Создание 3d из изображения на канвасе и шейдерах

Плоское изображение на канвасе с помощью js и шейдеров переводится в 3d.

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Тут картинка переведена в формат base64, исключительно из-за ограничений сервиса codepen.

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vIMQDqN1tY0MdbQr1SmlTudvPSxpHa5jFW6VWosZ6sZIhHQitTTPKFYyt9z01QzqvFb/AGc9SXpb51c6NVXzbNF0uEypMpHUyCYqGJx0pYbbPfyV89LGmZ1LLSc6s65jNc0ypFOQTFNuQmjqSa+f+R2yx7lE1UbTRbzq9UWrWPtOpld2ktCAvIb0YmqmaOpliMrShyee50KXJ9NUIp7Wp1YUsrs0ltBjqTQUreuZ0IhtaJkJ8FLDWE7e+TLXCsaQTQS+DgZakTKQJk0KOGTSppjnwnj9ptSyEVSgZ01YCdIUGsi3tFGLVld7bI6VikdKthpzBl2t8l5XUE5VCZAVzCGsrxSs7brn03b6MbGsVcrt651sdYQdBVPAM1Z2yCas65187dcyFnXNcs6S5plTyCpVsdX6ZnSWmQCjxHj9rWmUlpyCEwVBNI0mxDsplcttGK3pCpowOkiLGXEt22XRVOW0dbLV9SdJMuzrmKp+ubdImaIUgVpUUxoE5Y2psa5hNWNMxGypli4plTAOuSaNpU1wE0E0ypFMEQmbXjvI7GUiZAG1SzuBtaqqpGyWsGUtfpwy+Td9ogCXw4RLD0hqM6LanXz0Jki0OrB9wylCCpBnYy7fRlwUufW90ZcDLlcUdp1RIP1gmgiipSJGelrbIEza4AlkxtwE1LUJgnCP/8QAKxAAAgIBBAEEAgICAwEAAAAAAQIAAxEEEBIhEwUUIjEgMjBBBhUjJDND/9oACAEBAAEFAvK5jMpOK4FSFZxO+Z3OQE5wvPJn8czM+xM975E+5x247ZnKdxcQn5bYnW+YLoLckNtn+DqD8vlMtAuZxM4tDkTJmTO9viY/IbYinE4iZmJ9TMVpidg9zqcIMQYmVmMwjE+RmDAggOI0UT62z0BtjbGwJEWxc5gP8w02oI9rdjxvCGncwSOInhtywAhZJyEDmdHfkJyzt3BOp2ZgzDYwYN+5ybbuArscCfIxe2YHK7KZ1gz6AHUxsrwN+WDBD+AMxE9k0ZNWoOo1yltfY0TUmNqqzDrj42sUq3cNazxicVhwJzE4AzBEAJnxWfcCCdCZmZmZmZmZmZmZmd+IhEXAJ+RsXC/0uZkTMz1OP4L0Qw/HMH5dRVJnjeZeqHWKymyrDeNoSVnknNpzacmnMieQTms5QtOLGCsCZ2zMzM72xMTExMTExMTEwZ3svU+xwGxAxmfcyBDMTExO9g5EDgwb5P4Z2xO5yzCDsoLNkz5QtOKGYWcBOE4iBEMFQmFEzMzO+JiY2x+WJjfExOMxMzM/rGIvSj7P7dbZne2Ieotsztn8e9l0Wsaf63XYXS1ThpFcOqLbZZY44ZzXC05Nt8CfhMwvMzO2JiYmJiYg/EbY/PExOM7mZxmMQnYGEidmYh2xA+IrTvbO2dzrdY8Ls0yYcwkzDTm0yIGALvyaIhMwqwmZ2xMTG+P4MbYmJj+DEK78e2wJkmATGNsTE+tgSCrTO2Zk75nkaFhOpx77mPwRczpYTtiYmJjcCYmJiYnGYnGcJiYmJiYnGeOFZiYmN8TEK7cZ1AJnIgjdwjYgwEiKZmZ2ydjiZhImVg7P1DtiAQQnbExtiYmIFgScJwnCePMWkzwzwmeKeOePrjvgTHWIROMxMbYmJiFd+XyWCN9idw7EQdEPM/idvHGZEQwtt9xBiM2wEAmJiAQCCuV6cxdNPbGNRiLpSYNLPDPAAOHRCx4xxM4haf0XGC85wHbjOMxMfgRMYg/duoT8uU7mdsQiEQRWgOZmZWZhmBOU5HYwRRGMOwExMTECxKiZTpDE0uIKRDVPDmeLAFPfDEswsexY+oUSzUZDWkwuZynKZmZmBoHgboTEKxszMwTuVmCZxJir3iLDPvbEIggMDbGDuEgzE7mIYIv0dgIBMRVnCVUEzT6SV0gTxzjOECQrGxi69QL9STHuyWacXMb07XikpYJn8MzMzA0R9sRlnGYhEb7n1sOnMB2/sjcjYEbGE7DY9T7g+/6MAgEAiIcrXKqMzTUd11wLMTjMQyywKNRrQJbqMl2JmTMkATT+oHx26/QtXRT6FqG1f+NaOyzVaK/Sv+KtiVvs0KzEIjLmcIyz6h+sAifX4YhExAdsEkwQQL03yaCHYCARVlVcrpyadPFrAgWATGxMtuCjWa0YsuLQN2332YoOCe/SE8ot9FS0D/Gmzb6TrtLa2pu8llaGYImNsbK0qaDucYVhExCIRGXb62B3BmdiN87LFzGYwCf3sIsUStJVVKKYiTEA/C2zE12sljsxxifUVczh3xjVtNHqLaLdLqKLq4QDNT6PprT6loX0tpxAoMbjtx2reUsDOMKGEQiEQiMIy74272CqQADAhMIweLQjZBmF8CZAVRuoiiViVpKKpWsGw3dsTX6zjGcu2JiccwfGJiWYz5gA9k0NzLKfULkDesWY1PrHqRY28iozBxnxaMu2J9Sh+6vkCsdZiEQiERhOHUKzE+t7LHsPNufHlPBbtx7zjY7AdGCCKJWs0yZNSQCCCCGGa3UBFssNj/3CO0q5SysIOeJY7vMCtnsQT3M91NTqdLy86k8uUQhYSuBgz6D9wEGGIcHS2d8enXriIywwxhCOvkGzMZ2wQdguSMZ8z8TgTlAIIB22MwxYsQSoTRK0QQbDYS6zA9R1XN0qyPE3Jh81UZp8QbX6q6yxfIsLHFt0JJhTAp07Ws/p1qiJayyoq8OUi2Pxd4ELQriYmJpLMNV2t9eUXHF8Rm7Pyn9YyorniQzxLDjx5gMxMQzy1+H7gXGw7j4VYIYIsQShMyhYv4GGepajhX+zqVEtKKB9d4YcaGd1ZXJl9jfwVuUYYK5IKouFr7tpNcAE6lZw2jtypr6spPJtPPHxhWMkQCFeIK5ArHDHxMziK+RncdQwDM+vxEWVzTLKoNwZmO3XqlpZ6VzEo5Fqx5K1EsZK09xbY2cSxmCsxJ/MzTkEEYmnBIpUc9ZksEaYO3prwdhljLHWMI0+ibMgDoDsKTSRDtyzviY/FVyMdiIJUs04iRds7Ey5sLrGy+hrBLgIF5cVRpYwq06WOxbiZqMAfwGaRhAFIo4LRozUZqAoi04Z6kl1fehJV6/1ZemWWJGWONnM7g+m5KzQ7JFcT44JjQbGCU/T/sBKxKVlf0v0pmdiepq2wlnys0KAR15oeHA9ipWeWV14+Qmrz/FpP3wZokaxlq8NYrUwUjNlACvXKRh6P1InHqwR0liwiNF+ntCwjmdV7fzHfHXMcDmJCnGHZRK16I7CxBKB0IkzM9CZmZqz8MfOhMj2+BfUyM6XINLZymssRz4eM1o6/gM0g+Kz06kq1ueSlsm3AN3ydsyn/wBafqcenjiWiMphU5/WvDNC/ClxDsEMC4nHsDEKgonAowI2QTT1ZFulMVIqygQytpy2Bn9Gar9B/wCtHxbiTHpj6HBrrRY4ZC9js2oWxq/4dKv/ABV1WSrUMk862RPoZAsrybAZpf2pHUA6sAhEsWcPkV7dIv7Wr83i1s8WgCGoY8WZwMKwZxXanjYdDuUVEnT14gqBF2kxFSIIYmeS7cpnvOZf2hJVtMTxDxnPPxgg6cg+oniPCCr1Jx1VJrsH5qCzaen4jJiUzCcgpg6jdmyvrRVd1jqYhEMdcnxjNdWTaYp7+44r9rlSvhxPHGrnEc4YZkxUeaIhpVXFEKAizTQVziJxgrnGN1srdEzVDjZQ3kWossNZ4fJXNwYXU+4taixVPk5X0NZGRq3P5aXTkGpDyVErjvVkMJV2roHjxum0idLsYYR24GGXFbAJXd+gXjW74SnygVV6mcL58oVJn/0ahgpBjLMHOndJ7ZGmh9QGcQTEaoQqRAIBCIVnGMPnNcnx9Mv42A5bOYUDL4lgrwXazhxd4OQltAsL0WJ+CVsxq0i5QYNNRY3EiMnSMCgTECBDc4E48rNOvFRucwiNOOW1j1pL7g0GRECGyuDAllgJK0GrxVMPBqcPYxnIiF5paKna2rSkChFntNK606nX1NTelqCYzDXDTiYmIVhEuV4OZl65UjxPpLeaUsI9nE3IxVbHzzV42jrRb6bhD0TxaeBXLaZAy6RBFpEK9rXYDo2xMMQK+R01JFdnas/GXWKz6WvJQYEGzYVV1VDz3Gl422ag1rUrT/XWOT6akTTkTxOZfpp7ZYtFajGV+WDGM/vSaTViWuyWee8zT6rXcrNf4pRdprCmZx34icIVlgjL0Y4yNZT1o7vHK3LQAE3oyxqGULXxmeU1FOZZXlTV0kNagZxPk0p0qT/rJpxaeSO2PGGpa5RP1rsblK6ub0pxAOT9RrlSe61FgWlMmu+yckLHSnmFCDDTxz4xUgTM8AwtSRgAPHGIiUWWGt20pd/VdS1NMq1PptCL6khBRLZ7LQstXplFZU3iLeJ1viFIa5ZTDX3bVkW1+N9Jb8aWGW7jJ1ZUrS/nUUZy1gVn1WhEudKzXSSDoyhFOpSUtLSsWl+daDADuGrFUv1SLEF100+kKyvwF8lmtvppYaXVsnG1W5aopbTynH4lGmGrn94AVeUFOIoMAE6z48zxDB9T1Alnqury/qGusP8AsNSyrrb80a+zP+0uhve4VjUie506RVUjFkVeIyN8zIhAj1Ax6JqdEXFjW6c6T1BTKXDwGcARqB0KVEKsG5QV1Zsd7ALdRz83kq4YfwtyrKiZzOOvMXQah4dDo9ONObGW1mpqq0ZprKW2RKtLSqvzFNNfFkcMh8YZItj1gTiAiKTFSHxytMnjCBkLOMbqY6xAsX7qEzKDiVtP6XQWhqPTNK8r9K9PQLbpEnuUrC62tp7rSk8ZxgEwIVEfTVWC/wDx7ROR6Bq0ZdP65VFfXCeRmAStodBSSdBQw9hXk6KkFPTaLIfTKgE9L0wPtNNgU1LABOMKKBXTfejHTaSryau2l6adTF0KcrPTgLicU138RkwhDG/VeXkxX4+GJ+qeP4itCnAice/qAEziYfv7gWY6WJEmmHdd4uK4pTOvsiaa7OtsqR69B6rcp9M9Eoiv/jFYo1HpSrbrtLpjR6ilzf7jRZTXVWFSDMTAmNsQiFFnjSCpJwSdzg04mBUJwsvPE3HVKpT/ALF3tzW2s4nFK6m2nzxSRE487Hr42L5XeuwueQK1HjwnjE8S558XC5assCvxd+5yPIsZjMzMZirtiYxK+woMLeWVuAqsbIelcsYre3nt9VdE0GirjJp1FmvWyV6nRaNXGt1V1ivp0TW6LUAanQVz3emi21vF1lTS31Shbl9QssbT26u1W1yJK3qZuM8tTMbeFiOHnq1L2acUr4icTCjUverlhqGOlZ9LqK6PHLlDXDV4XxExPiETMbiSqK8PGWCzNZ5VC9omTPGAXBDxSHgGIwOcjCsBOS5VYKxDVBX0yd1pLWIWqhMKchRA1bPXczRcKFjfWqr94yirRVVUah7db69eH0+n1rWP6WbifThlratPNZbrBptQ3jpRq6tN6bpRpdPTwCXXu1yutZtuqWLrNHxZ6r4hTGsZuNt9oPN5b4gnlr5mzlLk08X3ljisw1GIgiFeWRjmIc8VAVWfDl41eCM1uzdlgYkAyW5YSNiZ6iVTjOM4xk7rHaJ5XU9qsuZ1XVA8KgK17MXqWu9tyoAP3u12p1WsbSek00RdHo1X2yR/Lp69GtqLqD/zIRrnSuta1sVpp8JKdSPdluMFnk1ldRCohQCnxn4WoiOEV3x8ENnt1gZTEqE8Zw5UStABY6gMVA8haBZ5Rw5vxWnLMyywYVe4AFOMQpOXLZupmIs75Iscd8OmEP3qAXTGAEi/RdEb07yWEfay+4U1aeoU0lvi+mD0JXWi4mITNV8pzE9Qd/BZXXhDxDcCbNS6ADGpTxZIHuycqU+f92CxWS0sOcPN1TSJwDAR3LFnPHBE5S7jxDvxqr4j5ZFS4XL2N8CndlykhAwTmOUrfEKRcqz9jx4ADT5ZAnGKOnSOCIU4kCIIV4wvzamk11BZY5ScvLqlnLv6ncDCGNCubJbl9Q47WN2dYs4/IMMMP+fPRfvkch3MFZ5cEJ6j/Yt6/YAZjNiW4aIGZ0rUioQfEl1IDJLOlB6dCABkYAK/bwEMHUQdgjG3IwbAGGAcjYsAMQzVXMmm8Pi04fMX6yDKqzWiZxg8ge5yOSYDBx4zI8hY4X9eUKggEYzLviPPlckqFclCVhHNQ3CZBH98LQPJY0WwzLRErMFdYcOUiFmVwcowjIrQKCjVzn0R2x2b6GclcTEJgAmO+MCwxh8eHTV5mMDHR+eoPdiRnPF8YAYhmAmQZzMzGbMz0DMrxGYjfFG5ILDhWJnmAC29lWM8IiBQ3RhCZw0EPKZGQWWeVgcvFqawmiosKlRURBGBL1jiR3BXP1AaBZ1yPEziASoEJ64ThsRv1Bt/Z+u+Xx5fGU8MHHlGMH/1/wDpV/5fKJ+rcp84ucHM7i8+Q/QZ4Ucs2Z5/0vGLxzG+xifHPwgnzh5Trn85/wAPP4z+xzy+OPwi/u37jhFzyhxEzHznuPBiHjgfRixsb//EADIRAAIBAQQHCAMBAAMBAAAAAAABEQIQEiHwIDAxQVFhcUCBkaGxwdHhAxPxUBQiMkL/2gAIAQMBAT8B1c6c6+dXJJPb47HFj1if+otZPYZHUTZOlPanrJ7dHZo1kk9pjtkauewx/kLTTJ1Ek6pf4Uauewx/iR/nSSSST2me3SSSSSTZOhJOseunRjsCskkkmyCNTItGNKBLWR2F6mCCLZWpkn/OgSI0LpA9TP8AmpCWlUSXxVamSf8AKVIlpxJFuP0LEemn/kpFK0VbJA6C4XVZGoWqjsr1NFJJJNkCQ7JJJZLE7Ex6hamdU9W9QhIYyRDqJ1Ei1VLHZGlHZHqErHozrI0XYimovDdk9gS7BTY7FrVa9NE6iO1IpGN2Uqx6tWMjTVi1D7EtOm12J2PVrQjQegtRGti16EWsZSOx69C03oJah2wRpq2CBqxoStdqtdtOsQidCNJWLSZEipIIIIItRSrU7Gi6O2CBoYtCBCII1SWuRNiIIIbfIVOjGhdKdBMbtkm1oa0ItnVpCH2BWP8AIs4eom85RjoXtGljp0o0twx6UCQ1Y9KLZ0YsekrEy/lYv4R5eb8X7CjOJJAqTGYjvWyPYjlnpiYaKpEiC6XbbxOjTBUkNWMVsWTr41Fx5z6WRlipnZ4ioSIWcTAwJLxeszn5GOxMkSq/p1JGxsnSpsggqQiLZ04I0YGLRggukrd4v4z0J4Z+B05+xLh45yxUreUpWTZJJfHU7JGOxCMXyP1ZfwXYGSYEaM2J2wXRq1PTTEK12JaEMzngh1kLf8LzKV19EQs8RPw2Tu9hZSl/ROfXeTOYtZeGOy8XtBCP19T/AI/Nn64GYjIHoQRouUNzoLQgggSIsgiySlS/flvMPr5dieHf9bCM5z75zv7i7378/RVU9/h9cOAmo458x0z3ZhcxPly8Nn2OlVd2du8z0Jl5xGx1ePAU7ytk2SSOyCBCEVDRnAhsqw+SRvOYNv8AfmyHnH0LxeHbJOdluBhoySSSY2RZeL8ejJz0M5+heHTaX+ue4Vc+jb9s4H/16tbiqifRvPmRn0Je7vb8xfzl0HEbkS55Ik2uC9uHU5JJsbgm2LEKyolvZs48enyYbDOcsgdZc4kLlnrPqXsoTnOPkN+PPH79R05xFTnEu5jAelBBFkEGBJNiyxRnD5E8BSXM8egpjzw+RQub8o67R8h7Mc8iml7dxS7qKWoEOvPAvZ5F7hBffj6F2UTCKkto8UIggkixLQQipz0W18eXTi+428l6/HcXYJHj8fOcOuzZzY6GxUERtxznbhxHVOc54Cz/AAu8PvPTuIR5c9g6hUMiC6XX/S6ume8aS/n2R354DJIIn34IeB+Nk79qEiMCmnuIXf4l2VK3F/x2dxTgs4n6Zx3F/cPHHy3DqEOprAU9xTBVg87D9fAq9C/JTswOQ1GJMiIGiGJEaCK6ozs553ip+la0yM5z73c52jEVp1dM5jFvb0u5zPyJZzn3qe5fzvzzEs/fwoKfxrOGX4Hl0+/kYqV77vRFP23wXyxU4+iz5le0q2ip3+A6Z+PgppbLlXtiKVPgxn46fNCoRHAomS443cy73lF4d2jrw3jr7uu3wFXl7B1FScHXuLohuXwFThAqOO3eU1H/AKWHgJCRVz8TzQoKhEWRpUqXPh8/FkjZXshb/TeXbGJ+Hr9Z3jY88l9kT045/pcMcwN5j4g2/X2Rn+7RbH4eIl45yvHhD2x3DpgdJAlJdhddvTgVNDcyNz88CWhvEhGL+F8lN5888Rrj3Iqrytuehe+5EiqopT+xLgXI27RsuOZLq+R/kwFS9vEpeI+RM9SfEvbmRFlJA2btKvHCybGynjmLGbfe29LkkkmxIukY+ZQ39fPEal8xSfrWBuxxHP0/oX/nywsTsUZ3F0umCH+dzCw57+4a8c7CmmBU2QUTv8EXVM+W4rrnAwHWx4LAWJVgih8Sp4l06lSLw8SkvaSsixiY1Oc9fARIsRUjKsSLGrETYtvcUuxFAxoWwgVJBdW0bLzsRc/ps3jEucFPiNpLAqqeeBW+A8RUkMpI4Ce6yRlI8BOybI1LwEhoYuHjnkiSoRn6sggaN9kCVkEjIKceQvxkQxtZ+CpT7GzO0uzbeXiXEtg6SFvwKqnuL7j1LslSgpKkJtE4iqLtisVidkWToKybd9jIFnvPYSkgggSzny8SBojGyMRrEujR+sdAmvYf5MobdmJKGYWNTzP1ohbB1qk/Y9vkX22VVP2KXCKnIx1G0gbN1kyJ2Xi9YnprQYtCvaIeegjDOYGIznO3aOP6Pabz8kFOz5zB652DkecuxDsxGYHD3g3CjPE/7R8cDHuOv2OCkx7x7BbBz3D2WIqKbKR2MQxW/wD/xAA6EQACAQEEBwgCAQMEAQUAAAAAARECECEx8BIgQVFhcaEDE4GRscHR4TDxIjJAUgRCYnIUkqKywtL/2gAIAQIBAT8BskknUiyDRFSaOrGpGpFk2TZBFj1J1X2Y6Br+xu1oI1FaydSBqzG2RjtVkjqspHqTrQOn+wlE2RqXCEiCNSCLXbJJOrCtdtwxMdj/AAOkj83Oc8p9CEd2LsoIFJosgRpGkTZBNkl7sdWrBBBBBBBFskjMCl2OyCLJ1GNfmuIIL7EaJBFkEEEEEodWrGpJJJP4HZpWIgwsVs2ukdP5I1Isgvskkk0jTJIIItn+wm2LJGMWviOj8UolGkaRIrLyCLb7IIIsn+2m2SSLGiLJtkdMjX4NBEECFZFkEWVVGIlbJP8AczbIiCbZ1XSRrwJWTrVMxErZ/tJ/DNk2xatSBrWVisepNjEv7SCP7CLh+w/gWrIx0ka+kRNiVrYl/YQQaJBBBFsEEfj2CFhnmRrJjGhrUVkEWsbF+KCCDRNE0TRIsn8TRH4UySYKmSMWomMga/AhjFY9ZISIsgjUbJJJI/E1+PFchDWtNj1XYrHa9ZCVsajY2TqSaW8TQ6R3a7Q9abV9En7X4pFqK1a8CWu2N6kklC0juUd0VUtDqbJ12vwJ2Y2RrTbFjGJD1HqpEa7qHUTZJJJJpReKqbXQv0V06IidZr+yTIJsb1G9dIWvUyp2zY7IEjTF2zO/Y+0YxvWmxr8Uk6kjYrdLWWoxCWu2V1aklNQylGIqWd2d2d2OgiCpCtQ1axr8ME/hgnUYh6lP4KmVVCYrKjs6CBIpptm2qiSq4xIEiYJsmyBrXkk0hYkDVs2zarGLVp12yp2U6iRBTT+CqmbIJGxMdisaHrpk6jp1n+JazYztGSU2QaMCEhL8PaKxiFarWP8ABN+pVTbJP4lruztWISsbkgRT+LtVZttkkpZNjGPXQhWumyBajsnUVkk6jKioQhjQhFP4u1sqskbJJEIY0PVZAkLVix6j11ZItSuyCmxoSEyn8XajKnYh20isZV+BCs0jSJ1mSSTYrExuxalYhIjURT+LtHeM0bZExWK2r8CJgdRJJpEkjsZUydWRWySTZXbJIybxVCqKKp/A2V1WSOyBK1Wux62CHVbJJOo6itCQiB0kEEEEWpkjIFa2Uq2mqBOdftaxk6yFqMjWXZvP0ONrz1HBKsSNF4bbU7K0Ks9LFY6fwo7RFI7ZKmKqymqBVrUdUFXaDGQK12Ip1GQMg0Tu8u5fL6HXovJe45zciLGxUypT8GbMSedsWVVDqNLOw7y72F2gmK80TR1ahMkd4rnZI1aymoVmkaY6ybWOyRskpELVdWfrZ4+RB15fPxJVXGPkvd7FmB9s3wO8O8b+vf7NIkdmc/o9M5ixWVED0SFsGn+ymnwKTR1IsYySRMrRpCGh0kjEylkkk2uoTGSRd6DsSKRWTvFXOfQ0Xt8lj5+y8xrf5K/9+hpx9k/5eXyVdo1hgVNzf42aJoyJEHdioRs47TRzcJE2OCou2KXx3j7aPhL3fwaU5vEaOf0J1fv5FXvu5/OrBBVSRYxnZsbsqpkagVlIiRlTKhEiL2VXCvNEWdpKLzu9r8XtzwRpPZd1fTPgV1Rdd5S/hZiSXGZjE0WuDxjFpdb/AEGrsPFwvvld1Gsz5bMyaLXDrl7x+vgZ4ik0H47t+/gUoSs0JNC7GyCBoaNON3iP/UPdT5D7Sdy5CXiKOQlzHVnAp6ehOXNukaQ2NDps0ZNFopZNjY1bpGkaQ7ZsVHhyvYuxSxKqkl7cdhf9/C935CW/4Gr0+H3jhcTF/wC9+GfhZ+lv4vmaWLw2Z+SihPDCcfad+/Eqpae7jwXphzkpri//ACwXLa/+OYavKqdk4X4bXE+G7iKt034ThN8rgthO+6V558iIU71HLkJSU0eSxY9HZidnTeaI0hLwNEVsjGMTKajH7w+/AuWXmPMpc8OChLpf1NFFNHF+f7FS1t818RY4z9miOgpRBA6EaGcfvqd2d0+RoVkVbuvyaL3P1FQ+Jo8/I7t5j5O7eWhdk8/R3WYO6XHxu9DQp3F3ImS87sfZt+q3Z49EaO/nnA2QvP3+3E7Crfe/ReN5ob9Hl9tlXZ6N3jC9/wDFcr6nwuJ/jLl7k9vz4+xR2kK/nSv1v2EvHx+fLexql3vwpp6YbirD1e/n8CnSvTb4Rdwz1IWjxZowYKduGz2F2d0sVCaNFo0RCUmhbJIxjEQqccdz2cX7Ivd+f1ywM5x9ic3+kio4vPI091/N5RNT35/6x1QqX+yM7H4MVPljdd0wfQVSn9fodWbvk0szeKyLZsYhIZJeQxUouGvmB6X6/l0/j8Dp/ljsieY4SzPS804Xl4ThO0cJ38nO3d/H0HL4LjjPBYX9Cm7+q6CmJlX+v/b68CqtRH+7y8+X0VrSfRRu6Fac++6Ng88Psp7O6cPVjo8X7/Rob5bd9x3anbdv2s04qjqaMs7NtXPPLgK6r0KjScjqIm8mxskmxjKVo/8AZ/0rd/y5/wCK8TC/F+n/AOnzu5neSaIrvDb7Ln1/643vgs+eZFWlh5sqrkxwu5e+3yc7immFmPPPiVZX3sRprbj08FniaVTwODh8MRUx+x1revMmcL+WHmaWdhpL9X58DS3X58Clt/v9krl889pSiBs0o6RvbfRCv+Ttabt95TTdGD2+/mNjqv8ADPMrrnC/fsic4H8tqlRG7xv2dRVulw8XhfszyndgLs2uWM8fGfhFd72c923zZ/5EKIvzed23f64viU3Xb9u3O7cU0T68RteQqVVf4DjZe9/0doquedh2d9PL1F2z2lHqd2kVq+XecSl6VwlHyVJkqCmo0kNkkkkjKKJ8Or2L54FVfXF/HDOFtLS8crPyOqM5zzu085w5FJUUXZznq685j4HVnOfahb8567kTOfZXvxhj7XOP3HG+C7nz+rugvBch1v4x9XBU/LBL/J/C3bXjcV1wrvF/Ht8nZylxzcURG4rrm7z3cnngKuHf5r32+xXWkadEb5vhFcNp+KFzO2r6OSrtXM9DTe27zu5naaKXo+HM7ymZv4LHMjrnFR6/R2ioFp9py3/7Rdm8Jnekv4+Y+zw2Xzde7imnxe7dzKWpe8ndyb9jTXLPv0HMXYIpULfO32ZVVDn9Dr3YbP2Vdngf01S/NFTHUUcPIS8GOSgqE7GySbJsqqhaKx/3fHhg7IKV5Z9cDs8dJ7P/AJbM+yNIvKbhq7j6c+PDfxVyRHTq/hGlv8sf36HeZzniSsyLOWeXpnoTz5/rDjPDckN3rz8h1X8sfifVrkts0r+Mu6+fgprnC/leU9pGIn18XmR1aPDncKuXdFyu57/D4KKHG+cXvfEVLUcG1d6ipaw5tbKhpVL22Ln9lNLSiPHeKp8ESljt2v2WxFa7NcPXy9xVJ/07r38v0Key39cJ3xt8TQ+ksCprB+S9yimLvP6K6kvZFTWLu4b+L3neThgU0neJKOu403HpNz/RT2UvMSOpYbthWrrsCnc8BKORG7DOBo7UaU2VXElNJt1uzuv8V4bfi1CpfmV3XLZjzf1AhCu9vnjw/Q6s5ztJ3Gh/GCF8miaJMFVRpmld045mDtEo3va37bimqFuWzO0bU59oO/d66epEu67z83iUKnhP+VOP/uKv6/J3rcN3YlVN+c9LKtJOf0xdo2jvCXVds8in/SqJf8nu/wBvi+AqksFC3L1b4lVclVbj1L1jd7knaxF3i3fjm4VbjR67Tsuzi9jmbhdmsfIV9V+GcwVXPmU31XnaLd5FCaW/gad5yKKtg6BSmVGgJMv1GInGxEQUuPHP1/6irESKnBV2mc5hIoKXBI0xVDKiM59/IznZ0KnKXMrpvsqR2iEhVIf9XQ0h1Dbm7r6ireF7FS37mghIqykLtOUbpjoL+Wzx+2UqSqrhpPYdpf8A8Sml1NTg+qRRQuP2js1vwFd4DrWIqkV3IT3lVO2yBFQnJUhXkWT+Gm9wOrOcyKopG5v8s8WReUDxXUT+vn48yTSznMDeXnO0TFGiIdQ6pM5yxMgRJXdhf6dbx9rd1b9C905QqHOX1KHGD5/Q/wCSu6YIVUE9Cc4mjUr8I24HeVPHcU1+G5kvZe/K4poTxwR3dKfoKvRKXKgrmSipDpTErh0bvI0hodjENWN2RqMgi1XU8Xd4bfMQhMefA9yqqLs8f0T0x8cDSJyx1Zz18hsTz8l2jnPgZjdnME/xKXd7Z9jSuz0W1+gm/jj+vg7yP3noU1job28c736C7JfspSnYXMaXPoQ3s5C8Rzz6/Jdz6Cqa/wCPud8yX/U/AXZuvh6nc0zEeIuzVKvKaEuWJUpZQoYhUGAqiDaOCIHSM0TRsa1Fa9V6nZ4cdkmeMlOHD/7eN+HQcl+cz5iGenvxzMYXCnZ09vYWDP8AadnJXj8fd55xt+/HMlMZgWOcfAzx6lWcr3KemfEu+d/SS7j6/As/RfneX3+0/o2/I524e3ifwnZO2d+cC7bj4nKfYUyVYX+Jd4CxHiKPEpxOY4KSqyoViGIdv//EAEQQAAEDAQUEBQkHAgQHAQAAAAEAAhEhAxIxQVEQImFxEyAygZEEIzBCobHB0fAzQFJicoLhFJIkQ1OiNFCTssLS8XP/2gAIAQEABj8CBvB0ZOAW8wDlRZqQ+DxCmRyWHo9NuC5feK/c6nwWOzI94259TQ9WW+Cr18Ntdvw6kzsHpK/cJuUPEfNdnwquw49yqwjjGzLVfRURd/VRVcO5ZlUGyngepVU24rDbX0NOoUSp+8A+T+UNsX/htWU8R8kbVr7F4xNxw9xhXnWZAOd2Qo3T3BRAriIXYB5rox5sRdNyGzzjFUO9JqVVo7lmFisSsVWqoe4rDqV9Njs4Irhtpsj0Eelo4Xl2m+KBbbD9hP8ACHSzbH89334+1HzQk51ooBDe5fJYlYrFZKoWCwWip96K4ld6jr6+l3vFTsuiJOEmFRYfDZQeCoSO5dv2LtqrvYqAn77K4oqOvioPj6Klg89ycXWVwM7ReQFv+UNA/KC75Ju8XAGs091U64G3i6Ru1Ag0k8/Ypm93rfWHitFRdpVJI4UVG9+P3/HZxOydlfTTetD+6US4+Kx6larBA6ImMf8Ak1Ng9PjsxhUcsf8AlfP0sbM+pT/lp4FDmfuHBBrO1mfusbKbSo+49ynuKnKfhGyqpl6HDqU+7z9QsZ/hRsCx9PXbjsOyNVx9HH3jHbRNteiJs31EVpryOS7Jpw+6cDs4/eo69VEoquyi368F52zv2bBdbZs3B36q75TaClHWNkDzNdB3VTrJlg10t7WLqnKpN73YIN8jf0Jb9re3xHvBPMZq7atiZuOycBmOH3GmVQpCnudt4bdfQSp+41KjbK4It9iqnWF6mJp8VW0MjMNapFuW9ylppXzzPiD/ACEXeWT5Sey2+d0ctOKJbrQD7jw2R4HbGyOvQKPuUbaqvhsFaqYQcyAcwdJQdZxMSRpOyoV5u4cxi08wrsNuO7N03u7URx24fdDLoIwGqNa5InKs/Xf4LgsMp7tepA8fuUTVTsmFVaoFcvFUxylVQDXlvIwRmQOZVbS9wOCF2J1VbUtZo3d9uKc44urOak7Dl6ae7qV8dt55l8RPCIReTLnVcTmVE0V2N2L/AEnq3ZiZ0mmt6ioPuhUnaAJlYcwpM+CBbLSNQtNdh1XxW85N6B9I3qEV+tFiqYKuCvZbK/cY6nFc10c7/Zml2MPH83fj6WvoLo2U71St1SVJ71LS4DANaqyjKgKqB1UN9qnZC1VHQt855KJlR1nAYxRU2argiDlgjwKk1uqEENVXqxc8/enpr2Wl347K+G2mPpyM9s+xR7VQTqE2RBJkrcMN1UXrxyJURX0FFrxRBBjVXkIxKM9wVdoaMVVEsMHNbxko57XI8tkI/eipVfBXfVblxU1cArzBJyKIfU5KRQ5hT7VPoc5U4J3CqACNJGqp4LCvoXckQdNgRHUDsL2Q1GPLUc/uxQUDJSMXYkqvii475BuwtxoH5Rgt3vzVM/RcQq0RrFU8gGB8VE1OKriVPtVEOueS7lCCu5SepdJgHPiMPkeaqp+5nZKdHZOa4DshEYPV0xoZUNpGLVRD0RWvJXBUxgiGjfzUO7WawUIwgh6CSoJ7k58EsYRfjinHyYFtjS6HY8epOmPz+s+aiN5UVV7vuDlKqVTwWF4q82ZGSD7rg71kWNiRqrz66KcfRwO5XxIdmqnvVGzxWCz5I6oT6I8KkoMwcBEag68fQTmrtrn2HcfrEadWfRlDTZxhQVevmG/FdrkVci8fWJ1RwdwRoKYAeijNToiTiV+U+xHNarjqvmsFr15X6QoImsniuWwwKDE7MNl2PntdZ2meB4o8OrI6lesQipd3L3KPao9i00CAqXOw+KEzGdQqLgfQQFEK6MfV+SvwWHjktHDNRM7IWC7+twATyOS4Yp3FTsDWC9aWkPtiPUYOy3m7E/wuisW9HZEC/q4jXvmNs5qYy/3a/Xj1ZCj1tOpI9BCKkJoFddh1KvTTQKV5u1i1bgDgg207edEYyVRPFXXde85AI5uhVUCmiM1LfaNm72s1jzQ6/FE9yLu5XnUBzNFOWp3R3XonuBXmxN7E1jxNwL/LA5ElVcx3c4e4/BdkftPzQynWijObvfhH1Tipy6kFXmPuuyXQ2pHSYA6qvpJRY7A4L37DRUrzUwiX4DDVOuwG+qc1XDGqr4rVvUgKuOwHTFAzRTAMIEeCaR6wj4ozn9e9RMTI8F7OvGi5KHOun1W5nkPjhxTWtrODbPfcf3dgd16NVNzo3dzn973Gn7R3qYE6udLvigXARlvBYz+k0WJHgfghaDymNbO0JBnuBBCobzvwhrj7Tcb71w7N38vy4LHa027+jsTpigLCyLGj/Md2j3IOgkhT0UP1Cu2gv2Qwdmpb4dSnVvNrwVRC5qdFezz2yEIqM0bLGaFeaEXUyXCCI5qNMii44krBQguSj8S5q0c+kUwWIGkhAPu1wLaSmuybR/19URiilReA4nBXog9UvdusGLjQeKlloC3XH/53ovbaBwGLpp4mncJPBXg4eS2f+ta7o/aDvOPO5yKcLJjrVwPnLa3pZz+jF54OwzOS85bl89r1Z8PYJgZALARy+cqG0aPVHxwnmVUoE0HFdkkfpu/90KbhnhDlhDdcfrwV+75vXPn/AB8epPRdGY7b1Dt53rLzFlcHFXOjniJUW1mpabhWvo5W+dgAPNflV8YuxCH4s1DjGkIWgMvGJAr/AAjTmPepO5Z6ux7gjTHBXj2jlopzR6PtD3K8VhuqN5vBNkxUb38KXDiOYV3XBcVEoi9QVXBUqpcYTRBLn/ZsHadyHvJgDMrzUNYaC0AvSdLPDpHaupZNxl0LpDPlNtk97r1mzlkTrcb/AGBQ90/qqO6zBu/utC/kr1k3pH4f1Npv9zMJ43blk3MnBdITftB/mHeI/RkDxAHABdGKBvqjL6z1PFUKmVUxz+ezQqp2cTjtwMCpMZJ4s/JCbTK0tGmmlF5wWjs4iFNpuN1zUtbfdFS/X+VuvbJxawU8T8lvsnjn4qDZNV6xLm8LxIUYxk75rzg6M8fn6LgmzjtwWnFRhxyQ5q8Pr/6r5wGY0Q6GtqKcO7imuDTE1+PcrxZP4YqpIocTxVawiBgVeE8uaE0u5KnZ5ojF2c/VFJ3RxUsa5zcqU8TA96nD2pzA6++zo5uhV2yyMF+QOg/E72NzM7qutm28qJuizFSXYwXdlmpwgVhF1q1hc77aLzi78kC7FnoybudoTvKbcsdakR0TWzdH4RlGp9bkGhAmzEikA+qrls/K87ycTMHJ0SSOAgayhFmRFJN1v88hkoDcePhkiHCNc0JBF7CRC4qBRblD+EbMNmK7S+0G9BLWsGIRAfwvQO9S62OF3u0QB8ocd0e/BSTePFTds3OOrF9lZcrqlkWbhmJ8F2WWo/tPyXnrN1gdXDd/uEhBzHmMiDIVd4Hgvy6LT0GCumeYQkjboVvwBxW66W6KDRb3YOK6QMlwF0acCt6oCvh26MkZbDtUbncMUDHjRR62WvgFEOcdAFDLINHE/KV560hubLP/ANjJ9idassgbT1b28Zy7Uohxl1m5zH2kYlv4R8e5PtO1caXAakCg7yrFpfhZ3bVwpJO843sqzMGeKi6bDyNtA1u69/h9mzgN52oQtIawMBAOAa04xkJzOJzVo4TZNdQHB1MxpPGudFudmau/n3qOxxz/AITjd+0y+LuCuh9BUU1+qIGILqidOWSJJiR4rmI5bIwYMSt0120qFoolc1w9BzwvUBT39N0N4fZeTbjeZLpM8QGr/E2ZfaD/AFHueDylbtjdGNC4YcZV1vlH7Q++fDeKp0kY1sX/ACauzaf9N/yUG0DTo7cP+6OtDmhw0KJaHWZ/KaeBU2XlHiD8FS0Y8cZXnLMH9H8q7aWJjOYj2rdY4fXs71ec5wLuWXyUX3magU9iu9IdcWqrwObqqhnhvFRU8Gt/lb7Hxo4x7GqBYt76qRufpVBskndFXHgmWzpsnT0jLLQZA/mip0NAnG1tLtneLq1q+pA1OgHgqM/pWH1ngOfGt3ss/cTyQdv+UM/HaPLbOmgGI5NDTkVvNs7x0nHvKvutC5rd6ysW0a0/iPHIHLRNc5xJyac0JFTVjfr2Kc/qVefieyxqEUOZ1RvNLjwWO85Qg71kXHNUxUFV2Y7K+gPQ/Zihtzh+0Znj2RxNELjHvJ03nHm4+/AcFQs8nH/Vf8GD2qbTyq1f+UXWj/aAmssmWnlnlT6MYX058tYEauCb/V+WGzH+h5NueLhj4Hmv8TZtBPr29pPvI9yug+Tkcrx8QJ9qmytmts8wXOu+D6KIu3tPN+x90Hux4rzdm54FSZZh45cUQHXnD1Wb/wD2XkGiLxwY43XeDmtWhGIPWwXZC7IR3RXFdkbe0u0DqsEwMs+ktHHsTFPxV0/hC5ZirmgkGYGZg3cPjwV42hDbsHAVP1knWL4deBlhzbnTRXLNhdabs0owHN3/AK4nSKoWj6vq287tV0H1TFG+PNAy1jp7XLA98gaLztIV5jZIx+aLR281MDQQhJxzHBQcDmr0xxzK1PxUOJLjUwpEwNdVdpzUZq449yjI4Ljtn0Lm3rvkzP8AiH/i/IDp+I9y3WxHYbgGgYcO4/2lTaG8T4fz304BTkMVTSY+oocMr2cMBktY02/lDu3HuLvVaMm6Vhf4i3LGf6Pk+5/c/tHjEBblhZtP4rt939zpKNo+AGCr3YAez2IB9r/R+Su7DW/8Ra8Q0Aus2HIxePei+x8itLKaC0e2657jgJdNq4nkg3yu9YNd9m11n0rff0QP/wCgeeOSDj5e6yZT7Togzlg32GiLekbaM/NN3xcLqnp7MXaVtAYnLH2L7ZkfqC3De5YeKF0OLHOuNtA2Wk/L83Z4roLNr7e2zbZgkAHMuwjxV2way1fmxhcbon1iQ0N4A1PJB/RWdx34bWY/2x7Uf6izfYAf5jhNn/e2f90K617ZNQJrHLY5rXTcN1/A6c+CunAkBkYkn2BOAndN0kiPDXmKJllZz520DXECYEE4GmWaFkwmxtABvNxHwQTrUYvaG1NBdk/FOs7MXiyL5NAJ96840FhbFKe/JOsLVl59sZ6cumRk0k13csKYBG7AaTeJ1dmU03hMY5D+SgwN3hmr0gI2YrOcVVTxhQBQK8acFDRLtVUzwXL3reco/Fjsl1UHR3otPiq+PUmOvdabpdjaZMbm4/DU4JlLtlZ/ZWeH7nfm92krd8SqklXuz5PZSS6e05uM/lZ7Xcluy20fvvJ9UHAfqjLmcZiBhx2VTLMOc2xYb8t7TiNAafvfDG4CTKdaAMsB6762to7m7dk954L+rtCGW3+VZkT0TT/5uHbd+0UC/pvIWi2t8OlYCRP5W1k8Zuq+/wD4ql6Gf1HlH7i/zdjwFI0TXeVl27WS82zvA3bMD9LHK/ZvbaNpFnatBb3XLvuKZZ2dkDbP7FkyBhiS71WjN3cATRODnNBtfNNuh1C8xidBNacldsmggRZ2NnkTgJ/K3E8k8WNp0jsba2zc7M/ADACAKKP8x5v2pOJcdfcjd3eWq6GzYHAfbEmAAcvzclecIBxePjmrxdHFWjLLfir2NFZznCvNWFq2WzD2fyFR6a5pqxwI+PsV+zqcgcF5ygOdaKdcHK8SZyGKq2OOa1zR3vNZOOCuyXHMAU8U3AclJ3nHJOOZwW7QesUYpKkYBSReJFCry3aNyTTjxQc4UyKlQe5G7/avwuVVxWEeg4I2z/sp8wzgPXP/AIquGWyGfaWhuWfM5/tElWXklkPtKXdLNuJV1uHHHb0Fn6kG3ca3ZwbxefBgqZMKgojLTdsT4u+Tfev6bycG5/mFvzwj6qpJIkQbNjnAH9RoXf7W8FdbZBrdBIHvW4+0s/02jvcZCfadNeYzeLbRg8AWXceSL/KG/wCIta2jhUcG8Gt075leT1gNcbRx0DW/yultmf4JgvWFmaXvzu5+q3SpU0a29eMUW6b3KqtCe2XGTywXlAYx9pJbL2iRMR39yrTmjdcPMs3G/mdie4KG59o8eKsxQwSICJsoBm85uTp+sUc+GiuhtdVWAt6oPrO+S3d1RZjKrkZE81DssAMFddpgEG+KIPc1S+nBbvZUkosOGqj+0FRNFdLezkhGBUPwWrVI7KvsPNRmtQuHoXWTaCjXHi49nwq7wV0UGA5bX21pSy8nbjxdU98XR3q38qtRFpauuNb+FjMvH3bS4C9aUFk3Vxw+tJKuTeeZdaP/ABPOJ+XCFRCxmGetCuMF1vUsrPJ7xe5Nrs6Ozi95QRYydD2vYgMTheOnDRXRAZkFUAlWjA7tUagyzAZu4xoqtF4eu3+UYM4OqNFV3csdl5tNRkVIy2FuSvPN9w9XLvW62GDILgo8VvU0VTAW4ObiujA5uzV8kcVRAxByW+KDBHipcob4LXgoW7horpWmirVSpCnrU7Zo359ysm5Xp8Adu9hit77PyefKLcfitTVjf20VmzMDe5mp9uwRVzqN+uCvTLbDdZxee0f2ig5lR4q6MVGzjtaZww2WA/CS5DawtyKa6FCDu7ZQowrokqRnigZosFPfAWAjRdnvWK7IcclhdTb+BRiVvCiwqFeURQqB3LeGOSvAkLGqk4qiqoWKj0Bf3N5fymnQ++m15xMQ0cXUTbI1faPb0p1JN53sEKdj7c4Aeb5D5lAYkVdzNTsZrMlT4dSUTnkuKBGWalarRVVNgc3eOq45lAQoojddzRgT8FCwwyVAicLuahxyWMaFbpvHVC8ZAUg4YbIO0kbJae5VGwKFCjZI69MTTbGKomt9Wx3/AN57PgKqz4XneyPjsgYu3R3prRRvwC/UalQMAEDjGPfsxjmiBh9fR8FXDZJKrjor3FO10XLNe5R8VRdqMyFX2oG6KLCFquzyWawlRip7PBSSr5HJCaBXbvejIXA1WC4o7D7VRXtkdSfQjb8tjp7frc5+u5D9FPFcU3vjmhyMKnaylfLH65IXezPtVF9Yrd2Cez8fr+Fu90J+qGiKMYcFndz/AJXFVnj9BUVVTBV71nwXFBO/lfNb2HwQwnO8jOPet2VRb3eh+FU2fmRRvKnU4qvoP//EACgQAQACAgIBAwQDAQEBAAAAAAEAESExQVFhcYGREKGx8MHR4fEgMP/aAAgBAQABPyGgLRVg+mTP0WFvoPVI/kl2wGv7BhuHnGPz+JVkt95rZUuMqjxKWyNtHu4lW24DBx5mfU/dP7U358/33HdOXESuRh4S0N2c4PpEQ/f2pg884gNWNNxFMy6Kr3leLth/xBa3KRitkqsO4bxmlk9ooD0Eocv0E54hGIwXEYML8wLFpmL+ZfLPCW19BKh5i5gXtgkWLPEYSrgH0P8AIhowPv8AL/FS5jflr8/MxcHiz8xLiDcYeZ+7/Yq8e6fxHHdekXzL/IS1rDpOfeI8y0XZs6l3ZzCNZeIhf4ZXIfaJvbMl/aK0GHuUD4nO6S3hb9o2yOYBgZ8yikSIc29GZYK4OIq2NR6InWIjKzLniGrHeZkpi6QtVlDy+gj9FTapU0j7SpPcQywYnZzPv5lzHcxKmIVLrUuXUzNMzCA5A/8AVNqyds09HzN+l1PtCEj87ijg9YMCiigzLVW9EYLzZNNd5/qUHqsmvmpR5PWp0J9/zDvZyOomzX7Yf7iI0mTuNekocTre5uVWx+GI2q9occetyueXRMFGHbG6sJMLJBtviA/giSop0E9n0m+Fe2ND+vpWkw92AKc41zKq49ZdKzncUrw/ieyCDhUZ1vqCrc3AVEyQM3nUo5mkqmVYfaWGGEMEuZltYlvGJpmPHmVMktiLKd5lmvlN9WauefRCHfkPxr2JUoN0KD5BJb+RVEotDTIsetGI5r+I3hNe9zONuLoO8By5gnDcbGxCjNmEW/PiMeRzlU8l6cwx7elP+xL+if6lR0WPn+GIrq/XcXZjlsQ3OWWu6t60Tc+MCB9Zr/6WV+miU9oQsKtiozLDB3Awc4YZXr9ow3pKDHxGyfKLSPo/NS7cajhEiS8QZN4zHINuhhvxMerOIIcblu5bbFhFx4hmV9AuIOFqyAYw8xsC2ZPprKa6Cmn8DKnUhgNl4yn2lL3BT7lzFbDl2RzUB9pdefxD/hivauyJtHzLcuUf6MO9egirQht4GbrMqFRfop9Smv8A4tFvqLcphYgVGqIUwAnoAWCz2AQL49UUG6lk0/ELUc/zMpjMJTeJyPohl6ivWfponB9BK1LxqdJnuWl8GV6HgfzDuVl1ZFgpBwIfLj5hRaX0FjhdzywDQo3u5kZXi1R/MEYMVvylvz0zynsiP9BideOgRllm2Uw+sqEVKlRlf+CvqsWgoGOadxK8BqaHLPzM2d69iLD5RajyVqc/dJ6sRMr1GeUHHLxFiLf1LOBh0IPFZlNR6mpXSeIHZXZPpAgacZcvp/MRqDpz2uvpKkdeNPb+UewCaiAqW0PDsPESJp36t4JQOmwlAhdTfq4lJgBLNsQMZJzyygmWXhwx3zvxBHidrX9faAC2dGouM5YfSIPqBKlSvoLYH0VKr/wn0MsUJTmZcqgLUTR2suneAL9WXlsdHiAo32S/EhIZU7/E1195YWOO4Jquo48y1Q7noqXfMviZczLhbb1qXw3t7cXFDFidJ9KG6plxT92Zh09oddoR3pleAUrgNt6KjRvLHc48RBUvjFrCSCAgQipUqEqVEbhSB9Rmk3qP0rEr6VH6TJBFgC/JqGi9LqOBp3KcbYoLhLJzR1MvoH3RvU2LHJBTGvoXMFU8Ey5+gjwkCKF6RjaZ7hchdyGJBfZK7Y1q5RxuLtKC5fFgmEEEVA+gY/U1gpeXlOvrn/h6LK5f6lRPoYTZF7jbbcrQiX2wVKhnUF7aIrariUROPoEse9xazi52M+YCW8w9BM3Ld0blOZ5MOQbh7nrOQ3uW3aRTuF+YBqVC2XsWFoQEIPoWR5f6LwWETx7wAallRfJ+/mLl7dEqfmUTE/smNuZdzxMpG+pSMpj6j9A2b+hgPFyhXt+HJHT5H8ZlMTXEwwzsfR+s7I2Su1+YKC3LL3mU+0ZSYcMEo35Q875fHp2xO9vMfUM7gOmCCLZxGoss+gQfULMRWIyYJi1FivaxCKxmHRXiNxV1mpVuArd/tzRrJnOv3xA1qq6/ruEFfF+cbiByZk1XrBS343LiuBmOoYZgO98wBiDW5X3jX6EiRITH2Js8ivbc1DlA97IABlW+bP4lAvbC2YVRy/KVy7i5hucXEWc7NMT3iiA5JwfCU+izOogwrIrMykOZeSjEUC/oEEn07hHUpCpiCNQggXaYJwTzGovUbl+D03OVN6e3XmeNN+IFRlFPH/evSIeVbuXD3jrvlHzhTTG7+7j8TX01zN4guUF1US7lZKDBmVo/E2NdRxCDM34iDwR+I2b28wnJqvv/AKJMYb9j7So401F93MAzx1+/MZf3iMdxeW2cE4+gFrgBaoI1meioLmUJeFMo8zf1s+hFxGCpoamgID6c24Jx6wpxGvMNN+n8kw1qLPIdv8Vca67az+M9vcV1uHHazbriOsgqx05BdBlckuFr2bYhFh9FzhshBBWfLAb/ACwRMM85lib/AJj9KMZgbiWs1Ducpwtet3X3ZR5qPxpzOmVy95YWfMc4+GJ8m5Rn5gn0HHiL6AfTS47hr5lO0OFRap/5Wpz1NEWSCjUAP/FVgAuMFY6/EKp0vwnXHcs21c/v7ib5riX81HzNq4b5BNGvzcNgmuUr610MBTnGagczgVgAdnAKIpWYkKtUljNe0K9Q1KOru5GmFLts0glgxMUxDSjWbNsOc5JUOJRxLbzBj0g4zCnWYP8AJ8HEfpBjy+lt4l8tv0e5POmRi5NfqLLB0ic7OZgK8brnr+5y6JMP7nZ8y8cz0KANzJgZXbL9LiVRUFfRVv1pH6ChjEIDEcEM9/8AmFUu1EZTY5o/fHcw965lVnL/ADxLiWn9I+hGCLNxZfC8DMBBJj3XhXVvD/EEUEssPfGZlAd5P5K9YgLoLBb9o8rd3MIeEUs7KBXoAvOo0cByGA67x5juFQe+odP1VJBQ/EFMfv7xHbEr0fRfrDFCxhn55PETOM+Ozr16lPhyfhnFzqJXLOCPDrZAp6P4lOeOZVenDK8xcSCF8kIKjLcu4I5hg+vXVA6hBDP6FfRYIZYI50c+vzEXUVpuPvRM4bsNVHOlFs9IHOw8zSuKGEhTxrY4F8xkLAPfufF/TDA+sqwdIZFtnLy3wdRjn2WIm1dJ4CzXIEbzf77RzxD7E8cRjTiVs90iqus9ypf0VfqWH6RkqVHK+eemF8Y8PDLkGVL5lDduCsY8yiNAWjNv9PMwpRydVQieKXza+JaHuZlr+Dyy17XvG4PLMG8y1nU4veYruXH2llrzKo/8g3JNErIJX0MGGIVz6BL65mKrzx/2XVLTiupX8EDlpEqLrnH8/aUq8q/XtG0+FiYxt3R/H74hi+Wl5F6Q5EM3fGQmRTVGW94TqrfbcNm9LffbwVfN/MvGMYzpxs3zTzFAlijsreXaqrlvMVpejHg1ZeZWVa8wQrjiZNxt6SlSkMR9FpyTljTOn/wXYfEbe8q8TBNqcPDM4bfD/I5LN7IUnhmHAHGooMUYCiDMnOUsu17W23dsQtXB6Az1Og8x8JdKujeIt4hfaFlEBYipUA+gMwfSaycJKAlRL1mbTCLiMMzO0bpjgl4HHMduM3RKPBHj2ljH9iEwo4wl+35lDTjlPi4zjDk4n95uBBx2iMZycNwuZHxvUyAvs0RfjeL23KrjzcAs+GYKgy/cQGa4uXml1+/ePoOX+ojI1MZzFUwsZBxG9uZSsRTP3icw/VNc7/iVQrMe2Ijylctd/v3mIMdHF/7C7uq7N+8s4iEFbVmuLr1eO2XU1oPT58dz1Q2amdVXv332iDzMtc8zLFRL8tRaeN+sMt/SIJolPFspXz1KA/8AAuJa7YDstnxfzEBvG4dScmN0PygjtZQZ6LXB6w443YfephO/u7lQSjk/5COzqJ5XE4DKLqQHlx/Mq+kq8SoPyIeF0gTU4YqgeVNV4mOsGThwR3x7McVeNQVXK6UPzE3H4MwoPx6TieCVIBpuZMSJzW3+JqeB+ZjQ6O6YZBz5lgrotz+JVQ7txNVF+89/vTNbLe/T1+fiUZRbqtavZz7uepzHvXHoq79dYlKgDtxFBl2wW8Ss5IH07/Scx8S4Sr6CENz8oqIXIDEvJuV408VEoy16L/dQOaq3hbfUvpHD/H9RiKsJ1xuPvIcswdf6YTc0lC+/piBjD94r5+eIkSWRVeGVhwz0v91PQARZF1XmYyw2XxOK2VTtE4RNcRB0X04i7M8m/vM41psfNdy7KdmviHIte2U8essb5gAuqPszxH+ELyf5Khvf2i7umCW03xDo08zLz9K+YbW7ix5jLMbhtYQJWYIcwamMYfoGDiYLZapWnqeIIuQvolrofAdxRpQabf8AEtfAH+efSWb02HEA5Zlrklw/Yb2lolnpuL1t5/8ANxlH0UlEMUQEUe0VqxT1DiXOqrbx7bhxOzFswLy5YalaUxfMaEriENc/Qf7TX5glyrEP4h+Rmgin8TF8gwFDzKQYt+foCZHDTNEBC3aoBW7aOvCGZjXHcu+kvfiXWvokCPBrAl7MpKanB7+i4qouJUS9ehWeLLFh40RCRQtv+5TRpL7TzMwWd08/aDM9QUPfiLkvn8h5gS0pwOXJfUxaTpr6n/pTMKrkJgpscxXWg2Zs68EdpGBq9vHiczNba/ibBfIwXhpXJ67lDySZy3iMfZEVMGpZ/U3MQWG/OQznNCaHQ+0KL+/typ4mISnu4Yko934XRPtFfQtTUsVZenH7Uv8Ag/vEHRMff6NH1KbQCkmaZZjIajiJwfTZNuLeYlPqZt6uW7bAa6mcOzqnXtCjaNBoquYcwaA4fBBHcP4H9QTDuMF+XmWWCW5KxNTZH6X/AOmOkq2PRbpZjXI7Gq79/wBJYHarVv29Y5pWmm/aAXEx885lXKDfv+8Snk/EO+Xe/Hn23F7gRXHEemfITg+hkXxLr7BM6l9TZJCqS7LUNw2OuJexnRGsNvPn6Ky+krEbgFOP8fA4h6kbzqq9K57uDyQcZkRU85XZ9Dv6SQs5pnjQ8R4mnmYxpcy9IouNulchaOp1xrEFQkGq4EQXYwJj/pLx7Vc38wH0S8yhm2a7Y5Bo47fHJNImXVVOPrf/AKLdLy5qZ7Ffu/3UJhTux9u6iFm9BSfG/eKIo9HH3PG4ScfN37+HPpAKbHrPGIWjnxUDQfU/eJpzZ3KxMjXVwo5LvURF+0t0Sw8cT5n8TKJuvvFlMUfAP5uIpmQbLNtjh54YABzDEvW/o1fdlJ4f2zpB4nFZ3fiA4EBh8/76wMw0U+B15urt5GSOU7/ckNzPOCgMCJqpnlBMJRE8TPzKMS23hiuCZUkyhFNh92VsOVCec5HqAN5H1TtCFKKVvz+5ljNMg35X/Ev3D5B/ZDxCn9i4Ya/8XL+rLxauCee5aM0V1VzU8iy9eK/EBbVNhlciftymRtww6VeXgPE8Yrwcnv1LKc5jg2eff9uUkYCWTYxxMb5gl36RDTrL7RFcD+Y9bowerHQqcC6twLnBA5XTLPL2mWWPqBaL94i0XXM0EXSBrNfu51G7uvhfV5qL6xCkeBZwrrsn8kwHlj+n+IT+08SmBMqJqPr9OqNvBG0acRUYnvN5fDhlU3ywYTiYWniJsPUL7aZjiB8/wjTsflLMWBr8z69SmMAeBy7OrIHhRkCW+9MxYo7wZ/LGeOYZl/6YIC1iPIN93+6le5XnvfPTJ3zGHITraeK0Hywr4do2fc37xeStxj7uPaUDS1qmIcC4/PmNZw6nK9H8+8XaYmhPFBS/ManyIcJBSAK4GXoQKGrX7dQBU9JXS7+CZpcGu5R+T8XGVQ8D9taelR1CyqgHjUNKaft+s8Jx3+heauG6msUs5gunkjeVHnzBq/pUxlL9mVNP0qualhMCpZBxKszBVyMMuIXz2HzFzhr+cCc5KH0lKGF5+aPYSgcXpcR0alg/7zDETTBk8VvxMSlMzGXMORFzTBKkVX3m/h/8FX15+n7EpnJeavF1/PczrkKS627tjugZVfx/cxI4Xk/a9ZgLwFh1/cDmmtccf7Fgv3wyRLey2vOfmCjEYsQy+11LBgUcvyztAUgLeFwIA0Iw1Pl36Sw03K28KxZv/RGlUUoLKybDOcXMHPS/kKlBqtijPsRoIy7/AMEGseDNfB0rwbnhedWMtl1vFwIc2pW1hiQHSdQ7lUMeVcWULUXH+vEEZGIE9JRIyIZ1MH1EmFNRR9JK4j2GxnyaXM8iYi+A348y+KXuVXQXWkFCC84xGAu6mlfupgOeLFDYwsIQDkq1lEHHq9ZmK6GXCoucSjEJ+VMTXHMxpK2nimIcJS+3XXcZoWNH+3MS6WYXgl23aWe3l8TkpmV53GIXEDk7TVuzR9YdAcU+3/Po51FxOrn6Y1BqXqAwaPe/yoezyIs/dVuHoxc37pF93YP7Q0PolG82g/auf4IM4J2K6su6bpKrubzZfB+Rd64JfBoZyz71r0CHiCUSzVgc1DRhJeOIuh47oPX8p8B5MOt+19oHTh0R0XEvl8cUuT8BS/ZirgW2sNez1zPOVhx7kC/FNz6x0/bCwea48k+eK2RNXCIMSAzf05JTmYNHBcHTeOZbj4Mfy07a9P3XicPHhh03d8Qhj6jhNu4/tVGqfkDkmLitRvZmr36S3Ozmvhu4QU58SHpoPYlxjuipynLpWXTAohkZILRsY5/dRYt3UK9P3MokUw3Rpb1zCwoLXU41jUeoNRUtO8JgtaUv1HJRULCKsb3rxiWOwoHGT7Zpgs0MuL0LxfxM60qps9c9+GBV9oXCRqNBMl4HqqCduJW8OwBB5+Mb08FEu8Yk90uORGvMv4hO0VOcLHjiUW7mqVXp1XKikqXdTH5DNDpFiAqVlXgWhwKVpzeN5qH3uVUV428DZj4lCu/NXf73K72XLh9il9CPWmtH3L7Sik0Qe5t+xCnVHNPy5A3UVquGf7fvp9ZYeV4mPWbAZp6vWvb4jwk3nZzZfXMwvJKiRb3xM+aa94juj6i+cYYOulUON/c/uBFfKEa39FIs1E6i4DlzL33LfeftZitHuVHsL4JUPFfZmWV8oQWqHROMT837mA2rX7OCZtkdiQOJ8C3oatzuWori0NG/U+COPCNi0/Q48QVUpoXeeff91Eb2tA/Kcyk5qF6Lvb12/eYZsp1rnmjgi0qNKVc5/wBgg9uVf5yV1D4pUjSdvwl/Uap59Dp6i2GW0OSj/bilFiDMIIpiLjPM5TQBt+CHVgB7RcDCaYDtZfC5BZDfPR8JkRm2418sjE6OKJUvFOwR0689vxcHShwgcnnEhpK58FsnDelT7u4yMp9Qs5V7ItziRr19x3atqVciquF15eH/ALLZwcsrwHpPkBOzF6xHyOi+fn+oPa56ZatM+JhJnrHYfzKVfOro+kdgBZTA3BZbkgdsMXeHA2RM0WlkxijHWP7Y+5uyhfLDmEHHkqAuE8DgupQ67WAH3H0hNp9BsedmYwfz87lpt/ziteyTBsvdem3zcSFqYrI+GPmp6pmFRDBfo47CN7Jiks5i4cJxFQWWPSECb7iDTtldQVETpikKCeHMfw+sWniwncsOjtCt654HUrY8uSi3DdpTyekAjQBefX+K4qDXZKz6qyNPZFXLYKYcX/Mc72H3IaxAPIUzn1nUiNe/HeskpkTdYue371Pnc55G3tx7TuhvpeR7L4uYds+AdcUcOM4PSEoAObh7W79viMnOOwD9Kvwiosu3P+A+8JEdyvUDEFyMjsk2Zo5CmxK8NlarTFNCN02IWnKPpcEDiqjcJxlrcEax3S5bmQUVFCHuEGbLOuK94bsFklJKOy16nW1FpCWCjjwXgUUFMVNLWraLfQ6d+XxLiFc0N+scnIX9pd8Bk1vHOdYafECs2t9nj0mPIHfpNr4IJz4HzXr3OMe5+/MJdt9SV/RGvHLibckIZoErTl+8yDlKyM4B4aiDKlaMdYEROKKAu+T03fMbkrK557494BrMFB8FdBEEcGPY3keYcJjFrG3J9fn0ilvHivytxbFVjnPbPepb3c25+RlZXr1P8jVGOzj0/qFeVHaIfKSr1KSNYN9LwkXg9o119rlOKDZd+I/9ypPmHXy87nHtjha6JlGBrpF02Ccj0gVkgWHJecTUzbaPniCNYgejo7JgB7jz6ECq+Ey98MyF5iun98ywbP5X3jn0eTo5z+JuRxp30ZfjbG9oamAib7pObqBjgTc0d2XeLwdazXnpwa+4ctHqFFWHe44CkZ6rUCXjRiKeCjSrLwtuqG3D8KDR6BFHF6/wyrtBTVoMCkOAAuuQHKcw70abThjz65Xlgi1qLuTyMkaT4ottVay8vlleyvjzVbQ4OQZ5s03S3xDoC6JzY0o2vqVo1WqL22hZaqvR5c+sBm/Ml8P7InJGoz93r8Rv7W9ep476mG2jWPzF0rZdL+f6gHPy3L3Vb95hz6xdFBarlzL3yRKxsXfRBqXH5eJZib47lnp4lNMAkrHXMO6jnGjgX4Cp3Q1MZaqjJ0bcLaNLuR8vW3npiei2z4ZhhXwS1Yu72LeHwTINLoJUXRdn95mQF1f8AcTXrqK4Z3Zj1RRqXBjhGIGX7LCUYAabH3EcKVz/AAJLYZ7wH2pLBOmC/ML9sx0F3uyvK5B7MTtqi+5eNC86hYiz2fro19p3w/B7bcVtlS4rAdjR/EEx03/AAv8AHxOa7gXvzbHmBHwZD8D96mH5duv5/eIzrnSnLeHFW75fiLw9Let/rLq4p23KXQOiDK+k3cE6C2i05UXNmKpQYsw2ZJ26u0RuKs1iKVdLvnIZvXbaNGqXu3kCQqS5aNfQvZ7ShIS28j3dvlAOSybq4/QUyPKjtq9RtefftXjuG9d5LQG/wrt59IuufY+tdYKlgBYNTmzp8+ILw3sYvjI/vcCIjUhx3b3HyL7Jiiwxs/BBod8PWEjKNMzxKlFiAjBjuGrw4meUXwhfiGj6LSnG6gLioqHzA2mMObIPhMVXbyQ1jUufkpyYzbQVhPjlr714ks8HJ8J3tcaatlTRlGSvIcERAb0Qc8Cf0Wle7+sn3rfGMGRWqZukUimtaU/Xc9M+sCBhWFC+RBg+fAhIHOq9ncOxSKcqqj/AVKiGwW9LR9JY7wMJHz/CWPDMYwtPWUgO4TtDyEHX8RMR4Cj7xJ7PEpPKsFLqpWcToa/qYpyKNsA377WLnACtcVOAXL7sGWm7FkDquBDpz2rleBUNsbF4vBjKuzE7ACS+Iy8OlxHtIKGidD3rdDXjQwVwIZbVRg9IYAa9sw8XfSFxymhgeOc11y55lg3QnLfL/o9DEyLXs4VM5vrr21GFUfAPjf8Ak3FDdSGFY0moiaLC4D+YZiiBNgU9N/LPpGv0egZovL2uKqts0O+ILC+ksoOH+niJe8CUdJhXsgzNTgueSaTJKcwKY3JklfLN6XX0ItWN8AcW9YZ4AD0AzlirqN2RRZvGvebpx7EqPoVrgCBIrGvLJovaygZK4EOHdqN5GFefJkA3DKeeJ4FvFo07rEGvN24teW2X3zMlmK9HvQPY8HURV1ApuDwjAzYRYQPQ4KP9A+8ZS1xdEUXVGDumz4QE1oKsByM5ZgkPOeUCYbwF3h1mOB1zDKcnRdVoOql5dvJ/1/EZdXChy9lPssZztKGu6TNaS4W0jMLUmOnEpU8i7wM5UPWghvI0gBMghZkWnIx7XPYbG43zl9xYAehwGgVAq2s2qkb8zBB54gZLNjJtz1QpbWWXVw7nvXdWN0AH592ym5NZN5VT3HbTM8UJM0OBcOBd01TY8BSYN7FXqkd8Sva6uCqbPqFgO877xLGDyCDYeVZQurznEouT1b8rll0Z9YGqmJxaoFMgNewzCYFvuF2ujK0BXEPdVnUu180V6Y5gMqFPH1OT3iO/UFbXvmvecehjmc/Lk65ltxK2GV9WJAKm0y1NFLVMfvmVuy7/ANdQZyKumvaEzrr2IBSo3r+eIOYeSVyZXA9QPwquNYcqxB21s6SzXDUFtGnW+ZkK9Z4Z1M5Glhnk+tmIxjOzdB5C4rXNaszPltmlcW1bzWcAoFH6UfyzGfKUfBUcNOCD5BVefhN2tRSwHG5vAMi7Ch1YRyC3zjXe7XKrH0SolUBa8AefHMU6jT9hyDyDsTgzlrtd3Jl1TbUXhAQvmjZzLscGZQwfGlp3ZDpgqoFtq+znkjlMkywffPkQEekqKCw8nbGvafQEyB2kw8E6SX2mDQ8JiuXrV9oej7HBTteIp5FeIOLMRvQwYVcJpYaACZSV7G3NRhoybpRbLrC3uoIqNz4SmWwWmiqtyxWFFlwLtryecncBqDVtW4A7eg3GmWdjpvkKWy2t9ZcoEBocnqGGWLZd5m6n7Di6sc5NZhCiilpk5urcGcHjFxNtF7E+S8e8YOwbrs8MGCNMfT+WCke+lnpfid1Z25NZYHKN9g9JX8EPRuz3Djk+cEJhYN0rcdv5mF3BaPX0muFg4YrdxwsTH5jzK04LV6J/P2hfgFwnksH4fSNdM+NRXBUd/wC+Y6LRMLuXp20uPeEH3QSi72lKDxyuPSBQFP3h1MynOYtzkgWgSiqrMc4hUh3jSblTGv8AX7mO6w8Hh4VW22rvqXhy4u/LOTuBVojdbPa+yQG3rYG0/RfKJd4VqUwclt2nlXlg4jXMdPzFCAUNTYI4FnPdElX8zlXRby8eOKMTAUGfFd84937ZRqblWoOlUFyrXjSXGMu25pVvIdElOHPtwH9yrPUYny/ajxXFAX1La8ssrGV+3XWS4Fi7SUvBtk4EsrwEBqXIdcA4sG1q1Dcxy7gA8a9pnSy5EPgMNtFXsDBxKFBdUaOzp8upfr7A/lhdhE0fkcB1b3HJXdVd8lf3BG2d4LzMEtgcm19N/wBo01lN2E9VUelz3TCkfeYF0Y1BeW2WOeAaIGLZOacvs/lmtIU/Nbm/EQIhoNb7rn3lQ8AlD+vWZAs04HzUu5ff+D+4kQcD32xhd0Gny9wqmFMBCvArUp2RvxlFlvGInft1H3oy4UvzLVrL0epKRfiHuX2PXHxt1fErTP169Jy6mBMWm2IlZ/JC57UU4MkFyblY6ghjcp/KFophxCJwonbaQPl4g5MKB00PQxj2IjmYHxGPwLTrp7wvmk/cJAPdvzAIB7S1qOl1z5ty8A4CHss5LJf1cdCJxtAYOVltD6bZbbe1hAYcH89ysaQA8R13Jj9HBLG+ZhsVTsN74MEYKxgYGKGh6QqQWsDPfmVLxhTPyU/eVUGghe8PZKw6pkc9t+fEFB5AX8ZfMquTot4EShPYVBoUK1f7/ELKcy0XuPclrHtfDCrn5lUNIxwfviOBg6NfzY/Mwn6CV8y2nDUXkq9trKH/AES2TyET/IDn9xA0D2cPfUclE7cR4+7+8IvJw5vzFgnM1b+8S2FjX1lSxPEIQeNtvcF4h4i0Vm9wGJXrBt5bUTtEoA08S32CAwZzR3Uc4JCLRKcrbk1fK8DP25hG2h3dqq3yrczXEaJlurL02/aYgWfAAu9gyOyozFT+bmX1TcuLNyr1VQ/dfAyzc7GeH+rVB9vK/e4VxBfYhjCHur9rlDf8oirjvX6QcQzRtf69X2GCDg13n/PgjSaCDwUfvxB7+5XeN8QATyTJj9+ZhUb4xBYAPTMxHLX3T9vWWDAnJFLGDa/mAYV2GZxarzlNW5Pnx4gWDLxDV1VyoYkt96+0FqK87n3eJUMLD8sOhV55YrUGy/r94ho3iSrQlQLN1zk/uKNX8bjEdjHpLwL6eosF/agsWwbhKZPggJgaGJZjzJUhCLJ9SUtBh0wp05iNZShPcrVctGYKgqOfoPAjcL9ht932qbjz+g/BSCiL+Jx33MUAe9yqalf4gFLwS27XPTiTIYD7n7YCKPC9fIfOId5eb9/8myCyT2/iAdj+3+vmKVbcowvp/wA8v4iueBrL+35+8dycfz7/AL1Bneo8fu4JwWtf3Gq7RT5MQ7UHMZTL6P70feFNf2l9v67/AKjAZedTmHHtKAKORQfOXxFCLtf4j2gcO3XGvLLq0aob+/MCIB+8S7Ug4aPCsXFurq8kLzPZTX+sW6XeKuYIt6Fc3XMSNALPFkAarSR2rQrQMR3OVPvFAK4fPEwZV7Y4JZdvHMO1W5ohTmCOanlJzgsLu5QXiI2MnMHFOWC7d8MPSYVOYCV7G7lfRLDM8FEdp0Xv/kxoFBg9IOLk5PEEu4Pev3fzL/zSzRYW6cHyn1JG2tfYAflKWkBey+hyfYuC1ZDHu17oQUGXI/LGfnRnvf43BWk8Ps+ZY55lNPk6e22ANBh8+Pjg+HMcXoax49jqG35y5t9/WALU69f2ibNBvkev7fpEsnFsXAEtqwD/AFx4IU34Za8BWX8bgdlvHZefjv0ik/esP99sfmNhy6/bljoB5HteFeuIJm76r/FStCAx6c1y+u4mZPb/AJAYY16UwTWCXCvGGdPM666uqsr7wHK+dUekUfQ4X8/mLmzeO4ADm8Rcrs7lA6WN24o30UxTFXUlap1cteBoZgKF8RlA9WVgc6dweVHJLq+yYZ+0CYZmDeY1ZEpmKYpV3mXnEPiH0c5XiY5jX4JeTwRwXu8cr8RyznvX3r/s5Bk4ea/bVeiehX/l/iZ0cjr9HpqN/rG8/bUvw4f8o+urzhl7/wBmdJkv/vN19r5mRpHBofFL8sX637zC4V/3778zv1xNKvAvHa8XetF1Wk9cz6vi861zufGzb18f+X+7mtuvb+MT7Uf959bjWmrX74efb3mcy5Y1Xv49Zm7L+V5+XtWpzp/P3/7LU8M+ntzN2H5/fM1baysfarm7p8vm6m7+X8QwvdcevtOR71lf4jgrX6/ajh4ca/LMew9Bn7m9cTak75+zFT0xx1/czcr+87C8ZQwreWKm/hxc16ubKv0T16FVg8TP989GpiRzO5xuPNv6C9Je2tTWdEx9P//aAAwDAQACAAMAAAAQAGUA1o8/OmQV/G0kdpwWak43WHWSkqEUd+9fHrYUU9zooeT+z0QUpHxKWchKLVRMPA8VEsPgF8k3Xr4ioAuylQcVG7gavTmZssrNoT49pkAdc4biaNnuua98Q87l+nI0KniBEzsfRkyQ/wBlAJU6ZLr9Pmkf+O3tw8iTpq8Wo29hqUFsNkHBoBPJHUhT22ZkO/glXBxzzTUICi87bZJqd0Encb5xHGggV1Au/tWfd+NuQtlvIlwut3WeLGMFvqivnI6DEW2Bd9eq3ZS55EW89lErWDSqq3Ekt2uZFRK+5kv/AHG6KXNMCrD/ACZRnw5IJvC4XGNCnxEDfldktfXrT4wYJVrPJ2O/NU4B2oAgngAguevVczjX8NaJFNVorDfwL4hcoeVG2zj7unE9q1r0vLenSj4sWvxEfYMOZ7o1u4hRCZqZGVLuZp4JG5rqPKr77XnQamJ6FUVUxNZxNghzj+pScPop7/P3wOytNAV9pYpKctiFJXrUwKbr19IJzoww3WotzclSGbd1MwG15TSUTTVfmCiIc6UiglhQh95j4OrlS7O2ZzBUf1dBy2v2lnwXPGposd+CLk2Eh40NXX/ZhYfqKrVd8lGDK6DuqOe9zeCQBul3GnptineiAO0CzKp22L4Mag2H5NEmDZzTEk9Nlb3sw2Y5G5E1c8m4zec7IEoGmk/1sAucJfh3axraeXTQtyvIw7XMskgk0+SnnJljq0FirNk5YlXQ/V0+UGPINImS4x+IfmgBXh2ue3iG/sm0X0Q/tOZBtAhXPRCuNjtkW3C219u/Z/jy9FuR1OxEkE/TPnVUk+P4WAWlvjeCiJWWKA6QHlUMkKX2r2bwa08A30e2V7ExIvCHewJPQVCUeJ+d6nuOfbj99mrKwe5fHZL/AMkacifGRWUYydhaGGxi1ljFLSCUG8APg7msfOFXZ8lyyTX9YLOCRUUvGmCmq0MPQ6l7DW/f9Nv24a+9s39XN3OeSzhUHN0hUyS9MG8krXjALfRRKUPBCT5ipI5WTtOu5ff7diDvaZ03GE2RSCVEmggH0TOxZZFGrsvuYeq7qFLneP6+SFZD8XghwQVtJtQt1UdDmYAQzNqVITPf7nRZl34BkRILZtOwD9aVhjk9SqRXr3hy4rbnJjbOko0XhZ+oEv3HA/J4hvT65ur4x1tD3Ke/d/xRPAUoxe395Wk1z4QaKVnd/jfC9NcTKULOJAKRoy7KDOyNmRUW+CBHkM3HjYP1CVv7V9ES3b9QOeLQ9rEORfQ5BZ2l8C9cVWJMcyrF8YDoMRuHrCvsiSNvW6sXGooB6juSq3vNBMSTvnO5VvveeKqp/wD/xAAoEQEBAQACAgICAQQDAQEAAAABABEQITFBIFFhcTCBobHwQJHR8cH/2gAIAQMBAT8Qz57bbbMX468N4bbeN4yzjOBmEMvcfLYpuJtvIxbBE5ExwHHdjZZzpx3ysu/AnO3mLMsssiLqzZ6vNkQYQW5ebY+Q5DDD8y223neM43jOdmyyyySeNt5e5LLLLLONeTOHq7uzJEMRPAcZwQYjnbGJeC2Gyyf1GXbWxOXSVteNt4bb8Qj4bxtvxyyyyOp7hkRbLLbZ8CIPO2xMWx3x1x3xv3PDx3b8lgj4Nm3+YvNiCTq3YNvEsfExEHY474It+C8bPG8bPCcBEz4b/wATYeGFs/LOCjbb8c+CScK2cMs5Djf+XttlmS8K28wc5wHLeNt3gfDbTjS2743gfHf58sgsss+LxscEt2DnOM4Oom8bb8U46+ORM+GfHbfhllkFlllnAWWWWWWfHeGWQ7y85DkNsPG8tjY8vAcE/HbbeTg4LbbeR5A2285ZxlnGQ8b3CQz8c4JsPKTd225bxsQWzPweGW22LYfkcmxNhh+AWWWWSWWQx5unc+dhi3nLOBhtt4q8ZZwzg+W/BbY4bwY8HcQgWWRHOxFbw2cMkkss208GQT8E4GHh1PXG2zbwcPLwTLg5XhbzFOLLfu/N/AMQ5by2XiI6f3MPLznA8LZ8Qj5bwMz8m7fBLeZGW1PqHcLv4h2z4PBB34McMdTYfLPizy8NnLyyw8PxbThTJvME+bZDI1A9RhOcnDEQm8PxGOpIeT5ZysxHfwXleD5PIpkvGWcOWckGTXTHBBLvyB+eRZJF3znDwstkwTB8vUvBE8Mts8LPmzbcZcPU4ssF+0adxmRruSzbOcslD8ckgjuZnwyJvfDLZPAcM8rr4HDN54Okx4PWSXqOpEuaOJ3Yi8Nl4YbeByUWWWWWWRo8PNlnOcsoLbL3BPDJPwHLwbq4LgpE6tEsvLDwYsNqW75mDecmG7DYYwRUySyyyzejgssktl5CWDh5Z4Zwctm8W5L3LwdQ5MX+Acnu2eD1FsOFdGN+FpLHJIOrOuR4yyzgn5DMskWWWTZBCZ5bwGWWf4hZ1OW7ieCUQngjjI0Zxl4hsss5CDgN4ySSSLLILLODDq8uAdvIx3L+X4cgskkjgS5Isgs7hZJJDdeZd4yOQsskkySElkWTPiEdS8Cwh4EfxjsstQWZBCYh4DwHBw9s/BlvAQckHDJhZJBwZM5PCUscghyGY/jiDqyY3eCfBEEEFlkdQXgh1MwuGcacDwLIODwg5Vk4JM57nkcHh/h8OLSZJjeZeDkoILNgsjG3UJwTecxgXjkJblpJwkIHU8N8OA8d2ZJojMf41khBbLL1wHGRDx0vCXOJwMLB1tt4yYlvAvJOWYc5RbZxwMYbPiLZ5EjLzJJw/MHJl43hsggiHqLY7YTgdsSFeC/lAwThYzd6tlkuyJhezzbvXu3kZiTwW7JsEcieuEjv4JSFnxIGR1dplmDeGcMgsghh7lyM8x9IQe0jMnQ7mk6LtOSjRMjq/T9k+UkkscQ+bO+J7ficST1w7yclt0wvHdrYkNlJHDxETuSyySyyCJ8RZ9wQcEyZNs5CMvETPMr9QdEeY1j0GTB+4+kGFK8SY/m9574FMBCfBegR0YEt7Cb5su7eB7jzdpxe2HXc45LmwcJs5JMJlknuO7Us8S2DYme7pDeg49mDYvLBOzeiLBh9mAdeJT6v1lmOJW9HANX8F9OQ/UcnlnkcWXv/ACgPaEg9SRfruFtmLpbw7JOGdFlZZIQjLwstryBZZnDC9lmQSXRvgjDzHXhetLA00B/WMXN8/iAnRsZA+SEey/2gHc7h/iVX8QPcn34kSfTd5dG3vieNkQsJ5gWDftWR95JjzpfkQF6vL8yO22jG5cDDl1Bt9CCJZBCH7tsvt8MIpspidT9ZQIYuz3kPPQd2qHvpeVze4iuBDjD0gye2QO1O0Nr9j2ftRRN0hngO8msPpoF7vaJ+HVicBQ7nX5v1lZwJ58xt7sevMEduQ8PMWeOoXvD/AKii7MjP96gfBAoE/q2GGe5L5Jp92lt/BkPuc43h04ah+0i/mMebQ4g6eY24h3AN1Zo66/RFZ0/2zrMAGoACDY4+JAZkA68JvJXsh0cQlOsG+7yej+5yggdvFl7LudSj5g9LNncdxAhOOZD0dPUjF/7/APLLoCNd9P8Af3Y+GV09RPTf6Tp5YyBu5/r8Tvv+3/i6G9/6fmCW7F1JtkcDiYmJxY+pR6u/uajrgTV8/d44zvbR2NPb13YWCPQ2AI/fYphXTrq9RvcNYeLD37hUPLD+kg/IAXRj5jzSex6mGCHb7Lr+rOQW6dXlZvBlkGPBQPNypVHrKT0Ory7vAfcJBYR5BhPE4bA2T+2a9Ov2UR8/5hTsGGxn/wCSPA/9Mry6tZv1Gn1DsFhrFdgfkcTWbnXAWbkZQDjfd2r4wl6qNLXX6ZTF8pE6c1EbHX4SE7htOp2aZg6G3cLrJy8EENXtuhQRq5HnoyP9WJfCwdzXRkOekb3qbqn0TEtb+J26M3kZZZwxYeWGQfRHjzLM8wVYUJ34CAGfBAvmd3khj56/rAg8a11HxW1fK3W89Qn37hWw0hh6eLSN7syEGDHQZOgvX5IgEjS+INTIzYwfytcWOAxDPhmnrCHqiD3mPyoHfcMdHQWAeoHY0hveSNx8s2A4LbCw+0aieJxBdzqyU7L0hUI7urVvxs9tt/PDLOc6u0eLJM6PzeDzSAGXRd7R4Z6A75jrw6gA6LR0f4/8WnkGGCz3+UdeMkQLnT2YWuXbkfy6t8zxk9PrLyvMjsHtDVr6gX5ZCDYE/UbpZ9WsgddZB+YhTt+4U8dQwunuG8ki7ORIy52jzR6wtAPNs7CNZ3eIZtp83XvylCdumHoT3PqH+kt/cYs7SMWxZdGPdgeOD5iO2KqvcXqUis9QO/EmeYTq0eeJqDbLX6LU7J9TQ+iHaeYAdOEMrLc1/guvp6inyM8wGPRdc9mxRj3Ejjxxd9xPAslfLtCM9xjso+O4+psddoe5Y8UdQY7ZSm6QO92xx+rwSMdhP1tZtn9U72Qv3EHXUscZL0yj1YTwylvQ46Wni2ZT6yaTVmX3g/pEE/rLsXWfS7gCZ0PCwnu7LpJd28g3lYLpBw2Q7YRh3BCe5Xzt+MpTt2JuLHxO/TbPdZexGe8m3a7hjz0yjkl3vZPXWRvbxGujdnB8dWkw8Q67teoK2Ynp2NR3Y2eGLxFskDscz5wxB5hjP3MiAyaZAbsRAOp3J6n+0du4DqzuYIeot6R0jMnZCqwjYGFIO8WvksT35s67YVDdh2h7jfWx4BiHuMWVwnmI7wrRkZK2IMsnrSe3TDpDzsnuWOzmbaS+mIqcNnhd2xD7hk0fRJ9Quzv1eyxQZ5D7lGn3Zv02wg+nmwldZyfHZCzsRduz/F1dxvWxPUcJr3aj52FH1YeWGd9QfbIHPqHpdgAlOrGOdwZ2iUDKPyQPJZPxDMyx23Uv3em7YKG2h1KwdwDrhnAvLwXlervI2164O3q9N9nixZ13zlxkRj3Y9X3nme7ueK6/e6OIN3vI6v8A7bzrIeO7GdW978zvq8Dxf2XvGQ7n0edh2ecg8M/wvXhOg3LW9T2dn28X2TOL6zbWd2LEZnHXqN2xtjO+Ouf/xAAoEQEBAQADAAICAgEEAwEAAAABABEQITFBUSBhcYGRMKGx8MHR4fH/2gAIAQIBAT8Q3I34tX8OG7ZZEAtscDryQ7Mz9xCMxtstPc9SbYuzC9eRYOpc4Z3Dxlp5YHBlln4ZyTE2y8P0Jz6tbOAh3SM2CxIkNsNt+Nj8Q3vI0tBafd37FS+WrFtyWxhAk8k2W7Kze56s1mDbbbbIZ86kk4z8s/J+yx93X2f5v5QFpaw/Jv0Jb9mTb98Fpul7GSu/q0PmBYkfEsNsY8G5GMGOvY1ul1IAL4EnxGRGGO2XvLbbbbuYzZxlpMHDZJbAf/CHRmyEzb0W/uBtHXuDmZdPGHKhfUdwrpaPzIODMk+JVsss/MB4Nbf1LibQjp37bs+2fGxYx3GGTPYhbwtMl9n8MmJgm3jThi18RBYb8x0s2YAu/kMtTD7yUrBZZZy238QW2222w42x07Kll3YlgL3w23h1DA/qUk49sOM4znC/SM8ggv2s/cQflbfws/V+kolWmIQmWzNtttt/Dbfx2Jskw6Y11d39XQIdbG8ZCRbH6XzkllknGfgfYSXzZPhhJ5aTIgXfxwNWC6vDyWPcUhPJiyy22z/qnG8OrL+M6jH8Fmlg4Rq6POAw8ln7IcZxlnGHjZImIEpPbqxtRj2O4Dy1XAEGTGLLxn4P4LxttvB+WxPZMl5NbB7Ord4MWybEglk8Mks5zil2fEdey0ht+otsbVcAS5M2X8ttl42W2W2223hvG22/gTIzayzh4WEOwwkh94skss40WQZG6e27DZMXfbs9WEEsv5bbyNtvOWcmWScDbxvG28DHfD6XbP3Bpv6nibCOCDSwmNnVpEXnES1g4XqXLbjCWW3nbZed4yyOM/FmSTHibbedi3gdn/lPeobh9/8As7Th5Z92ww8A4cLLGzhqR9oBwbLiEEuS/gssd87SEIRJdWJZttmY4TheG2xxv4ABgzpOCu38R1bDwCeSS5Ancu3UvI+4cLlZZbTlZHDlkucLwMVkElk87wnCnG8DbEXsz/ZwB836h6hiGIkGzuIJ5drcl1BrEuGWWWOvBlnAOcbfkG+y55P3k59pXkD+rutm3gZOAc7bDwG9l338zQ4wfEe8fENvcNslkAJLPUtu2Qt2XeTbLLwbsIILOdznt2LQm9i0Y9E/ZD+5Hfb+ghcbNsPInO22w8D3L/aP3Py5Yt+Y1NsQZw4FnVnUx1Lhl5jEEH4bnOGr2ccx9I0heOV9+MRfZKYbxsPMnO8DDDNsM/uwljI6vLTgTWyg22DXi2ZbZeYcnA8dd8dsOF0k0jEcNRF9volBbXdsDIdtyGbYjxJ+Gwwy7LkXxt0+R9T08UZZfGwZ7eLNtgtllL+Aa2EHGRbxlwJBB9yrR6u1j7LjriFzePJwn5JHstbn4MIOBxJNsPAwzicDENonc5Yx3FsC3SYksHX4heB3+A8EvB3wZ3z15GLvsh4PngDyHZxDwEK+4ztkgepGY7W3q9ngMxDHD8LRa4BfFhba8N6tydS7LHZeR4eBHJHP1SLB8g4e2FLPx5bWctnJHuOmR7fW0tJcKeAy27DDLDwPaHuGzbNszjZdiWRbMtvG8Bx222I4FrY9cPtZspkDqFpZH+jkz2SxvF1lJeCy7GExE2ZLbPpDDell3+QsMy22y2y4G2GHhS3bznq2B5s46Yx1j/QCaN27YuWM65BwHARElnC2E3ioY+mf4sdyJ2lt2CUvBZYZSxwDbbKeE9YZnNra4e/9IdRkMepT7s3ZbiveIujjkWxdIbIH7l13ENvHqE+ZfUscOW2W2GGUt4hDDM/iTWOJfibbBvgn3H+iu5Xafq3b1IyCLxeJh1wYbbbBuiDXeQZEca7Y8EznkbKXmSUQzCGcACzqWWEwY/0ox6mpnUPfDB4HUOE2BtknG5DLsdcOjZXgTzwIPki6cZDuTIYZmt4IhDVsNuthjvA/CD2S388Dbst+bUtsi9sMO8NsheQ2zu942WM6fbqwngmIgwWZD4/gTF9MQ4DfB0i1iDSO2SYOpc7tJN77hx8hI/EJ0j8tTCedwruILYhsbZZhPaSzCzLe41eu5jCIr4kwsj4XZA2cCiTEh09kdGkxPeBFGkQSWQXzZPbDslsnb0kC7S9bH8+2z+Jn88bwQlZbP44KIbpH4TLamL4u0t8jHsp+hn9jt6/iUHraQv8A+3WgkTs/873CIi9y79y+WszWfR7DSXIcPXyLLJMgnZaRjiUaM5Zk20nuGMKdXaHIZCyVnrLOT7lfM/LgO92jdLYJk1h1+Kjb+4Dw7wIBsDoAIo97/u+hBUL6gHzZ17/xCp+p8bn8oRsWG2Pu7e20NUrqBvcGn3ENIbBunlkYdTi7cXd1CsPQ9zn8SF0ZHBjEZvyW3PZMj8+7RwN6mSTDOARy3ZIar4B1PsZCgDtgwzDDWIf/AIxDrELXcx32U/MKfZCYOdtv2cP2TxsaASb68StEQv6LCuvn/My/OMNOn/iGgfhRyzIZu036ZnktLoti2/XzZhkEdYwtGSdR3tkSjSTfadmQsDry+Bhro7tBjHJg563+6O8APh4id6Vn7SK+s8g+js+yQ+TXzDHRgeyHRYDAAftj8HV9EBfiL5GQ2fibMBxR9X64La3P6LV3D4J/Yn+iovmr5h/ymDHHZ0MIDn1/CZtiTj2CwWl9EiWXLY979jE5nV8TfRBDeMtXT+Z78Xs+ZBHqdXxlfWBge0qzyDnpw9kEE11GCdCrXLB1D4Fff3HA6HuQAwCwH+5ELtGwMsICokxqgYu1Qs/K0m/STwwpA3c3/ScWjB0lyb3Nj1bbP4nduXQ18YFDo3+4Mtf+weYGe9ZAwCQetR6/Mn6xOSfDfZYkSPi1/UHfoSHi/wBp2+5b2Br1D5GN/i38f7F2ZR8yEK8T/v8AC2fP/X9wHvSAXgjHnifiGxNj7nNOssPSLonfB9QjD2U/6eJnc6P5RwIf7sQOhRGEYyPal0V7shScNAAx+y3eQX2gD7Jb5fcdeekNEW7ZU7Y6iWRxYJ4Sn21sPXUuTxLmyMdwWKHY+ZGHthyD4KBOvUDR2f5yCO1/uzl+T/NOXYZCjMesZfHX80BcM/wiH+rJgMOcF2X6kL5B9WfohbBP3SPm/hHphr/4GIOjPPVG2npiDwfP9w9gf4QkF7EJW2f50tb44qRHRBtDtQZ/RkBZ19iSOPjCiDifH5KzmOAe4dKUssgMD2S2huXwzbn3MEL4Ht5tzhYRd4i6Dm2amd0iC3vazo6ulYV3tWDyUL6hFnY/Si6zNYpPnWIAxRTqf8LPkgdbB9If0g4fSGdz7/U6t3YKwRh/mEiBjDtj2gC4ZEIcnTPiEEePiFj3UEA68hgG3pPmA6D4QNb1LFMB7BFDqACD3rJASGqexQgIU9/prodchjgGTvHUYcEmg1hFolHlp6/52zT2QMHHMdw6d4mEdn+RAXbucauUitu5pBNF77invyP23QB3DNW/nulvkLPfe6S9sYeBl076EHLo3/NUYfo/giux/wCZvkNSGpOs/wCvXNHPZO9u67ClkLDCyaM9wC0FTstskH6IzEOd/BMDSJg75QmE/gmHY79dkaFOoh+xk3yqTDdiZwn1AofD7CYPb2Q2HsRmdAkwXOj/AOoK1Atk0Id7mvXVRkpdjSHqDEYEx+bBvwoL0X1d+yH32x7mMKZZ+rWYTYi8uMk7dfEb1INKr8wK6ITTIHQ/UdszYoR31Qp7aJ2/P7/9rXw5NzU/6f3P3BwwORMZ0ZSS+A+2j6R7Xy1/5nXftDZjBO5DQMHydkSTowCio2Ai73+kGYdox4wL+U18x/zn0AiCdxpYdBj8eCC+iAggIi5ICQF9ek37XJRfjGeO6C4b1BOw1gD0lpIXntydyfnwur6SJ86Rf4TvqB8sZvBbDYW/iDq9vtkupmB7GAowawLA35mEk7kcANt0TM4nC0w+2TBG57UQHpD6HqTMUF/iEQH68Q6OM/qDT2Y/ZAPDshHt/svtEOnPm6h1OwN6unbYkdQzwlTpMGEdaeSsQID7Nwk+mZDgDad4WXg9jBjGJ6piLaM29TpnAEx0tw+RAdoF+mfa7jppGeyB2Nuo4OH7xvT9W3afmiB9yOptTZMSPzuz+kHU9uvTAetyDP3I+Z75G+98joeoQH3CxBn1aMRmSiOQDOg/iPRO52Lc6clL4fwjekOdfMXR3qDcyPevn2Qg4QCxhBg9N/8AsBnQID4TYrAcOdmMHBEJ67jDUnrOmHQMmdN2UMKZAp7jYHX2Rulj5gGWvj3LGTjqVt5DbE29Q/Fltsk2jv1N7sWRXkFdvqKH3JQ/mCOyISUPUT34/aM9t2Xe5Hx7AAnxJ2t692Y+dSU72Z8T6C6t7f4o7h92AQAdxuHOn7hCgBA7BvUfGwE3NnroiZBIhRZFz3UPqupjO1sGiPRE6Hs7I2HZA6+7fT4hftfOodMSwf1PzIfiGmNoc8sIPk4QG9cBx464MX4mSkp0HjiZ92cAerin7vgfBAHH0jUvfzdOlyA6F9Ovlr/+wexYb8+wPTfmBWvcD7fUhn7g6shd6tjxJ6HuCDnTJw7MgsfA/wCn9z3qI+GP4jQ5v+ERWcVVgcBYwb0iv/kJQie69Rscv0jLd2VzIMMD5G+7qBdWV3ES6nXd43bcvog4c5PpayPbrf8A1dbdfPuXi6y+Y9P7vpg7GsZnaF3dXy9nfxb+fLfNi/V/aH9y7/hdljx5DrOvCDtmfW+y+9Rre/qMZ1/wh27g9viPb9w6mxhOfwnT+j9W9MJumHe07WbZ+T4h1M2/Xx9nU1qM76XZ1atzvXHHzOZay/T8b//EACYQAQACAgICAgIDAQEBAAAAAAEAESExQVFhcYGRobHB0fDhEPH/2gAIAQEAAT8QKQJK+vb9hiBunNF/FMVFYW3AeLAuCCosc5kcr8QReVLLm8gNdhg5RXkQY9MqyNS9lf8AyIWywxRlX5ZwAtc33MQfJDP3E7F4csuZH4EyHM6KK/bFAsNHZ8dRRtKWhzR3Apioqxg66QQzeRxT1cX99hihi2qpHuK4tvu/zGXM4jfaXdyGarIlPEKBQRCRybPGog5Q0XkziEF0tXL3R42/ES3ydhW4cDFOKZfxAoMM0nnuJRkOddxFanfXuaEr1KjNSqHK4uoTSgUGreYWi/k1uIMb5HdkAq4D8wLZR30TS1isV6msbblhSVXXcT+x4mHakKbFW7So1OjwXzjqEqnSX631LkWW1fQvipXYD1ffMGHT8xTSq/PuVeQX9HxLhwvBwSl0r88QbIjwXELojWnRu4hxn1BgOWf98w3h4x9SnPmZLrz9w2qv1L8ePMdsOsFnPbqIKjBdFqvmIW4gBbS2t1bMWpUDTYt1iKjOvNY+RmdcCylh7gSoKsvB+RHlh8ryG4VlgJx/Fspza/LZ9ELA0HHBZ2GYiWzsRlwJZvErFw4KM+40YPXC/EW0lnTTfgii8ptFo9dzAGni1+qz9w4Al5QkFlT3KRlekC2eeJSyja5C8RrK0grB1rfiI7UCnBWTnfmNBifK33G4JB7flpcw5jdg5v5mTq2diX5yDsw8svd42PGu4qmrlLqpmAHkc15qVFIb3VHVTS5Dj2xq61X4G4AtuVvlq4vjsr1X/ZZGDgiEG36ipf5lqksPEblmHqXTWPUdDjfxFOLo5ja3FoVscRNiN0CW/LiWjHlRd49swWsLHbUULr7JUx3WYFK/KHfj9nmWdP8AmADvtg4YI0ZeFh8oJXWf4ha784gtHEvSKdpt5y6tMGuYjYRa4CgXN0gIu1EoOb2wBxwtPlBwjGsdJ/ioxObAKFYO4WEKlLKBm6LajQlkRFxrsrEN2t1sB1YCwdH0AfxmLPir213GbUvlPZBRRdlmeyEtPcCkmFuuDo6mWsppt/EM+zjTq9uvuLNLeV/Y2SgK/S68ykoE7WmCwfYPxKwFQ3DXqZZ7eH7mBWBtHWfMxWG8gr4uZeMUh/LBRT0XL4wNftlFapwg3FsZN8T9yqrcZs6i1qFtgBv3zOY1vBQSzFlNHb1ACcNmDUAGIV9pgIMHwrESWa9H7l7HAg9BxAzZNHTEWi8WTWJYrtyP/IlkvWfcBSbso/UqaVPcclF/zHU5zdZ+4lTw4Rn5ZkBTow4/+wZtpMVmDI4rOCISw3nP7gPb+MS+mXqNDSMMAuKIJRAe64lt5v8AlgErj6uFV88VMhmHTDqMXJokJkcRZpcQaZWoIwfREgGyPufYZIIboCpqlKopG0LhGIbsQyvcrSoYvuiIxpuWGUBStuqTWgwfLczyaFVWB8x7Y9Rp9kEIYeeB4xNKN2bPrW/ECYVHIH4GEpsugVXjAkS90pT8DD8wVhusuT71AaoYFE+kx/RA3xwwD55iiwvNAAhyFbxxUoUuvTibb/MXXn+ojD4h61KVuJmJE5z9TK47idsXbvO8Yl1aer3CtpdiNuWLojYPUpwaEo3xEo2h5remIK0Nq6bf2RF7wErhMA6YAynFzkmKyM3FpqwI9xnGzB5YF4NnBAAjd/hiarL1zKXUtga+vzEStLU37iAI2Rm+TEZwdi3APzBYGA4P3ENspmuIPar6RWkS++JgFbNMBwaIeB1/Eyih7buHS8dyl40eZdtOqv8A5KfplHpWbhCLoUdb6ofqKXNVGBMWcEELMxrFZKtN8wwSwHbGEsgXUYqu3Y956gaBYlBsVxn8QjUbSLXuBFn1VQo+YLBYpyLmA2ngNp4UmhqiqC55w1Gl6MefqZmFo1a3PzBPSwF3BykNtOZrRUyh+Jl6oMPnVxoAF44lvo1Nt/qVXy9Yi7xx8VBT+ZqcLL/fMMLeYDMreviK3uCr9/8Akb4ZV31Uoqsyzx/iJrqALKqadq8rEh6T+IwYFAH66i2AKiEWqyuwuJFf9xsVzXZ6/wDkoxZUdF7nXvh4qIRLdAb+0UMYRpKrOYpev5lZA7P+Ryt/6mOUdj0PiUQqdgUDFwFHD7lYbzWXJvyy2gz21qA2ADn4ljxn9S1D5QS7w7gy8L71UpXeXBxMN3j2QNGitQXVqwFjG6R0QIvYWmsfERF4LzuX/wBSw3dLgvyiNN24wxefmChJeY25q4BZLRdebJy8OQ0rLh4i6omy82PIxGo0ZKG+rgFZBQjml43VyUD9sMXBarRQK6IlFIGd26sywarHzPJF3e+4Xz2y7X3BnNgxKbMc/MB/vP8A4LhPlIV7eJ5a39/+Rmq+fUD8dQwwfU7cQG6c/wDZnx4+Yjq4l3iMOIjpgCmM59Edy0aSOKW0HWMsvQFalH2YhVaQhqj+4zqAFv4jReIOcZf+REAZLex5JesITj6xuPLMFy/7xA6P9cbNre/iMxYebwrUBTIXgYr2XG2b10WtzWUFxecRUqytr+ojksvxALcbDj3EVRb5PMHTfjiWF4HPqW/pLZ3pFdYv3KVqkBQLyMHCA0ZA4M3Z8kINMuzkSqmazO2oDahYo3EqSft9UHoYjuy23hzeLcsKgoLBR/BiF8AD/dQRaA5vH1ENUNBXWKx3ChLJDKPFb8IVYFoqrOBV/GQGjqMlYDH/AMlyMz4T6iWX+u4Vz3OSfZDPv/s0/Mox8Q+0t7/3/Yq/1iNV/ESx+Gf/AB9cw+XX/wB4jjUtluB/yNLEjfmZFyw8+ZtrzODkNwS+2G+orDoheKjyovXzW46DV0vQytzR5cH/AAI9JRuzdisxX4h45mTZsrXGWBRVJiv5nyo2afd9S10zRkfuOSg3R/CCV/CrDEggvpVj5ipVi7bgNEy5YmrFrCnCm3cORepTnjuo+CLZVclQ2MgZVsbHeuY7cg6ay5gpavSZ/UTYicVSS4WCm9bNwRAc1/ezGUKtux9Q2M9jYHTZxzHUBoLbYADegmy8ZRDK6N7dTCxiKtVXGpgqK2uf9iF11Asx4eZ0VB681PHF+/3Ma7i/zFma9/EzPWpnHF/UVSsdzWCU3jMEmCGeD3/cZIuoOWHiGk8uIua+ohS/iFqo9sA0kqsKnH+YF4Mn8Sn7JWnuW8Xk5YeSKIYALWoIjRwwSsWH41mADKvgafpiDQ4Z1kLa+WLOgcu+JojhvPcrJWiHG9w2pcsAqdn2EMNlcms8soo1jX1Mqz7zUonGM/8AVggYB5a+Yv8AEDFS3VnqJWPaMPwkw4EysjTYNytITaO2HGdrqt49xT5hA4zBtN9bH+Zdp/DGut7279QMqn0UQD8FZiAijrmGZZrWqipXnOY/HPzNjzx8f+aa/wAxNz/XUX/fuWUSj2hfKTiG2OxJcvvcLtN87x8wRqvjx7hR+FQpxSa4MQx88TTZbziHifxiXc0ZrL1G7TSOMjeo4wcOVzxE4v7MTAB8DZiCDquJRv6/EuVzf+3KO/5jaGtVqA4GIgWE08ws2RpXUKqKET/sS3ONn9R26FgdNv8AMoC2atrzLy1JvleiXoWVbm6C7YqDbq+IlvLP/wAmhq9MRGZ2YzzmODbnrJ9kpejfDOYTA2uhEYMJZNW5lKjX01K9m7hEsEJSfUbKs1njMuq2eAxmV68gMLIR0NXysTUHo4r1AnCeoLaSIrVECtuLa7m/b9Rmb9Ec071GVvvONwiJZLnx0zwS91/sx13dMwik1Khw8qy+cY543LSwo3EAa5myYFWjFO4rTLhf3C4znVnMMv8AC1ZyRSMb9HnP/YmmVG2rAI5jVuGpTSOMgubrGICqrq6Ot7jRa2Fh8EsA7tOltiB7Nm3PEwJszjBmEk27l1hlNnURMynD3HD+Ijen/cTB74hvGdwPWQ6+JaNmmYvsTeqZQvxien9kQxhBvjE49MIst6U+d38xUfQvkeGWB0ZezxUr0CYA8cxbqjryxcVAWsZ8QZmhwFoMLBQYpTXwxXkMnLEqk7b1Ml3czJX257g+SIUrXUbWh1TyQwZGuwS3AliKo4PyGWlquU5biKBrRG1/AlcH/pNmHv8AqC/KvxPnePURWmH5lNeJ4Jc6x3PB/iWJjzGwDK1HVZtxfj4mkleKftmTpdYP98wAotXBLYosvXfzEyWtd6zBVFgXhgvsjOxWs67ZRJAqWqYPbsKixTvuDVSqU5WtHT7Rh7FFcnl1Cx5LrgtwMJK4MKjCQgtJYow1dfE3hT1xTZRUozUOFbcHj5h9WM14riG3S2dMMDGh7LrUtmxwR1FCqBFpv6mV4uzoIrOMdzlb/XULj5PMHmYRMxlW4APu8vehBg2u4q+xhmvQNaFbfqSxvBjWeu41Eo4GLDUG6ooNH1KryMh8/jUuNb3TiyVUli0uKHr5IaXKOkzTyxgCrkLuAceQ4+qYQxgu05mzaG6nqNeu97irydDKjex7gm2AUwizyEBDQdyr53tIK6t47hcM4gXb8So31x1OV9PMZTpn5ozUqamTB18wODcxwjv13AhyM8TGaf7malAdXLW8waVG1ZRcHubYMblW0tWWVNFc4iYa0GxztpxBGreEKo71hjv8JZDjB4wJFCiilcYgiObcLbOssWVmwrWvFRFHPHc3KFcV4ilkTVuldniBW2i7VisN9xu04t1z8zCp80wcVtO3hY+FbW2suodC8+uFl/y7LElwGTj5OIUNwzTL0XL8rguynh/yJCDJyG/JL8N9SoOcNownpg3JobC7Vly/A5Ld9EUrbBvdG4AVm32/mZBvV9rGXWPM7D/7HSuL5cXrPuALqjSrvx8RVh1xXmWLooZP3L23huv7+YunyF25Y7tY4x/sStq+P+xf7jOpTMAPjUAFG17UgOR+1Tx4PsiHLH3N5wGz+2K3vb/UsC+P93FW38RMC/klJR9+4jrMz1Ef/ksCLILi7pSvwkEtV+oKUYhExX/ZQKSLvGDR5hQYV0gqKKPr5iyhZaffEIPMRdKm3deyCtCkbzXEAeVvTtxsooraOBRRlBpa5iNqlmgUOV6YAbTwOx9ZzSGzkbkA0q1jMsUukaRKfman1mDTv1cMRqC0pSurefMUc51T6lph+Yqy82HuX2cgAvhjyWhMdnEu3Bdc3/iLRNDObvW68Ry3DlQrUz1Gd0J4fE2fY14lKa2f77jXQNXYmMxl5DFgD/yK2gOboMS2pATDZFtXKLRR7DyktvaiZrO7iB5gqVM75j0NAJTNhlDnUpStIhsfH7hBYbAORu+IKxavLp3qMoW26HQwtXdm9fxLM7P2lWby4jBV0O+LiL1LFEKAtcCupkFyyEFNsF3V8y3gD/M3zLFuIu98zJUQDfr+o4csvnqVlDP+3FzF3UUD0Usa3U0qGcQIalHKX0TEYrmLaHuGAoZGFeEsUwDJrgVtatLXMoLunVB/UDq13BN0LdBHZQ8dJKoF4Dk6YKoMKA86bHwxDoYewFWiygQjOopAhUM3itVJMW+YoCN1E1NcoI1JCVd5AsDZLwgQDK719TssDfcKhwcfmUUyByvcUyZaozFleM5ZWFKouuPHWpVfk8QXpXQ5uMZpdFvnUKr8GA/Mpx/9dQyubsfMxclTj3KSww3dfuN5toFuOEcps+RIgYcBmQ2RwumDq9Pq4ZPfW/iVZlwyghorWeVfllphwsvJ2eSOwMyj2rxBCKrZTeS7JeiXTjlT1LMfGKYV/D9RZTBovlZf2t9sXAbivL4x+IyYTb4I8RWFDgiwHO4pvntjbL4IIPx8zViZ8+IKAYcBNNltne/iHqraeYkbbuGRkAFQKmXx/wCEGJAAUqyiuGN0KDKOWreMwQq05M8VuFmmNCDs2WJhtFHgrpzBx3Yzh/2IcNGhTKnOJZ+AmhxMm2cdZ6NkBtfKGPL8jL5ypTcrVVyuUZHzFZLNpNqQXAKYlFhMNRqQkZsFZwVEMctqS+Yiw1b7hShbbyzDJp4/qDVv5jqvWAnKG6Wav+MQLjbVvFLF7gFc3zGuaKv+Ne4yaw58/mVLqvxmDvW5vNTOK5fiUZ9dwrAZEOzuvDGyIkToW4Ltm8uZ/BU7DCWEoydaznEqFhZDhSrCaGAigvItUfUBVsw5MsPqLeg0A8IcwbAbZ2a2JKV0q6z6qPEGvXMuYY23jiOUiqjHxEgsODSxVS6/1xoVseI1acG/qNV9/MvbmnqWVRfeZYZ07har0d53mYK8MQXiEBr3CohV8RaHvUIPEo9ydtFt7epcf6FjtzBEqrW/56iwPPk77BitQedcFvHLuUpNusLGXqbqrj5+IYtyz0Jhn5JZIdnZ39zOOAkuALIAyLTKKg00HdwxDaC7BcZJfFFWEXwshHKgXNVzzmK3Gqyqq45ioLVqtc14lJEGtjKHZdLglvGq8nqWbkQs3w3jDlhYWCqsSr9fMSha2dC2Ma6Ko0R28Iv23ALcuv8Afc67K+vU+XzAMuN5JUr9/EWRs2RoIleTvxLqPU8k7qOcz0VHoK17mgY/5GcDFu6BUUp3hlyZoRSgznJhAMDrbnQKVWlAhsnRRdPZfrE8i3408jhiH8J51E/0fiADY6XuK2Y0bDo9xuXwzFNzihu3iMNpPrMQj3/EBX1KD3NV6l6XxuPWLNvNEEFWTEArMwQIUDlhwMYEVw73XuJRafMwVURoVs+olvpWFba2xFSCmgwvFcIKNnWNQo52L73LttAXjIlY+oamwsZeMD9pYxgECqXyMU/saimFy5bmOWNfFSJQN7hesu3FgaIh0NmrHNUtQQ4rEX2XgwJa6K4MkG1Ai8FKlMZGqIqAsCc1gkBD1XQ3z/8AIVd5gQcdFRx6wrStdkEpw31m9zi14e8b3AyFdPiCCZHcyw1Zby8Q7nKVXFffmVbovDrf+YKoseDj5gHKmBNJfLmHYhBuvnmCePjzMf5/5Btx81ADaGHpYwLbWmq8TKvbTbKJfhPnwyywg0NurjAG0UOLOn6mzWpG8JiuOZdXQECZ/qIjpkptVPdGQA6dqoW2CoeBPy1IgNvRZF6fiDC2XZA500wRUlYc892sXz9cQKBko+4dfEtEN411BamAaxVdv/2UG1U5moTUGTUswUnioBV+okVxLEGFmUfHxLoVo0nPgim1IA7riXT0JpG8cXNxavTuMhFgzoRDUO2FFWcqN76hFzXqy6Gj9o1I5YYrdKFQpRVbNLdosRi26wUGt1E4F3pd/wC4mmZpuPhiVRTJkIDwYlnmQoWBWTtABZsS7At6e5xEFju17jxuZFw92imlUvlzwkyWloGVQxmKoIQ484eLQgXwvENQYYSIkXDqpuHV1iFFcNUBfr+oV6tLc0+psnGDxVQlBSOn7haUI3s2ygb8l5iOTF8/3A5+5S+Bn3BcVUcas3cFCitXXcOqgPEWAr05HmKByy8j5V6aqUqxLgaX0hqX3iq7jBp2CLUqFxggIGtFPSVXycJyGYcMLamv/iWbRvZYiVXbmYSrW0IAuirfuUodApDupRxKD4lzn6lifuZRovd/zL1mA0OLQcSxPKKPNG6g9rEoUVB/ERfliFriK5THgmYGC2uoCmlXmzLaXHiDUd+SuphDR4xnmOHV2iWi7oxiIMYTJQGNPGZX1dVL4CxBBFQCI8sskWZaW5hm7zG9sNQXu0y4pN2wfN5gZamr0EQaIgByXeE+JW4jFDbODoS6xttbLrHzFOe4xDaVTw9wT4BatU83zH+DyqFLod3Lgd0CF92jFUhYAqjfiZ80zRRbMZBmnJ8xHIfZnuLwNa8YmQbMOetNR6YQO74u+vqDSitkOx44xMTgFKw4CoKI8PzOZ0VzQ/vuVQdjnt6lGroeWnaYDhLjign8RQcRdvgfE0xIuCblo2R2pr+U6zbnZxOGH5rwjwkAVkNqT5CDhJLQ1jArbvlFgwU03xAUDGxYewvoR+IeP/rCgagt8zJFsrm9viCbL/xRFsMUz/yVqhqBv5nNe5QmW/zCAVFpLy0+8x6+T0f3KeTre4SvM2KjYgEViDnCvEJm8nEFTlYOu8R7NeD+YbVShai/PzH2aS3LP1xAzoxLIZaYluO2ZwhW6N/MNUkhMCjypj/g6uLKus5KYPNnEul2HGGAUDYxfHO5aIqcq/5gEC2fuPZqBusH4LjbzRKpThoe/wD0TtZgcI9wCewkV28wHGItBC9UZhuwCgDL6P7l9EYSm04D/kcpEaLkNtNaj3g2urq/bzGCGhyd1BCUbEvLuMyoABURo/zHhvqtii/pDJHihb7fsJnKBVUAdgiXDWz1V+ahYFFtoYz19QltQxuZwlj8bfzGUGWbY03hdeNLqls69zOFWF7EL/Mxzii/ll02EU/lqZ0RChhrs7li00Vsd5zdxoyuO5Wr9PHX6mDLGc6uGWu1/iEuBxj6jWvk/mX6t9eoIyYINPxPHMb/AGCO4G+mVAP9cM8YjCqmWZzH6UoCmU+rgUTg36IILgtF3lmbTERaWqajGuJxDVC834gQOWUs+UzALxdvgL06Q2CRg5eP+xuIRhYGnqbUm6rOhSVGlJyaFZxUdNbC24MP/BlKz8Sm5YNtMJbWuIN3UFld1xL126Li79YltrUq3YtX3HEuUNvge3UXUGhBwu7PiWQixgafctOYFqNnRc4VVSafX3PLG7vNchKHSA8cuP8AsZvCl3w2y9wyuO5cv65iihxj6lJ0NhxxLItWz2zTKP4B7R+al1jXMYsA/iHtRWG8okzkYPbaIb+fiX/GN8TDeQHqAu1gr4DBNyY9Mc435mmmN5cVqbvAgmXt1DVhMpa2sEMf3UzfxLxWI9aUncyk5ij8R3cmHjcA8s4qCgPZxE1lyQ/OWgepo6MfmJSbP4hXY0DcwK7QmxhJqqtADi4ERyKWCnwjOG42yy6HGGYC2zRUNGnIj72Kq85b+cJA7SUvKftCSmFChxdO1y2sFzwK2M4CcwYmJX/rLqwdfUs2K68w9kV5hoVVWV52xotXiFlwDQ9ypa5pFYtNdoSk1UBF7MV9sUCkW4kHjpqAqpWAUT+TUBgwMNWU8pti4IAK8leeYDL8C7wYu4xHxCQi1hY6vVZPD8yk8GH9zCFgYR5lQnbg/Upow6nitSwwtyO6QRU5qrK6XTqKEXo2xIgRKDHraSiZr+6jPNtHsC7stKT1Qva1kQ5jq63jzGAol1j+YsUbMPT1ArbvqB7P7i8/4ht+SAmmrpzMJluCuAl4/wBuVEpu8SxweOMm4IXrTUVjI4ZuWzmfpzLgzUMsaMC+5SFuskSUYb8+fiYJYVozeYE9kjFBTEvF9pdaCsObXEurBLSaubysZGlKieQNNS/FaOdgcM17S5Ld6Ma0X4FytAWOA9YD4iyWlc5M+LzEWYqj/wALf+cf+r/5pxAFVBCipb2J2PuUxUQCgb7e0ICCQC2afS13LNiSgo8cte5gEDbFlbDLmBqaDFg9cXFomi5LsBWoAgDQyq5whdizwM45zCbcjBj7YddKLb7lSAWjXiuYexRV0He4Jf6b+fUorczOd6uFgYyPKwjArX0DZDFIyzo7qtG4lK/nM0C4NcoTJKHpcmU7wFXEcQ7XxDMVvUsyEUN5VCA6HmP7J7cKr2dYO0+HEzpWYrn/AO9QDlpV12H8ypOAljdTWdZK/wCwmR7uX/5mY/WP9ccbHpUOo4B91DRXEq29M4hs2uoiiaSFYXsV9wAOSnPPzMcwUMGad5gS81Q2e4LFGezTWceYLCAqHBsijsWW+SNkAKM0GMH6XDAlQAHwvLClsOIhjHzBYKULNi6CkbKUGUWCuoZw/wDBhAx/8YpoAySXR54go0MhbxagW4XUwEjZz/YQkxYioDxeiyEri8QGFubiXShlq0ODA4hcNUUdKoG8GazAbPIWCq4acVLmUsWcVkbqoNPSiqWX4qNnj2DBDw7PEeKjBnOep4yptZ2XF2Apy71tlNqjkpxe2IFmyPFwgVhSn2r9wkVEfhMt8rSDbUYVd95YirbzgX/cUPIgniKqyogwBH5HgrxDD+aOOW66mECpziXe9yFU5GoNNXLRE09sCaZOZXpsTs6hX8Elg51+IoGRVa5ZyWLgqVEaqmY9BXfcxidymJ8fnUTNcfqYFbYNRsHLMQWg2Cqc8y+nOnjLNRzg+CNlUq3vjMUpgAJVBUyXyBM3cOhTZJkJmoAw05dBXDEVIxvECmOcwSRjXVlzyHRCpUFAABRgGAPzKLVvZS6IpMIxlwYRlFixQKtkQNjw8JR5TlgXu+sykoltKFtyUNRSENonQLFyTm00a+BhptZmcg0HdyxQylI2HpCAicScZu1fXEu3WQrphdPxCixAF+KqKAGgqIIlCcZjnhYoHFS5Q2S2WjtR9blJclegP9Tu4UGFcD9xoMQpldi/BN1w0g3ZoS5H2CLvDzUC59LbqPplgxbUe2kGKKo1UFynmAI1tl164i6VhswoFtH8Jh3eC5dsjHc2LEemPq36xCYmsBocJ4nUx2Re07f3KKC53UGGmmXXEYBP89Sg3e4iczgalTkzpPMul58TLo/8hAJAABR2QoB0IU550xekQLv1D6AM4nLy1avDhioWFbCu/rzKRaNVU+LfcuWFKHlFfi5RkXV1BfZj83eg1Cit1iwXsgvnJToQoKJhCM2jiUEU0D2aDahLfkqVGxHbFdwV6lUt75/9IsUvGCgmtlddIaBi5NGAwOkxhcoBhw84WrvKgUKwjbboowRuDVBoqK0BTHCNTgQUNdXunqOcSmCqt8Je6a0lKHGatu5fSxQKOcXyvatwvc5Do68zAb1LGwA+YLeDtzDE4LKfEt2xC+3anq4hDD+AzCxtN+qaP0x4Nqy4tpVrEuu04d+pjDJi3ixXMbV12CSHmRDdUyGCveOoIKiyiwM/mDUmhg2tGcQYCJxRQtgdkci5t7yrOrilY1iw4jXDfUW+mLUVnD5ruAbrdmocIqjQIL13CimtwQCUIv3CXddscScI8QIsCzlq4MDliDYvuBTY1cDhzdnEz7LXA5HsjYUbyFaYF7NUNfupr40orlqE6IYEaUq3qWCKeAAxUdyDOAaKWOE4UWK6dzAAAaIeyhgKAC8Y++DUEvboIRpRjaMwuyngAusHUMvNNH7KxEqrN8AeGAumyx9/+VFqJAWi56TK0ZeKmkAhZWsH36mgg2nIuTJC1LACtM/hlCK261mTra/MGKnyAlFW5xqCoOAlLFa2qudoFKcCjxu7u1Age4XQGRB8uJkdKYHDwaxeYYSWG5QaW6aOmUFl+ZbA6UEllNESsZzEOwcm7PUP2rDtIKON9bs18QVjYUfUFhgaAq5fiGXh/AHVBaoeuaCkkasJRCiJBW5kWhBYULHmL5FLwerHeXgQBARy2ttALb5lmiKU3PvFV/8AIkqWjaAvU030iYiC2osavUttJfSIy9Iq4B5WA69w1BfJnsbxA7BAlP4hV0Vm82X7lReYaqrhFhTMKX2IGhYytg1+4I2SnnjeTqJ4WCzTHkrLk7PMQbxE21xDULaIoDLL9ykqkFcQw/wxYaQKbw1cMkY52jA6AOCGndR+MlJ2rFSlgFFrZp5uC1c24RLFfO9QrqGxExh+5c2jhgWDNtbi2XZ4crjiJ6YsFcc/5hKo1eL3B6S6tcAMRF6qdBP1BVjgUotw3xCelYnUtrTF+Db7F0Qcu0NXro+BsclRNrt24RpDXEOvWuhqye8IQ5XANDwxDKS6BD4njbL3LVULR7e3uDdgAGODVxwo19wty0f1LMse9xpDAsXyRKw5bBh2IILV0v8A9lF41rzfiU7hMW3JTDm4tqzpltE+nLf015nKxEFpXQXC6Xp4YleISgjYCiQYbEc+ltt6qMsRl1ne2hIdTjKaxTXQkEqzYuDlxjwh/WXl1CheGwEBltmEwNHGZeRXPDn6ZdzsC+aHlPUgNEKSssm77qVlJC61HVHFsqBMGkR8lIg5MJwQcmIY9p1meE3CWE9aCU5iSjDmo7QqWSZGPMzaVBA7OFE4zxChvrLbgwQbCZybuL7ZFAxddMo20q4azjuGAJo3yUmG5SFGKBW3j5jIFchPGR9y/onINj12biqS9EGuo3rzNrXMqfJNiUscDRJvT7uoxi6tKiqKJcVpIaFHB6xGjtmIrPOYlNkM083sggBakVG9VAIKgsZMYlfcDam+yCZVAC44GL8RTymvuTgfUShcZm1lALEEWtkABtL4qIxHLqi6LicS9YiYNvxakq2LUTTM+kCiVKLalAB6LWHRLvK3P0oc9J8su/mUlXV57T5iLRollhl45ggcobmVb9iJNW4d5/MhpcXk4l4Y/wBZciXr6VmgSHI7MUJO2F1Cqmg8G8IDWo0Iy+eaQlJQqzWYLhSfA7kmaMTeDrpaFgkWc0OreEWmAg2bxCiKStWogg3bWYtRmRibojE3NkFG1GUq8wh/Vab4X3IqGuH8xs1zAi3IA8vXcpSCAi4641VuAe5oLDfSPBLhEayAtnEOKykCzVkbMDcLoHwx+mMMDQ8tnyECkhOKL81KyzDAYAJbD8k7idQGflGBGg+BEAHhGHNi0QNMHIVsBhsitWGgG7lRrFCYfPcUFphEKrJcFrfZyj4jtZpVukxYbjALBTg8jpm5fG7jLRWoNwqx5k0vF+44xnpCXufQkOR4r4G2Dl7ICe1DB62EpylKpUsFK5dnqFElEHJs9JdIiNDoMB8EqwBiKlQq8RdFfRcFBBa/W6btBE6rGHHE2Re9jKGsiRErp0M1ggKBByriC0jEYHs/4QOqE6Y9zNYim1S83wDMRQQWADyB8wEowDVLMnzGSgVCmB7GJSJcFMU4Dn0TN4hMWxgU5q5aegAOoiydb2FB2iEFL6mocn2YwxTknCTNcUbIIbGXe3CoVeXV1FFHHXn2ByssxZUitlijPGXIBoKoP84ihdWgtC9uNRBKlgLUzWfzuMDbCeQ4TiJNwraAToyw+UUALAWr3LpG1a0nKdR/oQ0rIv8ACcTryuqu6lLDYtCCl1dCEdQwyuwquI1DwsfgMkASLUBWeDdJokkB0F2bTsMcxauQPCFdu1QBMOoTjI5pnPWrkgo6AJRFHmq8Kt+0G15SWenNICFTvNDwlfhFwNUUV8aU6WqPTiADVkC3DrCN3VPEDqMqk3eO4MCYtd83CRiXZ3XiYzVBuC+QjAN1NAN/MuKyb2svUFV3DXi4LsEUeTzAcVV0NH5ln85E38Z/DCFU8RNjFn5nAZlwaWewqoyQKt100mQVaIBiJ4DlBNnzWSjTcjLBh9AYAthMvcYsqSRABWQDAbYGKqWJh8xBbUxbQwaaygc7iBxLAk13mBYugopVgeUuINCMNKOFaXo5ReSzcy2HDZ4Ip0drCOLshb2he1LBvcuUVZhg2NXygH0oJ1BLZuNhxUcdSKrqRF7DIiL9KHGllY6BH/aCjhKMUaHQ1pfkM1K2OTlkOzVbL6CRKr1jFjAw0dfxTiWFWqsU5NrGYBoWxg2guTEtYGwCDY3qcKDWqsCLowyCkWOKZJpELNjMJLSDNK4piVyiDZlmgfHQICwKvU4ervEXhPV8nyymjY9hK+o5KVlVMeZ4xV1Wb9y0oDQdVLKa2IJiD8KkQBwQ/WAip4TJMVbiqLL0XYnYFwzTmJURioTJAkigscEg05zCJ5B9JsN4EJAFFekKZaby4wWVt7g8UbUL/oplI6Ud5G4MuAKWz8u0GEjrIXeXUAxBhtz0AhWKEciNj6ZpTllHc8iPMRrI9wFZaOauWNQpsjImTHEqq1gy8O0Bq282B2U3BjbJaIM9VAFaBqrrMbJA50/ECrQrKl64Zk+AQWJVekJvwzNBt8DcKOvR1gUhPqwtG+xxG7lYqIEbbY6YaMpf+VDOZRzxgDzF3kxC6mtpvDYAy+4to4CQhqHOuKRPKTcqeFOTveWcxgNAq5torkhVZawaFUKEEXdh7XRUwZTnpZpg0mFszftoq9L+ykA7zr5sNs5ISZgzykXKW0NvN2xWnpeyS6q3N7U8eulxmempRKTgYGgWUarlvQulmiwYJEhainbueSdq6hWBIst0qZIDgNzm7ZKsIFqU21di0LLuAqgMYVzTLXlB6tuIjuYvTaZeBlRdnFPUrck0zkHb4i43KUAU9LGYoZhdPaJSNKdM49wCjsDPzAEfzJxHlfEpCGwG0xUUavA9ukwDrQeIYsId0avo8ykspihoIotx41UP05naloceYILMLa2CIqzjkJnOsTPurirklRZevUChVYl2gQ1jXRtdDtUzBfM2kuoNNABY3KUTu4la3CwGfBMHcwnPUx6kWuE8MUmA/qUYNu5QyK6qOMKjEEUha+ZlZPbtn/YTHglCp5AMOKApHeeUv5ihMAuew0flM8GJ0B3SUbRcIAiciVntxQNyFV8BZQ/sLEqjQmBuyAgxVoHgqoeiIlQoIWCWVZzcP6Z0SS1lckglF1MxahZTgkUO/Qh4NvDNEVKwhrdhprm4b7TSZlwA8IiXobBSqVygUZcEDTQGxSnmK1KUlKp8AZfJNsKy4TCdxfjA2LrqYIFdcs6qWWssF4F7CExQKdcDHcqnazX2ohyw7y+UVplENUUE1ACghRSIqyYi9FVsGuODMSlrcNkreFAarKcoUo30ECYqBmhNv5GAoqFjKsIQ74jSyYAEcEByjKxQKGTHYQSapDdJe8F/cdzuNOO1ahB3hYmRO4Yro4Ovr5i4wReMFx6vTAOYtN3KdR7uABVyS/OIKAPhQf8AY1l/jiIF0uLgtVdfMcAx18SgOB3qVKNli0LNXlAOVeibh4TcptV1poiCUgZuLMrLBJQVDRSvIdvTIyBlUTerFmCKYDryGxahWeDG8yL4OYaiG0GWjW+QtMfUQEK14DQ5CdGEpiy7amI/Roky2uRFCnqoR5DiGxNX5Wj3k3HS45NeI86PTJwIghS22gazyIwourvMdd4izQ4gVpfUdlZ6oi+B+IYnIih9VLNG8NZgbpxqDQLA3VNgq7lQB5UC/bzL2hK1yq+eZjKMFNC/H9y5uhaqFeaoS9OBgqnWS9zJHXahfhAvEYYCUcioCa4wIXcYXjgkEES4jgd4JGDDVOudYFWyaZKXIpvV4Tks8kQKzdQKfTMBhdKacFwVIhcKWCs0TU22vA0lHAq5S+hqlxIDRXaqQU7qgARAsQDqBMu1RmdElAieQBSKhgBOopzpzA1PYLNDhHf1Le5cYzCy5wmTmORYKsHqK1qkstbpbxcqODBaQG1yigcHFPu5jAbQHxbmD5RrRprcDxVrE1UssDCsWdJMb4VOp5nVVLrWfEalMbmMzvqXVHmD2v7gbaJ1cLjbbRWb6CLcuaDoUmcKC5RwzSmSSgCJDTAdLx8FMSgxFNlA9r4AIILEACZCqyq9cpsMlBW1Aa512wQCWLi5FPBB81KJ/wAhgbgXKAyq1ZAM1Oqtu5EahAJ+6q5B1byjJJospkrWoXkYHxs942lQp6HoPrRIgoMhc/FoAgB1VEoZIDQsX0JluMBJCbdwINM7K0YEm5tSFLYMeSqDMNikEDm0SChEhA91HWVQRpu4qJBAct0Q3gjVSsImtIFI9QIuqpsgHUzsALELOSAQkN2DMNlUVhDMGxph1Nw6NygzTA02jTSWnVK0ox6LGt2UBDaMry0ZC+alqy7QTrzbUhUIjtBFW3AQU7vQlukJqOSg7IZCwRkvVZvhRSrabVECDd3GFJcyqO0F7BgxZWszZuHiyy+OzfFGYqBTuVpo26aElT7AWLT8FeYFeoTA5t6i9oNUFHZzFnb7VbDXgIgkys2M0gIdil7tjSa79QZjFBS2moMUsViyVw5gc8Ne1z+ZSVUCtU9sDVVVBumECpsWFeIpOrbv3pJRxvkmRL+6GmQ10n2Fpv1GUDOPuYaPgezq5kKPf3Narax7gl4+9xwmq3EtCIwB8TU5oA1oAEKENjp8xIgPQbuJWd1xmXE/NQ2EIzdYJGCNEZje1eqQ2kWMgqGOTnZyg6F3LyKn5Yii4pAC1VgBymyheANZZG4HyZaFvNQEGv4MMMfaseOAlA63bFwu3vLST1H4ajwpvSxndkjcX5tqhTtNY4FFLt+wZ4qyiarUtk2CECshFT824VwCoO1xVQxCQ3jhmpq+y4VIhAtjN1K1jYMUcK4BetAdhDXbaNWlFIiTlSOIhEoDgXJzfgKKNACosRkbSfZsrNqhHgZIyUtvT3FBrBRHTWT4mHOmopgACgbaZCsiEAFS6rhFFVCLIt/bVEm30hUoYVmgDtxVDMcptSjTaqscNv7NCwwo4TMbWI1Qgre4CFxasoxGiZs5QFYE5tTiz8Ix5AUg1t6wNSv0ajAAIPVC25avA/tLQjqawAK9UhRjrV8C6CPmyFN23AwrJwLWsg8YiBaURjLmliKgJAKryriC/wAUwS+BxHrgXyGzuHeTju65lSGtPOeUar5NVTjHMTwuk8x1HE0LrxLgaO+mbpDj3OQ/1lJdsaDc00vKFX1XPxOEVe9G4jZiNi99RKj5W0HleAiziKtzbEHTEkruLa6R/ghJTccxWRrrVIx1msiumOGpcrZK5EWNuXysp0yzbEfO628QBVhphNleuWFDBs0RZs4ExdkkRjVL5SR1j47P1h4hWZU1tRLYiHSYe7AlbWku9sXBGNgtvMFTd9miscAEnZC8XQHBWuL00OLcOkMpEIeOZbR5cKQk45ovAiJp0V4QYDoSwX0Wyt6W7KnK8/HNfN0VwLqLEA7Drkl1mq/BAu7RWl2NKSk1sY81D/IXFyGkrQsjVZ4j21CtsbF7EAuYEFZ3ANXCyoPi1T+Iiw842xrBzHQtxFXAD64ZoNkyF4b7kiMCZQqtovyIKK5DmSg0rvFDCUH+AGoBN5TeBLKekWWAu0puIlaCpSrSEpLRMgF/YiiEqEwNZTuOFOACbfMR3nFYt1XVzHJOArOy9IIqw4R6PaBxkTVA9EKls2ARTC4cMPzLWIMBfp6i6ymbD9kBOCA7s5qVy6RwnmZ7WwvD4jmQi7MJHT2ELVocTid98RIHhfaBMgmwe19/UJUM4fyf3BQNd/4jIVhdvY9zXzEZifhQG1BCEAA0IKBFfxL3n5dTJ9t2QaPwGTDNQyVbqnRAVZqF4DSRSB5NxprGiH01IR0WhPQpfTTIEtTBN3MAMT+WKb8mbUrPIuPRQraqVgVdcsxAz3WPuWMaH+4jk8DOWufclBbW3zn8wpv0jZ1Az7kReblz0rYWAML0TsnssbeYCI70i8YqfiH9U56KQBoq7yS5S4jWFtHa1mMcQBQNrK5RCUCv6KKZxx1AI16uJvxT9yhFEoKsd1WYsmFqG81fe0PiMHFMQB4p+mXHTG5fE3qWqnu3cuEcbKj1jLcITaXhXSqtXuKYJygaq9OKZpQBCgM1K8VG6yuBeAl9epTbK3Nj1KjKF33fNEqi3tKhsss06qJbN5sAOoCZuC2lFFVEm46mwpHkpit8iwAN0ZkPuBsByP7h0WDYtMNS3I1gqh8Wxc7XOufJCLhq8EdkEIpNrNJx4gKJjbC/DGrobo8tx5lLg4s8zPTU1V/JCN1iX5haW9wTT9Fy9HNbjnCu/wC5jCec8/c82THEs5r3FTWR5AFginJqQUI3N3Y6LYGj3UJVBuhZnzAoZKllxVYkNkEoPV4Hp/ZYvBi3pupWGyNgflyCEo5RwLi4tJSwpnydDoPIgk3KJfmzGBdRcrtXavMUsSbYNhzCcycq/QmSNHbgK+cxQZg7tq9s9amSKSiwgWlUKY4JQ22lHrUBe1mgyqI+4RYgM6BfqUWceApDvzKSG8CctZIilsGqqcP4i5BXk2FaeYVSvIUPdmZS7Y3TV7AG42SDZRjd6H4liTGd/wAJuJTbkgoGzyyxdQBRjt4ITELAJYv6xF0sYgPI0wQYmKmi17c8y2a6ki7vI1jMs9kzu8YYlzqvEBTrghlZIDbSoYSaJjUtBlkTNKhZs26N7SjhVcFNCONQYDeeMtM1nDuXP0tS0vQwwO3RyPT4htTDyU2PUFKLy6hGMyzNawPiVyvssrzfEQU+UtHWZkziaN31DJZKWtxFXFrUL3CaFkxWMR2GmEYuo98xiGG/iEVycXHlKZyxqoTr7lVYXXjmVtff9wN1sfy8spBkXolNCUHECt0xL7GXO6HKeIOzQO3co8jBtcCrCLPKjuTWorFbeW4RxcsudfMN94zf63JcgkBtCj57TMWVUcCvRBYMJRtt6x5QkGqmiNU7hnjBhLyG+BXzbHVC810PYz2QImnM4RNh3gulsljeewWfuUtxXawW6vPdoPRhC6A5X/YjcmzjYg8HqVJWOF4eWXvsIt28rRCpaWa7QkuIwyksHdLb7icaYRw4T4gnJTRTTuuCXIZdpXdfYR2lmQygBwYjILxdCqp4NyiADWffeL4rpil1eEGfiUhht1E3ZkY2rYdqyOqiMKUmzkiWG6VZtjNXHMeZBcDkWYalQCK4AjXI4Qwh0SkNNWJq2MsDyBjCsHxxKe+b50mDg6W2q34hvVtAApdQBLKHyJdoStNSiOFiVXqFK2Rl8cMByjyhG+MDdwbq3odkAq8DxMRqAp0kszsbeYILcCmq7iTWxWfUpA0mzubLcCefE0L94YVv+ILatwsRdRYVJdWnd+LQo1xTWgUS16DiUUn1FaOwcrgtb9IxkUn6Q3oO9wYCczGGSl8vKikxaES8tajtVLJVoEUGhl6s8R4GB0hAM1dnqoRYynAryWUIKQQNmAIXgURFbDW7dv1KrMi83bgZPiIyiKCiucdRCQxKYB8SnHJlBBi1a3B0pr8I6gaDa1MAK3bomV4tc2mw8qgPMTGpzWSDV0FApq6EA8AoWYL/ADDJkxrUFbVKdHcVNvFZFr0taQVJrbVgpO2LCBhMCqCy8MIOLO7prVtChmDR2lW8wuxYNjDJuDbdxTbJbX7EDRrCYsBymQMdzPaWjADZcrEZbCOZmsI7CHNXU8BziG+ziy1fo4QvoolA06tjY54cYrnrxK6mWyWy7W4AOCTsYxp1MXQIqqjszphmlBn0pX4qV+lOByjzGE47wHwx3FSqN2+Zt1GxxSbIMQL9PyPMdayfbB5GcwCeDnpcubBpgFnFh8MvBd5PD4jHQ99xOl+PUsAVDuyLOA5jG9/7hdPE4mPermnnNzC/i5pe3Huv6mbe6mFimOWv/s6b5DF0/FSp3pjED5yJcHM8aF+9jep/h+c7GunfxUptVmvgXculrN5wasO/X8Jf2zMmKhUsdt3SuYOM7r43dfFgeMD2OX7KI/waHSFPDBoyrXawbyxjVv6Arnv5i2nybloLM8gQThYNtA/OtlJbiLKGnjvE4up5F3zrNCxCCYsW8ZCJZjFnko5NW3BV1FOay64A15wJS2itG94sr7Umkq2jR4mkDFsXhzTxgxt9FbGayrG3S4KW5GsGPm0lMkafciouplftMaes+x1PpMZ/4+4MymlUAOdKVipU3Zd8i9H5T3T2v5rxAZulOYjpuUlVJR5F78HRF/nbPpwQpF+IBfzqAbjtnFW+VnKZ+lvxN1HEKufNM4QwhTwGb7rMzW5WqH91U6ppm8fqalW3Zv4smHZvoG5h/t3NJXFTT1jx1NfgVP0i9TAq50lUfU5T+l8ylrmTtH7eJxP/2Q==" alt="">

SCSS

body, html {
    touch-action: none;
    content-zooming: none;
    position: absolute;
    margin: 0;
    padding: 0;
    width: 100%;
    height: 100%;
    overflow: hidden;
}

canvas {
    position: absolute;
    display: block;
    width: 100%;
    height: 100%;
    background:#000;
    cursor: crosshair;
}
img {visibility: hidden;}

JS

"use strict";
{
    ////////////////////////////////////////////////////////////////
    const canvas = {
        init() {
            this.elem = document.querySelector("canvas");
            const gl = this.elem.getContext("webgl", { alpha: false });
            const vertexShader = gl.createShader(gl.VERTEX_SHADER);
            const fragmentShader = gl.createShader(gl.FRAGMENT_SHADER);
            gl.shaderSource(vertexShader,    `
                uniform mat4 camProj, camView;
                attribute vec3 aPosition, aColor;
                varying vec4 vColor;
                void main(void) {
                    vec4 pos = camView * vec4(aPosition, 1.0);
                    vColor = vec4(aColor * 1.2, 1.0);
                    gl_Position = camProj * pos; 
                }
            `);
            gl.shaderSource(fragmentShader,    `
                precision highp float;
                varying vec4 vColor;
                void main(void) {
                    gl_FragColor = vColor;
                }
            `);
            gl.compileShader(vertexShader);
            gl.compileShader(fragmentShader);
            this.program = gl.createProgram();
            gl.attachShader(this.program, vertexShader);
            gl.attachShader(this.program, fragmentShader);
            gl.linkProgram(this.program);
            gl.useProgram(this.program);
            return gl;
        },
        resize() {
            this.width = this.elem.width = this.elem.offsetWidth;
            this.height = this.elem.height = this.elem.offsetHeight;
            camera.proj.perspective(60, this.width / this.height).load();
            gl.viewport(0, 0, gl.drawingBufferWidth, gl.drawingBufferHeight);
        }
    };
    ////////////////////////////////////////////////////////////////
    const Mat4 = class {
        constructor(program, uName) {
            this.u = gl.getUniformLocation(program, uName);
            this.data = new Float32Array([
                1, 0, 0, 0,
                0, 1, 0, 0,
                0, 0, 1, 0,
                0, 0, 0, 1
            ]);
        }
        identity() {
            const d = this.data;
            d[0] = 1;
            d[1] = 0;
            d[2] = 0;
            d[3] = 0;
            d[4] = 0;
            d[5] = 1;
            d[6] = 0;
            d[7] = 0;
            d[8] = 0;
            d[9] = 0;
            d[10] = 1;
            d[11] = 0;
            d[12] = 0;
            d[13] = 0;
            d[14] = 0;
            d[15] = 1;
            return this;
        }
        translate(x, y, z) {
            const d = this.data;
            d[12] = d[0] * x + d[4] * y + d[8] * z + d[12];
            d[13] = d[1] * x + d[5] * y + d[9] * z + d[13];
            d[14] = d[2] * x + d[6] * y + d[10] * z + d[14];
            d[15] = d[3] * x + d[7] * y + d[11] * z + d[15];
            return this;
        }
        rotateX(angle) {
            const d = this.data;
            const s = Math.sin(angle);
            const c = Math.cos(angle);
            const a10 = d[4];
            const a11 = d[5];
            const a12 = d[6];
            const a13 = d[7];
            const a20 = d[8];
            const a21 = d[9];
            const a22 = d[10];
            const a23 = d[11];
            d[4] = a10 * c + a20 * s;
            d[5] = a11 * c + a21 * s;
            d[6] = a12 * c + a22 * s;
            d[7] = a13 * c + a23 * s;
            d[8] = a10 * -s + a20 * c;
            d[9] = a11 * -s + a21 * c;
            d[10] = a12 * -s + a22 * c;
            d[11] = a13 * -s + a23 * c;
            return this;
        }
        rotateY(angle) {
            const d = this.data;
            const s = Math.sin(angle);
            const c = Math.cos(angle);
            const a00 = d[0];
            const a01 = d[1];
            const a02 = d[2];
            const a03 = d[3];
            const a20 = d[8];
            const a21 = d[9];
            const a22 = d[10];
            const a23 = d[11];
            d[0] = a00 * c + a20 * -s;
            d[1] = a01 * c + a21 * -s;
            d[2] = a02 * c + a22 * -s;
            d[3] = a03 * c + a23 * -s;
            d[8] = a00 * s + a20 * c;
            d[9] = a01 * s + a21 * c;
            d[10] = a02 * s + a22 * c;
            d[11] = a03 * s + a23 * c;
            return this;
        }
        rotateZ(angle) {
            const d = this.data;
            const s = Math.sin(angle);
            const c = Math.cos(angle);
            const a00 = d[0];
            const a01 = d[1];
            const a02 = d[2];
            const a03 = d[3];
            const a10 = d[4];
            const a11 = d[5];
            const a12 = d[6];
            const a13 = d[7];
            d[0] = a00 * c + a10 * s;
            d[1] = a01 * c + a11 * s;
            d[2] = a02 * c + a12 * s;
            d[3] = a03 * c + a13 * s;
            d[4] = a00 * -s + a10 * c;
            d[5] = a01 * -s + a11 * c;
            d[6] = a02 * -s + a12 * c;
            d[7] = a03 * -s + a13 * c;
            return this;
        }
        perspective(fov, aspect) {
            const d = this.data;
            const near = 0.01;
            const far = 100;
            const top = near * Math.tan(fov * Math.PI / 360);
            const right = top * aspect;
            const left = -right;
            const bottom = -top;
            d[0] = 2 * near / (right - left);
            d[1] = 0;
            d[2] = 0;
            d[3] = 0;
            d[4] = 0;
            d[5] = 2 * near / (top - bottom);
            d[6] = 0;
            d[7] = 0;
            d[8] = (right + left) / (right - left);
            d[9] = (top + bottom) / (top - bottom);
            d[10] = -(far + near) / (far - near);
            d[11] = -1;
            d[12] = 0;
            d[13] = 0;
            d[14] = -(2 * far * near) / (far - near);
            d[15] = 0;
            return this;
        }
        load() {
            gl.uniformMatrix4fv(this.u, gl.FALSE, this.data);
            return this;
        }
    };
    ////////////////////////////////////////////////////////////////
    const gl = canvas.init();
    gl.enable(gl.DEPTH_TEST);
    const camera = {
        proj: new Mat4(canvas.program, "camProj").load(),
        view: new Mat4(canvas.program, "camView").load()
    };
    canvas.resize();
    window.addEventListener("resize", () => canvas.resize(), false);
    ////////////////////////////////////////////////////////////////
    const decode = () => {
        const img = document.getElementById("heightmap");
        const width = img.width;
        const height = img.height;
        const cmap = document.createElement("canvas");
        cmap.width = width;
        cmap.height = height;
        const cty = cmap.getContext("2d");
    cty.drawImage(img, 0, 0);
        const hmap = cty.getImageData(0, 0, width, height).data;
        // brillance
        for (let i = 0; i < width * height * 4; i += 4) {
            hmap[i + 3] = 0.34 * hmap[i] + 0.5 * hmap[i + 1] + 0.16 * hmap[i + 2];
        }
        let vertices = new Float32Array(6000000);
        let iV = 0;
        const face = (x, z, l, h, w, r, g, b) => [x,h,z,r,g,b,x,h,z+w,r,g,b,x+l,h,z+w,r,g,b,x,h,z,r,g,b,x+l,h,z+w,r,g,b,x+l,h,z,r,g,b];
        const attribute = (program, name, data, size, stride, offset) => {
            if (data !== null) {
                const buffer = gl.createBuffer();
                gl.bindBuffer(gl.ARRAY_BUFFER, buffer);
                gl.bufferData(gl.ARRAY_BUFFER, data, gl.STATIC_DRAW);
            }
            const index = gl.getAttribLocation(program, name);
            gl.enableVertexAttribArray(index);
            gl.vertexAttribPointer(index, size, gl.FLOAT, false, stride, offset);
        };
        const increaseArray = (oldArray) => {
            const newArray = new Float32Array(oldArray.length * 1.25);
            newArray.set(oldArray);
            return newArray;
        };
        const concat = (a1, a2, index) => {
            if (index + a2.length > vertices.length) vertices = increaseArray(vertices);
            for (let i = 0, l = a2.length; i < l; i++) {
                a1[index++] = a2[i];
            }
            return index;
        };
        const Rect = class {
            constructor(x0, y0, w0, h0) {
                this.x = x0;
                this.y = y0;
                this.w = w0;
                this.h = h0;
                x0 = Math.floor(x0);
                y0 = Math.floor(y0);
                w0 = Math.ceil(w0);
                h0 = Math.ceil(h0);
                const n = w0 * h0;
                let r = 0, g = 0, b = 0, l = 0;
                for (let x = x0; x < x0 + w0; x++) {
                    for (let y = y0; y < y0 + h0; y++) {
                        const p = (y * width + x) * 4;
                        r += hmap[p + 0];
                        g += hmap[p + 1];
                        b += hmap[p + 2];
                        l += hmap[p + 3];
                    }
                }
                // average colors
                this.r = (r / n)|0;
                this.g = (g / n)|0;
                this.b = (b / n)|0;
                this.l = (l / n)|0;
                // standard deviation
                let sd = 0;
                for (let x = x0; x < x0 + w0; x++) {
                    for (let y = y0; y < y0 + h0; y++) {
                        const l = hmap[(y * width + x) * 4 + 3] - this.l;
                        sd += (l * l);
                    }
                }
                this.sd = Math.sqrt(sd / n);
            }
            draw() {
                if (this.l > 1) iV = concat(vertices, face(
                    (this.x - width * 0.5) * 0.1, 
                    (this.y - height * 0.5) * 0.1, 
                    this.w * 0.1, 
                    this.l * 0.03, 
                    this.h * 0.1,
                    this.r / 256,
                    this.g / 256,
                    this.b / 256
                ), iV);
            }
        };
        const rect = new Rect(0, 0, width, height);
        const divide = (rect) => {
            if (rect.w > 1 || rect.h > 1) {
                if (rect.sd > 3) {
                    const hw = rect.w * 0.5;
                    const hh = rect.h * 0.5;
                    divide(new Rect(rect.x, rect.y, hw, hh));
                    divide(new Rect(rect.x + hw, rect.y, hw, hh));
                    divide(new Rect(rect.x, rect.y + hh, hw, hh));
                    divide(new Rect(rect.x + hw, rect.y + hh, hw, hh));
                } else {
                    rect.draw();
                }
            } else {
                rect.draw();
            }
        }
        divide(rect);
        attribute(canvas.program, "aPosition", vertices, 3, 24, 0);
        attribute(canvas.program, "aColor", null, 3, 24, 12);
        return iV / 6;
    }
    const pointer = {
        init(canvas) {
            this.x = canvas.width * 0.5;
            this.y = canvas.height * 0.5;
            this.ex = this.x;
            this.ey = this.y;
            ["mousemove", "touchstart", "touchmove"].forEach((event, touch) => {
                canvas.elem.addEventListener(
                    event,
                    e => {
                        if (touch) {
                            e.preventDefault();
                            this.x = e.targetTouches[0].clientX;
                            this.y = e.targetTouches[0].clientY;
                        } else {
                            this.x = e.clientX;
                            this.y = e.clientY;
                        }
                    },
                    false
                );
            });
        },
        ease(step) {
            this.ex += (this.x - this.ex) * step;
            this.ey += (this.y - this.ey) * step;
        }
    };
    pointer.init(canvas);
    ////////////////////////////////////////////////////////////////
    const run = () => {
        requestAnimationFrame(run);
        pointer.ease(0.02);
        const rx = (pointer.ex - canvas.width * 0.5) / (canvas.width * 0.35);
        const ry = (-pointer.ey + canvas.height * 0.5) / (canvas.height * 0.35);
        camera.view
            .identity()
            .translate(0, ry * 5, -50 + Math.sqrt(rx * rx + ry * ry) * 20)
            .rotateX(Math.PI / 2)
            .rotateZ(rx)
            .rotateX(ry)
            .load();
        gl.drawArrays(gl.TRIANGLES, 0, numElements);
    };
    let numElements = 0;
    const start = () => {
        numElements = decode();
        run();
    };
    requestAnimationFrame(start);
}