From 8a043ef1946d743424fbee2a53e7bae46e40686f Mon Sep 17 00:00:00 2001 From: vtempest <1274452+vtempest@users.noreply.github.com> Date: Tue, 3 Sep 2024 12:32:42 -0700 Subject: [PATCH] Trafilatura.js - port of 33 py to js files for extracting article/cite. also Readability2 --- data/dictionary-index-152k.json | 2 +- docs/assets/highlight.css | 7 + docs/assets/navigation.js | 2 +- docs/assets/search.js | 2 +- .../src_extract_content_core.Document.html | 23 + .../src_extract_content_core.Extractor.html | 25 + ...act_content_courlan_urlstore.UrlStore.html | 42 + ...xtract_content_deduplication.LRUCache.html | 10 + ...extract_content_deduplication.Simhash.html | 14 + ...rc_extract_content_downloads.Response.html | 13 + ...src_extract_content_settings.Document.html | 30 + ...rc_extract_content_settings.Extractor.html | 27 + ...xtract_content_spider.CrawlParameters.html | 19 + ...ml_to_content_readability.Readability.html | 365 + ...tocomplete.suggestNextWordCompletions.html | 2 +- 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| 312 + src/extract-content/python/filters.py | 286 + src/extract-content/python/htmldate-core.py | 982 +++ src/extract-content/python/htmlprocessing.py | 412 ++ src/extract-content/python/json_metadata.py | 268 + src/extract-content/python/main_extractor.py | 666 ++ src/extract-content/python/meta (1).py | 14 + src/extract-content/python/meta (2).py | 40 + src/extract-content/python/meta.py | 32 + src/extract-content/python/metadata.py | 496 ++ src/extract-content/python/network.py | 71 + .../python/readability_lxml.py | 520 ++ src/extract-content/python/sampling.py | 73 + src/extract-content/python/settings (1).py | 109 + src/extract-content/python/settings (2).py | 41 + src/extract-content/python/settings.py | 282 + src/extract-content/python/sitemaps.py | 301 + src/extract-content/python/spider.py | 351 + src/extract-content/python/urlstore.py | 575 ++ src/extract-content/python/urlutils.py | 173 + src/extract-content/python/utils (1).py | 260 + src/extract-content/python/utils.py 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h5uAoGbCs8/TSejD5ej/85GV2MPjaOHGluP36Xn4YXF/+cnF6Mhpejs+bhM9t3pu92fHN+fX2AwK0B2wp/Gd6en2buT/64Ho4b3x8LBmwrHA9/nZwOx8OLq8ZrhrmmtlX916fb8eiP8eRiePnrp+GvzW9gBQMvZkkTKztoVbMYrbINp7FVtccNPz5TYbX6kezu3q7uu5a7yJvqnv5lV7e214PumW9X96zlSZfGuu1ejcczWxfkc+RyaVd30HLDcGPdc8u6W24Zb6x7ZVl3y40vTXV/tnxdfu7puvwcWtYd9qTb8v3yc0/3ywfLuh/60r22rHvdj+4vkV3d2l4PunOb263obrvdvbHuxLLulhvumupeWs6TZU95srR8n1/2dJ9/tKz7sS/dlvP7saf8ji3nd9xTfseW7ztxT/ed1Re7urW9PnRbvi5XPV2XK8vPVauenqtWXy3r/tqP7sRyvJOe4r22fF2ue7ou15bjve4p3l8tv19+7e798pkCkmESLPzHmgUkNz+uW2Rz8/tmu+O3fRiNWyymbx2DysLV9dxfr8K7eXCb/bCpvKIF2xrTryrdRHdRsrqlg1RTY9GCbY2bXx8mExqxovSZ3H8MZ0G90tHZT+vmvS6PGcxOY//bvPbH8zZdmG1bRCFzChed0Vb18YggqftB140u0tSCsIOKu5SLal/hBdosfcJJ/LjmubsKrVsrXam88+ue2a8QuTHSlcY4+HywxMxGVwrrl7KskNi8nGWzKK5r1yqtiuO6cbnSRirDgxU2fFBqpO7LMvq2vFzXPPJbITJnqLNIrq5q1vqpCmZmpCuN+kN5fzz6ycPBSg1TFvUah6kn90Hyi78KPtUtRFUh2LTVpeKbIP2K7bJuLdZnNOetdaV6/ZiWGWhW3LJCdsFcV7o/h/MkiC9qFw+t0GyY6kpvuNI1YNOP/VmYKvK2LCrObcL6dHMxuR1f3dTep5vZ3jWz8FBa/cawTvIfDat6YdC/rPu+kOTLTFS/JWR20wbNnc3UYwXB9yRLyWY6ds2sqsm+UjmaB0aBzDqCjJZWNS2C+D5IS0BfZwaaqCJtreqKg0X0NRgtHpOnjdt1378zbaC9VX2rJA4fz6L13Txo8DG7TBtpa1WX/qZb+mmtRh+Gy3SRtvZ1/dHwe3U5WX+0/0pdhar0J3E0b6eLNrYfr3EQto3XrqndeD0E0y/jIGwWp00jq0q+L+bjaPy9WWS2jawq+RaHSTAOwvQz5I3U5BvaV/R+PZ8/BP6s4a2PtD1cV/WTR93vYTX4BFabu2xq/sB7rPl5q4PvsKmig++vpZra311TXVburaXa2t1ZU10H31dLNbW7q6aaDr6nVmtqeufaSTrgrlWqqOXdNNV0+L20Ok5N76S7OB1wHy2PU7O7qI5P63tok8/ufU8Xouq9CGY/rZyT88e3rs7+2ejc1sb8vl0LxzNn8HHBq48f0/oobTSZbe3quhl9vPptNDlEHjRhV+XVb6P0VPPk7Pz2dHhz1kYlNGFX5Xg0vNXHh1uLRBbsary+GZ2e36bFIA6QWWLErtKt6fOPw19H+pRsg6pFG6HYRkdX9gEBxTbs6hx+Gn+4usksNwyj0bQTVYbf7dSZJiyP8XA8+vXq5nx020phobnleWf4aztduYaWFZ2PL0btJOVaWtBkPn0s/GT68LdptEiNvJsHibF3I//woX852fxysvll3ffBqT+frud+EtyGi3Dux2Hy9MvT6YOfSi19OcY9Vpt6PkDY4+r46P999++1v/Lxnp5Mava/2c/qRka3+e9Pw9vhTWUYDNu5RnUdNlyo9nYVfU4W/vcKRze/aDz613F0t/kW9S3pBPm87aaifV33tz5Ve/4tCO8f3sXBPPjqL6fBu89x8O91sJw+VcRCt5ns2kx2bepGRxu42bYfB/HifaFbFJ3yjiss1o1XeSSeGeGH2F8Ft4/BNPwcTsOkrQvlBm16YObASm8HffctuNv+cZXEgb+Ag5/9YvItuNv+Mftx7f2rutHt+GY0/FgSo9Iu8m2fD0epW/Xj8C24qxmEb8Fdswj8njP9nPup8V2rNo6nfjTwOvwSPgaz0K/r+/b3DSNQ6ObZOOw6IhZaxWTXfWlkdjfa3B/TB4xpkDvbZcRm97P8Hzct2s2Lp1nj34J07+Xw+rwsWJU9V5usEb3KSDT1wrYLnej/qk2HfwXpl22Gq1My6k2kY1P2VJtZm0RfgmX4V/C3VZA+CU8D/Fi7/dlk97PaV+/jPExuC8bNiADzZrvn3QeOPO9zEj1+i+LZcz5vf1bX53D1exTPTqPFIlqe3y+jOJg96/iuD9C4ifc7l571Pt068i6J3k0f1ssvz4Qg/e0kiSbZbxuNfZrGt8HCXybhNH0BeTYHSF/YSIOQED+fj8vmD++S6DGcPheY/R/SH9feb7RpNja7KIsI6cRs3SQUxLVcLOS+yNU4/dVOU7hMgvizP33Oc93KihbyQa94cZp9MvHpAE1viZ3mAjNjpcfolmH63BysVoeINKzYlphG4NAI2pFVcuGl81Z6ocZRlLxbJQF+pdgpTH+ezhPpzyfpz2u/aEfLr0GcpNPsOLqJouQ231fJNVjsDZppcAEU3S2P0GM4fTcLV9k3t8JoCf6qJFiP4XSS/xn4q0aPmnrOOQvjcPowD5IzJIBGsI6EZ2zXCWudGFVGePW35b3xKapCJFeT7Bd1I7ZZZryM1svR7D74teJDV6Z91LBmDHZe5BTV/7JVTRlv4b/UKGhoSMT2YdCeGbjYX355t3vye/cleHrUKyKVY5k22j9xTvaN6g5vamD3iHoaLJPYn4+jf2ztVIe4vPdnzNbOg/KgPBPNVRB8yS6eeoHc/b5FDDejfTsa/WN8dX1+Wh002BM1UTtA0M+6OxCm0Tqe+3japYxi89vKmNTq7W/6e4ZN+pzoFrVvjemP84dvqvd7mH1sGzfHL6Z3+F1iGq/v2irbNu5Emf6n/14Hcdkqbo2o6eadqJsF02gWXK+XT+n/t1JomuhE5TKKF/48/Cv9clzdjU+mSMNCtxrfx/59gx2bJTq3VrrV2vaKyRuwp7DmHBfFQbMpLopRWpbvaGsRlbSLbdsDApK6VnUfTE931d1IamjLt+9C3/a4XEt5uebW1NXLpqznelsFt5I3berm1J2/Cqfvmxzeoh3lLLQPz9ZTfB+IFn64PEhk3kRHKjcfWo0OE0qsdKQ1LSdwkMy9gY4UpptaDlK4N9CRwvR98SCFewMdKfyanrn1kxY30q3EnIWONG5OBreXuDfQmcJL/2t476eSrv37ps+he52mme7URok+L51uO2uvNWfEplLr76XvHAtvposgwVsAygKVNqh7h/Vns1N/+tB0LHQX27bth0C7VvruF2vrTZ+KtLRcc2vq6o3WMki+RfGXRgO2aVN7dSyYhXGgQzEOVk3flradESvtw7T1uGmkVv7icR7myg/VCdW2UW1Smv4+vUM0TaNdR3sL7UO0c7VxjLbfzWkUo20Jxboncy6Gp/+4OL+t+43LQj87AwdEqPITRsOLi6vfR2eT9FN6tb/sVZBpWulKa1qv8kChORNdqRwPb34dZcU1W8vM27Cq84BPQz0vss3XoahWw2oZFq79AZ3ampt+Q6dStq3P6NRX3/BLOg3V15tQ1/F8lTRdBts2qpxQ88UoP8XzW6OXqtJEhV62rdtfUzsv9/IOKUlZrbB1VUqqdme2LCfTUxNxsFrldn0dJDtnrUPVs2hpIxHebux0qDRdN1nnXyIPUJuz1aHidAfCtF7Jsmf07ix1qDaJ/TB9DLyd+6t6dQOfEU0Ndqh9Hc9nlkK9N2VXr1k+8G79+XMQG0/+B2g2zXWpex75M2uqc8a61LwKkjNLs1zOVqeK03+1Fua8tW7jnJ6ZsCc7b65D3f7MWkbvTXWr930cLT4kucpEh2nOmetQ9yxcTf3YysPR3lSHeuNgFVi5o2wNdaj1Pkj+kZY+PtOszkouF012q//T8muYfklgZtcHYLZDP8LV6PuDv17t+rPhBTLaoQ/rbcR+D+7S/19drhd3gZV3sXLTHfqTfoxDZ7KtWZ4a7Fj7LoNt6qdGO/UhJVmfll/sjkHRaA8+WB8JZLZDPx781S9BsPwt68+GCwWLnc6u+rKzM6duTXV8V6tZ0b7GjaxhPfs2as+ib0ubb3hFkx3qD1aJfzcPVw/bLm+nD0G6fGrDkyrjHfqkf3VT+wsjz64i5ax1m0nWNOdsdatY79k4C+b+kyXZhsFutQ/n89Nona+Repj0vL0OlSdR4s8/xXN7D5gFi12+z25mgvFDHKweovnsJki3dNh5wS233aVH68Wjrak/Z6tDxY9xuEysP5ZBq517YVV8J5rrMsz6X+vI+dLowx33QTKez8Ll5/1nqOttnNl1tLdwEMisKHK+aUXWARrKNIx0pRR8fal5NDcWOtT4IVolw+XsOv9Zq+Y6c1Y61npgem5NdKXyc/j9Jpj7Sfi1zQ60nVJipju1+lX5IKFbC11pTBfqkiBe+q2vo72F7jTqF1/j01SNRe5MWFVZfX9Je0r309e6r2x/XHeTYfD9MYqT/1dzU9HOetZsAjdSPxOHnTtWNpaVKGqzm4yY+n/lizETfcRhYgzKITKPqcn2osEGLKj9c3reMbGsfme0M/2P2y9gT54CP56QD4gd5EWZ6c582Zaw/erP17klg4OcKNjsTH0Wn8nTYjaZ+stZaO9iKLHc4TjoujYWL2disTvl6fncrbhgNokL3+U8zI0K8x37lDaYhMv8V0EsuGJY7cyD+yCZLMKlxXwiFrtV7n+3rXxv0aby/MbeUdY6snQryJuzKfm5zb52RB+33fhb4kAuHGWb0rPzx18tJc3ek7zhHvyw+VC0d8LeU9HzHuRrp1uSn5nsQ3tY92xDfe0Nt4y01h7F4X2Yf/215EDObjde0LeDb3G0vJ/MounaqPhy6PtBwWyHbzjr5LNnS/jGVmdqZ0ESTJNJsJxGs/yZy4NkF412qD8tkZS+LFma+02DXeuOg9VjtFzZ1Z4z2t3bV5B+KGEdW5pw8ua6XHuYre/CaL2aPOS38B46txCjnemPg0c/jCef/fU8ebLoArTbmRcpXLUoPm+uu3fCtKyWRdGGvc5UJ3G40MW97YjOm7P6HpV/jjkdnn4YTW7P/2dkR7RhrzPVH4d/TN6fX9gUTk12p/38cnI2HNuSvbfWabSvr25vz3+5GE1Oh5dn52mPdY+r14g7Nt5dzl+Mhpfnl79OGtRaeC7tickO70mrICH1WA68GeUNdvf8lZ1jmayX3/xlfkPuYQ9gRaudebCVto7nFtfLgNUOc+c++D559GNbz7+mwe6eBtarJFrYFE4sdpkzGnFnC9G6O0uLfyWWO3y2ecq6Cr4/WnKBmuzuPWRxvzliaekVJG+vO/Lpp5+kXFpVXrDZmfp/rSK70k2D3eXKLIxWT8tp7K/CYGU3bUpMd/acMx6dT34bXpyfTdLP2dpxomCzB/XD8fjGuvyt0U71bz4APx6eX9jTbxrtVP/Z+W+T9Mn8vH51qhoOEKudeXA5+v3i/DL7urkl+dRkZ9pvr0en58OLyfurm4/D8fj88lc7DkC7nXnx+/n4g77Szn/5ZO2NsWi0wwy6TUM0+f3D+Xhk720Rme3u7X00Hlofg6LRzvR/OLd+EVCTNrV3trXRVL3p+J1jBRSaASkZiLd3XfpxPLmz78ozqfU27NajsH+P1t16tO7fI0ur6WUe2dmn0cSjdMVzPEyXO38/Pxt/sLeMahrtcFHDX4TLwCLpIBY7V56tOsyDdGuCpWXUMtOd+/IQ+DN7i0rEZmfqV8E83bFgeSMxsNqhB/ob7JsVFVv6ic3Ot6Lb3kAMzHZ+Bfh3d3FHVzM13f2cGi66mpmo6c582X1Za7LwE1uLZ0Wj3V/Z99ampbzBDg9oLG0eUcqbs6k5v4v40TiKVuuY20aslWNo9Y7h1f9c27bF899rE85A8BNR/UzVrKu3Bz9F0c+PlYnEj08t1R7+wFRXNnlSaqn3gGej54SWPhQ1lGrlMeh5sfD5p7HUg594nhNa/qjTUKudh5u62Yqfalom7eHPMXVl4weYtjPZwY8sz8kue1ZpKNjG00ntC+7+gInhsAeR5yQWn0AaCjzsmaPZ5zN3rTb/ENX8hOZO9r5do1t96U6oNp2+tbIDKh+Cqku8ZANUK+FWNj7VE472PbXSfOh+p3py4XanVnoP3uZUOzHKdzm1TQ47u5vqOYA3N7VSfvimpnqSwZ6mVnoP3MtUT2zJVqZWgi1sYaonGu1gaqX40J1LNROicuNSu9ywtmGpngsl+5VaabewT6mpaHOb0oGq229Pqi8b7U5qLfvQXUn1ZcNNSa11H7wZqZ5wvBeplerD9yDVk1yxBamVbktbj+qJL9t51Eq5jR1HddOkbMNRy1SxsdGonvSyfUathNvYX1RPNt5e1Er04duKaka6ZANBu0hb2DiAZXdQ5O6Z73gXX0yaA4YtBdlwhp4QQ+1vi+/G8dmPixffgosnx5r19PbQs2LNvuS9a9Xo48s72bW+vkyDBI7DNu/s7YGHYNGneNEcUDwB20Lr4edea8mlh17bKD3kqGvdmFadc20ZXVunW+u4gI+2tknhgw+0Irk1L/j6VbV36p+vqU1DVSwh1rCjt4dVDfsbLQpbeKMvLc7TVKidejw1BBuVeJqrbF1851lpZWV3mmq0UWmnhthijZ3mQg8rq1NXZKGgTkuhB9XQeVZssXpOU5mHFcypc63DUjktrvSDq+M8K7aiLk5TvZZK4TwruVgEp6nSw+rePCsQVLxpqvDAIjfPSiyWt2mq8LCKNgWBNZ8mdKlqvznf3bdr9FyBq4W36fHt4VXC887XkEzqYR4m+oAymPVkV9cGbyXeXk3wei6UlARvpd1CKfB6oisrgbeSbq0CeN2ogwLgLWN+YOHvmoKfrfvdTr3Vet9NXJkVy30f4IFhrSvhsMp3K9EHV/duIJgW924v+JCi3lgwvH9HsW71LoneTcP90vI7f508VL+rR7H2YJJEk7Tlzr2sZeU9vPgtq6HZHfxuzDMdGpZq71d/xv+W0Uv/o03s0v9oGLnTfFeN4qY7y1k5OGba65YRe+6qKXMibdcwYmd+24jN/H3EznDHzSJWh16UtV1F67j6jlTmRtayYdRuze4axW3ToWHp4Nht/G8ZvSRMqpd7ynzRDRvGbmx01ih0WXd5OwcHLnO9Ydwe1gt/+S793epdHEyj+2X4V6P4aQMTbWCyM9Awjpf+IpiNlkmYPDWLJu68aLV1bHF4cjGW+yIV2R3q6u5fwXT/OBYukyD+7E/bBDFvsDMPjDP12d1xYtzmrHrw1uzBjjdGN8+4tnqI4o5G5y3pon/njCIpnfiW1Pw43EGu1Zq4UgY+8xN/+xdN5qxt2+1ftHg0ex9Hi48bM83mrELnJVZbX/GFyDSM7DrWf56Zn6GtEdb0DEISTWZln56FMd28+n+6uRhHdb58W91p0VrrMJphaBfDz/7XcBq1CeKmZcPMfE/6axLBbY+mqUPDt41Ag/htXnrJS3DdGG5ewslLecM4fvTD5Snp99lYlvRcNNkqpiVRaR5X/d+rx2Aa+vN30we/ej0fOKj/e2Ngog00vNY/jD9e3GbtT43+64YYKCgxfUioQaBaRjuJ3t35q3D67jkwVeZrEk20Af1fLaI9jn5Jm6d/bBdsUwC2fHCszTBBn/zZ7Ozq4/utdBvOEJOdedE0Y9rNe+S/mz7ZtJzzaK+mORshbT/fxYE/8+/Cef7lsl4scy0r45j/ouIN6G3TqEFvN5U91w5e3vWSN4fHOEoi473hcLVv80YP1J03Xrc8pE0PdiXunFolIus7c7wPUsnQvL8Y/jq5Hd+cX08+XV6c/2N08c/brn08Rp3Wq47ZxvVnSvxpMb+Pzn/9MJ6cXgxvb0c9BcDs88f6r7eQTk6vLs/Ox+dXl8OLi3/2EwTQ8Q+LRHpIa3Q5nlxenY069z7f2Q/zeDz6oyd3dz39MF/PRu+Hny7Gk3Sbtz6ONxlfTa6HN7fdO1/e9Q+PxuVkfHWNNtB3HQva8Q+PRHr2OB2X29Orm/5Swuj1h8fg9MPwZjL+cDO6/XB1cdZbEMxuf1gUbka/jv647v4S2PTTp58/4lF27+f+L3nHLm/7LBvi9XIefgnmT6fbnWurHxKF46KOzrNhK+SZiyD68tF/ugvOk9XwtLBhsNcYISUvJUqP0SpMwq8/KDLb3l9KNJbBvf/jorHt/aVEQ3e0DKL1D5pb9v2/lIjcPc3D5Q/Kjqzvd+xlRCIOHuf+NHgf5Ssu9hqPvIKXkh+7kow/aALZdv9S4vE1nAXRD8qPrO+XEonVgx8HI1qitNeAGBJeSlyWwffkIlx++VF33Kz3lxKNxzj4+uOise39pUQjib4Eyx82mW57fynR+PYQJsHq0Z/+oHjs+38pEXnwVxTB9hqRff8vKCIPn3IHzvsOR9r5S4nFKp6uguSHRWPX/UuJx50SZ37i/7CA7Pt/KRH51ypaXsyGcRJO58H46fFHraEVdbyUCG2h9uTm6qIHpGJ29+MgwvlvmmuRupmdwQOjux/m9fBiPLpJhaR6Rn+cjq5Tjt29+yX9/rA4XN+MbkeX42FG8VFxya4iUdrzD8Rp1zej0+F4dKYrte0l9XVpVPf/43Lkw83wNi1U1k8YzO5+mNebDT56skpT9ea37vEy6POH+Z9u252Mbk+H16PJx+F1576T/n56zFrwd/+Pna9607EtSYF596+aVVE4nvfwqkkEPHNR3P/giNy/uIj4i8cfGxJ/8fjSYvLvdfSD8yRV8NKi4j/2AEeqU+WxD0TSLCqTx2iVXMfRNFj1tr4H+vzpb7fQ590PBp3vcELjXJYScbCIvgaX0ayHNZp8Zz9/EhjObv+FnXQ+JxhDWj7smvGnPxr7970MvdHhf8LwE4f3KeD2kALm8JalwecoHvnTh/R33Uck19nPP/yGs7t/4bUKYh809PkhLR32cDnracw3Pf0HDPjO0/1on3Q/2tuRLBvqVbQI+hnqbU8//1DvPd3N6d1vW9+PZNlQB1+D+Kmfsd519fMPds7V3d+z7qfx/WCWDfc0Wk79JP3JRbjqYesb7fDnH/qCw/sEUJ0nAB3esjS4D5LhfK6f9n8Pk4exf999YIp9/vzJgHze/UB0f6cH41w6M6SfDjjdqOn+Ksn19vOngent/p96mBDyo1r+ZP/9Jpjrwy6f4rCH0Scd/vwJUHB4/7gvenjcN4e39Kk/XDzOw89Pl8EqCWa97Y4v6ffnT4oyv/fvB90v+5WMedVzw2ZjnFE+uNMbaK7Dnz8pCg7vHxdkL48L+eEtRUJx8HhGv0jXHRjJ9fbzJ4Dp7R4Adb/+a4xq2dCnZ3T6WS7Y9vTzD/ne0/1wdz/170byGdzzS9wf6fkl/g+47+d93fOd7mf33HiWPgIGyQb/9PD4s+vr5x/yvK/7IR90/3i3H8+qe/nmpt/PzW3T2c8/6Iaz+5m9+ws9P6Rlwx4uwyTUp9P7uZub/f38g0/93f2j2/34k7Gt3sUzXM5+DZLL/Dc9O97dsu/x50+Dosf7iaD76b8wwhXv9Ze9PdjnOvv5E8BwdvcvsnsWmB/SsmFPv8N7Gy7CuR/brflcEgyzv59/8Km/+5W97m8CZGxLsU/69cxf+imklO/shx0b0hdGNAuGy2mwMr4I3ekckO/x50/8ose7f1a9UE9zhEtTIfbvenv3yXX245I/XP3mz8NZXxe80d3Pn/bE3d2/eT088xsDWzb862WwmvqPwYdkMddfFwz7gP2o158/GbDX+0eA7hf04WhX3Bb/6/bqsofyzPuufv4kyLm6f/jvftvnfjBfZgD2fxT7P/bCNzMxu7959lFxc8cufC6xBwC87fM/4iop+Lzn3p2fNkfj/MJDsv/j/loS3W8lKqqqdyUlfe8WaRC046SXnSXPB++ZGPZU7bhlEDf1kHu5tR0SxeD7NIgfe1jrbhfGjbyXn42rMAnSj5S/1EBu9b38SE7C1W24vJ8H5wv/vpeX1Fx3P/+zBXF3/07e/VRlDmz5O/m32H+8jFbTOHxM9G97eScv9vrzJwP2ev9O3j2Sg6NdTWhv9U97q7Sw6e7nTwbi7n5fTvczgzmwZcP/4G8mkLF/f75chbNtvfjuY1Pa9c+fFhWu7zdxdP9UUT745c8Rm1+kR72ideGDyB3eYmHHP3+qlDq+T5TuV3nLhr1iVjl9COezX+bR9EufE0qh158/QbDXexba/fMGHO3yGeT6IfZX4fK+x7mDdPnzJwVweT9fdJ8RxUEuT4ff+/vKhdHbf0IS5L3dv5X2cb/IjWoF+ThfLoN43Mu+0HxvP//Qm97u+VcvK1X7Ua0Y+tMHPz6N1n3M//ne/iOGPuftfr2y+6veGNXKGhC3ydO8txIQWWc//8Abzu7+hXVP7PJDWnHFpx8aOwuWq162AZv9/fyDT/3dT/ndFwAhY1s16ac6fg/C+4eepv19f/8RKWD4u5/6u3/gJ2NbOfn3NBP+/AO+cXP/dz1N9VXLPtsN0b0c7zX7+/kHnPq7X+Tp/uGOjG3FJH8TfRsuZ6fRfL1Y9veEX+j1508H7PU+KXrZ1FYc7Rcflv0f99s5VC8b2wq66m3fiKNv/RwhahO341RdP1tgngnfM1Gc6nYvOJAbga8hlpOFH39JP+459u96eZM3+/v553bq7371tvuHeTK2FSUdL/y/nvraTWR09/MnAHF392+8+7u6ObAVT3rpGm+fKzq5/n7+BKD+7u8UvRxiyY9tdT3faDkLkzBa+vN5D2lQ7PPnTwXk8/4H3dd5AONcmRIf/WT6EMx6+nhTocv/kIQwXd4v+Hd/gygOcmU6fAj8WdBHEYR8b/8hSbDzdj/+3Rc/MEa1dDFQ//vZ+nEeTv0kWPVUzRd2+/MnQ4nb+00/3W84xgNe+vYw9+/PV8NpWjK8h6fpXG8/fzKY3u5fHbpHgcaoVh85eD/vAxHs+/qRBVGu4+jOv5s//Rauwrs+ZsFClz9/0gOX94sm3S+pFQe5JB0e/XjVfTh0L30OunRYbqV1uUridWrapqOmWYt+lV65s2hq04GNvZ6U/9ft2dXH6zQPrI5C0XQf/vgdfRKCGu7RF/sFsgqWe/TmLLSbZYbZHv247eDQObDdi0dJEiwsn+rMG+1lHgvu1lYfE3cW+1C/8L+n52FW4+ja9l0f2O7Do+XdOHo89ZezcJa+41n1qGi7D4+mD348foiD1UM0n1n1h1ruxZusj3F0HQerILb7bg2t9+HVlyB47OC7gcRuH56sgjgrm273bmmY7WVeDlcpHbZfzq9guQ9v0mULu5m1tdiD+nlk9QaZmetGd9crA/PofvcSbP3TJ2lgSobg/cXw18nt+Ob8evLp8uL8H6OLf97a9KvEfg/JpXv+fXT+64fx5PRieHs7su9YwXxffp1ejIaXk9Ory7Pz8fnV5fDi4p/WncN99ODh6GL0cXQ5nlxenY1sekXs9uDJePSHfTfyRnvw4Wz0fvjpYjz5OPxjkkbwdjK+mlwPb26tOlXZS49eXk7GV9eT0+Hl2fnZcGx3yqjoo0cPx8NfdXBvT69uOhlC2kGPvp1+GN5Mxh9uRrcfruw+3JX20IN3N6NfR39cW03FvcnX+bi00b97ZLL8wLQNT8mArJfz8Eswf+pmNYH6dgy768DdZ2hg9OWj/3QXnCer4U5Jp36XdNi/54/RKrRN+wve5jrp38NlcO937mGuk/491HaXQbTu9lo1uunfS/tlkAse3nWAaGp6t/lG6/toaRcNFHwkHf2A6zGKF3pVrNsLMtdL/z5+DWdB1O047rro37vVgx9vixJ26yTt6UfcPb7rOgod3z12nfyAJ4A4+Nq5h7lO+vcwib4Ey64nnFwn/Xv4rZNybQUfjW769zItaZgZ6tRLo5sf4uXDp3jetYubPn7A3SOeroKkaw/zvfyAZ1Ul0rOaXTtpdNO/l/9aRcuL2eYTCOOnx47XCmB3/Xu9ZT2Tm6sLu4uoBct9LC+e/6aXo7OVaavLitRyD94ML8ajm7TXtPPRH6ej6xTvWHWrvIse/Lu+Gd2OLsfDDFpNhuPxzfkvnyyv5Vd10suC9/XN6HQ4Hp1Nbs//Z7Tvv4MUfbarPsb0w83w9vzyV/vuFSz34M2GF+srP82jm9+sghhsvge/Pow/XkxGt6fD69Hk4/Dapk9F068TXBA/jnc92LxH02CVbb+x+oqAPTue235BKIlgiY/3ffh4/2N99BePPTiZ9fLjvPz3OupjLDfd/MDRfLS7KFo2nI/WF0ab+Tl5jFbJdRxNg1UXKxbY/Ou8aQBftm981s8HorhVH4e1XiyD2H2lY5ZzYjdYtjd2GpEqHyUNs9IfjW1vFi7afrWjZTiyHbGB7YpFhYiVbuyO4pE/fUh/Z3d7t2H3lY5WzontSDHbJQKMSJVXklvO7A/R3uhrHZ+NB/tj7NYHZxuj0uMq0SKwPjI5o690ZLYe7A8bWH+A2AWpbGiCr0H8ZH1s8lZf6eDsXNhXzLM9OPsolZ7Di5ZTP0l/chGuLB/BLdp+pSNFHNmNl+1azIWIVdS0HM7n+kEw/dKh5SL22PwrHbuiL7tnCOu3KRC36pKUm87tHn01DL/SUct7sR0v+1dbPlQV1YNvgrneyfopDi0fvizYfqXDRRzZXWG2SzwWIlb6PBguHufh56fLYJUEsy425pV38UrHEPuzezW2vphREr+qW15XtXWKtl/pGBJHtoPHbRdVLESsdNU3Dh7Pouna9oeVqeFXOl55L3bLhtYXoYxYlRZMCb4n1t/SckZf6QhtPdiOjvWPEu9j9MyK7i92KxObZl/p6Ox92N2nrE91uTiVF0tJNiu8loul5My+0hHa+7AbIdvfAMvHqeo+tLlhWZ/A93Zf6RjlnNjdhKxfRvlIlRagXYZJVh7I+p2oYPqVjpXpx3a4lPXhIvGqZsLD5ezXILm0/H10ZPyVjhr1ZHeZWZ8LCzGreJ+67OKRz7T7Sscr58Ru9cn64nw+UmWjlATfk9twEc792PLHi4qmX+lYmX7sSZf1KZEErLxOYzD90kHNXNNuD/t7dYJGs2D7OVW7rx/A+CtNQOrJbsbogi+YMSsdudi/6+Jx17TbRw6Gq9/8eTjr4Hqill9p9hlu7FYp7D8PGtEqG631MlhN/cfgQ7KYj5ZJmISW6VZJB6907JA3+xuY9XVAGLyKyb+Doql5q6900HYu7OZ563tq9lH6sX7t/rT7ErDogiQY3T63j3xPHj4GiT/zE78jgpIz/3ozlfiyA0K2v72G4vZCPN39aZfO1j9NW97/c2U4OkSZ9SJxnNgnns/Ho/e6Vs3jkmmwXmvw0NAE36dB/Gh3na1xbPYiXlJoVl18EaVxbFadfDvl4OBMwtVtuLyfB/pr2ZbfQEzLr/Ruabixe5Gyfv2b0Sp/kfoW+4+X0Woah4+J/U/Xl3XwSscOebN/kbK+yA6DV41IbvVPuzg4t7f8SgfPcGNHia1feGa0ykbrwd9cn2P//ny5CmfbWntWXa7q5ZWOYqlL2xGV1nfOlEex/Ca4+UW6PTtaJ12cRC7v45WObIlDO/ZsfZ2qLIIV1+zpQzif/TKPpl86ulxRB690PJE3u4vU+r0Sxq78+rx+iP1VuLzv5sosWn+lY1hwZXc1Wh/AYtTKR+/3TopuUsOvdsz2XuzeLzqYPHOxqlhEPV8ug3hse8sOMfxKRyrvxe7V3vrjixGripE6ffDj02hteTIkhl/vSO282I2U9WvKiFXlib7b5GnexYG+nd1XOk45J3bv5dZX4fORqrie0qLbZ8FyZXtDVcH0Kx0r048d+bN+/JLEq2oGTLv9PQjvH+zPgYbp1ztiOT9286D1R0ESr8qZ0P708XrHR8vfHYrtZNqrejne7hezfT6lYPqVDo/px+5V2PpjBIlXxYR3E30bLmen0Xy9WHby6Ic6eKWjh7zZjWEX+xyKsXsx3u7+tCOSsou9DmUKnvugU/TN+h7ihsE43mjoOSLPBGaq2/3w2OxlvKzwTBZ+/CX9qsM4/eC63TAVTL/SWdD0Y7e8ZP0RkMSromrKhf/XUwfgmlp+peNluLF7NLR+uzKjVfHEkS5CdfRSbJp+peNl+rGbNLvYDpuPV3X5qGg5C5MwWvrzud1Rg+Zf6cgVfdmxkm4KShlhqxzAj34yfQhm9ksqI+uvefjyruz39XQyfEbUKkfvQ+DPAsun4ojh1zxmGy92R507Ga1tqEpXP/S/n60f5+E0/ZS2/dpRZT280qGD7uwmTOubsnD0Sp8q5/79+Wo4tf3tamr4lY5d3ovdI6X1ZXsjVtWbHt/PLa84Gma7GaXChpQ4uvPv5k+/havwzvLcgay/0twruLKbM6xz82LUSkbv0Y9XVr3cGuxmjNj+JENdS2zn3SKaredNvGPaJdOZXL7kT5xoa5vNP+lXX3adfl4vp+mTbqNui/aAkjZhZTViuY6N1o+zz7n/fCaY69hw6nH2OfefDaN5ffb+2ShW97c31CR81f5DxeHqUzw/XO/WTBdqa472ahr7j8G7de4TtLVGOmuX/m3dUc5afLp5/lIp72pn44CI5TxuHC3zP5tFzPzPhtdG05iRzja/OyBqxPNc5OT+HkrLa4TLJIg/+9OGodnWXetArXEvzCe9Balv17U/sFwp9/iZknCbsNjTbSvOzwn318lDFFuVvjPZk/jJNEys5vdb025fbqweojjpwo+t4b4cMR7aLfqR1P8m6UFuzHzL+bQx2Llw85i+DeVNTt0fJH0VreOpXe07k52L/xbFs8nU2P9iwwHDbA/JswhWib94XFnOoJzZLpyo+Zj4FK2T9V3wLljcBbNmT4mbphPdtPZDYvrjf2Ytr+f+UxA3fV40uy3aO+BZzAwGfnD8Z7QeF7XXTQlTvGGrA93mB6Qjf/ZbOAuiX57OZ9aFv6XmD3XD7KN068066NAnYr0fl3KB/NTiqb/JQH1q+xZw0Eh14hU1399Ypb+Yh6vm97haI5Wz3ts4deeRabwfhx7n/pNODfvu5E335Iy/XgVdeZO33Y87qyR67MibvOmenAmCL+MuPNna7ceN9IMmHY1J3nRP10scfA2j9aqrS4aY73lGG3YwRZvG+3FosW6xsvCsJxur/biwXn7sxImd3X7cCFdpdx08Su8N9zUZJ7+l+9U7GJK86X6cue/OmfvenVkFyW34VzfjsjHc26ikP7jzp19u2iyN1hkb0kFvI9StY8UOehux4Vc/nKeHH/ICmi/t1Rm70q56G8WLKHrsZPQ2hvubMB7Wnz+3WMOvNWfsbPc3mafPVxeRPwtm71O7YbTsZmaH/fQ6OwbxbdLl5Li335tbp+s4NT4OO7ofm/Z7c+tsHfudZWLOeL9XWSeLjabxfh0apU1O85/9su5WvoteJ4tuFh1N4707dL6cBd879WrbQz+u+bPZ6GuwTC7CVRIsO2Bgb0EP/biW7U/v2DvcSW9pef459ju6ce1M9+PMLFglcfRk35W94c4caUjnk+hdkq/114jPJ5H+9l3DbZwbpm6UGGxI6LcdFy1aYN3bkKCYhsaUuw2W/tvKKAhnIPhJjoWlZ9Q+Ve833nk9jdbx3F9uQNe+5bM+7lzbWKgQtJrG67tWgnItbQpaRvFCf2a2lSjS2qYw/bnFdkO3b2lT0KZFWjJt1VwUaW1T2OdwngRxS11mY5uy7vxVOH2vzTeXZTa2KWsWLfxw2VYXaW05v9KiA1FrbUUDNuXN/eV9W2VGW5uiHv3koa0oo61NUel23raijLY2RX3152G6XbfVjGo2tilr81nLVqqMtnZFXfpfw3u93nGd/1pPA2kFC5YFRslp7H/Tq9Ot5JntrT7i+IvHeZoqLe5GRluboj7F89skilvEKtfSpqC0zsx8Fi4/R80lGW07eMQ50ze51s84u+aW4/WLv2o3fRltLYv6EK2S4XJ27ScPrYSZ7TsQ1zrFco3tPq1+vwnmflq9oN0cUTRg/2G6rbJcW7vz/eh7EsRLv9VdMtfWrqh/LKNvy/TVoY2qfGOr740tXvnfOS/upX8r6YW99m9lvbAX/90AvqxX/62sl/fyv1X24l7/t8Je3gLAVtnLXALIpdqLWwTYanthywBbWS9sIWAr66UtBWx1vbTFgK2uF7kcsBf3QhcEcgJf2pLA7hHoJS0KbEW9qGWBraiXtzBAnoBe0NJALmYvbXEgJ+3FLQ8QbS9rgWD/VPvylgjMJ+4Xs0iwn/9f1jLBXldnCwX+fLqe+0lwGy7CuR+HydMvT+ln5vwpemLbbz54+2xLLDPb1PDsJJsv9QY6N351UEdog0h5h+av23W8Cvx4+vB7cFfVX/5Hh3RzO74ZDT8+39PudwcFs0YE2/tTqGaHnMn96CBPbkejf4yvrs9Pa7iU/227Tr8G6R6h8C+dWMPVabScBo+V0Sxt0U7At/RbajfBPPjqL6fBxtpvuo8qFdXNrEsZXp+3VJO1bJl46/v7YJVcBt+T36N4dhqlD+J6/1hlJla1aickib4Ey3TIo8dwWtl54ZctPX+ch8ltkN5LpkG1t/SXB02N4ZfwMZiFfo0JMvdTG+k2DuLF+zj49zpYTp/q5xpt1k7KIi36/9+fhrfDm6quzZ8d4LXOjrMwDqcP8yA5C1dJHN6tjcMTZZ5XNm0naRotvwaxLsV7+xhMQ3+ePkxUZl15k0oJ/3u0+dPf/+/N1yBO1wnf/P0NO+bHaZXoz2Ewn63e/P3PTNjRm2m0WGS1R2fRdK3/+L+bn2WTS/rj7Nd/O3lz9OfJkRocK3fwv/979Oe2sf4H/RdbG/u/0Q2dN0d/OkdKHPMT12joFBo6RkP25uhPdsQHx0qyI779g9j8wTDFCqaYYYq/OfpTIvG80JAbDcWboz/VEePHaXlv94izY8X4kbf9w2DzB8OmKNgUhk2ZBgSGUhZaSqOlSls6qKUqtFRGSzfvh8O2+h2++5NArrgFs65h1ksFwcB6hZae0XKQCfKO1Yl75Kjt6DruET859lwzUwYFYwMzxdKMczykwymmp0Py0zFi4x4xeSxOxJGzHdwjdpKKck480zLIXzOBHZ3BcLycYsY6Zso6PB8htrsQGEcXgFNMZMfMZEdgN5nYuSlRCjjFdHbMfHbSJGUKulnMaMdMaUcZibAd/iPmQjeLee6Yie6kCcpwKhSz2THT2fFKYrRLBY5ToZjtjpnuTpqwHKdCMbsdM73Tz5YhWXx3HXOOho4Vc5+Zuc/ShOUCyWLF9GZkfk4TlstUzWBwxNWRPDmWgkzMYGY285ylacpdKKGY1MxM6vTrG39yONqsmLfMzFuWZiIfwMbFvGVm3rI07QScxVkxSZmZpCxNOwFviqyYpMxMUublwy4YDHsxIZmZkCxNMcGP1Mmxq4j+YkIyMyF5mkUCpg0v5hw3c46nWSTkkfSOHabMxsWc42bO8TR5hDoS3jFtW8w0Th4C0twRLoo6B88BZqbxNHcEzDRezDRuZhpPc0cMYM/FTONmpvE0dyTMNF7MNG5mWvqN8j8lnHd4MdO4mWk8TRnJ4EgVE4ybCcbTlJEc+lxMMG4mmEhTRgrUWBQTTJgJJtKUkRI2LiaYMBNMpDkjFWxczDBhZpjQz5kww0QxwwR51ExzRnroihTgkdLMMJHmjIQZJooZJswME/oefHIknWPBSc/FDBNmhgn9aAnnMlHMMGFmmNA3XAYbFzNMmBkm9DMkzDBRzDBhZpjU91SYYbKYYdLMMKkfGWGGyWKGSTPD0i9G/6lghslihkkzw6R+KoQZJosZJs0Mk6Js8pTFBJPkpSVNGeUdSVFoC95azPySOr8GaB6RxfySZn5JtzQ5ZTG/pJlfMs0Y9wSGq5hf0swvmWaMCzNbFvNLmvml0oxx4dypivmlzPxKvwP3p8th42J+KTO/VJoxLsxsVcwvZeaXSjPGhZmtivmlzPxSacq4MLNVMcGUmWAqzRnXRdOfKmaYIi/Gac64HuwZvBqbGabSnHHh3KmKGabMDFNpzngww1Qxw5SZYem3u/708At9McOUmWFumjMeQwFzixnmmhnmOqW3dreYYa6ZYW6aMx58dnSLGeaaGeby/OOrJ9Djq1tMNddMNTdNHg+uPLjFVHPNVHPT5PHgC6tbTDXXTDU3TR4Pvq+4xVRzyTKMWzYDu2Cpxcw0V2cafAJ1i5nmmpnm6kyD7zpuMdNcM9O8NHcG8AnUK2aaZ2aal+bOAOa4V8w0z8w0L82dAYONi5nmmZnmpSkz4LBxMcE8M8G8NGUG8BXHKyaYZyaYl6bMAK+LFRPMMxPMS1NmALPTKyaYZyaYl+bMAGanV8wwj6zmpTkzgBnmgfU8M8O8QVlqe8UE88wEG+gEg9k5KCbYwEywgV5gPoHpOShm2MDMsAHTrWF+DoopNjBTbMB1a5igg2KODcwcGwjdGmbooJhkAzPJBtk6MkzRQTHLBmaWDVR+GnZOJJqHB8V8G5j5NnC1CJitg2LCDcyEG3hlOTMo5tuALCAPdM/wUXgAFozpirFeMj6BjwzZP5rtc3+3MZCl3SBdljsRkhgAa8MnZHH4RGeec4Luwdk/UgNkgfhEJ5+D2coJWBA+ISvCJ6L00Tr7N9qerPue6Ax0YPZn/0gNkLXfkwxowAsg+0dqgCz2nrilTyLZv9H2ZL33xKsaRLCqe0KWdU8qsjD7R2qA5KFTlYcIXhToRVUeQkZB8tCpykPEKSiocKryEIEJSiacijxE+IHyByfLQzgTOghBUAbhZHkIb9gOYg4UOmiO4DiYgSDuQMGDxgWOA2/cDsILlC9oZOCUMDCEGAhjcDQZ2N8QnAG6ITgAKTiEKTgaEzgM3pAdgBUcwhUcTQicMnCGyBnJSE0JHIYnJkAVHIIVnIwr7ILBOA4GyE3CGByNDRyGcxNgBodwBkejA4fh3ASowSGswdH4IOcL5DQO4A4OAQ+ORggOw0kKkINDmIOjMYJTQucAdnAId3A0SnAYfFJ0AHpwCHtwNE5wOM5NgB8cwh8czRScEpIHGIRDIISjuYLDcW4CDuEQEOFotuBwfNMELMIhMMLRfMHB1M8BPMIhQMLRjMHhOCUBk3AIlHA0Z3A4ni4Bl3AImHA0a3AwNXQAm3AInHA0b3AwOXQAn3AIoHA0c3AwPXQAo3AIpHA0d3AwQXQAp3AIqHA0e3AEzkTAKhwCKxzNHxyBMxHwCocAC0czCEfgTATMwiHQwtEcwsEg0QHcwiHgwhHmW4yAbzEOgBgOoRiOBhOOwCkJQIZDSIaj4YQjcEoCmOEQmuFoQOFgxOgAoOEQouFoSOEInJIAajiEajgaVOyjKU9gNAHhcAjicDS1cCR+JASUwyGYw9HkwpE4NwHpcAjqcKR5B5f4Dg64h0PAh6NhhpPCSPCSAeCHQ+iHI80klThJAQlxCApxNN1wZMlWG5CkBIc40jOluFgKyFbCRhyNOxyJ31sAHnEIH3GU+bwp8fMmYCUOgSWOKt9Q4ABc4hBe4qjSPQUOACYOISaOhiAY7juAmTgEmjiagzgK3wgAN3EIOHE0C8Fr+Q5AJw5hJ47GIZjUO4CeOASfOJqIYFjvAIDiEILiaCiCeb0DGIpDIIqjuQhG9g7AKA7hKI5GI5jaO4CkOASlOBlLgeDeATDFITTF0YAEs3sH8BSHABVHo5GS12dAUhyCUhw3S0AHOwASkOAURxMSTPEdAFQcQlQcDUkwyHcAU3EIVHE0KMEs3wFcxSFgxdGsBON8B6AVh7AVR+MSvAXCAXTFIXjF0cQE7whwAGBxCGFxNDRxFL5ZAsjiEMriaHDilIwAAC0OIS2OhieOwg9yALY4hLY4GqDgvVkO4C0OAS6OZih4X4QDkItDmIujMYqj8CsNwC4O4S6OV0r2HABeHEJeHA1T4PYKB6AXh7AXR/MUvMPCAfjFIfzF0UilZAoBBMYhCMbRUAXvs3AAg3EIhHE0VsFbLRxAYRyCYRwNVvBuCwdwGIeAGEejFbzhwgEkxiEoxtFwBe+5cACLcQiMcTRVwdsuHABhHEJhHM1V8M4LB2AYh3AYR7MVvPnCASjGISzG0XQF779wAIxxCI1hGq7gLRgMwBhGYAw7Kd/OwACLYYTFMI1W8C4OBlAMIyiGZShGwQdzBlAMIyiGabSCN3MwgGIYQTEsQzF4AmQAxTCCYliGYhTeSg1QDCMohmm04ii8nRqwGEZYDMtYjIu3VAMWwwiLYRmLceGCCAMshhEWwzIW48L7KAMshhEWwzRawTiKARTDCIphGYpx4YIKAyiGERTDMhTjlmzoB3lIUAxzRDlNYoDFMMJiWMZiXHgjZYDFMMJiWMZiXHwpARbDCIthGYtx8YkCwGIYYTEsYzEuvhQAi2GExbCMxbj4UgAshtHzHiw7z4QvBXSqgx7rYBVQkKGTHYWjHToT8dY0Bg91kEzMEEzJjIYOdtCTHRqkOB6+FtDhDnq6IyMvHr4W0AEPesIjIy94kxlDhzzoKQ/NTxy80Yyhgx70pEcGXPBmM4bOeNBDHhlwwZvGGDrnQYALy4AL3jjGAHBhBLiwDLjgzWMMABdGgAvLgAveQMYAcGEEuLAMuOBNZAwAF0aAC8uAC95IxgBwYQS4sAy44M1kDAAXRoALy4AL3lDGAHBhBLiwDLjgTWUMABdGgAvLgAveWMYAcGEEuLAMuODNZQwAF0aAC8uAC94kxgBwYQS4MM1PGN4nxgBwYQS4MM1PGN4qxgBwYQS4MM1PGN4txgBwYQS4MM1PGN4wxgBwYQS4MM1PGN4zxgBwYQS4MI1N2AnORMBZGOEsTGMThjeMMcBZGOEsTGMTdoIzEXAWRjgL09iEnZQcGgSZSDgLyzhLyc0VcBZGOAuTWSaWnDwEmUjwCpPZwWKcygCvMIJXmKYlDB8lZwCvMIJXmIYkDG/9YoCqMEJVmIYkzIFLTgxQFUaoCtNshDnwnZsBmMIITGGajTC86YcBmMIITGEaiTC86YcBhsIIQ2EaiTC86YcBhsIIQ2GahDC86YcBdMIIOmEahTAHZyJgJ4ywE6ZhCMN7fRigJ4zQE6ZpCMN7fRjAJ4zgE6ZpCMN7fRjAJ4zgE1Zx8IQBfMIIPmEahzCGJ2XATxjhJ0zzEIa3CDEAUBgBKEwDEYa3CDFAUBghKEwTEYaP8DOAUBhBKEwjEYZ3BjHAUBhhKEwzEYZ3BjEAURiBKMzNEhFnMqAojFAUpqkIwzuDGMAojGAUpqkIwzuDGMAojGAUprEIwzuDGOAojHAUprkIwzuDGAApjIAUpsEIK6kHAEgKIySFaTLC8M4gBlAKIyiFaTTC8M4gBlgKIyyFaTbCSuoJAJjCCExhnrEJgnEPn68HKUmoCtOQhJUUGABUhRGqwjQkYSVFBgBVYYSqME1JGN4ixABWYQSrMI1JGN4ixABXYYSrMM/Y+8AE3IbBAGBhBLAwTUwY3ivEAGJhBLEwzUyYwLkJIAsjkIWVn3BhgLEwwliYZiYM7zBiALIwAlmYhiYM7zBigLIwQlmYpiYM7zBiALMwglmYxiaYdDOAWRjBLGyQ5SO+IgBnYYSzMM1NmMQL9QC0MAJamAYnDBdEYIC0MEJamCYnDG9MYgC1MIJamEYnTOJJGrAWRlgL0+yESXwhANjCCGzhGp4wiethAdrCCW3hmp4wvA2JA9zCCW7hGp8wCTOZA97CCW/hGp8wictxAN7CCW/hmp8wCTORA+DCCXDhmp/sJzYF98pxQF44IS9cgxRcDIYD8MIJeOGaozCFa3wA8MIJeOGaozC8f4MD8MIJeOGaozC8fYAD8MIJeOGaozC8g4MD8MIJeOEapDC8hYMD8sIJeeFZqS68B4MD8sIJeeEapDAM4DggL5yQF65BClOQoXJAXjghL3xThgtXmQHkhRPywjVIYZjic0BeOCEvPKu9hQEcB+SFE/LCNUhhGMBxQF44IS9cgxSGARoH5IUT8sLNUzDMhcfTOUAwnCAYzpyKqwogGE4QDGes4qoCCIYTBMMZr7iqAILhBMFwJiquKoBgOEEwnMmKqwogGE4QDNdEpeyqAgiGEwTDmVtxVQEEwwmC4cyruKoAguEEwXA2qLiqAILhtNYWJykJtw9zVHeLFt7SaIVhtMpR7S1afEujFYbRKkcFuAoVuHRKYrTKYREukpIarTCMVjkqxEUrcWm0wjBa5agYF63GpdEKw2SUo4JctCIXzyoU4kkOFeWiVbk0WmGYjHJUmItW5tJohWEyylFxLsJiuEYrDJNRDlgMJyyGZywGk1EOWAwnLIZnLAaTUQ5YDCcshmcsBpNRDlgMJyyGZyzG225bP2ID/AgIsAwnWIZnWGaAnwEBluEEy/AMywzYXgx80eaA0HBCaHhGaAb4tgEIDSeEhmeEBtNKDggNJ4SGZ4QG00oOCA0nhIZr4JKW6lTHciCP2MDdVU8deKiuKAfYhhNswzNsMygp4weSlmAbrikMxwSSA2zDCbbhmsLwE+eIi2PpsSN+wvZ/hHVhOYA5nMAcnp2VOcEjDmAOJzCHazZTpktiXajuIcnq7ODMCX58AIiHE8TDNbEp0wULzHIAfjgBPzw7RYPP7HMAfjgBP1xzHH6ymzu4g+cOwIA4YUA8O0eDT99zwIA4YUBcIx3u4AdVwIA4YUBcIx2OUR4HDIgTBsQ10uH4/D4HDIgTBsQ10uEOflAFDIgTBsQ10+EY5XEAgTiBQFwzHY5RHgcQiBMIxDXT4Y63q3fuaL4sRFp0/ASmKkBDnKAhrkkPx3iNAzTECRrimvRwtruzcHwWngNKxAkl4hr6cIbnGUCJOKFEXEMfjkEXB5SIE0rENfThGHRxQIk4oUQ8q16GQRcHlIgTSsQ19OEYdHFAiTihRNzNUnVw5AyO00cGnitOnd7ytn90UEVoDjASJxiJayrEMYfiACNxgpG4pkKc70r2cy72f8S3AwCXOIFLXLMizvHtAMAlTuAS16yIYzbEAVziBC5xzYo4PjXOAVziBC5xr2JfJgdMiROmxDUi4nywi6c42f/R2TzwELMgrQlp4hocccx5OCBNnJAmrsFRqkCoYyXUEcekhwPoxAl04pohcYGnCQCdOIFO3IROXMiNKmIJZDKBTtxzTUuwdgYH9IkT+sQ1TOICbjPggD5xQp+4xklcQPjCAX/ihD9xjZM4hi8c8CdO+BMfZGQUP74C/sQJf+KDrGA8vhkB/sQJf+KDrHYkTlMAoDgBUHyQnQqHO/Q5AFCcACg+MJb9ucTrg4BEcUKi+KYAm8RSQG4SEsUHWW4qbACkJCFRfJAdBscpCUgUJySKa7CUCwZE5RwgKU6QlDjJ1rgGsPg1QFKCICmhCRNPD1EjA6DqN0FSQhMmjg/BCoCkBEFSQhMmruCGdwGQlCBISmjCxBXMTQGQlCBISmRISsFCBQKQKEFIlNBkiSuYkgKgKEFQlNBkiSuYkgKgKEFQlNBkiSuYkgKgKEFQlNBkiStcRR2gKEFQlHBOatw7BGBSgjAp4RgbSbiCBQ4EgFOCwCmhWRPHJ6MEgFOCwCnhZN/YgBOvAHBKEDglHKOaBnfhRycEoFSCUCqhoRPHhEYASiUIpRKOeXPHhEYAXCUIrhKaPnEXpzvAVYLgKuF4phT4dCAAtxKEW4ns8zB4YV0AbiUItxIZt8IL6wLgKkFwlci+BIMX1gXAVYLgKpF9DQYvrAuAqwTBVSI7MYSfjQXAVYLgKpHhKrwOIQCuEgRXiQxX4S3FAuAqQXCVYGZueg5MCMCtBOFWIivaho9PCcCtBOFWgpWWVhWAWglCrYSGUBwzBgGolSDUSmTUCjMGAWCVILBKZAeHMPoTAFYJAqsEzxISLhYIAKsEgVVCsyeOIYUAsEoQWCV49nUifFUDWCUIrBKaPXEMKQSAVYLAKqHZE8fHtwSAVYLAKqHZE8fHtwSAVYLAKqHZE8fHtwSAVYLAKqHZE8fHtwSAVYJ+SkazJ46Pbwn0NRn6ORnNnjg+viXQF2XoJ2U0e+IYiAj0VRn6WRnNnjgGIgJ9WabwaRmdifj4loBflyGZKLJvZeFMRF+YoZ+YySq14eNbAn1lhn5mRlMmgeGJQF+aoZ+a0ZRJ4ONbAn1thn5uRlMmgY9vCfTFGYKlhAZKAh/fEoBACUKghAZKAh/fEoBACUKghAZKAh/fEoBACUKghEZHAh/fEoA1CcKaRPYNGnx8SwDWJAhrEhoSCXx8SwCqJAhVEhoSCXz6SgCqJAhVEhoHCXz6SgB+JAg/EhoHCXz6SgB+JAg/EpoBCXz6SgBoJAg0EpoBCVx4WwBoJAg0ElnNNYxsBIBGgkAjkRVdw6evBIBGgkAjkZVdw8hGAGgkCDQSmgEJjGwEgEaCQCOhGZDAp68EgEaCQCOhjMdFgUsuC0CPBKFHQmMfwfDyB+BEgnAiobGPYHj5A3AiQTiR0KxHMPzACuCQIHBIaNYjGF7+AHBIEDgkNOsRDC9/ADgkCBwSmvUIht8HARwSBA4JzXoEw8sfAA4JAoeEZj2C4eUPAIcEgUNCoxzB8PIHYD+CsB/hminJBnD5A0AgQSCQyD51w3FKAtwjCO4RbkVtfgFwjyC4R2h6I3jJp+lAShLcIzS9Ebzk83QgJQnuEZreCI7fSAHuEQT3CM1pBMdvpADsCAJ2hOY0guOPIQKwIwjYEVlhNgzdBKA5gtAcoeGM4Pg9DtAcQWiO0ExGcLjbQgCIIwjEEVlpNo4/jgjYjSDsRmgUIwTcwikAuxGE3Yjs5BCsUCoAuhEE3QhNYvDLPAA3goAboTmMwMfABAA3goAbMaioDygAuBEE3AjNYQTmiwKAG0HAjdAcRuBS0wKAG0HAjdD4ReDjYwLwGkF4jdD4RQh8JQFeIwivERq/CIGvJMBrBOE1IvtaDi6SKACvEYTXCE1dhMBXEsA0gmAaqamLwLVuJcA0kmAaeZKV6sUfZASYRhJMIzV1EbiwtASYRhJMIzV1ERLO6RJgGkkwjdTUReByuRJgGkkwjdTUReB6uRJgGkkwjcwODOGCuRJgGkkwjdTUReCKuRJgGkkwjcxKteHVSQkwjSSYRp5kEyL+jinANJJgGqlhi8DlpyWgM5LQGelkmYhTGUAZSaCMzGq14bLgEkAZSaCM1IxFKHwtACgjCZSRGq0IXHdWAhYjCYuRGq0IfERFAhYjCYuRmqgIfF+QAMFIgmCkk1VNxdcCQDCSIBjpZMvcJZ/iBZlIyIt0skO9+FoA5EUS8iJZdm/GqQzIiyTkRWqQIvARFQnIiyTkRbKsfjlOZUBeJCEvUoMUUfKZXEBeJCEvkmXVe3EmAvIiCXmRGqQIF2ciIC+SkBep+YlwcSYC4CIJcJGanwhcwlUC4CIJcJEZcME1XCVALpIgF6kJisBFXCVALpIgF6kJinBLPg4NMpEgF6kJisBlXCVALpIgF6kJisB1XCVALpIgF8krGKAEyEUS5CI1QRGYQkqAXCRBLpJXnDCXALlIglykJigCnw+SALlIglykJigCnw+SALlIglykJijCw9cCQC6SIBepCYrw8LUAkIskyEVqgiI8fC0A5CIJcpGaoAgPXwsAuUiCXKQmKMLD1wJALpIgF6kJivDwtQCQiyTIRYosE/G1AJCLJMhFaoIiBjgTAXKRBLlITVAEPlUkAXKRBLnIDLkM8KwMkIskyEVmyGWAMxEgF0mQi8yQCz6LJAFykQS5yAy54FUoCZCLJMhFmt/EEQN4+lIC9iIJe5EZeym5qgB7kYS9yIy9lFxVgL1Iwl5kxl5KrirAXiRhLzJjLyVXFWAvkrAXmbGXkqsKsBdJ2IvM2EvJVQXYiyTsRWbspeSqAuxFEvYiM/ZSclUB9iIJe5EZeym5qgB7kYS9yIy9lFxVgL1Iwl5kxl5KrirAXiRhLzI7sLO/KODGJwkgjCQQRmYQpuQlCEAYSSCMzCBMyUsQgDCSQBipVMVLEGAvkrAXmbGXkpcgwF4kYS8yYy8lL0GAvUjCXmTGXkpeggB7kYS9yIy9lLwEAfYiCXuRGXspeQkC7EUS9iIz9lLyEgTYiyTsRWbspeQlCLAXSdiLzNhLyUsQYC+SsBeZsZeSlyDAXiRhL9JVFS9BALlIglxkhlxKXoIAcpEEuUjXq3gJAshFEuQiM+RS8hIEkIskyEVmyKXkJQggF0mQi8yQS8lLEEAukiAXmSGXkpcggFwkQS4yQy4lL0EAuUiCXGSGXEqe3wFykQS5SE/WgHgSsBdJ2IvcsBf8+ATYiyTsRZoHaMQAfnBOAggjCYSRmqmUrbcBCCMJhJHewJQCTytIgGMkwTEywzEl66cAyEgCZKTmK2XrpwDISAJk5IBVrJ8CICMJkJEZkClZPwVARhIgIzMgU7J+CoCMJEBGmidpxABufpCAzEhCZmRGZiBdkwDMSAJm5AbM4EkLgBlJwIzcgJmSfACpScCM3ICZkuEEGUnAjNqAGTicCoAZRcCMysAMJjsKgBlFwIzagBl4+1QAzCgCZtQGzMDbpwJgRhEwozZgBt4+FQAzioAZtQEzcN5VAMwoAmbUBszA26cCYEYRMKM2YAZmogJgRhEwo06MEwnyBJYVUIDQKEJo1EnF5gkFCI0ihEY5FZsnFCA0ihAa5VRsnlCA0ChCaJRTsXlCAUKjCKFRTsXmCQUIjSKERjkVmycUIDSKEBrlVGyeUIDQKEJolFOxeUIBQqMIoVFOxeYJBQiNIoRGORWbJxQgNIoQGqWBi0orXx2nZzNyR9/liXPEnGOHpYsy7IipY0bmfwUIjiIER2kgI/G2XAUIjiIER2VnZ57RdSRPxBE/OXZOPNIDSGWCeJQmNhLv21UA8SiCeJQmNi5vF0SAgBRBQEoTHYk3BiuAgBRBQCr7XI9yjph3LDYFMBpIBNcCYURKIx+Jtx4rwIgUYURKIx/lpbNrugm7oUJwrRCGpDQSknhvswIMSRGGpLJicyepQunKTKE6Ts+wpAod93gg0vNy+mJyHedIOiebP5K+wGVDcJPS9EjiXcwK4CZFcJPS9EjiXcwK4CZFcJPS9EjiA18K4CZFcJPS9EjiA18K4CZFcJPS9EjiwjMK4CZFcJPi22oezD2W3DWHSWzHUToKDhPgUYrwKKXxksTbnBXgUYrwKJUdAcISHW8vcYAlgrQnwEpp/iTxRyQUAFaKACuVnRF6ViJzsESQ7IRoKQ2oJP7KhAJESxGipUTFPSKt15KVbZFMbKZo0gO4GgjyUppgSVwcRwHkpQjyUtkpIzxlMHXExHF6HE8ydzd7MA8GFOAxRfCY0rRLMvxcAfCYInhMadrlpPPXyfFJWgcnHX5xLPSV4xw58lim69KpcOf45EQeSX6S/uDEo7EFFxFBaUqTMYm/7aAASlMEpSlNxiSuqaMASlMEpSlNxkpSPE0afuw4KjdOpAdwERHWpjQ6c0pewABrU4S1qazq3r5ulU5xeaxc90hyWJ1OAQKnCIFTmqNJ/FEKBcCbIuBNaY4m8UcpFABvioA3JSt2JSgA3hQBb0pzNFnyHgDAmyLgTWmOJkveAwB4UwS8KZklMH4PAOBNEfCmZJbA+HoF4E0R8KY0R5Ml7wEAvCkC3pTmaBIXSlcAvCkC3pTmaGkNM2QAgDdFwJvSHE0K/LwBwJsi4E1pjiZxZSMFwJsi4E1pfCbxUpUCvE0R3qY0PitLZcDbFOFtSuMzide6FOBtivA2pfGZxGtdCvA2RXib0vhMlqx1Ad6mCG9TKstEnMqAtynC25TGZ7JkrQvwNkV4m9L4TEoHLVkqwNsU4W1K4zNZstYFeJsivE1pfCZL1roAb1OEtymNz2TJWhfgbYrwNqXxmSxZ6wK8TRHepjQ+k3gVXgHepghvUxqfSbyIrgBvU4S3KY3PJF5EV4C3KcLblMZnEi+iK8DbFOFtSuMzifG5ArxNEd6mND6TGJ8rwNsU4W1K4zOJ8bkCvE0R3qY0PpMYnyvA2xThbUrjM4nxuQK8TRHepjQ+kxifK8DbFOFtSlMzifG5AphNEcymNDWTGJ8rgNkUwWxKwzKJ8bkCdE0RuqY0LJMYnytA1xSha0ozMonxuQJQTRGopjQjkxifKwDVFIFqSjMyifG5AlBNEaimslNOJfdGANUUgWoq+zwS5u8KQDVFoJrSjExi/q4AVFMEqimNxiTm7wqwNEVYmtJsTGL+rgBMUwSmKc3GJObvCsA0RWCa0mxMYv6uAExTBKYpzcZKhxFkIoFp7kmWifBacAFMcwlMc08qqny6AKa5BKa5mo1JD15MLoBpLoFp7knFG4sLYJpLYJqr2Zj04NXoApjmEpjmajZWqqCYiS6Baa5mY2mlbqigmIkugWmuZmOlCoqZ6BKY5mokJvE+DBcwNJcwNPekIhNdwNBcwtBcjcQk3jLqAobmEobmOlWZCBiaSxia62SZCCcUFzA0lzA016nKRMDQXMLQXCfLRDgjuYChuYShuU5VJgKG5hKG5jpZJsIpzQUMzSUMzXWqMhEwNJcwNNfJMhHOiS5gaC5haK5TlYmAkbmEkbkZI8P7bl3AyFzCyFxWlYkAgbkEgbkZAsMbd12AwFyCwNyq+nIuQFwuQVxuhrjwzl8XIC6XIC6XVWUiIFguIVhuRrDw1mEXECyXECyXVWUiIFQuIVRuRqjw3mMXECqXECqXVWUiwE4uwU5uhp3w5mUXYCeXYCeXV2UiwE4uwU5uhp0GeE4E2Mkl2MmtOuXkAuzkEuzkZthpgOdEgJ1cgp1cXpWJgCq5hCq5GVUa4DkRUCWXUCWXV2UigEYugUZuBo0GeE4E0Mgl0MjlVZkImJBLmJCbMSH8PRgXMCGXMCFXVGUiQD4uQT6uJjjqBM+JAPm4BPm4msqoEzylAYzjEozjior1RBdgHJdgHFeTFnWCpzSAZlyCZlxNWtQJnpEAmnEJmnFFVSYCNOMSNONqkKLw53NcQF5cQl5cUZWJgLy4hLy4GpmoEzwjAcbiEsbiyqpMBIzFJYzFlRXvzi5gLC5hLK7MMhFPaYCxuISxuLIqEwFjcQljcWXVnAgYi0sYi6uRifKOpKBVWlxAWFxCWNyMsOBFYRcQFpcQFldmeYjnZEBYXEJYXA1M0trOSABIQwJYXJWlIZ6SAWBxCWBxVVUaAsDiEsDiqmxCxFMyACwuASyuqro1A8DiEsDial6iHDwlA8DiEsDiqqo0BIDFJYDF1bxE4Q9CuQCwuASwuKpqQgSAxSWAxdW8ROEvSrkAsLgEsLiqakIEgMUlgMXVvEThnUEuACwuASyuW5WJALC4BLC4mpcovLXIBYDFJYDFdasyEQAWlwAW180yEd8UAGBxCWBx3apMBIDFJYDFdbNMxHM6ACwuASyuW5WJALC4BLC4bpaJeEoEgMUlgMV1qzIRABaXABbXyzIRz4kAsLgEsLhVnwxyAWBxCWBxvSwT8ZwIAItLAIvrVWUiACwuASyu5iWK4TkRABaXABbXq8pEAFhcAlhczUsUw3MiACwuASyuV5WJALC4BLC4mpcohudEAFhcAlhcryoTAWBxCWBxNS9JN5khBQCwuASwuIOqTASAxSWAxa0CLC4ALC4BLK7mJQp/QM4FgMUlgMUdZJmI50QAWFwCWFzNSxTDUxoALC4BLK7mJaUxAJlIAIureYlieEoDgMUlgMUdVNTVdAFgcQlgcTUvUQxPaQCwuASweJqXlCjwAGDxCGDxNC9RePOgBwCLRwCLd1KRiR4ALB4BLJ7mJYrDKc0DgMUjgMU7qXhd8QBg8Qhg8TQvUfiAjgcAi0cAi3dSkYkeACweASye5iUKn/DxAGDxCGDxTioy0QOAxSOAxdO8ROEjQh4ALB4BLJ5TlYkAsHgEsHialyh8xsgDgMUjgMXTvEThM0YeACweASxeFWDxAGDxCGDxNC9ReHOiBwCLRwCLtykjB6qTegCveASveJqWKPxVRg/gFY/gFc/J8hCemvAAXvEIXvE0LVEcVoT3AF7xCF7xsiNKAm5g9wBe8Qhe8TQtUbhCqwfwikfwiqdpicIFVj2AVzyCVzxNSxQusOoBvOIRvOJpWqJwgVUP4BWP4BVP0xIl4DZdD+AVj+AVT9OS9OOT0ADIRIJXPE1LlMCZCPCKR/CKlx0QEjgTAV7xCF7xNC1R+BuNHsArHsErnqYlCn+j0QN4xSN4xdO0ROFvNHoAr3gEr3ialij8jUYP4BWP4BVP0xIlcSYCvOIRvOJV4RUP4BWP4BWPV2zX9gBe8Qhe8XjFdm0P4BWP4BWPV2zX9gBe8Qhe8XjFdm0P4BWP4BWPV2zX9gBe8Qhe8XjFdm0P4BWP4BVPVGzX9gBe8Qhe8UTFdm0P4BWP4BVPVGzX9gBe8Qhe8UTFdm0P4BWP4BWvCq94AK94BK94omK7tgfwikfwiicqtmt7AK94BK94omK7tgfwikfwiicqtmt7AK94BK94omK7tgfwikfwiicrtmt7AK94BK94smK7tgfwikfwiicrtmt7AK94BK94smK7tgfwikfwiicrtmt7AK94BK94smK7tgfwikfwiicrtmt7ALB4BLB4smK7tgcAi0cAiycrtmt7ALB4BLB4smK7tgcIi0cIi6cqtmt7gLB4hLB4qmK7tgcIi0cIi6cqtmt7gLB4hLB4qmK7tgcIi0cIi6cqtmt7gLB4hLB4qmK7tgcIi0cIi6cqtmt7gLB4hLB4qmK7tgcIi0cIi6cqtmt7gLB4hLB4qmK7tgcIi0cIi+dWbNf2AGHxCGHx3Irt2h4gLB4hLJ5btYYDCItHCIvnVmzX9gBh8Qhh8dyK7doeICweISyeW7Fd2wOExSOExXMrtmt7gLB4hLB4bsV2bQ8QFo8QFs+t2K7tAcLiEcLiVREWDxAWjxAWz6vYru0BwuIRwuJVERYPEBaPEBbPq9iu7QHC4hHC4lURFg8QFo8QFs+r2K7tAcLiEcLiVREWDxAWjxAWz6vYru0BwuIRwuJVERYPEBaPEBbPq9iu7QHC4hHC4lURFg8QFo8QFm9QsV3bA4TFI4TFqyIsHiAsHiEs3qBiu7YHCItHCIs3qMpEQFg8Qli8QcV2bQ8QFo8QFm9QlYmAsHiEsHiDiu3a/39z37bsKpJr+y/1vGKXk5tR/8H5ho4OB9PO6UkvDG7A81I7+t9PZIKwJARb7n0ezlPNwl7DQCozlRpDUqkwLKVgWErYs0SFYSkFw1LCjly7VBiWUjAs5V4KS6kwLKVgWOCwI9cGhWEBwbDAXgoLKAwLCIYFDjtybVAYFhAMC+ylsIDCsIBgWOCwI9cGhWEBwbDAXgoLKAwLCIYFDjtybVAYFhAMC+ylsIDCsIBgWOCwI9cGhWEBwbDAXgoLKAwLCIYF3I5cGxSGBQTDAnspLKAwLCAYFnA7cm1QGBYQDAvsMSygMCwgGBZwO3JtUBgWEAwL7KWwgMKxgOBYwO3ItUHhWEBwLLCXwgIKxwKCYwG3I9cGhWMBwbHAXgoLKBwLCI4Fkh25NigcCwiOBfZSWEDhWEBwLJDsyLVB4VhAcCyQ7Mi1QeFYQHAskOzEE0HhWEBwLJDsyLVB4VhAcCyQ7Mi1QeFYQHAssJfCAgrHAoJjgWRHrg0KxwKCY4G9FBZQOBYQHAukO3JtUDgWEBwL7KWwgMKxgOBYIN05O4PCsYDgWCDdkWuDwrGA4Fgg3bNEhWMBwbHAXgoLKBwLCI4F0k25NigMCwiGBdIduTYoDAsIhgXSHbk2KAwLCIYF0m25NigECwiCBbIduTYoBAsIggX28ldAIVhAECyQ7ci1QSFYQBAskO1tzQrBAoJggWxHrg0KwQKCYIFszwwVggUEwQLZjlwbFIIFBMECe/kroBAsIAgWyHbk2qAQLCAIFtjLXwGFYAFBsEC+I9cGhWABQbDAXv4KKAQLCIIF8h25NigECwiCBfZqhIFCsIAgWCDfkWuDQrCAIFhgL38FFIIFBMEC+Y5cGxSCBQTBAvmeJSoECwiCBfIduTYoBAsIggXyPUtUCBYQBAsUO3JtUAgWEAQL7KWwgEKwgCBYoNiRa4NCsIAgWGAvhQUUggUEwQLFjlwbFIIFBMECeyksoBAsIAgWKHbk2qAQLCAIFthLYQGFYAFBsECxI9cGhWABQbDAXgoLKAQLCIIFjjtybVAIFhAEC+ylsIBCsIAgWGCPYAGFYAFBsMBxR64NCsECgmCB445cGxSCBQTBAscduTYoBAsIggWOOyJZUAgWEAQLHHfk2qAQLCAIFjjuiGRBIVhAECxw3JFrg0KwgCBYoNwRyYJCsIAgWKDckWuDQrCAIFig3LNEhWABQbBAuSPXBoVgAUGwQLl3XFEIFhAEC5Q7cm1QCBYQBAuUe5aoECwgCBYod+TaoBAsIAgWKPcsUSFYQBAsUO7ItUEhWEAQLAB7lqgQLCAIFoAduTYoBAsIggVgR64NCsECgmCBPYIFFIIFBMECsCPXBoVgAUGwAOSbZXqLPNPK9IJCu4CgXWBKbNHVNaDQLiBoFwBZZ/xZ1rjI819J8l9JvEW1FDoovAwIXgYizVLoCiJQeBkQvAxMmS+5qu8FhZcBwcu4w2E6c0+FqFPaQiA+49QposhhLgjOfmH+1/wn6EX8jWjkuspo/nSF4SRGYhqMQq2oPv/z1Y8k8kem/ipaF6z5wxVEKiHibChUtfH86QojkxhTTPNX7v4rS1cQa9OnFxGimIuRK7GY+dMVRiExjlOfEx1ibd70IkLEILt+jp4/XWGUEiMqg/ST8PzpCkNa+UT66GfZ+VOJ4aQVRxrnmOqvQ+F96EWESLYifPNnKwRpoRP1E/R2mokq3A+9iBiTiap69vnTFYY00cjnFIWaXDF/usKQNhopnY0Fp8jn1jS/iqLQ1x6FJaIX8UeiERdqCsX86QpDWvGUjlOoq+z86QpDWvGUkVOoiRTzpysMacVTUs5RzaWYP5UYibTiKS/nqKZTzJ+uMKQZT7TRcWONU3gjehExogN83DBChTqiFxEjGvJxwwgV9oheRIxoyEc1yWf+dIUhDXmikI5qns/86QpD2umUqXPcsFOFRqIXESPa6XHDThUmiV5EjGinxw07VcgkenHGmOikcsNOFT6JXkSMaKflhp0qlBK9iBjTcrthpwqrRC8iRrTTcsNOFWKJXkSMaKflhp0q3BK9iBjRTssNO1XoJXoRMSaCacNOFY6JXkSMqeXUhp0qNBO9iBjRTssNO1WYJnoRMaKdlht2qrBN9OKMMfFNsGGnCuFELyJGtFPYsFOFc6IXESPaKWzYqUI70YuIEe0UNuxUYZ7oRcSIdgobdqqQT/QiYkQ7hQ07VfgnehExop3Chp0qFBS9iBiT87phpwoLRS8iRrRT2LBThYiiFxEj2ils2KnCRdGLM0Ykl46HDTtV6Ch6ETGi93rYsFOFkaIXESOJGBt2qpBS9CJipBFjw04VXopeRIwsYmzYqUJN0YuIEYyuTLCJFDlZsuNkPvfqkr+h2XEu7TjSUUddVjF/usKQdhwZqaPexnD+dIUh7TiSUmlImdMODQqNRS8iRuxoFrLmVAzNjnNpx5GaSvON87VCZtGLiBHbloW0LxVDs+NC2nEkqNKQ+aViaHZcSDuOHFWab7xThdWiFxEjixiwgaHZcSHtODJVaaE2RJ8/XWFIO41kVbp1qFToLXoRMWKwrFA7iM+frjCknUbKKi227EOz00LaaWSt0kLtyj5/usKQdhqJq7TYsDGF6qIXESPaabFhYwrbRS8iRrTTYsPGFMKLXkSMaKfFxrxVOC96ETGinR633odmp0dpp5HHSvUO8/OnKwxpp5HKypINW1fIL3oRMY4RY8PWFf6LXkSMMmJsPYtmp0dpp5HTypINW1dYMHpxxoi0VpZs2LpChNGLiOEixsbYKlwYvYgYScTYsHWFDqMXESOGXpMNW1cYMXoRMbKIsWHrCilGLyJGvrdXKrwYvYgYxd5eqVBj9CJiHPf2SoUdoxcRo9zbKxWCjF5EDNjbKxWOjF6cMeCwt1cqNBm9iBhub69UmDJ6ETGSvb1SIcvoRcRI9/ZKhS+jFxEj29srFcqMXkSMfG+vVPgxehExir29UqHI6EXEOO7tlQoJRi8iRrm3Vyo8GL2IGLC3VypUGL04YbjDYWevdBrX5STX5SJxtbVXOo3rcpLrchPXtbFXOo3KcpLKchOVtbFXOo3LcpLLcodsZ690GpflJJflIjO1tVc6jcxyksxyh2Jnr3QameUkmeUOx5290mlslpNsljuUO3ul09gsJ9ksd4CdvdJpbJaTbJZzh5290mlslpNslnNuZ690Gp3lJJ3lIjuV6Alt86crDGmnkZ3aoMDnT1cY0k5dtnPOdhqh5SSh5SI7ler5A/OnKwxppxOhpSdyzJ+uMKSdRvJpg4J2Gl3lJF3lZrpKp9udRlc5SVc5Nx33tx5FM1NJV7nIPaUb5K/T6Con6SoXuadUl4LPn64wpJkmk3Rgw0w1uspJuspNvXo2EDQjlWSVi8xTqmsP509XGNJIk0kps2HoGlnlJFnlkslIVVnM/OkKQxppZJ4SPXNt/nSFIa00Mk+Jnoc5f7rCkFYamadUlx7Nn64wpJVO7Xt0LeD8qcSYL/7j1x91++n70V/+T3vx33/87e9//+N0Gn/u/o9f//3HqZ4uBm1V/LE//vbff4TN/m///e9ff4SdYfrDzVcSl81/JHglP0x/pOV8JUvS+Y/j/M/zdL4SenxPfxQzTmgHOf8B0x9H/PXQXm/+I8c/jvgHfhlvLHRAm//ALzv8ssMv4z0f8Q5Dr6j5D/xygl9O8ct486Gdz/wHfjnFL2f45SzDP/A7GX4nx+/kCf6BX84RucDvFPijxfIRAhYIeMQvH/HLR/zyEb98xC/j6IQ64/Mf+OUSv1zilwG/jKMTCirPf8xjGsoLz38k+EeGfxT4B37Z4ZdxmEp8qyW+sVBpZv5jvo0S77nEey7xnku85xLvucR7DsUV5j/wy4BfRhsDtDFAGwO0MUAbA7QxQBsDvHlAGwO0MUAbA7SxkAQ6/4HfQdMCNK2QIDj/gV9GGwO0qJB8Nf+xfISAaFqApgU4vwAtKmSLzH/gl9HGAG0M0MYAbQzQxgBtDHB0glZ7/mMe3KBcnv/A75T4OCV+ucQvA355GqZ//8KFbLqMK1j8LCxpp6of63Pj336aumVrVigdu6xZ5TQAZrhL3XMsR7CSw0tYQz36+G8ZYEIB3UuAYz02HC0F+qilEW0c/e0+Dvy+UnpfiQ3p7fH+7vtH3zCstCyfWNlkuf8z1vmj6seP3g8fXXPht3akt1ZY4fz5t2IcB2IcoYPXPAWND3xuqmHww9jdez/4/lOMbUlv9GiF9FXLYBJic8dlphTWBw94831S2FDE5QnrcCmGl2C79lKPdddWTfPD75ka4rKKlkb7juAfvrr4nltlSqffshSXVpMKsLdqPH/4S9tdvMCmy8Sy3pfG5SdiD+NPI1BdSQcPF7XCuHKcu/ZcjeFem3oYxfjldPxwUwSj5V782+PKrTWj1mp87Es9VG+N/+fQtWKW5nSoUuPzXrozHxM61Z3RNC/d+Z/Dpbvdq37wfPlO6Yx0xhnpP33/E8aAv/6Mvn70W8D4oO91e1lDkr3guDhHpfGx3+vvpvrrp75VV2GDCZ3p6OTA0fj47/V375tqrD/9o6+FDVLrdujFgXHjeW+qaz1U5wDNh4luPot/VRq37gDLX0BON9nUuAi9d72vzh/rUaLL8eLLTq7M/4x69WPVNHH1+arHj7G6cvCCvlAEhxfAJ9fg5sfqUo0V3+so+OICpsap/gRf+R2hFNUTOcFd9GBci65+fKsG/+gbCprkZIYlYBz8qx+D53DuHu3IF2I6CRafNDeaaoANe+iXr68fHDihz754tIV9yOq2DQfvb3G/dLAWZzo3LgZXPypr8oFuGXggB+vifPVjU7e/L74d6pFv9w7oO8DxL+zj3/rvcTXTgK4uKQ6Z1a0NqN0leCnBQROOxIFO4uXoZN31rn7s/bvvfXv23GTJC04P9vfad19Vezl3zePWrk03Sen6jcN2tMMH49KGLaEveDn0Hq1Tra/e5hWBv1u6jS2n0cTopH1UAw6ZWBxDxjixMrSHwmgPH9Vw/qiby1vTnX/7sETKFYK+5iO+5tz4mj+q4YPCAXMnzRhD3V4bP1bXuh3qi1fvk9pugStDZlwZJrf68rg39bka/aAcIuluuYQ5SqO7ULf1WFdN/Zdfz2e6pC2hDGdcKethfhlh3+we47lrx9WroRZSoIVkRguph/tHX4URULGpw7eEOXLjGlcP9757q96an896qN/kK8+pX4rYVl++nq0mun58KtIJXqBJZ0ZzrIfPqqkv2qmZTpUMTdB6Fq+Hr4969MO94stnKNBCXjEaSG40kN/e35WDbuj4Qg42RltouuqyDmQQpCw1Pu2t6n8HV2wMByXhmNMJgWFIOBpXylv1HWZEiD6Ekw5/ZmpQifEFtm9jdz9X7aW+hJWBAxYU0HiH+q5O52iCtnMwvs17N4z3vjv7YVAmaaiVvYAXSwz6aBz0e+/vyo4W6luShQunpzNOz4C6XGWwdCFf4sAH42j1/tZ9+qq9zO4Th6beboov2XqCnqDDOYqvUjRCsES7wXiemkBXcZdQXJycp/Agbd0yJ9Th3NcygumoX448EmTmt3tvqrN/435jqPZKhgw3mIPRvmbQ8A5GcUYNFc7Ja8BwTmm0scFX/fljtWDRuZalRr9u8P20gfPYSU4dmsSMNV46vnmk1DPKUqNbMUzevDwvA92UU9zgnNF4hvp2b+r3n9YPo7/M7oUYFmqdCf6A1bUfutvaDSqpDS3UV2m0oeAY+/VAO/pOjVDhWDDUt7qpenEyCJVcyQaPj20lPB6tH87V3X+Mt8a3Yz3WYjc50GHLcBpZ9+ZH+9VX97abZr0S8KIs9bHA9TozzqVPfw6Hj666sNMzfcXGQHZ1uZyr8wc3/yM1f+MeEoC69r1mxu8K8hadMVBdXS6X7vb+aM8hbs9tnTr+RWabmNXl4j99O4b4tG/5knGkp+yYg2VEfO+7W7AdbuLkabPMjDV25+4W6JnBXy71mW2TjgZZnDEeXF3WjiHdFjKje101TfflL6d71Vc3Dke9mMw46apm9P1p7E6X+vPkv8/+vh7ggngFBTJJpZFJqm53vm/n1NVCDt3ovFb3TngB9NYWIt4Yo66Y2SV0+idWq+uvw9j577GvwuxnVnIko5tYZ6wSGCkSOh2Mfl41SKtl+8e8uDk8pyfO+LyP8YM/ZkHeWj7bhkPZRIHChVgYxf4Dp3M98t2PRlmKdLl9ows1o17q4Vz1l9P3vRo/mCEllBZLrVNxQh0+up670fTMX6AUJdZkeQFWiqhyeswtMA4Sq7S8gKo9Ornb1OjtTWhvTXX+HZZwfuYjBjG7AM46IyNs9/ZPfxZvlO4xRirmjSJk1FHOU9skeiuycAQXDEPotEbWQ/S5jWHrt6r383pRd4yxp0yqMbge+A82llTkkBiPWAFEhmoog2oMb79VQ33mjsGBOga2FT6iTLT4ZKt8iSYbb2J0NSJiBKzbK99+6Xpvx3qvw57JkHIa4cHDaExVnf+yDgW7wYSeRRNjyFCdkyndJzOjmOmtuzDvnp64UcqVGI80AUsZz2NBlx7jO4pqIX+5dF9tCLcN3DUrqWtmfNBH3VyC49g9xvuDu3p0UjqrDQe8wKOt8ZKCPjGGbFOr+QXg0dcaLlDcHHFt22PE/daeP6G+X4oKxdQYsl2HgHOq7yiQLTmijLB8sou2yb06JzmqzDLOughyGuq/GFKWF3Qjm+8wN0o1zlVzfjTV6CM34Ie7P9fv9VkcmFN6t6lxhj+hIzVQN/X4M3Tv4636ZkNHeZM0s02FBft5wH/7Ccx4dRZrXkIPtinydTG9xfZDo792vTjhH6njhE4e2CbHE1F1ctjLMNrFRyXieJT5LDLbvhglhKcQGj/VrZheGVUWZXi0KowB1wl5dib85aSSyxndyjNUOBfO+FLDT4y+5qs2NVqUAKbG2F5EFB5VyghwFIPHshXzX8Yw1/nj0f7mh2Kqs0gL46oiTx8HZpfzXRVGTWpA+3MeJY5KnVo8KT3hMY2gwDSCwigGjT/48bhxQWhOz7eFdbQClKYKymkM5KU3Ib1pumMXmPtQGM8hM3EXAhialjY0wyXxAWQJjBqIyQuVEaUsZwccHBsjExUxq/Yy9vWNRwuIMSTGMx16tSfp72XUIc2Rc8mNgrAI+6+H7/leRQnR1LoNBig52+khJUVBRiy4g7PdaE6N5yEcRwnmFx62jx6ACKbR0LgzLvVd0/hzlDvV7XvHbo0ehpzR1Z2UPYL8paQiID91ND7s9KnY1OhozA4ZLryYu5EcrHc8/QAPtfCdmIxRauQcFljlCEGNKTU6HzOcPOHQGAHKQBKjHPEclcN+YxOmfFCOOUl5blzPZ+jPqnlwK80ot5phKKKw+mATrh6NcHTjdMYUk4BYN37s7vX5FuTnfHaSd2CGCyH4EKEosr/qu5Q70pCY2ZLmqD6XaNBIvHVv7NoQLmc4jvnzZhxB0bAFEsOHRqnwuWuHsX/IaDQVYmD4dEkQXBLY5tUEF+LFBcd8uAS/kiGJnS2bqtWjVOQXCXWvMDWtWAg+jOvHcuUv/MafamSLhpBegzt3PZ/VdMu2mh9CPfqG+2cpFd+keBbIrK4AB/5zlQ+UMgswyvJWqOINpNQXSq0HNQE6xdP47puXFNc8jxhucFv5yNMonZHwkKCtH7+6/jd3FahcwqhLlLhDFTQFIkBJj8OZ9VAogf041u1VODcFBf6PTDf48VFUwNdR6jUZo0QK8GOsOVWaUal4ZqQeEfjiUbcq9jiWjGN18WZMNfpIlfLGlDgE9N+j79uK75j0qZ2R0SWAqxMnlYQX1ijIjPfuvXhaiuaMakFEk6eqnIoaC5TWFxhXKoxiXAofQi58uaY2hLkRufWwIZDXuwGV++VG/niFulDJ3PxpLC8vXjPVBVsuiBmV++UvbgkLqrbAZDQHIzdmYK2Q16sA1RflL243C2xUJ1fyFec0FFsYeWWKPctLxRruqF07awBnhg0cwkmLvjjqKzijhh9Rb1XdnnTJAhXruRdNWFqXy+nyYFRjU7DVQ9MooTOmNCHg/fLOZYlkWGYH04zV++oyx90530lXV2MCiIKZ8BvN6I2+ZvIE9NR88wXX5Uf6Nl+z9+HcV1ydUOSsxIuRFlzwlDXEMURj6vMCWI/+Vt05B0CD7YlRi7cA3uuLIEBorYPEmG6LcCIkFpo20bf32rlktU4mBT2GHl4zGmEnCXVC0xd9EIWIofqv1ChzQLif7jE+3oQ6ii4KB7dwB/lLT/1et1ff3/uan0zpBvnC/th3zQabSo81mKeb2neFUGrptPJr6JE2w1TSwn4QCahBxrxS/jlaA8XZ/cUJcKyEWTpaBsUZdbUzXMg/W60QdEI7K2Mw4423JpKyVaPQfJQpwWhdLHr14i+MXVSMrJxdWpCisG/fATbEM956X/0Wr4Iulkb92oIoakQ4alDOysRPYP96dCIHyFEC0pkDvhFNpjs4GnJxVgJ2xurkMDi6gjtjiseM9uibsbt0wZfipkO9yNce9qvrL2PXd904jJ6RQymVWKdHq710v2uujShZ7Ms6ruIoQiBsAH311US1spdhnoS6sYmV4+19NfpV3iwriGQDeoS8mp+VfpFueLFdlhHss7747u2n5snzlCyPzcheQ5OOwpGJga0BzMcwdrfTKt8vo0rGHPfO3MqSP8ZTqAD1c4r5hFyoR30j68z6i4vfyBqZ5Lapfqk4BA3QGk8gq1PHgSxfsMiZbZuN3KqpJHwRNyCJtxD+sW2iFX6dB0AlZvkSwbcZHs85SqjqOsGib5lxSlz8ubv403vN9ewZrW+V4RstjCeGGbT3w71rhTVTgjpHFWZhZC4n4NXo0zfgjBz/BHV/tD9nkcSV0gN2apSnxfAlVzWQF4g2Y9Q0XPx79WjGWCftpBZKy6nksUAKqDS6awv+Ou+IsquJcSFEuFv1Pa0yUekh17GcOpYFliIsjR4h/kZ7Grv7SU9kzqnjUWBKfGl0tPAXgjsTHmCQscOceiIFrgyl0eOOvvtUwlArs+JoXMIZpe8TplJHIqHpKCnmIaZGgvji770PSr1L1FuGIoJ9/fYY/XoPySldU6BMpDTW7bjMyb0i4k9VHWgnzlgw4eKHse+4JPrAfAXrFuNHfx5Pvj13FxEuzCj1myERmxsZsFl0wVYcGpXOrJN4Fm/EHMmTluCa0KJjqfGIgLCP9qtqR87AZzRkkaPQODfWQ7rUw2RHYrhTWiEjNSahULA/o5SBQ2b/CeRnXLg0K6e8x1KAtrBFL5YLzEUkL3IRD1jxVgcaSkEV1oGOMEqeBB3k7FkHGlVGsdmI7QcEqU+ZvMx4TkcK7zTWN98J3T8lMhOjm42Ay7YaK8EJO6eSlcyYM3R53O4yeTSjAszMSAkt9XtCBR/u5dIws81YuLonoQ+WGJVN89JyWiW703BGsWQHGM3P3974Sy/oJMMgoQ1mDjmGg6IobEDnWeyYbcJs+Tujp2nMnsyM2SDcQ0moPSTGeL4fQnmZevhY6Oxgrw/hsFPhcGbkXfx3datbf6re3np1B8loPYcced7ceuMzfJTVq/A0oTPHUgS58RyJ8FPVK45LT1eoVcqNOz/iSh1bRtevHOu+58aEkAW1vm28DJqrkWPhpdyoTwtZ4T3XuRX0UHxE4S4Y413++y4yZjOqjs1Qj5ZjNlBuZFeChqIdwrYds+TZDvFq2GrB0rYxqnI5LMnIxUI+GKuPz7/xKY6xFN14RlyQphkx1XVhCzz1AxNjEaoFVcGjEqLEuqLOGpfpJteFdjOWO4zV73Ojy7+gy63SUfVEYt1E1vIZRvg9E9vRx7JWgpiRw22uuRxqWjkyRLnRHZyR10n6OY3HFcaz94y2ToaheehG14hghSodekYJreVgt9CIO31J8Mc0VGpe+Ge8lUjV0cxFh3G1wphXx3FXRASVO7qllYJRQTZjS1PKabJ0YYzZIdbqHJDRcvJZsaRq4Fod+5698Avv1Wd97gR3wgrJvGSkddeqbjylBRJjyeIZMohvOFtEnUhj8jnBisud73shuaEHfmdUuc2oId4jZLNU4/uUTS867oNRijX/QDACVa9NVwBjTAEhVWEPfbPWo8OEF/7ZJRaL4locyh4UxgMhQnaP1l+u/roqsEP55tQYUVeFVkzqveTaYIcjFNnnry0AK4kTIy6evZZemgV999aNgyqn4fL3l3aowfvf68gKK4BRPjOKX7LZoXv0Z7EQ0o3FKEqe0dY1y2lt1MKo+p/B5rOkdP6PByZhWYroOKOCI6K3vnvwwBKlGgrsuFMa96t3QaTRciDGY8N7JXISafogDq4xbqHuFmyGG+8plHk/CU41o28qx6hUYRRhRUiNjnI0IOKMHnJEE/fnaJTAGdNs3nnKNk2yTYxaukDcSafCUTo7MapkA1D4N6dGhD+o5DYxkh3Tcez0c7s8qRrupNMAG7b2Koyr3oSubKw0I2tZSw/Fwtga82ERn0+NhMFbDS9CPdrfbffVrqKD1OHPjFpURAylpke/KleX0RhhZlQHz5gSiqqis+PyFjGD0VkJ9tAQZX2IojX/cmxjlhuDrQEy5DqsTpE0S80ZY3QBbGOAqD9t9PsC2t6GTGPWxnTBALkz4jSzybp16FLKI8vvmIfZKLxmvWSkJdHp/qxrh839nLMuUk11netObfanyqkDWOBGXRrPqvEXArV0Pz3apv7tmx9RSJO+IkzOLI2EbUSf+oyctL5dVIVXoJSjNBZueO/O3LtwlMlxRpYuovhLFIRJLTUNhBuVtu9df6v4cY/qmRwuJpmRVJrwRsHI0iwGDMw6YwLaO39ISqUlhXH97P2/Hr49i7JB9DGnf5laF/m+u60KmjIRtTHYeg11W6vRv3VfUozH2hHZLOzqBR9F1jLj+F39pBNZbQdUxZyhkKAwpj1G1LpVVNeUFcEE6cIYA5z6OcWeLYLVo/u20VELYJ9V3YROAYGoeqvOv/tVKX5gQkRjeEXvsZTRSE1WLKHQ43LINOYchP5IYTW4+Kb64e+B/oLxxBHQHn3v2zGEgvjDsyOWsY7bNVQhn3ix9c5IRWzGXIOA9+hXWagFMHbSKAe/+vGjG8aqvciSGBnNy8ywxpo7YONbZ9WxzT8hS5lk1BHKjs8aTYcF3zwJ6vegC+anYaa4M8Ztr36MbtYUuBRVlqmkxqhFvfqRziQ2XLR7nTsYOa8Z0PfDKPGAaYheu8GVeBlYGpbRZSNgEw4bD7ZuGHeZ0JzqIfqWZDQmlxmJ3tCGqrmsTZAu6cUS6DwusZOD2W4W71e1HTrN7cuGXC9pBCozcsVXP0YNeJQhSCFpAcwIjecHhAwrmr+8K1VfCmCzz5hhgbhSrA5MImEMmQewUPdITDq2Rho97qvo8kKFrai6Lo2lkz6q261ur0EcVonqPnRzMcZBP6r20sRIoJS+OKovc0b//KMa3rxHQ+amR89HRkFB6HmmhP2pz18sbdSNm/PKR6TNFuwQq1rMNAqIO1BpdJyUXsHuwCbWc0uzAdYn/RSR0eK5+VKAx9h9IezC7WqfJIDodxnVAh/8XEIX08QYJVlRmI7nueB7W3jSReJndD7CDyQjj5SzBF7jtB1vzWlqK3K6VUJGT/lGQNH10fgOH/wd0tiLMarNQ7Q0Cp1gY4TcuADwpCPWFQFfPEYtE6OYoL7U3fDTnkNrOz8okpKMlf7H9q25sZDKquuco8mxidFK1l1caJGAbKHWbPtjfbuqz0klX1inMzcmXNQ3KXaiZMriks//xcDY0khhHrNXfuvPuQobswjyUl6FCuXSeCCUrNyvgIWwQ4iq8bqSVLdo2wdmuFWFU1YtxzaLZyiNlaZnXCN7gGj1MNx90/CdmIWPXxqEfz26nt8a9ausEyVCjb5nmaU009kYEJmRvurf9V1MYZqm+pLJhu90seSoKAhNCy4bQysT4oatsc39Bbhoa+FfCs0tZQRegHtayPgjWtqwejHGlTpihqHVo4X0Ll+ZYTjEkQTn5yIarjXOtPXBkrn0RtlHPZwuj7e6ewxKYV6qnUMXpDCeBOvhFAsDKYE+emw9LvmKxjeJsOtodUanS4a+a2G1y+H01Xft9bR8wkKedBfEgtq5kW6pB//9UT2G5UzMj8Q07mkMVgXEdXmzjK5jGTZudYfyqai0vosY/OHnHsowGqNIM06gf/l90ijAcfFky6UyhHW3GW4PcT4rShb9MZI99dBWn/U1hhJXizBNTMgOT6Xewo0Zs8nqoe2m8GwlGg+n1FXLDs/47zJwxmzeWmjsEqrZTMzmem+qR+yOPNOifNulfrXxwBVaI8f+B2v7p3kFxtBBPTz6ZqXOIq8QzCPyGN9LPtGpmaPiLwfjVj51apb2nrDqm+b1M2LJWt/Ud84Oz0DdEjU232oojzH5CfW17XpRwJc61amRnqu5CIOGzRMjxEokSpusmRHUQwetoIc9AfKjzcsIoM1lbiYXGomJnEMaCMPVtjSeWv8ZNobv8dRU7fUhT1/JgR3RbWY9I/Z+OD/4kZA7WMZn/6vIGEj26pD89j9z1xbu89CGJ0gup0adRdxY2gd3vqnDkhjFnr87brR0wTTy8GHkmD2wIPc8MXGGJsZclgCqNqWk7oLRVwxYWtoN9ZeWtIvDM/xvLPmPlstPoVTiiF0dMmOh/sa3V07CUZLI2Ee88eOqQA4lbVMjNdTUZy+0iKy/OcYWjJsOqSqwyhplRwtj8X2Bt+5v71J28jaan5Ts0bqJmP7njJVtYlbw+nhBi+UcsGiLkekOkEgmTx3MePSUnuiNB/EAtbpJFso1w+h1kBgVZOwCGND0QkgFYyaNB1ECt6qExEomWleWjvemp2NaWg24f6yahTnKxyVGNXLTP1b9yyiOsSBWI1gumuoFuLkbo7K3qn0E1dukhBMBLKr/TIxk6AIYhW93iUiTEo1nyVs1nj/+9agG0b6X0uhptqQlGSX6onlaRpMbMuMWGMRHQeu8tg5aLSPBMk85ns1yI22D+MPp7kMz2z52HOcBLno6T4win4C7Wj8TqsBKjEk+AeneDfEstlFJJ6PeRu4ww/eFV9z76dH5plHS/ds+6Kfe30OAa1X6kppTYmRhAh4qc0+Dl2p3agRGZj0gxh3y9FVfhMyH9izJsXNPbvRHb9X3WttPX6Ex2nqrvqW1UxM0yuJvVXD/vURibVUx7GI8At18f/Vf9fgRWtzIEkZU04nhi9R4vghcwbNuEbdt6mflmNiVG+sR3kTGJU03zoyurapUpNkF+WFJLjPf1SmUDZmaDa73PXpoNkavbs/64/5yCt9VVky6jhnz9zjuGpJu0cYePwFyY0mnD24kowPaVBV446lpnYbE6I4Q0DUedQeNZ5lV3yY6Ca0I9fvP+aPvbr6617EWgywjShMgbaAPKcNjlTCNL2tN4VDZwtJ50WYcrb/GnAR+7KCVazBPujQKtFofFHjX09dHPfpVU78jq+y01MawDWvrv0Lp4HUFqozKovIEQ4jGQ2vrv0cZP8xpPm+B8fLSqJINiNHl594+Oz1YB4hXKKKpIolREtCKcAv1CoynyTYwP43c2ujJo8DYfGkUaC2Qp+gNs+GkKe95ttTQsC2hC/BUQ0IUX6ZjYBSCLoDvfXW9iY04Zb0HjS7ggrhO0KfsrjH2uKDdq17cGw33GTfLBW3V4JZlkSxMV7GIs405L93vW/Xz5utxqNTsx5yWEygw1FMaj1Zd2/wEl0mTQ7DgG5JKxuSOrq+vtST/aMpPZiw5hkBr15VObSNtPm2aCi9L2Q/bjtd9+r5qmp2ul3T9So2okXv/uYs4JXWMjEL7EJZtGt+cQt1RccyhPr9Ry76qv1rQzLUSRUxg9FnDu9KivdT9PTynzEJoGm3mXoWwqs6x0A01wQ3VKAC8V4/BKxsVUzUYY3CRbggb/7o+JNV5FlgZoixsq9tdbIC0DpIZYuZWTz++6k/rgcpoedkM8y4LIyUeIo/KS2TpOsZc2wWKT+eiZIFCoxd874Z67duxMDpWJTTq2kPh23oQentWD9poK4iz12OX7l123MG3YzUlvm6ccHNKSxaY9VYaPaF77z+DdGc94CVTDxvPewFu7XvSDRDzQUpj1cKYtbydDk2j9JmRbJsgV0iUcjMKcucGY+uEATpZzIPdjZ3cW3KKVBhd0Xv/aP1KDc50e0ZvPSJhbeDwlEJ1Sr1Ps4U8Wr+eHjkr5Gbc9IRYgO6bRimw6AbkaEDQ6PxqcW/qWhodvdClhe8y9MSGerHS2Gmkr9rfYekIXa+Hs2/HvmrGbmHROYnOuo3bHrqvvlYVM+kKZ9zJ+upr1T+aylMSo9Jls/0bVVUYy2OEYugNz2ihS7dtWe39ubu28oBJEzKsEQ0Mrdch+4dHH1LKK2VGF7v3TPSU0A00MZ6pen/131rvEnrOdZgvYdTtRNC7IIzp6oeVXUpjoL73jf+UiWEJZfOsCfq9v3Wf/jR/SW15T1GN/PiEGtu1qPXcqSQoRVYmNZK+M/inb2MzqVAYgKkPDixUZ9xYen+v6v4UOyf8KGw8HX4UgxTGIoR9yJM/+/dOvIacohYogSnNk3ngVQxSmtmdmS1p8GPkhUU5SyoUxQIeuVtSyWzbmFqpimpljaLLXsTF6MQ2HqBCpyv2tmhZi9QYWui7L17mgEbojkh/g5H+7kVSFz1rG3mnVdpzQsNmifFMHNuBr4rdpEeW3PRUUy5CZGOzm6Fq67H+ywfSjTtZdKYaZ//UDHTV0ZJ59Eutf6u4ZTj3jzcZRWORmXKRHS+NPA7G0iVTKOAkldMZdaVyDHLlxkotC2gMN/CAEqUFsWNPbjyTTLjD2PuKN4Wjcow0f2rRX4H98m8ckxYQJZUIbZNxxgxpI/5SVxyZbYVLoRBjgGQqGMljBCyXx8j4D74JrVf0ynFUQpBnuLAaaYvFAeYWS5c0Iw88+FE/fDsqeUqMCSiDH/U2Ye7IkniMc90rAVNHXTFn5KMGPzZdx6T6BbBIjbEg4LBXqoOxRkZZ1uDH4ePx/s5zHgpgToxREBOwhGNelKwqgtHHH/SqCCxOZlSpDB9V7zUnMKe5swVuKqWxXsVQ31Y5/rRLgHGiT3kX4mxF/SjrGj/rcFZR34QWbkqsc7IeYwlL5tZSXxGJHPQ4jksVb6vV8RQM6gslRu9l4NFeKs5NjKkqQ+P9/STLJzmapJQYw7HrQryOdblG+yqSJaHKughNfXuZ6dJ4TGH0tGeczZINtINIgt6AsVbFcG/qUd8TaF3YdCmFaK0oGYFDHGPwt6od6/OqfXFKsyZSI8898KASy+Q1uuJDf/6zeoxdyBkPtU3Y/1B0Ytq2I3FAnuQk7CbJLZphAq0pTmn0jDZP3nnq4tDM/8WMg/9dkn64C6W5BI29Yi0FNDrMq8PAnEOuyiV4L6jbcNjdxeV424truPhzi/uFy1aCtM3cx/4Xdo3/hS3ff2Gz9pDygt/B+H+K5SpSbOeZYQghw7eX4WvL8L1l+OKyBK8gYZ1h4D7Hp8gxIJNjYfAcfz1/1kufPyqMNT/JUHT9n6su3VQBW2DdhyJZVEIYdMAFrMBBKLA7SIGFrufOab+wUnWoiII4eCBYaqQUePQosAEOGLlO/kDySEa3d3h2B1iK3ByerWwW2z5Y3d/+/GfUosSSERVvb5lQP8yaxvJEXGlcEuqLWWPeT7yhex+F3juhNZxSo1rriRjrrnI8mo9ojPwFvLW/klIzTLGjX4oRoNSYOB/BF+fqT93PSg+sSLtxq+vPf4Zwf4hA/7mx5dGjqjHPkMOO3T0kgApYelo1smgMVvIBKeXlUiOryRHnP/iGTM3VyFYw1PDoHJGO0wv7s9LOktJHxnaWC9LwZ6t0yaCmb3WXnoiBTeJ49Fmt/voTb6PXBH1so2Z+6M/DqrZfTg+/Be6jpTVoNArZWUITuhOjfD7UlOQxR9bx14whajw7LpyYdwQznufhqtT9ByY7dndFHcIO0InRZseu91rBN8fJCTuYUuCSVqW0rstKYC9dLfgWGFHUOaXBgcyoj45ZWpfu8db40KyaU0SsaY1D99A4dx7Xqx/GIO6dE/nDsWCVdUOGAs3NGoV+3EPNGn85vd9CBXRWXM3RYGFiDUE/EeMBUUTPaBTBmM04fPJJSmUIxviIUCpSEswYSVon3FK5NoY9nXGbGkPV/GqsRGJlQiueJkZ/SlocPYAvnTaMafKx1XqkTkU9Kbo5GYN4Y9WHKuAhbZzvdFS1lBnTh0ZfDTF7b1O7RUPGxpDe6OtT6DEdhHq1uMuMEvc5HrVy41YfkGdGeqxqTsHSAFiOh6Dcasi+nisjhWC3uGNayAmPuLlxz3gCS3vKWM3MJQ3TGBobfR1h1/W7WZ7WbKbmt8DrsaWUSE3Nd9bfQlPnq0gGTaneMzXylyuhDa32h+GCpxzXeDyMFUNWXZ4pO1JgUKI0qpAD5FqNmtAYY2rUR4d45zBWNy4IKQpWmsnIga06hrFCLhjqXLoQYMjgiMEZSJejt7GkXPxFda1jQnbbNqrUeqO7lM0f5UxdSusypiibTTEv6P+LyMqv/+cBkbH74PXugJUaMGL85jnEKU1hSo06C+1ImtMs7AKbeJZGnxURpxMWv0F60l96Dzijl7g6p1GZrB1B3BJ1p61uTTdWzaNv2sftTcjdaSwjMx7zRhFdp3SKdSPuqzru7Y0g2VJaGj0zysGC8COWeBCkh2OlRY2k+tjXN/6K6OPN091Y0Ddgrduj08hlfpinYmFd3fufuU/89120m6awbtF7GE2k//nobl6KSBydolZ5Q1BiaykwrIbNQpM9G65YneFVkVF6j7aJxZRRGZXf5kbN+UMwnJTwMGabPto61DcVBYnThEWcbDMAW3Cd+m51HKLnDizyWBr1/oirV7/IaXinwNrcpbGYyqNdZ0GzIj3G2b9kOHz5t/DfQVnmaNuPzJji8riHB1aLKbPOxEaV2kOsmjQyZowrSgqEtQ2Z5/uy7y9U7FIDbTl0Pj2C51/GMeubUwwX8ddBXSKjaPXRN29Ndf69KtTEVjG8deOE6hvZDCylR+TMmKoYlIryIVN6dMiSp1px6exr7HT5CAfm6rpq8F4yytS2CM1HOF6whCyzxlAwwqzKXdKY22HxGZ9NmIzy2s9Y2ie4WP57jN04zv4uqArm1jwbLthc9E/efIDG7BNjZ+sYmBUCIpoCgbOnNIYwV1pE6usave4v/6ZSaJSA+Y8ptMjyLUL/eUymkeIjw+ieZyDTturt/Ep1r/kPMaHH09m2TSv+Q5vlwxNgnODzcV54adErv9R9ff5o/Hiph0neKAIpacriFU+NqG2tn34pqE8jUxjEPe/1WTCcrC+8DTbU4hjulWgqTlfwAu+1NHa12pDIMs7Y+Hrr8WOzGhHtW4EH59w4uzfrALBq6LjbGEeo60O9nwevAlGwrp0Hoz/61dejf380zcTpMIulEc/UGJuPeKOvpSQ+oVHO1EgdfN+asRPNaxIa1UyN5bXmlvFT6zj+0pj82XJf//j1x72++1AF5o+//f0f//73/wUFd1td4VIFAA=="; \ No newline at end of file diff --git a/docs/classes/src_extract_content_core.Document.html b/docs/classes/src_extract_content_core.Document.html new file mode 100644 index 0000000..b9452e6 --- /dev/null +++ b/docs/classes/src_extract_content_core.Document.html @@ -0,0 +1,23 @@ +
void
+Removes the class="" attribute from every element in the given +subtree, except those that match CLASSES_TO_PRESERVE and +the classesToPreserve array from the options object.
+void
+Clean an element of all tags of type "tag" if they look fishy. +"Fishy" is an algorithm based on content length, classnames, link density, number of images & embeds, etc.
+void
+Clean out spurious headers from an Element.
+void
+Clean out elements that match the specified conditions
+void
+Remove the style attribute on every e and under. +TODO: Test if getElementsByTagName(*) is faster.
+void
+Concat all nodelists passed as arguments.
+Rest
...args: any[]...NodeList
+Iterate over a NodeList, return true if all of the provided iterate +function calls return true, false otherwise.
+For convenience, the current object context is applied to the +provided iterate function.
+Boolean
+Iterate over a NodeList, and return the first node that passes +the supplied test function
+For convenience, the current object context is applied to the provided +test function.
+void
+void
+Iterate over a NodeList, which doesn't natively fully implement the Array +interface.
+For convenience, the current object context is applied to the provided +iterate function.
+void
+Attempts to get excerpt and byline metadata for the article.
+— object containing any metadata that +could be extracted from JSON-LD object.
+Object with optional "excerpt" and "byline" properties
+Get the article title as an H1.
+string
+Get the number of times a string s appears in the node e.
+number (integer)
+Get an elements class/id weight. Uses regular expressions to tell if this +element looks good or bad.
+number (Integer)
+Get the inner text of a node - cross browser compatibly. +This also strips out any excess whitespace to be found.
+string
+Try to extract metadata from JSON-LD object. +For now, only Schema.org objects of type Article or its subtypes are supported.
+Object with any metadata that could be extracted (possibly none)
+Get the density of links as a percentage of the content +This is the amount of text that is inside a link divided by the total text in the node.
+number (float)
+Traverse the DOM from node to node, starting at the node passed in. +Pass true for the second parameter to indicate this node itself +(and its kids) are going away, and we want the next node over.
+Calling this in a loop will traverse the DOM depth-first.
+Return an object indicating how many rows and columns this table has.
+grabArticle - Using a variety of metrics (content score, classname, element types), find the content that is +most likely to be the stuff a user wants to read. Then return it wrapped up in a div.
+Check if a given node has one of its ancestor tag name matching the +provided one.
+Boolean
+Determine whether element has any children block level elements.
+Check if this node has only whitespace and a single element with given tag +Returns false if the DIV node contains non-empty text nodes +or if it contains no element with given tag or more than 1 element.
+Check if this node is an H1 or H2 element whose content is mostly +the same as the article title.
+boolean indicating whether this is a title-like header.
+Initialize a node with the readability object. Also checks the +className/id for special names to add to its score.
+void
+Determine if a node qualifies as phrasing content. +https://developer.mozilla.org/en-US/docs/Web/Guide/HTML/Content_categories#Phrasing_content
+Check if node is image, or if node contains exactly only one image +whether as a direct child or as its descendants.
+Check whether the input string could be a byline. +This verifies that the input is a string, and that the length +is less than 100 chars.
+Boolean - whether the input string is a byline.
+Look for 'data' (as opposed to 'layout') tables, for which we use +similar checks as +https://searchfox.org/mozilla-central/rev/f82d5c549f046cb64ce5602bfd894b7ae807c8f8/accessible/generic/TableAccessible.cpp#19
+Finds the next node, starting from the given node, and ignoring +whitespace in between. If the given node is an element, the same node is +returned.
+Run any post-process modifications to article content as necessary.
+void
+Prepare the article node for display. Clean out any inline styles, +iframes, forms, strip extraneous
tags, etc.
+void
+Prepare the HTML document for readability to scrape it. +This includes things like stripping javascript, CSS, and handling terrible markup.
+void
+Iterates over a NodeList, calls filterFn
for each node and removes node
+if function returned true
.
If function is not passed, removes all the nodes in node list.
+void
+Removes script tags from the document.
+Replaces 2 or more successive
elements with a single
.
+Whitespace between
elements are ignored. For example:
abc
Iterates over a NodeList, and calls _setNodeTag for each node.
+void
+Iterate over a NodeList, return true if any of the provided iterate +function calls returns true, false otherwise.
+For convenience, the current object context is applied to the +provided iterate function.
+Boolean
+Converts some of the common HTML entities in string to their corresponding characters.
+{string} - a string to unescape.
+string without HTML entity.
+Find all
+Runs readability.
+Workflow:
+Static
prototypeClean a node of all elements of type "tag". +(Unless it's a youtube/vimeo video. People love movies.)
+void
+Removes the class="" attribute from every element in the given +subtree, except those that match CLASSES_TO_PRESERVE and +the classesToPreserve array from the options object.
+void
+Clean an element of all tags of type "tag" if they look fishy. +"Fishy" is an algorithm based on content length, classnames, link density, number of images & embeds, etc.
+void
+Clean out spurious headers from an Element.
+void
+Clean out elements that match the specified conditions
+void
+Remove the style attribute on every e and under. +TODO: Test if getElementsByTagName(*) is faster.
+void
+Concat all nodelists passed as arguments.
+Rest
...args: any[]...NodeList
+Iterate over a NodeList, return true if all of the provided iterate +function calls return true, false otherwise.
+For convenience, the current object context is applied to the +provided iterate function.
+Boolean
+Iterate over a NodeList, and return the first node that passes +the supplied test function
+For convenience, the current object context is applied to the provided +test function.
+void
+void
+Iterate over a NodeList, which doesn't natively fully implement the Array +interface.
+For convenience, the current object context is applied to the provided +iterate function.
+void
+Attempts to get excerpt and byline metadata for the article.
+— object containing any metadata that +could be extracted from JSON-LD object.
+Object with optional "excerpt" and "byline" properties
+Get the article title as an H1.
+string
+Get the number of times a string s appears in the node e.
+number (integer)
+Get an elements class/id weight. Uses regular expressions to tell if this +element looks good or bad.
+number (Integer)
+Get the inner text of a node - cross browser compatibly. +This also strips out any excess whitespace to be found.
+string
+Try to extract metadata from JSON-LD object. +For now, only Schema.org objects of type Article or its subtypes are supported.
+Object with any metadata that could be extracted (possibly none)
+Get the density of links as a percentage of the content +This is the amount of text that is inside a link divided by the total text in the node.
+number (float)
+Traverse the DOM from node to node, starting at the node passed in. +Pass true for the second parameter to indicate this node itself +(and its kids) are going away, and we want the next node over.
+Calling this in a loop will traverse the DOM depth-first.
+Return an object indicating how many rows and columns this table has.
+grabArticle - Using a variety of metrics (content score, classname, element types), find the content that is +most likely to be the stuff a user wants to read. Then return it wrapped up in a div.
+Check if a given node has one of its ancestor tag name matching the +provided one.
+Boolean
+Determine whether element has any children block level elements.
+Check if this node has only whitespace and a single element with given tag +Returns false if the DIV node contains non-empty text nodes +or if it contains no element with given tag or more than 1 element.
+Check if this node is an H1 or H2 element whose content is mostly +the same as the article title.
+boolean indicating whether this is a title-like header.
+Initialize a node with the readability object. Also checks the +className/id for special names to add to its score.
+void
+Determine if a node qualifies as phrasing content. +https://developer.mozilla.org/en-US/docs/Web/Guide/HTML/Content_categories#Phrasing_content
+Check if node is image, or if node contains exactly only one image +whether as a direct child or as its descendants.
+Check whether the input string could be a byline. +This verifies that the input is a string, and that the length +is less than 100 chars.
+Boolean - whether the input string is a byline.
+Look for 'data' (as opposed to 'layout') tables, for which we use +similar checks as +https://searchfox.org/mozilla-central/rev/f82d5c549f046cb64ce5602bfd894b7ae807c8f8/accessible/generic/TableAccessible.cpp#19
+Finds the next node, starting from the given node, and ignoring +whitespace in between. If the given node is an element, the same node is +returned.
+Run any post-process modifications to article content as necessary.
+void
+Prepare the article node for display. Clean out any inline styles, +iframes, forms, strip extraneous
tags, etc.
+void
+Prepare the HTML document for readability to scrape it. +This includes things like stripping javascript, CSS, and handling terrible markup.
+void
+Iterates over a NodeList, calls filterFn
for each node and removes node
+if function returned true
.
If function is not passed, removes all the nodes in node list.
+void
+Removes script tags from the document.
+Replaces 2 or more successive
elements with a single
.
+Whitespace between
elements are ignored. For example:
abc
Iterates over a NodeList, and calls _setNodeTag for each node.
+void
+Iterate over a NodeList, return true if any of the provided iterate +function calls returns true, false otherwise.
+For convenience, the current object context is applied to the +provided iterate function.
+Boolean
+Converts some of the common HTML entities in string to their corresponding characters.
+{string} - a string to unescape.
+string without HTML entity.
+Find all
Runs readability.
+Workflow:
+// Using options
const customModel = await import("./custom-phrases-model.json");
const suggestions = await suggestNextWordCompletions("artificial int", {
phrasesModel: customModel,
limitMaxResults: 5,
numberOfLastWordsToCheck: 3
});
// Possible output: [{ phrase: "artificial intelligence" }, { phrase: "artificial interpretation" }]
-
Clean a node of all elements of type "tag". +(Unless it's a youtube/vimeo video. People love movies.)
+