX62zFIy3qcpDFLog8mdRpVm0PkT/b+vjnO47Pp09I2LL5Q5L5QkrtbQrYI+yxZ17+2BaPwJbZrv0WRfVlsbfrSzMfh6ZXp5+OS5Z0dik7t4C5DAAIQgAAEIAABCEAAApVU4B1MZagyTq9Yet5zUvAwL6tC+YdaeDc+jXh28M6JnTFs8E+7RF7ta5HU+HtZapqWU/v/wrasnD60pbN5kZSFXqImuvLnPylU9vGQkf0D+g7+auqKgw9yqPy7wchPZugvKUl6moQ4eTq8kwytkt59DAsCEIAABCAAAQhAAAIVW8Dkn/5VaSdXrrnf/MeV/o4sWUohHKU4RUwsXfhmkocpOVJ5ioRTx8GcPHgpVhJHDv22e0axRCa/qizp/F0Ft0GbQf1bevAUz85GrlgzI9t2/Yy29BzPm0P+/Miq8Ov8gNBuziYfUcW+wYgeAhCAAAQgAAEIQAAClVjAJJ/+32QWlPBixKb/fMavaW6rOz0hxLxO4KpNfdT2AnZCTOmwlCQjTUpc2vTo0MSRnkuq7TEp+fz4qIMJ4jbtbPJ7oCSP9oXOiEhsMmVxoA9XX7eld4USEIAABCAAgUojgB+HleZWYiAQgEApAibJZwr6oLJu7D0vziGLRvRdVHAyasLguAkbFnfjVecRSUamlGLZOQnoBWKZGRkywqvGMxwCy4zeLiD7lYRelaZZG8eyc7Mj6qzMXDWx0ewjQOXcifo1OOqV//RlE9s5GW6qFApchgAEIAABCEAAAhCAAAQqmIBpMwAGz+/HNeGy14+3yO79EbT8UefgXwf68JlMlZevEzlwOiGrYzt68oYS3T6TSAQB9WwMPsLDsHDxciQxcXeFQ9w1EzSKl3dTiUVdV552V2ZV+qnf50Rl+Af9NqkN9mmuYN96CBcCEIAABCAAAQhAAALlFjBBPkPnJgVhMK0EblYFX0lF1mxiZuvsKuDS6QfLo/eQRrFhKxdukQ1oQG7vXneVajShlwf97Ax9UPJXyckihfy5UEGUWclJjy2trKu7OVowOB7dA+rEbF7/+9/WX7bgJR9dsy9dEDCtIVdTSXoveuNFquWk7s5ZTx9nadthWDi5Vdf0hgMCEIAABCBQZQUK/2iusggYOAQgUEUETJDPGC3FrtYtaF5ueHj08rk7Cdej7aiQCd20L5+hD8WTXcHf703P++Li8p8uEqv28yOnNrYgbNe+v8yVh2/YFzrtT4rj1LjP9Ekj8162qXx197aQ5F5aNe3SmxjqfRe5tAsfy4aNvisoCAEIQAACEIAABCAAgYorwMgSCY2MXq1WKxQKuVyek5OTnZ0tEomEQqFaIe3Wo3f8tSttO3xqZDsoBgEIQAACEIDAuxM4d+q4b1O/I4cOPEh86ujowOfz7ezsbG1tra2tuVwuh8MxMzNjMg2u9n53waFlCEAAAqYWMME/Z29Wm5k6OLQHAQhAAAIQgEAZBPCjuQxoqAIBCFRQARPkMxV05AgbAhCAAAQgAAEIQAACEKjoAshnKvodRPwQgAAEIAABCEAAAhCougLIZ6ruvcfIIQABCEAAAhCAAAQgUNEFkM9U9DuI+CEAAQhAAAIQgAAEIFB1BZDPVN17j5FDAAIQgAAEIAABCECgogsgn6nodxDxQwACEIAABCAAAQhAoOoKmOZ9mhRVcmdISpq4N2Taxhv2n4eFDa9hZphYLf7v8NYtMWcSkrPVLBsPv95fjR/ajJ//rk39VSnZ8zNb1247fP2FlHAcvTsO/WZ099pWpb1Ms2y1tFFQsmcnVgYvj2+2OGJy3ks9806L78SEh+8491hMeDXbDvp2fL8GPG2maMy43gpKvwWuQAACEIAABLQCun4ogwYCEIBApRUwTT5Tkkf+9MD8oMjEkhd0nlG+OLZh2w2HHoFBDfmKpDPbN0eFSKpHhHR2MDh9ROUmbAhaclLQf1Joezd10onNq8OC5YL1PzSzNpTRlK0WIUrR/dN7tm/bdTWNEJsio1ClHg6duel+3f6TgxuSW7vXbQ5eyF07t7uARYwY19tB6dTDSQhAAAIQgAAEIAABCFRVgXeSz1DiaxFzIsUBs6e8XBhy1whatmu/RZF9WWxt+tLMx+Hplenn45LlnR0sDFVWPL9w+ZVt56AvOnqbE1LH/eu7p6fGxacqmllzDFQrWy0if7L3981xHp9Nn5a2YfGFwu3Lk2KjbzKaTwsK9LdjkJb1OEljlkQfTOo0qjantHG9NZSBceESBCAAAQhAAAIQgAAEqp6AwQmQsnGoMk6vWHrec1LwMK9Sl34V9MDIT2boE5QkPU1CnDwdSsu12HY1nBiia+fuZ2tWu8lf3Libxa3r41TK0ray1SKc2v8XtmXl9KEtnc2Lzv6ohXfj04hnB++c2BnDBv+0S+TVvhZJjb+XpdYMztC4ygRVtnuCWhCAAAQgAAEIQAACEKiUAqXlDG89aFXayZVr7jf/caW/I0uW8tbVifz5kVXh1/kBod2cS4uN6dR5yvjrwWFBY262+sQ59dwVs0G/TvDjGVpsRsdTtlp0RQZDZ8tKcYqYWLrwzSQPU3Kk8hQJp46DOXnwUqwkjoXmiUqMq7xQb0+LGhCAAAQgAAEIQAACEKhsAiaen6GEFyM2/eczNrC5rc4P/4b5KMmjvfN+XH2/yZSQQB9u6Q2openJKVKH5r0+bWDDYLJk908dvpKqNNwH/Yx+mWqV1ioxrxO4atPGNd8U2ibgdR0d4yofVKnBoAAEIAABCEAAAhCAAASqhEBpcyBvh0Bl3dh7XpxDFo3ou6igZtSEwXETNizu4WQ4d6Jy7kT9Ghz1yn/6sontnIyJS5KwafEeWf+wmUPp7dP69B/cY+2k4LAN7VvMbGloQ4Cy1dLvwOZV5xFJRqaUYtk5CejlcpkZGTLCq8bLH4LOcZUHSn8ouAIBCEAAAhCAAAQgAIEqJmBM3mA8CYPn9+OacNnrzZtl9/4IWv6oc/CvA334hpMZoko/9fucqAz/oN8mtSl9n2ZtRCrx00Qxu1pNft4DMwyeZ9MarINpqblqYq1/p+ey1TJAwLTz8nUiB04nZHVsR09KUaLbZxKJIKCejXbEesZVdigDkeASBCAAAQhAAAIQgAAEqpqAafMZwrQSuFkVGEpF1mxiZuvsKuDqTzC0paX3ojdepFpO6u6c9fRxlvYUw8LJrbqheiw772bOyp3r1+xj9fN1YqTfiNlwTeU6xMfeYF9lq0XHQ8lfJSeLFPLnQgVRZiUnPba0sq7u5mjB4Hj0HtIoNmzlwi2yAQ3I7d3rrlKNJvTy0D47o39cZYTS0uCAAAQgAAEIQAACEIAABLQCJs5nyqiqfHX3tpDkXlo17dKbFup9F7m0C9/AUzSc2p/Pma5au237nB820PkPz61Z/5+/GVazlP3NylaLEMWTXcHf703Pi+/i8p8uEqv28yOnNrYg7GrdgublhodHL5+7k3A92o4KmdCNfvkMfZRtXGVERDUIQAACEIAABCAAAQhUOQFGlkho5KDVarVCoZDL5Tk5OdnZ2SKRSCgUqhXSrj16x8ddbtexi5HtoBgEIAABCEAAAu9O4Oy/x3ybtTh66MCDxKeOjg58Pt/Ozs7W1tba2prL5XI4HDMzMyazlHXg7y48tAwBCEDAtAL458y0nmgNAhCAAAQgAAEIQAACEHh/Ashn3p81eoIABCAAAQhAAAIQgAAETCuAfMa0nmgNAhCAAAQgAAEIQAACEHh/Ashn3p81eoIABCAAAQhAAAIQgAAETCuAfMa0nmgNAhCAAAQgAAEIQAACEHh/AhUtn1Ekn9y6LipOqH5/ROgJAhCAAAQgAAEIQAACEPhIBSpaPiN/ejQ69twTybvIZ9QZR34IeH0EXcj5SG8ZwoIABCAAAQhAAAIQgAAE8gU+jvdpfhy3g2nXZurqejJlxqnFs3d+HCEhCghAAAIQgAAEIAABCEDAgADymUI4LGtnD2uisrplYUAMlyAAAQhAAAIQgAAEIACBj0XA9PkMJb6zf9uuM9f/S0oVSpT0OLnegUsWDHDX9KQSJezbuDnmzL1MJcu2Vut+Y78Z0Mg2b8mb/kuU9Mnxjau3HbuToWTza7pJCBEYoUflPDi4Ye3Os/+lywhhmNvV7PT9/PHNeAxNVWX65b/Xbo69+DSbwfNo2XvkN0NbOJYVghKdmz1q4cNPF2+c6G2ujUvxeNv4Sbtdg/74tY0NQ5159reg1eeSc1SEcBy82g/5dmxPTys6Ckp0deOSzeceJKfnKAixdG7SY9Sk/2sjMDNiaCgCAQhAAAIQgAAEIAABCOQJlPVjvH4/lTD+wMGLpOuYCV/VsOeylNkilbtA0w0luRM5PWi/Wdevfg6sayW8vntt5C+h3LXze1ZjGbikFl5YPn3FedtOgdP8XZTP4g7++Vh/32+uyO7+MXvtGZeBE+a2crOictKfp7BcLbXJDJUdv37q3H+Y7UZO/cqDenQscuvcqcJ5q8b7Wmsvv+3BsGn4aQNW3NVzT+XedTh0bWXK/86ksBuOaKjNnZjWnp2+/L6ro52lOuv+0Yh1a+Zyaq//tr45UUuexccnmQV8N8uPT2Xc3BexM3S+3drfBria/o687ZBQHgIQgAAEIAABCEAAAhVF4B19ejb3aN+tQxPLwgrqjLOb96b6TomY2ImvmZLx8iC3Ri46eDG9Wx+nV3ovOaad+ftcds2vfpvc34WOtYWP1eWD87JK11WK03IIz8OnaWNvexbdWYPXVdTpZ7b8k+76RdgPg2rQkyF+TTyUkyZFbT07tFEPxzJtjsCwbdTNh730/OmnI+p4coji2ekTyebNAn1t8tIjjrOfv3Ne5141qSunQm4mpCvrv85aHBq1btmMS4hvLVnc6HVnbgr7uZYtitJFUAICEIAABCAAAQhAAAKVT+Ad5TM6oOTJ1x6rFZJlI/suK3TV/rlQRWz1X7JJSUgm9p0bvO16MG6T0V+3+SVszogLddp07PRp90/93LnadEWWfOMJ3WDTavkru8ycm/vaR/17M1new7Fsj80w7Jr2bspZcObfJ1961iFPThx/Yd16fKP8dEYlvBGzaduhKw9fZlNWtlZSJRHIlFQJHhbPrZo5eZyZS+/bVqasqkSLOAEBCEAAAhCAAAQgAIEqIPD+8hmKPohtp+lzBntolmXlH2wenVioDFxi0B/vtVXf8uC49wja0PrBpZMnT574M2RvZN2Bs2aPaGKTlyy8fXOGemfwGvdpYz3r1NFHX7gqD5xIc+gU4E3PudCH8kXs3OA/UpoOG/dLixo86lXcxnmRQt1NMViah2pMG5junnAWAhCAAAQgAAEIQAAClUbg/eUz5q5NPBhnb91Tjm/raVH0URW1gUsuvh7k7LVLz+T16cVcb3mwbeu06VenTd8RSTHTJ25ad7jrqsGu5i6Na5CzN66lKLw8NFM0ihdX418R90YuBa0z2Rx6hZosW0YRrnGP1DC4Dfp1E/x7aM/ZWrLTWbW++Kx23s4ARP78WiLlPDBwSMeamr6kOQJzoiefecuhoTgEIAABCEAAAhCAAAQgQMj7y2eYDu1GBewM2ngT5K0AAAkfSURBVDMzSDzss1a17FmyzOQ0XpverZzYhi45+o/o+ffMHbPmqkb0blyNI07IIMSITcByb2+PuGDt28Szuo2ZPO3W3QzCdLE3p2dnmI7+I3tEz9w+dxlzRCcP9aPjW6KeO/aY186hYJkXg+vmaUsO79txzKapZVaayrtrB7fSUilOzV4DvGLWrggjFi2md3J+rcpx9nEjV49G7av9mY/AghLd02y2hgMCEIAABCAAAQhAAAIQMJHA+8tnCIPrM3rpQsEfW/dHLz9G77rMtHZpOtC3Zysnej9lQ5caj1s6m79+S+zaBbvpTY/ZvOoNOrhalfKQiVohUwuv71gRI6I3QyZmdjWbDAr6poP2UXuGdeOvl8yyCdu0a+nZXMJ1azFk1refF9nczLze55P6JIXFrpwXy7Tx7PGDf3s3TmkTNSxBxy86bP/lpGWv4S3tCgqzXfvQ6dvabXuWzviDDoTB4TrUbuFiWUrwJrq1aAYCEIAABCAAAQhAAAKVXoCRJTJ2AZRarVYoFHK5PCcnJzs7WyQSCYVCtULatUfv+LjL7Tp2qfRYGCAEIAABCEDg4xc4++8x32Ytjh468CDxqaOjA5/Pt7Ozs7W1tba25nK5HA7HzMyMycTv1j7+O4kIIQABowTe4/yMUfEYXYiSZz57limj9wMrdjA59q7uDualTagUr2bo6/fZl6E4cA0CEIAABCAAAQhAAAIQKCJQYfMZxZNds77fRz9MU+LgByzbMK5uaU+8lKhm4MT77MtAGLgEAQhAAAIQgAAEIAABCBQVqLD5DKfO2D/2j30/t/N99vV+RoReIAABCEAAAhCAAAQgUCkEsHy2UtxGDAICEIAABCAAAQhAAAJVUgD5TJW87Rg0BCAAAQhAAAIQgAAEKoUA8plKcRsxCAhAAAIQgAAEIAABCFRJAeQzVfK2Y9AQgAAEIAABCEAAAhCoFALvYD8ASnwnJjx8x7nHYsKr2XbQt+P7NeAhbaoU3y0YBAQgAAEIQAACEIAABD4uAZMnGqrUw6EzN12x6jI5OHhyF6srm4MXHk1VfVyDRjQQgAAEIAABCEAAAhCAQKUQMPX8jDwpNvomo/m0oEB/OwZpWY+TNGZJ9MGkTqNqm/KFMJWCHoOAAAQgAAEIQAACEIAABMopYOL5GbXwbnwa8ezgnRM7Y9jgn3aJvNrXIqnx97LU5YwT1SEAAQhAAAIQgAAEIAABCBQXMHE+oxSniImlA99M8jIlR5qSIuE4OJiTrJdiZfGO8TUEIAABCEAAAhCAAAQgAIFyCph6vVl+OOZ1Aldt6qO2F7ATYsoZIapDAAIQgAAEIAABCEAAAhDQLWCSfIZBUVRe82xedR6RZGRKKZadk4AQKjMjQ0Z41Xgm6Uf3EHAWAhCAAAQgAIE3AtofygyIQAACEKgiAiZeb8a08/J1Ig9PJ2RpExxKdPtMIhE0qWdj4n6qyN3BMCEAAQhAAAIQgAAEIAABQwKmnjfhePQe0ig2bOXCLbIBDcjt3euuUo0m9PLA5maGbgKuQQACEIAABCAAAQhAAAJlEjB1PkPY1boFzcsND49ePncn4Xq0HRUyoZuAVabYUAkCEIAABCAAAQhAAAIQgIAhAZPnM4QweQ0GTF89YLqhbnENAhCAAAQgAAEIQAACEIBAuQXwXEu5CdEABCAAAQhAAAIQgAAEIPCBBEyRz2APlQ9089AtBCAAAQhAQLcAfjTrdsFZCECgEgqYIp8xjiUgIMC4gigFAQhAAAIQgAAEIAABCEDAKIH3l88YFQ4KQQACEIAABCAAAQhAAAIQMFoA+YzRVCgIAQhAAAIQgAAEIAABCHxkAshnPrIbgnAgAAEIQAACEIAABCAAAaMFkM8YTYWCEIAABCAAAQhAAAIQgMBHJvDu8hlKmhgzc3BAwLg/nyheD5oS39mzaNLwPgEBfYZPWrT7tlj9kXEgHAhAAAIQgAAEIAABCECgAgmYIJ/RuSek/OmB+UGRiUUlUg+Hztx0xarL5ODgyV2srmwOXng0VVWBsBAqBCAAAQhAoEII6PzRXCEiR5AQgAAE3lbABPlMyS4p8bWIOZHigNlTWlsXvhobfZPRfHJQYJdWrboE/jypGeNG9MEkecn6OAMBCEAAAhCAAAQgAAEIQMAIgXeQz6gyTq9Yet5zUvAwL6uivyCKTyOeHbxzYmcMG/zTLpFX+1okNf5eFtacGXGfUAQCEIAABCAAAQhAAAIQKClg8nxGlXZy5Zr7zb8b7+/IKt6dmFg68M0kL1NypCkpEo6DgznJeilWFi+GryEAAQhAAAIQgAAEIAABCBgjwDamkPFlKOHFiE3/+Yxf09xW39pd8zqBqzb1UdsL2AkxxjeMkhCAAAQgAAEIQAACEIAABIoLmDafobJu7D0vziGLRvRdVNBT1ITBcRM2LKa/5hFJRqaUYtk5CQihMjMyZIRXjWfaEIoPEF9DAAIQgAAEIAABCEAAApVWwCTJBPWah8Hz+3FNuOz117J7fwQtf9Q5+NeBPnxmGCG+TuTA6YSsju3oyRtKdPtMIhEE1LMx+ZK3SnuzMDAIQAACEICAkQIFP5qNLI9iEIAABCqqgEnymTeDZ1oJ3KwKvpSKrNnEzNbZVcDVPkvTe0ij2LCVC7fIBjQgt3evu0o1mtDLg1NR6RA3BCAAAQhAAAIQgAAEIPCBBUyczxgeTbVuQfNyw8Ojl8/dSbgebUeFTOgmKLFpgOEmcBUCEIAABCAAAQhAAAIQgMBrgXeaz1j4fB+1v7A1k9dgwPTVA6bDHwIQgAAEIAABCEAAAhCAQPkF8PBK+Q3RAgQgAAEIQAACEIAABCDwYQSQz3wYd/QKAQhAAAIQgAAEIAABCJRf4P3lM/v3F1l6Vv7Q0QIEIAABCEAAAhCAAAQgUMUF3l8+U8WhMXwIQAACEIAABCAAAQhAwOQCJslnGCYPCw1CAAIQgAAEIFAOAfxoLgceqkIAAhVKwCT5TIUaMYKFAAQgAAEIQAACEIAABCqLgCnyGQovIa4s3w4YBwQgAAEIVA4B/GiuHPcRo4AABIwQMEU+Y0Q3KAIBCEAAAhCAAAQgAAEIQMDkAshnTE6KBiEAAQhAAAIQgAAEIACB9yTw/yyFEcQVvuuPAAAAAElFTkSuQmCC" alt="" />

Decode范例

现在,我们随便删掉两个数据(校验)块文件,如 40kb-image_k3.jpg 和 40kb-image_m1.jpg,然后试图decode重新获得我们的小丸子图片^o^.

1. decoder使用方法

./decoder 'inputfile'

在decoder中不再进行参数校验,因为在encoder中已经做过这个事情了,并且将参数保存在了meta文件中。当然,这只是Jerasure为我们实现的一个范例encoder/decoder的做法,具体处理方式可以由你自己通过调用接口来重新决定。

2. 执行

root@fs-:~/Jerasure-1.2/Examples# ./decoder '40kb-image.jpg'

decoder会到Coding文件夹中查找前缀为40kb-image_k#.jpg、40kb-image_m#.jpg 和 40kb-image_meta.txt 的文件来进行数据恢复的工作。

下图可以看到,我们的小丸子图片已经在Coding文件夹下被创建出来咯!而丢失的那两个文件依然还是丢失的状态。

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alt="" />

好啦,以上就是一个很简单很简单的使用过程了,同理其他的Erasure Coding实现的调用也很类似,重点在于参数的选择(m、k、w、packet size)。关于参数的问题,筒子们可以仔细了解各个算法来精心选择,当然也可以通过阅读源码中的实现来选择。

相关阅读

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《Performance Evaluation and Examination of Open-Source Erasure Coding Libraries For Storage》 推荐!!