2.0 Auxiliary Vladimir Jankijevic mail@jankin.com http://www.jankin.com Simple shader which traces reflection based on the normal of the current intersection point JV_NormalReflection 5 NDgyAAAAAAAAAAAAeNpVUF1PwjAUfXa/4rpXs66AH0hGkSAaCRgjYHwjdStQ 7MfSdbD9e9tMEB/ae3rOuScnTQaVFLBnpuBa9cMWwuGABMllFMEzU8xQyzL4 qmHOZS7Y52z6qFPYMpEzgwDGFUtL75hpBZNSQQdDq9XrXPduMCwXoyvcxhjc 6fqMvaAZhyhy+VXBV2suGNg6Z/1wmGVavai1DsErpzq36Aa57TuEu+37EIpa WVqt/rUlwUUyci032nBWkCQ+ezjpTVD7pI30yh92woJbwRzZTEcMS7vV5pVK Rj58UckNTKj65ju252kSn+kn93hGuSDSXQ87b1Uo1fJobURfT8ucqtp3+0WO XL5PydbavBfHh8MBna97yTmmVG1KuvElT9DR81JKanzaEfm0ojE2M0ji4weT 4AcSCpuW OTEAAAAAAAAAAAAAeNotylsKgDAMRNGtzJ5cQU2nJNCHJBG3bxH/7oF72Lg6 EVoqHY+aKNKLMOBsnZK2Js4SrNiRSszlo3Ss9klud86EzaTH/19r8wUX6yJC MTEwOAAAAAAAAAAAeNqlU11r2zAUfbZ/hdCe1cmyHNuEPcgfKhldF5K221tR E7U1OFKQlW1u8X+f5IQNr4U8DIOR7tc5956rD2C9rK7ApVTSCCu34KEH39cL sH4WW2nAt+ZFmG3oY8I7abpGK/AJQHKB/Qfn4Uo+SiPVRnrza0bKGaY8QqzE KaI4cifGUpRFMeckyVhNyOCylkbvpbH9WloAP9/dX2uzE62r1cqNdRj3+05a GL6GwVIYsZPWUYH6YCFwv/3BhoFzBZe3i2qEjWcxI2mMUZ2RHNEqTlDGeYFo XNR1yWhMqtzDBsFNv/dMN7rVxt2HCUCjrFRdY3sIGvUWpcjSilNKUcSKCtGa 5YgRTBGmeR3HCeWkiiYo3Ua0wowG+csejHhovVkrb7oT7cHfogv8hogax3Hf /Wzs5vl9MjGnOa1nMxTFiZs0j2LEihSjtKxnOKdFQfiUzIPWrRTqDJvxNoRD GH6RVpyW4F2FHFUxKnTtWHtK7wR5/BO8HTGlM6ykckV92Z1UVrTAiB4euztT KuBNK8/FfN37Y+dOvmIAfxy3FvpRe/9w6q+Sj+LQ2s638Ef4KY2/++ATbxcr oZ68w20+uNEn5YJS73ZCbbtRFp6UacLd2hOOExRFlZOF5QnCmDGMZ1lFSjzK 4mhMVJ4iX0rt5mv6jwtHwex1658m/B801/GV6N3rAfDUOZx0Pv+Hz9xnLNvD U+Mf/HERfMJ5CYbwN8cGPYQ= MzgzAAAAAAAAAAAAeNqlUMtOw0AMPMdfYal38gFBSFD1EVRaKamAW7TsOoql zW61cYUC4t9x9sAJTvhmz4w9nrLENe7JOEq4ZU+4o0DJCDl8m/G1rbEdMvjC HyY5gBX3wVGPj8/d8dQ83R+azfawWZ/r07Hbw0ohDvQHquJg/dUR3k55681w B1D+s3QBnucLYb7NwjEAiA4Wm5OkqxX4hGLk1hpvUlEUHITCxDJX2qj6p19Y DzF6MkGRENNofDe9s9ihyswdxZEkzWWtknSJfkkKvvK/md1Q78kuHjqp9GEK jntU5e+JfAOkG3Hq MTE3MzQAAAAAAAAAeNrtWltv2kgUfqbS/geE+tCq4p42tAlbEQMpu0CiQJI+ RIoG+xBmY2asmTFN9vLf94wvGAjGTpMm6S5SHuyZc86c+3yceP/zzdTOzkBI ylk9Vy6UcllgJrcou6rnzimz+DeZL1feV3Kff/3l1f4ZlS6xB8q1KD8W/A8w 1S+vMsHT8NaBes4nyRrv3uVw6ywU/bFQKumFPpki0W9nl30upsQ+gbGNrEiS iwQdnnaa9dxf1VqrWilXGvlGtVLL7xjV3fxBu9bIt3Z3as1a+f1Orf3xH802 JOIKVFug6G9cXM/PLFfLpd2KpkDdM/vHNlFjPFXqt+hVvwRqocFVjz5T9DiK Syz7Q87tNrXBfysuvxqcjemVK4g2JjhiaW3hnCaM3Ku/o9MyR65yXNWkAq3n 4raeK1x4NP5uhykQU7AoURBHs3SUH4lKyD0BQRVY6F0HhLodTACUrOdevzkz OkwqYtso9e2ZEbi/CWPi2kpenDpXgljQFnx6ZuyWCzPpoAjpiz2VcDTutY16 ruQvNIbdHmV0Sv8EaZy4bEin0KUjQcTtqSRXqNCY2BICdSdEEBPNGoCaa+o5 zXez9xR4SysGBy61rdYMmNLbPn0xlsFwpeJTjycN+ddet0kUOQQG6EAu0vCc w2gAYkZNQLfd3N6Lt9dpdiM6THtAx5ogJRfofHSil0P13GWzdXB6GFD1rjGs 6FCDTx2M8shGUUq4gUMzA9dxBIoYKCKU6xwQhgotUfhl0mIzKjiboiexQsIt TJggVr6OQW4V1xRqQdmjgO0LYHoIXQM+V2JYulp5JF/wUqZhWZ69xD5yAruL nezrN18HnUHz98uTo6Ph2wvKTNu1Qks0IeaZl+vz/FsQ1PGpw1qh4GX7osDi ssDYCJx3+tXKnh+HvUt8ax6dDwKmAyKpiYmOuoAxAfMa6avBXrAc+DRax6rB s0zfC5bvv8iCO1vatZuD4ZiT0HwpYYpZIbpUKuzfXW4GDgr5Q++NdJUvi54r wLHkp7oY0DqIIrtCd04E00fADOzIuOQU9IR0mG6pnm5t76Ge20msGMKwhVgn ILkrTLibRvGs8TwpC8/AZugKlFUuVatJp6HILmXXqTuVJo4phyY4wCy8jr38 lROdEAWbhsXn3xl+GNdlhmWHIvUZWBICdNETOyr75IBF2gSpvKmmULciU/mb 2ocwT4KuCKtxXzpjIelGQdIl5Lw1mhswGtxKBdP5HZI5IQha9CVk6QxG/bWB kcn6lNYNmK6WhMHScVrqIp2pw4WaF+4mPaJY+K21R8wJZTA/LD7qDR2SVDcF YXQMMlUqfW0i+TWkIT2QZlrS9o3BnTSEDcdB5EXHNF1ZHnOp4i/1/eISoNkM p07ABox1AqAKqBIg1RLVFlT9B0FV/xlBVZBdPwWsChtqh9nY1Nou89Rs3TiE BT+vfjju6q/FXQMlEHsco6ner9SFYKyirtCEFiMY2dAED7XoBrzKPhRA1Lmu okvVkDrRVSco+4Uq+14Mtyn26VBcKGEtjlvZ3IDkVii/E8u9GKzW/8mwWqFQ xL8RZSFWeqngLQaXbczjJ0VmmzTZYrOXgc089Jy9+bCTZtyFZGkmXnOyLT7b Dr0ef+iF6fXSAFo2Wxw7nyQCH1O9+BlYKWEG1ubeDe9PA5gJHT0G6nLuDEzu LMf3IeOyuDDeY2KmRcQPzRZ2k+ZmC6Tb0dkTwLGoonoN40un3/rU6DXDWyMF bMuO3PEYBJ+BGNv82+lPMnbLR2n24MlbbPk8/fAtTpVYjFfaYrxnmL+lQHkB ZTLOWyXcIr3tJO5HTOJeItZLgHr/v7ncjweMCdlwr/FcLGi8u588pHs4cNzO 6bbAcBEYbp7qvQzUl6DMFvc9Je5bWfK/dsNogMDyCL+FW3mffxbnP3oHYFBR wAyOiZqsrxDTcZaQkma9iznjvqELuBZt3nwpx4xQ7jkI2bvsHRiDvddv+jyA om9DQZs+EAoDVLxjZBrj1/zH+6HmV1Ka309r/sMsXDs3vr+N6zr/Krx6ljyY n3IPcPMoOfMsPn305HpEt/nrG5tV4WJdu5osNKvvFiIdy14rx3/y2+mhzUf4 49Jfjl72i2u+x8b1fwH84TAR NTgwAAAAAAAAAAAAeNp1kV9PwjAUxZ9dsu9wgZHQ6Nj70AT5IxmiJBsoiTGk W1updN3SjQf99LadIJr4tPbec8793bXTCg6VClIugxzvqeu4Tgce9IlxQWFG JVW4pgTSD9gkESQ7TKiCZ/6JFTHiJB4nEN7A/Gn7WKgci5gyQbOaF7KflaXr xNNkvVj9J6kKE7KIRjbEF7m5LkfzSRSbQpG+26vter0S19UhrWromuwrr9co UdDtF/qmkWsNd2waNISQSRxvNneL21kzJNJJepdkcr+Nl8sVCrjMxIHY3Tkj lMFkOlrPzlyX2vXmOlQSzowKCxHqkGY1PeBCG2VV/y27zi/CsCHT8iFn8AIt 8Am0T5I2vA6g3lEJ+Z5wBX553hwA49rp9TQUAj8De7J4CLxr8Avwhs3I7/kG xfw69GM79/jVDiv9sNZ4lOqveQvLngmKZajNKgdfMTixNKWzPb8A+uGV6Q== NzI1AAAAAAAAAAAAeNqdkNFKwzAUhq8X6DuEejPZUpK2suzCi7ZrFdExVpiX Utd0RGIzknYIc0/mhY/kK5iydTgsIrvLOec/5/v/fH18WuCBL5XUsqjggus6 EzCt6pxLmEpRV1yWMOGCDWEi1WtmNEzppkmwg7EFLtqlaDCA8dtaMa2hizG1 wEzJF7as+vaWhtE4ikOKaOgHiJAJRnRCCMI4wNGYmKnv7uxLeA3tu8XTtAGJ OSuE2TYoe9jZdjbLtSE0061HY88lboACz6XIj7wRChMaoHjk0wklVz5Nxjvb AnGZH1xZ4EbI50xYoLd/pPur/TZ1JMuCr2qVNcVMZFVh+LrxaDK2IrPdmzPB Ms3eH3npuWZ8UhuBYZ4QfhEPjv4ASl39JP4vrnNixAkMbMOiYtVh8byLYc1F 7uBzIrdpTPQ1UxVnXR97y/NjPZU5M4okuE/jTsCxY4Fvmn7kmQ== ODcwNAAAAAAAAAAAeNrtWU1MXFUUPjPDT6GUn5ZWRcRRflpsGRlmoEOxNQMM LXWQtrTQxSQGZgApD4bMDG1JwYUL7UbTGKOJqQuTurGJ2sS4cKWscGEwbky6 aOyC6Mq60XRhGb973n3DmynDvDdMgyScl/Pe/X3n3PPO373v5+WK3z67U3Wf UuAE2Wg1XkQFujaLRIZyIqusr8bjca05vgPbCh4B8+Q3zMdTfO9C4C5gEbAE WAzcDdwDLAWWyfGrO+Lb9nCOwrhiZCcfTeMZoTkyAwcoP2HzJRnG3qj19H54 d8liQ/n7UrXtDCiG6RL1gvoYSj66apK+1aJfj9F55fJ5noYpSpPkpwk8Y3QB 91HwpLVHM7ynDvRt0laM0rdI+xIwCArn+RsoNIL7VRpg+pfBTxClTPAi6O/F c58J+sJv58myZscaaj5Aqxfp7L9EtpfKp5BhBVCjXwncz99kbf4zKFcBnwVW A58D1gCfB9qBL/AaiGpZlkT1wAY5/xCejbJ8GM8jwCagA/gysFn2teDpSlnL UdQ9wHbgMdm3A4/D7X/+fuve2RbvzfmPGm++710hk/BXVxFtJVhyMP8dYDe0 JAALVGD3Qdh9AC0+WOcbNEQn6Rz8VIC8FMIVhqeKonaae19HPUJTmKVg1Ch8 mIJ7EJ5kgkeKWTO4FLbnYV17FK0htItSBH2BrPjP2+T6u8HtCM3SOC7hd4aY xyC9iVrUwHy79L8HTPgfm/QV69HvBI6Ch0lIJwxZiZi0ER+H4M0KdXmnUZl9 kIa+iD/C784kvtTGUmgAfbPxp1Dn/1Pp9/CaQ4gCYbRGMsYA0LcUyPcZpS/G NlgejwnXgV1sB2pUHsd9GLptZ64U1ogA9bEmi/4ocIxzh0GOnrNsBXbwHkM5 xPKzwwM74KkDeHMY75pimR5FvZctLIBIF+S60DsF/WOoE729pbyId8YM25A1 x21moIAs4kv+IWwKQfiTghVrsdAEvzXhGr9+rTx/yV+ez/Wlh8lE0+vfHOQz wnlJrvVfv19Mpd+H+xT71Dn4IpWXMF1Ja4VHoP/5cm9ilP4ezvtUEPYeY8rT rDFr2qVlpqo372JdESOTPdKxLPLP5PWH8f5ZrFl9s37NZ1ivJzb0RM2SfrGJ 9Yv926/J9n/dcg0plAficFELOYFepFpernlQckMALphGExx0D1pErw91N8rd QCe1crkHJrZA8waDo4MNbkYKeh7L3vogbJTzIL9xHtc1cNkMPp2g0go5tbGU XCi3s+R8QCdK7Whtw8gm9LlQEv0tuLpY2qK0gC/hbHG5W9vM2D97AJvMwQX8 dNu998Hqn3Fj8T+9/ml7oW4W2fC68x3QP6vcHxjVv6fkXkDAAHuY2YRgVTsb Q22c49/ax0pr/6b9z9Mi/tvUcj/U7RK8jogvqTY+yDuIzPsvQbfCxPoPyvhG HOMU3mlGOW6NQurpPE36/edm/I/guw+SVljOA/ydIxwzZxIekOg4qeLqgCoT 5dJVOKBrV1Lo9nP2padaxpqyHm+qUYqxu3jfmEveOjA616sVzkThDFfYlh3R pw3989LuxFsd0P7ORBbeidGhJFl4c87TWgzOhp9Xn7CMzPBy/AnKxgwfIhp7 Zbi4jDd0Yfy41FKRfaRfYYfJ/G+A6nY/8h5+74dTd+5+sbzv86EyP5X+WKX8 W1TbfyP+7sPlxVs+Mc5Pv1fW//JVbe3Jb1fuLxwcmXJr8z1jlYurizX+W5+G vvy45kG7ufmbhbN2ou/+F7vvbFIW9fxgO/Ov+VGRBws6Yd5/R6S3jWU8gdTi z34T8e8lTjjV8gXwJKgOYzWjwGS/HjUSfze1/zgFuYSY9jTWrODewxlJiKVg iL6lUv4XyYZ+P+c+Ctu/wHGd5LvREsksf46O5SboO8X5e47O30Tu9802TNy1 k8M6eG9x+j7JcyJ84i/OEJpxOfm0wLnh+i8uF29Kflstu9TVG7V7DapJPWjI M6F/bj63W///ywDiaZizvCBbhoH817T9t+rO3zayP6ex80/T9MXu7hUL5Qyy +f+lQXa2U199L7Te6XuxbLPKnQXJvztam/h7c1H+vdHaGuU4j67thGw7Ldtq OAPR/hga17QdyAT/AY6sV1U= MTYyOQAAAAAAAAAAeNqtVF1v2kAQfDaS/8OKSpEhJaivbUFqCa1SWaHCpM2b ddgLPul8R+7OJGnFf++tPwiNoC2kfgHf3M7O7uy634fR+TlEqtAJwkilCJ9R omYWU5g/wm10BVHGUtTwnf9gOvVbfqv/wocY4EomokjREOErXr3Ae1PmusiG O4ftL9/ia6VzJqa4EJhYruRF1v5/SvKVwBylZcRMtPhgUUtoj9pwGYbj26+T 6Qxy/lEpgczd2CPIbwV+y8v5SAmlPfd0NZpC2NflaeS4sTw19I8O93DEFror plnumuJ1/NZP0uLxRdDNeYxrJuJ5pSA4q671hrKkiM09t0nW6YC779LFVrME Y71lDmoxVfaz8qcJ7rxzQSgMnhIcL1HlxFCVmTDBNHBpURpuH2EAW+mmxJ6U by+V+asUvaGG7uApfhdZHkTmBxH2HCkxW2gZODtn05sxUPYNAQdcXyue7jU8 5pLbxvVj/a2mop4nCuPS2JLR9f1u6z55D1UEDAZwfROG4BCPIM9N7mxyOXnb 7OdSqDkTQCScCbeslBISWumlQgMZaoSAL0AippgSj1fzTPGuQGOBwQp1j7Qw 6T4H1TI+Z2QG7lEICAxasMo18tOHMBoDMSu7y/57VW4Yqp6TQ5t65g4V02jo mRUmfMGTo+ranOopPpzu6YtcS2gQitVfyzqyaf9K+6duuf3Z36w1akOfB6jL bjbrTbNUvwAGNuai MjcxMzYAAAAAAAAAeNrtWQ90U9d5v5JlLIMcKzlW6gQyhLATyobx07OMnmwn dmwlEGyQ/2DjECxk6RnJ6I/79J5jb7CRCQ+0h0/pmrNyGk4bx/Q07bod1sMa QpJWYBJC5m40TV3cZjte56VipqsbuuA2Lm/f9578B3DSna47287u75zv3vu+ +93vu993v3vffVLDk8dIFiHEAKQohJwhGqrJr8cM0F2rz95FTud+e80ZXf23 17QEQ3FrjxDbK/giVr8vGo2J1k7eKkhRayhqrdvebI3EAnxJXt7yooyOrQc+ 0Zi/ql8/R3dv+1d9nlpfy9S/1OuhXvcDvd6kyvTp16vPBfq71P5fqfy7t01l ntNq3RTyB1HfR83d4yakXpdNnvtycPMcb4Lo16zQ5RJigocnNd5zFijMQFb1 0ay2QWt2ZsxcTZ7XgnjPW2q3Nsi8uNaqg8WEvAf17BpCKjOB/lrWUhMkJKD7 9WtQuua2tYJ5Hv8Y+RKR7xOhPrs8MyFTZvFvVbGnRAj4RB8hXcsyvhvJvB9k IUeqSzQx8k4eTkaLDSm8Qy5VIsQFP8n4Wp2xef8S+gQ+HAPBV5/QYkDqgX7n DrlHCcVvBc2tslhU0CbvLyqQDxNIOLl6z0BKyh58zDB1X2J/qYFo7bzBbYbG tvRukEhcMCacRH6qyCzmDn7uNChpmsoZPJzCBWtrTp+FWv60qqpmT+KCaSAl LktUlhLJIL8xtby1LX2fpmOceMefKjJ1jGedwTwfrysyjqf+8a3xS+Mrx2sN Vy6N7zKM1xqxNl7ZahrfZdo1Mjo6mthfZCTScrmuyHQRbRBkLsJtj6NnbpOB gYagCMnfTYLmUmIePuQi5vRpA07JBHJDPQwxQwC6uWzsaZUdh6zE3CZXHYFK MgcnoFK+n0hVe5QxcGIIhYKzwPQoFoMVhw6jBmmdYoFtY5bzUMDTqIoETy0a rBpKXCjwdigTi+Y7NPkb2DevWWx/cin7KHKr/ckl7ctKa/Agvgss+3H4dKti OQiN9vbh0SqI1ptQDHwgZbOp6o6RxIMk3QaRC567F2JYDq2LhqLvWqC9Htrt bKpjRFZ2yNcaG9kU5zZJd3HZR2A2f1ip5GGdOGDSyXl70Exuc2tbMu9VUJ4/ 8A5YD8h5eIbI/QbZUQoCSbfJ88oF6J4qZFNXL8GaVlwUPxFMZ+FEy0Cgm7Q1 K2MQtx9P5Vx0m3DRh1Ig363vgPzL7V6d3g0n9VRl8EVch+ehuJiN/SiYroSu 9naQywHlIWAFT6DUcSjS92Nf0oGyrNLOHTBJRrBkcUIfV3UZuOKqIFZpFl0G HXmKZG5VJKNiQbaienz1blAKEcgfMEIjMKT61mdI8LNE80/zLf9jnZqddyox oxfzwKU/RZNX/wZXy4GrIzt6cIHH2iFcA6n8Q4fVHlwyZUyekd0m6DAnDxgT PzVUHDAJjYlHiHhdsYjoS454VdmkjCXdMxojmaPsmNHUKmOaEuwbkxtmYKNw DWYpm3MbxdPJBnOywZR0G+WZqS8rkkmx9GG6aErUdFETh00N48w596xk9GTi Bznk7dh16byJdEOwIT/TU+C6/Av5fXm3ETqT7kn2UrJhNukwlqL12YqfSWZO TR3JmGyYvPoS+FcxLWYnbuqlkiEraKg4JxrbWpuVyzA2cWCS5B/6LMgAJx3/ laIAE8NyMMNqA2sod1MnFUGQrW2e5nQt8Nq6CTRAXlWJxxdylMsDH6CpLKkW B6+FfhiUtUYzJJbMCRfP2Z9aKbuvyUY5N9kw4WlM/7Mek2xE5tMJfpLg0sOS 3lQUJZ2L2eCeTNvB9sjFbHQW2Iq2d3CTSNnp7ZgUklFuMMs7TOlRGNe+GwKn FB+FQFbkwZvXLOmvj1x9DeSCR/FIexmTY6S7IJjCyH5Gv0SSTCZmcMUwV1tw 0ab2dhvTn8VxOL25xQe5uSRqh0ETg+4Jz6B70oPTcRzUdHnSrQYM5ruKNKmM qSuuSBN4QhWoOXCrq++mH4fpjICx+9VJqo6CuvQ2kLlxZWXqxpX2zbuB3Xrm CEz+m1i0yTMVb8Tz5RwIsV65nLhoqLgp/MzboUodQ6ljHye16HwDW3KD8UwD XPC6OJ1oYFNgqqYy69wzTrwUSj9l3355hQ47NxfmP3tePr975JbzEcdDum+u zHoz/6WagubW/Jc+tYx9u22wzlg48EHvSvmASd5sqviFkCvvNGaNV3woLH80 kVpXMSak2RQk/C3qNH3dN4MTeD5/r5CYA0Pq7S9xzQhn4hAuLOOeYV+HkE8H hrEryachnNgK4pUsvR6ClrhgAI93wLw2IM+j9XjUHiP0VMjVRefSq29cTkzo MmshN0wHknhpI+0wKflfIAhquurYt6vgzEuprmO6ZuTZ1J0jRpXiMCZAcVAt A2pZjwf6fOrek6jCjUGkXDXPfk/b95i7o6Oav4oDVcJ72ZwMF5kHgX53YsH1 WXAdPFYkOL9mM1OBg2g+GiOLZ6VNq3EuoQrgKNYSPHgB3kpB1Jh+Wb19FO7O bK9rZtVQgp9R92Rz27e2vVf9yiv4MQSncd7AiJh74/KwAUSm9rQOumfgNVuI DkqzrARH5Sr0Z1qxWDN1kVrD7EBuHcq5f866p9npihtSzje3g+apFQPXpRz5 jXMT5hXTSQfavjGWdKCBDu+uS9qsnrm2Dvbx8PMVcOzlncDSchzLB57F0nEM y6qjUHYdtZxRq7yvqdUDR9Qq+5BaFR9Uqw37oTrx6exTFTgfMnxSrQ3DL0I9 6DYOn8bngYlZRbmYPe3Cd6KODGHn8EkXviePQ5lrIKmL2Sdc2htTDVly4AoM GTKozXehqVgq8cxPg1C3Lt2GK9INbzIjvkuLIAcUiwmaiSoUIJIRZFiUCaJu xWLW7lAFUF0aUYrr1FzarJbH1NKjljvV8inr7d8iFL8ZLtvguxeoHr5LS4FW ARmB/g0+0K8AnQf6OtBxoP1AHUCtQNVA3cWajvNr4ZsW6CTQTaBl0GcGWg/0 LDz/CVAfUBjoSaAngB4FKgOyARUCLQciQNNr75yj+Z6F1Q6E4/0Ra5cvFOYD 1ljUaiuO26zrgr5oIMy7rMWlzj4rLwgxAdqBT8I1v659W/32mjqXNRD2alLW qBQO49cviYS8ouDz816B7wrzfjEUiyKvJ8hHvXyvLzxnEzcAbgxsb/6vBBu2 ysE12haaw/cKlxbFc05dn0w993zMos3jKah7gOb4o7fJ/cG9mtzc85VF/Svg 2F0N5LQt2Hvfpn3n71/E+wasRZ31/1bevKd7nBfrfXHRjVkALunh2SPE/DWB gMDH44RsdTdtc9ez9pJAGFZ4fXaEj8R5EQ81rzcU6/R2SVE/Ie8aunqEUFTs It06Lx/1xwK8tycGDF4gh/XeiC8cjvm9fkEkk4YugecJ2TcnF/BihpE9Om+A v2WcQe8NRUMiNCMke6Ht5YlF5/VF4nu9fF8IZrICngLdUlz0dgVCvfip6vXW 9vTs9PeIj4XCqKmhubW2iStVXTgKvf4w74t6xf4eHrR2xbxRX4SPe1WrUczj 97K8UhQmvI/8OUjDqFhUNdWr96rcVVneDCcOXvT5+R4xs1uEMq8/FonAztiq Q3fBp05p715e8AZjsX2EvKbfglZQCx9w9/lh1F6erDE0h3m+h5xd3Fsbi/T4 BH5eiPwtqQvFfZ1hviUo8L5AfahT8An9tRDaOGnJapR4od/DC10xIeKL+vna mKRGsQtXtCXk36cyCPlLXPFaSRD4qKgp2hIg5KuLuLj8sPTA3o5jm/vjIh9p CUX4mjjEk8cW2WBogaUIRX0inxEn5Ct36iAPG3ZEtcigtxAnODQyi0IshmZe /Mju7+i3xOsywfNAKvI4ee03xsxvkD+AfaHL/KaI9CI8vwp0uVj77e0y0Cmg CaBpoPeBv+xBQlYDOYFaHkQtOqInWcRAnmj1bsPQhZvmTzc1X5bgL8XTcnGp DszbJTt6eSGunaEQh4ZYQArzm9VY0Nfs/1rgbfev7/tWnZIBjcj/T2h/AejU n+6BDt7O12s/79/Bh8u7eifaWU1IE3y0TGb+S6j0xeN8pDPcb+2LhKPxKpsk RF1xf5CP+OIbIiG/EIvHusQN8G5x+eKRkl7GZoVTPtTFx8VW7RipsjElpbaH 85ZbrZWiAG/DLfBm+09qY7VxMDLO+yUhJPZnnoEj8J+SwAof8AihXjj+9/Lx +c7F3e4+GIrnWj3fy4etYSyrbL74lmhvbB8v2KxSqMaP74QqW5cvHOdtD1du /IjBC8Y3frT1yo23zLVy47zT2nOA7+GjAbhizPkyzxFrMrFesDMX/S3YDSqt eDeosj0dirJ2mxWvB1W2hrm4lbTWwl2itqnFZu2diz1XUlpiZ0rt9hKnDf/R Q0djQo3gD4ZEOO4lART0OcuhT+oMh/xb+f4WiAouWpff2cl2cj6GZ5w824lh uX028x4v7cECP+Prf6/vztt9d4LvjtLyUqj/p31fGP+wp8ZTU1e3ZdvjO3dm Gr+NZ7xX1MGlY7ZUx9zNrGRszCeZUqaacTP1TDOzi/ExQSbC/D7zGeY55gXm K8wpJsW8zowy32V+yPwTk2Z+wvySud++1r7evtHutjfaY/an7c/Yj9pfsP+F fcT+Q/u0/d/tH9rvZVeyD7Gb2Cq2jt3F+tg/Zg+zx9lT7Jvs37E/YrPKCspW lz1U1lTWXtZR5i/rLnu67EjZl8q+XvZW2QOOJxx/5kg53nC84/iR4yeO646c 8lXlD5U/Ur6jvLP8i+Uny18vf6v8yKbBTV/c9Nqm72z6/qZq52POemeT0++M OQ84P+/8sfOaM4t7kGO5R7jHue3cLu6PuMPcCe4F7kXur7jT3FnuHPcm9/fc GPcP3CQ3xV3nPuSyXPmuQtcDrrWuDa5yV42rwdXk6nTtdUVccVfSdcx13PUF 10nXV12nXN9wad9N+Jl0srSIWceEmR6I0hnmVeYK83NmhqHvFgoKCgoKCgoK CgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoK CgoKCgoKCgoKCgoKCgoKCgoKCooF/AdpVuXM MzU4NAAAAAAAAAAAeNrtVktME2EQ/vZRoaIJSxMPXCjGA4mJaS0aTkC1Rmux VErEAxehBRGtSBGFYFIJUQ9cMCR6MAS8oGhINSZy0WBifFyoxMQYD0YvHDgV 1Hiy6/ztdK0NERq4IHybyez8j51/Zme+3Xcx7cvYo+KvyEIlFCR0M7ZkjEks SRQCMtsJXdfTw/om1hV+kZj4HaqsE5tp2TCow3m6umDFIYRId6IHuWAHTEbP K2RHTWPDMy9mtMkpTKDp1ofMtZH8EevQpzeSWFetpMZOIEg+w2ijU4SQOwoh SzrXrp7BQ8tBZW3CcbTDRlG3YB/OoQkeXKY8BOjuAi7RiJN0e9LqQiuaUUcn /oMK9p/GSnwLznxp+HdiL10hir8bZ9GBWtjZf4C89Rj+T1GeHJSpBjrF3/7F 8+Qc4hf9/pHvRa+LvQrnRNiC8/NI8tneSrqAZBvbm/h/YLfZbVgFElRxJkle ssZ9bY2VBfMz2miQuGBcGxKOhrnOxHwZ04LNqOVUHTeyjtJCC2mzmlovcw0G qAPD1BudxBod1Ctp7hD1uoeknuZFD1+kFUFiNj9OU/cEmGms8CXHwyRdWC3+ FX/k29x8byimXZtOcaGI8x73n5jnuCMVvKeaY7zB/XhniTzIPLadpJZY4QxF 0Zzk74OooUjdcCWfpXCunMSwbiPmbspVkFgNOEKyoL7qz3uoVU+MX61aPDm5 syTz/26FcB92HjM21bh8/nIqKE0cOvvpUl19jdPG5Sa7/F63g4zkVsXvchzY T1Zf6mTZW1UMSLBPD+3ubZ3VojGM7np983oJ4gMyfnyODAYK32vRpxh92z9W pCAeUXC0PDBYFPrpeV562/ykrNQRUeH6fmXqWfF9711VHXHUL87SW2jxuqsa LJbaBx19c2bP4wUpHsdGg8/4/oapioLUJZlVtTysVI25fv/MJLE1jCFX/2uN 9ez/N2fHhKU=