{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2025-12-14T01:33:56.000Z","description":"Problems submitted by members of the MATLAB Central community.","is_default":true,"created_by":161519,"badge_id":null,"featured":false,"trending":false,"solution_count_in_trending_period":0,"trending_last_calculated":"2025-12-14T00:00:00.000Z","image_id":null,"published":true,"community_created":false,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":null,"description_html":null,"published_at":null},"problems":[{"id":52050,"title":"Matrix convolution","description":"A certain convolution step involves an elementwise multipication between two 3x3 matrices and taking the resulting sum of the elements.\r\nGiven a 3x3 kernel matrix K, find its convolution with a 3x3 subsection of a given matrix A. The subsection will be indicated by r and c, the row-column location of the top left corner element.\r\n\r\nFor example, let K = [  ], A = [   ] and r = 2, c = 3. Then the relevant 3x3 subsection of A starts at row 2 and column 3, i.e. with the element 7. Thus, the 3x3 subsection is S = [  ]. The element-wise product of S with the kernel K is [  ], and the convolution y is the sum of these elements, making y = 45.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 354px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 177px; transform-origin: 407px 177px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA certain convolution step involves an elementwise multipication between two 3x3 matrices and taking the resulting sum of the elements.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 81.5px 8px; transform-origin: 81.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a 3x3 kernel matrix \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 5px 8px; transform-origin: 5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eK\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 187px 8px; transform-origin: 187px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, find its convolution with a 3x3 subsection of a given matrix \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eA\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 106px 8px; transform-origin: 106px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The subsection will be indicated by \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 3px 8px; transform-origin: 3px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003er\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 16px 8px; transform-origin: 16px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 173.5px 8px; transform-origin: 173.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, the row-column location of the top left corner element.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 222px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 111px; text-align: left; transform-origin: 384px 111px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 52.5px 8px; transform-origin: 52.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, let \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 5px 8px; transform-origin: 5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eK\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-24px\"\u003e\u003cimg 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style=\"width: 85.5px; height: 60px;\" width=\"85.5\" height=\"60\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 8px 8px; transform-origin: 8px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e ], \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eA\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-45px\"\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAO4AAADMCAYAAAB0ip8fAAAUN0lEQVR4nO2dXZXrOgyFN4cyCIESGARFUAbDoAxKoRgKoRxKoRiGwrkP6b5R3Dhx4t/M7G8tP5w5SSM7ki3LjgUIIYQQQgghhBBCCCGEEK3SATgsXHME8BVYjtkk7Un1nMP7d5bq3hoh76s1rP7Ukn1tu83p/O39e1Xo3gL8w7IRvN7XhZRrBlkPRlZbfgB8b/zNJ8Lq3gpr3lcLUN4fAJd34b8fKKf4W9rtgF5On44/0osZJpRrBHMVOiHcaP+h75FS0mG+Ebd0FheE1b0F1r6vFjhiMFB3lOP//SCv8ca0m9WPEjq+yOkt1AnDiLNUoQeWe8jD+3deacT8eP4LwNn87YjPl3IK/L0v7McItryvFqCH5nsn3+//v2V6fky7cbTd6sllJ2TU6dC/hKW5wRl53OQT+kb0yWfrcA/4Pb6UO/ZjBGQvXsIRy3Ky8/wpIM/advtGfm8gilDDDXELaAipXYg75ns+jvShSnBHP4LbUbdlI7DsxXBt2/pGXF6Tw0NzWdtuL/SjdLOBy1SKQOP5QfqKhkTvHggz3G/0L4Wd0R6MwLIXw7Wd6RPTOnFFvkCmy5p2O5trbR3OaMiIUykCK5trvrIEDXcu0seACD0CGW5ebPzBDVDxXbATzc2adptbPbH6U5VUikA3OTQ4lBo29pxL/cS4d5fh5uWAcVCISs+YxQ3lRrC17UY5r5g25Fp6/j8pFCGnmxxCh2Gu5Ou9r/h02WS4+XGNl3pSWvFj2+2M8XJkLV3/nxSKUNtNZh18o+0XpqPSMtwy+Iy3pPypBihbj0sa0baRokI13WQu7fjmtnPrcTLcMlDmKz430ZTSmVTtZjcCVdk5RWIrVNtNvsMfteT/+9Z2Zbj5YYCKBtphCCSylAj2pGw31qnE+rOXFL5/LTeZSzs+ubmIfsL0JnHu3PmHvh61N8CHsCfDpaxTHaeNOLe4jjsHt//u2nDZe5Z2k8+YN1rgs2cPLS0bxJ4Mly6lTzfszrXco27Kdiu5ccRLTIUYzS3tJocYLdDPqR4zxQYangjbj12bvRhuyDTEbovMvSc4x4hbKxgLIK5CuTeJT3HCstEeEWZ8muPmI7Rt92i47ry9CjEV4oh1XrowEe7OpykYspfh1oeusk8/7LbI3F5OaLvxYAWfPPQyq0aUge2KYN3kEq4ljfaJ4YPsqfJCeKPKcPNCWX1Rf3psIV90pZJlqd3sctUFY7k5KDwXfiM7/Fxvy4IyG71Ez0OjDQ0ubfkmt3UjAOLeVy34IYGr7Iz435E/PrKm3dyA5ut9PdegS27T/KCDP3BzQ9h8g/eX8PP5GV5IWaMIR+wjIJXifdWkQ6/8Vu4L8keSt7bbGWOdu73lbVlHhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCtAATXW05nvSI+cOjW4VyT5Ub2qvPnLxuKXXMbIe4Y0p58Hjpo05j5T6iP/Hx9i5FsxkcMM6WxuLLIzt1r3vO8Qtl0iXGwny5vjOZq59QP4E9E3ipXDPL0mHQnZhOglkwSnY0W+U+YDhsn+cyF+/cbWLetS+fJ7n/vK+5YJxxrUTWtVjsifZTpTX5mWAqtOSSf6qz32p0JbMxxMp9xGCwVc/ffrwFsflcjvis3JQLwMOhXVfDZhpoccQic9npWyXkwHbm4MmV9vGE3thOGGc43GJ0NntEbsONlZu5nzmYVctgcEKvuD7BbU/o5nP5mvibpYks3Qsw7UVrc1gfTJ2xpDBUsNxuMhA3WrLjtF5aKVd5rdy2g3mgcrLzO+ZHG5s9zTXAE+YV3iZ4apUXevlazzpPOoS5vjSEEm5+jOEyrUeNnE1r5LZxkCY6+pCIKZMerR05OeK26oZat4fl+f77HozYBzvbUsnFtxruN/qOk51Ry4Zrp40lvJgk0HDXzFXZQ1V3KWaYi8wu5dxtGXZIpZKLbzFcN69xy4Zrvc5/GAa65pc+qeChIycjzSXSJcbyhd7lv2LakKtmGN8I3eRSsm8x3CfGI1fLhvttrmOKzamlz6Y8SyarpkszxwF9b28r1Xq6ShdX/lLuZipKu8nAesO94jOxdcuG6y5vcpPFF3p9sR1+M240K7fUmzDC7CYBbmYyvwJ6DJR/D8miSWk3GVhnuF+YXsVo2XCtLkzZgasv1b00O09diztyzS0btYjdlNLyOrRLaTcZWDdX9K2Zt2y4IQOQ3RRTXV/u+HRp1mCVf28uJ7CPdWhLDTcZWOdy+jrwvRjuHE1Mrxiqj23EK8q/kFSwF92L4dZwk4EwA+BGF84N3WIDQGfz95wGEGq4dvCZw04Tq+g6J9wpHl6jJ00FZc+1bTA1VJzSc6wQA5iKfYSUnDoTarh2H8NcR1LVcFMaLTAo/15GLQtH3NIj2BYY/a/hpoUYwBXDHuupYoM7T4Ttxy4hNxDuNYYaeHJOWDbaI9Y1Zsk9s6nhHLd6lDAAupo1OpkUX/a0PMc9muvOM9dxWajoFl93J8sUDHuvMVx+edSam8yPtn114QhWPUIYCEesOcXKxW83XGBoX59R2t1Vxd4BjfaJvjK+8sJYkelC+D6Yb3nEsktVF4xdG3ZQT7TX4Uxh3eQa6+V/wXCtfFOGyd8q1tHb72ZDijVC93vdBwYj55bHVhXfDZZwK9sVfXtMfWPcKnSTa3gH/MzQdoJbKG24W+S2exPshyhs/6JbfLnbKaS4gh3eQttrru+/7WGn1Bnj+t9Q6QiSSBj4KenZdPAHnG5Yv2/3iDIBqVi5qfNWby7Y7wcpQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQggh9gQPHt/LUaeWI/oT/G4YkhmXoMP69jpi/oD3nDBB15ZjVTtzf2li5I65dxfwBPi9VPCA4fB3nrdbyhg6DGdVh7TX4X29ey6274D6lPDZ7rnbvvy3LsxRdcfQOfLenJ18jNyxdd4NKU64L8kRg8HmPt/XMqUQS+3FbAs/6M8JvmBIas2Sy3ht3mNfmcsVdfNcYw92z2G8MXLH1nk32JPp92C4TE7GF1DKtT+hN7oTxhnrltqLB3i7ctrMFLkyGzAflE3FccRn5zM1taBxvjDdxswwkcMIYuSOuXc3HNArjx0BWjZc28nk6u1DCPVQvuDP7A4MypQjtenp/bs++WwdXBmpF3OGaTvQlDoTI3fMvbuC6Rn2kNTaKlOtpFkk1HBPmJeTv5Mj3eMd8/M5m7XO7Ths1nnfyNSZa1KOujFyx9y7G77RuxSMFrZuuNbVqT1HSRUTYJ1yBExuWO7cbIJni50KzP0GO9LXRhmniJE75t5d4ObYbd1wbU9planW0koKw6UHUdPlpxK7c+zQUclmUiz5Dnxy5763Ok+MR63WDde6bkyzObW0UirUH2u4jDQXTfc4ASPztt1sVvc1hlsy2DMld4l7q3JFrzRWYVo3XHf5hJssvjCsM5Z0o7ca7gHj3K3s+WvM1zlH5XSJWF1YY7ilDMEnd+57q/KF6ahb64Zr51xTCnJwrsnd+28xXEaY3UTdtYJtrIPbnlYXliKvth1KeztbnhdzbzU4p5oSunXDDVHwE8ajWE5SzHHdkbfk8oSdX7u4S25zXFHWcOfkznlvVe7wK8eeDDf0upxzx1RRZbvLJ7fMljs+p0ukZVd5Tu6c91bjG/1L4LzQLTb4czZ/b6WSVrnnsIqUswNKuUXUjlolOk0uA849a4vh5pY9RO4c91Zlal4VUlqpqF17m+tM9mi4Jb0dBvKWnsNgX6jh5p6jh8qd+t7qXNE3sq/YwM7T/L2VyFvoqBRq4LHkMNzcGwLWKLDd7BIyMufY+UX+rNGG0Poc164tnmeu40iRU5GAtIbLPb85l7FOWFbgI4aO2uqDr73tO8k1v10rd6p7d0PrhgsMXoHPKO3uqjnjTkFKw+XXLLna3d0lNwWX06wSL+0wohfk+3oolq1yx967K/ZguEujAI2pRLg/1HCtck8pEV3SXOvOVOAnepl95YXPdrMRb7eO9oOPHN8Sx8gdc+/u2IPhAuO1zzOGnp5R8RJbCDuMd2pdZq51vwF9YFAcbnnMPdKGBiKnOg/+ht2002HwfnJ0ODFyp6jzrjiivYCUjwN6Q+UuJBpD7iNgOviDfDf4d3R9O9de33/L3c62fZbKXIfntjc/ncslf4zcqeoshBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBDiL9Nh/Yl1HYbkXrXYIjdlrnmM7N7kTvHsLXWuzRF9vZs7ubTDcHZv6EthPpU7+mNNbxjy5pZ6MWvlPuDzjGLm2ymZpHiL3Ff07W0P4n4hv9yp2myLjtWE9XbPV/YdSl+UqZeyJpmTm6eGB4o/kNd4t8htT9T3lZx5d4Dtcj8xnaLjjrztnaLNtupYTZhW5Ad9/S4Y2pqlmvGe3gKdMM6yt9SoNE5frhfmisllBFvlZm4dm3bkiE+lynUq/Va5ee1UpgObwmMuE8JWYttsa51rw8PpXf22GQ6aSDsSmsPGKorPMJk1rsQLCpX7hHH6i7nfuacUMOB5c3KHtKU1opSjbuo2S5ngLCdfmK8P2zt3OtMgQhvVZpz39bKduSa36xkqN9Nd+LAZ+kq8kDVyL8lkjTvlqJu6zfZiuCfMB6FYj9wpWIMIbVTr7sxVjqPyK5WAHkLlvmE5ImiTWecmVG6245xMNtFaSm8hdZvtxXCX4IhbMpjpJbRRQ3vYB8IMPJbU+WVLzV1StncXeF0O1rTZbzBcThVzB1+DCWlUmzl8jeHmTEGYUhmY8rJET7rWcJfmr7UMd02b7d1wGWluKjtfSKNal2yN4eY0hFTKwFHrhTKL7KFyh3aANQx3bZvt1XAPGOdTpofRxGaMtYa7NJeyv7cHw+XvlJq3bAkG+tq8lqu8ts32aLiMMNsO1LZ1deNda7hLc5or9mO4dt5SijXLbzZr/dSoa5eDSkU6t7TZHg3XxR15SywdzvKXXeU7eoUvOW9ZI/cRY+N9vO+/on8PdkfPLZO8Llva7DcYLjDeTfaDyvPdnFHlnC8pVhm+0RtFaUVaKzfnWTf0bcv94R3G3k3OQCDZ2ma/xXCBcZtXrUtoo7LnDzXc3POAGGXgRxI1Gj6VEtudbL4tqCmJabPfZLjW+9yF4d4Crys159qqDDWNFkgfVPuH8X7iHMS22W803OrbHkMb1fY0PkWx6725o7RblOGEZQU8ol1Pgdh2zh0kSdFmv8lwuc0095beRdY06tJuGfr/JVy3tcrArzvmPsniQnvLhmujzbl38aRqs99kuPxqqno91jSqjaq519o5V4nvFddGZ3/QK9hlpryQf2koRoltlDn3Lp6UbbYXw7UDz5QOc7pYIhA4S4fxckPIFyZ8ofazL37wXapSa+S231GGlJzyb2lvcsHQ7rmnISnbLKbOpXG/Neby2wXDlseqHQ+XEh4T5YZlxTi8r+HOEn4Glns3yRa5757rp0quUWyL3Af0BsE12wfKHQ2Uos1idawG1Gsr6xVldFv8Ejr0CvOFhja2CyGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCHK02H7oWQx98ay5dlH9Iew1TiIjc/dcqbyl6fc0P4phFvr3QJNyt5hOE92rWAx98ay9tm8/gfDWbn8d+4s4wd8ntnL/DMhx5Taw+anSsn8vmuIrXdNDuiPZn1hfPj7C5Vln2rUUOOLuTeWLc/mAd9TKTvsAe85jNdmf/CVpTw0NhPAVCmROWItKepdCx7wP5VKhzmJc6d/meSEXhlOGDIQhBpfzL2xbH02T9L3nbj//f7/HMmhmWvGJko74rPz8cnG0bb1Ecoltt41oW5NZV2w3k/VrAwxeV1q5oQJffYx4LpcqRNPGKdqcbF18GXd+0b+XMOpSVHvWjAb35y+2M6n2mH1v91wbXpQX+/Oa14pBcSQmsXHAeN53xQv9CPAnjIapKh3LegKz8lljbvaqPvbDdcqyRPTys8sbannXCHRXqYunVIUqyC2Dme0bcSx9a4J3eA5uexgUM1j+O2GC4xdGzeowODUC3Xc0bmcwzbL3VRktsWgVChLuZZrEeIJdIHXZeUvGC6TL7tKz7nYDfVGMBqnz7WknFdMG3KLwZ0QlupdC9u2czohw93I2me7xstGr6n47LnXjPZnjJdZftC22zzFlnqXgp7AUqcow93Ilmf7jLfWjhjWYe2o49aj5WTRU2ytdwm4NDg3f5WrHMGWZ/MeJouu6XJyPXDrHM9ucGhtnjhHbL1zc8B4SjKlFzZm8iwn2pi/YrhsbL6IDmO36B/KBnvu8Ee5Q2GdWovMzpGi3rk5Ymy8D/T6xg7/bv4vx6adIP6C4fLaKdfH9p6p13F9fL+fFdtmJ+zLcFPVuwQH9PGEG3rDvaPXow7D8mHV4OBfMFy6lL5Gtj1o7lH3jHTKm2vjSA5S1rsmdsvj1F7mYvx2w/0KuM5ui8wZMEmtvBxxq7lrgfwWowXGendeuLaYIH/VcIH8hnvCsvIesW55xJ23t0iOetfCdvDV91j/dsMFBtfG10PabZE5FIi7s+bccC7xdObfXzPycEmi1egssK3erWKjzVU+6XP5C4bLa33RTK7d5ehFqbxPDB9kT5UXxkZol6sujtxU9ifadT+31rtFbJT5jgaMtsM47L1mIT/m3li2PJuRQFfZ+dlcjhdC5f0XWKzL6y5V8SQGLknU3Ka5REy9W+OC4aCF6htGGNJ+TJQb5gWMuTeW2Gd36F+Eve+CfJHku0fWqTLVcZyd37hhWJJomdh61+SAYW84N4p8oy0ZhRAOHXpD3dP3z0IIIYQQQgghhBBCCCGEEEIIIWb4D842LQjIDGP/AAAAAElFTkSuQmCC\" style=\"width: 119px; height: 102px;\" width=\"119\" height=\"102\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 22px 8px; transform-origin: 22px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e  ] and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 3px 8px; transform-origin: 3px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003er\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 16px 8px; transform-origin: 16px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 2, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 137.5px 8px; transform-origin: 137.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 3. Then the relevant 3x3 subsection of A starts at row 2 and column 3, i.e. with the element 7. Thus, the 3x3 subsection is S = [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-24px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 64.5px; height: 60px;\" width=\"64.5\" height=\"60\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 65.5px 8px; transform-origin: 65.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e ]. The element-wise product of S with the kernel K is [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-24px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 115.5px; height: 60px;\" width=\"115.5\" height=\"60\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 217.5px 8px; transform-origin: 217.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e ], and the convolution y is the sum of these elements, making y = 45.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(K,A,r,c) %Do not alter this line\r\n  y = 1;\r\nend %Do not alter this line","test_suite":"%%\r\nA = magic(5); K = [-1 -1 -1; -1 8 -1; -1 -1 -1]; r = 2, c = 3;\r\ny_correct = 45;\r\nassert(isequal(your_fcn_name(K,A,r,c),y_correct))\r\n%%\r\nA = magic(5); K = [0 -1 0; -1 5 -1; 0 -1 0]; r = 1, c = 2;\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(K,A,r,c),y_correct))\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, 'for')),'loop forbidden')\r\nassert(isempty(strfind(filetext, 'while')),'loop forbidden')","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":31,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-06-06T14:45:47.000Z","updated_at":"2026-03-30T17:19:23.000Z","published_at":"2021-06-06T14:45:47.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA certain convolution step involves an elementwise multipication between two 3x3 matrices and taking the resulting sum of the elements.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a 3x3 kernel matrix \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eK\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, find its convolution with a 3x3 subsection of a given matrix \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. The subsection will be indicated by \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003er\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, the row-column location of the top left corner element.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, let \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eK\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e-1 \\\\;\\\\; -1 \\\\;\\\\; -1 \\\\\\\\\\n-1 \\\\;\\\\;\\\\;\\\\;\\\\;\\\\; 8 \\\\;\\\\; -1 \\\\\\\\\\n-1 \\\\;\\\\; -1 \\\\;\\\\; -1\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e ], \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e\\\\;\\\\; 17\\\\;\\\\; 24\\\\;\\\\;\\\\;\\\\;1\\\\;\\\\;\\\\;\\\\;8\\\\;\\\\; 15\\\\\\\\\\n\\\\;\\\\; 23\\\\;\\\\;\\\\;\\\\;5\\\\;\\\\;\\\\;\\\\;7\\\\;\\\\; 14\\\\;\\\\; 16\\\\\\\\\\n\\\\;\\\\;\\\\;\\\\;4\\\\;\\\\;\\\\;\\\\;6\\\\;\\\\; 13\\\\;\\\\; 20\\\\;\\\\; 22\\\\\\\\\\n\\\\;\\\\; 10\\\\;\\\\; 12\\\\;\\\\; 19\\\\;\\\\; 21\\\\;\\\\;\\\\;\\\\;3\\\\\\\\\\n\\\\;\\\\; 11\\\\;\\\\; 18\\\\;\\\\; 25\\\\;\\\\;\\\\;\\\\;2\\\\;\\\\;\\\\;\\\\;9\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e  ] and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003er\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 2, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 3. Then the relevant 3x3 subsection of A starts at row 2 and column 3, i.e. with the element 7. Thus, the 3x3 subsection is S = [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e \\\\;\\\\;7\\\\;\\\\; 14\\\\;\\\\; 16\\\\\\\\\\n13\\\\;\\\\; 20\\\\;\\\\; 22\\\\\\\\\\n19\\\\;\\\\; 21\\\\;\\\\;\\\\;\\\\;3\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e ]. The element-wise product of S with the kernel K is [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e \\\\;-7\\\\;\\\\;\\\\; -14\\\\;\\\\; -16\\\\\\\\\\n-13\\\\;\\\\;\\\\;\\\\;\\\\;\\\\; 160\\\\;\\\\; -22\\\\\\\\\\n-19\\\\;\\\\;\\\\;\\\\; -21\\\\;\\\\;\\\\;-3\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e ], and the convolution y is the sum of these elements, making y = 45.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":694,"title":"Remove NaNs and numbers adjacent to NaNs","description":"The aim is to remove the elements before and after NaN occurrences inside a vector.\r\n\r\nFor example:\r\n\r\n x = [6 10 5 8 9 NaN 23 10 7 3 21 43 NaN 4 6 7 8]\r\n\r\nThe output y will be:\r\n\r\n y = [6 10 5 8 10 7 3 21 6 7 8]\r\n\r\nIf NaNs occur at the beginning or end then first two or last two values are removed.\r\n\r\n x=[NaN 1 2 3]  yields [2 3]\r\n\r\nNaN values will exist in every case.\r\nNo case is an empty set.","description_html":"\u003cp\u003eThe aim is to remove the elements before and after NaN occurrences inside a vector.\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cpre\u003e x = [6 10 5 8 9 NaN 23 10 7 3 21 43 NaN 4 6 7 8]\u003c/pre\u003e\u003cp\u003eThe output y will be:\u003c/p\u003e\u003cpre\u003e y = [6 10 5 8 10 7 3 21 6 7 8]\u003c/pre\u003e\u003cp\u003eIf NaNs occur at the beginning or end then first two or last two values are removed.\u003c/p\u003e\u003cpre\u003e x=[NaN 1 2 3]  yields [2 3]\u003c/pre\u003e\u003cp\u003eNaN values will exist in every case.\r\nNo case is an empty set.\u003c/p\u003e","function_template":"function y = NaN_window_delete(x)\r\n  y=x;\r\nend","test_suite":"%% \r\nx=[1 2 3 NaN 4 5 6];\r\ny_correct=[1 2 5 6];\r\nassert(isequal(NaN_window_delete(x),y_correct))\r\n%% \r\nx=[10 20 3 NaN 4 50 NaN 6];\r\ny_correct=[10 20];\r\nassert(isequal(NaN_window_delete(x),y_correct))\r\n%% \r\nx=[NaN 20 3 5 4 50 55 NaN];\r\ny_correct=[3 5 4 50];\r\nassert(isequal(NaN_window_delete(x),y_correct))\r\n%% \r\nx=[10 20 3 5 NaN 4 50 55 NaN 60 80 90 NaN 100 110 ];\r\ny_correct=[10 20 3 50 80 110];\r\nassert(isequal(NaN_window_delete(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":80,"test_suite_updated_at":"2012-05-16T21:35:19.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-05-16T21:24:52.000Z","updated_at":"2026-03-10T15:29:04.000Z","published_at":"2012-05-16T21:35:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe aim is to remove the elements before and after NaN occurrences inside a vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ x = [6 10 5 8 9 NaN 23 10 7 3 21 43 NaN 4 6 7 8]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output y will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ y = [6 10 5 8 10 7 3 21 6 7 8]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf NaNs occur at the beginning or end then first two or last two values are removed.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ x=[NaN 1 2 3]  yields [2 3]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNaN values will exist in every case. No case is an empty set.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1441,"title":"Convolution Power","description":"Create the convolution-power vector from initial vector _x_ and power _n_.  In other words, similar to the scalar case, raising to the _n_-th power means repeating the convolution on itself _n_ times. \r\n\r\nAssume that _n_ is a non-negative integer and _x_ is a row vector.\r\n\r\n*Examples*:\r\n\r\n convpower(1:5,0)\r\n ans =\r\n     1\r\n\r\n convpower(1:5,1)\r\n ans = \r\n     1     2     3     4     5\r\n\r\n convpower(1:5,2)\r\n ans = \r\n     1     4    10    20    35    44    46    40    25\r\n\r\nNeither *string operations* nor *interpolations* are allowed!\r\n","description_html":"\u003cp\u003eCreate the convolution-power vector from initial vector \u003ci\u003ex\u003c/i\u003e and power \u003ci\u003en\u003c/i\u003e.  In other words, similar to the scalar case, raising to the \u003ci\u003en\u003c/i\u003e-th power means repeating the convolution on itself \u003ci\u003en\u003c/i\u003e times.\u003c/p\u003e\u003cp\u003eAssume that \u003ci\u003en\u003c/i\u003e is a non-negative integer and \u003ci\u003ex\u003c/i\u003e is a row vector.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExamples\u003c/b\u003e:\u003c/p\u003e\u003cpre\u003e convpower(1:5,0)\r\n ans =\r\n     1\u003c/pre\u003e\u003cpre\u003e convpower(1:5,1)\r\n ans = \r\n     1     2     3     4     5\u003c/pre\u003e\u003cpre\u003e convpower(1:5,2)\r\n ans = \r\n     1     4    10    20    35    44    46    40    25\u003c/pre\u003e\u003cp\u003eNeither \u003cb\u003estring operations\u003c/b\u003e nor \u003cb\u003einterpolations\u003c/b\u003e are allowed!\u003c/p\u003e","function_template":"function y = convpower(x,n)\r\n  y = x;\r\nend","test_suite":"%%\r\nuser_solution = fileread('convpower.m');\r\nassert(isempty(strfind(user_solution,'regexp')));\r\nassert(isempty(strfind(user_solution,'2str')));\r\nassert(isempty(strfind(user_solution,'str2')));\r\nassert(isempty(strfind(user_solution,'interp')));\r\nassert(isempty(strfind(user_solution,'printf')));\r\nassert(isempty(strfind(user_solution,'assert')));\r\n\r\n%%\r\nx = [1 2 3];\r\nn = 0;\r\ny_correct = 1;\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [3 8 1 2 3];\r\nn = 1;\r\ny_correct = [3 8 1 2 3];\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [3 8 1 2 3];\r\nn = 3;\r\ny_correct = [27   216   603   710   570   876   763   354   390   260    63    54    27];\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [1 3 2];\r\nn = 2;\r\ny_correct = [ 1     6    13    12     4];\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [1 1];\r\nn = 10;\r\ny_correct = [ 1    10    45   120   210   252   210   120    45    10     1]\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [1 5 2];\r\nn = 7;\r\ny_correct = [1          35         539        4795       27209      102725      261905      451225      523810      410900      217672 76720       17248        2240         128]\r\nassert(isequal(convpower(x,n),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":10352,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":54,"test_suite_updated_at":"2013-04-28T07:05:45.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-04-22T11:04:39.000Z","updated_at":"2026-03-11T08:30:52.000Z","published_at":"2013-04-22T11:07:31.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCreate the convolution-power vector from initial vector\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and power\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. In other words, similar to the scalar case, raising to the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-th power means repeating the convolution on itself\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e times.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAssume that\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is a non-negative integer and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is a row vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ convpower(1:5,0)\\n ans =\\n     1\\n\\n convpower(1:5,1)\\n ans = \\n     1     2     3     4     5\\n\\n convpower(1:5,2)\\n ans = \\n     1     4    10    20    35    44    46    40    25]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNeither\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003estring operations\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e nor\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003einterpolations\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e are allowed!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43494,"title":"Weighted Convolution","description":"Given two input vectors x = [x_1, x_2, ..., x_K] and y = [y_1, y_2, ..., y_K] of equal length, compute the weighted convolution output z = [z_1, z_2, ..., z_K], where \r\n\r\n     z_k = sum(nchoosek(k-1,j-1)*x_{k-j+1}*y_j, j = 1..k),  k = 1, 2, ..., K\r\n\r\nExample: x = [1, 2, 3]; y = [4, 5, 6]. Then z = [z_1, z_2, z_3] where \r\n\r\n  z_1 = nchoosek(0,0)*1*4 = 4\r\n  z_2 = nchoosek(1,0)*2*4 + nchoosek(1,1)*1*5 = 13\r\n  z_3 = nchoosek(2,0)*3*4 + nchoosek(2,1)*2*5 + nchoosek(2,2)*1*6 = 38\r\n \r\nHint: This can be seen as the linear convolution weighted by the binomial coefficient. It is straightforward to solve this problem using a for loop. I am wondering if there exists some more elegant way (e.g., vectorization) to do this. \r\n\r\n","description_html":"\u003cp\u003eGiven two input vectors x = [x_1, x_2, ..., x_K] and y = [y_1, y_2, ..., y_K] of equal length, compute the weighted convolution output z = [z_1, z_2, ..., z_K], where\u003c/p\u003e\u003cpre\u003e     z_k = sum(nchoosek(k-1,j-1)*x_{k-j+1}*y_j, j = 1..k),  k = 1, 2, ..., K\u003c/pre\u003e\u003cp\u003eExample: x = [1, 2, 3]; y = [4, 5, 6]. Then z = [z_1, z_2, z_3] where\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ez_1 = nchoosek(0,0)*1*4 = 4\r\nz_2 = nchoosek(1,0)*2*4 + nchoosek(1,1)*1*5 = 13\r\nz_3 = nchoosek(2,0)*3*4 + nchoosek(2,1)*2*5 + nchoosek(2,2)*1*6 = 38\r\n\u003c/pre\u003e\u003cp\u003eHint: This can be seen as the linear convolution weighted by the binomial coefficient. It is straightforward to solve this problem using a for loop. I am wondering if there exists some more elegant way (e.g., vectorization) to do this.\u003c/p\u003e","function_template":"function z = weightedConv(x,y)\r\n  z = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny = 1;\r\nz = 1;\r\nassert(isequal(weightedConv(x,y),z))\r\n\r\n%%\r\nx = 1:2;\r\ny = 3:4;\r\nz = [3 10];\r\nassert(isequal(weightedConv(x,y),z))\r\n\r\n%%\r\nx = 1:3;\r\ny = 4:6;\r\nz = [4 13 38];\r\nassert(isequal(weightedConv(x,y),z))\r\n\r\n\r\n%%\r\nx = 1:4;\r\ny = 5:8;\r\nz = [5 16 46 124];\r\nassert(isequal(weightedConv(x,y),z))\r\n\r\n%%\r\nx = 1:10;\r\ny = 2:11;\r\nz = [2,7,22,64,176,464,1184,2944,7168,17152];\r\nassert(isequal(weightedConv(x,y),z))","published":true,"deleted":false,"likes_count":6,"comments_count":7,"created_by":12569,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-13T05:39:48.000Z","updated_at":"2025-12-15T03:59:38.000Z","published_at":"2016-10-13T06:12:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven two input vectors x = [x_1, x_2, ..., x_K] and y = [y_1, y_2, ..., y_K] of equal length, compute the weighted convolution output z = [z_1, z_2, ..., z_K], where\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[     z_k = sum(nchoosek(k-1,j-1)*x_{k-j+1}*y_j, j = 1..k),  k = 1, 2, ..., K]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample: x = [1, 2, 3]; y = [4, 5, 6]. Then z = [z_1, z_2, z_3] where\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[z_1 = nchoosek(0,0)*1*4 = 4\\nz_2 = nchoosek(1,0)*2*4 + nchoosek(1,1)*1*5 = 13\\nz_3 = nchoosek(2,0)*3*4 + nchoosek(2,1)*2*5 + nchoosek(2,2)*1*6 = 38]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint: This can be seen as the linear convolution weighted by the binomial coefficient. It is straightforward to solve this problem using a for loop. I am wondering if there exists some more elegant way (e.g., vectorization) to do this.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":543,"title":"deconvolution","description":"* Suppose there is a vector v like [1 0 0 -1], representing polynomial coefficients.\r\n* In this example, the polynimial is 1*x^3+0*x^2+0*x-1 or (x^3-1).\r\n* Suppose there is another vector w like [1 -1].\r\n* In this example, the second polynomial is (x-1).\r\n* If x is any integer then the polynomial represented by (v/w) is integer?\r\n ","description_html":"\u003cul\u003e\u003cli\u003eSuppose there is a vector v like [1 0 0 -1], representing polynomial coefficients.\u003c/li\u003e\u003cli\u003eIn this example, the polynimial is 1*x^3+0*x^2+0*x-1 or (x^3-1).\u003c/li\u003e\u003cli\u003eSuppose there is another vector w like [1 -1].\u003c/li\u003e\u003cli\u003eIn this example, the second polynomial is (x-1).\u003c/li\u003e\u003cli\u003eIf x is any integer then the polynomial represented by (v/w) is integer?\u003c/li\u003e\u003c/ul\u003e","function_template":"function yesno = integ(v,w)\r\n  yesno=1==1/1; % yes\r\n  yesno=1==1/2; % no\r\nend","test_suite":"%%\r\nv=[1 0 0 -1];\r\nw=[1 -1];\r\nassert(integ(v,w))\r\n%%\r\nv=[2 9 6 -1 16 -5];\r\nw=[2 3 -1 5];\r\nassert(integ(v,w))\r\n%%\r\nv=[1 4 10 20 35 50 58 58 49 30];\r\nw=1:6;\r\nassert(integ(v,w))\r\n%%\r\nv=1:10;\r\nw=1:6;\r\nassert(~integ(v,w))\r\n%%\r\nv=3:12;\r\nw=-3:2;\r\nassert(~integ(v,w))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":60,"test_suite_updated_at":"2012-03-31T22:38:54.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-03-31T22:38:54.000Z","updated_at":"2025-12-08T23:40:32.000Z","published_at":"2012-03-31T22:38:54.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSuppose there is a vector v like [1 0 0 -1], representing polynomial coefficients.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this example, the polynimial is 1*x^3+0*x^2+0*x-1 or (x^3-1).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSuppose there is another vector w like [1 -1].\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this example, the second polynomial is (x-1).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf x is any integer then the polynomial represented by (v/w) is integer?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":46663,"title":"Kaggle: Planetoid Game of Life - Variable Iterations for a wrapping array","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 377.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 188.583px; transform-origin: 407px 188.583px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.05px 7.91667px; transform-origin: 203.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGame of Life at Wolfram\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eWiki Life\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 138.467px 7.91667px; transform-origin: 138.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 360.583px 7.91667px; transform-origin: 360.583px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to Evolve a given 25x25 matrix for a given number(1 to 5) of iterations per these revised Life Laws.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 350.35px 7.91667px; transform-origin: 350.35px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e1. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 188.65px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 188.65px 7.91667px; \"\u003elive cell with fewer than two live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 115.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 115.5px 7.91667px; \"\u003eif caused by under-population.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 315.7px 7.91667px; transform-origin: 315.7px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e2. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 288.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 288.75px 7.91667px; \"\u003elive cell with two or three live neighbors lives on to the next generation.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 311.85px 7.91667px; transform-origin: 311.85px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e3. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 192.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 192.5px 7.91667px; \"\u003elive cell with more than three live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by overcrowding.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 361.9px 7.91667px; transform-origin: 361.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e4. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 242.55px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 242.55px 7.91667px; \"\u003edead cell with exactly three live neighbors becomes a live cell\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by reproduction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 265.65px 7.91667px; transform-origin: 265.65px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 34.65px 7.91667px; transform-origin: 34.65px 7.91667px; \"\u003e5. Edges \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 231px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 231px 7.91667px; \"\u003ewrap around. Eight Neighbors. (Change to normal planar life)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.317px 7.91667px; transform-origin: 221.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 146.25px 7.91667px; transform-origin: 146.25px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (A,iter) Initial state(25,25), number of iterations\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 76.2333px 7.91667px; transform-origin: 76.2333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e B the final evolved state\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function B=iterlife(A,iter)\r\n B=A;\r\n \r\nend\r\n\r\n%Non-wap Life calc by Alfonso\r\n% C=convn(A,ones(3),'same');\r\n% B = C==3 | A\u0026C==4;","test_suite":"%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 4\r\niter=1;\r\nAstr='0001100000000000001000001000000000000001110010000100000000000000110001000100000000000000001001000000000000000000000010100000000000001000000000000000000000001010000000000000000000000001000000000000000000000001000000000110000000000000000000000100100000001100000000000001010000001001000000000000001000000110000000000000000000000000000000000000000000000000110000000000000000000000001000000000000000000011100000000000010000000000110000000000010100000000000000000000001010000000000000000000000010000000000000000000000000000000000000000000000000000000000000000000000000000000100000000011000000000110110000000010010000000011110100010';\r\nBstr='0001100000000000001100011000000000000001010110001100000000000000000011000000000000000000011111100000000000000000000001000000000000001000000000000000000000000010000000000000000000000001000000000000000000000000000000000110000000000000000000000100100000001100000000000000011000001000000000000000010000000110000000000000000000000010100000000000000000000000110000000000000000000001011000000000000000000011100000000000010000000001010000000000010100000000010000000000001010000000000000000000000010000000000000000000000000000000000000000000000000000000000000000000000000000001100000000011000000000100001000000010010000000010000100000';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 16\r\niter=2;\r\nAstr='0011100100000000001111000101000010000000011010010000111101000000001000011011011100101100000110000100110000010100000000000111001000000100000100000110001100000000000100000001100000000000000101001111010011000000000011110010101010010000111101001100000110110001111111101100001011111000110110110001100001110000000000100111000011011000000011011000110000000100000001111100011000011100000001001000100000000010000001110100000001100100010001000010001100010000110000010000000000000011011100010000100000000000001011000000001000000000001101100000101000000000000100000000111101000000000000000000110000000000000000000011000100000000000010000';\r\nBstr='0000100000000000111101000000011000000000010011001110001101010000010010011010100100101100000110001100110000110010000000000001000100000110000000001011001100000000000110011000100000000000000101001100010111000000000000001010100011010000000000000011100000011000000000000111000000000000110000001111100000000000001000000100000011000000000110001100010000110100000010000111011100011010000010100111000001001000000011111100000000000001000001001110000000101110111100110000000000001101101000000000100000000000010000000001111000000000010001000001100000000000000101100001001110000000000001100001100000000000000000000000110110000000000011000';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 2\r\niter=3;\r\nAstr='0100000101000001000000110011000010000001100000000001000000110011000000000001000000011110000000010000100000000001110000000000000011000000101000000000001011110000010100000001000100100110001110000011001110011011000101100000101010000100000000000000000000000000000000000000101010000000000011101001011011110000000001111110110010001100000000001011101000010100000000000011000000010010000000010000111110000010000000010001000000000000000000001000001111000000000000000001010001000000000011000000001001000000000010100000000010100000000000100000000000000000001000000000000000101000001110000000000000100100001101111000000011000000001100000';\r\nBstr='1000001100100010001000101100000111000001000000001110000011100000000000000011000000011011011000000001101100001111111000000000110110110110100000000100011010000110100000000011000101010011011110000010010010000001000100000000010010001011100010001101000000000011000000001000110111000000000000000100000000101000000000000000000000000010000000000000010000100010000000000000100010001100000000010001111011000001000000010101100000100000000000001001011010100000000000000001010010010000000011000000011000000000000010100000000000000000110000100000000000000000101000000000000000000000010001000000000111000000010000011000000011100010001000000';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 1\r\niter=4;\r\nAstr='0000100001101010011100110000000000010000100101110000011000000110110001000000010010000010111000000010001000000000011100000001100100011100010110000000001100000111001010000001110000111100010111100000011111110100110000110001100010000100100100001000100001000110001110000000000101000000000001000000010111100000000111000000001000010000000011000000000000001100100000000000001110000011010100000000000000000011001001000000000000000000000011100000000000000000001100001111100000100000000000000110101001101100000001100000000110100110000010000000110010010000000001110000011111000111100000000000010100000000001000011000110000001100010111011';\r\nBstr='0000000000000000010000000000000000000110001110000001001100001001001111100100100110001100101100000000010000000111100000000001000000000000010000000000000001100000011100000010000000100000001110000001111101100000001110000000100001111000000010000000001001100010001101000000001101100001110000000001110011000000001111100000000000000000000011110000001100000001000000000000000000000010101010000000000000000011000111011011000010000001001011010111010010100000010100110100001010001000001110011000000100100100000011000011001110000110000010010000000001100001000010000000000011101010000000001100000001000000000000110000000011000000001000000';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 3\r\niter=5;\r\nAstr='0110000000000011000000011100000000000001100000001001100000000000100001011001001110000110000000010101000000001111100000101100000011011111100001011100000000101000000001100000001100011100000000100100001010000000000000010010000100000000000000000110000001000000000100000000001100000000000010001100000110000000010001000110000000000000011000100001000010000000011000011000100001000000000110000100010001010000000000001100000000001100000000000100000000001110000000000000000000000100100000001000000000000001010000011011000000000000110000001101100000000000000000000110110000000000000000000000100000000110000000001000000000000000000000000';\r\nBstr='1100001000000100000000011100001000000101000000001011110000000100000000001000000100000100000100000000000000000010001001000000000011111001010100100100010001100100000000000001001100011100000001010000001010000100000000000010000100000000000000010010000001000000001100000001000000000000111110001100001000000011011000001000101100000010000000000000001011000001001110010001001000100000110001100000011000010000001110000001000000011000000010000001000000010000000000000001000000011100000001000000000000000100110001000100010000000010001000000101001000000000100100100001000100000000001000001000000100000000000000010100000100000000000000010';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-03T16:50:36.000Z","updated_at":"2020-10-03T17:35:03.000Z","published_at":"2020-10-03T17:35:03.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://mathworld.wolfram.com/GameofLife.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGame of Life at Wolfram\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eWiki Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to Evolve a given 25x25 matrix for a given number(1 to 5) of iterations per these revised Life Laws.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\\n2. Any live cell with two or three live neighbors lives on to the next generation.\\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\\n5. Edges wrap around. Eight Neighbors. (Change to normal planar life)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (A,iter) Initial state(25,25), number of iterations\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e B the final evolved state\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58926,"title":"Neural Net: Convolutional NN Matrices Determination for LED Digit images","description":"This challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. A fun extension is to add LED variants and see if trained WH/WP give expected result.\r\n[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\r\n \r\nThe matlab Latex code for making the CNN Processing chart included in template.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 691.5px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 345.75px; transform-origin: 407px 345.75px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. A fun extension is to add LED variants and see if trained WH/WP give expected result.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 162.5px 8px; transform-origin: 162.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 529.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 264.75px; text-align: left; transform-origin: 384px 264.75px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline;width: 875px;height: 524px\" 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data-image-state=\"image-loaded\" width=\"875\" height=\"524\"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 257px 8px; transform-origin: 257px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe matlab Latex code for making the CNN Processing chart included in template.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [WP,WH]=ConvNN_Process(XImg,K,WH,WP,EPY)\r\n %nX=size(XImg,3); %Number training images\r\n %nK=size(K,3); % Number kernels\r\n %XC=zeros(5,3,nK); %Pre-alloc for speed\r\n \r\n for epoch=1:1000 % Number of cycles to evolve WH and WP\r\n  dWH=0*WH;\r\n  dWP=0*WP;\r\n  for iCase=1:nX  %Cycle thru all Images while accumulating dWH and dWP\r\n %Forward Pass  X(7,5,nX)-Ximg,Conv-XC(5,3,nK),ReLU-XCY3(5,3,nK),XCY(1,nK*15+1)(1,91)\r\n % XCYV*WH-H(1,21), ReLU(H)-HY(1,21), HY*WP-P(1,10), Softmax(P)-PY\r\n   for k=1:nK\r\n    %XC(:,:,k)=(conv2(XImg(:,:,iCase),K(:,:,k),'valid')); %Use rot90 Kernel to make output align\r\n   end\r\n\r\n   %XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive; safer to leave in for K offset case\r\n   %XCY=[XCY3(:)' 1]; % 1,nK*15+1  (1,91)  add a 1 for offset term\r\n \r\n   %[dWPi,dWHi]=Neural_ReLU_Back_Propagation(XCY,WH,WP,EPY(iCase,:));\r\n \r\n %Accumulate across all sample cases\r\n   %dWP=dWP+dWPi;\r\n   %dWH=dWH+dWHi;\r\n \r\n  end % iCase\r\n\r\n  %WP=WP+dWP/nX; % dWP/nX  Valid\r\n  %WH=WH+dWH/nX; % Usage /nX^2 requires 10K epochs for \u003e.8 PYs\r\n\r\n end % epoch\r\nend %ConvNN_Process\r\n\r\nfunction [dWP,dWH]=Neural_ReLU_Back_Propagation(X,WH,WP,EPY)\r\n% X will be single case [X1 X2 ... XN 1]\r\n  LR=1; % Learning Rate\r\n  \r\n  H=X*WH;\r\n  HY=max(0,H); % ReLU\r\n  \r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 PY2 ... PYM]\r\n  \r\n  %Back Propagation Calculations\r\n  ErrPY=EPY-PY;\r\n  \r\n  dPY=PY.*(1-PY).*ErrPY;\r\n  dWP=LR*HY'.*dPY;\r\n  \r\n  dHY=HY.*(1-HY).*sum(WP.*dPY,2)';\r\n  dWH=LR*X'.*dHY;\r\nend % Neural_ReLU_Back_Propagation\r\n\r\n\r\n%{\r\nfunction NNConv_flow\r\n%Convolution neural net process flow\r\n\r\n%shape prep\r\nr = 10;r5=5;\r\nphi = 0:0.01:2*pi;\r\ncxA = r*cos(phi);\r\ncyA = r*sin(phi);\r\n\r\nrxA=[0 2*r 2*r   0 0]';rx5=[0 r r 0 0]';\r\nryA=[0   0 2*r 2*r 0]';ry5=[0 0 r r 0]';\r\n\r\n\r\nf=figure(1);clf;\r\nf.Position=[1935 122 1459 873]; % Dual Monitor setting\r\n\r\nplot([0;160;160;0;0],[-5;-5;100;100;-5],'k','linewidth',2);hold on\r\nxticks([]);yticks([]); %Ticks/Labels off\r\naxis equal;axis tight;\r\n\r\npatch(rxA*1.9+48,ryA+75,'y')\r\ntext(50,93,'Images','Fontsize',14);text(65,93,'Kernels','Fontsize',14);\r\nfor j=0:3\r\n plot(rx5+50+j,ry5+81-j,'k','linewidth',1);\r\n plot(rx5+65+j,ry5+81-j,'k','linewidth',1);\r\nend\r\ntext(79,90,'EPY','Fontsize',14);text(79,86,'WH','Fontsize',14);text(79,82,'WP','Fontsize',14);\r\ntext(49,76.5,'Initial Inputs','Fontsize',14);\r\nquiver(86,86,3,0,'k','LineWidth',3.5,'MaxHeadSize',1);\r\n\r\npatch(rxA*3.5+89,ryA*1.9+56,[1 .75 .4])\r\ntext(90,92.5,'Epoch:  Cycle over Training Images (1K to 10K)','Fontsize',14);\r\ntext(92,89,'Loop over Images to Update WP and WH','Fontsize',14);\r\ntext(92,86,'dWP=0;  dWH=0','Fontsize',14);\r\ntext(92,62,'WP = WP + dWP / nX   %nX = # Training images','Fontsize',14);\r\ntext(92,58,'WH = WH + dWH / nX','Fontsize',14);\r\n\r\npatch(rxA*3.3+91,ryA*0.95+65,[.75 1 .4])\r\ntext(92,82,'Cases:  Cycle thru Training Images','Fontsize',14);\r\ntext(94,79,'Loop over Convolutions per Training Image ','Fontsize',14);\r\ntext(94,75.5,'Create XC ( : , : , k ) - Convolution Planes Image_{i}','Fontsize',14);\r\ntext(96,73,'Create XCY - Convolution Set Vector [1,91]','Fontsize',14);\r\ntext(98,70,'Perform dWP dWH Back Propagation','Fontsize',14);\r\ntext(98,67,'Update dWP and dWH','Fontsize',14);\r\n\r\npatch(rxA*3.5+89,ryA*2.4+7,[.4 1 .75])\r\ntext(96,53,'Processing Numerical Convergence Concerns','Fontsize',14);\r\ntext(90,49,'Kernels need to be scaled(sum \u003c=1) or offset(sum~=0)','Fontsize',14);\r\ntext(90,45,'WH and WP require offset and scale normalization','Fontsize',14);\r\ntext(90,41,'WH=[(rand(90,20)-.5)/sqrt(90+20) zeros(90,1)]','Fontsize',14);\r\ntext(90,37,'WP=(rand(21,10)-.5)/sqrt(21+10);','Fontsize',14);\r\ntext(93,33,'Offset to achieve zero-sum','Fontsize',14);\r\ntext(93,29,'Scale to avoid large positive sum','Fontsize',14);\r\ntext(90,25,'nX factor for WP, WH updates needed for convergence','Fontsize',14);\r\ntext(90,21,'Scale mods change convergence rate and stability','Fontsize',14);\r\ntext(92,17,'(2*nX) requires 2K Epochs to achieve .90 Predictions','Fontsize',14);\r\ntext(90,13,'WH w=20 was arbitrary at 2 * # Classes','Fontsize',14);\r\ntext(90,9,'WH h=91 is conv(h*w)*Kernels +1 ','Fontsize',14);\r\n\r\npatch(rxA*3.5+89,ryA*.5-4,[1 .4 1])\r\ntext(90,4.5,'Kernels are to capture features','Fontsize',14);\r\ntext(90,1.5,'Internal Corners and Straights were selected','Fontsize',14);\r\ntext(90,-1.5,'Centering done for debugging (not required)','Fontsize',14);\r\n\r\ntext(1,97,'Convolution Neural Net: Forward Pass and Back Propagation WP \u0026 WH','Fontsize',20);\r\n\r\ntext(1,93.5,'\\color[rgb]{1 .5 .2}Ten Input Images(7x5) [Ringed by 0s]','Fontsize',12) %Valid\r\ntext(1,91,'\\bf 1  111 111 1 1 111 1   111 111 111 111','Fontsize',9,'Fontname','Courier')  %bf bold_font\r\ntext(1,91,'\\bf\\color{red}. .          .       ..','Fontsize',9,'Fontname','Courier')  %bold_font, color\r\ntext(1,89,'\\bf 1    1   1 1 1 1   1     1 1 1 1 1 1 1','Fontsize',9,'Fontname','Courier')\r\ntext(1,89,'\\bf\\color{red}. . ..  ..   .   ..  .. ..   .   .   . ','Fontsize',9,'Fontname','Courier')\r\ntext(1,87,'\\bf 1  111 111 111 111 111   1 111 111 1 1','Fontsize',9,'Fontname','Courier')\r\ntext(1,87,'\\bf\\color{red}. .                     ..           . ','Fontsize',9,'Fontname','Courier')\r\ntext(1,85,'\\bf 1  1     1   1   1 1 1   1 1 1   1 1 1','Fontsize',9,'Fontname','Courier')\r\ntext(1,85,'\\bf\\color{red}. .  .. ..  ..  ..   .  ..   .  ..   . ','Fontsize',9,'Fontname','Courier')\r\ntext(1,83,'\\bf 1  111 111   1 111 111   1 111   1 111','Fontsize',9,'Fontname','Courier')\r\ntext(1,83,'\\bf\\color{red}. .         ..          ..      ..','Fontsize',9,'Fontname','Courier')\r\n\r\ntext(1,80.5,'\\color[rgb]{1 .2 .5}Six Conv Kernels (3x3) TL TR LL LR V H','Fontsize',12) %Valid\r\ntext(1,78,'\\bf         1   1   1  ','Fontsize',9,'Fontname','Courier')  %bf bold_font\r\ntext(1,78,'\\bf\\color{red}... ... . . . . . . ...','Fontsize',9,'Fontname','Courier')  %bold_font, color\r\ntext(1,76,'\\bf 11 11   11 11   1  111','Fontsize',9,'Fontname','Courier')\r\ntext(1,76,'\\bf\\color{red}.     . .     . . .','Fontsize',9,'Fontname','Courier')\r\ntext(1,74,'\\bf.1. .1. ... ... .1. ...','Fontsize',9,'Fontname','Courier')\r\ntext(1,74,'\\bf\\color{red}. . . . ... ... . . ...','Fontsize',9,'Fontname','Courier')\r\n\r\ntext(1,71,'EPY=eye(10)','Fontsize',18,'Color','b');\r\ntext(1,66,'XC(:,:,k)=conv2(XImg(:,:,i),K(:,:,k),''valid'')  % [5,3]','Fontsize',18,'Color','b');\r\ntext(5,61,'XCY3=max(0,XC)  % ReLU [5,3,6]','Fontsize',18,'Color','b');\r\ntext(5,56,'XCY=[XCY3(:)'' 1]   % [1,91]','Fontsize',18,'Color','b');\r\n\r\nstr='$$ XCY*WH=H ; $$';\r\ntext(1,51,str,'Interpreter','latex','Fontsize',16);\r\nstr='$$ H=\\left[\\matrix{ H_{1} \u0026 ... \u0026 H_{20} \u0026 1} \\right]  $$'; \r\ntext(32,51,str,'Interpreter','latex','Fontsize',16);\r\n\r\nstr='$$ ReLU(H)=HY  $$'; \r\ntext(1,47,str,'Interpreter','latex','Fontsize',16);\r\nstr='$$ HY=\\left[\\matrix{ HY_{1} \u0026 ... \u0026 HY_{20} \u0026 1} \\right]  $$'; \r\ntext(32,47,str,'Interpreter','latex','Fontsize',16);\r\n\r\nstr='$$ HY*WP=P;  $$';\r\ntext(1,43,str,'Interpreter','latex','Fontsize',16);\r\nstr='$$ P=\\left[\\matrix{ P_{1} \u0026 ... \u0026 P_{10} } \\right]  $$'; \r\ntext(32,43,str,'Interpreter','latex','Fontsize',16);\r\n\r\nstr='$$ Softmax(P)=PY;  $$'; \r\ntext(1,39,str,'Interpreter','latex','Fontsize',16);\r\nstr='$$ PY=\\left[\\matrix{ PY_{1} \u0026 ... \u0026 PY_{10}} \\right]  $$'; \r\ntext(32,39,str,'Interpreter','latex','Fontsize',16);\r\n\r\ntext(5,34.5,'Softmax(P)=e^{P}/\\Sigmae^{P}','Fontsize',20,'Color',[1 .5 .2]);\r\n\r\ntext(1,28.5,'[ dWPi , dWHi ] = ...','Fontsize',18,'Color','b');\r\ntext(1,23.8,'Back\\_Prop\\_WP\\_WH ( XCY, WH, WP, EPY(i,:) )','Fontsize',18,'Color','b');\r\n\r\ntext(15,19,'WH','Fontsize',18);\r\nstr='$$ \\left[\\matrix{ WH_{1,1} \u0026 ... \u0026 WH_{1,20} \u0026 0 \\cr WH_{2,1} \u0026 ... \u0026 WH_{2,20} \u0026 0 \\cr : \u0026 : \u0026 : \u0026 0 \\cr WH_{90,1} \u0026 ... \u0026 WH_{90,20} \u0026 0 \\cr bH_{91,1} \u0026 ... \u0026 bH_{91,20} \u0026 1 } \\right]  $$'; %valid\r\ntext(1,6,str,'Interpreter','latex','Fontsize',18);\r\n\r\ntext(58,19,'WP','Fontsize',18);\r\nstr='$$ \\left[\\matrix{ WP_{1,1} \u0026 ... \u0026 WP_{1,10} \\cr WP_{2,1} \u0026 ... \u0026 WP_{2,10} \\cr : \u0026 : \u0026 :  \\cr WP_{20,1} \u0026 ... \u0026 WP_{20,10} \\cr bP_{21,1} \u0026 ... \u0026 bP_{21,10} } \\right]  $$'; %valid\r\ntext(48,6,str,'Interpreter','latex','Fontsize',18);\r\n\r\nend %NNConv_flow\r\n%}\r\n","test_suite":"%%\r\nImgsetstr= ... %5x3 digits 1:9 0\r\n ['010111111101111100111111111111';\r\n  '010001001101100100001101101101';\r\n  '010111111111111111001111111101';\r\n  '010100001001001101001101001101';\r\n  '010111111001111111001111001111'];\r\nImgsetv=Imgsetstr-'0';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\nnClasses=10;\r\nEPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nKsetstr= ... %3x3 kernel mask (will be scaled/offset)\r\n ['000000010010010000'; %Centered corners and vert/horiz\r\n  '011110011110010111'; %Kernels are identifying Features\r\n  '010010000000010000'];\r\n\r\nKsetv=Ksetstr-'0';\r\nKh=size(Ksetv,1);\r\nnK=size(Ksetv,2)/Kh; %Number of Kernels\r\nKset=reshape(Ksetv,Kh,Kh,nK);\r\n%Kernel needs normalization either scale or offset; Two large scale slows convergence or possible fail\r\nKsetr90=rot90(Kset(:,:,:),2)/3; % Rotate and normalize 3, each kernel sum is 3 Valid  2-Fails\r\n%Ksetr90=rot90(Kset(:,:,:),2)-.5; % Rotate and offset -0.5  Valid \r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\n%Stability sensitive to WP and WH values; rand start needs offset and normalization\r\n% X(7,5,nX) XC(5,3,nK) (XCY(1,91) WH(91,21) WP(21,10)\r\nztic=tic;\r\nfor ztry=1:5 %Allow five processing attempts to get a working solution\r\nWH=[(rand(90,20)-.5)/sqrt(90+20) zeros(90,1)]; % 90=nK*15, 20 is arbitrary at 2*nCases WH(91,21)  Valid\r\nWH=[WH; zeros(1,20) 1]; % offset row, Start with zero bias\r\n\r\nWP=(rand(21,10)-.5)/sqrt(21+10);  % 10 output states  Valid\r\n\r\n[WP,WH]=ConvNN_Process(XImgset,Ksetr90,WH,WP,EPY);\r\nfprintf('Process Time: %.3f sec\\n\\n',toc(ztic));\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),Ksetr90(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 PY2]\r\n  [~,pcase]=max(PY,[],2);\r\n  [~,pexp]=max(EPY,[],2);\r\n  \r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  \r\n  if isequal(pcase,pexp),break;end\r\n  \r\nend % ztry  Allowed 5 trials as rand may not always converge\r\n  \r\nvalid=isequal(pcase,pexp);\r\nassert(valid)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":3097,"edited_at":"2023-08-30T05:22:25.000Z","deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-08-30T04:01:42.000Z","updated_at":"2023-08-30T05:22:28.000Z","published_at":"2023-08-30T05:22:28.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. A fun extension is to add LED variants and see if trained WH/WP give expected result.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"524\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"875\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe matlab Latex code for making the CNN Processing chart included in template.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc 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GNZBb6wuFGhmx9vA2qHZRZjc3N4NslRm4ly5dqr9cBCUbNWqkLLGwvcw3+vr160Wturi49OzZs1evXuI1e+UJdoFERrRardjfnj17WlV4WZZTUlJEkVxcXEJCQsLCwrp16yZSurq66tez5SlNsrxI1p4c8l/JIllukRFxnwZAiXZZu0eyLJ86dUqZBVYcz8ocH/7+/qKEJk+qohLUarUlMzfZcKiYOYCtPZ87OzuLBHXq1Bk4cGBYWJiIKLm6uh45csTmqtu4caNoX2dn55CQkF69eolzl7+/v1hFPzJiYc7F+XdNvEtiEIYLDQ1VFj558kRkqL/jjx8/Fgv1b/5tOB7MW7VqldiRV155RRQJwIQJEyxZtzB2UGZkhJ5Hyqm4qAtChYsNTEXDzClm5MiR4iODngJ5un37trj4rl69+pkzZ5TlUVFR4v1kX19f5XGH8qsM4Isvvnjy5IlYfubMGSWxkkO3bt0AdOjQwWCL8fHxIgcxP6tVBchPZEQQd7aDBg1SlhhfQRZeneRGPy6g3Lb5+vrq97gxjgtotVrxarS3t/exY8f0a1hMReTv72++NvKsVQAffvhhXFzcnj17xB14QkKCuKobNGiQ/nOw69evi/s3Ly8vSzb67GtANtX6wsyZM0NCQkJCQkx2cTLOwfwIrPrpbTu89atduUE6ePCgsrryuBJGdwvt2rUD8PXXX4v/Wt5eZhr99u3bov+5v7+/0kXl8ePHyh2FJU0sW3B7o4x/JJ6KW3WwjRo1CkDt2rVv376tLIyPjxf1P2DAABtSGrOqSFadHAqkkkWybt26bctp7dq1H3/8sXjyP2bMGJv3SKvViu4Y3t7e+v1r1q5dKzYtDjzjk6rYC2dnZwufyVt7qMi5H8A2n8/173iTkpJEbfj5+SmJraq6mzdvivZt3bq10r5arVbM3ioo989W5SwX19+1d955B0bXACI0o+yp6OgxatQoJYE4ltRqtbJR2abjIU8ff/yxso/u7u6LFy+2cEVFAe6g/DQy0qxZs6W5++KLL0SBGRmhEkH5ihV1QahwsYGpaJg5xYSFhQFQqVTW5jlhwgTxI238pFSZjm7WrFliiXK1ZPxYRrwgo3/tLn7+VSqVQTfdsWPHAqhdu7YNBXg2kZHCq5Pc6McFZFlW3ijRfzfKOC6gdBQyeIwpy/Lp06cNLrVti4wEBwcbJBYXoO7u7sZBBGWAG+WCz7bISCHVgJx7ZMRyeQ6Y5+3trZ/etsPboNpF9xD955nz5s0DIEZZ1u/88uDBA3FDdfr0abHE8vYy0+jffvstAGdnZ4M3d7RarQ19Rvr06fMgp2PHjq1evVqcxABUrlxZdN6x6mATTaP0RFNMnjzZ399ff7nlKY1ZVSSrTg4FUsnmD04Y9WKwdo+UL6bxN07c4fv4+MhGJ1URFnFxcdmxY4f58iusPVTk3A9g287nxi9lKKcU5abUqqoTxXBzczN+eqF03FBOVlblLBfX3zXRL0OtVisBF7Eh/bdLxJ6Kd0+E0aNHA2jfvr1+VjYcD+bNmzdPf2xaJZRslQLcQflpZMRCjIxQiaAcsUVdECpcbGAqGmZOMeLSU3/oBAuJd5579epl8lPx/DkoKEj8V7laWrVqlUHKzZs3i4/u3bsnlmi1WvGEatq0afopxcP8b7/91oYCPJvISOHVSW4M4gKyqTdKjOMCop9z27ZtTeYp5iBU9tS2yMjy5csNEmu12oSEBOP7Iv21jO9VrI2MFEYNyEURGbHt8DaodtHHoV27dsoS8X1funSpiINcuXJFLF+6dCme3p0KlreXmUYXd27GY53Isjxr1iwLm1h+2srmubu7R0VFWVt4+enBYNCXwSTLUxqzqkhWnRwKpJLzrF61Wj1q1Cj9bghW7ZEYeqNZs2bGiS9cuLB8+XKRj/5JVazi6upq8HKcedYeKnLuB7Bt5/MtW7bklrhPnz7iv1ZVnSiGyZOP8paTEhmxKme5uP6uKYFapb/buHHjkPOFEWW+YeXNx9atW8MohGfD8ZCbR48eBQcHi1Xat2+vjIFqediuMHZQfhoZcXJy8sidUg+MjFCJoHw9i7ogVLiK3ZQHROIt6MzMTJ1Opz+4Wp5iYmIAdOnSxeSnrVq12rNnj/EUqi+88ILBEuX95ydPnog/VCrVgAEDpk6dumjRoo8++kgs3L9//6VLl1Qq1cCBA/NTgEJVeHViuVmzZu3Zsyc1NTU8PDw2NtbkrBk7d+4UW1mzZo3xp6LnfG6TUFioRo0aBktUKlX16tWVOaEzMzNjY2PPnTsXFRWlzERYIIpJDZjUokWLb775xuRHBuW07VgyqPbu3btPnTp13759mZmZYqfEgAVdu3Zt1qxZVFTUrl27wsPDAYh66N69u7KuDe1l3OhiZkplOAl99evXN5mJtVQqlZ+fX7du3T7++GPl2alVhR82bNjff/9948aN+vXr+/r6du3atVOnTvpDM9iQ0mQ5bTj+LTk5FGAlDx06dPr06cp/dTrdnTt3oqKifvvtt4iIiKlTpyYnJy9atMiGPRL9JsQrbAZq1qxZs2ZNg4UfffSRmKejRYsWbdq0sWovcmPyUNFncADb8B1UqVQdO3Y0Tuzr67tnz55Tp04pySysOp1OJ4phMlv9gVGszdlyz/53zdXVVZygoqKiWrZsiaez1ervb9OmTT08PG7durVjx45+/fppNBrR7cJkRZmU5/Fg4M0339ywYQOAadOmffTRRydPnmzRokVGRkbv3r2PHj1atWrV8ePHz549+9VXX122bNmz38GuXbsqkTJj27dv79SpU577SET0LDEyQsVOw4YNxR/nzp1ThuXPU0ZGhk6ng6mrH0F0409PTzdYbuGV+sCBA6dOnXr8+PFz586JrH7//XcAQUFB4grG5gIUnsKuEwt5enrOnDkzNDT00qVLn332mf59juL+/fsAdu3aJaYANElcDdsstxkif//997/++mvv3r1paWn5yd+MYlIDJnl4eFhy4W7zsWRQ7W3atPH09ExNTd20aVNISMjhw4fT0tKaNWvm5ubWrl27qKioiIiI8PBwnU4nHue+8cYbBhla1V4GW9doNJmZmQD0O58rGjVqlGeGBvr06fO///1Pf4lKpXJ2ds4tpGth4Tt27DhnzpyPPvpIzEo7Y8aMGTNmqNXqkJCQIUOG6LeX5SlzY+3xn+fJoWArWaVSGcz16+3tLUbS6du379KlSxcvXvzxxx/rZ2vhHokpUUuXLm1hSf755x8nJ6fMzMwdO3b88ccf/fr1s2pHrD1UBP0D2LbvYG6bqFu3LoCEhAT9hZZUnVIMkxFe8WDDWAGeZovqdy0wMDAqKmr//v0ffPDB/fv3RVCgQ4cO+mk6duy4fPnyTZs29evXb+vWrTqdzt3dvWnTpsa52XY86Fu2bJkIi0yZMkU8sGnQoMGCBQv69OmTmpr6xhtv7N+/f/Xq1cnJydevX3/2O0hEVBIxMkLFjhIZiY6ONh8ZiY2NnTJlSlBQUJcuXSy/wLVNnTp1mjVrduTIkd9//33SpEkajeavv/4C0L9//0Ld7vPhrbfe+uuvv1auXDljxow333zTOIG40vX39xcj5JtUtmzZgi1Venp6UFDQvn37xH9dXV3btGlTo0aNdu3a6XQ65X3vAlE8a6BIdOvWbcGCBVu2bAkJCRGPJUXv9w4dOkyZMmX79u0A9u7de//+fQ8PD/2H84XdXlb1UBPUarUlfeNhfeEHDx7ct2/flStXrl+/ftOmTenp6RqNZuXKlStXrhw5cqR+cM3ylPksUoGwoZJz8/nnn4tXrtatWyciI4W6R+7u7ps3b54wYUJERMT777/fqVMnk6Gf3Fh+qBSs3Cr80aNH+p/aUHXilJWnIjnMCkNgYODkyZPFCWrTpk0AfHx8lHm1hODg4OXLl+/duxfAgQMHkHvHlvwfD+IKxNvb+9NPP1UW9u7d+9ixY1OmTDly5EhgYODJkycBGMzZnJuC3UEiopKIkREqdgICAtzd3e/evbtkyRLzz+VWrly5cOHChQsX7tu3r02bNiqVSqfT3b5922Ri0W04tydalhg0aNCRI0f+/PPPSZMmrVu37v79++7u7m+99Zb4VDztKZACGF9xZmRk2FDgAixS/s2ePVt5o0QZa0Dh6uqalpbm7+//ww8/WJ5nPitqzJgx4np93Lhxw4YN07/PEc/iClZh1MAzU4DHUnBwsIiMABD1Lx5LBgYGqtXq1NTUs2fPioiJ8gq9kP/2UqvV4rH/jRs3jD+9cuWKJZnYxobCu7i4hIeHi3eLDh06tGnTptmzZ6emps6YMWPgwIH6vSQsT5nPIlnimVWycs+mTG9k1R5VqlTp/Pnzjx8/Npm58bucCxcubNmy5dy5c2vXrn337t13331XmcXm2bDtO5ienm7yvdRz584BUF4asrzqXFxc1Gq1RqO5du2acRmMG73AD7Oi+l0TJ6i7d+9evnxZnKCMgwLiVHbt2rXU1FQxKoeY2K4wJCcnA2jWrJnB8u++++7kyZMRERGRkZEAPDw8lBd+zStuO0hE9OwV2NMbooKiUqkGDx4MICIiIjo6Ordkd+7cEQPL+/r6igfLYlQ2ccdl7OjRowDy8354WFiYWq2+fPnyoUOHFi5cCKBfv376V5wFVYBbt24ZLLl06ZJtZS7sOrGch4fH7NmzAVy6dOmrr74y+DQgIACAMq2AgU2bNi1btsz4YMhnRc2fPx9AaGjo+PHjDR7/mrzoz6fCqIFnqaCOpW7duqnV6kuXLsXGxu7cuVOtVouXPtRqdWBgIIBdu3atX78eQEhIiP6KBdJeYvAL8bTTgBhFopBYXvjMzMxNmzbNnz9ff1iZli1bTpw4URkBUbxXZXnKfBbJWs+mkg8dOiT+EC+GwMo9atKkCYDY2FjjnI8fP+7g4FC2bFkRPhDEPLWVK1eeNGkSgHXr1injmzwzNnwHdTrd4cOHjROfOHECTysBVladGGHX5CghypimisI4zIrkd02lUokTVFRUlDhRGwcOvLy8RCBy3759Yugog7dRClC5cuXwtB0N/Pnnn0rfw0GDBpl878lYcdtBIqJnj5ERKo5GjRrl5uYGoFevXomJicYJNBpNeHh4amoqADGCOoAePXoAWLNmjfFAlYcPHxazgeQ5H4cZrq6uolfqqlWrRF/TQYMG6SfIZwGUwfbEox59Nl+CF3adWKVnz55ilhbltk0hnjsdPHhQXGzpS0xM7N69e58+fZR5bQuqosQb7+XLlzdYrtPpRAgDNo04a0ZB1UCRKKhjSa1WBwUFARg3bpxGo2nbtq0yDqIIkSxYsCAmJsbJycngaWSBtJcYuOTvv/8Ww0zoU6bwLAyWF16lUnXv3n3QoEHGgxdWrlxZ/CECspanzGeRrPUMKlmj0Xz55Zfi79dee038YdUeKd844+DIihUrAJQtW9bgVQLh/fffF6GfDz74QDy3f2Zs+w4q+67YvXv38ePHAYh+RrCy6t5++20AGzZsMIi5pKWlTZ482SCHwjjMiup3TZygNm3adPbsWbVabXITYsjSpUuXajSaBg0aWDV/rVXEhGWXL182Hl01Pj5e6Uj1v//9z2T4z6RitYNEREWgqCfHITuV5xG4fPlykcDd3X3KlCkpKSliuVar3bJli3hkBKBnz57KKrdv3xZz61atWvXMmTPK8qioKPGoqnr16o8ePRILlZn8bt68abBpMx/t2LEDTwe0r1evnsGnVhXAeBZYrVYr4kG1a9e+evWqWHjz5k39l4T1p7oUT9QbNWp07949sdx4dsNnUCcGjOes1Xfz5k1RHkGZs/bx48diCmRPT0/9GQevX78uegu7uLgo87laVVEmJ4YUxG2Pj4/P7du3lYX37t0TM6EKu3btMsjHhll7C7wGZFOtL8ycOVOMT6k0a27EVW/Xrl3NJ1PYdngbV7ssy3PmzFFqYMKECfpZKcuN53y1vL3MbP3x48dimgw/Pz/9I2r48OEmv2W5Ea3cv3//PFNaW3hZlkXvd+PZYYcOHSrOP8qsmZanzGeRrDo5FEgli2Rdu3bdmNP69eunTJmiDEGlzDtr7R5ptVqRiY+Pz4ULF5T069evF2f4KVOmyKZOqrIsx8XFiXFhu3XrZn4vZOsPFTn3A9i28zlyzqt64sQJkVh/jnCrqk6WZdFxwN3dfd68eWLi5IMHD77yyitKYmXWXmtzLp6/a0r+eHoB0L59e5NpRJ4izciRI40T2HA8mHTz5k0PDw/RCkrNaLXaGTNmiDeJlB46np6ep0+ftiTPAtlB+emsvfoz/uaWDzhrL5UQyvmqqAtChYsNTEXDklPMwoUL9WclcHV19fDw0F/Ss2dPg9u/yMhIcdmhUqk6dOgQFhYm+v2Ki4NTp04pKW2+Wqpatar4dNq0acafWl4Ak3fa06ZNEwvVanWHDh06dOggrj++/vpr48SjR4+GnsePH5u8iH8GdaLPfFxAluVVq1YpZVbiArIsnz59WgkZtGjRIiwsLDg4WOlNsHbtWv1MLK8oMzfJYvhGAF5eXv379x86dGivXr1Ex2PlFk65aCuoyEhB1YBx64vlSj8mkyEJfdZGRmSbDm+TxUhKSlJKTTfNyAAAIABJREFUHhkZqf+RMirh4sWLDdayvL3Mb/3IkSPizQi1Wh0cHBwaGip6WCjDmhRGZMSqgy0pKUl5Etu6deuwsLDQ0FDlzDNz5kz9mrQwZT6LZO3JIf+VDAu0b99ev4mt2iNZ7xunUqmCgoLCwsKUURuCgoIM9k7/pCrL8oQJE8TyhQsXmt+RAoyMyDadz8WLFb6+vmFhYZ07dxbdiKpXr56UlGRz1V29elWZiFelUimnKaWXgVJd1uZcPH/XFMoJSj/YpE+r1Sq1sXnz5txyyH9kRJblHTt2KG/K1KlTp2vXrsp/fXx8EhISlB9KV1fX+Ph4S/LM/w7KjIzQ80g5KRV1QahwsYGpaFh4iomPjx84cKDxW7LNmjVbvny5yVUuXLgQEhKi34dcrVYPHTpU/ypQzsfVknh5R61WK91YbCtAbnfaM2bM0O9T4OnpOW/ePKXG9BPfvn1b9GtVrhpzu4gv7DrRl2dcQJZl8UYJcsYFZFlOSkoaMGCActUltG7d+uDBg8aZWFhR5m+SFyxYoJ+JOLTE005xjzRw4ECDfPIfGSmQGjBufbG8UCMjsvWHd27FEF3BnZ2dxQNnRWhoKACVSnXv3j3jtSxsrzy3Hh8fL97oEVQq1fDhw5UBHQsjMmJ54YXr16+HhoYavAtTr14947sIy1Pmp0g2nBzyWckwRcxs6uPjExoaavKuzKpKlmX5ypUrBrXn6uo6btw45bDM7aSq1Wrr1asHwN3d3eDgN1CwkRHZ+vN5XFycfgcNlUr1zjvvGLejtVV37969sWPH1q5dW61WOzs7d+7cedeuXfobtS3n4vm7phAnKADHjh3LLY0I/6nVaoOTm1CAkRFZlk+dOtW6dWv9unVzcxs9erRy5Ij318z/HunL/w7KjIzQ80j5ihV1QahwSbJlT2aICpYkSeIPC4/A2NjYhIQEjUbj5OTUqlUr8TKFGRqNZufOnRqNxsXFpU2bNga3ms9APgtw6NCh27dvu7m5tWrVyvw8l5mZmdHR0U2bNtXvTVMYRXpmdDrd3r1709PTVSpVixYtjF9Q12d5RZkRHR2dkpJiyeaeDctrwPLWL1hFeywVVHslJycfPXr0Gbe7VYXXaDT79+8XR0Ljxo3NTBNrecp8Fslaxb+SAWRkZOzdu1ej0eTzTPIs5fkd3L59e6dOnQCI1y6uXbt24sQJMcqmmdNFPg+GDRs2vP766wAeP35ssBWrcn7+ftcKVWpq6tGjRzMzMytUqNCyZUuDA1jUZFGVjej5YO1tC5VQjIxQ0eAphoiIqJAYREYKMOdvvvkmJiamffv2Q4YMMfjov//975gxY9zd3e/cuVOAWyQiKlq8bbET9hhcJyKiAqdcNxDZLXu4aNbpdMuXL9++fftbb72l3/vjxo0bP/30E4A333yz6EpHRERkI/YZoaLB4CvRc0aSJH6byZ5JUjH6RSu8PiOJiYl16tRJS0vz8fF57733atWqpdPpjh8/PmvWrNTUVE9Pz2PHjinzRhMRPQd422In2GeEiIiIiCxStWrV9evX9+3b99KlS6NGjdL/qEGDBqtWrWJYhIiISiL2GaGiweAr0XOGfUbIzhWrPiPJycm7du0C0LNnz8IYoVmj0axbty4iIiItLQ1A1apVu3TpEhgYWOAbIiIqcrxtsROMjFDR4CmG6DnDyAjZuWIVGSEiooLC2xY7UQKmpiMiIiIiIiIiKiQcZ4SKF/nyP9LtRNOfVW2MCtUKYBs3E5B4Ao27F0BWJum0UDkUwXYLRNwe+XGa5NsKV06Y+LRaY7iUM7f6uUj9/8mu5aUX6wDA1hlo0QvlXjReQz6xXtLpAKBWa7hWwMXDuHcj+2NJktWlpAo1UalWdvrKDQvmSMiLfOmIpNXCt6XhB8fXoUqjfJUhM12O3y89SEX5Kni5Xd7FuHsdAKq9Ao+qtm+UiIiIiIhMYWSEihfp9HbEbMn6z6N7UDmilIv4nxz0sVQg98OXjmDTd4UUoZBPbpTOR6HnxGe83YKRfgfrvpGG/IGkeCwfZSLBkCXmIiPpd7D0A/0F0suvovdUAHKll6S/x2Pg/4xXkjZ+jzLl4VULVerDtQIOr8CVY6jkl/WxLEtXT0HzGP790PnDrPSvffJsIiPS0b+RmW4iMrJ+Mrp9bnsZ0m5h7tuS2glevtgzFxVrYcCvpqNpohg34nDlOOJ2yz0mSM9LZOTsWUydioAAhIcXdVFKgvnzceAAPv8cvr45lh8/jpkzUaoUJk5EgU4/YpHp05GQgB9/fNbbfV5x3msiomKCb83YJ0ZGqJjpOhpdR2f9/UMQqjdGr8nifyXimlE6tx+aJ0VdClvt+BUN/w03L7h5YVx09vL0O5gdhnpBqPSyudVFN5MvD8LB0eATqcG/sXeBHLNFqtfFxIq1Wmc3OoAq9dB3evZ/ZR3WT8LBP9DgNVR6GR+uV4JlJdXW6XB2xeCFUDsh7SZmheLQn2jVP9f0rfqhVT9MaPoMi1jorl7FvHkAGBmxyO7dWLwY4eE5IiPHj6N9e2RkYP36IgiLANi6FVFRjIwUJHnXu0VdBCIieye1N/Ekj+wBIyNUAmWmy/GRUma67OQi/Ssw+2H7+UOoVAsZD+VrJyCppKqNUD6vuQPNrCI+SruNpDOyupRUqw1KlXn60QFUfAluXln/TYqTdVrpxTry9VjpwS3onuBcJHxbmukF8HS7D3D1pOyglmq1gbMbkuKRdEZ2UEsvvwonvZv/+8ly4gkp85HsoDbcqfvJckK0pNOiamM4OskPUqTK9fOoJQAXD+N+kqxykCr6KW+p4H4yjq3B8JUmSrtmPFzKodMIAEi9iDs3UL1RVm1on+DCYZT3hmdNpF5E+arGYZEsTd+Q9s2HyciIeZIKbQfi2Bo59YJU6WVcP4OKPlmVb77Fbauce9fly8cg66QaTfIomNJefu2yaiMpTs58KFV7RT+NrM3I3i4AnRYxEXj9C6idAMC1Aup0wslN2ZERk61DlFN0NDp1gkaDLVsQEFDUpSEiIiIq4RgZoZImKQ5/jJScXODlK12PxY5ZeHt21n3yitHwa41z+6QaTZB8Hmm35QG/5LhNNWZmlRWjUb0hbpxDzRZSchw2T8XAOahQAwCWfiJ3/1Jq8O+sTPb/LmWmo+906cIh3L4CWUb0CtRsZi4ysmI0XmqBS4dRrZF05Thc5qBFH+ydg8p1pPOHUHExhi4VCeVTm6TV46WqjeBaXrpxDnevoe9P8G0FAOci8ddoyaMG3L2xaQp8WkhP0hH+ax61tOR9XItF9VckTQbOj0OnD7LuyU9ugntlE2+InN2N+Ej5nUWSpAKAUmWwcgzqB+H1/wOArdNxciOGLcva6Iu15Zgt0qWjcPNAo9dzDCxSJxBbfpCvncoRJrCMfOUfCZBKlcuqutc+yXopyUzz2VY5cXuw4nOpkh/KeiJiGsp44IVcgmvHN2LrT6jZXLp+FhE/Zh0bl09IW37A6G1wdstKtvpLqVYb6O2yfC1GknUo5529pFp96ehKyDpIqlxbx55oNFCr81iiLzMTuc1JKkawUeU+1LjNORetw4fRpQsAbNmCVq1MJDC/XzqdiToxX1fmM9RXbCuNiIiIyAxGRqikWT4aleui91RIKmgysXAI/v4Kb/+W9enVGHy4Hi7locnE7L7SwaUwHxkxv0pSPIYvg0t5yDosHIa1EzBogbms2v4HyfHQPBGDa+TheixGroFLefl6rDQnHMfW4sP1cHTGub1Y+rF89YRUpSF0Wmn9f9FuENoNAQBZh9/6I/pv+LaC9glWf4nG3bPeQ0m9iDnhqPL0DjyXWpKvnZLOH8SI1VkDee5fgH3z4R8GSYWLh7NX17f9Z9RunzWQKgA3L7nbZ9LqcXK9TpJWi8PLEDo1K6xwLRb3bkj3klCuEo5HYf8ihP6QPUiHmxdKlZEuRSPPyMj9FPnkRuV/0rVY6dhaVKkPv9YmEptsPpsqBzot1k5E4+7o9jkA+XqsNPftXCMjt6/gvb/gWgGaTPz+btax0TAIW37A6W1o8gYAJMUj5YLyOljW7qTfBYAq9bKXOJUBgCcZcuqFXFvnede7NwAMHoz33sO5c1CrMXgwfv0Vixbh889x4wZcXPDZZ/jqq+xV/vgD33+PmJis+/y2bTFjBho0yPp0wwZ8+inOnoVKheBgvPkmRo7EsmXo2BEAYmLw4YfYtQs6HTw9MXQovvoq+84/NRWffoqlS5GZCbU6K+d69VBMiLCIgwO2b0ejRjk+Mr9fvXvDyQn+/hg5Emo1FizAmjUAMHgwPvoIMTFZ1Th3bvY7O+Yz1FfMK61E23ns2p/bz+f26YgedRv5VijUAkxfder8tfs/jzR1BrZVdFzqwi3nEpIePHqsLevi2Kqe15Bu/3IrUwBBtemrTiUkpf34nn/+s3pm/txxfuc/18wkGBXasHY1d2uz/WXN6bNX7lrScJantNbZK3enLj8R0NA7vLNf3qlLgrf/u7t34EtBzXOM+XUt9eEnvx7644v2aoes3+v5m+MOxCR93reRb+Uco7MdP39z5urTpZwcJr7d1KOcs8lN3LqXkdtHljMukiDOJxmZ2iYve77dxa982VJWFfjXdbF3Hjz+v7DG+SweUfHEyAiVJPLlf6S71+Q3J2f1X1A7oVV/rBiNxw+zXmfwawuX8lkfvVgHGffyztTMKk17ZH0kqdAiFCtGI+0WXAvohf5aWdvNCjo06QFHZwDwaQ5ASk8DAJUDhi1FKdesVWQZLm7QPQGAc/uQ8QAB/8n6yLMmagciLRVma0kqVRYAopaiWS941kSbgWgzMCuHxJNoN9iwkGd349Zl9Jqkv0xq8G/E7ZXWfYMnGXilJ2q/CgCyDlXqoe3bWUEB7RMseg9rxuGTzdk39tUaIelc3jWTclHa8B0AaB5D1qJKfQQOQ7O3TCc22Xw2VQ4SovHoHtpmjXshvVgHtdpC1pjebrM34FohK4fW4VgxGul34FIe/3oVxzdkVcLxdfCuDc+aOVbMfUwvc63zvHvwAKdPY+NGfPAB6tTB/PmYPRtXr+LIEXzyCTw98cMPGDcOrVplhTZ++QUjRiAoCGPGwMkJUVGYNg1du+LKFahUWLMGPXqgQQMsWQIA33+PQYOQkYHMTACIjkb79vDwwKxZ8PLCvn34+mucOIG1a7MK06NH1gCx1avj2jWMG4e2bZGYCFfXXEr/DImwiKMjdu40jDvkuV8PHuDiRSxdiuBg3LiB2rXx4AHOnMH69Xj3XYwZg4MHMXMmXnsN8fEWZaivOFdaSXfm8t15m+Jy+7Sbf/XCjoxsjb6690RSQd02a7S6wd/vXbjlnNpBCnylclkXx9jLd9bsT/jxr1NrvuncvHbF/Jc2KjalZEVGImOSzDQxgN6BL9kQGdl+9Nr2o9csaTjLU1rramqa2LXnIzLy/fITkTFJ80fnmFEuPUMTOnF7ZEzyojGv4mlf4d3Hry/eGh/exU8/0HD8/M32H23IyNSun9TFZOzj7JW7b4zbNn2Ef8cmVfJTTpNFAvDe9P2z1sTW8ylfxdN11K+Hflh+8uAv3atWdLW8wMH+1WuGLW1Tv1JAA2+jzRKVeIyMUIlyPwmANG9Q9hJZBwDXTqNmcwDw1hsi1MJx/s2sUjF7lAfZxV0CkBSX9SZL/lX+l/7/ZBe3rG0bvIPj6IxDfyLlAm6cwYNUODjCpykAZDyA5JB1cy541RQ3/3nUUpePsGMWjqxAGQ+83A4te2fdumsey24VDavsn9WoXM/EwKuvf4EpneDkjNeeTmEjqXJ0jnBwRMveWDFavnpKqtrw6UInPMnMu2Z8W2aNwKrJxPpvcWaXHDhcym34EpPNZ1PlyBn3JSDHG0BlPXFfbwphfZ4vZWfgXFYCcD0Ovi3RuDuWjMS963CrhJitaDvIcEXxuoLmcfZQMqIAKjUq1Mi1dezA5ctYsgR9+wJAcDDKlcOGDYiLg58fADRvjrp1sXp1VmTku+9Qpw42b85at2dPZGRgxgxER6N5c4wcCV9fHDwIF5esT5s0QWxsVuIRI6BWIyoKXl4AEBICT0+MGYOICAQFIT0dkZEYPRrvv5+Vvlw5zJyJ2Fg0b/7MKsO0I0fwzTe4excuLibeWDG/X8LZs5gzB4P1QqCXLmVXe9++ePwYc+YgOhpNm1qUoVCcK+25sXFyUNeWz2JOrsIWPnnX0h0XBnTxm/lBa9fSWSf2NfsT+ny9o9uYiLhFocpDbPvxywdtfvmgjfg784m2VOd5IW1qrP66cz6z/axPw0FdzY6bbn1Ke5Z8O33870fnfdpOpcq+VrqW+vCNcduizqTkuXp0XGqnURs1WnnL911zCyscPpsSm3Ann+XMrUibDl2ZtSb247fq/zDMH0Bswp3W76/tP2nX7p9et7zAlT3LjOxZb9iP+08veDOf5SQqhp7/Ttr0XFGpASB0KsKmZ/3r9zP6z8KLtQt7y5JWA0B2NNW/UdzZFoaM+5jdF+f2okYT/PszfLYrq4MGIDuoATnHph/ezfrDfC21DMPnuxE6FXU6IH4//tcfd64BgKQy3BGdFucPoV4nEwU7swuSCk8ycWJ9jvT6HEoBkB4/zF4iy5aGqwS1E0LGwdNHWj4K965bvp6NlSNiUvpr5d6ysi67L4mk1QKQS5UGAN9WKFsRJzbiwmGk30XDIMM1X6gBAEnx2UvSbkHlmDUga26tYwdUqqx3agC4usLVFQ0aZIVFgKz3Ox4+PZoSEnDwYI7VPT0B4P59HD6MxEQMGpQVFgHg7Izhw7P+Tk1FVBS6d8+62xdGjACAZcsAwMkJTk5YvBh//omMDADo2xcHDhSLO/xRo1C2LGbNQno63ngjqwuMkOd+CSoV3n47R5761Q5kjVqSkmJphkJxrjQ7pNGa+0nS6WTzCfJcXaezfTLL3cevL91xIah51d8/f1UJiwAIaVNj3IAmqXczfl4dY1WG5ktrW8o8q8jmDeWn6sxnkvlEa7ywZR2vbv7VTeZgkInlKS3/1BLGdWWm9kzuo+UlsS1nfVOWnyjvWqp3YPZzkR9XnqozcEVc4t0GL71gft3DZ1M6jdoIwExYxAzLj0kzRfp59WlnJ4fJg7POy3VqlP/gjfp7TtwwGYsxU+ARIXVjE+78sS3eeC2iko6RESpJJA8fAPKTh6jZXPyTJQkxW+FQOCP+XT6W/XdqAlSOUrVGAKBSSWm3sz+6l1woWwfk8wfx8Bb6/oSWfeAXgFJlcDcrQCBV9IWskxOOZqe+cjzro9xrSb52CmsnwMERtV9F19F4dxE0j+XrpwGgdDnpes7evOcPQdaiZgvDYt1KxOYfEDgE7f6DLT/iViIA+co/+LoF4vZkJ7t5EZIDaujNNZt+J3t+HwtJKvT4Gk8ysWaiFSvZVDnwqAFAfpoSAG5dznUT12Kz/3PzEiQHqfLTdxsadkPsTpzeAr+22UOxKipUQxkP3NBb/UIUqjcCYK517ICLS47hPx0dUcWoN7Hu6ZWhSoWEBHz1FXr3Rps2KFUKY8dmfZSQACA7pCJUf3rNf+QIACxdigoVsv/VqAEAt24BgFqNOXOQnIywMJQpg4AAfP89kgvrK24dX19ERWHYMAwdipgYfPpp9kd57pfg4mI4SohBtSt/W5ihUJwrzU70nrij98Qd6yITqoUucew4t1Tnue/PiLz/MEcfvf2nkgI+WOfYaa5jx7kVeyz6akG0/g1hdFxq4McbHDrMcew4t1LPxZOWHDPYxM5j1xoOXunQYY5jp7kBH6w7fy3rzdPtR69W6L7wven7LSnn7HVnAIwNNzH+14gedeeMCujd/iUAk5Ycq9B94eGzOR56T191qkL3hecS71pSWkXMpdsdP9koUoq9NnOHaaaKPph5oEL3hZeTHuin/7+5hyt0X3gt9aH5DfWeuCN88q5f18WW6jy3dJd5y3ZesKSuDJjM5I9t8aJRSnWe59Bhzqsfrj95Ifv7GT55V43efyqr9564Y/vRq/X/85doxFc/XK80ouUphQ0HL/9rwArxaY+xW//ccb5C94Xbj161cEdE/i+HL3fsONex45xhP+4DsGjruRd7/eHYcW6Z1+ZPXJT9821+H/MsiZl2Sb376O3/7i7VeW6pzvMcO84J/HhDzCW9S7ucMp9oZ68780Y7H/2FX82P7tikSsz8N5u97Glmlw+fTeny6SYHlbTrx26t6nrllmzw93ve+ykSQI+x25TmMP+1NWamSNuPXg1qXtXJMbtjcvPangB2HTd88mS+wNUrlW3boNKstbEgeu7wbRoqUSrVgk8zactP8PBBpVq4mSCt+wblX4TJrhz5d/Rv+LaGb0v52ilp7xz4980aMsO7Nv5Zg7odUKYCIhcg5SJqPB2MSlLh9hWcP5TH3DSWkZxcAcgJ0VKDf0PWYe8cXD2FF+sCQKWX4Rcg/T0WXUfLzmWl0ztwLQY+zQBztSQ5lsbx9XDzwqvvQlLhZAQAycsPAGq8gvs5b2VuXoTKERV9cyyUdfj7S3j6oPXbkHWI3YlVY/DOIqnaK/CsiW0/o6IvylfG+QPYOxet+mV1hRArXotF42Cra6FCNbT7D3b9Jp9YLzU03efTkG2V82Id1GgqrZ+EsOkoXxmHluLyUdTK5b3r6JWo2RK+LeXEE5LYU6W5G3bD/vm4n4KQXKI5zXpi/0K5emOpSkP59FYpbjf6TANgrnUop4kTMW4cXFzQuTPq18eIEbh4EV98Yenqb74Jf6NRCHyeXvGGh6NTJ6xcia1bERGBffswfjx27Sr6HhC//QZvbwD48Ufs3IkZM9ChA4L1vlLm98sGlmdYbCvNTjx4lHni/O1Vey9+/Z9mDWq+8E/8zbHzo4/F39z/c3eRYOuRq699vrm6l+usD9t4lnPeFHXl60X/7D+VtHNaNwCHz6a0HbnO+wWX3z5u+0LZUit2X/xi7pH0DM03g5qJ1TMyNf/+PGJocJ0xfRufvHhr8pLjnT/ddPHPPgAyn+hu3X/8IP2JJeXcciTR2cnB5M2ha2nHwf/O6v7ZK8Dni7lHFm+N1x92ZO7Gs9UrlfWr6p5naRXRcantP9rg4VZq1odtvMqX3nfqxteL/jlx4dbab0zMH2++it5sV3PGqpglO84rY0/qdPL8TXH1fF6o7FnG/IYePMq8eOHB0h3ng1vXuHErvXa1csZbz5NxJr+sOT1iemRQ86pj+jZ2UquizqZMW3Gy6+cRV5b3Fa97PEh/cuv+Y2X1M5fvrj94+d1u/xoT1vjg6eSZq0+/9tnm+D96W5USwJr9CT3Gbm3w0gtLvgwE8P2yE4Om7MnI1GY+sahTw4NHmacv3dl46MoHb9SrU6P8/E1xs9eduZr68MjZ1E9CG3iWc/5hxclxC462quvVsUkV8/uYZ0nMt0uPsVvPXrk7dVjL6hVdr91KH7cguu3IdYkrwvR7Myk2HLySnqHp1CTHoOxHZvfIc/wXEWVwVKt2TutWz8dc15K+HX11MhZsjnv39dr1fV5AXsekSbkV6f7DTI1W9nDL8aqaf10vAMfib1pb4M5Nq4ydH52YkibGKCF6bjAyQiXNW99hzUT81geSA2QtfP3Rw4reBNap/xrWjsfDOxJkNO2FDu+JxXLQJ9JfY/BTMADUao2AgUqXBDT8N5Z+giUjEDYze1oWm/m1RsNu0upx2DAZWi3qd0GnD7BjFjSZUDvhjW+wdQZWfyVptWj4b9Ruj8xHWSvmVksVfRE8FlumYd98QEJpN7nHBKlCDQDyywHS+klZc8cKKRfgavSjuHcObpzFsKUAIKnwxrf4tTd2/w/th6Lfz1g1FjO6Q3IAZLTsi47vK+vJV45LsjbXQIN5bQchZpsUMQ212li6ig2VA+DNydm7ULEm/AIg5/JwpulbJo8NAKhQDVXq48511MplCMCAd3A3SZo3CJKDBKDTh/ALAMy1Duk7fx7jxsHfH7t3Zw+3MX581h81awJATAx69sxe5fLlHJ+WK4f39FoMQEYGnJ/GVzMzUaYM3n8f778PjQa//YYRI/Ddd1i1qnD2x2JKdw9nZyxfjiZNMGAATp5E1aoW7ZdVrM2w2Fbac+OLeUem/XXKYGGTlyt8925Wt75rNx/O/rjtkNf/BaBry2qlnBxGz476e++lngE+AN79Ya9nOeeoWSGe7qUB9AzwqeblOm7B0d8j4t4OevnDmQednRyiZoV4veAiPr1+6+F3S4+Pf7uJmNhCo5UXfBbQr1MtAL0DX7r3MHPWmtiTF241eMmja8tq8q53LdyLu2mZzWqbe7ou+FV196/rtXTH+ekjWomb/JMXbsVcuvPTCH8AeZZWMWJ6pNpBUlKGtKnhWa70mDmHIw4nGswtkmcVtalfybey21K9yMjOY9eS7zya9E5zSzZ09srdOaMClNCPbQwyCf5iS50a5Td/95r4b88An4xM7YxVMdHnUk0OZHvpxoMlXwb27eALoG8H38dPtHM2nI2OS21q1LnAfMqRP0f6VnY7ODPExVkNoGfbGk2GrLZqdIzLyWlK/sGtqpfr9vuGg1fiFr3lV9UdQPPaFesO/Gv1/oSOTap8t/S4mX3MsyRm2iWggXdkTPLoPg3f75HV37NcGaeZq0/HXr5jsva2Hb0KoGPOyEieYZEjZ1O/WfzP3bRMF2e1kzqPfvqBjStfTX24YHPca82rihFYzR+TJjPJrUjR51IBlHLK8cSujLMaQKYmO6RlYYEb1HwBQGRMcu9ARkboucLICBVjn0SYWOjsht5ToX2C1IvwrAn9gTn/b2+OlD0mmM622Zto9nTgKPOrVK2P1/8Pt6/BvZL+hqQX6+CDtbhzDaXLGr4u4dsKX0ZCp4XxiKFmtjsuOnv4DQdHjIvO/ihkPF7/Qk6Olyq9nNUroVV/AEi/I9++InX9VEwxCwB/fZbdd8ZMLTXujkav4+4NAChfWdmuVC8IW35C3F5lKBOEjDfcBQDgfU1BAAAgAElEQVTthmRNISx41sRXh7P+dvPCwP8h475885L0Yj2DLjNS7E78q32OUVFNMjnhsaTC8BVZf+tXXW7NZ3PluJRH/5l4/BDpd1E+l/l6AYw9CACdRuDWVZT3NtHWKkc0eC3X2XYlFbqPw7/HyDfOSJVzVlQurUP6zp4FgODgHKOQrl4NAJmZaNoUfn6YPx/vv4/y5QEgPR2zZmUlq10b1atj1Sp8803WpwA2bMDrr2PUKHz/PdatQ/fumDEjazBRtRrDhuHDD7Nf5CkmGjXChAkYOxZ9+mD//rz3y1pWZVhSKq1Ec1SrSjkZnlIc9QIBzk4O7+jdeA8LrjN6dtTKvRd7BvgcPptyOTltdJ+G4v5KGPVWwwkL/1l/8ErvwJcOnk7u37mWuHsU5o9up5IkJdCgUkniPlZoXa/SrDWxV1MfNnjJ6snaPNwsitUN6OI3dNq+iMOJYtzZhVvPqR2kfh1rZWRq8iytkHr3UdSZlAFd/PRTjuhRd8ycw8t2XjCIjJivInEXOqCL39j50cfP3xSTAS3aGu/s5NCvo68lG1KppLeD8tsB0CCThKV90x7l6KrjWc4ZgMFbVPqri5eVhFZ1veZsOJty55FVKQ+fTUlMeTj5neYiGAHA2Uk9vHudEdMjrdoRJX/X0o6updU1KpUVYREAvpXdADx8pDG/j3mWxHy7dGxS2clRtXhrfMOXPHq2reHspO7bwVf/IDdwNfWhi7Pa2cm6+6ZRvx6qWrHMpHeaD/9x/xvjth39raf+yyzmWXJMWs7MOCz675dZWOA6NcoDiDqToj/qCtFzgJERKpkcHE1MmFIYJBU8DJ8sZcntzllSwaFAR/BxcMya2VefykGaNwhBo9HiLQBIikd8JF4dYrCi6VqSVCYKr3JA63BELcuOjNjG2U2q0tBw4eOHOLYGg3/PV86Wy0/lAChVxqLxUCQVKhhNFSHrcOEwrvyD1/8vj9XVTtmz9hhkayYoQ0CTJnBywsyZCAhA06aIjsZXX+HcOeDpQCS//IJOndCqFUaOhEqFWbNwVe/99xkz0L07AgLw7bd48UUcP45PP4WnJ0aNAoBu3eDjg//7Pzg5oXFj3L+PuXOh0SA0tCh21awvv0REBCIj8dVXmDgxj/2ygeUZlqBKK7nGD2hifm4a/7pe+lNmuJZ2dHFW33uYCSAh6QGAJn45AtMuzmo3F8fYhDv7TyUZf6o/cycAl1Jq/cxVVo2lnXOjB04nWZIyrKPviOn7/9xxvmvLajqdvGTb+W7+1T3KOYshJMyXVjhyNhXA0p3nNxw0HDHq1v0MgyXmq0j8d1DX2uN+P7pwS3wj3wqZT7RLd5zv39nPydHBkg25lFKr831hYJCJSiUlJD1YuffSucR7V1PTjsSlmn+fxbARVbk2opmUoqL8quSo8Ope1nUcMMjf0UFVxdPwN1cnyzC7j3mWxHy7qB1Uc0YFDPxuT9g3O1UqqXU9r9dbVQ/vlCPipu/ew8zSTla/Iu1b2W3v9GBvD5eTF27NXnfm09+ipo+wdH5DS45Jy1UytV+ikp3U2ftlYYFFexl/j4hKOkZGiEomZzd0+gBbpuLQEpRyRUo8/tUeLfvmK0//MPyzVk48YfqOPT8O/YFGwYZDliiiV+Loavnt2QW23cKoHEton+AbfwBoHooCfAvm769weluB5VbyeXtj+XIMHozWrQFArcbw4Zg0CS1a4NAhdOuGjh2xYwfGj8fIkXB2xn/+gzp1MHRo1urBwVi7FiNHonvWCAxo0QLz52dNwqJSYft29OuXnd7DAz/9lGMCl+Jj6VLUqYOvv0ZgYB77ZQPLMyxZlfa8Kl0qj9s2tcrEnblOlkU80dqH4bYJaOAdcTgx+Xa6yfvP8Mm7Xm304n9eexmAa2nHPh18l+44P/fTgP2nkpLvPBI9Yqwt7ZvtavobDWviU6msycS5VZH4w9vDpWOTykt3nP/xPf8/d5zXaGVRVBs2VCAmLjo6bsFRF2d156ZV6td8YUSPehdv3P9i7pHC2+Kzl/99NNMu4Z39OjWpsnLvxa1HrkYcTtx3Mmn870d3/djN5Ns0GZkWzV9j4LdP2np7uAD48T3/nceuz1gV06Hxi8Gta1ieg/lj0nIihGQwHtCV5DQAXi9k90nJf4GJSjRGRohMk8N/ltyL96P7Vv1RrzOun4Gsg2fNArgVl1ToPwNpRjNP5J/Xy/A1/ZxEDv9ZTPcredUqyC0WeOVYwsERoVPl0m5SdRMzL9gu4D9y0xAA0gsmZlUsoTp2hP6l3caNhglu5hgSDk5OOdKHhCA4GDEx0OnQoEHWjCpKgjt3EBiIwMDs9D//DAAvvpj13+BgBAfjxg2cOYPGjbPfFhFq1sSBA8jMxP79qFLFcJqbIrFoERYtMrG8alU80Jsrw/x+GVey8ZLwcISH25JhMaw0e3M0Lsd3Jj1Dk56hKVfGCUBF99IAzibe1U+g0erupz95tdGLDV96AUDUmRQxRolw+GxKxOHEQa/Vrmz0MD8/QtrUiDicOG9znDJah2L/qaTFW+PvPHishBvCO9davDV+2c4Lu4/f8HR3Fq+lWF7ami+6ASjn6vReSF39DWVkaowDK+arSFkyMOjlPl/v2Hns2qKt8X5Vy7WpX8naDRWU89fujVtw1L+u1+4fuynvO4z//aj5tfKvprcbgJiE22L8GuFyclphbMv8PuZZkjzbJfOJtoyz+v0e9d7vUU+j1f22/syI6ZHfLT2xakIn48J4lS992vqeGkofH2cn9fKvOjQZsnrAf3efnNfLkoFLLTwmLeTk6ODt4XLx+n39hTGX7gBooRcJsrDAt+49xtNhSoieJ5y1l8g0qUrDvAfFKHJuXqj9Kv4VWGB3/uVelCrXL5is9NV+NXuSmpykKg2laq9I1V6Bk+kurLYr8MqxRO1XCzgsAqBCjawqcrX6lf7nmEqFBg3QqBGMn6hVrJjdzUGYPx+urmjQIMdCb28EBhre7SucnBAYWCLv8M3vV6FmWHIr7TmQfOfR3pM3lP/O2XgGQK+AmgACGnh7ujsv3HJOf77PORvP6nRyq3peXi+41K7mvvXI1YxMjfLpzNWnJyz8x8wLF7YZGORXtWKZb/84pl9UAKl3Hw36fg+AL/plR0w6NqlStWKZiMNXV+291L9zLVEYy0tbu5p7dS/XVXsu3XnwWFm44eDl0l3mfzr7kEHBzFeRsuStV2u6uzr9b/3ZPSduDOjiZ8OGCsrZK3cBBLeqrj8MxOr9lwBYOEeMbZq+7OlXtdz8TXHKzqZnaAppAlfz+5hnScy3y7rIhFKd5y3cek4sVzuohgXXUTtIuY3H4eleOj1DY37GXPMa+VaY8HaTu2mZfb7eYT6l6Bhl4TFpuTdfrRkZk3xOL9QyZ+NZZyeHzs2qWFvgExduAWhdr5INxSAqzhgZoZLh/v37a9asGTZs2PHjx/NObXEOli98ltnmvwD5LGrhldZyz0F7FUa2+W8vezBgANatQ+/e+P13/PILmjfH8eP4739NxFCISoqpK06GT95l/O+XNaeVNL3GbftjW/zx8zenrzo1+reotg0qicfpKpU0ZUiLc4n3Oo7auOnQlZMXbv2w4uSHMw/Urub+fo+6AL57t/m1mw+DRm/eeuRqdFzqVwuiF2+Nf7dbbdGv3rytR66W7brg3R/25pkSgJOjw59fdlBJUvuPNvSeuGPZzgt/7700/vej9f+z8lzivXEDmrSsk+OWL7yz3/JdF9IePenfKbtToeWlnfF+q+Q7jwI+WLcuMiE6LnXuxrP9J+3ydHce9VYDg5R5VpGSLLyL3/JdFwAM6Oxnw4YKShM/TydH1czVpw+cTs58oj1wOrnjJxvPJd6DTa9aWOWXD1pfTk5rNWLtr+tif1t/xn/EmquphdJnJM99zLMkZtqlm391H++y/zfnyG/rzxw+m7L96NW+3+zUaOXQ9qaHFO3ctAqA7Uev5WePvuz/Sut6XpExyV8tiDaZQAz5MWfjmUVbz1l4TFpudGhD19KOQZ9tjjiceC7x7vszIiMOJ37Rr7HJWYrNF/jkxdsAjGc1Iirp2A+KSoaqVauWLl06NTX1jTfeKMAcLF/4LLPNfwHyWdTCK63lnoP2Koxs899e9mDuXNSogaVLsXo1VCq0aIG1axEcXNTFIsqHXceum1ye+UQnXhZwLe04sme9gd/t1mhllUrqE/jSzyOzZ0l/O+hlJ0eH0bOj/j0mAoBKJYV19P1hWEvxWkFw6xrLx3X4+JdDXUZvAqB2kD5+q/73QyyaeF6j1aU9emL5KAxt6lc6+luPT3499NeeiyLEAKB2NfefRrQynufi7SC/b/84Vs+nvJgORrC8tMGta6z9pvPInw90/3KrWNLiXxXnj25ncpQT81WkGBjkN2NVTMcmlfXf3LFqQwXC28Nl+VcdB3+/p/WItcD/s3fmcVFW3x//PAMMi4goAiqigAS4gKLigoiKG6K5VpqZmZppbtk3Ncuy0vJnmqWpmYoWpahp7ogoIiYugAqKbLLJIpsIAiIOMPP7Y2gYhplnnmGYYfG8X/zB3Ofcc88592GG58y950JXh/locs/vP3AbuOjkzdi8CYM1uPVyVL/OwVvHf/377WXbwwz4unN9HHt0bbtw678NPpBSH5Vawj4vl7aMn/V9iETezET/5yWDFR22MmFwF10dJvReNnshZKX4fzmyx5y/1/vd8XLtVHdTjM9A674O7Y+Fph4LTZ0xohvHe5IjVuatzm8aN3tjyLjV5wHo6jBfzHJd+66SVa5yDQ4Mz+hl21bpocUE0exgRBpOLROEXJj/KttzvAMFAgGfz9fX1z937tyoUaPqMaJcDdwbtalWfQPUNFVz1nKnBcyXJtSqP1+ag2EY+jwhXmUYhusnmoLujChkQf36jl9z/mp0TknA++Kv1gc4WRgpKAGQ8rg488nzQd0t5B7GmfK4+HFB2aAeFuofpKIUoVB05+GTotKXPW3aKVqc8iinxOZt/62LB694Q842T+7WZheUxaUXutq3b9taX6lh7CFqwIHURygUxaQ+FYpELnZmDb71SRGFJS9lvPvlRMyy7dfv7p0qncBqKFh85G4Jy7wIKqquxeR0bt9KcmywIhb99O/5WxlphzVezV1QUcXj1TqFWp17si6xaYU5hWWeLh3r92eeXVDW+a2D25e6yxRwaUkwI/bIvJmr+thCNFNozQjRPODz5VepUFMD90ZtqlXfAO6SirpryFrutID50oRa9eeLIIgWDF9Ph706o10nE3FlynpcbVh4PEbpavzfzsbp6jCzR8uvz83d2o5mRlx2BqmqVs2B1IfHY1y6abv+lMUUP59BXU5tGCtp2R+QYGyo52KnEUtYfORuCcu88PV0vFw5ldtfOb33nrPxgeEZ4mLAmqNu+qNh/zB72LTtYVP/SlS/nYmzam8kPiuKIFoYlBkhCIIgtAejpe81tYQWvj1qSRGjL9sIjszeGPLsueB02KNPp7uYtTFobHOIGt4b6+AbkDDj22DvAZ2fl1f+cSExKqlgx/IhWlu00liW2HUy+fiNXl//flvTmZGmTOmLim3H7+/82KNBVq8QRFODMiMEQRAEQWgDhmn45Mjlyzh0SOHVJUvQpw8OHcLly7KX7O3h4QEPj+qXmzcjIQEzZ9Y671nC//0fkpKwcCH6928guxsUN0cLzR0Q2yjcffgkKav4vbEO6+c2yYi/wuxbOcymQ2v/y8knrqXyGGZgd4tTG8ZMHGLzKljyzZz+bgtPnA5LaxR/mwL/dyjKq6/VzJH2jW0IQWiEFvU5SrQchELRsWPMiBEwr15qm5SUlJaWJhQKIyMjTU1N+0v+Oa0jqQi5Grg3alMtmyT3yKhhasNYK3dqXqX50oRa9eerKdBiFg5obTVHy4iYhsIVFwdfX4VXJ0xAnz4IC1MoM306Dh8GgBEj8NlnCAhAYiKMjWvJBAZizRoMHdpE0yIAvp7Tr7FNaGDu73+zsU0gFLL23b5KK3dqBy1bYmyoF/fHW1obrgmyYZ5bY5tAEBqEKrASjQN7KSPRtWvM0KHYuhUrVohbLCws8vPzxb/zeLy4uDgHBwe5koqQq4F7ozbVskhyj4w6pqqvVq6pihrVtLbJzpcm1Ko/X5qDYwVWTawaaCy040uLiZj4Xb/Bfdm5E0uW4Nw5+PgolFm8GLt2ycokJmLOHNy4gR07sHgxAKxdi+++w8KF+PXXGrHSUjg5oaQEsbGwYi1H0IgVWAmCIIiGgiqwvrJQZoRoHJS/xaSkwM6Oky7uki2DZuSvXFObkf2EKlBmpFmPogWaWmYEQGIiHB0xYQLOnAEAoRDOzoiNRWgoPD2rZRYswN69+PNPzJqlxBLKjBAEQbQAKDPyyqLxU9kIop5wf3h+1R6zm5G/ck1tRvYTBNGiEa+sSk+vfsnjwd8fPB7mzEF5OQBcvoy9e/HGG8rTIgRBEARBNGsoM0IQBEEQxKvIzZsA0L17TYuLC774Aqmp2LABAgHmz4elJXbvbiwDCYIgCILQElSBlSAIgmhkmu/BtHItp6N8WahreYOE64svsHWrbGO/fti0qeZleTlKS6t/T0tDeDjWrgWAhQtr9fr6a5w4gU2bkJaG1FScPw8zswawkCAIgiCIpgxlRgiCIIjGpzlu3a1bAUQ7CQsNFezQNHLNZpiGKaSipwd9fTmN0kybJivA5+PnnzF8eK1GHg8HD8LVFQcP4qOP4O2trm3aYf/5hOsxOZ/N7GNv1aaxbWlM4tOLthyJ9uzdcfYYbVeh1gQFz8rN2hio2uvy3axDl5I+fsO5l207mUtq3idX72X7XUhUqXv9XNh58sHdh082LxzUtnXNH3bu07IvfCMAfDOnv5V5K5l2914dDPg6l+9kyaiyt2rj4dzBw7mDqjbUG0VRqp9Tc8c5ihUumdKzj317mbHoD58gGhDKjBAEQRAE0bz5+mu2Cqxili2Ds3P17zwe2rWDlxdMTORIurhgwgScPl1ryUkT50rU4z+DHs4e6/CKPyBl5pf6BiQAaO6Zkfj0omnrLm5bMnhUv86q9o17VOQbkDB1qG3dzIia90lixjPfgASO3dVxoexlpW9Ags/ALlM9bSWNwXcfiyd3UA/L+eOdJO2h97J9AxLcnCxuJ+aLBeoyfUS3w1+NVNWM+qEoSvVzSqJwwuCudTMj9IdPEA0I1RkhmgfFxcUnT55ctGhRVFRUMx2Lu1qVDNCQWu5oc2rUN0AT4Wp0A1QVJohXk7FjMX9+9c/cuZg8WX5aRAyPBwB8vtasI4hahMfnxaYVNrYVaqGOCyP6dALw7/0c6cbTYY8crNtYtjW8dLvWwpCgiEwAPgOtxS/PbfQWhSyQ/CT4vTW4p+WRkOSdJx/Uz5iGQh2nCILQArRmhGgeWFtbGxoa5ufnT6u7HrqZjMVdrUoGaEgtd7Q5NeoboIlwNboBqgoTBPHKIhSKhCKRro7CL8aUClRWCVmuqqqNBfaBhEIRj6fa7rW6CtmHEFRU8fV0FI0OgN0AFuUsmpWiTkjZYTFYabRV9UjpXdTf0dzYUC8iPk/ahnM302eNti8sEZwKS5M26VZcnr2VibWFsVxVDtamv68e5jj7aGB4xuLJPdkNY3eEfd6VRqkBnSIIQhNQZoRoHuTn5/P5fP26+8ibz1jc1apkgIbUckebU6O+AZoIV6MboKowQRCvINfu53y+LzwsJlcoFJmbGiyc2GPtLFfph0AWgRnfBgOYObLbku1hGXnP+Xq8BRO6fzfPzaSVwkU1irQt33H94MWHt3+b2rVDa4nw5/vC95yJi973hpV5q5jUpx/vuBES9VjS8avZfSVP0TO+Debr8Qb3tFy2PUxXh3dg9fAZXt1YvBZbPn+84+JtYYkZz3R1mPnjnX5dMdQvKPGzPeHZBWVGBrqr3+791ex+ki5/XXy4+Uh0TGqh+DF1qHOH7UvdXbpVl+E9e+PRyt234tOLeDxmonvXN4fbLdsedvirkZINIyz25xe9WLn7lv/lJEGFUFeHGerScftS97obXgDM3xx6JCQFwJQvL5qZ6KcdnsllBuuB0pk9HZa2ek94fHqRrg7z/jhHZ7ta1rLESq4L7JMrw/hBXY5fTZEkC64/yC19UTHWzbpcUHUkJPnqvezhfToBKH4uiEktXDixu1wlYhysTQGk55UqEmBxRHILrdh5Iya1UHx130pP6d0r7FHSkFMEQTQ4lBkhmgd8La5p1tBY3NWqZICG1GrCAA3R6OFqdANUFSaIlseWLTh8WE77wIFYvFjr1jQ9giIyx312vqul8a6PPczbGATcSl/vd+fa/ZzLWydwESh5IYhOenr8asr6uW4udu3uPHzy5f7Iuw+fXPtlkqrDvTnMbvvxmIPBSZ+/4yoWFgpF+wMSetm2szJvFZmQP2LFWTMT/V0fe1i2Nfz3fvZ6vzvRyQWnNowVC5e8EKQkl/gHJ00cYpNdUObURUlthZIXggephedupi+f1quHTdv9AQm7T8dl5j+PiM//33QX8zYGPx69t+7AbfeeluLUxs6TD5ZsC/MeYL1mpitfl3crPm/r0Xs+nwWmH5nJ4zEnr6VN+TLIpVu7g2u9AGw+HD3vh9ByQZWgQigejt3+KV8GxacXbVk0qKuFcVZB2boDkUOXnc44+o6xoZ6M2TNH2QtFOHA+YcHrTs627bjMYP1gn9nTYWmT1gb1sTc7uNZLKBRt8o/6+0qKpC97rOq6oHRyZRjVz+pISPKV6MderlYAgiIzeTzGZ6D1s+cCAJduZ4mTCOJNKGPd2Had3IzNBdC9S1u5V9kdKXkhiHtUdObGowUTuq95x/XGg9wdJx6MW33+4V8zxN3Zo6Q5pwiCaHAoM0IQBEE0RZrFwbRyjWyUo3ybRbjAOWKqhiskRH67QECZEQBY8ONV8zYGt3ZNNjc1BDDV07aLpfG6A7d/D0yY4+3IRSDryfPdnwz98PXuAHwGddHn66zafeufq6nStSQ5DmdvZeIvlRm5fDcrt/DF9x8MALBkW5iuDnNr12TLdkYAJnvYmLcxXLM3PDA8w3tA9VNifHrR3k89pWtVsvMot/TgWq+ZI+0BTHTv2mbC72dvpCf4vSVeRzDAyaLn+3+fuJYmzoxs8o/qYdP2/KZx4r5TPW3LBVXbj8dEJuYPcLJY9kuYvZXJjR2TjQx0AUwdatPvwxPSpTRY7Pd06RgWk7vq7d5Lp/QSC7dpxd9x4kHso8IBThYyNnu5WmXmPz9wPmHcAGuxYUonqN6wzOz/fr3Z1dI47JdJYn8nunftNffvolKBuCN7rOq6wGVyawehE4CbsXniJEJgeMZQ5w58PR1zU8M+9mbnbqZvmOcGICTqsTi5IOlYLqgqfVEh/j0tpyQ8Pn+tbwQARUsw2B0BkJpdIrmFZo60f1lRtfdsfGRCfn9HcwDsUWoopwBM+TKIbSIJglAbqsBKEARBNDkkJ7w25Z+6FoqR26gdGj0m7OHSRMQWL2YbVLyQZOdOiETKD6+R5sQJiEQtpAJreHzeo9zS97wdxA/VYj59qzePx5y5kc5FAIABX+cDqWTEook9ABy7Kue7caXa3hvrEJNaGJX0RHzJL+ihAV9n1ij7/KIXt+LyJg2xET85i1kypSeAw5eTJS08HjPHW4VzZ3g8ZsaI6h03xoZ6xoa6Lt3aidMiAOytTAA8f1EpfpnmP/PGjloLYczbGAAofi4Ij8/LyHs+z8dJ/AAMwICv+9GkHhJJdvv5ejy+Hu/PoIeHgpPKBZUAZo60v75jUt20SF24TFC9UTSz8elFSVnFs0a/JvHXpBV/7rgaSZZY1R2F4+RKY9fJxLZj69uJTwAUlryMiM+XJFDGuHWOSiooeFYO4PqDXHFyQdJx2rqLrX0OiH+c5x6b90NoQXH5z0sGi5dj1EWpI9K3EAD3npYA8gpfAFAapYZyCsDIvlbzfBxlfsQ3MEEQDQKtGSGaJEKh6NgxZsQImJuLG5KSktLS0oRCYWRkpKmpaf/+/RVJqqRWtbG0pZZNUhNqFcWQW2xVU9vY88Xd2uY1XyrftARBvDKk5ZQA6OdQ67xPIwNdEyM98XoHpQIABve0lK4uaWyoZ2Sg+0zeM7BSbfN8nNb9fvuPCw/72LcXVFT5Bye9O8aBr6cTEZ8PwP9y0tkbj2R0FhSX16jS11Wp/qiRvq605Xo6vM7mrWRkhP8l5Hg8Ji2n5NjV1MSMZ5n5pREJ+ZKdMmK/HDrX2r/T1bKmQCa7/bo6vL2fer6/KfSdDZd5PGZIL8vX3bvOHv2adKZAEVwmSBqVatMqmtnEjCIAPWxq7UDpYWMqPYqiWNWF4+TKMLxPJ//gJAAXIjIBjOpnJW4f3c/qB//oi7ezpg61iUoqWD+31kfesmm9nP+r3sLjMe1a63u5dmKpiaPUEZlbSPp3pVFqKKcALJnSc7KHjUzj7I0hSVnFLMMRBMEdWjNCNEVE168z06fjr78kLe7u7qNHj66srFyzZs3AgQMTExMVSaqkVqWxtKaWRVITahXFkGNsVVLb6PPF3drmNV+q3rQEQbxq6PLk/MsnlFqiwy5gqK9apU8WbR3NjEb1sxI/HB4KTqqsEs0dV7Mf5M1hdt+831/6Z8fyIeKFDFrgW7/bvecf//HovZcVVc527f74bMR3891U0sBi/+wxDplH39m+zN1noPWNB7mrdt+ye+dwuNRJJewonUEJ+no6AMoFVXUvvXhZCaBn15oneUUzKxQBAK/2VjdpG+oRK1Un13tA53JBVWxa4clraeamBuLdKwC8XK10dZjA8IzA8AyhUCTeoiJhbP/O88c7iX/mjnOc7GHDkhapnyMSlEapoZwiCEIL0JoRoinCeHggORl2dpKWvDz5/zrUlVRJrUpjaU0ti6Qm1CqKIcfYqqS20eeLu7XNa75UvWkJgnh1sDA1BBCfUSTdWFklLC6rEO8vUCoA4H41MCoAACAASURBVHbCE+mrZeWVZeWVbeQ9cHLR9r6349vrgy/fzfILeuhg3cbDuQMAu04mANoY82WOVi0XVBrwtfH/alLWs3UHbg/uaXnlpwmSjQxf/35b/ItdRxMAMWlPpUurPMqtOe5Eqf2CiqpWBrpLp/RaOqVXZZXwtzNxS7aFbfKPPv7NaHbDuIRUmnat9QFEJRfUrQITk1qoq8O0bV1zkJmimRWvrEnMrDVo9tMy8S/ssapL/SbX280aQGRi/tV72dK1SHg8xmdQl+jkAnNTA1Nj/qAeloo0KEVVR2Rgj5JctOAUQRD1g9aMEE0Vbg/PqkkqElZJgzbVch9LQzrVHEv9sDT3wGpIrYZMJQiiJeLp0tHc1OCPC4mCippFBHvPxQuFIvdellwEAOQWvrh6L1vqahyANzzlvBdx0fbWcDtTY/6eM/Gh0dnvja0uGuLUxbSrpfHx0NTCkpeSjmdvPDIcu3/l7ptqh0E58elFACa6d5Wu73DiWioAQYWwv6O5g3Wb/QEJEvPKyit3nYqVSLLbfzosTX+M7x9B1Qv6dHV4iyb20NVhhEK2yjpCIcAtpNKM6d+Zr8fbcyYuu6DWI/rZG4/i04vGuHWW3g+iaGb7O5pbW7Q6eClJetA/LiRyiVVdF+o3uSat+H0d2vtdeJhdUOYzsIv0Je8B1jGpTyPi89U8wIW7I3Jhj5JctOAUQRD1gzIjBEEQBEEQLYHv/ro7e2OI9M/ibdd4POaHDwcmZjwb9em5gJvp95ILfjx67+Md1526mC6d0hOAUgExb6y7+NfFh1FJT7Ydv7/qt1tDXTrIPZiGizYej5k91uFISDKA98bUlFPdvtQ9t/CF5/LTp8PSIhPy952Lf/f7EHNTg0/fctFs4AAA/RzM+Xq8HSceXH+QK6iouv4gd9T/ziVmPMN/m1Z2Lh/yKLfUfcmpX0/H/nYmbvCSk5n5pdIaWOyfMLirbcfWn++N+O1MXHh83qXbmTM3XK6sEk2XKu0pDV9XB8Dec3F+QYkcJ0iCkYHuhnluuYUvnOf+vXL3zUPBSfvOxc/cEDxpbZCxod7mDwfJyCua2R8+HJSY8cx79fnLd7OuP8idtu5idHIBx1jJuMAeHJZJ8XLtFHwni8djxrp1lm4f6dqpskoUGp09YXAXRX25wMURdliipAhNO0UQRP2g3TQEQRBE86AJHkzL/dRe9Q+mrQfNN2KNcvJxCyAoIlOmxcxEf+dyjznejnw9nVW7b41fEwiAx2PeGWX/46JBko0MSgWMDfWWTe31/qYrlVUiHo9526vbL8uGKDJDqTYA73s7bD8eM6qflZVUPdSJQ2xObRiz7Jfrk9ZWH1A6sLvF/lXDuJQpVZ+OZkZHvho1f3PokCWnAOjqMB9N7vn9B24DF528GZs3YXDXUf06B28d//Xvt5dtDzPg6871cezRte3Crf9ytP/SlvGzvg+RyJuZ6P+8ZPAML/mZEZ+B1n0d2h8LTT0WmjpjRDcuIZVm5fTeJkb8jQfvbjlyT9I41KXD7hVDZcqFsszsDK9ulVXCT3bdGPnJOQB97M3+b8HAT3be4BKrui7Ub3JH9rXacuSem6O59A4gAA7WprYdW6dml4zsa8XSXSlcHGGHJUqN5RRBEPWDEdE/GkRjwPz3by/dgQTRMmAYhstfM8PIeb6t2yg5tVdpYyOijtly49CIo2gBNc1uUr7IhWHU+kRjGEYUsqAB7ZFLyuPizCfPB3W3kDkQlF1g/JrzV6NzSgLeF3+pPsDJQnJGqZrDKSK7oCwuvdDVvr3Mo6MWEApFMalPhSKRi52ZzCEvhSUvZez55UTMsu3X7+6d2se+1sExLPYLKqquxeR0bt9KcnIwC4KKKh6PkT6LR9WQ5j4tu5/6lK+nI7cLl5kVCkX3UgpMjPjiWiEylxTFisWFRpxcRXBxRKkGRVEimh3MiD0yb+b02PKKQLtpiOZBcXHxyZMnFy1aFBUV1YAauDdqU60iSU2oVWksNdWqP4ncDdCmtdqcrwYRJgjilcWuk4mnS0eWh2p2Ab6ezvA+nTimRbgMp4iOZkZerlaN8uTM4zEu3cz62Lev+4RsMcVv0toL0i37AxKMDfVc7MxkJFns5+vpeLlacUmLiIVljihWNaSW7YxG9eustAvLzPJ4TB/79nIf+FlixeJCI06uIrg4olSDoigRBNFcoN00RPPA2tra0NAwPz9/2rRpDaiBe6M21SqS1IRalcZSU636k8jdAG1aq835ahBhgiAIoh68N9bBNyBhxrfB3gM6Py+v/ONCYlRSwY7lQ+r9OE0QBEE0HSgzQjQP8vPz+Xy+vn79v2GQq4F7ozbVKpLUhFqVxlJTrfqTyN0AlYSb0Xw1iDBBEIRKuDlaaOfc3CbOvpXDbDq09r+cfOJaKo9hBna3OLVhzMQhNo1tV/2hmSUIgpBA74ZE84DP52tCA/dGbapVJKkJtSqNpaZa9SeRuwEqCTej+WoQYYIgCJX4ek6/xjahqbD23b5r3+3b2FY0GDSzBEEQEqjOCEEQBEEQBEEQBEEQry60ZoQgCIIgiGbJzp24exebN6Ot1Dmkubn44gsA+OYbWFnJtru7Y+5cXL0KPz8sWYI+fWR17t+P69fx2Wewt9e8A5rk6r1svwuJn83scyEi8+7DJ5sXDpKueZn7tOwL3wgA38zpL31urrjdvVeHueMcDwUnXb6TJaPW3qqNh3MHD+cOKhlz+W7WoUtJ5YKqfo7mc8Y6NGD1TYmb9lZtdp58UA9P7a1M/C4kLpnSU+Z8GQD7zydcj8kRK+dukuacJQiCIDQHrRkhmiRCoejoUeTnSxqSkpIuXbokFAojIyMjIyNZJBUhVwP3Rm2qVSSpCbUqjaW1CFQjd3K53xvaslab86UoLCrHliBaBGVl8PVFSEitxuBg+PrC1xfnz9dqDw2Fry8qKgAgMRG+vkhLk6PzyhX4+uLxY03ZrDUSM575BiQ8Ligre1npG5AQcreWS8F3H/sGJPgGJJwPz5BuD72X7RuQUFEpBBAWkyOWkf5Zszd86LLTM74N5m7J4m3XRn5y7lZcXkHxy09/vek891hGXmmD+AgpNwHUz1OxhrQcOSZdiXosUc4RjTpLEARBaA6GjmUmGgX2g8FF164xQ4di61asWCFusbCwyP/vUZDH48XFxTk4OMiVVIRcDdwbtalWkaQm1Ko0ltYiIEbu5HK/N7RmrTbnS1FYVI2tJmAYhsvnCcOgrljdRvE7BJfGRkQds+XGoRFH0QJqmi23MTISbm74+GP89FNN44wZuHsXz55h+HAcPlzTPn8+fH2Rng5ra+zbhw8+wIkTmDxZVufs2fjzT4SGwtNTZQfV+Z+KYRhRyIJ6d6/LvnPxH2y5GrrtdSN9XbeFJz5+w/mnxYMlV2d8G3w36cmzUsHwPp0OfzVS0j5/c6hvQEL6kZnWFsaLt13bdTL23EZvn0FdJAKJGUVzNoXeeJC7Y/mQxZN7KjUj4Gb6+DWBn7zl/OOiwQBi0wqHLD3Vu5vZlZ9fb1g3PV06Ribk18PTCxGZH2y5emL9mMkeNjLKZ28M+TPooVg5F2M07SxBEFqAGbFH5s2c/bGFaDHQbhqiKcJ4eCA5GXZ2kpa8vDyOkoqQq4F7ozbVKpLUhFqVxlJTrUqBhYLJ5X5vyKW5zxcUhEXV2BJEy6B/fxgbIyKipkUoxLlzmDULhYU4dQpCIXj/rY69dQv29rC2bhRLaxD/h625f6+FQpHMIbL9Hc2NDfUi4vOkZc7dTJ812r6wRHAqLE26y624PHsrE2sLY0X6HaxNf189zHH20cDwDC6ZkV9OPDDg62ycP0D8sodN2+XTnL/543ZsWmEPm7bsfVmo6yYa2tN6oCFnCYIgCC1AmRGiqcIh2aGyJNHskDu5NOMUAYL4j/Hjcfx4TQbk+nWUlmLsWJSX48gRXL2K4cMBoLgYMTFYuLBRbZVC8g0kGi5LcjosbfWe8Pj0Il0d5v1xjs527SSXxg/qcvxqiiQvcP1BbumLirFu1uWCqiMhyVfvZQ/v0wlA8XNBTGrhwond2QdysDYFkJ5XCmDp9rAXLyvliu1bOQzApduZEwZ35evpSNoHOJkDCIl6LE4WBNxMn70x5N0xDtILPernZoN7KoP6zhIEQRBNFsqMEARBEATRXBk1CkeO4MoVeHkBQFAQeDz4+ODZMwC4dKk6M3LpEgCMHatZY6TzHZruJcPpsLRJa4P62JsdXOslFIo2+Uf9fSVFcnVUP6sjIclXoh97uVoBCIrM5PEYn4HWz54LAFy6nSXOF1y6nQVgrJuSdTU3Y3MBdO/SFsDvgYmlLyrkiu1bOaz4uaCySmRmUqsE6eCelgDuPnwifimoFBYUvywpE6jvZoN7KoP6zhIEQRBNFsqMEARBEATRXBEnRG7erP4lMBBDh4LPh7k5+vTBuXPYsAEAQkKqMybSTJmidXM1xv9+vdnV0jjsl0lGBroAJrp37TX376LS6nSDl2snADdj88T5gsDwjKHOHfh6Ouamhn3szc7dTN8wzw1ASNRjcR5BWnO5oEqSDkjLKQmPz1/rGwFAvOCiJOB9FqsiE/MB6PN1pBtbGegCEFQKxS8ne9hwL7DC7qY6nk75Mkjp6Oo7SxAEQTRZKDNCEARBEERzxc4Otra4fRsACgsREYGNG6svjRmDH35AQQHMzHD9enXGRJqRI2FjI6swNBRJSRo3u2GJTy9Kyir+YparOF8AwKQVf+44p2/+uC1+adfJxLZj69uJTwAUlryMiM/f+EF1LYwxbp1/8I8ueFZu1sbg+oNccR5BWvm0dRdlhuPr8X5eMli8+IIdoVDhRqHKKpWTBUrdhBqejuxrZdNBtuZIaHR2UlYxR/Ma1lmCIAhCy1BmhCAIgiCIZszw4fD3B4ALFwBg1Kjq9tGj8cMPuHgRU6ciKgrr18t2XLJE/tk02s+MiEQidfbUJGYUAZCpZNHDxlT65fA+nfyDkwBciMgEMKqflbh9dD+rH/yjL97OmjrUJiqpYP3c/jLKl03r5WxbXcuDx2Patdb3cu1k0qo6yXQoOEnRY//sMQ4d2hnVbReKRAD4ujp1L7HDxU3U19MlU3rKPZtGOjOiTWcJgiAILUOZEaJ5UFxcfPny5QsXLnz44Yd9+vRpFA1qoiEDGl2tJiQ1ZGrzslZDfhFEy8PbGwcOIDYWJ0/C3Bz9/3vg9fKCri4CA2FkBKGweruNRuFSS1UmA9Ig5VfFixV4tTXrSk7lAQB4D+h84HxCbFrhyWtp5qYG/R3Nxe1erla6OkxgeIaRvo5QKBLvRpFmbP/O0qf2yvDhj/8qKr0xe4yDQ+c2AErKagmk55YCsGxnyM25Gri4CTU8VYo2nSUIgiC0DGVGiOaBtbW1oaFhfn7+tGnTGkuDmmjIgEZXqwlJlVBJbTOyVkN+EUTLw9sbACIjcfVq9e9ixIVFoqNhbg5TUwwa1FgGytLgR/Z2Nm8FIDGzSLox+2mZ9EtvN2sAkYn5V+9lew+oqa/B4zE+g7pEJxeYmxqYGvMH9bBUaejs47NYrvL1dDqaGaU8rrUhJSa1EMBAJwuVBgI3N6ExT6FdZwmCIAgtI5toJ4imSX5+fk5Ojq5u/XN56mtQEw0Z0OhqNSGpEiqpbUbWasgvgmh5mJigb1/4+SE7W7bGqrc3YmIQEaHxU2m40+BpEQD9Hc2tLVodvJQkqKiSNP5xIVFaxqQVv69De78LD7MLynwG1loD4j3AOib1aUR8vqpntQAwNtRT9CMWeHO4XVhMrngjjJi95+IN+Dpj3DqrOhYXN6ExT6FdZwmCIAgtQ5kRonnAl6mb1xgamqYBja5WE5IqoZLaZmSthvwiiBaJlxeCg8HjyWZARo5EZSVCQzFhQiNZpi1++HBQYsYz79XnL9/Nuv4gd9q6i9HJBTIyXq6dgu9k8XjM2NoP6iNdO1VWiUKjsycMVrhrpt6smt7b2FDPe/X5wPCMxIyipdvDAsMzvpjlKskmnL3xqLXPgaXbw7ho4+ImGslTcHCWIAiCaLJQZoQgCIIgiObNyJEA4OaGtrWqc8LBAba2NQItmBle3f78fERM6tORn5wbsuRUyuPi/1swUEZmZF8rAG6O5m1b60u3O1ib2nZsLRFoWKzMW53fNA7AuNXnHWcf3X069otZrmvf7SsRqKwSlb6oePGykos2Lm6ikTwFB2cJgiCIJgstvSYIgiAIonnj7Q1Fm1RSUuQ0zp+P+fPly/v5wc+vwQzTJrNGvzZzpP29lAITI75dJxMAK95wlhbwHmAtClkgt2/KobfrNu5c7rFzuYf6hnk4d0g59HZsWmFOYZmnS0ddnVpfy032sDmwetituDyO2pS6CRU9nT/eaf54J7nCfmtG+K0ZwdEwMezOEgRBEE0Wer8mmiRCoejoUeTnSxqSkpIuXbokFAojIyMjIyNZJBWhmgbOarlrUGgAd50aUiuvkbta7oFVzVTO1qqkVlPWamC+VLpjVY4tQRAtER6P6WPfXpwvaGr0sGnr5WpVN1NQ+qJi9+m4N4fbcVfVlN0Uo8hZgiAIosnCaKISGEEoRXJsodw7UHTtGjN0KLZuxYoV4hYLC4v8/x4FeTxeXFycg4ODXElFqKSBu1ruGhQZwF2nhtTKbeSulntgVTKVu7UqqdWQtZqYL5XuWFVjqwkYhuHyecIwcr7br9sofofg0tiIqGO23Dg04ihaQE2zm5QvcmEYtaqrMgyjaJlDyya7oOzczXRFqzYIgiC0DDNij8ybOftjC9FioMwI0Tgof4tJSYEdt2+QuEuqpEEltepr4KhTQ2rVjyH3sdTX0DSt1dB8qTRWo0KZEVBmhBXKjCjr/opmRgiCIJoUlBl5ZaHMCNE40FsMQbQwKDMCyoywQpkRZd0pM0IQBNH4UGbklYU2QBIEQRAEQRAEQRAE8epCZ9MQBEEQBEE0D5gRexrbBIIgiOYKLc0jWKDMCEEQBEEQRLMhRET/2RMEQajMCIYyywQbtJuGaB4UFxefPHly0aJFUVFRDaiBe6OW1XKHu1qVrNKE2kaPQPOyVkPzRRAEQRAEQRCEDLRmhGgeWFtbGxoa5ufnT5s2rQE1cG/UslrucFerklWaUNvoEWhe1mpovgiCIAiCIAiCkIEyI0TzID8/n8/n6+vrN6wG7o1aVssd7mpVskoTahs9AioZ1ujWami+CIIgCIIgCIKQgXbTEM0DPp+vCQ3cG7WsVk0DuEsq6q4JtY0eAUXCTdNaDc0XQRAEQRAEQRAyUGaEIAiCIAiCIAiCIIhXF9pNQxAEQRBEs2TnTty9i82b0bZtTWNuLr74AgC++QZWVrLt7u6YOxeHDuHyZVlt9vbw8ICHh+bt1iQJkfkX/kjMSSt5+aLKqLVeL3fLCR92b2XSLJeVac6X49vu56SVLv5pcP26Pysob2NmINaTlVS87Jch6pskl+BDSXcuZ7EITP+0dxcnU1XVntz5ID2+iIvZ3CVVJT2+6MiW6N6eHcfMdmhw5QRBEPWAMiNEk0QoFB07xowYAXNzcUNSUlJaWppQKIyMjDQ1Ne3fv78iSUXI1cC9UctqFfrFPTJqmKohtapFQFEQ1IiABq1tPvNFEC2JsjL4+sLHB1On1jQGB8PXFwAGDcL8+TXtoaHw9YWbGwCEhVXL1GX6dBw+rDmTNUhVpXDz/KsX/kjU0WX6elkZtdZ7FFt47WTa3z/d33ByjNMAi8Y2UAU07UtkUGbsrbx6ZEbS44vWTbu4ZNvgfqM6i/VEX83RXGYkJiwnwDeBRcBrRrd6ZEZuX8q6fSmLi9ncJVUlP7NU7BplRgiCaCIwIpGosW0gXkUYhhH/IvcOFF27xgwdiq1bsWKFuMXCwiI/P1/8O4/Hi4uLc3BwkCupCLkauDdqWa0iv7hHRh1TNaRWpQgoCoI6EdCctc1ovjQHwzBcPk8YBnXF6jaK3yG4NDYi6pgtNw6NOIoWUNNsuY2RkXBzw8cf46efahpnzMDdu3j2DMOH18pxzJ8PX1+kp8PaGosXY9cunDsHH58agcREzJmDGzewYwcWL66Pg+r8T8UwjChkgXKxEXtCRPLFNswMDvZPHvuew/IdQwyN9cSN106mrX872Ki1nl/C9NZtm02RZk37smb8+dhbeaeevKdqxyC/xI3vXdly0UecGVkz/nz01ZyAkvfVMYYjFYKqMfq+HpNt1p8Yo6aq2Ju5z56UD57QtQElVeX2pcxPRwf4zHNcuW9YgysnCLmMYPZwfJuVeTNnf2whWgy0ZoRoijAeHkhOhp2dpCUvL4+jpCLkauDeqGW1ivziHhk1rdKEWpUiAAVBUCcCKhnWUueLIFoS/fvD2BgRETUtQiHOncOsWSgsxKlTEArB+6+i2q1bsLeHtbVCbQ4O+P13ODoiMLA+mZHGJerK42D/5AHe1p/9Ply63WOyzXvr+u1dE37il5jZX/WTvlQhqNLj6yhSyH61qlKoo6uwVh17X6XUwxd22K2tn2RdhEIRAB6PUXRV0aWGQu4QcueixyBLRRpQ2wXuktyvKqXuLNT7fuNiCYtyNe9kgiCaF5QZIZoqHJIdKks2LxT51VL9lYtcZ5tmBGi+CKIxGD8ex4/XZECuX0dpKcaORXk5jhzB1asYPhwAiosRE4OFC5VoE6+1Sk/XrM2a4PTuOACzv+xb99KUJT3btDdw8ewgfnnxr4dHNkenxhSKH6Sdh3ZYut29m4uZ+GpR/ovdK29d9k+qEAh1dBmXoR2Xbne37dVOfDU15umOj29EhTwWCkWm5gYTF/aY/VVfyVMlS9/blzK/nRHsNb3b8p3K67hw9OXg93ePbr23KWCc9Oaa49vu+62/s+P6JGsH04TI/N9W3YoOzRYKRW0tDact6/XO565yR2T3S8Lm+aEhR1IAfDnloomZ/uG0meL2u5ezdq64kXzvKY/H9BpiuWr/MCv7NuJL384I1uPzeg623L4sTEeXt/rA8Gsn05LuPvFLmC5RG+SXuPOTG+v/GePi2VFpcOpSdwivGd3YZ3nj7JDoq9li+7+dEQxg/HzHnStupMYUioVX7vMUu8BdUsyNs492r7yVHl/E4zHuE7sOf9Nu+7Kwrw6PFC+xYfdCrHzb4rCMxGc6usz4+U4rfh0a5Je457PwguwyAyPdt1f3ls6Isfuo1BKWSWf/KyAIoqVCmRGCIAiCIJoro0bhyBFcuQIvLwAICgKPBx8fPHsGAJcuVWdGLl0CgLFjlWi7eRMAunfXnL2aIuJCBt9Ap6e7nG/4DY31xs93Ev9+cueDbUvCBnhbz1zjqsvnxd/KO7r13mc+gUfSZ4q/V/9ySlB6fNGiLYMsuhoXZJUdWBe5bOjpoxnvGBrrJUTmrxhx1sRM/+NdHm0tDe//m+23/k5ydMGGU9VhZelbIRAWF7wsK6loQF8837Dd90VE0J8PpTMj5/bFd+ja2trBND48b9nQ0+06Gn3y29DW7fSvHE3Z90VEeVnlvA1uMjqV+iVh1Ex7kRDnDyS8vsDJ1rn6OVlQXvnZ+MCJC3vMXOOacq/g4MaolWMCDqW8Lb76okSQnFIS7J80ZKJNQXZZF6c2L0oEzwrKpdWKg1MhqOISnLrUHULpLJeVVBQXvJR0fxRXdOPMowkLur+zxvXBjdwTOx6sHnf+r4czVJIEcO1k2pdTgrq5tFt70AvA4c3RP8wLFZRXVQiEXLxIfVB481z6tOW9bHq0DdifcHp3XH7m8/iI/On/c2ljbnD0x3sH1t3u6W4pTm2w+6jUEvZJZ7mT6zdHBEE0CygzQhAEQRBEc0WcELl5s/qXwEAMHQo+H+bm6NMH585hwwYACAmpzphIU16O0tLq39PSEB6OtWsBKF9a0gQpLRI4uSmpRA7Af1OUTY+2m86PE7/0nGorKK86vj0mMTLfaYBFeVllTFju26t6T1naSyzQqg3/xI4Hj2ILnQZYbFsSpqPL7Lo1uZ2lEQCPyTZtzA33rgkPD8wY4G3N3neQTxdF5VHq7Yu1g2nPwZbB/klLtrmLH/iT7xWkxhQu+XkwgB0f3+Ab6Eis9ZxqW/D4uf+mqDlf95NZDMLul7Skq5dVfubz8wcSBoyzliw9qKoUrT7gOXrWawC8ZnR7/kxwclds8r0CyeKF9PiiT/d6ShI6mkBmiC8mXmCZ5brds1NL1h70GjnTHsDImfYVL6vO7o1PiMx37C87C+ySvywLs7I32XFjsoGRLoChU20+7HciLbaQoxe5j0olyt0ndp3Q5vcbZ9P9Et6ydjAF4DTA4v2ef187kSaOPPudrNQSlkl38ezIcidz9IUgiOZIPfdSEgRBEARBNDp2drC1xe3bAFBYiIgIeHtXXxozBlFRKCgAgOvXqzMm0kybhtatq3+cnTFvHgoK8PPP1ctMmh0mZgZKZfzTZu64MUm6pY25AYDnxQIAenyeHp8X9OfD4ENJgvJKACNn2u+4PslpgEVR/ou4W3lDJtmInyTFTFnSE8Dlw8nsfTXkC4Cx7zkUF7wMD8wQvwz6I1FHlxk16zVBeeWDG7ky1q7aP8wvYbpMWkSpX0rh8Rjxw7yYXkM6AMjPfC4t4D1HsyWxZYZgn2W53UfM6CZ5KV6tU5j3QiXJ+PC8vIznPvOcxMkIAHwD3Ukf9VDJC4lyQ2M9Q2Pdbi7txGkRAFb2JgBePK9U6qNSS9gnvWHvZIIgmhG0ZoQgCIIgiGbM8OHw9weACxcAYNSo6vbRo/HDD7h4EVOnIioK69fLdly2DM7O1b/zeGjXDl5eMDHRjtUNjIGR7oPrOUrFeDwmJ63k6rHUjMRn+ZmlCRH50jsddHR5n+713PR+6IZ3LotLZri/3nX07NfaWRrFR+QDuOyfdOPsIxmdxQXl7H015AuAUe/Yb1tyLfhQ0iCfLkKh6OLBpMETurYxM7h9KROAQ7/20sLS5TAkKPVLKfpGutIFPpk6xT71jXTrcMinCQAAIABJREFUXdWVIzJDsM+y3O7SLrDUK2WRzEkrAdDZoVaQLbsaq+SFtEIdPZ5551YyMiKhSDK0Ih+VWsI+6Q14JxME0bygzAhBEARBEM0Yb28cOIDYWJw8CXNz9O9f3e7lBV1dBAbCyAhCYfV2G2nGjpXdX9N8cfHsGB6Y8TS3TO7z28bZIX2Gdxo319Hv29sH1t02MNLtP6aznXO7KUt6ZacU7/ui5nSfMbMd+o3ufPVYSkRQZnhgxr1/c37/+vZPIRPEV4e9addzsGz5jw62rdn7qvplO0dfABga64182z7YP2nlPs/713IKc1+M/8AJgFAIAHwDrv/lsvvV7FA6yy0A9X1kmfSGupMJgmheUGaEIAiCIIhmjHj7TGQkrl6t2UoDVBcWiY6GuTlMTTFoUGMZqA08JtuEB2ac902oe/zK/Ws5QX8+LCl86eLZ4cC62z0HW/50ZYLkLNLfv74tLVwhqDJopTtlaa8pS3tVVQrP/Ba3bUmY/6boed+5ATBuw5+8uKe0vKC8UpKAUNT3m+OjG9wXcWYEwJjZrwX9+fDy4eSoK9mm5gbiyiDdercDEHcr7/UPa6rpxofnhQdmjJvnZG5VsxKhk52JUr8anKqKWis40h5wrcTBhaykZ0pnWRN0tDMBkBbz1HOqraQx91Gp4h71h91HpZYonfSGupMJgmheUJ0RgiAIgiCaMSYm6NsXfn7IzpZdA+LtjZgYREQoP5WmueP9voOFdau/vrt772q2dHtR/ovN80IBzPrCNT2+CID7xK6Sh0kA106kAhDvRAg7nTZG3zfoj0TxJR1d3sRFPXR0GaFQ1MXJ1LKrcejx1JLCl5K+N84+Gmu4f/fKm+x9NeGLpLHfqM4W1q3CAzOvHk8d8+5r4u0Y7SyNujiZRgRliutEiDmx48Ef39yR2Sqi1C+5CJWftaIQXb7Oi9LKF6U1x/TcvZxVf3V1UDrLGsKxv7m1Q5uA/QmSSJaXVZ7aFauJsdh9VGoJ+6Q34J1MEETzgtaMEE0SQSUCY3AnDUIhOppidC/Y16xgFJ2JZnpboUt7FgVyKBPgUmy1Tisz+PSCtVkDm12X60kiPR3GzVa6TXTxAVMmwKgeaKWvcQNOR8HVWmVPQxNEpS+Z8S4AUFAqupXKPHsusreUcUQhirpsD8IbA9FJzk5v0Z1HTMZT+dpcrdGlvdxIqqwkPAXZz2oaGUakr8vYtcdrHeT3YhmUgz1KxFQy5ko8eDx41qnhVyXE2Wj0toZN7T+H8BQIhRhkX6sxtxg3kzGoGyybZx0FglCMlxe2bAGPJ5sBGTkSlZUIDcWffzaSZdpCj6+z9tDI1ePOrxhxdtibdh6TbXT5vJR7T0/vji3MffHeun49BlkWZJfp8Xkndjzo7dnRoX/7xMgn+7+KzEh8hv/KNwye0LWjbeu9n0fo8nVeczV7Xiw4ty+hqlI0Yno3AEu3u6+dFLTc8/S879zad2qVFFWwe+VNU3ODtz51Udo3Iihz3bSLI9/u9r89ng3ii7T8mNkOf313F8Dod1+TNC7YNGDtpKBV3uff+dzVpJ3+9dOPgv58OHFhd7OOsjt02P2SQZevA+Dc3rjCnLIxs+tTV7W3Z8drJ9O+fvPSlKU9RULRiV8eFGSX1UOPIhz6mbPPsuZYvnPIp6MDlrifmrasF8NjTu16kJ+pkTUjSn1UagnLpJuaG7LcyQRBtGAoM0I0PXKLMdcXRWUYZAceD8Gx8P0XH3lh7lDxdWbzOfxvnGqZkZtJWHcS5ZUYYAseDwFR8A3F2omY2EcjLkj48zpjagTpB+MfAxn/W1jlrY20CICNZ0RrJzEqZUYKy7DhNPPXhwBE0RnM0j8Z63bobMbsCYVTR+yYBR22tWYsXUTdOjBf/4M979ftxVx6gAsx1S+evYAeD0bV8RF94s10aS8nkvVQcjQcd9Ph8F/qQSRi7mfiZSVmDcbHY+RoZBmUgz1KxFQy5n4m/rqOi6tgUuu8BtHlOGb9afyzWI7yijqZkaQcrD+NbW83emaEkVfdT83Glo06wXlFwjVyJLZsgZsb2rat1e7gAFtbpKZi5MhGskyLOHt0+O32lF//dzP075SQI9XnqnRxMl3ys7vXjG4AzDoafXVk1Ob5oUuGnAKgo8tM/qjnB9+7LRp4MvZm3uAJXXk8Zsul8d/PCtm68F9xdxMz/SU/DxZ3HzLRZsOpMb8su752UpD4aveBFqv2DxNXA2HvW1UpfFFaISivaihfpPGe4/DXd3dte7W171Pzj8GQiTbrjozc+cnNVWMDxM6+9Ynzh5vlbKli90uGgT7WDn3bhx5LDT2WOqKOJVyYurxXRmLR2T3x4iN1hr1hu+Rn9w3vXK6HKrkoneWGGqgu/UZ13ho8/vevb29fFsY30PWZ69i1R1vJ/dCAKPVRqSXsk85yJxME0YJhRCJaG0Y0Asx//63LuQO/OYXwFPz1Idr+90/J9iD43cDhRdUrR56VwUgfejqyHRWRko9398DDAd9MhoFedeP3Z/DPHRz8EI4K1gs0CIv8YGqEjW9Uv/wxEP638JkP3nDT4KDSDF4vWjupevUHR74/AyP96ofzKdvh1Kna/sfPMGUbVo3HtH5s3dm7vLFD9MFwZmwvNg3eP8K1a03QxMhEUilylXx6GBVCbJtZ0yIU4fszOHlX/p3AMihHe1jEVDIm/Qmm7sSaCbLBX3oQZS/hO1e5cgBhiVjuj21vY4hGzo9kGIbj50mLeVav66/YNZl2RY2vWrigSsTkSjbxf1gYRt4nmgrdGVHIAuViI/aEiJSICYWih3eelBa9tOnZru4SCaFQlBrzVCQU2bmYKTqFpEJQFXMtp33nVpIzU6UpyC5Ljyu0d23fuq2cFD97X1Vh90VMzqOSt238F28d/MYK57pXH6cUFzwu6zHIQukBMex+SVMhqOLxGHVOnKkQVD24nmvr3K4Nt/OJVYXLLDc4JYUvZUJ34peY7cuu7707VTpp1VCw+MjdEpZJb9g7mWgKjGD2cHyblXkzZ3tsIVoQtGaEaHpkPUWfLjVpEQCLRyEsGU+KqzMjcY9ha4HnL5FdiD5dqxdfVFQhPBkd28LOXFbhzktoY4gNU2slU1b64NpDRKRUP4I+fym6nsSUCURGfGa4U43kzSS81gHPy0XRWeAxTB9rWLUFIIp9DIDp0alGYUKOqEpYq0WGLedxOFz07VTGp/a/bmUCUdjD6qG9utesyLieBMcOiH8sevqC8XwNcY/lWqJEiQzhKcgpFunwGAcL+bs2cotx8i6OfVQd0n42oqn9qz8NOrWBhQnisoB+SMmXH3zrdgq7iJnWn9n/L9gzI9qEx+D9oTh5V5Scz2g0R6amMV3aw7kzLtyrlRkpKMWtZKydqGUz1YfLQy/3FEOLRzv5F6IlweMxjv3rfBRKXe3momQhoR5fx9XLStFVs45GipIUSvuqCrsvYs7+Fqejy4ye/Zrcq53sTMQVN5XC7pc00uUt6oceX6fPcMX/MKgNl1lucKZY+A3y6bLhVM2WtoD9CYbGenaasYTFR+6WsEx6w97JBEE0fSgzQjQ9upjhYqzo4gNmZA+IvwTQ4eHIohqBVUfxv3EY1A1rjsHbGZ+/DgDbgnDuHg4vktUmFOHfh3jTTXaNiZ4OAj6p/j08Bav/Ztq1gr0lcz8D2y9i17vVtTlWHcUQB/ybyPSzQVIunpaKdr7H9O3C3EzGn9cRvAqSrylWHGKm9IeizMiW8zgagR/eYry612pPyMGyvxgjPuwtmdjH2BWM3XOqNzv8zx/u9vj3IQOIvpvGrD8l1xIlSqRZehCxWejblSmvxLokLB+Nd91lZQLuwcq0eqeSng7WTqz5FiYpD7nFIjc7BkArffnBZ+kixqsHfrwgup/FODeV/zZEd9IZgGmjlc1NymAzZko/fHsKj5/VFGo5fw98XYyT8x0pQRDEq8DG2SHPnwnCTj+a/qmLhhZfENwZ+55DgG/CtzOCB3h3Ln9eeeGPxKSoguU7hmht0UoTtIQgiGYEZUaIpsfiUXiYy6w5Bn1dDLJDn64Y5iCnqoiliWj1BGbdCdHoXkxVFQ6HY8t0OemAlHwIRSIXa4UfhhVVWHMMg7pVb3koE2DRH/jsbxxcWC0Qk4kzH6OtEQSVmLmb8b+Bvl0wvjd2XcbVBAx3AiCKSGXySjC+t/whtpzH4XB0s8AwR9lLq46gpxW2zACPgaASH/6Br/7Bb3Oqrz54jIBPYKzP8HWx/pR8S5QqAQCI7mcxN5JwYkl1xufANez/F+8Mhsx/CeEpcO4sY6PoTjrzxzXcSMKcIdUbYZQFX04XMZYmaKXPRKaisTIjecWic/ckr5jYLObUXTh31tAGk4Y0ZpwzfgjAhft436O65Uw0Jrkq3FYWm4Xlh2q1FD1vGLMJgiCaBg/vPslKKh77nsPc9f0b2xYCK/cN62DT+rJ/8rUTqQyP6T7QYsOpMUMm2rzKlhAE0YygzAjR9GhrhD8+EEWkMqHxuP0IoRex7SJG98Q3k8Gvdccy411wNYHZcBrlFZjaV5ykkEH0/CUD1p36YQ/x7AWW/Fedz4iPuZ7432Ek5VVv3hnqUL21h6+LHp3wrBwALE3gZouzUeJBmYB76NdV7qkruJoAAEtGYccl/HQBn46rse3OIyarSLTxTUacnuDr4l13rDqK5y+rd6l4OqC9cY0qeZYoVyKOVWt9APC/hTfcYGeO9z1qHrCluZeB+cNk2hiBACN7QI+HgzfRw6raZdbgy+1STZ8uSMyRM7R2SMljNp0FgJeVqBLBuTMWeeEtbZV9UccYPR34OCPwv8xIQg6S8/DtFIXK+bowN67VUsW19iFBEESzYP/9NxvbBKIW767t++7avo1tBdCULCEIorlAmRGiicK42Vaf6FFYhhO3sesyrNviozqnC3zxOkb/AAO+dMahlp4enQAw+SUKRyouhw5Tq2aHU0cAeFxUnRlx7CilribDIprcl/nqH5QJoK+LoBjRZxPkZ190GNGPbzNutigXYN9VuNnVrBzJKQbAzPOtERafqPcgCwPsAKBn7eUbci1RqkSMTXusGItdwTgaAbNWGOaIGYPk1GR5WSmyMJF1RHzEycQ+2HAaX/2DK2uqV5qwBF9RFwB8HQgq6oRJWwyyr65LKqjEd2cQEif6yIvhXs23UY0Rvd6X+ecOEnLg2AFn7sLRkq1+sL2lbAmSsETcTGko2wmCIAiCIAiixUCZEaKJ8TAHv4aI5g+rKWXa1ghzhyI2C9eT5WRGQuLAYyCowJlo+Wem6OnAui3CU/BOnbP6lh+ClamouxUjAoSimkf34jIAUFZznhnVA9+fxfn7IgM9RodhvBVUFR3iwIhTPAuG40YSvj6Jw4uqN56Ih9gyHXq1/xKdVKnKxl3JO4PwlhvCHiI8BVfice4ejn5UKyUEgMdUJ1bE5BbDvHVNZNxfw8m7yC+ptl9u8Nm7ABCJmsRhG3xdrJuMtCfMp0fgv0j+ep8mZgzjbIVuFrhwD69Z4vx9LByhZTM1Cp3aqyp0ai9RP87vT4i5njPzsz5W9o36vtdkSIjMv/BHYk5aycsXVUat9Xq5W074sHsrE35j24Xj2+7npJUu/mkw9y7PCsrF9VZO7nyQHl+07JchGrNO2wQfSrpzOYtFYPqnvbs4qXyIjEqB0lxU0+OLjmyJ7u3ZcczsxtjbSxAEAKD+540RhEawaoewh8y5aNn2wjJ0qFNDJKMAP57Hh16YOww/XUBGgXydk/oh7KEoOkO6TRT7GGEP0aYVrNpCKBJFpddcE0t2V5ae0OFhQm+ExDJBMfBxUX6KMI/BhqmoqMLnx8QNjK0ZANHzCgywE/+IGAZBMVCl6D1HJaL7WfjmFPR0MNwJq3zgtwAvK0UPHsuqa2PIJFQ3iu6kY/xPCE+uuZpVCB6Ddq0A+cFX0kVMYZn0Np/GhMdg/RQIKvDtycY2hbMxE10RGINrD1FarrCuTTNEJJL9kduuSLip/Wg/XCwRa/RoNIWIEdJEXXkc4JtQ8LissQ1pfKoqhf8358pCtxOnd8dWCoRGrfUexRbuXnXrPaej8eF5jW0dIoMyg/5M5CicHl/0fs+/k+4+Eb+8fSkr8HeufZsFMWE5Ab4JLD/5maX1UKtSoDQX1fzM0gDfhOir2ZpQThAER2jNCNHEMOJj7jDsvYKiMox1FhkbMC/KcSEG0RnY/k4tSaEIa/+BrTnmDIFQhMuxWHMcfh/IlhQF8M4ghMQyS//EB8MxzAH6fFx7yOwKho0Z3h3MGPHRy4pZfwrbZqJLe1F0JvPbFfg41zo2WBETXfHuHgCivXM5fS9rbYYVY7HxLHaHYOEIvNYBbrbMzxdga4bXOiDtCbPhNDq1hYEet2ABAEcljKEezkTB0gQLhoPHIPAeAMbBUlZbXxvkFld36dsFjpbYEojt76JTG9xMwv5/8UZ/6OkoCj5bFzFCEWKzMNFVBQcl5DwTBT2o5VRvazk1d1WiS3vMHYbfQkRnopnX5SUaWAblaA93s5UaA8DHBduDsDMYPr1h1PhfaRIEQTRfNs4OCfZPHvuew/IdQwyNqz80r51MW/928JoJgX4J01u3bRp5fA7Eh+elxRZKXr69urfPvDpF35szy3d6LN9ZXR+tQlA1Rt/XY7LN+hNj1FSrUqBaXlQJgpCGMiNE0+PDYTDWx8HruBBTnW7oaoYfZ8DdvpbY3quIz4b/IgDgMfhuGmb8ij1X5Gwx0NPBr+9hxyXsuIRtF6vlxznj47HVz5Y/zcT6U5i6EzoMIwLe6I+PuX3WOnaArTmqqpjesue5KGRaP1xPxL6rogF2TN+u2PQWvj2Jt3+DDoMqEQbbs9XUVAQXJfYW+HIitl7A/n/BACaGom+mMDayJ/6IPB2Z78/U7C3aNgtrj2Piz9BhIAKmD8CKsQBr8BV1EeuPSmeqRBjymso+Arifydw/VqtF7mlEqjJvKC7GMFsD4fGanHQYy6Ac7VHJbHZjALQ1gqcjQuJFq8fTJgmCIDSHUCgSCUU6ijeWKhWoqhSyXFVVGwvsAwmFIrlntUZdeRzsnzzA2/qz34dLt3tMtnlvXb+9a8JP/BIz+6tau3S5xARAPY6GVcd9ufQYVOebD7XtrxBU6XFe06p09lkEFE2ZSshVUtcFuYGCglCoJKz0EkfqBoo9tizTpNQYlf5mCaLlwYhoGSvRGDD/7X1nuwOflYmSnzC27Tkt3+CCUITMAlGpgHHsAJ06b/0VVch4iq5mci5pmooqpOTDzlz5lhw1lQhFyC4CIFteREKVEN4/4ovXa50mU1wuynwqP2iKUNRly3nkl2ITnSbQAmEYpgE/T8TvEDIK5TY2fRT50rCOaGcU7SDX7KbvC8OwfqIp786IQhYoFxuxJ0SkXIyFjbNDgv58uC30dRfPjnIF7l/L2fd5eExYrlAoMjU3mLiwx6y1rtLPWiwC384IBjByZrftS8LyMp7r8XkTFnSf950bS9kORdp2LL9+8eDD325P7dC1tUR43+fhZ/bE7Yt+w9yqVWrM0x0f34gKeSzpOPurvpLnum9nBOvxeT0HW25fFqajy1t9YLjXjG7S4347IzjkSPKOsEk93WUfd1+UVlw+nOzi2cHawZSjy+PnO+5ccSM1ppDHY5yHdli5z9PKvo1SF9g1rxl/PvZW3qkn74lHSbr7xC9hukRPkF/izk9urP9njItnx83zQ0OOpLworTA01jMx0z+cNnPj7JDoq9mH02aqY7+4b1H+i90rb132T6oQCHV0GZehHZdud7ft1a7uVHKZfZZZUzplEljWjMhVcvGvh0c2R6fGFIrTJc5DOyzd7t7NxQyAdKCUhkIl4RtnH+1eeSs9vojHY9wndh3+pt32ZWFfHR7Zb5Sc79JuX8r8dHSAzzzHlfuGSSvftjgsI/GZji4zfr7Til+HBvkl7vksvCC7zMBI9+3VvaUzdyw+KjWG/U+pJTGC2cPxbVbmzZzTYwvR/KE1I0QTpo0R07dLQyrkMejSXmGqXE9Hzlkt2kFPh+2QkQZUwmMU5kTE6PAwewgO36qVGTExqCmIyxG5XZ6/xMm7+H2+aqoIgiAIbRERlPnZuPOWXY0/3uXRxtzgVkC63/o796/lbL08gYvAixJBUvTTq8dT5q53s3Np9/DOk/1fRj68++SXa5NUHW7Ym3bHt8cEH0x65/PqDZhCoShgf4Jtr3bmVq0SIvNXjDhrYqb/8S6PtpaG9//N9lt/Jzm6YMOp6lWKL0oEySklwf5JQybaFGSXdXGSLTcbcSGDb6BTNy0CwNBYb/z8mg9BpS4/iiu6cebRhAXd31nj+uBG7okdD1aPO//XwxnsLnCJtoQXJYJnBeXSLRUCYXHBywpBFYBRM+1FQpw/kPD6Aidb53YAykoqigteqmm/uPuXU4LS44sWbRlk0dW4IKvswLrIZUNPH814R7L/SNpI9tlnnzWlU8aFukpO7nywbUnYAG/rmWtcdfm8+Ft5R7fe+8wn8Ej6TB6PkQ6U0lBwF752Mu3LKUHdXNqtPegF4PDm6B/mhQrKqyoEQo5epD4ovHkufdryXjY92gbsTzi9Oy4/83l8RP70/7m0MTc4+uO9A+tu93S3FKc22H1kN0bpnxJBvDpQZoQgiNq8Mxin7oiiM5je1g2s+a+bmNin+ixkgiAIounx44KrbcwNdt2abGpuCMBzqq1lF+MD624H/p7gPceRi8CTrOef7B76+ofdAQzy6cLX19m96tbVf1I9p9qqOpyVvUmwf01a4e7lrMLcFx98PwDAtiVhOrrMrluT21kaAfCYbNPG3HDvmvDwwIwB3tUfXunxRZ/u9ZTOcUhTWiRwcuP0dYhSl7NTS9Ye9Bo50x7AyJn2FS+rzu6NT4jMd/bowOICF80ccfWyys98fv5AwoBx1nWXJNTbfsf+5uVllTFhuW+v6j1lafUBfK3a8E/sePAottBpgJxPc/bZVzpr7FPGERklX0y8YNOj7abz48QvPafaCsqrjm+PSYzM/3/2zj0uxuyP45+ZpukiFUmSlLSJLtiIkoSQtIRdl9jcYtfKbS92retiWWvXrrt1F6tl+UWStCVF0o1Quohu2m5SKpVpmvn98bTTNM3lmZlKOO9Xf5jznOd7Oc95JufbOd9vcxekDEVzRVI671kWbWSuvTfGU12TBWD4FNPP7AKEE8HIpCinSiDccaKJh86JmKBcv/Rp1D4mS/uu86z+vhWQTT1u/+1JUnyUbgydV4lAeE94BzdKEQgEpWAysPtTMFvhy6GPAd0ELoT3Hmq/KoPR5IdCpLH9/7zZEXvj7rfbESM0Jy2uuCinym2OBbWEppj2dX8mkxFzOZdOBwBsdZUJCxtXthMX9wMQdf6pAurGzbHISi7LTGqotxLq95itruI627y8pCY1tnjYJFNqLUcx2dcKwPW/GoujMZkMt7nSaqBq66krPyaUopFC5z6ofShlxTVSXKApWXmUtF+VzVRlM0NPPQ4/k8mp5QIY7WW+9/YksWERSH36dJ6azEdGBxEh/tlee2OabFnS0VcH8KqCI/ZeSUNBv3NaXHFx3iv3BZZUJAIAW5016Yt+8nohEK6hpaqhxept21lwvMvIXBtAzSuuTB+lG0PzVSIQ3hPInhECgdCM7jqM7orsYpWBi1J/BSK8b4jNNCG2nUDxNubmILQrCrMrAVjYNUnOra7J0tRWpf7CLLMDACsHA+EUjxpaquqarFcvxaxCZUpzX2B5YkPitZOPzQd0qePUh/tnjv3UQpWtkhZfAuC6f2ZMUI6IzAqhIydqmiwpuRLUNVkptwsljgVtIylFwi4L/1uSCzQlK4+S9quwmF8fdt4+L3LLrOtMJsN6mIHjRyZjvD8QXkgLI+Xp03lq0h8ZTUSEMJmMwuzKqPNZeRkvS55VpceXSDnSImUo6HemxryHRZP/RxmYaMnrRZMHocrU79FBpA+fxxeoluSjdGNovkoEwnsCiYwQCC1PRUXF9evXr1279tlnnw0YMKA9i20lUwkEAoHwlsIUtzQVrMFkdlDTkC+VuBRpeoaadq5G4f6ZS35zCD+TWc/lj5/feMZkxCdmVg6iWUK69eoIetg6G8aF5L0oqha7yN/mHTHApbtAncwxkYR0F5SRLBfKaBnrbWE3pkfU+afxoc/iQvIe3Cw8sTHxtwgPsdtGZD59JZ+aAvhtSjy+IVFdkzVobA8zm86Tfa0LnlYcWRPfehrbHiV9bPuHQiC0T0hkhEBoeYyNjTU0NEpKSqZOndrOxbaSqQQCgUB469DtqgEgL61cuLGey6uuqBvg0p1OBwDpic+Fr9ZWc2uruR10xNSmoSPNbV6fzTPD713PD/V7bGyhY+PUDUB3M20AWjpszyVWwvdyarlsdbr/s3XyNI0Lybt6NF2QBETAw1uFoaceV5a9Hj+/Dx0jpSPWBZruN7lU12SnQ3YKrX0lyttfx6lX78CavNR68lLrei7v8h+pu3yj/bff/+HCmOadpTz9Fnlq8pKf+fL4hkQrB4PfbngI6iud2JjYSuooDM20AWQnvxDOrVOUU9VK6qT7KN2YN/JQCIR2C8kzQiC0PCUlJYWFhSxWC/9SaQ2xrWQqgUAgEN46bJ0NdfXVr53MoCqeUFw5nMbj8a0dDeh0AFBWVPMgqkDoaioA54/NFFAHwGWamZYu+/KhtPuRBePmNCSP6Gmpa2CiFXkhq7LsteDGmKCccRrHDn5zh6azbvMsuhp3OP3jPWFrAZSX1OxYEAlg9pqBNI2UjlgX5JXMYqvUVHFrquoELfeu5zfXxWt2TERJ+6MDs8eqHQ09mUF9VGExJy7up8Ji8CTsN5Hy9FvkqclLblo5AMeJJsJlp28FZAGgWSZGAfoM0je20Ak+li7wtLaae2n/o1ZSJ91H6ca8kYdCILRbyHKIQGh52Gwxfxxrn2JbyVQCgUAgtGdO/3iv05E04Rbfat9IAAAgAElEQVTNjqrL9zl99vOQ7fMiv3a9MvO7Afo9OiT+k3/k+7ielrqTl1oBYDIZ0jtQbPj4ny92OvSy7nQ/suCPVbG2w7uJLUxDRxqTyRjnbXFhdzKTyRgrFFZYuttx7aTQ5c6BC34c3KV7h8yk0oPf3NHVV5/2tS3NEVBlq6w9M/rb8VdXjgwa8YmZk6cpi818+uBF4MFHZUU1czbY9RtqQN9lKUhyQS7J/Z0Nb13M3vhJ2OSlVnweP2BPSmlBtXAHFlsFwJXDqWWF1WO9FdTSHAcPE8NeHQ9/H89iq3wwUO9VBefKkfR6Ln/k9N6SbpHy9JV/avJiYaevymYG7E3p72xoMahLRsLzY+sT8jJeohWOLAmzfN+wr8cE+zpemrrMmsFkXNqfUvKstfaMyPRRujFt/1AIhHYLiYwQCAQCgUAgvF/Ehz4TadHWU1u+z8ltbh9VtsrBVbGrJ4QAYDIZrrPMF/86VLC1XmYHDS3VKcust8+7Uc/lM5mMUTN7L9szTJIZMqUBcJtncWF3sp2rkb5RYwbKYRNNt1wau2fZ7bWTQqmWvkO6rjo2QlJmULHYOHX7I3Hyga/uRP79NOJsQyWOnpa6vr87jhKqOULHSOmIdUEuyVOWW+dllAcdSosLyQMw4uNevr87bpl1XdBhiLuxxYddIs9nRZ7PEi6YoqT9TCbjl7AJW2dH7Pz8JtWirafm+7vDqBniIyPSn36LPDW50DPUXH/WdYdPpO+wSwBUWAzPL6wWbh28eMjFR3eKHTxMWkmvnWuPneETTmxM3L0smq3Ocp/fx6RfJ8EYtiwyfZRuTNs/FAKh3cLgk7T1hDcB47/CjO/wDFRTU7ty5Yqrq2v7F9tKphLeKxgMRhu8ze9SSde2+fIjI9ZmMBhK/UZjMBj8iEWyu408FMGX3U15/n1a8fzZq75Duwpv0ZfZYfWEq/ejCoMr59Vx6lNuF1nadxXUClVSnSRKC6pzU8vMB3bp2ElNrhuF4fH4j+8+ryp/bWrVWc9Q4oJQYSNlQlMyNaq9bDrrSKg3XMepZzIZksq7KGN/Hac++VZhlx4dBIVjm0P/6bfIU6MPj8fPSn7B5/HNbPWkl5tpKSrLXou4FrAnefey24fvTTEf0EXSXcogxUeaxrTxQ3kjjGQcovk1K/Jl/j4sWwggeUYI7RQej3/uHEpKFGx802IzMzPDwsJ4PF5CQkJCQoIiYsX1bA2xEmUqbW0LDCyB0Aw+/935ISPWPkeMQNHdTNvW2VDKElp6B1W2ygCX7jTDInTUSULPUHPgKCMl13JMJqPPIH071x5SwiJQwkiZ0JRMjaqksAjVQUrVW2XsV2WrDBxlJCUs0txOKU+/RZ4afZhMRm9bPfMBXdomLAJgcle/tZOuCbcEH0vX0FI1s9VrJY1SfKRpTBs/FAKhHUIiI4T2CP/2bcb06Th9WrHGNy7W0dFxzJgxXC539erVQ4YMycjIkFes2J6tIVaSTOWtVX5gCQQCgUAgEN46xs2xiA7M2TQjPORE+sV9KYvtAzKTShf9ZN9moZl2awyB0J4hp2kIbwbZ29KePoVZs1T29Bsl0ZZi26xnuxWr/MAS3h4knaZJS8Mvv8DZGd7etOTs24e0NOzZ09hSWgo9PfGXJLFrF7Kz8dtv4q/Ka5LyCFwgvMO8Y6dpFOPExsSshy/E1nMlvPOQpy/MqS13r/s/yc98yWAy+g7p+smXNsMmmhJj3izkNA1BOiQyQngzkK8YAuEdQ1JkJCwMY8ZgwQIcOUJLzuTJCAtDZSUApKVh6lTs2gUqB47wJelMmIDYWDx/Lv6qvCYpg4gLhHcYEhkhEAiE9gyJjBCkQ07TEAgEAqEd8e238Pdv+HdcHB49En/pbUHEBQKBQCAQCARCO4RU7SUQCATCm4HHAwBm0xD90KES+0u6xOGAzW5FkwRwuWC10K/NFrSZQFCM9ISSayczCrMrX9fUa3ZUtXY08Pisbwft1p2XL0trpSQQlcSrCs7+L2NYqswlvzmI1Jqt49Qf+OoOk8lY/OtQ4eSjinn309wbo2b0tnczltfCVuXivpTctHIpxY+FCTzwqLLs9azvByqv943MEDpc2PWwMLtqyW8O9G8RTDy5BlMuws9k3r2eL9JoZK5j49TNxqmboEUB41ub3LTys7/c7+9sONbb4k3bQiC8ScieEQKBQCC0HTNmYMYMhIXBxgYqKlBVhYsLMjMbO3h7w9QUAHx8sGQJAEye3NAiuERx+jT694eKCtTUoKICFxc8eNDyJlFXAwPRsydUVaGmhqVLUVHR5PY+fZoI9PNDly6IihLjQkkJ5s6FmhrU1KCqilGjkJysiM0EgjLUc3k/zb3x+eCAwIOPuByeZkfVnEdlB1fFzrE8lxZX3EpKc9PK51n9nXlPwiE3qXTQZuv30Ao8mLrLN1rk0m7f6IC9KX2HdBWERRT27uyO+8nRhYPG9lDAwlYlMSw/5ESG7H4AAIeJJid/SHwQVaCMxjcyQ+iTEPos9BTdARGZeHINplwkRxcGH00X+Tm8Om7Z8MBNM8IF3eQyvm0oeVYVfDT9vnJzhkB4ByB7RggEAoHQdlRWIjUVly9j0SKsXo2YGOzdi/Hj8fhxY4fSUgDw8gKPh+PHsWgRbGyaXAKwbx98feHmhtWrwWYjNhY7d8LdHbm5End8KGZSZSXu38eFC9i8Gba2uHsX69bh3j3cuiVqsAAOB6Wl4HDEuDB5ckP+VxMT5OdjwwYMH468PGhpKTKYBIJibPOOCPd/Mm6OxfK9wzS0VKnGWxezN88MX+0R4pc+vTUqd6bFFWc/KlP49rkb7RJCnwUfTXecaCJIHhl+JjPocJr7gj6jvcwFPRXz7kVR9YmNid8cHfG2F+zQN+owZZn1b4tvHU/5RGEhb2SGtBIiE2/mt/3dF/SR0l9Jtl1xG+reU/AxL6N8+9zIiLNPbId381xi1Xp6CQSC8pA9I4S3g4qKiosXLy5evDgpKUl6Y+tJaDNrJfVsDWuVl0nf2VYabcJbR1YWDh/Gb7/Bywt79mDhQmRmIiFBtNuoUXBxAYDx4zF3rujV7dvRrx+uXsWMGZgyBdu344svkJ8vRo7yJuXnY+9efPcd3N2xdi1+/hnR0fjf/2SLFXGhuhrR0ViwAEuXYuJELF6M339H374kEQmhTUm68W+4/xN7N+PvTrgIFr0AnDxN52ywKy+pDdjTZCMTjyc+42A9lydFSx2nXi6rpEujWH92dAdt1V98ol4UVQPIz3z562c3Tft1Wr638WSEvN4JOPvzfa1OaqNm9JbL7PaJp69V9qOyf04/lt1VHAqMIY/Hl/4EeTy+pIkkHZmS5aXfUAMHDxMFtCjmgrGF7rcnRgCIC8mT3lP6KyNde8u+jDKFS1EnRRedAWzZZ00gyAvZM0J4OzA2NtbQ0CgpKZk6dar0xtaT0GbWSurZGtYqL5O+s6002oS3DiYTM2Y0fnR0xOHDKJZzg3Z2NqqqmrTo6wNocs6lpUxSV8fChY1XFy/GqlU4fx5Tpsinhc0Gm41Tp9C/P6ZMgbo6vLzg5aWIwQSCwgQeTAXgve7D5pcm+1rpdFG3de4GYNOMcFU208rBYPeyaBUW89vjLlTUICv5xd4VMUkR//J4fF199Ymf9/Ne/6HgJMs/px+f3XE/K7mMx+MzmQyb4d2W7nbsbau3wycy4uxTAOsm/6Otp/ZXdsO8ly5NhK7GWisPDN8y6/qPsyJ+CnZbOymUz+NvChgjnHmEpnci1HHqAw+mTvCxlDJuiWHPNs0IHzW99/J9TlK6tfi9zbmw66Hf5rtSpHUz6Wg7vNul/Y/GzP5AAflyjeHDW4VHvo9Lji4SPMHZaweqslUAUEdIJvj02bcyJiu5jJoP3xxxNjLXAbB3+e1//nz8R+KUbiYdBdKOfB93+VDqkfsf6xt1kCJZhE0zwjPvPfdLny5oCfXL2PdlzOb/jb3mlyEy8bZ5R9yPKhDMQOlapLtAE2MLXQDFuVVir0p6Zehol/76lJfUHPwm9rp/Zh2Hp8Ji2A43XLrbsZd1Zzo2C1TvWhKdl/FShcWY4GO58sDwUL+MQ9/FlRZUq2uyZn7b33u9nUwvAMQE5Rz8JjY3rZzJZDhONHH5xGz3suj1f422c+1BxxECoc0gkRHC20FJSQmbzVZTU5PZ2HoS6KOkLkk9W8Na5WXSd7aVRpvw1qGp2eTAi7yHXwR3ZWfj/HlkZODZM8THg8NpLZMcHJq0aGlBUxMvX8qthcXC4cOYNw+zZoHJxLBh+OgjeHvDwEBRuwkE+Ym/lsdWV7FyFDPtNLRUBdGBmkrOk6eV4f6ZwyaalhZU97TUAZCeULJyZJC2ntqK/U6dDDQe3izw23z3yf3SLZfGAbi4L2WXb7S9m7HX6oEsNjMttvjczgffuYeczfVy9TLn83D1ePpHiyx72TSszaRLE8toL/OYoJxw/yfLnS9nPyr7/tRIatkpr3cixATl1lZz7cYYSRm3Og6vovR1dWWdlD6tca8IF/el7F0RM35eH+lBlkFjexxbl1CcV9XVWO6jevTHMD702XfjrxqYaK3Y76Sjrx4bnOu3+e7DW4U7r3sAqKnk5KSWx1zO8VjUd9bqgSkxRQF7U74df/X04xkARnxidmF3cvifmYJksTweP/hYei/rzvpGHaRLFqGmkvOytFa4hRrwOk5984lXXVlXUfqajv0yXaDJoztFAHr27dT8kpRXhslkSNcu8/VZNzk0N6188S9Du5poleZXH9+QsGx44Lm8WcL7gCRRU8nJSim7cyV36nJr036dgo+lBx5MLXn2Ki2+ZPpXtjr66ud+fXB8Q6KVo4Gdaw/pXty6mL1ucmhv285r/xwF4K8d939eEMmpra/jNGwPUeB7gEBoJUhkhPB2wBZXxUFsY+tJaDNdknq2hrXKy6TvbCuNNuH9ZNMmbNgATU2MHQsbG/j64ulTrFnTKro0NFpMlLc3xozB+fMIDUVICG7exMaNiIiAvX2LqSAQpFNVzrEcrE+nZ25a+deHnYVXwrt8o1VYjP2xnp0NNAE4eZrq6GscXh0XF5Jn72bsvz3JtF+n7VfHU52dp/Ti1NZf2J2ckVAycJRRybNXV4+n2483FvyhWLo0SVZ9dcj54a3C1Nhi11nmzfdE0PdOmMR/ngGwc5UWGRnq3jOCv0heycrfK0zggUe7fKM9Flp+dchZek8z284AkqOLRs2QOzJCfwx/XRSlo6++P9ZTV18DgPOUXgY9tY5vSAw5ke42tw+AgqzKtX+OorLAjPYyr3tdH3Q4LT2hpM8gfRunbkbm2uH+jZGRe9fzy4pqFm61pyOZJmInHn37pbsgViOntr6mqiEEVphdmRZXcnRtPICJn/dt3lnKK2Np31W6dumvT201Nzm6aOaq/pOXWlPCO+iwA/am5DwqoyTLpCinSqDacaKJh86JmKBcv/RpVCzS0r7rPKu/bwVk27n2kO7FnmXRRubae2M81TVZAIZPMf3MLkA484ti3wMEQmtA9ikRCAQC4S0jMxMbNsDBAWVlCAjAgQOYMUOpPSPSSUxs8rG6GtXV0BHaTF3X9C/BKSkSRXE46NABS5fi8mXU1GDvXlRXY/v2FjWXQJCFNr26uUwmw21uYxXP8pKa1NjiYZNMqQUMxWRfKwDX/3oCwD/ba2/MJGEJOvrqAF5ViHk5ZUqTRFlxzauXHADp8SWcWq7C3glT8uyVuiZLpB5we+PyH6m/fXHL84t+MsMiAEz7dQKQGqtgHRk6Y5gWV1yUU+U2x4IKK1BM+7o/k8mIuZxLfWQyGSOFUrdQ+1DKimuoj+PmWGQll2UmNVSNCfV7zFZXcZ1tTkey8tDUIt2F5myY+o97x+PUz3yb8z8viKworfX93WGAS/fmnWW+MpK0y3x9VNlMVTYz9NTj8DOZ1Gsy2st87+1JNMMiIqo1tFQ1tFi9bTsLtmgZmWsDqHnFle5FWlxxcd4r9wWWVFgEAFudNemLfoKeCn8PEAitQbv+HUAgEAgEAq9ZRra0NACYOBHC+5ACAgC0SnykqAhRUXD+bzFy+DAAfPxxw0c2G1VVqKpqrC9z/bqoBMqFwEBMmoTdu7F0KQCwWFi8GCtWiHGQQGg91DVZKbcL6fRU02QJH/VPiy8BcN0/MyYoR6RnRWktACaTUZhdGXU+Ky/jZcmzqvT4EsGG+ebIlCYWHo//wydhtdXc0TN7h/s/2bcyZuWB4Yp5J8yrlxy2hpgEFu2Hmqq6nZ/fBJCbTusgn36PDhA3kg+iCvy3NyZB7+dg8Ola0XwiNMewMLsSgIVdF5F7NbVVBTsC1DRZwrV+ROr+uC+wPLEh8drJx+YDutRx6sP9M8d+aqHKVqEjWXloapHuQnOmLrMWnBdjMhkdO6sNHNW9g7b4PbMyXxlJ2mW+Pios5teHnbfPi9wy6zqTybAeZuD4kckY7w+EAxDSEVGtosqkJpUwfB5fuhfUIPewaJKWxcCkcR+TYt8DBEIrQSIjhHYJj8c/f54xcmRDTkUgMzMzOzubx+MlJCTo6uoOGjRIUqMk5JPQzIC2tFZSzxawlp6pcoml76xcz4tAABoCH4cPo7AQ3t6N7XZ2YLOxdy+cnTFoEBISsH49MjIAcWGUFuHjj7FzJ6ytERmJVaswfHhj+lVnZ1y8iE8+wdKl4PGwZw8KCsS7MHs2evXC99+DzcbAgaiowJEj4HIxfboYjQRCK2HrbBgXkveiqFrsGmmbd8QAl+7j50s8sDDiEzMrB9EMFN16dQTgtynx+IZEdU3WoLE9zGw6T/a1LnhacWRNvBRjpEgTy/6VMRl3n/v8OHjmdwNyUssDD6bajzcWFPFV2DtOrVLFO9qGWasHAPhzW9KVI2nSk8VKofx57f2oxqhHBx0xK3a5xpApLk0mn14NFz1DTTtXo3D/zCW/OYSfyazn8oUfjTKS6dPiWgaN6yFctVc6Crwywkh/fcZ6W9iN6RF1/ml86LO4kLwHNwtPbEz8LcKD/rYRmijpBeT/HiAQWgkSGSG0R/i3bzOmT8fOnVi5kmpxdHQsKSkBsHr16jVr1qSmplpYWIhtlCRTLgnNDWhLayX1VN5amqZK6qzkwMr1vAgEAO7u+PBDnD+P8+eb1I4xNMTZs/DxwbBhAMBi4YsvsHUrhgzBnTvwEJOhTym0tLBsGebNA5cLJhMzZ2LPnsary5cjIwOHDiEkBAA+/hi//45Zs8S7EBaG2bPx+ecNV/X08PvvTVwjEFobJ0/TuJC8q0fTBfkdBDy8VRh66nFl2WuxkZHuZtoAtHTYnkushNs5tVy2Ois/8+XxDYlWDga/3fAQlPY4sTGxuRw60sTeEh2YfWF3cv8RhpTl68+O9ul/4RefqL4PuwrW8Ip518lAIzulxTYjtAYaWqo+W+3rOPU3/n66b2WM/XhjfSPRP+AL87L0NQD1DqIj6Tyll/OUXtJ10RxD3a4aAPLSyoU71HN51RV1Yk+OiMVtXp/NM8PvXc8P9XtsbKFj49QNgAKS6+uaBMXpPM0WsV8Z5H1lhKHz+tRx6tU7sCYvtZ681Lqey7v8R+ou32j/7fd/uDCmzbwwNNMGkJ38QnjWFeU0lulR4HuAQGg9SJ4RQnuE4eSEJ0+EF+TFxcX8/6ivr6dW1GIbJSGXhOYGtKW1knoqby1NU+USS99ZuZ4X4Z3B1RV8Po4cafh45QoqK5t08PYGnw9394aPAQGNHbS1kZiI169RVwc2u8klT08UF+P+fdy7h9evsWsX7O3B52PLlgYtz5+3mEkA1q7Fq1eIiEBlJU6fRiehIgNMJg4cQE0NIiLw/Dn+/hteXuDz4eoqxgUzM9y+jdevER6O9HQ8f47ly+mOJIHQIrjNs+hq3OH0j/ceRBUIt5eX1OxYEAlg9hrR9TBFT0tdAxOtyAtZlWWvBY0xQTnjNI4d/OZOblo5AMeJJsJ1VW8FZAEQPiAg2NUlXVpz7cV5VT/NuaGtp7b+7GiqxdhCd/EvQ8tLarfMbDzApph3uvoatdXcOk573zmiylb59rhLTVXdT3NuSO/55H4pAOthYkoUy4TmGNo6G+rqq187mSE8blcOp/F4fGtxdW3E4jLNTEuXfflQ2v3IgnFzGv5XIK9kFlulpooryHsK4N71fJE+zbcTtoj9ykDzlRGLzNcnOjB7rNrR0JMZ1CUVFnPi4n4qLAavpTfdSPeizyB9Ywud4GPpAjtrq7mX9j+i7wiB0JaQyAihvWJm9jYZ8BZZ+3b5RSAAbDZY4v50xGTC1hYDBihY91cBM1xcoCnhjDZ1VU9P4lVhF9hsjBoFEhskvBFU2Sprz4xmMBkrRwZtmhF+/a8nUf/LOrExcb7N+byMl3M22PUbKnFZuHS3Y1lRzXLnwOjA7PSEkitH0rZ+GqGrrz7ta1sLO31VNjNgb0rK7aI6Tn3K7aKvXK/kZbzEf2cTWGwVAFcOp4b6ZciUJqKXx+Nv/CSsqpyz6tgI4SMenkus7N2M70X8e+7XB8p4N2hsDwCJYaLLaWHiQ5+5dzz+66IosVdjgnLcOx7fvTRagXtl3i6MjVM3j4WWd8PzrxxJk9Lt6YMXACTVT5EOzTFkMhmf/TwkL+Pl165X7gTnPnlQeu7XB3tX3O5pqTt5qZVMLRRMJmOct0XE2ScAxv4XGZFXcn9nQ2qG3AnOjQnKWTUuuLSgWnC1+cRTTEuLI/OVkY7018fBw8SwV8fD38df/iM1La44MezZFq/r9Vz+yOm9ZUpuWS+W7xtWlFPl63gp8MCjy3+k+jpcLHlWJSxB5vfAusmhVOVjAqG1IfuUCAQCgUAgEN4jbJy6/ZE4+cBXdyL/fkotSgH0tNT1/d1x1AxpC6dhE023XBq7Z9nttZNCqZa+Q7oKohXrz7ru8In0HXYJgAqL4fmF1cKtgxcPufjoTrGDh8kQd2OLD7tEns+KPJ81ckZvVbaKdGnC/PHNndTYYo+FlsIpRShW+7nMs/r7j1WxdmOMetvqKeadg0dPFRbjQWSBlAwR9VxeTVWdpIwk9Vx+TVXd6xoxtXJk3ivzdhG+2OkQE5S7b2XM4HE9uhqLL8obF5LXy7pTT0tdOgKbQ3MM3eb2UWWrHFwVu3pCCAAmk+E6y3zxr0PlOgfhNs/iwu5kO1cj4fNBckmestw6L6M86FBaXEgegBEf9/L93XHLrIadRCITr4nqlrBfYfQMNaW/MtJvl/76MJmMX8ImbJ0dQSXuBaCtp+b7u4P0F7w1vLBz7bEzfMKJjYm7l0Wz1Vnu8/uY9OsksEqmIwC4nHo+yVNOaBMYfH4L76oiEOjAYDTkuyYzkEB4NxC81ATCe4syv9EYDAY/YpHsbiMPRfBld6MJj8d/fPd5VflrU6vOeoZ0i1YAKC2ozk0tMx/YpWMnNRGBWckv+Dy+ma2e2CoedZx6JpOh0jTtpSRpSiKXd78tvhl7Ne+vbC+F1YWcSE+NLRapldNmtwtTWlA9rcefS3c7iuRuUACaY/jv04rnz171HdpV+EhFi0BfMrVhoZdNZx1xJYfFTjwFtLQ4Ml8ZmUh/feo49cm3Crv06CAouNsaSPGisuy1iGEBe5J3L7t9+N4U8wFNCgO10veAMCMZh2h+zYp8mZNly3sCiYwQ3gzkK4ZAIBAIBAFvJDJCEPDv04pPPzi77YqbvZuxArfXVNV95Xpl4dbBA0cZtf3tIpzYmHj1WNrpzBltv84nEERwVT081L3nlkvjBC0LB17Iz6wIejmXZiRo9YSrs9d8aNUSyV9IZIQgHZJnhPB2UFFRcfHixcWLFyclJbV/sW8RZAQIBAKBQOhupv3xCmualUGaU11ZN8HHUuG4hpK3C1NTVXdh18NFPw0hYRFCe2DcHIvowJxNM8JDTqRf3Jey2D4gM6l00U/29DfI3AnOKyuuaVUjCQQKkmeE8HZgbGysoaFRUlIyderU9i/2LYKMAIFAIBAIAOb+MOjzwQHRgdnNs5nIRM9Qc4KPpcKqlbxdmDM/JX04ymi0l3mLSCMQlOSbIyO6mXa87v/kVkAWg8noO6TrlktjFXjFCIQ2gERGCG8HJSUlbDZbTa2FTx62kti3CDICBAKBQCAA0NBSPZk67U1boSwLtgx+0yYQCE34dO2Hn6798E1bQSDIhpymIbwdsNnst0jsWwQZAQKBQCAQCAQCgfCeQyIjBAKBQCAQCAQCgUAgEN5fyGkaAoFAIBAIBIJ40hNKrp3MKMyufF1Tr9lR1drRwOOzvh20W3e/4cvSWrG1V6XzqoKz/8sYlipzyW8ObPUm/8Wt49Qf+OoOk8lY/OtQ4dKtUrw7u+N+bnq5q5e52MSoZ35Kys98OfHzfn0G6cvvn2ztb5YLux4WZlct+c2B/i2CR3ZxX0puWvmyPcNaybakG/+GnMgoK6rh8/gaWqo2Tt0mLLTU0FKVS4jYCXZqy93C7MrPdwwVWzX24a3CkBPpbnP72Dh1U9x6ydoV4+K+lMf3ngNgqTJFSj6X5L868NWdNadHSqpVLOCf048Tw/L5PL71sG7j5nwg8u5Iknb1WHry7ULq398cGdECzhAIbxqyZ4TQHuFxubdXrnyemipoyczMDAsL4/F4CQkJCQkJUnq2B7FyNdKX2RpiJY2A8tYqaSqBQCAQ3iz1XN5Pc298Pjgg8OAjLoen2VE151HZwVWxcyzPpcUVt5LS3LTyeVZ/Z957rsC9HbTZ+j20Ag+m7vKNFrm02zc6YG9K3yFdBes6md4NGNk95HjGj7MjaqrqRKTFheQdXh33LOOlwmGRNzK29EkIfRZ6KoNmZ5FHlhiWH3KC7r3ysntp9MqRQWF/PubW8VRYjLT44n1fxnxqcTYvo1wxa4Xh8/jBR9NvnHsq9kb/7UkhxzOMPtBW3HrlprdYEsPyQ45nvCioLv23Wri9tpq7aXpYxNknPJ60KrOvKji+jpe2fhqRGlv86iVnz7RXinsAACAASURBVLLo+TbnC3MqRbqJlVZZ9vpFQXVcyLPgo+kt5Q6B8GYhkRFCe+ThoUOOv/+evHq1oMXR0XHMmDFcLnf16tVDhgzJyMiQ1LM9iJWrkb7M1hAraQSUt1ZJUwkEAoHwZtnmHXHtZMa4ORaXy+b+fM19c8BYv/TpmwPGVpa9Xu0RUln2ujWUpsUVZz8qU/j2uRvtrBwMgo+mRwdmCxrDz2QGHU5zX9BHuGKLTO/6DNL3Wj2gtKD64Dd3hFXUVNXt8InqoK261n+0wna+kbFtJUQe2cxv+6/zH9UaihLDngXsTXGe0ivo5bxfwyZsuzL+bO6sDWdHlxZU//BJmGLWCuM2rw+TyRAbEiovqYkNzrN369HZQFNxB5Se3mJRYTG2XRm/5dI4QUtJ/qsvRwUlRxfJvHfPstspMUULt9mfTJ225dI4/2wvXj3/e48Q4T6SpE37ynbblfEfjureIl5IIYK/yMnTtLW1EAggkRFC+6T/F1/kRkS4XLwoaCkuLub/R319vYWFhaSe7UGsXI30ZbaGWEkjoLy1SppKIBAIhDdI0o1/w/2f2LsZf3fCRfiogpOn6ZwNduUltQF7koX7S/rTdD2XJ0VLHadeLqukS6NYf3Z0B23VX3yiXhRVA8jPfPnrZzdN+3VavrfxfAdN7+ZtGmTar1PgwdQHUQWCPvu/jHme/2r5Pid9ow5yGS+vdmF4PL5033k8vvTdAVJupDOq9Ok31MDBw0ReLXTsv/7XEwCLdw5V12w87uEyrffI6b2fPHjRfNuIvH51NdYaNLZHcnRR800TYaczeTz+pCVW8qqgaQOd8aEjB8D53x7O63cuL728t21nmbb9c+qxlYOB13cDqBY9Q02frfZZyWV3gnPllUYgvAOQyAihndLTxaXFe7axWPqNchnQSmKV7NwaI0AgEAiEN0XgwVQA3uvE1Nqc7Gv19WHnkTN6A9g0I3ybd0TggUdj1Y6M0zhKrV0BZCW/+Mr1ymiVw66qRyZ39Tu+PkF44ffP6cc+/c+PVjk8Vu3oaJXDK1wuP3lQCmCHT+TvS6IBrJv8zwzTM4L+0qWJ0NVYa+WB4eUltT/Oiqjj1K+dFMrn8TcFjBHOnkDTOyaTsdZ/FJPJ+GnuDU4tF8C96/lBh9NGfNxrzOwP5BnOJtDUTvHwVuFy58AxqkcEvgvCSZtmhG+aEZ4Y9my+zd+jVQ6PUT2ywuVyfuZLAHuX357U5aTICv/I93GTupwsyX8lU7Iwm2aEe/c5K9wS6pcxqctJKlrU/JFt844QfnaK2S8WNQ0WgOwU0T0Xi7bbb708TpAcRMpskTTBBHz0WV8AoSdFt40EH0vTM9Qc6t5TpgqK9ISSL0cFUR2mdDv159Z7krRLfwqS3i8pHFufYOfa41jyJ30GyzjqlRZXwuPxe/dvEvIYMNIQQOI/+fJKIxDeAUgGVgKBQCAQCARCE+Kv5bHVVawcDZpf0tBSneBjSf27ppLz5GlluH/msImmpQXVPS11AKQnlKwcGaStp7Ziv1MnA42HNwv8Nt99cr+U2vB/cV/KLt9oezdjr9UDWWxmWmzxuZ0PvnMPOZvr5eplzufh6vH0jxZZ9rJpWLBJlyaW0V7mMUE54f5Pljtfzn5U9v2pkcYWugp4B6C3rd7sNQP9Nt89teWe9/oPd/hEdTLQWHlwePMb6UNfe3zos+/GXzUw0Vqx30lHXz02ONdv892Htwp3XvcAUFPJyUktj7mc47Go76zVA1NiigL2pnw7/urpxzNGfGJ2YXdy+J+Zs74fSIni8fjBx9J7WXemtrpIlyxMTSXnZWmtcEsdh1dR+ppawDd/ZNWVdRWlr5W0X+y4TVhoeWn/o03Twz2/6Dd0Qk9rp25MJgNAN5OO3Uw6Un2kzxaxE0wYx4kmuvrq4f5PvNfbCRqfPCjNSi4TRLJkTsi0uOJlwwM7G2p++cfwjp3Vbpx7emRNfG01t7l2mU9B7PslnYPxk3ta6srsBkBNU6V5Y1UZB0DJsyp5pREI7wAkMkIgEAgEAoFAaEJVOceS3l+Jc9PKvz7sLLye3+UbrcJi7I/1pJIyOHma6uhrHF4dFxeSZ+9m7L89ybRfp+1Xx1Odnaf04tTWX9idnJFQMnCUUcmzV1ePp9uPN7Zz7UFHmiSrvjrk/PBWYWpssess8+b7O+h7B2DORrubAVn+25MKsysLsiq3Xx2vZGER+tp/XRSlo6++P9ZTV18DgPOUXgY9tY5vSKSKpAAoyKpc++coKn/KaC/zutf1QYfT0hNKbJy6GZlrh/s3RkbuXc8vK6pZuNWepmSaiH1kytsvNrVtb1u9Hy+P+3l+pP/P9/1/vq/CYvQf0d1+XI8x3h8I0n9Iny3SrQXAZDLGz+vj//P9zKTn5gO6UI1Xj6YDGDfXgo4KAHtXxLDVVQQdnKf0Kv33lf/2pLkb7US003kKzd8v6dAPZJjZ6rHVVZJuFPB4fCrGBODWxWwA9Vy+vNIIhHcAcpqGQCAQCAQCgSCKNr31P5PJcJvbmKOqvKQmNbZ42CRT4VyVk32t8F+eCP9sr70xk4Ql6OirA3hVwWkuXKY0SZQV17x6yQGQHl9CHYRRzDsATCZjzZ+j+DyE/Znp+UU/KeEY+tDRnhZXXJRT5TbHglo2U0z7uj+TyYi5nCuwTfjoDbUPpay4BsC4ORZZyWWZSQ1lUEL9HrPVVVxnm9OUrDxK2i+Woe49/342a3PA2HFzLLqZdrwbnn9wVeyMnmeuHkuHErNFmPEL+gC4dvIx9ZHH4//z5+OBI7t3N9Omo4JTy02JKRLpsOrYCL/06SLVc2k+BZH3qwVhMhmfrLTJTStf81HIkwellWWvL+5LOfvLfRUWozXUEQjtH7JnhEAgEAgEAoHQBHVNVsrtQjo91TRZwku+tPgSANf9M2OCckR6VpTWAmAyGYXZlVHns/IyXpY8q0qPL6njSEwaIlOaWHg8/g+fhNVWc0fP7B3u/2TfypiVB5qcf6HvHUVvWz0Hj57RgTmLtg+R3vNBVIH/9iTBx34OBp+uFc0nQlN7YXYlAAu7LiL3amqrCuqbqGmyBH/tByD8b/cFlic2JF47+dh8QJc6Tn24f+bYTy1U2So0JSuPkvZLQoXFdPI0pYqVlBZUh51+fHrrvZ8XRPa01K0sfw35Z4sIxha6Vg4G4f6ZS35zABATlFNR+tpjUV/qqswJ+fBWYXOvjczFnIKh+RRE3q+WxWerfVlxTfDR9DvBeQC09dTWnhm9dtI1NQ0xB20IhHceEhkhEAgEAoFAIDTB1tkwLiTvRVG12DKl27wjBrh0Hz9f4rGLEZ+YWTmI5tHo1qsjAL9Nicc3JKprsgaN7WFm03myr3XB04oja+KlGCNFmlj2r4zJuPvc58fBM78bkJNaHngw1X688bCJpsp4x2AyALDYMtao5c9r70c1Rj066LCb95FLO1PcqphPo1KJnqGmnasRtcIPP5NZz+WLeKSwZLloKS31XF74mUzdrhrCe3b0DDWnf9O/z2D9lSODLh9KdZlmBvlnS3Mm+Fj+vCAyMeyZnWuPq0fTtfXUKMkCpKjg8QBAON2vdNrmKUjhmyMjZqzq/ySplMVWGeJuzOfxObX1wttYCIT3BxIZIRAIBAKBQCA0wcnTNC4k7+rRdEGiCgEPbxWGnnpcWfZabGSEOnSgpcP2bFrilFPLZauz8jNfHt+QaOVg8NsND2r/AoATGxMlmSFdmthbogOzL+xO7j/CkLJ8/dnRPv0v/OIT1fdhV0EkQmHvZOI8pZfzlF7S+9DUrttVA0BeWpNitPVcXnVF3QCX7nSMcZvXZ/PM8HvX80P9Hhtb6Ng4daPa5ZVcX9dkU0/z6jBiUd5+YRhMxvZ5kX2HdG1+mqnf0K4AuJx6BWaLWFxnm+9eGv3P6UwLO/2YoNwpy6wFm1lkqqBKvaTGFlNlbijS4orjQvLGL2iSK6Rlx0cxnjwo5fP45gO6CFIUR/0vC4DtCMO2MYBAaFeQPCMEAoFAIBAIhCa4zbPoatzh9I/3qOKsAspLanYsiAQwe43oqp6ip6WugYlW5IWsyrLXgsaYoJxxGscOfnMnN60cgONEE0FYBMCtgCwAwmdqeDxa0pprL86r+mnODW09tfVnR1Mtxha6i38ZWl5Su2XmdeW9axFoard1NtTVV792MkO4jOuVw2k8Ht9aXF2b5rhMM9PSZV8+lHY/smDcnMZcFXJJZrFVaqq4NVV1gpZ71/Ob6+I1OxGlvP3CMJkMB4+eKTFFgQceiVw689N9ALbDDenPlubWCqPKVhnr/UHk308j/nrC4/GFYxwyVXQ20OxpqRsf+kw4u03A3pSTP9wVhFco7S07Porx05wbGz8JE24598sDbT01B4+ebWMAgdCuIJERAoFAIBAIBEITVNkqa8+MZjAZK0cGbZoRfv2vJ1H/yzqxMXG+zfm8jJdzNtj1Gypx8bZ0t2NZUc1y58DowOz0hJIrR9K2fhqhq68+7WtbCzt9VTYzYG9Kyu2iOk59yu2ir1yv5GW8xH8nCFhsFQBXDqeG+mXIlCail8fjb/wkrKqcs+rYCOGDKp5LrOzdjO9F/Hvu1wfKe6c8NLUzmYzPfh6Sl/Hya9crd4JznzwoPffrg70rbve01J281EqmFkrCOG+LiLNPAIwViozIJbm/syE1sHeCc2OCclaNCy4tqBbu0PyRKaCFDsv2DtPVV//ti1u+jpfO/frg+l9PAvYkr3C5fPKHRCsHA4/P+oLGbJFkrQjj5/WpreYe/j7OysFApD6LTBWLtts/z3+1yu1qfOiz9ISS4+sTQk899lhkqWeoKay9xceHDjFBOe4dj+9eGk199FxilZ9ZscMnMvtRWVpc8Yap/6TEFC3+Zahw4JJAeH8gp2kI7Q4eD7duyT5gaWXF0NMDAC4Xt2+L6d+1K8PMDOymJ3zv3OFzOGCzMXSotCxfVLfOnRnW1nLZ/oa5fZufkYG5c8W7lpOD9HSMHSvxdqpD9+5o7nVmJm7cwLRp0NZuOXMJBAKB0I6xcer2R+LkA1/difz7KbW6BtDTUtf3d8dRQvVEmjNsoumWS2P3LLu9dlIo1dJ3SFdBtGL9WdcdPpG+wy4BUGExPL+wWrh18OIhFx/dKXbwMBnibmzxYZfI81mR57NGzuitylaRLk2YP765kxpb7LHQUjilCMVqP5d5Vn//sSrWboxRb1s9ZbxrEWhqd5vbR5WtcnBV7OoJIQCYTIbrLPPFvw6lfzbEbZ7Fhd3Jdq5G+kYdmrTTljxluXVeRnnQobS4kDwAIz7u5fu745ZZjRtwRB6ZYlro0NVY68j9j4+uiQ89lZESU0Q1amipfrzCZv7mQdSODJmzpfkEE6vL0r5rL+tOWcllzQ9VyVQxbKLphrOj9315Z9W4YAAqLMa0L20+2zG0ufaWHR861HP5NVV1r2sa9rNM8LF8UVh98ofE4KPpAHT11VefdBnr3SqlcAiE9g+Dz2+7HD8EggAGo2H13nwGcjhQU5MtISAAnp4AUFWFjpLzapmYwNsb338PdXUA2LEDq1YBwLVrEmMEYWEYMwYALlzAlCmyLWkn5OXB2hqLFmHHDjFXa2thZ4fcXFRWirl64wZ/6VJGcnLDRyMj/PQTf/bsxghLVRXMzeHqitOnW8N2AoFAeN9hMBj8iEWyu408FMGX3a1l4fH4j+8+ryp/bWrVWc9QTNJQSZQWVOemlpkP7NKxU5Pf6zwePyv5BZ/HN7PVE1uOpI5Tz2QyREpySJKmJAp715ba/31a8fzZq75Du7b4H/NpSqY2+PSy6awjod6w2Ecmrxaa8Hj8gqcVhdmV+j20eljoiJ1C0meLdGtpInNC/vu0ovTf6n5Du4ooaq5d4fFZNzk0Njg39LUP/VtCTqSnxhYLV2uq5/JSbhd10GVTQUO52OYdEXrqcdt/KSnGSMYhml+zIssTKcsWwrsEiYwQ3gx0IiO6utCQnBv72DG4uQFCkRHDpumiOBxUVoLDAQAHB0RFgcUCAEdHxMTAxATJydDSEhVbXQ1LS+TlYdastywKMGECbt9GTo6YbR1cLqZORWAgtLTEREaiovijRzO4XLi5wdoamZm4eBEA9u/H4sWN3fbswbJluHIF7u6t6QaBQCC8l7TnyAiBQGifyBsZqamq+8r1ysKtgweOMmoRA0hkhPAuQfKMENovly7x//0Xkn6osIgwGRlNOjx/jpoa7NwJADEx2LWroZufH9TVkZODNWvEKP32W+TlwcgI+/e3pm8tTUgIgoPxzTdiwiKlpXBzQ2Cg+Bt5PMydy+By8fvvuHoVO3YgIABXrwLA11+jqKix55IlMDHB8uUy8pYRCAQCgUAgENqGei5/m3fEz/Mj6XSurqyb4GPZImGRy3+kbvOOeHirUHZXAuEtgURGCO8yTCZWrsT06QBw5kxDo7k5fvoJAHbvFk1ocusWf+9eAPDz479dCTVWrwabDV9f0fYjR9C3L8LDoa8v/sbgYGRloV8/LF/e2OjmhnnzUF2NP/5obGQysWQJMjObNBIIBAKBQCAQ3ggWdl3s3XpUlNZWlNbS6a9nqDnBx1J2PxrUVNVVlNaa9NUd6i5aR5lAeEshGVgJ7z7u7vyzZxmPhKq8LV+Ov/9GdDQWLmTcv9+QpZXDgbc3A8CXX2LUqMYzq1yujF0STGbDOR0B587xg4MZL19CTQ1DhsDbG3r/ndxMSOAnJTF69hST5YTKcmpmxhfWLkWUgKgoflISY+ZM0Q0jf/3FX7iQAcDXF5MmNSRPEYE6ONP8gIyHB44fR0AA1q9vbJw7F999h927m5yyIRAIBAKBQCC0PZ+u/fBNqZ72le20r0TrQxEIbzVkzwjh3YfDYQCiwQvqTE1aGrZubWhZtw5ZWbC0xI8/Nuk5ezbU1KT9zJ7d2LmgAHZ2mD6dcfIkLl7E2bP48kuYmyO0IX85amuxcCEmTQKXCxE2bcLChUhJYdAUJeDIEQaAjz8W47uHBx4+xJ49YLPFH4ykAkZ2dqJXhw0DgAcPmkSF9PUxfDjS0nDnDjlmSSAQCAQCgUAgEN4RyJ4RwrvPkSMARPdomJnhp5+wYgV+/BFeXuBw8MsvYDJx9mxDFRsBWlpitmmIdKCorYWLCzIyMGIEfvmFP2gQo6oKu3djzRp89BFiYzFgAJycGL16ISsL587xvbwa94ZUV8PfHywWvLzoiqLg8XDhAgCMHClq2IwZjBkzZAzOw4cAoKsrmtedOn3D46G2FppCyfKHDEFkJAICGEOHypBMIBAIhPeB8DOZd6/nizQamevYOHWzceqmjOTEsGcBe1JqXnG7dNdc7dfsl1yb8yCq4Jpfhtd3A+KvPXt87/nnO4YKFyV5UVR9dE08gLk/DBIukUu1Wzt2Gz+/T4uMlcAMI3Odi/tSFLDEyFz7ml/GZF8r8wFdRIRfPZaefLuQEt5cNXVVuEWzI9tmeDcnT1OxBWLk5eK+lNy08mV7hsns2Xqz7o3zsrSWKgBEfzQIBEKLQCIjhPbLhAkMSeV7PT0b4h1S4PFw6xb/118ZsbEAsGQJH2jya1twpmb5crx8CR4PP/wA22YbA48cka2LYudOZGTA1hZhYWCxGAC0tPD99wCwZg1WrMCNGwAwfz7WrYO/P4MKglCcOQMuF56eDVEYmqIA3L3Lr65maGmhUydaRopQWwsA6uqig8NkgskEj4e7d/lOTo2XhgwBgOhoRXQRCAQC4d0jObow+Gi62Esjp/de/9doxcSW5L9aPSFEhcW0czXqYSFmld725GW8DD6aPs7b4nU1N/ho+hD3ns5Tegmu3gv/lxqHfkMNhFM5PIgsCD6abjm4K1porARmGJnrKGYJJcHBw6R5ZCTpxr+hpx5Twpurpq6KNJ7//aGRufbuWxM7Gyhb8zgxLD8xLJ9OLKCVZt2bJTetfMPUf3x3Odi59oA8o0EgEFoEEhkhtF+qqlBVJfFSc6javU1pWNKvXt0kdYgAPz9YWSEkBAAGD26SU0MBzp4FgG++4VOxDAHLlmHdOkRGoqwMnTphzhysW4fgYJSWNu5G8fMDgIUL5RMFIDMTAJydFbSZOtTDFHeujsUCh9NQ9liAmRkAxMcrqI5AIBAI7yTbrrgNde8p+JiXUb59bmTE2Se2w7t5LrFSQGBGYkkdh7d8n1NLJYxsQQaM7A7g4c1C4XhEdGCOsYVO1UtOYli+sM3xoc8ADBHKUtmCY6WYJfHXnsmlRYRdkR/ZOhtS/35Vwfl758OTPyTuXxmz9kxbxyNafNa9WdLiirMflQk+zvy2v/uCPm/QHgLhfYPkGSG0X65dQ2Wl+J8TJ2TfzmLBxAQzZyIigi9IJiKCmRk2bAAAJhN//aWUtTwekpMB4NEjhp8fX/jnf//jUyd0YmIAwNgYI0eCx2vUmJODmzehr99Qipi+KAB5eQygyYEXuaDSr4hNMUs1iuRnsbQEAA5HTJ4UAoFAIBAojC10vz0xAkBcSJ7IpXqutKzmPF5DHis+DwB0uqg370BTgnSl0oVIF9hnkL6GlmpafLFwnztXcgeO6j7ApXv0pWzhW1Jji43Mtbsaa0ECUsZKuhktbokCdNBmz91oZ9qvU9SFrOZX6zj10m+n/xToIGUkm4+ezIkk0zYp3vF4fLHPi+btFP2GGjh4mDSXLNMwOtoJBEJzyJ4RQvtFXZ2vpSXHsdXKysaUH02RJoRa6rNYDbshmuPj01DARRLU0Z7q6oZQwrZtEjXW/ldSzceHHxHBOHUKS5YAwMmTAPDppw17N+QSlZ0NABoa0iyUgro6qqoaktQKw+M1xD4GDRI9ZSMwQMJoEwgEAoEAYwtdAMW5DZs8s5Jf7F0RkxTxL4/H19VXn/h5P+/1H6qwGn6pbJoRrspmWjkY7F4WrcJi9rLunJtWDmDrpxGqaszN/xtr62z48Fbhke/jkqOLBBJmrx2oylYRK+Hb4y63LmYDmODTZ9eS6LyMlyosxgQfy5UHhof6ZRz6Lq60oFpdkzXz2/7e6+0kuRAdmH3o27jctHIVFmP8vD5mNp0Fl4ZO6Bl14SmPx6fya6TcLqqpqhs8zphTWx9x9smDqIIBLt0BvKrgZCWXTfy8r1xjRd+MFrdEMTQ6qnbQYQs+/nP68dkd97OSyyirbIZ3W7rbsbdtY8629ISSP1bF3o8s4PH4nQw0pi6znvX9wOZiL+x66Lf57qjpvZfvc6JpichINp8Vo2b0ljKRNs0IBzDaq/du3+jivFeqbKbHor4LfhzcQZuudzFBOQe/ic1NK2cyGY4TTVw+Mdu9LHr9X6OpAzJSbt/hExlx9imAdZP/0dZT+yvba5t3xP2ogr+yG45ey5z/ACb49Nm3MiYruYyS/M0RZ7GnoggEglhIZIRAkEFVFUpLZXSAUMjA35+vri4+nEEl6QAwbRpj8WLExiIzE+bmOHUKAObNa7gqlyiq5LD0usJSGDgQN2+iulq0nXKZyZS4G0XsARwCgUAgECge3SkC0LNvJwDpCSUrRwZp66mt2O/UyUDj4c0Cv813n9wv3XJpHNW5ppLz5GlluH/msImmpQXVrrPMcx6VXdz/aJz3B+YDuxj21o4Pffbd+KsGJlor9jvp6KvHBuf6bb778FbhzuseYiX0tNSpqeRkpZTduZI7dbm1ab9OwcfSAw+mljx7lRZfMv0rWx199XO/Pji+IdHK0UCwahUmOjB77aRQ8wF6a/8cxePx/bcn3fj7qeCqnatRxNkn92/8O3CUEYCE0GdMJmOIu/GrlxwAiWH5VDwiMSwfwOBxxs3lSxorucxocUsUINQvIzW2eN4PDQGmi/tSdvlG27sZe60eyGIz02KLz+188J17yNlcLyp2kxZXvGx4YGdDzS//GN6xs9qNc0+PrImvreYu2DJYWOzFfSl7V8SMn9eHflgEzUay+ayQPpFqKjmZ919EXXg6f/NgM9vOj+8+P7Yu4fG953tuTaLj3a2L2esmh/a27bz2z1EA/tpx/+cFkZza+joOT+btrl7mfB6uHk//aJFlL5vOAKor6ypKX1M30pn/OanlMZdzPBb1nbV6YEpMUcDelG/HXz39WFYqfgKB8B8kMkIgyODECRkZWKnzJpqaYLHA5aJ7d9lZP1gszJ6N/ftx5gzc3fmZmYwBA2Bt3XBVLlE2NgBQU0PLl+aYm+PmTTx4AE/PJu1UjtXm+WhfvQIAJlO0gg+BQCAQ3mc4tfU1VXXUvwuzK9PiSo6ujQdAbVLY5RutwmLsj/WkknQ6eZrq6GscXh0XF5Jn79awVs9NK//6sLMgL8ati9kX9z+yG9PDydMUwNJhl3T01ffHeurqawBwntLLoKfW8Q2JISfS3eb2ESsBQFFO1do/R432MgfgONHEQ+dETFCuX/o0ameBpX3XeVZ/3wrIFhsZOfDVHQMTrT3Rk9Q1WdTt863/ripvSL41cFR3AI/uFFPxiLiQPJvh3VTZKrr6GuYD9O5cyaXW+UkR/1JxCvpjJZcZyliybnKo5Ocpje8mhKiqMQHw6vmvq7l1HN7UZdaCrTf+25NM+3XafnU89dF5Si9Obf2F3ckZCSWW9l0B7F0Rw1ZXEUwG5ym9Sv995b89ae7Gxs07gQce7fKN9lho+dUhaf8NojOSIrNihukZ6RPpef6rLw8O/+izvgCGuvdkq6kcXBUb9b8sKpOLdO/2LIs2MtfeG+NJPazhU0w/swsQTh0i5faBo4xKnr26ejzdfrxx8wn566IomfO/IKtSMNtHe5nXva4POpyWnlDSZ5C+rEdKIBAAkmeEQJCJujq0tKT9CGIErq4AEBAgussjLw8aGujfHwUFjY2ffsoHEBCAwEAGAG/vJrfQF9W5M/BfHlYFoAIiAQGi7cHBADBhgmg7ld9EX5/sGSEQCARCIxum/uPe8Tj1M9/m/M8LIitKa31/dxjg0r28pCY1tnjYJFPh2iWTfa0AXP/rQ2RV2QAAIABJREFUiaCFyWS4zbUQKzwtrrgop8ptjgW1LKSY9nV/JpMRczlXigQmkzFyRm/q3xpaqhparN62namwCAAjc20ANa/E5M3KTSvPz6wYM/sDaokLoIM2e/z8xphLdzNtw14dMxKfA6gse50WXyII8Qwe2yMzqfRlaS2AlNtFVJyC5ljJa4Yylnw42sh9QR+RH2pMpPPBQD3b4Ya2ww0HuHQf4NJdhcW4uD/l3K8PqKv+2V57YyYJ99fRVwfwqoIDgFPLTYkpEpkMq46N8EufLjhadfmP1N++uOX5RT/pYRGaIyk8K+hMJLa6yoSFjSM8cXE/AFHnn8r0Li2uuDjvlfsCS8HDYquzJn3RT7iz9MGRBP35L5jtAKwcDQCUFSv6pzMC4f2D7BkhEFqM5csREoLduzFuXEMuVQBcLj7/HLW1UFODoWFj56FDGf36ISkJXC6YTMyeraCo4cMB4NEj8HiKRCs8PGBsjKQk7NmDpUsbGm/c4B89ymCxGmvlCMjLAwAXF7kVEQgEAuEdZuoy617/5b9gMhkdO6sNHNWdys6QFl8C4Lp/ZkxQjshdFaW1gn+rabIEa2MRCrMrAVjYNSkxq67J0tRWFf6DfHMJapos6gQHhYoqU79HBxHhfHG5KvMyygGY9mtyvMW0n67wxwEu3cP9MwFQpV7sXI2odrsxRv4/30/8J3/4FNPMpNL5mweJCJcyVgqYobAlk32tqP04wmzzjsjPrGhuiTALtgwW1KYB8KqC871HyIGv71gO1rd1NmQyGYXZlVHns/IyXpY8q0qPLxGcJQHw8FYhmj1K4VwYNVV1Oz+/CSA3/aV0M0BvJIVnBZ2JZOVgIDxnNLRU1TVZ1NEkSosk7yjhIhWmDUyapGSTPjiSoD//hS0X/jeBQKADiYwQ2i8jRkj7Tvf0FLPT4c3i5oZly7B7N8aPx8SJcHFBWRnOnkVGBnR1cfq0aP/58/H110hOhocH9PUVFKWnhwEDkJSE27f5Tk5y/xZkMnHkCMaNw7JlCA3F5Mm4cwfHjzN4POzcCRPRnOiIiAD+29JCIBAIBALFoHE9hOunNmfEJ2ZWDgYijd16daSvgikubiI2rqE8VGUcRtO1pYgB9m49rh5Pz35Udutitq6+uuDMwsBRRiosRlxInpqmCo/Hp067CCNzrOQyQxlLWoQO2uwZq/o/uFkYciLD1tnQb1Pi8Q2J6pqsQWN7mNl0nuxrXfC04siaeKozlRaNrS5tATJr9QAAf25LunIkTXrNZvojKYz0iaSmodL8qgDp3slEmdvbcv4TCO8nJDJCILQku3bBxgabNiEwEIGBDY1jx2LfPpibi3b29saqVeDxGnOvKiZq+nQkJSE0lOEkR5KyRsaOxbVr8PFBUBCCggBATw+bN2PxYtGePB6uXgWLhcmTFVFEIBAIhPeQ7mbaALR02J5LrITbObVc6StkAbpdNQDkpZULN9ZzedUVdc1PoLQI1NaSZxlNNL4oaJKufLCbMYCMhJIHUQWCAywAmEzGUPeeT+6X6uqra+my+w0VjQe1rBltY4l0qNgNj8fPz3x5fEOilYPBbzc8BCd3TmxMFPTs3b8zgNTYYiqRB0VaXHFcSN74BZYANLRUfbba13Hqb/z9dN/KGPvxxvpGott8FIbOREpPfC58tbaaW1vNpSrvSPfO0EwbQHbyCyojCUVRTmO9IZmDo4zZBAJBeUiqAEK7g80Gny/7R7BhREuroUWxIrKenuDz8fp1i9nv44PcXKSn48oVXL2KykpcuyYmLIL/Urfq6YlmP5VX1IIFYLHE7EkRxtmZweejslL81bFjkZuLhw9x5Qpu3uQXF4sJiwC4fh0VFZg1C3p6Yq4SCAQCgdCcnpa6BiZakReyKssaf9fGBOWM0zh28Js7dCTYOhvq6qtfO5lRx6kXNF45nMbj8a0dW2W132eQflfjDmF/ZgprvHYyQ7hPB222xYddrvk9Li2oHtJ054K9m3FW8ou0+BIla8HQMaNtLJHO1aPpAAa4GFK1lh0nmggnNLkVkAWAOjbS2UCzp6VufOgzTm1jepeAvSknf7grfPpDla3y7XGXmqq6n+bcaEE76UyksqKaB1EFQldTATh/bAZAund9BukbW+gEH0sXzPPaau6l/Y8EPWUODkXzaoNtP///z96Zx9WY/XH88zzlSpIlWUrWJmlTk0gisqVMtrEkZF+jsa+Dn2HsDCNbxViTYSSEJlqoVCJJqkmhkiSiJrmu+/z+eK67dbvd226c9+v+ce95znOe7/c533PvPd/ne76HQPg2IZ4RAqFaMDCAoyMcHOT5a06eFASMyM8PUm5T2tqYOxcZGQgNrVRQpYkJHB1ha0uVJY+nJwCsWFGZixAIBALhm2P+Xpu3uR88+gREBDxNuZt3xTv514khTbTVxiwptQWaLGiamrWtR2bquyUDrtwJfP4kIf/szoR9P0W2NWwyYr5x+edXiFnbrDNT3y13uHr/ZvajyNx1o/5+8iBfqo6Fvc69G9k0TVkNlthMxKK/zmce8yAsp+dQpdd6VECMmpFEyMlN9zdPCmFfmybcnPDdmfC/MgyttAdNMjCw1K7HoS/se/QoMvcT9/OjyNzFA65kpr6D2LqPmVu7v87+d5nD1digrJS7eUfX3g068c/QmYZardXFr2Jq22roDMN7N7KveCdXleQKGtK6H//+++Q/afGvz+95eGhZtFnvVmwYSLnaeXj2yn1W5G5zMeBA0qVDj917+udliWJGyj1dlaMC4IrX46DjqRUQm0AgVBKymoZAqGmKi6Gujrt3mU2bKJqGu3sVtLliBby9sXkzVX25UVNT4e+PiRNhKG/NL4FAIBAI0vRybr/x4qDfF0SuGSbYKbZLjxbLjtiJb1AiH4fJnetxVA4ui17pdA0ATVMDXPXn7LRWcD1OBbAf1+kzj79/UdSi/lcA6JtrzdzSw3NRlHid7/vr+u1I6Gyl3ahpffFyPYMmrTs0ysko/L6/bg2IUTOSCIkNyhK+r8eh2xk1dVtnOXaJGU1TWq3V1/oN2D49zL3XRQAqqtTwucYzfrWa08M/6c6rnkPbAejl3H6dX3/PRXeWDQ5k64xZZDpru3XpC83d1TPq8nPPhVFWg9u00KtQYHApyjWkBhr1Ri4w2Tol9DOPoWnK3qXTgt97sYfK1c5yQJtdN5z+WB+3d0EER03VcWrndkZN2YSyipzew1HP4PvmYecyws5liO8yo4jYBAKh8lAMQzL3EGoBihLETH6DFjhuHPz8BO+XLMH27VXT7PbtWLYM0dFM9+7Vko180iRcuoSkJIkddggEAoFQJVAUxYTMLL9av8MhTPnV6iz5OcXPH7/Vt2guNYFXnBfp719n/dvFuoXUVrjVBJ/PpCfkq2ty2GwptUUdEUNB+HwmI/ENw2c6mmnJ2SHlRfr7/BfFRtYtytqTqFqRaUgrna4+CH8ZWDiFjekw7N5CuAWvEDnaFb79KGXYF35P3Lsg0uv+SH3z5uWezvKJ+5mmqbLuSQ3b/3+MftRhBb9mpaYn3/K05ZuCOBoJhJrGwAA0DQ4Hc+dWmVsEwNKluHQJ7u5UTEyVtSkkPh4nTuDUKaZ1a7IJHIFAIBAqiFZrdalFE8qi01GzJr0DNE0J57S1SB0RQ0FomupkVn5CshruSqWuXo+jUlZyUznajWhx3Nqx7caLg4UlgUdSGmjU6yhWv9ybI9/lUbs3jUD4b0M8IwRCTbNhAzZsqJaWw8OrpVkA5uZgGADELUIgEAgEAoEgg8FuBoE+KRvG3eju0KbkX971Y6lp8fke+3rJCZwhEAh1B+IZIRAIBAKBQCAQCN86na1aVCZzx1Jvu1btG930fXL7QgZFU116tNh4cVAv5/ZVJyCBQKhGiGeEQCAQCAQCgUAgfOtMXm9ZyRYmrvl+4prvq0QYAoFQw5BdewkEAoFAIBAIBAKBQCB8uxDPCIFAIBAIBAKBQCAQCIRvF7KahkAgEAgEAoFQQe7fzA4+nfbjT6YdTJpJHbp6JCUx8uX4Fea6+o0r0HJCeM7146lKnf4uv6SxlloFriXn0v6ej/65/3r2dmvxDVnf5Bb7rI4FMPl/3bR1G0qVm9i04qip3LuZLdWsrn5jU9tWpratKi+hgih1Dyuvta6+5vXjqSPcjUvvpFNJYyAQCITqhsSMEAgEAoFAIBAqyLPHBYE+KbnPi0ofig99EeiTkv+iuGItZ6a+U/z058kFU4z/TLv/umLXknPpj8W8QJ+U+yEvxCvcv/Ei0Ccl0Ccl5mqmeHlCWE6gTwrvEz8x4iVbQfzltTJmQe+ADeNuVImQyiqiVOWKac228PJp1RsDgUAgVDfEM0IgEAgEAoFA+LpJjnn1NOltdbRs3k8HwMNbL8ULIwKe6Rk0btqyQVywRGBIbFAWgB6OeuzHzVccQpiZwtfxlDHGPVuG+D3x93xUHaJWIZXRmkAgEL5GiGeEQCAQCAQCgVBzfObx5Rzl8xn5p3/ifq7Cy5V76c7dtBto1EuOfSVe7c6V5xb2OuZ9dSIuPhU/63H0K119zRZ6GjLb1zNosvwPOwAx1zJlVhBHvpp8PiPnRpV7D8utXIVaEwgEwlcByTNCIBAIBAKBQKhe2CUk/cd32use8Srz33oceujMLtM2WTXU5AjrRAQ8Pbw85nlygYoqNWRK546mEolL/j75j9/2BxmJb/l8hqYp096t5u+16WSmBWD79LAQv3QAP4/4W1Or/pmn4wFkJL7Z91NUfMgLPp9poq3mPNto0trvVVRlPxSUf2lrp7bh59PZ6wJ4FJn7oeiT1WA9bsnnEL8nCeE55n11APz7npuR+NZ5dhc590HPoAmAV7IWH5WrJnsPnaZ39lwYlZH4lj261LuPeOYO+YrUltYEAoFQ9yGeEQKBQCAQCARC9fKhkJv24E34+fSpv1h1NGv2z73XR36++8/917/fHsZWiAh4umZYkL651ppT9nw+47s1PvTPdOHp/p6P9rhHdHfQG7/SQpVDJ0e/OrsrYYXjNb/n42maGjBen+Hj6tGUH2YadjBtBiDlbt7Cfpc1ter/tN+2acsGD2/lHP/l3pMH+RsvDi4tm/xLA7AcoBvi9+RB6AsLe10Ad4OyaJrq4aj37zsugLjgbNZHwK4xsRosb1FJ0p1cAG27NJV5VL6aHwq5zx4XRF16NnRmF9eVFo+ici/se7R8yNWT/4xTUJHa0ppAIBDqPsQzQqhb8Pm4fZsB0KoVZWAguw6Xizt3GABdulDa2tJHeTwEBeH1a4bLpTQ0GDMzyshI3hUjI5nUVEyeTFWF+NLk5iIlhWneXJ4MaWkIDcWYMdDUrA4R6gppaUhPh5oaY2NDqZb9xSPsjopZQmIi3rxh2rShOnasBh0UoCbNSSnLef8e8fEMgD59ZMuWmYmMDAaAjg6lry9xqPqUqvIBEhnJ8Hj47juqdesqFBMAcnLwzz+M0BoVkVzmiVISVsnwT00VDARra9mD5eZNJj2dmj5dodby8vD4sShI3tSUaip7BlcREhLw6hWMjSHVQenpyMoSXVT+twTh6+V19r+LDvb+YVYXANaObTn1VQ4uiw7/K6PPyA4ADiy+07Kdxu8Rw9TUVQHYOLebavJnUQGXPdd3a3x7o6Zbrw5hP/YZ2YFb8vn83sTUu3mG3VtY2OvmZf179WhK9yF6lgPaANjjHqGiSu2PHt6spToA2+HtG2s38FoZE3Mts7uD9Bxe/qUBWNjrAEi684r1EcRcyzTt3aoeR6WJdgN9c607V55P22gFID7kBes7EJ7ILfn8oegT+/7l08LkmDyfNbEAyoqwkK8mgJyMwjWn7PuP1wfQf7z+p4+fL3slp9zN69xNWxFFakbrn0cEybwigUAg1GVInhFC3YKmcfw4ZWdHWVkhs4xFuB4esLOj5syhGjWSKM/NxZw5aNAATk5wc6NmzICLC2VsjK5dBXPs0mRmYsgQ6tGjapnHArh+nbGzo1avllenVSusWYO5c6tJhNpn507o6OC77zB4MOzsqAYNMHky8vJk1BTvjopZwvLlsLOjdu6sJlXKoYbNSSnLiYmBnR1lZydbtoQEWFrCzo6aP59qLLmdYrUqVeUDZPBgys6OunKlSqST4MoV2NlRGzcKPioiucwTpSSs/PA/fZrp0gVubpSbG9W5M7Zska7w9i2GDaOuXlW0wRs3GNZU2FdUlKCcy0X9+rJfc+aU3+zu3WjeHF27YuBA6OigSxcEBoqO7twJ8YuWlCgqLeHrgqOm4jTDUPjReY4RgPBz6QCeJxdkp70fOOE7dpYOoKEmZ8hUUWXfp+P3RQ0Tb62xthqAf9/LmPYX5H14HP2q17D2rFuEZYS7MYCbZ55IVS730gB0Omq27tAoNe41gMK3H5Nj84TuFatBbdLi89/llwB4FJnL+g6EJ64b9bdjo6Psa6rpuW3Twt7nl7j/1pONtihNuWrSNNVvXCfhUWOblgDevvqgoCI1o/X3/XUdp3WWeunq/6ef/xAIhK8f8lCGUOfYuxdhYUhLg4sLbt+WPnr6NHPwIKWujgsXoKYmKo+MZIYPp/LyoKoKZ2eYmkJXF9HRCA5GQgJ696Z8fZlx46Rnd7Nng6bx88/VrJJcNDSwejUWLMD48XB0rE1JqoNJk3DiBGgaY8eiXTvk5SEwEMeOITwc0dGQCvmR6o6KWUItUsPmVFWWk5CAAQOQlwcrK1y/DqkAgVofI//tAVJJ7fLyMG0aZWiI4GA0agRnZ6xcCQcHmJuL6mzfjuJibNqkXMvt2mHAAABo21ZQcvs2w+XKdpB9+lROa0uXYscOcDiYOBGmpoiJwblzcHKCjw+mTgWAXr2Yjx8pAD4+yslJqAuwSSgUwbhnS/HKDTTqqamrskszMlMLALQ3kvgCam/URPwqL58Whp/LyEx9l5dVlBKb94lbZl7V5Ng8ADd906IuP5M69D5f2vFW7qVZzPvq3PBNAxB7PQuA5QBdttxyoK7vtgdxf2f3Htk+LT5/6i/dxM8atcCkw5fkHTRNNWpW38JeRzy1ihTlqllfXVX8Hoq/V1CRGtB6hLux7fD2Uk1tnhSSnfZettoEAoFQByCeEUKdQ10df/4JS0tERGDjRqxZIzqUloZZsygABw4wBgZi/wYy4eREFRSgXz+cOiWK054zByUlmDwZfn5wdaXMzCAe+n7tGgIDsWlT7S9jmTcPO3fCwwMODqD/Q4FcwcE4cQLq6ggJYbp3F/TX27ewt0d8PNauxYEDosqlu6MCllCL1IA59e9PXbmCFi0YQKBy5S1H6Bbp2RNXrki7RerIGFFWzRoYRKX7QinEJaxMJ/71F0pKsHix4Etv1SqEhMDHB7//LqiQm4udO+HqCkPZj43LxMIC3t4SJU+fUgBcXXHkiHRl+WLfvcvs2EGpquLWLdH3QEAAhg3D/PkYMwYaGhg/nho/HiCeka+TevVVAHBLZGyk8vEDD0A7Y8E3S/0GKqXrsDB8AKAknSy0WLbU4xvijq6LU1NX7TaoTUfTZiPcTXLS33uvjpUjmN3ojsY9W0oVturQSKqk3EuzdHdoc/VoytOkt7f9nzbRVmNXrwCwsNdVUaVirmXWV1fh8xl2BYqQboPbWDu2hcJUQE1lFVGqcsW0JhAIhK+R/9AkjPAfwtxc8IRz3TrExAgWwpSUYNgwFBXBzQ2TJkn8lru7o6AAZmYIDJRevq6mhtOnYWQEPh9Ll0ocWrkSHA7c3atTE8Wgacybh7Q0HDpU26JUKezMysMDwukQgKZNsXUrAPzxh0Rlmd2hrCXUIjVgTrq6cHREt27iTwsrZTlCt0jv3ggKknaLoM6MEcXVNDUFgObNq12k0n2hIKUlrEwnRkcDgM6XKYmNDQC8eCGqsGULeDysX690y6UJDQWA3r3B4Ui/5OcEOXyYAjBzpsT3gLMzzMxQXIwgko7g66dRs/oAnsTnlz6UkfhWRZVq1LQ++zEl7rX40ZJiXkkxr2FjDgDtNg0BZKUWiFd4k1PMvslOe3d0XZxxz5YBb91+uTBo4YHe9uM6yYkZ0emoCUCjMWf4PGPxl+O0zqX9FPIvLcTKQQ9A6t28hPAc8UwlNE1ZO7Z98iD/4a2XGk04RtbSvhjFUVbNiimiVOUa0JpAIBDqCMQzQqijrFgBOzvw+XB1Faw5nzkTSUkwMsL+/RI109IQEAAAu3czMldV0DTWrWNatkTjxuB/+YMRHs7Ex2PUKOmH4deuwdsb4eGy85JUrKYUd+8y3t7w9sZ7sajSyZNB09i7V1TC44HLlffi8SSa5fNx+jQzaRJGjMC4cdi9W6J9YZ3jx0V1tm+XzveRlgZvb6SmAsCZM8yECRgxApMn49o1iWrh4Yy3N0JDZeh+547oUOvW0NcXzNbEYUtKSsrvDihjCTIR1+j4cWbcOIwYgYULkZwsqJCQgPnzMWIExo/H2bMyNMrPx5YtGDcOo0Zh+XI8e4bsbHh7S8zoKmlOClZjdQkOligsbTkKInSLDBqEoCBoaEhXqBmlSqPgAJEJmzvWykogvyJWypKXB09PsENj1CjMnClt81LI7AsA+fn49VeBtWzYgPxSU0VxCZXVriykQjaE3wyZmdi3DzNnokoSErODyNhY6Q6dOpXx8oKbm/SJrVoBQEmJ0g0S6hrdBrWpx6EvHX6cLzmvjrr87HlygdWgNsIVH29zPySE5wgrXPF6DKDPjx0BdO6m3UKvYfCptE9cUezJ9WOp7JvnyQUAbJzbiSezuH0hA4CU44D9WWlr2KRlO42w8xmFbz+KyzO4wZGDS+9IyS//0kIaanIMvm9+/fg/+TnFPSTdK90d9DIS3yTH5lVyfxbF1ZSJgoooVbkGtCYQCIQ6AllNQ6i7nDoFExOkpWHlSvTsyZw4QXE48PODurpEtYsXAUBLC/b2ZT6/HTOGGjNGosTbmwLw44/SNXfswI0bmDaN6tOnHPEUrynOzZuMkxNVUoJ9+yQmnNra6N0bYWG4c4extqYATJgAPz95TY0dizNnBO/T0uDkhNRU0R3w88PmzQgIELQGICkJw4YhLU2izoYNOHUKzs6CkshIZsYM6rffMHcubtwQ1Tx2DD/+iD//FHwsKKBmzIC+PvXPP9JSLVhAxcbi1CkA2L0bu3fLkJx9+KymJprRldUdLApagkxYjXbtwvTpuHVLpNHBgwgLY+7fp+bOFTlofH2psDB4eopODw7G6NEoEHuotm8fZs/Grl1wdMSgQeXIr6CRKFiN1WX4cEECCJbSlqMIQreIgwMuXgRH1pr3mlFKCsUHiEysrHDtmiBwTEErBXDmDDNtGlUs+azUywt2drh5U/ZSEZl9IWUtf/2F/fsFeTRkSqisdqWxsMDRoygqEny8d48BRDt2/fILAIllaBWGz0dcHGgaNjZUejru3mUAdOyoUNSMtTVlbQ2pZUe5ubh5EwC+/76uhH0RKoyauuq0jVYHl0VPNf1zyJTO31k0Lynm3b+ZHeKX3kCj3qzt1uKV1/3499xdPTuYNH0QlnNoWbRZ71bsxjQAZm2z/sXlxnKHqxPXWHDUVM/uTHjyQOBcNLDUrsehL+x71LVPa4NuzVPvvj6y9m5m6jsADF/gXFPlqAC44vX47cviQZMM5u+1WTMsyKNPwLRNVs11GqbF5x9ceqeJttqYJWalVZBzaXEs7HX8diTQNGU1uI1EeX+dzzzmQVjOqhP9KnMnFVFTPgoqolTl6taaQCAQ6ggkZoRQd9HVxaFDDIDffsPcuRQAT0+YmEhXi40FgH7K/C7z+Th/XvZZ9eqBw0G9euU3onhNIeHhzA8/UCUlOHgQ8+ZJH+3RAwAuXBDMEzQ0oKUl7yV8yF9cDHt7pKaiXz/cvw+GwcuXcHFBXh5GjhTEWeTmom9fpKWhf39Bnaws/PQTioowbBhu3pT4y7VpE+LisG8fXr5EVhbYDTjOnRPtJTF0KLS1kZYmWuHCkpaG2FhoamLMGHmznW3bAMDFRfBRTnewKGgJcti0CcnJ8PHBmzd49Ai9e6OkBOPGUbNnY8kS/PMPXr3CsmUAsH+/4Nk4gOxsjBiBggK4uSErC58/49Ytpn177Nol0XjlzakCtiSOlOWUi3i0yKVLst0itaKUUgNEJvPn49UrwXsFrTQxEa6uVHExduzAmzdgGLx7h127oKqKsDAZOTXKIjsbo0ahoADTpuHFC3z+jL//hpoaNm8uU0JltSvNkCEAsG0b2GF+8CDrVGUApKbCxwfu7tDVVapJ2SQng8eDtjZ++AGdOmHsWGrsWMrKirK0RFKSck3x+fD3h60teDzMnq10AhRC3WTs0q6LDvZuoFHPb0fCRtebO2aE3/B9YtKr5f7o4eI5Phto1Bu5wGTrlNAZFn/tX3THbnTHjRcHC4/aj+u06kS/jMQ3i/pfce918UX6+5lberCHtFqrr/UbwC3hufe6OKi+j4ddQAfjpnvCfgCQdEcwono46hl83zzsXMZmt9BP3M+9nNtvvDiouPDTmmFBs60u7JgRrte5ye7QH8R3q1Hk0uJ8318XQGcrbeH6IBY9gyatOzQSVqgwiqgpHwUVUapydWtNIBAIdQQSM0Ko04wZQ7FbmeTnw8UF06fLqFNYCACNpFOqyePePaa4mNLQkJFYQfG9LRWvyXL7NuPkRBUX49gxRmZ2DHZqFBEh+MguKFAET09kZsLEBEFBggX/LVvi9Gk8fIjERJw7x0yYQG3YgLw89Oghiv/X1cXu3WjQAJs3Y/586tEjUYN5ebh1i7G1FQi5cSMePkRAAM6eFWyfQdNwc8OOHThxgureXXQimzpk0iR5eQd+/RW3bkFdXfQoW053CFHEEuSQn4+wMKZPHwpA06bYuxcWFsjIgLu7IOkJgK1bERSE+HjcuyfI6vrrrygqwo8/ilKi2NpSoaEwNpZYhVR5c1LWlqSQshz5CN0iAB4/RmGh7Nte80opO0Dn3tFeAAAgAElEQVTKRUEr9fQEn49p07B4saCCpiYWLsTjx/Dywu3bihrbjh14/x5Dh4qG7YABuHULBgZQZA9aZbVj0dfHtm1YtgxNm4LDwfv3WLQIfftSADZsAIeDFSuUa7AsEhIYgMrNRWQkpkyBjQ3u3IG/P+7dQ69eiIiQSG4thwkT4OsriNJydxdliiX8B/hhVpcfZnV5k1uc8fBNPY5KF+sW4ktChExc8/24ZV0fReYadm8h3C9WyMAJ3/Ufr5+ekK+uyWFzhfy40JQ9ZDu8vY1zu4zENwyf6Wimxa7QCWFmCs9tqMk5FDfyE/czTVMqqjSAXs7tezm3z88pfv74rb5Fc6mJveKXFtLdQU/8iuKcTneRKvHwtPXwtJVzRZnIV3PzlSFS9QdNMhg0yUBZRZSqrJTWTtMNnabL9neuPN5v5XESXUIgEOouJGaEUNdp3FjwRjytYGnqy/vDI01aGgAoFeRfSSIjmSFDqKIinDole9YHCHIBxCqUgV6CCxcAwMND2h+xZw/j68uwweonTwLA2rXS565ZA1VVJCUhPl5UaGgIoVuExcEBAP79V1QyZQoA+PmJlqIIr1I6oYCYSIIIlKNHGWHuAwW7Q0FLkEm7dmDdIixmX4KpXVwkRGVzQBQXC2qyq5mWL5eoo62NuXMlGq95c5JCKcth3SJTpkBbG5mZmDxZdrUaVqqaBogiVrpqFS5dwrp10ueyzhQuV9FrsdYyf75EoZ4eRo1S6PQKD/+lSxERwUydivHjERbG7NwJAElJOHUKCxeiZUsAyMnB6dPMyZNMQoLS7bPcv0/RNMzMkJqKI0cwfTq8vZGSAnNzFBRIrxiSg74+XFwwdChUVbFvH0aPFi0FIvw3aNZS3XJAG7M+rWW6RVjqcVTM++qUdouw0DSlb96cnaWXPtTJTEvfvLmcfYLrcVRUJDdY0WqtbmGvK98tUu6laxJF1Cy3BcUVqSNaEwgEQq1DPCOEOk1AAPbuFSSkCAvD9u0y6rDugA8flGg2M5MCFMpSUSUkJWHwYKqoCIaG+PHHMv/osFHlpVOrlktcHPBlIieOvT01bhxlZIT37wXJLMVzIrCoq6NXLwBIThbN/0s//m3YkAEkBDMygpUV8vJEQSi3bzPPnsHEpMzUA2vX4qefAODgQYnlNop0hyKWIIeuXSU+CjNHSOU4UFEBviTwy8tDfj5oWoY63bpJfKxhcyqNUpaTl4cZM3DkiCB0IiBAIq+KkJpUqvoGiCJWqqeHoUOhpwcAubkIDMQffzCTJ2PDBgASLhU5cLnIyQGAvn2lDw0apFB2gAoPfwA2NpSnJw4cELn/Vq+GurogCiYoCPr6cHWlJk6kunaV3qJLQbZuxadPiIuDMIkJAC0tHD0KANHRiq6pWb8eJ0/i0iWkpEBPD+fOCb4TCAQCgUAgEGoX4hkh1F0yM+HmBgDr1gkCDVaskAhtYGEfiubmKtHy06cA0KBB5WVUiNRUlJRATw/JyfK2zxRO19nY++nT0by5vBcb5M9uYQPI236CTZfI7q9ZGna5hPizcQVzQ7AP5I8fF3z84w8KkB2DUFKCcePwyy9QVYWvLzNrlsTRcrtDQUuQQ1mNy0yuyfLgAVCGa0BqC6QaNqfSSFmOfBYswOHDAODoiNmzAWDRIpQOJahJpSo2QBREESu9e5dxckL9+mjVCk5OmDKFOnZMiUsAAreIqqqMIaapqdBT34ppJ5P4ePj7Y/lyaGmBx8PkyWjUCI8f4+NHuLhgxw5cvlyRZmlaxio5c3NBwqPEROW2mOnYUbDsSDyDLOG/TWerFlaD2pRfj0AgEAiE2oB4Rgh1FD5fsMtDz55YsQLr18PcXFAo9Tfa3p4BEBoq7+kuj4cWLTBunGCvVnb2ouDT4MqjpoaLF3H6NANg82bpfJClYedIRUXIz5f3Yu+DcEL18WOZDbZqRaFsfdlyOT6Cspg4Eaqq8PMTPOj+80/QNCZMkK6Wnw97e/j5QUsLISHMuHHSE0X53aG4JVQtLVoAZUxTpZ7q17A5yUGRTtyzR/R+924YGIDLxahR0jezJpWq2ABRkHKtNDAQVlZUYCB0deHqih07cOECCgtlLD2TA7uNjszbpew9rMBIlGLRIjRpgkWLACAgADk5gkSnHI4g2IpdT1RVKLWSURw2hI3Px+3bVSgOoe4yeb3l/84PrG0pCAQCgUCQDfGMEOooS5ciOhqamvD1BQCaFuzSmpYmHX3t7EypqqKkBCdPljmh8vFBXh7+/BNaWgBgagoouQCnMjg4wNERtrYU+4jezY2SmbyAzeJB04KQhD/+QGGhvBe7GoKmBbOy6GjpBuPj8fvvuH2bYdNn8Hh49kzGde/fBwANDaXXM2towMUFPB7OnmUuX8b793BwEITwCMnLg60toqLQoQPi4qTTl7DI7w7FLaFqMTGBqqrsm5aVJfGxhs2pNFKWozhqavDzA00jLQ0zJfPr1aRSFRsgClKulbIX/eknpKfj5EksXozhw6GhgfR0Ja7SuDFoGny+DGtRMJytwp0oRWQkExKCpUsFoRxsql0jI8F3o64uVFXx+LHSzc6bh0mTBNFnUrA5sJs0KfMLZN48jBghb7kNh6NcvAmBQCAQCARClUP2piHURYKCBBujHjjAtGsn+MNtYIBduzB7Nnx84OiIkSMFldXVMXcu9u7FmjXUkCESy+BZ8vLwv/8BgIuL4GizZsCXHJM1yfbtuHQJycn4+WfRlihCoqIAQFtb8NBY8QnSoEE4dw63bws2jhHi64tt2zB7NmVrCysrxMbi7FnpLAPx8cjMBE2jd++KaDRpEk6cwOXLgj6aNk3iKI8HJyckJ8PKCleuyOgaFjndoZQlVC00DQcHXL4MHx9BygkhUju51pY5CZGyHKUwN8cvv2D1avj6wsFBlP20VpRSaoAojhwrLS5GZiYALFkifVZ4uBKXoGnY2SEkRMYQYzc/LpfKdKI4S5ZQLVsKAkbwJWJFVVXCbVFcrHSzkZGIj0fbtpRUkp3gYHC50NCQkcNIyMOHuHULXbtKL5W6do2VTSI7MkER+lGHa1sEAoFA+PpgQmTvskQgsBDPCKHOkZsriHWfOBHjx0v8Y541C5cv4/JlTJuGHj2gqysoX78e588jMxM9euDgQQwaJDrl7l3G1ZXKyYG2NthdGwCBFyApCXy+9DwkOBgvXjD6+rCxEV36zBmGy4WBAaytKTk1ZVYTR0MDhw/DyQnbtmHYMEb8EoBghlY6g2O5eHgw585Re/bA2ZkRXjo5Gfv3A8C0aQxALVjATJxIbdgAOzume3dBnfx8uLoCwMSJgmgaZRkwAHp6gs1xtLQwfLjE0Y0bERsLXV15bhGU3R0VsISq5eefmcuXqc2bYWQkWATE48HDQzCJLVd+KGxOiludTEpbjuLnAli1CoGBiIjAnDmUtTUMDJRWSsEBUq5gyg4QBdWUY6WqqoJYj5AQZsIEUSO//y7YQPfTJzkNS7BkCUJCsHEjBg8WbX50+jRz44ZC0/4KD39xbt5koqKoXbtEflUtLQagMjIEH/PzweOJxFOcSZMQH489ezBmjOj07GzBrjTLl4uMpHSnTJqEW7ewcyfGjBFld87OFkTruLvL2+SbUBryz55AIBAIhOqArKYh1DnGjkVeHvT1BRN7KY4cgbY2CgoEU3qWpk1x8yZ0dZGRgcGD0bEjRo/G6NEwNYWVFZWaCi0tBAQwwhB6LS2Ym4PHQ2SkdBT3li1wc6OOHJGYzLi7U25u1IkTlPyaMqtJ4egokNzNjZLKYRESAsjaPqZcbG2pn35CcTF696YmTIC3N+bMgZUVioqwaJFgD44JEyhXVxQVoVcvasIEHDqE+fNhbIykJJiYYPdupS8qZNIkcLngcuHqKjGF5vEESQ2ys9GiBShKxotdNFFWd1TAEqqW7t2pzZvB48HFhfruOzg5QUsL+/cLdvMRKlt5c1Lc6mRS2nIUP5fF1xcaGiguxqhR5XSKTGkVHCCKCKbUAFFczbKslMPBxIkAMGsWtXw5zpxhdu+GrS0WLIC5OfAltaoiODpi2jS8fw8rK8yciQMHMGIEXF0pdi1buVR4+IuzeDGlqyuxc/DAgZSaGry98fYtAGzbBgBDhijd8sKF6NcPRUXo0QMzZ+LIEcyZAyMjZGbCwQGrVolqlu6U6dMxdCiKigR35o8/mPnzBef27InNmyuqLYFAIBAIBELVQTwjhLrF+vUICwNNw9eXYdfJS6GtLcivERaGjRtF5QYGePgQS5ZAWxsZGTh3DufOITERamqYPRuPHkk/VR47FgCCgmohinvPHmhrIy1NsM0KC5+Pq1ehqooRIyrS5u7d2L8f2to4dQozZuDgQdSvj127RGEyAE6exK5d0NLCqVOYPRv79uHdOyxahKgowfY0FYN9aIxSS2mCg5UI2i/dHRW2hKplxQpcuoR+/ZCVhaAgmJri0iXMnCnY60eO/DVGJS2HRU8Phw4xABITBVu9ovaUqo4BUpaVAjh4EG5uKCnBtm1wcaEWLcK7d7h4UWB+0dFK7Hvl7Y3Nm6GmBi8vzJ2LgADMni1jWVBpqqQT/f0RH4/VqyVCMJo2hacnkpOho4O2bbFtGxwdBdtaKcu1a1i2DDQNLy9Mm4aDB8Hn4+efcelS+SuALl7Ezz8DgJcXpkyh9u0Dj4clSxAaWtm8KgQCgUAgEAhVAsUwJPMZoRagKMF0qzos8NkzPH4MPh/NmzPdulEy/7Xn5UFHB3p6iuZZHDECxsblz8AVrFaa4GAMHAg3N8Fsv8IkJuL5c3mKC+toajI2NmXWqWGU7Y7a5fffsWABJk4U7QVbi+ZUluVU2BSFKKWU4permGDVpyZLUZFghxQLC+kswsrC5+P2baa4mOrRQ1GfY5UM/19/RXo6Dh+W4aeIj4eXF/79Fw4OMjaHkuLMGcbFhRo+XLD+SAo+H5GRzPv3lJwvkLI6hb0zRUWUhgZjayv7XPaXobAQMv2h/20oiiIrZQgEAqHWofodlpqeVOu0hVB3IKt7Cf9B2rVDu3bs2zLnANragrytoaFM377lTBWKihAaKuNpc8WqycTTEwBWrKjIueKYmMDEBHIUV7BODaNUd9QYo0fj/Xv88osoMwsLmznSwkJUUovmJNNyKmOKQhRXSvHLVViw6lOTRUMDDg5V0A4AmlY6pWiVDH/xJS1SmJsLLlH5UU/Twh2mZDclp1PE7kxdGeMEAoFAIBAILCRmhFA71AXna04O9PVha4vr18upOXgwPn5EaGjVVCtNaio6d5aIQfgGUbw7aoyFC/Hbb+jfH/7+oifYR45g2jRwOEhNFTrggFoyp7Isp8KmKIWCSil+uYoJVt1q1i51bfjLjxkpl0p2CokZqW0pCAQC4VuHxIx8sxDPCKF2qCNfMdu3Y9kyREdLBwVIkZgII6Py19IrWK00kybh0iUkJaF1a6XP/S+hYHfUGDk5sLRETg7U1TFgAGgaiYlISwNN49QpGasSat6cyrKcCptiaRRRSvHLVUywGlCzFqlrw5/1jNC0IF/JxYvKRdNUrFM8PHDwIABBAmDiGSEQCARCbUE8I98sxDNCqB3qzldMnz4oKUFMTK0JEB8PCwucOsVIbUz7bVLr3SFFfj5+/RUXLuDZM/D50NTEDz9g2bIy9z2tSflrzHJqt1P+2wOkDmoXHs5s3SoSZt26mvBUenoiMFD08fz5bzEzK/GMEAgEQl2AeEa+WYhnhFA7kK8YAoFAIBCEEM8IgUAg1AWIZ+Sb5SuPQiYQCAQCgUAgEAgEAoFAqATEM0IgEAgEAoFAIBAIBALh24V4RggEAoFAIBAIBAKBQCB8uxDPCIFAIBAIBAKBQCAQCIRvF9XaFoBAIBAIBAKBUHE8/R/d/+f19tnWTRvVFxbmvile7RML4H+Tu+lqN5QqtzFpNXVI59M30m7ey5ZqTV+3sa1pK1vTVv9hwcoiPCHn+PXUFePNr8dm1bDk6S/ez9x568Sqfq211BUX+P2/3EX7o+qp0rvn9VTjSPyr5376vPjAHZqmds6xVlVR+lHooUuPAyKfAnCx158w8DvxQx77Ig3bNpnjbFTrQsok8lHu2iN3/TcO0mhQD8CQ5VfnjzB2tG4rXkdmN4mzZGxXw7ZNlL20p/+j5OcFvy/oVeWVq08MAoEghHhGCAQCgUAgEL5iij/yfAJTHHu0Hdmng7Dwxv0XPoEpAKyNWk53MhSWhyXk+ASmWBm2ABCR+JKtU5qx/TqdWdv/vypYWaRmvvMJTJk02KDmJf87Ljsx441SbhEAmg05bbQ1/ncs7hOP773UTvyQ+94Ir8vJp9bYV8Dj8Fd4xtzfbm+b1UNVhXLbEkrT1Pj++uyhO0m5+y48Sj81rtaFLIu41LzYlFesW+TZy8JrMZkLfzSVqiOnm1jG2XeqgGckOC47OC5bQZeEUpWrTwwCgSCEeEYIBAKBQCAQvmL6mesAuPXwpfg0PiDimYFe43dF3OC4bPFpfFBsFgDHHnrCkiubHcSfqKdmFkzeGuYX8qS3Wat5w42/RsHe/8uNf5Jv3K6pVmO1r0XyazGZDt31ZB6Sz/rJlkF3s3wCU5xt2jn3as8Wnr6R5nU5eZpjZ6FHQyl8riY727RbPMYMQNSjV95XkoXtrPKOne3cpV2rRrUuZFlEPcq1t9Bl30cnv6Jpyv57Hak6nh62nh627Hvup8/1B/kMt21/4ZdBlbz0cpeu0xw7V0fl6hODQCAIIXlGCAQCgUAgEL5iunXW1mhQLzb5lbCEz2eu3Hlub6HT11znYsRTPp8RHop+/EpfV1OvhUZZrRnoNfljuR2AazGZX6lgMcmv7Dwu3Xr4UkE5xcWoFcn5fOZy1DNnm3aKiFpaWr+1/TUb1pu+Izz3TTGAtOx3s3beMmrfdJ9HBaMGopNeaWkKlhE1bcSJS81j39+8n30rIWfVeIu6IGRZxKW+Nm7flH0f/fiVQZvGlQ9IKa0OAO6nz1Il1kYth/aU0Ykyb4hSlcs9pEjLvM/8ckuElNZOKUnktFxu4wRCbUFiRggEAoFAIBC+bpys254PT+fzGZqmAEQ+yi368GmwlV4J97NfyJPwhJy+5joA3v/LTcx4O9u5i/zWDPSaAHj+qqj0ofl7Iz585Mk8S2qhRA0LVjECIp4uPxyT/LxAVYWaMqSzacdmtSL5zfvZfAYDLHVlHh234QaA6U6dF3pGJWa8pWmqt2kr76V99HUbsxX0WmgcWNjbdeNN100hgVschq0J4jPMhQ0DpZJ6KE5rLXXhtPcTj9+4IYd9v8or1n2EiXiOlWoVUiljG/Fz0K2EHAD57z/uOZ94MCAJQOGHTwCaDzt2fGU/qVQjijBuww1OPbqnccsFeyNUVeijy/uOs+908u9/tvs9SMx4y9pGb9NWe+fbmHXSAjBpc0j4g5ynZ8YrckOUqnw56tnSg9HJzwtomnK2aTe6b8cFeyPOrO0/wLJNabFltjxvT0Rq5jtVFWq6k+GBhb2PB6WuOByTk1+srqa63KXr2kmW7LlytFNEksSMNz/tiwqJf8HnM9pN1GY7G62d9L3QM5VX8GHpwWjfm2ncT3xVFaq3Weu9821MOjSTVoBAqCWIZ4TwH4fPx+3bDIBWrSgDA9l1uFzcucMA6NKF0taWPsrjISgIr18zXC6locGYmVFGkknH7txhuFxwOLC2puRIwlZr1owyMZEoT0jAq1cwNkbr1krqVueJjGRSUzF5svRtefYMKSnQ0YHUrZBJDfQggLQ0hIZizBhoaiqgWNmkpgoksbaWLe3Nm0x6OjV9ukKt8XiIjJT9TEZHh2rbFhxOBeV8/x7x8QyAPn3kGa24DNbWVFmXY227c2eqZcsy28nLw+PHIl1MTammTZWXWxaVGUE8Hm7fZrhcysYGGpKPe9PTkZUlEtjGhlIlP5iEOswAS12/kCehD16w6wiC7mbRNOXYQ+/dv1wAwXHZ7DQ+OC4bwGCrclZt3EnKBdClrYxR+se11KIPn2SeJdMzUmOCVYCAiKfD1gSZ62udWmPP5zNbfeP/DE2vFcmvxmT2NGqh2VD2l2zhB+7jZwWXop7NHNplpatF1KPcfRceDVl+9Z+TomQf4/vrX4565nvjSR+PS0lP355Y1Y/1xVSMPl1bB8dll3B5NEVFJb1ysm4LIPDO8wdP8i9ulL3kpDqEVMrY+pq31mmunv6i8FpM5oSB+qw/a79/0iCrNvq6mm1keXPKpfADN/1Joe+NNOde7XPyiw3bNvb0f+S+J8Khu97K8RYcVTo6+dWuswmOK6499xtP01Rh8af89x8VvCGKV/a//XTEz0FmnZqdWmMPYPuZB9O2hZVwP3M/yY7LkGr5UcbbK3eee4wyMWrf9EhgysGAx1l5/8Ym5y0ea6bdWG3n2YR1R+NsjFsOsGwjX7tyJbmbktdv4WUtzfr7f7Jt2bTBrYc5vxy/9+BJ/sWNg1lhRvwclPy8YMcc63YtNLLzi9cdvdt7QUDmWVc2KQyBUOuQP3qE/zg0jePHKR8faGoiMRF6sv66eHjg4EHKyAhxcRLlublYvx7e3uDxALATSAqAmRk8PRlbW8GU8tYtatkyALh+HYPKWKMaHIyBAykA58+L3AG7d2PTJuTnCz4aGmLnTjg6VkbdOkRmJoYMoWbOlCgMDWXmz6cSEwUfdXWxZQszYYK8yXkN9CCAVq2wZg1CQ3HypNKaCjl9mpk4keLzBc1u3owVKyQqvH2LYcOoQYOgoGekpAR2dvJuTocOmDcPixcrLWpMjMAgmfLCcoUyvH4NLS3ZdYYOpfLzcewYM2lSmdLeuMG4uIiOXrkCR0dwuWhUxlr1qVNx4EA5slVmBOXkYMEC/PUX2P6iaQwdisOHIXTu7NyJ/ftFAhcWSrtOCIQ6hb2FDoA7Sa/Yafy1mMzepq049VS0mzQw19e6cuf5xmlWAELiX7DTe/FzS7ifhfPPpy8LY5Lz1vjEApAZB1EYOKVuCgbgj2spvM8MgMfP3wL4Oy7r9bsS9pB4WhAhiw/caddSI+L3YepqqgCcbdqZTP2zoIhb85IHx2WPsO0g8xBLRk7hqTX2bD6O8f31P3767HU5+W5KXrfOoqcBhxf3uf3wZfTjV64DpHeTUZa1E78Pis1qP85XVYVuUF9lvZslgJXeMYvHmLVsVmaO2CoXUilj8xhlCmD3uYeRj14eWNgbQPqL9/v9k1ZPsOhjVvFHT8nPC7yW9BHaj/Pq60btm17dOoT9OLJPhxLu573nE++m5nU3bCF1riI3RJHKC36P0NfVjNo3nDXUkb3bW866kPT0rYIqPMstErbsbNOu8dA/Lkc9Tzk+hnVLdTdsYTzlzwu3nw6wbLPVN16+dvIlcd8ToapCRe8fzhrJcNv22o0brPSKYXPoFJfwIhJzl7l0nT9C8D+4cUPOvguPkp69LX3rCIRagXhGCP999u5FWBjS0uDigtu3pY+ePs0cPEipq+PCBaiJZWqLjGSGD6fy8qCqCmdnmJpCVxfR0QgORkICevemfH2ZceMoAEuX4sIFREVh5kwkJsqYPhUXY+pUAHB1xciRgsKlS7FjBzgcTJwIU1PExODcOTg5wcdHUPlrZ/Zs0DR+/llUEh7ODBxI8XhwcICJCdLS4O+PiROpwkLMmSOvqeruQQAaGli9GgsWYPz4Cjqn8vIwbRplaIjgYDRqBGdnrFwJBweYm4vqbN+O4mJs2qR0446O0uEhJSW4eRMZGViyBM+fY8+eishc87RrhwEDAKBtWwCCeA2ZNT/JfkwoojIjKDMTPXogJweGhnB2Bo+HP/9EQAAePMD9+2CDWXr1Yj5+pAD4+CinI4FQK3TU0ezQulFc6msAbws/xibnbZ7RnT00yKrNNt8H+e9KtBqrRT7KZaf34ueOWve3VGucevRv7j3ZmIivSLD5eyPFQwz2+ycJ35f2jCQ/L0jLfr96ggU7xwOg2ZAzdYjh/47F1bDkuW+KE568YSfzZUHT1Lh+nYQfbYxbel1OfvX2g3idV28/sPEssSl5JVxehZfSAGjZTP3xsTGXo57TFByt26qq0GdDnzx9WbhsXFcAR66mBMdlNW1Uf+GPpsLlHjUvpEwiE18K06/eTc2jacrWpFLbPNM0NdlBFAL61He8VBiLdmM1AO//5co8t9wbUm7lmORXma/+3Tyju9BQ1Tiqc4cZue+JUFwFYcsaDeppNFBt36qRMFpHX1cTwL8feOVqJ1+SvIIP0Y9fuQ02EPeduY8wXukVc+bmE4fuepx6NKcefSLon66dtEb2bq/GUR3fX79qk+8SCJWEeEYI/33U1fHnn7C0REQENm7EmjWiQ2lpmDWLAnDgAGNgIJqhZWbCyYkqKEC/fjh1ShSlP2cOSkoweTL8/ODqSpmZgV2Xcfw4TE3x7BlWr5YxR12+HJmZ0NXF/v2Ckrt3mR07KFVV3LrFdO8uuG5AAIYNw/z5GDPmq386fe0aAgOxaZNocQqfj8mTKR4Pv/0GDw9RtSFDsGQJRo6EnIUYNdCDAObNw86d8PCAgwNo5ZO1/fUXSkqweLHgWqtWISQEPj74/XdBhdxc7NwJV1cYynhyWQ7Hj8uI1+By4e4OLy/s3YsZMxRamlTrWFjA21v08elTCoCrK44cka4pvwsqOYJcXZGTAxcXnDwpuND//oeePZGYiJ07sXEjAIwfT40fDxDPCOHroa+5ju+NNADXY7MAUdKKgZa623wf/B2XPbJ3+/i0/F+mdpM6ccEoE9MvS/1pmmrWqL69hU5ZKztO30grK7fipEGyVzzWjGAA8i9OYt/cvP9iyPKrfuv6D/+yDUppUjMLABi1l1jeYtReYnFHzUh+4/4LjQb1bIzL/hUE1OursssZhG1KVeDzmdH/Cy4u4bn07+R748lCzyj5rpZyUVWhh9u2F378+cjdxWPMNBtydp97uMorZvEYswdP8q1mX4j3GiXcp0twdr0AACAASURBVKbKhVTK2Eq4PN5nJjY5b5RdB3Z6H3L/hWHbJsUfeQDUOCoVy8OqXl9V/ESapp6+LDwXnpGa+S4rryg2Ja+sJS1Q4IYoUvnpy0IABm0ai1du11KJv4lSLddToUuvLeIzDMrTTr4kscl5AHxvpl2OeibVeP77EgCqKrTXkj5Ttoa5brxJ01Qvk5Y/2LSbNPA7OVFIBEINQzwjhG8Cc3Ns2oSVK7FuHQYNEkylSkowbBiKiuDmBqlVAO7uKCiAmRkCAyXCEACoqeH0aTx8iKQkLF2KK1cAQF8fW7bgp5+wdy9Gj5ZYpnH7NrNvHwXg+HFGU1NQfvgwBWDmTAgndQCcnWFmhoQEBAWJQku+UlauBIcDd3dRSWAgMjJgZCRyiwBwcMCUKTh6FIcOYe1aeQ1Wdw8CoGnMm4dly3DoUDkxLDKJjgYAnS+PA21sAODFC1GFLVvA42H9eqVbLgsOB4cP49o1ZGbizBnBfP7rIjQUAHr3VjphSmVG0O3bzK1bVLt2OHJE5H/R0MDy5czEidSFC1/lnSQQADh0b3P0akrS07f+t59qN1ETRuzbW+iqqlDXYjLV66vw+Qy7SEScwd3aKJ6cctbOW2WlfijLM1IzggEQBm6oqlAAOKoqUqEc4rAZRmlK4rdDVdIpWzOSB0Q8c1I+OagUC/dH3Ut9vWm61QoX88fPCg4GPB7SXc+5bMeQUhy5mpL/rmTRaDMAW0/HLxxtyq4kajXyxKHLj3+d3r2ahFTK2IauvH7jXjaAXWcf7jr7UFjeyPEogAu/DBJ39FSYDcfj1h2NU1dTHdStjWnHZu4jTNJz3q/2jq18y3WByms32q5jz1I+vg5ffGeTBhkMtGxzLjw9KDbrWkzmrYSX6/+IC9k9lKymIdQRiGeE8K2wYgWuXUNYGFxdqYcPoaaGmTORlAQjI1EoB0taGgICAGD3bkZNTYaDn6axbh2zYAHVuDH4fMHkysMDf/6JiAjMmEE9eCCY6XG5ghn7okWwtxc1NXUq0707ZWbGfEl+IaBVKyQkoKREVM7jgS9v4zPQNNjEkGwO0T59YGCA48eZwEDq40e0b49ZswRBCgkJ8PJCVhYaNMDw4cyYMdKq5eXh7FlER6OwEDQNLS2MHAkHB8HRzExcvw4AgwdLJPt4+xbnz0uUh4cz8fGUi4tENlN/fwAyFqoMHYqjR3HhQjmeEVR/DwKYPBkrVmDv3op4RoQti8P7klM/MxP79mHmTHTsWMGWy8LCApmZeP5cuvzsWSYwkHr3DvXro0cPTJpUZpaQWiQ1FQCMjaUHQrkoPoJK4+dHAZg9W9plNnIk5ewMdfLsivDV4mClB+Bual54Qo5Dd9HXNE1TjtZtHzzJ126i1kSDY20kLzahXHLOT6ibgikL+9g8NatAvDDnTbH4x5qR/Mqd5wcW2lamhYCIp3vPJ9p1bb3K1QKA39r+Xaefn74j/GGXFpV/IM/nMxuOxS0fb67RoB730+fctx/MOgp+TqwMtVMy31WfkEoZ28Zp3ayNWmw6ef/ixkFslMcPq68vGm3az1wHgKVBc8WbKou07Hfrjsb1NG4Zunuo0Om2/o84+WdVko6tNQEkPn0zso8oE82z3CrbnklIudrJl6SjjiaAxhqcecONxZsVXzPF/fS5oZrq/BEm80eY8D7zD1167L4nYqvvg/P/G1jl6hAIFaCy+3sTCF8Rp06hSROkpWHlSpw9y5w4AQ4Hfn7Sc6GLFwFAS0vClyHFmDHUy5c4fVpiJnz8ONTUkJyMX38VlPz8MzIyYGgonVrC2pqaPl3icTeA3FzcvAkA338vKp8wAfXry3tN+PK3ITKSmTEDV66gTx+4uVF+fvD3x2+/wcICMTHMoUOwsMC+ffD3h68vxo6l5s2TEOnMGaZ9e7i748QJ+Pvjr7/g5YUhQ9C3r8A1o6uLw4cxYwZcXCROnD4dM2bgjz9E7hJvbwrAjz9KVEtKAgBLS+mEn716AUBCQjkOIJbq7kFtbfTujeRkwf4ySmFhAQBFX/6r3LvHsA2y/PILAIl1QFUCny9IOtu+vagwJweWlhg7ljp2DP7+8PPDokXQ10dQUBVfvZKwwtM0bGyo9HScPcucPcvcvavQnVd8BJWGje6xthZciMtFcTEAqKtDUxNkAxrC14tmQ873Bs2PX/8nJ7/YsYdEDIJDd73EjDexyXnlbqFSLhoN6pX1ql3BxGneWM3RWq9F0wZy6nTrrK3XouGp4DTup8/CwmPXU2tY8jtJuUUfPvX/XvZ+vYqQ+arIbUuolmZ9v7X92RIDvSY75ljnFZS4bLxZGdlYfr+QWML9PH+EMb4s8eCL5e6up9gSlYoJqZSxWRu1VFdT1W6i5tyrvaN127YtNfh8ZlSfDo7WbR2t21bJko3k5wUAnG3aicciXbidAUDOmppK0q2ztoFe4yOBKW8LBdvNFJfw9l9Mkn9WBShXO/mSGLZt0q6lxvmwDOFRAJejnjUYfGTpwTsAAiKe1h/kcyxIMMRUVeg5zkaqKhSfr/Q/LgKhmiCeEcI3hK4uDh1iAPz2G+bOpQB4esrIzhAbCwD9+indfseO2LIFADZtQmoqEhOxYwdoGn5+0k+npeDz4e8PW1vweJg9WyIPhYYGtLTkvaTyKWzahORk+PjgzRs8eoTevVFSgnHjqNmzsWQJ/vkHr16B3Uln/37BE3sAiYlwdaWKi7FjB968AcPg3Tvs2gVVVYSFCXJA0DROn4a6OiIiRJuGeHvjr7/QpAl8fUW6sCEkUjfw4UMAaNJEesrK+g74fJSUlH+Hq7sHAfToAQAXLigXwgBgyBAA2LZNoMjBgxSACRMYAKmp8PGBuzt0K/7XVwZ8PubNQ3Y2ALAZMQCUlKBvX9y7Bzs7xMYyDIPCQmzahIIC/PAD4uOrUoBKkpwMHg/a2vjhB3TqhLFjqbFjKSsrytJS4EdTHDkjqDQPHgCAtTX1118wNkb9+mjYEI0aYflyhYyQQKjL2Fvo3LiXTdPUYKs24uX9LXR4n5mwBzlDe1Z21cZXIZi5fvMrm4fIz9wBYNss69TMdw7Lr968nx35KHfUur8fPMmXqlPdkl+LyTLr1Ky1VgXn7Xw+M3p9cEER98gyO/HJ/7zhxg7d9ULuv9h5NqEy4nE/fd7q+2Clqzn72F9VhTZs2yQ0/gWAog+fbt5/Ydm5/FiM6hZSSFzq695ftqFJSH+jqkJV7TINSwNtTj1634VHkY9yuZ8+Rz7KHbD4SmrmO0h6i6ocT49ez3KLbNwvHghIOnTpcU93/6y8qo8ZUUQ7+ZLsnW+T+/ZDH4+AgIind1PyvK8kT/w1RLuJ2pIxZgCG9mzXoXWjVV6xhy49jkl+FRyXNX7jTd5nZqxY3lkCoXYhnhHCt8WYMZSbGwDk58PFRfbmqYWFAMrcTFQ+Hh7o1Qs8Hjw8MHMm+HysWwczM3mnTJiAevUwYgTS0uDuLr1Tqbc3Xr+W9xLPZ8nqde4cM3UqmjaFkRH27gWAjAy4u2PrVujrQ1sbW7cKNkxh4xoAeHqCz8e0aVi8WLAxh6YmFi7ElCkARNvB6OsL8okuW4bsbKSlCZKGHDsmChi5d48pLoaGhqAdIeycU01N+q8DTQuiNoTCyKe6e5D1jEQomvFdhL4+tm1DdDSaNkXjxjh1CosWoW9fCsCGDeBwpHfwVYqFCzF9uug1dSrGjUOrVjh4EAA2bxb5AnbtQmoqzMwQHIxu3SgAGhpYtQqbNoHLxU8/VVyGKichgQGQm4vISEyZAi8vTJsGLS3cu4devZRwjsgfQVLw+eByAcDTE6NGITcXzs7o2RNFRdi2DQMGEOcI4euGDT2w6qzdtFF98XIDvSYdWjcSViCCsYyz73RiVb/EjDf9F13p5X4x/cX7LTN7SNWpbsmD47IGdWtTfr0yWHroTvTjVzOGGpbO1nF8ZV/tJmrLDkUnlHL3KM6evxJVVSjhNqsAds6x9glMcVp51XLWXx1bN5rjbCTn9JoRUkjUo1wLfcFKn9D4F5YG2vKTnipLay11v7UDSri8Xu4X6w/ysfMIMO7QNGzPDwDuJL2qwgtJMcCyzY1dTtpN1BbsjVhy4E5fc51ts6yr/CqKaCdfEude7S9uHFRY/GnYmiCr2Rdm7AjvrNckdPcPrDuMpqngHU6mHZvN3nWrxxz/gUsCg+OyfnPvOc6eeEYIdQWKqU4fJ4FQFtSXnGc1b4EeHgJ/gZ2dIAGkFE5OCAzE7NnlTLHKIj0dxsaC+ZWVFWJiyqm/fj3S0vDuHa5dA4+HH3/E0aMV2Zvm+HHGzY1q1w5Pn4oK+XyoqABARARjYyP6fzB6NM6dE+1vmpmJBw/QtatEAhEA3t6C5TOnT4sKR4yAvz8cHZGXh9hYLFggsR3PmTOMiwvl6CjKbMrCdnhYGNOnj/TflPr1weXixg1GzuIXcaq1B+PjYWEBDgcfP5ZfuTSRkcypUxSfDxcXgaZJSTA2xsqVgjVWOTkICWH4fJiZUfJdZgCKiuT5d2gavXph1SpRLhgAXbsiIQEnTjATJkjczKIisElV3rxB06YIDsbAgQBQ7vgTyvD6dZmZSpo3R34+jh1jpPLgisMaxvDhuHBBULJ8OXbsgIkJgoNFy47y8zFgAOLj0aMH7twpRzYWpUYQl4v6X2Y3c+dizx7B8pmYGGboUCovD8uWYetWiVNY0y0s/Op3jCLUcSiKYkJm1rYU3yJ8PpOQnq+pzmETJdQwN+9nG7drWme35/grPEOnubpUIpXk5wWRj3LVOCrs3qu1JVtpguOyTDs0Y29mwpN8mqZMvuwQVIXw+Uxixhs+w5h11Kpaz0tZvC38KOWY+/1C4oK9kfe9RprrV0H+FHHka6egJDn5xY+fv7XQby5VmYX76fPtxJdtmjcU7hxc16D6HZaantTitIVQk9ShrzMCoQYICMDevVBTA5eLsDBs346lS6XrsDOlD7L3my+fjh2xbh1WrgRN48yZ8usLNytJT0ffvjh3Do0bS0eCKE7XrhIfhUk0pDIvsO4SYWoPPT2RTyQ3F3FxePWKCQ2l2KwNUhlAvL0RFYXAQAAwMcH27RJHMzMpQEYaS1XVMrPJsoUK5neo7h5kgy+4XPB4FUk5YWNDsbvSCDOArl4NdXUsXgwAQUEYMQLFxYJDS5ZI372y8PKChgYDgM/HrVvU4cNQU8Ovv0ps9MMeTUwEgKQk6vhx6R9vNTWquBhRUTLy4NYKW7di82bw+RL3WUsLR4/CwgLR0YL0uuVSsRHUowc8PUUfu3en9u5lXFyo/fuxeXNFtm0mEAhfKTRNVfn0UnHsLWonikdBxHNtCjFs28SwbV2c0w6wFEXfmHWqrqzjNE1VX+P/Z+/e42LO/j+Av2YaYyRdJKkkbJt0Qeuy5B4lsWj93MktrUuu67bL0mLXut+vJeSS60pI26YbSWEllWpDhFRSlLQZM78/PvOdpplpmu4T7+ejxz6a8zlzPu/POZ9pfc6ci1zNnX2cure6uG6QOMU7IFmjUQPxUrjVSPHVKRmJga66ggli3AZqKn7bky8W9YyQL0h6OpiJGKtXo7AQa9di+XLY24umlojp6wNAZmblT8Q8XXM4FduIpG1beHlh0CAcPozt20VfULu6inZ1KcuIEaUeAhuVsd5cuU96d+4IV69mBQeL5howD/bG8taV09XFihWYNw8AfvxRyOWW6nNhRqzIhsHjoaAAxcXS3z8IBKINXJipH4rVQguKK6qoqBrGCMTGws8Pv/4KXV3w+ZgyBU2a4O5dtG2LKVOweTP69sXQoeWX4+wMXV1R/Ywfj3HjhIMGsRYsQFJSqXExhYWibqb161HW5iwVnS0irpDMzDLHjHz6BKDCO+9CYi6VpE6doKGBggLExwstLCrwdZzcT5AUcS8MM1NM0ujRrAkTUFCAuDjpO4oQQgipK5MHmR0KSB675ppjt5bvi/hH/0qJTc3ZPb9n7YxYUc1ICKkJ1DNCvhQCAUaNQl4eevTA8uUQCHDpEmJjMWoU7t0r9RBlZyf09GSFhZXaz1UKnw9DQ9jZwcOjnOUeK2TgQFGoN26IpkgUFCBH4dzbgupYhCsgAEOGsAC0aQNbW9jY4KuvMHAgTp3CjBnSmXNzS0Y6rFrFGj681JIizOOx7NgQGxtcvy7aBEQSc3Vsdvm7pdZyC1bLqIFFi6CtjUWLAMDfHxkZWL1adLpNm+Dri+PHleoZkdKnD2vXLsyYgf37YWaGhQulY/b1lb9dMf63kIryxIsHP39e5ggO5iZUV6+2fxg1bFjJG1v2EySFzRZ1u+jLrMzI3IQFBciqwdnihBBCSMV4LenbukUT35BHF248YbNY37ZvfnGdg+yiLV9UJITUBOoZIV+KJUsQHQ1NTdEuKsyWMTY2SE3FggWlhl0MG8bicFBUhOPHy1w34dAhZGfj7FnRiqQVNWcOXr7Eb7+V+ajJ5QqZ7/yPHClnXkC1bDI6cyYALFiAbdtKpT9+LCfznDlIT4eDAzgcBARg1qxSk4asrQF5M1lMTXH9OuLiMGJEqXRmrdNyV9xAbbXg+/eiwhVvJ6SMmzeFoaGs334T9dpkZwOAhYWoZY2MwOHg4cNKFu7qikuX4O+P5csxeLCot0VdXTRrydAQffpUNX4Gmw0jI7x4gSdP5GdISRGN+qnQCCkAc+YgPx/z5gllhwsxa+jK7mQk+V4lP0Gy+vXD5cuiPX2kMANqWtXN3h2EEEKIfCsnfbNy0jd1HQWgSpEQUu1oLjX5IgQFYetWANi3T2hiIko0MxMlHjqEP/8syayujtmzAWDlShbzNCslOxu//goA48aVrBxZIQ8ewM8PZ85IpwcGAgCHA/EypTweNDQU/VT9Ab6wEOnpALB4sfShiAjplJMnhb6+0NSEtze8vKCtjdOncfJkyZIWTZsCQGqq9BuZDhHx6ptizHolQ4aUE2SttWBUFADo6VXDmJHFi1n6+qIBIyhZTqXU47rsIBrl7d8PDQ0UF4uW0WUwgyZkdx1OT0ejRujYERkZFT4RUyazD46s48cBQE9PzvbJit28iWPH4OcnHSozpUtDQ3ReuZT/BMmyswOAY8ek0yMihHw+9PWrcxQYIYQQQgipF6hnhHz+MjMxcSIATJqE8eNLPS/98INoLsP06aW+Q/bwgJER0tPx7bcICipV2p07wl69kJEBPT1s2VLJkFxcAGDLllJbk754IRq74e5ePSNBlMThiHoBQkNLrdm5a5doQMfHj6KU9HTMmcMCsG0bjIxgYCCaVjNnDktce717A0BiovSEmqFDYWyM2NhSYzTCwoSHDoHDKTVn59QpoY+P8NatkmBqswWZTqJ+/WSqqYJCQoRRUVi2rKTrSldXCJSMvMjJAZ+v1GCZshgYYONGAIiKKllthFmTdedOUR8Bg8/HzJkoKkLDhjAwqPCJ3N2FAGJjMWSIqH4YxcXYsgVr1wIQrTtTIcynYMcOxMWVJL54IeroWbasVOeU1F1RoU+Q1HtnzICuLqKjSy1/m5srureZPjVCCCGEEPJFoZ4R8vkbMwbZ2TA1xd69co56e0NPD3l5mDChJFFHByEhMDLCkycYNAht22LUKIwaBWtrdO3KSkmBri78/YWySxUoydUVQ4eioABdu8LNDUeOCOfOhYUF0tPRowezfGbt4XIxaRIA/PADa9kynDol3LYNvXph3jzROpTiUQaTJiEvDw4OJYMUXF0xYECp2tPVRadO4PNx82apfhY2WzThZd48fPcdvL3h5gZ7e5ZAgM2bIR4GAsDdnTV5MuvYsZIekNpswdBQAIpGKyjpxx9ZRkaYO7ckxd6exePBywu5uQBEnRqDB1fpLLNmoUcPAFi6VNQx5OiIefMgEGDwYAwfjm3bsGoVLC0REABtbdH4DkkslvyfOXNK8nTpwmLuyYAAtGoFS0sMGYLOndG4sWic0dChWLmywsEvXIj+/VFQgG+/hZsbvL0xa5boU+DoiJ9/LpVZ6q6o0CdI6r0aGjh5Elwuli5Fv37YsQOrVsHaGvHx6NFD+ryEEEIIIeRLQD0j5DPn4YHwcLDZ8PUVyt2rQk8PR44AQHg41q0rSTczw4MHWLwYenp48gTnzuHcOcTHg8fDzJlISED37lVab/LiRfzyCwB4emLqVNbu3eDzsXgxwsKqYYJMRe3fj8mTUVSEjRsxbhxr0SK8fYuLF0VVFx2NzExs2oTwcNE8GkmHD0NdHeHhJeMvxowBgKAg6fpxcMBff8HYGJcvY/p0eHpCSwt790pvPSulNltQIMDVq+Bw4OxcXpUp5OeH2FisWFFq5IKODvbsQVISDA3RqhU2boSTE1xdq3QiAN7e4HBQUCAaLgFgxw54esLYGP7+WLQIa9ciJQUODrh9G2ZmlTzL8uW4elW0emtiIgIC8M8/4PPRpg22b8elS5UsNjAQS5eCzYanJ6ZPx/79EAjwyy+4dKn82UxV+QQ5OCAyUvjNNwgPx4IFWLsWGRmYORNBQbU6XIsQQgghhKgIllAoLD8XIdWNxRI9lNaLO/DpUzx8CIEAzZoJu3RhVcuuJQyBADduCAsKWBoawl69qrPkSigowI0bAGBjI2fnDuVlZ8PQEMbG8hdwBRAfj2fPoKkptLWVf8nOzrC0LNXNUUVKtmBwMOztMXmyqKul0n7/HY8f4+BBOY/3sbHw9MT793B0FI4dW7O73KWkIDUVbDZ69aqGHYgZxcWIiEBxMdhsWFvDyEjZN546JRw3jjVihJy1ZgQC3LwpfPeOpeCWQBl3hZKfoLLuqPR0PHgANht2dmXuOsz8rcrPr7Y6JEQuFoslDHWr6ygIIeRLx+p/UOrxpH49tpBKo54RUjfoT8znbf587NyJ0FBhv34VfvgvKICxMY4dq8x2tlXk7Aw/Pzx8SGtwVj8FPSPKqMpdUcU7inpGSO2gnhFCCFEF1DPyxaLZNISQ6rd8OdTVsX59ZcZEjByJjh3roFskJQV+fpg0ibpFVFFV7oq6uqMIIYQQQkh9QT0jhJDqZ2AADw8EBSEmpsKd61u2ICSkJoIqx7p10NbGhg11cOovh78/GjZEw4alts5RRlXuisq9d/58UaiEEEIIIeSzRz0jhJAasWQJeveGu3uFh41YWZW/+ma1i43FsWPYs0dYiU1tiTIMDeHkBEdHDByIgQPRtGnFusyqcldU7r1mZqJQnZzg5EQrsxKVtscvwXVTeG7+f5KJmW8KXTeFu24Kf5H9Xjbd+2oygIi4DNdN4bGpr2XL9L6a7LopPPXF2884trIwp0598bZOgn/88t3AH69k5BRWKOZ374tdN4XP2na9qJgvdaj446e5OyPn777J/ySoUJmEEPJFoZ4RQkhNiYhATExdB6GcTp0gFGL8+JpdEvVL1qcP68oViH+6dVP1qp4zB5IB1/6OUYQor/A//qGA5NB7LyUTr917eSgg+VBA8tWYdMn08LiMQwHJH/kCACnpbw8FJKe9KpAtMyz25aGA5JcVfD6vX7GVhTn1y5zCOgn+77sv4p+8MdBVr1DMmo25LfU09vs/dN8RKXXIfWfk7gsJ37ZvzlGjf/YTQkiZ6E8kIYQQQkg91r+TIYDrD15JJvpHPjUz1tLXaRR894VketDt5wCcvjX+7GN79744Ii4j521RpUuok+ADY9Idu1WmEI8pnXtY6h8KSPaPTBMnnryW6nk5abpTu/EDTKsYGCGEfN6oZ4QQQgghpB7r0k5Po1GD20lZ4hSBQHjl1jM7G8N+nQwvRqYJBCXz16IfZpkaaRo3r6XNluowtpikrL7zL0n1ayggGQmj9oMXCISXo54OszVRJqdswKdXDdBs3MB1c0Tmm0IAqS/e/rDlukVrnd3ze1YlKkII+RLQzGlCCCGEkPptSPdW5yMeCwRCNpsF4GZCZsGHj4O6GhcVfzod+igiLqNfJ0MA794Xxz/JnTmsfVXONXdn5If/pBezYHgt6Vu3sVWOf2TasoMxSc/yOGqsqYPbWbdtWlfBh9x7IRBiYGcjuUfHrrkGwHVIu4V7ouKf5LLZrN7WLbyW9DE10mIyGDfX2Lew94R1IRN+Cw34w3H4yiCBUHhhjT2PS//gJ4SQctAfSkIIIYSQ+m1gZ6PToY/C7r+0szECEHTnOZvNcvrW+O37YgDBd18wD/DMBJBBXas04+NIYErBh49yD8ntGanN2CrBPzJt+MqgTqa6J1baCQTCDb6xZ8Me11XwV2PSe1g012zMlXs0/0Pxw6d5l6Keug1t/9MEm6iEzN0XEgYvu/rv8bHiPOMHmF6Oeup77VGf+ZcS03KP/dzfzFi7ilERQsiXgHpGCCGEEELqNzsbQwC3ErOYB/jAmPTe1i24DdT0tBt1MtW9cuvZuuldAYTGvmQe7CXf6/xLUIXOlR8wVWVjA3AkMJn/SQjg4bNcAH/fff76f0uNuA4xl83/475bJvoakbuGq/M4AIbZmlhNO5tXUFwnwQfffeHcq42CDE8y8k+stGMWDRk/wPS/j588LyfdSc7u0k5PnOfgj31uPHgV/TBrwkDTifZfVzQGQgj5MlHPCCGEEEJI/dbWULONQZO7Ka8B5Ob/dzspe/2Mbswhh64tN/rez3lbpKvFu5mQyTzYS753wDdGrVtIr44Rfj8j9cW7+hjb3J03JYe07PVLFP8u2zOS9Cwv9cW7FRNtmG4RAJqNudMGm/969G7tB5/5pjDu0Zt9C3uXdWkA2GzW2P5fiV/aWup7Xk7Kyv0gmScr9wMzpOV2cnZRMZ+m0hBCiDLobyUhhBBCSL3Xr5Oh77VUAH/dfg6UrFVh39loo+/9v++++L5369jUnLXTuki90d3ZckSv1lKJLutDy3qAP3ktlf9JIPeQi4NZ3cYGIOeiC/NLyL2Xg5ddPb16wIie0iWIpaTnAbBorSOZaNG61PSTWgv+2r2XGo0a2FrqlxUtAPWGHGbFE4bk7wyBQDjq1+DCKlMPJAAAIABJREFUIv64AV/5Xnu0cE+U4q4WQgghDOoZIYQQQgip9xy7tTx8NTkxLdfvRpqeNk88vcLOxoijxgqMSVdvqCYQCJnpIVXxw5brZa0zUlbPSK3FBkA8cIOjxgLA5ahJDeWQxOzuwmaV6l/gsEtt3VhrwftHPh3SvVUVC1m4N+qflNe/uXZdPq7Tw6d5+/0fDu5mPKzsviFCCCEM6hkhhBBCCKn3HLsaA7iTkh0Rl+HYrWTBCzab5dS91f1HOXraPG0NbncLRUMSlJFxfqLKxlZRLfUaA0h5nieZmPGmUPJlrQV/5dazfQt7VaUE/8i0nefj+3Y0+HmCDYDTqwZ0dD3vujniQfvm+k3VqxgeIYR83tjlZyGEEEIIIapNszH3G7NmPn/9m5FT6PRtqaEHjt2M45+8uZ2UXS07v2g0alDWT53HJqmZFs+pu3FznUYK8nRpp2fcvPGJ4NTij5/EiUf/Sqn94G8lZhZ8+DjgG/n79SojPatg8h9hupoNT68awKSYGWtvntU9O69o3LqQKoZHCCGfPRozQj5zAgFu3BACaNGCZSZ/kC+Ki3HrlhBA+/YsPT3po3w+goLw+rWwuJiloSHs0IFlYVEqw61bwuJicLno3l16uq9stqZNWVZWFYg/OxsPHwrFL62tWVpaqn5FcXHIyoKlJQwMyrm6mzeFKSmYMkX+WVJTERaG0aOhqSn9Lj4fX3/NKrd8SU+fIjkZDg4lKY8f4/nzkrq1tWVxqukvYkqKqP67d5ffRiEhwsePWa6uSpUmew/o6Ejnkb06ZSQm4vlzWFrCSLl/itdmHRJCKsHOxnDz6Tg2mzWoa0vJ9AE2hvxPwvD7Gcd+7v/lxNbJtNmV9YPLzbbxh+7j1l5zXHZ15SQbHpez5Uzc/Uc5UnlqIfjAmOcdvmpqoFvJkR0CgXCUR3BeQfHFdQ6Sw0PmjLC8HPUsMCZ9y5m4H0d3qGKQhBDyGaMxI+Qzx2bDx4fVty+ra1ekp8vPM38++vZlzZrFatKkVHpmJmbNQqNGGDIEkyezZszAuHEsS0t07Cjqm2Bcv87q25fVowcrqOzt+YKD0aMHq29fVkpKmXnkunZN2LcvS/wTFaXSV7RtG5o1Q8eOsLeHoSHat0dAQJklpKdj8GBWQkKZnS8tWmDlSsyeLZ0+aBCrb1/WlStlliyrqAhOThg5slTili2QrNuiogoUqMDJk8L27TF5MmvyZFa7dvjjD+kMubkYPpx19aqyBcreA1LkXp1i+/bB0BCWlhg0CC1bwtpaUUspOEsN1SEhpHKYEQdd2+npNGkomW5mrN3GoIk4Q51Q2djG2n117Of+8U/eDFh0paf7xccv3/3h9q1UnloIPvjuc4cuLcvPV4YlB25FP8yaMdRcdkkRn5/66Wnzlh6IjpPp8SGEECLGEgqF5ecipLqx/rfaWS3cgYWF6NgRqano2RM3bkgfPXlSOGECS10d9+5B8uv9mzeFI0awsrPB4cDJCdbWMDJCdDSCg/HiBQD4+grHjhVdha0toqJgYoL4eGhI79CHwkKYmyM9HRMm4PjxigV/6pRw3DiWiQkGDgSABQtgZaWiV7RkCTZvBpeLMWNgbY2YGJw7BwCHDmHaNDmXNmQIbt7E06fSQ0Ik7dqFefNw5QqcnEoSmzRBQQE8PaHkmAs+HyNHwt8fGhrIzy9VUSEhLCZCAPn5cq60orKz0aoV2rZFcDCaNMGwYQgNxb176NSpJM/PP2PDBiQkwFx6+0j55N4D5V6dAgsXYvt2ABgwAB07Ijsbp0+juBhbt2LhQvlvqc06JOTLxGKxhKFudR3Fl0sgEMY9ztFU57Y1LPv/STUp5N4LSxMdWg2EkDrH6n9Q6vGkNh9bSB2inhFSN2r5T0xsLDp3hkCAtWuxcmVJemoqbGxQUICjR4UuLiWDF9LT0aED8vLQvz9OnCg1K6SoCFOm4PRpsNl48ADMPJTUVFhbo6gI8+Zhxw7ps8+di927YWSExERFvQByMU/FI0bgwgWVvqI7d4Rdu7I4HERGCrt1E53X3x/Dh0NdHZmZ0g/MgYEYPBi//Yaff1Z0+QIB2rZFgwZIToZ4rwCmZ6SsDhcpOTkYMwbXrgEos++AuRmr5an+wAHMnFkSW3Aw7O3h7o5du0QZMjPRqhXGjIGPj7JllnUPQLmrkxISIhwwgAXgxAnh+PGilkpMRL9+yM7G/fvoIDPaupbrkJAvE/WMEEKIKqCekS8WzaYhX4ROnfDbbwCwejViYkR/1IqKMHw4CgoweTIkOxEAuLsjLw8dOiAgQHqxDB4PJ0/CwgICAZYsESWamoomTezcWWpaCoAbN4S7dwOAj4+wot0i9eiKDh5kAXBzg7hbBMCwYejQAYWFkJ2V89NP4HLh7l7OZbLZmDMHqak4cKAk0doaAJo1K+e9ALy80L49rl2D7GIrNSQ6GgAM/7d1o60tALx8WZLhjz/A58PDoxrOVbmr27WLBWDyZIi7RQBYWGD1alF41XIWQgghhBBC6hHqGSFfiuXL0bcvBAJMmCBaDcHNDYmJsLDA3r2lcqamwt8fALZtE/J4copis7F6tVBfH1paEAhEifPno2dPAJgxg1VcLEosLhb1UCxaBDu7kgdRPh/FxYp++Px6dkXTpgk9PTF5snRXeosWAFBUVCo9IkIYG4uRI6VH0AQGwssLERGlMk+ZAjYbO3eWpJiaAkDXrvKrRezUKeGMGcjOhrs7Tp4sJ3P1Ypf+yypuzfR07N4NNze0bVvVU1T66oKDAeD//k86nUk5f756zkIIIYQQQkg9Qj0j5Aty4gS0tZGaip9+wpkzwmPHwOXi9Gmol57Ve/EiAOjqlnrylzJ6NOvVK5w8WeoZ2McHPB6SkvD776KUX37BkycwNxeN7xCbOBENGyr6mTixnl1R9+4sV9dSA0YAZGYiJAQAvvmmVLqXFwvyHs43b8aMGfDxKZVZTw+9eyMpSbTbC4CuXaGnV/7GNwCGDsWDB9i1C1xuLY1+tLEBgIIC0ct//hECJaMt1q4FUGr2U1VU7uoKCwFAU1P6Lcx+N8XFokVnqngWQgghhBBC6hHqGSFfECMjHDggBLB9O2bPZgHYsweye+jevg0A/Su+AV/btqLJCL/9hpQUxMdj82aw2Th9GlIjNTQ0oKur6EfJxRpU54qkCATw80OvXuDzMXNmqaVGBQLRwATZeBo0AJeLBg2k07/9FgAuXBD1mMydi6ys8oMfO5Z16ZKc2qhRgwcDwMaNYEbx7N/PAjBxohBASgoOHYK7u7Jb5CpW6atjes0KCqT7yLKzRb88eFANZyGEEEIIIaQe4dR1AITUqtGjWQEBOHoUOTkYN07+5ibMApNS+90qaf58nD2LyEjMn4+3byEQ4Ndf5Sxp6eUFL6/KlC9LRa5I0sSJ8PUVzcqRXHyU8c8/wsJCloaGaJCCpLI2smV6RiIjKxN/LTM1xcaNWLoUOjrgcvHuHRYtQr9+LABr1oDLxfLldRyhnR38/aW3+wFw7JjoF/F0KkJILWP1P1jXIRBCCCFfKOoZIV8cLS3RL5LrYspq2LCS5fv4wNISgYEA0LUrVq2qZDnKU7UrMjXFuHF4+xaBgdi9G69e4fDhklEwqakA0KdPBQJgVuVgRr6oviVL0LOn8MQJlkCAceOEffqwACQm4sQJ/PQT9PUBICMDoaFCgQAdOrAUdzNVux9+gL8/9u6FjU1JP1pwMH77DRyOUgvcEEJqAm15QAghhNQhmk1Dviz+/ti5Ezwe2GyEh2PTJjl5OBwA+PChkqdo21a0zQebjVOnKhuo0lTwijw8cPw4Ll1CcjKMjXHuHBYsKDmans4CpFdCUYyZjKPkwrSqwNaWtWcP9u0D0y0CYMUKqKvjxx8BICgIpqaYMIE1aRKrY8eS/YBqh5MTZs4EgBkz0K4dRo1C9+6wt4edHezsAJnlYwkhhBBCCPns0T+ByRckPR2TJwPA6tVYsQIAli9HbKx0NuZb/czMyp+IeZLncMrcgsTVFc2aKfqROylGlupckVxt24omDR0+XLIoaVoaADRqVIFyxM/qzOId9U5sLPz8sGwZdHXB52PKFDRpgocP8d9/GDcOmzfj8uVajWffPmzfDn19pKTg3DmkpmLtWly8iIQEAGjZslaDIYQQQgghpM5Rzwj5UggEGDUKeXno0QPLl8PDA506iRLFD+0MOzshgLAwRQsu8Plo3hxjxyIpqTLBFBQgJ0fRj1RIqn9FZRk4UBTqjRuiFC5XlFIJ9XQ4w6JF0NbGokUA4O+PjAzRqrRcrmiMz/HjtR3S/Pl49Qr5+Xj1Cq9fY+VK8PnIyACbDQuL2g6GEEIIIYSQulU/nzMIqbglSxAdDU1N+PoCEG2woq6O1NRScz0ADBvG4nBQVITjx8uc9X3oELKzcfYsdHUrE8yRI8jPV/Rz5Eg9u6I5c+DsjMTEMjOI93y1tgYqOLXn/XsAYLPL2RBHNd28KQwNxZIlopVWmC1gLCxEtWFkBA4HDx/WakjieUkaGqLxRABCQiAQwMqqvnY/EUIIIYQQUmn0T2DyRQgKwtatALBvn9DERJRoZiZKPHQIf/5ZklldHbNnA8DKlSzxVqaSsrPx668AMG4c9PQqEw+PBw0NRT/ldgGo2hU9eAA/P5w5I53OrNvK4ZSsuNG0KfC/dViVFBUFAHp69fKhffFilr6+aMAI/jdYhsMptWluYWHtxePqioYNsW6ddPqBAwAwZkztRUIIIYQQQoiqEBJSF2rzDnz1SqinJwSEkybJOTp0qBAQamsLnz8vSXzzRmhkJASEbdoI//qrVP7btwVmZkJAqKcnfPVK/hkvXBACQi63GoL39RUAwhEjSiWq4BV5egoBoYaGMCGhJPH5c6GxsRAQLlhQkvj6tRAQcjjCT5+kC/n7b+HRo4LISIFU+v79QkA4ZkyZZy9XeLiACU8uQAgI8/MrX35Zrl0TAMKtW0tSTp8WAMLNm0Uvmdr4/ntFhci9ByQpvjpfX8HRo4KoKFGt/vWXEBAaGAizskryHD0qYG6A168reZaaq0NCvhB1+E9BQgghksr6+1wn/3cgtYZ27SWfvzFjkJ0NU1Ps3SvnqLc3LC2RnY0JExAWJkrU0UFICOzs8OQJBg1Cmzbo3BkAkpIQH88CoKsLf3+hvj5LTok1TwWvyNUVFy/i8mV07YoJE2BrK7x7l+Xjg3fv0KMH1q8vyamri06dEBuLmzeFvXqVOt0ff+DaNdb06bC1LVV4aCjwvyVL6pcff2QZGWHu3JIUe3sWjwcvL0ybBh0dbNwIAIMH12AM7u6snBzMno3u3QHAwQGOjggMhI0Npk2Dnh4CAxEQwOJw4ONTyblUhJBq4SYMresQCCHkS3eQ1b+uQyB1ox6OTSekIjw8EB4ONhu+vkJmoQcpenqiRT3Cw0tNMTAzw4MHWLwYenp48gTnzuHcOcTHg8fDzJlISED37nXTLaKyV3TxIn75BQA8PTF1Kmv3bvD5WLwYYWHSk4OYKRtBQUqdTiDA1avgcODsXJXo6oCfH2JjsWKFaNdkho4O9uxBUhIMDdGqFTZuhJOTslsRVZezZzFjBjIysHYt5s1DQAA6dUJkpNDRsVbDIIQQQgghREWwhDSAk9QFFkv0VFwv7sCnT/HwIQQCNGsm7NKFVZurXZw6JRw3jjViBC5cqM5ia+6KBALcuCEsKGBpaAh79ZJfcnY2DA1hbIzHj8svMDgY9vaYPFmpVWkrh7kZ8/Mht6ep0n7/HY8f4+BBOcujxMbC0xPv38PRUTh2bDk9RFW/B5ydYWkpvbZIUZFouyJraxgbV7JksRqqQ0K+HCwWi8aMEEJInTvI6i/1eFK/HltIpdFsGkLKZ2KC/61yWjfjRKpdzV0Rmy1ebLXMkvX0MHs2du5EWJiwX79yAtizBwCWL6/GGGvJzz+XeahTJ9F11cIdVVCAsDBMny6dzuOBBokQQgghhBACmk1DCKkTy5dDXR3r15fTL5CSAj8/TJoEc/PaieszNHIkOnbE0KF1HQchhBBCCCGqinpGCKkH/P3RsCEaNhRtgvsZMDCAhweCghATo2hc4rp10NbGhg01EsP8+aJarRcqfQ9s2YKQkJqJqb7VISGEEEIIIXLRbBpCVJqhIZycSl42bSr8bGb0LFmCS5fg7s6KiZGfITYWx47hxAmhgUGNXLKZWan9bjiq+uewiveAlVX1hyRWX+qQEFJRqSevvQj5RypRy9SoRS/rFr2s6ySkyknY45eX9KznrnnVXjJTRW3/r6+xYzepQyk+QRkR9223uzfQaFTt562o6qqBBzvOF6S96rFtjuJs2XeSU47+lZ/26tOH/xo0Ude3tWr/w1CuZuMqnp2A6paQGkYrsJK6QUsZEUIIIWKqtgLrjTk7Evf6yT301Zj+A06tquV4Ki3I+ZcXwXen5gdUe8lMFfH0tEclHG6kpy15KNx1U/KhAJfXfjxdrWo/b0VVVw1cHfJTVnTi5NcXy8og4H+KcN2UcvQvFkfNyO4bjnrD3MSnb1PS1Q10HfzWNe9G02Irj+q2NtEKrF8s+oKPEEIIIYTI4XhlfSun7uKXeSnp4VM2PDod2qJ3B8s5I+owMOV1XDau3XSn8vNVVlF23o3Z2+3PetTcKaqopmtALNRl/SPfa2aTB/XcPV88WCbN78a1cWsDh/40JtmnoU6TWgjjs0R1S0gtoHVGCCGEEEJI+bTNjPseWQYgPbDUNEihQCCbWSgQCPifFJSm4KjiN34q/qj8If3uFiZDe8jNLBQI5Eau+JAUDRP9J+fCH50JUyZzuWQvvNJ1KI5fQQ0oeLuCSpbrZVjsI99rxo7d+h1ZLjmHqPWIXp1XTy7KzovfVWrn+XJvD+WbQFa5JVf0XIoLLLeESt/qjGqv25oLuKw/BWWdq6K3GSE1isaMEEIIIYQQpWibGQMoeJYF4NrYNWxuA/0elpHzdrI5av0OL/tqrB2AVzcexPzslRkZLxQIeHraFjOH2aycqMZtwJSQfSc5eumBjPD7QoGgkb6O1byRNj9PYA69iX8StWD3y9BY8Ru/WeXC5qgxRz9k50Uv2Z/qGyIo/sjiqBn07mC7c25TqzaKD4W6rM+IuD8+7RRTyLWxawC0cx0StXBPbvwTFpvdord1H68lWqZGTIanl6Oil+zPS3rGYrNNhtm2HdUvct7OAadWtRzYWW6F9Ng6O8Jty43Z2wz7d5KaUyN2beya1/dSxyT7iFNSfIKiFu1x+HOtQZ8O4pAi5+x4m5LO4qiZuw7pvW9hik9QzPKDhRk5HHVex2XjOq9yEb9dQUXJNsqzgGjJGlDcBP8e//v+ptO58U+EAgFTObY75+p2+KrcG+Phfn8A3/ziInvI0t2Z10yrRZ8OzEsFt4fi1rk5f/e/J/7+/u6BJiYtxIXH/Oz18OCl/7vv1dhIT/H9I/d2Vdzc5RaoIFrF9ay45Jqo2xoNWLZu0/xuKDiXgg8sIXWIekYIIYQQQohSMm8lAtBp3wpAcf6H/MePUn2vtR7WszAjR8u8FYDnQbevDl6uYaLfa+8Cnp7Ws4Dof9b6vLrxYGjIVgBZMUn+veepGzTtfWBRw6ZNHp8Ju73Ci19Y1HXd9Ow7yZf7L2yoq9lr74JG+joZ1x/8s9Yn5/6jQRfXMacOcv4lL+lZ982zNEyaF77IubP6sH/veRPSzzTQaKTg0Mf8wv9y3onjL87/kPfw6dNLUe3dhtr8NCEzKiFh94Wrg5eN/fc4gDS/G0HOvzTt8JXdiZUA7m86FT5946eiYkHZ32zzmmn32rvw2phfI1w3i0OVUpz/oSjnrWSKoPjjfznvmC/Mi/M/5CY8eXblltX8kToWrZO9Ax7u93//PDv7dlKHH8fw9LTitpy5u/qwvq0l87iuuKJkG+Xj6VDJGlDQBAl7/CLddxg7drP5aTyby8mKTorbeibQafn4Z6dZ7HKGmaf/dVuNx9W3tZQ91ECjkbnrEOZ3xbeH4tZpO6pv/M7zqSeuiR/XhQJBsndAU6s2jY30yr1/ZGtGcXMrU6CCaKtyq9dE3dZowLJ1q/hcCj6wim8zQmoU9YwQQgghhBA5PhUVfyz4wPyen/YqOybp9spDANrPHMYk5iU96+O5WPxsBiDCbQtPT2tE9F5mAEWb7/totNK/u/pw8pHAdlMcoxbsVuNxR0TvVddvyhx9/zIndoNvZ48pke47WBw18aHWI3o10tOK+ckzPTDG2LEbv7AoMzK+49JxVnOdmRNxtRon7L6Qm/i0qVXrsg7JXZky/0mG3YmVpuMHADAdP+DTfx+TPC9n30nW69Iuct4uTVOjEVG7Oeo8AK2/732h8w+5iWmKa+mr0f0enw598mdE6slrTLEVVfA0UxySyTDbI1pDn12OGp3sw4zQad7N/Kzl1LQLN5ieEcUVJbdRJClogtgNvjoWrQdf3cDkbPN9n09FxfE7z2ffSSl3jc/ivAK9ruWvA6r49oDC1mnRy1rT1CjVt6Rn5EXIvQ+Zud1+n6FMtcjWzF/DVihobmUKVBBtpW/1mqvbGg1Y9q4r61w6FiYV+sASUmtonRFCCCGEECLH3yNXH27ixPycs54WPn1jUc67HtvdDft1YjKw2Gyz/z10AciKSSp4mmk22VFyXknHxaNZbPazS1H8ouLMqITWw3syz1eMvt5LxyT7/JebnxX9UOqQpbszgEenQgCwuQ3Y3Ab/HgtKPXmNX1QMwHT8gOE3dzfvZq7gkNyLYrHZX43tL37JfBX/ISs3KybpfXqW+XQn5jkZAIfHtZg9XJmK6rV/YUNdzRtzthdmvlEmv4KQGmg04mg0atrhK6ZbBICmqREA/vsPAD5k5ymuKMg0iiQFTcDmqI1P8x0etVsyP09PC0Dxu/fKXAVPV1NxBsW3hzh4ua3DvDSbPCg3/snr2FTm5b8+QWo8runEgcpUC0rXjOLmVr5AudFW5VaXq1rqtkYDlr3ryjpXRT+whNQaGjNCCCGEEELksJo3sqm1aPI/i81u2LSJoZ0NV7OxOANHvaHk4gj5aa8ANOtsJlkIR53XQFM9NzHt1Y0HskeZdQeeBdwCkOob8vRyFEorynkHgM1R6+O5OHzqhpAJ61hstn5PK5PvbL92sVfXb6rgkNyL4qg3lJwbIv6dCV7LrKVkZg0T/XJrCUAjPdGcmutuW8uaE6GAVEjsBmqNW+pJ5REKhACybydBYUVBplEkKWgCACw2Oz/t1ZNzEW9T0gueZ2ffTlYwjUjmEnivbiYozqP49hAHL7d1GObTne6uPvLv0b+adTL9VPwx1fea2SQHNW4DZaoFpWtGcXMrX6DcaKtyq8uqrrqt0YBl77qyzlXRDywhtYZ6RgghREXt2bMnICAAwLJly/r06VPX4ZCaIm7oFStW2Nra1nU4hJRoOaiL5K69SmJz5AxJFgqEEAgAcHjcst7YdlRf/R7Siyk0aSNabtPMxaGlfefH5yKeB91OD4x5dT3urseRoaHbmnczV3CoosFXmnhOTYpPUE2fS3FFKaKwCe6u8bm7+jBHndfSoUtT67ZW7s7vHmfcXuGlTEgGfTqkB8YUZr6R+3wb6rLesF8njkYjKLg9lKBuoGs0sHOq77Ue2+aknrwm5H9qN22w+Gjlq6UMNVTPFS25Nuq2WgMulyp8YAmRRT0jRHXFxMS8fPlSMmXEiBEAioqKAgMDxYk8Hs/RUf6o0djY2BMnTqSkpPD5fC0tLTc3t379+gFYtWrVmjVrcnJyrl+/LpnfzMzMwsJC/DIxMTElJUXq7FVx8+bNrKws8UtDQ8Nu3boB8PPzk8xmY2NjYmICIDU1NT4+nklks9nDhg1TXCCArl27GhkZxcbGpqWlSaabmppaWVlVMX7FVCqYqlCdC0lMTJw8efKIESM4HPl/q1Un1Dr0GVTCDz/8MGPGjH379kldCCH1TqPm2gDyktIlEwX8Tx/fFRr269S041cAsqIftv/hO/HRrJik9MAYgz4dAHC1NCznlPpfLb+oWPy09qn4I6cxz2qus9VcZwH/08MDlyLdd9zf4Gt//lcFh5QPXrOtAYA38Wltvi/piS54mql8Cb32L8y4Hndz/q4WvaylDgk+ltrrNDchTfliSwdpiPIqSgEFTWBkZ3N39WH9HpZDw7aJdzO563FEycBaj+iVHhiTfOiqeBEQsVc3Hvx7LOi/3PwOP45G2beHkidqN9Xx2ri1L0Lu/esTpGVmzFR1JapFcXPXXD0rc6tLqYW6rd6Ay1UtH1hCqh2tM0JUV0FBQXp6uru7u7Oz8++///7unWjMXn5+flRUlLOz86JFi+7cucPn82Xf+/jx48GDB0+dOrVHjx5nz569cuWKt7d3cHDwrl273NzcmP6O4uLid+/eHT582NnZeebMmRkZGVxuqT/xeXl5v//++5gxYy5fvlxUVFT1K3rz5o2fn5+zs/Ps2bOfPn3KRC4QCAoKCnbu3MlcZl5e3qdPn8T5IyMjnZ2dPT09xZcvqbi4OC8vb9y4cc7Ozv/8809BQQGTXlhY+O7duxUrVjg7O//111/v3r2TurSaoFLBVIVKXQiXy+VyuewyNgVQqVDrSr2ohNTU1H79+oWFhck9yuFwuFxuWf1fhNQjBn068PS0U47+9UliFkaS5xWhQKBva6Wu31TbvNXzoNvM4gKMhN0X/vn1qHY7Yw0T/Sfnw//LzRcfeno5yrvRoFtL9gNI84881NAh5ahoOAabo2YxaxiLoyYUCBQcqlDwel3aaZkZJ3sHiGPgFxYl7r2ofAmN9LR77p5fnFfwrPS8AzUuh1/wQbyWLYAXIfcqFJuYtnkrxRWlmIImePf4JQCTYbbibhEATy7cAKDMnBqzqY6NjZvf++14RkScZPqH7Lzw6ZsA2KyYqPj2KPcUjLaj+3G1NZIOXsoIv282eRCTWIlqUdzcNVfP5d7qsmqhbqs3YMWq6wNLSLUoJT5MAAAgAElEQVSjf4cR1WVnZ2dnZ8dms93d3Tt37uziItrIXU9Pr3PnzpMmTfLy8pL7qOPn5zdhwgQ3N7crV66IHyl5PN66detGjRp17ty5/fv3AzAwMHBxcfnuu++aN2/+9u3bGTNmSD2ZdOnSRV1d/e7du9X1PfPQoUObN29+9OjRfv36zZ8/n0lks9kTJ04UCAShoaGzZ8+eMmWKOH+3bt1MTExycnK8vb3lFtivXz8+nz9jxgwrK6s1a9aI021tbW1tbX/77TcOh7Nnz56ynqurl0oFUxX16ELqUag1R5UrISUlxcPDIysrq6CgIDo6Wm43LiGfExab/e3GH8KnbrgycHGn5eMat9R78ffdmJ+9tM1bWc51BtBtg1vQ8JVXHZfa/DyhYVPNp/43/z0W1H7mMHUDXdudc4OGr/TvM7/rb9MbGzbLiU29tWQ/T0+7w+LRAEyG9mjSxuD2z55qXI6uzdfF794ne10R8j99Naa/gkMVjb/nnvkB9osv2rpbzRvJYrMS9l4seJ5doRK+Gt3v8dmwJ+fCJRMN+nRM87sRPMrDcq6zUCBM2HWhMCOnorGJKa6ocpXVBC3tu7C5DRJ2XzDo07FZF7PXd1LurPJ+m5IO5aZjqHEbDDi58urgZZf7L2w7qm/rEb3YXM6buMeJ+/0/ZOZ2Xj1Zv7sFAMW3hzJYbLaZy6D4nedZbLbZZIeqVIvi5q6hei73Vq+ruq3GgBWrxg8sIdWLekaIqps6derSpUuPHDmyadMmDQ0NADdv3gwKCvLx8ZGb/88//xw5cuS8efO2bdsme3Ty5Mnnzp3r3bu3OEVHR8fJycnf3//MmTPjx4+XzOzq6rp58+bqHX7PlPb+vfQy77m5uQBSU1Ol0jdv3rxlyxYFBYaFhfH5/F69ekml5+TkpKSkODo61uYDoUoFUxX16ELqUag1R2UrwdTU1MfHh8Ph+Pj4REdH10kMhNSydlMc1bgNopfuDxzyEwAWm206YWD3LbOYgfeth/UccHr1rUV7AgYtBcDiqFkvGt190w/MIYeL627O2xU0fCVTVPNv2/f1XsqsrcBis4cEbw6d+Pv1mVuZow11NXtsd/9qrB0ABYcqpOXAzkOubb3rcSRy3k4Oj9tumpOOhYm4WCX12rsgI/x+UXaeOMVq/vd5KelJBy+nB8YAaPN/fW23u4dMqPBCrQzFFaXM2+U2AYvNHnh6Vbjrpos93Zl0y9kjuv4+w+/bWVm3Ek2G9ii35Ba9rJ3vHrj1477HZ8MfnQ5lErXNW9lKtIXi20NJZlMd43eeNxrYubFRyTq1lagWxc1dQ/VcuZJroW6rN2AFFH+WCalDLKFQqRWPCKleLBaL+UWZO3DWrFn79+/fvn37/PnzY2NjN2/efPz4cbk5k5KSbGxszMzM7t27J/dZqLCwsFWrVq9fv5ZMZGa4ODo6Xr16VZz4888/9+nTp6wVTCpNIBCoqan17Nnzxo0b4sSCggI7O7vbt2/PmDHj4MGD4vS4uLjw8PC5c+cqKHDNmjWrV68+f/78999/L5l+5syZMWPGrF27duXKldV7CfUlmKpQkQuZM2eOvb294gVuVCTUuqX6leDj4zN58uS///574MCBZeXZs2ePkZFR1dczIvUUi8VyE4bWdRTV6d3jl++fv27evb3k7AzJo4Uvc5p3t5DdRaUwIyf34bNmNqYNdZrIvvFT8cdXN+Ibt2wm3tRWmUNK+i83X+qk8bsu3Jy38/t7ns06mVauTMnwMm8mNLVuw9PVqmJRDMUVVS65TSAUCN7EPxEKhLod2rIq26csFAhe//Pvf3kFTS1bqxvolnV2BbdHVShfLUo2d03Uc6VLroW6rd6AFaj6B7aGHGT1l3o8qdBjC6m/aMwIqQfmz5+/f//+vXv3Dhky5I8//jhy5EhZOd3c3IqKinbs2FHWV8R8Pl/2yWTYsGGamppBQUGZmZn6+voAvL29TUxMKtQtcufOncuXL3t4eCjOxmazORxOQkKp3de2bt06c+bM27dvi5dIYOzevVuyo0SuiIgIAP37Sw9BDA4OBlDLG5qoVDBVUY8upB6FWnOoEghRQZptDZllLCt6VN1At6xHPgBq3AZGdjYVPaQkn+bOrZy6S267m+wd0ECjkW6HtlUplqHGbaD8OqPKUFxR5ZLbBCw2W7fDV1WLCyw2W69Lu0qcvVooXy1KNndN1HOlS66Fuq3egBWo+geWkOr1+Y+yJp8Bc3Pz3r17p6SkzJkzx8vLi8fjyc0WERFx/fp1KysrZgMaudTV1detkx6/ymazx4wZIxAImKEowcHBCQkJP/zwQ4WCfPny5d27d5XJqa6uLrme6+PHjzkczpAhQ1B6ls2ZM2dGjy5nAqdAIAgPD7eystLR0ZE6FBkZyeVyZecX1JxKBJOTk9OyZcvOnTvXVoxKUalaVawehVpzqBIIIdXFbPKgp/6R18auST4SmLDH70K3WTmxqd3+cKv06Amiyqi5CSGSaMwIqR9cXV2vX7+uo6PDLDUiF7PyyKhRoxSUw+FwTE3lDIh1cXHx9PQ8cuTIoEGDjh8/rmBYihQvL69nz555eHhoamoyXTZxcXG//PLLhQsXyhq3Ym1tHRkZKX65bdu2TZs2MYu/intMiouLr1+/vmvXLsVnZ5ZXyM/Pd3YutbwWn89PTExUZnmFNWvW3Lun1Ar5p0+fVry1RyWCefv2bWZm5vv37wUCgeosh6FStVrToX4GqBIIIdWlr9eSJq1bPPINeXLhBovNav5te4eL61oP61nXcZEaQc1NCJFEPSOkHigqKgoICNDT0zt79uyOHTuYCS+ybt++DaBLly6VOEWvXr1MTEzi4+NXr1594sQJ5d/YrVu38+fP29raent7N2nSZMuWLTt27Jg7d66ChzHmm+2ioiIejxcREfHtt98yXSpsNlv8OL1582bx5jUKMIuVbN26VWp5hVOnTl2+fFlyodmyLF26VMn9Msp9gK9EMG3btk1ISGjUqJFKPbuqVK0qVtFQU1JSPD09O3bsOHHixKqcV6VUqBISExNPnjyZk5OTlpY2atSoadOmAcjOzl61alXXrl3T0tLMzc2lVmImhHxRvlk56ZuVk+o6ClJLqLkJIWLUM0JUnUAgmDZt2qpVq8zMzNauXXvgwIFVq1bJzfn48WMAPXooWj49Pj6+rL1mOnfu/PTp0927d5c1W0euDh06XL16NSkp6ccff4yIiLCxsWFmxyh4C1M+8wzm7e0tHp/C4/GY2TQZGRnFxcVyx7ZIYcaeyC6vEBQUBECZSQQVutiaCMbMzKy6AqguKlWrilUo1KCgoLy8vLi4OGtr69oJr3YoXwl8Pv/o0aMbNmwAkJ2d3apVq6ZNm44YMcLNzW3MmDFjx44FYGlpaWVl1aFDh9q7AEIIIYQQUtdU6HtaQuRyc3NbsGCBhYXFjBkz2Gz2wYMHBQKB3JyNGzcW/1euW7du3blzp6yj169fNzMzMzAwqGiE8fHxHh4eBgYG1tbWvr6++/btUzxegInw2bNnBw4ccHd3F6cbGhoys2m2bt26aNGics8rEAhCQkLkLq9w/fr12l9kRHWCqYp6dCEVDdXBwWH06NHq6uq1GGONq1AlhIWFbdy4kekx0dPTc3BwOHHiRHZ2tr+////93/8xefr16+fp6Vlr8RNCCCGEEFVAY0aISps1a9bo0aO7desGwNjYeOjQof7+/n5+flLD5hm9e/c+d+7c48ePzc3N5Zbm5eW1d+9euYdSUlKys7OdnJwqGuGaNWu2bdt29OhRCwsLDw+PXbt2TZkyZcOGDWlpaWWNHNHT0wOQlZUVHx8vuc6rmZlZamrqzZs3W7durampWe6pIyIi+Hy+7IN6ZmZmamqqk5OTMlNUtmzZcv/+/XKzAfD29lYwFqZaglEFKlWrin02dV4VFaqEPn36rFixomPHjsxLPp/fuHHj6OhoHo8nboXOnTuXtSk4IYQQQgj5XFHPCFFdK1eutLe3d3BwEKcsXLjQ399/+/btcntGZs2ade7cOT8/v+XLl8se3bdv3/fff1/Wsg7MUgUV2qaXMXXq1BkzZhgYGAQGBr5//15HR+fixYsREREKHnfbt28PYP369cx312LMFIydO3eeOnVKmVMzO5Xa29tLpYeGhgJQZjkMAN999534QVEByUfH6g0mLi6Ox+OpzpwalapVxaol1OoSHx+vrq7etm3bCqVUXYUqgcvliremyszMDAoKCg0NffbsmeSfBQ6HExcXV40REkIIIYQQ1Uc9I0QVvXv3btGiRYWFhVI77Pbr18/AwOD69etJSUmyA0Ps7OymT5++fv16JycnqWUC/vjjD0NDQwVDQq5evYpKPUwaGxszvxQVFRUWFjK/9+nTR8FbmB6QUaNGGRkZSaY3atQIgJubm5KnDgkJAdC3b1+pdKbD5ZtvvlGmEDMzs2rplahcMCkpKR07djQwMHj58mXVY6gWKlWrilVLqNUiNTXV2tpaW1s7JyeHGaOhTEq1qHQlzJ8//48//ujVq9fx48fV1NQkD3369Km6whPLz88HoOS6vIQQQgghpJZRzwhRLWFhYWvWrLl+/Tqfz+fxeDt27BBv0RIRETFnzpyMjAwANjY2AwcOXLFiRffu3SXf7uXl1bp16549e06bNq1///4cDic5Ofnu3bsLFixgpuRIKS4uHjNmTHZ2NrOI47hx4/T09M6fP1+JyB0dHZV8GNbQ0DAwMJAd2KKurj5s2DA7OzvFb09PT3d3d8/IyGD24hk5ciSza49AIBg5cmRubm54eDiAJUuW7Nmz5/z581UZlVCuKgbTokULExOTnJycwsLCul3/QqVqtd6F2rx5c1NTUyMjI3GXhzIpVVHFSli3bp2DgwOzMY2GhsaHDx/Eh/h8fsuWLaseodjw4cOfP38eGxsL4LvvvuvZs2fbtm29vb2r8RSEEEIIIaSKWEKhsK5jIF8iFovF/FITd2BBQUFwcPCbN2+4XG6HDh1UbZuJFy9evHjxQranJi4uTldXV2ogyZfgyJEjY8eOrbX9XOqROXPm2NvbjxgxohrLdHZ2dnZ2dnFxqcYy65fjx483bdqUGUEWERFhaGjYrl27jx8/Ml02CxcufP78+dmzZ2s/sD179hgZGVVvc5N6hMViuQlD6zoKQgj50h1k9Zd6PKnRxxaiOmjMCPkMaWhoqPLThZGRkdzuD1Xrwak1Dx48mDJlSl1HQb4IAQEBDx48sLe3Dw4OFggEERER69atMzU1DQkJGThwIIDbt2/PnDmzrsMkhBBCCCG16vPfuYAQosqys7Nl91slNcHHx2fKlClhYWEbNmxwc3P7AtcZTUpKGjly5MaNG+3t7e3t7QcNGmRlZQVg27ZtHh4emZmZf/75p5aW1sSJE+s6UkJKJHtfDXfd9Db1hVT669jUcNdNN+bsKMp5W/tRPdhxPmrhnto/b0VlRMTJrT2xStfegx3nI+furGxctaQqzVRW1YVN+SM9MKbKoamK9y+yr41dI+CXWl4qcZ//vd9P1FVIjOfBd/8avvLKwB9DXdbLvqwi2du+Xjfri5B74a6bQib+9mDbuf9y88XpqtCOpH6hnhFCSF1as2bNggUL6jqKL4KLi8uRI0dyc3MTEhIOHjz4BY5RMjc3//Dhg1DC2LFjATg5OV24cOH27duGhoZXrlyp6zAJKeVlWGzyoYDClzmSia9jUy/3X5h6Iri1cy+erlbtR/U86E7KsaDy89W1tynpsrXHyEt6dtZy6ut7qZUr+XnQnZQjgVWLrsZVpZnkVt39TadfRca3dOhSHdHVPX5hUfCYNY9OhwoFAsl0k2E97v56NCOizr4/eP8iO3DITy+C73IaN9Iyayn1sioly73t63Wz3piz48qARVnRD//LeXdr8b5z1tMK0rOYQ3XejqTeoZ4RQkhd2rVrl4aGRl1Hobq2b9/u4uJy69atug7kM6enpzd06FCpFZ1rjY+Pj4uLy7Fjx+rk7KTeyb6TfLn/QiH/k9Nfm1oO7FzX4dRXWTFJuYlpdR1FfVKY+eaux5Gua6exqm9/sWpUmPmmQvnfv8i+bLcoMzJe9lBjIz2red/fmLWtmkKrsOy7KYLij7Y73AddXPfNyklSL6tSsuxtr+LNqtizgFuJe/2sF40e9cB78NUN//fg0Mf3RaGTfmeO1nk7knqn/n0GCCHkCzF//vyVK1e6uLi0adOmrmMhNah79+4uLi7r1q3r2bNnXcdCVF1WTNIV+8UAnP7aZNBHzsgvqXkBUqS+Gxcnyk1XpkBJn4o/Kpmz3JOWe95KXKaShAKB8pesTDAVKk1xHSooqkKVr6AcBVV3f+PphjoaX42V3kGvQqdWJpiK1n9WTFLIxN9OtByt/FsebDt3xmJqXnJ60w5fyc1g6T4iNzHt3+N/Ky5H8d2izH0ovwSBEACvmZb8l/9Tbs0rU5NlNasy5Vfo1BVtVmUk7LqgxuN2W+/KvNSxaG09f2RG+H1x74+S7UgIg1ZgJYQQFWVmZqbkVtCkXqOGJkrKikkKGLSEpcYeErylWSdTyUNv4p9ELdj9MjRWKBDw9LQtZg77ZpULm6PGHL02dg2b20C/h2XkvJ1sjlq/w8vS/G4AaOc6JGrhntz4Jyw2u0Vv6z5eS7RMjZQpUNKH7LzoJftTfUMExR9ZHDWD3h1sd85taiWnP/fa2DWKT1ruecuNKs0/MmbZwbykZyyOWrupg5tat5Vbk+Gumx6fDgXwt/MvDXU1x6edAvDqxoOYn70yI+PFhdusnKjGbaCgRdL8I6MW7Ml/kqHG45q7Dum2fkYDjUYVrcBy6zD7TnL00gMZ4feFAkEjfR2reSNtfp7AHPr3+N/3N53OjX8iFAiY+rTdOVe3jKd9xSEprrpPxR8f7vc3dx2iTMzXxq55fS91TLKPOHOKT1DUoj0Of65luvPEd0LknB1vU9JZHDVz1yG99y1M8QmKWX6wMCOHo87ruGxc51WKtlETCgTJ3lcT9vjlxKY21NW0XvB/THrk3J38D//JfUtfryXML3dWebd06Gq70/3O6iNv4h7J5mxi0qJF7w6Jey9+PdFeblEK7hbZj5vcfoeySghy/uVF8F0AoZN+ZzdsoGPROufev+KXDn+u1W7fSvEnrqyGlr3tZZsVVWjZamlWSeU25fPguyZDe0h+SPW6mQN4GRqrY9EaSrQjIZKoZ4QQQgghRNUx3SLsBpyhIVul+h2Y+TUNdTV77V3QSF8n4/qDf9b65Nx/NOjiOiZDcf6H/MePUn2vtR7WszAjR8u8VXH+h7yHT59eimrvNtTmpwmZUQkJuy9cHbxs7L/HlSlQUpDzL3lJz7pvnqVh0rzwRc6d1Yf9e8+bkH5G3Ecgpvik5Z633KjS/CODhq/U7WRqd2KlUCCI3eD7+GyY3Mo0HT8QAmHy4avmbt81tW4D4HnQ7auDl2uY6Pfau4Cnp/UsIPqftT6vbjwYGrK1rBbhFxX/PXK1zU8Tmn3z9avI+LjNp988ePxd2PaKVqDiOsyKSfLvPU/doGnvA4saNm3y+EzY7RVe/MKiruumJ+zxi3TfYezYzean8WwuJys6KW7rmUCn5eOfnZadGaE4pHKr7tnlKH5hkZF9Z2ViLs7/ILXGp6D4438578RjEIrzP+QmPHl25ZbV/JE6Fq2TvQMe7vd//zw7+3ZShx/H8PS04racubv6sL6tpdz5YvlPXyV5Xknc7/9fzju9ruZ9Dy392sVB3MWTciTwY8EHufUs7hlxvr1f27yV3DxiLR263PnFuyA9S8O4udQhxXeL7MdNtnAFJbT/4Tt1w2aJe/2+dhnUzMZUjcfNjEoUv9T8ykDxJ05BQ8ve9rLNWpWWrUSzfir+mBP7qNk3X0t1GjI9fYqbsvjdeyH/U0NdTcl0/R6WAF7f+1eZdiRECvWMEEIIIYSotOzbSf+sO1acV8BR57G50v94i3TfweKojYjeq67fFEDrEb0a6WnF/OSZHhhj7NiNyZOX9KyP52LJL4fzn2TYnVhpOn4AANPxAz799zHJ83L2nWS9Lu2UKZDBLyzKjIzvuHSc1VxnJoWr1Thh94XcxKfNu5nLXoiCk5Z7IeVGdevHfRom+sMjd3HUeQBMhtmetZpWnFcgG4aRnc3759nJh68aD+7GPKRFuG3h6WmNiN7bSE8bQJvv+2i00r+7+nDykcB2UxzlNoqQ/6n3/kXtf/iOCYar1fjOL97PAm61cuqufAWWW4dRC3ar8bjiotp83+f9y5zYDb6dPabEbvDVsWg9+OoG5l1tvu/zqag4fuf57DspspWvOKRyq+7533cBGP3vgbai7S6r4Gmm+E4wGWZ7RGvos8tRo5N9tM2MATTvZn7WcmrahRuyPSN/j/JI+/M6i6NmNnmQxezhUoOnAEzNDyj37OV2iwBo2qEtgMzIeA2ZER/l3i2yH7cKlfCpqDhxr19L+86tR/QC0ECjkfhluTWvuKGlbnupZkWVW1b5ZhXwP11325Jy9C+hQMDiqBk7drOaP7LlwM78ouLY3080796+lVN3xU2ZfScFgFpDrmQipzEPgKCYL05R0I6ESKF1RgghhBBCVNqtxfsaNFHvtXchv7Do75GrJef/f8jOy4p+2Hp4T+ZBiGHp7gzg0akQcQqLzTYr/YTPYrO/Gttf/FLf1hLAh6xcJQtksLkN2NwG/x4LSj15jV9UDMB0/IDhN3eX9RBV1knLvZByo8pLevYu9cXXE+2ZZ3sAXM3G5tMGyw1DSlZMUsHTTLPJjsxjKqPj4tEsNvvZpaiy3qXG45rPKHn0tZwzAsDjM2EVqkAorEN+UXFmVIJUUX29l45J9mFz1Man+Q6P2i1ZFE9PC0Dxu/dSp1AckjJV9/55Nkedx+Fxy425rOqSInknNNBoxNFo1LTDV8zzMwBNUyMA/Pdyxgs89b8pFAg6LRvXbb2rbLdINWKmY2RFP5RKV+Zukf24VbSEsiiu+Yree1LNWm755VK+WTNvJiQfvtpqaI+vJzlom7d6djkqwH6xV0OHw40H/7PWR3wrKqDk6khltSMhsmjMCCGEEEKIStM0NRoWsUPdQDcn7tHD/f7RSw7Y7nBnDmXfTgKQ6hvy9LL0M1VRzjvx7xz1hlLj1TnqDSXnXIh/V7JABpuj1sdzcfjUDSET1rHYbP2eVibf2X7tYi/5YKbMScs9b7lR5aWk439PQWL/z955hzV5fQ/8JIQYhgwRkCWKFJGNgCIqogIiIor+FESLaJ0VR7VqHXVX66p1UGtVRFx1K1WgEVkCMsSBgBBRkT0aGSLEEF5+f7zfpjHjTQIBgt7Pw9OHnPd9zz33nBvLPe+952p8+lEU74sqAaCvwyflfijKNEU1ZYLza3SGD+G1v5dmbwUaVRJT+SDwYWXyc0HDuGVZSGTy+6LKN9eS6hkljaU1NZkFmIiSmcQmSeI6dv0HBSWe+bOUcReEbySQFRVUDLX57mnD2gQfnBx/KOfI9Sc/nX+y54LZ3AkWS3zxBUdcCi/eF1Xs0yzIU0LzAAC3RzBkkowWwa+btBpEQex5acceX1jF6heL5GGlaqj4PjjSb5Q1LqxKzc0Pi2oq+4dMVRw8z0vfzQ7EhVK5nxCTcOUKPAvrRMURgRAEZUYQCJnBYrGOHj26du3ajigJDw+fNGmStjb//0gQCEkIDQ2NiooCgPXr17u6una3OYgeBnf8bNq0ycXFpbvNQfzH6BNrlPW0AGDEoWXlcU9yjlzXH28/wPe/w4xMZozBN9jz0ntgv3a3KLlCsyBPQw+H19eSSumZJTEZlQ+ys7aF+8Qfknz5gOTtEl3F2gCARCbxXiJTpFgcLfRmoZNzHIpSLz4J75xQqoiI8iFgGADwvtLnJWtHRNbWMxRlmqGnYx9rE6sQv4bXFZmbTokyWJRJ+NYDYte1stgS2ty+uEuOroulroul88GaFyfu5P0eWXA6SsvO1HLZVLNgLzwZ8WDxQVHFKaTKjBAj7WiRoQaxnpd87AmGVRL9MoGvTjAeVr57iEOpbmYIAC3vm3jljcVVAKAkcYYOgeAFZUYQ8ktaWlplZSWfkEwmW1hYmJpKvX4yNTW1urqaV0KhUHx8fHglVVVVDx9+kmVXVVV1d3fHf7916xavGb6+vrx3YhgWHBy8e/duse06OTkZGBg8ffq0qKiIV25qamplZTVlypQ5c+acP39eU1NTqg52EGntZDKZDx484JWbmZlZWFhwP+bl5TEYDO7HqVOndordnYBUrtDT05MrP+Tl5c2dO3fq1KkUish/3nt0B7uYL+17sXjx4oULFx4/fpyv14huh/v+mUKjjr+85abD4oS5P/9f9mlVIx01E30AoKqr4rs5uHBYbFEzamKkVdjKbqGo0KyW+1kt98M4rS9O/JUScvjZ3kse17fLsN26/GJiq/A3w3WMUt6rTRXvJGlaSUcDAOryS3iFGKe1paEJf3ctlKq0PN6PLY3NnCYWTUutHRER5cORv60EgOr0F3g1E5zqjPySmAyDcfZZW8/ojrD0STjEPZsja1u4UP3EJtU8KgBxrlPS1azNLZLEZjzuWMsnr/r5nu04KgbajjvmDd0S9DKCnnP0RtLCA+k//DH3n9sAMKfiukya+Mish3/rVvDSvtEiQw0Enpd27AmGlVg/dH5keSEOpQJVUVlPq+F1+Sf25LwBAJ3h/yVxRMURgRAE1RlByC9sNruurm7FihV+fn5lZWUsFquxsfHVq1eBgYG2trZpaWnt0DZr1iw/P7+MjIyGhgZMYIMim81ubGy8ceOGn5/fvn376urquNNLDodTV1e3e/fuGTNmxMfHs1gsvmc3bNjg4+NjYsJ/QCBvu48fP25s/F89s6ampoaGhk2bNvn5+f39998NDQ1UKhUANDU1t2/fHhwcLFXvOo60drLZ7IaGhjNnzvj5+S1ZsqSiogKXc8Hd5e/vf+fOHUF3yeV702EAACAASURBVDNSuUIO/UClUqlUKlngYAIuPb2DXcnn970oLCx0c3NLSEgQepVCoVCpVIK0GkIe6Gtn6rA9mF3XeH/WTgDQMO+vaqz75nrix9r33Hve3nkYpjQhbe3v7dAvlcKiyJTTvTwZZ+n4RzJFwWKpL4miQFACoH3tirVK23GwipFO4YVY3iIsjLN/i2kVwwBAz9WGpq3BOPs377P5J++2YZiui5WoR9l1jbzJkbzjkQAw8P/GSBsRAh8q6/bRMO9fSs/k8Lzbzz128/H2s/iE0NjXhffI0jc3kwFAcE8NsUmSuE5JW4PTxOLeQBx3BSqF09jM+7a/LO6JKDd2BDJFYfD8idOfnJyScszQ0wkXKqoqifqRSjnz2SsA6DeSfwC0b7TISgOx5yUde/9+PfnCKlZ/l0UWR2woTWa4VaXk4NvBcPJP3lWgUbmDAUTHEYEQBP31g5BfXF1dXV1dly5damdnt2zZMq78u+++c3NzGzt27LNnz8zMzAg08OLm5sbhcBYuXGhhYSG4sgPHyMhozpw5T548AYCNGzfyriihUCjBwcHKysqvX7/+4Ycf+B7My8uj0+l79+4laNfKymrHjh1cuYuLi4uLy08//UShUEJDQ3nnsY6Ojr17975x48a0adMk7F3HkdZOPT29oKCgyZMn6+jo1NfXL1y4kG825ejoqKysnJWVZWXVw/5vJK0repwfPvsOypDP5nvBYDC2bdtWXV3d2NiYnp7O4XDEP4OQY4Zu/rokJqMqJefRljOOO+a5HFlOn7I50nWl00/fqOj3ZT4tTFv7O01bw+b7me3TL7lCY58RvQfqZW48qUClaNl/xW74UHDqbhundZD/WKGaO9KuWKuc9y2+P2tntNd6+81fU2jU7INX8EmRUPBKBC9O3m2qrDUL8hy+b3HivL133b+3+2GWiqF22b2sjI2nNMz7W/57QocgiqpK96ZtcT6wVN3MsCLxWcbGk/1G2xj7jJDKgWJ9OGzvIvqUzdFe6+w3zu7VR+1tZOrLc/QhS3wNPRzJVMXcYzf1XG37Opr984jxaEtYPaMEROzIIDZJrOsMPR0LzkSXxWb193YWa7Oeq23RreTYGdssl/u1YW25R282VTDFBb9DCN2L0UHeZb8GAL4iJgBAIpPbMVpkpUHsN4440HzDni+sYvV3fWSJsV3nXxAWFe21ftRvq3qb6OUevVkSk+G4cz5vFkxUHBEIQVBmBCHXPHr0iMViubm58cktLS0TExNv3LghmKQgICEhgcPhiC2+kJKSQiaTvbyEFBVPSUmZN2+eoHzHjh3Lly8nbnfUqFF8ciaTyWAwvLy8BF/vr1q16ptvvunKzAi0y05NTU1vb+/IyMgrV64EBgbyXlqwYMGBAwd66GxZWlf0OD989h2UIZ/H98LU1DQiIoJCoURERKSnp3dx64jOYPylH69aBD/eGaE/zn6A70jP27tSVxylT9mMX9UZPmRM2DrJy2HyIblCEpk8KfZA/JzdD5b8gkt6aamN+DVkULsOyCRuV6xVgwLGYZzWh6t/uzt+NQBo2ZkO/3nRw9WhQtsy8h7ed6jZm2uJb64lDgoYOzjYS4GqmL7u95hJG/B+mc52dz64lGBHUj9X234jreLn7mnjtALAoFnjR//+nSQd4YPYhwN8R46/vDVtdWjUhHUAQKIoWK+e6bx/MYlMdr+8JXHB/tsjQ3C55bdTnXYvvDV8aXVaHp6gkdy3Yl3X32cEiaJQkZiNT6GJbbZaOa2OUZL/x52SmAwAGPh/Y1x+DYmbvUuUJ+WTkpgMTauBQs/3bcdokZUGsd844kDzDXu+sIrVL2+RVTHQnhi9Nz5oT/TE9QBAoijYb5ozdPPXvPcQxBGB4IPU1iZFrSAEQlaQSP8r9EU8Ag8fPrxq1arbt2/zFfUICAi4fPnymTNnpNp1smPHjq1bt16/fp0g48Bms5WUlEaMGJGcnCx41dXVNSkpiU9YU1NjaGhYX19PownfxCiq3StXrvj7++/cuXPz5s2CT3311Vdnz57tyiKI7bPz1q1bfn5+Xl5e0dHRXOHGjRtdXV2FZpd6BO1whZz4YdmyZR4eHmKrV/TcDnY9n9n3IiIiYu7cuffu3eNWUBIkNDTUwMBA3mqgfPaQSKRFbfEdVNJUwax9UdzX3rSXZm+ZWCW5wlZ2S2VyjophX+4JnZ3XLvHVNgxjZr+mqinjNRfEmk0ik3mPEWl4Xf6h9B8d5yG8u1QIwDitlcnPtR0HC92sIVVEiH3Y8Lq8qZyp42zBa20bhr3LedOGtWnZmJBEb6KU0CRi1z1YeqgkOj2w6E8JbW5lt1Sl5vaxHkjTUpfEMLmiqYJ5wXCmy5HlfAU7+JB2tMhQg9hvHEGgeYe90LAS65fDyNbmFTVV1uq52vAdCSRhHPn4gzSWb3oi4bQF0dNBa0YQck1CQgKZTOb7C57JZN6+fdvAwEAwwZGTk1NcXOzg4KCrqyuoDU9qjB1LtMQ3JiYGw7CRI0cKXmKxWELVRkdHjxgxQlRahKDd2NhYABC1hmXEiBE3b97sysxI++z09fVVU1Oj0+lVVVW4f8LCwoyNjXv0bLkdruhZfvjsOyhD0PcC0YNQ1tPCj7DpeoUKVEWDcfZd0y7xVRKZ3NdO0jLtgtNRNRN9SVIqXMgUBYKqmVJFhNiHQg0jkcl8Z3yIhcAkYtfZrvXHFwsYeQ2TxGYFqqKEFUnlkBcn/lI26Gu+cBLxbdKOFhlqEPuNIwg077AXGlZi/XIYWU2LAZrCjuiWMI4IBA6qwIqQXzAMi4mJcXJyUlZW5gpra2v9/f3Nzc1TUlLU1NS48sjISBcXl/j4eABYs2bNjRs3BLUlJiZaWFgQn/mCnysxevRowUt0Ol1wXw8uJzgrB2/XyspKsN2UlBQqlSq4Sh/H3d09MzOTwFTZ0m47yWSyv78/hmHnz58HgNjY2Nzc3MWLF3e6xZ1G+1zRg/zw2XdQhqDvBQKBQOComehbrfo/UcfffE60NDY/P3x9+M+L2r0SpAfxGYf1i4ojQiagNSMI+QUvMkKlUk+dOgUA9fX1T548+fjx4/z58/m27h8+fHjbtm3Z2dlGRkYAMG7cuNmzZ/OtKMGLBQhdDMILQZGRxMTEuXPnCsrLy8tnzJghSiHe7vv37/38PqmqxeFw8vLyhBYpwOnTpw/fEcKC7NixA68XK5bLly/znZEhKzsBICgo6OTJk+Hh4RMmTDh//nx4eLgkJskt7XZFB/0gw2gS010d7Img7wUCgUBwcdwefNNpSVFkygBfMX9N9Wie/nzRYNxQ08Dx3W1IF/G5hvVLiyOi46DMCEJ+wZdvrFq1Cj8jpqKi4vnz58+ePeNb1p6RkbFq1apff/0VT4sAwJUrV6ytrfm04XVDiJeys9ns9PT04cOHCz20Misr6+DBg0LlixYtEqUTb/eXX37hy9T8+eefd+7cEbo4BYdGo7HZbA6HQ3CC5rp16yQ8Y0LsRLrddgLAqFGjjI2Nc3Jytm7deuHCBUnskWfa7YoO+kGG0SSmkzrIYDBOnjxpa2s7Z86cjpgnV3TS9yIvL+/ixYtMJrOoqGjGjBnz58/H5TU1NVu2bHFycioqKjI3N+dLASMQCET3oqiqNPPF2e62otNx2vVNd5vQpXyuYf3S4ojoOCgzgpBfkpOT8eUb+DzQ2Ng4LCxMSUlp/fr1ERER3Nu2b98OAOrq6ufPn2cwGJWVlUOGDNm2bRuftpSUFBBWLIDD4SQnJ+PbZOh0OoZhQmc7bDZbX1/4RlA2m01QZERUu3Q6HQBELcUHADwhgv175rxQCNqVlnbbiePg4PD27dtjx47J0KTuoiOu6Igfusx1ndFBOp1eV1eXnZ0tmJTs0XTG94LD4Zw9exY/5LumpqZ///59+vTBy50uWrTI398/ICAAACwtLa2srGxsbGTaIQQCgUAgEAiEEFBmBCGn4EVGbGxseIuM4PLc3FxeCZ1OHz58uIWFhbm5ubKystAVFhiGxcXFCS0ycv78+QEDBuC/p6WlgYgiI1FRUaLeD5PJZFH5C7xdoUUKHjx4QFCkAAAkXD4gEzpiJ/c2MzMzPT29TrOxi+igK+TfD53UQU9PTwC4dOmSbK3tXjrpe5GQkLBv377x48d7enpqa2t7enpeuHBh6tSpNTU1kZGRV69exW9zc3M7efLk0aNHZdgjBAKBQCAQCIRQUGYEIadkZGSwWCy+iUdqaiqHwzE0NORK8P0mVlZWw4YNE9DxH0lJSaKKjFy9evXu3bv47+Xl5QAwfPhwwduOHz9+8eJFocoNDQ2bmpoI2hWcPlVVVRUWFnp7exMUKWCz2WQymXjfxMGDB589e0ZwA5ewsDCCXTkdsRMAGAxGTU2Nt7e3JJbIOR1xRQf9IKtoEtONHexxdNL3wtXVddOmTba2tvhHDoejoqICAOnp6TQajRtZBwcHvHorAoFAIBAIBKKzQZkRhJyCL2IfP/6Tskn4WS34LAIAysrKDAwM1NTUevXqxfd4ZGSkr68v9yN+7qZgkZHQ0FDu/AQALC0thRpz8eLFMWPGaGkJP/zMwsIiPz9f6CW8XQ8PDz45foYOcZGChoYGsUsPJk+ezGu/KHinWzK3EySr4dJT6IgrOugHWUWTmG7sYLvJyclRVlY2MTGRStJxOul7QaVSd+3ahf9eVVVFp9NxhQ0NDbyZUAqFkp2d3aEOIBAIBAKBQCAkA2VGEHJKbGwsAIwbN45XWFtbCzwFOLZv3/7HH38sWbIkKyuL97YTJ040NDTwSuLi4gBgzJgxXAmLxdq9e/fOnTsLCgq4wsDAwG3btl28eHHlypVcYWRkZGxsbFhYmChTbW1t+Tb4ELSLgxcpGDp0qCidAJCXlyd2rb6ZmZmZmRnxPZLQETsBIDo6GiSYKPYIOuKKDvpBVtEkphs72D4KCwutra01NDSYTCa+RkMSiUzogu/FypUrf/75Z/ybjmGYgoIC79XW1lbprRbD+/fvoWs36yEQCAQCgUDIPygzgpAvGhsbZ8+eXVNTgx9Y6+vra2hoyF1SHhQU9Pvvv79+/bqhoWHr1q2rVq0CgO3bt8+aNWvLli1Dhw599epVYWHhjBkz8JRKSUlJSEhIRUUFvthk/vz5+Kypvr7+wYMHHA5n+PDhvHNRPT2927dvBwcH19bWOjo6NjQ0XL58efjw4QRpEQBwd3fHzxXmwtfu9OnTtbW1r169imHY9OnTa2trExMTAWDt2rWhoaHXr18XugQgPT2d4DBgmdBBO9lstr+/f01NDb7AZ9asWdra2tevX+9UmzuJjriiR/ih53ZQR0fH1NTUwMCAm/KQRNIRuux7sWvXLk9PT+7BNKqqqs3NzdyrfDsHO86UKVNKS0ufPn0KAJMnTx45cqSJiQnxP24IBAKBQCAQXwiktra27rYB8SVCIpHwX6QdgY2NjVFRUU1NTWPHjjU2NubKS0pKXr586eLi0vEDPlgsVkxMTF1dnbKysre3t6qqqthHBgwYEBkZKcNTJJqamrS0tMrLywVLPyIQBCxbtszDwwM/6KTr8fPz8/PzCwoK6pbWexbnz5/v06cPXoUkKSnJ1dW1sLBw8ODBLS0teH7nu+++Ky0t5RZk7UpCQ0MNDAy6axR9sZBIpEVt8d1tBQKBQHzp/EEayzc9afe0BdGzQGtGED0MVVXVmTNnCsqNjIyMjIxk0gSNRpN2SrBy5cozZ84cOnRIJgYAwOnTp4ODg1FaBIH4LImKinr+/LmHh0dsbCyGYXhmxNTU1NTUNC4uzt3dHQAyMzOXLFnS3ZYiEAgEAoFAfBGgzAgCIQNWrlxpa2uLV4TtuDY2m33q1KmYmJiOq0IguoaIiIi4uLiEhAQGg5GcnBwSEiLDJVSfGfn5+dOnT2exWPv27cMl3NOODx06tG3bNmtr65SUFHV19Tlz5nSfmQi5IDf01j9PXjrvX9JLszdX2FT1LnPTaQBw3B6sYqDNJ+/nYjV4/sSKpGxGxN+WIX597Uz5dBaERVem5tj9EKhuKoP/YRGDmyG0rfZ1TYFGLYt7zKdK3dSg3yjrfqOsO60f0pEbeqsuv3jk0RVd01xpbFbu0ZucD83K+n3HRmwQKukILGY9TUtdFpaKgWC0dBLPD19vLKoccWhZ1zTXlfB2TbYDkjseunicIxBdgMwq1SEQXzJkMvnChQsrVsjmfw8bNmzYtGmT2INpEAj5ISgoKDw8vLa2Njc3948//kBpEQLMzc2bm5vbeAgICMAveXt737x5MzMzU19fn3uaOOJLhtP0seB0VHn8E15h+f0nBaejCk5HlURn8MorErMLTkdhLRwAqGeUFJyOaiyqFNRZnvC04HRUUzmzUy3Hwc0Q2lb7ulaZkoPfwPuTseFk5OgV9wN2dG5nJKYsNosR3kXvNj6U1cRM2lAWm0VRUVI3MxQqaTd1+cVXLef986RQRsaKgWC0dBKl9EeMc/Qua64r4e2arAYk33joynGOQHQNKDOCQMgGGxubxYsXb9u2rYN6Ll68aGJiInTHEAIhCb/++mtQUFBaWlp3G4JoD9ra2j4+Ps7Ozt3SekRERFBQ0Llz57qldYQg+mPtAKDywXNe4dvIFHUzIyVdzbLYT85lK6VnAoCR9/CutLDddKRrXnf3LGqL5/7MLIjQHWH56nJ8buitrjKfCNv1s8Zd+rFr2qrJYmDsFpfDIRNu7xq6+WuhknZTnZFfm1ckG0MR3YesBiTfeOjKcY5AdA1oNw0CITM8PT1NTfnXLUvL6NGjZVUwBfEFsnLlyuLiYgAYOHBgd9uC6Hk4Ozvr6+sDgK2tbXfbggAA0HYcrKiqVJ2Zz5W0YVjx3TTTOR7s2vdFt1PaMIz075FM1ekv1EwNVI10ZNJ0K7tFgapIcEMbhgEASdiBULxWiUKGXdMwMxoTvv7K4KCSmAzLZURlwoQahnFayRQFye8Xi66zheSqCFoX1NCGtfHfjLUBAK2vOpEEAMQFVHIzhEKsnGCogJROFjssCToi9llJlAiF+LsgJGqf3iDJmOxIv4QOSGIk8ZWocU7cXxA3HhCIbgRlRhAIWWJiYtJBDSgtgugIZmZmvAdRIxBSgcaPHNJ/kvPr60nc6VNVam5LY7PRBKdWFvvV5fiKpGx9NzsAYDd8qM15M2SJbwebe3n+3rP9l2tz3uAt9htt7XJkuZbNIPwqvmNl8IJJD78Lrc15g9/gemottzBEUWRKxvo/6vKLSRSFwfMm9rEm+n+iDLumYWYEAI3F1UKv3g/YQaYq6o6wTFlxhExRcDuzflDAuHc5bx6uOlYe/7QNw2jaGhZLfIduCeLO6N7eeZix/o/avCISRcF01viB00YnLtjveWOnnqsNrvCfJ4X+BRHcJhgR9IerQ/Eb4oP2VCQ9Cyz6U1TTAEDcOh+Vyc8zNp6qSsnh3my/eY4CVZHu9yO+uCb+693kXoqeN3Y+P3SVT6IxpH/62t8LL8Vh7BYSRUFvtI3LkeV9rP6XOicwI3HB/teX4wHgnt+PvbTU8O7wQTBaxA4VkGa0NNfUEfQCAGoeFaSvO1GR+KwNw5R0Na1WTLffOFuskXxIFRSxHRQVNe7jfAOj6FYyrjBl2eF6RgmJomC+YNLo498xIugZP/zRVMGkKNNs189y2BIkbb+4A7I0NkvopjNDd4fxf24h1ik4HnjHuST9JXYXAiEPoMwIAoFAIBAIhJxi4O7w6nJ8ecIzg3H2AFBKf0Qik428h7PrPwBAWWwWnj7A58NGE5w60lZu6K2UkMNGXsPsNwSSqZTq9PzsX67EeP8QWHwZT16w3zfXvXj79q+HQxb52G+YXfUwN/fYzeiJ6wNengeAosgU+pTNWnam4y5sbsOwp3svvb6a0DVdq0rLAwDNIf2FXmW/b37/+lXhpfsDfEc2VTDVzfvXPCq4M/a7Xlpqo35bpaSrWfHg+eOdEcxnrybc3sXtiO5IK8/buwBre7zzXCk98yOzoZXdwlXIYtbzNoGxW7g3tLxv+shsENU0ABC3zkcpPTN64g+qxrqjfltF01Yvjkp/vDOiMvm5T9wvQxZPVtbvm/fbra+CJvS1N1UbpCcoofv9WJdf7HxgqaqxTlMZ89HWM5GjV8wuuaKoqkRshmmgO2BtBWeizRdN7mMtZBEi8WghHiog5Wgh6AUAVGfkR45eoazXZ/SJ1b369H59JSFz0ylOE8tp1zdihzQXqYIC4r4LBFETNTDY75trc98U302zWjld02JAQVjUi98jP5TW1GTm26zxp2mrZx+8krX1jK6LpaG7g+T94h2Q6l8ZOG6fx5WTyOSiW8ml9Ex1MyOxARUcD7zjXJL+Eo8HBEIeQJkRBAKBQCAQCDlFf5w9AFSn5eHpg5KYjH6jrRWoikraGlp2psV305x2fQMA5fFP8bQC77N0P+mqADzde0nTYsDE6L34x4HTXFtZ7Jwj12seMXSGmePC928qxl3YbBo4HgBMA8e3fmzJP3mn5lGBtuPgtDXHVY11p6QcpSjTAMDY1+Wq1Xx2XaPMu9bKYrc0Nv/PnqLKmoz8zM2nAYBgXUldfrHrye/NF0zCP95y/pZEUZia/puybh8AGDB1lJK2esaGkyUxGUZew9LWHFcx0pkUe5BCowKAgbvDVat5ojSLha9pAEgJOUzQOt/jSYsO0rTVp6b/pqStAQADp7mq9tfN2nqmIDxmcLBXK4ud99stQw+HAVNHAYCKgTavhNPEqkrJsV03y2q5H66Nqq6Se+xmbd5bnWHmxGYYjLP/UFpTcCbaaOIwQ3cHwX6JHS0EQwUAJB8txL0AgIerjinQqNyODJzm+qGc+XTvJYdtwZIM6XYEBYegg8RREzUwGt9WcRUa+7qEq/sU33k4syACXxKlM8z8quW8opvJhu4OkveLl97G/Xi3m5XGZpXFZvX3GeG4Y57YgBKPB0n6SzweEAh5AG3xQiAQCAQCgZBT1Ez0ew/U+yeLAQAfa9/XZOZz52mGnk7Mp4X44oWq1Fw8rcD7rMH4oYO/8eb7URO9fD2w6NKUh8d4JTRtdQBgN3zgSkhk8qCAsdyPui6WANBcXVuXX9xQWPbVHA98ogsAVDUV8/kTO6Nr96ZvPdPbG/+5Zj0/8Zt9LGbDiF9D8DUmQiGRyWb/ztCaa+qq018MmDISnwPjWIb4AcCrP+PwjgzyH4unRQBAUVVp8Hxvgo4Qw9u02Nb5nq3OyG98W2U21wufcOLYfj+TRCYX//VQbNNkqiKZqvjyHL3w4n0Oiw0ApoHjp6Qe0xlmLpUZQhE7WkQNFQCQarQQ9AIAOCx21cNcvo6MCVvnXxBBpihIMqRByqBwEdVBCaPGNzD4FCqqKlFUlfrYDMLTIgCAf3M5H5pBsq8qMe9y3tybvlXLztT98hZc0m6dkvdX1HhAIOQEtGYEgUAgEAgEQn7Rd7MrvHQfAEr/zgQAg39f2Bp4ODzbd6nsXtaAaaOZTwsdd87ne9AyxA9fSsBLfNCehsIyoQ2RyOT3RZVvriXVM0oaS2tqMguwf/ePcKEo9+Jdrs/9vY5RAgCaFgN4b9b49KOsuma1Yjp3fweJTO7Vp7f+OHuqmgpBQxTlXtyCETWZ+QBQeCnu7R3+5AKL2YB3RMv2k3oNfazEdETCpsW2zid5X1QJAH0dPqn+Q1GmKaopS3JqDJmi4Hry+8R5e+Nm7yKRybojrYwnu3wV5KGs20cqM4QidrSIGiog5Wgh6AUAVCY/BwEXcatXSDKkQcqgiO2ghFHjGxiCCsmKCiqG2nyNtmFtkvdLFE0VzCjPtYoqNK+oPdzkVLt1St5fUeMBgZATUGYEgUAgEAgEQn4x9BpWcCa6Nq+o6FYyTVuDu/jcYJw9iaJQEpOhoNyrDcPwzSkdIWtHRNbWMxRlmqGnYx9rE6sQv4bXFZmbTkn08P8mbCReGZkiZvLTvq4ZTnDs793Rk61NZozRHWHJJ+w9sB/GaRW8WeazOFGtC71ZqBvxGbJYzII8DT0cXl9LKqVnlsRkVD7IztoW7hN/qB1m8NGVo0VUL3SGmQOGAQB3gU9HjOyINwTpSNTE0hHntzQ2R3v/0PK+afKDI7xrZDoU0E7uLwLRNaDMCAKBQMgXoaGhUVFRALB+/XpXV9fuNueLgOvzTZs2ubi4dLc5CMQnGHk5AUDNI0ZFUjZvyQMSmdzf25n57BVNW4OqodqOszl5qS8sy9p6RneEpU/CIe7Wlaxt4RI+jr/crmOU8gqbKt4RP9U1XeNDzUQfAKjqqnxH/HJYbAqNir/lfvf8De8l1j+f1FsFAKzlkwRKbW6RTFrnu1lJRwMA6vJLPmma09rS0ESwdYiXVnYLRYVmtdzParkfxml9ceKvlJDDz/ZecvrpG8nNEKSLR4uoXnhc397HdhAAVKe/GLJ4Mvf+6oz8kpgMg3H2EhopVVDE0vGoEdNB59+bvpX5tHBi9N6+dqYy0dnZ/UUgugyUGUHIL6mpqdXVn5zA5+TkZGBg8PTp06KiIl65qampnp7egwcPeIVmZmYWFv/9LZWXl8dgMLgfp0795H9+MrFQX19/2LBhAHDr1i3e2+zt7Y2NjQGgsLAwJycHF5LJZF/fT2rFpaWlVVZWCrZCpVLd3NyUlZU7brAkyIkZ3Ui3eyAvL2/u3LlTp06lUET+E93tRnYLndfrxYsXL1y48Pjx43z/5iAQ8gBVTaXvULOXEX83VTD7f1pj1chrWMqKI1R1lQ6eSgMAdfnFAGDs68Jb0ePNzWQAkGRRvbbjYBUjncILsXY/zOJqYJz9m/iprukaHxrm/VWNdd9cT3TaNb+XZm9c+PbOw78nb7T53t95/xI1U4NXl+MctgdzZ8UFYdG8GhSoFE5jc0tjM342CgCUxT2RVeu8N+u52tC0NRhn/7b5fibXq/kn77ZhmK6Lldi28PNfXI6swGuXkikKFkt9U1cda8MwKczAMEHNXTla5agmUwAAIABJREFUCHoBAMq6fTTM+5fSM3mzGLnHbhZeiO09QFdCI6UKilg6GDWxdMT5iQv2l9IzRx5byVdWVgqdAuOhs/uLQHQZaIsXQn5hs9l1dXWzZs3y8/N7/PhxY+P/KpY3NTU1NDRs2rTJz8/v77//bmhooFKpbDa7oaHhzJkzfn5+S5YsqaiooFI/SfPX1dXt3r3b39//zp07LBZLJha+e/fu1q1bfn5+33777du3bzkcDgBgGNbY2HjkyBE/P7/du3fX1dW1trZy709JSfHz8zt58mRDA//OVby/K1as8PPzKysrY7FYLBarrq7u2rVrmpqaW7ZskYnNYpETM7oRefAAlUqlUqlk0eu35cHIrqfzek2hUKhUKkEqCoHoXvTH2Zfdf0wikw0/TRPoj7dv47RWJD7r7zOig01oO5iRqYq5x25Wpea2sluqUnPvuq+pZ5SAxEvinfctrmeURHutL4t7UpWae2/6VuazV2Kf6oKuCeJyZHlzVW2k68qiyJSaRwX5p+7Gf72bpq1h8/1MABgVurLxbVWU59rS2KyqtLz7gbuqHubyPq7natuGYbEzthVHpb298zBqwrqmCqasWueFRCYP37e4nlFy1/374qg0Zvar7INXUlcd0zDvb/nvQS0EGPuM6D1QL3PjyRcn/qrOyC+NzYoL3NXGaR3kP1YSMxSoFAB4cfIuI4LOp7krRwtxLwBg2N5FH8r+ifZaV0rPrHlU8GjLmZfn6OaLfAw9HCU3UvKgiKWDURNLu53//PD1gtNRWnamVHUVRgSd96evvalYnaLGQ2f3F4HoMtBfgQj5xc3NjcPhLFy40MrKaseOHVy5i4uLi4vLTz/9RKFQQkNDubPHoKCgyZMn6+jo1NfXL1y4kG+S4+joqKysnJWVZWUlswS2j4+Pjo7O2bNn3dzcVq5ciQvJZPKcOXMwDIuPj//222+Dg4O59w8bNszY2JjJZIaFhQlqc3V1dXV1Xbp0qZ2d3bJly7jy4OBgJyenb7/9Vl1dfc2aNbIyXhRyYkY30iM80COMlDlfZq8RCAAwGD80+8BlbafB3BfaOBpmRr0H6r1/U2EwfmgHm1DW03K/vCVxwf7bI0MAgERRsPx2qtPuhbeGL61OyzOWID0xKGAcxml9uPq3u+NXA4CWnenwnxc9XB1K/FQXdE2QAb4jPW/vSl1xlD5lMy7RGT5kTNg6vOyCoafThL92P1h0MMrje7wjDlvnZm0/y33cauW0OkZJ/h93SmIyAGDg/41x+TUkbvYumbTOx+BgLwWqYvq632MmbQAAEplsOtvd+eBSSXZ5kMjkSbEH4ufsfrDkF1zSS0ttxK8hgwLGSWKGkffwvkPN3lxLfHMtcVDAWN7VBF05Woh7gXdk/OWtaatDoyasw42xXj3Tef9iEpksuZFSBUUsHYmaWNrtfPwcKObTwvivd/Nd+uYjXaxOvvHQZf1FILoMUlsbKo2D6AZIpP+V3SIegbGxsR4eHkuWLDl+/DivnMlk9u3b18vLKzo6mu+RKVOmREZGXrhwITAwkFceFBS0YsUKR0dHWZj/H01NTSoqKr6+vrdv3+aVHz58eNWqVZs2bdq165M/ldauXbtx40ZNTU2h2h49euTk5LRq1apDhw7xyqOioiZNmuTj4/PXX3/J1n55NqMb6V4PLFu2zMPDQ+yGry8zTJ3a69DQUAMDA5lstUMgpIVEIi1qi+9uK6ANw97lvGnD2rRsTNpXdrQNw5jZr6lqynjtBjmnqYJZ+6K4r70pX14Gh5n9iqJMUzc1yD91N2nhAe97Bwz/PT0HAPBX632sB9K01DujdT4aXpd/KP1Hx3kI39nMktDKbqlMzlEx7Ms9AlZyM1rZLSQyme8UFZwuHi3EvQCAhtflTeVMHWcLXmulNVKqoIilI1EjpuPOb59OgvEAndnfruQP0li+6YmE0xZETwetGUHINampqQDg4eHBJ79//z4AjBw5UvCRefPmRUZGnjt3jjczsnHjxsDAQJmnRQCARqMBAJP5yTLaxsbGCxcuAABfzYLs7Oz+/fuLSosAQEpKCgCMHTuWT/7u3TsA6LKl/nJiRjfSIzzQI4yUOV9mrxGILoNEJmvZDBJ/H6EG3sqOco6ynpaynpaoq8SuUKAqdrDAJHHrfKiZ6Lc72aRAVTQQfXQRsRkEU9wuHi3EvQARLpLWSKmCIpaORI2Yjju/fTqJUx6d118EogtAdUYQck1SUhIImwXFxsYCgNBjO3x9fdXU1Oh0elVVFS4JCwszNjb28vKSvN1Hjx5t27ZNkjvJZDKFQsnN/WQH8i+//LJkyRIA4NZGwTl27Njy5csJtCUkJJDJZHd3dz45nmfx9/eXxKSOIydmdCM9wgM9wkiZ82X2GoFAIBAIBALRqaDMCEJ+wTAsMTHRyspKcJFFSkoKlUodNWqU4FNkMtnf3x/DsPPnzwNAbGxsbm7u4sWLpWq6vLw8KytLwpuVlZV5S7q+fv2aQqFMmjQJAD58+MCVX7lyZeZMojpeGIbFxMTY2dnxHbERGxsbExOzevXqgIAAKfrQXiQ3g8lkGhoaOjg4CFPTg5GTQBDTI4yUOV9mrxEIRLej2l/HyNuZ1redu2YQCAQCIf+ghccI+SUhIYHD4bx//97P75PS1hwOJy8vz8vLS9TJHUFBQSdPngwPD58wYcL58+fDw8MlbPHUqVPFxcXbtm1TU1PDt8lkZ2f/+OOPN2/eJDglxNraGl/hj3Po0KH9+/fjq/q5GRM2m/3gwYOjR48StP7o0SMWi6Wvr4+vlAGAxsbG+/fvR0VFXbp0iWDKt2PHjidPJDov8PLly3xH9nTEjPr6+qqqqg8fPmAYRuCfHke7AwGyjkUnGdlz+TJ7jUAguh1DTydDTxkfHoxAIBAIuQJlRhDyS3JyMgD88ssv06ZN45X/+eefd+7cGT16tKgHR40aZWxsnJOTs3XrVnyNvYQMGzbs+vXrLi4uYWFhvXv3Pnjw4OHDh5cvX0487ceXtLBYLBqNlpSUNHz4cDyrQiaTuZPkAwcOcA+vEcWDBw8AoH///gwGA5fQaLRZs2YdPHiQ+MF169bhBwaLRZKpuORmmJiY5ObmKikpfU5pEehAIEDWseiIkQwG4+TJk7a2tnPmzOlIQ3KFJKER7HhNTc2WLVucnJyKiorMzc35ajMjEAgEAoFAIBAoM4KQX0SVWqTT6QAgdCsNFwcHh7dv3x47dgxPUkiIjY1NdHR0fn7+mjVrkpKS7O3t8a0xxE/hTeCTrrCwMO4SFRqNhu+mqaioYLPZpqZiaozhmaCNGzcaGBhIbjPXAFkhlRlmZmYybFpOaHcgQNaxIIDYSDqdXldXl52dbW1t3TX2dA1iQyO044sWLfL398dXlFhaWlpZWdnY2HSNwQgEAoFAIBCIHsFn9aYX8TmBYVhcXJzQIiMPHjwQVWSE9x4zMzM9PT1p283Jydm2bZuenp61tfWlS5eOHz8udgmAiooKABQXF584cSIkJIQr19fXx3fT/PLLL6tXryZWghdQMDY2bsdsXIbIiRndSI/wgFgjPT09Z86cyVeMo6cjSWgEO15TUxMZGfl///d/+Ec3N7eTJ092uq0IBAKBQCAQiB4FWjOCkFOSkpI4HI5g+qOqqqqwsNDb25tgBweDwaipqfH29pa20R07dhw6dOjs2bMWFhbbtm07evRocHDw3r17i4qKCFaOaGtrA0B1dXVOTg5vqVczM7PCwsLU1NQBAwaoqakRN52RkcFisYSetiOWgwcPPnv2TJI7w8LCiJfAdMSMz4MOekCGsSDgywxT+3qdnp5Oo9G4rnZwcMBrMyMQCAQCgUAgEFxQZgQhp+AVFj08PPjk8fHxAEBQZAT+XXIv1TG9OPPmzVu4cKGenl5MTMyHDx80NTVv376dlJREPIMdMmQIAOzZswff5sMF31hx5MiRP//8U2zT+NahdtgMAJMnT7a1tRV7G+/8UFZmZGdn02i0z2lPTUcCATKNBQEdNLKD5OTkKCsrm5iYSCXpOO3rdUNDA29JFwqFkp2dLUOrEAgEAoFAIBCfASgzgpBT4uLiAGDMmDF8cjz7MHToUIJno6OjQVz2RChGRkb4LywWq6mpCf9d7DtqPAMyY8YMvkX+SkpKALBo0SJJmo6NjQWAkSNHSmkyAICZmZmschNSmcFgMGxtbfX09MrLy2XSujzQkUCATGNBQAeN7AiFhYXW1tYaGhpMJhNftyWJRCa0r9cYhikoKPBKWltbZWUSAoFAIBAIBOLzAGVGEPJFSUlJSEhIRUVFZmYmAEyfPl1bW/vq1asYhk2fPr22tjYxMREA1q5dGxoaev36dd4X72w229/fv6amBn+3PGvWLG1t7evXr7fDDC8vL8nnt6qqqnp6ej/88AOfXFlZ2dfXd9y4cQTPNjY2zp49u6am5uHDhwDw9ddfa2lp3bx5sx02d4T2mdGvXz9jY2Mmk9nU1NTTS1rISSCIkQcjdXR0TE1NDQwMuCkPSSQdoYO9VlVVbW5u5n7kcDiGhoYdtwqBQCAQCAQC8TmBMiMI+cLIyOj27duCcjKZLHYuRKVSZTVLpNFoFhYWEt7s4OBw69YtwUNJQkJCtLS0iJ9VVVUV2t8upn1mqKmpFRUVhYeHfwan9spJIIiRByPV1NRevnwpraQjdLDXVlZWLBYLwzB8lD5//tzc3FxWtiEQCAQCgUAgPg9QZgSB6CgGBgZCD8v4Qk4Gff78eXBwcHdbgUAIx9TU1NTUNC4uzt3dHQAyMzOXLFnS3UYhEJKSG3rrnycvnfcv6aXZmytsqnqXuek0ADhuD1Yx0OaT93OxGjx/YkVSNiPib8sQv752/AfGF4RFV6bm2P0QqG4q/gQu3AAAICtSRh//jitPCP55UMA4I69hHeygJOB9ETSYz4aX5++VxWa1YW39Rlp9NXcChUblvbks7knhxdhWFlvbYbBZ8ARefwrShmGvrySUxmZhbI6KobZp4Pg+VgMl1JZ3PPJj7Xv7jbOl6mNl8vOG1xV8QsMJjsq6fQh0Nrwuf7Do4NhzG5X1xLyGaQcsZj1NS51XIpXDQUqf89H1IeheOm8wc/lQVpO25vjY85vIlP/tMOVzFP4vA/77mFNrZdMxBKJH0ePf9CIQiG6kpqZG8FhlRLcTERERHByckJCwd+/eRYsWfTk1R4V2/NChQ9u2bauqqrpx44a6uvqcOXO620wEQlI4TR8LTkeVxz/hFZbff1JwOqrgdFRJdAavvCIxu+B0FNbCAYB6RknB6ajGokpBneUJTwtORzWVMyUxoCw2i3EmpqniHe/9z/ZfrkzJMfR0bE+XpAfvC5/BvDawGz7cdgmJ/3p3dfoLdv2HlBVHr1nPf//2v74nLzt8d/zq6vQXH5kNad8fv2Y9v7GkWlRzH2vf33Raen/WTuaTQnb9h7zjt69Zz88NvSWhNmPfEVnbz1YkSfev7uOd5xLm7uH7qS8oJdZZdi/rXc4bmadF6vKLr1rO++dJIa9QKoeDlD7no1tC0I103mDmwmlixfrveHU5vg3DuEI+R32sfd9U8a40JqPgdJSsu4hA9AzQmhEEAtF+duzYsWfPnu62AsFPUFBQUFBQd1vRDQjtuLe3t5OTU3p6ur6+/t27d7vFMASifeiPtQOAygfPB077rxb428gUdTMjdn1jWWyW+YJJXHkpPRMAjLyHy9YGEkVh4t3//p1vqnqXtS18zOm1pO7bR8lnQ+qKo1UPc4ftWWj3QyAANFUwb49cHuOzccbzMAAojkrL++2W9eqZIw4uBYDavKLbI5fHf717csKvQpWnr//jn8cMz9u7BviOBICWxuZo7x9SQg7rj7XTtBggVpuKgbbVimnJSw/NyD0jeY/KE54aejrZb/okb9t36FfEOktiMjpj2U51Rn5tXhGvRCqHg8Q+Zzd8YD59pWlpzLc4pVtC0F106mDG+VBWc2/61ur0F3xyPkfZrJlps2ZmfNCel+fowtQgEJ8/aM0IAoFoP0ePHlVVVe1uKz5Dfv3116CgoLS0tO425DNBW1vbx8fH2dlZ1A0RERFBQUHnzp3rSqsQCLFoOw5WVFWqzsznStowrPhumv44e303u6LbKbxvgKvTX6iZGqga6XSqSc/2Xe6lqToogL+4OK8lvLSyWwi0tWGYqAdFyflswDitL8/d0x1hic8kAUBZT2vY7gW1OW+Ko9IAIPfoTQUaddieBfhVTYsB1iunVyQ+45v8cxtlnP3b0NMJn5MDgKKqkt0PswDgbWSqhNosQ6bW5hW9PH+PoOO8vH9bibFbjLyG6bna8P4oqioR6GzDsLd3Hhr7uvCqIvA2gT/F3iCVw0Fin1dn5P81ZmXlg+d8ZnR9CISCcYgOMhN0VxuGETwiKjSdN5hxnh+6dsViXl1BSR+bQYJXZeIoBOKzAa0ZQSAQCPli5cqVxcXFADBw4ECxNyNkgrOzs76+PgDY2tp2ty0IxCf0n+T8+npSG4bhr5SrUnNbGpuNJji1stivLsdXJGXru9kBALvhQ23OmyFLfKVSnrL8CKf5o9BLQgsNtLJbXvweybtQ5X7ADjJVUXeEZcqKI2SKgtuZ9fgc7+X5e8/2X67NeYNb3m+0tcuR5Vo2g/BHAGDwgkkPvwutzXmDX3U9tZZbRqQoMiVj/R91+cUkisLgeRP7WJsQ2FCTkd+GYX1sP5n16Y21A4Cye1n9vZ1LY7OMfUYoUBW5V7WHmQNAefxTTYsBfB1sw9rGX9pM66vBKyRTFQGA3dAEAJJo623cr99om7zfbn81x0Oob/n4J4sBAOqDiY7NEtRZFvcEsDYDdwcAaK6pS1/7e+GlOIzdQqIo6I22cTmynFuY4+2dhxnr/6jNKyJRFExnjR84bXTigv2eN3bqudqAQAR1R1jWZOYDwD2/H3tpqQUW/SmtwyX0kig6OwSlsVn4COTD0N1h/J9bAOBdzpuHq46Vxz9twzCatobFEt+hW4K4tTmEDvjK5OcZG09VpeRwH7HfPAe3kDg0nTqYcR5tCTP0dHI5EvJoa/i77Fd8V6UdqwjE5w3KjCAQCIR8YWZmJvmh0QiZgHyOkFsM3B1eXY4vT3hmMM4eAErpj0hkspH3cHb9BwAoi83CMyNlsVkAYDTBSSrljPCYlsZmoZeEZkaK7zzkNLEMPBy4Evb75vevXxVeuj/Ad2RTBVPdvD8A5IbeSgk5bOQ1zH5DIJlKqU7Pz/7lSoz3D4HFl0lkMvt9c92Lt2//ejhkkY/9htlVD3Nzj92Mnrg+4OV5ACiKTKFP2axlZzruwuY2DHu699LrqwkENigo9xK0k13bCACNpTXshg9tnNZeWmq8V3VHWAIAXlmWDzJFgXfjEk7J3TQAMHB3kFyboafjox/DGkuqJVnC88/jl/h/U1cee/+6opeWmtncCQ5b5/KuGRHUWRKdoTPCgqqmAgB0vx/r8oudDyxVNdZpKmM+2nomcvSK2SVXFFWVcH/qjrTyvL0LsLbHO8+V0jM/Mhu4Sxj4IjgoYFzvAf0KzkSbL5rcx3ogSOlwAJDW53x0dgjUvzJw3D6P+5FEJhfdSi6lZ6qbGQFAzaOCO2O/66WlNuq3VUq6mhUPnj/eGcF89mrC7V1C3aVu3r+Unhk98QdVY91Rv62iaasXR6U/3hlRmfzcJ+4X4tBI69v2OdYv83cN8/6irhI4CoH4AkGZEQQCgUAgEAg5RX+cPQBUp+XhmZGSmIx+o60VqIpK2hpadqbFd9Ocdn0DAOXxT/GMCe+zdL8fiZXPey9dqcXSe1kAgK9T4FKXX+x68nvehSRP917StBgwMXov/nHgNNdWFjvnyPWaRwydYeYA8P5NxbgLm00DxwOAaeD41o8t+Sfv1Dwq0HYcnLbmuKqx7pSUoxRlGgAY+7pctZrPrmsUZYOWjYkCjVqR8JS7rAYAim4lA0Abp7XmEQMAFHp9crQHRYUGABibI1GX6ZnPf72mN8bWYJx9WdwTCbX1sTEBgKqUHFWBbUeC1OYWAcCLP+6YBXnStNRfX0/MPnC5KiXHN/kIbzEXPp1lsVkD/UYBAKeJVZWSY7tultVyP/xOqrpK7rGbtXlvdYaZp605rmKkMyn2IH6+iYG7w1WreXwG8EVQgUYtOBNtNHGYobsDSOlwABDr84LwGPzO2hfFuH7WP/X4bbyjiItsQ9DbuJ/lsqn/KY/NKovN6u8zwnHHPABICTlMoihMTf8NPxVowNRRStrqGRtO8pZ04XPXxQEBNG31qem/KWlrAMDAaa6q/XWztp4pCI8ZNNONIDTS+rZ9g5k4LULgKATiCwTVGUEgEAgEAoGQU9RM9HsP1MM3XHysfV+Tmc+doRl6OjGfFrKY9QBQlZqLZ0x4nzUYP3TwN958P2oSHNYrig+lNRRlGt8ZoiQy2SzYi1cSWHRpysNjvBKatjoAsBs+cB8ZFDCWe1XXxRIAmqtr6/KLGwrLvprjgadFAICqpmI+fyKBDSQy2fq7GXX5xTGTNzGzX32sfZ8beuvZgcskigIQ1s4griKBU0rP/HvKZlVj3fGXt0ilDd/aIFjzUiiq/XXN5k6YkRPmtOsb6+/+b0ry0SFLfKse5uaG3hals6nq3bvsV4aeTgBApiqSqYovz9ELL97nsNgAYBo4fkrqMZ1h5rg/B/mP5bpLUVVp8HxvPgMEI8iLVA4HCbyUuvxI0sIDSQsPPP/lCgDk/XYL/5i08IDgI50agnc5b+5N36plZ+p+eQsANNfUVae/GDBlJJ4WwbEM8QOAV3/GcSW87qrOyG98W2U21wtPi+DYfj+TRCYX//WQIDT4nV05mEUh1VhFID5v0JoRBAKBQCAQCPlF382u8NJ9ACj9OxN43jAbeDg823ep7F7WgGmjmU8LHXfO53vQMsRvwNRRfML4oD0NhWX474UX74uaU5kFeQoK2fUfFJSofEKKci9uFQYcEpn8vqjyzbWkekZJY2lNTWYB9mn5SYpyL97VENzf6xgl8O9UjYvGpx8FbRi2e0FzdW3B6aiSqDQA6KWlNv7i5r+nbFZQ6qXcrw8I0Ia1AYACVczfwIwIeuK8vb1N9HyTDuNTZcm1qRhqAwCL2VCRlP107yWuXHeExdDNX/NpcDkcwidx3DHvxe+R5XGPuWsNeHUCQPn9J4qqSnhGiUxRcD35feK8vXGzd5HIZN2RVsaTXb4K8lDW7YP7U+vTuhV9rAbwNScYQV6kcjhI4KUg5v8yPuVxT6Inrh9/eeuAqSOFNi2TEIjqV1MFM8pzraIKzStqD56JwwusFF6Ke3vnId/NvHp43fW+qBIA+jp8shmTokxTVFOuzSsiCA1+Z5cNZgLEOgqB+HJAmREEAoFAIBAI+cXQa1jBmejavKKiW8k0bQ1tx8G43GCcPYmiUBKToaDcqw3D8H03UvFg8UFRdUaEZkZaWWxJ1GbtiMjaeoaiTDP0dOxjbWIV4tfwuiJz0ynxT2JtAEAik3hlZMonC5yF2jDm1FrbdQHMp68UqBQj7+FtWFsri62kraFuZggALe+beG9uLK4CACVdIfNMLg/XHH/+y5V+o20m3N7VS7M3LmyHNtY/dZVJz7gfqeoqBI1yUdLWIFMVCbz9NjKl/6T/DtsyC/I09HB4fS2plJ5ZEpNR+SA7a1u4T/whoc9Ke9yyVA4HCbzEXdmEL4VQoFL41jrhyCoEQsFPAm553zT5wRHlTx80mTEGL97BS++B/Qi08Q1RHDxnISo0+LKRrhnMCARCQlBmBIGQd1gs1tGjR9euFVIMTxLCw8MnTZqkra0tW6sQckVoaGhUVBQArF+/3tWVv3YdomfBjeamTZtcXFzE3o/47DHycgKAmkeMiqRs7lYaACCRyf29nZnPXtG0NagaqrrOFtJqnlNxXar7lXQ18aIYBNQXlmVtPaM7wtIn4RB3xpu1LVwS/fjr6zpGKa+wqeIdsQ3M7FdtWFtfO1MNMyNc8uZGEgDojbFRoCoq62k1vC7nvb825w0A6Aw3F2VG4oL9BaejBs0aPzZiA+9iCsm1fWTWAwBFhTZwmqtgPVFePpTVZGw4pe1kzrs8pKWxGWO3UD6twMrVCQDFd9NGHf+Oe6mV3UJRoVkt97Na7odxWl+c+Csl5PCzvZccd84DgHfP3/Dq4Rb1kBCpHA7SeIkAGYZAqP5707cynxZOjN7b186UK1Qz0QcAqroqbyESAOCw2Hw7yLgo6WgAQF1+Ca8Q47S2NDThpZFFhcbj+nboksEsFmJHIRBfFCgzgpB3CgsLjx49WlpaSiaTra2tV69eXVlZmZGRERgY2D6FJ06cqKioaG5u/v777+U/X4BhWHBw8O7duwUvpaWlVVZWCsqpVKqbm5uysjL+ccqUKXPmzDl//rympmbn2tou85hM5oMHD3hvMDMzs7D47+/7vLw8BoPB/Th16id/r3QGPdHyvLy8uXPnTp06lUIR+a+6JP2Sq051C/LgpcWLFy9cuPD48ePV1dXSWY/4TKGqqfQdavYy4u+mCmb/T2usGnkNS1lxhKquIu2pNDh8p5+IRUlbg9PEamW3CH3Jj1OXXwwAxr4uvPe8uZkMAHx7agTRdhysYqRTeCHW7odZ3McZZ/8mtiFh7s8tjc340TY42Qeu9NJS6+8zAgBMZrjlHLlexyjhTjXzT95VoFHxIh2CPNl9oeB01JAlvqN5Ug9cJNTGfPYKAPqNtCLuLwAo62m9uZ5UnvDUfOEk7vQ799hNADCe/ElilKuzKi2vpbHZYPxQXI6fPuNyZAWeWyFTFCyW+qauOtaGYZoWA9RMDV5djnPYHsxVXhAWLdYqAIB/q1pI63DJvUTrq27k7aykw//HSWeHIHHB/lJ65shjK3nzjACgYd5f1Vj3zfVEp13zuatU3t55+PfkjTbf+zvvXyKoSs/VhqatwTj7t833M7n+yT95tw3DdF2sCELTPt9KO5glQfLbUVl7AAAgAElEQVSxikB89qAKrAi5Jjw8PDg4eOHChdevX7969aqrq+vXX3/t6emppqYm/mFhnDhx4syZMzNnzjx79ixfuoHNlmiRcBezYcMGHx8fExMTwUtsNruurm7FihV+fn5lZWUsFovFYtXV1V27dk1TU3PLli34bZqamtu3bw8ODu5SuyU2j81mNzQ0nDlzxs/Pb8mSJRUVFVTqJ29m6urqdu/e7e/vf+fOHRaLhSwXBZVKpVKpZNHLpCXpl7x1quuRBy9RKBQqlUqQ5EJ8geiPsy+7/5hEJht+mgHRH2/fxmmtSHzGnZR2KoaejvDvCcGi0HYwI1MVc4/drErNbWW3VKXm3nVfU88ogX/3FxDjvG9xPaMk2mt9WdyTqtTce9O34jM3Ahssl01tKCxLXLC/Nq+oOiP/3vStVQ9znQ8sxWebtuv8FVWVor3Wl8Rk1DFKUpYfKYnJsN80h5sVenvn4Zne3inLjwBAU9W7rO1nAYDzgRUftIf3B08oiNWG8y77NQBw9z3xUUrPPNPbO2nRQQAgkcmOO+Z9KKmO8f6hPOFpXX7x413nMjac1Btjy7ehiauzNCajj80gZT0tXG7sM6L3QL3MjSdfnPirOiO/NDYrLnBXG6d1kP9YABgVurLxbVWU59rS2KyqtLz7gbuqHuYShwAvWvHi5F1GBL0dDpfcS33tTCfe3YNXS+HS2SF4fvh6wekoLTtTqroKI4LO+9OGYS5HljdX1Ua6riyKTKl5VJB/6m7817tp2ho2388U6isSmTx83+J6Rsld9++Lo9KY2a+yD15JXXVMw7y/5XI/4tC0w7dSDWYJIR6rCMQXBfrDCyG/REVF7dixIzs7W1VVFZe4ubk9f/48MjLSy0tkEXVifvrppzlz5pSWln748GHSpP8Oh2toaNDT0zt9+nRAQIAMTJcReXl5dDp97969Qq+6urq6urouXbrUzs5u2bJlXHlwcLCTk9O3336rrq6+Zs0aAHB0dOzdu/eNGzemTZvWRaZLbJ6enl5QUNDkyZN1dHTq6+sXLlzINyF0dHRUVlbOysqysuqiFxo913JiJOxXz+qUzEFeQsgnBuOHZh+4rO00mPsqG0fDzKj3QL33byq4Kwg6lf4+I0gUhYrE7P7ezqLuUdbTcr+8JXHB/tsjQwCARFGw/Haq0+6Ft4YvrU7LMxaXwRkUMA7jtD5c/dvd8asBQMvOdPjPix6uDiWwwXzBpKbKd1nbzxacjgIAmraG29kN3LSCioH2xOi98UF7oieux+2x3zSHtwxqG6e1pbGZ0/wRAMrvP8EXtrw8R+czjEylDJ4/Uaw2nJKYDE2rgaIOTMU4rS2NzdwaEzZrZpLI5Efbwu+M/Q4ASGTy4G+8XX7lL8vK1Vkam4XPqHFIZPKk2APxc3Y/WPILLumlpTbi15BBAeMAwNDTacJfux8sOhjl8T3uT4etc/HUgyiMvIf3HWr25lrim2uJgwLGSutwSXxOQGeHAD/mifm0MP5r/tW4gwLGDvAd6Xl7V+qKo/Qpm3GhzvAhY8LWKYsu5DE42EuBqpi+7veYSRsAgEQmm852dz64FF+kQxAa6OTBLCHEYxWB+KIgtbWJz98jEDKHRPpffTWCEfjVV1+tWrWKd3ICAE+fPg0JCUlOTm5HowwGY/DgwTdv3hRc3H7jxo3p06e/ePHC3Lz9ezVlTkBAgKen5/z5/McNcHn06JGTk9OqVasOHfqk0FpUVNSkSZN8fHz++usv7p3ffPPNs2fPhKnpLCQ3DwCmTJkSGRl54cIFvn1SQUFBK1ascHR0hC6kx1m+bNkyDw8Psbs2JO+XPHSqu5ATL4WGhhoYGHx++5UQoiCRSIva4rvbCn7ofj8WR6Uv+PjfHPXB0kMl0emBRX8SP9iGYe9y3rRhbVo2JtKW/MQfZ2a/pqop46Uf+BBqA8ZprUrNpWqoaNkMEnwEAGrzipoqa/VcbQTPYSkIj6lOfyF074YoCLQ1VTAvGM50ObKcr1wFMbjHPr5732+UNbHOsrgnmpbGgnP1VnZLZXKOimFf7lYLXpjZryjKNHVTg/xTd5MWHvC+d8Dw30OOhNLKbiGRybgl7XM4EHqp48g8BHwaal8U97U35ctFEtDwuvxD6T86zkME95oRhKZ7B7Ogo+KD9rw8R5fDf4u6kj9IY/mmJ5JMWxCfAWg3DUJOyc7OLiws1NPT45OTyeSRI4Wf7iaWx48fA4CTk5DdmPHx8bq6unKVFqmpqbl58yZxOZWUlBQAGDt2LJ/83bt3AMD7HtvR0bGpqSk1NbUTLJWBeQAwb948ADh37hyvcOPGjYGBgV0/D++5lhMjeb96UKdkDvISAkGA7Vr/DyU1JTEZxLeRyGQtm0F97UzbkRbBH+9rZyo0LSLKBjJFQc/VhmCWrmkxwGCcveBMsqWx+cXvkSYz3KSyUJQ2AHhx4i9lg77mCycJXiIA95i+m51YnQbj7IUuYVCgKhqMsxeaFgEALZtB6qYGktujQFXkWtI+hwOhlzqOzEPAi7KelsE4e8nTIgCgZqKv52ojtAQPQWi6dzB33FEIxOcEyowg5BR8EvLbb79h/9apwtHS0vr2228F72cwGFFRUa9fvybQmZ6eTqPRDAyE/GWQnJw8btw4PmFqamphYSH+O4ZhCQkJcXFxXHs4HE5MTExGhsi/DvEbsrOzhV5tbGyMiYkpKflfPfP8/Hy+hTDR0dEjRoyg0YiqhSckJJDJZHd3dz75hQsXAMDf359XOGLEiJs3bxJokzlSmefr66umpkan06uqqnBJWFiYsbFxu3dOdYSeazkxkverB3VK5iAvIRC8tHFa44P2JM7fh39UM9G3WvV/Ep4100nI1oaW903mCyYZSH/msXBtjc3PD18f/vMigiK18qBTKuQh6JLT7e6Sim4czHyOenHir/igPZXJz2ViCQLRE0GZEYScMmrUKF1d3fv375uami5duvTGjRsNDQ0AYGBgYGxszHtnWlqam5sbvr599+7dQUFBgtr2798fEBBw+fJlLS2tgICAgIAA/OSIyMjIgICAyZMnP336tLi4OCAgYNGiRfgjBw8eLC4u9vf3j4iIiI2N3bBhQ11dXUZGhqmpaVVVVVhY2L59+zgczqlTp3jrlXAJDw8fNWpUU1NTYmLizz//7OrqmpaWxr0aGRm5c+dODoezZMmSEydOHDx4MDExMS4uztn5v53bdDrd1NRUUDMXDMNiYmLs7Oy4p6XgxMbGxsTErF69mq9miru7e+b/s3fncVVUbRzAf3O57Aiyq6wiIgmIihqC+4KKu2bupuVSuWWZpVma+lZWZppauacmWm7hGoIKggiIAgICIjsiIIFs4uVy5/1j8HK5G1wWUXm+Hz/vh5k5c+Y5Z3qzOZzznIgIJRU2LVXD4/F4U6dOFYlER44c4YrFxcUtWrRIbuUFBQWWlpZubspmAr+ckbcgldr1qjSqyVEvESLJxM3BcmSfioLiioJi8cleX88VPClL8w1pwcCaMAad9saO85vsd+ZR3x21GNLTfsbQpqqwyevUszaz8nbXMjFQ6a6X4aXXU3O8gmbVUv8wS3VUZenTioLitm/YWCnOIkTI643yjJCWUZ8Fe/7+/lOmTCkqKuIO+Xz+d999x6UUFfP19Z09e3ZgYGD37t25M507d164cOGnn34qW6GBgcGMGTN+/fVXqfOySUaEQuEnn3yybdu2KVOmREREfPLJJ0uXLuUuqaurDxkyZPny5d7e3gDi4+OdnJxCQ0MlBzW2bdu2efPm6OhoblfgOXPmHD58ODo6ulu3bgASEhKOHTu2fv16Lv7p06dv2rRpxYoV7dq1KykpKSsr4yoZMmTIlClTPvjgA0X9Ex4e/uabb44ZM0bc2NLS0oCAgAsXLqxbt042ley5c+cmT5787JnCvFwbNmy4c+eOoquSjh8/LrUZR+PDAxAcHNy/f39nZ2cfH58ff/zx4MGDiipPSUnp0qWLnp5eQUGBkt1YGqZZI5fVJN1enzwjqrarMY16db08vUR5RlqblzPPCCGEtDaUZ6TVor1pyMtr2LBh+fn5586du3z5sr+/f1JS0sqVKz09PcVjECkpKVOnTv3yyy/FwyIAnJ2djx07JjsyUlhYWFxcPHDgQNkHXb161djYWDLJyLlz54YPHw4gMjLS3t5ePCwiEAiEQmHXrl25YREADx8+BFBeXi6+Nz4+/uOPP96+fTs3LALAwMBAT0+PGxYB8Msvv2zZsoX7OS8vr7y8nNtSd+/evWZmZuJ6IiMjxRNY5Lp+/ToAa2trbv4LAC0trenTp4srl6KlpcXFr2g30FWrVgmFQiVPFKtzWKQB4QHo16+fjY1NbGzsunXruJULitjZ2cXFxWlrazf5sAiaOXJZTdvtSqjarjoblZSUtGfPHldX11mzZjUmsJfKC+il/Pz8r776qnfv3mlpaY6OjspzCRFCCCGEkBeARkbIS43P50+YMIH7rel33323evXqkydPikdG1q5dKxQKly1bJnlLdnZ2enq6bFVcVkW5OVaDgoKkcgoMHDjQ0NAwJycnNTX1m29q9nXz9/dH7UQD9+7d4/F4AwYMEJ/ZsGEDj8d77733xGeCg4Ml8w5s2rRJnD3E39/f2dnZ0NAQwJgxYyRjEAgEypOMcHlJ1qxZIzdziixuQEQqb4sk5Y9Tlarhcdzc3NLT03fs2FFnMA4ODo2KT7HmjlxK03a7Eg1ol5JG+fn5FRUVxcTEuLi4NHGgLeoF9NLChQunTp3KTT9xcnJydnYWD5sSQgghhJAWQXlGyMto27ZtsidXrVrF4/FKS0u5Q5FI9Pfffw8bNkxPT09cRigU3rlzR+7EkNjYWD6fL/sFUlxcHBMTI7UPBTdUERgYCKB///7i88HBwVpaWpILZ06ePOnl5SWehSEUCk+ePDlw4EDxN1J5eXlMTMygQYOkKudcu3atX79+cjuBx+MpGcXgsiHY2NjU//utnhMTmkQDwuNcv37dwcFBdk+iF+bVjVy5hrVLSaO8vLzefvttqWQcr7oX0Ev5+fm+vr5vvfUWdzho0KA9e/Y0MmxCCCGEENJINGeEvIyCgoKWL18udZIbJhgxYgR3+OTJE6FQaGdnJ1nm1KlTQqFw7NixsnVGRkZ269ZNdvEFNw1EPJiSnp4uzvAq+40kNfsjJyfn+vXru3btEt8YFRUlFAr79OkjLuPn5ycSibj6s7OzJWtLSkrKzc3llu1wDczNzRV/X1laWkou0pESHh5eUVEhOVelTgKBgMfjKVmRsWXLlujo6PpUtX//fkVLchocHoCkpKT8/HzxSqUW8eIjb8JuV6IB7XoZXscL9gJ6idshS/we3dzcuOythBBCCCGkBdHICHnpREVFiffKlXTo0CEbG5tx48Zxh7q6ujwez9nZWbLMTz/91LNnTy5th5TIyEi5szMCAgLESUaioqKuX78uzioSFBQk+Y0kFApDQkK+++478Zljx47xeLyZM2cC+N///rd7924jIyMAklEFBgbq6ek5OzuHh4cnJyfPmDFjy5Ytffv29fDwuHr1KgDxdJUzZ87o6emJR0a6du2akJCgqJe4xUEqbQ5aXFysfEbD2LFjXV1d66xH8ruuCcPD84UM9bwrJiZGS0urydfUvIDIpTRhtyvRgHY1plGNFBsbq6OjIznuKXVGtkCTeAG9VFxcLDk6yefzFW3sTQghhBBCXhgaGSEvnevXr8fExJw7d04y70ZycvL69eu5kQjujIaGxpgxYwIDA8W7t3z33XePHj3ivm2kCASC1NTUFStWyF4qKCjw9PQEIBKJfvrpJ/HWErJJRrjZH1xhzo0bN8aNG6enp3fq1CkujaKdnZ2Dg0NOTg5X4ObNm4cPH+aW0ly6dGnx4sUXLlxYuXLlhx9+6OHh8ffff/P5fG5xTWlpqa+vr+TGFq6urnFxcYp6iZvqIhlMneLj4xWt3OE4ODg01UBDA8IDcPHiRdRevqRIUlKSq6tr+/btuQy4Tai5I5fVhN2uRAPa1ZhGNUZycrKLi0vbtm3FGw9JnZEt0FReQC+JRCI1NTXJM1VVVfV/HCGEEEIIaQ40MkJeOkFBQT4+Pvv27Ttx4oS3t7eOjk5UVNTJkyePHTvm4eEhWXLv3r2TJ0/esGGDs7Ozr6+vtrb2nTt3JLN4SNYJQO5v5hcuXLh8+fJTp05duHBh48aN4g+tsLAwHo8n+cFz69YtY2NjySQjM2fO/P777/fu3ZuRkbFhwwbu5OHDhxcsWGBlZZWUlKSpqXnmzJkFCxYcOXKkoqLC2NjYwcHB0dGxd+/eK1as+O67737++ecVK1b07t37ypUrP/zwg2Rgw4YN27t3r1S0paWlM2fOzM/PDw0NBTB79mxjY+PTp0/Xp2PDwsKmTJlSn5IN1rDwBALB1KlT8/PzuVGt6dOnm5qanjx5Uskt7dq1s7GxKSgoKC8vb5JUFy8s8hesAe1q8UaZmZnZ29tbWFiI/88odUa2QCO9yF7S09N7+vSp+FAoFFpaWja6BYQQQgghpFEY2paZtAglG4PfvHmTG32IjY2NiooSCASWlpbDhg1T9BWUnp6enp7u4eGhZK3Bzp07V61aVVJSIreSwsLCe/fuubu7S14ViUTJycmSv8wvLi5+8uSJlZWV5L2ZmZllZWVSW94IhcLg4OCePXvq6+tz9d+/f1+cfEQoFN64ccPd3Z2bVJ+UlFRRUSF3cwpbW1tfX98m2beivLzc2Nj44cOHckeOXlEHDx6cNm3aC9vb5WW2ePHi4cOHc7s4vUgTJ06cOHHinDlzXvBzXy2SvZScnNylS5fKykru3zYrVqzIysr6+++/Ze/auXOnhYXFi3+npKUwDLOQvdrSURBCSGu3mxks9Xmi5LOFvE5ozgh56YgnZTg7O0ulEZHLxsZGnDNVSlJS0tWrVxctWhQSEjJ9+nRFYyuGhoZSs1EA8Hg8qTUO+vr63EiHJKmBEg6fz5fajEYyJyufz5dMX6JkJcXy5csPHDiwdetWRQXqb9++fXPnzn2dhkUA3L17V25OGUJeWvb29vb29leuXOF2Co+IiHj//fdbOijy8orbeebxnfvuP7yvadhGfLI897+IL/YB6PX1XF0LU6nz7Tycu7w7KvloQPaV21K1GdhbtOvn0q6fyjttX5v7XadpQ6xG9qm7aKPlBMUkHfq3++czDOxrEpZLBcCKRCl/XcvyjxQJhLqWpvYzhho5d5Stqiw7/+Ynvw4+8gWPryZ7tf7ls6/cST7qX1UhMHXr4jB3hPhdxP/q+6ywpMeamaq28VHw3eKUHKmTliN66ZgbKamzOOXh9YVbBh9eo9PeWNUn1qmi4ImWsYHkGck+b6YOr38NTf4KCCFEFo2MkNfZ1KlTY2JiZs+efe3atStXrrR0OCpbvny5q6ur1I42DSAQCPbu3Xvp0qWmCuxlkJ+f/5oN9LxaDh06dOXKlWvXriUlJQUHBy9ZsqRJJje9ZuT20tatW9evX+/i4hISEmJgYDBr1qyWDpO8vITlzxL3XbD2frPjpJrx9IcBdxL3XQBg7t7Vcf5o8fmcwJjEfRfMejsCeBQSy5WR1Wnq4KHHvqp/DNE/HH8UEjtw/6oGtkFFT5IyE/ddcJgzQjwyIhXAs8KS88NWPr6dZNLTQdfSNP3sjahv//Tcsdxpca0JVsLyCv+pG3JDYgcdWg3U/aGuqHzw4m3xu84YOnfUszS9ufLXmC3Hx4fu1LMyA2Azrq+P3cx2/VzaD1Dt3363Nx7O8ouQOjk2cJuOuZGSOrMvR/4Xm9rkwyJFCRmXJ6/ru22J5TA38UnJPm+mDpf1Il8BIYTIopER8jrr3bu3h4fHunXrlixZIrXg5ZXA4/H+/PPPZcuWNTLLw+rVq7/44gvlG9O8cjZs2PDtt9+2dBSt15w5c2gRTZ3k9pK3t3fv3r3DwsI6dOhw/vz5FgmMvCo6DO4O4NH1u5IjI+m+IQYOVoInpdn+kZIjI9zHtpX3m+IzI89/a+1dkxurKCkzcO7mB8evtuvfTeqzVpHy3P8i1x8cuO9TpkmzHdefbABhn+1+fDvJ659NtuM8AVSWPr3o/XnIkm0dBnc37GrLlSnLzr88eV1e2L16PkVR+YwLN+N3nXH5+O2+Wz4AUBif9o/n0quzvxl77WcAuhamzssmBX+wdUrcAZUa9fBalKVX7x5f1BoVNenZWXmdmZfCm2PaTl54QmF8muQZqT5vqg4XFJcVRD0wdLKRmpyivIZmegWEECKrZf6eI+TF2L1799SpU2fOnLlmzZqWjqWBunXrtmjRovXr1ze4hqNHj9rZ2b399ttNF9RL4ZdfftHT02vpKF4iP//885w5c27evNnSgZC6mZqajhkzRjKds6RDhw7NmTPn8OHDLzgq8hIy7dVFXU87L6JmB3dWJMo4f7PDkB4dBnVP+yeEFYnEl/LC7unbW3C/S5errYPVwIOfAci8FF7PAKK/P65pqNdp2hCp85LPFasSVCqvjRWJ5N6oqELZAFiRKOmPfy29enNf6QDU9bS7fz4dQLrvDe7M3a0n/uo6rygx06hbJ+Xx1Fk+7pfTaloafb6dzx0adrV1WT45JzBaPJTgtGRCYXza/SOX6/MgTkn6I5Gg0mpkn/YDukn+UdfTVlInKxKlnwu1GVdr5a+SDlfUn/W5KtnnTdjheeEJZwcuf3T9ruylF/wKCCFELpozQl5zkhk9XlFeXl729vYNvr1///5yk6GQ18ny5cszMjIAdOwoZ+03ebW4u7t36NABCrbTIq2N9Wj3lJNBrEjE/QI/90ZcZelTqxG9qyoED45fzQmK6TCoOwBBcVlhbOob749TXltbBysApRl5AEKWbhc+fSa32MC9nwKoElTe+81XclpKwLQNPA11875OIcu28/hqgw581mnakPtHLkf/cLwwNpULsl1/F4/tS42ff+IGTNsAoMv80aErdhbGpnIFBuz9VLxYJs03JPyz3UUJGQxfrcu8UUYuduLHyQbAitihPmu1TNpKRsvTUAcgKC7nDm99td/Sq7fH9iW31h38L+ZBnT2spHyWf6TNmL5qGuriM6Z9HAE8vBrFTZdoY9OuXf9u8bv+6TxreJ0P4jyOTAJg0EXhplRy68y+cgci1mKYG4Cn+UVhn/6W7HNFJKhk+Grt+3fz2L5UnPgj/Vxo+Ge7C+PTGL6a/fShHSf1D5z/g9epje0HdJN9fVn+kSnHrwK4PPFLTWP9GWnHpPq8OTpcVtO+gowLN6/O+dZhtlffrYsbEAwhpNWikRFCXgF2dnZ1F1KAhkVaAwcHByWpfMmrhd4mkWQxzO3B8asPr0VbDOkBIMvvFsPjWXm/KXhSBiDbP5IbGcn2jwRgNaK38tpyb8YDMHzDGkDSwUuVpU/lFuNGRjLOhQrLKyyG16SfEJQ8LUl5kOwTYDvOszynwMDROm7nmZAl26xG9umxegZPg58XlhDz01+XvD+fkXGcG8oRlDwtupeefjb0jYVjeqyemRsaF7fj9MVRn027fwRAmm+I3/i1xt3th/y5lhWJojb7pPx9Tfw42QB4fDXJhUWczPM3uY7iDidG/NbW0brunn1OUXlBcRkrrNI0rpV53byvE4DHd+6Lz1h69br15f7SzDwls3UkPb59n/vfG8t3lKTkaBrrO7wzwm3dO+I5I3LrzLwYbta3q4a+LgC/iV8WJWS4//iBno1ZeXbBrXUHfPsvm5n5l7qeNtef5p7OXv9sgojlEpo8KyjmZpfIvj4tM0OI2MQDFx0XjjVy6QiZPm+ODpfVtK9AJBA+KygWlJQ3JiRCSCtEIyOEEEIIIS+pDkN6AMi7Gc+NjGReCm/X30VNQ13btK1xd/uM8zd7b3oPwMOrUdyIieS9VRUC8dhHSdqj/PCEiLX7AHBTS+aVyE/RKpZ1ORISH8CcooSMAXtWiucU/DvuC8OutqMubuYOO04aUFUhiN1+Mv9Wklmf6vReJak5Q/5caz9jKAD7GUOrnlUm7DmXfyvRtFeXm5/8qmdjPj7kF76OFgCbcR5/O78rKCpVEoB0kH4Rd38+0X6gK9c/AFT9SldUPv9WEgA1TQ3Jk3xdLQAigVB8xqibHYDckFg9mTVHchXGpQG4t/ucwxwvLWODlJOBMT8ezw2JHRe8XZxLRbbObP/IjhP7ARCWV+SGxLqumu68dCJ3ScNAN27H6cL4dLM+jjc/+VXXymy0/xa+lgYAi2FufzvPk3y61OsDUJaVn3jgotWoPlwG1jr7XNUOTzx4iRVWASi8l8HVX/H4CXdJHEbTvgLbCf1oA2xCSAPQyAghhBBCyEtK365Dm47tuSUYzwpL8iMS+ny7gLtk6dU7+nsfbr/V3Btx3IiJ5L2XJ6+Tqo2nod735yXcNJM6lWXl83W0uG9sMYbHc5g7Unw4I81HauKJlqkBAEFxmeQtnaYNFh+aezgl7Dn3NK+wKCGjODm7xxezuGERABr6uo7vjor8+g8lAUjK8ov4d/xaPRvzocdV2G2nnpQk4xAJq8Q/c2s68sLuyWZjkUvP2tzhnREe25dyE0BcVrx1/YOt937zjdv5j3iwQ6rO8tz//ot50P/XFQB4Guo8DfX7h/2MXTvZTurP19KwnzGUG3Xi+rPbyqniHlPX0+7yrnfkuprspFKvT5byPm9Ah99Yul3yn5D4XWfEP0sO0MjVTK+AEELkopERQgghhJCXV4dB3ZN9AgBk/RsBid/nWwx3i/7eJ/typO2k/gVRyb02vit1o/OyydwSCQAMj6dp1KbDkB7cBzmA5KMBkp+XkhzmeAEQPClT05b+QubraPL4NTuqMjxeSdqj1BNBT5IyS7Py8yMSRTJpQfk6mpJb24h/LkrKxPPPWrG2EodyAxBLOuQXOG9zG7v244K26ZgbKSrWYDrt5NTJilgAaho1//2sa2kKoKKgGEBOUEzUZh/xJfO+XaSPKIEAACAASURBVHuunS1Vg8e2JVJnem2Yd+8334dXbotHRiTrBPAw4I66nra5hxMAHl9twJ6VgfM2X5m5ieHxzD2dbcZ6dJ4zXMfciOtPY9daSUyNnG0lD6Venywlfd6wDp9T8E91K67cuTjqs6HH19lO8KznvQ14BYQQ0mA0MkIIIYQQ8vKyHNkn8cDFwvi0tDPBWqZtTXt14c5bDOnB8NUyL4Wr6WiyIlGH56sbam4c0Uty114p1xdtUZRnhBsZqaoQ1Blb5IZDkesO8HW0LL16GbnYOS+ZWJySE/HF3no1TMQCYHiM5Dkev2YMRUkAoZ/8evenv9r17zbin02ahm3q9TgVGThYAqisna6iNCMXgLaCcYGKx0WPgqLFhxoGuvV5kLZpW56GupLGpvuGWI+ueY8Oc7wsh7ulnAjK8ovIvBT+6HpM5PqDY65ulXuvqtstKwqjwR0unsfE8NUAqGnwpWY2KdGAV0AIIQ1GIyOEEEIIIS8vq5G9AeTfSsoJirEa2Ud8nuHxrL3dC6IfaJm21WirZ+7eVaVqZ+WcVF5A29yQS4qhyJPk7Mh1B8z7Oo25tlX8uRu5/mA9A+B+1V+UlCV5sjznvzoDCJz/Q+K+C52mDx18aLXyGRCNoaahrtPeuDjloeTJwthUAGZvOorPPCt4gufJLzpOGiCbr1RSWXZ++Oq9pr0dxdNDAFSWPhUJKvkSGVgl6wSQcf5mv19XiK9WCSr5ulrOSyc6L50oElbd+/1syJJt0Zt9em2cB+C/u6mSTxQn9agnuX3+YjpcVgNeASGENBiNjBBCXh9snB9zYo30WYYHXSPY94XnPJg0Kn9+03q1oiWEtBQNfV2Tng73D/1bnlNgXTvHqtXIPiHLtmsY6Na5K40syc1Q5NI2bSssr6gSVCr6JX9RQgYAm3EekgVSTwcDkF1TI8u0VxddK7PkP/27fz5dXEPSH/8qD+DON38m7rvwxvvj+ksMFjQTuymDYrefLErK5HY7BpCw57yaloalV01vF0Q/ANDO07k+Feq0N049GfTwWpTjgtHiXB5xO04DsBnrIbfO3JvxlaVPLYb25C5xu894bF/Gja3w+GpdPxh346MdrEhk2NVW397iwfErbl/PFVeeuP9ivZr6PKOHbJ83VYdrmRhYebtrmxmqdFeTvwJCCFFEtSl2hBDyCtA3R5dB1X8cBsK+L6oqEXUWu2chL7mlg5PxakVLCGkJHYb0yA64zfB4lrVHQDoM7cEKq3ICo63H9G3yh1p69cLz/YDlMnVz4Gmox+04nXsjrkpQmXsj7vywT54kZeJ5Mog6uX+/6ElS5sWRn2VfuZN7I+7y5HXcV66iAMpz/+PyswrLKq7O+VbyT32GANLPhR5o4x2ydHt9YgPgumqqup72xZGfZV4KL0rKDFm6PfNSeI8vZkkOKv0XkwJAvMRJVpZfxIE23kELtwBgeLxeG+aVZeZd8v784bWoooSM25sOh6/e036gK7eCSbbOrEvhRt066bQ35i7ZjOnbpmP7iDV77v1+Ni88Ics/8sqMTaywqtPUwQD67Vxemp57wevTLP/I3JvxATM25YbGKW8jl7Dj3p7zSYf8INPnjexwSSbd7Ued/5bLllJ/DXgFqr5lQgjh0JwRQshrx7YXJn5d6wwrwskvEHcZl7dh5i8tFJYCr1a0hJCWYDG0Z8yPx017d5FK8dDWwapNx/YlqTniOQVNyHpMX4avlhMYoyhZiU5742HHvwqc/8M/nksAMHw1pw8n9P5mwZk3P8i7GW9Tj8GaTtOGiIRVoR/vOj/0YwDG3e3f/G5h6Mc7FQXwMOAONxvl/mE/qap4Gvwu745S/jhWWFVZ+lT49FmdgXF0LUxHXdx8dc63F0d9xjWwxxezpJKqZl4KN3TuqGTnWpGwqrL0qTh/R7dP3mZ4vFvrD54bvAIAw+N1ec/b4+daaVkl68zyj+RGKzgMjzfa/8ers765/v5P3BlNY/2+Py/htmWx9Oo94uw31xduuTB8JQDj7vZu694R7/Ujl5X3myY9HVJPBKaeCOw0bbBUnzeywxuvAa9A1bdMCCEchmXrNahPSNNimOqMa/RPIGlC1etTuo2WHmsAUF6IH4aD4eHLm2Beiulyr1a0hJBmxTDMQvZqS0ch7foHWzMvhs1IO6akDCsS/RebyopY4252qub7FNdQEJOioa+jb9ehAQGoJPHgpbywe6ouDCmMTyt/VNh+QDepLBvlOQV/Wr7tsX2p0+IJKlXIddqz/0ra9XNRXmf2lTuGTjaye8FUCSofBcfqWpqIl5lIKoh5wNfRMrC3SNh7PmjBj96Xf7R8vqWRXFWCSobH4yJp8j5vEiq9goa9ZUI4u5nBUp8n9NnSStB/cBNCWgcdQ/DUwYogkr9L5cvl1YqWEPKacv10allmfualcCVlGB7PuFsnk+72DRsW4Wow6W4vOyxSzwDqr7L06b3ffO2mDFL1RsOuthZDesgmH733+1kdCxPHBaNVrZDrtA6DutdZp8WQHnK3yFXTULcY0kPusAgA426dDOwt6h+Pmoa6OJKm7fOmUv9X0OC3TAhp5WhkhBDSOjzOgKgS6lpQq+9+gS3p1YqWEPKa0rfr4PzRW/XfbuYlD6CypNxx/mgLme2NG1hb6dO7206++d3C+m9D2yJ1qqrFX3r9ye2upn3LhJDWg0ZGCCGtQH4KTq0BgB6qTXhuGa9WtISQ11qvr+cKnpSl+Ya8BgHotDd2nK/y/A5For47ajGkp/2MoU1VYXPUqWdtZuXtrmVioNJdLf7S60ludzXtWyaEtB6UZ4S0DFqwR5pDdeYOnjo0dWrOPiuHqBIAzDrh3f3Q1G2p8KS8WtESQprVy5lnhBBCWhvKM9Jq0d40pJUpLWBTw5jU2xAKwDDQN4dFVzj0B0965WpDiKoQfQ7pdyASQUMHnrNhqMIq35fLhe+hoY1hS6sPk4IgEskpxuOBpwErF+kP+NLHuLSFdRzEOI9o9lDrZNgBJh1h64bebylcnJIUhJiLbJ8pjHXT7++gmvpESwghhBBCCGk6NDJCWo2KYlz6CTEXGFbmC1/bAAPmw316o+qvqsTBhci6W3PGoT8MLdiH8UxGdGMrf8Gu70fEX+xb3zLiMyfWorJc2S3mndn+7zJOw6sP9UxQJWROr0e7LjCxbcZQ5XL2krPbi3KR/yApkBm4AAAKMtnsmPrfyti9CT0T1R4nqQHREkIIIYQQQpoOjYyQ1qGyAgcXIfc+AOgaw6Y71LUhEqE0H2m38fQJ/t2C/FSMXdPwR0T5Vg+LWLmiXRcIBbDpjsDfmWt7XrFsEY/TcPU3WDjXDHOIMTwwMpNruKUfufeZE6tRmIV+86rPD1uGxECcWY/5B5s34MZjRbgfDH1zmNoBwJMc5vQ6ANA1xsD5tUo+LUJpIaqEqHiCBzfxrAwApm1Bl4EvPGhCCCGEEEJI06CREdI6BB+sHhYZ/hE8ZtW6VPoYJ9ci7RZun8Ibg2Dv0cBHZN4FAGMbvLuv5mR2fANra0EXfwQrYr2WMbKXXEbJmd3Aiti4y8zFH1FeiCu/wnFw9SQRYyv0mIDbpxDli+7jmj3sxki9BbYKdn2qD+36wHUMos+hrAA8Htwmy7+rqhJ+PyP8OPusVE5fEUIIIYQQQl4RtDcNaR1unwEA5xHSwyIA9Eww/SfoGAJA6NGGP0L4DABMOja8hpcAmxmNlJsw76JCug2GxziPwOT/AQArQsSJmkt9ZwHA1d8hu4LppZJ0HUCteR/eq6BvDgD/bkVhtvy71NQx6lPY9mKy4po/REIIIYQQQkhzoZER0jqUPgbAdlYwH0RDB9zKkbRI+QWqKpF8A0lBbGoERFVNGZignKsZBZlSV9jMaCQFsVnR9ajhJpKCkBSC/JRGhsNc/Q0Aek9S+U67PtVDCUUPa06aWMPGDcW5iDrbyMCqiarY1IimfxGp4WB4taYLaeiwb30DAJUVOKF0jZXnHJQXvtBoCSGEEEIIIU2KVtOQ1oGnDlElc/8GuinY4r7fO3AYAFNr6fOF2QjYgfgAbtYDA4BRQ4/xGLwIesbVZY4ux/2Q6p8Tr+HrXgAwbDj8L1efvHMGd86Ap44vQ5ESjsMfQl0Hn1+F/07c/BPs829mGze89Q30jJFwDRe+Z0ryqp/YxgzjvoK9u3RsSUG4ths5CbVO6pnA853qhK/Fufh1GipKYGyLxX+BqRkJZdNvMwcXAkCfaRi1svpsQSZSI8DwIJthpD6MrFCcC6Gg1kmn4UiPRMTf6DG++tGpEczdf+uuzX0azOxrDssLEfAr7vzDsFWQfBFDF0PHoCHRipU+Rt4DWPcEX0PyNGPlir5zEHoID+MQtAcDFsi/3e5NBP8hfbL5oiWEEEIIIYQ0NRoZIa1Dt5GIOovYf6FrhH7vyNlJRN+8esqDBDYrmjmyDM/KwPBg4wY9I5QUIOM2bp9CwlXM2wcTawDQMoCeCSpKIHwGvia02gCAgb70SakdWH0+QnIodI3RwRFFOchPQXokjq9k+0xhTn0Fnjrs+6KiFFl3UZKH459gyd8w6FBz+80/8e9WANAzgaUL1Ph4VooH4Sh9jH+3oOoZPOdC35wd/Tlz8gsUpOHabgx+v/reimLm5FoAaO+IEStq6oy9AABW3aGlr3IPs6LqBLQa2rXOd+mPC98hJwGP07j8I8zjNNw5U3eFjoNrRkaePMS++SjJAwDrnmhjjKclSA3H7VN4EIr5B8QvlHHygpOXapEn3wCATr3lXBq2GA9CkPcA1/aw9p5Mh65yyvDUYGxT60yzRksIIYQQQghpajQyQlqHwe8jKRjlhQjzQfhxWDjBpiesXWHvCZ7MZiucimLGZyWelcGgPWb9It56ln0YzxxdgbICHF2OpSfB8DBpAwCcWI24y+jUF9N+rK7BeXX1dBKXURi3tlblleVIDsWQD9FvbvVUDr/tCD2ErLtMdjychmPcl9DQATfD4vBiCJ/htm/N0MaTh/DbBgA9JmDsmprJIKWPcehD5Kcg1AeecwEwziOQFIK7F3B9P5yGVY81/LMRJXnQ1MXU72s1/34oAFjI+/6vU+if1ZlWbGonKNE3h64xygqQHPI8M6uNwpk7tW40q/6BFeHoCpTkQc8EM7ehXZfq8wWZOLIERdk4/ineO9CQmDnJoQDYTu5ysqjy1DD5f/h9NkSVzIkv8OFxqXkl1SS3NGruaAkhRHUFMQ8S9118kpxdnJxt4GBp7NrJccHoNjbtpIpl+UfG/XJaWPZUp4PJ4EOrpQ4bGUNFwRMtY4WT5pRfbQ53t50sTs72/GWZogJxO88UJWQoKUAIIeR1QnlGSOugb45FR8BlFeVmN4T8AZ+PsakvDixEyEE5qSLCj6O8EIwaZu0UD4sAYDp0Zaf/CACFmbh1quEhOQxE/3drBjUGza/+uY0JJm3ihkUAMB17w74vAOQ9qLk3LgCsCFpt4L1Kco0M9EzY/nMBoKygJrHF6M+gbw5WhFNfAmCjzyLhKgB2zJpak1BYER7GA2CVjIyIhBCU1/rzKBEJ13DqK1zeBgBtzNBzvPRdli4AkBVbfWjXBxO/rvtPu87VccVd5trOTv+pZqABgLEVZmwFgKy7SAlXGLNyrAhJIdA2YCxc5Bcws8fQDwGgMLO6jcrra9ZoCSFEdTeW7zjpOj9ux2nBk1LDrjZlWfl3/nfkmP2su1tPSBYry86/NHp1tn8kX1fbwMFS6rAxARQlZPztNO/xneQGXG0+WX63kg5eUlIg2z9SeQFCCCGvE5ozQloNfXPM280+jGdi/fAgtHqggRUh4zYybuPK7xi8EP3m1ZSPvwIAbwyqXjIjgbFwgY0b0iORFIjebzUwnu61501o6ICvgcoK2PWRnsaiZQCgVgrPvjPhNJQtK2JkpjAwms9/5yZ8Vj28oqnLvvUNs/895N7HxR+ZO74A0GMC4zyi1p35KdW5VLTbKow59l/EKk4RotWGnfYj83xMp4ZOW6D2yI4qmDh/ALDuKWcxi6kdLJyRHYtYv5o9d1XBZkYxleVwUJpXxWM2Eq8j4zbCj7MuXoyla0tFSwghqrr+wdZ7v/laebv3/22FnlX1XLzC+DT/qRtCP94JHuOyvHpj8vzIJJGgst/O5Y7zRwNI8w2RPGyMvPCEwvi0hl1tQa6fTe/ynndLR0EIIeQFoZER0rowHbqiQ1fgIzwrQ0oY7t9A8g2U5EFUiYCdqCjFsKXVRbkveXsF29lYuSI9Eul1bRyjGKvVRmb5Bg8AzB1kgmYA1CRqBcDwYNCBEc/4qKpEfgpbkMFkx+FBqOyzGCtX9HsXwfsRfgwATO3gvUq6kHhvWrNOqrWE4cHIGg4D4DGDkU3gIq5Q0d63dUq7BQA8HhKuybmqpgEA/0nv7FNPzINwAKzjIDlLaSRN3ogdU2BkxZh1rqPG5oyWEEJUknsz/t5vvhZDe446/63kecOutuOCtp1weTds1e8dJ/WvHjERsQC0TJ4Pr0sdPlclqFTTUIcCImEVj69gjaqKWJGIFbEq1dbg2FiRCADDqzWT2txd/gzKxrSxCftHeXOk2tLknalqbE3YcEIIaSY0MkJaK01dvDEEbwwBgMRAnPsWpY8R8ge6j4WJLYQCbgJFdTpVGayJFQNAWNHg5zOmHRUEJjPnQgE2+iwT54+0O6gsB7cBihJD3se9ABSkA8DIlbL5MlihoLoGbcXpV51HYOwXtc4wPPA1aq3okY1TW48BqrOQAEi+UZ9VSOyAd6unXTwrA4C0W9WDDnLlNXQadnIoAMZOZt8fqWAKsxntNpi1HbIzYqQ0a7SEEKKK+F3/AOj9jZyttTQN2/T4Ynbwh1sTD1xy+2qO38Qvs/0jAVyd/Q1PU92wq23BnfviQ69TG9u+YR326W/JPldEgkqGr9a+fzeP7UuNnKv/IvsvNjX0ox0Pr0axIpGWaduu74/r+dUc7ks4cP4PKcevArg88UtNY/0Zacckw5B79VHw3fA1e3NDYsW19Vg7S8lX+v0jl6N/OF4Ym8qNCLTr7+Kxfalxt+pR/vxbiWGrfs8JjGZFIm1zQ+dlk3usmSm+N/vKndAVO/+LecDweOaezgP3rzKwt+AuXZ3zbU5QtDhgRW28sXzH/T8vT4r8XTJvS/iavfd2n30req+uhany/pGU5R8ZMG2DbAMth7kNPfZVnV0dMG0DT0PdvK9TyLLtPL7aoAOfdZo2RNXOfJpfpOhFB0zb8PhO8tTEQ+LCSYf8Qj/e6XVqY/sB3bjIu8wfHbJ425OkTIav5jh/dP9fVyQd8gv/fHd5TgFfR8v1s+luX81R9GhCCGlZNDJCXn/sw3imJJ/VactYKVgH0WUgjKyw620ASLwGk7kvIixeA38VAwCVFTiyjMm4XX2orgMbVxhYsB17gmWZk1/I3sFm32W4YREAoYcbuJqDx697aEAWN24iHj0pzEbitbpv6jmx+iduiMrSBUYyeyqLaeqqHBWAZ2V4GAfzLnXspPs4jTnzNWb9UrNPc21snB8j3mKm+aIlhBAVZV4K5+tomfVxlHvVdlK/4A+35oXGAXhj0VidDibxu850njPCpIe9mpZGbmi8+FC/U3u/iV8WJWS4//iBno1ZeXbBrXUHfPsvm5n5l7qedv6txHODV2ga6/fb9ZG2uWHO9bu3Nx4qiH4w4p9NAOxnDIOITTxw0XHhWCMX6V8JyF7N8ou4OOpzPRvzfrs+0jI1yLgQdnvjoUfBd8dc+UluK+J2nglZss1qZJ8eq2fwNPh5YQkxP/11yfvzGRnHGR4vLzzBt/8ynfZG/X//WNOoTcpf1yK+2Cssr+i96T0AwgrBpdGfd31/XI/VMwpiUqK+/fOC16fTU45yNVeWlD8rKOZ+VtJGuykDY7efTP4zQDzgwopEifsvGDl35IZFlPePJIPOFr2+rlnVy/B4aWeCs/wiDBys6gwDgKDkaUnKg2SfANtxnuU5BQaO1qp2JgAlL1pQ8rSi4IlkYZGg8llBcZWgknt6YVxqxvmbzssnG3a1Tdx/4d5vvmVZ+fkRCd0+maplahCz5a/IdQfMPZwsh7kpejohhLQgGhkhrz8maD8SrzGWLsr2BDG1g1YbVJSgIAtA9TwIVoSKEvl15j4AAL5WcwRcN/8d4IZFBi2A21viL3YGQFKQnPKCcubkVwDQ3hE5CUgORcTf6D1Fsgijrln907PyOkYKVMSUFwOomaVi6wbvz+q+zfz5f0Cr66CyHFau8PqoCaMCwCaHMAA6eyorVF6II0vZSV8zpnaKijDX/6jZfLfZoiWEEJWwIlFFfpHZm28oKqBjbsTw1XJvxgOwGtmnqkIQv+uM5XA32wn9AKjraYsPheUVuSGxrqumOy+tHrPWMNCN23G6MD7drI9jyJJtDF9tQtguHXMjALYT+mmbGoSv3pN5KdxqZB+LIT3KsvITD1y0GtVH9pNY9mrQwi1apgYTwnZpm7YF0HHSAD1r88h1BxIPXuoyd6RsK6I2+xh2tR11cTN32HHSgKoKQez2k/m3ksz6OIZ+tENNS0McW8dJA8oeFkRt9nFbPxcAK6wacOCzzrOGA+g0bYjgSVn8rjMFMQ/E803ElLdR394i2admZCT7yp2nuYV9nk/VUX6v5FPa2LRzWjxBfJjlH5ntH2k9pm+vDfPqWVVRQsaAPSvFqWGO2k5TqTOVv2jZ8lJK03OH/LnWfsZQADbjPA4ajMk4F/p24qG2DlYAzPo4/u00L+10MI2MEEJeTrQ3DWkFuDwXWXfxOENhGVYEoQAADJ8n7+AySiTfkF/+4T0AsFGWjLMZcVlUnYZj4CLpiQwl+XLKX/wBRdnQ1MW0LXhzOgD4/SzdG4bPtx54lNjE0XIZWwyr5yfD1A69p9T9R5xFxbYHAGQqSOmSFMLG+bEP4xsQF3PvKgDWXvFSGkE5jixlhy1hrHsqKsI+jEfb9jXHzRYtIYSoRCSsAqCpdCtcHl+NFbF1VsXTUOdpqN8/7Jd8NEBYIQBgP2Po+Bs7zPo4Ps0vygu7Zzvek/tW5zgtmQjgwbErqsacF55Qmp7r8M5I7kue47rybYbHyzgrJ4sWgBlpPuNDd0ie0TI1ACAoLhNWCHJD46RiG7h/1dTEQ9zyE4bH4z7jOe08nQGUZUn/NVpnGx3eGVEYm/o4qnql5P1DfmpaGvazhtXnXkX+i029PHmdcXf7Yce/qmcYXIscng95NKAzlbxoJaGKMTxep2mDuZ/V9bT5etpG3Tq1fT7hRd/eAoCw7Gl9qiKEkBeP5oyQVsB1DIIPgBXh1BrM+gU6hnLKXNtdnQijy4DqM10HITcR966hIBPGVpJl2YfxTHokANj3b97IFaksB57vWSOJFSHieQoPkbD6h4RriDoLACM/gb45hi5GYhCKsnFiNRYdrlnkYmLLTZNhnxbVkbJEVeVFAGBm38DbO/fH/RBk3WVTI5iOvWtdKs7FsY8ZtgpvTofsXjB1Sr0FviZj3V3+VVaE46vgNEx6E5/amOgL0JZIRtN80RJCiCrUNNQZvtp/d1MUFWBFoqoKgXilhhI8vtqAPSsD522+MnMTl4/DZqxH5znDdcyN8iMSACT7XEk/J/2xXfF8KUr9laQ9AmDiVisTOV9HS11fR9H+NQyPV5L2KPVE0JOkzNKs/PyIRJGgkrv0KPiubG3iNCIA+DqakplKGZ78v/3qbKPje96R6w7e/+Nfk+72VYLKZJ8Ah9leXC6PhvVPeU7BBa9P1XW1Rl74lq+jVc8wuBaJ05co78ycoJiozT7i8+Z9u/ZcO1vJi1YUau3Ka/UnT11N19JUqkx9RuIIIaRF0MgIaQWMreA5F8H7kZOAnW+j7ww49K/+UGdFSL2F8L+qM184j6j5gO8zFWF/obwQh97H7J0wseVOsw/jmaMrAMCgPdwmyDysNi6ZyMN7eFYGvgbUGpFbpFaLbFCQjgehqCiG1vOEqc/KcGY9cqtnfLC5yYxNT5QWwHcjANi5o/s4AFDXYieuYw4sRG4irv6OIR9U387wYOmCzGgm9XbN2pAmkXEHAKx7NPD2nuNx4zCKspkTa9i3vqkZbih9jOOrwFZBXQses1Su9lEiygvRdajC9LFnv4FBO3jOVVZJwjWEH8OwJc0eLSGEqK6dp/Oj63ef5hdJzhoQe3gtGoCpm8yGaPI4zPGyHO6WciIoyy8i81L4o+sxkesPjrm6lbtqN2WgeV8nqVvadGwnU0298Phy/rWs6Is6csOhyHUH+Dpall69jFzsnJdMLE7JifhiLwCIRAD4WtIZxxtGSRt12htbDHNL9gnou3Vx8tEAVljV5d1R9bxXVmXp04ven1eWlI+9vl12SELVrlbUmRWPix4F1Uxv1DCoToCl6EXXc9oIIYS8umhkhLQOQz/E02JEnkB5IQJ2ImAnGB4YNYgqa8rYuWPclzWHWvrs9B+ZQ0tRnItdb8PWDXqmePKoOu+pjiFmbJXd4UWaiQ0SgdxEfDcQANbKn7+qKnbwIubEGhRlY8cUdHKHujaeFiIpGMJn6P02Iv4CwDwtBoDT6/D0CTR1Mb6maYx1T7i9hcgTuL6PdfBgLJ+vCbJ3R2Y0su42SZDVHmfg6RMAsO/bwBrU1DFjKw4uQnkhc+gDWDjDyBrPynA/uHon48n/g765ytWmhANQmIk2aA8ehGL8uupikoSVQBWe5CHhGlJuAmDbdqj5PWMzRUsIIarrNHVITmB07LaTXMJRKXe3/g2g85x6DYVXCSr5ulrOSyc6L50oElbd+/1syJJt0Zt9ev/vPQAaBnqSCTIACCsEDRiS0DZrC6AoodbW5iJhVWVxeYdBcub3PUnOjlx3wLyv05hrW8X7rUSuP8j9YOTaCUBe2L03Fo0V35IXnpB5KdzxvVEylSmkb9cBdbWxy7yRAdM3Zl+5c/+Qn4GDVbt+LvW/V8rlyesKopJHXdxs0r3WXEtVq1LeTh4EWQAAIABJREFUmR0nDeg4aYDsXYpe9PCTXwMQVVZJFi6MS5PbBEIIeRVRnhHSaoz5nJ27G509wagBACuqGRYx64TxX2H2DqjXyqjKWLriAx90GQQAqRG4ewEZt8Gowe0tfHCsXstD+r0DiR1h2eymGXRgnLzYCeugY4iyAsScR+QJxAfAzB6zd8F7FTo4AUBiIML+4j7dMeJj6a9xr2UwaA+AObEWgvLqk04jASA3EaWPmyROAEi+DgAWzjV5RhrA1A4fHIPrGDBqyI7F3QtICgRbBStXdv4BdBnYkDrvhwBA537yYr6Jq7+jOBeHP5Tzx2c5fD7Ghe+q+xZgNPWaPVpCCFHdG4vGGHa1vfO/I7IpLSI3HMo4F2o1so/cEQcpab4h+zS9kv7w4w55fLWuH4xj+GqsSNTW0VrPxjz1ZOCzwpqE5ennQvdrj7j56W+1ahGJlD1DJALQfkA3LdO2SX/8WyWo+b1Fwp7zrEhk7uEse1NRQgYAm3EektvQpp4OBiASVOqYG7V1tM7yi+BSZnDidpy+/fUfkos+6lSfNtq9PUijrV7C7rM5gdEO74xQ6V5JgfN/yPKL8NyxXCo5awOqUrUzofRFA1DT4AtLn1aW1iQKyb5yR249hBDyKqI5I6QVYWx6wqYnWBFy76M4FyIR+Bro4KRsKxZDC0z7EaIqpERAVMVqajNWruCpySn51rd461vpk1r6mL0DVZVsTjzTvivDraZZd0v+s9bI21YGwMSvMfFr6ba4joXrWPZhPFNaCB4DS+eaZTUL/qgp9+bb8uvU0MFHZ6VPGluhY2+kRiDmkvSKD0Wx1Sn2MgC2z5TG5i7RM8aE9Rj/FZsRxTx7Km5yw6t1nw736fKnb9i7K3xH9dTk0RJCiOoYHm/Upc3/eC4NmL4x8cClzrOHq+tpl+f8l/THpbyweyY9HQYfWVOfemzG9G3TsX3Emj1qGnzjHp0FxWWJe8+zwqpOUwcD8Ni+1G/8Wt8By3v/7z3dDiYFUck3P/1Ny7Rtt5XVfwGpafAB3NtzvvxRoYPMFBWpq29+vyhw3ubzw1Z2/3y6rqVp9uXI8DV72zpaOz3fLUWSqZsDT0M9bsfp9gNcTXo5PL6VdOur/U+SMvF89U2fzQv9xq+9OHJVjzUzNY30031v3D/s98b743Tay9+FXZE628jweA5zRsRuP8nweA7veKl0r9jdbScT910w7m6vYaCbdMhP8lLnWcMYHq/+VXEhqdSZqOtFtx/gmnYm2H/KeqelE1kRG/fL6fKcApW6kRBCXmY0MkJaH4aHdl3QrosKt/DUYO8OblvcBlBTr1mx0qSYpk7kyQ5awKRGIPps0+TCyE9Bdiz0zRkXFeYtK8PwGBuF28So5gXM3WjCaAkhpEH0rMzeit57e9ORhL3ns/wiuJO6FiZuX8/r/vl0yakWSjA83mj/H6/O+ub6+z9xZzSN9fv+vKTTtCEAbMd5ev2z6cayX/zGr+Wumr35xsD9q8Q5Mqy83zTp6ZB6IjD1RGCnaYOlHip1tcvckWoa6mGrfrs0ejX3aPuZw9y3fCB3wYhOe+Nhx78KnP/DP55LADB8NacPJ/T+ZsGZNz/IuxlvM6av7TjPocfX3fx454URq7gCLh+/7f7DIlW7sc42AnCYNzJ2+0mLYW66Fqaq3st5HJkEoCAq+ersb6QudZo2WE2DV/+qOCp1Jup60c7LJxUlZSbsPpd5KRxAx7cGevy85MrMTUp7jhBCXhkMy1KOaNICGKZ6kIH+CXzpHFiIjNvsnF+lt1ZpgLPf4PYpjPsSPcY3RWSEEPLaYhhmIXu1WR9RlJRZmpFn+Ia11Kd7/VUJKh8Fx+pamrSVt6NNeU5B4b0Mkx72moZt5N7L8HjinVPqvFqc8rAs67GZ+xt1Dt+wItF/samsiDXuZqdomUxxysPyhwVm7l0VBVBPytvYfPc2sqr6dyZHyYuuElTm3ogzcumopXRDaEJeXbuZwVKfJ/TZ0krQyAhpGfSvmJfXo/v4fTosnDH/YKPqefIQ2ybArBPe96m7MCGEtG4vYGSEEEJInWhkpNWiDKyEkNradYbnO8iORWJgo+rx3wkAkzY2SVCEEEIIIYQQ0kwozwghRMbQxagoQ2ZMw5NxlD4GK2LHf8nUZwcfQgghhBBCCGk5tJqGtAyalkYIIYSI0WoaQgh5GdBqmlaLVtMQQgghhBBCCCGk9aKREUIIIYQQQgghhLReNDJCCCGEEEIIIYSQ1otGRgghhBBCCCGEENJ60cgIIYQQQgghhBBCWi8aGSGEEEIIIYQQQkjrRSMjhBBCCCGEEEIIab1oZIQQQgghhBBCCCGtF7+lAyCEEEIIIc3l4bWopIOXnuYWsiJWXU+7XT8XxwWj1fW0G1/z3W0nS9Me9d26uME1VBQ80TI2aHwkTShu55mihAzPX5bJvZoTFJN06N/un88wsLeQutT43nglyPaP+CUq7zpCCHnJ0ZwRQgghhJDXU8jS7ecGr7j/p7+oUsjw1fIiEkI/3nncYXZRUmbjK8/yu5V02K9h9xYlZPztNO/xneTGh9G0sv0jkw5eUnT1SVJm4r4L5Q8LZC81pjdeIZL9I/USlXcdIYS85GjOCCGEEELIayjLPzJux+mOkwYMPryar6PFnXzw17WAqV/7T/n6rei9LRhbXnhCYXxaCwagiOtn07u8593SUby8JPtH6iVS1xFCXmk0MkJeOvn5uHePFR+6uDCGhircnpOD+/fZdu0YBwcAiI/H48c1h1KCglgARkaMs7OcqzdusEIh3niDMTTEjRusbAEzM8bODhoa0udzc5GYyJqYMF27qhC5qiRb2iTNNDWFSITgYBZA9+6Mvr785968yQoE6NKFMTcH6tHYlBRkZdX0nocHw6d/8RBCSPN7cOwKAPefPhAPiwDo9PagtFNBD45fLUrKbOtgJVleJKzi8dUU1VYlqFTTUK/Pc5XXoxwrErEiVqXb6x9YfR5k7i7nLzNWJGJ4DZ9nrSRC2ZpZkQiAksep2r1KytfZ27KRy+2fOi81LLw6g2nkgxrzDyoh5PVDHyjkpRMQwE6fzogPz5+Htyq/gTh/HgsWMLNn49AhADh2DBs3Mp6eCA6WLpmQgIEDGQBt26KwUPpqeTk8PRkAd+9CW7u6pFw2NpgzB2vWQOv5f3n++y/7zjvMhAk4fVqFyFUl2dImaaapKYTC6sKXL2PYMPnPHTOGKSjAH3+wc+YwqEdjt2zBrl01vVdSAj29BjSXEEKIavjamgAK49La2LSTPN9n80L7WcM1Ddtwh/m3EsNW/Z4TGM2KRNrmhs7LJvdYM1Nc+P6Ry9E/HC+MTeW+4dv1d/HYvtS4WyfZx/0Xmxr60Y6HV6NYkUjLtG3X98f1/GqO3C/PwPk/pBy/CuDyxC81jfVnpB0D8Cj4bviavbkhseLbe6ydpeRLWFFgN5bvuP/n5UmRv0u2OnzN3nu7z74VvVfXwlT5g67O+TYnKJoLCUCab0j4Z7uLEjIYvlqXeaOMXOzq1fV1dV3AtA08DXXzvk4hy7bz+GqDDnzWadqQ9HOhYZ/+VpSQwfB4NuM87KYMClm2feixryyHuanUvVz9ADrNGBqyZHtZZh5PQ/2NhWN6/+89DX1droDyTniaXxT26W/JPldEgkqGr9a+fzeP7UuNnDtK9o/sS5TsujrfQv2boyQYrqWP7yRPTTwkLp90yC/0451epza2H9CN64cu80eHLN72JCmT4as5zh/d/9cVSYf8wj/fXZ5TwNfRcv1suttXc+r/WgkhrysaGSEvKRub6i9za+tG1TNkCLtxIxMWBpEIUr+AOX+++oeiIty8ybq71xr78PMDAFNTODujtLT6ZPv2tWoQCFBSgvR0bNwIf38EBaGlZkM0STObiacn++wZA2DfvuZ6BCGEEFmOC0bH7/onYOqGrh9OsB7t3q6fMzcToY1NO/H3al54gm//ZTrtjfr//rGmUZuUv65FfLFXWF7Re9N7AOJ2nglZss1qZJ8eq2fwNPh5YQkxP/11yfvzGRnHpSY15N9KPDd4haaxfr9dH2mbG+Zcv3t746GC6Acj/tkkG5j9jGEQsYkHLjouHGvk0hFAll/ExVGf69mY99v1kZapQcaFsNsbDz0Kvjvmyk9ym6YkMLspA2O3n0z+M0A8vsOKRIn7Lxg5d9S1MK3zQZUl5c8Kirmf03xD/MavNe5uP+TPtaxIFLXZJ+Xva/XsfOVdJyh5WpLyINknwHacZ3lOgYGjddqZYL+JXxp16zTkz7UAon84Fvje91UVApGgUtXuBSAoefpfdHLKyaDeG9816mb3+Pb9W1/uf3zn/vjgX+rT234TvyxKyHD/8QM9G7Py7IJb6w749l82M/MvdT1tcf/IvkTJrlP+FlRqjpJguJZWFDyRLC8SVD4rKK4SVHJXC+NSM87fdF4+2bCrbeL+C/d+8y3Lys+PSOj2yVQtU4OYLX9Frjtg7uHEDT8RQlozGhkhL6kePbC3KVZADxjA8PkQCnHtGjtkiJxBgUmTcOoULlxg3N1r3Xj9OgCMHFnrZFKS9HwHkQjbtuHjjxEaim3b8MknADB0KHP+PMzMWEDhTJOm1bTNVEmdjZ0xg5kxA6CREUIIebGMu3UacfZ/ge9+H/29T/T3PgxfrcNAV8sRfTrPGa5jbsSVCf1oh5qWxoSwXdyZjpMGlD0siNrs47Z+Lo+vFrXZx7Cr7aiLm7nCHScNqKoQxG4/mX8ryayPo+SzQpZsY/hq4npsJ/TTNjUIX70n81K41cg+UoFZDOlRlpWfeOCi1ag+3Bdp0MItWqYGE8J2aZu25R6kZ20eue5A4sFLXebK+StKSWDt+rno21sk+9R8k2dfufM0t7DPNwtUfdDNT37VszEfH/ILtxzJZpzH387vCopKUQ91dl1RQsaAPSsd54/mCvw77gt9e4sJoTu4Z9lO6n/abZE4i4dK3cspy37c/7eP31g0FoC1t7uapkbYqt9STwV1nDRAeScIyytyQ2JdV013XjqRq0rDQDdux+nC+HTJly77EiUpfwv1b049g1GiND13yJ9r7WcMBWAzzuOgwZiMc6FvJx7ilpKZ9XH822le2ulgGhkhhNDeNOQ1x+NVL8aJjKz13S4U4soVmJpi6VIWgL+/9I2hoQAwcqSc9CJS9a9YgalTAeDo0eqTFhbw9kavXi9oWATN30wlXnxjCSGE1JO1t/vMrL+9Tm90eGdEG9t22QG3w1b9dtR6WuL+iwCEFYLc0Djb8Z7igRIAA/evmpp4iFvXMCPNZ3zoDskKtUwNAAiKyyRPPs0vygu7J1WP05KJeJ7rRLm88ITS9FyHd0ZyH+oc15VvMzxextlQubcoD8zhnRGFsamPo6r3TLl/yE9NS8N+1jCVHlSUkFGcnN151nBxlhYNfV3Hd0fV2Zz6RAiA4fEcno/F5IUnlGXmOb7nLX4WX0uj64fjuZ8b1r1qWhqOC0aLD7t+MA5AyomgOjuBp6HO01C/f9gv+WiAsEIAwH7G0PE3dtRzJEJM0VtQqTmND4bh8TpNG8z9rK6nzdfTNurWSZxhR9/eAoCw7KlKTSOEvJZozgh5tRUU4PffERODykq4umLxYjllhgyBry9u3qx18tw5CIUYORIDBjBaWggLQ2EhxKlehUKEhQHAiBH1+uD39maPH2fi46sPk5Nx7RpsbRWm6miAOlv6ApopVxM2ViiESKSsAI/XYuuVCCHkFcXjq9lO6Gc7oR+A8pyC+0f873xzJPC979s6WleWVwAwcauVu9vA3kL8M8PjlaQ9Sj0R9CQpszQrPz8ikVvcISU/IgFAss+V9HPS4wsVz5dXKFGS9kg2DL6Olrq+jqL9a5QH5vied+S6g/f/+Neku32VoDLZJ8BhtpeahrpKD+I2Njbsait5sm3tQyXq7Dq+jqY4rQYXmIGDpWQBPRtz7oeGda95XyfJFU/qetp8HS3Bk7I6O4HHVxuwZ2XgvM1XZm5ieDxzT2ebsR6S84zqSdFbUKk5jQ+Gr6Mp2Q88dTVdS1OpMqyo4b8fIoS8Nugjg7zC/P0xZQqKiqoPT53Crl14913pYgMHAs8XlYhdvgwA3t4sj8d4e+PUKfz7LzttWvUAgZ8fRCJ07w5j43pFIhAwQM1H+40b7IIFzIQJTTYyUp+WvoBmytWEjZ01C8ePKyswdSqOHWvsUwghpDUQCauSjwZom7WVXJ6g097Y9dOppr27nBu84t7us9wSA76WzBZrz0VuOBS57gBfR8vSq5eRi53zkonFKTkRX8hf7Go3ZaB5Xyepk206tpNbWBaPL2cis6JPVuWB6bQ3thjmluwT0Hfr4uSjAaywqovEXI/6PkjEAmB4tX5zIPfeBkTYAKp2r5q2ppLalHeCwxwvy+FuKSeCsvwiMi+FP7oeE7n+4JirW1WaNqL8LdS/OU0SDCGE1IlGRsirKjsbkyejuBjvvYeNG2FujitXMH8+vv1WuiT35V9QgIQEOD7/a5QbQRg+nAHg5VWdg2PatOqr3A4v9f/U51KieHk1qkWK1LOlTdvMioqavLMvjJ5eHWM0tKkNIYTUE8NjAudtNvs/e+cdF8XRxvHfLiecSFMEREQsBFFRsWPDhoJorCl2jRqNCdaoiYmJJvqaqFGjscZOYktiVFRUBASkCEpsdM+KiogEFEQ8j7v3j8XjOI69PThafL4f/zhmn515nmefOW9mZ57p2rJkHgprt1YACqSyeu2aA3gSnchlo+B4EpOUeibGeeog2Utp7NI9Nt1aDwlZrzy1JHbZ3pJtmTVrCMDQ3KT1Z8NVy2X5Up5pFyW1rS0AZCelqhbKZQWvn+c17ONaUv6Z5KFWxVp85BU0ZvnD4Cs3fQPMnewb9Gyja0PcyoLslAeqhXlp/2o1R6CGqpg1swXwb9zdpiPdlYW599LfXC2Le5/GJhcTzsuX5eUbmtcR4oQC6WtRHbHLrBEus0bIZQWJ209E+Gy4turggCPfabVdFY1PQVdztCojf12gKp8Vf1cnJQmCIDgozwhRU/npJzx/jiFDsHMnbG3BsvDwwIULRUfnqsIN/mNiCl+GpKRAIkGHDoXj8P79AcDfv0g+MhIABgzQooNcjrAwxbBhhXtSPvusQlZjCrdUj2a++y5MTTX/y8zUs4FKdu7E06d8//SSlJcgCOJtgGHZxkO6pUfFJ2z1U7t07ccDAGx7tTW2qWfh3PhBwCUugwNH/Kaj/3y3j2HZ7KT7AByGdlc9OvfO0XAAahtDLJwbmzjY3DkS+iorR1l472TU7tqeFxdu49NSLgdg695WbGWRsu9sgUq1STtOKeRym+4aDk4TolizD/oYWpgk/XoiLfSa0yRPrlCnhqw6tahjby3ZH6gqnLLvLJ85umio1pa5k33ybn+lA2V5+QlbjnOfy+bel+lZaWHXlX8m7jgFoNl77lqdcNcvYpfRwJR9hWtQWZFBq5lDGZGBorT9rqXvg9X4FHQyR6syBoYiWe7L17lFiUIeBl8pTR+CIAgeaGaEqKlw2y5mzSpWaG+PUaM0CHMZRgMDC9fEnj0LAIPeLOp0dISjIzIzcfmyAoBMhogIiEQaFlOYmoJhiv4ZGKB3b8bPDwAWL4baoTD6Qril+jITgFgMExPN/wiCIIgaQY9Ns8VWFuGfrj/e3ef62j9uHQqO++XoiT5zY7/bZ9OtdcsZQwB0WTX9xcOnp70WPQi4lHE5+fK3e27+FuA8fYixraVVRyfWsFb8pqPpkfEF0tfpkfGnPD5/lpIKTXtPum+c9TI9y899zl2/iIzLyUk7T52fsFJsZdF2wQcadTMwFAFI3HEqxTeAYdmuq2c8S0k95bHgvv/FzOu3rq/9I3LuJgvnxq3fnEiiihDFGJZ1muh56/B5AE6TBioLdWrIbfWMZympp72+eBh8JT0y/tyopZnXbgnxvE6u4+ixeU7uvfTj3X0Stvolbj9xrJtP7oOMMruX49x7S2/+fu7pVcmNDUeiF21v0Ktt05HuWp3gMKSbaVPbS1/tSNx+4klM0oPA2OCxKxSyguYf9lWrX/UhalRA41PQyRytyti6t1PI5YHvL7vvf/HeySh/z0V5aRX2AocgiP80tJuGqJFIpUhLA4A+fdQvDRyo2L9ffYaC204S9SbVF3dEi4dH0UGzAwdCIkFgINOpE8LCFDIZM2QIWG0zhyIR7OzQvTumT1f06VMh0yI6WapHM0+cKHUzUf36FbhshCAIgtAXJvbW713beenrXSm/BaRHxXOFtUxqt5n7XqflU7i0lE2G9uh/eOnF+Zv9PRcBYEQGbeZ/4LZmBgBjW0uPw9+GTltzvIcPd6n1p8M7r/z4WNeZTy4mOAzpptpWk6E9Bh5fETn7l4BhS7gS664te+9eVFqmTHvvrvU7ON35K/TOX6HNR/dtMdnLwLBW9KJtZwYvBsCwrOM4D7e1MzVurxComNNHXnEbj9h5dKxjV5RxU6eGmo/uJ5cVRM3fcqr/fACWro5df5weNX+zVs/r5DqORh4dBweti122N2L2RpHYsMUU77qtHC58sq5s7gVQy6S2y+yRIR+tUsgKGJZtPqZfj19mC3ECw7KDA386P36lsnUjS7NuP/s0H91PrQm1h6hRDY1PQbg5WpVxmTMyOyU16deTqWdiADR9r3f3n32Cx60ozS0EQRClwSgUlI2ZqAIYpnCsXjICDx1SjBnDDB+Oo0dLvf3ePTRpApEIr0ssSj12DCNGYMIE+PoWK3/nHUgk+PdfmJqidm2IRHjxomhSgLvL2xunTuH777F0KX7+GXPmFF7NzYWpKQDk5AhaNOHrq5g0SYsJAtHV0vKYCUAqhZERAJw7p2VmZN8+xcSJjE7Gcs+cx4fTpuHYMb4ahg+nDTUEQfw3YRhmuuJ8BVWukMuf307LufvYpJGVuVMjRtOM+PPbj/IeZVq7tVIemKK899+4Owq5wrJtM403qpGXlpmVeL9+e0ejuqZahQukrxmWVW3x+e1HLx48tXZrqboPpTSjdFJMDZ0ayrx+29DMmEuQIRydNHyVlaPmsbhfjkbO3jjyyo76ro7KQoHuPT148eOwax/l+HMrVqy7OCvPA1aF3wkF0tePw+PqNKqvPONWIyUfonCERwu/MpyZ9do0FVual0ENglDlV6av2vCEZ9hC/JegNSNEjcTMDChlZ2tp211794ZEgtBQiMWQyTBqVLG1EtzSieBg4M2aC61JRioHXS2toWZy5OZqWY1S+UlhCYIg/gMwLGvuaKd6HG9JzJo11DjyZ1jWsm1z4W0Z21oa2wo98KzkgLw0NcqvWHkaUp2bEI5OGvpaj2js7eZ5vGixQ/Ju/1omtS3bNlMV08m9AAwMa2nMYsvB7wQDw1p2/doLaUK4PmoIN4dfGX4zCYIghEB5Rogaibk5WBZyOe7dU7+Unq75Fm9vAIiIKDyQpW/xVZ8iEXr1Qn4+rl9HYCDs7NCqld61Lgu6WlpDzeTYuxc5OXz/9u6tahUJgiAIogJwmuR5zy8iaPT3yXvPxG8+drTLzMyrki4/Ti/DchiCIAiiDNCaEaJGwrLo3Rvnz+OPP7BwYbFLR45ovmXgQLAs4uLw6hXwZgZBTSA0FHv2QCbT4bzeikZXS2uomRwazxUiCIIgiP88vXcuNG3S4NbB4DtHwxmWse7acuDxFU2G9ihbbdadWwg5L5kgCIJQQjMjRE1lwQKcP48VK+DpibZtCwsPHFAEBWnOhGpigo4dERICmQyOjrAvsU3Vw0Px9dcMdxDM0KEVp3gRhw4ppFI4OcHNjS97q06WVkMzK5PAQDx6pHB0RPfuDE+hRjGCIAiCqEI6LJnQYckEvVTVcdlkvdRDEATx9kAr9Iiairc3pk7F8+fo3BnTp2PrVowYgXHjGMfS9wL37Yv8fMhk8PLScLVLF8bSEmlpYFn1TSgVhI8PM2kS89tvWgbnulpa3cysTH78EZMmMbt3M/yFGsUIgiAIgiAIgng7oZkRogazcyd++AFiMXbswKefws8Pn3yCVatKle/fv/CDp6dmAW53SefOqFtX37qWD50srblmEgRBEARBEARBVD50ai9RNZTz1F5V5HKEhyvy8piuXWveUH/ECLRujRUrtEuihlsKAaf2EgRBvLVU6Km9BEEQhEDo1N63FsozQtR4WBbu7jVyW0RuLkJCMHWqUPmaaylBEARBEARBEES1hXbTEESVMWoU2rXDkCFVrQdBEARBEARBEMRbDM2MENUUPz8YGcHICGfOVLUqFcbatQgOrmolKp45cwofJUEQBEEQBEEQRDWEdtMQ1Y6GDeHtXfRnvXoK4L+5hcTFpao1qBScnApzvnKI6FuHIAiCIAiCIIjqBGVgJaoGSmVEEARBEEooAytBEER1gDKwvrXQbhqCIAiCIAiCIAiCIN5eaF07QRAEQRBEzUP6/EXU/C1sLVG39Z+JxIaqlwqkry9+vpVhWbe1M1mRQcl7HwTGxv9yVPbipXHD+n19F5dTk/zMZ2JL83JWokSPusVvPvb0yk23NZ8Y1TVVFual/3vp610AOn03uY6dlVp5g+4uBmLDh8H/qFVl7mjXoGebBj3bVFy7LaYMSgu7nuJ7trXPiPqujmp1Ju8+/TgyzvXLseaOdkLtLyucGjq1pd8YqBLKYLXw2/Xb4wiCqAhozQhBEARBEETNw9Csjkkjq8RtfhE+G9QuRfhsjN901LprS43TIi8eZpwZvPhhYKyoTm1zp0bl0SE76f6frT96ekVSnkoqSDcAsrxXybv8H52/olr4KOhK8i7/5F3+qadjVMvTQq8n7/KXv5Y9jojjBFT/xSze4ddrdtDo7yuuXQDPUlKTd/nn3n1css5HIVeTd/nnPcoUaHt54NQQ2JbeY6Cq0MlqnW7Xb1QTBFFB0JoRgiAIgiCIGknHZZMfBFxO3uXvMLR7k6E9uELJgaCkHSdbTPV2HNtf411abarAAAAgAElEQVQZsSly6euem+c4TxtcTgWexCRlJdwtZyWq6FE3AA37ugJ4fOFG05HuysJ7fhHmTvbSZ7kPA2NVW3kQcAmAvXfXzOu3AXid+qGxt5vyanZKaujkVbcOn2/Qq23rz4ZXRLvls7XK0HsM/PfQb1QTBFFB0JoRgiAIgiCIGoBCLlfI5WqF/Q9/W8usTti0n/LS/wXwTPLwwoy1dVs16bFpTqkVyRUAxPU17H0okL7m10EuKxCoKo9kSSu06la2Cq06tahlUvvJpSRVyfunLjbs175hH9e7xyNUb3wSnWjmaGdib62xKgsn+957vwCQeiZGo0AFtat3yvhc3qA1QgS2pWtVGoNfYEP8AkKsLuftPD2u7D1FmG78nuH3annaLUND5VSV53aB31oEQWtGCIIgCIIgqinc9o0W0wZHzducFXeHYdkGvdq471yozGVgYm/da+u84HErzo/7n5f/jwHDlijkigFHv1fLPKIkYMQ3DwNjAZyfsJI1qjXw7+W27m1v/n7u2prDWXF3FHI510T3jbMs2zZX3pVxOTl60fa00GsKuby2TV2X2aPafzUudNqa24fPAzg34hsjS7Oxdw8BeBx+I+arnekRcQq5XGxl0eqToe2XjDcwrMXZwhrWsunWOmL2RlZk0GfPF81H99OqW3kqBNB4sNvtI2GcXQDSI+Nf57609+xckC+9dfh8Wtj1hn1cAUifv8iKu9Pyk6E8z8LCyR5A7v0nQh6cHtvVStDo759ekXyY7KssSfENiJq/mXMg3kRR87H9I3w2vkh9whrWajl9SOf/TTU0q8PJ3/WLiPni1+yk+4zIoMVHg+q1aabWRGkRojEG/o27EzV306PzV5WPrMO3E5Ubu15mZEcv3CY5GCyXvmZEBra92nbfOKueS1ONdoE3+Pkb0iqg1epy3s6hMapRvp6CUrqk8ip/5TxejZyz6eb+cyNjt5s6NFDWFvPVzsRfT7x3bWcdOysen2hU+97JqOiF27KT7jMs6zC0e7P3+0TM3tj/0LeNPDpqdbLWAOD3g9bwIAg1aGaEIAiCIAiimiLNeZmdeO/eiaiW04e0XzwuPSo+ftPR04O+GH3zd6WM49j+905G3ToYdMJ9TlbC3b6/fcWN4TXScsa7xg3rJ2w59s5Ez/rtHc2a28ZvPhbhs8Heq0v7xWNZQ9GT6KTr6/444/3l2PuHuVH9k5gkv16zjW3r9do+36ie6e0/Qi59vVOWl+841gNyRfKe087T363XpimABwGXTg/60sTBpueWuWIr8/v+0f8s930cfmNI8DrOlpzbtyQHg5oM7ZGXlmnu3FirbuWsEICdR8dbh88/Crlm1689gAcBlxmWtffuKn32AsDDwFhuhoIbu9p7duZ5FukXEwDUbamhlQptVyvSnJf5mc9US+TS168ynysXZUhzXv57TXL7SFjn5VPqtW329J+bl7/Z/fTKzWHhvwC46xcRMGyJpatjv/1LFHL51VUHb/8ZolobT4SUjIGMy8kn+84zsjTruWVubZu6aRdu/LPcN/PaLc/jK7jaAkZ8k5103+2nmSYO1nkPMy8v3ePXa/a41D9qmdQuaRdP8GttiF9Aq9XlvF1JyahGuXtKaV2y84qpQirn8Wqz93vHbTwi2R+knF9QyOXJu/3ruTStY2fF75OSat89Fh4w4pt6bZv3278EwLU1h0Knri7Il8rfRKbWCvm//Xj8oDU8CKIkNDNCEARBEARRfcm5k9Zv/xIuaYjj2P4Fr14n7TiZcTnZqlMLpYz7r58/Dr/xJDrRcZzHO+MH8NRm79WlIF+asOVYowEdmwzvCeDqqoN1WzUZdHoVJ9B0pHtBvjRu45GMyynWXZwBRM3dZCA2HB69xdimHifw4lHm1VUHOy6b/OJBRvKe0/aDunBvgMOmrxVbmQ+P3lLbyoKTNGlsE7t0T/LeMy0mewHITrrvvmNBadkWSup2vMes8lQIoGG/9gCeXEzgZihSz8Q06NXGwLBWbSsLS1fH+6cucoPJR+evcjMXyhsL8qWvc18WPoK7jzNiki4t2QVA4PqOMrcLIGDEN0Ka0IkXD5/22ja/5Yx3ATT2djMwMoxetO3O32FNR7pf/HyriYPNsIhfRMZiAA5Du//pMkWanau8lydC7Pq1V4uBCJ8NjMhAGS1NhvesbWUes3hH6pkYe68usrz89Ii4dovGuMwawdVmaF4nftPRrIR7XLCpwRP8/A1p1USr1eW8XUnJqEa5ewpPl2RFBlor5/Fqg55tzBztJAeLZkYeBl95mZ7VZeXHWn1SUu2zQ782c7QbHrWJ81KTkb2OdpyhmpVGa4X83348ftBaM0GUhGZGiGrH8+e4elVRsrxDB8bEpGKbTk9HcrKifn2mVSs91CaTITJSgyHW1kyzZjDUvMy5upCQgKdPFQ0aME5OGq6GhSkA1KvHuLhouBoZqZDJ0LIlU7duhXhAL7pZWiI8XAHA1ZUxM9Pc0MWLCqkULVowNjaCFIuMVKSkYPJkRuNVubywxdI0ByCV4uJFBYCWLRkrK/WrMhkCAvD0qUIqZUxMFG3bqgcqp7ChIdzcNOugKlaaizRSbX2uR/WsrCqqzyofPT+tWzOWloCOXx3lfOiqQVvmL0CJBCEh+OADlPZYyyBJqMKwbPPRfZV/2nRvnbTj5MsnWaoyL59kcYsRMi4ly/KlpW2l0cjYuweVUwAcYitzANLnLwDI8qXpUfHvTBjIDTA4eu9exLCM2rr0JzFJuffS2y0aw43HONot+OCf7/bdPxHFDckYlnWa7CVQMb1UaNasoWlT26exKQBeZeVkXErq8sPH3KVGAztfW32QO242PTKem7lQ3nhu1FK1qljDWt1+9uHWemilzO0CsOvfwaRJA7UK00KvPZc8FNK0RgzEhs4fFw2zW80cGr1o2+2/wuq2avJc8rD91+O5sSsAQ7M6zlMGxX63TynMHyGqvMzIfhKd6DTJUzVaWvuMiFm849ahYHuvLqxhLdaw1s3fAizbNW8yspdIbOg4tn9pqYJRevBrbYhfwLRJA36ry3k7P+UMbP4uKbBynq8Up0mel7/Z/fSqhDs6+qZvgIHY0HG8h1afq6n9JCbpReqTLj98rPSSSGzY6tNhyrO0BFZYmqo8fniVlaO1ZoIoCc2MENWOmBgMGKD5J76JCaZNw/LlqKApkrNnFZMmMcOH4+hRPdSWn4/evUsdqzg4YOJEfPUVxGI9tKV3Dh3C8uVMjx4ID1e/lJRUaJeFBbKy1K/m5aFHDwbAjRuoXbtCPKAX3czNCyXPnYOHh+aGhgxhMjOxb59i4kS+MSdHaioGDWKmTy9VgGXh68vs2gUzM8TFwV7TUvc5c7BtG9OqFWJji5Wnp2PZMuzcCZkMAKcMA6BtW2zerOjZs1C9CxeYRYsA4OxZDByoWY3AwML+deQIhM+MVE+f61c9K6uK6rMyGV+1So4exfDhgI5fHeV56GpBW+YvwAYNsGQJQkLw++96kyRUERkbcbtaOFQ/cyjk8sD3v5Pl5Tcf0//WwaCoeZt7bZ0nvH6GZXPuPr7zV9izlNTcBxkZl5LlKqkxH4ffAFC/Y7F5R9V9/kpy7j4uKSkyFtcyM1a+JRYZGwnf56+vChv2cZUcDALw4OwlAHZvEhzYDeh4bfXBh+dim4zslXlV0mn5FNW7XGaP4raHAGBY1qieacN+7ZWJOYRQtnYBtPYZoVxcoOT8xB/KMzNi0621auTUMqktMhZLn73ITkkFULdVE1Vhi+J/8keIKhmXkgBIDgbfOxmldik/8zkAVmTgvmNB6EergsetYFjWpoeLw7vd35k4QHUEq0ppwa+1IX4BrVaX83Z+yhnY/F1SYOU8XynOU71jl+69ue9sfVfHAulrycEgpwkDDQxrafW5mtqcJmqnFJs4FL33EFhhaary+OG+/0WtNRNESWhmhKi+2NoWfpDLIZMhJwe5ufj5ZwQHIzq6mk4oaERpCIdUipwc3LuH5csRGIiwMIiqX0fs10+xfDkTHQ25HGo/wk+dKvyQnY2LFxVqb6oDAgDAygouLsh9s6pUvx7Qi25SqQ4tCuGTT8Cy+IZ3BfTGjQgNhUSCMWM0jOEPHFBs28YYG+Po0WLhHRmpGD6cyciASIShQ9GmDezsEB2NwEBcv45evZiDBxWjRzMAFi7E0aOIisL06YiL0zCBmJeHKVMAYNw4jBypg3XV0+f6VU+VCuqzFhaorb6PvoiS32lC1CjPQxcStEIwMcHXX2P2bIwdC29v/UgSOhE1b8vTf1I6/2+a65djshPvJW7zsx/URXmIr1Ziv/eNXbpHZCxuNLBTvTbNXHxGPL+ddunrnYWX5XIAwhehsCIN5x4q5NqXTVVchY28uiTvOZ2VcPfusXCxlYVyF5Jdv/aMyCD1TIyBsZFCLuf2vxTd5dlJ9dTeMlC2disIg9pGmi/IFQAYtth3o5rPtURICZq939umW2u1QtOmhatgnCYObDSg4+2/wh4EXEo9E/P4wvXYZXuHnF+vcTcNP/wN8QjIpTJos7r8t/NT9sAW0CXL02uMbS3tPDpKDgZ1W/+Z5ECQQlbQYsog5VWtPteVsleozQ96V5X4z1P9BmQE8YZHj9RLzpzB++/j+nWsXInvv68KncpESor6cEUux4YNmD8fUVHYsAGff15FmpWOuzsjEkEmQ0iIol8/DYPJkSPx99/w92fciv9uvHABALyKrwDVrwf0q5teOHMG/v743/+07BEwNsaff6JjR0REYMUKLFlSdEkiwYwZDICtWxVOTkVGpaZi8GAmOxt9+2L//qKh8syZyM/H5Mk4fBjjxjFt24LbAeHrizZtcO8evv4aGzaoK/DFF0hNhZ0dtmzRzcBq6PMKVa+C+uzx4wp3dx3WwghUo2wPvWTQ9u/PnDoFa2vFm3VJOvDZZ1i7FnPmwMtLfXKqzJKEQO76RcRtPGLbux2XF6D/4W+PtJsWNu0n6xstS3sPr8ozycPYpXtsurUeErJeuacjdtlepUC9ds0BPIlO5FJUcDyJSUo9E+M8dZBqVbWtLQBkJ6WqFsplBa+f5wncgaKGviq09+oMIONySlrYddWF9AzLNvZ2y7x2S2xlYWhhYuOmj520VdSu/HWxc0mz4u+qCTyNTVb9U5aXL8vLNzSvU6eRFYDslAeqV/PS/lV+1hohqpg1awjA0Nyk9WfDizWnssOrQPpaVEfsMmuEy6wRcllB4vYTET4brq06OODIdwKNFdIQv0DG5WR+q8t5Oz/lDGz+LqmXXtPiI6+gMcsfBl+56Rtg7mTfoGcbCHu4qpg1swXwb9zdpiPdlYW599JVBHSrUA0eP3Cn/5S5ZuKthX6VEDUJLy/MmwdAP7tdqhCWxbx5+PBDADhwoKq10QTLFr7RjY0tNkaSyRAcDCsrzJqlABAYqH5jVBQAeHlpeS9RHg9UtG5lYPFiGBrCx0e7pKsr/vc/AFi6FDExhZrk52PYMOTmYtIkqO0i8fFBdjbatoW/v/oKArEYBw6gVSvI5Vi4sLDQ0RE//ggAGzeq57YID1ds2gQAvr4KXbM8VEOfV7J61aTPalSjbA+9ZNDa2cHbG5066Twtwin22WeQSLB9u94kCSHkpj4JmfSjkaVZ/8PfciUWTvZuP83Mz8gOHiPoCIbspPsAHIZ2V011cedoOABux4SxTT0L58YPAi7J8ovWfcVvOvrPd/uKVrbL5QBs3duKrSxS9p0tUNlqkbTjlEIut+kuePOeCvqq0NCsTv0OTjd9z+alZTYunuvU3qvLv3F3Mi4llfN0mKpt18BQJMt9qZoK5GHwFTWZl+lZaWHXlX8m7jgFoNl77ladWtSxt5bsD1R1csq+s8rPWiOkELkcgIVzYxMHmztHQl9l5Siv3DsZtbu258WF2wDc9YvYZTQwZV8Ad4kVGbSaOZQRGSjkcp1M1toQv4BWq8t5Oz/lDGz+LqmXXtPsgz6GFiZJv55IC73mNMmTK9TqczWsOrUwd7JP3u2vlJfl5SdsOa4U0LVC4X6waGFfnpqJtxaaGSFqGC4uCgAZGerlGRnYvBkTJ2LECIwahenTceaMhtvlchw4oODERo/G+vV4rm2/4eXLip07sXOndkld8fZWAEhIKPxTIsHOnUhJwcOHmDYNo0Zh7Vrk5xdp7utbpPmaNepO4G4PD1fk52PtWowejVGjsHAhkpLKqF6/fgBw8WKxwpMnIZPBywvu7oxYjOjoYrkbZDJERwOAp6egwZWaB6qVbsIJC1NcvYpRo4QmlfzyS/TuDbkc48Yx3POdPh0JCWjVSv2tvkQCPz8AWL9eoXH7GMti6VKFjQ3MzaH8VTlnDnr0AICPP2aUG1ik0sI5l/nzobaqQiDVyudVpV6ZI1a/lFRD14euMWi575CS80dqnDmDnTsL89qqMnkyWBYbN2rXX7gkwY9CLg98f5k0O7f37kXFEg1+Ntzeq8uj81eur/1DayVWHZ1Yw1rxm46mR8YXSF+nR8af8vj8WUoqVNbed1k1/cXDp6e9Fj0IuJRxOfnyt3tu/hbgPH2Isa2lgaEIQOKOUym+AQzLdl0941lK6imPBff9L2Zev3V97R+RczdZODdu/eYgEp3QY4UN+7V/GPQPw7KNis9ENOzfXiErSAu91nhIN13Vu3cyao+pd8QsvlCuiHZLYuvejguG+/4X752M8vdclJeWWVLs3HtLb/5+7ulVyY0NR6IXbW/Qqy33Mt9t9YxnKamnvb54GHwlPTL+3KilmdduKe/SGiGqMQCg+8ZZL9Oz/Nzn3PWLyLicnLTz1PkJK8VWFm0XfADAYUg306a2l77akbj9xJOYpAeBscFjVyhkBc0/7FtSYX74G9IqwG91+W/nofyBzdMl9dJrGJZ1muh56/B5AE6TilJYafW5Gj02z8m9l368u0/CVr/E7SeOdfPJfVDsx6uuFQr3QzlrJt5OaDcNUcO4epUB1BMNHjqkmDqVycsrVrhjB3r3RnBw0YJtiQSDByMlpWiEcPgwfvgBfn7q2QeUBAcrBg9m8vOxaZP+D1OQShmgKGFBZKTi44+Zdeuwfj1SUwHg2DGMHg07OyQkYNgwSCTFNP/+e+zfj6FDi90+ZgyTmIirVwsPsJBKsW4dNm3CzJk6q9e7N/BmM4KSc+cAwNtbwbKMtzf+/htnzxYmueCE5XK4uoI7YkNXD1Qr3YSzcycD4L33dLhl/364uEAiweLF6NZN8dtvjKEhDh+GsXExsePHAcDSkm8u44MPmA9K/C/v64vWrZGUhJUrsWwZAHzzDe7cgbNz4YqVMlCtfF5V6pU5YvWLRjV0eugag5b7Dhk+vNT8uBw//YSgIEydyri7Fyu3skKvXggN1ZDPRQ3hkgQ/FxdufxKd6PzxkJIpRfr4Lv6z9UfRi7bbDeho2bY5TyXGtpYeh78NnbbmeA8fAIzIoPWnwzuv/PhY15lPLiY4DOkGoMnQHv0PL704f7O/5yJOps38D9zWzABg7921fgenO3+F3vkrtPnovi0mexkY1opetO3M4MUAGJZ1HOfhtnZmmVew66tCu/4drv902KpzC6O6pqrlFk72pk1tc+6k2fXvoKtuClnB69yXspevKrndkrjMGZmdkpr068nUMzEAmr7Xu/vPPsHjii0aqmVS22X2yJCPVilkBQzLNh/Tr8cvs7lLzUf3k8sKouZvOdV/PgBLV8euP06Pmr+Zu6o1QtRioMnQHgOPr4ic/UvAsMIto9ZdWyon7xiWHRz40/nxKy98so67amRp1u1nn+aj++lqNX9DWgX4rS7/7fyUM7B5umT5K+dw+sgrbuMRO4+OdeyKjsrT6nM1Gnl0HBy0LnbZ3ojZG0ViwxZTvOu2clA++jJUKNwP5ayZeDthFIqKXeRMEBphmMJfwyUjMDAQAwZwl4qV5+djxw7Mnw+xGLGxUB7PGReHdu0gl+OnnzBlCurWxfPn2LULixZBJsOOHZg2DQDy8uDsjNRU9O2Ldevg6or0dMybh4MHYWuL27chFsPXt9jRDGFhikGDmLw8bNuGGTN0tjE3F6amAJCTo/kwHTc3REdj5EgcOQKgsHVbW7x8ienTUacOMjLwyy9IT0ebNsjIQP/++OknuLri4UP89BN+/hkAgoIKEytwtwMwM8OePRg5EnI5tm7F7NmQy3H+vKJPH51HIPXrIzMTiYlwfpMW7Z13IJHg6VNYWmL7dnzyCSZMgK9v4dWvvsIPP2DBAqxZUxYPVKZuUimMjADgxAn06aO5iSZNoPWcFLkcpqbIy8O//6JuXR30/+MPxYcfMgAsLZGZWRSoqowejcOH8d57+PNPHWrm2LABc+dCJEJ8PKRStGsHAFeuoG1bnatSUk18XkHqocIiVml4aKigPCNlVkPgQy8taNW+AEtj0CAEB2PKFGzdqn7piy+wejUWLcKqVVpsFC759sAwzHTF+apqXSGX/xt3RyFXWLZtVvLsGyXPbz/Ke5Rp7dZK7dSMAulrhmVVC5/ffvTiwVNrt5Zq59GWGb1XqBeS9555Ep2o00lAFQe3oKNem6ZiS3O1S6cHL34cdu2jHH9OxrqLs/IgVSUKuTzz+m1DM2Mu+0PJq/wRUjIG8tIysxLv12/vqDYrpJR/HB5Xp1F9CydNR7XpAn9D/AL8Vuvldn7KGdildUm9VM6DVp9zvMrKUROI++Vo5OyNI6/s4I4E1rXC0uDxQxlq/pXpqzY84Rm2EP8lqvrNF0GUjlHxNOrcEnFHR+zfXyxF5ebNkMsxdWpRTkQzM8ybh8RE7NiB8PDCAefmzUhNhYsLAgIK37Xa2ODAAdy4gbg4/PWXYvz4YiOW8HDF4MFMXl4ZB2k8yOUID1esXctwK/k/+6xYvsO0tKLJDo7vv0dGBrp2LVrlbmeH9etRuzZ++AGzZjHx8cXq378fQ4YAb/bz5+Rg8WJ8+SWjttFACB4eOHwYMTEKZ2cGQEoKJBJ06FD4jr1/fwDw9y+Sj4wEUDixVWYPVLJu776rXqIT//yjyMtjTEx0mxYB8MEHjL8/9u1DZibGjNEwLQIgJwdA4SBZV+bMwZ9/IiICc+bg2TPI5fjuu3JNi6Da+Lyi1SuJXiIWwODBjFEpp0MMH46dpZ7zIFQNgQ+9zEHLcfp0qZe6dgWAiAjtlQiXJCoHhmX5l5ZwmDVrqHEEWHLcVZpkmdF7heXnde7LxG1+nVd+XNWKFGJgWEtrik0eGYZl1Qaralf5I6RkDBjbWhrblrokz8Cwlp2eDuXhb4hfgN9qvdzOTzkDm//2ius1Wn3O4Ws9orG3m+fxouVLybv9a5nUtmzbrGwVlgaPpeWsmXiroDwjRPVFKi32j0MiwTffMA8fFol99RVOnMDSpeq3d+lSWAkH9xZ0zhz1JegbNigOHlR06FBsgBEZqRg0iMnNxf79epgWMTUFwxT9MzBA794Mlz9i8WL1jRK2tuolv/8OAN9+q17tkiUQiZCQgKtXiwpdXAqnRZTMnQuWRXQ00tOhK1xmysDAQn3OngWAQW/OInB0hKMjMjNx+bICgEyGiAiIRBqW4uvkgUrWTSyGiYnmf0KQSABAbVuBQMzfvNUreQyTKqWNpbXi6wuxGGfOICoKnTtrCCFdqSY+r2j1UDERCyA3F5mZmv8pj7gupxpCHnp5gpafZs0A4NIlfUoSRLXldU6e87TB+hreE8R/D6dJnvf8IoJGf5+890z85mNHu8zMvCrp8uN0noVpBFGF0JoRovryqvjW3cxMBAUpvvuOCQhAt25ISCgcR9nbw/7NSsz0dMTG4skTRUgIExwMoCgtZWws8Ga6RJWSo4uEBHh6Mrm5cHbGe+/pfw+8SAQ7O3TvjunTNexw6Vosez2ePy/M/Fpy/GZsjB49EBqKpCSFq2thPZ1LJLkXi9GqFeLiEBWF4cPVr/IzYACDN+d34M3RHh4eRW+qBw6ERILAQKZTJ4SFKWQyZsgQ7Sdx8nugknU7caLUrArc7gx+UlMZQD0/iBD8/LBxI8RiSKUIDcWaNUXnyyjhZvFevix5tyCaNcPSpVi8GCyLQ4fKWIkq1cTnFa1eSfQSsQDOnkX37qU2oRc1hDz0MgetVrh9TFIpZDItFgmXJIhqi7GtpfO0wVWthSCsO7egw0qJyqf3zoWmTRrcOhh852g4wzLWXVsOPL6iZF4kgqgm0O8RovpiWPw/cVtbjB/PeHqiWTOkpmLr1qKR5OXLiqVLmcBA5QoRBiiaLgEgkxVeaqa+fE8DKSkQiWBvj6QkLFuGlSvLa0hpyQI0LshXWyBw+bICYAwN1b3BwS2GlxadVobatTWINW6MuDjk5+u8BcDODo6OkEiQlQVTU/j7QyyGaqKEAQOwZQsuXMCXXyI8nIGmGRzo6IFK1q2c3L0LlOJ2HlJTMWkSACxdirw8LF+OL7/EgAFwLb7G2cYGQFkW+yjhxp8ikaDI10o18XklqFcREQtALFaYmOhQQ9nU0PrQyxa0QlBOM+Xna1kBJFySIIjy03HZ5KpWgXhL6bBkQoclE6paC4IQBK1lImoYVlbw8gJUjuf090fnzoy/P+zsMG4cfvoJR48iJ6fYMnLlr/BXfCnkCxGLcfw4DhxQAPjhB8TEVGWypQYNGKisfFGDK9f60puz2tCwLIM67siP0FAEBkImw7BhxZrjXrlzy3O4d/VCsjboi+qgGzdjVdoD0ohcjvffR3Y2unXDl19i2TK4uhYWqm2p6NdPASAkhK9+mQzW1hg9uuzHM+tEdfB5zVWvmlCGoNUV4QulaUk1QRAEQRDVAfpJQtQ8DIqnnf7kEwCYOxe3b+P33/H55xg+HCYmuH27SIZlC8/c5TIXqnL1Kn75BeHhRdMfXl7w9kbPngxX86RJjOqijErG0REAZDLcu6fh6pUrAKD6FvrZMw1i3CCwYcOyTPF4ewNARATCwwGgb99iV0Ui9OqF/Hxcv47AQNjZoaHkS8kAACAASURBVFWrMjRSRqqDbm3aADpueFm4ENHRMDPDwYMAwLKF5/VKJJg7t5jk0KGMSIT8fPz+e6nPbtcuZGTgzz8r42RcVA+f11z1qgllCFqBvHgBACwLsfqpF2WXJAiCIAiCqARoZoSoYTx/XvjKt3VrAMjLQ2oqACxYoC4ZFlbsz4EDARSOl1Q5eBCzZ2P/fg3rKdasgZ0dkpLwzTd60LxsGBoWpg754w/1S1evIjUVLItevYoKAwPVXwWHhyvy8mBlBTe3sqwZGTgQLIu4uMKDPLiRp5oAgD17IJNV6taJaqJbvXrAm5SWQggIwLp1ALB1q8LBobDQyamwcNcu/P13kbCxMT79FACWLGEyMjTUlpGB774DgDFjYGVVFv11pTr4vOaqV03QNWiFw03CWllpXwkiXJIgCIIgCKISoJ8kRI1BJkNAAPr2RUYGjI0xYwYAiESFP6zPny/2Uv2XXwrPg3z9urBkzhwFgA0bcPFikWRSErZsAYCpUzW8kzcxwa+/AsDq1YiMrLI9NbNnKwB8/32xfT2ZmRg3DgAmTCi2WCA9HXPmQFXs448ZAD4+ZWzdxAQdOyIkBBcuwNGxWPYWDg8PBYDDhwFg6NAytlJzdeOmpRISBO1NSE/H+PEAMGECxo4tNlE1Y0bhoUJTp0L16KVly2Bnh9RUdO2KgIBitV2+rOjZE2lpsLLC2rVlN+HQIYWvr0K1X/BQJT4XrmHlq6eT96oJwoNWo3WBgfD1VWj8SuTmqfv00a6DcEmCIAiCIIhKgGZGiOqL6nGVDINateDpiX/+Acti1y6FnR0AGBpiwgQAmDGD+eILHDqkWL8ePXti9uzCZJZpaYW19ezJzJ2LvDz06sWMH4+dOzFzJjp3Rm4u5s9Hp06a11N4exdOQEyaxOTnV7zNmhg/nhk3Drm56NGDGT8e27dj1iy0bo2EBLi4YP36YsImJti0Cd27Y+1afPEF2rRBUlJhPosy07cv8vMhkxVmeFGjSxfG0hJpaWBZ9c0LlUCV62ZpCVdXyGSC5s4+/BAZGXB0LJyPU2P3blhZITu7MOQ46tZFcDDs7HDnDrj0w++/j/ffR5s26NyZSUmBpSX8/BRcrtay4ePDTJrE/Pab0CVFle9znTSsZPV00q13b0bta03134gRetBHCMKDVqN1P/6ISZOY3bs1mHz+PCAs7a5wSYIgCIIgiEqAZkaImgG3Hd3VFXPnIjERo0cX/Sjftg2TJiE/H6tXY8wYZv58PHuG48cRGgqWRXR00dEe69djyxZYWWH/fnz8MbZtg5ER1q3T8r59wwZYWUEiwddfV6SFvPz+O9atg6Ul9u/HJ59g0yY8e4b58xEVVXg8jZLBg/Hzz7h2DQsWYPVqZGRgwQIEBmo+2kYg/fsXfvD01CzADW86d1ZXphKoDrp9+CEABARoGRsvW1YYkwcPKjQexmFlhb17ASA0FCtWFJU7OeHGDSxYACsr3LmDv/7CX38hLg5iMT75BPHxZdwnVWaqg895qObqVRMEBq1OyOU4fRoikfYpHuGSBEEQBEEQlQOjUNSkNcDEfwaGKfxFrq8IzM0tzCHSvj20vj+Pi8P9+6hfX9GpE1OzdrlzmpuZKbp3V9fc11cxaRLz4Yc4dAgyGUJCAKBPH4jobO4KJiMDDRvC3r5Y0t8K4t49JCZCLtdz9I4Ygdati03HVDeqs4bVWbfSEB60wq0LDMSAAZg0qXCCTy+SbxUMw0xXnK9qLQiCIN52fmX6qg1P9D5sIaonNGYi/iOYmGhePK8RFxe4uACo1DftekGg5iIRLVOvPKys8Omn2LgRISGKPn0qNqgcHPAmb6veGsrNRUgIpk7VV336pzprWJ1140Fg0Opk3ebNAARt3BMuSRAEQRAEUTnUqNflBEEQ1ZIvv4SxMX74oebNtQEYNQrt2hXmf62eVGcNq7Nu/AgJWuHWpaTg2DFMmABnZ71JEqo8CrkaMvnH04O+8PdcdG7U0hvr/3qdq5+Dl29sOBI1b7NeqtI7aWHXQ6eteSZ5qF1UMDc2HImYtVGPFRL/efIzn1W1CkC5u4NwK/j7SPzmY8qrqt8equW6tkgQ1QRaM0IQQgkLU6xaJWjo268fPv+8otXRmeqsf3XWTQi2tli2DIsWISZG0aVLDZsfWbsWrVpVtRK8VGcNq7Nu/AgJWuHWrVgBCwusWqVPSUJJxKyN8ZuOMiKDhr3bsUaGTy4l3fk77NqaQ0NC1ls4lTiBSUceBFx+Ep3Qbf1nelFVvzxLSU3e5e800dPc0U5fdT4IuPw47FqPX2brq0LiP0x20v1zo5Z22+DTyKNjVetS9u6gqxX8feRhYOzDwFjuquq3h2p5tfIbQQiHZkYI4j9Co0bw9i48kYeofBYuxIkT8PFhYmKqWhUdcXGpag20UZ01rM66aUVr0Aq07upV/PYb9u9X2NpqmRYULkkoeRAYG7/paNOR7n1/WywyFnOFt/4ICfrwu8D3v3vv2s6qVY8g/sM8iUnKSrhb1VqUF/1a0e6LMS2mevOX/zf8RryF0MwIQQjF3Z1xd69qJUqnXz+mXz8+geqsf3XWTThhYVWtAUHoiF6C1tUVCgWE5L4RLkkouXUoGIDbupnKaREAzT/oc/fvsFuHz2enpKotG5HLCliRQWm1FUhfGxjWEtIufz1C5EurQSGXK+QKnsoVcjlPfmnhJvCrwTUEoLS2tDbEczt/zfxa6SSv1ZlClCmbkiUfU/mt5q+B53ad/KkxwPQYVyUpZyzp9Ox0MkSrcEkzbdw0ryQsrZwgahA0M0IQBEEQBFFNEdU2ApAVf9fUoYFqeZdV0x3HDzCqa8r9mXE5OXrR9rTQawq5vLZNXZfZo9p/NU4pfPP3c9fWHM6Ku8ONshr0atN94yzLts1LNvdv3J2ouZsenb+qkMvFVhatPhna4duJpY0Ag0Z/D6DFtMERn214lpLKiAycpw3utXVeim9AzJe/5qVliozF7b4Y0/HbiZz84/AbMV/tTI+IU1befsl41YHZXb+ImC9+zU66z4gMWnw0qF6bZspLLzOyoxdukxwMlktfMyID215tu2+cVc+laWl+43fIw+ArUfM2/3v9FsOyNj1ceu9epNyhwO8rpclR8zZnxd3hBNx3LlTefu9kVPTCbdlJ9xmWdRjavdn7fSJmb+x/6FtuW4FO7uW3gt+ZPHpGztl0c/+5kbHbVSMq5qudib+eeO/azjp2VvxKBo3+njWsZdOtdcTsjazIoM+eL5qP7lceq7W6lMcJuoZrSc15HnfotDW3D58HcG7EN0aWZmPvHtK1xXLGEk93KElpHUSjFUK+EO76RUTN3ZxzJ81AbOg8bXCXHz6uZVIbwPmJP6SFXePqUUVZXrLFKyv3X1/3xyD/VdZdivJL3dhw5J/lvsMiN5V/SyBB6AuaGSEIgiAIgqimOH88OGHL8aAPv2/16fDGg90a9HThXiCbOjRQjmyfxCT59ZptbFuv1/b5RvVMb/8RcunrnbK8/M4rpoLLjOizwd6rS/vFY1lD0ZPopOvr/jjj/eXY+4fV3kVnXE4+2XeekaVZzy1za9vUTbtw45/lvpnXbnke13xuszTnZVb8nfunLrrMGVW3VZPk3f6J2/xePMjIuJTU9vMPxVbm19f+Ebt0j0331o08Oj4IuHR60JcmDjY9t8wVW5nf94/+Z7nv4/AbQ4LXcbXd9YsIGLbE0tWx3/4lCrn86qqDt/8MUbYVMOKb7KT7bj/NNHGwznuYeXnpHr9es8el/sGN1tTgd4gsX3pm8JetPhnafvHYzOu3r/6w33/gwjG3DwjxlTTnZXbivXsnolpOH9J+8bj0qPj4TUdPD/pi9M3fAdw9Fh4w4pt6bZv3278EwLU1h0Knri7Il8qlr8vgXh4rtDqTR89m7/eO23hEsj9IOb+gkMuTd/vXc2lax85Kq5LSnJc5t29JDgY1GdojLy3T3LlxOa3mdymPE8oQrmqa8z9ux7EekCuS95x2nv5uvTZNdX2C5Y0l3u5QktI6SEkrhHwhyPKl50Ytbb94XP0O7zyOiLv+0+F/b9x+N+RnAK9z8l5lPi+pgLK8ZItN33O/9PXOm78FqM6MJO08ZerQgKZFiGoFzYwQBEEQBEFUUyzbNvc88b/QKauvrT54bfVBLg9rI88u70wcYGxTj5OJmrvJQGw4PHoLV9J0pPuLR5lXVx3suGwyKzK4uupg3VZNBp0uTHvbdKR7Qb40buORjMspqgMVABE+GxiRgbKeJsN71rYyj1m8I/VMjL1XF43q5d5L77d/iePY/gAchnbfaz7k/smoD5J9uQGPdRfnP1t/dPdoeCOPjmHT14qtzIdHb6ltZcGpYdLYJnbpnuS9Z1pM9gJw8fOtJg42wyJ+4fYNOQzt/qfLFGl2LgBZXn56RFy7RWNcZo3g2jU0rxO/6WhWwj01E7Q6BIBCVuC+54t3xg8A0Hx0P+mzFwlbjmVev2XZtrkQX+XcSVOa7Di2f8Gr10k7TmZcTrbq1CJi9i9mjnbDozZxJjQZ2etoxxnKhAu6upfHCq3O5NGzQc82Zo52koNFMyMPg6+8TM/qsvJjgUpmJ91337HAedpg7s+zQ78up9U8LuVxQhnCtaTmPI/brl/7Fw8ykvecth/UhVv8olOL5Ywlnu5QEp4OUtIKIYopZAW9ts1vOeNdzkxD8zqXv9l93/9iY283jQqoUrJFCyd7m26tJQeDum/w4SZfMq/fyoq70+1nH621EURlQqf2EgRBEARBVF8ae7uNe/DnwKPLnSZ5mjZp8DDon+hF2w40Hp28+zQAWb40PSq+ybAeyokSAL13L/ow2Zdb5D/27sFhUZtUKxRbmQOQPn+hWvgyI/tJdKJaPa19RuBNrhONMCzbfHRf7nMtk9oik9r12jZXvgc2c7QDIHvx8klMUu69dKdJXtxInqPdgg8Ylr1/IgpAdtL955KH74wfoEynYmhWx3nKIO4za1iLNax187cAyYEgWb4UgOPY/sMiN2mcFtHqEIZlubEoR4MeLgBePMgQ6CtVkwHYdG8N4OWTrCcxSS9SnzhP9VaaIBIbtvp0WNncy2PF039u8juTX08ATpM8s+LuPL0q4S7d9A0wEBs6jvcQqCTDsk5v5l/0YnVpqvI44VVWTtnCVak5BHcNnWzRqfLSDOfvDiXRqYMIUcxAbOj88eAiMz8bDuD2HyGlKaAVp0merzKfp54pTPedsi+AERm8M96jzBUSREVAa0YIgiAIgiCqNazIoMnwnk2G9wSQl5Z58/fAKyt/D5262sK58eu8fAD1Ozqpyque68mwbM7dx3f+CnuWkpr7ICPjUjK3zUGNjEtJACQHg++djFK7lK9p8TyHyNhIdUsOW8ugTiMrNRmFXJFz93FJJUXG4lpmxtziguyUVAB1WzVRFbB48ycrMnDfsSD0o1XB41ZwmUEc3u2uumpGlcfhN0q2peoQNZ0ZllH5rN1XJW4v/MzZaO7USFXYxMGG+6Cre3msyLicUvKSqjP59QTgPNU7dunem/vO1nd1LJC+lhwMcpow0MCwlkAlRcZGyswaerG6NFV5nHDf/6KQmtVQ1RyCu4ZOtuhUeWmG83eHkujUQYQoZt21papiRnVNDcSGPI7ViuM4j3CfDZIDQY293RRyuWT/OYch3cSW5mWukCAqApoZIQiCIAiCqI7IZQWSA0G1rS1U1+ob21q2W/ihVecWJ/vOS/z1BLf8QSQ2LK2S2O99Y5fuERmLGw3sVK9NMxefEc9vp136WvNxv83e723TrbVaoWnTBhqFdYUVaTx6QwEAcgWKT1KoyTtNHNhoQMfbf4U9CLiUeibm8YXrscv2Djm/XsNbcbkcvA7hQSdflQEd3KvNCj5nasPY1tLOo6PkYFC39Z9JDgQpZAUtVNYj6D0Gyl6hNieUU9UyPG7hLZYrlrR1h5II7yBCFOMSP6tShrONVKllUttxTH/JwSD3nQsfh994mZ6luiaFIKoJNDNCEARBEARRHWFYJvSjVdZdW5bMYmDt1gpAgVRWr11zAE+iE7mkABxPYpJSz8Q4Tx0keymNXbrHplvrISHrlQeXxC7bW7Its2YNARiam3Ar55XI8qVlm2VQpba1BYDspFTVQrms4PXzvIZ9XAFwK02yUx6oCuSl/av8XCB9Laojdpk1wmXWCLmsIHH7iQifDddWHRxw5Du1tvgdwqPkM8lDgb7SiFkzWwD/xt1tOrLoFPrce+lvrurmXh4r6rZyAK8zhdDiI6+gMcsfBl+56Rtg7mTfoGebMiipd6vV4HGCrXvb8tQM3R+3TraUM5a0doeSCOwgAhVLv5ig+ufr3JeyvHyxpZlA/TXyzsSBN38LuHUoOC3kqtjKorRcMARRhVCeEYIgCIIgiOoIw7KNh3RLj4pP2OqndunajwcA2PZqa2xTz8K58YOAS1x+AY74TUf/+W4fw7LZSfcBOAztrno47p2j4QDUltBbODc2cbC5cyT0VVaOsvDeyajdtT0vLtxWTkNs3duKrSxS9p0tUGk0accphVxu090FgFWnFnXsrSX7A1UFUvad5T7c9YvYZTQwZV8A9ycrMmg1cygjMlDI5SXb4ncIj5LCfaURq04tzJ3sk3f7Kx0oy8tP2HKc+6yre3mssOnWit+ZQmj2QR9DC5OkX0+khV5zmuRZNiX1brVwJ1i0sC9nuOrwuOVyXW0pfyzxdIeSCOogcrlwxaTZuaqTI9z3T9P3emvVvBjFu2cjj4517K0fnIm5cyTsnQkDy7kIhSAqAlozQhA1hoSEhKdPnzZo0MDJyank1bCwMAD16tVzcdHwwygyMlImk7Vs2dLKykoul4eHhwNwdXU1M9P8BuDixYtSqbRFixY2NjZ6NYIgagD66msymSwyMrKkjLW1dbNmzQwNy/senngb6LFpdnpUfPin62/+FtB0lHsdu/ovM57dORKaFnrNplvrljOGAOiyanrAsCWnvRa1/2qcUT2ze36RN38LaPnJUGNbS6uOTqxhrfhNR23d29Xv5PT0csrlb3c/S0mFpp0X3TfOChi2xM99Tuf/Ta3TsH7mVcnFhdvEVhZtF3xQTisYlu26ekboR6tOeSxw/XJMnUZWD8/Fxny108K5ces3p2m4rZ4RNGb5aa8v2i+ZIBIbXl/7R+a1W9wlhyHdTJvaXvpqh4GhyLL9O9LnL5J3nlLICpp/2FdjczwO4VFSJ19ppMfmOf4DFhzv7uMyexTDMvFbjuc+yFBe1dW9pVlRx85KqzO1wrCs00TPuI1HGJZ1mjSwzErq3WqBTjC2tSxnzUIet4GhCEDijlN5j7OcJg4U3mL5Y4mnO5SEv4OoWtFoQEchitUyqX1u5LduP800d2qUFnot5qsdDXq1dRjSTYjmJf2mLHeaOPDK/34H8M6EAQKrIojKhGZGCKLGcOjQoeXLl/fo0YOb11AlKSmpd+/eACwsLLKystSu5uXl9ejRA8CNGze40RonfO7cOQ8PzYnBhwwZkpmZuW/fvokTJ+rfEoKo3uirr+Xn53PCGnFwcJg4ceJXX30lFov1bQHx38HE3vq9azsvfb0r5beA9Kh4rrCWSe02c9/rtHwK9961ydAe/Q8vvTh/s7/nIgCMyKDN/A/c1swAYGxr6XH429Bpa4738OEutf50eOeVHx/rOvPJxQS1oU6ToT0GHl8ROfuXgGFLuBLrri17716kMY+jrrSY7GVgWCt60bYzgxeDOyBmnIfb2pnKnQjNR/eTywqi5m851X8+AEtXx64/To+av5kTHhz40/nxKy98so4TNrI06/azT/PR/TS2xeMQHnTylUYaeXQcHLQudtneiNkbRWLDFlO867ZyUOqsq3t5rNDqTCE4feQVt/GInUfHOnZFSXPLEAP6tVq4E8pZs5DHbe/dtX4Hpzt/hd75K7T56L7CWyx/LPF0h5LwdxBVK6a+ChCiWAP3dg16uJyf9INCVgCg+Zj+vbbNE+JVDjW/KdenOE32uvK/3+u6NK3v6ii8NoKoNBiFQtDMJUHoF4YpTCtFESickJCQvn37ikSiV69escVXIa5du3bBggXc56ioKDe3YgfOHzt2bMSIEVZWVk+ePAEglUqNjIzAOzNSv359mhkh3lr01ddyc3NNTU0B2NraqopJpdKcnBypVAqgW7duYWFhIhG9qHjbYRhmuuI8j4BCLn9+Oy3n7mOTRlbmTo00rkV/fvtR3qNMa7dWqgdwcPf+G3dHIVdYtm0mZBF7XlpmVuL9+u0djeqa6mqIVp7ffvTiwVNrt5aq6/lVVc28ftvQzJhL66BGgfT14/C4Oo3qKw8G1tqWRofwoKuvVHmVlaPmsbhfjkbO3jjyyg7VoaCu7uWxgt+Z5UG4khVktRo8TihPzUIed4H0NcOyqu0KbLE8saSsgac7aFS1tA6iaoVAxeSygsfhN6w6tahlUrsMypf0W869xwebjOm27rM2894rQ4WVxq9MX7XhCQ1b3hLopxhB1Bjc3d1FIpFMJgsJCenXr9iLsoCAAAAjR478+++//f391UZrFy5cAODl5VWZ2hJEzUXvfS0lJcXExES1RC6Xb9iwYf78+VFRURs2bPj8888rxBLiPwTDsuaOdqqnz5bErFlDjSMohmUt2zYX3paxrSX/xpPyUJqSHAzL8rxPNjCsZdevvb7aKk0BnXyliq/1iMbebp7HVyhLknf71zKpbdm2maqYru7lsaIMBgpEuJIVZLUaPJaWp2Yhj7vkrJPAFssTS8oadFpewdNBVK0QqBgrMhCe05e/RY7E7ScZkcE7E2krDVFNoeQ3BFFjYFnW29sbQGxsrGq5TCYLDg62srKaNWsWgMDAQLUbo6KiQDMjBCGYSuhrLMvOmzfvww8/BHDgwAF9aU4QRBXiNMnznl9E0Ojvk/eeid987GiXmZlXJV1+nP7fTjb5dlpN6MT5iT+cHbbk6g/728x9T2xpXtXqEIRmaM0IQdQk+vXr5+fnd/HiRdXCkydPymQyLy8vd3d3sVgcHR2dlZVVt25d7qpMJouOjgbg6elZBRoTRM2kcvqat7f34cOHExIStIsSBFHt6b1zoWmTBrcOBt85Gs6wjHXXlgOPr2gytEdV61WxvJ1WEzrx9MrN55KHTpM8Oy2fUtW6EESp0MwIQdQkuGyO3Hp+JefOnQPg7e3Nvej++++/z549O3r0aO5qQECAXC53dXW1tKyopdEE8d+jcvoal2qEkowQxH+GDksmdFgyoaq1qGzeTqsJ4bx/Y3dVq0AQ2qF1bgRRk+AGXbm5uUlJScpCbvA2YMAAAAMHDgTg7++vvModrqEx02p+fn5uKVS0IQRRzdFvXyuNnTt3KqsiCIIgCIIgqgqaGSGIGgY37oqJieH+TElJkUgkHTp04F5T9+/fH8VHa5GRkXgzllPj3XffNS2FzMzMSrCFIKozeuxrasjl8rCwsGHDhnG7bz777LMKUJ8gCIIgCIIQCs2MEEQNg0vuqEz9ePbsWQCDBg3i/nR0dHR0dMzMzLx8+TIAmUwWEREhEok0vscWi8UmpVBJxhBENUaPfc3U1JRRwcDAoHfv3n5+fgAWL16sdvwNQRAEQRAEUcnQzAhB1DC4N9LcERh4M2xTHYxxK/O58rCwMC5hJKspRfyJEydySoGSkhCEHvuaGiKRyMHBYcyYMefPn1+5cmVFKE8QBEEQBEEIh2ZGCKKGYWdn5+joKJFIsrKyZDKZv7+/WCx2d3dXCnDDuQsXLqBMiQ8IguDQY1/LyclRqPD69eu7d+8eOHCgT58+lWEJQRAEQRAEwQvlwyeImkfv3r0lEkloaKhYLJbJZKNGjVJ9TT1kyBCWZYODg/HmdbeQxAcEQZSE+hpBEARBEMTbAK0ZIYiah7e3N4CIiAjuNXXfvn1Vr4pEol69euXn51+/fj0wMNDOzq5Vq1ZVoyhB1HCorxEEQRAEQbwN0MwIQdQ8Bg4cyLJsXFwcdxYGN3hTEwCwZ88emUxGW2kIosxQXyMIgiAIgngboN00BFHzMDEx6dixY0hIiEwmc3R0tLe3VxPw8PD4+uuvDx8+DGDo0KFVoSNB/BegvkbUOEIm/9h8dD97ry4AFHL57T9CHgTGyqWyOo2sHMf2r+fSVE3e33NRx6WTbLq31lqz9PmLqPlb2Fqibus/E4kNVS8VSF9f/Hwrw7Jua2eyIoOErX6vsnLafzVOj3aVh/jNx7KT7vf4ZXblNMfj9uTdpx9Hxrl+Odbc0U71lqdXJfGbjhoYGXb6frLY0lytwofBVyQHAktrrrXPiPqujnq3QsmNDUeeSx7q0Xv5mc9K2ljR8FtRyRHCw83fzz0MjFXIFQ16uLwzyVOto+FNMBTkS606tnCa7GlU11RjPZIDQQ+D/1ErNHe0a9CzTYOebfSocFrY9RTfs8qQ1smTykioPv4n3nJozQhB1Ej69u2bn5/PnYVR8mqXLl0sLS3T0tJYllVb/08QhE5QXyNqENfWHH4cEddoYCcAr7JyjnaeGTRmeeYVifTZi4Stx/9qMyV+8zFOUiGXPw6/AeBx+I3Xefk59x7npj7hr9zQrI5JI6vEbX4RPhvULkX4bIzfdNS6a0tWZADAYWi32O/2pYVd17+FZeJhYGzK3jOV0xa/2x+FXE3e5Z/3KFP1lqdXJSf7zpPsD2wyoqfGKYPsxHvJu/xL+5d793GFWvQg4LK+vJeddP/P1h89vSLRS206wW9FZUZIaUifvzje3ef8hJVPohOlz15EzP7lrzZTcu4Ve7jhn2041X/+k+jEV5nPLy7Y+lebKaV128cRcSVDJWbxDr9es4NGf69HtZ+lpKqGtEBPqkVCdfA/QYDWjBBEDaV///6rV68G4OnpqVHAw+P/7J1nXFRH18DPXpaVJoL0jkgQARGCqICggqIiQdQYBSN2H31sMbHEWBN7iPGxobFLEhEjrw0RkSIoghRBQJoIuPzEpgAAIABJREFUSG8rfcFluft+uLpZt9xdlo7z//lhd2buzJk5Z3Dn3JkzUwIDA21tbZWVlXtWNARiQIHmGqK/wKh8l7z3ysSLWygYBgDPt52reZHreme/oYcDALQ1tTxw+zF23XHtyVbKZoblMWnBkzcNtRyOs9pTD/5dFpVivm62yHe2NnuXlIQl5VwMMfCwJ6oFgLxrEdnng0csdzP2diFS5HXULDbMebrm2LxXl7uzx+IyepvXiOW8R+G6CfJh5y9fnZRzf+pmNqvd7aGvlpMlSc3T7x/SdxvfTWL3DFUJ2bWZhb0thQB60kKE8WzDycq4V2MPrbT60RsAGOX0Ow7rQ91/mpd+iShQFBKf6Xd71Pff2B1dAwC1mYV3HNZHLTr41eP/CauTx2bqcoujlxx5Exil6WhpvtazO3oh5kjyWEJfGH8EAtCeEQSin+Lq6kpc/+nu7i6wwPXr19lsdnx8PH8WjUYjniUJi1BTU8Nms318fLpMYgSif9KZuaagoEA8q6Cg0M1iIhDw8tfAQcoKwxc4AwAbx3OvPtR1teX4L6QVZK1+9AKAt3efAYD2JKtvy25qT7LCmW0sRuusuNP2x9fxVMjGcTaO8yS6BO6WVpSPWfEbo/IdANTnlT75z1FlM0OHUxu5i5mv86zNLHz91yNymfnrBwCc1d7RR8jRGG9m4G7X+dbbmW3kDYkcdh6qErLvT90MACLdIh2CpAtsHCcfXpGPk4y/yPHpjFQdakukCfH0QpiFdFQqiZ/FWe2v/3ykYWdOuEUAQE5LZezBFbUZBUUhH/5zeXXylpQMbeyhFcRXZTPDURvnlke/FN/ZpGSiN/HKNgAoDk3gyeroXBBmBpKNJMkM7agqOUhsjYjPGbRnBIFAIBAIBKJ/085syzp713TFTOIrG2e7BOyUUVXiLoPRpAGA2cAgvjIbGbn+Dx1ObUz46UJ1Yo7GeDMAIHbaj1gxM27T6dqMAgqGaTqOcrqwhRMXQ0FP3fHMpsiF+6MWHpgecjhs1k42zp566xeegAiDDTQ1HS0z/e588a2Aq6wjFvyC0aQ17MxjN5zAqFKTLm8bvsD5XUZB3HenyqJS2Tguo6Zkttrjy90+xPEcgrfBcQnbztVmFlKoUsZeLsPmOEav8HX9v31aTpYRC36pScmbn+PPKZzrHxb3/WkiN8rnUHnMS+/C65K13lJd93zL2byASJzZRqFKaTla2p9Yzx+xRcxh51CVkB0ybQtFCpsZfrTzgUIIxQ33doldd6K5uAqjSY9c5W57YDlNUZ4oUPE0PeGnC5WxGZwOWu/8VoomzamhOinn+dY/yqNfsnFcVkPZYsNc7kgxpZEpcZtOv0t7Q8EwDQeLiZe2ckxCzPGJXuGbHxgFAI9m7xqkokioQ6RUPLz+69FL38DajAI2jhPGaX9ivYrlcHG6QNILHgsRZgzPNp56/fejOcl/DDbQ5NSZ8NOFrHP3vn55QV5HjeRZcvVVJ2SzcXzo6OHciVqTrQCg9FEyse+jJDzZwN2Oe3DUxpoCQFlUqsDtSAJRMtEDgKaiD2dwJJiJhXdjE7adq8suolClRiydMXSUEXf9PCMpUCP8lsDzFJAaBvnfKPFnKwLBD/KMIBAIBAKBQPRvioLjWIxWnak2xFeMKjVsjhNPmeL78QCgM+VDmaaiKsNZDuZrPamygxryy4hEZmNLXdbbt/fiRq5yt96+sDLu1atTtx7M2Lbg9V+ceoy9Xd4Gx70JiLjntLE2s3Dynz8Ryy0edF3HJO261FRcpaCnzpPFbGxpzH+TFxBh6OHAKKcPMdWvTsoJnrxpkIriBL/vZDWUy5+kv9jnT3/5Ztqd/cQjhXdjw2bt1HCwcL2zH3D2i31/loQlvqc3EG+GmY0trfR67iZwZhsnt62R8Z7eIHHrYbN31WUXjf9tjYKBOqOUnrTn8l3HDQuLb0gryPL0S5xhJyDcIpg01T3y9y5ZtjEbW969zMsPirHdt2yopVHNi9dJuy7VpLye9fQkAJSEJT6Y8aOCgcYEv+9k1IYUhTx/sc+/4mm6e+TvHHnuOm6Q0xrq+Mf3g4YOzr/xOHHHBRaj1Xb/cgBgtTJDZ/5ottrDers3PS0/9dDfIa5bvPKvEc+KOT7G3lMAZ+dcfmC66quho4aJIxUPr07fjl13XG/6WOvt3hiNWvU8O+33G6FuP3oXBVIwjLwL5L3gthASYzCaNzHjRFDe3xEchwsbx3MuhQy1GEa4RUSasTCk5AYJ0GltEwA0lVQDALOhmc1qH6SiyF1Aw84cAGpSXpNXzk1lfCYAKI/U/9BEB+cCMQ1VrIyd/97JxvHUIwH5/zzmrp97JIVphN8SeGYouWGQ/40Sf7YiEPwgzwgCgUAgEAhE/6bkUTLwLb8/KRCWmP6/m1oTR+s4WxMpulNsdKfYAMCIZTO4SzYWlDv/vZMIGmLs7dL+vi37fHB1Uo7amBGcMk7nfqh4ml71PMt44RSBu0IAYKilEQBUxmYoLHDmz63LLnI6v5mzyeX2+P9SqFKez/3kNIYCgKHnBFm1IQnbzxeHJhD37MT/cEZeT31m+FFic4rOFJt/LJaKPTySt67lZFkZmzF6q5fF+tlEYdoQ+VenbtVmvlUfayqyIf5hB4DqxOwX+/9k1jVR5WQwmrg/xRN3XEz//R+eRFWbEeOOrCI+N5fWOJ79fuR/vgIAfbfxUoNoz7eeLfi/mGFznGJWHZVRG+L53E9WTQkAhs1xUtDXSN5zOedK6Igl0wEg7rtTUjI0zggMm+PUXEZPPRJgs3cJALBZ7U6XtxGKHr7AmVnfnOl3m572RsVyOIvRKub46DhbN5dU51x+oDdjLGF4IqXiIfVIgLKZ4YwHR4ivw+Y4tbcyM04EVSflqo81JekCsd+BpBfcrcSuO05iiorGOnkB/3pGSiNTWiprxx5cKc6zJMpVsTSSkqGVP04l9sIQiYW3nxJiA0B1Ui4ASA36ZGcWVV4GAHAmS1i17a3MtqYW4nNjYUV1QnbizosAMHL1vzepdWgmxv9wRsFAY1bsSaqcDAAYeNj/Y7GMWdcksHUSjfBYAg8iDUPY3yhlM4POzFYEAsUZQSAQCAQCgejfNJdUU+Vk+O/4JCgJS3w4a6eCgYZL4G6RVVEwbPiCfy9aIi70bamq5S7TUlXLrG8GgOrEHFYrU2A9xA7/qudZwlox+bj6bamuq3qeZTjLgVhBEZivmw0Ab65HAkBddlFDXunw+ZM5HZRWkB2xTPKQjeK3jtGkMZr06z/D8q5FED019naZ9eyUmG4RgcMev/mM9GC5CX6bWIzWR3P3iBkQAZOmYoNovP+k/z2mISVDM105k/PVbI0HAOTfjKlKyG56W2myeDqxziQYvfkbCoYV3YsDAFYrszLuFc8ITLy0dX6OP+FToGAYJ7wuAGg6WABAc0k1AEg8PiKl4se7MGBW3CnuFBm1IQDAbGgW2QXyXnAQaYomi6fVZhTUpH64VOW1f5iUDM342yniPEsCBcNGbZpXl10U+tUOetqb97WNr07ffvlbIOWj8CThXUgicTyau+fyYDfi381Ry6KX/9pKb7D73zrtSVbcTYs5F4hp+MW3Uwm3CADQFOVNP/WrchBHIwIRxzCE/Y3qzGxFIADtGUEgEAgEAoHo7zDrm6VkBbtFcv3DopceGWyk5RFznHuVIgyq3CDOW2sA4P5MwMbx8Hk/sxitw71c3gRExG067XhmE3898rpqANDKtUmepxXOAqk6MRsA8gIi3wbzLomJx+tyiwFA5dMoDEMtDEX2RRjit45RpZzOb45eeiRy4X4iOIXBV/Zf+EwVOZIkw65orOMRc1xOS4We9ibr7N3nW/7gD3/Lj83exeR302jYmXMrS1pBlionw6xvbiysAABVGxPuwlQ5GWlFOSJ4J3F/M08BThgREGASFM5nicdHpFT8UDCssbCi4GZMfW5xU0l1dWIO/tGpJLIL5L3gINIUTZe7Je+58vrqQ1Ur43ZmW15AhMkiVyL+hchnyRl7cEVLVW3OxZDikHgAGKSi6HJt58NZO6VkBwGAnKaA8WTjbACQEr7tyGLDXOK4CgBQMGzQ0MHaztac0DME4s8FYhryxDRREhLiRByNCEQcwxD2N0pia0QgCJBnBIFAIBAIBKJ/0y5k40bcD2fSf7+h6Wg57c7+QcqDu6StuE1+NS9ybQ+ssPrRqy7rbdbZu3ozxnJuY5EYo3kTibgJ3AwepimwMAhy2XRT6yY+rrpTbfJvxpSEJRaHJlQ8SUvee8U96hjJi2jyYXf84wc5LRUAsDu2tiwyJeNEkLaLdecHkFhCCwOjChguYmkNOA4AwjYciUSC8RFLKj6Sf/FP3nOZKiej6zpm6Cgji3WzG/LLE3dc6HwXeCAxBjktFZ0pNnkBEXbH1uZdi2Cz2nkOo3XUjLmZeGHL6K0L6KlvpGhUPbdxbJzd3soktk4MMdEFgLbGT+L4NhVVAoCs8GW/7rQxEtz0LKwLxLEdHo+SQA0CdFYjHTIMbjpjjQgE8owgEAgEAoFA9G9kNZRrXxXyJEav8M25GDLcy2Wy/3aRt2OISeHd2IwTQVoTRxOhFlwCdweNXhGz4jf19JE8L2bf0+vhYygEchSNtAGANkTBfK0ndzqrlUmsrIhXze/SC7hzW2s+Dbna9smZAv7RkLj1dmYbVV7GYv1si/WzcVZ71h/3Ytcdf3kkYGrQzwIrFDnsnESqDM0lcPctm/88Xnz467SL/KFqO0RNcs4n8jNaWYxW2hB5WXUlAKjLLubOxVntbQ0M4lQFcSVK1fMsIkYJQVVCdnFogulywWcluOno+BCIlIqH+rzS5D2XNezM3R8f49zPkrz3CvGBvAtEeFRxEGkMADBi6fQIr32lkSmv/cOGmOhpThgl/rMk0NPesHG2qpUxJ55xwf/FAIDWREsAkKJJy2mpcCIlE9RmFACA+rguW/OTd6E6KQcA6nJLuLMY5e8EViWxUXXUMHiQzBoRCAIUZwSBQCAQCASifyOrpsRitHJHrEg5+HfOxZCRqz1cru3sKrdIU3HV48WHB6kocgJnKJnojf9tTWt1XaQX7+0b9Jdv4GM0B3KUTPUVDDQKgqLf1zZyEt8Gx12SnRa/5SwAKJsZKhrrvAmM5I5pknPpAeezFI3KamrhBJsEgNLIFDE7Rd564d3Yi4Ncc6+GEekYVcpsjQeFKiUs7kNHh13Vytjm5yXMuqYIr31iCiyMlsra8pg0ztes8/cBwOhrJy0nSxk1pdyrD7nNI/v8fTaOa9hbAICcxlAlU/2SsETu4X116taLn6+K3JjT0fEB+LCbQKRUPNRlFwGAgYc997W1BbeeAgDObOtMF7gRaYoAYPTNJJqSQva5e+XRL00WT+vQsyQ8Xnw4fN5e7pS0324MUlHUd7f70O68SZWxGcSRFoLs8/elZGi6rrbid5Ac8i6ojRkhr6ee93c4t8pyrz4UWJVYGhFkJB01DG4ksUYEggu0ZwQxYElISMjPz+dOMTQ0HD9+PADExMSUlX3idzczM7O0tCQ+X79+nTvr66+/plL/nSksFuvmzZs8bSkoKLi7uwNAeHh4TU0NT66bm5uioiIgRIFUhiDoJkvAcfzGjRvCGlVUVJwyZQqN1jWbsT8HkJr6FLquY3IuPygNTyY2zzMq3yX/fBUAWM2tUT6HuEtqT7IaISRoIjlsHA+ft5dZ1+R6Z/8nARrXehYFxxWHJqQdvWH5wzec9Hdp+QDAfaMNCfYn1ofN2nnXaaPtgeXy2qr01Lz4LWdl1JQsN3+ocMLpjSHTtoa4bvlyt4+0gmzGif+rjHvFeVzLaXTh7afh8/aar5/NxtmvTt5ilNPF7xpJ67JqSoOHaSX+dF6KRlWx/oLZ0Jxz4T6b1T58/mT+eiQb9i93LioOTaiMzUjafXnML0Iv3En77cab61H86erjRnLe8D/6eo/d7/9VthhWHv3y+dY/NB0tiVuEx/36n+ilR+5P2Wz1o5e8rlrpo+SEny4omeqbf7zCY+yRVWGzdj6YvtX6p4WDhiq+vfvs9Z9hI1d7EKd+SDBwtxN/fIiIGFnn7zMqak18XEVKxY2ajQlGk3516paW02jVMSY1SblJuy/V5xbDx0MWEneBB5GmSMEwE59pGSeCKBhmsti1Q89yUxKW+GjunuFeLk7nfgAA87WeMSt/i17ha/n9vLam1pdHAirjXk28vI3jCRq9dX7OpZAH07dN8PtusJHWq5O3ikMTxuxb1rX30ZJ3Yfyv/4nw2vdg+jbrnYuoMrS0ozcIB6hASDTCYwncT1EwrEOGwU2HrBGB4Ad5RhADloaGhszMTF9f39bWVisrq7lz5+rrf7i/ncFgJCYm/v777wDg6Oj41VdfcX6y4zheXl7u7++fmprq4OAwd+5c7NO3DXQ6vampqaio6MCBAziOu7q6enh4KCgoELkVFRXV1dUnT54sKCgwMTFZtGiRpqamnJxcD/a7H4NU1kkeP368f/9+VVVVAKiqqvrll18mTJjQ20JJQjdZAovFampqKikpOXDgAIvFWrly5dixH65RzM/PDw8PnzVr1o4dO/bu3dtzXe3PIDX1KfTd7ShUqfLoNMIzUhaRQgSnfP1nGE9JjEaVzDMSv+WPqudZpivd+SNiTPLf/o/50udb/9CZasO5A7U4NEHZYpiSqb44lRt6OLje2f9sw8mwWTuJFPVxIyde2spxwei62k67d/DJqqMhUzcDgIqVsc2exYQbAgAsNs6pyy3OPhdcHJoAAMO+nmj/v3WRC3m3sUjW+szw36K+Pfhk9e9E1iAVRbv/rRsu6CpiiYfdJWDXP2ZLXuzz13a2FnZkoCxK8C4YnNlGeEakFWQtNsx5vPQIm9VOwbDhXs4OJzcQZUYsmS5Fk36+9WzozO1A3NKycMr4o2s4pzwMPRxcAvfEf386ZNpWAKBQpUZ9/8143/8IE5gDBcPEHx89t3GqX5oU3IwuuBk9fMFkkVJxI6elMiVwd/QK3zsO6wgJzf/raXtw5e1xa6riMw3c7STuAg8iTREATJZOzzgRpDPFhuecjjjPcsBZ7W1NLZwIQaYrZjIq3iX/fDXnYggAyKgpTbq6ndtrIK+jNuPBkSifQw9mbCM6aL3j2y93LupoB8kh78LwBc44qz3ue7/7Lt8DgIqV8bjDq+K+Py2sKmEa4bEEngc7ZBjcdMgaEQh+KGy26GA2CESXQ6F8CODU3RY4Y8aM0NDQoKCgOXPm8GTJy8szGIyIiAhnZ96/mDdu3AgLC7tw4YKwaul0uqqqKpVKbWlp4X7bSTBhwoTY2Nhbt255enoKfBxBAlKZZISEhMycOTM6OtrJyQkAYmJiJk6ceP/+fTc3yS+27F26yRKYTKasrCyNRmtubuZZk2/cuPHEiRN79uxBq27xQWrqKigUyiq2gB0B4vNkzbHiB8+9C6+LLtr9MMrpf+t+Y39iPU/AAnEerM0qUrU2FhYvlp72hionM8RYJ/vC/ZiVv7k9+k13ig2R1c5sq3z2auioYTIqQyQWW1jr7cy2iqcZ8rqqnDAQfYoHM7dXxLxc2hhCDIL6WFPO1arcNOSXNZfUqI8fyX0mhacAo4yuPt6soyewxB+fdmYbBcO46xcpFQc2jr/LKGDjbBVLI2HHZCTuAg8iTbE7nsVZ7ZXPXtGU5DkeRn5qMwsZFbVaTpZddUpOICRdYOM4PS2fpihHxCURiTCN8FsC/4NiGgYPnZyt5yiTeZYnPbZsQfQuaM8IYoBDbLpmMBj8WYMHD2YwGK2trfxZgYGBAQEBJNVGREQAgKOjI/8am8VixcXFYRjGvxhAiANSmQQwGAwfHx93d3fCLQIATk5O06dPX7ZsWWFhoYyM6AiIfZBusoTQ0FAcx52dnTG+X9VTp049ceKEr6/vAFtydytITX2H0VvmE5sm9KaP7W1ZIOuPe3I6qqYrZ3b0QTktFfLjDyQrRimatDgxGiVrXYomreNs3ZnKewbyQVA00iZfzYosQNKumOPDv8oVv1EKhpEYQEdrI0ekKXbHsxhVSsvJkryMspmhspC7crsQki5QMEzVylj8qoRpRKS/owesEYHgBkVgRfQDHj9+PFgQhoaGIp+Vl5cHgOrqap70+Pj4yspKAOD/1f7XX3/Nnz+f/Bx7WFgYAHBWoTxZOI5bWFigQBWSgVQmAVevXqXT6V5eXtyJCxcurKys5InpAACGhoYCJ9Tjx4+7XLA+OHmjo6MBwMFBwAWZTCYThCzyEcL4TNTUk7NGYhSNtC2++5pzW0cv0tbUkn48aNzhVR1904tAIBAIRG+B9owg+gHEsXM9PT0TExPu9MGDRe9RJAJG5Obm8qT7+vq6u7sHBwfz/LxubW29c+fOP//8Q15tbGwsAAgM4vDs2TMQsgJHiANSmQRERkYCgJGREXeitrY2AISGhi5ZsoQ73draurGxkTslNze3uLiYxWJ1uWD9a/ISq3ELC9FXaSA4fCZq6slZ0xnG/Lzklu3qwrux/KFAepLUw9d0nL809nbp1lYU9NX13MbLqEp4cGaAoW47QpyrYREIBAIhDOQZQfQbvvrqq9OnBQd5IoF4Nd3S0sKdeOXKlcWLFxPv0ktKPrmY/fDhw7t27SKvk06nZ2dnU6lUgYcvnj59CgAuLt37i3AAg1QmAcnJyQDACXJJMGbMGACIj4/nKXzr1i2elLVr1/r5+XWfeH1n8jKZzMTERBqNxr/kbm1tJc53HDhwoKOifs58Jmrq+VkjGdIKst9kXe1tKcB2//IeaEXX1bYL7yvt79jsXdLbIiAQCET/Bp2mQQxwdHV1AaC5uZmTwmAwQkNDPTw8iFed3LdOlpaWVlZW8iwv+eFErOA/AM9isWJjY/t1xIpeB6lMAoqLiwGAJ54I8bW8vLx3ZOo03WEJJNErVq9eXV1dffbsWQ8Pjy7rw2cAUhMCgUAgEIgBANozghjgED/NuQ+6Hzx4cPfu3fDxVSf3Tu89e/bs27dPZJ3h4eEAkJycTJxW4IbJZLJYLEtLy/4bsaLXQSrrKDiOE1v6+ZeR8DEoQ3+kOyyBOIihoqJCmAQA4DheUFDg5+enrKyckpJiZdWp8I2fIUhNCAQCgUAgBgDIM4IY4PC8tHz79m19fb2ZmRl8fNXJ2QQeHx9vZGSkpaUlss4nT54AQFBQ0JQpU3iytm3b9uuvvwqLWJGRkSHO2Xgxiw1U+pfKcBwPDQ0FACcnJwUFBZ7cmJiYurq6cePGaWhoiBRSYvpapIOuojssgYheUV9fzzkcoaysbGpqGhISoqOjw1MYTVhx6F01dVJHPTNDEQgEAoFA9H2QZwQxwCF+tXMOuv/888++vr7cWZxXnUeOHAkMDBRZIXnECuIHPU/Eitzc3MzMzIiIiLNnz7a1tQmrWcxiA55+pLK0tLTz58+7uLiUlpauWLFi+/bt69evJ7KamppcXV23bt1qY2OzevXqefPmeXt7ixRVMjh3fOA4zr9tROBGkn5Bl1sCEb0Cw7CgoCCSi1HQhO0QvaKmzuuoJ2coAoFAIBCIvk9//cWMQIgJEYSS2M4dExNjYmKiovLhenbiDX9WVhYA+Pv7e3l5kd8iSUAesSIuLo4/YgWDwaDRaFOnTiV/ty9msQFPP1LZ4cOHjx8/7unpuXbt2lOnTm3YsIEI5goAO3bssLGx8fT01NPTO3Xq1NKlS7s13gexBOU5OEOsSIms/kiXWwIRvcLW1pa8MJqwHaJX1NR5HfXwDEUgEAgEAtHHQZ4RxACHWBayWCwcx48ePbp161ZOFhFXgk6nMxiMe/fuffPNN+JUSJx7F3iXZFhYGI7jFhYWPBErrKys3NzcqFQRW7TELDbg6S8qa2hoCAgIWLt2LfHV09MTAK5cuQIAOI5fuHCBsw9FR0fH1NT02rVr4kgrGePGjQOA7Oxs7sTU1FQAsLa27r52u5UutwQieoWdnR15MTRhO0SvqKmTOur5GYpAIBAIBKKPgzwjiAEOlUoldgocP3586dKl3LsGiPsRGAzGr7/+KvIWSQ7E4Qt7e3v+LGK/gLCIFQgx6S8qU1BQWL169YwZM7gTpaWlASA7O5vBYHB7WwwNDRMTEyVoRUwI90dubi53Yk1NDQCYm5t3X7vdSjdZwuTJk7tB2M+X/qimnp+hCAQCgUAg+jjIM4IY+BB3l4aFhRFv9TkQO71ZLFZ1dbXIWyQJ6HR6ZmYmlUrlD+QJH5fZPBEr+jhhYWGrVq3i2UbOnyiwWPfRL1SGYdiZM2c4V4dGRkYCwKJFi+BjNMqRI0dyCsvKyjY2NkrQipjMnTsXAKKiorgTHz16BAALFy7svna7my60BE70iv57PbOYs1VYYvfR79TU8zMUgUAgEAhEH+dz3waM+BzQ19fPzs7mBAXkgGEYlUql0Wh79+4VsyriogQ7Ozv+7dm1tbXEq87+te6aN29eQ0MDAJw7d44kUWCx7qPfqQzH8S1btnz//ffEzhQiqMHgwYN5ynSyFRLs7e0dHByuXbt28OBBZWVlAGhqarp27dr06dMFHiPqL3ShJdy4cYM4OcV/hVB/QczZKiyx++h3aur5GSoxr07frkl5Pd539SDlf6VlVL5L3HERAMb8vEReR40nXdPeYsSyGeUxabn+D83XzVa1MuapM+fSg4pnGVY/eg8x5r2PqWth43j+jccl4ck4kyWvq2bs7TLUYhh3gdLIlLxr4e2tTDWbESZLpnH3sT+SfjyoIa/U4eQGgbmvTt+uyy7izm2l18uoDOkp6ToMiXgiNctPyLStNnsWa9iT7WGsfPYqafcl19v7pRVkAeDBjG3m62fru40neaQ6KSf36sPGwor2lvfSg+U07C1G/sedpihP5KYfD2oqrLA7tpZcNgQCgSBAe0YQAx8jI6Ply5cLvLJRTk5u165dampq/FncsFgsQ0NDZWXllStXAsCTJ0+UlZVHjRpSXtWeAAAgAElEQVRF5K5atUpdXV1dXZ34Ya2lpaWpqZmUlNTV/egWvL295eTk5syZQ54osFj30e9UtmnTJmdn56NHjxJfCS9MRUUFp0B7e3t33xHzzz//aGpqLliwIC8vLzc3d/78+UZGRv7+/t3aaHfTeUsgKlFWVl68eDEAZGRkKCsrf/HFF10va/cj5mwVlth99Ds19coMlQwW433OxZCyqBTuxLKIlJyLITkXQ4ofJHCnl0en5VwMwdtYAFCfW5xzMaSpsAL4KHucmnMxhFFG71bJ39c23rJdE+G1j56Sx6xvzjxz5+aoZa9O3+YUeLr2+H2X76ueZ72nN8RvPnNz1LKm4qpuFam7KQlLyr0SKiy3NDyZk1uXXfSP+dKalLyeEq1jkIsnUrPcsHG84mk6AFQ8TW9jtDa+rSDRcnVyblViDuEWaXxbURyagFGlhBXGWe2Plxy+Zbs68+xdnMmSHixXm/n2+dazN0wXVyV8CLlVEpaU+2eY+B1HIBCfOWjPCGLgM3/+/JkzZwrM2r9/PyeCJglUKrWwsFBY7rlz53rmxWx3cObMmTNnzohMFFis++hfKjt27JiRkdHGjRs5KYaGhgBQWFhobPzhbW1rayvPC+ouR0tLKysrKzg4+K+//sIwbM2aNe7u7t3aYg/QeUuAj0cnBgBizlZhid1Hv1NTr8xQydCebAUAFU/Sh835NxzS27uxQ0z0mPVNpeHJpiv+HfmSsEQA0HMb1/Ny8vN827maF7mud/YbejgAQFtTywO3H2PXHdeebKVsZlgUEp/pd3vU99/YHV0DALWZhXcc1kctOvjV4//1tuDdxehtXiOWuxGfqxKyazMLe1UcMsjFI9csT+HymLTgyZuGWg7HWe2pB/8ui0oxXzdb2LaayrhXOs4fQoZXPc+mYJi285fCxIjyOfQmIMJk8TSHUxsJZwoAFN5+GuG1L9R9+/wc//6+BQmBQPQ8ffENCQLRtfj4+HBukeRh/fr1ffM94WdOP1LZ9evXVVRUOG6RH374AQDMzMzk5OSIAKgE6enpAt+ody0Yhnl4eOzdu3f37t0DwC0C/coSPmf6nZp6a4ZKgNqYEdIKslWJ/147xcbxovvx2s7W2pOsCu/EsrkOAVU9z1I01lHQU+8NST+BjeO5Vx/qutoSi2cAkFaQtfrRCwDe3n0GAK9O3pKSoY09tILIVTYzHLVxbnn0yy70F7Qz2yTI6mh5tpBDWDirnSdFY7yZgbuIi7EE1kYurTABxKdDoyFSszxoT7L6tuym9iQrnNnGYrTOijttf3ydsMprknOVzQ2Jz1XPs4aY6ArbM1L2OPVNQITe9LGTrvzIcYsAgKHnBJs9i1ur6zJO3iLpBXmXJbYcfqWL/ywCgegLoD0jCERvcvv27V27dgUHBxsYGPS2LAix4FZZZGTk7du3PT09r1+/DgDFxcW2trYAgGGYl5dXSEjIggULAODt27fFxcXe3t69LDqic6DZ2vcRU0f9a4bqzxyfHxTDxnEKhgFA5bNXbU0tetNs21uZbwKjymPStCdZAQCzobk2o2Dkag+JG7o/5YeW6vqvX14gvjIbmgOMvJXNDD1ijhMpdbnFd+zX2e5bbrbGI3b9CVbLe4H1TLywhY2zXQJ2yqgqcadjNGkAYDYwAKAkPNnA3U6KJs3JVRtrCgBlUan8+w46JNjrvx699A2szSggRkzTcZT9ifUqlsMBoKW67vmWs3kBkTizjUKV0nK0tD+xniRABklVEQt+wWjSGnbmsRtOYFSpSZe3DV/wIV5V4d3YuO9ONxaUS8nQTFfMHHtoJbF0j/I5VB7z0rvwevQK3/zAKAB4NHvXIBVF78LrAmsjaZ1fAMNZDiXhyTNCjqiPNeXIn3486MU+/1nPTimZ6InfO37xuJ8SqVl+mI2MXP+HDqc2Jvx0oToxR2O8GU+BsNm7yp+kAcB7ekPG8aDMs3cBoK2xBQCuqs6a7L+dP9RI1tm7APDlLh/+5szXzZZRHaLpJCDkM/mQkpgHueW8yyiI++5UWVQqG8dl1JTMVnt8uduH49PpqNUhEIheBHlGEIhu59mzZ35+fikpKQDg5ORkZGR06tQpIr5gTU1NUVFRdHS0j48PSTFEDyOOyubMmTNr1qympqbAwEDOgxEREcSHAwcOjBs3Ljg42M7Obt26dX5+fkZGRr3SF0RHEaZ97tlKUqyXpf886LyO+tEM1Zli8yYwquzxS+KgQUlYEgXD9NzGMeubAaA0PJnwjJSGJwOA3jRbiRvSsLd4sc+/LreYWEgXhzx/T2+ojM1gNjQTIS2L7z9/T2/QnTYGAHKvhLY1tQisZ+KFLRhVivv4D0Hx/XiiO8yGZjarfZCKIneuhp05ANSkvO6MYK9O345dd1xv+ljr7d4YjVr1PDvt9xuhbj96FwVSMCxs9q667KLxv61RMFBnlNKT9ly+67hhYfEN7k0HHMirYja2NOa/yQuIMPRwYJTTh5jqE0+xWpmP5u6x3r5Q9csvKmIz0n4LfJeeTxwRamtkvKc3AICx9xTA2TmXH5iu+mroqGEAwF8beev8jwxf4PwmMOr1n2HcnpHsC/cHG2gKdIuQ1M8vHjfkmuVvCACaiqoMZzmYr/Wkyg5qyC/jL6A1yUpOW7Uxv6w4NMH426lEBzP9buu62ioa68jrCohSVPwwUUqGJjCeq7SCLPcRM3G6TLRIYh4kWdVJOcGTNw1SUZzg952shnL5k/QX+/zpL99Mu7OfaLdDVodAIHoX5BlBILode3t74soSflasWLFs2bJr166RF0P0MOKoTEFBgeSaTw0Njfz8/NDQ0IiIiGPHjnHCGSD6PsK0zz1bSYoheoDO66gfzVBtZ2sAqIrPJDwjxaEJmo6jpGjSsmpKKlbGRffjbfcvB4CyqFTCY8L9bNjsXeI3pO9u92Kff1lEygcHRGiCorFOQ15paXgysRh+e+/ZUMvhikbaALC0MaRDvSgJS0z/302tiaN1nK1LI1MAQGoQjbsAVV4GAHAmqzOCpR4JUDYznPHgCPHgsDlO7a3MjBNB1Um5Qy0MK2MzRm/1slg/m8ilDZF/depWbeZbbm8CB5KqiPJ12UVO5zfzLMLZrHbHs9+P/M9XAGDoOYE2RD5p16WikHjuXQ86ztbNJdU5lx/ozRir+9GbwFPbQ48d5K3zP6JhZ54XEGF/fB2xzqenvanNKLD7n+CjKyS9EygeCdyaFVhAd4oNUc+IZTMEFhi1cS4ApB+7WfHsleOZTQDQkF+W6Xfbese3WoK2fgAAs65JzVaA1kggVyiL0SrMPMgtJ3bdcQpVyvO5n5zGUAAw9JwgqzYkYfv54tAEveljSaoVaHUIBKJ3QZ4RBKKXCQ8PHzNmTG9LgegAYqoMwzA3N7cekAfRY6DZ2vcRX0f9ZYYqGmkPHqZVk5wLAO9rG6sTs8ceWklk6bravvw1gLhdtfLZK8Jjwv2sjsuXCoaaPBWWR79syCvlb0h9rKmshnJpeLLZGg8AKAlLGrFsRvqxmyWPkofNcWpntpVHv7TaLsmZo5KwxIezdioYaLgE7gbS0BgCIzWIL5h3YQDPThYZtSEAwGxoxmjSGE369Z9hKqOHG85xpMrQjL1djL1dhElCUhXxlYJhJkum8zwlJUMzXfmvr8R8rWfSrkv5Nx6TXz3LX5vI1vkfMVk87cnq34tDE4i2cq+GUahSX3w7RbLeiQmPZjtDxbMMjm+lOimXgmGaE8hC/8h8uudIJORdJjEPnNUuLKuluq7qeZbJ4mmEW4TAfN3shO3n31yP1Js+tqNWh0AgehfkGUEgepOmpqaEhARXV9feFgQhLkhlny1I9X2fgaoj7UlWeQERAFDyMBG4ji3oTLV5+WtA6aNkwzmO9NS8MfuW8Txovm62oecEnsQon0MCPSMAYODh8PrPMDaO1+eWMMrp2s5f1mUVVcSkAUBRcBwbxw0+xt3MuxYhLN6kic8n45/rHxa99MhgIy2PmOPEAlJOcyj/U2ycDQBSNMG/S8UUjIJhjYUVBTdj6nOLm0qqqxNz8I9hLzGqlNP5zdFLj0Qu3E/BMA0HC4Ov7L/wmcq9puWGpCoCqtwg/vig6uNGUrhCDg9SHiwlQ2ulNwhsgqQ2ka3zP2K8cMrTdcfzrkXou41n43je348M3O1kVIZI1jtx4NesZLBamWxWe3Vi9rC5EwnnRVlUipKpPovxHgCkZGj840yVk6l49qpDrZB3mcQ8SLKqE7MBIC8g8m1wHE9zhNI7anUIBKJ3QZ4RBKI3aWlp2bx5c29LgegASGWfLUj1fZ+BqiPd6WNzLj+ozSwsvP1URk1JbcwIIl3H2ZpClSoOTZCSG8TGcW0hxxnEx9DTIft8cHlM2rv0AgpVSnvS6Pqc4oL/i2mprisKjpfTUuEcAXjyn6PC4oxwe0bifjiT/vsNTUfLaXf2c25RHWKiCwBtjZ8E7GwqqgQAWSErRjEFS/7FP3nPZaqcjK7rmKGjjCzWzW7IL0/ccYEjmO5Um/ybMSVhicWhCRVP0pL3XnGPOibwXAN5VcKgyg7iSaFIdDeTBK1LK8gae7nkBUQ4XdhS8TS9pbKWe/dK5+vnQaBmJeOh+/bSiBcAkP77jfTfb3DSLw92AwDXW/v4vXtaTpbFoQmMyncCXQxRPoe0J1nxHN4R2WUS8xCWRTxoNG8iESWHm8HDNEVWK9lwIRCI7gN5RhCI3kRNTUBoMURfBqnsswWpvu8zUHWkN90WAKqTcstj0vSmj+WkUzBM3208/eUbGTUlmpIC/60fHW9oLEaTLg1Prssq0nW1pWCY9mQrACiLePE2OG74/Mmckt+WB4msLXqFb87FkOFeLpP9t3O/9peiSctpqfAE46zNKAAA9XGCl4viCFafV5q857KGnbn742OcU0XJe69wKmlntlHlZSzWz7ZYPxtntWf9cS923fGXRwKmBv3M05zIqoRRGZ/J/bWtqYXFaO3ouQ+JW//Cx/X1n2FvrkeWP06VUVPiNpUuqZ+DMM1Kxpj9y9XHm6Uc+Mv1zn6itodf7Rj1/TxCxao2JvyPGHpOKA5NyLn4wPqnhTxZFU/TX/8Z9r62kdszIk6XScxDWJbtgeUAQBuiYL7Wk7sqViuTKkMTWW3nhg2BQHQ9kniyEQgEAoFAIBA9A01RXvVLk9f+DxnldP1PY6zqTR/7LqOgOjG7M7fScKBg2LDZE4ofJBSHJhBX3iiZ6stqKCf/fLW1us5glgOnpLSCrLB/RIGUg3/nXAwZudrD5dpO/sWz0bxJlbEZdbnFnJTs8/elZGi6roJ7IY5gddlFAGDgYc8dbKXg1lMAwJlthXdjLw5yzb0aRqRjVCmzNR4UqpTAoCfkVZEMILOuids5knnmLgAM+3qi4NJC4q1I3LruFBt5PfWS0ISCoJgvFrkK264ibv1CxCPXrARojDejysnIqCkZejjou41X0Ndg4/iwuU76buP13cYL3BVisnS6vJ56yoG/ymPSuNNbquuil/sCgPWOb7nTRXaZxDxIspRM9RUMNAqCot/X/huO/W1w3CXZafFbzpJX28lBQyAQ3QHaM4JAIBAIBALRp9F2tk77LZCCYbqfekC0XazZrPby6JeT//ypSxrSd7eLWnQQAIg39gCg62r7+s8wqpyMsMtH+GFUvkv++SoAsJpbo3wOfSLwJKsRy2aM3jo/51LIg+nbJvh9N9hI69XJW8WhCWP2LSO5ylSkYGo2JhhN+tWpW1pOo1XHmNQk5SbtvlSfWwwAbJxt4G43eJhW4k/npWhUFesvmA3NORfus1nt3BthOJBXRdJxaQXZR3N2j/9tzRAT3fLolwk/ndd0tDRwt+MpRoRTyTp/n1FRyxOWpTOtA4CJj2vKgb8A4ItFU4WVEVk/iXgiNUsunjBqknO1HD9cQ/MuLZ9ClSI/bCJFk3a5tvPBjG3BkzcZzZto6DkBo1HfpeVnnr3bUllrs2cxz/4pkV0mMQ9yy7E/sT5s1s67ThttDyyX11alp+bFbzkro6Zkufkb8molGygEAtGtIM8IAoFAIBAIRJ9Gx+XLtN8C1WxH8MR0UDLRGzxMq7GgXMflyy5pSH/meAqGURVkOdFM9N3Gvf4zzGCWg/ghM8oiUohX8a//DOPJwmjUEctmyOuozXhwJMrn0IMZ2wCAQpWy3vHtlzsXdUYwOS2VKYG7o1f43nFYR9Rp/l9P24Mrb49bUxWfaeBuNzP8t6hvDz5Z/Tvx+CAVRbv/rRu+wJm/LZFVCRNS02m0poNF1OJDbFY7AAz3cnE8u4m/mJ7bONUvTQpuRhfcjB6+gHeRLHHrAGCyZHrKgb+ULYapWgm9iFpk/Tzice+zEKlZEtlIqIx7ZfbfWR+aeJyqZmMi0tg0J4yanfxH/A9n8v+JfhMYRSQqmerbC9KpyC5TMIzEPEiyDD0cXO/sf7bhZNisnUSu+riREy9tJba6kFeLQCD6GhQ2W4T7GYHoDigUCvFBHAsMDw+fOnXqf//739OnT4vfREJCQn5+PneKoaHh+PHjASAmJqas7JMTzmZmZpaWH95XXL9+nTvr66+/plL/9SGyWKybN2/ytKWgoODu7k6IWlNTw5Pr5uamqNixY8afJ0hlvcXatWv9/PwePXo0ZYrgKx4lpk9NXhzHb9y4AUJQVFScMmUKjUYTX87PnM9cTV0+aygUyip2VJdU1Y+ozSxkVNRqOVl2ybkMAGDj+LuMAjbOVrE0Eri6bme2VTzNkNdVVTLR62RVwsBZ7RVP09XGjCDZAkNIQsEwYR2XrPXGtxUBhl52v68dtelr8pLiDBSJeF1LSXjy0FHDCG8CPe0NBcOGWgwT81k2jte8eP2+rmmouaGclgp5SZFDSmIe5JbDKKfXZhWpWhsLjEcrvtUh+gLnKJN5licdWrYg+i9ozwhiwNLQ0JCZmenr69va2mplZTV37lx9fX0ii8FgJCYm/v777wDg6Oj41VdfcX6y4zheXl7u7++fmprq4OAwd+5c7NP/Pul0elNTU1FR0YEDB3Acd3V19fDwUFBQIHIrKiqqq6tPnjxZUFBgYmKyaNEiTU1NOTm5Hux3PwaprJM8fvx4//79qqqqAFBVVfXLL79MmMAb0r9f0E2WwGKxmpqaSkpKDhw4wGKxVq5cOXbshwiF+fn54eHhs2bN2rFjx969e3uuq/0ZpCZE51E2M1Q2M+zCCikYpmI5nKSAFE1azGNBIqsSBkaVIoKhkMO9F6OrWs/6I5hClfrCR+hRGvHrJxeva9H9eBE1AHS01xQM42wjEllSZOUk5kFuOXJaKiR+GfGtDoFA9CJozwiid+iBPSMEM2bMCA0NDQoKmjNnDk+WvLw8g8GIiIhwdubd1njjxo2wsLALF4TeYEen01VVValUaktLC/fbToIJEybExsbeunXL09NT4OMIEpDKJCMkJGTmzJnR0dFOTk4AEBMTM3HixPv377u5uYl8tq/tGSHoJktgMpmysrI0Gq25uZlnTb5x48YTJ07s2bMHrbrF57NVE9ozguhTRPkcYtY3v70ba7l5/njf1b0tDgLRj0F7Rj5b0N00iAEOsemawWDwZw0ePBgAWltb+bMCAwP9/PxIqo2IiAAAR0dH/jU2i8WKi4vDMIx/MYAQB6QyCWAwGD4+Pu7u7oRbBACcnJymT5++bNkygcPVL+gmSwgNDcVx3NnZGePbTT116lQA8PX1lVjmzxCkJgSiL1CT8rokLNFk8bQx+5b1tiwIBALRL0GnaRADHHl5eQCorq7mSY+Pj6+srARBv9r/+uuv+fPnk59jDwsLAwDOKpQnC8dxS0vLzypQRReCVCYBV69epdPpXl5e3IkLFy4MDQ29fv36kiVLekmuTtFNlhAdHQ0ADg4O/FlMJhOELPIRwkBqQiD6AvPSL/W2CAgEAtG/QXtGEAMcImBEbm4uT7qvry8RgJPn53Vra+udO3e++eYb8mpjY2MBQGAQh2fPnoGQFThCHJDKJCAyMhIAjIyMuBO1tbUBIDQ0tHdk6jQ9bwnEatzCwqITUn92IDUhEAgEAoEYACDPCGKAY2hoCAAtLS3ciVeuXFm8eDGx07ukpIQ76/Dhw7t27SKvk06nZ2dnU6lUgYcvnj59CgAuLi6dE/zzBalMApKTkwGAE+SSYMyYMQAQHx/fOzJ1mu6wBCaTmZiYSKPR+Jfcra2tAQEBAHDgwIFOy/4ZgdSEQCAQCARiAIA8I4gBjq6uLgA0NzdzUhgMRmhoqIeHB/Gqk/vWydLS0srKSp7lJT+ciBX8B+BZLFZsbGy/jljR6yCVSUBxcTEAyMjIcCcSX8vLy3tHpk7THZZAEr1i9erV1dXVZ8+e9fDw6LI+fAYgNSEQCAQCgRgAoDgjiAEO8dOc+6D7wYMHd+/eDR9fdXLv9N6zZ8++fftE1hkeHg4AycnJxGkFbphMJovF6tcRK3odpLKOguM4i8UCAP5lJHwMytAf6Q5LIA5iqKioECYBADiOFxQU+Pn5KSsrp6SkWFmJvmsTwQ1SEwKBQCAQiAEA8owgBjg8Ly3fvn1bX19vZmYGH191cjaBx8fHGxkZaWlpiazzyZMnABAUFMR/WeO2bdt+/fVX/ogVOI4T4R6cnJwUFBTI68/IyPicj9D3L5WRF4uJiamrqxs3bpyGhoZIISWGcIsMPLrDEojoFfX19bdu3SJSlJWVTU1NQ0JCdHR0OMXQhBWf3lJTl+ioZ2YoAoFAIBCIvg86TYMY4BC/2jkH3X/++ee9e/dyZ3FedR45cmTz5s0iKySPWEH8oOeJWJGWlrZx40Ymk1lQUGBiYnLy5EmBNefm5t6+fXv9+vXW1tbidW5g0o9URlKsqanJ3t7+3bt31tbWq1evvnbtmkg5JYZzxweO4/y5AjeS9Au63BKI6BUYhgUFBZ3+yP79+7/99ltutwiasB2iV9TUeR315AxFIBAIBALR90F7RhADHCIIJbGdOyYmxsTEREVFhcgiXjNmZWUBgL+/v5eXF/ktkgTkESvi4uL4I1YcPnz4r7/+IspraWnNnTvX2tqaP7Igg8Gg0WhTp049deqURH0dIPQjlZEU27Fjh42NjaenJwCcOnXKyMho8uTJ4rwtlww5OTkGg8FkMrlDjRArUmJ12h/pcksgoleMGzeOvDCasB2iV9TUeR318AxFIBAIBALRx+mv7xIRCDEhloUsFgvH8aNHj27dupWTRcSVoNPpDAbj3r17Im+RJCDOvQu8SzIsLAzHcQsLC+6IFQ0NDQEBAWvXriW+Ej/Er1y5wv+4lZWVm5sblfq5+yv7i8pIiuE4fuHCBc4+FB0dHVNT0259KT1u3DgAyM7O5k5MTU0FgP67o6HLLYGIXmFnZ0dSBk3YjtLzauq8jnp+hiIQCAQCgejjIM8IYoBDpVKJ94rHjx9funQp964B4n4EBoPx66+/irxFkgNx+MLe3p4/i7j8lSdihYKCwurVq2fMmMGdKC0t3bFufE70F5WRFMvOzmYwGNzeFkNDw8TERDEFlgDC/ZGbm8udWFNTAwDm5ubd12630k2WMHnyZJIyaMJ2lJ5XU+d11PMzVGJenb4dvcL3fW0jdyKj8l30Ct/oFb7NpdX86TmXHgBAeUxa9ArfmtQ8/jpzLj2IXuFbn1fKn5V+PCh2/YnOi/36r0ePlxyO8jmU9cc9VqvgINDNpdURC37BWe3CKnl1+naXCNPzPF5yuDg0AcQbz5BpWyufvZKglcwzd1MO/i2yQmHqrknNi17h+3Tt8VZ6vQStd5L040Fxm053dysibQyBQCC4QZ4RxMCHOF8QFhZGvFrkQOz0ZrFY1dXVIm+RJKDT6ZmZmVQqlT+QJ3xcZvNErMAw7MyZM5wLJiMjIwFg0aJFkvSkGwgLC1u1ahXPxa78iQKLdR/9QmUkxYholCNHjuQUlpWVbWxshG5j7ty5ABAVFcWd+OjRIwBYuHBh97Xb3XShJXCiV5Bfz9yXJ6yYs1VYYvfRw2rqvI56foZKDIvxPudiSFlUCndiWURKzsWQnIshxQ8SuNPLo9NyLobgbSwAqM8tzrkY0lRYwV9n2ePUnIshjDI6f1ZJWFLuldDOCMxsaL5jvy5q0cGq51nM+ubYDSdvjlrW+JZXDBajNXz+L28Co9iCoiMRlIYnd1KYXuGlb2BFbIau6xggHU82jlc8TQeAiqfpbYzWxrcVTcVVHWrIwMMu+eer5TFp5BUKVHdNal7w5E15f4cbzp4gozKk473sLCVhSbl/hnVrE+LYGAKBQHDzuW8DRnwO6OvrZ2dn+/r68qRjGEalUmk0GideoEiIixLs7Oz4t2fX1tYSrzpJftDjOL5ly5bvv/9e4P6FXmHevHkNDQ0AcO7cOZJEgcW6j36nMp5ixGUxgwcP5ikjpswSYG9v7+DgcO3atYMHDyorKwNAU1PTtWvXpk+fLvAYUX+hCy3hxo0bxMkpkfeYcOhrE1bM2SossfvoRTVJpqOen6ESoz3ZCgAqnqQPm/Pv1ra3d2OHmOgx65tKw5NNV8zkpJeEJQKAntu4npeTw7MNJyvjXo09tNLqR28AYJTT7zisD3X/aV76JU6Z5tLqR3P3VD3PIq9q9DavEcvdulfcroZR+S5575WJF7dQRIW+Lo9JC568aajlcJzVnnrw77KoFPN1sx1ObhC/LXkdNYsNc56uOTbv1eUOVVidlHN/6mY2q93toa+Wk1guyz4Is6GZnvpG2dxAoGdHTBtDIBAIbtCeEcTAx8jIaPny5QKvbJSTk9u1a5eamhp5DSwWy9DQUFlZeeXKlQDw5MkTZWXlUaNGEbmrVq1SV1dXV1cnflhraWlpamomJSXx17Np0yZnZ+ejR492tktdh7e3t5yc3Jw5c8gTBRbrPvqdyniKEV6Yiop/X5O2t7d39x0x//zzj6am5oIFC/Ly8nJzc+fPn29kZOTv79+tjXY3nbcEohJlZeXFi9zD6yIAACAASURBVBcDQEZGhrKy8hdffCFO631twoo5W4Uldh+9qCbJdNQrM1Qy1MaMkFaQrUr8N4QQG8eL7sdrO1trT7IqvBPL/T686nmWorGOgp56lzTNxvGOvmzHWe2v/3ykYWdOuEUAQE5LZezBFbUZBUUh8URK+rGbN8yW1uUUD7UcTl6bxngzA3cB4WbamW0dEklgOhvHRR6ykGAEXv4aOEhZYfgCAd52ntq0J1l9W3ZTe5IVzmxjMVpnxZ22P76uQ20BgPk6z9rMwtd/PRK/wqqE7PtTNwMAiVuEZGQEDojIgRLzPEuHNFuVkH1v4saKJ+n8WeLbGAKBQHCD9owgBj7z58+fOXOmwKz9+/dzwviRQKVSCwsLheWeO3dOnBezx44dMzIy2rhxo8iSPcmZM2fOnDkjMlFgse6jf6mMv5ihoSEAFBYWGhsbEymtra08L6i7HC0traysrODgYOLOjjVr1ri7u3driz1A5y0BPh6d6Ch9cMKKOVuFJXYfvaUmiXXUKzNUYvRnjs8PimHjOLENofLZq7amFr1ptu2tzDeBUeUxadqTrACA2dBcm1EwcrVH51ssjUyJ23T6XdobCoZpOFhMvLR1iPGH+5Jj159gtbwX+NTEC1uqE7LZOD509CfLUa3JVgBQ+ihZ3208ACTtvqTramt/Yl3Snivv0t6QiBHlc6g85qV34XXia0t13fMtZ/MCInFmG4UqpeVoaX9i/VCLYQKfrU7Keb71j/Lol2wcl9VQttgw1/qnD+cKK56mJ/x0oTI2g43jMmpKZqs9rHd+K0X7EKcmYsEvADBixcy4TadrMwooGKbpOMrpwpYhxjrPNp56/fejOcl/DDbQ5DSU8NOFrHP3vn55QV5HrZ3ZlnX2LvcuHvLxZDYycv0fOpzamPDTherEHI3xZven/NBSXf/1ywvEg8yG5gAjb2UzQ4+Y40RKXW7xHft1tvuWm63xAIDBBpqajpaZfne++HaqwAp5JKlKyA6ZtoUihc0MP6pqZcyT+y6jIO67U2VRqZyR+XK3D0aVIoYFo0lr2JnHbjiBUaUmXd5WePupsIESp0JuOqRZcRDfxhAIBIIb5BlB9AOampoAoK6uTrLHfXx8hGWtX79eQpk6yPXr11VUVDiS/PDDD33nRXQfpB+pTGAxMzMzOTk5IgAqQXp6+ooVK7pbZgzDPDw8OPEXxIeYXMRE61r66eRFE7ZD9IqaOqOjLpmh3TdreNCZYvMmMKrs8UsdZ2sAKAlLomCYnts4Zn0zAJSGJxOekdLwZADQm2bbyeZYrczQmT+arfaw3u5NT8tPPfR3iOsWr/wPF/fkXglta2oR+ODEC1uk5AbxpzNrmwCgqeRDsNjZiWeVTPXFkaStkfGe3sD5GjZ7V1120fjf1igYqDNK6Ul7Lt913LCw+Ia0gizPg1UJ2XcdN8hpDXX84/tBQwfn33icuOMCi9Fqu395SVjigxk/KhhoTPD7TkZtSFHI8xf7/CueprtH/v5B2saWuqy3b+/FjVzlbr19YWXcq1enbj2YsW3B67+M5k3MOBGU93cEx8nCxvGcSyFDLYbJ66gBQFFwHIvRqjPVRszxbCqqMpzlYL7Wkyo7qCG/DAA07C1e7POvyy1WMtEDgOKQ5+/pDZWxGcyGZpqiPAAU33/+nt6gO20Mp35d1zFJuy41FVcp6KnzV8gzLCHTtmDSVPfI3/n9DtVJOcGTNw1SUZzg952shnL5k/QX+/zpL99Mu7OfGJbG/Dd5ARGGHg6McvoQU32SgRKnQm7E16yYiG9jCAQCwQ3yjCD6AcSBcyUlpd4WREIiIyNv377t6el5/fp1ACguLra1/fDj9fbt27t27QoODjYwMOhVGRGfIKbKhBXDMMzLyyskJGTBggUA8Pbt2+LiYm9v797rkAiIySV+AA7x6Y+TV5ha0WztO3RSR10yQ7tv1vCg7WwNAFXxmYRnpDg0QdNxlBRNWlZNScXKuOh+vO3+5QBQFpVKeEy4nw2bLe6VQBzYrHany9uIPQjDFzgz65sz/W7T096oWA4HgKWNISTPqlgaScnQyh+ncna4AACxuYD98TyFZEtWFqO1MjZj9FYvi/WziRTaEPlXp27VZr5VH2vKUzjuu1NSMjTP535yGkMBYNgcp+YyeuqRAJu9S2JWHZVRG+L53E9WTYnIUtDXSN5zOedK6Igl04nHGwvKnf/eaeztAgDG3i7t79uyzwdXJ+VoThilaKyTF/CvZ6Q0MqWlsnbswZXE15JHyQCgM+UTzwjJeOpOsdGdYgMAI5Z9uGhJ393uxT7/soiUD56R0ARFY52GvNLS8GQi0Mzbe8+GWg5XNNLm1D/U0ggAKmMzFBY481fIoTox+8X+P5l1TVQ5GYwm4Md/7LrjFKoUZ9AMPSfIqg1J2H6+ODRBb/pYAKjLLnI6v5l7R4ywgVIbM0KcCiXQLADkXAklbKk2q4gY89aaD3frcGRDbhEEAiEZyDOCQHQvTU1Ns2bNampqCgwM5CRGREQQH2pqaoqKiqKjo318fJ49e+bn55eSkgIATk5ORkZGp06d6oGf3QgexFTZnDlzSIodOHBg3LhxwcHBdnZ269at8/PzMzIy6sleICSDRPvcsxUA0ITtLbpER/1ohioaaQ8eplWTnAsA72sbqxOzxx76sBTXdbV9+WtAK71eRmVI5bNXhMeE+1kdly8VDDV5KiyPftkg6MpeAgqGEWtdAk0Hi0y/280l1SpihGygYNioTfNSD/0d+tWOsYdWKOip512LePlbIIXvAEVHwWjSGE369Z9hKqOHG85xpMrQjL1duOXkwGplVsa9+mKRK7EgJ5h4aSsFo9S8eN30tnL0Vi/CLUIwevM3L36+WnQvjuMZoWDY8AX/XhqtYW+efT64paoWAEwWT0vadakmNY84ivLaP0xKhmb87YeLz5pLqqlyMlQZGs+YiD+e6mNNZTWUS8OTicMyJWFJI5bNSD92s+RR8rA5Tu3MtvLol1bbP3HhKZsZAkDV8yyBwU04xG8+I6+nPvbgyqf/PfZo7p45yX9wm0pLdV3V8yyTxdO4B8183eyE7effXI8kHBkUDDP5OEQiB0qcCgnE1yzBs/UnuHctZfrd5nzmP8eEQCAQHQJ5RhCI7kVBQYHkMsgVK1YsW7bs2rVrAGBvb99HrsD4zBFTZeTFNDQ08vPzQ0NDIyIijh07xglngOjjkKiVe7YCmrC9R5foqH/NUO1JVnkBEQBQ8jARuHYl6Ey1eflrQOmjZMM5jvTUvDH7lvE8aL5utqEn7+1UUT6HSDwjVLlB3PeqUDAKd27etQhh0TRNfFwBYOzBFS1VtTkXQ4pD4gFgkIqiy7WdD2ftlJIVcNBGfDCqlNP5zdFLj0Qu3E9E6zD4yv4Ln6ncC28C4uZaVRsT7kQi+EV1Ui5/FlVORlpRrjazkCuFZwT+/Wy63C15z5XXVx+qWhm3M9vyAiJMFrlyXAzM+mYp2U/cIoJqowApBh4Or/8MY+N4fW4Jo5yu7fxlXVZRRUwaABQFx7Fx3MDDgbu8vK4aALRyHTsSiKKxjkfMcTktFXram6yzd59v+YM7Pmt1YjYA5AVEvg2O43mQUzNVbhBPiBCSgRKnQgLxNUvgQ79DfCiLTHkwY5tL4B5DTweBJREIBKKjIM8IAtHLhIeHjxkzRnQ5RJ9BTJVhGObm1s+unESQg2Zr30d8HfWjGao7fWzO5Qe1mYWFt5/KqCkRpxUAQMfZmkKVKg5NkJIbxMZx4txNt/LkP0eFxRkhPCMAMPHCltFbF9BT30jRqHpu49g4u72Vyb1NQzJMfFx1p9rk34wpCUssDk2oeJKWvPeKe9Qx3jMXOA4APBs3uMGoAi4hYuNscWSQ01LRmWKTFxBhd2xt3rUINqud+9xKeytTzL6QYOjpkH0+uDwm7V16AYUqpT1pdH1OccH/xbRU1xUFx8tpqQg8YyISxz9+kNNSAQC7Y2vLIlMyTgRpu1gbfupkMZo3UcPOnOfBwcN49xyJj5gViqtZAADg+KGIjUhSNCrPPikEAoGQGOQZQSB6k6ampoSEBFdX194WBCEuSGWfLUj1fZ+BqiO96bYAUJ2UWx6Txn0SgYJh+m7j6S/fyKgp0ZQU+O8i6XK+LQ8iL0BPe8PG2apWxkSkDAAo+L8YANCaKPiCWPFpZ7ZR5WUs1s+2WD8bZ7Vn/XEvdt3xl0cCpgb9zF2MuBmn6nnWyP98xUmsSsguDk1QNjMAgLrsYu7yOKu9rYFBRLEVhxFLp0d47SuNTHntHzbERE9zwihOlqyGcu2rQkn79wG96WMxmnRpeHJdVpGuqy0Fw7QnWwFAWcSLt8Fxw+dP5in/nl4PAFR5GfJqOds9qDI0l8Ddt2z+83jx4a/TLhJ3PBOBS2hDFMzXenI/xWplkviYSOhQhWJqFoFAILobAY5zBALRY7S0tGzevLm3pUB0AKSyzxak+r7PQNURTVFe9UuT1/4PGeV0/U9jrOpNH/suo6A6Mbvzt9KIg7SCrLB/RIHHiw+Hz9vL/UjabzcGqSjqu9t1pt3Cu7EXB7nmXg0jvmJUKbM1HhSqFBvHeUrKaQxVMtUvCUtkce3geHXq1oufr2rYmcmoKeVefdjObONkZZ+/z8ZxDXsLMSUx+mYSTUkh+9y98uiXJouncWfJqimxGK3clUsABcOGzZ5Q/CChODSB8NcomerLaign/3y1tbrOYBbvyRH6yzcAoOkgrvwAoGplbPPzEmZdU4TXPiJFyVRfwUCjICj6fe2/59TeBsddkp0Wv+WsBL0Qv0LxNcuDjOoQPbfxsurKEoiHQCAQAkGeEQSiN1FTU5OREfGqB9GnQCr7bEGq7/sMYB1pO/8/e3ceEFXV/w/8wziOgLggIKIISESEuGuyKCmCIRIiZgIqWpqZa2nar80l02/mYz254G6574+IiIS4oShrKiIgEqKgiIgg4ojTePn9cW2aZr2zsM779Zfce+bczzmfc2vumXvP7XPv9B9GPJ7tv2dAOg/rUyt+WXL+mo5TD/rSfWZwVf6981NXVWQXPkzNPTVmcenlG+7/+UTHRx7sAz3adLNJ+2pLzqbjD1NzixMyzoR/Xyt+KX8PBRG9tXLas3uPTvovLI5PK0u/mb7o11u74l2mBbbuYjXwx4+f5BWd8P38bmxyeeafmasPXvp0XXsXu+5/vxhFLSMezzninT8PnCUi50n/ujvJdnh/+vv1ybqwC/R49EeeWFjD3i1CRLbDB1Tm3uWbGneRe2DqcWYBEUkesOKo7zcTrb3cSpOy0hf9ym7xXDP7eWlFtPfcwuiksvSbuVtPnJ24wtiqfc/P39euFRwr1Ciz0ix7O4048X/WnrJP6wAAaA1P0wAAAAA0al2G9c38zwGrAW+0Mm8jvb29c9c23Wye3i7pMqxvQ8UmzWXqSOGDxxlLd9zcFktExlbth+z4UrIEidaMeLyRCf85O2HFhek/sVtaWbT1+O8shS9kcQjyGnZgcfK89bHvLCQiI36LHvPed1/1MRG9Mdm/haBlysKNcSO/ZKt1Gu/rvvoTjZ4Zcf7AP2vNkS6+/Vp3sZLebhfoYcRvUXI+0y7AXeuWEpHdSHcjHo9vZiKZ77ALGHhrV7z9KC/pVU5ZRXGp5m7dtHhP7bB93x5ynfzHsp2dffp0HtLbIchr+LHvL81ZGz/qG7ZAx4Fvvr19obKVUNXiWKFGmQUAqFNGtbWcFp0C0C8jo1fLs3MZgQkJCX5+fjNmzFi/fn0dxwVgiGbOnBkZGXnq1ClfX1/91oyTF5orvZ81RkZG02rP6qWqBseIX5ZeuiFo35rLu3418lL014OLWa1tLSXrmKhQVXBfeL+8o7srT+61wVUF958VP+ro/qZ+1++88MnPRSdTwgv367FOFYQl5Xts3/dcM1tmOQ8d66zIuWvZx0lmDq6uK9QoswB1arPRUJnLE40uW6Dpwj0jAAAAAKA3PH4LG29dl1xVqIWgpfwTJcq0dezMLgWq0S5d9FowLndzTFFcqvRCuXUnZ9Nx0y6WLh+N1GOdpjYW7Fts6rlCjTILAFAXsM4IAAAAAICu2jp2dvv0vYwlv9XDsf6qfn79lyMDf5iG19YCAOgFZkYAAJqJc+fO+fr6hoaGhoaG+vj4XLx4saEjAgAwLP2XThY9eVYYnVTXB7r6w94uPn2dwofV9YEAAAwEnqYBAGgOYmNjR44cef78eW9vbyJKTEwcPHjwiRMnAgICGjo0AABD0dLM5P2cHfVwoAHfT6mHowAAGA6swAoNQ6OljEpKSk6dOuXs7OzurtN67wDNlVAotLOz8/DwOH78uGTjiBEjrly5UlhYqPY9psnJyXl5eX5+fjY2NvoNDCcvNFd6P2ua0wqsAABNF1ZgNVi4ZwSagBs3bkyaNGnGjBm4uAJQaMeOHeXl5WFhYdIbx48fHxcXt3///smTJ6v++K5du9i3bOh9ZgQnLzRXdXHWbDYaqq+qAAAAQCOYGQEAaPLOnDlDRI6OjtIbO3fuTERxcXFqZ0YAoMHhp0gAAIAGhBVYAbRUVlYWGxvb0FHUiWbcNIlm1saMjAwi6tnzX6/J7N+/PxElJyc3TEyNUjPLOzXHFslo9g0EAACAxgAzIwBaGjJkyMiRIxctWtTQgehfM26aRDNrY1FRERHJrCfC/llSUtIwMTVKzSzv1BxbJKPZNxAAAAAaA8yMAGiJx+MREZ/fDB9Ja8ZNk2hObWQYRiwW09+NkiESieo9osarOeWd1fxaJKPZNxAAAAAaA3zVANBSYmLilStXfHx8GjoQ/WvGTZNoTm1kp0WAi+aUd1bza5GMZt9AAAAAaAxwzwiAlszNzZvrl/Vm3DSJ5tRGgUDA/oNhGPm9Cm8kMVjNKe+s5tciGc2+gQAAANAY4J4RAIAmz9TUVCgUikQi6aVGampq2F0NFxcAcGVkZNTQIQAAABFeFmaoMDMCANDkDRw48OzZs7m5ub1795ZsvHr1KhH16dOn4eICAA3UTsN3cQCABma0GfPUBgp3WQMANHns9EdeXp70xkePHhFR9+7dGyYmAAAAAIAmAjMjAFqKj4+fNm1as3wlajNumkQza+OYMWOI6OzZs9IbT506RUTjx49vmJgapWaWd2qOLZLR7BsIAAAAjQGepgHQ0tixY6uqqoho8+bNDR2LnjXjpkk0szZ6enp6eXnt3bt3xYoV5ubmRFRdXb13715/f/9BgwY1dHSNSDPLOzXHFslo9g1Ua/vN7ZceXPp/vf+fUzsn6e1XH11dd2Ndqxatvuv/nYWxRT1H9cv1XwqrC3/2+Lmej8tReU15/feJWvUcVUJxwtoba5+Jn3U27bxz6E7dK2ycvQoAoC+4ZwRAS+Hh4aampiEhIQ0diP4146ZJNL82Hjp0qFOnTqGhofn5+Xl5eePGjXN0dNy5Uw/fhpuT5pf35tciGc2+gWqdu39u281t94X3pTdefXR1aMzQPfl7RjuMbpCL1fji+F15u+r/uGrlVuZ2P9T9yqMrDR3Iv9R/VPee3RsZNzLhXkJrfmvnds461tY4exUAQL9wzwiAljZs2LBhw4aGjqJONOOmSTS/NtrY2OTk5MTExOzevZvH433yySeBgYENHVSj0/zy3vxaJKPZN1AL6WXpfif8xLXi3wN+97bxbuhwGpfUh6nZFdkNHYWs+o8qoyxDxIjWD1o/1WWq7rU1zl4FANAvzIxAE/D48WMiKi0tbehAABo1Ho8XFBQUFBSk6QfZk4s90fQLJy80V3V31qiW+jD1ndh3iOj3gN89rT3lC4gZMZ+n9NsdU8vwjGTvF2ZqGSKS386lQmmilyJBCwGXkmoLK4yTeyQKK2RqGe4fV30s1cHrEqcMrfuBIYaILI0tNQ1PoySqiUHz4PV4dAAATeFpGmgCOnToQETW1tYNHQhA88SeXOyJpl84eaG5qruzRgV2WqSFUYuzgWdlpkWyHmf5nvBtsaVFy60tO+7suCh9kZgRS/aGng6NOBuxIXtDq62tTLaZ7P9zf+jp0NDToQnFCT0O9WA/NeT4kPwn+RwrlFb2vGzyucmttrZqta1Vyy0tfWJ8sh5nKWvC7lu7ex3u1WJLi1bbWrXY0mLI8SGZ5Zkq4tQokqnnp85MmklEo0+NdtjrwG68+OCid7R3y60tJR8XvRQpCy+9LN0nxoc9VqddnVZcWcExeLY/owuj7fbYtdzastXWVrOTZleJqpRFFXo69I0Db0hXvjNvp+UOy8SSRN37YXT86IlnJxLRxLMTJXWq/riKpsnHr/fgNRpCAAB1BPeMAAAAADR27LRIS17LM4Fn3Dq4Se9KL0sfGjPUopVF5KBIaxPrCyUXlv2x7Fr5tWPvHGMLPBU9LXhasC9/X5BDUImwxKWdy1PR05zKnON3jk97c9qXfb68XHp53Y11I06OuBV6i0uF0kbHj86tzP2P+3/szezvCe8tTl88OHpw0fgis5ZmMiXX31g/K2mWf1f/L/t8KeAJUh6m/JT5U0BcwN3wu+zNBfJxahRJuFM4Q8yvN3+d5jKtR4ceRBRfHD/i5Ah7M/vIQZFWxlaxd2OX/bHs4oOLZwLPKOzhwdGDbUxtNg3e1KFVh4MFB79O+1ooFn4/4Hu1wT8VPb32+NqRgiPLBizr2aHnH4/++Db92yuPrlwcdVE+Kral5TXl0kcXMaLyF+XsrI2O/fDxmx93Nu0cmR0Z8XpEH8s+r7V9TfXHVTdNPn69B899CAEA1B3MjAAAAAA0amllad//8X2lqNKUbyrgyT5uMCtpFt+InxKcYm1qTUTBDsFWJlZfpn4ZVxTn39WfLZNbmbvFe4v0qhO3n97e47Mn3CmciMKdwl+8fLEld0t6WXp/q/5cKmQJxcKk0qSFvRbOdpvNbmknaLfuxrrsiuy3Or4lE+fKqytdzV1PjjjJ/hnSLaTmZc2arDXpZemSwjJxuke5c4yEiHy6+BQ/K/715q8juo7wtfUlommJ06yMrVKCU6xMrNgj2pnZLc5Y/NvN3ya/MVnm459e/tS4hbHkWCHdQu4/u7/y6sol/ZbweXy1wd97dm/j4I0fv/kxEQXYBbRq0WphysL/3f5fSLcQmai40KUf/Lv617ysicyO9LP1C3YIJqIxp8ao+Ljqpsn3qn6D12gIAQDUHTxNAwAAANCofZ78eZuWbSIHRQrFwjGnxkg/D1L2vCzlYcooh1HsZSdrVvdZRMQ+yMDiGfEmO0+WrpNnxAt9LVTyJ/t4zsPnDzlWyBLwBAKeYNetXXvz99aIa4go3Cn80qhLCq9pC8MLL4+6LL3FytiKiNinTuTj1CgSeakPU+9U35nkPImdFmF93utznhHv+N3jMoVrxDWXSy/LHGv729tvjrvJrouhNnjjFsYfuXwk2fuJ6ydEdLjgsNo4FdJjP6j9OJe81F3wGg0hAIC6g3tGAAAAABo1p7ZOiUGJNqY2meWZG3M2LkhZ8IvnL+yutLI0ItqXvy/mTozMp6QfeTDlm8qsfGnKN5VeIFPyb44Vsvg8/hbvLR+c/2D8mfE8I56Xtde79u9GvB4hfRksfYjCp4WHbx/Oe5JXXF2cVpYmYmSX/JCOU6NI5BU+LSSifpb9ZOpv27Kt/JtWLj64KF/YqZ0T9+A9rD2k+9OspZkp3/SJ6InaOBXSYz+o/TiXvNRd8BoNIQCAuoOZEQAAAIBGbdPgTTamNkT0s8fPZ+6fWZO1ZljnYUEO/7yIaqzjWA9rD5lPdWvTTesjcq8wwjnCz9bvcMHh+OL4uKK4Cw8uLMlYcjbwrPxv/t9lfLc4Y7Ep33S47fAeHXrMcptVUFXwddrX+opEIYVvQmFfx/OvLcQQkTHfWFk9aoM3aWHCMSTt6NgPKj6uXV40ojp47kMIAKDuYGYEAAAAoFGTXN4b840PDDvQ72i/SecmZb6X2dWsq2NbRyJqJ2g3s/tM6Y/UiGtUXOeroGmFopei1vzWs91mz3abLWbEm3I2zUqatfLayiN+R6SL5T/JX5yx2MPa41zgOcmbWZdkLNFjJDI6mnQkotzKXOmNYkZc9VfVkM5DZAr36tCLiFIeprALhbBSH6bGFcVNcZnyXPxcbfAZjzKk/xSKhUKxsJ2gnbLw/mL+kv7zRsUNZSV17AfVH9ciL3oPnuMQAgCoU1hnBAAAAKDJ6G3Ze2m/pZWiyrDTYUTk0t7F3sz+yO0jFS8qJGVi7sSYbDdZkLxAi/o1qjC6MLrVtlY78nawf/J5/E9cP+Eb8eVvymBnKILsgySX30R09PZRIlL27IbWTWNvAPG28bYyttqRt0N6WZYtuVuYWkbmncdEZG1q7dLeJb44nl3qgrXuxrqlfyzlGfG4BF/6vJR9be2rA+VsIaL3HN+TiYolaCGoFldX/1Ut2XLmnoLX5ejYD1w+zj0vkvj1Gzz3IQQAUKcwMwIAAADQlHzT9xsva6+k0qRF6YuIaI3nmtLnpd7R3tGF0ell6Vtzt048O9HK2Orznp9rVz/3CgPtA7u16fZV2lebcjalPkxNKE4IPxMurhWPe22cTMl+Vv0EPMG6G+sulV4SvRRdKr3ke8I370keKXq2RYtIWOzl/ZacLTvzdvKMeD8O/DHvSZ7vCd/Yu7GZ5ZmrM1d/eulTl/Yus7vPlv/syrdW3nt2z/+kf3xxfHpZ+qL0Rbtu7ZrmMs3G1IZj8O+dem/3rd1XH1395fovC1MWDu40OKRbiExUbElvG2+mlhmbMDb2bmzMnZh3Yt8pEZboJSOafpxL02Ti12/w3IcQAECdwtM0AAAAAE3MvmH7XA+5LvtjmU9nnyCHoGPDj825NGdU/Ch278COA7e/vV3rNSy5V8gz4iWMTJhwdsL0C9PZLRatLP7r8V/pt96wbExtDvgemHp+qtcxLyLiG/FndJ+xYsCKgVEDkx8mB9oH6hgJK6BrQF/LvodvHz58+3Doa6GT35gsaCFY9vCZzwAAIABJREFUmLJwZNxINtrxTuNXu69W+BBKkEPQgWEH5iXPeyf2HTbCeT3mrXJfxTF4s5Zmc9zmfHDuA3GtmGfEC3stbK3XWoVRCVoI5rrNzavM25y7Oa4ojoje6/befz3/O/7MeN0zosXH1TZNJn79Bs99CAEA1Cmj2traho4BDJGRkRH7Dy4jMCEhwc/Pb8aMGevXr1ddMjU1taCgQHqLg4ODu7s7ESUmJt6/f196l6ura8+ePdl/79//r/fevffee3z+P/OGYrH48GHZF++ZmZkFBgay4T169Ehmb0BAQNu2bdU2DZCyxmDmzJmRkZGnTp3y9fXVb80NfvIyDHPw4EFlB23btq2vr69AIFBWAKQhR9L0ftYYGRnVTtP1K1mJsCSnIqePZR/zVuZ6iYp7haKXoosPLtq2tnVu76yiGFPLZD3OYmqZnhY9pd/kosdI2GB4RjzptVcLqgqKnxW7d3SXfmZEmYKqgvvC++4d3WVWb1UR/MiTIxMfJD794Cl728VbHd8y5ZuqjYot3KNDDwtjC7VRsXRMsbKPc8mLTPx6D57jEAKoa0abZS+QNbpsgaYL94xAs1JVVZWdnb1q1aqamprevXuPGTPGzs6O3SUUCtPS0n766SciGjx48Lvvviv51s4wTElJyc6dO69everl5TVmzBge719fC8rLy6urq+/evbt8+XKGYYYPHx4UFGRmZsbuffDgQVlZ2dq1a2/fvu3s7Dxx4sROnTqZmsp+JQKFkDI9Onfu3Pfff29paUlEDx8+/O677wYNGtTQQXFVRyNBLBZXV1cXFxcvX75cLBZ/9NFHb7316mUHBQUFCQkJo0aN+vrrr5csWVJ/TW2ykKPGz8bUhn2FTf1XKGgh8Onio7YYz4jX06JnnUZCfz/9Ic2xrSO7FCgXygpzCV7QQiC/vKuyqFQUVkbHFCv7OMemyfyp3+A5DiEAgDqCe0agYdTRPSOsESNGxMXFHTlyJCQkRGZX69athULh6dOnfXxk/+978ODB+Pj4rVu3Kqu2vLzc0tKSz+c/f/5c+gdP1qBBg5KSko4ePRocHMwlSJCGlOkuNjZ25MiR58+f9/b2JqLExMS33377xIkTAQEBaj/bGO4ZYdXRSBCJRCYmJgKB4NmzZzKX5XPnzl2zZs3ixYtx4c0RcsRqnPeMQEOR3DPS0IEAgK5wz4jBwgqs0AR07959x44dEydO5Fieve9aKBTK72rTpg0R1dTUyO86cOBAZGSkimpPnz5NRIMHD5a/xhaLxZcvX+bxePLXA8AFUqYjoVAYERERGBjITosQkbe3t7+//4cffqiw62RMnDhxx44d3bt313tgjeTkjYuLYxjGx8dH5pKbiPz8/Iho1apVHCME5IhVd2cNNEUDOg4Ybju8oaMAAADtYWYEmoCcnJyPPvpo3759HMu3bt2aiMrKymS2Jycnl5aWkqIv7rt37x43bpzqR9nj4+OJSHLlKbOLYRg3NzeDXahCR0iZjnbs2FFeXh4WFia9cfz48aWlpTJLPCi0b9++jz76KCcnR++BNZKT9/z580Tk5eUlv0skEpGS63xQCDli1d1ZA03Rkn5LjvgdaegoAABAe5gZgSaAYRiRSCQWizmWZxeMyMvLk9m+atUqdgFOmW/YNTU1x44de//991VXm5SUREQKF264dOkSKbkCBy6QMh2dOXOGiBwd//VgfOfOnYkoLi5O7cfFYrFIJGIYpS/O1FrjP3nZC3I3NzeOEQJyxKq7swYAAADqH2ZGoBlycHAgoufPn0tv/O233yZNmsTe7F1cXCy964cffvj2229V11leXp6bm8vn8xU+fHHx4kUiGjZsmG6BGy6kTEcZGRlEJFnzktW/f38iSk5ObpiYtFIXI0EkEqWlpQkEAvmr7pqaGvZ+luXLl+scu6FAjupZbmXu1PNTd+bt1OhT5TXldRSPar9c/+Wzy5+pLpNelj47afa7ce/6nvAdHT961bVVVaKq+gmvSUgsSZx6fmr+k3xlBc7dPzf53OQRJ0e8E/vOmFNjfr7+c/Vf1fLFtB4D62+sn500m2PhX67/orZwQ43GBsfldOBOl25UO6gAgDAzAs2Sra0tET179kyyRSgUxsXFBQUFsb92Sr948t69e6WlpTKXlPIkK1bIPwMvFouTkpKazYoVDQIp01FRURERGRsbS29k/ywpKWmYmLRSFyNBxQIW06dPLysr27hxY1BQkN7a0NwhR/WsuLp4281tiSWJHMvnVuZ2P9T9yqMrdRqVMvHF8bvydinbK2bEk89NHnB0wMbsjSJG1KZlm+yK7IUpC10OuqQ+TK3POBuzvCd5225uuy+8r3Dv7KTZQ2OG7rm15y/mL74RP+1h2rzL85wPOOdV/nMbl45jIOFewm95v3EsHF8cr6Jww47GBqf6dOBO925UPagAgIW39kIzxH47l37WfcWKFYsWLaK/f+2Uvtl78eLFy5YtU1tnQkICEWVkZLBPKEhjHxbo2bOn/IoVycnJDx8+HDhwoLW1tfT2xMTEyspK+e3ysrKyGts95HWheaSMYRj20RVvb2/JG4I1qkE7DMOwj6vIX1XS32s0NBV1MRLYZzEsLCzYIUFEDMPcvn07MjLS3Nz8ypUrvXv31lfuDOGEbagckcpTTPcc1d0ZWs9SH6ZmV2Q3dBSKRZyN2PfnvknOk9Z5rTNr+SqDUYVRYafDAuMCb467ad7KvGEjbOQSihPW3VgX0i1k19BdpvxXb5o/+OfBcafHjU0Ye+29a+wWHcfAF72+mPLGFD2E27hHYxOCbgSoH7hnBJohmd8t79y58+TJE1dXV/r7107JfeDJycmOjo42NjZq67xw4QIRHTly5L6cKVOmkNyKFWVlZT4+Pvn5+WZmZnPnzo2Ojma3V1dXe3p6Pn78uE+fPtOnT9+7d6/Cw+Xl5UVFRc2ePbtPnz5a9UET0wxSlpmZOXfuXJFIdPv2bWdn57Vr10p2caxBa9xX8Wj86mIksAtYPHny5OjfEhMTW7duHRsbe+7cud69e+ueO4M6YRskR6T8FNM9R3V9htYdppZhajVY6ETMKP1vhcJ61NYveqnBxOu5++f2/bnPv6v/b0N+k0yLEFGwQ/DifovLasrWZq2V+QhTy+g9Zo0q1KiBasurjo1LKvf/uZ+IfnL/STItQkTvv/b+uNfGZT7OlL5thPsh5GN2t3YPtA9U+HHVQWo0IDXtW440HTAqystTHbNGVakuzL0q1SU1+u8DAOCeEWiG2C/ukmfdly5dKnndo8yvnStXrjxw4IDaClWvWMF+p5dZsSIsLMzd3X3ChAlE9Prrr7u6upaUlJiZmX399df9+vULDg4monXr1jk6Og4dOlT+ykEoFAoEAj8/v3Xr1mnQ8iarGaTshx9+2L17N3vXho2NzZgxY/r06cMumsCxBq1JXvnBMIz8bSMKbyRptPQ+EtgFLHg83pEjR5S9G0X33BnUCdsgOSLladI9R3V9hupX6OlQIpr6xtTPLn+WVZHFM+IN7jR4q/dWp3ZORDT1/NQDBQeIaPSp0RatLArDC4ko63HWp5c/PXv/LFPLWBlbTXedvqjvIj6Pz9Ym4Ak8rD3mJM3h8/i/Dvk1qjBKRf2s3bd2r7q2Kqsii6ll2AJrPNf0tFDzzNTGnI1E9G1fBYvOzOo+y9LY0rvTP7PVFx9c/Cr1q6TSJEnM3/T5RtBCoHXMGnXCsM7DFqQs2Je/T8SI+Eb8wTaD13iuceug9HYwFR2iOl+s6MLoL1K/yK3M5RvxP3jjgx4deig7kAnfhIhuVNywb2MvvX3lWysnOE1g77iRHwPyDQx9LVRFzBFnIxJLEtnBw4q5E7MgZUFuZS7PiBdkHzTWceycpDn7h+33tfVlC5y5d+azy59lPs7kGfG8rL22v73dqZ2TwtFY9ryMS9/6nvAte14muQumSlTluM/R1dw1MejVY2V5lXmexzyXDVj2iesnmuY39LVQFeXlqY5Zo6pUF04vS1+YsvB8yXmmlrE2sZ7jNuerPl9pelKzuA8qAJBoSt+YAThiF55k7+hOTEx0dna2sLBgd7E3YLPvWdy5c2dYWJjqF0myVK9YcfnyZZkVK/Lz80+fPs2GQURdu3YloqioKIZhtm7dKrkg79Kli4uLi8LfJ3v37h0QEMDnG8rcZVNPWVVV1b59+2bOnMn+yV5i/fbbb0TEPem6YK9IZR6cYS9Q2V1Nhd5HAruAxYABA5QV1kvuDOqErf8ckfI06Z6j+jlD9eip6Gnqw9RR8aN8bX33+OyZ4TrjfMn5ESdHsHvDncLHOo4lomku05b0W0JE6WXpHsc88p/kRw6KPDr86MTXJy77Y9mYU2MktaWVpc1JmhPkENTHso9LOxfV9RPR+hvrJ56d2Ll15z0+e474Hfm85+dJD5IC4gLU/jr9e9Hvxi2MPa095XeZtTSb6jLVub0z+2d8cfzbx98uflYcOSjyiN+RIPugZX8s8z/pr3XMmnbC6PjRMXdi/uP+n2PDj63xWpP1OGtw9GCFq5yq7RC1sUUXRo+KH2XcwniPz55fh/x6ufTyovRFyvrwI5ePeEa8cafHfZHyRWJJoqTP7dvYB9oHWplYkaIxIN9ANTH/9bT8xT+LfUYVRr37+7sCnmCPz55dQ3cVPi2ccn5K+YtyEfPq/zg14pqRcSN9uvjsG7bvi15fXHhwYXjscIWREBHHvvW09pS+Cya2KLb8RXlSaZJksd4TRSfKX5S/Y/uOFvlVXV6eipg1qkp14dSHqV7HvAqqCjYN3nTE78iQzkO+Tvv6m7RvND2pScNBBQASBvE1DgwNeykoFosZhlm9evXRo0clu9h1JcrLy4VC4fHjxw8dOsSlQvbRd4Wvk4yPj2cYRmbFCvZ9ltLX5K1atYqPj+/bt69QKJQu6eDgkJaWpmkDm5+mnjIzM7Pp06ePGDFCemPLli2JKDc3tx6SPnDgwLNnz+bm5rLPHbCuXr1KRE3r+Q69jwR2AQsPDw9lBRo8d01O/eeIlKdJ9xw1xSzffnp7j8+ecKdwIgp3Cn/x8sWW3C3pZen9rfr7dPEpflb8681fR3Qdwf6ePytpFt+InxKcYm1qTUTBDsFWJlZfpn4ZVxTn39WfiHIrc7d4b5nqMpVL/US08upKV3PXkyNOsoVDuoXUvKxZk7UmvSz9rY5vqQi7UlQ5wGoAlwZOS5xmZWyVEpzCXuqHdAuxM7NbnLH4t5u/TX5jshYxa9QJQrEwqTRpYa+Fs91evXKlnaDduhvrsiuyFTZQbYeojm1+8nx7M/ukUUnsAzJB9kFuh9wqRZUKe6anRc/j7xz/8PyHP1778cdrP/KN+G93fvsd23ciXo9gm0ZE8mNAvseCfg/insQ5SXOc2jpdDr7MRhjiENLvaD/pZS/EteJfvX+d8PoEIgp9LfSJ6ElkdmRmeaZ8JNz7NtAucNkfy07fP83Ol8UVxTm1dcqvyk+4lxDSLYSIjt853rNDT8e2jprml4jco9xVl5emOma1h5amuvCnlz81bmEs2RvSLeT+s/srr65c0m+Jpie1RoMKACRwzwg0Q3w+n73E/eWXXz744APpy132FQlCofDHH39U+yJJCfbhC09PBb90sS9/lVmxwtnZmYgY5p8f0F68ePHs2TP2yfw333xTst3ExOTp06dcG9Z8NfWU8Xi8DRs2SN6dcebMGSKaOHEi/b0cQ10nnZ3+YOd3JB49ekRE3bt31++x6lQdjYShQ4cqK9DguWty6j9HpDxNuueoKWaZZ8QLfS1U8id7F8bD5w/lS5Y9L0t5mDLKYZTkspmIZnWfRX+vWMHWNtl5Mvf6C8MLL4+6LF3eytiKiLi8edfC2EJtmdSHqXeq70xynsROi7A+7/U5z4h3/O5xLWLWtBMEPIGAJ9h1a9fe/L014hoiCncKvzTqkrJ5H7UdoiK23Mrc/Kr8Ca9PkKwb0lbQ9kOXD1X0T4BdQPH44qPDj05ynuTQxuH0vdMLUxba7bXbfnO7ik/J9Bj3JKY+TC16VjTFZYokQmO+8QzXGTKVs/M+LK9OXkRU/Oxfb+9mce/btzq+ZW1inXDv1ZLM8cXx414bZ8o3PVV8iohEL0XnS86/a/8uaZ5fLuU5xqxRVaoL14hrLpdeltm7/e3tN8fdlHkwR+1BtRhUAMDCPSPQPBkbGwuFwvj4+JMnT0pvZ2/2FovFZWVlal8kySovL8/Ozubz+b6+vvJ72ctsmRUrnJycPDw8JJepeXl5PB6PfR8KEbVp00a6sPTVeP2Lj48/fPjw0qVLpR+ql9+osJh+NZuUMQyzYMGCefPmsfMy9ZP0MWPG/PTTT2fPnn3//fclG0+dOkVE48eP1++x6poeR4JkAQuOr2dukNxxx/FsVbZRjxowR/TvNEVFRZFuOWpsWebClG/KM/pnQkr63zLSytKIaF/+vpg7MTK7ymvKJbXJXHqprp9nxCt8Wnj49uG8J3nF1cVpZWmSpyrUhn3pwSW1xQqfFhJRP8t+Mp9t27Kt5D4FjWLWtBP4PP4W7y0fnP9g/Jnx7KoZ79q/K31Thgy1HaIiNvZpEVdzV+nyru3/9ac8Po8f7BAc7BBMRCXCkt23dq+4smLK+Sku7V0UPqxEcj3GPYlsOpzbOUtvtDf71yon3AekRn0bZB+069YuppbJe5JXIizx6eyTU5mT+CCRiGLuxjC1TJB9EGmeXy7lOcasUVWqC198cJHkhr30YjQc6yFtBxUAEGZGoLmys7PLzc2VrAsowePx+Hy+QCBYsmQJx6rYe8U9PDzkH1CvqKhgf+2U/05/4MCB8ePH9+3bt3Pnzr///rudnV3r1q3ZGh48eODk9Or/di9fvmzYBTLHjh1bVVVFRJs3b1axUWEx/Wo2Kfvss898fHxWr17N/lk/Sff09PTy8tq7d++KFSvMzc2JqLq6eu/evf7+/gofKWrM9DgSDh48yDCMm5ub/It4FWqQ3HHH8WxVtlGPGjBH9O806Z6jxpblujDWcayHtezDSt3adNOutu8yvlucsdiUbzrcdniPDj1muc0qqCr4Ou1rtR/0tvGOK4orFZYqvAyOOBsxpPOQD9949cu2wgUsdXnRhkadEOEc4Wfrd7jgcHxxfFxR3IUHF5ZkLDkbeFbhbSNadwgRMcSQ3FSCssU7xYx4b/7ejiYdpR/TsDG1WdBrwQCrAUNjhm7O2axsZkSPMeuIe98GOwRvyd2SWJJ4/fF1vhF/SOchN5/c/N/t/5U9L4u5G2NjaiP9EU0HuV7GgxZVKSvMjgRjvrGygLnHr9GgAgBpOE+geXJ0dPTy8nJzU7CSvKmp6ZdffmllZSW/S5pYLHZycnry5EllZSURXbhwwdzc3NbW9vr160Q0bdq0qKioiooK9qdFGxubNm3axMTESC/hee7cucTExEePHs2fP/+7774bN26cg4MDERUWFkq+gtfU1Mj8VlnPwsPDd+7cGRISonqjwmL61TxS9vPPPzs6Os6dO1eypd6SfujQoSFDhoSGhq5fv55hmM8++8zR0XHnzp16P1Bd030ksJVUVFSwswNZWVnm5uaWlpa3bt1S8ZEGzB1HHM9WZRv1qKFyRHJp0j1HjS3L+sWuwtBO0G5m95nS22vENdyvwaTlP8lfnLHYw9rjXOA59k0xRLQkYwmXzwY7BMcVxW27ue2rPl/J7Lr44OKuW7sqXlR8+MaHHU06ElFuZa50ATEjrvqrakjnIVrErEUniF6KWvNbz3abPdtttpgRb8rZNCtp1sprK4/4HZEpqUuHEJFta1v6+0d+iRJhicLCPCPeB+c/GNhxoPwCFu4d3Ynze3A1ipntvazHWezqHqw71Xe4HEgh7n3r39VfwBMk3EvIqcwZbjucZ8Qb2nkoEZ2+fzrmTsy418ZJR8g9v3ocD8sHLOdelerjlgpLiSjlYcrHb34s2ZX6MDWuKG6KyxSN4tdoUAGAtGb1qwiAxLhx41auXKlw1/fff79w4UK1NfD5/MLCwoqKitq/VVRUsNfYRLR58+aHDx/+9ddf7K5nz549ePBAco1NRFlZWQUFBUOGDBkyZAj77f/99993dXU1NTVlV39gXb9+XeHVRb3ZsGHDs2fP/P39VW9UWEy/mkHK9u/fb2FhIblmmz9/PhHVW9JtbGxycnJmzpy5e/fu/fv3f/LJJ1euXOFygdrY6D4SiKigoKCiouLly5eSkaD6krthc8cRx7NV2UY9apAckaI06Z6jxpZlfWF/N3Zp72JvZn/k9pGKFxWSXTF3Yky2myxIXqBFteyERZB9kOSKmoiO3j5KRGqfqfnA+YOurbsuv7I8sSRRenvZ87Ip56cQ0dd9viYibxtvK2OrHXk7pK/zt+RuYWoZjjdEyNC0E6ILo1tta7Ujbwf7J5/H/8T1E74RX+EdK7p0CBH1t+rftXXXPfl7pBsrObQMnhEv0C7wcunlDdkbZHb9cO0HIhpsM1h6IzsGdIy5v1V/53bO229ul/SeUCyMzI5U2zSFkWjUtzwj3uhuo08WnYwrimMnxVzau1ibWC/NWFpWUzbKfhRbTNP86nE8aFSV6sLWptYu7V3ii+PZpUxY626sW/rHUsndHxxPao0GFQBIw8wINE8RERGSF0nKmD17dj3cKR0WFrZgwav/L65du3bKlCnOzs48Hi8sLCw2NpbdfufOnaKiovDwV+uWRUVF9ejR484d7X+KadKaesrOnDkTFRUlEAj279+/f//+VatWDRgwgIhU16BfPB4vKChoyZIlixYtCgwMrItD1IP6Hwla5A5na/2frQrTpPt/VOvzDK0f7OXulpwtO/N2EtEazzWlz0u9o72jC6PTy9K35m6deHailbHV5z0/16Lyflb9BDzBuhvrLpVeEr0UXSq95HvCN+9JHnF41EXQQrB32F6eEW9ozNDQ06H7/9z/v9v/W5KxpMfhHnlP8hb3W+xu7U5EPCPejwN/zHuS53vCN/ZubGZ55urM1Z9e+tSlvcvs7rO1iJk07IRA+8Bubbp9lfbVppxNqQ9TE4oTws+Ei2vFkpsU9NUhrB/df8x7kud/0v/MvTOXSi+NOTXmWvk1ZYXXea2zMraacXGG5zHP1Zmr9/+5f23W2iHHhyzNWOph7SG53UBmDOgY83qv9Xeq73ge89yQvWFTziaPKI/iagWrqyokE4lGfUtEgXaBfzz6QygWsneLENFw2+G5lbmmfFOfLv88EqvpINfjeNCoKtWFV7618t6ze/4n/eOL49PL0helL9p1a9c0l2k2pjaantQaDSoAkMDTNAB1IiwsjMfjJSYmpqWlpaSkHDny6jbR5cuXDxw4MCYmxsPDY9asWZGRkY6OjuyuR48e3b179/z58xEREZcuXYqMjLxy5QoReXt7Ozo6rlu3jvtz+KAFXVIWEhIyatSo6urqAwcOSCo8ffq02hqgwVVXV2uRO+mzlYhwwtY1FWnS/T+qzewMDega0Ney7+Hbhw/fPhz6WmiQQ9Cx4cfmXJozKv7Vb+wDOw7c/vZ2ZeuJqmZjanPA98DU81O9jnkREd+IP6P7jBUDVgyMGpj8MDnQXs2E7KBOgzJGZ8xPnn+o4NCBP1+l0qW9y389/yv99pbJb0wWtBAsTFk4Mm4kEfGMeOOdxq92X63dE0BEpFEn8Ix4CSMTJpydMP3CdHaLRSuL/3r8K0IJHTuEiEJfCxUz4nmX5w07MYyIelv0/mHgD/Muz1NYuKtZ12vvXfs67etdebsul756uYxZS7NPe3y6rP8yyc0FMmNAx5h9bX1Pjzy9JGPJnKQ5xnzjD9/40NXcVdI5qslEImgh4N63RDTSbiTPiGfGN2PfcExEAXYBu27tGmU/SnodDU0HuR7Hg0ZVqS4c5BB0YNiBecnz3ol9h4j4Rvx5Peatcl8l341qD6rRoAIACaPa2tqGjgEMkZGREfsPLiMwISHBz89vxowZ69evr+O49CkzMzM3N9fOzs7d3V16O8MwcXFx1dXVffv2lTzZLtm1d+/eCRMm1G+k8ErdpUxFDY3BzJkzIyMjT506pfBtPrpooievNGW5w9naeDTIGar3s8bIyKh2mt6+koleinhGPOllF0uEJTkVOX0s+5i3MtexcqaWyXqcxdQyPS16qngRieoa/nj0R+WLyu4dutuYKn2DUkFVQfGzYveO7tLPfehCo04QvRRdfHDRtrWtc3tn1SX10iGZ5ZltBW3ZVSS4lC+oKih8WmhrZuvczlnhQeXHgHYxV7yokOmutVlr51yacyXkSm/L3lyilY+Ee99qRNNBrsfxoFFVqgsXVBXcF9537+gukztNT2pNBxVIGG2WvUDW6LIFmi7cMwJQV3r27KnwvZU8Hi8gIEDhRxISEqRXvoB6VncpU1EDNHLKcoeztfHAGSpPfirBxtRGxRyERnhGvJ4WnN7KrKIGyV0AKji2ddTvRZ1GnSBoIZB+ZEMFvXQIx1kGSXmndk4K3+oqoXo6iXvMHXd2DLALOPbOMcmW7Te3m7U0495k+Ui4961GNB3kehwPGlWlurCyYa/pSa3poAIArDMC0FhUV1enpqa6uLg0dCDAFVJmsJD6JgFpAtDdJOdJ0XeiQ0+H/nbzt/U31r919K2r5Vd/eOsH7e6OAQBotHDPCEBj8fz5888/12ZJPGgoSJnBQuqbBKQJQHdb397q0MZh35/7jt4+yjPiDew48NjwY0EOQQ0dFwCAnmFmBKCxaIovWDVwSJnBQuqbBKQJQC++6fvNN32/aegoAADqFm6EAwAAAAAAAADDhZkRAAAAgMYuvSx9dtLsd+Pe9T3hOzp+9Kprq6pEVfo9RHlNudafXX9j/eyk2XoMRoXEksSp56fmP8mvn8PJSChOGPX7KN8TvhFnI+qifu6t++X6L/XW5/LqIeOTz02OK4rTV226DG/90m/XyQyYDdkbVlxZoa/KAQwKZkYAAAAAGi8xI558bvJZ3ct/AAAdmUlEQVSAowM2Zm8UMaI2LdtkV2QvTFnoctAl9WGqXg6RW5nb/VD3K4+uaF1Dwr2E3/J+00swauU9ydt2c9t94f36OZy0e8/ujYwbmXAvoTW/tXM7fb5xVoJ76+KL4+utz+XVdcZXXVuV9CBpuO1w3avSfXjrl367TmbABNkHLc1YmliSqK/6AQwH1hkBAAAAaLwizkbs+3PfJOdJ67zWmbU0YzdGFUaFnQ4LjAu8Oe6meStzHQ+R+jA1uyJblxq+6PXFlDem6BhG45dRliFiROsHrZ/qMrWhY2lgdZrxUmHpkowl297eppc34Og+vPWrTruuS+suc9zmfHLxkxtjb9TRIQCaK8yMgKHYv39/YWFhQUHB66+/vmDBAoVlxGLx4cOHZTaamZkFBgYSUUJCwqNHj2T2BgQEtG3bti4CBqQMWFxGAsMwBw8eVFZD27ZtfX19BQJBncVo6LjkiJAmrZy7f27fn/v8u/r/NuQ36e3BDsGL+y3+MvXLtVlrF/VbJL1LzIj5PFVf8Jhahog4XnOqro2pZdh63K3dtTiWRpFIjqVsL1PL6NJwtf1GRAwxRGRpbKnR0VVHzrGM6vC4BK/i0KQyCwoLaJFx7un+8dqP5q3MQ18L1bQSLsNAGWUpUNG3XDIrT2HXKaxKu0PP6j7rP5n/2X1r94TXJ2gaG4Ahw9M0YCiqq6uTkpK2bNly69YtZWXKy8urq6uzs7PHjx8fFhb266+/lpf/81TqgwcPSkpKvvrqq7CwsMWLF+fn51dXV5uamtZL+IYIKdPO1atX33zzTaFQ2NCB6A2XkSAWi6urq3NzcydOnBgWFnbmzJnqv2VmZi5ZsqR169ZLliypx6gNC5ccEdKklY05G4no277fyu+a1X3WFu8tkqvHrMdZvid8W2xp0XJry447Oy5KXyRmxJLCoadDQ0+HJhQn9DjUgy0z5PgQdm2CqeenzkyaSUSjT4122OvAsbaIsxEbsje02trKZJvJ/j/3R5yNkHxWxbEkYu7EvHnwTXbv6PjRe/P3Wu6wTChOUNgJ0YXRrwpvaTktcdpz8XPpvRcfXPSO9m65taUkVNFLEZeGc2mptNHxoyeenUhEE89OtNxhyT6woOLo8r2kRevUhhddGO24z7Hl1pYm20xmJ82u/qtauu1vHHhDuvDOvJ2SyLlkQUUBjTKuUbpFL0UbczaO6TZGuiFqR5SyRCgc3tKUpUl1z8fciel+qDubtYizEVGFUZKOVdvtMl0nf3TVh1Y9YIjIvo394E6DI7MjFXYvACiDe0bAUEydOtXU1DQmJsbf319ZGWtr66lTp5aXly9btozP5584cYLP/+ccmTBhAhEdOXLk9u3bK1euDA4Oro+4DRhSppHt27cnJydnZ2dfv369qqqKYZiGjkhvuIwEgUAwdepUkUi0bNkyY2PjjRs38nj/TP2vWLFi7ty5S5cuJSJceNcFLjkipEkrvxf9btzC2NPaU36XWUszyTMd6WXpQ2OGWrSyiBwUaW1ifaHkwrI/ll0rv3bsnWNsgaeipzmVOcfvHJ/25rQv+3x5ufTyuhvrRpwccSv0VrhTOEPMrzd/neYyrUeHHhxrK3hasC9/X5BDUImwxKWdy4G/DpS/KFd7LLZAVGHU6PjRPTv03OOzh4hWXVs15fyUmpc1IkZEcqILo0fFj+pt0XuPzx6mlll5deWhgkOSvfHF8SNOjrA3s48cFGllbBV7N3bZH8suPrh4JvAMl2DUtlTax29+3Nm0c2R2ZMTrEX0s+7zW9jXVR5fvJU1bpza8GnHNmFNjvuzzZV/LvkkPkv6T+Z/rj6+fe/ecpO0yy46KGFH5i3J2ykBtFlQXePrXU44Z1yjdRBRzN0YoFvp18ZNsUTuiVCRCfnjLUJgm1T3PZs3L2uvY8GMMMcv+WBZfHC/pWNXdLt91MkfncmhlA0ZiuO3wb9O/Laou6mrWVWEnA4A8zIyAAYmPjyeit99+W3Wx06dPE9HgwYOlr7FZYrH48uXLPB7Px8enjoIEaUgZd+3btw8ODv7pp5/GjRsXGxvb0OHoGceREBcXxzCMj4+P9PU2y8/Pb82aNatWrcIldx3hmCNCmjRUKaocYDVAbbFZSbP4RvyU4BRrU2siCnYItjKx+jL1y7iiOP+ur6arbj+9vcdnT7hTOBGFO4W/ePliS+6W9LJ0ny4+xc+Kf73564iuI3xtfTnWlluZu8V7i7LlNpQdq79VfyKakzTHqa3T5eDLpnxTIgpxCOl3tJ+ylSDmJ8+3N7NPGpXEFg6yD3I75FYpqmT3TkucZmVslRKcYmViRUQh3ULszOwWZyz+7eZvk9+YrDYYLi2V8O/qX/OyJjI70s/WL9ghmIi8jnmpPrrqXlLbOrXhiWvFGwdv/PjNj9m97QTtvk3/NvZubIBdgLIjSqjNgkZpUtHJGtVDRKeKTxGRbxdfjvWTumEgM7zlyadJdc/PT57ftXXXhJEJxnxjNlS3Q25qO1wZmaO7R7mrPrSKASPRs0NPIkoqTQo1U/BEEgAohKdpwIAkJia6urpaWFioLsZ+v/f29la4i2EYNzc3LFRRP5Ay7kJCQgICAszMzBo6kDrBcSScP3+eiLy8vOR3iUQiImpODxk1NhxzREiT5iyM1fRq2fOylIcpoxxGsZdSrFndZxGR9BMcPCOe9MIN7H0oD58/1Lq2yc6TlYWk4lipD1OLnhVNcZnCXtoRkTHfeIbrDIX15Fbm5lflT3h9gqR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Net: Convolutional NN Matrices Determination for LED Digit images; Variant Images Scored","description":"This challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. Sets of variants will be tested to show success beyond the training set. (Scale, Offset, Noise, zeroed node(s), intra-shifts). \r\nResults of scaling/Offset/Noise indicate additional Training sets required with Offset and Scale. See Test Suite 1 Figure. \r\nWould training images with Noise improve performance?\r\nTest sets 2 thru 5 show various Pixelations of numbers and the Neural Net success rate. Just fun to look at the data.\r\nAppears more training sets required and possibly more nodes to have high success. One translate not good.\r\n[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\r\n \r\nThe matlab Latex code for making the CNN Processing chart included in template.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 781.5px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 390.75px; transform-origin: 407px 390.75px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. Sets of variants will be tested to show success beyond the training set. (Scale, Offset, Noise, zeroed node(s), intra-shifts). \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 376.5px 8px; transform-origin: 376.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eResults of scaling/Offset/Noise indicate additional Training sets required with Offset and Scale. See Test Suite 1 Figure. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 176.5px 8px; transform-origin: 176.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWould training images with Noise improve performance?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 363px 8px; transform-origin: 363px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTest sets 2 thru 5 show various Pixelations of numbers and the Neural Net success rate. Just fun to look at the data.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 342px 8px; transform-origin: 342px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAppears more training sets required and possibly more nodes to have high success. One translate not good.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 162.5px 8px; transform-origin: 162.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv 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data-image-state=\"image-loaded\" width=\"875\" height=\"524\"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 257px 8px; transform-origin: 257px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe matlab Latex code for making the CNN Processing chart included in template.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [WP,WH]=ConvNN_Process(XImg,K,WH,WP,EPY)\r\n %nX=size(XImg,3); %Number training images\r\n %nK=size(K,3); % Number kernels\r\n %XC=zeros(5,3,nK); %Pre-alloc for speed\r\n \r\n for epoch=1:1000 % Number of cycles to evolve WH and WP\r\n  dWH=0*WH;\r\n  dWP=0*WP;\r\n  for iCase=1:nX  %Cycle thru all Images while accumulating dWH and dWP\r\n %Forward Pass  X(7,5,nX)-Ximg,Conv-XC(5,3,nK),ReLU-XCY3(5,3,nK),XCY(1,nK*15+1)(1,91)\r\n % XCYV*WH-H(1,21), ReLU(H)-HY(1,21), HY*WP-P(1,10), Softmax(P)-PY\r\n   for k=1:nK\r\n    %XC(:,:,k)=(conv2(XImg(:,:,iCase),K(:,:,k),'valid')); %Use rot90 Kernel to make output align\r\n   end\r\n\r\n   %XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive; safer to leave in for K offset case\r\n   %XCY=[XCY3(:)' 1]; % 1,nK*15+1  (1,91)  add a 1 for offset term\r\n \r\n   %[dWPi,dWHi]=Neural_ReLU_Back_Propagation(XCY,WH,WP,EPY(iCase,:));\r\n \r\n %Accumulate across all sample cases\r\n   %dWP=dWP+dWPi;\r\n   %dWH=dWH+dWHi;\r\n \r\n  end % iCase\r\n\r\n  %WP=WP+dWP/nX; % dWP/nX  Valid\r\n  %WH=WH+dWH/nX; % Usage /nX^2 requires 10K epochs for \u003e.8 PYs\r\n\r\n end % epoch\r\nend %ConvNN_Process\r\n\r\nfunction [dWP,dWH]=Neural_ReLU_Back_Propagation(X,WH,WP,EPY)\r\n% X will be single case [X1 X2 ... XN 1]\r\n  LR=1; % Learning Rate\r\n  \r\n  H=X*WH;\r\n  HY=max(0,H); % ReLU\r\n  \r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 PY2 ... PYM]\r\n  \r\n  %Back Propagation Calculations\r\n  ErrPY=EPY-PY;\r\n  \r\n  dPY=PY.*(1-PY).*ErrPY;\r\n  dWP=LR*HY'.*dPY;\r\n  \r\n  dHY=HY.*(1-HY).*sum(WP.*dPY,2)';\r\n  dWH=LR*X'.*dHY;\r\nend % Neural_ReLU_Back_Propagation","test_suite":"%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 1:9 0\r\n ['010111111101111100111111111111';\r\n  '010001001101100100001101101101';\r\n  '010111111111111111001111111101';\r\n  '010100001001001101001101001101';\r\n  '010111111001111111001111001111'];\r\nImgsetv=Imgsetstr-'0';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\nnClasses=10;\r\nEPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nKsetstr= ... %3x3 kernel mask (will be scaled/offset)\r\n ['000000010010010000'; %Centered corners and vert/horiz\r\n  '011110011110010111'; %Kernels are identifying Features\r\n  '010010000000010000'];\r\n\r\nKsetv=Ksetstr-'0';\r\nKh=size(Ksetv,1);\r\nnK=size(Ksetv,2)/Kh; %Number of Kernels\r\nKset=reshape(Ksetv,Kh,Kh,nK);\r\n%Kernel needs normalization either scale or offset; Two large scale slows convergence or possible fail\r\nKsetr90=rot90(Kset(:,:,:),2)/3; % Rotate and normalize 3, each kernel sum is 3 Valid  2-Fails\r\nK=Ksetr90;\r\n%Ksetr90=rot90(Kset(:,:,:),2)-.5; % Rotate and offset -0.5  Valid \r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\n%Stability sensitive to WP and WH values; rand start needs offset and normalization\r\n% X(7,5,nX) XC(5,3,nK) (XCY(1,91) WH(91,21) WP(21,10)\r\nztic=tic;\r\nfor ztry=1:5 %Allow five processing attempts to get a working solution\r\nWH=[(rand(90,20)-.5)/sqrt(90+20) zeros(90,1)]; % 90=nK*15, 20 is arbitrary at 2*nCases WH(91,21)  Valid\r\nWH=[WH; zeros(1,20) 1]; % offset row, Start with zero bias\r\n\r\nWP=(rand(21,10)-.5)/sqrt(21+10);  % 10 output states  Valid\r\n\r\n[WP,WH]=ConvNN_Process(XImgset,Ksetr90,WH,WP,EPY);\r\nfprintf('Process Time: %.3f sec\\n\\n',toc(ztic));\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),Ksetr90(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  [~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Ideal Input Training Cases\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  %fprintf('\\n\\n');\r\n  \r\n  %Scaled-50%\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  XN=XImgset/2; %Scale to 7x5 Image planes\r\n  XNS=XN; %figure variable\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XN(:,:,iCase),K(:,:,k),'valid'));\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,Xpcase]=max(PY,[],2);\r\n  [~,Xpexp]=max(EPY,[],2);\r\n  \r\n  fprintf('50%s Scale - NN Strong Scale Invariance, Worst is 8\\n',char(37));\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',Xpexp(i),Xpcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(Xpcase==Xpexp)/nX,'%');\r\n  \r\n  %Scaled-50% and Noise 60% added\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  XN=XImgset/2+.3*(rand(size(XImgset))-.5); %Scale and add Noise to 7x5 Image planes\r\n  XNSn=XN; %figure variable\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XN(:,:,iCase),K(:,:,k),'valid'));\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,Xpcase]=max(PY,[],2);\r\n  [~,Xpexp]=max(EPY,[],2);\r\n  \r\n  fprintf('50%s Scale and 60%s Noise added - Imperfect Results Expected\\n',char(37),'%');\r\n  %Note: double % is a special Cody sequence so using %s to write % character\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',Xpexp(i),Xpcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(Xpcase==Xpexp)/nX,'%');\r\n  \r\n\r\n  %Offset+50%\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  XN=XImgset-.5; %Offset to 7x5 Image planes\r\n  XNo=XN;\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XN(:,:,iCase),K(:,:,k),'valid'));\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,Xpcase]=max(PY,[],2);\r\n  [~,Xpexp]=max(EPY,[],2);\r\n  \r\n  fprintf('50%s Offset - NN Somewhat Strong Offset Invariance - Weak 1,3,8,9\\n',char(37));\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',Xpexp(i),Xpcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(Xpcase==Xpexp)/nX,'%');\r\n  \r\n  %Offset-50% Noise-60%\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  XN=XImgset-.5+.6*(rand(size(XImgset))-.5); %Offset to 7x5 Image planes\r\n  XNon=XN;\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XN(:,:,iCase),K(:,:,k),'valid'));\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,Xpcase]=max(PY,[],2);\r\n  [~,Xpexp]=max(EPY,[],2);\r\n  \r\n  fprintf('50%s Offset 60%s Noise - NN Mildly Strong Offset/Noise Invariance - Weak 1,3,8,9\\n',char(37),'%');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',Xpexp(i),Xpcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(Xpcase==Xpexp)/nX,'%');\r\n  \r\n\r\n  figure(1); imagesc([reshape(XImgset,7,[]);reshape(XNS,7,[]);reshape(XNSn,7,50);reshape(XNo,7,[]);reshape(XNon,7,50)]);\r\n  xticks([]);yticks([]);axis equal;axis tight\r\n  \r\n  if isequal(pcase,pexp),break;end\r\n  \r\nend % ztry  Allowed 5 trials as rand may not always converge\r\n  \r\nvalid=isequal(pcase,pexp);\r\nassert(valid)\r\n\r\n%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 1 variants,3 variants\r\n ['100001010010000011110011111011';\r\n  '100001010110010011110001001001';\r\n  '100001010010010011010111011011';\r\n  '100001010010010011010001001001';\r\n  '100001111010010011010111111011'];\r\nImgsetv=Imgsetstr-'0';\r\npexp=[1 1 1 1 1 1 1 3 3 3]';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\n%nClasses=10;\r\n%EPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nnK=size(K,3); %Number of Kernels\r\n\r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\nfigure; imagesc(reshape(XImgset,7,[]));\r\nxticks([]);yticks([]);axis equal;axis tight\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),K(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  %[~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Morphed 1s and 3s; Need more training\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  fprintf('\\n\\n');\r\n\r\n\r\nassert(1)\r\n\r\n%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 2 variants,4 variants\r\n ['011011100111110001000101101001';\r\n  '001001010001001101101111101011';\r\n  '111111001010010111111001101111';\r\n  '100100010100100001001001111001';\r\n  '111110001111011001001001001001'];\r\nImgsetv=Imgsetstr-'0';\r\npexp=[2 2 2 2 2 4 4 4 4 4]';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\n%nClasses=10;\r\n%EPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nnK=size(K,3); %Number of Kernels\r\n\r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\nfigure; imagesc(reshape(XImgset,7,[]));\r\nxticks([]);yticks([]);axis equal;axis tight\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),K(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  %[~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Morphed 1s and 3s; Need more training\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  fprintf('\\n\\n');\r\n\r\n\r\nassert(1)\r\n\r\n%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 5,6,7,8 variants\r\n ['110110010111110100011111010010';\r\n  '100100100100100100001001101100';\r\n  '111111111111111110001001010010';\r\n  '001001001101101101001010101001';\r\n  '111011010111111110001100010010'];\r\nImgsetv=Imgsetstr-'0';\r\npexp=[5 5 5 6 6 6 7 7  8 5 ]';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\n%nClasses=10;\r\n%EPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nnK=size(K,3); %Number of Kernels\r\n\r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\nfigure; imagesc(reshape(XImgset,7,[]));\r\nxticks([]);yticks([]);axis equal;axis tight\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),K(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  %[~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Morphed 1s and 3s; Need more training\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  fprintf('\\n\\n');\r\n\r\n\r\nassert(1)\r\n\r\n%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 7,9,0 variants\r\n ['110111111011111010010111101101';\r\n  '010101101101111101000001101100';\r\n  '010111111111111101010011111111';\r\n  '010001001001111101000001101001';\r\n  '010011111001111010010001111001'];\r\nImgsetv=Imgsetstr-'0';\r\npexp=[1 9 9 9 10 10 1 7  8 4 ]'; %Shape/Missing LEDs\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\n%nClasses=10;\r\n%EPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nnK=size(K,3); %Number of Kernels\r\n\r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\nfigure; imagesc(reshape(XImgset,7,[]));\r\nxticks([]);yticks([]);axis equal;axis tight\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),K(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  %[~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Morphed 1s and 3s; Need more training\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  fprintf('\\n\\n');\r\n\r\n\r\nassert(1)\r\n\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":3097,"edited_at":"2023-08-31T19:50:57.000Z","deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-08-31T13:45:50.000Z","updated_at":"2023-08-31T19:50:57.000Z","published_at":"2023-08-31T19:50:57.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. Sets of variants will be tested to show success beyond the training set. (Scale, Offset, Noise, zeroed node(s), intra-shifts). \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eResults of scaling/Offset/Noise indicate additional Training sets required with Offset and Scale. See Test Suite 1 Figure. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould training images with Noise improve performance?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTest sets 2 thru 5 show various Pixelations of numbers and the Neural Net success rate. Just fun to look at the data.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAppears more training sets required and possibly more nodes to have high success. One translate not good.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"524\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"875\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe matlab Latex code for making the CNN Processing chart included in 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to multiply?","description":"Imagine you are in 3012 Anno Domini, when everyone must learn how to multiply,\r\nand competing for the highly prestigious post of,\r\nChief Comptroller of Ylpitlum Corporation.\r\nYou are being tested via MATLAB Cody for multiplication of two positive integers X and Y,\r\nboth are fortunately in decimal system, and only a few dozen digits or less,\r\nand delivered as ASCII strings.\r\nPlease output the result Z in similar style.\r\nPlease adopt a general strategy, as X and Y may be changed later.\r\nPlease rename the function Z = ylpitlum(X,Y).\r\nFunction Template:\r\nfunction Z = ylpitlum(X,Y)\r\n   %  098765432109876543210987654321098765432109876543210987654321\r\n   X='170000000000000000000000000000';\r\n   Y='190000000000000000000000000000';\r\n   Z='32300000000000000000000000000000000000000000000000000000000';\r\nend","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 346.933px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 173.467px; transform-origin: 407px 173.467px; vertical-align: baseline; \"\u003e\u003cul style=\"block-size: 204.333px; counter-reset: list-item 0; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 102.167px; transform-origin: 391px 102.167px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 254.5px 8px; transform-origin: 254.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eImagine you are in 3012 Anno Domini, when everyone must learn how to multiply,\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 151.5px 8px; transform-origin: 151.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eand competing for the highly prestigious post of,\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 131px 8px; transform-origin: 131px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eChief Comptroller of Ylpitlum Corporation.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 76.5px 8px; transform-origin: 76.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou are being tested via\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eMATLAB Cody\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 154.5px 8px; transform-origin: 154.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e for multiplication of two positive integers X and Y,\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 233.5px 8px; transform-origin: 233.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eboth are fortunately in decimal system, and only a few dozen digits or less,\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 96.5px 8px; transform-origin: 96.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eand delivered as ASCII strings.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 129px 8px; transform-origin: 129px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePlease output the result Z in similar style.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 210.5px 8px; transform-origin: 210.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePlease adopt a general strategy, as X and Y may be changed later.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 141.5px 8px; transform-origin: 141.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePlease rename the function Z = ylpitlum(X,Y).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 60px 8px; transform-origin: 60px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFunction Template:\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 122.6px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 61.3px; transform-origin: 404px 61.3px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"border-block-end-color: rgb(14, 0, 255); border-block-start-color: rgb(14, 0, 255); border-bottom-color: rgb(14, 0, 255); border-inline-end-color: rgb(14, 0, 255); border-inline-start-color: rgb(14, 0, 255); border-left-color: rgb(14, 0, 255); border-right-color: rgb(14, 0, 255); border-top-color: rgb(14, 0, 255); caret-color: rgb(14, 0, 255); color: rgb(14, 0, 255); column-rule-color: rgb(14, 0, 255); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(14, 0, 255); perspective-origin: 36px 8.5px; text-decoration: none; text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); transform-origin: 36px 8.5px; \"\u003efunction \u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 68px 8.5px; transform-origin: 68px 8.5px; \"\u003eZ = ylpitlum(X,Y)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 264px 8.5px; tab-size: 4; transform-origin: 264px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003e   \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(2, 128, 9); border-block-start-color: rgb(2, 128, 9); border-bottom-color: rgb(2, 128, 9); border-inline-end-color: rgb(2, 128, 9); border-inline-start-color: rgb(2, 128, 9); border-left-color: rgb(2, 128, 9); border-right-color: rgb(2, 128, 9); border-top-color: rgb(2, 128, 9); caret-color: rgb(2, 128, 9); color: rgb(2, 128, 9); column-rule-color: rgb(2, 128, 9); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(2, 128, 9); perspective-origin: 252px 8.5px; text-decoration: none; text-decoration-color: rgb(2, 128, 9); text-emphasis-color: rgb(2, 128, 9); transform-origin: 252px 8.5px; \"\u003e%  098765432109876543210987654321098765432109876543210987654321\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 152px 8.5px; tab-size: 4; transform-origin: 152px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 20px 8.5px; transform-origin: 20px 8.5px; \"\u003e   X=\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 128px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 128px 8.5px; \"\u003e'170000000000000000000000000000'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 152px 8.5px; tab-size: 4; transform-origin: 152px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 20px 8.5px; transform-origin: 20px 8.5px; \"\u003e   Y=\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 128px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 128px 8.5px; \"\u003e'190000000000000000000000000000'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 268px 8.5px; tab-size: 4; transform-origin: 268px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 20px 8.5px; transform-origin: 20px 8.5px; \"\u003e   Z=\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 244px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 244px 8.5px; \"\u003e'32300000000000000000000000000000000000000000000000000000000'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 12px 8.5px; tab-size: 4; transform-origin: 12px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"border-block-end-color: rgb(14, 0, 255); border-block-start-color: rgb(14, 0, 255); border-bottom-color: rgb(14, 0, 255); border-inline-end-color: rgb(14, 0, 255); border-inline-start-color: rgb(14, 0, 255); border-left-color: rgb(14, 0, 255); border-right-color: rgb(14, 0, 255); border-top-color: rgb(14, 0, 255); caret-color: rgb(14, 0, 255); color: rgb(14, 0, 255); column-rule-color: rgb(14, 0, 255); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(14, 0, 255); text-decoration: none; text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); \"\u003eend\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Z = ylpitlum(X,Y)\r\n   %  098765432109876543210987654321098765432109876543210987654321\r\n   X='170000000000000000000000000000';\r\n   Y='190000000000000000000000000000';\r\n   Z='32300000000000000000000000000000000000000000000000000000000';\r\nend","test_suite":"%%\r\nX='170000000000000000000000000000';\r\nY='190000000000000000000000000000';\r\nZ='32300000000000000000000000000000000000000000000000000000000';\r\nassert(isequal(Z,ylpitlum(X,Y)))\r\n\r\n%%\r\nX='235711131719';\r\nY='232931374143475359';\r\nZ='54904517812220391149679812121';\r\nassert(isequal(Z,ylpitlum(X,Y)))\r\n\r\n%%\r\nX='7657534422342987897979879745232234';\r\nY='9878765654343431233130980808776767';\r\nZ='75646988048394475543709477144832189651639589891288011407029878707478';\r\nassert(isequal(Z,ylpitlum(X,Y)))\r\n\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":2,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":82,"test_suite_updated_at":"2021-11-28T17:15:31.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-04-03T06:24:52.000Z","updated_at":"2026-02-10T19:25:06.000Z","published_at":"2012-04-03T06:24:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eImagine you are in 3012 Anno Domini, when everyone must learn how to multiply,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand competing for the highly prestigious post of,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eChief Comptroller of Ylpitlum Corporation.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou are being tested via\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eMATLAB Cody\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e for multiplication of two positive integers X and Y,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eboth are fortunately in decimal system, and only a few dozen digits or less,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand delivered as ASCII strings.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlease output the result Z in similar style.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlease adopt a general strategy, as X and Y may be changed later.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlease rename the function Z = ylpitlum(X,Y).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFunction Template:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[function Z = ylpitlum(X,Y)\\n   %  098765432109876543210987654321098765432109876543210987654321\\n   X='170000000000000000000000000000';\\n   Y='190000000000000000000000000000';\\n   Z='32300000000000000000000000000000000000000000000000000000000';\\nend]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":52183,"title":"List the nth prime quartet prefix","description":"Prime numbers larger than 5 can end only in 1, 3, 7, or 9, but of course not all numbers ending in these four digits are prime. Let’s call a group of four prime numbers between  and  (with  an integer and ) a prime quartet. The first one is 11, 13, 17, and 19, and the second is 101, 103, 107, and 109. Therefore, the prefix (or the number excluding the last digit) of the first prime quartet is 1, and the prefix of the second prime quartet is 10.\r\nWrite a function that returns the th prime quartet prefix. \r\nOptional: Prove that the sequence of prime quartet prefixes is infinite. Just drop your proof in the comments below. ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 144px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 72px; transform-origin: 407.5px 72px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 42px; text-align: left; transform-origin: 384.5px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384.5px 7.66667px; transform-origin: 384.5px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePrime numbers larger than 5 can end only in 1, 3, 7, or 9, but of course not all numbers ending in these four digits are prime. Let’s call a group of four prime numbers between \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"10k\" style=\"width: 25px; height: 18px;\" width=\"25\" height=\"18\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 15.5583px 7.66667px; transform-origin: 15.5583px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"10(k+1)\" style=\"width: 61px; height: 18.5px;\" width=\"61\" height=\"18.5\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 18.6667px 7.66667px; transform-origin: 18.6667px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (with \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003ek\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 48.625px 7.66667px; transform-origin: 48.625px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e an integer and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"k \u003e= 1\" style=\"width: 36px; height: 18px;\" width=\"36\" height=\"18\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 10.1083px 7.66667px; transform-origin: 10.1083px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) a \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 41.2333px 7.66667px; transform-origin: 41.2333px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eprime quartet\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 30.7583px 7.66667px; transform-origin: 30.7583px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The first one is 11, 13, 17, and 19, and the second is 101, 103, 107, and 109. Therefore, the prefix (or the number excluding the last digit) of the first prime quartet is 1, and the prefix of the second prime quartet is 10.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 99.4333px 7.66667px; transform-origin: 99.4333px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that returns the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003en\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 71.95px 7.66667px; transform-origin: 71.95px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eth prime quartet prefix. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 355.5px 7.66667px; transform-origin: 355.5px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOptional: Prove that the sequence of prime quartet prefixes is infinite. Just drop your proof in the comments below. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = PQPrefix(n)\r\n  y = f(n);\r\nend","test_suite":"%%\r\nn = 1;\r\ny_correct = 1;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 2;\r\ny_correct = 10;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 4;\r\ny_correct = 82;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 8;\r\ny_correct = 325;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 16;\r\ny_correct = 1804;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 32;\r\ny_correct = 7969;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 64;\r\ny_correct = 27604;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 128;\r\ny_correct = 66466;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 256;\r\ny_correct = 167056;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 512;\r\ny_correct = 454324;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 1024;\r\ny_correct = 1221643;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 2048;\r\ny_correct = 3229894;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 4096;\r\ny_correct = 8166751;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 8192;\r\ny_correct = 20302084;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 10001;\r\ny_correct = 26538121;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn1 = 3;\r\nyyy_correct = 3350308;\r\nassert(isequal(PQPrefix(PQPrefix(PQPrefix(n1))),yyy_correct))\r\n\r\n%%\r\nfiletext = fileread('PQPrefix.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp'); \r\nassert(~illegal)","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":46909,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":"2022-01-29T15:41:32.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2021-07-02T13:04:42.000Z","updated_at":"2025-11-29T23:51:09.000Z","published_at":"2021-07-02T13:11:31.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePrime numbers larger than 5 can end only in 1, 3, 7, or 9, but of course not all numbers ending in these four digits are prime. Let’s call a group of four prime numbers between \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"10k\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e10k\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"10(k+1)\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e10(k+1)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e (with \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"k\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ek\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e an integer and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"k \u0026gt;= 1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ek\\\\ge 1\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e) a \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eprime quartet\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. The first one is 11, 13, 17, and 19, and the second is 101, 103, 107, and 109. Therefore, the prefix (or the number excluding the last digit) of the first prime quartet is 1, and the prefix of the second prime quartet is 10.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that returns the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"n\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003eth prime quartet prefix. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOptional: Prove that the sequence of prime quartet prefixes is infinite. Just drop your proof in the comments below. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":44832,"title":"Generate Convolution Matrix of 2D Kernel with Different Convolution Shapes (Full, Same, Valid)","description":"In this problem the challenge is to build the Matrix Form equivalent of the function `conv2()` of MATLAB.\r\n\r\nThe function to be built will generate a sparse matrix `mK` which is the convolution matrix of the 2D Kernel 'mH' (Which is an input to the function).  \r\nThe input to the function is the 2D Kernel and dimensions of the image to apply the convolution upon and the shape of the convolution ('full', 'same', 'valid' as in 'conv2()').\r\n\r\nThe output sparse matrix should match the output of using 'conv2()' on the same image using the same convolution shape.\r\n\r\nFor instance:\r\n\r\n  CONVOLUTION_SHAPE_FULL  = 1;\r\n  CONVOLUTION_SHAPE_SAME  = 2;\r\n  CONVOLUTION_SHAPE_VALID = 3;\r\n  \r\n  numRowsImage = 100;\r\n  numColsImage = 80;\r\n  \r\n  numRowsKernel = 7;\r\n  numColsKernel = 5;\r\n  \r\n  mI = rand(numRowsImage, numColsImage);\r\n  mH = rand(numRowsKernel, numColsKernel);\r\n  \r\n  maxThr = 1e-9;\r\n  \r\n  \r\n  %% Full Convolution\r\n  \r\n  convShape       = CONVOLUTION_SHAPE_FULL;\r\n  \r\n  numRowsOut = numRowsImage + numRowsKernel - 1;\r\n  numColsOut = numColsImage + numColsKernel - 1;\r\n  \r\n  mORef   = conv2(mI, mH, 'full');\r\n  mK      = CreateImageConvMtx(mH, numRowsImage, numColsImage, convShape);\r\n  mO      = reshape(mK * mI(:), numRowsOut, numColsOut);\r\n  \r\n  mE = mO - mORef;\r\n  assert(max(abs(mE(:))) \u003c maxThr);\r\n\r\nThe test case will examine all 3 modes.\r\nTry to solve it once with very clear code (No vectorization tricks) and then optimize.\r\n\r\nA good way to build the output sparse function is using:\r\n\r\n  mK = sparse(vRows, vCols, vVals, numElementsOutputImage, numElementsInputImage);\r\n\r\nLook for the documentation of `sparse()` function for more details.","description_html":"\u003cp\u003eIn this problem the challenge is to build the Matrix Form equivalent of the function `conv2()` of MATLAB.\u003c/p\u003e\u003cp\u003eThe function to be built will generate a sparse matrix `mK` which is the convolution matrix of the 2D Kernel 'mH' (Which is an input to the function).  \r\nThe input to the function is the 2D Kernel and dimensions of the image to apply the convolution upon and the shape of the convolution ('full', 'same', 'valid' as in 'conv2()').\u003c/p\u003e\u003cp\u003eThe output sparse matrix should match the output of using 'conv2()' on the same image using the same convolution shape.\u003c/p\u003e\u003cp\u003eFor instance:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eCONVOLUTION_SHAPE_FULL  = 1;\r\nCONVOLUTION_SHAPE_SAME  = 2;\r\nCONVOLUTION_SHAPE_VALID = 3;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003enumRowsImage = 100;\r\nnumColsImage = 80;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003enumRowsKernel = 7;\r\nnumColsKernel = 5;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003emI = rand(numRowsImage, numColsImage);\r\nmH = rand(numRowsKernel, numColsKernel);\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003emaxThr = 1e-9;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003e%% Full Convolution\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003econvShape       = CONVOLUTION_SHAPE_FULL;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003enumRowsOut = numRowsImage + numRowsKernel - 1;\r\nnumColsOut = numColsImage + numColsKernel - 1;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003emORef   = conv2(mI, mH, 'full');\r\nmK      = CreateImageConvMtx(mH, numRowsImage, numColsImage, convShape);\r\nmO      = reshape(mK * mI(:), numRowsOut, numColsOut);\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003emE = mO - mORef;\r\nassert(max(abs(mE(:))) \u0026lt; maxThr);\r\n\u003c/pre\u003e\u003cp\u003eThe test case will examine all 3 modes.\r\nTry to solve it once with very clear code (No vectorization tricks) and then optimize.\u003c/p\u003e\u003cp\u003eA good way to build the output sparse function is using:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003emK = sparse(vRows, vCols, vVals, numElementsOutputImage, numElementsInputImage);\r\n\u003c/pre\u003e\u003cp\u003eLook for the documentation of `sparse()` function for more details.\u003c/p\u003e","function_template":"function [ mK ] = CreateImageConvMtx( mH, numRows, numCols, convShape )\r\n%Generates a Convolution Matrix for the 2D Kernel (The Matrix mH) with\r\n%support for different convolution shapes (Full / Same / Valid).\r\n% Input:\r\n%   - mH                -   Input 2D Convolution Kernel.\r\n%                           Structure: Matrix.\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: (-inf, inf).\r\n%   - numRows           -   Number of Rows.\r\n%                           Number of rows in the output convolution\r\n%                           matrix.\r\n%                           Structure: Scalar.\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: {1, 2, 3, ...}.\r\n%   - numCols           -   Number of Columns.\r\n%                           Number of columns in the output convolution\r\n%                           matrix.\r\n%                           Structure: Scalar.\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: {1, 2, 3, ...}.\r\n%   - convShape         -   Convolution Shape.\r\n%                           The shape of the convolution which the output\r\n%                           convolution matrix should represent. The\r\n%                           options should match MATLAB's conv2() function\r\n%                           - Full / Same / Valid.\r\n%                           Structure: Scalar.\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: {1, 2, 3}.\r\n% Output:\r\n%   - mK                -   Convolution Matrix.\r\n%                           The output convolution matrix. Multiplying in\r\n%                           the column stack form on an image should be\r\n%                           equivalent to applying convolution on the\r\n%                           image.\r\n%                           Structure: Matrix (Sparse).\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: (-inf, inf).\r\n% References:\r\n%   1.  MATLAB's 'convmtx2()' - https://www.mathworks.com/help/images/ref/convmtx2.html.\r\n% Remarks:\r\n%   1.  gf\r\n% TODO:\r\n%   1.  \r\n%   Release Notes:\r\n%   -   1.0.000     dd/mm/yyyy  firstName lastName\r\n%       *   First release version.\r\n% ----------------------------------------------------------------------------------------------- %\r\n\r\nCONVOLUTION_SHAPE_FULL  = 1;\r\nCONVOLUTION_SHAPE_SAME  = 2;\r\nCONVOLUTION_SHAPE_VALID = 3;\r\n\r\nswitch(convShape)\r\n    case(CONVOLUTION_SHAPE_FULL)\r\n        % Code for the 'full' case\r\n    case(CONVOLUTION_SHAPE_SAME)\r\n        % Code for the 'same' case\r\n    case(CONVOLUTION_SHAPE_VALID)\r\n        % Code for the 'valid' case\r\nend\r\n\r\n\r\nend\r\n\r\n","test_suite":"%% Testing\r\n\r\n\r\nCONVOLUTION_SHAPE_FULL  = 1;\r\nCONVOLUTION_SHAPE_SAME  = 2;\r\nCONVOLUTION_SHAPE_VALID = 3;\r\n\r\nmaxThr = 1e-9;\r\n\r\n\r\nfor numRowsImage = 28:32\r\n    for numColsImage = 28:32\r\n        \r\n        mI = rand(numRowsImage, numColsImage);\r\n        \r\n        for numRowsKernel = 3:7\r\n            for numColsKernel = 3:7\r\n                \r\n                mH = rand(numRowsKernel, numColsKernel);\r\n                \r\n                for convShape = 1:3\r\n                    \r\n                    switch(convShape)\r\n                        case(CONVOLUTION_SHAPE_FULL)\r\n                            numRowsOut = numRowsImage + numRowsKernel - 1;\r\n                            numColsOut = numColsImage + numColsKernel - 1;\r\n                            \r\n                            convShapeString = 'full';\r\n                        case(CONVOLUTION_SHAPE_SAME)\r\n                            numRowsOut = numRowsImage;\r\n                            numColsOut = numColsImage;\r\n                            \r\n                            convShapeString = 'same';\r\n                        case(CONVOLUTION_SHAPE_VALID)\r\n                            numRowsOut = numRowsImage - numRowsKernel + 1;\r\n                            numColsOut = numColsImage - numColsKernel + 1;\r\n                            \r\n                            convShapeString = 'valid';\r\n                    end\r\n                    \r\n                    mORef   = conv2(mI, mH, convShapeString);\r\n                    mK      = CreateImageConvMtx(mH, numRowsImage, numColsImage, convShape);\r\n                    mO      = reshape(mK * mI(:), numRowsOut, numColsOut);\r\n                    \r\n                    disp([' ']);\r\n                    disp(['Validating solution for the following parameters:']);\r\n                    disp(['Image Size - [', num2str(numRowsImage), ' x ', num2str(numColsImage), ']']);\r\n                    disp(['Kernel Size - [', num2str(numRowsKernel), ' x ', num2str(numColsKernel), ']']);\r\n                    disp(['Convolution Shape - ', convShapeString]);\r\n                    \r\n                    mE = mO - mORef;\r\n                    maxAbsDev = max(abs(mE(:)));\r\n                    if(maxAbsDev \u003e= maxThr)\r\n                        disp([' ']);\r\n                        disp(['Validation Failed']);\r\n                        disp([' ']);\r\n                    end\r\n                    assert(maxAbsDev \u003c maxThr);\r\n                    \r\n                end\r\n            end\r\n        end\r\n    end\r\nend\r\n            \r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":6204,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":"2019-01-15T23:13:37.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2019-01-15T21:20:18.000Z","updated_at":"2019-01-15T23:13:37.000Z","published_at":"2019-01-15T21:20:18.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this problem the challenge is to build the Matrix Form equivalent of the function `conv2()` of MATLAB.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe function to be built will generate a sparse matrix `mK` which is the convolution matrix of the 2D Kernel 'mH' (Which is an input to the function). The input to the function is the 2D Kernel and dimensions of the image to apply the convolution upon and the shape of the convolution ('full', 'same', 'valid' as in 'conv2()').\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output sparse matrix should match the output of using 'conv2()' on the same image using the same convolution shape.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor instance:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[CONVOLUTION_SHAPE_FULL  = 1;\\nCONVOLUTION_SHAPE_SAME  = 2;\\nCONVOLUTION_SHAPE_VALID = 3;\\n\\nnumRowsImage = 100;\\nnumColsImage = 80;\\n\\nnumRowsKernel = 7;\\nnumColsKernel = 5;\\n\\nmI = rand(numRowsImage, numColsImage);\\nmH = rand(numRowsKernel, numColsKernel);\\n\\nmaxThr = 1e-9;\\n\\n%%Full Convolution\\n\\nconvShape       = CONVOLUTION_SHAPE_FULL;\\n\\nnumRowsOut = numRowsImage + numRowsKernel - 1;\\nnumColsOut = numColsImage + numColsKernel - 1;\\n\\nmORef   = conv2(mI, mH, 'full');\\nmK      = CreateImageConvMtx(mH, numRowsImage, numColsImage, convShape);\\nmO      = reshape(mK * mI(:), numRowsOut, numColsOut);\\n\\nmE = mO - mORef;\\nassert(max(abs(mE(:))) \u003c maxThr);]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe test case will examine all 3 modes. Try to solve it once with very clear code (No vectorization tricks) and then optimize.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA good way to build the output sparse function is using:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[mK = sparse(vRows, vCols, vVals, numElementsOutputImage, numElementsInputImage);]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLook for the documentation of `sparse()` function for more details.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"}],"problem_search":{"errors":[],"problems":[{"id":52050,"title":"Matrix convolution","description":"A certain convolution step involves an elementwise multipication between two 3x3 matrices and taking the resulting sum of the elements.\r\nGiven a 3x3 kernel matrix K, find its convolution with a 3x3 subsection of a given matrix A. The subsection will be indicated by r and c, the row-column location of the top left corner element.\r\n\r\nFor example, let K = [  ], A = [   ] and r = 2, c = 3. Then the relevant 3x3 subsection of A starts at row 2 and column 3, i.e. with the element 7. Thus, the 3x3 subsection is S = [  ]. The element-wise product of S with the kernel K is [  ], and the convolution y is the sum of these elements, making y = 45.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 354px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 177px; transform-origin: 407px 177px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA certain convolution step involves an elementwise multipication between two 3x3 matrices and taking the resulting sum of the elements.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 81.5px 8px; transform-origin: 81.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a 3x3 kernel matrix \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 5px 8px; transform-origin: 5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eK\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 187px 8px; transform-origin: 187px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, find its convolution with a 3x3 subsection of a given matrix \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eA\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 106px 8px; transform-origin: 106px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The subsection will be indicated by \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 3px 8px; transform-origin: 3px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003er\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 16px 8px; transform-origin: 16px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 173.5px 8px; transform-origin: 173.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, the row-column location of the top left corner element.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 222px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 111px; text-align: left; transform-origin: 384px 111px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 52.5px 8px; transform-origin: 52.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, let \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 5px 8px; transform-origin: 5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eK\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-24px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 85.5px; height: 60px;\" width=\"85.5\" height=\"60\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 8px 8px; transform-origin: 8px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e ], \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eA\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-45px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 119px; height: 102px;\" width=\"119\" height=\"102\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 22px 8px; transform-origin: 22px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e  ] and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 3px 8px; transform-origin: 3px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003er\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 16px 8px; transform-origin: 16px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 2, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 137.5px 8px; transform-origin: 137.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 3. Then the relevant 3x3 subsection of A starts at row 2 and column 3, i.e. with the element 7. Thus, the 3x3 subsection is S = [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-24px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 64.5px; height: 60px;\" width=\"64.5\" height=\"60\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 65.5px 8px; transform-origin: 65.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e ]. The element-wise product of S with the kernel K is [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-24px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 115.5px; height: 60px;\" width=\"115.5\" height=\"60\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 217.5px 8px; transform-origin: 217.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e ], and the convolution y is the sum of these elements, making y = 45.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(K,A,r,c) %Do not alter this line\r\n  y = 1;\r\nend %Do not alter this line","test_suite":"%%\r\nA = magic(5); K = [-1 -1 -1; -1 8 -1; -1 -1 -1]; r = 2, c = 3;\r\ny_correct = 45;\r\nassert(isequal(your_fcn_name(K,A,r,c),y_correct))\r\n%%\r\nA = magic(5); K = [0 -1 0; -1 5 -1; 0 -1 0]; r = 1, c = 2;\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(K,A,r,c),y_correct))\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, 'for')),'loop forbidden')\r\nassert(isempty(strfind(filetext, 'while')),'loop forbidden')","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":31,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-06-06T14:45:47.000Z","updated_at":"2026-03-30T17:19:23.000Z","published_at":"2021-06-06T14:45:47.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA certain convolution step involves an elementwise multipication between two 3x3 matrices and taking the resulting sum of the elements.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a 3x3 kernel matrix \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eK\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, find its convolution with a 3x3 subsection of a given matrix \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. The subsection will be indicated by \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003er\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, the row-column location of the top left corner element.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, let \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eK\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e-1 \\\\;\\\\; -1 \\\\;\\\\; -1 \\\\\\\\\\n-1 \\\\;\\\\;\\\\;\\\\;\\\\;\\\\; 8 \\\\;\\\\; -1 \\\\\\\\\\n-1 \\\\;\\\\; -1 \\\\;\\\\; -1\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e ], \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e\\\\;\\\\; 17\\\\;\\\\; 24\\\\;\\\\;\\\\;\\\\;1\\\\;\\\\;\\\\;\\\\;8\\\\;\\\\; 15\\\\\\\\\\n\\\\;\\\\; 23\\\\;\\\\;\\\\;\\\\;5\\\\;\\\\;\\\\;\\\\;7\\\\;\\\\; 14\\\\;\\\\; 16\\\\\\\\\\n\\\\;\\\\;\\\\;\\\\;4\\\\;\\\\;\\\\;\\\\;6\\\\;\\\\; 13\\\\;\\\\; 20\\\\;\\\\; 22\\\\\\\\\\n\\\\;\\\\; 10\\\\;\\\\; 12\\\\;\\\\; 19\\\\;\\\\; 21\\\\;\\\\;\\\\;\\\\;3\\\\\\\\\\n\\\\;\\\\; 11\\\\;\\\\; 18\\\\;\\\\; 25\\\\;\\\\;\\\\;\\\\;2\\\\;\\\\;\\\\;\\\\;9\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e  ] and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003er\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 2, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 3. Then the relevant 3x3 subsection of A starts at row 2 and column 3, i.e. with the element 7. Thus, the 3x3 subsection is S = [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e \\\\;\\\\;7\\\\;\\\\; 14\\\\;\\\\; 16\\\\\\\\\\n13\\\\;\\\\; 20\\\\;\\\\; 22\\\\\\\\\\n19\\\\;\\\\; 21\\\\;\\\\;\\\\;\\\\;3\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e ]. The element-wise product of S with the kernel K is [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e \\\\;-7\\\\;\\\\;\\\\; -14\\\\;\\\\; -16\\\\\\\\\\n-13\\\\;\\\\;\\\\;\\\\;\\\\;\\\\; 160\\\\;\\\\; -22\\\\\\\\\\n-19\\\\;\\\\;\\\\;\\\\; -21\\\\;\\\\;\\\\;-3\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e ], and the convolution y is the sum of these elements, making y = 45.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":694,"title":"Remove NaNs and numbers adjacent to NaNs","description":"The aim is to remove the elements before and after NaN occurrences inside a vector.\r\n\r\nFor example:\r\n\r\n x = [6 10 5 8 9 NaN 23 10 7 3 21 43 NaN 4 6 7 8]\r\n\r\nThe output y will be:\r\n\r\n y = [6 10 5 8 10 7 3 21 6 7 8]\r\n\r\nIf NaNs occur at the beginning or end then first two or last two values are removed.\r\n\r\n x=[NaN 1 2 3]  yields [2 3]\r\n\r\nNaN values will exist in every case.\r\nNo case is an empty set.","description_html":"\u003cp\u003eThe aim is to remove the elements before and after NaN occurrences inside a vector.\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cpre\u003e x = [6 10 5 8 9 NaN 23 10 7 3 21 43 NaN 4 6 7 8]\u003c/pre\u003e\u003cp\u003eThe output y will be:\u003c/p\u003e\u003cpre\u003e y = [6 10 5 8 10 7 3 21 6 7 8]\u003c/pre\u003e\u003cp\u003eIf NaNs occur at the beginning or end then first two or last two values are removed.\u003c/p\u003e\u003cpre\u003e x=[NaN 1 2 3]  yields [2 3]\u003c/pre\u003e\u003cp\u003eNaN values will exist in every case.\r\nNo case is an empty set.\u003c/p\u003e","function_template":"function y = NaN_window_delete(x)\r\n  y=x;\r\nend","test_suite":"%% \r\nx=[1 2 3 NaN 4 5 6];\r\ny_correct=[1 2 5 6];\r\nassert(isequal(NaN_window_delete(x),y_correct))\r\n%% \r\nx=[10 20 3 NaN 4 50 NaN 6];\r\ny_correct=[10 20];\r\nassert(isequal(NaN_window_delete(x),y_correct))\r\n%% \r\nx=[NaN 20 3 5 4 50 55 NaN];\r\ny_correct=[3 5 4 50];\r\nassert(isequal(NaN_window_delete(x),y_correct))\r\n%% \r\nx=[10 20 3 5 NaN 4 50 55 NaN 60 80 90 NaN 100 110 ];\r\ny_correct=[10 20 3 50 80 110];\r\nassert(isequal(NaN_window_delete(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":80,"test_suite_updated_at":"2012-05-16T21:35:19.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-05-16T21:24:52.000Z","updated_at":"2026-03-10T15:29:04.000Z","published_at":"2012-05-16T21:35:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe aim is to remove the elements before and after NaN occurrences inside a vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ x = [6 10 5 8 9 NaN 23 10 7 3 21 43 NaN 4 6 7 8]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output y will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ y = [6 10 5 8 10 7 3 21 6 7 8]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf NaNs occur at the beginning or end then first two or last two values are removed.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ x=[NaN 1 2 3]  yields [2 3]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNaN values will exist in every case. No case is an empty set.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1441,"title":"Convolution Power","description":"Create the convolution-power vector from initial vector _x_ and power _n_.  In other words, similar to the scalar case, raising to the _n_-th power means repeating the convolution on itself _n_ times. \r\n\r\nAssume that _n_ is a non-negative integer and _x_ is a row vector.\r\n\r\n*Examples*:\r\n\r\n convpower(1:5,0)\r\n ans =\r\n     1\r\n\r\n convpower(1:5,1)\r\n ans = \r\n     1     2     3     4     5\r\n\r\n convpower(1:5,2)\r\n ans = \r\n     1     4    10    20    35    44    46    40    25\r\n\r\nNeither *string operations* nor *interpolations* are allowed!\r\n","description_html":"\u003cp\u003eCreate the convolution-power vector from initial vector \u003ci\u003ex\u003c/i\u003e and power \u003ci\u003en\u003c/i\u003e.  In other words, similar to the scalar case, raising to the \u003ci\u003en\u003c/i\u003e-th power means repeating the convolution on itself \u003ci\u003en\u003c/i\u003e times.\u003c/p\u003e\u003cp\u003eAssume that \u003ci\u003en\u003c/i\u003e is a non-negative integer and \u003ci\u003ex\u003c/i\u003e is a row vector.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExamples\u003c/b\u003e:\u003c/p\u003e\u003cpre\u003e convpower(1:5,0)\r\n ans =\r\n     1\u003c/pre\u003e\u003cpre\u003e convpower(1:5,1)\r\n ans = \r\n     1     2     3     4     5\u003c/pre\u003e\u003cpre\u003e convpower(1:5,2)\r\n ans = \r\n     1     4    10    20    35    44    46    40    25\u003c/pre\u003e\u003cp\u003eNeither \u003cb\u003estring operations\u003c/b\u003e nor \u003cb\u003einterpolations\u003c/b\u003e are allowed!\u003c/p\u003e","function_template":"function y = convpower(x,n)\r\n  y = x;\r\nend","test_suite":"%%\r\nuser_solution = fileread('convpower.m');\r\nassert(isempty(strfind(user_solution,'regexp')));\r\nassert(isempty(strfind(user_solution,'2str')));\r\nassert(isempty(strfind(user_solution,'str2')));\r\nassert(isempty(strfind(user_solution,'interp')));\r\nassert(isempty(strfind(user_solution,'printf')));\r\nassert(isempty(strfind(user_solution,'assert')));\r\n\r\n%%\r\nx = [1 2 3];\r\nn = 0;\r\ny_correct = 1;\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [3 8 1 2 3];\r\nn = 1;\r\ny_correct = [3 8 1 2 3];\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [3 8 1 2 3];\r\nn = 3;\r\ny_correct = [27   216   603   710   570   876   763   354   390   260    63    54    27];\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [1 3 2];\r\nn = 2;\r\ny_correct = [ 1     6    13    12     4];\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [1 1];\r\nn = 10;\r\ny_correct = [ 1    10    45   120   210   252   210   120    45    10     1]\r\nassert(isequal(convpower(x,n),y_correct))\r\n\r\n%%\r\nx = [1 5 2];\r\nn = 7;\r\ny_correct = [1          35         539        4795       27209      102725      261905      451225      523810      410900      217672 76720       17248        2240         128]\r\nassert(isequal(convpower(x,n),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":10352,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":54,"test_suite_updated_at":"2013-04-28T07:05:45.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-04-22T11:04:39.000Z","updated_at":"2026-03-11T08:30:52.000Z","published_at":"2013-04-22T11:07:31.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCreate the convolution-power vector from initial vector\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and power\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. In other words, similar to the scalar case, raising to the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-th power means repeating the convolution on itself\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e times.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAssume that\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is a non-negative integer and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is a row vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ convpower(1:5,0)\\n ans =\\n     1\\n\\n convpower(1:5,1)\\n ans = \\n     1     2     3     4     5\\n\\n convpower(1:5,2)\\n ans = \\n     1     4    10    20    35    44    46    40    25]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNeither\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003estring operations\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e nor\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003einterpolations\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e are allowed!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":43494,"title":"Weighted Convolution","description":"Given two input vectors x = [x_1, x_2, ..., x_K] and y = [y_1, y_2, ..., y_K] of equal length, compute the weighted convolution output z = [z_1, z_2, ..., z_K], where \r\n\r\n     z_k = sum(nchoosek(k-1,j-1)*x_{k-j+1}*y_j, j = 1..k),  k = 1, 2, ..., K\r\n\r\nExample: x = [1, 2, 3]; y = [4, 5, 6]. Then z = [z_1, z_2, z_3] where \r\n\r\n  z_1 = nchoosek(0,0)*1*4 = 4\r\n  z_2 = nchoosek(1,0)*2*4 + nchoosek(1,1)*1*5 = 13\r\n  z_3 = nchoosek(2,0)*3*4 + nchoosek(2,1)*2*5 + nchoosek(2,2)*1*6 = 38\r\n \r\nHint: This can be seen as the linear convolution weighted by the binomial coefficient. It is straightforward to solve this problem using a for loop. I am wondering if there exists some more elegant way (e.g., vectorization) to do this. \r\n\r\n","description_html":"\u003cp\u003eGiven two input vectors x = [x_1, x_2, ..., x_K] and y = [y_1, y_2, ..., y_K] of equal length, compute the weighted convolution output z = [z_1, z_2, ..., z_K], where\u003c/p\u003e\u003cpre\u003e     z_k = sum(nchoosek(k-1,j-1)*x_{k-j+1}*y_j, j = 1..k),  k = 1, 2, ..., K\u003c/pre\u003e\u003cp\u003eExample: x = [1, 2, 3]; y = [4, 5, 6]. Then z = [z_1, z_2, z_3] where\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ez_1 = nchoosek(0,0)*1*4 = 4\r\nz_2 = nchoosek(1,0)*2*4 + nchoosek(1,1)*1*5 = 13\r\nz_3 = nchoosek(2,0)*3*4 + nchoosek(2,1)*2*5 + nchoosek(2,2)*1*6 = 38\r\n\u003c/pre\u003e\u003cp\u003eHint: This can be seen as the linear convolution weighted by the binomial coefficient. It is straightforward to solve this problem using a for loop. I am wondering if there exists some more elegant way (e.g., vectorization) to do this.\u003c/p\u003e","function_template":"function z = weightedConv(x,y)\r\n  z = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny = 1;\r\nz = 1;\r\nassert(isequal(weightedConv(x,y),z))\r\n\r\n%%\r\nx = 1:2;\r\ny = 3:4;\r\nz = [3 10];\r\nassert(isequal(weightedConv(x,y),z))\r\n\r\n%%\r\nx = 1:3;\r\ny = 4:6;\r\nz = [4 13 38];\r\nassert(isequal(weightedConv(x,y),z))\r\n\r\n\r\n%%\r\nx = 1:4;\r\ny = 5:8;\r\nz = [5 16 46 124];\r\nassert(isequal(weightedConv(x,y),z))\r\n\r\n%%\r\nx = 1:10;\r\ny = 2:11;\r\nz = [2,7,22,64,176,464,1184,2944,7168,17152];\r\nassert(isequal(weightedConv(x,y),z))","published":true,"deleted":false,"likes_count":6,"comments_count":7,"created_by":12569,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-13T05:39:48.000Z","updated_at":"2025-12-15T03:59:38.000Z","published_at":"2016-10-13T06:12:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven two input vectors x = [x_1, x_2, ..., x_K] and y = [y_1, y_2, ..., y_K] of equal length, compute the weighted convolution output z = [z_1, z_2, ..., z_K], where\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[     z_k = sum(nchoosek(k-1,j-1)*x_{k-j+1}*y_j, j = 1..k),  k = 1, 2, ..., K]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample: x = [1, 2, 3]; y = [4, 5, 6]. Then z = [z_1, z_2, z_3] where\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[z_1 = nchoosek(0,0)*1*4 = 4\\nz_2 = nchoosek(1,0)*2*4 + nchoosek(1,1)*1*5 = 13\\nz_3 = nchoosek(2,0)*3*4 + nchoosek(2,1)*2*5 + nchoosek(2,2)*1*6 = 38]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint: This can be seen as the linear convolution weighted by the binomial coefficient. It is straightforward to solve this problem using a for loop. I am wondering if there exists some more elegant way (e.g., vectorization) to do this.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":543,"title":"deconvolution","description":"* Suppose there is a vector v like [1 0 0 -1], representing polynomial coefficients.\r\n* In this example, the polynimial is 1*x^3+0*x^2+0*x-1 or (x^3-1).\r\n* Suppose there is another vector w like [1 -1].\r\n* In this example, the second polynomial is (x-1).\r\n* If x is any integer then the polynomial represented by (v/w) is integer?\r\n ","description_html":"\u003cul\u003e\u003cli\u003eSuppose there is a vector v like [1 0 0 -1], representing polynomial coefficients.\u003c/li\u003e\u003cli\u003eIn this example, the polynimial is 1*x^3+0*x^2+0*x-1 or (x^3-1).\u003c/li\u003e\u003cli\u003eSuppose there is another vector w like [1 -1].\u003c/li\u003e\u003cli\u003eIn this example, the second polynomial is (x-1).\u003c/li\u003e\u003cli\u003eIf x is any integer then the polynomial represented by (v/w) is integer?\u003c/li\u003e\u003c/ul\u003e","function_template":"function yesno = integ(v,w)\r\n  yesno=1==1/1; % yes\r\n  yesno=1==1/2; % no\r\nend","test_suite":"%%\r\nv=[1 0 0 -1];\r\nw=[1 -1];\r\nassert(integ(v,w))\r\n%%\r\nv=[2 9 6 -1 16 -5];\r\nw=[2 3 -1 5];\r\nassert(integ(v,w))\r\n%%\r\nv=[1 4 10 20 35 50 58 58 49 30];\r\nw=1:6;\r\nassert(integ(v,w))\r\n%%\r\nv=1:10;\r\nw=1:6;\r\nassert(~integ(v,w))\r\n%%\r\nv=3:12;\r\nw=-3:2;\r\nassert(~integ(v,w))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":60,"test_suite_updated_at":"2012-03-31T22:38:54.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-03-31T22:38:54.000Z","updated_at":"2025-12-08T23:40:32.000Z","published_at":"2012-03-31T22:38:54.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSuppose there is a vector v like [1 0 0 -1], representing polynomial coefficients.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this example, the polynimial is 1*x^3+0*x^2+0*x-1 or (x^3-1).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSuppose there is another vector w like [1 -1].\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this example, the second polynomial is (x-1).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf x is any integer then the polynomial represented by (v/w) is integer?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":46663,"title":"Kaggle: Planetoid Game of Life - Variable Iterations for a wrapping array","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 377.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 188.583px; transform-origin: 407px 188.583px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003ca target='_blank' href = \"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 203.05px 7.91667px; transform-origin: 203.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://mathworld.wolfram.com/GameofLife.html\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eGame of Life at Wolfram\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 1.95px 7.91667px; transform-origin: 1.95px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eWiki Life\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 138.467px 7.91667px; transform-origin: 138.467px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 360.583px 7.91667px; transform-origin: 360.583px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis Challenge is to Evolve a given 25x25 matrix for a given number(1 to 5) of iterations per these revised Life Laws.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 350.35px 7.91667px; transform-origin: 350.35px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e1. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 188.65px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 188.65px 7.91667px; \"\u003elive cell with fewer than two live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 115.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 115.5px 7.91667px; \"\u003eif caused by under-population.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 315.7px 7.91667px; transform-origin: 315.7px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e2. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 288.75px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 288.75px 7.91667px; \"\u003elive cell with two or three live neighbors lives on to the next generation.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 311.85px 7.91667px; transform-origin: 311.85px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e3. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 192.5px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 192.5px 7.91667px; \"\u003elive cell with more than three live neighbors dies\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by overcrowding.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 361.9px 7.91667px; transform-origin: 361.9px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 26.95px 7.91667px; transform-origin: 26.95px 7.91667px; \"\u003e4. Any \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 242.55px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 242.55px 7.91667px; \"\u003edead cell with exactly three live neighbors becomes a live cell\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; \"\u003e, as \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 73.15px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 73.15px 7.91667px; \"\u003eif by reproduction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 265.65px 7.91667px; transform-origin: 265.65px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 34.65px 7.91667px; transform-origin: 34.65px 7.91667px; \"\u003e5. Edges \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 231px 7.91667px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 231px 7.91667px; \"\u003ewrap around. Eight Neighbors. (Change to normal planar life)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.317px 7.91667px; transform-origin: 221.317px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.4333px 7.91667px; transform-origin: 19.4333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 146.25px 7.91667px; transform-origin: 146.25px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (A,iter) Initial state(25,25), number of iterations\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 25.2667px 7.91667px; transform-origin: 25.2667px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 76.2333px 7.91667px; transform-origin: 76.2333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e B the final evolved state\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 7.91667px; transform-origin: 0px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function B=iterlife(A,iter)\r\n B=A;\r\n \r\nend\r\n\r\n%Non-wap Life calc by Alfonso\r\n% C=convn(A,ones(3),'same');\r\n% B = C==3 | A\u0026C==4;","test_suite":"%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 4\r\niter=1;\r\nAstr='0001100000000000001000001000000000000001110010000100000000000000110001000100000000000000001001000000000000000000000010100000000000001000000000000000000000001010000000000000000000000001000000000000000000000001000000000110000000000000000000000100100000001100000000000001010000001001000000000000001000000110000000000000000000000000000000000000000000000000110000000000000000000000001000000000000000000011100000000000010000000000110000000000010100000000000000000000001010000000000000000000000010000000000000000000000000000000000000000000000000000000000000000000000000000000100000000011000000000110110000000010010000000011110100010';\r\nBstr='0001100000000000001100011000000000000001010110001100000000000000000011000000000000000000011111100000000000000000000001000000000000001000000000000000000000000010000000000000000000000001000000000000000000000000000000000110000000000000000000000100100000001100000000000000011000001000000000000000010000000110000000000000000000000010100000000000000000000000110000000000000000000001011000000000000000000011100000000000010000000001010000000000010100000000010000000000001010000000000000000000000010000000000000000000000000000000000000000000000000000000000000000000000000000001100000000011000000000100001000000010010000000010000100000';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 16\r\niter=2;\r\nAstr='0011100100000000001111000101000010000000011010010000111101000000001000011011011100101100000110000100110000010100000000000111001000000100000100000110001100000000000100000001100000000000000101001111010011000000000011110010101010010000111101001100000110110001111111101100001011111000110110110001100001110000000000100111000011011000000011011000110000000100000001111100011000011100000001001000100000000010000001110100000001100100010001000010001100010000110000010000000000000011011100010000100000000000001011000000001000000000001101100000101000000000000100000000111101000000000000000000110000000000000000000011000100000000000010000';\r\nBstr='0000100000000000111101000000011000000000010011001110001101010000010010011010100100101100000110001100110000110010000000000001000100000110000000001011001100000000000110011000100000000000000101001100010111000000000000001010100011010000000000000011100000011000000000000111000000000000110000001111100000000000001000000100000011000000000110001100010000110100000010000111011100011010000010100111000001001000000011111100000000000001000001001110000000101110111100110000000000001101101000000000100000000000010000000001111000000000010001000001100000000000000101100001001110000000000001100001100000000000000000000000110110000000000011000';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 2\r\niter=3;\r\nAstr='0100000101000001000000110011000010000001100000000001000000110011000000000001000000011110000000010000100000000001110000000000000011000000101000000000001011110000010100000001000100100110001110000011001110011011000101100000101010000100000000000000000000000000000000000000101010000000000011101001011011110000000001111110110010001100000000001011101000010100000000000011000000010010000000010000111110000010000000010001000000000000000000001000001111000000000000000001010001000000000011000000001001000000000010100000000010100000000000100000000000000000001000000000000000101000001110000000000000100100001101111000000011000000001100000';\r\nBstr='1000001100100010001000101100000111000001000000001110000011100000000000000011000000011011011000000001101100001111111000000000110110110110100000000100011010000110100000000011000101010011011110000010010010000001000100000000010010001011100010001101000000000011000000001000110111000000000000000100000000101000000000000000000000000010000000000000010000100010000000000000100010001100000000010001111011000001000000010101100000100000000000001001011010100000000000000001010010010000000011000000011000000000000010100000000000000000110000100000000000000000101000000000000000000000010001000000000111000000010000011000000011100010001000000';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 1\r\niter=4;\r\nAstr='0000100001101010011100110000000000010000100101110000011000000110110001000000010010000010111000000010001000000000011100000001100100011100010110000000001100000111001010000001110000111100010111100000011111110100110000110001100010000100100100001000100001000110001110000000000101000000000001000000010111100000000111000000001000010000000011000000000000001100100000000000001110000011010100000000000000000011001001000000000000000000000011100000000000000000001100001111100000100000000000000110101001101100000001100000000110100110000010000000110010010000000001110000011111000111100000000000010100000000001000011000110000001100010111011';\r\nBstr='0000000000000000010000000000000000000110001110000001001100001001001111100100100110001100101100000000010000000111100000000001000000000000010000000000000001100000011100000010000000100000001110000001111101100000001110000000100001111000000010000000001001100010001101000000001101100001110000000001110011000000001111100000000000000000000011110000001100000001000000000000000000000010101010000000000000000011000111011011000010000001001011010111010010100000010100110100001010001000001110011000000100100100000011000011001110000110000010010000000001100001000010000000000011101010000000001100000001000000000000110000000011000000001000000';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n%%\r\n%Test Cases taken from Kaggle Training set\r\n%Case 3\r\niter=5;\r\nAstr='0110000000000011000000011100000000000001100000001001100000000000100001011001001110000110000000010101000000001111100000101100000011011111100001011100000000101000000001100000001100011100000000100100001010000000000000010010000100000000000000000110000001000000000100000000001100000000000010001100000110000000010001000110000000000000011000100001000010000000011000011000100001000000000110000100010001010000000000001100000000001100000000000100000000001110000000000000000000000100100000001000000000000001010000011011000000000000110000001101100000000000000000000110110000000000000000000000100000000110000000001000000000000000000000000';\r\nBstr='1100001000000100000000011100001000000101000000001011110000000100000000001000000100000100000100000000000000000010001001000000000011111001010100100100010001100100000000000001001100011100000001010000001010000100000000000010000100000000000000010010000001000000001100000001000000000000111110001100001000000011011000001000101100000010000000000000001011000001001110010001001000100000110001100000011000010000001110000001000000011000000010000001000000010000000000000001000000011100000001000000000000000100110001000100010000000010001000000101001000000000100100100001000100000000001000001000000100000000000000010100000100000000000000010';\r\nA=reshape(Astr-'0',25,25);\r\nB=reshape(Bstr-'0',25,25);\r\nC=iterlife(A,iter);\r\nif ~isequal(C,B)\r\n logical(A)\r\n logical(B)\r\n logical(C)\r\nend\r\nassert(isequal(C,B))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-03T16:50:36.000Z","updated_at":"2020-10-03T17:35:03.000Z","published_at":"2020-10-03T17:35:03.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.kaggle.com/c/conways-reverse-game-of-life-2020\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eKaggle's Conway's Reverse Game of Life 2020 \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003econtest inspires this Life challenge. The kaggle contest runs from Oct-01-2020 thru Nov-30-2020. References:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://mathworld.wolfram.com/GameofLife.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGame of Life at Wolfram\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eWiki Life\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The Kaggle event is 50K cases to solve for a state 1 to 5 iterations prior to a given state. Imperfect solutions are allowed but penalized. Input file to Kaggle is a csv so Matlab solutions can be posted at the Kaggle site for this event.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is to Evolve a given 25x25 matrix for a given number(1 to 5) of iterations per these revised Life Laws.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1. Any live cell with fewer than two live neighbors dies, as if caused by under-population.\\n2. Any live cell with two or three live neighbors lives on to the next generation.\\n3. Any live cell with more than three live neighbors dies, as if by overcrowding.\\n4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.\\n5. Edges wrap around. Eight Neighbors. (Change to normal planar life)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: The edges wrap so the matrix represents the surface of a sphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (A,iter) Initial state(25,25), number of iterations\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e B the final evolved state\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58926,"title":"Neural Net: Convolutional NN Matrices Determination for LED Digit images","description":"This challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. A fun extension is to add LED variants and see if trained WH/WP give expected result.\r\n[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\r\n \r\nThe matlab Latex code for making the CNN Processing chart included in template.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 691.5px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 345.75px; transform-origin: 407px 345.75px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. A fun extension is to add LED variants and see if trained WH/WP give expected result.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 162.5px 8px; transform-origin: 162.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 529.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 264.75px; text-align: left; transform-origin: 384px 264.75px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline;width: 875px;height: 524px\" 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data-image-state=\"image-loaded\" width=\"875\" height=\"524\"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 257px 8px; transform-origin: 257px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe matlab Latex code for making the CNN Processing chart included in template.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [WP,WH]=ConvNN_Process(XImg,K,WH,WP,EPY)\r\n %nX=size(XImg,3); %Number training images\r\n %nK=size(K,3); % Number kernels\r\n %XC=zeros(5,3,nK); %Pre-alloc for speed\r\n \r\n for epoch=1:1000 % Number of cycles to evolve WH and WP\r\n  dWH=0*WH;\r\n  dWP=0*WP;\r\n  for iCase=1:nX  %Cycle thru all Images while accumulating dWH and dWP\r\n %Forward Pass  X(7,5,nX)-Ximg,Conv-XC(5,3,nK),ReLU-XCY3(5,3,nK),XCY(1,nK*15+1)(1,91)\r\n % XCYV*WH-H(1,21), ReLU(H)-HY(1,21), HY*WP-P(1,10), Softmax(P)-PY\r\n   for k=1:nK\r\n    %XC(:,:,k)=(conv2(XImg(:,:,iCase),K(:,:,k),'valid')); %Use rot90 Kernel to make output align\r\n   end\r\n\r\n   %XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive; safer to leave in for K offset case\r\n   %XCY=[XCY3(:)' 1]; % 1,nK*15+1  (1,91)  add a 1 for offset term\r\n \r\n   %[dWPi,dWHi]=Neural_ReLU_Back_Propagation(XCY,WH,WP,EPY(iCase,:));\r\n \r\n %Accumulate across all sample cases\r\n   %dWP=dWP+dWPi;\r\n   %dWH=dWH+dWHi;\r\n \r\n  end % iCase\r\n\r\n  %WP=WP+dWP/nX; % dWP/nX  Valid\r\n  %WH=WH+dWH/nX; % Usage /nX^2 requires 10K epochs for \u003e.8 PYs\r\n\r\n end % epoch\r\nend %ConvNN_Process\r\n\r\nfunction [dWP,dWH]=Neural_ReLU_Back_Propagation(X,WH,WP,EPY)\r\n% X will be single case [X1 X2 ... XN 1]\r\n  LR=1; % Learning Rate\r\n  \r\n  H=X*WH;\r\n  HY=max(0,H); % ReLU\r\n  \r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 PY2 ... PYM]\r\n  \r\n  %Back Propagation Calculations\r\n  ErrPY=EPY-PY;\r\n  \r\n  dPY=PY.*(1-PY).*ErrPY;\r\n  dWP=LR*HY'.*dPY;\r\n  \r\n  dHY=HY.*(1-HY).*sum(WP.*dPY,2)';\r\n  dWH=LR*X'.*dHY;\r\nend % Neural_ReLU_Back_Propagation\r\n\r\n\r\n%{\r\nfunction NNConv_flow\r\n%Convolution neural net process flow\r\n\r\n%shape prep\r\nr = 10;r5=5;\r\nphi = 0:0.01:2*pi;\r\ncxA = r*cos(phi);\r\ncyA = r*sin(phi);\r\n\r\nrxA=[0 2*r 2*r   0 0]';rx5=[0 r r 0 0]';\r\nryA=[0   0 2*r 2*r 0]';ry5=[0 0 r r 0]';\r\n\r\n\r\nf=figure(1);clf;\r\nf.Position=[1935 122 1459 873]; % Dual Monitor setting\r\n\r\nplot([0;160;160;0;0],[-5;-5;100;100;-5],'k','linewidth',2);hold on\r\nxticks([]);yticks([]); %Ticks/Labels off\r\naxis equal;axis tight;\r\n\r\npatch(rxA*1.9+48,ryA+75,'y')\r\ntext(50,93,'Images','Fontsize',14);text(65,93,'Kernels','Fontsize',14);\r\nfor j=0:3\r\n plot(rx5+50+j,ry5+81-j,'k','linewidth',1);\r\n plot(rx5+65+j,ry5+81-j,'k','linewidth',1);\r\nend\r\ntext(79,90,'EPY','Fontsize',14);text(79,86,'WH','Fontsize',14);text(79,82,'WP','Fontsize',14);\r\ntext(49,76.5,'Initial Inputs','Fontsize',14);\r\nquiver(86,86,3,0,'k','LineWidth',3.5,'MaxHeadSize',1);\r\n\r\npatch(rxA*3.5+89,ryA*1.9+56,[1 .75 .4])\r\ntext(90,92.5,'Epoch:  Cycle over Training Images (1K to 10K)','Fontsize',14);\r\ntext(92,89,'Loop over Images to Update WP and WH','Fontsize',14);\r\ntext(92,86,'dWP=0;  dWH=0','Fontsize',14);\r\ntext(92,62,'WP = WP + dWP / nX   %nX = # Training images','Fontsize',14);\r\ntext(92,58,'WH = WH + dWH / nX','Fontsize',14);\r\n\r\npatch(rxA*3.3+91,ryA*0.95+65,[.75 1 .4])\r\ntext(92,82,'Cases:  Cycle thru Training Images','Fontsize',14);\r\ntext(94,79,'Loop over Convolutions per Training Image ','Fontsize',14);\r\ntext(94,75.5,'Create XC ( : , : , k ) - Convolution Planes Image_{i}','Fontsize',14);\r\ntext(96,73,'Create XCY - Convolution Set Vector [1,91]','Fontsize',14);\r\ntext(98,70,'Perform dWP dWH Back Propagation','Fontsize',14);\r\ntext(98,67,'Update dWP and dWH','Fontsize',14);\r\n\r\npatch(rxA*3.5+89,ryA*2.4+7,[.4 1 .75])\r\ntext(96,53,'Processing Numerical Convergence Concerns','Fontsize',14);\r\ntext(90,49,'Kernels need to be scaled(sum \u003c=1) or offset(sum~=0)','Fontsize',14);\r\ntext(90,45,'WH and WP require offset and scale normalization','Fontsize',14);\r\ntext(90,41,'WH=[(rand(90,20)-.5)/sqrt(90+20) zeros(90,1)]','Fontsize',14);\r\ntext(90,37,'WP=(rand(21,10)-.5)/sqrt(21+10);','Fontsize',14);\r\ntext(93,33,'Offset to achieve zero-sum','Fontsize',14);\r\ntext(93,29,'Scale to avoid large positive sum','Fontsize',14);\r\ntext(90,25,'nX factor for WP, WH updates needed for convergence','Fontsize',14);\r\ntext(90,21,'Scale mods change convergence rate and stability','Fontsize',14);\r\ntext(92,17,'(2*nX) requires 2K Epochs to achieve .90 Predictions','Fontsize',14);\r\ntext(90,13,'WH w=20 was arbitrary at 2 * # Classes','Fontsize',14);\r\ntext(90,9,'WH h=91 is conv(h*w)*Kernels +1 ','Fontsize',14);\r\n\r\npatch(rxA*3.5+89,ryA*.5-4,[1 .4 1])\r\ntext(90,4.5,'Kernels are to capture features','Fontsize',14);\r\ntext(90,1.5,'Internal Corners and Straights were selected','Fontsize',14);\r\ntext(90,-1.5,'Centering done for debugging (not required)','Fontsize',14);\r\n\r\ntext(1,97,'Convolution Neural Net: Forward Pass and Back Propagation WP \u0026 WH','Fontsize',20);\r\n\r\ntext(1,93.5,'\\color[rgb]{1 .5 .2}Ten Input Images(7x5) [Ringed by 0s]','Fontsize',12) %Valid\r\ntext(1,91,'\\bf 1  111 111 1 1 111 1   111 111 111 111','Fontsize',9,'Fontname','Courier')  %bf bold_font\r\ntext(1,91,'\\bf\\color{red}. .          .       ..','Fontsize',9,'Fontname','Courier')  %bold_font, color\r\ntext(1,89,'\\bf 1    1   1 1 1 1   1     1 1 1 1 1 1 1','Fontsize',9,'Fontname','Courier')\r\ntext(1,89,'\\bf\\color{red}. . ..  ..   .   ..  .. ..   .   .   . ','Fontsize',9,'Fontname','Courier')\r\ntext(1,87,'\\bf 1  111 111 111 111 111   1 111 111 1 1','Fontsize',9,'Fontname','Courier')\r\ntext(1,87,'\\bf\\color{red}. .                     ..           . ','Fontsize',9,'Fontname','Courier')\r\ntext(1,85,'\\bf 1  1     1   1   1 1 1   1 1 1   1 1 1','Fontsize',9,'Fontname','Courier')\r\ntext(1,85,'\\bf\\color{red}. .  .. ..  ..  ..   .  ..   .  ..   . ','Fontsize',9,'Fontname','Courier')\r\ntext(1,83,'\\bf 1  111 111   1 111 111   1 111   1 111','Fontsize',9,'Fontname','Courier')\r\ntext(1,83,'\\bf\\color{red}. .         ..          ..      ..','Fontsize',9,'Fontname','Courier')\r\n\r\ntext(1,80.5,'\\color[rgb]{1 .2 .5}Six Conv Kernels (3x3) TL TR LL LR V H','Fontsize',12) %Valid\r\ntext(1,78,'\\bf         1   1   1  ','Fontsize',9,'Fontname','Courier')  %bf bold_font\r\ntext(1,78,'\\bf\\color{red}... ... . . . . . . ...','Fontsize',9,'Fontname','Courier')  %bold_font, color\r\ntext(1,76,'\\bf 11 11   11 11   1  111','Fontsize',9,'Fontname','Courier')\r\ntext(1,76,'\\bf\\color{red}.     . .     . . .','Fontsize',9,'Fontname','Courier')\r\ntext(1,74,'\\bf.1. .1. ... ... .1. ...','Fontsize',9,'Fontname','Courier')\r\ntext(1,74,'\\bf\\color{red}. . . . ... ... . . ...','Fontsize',9,'Fontname','Courier')\r\n\r\ntext(1,71,'EPY=eye(10)','Fontsize',18,'Color','b');\r\ntext(1,66,'XC(:,:,k)=conv2(XImg(:,:,i),K(:,:,k),''valid'')  % [5,3]','Fontsize',18,'Color','b');\r\ntext(5,61,'XCY3=max(0,XC)  % ReLU [5,3,6]','Fontsize',18,'Color','b');\r\ntext(5,56,'XCY=[XCY3(:)'' 1]   % [1,91]','Fontsize',18,'Color','b');\r\n\r\nstr='$$ XCY*WH=H ; $$';\r\ntext(1,51,str,'Interpreter','latex','Fontsize',16);\r\nstr='$$ H=\\left[\\matrix{ H_{1} \u0026 ... \u0026 H_{20} \u0026 1} \\right]  $$'; \r\ntext(32,51,str,'Interpreter','latex','Fontsize',16);\r\n\r\nstr='$$ ReLU(H)=HY  $$'; \r\ntext(1,47,str,'Interpreter','latex','Fontsize',16);\r\nstr='$$ HY=\\left[\\matrix{ HY_{1} \u0026 ... \u0026 HY_{20} \u0026 1} \\right]  $$'; \r\ntext(32,47,str,'Interpreter','latex','Fontsize',16);\r\n\r\nstr='$$ HY*WP=P;  $$';\r\ntext(1,43,str,'Interpreter','latex','Fontsize',16);\r\nstr='$$ P=\\left[\\matrix{ P_{1} \u0026 ... \u0026 P_{10} } \\right]  $$'; \r\ntext(32,43,str,'Interpreter','latex','Fontsize',16);\r\n\r\nstr='$$ Softmax(P)=PY;  $$'; \r\ntext(1,39,str,'Interpreter','latex','Fontsize',16);\r\nstr='$$ PY=\\left[\\matrix{ PY_{1} \u0026 ... \u0026 PY_{10}} \\right]  $$'; \r\ntext(32,39,str,'Interpreter','latex','Fontsize',16);\r\n\r\ntext(5,34.5,'Softmax(P)=e^{P}/\\Sigmae^{P}','Fontsize',20,'Color',[1 .5 .2]);\r\n\r\ntext(1,28.5,'[ dWPi , dWHi ] = ...','Fontsize',18,'Color','b');\r\ntext(1,23.8,'Back\\_Prop\\_WP\\_WH ( XCY, WH, WP, EPY(i,:) )','Fontsize',18,'Color','b');\r\n\r\ntext(15,19,'WH','Fontsize',18);\r\nstr='$$ \\left[\\matrix{ WH_{1,1} \u0026 ... \u0026 WH_{1,20} \u0026 0 \\cr WH_{2,1} \u0026 ... \u0026 WH_{2,20} \u0026 0 \\cr : \u0026 : \u0026 : \u0026 0 \\cr WH_{90,1} \u0026 ... \u0026 WH_{90,20} \u0026 0 \\cr bH_{91,1} \u0026 ... \u0026 bH_{91,20} \u0026 1 } \\right]  $$'; %valid\r\ntext(1,6,str,'Interpreter','latex','Fontsize',18);\r\n\r\ntext(58,19,'WP','Fontsize',18);\r\nstr='$$ \\left[\\matrix{ WP_{1,1} \u0026 ... \u0026 WP_{1,10} \\cr WP_{2,1} \u0026 ... \u0026 WP_{2,10} \\cr : \u0026 : \u0026 :  \\cr WP_{20,1} \u0026 ... \u0026 WP_{20,10} \\cr bP_{21,1} \u0026 ... \u0026 bP_{21,10} } \\right]  $$'; %valid\r\ntext(48,6,str,'Interpreter','latex','Fontsize',18);\r\n\r\nend %NNConv_flow\r\n%}\r\n","test_suite":"%%\r\nImgsetstr= ... %5x3 digits 1:9 0\r\n ['010111111101111100111111111111';\r\n  '010001001101100100001101101101';\r\n  '010111111111111111001111111101';\r\n  '010100001001001101001101001101';\r\n  '010111111001111111001111001111'];\r\nImgsetv=Imgsetstr-'0';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\nnClasses=10;\r\nEPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nKsetstr= ... %3x3 kernel mask (will be scaled/offset)\r\n ['000000010010010000'; %Centered corners and vert/horiz\r\n  '011110011110010111'; %Kernels are identifying Features\r\n  '010010000000010000'];\r\n\r\nKsetv=Ksetstr-'0';\r\nKh=size(Ksetv,1);\r\nnK=size(Ksetv,2)/Kh; %Number of Kernels\r\nKset=reshape(Ksetv,Kh,Kh,nK);\r\n%Kernel needs normalization either scale or offset; Two large scale slows convergence or possible fail\r\nKsetr90=rot90(Kset(:,:,:),2)/3; % Rotate and normalize 3, each kernel sum is 3 Valid  2-Fails\r\n%Ksetr90=rot90(Kset(:,:,:),2)-.5; % Rotate and offset -0.5  Valid \r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\n%Stability sensitive to WP and WH values; rand start needs offset and normalization\r\n% X(7,5,nX) XC(5,3,nK) (XCY(1,91) WH(91,21) WP(21,10)\r\nztic=tic;\r\nfor ztry=1:5 %Allow five processing attempts to get a working solution\r\nWH=[(rand(90,20)-.5)/sqrt(90+20) zeros(90,1)]; % 90=nK*15, 20 is arbitrary at 2*nCases WH(91,21)  Valid\r\nWH=[WH; zeros(1,20) 1]; % offset row, Start with zero bias\r\n\r\nWP=(rand(21,10)-.5)/sqrt(21+10);  % 10 output states  Valid\r\n\r\n[WP,WH]=ConvNN_Process(XImgset,Ksetr90,WH,WP,EPY);\r\nfprintf('Process Time: %.3f sec\\n\\n',toc(ztic));\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),Ksetr90(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 PY2]\r\n  [~,pcase]=max(PY,[],2);\r\n  [~,pexp]=max(EPY,[],2);\r\n  \r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  \r\n  if isequal(pcase,pexp),break;end\r\n  \r\nend % ztry  Allowed 5 trials as rand may not always converge\r\n  \r\nvalid=isequal(pcase,pexp);\r\nassert(valid)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":3097,"edited_at":"2023-08-30T05:22:25.000Z","deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-08-30T04:01:42.000Z","updated_at":"2023-08-30T05:22:28.000Z","published_at":"2023-08-30T05:22:28.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. A fun extension is to add LED variants and see if trained WH/WP give expected result.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"524\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"875\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe matlab Latex code for making the CNN Processing chart included in template.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc 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Net: Convolutional NN Matrices Determination for LED Digit images; Variant Images Scored","description":"This challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. Sets of variants will be tested to show success beyond the training set. (Scale, Offset, Noise, zeroed node(s), intra-shifts). \r\nResults of scaling/Offset/Noise indicate additional Training sets required with Offset and Scale. See Test Suite 1 Figure. \r\nWould training images with Noise improve performance?\r\nTest sets 2 thru 5 show various Pixelations of numbers and the Neural Net success rate. Just fun to look at the data.\r\nAppears more training sets required and possibly more nodes to have high success. One translate not good.\r\n[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\r\n \r\nThe matlab Latex code for making the CNN Processing chart included in template.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 781.5px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 390.75px; transform-origin: 407px 390.75px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. Sets of variants will be tested to show success beyond the training set. (Scale, Offset, Noise, zeroed node(s), intra-shifts). \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 376.5px 8px; transform-origin: 376.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eResults of scaling/Offset/Noise indicate additional Training sets required with Offset and Scale. See Test Suite 1 Figure. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 176.5px 8px; transform-origin: 176.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWould training images with Noise improve performance?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 363px 8px; transform-origin: 363px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTest sets 2 thru 5 show various Pixelations of numbers and the Neural Net success rate. Just fun to look at the data.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 342px 8px; transform-origin: 342px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAppears more training sets required and possibly more nodes to have high success. One translate not good.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 162.5px 8px; transform-origin: 162.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv 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data-image-state=\"image-loaded\" width=\"875\" height=\"524\"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 257px 8px; transform-origin: 257px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe matlab Latex code for making the CNN Processing chart included in template.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [WP,WH]=ConvNN_Process(XImg,K,WH,WP,EPY)\r\n %nX=size(XImg,3); %Number training images\r\n %nK=size(K,3); % Number kernels\r\n %XC=zeros(5,3,nK); %Pre-alloc for speed\r\n \r\n for epoch=1:1000 % Number of cycles to evolve WH and WP\r\n  dWH=0*WH;\r\n  dWP=0*WP;\r\n  for iCase=1:nX  %Cycle thru all Images while accumulating dWH and dWP\r\n %Forward Pass  X(7,5,nX)-Ximg,Conv-XC(5,3,nK),ReLU-XCY3(5,3,nK),XCY(1,nK*15+1)(1,91)\r\n % XCYV*WH-H(1,21), ReLU(H)-HY(1,21), HY*WP-P(1,10), Softmax(P)-PY\r\n   for k=1:nK\r\n    %XC(:,:,k)=(conv2(XImg(:,:,iCase),K(:,:,k),'valid')); %Use rot90 Kernel to make output align\r\n   end\r\n\r\n   %XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive; safer to leave in for K offset case\r\n   %XCY=[XCY3(:)' 1]; % 1,nK*15+1  (1,91)  add a 1 for offset term\r\n \r\n   %[dWPi,dWHi]=Neural_ReLU_Back_Propagation(XCY,WH,WP,EPY(iCase,:));\r\n \r\n %Accumulate across all sample cases\r\n   %dWP=dWP+dWPi;\r\n   %dWH=dWH+dWHi;\r\n \r\n  end % iCase\r\n\r\n  %WP=WP+dWP/nX; % dWP/nX  Valid\r\n  %WH=WH+dWH/nX; % Usage /nX^2 requires 10K epochs for \u003e.8 PYs\r\n\r\n end % epoch\r\nend %ConvNN_Process\r\n\r\nfunction [dWP,dWH]=Neural_ReLU_Back_Propagation(X,WH,WP,EPY)\r\n% X will be single case [X1 X2 ... XN 1]\r\n  LR=1; % Learning Rate\r\n  \r\n  H=X*WH;\r\n  HY=max(0,H); % ReLU\r\n  \r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 PY2 ... PYM]\r\n  \r\n  %Back Propagation Calculations\r\n  ErrPY=EPY-PY;\r\n  \r\n  dPY=PY.*(1-PY).*ErrPY;\r\n  dWP=LR*HY'.*dPY;\r\n  \r\n  dHY=HY.*(1-HY).*sum(WP.*dPY,2)';\r\n  dWH=LR*X'.*dHY;\r\nend % Neural_ReLU_Back_Propagation","test_suite":"%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 1:9 0\r\n ['010111111101111100111111111111';\r\n  '010001001101100100001101101101';\r\n  '010111111111111111001111111101';\r\n  '010100001001001101001101001101';\r\n  '010111111001111111001111001111'];\r\nImgsetv=Imgsetstr-'0';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\nnClasses=10;\r\nEPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nKsetstr= ... %3x3 kernel mask (will be scaled/offset)\r\n ['000000010010010000'; %Centered corners and vert/horiz\r\n  '011110011110010111'; %Kernels are identifying Features\r\n  '010010000000010000'];\r\n\r\nKsetv=Ksetstr-'0';\r\nKh=size(Ksetv,1);\r\nnK=size(Ksetv,2)/Kh; %Number of Kernels\r\nKset=reshape(Ksetv,Kh,Kh,nK);\r\n%Kernel needs normalization either scale or offset; Two large scale slows convergence or possible fail\r\nKsetr90=rot90(Kset(:,:,:),2)/3; % Rotate and normalize 3, each kernel sum is 3 Valid  2-Fails\r\nK=Ksetr90;\r\n%Ksetr90=rot90(Kset(:,:,:),2)-.5; % Rotate and offset -0.5  Valid \r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\n%Stability sensitive to WP and WH values; rand start needs offset and normalization\r\n% X(7,5,nX) XC(5,3,nK) (XCY(1,91) WH(91,21) WP(21,10)\r\nztic=tic;\r\nfor ztry=1:5 %Allow five processing attempts to get a working solution\r\nWH=[(rand(90,20)-.5)/sqrt(90+20) zeros(90,1)]; % 90=nK*15, 20 is arbitrary at 2*nCases WH(91,21)  Valid\r\nWH=[WH; zeros(1,20) 1]; % offset row, Start with zero bias\r\n\r\nWP=(rand(21,10)-.5)/sqrt(21+10);  % 10 output states  Valid\r\n\r\n[WP,WH]=ConvNN_Process(XImgset,Ksetr90,WH,WP,EPY);\r\nfprintf('Process Time: %.3f sec\\n\\n',toc(ztic));\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),Ksetr90(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  [~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Ideal Input Training Cases\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  %fprintf('\\n\\n');\r\n  \r\n  %Scaled-50%\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  XN=XImgset/2; %Scale to 7x5 Image planes\r\n  XNS=XN; %figure variable\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XN(:,:,iCase),K(:,:,k),'valid'));\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,Xpcase]=max(PY,[],2);\r\n  [~,Xpexp]=max(EPY,[],2);\r\n  \r\n  fprintf('50%s Scale - NN Strong Scale Invariance, Worst is 8\\n',char(37));\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',Xpexp(i),Xpcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(Xpcase==Xpexp)/nX,'%');\r\n  \r\n  %Scaled-50% and Noise 60% added\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  XN=XImgset/2+.3*(rand(size(XImgset))-.5); %Scale and add Noise to 7x5 Image planes\r\n  XNSn=XN; %figure variable\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XN(:,:,iCase),K(:,:,k),'valid'));\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,Xpcase]=max(PY,[],2);\r\n  [~,Xpexp]=max(EPY,[],2);\r\n  \r\n  fprintf('50%s Scale and 60%s Noise added - Imperfect Results Expected\\n',char(37),'%');\r\n  %Note: double % is a special Cody sequence so using %s to write % character\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',Xpexp(i),Xpcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(Xpcase==Xpexp)/nX,'%');\r\n  \r\n\r\n  %Offset+50%\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  XN=XImgset-.5; %Offset to 7x5 Image planes\r\n  XNo=XN;\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XN(:,:,iCase),K(:,:,k),'valid'));\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,Xpcase]=max(PY,[],2);\r\n  [~,Xpexp]=max(EPY,[],2);\r\n  \r\n  fprintf('50%s Offset - NN Somewhat Strong Offset Invariance - Weak 1,3,8,9\\n',char(37));\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',Xpexp(i),Xpcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(Xpcase==Xpexp)/nX,'%');\r\n  \r\n  %Offset-50% Noise-60%\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  XN=XImgset-.5+.6*(rand(size(XImgset))-.5); %Offset to 7x5 Image planes\r\n  XNon=XN;\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XN(:,:,iCase),K(:,:,k),'valid'));\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,Xpcase]=max(PY,[],2);\r\n  [~,Xpexp]=max(EPY,[],2);\r\n  \r\n  fprintf('50%s Offset 60%s Noise - NN Mildly Strong Offset/Noise Invariance - Weak 1,3,8,9\\n',char(37),'%');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',Xpexp(i),Xpcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n\\n',100*nnz(Xpcase==Xpexp)/nX,'%');\r\n  \r\n\r\n  figure(1); imagesc([reshape(XImgset,7,[]);reshape(XNS,7,[]);reshape(XNSn,7,50);reshape(XNo,7,[]);reshape(XNon,7,50)]);\r\n  xticks([]);yticks([]);axis equal;axis tight\r\n  \r\n  if isequal(pcase,pexp),break;end\r\n  \r\nend % ztry  Allowed 5 trials as rand may not always converge\r\n  \r\nvalid=isequal(pcase,pexp);\r\nassert(valid)\r\n\r\n%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 1 variants,3 variants\r\n ['100001010010000011110011111011';\r\n  '100001010110010011110001001001';\r\n  '100001010010010011010111011011';\r\n  '100001010010010011010001001001';\r\n  '100001111010010011010111111011'];\r\nImgsetv=Imgsetstr-'0';\r\npexp=[1 1 1 1 1 1 1 3 3 3]';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\n%nClasses=10;\r\n%EPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nnK=size(K,3); %Number of Kernels\r\n\r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\nfigure; imagesc(reshape(XImgset,7,[]));\r\nxticks([]);yticks([]);axis equal;axis tight\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),K(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  %[~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Morphed 1s and 3s; Need more training\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  fprintf('\\n\\n');\r\n\r\n\r\nassert(1)\r\n\r\n%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 2 variants,4 variants\r\n ['011011100111110001000101101001';\r\n  '001001010001001101101111101011';\r\n  '111111001010010111111001101111';\r\n  '100100010100100001001001111001';\r\n  '111110001111011001001001001001'];\r\nImgsetv=Imgsetstr-'0';\r\npexp=[2 2 2 2 2 4 4 4 4 4]';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\n%nClasses=10;\r\n%EPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nnK=size(K,3); %Number of Kernels\r\n\r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\nfigure; imagesc(reshape(XImgset,7,[]));\r\nxticks([]);yticks([]);axis equal;axis tight\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),K(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  %[~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Morphed 1s and 3s; Need more training\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  fprintf('\\n\\n');\r\n\r\n\r\nassert(1)\r\n\r\n%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 5,6,7,8 variants\r\n ['110110010111110100011111010010';\r\n  '100100100100100100001001101100';\r\n  '111111111111111110001001010010';\r\n  '001001001101101101001010101001';\r\n  '111011010111111110001100010010'];\r\nImgsetv=Imgsetstr-'0';\r\npexp=[5 5 5 6 6 6 7 7  8 5 ]';\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\n%nClasses=10;\r\n%EPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nnK=size(K,3); %Number of Kernels\r\n\r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\nfigure; imagesc(reshape(XImgset,7,[]));\r\nxticks([]);yticks([]);axis equal;axis tight\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),K(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  %[~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Morphed 1s and 3s; Need more training\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  fprintf('\\n\\n');\r\n\r\n\r\nassert(1)\r\n\r\n%%\r\nglobal WH WP K\r\nImgsetstr= ... %5x3 digits 7,9,0 variants\r\n ['110111111011111010010111101101';\r\n  '010101101101111101000001101100';\r\n  '010111111111111101010011111111';\r\n  '010001001001111101000001101001';\r\n  '010011111001111010010001111001'];\r\nImgsetv=Imgsetstr-'0';\r\npexp=[1 9 9 9 10 10 1 7  8 4 ]'; %Shape/Missing LEDs\r\n\r\nnX=size(Imgsetv,2)/3;\r\nXImgset=zeros(7,5,nX); % Images Zero Ring for conv2(I,K,'valid') where K is 3x3\r\n\r\n%nClasses=10;\r\n%EPY=eye(nClasses); % One case for each digit from 1 to 9 and then 0 which is class type 10\r\n%One input for each Class\r\n\r\nnK=size(K,3); %Number of Kernels\r\n\r\nIh=size(Imgsetv,1);\r\nImgset53=reshape(Imgsetv,Ih,3,size(Imgsetv,2)/3);\r\nfor k=1:size(Imgset53,3)\r\n XImgset(2:end-1,2:end-1,k)=Imgset53(:,:,k);\r\nend\r\n\r\nfigure; imagesc(reshape(XImgset,7,[]));\r\nxticks([]);yticks([]);axis equal;axis tight\r\n\r\n  X=zeros(nX,91); %Forward process all images in one sequence\r\n  for iCase=1:nX\r\n   for k=1:nK\r\n    XC(:,:,k)=(conv2(XImgset(:,:,iCase),K(:,:,k),'valid')); %Need to rot90 Kernel to make output align\r\n   end\r\n   XCY3=max(0,XC); %ReLU  Not needed with all K coeff positive\r\n   XCY=[XCY3(:)' 1]; % 1,nK*15  1,91  add a 1 for offset term\r\n   X(iCase,:)=XCY; \r\n  end\r\n\r\n  H=X*WH; % Process all 10 cases\r\n  HY=max(0,H);\r\n  P=HY*WP ; %\r\n  PY=exp(P)./sum(exp(P),2); %Softmax [PY1 ... PY10]\r\n  [~,pcase]=max(PY,[],2);\r\n  %[~,pexp]=max(EPY,[],2);\r\n  \r\n  fprintf('Morphed 1s and 3s; Need more training\\n');\r\n  for i=1:nX\r\n   fprintf('Exp:%2i Pred:%2i   ',pexp(i),pcase(i));\r\n   fprintf('.%04i  ',round(10000*PY(i,:)));fprintf('\\n');\r\n  end\r\n  fprintf('Accuracy %.0f%s\\n',100*nnz(pcase==pexp)/nX,'%');\r\n  fprintf('\\n\\n');\r\n\r\n\r\nassert(1)\r\n\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":3097,"edited_at":"2023-08-31T19:50:57.000Z","deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-08-31T13:45:50.000Z","updated_at":"2023-08-31T19:50:57.000Z","published_at":"2023-08-31T19:50:57.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis challenge is to return final WH and WP matrices, given XImgset, WH, WP, K, EPY using convolution(Ximg,K), ReLU on the hidden layer and Softmax on the output layer. Training images are LED binary matrices of digits 1:9 and 0. Sets of variants will be tested to show success beyond the training set. (Scale, Offset, Noise, zeroed node(s), intra-shifts). \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eResults of scaling/Offset/Noise indicate additional Training sets required with Offset and Scale. See Test Suite 1 Figure. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould training images with Noise improve performance?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTest sets 2 thru 5 show various Pixelations of numbers and the Neural Net success rate. Just fun to look at the data.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAppears more training sets required and possibly more nodes to have high success. One translate not good.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[WP,WH]=ConvNN_Process(XImgset,K,WH,WP,EPY)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"524\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"875\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe matlab Latex code for making the CNN Processing chart included in 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to multiply?","description":"Imagine you are in 3012 Anno Domini, when everyone must learn how to multiply,\r\nand competing for the highly prestigious post of,\r\nChief Comptroller of Ylpitlum Corporation.\r\nYou are being tested via MATLAB Cody for multiplication of two positive integers X and Y,\r\nboth are fortunately in decimal system, and only a few dozen digits or less,\r\nand delivered as ASCII strings.\r\nPlease output the result Z in similar style.\r\nPlease adopt a general strategy, as X and Y may be changed later.\r\nPlease rename the function Z = ylpitlum(X,Y).\r\nFunction Template:\r\nfunction Z = ylpitlum(X,Y)\r\n   %  098765432109876543210987654321098765432109876543210987654321\r\n   X='170000000000000000000000000000';\r\n   Y='190000000000000000000000000000';\r\n   Z='32300000000000000000000000000000000000000000000000000000000';\r\nend","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 346.933px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 173.467px; transform-origin: 407px 173.467px; vertical-align: baseline; \"\u003e\u003cul style=\"block-size: 204.333px; counter-reset: list-item 0; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 102.167px; transform-origin: 391px 102.167px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 254.5px 8px; transform-origin: 254.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eImagine you are in 3012 Anno Domini, when everyone must learn how to multiply,\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 151.5px 8px; transform-origin: 151.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eand competing for the highly prestigious post of,\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 131px 8px; transform-origin: 131px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eChief Comptroller of Ylpitlum Corporation.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 76.5px 8px; transform-origin: 76.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou are being tested via\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eMATLAB Cody\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 154.5px 8px; transform-origin: 154.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e for multiplication of two positive integers X and Y,\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 233.5px 8px; transform-origin: 233.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eboth are fortunately in decimal system, and only a few dozen digits or less,\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 96.5px 8px; transform-origin: 96.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eand delivered as ASCII strings.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 129px 8px; transform-origin: 129px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePlease output the result Z in similar style.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 210.5px 8px; transform-origin: 210.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePlease adopt a general strategy, as X and Y may be changed later.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 141.5px 8px; transform-origin: 141.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePlease rename the function Z = ylpitlum(X,Y).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 60px 8px; transform-origin: 60px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFunction Template:\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 122.6px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 61.3px; transform-origin: 404px 61.3px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"border-block-end-color: rgb(14, 0, 255); border-block-start-color: rgb(14, 0, 255); border-bottom-color: rgb(14, 0, 255); border-inline-end-color: rgb(14, 0, 255); border-inline-start-color: rgb(14, 0, 255); border-left-color: rgb(14, 0, 255); border-right-color: rgb(14, 0, 255); border-top-color: rgb(14, 0, 255); caret-color: rgb(14, 0, 255); color: rgb(14, 0, 255); column-rule-color: rgb(14, 0, 255); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(14, 0, 255); perspective-origin: 36px 8.5px; text-decoration: none; text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); transform-origin: 36px 8.5px; \"\u003efunction \u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 68px 8.5px; transform-origin: 68px 8.5px; \"\u003eZ = ylpitlum(X,Y)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 264px 8.5px; tab-size: 4; transform-origin: 264px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003e   \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(2, 128, 9); border-block-start-color: rgb(2, 128, 9); border-bottom-color: rgb(2, 128, 9); border-inline-end-color: rgb(2, 128, 9); border-inline-start-color: rgb(2, 128, 9); border-left-color: rgb(2, 128, 9); border-right-color: rgb(2, 128, 9); border-top-color: rgb(2, 128, 9); caret-color: rgb(2, 128, 9); color: rgb(2, 128, 9); column-rule-color: rgb(2, 128, 9); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(2, 128, 9); perspective-origin: 252px 8.5px; text-decoration: none; text-decoration-color: rgb(2, 128, 9); text-emphasis-color: rgb(2, 128, 9); transform-origin: 252px 8.5px; \"\u003e%  098765432109876543210987654321098765432109876543210987654321\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 152px 8.5px; tab-size: 4; transform-origin: 152px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 20px 8.5px; transform-origin: 20px 8.5px; \"\u003e   X=\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 128px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 128px 8.5px; \"\u003e'170000000000000000000000000000'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 152px 8.5px; tab-size: 4; transform-origin: 152px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 20px 8.5px; transform-origin: 20px 8.5px; \"\u003e   Y=\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 128px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 128px 8.5px; \"\u003e'190000000000000000000000000000'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 268px 8.5px; tab-size: 4; transform-origin: 268px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 20px 8.5px; transform-origin: 20px 8.5px; \"\u003e   Z=\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 244px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 244px 8.5px; \"\u003e'32300000000000000000000000000000000000000000000000000000000'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 12px 8.5px; tab-size: 4; transform-origin: 12px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"border-block-end-color: rgb(14, 0, 255); border-block-start-color: rgb(14, 0, 255); border-bottom-color: rgb(14, 0, 255); border-inline-end-color: rgb(14, 0, 255); border-inline-start-color: rgb(14, 0, 255); border-left-color: rgb(14, 0, 255); border-right-color: rgb(14, 0, 255); border-top-color: rgb(14, 0, 255); caret-color: rgb(14, 0, 255); color: rgb(14, 0, 255); column-rule-color: rgb(14, 0, 255); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(14, 0, 255); text-decoration: none; text-decoration-color: rgb(14, 0, 255); text-emphasis-color: rgb(14, 0, 255); \"\u003eend\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Z = ylpitlum(X,Y)\r\n   %  098765432109876543210987654321098765432109876543210987654321\r\n   X='170000000000000000000000000000';\r\n   Y='190000000000000000000000000000';\r\n   Z='32300000000000000000000000000000000000000000000000000000000';\r\nend","test_suite":"%%\r\nX='170000000000000000000000000000';\r\nY='190000000000000000000000000000';\r\nZ='32300000000000000000000000000000000000000000000000000000000';\r\nassert(isequal(Z,ylpitlum(X,Y)))\r\n\r\n%%\r\nX='235711131719';\r\nY='232931374143475359';\r\nZ='54904517812220391149679812121';\r\nassert(isequal(Z,ylpitlum(X,Y)))\r\n\r\n%%\r\nX='7657534422342987897979879745232234';\r\nY='9878765654343431233130980808776767';\r\nZ='75646988048394475543709477144832189651639589891288011407029878707478';\r\nassert(isequal(Z,ylpitlum(X,Y)))\r\n\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":2,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":82,"test_suite_updated_at":"2021-11-28T17:15:31.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-04-03T06:24:52.000Z","updated_at":"2026-02-10T19:25:06.000Z","published_at":"2012-04-03T06:24:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eImagine you are in 3012 Anno Domini, when everyone must learn how to multiply,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand competing for the highly prestigious post of,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eChief Comptroller of Ylpitlum Corporation.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou are being tested via\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eMATLAB Cody\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e for multiplication of two positive integers X and Y,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eboth are fortunately in decimal system, and only a few dozen digits or less,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand delivered as ASCII strings.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlease output the result Z in similar style.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlease adopt a general strategy, as X and Y may be changed later.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlease rename the function Z = ylpitlum(X,Y).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFunction Template:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[function Z = ylpitlum(X,Y)\\n   %  098765432109876543210987654321098765432109876543210987654321\\n   X='170000000000000000000000000000';\\n   Y='190000000000000000000000000000';\\n   Z='32300000000000000000000000000000000000000000000000000000000';\\nend]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":52183,"title":"List the nth prime quartet prefix","description":"Prime numbers larger than 5 can end only in 1, 3, 7, or 9, but of course not all numbers ending in these four digits are prime. Let’s call a group of four prime numbers between  and  (with  an integer and ) a prime quartet. The first one is 11, 13, 17, and 19, and the second is 101, 103, 107, and 109. Therefore, the prefix (or the number excluding the last digit) of the first prime quartet is 1, and the prefix of the second prime quartet is 10.\r\nWrite a function that returns the th prime quartet prefix. \r\nOptional: Prove that the sequence of prime quartet prefixes is infinite. Just drop your proof in the comments below. ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 144px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 72px; transform-origin: 407.5px 72px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 42px; text-align: left; transform-origin: 384.5px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384.5px 7.66667px; transform-origin: 384.5px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePrime numbers larger than 5 can end only in 1, 3, 7, or 9, but of course not all numbers ending in these four digits are prime. Let’s call a group of four prime numbers between \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"10k\" style=\"width: 25px; height: 18px;\" width=\"25\" height=\"18\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 15.5583px 7.66667px; transform-origin: 15.5583px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"10(k+1)\" style=\"width: 61px; height: 18.5px;\" width=\"61\" height=\"18.5\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 18.6667px 7.66667px; transform-origin: 18.6667px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (with \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003ek\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 48.625px 7.66667px; transform-origin: 48.625px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e an integer and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"k \u003e= 1\" style=\"width: 36px; height: 18px;\" width=\"36\" height=\"18\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 10.1083px 7.66667px; transform-origin: 10.1083px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) a \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 41.2333px 7.66667px; transform-origin: 41.2333px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eprime quartet\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 30.7583px 7.66667px; transform-origin: 30.7583px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The first one is 11, 13, 17, and 19, and the second is 101, 103, 107, and 109. Therefore, the prefix (or the number excluding the last digit) of the first prime quartet is 1, and the prefix of the second prime quartet is 10.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 99.4333px 7.66667px; transform-origin: 99.4333px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that returns the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003en\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 71.95px 7.66667px; transform-origin: 71.95px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eth prime quartet prefix. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 355.5px 7.66667px; transform-origin: 355.5px 7.66667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOptional: Prove that the sequence of prime quartet prefixes is infinite. Just drop your proof in the comments below. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = PQPrefix(n)\r\n  y = f(n);\r\nend","test_suite":"%%\r\nn = 1;\r\ny_correct = 1;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 2;\r\ny_correct = 10;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 4;\r\ny_correct = 82;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 8;\r\ny_correct = 325;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 16;\r\ny_correct = 1804;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 32;\r\ny_correct = 7969;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 64;\r\ny_correct = 27604;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 128;\r\ny_correct = 66466;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 256;\r\ny_correct = 167056;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 512;\r\ny_correct = 454324;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 1024;\r\ny_correct = 1221643;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 2048;\r\ny_correct = 3229894;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 4096;\r\ny_correct = 8166751;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 8192;\r\ny_correct = 20302084;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn = 10001;\r\ny_correct = 26538121;\r\nassert(isequal(PQPrefix(n),y_correct))\r\n\r\n%%\r\nn1 = 3;\r\nyyy_correct = 3350308;\r\nassert(isequal(PQPrefix(PQPrefix(PQPrefix(n1))),yyy_correct))\r\n\r\n%%\r\nfiletext = fileread('PQPrefix.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp'); \r\nassert(~illegal)","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":46909,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":"2022-01-29T15:41:32.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2021-07-02T13:04:42.000Z","updated_at":"2025-11-29T23:51:09.000Z","published_at":"2021-07-02T13:11:31.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePrime numbers larger than 5 can end only in 1, 3, 7, or 9, but of course not all numbers ending in these four digits are prime. Let’s call a group of four prime numbers between \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"10k\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e10k\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"10(k+1)\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e10(k+1)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e (with \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"k\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ek\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e an integer and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"k \u0026gt;= 1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ek\\\\ge 1\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e) a \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eprime quartet\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. The first one is 11, 13, 17, and 19, and the second is 101, 103, 107, and 109. Therefore, the prefix (or the number excluding the last digit) of the first prime quartet is 1, and the prefix of the second prime quartet is 10.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that returns the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"n\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003eth prime quartet prefix. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOptional: Prove that the sequence of prime quartet prefixes is infinite. Just drop your proof in the comments below. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":44832,"title":"Generate Convolution Matrix of 2D Kernel with Different Convolution Shapes (Full, Same, Valid)","description":"In this problem the challenge is to build the Matrix Form equivalent of the function `conv2()` of MATLAB.\r\n\r\nThe function to be built will generate a sparse matrix `mK` which is the convolution matrix of the 2D Kernel 'mH' (Which is an input to the function).  \r\nThe input to the function is the 2D Kernel and dimensions of the image to apply the convolution upon and the shape of the convolution ('full', 'same', 'valid' as in 'conv2()').\r\n\r\nThe output sparse matrix should match the output of using 'conv2()' on the same image using the same convolution shape.\r\n\r\nFor instance:\r\n\r\n  CONVOLUTION_SHAPE_FULL  = 1;\r\n  CONVOLUTION_SHAPE_SAME  = 2;\r\n  CONVOLUTION_SHAPE_VALID = 3;\r\n  \r\n  numRowsImage = 100;\r\n  numColsImage = 80;\r\n  \r\n  numRowsKernel = 7;\r\n  numColsKernel = 5;\r\n  \r\n  mI = rand(numRowsImage, numColsImage);\r\n  mH = rand(numRowsKernel, numColsKernel);\r\n  \r\n  maxThr = 1e-9;\r\n  \r\n  \r\n  %% Full Convolution\r\n  \r\n  convShape       = CONVOLUTION_SHAPE_FULL;\r\n  \r\n  numRowsOut = numRowsImage + numRowsKernel - 1;\r\n  numColsOut = numColsImage + numColsKernel - 1;\r\n  \r\n  mORef   = conv2(mI, mH, 'full');\r\n  mK      = CreateImageConvMtx(mH, numRowsImage, numColsImage, convShape);\r\n  mO      = reshape(mK * mI(:), numRowsOut, numColsOut);\r\n  \r\n  mE = mO - mORef;\r\n  assert(max(abs(mE(:))) \u003c maxThr);\r\n\r\nThe test case will examine all 3 modes.\r\nTry to solve it once with very clear code (No vectorization tricks) and then optimize.\r\n\r\nA good way to build the output sparse function is using:\r\n\r\n  mK = sparse(vRows, vCols, vVals, numElementsOutputImage, numElementsInputImage);\r\n\r\nLook for the documentation of `sparse()` function for more details.","description_html":"\u003cp\u003eIn this problem the challenge is to build the Matrix Form equivalent of the function `conv2()` of MATLAB.\u003c/p\u003e\u003cp\u003eThe function to be built will generate a sparse matrix `mK` which is the convolution matrix of the 2D Kernel 'mH' (Which is an input to the function).  \r\nThe input to the function is the 2D Kernel and dimensions of the image to apply the convolution upon and the shape of the convolution ('full', 'same', 'valid' as in 'conv2()').\u003c/p\u003e\u003cp\u003eThe output sparse matrix should match the output of using 'conv2()' on the same image using the same convolution shape.\u003c/p\u003e\u003cp\u003eFor instance:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eCONVOLUTION_SHAPE_FULL  = 1;\r\nCONVOLUTION_SHAPE_SAME  = 2;\r\nCONVOLUTION_SHAPE_VALID = 3;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003enumRowsImage = 100;\r\nnumColsImage = 80;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003enumRowsKernel = 7;\r\nnumColsKernel = 5;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003emI = rand(numRowsImage, numColsImage);\r\nmH = rand(numRowsKernel, numColsKernel);\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003emaxThr = 1e-9;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003e%% Full Convolution\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003econvShape       = CONVOLUTION_SHAPE_FULL;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003enumRowsOut = numRowsImage + numRowsKernel - 1;\r\nnumColsOut = numColsImage + numColsKernel - 1;\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003emORef   = conv2(mI, mH, 'full');\r\nmK      = CreateImageConvMtx(mH, numRowsImage, numColsImage, convShape);\r\nmO      = reshape(mK * mI(:), numRowsOut, numColsOut);\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003emE = mO - mORef;\r\nassert(max(abs(mE(:))) \u0026lt; maxThr);\r\n\u003c/pre\u003e\u003cp\u003eThe test case will examine all 3 modes.\r\nTry to solve it once with very clear code (No vectorization tricks) and then optimize.\u003c/p\u003e\u003cp\u003eA good way to build the output sparse function is using:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003emK = sparse(vRows, vCols, vVals, numElementsOutputImage, numElementsInputImage);\r\n\u003c/pre\u003e\u003cp\u003eLook for the documentation of `sparse()` function for more details.\u003c/p\u003e","function_template":"function [ mK ] = CreateImageConvMtx( mH, numRows, numCols, convShape )\r\n%Generates a Convolution Matrix for the 2D Kernel (The Matrix mH) with\r\n%support for different convolution shapes (Full / Same / Valid).\r\n% Input:\r\n%   - mH                -   Input 2D Convolution Kernel.\r\n%                           Structure: Matrix.\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: (-inf, inf).\r\n%   - numRows           -   Number of Rows.\r\n%                           Number of rows in the output convolution\r\n%                           matrix.\r\n%                           Structure: Scalar.\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: {1, 2, 3, ...}.\r\n%   - numCols           -   Number of Columns.\r\n%                           Number of columns in the output convolution\r\n%                           matrix.\r\n%                           Structure: Scalar.\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: {1, 2, 3, ...}.\r\n%   - convShape         -   Convolution Shape.\r\n%                           The shape of the convolution which the output\r\n%                           convolution matrix should represent. The\r\n%                           options should match MATLAB's conv2() function\r\n%                           - Full / Same / Valid.\r\n%                           Structure: Scalar.\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: {1, 2, 3}.\r\n% Output:\r\n%   - mK                -   Convolution Matrix.\r\n%                           The output convolution matrix. Multiplying in\r\n%                           the column stack form on an image should be\r\n%                           equivalent to applying convolution on the\r\n%                           image.\r\n%                           Structure: Matrix (Sparse).\r\n%                           Type: 'Single' / 'Double'.\r\n%                           Range: (-inf, inf).\r\n% References:\r\n%   1.  MATLAB's 'convmtx2()' - https://www.mathworks.com/help/images/ref/convmtx2.html.\r\n% Remarks:\r\n%   1.  gf\r\n% TODO:\r\n%   1.  \r\n%   Release Notes:\r\n%   -   1.0.000     dd/mm/yyyy  firstName lastName\r\n%       *   First release version.\r\n% ----------------------------------------------------------------------------------------------- %\r\n\r\nCONVOLUTION_SHAPE_FULL  = 1;\r\nCONVOLUTION_SHAPE_SAME  = 2;\r\nCONVOLUTION_SHAPE_VALID = 3;\r\n\r\nswitch(convShape)\r\n    case(CONVOLUTION_SHAPE_FULL)\r\n        % Code for the 'full' case\r\n    case(CONVOLUTION_SHAPE_SAME)\r\n        % Code for the 'same' case\r\n    case(CONVOLUTION_SHAPE_VALID)\r\n        % Code for the 'valid' case\r\nend\r\n\r\n\r\nend\r\n\r\n","test_suite":"%% Testing\r\n\r\n\r\nCONVOLUTION_SHAPE_FULL  = 1;\r\nCONVOLUTION_SHAPE_SAME  = 2;\r\nCONVOLUTION_SHAPE_VALID = 3;\r\n\r\nmaxThr = 1e-9;\r\n\r\n\r\nfor numRowsImage = 28:32\r\n    for numColsImage = 28:32\r\n        \r\n        mI = rand(numRowsImage, numColsImage);\r\n        \r\n        for numRowsKernel = 3:7\r\n            for numColsKernel = 3:7\r\n                \r\n                mH = rand(numRowsKernel, numColsKernel);\r\n                \r\n                for convShape = 1:3\r\n                    \r\n                    switch(convShape)\r\n                        case(CONVOLUTION_SHAPE_FULL)\r\n                            numRowsOut = numRowsImage + numRowsKernel - 1;\r\n                            numColsOut = numColsImage + numColsKernel - 1;\r\n                            \r\n                            convShapeString = 'full';\r\n                        case(CONVOLUTION_SHAPE_SAME)\r\n                            numRowsOut = numRowsImage;\r\n                            numColsOut = numColsImage;\r\n                            \r\n                            convShapeString = 'same';\r\n                        case(CONVOLUTION_SHAPE_VALID)\r\n                            numRowsOut = numRowsImage - numRowsKernel + 1;\r\n                            numColsOut = numColsImage - numColsKernel + 1;\r\n                            \r\n                            convShapeString = 'valid';\r\n                    end\r\n                    \r\n                    mORef   = conv2(mI, mH, convShapeString);\r\n                    mK      = CreateImageConvMtx(mH, numRowsImage, numColsImage, convShape);\r\n                    mO      = reshape(mK * mI(:), numRowsOut, numColsOut);\r\n                    \r\n                    disp([' ']);\r\n                    disp(['Validating solution for the following parameters:']);\r\n                    disp(['Image Size - [', num2str(numRowsImage), ' x ', num2str(numColsImage), ']']);\r\n                    disp(['Kernel Size - [', num2str(numRowsKernel), ' x ', num2str(numColsKernel), ']']);\r\n                    disp(['Convolution Shape - ', convShapeString]);\r\n                    \r\n                    mE = mO - mORef;\r\n                    maxAbsDev = max(abs(mE(:)));\r\n                    if(maxAbsDev \u003e= maxThr)\r\n                        disp([' ']);\r\n                        disp(['Validation Failed']);\r\n                        disp([' ']);\r\n                    end\r\n                    assert(maxAbsDev \u003c maxThr);\r\n                    \r\n                end\r\n            end\r\n        end\r\n    end\r\nend\r\n            \r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":6204,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":"2019-01-15T23:13:37.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2019-01-15T21:20:18.000Z","updated_at":"2019-01-15T23:13:37.000Z","published_at":"2019-01-15T21:20:18.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this problem the challenge is to build the Matrix Form equivalent of the function `conv2()` of MATLAB.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe function to be built will generate a sparse matrix `mK` which is the convolution matrix of the 2D Kernel 'mH' (Which is an input to the function). The input to the function is the 2D Kernel and dimensions of the image to apply the convolution upon and the shape of the convolution ('full', 'same', 'valid' as in 'conv2()').\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output sparse matrix should match the output of using 'conv2()' on the same image using the same convolution shape.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor instance:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[CONVOLUTION_SHAPE_FULL  = 1;\\nCONVOLUTION_SHAPE_SAME  = 2;\\nCONVOLUTION_SHAPE_VALID = 3;\\n\\nnumRowsImage = 100;\\nnumColsImage = 80;\\n\\nnumRowsKernel = 7;\\nnumColsKernel = 5;\\n\\nmI = rand(numRowsImage, numColsImage);\\nmH = rand(numRowsKernel, numColsKernel);\\n\\nmaxThr = 1e-9;\\n\\n%%Full Convolution\\n\\nconvShape       = CONVOLUTION_SHAPE_FULL;\\n\\nnumRowsOut = numRowsImage + numRowsKernel - 1;\\nnumColsOut = numColsImage + numColsKernel - 1;\\n\\nmORef   = conv2(mI, mH, 'full');\\nmK      = CreateImageConvMtx(mH, numRowsImage, numColsImage, convShape);\\nmO      = reshape(mK * mI(:), numRowsOut, numColsOut);\\n\\nmE = mO - mORef;\\nassert(max(abs(mE(:))) \u003c maxThr);]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe test case will examine all 3 modes. Try to solve it once with very clear code (No vectorization tricks) and then optimize.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA good way to build the output sparse function is using:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[mK = sparse(vRows, vCols, vVals, numElementsOutputImage, numElementsInputImage);]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLook for the documentation of `sparse()` function for more details.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml 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