{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2026-04-06T14:01:22.000Z","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":"2026-04-06T00:00:00.000Z","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":58389,"title":"Minimum number of crossings in a complete graph","description":"This problem is related to problem 58384.\r\nA complete graph may be drawn in different ways, such that the number of line crossings differs between drawings.\r\nTo date, the question of how to draw the graph so as to minimize the number of crossings remains unsolved.\r\nNevertheless, an upper bound can be calculated for the number of crossings, based on the number of vertices in the graph.\r\nGiven the number of vertices, n, calculate the upper bound, b, for the minimum number of line crossings in the resulting complete graph.\r\nExample:\r\nn = 6;\r\nb = 3","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 242.898px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.989px 121.449px; transform-origin: 406.996px 121.449px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThis problem is related to \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/matlabcentral/cody/problems/58384-minimum-number-of-crossings-in-a-complete-bipartite-graph\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eproblem 58384\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://en.wikipedia.org/wiki/Complete_graph\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ecomplete graph\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e may be drawn in different ways, such that the number of line crossings differs between drawings.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eTo date, the question of how to draw the graph so as to minimize the number of crossings remains unsolved.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eNevertheless, an upper bound can be calculated for the number of crossings, based on the number of vertices in the graph.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42.017px; 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: 383.991px 21.0085px; text-align: left; transform-origin: 383.999px 21.0085px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven the number of vertices, n, calculate the upper bound, b, for the minimum number of line crossings in the resulting complete graph.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eExample:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 40.8807px; 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: 403.991px 20.4403px; transform-origin: 403.999px 20.4403px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4403px; 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: 0.909091px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.909091px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.909091px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.909091px; 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: 403.991px 10.2131px; transform-origin: 403.999px 10.2202px; 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: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003en = 6;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4403px; 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: 0.909091px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.909091px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.909091px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.909091px; 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: 403.991px 10.2131px; transform-origin: 403.999px 10.2202px; 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: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eb = 3\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function b = your_fcn_name(n)\r\n  b = n;\r\nend","test_suite":"%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext,'regexp')))\r\nassert(isempty(strfind(filetext,'assign')))\r\nassert(isempty(strfind(filetext,'eval')))\r\nassert(isempty(strfind(filetext,'echo')))\r\nassert(isempty(strfind(filetext,'!')))\r\n\r\n%%\r\nn = 6;\r\nassert(isequal(your_fcn_name(n),3))\r\n\r\n%%\r\nn = 12;\r\nassert(isequal(your_fcn_name(n),150))\r\n\r\n%%\r\nn = 35;\r\nassert(isequal(your_fcn_name(n),18496))\r\n\r\n%%\r\nn = 84;\r\nassert(isequal(your_fcn_name(n),706020))\r\n\r\n%%\r\nn = 99;\r\nassert(isequal(your_fcn_name(n),1382976))\r\n\r\n%%\r\nn = 200;\r\nassert(isequal(your_fcn_name(n),24012450))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":15521,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-06-02T18:43:47.000Z","updated_at":"2026-03-03T22:13:51.000Z","published_at":"2023-06-02T18:43:46.000Z","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 problem is related to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/cody/problems/58384-minimum-number-of-crossings-in-a-complete-bipartite-graph\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eproblem 58384\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\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\u003eA \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://en.wikipedia.org/wiki/Complete_graph\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ecomplete graph\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e may be drawn in different ways, such that the number of line crossings differs between drawings.\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\u003eTo date, the question of how to draw the graph so as to minimize the number of crossings remains unsolved.\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\u003eNevertheless, an upper bound can be calculated for the number of crossings, based on the number of vertices in the graph.\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 the number of vertices, n, calculate the upper bound, b, for the minimum number of line crossings in the resulting complete graph.\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\u003eExample:\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[n = 6;\\nb = 3]]\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":45505,"title":"Square root","description":"Given x (a matrix), give back another matrix, where all the elements are the square roots of x's elements.","description_html":"\u003cp\u003eGiven x (a matrix), give back another matrix, where all the elements are the square roots of x's elements.\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [4 9;16 25];\r\ny_correct = [2 3;4 5];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [9 4;25 16];\r\ny_correct = [3 2;5 4];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1 1;1 1];\r\ny_correct = [1 1;1 1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":13,"comments_count":0,"created_by":406787,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2610,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-05-08T12:23:10.000Z","updated_at":"2026-04-15T14:41:49.000Z","published_at":"2020-05-08T12:23:10.000Z","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\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"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\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 x (a matrix), give back another matrix, where all the elements are the square roots of x's elements.\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":2,"title":"Make the vector [1 2 3 4 5 6 7 8 9 10]","description":"In MATLAB, you create a vector by enclosing the elements in square brackets like so:\r\n\r\n x = [1 2 3 4]\r\n\r\nCommas are optional, so you can also type\r\n\r\n x = [1, 2, 3, 4]\r\n\r\nCreate the vector\r\n\r\n x = [1 2 3 4 5 6 7 8 9 10]\r\n\r\nThere's a faster way to do it using MATLAB's \u003chttp://www.mathworks.com/help/techdoc/ref/colon.html colon notation\u003e.","description_html":"\u003cp\u003eIn MATLAB, you create a vector by enclosing the elements in square brackets like so:\u003c/p\u003e\u003cpre\u003e x = [1 2 3 4]\u003c/pre\u003e\u003cp\u003eCommas are optional, so you can also type\u003c/p\u003e\u003cpre\u003e x = [1, 2, 3, 4]\u003c/pre\u003e\u003cp\u003eCreate the vector\u003c/p\u003e\u003cpre\u003e x = [1 2 3 4 5 6 7 8 9 10]\u003c/pre\u003e\u003cp\u003eThere's a faster way to do it using MATLAB's \u003ca href = \"http://www.mathworks.com/help/techdoc/ref/colon.html\"\u003ecolon notation\u003c/a\u003e.\u003c/p\u003e","function_template":"function x = oneToTen\r\n  x = 0;\r\nend","test_suite":"%%\r\nx_correct = [1 2 3 4 5 6 7 8 9 10];\r\nassert(isequal(oneToTen,x_correct))","published":true,"deleted":false,"likes_count":224,"comments_count":56,"created_by":1,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":52952,"test_suite_updated_at":"2012-01-18T01:00:17.000Z","rescore_all_solutions":false,"group_id":2,"created_at":"2012-01-18T01:00:17.000Z","updated_at":"2026-04-15T11:20:05.000Z","published_at":"2012-01-18T01:00:17.000Z","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 MATLAB, you create a vector by enclosing the elements in square brackets like so:\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 = [1 2 3 4]]]\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\u003eCommas are optional, so you can also type\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 = [1, 2, 3, 4]]]\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\u003eCreate the vector\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 = [1 2 3 4 5 6 7 8 9 10]]]\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\u003eThere's a faster way to do it using MATLAB's\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://www.mathworks.com/help/techdoc/ref/colon.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ecolon notation\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\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":45155,"title":" calculate the length of matrix","description":"input 1 array, calculate the length","description_html":"\u003cp\u003einput 1 array, calculate the length\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1 2 3 4 5];\r\ny_correct = 5;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":11,"comments_count":1,"created_by":343758,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2503,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2019-10-07T17:31:43.000Z","updated_at":"2026-04-14T05:31:36.000Z","published_at":"2019-10-07T17:31:43.000Z","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\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"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\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\u003einput 1 array, calculate the length\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":1,"title":"Times 2 - START HERE","description":"Try out this test problem first.\r\n\r\nGiven the variable x as your input, multiply it by two and put the result in y.\r\n\r\nExamples:\r\n\r\n Input  x = 2\r\n Output y is 4\r\n\r\n Input  x = 17\r\n Output y is 34\r\n","description_html":"\u003cp\u003eTry out this test problem first.\u003c/p\u003e\u003cp\u003eGiven the variable x as your input, multiply it by two and put the result in y.\u003c/p\u003e\u003cp\u003eExamples:\u003c/p\u003e\u003cpre\u003e Input  x = 2\r\n Output y is 4\u003c/pre\u003e\u003cpre\u003e Input  x = 17\r\n Output y is 34\u003c/pre\u003e","function_template":"function y = times2(x) % Do not edit this line.\r\n\r\n  % Modify the line below so that the output y is twice the incoming value x\r\n\r\n  y = x;\r\n\r\n  % After you modify the code, press the \"Submit\" button, and you're on your way.\r\n\r\nend % Do not edit this line.","test_suite":"%%\r\nassert(isequal(times2(1),2));\r\n\r\n%%\r\nassert(isequal(times2(11),22));\r\n\r\n%%\r\nassert(isequal(times2(-3),-6));\r\n\r\n%%\r\nassert(isequal(times2(29),58));","published":true,"deleted":false,"likes_count":2291,"comments_count":147,"created_by":1,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":114561,"test_suite_updated_at":"2012-01-25T22:41:49.000Z","rescore_all_solutions":false,"group_id":2,"created_at":"2012-01-18T01:00:16.000Z","updated_at":"2026-04-15T17:07:06.000Z","published_at":"2012-01-18T01:00:16.000Z","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\u003eTry out this test problem first.\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\u003eGiven the variable x as your input, multiply it by two and put the result in y.\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\u003eExamples:\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[ Input  x = 2\\n Output y is 4\\n\\n Input  x = 17\\n Output y is 34]]\u003e\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":45161,"title":"Converts numbers into characters","description":"Converts numbers into characters","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 107px 8px; transform-origin: 107px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConverts numbers into characters\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n~y=x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = '1';\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":9,"comments_count":1,"created_by":343758,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2063,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2019-10-07T17:45:44.000Z","updated_at":"2026-04-15T03:14:51.000Z","published_at":"2019-10-07T17:45:44.000Z","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\u003eConverts numbers into characters\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":1339,"title":"Travelling Salesman Problem (TSP)","description":"Find a short way through given points. This is the travelling salesman problem. But the solution should be a fast and small function.\r\nhttp://en.wikipedia.org/wiki/Travelling_salesman_problem\r\nHave fun!","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: 102px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 51px; transform-origin: 407px 51px; 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=\"\"\u003eFind a short way through given points. This is the travelling salesman problem. But the solution should be a fast and small function.\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\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ehttp://en.wikipedia.org/wiki/Travelling_salesman_problem\u003c/span\u003e\u003c/span\u003e\u003c/a\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: 30.5px 8px; transform-origin: 30.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eHave fun!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = TSP(x)\r\n  y = x;\r\nend","test_suite":"%% Test 1\r\nx = [8.2 -6.9 3.2 -9.5 15.5 0.3 -4.9 7.6 4.5 -7.1 6.5 -7.5 5.6 -0.5] + i*[-4.4 3.8 7.7 -8 -1.9 16.5 2.3 6.8 6.6 -1.6 -1.2 5.5 -9.3 8.9];\r\ntic;\r\ny = TSP(x);\r\nT1 = 1e4*toc;\r\nL1 = sum(abs(diff(y)));\r\n%S = calculateSize('tsp.m')\r\nassert(isequal(y,sort(x)))\r\n\r\n%% Test 2\r\nx = 10*sin(primes(200))+10i*cos(primes(200));\r\ntic;\r\ny = TSP(x);\r\nT2 = 1e6*toc;\r\nL2 = sum(abs(diff(y)));\r\nassert(isequal(y,sort(x)))\r\n\r\n%% Test 3\r\nx = [75.5 5.43 94.73 3.89 .37 42.38 -8.5 36.72 .54 .02 83.27 47];\r\ntic;\r\ny = TSP(x(randperm(12)));\r\nT3 = 1e5*toc;\r\nL3 = sum(abs(diff(y)));\r\nassert(isequal(y,sort(x)))\r\n\r\n%assignin('caller','score',round(S +T1+L1 +T2+L2 +T3+L3));","published":true,"deleted":false,"likes_count":3,"comments_count":10,"created_by":3105,"edited_by":223089,"edited_at":"2022-09-15T06:05:23.000Z","deleted_by":null,"deleted_at":null,"solvers_count":139,"test_suite_updated_at":"2022-09-15T06:05:24.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-03-10T18:58:10.000Z","updated_at":"2026-03-30T17:25:01.000Z","published_at":"2013-03-10T19:04:41.000Z","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\u003eFind a short way through given points. This is the travelling salesman problem. But the solution should be a fast and small function.\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:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttp://en.wikipedia.org/wiki/Travelling_salesman_problem\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\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\u003eHave fun!\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":1702,"title":"Maximum value in a matrix","description":"Find the maximum value in the given matrix.\r\n\r\nFor example, if \r\n\r\n A = [1 2 3; 4 7 8; 0 9 1];\r\n\r\nthen the answer is 9.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20px; 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: normal; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"display: block; min-width: 0px; padding-top: 0px; transform-origin: 332px 56px; vertical-align: baseline; perspective-origin: 332px 56px; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind the maximum value in the given matrix.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example, if\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-bottom: 10px; margin-left: 3px; margin-right: 3px; margin-top: 10px; transform-origin: 329px 10px; perspective-origin: 329px 10px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; 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-top-left-radius: 0px; border-top-right-radius: 0px; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-height: 18px; padding-left: 4px; white-space: nowrap; \"\u003e\u003cspan style=\"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-right: 45px; min-height: 0px; padding-left: 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; perspective-origin: 0px 0px; margin-right: 45px; \"\u003e\u003cspan style=\"margin-right: 0px; \"\u003e A = [1 2 3; 4 7 8; 0 9 1];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 10px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ethen the answer is 9.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1 2 3; 4 5 6; 7 8 9];\r\ny_correct = 9;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = -10:0;\r\ny_correct = 0;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 17;\r\ny_correct = 17;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = magic(6);\r\ny_correct = 36;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [5 23 6 2 9 0 -1]';\r\ny_correct = 23;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":84,"comments_count":25,"created_by":6728,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17796,"test_suite_updated_at":"2013-07-10T18:41:46.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-07-09T04:08:24.000Z","updated_at":"2026-04-15T11:10:44.000Z","published_at":"2013-07-09T04:08:24.000Z","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\u003eFind the maximum value in the given matrix.\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, if\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[ A = [1 2 3; 4 7 8; 0 9 1];]]\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\u003ethen the answer is 9.\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":475,"title":"Is this group simply connected?","description":"Given connectivity information about a graph, your job is to figure out if the graph is fully connected. You are given a list of vertex pairs that specify undirected connectivity (edges) among vertices. Vertex labels are always positive integers.\r\n\r\nExample 1:\r\n \r\n Input  node_pairs = [ 8 9\r\n                       8 3 ]\r\n Output tf is true\r\n                       \r\nThe three nodes of this graph are fully connected, since this graph could be drawn like so:\r\n\r\n 3--8--9\r\n\r\nExample 2:\r\n\r\n Input  node_pairs = [ 1 2 \r\n                       2 3\r\n                       1 4\r\n                       3 4\r\n                       5 6 ]\r\n Output tf is false\r\n\r\nThis graph could be drawn like so:\r\n\r\n 1--2  5--6\r\n |  |\r\n 4--3\r\n\r\nThere are two distinct subgraphs.","description_html":"\u003cp\u003eGiven connectivity information about a graph, your job is to figure out if the graph is fully connected. You are given a list of vertex pairs that specify undirected connectivity (edges) among vertices. Vertex labels are always positive integers.\u003c/p\u003e\u003cp\u003eExample 1:\u003c/p\u003e\u003cpre\u003e Input  node_pairs = [ 8 9\r\n                       8 3 ]\r\n Output tf is true\u003c/pre\u003e\u003cp\u003eThe three nodes of this graph are fully connected, since this graph could be drawn like so:\u003c/p\u003e\u003cpre\u003e 3--8--9\u003c/pre\u003e\u003cp\u003eExample 2:\u003c/p\u003e\u003cpre\u003e Input  node_pairs = [ 1 2 \r\n                       2 3\r\n                       1 4\r\n                       3 4\r\n                       5 6 ]\r\n Output tf is false\u003c/pre\u003e\u003cp\u003eThis graph could be drawn like so:\u003c/p\u003e\u003cpre\u003e 1--2  5--6\r\n |  |\r\n 4--3\u003c/pre\u003e\u003cp\u003eThere are two distinct subgraphs.\u003c/p\u003e","function_template":"function tf = isConnected(node_pairs)\r\n  tf = true;\r\nend","test_suite":"%%\r\n\r\nnode_pairs = [8 9; 8 3];\r\ntf = true;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n%%\r\n\r\nnode_pairs = [ 1 2;\r\n               2 3;\r\n               1 4;\r\n               3 4;\r\n               5 6 ];\r\ntf = false;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n%%\r\n\r\nnode_pairs = [ 1 2;\r\n               2 3;\r\n               1 4;\r\n               3 4;\r\n               5 6;\r\n               6 2 ];\r\ntf = true;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n%%\r\n\r\nnode_pairs = [ 1 2; 2 100];\r\ntf = true;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n\r\n%%\r\n\r\nnode_pairs = [ 1 2; 50 100];\r\ntf = false;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n%%\r\n\r\nnode_pairs = [ 4 17 ];\r\ntf = true;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":2,"created_by":7,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":36,"test_suite_updated_at":"2012-03-09T22:15:16.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-03-09T22:05:26.000Z","updated_at":"2026-03-03T23:05:27.000Z","published_at":"2012-03-12T16:23:04.000Z","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 connectivity information about a graph, your job is to figure out if the graph is fully connected. You are given a list of vertex pairs that specify undirected connectivity (edges) among vertices. Vertex labels are always positive integers.\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 1:\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[ Input  node_pairs = [ 8 9\\n                       8 3 ]\\n Output tf is true]]\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 three nodes of this graph are fully connected, since this graph could be drawn like so:\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[ 3--8--9]]\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 2:\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[ Input  node_pairs = [ 1 2 \\n                       2 3\\n                       1 4\\n                       3 4\\n                       5 6 ]\\n Output tf is false]]\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\u003eThis graph could be drawn like so:\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--2  5--6\\n |  |\\n 4--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\u003eThere are two distinct subgraphs.\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":52799,"title":"Plotting Practice","description":"Plot cos(x) vs x as shown in the figure below. Include the appropriate title, x-label, and y-label. Note, it is case sensitive. Make sure the colors of the axes, markers, and lines are correct. The markers should be square with magenta edges and a cyan face. The plot line should be dashed and red. The axes background should be yellow. The marker size should be 5.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 751.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 375.833px; transform-origin: 406.5px 375.833px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 383.5px 375.833px; text-align: left; transform-origin: 383.5px 375.833px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ePlot cos(x) vs x as shown in the figure below. Include the appropriate title, x-label, and y-label. Note, it is case sensitive. Make sure the colors of the axes, markers, and lines are correct. The markers should be square with magenta edges and a cyan face. The plot line should be dashed and red. The axes background should be yellow. The marker size should be 5.\u003c/span\u003e\u003c/span\u003e\u003cimg class=\"imageNode\" width=\"878\" height=\"683\" style=\"vertical-align: baseline;width: 878px;height: 683px\" 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\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n  figure\r\n\r\n  % Do not edit below here\r\n  h = gca;\r\n  y = {h.Title.String;h.XLabel.String;h.YLabel.String;h.Color;h.Children.YData;h.Children.XData;h.Children.Color;h.Children.MarkerFaceColor';h.Children.MarkerEdgeColor;h.Children.MarkerSize};\r\nend","test_suite":"%%\r\nx = 1:100;\r\nfigure\r\nplot(x,cos(x),'sr--','MarkerFaceColor','c','MarkerEdgeColor','m','MarkerSize',5);\r\nxlabel('Time (s)')\r\nylabel('Amplitude (mV)')\r\ntitle('Cosine Signal')\r\nset(gca,'color','y')\r\nh=gca;\r\ny_correct = {h.Title.String;h.XLabel.String;h.YLabel.String;h.Color;h.Children.YData;h.Children.XData;h.Children.Color;h.Children.MarkerFaceColor';h.Children.MarkerEdgeColor;h.Children.MarkerSize}\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":1375684,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":630,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-09-26T03:55:24.000Z","updated_at":"2026-04-11T16:25:21.000Z","published_at":"2021-09-26T03:58:09.000Z","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\u003ePlot cos(x) vs x as shown in the figure below. Include the appropriate title, x-label, and y-label. Note, it is case sensitive. Make sure the colors of the axes, markers, and lines are correct. The markers should be square with magenta edges and a cyan face. The plot line should be dashed and red. The axes background should be yellow. 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A the inverse of B?","description":"Given a matrix A and a matrix B, is A the inverse of B?\r\n\r\n  \r\n\r\n  \u003e\u003eA=[2,4;3,5];\r\n  \r\n  \u003e\u003eB=[-2.5,2;1.5,-1];\r\n  \r\n  \u003e\u003eisInverse(A,B)\r\n  \r\n  ans = 1\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: 174.033px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 87.0167px; transform-origin: 407px 87.0167px; vertical-align: baseline; \"\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: 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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: 28px 8.5px; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans = 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = isInverse(x,y)\r\n  y = x;\r\nend","test_suite":"%%\r\nA=[2,4;3,5];\r\nB=[-2.5,2;1.5,-1];\r\ny_correct = 1;\r\nassert(isequal(isInverse(A,B),y_correct))\r\n\r\n%%\r\nA=[1,2;3,5];\r\nB=[-5,2;3,-1];\r\ny_correct = 1;\r\nassert(isequal(isInverse(A,B),y_correct))\r\n\r\n%%\r\nA=[1,2;3,4];\r\nB=[4 3; 2 1];\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=[1,1;1,1];\r\nB=[0 0; 0 0];\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=1;\r\nB=1;\r\nassert(isequal(isInverse(A,B),1))\r\n\r\n%%\r\nA=spiral(3);\r\nB=eye(3);\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=magic(5);\r\nB=ones(5);\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=eye(7);\r\nB=eye(7);\r\nassert(isequal(isInverse(A,B),1))\r\n\r\n%%\r\nA=[1 2 3;2 1 2;3 2 1] %Toeplitz matrix\r\nB=[-0.375 0.5 0.125; 0.5 -1 0.5; 0.125 0.5 -0.375];\r\nassert(isequal(isInverse(A,B),1))\r\n\r\n%%\r\nA=meshgrid(1:4);\r\nB=fliplr(meshgrid(1:4));\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=hadamard(8);\r\nB=hadamard(8)/8;\r\nassert(isequal(isInverse(A,B),1))","published":true,"deleted":false,"likes_count":15,"comments_count":12,"created_by":1103,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1351,"test_suite_updated_at":"2021-05-14T10:50:59.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-04-01T04:32:36.000Z","updated_at":"2026-04-14T07:37:30.000Z","published_at":"2012-04-21T21:38:35.000Z","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\u003eGiven a matrix A and a matrix B, is A the inverse of B?\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[\u003e\u003eA=[2,4;3,5];\\n\\n\u003e\u003eB=[-2.5,2;1.5,-1];\\n\\n\u003e\u003eisInverse(A,B)\\n\\nans = 1]]\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":2730,"title":"Graph Algorithms 3: Number of Connected Components","description":"Given an adjacency matrix of a simple undirected graph, find the number of connected components.","description_html":"\u003cp\u003eGiven an adjacency matrix of a simple undirected graph, find the number of connected components.\u003c/p\u003e","function_template":"function y = cComponents(x)\r\n  y = x;\r\nend","test_suite":"%%\r\na = ones(3) - eye(3);\r\nb = zeros(3);\r\nmat = [a b; b a];\r\nn = 2;\r\nassert(isequal(cComponents(mat),n))\r\n\r\n\r\n%%\r\na = randi(20);\r\nmat = ones(a) - eye(a);\r\nn = 1;\r\nassert(isequal(cComponents(mat),n))\r\n\r\n\r\n%%\r\nmat = [0 1 0 0 1;\r\n       1 0 1 0 0;\r\n       0 1 0 1 0;\r\n       0 0 1 0 1;\r\n       1 0 0 1 0];\r\nassert(isequal(cComponents(mat),1))\r\n\r\n\r\n%%\r\na = ones(3) - eye(3);\r\nb = zeros(3);\r\nmat = [a b b; b a b; b b a];\r\nn = 3;\r\nassert(isequal(cComponents(mat),n))\r\n\r\n\r\n%%\r\na = ones(3) - eye(3);\r\nb = zeros(3);\r\np = floor((randi(20)+3)/3)*3;\r\nmat = [];\r\nfor i= 1:p\r\n    c = [repmat(b,1,i-1) a repmat(b,1,p-i)];\r\n    mat = [mat;c];\r\nend\r\n\r\nassert(isequal(cComponents(mat),p))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":17203,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":40,"test_suite_updated_at":"2014-12-07T06:39:46.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-12-06T07:19:29.000Z","updated_at":"2026-03-30T17:12:13.000Z","published_at":"2014-12-06T07:19:28.000Z","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\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"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\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 an adjacency matrix of a simple undirected graph, find the number of connected components.\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":2685,"title":"FloydWarshall","description":"Our task is to find shortest paths between every pair of nodes. Floyd-Warshall is a graph algorithm for finding shortest paths in weighted graph. The input of a function will be in weighted adjacency matrix representation. If two vertices does not have any edge than this matrix has Inf value. Function will return a matrix with values of shortest paths between each pair of nodes.\r\nExample :\r\n input= [0   1  Inf Inf \r\n        Inf  0   2  Inf\r\n        Inf Inf  0   3\r\n         4   7  Inf  0]\r\n\r\n output= [0   1   3   6\r\n          9   0   2   5\r\n          7   8   0   3\r\n          4   5   7   0]","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: 307.9px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 153.95px; transform-origin: 407px 153.95px; 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\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: 372.5px 8px; transform-origin: 372.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOur task is to find shortest paths between every pair of nodes. Floyd-Warshall is a graph algorithm for finding shortest paths in weighted graph. The input of a function will be in weighted adjacency matrix representation. If two vertices does not have any edge than this matrix has Inf value. Function will return a matrix with values of shortest paths between each pair of nodes.\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: 29.5px 8px; transform-origin: 29.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExample\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; 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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: 96px 8.5px; tab-size: 4; transform-origin: 96px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e input= [0   1  Inf Inf \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; 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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: 92px 8.5px; tab-size: 4; transform-origin: 92px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e        Inf  0   2  Inf\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; 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white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e          9   0   2   5\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: 92px 8.5px; tab-size: 4; transform-origin: 92px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e          7   8   0   3\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: 96px 8.5px; tab-size: 4; transform-origin: 96px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e          4   5   7   0]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = floydwarshall(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [0   1  Inf Inf;\r\n    Inf  0   2  Inf;\r\n    Inf Inf  0   3\r\n     4   7  Inf  0];\r\ny_correct = [0   1   3   6;\r\n             9   0   2   5;\r\n             7   8   0   3;\r\n             4   5   7   0];\r\nassert(isequal(floydwarshall(x),y_correct))\r\n\r\n%%\r\nx = [0   8  Inf  1;\r\n    Inf  0   1  Inf;\r\n     4  Inf  0  Inf;\r\n    Inf  2   9   0];\r\ny_correct = [0   3   4   1\r\n             5   0   1   6\r\n             4   7   0   5\r\n             7   2   3   0];\r\nassert(isequal(floydwarshall(x),y_correct))\r\n\r\n%%\r\nx = [0   3   6  Inf Inf Inf Inf\r\n     3   0   2   1  Inf Inf Inf\r\n     6   2   0   1   4   2  Inf\r\n    Inf  1   1   0   2  Inf  4\r\n    Inf Inf  4   2   0   2   1\r\n    Inf Inf  2  Inf  2   0   1\r\n    Inf Inf Inf  4   1   1   0];\r\ny_correct = [0 3 5 4 6 7 7\r\n            3 0 2 1 3 4 4\r\n            5 2 0 1 3 2 3\r\n            4 1 1 0 2 3 3\r\n            6 3 3 2 0 2 1\r\n            7 4 2 3 2 0 1\r\n            7 4 3 3 1 1 0];\r\nassert(isequal(floydwarshall(x),y_correct))\r\n\r\n%%\r\nx = [0   3  Inf  5;\r\n     2   0  Inf  4;\r\n    Inf  1   0  Inf;\r\n    Inf Inf  2   0];\r\ny_correct = [0 3 7 5\r\n             2 0 6 4\r\n             3 1 0 5\r\n             5 3 2 0];\r\nassert(isequal(floydwarshall(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":32478,"edited_by":223089,"edited_at":"2023-01-03T06:19:00.000Z","deleted_by":null,"deleted_at":null,"solvers_count":33,"test_suite_updated_at":"2023-01-03T06:19:00.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-11-23T22:43:29.000Z","updated_at":"2026-04-13T12:21:23.000Z","published_at":"2014-11-23T22:44:41.000Z","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\u003eOur task is to find shortest paths between every pair of nodes. Floyd-Warshall is a graph algorithm for finding shortest paths in weighted graph. The input of a function will be in weighted adjacency matrix representation. If two vertices does not have any edge than this matrix has Inf value. Function will return a matrix with values of shortest paths between each pair of nodes.\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\u003eExample\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[ input= [0   1  Inf Inf \\n        Inf  0   2  Inf\\n        Inf Inf  0   3\\n         4   7  Inf  0]\\n\\n output= [0   1   3   6\\n          9   0   2   5\\n          7   8   0   3\\n          4   5   7   0]]]\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":2372,"title":"Determine connected components of a graph","description":"Adjacency matrix of an undirected graph is given. Return the number of connected components in the graph.","description_html":"\u003cp\u003eAdjacency matrix of an undirected graph is given. Return the number of connected components in the graph.\u003c/p\u003e","function_template":"function y = conctCom(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx=[0 1 0 0 0; 1 0 1 1 0; 0 1 0 1 1; 0 1 1 0 1; 0 0 1 1 0];\r\ny_correct = 1;\r\nassert(isequal(conctCom(x),y_correct))\r\n\r\n%%\r\nx=[0 1 0 0 0; 1 0 0 0 0;0 0 0 1 0;0 0 1 0 1;0 0 0 1 0];\r\ny_correct = 2;\r\nassert(isequal(conctCom(x),y_correct))\r\n\r\n%%\r\nx=[0 1 0 0 0 0 ; \r\n1 0 0 0 0 0; \r\n0 0 0 1 0 0; \r\n0 0 1 0 0 0 ; \r\n0 0 0  0 0 1; \r\n0 0 0 0 1 0];\r\ny_correct = 3;\r\nassert(isequal(conctCom(x),y_correct))\r\n\r\n%%\r\nx=1;\r\ny_correct = 1;\r\nassert(isequal(conctCom(x),y_correct))\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":2,"created_by":17203,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":62,"test_suite_updated_at":"2014-06-18T16:25:21.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-06-18T07:37:21.000Z","updated_at":"2026-04-13T12:06:37.000Z","published_at":"2014-06-18T07:37:54.000Z","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\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"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\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\u003eAdjacency matrix of an undirected graph is given. Return the number of connected components in the graph.\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":1169,"title":"Count the Number of Directed Cycles in a Graph","description":"Given an asymmetric adjacency matrix, determine the number of unique directed cycles.\r\nFor example, the graph represented by adjacency matrix\r\nA = [\r\n  0 1 1 0;\r\n  1 1 0 1;\r\n  1 0 0 1;\r\n  1 1 0 0];\r\nhas 7 cycles. They are:\r\n[2 -\u003e 2]\r\n[1 -\u003e 2 -\u003e 1]\r\n[1 -\u003e 3 -\u003e 1]\r\n[2 -\u003e 4 -\u003e 2]\r\n[1 -\u003e 2 -\u003e 4 -\u003e 1]\r\n[1 -\u003e 3 -\u003e 4 -\u003e 1]\r\n[1 -\u003e 3 -\u003e 4 -\u003e 2 -\u003e 1]\r\nThe input is an adjacency matrix of 0s and 1s, and the output should be the number of unique (simple) directed cycles in the graph.","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: 399.2px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 199.6px; transform-origin: 407px 199.6px; vertical-align: baseline; \"\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: 225.5px 8px; transform-origin: 225.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven an asymmetric adjacency matrix, determine the number of unique\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: 2px 8px; transform-origin: 2px 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: 29.5px 8px; transform-origin: 29.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003edirected\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: 23.5px 8px; transform-origin: 23.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cycles.\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: 178px 8px; transform-origin: 178px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, the graph represented by adjacency matrix\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; 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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: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eA = [\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: 40px 8.5px; tab-size: 4; transform-origin: 40px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  0 1 1 0;\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: 40px 8.5px; tab-size: 4; transform-origin: 40px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  1 1 0 1;\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: 40px 8.5px; tab-size: 4; transform-origin: 40px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  1 0 0 1;\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: 44px 8.5px; tab-size: 4; transform-origin: 44px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  1 1 0 0];\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: 73.5px 8px; transform-origin: 73.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ehas 7 cycles. They are:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 143.033px; 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 71.5167px; transform-origin: 404px 71.5167px; 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: 32px 8.5px; tab-size: 4; transform-origin: 32px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[2 -\u0026gt; 2]\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: 52px 8.5px; tab-size: 4; transform-origin: 52px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 2 -\u0026gt; 1]\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: 52px 8.5px; tab-size: 4; transform-origin: 52px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 3 -\u0026gt; 1]\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: 52px 8.5px; tab-size: 4; transform-origin: 52px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[2 -\u0026gt; 4 -\u0026gt; 2]\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: 72px 8.5px; tab-size: 4; transform-origin: 72px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 2 -\u0026gt; 4 -\u0026gt; 1]\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: 72px 8.5px; tab-size: 4; transform-origin: 72px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 3 -\u0026gt; 4 -\u0026gt; 1]\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: 92px 8.5px; tab-size: 4; transform-origin: 92px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 3 -\u0026gt; 4 -\u0026gt; 2 -\u0026gt; 1]\u003c/span\u003e\u003c/span\u003e\u003c/div\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: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; 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: 380.5px 8px; transform-origin: 380.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe input is an adjacency matrix of 0s and 1s, and the output should be the number of unique (simple) directed cycles in the graph.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function nCycles = count_directed_cycles(A)\r\n  nCycles = 0;\r\nend","test_suite":"%%\r\nA = [\r\n  0 1 1 0\r\n  1 1 0 1\r\n  1 0 0 1\r\n  1 1 0 0];\r\nnCycles = 7;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n  0 1 0 1 0 1 0 0\r\n  0 0 0 1 1 0 1 1\r\n  1 1 0 1 1 0 1 1\r\n  0 1 0 0 1 0 1 0\r\n  1 1 0 0 1 0 1 0\r\n  1 0 0 0 0 0 1 0\r\n  1 1 1 1 0 0 0 1\r\n  0 0 0 1 1 1 1 1];\r\nnCycles = 197;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n  1 0 1 0 0 1 1 0 1 1\r\n  1 0 1 0 1 1 1 1 1 1\r\n  0 0 1 0 0 1 1 1 1 1\r\n  0 1 0 0 0 0 0 0 1 1\r\n  0 0 1 0 1 0 1 1 1 0\r\n  1 1 1 0 0 0 0 1 0 0\r\n  0 0 0 1 0 1 1 0 1 0\r\n  1 0 1 1 0 0 0 0 1 0\r\n  1 0 0 0 0 0 1 0 0 1\r\n  1 0 0 0 0 0 0 0 1 0];\r\nnCycles = 744;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n  0 0 0 0 1 0 1 1 1 1\r\n  0 0 0 1 0 1 0 1 1 1\r\n  0 0 0 0 0 0 1 1 1 1\r\n  0 0 1 0 1 1 0 1 0 0\r\n  0 1 0 1 0 0 0 0 0 1\r\n  1 0 0 1 1 1 1 0 1 1\r\n  0 1 1 1 1 0 1 1 0 1\r\n  0 1 0 0 1 1 0 0 0 1\r\n  1 0 1 0 0 1 1 0 1 1\r\n  1 0 1 1 0 1 1 0 0 0];\r\nnCycles = 4961;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n    0 1 1 0 0 0 1 0\r\n    1 0 0 0 1 1 1 1\r\n    0 0 0 0 0 1 0 1\r\n    1 1 0 0 1 1 1 0\r\n    1 1 0 0 0 0 0 1\r\n    0 0 1 0 1 0 0 0\r\n    0 1 0 0 0 1 0 1\r\n    0 0 1 1 0 1 0 0];\r\nnCycles = 116;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n    0 1 0 1 1 1 0 0 1 0\r\n    1 0 0 1 1 0 1 0 0 1\r\n    0 1 1 0 1 0 0 0 1 1\r\n    0 1 1 0 1 1 0 0 1 0\r\n    1 0 0 0 0 1 1 0 0 1\r\n    0 1 1 0 0 1 0 0 0 1\r\n    0 1 1 0 1 0 1 1 1 1\r\n    1 1 1 0 0 0 0 0 1 1\r\n    1 1 1 0 1 1 1 1 0 1\r\n    0 0 1 1 1 0 1 0 1 0];\r\nnCycles = 5888;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n    0 0 0 1 1 0 1 0 1 1 0 0\r\n    0 0 1 1 1 0 0 0 0 0 0 1\r\n    1 0 1 0 0 0 1 1 1 0 1 1\r\n    1 0 1 1 0 0 0 0 1 0 0 0\r\n    1 1 1 0 1 0 0 0 1 0 1 0\r\n    0 1 0 1 0 0 0 0 1 1 0 0\r\n    1 1 1 1 1 0 1 0 1 0 1 0\r\n    0 1 0 1 0 0 1 1 1 1 1 1\r\n    0 1 0 1 1 0 0 1 0 1 1 0\r\n    0 1 1 1 1 1 0 0 0 1 1 0\r\n    1 1 1 1 0 0 1 1 0 0 0 0\r\n    0 1 1 1 1 1 1 1 0 0 0 1];\r\nnCycles = 50093;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":1057,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":28,"test_suite_updated_at":"2021-12-31T15:51:58.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-04T13:38:03.000Z","updated_at":"2026-04-13T12:20:06.000Z","published_at":"2013-01-04T13:48:40.000Z","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\u003eGiven an asymmetric adjacency matrix, determine the number of unique\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\u003edirected\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cycles.\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, the graph represented by adjacency matrix\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[A = [\\n  0 1 1 0;\\n  1 1 0 1;\\n  1 0 0 1;\\n  1 1 0 0];]]\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\u003ehas 7 cycles. They are:\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[[2 -\u003e 2]\\n[1 -\u003e 2 -\u003e 1]\\n[1 -\u003e 3 -\u003e 1]\\n[2 -\u003e 4 -\u003e 2]\\n[1 -\u003e 2 -\u003e 4 -\u003e 1]\\n[1 -\u003e 3 -\u003e 4 -\u003e 1]\\n[1 -\u003e 3 -\u003e 4 -\u003e 2 -\u003e 1]]]\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 input is an adjacency matrix of 0s and 1s, and the output should be the number of unique (simple) directed cycles in the graph.\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":458,"title":"Parcel Routing","description":"Given a matrix that represent the distance along highways between major cities numbered 1 to _N_, provide the path and shortest distance from a given city, _from_, to a given city, _to_. Assume that 0 represents no direct path between two cities. If there is no solution to the problem, return -1 for both the path and the distance.","description_html":"\u003cp\u003eGiven a matrix that represent the distance along highways between major cities numbered 1 to \u003ci\u003eN\u003c/i\u003e, provide the path and shortest distance from a given city, \u003ci\u003efrom\u003c/i\u003e, to a given city, \u003ci\u003eto\u003c/i\u003e. Assume that 0 represents no direct path between two cities. If there is no solution to the problem, return -1 for both the path and the distance.\u003c/p\u003e","function_template":"function [route d] = parcel_route( from, to, graph )\r\n  route = -1;\r\n  d = -1;\r\nend","test_suite":"%%\r\n[route d] = parcel_route( 1, 5, zeros( 5 ) )\r\nassert(route == -1 \u0026\u0026 d == -1);\r\n\r\n%%\r\n[route d] = parcel_route( 1, 2, [0 0.320527862039621 0 0 0;0.320527862039621 0 0 0 0.85044688801616;0 0 0 0 0;0 0 0 0 0;0 0.85044688801616 0 0 0] );\r\nassert( isequal(route,[1 2]) \u0026\u0026 abs( d - 0.320528 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 4, 2, [0 0 0 0 0.648056184801628;0 0 0.168504735306137 0 0;0 0.168504735306137 0 0 0;0 0 0 0 0;0.648056184801628 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 3, 3, [0 0 0 1.07077622171054 0.00497624606093106;0 0 0 0 0;0 0 0 0 0;1.07077622171054 0 0 0 0;0.00497624606093106 0 0 0 0] );\r\nassert( isequal(route,3) \u0026\u0026 abs( d - 0 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 5, 2, [0 0 0.478447257684744 0.52778921303553 0;0 0 0 0.344727452766697 0;0.478447257684744 0 0 0 0;0.52778921303553 0.344727452766697 0 0 0;0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 1, 4, [0 0 0 0 0;0 0 0 0 0;0 0 0 0 0;0 0 0 0 0;0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 10, 5, [0 0 0 0 0.758920911298127 1.17184862472796 0 0 0 0;0 0 0 0.229051389055984 0 0 0.110344033764499 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0.229051389055984 0 0 0 0 0 0 0 0;0.758920911298127 0 0 0 0 0 0.582786870390757 0 0 0.266149081187709;1.17184862472796 0 0 0 0 0 0.91437757836659 0 0 0.928664694998184;0 0.110344033764499 0 0 0.582786870390757 0.91437757836659 0 0.72845914907191 0.440667818657679 0.0752998054887686;0 0 0 0 0 0 0.72845914907191 0 0 0;0 0 0 0 0 0 0.440667818657679 0 0 0.72584117080215;0 0 0 0 0.266149081187709 0.928664694998184 0.0752998054887686 0 0.72584117080215 0] );\r\nassert( isequal(route,[10 5]) \u0026\u0026 abs( d - 0.266149 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 7, 3, [0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0.348270614748404 0 0.963402246386651 0 0 0 0;0 0 0.348270614748404 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.00647302663148808 0 0;0 0 0.963402246386651 0 0 0 0 1.11338837090812 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0.00647302663148808 1.11338837090812 0 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 4, 7, [0 0 0.529236850857286 0 0 0 1.60144982503606 0 0 0;0 0 0 0 0 0 0.828441215877115 0 0 0;0.529236850857286 0 0 0.0279102825979989 0 0 0 0 0 0.0544746812572747;0 0 0.0279102825979989 0 0 0 0 0 0 0;0 0 0 0 0 1.04094484718858 0 0 0 0;0 0 0 0 1.04094484718858 0 0 0 0 0.124040053577104;1.60144982503606 0.828441215877115 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.37043522751259;0 0 0.0544746812572747 0 0 0.124040053577104 0 0 0.37043522751259 0] );\r\nassert( isequal(route,[4 3 1 7]) \u0026\u0026 abs( d - 2.1586 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 4, 7, [0 0 0 0 0 0 0 0 0 0;0 0 0 0 0.577543761888686 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0.124487323633357 0 0 0.679813903514902;0 0.577543761888686 0 0 0 0 0.560623889702786 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0.124487323633357 0.560623889702786 0 0 0 0.250828758360099 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0.250828758360099 0 0 0.914651700028183;0 0 0 0.679813903514902 0 0 0 0 0.914651700028183 0] );\r\nassert( isequal(route,[4 7]) \u0026\u0026 abs( d - 0.124487 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 1, 9, [0 0 0.210714289971845 0 0 0.655795786759233 0 0 0.417975370686535 0.0762383289683841;0 0 0 0 0 0 0 0 0 0;0.210714289971845 0 0 0 0 0 0.627639413184948 0.546973506820504 0 0;0 0 0 0 0 0.44290978142888 0 0 0 0;0 0 0 0 0 0 0.494959375382896 0.199417369123429 0.61193318690704 0;0.655795786759233 0 0 0.44290978142888 0 0 0 0 0.295901565877421 0;0 0 0.627639413184948 0 0.494959375382896 0 0 0 0 0;0 0 0.546973506820504 0 0.199417369123429 0 0 0 0 0.882898432991531;0.417975370686535 0 0 0 0.61193318690704 0.295901565877421 0 0 0 0.0999710063468799;0.0762383289683841 0 0 0 0 0 0 0.882898432991531 0.0999710063468799 0] );\r\nassert( isequal(route,[1 10 9]) \u0026\u0026 abs( d - 0.176209 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 12, 3, [0 0.139438875035701 0.112367141305958 0 0 0 0 0 0 0.742115072015769 0 0 0.244537467584915 0 0;0.139438875035701 0 0.135942047224331 0 0 0 0 0 0 0 0.374140881779805 0 0.217860680093506 0.379818098539566 1.17229854239237;0.112367141305958 0.135942047224331 0 0 0 0 0 1.7792137360137 0.350752848520651 0 0 0.284985494377118 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.161446305533344 0 0 0 0.183948436622344 0 0 0;0 0 1.7792137360137 0 0 0 0.161446305533344 0 0 0 0 0 0 0 0;0 0 0.350752848520651 0 0 0 0 0 0 0 0 0 0 0 0.362973369969354;0.742115072015769 0 0 0 0 0 0 0 0 0 0.263865914379949 0 0 0 0;0 0.374140881779805 0 0 0 0 0 0 0 0.263865914379949 0 0 0 0 0;0 0 0.284985494377118 0 0 0 0.183948436622344 0 0 0 0 0 0 0 0;0.244537467584915 0.217860680093506 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0.379818098539566 0 0 0 0 0 0 0 0 0 0 0 0 1.863621808387;0 1.17229854239237 0 0 0 0 0 0 0.362973369969354 0 0 0 0 1.863621808387 0] );\r\nassert( isequal(route,[12 3]) \u0026\u0026 abs( d - 0.284985 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 14, 13, [0 0 0 0.0850075668378245 0 0 0 0 0.0463952689981919 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0.0850075668378245 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.831785345865625 0 0 0 0 0 0 0 0.300824537605104 0;0 0 0 0 0.831785345865625 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.316676635592728 0 0 0.18465657297998 0 0;0.0463952689981919 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.316676635592728 0 0 0 0 0 0 2.01596808102817;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0.735349103904233 0 0;0 0 0 0 0 0 0 0.18465657297998 0 0 0 0.735349103904233 0 0 0;0 0 0 0 0.300824537605104 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 2.01596808102817 0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 8, 8, [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.669844066951192 0 0 1.79425332134151 0 0 0 0;0 0 0 0 0 0.354813543185228 0.350829365088585 0.334017411457367 0 0 0.750194269879854 0 0 0 0.837083783283494;0 0 0 0 0 0 0 0 0 0 0 0.7666462425288 0 0 0;0 0 0 0 0 0 0 0 0 0 0.335432927184154 0.290662441159473 0 0 0;0 0 0.354813543185228 0 0 0 0 0 0 0 0 0.612746104915618 0 1.3702409817804 0;0 0 0.350829365088585 0 0 0 0 0 0 0 0 0 0 0 0;0 0.669844066951192 0.334017411457367 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 1.79425332134151 0.750194269879854 0 0.335432927184154 0 0 0 0 0 0 0 0 0 0;0 0 0 0.7666462425288 0.290662441159473 0.612746104915618 0 0 0 0 0 0 0.600235691901178 0 0;0 0 0 0 0 0 0 0 0 0 0 0.600235691901178 0 0 0;0 0 0 0 0 1.3702409817804 0 0 0 0 0 0 0 0 0.25725306655894;0 0 0.837083783283494 0 0 0 0 0 0 0 0 0 0 0.25725306655894 0] );\r\nassert( isequal(route,8) \u0026\u0026 abs( d - 0 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 9, 2, [0 0 0 0 0 0 0 0.216161539093326 0 0 0 0 0 0 0;0 0 0 0.154899548332433 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0.195632123891572 0 0.638112022611646 0 0;0 0.154899548332433 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.924920233869358 0 0 0 0 0 0 0.225753938901222;0 0 0 0 0 0 0 0 0 0 0 0.105130198814148 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0.216161539093326 0 0 0 0.924920233869358 0 0 0 0.283480661544537 0 0 0 0 0 0;0 0 0 0 0 0 0 0.283480661544537 0 0 0.860820315822094 0 0 0.114189406386242 0;0 0 0 0 0 0 0 0 0 0 0.777006911310097 0.0395282910845656 0.559642782958394 0.0374763085984708 0;0 0 0.195632123891572 0 0 0 0 0 0.860820315822094 0.777006911310097 0 0.107327989339846 0 0 0;0 0 0 0 0 0.105130198814148 0 0 0 0.0395282910845656 0.107327989339846 0 0 0 0;0 0 0.638112022611646 0 0 0 0 0 0 0.559642782958394 0 0 0 0 0;0 0 0 0 0 0 0 0 0.114189406386242 0.0374763085984708 0 0 0 0 0;0 0 0 0 0.225753938901222 0 0 0 0 0 0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 6, 8, [0 1.00600776349789 0 0 0.409642943366229 0 0 0 0 0 0 0 0.780942905018081 0.218269812307052 0;1.00600776349789 0 0 0 0 0 0 0 0 0.604439587022491 0 0 0 0 0;0 0 0 2.19497071462911 0 0.384068674620751 0 0 0 0.752596352506117 0.210553220187945 0 0 0 0.101200876472261;0 0 2.19497071462911 0 0 0 0 0 0 0 0 0.0821684991109088 0 0 1.39540244685607;0.409642943366229 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.384068674620751 0 0 0 0.0278385656290563 0 0 0 0 0 0 0 0;0 0 0 0 0 0.0278385656290563 0 0 0 0 0.314664537582249 0 0 0 0.157551652892199;0 0 0 0 0 0 0 0 0 0 1.37753279184511 0 0 0.647734508061038 0.538120114299927;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0.604439587022491 0.752596352506117 0 0 0 0 0 0 0 0.38099752988379 0 0 0 0;0 0 0.210553220187945 0 0 0 0.314664537582249 1.37753279184511 0 0.38099752988379 0 0 0 0 0;0 0 0 0.0821684991109088 0 0 0 0 0 0 0 0 0.724941186609613 0 0;0.780942905018081 0 0 0 0 0 0 0 0 0 0 0.724941186609613 0 0 0;0.218269812307052 0 0 0 0 0 0 0.647734508061038 0 0 0 0 0 0 0;0 0 0.101200876472261 1.39540244685607 0 0 0.157551652892199 0.538120114299927 0 0 0 0 0 0 0] );\r\nassert( isequal(route,[6 7 15 8]) \u0026\u0026 abs( d - 0.72351 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 15, 1, [0 0 0 0 0 0 0 0 0 0 0 0.444956179153313 0.694837045312089 0 0 0 1.21296662658388 0 1.56620351515086 0.139996151546743;0 0 0.436509042497808 0 0 0 0 0 0 0.51021617110356 0.382775864014207 0 0 0 0 0 0 0 0.0458660640982067 0;0 0.436509042497808 0 0.142843784706697 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.142843784706697 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.923358421898822 0 0 0 0 0 0 0.535622573665002 0 0 0.0623807988546017 0 0 0 0;0 0 0 0 0.923358421898822 0 0 0 0 0 0 0 0 0 0.0225268450194125 0.789248499651178 0.131644262096824 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0.157622272676696 0.474149476188578 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 1.38990078830045 0 0 0 0 0.691403775437505 0;0 0.51021617110356 0 0 0 0 0 0 0 0 0.597507997139564 0 0 0 0.354205526419423 0 0 0 0 0;0 0.382775864014207 0 0 0 0 0 0 0 0.597507997139564 0 0 0 0.659672915756231 0 0 0 0 0 0;0.444956179153313 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.138835508200668;0.694837045312089 0 0 0 0.535622573665002 0 0.157622272676696 0 0 0 0 0 0 0 0 0.112112626230952 0 0 0 0.0843937952650982;0 0 0 0 0 0 0.474149476188578 0 1.38990078830045 0 0.659672915756231 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.0225268450194125 0 0 0 0.354205526419423 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0.0623807988546017 0.789248499651178 0 0 0 0 0 0 0.112112626230952 0 0 0 0 0 0 2.40412068693751;1.21296662658388 0 0 0 0 0.131644262096824 0 0 0 0 0 0 0 0 0 0 0 0 0.332961917093088 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.464569385286 0;1.56620351515086 0.0458660640982067 0 0 0 0 0 0 0.691403775437505 0 0 0 0 0 0 0 0.332961917093088 1.464569385286 0 0;0.139996151546743 0 0 0 0 0 0 0 0 0 0 0.138835508200668 0.0843937952650982 0 0 2.40412068693751 0 0 0 0] );\r\nassert( isequal(route,[15 6 16 13 20 1]) \u0026\u0026 abs( d - 1.14828 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 6, 9, [0 0.366176160541789 0.786653302253499 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.21056171145861;0.366176160541789 0 0 0 0 0 0 0 0 1.00794652016003 0 0 0 0 0 0 0 0 0 0;0.786653302253499 0 0 0 0.00852440175782365 0 0 0 0 0 0.17749671083585 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.104971160045632 0 0.612122585766863 0 0.283798036821908;0 0 0.00852440175782365 0 0 0 0.643083445674635 0 0 0 1.48191061231689 0 0 0 0.200776975353452 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.20656027667801 0 0 0;0 0 0 0 0.643083445674635 0 0 0 0.0293301078099069 0 0 0.0684877514911584 0.244866042619905 0 0 0 0 0.844967783108164 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0.0293301078099069 0 0 0 0 0.112122931478046 0 0 0 0.904924565740344 0 0 0 0;0 1.00794652016003 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.17749671083585 0 1.48191061231689 0 0 0 0 0 0 0.356911349006201 0 0 0.157837394902406 0 0 0 0 0;0 0 0 0 0 0 0.0684877514911584 0 0.112122931478046 0 0.356911349006201 0 0.682956498987976 0.369934947078526 0 0 0 0 0 0;0 0 0 0 0 0 0.244866042619905 0 0 0 0 0.682956498987976 0 0 0 0 1.43719870645473 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0.369934947078526 0 0 0 0 0 0 0 0;0 0 0 0 0.200776975353452 0 0 0 0 0 0.157837394902406 0 0 0 0 0.0962643536575907 0 0 0 0;0 0 0 0.104971160045632 0 0 0 0 0.904924565740344 0 0 0 0 0 0.0962643536575907 0 0 0 0 0.884861315533158;0 0 0 0 0 1.20656027667801 0 0 0 0 0 0 1.43719870645473 0 0 0 0 0.00316254045496533 0.917601066178612 0;0 0 0 0.612122585766863 0 0 0.844967783108164 0 0 0 0 0 0 0 0 0 0.00316254045496533 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.917601066178612 0 0 0;0.21056171145861 0 0 0.283798036821908 0 0 0 0 0 0 0 0 0 0 0 0.884861315533158 0 0 0 0] );\r\nassert( isequal(route,[6 17 18 7 9]) \u0026\u0026 abs( d - 2.08402 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 15, 8, [0 0 0 0 0 0 0 0.444927230771171 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0.0904807891398611 0 0 0.117980802815763 0 0 0 0 0 0 0 0 0 0 0.786791961925432 0 0;0 0 0 0 0 0 0 0 0 0.159132007464481 0.110433064086588 0 0 0 0 0 0 0 0 0.139982926657546;0 0.0904807891398611 0 0 0.388870980511861 0 0 0 0 0 0 0.973527639623757 0 0 0 0 0 0 0 0;0 0 0 0.388870980511861 0 0 0 0.305597627987039 0 0 0 0 0.027077532916115 0 0 0 0 0 0.290796760442986 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0.117980802815763 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.27266472620458 0.665594866955372 0 0.626568354787985;0.444927230771171 0 0 0 0.305597627987039 0 0 0 0 0 0 0 0 0 0 0 0 0 0.498229667608556 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.159132007464481 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.110433064086588 0 0 0 0 0 0 0 0 0 0.611004915345871 0 0 0 0.561899811991367 0 0 0;0 0 0 0.973527639623757 0 0 0 0 0 0 0 0 0.949329689605504 0 0 0 0 0 0 0;0 0 0 0 0.027077532916115 0 0 0 0 0 0.611004915345871 0.949329689605504 0 0 0 0 0 0.45822991145669 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.916926430883478 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0944227233455792;0 0 0 0 0 0 1.27266472620458 0 0 0 0.561899811991367 0 0 0 0 0 0 0.0123263072768274 0 0;0 0.786791961925432 0 0 0 0 0.665594866955372 0 0 0 0 0 0.45822991145669 0 0 0 0.0123263072768274 0 0.708053638455894 0;0 0 0 0 0.290796760442986 0 0 0.498229667608556 0 0 0 0 0 0.916926430883478 0 0 0 0.708053638455894 0 0;0 0 0.139982926657546 0 0 0 0.626568354787985 0 0 0 0 0 0 0 0 0.0944227233455792 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 5, 4, [0 0 0 0 0 0 0 0 0 0.482056160228392 0 0 0 0 0 0 0 0 0.00508309589200806 0;0 0 0.342764171753101 0 0.592230924022738 0 0 0 0 0 0 0 0 0 0 0 0.616196530219501 0 0.105964156030294 0;0 0.342764171753101 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.06756913797405 0 0 0 0 0;0 0.592230924022738 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 1.75169005582658 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.198256254136309 0 0.117040404671406 0.742253008190119 0 0 0 0 0 0 0 0 0;0 0 0 0 0 1.75169005582658 0.198256254136309 0 0 0.193487168668438 0 0 0 0 0 0.213470445629309 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0.672768253513765 0 0 0 0 0 0 0 0;0.482056160228392 0 0 0 0 0 0.117040404671406 0.193487168668438 0 0 0.182397544709499 0 0 0 0 0 0 0 0.352313653363684 0;0 0 0 0 0 0 0.742253008190119 0 0 0.182397544709499 0 0.863897537114491 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0.672768253513765 0 0.863897537114491 0 0 0 0 0 0.849422540372472 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.126177070732391 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 1.06756913797405 0 0 0 0 0 0 0 0 0.126177070732391 0 0 0 0 0.810675752838635 0.192588746332897 0;0 0 0 0 0 0 0 0.213470445629309 0 0 0 0 0 0 0 0 0 0 0 0;0 0.616196530219501 0 0 0 0 0 0 0 0 0 0.849422540372472 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.810675752838635 0 0 0 0 0;0.00508309589200806 0.105964156030294 0 0 0 0 0 0 0 0.352313653363684 0 0 0 0 0.192588746332897 0 0 0 0 0.473102743220109;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.473102743220109 0] );\r\nassert( isequal(route,[5 2 19 15 4]) \u0026\u0026 abs( d - 1.95835 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 18, 3, [0 0 0 0 0 0 0.588131422298983 0 0 0 0 0 0 0 0 0 0 0 0.411615488806083 0;0 0 0 0 0 0 0 0 0 0.148093137302263 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.513126690185934 0.314081294727961 0 0 0 0 0 0 0 0 0 0 0.105622237791164 0 0;0 0 0 0 0.0233388222703319 0 0 0.620281238898666 0 0 0 1.01777898612281 0 0 1.02802169259185 0 0 0 0 0.829878923718159;0 0 0 0.0233388222703319 0 0.103664033766553 0 0 0 0 0.800687507355036 0.724909646173659 0 0 0 0 0 0 0 0;0 0 0.513126690185934 0 0.103664033766553 0 0 0 0 0 0 0 0.51932792913499 0.111508583765534 0 0 0 0 0 0;0.588131422298983 0 0.314081294727961 0 0 0 0 0 0.632615202648636 0 0 0 1.12039468709595 0 0 0 0 0 0 0;0 0 0 0.620281238898666 0 0 0 0 0.665853755155897 0 0.443519419164187 0 0.0287540443670959 0 0 0 0 0 0 0;0 0 0 0 0 0 0.632615202648636 0.665853755155897 0 0 0 0 0 0 0 0 0 0 0 0.341087071649035;0 0.148093137302263 0 0 0 0 0 0 0 0 0.0523829918450132 0 0 0 0 0 0 0.401940201122634 0.691832558529399 0;0 0 0 0 0.800687507355036 0 0 0.443519419164187 0 0.0523829918450132 0 0.491690939364275 0 0.757845451055127 0 0 0 0.024463668194654 0 0;0 0 0 1.01777898612281 0.724909646173659 0 0 0 0 0 0.491690939364275 0 0 0 0 0 0 0 0 1.02836268723464;0 0 0 0 0 0.51932792913499 1.12039468709595 0.0287540443670959 0 0 0 0 0 0 0 0 0 0 0 0.366143225287491;0 0 0 0 0 0.111508583765534 0 0 0 0 0.757845451055127 0 0 0 0.223088374978438 0 0 0 0 0;0 0 0 1.02802169259185 0 0 0 0 0 0 0 0 0 0.223088374978438 0 0.344909749483892 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.344909749483892 0 0 0 0.353158597614942 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.105622237791164 0 0 0 0 0 0 0.401940201122634 0.024463668194654 0 0 0 0 0 0 0 0 0;0.411615488806083 0 0 0 0 0 0 0 0 0.691832558529399 0 0 0 0 0 0.353158597614942 0 0 0 0.849677928981906;0 0 0 0.829878923718159 0 0 0 0 0.341087071649035 0 0 1.02836268723464 0.366143225287491 0 0 0 0 0 0.849677928981906 0] );\r\nassert( isequal(route,[18 3]) \u0026\u0026 abs( d - 0.105622 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 17, 23, [0 0.151141399637051 0 0 0 0 0 0 0 0 0 0.105216194021975 0 0 0 0 0 0.437381445735918 0 0 0.949941070771521 0 0 0 0;0.151141399637051 0 0 0 0 0 0 0 1.22583368379244 0 0 0.079829221583307 0.71041636270324 0 0 0 0.1075924794072 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 1.21948687450578 0 0.567263036089771 0 0 0 0 0 0.857795458880245 0 0 0 0 0.731569267553795 0 0 0;0 0 0 0 0 0 0.186039341309778 0 0 0 0 0 0 0 0 0 0 2.00348310018009 0 0 0 0 0 0 0;0 0 0 0 0 1.32070145417138 0 0 0 0 0 0 0 0 0 0 0 0.430765092398605 0 0 0 0 0 0.46856479561555 0;0 0 0 0 1.32070145417138 0 0 0.203767017753022 0 0 0 0 0 0 0.487213897131877 0 0 0.896335225888555 0 0 0 0 0 0 0;0 0 0 0.186039341309778 0 0 0 0 0 0 0 0 0.406945507381253 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.203767017753022 0 0 0.15769661193131 0 0.65001597680104 0 0 0 0 0 0 0.15666137867965 0 0 0 0 0.723509833846064 0 0;0 1.22583368379244 1.21948687450578 0 0 0 0 0.15769661193131 0 0 0 0 0 0 0 0 0.508542446617735 0 0 0.696934855529271 0.169312519482881 0 0.00704092733099992 0 0;0 0 0 0 0 0 0 0 0 0 0 0 1.08493079525094 0.214254564261975 0 0.425013648805044 0 0 0 0 0 0 0 0 0.00543872970590864;0 0 0.567263036089771 0 0 0 0 0.65001597680104 0 0 0 0 0 0 0 0 0.696979111426999 0.525282567629852 0 0.621146400617813 1.20050590589561 0 0 0 0;0.105216194021975 0.079829221583307 0 0 0 0 0 0 0 0 0 0 0.459862031186997 0 0 0 0 0 0 0.698687249438191 0 0 0.00200957746053532 0 0;0 0.71041636270324 0 0 0 0 0.406945507381253 0 0 1.08493079525094 0 0.459862031186997 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.214254564261975 0 0 0 0 0.380308744719566 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.487213897131877 0 0 0 0 0 0 0 0.380308744719566 0 0 0.0449909078512449 0 0 1.22341039971646 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.425013648805044 0 0 0 0 0 0 0 0 0 0 0 0 1.43760755773283 0.719177032769178 0;0 0.1075924794072 0.857795458880245 0 0 0 0 0 0.508542446617735 0 0.696979111426999 0 0 0 0.0449909078512449 0 0 0 0 0 0 0 0 0 0;0.437381445735918 0 0 2.00348310018009 0.430765092398605 0.896335225888555 0 0.15666137867965 0 0 0.525282567629852 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0.696934855529271 0 0.621146400617813 0.698687249438191 0 0 1.22341039971646 0 0 0 0 0 1.1519343197436 0 0 0 0;0.949941070771521 0 0 0 0 0 0 0 0.169312519482881 0 1.20050590589561 0 0 0 0 0 0 0 0 1.1519343197436 0 0 0 0 0.214330337662627;0 0 0.731569267553795 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.723509833846064 0.00704092733099992 0 0 0.00200957746053532 0 0 0 1.43760755773283 0 0 0 0 0 0 0 0 0;0 0 0 0 0.46856479561555 0 0 0 0 0 0 0 0 0 0 0.719177032769178 0 0 0 0 0 0 0 0 0.649429697531317;0 0 0 0 0 0 0 0 0 0.00543872970590864 0 0 0 0 0 0 0 0 0 0 0.214330337662627 0 0 0.649429697531317 0] );\r\nassert( isequal(route,[17 2 12 23]) \u0026\u0026 abs( d - 0.189431 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 2, 9, [0 0 0 0 0 0.390568942736463 0.253317405921882 0 0 0 0 0 0 0 0 0.035303866587423 0 0.0932427029924401 0 0.228317786309953 0 0 0 0 0;0 0 0 0 0 0 0.22325539367323 0.0737968434096563 0 0.0216391156829114 1.01817561468837 0 0 0.166613690540579 0 0 0 0 0 0.0929136548216463 0 0 0 0 0;0 0 0 0 0 0.324975382720294 0 0 0 0 0 0 0 0 0.257683850031889 0 0 0 0.818836795828793 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0.0227807501033899 0 0 0 0 0.254392094407223 0 0 0 0 0 0.499630884751228 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0.645309316664204 0 0 0 0 0 0.377002225744615 0 0 0 0 0;0.390568942736463 0 0.324975382720294 0 0 0 0 0 0 0 0 0.381625987614713 0.187530187877611 0 0 0 0 0 1.03662835165178 0 0 0 0 0 0;0.253317405921882 0.22325539367323 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.420116352005782 0.288516971344659 0 0 0 0 0.290423766876168 0;0 0.0737968434096563 0 0 0 0 0 0 0 0 0 0 0 1.14302504189143 0 0.894497023541543 0 0 0 0 0 0 0.181212342324972 0 0.4790219658659;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.66947645498941 0 0 0 0 0 0 0 0.881432911415172 0.190738003819626 0;0 0.0216391156829114 0 0 0 0 0 0 0 0 0 0 0 0 0 0.406383564162139 0 0 0 0 0 0 0 0 0.0727730905533963;0 1.01817561468837 0 0 0 0 0 0 0 0 0 0.968244418446258 0 0 0.528273242216383 0.125653272829919 0 0 0 0 0 0 0 0 0;0 0 0 0.0227807501033899 0 0.381625987614713 0 0 0 0 0.968244418446258 0 0 0 0 0.545221500471632 0 0 0.602095719309548 0 0 0 0 0 0;0 0 0 0 0 0.187530187877611 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.926256705235548 0 0 0 0;0 0.166613690540579 0 0 0.645309316664204 0 0 1.14302504189143 0 0 0 0 0 0 0 0 0 0.21560951711239 0 0 0 0 0 0 0;0 0 0.257683850031889 0 0 0 0 0 0.66947645498941 0 0.528273242216383 0 0 0 0 0 0 0 0 0 0.213055228450905 0 0 0 0;0.035303866587423 0 0 0 0 0 0 0.894497023541543 0 0.406383564162139 0.125653272829919 0.545221500471632 0 0 0 0 0.450996873658263 0 0 0 0 0 0 0 0;0 0 0 0.254392094407223 0 0 0 0 0 0 0 0 0 0 0 0.450996873658263 0 0 0 0 0 0 0.219529444302005 0 0;0.0932427029924401 0 0 0 0 0 0.420116352005782 0 0 0 0 0 0 0.21560951711239 0 0 0 0 0 0 0 0.863470148104069 0 0.444628451921207 0;0 0 0.818836795828793 0 0 1.03662835165178 0.288516971344659 0 0 0 0 0.602095719309548 0 0 0 0 0 0 0 0 0 0.109259232718513 0 0 0;0.228317786309953 0.0929136548216463 0 0 0.377002225744615 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.615496286883062;0 0 0 0 0 0 0 0 0 0 0 0 0.926256705235548 0 0.213055228450905 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.863470148104069 0.109259232718513 0 0 0 0 0.0137884729469751 0;0 0 0 0.499630884751228 0 0 0 0.181212342324972 0.881432911415172 0 0 0 0 0 0 0 0.219529444302005 0 0 0 0 0 0 0.365687691203556 0;0 0 0 0 0 0 0.290423766876168 0 0.190738003819626 0 0 0 0 0 0 0 0 0.444628451921207 0 0 0 0.0137884729469751 0.365687691203556 0 0;0 0 0 0 0 0 0 0.4790219658659 0 0.0727730905533963 0 0 0 0 0 0 0 0 0 0.615496286883062 0 0 0 0 0] );\r\nassert( isequal(route,[2 7 24 9]) \u0026\u0026 abs( d - 0.704417 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 12, 4, [0 0 0 0 0 0.714172260222902 0 0 0 0 0 0 0 0 0 0 0 0 0 0.361655390928043 0 0 0 0 0;0 0 0 0 0 0.181492418867339 0 0 0 0 0 0 0 0 0 0 0 0 0.22307965545124 0 0 0 0 0 0.779096496125678;0 0 0 0 0 0 0.47292346615082 0 0 0.168841046075892 0 0 0 0 0 0 0 0 0 0.0217708463553388 0 0 0.667747131809592 0 0;0 0 0 0 0 0 0 0.57532352865356 0 0 1.14531063150095 0 0 0 0 0 0 0 0 1.81120439254402 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0.347520308679668 0 0 0 0 1.19301977580358 0 0.820270346367214 0 0 0.0596854204267023 0 0.365147722552969 0.160828167983497 0;0.714172260222902 0.181492418867339 0 0 0 0 0.993473525288174 0 0 0 0 0 0 0 0 0 0 0 0 0.900267645686867 0 0 0 0 0;0 0 0.47292346615082 0 0 0.993473525288174 0 0 0 0 0.303524976604928 0 0 0.988108387042638 0 0 0 0 1.09908596860658 0 0 0 0 0 0;0 0 0 0.57532352865356 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0496932258637628 0 0 0 0 0 0 0.220051533000778 0 0 0;0 0 0.168841046075892 0 0 0 0 0 0 0 0 0 0.415893111213311 0 0 0 0 0 0 0 0 0 0 0.252874847836154 0.7525160069564;0 0 0 1.14531063150095 0.347520308679668 0 0.303524976604928 0 0 0 0 0 0.315427799185682 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0.0659140954680451 0.229430180128888 0 0 0 1.02421541676855 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.415893111213311 0.315427799185682 0 0 0 1.43148800286315 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0.988108387042638 0 0 0 0 0.0659140954680451 0 0 0 0 0.0723048054691602 0.570598773372364 0 0 0 0 0 0 0.816798020448907;0 0 0 0 0 0 0 0 0.0496932258637628 0 0 0.229430180128888 1.43148800286315 0 0 0.0969052461008522 0 0 0.562394406606289 0 0 0 0 0 0;0 0 0 0 1.19301977580358 0 0 0 0 0 0 0 0 0 0.0969052461008522 0 0.830027198843182 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0.0723048054691602 0 0.830027198843182 0 0 0 0 0.471570888980097 0 0 0 0;0 0 0 0 0.820270346367214 0 0 0 0 0 0 0 0 0.570598773372364 0 0 0 0 0 0 0 0 0 0 0;0 0.22307965545124 0 0 0 0 1.09908596860658 0 0 0 0 1.02421541676855 0 0 0.562394406606289 0 0 0 0 0 0 0 0 0 0;0.361655390928043 0 0.0217708463553388 1.81120439254402 0 0.900267645686867 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0.0596854204267023 0 0 0 0 0 0 0 0 0 0 0 0.471570888980097 0 0 0 0 0.920738174557066 0 0 0;0 0 0 0 0 0 0 0 0.220051533000778 0 0 0 0 0 0 0 0 0 0 0 0.920738174557066 0 0 0 0;0 0 0.667747131809592 0 0.365147722552969 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.431353900603143;0 0 0 0 0.160828167983497 0 0 0 0 0.252874847836154 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.139899289183316;0 0.779096496125678 0 0 0 0 0 0 0 0.7525160069564 0 0 0 0.816798020448907 0 0 0 0 0 0 0 0 0.431353900603143 0.139899289183316 0] );\r\nassert( isequal(route,[12 14 17 21 5 11 4]) \u0026\u0026 abs( d - 2.16231 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 21, 9, [0 1.30397831279197 0 0 0 0 0 0 0.205205702932437 0 0 0 0 0.462991342326146 0 0.0919395070383298 0 0 0 0 0 0 0 0.788285106392582 0;1.30397831279197 0 0 0 0 1.05960547137835 0 0 0.153644616706166 0 0 0.860262579703983 0 0 0 0 0 0 0 0 0 0 0 0.773468224481749 0;0 0 0 0.13195985000036 0 0 0 1.51813223209895 0 0 0 0 0 0.0156327604904785 0 1.27556519583119 0.93793259222666 0 0 0 0 0 0 0 0;0 0 0.13195985000036 0 0 0 0.458734989962526 0 0 0 0 0 0 0 0 0 0 0 0.835183344604242 0.11324698880843 0 0 1.27194671889278 0 0.873215204449672;0 0 0 0 0 0 0.0522387394084536 0.441514133149768 0 0 0 0 0 0 0 0 0 0 0 0.104845115642955 0 0 0 0 0;0 1.05960547137835 0 0 0 0 0 0 0 0 0 0.323427832607934 0 0 0 0 0 0.548178891330981 0 0 0 1.78927187214965 0 0 0;0 0 0 0.458734989962526 0.0522387394084536 0 0 0.128458273651367 0 1.10447307401052 0 0 1.60635812839544 0.490059715639469 0 0 0 0 0.87297695015148 0 0 0 0.0385154612576837 0 0;0 0 1.51813223209895 0 0.441514133149768 0 0.128458273651367 0 0 0.0426997868037813 0 0 0 0.316089962309322 0.556234063736422 0 0 0 0 0 0 0 0.125426946797567 0 0.501620852747415;0.205205702932437 0.153644616706166 0 0 0 0 0 0 0 0 0 0 0 0 0 1.22841179064666 0 0.506177174936367 0 0 0 0.139674374757514 0 0 0;0 0 0 0 0 0 1.10447307401052 0.0426997868037813 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.695460494256037;0 0 0 0 0 0 0 0 0 0 0 1.09170738934842 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0.860262579703983 0 0 0 0.323427832607934 0 0 0 0 1.09170738934842 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 1.60635812839544 0 0 0 0 0 0 0 0 0 0 0 0 1.27248881503698 0 0 0 0 0.162219187624835;0.462991342326146 0 0.0156327604904785 0 0 0 0.490059715639469 0.316089962309322 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.111140488918591 0.0639936929497993;0 0 0 0 0 0 0 0.556234063736422 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0.0919395070383298 0 1.27556519583119 0 0 0 0 0 1.22841179064666 0 0 0 0 0 0 0 0.772788879713252 0 0 0 0.00743946114818939 0 0.662296573850469 0 0;0 0 0.93793259222666 0 0 0 0 0 0 0 0 0 0 0 0 0.772788879713252 0 0 0 0 0 0 0 0 0.235465388137087;0 0 0 0 0 0.548178891330981 0 0 0.506177174936367 0 0 0 0 0 0 0 0 0 0.596123003045261 0 0 0.50807778971881 0 0.192149930306311 0;0 0 0 0.835183344604242 0 0 0.87297695015148 0 0 0 0 0 0 0 0 0 0 0.596123003045261 0 1.75354812715354 0 0 0 0.230875543406997 0.402865723829543;0 0 0 0.11324698880843 0.104845115642955 0 0 0 0 0 0 0 1.27248881503698 0 0 0 0 0 1.75354812715354 0 0 0 0.286957051522517 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00743946114818939 0 0 0 0 0 0 0 0 0.12234328650336;0 0 0 0 0 1.78927187214965 0 0 0.139674374757514 0 0 0 0 0 0 0 0 0.50807778971881 0 0 0 0 0 0 0.0229366876888033;0 0 0 1.27194671889278 0 0 0.0385154612576837 0.125426946797567 0 0 0 0 0 0 0 0.662296573850469 0 0 0 0.286957051522517 0 0 0 0 0;0.788285106392582 0.773468224481749 0 0 0 0 0 0 0 0 0 0 0 0.111140488918591 0 0 0 0.192149930306311 0.230875543406997 0 0 0 0 0 0;0 0 0 0.873215204449672 0 0 0 0.501620852747415 0 0.695460494256037 0 0 0.162219187624835 0.0639936929497993 0 0 0.235465388137087 0 0.402865723829543 0 0.12234328650336 0.0229366876888033 0 0 0] );\r\nassert( isequal(route,[21 25 22 9]) \u0026\u0026 abs( d - 0.284954 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 5, 5, [0 0 0.235687387990488 0 0 0.518662908555243 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00169033754843562 1.18573193396702 0 0 0 0 0;0.235687387990488 0 0 0 0.350144748614205 0 0 0.499051956190166 0 0 0 0 0 0 0 0.428154355783706 0 0 0 0.988646147648288 0 0 0 0 0.766292681932783;0 0 0 0 0 0 0 0 0 0.306976149669423 0 0 0 0 0 0 0.148608071246878 0 0 0 0 0 0 0 0;0 0 0.350144748614205 0 0 0 0.366820040758671 0 0 0 0.947779130029861 0 0 0 0 0 0 0 0 0.781367996905263 0 0 0 0 0;0.518662908555243 0 0 0 0 0 0.28467286265608 0 0 0 0 0 0 0 0 0 0 0 0.814169013559602 0 0 0 0 0 0.514510683872373;0 0 0 0 0.366820040758671 0.28467286265608 0 0 0 0 0 0.137928171247269 0 0 0 0 0 0.581896713318172 0 0 0 1.00288388568789 0.926366539848811 0 0;0 0 0.499051956190166 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.211128675902371 0 0 0 0 0 0 0 0 0;0 0 0 0.306976149669423 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.332300868928405;0 0 0 0 0.947779130029861 0 0 0 0 0 0 0 0 0 0.140274584917356 0 0 0 0.276337784565307 0 0 0 0 0 0;0 0 0 0 0 0 0.137928171247269 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.422423933152413 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.16443124331918 0 0 0 0.113521569230241 0 0 0.431552467605628 0;0 0 0 0 0 0 0 0 0 0 0.140274584917356 0 0 0 0 0 0 1.01590071824433 0 0 0 0 0 0 0;0 0 0.428154355783706 0 0 0 0 0 0.211128675902371 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0.148608071246878 0 0 0 0 0 0 0 0 0 0.16443124331918 0 0 0 0 0 0.816401527141028 0 0 0 0 1.51727966787778;0 0 0 0 0 0 0.581896713318172 0 0 0 0 0 0 0 1.01590071824433 0 0 0 0 0 0.0315916186043663 0 0 0 0;0 0.00169033754843562 0 0 0 0.814169013559602 0 0 0 0 0.276337784565307 0 0.422423933152413 0 0 0 0 0 0 0 0 0 0 0.113122720118215 0;0 1.18573193396702 0.988646147648288 0 0.781367996905263 0 0 0 0 0 0 0 0 0 0 0 0.816401527141028 0 0 0 0 0 0 0 1.22595526329414;0 0 0 0 0 0 0 0 0 0 0 0 0 0.113521569230241 0 0 0 0.0315916186043663 0 0 0 0 0 0.0278718835255773 0;0 0 0 0 0 0 1.00288388568789 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.627233109842477 0 0;0 0 0 0 0 0 0.926366539848811 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.627233109842477 0 0.210579136296008 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0.431552467605628 0 0 0 0 0.113122720118215 0 0.0278718835255773 0 0.210579136296008 0 0;0 0 0.766292681932783 0 0 0.514510683872373 0 0 0 0.332300868928405 0 0 0 0 0 0 1.51727966787778 0 0 1.22595526329414 0 0 0 0 0] );\r\nassert( isequal(route,5) \u0026\u0026 abs( d - 0 ) \u003c 1e-4 );\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":134,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":26,"test_suite_updated_at":"2012-03-07T20:02:13.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-03-06T18:48:13.000Z","updated_at":"2026-03-30T17:22:55.000Z","published_at":"2012-03-07T20:03:56.000Z","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 a matrix that represent the distance along highways between major cities numbered 1 to\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, provide the path and shortest distance from a given city,\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\u003efrom\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, to a given city,\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\u003eto\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. Assume that 0 represents no direct path between two cities. If there is no solution to the problem, return -1 for both the path and the distance.\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":55420,"title":"Power Outages Histogram","description":"Create a function that takes power outage data as an input and creates a histogram of the number of outages as a function of Region. Note that the Region column of the power outage table contains a cell array of character vectors.\r\nRotate the x-axis tick labels by 30 degrees and label the y-axis with \"Number of Outages\".\r\nYour function should return the figure handle as output.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 424.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 212.333px; transform-origin: 407px 212.333px; 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCreate a function that takes power outage data as an input and creates a histogram of the number of outages as a function of Region. Note that the Region column of the power outage table contains a cell array of character vectors.\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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eRotate the \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ex\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e-axis tick labels by 30 degrees and label the \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ey\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e-axis with \"Number of Outages\".\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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eYour function should return the figure handle as output.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 313.667px; 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 156.833px; text-align: left; transform-origin: 384px 156.833px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"678\" height=\"308\" style=\"vertical-align: baseline;width: 678px;height: 308px\" 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function f = plotOutages(T)\r\n    f = figure; % gets the figure handle\r\n    \r\n    \r\nend","test_suite":"T = readtable(\"outages.csv\");\r\ng__  = plotOutages(T);\r\n%% Is there a histogram?\r\nassert(isequal(g__.Children.Children.Type,'categoricalhistogram'))\r\n%% Are the XTick labels rotated by 30 degrees?\r\nassert(isequal(g__.Children.XTickLabelRotation,30))\r\n%% Is the y-axis labeled correctly?\r\nassert(isequal(g__.Children.YLabel.String,\"Number of Outages\"))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":6,"created_by":140016,"edited_by":140016,"edited_at":"2022-10-10T14:27:44.000Z","deleted_by":null,"deleted_at":null,"solvers_count":217,"test_suite_updated_at":"2022-10-10T14:27:44.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2022-09-02T17:58:22.000Z","updated_at":"2026-04-03T09:09:12.000Z","published_at":"2022-10-10T14:27:44.000Z","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\u003eCreate a function that takes power outage data as an input and creates a histogram of the number of outages as a function of Region. Note that the Region column of the power outage table contains a cell array of character vectors.\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\u003eRotate the \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-axis tick labels by 30 degrees and label the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ey\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-axis with \\\"Number of Outages\\\".\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\u003eYour function should return the figure handle as output.\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=\\\"308\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"678\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" 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of Eratosthenes - 02","description":" \"Sift the Two's and Sift the Three's,\r\n  The Sieve of Eratosthenes.\r\n  When the multiples sublime,\r\n  The numbers that remain are Prime.\"  ...anonymous\r\n\r\n\r\nSieve of Eratosthenes is a simple but ingenious ancient algorithm for finding all prime numbers up to n.\r\n\r\ngiven a limit n, u've to find all the primes up to n.\r\nThe built-in prime function of matlab is restricted.","description_html":"\u003cpre\u003e \"Sift the Two's and Sift the Three's,\r\n  The Sieve of Eratosthenes.\r\n  When the multiples sublime,\r\n  The numbers that remain are Prime.\"  ...anonymous\u003c/pre\u003e\u003cp\u003eSieve of Eratosthenes is a simple but ingenious ancient algorithm for finding all prime numbers up to n.\u003c/p\u003e\u003cp\u003egiven a limit n, u've to find all the primes up to n.\r\nThe built-in prime function of matlab is restricted.\u003c/p\u003e","function_template":"function y = sieve(n)","test_suite":"%%\r\nassert(isequal(sieve(50),primes(50)))\r\n%%\r\nassert(isequal(sieve(5000),primes(5000)))\r\n%%\r\nassert(isequal(sieve(19),primes(19)))\r\n%%\r\nassert(isequal(sieve(6660),primes(6660)))\r\n%%\r\nassert(isequal(sieve(20050),primes(20050)))\r\n%%\r\nassert(isequal(sieve(200500),primes(200500)))\r\n%%\r\nfiletext = fileread('sieve.m');\r\nassert(isempty(strfind(filetext, 'primes')),'primes() forbidden')\r\nassert(isempty(strfind(filetext, 'isprime')),'isprime() forbidden')","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":363598,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":137,"test_suite_updated_at":"2020-03-16T19:32:16.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-03-16T19:27:09.000Z","updated_at":"2026-03-30T17:27:11.000Z","published_at":"2020-03-16T19:32:16.000Z","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=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ \\\"Sift the Two's and Sift the Three's,\\n  The Sieve of Eratosthenes.\\n  When the multiples sublime,\\n  The numbers that remain are Prime.\\\"  ...anonymous]]\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\u003eSieve of Eratosthenes is a simple but ingenious ancient algorithm for finding all prime numbers up to n.\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\u003egiven a limit n, u've to find all the primes up to n. The built-in prime function of matlab is restricted.\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":58389,"title":"Minimum number of crossings in a complete graph","description":"This problem is related to problem 58384.\r\nA complete graph may be drawn in different ways, such that the number of line crossings differs between drawings.\r\nTo date, the question of how to draw the graph so as to minimize the number of crossings remains unsolved.\r\nNevertheless, an upper bound can be calculated for the number of crossings, based on the number of vertices in the graph.\r\nGiven the number of vertices, n, calculate the upper bound, b, for the minimum number of line crossings in the resulting complete graph.\r\nExample:\r\nn = 6;\r\nb = 3","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 242.898px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.989px 121.449px; transform-origin: 406.996px 121.449px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThis problem is related to \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/matlabcentral/cody/problems/58384-minimum-number-of-crossings-in-a-complete-bipartite-graph\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eproblem 58384\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://en.wikipedia.org/wiki/Complete_graph\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ecomplete graph\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e may be drawn in different ways, such that the number of line crossings differs between drawings.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eTo date, the question of how to draw the graph so as to minimize the number of crossings remains unsolved.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eNevertheless, an upper bound can be calculated for the number of crossings, based on the number of vertices in the graph.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42.017px; 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: 383.991px 21.0085px; text-align: left; transform-origin: 383.999px 21.0085px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven the number of vertices, n, calculate the upper bound, b, for the minimum number of line crossings in the resulting complete graph.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.0085px; 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: 383.991px 10.4972px; text-align: left; transform-origin: 383.999px 10.5043px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eExample:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 40.8807px; 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: 403.991px 20.4403px; transform-origin: 403.999px 20.4403px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4403px; 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: 0.909091px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.909091px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.909091px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.909091px; 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: 403.991px 10.2131px; transform-origin: 403.999px 10.2202px; 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: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003en = 6;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4403px; 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: 0.909091px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.909091px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.909091px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.909091px; 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: 403.991px 10.2131px; transform-origin: 403.999px 10.2202px; 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: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eb = 3\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function b = your_fcn_name(n)\r\n  b = n;\r\nend","test_suite":"%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext,'regexp')))\r\nassert(isempty(strfind(filetext,'assign')))\r\nassert(isempty(strfind(filetext,'eval')))\r\nassert(isempty(strfind(filetext,'echo')))\r\nassert(isempty(strfind(filetext,'!')))\r\n\r\n%%\r\nn = 6;\r\nassert(isequal(your_fcn_name(n),3))\r\n\r\n%%\r\nn = 12;\r\nassert(isequal(your_fcn_name(n),150))\r\n\r\n%%\r\nn = 35;\r\nassert(isequal(your_fcn_name(n),18496))\r\n\r\n%%\r\nn = 84;\r\nassert(isequal(your_fcn_name(n),706020))\r\n\r\n%%\r\nn = 99;\r\nassert(isequal(your_fcn_name(n),1382976))\r\n\r\n%%\r\nn = 200;\r\nassert(isequal(your_fcn_name(n),24012450))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":15521,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-06-02T18:43:47.000Z","updated_at":"2026-03-03T22:13:51.000Z","published_at":"2023-06-02T18:43:46.000Z","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 problem is related to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/cody/problems/58384-minimum-number-of-crossings-in-a-complete-bipartite-graph\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eproblem 58384\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\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\u003eA \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://en.wikipedia.org/wiki/Complete_graph\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ecomplete graph\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e may be drawn in different ways, such that the number of line crossings differs between drawings.\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\u003eTo date, the question of how to draw the graph so as to minimize the number of crossings remains unsolved.\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\u003eNevertheless, an upper bound can be calculated for the number of crossings, based on the number of vertices in the graph.\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 the number of vertices, n, calculate the upper bound, b, for the minimum number of line crossings in the resulting complete graph.\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\u003eExample:\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[n = 6;\\nb = 3]]\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":45505,"title":"Square root","description":"Given x (a matrix), give back another matrix, where all the elements are the square roots of x's elements.","description_html":"\u003cp\u003eGiven x (a matrix), give back another matrix, where all the elements are the square roots of x's elements.\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [4 9;16 25];\r\ny_correct = [2 3;4 5];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [9 4;25 16];\r\ny_correct = [3 2;5 4];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1 1;1 1];\r\ny_correct = [1 1;1 1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":13,"comments_count":0,"created_by":406787,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2610,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-05-08T12:23:10.000Z","updated_at":"2026-04-15T14:41:49.000Z","published_at":"2020-05-08T12:23:10.000Z","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\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"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\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 x (a matrix), give back another matrix, where all the elements are the square roots of x's elements.\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":2,"title":"Make the vector [1 2 3 4 5 6 7 8 9 10]","description":"In MATLAB, you create a vector by enclosing the elements in square brackets like so:\r\n\r\n x = [1 2 3 4]\r\n\r\nCommas are optional, so you can also type\r\n\r\n x = [1, 2, 3, 4]\r\n\r\nCreate the vector\r\n\r\n x = [1 2 3 4 5 6 7 8 9 10]\r\n\r\nThere's a faster way to do it using MATLAB's \u003chttp://www.mathworks.com/help/techdoc/ref/colon.html colon notation\u003e.","description_html":"\u003cp\u003eIn MATLAB, you create a vector by enclosing the elements in square brackets like so:\u003c/p\u003e\u003cpre\u003e x = [1 2 3 4]\u003c/pre\u003e\u003cp\u003eCommas are optional, so you can also type\u003c/p\u003e\u003cpre\u003e x = [1, 2, 3, 4]\u003c/pre\u003e\u003cp\u003eCreate the vector\u003c/p\u003e\u003cpre\u003e x = [1 2 3 4 5 6 7 8 9 10]\u003c/pre\u003e\u003cp\u003eThere's a faster way to do it using MATLAB's \u003ca href = \"http://www.mathworks.com/help/techdoc/ref/colon.html\"\u003ecolon notation\u003c/a\u003e.\u003c/p\u003e","function_template":"function x = oneToTen\r\n  x = 0;\r\nend","test_suite":"%%\r\nx_correct = [1 2 3 4 5 6 7 8 9 10];\r\nassert(isequal(oneToTen,x_correct))","published":true,"deleted":false,"likes_count":224,"comments_count":56,"created_by":1,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":52952,"test_suite_updated_at":"2012-01-18T01:00:17.000Z","rescore_all_solutions":false,"group_id":2,"created_at":"2012-01-18T01:00:17.000Z","updated_at":"2026-04-15T11:20:05.000Z","published_at":"2012-01-18T01:00:17.000Z","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 MATLAB, you create a vector by enclosing the elements in square brackets like so:\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 = [1 2 3 4]]]\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\u003eCommas are optional, so you can also type\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 = [1, 2, 3, 4]]]\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\u003eCreate the vector\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 = [1 2 3 4 5 6 7 8 9 10]]]\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\u003eThere's a faster way to do it using MATLAB's\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://www.mathworks.com/help/techdoc/ref/colon.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ecolon 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5];\r\ny_correct = 5;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":11,"comments_count":1,"created_by":343758,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2503,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2019-10-07T17:31:43.000Z","updated_at":"2026-04-14T05:31:36.000Z","published_at":"2019-10-07T17:31:43.000Z","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\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"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\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\u003einput 1 array, calculate the length\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":1,"title":"Times 2 - START HERE","description":"Try out this test problem first.\r\n\r\nGiven the variable x as your input, multiply it by two and put the result in y.\r\n\r\nExamples:\r\n\r\n Input  x = 2\r\n Output y is 4\r\n\r\n Input  x = 17\r\n Output y is 34\r\n","description_html":"\u003cp\u003eTry out this test problem first.\u003c/p\u003e\u003cp\u003eGiven the variable x as your input, multiply it by two and put the result in y.\u003c/p\u003e\u003cp\u003eExamples:\u003c/p\u003e\u003cpre\u003e Input  x = 2\r\n Output y is 4\u003c/pre\u003e\u003cpre\u003e Input  x = 17\r\n Output y is 34\u003c/pre\u003e","function_template":"function y = times2(x) % Do not edit this line.\r\n\r\n  % Modify the line below so that the output y is twice the incoming value x\r\n\r\n  y = x;\r\n\r\n  % After you modify the code, press the \"Submit\" button, and you're on your way.\r\n\r\nend % Do not edit this line.","test_suite":"%%\r\nassert(isequal(times2(1),2));\r\n\r\n%%\r\nassert(isequal(times2(11),22));\r\n\r\n%%\r\nassert(isequal(times2(-3),-6));\r\n\r\n%%\r\nassert(isequal(times2(29),58));","published":true,"deleted":false,"likes_count":2291,"comments_count":147,"created_by":1,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":114561,"test_suite_updated_at":"2012-01-25T22:41:49.000Z","rescore_all_solutions":false,"group_id":2,"created_at":"2012-01-18T01:00:16.000Z","updated_at":"2026-04-15T17:07:06.000Z","published_at":"2012-01-18T01:00:16.000Z","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\u003eTry out this test problem first.\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\u003eGiven the variable x as your input, multiply it by two and put the result in y.\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\u003eExamples:\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[ Input  x = 2\\n Output y is 4\\n\\n Input  x = 17\\n Output y is 34]]\u003e\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":45161,"title":"Converts numbers into characters","description":"Converts numbers into characters","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 107px 8px; transform-origin: 107px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConverts numbers into characters\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n~y=x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = '1';\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":9,"comments_count":1,"created_by":343758,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2063,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2019-10-07T17:45:44.000Z","updated_at":"2026-04-15T03:14:51.000Z","published_at":"2019-10-07T17:45:44.000Z","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\u003eConverts numbers into characters\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":1339,"title":"Travelling Salesman Problem (TSP)","description":"Find a short way through given points. This is the travelling salesman problem. But the solution should be a fast and small function.\r\nhttp://en.wikipedia.org/wiki/Travelling_salesman_problem\r\nHave fun!","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: 102px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 51px; transform-origin: 407px 51px; 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=\"\"\u003eFind a short way through given points. This is the travelling salesman problem. But the solution should be a fast and small function.\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\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ehttp://en.wikipedia.org/wiki/Travelling_salesman_problem\u003c/span\u003e\u003c/span\u003e\u003c/a\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: 30.5px 8px; transform-origin: 30.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eHave fun!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = TSP(x)\r\n  y = x;\r\nend","test_suite":"%% Test 1\r\nx = [8.2 -6.9 3.2 -9.5 15.5 0.3 -4.9 7.6 4.5 -7.1 6.5 -7.5 5.6 -0.5] + i*[-4.4 3.8 7.7 -8 -1.9 16.5 2.3 6.8 6.6 -1.6 -1.2 5.5 -9.3 8.9];\r\ntic;\r\ny = TSP(x);\r\nT1 = 1e4*toc;\r\nL1 = sum(abs(diff(y)));\r\n%S = calculateSize('tsp.m')\r\nassert(isequal(y,sort(x)))\r\n\r\n%% Test 2\r\nx = 10*sin(primes(200))+10i*cos(primes(200));\r\ntic;\r\ny = TSP(x);\r\nT2 = 1e6*toc;\r\nL2 = sum(abs(diff(y)));\r\nassert(isequal(y,sort(x)))\r\n\r\n%% Test 3\r\nx = [75.5 5.43 94.73 3.89 .37 42.38 -8.5 36.72 .54 .02 83.27 47];\r\ntic;\r\ny = TSP(x(randperm(12)));\r\nT3 = 1e5*toc;\r\nL3 = sum(abs(diff(y)));\r\nassert(isequal(y,sort(x)))\r\n\r\n%assignin('caller','score',round(S +T1+L1 +T2+L2 +T3+L3));","published":true,"deleted":false,"likes_count":3,"comments_count":10,"created_by":3105,"edited_by":223089,"edited_at":"2022-09-15T06:05:23.000Z","deleted_by":null,"deleted_at":null,"solvers_count":139,"test_suite_updated_at":"2022-09-15T06:05:24.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-03-10T18:58:10.000Z","updated_at":"2026-03-30T17:25:01.000Z","published_at":"2013-03-10T19:04:41.000Z","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\u003eFind a short way through given points. This is the travelling salesman problem. But the solution should be a fast and small function.\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:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttp://en.wikipedia.org/wiki/Travelling_salesman_problem\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\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\u003eHave fun!\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":1702,"title":"Maximum value in a matrix","description":"Find the maximum value in the given matrix.\r\n\r\nFor example, if \r\n\r\n A = [1 2 3; 4 7 8; 0 9 1];\r\n\r\nthen the answer is 9.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20px; 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: normal; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"display: block; min-width: 0px; padding-top: 0px; transform-origin: 332px 56px; vertical-align: baseline; perspective-origin: 332px 56px; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind the maximum value in the given matrix.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example, if\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-bottom: 10px; margin-left: 3px; margin-right: 3px; margin-top: 10px; transform-origin: 329px 10px; perspective-origin: 329px 10px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; 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-top-left-radius: 0px; border-top-right-radius: 0px; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-height: 18px; padding-left: 4px; white-space: nowrap; \"\u003e\u003cspan style=\"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-right: 45px; min-height: 0px; padding-left: 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; perspective-origin: 0px 0px; margin-right: 45px; \"\u003e\u003cspan style=\"margin-right: 0px; \"\u003e A = [1 2 3; 4 7 8; 0 9 1];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 10px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ethen the answer is 9.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1 2 3; 4 5 6; 7 8 9];\r\ny_correct = 9;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = -10:0;\r\ny_correct = 0;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 17;\r\ny_correct = 17;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = magic(6);\r\ny_correct = 36;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [5 23 6 2 9 0 -1]';\r\ny_correct = 23;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":84,"comments_count":25,"created_by":6728,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17796,"test_suite_updated_at":"2013-07-10T18:41:46.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-07-09T04:08:24.000Z","updated_at":"2026-04-15T11:10:44.000Z","published_at":"2013-07-09T04:08:24.000Z","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\u003eFind the maximum value in the given matrix.\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, if\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[ A = [1 2 3; 4 7 8; 0 9 1];]]\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\u003ethen the answer is 9.\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":475,"title":"Is this group simply connected?","description":"Given connectivity information about a graph, your job is to figure out if the graph is fully connected. You are given a list of vertex pairs that specify undirected connectivity (edges) among vertices. Vertex labels are always positive integers.\r\n\r\nExample 1:\r\n \r\n Input  node_pairs = [ 8 9\r\n                       8 3 ]\r\n Output tf is true\r\n                       \r\nThe three nodes of this graph are fully connected, since this graph could be drawn like so:\r\n\r\n 3--8--9\r\n\r\nExample 2:\r\n\r\n Input  node_pairs = [ 1 2 \r\n                       2 3\r\n                       1 4\r\n                       3 4\r\n                       5 6 ]\r\n Output tf is false\r\n\r\nThis graph could be drawn like so:\r\n\r\n 1--2  5--6\r\n |  |\r\n 4--3\r\n\r\nThere are two distinct subgraphs.","description_html":"\u003cp\u003eGiven connectivity information about a graph, your job is to figure out if the graph is fully connected. You are given a list of vertex pairs that specify undirected connectivity (edges) among vertices. Vertex labels are always positive integers.\u003c/p\u003e\u003cp\u003eExample 1:\u003c/p\u003e\u003cpre\u003e Input  node_pairs = [ 8 9\r\n                       8 3 ]\r\n Output tf is true\u003c/pre\u003e\u003cp\u003eThe three nodes of this graph are fully connected, since this graph could be drawn like so:\u003c/p\u003e\u003cpre\u003e 3--8--9\u003c/pre\u003e\u003cp\u003eExample 2:\u003c/p\u003e\u003cpre\u003e Input  node_pairs = [ 1 2 \r\n                       2 3\r\n                       1 4\r\n                       3 4\r\n                       5 6 ]\r\n Output tf is false\u003c/pre\u003e\u003cp\u003eThis graph could be drawn like so:\u003c/p\u003e\u003cpre\u003e 1--2  5--6\r\n |  |\r\n 4--3\u003c/pre\u003e\u003cp\u003eThere are two distinct subgraphs.\u003c/p\u003e","function_template":"function tf = isConnected(node_pairs)\r\n  tf = true;\r\nend","test_suite":"%%\r\n\r\nnode_pairs = [8 9; 8 3];\r\ntf = true;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n%%\r\n\r\nnode_pairs = [ 1 2;\r\n               2 3;\r\n               1 4;\r\n               3 4;\r\n               5 6 ];\r\ntf = false;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n%%\r\n\r\nnode_pairs = [ 1 2;\r\n               2 3;\r\n               1 4;\r\n               3 4;\r\n               5 6;\r\n               6 2 ];\r\ntf = true;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n%%\r\n\r\nnode_pairs = [ 1 2; 2 100];\r\ntf = true;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n\r\n%%\r\n\r\nnode_pairs = [ 1 2; 50 100];\r\ntf = false;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n\r\n%%\r\n\r\nnode_pairs = [ 4 17 ];\r\ntf = true;\r\nassert(isequal(isConnected(node_pairs),tf))\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":2,"created_by":7,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":36,"test_suite_updated_at":"2012-03-09T22:15:16.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-03-09T22:05:26.000Z","updated_at":"2026-03-03T23:05:27.000Z","published_at":"2012-03-12T16:23:04.000Z","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 connectivity information about a graph, your job is to figure out if the graph is fully connected. You are given a list of vertex pairs that specify undirected connectivity (edges) among vertices. Vertex labels are always positive integers.\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 1:\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[ Input  node_pairs = [ 8 9\\n                       8 3 ]\\n Output tf is true]]\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 three nodes of this graph are fully connected, since this graph could be drawn like so:\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[ 3--8--9]]\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 2:\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[ Input  node_pairs = [ 1 2 \\n                       2 3\\n                       1 4\\n                       3 4\\n                       5 6 ]\\n Output tf is false]]\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\u003eThis graph could be drawn like so:\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--2  5--6\\n |  |\\n 4--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\u003eThere are two distinct subgraphs.\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":52799,"title":"Plotting Practice","description":"Plot cos(x) vs x as shown in the figure below. Include the appropriate title, x-label, and y-label. Note, it is case sensitive. Make sure the colors of the axes, markers, and lines are correct. The markers should be square with magenta edges and a cyan face. The plot line should be dashed and red. The axes background should be yellow. The marker size should be 5.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 751.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 375.833px; transform-origin: 406.5px 375.833px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 383.5px 375.833px; text-align: left; transform-origin: 383.5px 375.833px; 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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ePlot cos(x) vs x as shown in the figure below. Include the appropriate title, x-label, and y-label. Note, it is case sensitive. Make sure the colors of the axes, markers, and lines are correct. The markers should be square with magenta edges and a cyan face. The plot line should be dashed and red. The axes background should be yellow. The marker size should be 5.\u003c/span\u003e\u003c/span\u003e\u003cimg class=\"imageNode\" width=\"878\" height=\"683\" style=\"vertical-align: baseline;width: 878px;height: 683px\" 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\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n  figure\r\n\r\n  % Do not edit below here\r\n  h = gca;\r\n  y = {h.Title.String;h.XLabel.String;h.YLabel.String;h.Color;h.Children.YData;h.Children.XData;h.Children.Color;h.Children.MarkerFaceColor';h.Children.MarkerEdgeColor;h.Children.MarkerSize};\r\nend","test_suite":"%%\r\nx = 1:100;\r\nfigure\r\nplot(x,cos(x),'sr--','MarkerFaceColor','c','MarkerEdgeColor','m','MarkerSize',5);\r\nxlabel('Time (s)')\r\nylabel('Amplitude (mV)')\r\ntitle('Cosine Signal')\r\nset(gca,'color','y')\r\nh=gca;\r\ny_correct = {h.Title.String;h.XLabel.String;h.YLabel.String;h.Color;h.Children.YData;h.Children.XData;h.Children.Color;h.Children.MarkerFaceColor';h.Children.MarkerEdgeColor;h.Children.MarkerSize}\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":1375684,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":630,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-09-26T03:55:24.000Z","updated_at":"2026-04-11T16:25:21.000Z","published_at":"2021-09-26T03:58:09.000Z","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\u003ePlot cos(x) vs x as shown in the figure below. Include the appropriate title, x-label, and y-label. Note, it is case sensitive. Make sure the colors of the axes, markers, and lines are correct. The markers should be square with magenta edges and a cyan face. The plot line should be dashed and red. The axes background should be yellow. 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A the inverse of B?","description":"Given a matrix A and a matrix B, is A the inverse of B?\r\n\r\n  \r\n\r\n  \u003e\u003eA=[2,4;3,5];\r\n  \r\n  \u003e\u003eB=[-2.5,2;1.5,-1];\r\n  \r\n  \u003e\u003eisInverse(A,B)\r\n  \r\n  ans = 1\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: 174.033px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 87.0167px; transform-origin: 407px 87.0167px; vertical-align: baseline; \"\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: 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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: 28px 8.5px; transform-origin: 28px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans = 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = isInverse(x,y)\r\n  y = x;\r\nend","test_suite":"%%\r\nA=[2,4;3,5];\r\nB=[-2.5,2;1.5,-1];\r\ny_correct = 1;\r\nassert(isequal(isInverse(A,B),y_correct))\r\n\r\n%%\r\nA=[1,2;3,5];\r\nB=[-5,2;3,-1];\r\ny_correct = 1;\r\nassert(isequal(isInverse(A,B),y_correct))\r\n\r\n%%\r\nA=[1,2;3,4];\r\nB=[4 3; 2 1];\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=[1,1;1,1];\r\nB=[0 0; 0 0];\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=1;\r\nB=1;\r\nassert(isequal(isInverse(A,B),1))\r\n\r\n%%\r\nA=spiral(3);\r\nB=eye(3);\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=magic(5);\r\nB=ones(5);\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=eye(7);\r\nB=eye(7);\r\nassert(isequal(isInverse(A,B),1))\r\n\r\n%%\r\nA=[1 2 3;2 1 2;3 2 1] %Toeplitz matrix\r\nB=[-0.375 0.5 0.125; 0.5 -1 0.5; 0.125 0.5 -0.375];\r\nassert(isequal(isInverse(A,B),1))\r\n\r\n%%\r\nA=meshgrid(1:4);\r\nB=fliplr(meshgrid(1:4));\r\nassert(isequal(isInverse(A,B),0))\r\n\r\n%%\r\nA=hadamard(8);\r\nB=hadamard(8)/8;\r\nassert(isequal(isInverse(A,B),1))","published":true,"deleted":false,"likes_count":15,"comments_count":12,"created_by":1103,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":1351,"test_suite_updated_at":"2021-05-14T10:50:59.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-04-01T04:32:36.000Z","updated_at":"2026-04-14T07:37:30.000Z","published_at":"2012-04-21T21:38:35.000Z","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\u003eGiven a matrix A and a matrix B, is A the inverse of B?\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[\u003e\u003eA=[2,4;3,5];\\n\\n\u003e\u003eB=[-2.5,2;1.5,-1];\\n\\n\u003e\u003eisInverse(A,B)\\n\\nans = 1]]\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":2730,"title":"Graph Algorithms 3: Number of Connected Components","description":"Given an adjacency matrix of a simple undirected graph, find the number of connected components.","description_html":"\u003cp\u003eGiven an adjacency matrix of a simple undirected graph, find the number of connected components.\u003c/p\u003e","function_template":"function y = cComponents(x)\r\n  y = x;\r\nend","test_suite":"%%\r\na = ones(3) - eye(3);\r\nb = zeros(3);\r\nmat = [a b; b a];\r\nn = 2;\r\nassert(isequal(cComponents(mat),n))\r\n\r\n\r\n%%\r\na = randi(20);\r\nmat = ones(a) - eye(a);\r\nn = 1;\r\nassert(isequal(cComponents(mat),n))\r\n\r\n\r\n%%\r\nmat = [0 1 0 0 1;\r\n       1 0 1 0 0;\r\n       0 1 0 1 0;\r\n       0 0 1 0 1;\r\n       1 0 0 1 0];\r\nassert(isequal(cComponents(mat),1))\r\n\r\n\r\n%%\r\na = ones(3) - eye(3);\r\nb = zeros(3);\r\nmat = [a b b; b a b; b b a];\r\nn = 3;\r\nassert(isequal(cComponents(mat),n))\r\n\r\n\r\n%%\r\na = ones(3) - eye(3);\r\nb = zeros(3);\r\np = floor((randi(20)+3)/3)*3;\r\nmat = [];\r\nfor i= 1:p\r\n    c = [repmat(b,1,i-1) a repmat(b,1,p-i)];\r\n    mat = [mat;c];\r\nend\r\n\r\nassert(isequal(cComponents(mat),p))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":17203,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":40,"test_suite_updated_at":"2014-12-07T06:39:46.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-12-06T07:19:29.000Z","updated_at":"2026-03-30T17:12:13.000Z","published_at":"2014-12-06T07:19:28.000Z","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\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"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\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 an adjacency matrix of a simple undirected graph, find the number of connected components.\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":2685,"title":"FloydWarshall","description":"Our task is to find shortest paths between every pair of nodes. Floyd-Warshall is a graph algorithm for finding shortest paths in weighted graph. The input of a function will be in weighted adjacency matrix representation. If two vertices does not have any edge than this matrix has Inf value. Function will return a matrix with values of shortest paths between each pair of nodes.\r\nExample :\r\n input= [0   1  Inf Inf \r\n        Inf  0   2  Inf\r\n        Inf Inf  0   3\r\n         4   7  Inf  0]\r\n\r\n output= [0   1   3   6\r\n          9   0   2   5\r\n          7   8   0   3\r\n          4   5   7   0]","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: 307.9px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 153.95px; transform-origin: 407px 153.95px; 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\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: 372.5px 8px; transform-origin: 372.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOur task is to find shortest paths between every pair of nodes. Floyd-Warshall is a graph algorithm for finding shortest paths in weighted graph. The input of a function will be in weighted adjacency matrix representation. If two vertices does not have any edge than this matrix has Inf value. Function will return a matrix with values of shortest paths between each pair of nodes.\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: 29.5px 8px; transform-origin: 29.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExample\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; 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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: 96px 8.5px; tab-size: 4; transform-origin: 96px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e input= [0   1  Inf Inf \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; 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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: 92px 8.5px; tab-size: 4; transform-origin: 92px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e        Inf  0   2  Inf\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; 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white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e          9   0   2   5\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: 92px 8.5px; tab-size: 4; transform-origin: 92px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e          7   8   0   3\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: 96px 8.5px; tab-size: 4; transform-origin: 96px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e          4   5   7   0]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = floydwarshall(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [0   1  Inf Inf;\r\n    Inf  0   2  Inf;\r\n    Inf Inf  0   3\r\n     4   7  Inf  0];\r\ny_correct = [0   1   3   6;\r\n             9   0   2   5;\r\n             7   8   0   3;\r\n             4   5   7   0];\r\nassert(isequal(floydwarshall(x),y_correct))\r\n\r\n%%\r\nx = [0   8  Inf  1;\r\n    Inf  0   1  Inf;\r\n     4  Inf  0  Inf;\r\n    Inf  2   9   0];\r\ny_correct = [0   3   4   1\r\n             5   0   1   6\r\n             4   7   0   5\r\n             7   2   3   0];\r\nassert(isequal(floydwarshall(x),y_correct))\r\n\r\n%%\r\nx = [0   3   6  Inf Inf Inf Inf\r\n     3   0   2   1  Inf Inf Inf\r\n     6   2   0   1   4   2  Inf\r\n    Inf  1   1   0   2  Inf  4\r\n    Inf Inf  4   2   0   2   1\r\n    Inf Inf  2  Inf  2   0   1\r\n    Inf Inf Inf  4   1   1   0];\r\ny_correct = [0 3 5 4 6 7 7\r\n            3 0 2 1 3 4 4\r\n            5 2 0 1 3 2 3\r\n            4 1 1 0 2 3 3\r\n            6 3 3 2 0 2 1\r\n            7 4 2 3 2 0 1\r\n            7 4 3 3 1 1 0];\r\nassert(isequal(floydwarshall(x),y_correct))\r\n\r\n%%\r\nx = [0   3  Inf  5;\r\n     2   0  Inf  4;\r\n    Inf  1   0  Inf;\r\n    Inf Inf  2   0];\r\ny_correct = [0 3 7 5\r\n             2 0 6 4\r\n             3 1 0 5\r\n             5 3 2 0];\r\nassert(isequal(floydwarshall(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":32478,"edited_by":223089,"edited_at":"2023-01-03T06:19:00.000Z","deleted_by":null,"deleted_at":null,"solvers_count":33,"test_suite_updated_at":"2023-01-03T06:19:00.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-11-23T22:43:29.000Z","updated_at":"2026-04-13T12:21:23.000Z","published_at":"2014-11-23T22:44:41.000Z","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\u003eOur task is to find shortest paths between every pair of nodes. Floyd-Warshall is a graph algorithm for finding shortest paths in weighted graph. The input of a function will be in weighted adjacency matrix representation. If two vertices does not have any edge than this matrix has Inf value. Function will return a matrix with values of shortest paths between each pair of nodes.\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\u003eExample\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[ input= [0   1  Inf Inf \\n        Inf  0   2  Inf\\n        Inf Inf  0   3\\n         4   7  Inf  0]\\n\\n output= [0   1   3   6\\n          9   0   2   5\\n          7   8   0   3\\n          4   5   7   0]]]\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":2372,"title":"Determine connected components of a graph","description":"Adjacency matrix of an undirected graph is given. Return the number of connected components in the graph.","description_html":"\u003cp\u003eAdjacency matrix of an undirected graph is given. Return the number of connected components in the graph.\u003c/p\u003e","function_template":"function y = conctCom(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx=[0 1 0 0 0; 1 0 1 1 0; 0 1 0 1 1; 0 1 1 0 1; 0 0 1 1 0];\r\ny_correct = 1;\r\nassert(isequal(conctCom(x),y_correct))\r\n\r\n%%\r\nx=[0 1 0 0 0; 1 0 0 0 0;0 0 0 1 0;0 0 1 0 1;0 0 0 1 0];\r\ny_correct = 2;\r\nassert(isequal(conctCom(x),y_correct))\r\n\r\n%%\r\nx=[0 1 0 0 0 0 ; \r\n1 0 0 0 0 0; \r\n0 0 0 1 0 0; \r\n0 0 1 0 0 0 ; \r\n0 0 0  0 0 1; \r\n0 0 0 0 1 0];\r\ny_correct = 3;\r\nassert(isequal(conctCom(x),y_correct))\r\n\r\n%%\r\nx=1;\r\ny_correct = 1;\r\nassert(isequal(conctCom(x),y_correct))\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":2,"created_by":17203,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":62,"test_suite_updated_at":"2014-06-18T16:25:21.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-06-18T07:37:21.000Z","updated_at":"2026-04-13T12:06:37.000Z","published_at":"2014-06-18T07:37:54.000Z","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\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"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\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\u003eAdjacency matrix of an undirected graph is given. Return the number of connected components in the graph.\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":1169,"title":"Count the Number of Directed Cycles in a Graph","description":"Given an asymmetric adjacency matrix, determine the number of unique directed cycles.\r\nFor example, the graph represented by adjacency matrix\r\nA = [\r\n  0 1 1 0;\r\n  1 1 0 1;\r\n  1 0 0 1;\r\n  1 1 0 0];\r\nhas 7 cycles. They are:\r\n[2 -\u003e 2]\r\n[1 -\u003e 2 -\u003e 1]\r\n[1 -\u003e 3 -\u003e 1]\r\n[2 -\u003e 4 -\u003e 2]\r\n[1 -\u003e 2 -\u003e 4 -\u003e 1]\r\n[1 -\u003e 3 -\u003e 4 -\u003e 1]\r\n[1 -\u003e 3 -\u003e 4 -\u003e 2 -\u003e 1]\r\nThe input is an adjacency matrix of 0s and 1s, and the output should be the number of unique (simple) directed cycles in the graph.","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: 399.2px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 199.6px; transform-origin: 407px 199.6px; vertical-align: baseline; \"\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: 225.5px 8px; transform-origin: 225.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven an asymmetric adjacency matrix, determine the number of unique\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: 2px 8px; transform-origin: 2px 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: 29.5px 8px; transform-origin: 29.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003edirected\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: 23.5px 8px; transform-origin: 23.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cycles.\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: 178px 8px; transform-origin: 178px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, the graph represented by adjacency matrix\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; 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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: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eA = [\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: 40px 8.5px; tab-size: 4; transform-origin: 40px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  0 1 1 0;\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: 40px 8.5px; tab-size: 4; transform-origin: 40px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  1 1 0 1;\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: 40px 8.5px; tab-size: 4; transform-origin: 40px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  1 0 0 1;\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: 44px 8.5px; tab-size: 4; transform-origin: 44px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e  1 1 0 0];\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: 73.5px 8px; transform-origin: 73.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ehas 7 cycles. They are:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 143.033px; 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 71.5167px; transform-origin: 404px 71.5167px; 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: 32px 8.5px; tab-size: 4; transform-origin: 32px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[2 -\u0026gt; 2]\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: 52px 8.5px; tab-size: 4; transform-origin: 52px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 2 -\u0026gt; 1]\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: 52px 8.5px; tab-size: 4; transform-origin: 52px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 3 -\u0026gt; 1]\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: 52px 8.5px; tab-size: 4; transform-origin: 52px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[2 -\u0026gt; 4 -\u0026gt; 2]\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: 72px 8.5px; tab-size: 4; transform-origin: 72px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 2 -\u0026gt; 4 -\u0026gt; 1]\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: 72px 8.5px; tab-size: 4; transform-origin: 72px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 3 -\u0026gt; 4 -\u0026gt; 1]\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: 92px 8.5px; tab-size: 4; transform-origin: 92px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e[1 -\u0026gt; 3 -\u0026gt; 4 -\u0026gt; 2 -\u0026gt; 1]\u003c/span\u003e\u003c/span\u003e\u003c/div\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: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; 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: 380.5px 8px; transform-origin: 380.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe input is an adjacency matrix of 0s and 1s, and the output should be the number of unique (simple) directed cycles in the graph.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function nCycles = count_directed_cycles(A)\r\n  nCycles = 0;\r\nend","test_suite":"%%\r\nA = [\r\n  0 1 1 0\r\n  1 1 0 1\r\n  1 0 0 1\r\n  1 1 0 0];\r\nnCycles = 7;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n  0 1 0 1 0 1 0 0\r\n  0 0 0 1 1 0 1 1\r\n  1 1 0 1 1 0 1 1\r\n  0 1 0 0 1 0 1 0\r\n  1 1 0 0 1 0 1 0\r\n  1 0 0 0 0 0 1 0\r\n  1 1 1 1 0 0 0 1\r\n  0 0 0 1 1 1 1 1];\r\nnCycles = 197;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n  1 0 1 0 0 1 1 0 1 1\r\n  1 0 1 0 1 1 1 1 1 1\r\n  0 0 1 0 0 1 1 1 1 1\r\n  0 1 0 0 0 0 0 0 1 1\r\n  0 0 1 0 1 0 1 1 1 0\r\n  1 1 1 0 0 0 0 1 0 0\r\n  0 0 0 1 0 1 1 0 1 0\r\n  1 0 1 1 0 0 0 0 1 0\r\n  1 0 0 0 0 0 1 0 0 1\r\n  1 0 0 0 0 0 0 0 1 0];\r\nnCycles = 744;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n  0 0 0 0 1 0 1 1 1 1\r\n  0 0 0 1 0 1 0 1 1 1\r\n  0 0 0 0 0 0 1 1 1 1\r\n  0 0 1 0 1 1 0 1 0 0\r\n  0 1 0 1 0 0 0 0 0 1\r\n  1 0 0 1 1 1 1 0 1 1\r\n  0 1 1 1 1 0 1 1 0 1\r\n  0 1 0 0 1 1 0 0 0 1\r\n  1 0 1 0 0 1 1 0 1 1\r\n  1 0 1 1 0 1 1 0 0 0];\r\nnCycles = 4961;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n    0 1 1 0 0 0 1 0\r\n    1 0 0 0 1 1 1 1\r\n    0 0 0 0 0 1 0 1\r\n    1 1 0 0 1 1 1 0\r\n    1 1 0 0 0 0 0 1\r\n    0 0 1 0 1 0 0 0\r\n    0 1 0 0 0 1 0 1\r\n    0 0 1 1 0 1 0 0];\r\nnCycles = 116;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n    0 1 0 1 1 1 0 0 1 0\r\n    1 0 0 1 1 0 1 0 0 1\r\n    0 1 1 0 1 0 0 0 1 1\r\n    0 1 1 0 1 1 0 0 1 0\r\n    1 0 0 0 0 1 1 0 0 1\r\n    0 1 1 0 0 1 0 0 0 1\r\n    0 1 1 0 1 0 1 1 1 1\r\n    1 1 1 0 0 0 0 0 1 1\r\n    1 1 1 0 1 1 1 1 0 1\r\n    0 0 1 1 1 0 1 0 1 0];\r\nnCycles = 5888;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n\r\n%%\r\nA = [\r\n    0 0 0 1 1 0 1 0 1 1 0 0\r\n    0 0 1 1 1 0 0 0 0 0 0 1\r\n    1 0 1 0 0 0 1 1 1 0 1 1\r\n    1 0 1 1 0 0 0 0 1 0 0 0\r\n    1 1 1 0 1 0 0 0 1 0 1 0\r\n    0 1 0 1 0 0 0 0 1 1 0 0\r\n    1 1 1 1 1 0 1 0 1 0 1 0\r\n    0 1 0 1 0 0 1 1 1 1 1 1\r\n    0 1 0 1 1 0 0 1 0 1 1 0\r\n    0 1 1 1 1 1 0 0 0 1 1 0\r\n    1 1 1 1 0 0 1 1 0 0 0 0\r\n    0 1 1 1 1 1 1 1 0 0 0 1];\r\nnCycles = 50093;\r\nassert(isequal(count_directed_cycles(A),nCycles))\r\n","published":true,"deleted":false,"likes_count":5,"comments_count":0,"created_by":1057,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":28,"test_suite_updated_at":"2021-12-31T15:51:58.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-04T13:38:03.000Z","updated_at":"2026-04-13T12:20:06.000Z","published_at":"2013-01-04T13:48:40.000Z","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\u003eGiven an asymmetric adjacency matrix, determine the number of unique\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\u003edirected\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cycles.\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, the graph represented by adjacency matrix\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[A = [\\n  0 1 1 0;\\n  1 1 0 1;\\n  1 0 0 1;\\n  1 1 0 0];]]\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\u003ehas 7 cycles. They are:\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[[2 -\u003e 2]\\n[1 -\u003e 2 -\u003e 1]\\n[1 -\u003e 3 -\u003e 1]\\n[2 -\u003e 4 -\u003e 2]\\n[1 -\u003e 2 -\u003e 4 -\u003e 1]\\n[1 -\u003e 3 -\u003e 4 -\u003e 1]\\n[1 -\u003e 3 -\u003e 4 -\u003e 2 -\u003e 1]]]\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 input is an adjacency matrix of 0s and 1s, and the output should be the number of unique (simple) directed cycles in the graph.\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":458,"title":"Parcel Routing","description":"Given a matrix that represent the distance along highways between major cities numbered 1 to _N_, provide the path and shortest distance from a given city, _from_, to a given city, _to_. Assume that 0 represents no direct path between two cities. If there is no solution to the problem, return -1 for both the path and the distance.","description_html":"\u003cp\u003eGiven a matrix that represent the distance along highways between major cities numbered 1 to \u003ci\u003eN\u003c/i\u003e, provide the path and shortest distance from a given city, \u003ci\u003efrom\u003c/i\u003e, to a given city, \u003ci\u003eto\u003c/i\u003e. Assume that 0 represents no direct path between two cities. If there is no solution to the problem, return -1 for both the path and the distance.\u003c/p\u003e","function_template":"function [route d] = parcel_route( from, to, graph )\r\n  route = -1;\r\n  d = -1;\r\nend","test_suite":"%%\r\n[route d] = parcel_route( 1, 5, zeros( 5 ) )\r\nassert(route == -1 \u0026\u0026 d == -1);\r\n\r\n%%\r\n[route d] = parcel_route( 1, 2, [0 0.320527862039621 0 0 0;0.320527862039621 0 0 0 0.85044688801616;0 0 0 0 0;0 0 0 0 0;0 0.85044688801616 0 0 0] );\r\nassert( isequal(route,[1 2]) \u0026\u0026 abs( d - 0.320528 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 4, 2, [0 0 0 0 0.648056184801628;0 0 0.168504735306137 0 0;0 0.168504735306137 0 0 0;0 0 0 0 0;0.648056184801628 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 3, 3, [0 0 0 1.07077622171054 0.00497624606093106;0 0 0 0 0;0 0 0 0 0;1.07077622171054 0 0 0 0;0.00497624606093106 0 0 0 0] );\r\nassert( isequal(route,3) \u0026\u0026 abs( d - 0 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 5, 2, [0 0 0.478447257684744 0.52778921303553 0;0 0 0 0.344727452766697 0;0.478447257684744 0 0 0 0;0.52778921303553 0.344727452766697 0 0 0;0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 1, 4, [0 0 0 0 0;0 0 0 0 0;0 0 0 0 0;0 0 0 0 0;0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 10, 5, [0 0 0 0 0.758920911298127 1.17184862472796 0 0 0 0;0 0 0 0.229051389055984 0 0 0.110344033764499 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0.229051389055984 0 0 0 0 0 0 0 0;0.758920911298127 0 0 0 0 0 0.582786870390757 0 0 0.266149081187709;1.17184862472796 0 0 0 0 0 0.91437757836659 0 0 0.928664694998184;0 0.110344033764499 0 0 0.582786870390757 0.91437757836659 0 0.72845914907191 0.440667818657679 0.0752998054887686;0 0 0 0 0 0 0.72845914907191 0 0 0;0 0 0 0 0 0 0.440667818657679 0 0 0.72584117080215;0 0 0 0 0.266149081187709 0.928664694998184 0.0752998054887686 0 0.72584117080215 0] );\r\nassert( isequal(route,[10 5]) \u0026\u0026 abs( d - 0.266149 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 7, 3, [0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0.348270614748404 0 0.963402246386651 0 0 0 0;0 0 0.348270614748404 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.00647302663148808 0 0;0 0 0.963402246386651 0 0 0 0 1.11338837090812 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0.00647302663148808 1.11338837090812 0 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 4, 7, [0 0 0.529236850857286 0 0 0 1.60144982503606 0 0 0;0 0 0 0 0 0 0.828441215877115 0 0 0;0.529236850857286 0 0 0.0279102825979989 0 0 0 0 0 0.0544746812572747;0 0 0.0279102825979989 0 0 0 0 0 0 0;0 0 0 0 0 1.04094484718858 0 0 0 0;0 0 0 0 1.04094484718858 0 0 0 0 0.124040053577104;1.60144982503606 0.828441215877115 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.37043522751259;0 0 0.0544746812572747 0 0 0.124040053577104 0 0 0.37043522751259 0] );\r\nassert( isequal(route,[4 3 1 7]) \u0026\u0026 abs( d - 2.1586 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 4, 7, [0 0 0 0 0 0 0 0 0 0;0 0 0 0 0.577543761888686 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0.124487323633357 0 0 0.679813903514902;0 0.577543761888686 0 0 0 0 0.560623889702786 0 0 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0.124487323633357 0.560623889702786 0 0 0 0.250828758360099 0;0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0.250828758360099 0 0 0.914651700028183;0 0 0 0.679813903514902 0 0 0 0 0.914651700028183 0] );\r\nassert( isequal(route,[4 7]) \u0026\u0026 abs( d - 0.124487 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 1, 9, [0 0 0.210714289971845 0 0 0.655795786759233 0 0 0.417975370686535 0.0762383289683841;0 0 0 0 0 0 0 0 0 0;0.210714289971845 0 0 0 0 0 0.627639413184948 0.546973506820504 0 0;0 0 0 0 0 0.44290978142888 0 0 0 0;0 0 0 0 0 0 0.494959375382896 0.199417369123429 0.61193318690704 0;0.655795786759233 0 0 0.44290978142888 0 0 0 0 0.295901565877421 0;0 0 0.627639413184948 0 0.494959375382896 0 0 0 0 0;0 0 0.546973506820504 0 0.199417369123429 0 0 0 0 0.882898432991531;0.417975370686535 0 0 0 0.61193318690704 0.295901565877421 0 0 0 0.0999710063468799;0.0762383289683841 0 0 0 0 0 0 0.882898432991531 0.0999710063468799 0] );\r\nassert( isequal(route,[1 10 9]) \u0026\u0026 abs( d - 0.176209 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 12, 3, [0 0.139438875035701 0.112367141305958 0 0 0 0 0 0 0.742115072015769 0 0 0.244537467584915 0 0;0.139438875035701 0 0.135942047224331 0 0 0 0 0 0 0 0.374140881779805 0 0.217860680093506 0.379818098539566 1.17229854239237;0.112367141305958 0.135942047224331 0 0 0 0 0 1.7792137360137 0.350752848520651 0 0 0.284985494377118 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.161446305533344 0 0 0 0.183948436622344 0 0 0;0 0 1.7792137360137 0 0 0 0.161446305533344 0 0 0 0 0 0 0 0;0 0 0.350752848520651 0 0 0 0 0 0 0 0 0 0 0 0.362973369969354;0.742115072015769 0 0 0 0 0 0 0 0 0 0.263865914379949 0 0 0 0;0 0.374140881779805 0 0 0 0 0 0 0 0.263865914379949 0 0 0 0 0;0 0 0.284985494377118 0 0 0 0.183948436622344 0 0 0 0 0 0 0 0;0.244537467584915 0.217860680093506 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0.379818098539566 0 0 0 0 0 0 0 0 0 0 0 0 1.863621808387;0 1.17229854239237 0 0 0 0 0 0 0.362973369969354 0 0 0 0 1.863621808387 0] );\r\nassert( isequal(route,[12 3]) \u0026\u0026 abs( d - 0.284985 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 14, 13, [0 0 0 0.0850075668378245 0 0 0 0 0.0463952689981919 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0.0850075668378245 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.831785345865625 0 0 0 0 0 0 0 0.300824537605104 0;0 0 0 0 0.831785345865625 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.316676635592728 0 0 0.18465657297998 0 0;0.0463952689981919 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.316676635592728 0 0 0 0 0 0 2.01596808102817;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0.735349103904233 0 0;0 0 0 0 0 0 0 0.18465657297998 0 0 0 0.735349103904233 0 0 0;0 0 0 0 0.300824537605104 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 2.01596808102817 0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 8, 8, [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.669844066951192 0 0 1.79425332134151 0 0 0 0;0 0 0 0 0 0.354813543185228 0.350829365088585 0.334017411457367 0 0 0.750194269879854 0 0 0 0.837083783283494;0 0 0 0 0 0 0 0 0 0 0 0.7666462425288 0 0 0;0 0 0 0 0 0 0 0 0 0 0.335432927184154 0.290662441159473 0 0 0;0 0 0.354813543185228 0 0 0 0 0 0 0 0 0.612746104915618 0 1.3702409817804 0;0 0 0.350829365088585 0 0 0 0 0 0 0 0 0 0 0 0;0 0.669844066951192 0.334017411457367 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 1.79425332134151 0.750194269879854 0 0.335432927184154 0 0 0 0 0 0 0 0 0 0;0 0 0 0.7666462425288 0.290662441159473 0.612746104915618 0 0 0 0 0 0 0.600235691901178 0 0;0 0 0 0 0 0 0 0 0 0 0 0.600235691901178 0 0 0;0 0 0 0 0 1.3702409817804 0 0 0 0 0 0 0 0 0.25725306655894;0 0 0.837083783283494 0 0 0 0 0 0 0 0 0 0 0.25725306655894 0] );\r\nassert( isequal(route,8) \u0026\u0026 abs( d - 0 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 9, 2, [0 0 0 0 0 0 0 0.216161539093326 0 0 0 0 0 0 0;0 0 0 0.154899548332433 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0.195632123891572 0 0.638112022611646 0 0;0 0.154899548332433 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.924920233869358 0 0 0 0 0 0 0.225753938901222;0 0 0 0 0 0 0 0 0 0 0 0.105130198814148 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0.216161539093326 0 0 0 0.924920233869358 0 0 0 0.283480661544537 0 0 0 0 0 0;0 0 0 0 0 0 0 0.283480661544537 0 0 0.860820315822094 0 0 0.114189406386242 0;0 0 0 0 0 0 0 0 0 0 0.777006911310097 0.0395282910845656 0.559642782958394 0.0374763085984708 0;0 0 0.195632123891572 0 0 0 0 0 0.860820315822094 0.777006911310097 0 0.107327989339846 0 0 0;0 0 0 0 0 0.105130198814148 0 0 0 0.0395282910845656 0.107327989339846 0 0 0 0;0 0 0.638112022611646 0 0 0 0 0 0 0.559642782958394 0 0 0 0 0;0 0 0 0 0 0 0 0 0.114189406386242 0.0374763085984708 0 0 0 0 0;0 0 0 0 0.225753938901222 0 0 0 0 0 0 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 6, 8, [0 1.00600776349789 0 0 0.409642943366229 0 0 0 0 0 0 0 0.780942905018081 0.218269812307052 0;1.00600776349789 0 0 0 0 0 0 0 0 0.604439587022491 0 0 0 0 0;0 0 0 2.19497071462911 0 0.384068674620751 0 0 0 0.752596352506117 0.210553220187945 0 0 0 0.101200876472261;0 0 2.19497071462911 0 0 0 0 0 0 0 0 0.0821684991109088 0 0 1.39540244685607;0.409642943366229 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.384068674620751 0 0 0 0.0278385656290563 0 0 0 0 0 0 0 0;0 0 0 0 0 0.0278385656290563 0 0 0 0 0.314664537582249 0 0 0 0.157551652892199;0 0 0 0 0 0 0 0 0 0 1.37753279184511 0 0 0.647734508061038 0.538120114299927;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0.604439587022491 0.752596352506117 0 0 0 0 0 0 0 0.38099752988379 0 0 0 0;0 0 0.210553220187945 0 0 0 0.314664537582249 1.37753279184511 0 0.38099752988379 0 0 0 0 0;0 0 0 0.0821684991109088 0 0 0 0 0 0 0 0 0.724941186609613 0 0;0.780942905018081 0 0 0 0 0 0 0 0 0 0 0.724941186609613 0 0 0;0.218269812307052 0 0 0 0 0 0 0.647734508061038 0 0 0 0 0 0 0;0 0 0.101200876472261 1.39540244685607 0 0 0.157551652892199 0.538120114299927 0 0 0 0 0 0 0] );\r\nassert( isequal(route,[6 7 15 8]) \u0026\u0026 abs( d - 0.72351 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 15, 1, [0 0 0 0 0 0 0 0 0 0 0 0.444956179153313 0.694837045312089 0 0 0 1.21296662658388 0 1.56620351515086 0.139996151546743;0 0 0.436509042497808 0 0 0 0 0 0 0.51021617110356 0.382775864014207 0 0 0 0 0 0 0 0.0458660640982067 0;0 0.436509042497808 0 0.142843784706697 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.142843784706697 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.923358421898822 0 0 0 0 0 0 0.535622573665002 0 0 0.0623807988546017 0 0 0 0;0 0 0 0 0.923358421898822 0 0 0 0 0 0 0 0 0 0.0225268450194125 0.789248499651178 0.131644262096824 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0.157622272676696 0.474149476188578 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 1.38990078830045 0 0 0 0 0.691403775437505 0;0 0.51021617110356 0 0 0 0 0 0 0 0 0.597507997139564 0 0 0 0.354205526419423 0 0 0 0 0;0 0.382775864014207 0 0 0 0 0 0 0 0.597507997139564 0 0 0 0.659672915756231 0 0 0 0 0 0;0.444956179153313 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.138835508200668;0.694837045312089 0 0 0 0.535622573665002 0 0.157622272676696 0 0 0 0 0 0 0 0 0.112112626230952 0 0 0 0.0843937952650982;0 0 0 0 0 0 0.474149476188578 0 1.38990078830045 0 0.659672915756231 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.0225268450194125 0 0 0 0.354205526419423 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0.0623807988546017 0.789248499651178 0 0 0 0 0 0 0.112112626230952 0 0 0 0 0 0 2.40412068693751;1.21296662658388 0 0 0 0 0.131644262096824 0 0 0 0 0 0 0 0 0 0 0 0 0.332961917093088 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.464569385286 0;1.56620351515086 0.0458660640982067 0 0 0 0 0 0 0.691403775437505 0 0 0 0 0 0 0 0.332961917093088 1.464569385286 0 0;0.139996151546743 0 0 0 0 0 0 0 0 0 0 0.138835508200668 0.0843937952650982 0 0 2.40412068693751 0 0 0 0] );\r\nassert( isequal(route,[15 6 16 13 20 1]) \u0026\u0026 abs( d - 1.14828 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 6, 9, [0 0.366176160541789 0.786653302253499 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.21056171145861;0.366176160541789 0 0 0 0 0 0 0 0 1.00794652016003 0 0 0 0 0 0 0 0 0 0;0.786653302253499 0 0 0 0.00852440175782365 0 0 0 0 0 0.17749671083585 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.104971160045632 0 0.612122585766863 0 0.283798036821908;0 0 0.00852440175782365 0 0 0 0.643083445674635 0 0 0 1.48191061231689 0 0 0 0.200776975353452 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.20656027667801 0 0 0;0 0 0 0 0.643083445674635 0 0 0 0.0293301078099069 0 0 0.0684877514911584 0.244866042619905 0 0 0 0 0.844967783108164 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0.0293301078099069 0 0 0 0 0.112122931478046 0 0 0 0.904924565740344 0 0 0 0;0 1.00794652016003 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.17749671083585 0 1.48191061231689 0 0 0 0 0 0 0.356911349006201 0 0 0.157837394902406 0 0 0 0 0;0 0 0 0 0 0 0.0684877514911584 0 0.112122931478046 0 0.356911349006201 0 0.682956498987976 0.369934947078526 0 0 0 0 0 0;0 0 0 0 0 0 0.244866042619905 0 0 0 0 0.682956498987976 0 0 0 0 1.43719870645473 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0.369934947078526 0 0 0 0 0 0 0 0;0 0 0 0 0.200776975353452 0 0 0 0 0 0.157837394902406 0 0 0 0 0.0962643536575907 0 0 0 0;0 0 0 0.104971160045632 0 0 0 0 0.904924565740344 0 0 0 0 0 0.0962643536575907 0 0 0 0 0.884861315533158;0 0 0 0 0 1.20656027667801 0 0 0 0 0 0 1.43719870645473 0 0 0 0 0.00316254045496533 0.917601066178612 0;0 0 0 0.612122585766863 0 0 0.844967783108164 0 0 0 0 0 0 0 0 0 0.00316254045496533 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.917601066178612 0 0 0;0.21056171145861 0 0 0.283798036821908 0 0 0 0 0 0 0 0 0 0 0 0.884861315533158 0 0 0 0] );\r\nassert( isequal(route,[6 17 18 7 9]) \u0026\u0026 abs( d - 2.08402 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 15, 8, [0 0 0 0 0 0 0 0.444927230771171 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0.0904807891398611 0 0 0.117980802815763 0 0 0 0 0 0 0 0 0 0 0.786791961925432 0 0;0 0 0 0 0 0 0 0 0 0.159132007464481 0.110433064086588 0 0 0 0 0 0 0 0 0.139982926657546;0 0.0904807891398611 0 0 0.388870980511861 0 0 0 0 0 0 0.973527639623757 0 0 0 0 0 0 0 0;0 0 0 0.388870980511861 0 0 0 0.305597627987039 0 0 0 0 0.027077532916115 0 0 0 0 0 0.290796760442986 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0.117980802815763 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.27266472620458 0.665594866955372 0 0.626568354787985;0.444927230771171 0 0 0 0.305597627987039 0 0 0 0 0 0 0 0 0 0 0 0 0 0.498229667608556 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.159132007464481 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.110433064086588 0 0 0 0 0 0 0 0 0 0.611004915345871 0 0 0 0.561899811991367 0 0 0;0 0 0 0.973527639623757 0 0 0 0 0 0 0 0 0.949329689605504 0 0 0 0 0 0 0;0 0 0 0 0.027077532916115 0 0 0 0 0 0.611004915345871 0.949329689605504 0 0 0 0 0 0.45822991145669 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.916926430883478 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0944227233455792;0 0 0 0 0 0 1.27266472620458 0 0 0 0.561899811991367 0 0 0 0 0 0 0.0123263072768274 0 0;0 0.786791961925432 0 0 0 0 0.665594866955372 0 0 0 0 0 0.45822991145669 0 0 0 0.0123263072768274 0 0.708053638455894 0;0 0 0 0 0.290796760442986 0 0 0.498229667608556 0 0 0 0 0 0.916926430883478 0 0 0 0.708053638455894 0 0;0 0 0.139982926657546 0 0 0 0.626568354787985 0 0 0 0 0 0 0 0 0.0944227233455792 0 0 0 0] );\r\nassert( isequal(route,-1) \u0026\u0026 abs( d - -1 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 5, 4, [0 0 0 0 0 0 0 0 0 0.482056160228392 0 0 0 0 0 0 0 0 0.00508309589200806 0;0 0 0.342764171753101 0 0.592230924022738 0 0 0 0 0 0 0 0 0 0 0 0.616196530219501 0 0.105964156030294 0;0 0.342764171753101 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.06756913797405 0 0 0 0 0;0 0.592230924022738 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 1.75169005582658 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.198256254136309 0 0.117040404671406 0.742253008190119 0 0 0 0 0 0 0 0 0;0 0 0 0 0 1.75169005582658 0.198256254136309 0 0 0.193487168668438 0 0 0 0 0 0.213470445629309 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0.672768253513765 0 0 0 0 0 0 0 0;0.482056160228392 0 0 0 0 0 0.117040404671406 0.193487168668438 0 0 0.182397544709499 0 0 0 0 0 0 0 0.352313653363684 0;0 0 0 0 0 0 0.742253008190119 0 0 0.182397544709499 0 0.863897537114491 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0.672768253513765 0 0.863897537114491 0 0 0 0 0 0.849422540372472 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.126177070732391 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 1.06756913797405 0 0 0 0 0 0 0 0 0.126177070732391 0 0 0 0 0.810675752838635 0.192588746332897 0;0 0 0 0 0 0 0 0.213470445629309 0 0 0 0 0 0 0 0 0 0 0 0;0 0.616196530219501 0 0 0 0 0 0 0 0 0 0.849422540372472 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.810675752838635 0 0 0 0 0;0.00508309589200806 0.105964156030294 0 0 0 0 0 0 0 0.352313653363684 0 0 0 0 0.192588746332897 0 0 0 0 0.473102743220109;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.473102743220109 0] );\r\nassert( isequal(route,[5 2 19 15 4]) \u0026\u0026 abs( d - 1.95835 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 18, 3, [0 0 0 0 0 0 0.588131422298983 0 0 0 0 0 0 0 0 0 0 0 0.411615488806083 0;0 0 0 0 0 0 0 0 0 0.148093137302263 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.513126690185934 0.314081294727961 0 0 0 0 0 0 0 0 0 0 0.105622237791164 0 0;0 0 0 0 0.0233388222703319 0 0 0.620281238898666 0 0 0 1.01777898612281 0 0 1.02802169259185 0 0 0 0 0.829878923718159;0 0 0 0.0233388222703319 0 0.103664033766553 0 0 0 0 0.800687507355036 0.724909646173659 0 0 0 0 0 0 0 0;0 0 0.513126690185934 0 0.103664033766553 0 0 0 0 0 0 0 0.51932792913499 0.111508583765534 0 0 0 0 0 0;0.588131422298983 0 0.314081294727961 0 0 0 0 0 0.632615202648636 0 0 0 1.12039468709595 0 0 0 0 0 0 0;0 0 0 0.620281238898666 0 0 0 0 0.665853755155897 0 0.443519419164187 0 0.0287540443670959 0 0 0 0 0 0 0;0 0 0 0 0 0 0.632615202648636 0.665853755155897 0 0 0 0 0 0 0 0 0 0 0 0.341087071649035;0 0.148093137302263 0 0 0 0 0 0 0 0 0.0523829918450132 0 0 0 0 0 0 0.401940201122634 0.691832558529399 0;0 0 0 0 0.800687507355036 0 0 0.443519419164187 0 0.0523829918450132 0 0.491690939364275 0 0.757845451055127 0 0 0 0.024463668194654 0 0;0 0 0 1.01777898612281 0.724909646173659 0 0 0 0 0 0.491690939364275 0 0 0 0 0 0 0 0 1.02836268723464;0 0 0 0 0 0.51932792913499 1.12039468709595 0.0287540443670959 0 0 0 0 0 0 0 0 0 0 0 0.366143225287491;0 0 0 0 0 0.111508583765534 0 0 0 0 0.757845451055127 0 0 0 0.223088374978438 0 0 0 0 0;0 0 0 1.02802169259185 0 0 0 0 0 0 0 0 0 0.223088374978438 0 0.344909749483892 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.344909749483892 0 0 0 0.353158597614942 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0.105622237791164 0 0 0 0 0 0 0.401940201122634 0.024463668194654 0 0 0 0 0 0 0 0 0;0.411615488806083 0 0 0 0 0 0 0 0 0.691832558529399 0 0 0 0 0 0.353158597614942 0 0 0 0.849677928981906;0 0 0 0.829878923718159 0 0 0 0 0.341087071649035 0 0 1.02836268723464 0.366143225287491 0 0 0 0 0 0.849677928981906 0] );\r\nassert( isequal(route,[18 3]) \u0026\u0026 abs( d - 0.105622 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 17, 23, [0 0.151141399637051 0 0 0 0 0 0 0 0 0 0.105216194021975 0 0 0 0 0 0.437381445735918 0 0 0.949941070771521 0 0 0 0;0.151141399637051 0 0 0 0 0 0 0 1.22583368379244 0 0 0.079829221583307 0.71041636270324 0 0 0 0.1075924794072 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 1.21948687450578 0 0.567263036089771 0 0 0 0 0 0.857795458880245 0 0 0 0 0.731569267553795 0 0 0;0 0 0 0 0 0 0.186039341309778 0 0 0 0 0 0 0 0 0 0 2.00348310018009 0 0 0 0 0 0 0;0 0 0 0 0 1.32070145417138 0 0 0 0 0 0 0 0 0 0 0 0.430765092398605 0 0 0 0 0 0.46856479561555 0;0 0 0 0 1.32070145417138 0 0 0.203767017753022 0 0 0 0 0 0 0.487213897131877 0 0 0.896335225888555 0 0 0 0 0 0 0;0 0 0 0.186039341309778 0 0 0 0 0 0 0 0 0.406945507381253 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.203767017753022 0 0 0.15769661193131 0 0.65001597680104 0 0 0 0 0 0 0.15666137867965 0 0 0 0 0.723509833846064 0 0;0 1.22583368379244 1.21948687450578 0 0 0 0 0.15769661193131 0 0 0 0 0 0 0 0 0.508542446617735 0 0 0.696934855529271 0.169312519482881 0 0.00704092733099992 0 0;0 0 0 0 0 0 0 0 0 0 0 0 1.08493079525094 0.214254564261975 0 0.425013648805044 0 0 0 0 0 0 0 0 0.00543872970590864;0 0 0.567263036089771 0 0 0 0 0.65001597680104 0 0 0 0 0 0 0 0 0.696979111426999 0.525282567629852 0 0.621146400617813 1.20050590589561 0 0 0 0;0.105216194021975 0.079829221583307 0 0 0 0 0 0 0 0 0 0 0.459862031186997 0 0 0 0 0 0 0.698687249438191 0 0 0.00200957746053532 0 0;0 0.71041636270324 0 0 0 0 0.406945507381253 0 0 1.08493079525094 0 0.459862031186997 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.214254564261975 0 0 0 0 0.380308744719566 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0.487213897131877 0 0 0 0 0 0 0 0.380308744719566 0 0 0.0449909078512449 0 0 1.22341039971646 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.425013648805044 0 0 0 0 0 0 0 0 0 0 0 0 1.43760755773283 0.719177032769178 0;0 0.1075924794072 0.857795458880245 0 0 0 0 0 0.508542446617735 0 0.696979111426999 0 0 0 0.0449909078512449 0 0 0 0 0 0 0 0 0 0;0.437381445735918 0 0 2.00348310018009 0.430765092398605 0.896335225888555 0 0.15666137867965 0 0 0.525282567629852 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0.696934855529271 0 0.621146400617813 0.698687249438191 0 0 1.22341039971646 0 0 0 0 0 1.1519343197436 0 0 0 0;0.949941070771521 0 0 0 0 0 0 0 0.169312519482881 0 1.20050590589561 0 0 0 0 0 0 0 0 1.1519343197436 0 0 0 0 0.214330337662627;0 0 0.731569267553795 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0.723509833846064 0.00704092733099992 0 0 0.00200957746053532 0 0 0 1.43760755773283 0 0 0 0 0 0 0 0 0;0 0 0 0 0.46856479561555 0 0 0 0 0 0 0 0 0 0 0.719177032769178 0 0 0 0 0 0 0 0 0.649429697531317;0 0 0 0 0 0 0 0 0 0.00543872970590864 0 0 0 0 0 0 0 0 0 0 0.214330337662627 0 0 0.649429697531317 0] );\r\nassert( isequal(route,[17 2 12 23]) \u0026\u0026 abs( d - 0.189431 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 2, 9, [0 0 0 0 0 0.390568942736463 0.253317405921882 0 0 0 0 0 0 0 0 0.035303866587423 0 0.0932427029924401 0 0.228317786309953 0 0 0 0 0;0 0 0 0 0 0 0.22325539367323 0.0737968434096563 0 0.0216391156829114 1.01817561468837 0 0 0.166613690540579 0 0 0 0 0 0.0929136548216463 0 0 0 0 0;0 0 0 0 0 0.324975382720294 0 0 0 0 0 0 0 0 0.257683850031889 0 0 0 0.818836795828793 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0.0227807501033899 0 0 0 0 0.254392094407223 0 0 0 0 0 0.499630884751228 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0.645309316664204 0 0 0 0 0 0.377002225744615 0 0 0 0 0;0.390568942736463 0 0.324975382720294 0 0 0 0 0 0 0 0 0.381625987614713 0.187530187877611 0 0 0 0 0 1.03662835165178 0 0 0 0 0 0;0.253317405921882 0.22325539367323 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.420116352005782 0.288516971344659 0 0 0 0 0.290423766876168 0;0 0.0737968434096563 0 0 0 0 0 0 0 0 0 0 0 1.14302504189143 0 0.894497023541543 0 0 0 0 0 0 0.181212342324972 0 0.4790219658659;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.66947645498941 0 0 0 0 0 0 0 0.881432911415172 0.190738003819626 0;0 0.0216391156829114 0 0 0 0 0 0 0 0 0 0 0 0 0 0.406383564162139 0 0 0 0 0 0 0 0 0.0727730905533963;0 1.01817561468837 0 0 0 0 0 0 0 0 0 0.968244418446258 0 0 0.528273242216383 0.125653272829919 0 0 0 0 0 0 0 0 0;0 0 0 0.0227807501033899 0 0.381625987614713 0 0 0 0 0.968244418446258 0 0 0 0 0.545221500471632 0 0 0.602095719309548 0 0 0 0 0 0;0 0 0 0 0 0.187530187877611 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.926256705235548 0 0 0 0;0 0.166613690540579 0 0 0.645309316664204 0 0 1.14302504189143 0 0 0 0 0 0 0 0 0 0.21560951711239 0 0 0 0 0 0 0;0 0 0.257683850031889 0 0 0 0 0 0.66947645498941 0 0.528273242216383 0 0 0 0 0 0 0 0 0 0.213055228450905 0 0 0 0;0.035303866587423 0 0 0 0 0 0 0.894497023541543 0 0.406383564162139 0.125653272829919 0.545221500471632 0 0 0 0 0.450996873658263 0 0 0 0 0 0 0 0;0 0 0 0.254392094407223 0 0 0 0 0 0 0 0 0 0 0 0.450996873658263 0 0 0 0 0 0 0.219529444302005 0 0;0.0932427029924401 0 0 0 0 0 0.420116352005782 0 0 0 0 0 0 0.21560951711239 0 0 0 0 0 0 0 0.863470148104069 0 0.444628451921207 0;0 0 0.818836795828793 0 0 1.03662835165178 0.288516971344659 0 0 0 0 0.602095719309548 0 0 0 0 0 0 0 0 0 0.109259232718513 0 0 0;0.228317786309953 0.0929136548216463 0 0 0.377002225744615 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.615496286883062;0 0 0 0 0 0 0 0 0 0 0 0 0.926256705235548 0 0.213055228450905 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.863470148104069 0.109259232718513 0 0 0 0 0.0137884729469751 0;0 0 0 0.499630884751228 0 0 0 0.181212342324972 0.881432911415172 0 0 0 0 0 0 0 0.219529444302005 0 0 0 0 0 0 0.365687691203556 0;0 0 0 0 0 0 0.290423766876168 0 0.190738003819626 0 0 0 0 0 0 0 0 0.444628451921207 0 0 0 0.0137884729469751 0.365687691203556 0 0;0 0 0 0 0 0 0 0.4790219658659 0 0.0727730905533963 0 0 0 0 0 0 0 0 0 0.615496286883062 0 0 0 0 0] );\r\nassert( isequal(route,[2 7 24 9]) \u0026\u0026 abs( d - 0.704417 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 12, 4, [0 0 0 0 0 0.714172260222902 0 0 0 0 0 0 0 0 0 0 0 0 0 0.361655390928043 0 0 0 0 0;0 0 0 0 0 0.181492418867339 0 0 0 0 0 0 0 0 0 0 0 0 0.22307965545124 0 0 0 0 0 0.779096496125678;0 0 0 0 0 0 0.47292346615082 0 0 0.168841046075892 0 0 0 0 0 0 0 0 0 0.0217708463553388 0 0 0.667747131809592 0 0;0 0 0 0 0 0 0 0.57532352865356 0 0 1.14531063150095 0 0 0 0 0 0 0 0 1.81120439254402 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0.347520308679668 0 0 0 0 1.19301977580358 0 0.820270346367214 0 0 0.0596854204267023 0 0.365147722552969 0.160828167983497 0;0.714172260222902 0.181492418867339 0 0 0 0 0.993473525288174 0 0 0 0 0 0 0 0 0 0 0 0 0.900267645686867 0 0 0 0 0;0 0 0.47292346615082 0 0 0.993473525288174 0 0 0 0 0.303524976604928 0 0 0.988108387042638 0 0 0 0 1.09908596860658 0 0 0 0 0 0;0 0 0 0.57532352865356 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0496932258637628 0 0 0 0 0 0 0.220051533000778 0 0 0;0 0 0.168841046075892 0 0 0 0 0 0 0 0 0 0.415893111213311 0 0 0 0 0 0 0 0 0 0 0.252874847836154 0.7525160069564;0 0 0 1.14531063150095 0.347520308679668 0 0.303524976604928 0 0 0 0 0 0.315427799185682 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0.0659140954680451 0.229430180128888 0 0 0 1.02421541676855 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0.415893111213311 0.315427799185682 0 0 0 1.43148800286315 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0.988108387042638 0 0 0 0 0.0659140954680451 0 0 0 0 0.0723048054691602 0.570598773372364 0 0 0 0 0 0 0.816798020448907;0 0 0 0 0 0 0 0 0.0496932258637628 0 0 0.229430180128888 1.43148800286315 0 0 0.0969052461008522 0 0 0.562394406606289 0 0 0 0 0 0;0 0 0 0 1.19301977580358 0 0 0 0 0 0 0 0 0 0.0969052461008522 0 0.830027198843182 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0.0723048054691602 0 0.830027198843182 0 0 0 0 0.471570888980097 0 0 0 0;0 0 0 0 0.820270346367214 0 0 0 0 0 0 0 0 0.570598773372364 0 0 0 0 0 0 0 0 0 0 0;0 0.22307965545124 0 0 0 0 1.09908596860658 0 0 0 0 1.02421541676855 0 0 0.562394406606289 0 0 0 0 0 0 0 0 0 0;0.361655390928043 0 0.0217708463553388 1.81120439254402 0 0.900267645686867 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0.0596854204267023 0 0 0 0 0 0 0 0 0 0 0 0.471570888980097 0 0 0 0 0.920738174557066 0 0 0;0 0 0 0 0 0 0 0 0.220051533000778 0 0 0 0 0 0 0 0 0 0 0 0.920738174557066 0 0 0 0;0 0 0.667747131809592 0 0.365147722552969 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.431353900603143;0 0 0 0 0.160828167983497 0 0 0 0 0.252874847836154 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.139899289183316;0 0.779096496125678 0 0 0 0 0 0 0 0.7525160069564 0 0 0 0.816798020448907 0 0 0 0 0 0 0 0 0.431353900603143 0.139899289183316 0] );\r\nassert( isequal(route,[12 14 17 21 5 11 4]) \u0026\u0026 abs( d - 2.16231 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 21, 9, [0 1.30397831279197 0 0 0 0 0 0 0.205205702932437 0 0 0 0 0.462991342326146 0 0.0919395070383298 0 0 0 0 0 0 0 0.788285106392582 0;1.30397831279197 0 0 0 0 1.05960547137835 0 0 0.153644616706166 0 0 0.860262579703983 0 0 0 0 0 0 0 0 0 0 0 0.773468224481749 0;0 0 0 0.13195985000036 0 0 0 1.51813223209895 0 0 0 0 0 0.0156327604904785 0 1.27556519583119 0.93793259222666 0 0 0 0 0 0 0 0;0 0 0.13195985000036 0 0 0 0.458734989962526 0 0 0 0 0 0 0 0 0 0 0 0.835183344604242 0.11324698880843 0 0 1.27194671889278 0 0.873215204449672;0 0 0 0 0 0 0.0522387394084536 0.441514133149768 0 0 0 0 0 0 0 0 0 0 0 0.104845115642955 0 0 0 0 0;0 1.05960547137835 0 0 0 0 0 0 0 0 0 0.323427832607934 0 0 0 0 0 0.548178891330981 0 0 0 1.78927187214965 0 0 0;0 0 0 0.458734989962526 0.0522387394084536 0 0 0.128458273651367 0 1.10447307401052 0 0 1.60635812839544 0.490059715639469 0 0 0 0 0.87297695015148 0 0 0 0.0385154612576837 0 0;0 0 1.51813223209895 0 0.441514133149768 0 0.128458273651367 0 0 0.0426997868037813 0 0 0 0.316089962309322 0.556234063736422 0 0 0 0 0 0 0 0.125426946797567 0 0.501620852747415;0.205205702932437 0.153644616706166 0 0 0 0 0 0 0 0 0 0 0 0 0 1.22841179064666 0 0.506177174936367 0 0 0 0.139674374757514 0 0 0;0 0 0 0 0 0 1.10447307401052 0.0426997868037813 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.695460494256037;0 0 0 0 0 0 0 0 0 0 0 1.09170738934842 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0.860262579703983 0 0 0 0.323427832607934 0 0 0 0 1.09170738934842 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 1.60635812839544 0 0 0 0 0 0 0 0 0 0 0 0 1.27248881503698 0 0 0 0 0.162219187624835;0.462991342326146 0 0.0156327604904785 0 0 0 0.490059715639469 0.316089962309322 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.111140488918591 0.0639936929497993;0 0 0 0 0 0 0 0.556234063736422 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0.0919395070383298 0 1.27556519583119 0 0 0 0 0 1.22841179064666 0 0 0 0 0 0 0 0.772788879713252 0 0 0 0.00743946114818939 0 0.662296573850469 0 0;0 0 0.93793259222666 0 0 0 0 0 0 0 0 0 0 0 0 0.772788879713252 0 0 0 0 0 0 0 0 0.235465388137087;0 0 0 0 0 0.548178891330981 0 0 0.506177174936367 0 0 0 0 0 0 0 0 0 0.596123003045261 0 0 0.50807778971881 0 0.192149930306311 0;0 0 0 0.835183344604242 0 0 0.87297695015148 0 0 0 0 0 0 0 0 0 0 0.596123003045261 0 1.75354812715354 0 0 0 0.230875543406997 0.402865723829543;0 0 0 0.11324698880843 0.104845115642955 0 0 0 0 0 0 0 1.27248881503698 0 0 0 0 0 1.75354812715354 0 0 0 0.286957051522517 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00743946114818939 0 0 0 0 0 0 0 0 0.12234328650336;0 0 0 0 0 1.78927187214965 0 0 0.139674374757514 0 0 0 0 0 0 0 0 0.50807778971881 0 0 0 0 0 0 0.0229366876888033;0 0 0 1.27194671889278 0 0 0.0385154612576837 0.125426946797567 0 0 0 0 0 0 0 0.662296573850469 0 0 0 0.286957051522517 0 0 0 0 0;0.788285106392582 0.773468224481749 0 0 0 0 0 0 0 0 0 0 0 0.111140488918591 0 0 0 0.192149930306311 0.230875543406997 0 0 0 0 0 0;0 0 0 0.873215204449672 0 0 0 0.501620852747415 0 0.695460494256037 0 0 0.162219187624835 0.0639936929497993 0 0 0.235465388137087 0 0.402865723829543 0 0.12234328650336 0.0229366876888033 0 0 0] );\r\nassert( isequal(route,[21 25 22 9]) \u0026\u0026 abs( d - 0.284954 ) \u003c 1e-4 );\r\n\r\n%%\r\n[route d] = parcel_route( 5, 5, [0 0 0.235687387990488 0 0 0.518662908555243 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00169033754843562 1.18573193396702 0 0 0 0 0;0.235687387990488 0 0 0 0.350144748614205 0 0 0.499051956190166 0 0 0 0 0 0 0 0.428154355783706 0 0 0 0.988646147648288 0 0 0 0 0.766292681932783;0 0 0 0 0 0 0 0 0 0.306976149669423 0 0 0 0 0 0 0.148608071246878 0 0 0 0 0 0 0 0;0 0 0.350144748614205 0 0 0 0.366820040758671 0 0 0 0.947779130029861 0 0 0 0 0 0 0 0 0.781367996905263 0 0 0 0 0;0.518662908555243 0 0 0 0 0 0.28467286265608 0 0 0 0 0 0 0 0 0 0 0 0.814169013559602 0 0 0 0 0 0.514510683872373;0 0 0 0 0.366820040758671 0.28467286265608 0 0 0 0 0 0.137928171247269 0 0 0 0 0 0.581896713318172 0 0 0 1.00288388568789 0.926366539848811 0 0;0 0 0.499051956190166 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.211128675902371 0 0 0 0 0 0 0 0 0;0 0 0 0.306976149669423 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.332300868928405;0 0 0 0 0.947779130029861 0 0 0 0 0 0 0 0 0 0.140274584917356 0 0 0 0.276337784565307 0 0 0 0 0 0;0 0 0 0 0 0 0.137928171247269 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.422423933152413 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.16443124331918 0 0 0 0.113521569230241 0 0 0.431552467605628 0;0 0 0 0 0 0 0 0 0 0 0.140274584917356 0 0 0 0 0 0 1.01590071824433 0 0 0 0 0 0 0;0 0 0.428154355783706 0 0 0 0 0 0.211128675902371 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;0 0 0 0.148608071246878 0 0 0 0 0 0 0 0 0 0.16443124331918 0 0 0 0 0 0.816401527141028 0 0 0 0 1.51727966787778;0 0 0 0 0 0 0.581896713318172 0 0 0 0 0 0 0 1.01590071824433 0 0 0 0 0 0.0315916186043663 0 0 0 0;0 0.00169033754843562 0 0 0 0.814169013559602 0 0 0 0 0.276337784565307 0 0.422423933152413 0 0 0 0 0 0 0 0 0 0 0.113122720118215 0;0 1.18573193396702 0.988646147648288 0 0.781367996905263 0 0 0 0 0 0 0 0 0 0 0 0.816401527141028 0 0 0 0 0 0 0 1.22595526329414;0 0 0 0 0 0 0 0 0 0 0 0 0 0.113521569230241 0 0 0 0.0315916186043663 0 0 0 0 0 0.0278718835255773 0;0 0 0 0 0 0 1.00288388568789 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.627233109842477 0 0;0 0 0 0 0 0 0.926366539848811 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.627233109842477 0 0.210579136296008 0;0 0 0 0 0 0 0 0 0 0 0 0 0 0.431552467605628 0 0 0 0 0.113122720118215 0 0.0278718835255773 0 0.210579136296008 0 0;0 0 0.766292681932783 0 0 0.514510683872373 0 0 0 0.332300868928405 0 0 0 0 0 0 1.51727966787778 0 0 1.22595526329414 0 0 0 0 0] );\r\nassert( isequal(route,5) \u0026\u0026 abs( d - 0 ) \u003c 1e-4 );\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":134,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":26,"test_suite_updated_at":"2012-03-07T20:02:13.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-03-06T18:48:13.000Z","updated_at":"2026-03-30T17:22:55.000Z","published_at":"2012-03-07T20:03:56.000Z","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 a matrix that represent the distance along highways between major cities numbered 1 to\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, provide the path and shortest distance from a given city,\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\u003efrom\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, to a given city,\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\u003eto\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. Assume that 0 represents no direct path between two cities. If there is no solution to the problem, return -1 for both the path and the distance.\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":55420,"title":"Power Outages Histogram","description":"Create a function that takes power outage data as an input and creates a histogram of the number of outages as a function of Region. Note that the Region column of the power outage table contains a cell array of character vectors.\r\nRotate the x-axis tick labels by 30 degrees and label the y-axis with \"Number of Outages\".\r\nYour function should return the figure handle as output.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; 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: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 424.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 212.333px; transform-origin: 407px 212.333px; 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCreate a function that takes power outage data as an input and creates a histogram of the number of outages as a function of Region. Note that the Region column of the power outage table contains a cell array of character vectors.\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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eRotate the \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ex\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e-axis tick labels by 30 degrees and label the \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ey\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e-axis with \"Number of Outages\".\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 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eYour function should return the figure handle as output.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 313.667px; 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 156.833px; text-align: left; transform-origin: 384px 156.833px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"678\" height=\"308\" style=\"vertical-align: baseline;width: 678px;height: 308px\" 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function f = plotOutages(T)\r\n    f = figure; % gets the figure handle\r\n    \r\n    \r\nend","test_suite":"T = readtable(\"outages.csv\");\r\ng__  = plotOutages(T);\r\n%% Is there a histogram?\r\nassert(isequal(g__.Children.Children.Type,'categoricalhistogram'))\r\n%% Are the XTick labels rotated by 30 degrees?\r\nassert(isequal(g__.Children.XTickLabelRotation,30))\r\n%% Is the y-axis labeled correctly?\r\nassert(isequal(g__.Children.YLabel.String,\"Number of Outages\"))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":6,"created_by":140016,"edited_by":140016,"edited_at":"2022-10-10T14:27:44.000Z","deleted_by":null,"deleted_at":null,"solvers_count":217,"test_suite_updated_at":"2022-10-10T14:27:44.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2022-09-02T17:58:22.000Z","updated_at":"2026-04-03T09:09:12.000Z","published_at":"2022-10-10T14:27:44.000Z","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\u003eCreate a function that takes power outage data as an input and creates a histogram of the number of outages as a function of Region. Note that the Region column of the power outage table contains a cell array of character vectors.\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\u003eRotate the \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-axis tick labels by 30 degrees and label the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ey\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-axis with \\\"Number of Outages\\\".\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\u003eYour function should return the figure handle as output.\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=\\\"308\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"678\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" 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u4jtrAKjZ0jbXv0oaW3DdFrlnC0yoOQRmoSzqVhMFnjF9KdHp0boy05zeYtB0ktrI1vE3ovT3TyhMoCjuyOIOpCFdg60b5bX9r4Nbij236n/QtGTH+jqorClCKMZhUWNUZORnzH98u3Y6VzQGdRyZqpHzNr1zmUzAg+evNzovM16M1ZLBj9MtMWHcdgrUFtrcO6uoglS2ZwNqu8LnAJB+dN5vkf9mPUO2DO2Mbn48I5UGrAXJ7H4s/HsXhbHHoHe46smsbyg0n/aMT23ypx2xyWeb3Cu3f7Y4uOgHs/5al2+9h8MJuC44t4feFhrGz16I2pfD9pMacUBQtLa2ztrLGwskGv16N30GFlWfvAoLGxx0GvR6+vYffEp5h/pABKYvj2P2OZdtiI3rqG4zOm8tLoRWTamDiw+EtmbDmBXq/HpiqLOeETWHwih4Y9R/PeC724eDtwaTKA0a89iocO1Nb2WJQk8tPiRWQVG0GlQlOWyuyvf2BnoZb9C95i+ZFotn/5PnNPVnN22wymLdoIWnvsrWr49ceP+XHzGczKndvvt0cphxd+zZjv92LUO1CTvZMvxn3K/qIKClK38s3nC8g12aLXV7JjzgxWHk7GTCzTR4zl10QVej2krf+eD38+QOkd3pKY/buw6/MID3b0QmVhSd9h4/nw2XtwaeDIiV/eYPGxPOwd9OhTV/PhfzeTTRZrPxzP5H1V6PVaSk//yvgv1pOLCktrW2xtNKis7GrPX3tb1BYqjJWHmfjqp2xON2GvN3F4xmgmzz1EVfZBXnxhCpHp6cye/j2xZfH88sIYdpzNYPXXHzDnWDp6vR6rgtNMeusj1qdVY2FpTVn8Jj585QmeG7uKrPJkfly2nsKKE/zwwlvsSVOj1yskL5/C54sjKb/+LrhtqjMyyc+tRqVSocrewmfj3iW2XI1er6dsZzhvfrKA5PI0lr3+Kt8fMaHXW1N0dA2vTNpIPiostbbYaS1RWdftX50NagsozdnFx29OYX++gqO+ip3fvsT3y49SjhqtzobN347g6ac/55jBgtStXzNn/wUsLLXoHPXo9XZkHfmFKcsOA2BppcXO1hoLK9u6Y6hDo67tPjU29lSe28yERduu2KpUFr84mjc3pGGhtyJ37xc8+dh0zllYUhSzgY9e/YA9yVVoy1OYPn0+sSUGvPqN5s2nu+BQF8Ez+H5Gv3A/zjag1tqj5J3mu0XLKaowg8oCq9JEvpv0PfsqHNkx733WRZ1i8ydvsjDqT/q93edu74H9f6783DEWJnnw2XevEeIIDo268u2M+TzUAlRqDbb2juj1esx5J5k9ZzEZxdVYaizZsHQyh1KrcHTUUxb5Cz8sO0Yp55n52FMsi6lBr1eTvWMer329g6LKdFZOeZ85J7LQ6/Vo8qOZ+OZHRGT+6zuLa1P+JSKn3qOorO0URwcHxa7pYGXKyQuKsaJA+eqp5orGWqs4ODoqjg72irVGrQyauEVJ+Lan0n3sEiXHXKMo1SYlceazyt1Pz1HS6+IVpx5Xnh39kLLtbF5tQe4Z5Y1ho5RvjqUo1YqiVJsTlR+G91JeXJGvFKUcVZ4Z+YCy+VS2otSYlfUTRiljvt2hlN2pnVGPRX47QLEYHXFV2ZLRjsrjs04qUXOeVpxGL6wtTNyihLUdrWyoqVEURVHOrnhT8R/9/e/i7Vr4vhIc7Kg4OtorNpYWyn9WpSl5e79TWvR/RzlTVa0oNdVK1aEflIb2o5XtOXHKW/f5KxqtjeLo6Kg42OsUK0u18vBPMZfinZj5iGI/+pff1ZMdvV65b/QY5Wxm3VFN3asM7/GcsjS/XPlmVDPlvdUblC96BCkvbjAoM0YFKRora8XBofac02rUStj7K5VK003aifVCovLRPU2VqbtyLhflxyrvDB+lTD6UWHeNJCszHrtLefGXLCUnYa1yn7+VorN3UPr1u0uZuHSvkmk0K4qSpHzYRqVo7RyUtm1bK2MmLlZiKoxKzZ3arDrL3hukvPTTAaXiD5bNHu2ujFl4uvYfm19WWnT9rxKv5CqLR7ZRLG3sFT8/X+XxVz9VdmUUKtV1vzn2w/2K9ejVV8UpXvOi0n3oNOWcqVpRlGolLXqaMmrIq0r0pu8Va81IJSJ2l/LwqCeVQ0kbldG6BspXy7YrD3dxV6xs7GrPX52tYmmhVkZvMCqKoihxq95RApwHK2uLKxVTtUkprzQo1TXnlDdDLRStnYPSoUN75cUvVyrx9WD/5pzaoNzfuvZ8cHByV8ImrFNSTNVK4k+DFEsLtWJr76A4OjoqOq1a8e10n7IjJVuZ/VBjRWNjrwQENFGeeuML5WB+2aX9e/CLHorNS5uvqiNp/gvKgJGzlVRzjaIo1Urszs+VUU98opwvVBSzoUx5v7+PMuqrzUpRdY1iMpQpFUazknlyo3LvQBfF0dFB0dlYKaGvXr4XnFr4vOI2es4fbk/82g+UwNFfXy44s0hp4vqs8mulSalRahRz1T7lOStb5ZtIRYlb/a7S9NkvlSpTtVKTflh5Nmy0svBC4aWfRn47UFGPXv+7OtIPL1LuHv26kl5oqC1I3Krc0+45ZZ2pRpk4qrUyadMG5ZPWjZXX1v9Zv7f1Rg7V/6y8fdOVkHvfV879wbKilCjlP893VPR6R8VeZ6s0HjROic0yKMayPOWt0b2U2fsvKIqiKKd/HK3c/59lSo5yQZnSWa1Y2dorwcEtlZEf/qRElVUpxbFblAc7uilWtrqrrukxm+70FXpn/btGTJ9eRlZqFOPDDGxfdpS8KgusrZvy2MSVJOUXUliQR3JcFF8/3RErnT2UFVBuqAZTJTkX3yP+GUs1NhozuXllmFAwV1ZQXKnB1q7uVb9ajUajBkClUqHUKPyPP/P8Id/QPvie3squrDLMmClN38qBKHc6tvS6vJJSTXlRAVVVl2eeajRWWFiYqFIUKnMzOJeSh/nMN7wzYRfha86Tk7iH11vWrqu2skZrLCKnyAQ1ZorzSqipqcHCQo21VQhjft5OVlERhfnZJJ45wcQhfje4NRaoLQAVWFhcnPKhwlrbmAfeW0x8XgGFhQWkJETz3fO9sVLfYDX/DxQlHSE2txKtppq8vNJL10iJwRJbWxX2zm35ZP4hFs79gr59/Jj17utMWXIUQ5WOh36IZsOyuTzzTG+OzxvPsKcXkH2Ht8dRpyV5/y7OZFQACob8NM4np2OsvuKqNpWTnVE3V8SspfNrS9kXsZH3338SQ/w6+vebxMUxKo2VFjBgrDFTlnGBuLQiVHZ2WBiKKak0o2CiLLcMs6UNlpYAaixUgMri0mstC0sNWsuOvLstmuyiIgryMkmIPsrbXa94PzusH/c5aLG0sMRWa42F0Z6npp9k3dJZPP54Vw58/yJPvrKcPOqBjs9wOC6dXfOepfzIEqJjS7G009Ek6GU2pWRTUFRETkYCv/78Be0aaunx3gZ2r1vL+PHDKTi+mO69viCpLpSVtQ1QibHGRElaCrHppVjY2lBTUUKpwQwYKSuooMZKi/ridejnRZu2zXG0UGFpbYdNaRSTxn2K/9h9FOScZ+WEx/C0udxcjcYalcpIlVJDRU46Can51PzZTd7aGgdVGZl5lZipwVBYQpHiiM3FeBorrCwtakeJFai54d7i8j1IpVKhAlSqP+j3YqP45ukON1jH/yZLeyf8s/cxc20sRSbAVEFO3HHOpWUQ8cNn5Pi+Rl5BFpHLJ9LJ+Q8CVJWQl1M3A99oxz1To9myaikvvDCQ8xFf0nvgD2RqNGg1nXh/x2myi4rIz8sgPiqS8Z1VfxDwf4d6woQJE+50I/6ZajLP7GbB3PnsjS3ExymIhx/pwvGv32VlqoHOXdpzatd6Dp2KJnLfdhYuW0SOfSsGh3Ula+9CNh88zbHtq1gw5xA1TXoy9P7W2JPEis++Y83Bo2RnW+DRqQteDWxwUWWxZsNuIk8c5MiG3aSoe/HcmE4U7fqZGSv2kOPQisH+OUyfMocjxXr63t0OF+2/aGLhTWDnF0JHZRtfrTjKmaPb2f9rBHT8gFGPhqJTsti/cxepcXGcOXmC/YejyXMK5e42XjhoDRzas5rIEwnsW72D6Cp7uvo3YOfOZJLz0kmIO8WxXbuJt/CifbdutDLsZM76Q8Qd3smK+Rs4luzCiM+GE6otZvXKNRw/e4aDezYzb9ESKv370MXfEUousGrpPDYeSaNV1/4EuloDUFMdz5LPfiDi6CkKs8G9XWtKj69h9uItZNoHYZ84nxMVnmhPRxNZpOe+oaGc3rme/VFRHN+/i8UrFpJmGUiPEB/U/5L7TdHxX/hi5gZSiowkRh9kUfgTLLN5mHFdLVm/cTeHTxzmyMZdJNONEc93pWrvFF56ewkm+wZoVHqcnP0I6tKNNtY7Gd7pZVLd3LGtscGloQeuLXoS1t2vdq7wHdIoqA0WMVv4aeMe4k9Gsn3Vdk6UWNGhVTOqK06wY3cMcfEJ5J7cz9ozlYSGWDPvxTfZWKXB0azGXueGvVc7Bt8bjB6wta1g+6bFJJxJZNeq7STY+tH37rYUH/6VdUeiiD64iUMbSmh6Xxg1CVv4ZVsUDRp7kxe1gRJnf4pXbCY/tD8D21uxdPFKYuNOs3d3BD/PXoZtt0dooytkx9oFrNgVi7kwnRr3Vvg5WcGFxTzQ520yXVyxqbHFzdkTj5De3NXJG5vr7oVbQ6nJY8P0KazcfYqC7Ib0HjUSvwtbmLF0M+79n6NRwR5W7DxI7IlIInbOZcPOLNqG2jBh8HPsstThYNbgaO+GzrsD99/bEkfAzq6cTeuXkhSTyI6V20hybsFd3QPIPLiFDZEniD6wkcid1bR65FG6BjujxEUw8cdlpGaVUe7QlLb+DcBYRczxCxxLOkdqdDTHjx3meFw6FR5t6RbQABttJft2rCAqOoG9q3ZwBmd6hvpQdOEQi6bOYfvpVGqKwK1VKA3dG9K4+Ahztx7jzPGdHFh2nJLOrzFqmJ6Dy2eyZt85LHw74pG3l58XbiLNNpCwLgFoi5JYsmguW05k06lHPwJcau9BxoozLJk0g43Hz1Kco+DWOoi8Q6uYs2wHuU6hWMXO5ozZC03kUU6aGzFoUCDHtl7R7/2yiByH1vRs6XGHjvr/P1o3f7o1b8C2bz5g7Zk0zuzcw/oVv2IM6Yt7SS77ohM5fyaGk2eOExl5miynEO5p7UlG8m4O7I8h6uw50o/tZke6Nd1a5vNq11EkuHugq7bGSe+OvklXht3XCh+LdGbNX0lc3Gn27l7PrNnLsev1OG0a/ks6ixugUhTl//nAnkJZbirx5y9QYQadvjHNg10oiT/FuQITTVq2gfx4zmcUUWOhxsrRmSZ+PjS0taYi/xxx57MoN0Ly6g9Yrn2deeGD0VNE7L7TdaMKtjRu17b2ydlUQU5GCvEX8tFo7PHyb4aniw0FySc4m14OTn5081Nx4ngSFdqGBIU0pYG1zDb/vUrOx5wls6ACO+dGtGjujxaAcpJjTpFWDA2dnakqKaRM40nH0EZYUcmF+DOk5FShsXHGv5k3Lva2ZMWe4HyeCVsPVxzK0sgy6vBv2pxGNiXEn40npwwqo5bw4GwXjh6bQFOzgfSksyRll4OlJVq9C00b++JoZQlVJcTFx5NbbMAtsANN6zoFRSkgZn8MtXPWdTRtF4Im7xwJKbmY7H3xtEohv1qPo8FArtGaFm2aU52TwPn0AsxYYKV3xt/HGxfdnUoFbj5DVgxHz139Pb6+cSuCXSzJyUiuu0Z0NPJrhqerLcbCZE7HpGGoW9fGvTGBfp7oqnM4GRlP2cUgOlcCWzSjbtffUebSbE7HJVJmqMFS64pfUx/cHK0xG7M5G51AiUpPC3ctZ1OL8PT2xJyXQU5Z3RZqHfBu1gJfh4sPpmUknoomo1iFtc6FgOY+NNBqqCzIID45ndIKI04Nm+LnpyPnfBzpRRVY6z3QmjMxOTZCl55BuZMXzfxdyEk6RVqBCayssHV0pUUzX2yqDSSfiyMtrwyV2hLv5m3xaWAFhixOHD13eU6pvTvNWwTgfCc/zFQqOXfiGFkVAM6EdA9EU5BOfEIytk0642uZQ2xCIqVVoHJwwN2lEb7OlpyPiiXXUPflvo0e3+Yt8ba7OJ5cSkJUFNmllmgdXGjWwhcHSwvK89OJT86g3GDC2TUQ38Yu2FhCdX4CB8/WjsvrvINp7asHoCwzmejEdFTWDdA7KpTmFVLtFkyXxnqggpTY01zIM2Nl60zjQB+c7bRUlqQTF51EGWCh1tO8XTBOVoChmOTkJNLyyrC1dceveRP06nKSEs6SWVSFpWdLmmvziEvMwaTzoUNrH6yrioiJTaCgtArP5h1pXHegqk15nD0cS1Fti2nWLghVzjnOX8jHbO+PhyaJApxwLCsjX9HRPDQAY9Yf93vi7ym7EMXJlFJAi87FjxaBzlCUR2zCOUqrbNDhhqROAAAgAElEQVR76TDnZlKma0z3Fh6UFaUQF5dGpbUrAfoazuWYaNqkIdmxSZRcTLfsnAlo0Rx3LWAqJzn+FGmF5svXdKDfHXtwrA/+BYnpjYuc/wqPvvAzmUCD/q/x64xwgl3vdKvETXFhMd2bj+IEQJPezJu/jAdb293pVgkhhBDiGv6nE1MhhBBCCFF//Ls+fhJCCCGEEP9vSWIqhBBCCCHqBUlMhRBCCCFEvSCJqRBCCCGEqBckMRVCCCGEEPWCJKZCCCGEEKJekMRUCCGEEELUC5KYCiGEEEKIekESUyGEEEIIUS9IYiqEEEIIIeoFSUyFEEIIIUS9IImpEEIIIYSoFyQxFUIIIYQQ9YLlnaq4JCeZrCLjnar+X8PKwRVfNz0q1a2Jr5iryM1Kp6jCfGsqEDfE3t0fDwfNLYtvLsslKaMQ5ZbVcGNUFpY09PTFyVZ9y+owFaWRlFNxy+LXZxaWVjh7eKO3uXX711iYSnKu4ZbFF3+flYMLPm4NsLhV/Ui1kbysdArLTbemAlFvaZ198XGy/lu/uWOJadyuRczfm3Wnqv/XcO30EG8/2gON+tbcUcxluexcM5t9ccW3JL64MW0e/5gRnZ1uWfzyxH18N2sHNfUsM1Vr7Rkw4h3CWtjfsjqKo9cwbXncLYtfn2kcXBny7H/oFaC7ZXUUHl/OtDXJtyy++Ptc2g/lzcd6Y6O5NS9Rq8sL2LtuDjtjCm9JfFF/+Q5+izf6e/2t36gURalnXY8QQgghhPhfJHNMhRBCCCFEvSCJqRBCCCGEqBckMRVCCCGEEPWCJKZCCCGEEKJekMRUCCGEEELUC5KYCiGEEEKIekESUyGEEEIIUS9IYiqEEEIIIeoFSUyFEEIIIUS9IImpEEIIIYSoFyQxFUIIIYQQ9YIkpkIIIYQQol6QxFQIIYQQQtQLkpgKIYQQQoh6QRJTIYQQQghRL0hiKoQQQggh6gVJTIUQQgghRL2gnjBhwoQ73YjKpPX895uNODZrjbuDpq40j21fT+az7ZUM6RlwaV1jVQo/fzWJ72YtIionh/hjVbRr533T2lIcvYY3PppMdeB9BDa8WKqQfmo9X749iQVrj+PQvj0xiz/k8+8XE61uRa/ABjet/lopLH7hLdbkutKrjdel0pLU4/w4Zw7GwNb42ljf5Dqv5xyzPhnHtLnbic3U0SbECyvL2ueaouPb+Gr2ZyzZkE+DgGZ4N7ACwJCZxKpFX/D19H1kNgyhvY9tXaxTfPPe28xYuI80gxcdg12uW3tp/FFmz5vIjPlnwTeIQDctAAXZ25k84VPmLomk2DaY1k10141VeHQzU2aH88uvxbgENKORXkN1tYnUuD2sXjGdDbkB9Gx6/WNaXJzKuX3r+GntChSXjvg5WdUtKeHQrz8y8YsZRGxOoaFfS7xdrn288vLiiN62grm7j+HmHYKznWXdkjLOb5zHuInfsW1/DO5+QXg0tLlu226uLNZP+JTvshox8OKxyt3Nh2M/Zv7ataxdm4j/kM64q1RAGQnrfuaNST+w/VA83v4tcXO6dnvNlWUs++oDpvy8mKhcD0LaeVF7phQSNXcK70ydw/7TRbQJbY6d1vKasW4Wk6mClNM7WfrLNHaUtaV7Y7u/8KsCjv08mfemzeVATBkdWjdHa60G8tmx/Cs+mzKHnfvy8GgSiHvduWLITmHNoi/4esZe0p2C6XDpGjnN1PfeYsbCvVyobESnENcb3hZzWRE7lk5myk+/ckIdRM+Ay9dIjdnIgc0/M3nadyw7oqJH7+bYXiPWzVPKkS0zmPjf6azflEQD3yB8XGuvEVNJPtuWTOarn7YQbRVMjyuu6fPrZzDp5wVsT9HTPdQLSwsVkMOm+Z8z8ZuF7Dtagk9AU5wdNX9Sby2l2syR5V/x5cw1HKrwo0/Lizf7FBZ+MZ6vZ20k6ryaoJZ+2GnV14xlLMzm1yWT+WrGds7aBtPNv/Zc2TNtHBOmL2Xt2rWsXbuWU9Yd6dXU/k/jmM1VpMTsYsWy79lUGErPgKvXNRRlsmrZ13w9bS4Hslzp1M6bP72rGDJZ9+NXfDl9HqvXbiO9ypWWwZ5YAca8dCIWf8nXM3Zx3j6Yzn5/5dy+iZQaEnbP5ceIZIKDm2GjuTg+9sf93rVU5Jxjza+bcPRsgcN1jtP/ioqig0wZPwdL72Z4uf75+XYrpB9awEcLD+DXvQPO/yBOvRgxPbdxBqUtBlxKNmo1oDj5IPM2nrl63bnjMPs/QXh4OIM8jezZc+6G6007Ec+qNXsou6LMPvAunmycRFTOlWuqcGvoiW2rjjz/xvN0crOj18OjCWrgR+92N56UznzgXaL/cIknuTFL2Xgg6apSnUdLOtkns2FP7g3XeaNWj5vKqeDRhL/7Gs0St/DZrwW1C9L28c2JKkaO+owPR7QiK/4Q6aWAqYLDBzeiafMcn376Er2KfmZ9Qu1PZt0/HkOvlwkfNxJtxBQ+2XedygsSWBaZQKfB4/n0nQdxTNvIiazaRQvGz8N32DjCX36YnC9G8nPUdWKl7OKLEwpjxoTzwZPNSY49SnY5qNWWNGrckaEh7uxNKP1L+8Te3oOmXe6jr6uR+Jyqy1UcPsOGo/DiWxP4zz0t2DZ7Hqeuc8gaNPCnVee78dVUklViulReeGwNy2MbEh4ezn8eDObIyYMUGP5S826SSo7MW0yCcw1nIzMvF5fFEd9wCOHh4YSHP0OgSgVAweFl/HLOi/DwcF4d3IQ9J45Rarx2DflbP2NlZjveeSecFzuWkBBZW5654Uvm5oURHh7OiFb5/HQg+xZt4+9ZWmrxCuzGI0GObD5b8pd+k7F2IktLBhAeHs4zLS/w7f58AGI2HmBzqgcffvIZz7ZpwJqF60gtAcwGjh5YD6Ej+eSTl7ireBZr42tj/fzA25T3HEv4G6Ow2zSVCXv/YsMjv+Xx+SlXFaXv+Z4Y14f44IPXGGOezMyTl5fFzv6YY0VBvPJKOOEv9kX/F6v5py4cO0vEITOjx0/gjcGh7Jg9m6i6w5u8dxaJjR7hww9fZYRhCnMu3iQPT2ZCZhfeeOMdXm9+mol7ai+E479sY1tJEOGffcpwf1jyyw7yKq9df9XOD4lQD+Sdd95grP1S/nuwtnzrxLns93qU8A/eolPFKb5Zf/6625KwbwFZ/o/z0Uev8FjFVBadri2P31HNfeHhhIeH80pPLVtii68ZR622wqtpFx4KdmZzzNXnXLWhnN1LF4HzUD76KJzXH2rNNdNJUxFRBi9ef/sjwsPf57EBwXUPHAqn9y+jpNnTTJjwMveX/cCys9fdxJtKqakm+mQk3q074qi9MgX5437vWrROPoT1G4Sb/V97YD26eAub4lL/ZotvnoUfzORW115jcufEoQgSM659vt0Kbq3uo3fhdyw7+M/i1IvEtNpYhbWDHq2l6opSNVpbC2zbhVy9srWWFEMSGQUF6FsPZ86cpwAoyYrmm/efJCQkhP53jWLmvnMYDCXM/k8vhnywmJIqWPpac9oNe5kjKRUoKfMZ/eAgXn3laTqFhNChex/WxIOFtT0uDtacnP8WvVqEENB9GAvyjVg6OmNrZYebXRojPHwYv/wUNnof2uq0mMsL2fTdK/TpEkJoaCve+2k1meW1N828xPU89VBfgkJCeOC13jw+cjEUn+KzRwfy0eYZDAsJISQkhDdWJl+xkRrs7MG6RcBVm26h0dLEvxlgxe02dMo0pg7rgmcTL1p21WFbN4iRHJ9BI68GuLh44u7jSk7KBcryizAZTWSl5NCsRRM8PFywbmBHYuQpAJ5bs4m3+7fFs4UvrbtrsLzOPSUvuwhLlYK3jw8ejVyoqCwjJ/ECAK/Om89TXYPxDPGjfY8a1NeJlXj2An6NXXB2rm1v5rlkKotLARUaazv0OntUKtW1g9SxsNBgbeeI3lZ7Vblvpy58+v5rBDfxxaejN/6BChaXQhqI+PhVPFRD2HLFb9RqK2x0jui0V4+BWFiqMTrrMRgKMVapyC0oxGw2/6X23QwXjuzhQKUvj/ZtzW/HoMyVJRQUFFBQXoqpLi9XaS62twijEXLy86murr5mHbnp8fQYNpCAAFdsvAtYMWUOVYCFlSWVrg0xGEoxmlSkZWVeM87NpFJZYKW1o4Hu+iPwF1lYqzG4OGEwlGE0qbiQmQFAy4GD+e+4kfh6NcKvkwde/goqFZjN1WQkZhLYsvYasXHWcf5wbRY2cmUE74a1w7O5D626WWFZt/PLzkcyaUw3QkJC6DPkMZYeOIWiXNEIUykF5Vfv7xP7YmjVLhB3d1ecA704tXl/7YLzc/jubGcGt3PEUFOFrc6W2zXm5N2uI598+DqtAnzx7uBD4+YKqrre6PSROELbNsPd3RWnpp7EbD8EwJ6Nx+jVLxRXV3dcm3hy6JdNALR9+DGmjH0Uz0aeNO7khoeXwvWu4O1rDtOxW0vc3V1xadaIo6u2AtDv3Y/48bE+ePp7EdhVj6OTcp1IEHvyPMGtmuLh4YKjnyuxu2ufrJ5b/Q1DPT3xdHPibFwrwl9uds04KtXFe5CO325AxekfiKlqQ5vGKoqNNeh0tld03gkMUnkx8ovNXJXOmgwUFRZQUFRIaZURpQZQIDEmlZYhAXh4uGDfqAFx+45fdxtvthoF7HR2qC2u3NDf93uzHvAkoNeTbIurHSxYNa453qH3sPFwKhz4nJDgIHqO+ITY7NobUEVqJK8PDabV8Me5NzCE5h368s6mw5gViN/0Oa+MH8WYQf0ICQlhwFOvc7xugOPcph957J7avvjxd6ZxJq82qTs561FCmvnw8AeLGTdoAG3uf5lDJv6cYuLE7ukM6NeV4JAQhrw0hMlTd0POdp5qFcpbP35Iv7o+f3LtaU1Z7lmmh48mJCSEvr2e4Ltfz1AFFCUe5PXBvrR+fi4/ffQKYZ3D+O/OJUzs0hzvTsMZ3PUe3h3/PEMCQwh7YzJxdQMAKgtr7LycsGx4s9/kXp+ljSOtmgdTVXX9da8Z5+Y058aVxh5h9yEVTXv8/vkv9N77mVjd+qqywEcncc/sBaybswsLFxsa+DzGqw84M3/aFtq8Op9Tn6mgPId5b33HwZBPeGj0u5RF1QDwyKfbqVlXezNT+T7Fj4vbsy8xnfse7cdvB7xN2rtZfvS/GCI+4LEFKTz5oi26knLKT20i556H6HpyN1FNu1NtaUnGmd1sOV7GPQ89iwbIOraDtXp3Rg7vQkHcdlRN2vNEF3d0Jee4ENwcHEN4f8lGdL1eosfu72n3B/ul53Mv4eAb8LtyW1sdxWvmEdHkZQYFO9zILr9xSjXZ0ZvZmObL48/+Sd15hdSelVcnaxiNkFtw+d/mUs7tWUOEcRAvdwYo48zmzew4k8Ll696foa8P/d2xoaQM7K4Y5zZkczxiGRFOb/NhEEABh+av4kDelbfpljzy+j2/b29ufm3bboWSM2z5ZS1K0EMEXHqvoaZxl948/3ohvn8hhGNgENbb9xERsQm1IZCWHVthb3v7Lttt898h0jSAmowUUqNdOJjUmS7+duAYShftcubMiQJbS3Qtx/Dxo/40aBGK1daDRESkoK4MoFW3DthYXzvd8e7wAHGzP+W/+20xGlI4U9CYZCCwSy/4MIKIomI0JQ7c+0jj27LNN8q9212YJ6wnoqAMTbEd9z/5m/YWnWTzxoM07PQgHvbAb0e+jaba8/Eicxnn960houoexnYGjIWsXrCUIu+BPPusDRgKWTZxAe3XfI5Dwm7WbDpJWfJ+kjMq+KqyId7twrive9DvG5pe2xuXxp9h69HzlE12w8UvgJBWPRh2bydu612lJIatS1ZjavEggX80o0dRIONPRsrPXz0yXJN3lM07Y/Hv9SB6G6gsPsP6nzeTdmkNO1p06UffLn9wHiVfuOqfRQk72RRjRf+HGgE15CQcZNP6w1w+Og3pPGQgXZr8ptE1NZB11es2qtIPEuvny3DVjY8D5UUdYsHGSGITXNE1CaJXx17069aS2kkyDbj/9dHYd/C7PGRh5UQnDyNrli+i2kKFxqc9ox4aQhO339yXzdWQdXvfwBUc205iooZu9/9+IsJv+72npi2meEE5fqVH+HGplkHjI/jEZz9tWvuA9Tsc2zGIb+seUABsfTrw9tinOLXZiW+nL8IpZSPv78zA3E+h2YB3mPJREJldQxgW5H+50pLTfPP1alrc8yztAfJOM+XDFXz1w0haP7eEfQ1fYNjGKl7/fAlfuudRXAb8Sc5XYzaSkRqDX7d+3OXgiLkki4bNvcC1CfOjopnxytf0+/Y/XDoDjQWsnLMd/4cnc+o9B6gsYPmnP7GrU0vCGnfhqy+/4u4PT6Ia+DIrxtZO57FbUMKx0el88nk3XvzsENP3RXFmzhtcSIdAf7C21fHEs4/QyPt2vf+4moO+ARfWzySy8eNXTE36e+54YqpxdMbdBfIMv38M8e4+ipd/U6a29qLPC+/QB6gsWMaLgyK4MPBuEu39ePHiPcLOlQD3FE7nU3ui3YAOw/vhagf4O0EmYOWAQ4mGVb+uoOnAldjsHc253I5goaLaogBXXTCtg2o7gaCg9ng3D8QC8L9rPGN1pyhIL6Qi7zyROX9teL3Z/RP5o+drs9mElWcAXg2uPYfqVkhc+QMrSgIZ8khP/HQXbyoF5BbouTSu0MARrKyAaioq0ymvABwAjQYaXr5QDi5dRJRVS0aM7Ejt7C4N+ka+tEDH5fEel7qktJziknxMJmrPWJ1d7R/AVJzLhuUbqPTqxDsvd8QRAGtcmjQjyO3K93me2AIG8snNL79c3FBf27abrOjkLr7dnkWvux6ib+umV8wF09Cy/1Am9P9rcdIjY7BrdxdjewVSnX6cH/ekUVpRjY3u9oxt9R7xOZ65QO5OdLEuuFx8ZebUmXFTOtf+vWofTwzZCo+OJu3QKey7DuCVHv6YUw/z7f5MKqtCsLb58/Y6tBnOG2N8iM+swNEzGCWlEC8gbv0evJ/5mFdCwRi1nHGHMxgUcONzLW+1s2t24v/M57wSAsbji3h5fzr3+tX2YAWHIvh8dyVDBz9A65a+WAJmaqgwpFFWATgCGktwunyNHP5lIcctW/LsyA6114i6DEOVI51aBGGrr01Jgto546i2wNrRg8AgEwbVKXQ0IyjIHSd3PWoVmMyJFJUAF++P7rV/KSzII8/cmI8mTqSJs4qICWPY06ETg27TLi6O3sO0bRl07/MQvds0u3SNGI1JFJcADQGVCtwuPtWdJzMbuJhT+Da6FCtvzwomHVQxfOhQQpt5ogYsrfT4BQXV3RMArPFwsccCUJRY8goAj7pFXh6X1spY9wOz0vwYOuxemrs7AApaB1cCgoJwv7SWDlf72iTPWJVCSSngBKgswOXSxwmAmaRTuQQ0a4qF+q+9ifkjuTm5uDR5gs8mjcBFZ2L5xHeICf6Gdo4Azjw35cOrf2DtRv9n/0N/gJpiIpaupyKjANw8MVSlUlpObXKlVoOL0w2360ZYN/TA3l6h0ljzu2W/7ffUzl3wqn6L5Rv8MZ3ZxwbT/VTYh+B6nU8s2nQfSBMnoMwOe/vr7HdNKtVVoXQMuvgQF0Rnp8BLSb6Fxoqu9w+gU4ge0P9ZTlq3rg3dB47FMTqJ8tQsUjLTKSwu//MfVOWQqnVm0MVvEGyc8HPLZl8ehNVV5Nl7AKOGNL38m1LQeTcjyAWsWvnTwhkuXJGDWto40HfwM9fe5lvIZKzCzrvZFd9J/H13/FW+1qMxgU0Uskv+yqjVfl7Sh7EpqvaJ36a4GFNYF7z1bemRc4CpCXXpUV4cO093ol/dY8mFzGxM5mp2LJzKdz8fuiJeKTl5eVQZIfKTMYx/Zi5/PrvQHle3cg6caMcjw9xoZKPCpQYs1WqcnLtSrsvEpWUHwsLCCAvrSUtfJ9TAN0OeJ1bfmrBHHiG0rxUa1eUrSlHOkJYBuTuX8oD7GJL/wh4wGquwadGN1o1u5wcw+Sz5/Am+yxnImyP6oz/5I2+trx0V8GvbCYcaO1AUClJzKTdaonVqgEZrS3DXfpjza0ctI9ccxKNdKyCDqS/04JB2EGOG94Q1L/DGdgBrGgW35+6wsLp9GEZYWFucAWdffxp5NqWmsoqqcgMX4rLR+/sAiUz58BWqA+/j0Xs6UvBNd749CmBHk249r4gTRlhYCHqgccdu2FbVJqK5SVlUqWyxdryZY0QK56OWMWl1LM+PGEZXfx2b53xxaU4sGIj45FU8LO6/6lX+n9FalpGfnwhAZUUJFllZWFT//oZ+q/i3rdt/PUNw8m5NgHPt+TtzyBCeXFA7OfjoxlUs8fWqa28peRfbW16EZVY2FpeaW8jU/j1Qq8cQeUUd1WoNtqE9CAtrRfm8mQSMeg47QKcpJC2jdg55cVEG9jlFt2GL/woTe2Z8ShOLMFaXXX5npdMUkJZVOyexqDADx5wSwETU7hlM3FrOZ68/QBt9CcsWziGpCCytrAntMQBz3WvDQ8v349GxDZDBtLG92Gc1iBce7olq3cu8vg1Qe9O5hYafUquuOK/b4aJS4eDZgl5hYYR1CsC5RQ/CwsLoENgISwvo9sgIjGm1o2K/frUS/7t7AuDz+Ce8azeX3emFkB3LniNt+AffWP0NCkmnVzJpxSlGPD2M7k31bJ0zkaN1MzU6D3sSY0bt2OSWqavx7d0NgJ7PvkjF6dr5hycjDtFsyADAwOGNUwjfp+XL8Q8QpE5m7pJV5JSDxqYRHa+6B/QmNMAFDdBv7FsYEmsr3D1rE4H3DwCKWT/9FT5N6MkHLw7EM3UdE1edBlQ4uDWl21WxuhHgao8KaD/4YYxZtW+Dds7YgHePzpc31VjCqbIKmrg0+kedbcgLX9LVHMG54gpIOsTJmLb4XMq4Exhs4c1zX2659Co/dvNmHnvtCwrKqygtyGPN2RNk2ViDSkWb/kMxZRcCsGfeNry7dvgHLfv77Pxa4uJiprjyWu/Ea6nVKgLdKzlQ7cmIxxuzdOka3Dq2/QdTTnJIuVBBjdHAkmfHMHPmXkw2A+kWGscZK+9Lx7drB78b+gjQUFzK1HdmYNG0C2FPP02z9irUV0yCqqhIoqAQUheFc4/bG2TZN6djyTnmx9e9ASxM4mBMC+4NuPGHmDutsqICp9a98G9441MO7/iIKYCNvgEF52LIK3PGWXetJulp2r05Oxe9w9dvpkPTu/jq+x4ADP3qPVZNfZ3+Y2Nwde3MU1PG1Q6X+7bnbt0XPPPQABq0GciD3Q38tGYvHV8Nw625Oy6/zubZQXOw6vAQX379DObIBby5UUF18AX2WY1k3Zwj2CZuZkaHRQxoY41zWg/6am2JCRvDoPJmaNRg59uEl4Z2ZsL4ESQVVKJrexfPPPw0A1u74duyN4fnjmfBqUwI7Mc3H3a9tDUP/Pc+Pn6mP9+7B/Ha1s/xu85+MpbmcuBkNNYhD/7DPf43lfwfe+8dV2X5P/4/4bDnAQXBI+IWt+LehoimOTLLbJhZVrYzNdumVra0TNMcpblSc5SiuPce4AAU2XtvDhzOeP3+OIhYBr7V1M/vez8fj/MQr/m69uu+7uu+XumkxguX4iYycIvZKWDqi+Y/1B0Y0/BPHhk8CFuv5rz+/uf4ugLY0bpxe775+m2mX0kmYMoqprUAcuKIj3MgfPF4diw2J/HYVzXk7+BLYMNEJr35FKlaC57+eAld6wJpkcRH5rBv5lP8DGDhyKuDa0jLvTNjG2wkKCgIp/pteWvadLydoLw4m1+mP8WmCwDrCdrjwZMvfcD4R27yKrSCmO2zeGf+IcoMAMfZ4DucXYtfQZuURNzxnTx7fBMA9TsPYVrl84gBj0Z16ROopuq+yoXlzzF5TcXK/OtmPvd7gV3zRlOr+xP0XbeIoKC5OHu14t0pH9T4xfHdJvnoMj6auw7KnfjtVAfGdnFnwp8/YzFzOkFBM6jfeTAJix4GoHbvZ+i3ej5BQV/hqmnP1KlTcXG8tozo8PFvQ3+a3/C6WLtvJe/NXomFpj3jP9jMMxWbA5pRn9B/7kyC5kRSp8Vgvvmk6z0rc3F6JAtmvcXeKLBiN0EHGvDGO9MY2qsRYMJN407PwA54qK6rGz5PzqLndzMI+uYKXq2HM/fTjmDQUZSYSdzhjQw9vAyAZv3HMsgKsLShReOOzPl6EjMjk+g7eSUftgRyEoiPdeBi1Hh2LjGnPXK2+d82Y19h9rI5BAUtA3d3fNo9yfT3huNz7ayea0M6+Nz40OrRZCTFc2YQ9HkkLV5aww9drvnU5/WFG/n0i7EESTumzZ1+S8dL7galSYnEndjBuBN/AlCv40CmDTf71W0yhJDvphP02RXaTFzLd9deezUYxxjr2QQF7UMzYCI/jXOE8nzyE3KJOzCPgQfmAdBq6OvY1KC52DSdSL3tnxAUdJYmY77ip75ASQ6Z8Trizk1i4E5zuB4v96g2HQDfxoGEfPsRQR9H4//6CmZ3uO5n0OnxdHOhrk/NGn9pbgKLZ0wgOALs2UrQgbq88Pr7jA5sjr1LR558YhhfvT2KTz37M2fOe1w/RJBPu8DeuPm6Vy7ofgN7M4lEnn/yUUw2Ljz59of0aWHeeW7cuDch30zjm/fj6Pr2b8xsW6Nodx1blRAdl0hZK1fsrKtRwixVqDw6MtDaG/WQSYxav5iW9QCiWTDsbf4sM29o7dmxBxu74Xy5qDdbt54lLGIPy73XU+vkFs79Fc5UFz/mjW5Iq8GtOPTJZwz6vphWw17jg6d6Yw2MmvElS2bMJujLdPDzI6jPq7w8yoltr3/Mr1EpwFiCfoCAqauZFvjvt8hYWtnS0MOdpZ+8yPTkfDx7P8sXb7ao9O8a6Mp3o4PIadiLr8K+xQvw+ug1jEu+JejD07i7t2XM9Ck0s4DEc2v5YtqvpANBW0DTIZD3po7i0LQQ0kwuLD37KP45Iby9KYBB2kKCt2ykwyuPcerScMkAACAASURBVM8vbalCSfplgs9FU+tm5xP/ByxEpObT3f8x5ekn+GNXKl0HP0Lj2vf+w57/K2gzowk5cpqmA4bTxvneXOqioKCgoKBw9xBSzu/iYLwTQwd2w1m55un/N+RE7mH9+VIeeXIod3KJ5wOhmCooKCgoKCgoKCjc9zOmCgoKCgoKCgoKCqAopgoKCgoKCgoKCg8IimKqoKCgoKCgoKDwQKAopgoKCgoKCgoKCg8EimKqoKCgoKCgoKDwQKCaPn369PstRHn6cX7feArHeo1xrzS3WMC5Pzaw6lw5Pdtet/BhKM9gxx9r2bJ9LzH5+SRF6WnW7O7dCl0Se5SfV2zA5NMDnyqXLeoLUtm1eSWbd+zn6NGj5l9kPv6tGmFtdbf1+wz2/rCEYwVq2ja5fmdaSeZVtobsxOjTmDq299ryUwrbVy5i885zJOba07ShB1YVlkyKr57jj5BV7DtZhHPdenhWWAcqz03jyN51bNx6iVzXhjSrNNeRR+ju7WzZuI3wrHIa+DX8uwHTf1CaHMWOXWvYtisR6jTAx818rVh2eiTnju3kcIolbX1vpR/kc2bP76z6YzcXL5fgoamH2skKMFGUfZUDGzaxZddeclVu+NTz+Id9+H+kFrqPtSF/cuKqBb6+XjjamPuCNjGSbTvXsGNfKpZevtRT30p76UkK28/vh1Np5+dTaUc69eROFq7ZxLnwBOzq+OLpYlujLfC7RXr4blYu38j+o0c5E1pOoy4NMdvcKuDSwZ1sXv8X59NKaNCiMfYVQhVGHGfdjvUcPq+jdj0Nbg7VXweTk32Vi8d3czC+lOY+dbGyvLF02bHHWLc9Ap9G9XGo6YLKu4aOmIs7Wfv7Fg4dTcLBswFe7tVfZVdUlErS+SPsOBOGfa0m1Kq0fFJI2ME/WLUhhNDwAmp5++B+bYzkZXB07zo2brtIlnNDmntWHQllXD28g7WhxXTxq3vbJTGWFhN2YAMbgk9z1bIBba8Z5yiMYOUPv7Lz6FGOHk3CrX1TPGweiKutFW6BgoQzrP99FZekBS2cC9izZSWbtu8nTF+PLg1ubo4y78xqflwVcn0NO3qC2CwL6jXyoYZhehcRUs7vZOuJDBo00GBbuX7efN2rjrL8FI6dPo1DrfqVc+//6+iKI/hjcQgqTx881Pf2UtPsyD2s2BuOV+vmVSyu/e88EC0Zt2MuxwvdcL3BbKEtUXt+Y9pPh24IG79lBpF53vj7++OaF87vv5+97XwzLiewd/85qhqutHb1xiNpA3vjbwxraeOIuiya4DgV/v7++PvV4uKhs+jMt6vfFpve/ZGrN/Vx4NyaT1nwx/kbXK3t1VglhrDhROZNY/2X7PtuETtKvPFv0ZSivVv46XCFFZ6MUH45mkDjph1o52NJZPg5MksAQxlhJ0JItmhAhw5+OEf/zsFEc5SUTdNYH2+gtb8/xrg1fLYtrfrMCxMJPnYO29ot6NCqLnmX93G5wmi1nYM73tZF7AlNqD6NCq7sOczGsDz8/TtQOyee9X8cJrcUjKUF7N3+G9lOXnTw9+fy0Z8JCS+sPrHoYD45oqdFi3a0cYhnW2hFOfJi2HLsIi7erWjfvDaZkQeJzqtZtpLsSHb+vppNx6IwGCrMJaUc5/3FR/Hy8qdtIw+KEwoo11Wfzt0kJeEC6SbzeGvXth7Xprn04Fksjiihtb8/VunBvLepwiJ50mG+P5KDn18H2noUceLCFUpqMPBiZ6emjr2BkxdjKNXfaNVKTEkEL/yZrWHR5N+Sdbi7Q258Eps2n6RWo9a0dbMmZMkKztcw7KytHXGtXZeypFDC08oq3WOPnGLjyVTatO9A3eIMNv6+h7RiwFjOxRPBJIgv7du3wC1mLfurdOPs6NPsDdnCun1Rty54+Bre33rjeMo4uZIjeXVo164lzRN/ZuPlCo/8UH47bWGez/yb4m6l3Cf5fwkbZ08srp7ipy8WctXGgfqesGdHHG00zv8aJ+vwAk5qffEoPs2ZQjdaNmnMpT17yLqHc4oYDZw5+CcZ4ozNDZs6N1/3qsPK1om6dethb31rqkzE9uMcia9hvfkPCV6wkf8693KtsGHZj4RG3Xs9wd7NB9PR6ay/9Sa8KQ+EYlqan4d745Z/s61qh52jDRZtmt8Qtig1irT6GjoFBDD06SmsWjUWAJFkvp/YG5VKRcOGw/k1KhOjNo/vnm1OwJSVFOpg4RMq6gW8yKkELRI1l/6tGjGgfyecVCqcPeqx4gLY1GpEl6buRG2aTEOVClXroewQUNm70qSRL55N/fFvoyX5og8rf/sEtasdFGYS8vFQfNxUWNv0Yf6W05W244tyT/DkQ01RqVR0e74rL7ywBnJP8Xq3Zoya8xZ+KhUqlYoxS69UKaUzDi4W0ORGOyw2zh50b9cWnfbe72oEvDuTH195lsChgxg+2Jo0rVkhjw+/ir13HTp3DqRf3xZkJ8aSl12AXqcj7ko87XsHEhDQhfqeBsJORAKgGfkzX054gl4BATT30HM1pbS6rMlOyaDEYMK/eyABAR2w1GWREJ0KgJNLHRr7NsLFvgbjyRU0DxzKl5PfITAwkIcfb42rWy46I6js3RgxdhZPjXyEhwICcLPMITO/eo0qbN8JGj/Uk27dHqJXjwac3n8KgIzEVMpVKjp2CyTgoXYYi9NJjrtmk7SMbZ+9hbfF8BtNkoqw/YtZOAx7B3+NU6VzTmI4DQc/ztixgfQNbEPckT0U5xTcUlnvCrZONG7XnYCAAPr0bsK1Jc9ryDfMmziGHgEBtKir4nKSFoArpy9Qu1VzunQJoE+vpsRcCKestPpVz9HJgwa+jXF3+pvRCBG2v/oUhUM/o29T9R2YIfzfcW/QhCmfzODJoYMJfHYwbZskkV9WfRw7O1c8fP1o4nmj7fFGvQKZOXUKAwcMYNBofzw9sigzgEGvJyYihvZ9zGOkgbeR0GMR5khiYsevv+M7fDzN3K7vokrGRd4fVgeVSkW9dv3442IsN1xEXRBHWPKN4+nUriO0eyiQvn2707mtPQd3nKr0s67fgYCAAAIC/Kljq+yW/l/C3r0+LXzrM6pPEj8vukyLNq3xrtOMPk3dIfUyyyd2xclOhUe9R9l4yPw00uydY2ycPprubX3xbdONR0aO4Kv5H+P377rsf0K50YL6DetjZ1X17cg/172vu1tSu20Qmy+Y57zlT6uw9O7J5oPRsPstbJ3cCXh9AXE55ofW4uiDPN3LG/8xT9FRpUJVtzWfHArDCFxY9xaDHulJn8b1UKlUNOnzBEeSzPlkHF5K7ybmtbjHhG9Iqrje/fjsrtg6qXlxzlZe694S+87PcLjakhm5fGol3Vp4oVKp6DnuYX744SCkbqGPjTVD33icehVr/pR95hgi6Sx+b4h5TNcLYP6JeATz7uMTHSxpP2UrG2aMpXkdP6buXMJbXu549BhF94Yd+OKLl+mpsqLzpHnEVUhgaemGbV1XLNR309T2reHo1Zwh/k3IvYWNmOq474ppWVosl6MtqOPyT8WiVd+OvDWw3Q1ubV5eSPdD83llyBBeev9TNu9JBX0hv77/C/U/PITRaCTu/AJKv17GOdx46YN5jOhoNsU2cVkiX79gtmNs0ewdgo9dZOXqneQbjRRlJfNcFdNsCUkdOZxnJGJySz7/4fq+Zuwfn/LE2G+5WFUoJweaj57E0tXBbN3yHkVHP2N/vNkrftdi1MPf5Y/gYKZ27oy+SV1w78L8E1HM6TORU0YjRqORtS/eqIB3fyyQJ7s1+Ued2NjYUhpx5B+Lzz1BTBTEHOS30Do83/tfZrL0LCi7yQqu00Ha9Se4rKt7ef/JAXy7uzGfDfYCdKRcPM3ukBBCKn9nybpZHvkF5t+/UkL00YNV0gkhJOQiVceKFMexd+8p1PX88ajUA7WcWTWdkYEPcbbgEQa3/B8Hdmzizd1z86GwqOI/lng0acFDg/ypXSVI5E+DmJfWGfe0o8ReOc/pBLPt5Fq+bcg4sJ5ff93BH2uXsW77AXboa7YxfbdwQc+ueW8wZMgQHn3rY3ZdLKr0K0w/zYxng/h8kwNfD9fcPIHkNNDf3luFmNUv8F7yQJrmHeRy+AVCE3JvK507oiydC1vmcEE1gk717zAtbQKHdu/Fsk53NDd706orh7QMAC7M9md9ZjMs4k+SHBPKmUQtGErYuOpPGoxdQHBwMEs/Gc/+79eQYTBRmBrBgZAQQk5cJTviECEhIZy6nMLfNqDNxFWsxnbeNIn4jiFDhjBk7It891f8HRZQ4b4w5CeCLDexO6qAyub2rEWn577gj83BLPsmiAuHfyEy+34KeZ2S+Agys6xwtf/n8aa/r3tvrf2Dd8ZNo4dzCvtOXGXw3BiWfzCWTl2awIAfKEkK4/WgepXhnZr0Ze5n72Dt2JrlqUbStnxJxokY9Aah7egfWPfzFv64EI3RaCT60Hp6+QClycxftJ/X5wcTHBzMJ93LmTttJVqg+7STZPw2mnP7Ixj27SGKt0yheTUbkabyUiLOn2DAe9/yV3AwY1u3xFjXHeqO4FC5noWvf8fVijX/mwDAUMKGr9bg+txqjEYjyZfX4LJhM8dKhNotAlm/dgNOZ7dxwWsSJ84d5f3WI5l75Et6ii9zf5tNyE43vk8s593a8cRUaKY29raMGNmH5t5ud6fB/kfsHRzIDTtQ+bBwO9z3R2R9QTYZ2eBu909Rmg6bwXd/c7Oyb8Ko2csYBRQk/cKLz62nZ6c+XFK35Ntra6NLPdo1uMy5dPC7TbkGvDWGei5ASy84dt290eMzWPVKfWIuXN+/yUs6w/alGynR+GCtUiGO1886Nh02mYDfQ4g7eRLrDANe/rem7Pi/shH/m7hbWVlTnhZDcr6e9vXu7fmR1AMb2RpvSd/HB9Gs8uxKIfmFpdd3bZydwNoaMFGmyzLrqC6AlRW4XN8J9GgayOwVPYnc9y3vfn2Q7T/2Jj81kcsRCVxXuxrSfFBHnCmluKQAgxFzj7W3M//+FR3ZMVeJyL7xVXzbQW1wAwrOH2TFqRSaNetHvz5NqgwCBzo/+xlbhhWw5fcvCd7bjldGteDfySI7p8rKX+vaRKClqLjILK8KcLAHu2vy2tD16VdY8/SNKTm3H82junwirsSSnZFJfI6OPgB1u/L164UsCb5Imasbndq1pY31vds7bNr/dVb1fx2AwqTV/LI+lKA2fQBw8erCp78EE334J577bDdHl48A8sjNrzIhqV1AdXvPv44tBzM+IJGIy9Gkp6WQlKu90+L8T2gTIvjz8HlUtj0YP75bxdna26Mw/BirjsdRv0EfhgX6YQMYMKErz6K0DHAFrFSVY8Sl63gesjUQERVPflYRiXl6Onnlk5mcQ2HJVUqczA/yjVu1QmtpgWVBOlERERTHZ1KcdpWIiFx87H1o11SD0ZhKUQlUGld3r9CKPQOYtyOgorDHefGVgzCswR2UUuF+0bZHN7YdOUpemSdgJOH0QXZtOoJ4+WCpzwW7+6Ok3AxdThrFRRbY3+RM6N/XPZX3EJqUTGftKleunIkg9cVHybXpgFcNS1/fYeNoUwfQueDmVsO8oT9LXIQJt4gIUgCwp33HVpQDDoDKxo4hrzzHwJ61gdpU9yWDpY0DPYKepHDHaa4cuUx5gYo6baoxH16axBWHurx67dy3kxct6idyJBV6NjU7NRr1HDNfan89Tiy4NutANw3Y9m5J57qQV2WXw9qxFk+88HH1Zf4PsbaxpSTpKtklXWhY6/ZMzN93xdTZrwt9uwmbMkuAmt4nhDKr+0L6Lv+C3s1r42qhwrGDH67OLfDP2cSqhMcY2wDIi+NUdFv61wNiID0rB4PRyMmtq1i7MZmPez1VkV4JuXn5lOvh0tLP2JXcjpc/H1GjzLb2jWjZFQ4v2IjpucF4x5wmz6UXb736BNlnVvDT79d389ZOWkCtd2cwqaErMTun8MmZ6ztOQjQZWZAbt4MZU04x5eCn/Mu+UyVabTGu/Z/jkdb3cps+n+1LZ3NGN5IJT7XF6vJKvk8cyeR+tdC08MN6rwlEKEjLpRQ7bN1csbLV0aitP7rcYvB04tL+C3gMfQmAVWPHYpryDWPb2FIWt5dw6QQ40WrgY7Qa+M/cjXW9cXfLw1hajt5UTnpSPs271ftnwErc6Tb2Rbr9w72cS0fX8ecxO8Y8PQwPiSEkOIR+Dw3CsSyX5T+toM/LL9Hao4jc6AOk1xpbba349etN0f4M6OtC4vkYXFq1AqCWjw+uVwyYdAbKTKVkZZZQr593RSwdBxfO5dOfUvni4jx6VLjW6zmeST2Bggtk2Vzmcf9alfmUNB/ApOb9yY7cxrYyPQ1d7l3bf//mezR+6Q2Gtq7HkV1/EeE4BYA/3niDrOc/YKK/I7rkw5yXBgA06OiPcZ95xzwzJg2LWl5YVSrlhax86TW+PtGUtRc+oXUNeXv5j2KSP1ASj2r1UYZ1qK7N7y7ZyUdYufYs3R5+Ev9WbpzaOJfEHu/QyRvAwNn1S/lw5jkmn5xPoEN1k6+BK2c2sWm/gcdGD6WuXTp7t26mY79H0ThY06h9J3Q5xVDHiQu7w/B45GUAGgS8yaQAIOco4fpMRrZzBRzp3Loui02tWDJh8I3ZtAjgpRYBcKyU3efHMGlio0qvdoMGEZqSBw3cOLJiN5pAcx7bPvyQ4HZDWfhEN6JCT3HA7u59RKpwb9G060rtE78TlgMYy7l6NQKnxo/y/It9uPTnbFaeK77fIlbi3rE/jY7+RXqBDqhew7SysqChVw4bktrzxeNpTPptC4+/t7jGj1L/nRxS00sxNdMR8tlstO2HMmJUIAHd1qPqNZznujS+7ZQBdMVaNv96nO4TX6W9mw371r3PuZzrinFZWQoFhZB2aDHTvy7k8wNv0Kb4L/5K0PJ8W1soTCEsphF97/TtzH2kMD8Pn6ET6HwnZZAHgAvzh8jUtRFSWm6qIeQpmdpomDzxRC/RaDSiefgNOVnplyZL3hsuGo1GunR5TtbFZpudi9Ll95mjpXEDjXR7ZqpMHjdU+r23TkREtDlXZO6LgdJEo5FWz8yUiEyRzH3fSaumvtK6x0DZvm+/jA7qKJp6PvLe4mB557EO5nwrf0/IX7klUpYVLTPGdhGNRiMj3lskc6YMkxe++kvyykV+GjlJHnushzn84LfldMr10kTtnCx9NRrRdBsuq09k1lhPxvJSObZ0gkz9M+Z/reI7I/eUvNu/8w1lf33D9YKkh/wivj4+4tfzEdkQmlfpXhQdKhOG9K4In3Q9vdhYeX/sQ6LRaCRwwq+ScAsi5JwIlr7+rcW3WWuZu/96Xf06oWp71JOnp2//90R0WfLHjLHiV6Ucw6YukYxiEdHr5fL2tTKwR2vRaDTy2rzTknsLcsUv/1Q0Go10GvOBhKeVVrpnH9ksXdv4ScNWnWTB4awqMfJl95w3pL3meTn4t7S02fHy4aNmuR6ZH2F2jD0jU/p2FR+fBjLp45WSUngLQt1FUqJ3yhNBHUWj0ciYz36TyppPSJBZLw0QjUYj/Z75XmJM18du8sbvRaPRSJuHn5d9UUVVUkuQJU8OlHr13pOwKq6b3tDc0LcGvr2x0s9kNMjcZ8zuAz7f+18W9QYub/1EOleRqeuw8XIs+ZqvVo7/9pF004yR7cW6yjhnFgy/cX4Y+JVIeYFs/26CtKri/vCbcyWhwBynOPaCTBzWVzQajbyyLukGGfJijsvEgeY4T62Ir3DNkqNfjDWn1aGD9H11mVw1VJk3T/8gT1eGNaPLTZfZ44eJRqORoYuiq/gky9y3BotGo5Geo16TsMKSu1J3CveGxEM/y8Odzf3j4+A0kehgCXrhRxERKbq6X8YPbisajUbGf/ytvDtumExbFyoiJjnww7OVfbFVh5kScY/lNhnK5Y+5E+XXQ0liMNaw5pv0cmLFDPngu+1SUJ4kH3aeIObp9KJ83KzxDeOtcbOP5UTcMXl1WHvRaDTy1b5sWfHBCPN8usBcytzYnfJG33aiqd9ARlSZT0uyTsr7I7qZ03rkEXln0TnJkxiZN7j3v657N6O0sES+e+YV6d3bXPddXvpOruZc9w/5cax01GhEEzhBDlcufJmyauYzotFoxN9/lPx6zjwPRB2aJwOq5N1r9FtyLj1cZrRtIZrW3WXWwmUyOqijDF8cI2un9pNhU36WtOL/uTnuKnptnmye2lI+O3Zn6ViIiNSsvv63lMZtY86KaB6Z8DLtNPf29fT/JQoTQ/llcwgdx75Ob7d7fFpdQUFBQUHhThETVw+uYH24GxOfH4r7vbunSuE/JvXkKr49UMxL771y28coAR4IxVRBQUFBQUFBQUHhvn+Vr6CgoKCgoKCgoACKYqqgoKCgoKCgoPCAoCimCgoKCgoKCgoKDwSKYqqgoKCgoKCgoPBAoCimCgoKCgoKCgoKDwSq6dOnT7/fQhjyr3L8dCy27nVwsr2mK5cSf+okR+MNNKt/3WqF0VDAhVPHORMWToZWS26aAW/vu3fhuC4zin2HT2Jyb0qtKjdXGbV5XDxzlDPnI4iKijL/UrQ08PFEZWnx7wneFgWEh+znqtaR+nWuXwulK0wn9MIFTLXq4Gp1r6/YyOP8kb2cuRBPTrENXh4uleUuS4/n1IWjRESXYudWCxc7s2yG4nyuhJ/gdGgSxfaeeLtcuxa5hISL5zlzOpTkIgMedT1qvDC5PDeN8xePE3oxB1xrU8vRbBuitCSeU4ePcCEiDZ21B3XcarY0UZYWy8kLx4iM1eHg5o6znQpDeRlhh0I4G25u29ikNKzVdVHbV1fPhYSf3M+psGgy8iyoXdsVGytLjEYdBZnxXAo/TbrUpa5rzddBl5bmkBl/mYtJ6Tg6e+JwzSpKeR4Xjh3n9MVwoqKS0du5UsvV/gF4oszh7KF9nLuYSL7OAU2da1a9ysm9ep69x88Sn5KLs7o2jvbmttJmpXDi+HEuRlyhzNoTdzc7bqUXF2Ve5WRYCu6etbC1ujclN5n0FGQlEhFxhgS9F/XUt2rBRChIj+LkhXQ869TCWmUJlJJw+RRHT14gIVmLs7oWjhX9SleQw7kTRwm9FEmh1KZ2bfsqdaIn/cp5jseX0bju7VvuMZWXkRBxkpNhsWRY1qb+tTFSmsKRnYe4EBVFVFQOjr7euNyj+oVyUuNCOXbiHNGx+di51salYkybdKXERZzkVFgcWSoPfKqM6byroZy4cImEAjvqeTpjaWEB6MlLjeXcweNcTk7DysUdFwdbqp2VxURq5ClOhEWRanDFt/a1yb6A8BP7ORUWQ2a+BbVrq7G2qn5+L8xPITbqPFH5NtSvfX2+Tjyzl8Pnrq8XWSpv6rv/0/R2VfQF2USEH+dMaBrlzp54OlfUiaGAy6eOczIsnAytI75e1a95BkMZ+RlxXAg/RTb18HL5+xxUzNVDRwjVOtPIoxrLRP8JQm7iRc5FF+Dh4Ya16lr93nzdqw69No+rsbHYOtXGtoZ2+n8FfVkKp/ZfwNLFHRfH27O8dLsUpV7i8KVkXH28uZNe9UAopvF/Tub746706NwSt8o7zUrZ+vHLjF5r5NMXelSGTd7zFb8fKaFMm0tWUijrN+QzcmS728o3NyGd8JgUatWtXWkCqzw7ms3fv8nFBq/Sp4rlAmNpAac2fsun21Jo4GpBXlokazaGM2xIL+xvYk71VjgwbwOqrq1w/YdPEUtG9mJ+SjteHHbdPk55YSa7Vn/Ocbse9Kn/z1j/JWfXLGTJ2VhU+WVE7TtLsmdb2tazg9wo1u08Q0lJMulJxWQbhLre3thblBN+bBtHo9LIydShK7xKuXsrvJ0g68CX/Hw8F4v8XMIvbuOsVXd61q+mG5eks3f/IeIyUslI0VGoy8XJoyFqO9g2bwYHU4rRpxRwZtNuLDv2o0F1VZMdyaqQUHRlyaQnFZFpVOHjXQdjQS6/zp5DpoMD2rw8Tu/4hXzfoXSqRq7w4LUsOhyGZZGO2MMXSbD1oUNjNUZjOYXZyUTt+ob5qX14osPNDKPfSGlpHrlxF9m09wBO9bvSwL1iQskP4+MvN2NtD3l5Olzq+uLj6XzfFdNjS2azOiIdixwtETtPkNqoF609LSiJ2ceGTefILMojN+kKSTonmjfUYKXPJ3jNSkKOpWBhUYKF0QFXdw3ONcxeIhls+/5zfjySS+8uHajlfG8mWpPJQGFOMjH7FzDjSmee6+p+S/GM+lS2zvuSeUcKCOzZAVcHa1LOn2T5X8GUlBhIPxfP5Qw9jVs2wEGl59Rfy1m5PRoLi1IsDJY4qn1xq9Dx85PD+HPZj3x1RMVLQ29xjovbxcJwVzpX6bdZZzey8Ww6xXklGLLOkuXSiQZqIG0rz713AK86luTlWVK/fVNq29ybB96cuCus/n0N6QXl5EWkcSkqE01rP1xtIe3MJv4KTacoT4s+6xy56o74ugIx2/luezLosilKiyPKuhWt66jQJhxhScghLLLyuZp8hZPpWto2bYqD9b+PkvJL61l2JIOyogJ0GZdIcOxIM3e4tHU1C49eRFWkI+bQBeLtfenQqPq5tig/leRTm/jujB2je1y3877htckcV7tikZdHwqHlLMrpxfjuHv+ekK6Q04d2cT4hlcw0A6UliVjWao6Hg3nd23KkhEJtLlmhIeTWH0iTap5VDAYdhVlJXAn5gl9y+vNou6plKCf60BY2bVrNgos+TBjQsNry3W3EZOTAys/Yl+VLj7a+VRTKm6971WHQ5hObmISbp8/1h/lqiDt+iUQrFV41TTz/Ecc2HsChZYM7UtpqQptzmUlj3sKpXX/aNK5dc4S7SElaBKt/nEJqq/F0urUp8+bc+V3/d07onECz5Yq/sXnSYLEcu/EGt3Nz+su07RelSETKS/IkJSW/widDln86Rvz8/CQg4BXZFJ8jhtIC+WXKQBn71RYp0omsedNP+oz9UM6nbuSezAAAIABJREFUaMUU96sE+TaUunV9pJmfn7Tv2ls2XTanFLPwYXlh+lcS4OcnfkNelkMVOWQe+F5GzdkvBTn7ZPOCvZKVkSNGo0mkKFsOff+y9OnkJy1bPiWr9lyslLc4P0zeeXaA+Pn5yePTHpcPP9wqkn9ePnt8gHg6uEkDPz/x8/OTd9bH3lDO+YEu0m3G320DiaTu/EKmbk68zZq+fQpSUyWjuFzEaJSEzTNl0pYMERFJPvSHzN96WIwmESlOkMUr1siVpCIpLymQDfOmS2i2UURE4o78IPMrLFbpcuMlvdBsJenIqufk4YXVW7LKvXJGflm1WtK1JhF9sezcskx2nTXnn52cIoU6g4heL2c/6yk/nK6+HIl7V8sP2yvshRXFyPxlv0t8eokYDQbJz84XfUW4pa98IqFaQ7VpFWVmSlphmYjJJGn7lsin68JuDHDwI3lsWdzfYpXJ/vmfSy+/V+XI3xMsyZRNa36SA1erWEvKPiYTpm/8e8j7Tl5SkmRpy0UMBole+Za8vN3czlmH5stH68JFRKQwIkTen7dSckoMosuOkRVL5srZxHIREbl8cosc2HypxnwOfDJKfvjzpHy1cJXEphTVGP6uc/xreWje1VsOvnf6GPnpr2My48c1kpJltqRUVlgoGTkFYhKR4pgz8vPSXyQ2T8SoK5GtP78vIZFlYjKJZMZvlU2LTlSm9ceXU2TznmAZ+/Gm6xlkX5HvXu4ufn5+0nvoMxJyJUlusJ1zdJYM+unG8bRjxnMSklzRl8O/kkkLL5j/TlglD7+753+ojLtHuVYrmVm5ojeapDw7WdYs+FxOpZr9tn3+kuxNMcurv/CVvL/U3E9Ozx4r318y9x9J2iKPvL9PREQM2nxJzTFbnEuPPiRvzFkoiXnl1ea/f+ogWRdbMdqjFslTX5wSkYoxXWQe06l7FsnH6y9Wk0oVov6UFxfeOF/nJWfKNVtaIR/Pkd8ytNUmUZIeL6uX/CBRBeaxdG73Qlm91zzXn/9hkCw9Y5Y39ueh8vzaqhaI4uVlv77y4dLD8o8RsneyPPvbjbb1cq+Gyo/zlkvkmaXyyJR7Z03tGiZDuayfM/EGK4HX+Pu6t+QJP+k69HnZddlsomnjJD/x6zlGdp2MFzkyS/z8/KTfi7PkSkaZiIiUxJ+Ud8f0lJGTJsmjfn7i12uI/HA6Uowicjl4lnT1qieaho3Fz89PAp96U85U9LnsMxvkqUDzWjz6o6VyTRs59/MoadW+k3y0fL989sTD0mbkZKl+iTFK7IU/5fFBPcTPz0+enPai/PbbKZGM3fJUyxbi5eYpjSvW/NmV1pGyZN03E8xjuvdYWXXe3La50UflzeF+Mvzr/RIyf6oE9RgoXx9eJ7N6dJZuT74pTwSMkJ9//kSe9Gshj335m1wzTFeclSJjBgbI6uNJNxPwP+fqz8Pkg/13lsb93njBWFJIXoEFDjd5Um/UxoMRvdve4Nb6pe9p8Nvr9PH1ZeikuaRmW4GpnN8nz0E/djWRkZHs3TCZ6I9+44qVC6Oef4eO9W0wCYyZtYeXgxpQphcsGoxj8bptfP3tMs5ERhJ64hCPNr+ez+k99iw5FsnawQ68//3VSveIReNo1elFduYZqO3pjqWlBTg60HTkJH5Zu5PtwTPJ3zeNffHm8JfXzYAhU9i0cyeTO3pzWmsE17Z8sn4X73cawx+RkURGRjLn8RufWtv2rEefdk34Oza2dhjy08kuMdx2nd8OLt7eeDpaUZ59nrWhbjzd0xEAvd6IzbWdCUsLjMnpSEkJiGA0mLCu8BO9EUNckrkMbr4Y44IZ08mHaVvbsOKZ+oCRkpxMkhITSaz8ZVEKGI0mLC0w17WFBca8AkxZOQDU0tTF2cpIUdR6Pjr/PKM7AegpSEutkk4iiYk56AB9uRHba33NwgJDYipSWoqlSoVrLVesAEP4HE42HUb7al/jg5OHB17OthgKYwkOLaVn6zq3VJdGfTmlWh3GWwmsssX95Hf4+vri27Yb7yzeT4nu/tvEUNerR207FWXpx1kc2pypg8y7HrV7PoTtge949NHmvDbrGF06dcDFQYWNrQPa7FyO7T1HYuJBVi1dxvr4VIqqySNx3UQmxw5lRHMD2vwcsop096Zwt0n86vF8Ej+EIU31lBZkk1VUDoCtszOe7i5YGIq4cO4Qeuf21FWDpaUKC6OKYzuOEBd3jDU/LWBNZByZwOU53fmzuBf+tcvQFWaRWWwA0RP8xx7avPYzO3fuZNUXEzn160ZKjCbKS/JISUwkMaOA0jxz38/MK8EkUFaqx+5an7e2QR8RZf7bygHVhvHmvtVrOEsOZt6zurK2t8ejthtWJi0J59Zy1dSLlt5mv3KdHltbs7xiZY3+cjQAWm05jg4Vr6RVVuhOhZn/tHfF272URcN9eejxmXRp8RB1XawwGUrIuGEOSCGnoBQTUFJSfv1Nl7U15ecuAhVj2skWQ0E020LL6dfW0yyTtoC0G9JKo6C0vNoyqjUeOACm7NPsc/XlyVrVv8Y3mQQxCVYq85xpKinFmJIOQKNnxnPo00AefXQ080J7Mm1U3SoxBZ22FJ3eVFO1A8KuFTPAvQkO5UWUFWdTUHZLM9FdQ1+US2mp5U2P5fx93Xt25mQGDJhAT289yRn59J+2i4/GdKFJa1/o+SGhe9fzcEtrdAbznOjg24WpLwwjPM7Ee7sj2TP7RS7svEC5QWg++EPmzljAvK27iYyMZPfqH+joDRiKWfHbYSYv28nOnTv5eoANi2etxQB0eGkDRz5sz6r522j2/DLOfTsS75R/L5tJV8zJg9vpMXUu23fu5NEGjkTpjOAZyOrwCKY/M41dFWv+e90Bk56tny8lP3A2kZGRHNo6i6LFm7mgB7fGPfhh9iySV81jTe5wVq1azjhNX6Ytf4FakWW8+P4r/LYwj5eDLzFCF0pknFkGKxsVvfo0wcfj9o//3Al29k6UZadQeAf96vbeQd9FCi4dYfchC7qMcvqHX9txy9n4Nzdrx9a8vPYALwPZl3/k2UnLWbumO6dqd+Lba7qde2N6NA/lcCI8dZtyPT77DRq5AZ184Nh195avLGfFi26EHbpedcUZ4YT8tJCTOSYMJktc3V1pUeHn9+RkvGf/wpy/tNTCkYFP3Norit7Tw+l9E3dHR2fygxeyocnXTOx1b7fpc84fZndYLP4jB9KmtmOFq5YSrY5KVcneDlRWgKDXF1Cur3BXqcDh+qHdum0fY+2BgZz4cwbPfXGc7V+0IezPVaw5Hsn16b4Nby5+E2/KKSsrwXht3rWxMf8AY1kJl0/t43iYga83voBZNczm0KJ5/JWaU0X67ry3ZDyWaCnRVllQHOzBsqoCWsqxlSfpPmHSLdVJYeQJdoVG4tmpNz1aet1CDFv6vz2dM2/fUvKg9mf29qPMBtDFM3/REYoLtDh6OtYU8z8n7dwB9oUlMuS14TSyMCumBRFXsR09g819NZTFnGRleCba8pa4OHkxdswQ5i1ZzcyjpXg3DKJbHdtqzxYb3ZvQ3u4wM7/czqWYDEo0vejSvNa9KdxtYKrVjBZWB5g5u4ALV7MxNX6Idg3Nxzi0iZHsP3uS3LKWPP5MB2wBrGwJHPk0Kb8s5ssvi6jfdgT99PbYAcY67bGN3MrMbzMIDS9l9ZlHeadbMdFhpzh/+BQq+2s115oYQH1xO/OXHSA/I4yY3ARmxrnQLHAcr43sicmUS2lZFUGdK/pO3UfZmvCo+e/Cwzw7aS8T+o65J3UF5rPeR88eJzahIS+83odrPdpozKXsmrwWgNM1nxwKi6sk4Fb19bQ3r2yJ57Gw/Xy+eTd9O/rgZhHGipnLub6t4EzXoc/x1LB2IJmUaKtEd71+ZrMw4ji7Qq/g3a0v3Zp7AibSL+9n6cJg0ipD1eWR115kaHufGo7VmEgJj6OBXwMsLWvaBzJQXl6E4dqeg7UV2JmV2bRD5xg05wBjmkH2uvdYcraY97teWzMb8GvCyRrSvo6TRy32HFjO+W1XiYn14nDMIB5pdfe+06iJ7BM7uBplzQi13T/8/r7uqXyfoVX2V6ycH8KOw2mMe/8xcuhC3RrehQ8bN4Wu9QCTG7U9tdUHzt/BwW1hRGpnVjppmj1OHuABqOwceGb6ZJ4c5AV4o6kmKUtbR7oFDGDp0iV8kVqEu0tDuo/3/fcIJTGEOTfg1YYVfdzVh45No9kbL7Rtap5TW748mRWvXj/OSCzUatebAY3g6yGd6NcQdnlf97Z1qcOrH/xcfZn/Q9RutYhf+QPHWn3MoBa3Zzr9vium7l0H88TQuWxKLGBEa/saQl9h6bg/6PjZa3TwVVPbvTYajQ2WDg3xK9jB9jR4pC5QlEp4UlPa1gESISevAKPJxKVD2wnZF83rva6lV0pBURF6A8RsWczxzGY89mq/GmV2cG5HjyEQun4f8kgPXK4cJtHYhy/nPIP2SjDL1qytDLt3/iG6vvItUzxtidk+jfdOxTJpeGMAhCRy8qAw9RhLvr/Es0tewrOGvAsL86n9zIx7rJQWcWTzcs4mN6HvkBHUK97P72c9eLajKx4N62I8YgECxdmFlNk4YaN2QWWto04jX0pzSqGWPdFnY3DrNg6A7Z98gox9myFNrHGTWGKycwE1PcdPouf4f+au81Bjb++CoVSPQfTk5JTSoEtdIJM/ly9DW2sAD48LwjL4E3b4zeDhxt4M/Ww2Q29SkuIm9Sg/bn6SK8zMR++kxsqlykNRfhjLM4P4unFNdaLl3N71HLroRveBw2hqdZGQkwk81rWaSQgAPef+WM2iDVm8vm4KbWsIHbVvH5szhfee7E9+Xg7h2ZmMqEm0/5wC9q7+iSslXej38Eg80jazpGAsEzpYUJKeTLneE9AgUkJhYhomvQlsVIhvV96Z1RVb0ti18Becm7bBvDSZiDq4jQU/hTF6yVR6uJhdGw54lyUDgJJ4flh9lGH9m92/It+AkcjdW1iw9DJjV0yli51ZSWw0aBpLBgHF0Xz922meCWwEGEmI2MfOvek06jqAYU0MhB7aDx0fwtMRpI4fz7w/h5fI5Miibylq9SguQKunF7LkaSDnKC/My+Sdfh6AM/7t25Hn1pHpT/S5UaRuT/NNt6fh2Oc8fH4MSyY2qvRq0q0NV1IKwceFsG0n8ew5FoDDP/3Ekaa9eX9AGxLjrhJprPkjvbtFZtJJgv+8SJ22/Rn9Qi0u799MWftHaewGDTu2IimtCDTOXNh+Go/u4wBo8ZA/O8IzoY0n8Wej8A4aDsDVAwc4ZnDhucAO2LgUUJifhN5owsmrJ1OX9Lxp/m0GdSM4Lg8auxGxL4y6QR8DWs7u/p3Dl2rT4+GhNLY8z/ZTSYzq4kN9/xHMWHIbI89QzKUMHU2beFHTN7J2zg6oPeugK9SBqy3J0Rm49DW3Y05kKCa/fECNyZRC7pUcqFRM05k9+jPUT7/Cc8PaUf0qasGQN5cwBCBxJUPna+6pUgrgPeBp2kaeIi5bS8d61Z8ZV6mgnncSW1MD+GxoOl/88icDJnxJ9XvP1VFAVrYOMZRzdPFydM370K9/Pwb134fPWx/ySKt6t50yQLlWx5nDJYz9aB7NbE3sXfsxp6IyGNHNrDmW6zIpLoHsc5v4+bcSXls4gibaEA6mlTHS1RZKMolK1uB/K3scDyjZWRn4TVzHoBY1h/1X7sqhgjvk386Y/pMj8pJdD3l4SAdRq9Wi7jNO9pSaz92Ua2Nk7ptBolarpU2rx2XZhRQxiogpP1GWTn1YvGqrpeXQl+X5oT2k41urRESkKOOSzHiis3ip1eLzyGQ5HaeT9N1fim9te9G06SN/7d4jw7s3EitHtby94E+ZOLChWNs7mfNWq8XRbpCsyy4WbeoFmTy8ubi6qmXA69/Kpy/2kNEzNkuuTuSrvuNkwKB2olarxaXPONkfra8szfn1z0t7F7W4tnpIftoRL8ZbqIGIta/LpA3R/3sl3wk5x+Wljg3F1t5F1Gq1uDrZyTO/VZxfMRkkftNPUtvdXeq1e0iWH8swnzcVk+RHnJCn+nUUtVotz/1yWcorjrmVhYXJa491EbXaVbo+8Z2c1+r/LeeKPIySdnCjdGreUGprGsrMbQliMIpI3FLpZGstjk6u5vp1sKnxjKmYDBK74QdRq9VSv9NAWXMqs0JeM+khn8nrm3NqrpOCcPl0WCdxsHeuqBMHefS7wyIiknkxWEZ3U4vayU6sHVxE3XSA/Hn42rm/PNk6/VnxYpjsrJLckZkdRO3qKo4O9uLk4irq/nNFRESvS5MVXz4varVaGrTpKvP3npUyk0nuKxm7ZWQ9d7FzMPcHF0dbmRBs7r0mfaqs+PxZUavV0qj9w7LtcLyYTCJSlC3r3xgj9dVqCQp6U07Eas1tKCIiZXJs+WRpQoCszSy8ISuT0SBfj3IRewcH6fHxTrlX5Meflpf7qUXtZC9W9i6ibthDlv517byhVg4ufEMaMkA2FpXdEM9QViyzRriIvb2D9J5xUKQ8XzbPGi1edg7mfuLiLD2fnymxeSKi18nBmROliVotffuOlwNXikVf5VhzbvQRGd/bSWzsHGXk0jhz+rpE2THtUfMc1Ly5dHlhkVwxVOkPNzljWpaZIB8/EShqtVr6fX1Oyiry0JVckU+f7y1qtVraDXpG9qf/88zff4LJKMd/mSi+dvbi4qoWtaurtBvyYuUZU21qtEwd+ZCo1WoZMOd8pbxi1MmeT8eLWq2W9uPnSmaR2cOQni6rZ04QtVotvi37yLydV2ocI8ayQlnw0ghRq9XS48PtUqoXkYKL8uHgDmJfZUyPnHu8xuLMG6MWtYuj2Ng7ibqWl4ybdb2flucmyO/L58r59FsZsybJPrNbBnVqJWq1Wt76PVr0FWOkOOeojKtY9/qM+0VKdVVXi50yBI2M/ypECipcUk+vk+Ed1aJ2shUbBxdR+w2V/Wevf5twZcuH0tbXQRxqN5Cv92Tcgmx3j+rOmP4DY7kc+uldmTh9o+SWXJGJDR6TXekiImEyVeMlri7OYm9vL84uruKlmSpHY47I+ID6YuvoIrN2Z8nSSYFi6+Ao/b83n1POjNgiz3VoJGp3Dwl4Y4HEZJnXnryE3fJa/9bmcRUYKK/9eFpy5ap891BHcXW0FTtH81w3YW3yv8sqIqX5RTJ98JPSwb+xqNVqaTHmU7mQen1Qb5o1VJq6qsWl8xMSfF4rJhHRlybIog8eE7VaLX7NB8uPh66KQUQu7/9OejlX9Cu1WjoOf0VOp16Ujxp5iY1XS/nk+/kS2LmxDFxwVX6Z2EYeemOBpN6HY/h/59Anfnd8xtRCRO77gbWSyF9564uLjPtsJr0a3f9XlA8quVEHmbVoNf2mfcUwz/tzfkRBQUFBQeG2ERPnt3zJjyc9+PzD8dRxvu8vbhXuErG7vuHNzQXMWDgL/ztI54FQTBUUFBQUFBQUFBTu+1f5CgoKCgoKCgoKCqAopgoKCgoKCgoKCg8IimKqoKCgoKCgoKDwQKAopgoKCgoKCgoKCg8EimKqoKCgoKCgoKDwQKCaPn369PsthEmXT1pGASo7B6xV124hNlCYkU5qoQk3ZztAT35qGmnZuZSWC9YWOlLT0skrLMbS1vGm5s3uBEN5IempeVjZ2WF9l9O+XYzlWrKysxE7B2xrtCJyt9GRlZpEZnYRZXpLHO1tsKiw9mPUFpKRnUpugRErWztsrMzuJr2OvNx0MrKK0VvZ42hTVWYTJblZpBcZcXWs+bpkY1kJ2dnpZOWUgq09dtZV0zJQmJ5Gapk1bg41XxJuKCkgPTuN3AIj1nZ22Kiu33xtLNeSmZVCVk4RJpUt9rZWVHcvtqEwl7TsTAq0Ftjb26KytAAxUJCdQXpmNnn5hZQbrbB3sLmFp0ChrCiXtDwdLo72WFTJWEwlZCTnILb2d72v14x57GXqrXGttDhkoDg3m4z0TIrKjdg7OVDVfpbJWEJGai7Y2mNTg7xi0pGXnk56dg6lBhucHc2XbhsMOsqK8skqLMDS2vGGdvrvEfS6EnLS0snMy8NkaYOdrXW1feEa5SV5pOVocXCwN5vR5doYSSM3X4/Kzh7bijFi1GvJy8ggMzuHcqyxszf3k8K0eFKz88jPzyc/Px+dyhkn29trdzEZKcpNJz2rAK2FPc52FS1lKCY1IYXs/Hzy88uwdnHEpqZb4O8aRkoKs0hLy6KgoBwrW/tK08ZiNFCYm05GViGllvY4217vWbr8LNKzcyjUqXBysLlxjIiWjOQsTLcyRkQoycsgPSuPYpMtLvY3XlmkLysgI7MIG3t7rGqoEzHqKczNICOrkDJLhxvaScREUUEW6RmZ5GktcXa2q3YeMJWXkpOTTkZmCSYbexyqzJkmo568vAwyMrMp1lvj6Pjvc4rJZESnLSQ7N51SnG6Ye8WgpyAnnfSsInQqh9vuV3dCWVE2mQU67O3tsKxsxHJyEpLIN1jj7FD9xft3gq4glexyO5xsqzc5/aBQlp9FUlom+flF6MQGBzvrG/r9LWEoJT0tnaycPMTWGXvrW2vzcm0+6emF2Dvam9e2GtCX5JCaU4yts+MdWW96IBTTlB3v8vaSBNp26VTlTrM81rz8OIE/a/n0xR5ANvs+nMCoRSdQWTqjsUth0c8/Mueb9TQcMIKmtf73jlyUmUdiWg4u7i78vYumR27lqaHv06hXfxrVdb1p/HtNcWo4P30zmfN1+tKj7r211hF98Ddm/byUo/vCOLU/FlWTtjT2tIH/j733joryaB/3L3qHpYMFe8HeEF0Ve+/G3mJsscQeE1vsRo3ttfcodsHesfeOigUULID0zgLLsm2+fywiJhF8E+Pr7/Pb6xzOYWeeuafP3FOe586I5uzxM5y7tpdzl+KQW0so6e6EqYGK13cD8D9xiOMnQ4hT5eBctAz2uVboMhODObR8JiMOKxjdpWbBkStSuXfhDCcu+HHydAQyU1OKuhdFp79oSAy7hu/8GQy57MKkDmULliV7y6ljpzl/fR/nryaQbe1AKXdHTIxAmRrHnavn2Xd4D2cvP0ZtX46KJRz+1DbySAph5+5TXLp5nJsPElE7lqC8qyXI37B2/gL8T13m9p1AElVuVKpWrFBrJcqst5xYNYuxe6Pp375uvgVRJg8PLOOXZYfRFqtD9RJfsj2qiQu+wNbZ05kcWJzRrXWWaDJC9rJ6zzlunjzD+XtXiHVvQG3XdyYGM7nv9xszVpzArFRtKhcruK3G39vMpo2nOXX5Eo8Dn+JQtTHu1iCTRRF+/wLrd24gy6U5Vdz/bMLw30IjT+Ty2R2c3HuKk5evEBQbS5Ey1XG2LHgy06qTCNgwm0nbQ2jRxAuJpQlkxnL+xBnOXtX1kSxLO0oWccbUQMmjy1vw33OGMxcucTv0MTZlvfGwMWFjhyZsfBHBoxs3CPBdwG5VewZ4ORSe8LiHnIq0opzz+9aWFnyBnQeOcvrsA14np2JXtBKuVkCUP+07LyE04jE3bsRSrHFNipp/GetPGfGv2bH1Nw4cv8yN0yHEpBtTyrMkViaQ9PQcuw4e5fTZh4SnpSEp6omLFRB7ny07T3Lx2nkevEjGwL0ypezf1UcWjw4tY9aSg+QUrU3NkpIC41eHX2Xr3uOcu3SL5zEpWBStQtE864kyLm+dx0+b7lKljhdF7Atud/FB59hz+DCnAoKIzJBhX7QizrkmM2MDL+J/6gRHj5/kargtjRqW+bhlJpWcp9cDOHz6AMeOvyTFEFyLlMDOTKdMht06h9/xQ5w4eY6QzCJ41yzGx2a9nBwZUSE3ObxpNNtT29K1+vsxIzowgL1HD3PqzFOi5Jk4FC2PU2FGFz8nWjUXt05iw01DGnpVyKckxbDYqwoLX1VgaKdPM939d4i8so6DiZ7UK/nlv5kecuMJZh6un265ShHLtl+ms/XyLe7feEisYUlqlXfhv96bSAll85bN+P42nkdufWld8b2p0NTIOGIys5HYWv1h4S0IvbyNnv1X0bRTK5wkhTeShKCjTJ09gxzpQKr9PWukwFdgkhQg6WUonp1/oWqR/AOAI/ZuNqB5Z5nWlXaju1B5TyV6Vkth1dEE5iwYjuX3T2lezhpSXrJx6RTOvhA4l6vDqB9HU83JFsjm4UV/lm0+gdbUmBKVpQzu2ouyVreZ2G8VQVkK3Iu7YGltz/C5W2iaa1HS2LQMNiVtwPzLTYaFYVu8Bt+1rMWqtxqo/WXjNrOpweiZvajmYEbo/l9ZHyqnVWVrEoLvEWxegkmTB2CUFc62Y3eJLetBKYmax4+DaDBgHuNdjYm4uoIzdyrxfWudybdr/oew8G5L9buFN/aMmHCepqrpM2o5RcyyuXB6P09flaFZNQeyk+I4G/CMmn06Udqv8HzEP75FiE0Ffv75W5C9ZOPRIJLKF8fDAULvXyPTsCw//vgNtraF9/w3lw7zvPIQFjYdAXHX+NH/Ee2rttB5lmnM3J86U/xPNu2V3Pfbyfr9iYw9OIXq+Xxu71hPeplWeBtqPxggXhzehH9sIzr3fV2IucHPT0b0a05diMRnWBcuH3nvbmhempZ92+Dl4cj9wxMZdyGB4dV0ysDzA2s5luRDxx4RWH9Ebn7ibp+kaJ+DTK9rxusN7Vh+K4laXZ2QSEoiae5Bj7RoIv6d7H0cQ3NKVG6OV+tRWBtrWL36R55HZVOpkAXw/S0LCHdqQaO6ct6peIkhgQSbFGHCj+sxyX7LzmM3iU7woEIRc5xLSvl2+hDcbS3YtaIbd15k0qCIBe3nbae/Tw0cgLNTp/OyTa6NwvRIdq2dxeFAGRKPSgyd8AP1PVzfJ+D1KVYH9aFdpfeLgUen/SjRbQ1jSpvBo/lMORPGooHlALBuOZ4NS5t/xoL7NIxMHGjccSKDy5XEICGSvfv2EJ7eGGdLCDp/jHLdVzC2pCnqB/OZd646c/qWIfjQRpKQ4iSVAAAgAElEQVQarmR+XUsIP0D3PQ9pOq0uAKFHN7MvqhFd+rt/fCGZjwe7VmD1zT5+q2QOwasZ7P8Mr7GVAQjaMpeHJk1p3iyFTxn9g64EUKnnYsZ6mJJ1byErL1XDs0cpSDjP0TPJtBn8A8NcbDAuZLZVpCXxNDyatkMWMdHBiKBz67j1uALFG7qiiDzFvWdm9Bk0HXcniz/smMXy6zczsRswmsFdamABmJtLKFu7HePSLzEwOv+zgqDbV6nRex7jipmQcvs3tl2tSoUuhZlS/nwIIUhXGtGifXMcPljoFcelpCG4Oed7WEv4TT9W/O5PVBp4fTOKkX2bo1Oz49g6YTGnIrPw+rYHNju2kFyvHTYpV6DFQkbVFuz4bTSPiwxn+YhWmGTHs2/LMvyvvaba0G/zorjw2wh2hbgg9dRw7c5zsso1Z9LkgRgHbGL9PTW1TANJMG1KcdNnXJCVYdaS8VTKSuDUrmX8fvYlFvZu9Bw9gTY1yxJx4GfmX8rE3dCQ1zExSBr15JfxvSiWcofpw5dw+lEoLtXLYQV0mnWQbwuwSZ0RFcSGRWNZczQaz7rVybG1pW8ZO8yNIemiL0v9jhGWWIxW3w3i+w41kT07ybTlu/Aev5d2ppdYuWoNiqaL+K17OXCqzIQZi3ludZPN+eJID9nP2CHrCTUypIiLPRL3Moyc9ht1iwAYYGbpgWVJOzD5tAWru1cfpjTYzu5QoMgnBflLvo4z6o9QtATUrZOv5iws4e59wsMvEXv+IZEhgbwpWwkz4Pi+ABrO2Iavry/LfmjPiXX7AMh4cYP9j2P4fuUG1iyejVoWRXiqHAO3NkyatZDvR/7ERl9ftqxbScPi76MyN4dqNVywtf2UqfXLYWpuhYHBl6+24rVqUc3FChRvOBpsQ/d6OhVJnqXExjL3uNvIiJyIGLSyTIRWoMxWYZl7RKbVgiL0NQCv1rUkQNGcblIPPuUUKSdHjbEhuh1EAwOUKTJUcQkA3N4+iTS3pviU/zRLWFmZOdha5XYyIyMUb96izZKDKpuI14Hs3jCa0iXsqDF4KS9TCpaVnpqNm3Ou4mlqStbDp+89b2+mRmlXbJzc+WbOfuKz3nloiQt5zKlDt4jPJyty5wDWRzVnYKvyWOebwFLu+vLbVStmj2yI+983EP23ubLrV4zLNKVeiQ/7gVWp+pTW3qd3ZRuGb7fn7GjdTnXyzU0suObEjOFSXD8xvSV69uXsz3Vp3rwDSx40ZnxHx8+djf8aI3NbypUtyoUpzXFwLkq82QA6VS145zf64FhmBbdgeKfK2OYbx7PlSqwsjHXKhKERirexaNIzMDA0onjZ8jzfMhIPJxtOp41mjI8TAGVylVJSbnPApBbf51rEu3jiKpW+m4evry+rfurPA7+TaDTaAtOVniLHzia3MqyskQc+yfNLWtURGxsbbKq3Y/8D2X9bTH8bSwcHKnuWxtzYEFn0cUJzalE+V/fOSM/G1ka3ABAWVsgfPdOlNSETt3dbkWYWyC7fAiD13i6WXDFj7qhGfOqmemJ8Bo7vdkItrci4cQ+AuFOz+CmwHmN71cThEw/hMjMU2FjnptfMnOwnITqPkEscfPWEYa2KYO/dlVMvNAXKUau1aNUazHOPmNXZOeSEvwVA+fQcflf9aF/XBdvGQ7n59oMUcPPQaR6ExqMqLLECsjNzsM4dA4WRCfJnLz4to1+AshWhkme5vN9qlZo7T1KYssoXX19f+pfO5PT+ywBs7DAYi1EL8PWdifT5HmYkeTP5h950b1SGmAw1ZrYuDPx2GGbGajQCsHKh24g5LOhoy/XXeQMyPmOXU+z1JiKtfFi6zhffWU14Om8r9k1rob1wFdFrDZLwhwQbdKG3+goHb0LQvWdYe/Vgm68vGxZNRfXoNnFvEynRaiKeRq+QV+7Guq2+eL06xNHrSWBfmxnbtzOoZV+W+ury0rtywWVhXaQKY36ejrTuUA74+uK7ZjbSqjptz9q7IT9M88XXdyFFTjVk/QOwqdiKMfUFTxPBoWwjpg5sxpPo7ALjsC3flXETZzDqp9n87uvLmt9mU8stXxpsoHrNoliYf/rkY2lV8GnFp/A/3zGNP7uD1b8b0u/wn4+pvMae5FZ+B48KlEt+RajGnErVszjsfxtt5S6Q8ZibJw6xaNce3m81NaHVTKhToQaNbh5jVo+OCIUBtVsNo3xpNzA0wcLCEnNzc6ysrfnjvpatR00WLNr072T6H2Dv4ETMrP5MN9rLgg7uXzTurKgXXL14llLtmuPl/m6fXkWOUv3+IWNjMDQABBpNNpp3Y7GhIe+2DBKzFNw7MhmffTLCYlVMqu3Nsi6mnJo/j6Wn75OTJ6w+S68vpRxqVGoleTbKjAzBSDd4p6S+Zc/h4exRJvM0yphVfWoztrGc3wdMZOvruHypb8OGG79ghRKlMt8EYWwMBgao1Sqe3DhDbJkJRPgNQJ78iBsPzuHSrCUf3zzNRqHIZzjNNHcmsyrDJN9LTPIF1BmcOHqI0OBoXL2KAuZ0mLWS2FkfSkrOziHy8iwan88iIj6bBJeabB1YDrlSTXbYDpo13k56WiKuLTQ0rD0EJ6sv03VTk8LYuGAQG3MSCU11ZGv3Ggypr1McHUu2Zt/tGK74zafV3HvcmO9NllKNIsyXZk22kJaaSNH2hjSoMRBb84/vY2W+eEv7dUH084QY3x85/FxJ2Sr/Ay38T9jT7T9X6Tz+NYu3r+PYvVJ083b56NOp2TnIAn+lSSsF0YmZBImy7B7tBahQKtXv229eHwGwpunE7UT2WciGjVNZfbosEzu8273SEhX4mLLSxrpdQPkrHp7z5/DKNQiTd+VZjxrjwSlgGT/PPURiRhTBWYdosMucmr2msWhEe4SQo8rXRTHN1Zo9+nFX2U/3f8oles04S6913T9DuX0aKlkSr5+d5shRY4YsasO7w2atVo4qv4b1Lr1kocjJ526u629ZKjXZL3fRrPFOZGkJODdT0aj2cMwyA5ja/VeC8gLY02rwFCYOaQhkoFTmk2Wmk5Weo0T5bAVNWywmPimd6kNcOTilOaGXtzJnui/heQFK8d2iWQxuVE6X3rzyNcjbXXoTFkzgjVQ27HvL+VpqNi2eQ8iEuXh+VOHVoFEr0L5bZxgagrGunl88uU9IQlV2XIyjfql0fDeuotjgsXiYAJTjhIgquLDzx6LNRv1uCDQw+OTdsM9FxL6l3LxhwdC+f970ab06ndb5fmsiNrJh/jpW7dyd62JJ/S6TaRV7HD95Sy6UswQs8enThloBiViYm2FmaoKBygAMDDEzt8DYUK4LamCIqbklVubG8F4vxcTcEgfHxtTo2RoXZ4BKlPVcS9jbOhhXbc7Yqlbsb1wUiWcFaoQIghSpvL6zhxV7H6CxebcS8mS8tAXdnC2oVN2bRq2b4iiB5s3LcEwjwMAYC2trzEzMsLS2/qSTJANDI8wtLDAxNsPaOn+IdIJ2r2T5kdtEpZtQ1tGE2lowMDLB3FQ3LxgYGWNhbk5hl+INjEyxMLfA3NwUa2tr/tgSXKp1YHW1Dp+Q2ve4Fy3Og+ld2bXyd/rX+Xum0//niqlrq4GMGbyTQ6EpNCvrVsjT5bBMvE9QRDWGdi7D3EknKNNQAjZ21K3XnLItezCkfrkPQiS9TMO0/GBOX/wPvA1h6e8HiYhKoYSTO5BDllyORgMx14/zLLU4Pl1qfPr9j/8BqSlJFPlx1xdWSuU8uXaGBw+ycW3Yg6aSMC6/yKJVBSsk7lZk3VMhBGSny1Ha2GFsa4uhcQ42LtZkpuSAvRnRL2OxqVQegHqTr3FjMpB0nUErE1nWRbcKbDdjJe1m/EXsdmaAIcpsDRqhJl2uxb2Irq18s+AG3wBEH6ThPCvGNtYdAw3eeZDBf5GT1KI2yB7qZrestEzU9o4YWVthaJpD+dpNMXN0wtTIgMzYLNLfZKLS8NFzBbcKDkSHpEEdG1KiErGo7KmLIyKCy8/Cad5MioWBmqjEeCyLvJsJ1IReOcexy+l0ndWbMrmuNYf7cWM4kP6YqZufM7OX7i5nsYZD2HNiCGiVXD69gzSb1l9MKQUYsOQGAwAid9N2pVueUhq4dy+ZDdrR2MOMciUg6sQLwBuPJqPwbzIKNHICTuxF69oqn1Kq4PbOPQS8dmHYrA55Jz2vr17DrO9owBoLy0ReBcVDFY8vlse/IjMhgbuPw6jRwBv7YhYUMU8jMyUVcAG0RNy/xpGTkbSa2gfP3MmgSv+N3OgPZL7ktx336N9TtyVi52aFPEKN0AqyM+QoLW0wkdihUam4fvo8pRo3w8PdggrOci7GxgO5iqkqjXsRZtRvkrsDYelKtTotsO3bgGGt/mCJuvUkjrSeBDcX0DaoD6dHls7zcq/oyNtoObhb8vJWMJJ6PQB4fOQIT4pVo1+d0sSnJJEsy/z3CvQPpCUEc/XkHZLsajN0bhkSHl4jpmwjitiAa1kHkmLl4GbJq7vPkXj1AqBETVdOB6dBRQlxoVE4NmsEQDHpIHYdGwRCzbUz20iwaIWLjTHYtGfdjfZ/GX8pL3euvMmAEjaEP3iJY5PhAFToupBLXYHsGLb4XaBeo7qAEeWbDGf3jeF/Kcu5pIT0+GxwseDNgzBsa/UGwL5Wa9pUvUvl4iaQIUdxL550BXzsYqiphQlm1mZky1RgY0JinAyr6iUBcPXuSNsUDcUcjSE1h6zHyWSqQKdJpLBnznasW3SmdYMyBc9fBuBQ3BZZggKczIl4Eo5d9T4FhfjslOj9I9KEcYTEZlLZteDdNSOPFnTrm02LSd/j6Zrvbn1GKJ6c4qkMqthmE/U0jGjey0pOSUOjcuDhjTtERBX/C8kfoswO503wGxrUL4WpaQop8fZ4fEynMrGiZNXm9PPozrC+rfK9vAUaRXqB8ahUqWRnQ3rYVY4HKOgyudUnKakfkHqWTbtgzq7LFDGK4PDsNuSPNTEllRyZmstn7pFjWMj7GwAoyMgUaAW8OnucGONy1Gte8U9K6qcSG/2WWgsO07/O3xQAIL4CHi5vIX45GftJz27v4yL6zzoicrJuih/c6olNoTr3jJi7YtP4nkIqlQppt25i4NwTIloIEXzmupj83QDh06SRqNe4mfju113ibYpSCCFE2tvHYv6gtqJRPalo2GOiOH8nXqj/pTx+Ll74TxATD7z6spGmBYoJTSsL99K1hFQqFV6VPMSg3VE6P1WmeHzwd9GwQQPRtGMfsfXCS6FQCyG0GhH/+KoY07e7kEql4of1V0WSPJ/I8Htiet8qwrlYBTHxcHTB8WsU4tXFQ6Jb29aiYdOWYuGBIJGR8947+vYu8W3bCsLWrbJYeTmhYFmqDPFo/yYhlUpFs84Dhe/lNyJHLYQQWpH19oFY9VNX0ahhfdF53HJx74VMaAqSlZMirq9dKKRSqWg98Cdx/lmyEEKI7PQ4sXfDTNG8qY9o1LSZ+HnzfvE2U5kbKF0cnz1IuNFJBPxBXHZqlFg2rLooWqK8GOwb+oHfpfn1RGXPMqLZmA0iMVNVcB4/MxGX14kezcoJp9L1xJabSUIIIeIuXBBTxvQSUmld0anvJLEvLOWDMGfn1BOVKpYRLSf9LtKz3/WqSLGiZW1hYPC9uJvv2aSwg2Lkd12EVCoV/UavEm8TFEIIIZ7tGyOk0vqiaoUSony1ukI6cO0XyK2OnNRUcWr9b6J9m2aiQUMvMW6JvwhLV+T6ysWV9RNEKVqKgxmKD8Kpc+Ri45haokTp8qLvmtxcqjPFk8PbReNGjUST9r3EpnNhIlslhFalEjd9N4re37QRUmktMXjKZhGYmJUnSxH7RGzZ4SteJb0flbISHoud0wfpxrmOHUWfmX4iXKN9n4Ab80WbdR+OD5nRT8WCkd8JqVQqesw/IaIzdO4JYdfF5NHfCKlUKtr3GyK2P3772cqvYDTi3r7JolqxUqJO3XqivreXaNV3lLgbo/OVRQSJ2cO/FVKpVPReeFrE5qZXKOLFkflThFQqFR1+WCqexik/kHr11/qiimcZ0XT0WhEvK7iPqGURYu2kUUIqlYpu03eLiPQP/fdMriPKlC0nui38Yy/9M2mvA8X0If2FVCoVA5acFXGZ73wUImjPTPFNWy8h/Wa48D3+VuQUJEirEm/vBIhB3ToJqVQqpmy/LVKzc0ssJ0UErBkj2rXwFtK+E8Wxqwnife4vifYUFYMXnxHvspH49IwY00sqpJWLCOdytYW00w/ibrBujk0OvSN+GtRHSKVSMWTFBRGfJb4oWrVS+C0fKfwfphb+rFYtnp5dL77r0lJIpVLRZNQksSHglZALIWKfBojpPfoLqbSDGLV0qejVbLUQQgjlm2ti/IDGor5PUzHg28Gifr0GYvCOMPE2aI/4TioVtcu7CrvStYRU2l0sP/JIKIQQS9o2Fr/8OkN0bikV0mEzxYXbIeLsmvGiglNJ0XrpZbFvdlfhM36zCFzZQXg26yNOPnojjq+YKBo2kAppy5ai65SN4m5spnj2+7eiYpniYuCSEyLj1lpRq2IxUaf/bPEkRleR+2Z+I5rVlYrabQcK3yNvhPLjWRexwXfFD22rCGfHkrr+3muMOPM0UYjsOLF1TFPh5SUV3UdMETunVRVNBqwUz2VCKB77i97tagnvFp3E5GF9hVv5OmJ+wCtxe+cC0UkqFTVL2ogiFesIqXS4OPxGN5YnPL8ifu7RUjSoLxWtv50pbj5OLnjeK4Tb82uIaZf+gQAhhIEQQhSuvv67ZDxYQpcxd5i85XfaeH7Zt83/v0TC4xOMnreKjv/ZzcCizoUH0KNHjx49er4mhIZb28Yx44I7vmt/opjkn10l0KqVKHKuM6n9I1acHZt3nP2pqBRylvUcQLXVu2hVzAxjo6/61Zuvmuf+k+j0ezJbT2+n0T+Q81Uopnr06NGjR48ePf8tsff3s2idH1EyY7y7Tuanfv/dGfKF30aw7k4iSCoydfJY6lR0LTyQnn8VvWKqR48ePXr06NGj56tAv2etR48ePXr06NGj56tAr5jq0aNHjx49evTo+SrQK6Z69OjRo0ePHj16vgr0iqkePXr06NGjR4+erwK9YqpHjx49evTo0aPnq+CrUEwTLvxEu64TuPkmn50w4tjUvQFG9Zfl/k7n3Oy2uEoa4hesey7t4BicPGqx5MCjvFCH14zi7POMv4wn8dUBejfsw5W7ASyp4k6xSs2ZuvE8oSfmI61fizpthnIrQv638pCRkEpS5l/ZpVVyZ+d0KlT+ltQMxd+S/Y7Ul9cYM7gNq0Ni/5Gcv0Ni2CGG9qyLT4N2DBi0hocRuXlVpHHPfyujRzWmbY9Z7L4ZQY4GEBpiAi/w65TeNGs2jBl775KUW7TRQZvo39Ubn/pd+H7MLt6kFRK5Sk7IOX9+Ht+OZq0msPpMCBm55gRjnvkxb9RA2vr40GfCDO4mKwsUlZERw8OAzYzoU4xJR2I+8NPIZTy5coTvh7fAp3V3lh19Qs5H5ACQGUfA2kUMGtSab0at5nLoe/sbqrREbp3aQf/+Pvh0Hsmhh1EU9PmLuLhHnNs2g55jR3Ll5XsLPGpZKKd+m4SPjw9tO/XD73wIqoJNo39WXj0LYN3MzjSff/IDd0XceVaN6IuPjw+9Bs8iLOV97nISIjm9dyXdu/vg02cuT2WFtXuBPOUpm77viOtg/z94ybm+42ekHX8iJObLWSZSyhPYu3YErVs0pEm9oazadp/0AhsDJCQ84/qeX+k7shdHHr9vC1lJz1g+szuNGzeiXcsf2XsqDIUalFkZjGtQDm8fH3x8fKhbuyrLLyXqAr1cRYPSNfHx8cHHZzr3PzXhsrc8jf2wvDPeBLJ65lDatRvAyPUXiX43PEbuRlqsWm4c4ziXnPVnef8SClkkvy/7jpbNGtK80Sg27g3K69PpYXdY+ctg2rYdyA+br5BX7ekRHFgynd69O9Nv2g6exuvsgGbEP2DB5I74NGpMx3bTOHwxXGexrQA0Cc/ZOm8MXbr0YsjSE0TkVpcy5T5bV//Ctz4+tO/Vn+33wgrNy6vgs2yY3ZUW845+mMe4C6wZ2Q8fHx96fjeTF0kFd1y1IpVDW8bQrmUDfLwGsXTjbVJzqzLt9REWTRxGJx8feoyezNWEghujPDWMtfP70qxJI1o3HY/vkRDkuWZeXwXuYtbgPrT08eG7GQsJSi14zPzsaNVcXD+cHhM2kZCR31ZuGFOKWVN/2L4vm54vSNyraP6ZFlA46bEnaF2iLnvOPv+XY/oz4edX0LxzB44UbACrUP7nJkkBYh4/pM6wnUhL5bdY74ZLCQlonHJ/29FycH/Kn/Yj+swVZB7lWXvbmUE+nenYvQZE32bWxlOYOtakg02+bOVk8ODyQU7ceo2JbWnq9eyAMxX5cesQYkJ60d/tFQfTW3H6RCP2rUuidglLSH3Nvj3bCY4H5/Je9O3fEZ0hxiweXTrBoUvPsHK0wsGhGgN6tCTzzXkWTt1BpLM9nu6O2BUtT9de/SktATDFSlIaS490MPhn6wD7so2Y1KUOa5/ngOc/EvVfE//chJ6LA2hV1Ion239la2AGNUtYkBZynQuiDKvWXsEo4zU7zwQSVcaNknZK7j+8S+MffJlWzIzIS0s4drcUg5s4E/XQlDFrz+MtMeL6b8NZG9ifpc0/Hrc8Jozr8SrGzD1OMYtsLgX48eBVMRp72pCTaUDbKSv4xcORUysasO/qSOp2LfpRWTY2RajZehhrNQ/4Kf94rFXy+t4lwpIdmLcgABfnj9t2f0fs5Z2c8OjP9tFTIPoS004/oUn5hqBMIfDseRKdqrNmzVUkH1jdU/Pi0lmOXkqj29y+lM11dXOrgVuvomSaH/ggjvRnV7nn/A1Xry4jM+wyay4/IEVeAVfrL7OmLFO5NaP6ybl30e4D99hjq0htv5OrG+yIPjyRH04kc3igE8gjCNgTgHnDTmzfPg7rT7C3p1ZkceXwBRxbtaH6VYsP/EKPrSYwtSyNW1pi/pHw/wbKLAPcKg5k74m62KUnsn3dSh7F16FxAZZSXVwq49KrLBrj1aTmc89MMqJq+zmMm1MJ2cMbbLtynVhpOTysLBg0fz/zmtbCFvCfNALzfGNgjdEbWDvJ+8NIMuM5d2Qb10LlWLuUoH2PblR2zWc78ekOJv/BJOnTU7/j2mcVp+Zawt1fmBlQnrndiwEg6b2CUwV1vn8JhcyQkl6jOTymJsbRr9i+5wDPk6vj5Q6Pz+3Fo/9aTs+zQH17JovOl2NGlyKEH/6N+3UWsG+yBF7uo9/+F+weWxlZnBFefZYz/beyxN84zbagQBp4l8TF6uPxv9gzi5x2WznyizUELWfEwXA2DC6JMkmGad0B+I6ZR9itLUy//pJBXuU+LggoU6kVZfopCLzwoXnN2BNrSGy7navr7Yg5OpkxpxI5OPDj38hUKQxw8OjB9qPLcVFksGPZLO7E1KNNaVAkZlJ/1HymlHXl4qZObDoTh8/AXNO1JLNr5u9Yt+pK24ZlMQPkKYZUaPYzp6dWRfn8EdtOXSAi3RNPJ1Cprem5YD1z3CX4r2jHsbuDqd76y327UwhBssKYXt/21JmOzaMcxT2NwCF/OQpS4p5yyP80kYmZFK9ZGk9nHxo2LA0pL9mzZwfPE8ClYj369m2HaWwwhw/sIywRKrf/nlKJpzlxNxKKtWTu4Do8v3WCo1eeIFcb4d2+N828KmAOBPrN5IKsOo0qufIs4BwKr1b07dAAh/RIDu3bwqNosC9ZhR59OlPMoiCjr4Kk6CAOHgggOjmL4jXKUsXdh/qVs9mybC+HT9+mdJt62APSQXNpUxogk/sBhzl2Iwwbm5L49OmGdzEJ8sRXHPPzJblsP5qYPuXcnSg8uzdAffAsjx1K4yhLoaJXMZ6fv4+2fjt6tdXJNTaphWNZczD/8sbVS7aYwPInR/B7CF2a/H05X8WO6cdwcYeqXtU/cLOq05dyDq/w27Sft1UHkjf8SkrRoWMHLOKu5NsxUPHs/mkCX1vTsm0HGlU149nduyQA2DvCo1tcu3WU2+vPERn/gjTXkpgChzbvpljjDnTo0IEmpYxYs1i3gkt7cJi1gfHU6tCBBlXcOHThFvIcNdZulahdw5s6Pk3p0KEDLRrWxSnf/GpjC541SmJkXLiyUxiW1hIMDb/8eqJKx460KmUP6jhuJ9nQuoau0aelynG0M8UAwMSErIho1OkytBot2RkKJLa65zRGJmSE6HYfvAcNwruIDShDOR3vSXevguOWy5WYGoKZmREYGqJIzUQRrds1LuXdBavgvfRo7s22iMGMb/I3LWKp5Lx6+YCrp9fRrbOU7jO3E1nIqi8+RkbZUrmDqIUlqfeDdP/LorkbGc69PT/SumNTJqw/Q3LeZrqasKsBrJi3n9efkCy7qrUwDfZj6NAGTF12nSLFS2NrYVB4wH+ZIl37EL1rNEOH9mP1BVtGtMzVAmKDOBkr5+aa3jT/pjurTjwtdPfqxf7JBGlq0qZuaYzzjUgJF5cx44wzvfu0xO1LaqWAtbMzTZtLcTA3RpN5kTdUo7zb35PlWrEiLb0rY2RgQGL6CwztS+FkA0YmxtTMVUqJOUaAUXtalLTMC/dg5WC8vb3x7vszd6N1bncuXMe4Yn06dOhAy9qluH7kLBptwTtx8dFpuDrlyrV3JO3Owzy/tN0/6OL4ZiRngr/cjrSkWDGa+dTB2tQIecZtEk09KZm7B5EUL8MldwAVdvak39OdiEW+SaFsydz+ZmVD4rmrABStXp1WtcoBWqLSopC4FsPG4o8xfsibl0kUL5K7arKTkHzpJgDW5ZsxwNuSZX28Gb30AUN8qv7tPBbp3IvY3T8wdGgfVp6zYljzgldpFhIJTVr54GJpAllneaqqReXcNbabd19KJl/guzberH7Ugjnt3POFTGHfvJUcv/kq74THqUwZWkirY2ZkSFpGEG26mdEAACAASURBVDnW5XDLLbqK3m1QXltDu8benErqz5B6Dn87j58bj1JQptL7hYDQqLh5civxRavSpkMHzOKvc+DmGwD81+/Ao0nuPO0hWL/MHzM7d8pZpXIlw4PaJSWUdLYgIlbQyrs0iTHxvIrPpknbDnRo1wbjqCc8e/RSF28lKWk39jNl5X2KVGlHPbtsNDII2H8M54a6OJpXsGP3+sMFpl+bk8XV0ztILVmDth06YBBznaN3I8DcjQYdOlKtVGWaddDJq5Tb3m//vpsbVND1ae+S3FkfQKQAU2tn6pS0YtO0OSw+paG6ZxVcFZZU8pRzZtVJtFamLJ56EqNq7ZFdP8rT3ANAIyMoW8kBiaP9xxP6L2In+ZsDZX7+mUXTf85b/2WivWtrcTfqE6yzRuwSbSYGiMCLa0SPlkNEUlKmWNtvtgjJ98jh5UPFrnu5drtzZOLMvv+IU8G5FoQViWL3yuXizp1wodWeEfN7zxKzt60S8zp2EXMWjxNzz8QJEX9GdHB2EhKJJO/PwXGCeCCEEOKFWDSsqpBIJKJMyepi4dYbIkets1N91/e0OBD4/DOWzF+jfbJL9CpTTAzcGfGvx/VH1Fmp4sbOBWLr6dsi14SzeHNhn9hw6rrQaIUQ8kixfuEK8fx5vFBmpom9y2eIJ2m6515fWi7+s+pKnixlSpjwXzhLHAiLynWJFbtHdhbu+cpdIukhzmq1IjH4jti2a6dIUAgh1Fni1PYV4kxA/loXQsTEiDVjGosJfhFCiBdiUf2qH9ShRDJC3M6fl5MjxMTD0Xm/VRnxYmGfCqLakDVCptCI+Lh74uiVKyJLKz7Kw41TxfIgme5H8m0xYvB/hBBCZL68Kvo1Ki4azL4ohFCJJ0HnxKXnLwq3P5yVIA7tWScuh2XkOWnir4nFF3XpzAwLFH5nL4u0ggws/xs8PyQGrbv2gZMqZK2Ye133f8yRlWLxM50998Sra4Snh4Po8fsbIUSGCDi1VzyUZYqC8BueW0e2VsLEzEqM3K+z2X5/bWedu52tsLC0FNJfCrdb/jnRqpUiK2yfGN9xsnj0qYHUCnF5/xJxOCjtA2eNUiEynq4RsyasFK/+FEgrQtd3F3NufETm272i7dgAITJeiIW9GglnO7t87bq7OK1Ui0f7JglPiURIrM2FsYWtkEgkov20XSJNIcThqb3ExfhcWaErxJhxB/8cR3yA6DzuyKfm8rOgVSlF5gtf8VPfWeJZPveDvwwU1xJ0/yuDl4sffzoqhBDiysweYuPL3IdiToiWrf6TF0ajVIiUByvEgllbRGSuW3L4btH2gzGgnBi28LRIFUKcGO0jjrwbet5sFd17bv8wcdnZ4u6uZaLjvBNCCLV4dHSeqPuBrHri15NP3vfp0KNi6PorH4hQPV8vZud2m9ijq8WSpzmFl4laJeSvDolxbcaL+3/1QHy82D61k+i39eVf+X4oS5UjMoM3ienfLxahf/VAZKRYOr6jmHsy+q98/zWerxwrhrT6UbxKLmBwzUMtHt9YIOqVlwiJra3o2m2qCHyrEiL2hGhpa/fBGO9W9Kfcfpog5vSeJF4oteKBv79Y6XddqLRCBPlNEOUtrfOFqS5+3n5TyIUQIjNO+O9eL669yjdWJd8UQ2uU+8M8MkzcLDC9ShF4cZaoU1aX3u69ZolH0ao83w1jln/Y/2UhYu7KvSIpTZHndPc/48Xy0NyyCTkgBqz9w8DwaoMYOHCnEK/OiBbTfYXQakTAxgni3OtPKM4vgObiNNGoeCXxn8sJf1vG/3zHtFj3icz/WcPxoIRPDGFEraaj8Tu7BUfHAs5qAAwNMTExQp4sQytAnZNGQmIauqs21Yh7cIcUpSXderkRsO8ulubm4FKRxs2GEfAojNTUVFJTU0lOWk5NIDHMgFbTzpOalMQDv4UE3b5OZta78+Ac5HI1CEHU/UBehiXwb1wFTEyIpcSyW/j2L+BM8bOjJDLkDsc37SDMvS9da9ryIka3K21lryE5IQshQCnPQe3ghJGtNQZGYGSRjSxFV9opSRlYVCgDZBMaeBG/ndewbDuSFibRBMUDuNF33RFicstc9+dHSwMDzCy1ZCuyycnWolVrkBuYYOKuO3p6fuM2URk54C6ha8uSyB4HA+X5+ebjfHJSSU1dj/df5k2HgbEp7lWaMaJNFSxMDDBM1JIWGk2m6uNhJEXUvMndZcpMlmFauSIARtb2lKrehmkdS4DWAOO36USHp6IVABpigh9yzO8G8Z9Q8m8fPcdUHQWAmbmKt2+iyZYXkKgvRKD/GZwcdJeGJfZZXA54BYCZc3E8a3VmentnUBthFhpFSOy79CoJvXIRf/9AUvLJ6rExt45e+NNi5D7W9dQdM9cedUTnHh3EwhWb2DVC+sXyp8iK4/ZRf9acd+Xnowtxef2YxLzr51oSXwVz0u8q0erCermWtMRXXN27iyU36jFqwUAMI96Qlb8Kc8LYf9OLHvmyF3bpEg/e6kopWavBLCYerF2oXK83vmfv5mvX/rQxMaJ6r6UEp6aSGjCDFssekpqayokF/bAzA1v3HJJidHtpcaFRWNWuBkDE3btce6VrhelaLSaxnzoG/3Oy0qO4eWgfKy+VYaLvVOzehJCSe9Bl7ZJDUpwuvfEvY7CsUQUA51Iq3oTkvl8Qm4yNT31AQ3LsCy7t3M7Kh00Z9mMnlJFR5KjBoURfTn0wBoSyaUobJIBLGSUx4boIE1/HYdNQd2wT8+QJgTHpYG6Cp1dRjF+FAkZU7zSDOx/IusXUdlUKPHJ8cCAAJ0ddo7Gzl3PlXMFnJEpFIndPHmRdgC0/nVxO8dcPicvdxH5x5Spv0hTgYkvbZiVIuxeUL2Qm1/yOc+9FXO7cJpClhHPNbzfLrlZj7MpRmIW/RJa7nRp85z7xWUoo7kib+q5khhR+j/ZzUn70Ulq3yeJBYUdSgNCAkUkbjj1MIPXlS8b5ZLLn8B1wq0Sz5t9z/vHLvDqJjVqM7nzVmZHDTdi66g7PIl5Rv2YVjA1AUqkNUxf5Eh6bkBvmEYu+rc9HN9cdSuLtM4ij95/nq/dN1C8gvRoVmNl04czjBFLDwhhWNw3/E+9viGs0WSiVII8I5urRIBTGNjioMgl/d9dWmUWyzBb3T7gC9bUSGf6SRjueMa7x3zy95Cu5Y/pJZIaxbeVBnp5TMW91FkN6luHQ4g3svRNEmp83lWLuc/JZBOFPrqG+Mo7LzvWZuPl7qlarwzG/1YzamYKRmQuqtDjubjtFA68ROFRIxMLGk3JNbSgx/hGlS9gBdvSdUIlNq2ayWaYCd3fKlO/JiP5VCD51k4Nxj1mXJENpaECxGt2wMDcBwLmslv1blnJluzEYF+fbIUPfXzP4jGTIktBov7BikhnG5mljOJJQinrPnnAu+hEW3x5lc68iOFduTZNXZxn5/XAwtaFO24G4OVpibKKhnnc7tq6bwba0FJwrt2HYoKKQdp15A/sR5t6Uqk9usvPlFYrOCKV6AVecbIpWoWGJeJbPGEeGSkOFRr3wKaM7pkh68oDNx/YhS0nA1MiVFmMKtpOc+PQ063wPEfnkBvc06Qy73YC5Pw7C3cmWTt17snXH74wM2Ill0Vp07/ANDqYfl1Wy2RhabjvKsGGBGNkUpXXfEQCYu1ZkZJ8mrNw1g8Mb7XAq2ZB+fTwxMgCQ88B/Ld/PTsS351Fa5coKPTKNJUcjCY94g9mRO+yq3ovN09riVqMWFoeOM8xvM6YmljRo0QuJxT+/EvKpnF49jENXw7kRa86wR3up234EwzpVpVKP3hzbN4th0WnY2rgx7TtdBdpUbMXigcEsmT0YrWERSpZpxdDi70bZRE4tmMLE87W406M2+Q8QU1/dZOualTw9L/j9tpTBuceLQmg5uWEK+47EE2XhyZIBtb5IvqPu7mL6PD+cPSsTem8H2Rotw+duz71jqiTk3DbGjAxiacZxulnrrqu8PrOIhf6hxIY/I0fyhJM1urJ5WgvuH17FL5ue4ln9Fj9fTkFbogGzf57Eu1sgsmfXiGrY5oNr40p5OL+v8GN9hhoTWzMaTZoKSGjYvio7dq3j0OYssLPDrUJbRg9phpvhx6931Ok0hc2bf2XY2hhMi9Rl5A+6m82q7Gj8NmxnR5oKYysTqg0f+6+U5Z8RhF3ZyrRFZylWuQLTbq1HaeHE2Jn/wcEdvNqNY8vWBQxbFYt58fqMHKUbST27/0aVdZsYdjQYY/uy/PB9b1Clc23XEhb4vaVGjftMDoiDyt34bdJ3uBQwu9UcuIH7a5cxbHs4Jq41GDW6EgDq+HhOndjLhtexGBkYUq3T94XmJmDNMA5cjeBajCnDHu6jTtsRfN+lGp7de3F032yGRaVia+3K5O8KvseZ+Hg/M2Zuw7ZiVZ4/2EdWZgoDFxykjTVkvghhf8ARUhMTMDG0p/MHi7THLO41EtfFW1nxkxsmWiVPTq1n6orblK1alinXM1E7V2bqtJnYmkFM4E02++8gMz0Rc6vStBr1968r/NtoVGoOLFxNVClrhEyBws6Rfv0qAfYMmFyJTf+ZwQaZGooUoULFXgzrUwk7wLnpWMr7T+NZld50KqG7H+9avDpOlpuYPuEMOVoDrDzr0619JxqUS2Tr6Hn4RYZjcfQ2vrYm9Ji6mVal3ek4uDKbN8xhZ5oKnJ3xKN+VUYO8ct85+TMquYIDi1cRXcwSkZlDjr0rA/tXzPO3tXvGoqHDyBGG1K09GC+LonRuVo5jx9ew4cFL7CyKUMKrFQPdDYgNPsWmWeu5FWPJsIeuuFSsz5AhLQlceJBbjyUceNAenhxm0flWlIp4yrVT56gzpCWSL3zt6Y+kJEZCqX8mw0AIUdDLwl+ElBsz6T4jnOkb19K8vM1fP6TNITk+iSyVFlMLWxztzUiLTyJbA5Y2tpio5aRn53+bxRIXDyfMtRqyZMmkZCgwMLLA0tyI7Bwo6u6ALDkWAwtHbCwFqdEyLNycMTcCUJORlESqXAkmJpiZ2ePkYI46Q45cmUlGlgKMTLCVOGJnpbtfqVUrSEtKJlOpwdTaHieJzQf35T4HScFnGT9nEQ0X7mVE6S93WR1tDinxyWSq3r9BaeVYFEcrnYKkyc4gJjEVA2Mz7J2csTLVZVyrUpKSnIxcqcLKsQiOVsagySY+OvGDt91tXTwK7UzaHDnxSSmoBdg6uWOnqyi0OQqS01LIzlFjZu2Ck4M5BaltaoWMpOQ0lO/uPRpb4O7iiImxIWg1ZKYnkZqZg5GlBBd720LrUJ2ZSkxKBkbmNjg7SjA1ylUQNCrSUxNIzxZY2NjjYGeVq5hqyU5PJSVdi6OHc94LPTnpMcSn53tD1UyCh6stoEUuSyUpLQtDYzMcHZ2wMPtyiqksMZK0d/djDQywsnXC0c4CUJOWlIRMrsTEwg5353wvR6lzSE6KJ0tjnNtHzHR3kFGTkZBEqsIUNw8H8uv8mpwskpOTUah531ZySU+MJD0bTG2dcZMUcnnwM6GSp5KYlMG7GjE2s8DR0RkzYwBBTmYaySkqJMWdsTTQ5S5HFk98Wr6WbWqHh6sNclkKKenyvBMUUys7nOzt8tqWRiEjQ1j9YcGhJjUxkYxsFSaWNjg72efuImhQpKWQIMsGIyNMzG1xcrTB5F2wHBmJKkucrd+Xn9BqSE9OQpadg5m9O642JnlxpCcnkZ6lxNjcCicnB0wLUHA/JzmZKSSlZPKuG5qYW+Po6ICpEQiNmrSUJDKylZjZF8E13wsyOenJxKdnYWJlj5uDDQZoyEpLITUjO698zWwccJJYY1RQVoQgMyWRlCwFprYuuL0bgDQaMmTJpGYoMDK1wsHJHotCBoE/9hFLWyec/qKPuDnbUVCS1NlpJCTK8tqckak5jk4umBuDUClJSU0iS6HG1MoRJ0erfLtKChIjkzGSOCKxNccQgUKWQnJaVl75mlra4uggwcQQ1Ao5KampKFQaLGxdcJAUPGZ+doSGKxtH8OvdCmxbMY4idiYff1QIZInJyDU5qFQajCxscXGQYPJunk5MJDVbBSYmmJvb42j/Pi8KWSJyIwkOVu/kC9TZGSSmyFBptBhaWCOxtcPKTE1yZDz5v8cjcfPA1hRAgzw5kaQsJRgbY2omwcnR8qM7ekIrkCUnI1fr0mtsaYezgx0muU0oW5ZISlo2GlNLXJycMDfWxZGZlkKKLBsjI3NsnR2wMTVGpZCRnJDGO63GxNwKR0db5HHxyIQhtrY2KOUyhJUrVqpEsrDGyd6m4Hb/LxN69Bd6rH/G4qOHaPMP3r36KhRTPXr06NGjR48ePXr+53dM9ejRo0ePHj169OgBvWKqR48ePXr06NGj5ytBr5jq0aNHjx49evTo+SrQK6Z69OjRo0ePHj16vgr0iqkePXr06NGjR4+erwK9YqpHjx49evTo0aPnq+CrUEzTbs2mccNenH2ekc81krWdvDGqvyz390uW+1TB1NqFZv0Wc+3YMiqWcsXRoyobbyb/rXi1ag05OSr+6ntZbx9tpL5Hcy7cj/xbsv8NEp+eotc3TdgU/ik2gz4vOZmX+K6JPU6O5WjbdxPRKblfV9OqeHV4Pe3buVCqzg/svJOQa+FIkPrsJjOGeOPu3pzhu0Lzvh2qUTxi9bieVHFyQtpnIk8UhRhTFxqiLx/gu57lcC/Rg0Vn3vLO4I7Qaol/fovRQ7xwcnKm44yTFGRPJC0tnBt+C2jTwppJR2LyxaEi/Mpm2tUqh5OTEyMXXnz/rdOPoVbweN0UfHxKUK3rUu5H6qzSaFSx7Fz6DSWLOlGiVG92nH6f3gKzqZVxcc1oyrWfQ1bOu8JScmHBCOztnShXqy3brr1F9f+XD7ypFQQuH4dUWoaafdfxPF7xv07R/y3U2VxfPIK6dSvgNWQbUWnqwsN8JrTqOPas6EnpYo4U9+jBthOReX1EHh3KijEtKFWqIR3XPEHxLlkqOZcWDqNOHU+8R+wiIVPXR4Q6jiv75tPayYky1eqx9nwgOYX0Ea08ld1Tv6FSpdo0nXOZ/MbUNIosjm2eTNWqTjg1msabQvISHOjPnB8a0mjWoQ/jyHnGxgE+ODk54d1lNunZBQ8CSmUWDy9tYVT/CkiXP//ATy1LYPtPnalY0YvmC66TXVhVZYQwr6cPro6OODmV47vZx/NZWxOoFEHMq1sRj58uFiLoX0BouLZxGM36LyQ6Lb+xmCdMdLSi/rB9nyxKkZXNXw3TORlyPocZmrv/aYmTY2tOxv2V7yPGWJrQ7IcDnyGm/xu8OPQzFVv24Nw/LPyvQjENv32DxtNW0qpi/o/re1C0nBNI3rmVZeLKoTSfdQ7/Xzsjs27Gw9CzjPIZRF+pI2SncO/8Pvbu3cuxs1eJl7/70LWK2NePOOC/H/9D/py7fofk5CzIeMHORSuY9ONstu/di/+hI7xJex+7mWVdnMqYgvHXYxzLuUo7fu1Xl9AH8sIf/swE7gmj2ZrnJEU/Ya7XW367qCusrODz7JJX4NiJBN5cmIBx9C3Ck1VoczK5ee86LWZcJjb2AjPdD7HvngyAxEtHsO23kKdJSSzpkMLP2yMKjDsnJpgTb5XM3hRC7MttSDXnufVa90VrWfg9Ll0NZ+SUiyQlJXJ8fnvsCpAlkZSkQc/pnJw44AN3dVYqD59EMufAE5KSkuhls4NDwTkfkaIj9coGljt+z9WrETxeWYMT10IASHqVjnHpkTx+HU/wiakk39rL4zxrjxpinj7gyN5r/HGsC710gBeKIjSs75nXMZUhR1mbVp/nz5MIu7mNcilxKGT/e5OkX4Lks0tYVmwqN2++4uH8YmwJePm/TtL/KRKPzfl/7J13dJTF14Cf9N7bpgEJCZAQem8CoXdBQUBUiiACgiA2FEGKAiogKgJKL6FJEem9kwSSkN577z2b3c3O98cGkggERER+fvuck3OyU+6dmfedmTtl97K92RL8/KLw/9iQZYcTn5vuvIQSNBu8TUBsFtFnFlN0axeB1evt0NO/YD/tMAkJ1zjcajffn1eZVDlHPudgi6+4fTsC3/fhk/0pAJQlRhFh2oXTubncOPwNUSH+ZBfV30eS98whc+ivhIff4eKQW3xyqLqDVqRxevX3KJpO4+bNXHKvfvVYJzae7UazaM5HNLO3rhOetPNz0kccIjc3l8OTynj3aP0uOHV1jWjT+23Wvz8LrT85OkjY/yklo7YTGenP+X4XWXg0p1ZsCZd9juIbkVHXGOs+g/CEdHJzY9i6eNh9T2uVRRn88csFPBe+Xe3C8/kilEoyy3WYMf9dHM1r/7h+Cxq31QYTo9qJKYjy5cQRH3x8ThEcX/OcLhzYz6zhU/jBxwcfHx/uZAKKEiJunGVu39dZWh1+KSRVtVkiqyDt7iUOH/Rh3/4LxKYX3FejkOZw+9wxfHx88DkbQYDvbfJk0PH9s3zWFhTFWVw/cxgfHx+O3UiodhDTGrf2GmBs+I+32f8KTUetZFffZC5d/3tyXgjD9FFYWEPjjq1rAqxs4HYAIVd3sWbRdpLi75Bn54kJEHD2DKmVFUilUirzkzly6DwA0oxQ9p78nciiUkoLM9iz34eQuFwQCuSVlcjlMqRSKVJpJVW1Vtk6OtCgmR2Gpo/wRPUvYWJui5bWoz1l/FN0nTaNN7zsgEKSNM3o6qHy25OTXYKDtT4aGoCuLkVJ6cgLi6lSKCktKMPGSuWpR65rSEGIynCTDFrMMNssvpk3mZ13GjG3d/0+dUuKpehrgaGBNmhqUlZUTnmKarczL+w4/jExbFk7hylf7SChoF5Rj0RTzwBTiSFHtnzE8uWbCSvzwP0xzrWS4vJo07y67MYmZN0KBMCuWTPGjeqLqZ4WlZoJCOuGSO5by3ICftvOu+O/JbiWrNyr69l8VsaA0cOQ1PKCJRBoaWqhoSEoKopkr88e/Ipqnyz8d4mLyqFjG4nqg4kZGZdv/bsF+o8RHZ5Juxa2qg9m5qSdufzcdNu4uzP2lf6Y62sj04hDYdUI++o+kpaUh7ODatwVNnbk3roDQERoRk1/M7Mg9YRqjDd268n0wW04uWwyn32zn6YNWmJpWL8vo7CgNJq4qtwaY21Lxtkrqv8Tz7M5zZbUs18ze9ESTofkPFrI4+r4Uj/yrvzA8uUL2ednQN/mTy2KqNB03BpV+7C1sSPz/LVasZl8M34mm44FU1E7U+Rp5s6YxuTp7/HTsduUVh9y3fl9G3n23Rjk+Ry9Bz4hEgdw9HSvFSKQluVSWCBFKpVxa9eH3EoDhBKZVIq8SkGlVIpUKq3ecRco5DLkSgWy6nDZ/eMqGcWFBZSWSCkvKeLi4R+Jrt5G9t+7jmuJuSpbIOUuO7/YSlxpTSkKM+LY/OMmroTnI5NX3T9ltXcEh2Zu/3Sz/E9hbdvob8v417cD0w//wJI1Wnx47UHjpOvsHVwXtfa/HJ1pnOdHmrYOzRxkXDjuS7HXx1AUwv6fvmVbWKaqQkoFJaV9aD5hMN1sLDEu8GXtr0HoaJsy4s0vaNrUCUy16DdUA4P4NIaP68efzU/zBl58vXItBkbGvEhY20hInuXNtIrzbBrr/HyVKyu5e3wn2U7tecPjEfuSFVKoUvDAq1VVBeU1R7Fmjq2Z9PZcDu78lh1+BfRrWs7+uXP47MC1WoOrNztSttPyzzpkMtUfEHnzFIcCW7BhxQKaNyjm2o2TWA5xZ0ufCXwXlVor06scTl1Lh0dUTVNDA/2GLenjMZEWtvpEHt2EQucv+lQrKa37OXU/a1eGMOzHz7G/70lTj77zlhD4tgKLWkkjz//Aj+tz2bNDk+JyBSEGXvwx0xO9ZsP5vNlcWrb8BMsGjfC07kS+9hPcC/gvUvz/wyD/1ygqfv46Uw/w7dJAhv68CMeHbTwJoPQRJ0SFtctrRo9pS7A4f5otkVEU9e1AZdZB3u4yD7/7aawZOfcbln3Q70FZ1XXPSojmvM96LFedYelQUy5dOUtSi9coOfEd701bR8z9DE14f8uPzOvv+cjdHWMDQ8z7z2RaJ8g9t4/Lhqb1NsVfok5fcGF76m00zSxq5jFjd95ftoqSChlCXsipKwFEJ7rS1t2Cq4eWs+raOhZryyjWsOX7wVeZ06v+zYFnSeymBZw/Z8j8Nx9sj6HrIumja1srRJCXco5Naw8Qmwet2ulh9Ap0dnRm4Btvkngtkz6TJlFjyprSoucQujS8QeNJk+hZW7iynOSQfXy77hoFUiXtB3aj2XBoYnmTs2cc+XDHWyr3s4pKioYNxKB6HSAvv8y6n1YwctZq5vRqioluzRMf/nMi/fVePAP/38S5oSs3pnVg/ZaTzOhu/fgMD+Ff3zF1GPkeX8yt4mTogytTHSOrOj6f0XJH484drsSkMezlhhz/zR9dAwMws8St9VtcD4wgNTWV1PRMiop30x2QSa0YNn0XCQmphB3ZgWF+GOEx9+4WVqGoqkIIqMhOJzO14L6/ZQ0tHUxNzdH5Nx3PPoTcnEwafH3hORulVRTlpHJp7decEsMYP8CLsjLVzR5d/WIyMosRAqrkVShtbdAwMkJDQ4lMmUlRoapFKyqr0HFRlTkvPp5ChQ7Wnp68Oa4NqYfOA3aMWbOXmNRU1TNMTSU1dQfeGhpo61RQWJxHpVQglAK5gSFaNlYq/TZNeG3Iy/Rq44qjqRvKwOskF7sx9/ytWnJSSa3HKAWoLC0n1S8Aeyc7bGwssDApICS8/rvL+qbZxEapjG1ZeSVazVTDo0xaRMSxXczaasa0zYtoKi+puScHyCvKKSwoq3Ps1n1xBOXFOaRGnGXm5z9z4O2mqghtfTwn/UxmZirBl7fzsncrvLVqban+hzEwyyQqXLUAqSyTotPS418u0X8LQ/N0YqNU7SstqUC33QNLwH8MmbSYiON7mL3NhHd2LMFDUXy/j2jqpZGTpRpfSvNL0PFQ7UgZWaQSF32vvOXoVZ+mVRQUkJFfv3Ep2AAAIABJREFUjrGtE+0HtMepNBtFSTmWzmM4VGcMCOKHD/phBhhZJJKarFJYVlCKXnXdNQ3NsfSawtfjW+Fo0whJpC+XUrTwGvwRF+vIusD8eoxSgOu/HqVhMwtsbGxxd1Fw6FhMPanrR98smfTU6vLml6DbxqtWrJLSgiLKpTXfl6gsk1JYqYGdvQP2zg6YKirRLikDDQ0+PlxGXk4mqb7f03PC+udqlAK4TfuKPn3LCUp5cCGkZ2aPuUHNbres6Ahb1mnx8/EIEqJCmNOl7higVMqoqgJ5US4J4RnUDLMyZHLVfeGM2HQqlYJov8Ncv9uNs/5xRAXeYoxXw+q02ig1ikmtVM1VMqWcMmkBldXCtLSM6GDriVZePBWadS8v65s71CmvGkhJiqfrJv+nNkrhBdgx/WvY49ktEL+qxXTuZYbP+5tp6WEPwIChlqz54VuczM3A1BQbpy4MH9ic9Ou32XrmDDZONlAlpdKpAU4S1W0bA3MFmcFnWJ8RTlFcIk06vMH4KR34i/tkz5WKsiKUysd9K+dZK43n5/lTOVnWjRGcYN3882T0+ZWfR9vj0GYQHVP9WLd2DQq5AiPXLthYG6OtK6frSyM58dsmbolyKuVGDJ7oCkDY7t2cMzPDXFFEaVIELSd9Wa968wYt6OxSxG9bfkRRJUPTvDGjGqtW1Z3HfUDsxp/45rtwDA2MkLi8hls9GxNFif78fuYq2beDuaPYxOq8trw1uj8WBvrYOepwZOs6TiqVGFZZ0r1j/QZgs8FzaL/zPKtXp1FZLqNDj/EglERc3MjnP/jToWdH9q68SXqJjAlzvqKtBKCMyz8vZuriTLaLo/SvJU9RUciVIzvxu5LNgW69eLOLLRRmcPTICVILS3C2Nse+XXuMLF+sXfx/ihavfE7bLb+xenUG0tJK+vZ/+98u0n+KNq9/jf+2A6yOyKKiRMqrI2c/J82C6Ku/sOD7G7R7qTN7V/mRUVDK2PdX0cEeur7yIftPbGH1qRKK87QY/K7qDLzdW6u5vW0/q8OyKS+W8vrYYQBkh4Sw784dtIVAUZpIrm1b9MwN6isA3WduJsJnJ6uvF1CSX8brk9oDYNNrGjsGvcOy75bRwNSSKu2BTH7MHsDto6u54htGSIwBq6VBNO0wjCHdXPAY3JOTJzewWi5HuzSXqS9Z1CtHXpbH5WPbCfa7Rlp8Oqt1mtDDexAdPCR0n/oj0Qd2svpKASV55Yyd0rZWzrvMbDESu5WbWfPRAEyBwrQEth/8DV19EzSVlaTrWeDpZHk/R370ZQ4fPEVSsATfxM50avRi3pPUKLfAxL2Ywzt+wcREg7yoJMptbzOkSXvMdcDILIpdX69GKz8ZaUVPPvt5JKaAc5siji1Zjb9mIflpEj5Y/w76Bhag78e2jT9hoCcn7m4YjZvG0cmxA/0HbWHjmp9wMKwiV6cYI6kBoyZ/jFncHm4WtGfMa/24tGoh82OCGPvqewz2fIa73/8xSoqyH5/oMWgIIf717/hmnv2Aqb/qsHDVF3RsWH8HyQg9S7Z+a1q56RN1KQqTTu1xMACoJDcsiNspBWBggImlG21aOCJyi0hNjSU5J48qtLBzbU7zRhJ0taBKVkpi2F3is0rQtHGho1dTTF5gq7Qw/iZLVyylwexfmePl8PwUywsI9QsmtaTmkN2hZS9aOqgMt8rsZC4FRqBlYIZnq3Y4mKnuwCrKiggNDiazqAyHlj1p6VA9WZSXEx4RQHJOKSZ2nrRp04DHDYuygiz87oZRroDGrbvR2Lr6QSkV5KZEEhqbSqWxM51bN8esnmdYnhtPYGg0JfduFRjY0b2jF8YG2pQWphEcHE1xuQynJp3xcjV/bNOUJ0dyJTwRfesGtPNqhom+BgUpYQSFpXLvq1PGNs609GqOqR6AnJzYCEJjFbQY2Jbaa8oqWTlRgVdILgDzJt3o7GoC5YWEBdwltawSxwYeuLk7o/8/tpz8O5QlhnE1MgUDu8Z09GqMgc6/fsjzn6IoLoSbMWkY2jeli1ej53ZCVJgaRmBoyv0+YmTtRMsWXpjpgVJWQXRIEIk5RVh6vFRnTsiPDcYvNh0jRw+6Nm+g+pKQXE5mciRBMWnoGJjTpEUrHC0N6j8OFEqSwwIIT83FtHEHurpb1cSV5xIQeJtsuRnNvFrRyLr+0Skh4BRR9+ZiDS0krq1p7W4DVBAdFEh8ZjHG1m50a+emuov/CKoqS4kMvEbKvS/hahvRxLMlrg5mCGUVSaEBRKbnYebWiS5utY3cXO6cCkWvqRfNXKyrd5sU5KbFERSehNDUwdWrNY3sLLi3t1eWGcntsEQqhW7d8fR5oFRwfsMMNid24fsv3qh7KvpnhJLksOuEp5Zhat+YhoZ5pJTb0dLLBUMtyEkMICwyG6mJLe3btOXeo6rIjyHQL45iPWMaN2uFm70JorKEyJA7JOdKsWzQFIuqLMoMXfFytUXICwgNDCGroBzMzWnt0RqJmT6F8Tfxj9fBo5UTmZFB5JaBfYuetHKsf+Hz/5WkSz/x7rrjTPn1BK9YPj79o3ghDFMQKJWgoanBi3Vw/qIhEEKAhqa6ndSoUaNGzf8mQqBEdbdfzX8IIVAK0NT8e8/1BTFM1ahRo0aNGjVq1Px/R30upkaNGjVq1KhRo+aFQG2YqlGjRo0aNWrUqHkhUBumatSoUaNGjRo1al4I1IapGjVq1KhRo0aNmhcCtWGqRo0aNWrUqFGj5oXghTBMS4LWMrTvBM5G1XazlsLm1wdiP+Tn6s9xrO3XGYnEiX5vfsO1Y2vwcnfGpWVXfr1Zv4eepyEtdAuDW7/K1btpz1z205ITepIJbwxnT0buv6DdnzkDJUgknox8Zw+FpTU+NjJPbmHEMAfcu8zlQGDh/fDS2CCWvtsNZ+f+zNif+id5BRxfNhXPKVueSHv+rT94Z7wHzm7jWH2xrpewwqS7fDCjKxKJPS9/cYKieiUlsXFBHyQSe9r1+IirITWpS6L8+WJaZ5ycBvL+occ/9+zsUC5t/pShE7zZ5V/wkBQ3edetBR/+FvkENUzh0NfT6SSR0O2194mU1bTv7R/nI5FI8Og4nJ230mp5N/nniQ3+gT6tJUgk3izenlQrJpn9S6fSQSKhx+sfElf94x75+bFc27OEoaM8+O7Ck/3QcnH+b4zqIkEi6cJ7a4LrxJ2bPwSJREKHofO5kVX2rKr1n+OHNyS0m/AlsbmVBK0diEQiQTJqEZlFlQ9NH3t8GZ09Jby+I4nSmEtMHtgciURC7+98n1OJ8/j9l4k0bSTBtckE9l+u6dOVOalsmD8Id/eevPxrQp1cd9bOoHNnL7rO/o0yWV3XvHLpKcZ2GMLWG38eax5EKGQc+fI1WrToRL+v/R6IP7/zM9q2lSDp9TmJj5GVELaefm0kSCS9Wbi1buqb302jQ4eWdP/gGApl/T+AI5OVEXRpC+9NbsfQDXW9RMnLiln6alckEgkDZv7G42pYWpqJ37E1jHnFhVkHH0ydF3OTaRNbIXF2Z/Kai5Q+RMY/hqjCb+c8hk75hrSi2v7vQvjc3YUhHxz5R9Xf/mEIY/70nF5kfFfPUvVnSXNeWXKRUtlTCEm6yKt9WmPv4Mjik5lPmElJxNlv6dVhMrGphY9PDkQd/pTWo97hxlMUsQ7iBSBwdV+x8HjGA+GH5w0Wmr1/qAnwWyUGrg0XZQXZIiI2TcgU4eKz178S+UIIISsTKTFBIigoSIRHx4sSmbw6U5UozksTIcF3RXBosIhJSBZlZZVCSLPFhZ2HxFcrNogbQUEiOCRM5FXUqMqKChBDe/QT5+6k/JNV/8tE7n9fzDsY99z1nli0SKy6mSJEWZm4snSBmLU/SwghRGXUabFg6xkhr1IKkR8t9h89JhLyFUIpLREnd34jzkSVCiGESD29TOwOkN6XF35ul1i/6mMx7ONDj9UtzwgV67fvFvF5lUJUFotrx7eI6wkyIYQQpSmhYs+PG8WtoIInqkfosWPim30XhRBCJB8/Ir74aq9ILxFCWZYnju5cKy7FlQkhhIg/tUIcuCutR1INYYe+EJuu59YJqyiIFOunzhQ/Hf1BrNwVUiumShRlporQoARRXCs07fAH4oPDt4UQQtz5/RPx0mpVHkXEIdF/6g8iOVkIUZYh/E+HidISxROV61mw6ZNF4lpKkRAZGWLDyIHi1yBVeOrB2eLTYwFCCCH8D80VXVdH1cmXf+x9sfjkg336YWx7Z4Y4Ep0rRG6u2DV6gFh6TRUuu7ZC2IzaJbKyhBD54eLE/qRnVa3/HLmRd8TnY0aK1dfChVBUiDM7Vos//ggVQgghy08XMeFBIigoUqRkF93Pc23pW+Ll0XPF5bxyITJPiaGDVj+38qYGBYm1P/uInDKZKA0KEF/PWy780lVxgbs/Edv8Vf1Zfu59sfpyuRBCiNLjH4s396aqEoVsEdP3Zd2XV5Z9W6x49S2xZMcmcfBi4mP1Z/tMEUvOZqs+3PhSzD9WovpfViRufrtAbDh6VxQWPlldfvloobiSXChERobYOKKf2BioCi/5fa6YeqC6UkEbxeS9+U8m0H+d6L4msk5Qus8U8frSq6K0VAiRel6cOFJbllTEB4WJ5Kxi8cDIcH6+eGNH3X5TEOUntq3fJoLCy56sPM8YpUIm9q9+VxwIfHDM/rGvqeg882Dt1KK8IENEhqnm9oSMPCG/H1cpUiMjRVBQmEjIzhXJd++KuMQ0kRgTKhLzKkWVXCpSY4JERHKuUCqFEAqpyEiKEkFBQSIup/K+lLyEcBEaGitSE2JESFCQCIpOFgUyhSjMSBShkQkiOfquiI1NEalxEeJuVJIoFUIIRaXISYkWd4OCREhYhMguLhNKIURZZrQIjYgQMRER4m5QkAhPyhRSIYSQFYqYu0Hi83HzxR9BqrqkldTfTvKKYpFwa4sY2n+cOB4UJIJCo0V+sWpOkuWliej7fVo1k8hLckREWLBILxFCVponYiOCRHRm3Wccsbq7mHc4rUZHaYY4tm6bWLlxt7gdFCRCI6JFYa1pL+7aMdHjpdEiIukJ310hxI0lLcWCi0+c/KG80D5kTMzAoVPrmgA7BwgI5I51DAs2FrJ1e3tKLZpjAcRcO8vl8OtEJ4G5tR3Onp14Y2h3ZHnR+BzYg398BVZaMuLzq3hvyof0cEni4qljBBSVkpUXh5GBCSOne2Kp8nCKtjbYutmhZ2byr9T9UVhYOaJdovvc9Q5avJhBALJ8KiVmtHRRvTrpqYU0sndS/VCyvj55SelUNi9CoatFUU4JXhIjAGSGpuQEhUKbdhTc8eHYrRJGjB6K786cRyutprCgHENtMDbSBS0FxSVSNJNToZEL2aGHiSmwoejyL1wNa82E4f2Q1OOxs/nQoagcHAqqLBVIGllgoAOV5QrKC8poaqNyHVKpa0huSAS0bP1oYY9AXpjK8e2HMZu8mF7ae9kVVTtWxpUNq5i6OLGOS1KHl79leWkSv//yDUHpmozuqfJEUymVYt/ICRMTQVllMocPHKPKYx6djOt3b/ismPr1YtU/xalUNnSjSbVbbcdXvmdhYTyHN31DSIY+43o/fXne2vCT6p+yBMqcXWnuqPpYXlaKu1czDA3l5BVEsXndHZqPXkqDp6/Ofxr3Tu5EHD1CkMfcOuGlMZc5fCyAnEpbbPQi6T3jV9pXj3Pdx3Ti7r7jNB/yfMc5x1atmNOqlap8ZsWYNJJgpRoqSIjKwm2AyuuacGxI+iFfeKkXd3yT6DGx+uWwsiXu6GkY8wbSjFB2bvidpkt/xSphK0+yT+93LYHWn1W/zPZOJO48D0NHQOIfrItvxmir02zae5fe/YfR3qV+D3Bvr1yi+qckHWlDN7xU3pK5fSOBbtOrG9rGjtjlx+G1CU/aRHWoqCjF2dURHZ0ykvP82fJTGB1HvIdqlEjmvdb967gkfTSCxLDz5BSbcfX0T1wN78hrA3tiY/RUxXrmWFiBdfOm9z8rFVXcOLqdW0l5FJWCi2cb2nfsSgfPhgTu38yZ8HLyyguxsNXkj598mbhkFhohG/Bvs54fhhnhd3AFW8qGcmDRePTlpQRfO8khny3EDTzE2ZmNAYi9coQvVuzBa9AQdKuUKNzcaWHfFFfNW8xfdJ2eI5uQG1CMgZ0BOXnpDP1hP/3Lwrl0+RC3Y6XoGRjh0qITL/d/idKgI3yyZj96tt1wsdUlvbCCCYtWMcgshTO7d+MXdYes3RqYAy9Na4WD26PborI4k6vnzxKflMml3bvByImxY8di0dSW4uhLHD4eRG6lLbZ6UXjP/IWm5ZHsWjIL+bQgFjSO5+wvn+Nj9xWXP2r7SB3S7GAuXzpDlJYWWbFBmFo78eokd8yqu4auLtg1c0LboH733LWxd2r2xGkfxb9umGZf8GHjTk1G7n1wYuswaRmHlE1qAmwlOKcHka5ZRXMrGdfO+JLrNRNKY/BZ/yNnCsFQQwNkZcRviMJraHda6Gsiy48k+m4+xlr6eHR+BadGdmDTkCnvWdM0Po3h4/rx52HZ1MGNBQsWYOP4YvklN7ewInP5VJbqbWPhQLvnq1wpJ/rSASL0vBjb0uzhaUrKQCGH+87vqlEooFh1YBS8ZxY//uHGubNKwpLlfNapM8uH6nLmm1X8cDaQmsPHjiw7vQzXP+uokKr+gHi/c/hcb8gHk0fTykWDm37X6eftzOFpn7EzMatWpr6sOfNRtVEKypRD/H42ja7TJmGqB7LyP+mQK1R1eQqKUoP57fCvpB4+y0ZpOtKG6QzotbDajZ0und+Ywb6uFffLcg8tHRMaNXAnJv4ysdmq+hk26cuYK8sYOvQnLCSG6JQ0pKVGFZ2eqmRPSXEoe77dh9GbH9OtlidcbT1TXBq4ERt3iZichx8ZPzHlSZzashf5iNkMaqQKMus0lbfPz2HIkGKsGjqgkJkQB2rD9FHYNmdS+yKWLD7G8A5wz9ao0s0lITqI2AKw4Rzaw2oMU0OvoTS4vp7Ld8xQPlLwP0jWWTavvYrHnDk0fJhFJQQUPOJyTpbqSlNW6Em2/34A4xs3KMhLx6qn4KX2k9ErvcDiN78l9H4Gc7wnzGPWm50flJWjug6WnxDDxZN70XNeyPhutoTduYyDy1DKr+1kxZI9JN/P0JAJX37KhC6uqvtwxeHsXbMPg7c+rdNH6pD5+EX4o3DsOx/txbMZ+Gsxds3bYWBgRg5UG6aOLD3jg56752NdOwNE3zrBjkgvPp04DAtJJf53b9Ora/snyvssSP7tB3xvGfDWuAfn1gFfHqG1WY21Jk86yHcrtiF1dkYb8LtyndtROrh9mMGqDamsObEcib6cIv9NHDo5lKlvDCX7fDjRZdroGlsxcvx0fE9XD+4GVvQfPwcPzVAm17r91/HNT+l74CIukz7iZQ9LtLTK+ePbL1AMGImnSwkz533KpU3LyfeYyDtxH3IwugTzoK1sOOiPtrExVMk5djAEw6ZejO45jQmRaej2WsyIluYEbX2fq/GlDOrpxYyVq9CavYZ+q+Y+OKc9BCNbd96Y9i5n795m1aq6i02FjqpPxxWArcZ5dEf8Qtv23Zk62Iv1gFnD9kx/czRHL9dv4hm79GfiJCNC9XUZ1bcDOn+Kt/XozLKPPHAyf3KXtXb2TgQtGc9+s/WMafN4t94P4183TG29x/HOG1s4FFtA/yaSOnGmzm3oUDtA3x2Nazu48JKCQcM82LTrBJaT9MFYYO48miv7pj7oCsuoCTMX7GfWAqi8c4NFvx4jJjELF9uGfyqJQAiN+76MtfVNaOzm8ayr+7cpLMhDMvuX52+UIghaPY/tZlP4cmrrWoZ8JqkZRghVEpDYgIEBIKe4NIaiYsAU0NMFB9VWQs/v8kj+Dsi9xsTvc1g+VDVL9v9wJf0/fFBzLoXk5KVTKUP1xpqbqf6AsipDhg9/m7df64EQSn5bOZ/otqt5Y9NO3nhETVIPrmHcBQ/2rZ9NzRwio6gkTmU7mwAG+qq6PAXWXoPZc2kwAOm3f2RXVK9avpU1sXZtQg8X6rqVFQItPUtaDniZli008X79CIyZC4Y2DJ79PYNnA2Sye9VJ+mj9efj45yhPjmTthgt0nP4hfRvUWr4JgY6BNa0HjqR1C0G3MQfglbmPFlQrnwA0arkiVJQWsvPbXWgNnsT0jvY1SxqzBkxaeZhJAETw5YSL9H5mNftvYtbpPT6+05tlAcN5sy/ARZa8fJnXTu6mp4cNMWu780et9Bq6RrzUrRVbTx6nRNrouZY159J+ZhyCVeuW4FIrXFoZorITrQANDWjkpCorQcQlwr3EGs1VmxYN+33IjcAPQSi4emor2Qb9Vf7Xjfuz+kx/HoYQvqRmANUGOk1Vu2eVlVKKnSaz9ZPxANxcOY3DcSOY2X0iv56Z+FBZFWkxrFt/htZvz2WsS+0FewDxSUBDAAFeTR+a/0nQc27P0s3Hqgt/gS/fSKNmX8qQ1n27g8aTufQu07DmrbFTGDeyHZVFuRzevoHkFu1p9pw2zRu88h6d0uYQlVlKC0ldw8Wqae9qY1uFhqMpw0as5N0Vw+sKyThGDtZI9AF0MJNYYcpDvnvxhI4ttXQssLC1REsLwBBDkwrKKwBjS5wNQddCD2MLA4yMAB0NDJ068f2379Oiq0sdOVXSIgyNzbCyMkdTAywsH23uCyHqjINPznmWj7nB+BN76NHUmug13ThVW24t+X8ZIQCN+5OTrrE1TY2t/5KIrIxUWn+xjzFt/rr6e/zrhulfowGePe4SXDWf7r0N2ffJBlp6qAzMgT2lTPzqJ17v4A4GBphYNKZNC0cST59n6xV/undvjaaiGAN3R+xtVLuzOoYVpEf7c/a4kuzzv1NhPYJ3FvR/bivHp0FWWYEQz3lvQ57Mjx9M54IYwztDszj59WSuNf2KH0ZJaNRxCF7Z0Zw9fRppQQ5yLWssrEzRMZDRre84gq6focRcEHMrhzaTawx9eVke4bf9SI8vIiBlIG2dDR6p3tq1FW0by7h98QzBGlLiUjTo10NlUvZ8ewExG7ez83ABtqKAfMNXGPioRZqyjEt7V7D+jDafj9Pg9o613Cm2ZPrEN7E3taLLSy8Tfu0M+aaCGP8C2k5s8ghBKkpS7+IbkUlCYBxhFhc5LZozoFtNHQtir3L5VgSJJQ3IL/fA0lALKOePL+czdXFanaP8MwsXcqVZe3rYKMm45YMY8b4qoryQy4HBVJZVYCDLxqRJUwwsH7Fb/awpv8lH73+Jfe+pVEXcZNO3S9Cacp0preDkxx9zs1VXullXkX59N1pjPgGgLCuagPAEsgOSiNO6xGkjT3p1bo6ejhaQw9oBw5l3rhW+yg2qRac0iI/HT0Oj8zz6FYSwa/bLpLzmx+fdgKIsDt0KwlxHA430SFq9Peb51Pt/kLSom4SEJGHdKhvvqQvRf+NrsukPmVI0e9qQFRLA0bvJ3LkaTqllBBmOWoQkpRN54wLZA1vQzHAXd+VPtxD76wiirm1i+S8hjBo5iIgj+9kfHoz3pGV0sIdeEz7nlO8ZTicIYs5G0+MdVV/oMWMdfgfOclqmJPPuHYa8Nr+O1OywM/gFhCNzbo5U3gB9nUdP+gM+3smvZ85wOkeQeDWUoWMmA2A/7EN8zgxjwWYHetrpE5zfjwmN66lK+S0+eu8LbHtOg2hffvnuC8TbvkxrDb3mbCTw0FlOVyhJDwhk1FsL622VqspSooKuk+IfSUGkIafPZ9PEoyUuDmbIMuM5dTcGC0MNyv0v0O2TFbVy3mWY5pA6R/mVRRmEhAST559Iet5lTl9qRvs2LbAy02fwG5PZcmA7B45lol+ah8J0EA1erBtr99HW7oulzWf8sFNKE1szNC1taOTUBFf7YczuOJuNR2/QSD+fvOCbpOEOgK6xDemXjnBC04k7f/hwJdcZ/97daGeVz12/KOLuppJXcpXTp9Np2NwLdycLKooDuLTXB4WbJcJKk7ySHjTXSiYnI4oLUXlQXkBCcjoyhSAp+C5WrSXsv7KX1OK2aOpoY2DVgObNXNBMvE1AWByNmqXRUb+MK0EJJDhHU9jREnMDLQThnP/tNDciLnDNtzFfH5vGoy5BSYvyCLnhR3pmDKdPnwYjK1q2aIF9hRStHtZkBt/haEASt69GILWJorhVUwwsnYm9tJ3Dedpc37mbNBspoRmuSKSJhEWnERtVQFLhJU4bNMazW2ucjfXQNykl/mYUZ+T5xB4/iUnLMbw+rStPvkf6p3JXFD9lzhq0Fi9evPhvS/mbyLNvsvdMFp5tW6tWuvVgYSdH4tmXVi2aYGfmQeuentjogVWz5rSRpXIlNJ6c0lIqNWxwc7PFUNsQc/0KouLiySmU4dW5P+2bOaCjBfqmeuhUZBMZnYhGqwGMn+CN2fPbjPrLlKSFssVnD0ZdhtDNsf6bRM8UWRmFRdro6xaSk5NDibYtXTt3xt1GD3Qtaahfxpkb/pRpmeI9aBCNLLVBQwszIzNSYgKJTEimyYiZ9HWredVlpbkE3Q3HwkwfDYdWeNjVc4dF2wiJoQZ3Au+Qnl9Cx2Gv09pB9aD0jSU4WhoRFRFJmp47o1/rheWjruAqFVQUVSCqysnIySG/XODavCMtG9ujq62DhZEJCZEBRCem4DHiXXq51t81i5LucNkvggo9e8woIqfShC6talbQeZEX8E0ywLmBLY1cXDHT1wKUaOvr0sCzJZ27NOOeDd24fXv0ckIIjEjDoMloPn+rK4aaGlBWQMwNX8JT0rFw7kwP7/YYP+2I8VcpyyE7VxN5VSHZ2dko7drSvUsH7IzAvWNHtDJDCIpIw9BjHIsndsJAA0ozwrjuG0SmRgMk2iVkl+vR1ssVXW0tQIGugSlNOnWiexdXjAHK88nN00NDu4Ts7GzKzb3o1b0rTqZAYQZB56+SUijFqd1QenZ0ROuF+B2RF4+kiKvky4zRsHChnVtLPNwckR9LAAAgAElEQVRdcWjgiq1zS5pa5+MbkYCGdVNeHtab8kKBjUkF6TIDDMsLsWjUiV6tvLC0b0h7T8fnUl5ZUQEV5TLyinLJLSjG2q0D7Zq7YawLhsYOlKQEEhQVj/3wD3nFq3psMG5MA0UUFwPC0WsxgMkvOaNV64QsI+h3ovJNsXRyxsPVCT3tRxummiZN0MkNxjc0GoveU3izw73FngFNu/alNMaPyEJ9er82iCYW9YxNZTnk5GohVxaRnZ2NwrYtPbp0xM4IMHbDXhrB5cAIDFoPZdpL9tS3QVZVWULIrTOEFFrQxkpKdkE51vYuONoYo0iLwvfaHfLK9Gj1ynQ6uNaeJyswMHGmTa9OuDmaowVIC1Lx971OjMwJd+MysksEbo1dMDfWw9jCGTsjCA2LpsiyOSNGdMH8Oc57GghSA//gbJQeXdu6oa/z6E6toamJq3tDcqIiiEpKI0+piamZE442hnj27UKJ7w3uJhYi6d0KzbNFDHqrI/qWDbCVRhCUUEDTbv1o56RNkYk7rvrp+F7wJ8vQlZYWFWRnl2Li0IgGdqYE/HYZp6G9yIsNJqXCluHjB0BqOpqGghxTd7o66lCCGV5NG1OUnU6THoN5yUbBRf9QsgoKKMUUZ2d7SPEjqtAEKzsnmhjkcile4GhjTmPXRpjoaWFuVUV8cBQFDq2ZvmB89Y7vwykvzOHO7XBsXazIzs4mu1zg3MgVG3sv3C1y8Y1IRMPGg5HDelFWBC5NG2Hn5IFprh/Rhbp4Dx+Ck0Y22o6emBZE4Xs7lGKrNjjrlZKdrcChhTt2hroYWxlCXhJhccmYdh3CyBFdMH7K9yEr8BBf7b9Jm9Fv0fpv7J9oiKfa7322KCtySEwvx8bJGRM99czzKBTSYtKycjF1aICFzv/YZrcaNWrUqFGDoDw/ncxSHZwdbdDReprj7BqSL6/nvUXfcT2wiglLtrF2Tq+/lP/Q3AHM3OKLQcvhbFn3Fb3aOP2t8vx/prIoncT8KpxcnPk736d7IQxTNWrUqFGjRo0aNWrU25Nq1KhRo0aNGjVqXgjUhqkaNWrUqFGjRo2aFwK1YapGjRo1atSoUaPmhUBtmKpRo0aNGjVq1Kh5IVAbpmrUqFGjRo0aNWpeCF4Iw7Q8ahezpi3gZmJtF5CZHP70XfrM2l/9OYVd70zA27sf73y2jcDLuxg1rD+DXn2TQ3cf4bLub5Ade4QZYz4gIOpJPC8/Hwpir7NgwWxO5BT+C9rDWPmuN97eL/P+0hOUlFfdj8m9dpg5s/sw7I1vOBNZcj+8PCWSTcveon//6Sw/U9s9qB8LJnnj7T2ORT/feSLtRcFXWPLJy/Qf8jE7/QvqxJVkRPHt8jfx9u7DnPVXKX2MrNzLB5g1y5vhE9dwMaZu6vxYXz78YBDeg19jzbFQ6nO0mZ8fi//hdcxa8DZ/hNX9UeHEC/sZPWwgA4a+wuZzCVQ8toZ3WTrNG2/vV/ho1QXkins/llFMuM/XeHt78/L42VwPfr7vY3F2ABs+mMpgb28++vl38qvDMzICObP9S2atXEV4pvR++qKiFAJPbGTWvJfZ7pf/cKF/Ql4Wxc/zJuDt7c27Ky7UjRSCK4e/Y/Rob7ynbiLjGdXrv4bPZ96MXbCBlAIZkbvexdvbG++568ktlT00fcrVTUx42ZtPjmVQnuzPF++Owtvbmyk7Qp5TiQu59NtChg/yZvCwTzlzu6ZPywqyOPDdDIYOncz7h9Lq5ArftZwJE0bx5opzVMjvORpJY9+ayXh792Hc5O8JinvcCABCIefCho945ZXXmbY59IF43z9+4LXXvPGe8iPpj5FVmZuGzzfvMGTIFD48WpP6xBdjVc+h+m/mvqTHlqs0JoA1i8bi7T2LdZdrPBkpKys489MHjBo1genbIx8rh/Jkdi58l/7e3nh7j2DxxivcmyXjwk6zfuXbzNp+6/Fy/gmEktBj3zJr0TaySxS1ImL4ceggZn534ZFZnwVhPjOZf+RxT/XFIWTH19Xv0EjmbfSnXP4UQtL9+GDqaLz79OXnaw/xkPVQBPG3tjN5/BckZ5U8PjmQeOF7Rs9dyt2nKGJd1S8Agav7ioXHMx4IPzxvsNDs+l1NwPXlYuD6WKGsqhJyuUIoRZxY8PqXIkcIIZRKoZDLhEwmU8Upa7IpqxRCJquOUyiEUqkUQlklYq8Fie07T4o8mUzIZHJRVStPVlSAGNrFW5zzT/7H6v00hO2ZIeYeiHnuen2mThUfnIsToqREnP30EzFzb5YQQghlwjkxf9MpIa9SCpEXKQ6dOCESC4UQlaXizN7V4nhYkRBCiLQTi8W+MFUDf9+zp1jrlypEbq7YPW6s+ODcY5TnhIsft+0WMTlSISqLxI0TW8StVJUsaVaS2L3mW3H+Zu4T1UMZe1K8t7FaYXaI2Hv8nEgvUX0sDLkm1qz5VYSEyf5K04iwQ1+ITddr6c8MEjNnfyHOXisQQlYukvyDRUZGzculeh8VotbrJra+9ppYeDlRiMJCcey9WWL60XIhhBC5N34Ri9ecFEIIURJ9Ufy4+7DIKftLxftb/L52gtjlHyeEEOLg6v5i0Yla/bQ4Tfjs2iRuJjxYoPxj74vFJx/s0w8jcPUgsfVUphBCiLifB4mlV6tbRlklwr+bLlbuvi0KCv5ePf7r5EbeER+OGCl+CUsQQlEhzuxYLf74I1QIoXrf5HLVGKeoNchdW/qW6DdkngioUgqReUoMHbT6uZU34eZNsWDJepFeUilKfH3F4hnLhV+6Ki78t4ViQ3V/kp+cIX7wV5VZeWmhGLU5QZUocJOYc7xUCCGE77ZtYt6m40IolSJu3z7x8ZKDIqu0fv1lx2aIT49VK7z8uVhw8V67VImodbPF0u23RF7ek9Ul8OCXYquvKnH5yffFxjsqWZtf/UxcrU6Temi+6Lk2on5BJeli766N4kZ1f4o4sVqcjFXJyv99dk1/uvCRWHy59uihFPI/PVtRHC6WfO8jcoukD9cVcUBM+OnGk1XwGaNUyMT+1e+KA4EPduof+5qKzlN96qavUgh59fytUFTVjhEKubz6va4Siur5XSGXVbeFyiaQ38+jFAqFXGUH1GqrKkW1jOo4mVwhqpRCVCkUQiZXyZPLFSpd8nvjtrI6n0zI5HJRVW1wKKvkQiaXC7m8Wo+iSpVeWSXkMpn4aeY3IupeXWo/woc2lFIoMi6I11+dWZ2ntp6H9OlqHQqlEEpllZDL69ZTCCEiVncX8w6n1X4YIujIZbH75A1Rdr8uNdFx146JHl1HiojEJ+wMQojLC5uIBRefOPlDeaF/pV3fECw61XK46tQQtgVx02cfczblsn9PF+RGnlgDmQHn2LH3e65EgI2LJ0PGTuDVbi1RlCazb89Gth8PxkhXidzQmU9nfkpXx0CWfryGu+WV7Nn7I0bGFry7Yid9G6lUaWmBqYsEHbMXy1ebtZ0LOiX1uIv4hxi7aRNjARRlmLcwx8VBtdmeFJ9HkwZOaGpogIEhWYkZSJsVILfVJD+9EK9BKg9VlaZWZNwJBs9WzL50SSVUlo9texsaPsYVb25OKcY6YGaiB1pVFJbJ0ExIAccGZIbsI1fLHbviW5y40ZBubb0wq6d5EmJyaN7YU/XB0IjM2GQqWxWDHgSGBmBv05CUxDPkyprSwdMNo0d5kaoHqbSchk0b0cjViCqNPG75ncY4X4dBkmZoIOX40o+ZujixjkvSiXv3qv5RFGPZ2hIXO1X76lpYoWlQwY0bJ1Fkl1Aq1UCDKqjxKP+PMmzONvKTwjl/+jgpUleVt69njEGDhmTnRXDjRiKlRVZoynMBG4jfw7Job95vl8n1wBu0aNmWBlbP/93/X8Grsx03Nh+j3+KpdcLzLmxkybYTxBc607aTPZPe+wKXapdj/V514fyvZ3Af8nzL2qhzZ5Z37gxAhbMuzl5m9z2aRd5NxaunymO6aORO0rHr0L47Vy/EMGhiI1UiOwfC1x2HwWPo+NZbdFSlRt/NkEZKbR7nf+TiqUi6fGav+tDAhejvT0GvQZDwG19HdWPmmFxuBl3Ds0VbXGzqd1IdF56BR29LAKocG5Fy0RfadmbygWWqBPJiztxuwqov3euVU1pSiaKsAkm1vjItPXLCoqBxM66fj6bjJ5LqxmtMzM9n4aV7o0csL+v2ruOSFIC8BM6fPomRiRH2bi3wcpGg+3yGjafGyBhMvJre/yyqFFzfs5Ltp2+SUQhtBoxl3KiBeDpak+h7lG0bz3I7u4CmvVsRvnIv7efOQi96M/F99vDzMD22fD6KfbrvcGrlW+hLM/H5eQVbfQ6jOeUiZ2eqfM2eWzmNzzcH061vS1KTsqlo3o3xw4cgid3DnO8j8e6kJDPFHhvLAgJzNZm/dy99SiI44rOaA9cyMTCzxnv0W4wf0JXMw/N566crWJg1RVujHKltMxZ+9xU9xB0WTPqKUyHxHEy8hCEwcvkfTGn16LYoTg3ip2Wfcel6EYUjR4KZOx98MI/ebZ3JOfczS3ecIqHQmXadHZj03kIsUv5g1uy5OHwex0f2F/h28QdcabOZ65+0f6SOovC9fL1sPdFaGuz60RxzBzfeW7SWLtUO4LS1wczdGS2DJx93G7i0fuK0j+JfN0wL7pzlyClNWvV50ABs8+o0flbWenIWltgmhJPRq4xWJjJuX/QnvcWbUJHCrvW/Em7cGDc3DajIYvW8rbT0XUMjWSGZ+RlIGjbCWlMDLYtmWNhbouH4Ml9+14Rr8WkMH9ePP2s3sXVi1szJNJYY/7MN8BcxMTEjb8sKttotYVJny+erXChI8T/GtRI3xrR7hEvUgiKQyYA/vchyOeTXuoIgLyD41EHuWL/M9FYARfju3s1B/2hqTio8mLbmHWz/rKO0HMpU1z5SAi6x7UIQw0rbYNW4FIES7652XF6xgVOZtY/8OzBn7esPlje/EORylHJBzO3jbE9qyMiuHuiVSdHW1aSTpyt/1Tubvo07zXQvsmLBPIzNS8lJ1ae9azn9AW20aT5wFEvNi2n254xVFcRePcot0YFJ7VRaTZxd0BWRpKamQbEVbo1dMdB7nrOLQFqUQ+Lt28RlWdDU8NnrlrTvTPnhJFK1TRBSF7q0VvlsL4qN5OKNq+ia9KG1pxNZheWMGNkXq2degv8ITl2Y3jydFT9eo69TTQ/UcjbD3tkNTWso9l/MkegvmKuy5DDqNBGnqz9xNVSC8pGC/0Hy/Ti0+RQmAybS+GHDmRCQnffwvMl1j/mrMi5w8mICHiPGYaYHZXm+bF7qQ/z9FMa0GzCWVwZ5PSgrVXVJpDgxhis3TqPQ86Z9cycyiyoYMbIP0rsn2bn1LDUXkiQMmPIGA1v8yYWrUEJO3fJWpPiS5NqQNzT+4s25ikoofsQRanpmrQ82TFv7JYbdm9WMunp2DOjggl9cElUaVdxJyMFo2AiaOv0dfzzPhqyLBwgL02PwKwYPxHm/vwJne7f7n+UZF/hl63kMW7bEzRqybxzl10IjvpzjzlefXmD+7z+x2FhK5rm19G0xhZOfTiH7fB7flumiZ2bPux+uIOl0uUqYsT0TPvyens7lTK71iPov2ELQtW7YT1zCqvZO6OgUcmj5SgxeHUbHAzImf7WMgPWLyfGYw+SkBfx+txyj6P2cD5Xi6uaGhlzK8Z/24NykCQNHLWNG6seI7ot4vbM9N3+awZ2QInr07MKq34/RePYa+q2bi+sTtJOpcxs+Xb6SiMLb7Ng3t06clrM59k5uaFlDkd9ifo9ZyOz2w1k2cT/rASuPvny9YDaDLte/s2LW/HUWLmpEqL4uo/p2eGCus2ncnPnTrZCYPvmGhKW1DTFbFnHeYT59mjzdxt6/bpgau7ehS3tBcG4F/MmJlV2rEYyuHWDSFIM7h7nWV07vAQ3Zv+8SeqNngq4MDd02fPTOcDSqnRG/gwmOgK6lJ1PeXkxWbhmy8BB2XYwgN78EnOtvMF0TG7p07fMMa/psqKgow7THGPo1e/47uZFbv8ZH2Yu3x7fHyfDeC59DZo4p992HWVuCnh5QRWl5EiVlgCmgqwu2NSbFhV83E+HgzZSxLVC51DWiWe+hvN22rNYEaYyzBkgpIb8wG5kc1RtragwmqgVDfrGcjj3H8ekHg9HTlnNwzRJivRbRfszrNKysfRnHDAmQQTYZ2Q1qgm2tQFcXpbKCvApDxo6dxoxR7ShOCefElcs0dnXF/q9u0hlaM3jcdDxeykYhZET4BmCnb1S9x6mNS6eevN3pwWwBW9dwWr83b41rg7V29Y70zRBMPNozpqcHyvQAvr+QTHG5AkOT59V1tXFo6c0Ujx4kXl3Btt/vMMiz9zPVcHvHaTpM3sMQR5CfvMH7FzPoPcqe0tJisnW6seKLBdiZaHDhq3c53aEv49UeAx+Jfe8ZvBL0Oj7h3ozqDuDLuokn8PxyJi87W5B94CoBtdJr6hnRuYMn+69eoazS4bmWtcD/FF8eL+KNt6fj5WTLvRGlsjJatYa1AjQ0wMGuOiaSlHTApfpj44b3ZWWe2sJH12345L0JuNtaoAnomzZjxDvvUH4/lTZm1vboAUIEk5UDVG+a4uIMQFlpCRlanfhm0QIkpppcWT2PP5L7Mta1I6+941rrzrke1k5WaABSaSwFRYAloKkJ9rWX0nLiQ/Jp4tYUzce63pRSXJJGhRTVVGhoANqqre0qZSh5uUD1pikNa3cCc4bPmVJXlK4lHYeOVe0ki2JO+vyOIisfXgDD1KJVDxrevEFOiQyoa/A06PkuDWoHmJbSpPGrjHrn3pijibGFBIOyK8ThQhNjAH0kTV2wI+epy6Sj74STmxM6OgDmmFsXq56plTOtzCHS0RgrR1MsigGtKjQMJYwe3I3G992XGmDnYguUY25lh1UDe7Q0wdHZnCf7FsVf4RY/Tj2N16J3GelkQfaBK3//TucjMLB2oae1y+MT1qKkuAiHAe/T2vHBhceT8q9/+UnH1Bo7a0GJVPH4xLji1iKY0oqe9OnXBOXN4P9j77zDsqz+x/9iw8N42AKyBGW4t+KeOVIzTdPKbJlZoZXNT2V+bGnDzJy5V+6BA3ELgqAMlSUi+2HvvXnO748HGWlgaubv871f1/VcXJzxPuM+6z7nfZ837h0cQMOZUX0qWHg8HAMDAwyMjTFpY4IOcPPUBb5bexyltgxZJ2fM2xthUL8tra5ZSlZqAknxCrw/n8fiBftb/XDm36a6qhItq3bYGv/dfbyHQJnJli+f46fM4bwxxpHco4v5wEu1d+DYexg26jqkpiiIDIulQinDwMwYLT19eg6ZSFHcbRQKBX7Ho3Du0xnqEvl+Vh981YcyqacF8ete4MNzAJrIbexxdXfHveFnhwFg7uhKB3tXspMSSbidRFJcCZbOqolk4KsLaVvgxdVbcSiunCC1aDD2RtqYO7VvIscdd3cb9AAnj1FY1YFCoSA8JIY6LTkyuSGaBqZMmTyMtLjTxCUlExcaiVB2waSFRWlNaR6pqQoyc4vJz05DcWeHtq4WRUUtGnr66KvlUldYgU0nV1TTUgXH/+uJtdoznG6o3zTWvD+OrUXDeWmoLRl7F/LuCdXnUkam6hRkRaNQKIhPUiArKubRH6b/Nb/MeZf9V2+iyAzj/L6t5DiqFglVheko0tLJy88nOyMVRbZqZ6e2opCMNAVpOSUU56SjyMijTnnntSWPFU8NRF39LYKbpNGmrRJFfAQKhYLrt5NxVVO9mrSd+h/W2mxm2+XrKCKDCLjtwWBpUXpPygqzyM/PJ6dMiwEL5pB7dT/ZAIp4Eh3tcGljR1X6dY5ciqa0sIDysiLyS8sozExH170XbapjCa28vw8cHh5BfOhOvtoZwqypfTArTeePVUsIrv+ybdDzb1MeG4NCoeDg6ot0Hqk68h8y5z+oR15HoVBw9uBV+kwdA6Ic/0Pf8uV5db59szsasedZuXU/2WWgoSXHodkY0AEbCwM0gKfeX0ZNTBQKhQKvjZfoO2U0ANYT32eNwx42+l9DER1MUGwPhturoWtogVMzWU5YGKoGhwHPvk7Z7VsoFAqObryM+9A+jSWtKia6oox25natTrYG5lZ07jaIvIR4FAoF1y4rsOuiOv4f9c7XVN9S5ffwej96PzOiScybTFCz5fUfTnHnE8w43wu88dH3RN5O4FZkJEfiYsgzUr3MF+coUGTkUlaQhSI1jfziSh4n2qZWGBgoqaipazWsht7TWFhHEJJRioGBAYZmphgZydCwnsisNpfZfi0ThSKa07vPEnUnjpYeCdEhJNy+yYqlq/HziyC7pIbaqhKyFArS88qoLMhAocigsLQKAZQVBnBh3wnibytQZIWRlNgFJ8tSKsoLSSushNoqSkrLUCqhJL8MBzsbTiZGoCfTx8DICGMLE2RaGtSU5JCbX0xRSRnKykIycksoKSqiuv5j1urq28RGKriy9iumdfm6xaV0XXUl2ZnZlJUXolAoUGTkUF5dBylxJDvY0d7Sjqq0MA773aS0sJBqJWjqGnDrxmVuhvqx8KON5KamkF9eQ2VxPukKBZmFVZTkpqNQZFNaX/8a2kUo4pJISVawd8E7rPj+FA/TIirLS9Fv2x4z/QffPNFYvHjx4ofIwyOhLPEsJ6N06dHVBbley0eFWmphaLSbxNBBbmhkmdFtsgd2MrDq0YPuCWdYtu0wvjduEJtjTJee9mhXqlGXd5M9hw7heyUKh76TGNHbGW0N0DNSo+CmL7v3HyOx3Wg8F07D/HHO+n+TivxkvI7sotJtFEMd5I8v4bJMbgQmkJISiK+vL8GJFfQYPJZednqgY4lTbSKLfl7NtbQyxk+fRcc22qCmiYmOHuePbGbPkRNYP/8dM7vJoDiRgAupJKeF4OvrS1iWLkPGTKKTRQvpaxlhQzEbNq3ndEAYvV9YyFAn1YOSGdpirlHM3l27OZVnw1zPqVi1tMOpa4VzTSyf/7SGiJw6Jk6fiYuFFqCOmY0L2lnX+H37YZJMuvLC9GEYt3ASkha0naWrd3NdUU1+7BV8Y+qYNLwLlOZxZcdmNu07THapHWNeeRn7hmPKGiqKc6jTd2DopL4qNYXSNEL8k0hRXMHX15cQRR39R0ygh7UmetbO6KaEsHztTq4rlDz93Eza2Ty+XQ/XDjZc9NrGwaOXMRy5io9mdEQXiDu+mO+3B5CZlc+tawH4JsqZNNiZ7PDjrFyzifPxUJUcjG9UCcM9uqCrrQGUU5JTgLZtV8ZN6ka9miNyt96EH97GHwe9yXOaz0cvuNf7GNBzxFOEHFzN/mslTPScRTdzScf0Xlw+tAzf8GxSNZwY3d0DZ2tTTNq6YO8yAGcCWPnHURTY8eLknlwPzcFYK5mzEamkXw9G22kMU/p0IE9YMMajfeuJPQIK4m8QFnwD/yuX8Lt8lRrTzgzu1wNjXdDTtyHm3HY27/NC47kVvONR396NOmGTeozvNuwip93TfPmsK5rKChSRUdyMCuGcry+Xr8dh7Nwfjy7taEnjRV3ehdKQP/htxwEqh37Ef0bfGYD06T7sKcIPr2ZvcB4j57xArzYt9zcDPUtunN7G1gNH0Zu2nDf7Noavq6qgsqKcti6dafU0VEMXC00lh3Zv5NBxH1xeXMxEd9Wuk6bcnfygXazZdZDqUV/wyYimeg9Z5KbW4jJ8KN3aW6IJmDpa46Sfy7r1Owi6Ec+Eaa8ztLMtGgjObFzI+rPp6BXG4nspiDJdJ3q43KUw9Q+iJCnUm+sF1vTpaIt2CzvJ6hoadGhvSdChPew7fhp/RTYaug442RrR+7lhRK9bw5ZjwWiNHIpVQCnjZvdFZmqL1s3dbD4ahFWv4ThqJHODznTUCGP9t2u4kKmFeeF1fH0jqLN0xtXBjOuHLmHi0Y6z+7fhc1uHWe/NpDTIj/jUGC4pXRkmzyQkXYNeTnIuX7yI68TZjNZN5rs127kYGMSNLDUc2rejMmgDuwKyqTOwpqdGON8djEEIgat7J0xlGmirx+O1ZR+XNTrw+eoPcWihaRWkxLJ1ww7KNEvw9fXFNzqdtu07YevYF4e6S6zafQyFuiMvPdOD62H5uPTqjJ2dK6UBq9h/JZPhE8dSe/s8RVa90Iv1Zu3aHVwtaYNIDcHXNwmLft1wNNRF31SNzEBvdhz2pqTnJN54fVyL815LFCYEsmHfQayeeoM+rXw70hJqQgjRerB/lpr8aPxC8nDv1x8b+WPcCfz/jMrCNIIjbtG290Cc9J7gFbSEhISEhMQ9EeTGh3AjUw+PPh2RaT/cwW1m6AF+/H0dx46W8NbyNXwws9ffin9huScfLPfCeNSr/PTZO/RyfZyL9P8tilPCuBhfRf/hHnd/G/I3eCIWphISEhISEhISfxdlTSVlFZXUKUFLVx993b+3uVVdVkx5jRLUNdGXydDS/Nc1HP/PIy1MJSQkJCQkJCQkngikVwMJCQkJCQkJCYknAmlhKiEhISEhISEh8UQgLUwlJCQkJCQkJCSeCKSFqYSEhISEhISExBPBE3GPaWXKKVauO4uhc2csGyza5OO7dhU/+1UyfoDKgFfCqWUsXnsUYdcPq9wLLP5hFV7nAqk074i79aMxHVoc7c2ipauo6zCO9iaN7tV5ieze8BMbdh3h5MmTql9ILkP7dURb81GbaUzlwEeLOZlnzoAujdZYSlLD2fLHH9S074Kd7gNeNPbAJLLzx0Vs2OPH7Sx9unZsi5am6v65onBf1u5azqHT+Ri3a0/b+sv/q7KSOXHgN9ZtvUKWqXsTSxA5XNq7gw3rt3ElvQr3nu60bI0aSuOvs2vvL2zbexvsXGlfb7P98PeerNlX/zxO+lDZdgDuLVxkWl6eS9K1c2zbu4ZM/QG4t2ketjg1ig3blrJjnz8l+o642pv8pVX64uJUEoJ82OFzFKVZT+xNmj+T/LggVm5Yxl7vGAzs22Nvps9f39gXx5ZlX9Df77sAACAASURBVLF5rz+JBcb07GSNuroaUEZi6Fk2fb8Sr6s3kNk609bU8LG9UWalnGHVjyvYe/gGlUbuuNvfeVJ5XPHazYbVWwhILsatdyf0662uJfjsYNGvG/ELicPAwRUbY90Wyg21FWV4rf2eNTsPEpXXho7dVMYQoJCo84f5ffnvnItJxbajG2aPvd3/m5QTfmwnK/yKGNXLscH19tHfWbxqKwHXUzF1dsXasGmdJLDj/W+5ZtSR7nYqs8FVZYmc3rqFDVv/ILxIl45d2jUxGFxHcshRVh64SY+uHdDRelwtq5Swi9v4ZeVWfM6lYGznim39JdK1JflcPLSKNdsvEq3tTn/Hxssek05t49dde/FTyOnfyQZNdTWgnKSwc2z87le8rlxHz9aJtmZGLfYRUVdLmNdaVu3wJqTcnkGuqsE+4ugGvl+9lRPeqjHlerk1gztatyAJ0pOCOe+9E+9kAzxcrBrcL29YxA9bDzXMFzd1ejLAqeV5qkJxi4P7V7J+SxhlNh3pVD+WZWWEE3R6H0eii+ni3A5tzZatSFVWFpEc4csf+9cQo9aHbk2s8GQknWLVj7+y70g41XJ33OxbG30fMUJJwuXdbDmdgpubM3oNbe7e8x5ARsg5lv7yG0eOneJasiZOrk4Y6UB5biInz53D0KoDhroPMw9Xc9vvAL/uCGfwwE71Y6/E3yUjdB/L9l/Frn+PhzId/UTsmMZ7ryHd2oN2Zk0HWEOyo8+x5uD1BhfrPjPpkOrL8aPeFDv05Y2nLUiJNWZw0xXk3yDtRhzHjgdQ1sRN5tCPcSY3CMloHlbTyJpedlrEGfbD09MTz1fHIdLSqa1q3XrFX7Htpf82WKtojgWpQRs5cP52M1eZhRPualEc9c9+4DQflOP/+Y1gu8l4vvYCbSJPsuxMvsojLYhVIcU8O/Vd5j7jjOLWVdJLgZpyrgaepMb5Wd55ZwY9srdxMl4VJXnbPLyqHXjN0xO3uuN8uEfRcuIF8Ry8chP3Qa/wzmsj0U7y4UZ9FaTc0GCCpyeenp5MNAzAP6Fl2106OnJs3TyYYpmDf0JZM7/S22HsO3GVjl3m4DnvVYZ3sW7RZq9MZoF9t2H00M0jOqO5rYz8oOOsP53C4MGeeL4xja5tjVtcnB2cv4wY5yl4vvI8Rpf3suRiNQCF14+x/HIy0z09mTLMmUNnzpFXej9W0h4Ne5Ydwnb0y3g+N5zYnxZyIEblnrrvEzblWPKKpyfd9YKYty1J5ZFwmnnbEpk82ZM5UwahnlZGbXXLaeSfX8aeOCdee82T593yiK23mZl16hc+C9fiJU9PBjvk8+3+8H+snE8imdGX8QsKIPhmk/4ee4QXN2Uydaonr0/sQVVCBY33qhRw7LOfSHKVcSs6tyHKtT1LuGXZk7menlgpfuCXU40W3yuLb3Jy50GuZxVRXf3gY9nfJfVaDEcvFfDs7Ld4ub8DZzdvJ6LeDE5ywBZuGY9h7twXmVy0gp2R9ZFCVvJ1UidefvkNXra9wY8BKgOhRTdOsCIggemenkwd4cqRM2fILq65d8L1VF/6lmPVA3jjjdnM0NzLiqsq96TAYjrNeQtPT09mDbbiRkJ6q2Uxs3JloLMl15MKmrlHe+fjUT82Pe9ewZEbBX8hoZ7yHM5duYxJ1+fx9JyGfdp+LtUPjSZmTvRycyYnp4DKWmXLcgBtbX1s2vdhsnUJZ281GROFYO/PR3EYMxvPqUOJWf4xh261Ku6RIpR1XA/xx9CpE4a6TZcg9573KE/hyMnzdJ88A0/Pt3lxUi8s6t9VdOVWDPAY8lBWhlRoUpKRxoFj55tYqpP4u5i5DKOLYjn7rj6cnCdiYVpTUY7MvA36zS7a1UJXpoFuj84NLnqm9jia62IoUggLK8LJ3gJDfTMsDLUpz49mxSfP4eTkxOABs9l4NYlaIOv6EV4abEGPhSdY+/HrDOj9FCtDbiESNzFr/DBef+05Ojk50alHfw7EgKa+GfbmMiJ2fUw/Byfa9n+WPcU1qGvpYm5mgra2FhWl/lw4qcmq9Z8il+tCSQ4XfnyVfl2ccG4/jdX7zlJRv3bIT/HhpWcG4ujkxIR3hzDr9T+g6AaLnh3GBweX85STE05OTnjuSWhSdh1khmpouzo3qycNHQPcO7ihrHv8u0YTvlvOrzNG4tLNnT5DZaCt6rxJt1KwbGuGvb0L7V3bkpOcTEluITXVNaQnZuDerTMdOthjaKZN7FXVDOMw+wBLpw9GpqeFhpom6q0MBLmZ+YDA2cWdDq52VFUUkxmfCsCCPSsY4+KCi1NbggOH8sqzbVuUpaGhhZ6ROXamf7KcVVPCtRvBODr1wMlRF5ncFBNDvRYXk5qaOugbW9JG/ifzHSVxeIfl8eyQbljb6CA3McGw4W69So7/d0Fzk6TA1JUbWPbccFx6uNN3qDY1aqo6Me4+g98852BkoIWmhhbqQg0e47i5YPVaXhraB5eBnenvUUZ1fdq20zey9pWRqmeorola/ZqmIDOBzuMnMXSoC46ucq4cP0J+SdlfJwBkJUcwdMZzdOvmjIVbKYd/2koN0GbMfzn63jMYyLTQVNdEvfX5+H+GmuIMju8+Q+epr+Jg2HgvY25qLL2mv8igQR2wdzXg4u7dlNUpEbXVXNuzixt9P2D+AHOajhD9X9/MO6O7oaPTvL/Vluaw/4tvMX3hc3q0aXlX+1Fj26M3i7/8GI9unXAf5oZzh0ruDAPhgVF07duV9u0daetqwY2zVwDwOxaIx1O9adfOGUc3a/z2+AAg7zaNFZ5vIjfQQlNTU9VHWuHsAT96DemBk1M7HNzbEHDwHAATv1/InC6dcOngTGVJZ156ulOrsnR0jTA3NUPnTydnbxxexQsuLri0dyQtuRdLPF1alFNaVEZRfjEunTrh4mKPpk4dSRGqRZq2tgEmJubo69zrjs7bd5kkVVfXRM/QFFsz4+ZB1dR477fVvDCkNy6DutC3Xyk1/8I6rE4JJqbG9Tved7h73lPWVPDL3IF8sXwdC2c+z9hJz7PxxE2VVa9L/8W5fQeGzVlKbHZVQ5xYry/o52LCyK9Os2TWZLoPnYF3aTV1pbkc++VNendxooOLG59vOkZO5Z23ZnU0tbXRdXMANWm39EHRNrSkX6eOlJc/nJyHfc14aErjrhEYqka7gXp3+XUdO47Fdd2aO2rJ6D5oEMlRgaQZ16/+qnLZ+vMxOn+wn4RlalCayeaP13HZbTFDuk9m5+oCun7oj+Y7n3H6Q2Nq0UXN8nW2HPLAPyGNSTNHY/jnfIlhHI36gYpjn/PS5iRmvKeyWZwdtJ8VijpsnOY1BpbpYj34aebK+1OjrEMRtILAvqMY4QjZN46j1W0UH4y3QTfvBtHG7UHejSWHL2I69B0G+67mXnYqBr/yKrJ2d5sH1NPTp+Tkfs64vcFo1z/n+h9G1JETfQavBDtmvf4XaefkQ1UV8Kfj9KpqyM5r+Lc4M5Ldy9dxrcyWmR8YA+XcunAB/9hUGvcD7Rk3d9zdx/zFJaDf3K53WfgWrox5nc8BKCR0vzch+U3DuPDM3OFYcW+UNdUkRpxle8QFnCzkGHUZyPRxT9HT2epvd5KaogKiIo+zz+8kNuaWWPccxowJI3GxlKOGBg69BjBrrht3mX1XVpNxzZvDaV1459mmE1AJQduWciAaOo5/GQOdx/w+WZlJ2LHdeMvm84V7o3NFYTyHfl1OUEEbXlqgOrUwceqH1sHdLEsJxFA/gVMB+bR5fxbTWxBv12sSEdu/Y1WIEaUFkYRmdyABcAWEyMNn3TecSzNi+Oy/enr/e0SsGMHOm5OZaeLFrdASvKNHMr6jEeauQ9A4sIYfU5zR04njXHAxnYVgaGoYO094I+9Yx9ZrgUSV6pFS0LFevaSOzJu+bN5wkDj6M2+qqu/G7nyNH262592gvYRcTsW75yBmDbqrVf6zlMZyYd8BSh0mc0+DO0JAWua9495ObPJPCUHbl7I/SuA+7mUMdTSoLLnF6T8u0nj4JaNDryEM7O1wt6yE5Gb/1hUlE6dVyABjS0CQmxjC+dNhNO55mtJrzAh6OZq1uqCvTgsk0tGBr9T/Zr8tq4DiwvsIKGfs3Jcw6m7HfW9ZVGYQ6rWbM/rv8pnb38vWw1IY7k9yshZ9De+2XvjneU9dS4/3116kzvEoM+a+iq1tk4X24K+4GTiFlXtPNpPh8sw3XDEWuC0Npfuna/jEvZbick2S4v0JiNfm1Xc/QVMoSbl+EW9LG16c2AtNwLZjZ+Zra/xpsSzxdzE0kpN+ZhfXO0xpor739/jXF6bqOnroy6Ci9u7XNofh7/LRPeIYt+tCu2Q/9oepAQZQkUKcoTNv3RnYDKxwtUkkMheGGNXLmvg8c565fzvQHi+Np40B4GwOjSdf2I55l9/fdiU9sXGQyUnwx3tbIOaDeiPX0aSmoHHXzumpj3lVO5ic1EKqC6FMu4r7wX36Ctzv4a5UKlHXN8awJUPQ/xBJRzdxKM+WMc+PpZ3hnYVnAXkFJo2beMZGoK2aDCsqMyivAIwALS0wadylNHXoz/s/9iQlcCVvLT/HuI3j0DU0wtzcvMnC1Kh+oC2juCSfmlpULVZfpvo1UMrVE9lMfvPO7oYGMhMTzNWbDnyGtGQPRKmsIz2zlAETPuXL2UMozYjidOAFHO1mYvk3N6irqypRZNUyff4PvDTUgfggb4JjYnC26IemmhZdJjzPDxPujhdzZBunS+2ZPGsYbbWaPl8Txn66jkHJwXy/8QqFI7sjs2zZfvejojo3jWPHzlHXpj8fenpg1MTPwLwL877/nWdCNjHtm5NM3jcTrHqwaEEdJ4OT0TGwYHDPNHpqtDwhy3u9yPtqF4hQlGIywIHqxELuaJipqVnx0n9/Z2zkYeatvsjLw9r9Y2V9kmg76Xs8O9VByS10ZGB0R3+ubX+WfSzwCU1HV27JoJsp9FRTQ8fcmemvvE5qIZQn66Nbq9/EBrkm9r0ns7jTGOIuLGLlzqsMXDScNsPeY7FFIVSkIdMvwkjv8U4HxVGX+f18Mt16T2KaR8eGV9nqmhSKSwAzVLtXFne01RLJzAHuNAG7prqfJoz5dD2DkkNYuukyBfndaGOki9zcnMZDfV0MZdqoA0LcJq8AuCPCpvlLT0FWJppKA0wtZYBAU1uGibl5E31zI2Ta91NftSRFZuHs0v4+9BarKCvLVr3X6wO6OnDXlsm9sOTddUvvI1x9KjkKjh67ANYD+OD5/s369ONAQ08fbW1BrfLuI5C/mvcehK7TZzJpqGoksQDyY7MwELZYmauMuJsPa0f7zg4NLxamrsN4xfURJf5/GGVdHVqGJsgeQl/9Xz/Kl9m50dVdkFZY2XrgO2ga0m/GU2QcXkEEgLwbA3KusDa+fnmUdxu/6D6McGxNUCk5eXlUVUPY0gV8+dYuWtZQVKGlY42DWxtOf7sNn+Iy8pNvUNF2AM89O5OuBhncvN34jr5mxkLS7AYz9bXX6DtKh9qqxsFJiJukZUCu30FedFpA8r0S+xNVVRXo9xhNf8fHqbCez/6f32BN2hDemTUWi5tbWeStUgiz79YL/To9EIL81FzKarXQNTVGS1cPt75DqclT7VqGHr+KVa+uAKx56ilWh6aDdgnpQbu4ZmgA6OLQezDPTJ3K1IbfQKwAMztHrNo4oayoprq8itS4HOSO9o3ZK4zlmHpnXm5zx8EQ91HjmsiZytSpvVtUxtbUN2Hc+EFUFUZQoxSUxMRTnm+LwQNoTcjadWNWPwPCMhKhpoqMyBIM6kxQzUuV+Cz9mPZGMzjfECOHHV/PZE/BUObOHI08eAUfnVL1h6vbtvHJ1jOgJigvDCM8N46qx/ZGH8+KH79Bz20sU8f2J3vdVLZHqHy2Pv88SwMVoFVG5rUDXJU3TqB59r2ZOnUyvcyqsHTrgLXBnUV0IWueeQq5fAFhTVJRampj3HcMU6cOQv3wDpxfeRVDwOujj3jvbDxoVJEXf5ow7u+l7n+BNt0nq9rtxKE4unswyKnxRSTX0YOpUyfSRSsP6/59sVJXR9vQgn4jVW190qhuODt1xMpI9Sq2fMbLHL6VC3qFJJ1aQ0z9S52Z20hVGs88RcdufRn0gLr6fx9BcrQXPx24ztTnnmFolzb47fiJsPqN0T4Tp1GVrtJhP7/2GPbDPAAYOOt1yiJVo2T4yau0nzQWgJCdO/l0sw8gKC++RkT2bao01NHWd2BoszHgafp0tEYLGDHXk4oEVYL+287QYdKYZjnMyIyk1qwLFloAahi37cToZrJG09FG3rr6Q00JEcUVtLdoS2vdVt/UjHZuPaktVp2Dxly+hXmnlo//VcQzzciNd1aco6S1oCKOX39ehmGncUwZ24+MddPZFdlapEeLYYceWFvXkl/Wsh7wo8bCqh8VpmV0HDSq/hmOpVs787/8uFXiwSgrK8Wi/3hcLO/eEb9vxBNA9MapYv5af5FfVttiuBtbZgsPDw8x9pUPRUBCqRAhq8SLi73rfbPFnmVvCg8PD/Hssx+K4ykFQohqEenzm5ju4SE86n+zPvtNJBSoYlQUJIhNn74khnt4iDHvrxK384TIvbxRjBkxSIx9bra4cDlIeL48SXgMGCiW7b4gvnl7QoMc1c9TnC0sF1V5SWLlwsnCw8NDzF32h9j0/RzxyfqzoqhaiJ3zvhHz5j2nCv/a1yI8s7E8iX7fiRkeHsJjypvC61peq/VUXZonvH+dLT4/mfBgFf2gFN4Q3740uVnZv/LOavDO8d0vBg0cIEZNe0N4RxU1uJclRYvPXn++PnxGozyFQvywcGb989gv0u4jCwXXzosZE8eIwSPHis2Bzeuq+KaP2Ho++r6Kkhq4Xcya2OQZTvlEJKTX57k0S3itmCeGDPIQ07/aKpILW5Z168jnYsSQJrJe/LnRMz9BrP9kovAYMlJ8sNZH5JU35Fb4b1osnvb4WFxpCBss/jN5bLP6/fZifYSiInFm43+Fh4eHGDNlrjhyLVPU3FdJHwGKveKFJnkaOmqsOBpb75eWJlb9Z5bw8PAQMz/YLJKV9e5J18WSqRPF4MHDxNKVx0R2aVOBaWLP/NnCY8Ay0fRpFfpsFNM8PMS0ae+K8zFljR7Z2eKP7+cIDw8PMWXOUhGaUyb+L1GUEia+nK2q+wUHU1WOcVfEJ+NGi2HDRotfNpwV+RXN44RvfUU1Rs6uHyOFEIURoeLjOVOEh4eHmPN9gMhuEr66rECseleVxqsbwx9PwYRSRHh9LyY0aVvPL/hWROeofKvyMsSvC18THh4eYt5eRbOYYb9/JTw8PMT0JXtFWXWdyrGoSJzd/LXw8PAQTz37hjgUmtFqH1HWVIuD3ywQHh4eYva64Lv8Qw8tE/6Ke0S8B7s+ajIGDBwqPl8f0OBXU5QhzpzYLeLy709W8a1g8fZM1Vj78/nGJ3VmiUez8aFx3hNCiECx0GOS+HZnkLjT3XIifYTn9CZxJr4jrkZnCGXKbjGziZzhYyaI47fvL2+PCmVttTi84i2x8li0qKxRthi2tqpCfPt8k3KMnCCW+cQLIWLE8hFDm9XJ0BHLRYzIEz7LPhAjm7gv+N1XqJpKpUi5tEPMGD9CeAwcKMa8/604cv0xjqf/ByjPSRAbF3QXy8IeTo6aEOJf/wStKt2PHUcVDJny3MOtsv/HKc2Mwev8ZdwnPE9Po8dzlCshISEhIfHIEEpSQo9zOt6Qac8MQf5Q1zxJPEnkRJxge2g5U1+ZhuNDyHkiFqYSEhISEhISEhIS/7qOqYSEhISEhISEhARIC1MJCQkJCQkJCYknBGlhKiEhISEhISEh8UQgLUwlJCQkJCQkJCSeCKSFqYSEhISEhISExBOBxuLFixf/25mozg7Fy/saMmtHjPXuXB1RQsSJYxyKrKaPuxVQSez5Axw6n4SFmwtyLSAtkDV7zlOtbYl9G9UF35EBhyjUdcJM/26rHGV5kRzfH4iBjRbXtu3BOzic3DpDjEuusW2/D5HJeZhbOyDXe5TXV9SRcTOQo2du4+rmgGYrVnBaoiI3kTMXL1Jr7YiFdkt2jP4JMjl/YDsnL0aQVqBLO3szNOsty5QlRnDi4iECwkrRt7LBvL7uawqzuXrJC++ztyg0tMPJvOlVYJUkBJ7jcHQFPdq3uUd6zanMSOC872HO+qWBuS02clX5q0uL8Du2n5MXA0gtb4O9o7wVs3zF3LjkxaETfsTElWNmbY2RTJOailLO79vIKf9ggoODuX4zAd027bE0+GvrLuXluWTGhHIuJAhh1B6L+rA1NRXkJEfg6+9NorID7S3u7wq0zJAzHDl/iag8A9wdTFCvt9mcee0i2w97E3ErFR0LO8wMtR+bXfPCnDCOHjiM7+UEamT22DVc51ZM1CkvDpz2JS5bnc4uNs3ylBMfgpfPES6FF2HnYo+B5l+3++ADa/C6qKr34OBgSuTutDPTBrK5eGgb3hfCUeRqYW9njnYLcv7XqK0q5XrwKY77nONauh5urpYN1svSbwXh5XMU/6gy2ndyQKuuipyUSPwDThJT49zs2r26yjKiLh/n+NnrJGnY4W7V1FywkqzYII76K3B2skHrIcanv0cFceFnOex1htDr2RhY2GFe36frykuICDjO8bPhpGja4damMb9ZoWfxuuBHZI4MNwdTNJrcWq+sTeTErgtUW9hieQ9zl00RyjriA09w9Fwwt6ss6WRr0OCnuHSUXSfOcTO5CBPbtsh1WrbwVJR7nWMHDuEbkECVnj329XV/02cH+08HNLTrFK32dLT6axONdXU15KZFExR4mutl9rj/KWxNWSFXA4/jfeoisYVGtHcyb8GaXTV5KVGc2++F3/VIhLwNliaGqAO+u9fgfUmVp7AbkWDh2jCePh4EGdG+nAnNwc7OGm3NO88wF/+NuwgpNsLdsSVzKA9H5rVDnM9ri+v/J1dTZoScY8cRH4KDI0mvNcfZRs7f7qbFKRz1OsJ5vyBqzN2xM7kfyzGCvOQQjh2PwLadHbqt9AOA/NuX2Ocfi6Wb833ZLPsrnohRPsnnJ86kqKPTbNLRIPLoOt796Vz9/+rIam/y6wJPDp9X2UiO2LOKbXsvUqLfWMn6cnP0tO9dLHUtdVJjo8hOKsU40wufFG1MjfTQkplgbFhFyIVrKDUfbMq/fTGMwPi0e/plRl9l6fLtlFc+nKULdS1dSiMPsvdK9kPJeRD8Vv3OoXQNbEyNST1+kI0BRSqP7HB2+MViYmqNtayM8Ijr5JQDtZWEB/lwu9QQa2tzxM0DBKQ2ysuNC+HM8b1sOHofZkeKU/EJuEqllhnW5nqkR10kVmUYhmTfLfxxIQ9zcxvMyqNJjGtZVNzFS+wNTMTGxhrio9l38DIFlVBVUkmY3y30bGywsbEh6+pOLsWXtShLXV0LHX05FbfPEZDQGFZNTR1tPUPMMs+zITCv9fIBRO1ixdUa2rSxwiLPl01h9YZZM4JZtPYs6uo2WBlpkJtQQHX1/Yl8FBz+bRupGGGjrcb5Zd9xtt48edbpZRy7ATY2NmjG7mNdaOOtczm++9lxMREtLRts2hij3YrJG7/fz1BTX+8aEZvYHqx6uIEbtrEnRQ0bMxOyzhxns+/jb/f/JpHH9xB6uwZzcxuszfQbBuusMzvYF6BAV9cGG0tjNNVUbU5L1wDT7Eus9sttJic7eDcXUrWxsrLEPHYjR283+lWXJeCzdQM7L4RTVlHL4yL71m0OHAtCx8QS45I8vLYeIq7eEH1a8D78M3SwtrbE5NYmvOPrI0Xv5uegaiwt22BZ4M+Wa007Qh7HvljCschrhN8ZHFqgJnQD+2+pY2XVBouU/eyKqvdI8GH2j/7o6NjQRreSpJsVrco6vHIzKUpVH7m49GtO1/eRgPWnKaxv17qpZ/jlfGaLctTU1NDW0cc4P4Tl55u3dWV1JcEnDnFToU6bNjZYmshatFhUkXqDXadPo21igVwmOH76CHE5VSAEV46HoVmfr7LgDZyMbtVe1CNFKGsJObuX20Xqf1pgaRGwbiE/7gr9R9PXNjDHXP/fuTv19IajTS2ct05xNGvXH0DDxgYbGyvMjXRQe5AlioYuZhZWKEN+4+CNomZeKSEx+N+I4169Pz/xFiuW/05mfstz4R209OTknfqcfQ9rTezh7/p/eK4tHyW+PJFxl/vhD8YL9TeONjok7xRDZ38nNizeLNKyzohnPzgkVr64WNwUQojQ1cJAX19Ydx0hdocWNMYpThfb/zNemMllwtZ9upj31U4RdSVJKGN+Fu+t9BWHPn1LtH3xd1GYe0xsXnJSKIUQIuGCmNlXJmQymeg5ZYGIaxCWI3Z9+6KQyWTCoZuDGD75Y1FUVCFuHf1EdNDWETq6ukImkwnXwVPEheTGLEQc3Si6T/9E5JdVP3RdZZ79QXx85D5NkjxCaqqqRFWtykpH+slvxUIvleWn5PP7xLqT/qJOKYQoSxHrNu8UMclForq0UOz9ZZGIKFTFSbi8Svy6P6ZB3s5FC4T35Qvi5S8OtZp27s2rYuuuXSK7UghRUypOHtkkfK6kCyGECFgzW+yLVFmAUdZ6i98+9GpRVl1NjaiqUVkYK4kLEGt37BHpJUIIpVLUVNeIO3ZI1r7+tYiua9kqyR2iDi0Svwfk3u3h+4WYuinxT44VwvvbD0U72TRxtomr36LpYkNcfXppXmLk/JNCCCHyAjeKL/ddF0qlEEJkiF0/bhO56UXicVFdVSVqlUohlEoRtnys2Hhd5Z6wfqJY7KvKb+qh98WgFfUmoXL9xXdfHhRVNbX1eW6dmspqUW/DR/w+4X1xsd4aTG2TNpd1boX47PBjtnj2bxK3Wiz/KUDU1P6pErPOis8/Oiyqa+ruXb8B34ixa+KbOXl98aI4n1Uf+NZyMX9Fo6Wjox9MEhsvhIv//rpb5BZWPuJC/DXKujpRXd/faooykLQezgAAIABJREFUxYEN34qrqi4tDn/1mvDLVuW3Ovpn8dEalRkZ///OFOsa+sgxMea9RutHV3/xFJ7HSsWFE7+LAxeSWk3/5PyR4nBqvayEjWL6Ij8hhBAZxz4Tc48Uq+pWGSt+mPd7q7KqKxv7yPWfR4v111TuTdv10Y9XiiPl9zn+B68Ug36JaeZUEr5abNoQKmr/3B6EEELEiSmy9uKt5WdEcb2Lsq5WVNdUC6UQojjntvhy+dfiarLKclpNVeM4t+qZhSLsnjL/OZS11WLf8nli/7WCu/xWjTIS/b8LaBpY3Ni/RPRqp5qPpy3e1sRyWbxY2Lu3kMk6iOm/bhZzDY3FxBc/FbOHO4rZ2xNEWXa8eG+kTHR/63eVhamCePH1KwOETCYTT69r7CNbZ7oLe/sx4r2ZI4WNTCZkQ+eJg6n54tjil4V9nxlizmBjMXr0u2LBpO7CeOCrwl8IIQqTxdr5g4WBvkxYOXcRK0+HiEohRMjSwcKuc2cxvFs3YSyTCddXvxUxQgiR7iVGGhgIbU1toSdTleXTCy3XU+7Nc+KFvrpCU0NTFcd+kNh9RtUuFNs/E0NdZUIm6yk8fzslhBAi59Jq0bWdmfj8ohBpQTvEmM4yMWhpc6tmN5cPEh8cbrS1mB3wteiooyt0dFRrF/sugxqt+wkh4v2PicFT5oqbGSUtZ7YJCZueE/9ppWyt0fre7D9MVY6CxBQ1zHrdfZTgNqAjc2u7NnPTk3fGqXMcqxbdYMC0RWhsCVd59HybktK3OfLLHMqU9bs3opIAPy+UPb8nI68rNblXWPTpdjIZhLtMhtaNqyS5aPB0QCxXIwtJdZ6AWnUB3y3awNSfT/E2QM5NPnz2e3Yc/oza696cqnNl66lTmBfGs/FiEUp1dVwmLmXXhmGkdG7H1J6ud5XD0rENM8YaoaP58G9p2to6VMaHEZNl3uyI659GU1sbhJLS5MvsDLPklXmqoy+lEA1HzqiByMiGigpAFyFUuwAAVFUj0jIBVyK+78bhgnd5Lz+aHEUhUZnj6GSlTlZsLAnZhdQ1pGpKp0EdaWYCQg1EQRFquoWANeY2buzYvgXTp0yJC9qCV/wonqYCjWtRpJRVNoloSddBLhhpaqINiPJU/PyuYuQwHnMDlWBNLVV3qAz9hogez/DWP2KTXh25tS1dempi1MRVWadEXeNOPaohwm8CYzG1dUOx7RD7lMUY6gSx+2g4ddPGM+sfyNm90NLWhppiFIF/8FvaXH7qpnJv9/JbpL/2Gm/9ITDTduWnpe0BqMlQEKLw45XJ36OgHWNeeId3pw3GWOuvD2c0derVMuL34dNrMnPqTy00tLXRAMpTr7InRI8ps0z/0bI+SVRGBLPX7yrnfBZSZDOQj+cvZEwva9QUiQSlXuelZ74lXcuFybM8mTelH7IWtlGUdU37qBoiPhnoze1N0/gufQQ/VocTlBBHZHopQ+WP53hTTV0dLXV1qMom/Mw2krRHM85a5SeEQL2h76khElKAHtTVicajezU1lBExwDiy/dezLESX93qFcONKHJVtu1NVa496bTYxIbdp3B/SxsK+Pc72pnfLir4NDMbKpS9Rny3jcN0I1CrOsf9COt15A4+8FGJvKihvkCXDvqMrdqb6aOloQ20xqYF7+EUxj5+7q0Lcade1mYEE2tizRPvBp9uSiCC2HLvE/t3JlLYbzpcLFjC8yx3VDh2ce3bBtI1Rwy6qmroGWupFHP3kZZZfrmb8G4sa5gvN+nxURazEr98LvKPxuBSDVFSkxZOfr4Gj7t310XdCf8o6tW/4v6ZYwcmgIr7ZfgoDoCgmkF1rT/LO6/34btwnjDsRzE+WxURtWcToPl+TvvNdss+Z8FOZDjILG37Z7M2np8oRAMZOfLElgNlj5vBaXuOkMvuPaFJHd0D32b3EbeqJnl4q2z9eQ88FbzLKZw1jtqWRvfwTUt02cDjzG8741qKW54dGrzc4Oe07qCrG7+xZop3a0n3BMf5TMof8novweaYz3otfxsc3B9ehkzhbUsL6+b8weuX7ON1HPZm5jWDXidNovBPC9r3vN/MzHjuJJdbjUdeFqPVDWdm/jvmD3ubo4susqQObfi/hs7OKcb4tH9lbDPiCfQeGE6mrzZRRfe5SDTGxMuW5cb0xlt3/WkNPT5+imGBSu3fH1vjBVET+/YVpVjJxSWq0Nbh7QHSb+iNr/uyoqYtbjwFkFzsyycOArVtaEF5TQ2lpFZZdHdHSAC1jZ3r2aI8BgG0P1GI2k9bXncE9A9m5O4v2z74M1VHcCi+n7sIFouvF9O7dixLAuvt4Xk/6A99z59DMycXYuP996YxadpnAJ13uqzpaRVtbh8rYq0RmDHmsC1OAzIBjnIirYuC0MbiZyOpdSygqqaChmxvog6YWoKSqOo/Kqnp3TQ0wVJlRlXWbTrfaTC74p5CZXEZ4WgWdrDTJjLmO741EGhUe2mM1qCPGVFJWXkxtHaoWq6ur+gHOo9/kucqdXL6cjm2PaYzMU2JCGeFXA/HNLmyS+644DHLBCCiOusze4ASsbAcyfoTLnzpjKb7bYxj00RePtO4a0WbAqwvwevXP7hkUNM2upbnqr+1Afn23kF8PXURmok+Prt3oqPX4jqFqinK57HuepDwbvvxpEneWhgle5+j02Rbmd4GScyv54Hwe/SaYU1SQx83weBZtOM2MnvoEHNjIpYzuTLSXt5JSFVHnExg2ZWwz19zLR/GKraDH06Ppat2ajP8dUlMSKKzqxe9bz9O1bQ27lnxBpMtK2ubnEH0jjtW7z/JsVx0ubF/F+dw+TLD46zZRV5dJaXkTBxNVPeq6PsX49EwuXEog8XYm4YoShrr/c7p9f6YsMZJjgeGoafZi1st9uDOi1NZmUVYOmAFqgPGdV7gM8pv1EVVetaw6MrpXNhcuXiT59i20RAZVtUo0KzMJu3CBlIYIBnQZYoyDvSlCpFJcAtQvhjGvb9kukzn6aQmrfAKQ21gzpLMezghKcxK5euESOQ2yLBhi2RY7U31qivMIuniOhLw2LPrlGZrXYB2KKAXtXJ1Qe4gXXUVSPLX6Y/lt41baW1Twx/Ll3HZaQkd9AFt+uHToHrFMmbTsOKOSolj5x3Fi4t3o07F+XKGcoAOxjHp1/gPn6UEpU8SSl6dBl3ssTPssOEWfJv8ryy4SczWTavmFehcdOvSyozovAD8xgK8sAYzoNMoD9505d8m7X2SGPek+rCd6egC22Dqnk5IGOPVmqi3s7WaBtrsVDjcBUUZ++i1iw8vJTE6uF9CWWplKJ7htO3e69u2MtgZ062VL8gPn6q9I4PjXm7lpbIamlgw9PbtWvqt4cEycBzDfecDfiqOrp0dBwGVSCjr+/7swNeo8iNFDlBzKLAUMWg0P6tg49WPG/bxyaGlhaKBDbFQiNS7dqCmMIzQsDqv+oEZX6iqT0NYbz1Pjs1n/+j4GzjEFg55MGqRHVJ9nWDS2+W5t2N5zBBsO4stFPSiO9+PTzVHU1inrfQvIzLZCKJVcWPYD+U6jeOb53i0opz8YZWUlGI97i+e6Gz9iyS1RxOltywkpeYoXp/dAlrSfNZcmMn+wKdauHdC4IEAIijILqFDXQ8dEjqZ2JQ4dO1OVVwYW+kT7RWM+dg4AzuM/58vxQK4/8b/mMLOXCQDdJr1Et0l3p15rZYmxPJe6ihpqlNVkpRfh0r8tAEqZKb2en89Icri89B1kT63HGBOGzPVkyF2SqokOOsTxAHUmTJ2IrXYK50+dZdCQUZjf+c4gL5StlePYYPtP1KMqD/6bVvHdhgy+CvqRfvWuPZ4Zy5noDOhuzS3fcBwmvtEQo6LT03zZaTx5t7w5RiXOhkb3Fv3IUbB9/e8Yd3+ZyS86kbPvfY72+IVJHaA6+zbl7TIBKyorM6i6nQ+YY9x9FK+47SZbWQ7ltaSFq2M9sPGDxj3zF7Ii2IktgZ/i3jSpMgXnim15vl3jx1Xnd6/iUtZgXp4xEsP042zy1WHeUJvHVPZ/F9vpnzMpeA2logaykrkV1ob+umDadyJvOu8jV1kBJeUkX9fGfWrLsjqPGk54WiE4GBP4x3lshqjalt2gOXw5CCiJgS3XeaGfdcuCHiHp8efZf/g2fZ+aTLf22lw9tpU8j1dwNwf3IYOJSy8COzlX9vpiPexNAHpMHMPJqHToYUOsfyT241TnBibtBzP3/cEgarnks4VsvW4Y6WqAbjdmf9ntnun3nTaJg4m54GLONa9AHMb93OBX1mcWX/apQnFpO0drRuKEOrgN460vh91DUio71q3FqOtsJr/gTN7e+RzpsZLJLvXeNaVE5lXSwcWah9mYdH7ufYal+VBBLaTHkRRlwaCGvRwFC/u/jem7X/DeS/3QB5KCgjh2O4/XZoxFTS+H7OwYSpXKRoGFUewv9+A7xwfP04Ni3n8cHa76kF5YCbS8uaJhPp7ufSPoNmMOwzpYNXrUtGWY2jbOZL/PaMsiIk8HEI1Lg3dKaga1lUYc27Gfa9k9W81TeXEooRdC6T+xF3p6qSjibOg94a8yZUCHDp3xV1bzn3dfavYBXl1l0V9EUlFZmU5RMWRd3sJ3K0pY5DOfv/0qmHaJE4nmfLdhCbr5l1j9yU80PUtKSk2nLKeKjb8cpNT13u2/OSXk5umgVMKV35YSo+3BjHlDedCzk8KCfByfW8CAdg8oAJ4MHdMbK8eKzw4m3K1P1ZTcy2JeP3chl5uJIc9/J27GnRMz2tsJudxBvPifFeKbKUOFsVwu5A2/WeKiEEIUp4udX0wSVuZy4dj1BbHA01O4931PCKVS/Ph6b/Hb/mtCiMtiofPz4mzWncQSxfpZA1Ry+vUTT71/RqQLIfzXHhYfvTVB5e7cS3y1O1RUq9QVRUHiGfHOAFchNzYRw99fL5ILH309KWurRcjWueLDQ3GtB36U5AWJdzw6NalbuXhjd2qDd/rx9cLM1ETY9RjZTL+3JDZUzBrRSxX+j5TmIm9dFLMHqWQ9d5ce5t3kBniJPq7thHlbJ7Gs8UGJuN+/EJ3lctG37zRxprVqqcwWe76YLuyalGP0gjUio7QxSOapb8UnPsV/LaMJN7a8ImwsmrS5/h8JIYTIjjghnu/XxL3DaOF16Y5OU6HwWTpHdJDPFOf+JO/ikteEXC4Xvd/eICqq67XT4q6I+X26CFNTc/HOx5uF4vGplwoRv0b0a1JXlrZOYnv4Hc8ksejlgUIul4u+z/0glE0VHhWBYu4wuZA79RCf77oqqmob46yZPFgYG78nQv+UVHHMabHm4DlRUlXvUBAmPhrds1mbm73p5j9Z2ieOuJMrxGB3uZB7vCguNFWvTfITrwySC7mLh1h6JEoolULkx9a73akvp8Fip4+qvqryMsSSF0YLuVwuRv0W2yyNqpIc8eVEVZyhS4MeT8GUdeLKtvnCpcmz7f3sOyK0/jODyqwU8Z9pw4VcLhfj1jbXl/X/9g0hl8tFr7fWipLKumZ+x99Vyeo66zuRWtiyPmdddZXY8PazQi6Xi8FLLjZ6XPcWEy0tRNu2HcTiX31EYUUrZYlfJ/o3KYeFtZ3YcqPRuzo/RRzctVpE5rRWKUKUZsSIBaObPEO7HmL5nvqeUlstQnYvEr2c5UI+dI643Gw4PSOmyd3EOyvONeiYiuJicXbtF6KtlbmwduwqfvCKFeVNYuT6rxNLjv87OtvK2mqx/5d5YldQlmhdjV8pssMPiun9OqjGoPHPiSV7o4VqyE4QH/fvL+TyjmLmbxuF54jfVFGyo8WSmS5Cbmkrpr+5QIzy6CJG/hIp4gNXiiHN1ghdxcdbLotyIcTyCRPEf7//QHR2kAv5yHdFcFq+OL7kVeEslwuHD0+Ig4snie6v/iyCV08X9h37iIMxhSJs/fvC1MRYyO3sRKcXvxbnU4pE6I+qdvv0ZztF4elFQi6XC9fxbzfo9x7/ebpwk8uFfMAscTGx5ZKnhJ4XE1yb5LfnJLE3WKWI7f1F/dg77X1xatVo0WfcZ+J6gRAi5bKYM1S1Pln06QJha20p5u2NFmeWv61Kt+E3WmyOUXW44rQg8dn47sJMLhc9X/9J3M57oMcqhBCirrpcnPzMTSy69OAyhBBCTYhmGnz/ChXxh/h2fSzPei6gl91fX6fxf52ipGDW7jlG3zkfMsLsce2aSUhISEhIPCKEkpizv7PzhinvzZvScL3gg1KaEU1AyBF+/TyJL3YtZkCXv3eqknjZm/++/y2O879h7pi+WJvrP1R+/i+TGrCJr8+UsGDxe3R8CDlPxMJUQkJCQkJCQuLvUpwSxulLoRRUaNCu2yhG9bH/W/Fvnd2DX2IJyKwYM3IY9lYPcwOnxKNAWphKSEhISEhISEg8ETwRF+xLSEhISEhISEhISAtTCQkJCQkJCQmJJwJpYSohISEhISEhIfFEIC1MJSQkJCQkJCQkngg0Fi9evPjfzkRdSTLXIxRoy82Qad9ZK1eSFnGDa2l1ODax+KKsKyUm4hpRMXHkVVRQlKvEwuJ+Lua/P6rzkwgKuYEwdsS4yd2/dZXFxEaGERkTT1JSkuqXXUHbNmbNLth9NJQS53+FpAq9ZldX/L/27js6iqp94Pg3vW56QpKlhSK9BxCpIhBAqqIoioII4msDQZAqSJEIAoqIAgLSe5cOobcAIYGQBum9t012s+X+/tgQgmBAVMj7e+/nHM4hMzt37p2d8sydu/OUFGZyKyICg5Mbin8gvelfk0/4tQvcjEgit8gCNxf7srSBmswkbkQEcSdeg5WjE/ZWxu9QX1RA7O1gboSlUmTlgrt9+deCaMmMDicoWUt1j0e/+kqbl0FE5HXConLB3hknG2P79ZpiokKucjPiNjklDri42jwya4QmI5GQiGvcSSzB2tERO0tTEHqyEsIJCgolOjaWtCxTXLwdK0yQUFJSSF5qHGFxMWDjjsLKWKfivExuXrtMxB3jfpKcU4TCyQXrCtJyGhnITb7N9Zh8vNydStNIasmPj+RCUChJaTnYKlywfUjGlH9LVOBJbkQZ2xGXkAQKz9JtryY1OoKbwbdILijBuYrrI5JJGFAXZBAVHEJo1B1KzO1xdLDFFDDoCogOuU5I+G2y1LZ4l+7zGVHBBN4ILzveMg0OeDv/r7xOrpjkqHBu3ggjrVCHs4fLfds3Ny2a6zeDuZ2swcPbFQsTE7R5mURGBXErMgcULmXHSPSVkwRHxpZtR62dF6525oCGjLjb3Lx+k6TcYhzdXLAyfVp9FVrSE8MICr5FXEIBVgpn7EvrayhRk3QnhJCwRLJNXfB0uNfy/LgwrkdEkVxoiaeL3b1Uq4AwZHLjUjg6e2ccHnWMCAPp0TcIDo8lXafA2/neyT4nKphLN8JJySrGztkZm0cctwZNMQl3QggJSyLXvFx91SlcOXuVyNhYYmPzUdTwqDB1LOjJSb9NcNANbkdnY27ngkPpq5SEQU/6nRuEhMeRrnfE2+lxX3+eQ+i5YApsXHCxu7cdtUW5RERcIzQ8jkLscXWyeYq9VIK85EhuxRfi4uKIedn18+HXvX9afvw1wgud7tuvKrO8uDAuXg8lNjaJPL097k42/OWQozib4ODrhEdFo7f3wsX28a4hqqxYgkMScXZzwcL80XuIKj2Kq1FpKDzdH5E6oWKVIjCN3zeeb46a0rZ1E1zK3mmmYvfE93hlnZavRtxLiZV06jt+O5RISnIsifFBbN2SwyuvPE52gwflJqQTHpuCs6dLWTCjTr7BmrmjCa31EZ3KvXVCr8rk1LpZfLk1AieTQhJuX2XN1psM6NMJmycMFM6t2ItZq3o8GJblsLRXW75PaML7/RqXTVXnJLJ71UwuK9rTsdrTTc8YvPMXlp4IJD8+i9ATIWR6NaWRtxXk3GHnofMkpdwgKiKPbMyp6lkFa5MSwi8c4Pj1MO5E5VKoSsTEvQFVSs83eUnX2f3LQmYEwOi+j/j+itI5dSKAG3dCiQzPJ1+vwsmjBo5WEH92E/N+OUlOXiYlxQbsXOvgVlGcmx3J1gMXSUm7ye2IPLJNrKju5YEVRZzY8TO7j0eRm5dOXpEL9VpUo6IwqLg4h6zYMA7sWUa84iVaVTMmVYwPvMKqdetJKSgk8fYtDp48i3fjLtR0rThxnDr/DvuW+jPnWCFDerbCwtyUovjz7Nx6ktDYWBJvh5FaYkddn6o8raykP334ETeFCZkJCVzZ4U+E5yC61LUnJ3AZPxyJojAmhqAbx7lq0YaO1W3/tBy9KoPjh34j6FosUfHxBEVdR1GtFUoHCxJPLmTb4QTikuNIuhaAunZ3fJzg0MxZbMvJoyghgYjTW1mTUJ13OtV+Og1/xrLOL2LZ8VjyYmO4FnyYUNt2tKtq3Btzrhxmx7mbRISHEZdrRdOWdbEtzuJMwHGCb4cSGVFAga4Axyo1cbSCn4e/zzUzc7ITEri+ZRoXXN6kV0MHcq+vZcGBUIpjorkeepqrNKCjj/NTaV9OfBTrN6wiLDaNhKvxRMbmU7XRczhYQeq1Pew6H0FcTAaFWeEUuzanqgMQe4zv94SRnR5NWkI8ibaNaFCWijWPM8vmsnTfFajSjGY1K86Mpw3fza9HI0lNSiIn9TaZji2o7QwkX2L0F7+Slp2HqiAPYV2bml4VX2ITr+xl76Vw4qIzKcyJosStKUoFkLCFYeMPYWZRQEKCnlrtG+JaQURRlJPB1jVLCIxKITUkhZshCXg0bYKrDahD97DmRATJCcnkpkWS49QCn0cm/yvk8trFrNx5lHirpnQsTUeqzU3nfMAxzgeFEh2TBE4+1K3uzNPq6hAGPQFrp7M/zoP2zX2wKgt4Hn7d+6dl3jrCleLaNPF++je5l/edw6Ze9QqvK/dRxfLTzPlcyy0gMyEDraIGDWo48xiZ0P9QTgonAk4R8OuXXHF7E7/6916JlRYeR0xuIW4uDn+4ORHEXNjB+x8vp2s/P9ycHl3r/Lgr/PLdRDKaDafl3zmV/L338/8zghZ2E9N+T3lg+q7PewvTt7fdN+3awpfE5AM3RaEQQp2fLqKjM0vnpIuNc98Tvr6+ok+fsWJvXLbQFeeJdVMHig8W7xeFJUJsm+Aren4wS9xMLhaGuA2iX4NGwqfWc6KFr6/o0LWn2FuaFOXOsl5i5KxFoo+vr/B9bYw4f3cNJxeLQQsDRH72KbFv+QmRFJ8qdDq9EAVZ4txPn4menX1F6zYjxJaAW2X1VeXdEJNGDRC+vr7inRnviK+/PiRE3k0x790BoprCQzTw9RW+vr5i0q7Y+9r5YzcH8fyMk+KPkg7NFl/sin9g+r8tKyZGxOephdDpRMz2WWLsbmP2peSzO8QPe08LnUEIURgrVqzdJCISC4RWlSe2/zhTXMswpv2JObNYLN0XU1bezvmTxa4ju8VbU3Y+ct05kVfEqvUbRIrKIIS2UBzZ86s4ei1dCCHE+WXDxarzBUKvF8JQdED8OutEhWUlBmwUi36/ZPwj/7ZYunqLiE1TCaEtEPt2/iqOXk7+y9smdOd0sfxcZtnf6gKVyMrOF3ohRH5quvj12xUipixLjVqcWT5f+Pl+Li78oZzD8z4Sa/YdFmPmbRFFauN2yzy/QszYZMz+UhAZIL5askqk5Gn/ch2fVHpcqlCX/v/XwR+KgNKMOur0KBGdWSCEECJw51jxwsKICssxaNUiLTVeFGq0QgiDWLJwlNh4JVsIIUTQ933E6ivGcu8s6yVGbTWeC7LjUsXdBGoXl68Xv157NplqngV1WriIyzbmtzm34T3RY2lpWrOsi2LBlI0iMaNAaMvtBrm3g8TqdWtFkkovhK5IHN+3UhwMNB6jadFJ4m4Co9V93hUHso3ptTSZ0SIy3ZhKLPjQ16L7wstPpW1CCKEuKBAJSWmiRG8QmvQEsX7JHHH30DvwzQfiaKKxcdrgb8Tk1cbz6bUFw8SC4NK9MX6X6Df1VFl5N9bOFJ+vvin27lkutgfcfy59mNOTe4uNUaXZoSJ+Em/7G4+xjIPTxeCVcUKjEUJoI8XSiVseWdb+bz8RAUnG+hZe/VZ8vT7cOCN6hXhj+qkKlryfVq0WifFJokirF0KtFnvmfywOlia+Cpg2QGy7U1rfsB/EiIVB5ZaMF5/59hJf/3ZBlEtiJyL3/iQmLA8UlwKWiiXb72VNizq9QezfEyQKVDrxLBh0JWLrwg/FtqCcB+Y9cN0z6EXE4WXiNT/jdfLzpXvEvcRECWL+4MHC1/dlMW79TjGzTTvx0cRFYvJ7PcTkvYmiODte+I/wFa9+vU1otAYh8uLFz1PeFr6+vuI/WxPKStn9RV/RvfsHYt4XI8SLvr7Cd9gscTQtT5xcOkl0f2O8mPFOOzFy5Bwx7+NXRbu3p4prQgiRnyy2fPOOaN3aV3TuOVBsOHdTaIQQob++I7oNGCCGv/qqaOfrK/pMXS5ihBAiPUCMaNNa1PCoJpqUXvMXPeJwy4m+KCa8Vk+4OnsYl+k2VBw4HyOEECJ172IxrI+v8PV9TczdeM74+aubxCt+HcT3gUKkBe8THwzwFe+svHlfmWELO4jPdyWV/Z0d9Ivwq1Nf1HqugWjl6yu6DRwqAuLuff7O2X2iY98RIiz58bIhCiFExLI+YnLAY3/8oZ75GFNDSTFFxSZYPiSRcM369vi1uz9ffeNRC/H8ZRgtXV3xG7uUIo09CB1bx80n97WVBAYGsm/Nh4ROWs9tSwf6D/mAhlVM0Rtg0NTdDO3oiarEgEn1IfyweiuzZv/IqcBAzhw/SN+699Zzbq+eRYcD+aWj4IvFUWXTb/4wmBr132RvuhbvalUwMzMFO1vqDhzLqo2HObh/DjnHvuBErPHzoeumUNJrHDsOH2ZcC2eOpxWCQyMmrtnF5y0GsS4wkMDAQOYOqHFfOxu1dqZtkzoPbBNLSxtEcT6FGsMD8/5NLjVrUs3BEl3eLTYHOTLkBWPvmEZDmKozAAAgAElEQVSjw9rSDBMAU1N0CSmIQhVCCHQleiwtjffhQmdAeycOgIiFz3NQ8yKdfCzQqwsp0BgAAxpVATnZ2WSX/StAC+h0BkxNwMzMBExAl52HPj0TAHuFGxcPnyUlJZSdP/qz4uINYtBTnJdbrpxssrNV6ACNWodN6SN3TE3RxiYhiooBEyzjzvNhz8a4urrS8r1vCE3VP9G2srK3xcVZgSmQH7OB7GrtqWl191ATqHKyiItOo7jcMtErX2Fpuh99G9sgNIUUaIzrdn2+E9Znf6BnT0+Gf3mExk1b4urw9B7lu1evghVgiF7DzpqD6eJofPxl5V4Hx4ILvN3MhQ/WOHFgdMU9mSbmVnhUUXBiRj9cnV24w1BebWbs8vF5cyhHv2xHz54DWBjUhYmvGnNiO1evgiMgCqO5hAkvenr8m02tVKw86mGeeJBXGrkwdlcjto8wJp42JIZxMiuSz/tWo0rT9szZfh2dKD1GEMbzESboc/LRp2UA4OHjjTVgiN/Gap+36eVs7Lm3dPWhqmUUo31dGLowjxVvNXp67bO3p6q3BxaUkHprCxEl7WjgZZynLi4pewolLKwoCY0EoCBfjaOi9BG2uQXFF64CkHXhV/wvKJjS1x1TtYoidQkGAcKgIf++c0AuhcVaBJCfp8b+7qNtSyvUgdcBcPOuyZnNG4mMTObaqa0s27afo4C+pJi8+8rKo7jEeIyq1dp79TU3pyT8trFcMytSfhyIq6srrm0GsO16+SP+QeZWViireWNjqkMVtpTDGd15vpZxXmG+Gjvb0vpaWaG+GlJuSS1p0fFk5BVx96qQf+sgy46nMapHVczURajVanQGAQjSIy+wfOUXNKnrTu3XpxGUZNwmT4teraJEa4L5Q675f7zuadWFnA0p5NuNhzl8+DCj6xWy57ejGAxaFr00ktrfbSYwcB1vZPzOIvsh/DhvDJ8NeQmtMMHauRoTpi+gjqedcbs4VOOD2evYOa45kemasnX0/3YvHXX70NR/l/2nAglc/RYxs3/Ga9DLVAuPQjn5GE30CWRUH8cM7xvsOS24cj4Ihw4jOXjoMDtXzkd/9RzxsWnUG/IDfevo8Og/gYALgbypOs6eUxng3oWVly4zafBYdpde88e0rng7Ofm0xf+nFfTu/iUhgYEEHl1Lr3Y1AXDs2ovp3x/m8OGfqXe8Iz9cAaeWb7BwSA2S8sGjaR9+njGadFXF1zDn5qP4btFK5i79jQuBgRzduZYu5Z4UOzhb0qFdbexsHv/BvI2tPdrCXNTaJ49Rnt4V7k/kBB5mxwETXhz44KPp5iO3cOAP0yzsmvLJ7kA+AdJDF/H2+FVsX9+Wi+5tWHD32uhal44NZnMyFoY8Yb3eXDSOOi5A2xpw/t70xp9u4coIBVeP3xufUpQRzsEfF3MiVoVGb4q7twN3Y9yGb4/H4aulTFxTTBVLdwYN932s9XeZG0uXh0xXODiSuWgWK7yWMLaL+xO27snkhl3i+OWbNHulB83KxvWqKSouufchayswMwMEWl0BWm3pdDNTKN251Y61KQj8lY+uZnApUsNPPf2Y2M2Ci2t/YtXpm9wrrTkTN06kKiVoNMUY7u7nlhZgYdz+9ft+Tudf5jB+fCZ1u75Nn+fAnlQOzJ7H9sTMcrXvyIxN/8GCYoqKtfcm21iDqRmY29FjzEqixqwEIOryas6dvEWjN5r8jS2m4uaBYBqMHFNumjV+E74hbML9n9QoqmObvJGPxuUSHJ2PbdOuzB1Qk4LIaCwGzeBQlzWoY6+xJSSdArUBF+uneU+pIWh3IF3eHnbfVJea3Vl/PoHAffPpPeUM5xZ2eUQ5TvSde4CsT1JYsmYhO87W5M0uVcm4fIu+S6/wxnOQvmE864KKGNfq3rCAnIQk7O1ssHf+30oV6N1kEDsv+nFu59cM+voCh+e0JyMthauH9zJpTRRbOtlwZONqzuY3oQlaNCXFGPQYz+oWFsbjpEwJoYeC6DZ89n3rsHFsxc9nkgg+/BMj55/iyPxeT619mvR4rgSdJviGN++Pf5G7ZxS9Pg/N3bjBBLC7+wgxh0JVuQIcjY8jddbOeIpjfPTRRTJSY3Bo50zvjj5Yqi6y6LOfCb+3AO1fHcnwQa1AZFFUPk5UlK696XCujZ/NmDnjcPWpRecmNfHEQPz1vSxdtJuksgWq8sq4j3nVt4axvmUnLROwLa1v9aGczBpaWvUj9Pt4L69tGFzhNinJSSMk6BRnTzkw1r8fd5/WC5FNsfoh9QWgFpuybt5Xjt5SgatJBFO/HEtBZhSaWjDQrwG13SyJuB5IcY13uLjhIAqTWPYf2o6y/5t4PKUhl6nHt3DzhhWvv/Xg0J8/XvcMqZvYvWovR69eLZ1iQ/Nu71GQdoj9ogfHlQDO+L7anZb7Mp64TvZOHWjetyO2tgA+1G4Ux+3Y9tCwM+/Xgi3tvLBtUI26YXBen0fSjUOsOxzDb253v4fauPcxwwfwqd8S3xfbYGUO7TrVYu8T1+rPpHFmyffsCEshr8QKT+GKzz++DiO3hj2Y27DHX1rGxa0Kkb9M4UjNufRr/GRDDp95YOrafgBDX13Kzphc+jTwfMSnb7Puo700/3IETao54uHhRQ13Uwy2Naibf4RjadDDEyhMJTypFo3cgUTIzstHbzAQduEox0/foU6Hu+WpyS8oRKeDmANruZJRm74j2j+yznYOreg0EEJ2n0b4tcUu/CQx6i4sWvY26uijrN6wvuyzp1ddo9v4X5juasGdA5P44nQEH/cy9o4KksjJhYLUy6z9OZzBi9/B7RHrzsvLwWPEgqcclBZy6feNXI32pFWPV6iju8Cu61683twBtxruaM8LhABVVgEaawUWjg6YWZTgXt2LouxicLUhJjgOp5bvAtBsxAY2jQAyzzLs+wwmdjP2hHX+cAqdP3xw7WpXByytbNEW69AJLdk5Gqq3NuZDNnHwpN8XSxhCDiG/TSWk7QTcUfLq/CW8+pCWFNTyRH1JZ/x/Zh46hTPmCjvUBQXs3LSb5v360dDTkdDbYeSYtPp7my3zDPuyuzOrWvmJWoL3bmPNnize//UT7vZRNRi8mE2DgbwQJq0IZ1ov40IFyYnoimyBmphQTG5CMjqNHp5mYFoYyc6kFnxUbtjXqR9+IK/XW/Sra4O7bRp3ElPKLZDFyhFTyHn+bd4f2QFnoCA9nWMBl3j+ZT+8vEyw18aTW1gIQFpwICbP5QMOmJgkkxaeCa3u3rYLElITsHFsfN+PEf+/O+bvj/61UfjVsqCKTQoxyWkAODTsyICGx6juaQJFxeTcUOPWC+xdFFhZ26Mt1qI31ZGZVYRnC+W9AoviOJhch3eb3euluvjrr8S90I/BDRS42meSkJL81NqXmXSFQ3uDsavbibc+9uTO2d8xNHmZmo5Qo1ltklIKwdue0GNBuLY1BnfPdWjEwVuZ0NiN+OA7eHY3BtFVWrzC/GWvgNBx5tBq0m26GH/cZdeZrzZ1fuj6G77UjEMxuVDLiYjTN/DsPrFsnonfVDb5aUm7vpMtx91ogim0GcyCTQ8PKqs28iEnVQWedoSfvoGLr7G+p3/8kbAWPfig/XPExt4mWl/xoFBVXgT7twZgWq0jw2c0IvnUBm42fIvG7lCvUxPOxOVBTUfCA4Kp8uL0ckum8f2Ib3EYNJw3ezXGGnCu04Epi4wXutvnf+JQSldquxl7m+t37EX7RDMsLcAQn0XeHT1P8/mb8uX3aHnnM+5kqGihrHibmHn3oPvLKbzw6Se0quZ6b0ZRAi1NdnA5G9q4qLhzKYQYvMpmp6Znoi9x4szB40TG1H1IyfdTq8IJvxrOCy/Wx8oqnbQEd+r9WTxmbk+thi/Q1rkr497rf98P8PTqvArXU1KSiUoF2Tf2s2azihGLB/OXQ7eME2w8Zs2U3zbiWhLK+qkn7+vxTknPoDhHy95NJyh2bv4YBRaRm6fHYIDQrWuJtWxC91daUPEvIiqoXloKjcZu4W8NE/57IwH+GX82xvRBZ8UomxdEv4HthFKpFMru74lD+cbxUkW54WLRuP5CqVSKNr5viZVX4oRWCGHIiRXLJ/YVPjWUosWA0eLdPh3EC+M3CyGEKEi5IWa90V7U8laKuv3HiQsRKpF64jtRz9te1PD1EwdOBIjBXeoJK2cvMXH57+KzPs8JG0c347qVSuGq6CO2ZhWKwsQg8cXAJsLbWyn6fLZATH+/vXh77l6RUyKEf+d3Ra9+zwulUimqvDRcHA3XlLXm2oZ3RRtPpfBq0UMs2RUpHmfEz63Nn4jPt93+6xv578i+KD5sU0fYO1URSqVSeLk5iKHrSsfo6EvE7Z0/i+rVqonn2vqJ1WeThE4vhBAGkR16Xrzr10EolUoxYmWIKCo3Ji476oz44CV3YatwEW+vjXvYWu8x6ETiyR2iQ/NGokbdRmL23jtCU7qx7qz+WvgqlaJLl7fEgWvpokhTcVFCrxGRW5cIpVIp6rXvKzZcSBE6gxAGvUZcOrxMdG7TUCiVSjFszkoRW1zxWM6b60eLuj5K4eGiEE7uXkLZdep98xM2DBUTDqn/sFSu2DfjHeFJP3H4D3OKMmPFlP4eQuHoIl7+MbS0uoli3YJRQqlUioate4kdxyKFXm94RCP/WVkXVojJW+4fq1R47ZqYOKyrUCq9xAsDp4jT2cXl5l4QQ7ERL779q0gsnaJXqcSZNYtEuxb1hVLpKT5ccEQklo6jzU0+Lob3Nx7TPd7/VeSXH/tm0Isjv04Qh6OezXi4Z6Xg8mXx6ZBOQqn0Eh1fnysu5N7dj/SiMGiHGNLZUyibdRaz1l8RJQYhhEEnkk7vEp1bNhbVa9cXM3ffLjtGhBAiN3i7mLPprCi/66hu3BAzR/cQSqW3aNP7M3Ew7sExf/8Kg15c/O1jUVvhJDy9vIW3t5do3X9k2RhTVVKEmDS4l1AqlaL3gsuisHRopdCpxOGZo4VSqRTPj1wkEnPv3ycOjfMWbq5Oovk7/iIpt0RURF+ULZb+Z7BQKpWiy5Q9Iu/u5g05Il6pVVPUq9dMfL1wl0jKrrgcIYQoiLspPn+1h1AqlWLA4itl9S3MChLj3+kslEqlaPfqKHEyU1VhObFHp4uGCoXwqOItlEqlaPRCj7IxptqCNLFo1CChVCpF168Oivz7znNHxMsoxXv+h0TeH8o8O6u5qOLuJOr1GSOCEouEEELochPEhpmvi/q1vUWD16eIy3eKxdM8o1Q0xvTBD+tFzLk14vUOTYRSqRS1Xh0q5u0MF4VCiMKMK2J8565CqWwp3l6wRIzoukQIIYQ+8YqY8FpD4e3znHj1nfdFu5aNxcs/3hIxl38WPZVK4eliJ6ycqgilsp2Ytv6iKBZCfNe7h5g2+3PRuoFSKPuMEWduJYj9c0eIaraOouHkQ2Lz1N6i+YjF4vKiPqJqs85i541UcfL7T0T1qlWFsn590WaEvziVmC+CFvcSrk4K0XfaFpF3Yo6o4qIQz/X5TFyJN2777bP6iyZeSuH5whti98XcCq/5iUGnxWvN3YStjaMx5ugwWOy4liqEtlBsHtNWeHkpRcc3PhPbZ7cSrfrMECG5QugiD4khnaoIr0btxISPhgtXz6pizM5wEfDjWNFSqRRVHC2FvYunUCr7iXWRxjHo2dFnxLherUR1pVK0fvtrcT327+0PZ2c0/NtjTE2EEE9zeMlDFd5czgczrjNq3rd0rvPPvfrp/5us8BNMX7KGl6Yv5pUqLs+6OpIkSZL01wg917bP5LtzVfju61F/+7VNJQUZxCcfZcawML7ZPYFqVRSPXqicnIQo5g3/lPqzfmJQMyUK2yftK5TuHJjDyG05+K9ewCOG0FaoUgSmkiRJkiRJf1Vm6GF+3XKYNJUZTboOY/jLf+1HfJdWz2LLjRxQ+DBi2BAa+bg+eiHpXyUDU0mSJEmSJKlSeOavi5IkSZIkSZIkkIGpJEmSJEmSVEnIwFSSJEmSJEmqFGRgKkmSJEmSJFUKz/wF+wBCpyI3X4etgwNW5ndfVqunODefAmGFh7MtoEeVnYtKp8fcyg57a8jPL0KYmGLv6IyNxT8bY+t1xeTnarBzUmBpbvaPlv2kDDoNBaoirBSOWJs+7XsKLfk5Oai1plhY2+GksOHue4UNmmLyigrQGaxRONhjXfpdCL0WlSqfYo0JVgpHHKzLb0cDmsICCvSWuDnaPLi6PzBoNRSqCtBozbF1dMDO0rgOvaaQ3LwijInXbHD2UFDxy0f0FBXkUVisw8zcBoWDPZbmJoBAV6KmuLgInYUjzraPc2joKMzNoagEzC3tcHSwwczUBCEM6ErUFBWrwNoFR+vH3X8E2uJC8jWmuDjaGbevQUtBbj7FOj1gho3CAXsbCx5M5vfv0GnVqIuL0JrZ4WxndW+GvpjsrAKMqQoscfJwKnshs1aVT45KjamZJfYODmX7w58RwoAqL4eiEj0W1g44OFhzd4uVFOSQW6zFzMIGhaM9lqZPq+X/XYry0inGFieFHYbiXHJUWrC0xc3R7r4XgN+l1xSSW1CEmZ0rjpZ68vPz0WgNmNs542L3NFIAGdAUFVCg0iCwROHogHXpMS0MeopV+ajUAnN7R5xt7h0/WlU++eoSsLDHRWHNfU0TGnKzi7BSOGBj+ahjTqAuzKNQrcfUxuFemw0acrPyKRECMMfe2RFbi4rL0uuKyMstRGcwx1bhiH1ZfUvIy85FozPF0kaBk8KqwnIAhK6EQlUBxRpTbBwdUViVP3YMqPPzKcAad4dHZZswoFblU1BUgomJFQpHBValx6FBX0JRQSHFJTosbBU42Ns89R4qbXEBhSWmODjYcS8zqY7CjBy01gqcFf9eNg1tUQ4qEwecbCrHdf1R7p5PwRRLWwcc7Sx5yCFdMX0JuXn5lOgM2Dq6YW/1eN+4TqMiv1CHo5OiNN3xIz6vLiBXLXB0cnjEdbhiZjNmzJjxN5b/R6QcGs/oRaE0bNMGr7J3mmWzdvgAuiwt5Kv3XwDSODhmKP0WHUVTYovSKpZvF8xl3rxNVOs6kHpujz7o/0iVmUdSeg72Tgr+uIumhO7kNb+J+LTvSi3vJ0ur9U/LTwjmu9mfcUPZhXaeDk913bEXNzBt/rf8vvsC5wPisavXhJpulqBK5cSevWw/8Au7DyShdvKglpcrliY6YgOPsH7LatZvvkaiwRRlVZ+y7D2qrHC2+3/J8G0qPh7QouKVa/K4evx3Nu9ZwabtUeTb2lNd6YWtBdw5/g2jPv2FM5dOcfRoMS0HtsC5gqKyYgJZsmQWG7ccJmB/BCprD+rWdsdU6EiIOsf+NZOZdL0Bw1/wqqAUo6Tg/Xy9YA57dp3h7NFoTJV1eU5pT0lJAXE3Ati0dDRL03rweouKs5vcVVKUxO8/TGXU6liG9mmDhbkpZF/mk+GT+P1UAEeOXKXErTYNfdwe2F//LYkxFzm2cQ7Tzit4u+O9HNbErabXy3O4GHyOI0eSqTuwHZ4mJpAfz5KvZrNk7R6uBIdh4lKfWkoHHpIWu0xBRADjx8xh9+GjRKVYoqxbHzc7ICuMLz+YwPp9xwiOSMFe2YSa7vIdgw+z95vXGbv0EvU6dUScXcCwT79mW6gp/bu2wOYhgVXa9V2MHz6E3+Lr061hCesXfM67Hy2jsF5XujV4VP65v68wI4a1K75m5bo9HN11k/RiW2o3qI6tBWSHnuS3DWvZvOMcEXkaPGvUw80GSA9hzaot7Dywm3O3crGr3ojqTnfbVsTNA4uZMO03iqu2pkXNio85XfxFfl2zgW17jhGUpMK1RiM87YHUg7zcbSIXQs5x5EgEDs2bUNel4lS4AZtm8t3ydRzcfpWQG3lU922Cqw3cPrWCrxYu5sDuS1w8nYhTc1+qOVZwIOiKCTt7iI07VrFu400yLayoWrUaCksAQX7KdTbM+oKh+8wZ27/iVyLlJYex8uev+W3jfo7tvkWOwZHaz3ljbQ5h51ayZvk2tu3aw9mwGzjWe4HqiqfYR2XQcWLlZyw8rqVjm/rYWt4NeBKY1eQ5ZkU9x/t/K21QxaIP+bMupTEdaj39FMdRgWFYKd0fP6uSJp21Uyfw3a4DnDxynlhRkzYNqmD+V+8kMkNZtGghy2Z9SojXW/jVv/eu19ykDNKK1DjY2/6hw0MQceIXBg5eTJd+PXBzenQHUkrgZj6bMg1Dp6E0+RuvpK8UPabpEWE0fm0yLaqWb7gbrt4OoL8bIHjRf+wr/Ly5KcPb5fHL8RzmLP6cRaOu06O+AnJiWPPjTAJuC1xrNWfEJ+/TyEUBqLlxZjc/rj2CwcKM6vXb8FafgdSyvcKX7y3jemER1Xy8sbNz5J1JP9CxNH2khdVzOPjYG3O/VxKONVoxsmcrfojRweNkGvsHCUMdRs1ch6+bNeGb5vJLmIou9e3IDL1EkGVNpkxfi1lhLGv2B5JSuyo+TjqCg6/TYfh8xnlZEH9qIYcv12Nkd2Mq0XPbd2HZugfNrz76ZciFydEEZ+l4d8zPeFsVcfzQVm7c8eHFxs5g787Ln83no1fqPWZD3Ok5dA5T61Uj6+pxfgu8Qa66IV72Fvg07MqIkmi2nX68ez0hqvPWhJW0VToQe2AFK2+n8nKbKlhZOVDXty/jii4z6PYfl9JyffcWVu3KZNRvYyh/+g3cuJzsal14HrP7TxCt3mLdV688Xvv+YdXrdKB6nwyOnHjwLFP1lWms+6rDfdMKIo4RrOzH+q+7YW+VzN41IWgauWHh8OfHUfLZ5VR9eyE/vuyNheY4K78/T/0pL5BzeR1Braaz9+MG2JqG8cs3Z+k8s+c/3sb/D7oMmUVi1mw27LvKsg+mMbHAjRKXzjjbWpB7bgtLdh7gdqYXnd94k/d6NcPLdzAf+B1ka+4hDt7+nDHjRnP85i2+GfiYx9HfpqBNjzG8O7YupqmxrN+0mejc9rjaQPCxXdR+fQGf1rJCd+VrZh9twozBNYnYuZTEF77ju3b2ELON1zeH0H6iMW3wnQNr2BDWjH7D3HicM3bIhvlY9t3Aj41tIPQHRmwP59eP6htndv6MdT++/Ngt8ajWi1nfT0NpquPIVwMJiHuTus4gRH0+nj2UZs4WhPw6kWUhetpV+/OIQp2bQXB0In1GL2aCqznBR5dyLqQOr73ggU5dRMDuE3h2702j438MENJY+O43OA4ewZDeTTDOdaJj/y/5qEEtNNEhrPv9DMkFvjhagb1bI4ZMfgsfV3u2LepNwI08Ong/vXy/QghyNeb0GtDTmDq2TA08a5tBlXLvERUG4i/vZtmGPSTnQYu+I3hvUCeM3TLprJ/yPUcTi2j5Zn/sNq8jx7cb9jnnoct0RjQzsPmHCYR6vsPs4V2xUKezc+1S9lyMo9HQe6s49cM4tkW60aaengtXoiiq3YmPPn4D8xO/sSpIRzOLYDIsO6C0iOB0YU0mzBxNvaJMjm37kfUnYrB28mDAiA95qWktEvbO4LszKjxNTYlJTcWp3QDGjx6Id85VZo9dwu+XQvFq0xAF0HPib7zZ8M+3U2FyKKsXjWPxzjiadWqDqcKDLo3dsDaH7DObWbLrINFZ3rw45E2G+TWlIPwIs37aRqvRK+hheYaff1mJpsNXzOhfCzyaMmnOEsLdrrOi3DryI3bxxX+WE2lmSnUvNxyr1GT45zNp5QlggpWdD3Y1r4LF44WKynbvMv3KejaGAVUea5GHqtRjTL2qgW/rpvcm2NpD4BWibx8jav9F4sKvElerIdbAgW2HaP7hN/j7+zNpSEf2/7wNgMKo82y+FsOrk2cwffxH5KTeJjpTBW4dGfHxON58cyRf+/sze8ZUfMt1kllZQ6NmHjgoKlcmKisbe0xNn/4jCJ8XXsDXSwEl8Ry6rWBAa+OJrLBQg6Nd6aNlczPUccno8wswGAxoikqwL31EpseUoog7AMSs6M/hwvYMaF/rsVK+q9U6zE3BwsIUTE0oyc6nJDndODMnnp9GdMDLywvvfhO4nlpxWa61auFbrxoIA9GJYVg518L5CW+cqzZvTtvqzqDL4kKMBt/6j5ONS09icCDb1gZQPjN5wuaR/BzTjrd6NuKBzotDM/Dy8sKrYVumrL9Ise7J6vtPC1/Q31ivT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